From f3ed57046fa0cc8594b46a304138b09746a8c6e5 Mon Sep 17 00:00:00 2001
From: Maxence Larrieu <m@larri.eu>
Date: Wed, 6 Dec 2023 21:16:41 +0100
Subject: [PATCH] add step 1 and 2
---
.gitignore | 2 +-
.../concatenet-enrich-dois.py | 60 +
.../datacite-parser-instructions.json | 66 +
.../z_personal_functions.py | 192 ++
2-produce-graph/hist--datasets-by-year.png | Bin 0 -> 26239 bytes
2-produce-graph/hist-quantity-by-repo.py | 39 +
2-produce-graph/pie--datacite-client.png | Bin 0 -> 30740 bytes
2-produce-graph/pie-datacite-client.py | 30 +
2-produce-graph/z_my_functions.py | 14 +
README.md | 10 +-
dois-uga.csv | 2827 +++++++++++++++++
run-all-codes.py | 3 +-
12 files changed, 3239 insertions(+), 4 deletions(-)
create mode 100644 1-enrich-with-datacite/concatenet-enrich-dois.py
create mode 100644 1-enrich-with-datacite/datacite-parser-instructions.json
create mode 100644 1-enrich-with-datacite/z_personal_functions.py
create mode 100644 2-produce-graph/hist--datasets-by-year.png
create mode 100644 2-produce-graph/hist-quantity-by-repo.py
create mode 100644 2-produce-graph/pie--datacite-client.png
create mode 100644 2-produce-graph/pie-datacite-client.py
create mode 100644 2-produce-graph/z_my_functions.py
create mode 100644 dois-uga.csv
diff --git a/.gitignore b/.gitignore
index 73ed033..d00676d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,5 +1,5 @@
/0-collect-data/personnal-keys.json
/0-collect-data/bso/
/1-enrich-with-datacite/__pycache__/
-
+/2-produce-graph/__pycache__/
/hide
\ No newline at end of file
diff --git a/1-enrich-with-datacite/concatenet-enrich-dois.py b/1-enrich-with-datacite/concatenet-enrich-dois.py
new file mode 100644
index 0000000..1bed06d
--- /dev/null
+++ b/1-enrich-with-datacite/concatenet-enrich-dois.py
@@ -0,0 +1,60 @@
+import z_personal_functions as my_functions
+import requests, json, random, pandas as pd
+
+
+# ______0______ load DOIs and remove duplicate
+
+## specifier la liste des entrepôts à importer
+repo_list = ["nakala", "bso-via-hal", "datacite", "zenodo", "rdg"]
+
+dois_raw = my_functions.from_repos_load_dois(repo_list)
+print("DOIs loaded\t\t\t", len(dois_raw))
+
+## remove duplicate
+dois = list(set(dois_raw))
+print("DOIs to treat\t\t\t", len(dois))
+
+
+# ______1_____ load metadata from dataCite and get specified metadatas
+
+## pour essayer avec un seul DOI
+# # random doi 10.25656/01:8509
+# temp_doi = dois[random.randint(0, len(dois))]
+# #temp_doi = "10.57745/QYIAWX"
+# print(temp_doi)
+# raw_metadatas = my_functions.get_md_from_datacite(temp_doi)
+
+doi_error = [] # retrieve doi error
+temp_rows = [] # put data in dict before df
+
+df_old = pd.read_csv("../dois-uga.csv")
+print(f"\nnb of dois already treated\t{len(df_old)}")
+
+# req dataCite and paste data following instructions
+for doi in dois : #[:300]
+
+ ## if doi already treated
+ if doi in df_old["doi"].values :
+ #print(f"\talready treated\t\t{doi}")
+ continue
+
+ ## get md from datacite
+ raw_md = my_functions.get_md_from_datacite(doi)
+
+ ### if doi not in datacite
+ if raw_md == "error" :
+ doi_error.append(doi)
+ continue
+
+ ## from manual instruction retrieve accurate data
+ selected_md = my_functions.parse_datacite_md(raw_md) ## placer les resultats dans un dictionnaire
+ temp_rows.append(selected_md) ## ajouter ce dictionnaire à une liste
+ print(f"\tadded\t\t{doi}")
+
+
+if temp_rows :
+ df_fresh = pd.DataFrame(temp_rows)
+ df_out = pd.concat([df_old, df_fresh], ignore_index=True)
+ df_out.to_csv("../dois-uga.csv", index = False)
+ print(f"\n\nnb of doi exported \t{len(df_out)}")
+
diff --git a/1-enrich-with-datacite/datacite-parser-instructions.json b/1-enrich-with-datacite/datacite-parser-instructions.json
new file mode 100644
index 0000000..b67cbc4
--- /dev/null
+++ b/1-enrich-with-datacite/datacite-parser-instructions.json
@@ -0,0 +1,66 @@
+{
+ "title" : "explique les chemins et les champs des données de datacite à récupérer",
+ "version" : "2023-11-20",
+ "comentaires" : {
+ "0" : "non prise en compte de l'attribut dates",
+ "1" : "non prise en compte de l'attrbut relatedIdentifiers"
+ },
+ "path-and-fields" : {
+
+ "attributes" : {
+ "titles" : {
+ "type" : "list of dict",
+ "past_first_occ" : "title"
+ },
+ "publisher" : "string",
+ "publicationYear" : "int",
+ "subjects" : {
+ "past_values_w_this_key" : "subject",
+ "flatten_all_in_this_key" : "subject_raw"
+ },
+ "language" : "string",
+ "types" : {
+ "type" : "dict",
+ "past_values_w_this_key" : "resourceTypeGeneral"
+ },
+ "sizes" : "string",
+ "formats" : "string",
+ "rightsList" : {
+ "type" : "list of dict",
+ "past_values_w_this_key" :"rights"
+ },
+ "descriptions" : {
+ "type" : "list of dict",
+ "past_first_occ" : "description"
+ },
+ "geoLocations" : {
+ "flatten_all_in_this_key" : "geoLocations_raw"
+ },
+ "FundingReferences" : {
+ "flatten_all_in_this_key" : "FundingReferences_raw"
+ },
+ "source" : "string",
+ "isActive" : "string",
+ "state" : "string",
+ "viewCount" : "int",
+ "downloadCount" : "int",
+ "referenceCount" : "int",
+ "citationCount" : "int",
+ "versionCount" : "int",
+ "created" : "string",
+ "registered" : "string"
+ },
+ "relationships" : {
+ "client" : {
+ "go_to_sub_key" : "data",
+ "get_key" : "id"
+
+ },
+ "provider" : {
+ "go_to_sub_key" : "data",
+ "get_key" : "id"
+ }
+
+ }
+ }
+}
diff --git a/1-enrich-with-datacite/z_personal_functions.py b/1-enrich-with-datacite/z_personal_functions.py
new file mode 100644
index 0000000..f10137a
--- /dev/null
+++ b/1-enrich-with-datacite/z_personal_functions.py
@@ -0,0 +1,192 @@
+import requests, json
+
+def get_md_from_datacite( doi ) :
+ """
+ retrieve data research metadata from datacite
+ """
+
+ req = requests.get( f"https://api.datacite.org/dois/{doi}" )
+
+ try :
+ res = req.json()
+ except :
+ return "error"
+
+ if "errors" in res :
+ return "error"
+
+ return res
+
+
+def parse_value_following_instruction(key, instruction, datacite_content) :
+ """
+ permet de récuéprer les données reçues depuis datacite avec leur propre sturcturation selon les instructions précisées manuellement
+ key : la clé à traiter
+ instruction : les instructions à appliquer pour récupérer la valeur de la clé
+ datacite_content : le contenu de datacite à la clé précisé
+
+ la recherche des instructions est effectuée notamment depuis leur type (string ou dict) : à revoir pour plus de cohérence
+ """
+
+ buffer = {} ## pour récupérer les données avec un dictionnaire
+
+ ## quand les données à récupérer sont des objets simples, on récupère simplement la valeur
+ if instruction == "string" or instruction == "int" :
+ return {key: datacite_content}
+
+ ## qaund les instructions sont fomratées en dict
+ if isinstance(instruction, dict) :
+
+ ## si past_values_w_this_key est dans les instructions
+ if "past_values_w_this_key" in instruction :
+ ## pour débbugger
+ ##print("attribute is", key)
+
+ ## quand les données sont directement sous forme de dict (eg. datatype)
+ if instruction["past_values_w_this_key"] in datacite_content :
+ temp_key_to_get = instruction["past_values_w_this_key"]
+
+ buffer.update(
+ { instruction["past_values_w_this_key"] : datacite_content[temp_key_to_get] }
+ )
+
+ ## quand les données sont des listes et qu'il faut itérer dessus
+ else :
+ all_vals = []
+ temp_key_to_get = instruction["past_values_w_this_key"]
+ [all_vals.append( item[ temp_key_to_get ]) for item in datacite_content]
+
+ buffer.update(
+ {temp_key_to_get : ",".join(all_vals)}
+ )
+
+ ## quand il faut sortir toutes les données brutes
+ if "flatten_all_in_this_key" in instruction :
+ buffer.update(
+ {instruction["flatten_all_in_this_key"] : str(datacite_content) }
+ )
+
+ ## if past_first_occ in instruction
+ if "past_first_occ" in instruction :
+ temp_key_to_get = instruction["past_first_occ"]
+ buffer.update(
+ {temp_key_to_get: datacite_content[0][temp_key_to_get]}
+ )
+
+ ## if go_to_sub_key in the instruction
+ if "go_to_sub_key" in instruction :
+
+ temp_parent_key_to_get = instruction["go_to_sub_key"]
+ ## identifier les clés enfantes à retrouver dans dataCite
+ temp_child_key_to_get = instruction["get_key"]
+
+ buffer.update(
+ {key : datacite_content[temp_parent_key_to_get][temp_child_key_to_get] }
+ )
+
+ else :
+ buffer.update(
+ {key : "to_do"}
+ )
+
+ return buffer
+
+
+
+def parse_datacite_md(raw_datacite_mds):
+ """
+ from json file load instruction
+ from DOI get datacite cotent
+ iterate on all datacite attributes
+ if data from datacite is needed get it with parse_value_following_instruction()
+ iterate on all datacite relationship
+ if data from datacite is needed get it with parse_value_following_instruction()
+ """
+ doi_md = {
+ "doi" : raw_datacite_mds["data"]["id"]
+ }
+
+ ## ____0____ from json file load instructions
+ with open("datacite-parser-instructions.json") as parser_file :
+ datacite_parser = json.load(parser_file)
+
+ ## liste de tous les attributs à récupérer
+ attributes_to_get = datacite_parser["path-and-fields"]["attributes"].keys()
+ relations_to_get = datacite_parser["path-and-fields"]["relationships"].keys()
+
+ ## ____1___ iterate on datacite attributes
+ for attribute_key in raw_datacite_mds["data"]["attributes"] :
+ attribute_value = raw_datacite_mds["data"]["attributes"][attribute_key]
+
+ ## ne pas prendre les valeurs si elles sont nulles (sauf pour les nb)
+ if not isinstance(attribute_value, int) and not attribute_value :
+ # pour suivi print(f"{attribute_key} is empty")
+ continue
+
+ ## si l'attribut fait parti de ceux à récupérer
+ if attribute_key in attributes_to_get :
+
+ ## redistribuer le nom de la clé et sa valeur
+ value_to_add = parse_value_following_instruction(
+ attribute_key,
+ datacite_parser["path-and-fields"]["attributes"][attribute_key],
+ attribute_value)
+
+ doi_md.update(value_to_add)
+
+
+ ## ____2___ iterate on datacite relations
+ ### nb : on pourrait alléger en regroupant attribut et relationships
+ for relation_key in raw_datacite_mds["data"]["relationships"] :
+ relation_value = raw_datacite_mds["data"]["relationships"][relation_key]
+
+ ## ne pas prendre les valeurs si elles sont nulles (sauf pour les nb)
+ if not isinstance(relation_key, int) and not relation_value :
+ continue
+
+ ## si la relation est préciser dans les instructions
+ if relation_key in relations_to_get :
+ ## to debug print("relation is", relation_key)
+ relation_to_add = parse_value_following_instruction(
+ relation_key,
+ datacite_parser["path-and-fields"]["relationships"][relation_key],
+ relation_value
+ )
+ doi_md.update(relation_to_add)
+
+ return doi_md
+
+
+def from_repos_load_dois(repo_list) :
+ """
+ from repo name (eg Zenodo) load file
+ """
+ dois_raw = []
+
+ ## load all dois
+ for repo_name in repo_list :
+ dois_raw += load_dois_from_file(repo_name)
+
+ return dois_raw
+
+
+def load_dois_from_file(repo_name) :
+ """
+ charge les dois des fichiers texts
+ file name syntax "entrepot-dois.txt"
+ """
+
+ file_name = repo_name + "-dois.txt"
+ folder_path = "../0-collect-data/"
+ dois_in_repo = []
+
+ with open(folder_path + file_name) as f:
+ ## attention à la fin des lignes il y a un retour à la ligne, d'où le (line)-1
+ ## on passer les DOI en miniscule également
+ [dois_in_repo.append( line[ :len(line)-1].lower()) for line in f.readlines()]
+
+ print(f"{repo_name} DOIs \t\t {len(dois_in_repo)}")
+
+ return dois_in_repo
+
+
diff --git a/2-produce-graph/hist--datasets-by-year.png b/2-produce-graph/hist--datasets-by-year.png
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diff --git a/2-produce-graph/hist-quantity-by-repo.py b/2-produce-graph/hist-quantity-by-repo.py
new file mode 100644
index 0000000..9a05fc1
--- /dev/null
+++ b/2-produce-graph/hist-quantity-by-repo.py
@@ -0,0 +1,39 @@
+import pandas as pd, matplotlib, matplotlib.pyplot as plt
+import z_my_functions as my_fct
+
+
+df = my_fct.load_and_treat_csv()
+
+print(df.columns)
+
+print("nb de datasets\t", len(df))
+
+## publicationYear contient une année de 1995 : on reconstruit un champs année à partir de "created" : date d'enregistrement du dépot
+df["year"] = df["created"].str[:4]
+#print( df["year"].value_counts() )
+
+
+df_hist = pd.DataFrame( df.groupby(["year"])[["doi"]].agg(["count"])).reset_index()
+## rename columns
+df_hist.columns = ["year", "nb_dois"]
+#print("\n", df_hist)
+
+
+## ____N____ do graph
+
+fig, (ax) = plt.subplots(figsize=(8, 6), dpi=100, facecolor='w', edgecolor='k')
+ax.bar(df_hist.year, df_hist.nb_dois , align='center', alpha = 1.0, color='#7e96c4', ecolor='black', label="tba")
+plt.xticks(df_hist.year.values)
+
+## remove axi
+ax.spines['top'].set_visible(False)
+ax.spines['right'].set_visible(False)
+ax.set_ylabel("number of datasets", labelpad = 10)
+
+plt.title(f"Number of datasets by year", fontsize = 22, x = 0.5, y = 1.03, alpha = 0.6)
+plt.suptitle(f"n = {len(df)}", fontsize = 12, x = 0.5, y = 0.8, alpha = 0.6)
+plt.savefig("hist--datasets-by-year.png")
+
+
+
+
diff --git a/2-produce-graph/pie--datacite-client.png b/2-produce-graph/pie--datacite-client.png
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diff --git a/2-produce-graph/pie-datacite-client.py b/2-produce-graph/pie-datacite-client.py
new file mode 100644
index 0000000..c79f21d
--- /dev/null
+++ b/2-produce-graph/pie-datacite-client.py
@@ -0,0 +1,30 @@
+import pandas as pd, matplotlib, matplotlib.pyplot as plt
+import z_my_functions as my_fct
+import seaborn as sns
+
+
+df = my_fct.load_and_treat_csv()
+print(df.columns)
+
+df_client_raw = df["client"].value_counts()
+
+## regroup small values in "other"
+treshold = 8
+df_client = df_client_raw[df_client_raw > treshold]
+
+## remove point in client name (eg. zenodo.cern)
+clients_name = [item[: item.find(".")] for item in df_client.index]
+
+df_client["other"] = df_client_raw[df_client_raw <= treshold].sum()
+clients_name.append("other")
+
+
+#define Seaborn color palette to use
+colors = sns.color_palette('pastel')[0:len(df_client)]
+
+plt.pie(df_client, labels = clients_name, colors = colors, autopct='%.0f%%')
+plt.title(f"Distribution of datasets by DataCite client", fontsize = 20, x = 0.5, y = 1.03, alpha = 0.6)
+plt.savefig("pie--datacite-client.png")
+
+
+# print(len(df))
\ No newline at end of file
diff --git a/2-produce-graph/z_my_functions.py b/2-produce-graph/z_my_functions.py
new file mode 100644
index 0000000..bac1d1f
--- /dev/null
+++ b/2-produce-graph/z_my_functions.py
@@ -0,0 +1,14 @@
+import pandas as pd
+
+
+def load_and_treat_csv() :
+
+ df_raw = pd.read_csv("../dois-uga.csv", index_col=False)
+
+ ## remove datacite type that are not "research data"
+ type_to_explude = ["Book", "ConferencePaper", "JournalArticle", "BookChapter", "Service", "Preprint"]
+ df = df_raw[ ~df_raw["resourceTypeGeneral"].isin(type_to_explude) ].copy()
+
+ return df
+
+
\ No newline at end of file
diff --git a/README.md b/README.md
index 62e5442..53709f6 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,14 @@
# UGA Open Research Data monitor
-> let's describe _open_ research data produced in by Grenoble Alpes University !
+Let's describe _open_ research data produced in by Grenoble Alpes University !
+
+_in process_
+
+## Example
+
+
+
+
## Sources
diff --git a/dois-uga.csv b/dois-uga.csv
new file mode 100644
index 0000000..1e73c80
--- /dev/null
+++ b/dois-uga.csv
@@ -0,0 +1,2827 @@
+doi,title,publisher,publicationYear,language,resourceTypeGeneral,rights,description,source,isActive,state,viewCount,downloadCount,referenceCount,citationCount,versionCount,created,registered,client,provider,subject,subject_raw,sizes,formats
+10.57757/iugg23-4563,Constraining earthquake depth at teleseismic distance: Picking depth phases with deep learning,GFZ German Research Centre for Geosciences,2023,en,ConferencePaper,Creative Commons Attribution 4.0 International,"<!--!introduction!--><b></b><p>Automated teleseismic earthquake monitoring is an essential part of global seismicity analysis. However, while constraining earthquake epicenters in an automated fashion is an established technique, constraining event depth is substantially more difficult, especially in the absence of nearby stations. One solution to this challenge are teleseismic depth phases but these can currently not be identified by automatic detection methods. Here we propose two deep learning models, DepthPhaseNet and DepthPhaseTEAM to detect depth phases. The first model closely follows the PhaseNet architectures with minor modifications; the latter allows joint analysis of multiple stations by adding a transformer to this basic architecture. For training the models, we create a dataset based on the ISC EHB bulletin, a high-quality catalog with detailed phase annotations. We show how backprojecting the predicted phase arrival probability curves onto the depth axes yields excellent estimates of earthquake depth. The models achieve mean absolute errors below 10 km. Furthermore, we demonstrate that the multi-station model, DepthPhaseTEAM, leads to better and more consistent predictions than the single-station model DepthPhaseNet. To allow direct application of our models, we integrate them within the SeisBench library for machine learning in seismology.</p>",fabricaForm,True,findable,0,0,0,0,0,2023-07-03T19:58:09.000Z,2023-07-10T20:46:27.000Z,gfz.iugg2023,gfz,,,,
+10.5281/zenodo.4767088,Atlas.TI deductive coding of normative assumptions in SE scholarship,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access",Deductive content analysis of a sample of 100 influential publications in the field of social entrepreneurship (SE) to identify the normative assumptions in SE scholarship. Eight contemporary schools of thought in political philosophy are used as a template for analysis.,mds,True,findable,0,0,0,0,0,2021-05-17T08:55:20.000Z,2021-05-17T08:55:21.000Z,cern.zenodo,cern,"social entrepreneurship,political philosophy","[{'subject': 'social entrepreneurship'}, {'subject': 'political philosophy'}]",,
+10.57745/3d4dfw,"Stream concentrations of micropollutants in the Claduègne, Ardèche",Recherche Data Gouv,2023,,Dataset,,"Stream concentrations of different organic micropollutants at different times and locations throughout the Claduègne catchment in Ardèche. The data include mainly human and veterinary pharmaceuticals. The analyzed molecules are: Atenolol, Bisoprolol, Caffeine, Carbamazepine, Cetirizine, Diclofenac, Fenbendazole, Irbesartan, Iopromide, Ivermectin, Lidocaine, Metformin, Mebendazole, Nicotinamide, Sulfamethoxazole, Trimethoprim, Telmisartan. The samples were taken in 2019 & 2020. An article describing and interpreting the data will be linked once published.",mds,True,findable,189,2,0,0,0,2023-04-20T13:24:04.000Z,2023-06-20T12:31:16.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.4761299,"Fig. 10 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 10. Dictyogenus jurassicum sp. n., larva. Spring of River Doubs, Mouthe, Doubs dpt, France. Photo A. Ruffoni.",mds,True,findable,0,0,4,0,0,2021-05-14T07:44:25.000Z,2021-05-14T07:44:26.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.3874714,Raw diffraction data for [NiFeSe] hydrogenase G491A variant pressurized with O2 gas - dataset G491A-O2,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","Diffraction data measured at ESRF beamline ID30A-3 on September 27, 2017. N.B. Image files 1416-1419 are damaged and cannot be used for integration.",mds,True,findable,0,0,0,0,0,2020-06-03T13:56:40.000Z,2020-06-03T13:56:41.000Z,cern.zenodo,cern,"Hydrogenase,Selenium,gas channels,high-pressure derivatization","[{'subject': 'Hydrogenase'}, {'subject': 'Selenium'}, {'subject': 'gas channels'}, {'subject': 'high-pressure derivatization'}]",,
+10.5281/zenodo.8189792,ailsachung/IsoInv1D: IsoInv1D,Zenodo,2023,,Software,Open Access,1D numerical model for ice sheet age-depth profile constrained using radar horizons,mds,True,findable,0,0,0,1,0,2023-07-27T14:03:02.000Z,2023-07-27T14:03:02.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23575369.v1,Additional file 4 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 3,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:49.000Z,2023-06-25T03:11:51.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['45056 Bytes'],
+10.5061/dryad.1sf007b,Data from: Species Selection Regime and Phylogenetic Tree Shape,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"Species selection, the effect of heritable traits in generating between-lineage diversification rate differences, provides a valuable conceptual framework for understanding the relationship between traits, diversification and phylogenetic tree shape. An important challenge, however, is that the nature of real diversification landscapes – curves or surfaces which describe the propensity of species-level lineages to diversify as a function of one or more traits – remains poorly understood. Here we present a novel, time-stratified extension of the QuaSSE model in which speciation/extinction rate is specified as a static or temporally-shifting Gaussian or skewed-Gaussian function of the diversification trait. We then use simulations to show that the generally imbalanced nature of real phylogenetic trees, as well as their generally greater-than-expected frequency of deep branching events, are typical outcomes when diversification is treated as a dynamic, trait-dependent process. Focusing on four basic models (Gaussian-speciation with and without background extinction; skewed-speciation; Gaussian-extinction), we also show that particular features of the species selection regime produce distinct tree shape signatures and that, consequently, a combination of tree shape metrics has the potential to reveal the species selection regime under which a particular lineage diversified. We evaluate this idea empirically by comparing the phylogenetic trees of plant lineages diversifying within climatically- and geologically-stable environments of the Greater Cape Floristic Region, with those of lineages diversifying in environments that have experienced major change through the Late Miocene-Pliocene. Consistent with our expectations, the trees of lineages diversifying in a dynamic context are less balanced, show a greater concentration of branching events close to the present, and display stronger diversification rate-trait correlations. We suggest that species selection plays an important role in shaping phylogenetic trees but recognize the need for an explicit probabilistic framework within which to assess the likelihoods of alternative diversification scenarios as explanations of a particular tree shape.",mds,True,findable,151,15,0,1,0,2019-11-26T16:06:13.000Z,2019-11-26T16:06:14.000Z,dryad.dryad,dryad,"Cape flora,enviromental change,gamma statistic,species selection,tree imbalance,time-stratified QuaSSE model,trait-dependent diversification,diversification landscape","[{'subject': 'Cape flora'}, {'subject': 'enviromental change'}, {'subject': 'gamma statistic'}, {'subject': 'species selection'}, {'subject': 'tree imbalance'}, {'subject': 'time-stratified QuaSSE model'}, {'subject': 'trait-dependent diversification'}, {'subject': 'diversification landscape'}]",['40229140 bytes'],
+10.5281/zenodo.8181417,"Code used in the Publication ""Coated microbubbles exploit shell buckling to swim"" submitted to Nature Communications Engineering 2023",Zenodo,2023,en,Software,"Creative Commons Attribution 4.0 International,Open Access","This is the code used for the simulations that have been performed for the Article ""Coated microbubbles exploit shell buckling to swim"" submitted to Nature Communications Engineering 2023 authored by Georges Chabouh, Marcel Mokbel, Benjamin van Elburg, Michel Versluis, Tim<br> Segers, Sebastian Aland, Catherine Quilliet, and Gwennou Coupier. Responsible for the code are Marcel Mokbel and Sebastian Aland. Paper abstract: Cleverly engineered microswimmers show great promise in various biomedical applications. Current realizations are generally<br> either too slow, hardly manoeuvrable, or non biocompatible. To overcome these limitations, we consider lipid coated microbub-<br> bles that are already approved for clinical use as diagnostic ultrasound contrast agents. Through a combination of experiments<br> and numerical simulations, we investigate the swimming motion of these microbubbles under external cyclic overpressure.<br> Reproducible and non-destructive cycles of deflation and re-inflation of the microbubble generate a net displacement, through<br> hysteretic buckling events. Our model predicts swimming speeds of the order of m/s, which falls in the range of blood flow<br> velocity in large vessels. Unlike the acoustic radiation force technique, where the displacement is always directed along the<br> axis of ultrasound propagation, here, the direction of propulsion is controlled in the shell reference frame. This provides a<br> solution toward controlled steering in ultrasound molecular imaging and drug delivery.",mds,True,findable,0,0,0,0,0,2023-07-25T08:15:48.000Z,2023-07-25T08:15:49.000Z,cern.zenodo,cern,,,,
+10.57745/uogrpy,Synthetic Datasets and Evaluations for Sub-pixel Displacements Estimation from Optical Satellite Images with Deep Learning,Recherche Data Gouv,2023,,Dataset,,"Contains 3 synthetic datasets (UNI, DIS, UNI-5px), with three corresponding trained models, based on a CNN architecture. The three datasets contains pairs of small (either 16x16 or 32x32 pixels) windows that simulate shifts. Contains also evaluations on realistic synthetics examples of a deep learning pipeline using two of the three models presented.",mds,True,findable,21,0,0,0,0,2023-09-15T08:36:13.000Z,2023-11-02T16:12:28.000Z,rdg.prod,rdg,,,,
+10.6084/m9.figshare.12295910,Metadata record for: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data,figshare,2020,,Dataset,Creative Commons Zero v1.0 Universal,This dataset contains key characteristics about the data described in the Data Descriptor The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format <br> <br> <br>,mds,True,findable,0,0,1,2,0,2020-05-29T12:13:47.000Z,2020-05-29T12:13:48.000Z,figshare.ars,otjm,"49999 Earth Sciences not elsewhere classified,FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences,Environmental Science,Climate Science,Biochemistry,60302 Biogeography and Phylogeography,FOS: Biological sciences,FOS: Biological sciences","[{'subject': '49999 Earth Sciences not elsewhere classified', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Environmental Science'}, {'subject': 'Climate Science'}, {'subject': 'Biochemistry'}, {'subject': '60302 Biogeography and Phylogeography', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'FOS: Biological sciences', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['37506 Bytes'],
+10.5281/zenodo.5348289,Replication Package for the paper: Verification of Distributed Systems via Sequential Emulation,Zenodo,2021,en,Software,"BSD 3-Clause Clear License,Open Access","This package allows to replicate the experiments described in “Verification of Distributed Systems via Sequential Emulationâ€. Instructions for full replication are also included. Repository contents <code>main.sh</code>: Quickstart script to run all experiments <code>permissions.sh</code>: script to give adequate permissions to executables <code>replication.tar.gz</code>: gzipped archive containing: <code>emergence</code>, <code>invariant</code>, <code>stock</code>: C programs used in the experimental evaluation. Each directory also contains a <code>_logs</code> folder with the log files referred in the paper. <code>labs</code>: LAbS specifications used for <code>emergence</code> and <code>invariant</code> experiments. <code>LICENSE</code>: conditions to use the repository contents <code>tools</code>: Software used to generate C programs and run experiments <code>README.mdown</code>: the README file of the original replication repository (https://gitlab.inria.fr/ldistefa/tosem-artifacts) <code>README-ZENODO.mdown</code>: this document <code>replication.py</code>: Python script to replicate the experiments <code>replication.sh</code>: fallback shell script to replicate the experiments Requirements All experiments should run successfully on most x64 Linux machines. Python 3.7 or above is needed to run the <code>replication.py</code> script. Alternatively, one may run the <code>replication.sh</code> shell script. Some caveats about specific tools: Symbiotic requires a <code>python</code> executable in the machine’s PATH (usually <code>/usr/bin/python</code>). This may be a symbolic link pointing to a Python 3 executable (usually <code>/usr/bin/python3</code>). SeaHorn requires a Python 2 executable (usually <code>/usr/bin/python2</code>). To generate instrumented programs (see below), an external C preprocessor is required. For instance, we use <code>gcc -E</code>. We do provide ready-to-use instumented programs. Quickstart Download the whole repository to some directory <code>dir</code>, then: <pre><code>cd /path/to/dir # Gives execution permission to main.sh, tools, and their dependencies chmod +x permissions.sh # Unpacks the archive, makes log directories, and runs all experiments ./main.sh</code></pre> The script will create a <code>dir/logs</code> directory with subdirectories <code>emergence</code>, <code>invariant</code>, and <code>stock</code>, where it will store the output of each verification task. Replication details Generation of C programs from LAbS specifications The following commands will use <code>sliver</code> to create C emulation programs from each LAbS system considered in the paper: <pre><code># Invariant programs tools/sliver-v1.5_linux_x64/sliver.py labs/formation.invariant.labs size=10 range=2 n=3 --fair --no-bv --show > invariant/formation/formation.c tools/sliver-v1.5_linux_x64/sliver.py labs/approx.labs yes=1 no=2 --no-bv --show > invariant/approx-a/approx-a.c tools/sliver-v1.5_linux_x64/sliver.py labs/approx.labs yes=2 no=3 --no-bv --show > invariant/approx-a/approx-b.c.orig tools/sliver-v1.5_linux_x64/sliver.py labs/maj.labs yes=1 no=2 --no-bv --show > invariant/maj/maj.c.orig # Emergence programs tools/sliver-v1.5_linux_x64/sliver.py labs/boids.labs birds=3 size=5 delta=5 --fair --no-bv --show > emergence/boids/boids.c tools/sliver-v1.5_linux_x64/sliver.py labs/flock.labs birds=3 size=5 delta=5 --fair --no-bv --show > emergence/flock/flock.c tools/sliver-v1.5_linux_x64/sliver.py labs/formation.emergence.labs size=10 range=2 n=3 --fair --no-bv --show > emergence/formation/formation.c</code></pre> Each folder under <code>invariant</code> and <code>emergence</code> contains a <code><program>.c</code> file which is the output of one the above commands. Notice that, for <code>approx-b</code> and <code>maj</code>, we have manually performed some additional transformations. The unmodified <code>sliver</code> output is named <code>maj.c.orig</code> and the final program is named <code>maj.c</code>. Instrumentation of C programs SLiVER was originally tailored towards BMC verification, so it generates programs that can be directly verified by CBMC. Other tools require an instrumentation steps. Typically this amounts to replace verification intrinsics with those supported by the tools, add specific headers or function declarations, etc. We have automated this steps by means of a helper Python program called <code>absentee</code>, which can be found in the <code>tools</code> directory and at (https://github.com/lou1306/absentee) Typically, to instrument the SLiVER program <code>program.c</code> for verification by a specific tool, one can use the following command line: <pre><code>cd tools/absentee gcc -E /path/to/<program>.c | python3 -m absentee --conf <tool>.conf - > /path/to/<program>.<tool>.c</code></pre> Preprocessing the original program with <code>gcc</code> (or another compiler) is needed because <code>absentee</code> does not support preprocessor directives. Each folder under <code>invariant</code> and <code>emergence</code> already contains a file <code><program>.<tool>.c</code>, which is the result of this step for each tool in our experimental evaluation. Verification Each tool needs a specific set of arguments, environment variables, etc. to correctly perform its verification task. To investigate the actual commands we used in our evaluation, please check the <code>replication.sh</code> script or the <code>replication.py</code> program. About the <code>stock</code> case studies We wrote the <code>stock-safe</code> and <code>stock-unsafe</code> case studies directly as triple structure, and then encoded it as C programs using the same procedure described in the paper and implemented by <code>sliver</code>. We provide these C programs, as well as their instumented version for 2ls, in the <code>stock</code> folder. Usage instructions for <code>replication.py</code> In case one wants more granularity, <code>replication.py</code> may be run manually. <code>./replication.py --help</code> shows usage instructions. In brief: <code>./replication.py</code> runs all the experiments. <code>./replication.py tool1 tool2 ...</code> only runs the experiments with the given tools. <code>./replication.py --list</code> lists the tool names. <code>./replication --timeout <n></code> overrides the default timeout to <em>n</em> seconds (<em>n</em> must be a positive integer) By adding <code>--dry-run</code>, the script only shows the experiments’ command lines, without actually executing them. Keep in mind that most tools also require custom environment variables or won’t run properly when invoked outside of their own directories, so these command lines are only for reference. Support For further information, you may look at the original Git repository for the artifacts: (https://gitlab.inria.fr/ldistefa/tosem-artifacts) You can also contact the paper’s corresponding author: Luca Di Stefano luca.di-stefano@inria.fr Acknowledgments Work partially funded by MIUR project PRIN 2017FTXR7S <em>IT MATTERS</em> (Methods and Tools for Trustworthy Smart Systems). Disclaimer The authors of this repository do not endorse using its contents for ANY purpose besides replication of experiments presented in the paper “Verification of Distributed Systems via Sequential Emulationâ€. Please enquire with the paper’s corresponding author (Luca Di Stefano luca.di-stefano@inria.fr) about software packages intended for generic usage.",mds,True,findable,0,0,0,1,0,2021-09-15T12:19:52.000Z,2021-09-15T12:19:53.000Z,cern.zenodo,cern,"formal verification,multi-agent systems,reachability,termination,sequentialization,structural operational semantics","[{'subject': 'formal verification'}, {'subject': 'multi-agent systems'}, {'subject': 'reachability'}, {'subject': 'termination'}, {'subject': 'sequentialization'}, {'subject': 'structural operational semantics'}]",,
+10.5281/zenodo.10055462,Mont Blanc ice core data for NH3 source investigation in Europe,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,Dataset to interpret the δ15N(NH4+) in a Mont Blanc ice core,api,True,findable,0,0,0,0,0,2023-11-03T08:48:41.000Z,2023-11-03T08:48:41.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4661481,phrb/phd-journal: First Zenodo Release,Zenodo,2021,,Software,Open Access,No description provided.,mds,True,findable,0,0,0,0,0,2021-04-03T18:55:25.000Z,2021-04-03T18:55:26.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7835266,Discrete and continuum simulations of bedload transport with kinetic theory of granular flow,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This depository contains the simulation results used in the publication Chassagne, R., Chauchat J. & Cyrille B. (2023). A frictional-collisional model for bedload transport based on kinetic theory of granular flows: discrete and continuum approaches. It contains DEM results as well as the results of the continuum model. The results are written in text files containing headers with name and units of the variables.",mds,True,findable,0,0,0,0,0,2023-04-17T08:08:38.000Z,2023-04-17T08:08:38.000Z,cern.zenodo,cern,"Granular flow,Sediment transport,Kinetic theory of granular flows","[{'subject': 'Granular flow'}, {'subject': 'Sediment transport'}, {'subject': 'Kinetic theory of granular flows'}]",,
+10.5281/zenodo.8363118,Bulk chemical composition of rock samples used to calculate their seismic velocity at lower crustal conditions,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These data are linked to a published study, whose aim is to compare the seismic velocity variations, derived from tomographic models (here the CIFALPS profile in the Alps, derived from Nouibat et al., 2022) and interpreted as rock transformations, with the seismic velocities of field samples. One way to predict seismic velocity at lower crustal conditions is to consider natural rocks as isotropic and to calculate their seismic properties from the relative abundance of mineral phases using their acknowledged properties (Abers and Hacker, 2016). In this process, the bulk chemical composition of the samples constitutes the starting data for this study. The subsequent work is based solely on thermodynamic models (here mainly using Holland and Powel, 1998 database) and the physical properties of the mineral phases (database from Abers and Hacker, 2016).",mds,True,findable,0,0,0,0,0,2023-09-20T11:07:28.000Z,2023-09-20T11:07:29.000Z,cern.zenodo,cern,"chemical composition, seismic velocity, lower crustal conditions, Alps","[{'subject': 'chemical composition, seismic velocity, lower crustal conditions, Alps'}]",,
+10.5281/zenodo.5120376,Ensemble of ice shelf basal melt rates and ocean properties for tipped-over continental shelves,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Summary</strong><strong>:</strong> This dataset contains the reference and tipped states from several model configurations developed at the Alfred Wegener Institute (AWI) and the Institut des Géosciences de l’Environnement (IGE). They were gathered here in the context of the TiPACCs European project and constitute a useful ensemble of reference and tipped ocean–ice-shelf simulations that <strong>can be used to feed ice-sheet simulations or to train melt parameterizations</strong>. The simulations produced by AWI are based on the FESOM global ocean–sea-ice model using either Z- or Sigma- coordinates and all show a cold-to-warm tipping point for Filchner-Ronne Ice Shelf. The two sets of simulations produced by IGE are based on the NEMO ocean–sea-ice model. They include a global configuration showing a cold-to-warm tipping point for Ross Ice Shelf, and regional Amundsen Sea configuration showing a warm-to-warmer transition (likely not a proper tipping point). The files include 3-dimensional and sea-floor ocean temperatures and salinities, ice-shelf melt rates, as well as topographic and grid data. All variables are interpolated onto the common 8km stereographic grid that was used to provide ocean forcing in ISMIP6 (Nowicki et al. 2020). We provide the reference state and the anomaly, so that the tipped state is: <em>Tipped = Reference + Anomaly</em> To have an overview of the reference and tipped states, have a look at these figures: <em>figure_ref_and_anomalies_1.pdf</em> <em>figure_ref_and_anomalies_2.pdf</em> <em>figure_seafloor_temp_zooms.pdf</em> _______________________________________________ <strong>Detailed Data Description</strong><strong>:</strong> <strong>reference_high_FESOM_sigma_AWI_TiPACCs.nc</strong> contact: Ralph Timmermann ralph.timmermann@awi.de, Verena Haid verena.haid@awi.de model: FESOM1.4, sigma-coordinates (global with refined grid around Antarctica) atmospheric forcing: HadCM3 20C provided average: 1990-1999 (10-year mean) more: Timmermann and Hellmer (2013) <strong>reference_low_FESOM_sigma_AWI_TiPACCs.nc</strong> contact: Ralph Timmermann ralph.timmermann@awi.de, Verena Haid verena.haid@awi.de model: FESOM1.4, sigma-coordinates (global with refined grid around Antarctica) atmospheric forcing: HadCM3 20C provided average: 1990-1999 (10-year mean) more: Timmermann and Goeller (2017) <strong>reference_FESOM_z_AWI_TiPACCs.nc</strong> contact: Verena Haid verena.haid@awi.de model: FESOM1.4, Z-coordinates (global with refined grid around Antarctica) atmospheric forcing: ERA Interim provided average: 2008-2017 (10-year mean), i.e. model year 30-39 more: same mesh as Gürses et al. (2019) <strong>reference_NEMO4_eORCA025.L121_IGE_TiPACCs.nc</strong> contact: Pierre Mathiot pierre.mathiot@univ-grenoble-alpes.fr model: NEMO-4.0, eORCA025.L121 (Global, 1/4°, 121 vertical levels) atmospheric forcing: JRA55do provided average: 2<sup>nd</sup> cycle of 1989-1998 (10-year mean); we first run 1979-2018, and we redo 1979-1998 starting from the 2018 state. more: https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM021.html <strong>reference_NEMO3_AMUXL12.L75_IGE_TiPACCs.nc</strong> contact: Nicolas Jourdain nicolas.jourdain@univ-grenoble-alpes.fr model: NEMO-3.6, AMUXL12.L75 (Amundsen, 1/12°, 75 vertical levels) atmospheric forcing: MAR (Donat-Magnin et al. 2020) provided average: 1989-2009 (21-year mean) more: similar model set-up as Jourdain et al. (2019). <strong>anomaly_high_FESOM_sigma_AWI_TiPACCs.nc</strong> continuation of reference_high_FESOM_sigma_AWI_TiPACCs.nc forced with HadCM3 A1B provided average: 2190-2199 (10-year mean) <strong>anomaly_low_FESOM_sigma_AWI_TiPACCs.nc</strong> continuation of reference_low_FESOM_sigma_AWI_TiPACCs.nc forced with HadCM3 A1B provided average: 2190-2199 (10-year mean) <strong>anomaly_high_FESOM_z_AWI_TiPACCs.nc</strong> same model set-up as reference_FESOM_z_AWI_TiPACCs.nc atmospheric forcing south of 60°S HadCM3 A1B starting 2050, otherwise ERA Interim starting 1979 provided average: model year 69-78 (10-year mean), i.e. 2008-2017 of 2<sup>nd</sup> 39yr-cycle <strong>anomaly_medium_FESOM_z_AWI_TiPACCs.nc</strong> same model set-up as reference_FESOM_z_AWI_TiPACCs.nc atmospheric forcing: ERA Interim modified with a strong imprint of the seasonal cycle of HadCM3 A1B 2070-2089 provided average: model year 69-78 (10-year mean), i.e. 2008-2017 of 2<sup>nd</sup> 39yr-cycle <strong>anomaly_low_FESOM_z_AWI_TiPACCs.nc</strong> same model set-up as reference_FESOM_z_AWI_TiPACCs.nc atmospheric forcing: manipulated ERA Interim with prolongued summer and shorter, milder winter south of 50°S, additional modification of winds in Weddell Sea region provided average: model year 108-117 (10-year mean), i.e. 2008-2017 of 3<sup>rd</sup> 39yr-cycle <strong>anomaly_NEMO4_eORCA025.L121_IGE_TiPACCs.nc</strong> similar to reference_NEMO4_eORCA025.L121_IGE_TiPACCs.nc perturbation of the model parameters: Different iceberg distribution and different sea-ice–ocean drag and snow conductivity on sea-ice, leading to less sea-ice production in the eastern Ross Sea. More: https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM020.html <strong>anomaly_NEMO3_AMUXL12.L75_IGE_TiPACCs.nc</strong> similar to reference_NEMO3_AMUXL12.L75_IGE_TiPACCs.nc perturbation of atmospheric forcing: MAR forced by the CMIP5 multi-model anomaly under the RCP8.5 scenario (Donat-Magnin et al. 2021). provided average: 2080-2100 (21-year average)",mds,True,findable,0,0,0,0,0,2021-07-21T19:18:55.000Z,2021-07-21T19:18:56.000Z,cern.zenodo,cern,"Tipping point,Antarctica,Ice shelf,Southern Ocean","[{'subject': 'Tipping point'}, {'subject': 'Antarctica'}, {'subject': 'Ice shelf'}, {'subject': 'Southern Ocean'}]",,
+10.5281/zenodo.8269693,"Contrasting the magnetism in La2−xSrxFeCoO6(x=0,1,2) double perovskites: The role of electronic and cationic disorder",Zenodo,2019,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data sets for original figures in the article 'Contrasting the magnetism in La<sub>2−x</sub>Sr<sub>x</sub>FeCoO<sub>6 </sub>(x=0,1,2) double perovskites: The role of electronic and cationic disorder' published in Phys. Rev. B <strong>99</strong>, 184411 (2019). The file name of each xls file corresponds to the figure number in the published article. The files can be opened using the Excel program. If there are sub-figures, or multiple frames in each figure, the data of each sub-figure is stored in separate sheets within one xls file. The files with the file extension 'vesta' can be opened using the freely available program VESTA.",mds,True,findable,0,0,0,0,0,2023-08-21T15:06:10.000Z,2023-08-21T15:06:10.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3627732,FlauBERT: Unsupervised Language Model Pre-training for French,Zenodo,2019,fr,Other,"Creative Commons Attribution 4.0 International,Open Access",Unsupervised Language Model Pre-training for French,mds,True,findable,0,0,0,0,0,2020-01-25T22:42:24.000Z,2020-01-25T22:42:25.000Z,cern.zenodo,cern,"Language model, BERT, Transformer, French","[{'subject': 'Language model, BERT, Transformer, French'}]",,
+10.6084/m9.figshare.21430971.v1,Additional file 1 of Digitally-supported patient-centered asynchronous outpatient follow-up in rheumatoid arthritis - an explorative qualitative study,figshare,2022,,Text,Creative Commons Attribution 4.0 International,Supplementary Material 1,mds,True,findable,0,0,0,0,0,2022-10-29T03:17:13.000Z,2022-10-29T03:17:13.000Z,figshare.ars,otjm,"Medicine,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['24235 Bytes'],
+10.5061/dryad.n13hn,Data from: Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy,Dryad,2014,en,Dataset,Creative Commons Zero v1.0 Universal,"Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.",mds,True,findable,507,115,1,1,0,2014-07-08T17:34:21.000Z,2014-07-08T17:34:22.000Z,dryad.dryad,dryad,"alpine grasslands,hyperspectral data,reflectance","[{'subject': 'alpine grasslands'}, {'subject': 'hyperspectral data'}, {'subject': 'reflectance'}]",['197771 bytes'],
+10.5061/dryad.0p2ngf1w2,Electrical conductivity versus temperature in freezing conditions: a field experiment using a basket geothermal heat exchanger,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"In-situ experiment. Geothermal setup: Five heat exchangers (HE) are arranged in a line and are buried between 1.1 and 3.5 meters. Just two baskets worked: one (HE.5) for a correct functioning of the heat pump and the other (HE1) to freeze the ground. only, this last exchanger (HE1) has been monitored in temperature and electrical resistivity tomography. The basket HE.5 is too far away to have an influence during this experiment, the heat pump was started at 0 hour and worked during 518 hours. The temperature of ground was recorded every minutes, thanks to 41 probes (4 wire Pt100), divided into 7 vertical profils. theses profiles are located at 0, 3, 6, 7, 8, 11, 20, 21 meters (x-distance), and the used heat exchangers are at 7 meters for the HE.1 and at 24 meters for the HE.5, respectively. Electrical Resitivity Tomography (ERT): Before and during the running of the geothermal system, gephysical monitoring was carried out. At the end, nine tomography images were recorded using a SAS-1000 Terrameter (ABEM) associated with 64 electrodes arranged in straigth line (2D acquisition, with a spacing between electrodes of one meter). Apparent resisitivities were inverted with IP4DI software, incorporating spatial and time regularization --Laboratory experiments-- we sampled the soil around the exchanger using an auger. the soil consists of a mixture of clay, silts and some gravels. Two samples are selected in order to conduct some electrical measurement at different temperature. They were dried and then saturated with water from the aquifer (0.117 S/m at 27°C) and put in a thermo-regulated bath (KISS K6 from Huber). At each temperature level, a SIP spectrum was performed with ZSIP, from 0.01 hz to 45 khz.Temperature levels are 20, 15, 10, 5, 2, 0, -2, -4, -6, -8, -10, -14, -18°C. FIles--- Field. Temperature measurements and inverted resitivity: This file contains the temperature measurements and inverted resistivities from geophysical monitoring, presented in the article. Field. Comparaison conductivity vs temperature: This file corresponds to the data extracted from the temperature and inverted resistivity sections in order to attest the resistivity vs temperature relationship. - Laboratory. Comparaison conductivity vs temperature: This file contains the data of the phase and quadrature conductivity as a function of temperature for both samples measured in the laboratory by SIP method.",mds,True,findable,167,19,0,1,0,2019-12-09T15:34:04.000Z,2019-12-09T15:34:05.000Z,dryad.dryad,dryad,"Permafrost,soil freezing curve,electrical conductivity","[{'subject': 'Permafrost'}, {'subject': 'soil freezing curve'}, {'subject': 'electrical conductivity'}]",['283011 bytes'],
+10.5281/zenodo.3759301,"Sense Vocabulary Compression through the Semantic Knowledge of WordNet for Neural Word Sense Disambiguation - Model Weights - SC+WNGC, hypernyms, ensemble",Zenodo,2019,,Other,"Creative Commons Attribution 4.0 International,Open Access","This is the weights of the neural WSD model used in the article named ""Sense Vocabulary Compression through the Semantic Knowledge of WordNet for Neural Word Sense Disambiguation"" by Loïc Vial, Benjamin Lecouteux, Didier Schwab. This is an ensemble of 8 models trained separately on the SemCor+WNGC corpora and using the sense vocabulary compression through hypernyms described in the paper.",mds,True,findable,0,0,0,0,0,2020-04-21T13:49:32.000Z,2020-04-21T13:49:33.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7982056,"FIGURES C10–C15 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,Open Access,"FIGURES C10–C15. Leuctra signifera, adults (Julian Alps). C10, adult male (Italy), dorsal view; C11, adult male (Italy), dorsal view; C12, adult male (Slovenia), dorsal view; C13, adult male (Hungary), dorsal view; C14, adult female (Italy), dorsal view; C15, adult female (Italy), lateral view",mds,True,findable,0,0,0,3,0,2023-05-29T13:44:01.000Z,2023-05-29T13:44:02.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.4687049,VHF Radio Echo Sounding from Dome C to Little Dome C,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These are ice-penetrating radar data connecting the newly chosen Beyond EPICA Little Dome C core site to the EPICA Dome C core site, collected in late 2019. These data are presented in a paper in The Cryosphere (https://doi.org/10.5194/tc-2020-345), where full processing and collection methods are described. <strong>Data collection and processing</strong> Data were collected using a new very high frequency (VHF) radar, built by the Remote Sensing Center at the University of Alabama (Yan et al., 2020). The system transmitted 8 us chirps, with peak transmit power of 125--250 W per channel, at 200 MHz center frequency and 60 MHz bandwidth. There were 5--8 operational channels at various points. The antennas were pulled behind a tracked vehicle, with controlling electronics in the rear of the vehicle. Data were collected at travel speeds of 2--3.5 m/s. Data processing consisted of coherent integration (i.e. unfocused SAR), pulse compression, motion compensation (by tracking internal horizons), coherent channel combination, and de-speckling using a median filter. Two-way travel time was converted to depth assuming a correction of 10 m of firn-air and a constant radar wave speed of 168.5 m/us (e.g., Winter et al., 2017). After other processing was complete, different radargrams were spliced together to create a continuous profile extending from EPICA Dome C to the Beyond EPICA Little Dome C core site, and then the data were interpolated to have constant, 10-m horizontal spacing. The re-interpolated data were used for horizon tracing, which was done semi-automatically to follow amplitude peaks between user-defined clicks. For the bed reflection, we always picked the first notable return in the region of the bed. <strong>File description</strong> The file format is hdf5, which can be read with many programming languages. There are three groups in the file: processed_data, picks, and geographic_information. The processed_data gives the return power matrix (dB), and the depth (m) and two-way travel time (us) for the fast-time dimension. The picks give the depths (m) of different reflecting horizons traced in the corresponding paper. Ages and age uncertainties (kyr), interpolated from the AICC2012 timescale, are included as attributes on each pick. Bed and basal unit picks are included (ageless). The geographic_information gives latitude and longitude (decimal degrees), and the distance along-profile (km). <strong>References</strong> Bazin, L., Landais, A., Lemieux-Dudon, B., Toyé Mahamadou Kele, H., Veres, D., Parrenin, F., Martinerie, P., Ritz, C., Capron, E., Lipenkov, V., Loutre, M. F., Raynaud, D., Vinther, B., Svensson, A., Rasmussen, S. O., Severi, M., Blunier, T., Leuenberger, M., Fischer, H., Masson-Delmotte, V., Chappellaz, J., and Wolff, E.: An optimized multi-proxy, multi-site Antarctic ice and gas orbital chronology (AICC2012): 120-800 ka, 9, 1715–1731, https://doi.org/10.5194/cp-9-1715-2013, 2013. Winter, A., Steinhage, D., Arnold, E. J., Blankenship, D. D., Cavitte, M. G. P., Corr, H. F. J., Paden, J. D., Urbini, S., Young, D. A., and Eisen, O.: Comparison of measurements from different radio-echo sounding systems and synchronization with the ice core at Dome C, Antarctica, 11, 653–668, https://doi.org/10.5194/tc-11-653-2017, 2017. Yan, J.-B., Li, L., Nunn, J. A., Dahl-Jensen, D., O’Neill, C., Taylor, R. A., Simpson, C. D., Wattal, S., Steinhage, D., Gogineni, P., Miller, H., and Eisen, O.: Multiangle, Frequency, and Polarization Radar Measurement of Ice Sheets, 13, 2070–2080, https://doi.org/10.1109/JSTARS.2020.2991682, 2020.",mds,True,findable,0,0,1,0,0,2021-04-15T09:57:57.000Z,2021-04-15T09:57:58.000Z,cern.zenodo,cern,"ice-penetrating radar,Antarctica","[{'subject': 'ice-penetrating radar'}, {'subject': 'Antarctica'}]",,
+10.5281/zenodo.8052937,pwkit 1.2.0,Zenodo,2023,en,Software,"MIT License,Open Access",pwkit is a collection of astronomical utilities created by Peter Williams. Learn more at the pwkit website.,mds,True,findable,0,0,0,0,0,2023-06-18T21:36:30.000Z,2023-06-18T21:36:31.000Z,cern.zenodo,cern,"Astronomy,Python,Visualization","[{'subject': 'Astronomy'}, {'subject': 'Python'}, {'subject': 'Visualization'}]",,
+10.5281/zenodo.6827882,"ASTRI Mini-Array Instrument Response Functions (Prod2, v1.0)",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Aim:</strong> This data repository provides access to a set of Instrument Response Functions (IRFs) of the ASTRI Mini-Array, saved in a FITS data file. The IRFs can be used as input to science analysis tools for high-level scientific analysis purposes. <strong>Citations:</strong> In the case the present ASTRI Mini-Array Instrument Response Functions (IRFs) are used in a research project, we kindly ask to add the following acknowledgement in any resulting publication: ""This research has made use of the ASTRI Mini-Array Instrument Response Functions (IRFs) provided by the ASTRI Project [citation]."" Please use the following BibTex Entry for [citation] in the reference section of your publication: https://zenodo.org/record/6827882/export/hx <strong>Instrument:</strong> The ASTRI Mini-Array is an international project led by the Italian National Institute for Astrophysics (INAF) to build and operate an array of nine 4-m class Imaging Atmospheric Cherenkov Telescopes (IACTs) at the <em>Observatorio del Teide</em> (Tenerife, Spain) [1]. The telescopes are an evolution of the dual-mirror ASTRI-Horn telescope, successfully installed and tested since 2014 at the INAF “M.C. Fracastoro†observing station in Serra La Nave (Mt. Etna, Italy) [2][3]. The ASTRI Mini-Array is designed to perform deep observations of the galactic and extragalactic gamma-ray sky in the TeV and multi-TeV energy band, with a differential sensitivity that surpass the one of current Cherenkov telescope facilities above a few TeV, extending the energy band well above hundreds of TeV [4]. The main science goals of the ASTRI Mini-Array in the very high-energy (VHE) gamma-ray band encompass both galactic and extragalactic science [5][6][7]. Important synergies with other ground-based gamma-ray facilities in the Northern Hemisphere and space-borne telescopes are foreseen. <strong>Monte Carlo Simulations:</strong> The IRFs of the ASTRI Mini-Array were obtained from a dedicated Monte Carlo (MC) production (dubbed ASTRI Mini-Array Prod2, version 1.0). Air showers initiated by gamma rays, protons and electrons were simulated using the CORSIKA package [8] (version 6.99), while the response of the array telescopes was simulated using the sim_telarray package [9] (version 2018-11-07). The layout of the ASTRI Mini-Array telescopes considered in the MC simulations is based on the actual telescope positions at the Teide Observatory site (28.30°N, 16.51°W, 2390 m a.s.l.). The nominal telescope pointing configuration, in which all telescopes point to the same sky position, was assumed in all MC simulations. Air showers produced by the primaries were simulated as coming from a zenith angle of 20° and an azimuth angle of 0° and 180° (corresponding to telescope pointing directions toward the geomagnetic North and South, respectively). Although not-negligible differences in performance (on the order of ≤15% at a zenith angle of 20°) are found between the two azimuthal pointing directions, the final IRFs were obtained by averaging between the two directions. Finally, all MC simulations were generated with a night sky background (NSB) level corresponding to dark sky conditions at the Teide Observatory site. <strong>Monte Carlo data reduction and analysis:</strong> The MC simulations were reduced and analysed with A-SciSoft [10][11] (version 0.3.1), the scientific software package of the ASTRI Project. The calibration and reconstruction of the MC events were achieved with the standard methods implemented in the data reduction pipeline (see [10][11] for more details). In particular, the background rejection and energy reconstruction were achieved with a procedure based on the Random Forest method [12], while the arrival direction of each shower was estimated from a weighted intersection of the major axes of the images from different telescopes. After the full reconstruction of the MC events, the background (proton and electron) events were re-weighted according to recent experimental measurements of their spectra, while gamma-ray events with a power-law gamma-ray spectrum with a photon index of 2.62. This approach follows a similar procedure adopted in [13]. The final analysis cuts were based on the background rejection, shower arrival direction, and event multiplicity parameters. They were defined, in each considered energy bin and off-axis bin, by optimising the flux sensitivity for 50 hr exposure time. Then, five standard deviations (5σ, with σ defined as in Eq. 17 of [14]) were required for a detection in each energy bin and off-axis bin, considering the same exposure time (as in the cut optimization procedure) and a ratio of the off-source to on-source exposure equal to 5. In addition, the signal excess was required to be larger than 10 and at least 5 times the expected systematic uncertainty in the background estimation (assumed to be ∼1%). It should be noted that these analysis cuts, based on the best flux sensitivity, do not provide the best angular and energy resolution achievable by the system. Other analysis cuts, which take into account both differential flux sensitivity and angular/energy resolution in the cut optimization process, may actually provide better performance [4]. <strong>Instrument Response Functions (IRFs):</strong> The IRFs are saved in a FITS data file [15] which contains the following quantities (FITS tables): effective collection area (""EFFECTIVE AREA"" table), angular resolution (""POINT SPREAD FUNCTION"" table), energy resolution (""ENERGY DISPERSION"" table), and residual background rate (""BACKGROUND"" table). These quantities are provided as a function of the energy and the off-axis. The energy bins are logarithmic and range between 10<sup>-0.7 </sup>~ 0.2 TeV and 10<sup>2.5 </sup>~ 316 TeV. Five energy bins per decade are used for the angular resolution and residual background rate, while ten energy bins per decade for the effective collection area. In the case of energy resolution, the energy migration matrix is provided with a much finer energy binning. The off-axis bins are linearly spaced between 0° and 6°, with a bin width equal to 1°. In the case of the residual background rate, a 2-dimensional squared spatial binning is used, which ranges between 0° and 6° with a bin width equal to 0.2° in each direction. The IRFs can be used as input to science analysis tools and, in particular, are compliant with the input/output (I/O) data format requested by the science analysis tools Gammapy [16] and ctools [17]. <strong>Dataset:</strong> The dataset consists of one file: ""astri_100_43_008_0502_C0_20_AVERAGE_50h_SC_v1.0.lv3.fits"". The naming convention is: astri_[ARRAY_ID]_[ORIG_ID]_[REL_ID]_[PACKET_TYPE]_[CLASS_CUT]_[ZENITH]_[AZIMUTH]_[ EXPOSURE_TIME]_[AIM]_[VERSION].lv3.fits where: [ARRAY_ID] = 100 (100 = ASTRI Mini-Array with 9 telescopes) [ORIG_ID] = 43 (4 = INAF-OAR; 3 = AIV/AIT MC simulations) [REL_ID] = 008 (008 = MC prod2, v1.0) [PACKET_TYPE] = 0502 (0502 = IRF3) [CLASS_CUT] = C0 (C0 = cuts based on sensitivity maximisation) [ZENITH] = 20 [deg] [AZIMUTH] = AVERAGE [deg] [EXPOSURE_TIME] = 50h [AIM] = SC (SC = SCience) [VERSION]= v1.0 <strong>Acknowledgments:</strong> This work was conducted in the context of the ASTRI Project thanks to the support of the Italian Ministry of University and Research (MUR) as well as the Ministry for Economic Development (MISE) with funds specifically assigned to the Italian National Institute of Astrophysics (INAF). We acknowledge support from the Brazilian Funding Agency FAPESP (Grant 2013/10559-5) and from the South African Department of Science and Technology through Funding Agreement 0227/2014 for the South African Gamma-Ray Astronomy Programme. The Instituto de Astrofisica de Canarias (IAC) is supported by the Spanish Ministry of Science and Innovation (MICIU). This work has also been partially supported by H2020-ASTERICS, a project funded by the European Commission Framework Programme Horizon 2020 Research and Innovation action under grant agreement n. 653477. This work has gone through the internal ASTRI review process. We would also like to thank the computing centres that provided resources for the generation of the Monte Carlo (MC) simulations used to produce the ASTRI Mini-Array Instrument Response Functions (IRFs) released in this work: CAMK, Nicolaus Copernicus Astronomical Center, Warsaw, Poland CIEMAT-LCG2, CIEMAT, Madrid, Spain CYFRONET-LCG2, ACC CYFRONET AGH, Cracow, Poland DESY-ZN, Deutsches Elektronen-Synchrotron, Standort Zeuthen, Germany GRIF, Grille de Recherche d’Ile de France, Paris, France IN2P3-CC, Centre de Calcul de l’IN2P3, Villeurbanne, France IN2P3-CPPM, Centre de Physique des Particules de Marseille, Marseille, France IN2P3-LAPP, Laboratoire d'Annecy de Physique des Particules, Annecy, France INFN-FRASCATI, INFN Frascati, Frascati, Italy INFN-T1, CNAF INFN, Bologna, Italy INFN-TORINO, INFN Torino, Torino, Italy MPIK, Heidelberg, Germany OBSPM, Observatoire de Paris Meudon, Paris, France PIC, port d’informacio cientifica, Bellaterra, Spain prague_cesnet_lcg2, CESNET, Prague, Czech Republic praguelcg2, FZU Prague, Prague, Czech Republic UKI-NORTHGRID-LANCS-HEP, Lancaster University, United Kingdom <strong>References:</strong> Scuderi, S. et al., ""The ASTRI Mini-Array of Cherenkov telescopes at the Observatorio del Teide"", Journal of High Energy Astrophysics 35, 52–68 (2022). Giro, E. et al., ""First optical validation of a Schwarzschild Couder telescope: the ASTRI SST-2M Cherenkov telescope"", A&A 608, A86 (Sept. 2017). Lombardi, S. et al., ""First detection of the Crab Nebula at TeV energies with a Cherenkov telescope in a dual-mirror Schwarzschild-Couder configuration: the ASTRI-Horn telescope"", A&A 634, A22 (Feb. 2020). Lombardi, S. et al., ""Performance of the ASTRI Mini-Array at the Observatorio del Teide"", in [37th International Cosmic Ray Conference. 12-23 July 2021. Berlin], 884 (Mar. 2022). Vercellone, S. et al., ""ASTRI Mini-Array core science at the Observatorio del Teide"", Journal of High Energy Astrophysics 35, 1–42 (2022). D’Aì, A. et al., ""Galactic Observatory Science with the ASTRI Mini-Array at the Observatorio del Teide"", Journal of High Energy Astrophysics 35, 139–175 (2022). Saturni, F. et al., ""Extragalactic Observatory Science with the ASTRI Mini-Array at the Observatorio del Teide"", Journal of High Energy Astrophysics 35, 91–111 (2022). Heck, D. et al., [CORSIKA: a Monte Carlo code to simulate extensive air showers.], Report FZKA 6019 (1998). Bernlöhr, K., ""Simulation of imaging atmospheric Cherenkov telescopes with CORSIKA and sim_telarray"", Astropart. Phys. 30, 149–158 (Oct. 2008). Lombardi, S. et al., ""ASTRI SST-2M prototype and mini-array data reconstruction and scientific analysis software in the framework of the Cherenkov Telescope Array"", in [Software and Cyberinfrastructure for Astronomy IV], Chiozzi, G. and Guzman, J. C., eds., Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series 9913, 991315 (July 2016). Lombardi, S. et al., ""ASTRI data reduction software in the framework of the Cherenkov Telescope Array"", in [Software and Cyberinfrastructure for Astronomy V], Guzman, J. C. and Ibsen, J., eds., Society of Photo- Optical Instrumentation Engineers (SPIE) Conference Series 10707, 107070R (July 2018). Breiman, L., ""Random Forests"", Machine Learning 45, 5–32 (Jan. 2001). Cherenkov Telescope Array Observatory, & Cherenkov Telescope Array Consortium. (2021). CTAO Instrument Response Functions - prod5 version v0.1 (v0.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5499840 Li, T.-P. and Ma, Y.-Q., ""Analysis methods for results in gamma-ray astronomy"", ApJ, 272, 317 (1983) Pence, W. D. et al., ""Definition of the Flexible Image Transport System (FITS), version 3.0"", A&A 524, A42 (Dec. 2010). Deil, C. et al., ""Gammapy - A prototype for the CTA science tools"", in [35th International Cosmic Ray Conference (ICRC2017)], International Cosmic Ray Conference 301, 766 (Jan. 2017). Knödlseder, J. et al., ""GammaLib and ctools. A software framework for the analysis of astronomical gamma- ray data"", A&A 593, A1 (Aug. 2016).",mds,True,findable,0,0,0,0,0,2022-07-13T16:42:00.000Z,2022-07-13T16:42:01.000Z,cern.zenodo,cern,"ASTRI Mini-Array,Cherenkov telescopes,gamma-ray astronomy,high-level science-ready products,scientific analysis","[{'subject': 'ASTRI Mini-Array'}, {'subject': 'Cherenkov telescopes'}, {'subject': 'gamma-ray astronomy'}, {'subject': 'high-level science-ready products'}, {'subject': 'scientific analysis'}]",,
+10.5281/zenodo.5243264,Norwegian DBnary archive in original Lemon format,Zenodo,2021,no,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Norwegian language edition, ranging from 6th February 2015 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T10:53:45.000Z,2021-08-24T10:53:46.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.2641868,X-ray diffraction images for Thiazole synthase from M. thermolithotrophicus.,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Anomalous data collected at ESRF (Grenoble, France) using beamline ID23-1. The crystal (Crystal form 3) was in the presence of the crystallophore Tb-Xo4.
+
+
+
+Related Publication: Engilberge et al. (2019)",mds,True,findable,0,0,0,0,0,2019-04-16T10:25:32.000Z,2019-04-16T10:25:33.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.c.6900580,Bacterial survival in radiopharmaceutical solutions: a critical impact on current practices,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background The aim of this brief communication is to highlight the potential bacteriological risk linked to the processes control of radiopharmaceutical preparations made in a radiopharmacy laboratory. Survival rate of Pseudomonas aeruginosa (ATCC: 27853) or Staphylococcus aureus (ATCC: 25923) or Staphylococcus epidermidis (ATCC: 1228) in multidose technetium-99 m solution was studied. Results Depending on the nature and level of contamination by pathogenic bacteria, the lethal effect of radioactivity is not systematically observed. We found that P. aeruginosa was indeed affected by radioactivity. However, this was not the case for S. epidermidis, as the quantity of bacteria found in both solutions (radioactive and non-radioactive) was rapidly reduced, probably due to a lack of nutrients. Finally, the example of S. aureus is an intermediate case where we observed that high radioactivity affected the bacteria, as did the absence of nutrients in the reaction medium. The results were discussed in the light of current practices on the sterility test method, which recommends waiting for radioactivity to decay before carrying out the sterility test. Conclusion In terms of patient safety, the results run counter to current practice and the latest EANM recommendation of 2021 that radiopharmaceutical preparations should be decayed before sterility testing.",mds,True,findable,0,0,0,0,0,2023-10-27T03:41:27.000Z,2023-10-27T03:41:28.000Z,figshare.ars,otjm,"Biophysics,Microbiology,FOS: Biological sciences,Environmental Sciences not elsewhere classified,Science Policy,Infectious Diseases,FOS: Health sciences","[{'subject': 'Biophysics'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Environmental Sciences not elsewhere classified'}, {'subject': 'Science Policy'}, {'subject': 'Infectious Diseases'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5061/dryad.6226d,"Data from: Tempo and mode of genome evolution in a 50,000-generation experiment",Dryad,2017,en,Dataset,Creative Commons Zero v1.0 Universal,"Adaptation by natural selection depends on the rates, effects and interactions of many mutations, making it difficult to determine what proportion of mutations in an evolving lineage are beneficial. Here we analysed 264 complete genomes from 12 Escherichia coli populations to characterize their dynamics over 50,000 generations. The populations that retained the ancestral mutation rate support a model in which most fixed mutations are beneficial, the fraction of beneficial mutations declines as fitness rises, and neutral mutations accumulate at a constant rate. We also compared these populations to mutation-accumulation lines evolved under a bottlenecking regime that minimizes selection. Nonsynonymous mutations, intergenic mutations, insertions and deletions are overrepresented in the long-term populations, further supporting the inference that most mutations that reached high frequency were favoured by selection. These results illuminate the shifting balance of forces that govern genome evolution in populations adapting to a new environment.",mds,True,findable,1529,297,1,1,0,2016-06-16T16:29:13.000Z,2016-06-16T16:29:20.000Z,dryad.dryad,dryad,"Microbiology,FOS: Biological sciences","[{'subject': 'Microbiology', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['27771696 bytes'],
+10.5281/zenodo.4314872,"Amory et al. (2021), Geoscientific Model Development : data, model outputs and source code",Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Data and model outputs for the replication of the analysis made in:</strong><br> (see the published version of this article in Geoscientific Model Development, 2021 - please cite this version if you use these data)<br> C. Amory, C. Kittel, L. Le Toumelin, C. Agosta, A. Delhasse, V. Favier, and X. Fettweis: Performance of MAR (v3.11) in simulating the drifting-snow climate and surface mass balance of Adelie Land, East Antarctica, Geoscientific Model Development, accepted, 2021. See README.txt for a full description of the dataset content Please contact me at amory.charles@live.fr if you need other half-hourly outputs or for more details on the dataset",mds,True,findable,0,0,0,0,0,2020-12-10T14:32:28.000Z,2020-12-10T14:32:29.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23822166.v1,Dataset key for the replication experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,Key for the dataset for the replication experiment,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:30.000Z,2023-08-02T11:18:30.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['1002 Bytes'],
+10.5281/zenodo.56682,Ncomm-Goldnp-2016: Release 3.0,Zenodo,2016,,Dataset,"Creative Commons Attribution 4.0,Open Access",Supporting x-ray scattering data for Nature Communications Article on Polymorphism in Gold 144 clusters (DOI: 10.1038/ncomms11859),,True,findable,0,0,1,0,0,2016-06-29T16:40:36.000Z,2016-06-29T16:40:37.000Z,cern.zenodo,cern,"pair distribution function,gold cluster,nanoparticle,x-ray diffraction,polymorphism","[{'subject': 'pair distribution function'}, {'subject': 'gold cluster'}, {'subject': 'nanoparticle'}, {'subject': 'x-ray diffraction'}, {'subject': 'polymorphism'}]",,
+10.34616/wse.2019.13.61.80,"Anti-Unism in a landscape of Unism : a revival of Avant-Garde in Dong Yue's work ""The Looming Storm""","Wydział Prawa, Administracji i Ekonomii Uniwersytetu Wrocławskiego",2019,,JournalArticle,,,fabricaForm,True,findable,0,0,0,0,0,2021-09-20T11:37:56.000Z,2021-09-20T12:08:39.000Z,psnc.uwr,dxmj,,,,
+10.5281/zenodo.6913393,Evidence of dual Shapiro steps in a Josephson junction array,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","QCodes type databases containing raw data associated with the paper ""Evidence of dual Shapiro steps in a Josephson junctions array"" by N. Crescini, S. Cailleaux et al. acquired in the Institut Neel, CNRS, Grenoble, France between January 2022 and June 2022. There are two databases: one contains the characterization of the sample without microwave pump and the other one contains the study of the sample under microwave irradiation. Two Jupyter notebooks (python 3.8.11) are provided to analyze the datasets contained in the databases and reproduce the results of the article. For any additional information please contact: nicolo.crescini@neel.cnrs.fr or samuel.cailleaux@neel.cnrs.fr",mds,True,findable,0,0,0,1,0,2022-07-27T12:45:12.000Z,2022-07-27T12:45:13.000Z,cern.zenodo,cern,"Josephson junction,Superconductivity,Circuit QED,Metrology,Quantum physics","[{'subject': 'Josephson junction'}, {'subject': 'Superconductivity'}, {'subject': 'Circuit QED'}, {'subject': 'Metrology'}, {'subject': 'Quantum physics'}]",,
+10.5281/zenodo.4715737,Research data: preparation of nanocellulose using non-aligned hemp bast fibers,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","The data files and archives contain experimental results and Optical, FESEM, and TEM micrographs of hemp fibers, raw and pretreated, and of the nanocellulose obtained from them. The files are named following this convention: Hemp_A_B.ext where A is the type of material: PT = fibers after all pretreatment steps PT(xx) = fibers after the pretreatment step indicated in the parenthesis PT_NC = fibers after all pretreatment steps and nanocellulose NC = nanocellulose and B is the type of measurement done: TEM = Transmission Electron Microscope FESEM = Field Emission Scanning Electron Microscope Dimensions = lengths and diameters of the fibers, as analyzed from the Optical, FESEM, and TEM micrographs with the software ImageJ XRD_bkgsub = X-ray diffraction measurements, with background subtracted FTIR = Fourier Transform Infrared Spectroscopy (in ATR mode) TGA = Thermogravimetric analysis The data will be made open as soon as possible depending on the publishing process of the article",mds,True,findable,0,0,0,0,0,2021-04-23T15:45:27.000Z,2021-04-23T15:45:28.000Z,cern.zenodo,cern,"Hemp,Nanocellulose","[{'subject': 'Hemp'}, {'subject': 'Nanocellulose'}]",,
+10.5281/zenodo.5913981,artefact for ESOP2022 paper The Trusted Computing Base of the CompCert Verified Compiler.,Zenodo,2022,en,Software,Open Access,Coq source code demonstrating the examples in our ESOP 2022 paper <em>The Trusted Computing Base of the CompCert Verified Compiler</em>. Comes with a Docker container with a complete Coq installation.,mds,True,findable,0,0,0,0,0,2022-01-28T14:02:09.000Z,2022-01-28T14:02:10.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3583364,Data for Helical quantum Hall phase in graphene on SrTiO3,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Data plots in spreadsheet form,mds,True,findable,1,0,0,0,0,2020-01-31T10:19:41.000Z,2020-01-31T10:19:42.000Z,cern.zenodo,cern,,,,
+10.13127/efsm20,European Fault-Source Model 2020 (EFSM20): online data on fault geometry and activity parameters,Istituto Nazionale di Geofisica e Vulcanologia (INGV),2022,en,Dataset,CC BY 4.0,"The European Fault-Source Model 2020 (EFSM20) was initially compiled in the framework of the EU Project SERA, Work Package 25, JRA3. EFSM20 includes only faults deemed capable of generating earthquakes of magnitude equal to or larger than 5.5 and aims at ensuring a harmonized input for use in ground-shaking hazard assessment in the Euro-Mediterranean area, namely the European Seismic Hazard Model 2020 (ESHM20). The EFSM20 database is hosted, maintained, and distributed by INGV through the EDSF installation (https://seismofaults.eu/) operated under the auspices of the EPOS-ERIC, TCS EPOS-Seismology, EFEHR Consortium, and the EPOS-MIUR Joint Research Unit.",api,True,findable,0,0,0,0,0,2022-10-30T16:28:46.000Z,2022-10-30T16:28:46.000Z,crui.ingv,wngn,"model of seismogenic faults,Europe,earthquakes,magnitude,slip rate,crustal fault sources,subduction fault sources,hazard model,Earth Sciences and Geology,QE - Geology,551 Geology, hydrology, meteorology,554 Earth sciences of Europe,555 Earth sciences of Asia,556 Earth sciences of Africa","[{'subject': 'model of seismogenic faults'}, {'subject': 'Europe'}, {'subject': 'earthquakes'}, {'subject': 'magnitude'}, {'subject': 'slip rate'}, {'subject': 'crustal fault sources'}, {'subject': 'subduction fault sources'}, {'subject': 'hazard model'}, {'subject': 'Earth Sciences and Geology'}, {'subject': 'QE - Geology', 'subjectScheme': 'LCC'}, {'subject': '551 Geology, hydrology, meteorology', 'subjectScheme': 'DDC'}, {'subject': '554 Earth sciences of Europe', 'subjectScheme': 'DDC'}, {'subject': '555 Earth sciences of Asia', 'subjectScheme': 'DDC'}, {'subject': '556 Earth sciences of Africa', 'subjectScheme': 'DDC'}]","['1248 crustal faults', '4 subduction systems']","['application/vnd.geo+json', 'application/vnd.mif', 'application/x-zipped-shp']"
+10.5281/zenodo.7006744,"Simulation outputs associated to the study: ""Brief communication: Everest South Col Glacier did not thin during the last three decades"" by Brun et al.",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This folder contains the outputs of the South Col Glacier mass balance simulations used in the study: ""Brief communication: Everest South Col Glacier did not thin during the last three decades"" by Brun et al., submitted to The Cryophere Journal in August 2022. The simulation outputs are obtained with two different models: COSIPY (Sauter et al., 2010) and Crocus (Vionnet et al., 2012). Note that forcing and initialization information are provided to reproduce Crocus simulations.",mds,True,findable,0,0,0,0,0,2022-08-18T09:29:42.000Z,2022-08-18T09:29:42.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5744873,"High-resolution spatialization for estimation of precipitation in the Cordillera Blanca, Peru",Zenodo,2021,en,Image,"Creative Commons Attribution 4.0 International,Open Access","Supplementary materials for the article ""High-resolution spatialization for estimation of precipitation in the Cordillera Blanca, Peru""",mds,True,findable,0,0,0,0,0,2021-11-30T15:53:00.000Z,2021-11-30T15:53:01.000Z,cern.zenodo,cern,"Precipitation, regression model, cordillera Blanca, RMSE","[{'subject': 'Precipitation, regression model, cordillera Blanca, RMSE'}]",,
+10.5281/zenodo.3725791,Dataset - Learning to Measure Static Friction Coefficient in Cloth Contact,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Dataset for: Learning to Measure the Static Friction Coefficient in Cloth Contact,mds,True,findable,0,0,1,0,0,2020-03-28T15:08:16.000Z,2020-03-28T15:08:16.000Z,cern.zenodo,cern,"Machine Learning,Friction Estimation","[{'subject': 'Machine Learning'}, {'subject': 'Friction Estimation'}]",,
+10.5281/zenodo.7372398,"Video recordings of ""Modular Tangible User Interfaces: Impact of Module Shape and Bonding Strength on Interaction""",Zenodo,2022,,Audiovisual,Restricted Access,"We provide the video data recorded during the experiment presented in the publication https://doi.org/10.1145/3569009.3572731. We conducted the first study on how the bonding strength and the shape of modules impact usability during user interaction with modular tangible user interfaces (TUIs). We built six magnetic modular prototypes featuring 6x6x6mm modules with three different levels of bonding strength (low, mid, high) and two different shapes (cubes and rounded cubes). We asked participants to perform eight common tasks found in the HCI literature for (non-)modular TUIs, which are presented in section 3.3 from the publication: Lift Split one module Split two modules Split a line of modules Split half of the modules Slide parts of the interface Bend the interface Fold the interface <br> Participants performed the manipulations on two types of configuration of modules: a flat configuration (i.e., one layer of 80 modules) or a thick configuration (i.e., two layers on 40 modules each). The video data we provide consists of recordings of the hands of the participants when they perform the tasks with each condition of prototype. The video data we provide consists of recordings of the hands of the participants when they perform the tasks with each condition of prototype. The procedure presented in the video recordings is as follow:<br> <br> The participant sits in front of a table with a delimited manipulation area, with an overhead camera pointing towards the manipulation area. Participants are asked to perform the experiment within the borders of the manipulation area.<br> The experimental software (not shown in the recordings, but in the publication) presents the participants with a picture of a starting State A (e.g., a rectangular block) and a target State B (e.g., the rectangular block split in two halves). Reaching state B only requires the use of one elementary manipulation. There is no indication as to how the UI was grabbed to reach State B, to avoid bias. The experimenter places the first prototype on the manipulation area, mimicking State A. The participant manipulates the prototype to reach State B. The task is repeated three times to allow exploring different strategies. After completion of the task, the participant fills a short questionnaire, which is when a mobile tablet is shown in the recordings. They are then presented with the next task to perform (i.e., new State A and B pictures) while the experimenter presents the next prototype. This procedure is repeated for each manipulation and each condition.",mds,True,findable,0,0,0,0,0,2022-11-29T17:05:23.000Z,2022-11-29T17:05:23.000Z,cern.zenodo,cern,"Tangible User Interfaces,Tangible interaction,Modular user interfaces,Bonding strength,Shape,Detachability,Solidity,Human-Computer Interaction","[{'subject': 'Tangible User Interfaces'}, {'subject': 'Tangible interaction'}, {'subject': 'Modular user interfaces'}, {'subject': 'Bonding strength'}, {'subject': 'Shape'}, {'subject': 'Detachability'}, {'subject': 'Solidity'}, {'subject': 'Human-Computer Interaction'}]",,
+10.5281/zenodo.5237214,Modern Greek DBnary archive in original Lemon format,Zenodo,2021,el,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Modern Greek language edition, ranging from 12th June 2013 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-23T18:56:41.000Z,2021-08-23T18:56:42.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.8329497,Source data figures Diverse Slip behaviour on Velocity-Weakening fault segments,Zenodo,2023,,Dataset,"Creative Commons Attribution 1.0 Generic,Open Access","txt data files for figures 3, 4 and 5 displayed on manuscript Diverse Slip behaviour on Velocity-Weakening fault segments",mds,True,findable,0,0,0,0,0,2023-09-08T17:26:19.000Z,2023-09-08T17:26:19.000Z,cern.zenodo,cern,Data source files,[{'subject': 'Data source files'}],,
+10.5281/zenodo.12381,XMI-MSIM 5.0,Zenodo,2014,,Software,"GNU General Public License v3.0 only,Open Access","XMI-MSIM is an open source tool designed for predicting the spectral response of energy-dispersive X-ray fluorescence spectrometers using Monte-Carlo simulations. It comes with a fully functional graphical user interface in order to make it as user friendly as possible. Considerable effort has been taken to ensure easy installation on all major platforms. Development of this package was part of my PhD thesis. The algorithms were inspired by the work of my promotor Prof. Laszlo Vincze of Ghent University. Links to his and my own publications can be found in our manual. A manuscript has been published in Spectrochimica Acta Part B that covers the algorithms that power XMI-MSIM. Please include a reference to this publication in your own work if you decide to use XMI-MSIM for academic purposes. A second manuscript was published that covers our XMI-MSIM based quantification plug-in for PyMca. Soon information on using this plug-in will be added to the manual. XMI-MSIM is released under the terms of the GPLv3. Development occurs at Github: http://github.com/tschoonj/xmimsim<br> Downloads are hosted by the X-ray Micro-spectroscopy and Imaging research group of Ghent University: http://lvserver.ugent.be/xmi-msim Version 5.0 release notes: Changes: Custom detector response function: build a own plug-in containing your own detector response function and load it at run-time to override the builtin routines. Instructions can be found in the manual. Escape peak improvements: new algorithm is used to calculate the escape peak ratios based on a combined brute-force and variance-reduction approach. Ensures high accuracy even at high incoming photon energies and thin detector crystals. Downside: it's slower… Removed maximum convolution energy option. Was a bit confusing anyway. Number of channels: moved from simulation controls into input-file Radionuclide support added: Now you can select one or more commonly used radionuclide sources from the X-ray sources widget. Advanced Compton scattering simulation: a new alternative implementation of the Compton scattering has been implemented based on the work of Fernandez and Scot (http://dx.doi.org/10.1016/j.nimb.2007.04.203), which takes into account unpopulated atomic orbitals. Provides an improved simulation of the Compton profile, as well as fluorescence contributions due to Compton effect (extremely low!), but slows the code down considerably. Advanced users only. Default: OFF Plot spectra before convolution in results Windows: new Inno Setup installers. Contains the headers and import libraries Windows: compilers changed to GCC 4.8.1 (TDM-GCC) Windows: rand_s used to generate seeds on 64-bit version (requires Vista or later) Windows: new gtk runtime for the 64-bit version (see also https://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer) Mac OS X: compilers changed to clang 5.1 (Xcode) and gfortran 4.9.1 (MacPorts) Original input-files from our 2012 publication (http://dx.doi.org/10.1016/j.sab.2012.03.011) added to examples Updater performs checksum verification after download X-ray sources last used values stored in preferences.ini xmimsimdata.h5 modified: even bigger now... Bugfixes: Windows: support for usernames with unicode characters. Fixed using customized builds of HDF5. Thanks to Takashi Omori of Techno-X for the report! Spectrum import from file fixes. Was never properly tested apparently Note:<br> For those that compiled XMI-MSIM from source: you will need to regenerate the xmimsimdata.h5 file with xmimsim-db. Old versions of this file will not work with XMI-MSIM 5.0.",mds,True,findable,0,0,2,0,0,2014-10-24T09:46:55.000Z,2014-10-24T09:46:57.000Z,cern.zenodo,cern,"X-ray fluorescence,Monte Carlo simulation,M-line,Cascade effect,Pulse pile-up","[{'subject': 'X-ray fluorescence'}, {'subject': 'Monte Carlo simulation'}, {'subject': 'M-line'}, {'subject': 'Cascade effect'}, {'subject': 'Pulse pile-up'}]",,
+10.5281/zenodo.7763080,URPEACE - Grenoble,Zenodo,2023,fr,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This study aims to contribute to knowledge about the peace-building agency of civilian actors in marginalized social-housing neighborhoods, who deal with the consequences of terrorist violence in European cities. The bulk of peace and conflict studies literature has provided insight in the dynamics of violence rather than peace. The innovative character of this study therefore is that it interprets existing and new data on dealing with violence with a novel approach, that of geographies of peace. This innovative approach breaks with the tendency of peace and conflict studies to focus on the Global South, state processes and armed conflict and makes it very relevant for studying initiatives in European cities that deal with the aftermaths of paroxysmal violence. The study draws on data collected in three different cities: Grenoble, Basel/Freiburg and Brcko. This dataset concerns the data that has been collected in Grenoble. URPEACE worked in Grenoble with existing data collected by the researcher during long-term research (2015-2018) carried Claske Dijkema for her PhD. (https://theses.hal.science/tel-03420654/file/DIJKEMA_2021_archivage.pdf) Data was originally collected with the aim to rethink the stigmatization of marginalized social housing neighborhoods (MSHN) in France and to make alternative realities visible that have so far remained under the radar of social science research. Its focus is in particular on neighborhood youth and Muslim women. A lot of data has been collected throughout my long-term ethnographic and participatory field research that have not been previously explored. In the context of paroxysmal violence (urban, terrorist and youth violence) in the neighborhood, the issue of peace and how it can be built were recurrent themes that have not been the focus of my PhD manuscript. The method of data collection has been developed in order to deal with the methodological challenge that power asymmetry between the researcher and research particpants constitutes for qualitative research. The latter heavily relies on speech. However, using speech as a method with people whose voices are silenced, poses a methodological challenge. In a context of subalternization, territorial stigmatization and urban violence in marginalized social-housing neighborhoods, the developed method contributes to creating spaces of speech. A space of speech refers to a space in which speech becomes possible because it is configured in such a way that power dynamics are mitigated. In the context of this study there are 4 different spaces of speech Meetings Street debates (see document ""More info street debates"") Discussion circles/workshops/focus groups Public debates In this space a public comes together and exchanges with each other about a specific theme. It belongs to the public sphere and is publicly accessible; it may form in public space but is more often a space that is closed by walls and a door as this closure offers a form of protection and separates the space from the street. This method can be considered as a specific form of participatory action-research with different local initiatives in two marginalized social-housing neighborhoods in Grenoble (Villeneuve and Echirolles) in a context of post-violence. These local initiatives are (among others): Université Populaire de Villeneuve Agir pour la Paix Nous Citoyennes Marche Blanche Creating spaces of speech and public debates as a research method has allowed the co-production of the following primary data: field notes, and in the case of the plenary debates of the Université populaire video and audio recordings in addition to field notes. Table 1 lists which spaces of speech produced which kind of data. <strong>Table 1 The data produced in different spaces of speech</strong> <strong>Space of Speech</strong> <strong>Number</strong> <strong>Data</strong> <strong>Meetings</strong> UP meetings 2017 6 Audio recording, transcripts Other working groups 30 Written field notes, notebook <strong>Workshops</strong> Discussion circles UP 2 Video and audio recording, transcripts Workshops APLP 6 Field notes Workshops Marchons 4 Field notes, partly audio-recorded but not transcribed Workshops UP 1 Field Notes <strong>Street debates</strong> UP 5 Field notes, summary document APLP 2 Field notes Villeneuve Debout 1 Field notes <strong>Plenary debates</strong> UP 16 Audio and video recordings, pictures, Field notes, proceedings Other 25 Field notes <br> <strong>Types and formats of data </strong> <em>The existing dataset (retrospective) exists of: </em> Ethnographic observations and informal discussions (field notes) Transcripts of public debates (10) Zines published after public debates (7) Flyers of public debates Documents by local actors Transcripts of 20 interviews (audio-recorded) Videos produced by the Université Populaire (6) <br> <strong>Field notes</strong> The collected field notes fit into two categories: 1) notes written in a notebook during working group meetings and debates, which were a combination of logistical organization, the stories I heard and my own observations; 2) notes written on the computer once I returned to my desk (at home or at the University) after meetings or debates, or other spaces of speech. They are both descriptive and reflective. Field notes are separated in different documents: 10 written workbooks and word documents organized per year (2013-2019). <em><strong>The field notes have been written for personal use and are closed for access.</strong></em> <strong>List of plenary debates</strong> The table below provides a list of all the plenary debates I have been involved as co-organizer. The list provides information about the title of the debate, where they took place (PLACE) and how many people participated (PART.). Five categories indicate the number of people present at each debate: 1) 5-25; 2) 25 – 50; 3) 50 -75; 4) 75 – 100; 5) + 100. <em><strong>The last column indicates the documents that are accessible in this repository (x= available; - = accessible upon request).</strong></em> <strong>Table 2 Overview of plenary debates</strong> <strong>2013</strong> <strong>PLENARY DEBATES</strong> <strong>PLACE</strong> <strong>PART.</strong> 16-févr Villeneuve Debout - Repas Citoyen ""Violence dans le quartier, parlons-en!"" La Cordée, Villeneuve 3 x 14-nov Villeneuve - Décryptage public de Envoyé spécial Salle 150, Villeneuve 3 x <strong>2014</strong> <strong>PLENARY DEBATES</strong> <strong>PLACE</strong> 17-juin Marche Blanche and Villeneuve Debout- “Comprende et agir sur la violence, soirée hommage à Kevin et Sofiane†Musée de Grenoble 5 x 02-oct Marche Blanche – International Day of Nonviolence Lycée Marie Curie Echirolles 5 x <strong>2015</strong> <strong>PLENARY DEBATES</strong> <strong>PLACE</strong> 20-mars UP Cycle I “Pour comprendre les discriminations, l'islamophobie etc†<strong>– UP Cahier 1</strong> Salle Polyvalente des Baladins 4 x 11-mai MJC Roseaux - Latifa Ibn Ziaten - Jessy Cormont Maison de Quartier Aragon 3 - 31-mai Fringale/FUIQP – “Quartiers populaires et luttes contre l’islamophobie, la lutte des femmes – Rencontre avec Ismahane Chouder†MJC l’Abbaye 3 x 02-juil MJC Roseaux - Réunion public après la mort de Luc Pouvin Maison de Quartier Aragon 4 - 21-sept UP Cycle I “Pour comprendre - histoire d'immigré†Salle Polyvalente des Baladins 2 - 02-oct 2 October collective – Debate at high school with activists involved in MSHN struggles using non-violent methods College Henri Vallon 5 x 02-oct 2 October collective – Debate with APLP “Comment faire société au-delà de nos différences?†Alpexpo 2 x 02-oct 2 October collective – Debate “Quelle mobilisation collective pouvons-nous mettre en place pour répondre de façon nonviolente aux violences?†Alpexpo 3 - 02-oct 2 October collective – International Day of Nonviolence<br> <strong>- Magazine: Marchons 2015</strong> Summum 5+ x 24-oct MJC les Roseaux – “Journée tous ensemble contre les violences†L’Heure Bleue, Saint Martin d’Hères 5 x 28-oct Fringale/FUIQP Projection débat ""Qui a tué Ali Ziri"" Cinéma le Club, centre-ville 5 - 20-nov UP Cycle I “Pour Comprendre les ZEP, ZUP, ZUS, ZSP - Said Bouamama†<strong>– UP Cahier 2</strong> Salle Polyvalente des Baladins 5 x 19 dec Fringale/FUIQP - Restitution Marche pour la Dignité à Paris MJC Desnos 1 x <strong>2016</strong> <strong>PLENARY DEBATES</strong> <strong>PLACE</strong> 11-mars UP Cycle I “Pour comprendre la liberté d'expression†<strong>– UP Cahier 2<br> – Texte: UP liberté expression extraits paroles à citer<br> – Videos </strong> <strong>Université populaire de la Villeneuve, Préfuguration (3’45)<br> Université populaire de la Villeneuve (1) version courte (7’32)</strong> <strong>Université populaire de la Villeneuve (2) version longue (43’07)</strong> Salle Polyvalente des Baladins 3 x 03-juin UP Cycle I “Pour comprendre la géopolitique†Salle Polyvalente des Baladins 3 x 10-juin UP Cycle I “Pour comprendre le djihadisme†Salle Polyvalente des Baladins 3 x 25-sept APLP – Debate with the Danish resource center in Norrbro theme “Face aux représentations politiques, peut-on être religieux et citoyen en Europe aujourd’hui?†MJC Desnos 2 - 2 - Oct 2 October collective – International Day of Nonviolence <strong>- Magazine: Marchons 2015</strong> Alpexpo 5+ x <strong>2017</strong> <strong>PLENARY DEBATES</strong> <strong>PLACE</strong> 01-avr FUIQP (co-organizer) - Table-ronde regards croisés ""Violences policières, islamophobie, racisme d'Etat et sionisme dans la politique française: <em>Khlass</em> la <em>hogra</em>"" Salle 150, Villeneuve 3 - 13-avr MJC des Roseaux - Debate with youth from several neighborhoods in Grenoble (métropole) and Molenbeek organized by Jeunes Debout. Participation youth from Villeneuve organized by <em>service jeunesse</em> Maison de Quartier Aragon 4 - 01-juil Ad hoc public debate incendie collège -dialogue des savoirs avec parents d'élèves Parc de la Villeneuve 2 - 13-oct UP Cycle II - ""Mémoires de la colonisation, entre récits et tabous""<br> <strong>– UP Cahier 3</strong> MDH des Baladins 3 - 20-oct UP Cycle II - soirée film MDH des Baladins 2 - 10-nov UP Cycle II - ""La France et ses colonies"" <strong>– UP Cahier 4</strong> Salle Polyvalente des Baladins 2 x 20-nov UP Cycle II - ""La guerre d'Algérie, connaître les faits"" 1 La Cordée 2 - 22-nov UP Cycle II - ""La guerre d'Algérie, connaître les faits"" 2 La Cordée 2 - 24-nov UP Cycle II - ""La guerre d'Algérie, connaître les faits"" 3 La Cordée 2 - 08-déc UP Cycle II - ""Quelles continuités de l'imaginaire colonial après 1960?"" <strong>– UP Cahier 5</strong> Salle Polyvalente des Baladins 3 x <strong>2018</strong> <strong>PLENARY DEBATES</strong> <strong>PLACE</strong> 21-janv UP Cycle II - ""Repenser le monde avec Césaire, Fanon et Glissant"" <strong>– UP Cahier 6</strong> La Cordée 4 x 24-janv Court trial Chaambi Grenoble - soirée débat “Quelles libertés pour nos luttes?†Solexine,<br> centre-ville 2 - 26-avr UP Cycle II -""Mixité sociale, injonction à ",mds,True,findable,0,0,0,0,0,2023-06-19T12:00:43.000Z,2023-06-19T12:00:43.000Z,cern.zenodo,cern,"social housing neighborhoods,territorial stigmatization,racism,islamophobia,terrorist violence,colonialism,France,social movements","[{'subject': 'social housing neighborhoods'}, {'subject': 'territorial stigmatization'}, {'subject': 'racism'}, {'subject': 'islamophobia'}, {'subject': 'terrorist violence'}, {'subject': 'colonialism'}, {'subject': 'France'}, {'subject': 'social movements'}]",,
+10.5281/zenodo.3585723,Specific Heat of Holmium in Gold and Silver at Low Temperatures - Data,Zenodo,2019,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data from measurements on the specific heat of a variety of Au:Ho and Ag:Ho alloys. This data is associated with the manuscript: Herbst, M., Reifenberger, A., Velte, C. <em>et al.</em> Specific Heat of Holmium in Gold and Silver at Low Temperatures. <em>J Low Temp Phys</em> <strong>202, </strong>106–120 (2021). https://doi.org/10.1007/s10909-020-02531-1 For information on the motivation, measurement techniques, equipment, and data processing, please refer to this manuscript.",mds,True,findable,0,0,1,0,0,2019-12-19T16:49:45.000Z,2019-12-19T16:49:46.000Z,cern.zenodo,cern,heat capacity; Schottky anomaly; dilute holmium alloys; metallic magnetic calorimeters; ECHo,[{'subject': 'heat capacity; Schottky anomaly; dilute holmium alloys; metallic magnetic calorimeters; ECHo'}],,
+10.5281/zenodo.8086478,"Data of ""Inferring the Basal Friction Law from long term observations of Glacier Length, Thickness and Velocity changes on an Alpine Glacier""",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the surface velocity and elevation of Argentière Glacier in 2003 and 2018 used in: Gilbert, A., Gimbert, F., Gagliardini, O., & Vincent, C. (2023). Inferring the Basal Friction Law From Long Term Changes of Glacier Length, Thickness and Velocity on an Alpine Glacier. <em>Geophysical Research Letters</em>, <em>50</em>(16), e2023GL104503. https://doi.org/10.1029/2023GL104503 Surface DEM files contain elevation Z on a 20X20 meter grid (geotif files, coordinnate are in Lambert 2E ( EPSG:27572 ) ) Horizontal Velocity files contain measured horizontal velocities Vh in m/yr on a 20X20 meter grid (geotif files, coordinnate are in Lambert 2E ( EPSG:27572 ) )",mds,True,findable,0,0,0,0,0,2023-06-27T11:59:18.000Z,2023-06-27T11:59:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3937672,Extended Data: Structure-dependence of the atomic-scale mechanisms of Pt electrooxidation and dissolution,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Abstract:</strong> Platinum dissolution and restructuring due to surface oxidation are primary degradation mechanisms that limit the lifetime of Pt-based electrocatalysts for electrochemical energy conversion. Here, we studied well-defined Pt(100) and Pt(111) electrode surfaces by in situ high-energy surface X-ray diffraction, on-line inductively coupled plasma mass spectrometry, and density functional theory calculations, to elucidate the atomic-scale mechanisms of these processes. The locations of the extracted Pt atoms after Pt(100) oxidation reveal distinct differences from the Pt(111) case, which explains the different surface stability. The evolution of a specific stripe oxide structure on Pt(100) produces unstable surface atoms which are prone to dissolution and restructuring, leading to one order of magnitude higher dissolution rates. <strong>Contents of this repository:</strong> <strong>1. SXRD data:</strong> The experiments for the acquisition of the raw SXRD data were performed at the the European Synchrotron Radiation Facility, Grenoble, France at the beamlines ID31 and ID03. We thank H. Isern and T. Dufrane for the help during the SXRD experiments. tomo_tomo.spec is the file with the X-ray diffraction metadata for the CTR scans. It is a plain text file. Each HESXRD dataset is saved in a folder, which denotes the potential (e.g. 1V0.zip). The png-image files are previews of the corresponding dataset. The individual raw cbf files can be opened by pyMCA or silx. From python, the images can be accessed using the fabio library. calibration.zip contains the pyFAI calibration files and a list with indexed Bragg reflections for the UB matrix calculation CTRs_parameters.zip contains the averaged CTR structure factors used for the structual analysis as well as files with the atomic coordinates of the refined structural model. steps.zip contains the full datasets from the potential step experiments in Fig. 1e. <strong>2. DFT:</strong> CONTCARs.zip contains the atomic coordinates of the optimized computational models.",mds,True,findable,0,0,1,0,0,2020-07-12T15:39:02.000Z,2020-07-12T15:39:03.000Z,cern.zenodo,cern,"Catalyst,Electrochemistry,Chemistry,Sustainable Energy,Stability,X-ray Diffraction,Density Functional Theory,CTR,Platinum","[{'subject': 'Catalyst'}, {'subject': 'Electrochemistry'}, {'subject': 'Chemistry'}, {'subject': 'Sustainable Energy'}, {'subject': 'Stability'}, {'subject': 'X-ray Diffraction'}, {'subject': 'Density Functional Theory'}, {'subject': 'CTR'}, {'subject': 'Platinum'}]",,
+10.5281/zenodo.4760503,"Fig. 23 in Contribution To The Knowledge Of The Moroccan High And Middle Atlas Stoneflies (Plecoptera, Insecta)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access",Fig. 23. Capnioneura atlasica sp. n.: female abdominal tip in ventral view. Fig. 24. Capnioneura petitpierreae.: female abdominal tip in ventral view.,mds,True,findable,0,0,2,0,0,2021-05-14T05:28:10.000Z,2021-05-14T05:28:11.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Capniidae,Capnioneura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Capniidae'}, {'subject': 'Capnioneura'}]",,
+10.5281/zenodo.4761305,"Fig. 26 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 26. Dictyogenus jurassicum sp. n., biotope. Karstic spring of River Doubs, Mouthe, Doubs dpt, France. Photo: J.-P. G. Reding.",mds,True,findable,0,0,2,0,0,2021-05-14T07:45:09.000Z,2021-05-14T07:45:10.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.7221105,Frozen Light - Transverse Confinement of Waves in Three-dimensional Random Media,Zenodo,2022,,Software,"Creative Commons Attribution 4.0 International,Open Access",The code allows for computing the temporal evolution of the average spatial intensity profile resulting from transmission of a short pulse focused to a point on a slab of disordered medium.,mds,True,findable,0,0,0,0,0,2022-10-18T15:16:01.000Z,2022-10-18T15:16:02.000Z,cern.zenodo,cern,"Anderson localization,Wave scattering,Strong disorder,Wave diffusion","[{'subject': 'Anderson localization'}, {'subject': 'Wave scattering'}, {'subject': 'Strong disorder'}, {'subject': 'Wave diffusion'}]",,
+10.25914/604eb7628b4e7,High-Resolution Modelling of Extreme Storms over the East Coast of Australia v1.0,NCI Australia,2021,,Dataset,,,fabricaForm,True,findable,0,0,0,0,0,2021-03-15T01:24:51.000Z,2021-03-15T01:24:53.000Z,ardcx.nci,nci,,,,
+10.6073/pasta/b473b048846875b721d139416b8fd882,Global Lake Ecological Observatory Network: Long term chloride concentration from 529 lakes and reservoirs around North America and Europe: 1940-2016,Environmental Data Initiative,2017,en,Dataset,,"This dataset compiles long term chloride concentration data from 529 freshwater lakes and reservoirs in Europe and North America. All lakes in the dataset had greater than or equal to ten years of data. For each lake the following landscape and climate metrics were calculated: mean annual precipitation, mean monthly air temperatures, road density and impervious surface in 100 to 1500 m buffer zones, sea salt deposition. The dataset includes three files: 1) Descriptive data of lake sites (physical lake metrics, climate, land-cover characteristics), 2) Chloride time-series, and 3) GIS shapefiles.",mds,True,findable,0,0,1,1,0,2017-05-10T22:08:13.000Z,2017-05-10T22:08:14.000Z,edi.edi,edi,,,,
+10.5281/zenodo.7762437,"FIGURE 1. Bulbophyllum sondangii Vuong & Aver. A. Flattened flowering plant. B. Inflorescences. C in Bulbophyllum sondangii (Orchidaceae), a new species from Da Lat Plateau, southern Vietnam",Zenodo,2023,,Image,Open Access,"FIGURE 1. Bulbophyllum sondangii Vuong & Aver. A. Flattened flowering plant. B. Inflorescences. C. Floral bract, adaxial and abaxial side; D. Apical portion of inflorescences, view from above and from below. E. Flowers, view from above, from below and side view. F. Median sepal, adaxial and abaxial side. G. Apex of median sepal. H. Lateral sepal, view from above and from below. I. Petal, abaxial and adaxial side. J. Petal margin. K. Lip, views from different sides. L. Pedicel, ovary and column, side view. M. Apex of column, views from different sides. N. Anther cap, view from above and from below. O. Pollinia, view from different sides. All photos by Truong Ba Vuong, made from the type specimens BV 704, photo correction and design by L. Averyanov and T. Maisak.",mds,True,findable,0,0,0,3,0,2023-03-23T07:56:18.000Z,2023-03-23T07:56:18.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Bulbophyllum","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Bulbophyllum'}]",,
+10.5281/zenodo.7327824,1971 San Fernando earthquake 3-D coseismic displacement field,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","1971 San Fernando earthquake displacement maps and digital elevation models, produced using aerial photographs taken in 1969 and 1972. Images were acquired from the United States Geological Survey's Center for Earth Resources Observation and Science (EROS; http://earthexplorer.usgs.gov). 1969-1972-EW.tif - east-west displacement map 1969-1972-NS.tif - north-south displacement map 1969-1972-vertical.tif - vertical displacement map 1969-DEM.tif - digital elevation model produced from images acquired in the San Fernando Valley in 1969 1972-DEM.tif - digital elevation model produced from images acquired in the San Fernando Valley in 1972",mds,True,findable,0,0,0,0,0,2022-11-17T07:38:05.000Z,2022-11-17T07:38:06.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10199624,Improved Converted Traces from Rebasing Microarchitectural Research with Industry Traces,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"Improved converted traces of the paper ""Rebasing Microarchitectural Research with Industry Traces"", published at the 2023 IEEE International Symposium on Workload Characterization. It includes the CVP-1 traces used in the paper converted with our improved converter.
+Abstract:Â Microarchitecture research relies on performance models with various degrees of accuracy and speed. In the past few years, one such model, ChampSim, has started to gain significant traction by coupling ease of use with a reasonable level of detail and simulation speed. At the same time, datacenter class workloads, which are not trivial to set up and benchmark, have become easier to study via the release of hundreds of industry traces following the first Championship Value Prediction (CVP-1) in 2018. A tool was quickly created to port the CVP-1 traces to the ChampSim format, which, as a result, have been used in many recent works. We revisit this conversion tool and find that several key aspects of the CVP-1 traces are not preserved by the conversion. We therefore propose an improved converter that addresses most conversion issues as well as patches known limitations of the CVP-1 traces themselves. We evaluate the impact of our changes on two commits of ChampSim, with one used for the first Instruction Championship Prefetching (IPC-1) in 2020. We find that the performance variation stemming from higher accuracy conversion is significant.",api,True,findable,0,0,0,0,0,2023-11-23T06:56:43.000Z,2023-11-23T06:56:43.000Z,cern.zenodo,cern,"ChampSim,CVP-1 traces","[{'subject': 'ChampSim'}, {'subject': 'CVP-1 traces'}]",,
+10.6084/m9.figshare.c.6627480.v1,Healthcare students’ prevention training in a sanitary service: analysis of health education interventions in schools of the Grenoble academy,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background The sanitary service is a mandatory prevention training programme for all French healthcare students. Students receive training and then have to design and carry out a prevention intervention with various populations. The aim of this study was to analyse the type of health education interventions carried out in schools by healthcare students from one university in order to describe the topics covered and the methods used. Method The 2021–2022 sanitary service of University Grenoble Alpes involved students in maieutic, medicine, nursing, pharmacy and physiotherapy. The study focused on students who intervened in school contexts. The intervention reports written by the students were read doubly by independent evaluators. Information of interest was collected in a standardised form. Results Out of the 752 students involved in the prevention training program, 616 (82%) were assigned to 86 schools, mostly primary schools (58%), and wrote 123 reports on their interventions. Each school hosted a median of 6 students from 3 different fields of study. The interventions involved 6853 pupils aged between 3 and 18 years. The students delivered a median of 5 health prevention sessions to each pupil group and spent a median of 25 h (IQR: 19–32) working on the intervention. The themes most frequently addressed were screen use (48%), nutrition (36%), sleep (25%), harassment (20%) and personal hygiene (15%). All students used interactive teaching methods such as workshops, group games or debates that was addressed to pupils’ psychosocial (mainly cognitive and social) competences. The themes and tools used differed according to the pupils’ grade levels. Conclusion This study showed the feasibility of conducting health education and prevention activities in schools by healthcare students from five professional fields who had received appropriate training. The students were involved and creative, and they were focused on developing pupils’ psychosocial competences.",mds,True,findable,0,0,0,0,0,2023-05-03T03:20:27.000Z,2023-05-03T03:20:27.000Z,figshare.ars,otjm,"Medicine,Biotechnology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}]",,
+10.5061/dryad.18tg7,"Data from: High-throughput microsatellite genotyping in ecology: improved accuracy, efficiency, standardization and success with low-quantity and degraded DNA",Dryad,2016,en,Dataset,Creative Commons Zero v1.0 Universal,"Microsatellite markers have played a major role in ecological, evolutionary and conservation research during the past 20 years. However, technical constrains related to the use of capillary electrophoresis and a recent technological revolution that has impacted other marker types have brought to question the continued use of microsatellites for certain applications. We present a study for improving microsatellite genotyping in ecology using high-throughput sequencing (HTS). This approach entails selection of short markers suitable for HTS, sequencing PCR-amplified microsatellites on an Illumina platform and bioinformatic treatment of the sequence data to obtain multilocus genotypes. It takes advantage of the fact that HTS gives direct access to microsatellite sequences, allowing unambiguous allele identification and enabling automation of the genotyping process through bioinformatics. In addition, the massive parallel sequencing abilities expand the information content of single experimental runs far beyond capillary electrophoresis. We illustrated the method by genotyping brown bear samples amplified with a multiplex PCR of 13 new microsatellite markers and a sex marker. HTS of microsatellites provided accurate individual identification and parentage assignment and resulted in a significant improvement of genotyping success (84%) of faecal degraded DNA and costs reduction compared to capillary electrophoresis. The HTS approach holds vast potential for improving success, accuracy, efficiency and standardization of microsatellite genotyping in ecological and conservation applications, especially those that rely on profiling of low-quantity/quality DNA and on the construction of genetic databases. We discuss and give perspectives for the implementation of the method in the light of the challenges encountered in wildlife studies.",mds,True,findable,484,27,1,1,0,2016-08-10T18:52:23.000Z,2016-08-10T18:52:24.000Z,dryad.dryad,dryad,"Ursus arctos,individual identification,parentage analysis,short tandem repeat (STR)","[{'subject': 'Ursus arctos'}, {'subject': 'individual identification'}, {'subject': 'parentage analysis'}, {'subject': 'short tandem repeat (STR)'}]",['5058001164 bytes'],
+10.5281/zenodo.8424333,RENO - a multi-agent simulation tool for a renewable energy community,Zenodo,2023,en,Software,"Creative Commons Attribution 4.0 International,Open Access",A multi-agent simulation tool for simulating renewable energy communities in different configurations. GitLab up-to-date public repository: https://gricad-gitlab.univ-grenoble-alpes.fr/ploixs/energycommunitymodel,mds,True,findable,0,0,0,0,0,2023-10-10T06:42:43.000Z,2023-10-10T06:42:44.000Z,cern.zenodo,cern,"energy community,multi-agent,energy management,photovoltaic,self-consumption,self-sufficiency,human-centered control systems","[{'subject': 'energy community'}, {'subject': 'multi-agent'}, {'subject': 'energy management'}, {'subject': 'photovoltaic'}, {'subject': 'self-consumption'}, {'subject': 'self-sufficiency'}, {'subject': 'human-centered control systems'}]",,
+10.5281/zenodo.1479794,Brainstorm software 7-Nov-2018,Zenodo,2018,,Software,"Creative Commons Attribution Share Alike 4.0 International,Open Access","Brainstorm snapshot from 7-Nov-2018, for replicability of a published analysis pipeline (including FieldTrip 17-Dec-2018).",mds,True,findable,1,0,0,0,0,2018-11-07T17:21:55.000Z,2018-11-07T17:21:56.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3888347,Spam: Software for Practical Analysis of Materials - datasets for tutorials,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Datasets for spam tutorials: <strong>VEC4</strong> dataset from E.M. Charalampidou, E. Tudisco, S.A. Hall Experimental details available here: Charalampidou, E.M. (2011), ""Experimental study of localised deformation in porous sandstones"", <em>PhD Thesis</em> This dataset is two x-ray tomography scans of a notched sandstone sample scanned before and after deformation in an external rig.<br> There is a rigid body displacement between the two scans that can be taken into account nicely with a registration.<br> Scans from Laboratoire 3SR, Grenoble.<br> <strong>M2EA05</strong> dataset from E. Andò, G. Viggiani and J. Andrade.<br> This data already used in the following papers for comparison to numerical simulations: Kawamoto, R., Andò, E., Viggiani, G., & Andrade, J. E. (2016). Level set discrete element method for three-dimensional computations with triaxial case study. <em>Journal of the Mechanics and Physics of Solids</em>, <em>91</em>, 1-13 Nadimi, S., Fonseca, J., Andò, E., & Viggiani, G. (2019). A micro finite-element model for soil behaviour: experimental evaluation for sand under triaxial compression. <em>Géotechnique</em>, 1-6 This dataset is a series of x-ray tomographies acquired during the triaxial compression of a small sample of a ""Martian Simulant"" soil, performed in Laboratoire 3SR, Grenoble.<br> <strong>c01_F10_b4</strong> dataset from O. Stamati, E. Roubin, E. Andò and Y. Malecot <em>This dataset belongs to a paper which is under review</em> This is a 4-binned x-ray tomography of a small cylindrical sample of <em>micro-concrete</em><br> Scans from Laboratoire 3SR, Grenoble.<br> <strong>SandNX</strong> dataset from M. Milatz <em>The dataset is currently being analysed further</em> See this publication for the experimental setup: Milatz, M. (2020). An automated testing device for continuous measurement of the hysteretic water retention curve of granular media. <em>Acta Geotechnica</em>, 1-19<br> Data acquired on NeXT-Grenoble, a simultaneous Neutron and X-ray scanner at the ILL in Grenoble (Experiment UGA-73).<br> Neutron tomography has had a x0.7 downscale to bring it approximately in line with the pixel size for the x-ray tomography.<br> <strong>YehyaConcreteNX</strong> dataset from M. Yehya, A. Tengattini, E. Andò, F. Dufour Yehya, M., Ando, E., Dufour, F., & Tengattini, A. (2018). Fluid-flow measurements in low permeability media with high pressure gradients using neutron imaging: Application to concrete. <em>Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment</em>, <em>890</em>, 35-42 Data acquired on NeXT-Grenoble, a simultaneous Neutron and X-ray scanner at the ILL in Grenoble (Experiment UGA-25).",mds,True,findable,0,0,0,0,0,2020-06-19T07:37:28.000Z,2020-06-19T07:37:29.000Z,cern.zenodo,cern,"tomography,digital image correlation,digital volume correlation,photo mechanics,granular mechanics,sandstone,strain localisation","[{'subject': 'tomography'}, {'subject': 'digital image correlation'}, {'subject': 'digital volume correlation'}, {'subject': 'photo mechanics'}, {'subject': 'granular mechanics'}, {'subject': 'sandstone'}, {'subject': 'strain localisation'}]",,
+10.5281/zenodo.6321323,Model Lagrangian trajectories and deformation data analyzed in the Sea Ice Rheology Experiment - Part I,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Model Lagrangian trajectories and deformation estimates for sea-ice models participating in the Sea Ice Rheology Experiment (SIREx) - Part I. Model Lagrangian trajectories are integrated offline, starting on January 1st with all available raw RGPS cells positions (interpolated to January 1st 00:00:00 UTC). The trajectories are advected at an hourly time step with the models daily velocity output until March 31st. The trajectories are then sampled at a 3-day interval to match the RGPS composite time stamps, and the velocity derivatives (deformation) are calculated using the line integral approximations on the cells' contour. All model trajectories and Lagrangian deformation data therefore have nominal temporal and spatial scales of 3-days and 10-km (same as the RGPS composite), regardless of the original resolution of the model output. The model Lagrangian deformation estimates form the basis quantity for the statistical and spatio-temporal scaling analysis presented in Bouchat et al., Sea Ice Rheology Experiment (SIREx), Part I: Scaling and statistical properties of sea-ice deformation fields, Journal of Geophysical Research: Oceans (2022). This paper also provides further details on the model trajectory integration and deformation calculation. There is one netCDF file per model, per year (1997 and/or 2008). Data are organized in matrices where the (i,j) indices are the Lagrangian cells identifier. This allows us to keep track of neighbouring cells for the scaling analysis. See below for more information on what variables are included in the files, their structure, and how to cite. <strong>1. File naming convention</strong> ""< Model simulation label >"" + _ + ""deformation"" + _ + ""< year >"" <strong>2. Variables included</strong> <em>(x1,y1), (x1,y2), (x3,y3), (x4,y4)</em>: Position of the cells' corners (Lagrangian trajectories) - (meters); <em>A</em>: Cells' area - (meters squared); <em>dudx, dudy, dvdx, dvdy</em>: Cell's velocity derivatives (strain rates/deformation) - (1/seconds); <em>d_dudx, d_dudy, d_dvdx, d_dvdy</em>: Trajectory error on cells' velocity derivatives - (1/seconds); <em>time</em>: Day of year. <strong>*Note:</strong> the model trajectories are terminated if they move within 100 km from land. Before computing deformation statistics to compare with RGPS composite data, one should mask both deformation sets to only keep cells available in both the model and RGPS data sets. <strong>3. Variable structure</strong> All variables (except <em>time</em>) are matrices with axes (<em>it, i, j </em>), where <em>it</em> is the time stamp/iteration and<em> i,j </em>are the cells identifiers. See below for how the cells are defined: |--------------------------------------------------------------><sub> <strong>j-axis</strong> </sub> <br> | <br> | <strong>(</strong><strong>x1_ij,y1_ij</strong><strong>)</strong> <strong>o</strong> -------------------<strong> o</strong> <strong>(</strong><strong>x2_ij,y2_ij</strong><strong>)</strong> <br> | | | <br> | | <strong>A_ij or dudx_ij</strong> | <strong> </strong><br> | | | <br> | <strong>(</strong><strong>x4_ij,y4_ij</strong><strong>) </strong><strong>o</strong> ------------------- <strong>o</strong> <strong>(</strong><strong>x3_ij,y3_ij</strong><strong>)</strong> <br> | <br> |<br> V<sub><strong>i-axis</strong></sub> Hence, coordinates are repeated between neighbouring cells, for example: (x2_ij,y2_ij) = (x1_ij+1,y1_ij+1) and (x4_ij,y4_ij) = (x1_i+1j,y1_i+1j) <strong>4. Recommended citation usage</strong> If <em>all</em> simulations included in the current archive are used in a future study, we ask to cite this archive and the SIREx paper (Bouchat et al., 2022). If only <em>selected </em>simulations are used, we ask to cite both this archive and the reference paper(s) applying to the selected simulation(s) (as stated indicated in Table 1 of the SIREx papers).",mds,True,findable,0,0,0,1,0,2022-03-03T02:00:46.000Z,2022-03-03T02:00:47.000Z,cern.zenodo,cern,"sea ice,deformation,sea ice modelling,scaling analysis,rheology","[{'subject': 'sea ice'}, {'subject': 'deformation'}, {'subject': 'sea ice modelling'}, {'subject': 'scaling analysis'}, {'subject': 'rheology'}]",,
+10.5281/zenodo.3529760,Environmental co-benefits and adverse side-effects of alternative power sector decarbonization strategies,Zenodo,2019,en,Software,"Creative Commons Attribution Share Alike 4.0 International,Open Access","This package contains the data and source code used in preparation for the<br> paper ""Environmental co-benefits and adverse side-effects of alternative power<br> sector decarbonization strategies"" by Gunnar Luderer et al., published in Nature<br> Communications.",mds,True,findable,10,0,0,0,0,2019-11-05T21:11:41.000Z,2019-11-05T21:11:41.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10020957,robertxa/Therion-TextWrangler: First Release,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,Syntax Color file of Therion input files with TexWrangler,api,True,findable,0,0,0,0,0,2023-10-19T08:40:29.000Z,2023-10-19T08:40:29.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4760491,"Fig. 15 in Contribution To The Knowledge Of The Moroccan High And Middle Atlas Stoneflies (Plecoptera, Insecta)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 15. Distribution of Protonemura berberica, P. dakkii and P. talboti.",mds,True,findable,0,0,2,0,0,2021-05-14T05:27:11.000Z,2021-05-14T05:27:11.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.7142646,Validation of an Uncertainty Propagation Method for Moving-Boat ADCP Discharge Measurements,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","ADCP intercomparisons data from Génissiat (2010) and Chauvan (2016). Data used in the article <strong>Validation of an Uncertainty Propagation Method for Moving-Boat ADCP Discharge Measurements</strong>, <em>Water Resources Research</em>, Despax et al..",mds,True,findable,0,0,0,1,0,2022-10-04T09:43:18.000Z,2022-10-04T09:43:19.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.897674,simex_platform-0.3.3,Zenodo,2017,,Software,"GNU General Public License v3.0 only,Open Access",simex_platform: A software framework for simulations of photon experiments at advanced laser light sources.,mds,True,findable,0,0,0,3,0,2017-09-25T12:10:08.000Z,2017-09-25T12:10:10.000Z,cern.zenodo,cern,"simex, eucall, SIMEX, EUCALL, start-to-end simulations","[{'subject': 'simex, eucall, SIMEX, EUCALL, start-to-end simulations'}]",,
+10.5281/zenodo.5765565,DATA_PRF2021_Chauchat,Zenodo,2021,en,Other,"Creative Commons Attribution 4.0 International,Open Access","The repository contains 2 netcdf files, the file PRF2021_ChauchatEtAl.nc contains sheet-flow experimental data from Revil-Baudard et al. (JFM 2015, 2016) as well as two-fluid LES data by Cheng et al. (AWR 2018) using sedFOAM. The file ShenDataPRF.nc contains experimental data from Shen and Lemmin (JHR 1999). The folder Lyn2008 contains the data for Schmidt number gathered by Lyn (2008). The python script figuresPRFnc.py allows to read the data and make the figures from the article Chauchat et al. (PRF 2021).",mds,True,findable,0,0,0,0,0,2021-12-07T20:58:07.000Z,2021-12-07T20:58:08.000Z,cern.zenodo,cern,"Sediment transport,Suspended load,Turbulent Sclmidt Number","[{'subject': 'Sediment transport'}, {'subject': 'Suspended load'}, {'subject': 'Turbulent Sclmidt Number'}]",,
+10.5281/zenodo.4964209,"FIGURES 17–20 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 17–20. Protonemura bispina sp. n., 17. male, paraproct median lobe with sclerotized stem. 18. male, paraproct outer lobe with trifurcated sclerite. 19. hybrid x Protonemura auberti, male, ventral view (Julian Alps). 20. female, ventral view",mds,True,findable,0,0,5,0,0,2021-06-16T08:25:07.000Z,2021-06-16T08:25:08.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.8279040,Dataset for Nanoscale Growth Mechanisms of Gypsum: Implications for Environmental Control of Crystal Habits,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset collected here has been used in the paper ""Nanoscale Growth Mechanisms of Gypsum: Implications for Environmental Control of Crystal Habits"". The files are in .dat format and each one corresponds to the images indicated in the file name.",mds,True,findable,0,0,0,0,0,2023-08-24T12:39:54.000Z,2023-08-24T12:39:54.000Z,cern.zenodo,cern,"gypsum,crystal growth,particle-mediated growth,2D-nucleation,spiral hillocks,classical and non-classical growth,morphology control,sulfate mineral","[{'subject': 'gypsum'}, {'subject': 'crystal growth'}, {'subject': 'particle-mediated growth'}, {'subject': '2D-nucleation'}, {'subject': 'spiral hillocks'}, {'subject': 'classical and non-classical growth'}, {'subject': 'morphology control'}, {'subject': 'sulfate mineral'}]",,
+10.5281/zenodo.5833771,"Pléiades co- and post-eruption survey in Cumbre Vieja volcano, La Palma, Spain",Zenodo,2022,en,Dataset,"Creative Commons Attribution Non Commercial 4.0 International,Open Access","<strong>Introduction</strong>: This repository consists of a series of topographic surfaces of the Cumbre Vieja volcano (La Palma, Spain), presented as a series of Digital Elevation Models (DEMs) obtained from multiple Pléiades stereoscopic surveys acquired from the 22<sup>nd</sup> of September 2021 until the 14<sup>th</sup> of January 2022. We also present a series of grids showing the difference of elevation between the pre-eruption surface and the co- and post-eruption surface, which reveal the lava thickness of the eruption. This was used to calculate the lava volume and effusion rate or Time Average Discharge Rate (TADR) at the time of the Pléiades surveys. <strong>Data</strong>: 1 – Pléiades stereo images: A pre-eruption Pléiades stereopair was collected from 2013. A total of ten stereopairs were collected between the 23<sup>th</sup> of September 2021 and 2<sup>nd</sup> of October 2021 as part of the CIEST<sup>2</sup> initiative (https://www.poleterresolide.fr/ciest-2-nouvelle-generation-2/). Four additional pairs were acquired between the 11<sup>th</sup> of December 2021 and the 14<sup>th</sup> of January 2022 as part of the Dinamis initiative (https://dinamis.data-terra.org/). However, only some of these stereopairs were acquired with sufficiently large cloud-free areas around the eruption site. The following Pléiades stereo images were processed and are presented in this repository: Date Sensor IDs 2013-06-30, 12h02m PHR1B 5944045101 & 5944046101 2021-09-26, 11h58m PHR1B 5962414101 & 5962415101 2021-10-02, 12h02m PHR1B 5988066101 & 5988067101 2022-01-01, 12h02m PHR1A 6122469101 & 6122470101 2022-01-14, 12h02m PHR1B 6135055101 & 6135057101 Table 1: Date, sensor and image ID of the Pléiades stereoimages used in this repository. 2 – Lidar pre-eruption surface: A lidar survey acquired in 2016 by the Spanish Mapping Agency (IGN, Spain) was downloaded through the portal: http://centrodedescargas.cnig.es/CentroDescargas/catalogo.do?Serie=LIDAR#. Specifically, we used the Digital Surface Model (DSM) product, available in 2x2 m Ground Sampling Distance (GSD). This means that trees and human structures were removed based using classification of the multiple returns of the lidar pulses. The coordinate reference system is REGCAN (UTM zone 28N, EPSG: 32628), and the heights are orthometric, using the height reference system REDNAP, built upon the geoid EGM08. Using the REDNAP geoid model, we converted the heights to meters above ellipsoid (WGS84), since the Pléiades data is acquired with satellite attitudes referred to the ellipsoid WGS84. <strong>Methods</strong>: The Pléiades stereoimages were processed using the Ames StereoPipeline (ASP, Shean et al., 2016, see ASP branch in repository), yielding a DEM in 2x2m GSD and an orthoimage in 0.5x0.5m GSD. The processing was done using as only input the stereoimages and their orientation information, as Rational Polynomial Coefficients (RPCs). The <em>parallel_stereo </em>routine performs all the steps needed in the correlation of the stereoimages, yielding a pointcloud which is then interpolated using the routine <em>point2dem</em>. Besides default parameters, the <em>parallel_stereo</em> parameters used for creation of the DEMs were the standard parameters, plus the following ones: <em>--corr-tile-size 2048 --sgm-collar-size 256 --corr-seed-mode 3 --corr-max-levels 2 --corr-timeout 900 --cost-mode 3 --subpixel-mode 9 --corr-kernel 7 7 --subpixel-kernel 15 15</em> Once the DEM was created, DEM co-registration was applying in order to align and minimize positional biases between the pre-eruption DEM and the Pléiades DEMs. We followed the co-registration method of Nuth & Kääb (2011), implemented by David Shean’s co-registration routines (https://github.com/dshean/demcoreg, Shean et al., 2016). The co-registration involved a horizontal and vertical shift of the Pléiades DEMs, as well as a planar tilt correction. The horizontal offset obtained from the DEM co-registration was also applied to the Pléiades orthoimages. Lava outlines were manually digitized from the co-registered Pléiades orthoimages, excluding kipukas and major building constructions which were not covered by the lavas. The lava outlines are available as GeoPackages in the “GPKG†branch of the repository. Lava volume calculations were done using the average lava thickness, multiplied by the area covered by the lavas. The uncertainty in volume was assumed to be the Normalized Mean Absolute Deviation (NMAD, Höhle and Höhle, 2009), multiplied by the lava area. The TADR was calculated as the total volume divided by the time, in seconds, between the start of the eruption, defined as 2021-09-19 11:58:00 local time, and the acquisition of the Pléiades images. For the total TADR, we used the volume extracted from the Pléiades images from the 1<sup>st</sup> of January 2022, divided by the observed time of beginning and end of the eruption, defined as 2021-12-13 22:21:00, local time. The TADR values shown in this repository do not account for submarine lavas nor tephra deposits. In addition, another set of DEMs were produced automatically as soon as the images were made available by the on-demand processing service DSM-OPT provided by ForM@Ter (https://en.poleterresolide.fr/on-demand-processing/#/mns). This processing is based on Micmac (D. Michéa and J.-P. Malet / EOST; E. Pointal, IPGP, Rupnik, 2017). The DEMs produced correspond to the file created automatically “A2_dsm_denoised.tifâ€. They were obtained in 1x1 m GSD, and they were cropped over the area of interest. These DEMs have not been co-registered. These data are available in the “MM†branch in the repository. <strong>Results: Lava area, volumes and effusion rate:</strong> Date Lava Area (km2) Lava thickness (m) Lava volume (10e+6 m3) TADR (m3 s-1) 2021-09-26, 11h58m 2.6 11.4±1.1 29.8±2.8 49.2±4.7 2021-10-02, 12h02m 4.3 10.0±1.4 43.0±6.1 38.2±5.4 2022-01-01, 12h02m 12.25 16.6±1.1 203.3±13.9 27.5±1.9 Table 2: results of lava area, thickness, lava volume and TADR since the start of the eruption. <strong>Repository structure:</strong> zenodo_lapalma/<br> ├── ASP<br> │ ├── 20130630_1202_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ ├── 20210926_1158_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ ├── 20210926_1158_lapalma_PL_2x2m_UTM28N_thickness.tif<br> │ ├── 20211002_1202_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ ├── 20211002_1202_lapalma_PL_2x2m_UTM28N_thickness.tif<br> │ ├── 20220101_1202_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ ├── 20220101_1202_lapalma_PL_2x2m_UTM28N_thickness.tif<br> │ ├── 20220114_1202_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ └── 20220114_1202_lapalma_PL_2x2m_UTM28N_thickness.tif<br> ├── GPKG<br> │ ├── 20210925_1202_lapalma_PL_UTM28N_outline.gpkg<br> │ ├── 20211002_1202_lapalma_PL_UTM28N_outline.gpkg<br> │ └── 20220101_1202_lapalma_PL_UTM28N_outline.gpkg<br> └── MM<br> ├── 20130630_1202_PL_1x1m_UTM28N_MM_DEM.tif<br> ├── 20210926_1158_PL_1x1m_UTM28N_MM_DEM.tif<br> ├── 20211002_1230_PL_1x1m_UTM28N_MM_DEM.tif<br> ├── 20220101_1202_PL_1x1m_UTM28N_MM_DEM.tif<br> └── 20220114_1202_PL_1x1m_UTM28N_MM_DEM.tif <strong>Acknowledgements</strong>: Pléiades images were provided under the CIEST² initiative (CIEST2 is part of ForM@Ter (https://en.poleterresolide.fr/ ) and supported by ISDeform National Service of Observation) for the reference image acquired in 2013 and from the 23<sup>rd</sup> of September to the 2<sup>nd</sup> of October 2021, and through the Dinamis program (CNES, France) from the 12<sup>th</sup> of December 2021 to the 14<sup>th</sup> of January 2022 (image Pléiades©CNES2013,©CNES2021,©CNES2022, distribution AIRBUS DS) <strong>Dataset Attribution</strong> This dataset is licensed under a Creative Commons CC BY-NC 4.0 International License (Attribution-NonCommercial).<br> Attribution required for copies and derivative works: The underlying dataset from which this work has been derived includes Pleiades material ©CNES (2013,2021,2022), distributed by AIRBUS DS, and data provided by the Spanish Mapping Agency (IGN, Spain), all rights reserved. <strong>Dataset Citation</strong> Belart and Pinel (2022). “Pléiades co- and post-eruption survey in Cumbre Vieja volcano, La Palma, Spainâ€. Dataset distributed on Zenodo: 10.5281/zenodo.5833771 <strong>References:</strong> Höhle, J. and Höhle, M.: Accuracy assessment of digital elevation models by means of robust statistical methods, ISPRS J. Photogramm. Remote Sens., 64, 398–406, https://doi.org/10.1016/j.isprsjprs.2009.02.003, 2009. Nuth, C. and Kääb, A.: Co-registration and bias corrections of satellite elevation datasets for quantifying glacier thickness change, The Cryosphere, 5, 271–290, https://doi.org/10.5194/tc-5-271-2011, 2011. Rupnik, E., Daakir, M., & Deseilligny, M. P.: MicMac – a free, open-source solution for photogrammetry. Open Geospatial Data, Software and Standards, 2(1), 1-9, 2017. Shean, D. E., Alexandrov, O., Moratto, Z. M., Smith, B. E., Joughin, I. R., Porter, C., and Morin, P.: An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery, ISPRS J. Photogramm. Remote Sens., 116, 101–117, https://doi.org/10.1016/j.isprsjprs.2016.03.012, 2016.",mds,True,findable,0,0,0,0,0,2022-02-08T08:33:25.000Z,2022-02-08T08:33:26.000Z,cern.zenodo,cern,"Pléiades, DEM, lava thickness","[{'subject': 'Pléiades, DEM, lava thickness'}]",,
+10.6084/m9.figshare.24196813,Additional file 1 of Sonometric assessment of cough predicts extubation failure: SonoWean—a proof-of-concept study,figshare,2023,,Text,Creative Commons Attribution 4.0 International,"Additional file 1. Supplemental Fig 1: Description of the Pulsar Model 14® Sound Level Meter and method for measurement. The Model 14 is a general purpose digital sound level meter which meets the full requirements of IEC 61672 to Class 2. Before each inclusion the Sound Level Meter was calibrated acoustically using an external reference, i.e the Sound Level Calibrator Model 106, which is placed over the microphone. The calibrator generates a stabilized Sound Pressure Level of 94dB (+- 0.3dB) at a frequency of 1 kHz. Using a Low range (Low = 35dB to 100dB), maximum sound level was measured pressing the MAX HOLD button for at least ½ second and was ultimately noticed. A level of sound in decibels (L) is defined as ten times the base-10 logarithm of the ratio between two power-related quantities I (i.e cough-volume related sound) and Io (i.e the human hearing threshold) as follows: L = 10 * Log 10 (I/ Io). Thus, an apparent mild increase from 73 to 76 dB in sound level results in multiplying acoustic energy by a factor two.",mds,True,findable,0,0,0,0,0,2023-09-26T03:25:47.000Z,2023-09-26T03:25:47.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Physiology,FOS: Biological sciences,Immunology,FOS: Clinical medicine,Infectious Diseases,FOS: Health sciences,Computational Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Infectious Diseases'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Computational Biology'}]",['117717 Bytes'],
+10.7280/d1667w,Greenland Marine-Terminating Glacier Retreat Data,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"The thinning, acceleration, and retreat of Greenland glaciers since the mid-1990s has been attributed to the enhanced intrusion of warm Atlantic Waters (AW) into fjords, but this assertion has not been quantitatively tested on a Greenland-wide basis or included in numerical models. Here, we investigate how AW influenced the retreat of 226 marine-terminating glaciers by combining ocean modeling, remote sensing, and in-situ observations. We identify 74 glaciers standing in deep fjords with warm AW that retreated when ocean warming induced a 48% increase in glacier undercutting that controlled 62% of the glacier mass loss in 1992-2017. Conversely, 27 glaciers calving on protective, shallow ridges and 24 glaciers standing in cold, shallow waters did not retreat; and 10 glaciers retreated when their floating sections collapsed. The mechanisms of ice front evolution remain undiagnosed at 87 glaciers with no ocean and bathymetry data, but these glaciers only account for 16% of the retreat. Projections of glacier evolution that exclude ocean-induced glacier undercutting may underestimate future mass losses by at least a factor two. In this dataset, we present data for 226 glaciers over the time period 1985-2017. In particular, we provide estimates of glacier geometry, ocean thermal forcing on the continental shelf and at the glacier terminus, ice velocity, ocean-induced melt, and thinning-induced retreat. Most of the data is compiled in a netCDF file for each of the 226 glaciers investigated durign the study period, with the exception of ice front boundaries for the years 1985-2019 digitized from Landsat 5, 7, and 8 imagery, which we provide in a single shapefile. In addition, we include a PDF which displays the data enclosed for each glacier.",mds,True,findable,480,61,0,2,0,2020-12-01T18:09:19.000Z,2020-12-01T18:09:21.000Z,dryad.dryad,dryad,"glacier,ice-ocean interactions,ice mass balance,ice front,ice front position,ice velocity,ice thinning,glacier melt","[{'subject': 'glacier'}, {'subject': 'ice-ocean interactions'}, {'subject': 'ice mass balance'}, {'subject': 'ice front'}, {'subject': 'ice front position'}, {'subject': 'ice velocity'}, {'subject': 'ice thinning'}, {'subject': 'glacier melt'}]",['52236257 bytes'],
+10.6084/m9.figshare.22613066.v1,Additional file 1 of Digital technologies in routine palliative care delivery: an exploratory qualitative study with health care professionals in Germany,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1. Interview guide.,mds,True,findable,0,0,0,0,0,2023-04-13T12:27:56.000Z,2023-04-13T12:27:56.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}]",['19572 Bytes'],
+10.5061/dryad.5b58400,Data from: Mapping the imprint of biotic interactions on β-diversity,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"Investigating how trophic interactions influence the β-diversity of meta-communities is of paramount importance to understanding the processes shaping biodiversity distribution. Here, we apply a statistical method for inferring the strength of spatial dependencies between pairs of species groups. Using simulated community data generated from a multi-trophic model, we showed that this method can approximate biotic interactions in multi-trophic communities based on β-diversity patterns across groups. When applied to soil multi-trophic communities along an elevational gradient in the French Alps, we found that fungi make a major contribution to the structuring of β-diversity across trophic groups. We also demonstrated that there were strong spatial dependencies between groups known to interact specifically (e.g. plant-symbiotic fungi, bacteria-nematodes) and that the influence of environment was less important than previously reported in the literature. Our method paves the way for a better understanding and mapping of multi-trophic communities through space and time.",mds,True,findable,357,65,1,1,0,2018-07-27T17:58:03.000Z,2018-07-27T17:59:10.000Z,dryad.dryad,dryad,"partial correlation networks,interaction network,graphical lasso,meta-communities,Holocene","[{'subject': 'partial correlation networks'}, {'subject': 'interaction network'}, {'subject': 'graphical lasso'}, {'subject': 'meta-communities'}, {'subject': 'Holocene'}]",['420248 bytes'],
+10.5281/zenodo.8404376,vispy/vispy: Version 0.14.1,Zenodo,2023,,Software,Open Access,<strong>Fixed bugs:</strong> return to oldest supported numpy #2535 (brisvag) <strong>Merged pull requests:</strong> Bump pypa/cibuildwheel from 2.16.0 to 2.16.1 #2534 (dependabot[bot]) Bump pypa/cibuildwheel from 2.15.0 to 2.16.0 #2531 (dependabot[bot]) Bump docker/setup-qemu-action from 2 to 3 #2529 (dependabot[bot]) Bump actions/checkout from 3 to 4 #2527 (dependabot[bot]),mds,True,findable,0,0,0,0,0,2023-10-03T22:23:30.000Z,2023-10-03T22:23:31.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4453192,How dopants limit the ultrahigh thermal conductivity of boron arsenide: a first principles study,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The dataset contains the necessary information to reproduce the phonon-defect scattering rates and the phonon thermal conductivity of cubic boron arsenide (BAs) upon doping, via the almaBTE software. Input files contain: 1) Interatomic force constants for the pristine BAs, required to extract the phonon band structure and the intrinsic scattering processes; 2) Unit cell POSCAR; 3) Interatomic force constants for the C, Ge and Si impurities, required to compute the phonon-defect scattering rates beyond the mass-only approximation. Output files contain: 1) Phonon-defect scattering rates (mass-only approximation, bond-only approximation, total) for charged and neutral impurities; 2) Thermal conductivity at 300 K as function of the impurity concentration.",mds,True,findable,0,0,0,0,0,2021-01-20T19:40:40.000Z,2021-01-20T19:40:40.000Z,cern.zenodo,cern,"Boron arsenide (BAs), phonons, thermal conductivity, defects","[{'subject': 'Boron arsenide (BAs), phonons, thermal conductivity, defects'}]",,
+10.5061/dryad.m37pvmd0v,IS-mediated mutations both promote and constrain evolvability during a long-term experiment with bacteria,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"The long-term dynamics of IS elements and their effects on bacteria are poorly understood, including whether they are primarily genomic parasites or important drivers of adaptation by natural selection. Here, we investigate the dynamics of IS elements and their contribution to genomic evolution and fitness during a long-term experiment with Escherichia coli. This data set includes the Rmd file to analyze the genomic and metagenomic data (Tenaillon et al. 2016 and Good et al. 2017) in light with the IS dynamics and their correlation with fitness improvements described in the present work.",mds,True,findable,284,26,0,0,0,2020-10-30T17:38:33.000Z,2020-10-30T17:38:35.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['13769300 bytes'],
+10.5281/zenodo.7474128,"Source code supplement for ""Topological magnon band structure of emergent Landau levels in a skyrmion lattice""",Zenodo,2022,,Software,"GNU General Public License v2.0 only,Open Access","<strong>Skyrmion, conical, and field-polarised magnon dynamics in MnSi</strong> <strong>Description</strong> This is the supplementary source code to our paper, <em>Topological magnon band structure of emergent Landau levels in a skyrmion lattice</em>. (The complementary data supplement can be found here.) The code contains a <em>Takin</em> plugin module and its helper tools. The module calculates the dispersion relations and the dynamical structure factor for the conical, the field-polarised, and the skyrmion phase of MnSi. The development repository can be found here: https://code.ill.fr/scientific-software/takin/plugins/mnsi. Videos comparing the skyrmion and conical dispersion relations are available here: https://youtu.be/CuoA6sIM2oM, https://youtu.be/n3Pvjo7iNHE. <strong>Dependencies</strong> The <em>Takin</em> software and the <em>tlibs</em> libraries are needed for compilation. Their repositories are available here: Stable releases: https://github.com/t-weber/takin2 Development versions: https://code.ill.fr/scientific-software/takin Binary releases: https://wiki.mlz-garching.de/takin DOIs: <em>Takin 2</em>: 10.5281/zenodo.4117437, <em>tlibs 2</em>: 10.5281/zenodo.5717779, old <em>Takin 1</em> and <em>tlibs 1</em>: 10.5281/zenodo.3961491. <strong>Setup</strong> Download the external dependencies: <code>cd ext && ./setup_externals.sh && cd ..</code>. The ext/ directory should now contain the source code of the external libraries. Build the module: <code>make -j4</code>. Copy the built plugin modules to <em>Takin's</em> plugin directory: <code>mkdir -pv ~/.takin/plugins/ && cp -v lib/*.so ~/.takin/plugins/</code> The helper tools can be found in the bin/ directory. <strong>References and Acknowledgements</strong> This source code is based on theoretical magnon dispersion models and their <em>Mathematica</em> implementations by M. Garst and J. Waizner, see these references and our papers below: M. Garst and J. Waizner, Skyrmion linear spin-wave theory and <em>Mathematica</em> implementation, personal communications (2017-2020). M. Garst and J. Waizner, Helimagnon linear spin-wave model and <em>Mathematica</em> implementation, personal communications (2014-2019). M. Garst and J. Waizner, Field-polarised linear spin-wave model and <em>Mathematica</em> implementation, personal communications (2016-2019). M. Garst, J. Waizner, and D. Grundler, J. Phys. D: Appl. Phys. <strong>50</strong> 293002, https://doi.org/10.1088/1361-6463/aa7573 (2017). J. Waizner, PhD thesis, Universität zu Köln, https://kups.ub.uni-koeln.de/7937/ (2017). Furthermore, the present source code is based on optimised <em>Python</em> implementations by M. Kugler and G. Brandl of early versions of the theoretical models mentioned above; it started as a translation of the following <em>Python</em> codes into <em>C++</em>: G. Brandl and M. Kugler, Helimagnon implementation in <em>Python</em>, personal communications (2015-2016). M. Kugler, G. Brandl, J. Waizner, M. Janoschek, R. Georgii, A. Bauer, K. Seemann, A. Rosch, C. Pfleiderer, P. Böni, and M. Garst, Phys. Rev. Lett. <strong>115</strong>, 097203, https://doi.org/10.1103/PhysRevLett.115.097203 (2015). M. Kugler and G. Brandl, Skyrmion spin-wave implementation in <em>Python</em>, personal communication (2016). The following alternate <em>Python</em> implementations of the skyrmion spin-wave model exist: D. Fobes, Implementation in <em>Python</em>, personal communication (2016). L. Beddrich, Implementation in <em>Python</em>, https://github.com/LukasBeddrich/skyrmion-model (2017). The helimagnon and ferromagnetic parts of this code have been used in the following papers: T. Weber, J. Waizner, P. Steffens, A. Bauer, C. Pfleiderer, M. Garst, and P. Böni, Phys. Rev. B <strong>100</strong>, 060404(R), https://doi.org/10.1103/PhysRevB.100.060404 (2019). T. Weber, J. Waizner, G. S. Tucker, R. Georgii, M. Kugler, A. Bauer, C. Pfleiderer, M. Garst, and P. Böni, Phys. Rev. B <strong>97</strong>, 224403, https://doi.org/10.1103/PhysRevB.97.224403 (2018). T. Weber, J. Waizner, G. S. Tucker, L. Beddrich, M. Skoulatos, R. Georgii, A. Bauer, C. Pfleiderer, M. Garst, and P. Böni, AIP Advances <strong>8</strong>, 101328, https://doi.org/10.1063/1.5041036 (2018). Completion of dependencies and Docker build info: N. Garofil, Universiteit Antwerpen.",mds,True,findable,0,0,3,5,0,2022-12-22T19:07:09.000Z,2022-12-22T19:07:10.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6671769,Extracted opinions from the French National Great Debate (Grand Débat National) about transport and socio-economic description of municipalities participating to the debate,Zenodo,2022,fr,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This data set contains : - motifs_with_geom.json : extracted propositions from the answers to the online public consultation related to the French National Great Debate (Grand Débat National) which took place in 2019. The propositions consist of automatically extracted patterns. The propositions are related to transport. Extracted propositions are also georeferenced by postal codes and associated coordinates (WGS 84). - communes_with_all_data.geojson : socio-economic features which describes municipalities in France (mainland + overseas territories). These data are also georeferenced by postal codes and associated coordinates (WGS 84). data_geo.zip are the source files to build this file. The features are described in data_cadrage_meta.csv - motifsxcommunes_without_geom.csv : joined file of extracted propositions and socio-economic features of municipalities, without coordinates. These data are used to performed statistic analysis. - transportonto4.owl : ontology describing transport in French, used to extract propositions related to transport.",mds,True,findable,0,0,0,3,0,2022-06-20T17:06:33.000Z,2022-06-20T17:06:33.000Z,cern.zenodo,cern,"https://fr.wikipedia.org/wiki/Grand_d%C3%A9bat_national,https://fr.wikipedia.org/wiki/Transport","[{'subject': 'https://fr.wikipedia.org/wiki/Grand_d%C3%A9bat_national', 'subjectScheme': 'url'}, {'subject': 'https://fr.wikipedia.org/wiki/Transport', 'subjectScheme': 'url'}]",,
+10.5281/zenodo.4543130,JEts through VEegetation in a Rotating Basin,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Contaminants, nutrients and sediment particles flow into inland and coastal water bodies often forming turbulent jets. The aim of the present project was to improve our capability to describe how jets interact with the environment in which they discharge, providing useful insights for possible mitigation of undesired and harmful impacts. We focus on the case of a jet interacting with porous obstructions, mimicking rigid vegetation or marine farms, under the effect of the Coriolis force, as is often the case with large scale rivers discharging into the sea. The experiments were carried out in the large scale facility 'Coriolis Platform' at LEGI Grenoble (FR), in the frame of the project ""H+-CNRS-06-JEVERB"" which received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 654110, HYDRALAB+. DETAILS ON DATA The dataset here provided is the result of the PIV system acquisition, used in the project at LEGI. The data format is 3D Matlab file '.mat'. Each file includes the 3D matrices of the measured velocities with size (314 x 295 x 1999) and the coordinate reference (X,Y). The third dimension is relative to time. The PIV sampling frequency is 33 Hz. The experiments and the procedure used for data processing are described in 'JEt interacting with VEgetation in a Rotating Basin', Proceedings of HYDRALAB+ Joint User Meeting, Bucharest, May 2019.",mds,True,findable,0,0,0,0,0,2021-02-16T13:09:01.000Z,2021-02-16T13:09:02.000Z,cern.zenodo,cern,Momentum jets; obstructions; rotating environment,[{'subject': 'Momentum jets; obstructions; rotating environment'}],,
+10.5281/zenodo.4964203,"FIGURES 5–8. Protonemura auberti. 5–6. male terminalia, ventral view. 7. male, paraproct median lobe with sclerotized stem. 8 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 5–8. Protonemura auberti. 5–6. male terminalia, ventral view. 7. male, paraproct median lobe with sclerotized stem. 8. male, paraproct outer lobe with trifurcated sclerite",mds,True,findable,0,0,7,0,0,2021-06-16T08:24:51.000Z,2021-06-16T08:24:52.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.10047691,preesm/preesm-apps: ACM TRETS Artifact Evaluation,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,"Release for ACM TRETS Artifact Evaluation.
+https://dl.acm.org/doi/10.1145/3626103",api,True,findable,0,0,0,1,0,2023-10-27T13:56:35.000Z,2023-10-27T13:56:35.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10067270,yt-project/unyt: v3.0.1,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,"What's Changed
+
+
+
+Update readthedocs python and ubuntuversion used by @jzuhone in https://github.com/yt-project/unyt/pull/461
+
+BUG: fix backward compatibility for calling np.histogram with implicit range units by @neutrinoceros in https://github.com/yt-project/unyt/pull/466
+
+BUG: fix an issue where array functions would raise UnitConsistencyError on unyt arrays using non-default unit registries by @neutrinoceros in https://github.com/yt-project/unyt/pull/463
+
+TST: minimize build time in tox runs by @neutrinoceros in https://github.com/yt-project/unyt/pull/426
+
+BUG: fix an issue where array functions would crash (AttributeError) when passed non-ndarray array like objects (e.g. Python lists) by @neutrinoceros in https://github.com/yt-project/unyt/pull/464
+
+DOC: update pyenv commands in docs by @neutrinoceros in https://github.com/yt-project/unyt/pull/467
+
+Update history for v3.0.1 by @jzuhone in https://github.com/yt-project/unyt/pull/468
+
+
+Full Changelog: https://github.com/yt-project/unyt/compare/v3.0.0...v3.0.1",api,True,findable,0,0,0,0,0,2023-11-02T17:02:12.000Z,2023-11-02T17:02:12.000Z,cern.zenodo,cern,,,,
+10.34847/nkl.9bd4vqc6,"Figure 10 : Extraits vidéos ""Différences de cadrage""",NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,fr,Audiovisual,,"La captation de cette vidéo a eu lieu dans le cadre du projet FOCUS(E) financé par l'IDEX de l'Université Grenoble Alpes.
+Les participants (et les détenteurs de l'autorité parentale) ont consenti à la diffusion de leurs images dans le cadre exclusif du projet.",api,True,findable,0,0,0,0,0,2023-10-13T12:59:45.000Z,2023-10-13T12:59:45.000Z,inist.humanum,jbru,"enfant,méthode","[{'subject': 'enfant'}, {'subject': 'méthode'}]",['215322977 Bytes'],['video/quicktime']
+10.34847/nkl.bc2b1071,Bulletin franco-italien 1912 n°3 mai - juin,NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Book,,"1912/05 (A4,N3)-1912/06.",api,True,findable,0,0,0,0,0,2022-07-12T10:40:43.000Z,2022-07-12T10:40:43.000Z,inist.humanum,jbru,"Etudes Italiennes,Etudes italiennes","[{'subject': 'Etudes Italiennes'}, {'subject': 'Etudes italiennes'}]","['6464874 Bytes', '21194044 Bytes', '20981389 Bytes', '21201160 Bytes', '21170605 Bytes', '21009112 Bytes', '21218584 Bytes', '21088960 Bytes', '21271426 Bytes', '21317947 Bytes', '21327454 Bytes', '21287920 Bytes', '21089296 Bytes', '21296776 Bytes', '21203305 Bytes', '21091444 Bytes', '21347104 Bytes']","['application/pdf', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff']"
+10.5281/zenodo.4498331,Results of ISMIP6 CMIP6 forced simulations: a multi-model ensemble of the Greenland and Antarctic ice sheet evolution over the 21st century,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This archive provides the ice sheet model outputs produced as part of the publication ""Payne et al. 2021 Future sea level change under CMIP5 and CMIP6 scenarios from the Greenland and Antarctic ice sheets"", published in GRL Contact: Tony Payne a.j.payne@bristol.ac.uk, Sophie Nowicki sophien@buffalo.edu, ismip6@gmail.com <br> Further information on ISMIP6 can be found here:<br> http://www.climate-cryosphere.org/activities/targeted/ismip6<br> http://www.climate-cryosphere.org/wiki/index.php?title=ISMIP6-Projections-Antarctica<br> http://www.climate-cryosphere.org/wiki/index.php?title=ISMIP6-Projections-Greenland Data usage notice:<br> If you use any of these results, please acknowledge the work of the people involved in the process producing this data set. Acknowledgements should have language similar to the below (if you only use CMIP5 forcing, remove CMIP6 and vice versa). “We thank the Climate and Cryosphere (CliC) effort, which provided support for ISMIP6 through sponsoring of workshops, hosting the ISMIP6 website and wiki, and promoted ISMIP6. We acknowledge the World Climate Research Programme, which, through it's Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the CMIP data and providing access, the University at Buffalo for ISMIP6 data distribution and upload, and the multiple funding agencies who support CMIP5 and CMIP6 and ESGF. We thank the ISMIP6 steering committee, the ISMIP6 model selection group and ISMIP6 dataset preparation group for their continuous engagement in defining ISMIP6."" You should also refer to and cite the following papers: For Greenland datasets Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andy Shepherd, Erika Simon, Cecile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald Slater, Robin Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6 , The Cryosphere, 2020. doi:10.5194/tc-2019-319 Slater, D. A., Felikson, D., Straneo, F., Goelzer, H., Little, C. M., Morlighem, M., Fettweis, X., and Nowicki, S.: Twenty-first century ocean forcing of the Greenland ice sheet for modelling of sea level contribution , The Cryosphere, 14, 985–1008, https://doi.org/10.5194/tc-14-985-2020, 2020. Sophie Nowicki, Antony Payne, Heiko Goelzer, Helene Seroussi, William Lipscomb, Ayako Abe-Ouchi, Cecile Agosta, Patrick Alexander, Xylar Asay-Davis, Alice Barthel, Thomas Bracegirdle, Richard Cullather, Denis Felikson, Xavier Fettweis, Jonathan Gregory, Tore Hatterman, Nicolas Jourdain, Peter Kuipers Munneke, Eric Larour, Christopher Little, Mathieu Morlinghem, Isabel Nias, Andrew Shepherd, Erika Simon, Donald Slater, Robin Smith, Fiammetta Straneo, Luke Trusel, Michiel van den Broeke, and Roderik van de Wal: <br> Experimental protocol for sea level projections from ISMIP6 standalone ice sheet models, The Cryosphere, doi:10.5194/tc-2019-322, 2020. For Antarctica datasets Seroussi, H., Nowicki, S., Simon, E., Abe-Ouchi, A., Albrecht, T., Brondex, J., Cornford, S., Dumas, C., Gillet-Chaulet, F., Goelzer, H., Golledge, N. R., Gregory, J. M., Greve, R., Hoffman, M. J., Humbert, A., Huybrechts, P., Kleiner, T., Larour, E., Leguy, G., Lipscomb, W. H., Lowry, D., Mengel, M., Morlighem, M., Pattyn, F., Payne, A. J., Pollard, D., Price, S. F., Quiquet, A., Reerink, T. J., Reese, R., Rodehacke, C. B., Schlegel, N.-J., Shepherd, A., Sun, S., Sutter, J., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., and Zhang, T.: initMIP-Antarctica: an ice sheet model initialization experiment of ISMIP6, The Cryosphere, 13, 1441–1471, https://doi.org/10.5194/tc-13-1441-2019, 2019. Jourdain, N. C., Asay-Davis, X., Hattermann, T., Straneo, F., Seroussi, H., Little, C. M., and Nowicki, S.: A protocol for calculating basal melt rates in the ISMIP6 Antarctic ice sheet projections, The Cryosphere, 14, 3111–3134, https://doi.org/10.5194/tc-14-3111-2020, 2020. <br> Sophie Nowicki, Antony Payne, Heiko Goelzer, Helene Seroussi, William Lipscomb, Ayako Abe-Ouchi, Cecile Agosta, Patrick Alexander, Xylar Asay-Davis, Alice Barthel, Thomas Bracegirdle, Richard Cullather, Denis Felikson, Xavier Fettweis, Jonathan Gregory, Tore Hatterman, Nicolas Jourdain, Peter Kuipers Munneke, Eric Larour, Christopher Little, Mathieu Morlinghem, Isabel Nias, Andrew Shepherd, Erika Simon, Donald Slater, Robin Smith, Fiammetta Straneo, Luke Trusel, Michiel van den Broeke, and Roderik van de Wal: Experimental protocol for sea level projections from ISMIP6 standalone ice sheet models, The Cryosphere, doi:10.5194/tc-2019-322, 2020.",mds,True,findable,0,0,0,0,0,2021-02-03T16:01:49.000Z,2021-02-03T16:01:49.000Z,cern.zenodo,cern,"ISMIP6, Greenland, Antarctica, CMIP","[{'subject': 'ISMIP6, Greenland, Antarctica, CMIP'}]",,
+10.5281/zenodo.7495559,Acetaldehyde binding energies: a coupled experimental and theoretical study,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",CRYSTAL17 output files of the atomic structures used in the related publication,mds,True,findable,0,0,0,0,0,2022-12-30T20:34:37.000Z,2022-12-30T20:34:37.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10037888,Pooch v1.8.0: A friend to fetch your data files,Zenodo,2023,,Software,"BSD 3-Clause ""New"" or ""Revised"" License","Does your Python package include sample datasets? Are you shipping them with the code? Are they getting too big?
+
+
+Pooch is here to help! It will manage a data registry by downloading your data files from a server only when needed and storing them locally in a data cache (a folder on your computer).
+
+
+Here are Pooch's main features:
+
+
+
+
+Pure Python and minimal dependencies.
+
+Download a file only if necessary (it's not in the data cache or needs to be updated).
+
+Verify download integrity through SHA256 hashes (also used to check if a file needs to be updated).
+
+Designed to be extended: plug in custom download (FTP, scp, etc) and post-processing (unzip, decompress, rename) functions.
+
+Includes utilities to unzip/decompress the data upon download to save loading time.
+
+Can handle basic HTTP authentication (for servers that require a login) and printing download progress bars.
+
+Easily set up an environment variable to overwrite the data cache location.
+
+
+
+Are you a scientist or researcher? Pooch can help you too!
+
+
+
+
+Automatically download your data files so you don't have to keep them in your GitHub repository.
+
+Make sure everyone running the code has the same version of the data files (enforced through the SHA256 hashes).
+
+
+
+Pooch v0.7.1 was reviewed at the Journal of Open Source Software: https://github.com/openjournals/joss-reviews/issues/1943
+
+
+Documentation: https://www.fatiando.org/pooch
+
+
+Source code: https://github.com/fatiando/pooch
+
+
+Part of the Fatiando a Terra project.
+
+
+Note: Authors are listed in alphabetical order by last name.",api,True,findable,0,0,0,0,0,2023-10-24T17:27:36.000Z,2023-10-24T17:27:36.000Z,cern.zenodo,cern,Python,[{'subject': 'Python'}],,
+10.6084/m9.figshare.21430977,Additional file 3 of Digitally-supported patient-centered asynchronous outpatient follow-up in rheumatoid arthritis - an explorative qualitative study,figshare,2022,,Text,Creative Commons Attribution 4.0 International,Supplementary Material 3,mds,True,findable,0,0,0,0,0,2022-10-29T03:17:16.000Z,2022-10-29T03:17:16.000Z,figshare.ars,otjm,"Medicine,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['493283 Bytes'],
+10.34929/xttd-nb60,Faire l'Europe par la culture ,Editions et presses universitaires de Reims,2021,fr,Text,Creative Commons Attribution Non Commercial 4.0 International,"The European Union is a unique institutional construction in history. Built and enlarged slowly and peacefully, with the aim of reconciling sworn enemies after two terrible wars by means of an economic alliance designed to create a lasting human understanding, it is today much more than a simple free trade area. What about European culture? How does it relate to the continent's economic and political integration projects? Constantly under development, constantly questioned, even contested, European culture is the subject of the studies gathered in this volume.",fabricaForm,True,findable,0,0,0,0,0,2022-04-26T13:53:48.000Z,2022-04-26T13:53:49.000Z,inist.epure,vcob,FOS: Humanities,"[{'subject': 'FOS: Humanities', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['350 pages'],['PDF']
+10.5281/zenodo.7464081,"Open data for ""Programmable frequency-bin quantum states in a nano-engineered silicon device""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The folder includes includes the raw data that were used for generation of all Figures in the paper ""Programmable frequency-bin quantum states in a nano-engineered silicon device"".",mds,True,findable,0,0,0,0,0,2022-12-20T15:03:11.000Z,2022-12-20T15:03:12.000Z,cern.zenodo,cern,"Quantum Optics,Quantum Photonics,Integrated Optics,Frequency-bin entanglement,Quantum Technologies","[{'subject': 'Quantum Optics'}, {'subject': 'Quantum Photonics'}, {'subject': 'Integrated Optics'}, {'subject': 'Frequency-bin entanglement'}, {'subject': 'Quantum Technologies'}]",,
+10.5281/zenodo.8265979,Code Artifact: Rebasing Microarchitectural Research with Industry Traces,Zenodo,2023,,Software,Apache License 2.0,"Code Artifact of the paper ""Rebasing Microarchitectural Research with Industry Traces"", published at the 2023 IEEE International Symposium on Workload Characterization. It includes the proposed cvp2champsim converter and the two versions of ChampSim used to evaluate the converted traces.
+Note: the improved converted traces used in the paper are available at https://doi.org/10.5281/zenodo.10199624.
+Abstract:Â Microarchitecture research relies on performance models with various degrees of accuracy and speed. In the past few years, one such model, ChampSim, has started to gain significant traction by coupling ease of use with a reasonable level of detail and simulation speed. At the same time, datacenter class workloads, which are not trivial to set up and benchmark, have become easier to study via the release of hundreds of industry traces following the first Championship Value Prediction (CVP-1) in 2018. A tool was quickly created to port the CVP-1 traces to the ChampSim format, which, as a result, have been used in many recent works. We revisit this conversion tool and find that several key aspects of the CVP-1 traces are not preserved by the conversion. We therefore propose an improved converter that addresses most conversion issues as well as patches known limitations of the CVP-1 traces themselves. We evaluate the impact of our changes on two commits of ChampSim, with one used for the first Instruction Championship Prefetching (IPC-1) in 2020. We find that the performance variation stemming from higher accuracy conversion is significant.",mds,True,findable,0,0,0,0,0,2023-08-23T10:18:09.000Z,2023-08-23T10:18:09.000Z,cern.zenodo,cern,"ChampSim,CVP-1 traces","[{'subject': 'ChampSim'}, {'subject': 'CVP-1 traces'}]",,
+10.5281/zenodo.7982048,"FIGURES C1–C6 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,Open Access,"FIGURES C1–C6. Leuctra signifera, adult male (Austria, Gutenstein Alps, Urgersbachtal). C1, dorsal view; C2, lateral view; C3, stylus and specillum, lateral view; C4, dorsal view; C5, dorsal view; C6, ventral view with vesicle",mds,True,findable,0,0,0,0,0,2023-05-29T13:43:50.000Z,2023-05-29T13:43:50.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.6084/m9.figshare.c.6579520,Early management of isolated severe traumatic brain injury patients in a hospital without neurosurgical capabilities: a consensus and clinical recommendations of the World Society of Emergency Surgery (WSES),figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Severe traumatic brain-injured (TBI) patients should be primarily admitted to a hub trauma center (hospital with neurosurgical capabilities) to allow immediate delivery of appropriate care in a specialized environment. Sometimes, severe TBI patients are admitted to a spoke hospital (hospital without neurosurgical capabilities), and scarce data are available regarding the optimal management of severe isolated TBI patients who do not have immediate access to neurosurgical care. Methods A multidisciplinary consensus panel composed of 41 physicians selected for their established clinical and scientific expertise in the acute management of TBI patients with different specializations (anesthesia/intensive care, neurocritical care, acute care surgery, neurosurgery and neuroradiology) was established. The consensus was endorsed by the World Society of Emergency Surgery, and a modified Delphi approach was adopted. Results A total of 28 statements were proposed and discussed. Consensus was reached on 22 strong recommendations and 3 weak recommendations. In three cases, where consensus was not reached, no recommendation was provided. Conclusions This consensus provides practical recommendations to support clinician’s decision making in the management of isolated severe TBI patients in centers without neurosurgical capabilities and during transfer to a hub center.",mds,True,findable,0,0,0,0,0,2023-04-13T10:34:19.000Z,2023-04-13T10:34:20.000Z,figshare.ars,otjm,"Medicine,Genetics,FOS: Biological sciences,Molecular Biology,Ecology,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Ecology'}, {'subject': 'Science Policy'}]",,
+10.5281/zenodo.5564457,Tailored nano-columnar La2NiO4 cathodes for improved electrode performance,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","La<sub>2</sub>NiO<sub>4</sub> is a promising cathode material for intermediate and low temperature solid oxide cell applications, due to good electronic and ionic conductivity and high oxygen exchange activity with a low activation energy. Oxygen incorporation and transport in La<sub>2</sub>NiO<sub>4 </sub>(LNO) thin films is limited by surface reactions. Hence, tailoring the morphology is expected to lead to an overall improvement of electrode performance. We report on the growth of to nano-architectured La<sub>2</sub>NiO<sub>4</sub> thin film electrodes by PI-MOCVD, achieving vertically gapped columns with multi-fold active surface area, leading to faster oxygen exchange. This nano-rod structure is rooted in a dense bottom layer serving as good electronic and ionic conduction pathway. The microstructure is tuned by modification of the growth temperature and characterised by SEM, TEM and XRD. We studied the effect of surface activity by electrical conductivity relaxation measurements in fully dense and columnar-structured La<sub>2</sub>NiO<sub>4</sub> thin films of various thicknesses on single crystal substrates. Our results indicate that the increased surface area, in combination with the opening of different surface terminations, leads to a significant enhancment of the total exchange activity in columnar structured films.",mds,True,findable,0,0,0,0,0,2021-12-14T13:21:27.000Z,2021-12-14T13:21:28.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6405782,Automatic affective reactions to physical effort,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset for the study titled ""automatic affective responses during physical effort: a virtual reality study"". This dataset includes: <strong>1) A codebook (including the name of the main variables)</strong> --> ""code_book_affect_effort.xlsx"" <strong>2) Behavioral data (raw)</strong> --> in the folder ""data_ps_VR"". The raw data are added for transparency, but are not necessary to run the models. <strong>3) Self-reported data (raw)</strong> --> ""20220112_VR_expe.xlsx"" --> ""20220112_VR_pilot.xlsx"" The raw data are added for transparency, but are not necessary to run the models. <strong>4) clean data ready to used for the statistical analyses</strong> --> ""data_VR_all_clean.csv"". This clean data are produced by the R script. These data included the self-reported and the behavioral measures. <strong>5) R script for the data management (i.e., from the raw data to data ready to be analyzed)</strong> --> ""data_management_effort.R"" to create the dataset (return the file: ""data_VR_all_clean.RData"") <strong>6) R script for the models tested</strong> --> ""Data_mixed_effects_models.R"" for the models tested in the paper <strong>7) The video of the experiment</strong>",mds,True,findable,0,0,0,0,0,2022-04-01T11:17:14.000Z,2022-04-01T11:17:15.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4302473,Alternative architecture of the E. coli chemosensory array.,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","We present molecular models for extended patches of the <em>E. coli</em> chemosensory array. The models display either the canonical p6-symmetric architecture or an alternative p2-symmetric architecture recently observed in <em>E. coli</em> minicells. For more information, please see the associated BioRxiv preprint. Questions regarding the coordinates may be directed to Keith Cassidy (keith.cassidy@bioch.ox.ac.uk).",mds,True,findable,0,0,0,0,0,2020-12-06T13:52:06.000Z,2020-12-06T13:52:07.000Z,cern.zenodo,cern,"bacterial chemotaxis,chemosensory array","[{'subject': 'bacterial chemotaxis'}, {'subject': 'chemosensory array'}]",,
+10.7280/d1b114,"Dataset for: Fast retreat of Pope, Smith, and Kohler glaciers in West Antarctica observed by satellite interferometry",Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Pope, Smith, and Kohler glaciers, in the Amundsen Sea Embayment of West Antarctica, have experienced enhanced ocean-induced ice-shelf melt, glacier acceleration, ice thinning, and grounding line retreat in the past thirty years, in a glaciological setting with retrograde bedrock slopes conducive to marine ice sheet instability. Here we present observations of the grounding line retreat of these glaciers since 2014 using a constellation of interferometric radar satellites with a short revisit cycle combined with precision surface elevation data. We find that the glacier grounding lines develop spatially-variable, km-sized, tidally-induced migration zones. After correction for tidal effects, we detect a sustained pattern of retreat coincident with high melt rates of un-grounded ice, marked by episodes of more rapid retreat. In 2017, Pope Glacier retreated 3.5 km in 3.6 months, or 11.7 km/yr. In 2016-2018, Smith West retreated at 2 km/yr and Kohler at 1.3 km/yr. While the retreat slowed down in 2018-2020, these retreat rates are faster than anticipated by numerical models on yearly time scales. We hypothesize that the rapid retreat is caused by un-represented, vigorous ice-ocean interactions acting within newly-formed cavities at the ice-ocean boundary.",mds,True,findable,993,97,0,0,0,2021-11-01T23:46:08.000Z,2021-11-01T23:46:09.000Z,dryad.dryad,dryad,"FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences","[{'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['2646545672 bytes'],
+10.57726/9782919732890,Les remontées mécaniques et le droit,Presses Universitaires Savoie Mont Blanc,2019,fr,Book,,,fabricaForm,True,findable,0,0,0,0,0,2022-03-04T15:01:42.000Z,2022-03-04T15:02:03.000Z,pusmb.prod,pusmb,FOS: Law,"[{'subject': 'FOS: Law', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['496 pages'],
+10.5061/dryad.6t1g1jx0m,Adaptive potential of Coffea canephora from Uganda in response to climate change,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Understanding vulnerabilities of plant populations to climate change could help preserve their biodiversity and reveal new elite parents for future breeding programs. To this end, landscape genomics is a useful approach for assessing putative adaptations to future climatic conditions, especially in long-lived species such as trees. We conducted a population genomics study of 207 Coffea canephora trees from seven forests along different climate gradients in Uganda. For this, we sequenced 323 candidate genes involved in key metabolic and defense pathways in coffee. Seventy-one SNPs were found to be significantly associated with bioclimatic variables, and were thereby considered as putatively adaptive loci. These SNPs were linked to key candidate genes, including transcription factors, like DREB-like and MYB family genes controlling plant responses to abiotic stresses, as well as other genes of organoleptic interest, like the DXMT gene involved in caffeine biosynthesis and a putative pest repellent. These climate-associated genetic markers were used to compute genetic offsets, predicting population responses to future climatic conditions based on local climate change forecasts. Using these measures of maladaptation to future conditions, substantial levels of genetic differentiation between present and future diversity were estimated for all populations and scenarios considered. The populations from the forests Zoka and Budongo, in the northernmost zone of Uganda, appeared to have the lowest genetic offsets under all predicted climate change patterns, while populations from Kalangala and Mabira, in the Lake Victoria region, exhibited the highest genetic offsets. The potential of these findings in terms of ex-situ conservation strategies are discussed.",mds,True,findable,322,27,0,1,0,2022-01-31T07:37:46.000Z,2022-01-31T07:37:47.000Z,dryad.dryad,dryad,"Climate change,Conservation genetics,Landscape genetics,Agriculture","[{'subject': 'Climate change', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Conservation genetics', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Landscape genetics'}, {'subject': 'Agriculture', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['2563202 bytes'],
+10.5281/zenodo.6303309,Structural Defects Improve the Memristive Characteristics of Epitaxial La0.8Sr0.2MnO3-based Devices,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data files (.txt) of the data presented in the publication 10.1002/admi.202200498 File names are referred to as the reference of the Figure and number in the main manuscript, followed by the sample (LSM/STO or LSM/LAO) and keywords of the figure. Each file corresponds only to the data of one sample. Regarding the series in a Figure, in the case there is very little data, the series are in a single file, arranged in columns. Otherwise, the series with large amounts of data have been split into single files named according to the series (legend). All the files include two headers (Name and Units) for each column. The files containing data from multiple series contain an extra header to precise the data series.",mds,True,findable,0,0,0,0,0,2022-08-24T15:16:09.000Z,2022-08-24T15:16:10.000Z,cern.zenodo,cern,"epitaxial thin films,manganites,memristive devices,metal-organic chemical vapor deposition (MOCVD),resistive switching,structural defects,valence change memories (VCMs)","[{'subject': 'epitaxial thin films'}, {'subject': 'manganites'}, {'subject': 'memristive devices'}, {'subject': 'metal-organic chemical vapor deposition (MOCVD)'}, {'subject': 'resistive switching'}, {'subject': 'structural defects'}, {'subject': 'valence change memories (VCMs)'}]",,
+10.5281/zenodo.3135479,Fast and Faithful Performance Prediction of MPI applications: the HPL use case study (experiment artifact),Zenodo,2019,en,Other,"MIT License,Open Access",Artifact repository for the article Fast and Faithful Performance Prediction of MPI applications: the HPL use case study.,mds,True,findable,0,0,0,0,0,2019-05-22T08:58:00.000Z,2019-05-22T08:58:01.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4724109,Restoring the strange metal phase via suppression of charge density waves in an underdoped cuprate superconductor,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","[This repository contains the raw data for the manuscript ""<strong>Restoring the strange metal phase via suppression of charge density waves in an underdoped cuprate superconductor</strong>"" (arXiv:2009.08398)] The normal state of cuprates is dominated by the “strange metal†phase that, near optimal doping, shows a linear temperature dependence of the resistivity persisting down to the lowest <em>T</em>, when superconductivity is suppressed. For underdoped cuprates this behavior is lost below the pseudogap temperature <em>T</em>*, where Charge Density Waves (CDW) together with other intertwined local orders characterize the ground state. Here we show that the <em>T</em>-linear resistivity of highly strained, ultrathin and underdoped YBa<sub>2</sub>Cu<sub>3</sub>O<sub>7-δ</sub> films is restored when the CDW amplitude, detected by Resonant Inelastic X-ray scattering, is suppressed. This observation points towards an intimate connection between the onset of CDW and the departure from <em>T</em>-linear resistivity in underdoped cuprates, a link that was missing until now. It also illustrates the potentiality of strain control to manipulate the ground state of quantum materials.",mds,True,findable,0,0,0,0,0,2021-04-27T22:58:24.000Z,2021-04-27T22:58:25.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4059193,CNRM-ARPEGE v6.2.4 contribution to Antarctic Cordex,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This data set is a contribution to Antarctic Polar Cordex using the stretched grid capacity of CNRM-ARPEGE atmospheric GCM. Model outputs have been interpolated from the native ARPEGE grid, with horizontal resolution varying between 35kms (near the stretching pole) to 45 kms on the Antarctic continent, to the ANTi-44 domain (actual lon/lat). The data and metadata format respect almost all of Cordex/CMIP conventions (variables names, units, file names...). The data set consists in six simulations of 30 years time slots : 1981-2010 for ""historical"" simulations and 2071-2100 for future projections using radiative forcing from RCP8.5 scenario : - ARP-AMIP : amip-style control run driven by observed SST and sea-ice (1981-2100) - ARP-NOR-OC : Future projection driven by NorESM1-M RCP8.5 climate change signal on SST and sea-ice (2071-2100) - ARP-MIR-OC : Future projection driven by MIROC-ESM RCP8.5 climate change signal on SST and sea-ice (2071-2100) More details on these three simulations are given in Beaumet et al., 2019 (<strong>10.5194/tc-13-3023-2019) </strong> - ARP-AMIP-AC : Driven by observed SST and sea-ice + run-time flux bias correction* - ARP-NOR-AOC : Driven by same SST and sea-ice as NOR-OC + run-time flux bias correction* - ARP-MIR-AOC : Driven by same SST and sea-ice as MIR-OC + run-time flux bias correction* Empirical run-time bias correction uses correction terms derived from the climatological mean of tendency errors of a simulation nudged towards climate reanalysis (here ERA-Interim). The method is presented first in Guldberg et al., 2005 (10.1111/j.1600-0870.2005.00120.x) and Krinner et al., 2019 (10.1029/2018MS001438). The method applied with ARPEGE over Antarctica and the evalution of the simulation are presented in this paper : https://doi.org/10.5194/tc-2020-307 (In review) Outputs are available at daily time scale for near-surface atmospherique mean (tas), min (tasmin) and max (tasmax) temperature, total precipitation (pr), snowfall (prsn), snowmelt(snm), surface snow sublimation (sbl_i) and surface runoff (mrros). If you consider using these data, please email me (Julien.Beaumet@univ-grenoble-alpes.fr) to see how I can help and/or be involved.",mds,True,findable,0,0,0,0,0,2020-09-30T14:02:31.000Z,2020-09-30T14:02:31.000Z,cern.zenodo,cern,"Antarctic,Cordex,ARPEGE,Climate projection,Surface mass balance,Bias correction","[{'subject': 'Antarctic'}, {'subject': 'Cordex'}, {'subject': 'ARPEGE'}, {'subject': 'Climate projection'}, {'subject': 'Surface mass balance'}, {'subject': 'Bias correction'}]",,
+10.5281/zenodo.6902628,"Exoplanet imaging data challenge, phase 2",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Datasets for the second phase of the Exoplanet Imaging Data Challenge</strong> (https://exoplanet-imaging-challenge.github.io). The second phase of the Exoplanet Imaging Data Challenge is focused on the characterisation of exoplanet signals in high-contrast imaging data. The participants must perform two tasks: provide (1) astrometry of the detected signals, and (2) spectrophotometry of the detected signals. For this phase, we therefore provide with <strong>8</strong> high-contrast data sets, taken with two integral field spectrographs: SPHERE-IFS installed at the Very Large Telescope (VLT, Chile) and GPI installed at the Gemini-South telescope (Chile). Each data set consists of the following files (in <em>.fits</em> format): (a) <em>image_cube_instxx.fits</em>: the coronagraphic multispectral image cube, acquired in pupil-stabilized mode;<br> (b) <em>parallactic_angles_instxx.fits</em>: the corresponding parallactic angle and airmass variation during the observation sequence;<br> (c) <em>wavelength_vect_instxx.fits</em>: the corresponding wavelength vector for each spectral channel;<br> (d) <em>psf_cube_instxx.fits</em>: the non-coronagraphic (point spread function) multispectral image of the target star;<br> (e) <em>first_guess_astrometry_instxx.fits</em>: a first guess position w.r.t the star of the (2 or 3) injected planetary signals. Each data set has 2 to 3 injected planetary signals in various locations.<br> Each data set has very different observing conditions, from very good to very bad. <em>Additional information and ressources can be found on the website and dedicated Github repository.</em> <em>The results of the data challenge must be submitted directly by participants on the EvalAI platform.</em>",mds,True,findable,0,0,0,0,0,2022-07-25T15:56:47.000Z,2022-07-25T15:56:48.000Z,cern.zenodo,cern,"Exoplanet Data Challenge,Exoplanet imaging,High contrast imaging","[{'subject': 'Exoplanet Data Challenge'}, {'subject': 'Exoplanet imaging'}, {'subject': 'High contrast imaging'}]",,
+10.5281/zenodo.8082768,Polar atmospheric and aerosol river detection catalogs,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These detection catalogs of atmospheric and aerosol rivers were created for the publication <em>Lapere et al., ""Polar aerosol atmospheric rivers: detection, characteristics and potential applications"", Journal of Geophysical Research, Submitted</em>. The associated methodology is described in this publication. They provide binary detection of Atmospheric river (AR), Black carbon aerosol atmospheric river (BC_AER), Dust aerosol atmospheric river (DU_AER), Sea salt aerosol atmospheric river (SS_AER) and Organic carbon aerosol atmospheric river (OC_AER), in NetCDF format, for the period 1980-2022, with a 3-hour time resolution and 1x1° spatial resolution, for the regions 30°-90°N (indicated by the suffix ""NH"") and 30°-90°S (indicated by the suffix ""SH""). The code for pre-processing raw MERRA2 data, along with the detection algorithm are also provided here as Python Jupyter notebooks.",mds,True,findable,0,0,0,0,0,2023-07-07T14:41:15.000Z,2023-07-07T14:41:15.000Z,cern.zenodo,cern,"Aerosol river,Atmospheric river","[{'subject': 'Aerosol river'}, {'subject': 'Atmospheric river'}]",,
+10.5281/zenodo.7558920,Modelling deep rooting thrusted mechanism of crustal thickening for Eastern Tibet,Zenodo,2023,,Software,"Creative Commons Attribution 4.0 International,Open Access",This is the FEM code that was used to produce all results in the publication.,mds,True,findable,0,0,0,0,0,2023-01-22T17:12:28.000Z,2023-01-22T17:12:29.000Z,cern.zenodo,cern,geodynamics,[{'subject': 'geodynamics'}],,
+10.5281/zenodo.59144,fflas-ffpack: fflas-ffpack-2.2.2,Zenodo,2016,,Software,Open Access,FFLAS-FFPACK - Finite Field Linear Algebra Subroutines / Package,mds,True,findable,0,0,1,0,0,2016-07-30T18:21:24.000Z,2016-07-30T18:21:25.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5243362,Turkish DBnary archive in original Lemon format,Zenodo,2021,tr,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Turkish language edition, ranging from 8th July 2013 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry. <br>",mds,True,findable,0,0,0,0,0,2021-08-24T11:52:51.000Z,2021-08-24T11:52:52.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.3898495,"Data Accompanying ""Fracturing process of concrete under uniaxial and triaxial compression: insights from in-situ x-ray mechanical tests""",Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These are the datasets analysed in ""Fracturing process of concrete under uniaxial and triaxial compression: insights from <em>in-situ</em> x-ray mechanical tests"" by Stamati <em>et. al.</em> (submitted on June 2020 in Cement and Concrete Research) The datasets contain the reconstructed x-ray 3D images of selected tests and the corresponding DVC analysis. Note that details regarding the DVC analysis can be found in the paper. Each folder contains a separate test; uniaxial compression (""<em>C-02""</em>) and triaxial compression at 5MPa (""<em>TX5-01""</em>), 10MPa (""T<em>X10-01</em>"") and 15MPa (""<em>TX15-01</em>"") confining pressures. For each test, folder 01 contains the first scan, where 01 is the reference state for the DVC analyis. Folder 01 also contains the image of the labelled largest aggregates used for the discrete DVC. Folrders 02-XX contain the scans at intermediate loading steps and the corresponding DVC analysis; ""<em>reg</em>"" contains the registration result in downscaled 2-binning images. ""<em>ddic</em>"" contains the discrete DVC computation. ""<em>ldic</em>"" contains the local DVC computation, before and after the merge and filtering of the grid and discrete DVC fields. ""<em>strains</em>"" contains the strain fields coming from the corrected merged DVC field. Folder ""<em>stressStrain</em>"" contains the stress-strain curves measured during the tests after subtracting the displacement corresponding to the loading system. Folder ""<em>doubleScanUniaxial</em>"" contains the two reconstructed images of the ""repeated scan"" of the uniaxial tests, from which the DVC measurement uncertainties were evaluated.",mds,True,findable,20,0,0,0,0,2020-06-18T09:48:30.000Z,2020-06-18T09:48:31.000Z,cern.zenodo,cern,"Concrete,Meso-scale,In-situ x-ray tests,Fracture process,Uniaxial compression,Triaxial compression,Digital Volume Correlation","[{'subject': 'Concrete'}, {'subject': 'Meso-scale'}, {'subject': 'In-situ x-ray tests'}, {'subject': 'Fracture process'}, {'subject': 'Uniaxial compression'}, {'subject': 'Triaxial compression'}, {'subject': 'Digital Volume Correlation'}]",,
+10.5281/zenodo.7982044,"FIGURES B7–B12. B7–B10 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,Open Access,"FIGURES B7–B12. B7–B10. Leuctra austriaca, adult female (Austria, Gutenstein Alps, Urgersbachtal). B7, ventral view; B8, ventral view; B9, lateral view; B10, lateral view. B11–B12. Leuctra austriaca, adult male and female (Hungary). B11, adult male, dorsal view; B12, female, lateral view.",mds,True,findable,0,0,0,5,0,2023-05-29T13:43:40.000Z,2023-05-29T13:43:40.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.3941003,Program Code: Structure-dependence of the atomic-scale mechanisms of Pt electrooxidation and dissolution,Zenodo,2020,en,Software,"MIT License,Open Access","<strong>Abstract:</strong> Platinum dissolution and restructuring due to surface oxidation are primary degradation mechanisms that limit the lifetime of Pt-based electrocatalysts for electrochemical energy conversion. Here, we studied well-defined Pt(100) and Pt(111) electrode surfaces by in situ high-energy surface X-ray diffraction, on-line inductively coupled plasma mass spectrometry, and density functional theory calculations, to elucidate the atomic-scale mechanisms of these processes. The locations of the extracted Pt atoms after Pt(100) oxidation reveal distinct differences from the Pt(111) case, which explains the different surface stability. The evolution of a specific stripe oxide structure on Pt(100) produces unstable surface atoms which are prone to dissolution and restructuring, leading to one order of magnitude higher dissolution rates. <strong>Contents of this repository:</strong> The custom CTR calculation software datautils. The software is written in python and has dependencies, which are stated in the requirements.txt file. Using pip you should be able to easily install the package using <pre><code>pip install .</code></pre> inside the root directory of the package. This should also handle all requirements. An example for a CTR fit is given in the jupyter notebook in the example folder. The binoculars backend for the HESXRD data extraction.",mds,True,findable,0,0,1,0,0,2020-07-12T15:37:54.000Z,2020-07-12T15:37:55.000Z,cern.zenodo,cern,"Catalyst,Electrochemistry,Chemistry,Stability,X-ray Diffraction,Density Functional Theory,CTR,Platinum","[{'subject': 'Catalyst'}, {'subject': 'Electrochemistry'}, {'subject': 'Chemistry'}, {'subject': 'Stability'}, {'subject': 'X-ray Diffraction'}, {'subject': 'Density Functional Theory'}, {'subject': 'CTR'}, {'subject': 'Platinum'}]",,
+10.5281/zenodo.4765855,"Fig. 1 in A New Stonefly From Lebanon, Leuctra Cedrus Sp. N. (Plecoptera: Leuctridae)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 1. Map of Lebanon, with the collecting sites for Leuctra cedrus sp. n.",mds,True,findable,0,0,2,0,0,2021-05-16T16:24:27.000Z,2021-05-16T16:24:27.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.7785223,Automatic 3D CAD models reconstruction from 2D orthographic drawings,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset is built to reconstruct 3D CAD models from 2D drawings and is based on the public dataset Fusion 360 gallery. The dataset includes two parts that are the original data and the reconstructed data (in folders '/original_data"" and '/reconstructed'). The part of the original data contains the '.svg' files of 2D drawings and the '.step' files of CAD models. Our reconstruction results are shown in the second part (folder '/reconstructed'), which includes the reconstructed 3D wireframes, 3D shapes with faces (storage in FreeCAD files '.FCStd'), and the images of reconstructed models (screenshot). We also test some cases from the ABC dataset, shown in the 2_ABC folder. Please cite our paper if you use the dataset. <pre>@article{zhang2023automatic, title={Automatic 3D CAD models reconstruction from 2D orthographic drawings}, author={Zhang, Chao and Pinqui{\'e}, Romain and Polette, Arnaud and Carasi, Gregorio and De Charnace, Henri and Pernot, Jean-Philippe}, journal={Computers \& Graphics}, year={2023}, publisher={Elsevier} }</pre>",mds,True,findable,0,0,0,0,0,2023-03-30T14:44:34.000Z,2023-03-30T14:44:34.000Z,cern.zenodo,cern,3D reconstruction; CAD,[{'subject': '3D reconstruction; CAD'}],,
+10.5281/zenodo.1009126,Esa Seom-Ias – Spectroscopic Parameters Database 2.3 Μm Region,Zenodo,2017,,Dataset,"Creative Commons Attribution Share-Alike 4.0,Open Access","The database contains molecular absorption line parameters obtained within the framework of the esa project SEOM-IAS (Scientific Exploitation of Operational Missions - Improved Atmospheric Spectroscopy Databases), ESA/AO/1-7566/13/I-BG. Details on the project can be found at http://www.wdc.dlr.de/seom-ias/.
+
+FTS and CRDS measurements (performed at the German Aersopace Center (DLR) and at Université Grenoble Alpes) were analyzed in the spectral range 4190-4340 cm<sup>-1</sup> within the framework of the esa project SEOM-IAS resulting in an improved line parameter database of H<sub>2</sub>O, CH<sub>4</sub> and CO absorption lines according to the needs of the TROPOMI instrument aboard the Sentinel 5-P satellite. The parameters are compiled in three ASCII files, one for each molecule (CH4_sigma_S_air_broadening_Tdep_May17_V3.hit, H2O_May17_V3.hit, CO_Sep16.hit).",,True,findable,22,0,0,0,0,2017-10-11T15:09:40.000Z,2017-10-11T15:09:40.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4761311,"Figs. 29-30 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 29-30. Dictyogenus muranyii sp. n., male terminalia. 29. Hemitergal lobes, dorsal view. Karstic spring of Bruyant, Isère dpt, France. Photo B. Launay. 30. Hemitergal lobes, lateral view. Karstic spring of Bruyant, Isère dpt, France. Photo B. Launay.",mds,True,findable,0,0,6,0,0,2021-05-14T07:46:04.000Z,2021-05-14T07:46:05.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.6084/m9.figshare.24202753.v1,Additional file 3 of Obstructive sleep apnea: a major risk factor for COVID-19 encephalopathy?,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 3: Supplemental Table 3. Cerebrospinal fluid analyses at the time of COVID-19 acute encephalopathy.,mds,True,findable,0,0,0,0,0,2023-09-27T03:26:11.000Z,2023-09-27T03:26:11.000Z,figshare.ars,otjm,"Biophysics,Medicine,Cell Biology,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,Sociology,FOS: Sociology,Immunology,FOS: Clinical medicine,Cancer,Mental Health,Virology","[{'subject': 'Biophysics'}, {'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Mental Health'}, {'subject': 'Virology'}]",['19116 Bytes'],
+10.5281/zenodo.4804621,FIGURES 2–6 in Review and contribution to the stonefly (Insecta: Plecoptera) fauna of Azerbaijan,Zenodo,2021,,Image,Open Access,"FIGURES 2–6. Morphology of Leuctra fusca ssp. (Linnaeus, 1758) from the Talysh Mts—2: male terminalia, dorsal view; 3: male paraproct and specillum, lateral view; 4: same, ventrocaudal view; 5: female terminalia, ventral view, matured specimen; 6: same, young specimen—scale 0.5 mm.",mds,True,findable,0,0,3,0,0,2021-05-26T07:54:53.000Z,2021-05-26T07:54:55.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.61692,pddl4j: PDDL4J V3.5.0,Zenodo,2016,,Software,Open Access,Changes: Add a JSON adapter Update hsp to use JSON adapter Add String handler for domain an problem Add option to skip statistic computation Add encoder Junit test Update Javadoc Fix styling issues Remove to long and hudge memory usage tests Add auto plan validation for test using separate plan val,mds,True,findable,0,0,1,0,0,2016-09-07T08:59:29.000Z,2016-09-07T08:59:30.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4010153,I Sit But I Don't Know Why: Integrating Controlled And Automatic Motivational Precursors Within A Socioecological Approach To Predict Sedentary Behaviors,Zenodo,2020,,Dataset,Creative Commons Attribution 4.0 International,"This file contains the raw dataset analyzed.Â
+
+
+Sheet 1 contains scored variables.
+
+
+Sheet 2 presents a description of the variables. ",mds,True,findable,0,0,0,0,0,2020-09-01T07:15:48.000Z,2020-09-01T07:15:49.000Z,cern.zenodo,cern,,,,
+10.25364/19.2022.7.3,La comparaison dans Philandre (1544) Procédures figuratives en contexte narratif,Universität Graz,2022,fr,Text,Creative Commons Attribution 4.0 International,"La comparaison participe à l'élaboration des types de texte en s'adaptant aux contraintes formelles
+des genres et aux principes de la production des discours, qui évoluent dans le temps. Elle joue en
+l'occurrence plusieurs rôles dans l'élaboration des séquences narratives de Philandre, un roman de
+chevalerie composé par Jean des Gouttes et publié en 1544. Une double approche de linguistique
+textuelle et de stylistique historique permet d'identifier trois grandes procédures figuratives Ã
+l'oeuvre dans les énoncés comparatifs de ces passages, qui méritent une description et une analyse.
+La première consiste dans l'expression du haut degré des propriétés qui fondent la ressemblance, la
+seconde dans la recherche de précision dans l'identification de celles-ci et la troisième dans l'évaluation
+des éléments rapprochés et de l'acte de comparaison",fabricaForm,True,findable,0,0,0,0,0,2022-04-04T09:30:40.000Z,2022-04-04T09:30:41.000Z,ugraz.unipub,ugraz,,,,
+10.5281/zenodo.4760131,Fig. 12 in Contribution To The Knowledge Of The Capniidae (Plecoptera) Of Turkey.,Zenodo,2011,,Image,"Creative Commons Attribution 4.0 International,Open Access",Fig. 12. Distribution area of the Turkish Capniidae.,mds,True,findable,0,0,14,0,0,2021-05-14T04:30:07.000Z,2021-05-14T04:30:08.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Capniidae,Capnioneura,Capnia,Capnopsis","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Capniidae'}, {'subject': 'Capnioneura'}, {'subject': 'Capnia'}, {'subject': 'Capnopsis'}]",,
+10.5281/zenodo.1495070,Synthetically Spoken STAIR,Zenodo,2018,ja,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset consists of synthetically spoken captions for the STAIR dataset. Following the same methodology as Chrupała <em>et al.</em> (see article | dataset | code) we generated speech for each caption of the STAIR dataset using Google's Text-to-Speech API. This dataset was used for visually grounded speech experiments (see article accepted at ICASSP2019). <pre><code>@INPROCEEDINGS{8683069, author={W. N. {Havard} and J. {Chevrot} and L. {Besacier}}, booktitle={ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, title={Models of Visually Grounded Speech Signal Pay Attention to Nouns: A Bilingual Experiment on English and Japanese}, year={2019}, volume={}, number={}, pages={8618-8622}, keywords={information retrieval;natural language processing;neural nets;speech processing;word processing;artificial neural attention;human attention;monolingual models;part-of-speech tags;nouns;neural models;visually grounded speech signal;English language;Japanese language;word endings;cross-lingual speech-to-speech retrieval;grounded language learning;attention mechanism;cross-lingual speech retrieval;recurrent neural networks.}, doi={10.1109/ICASSP.2019.8683069}, ISSN={2379-190X}, month={May},}</code></pre> The dataset comprises the following files : <strong>mp3-stair.tar.gz</strong> :<strong> </strong>MP3 files of each caption in the STAIR dataset. Filenames have the following pattern <em>imageID_captionID</em>, where both <em>imageID</em> and <em>captionID </em>correspond to those provided in the original dataset (see annotation format here) <strong>dataset.mfcc.npy</strong> : Numpy array with MFCC vectors for each caption. MFCC were extracted using python_speech_features with default configuration. To know to which caption the MFCC vectors belong to, you can use the files dataset.words.txt and dataset.ids.txt. <strong>dataset.words.txt</strong> : Captions corresponding to each MFCC vector (line number = position in Numpy array, starting from 0) <strong>dataset.ids.txt </strong>: IDs of the captions (<em>imageID_captionID</em>) corresponding to each MFCC vector (line number = position in Numpy array, starting from 0) Splits test <strong>test.txt </strong>: captions comprising the test split <strong>test_ids.txt</strong>: IDs of the captions in the test split <strong>test_tagged.txt </strong>: tagged version of the test split <strong>test-alignments.json.zip </strong>: Forced alignments of all the captions in the test split. (dictionary where the key corresponds to the caption ID in the STAIR dataset). <em>Due to an unknown error during upload, the JSON file had to be zipped...</em> train <strong>train.txt </strong>: captions comprising the train split <strong>train_ids.txt </strong>: IDs of the captions in the train split <strong>train_tagged.txt </strong>: tagged version of the train split val <strong>val.txt </strong>: captions comprising the val split <strong>val_ids.txt </strong>: IDs of the captions in the val split <strong>val_tagged.txt </strong>: tagged version of the val split",mds,True,findable,2,0,0,0,0,2018-11-26T09:03:10.000Z,2018-11-26T09:03:11.000Z,cern.zenodo,cern,"mscoco,stair,speech,visually grounded speech","[{'subject': 'mscoco'}, {'subject': 'stair'}, {'subject': 'speech'}, {'subject': 'visually grounded speech'}]",,
+10.5281/zenodo.5109574,Snow cover in the European Alps: Station observations of snow depth and depth of snowfall,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Auxiliary files, code, and data for paper published in The Cryosphere: Observed snow depth trends in the European Alps 1971 to 2019 https://doi.org/10.5194/tc-15-1343-2021 <strong>Auxiliary files:</strong> aux_paper.zip: Auxiliary figures to the paper (time series showing the consistency of averaging monthly mean snow depth of stations within 500 m elevation bins; times of seasonal snow depth and snow cover duration indices). aux_paper_crocus_comparison.zip: Time series comparing spatial statistical gap filling from paper to gap filling using snow depth assimilation into Crocus snow model (only for subset of stations in the French Alps) aux_paper_monthly_time_series.zip: Plots of monthly time series of snow depth, for each station. aux_paper_spatial_consistency.zip: Aggregate results from spatial consistency (statistical simulation using neighboring stations), and time series of observed versus simulated monthly snow depths. <strong>Code </strong>(working copy, not cleaned, all written in R statistical software): code.zip to read in the different data sources to do quality checks and data processing to perform statistical analyses as in paper to produce figures and tables as in paper <strong>Data</strong>: > 2000 stations from Austria, Germany, France, Italy, Switzerland, and Slovenia Daily stations snow depth and depth of snowfall, as .zips, grouped by data provider. Information on column content is provided in ""data_daily_00_column_names_content.txt"". Monthly stations mean snow depth, sum of depth of snowfall, maximum snow depth, days with snow cover (1-100cm thresholds), as .zips, grouped by data provider. Information on column content is provided in ""data_monthly_00_column_names_content.txt"". Meta data (name, latitude, longitude, elevation) in ""meta_all.csv"", along with an interactive map ""meta_interactive_map.html"", and column information in ""meta_00_column_names_content.txt"". If you <strong>use the data you agree to adhere to the respective data provider's terms</strong> as listed in ""00_DATA_LICENSE_AND_TERMS.PDF"" The license terms especially (and additionally to any other terms of the single data providers) include: <strong>Attribution</strong> — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. [from CC BY 4.0] <strong>Version history:</strong> v1.3: added maxHS and SCD (with various 1-100cm thresholds) to monthly data v1.2: uploaded data v1.1: changes to aux-paper.zip and code.zip as consequence from submitting a revised manuscript v1.0: initial upload",mds,True,findable,0,0,0,1,0,2021-07-16T10:47:06.000Z,2021-07-16T10:47:07.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5718043,GazeEEGSynchro,Zenodo,2021,,Software,"Creative Commons Attribution 4.0 International,Open Access",The GazeEegSynchro software runs under DOS. It allows to synchronize data coming from Eyelink ASC data files and Brainamp EEG+VHDR+VMRK data files. The synchronization process is based on piecewise linear alignments of shared triggers in both acquisition devices. <strong>A gitlab project is also available.</strong>,mds,True,findable,0,0,0,0,0,2021-11-22T10:33:25.000Z,2021-11-22T10:33:26.000Z,cern.zenodo,cern,"EEG,co-registration,synchronization,clock-drift,drift correction,eye movements","[{'subject': 'EEG'}, {'subject': 'co-registration'}, {'subject': 'synchronization'}, {'subject': 'clock-drift'}, {'subject': 'drift correction'}, {'subject': 'eye movements'}]",,
+10.5061/dryad.q1d7f,Data from: Prevention of ventilator-associated pneumonia in intensive care units: an international online survey,Dryad,2013,en,Dataset,Creative Commons Zero v1.0 Universal,"Background: On average 7% of patients admitted to intensive-care units (ICUs) suffer from a potentially preventable ventilator-associated pneumonia (VAP). Our objective was to survey attitudes and practices of ICUs doctors in the field of VAP prevention. Methods: A questionnaire was made available online in 6 languages from April, 1st to September 1st, 2012 and disseminated through international and national ICU societies. We investigated reported practices as regards (1) established clinical guidelines for VAP prevention, and (2) measurement of process and outcomes, under the assumption “if you cannot measure it, you cannot improve itâ€; as well as attitudes towards the implementation of a measurement system. Weighted estimations for Europe were computed based on countries for which at least 10 completed replies were available, using total country population as a weight. Data from other countries were pooled together. Detailed country-specific results are presented as an online supplement. Results: A total of 1730 replies were received from 77 countries; 1281 from 16 countries were used to compute weighted European estimates, as follows: care for intubated patients, combined with a measure of compliance to this guideline at least once a year, was reported by 57% of the respondents (95% CI: 54-60) for hand hygiene, 28% (95% CI: 24-33) for systematic daily interruption of sedation and weaning protocol, and 27% (95%: 23-30) for oral care with chlorhexidine. Only 20% (95% CI: 17-22) were able to provide an estimation of outcome data (VAP rate) in their ICU, still 93% (95% CI: 91-94) agreed that “Monitoring of VAP-related measures stimulates quality improvementâ€. Results for 449 respondents from 61 countries not included in the European estimates are broadly comparable. Conclusions: This study shows a low compliance with VAP prevention practices, as reported by ICU doctors in Europe and elsewhere, and identifies priorities for improvement",mds,True,findable,539,125,1,1,0,2013-03-19T15:39:42.000Z,2013-03-19T15:39:43.000Z,dryad.dryad,dryad,"patient safety,Quality of care,ventilator-associated pneumonia; intensive care units,healthcare-associated infections","[{'subject': 'patient safety'}, {'subject': 'Quality of care', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'ventilator-associated pneumonia; intensive care units'}, {'subject': 'healthcare-associated infections'}]",['1197438 bytes'],
+10.34847/nkl.87788ro3,"Marcher les lieux possibles. Itinéraire de Christophe Séraudie, le 8 octobre 2020, Rioupéroux",NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Other,,"Itinéraire réalisé dans le cadre du projet de recherche-création Les Ondes de l’Eau : Mémoires des lieux et du travail dans la vallée de la Romanche. AAU-CRESSON (Laure Brayer, direction scientifique) - Regards des Lieux (Laure Nicoladzé, direction culturelle).
+
+Pour se projeter dans le futur possible d’un territoire, rien de mieux que de commencer par s’y balader. C’est cette attitude qui guide notre rencontre avec Christophe, architecte attentif aux potentiels des lieux. Le canal : une promenade surélevée ? Les lignes électriques : des liaisons aériennes ? Accompagnés par des étudiants de l’école d’architecture, nous cheminons entre passé et prospective.",api,True,findable,0,0,0,0,0,2022-06-27T12:24:56.000Z,2022-06-27T12:24:56.000Z,inist.humanum,jbru,"roman-photo,itinéraire,matériaux de terrain éditorialisés,Histoires de vie,paysage de l'eau,histoire orale,Marche,Sens et sensations,Mémoires des lieux,Cité ouvrière,friche industrielle,méthode des itinéraires,Aménagement du territoire -- recherche,Romanche, Vallée de la (France),schémas de cohérence territoriale,gestion du risque,tissu urbain,architecture industrielle,désertification,rives -- aménagement,biens vacants","[{'lang': 'fr', 'subject': 'roman-photo'}, {'lang': 'fr', 'subject': 'itinéraire'}, {'lang': 'fr', 'subject': 'matériaux de terrain éditorialisés'}, {'lang': 'fr', 'subject': 'Histoires de vie'}, {'lang': 'fr', 'subject': ""paysage de l'eau""}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'Marche'}, {'lang': 'fr', 'subject': 'Sens et sensations'}, {'lang': 'fr', 'subject': 'Mémoires des lieux'}, {'lang': 'fr', 'subject': 'Cité ouvrière'}, {'lang': 'fr', 'subject': 'friche industrielle'}, {'lang': 'fr', 'subject': 'méthode des itinéraires'}, {'lang': 'fr', 'subject': 'Aménagement du territoire -- recherche'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'schémas de cohérence territoriale'}, {'lang': 'fr', 'subject': 'gestion du risque'}, {'lang': 'fr', 'subject': 'tissu urbain'}, {'lang': 'fr', 'subject': 'architecture industrielle'}, {'lang': 'fr', 'subject': 'désertification'}, {'lang': 'fr', 'subject': 'rives -- aménagement'}, {'lang': 'fr', 'subject': 'biens vacants'}]","['23920735 Bytes', '985594 Bytes', '840324 Bytes', '381456 Bytes', '1945082 Bytes', '1684244 Bytes', '1499318 Bytes', '1664219 Bytes', '1902591 Bytes', '1641971 Bytes', '1591326 Bytes', '1557311 Bytes', '1662693 Bytes', '1743507 Bytes', '1566403 Bytes', '1879143 Bytes', '2223816 Bytes', '1890148 Bytes', '1610157 Bytes', '2027273 Bytes', '1871130 Bytes', '1988235 Bytes', '1727845 Bytes', '1730555 Bytes', '1229652 Bytes']","['application/pdf', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg']"
+10.5281/zenodo.8094516,A Tale of Resilience - Code Artefacts,Zenodo,2023,en,Software,"Creative Commons Attribution 4.0 International,Open Access","C-based implementations and Thumb-2 binaries (Cortex-M3, Cortex-M4) of the AES-128 masked implementations and<br> leakage micro-benchmarks employed in the research article ""A Tale of Resilience: On the Practical Security of Masked Software Implementations"".",mds,True,findable,0,0,0,0,0,2023-07-01T06:52:42.000Z,2023-07-01T06:52:42.000Z,cern.zenodo,cern,"masking,processor micro-architecture,side-channel analysis,software masking","[{'subject': 'masking'}, {'subject': 'processor micro-architecture'}, {'subject': 'side-channel analysis'}, {'subject': 'software masking'}]",,
+10.5281/zenodo.4139737,"Radiation data (2014-2019) at site D17 (Adelie Land, East Antarctica)",Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This dataset reports raw half-hourly radiative fluxes acquired at site D17 on the marginal slopes of Adelie Land (East Antarctica) and complements another dataset on near-surface meteorological variables including drifting-snow mass fluxes at the same location. The available data have been measured almost continuously since mid February 2014 with a Kipp and Zonen CNR4 net radiometer installed 2 m above ground and include downward/upward shortwave/longwave radiation. Latitude: 66.7°S ; Longitude 139.9°E Date/Time (UTC): Start:2014-02-18 06:00 ; End: 2019-12-07 23:30 Elevation 450 m The data files contain the following variables and units: YYYY: year; MM: month; DD: day; hh: hour; mm: minute; SWU: upward shortwave radiation (W m<sup>-2</sup>); SWD: downward shortwave radiation (W m<sup>-2</sup>); LWU: upward longwave radiation (W m<sup>-2</sup>); LWD: downward longwave radiation (W m<sup>-2</sup>);,mds,True,findable,0,0,0,0,0,2020-10-28T08:14:52.000Z,2020-10-28T08:14:53.000Z,cern.zenodo,cern,Antarctic climate - radiative fluxes,[{'subject': 'Antarctic climate - radiative fluxes'}],,
+10.5281/zenodo.3928606,Terrestrial Laser Scans of surface deformation associated with the 11/11/2019 Mw 4.7 Le Teil earthquake (SE France),Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Terrestrial Laser Scans of surface deformation produced by the 11/11/2019 Mw 4.7 Le Teil earthquake in SE France. All scans were produced with a Faro X330 equipment at 1/2 resolution, low laser power, with in-field filters (lost points). Processing includes import and registration with Faro Scene software, export as LAS files, manual editing of noise, vegetation and scattered points with CloudCompare software and rasterization with universal kriging with Golden Software Surfer software.",mds,True,findable,0,0,0,0,0,2020-07-02T21:18:29.000Z,2020-07-02T21:18:30.000Z,cern.zenodo,cern,"Surface rupture,Earthquake,Lidar,Terrestrial laser scanning,Le Teil","[{'subject': 'Surface rupture'}, {'subject': 'Earthquake'}, {'subject': 'Lidar'}, {'subject': 'Terrestrial laser scanning'}, {'subject': 'Le Teil'}]",,
+10.5281/zenodo.5563067,Structures and Properties of Known and Postulated Interstellar Cations,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Positive ions play a fundamental role in interstellar chemistry, especially in cold environments where chemistry is believed to be mainly ion driven. We have carried out new accurate quantum chemical calculations to identify the structures and energies of 262 cations with up to 14 atoms that are postulated to have a role in interstellar chemistry. Optimized structures and rotational constants were obtained at the M06-2X/cc-pVTZ level, while electric dipoles and total electronic energies were computed with CCSD(T)/aug-cc-pVTZ//M06-2X/cc-pVTZ single-point energy calculations.",mds,True,findable,0,0,0,0,0,2021-10-11T21:48:23.000Z,2021-10-11T21:48:24.000Z,cern.zenodo,cern,"cations,ISM molecules,astrochemistry","[{'subject': 'cations'}, {'subject': 'ISM molecules'}, {'subject': 'astrochemistry'}]",,
+10.5281/zenodo.7122113,"New insights into the decadal variability in glacier volume of a tropical ice-cap explained by the morpho-topographic and climatic context, Antisana, (0°29' S, 78°09' W)",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The dataset contains five periods of surface elevation change observed on the Antisana icecap in the inner tropical region. Data were obtained by geodetic observations of aerial photographs and high-resolution satellite images for the study periods: 1956-1965, 1965-1979, 1979-1997, 1997-2009, and 2009-2016.",mds,True,findable,0,0,0,0,0,2022-09-29T04:18:20.000Z,2022-09-29T04:18:20.000Z,cern.zenodo,cern,"Geodetic Mass Balance,Tropical Glaciers,Climate variability","[{'subject': 'Geodetic Mass Balance'}, {'subject': 'Tropical Glaciers'}, {'subject': 'Climate variability'}]",,
+10.5281/zenodo.6685515,Natural color composites of VENµs images over South Col Glacier,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This datasets contain images of South Col Glacier obtained from VENµs platform from 27 Nov 2017 to 30 Oct 2020. The images are shown on a UTM45\WGS84 projection, and correspond to the band combination 7-4-3. The two stars show remarkable locations.",mds,True,findable,0,0,0,0,0,2022-06-22T14:46:29.000Z,2022-06-22T14:46:30.000Z,cern.zenodo,cern,"venus,images,south col glacier","[{'subject': 'venus'}, {'subject': 'images'}, {'subject': 'south col glacier'}]",,
+10.6084/m9.figshare.23575390,Additional file 11 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 10,mds,True,findable,0,0,0,0,0,2023-06-25T03:12:05.000Z,2023-06-25T03:12:06.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['36864 Bytes'],
+10.5281/zenodo.6991116,UFO model for NLO predictions in supersymmetric QCD,Zenodo,2022,,Dataset,"Creative Commons Zero v1.0 Universal,Open Access",NLO Predictions in suspersymmetric QCD,mds,True,findable,0,0,0,0,0,2022-08-14T20:40:21.000Z,2022-08-14T20:40:22.000Z,cern.zenodo,cern,,,,
+10.6096/mistrals-hymex.1438,Auzon data paper,SEDOO OMP,2016,en,Dataset,"The individual datasets correspond to data collected by a specific instrument, a network of instruments or a type of GIS descriptors (see the attached pdf document for the list of individual datasets). This granularity enables to associate each dataset with a Principal Investigator that is very familiar with the data and who will be an essential resource for any user in case of need. In addition, the added-value dataset corresponding to the results of the rainfall re-analysis for the 2007-2014 period has been included. All the individual datasets are available through the Hymex database (http://mistrals.sedoo.fr/HyMeX/). Most of the individual datasets have “public†access. A few of them are subject to the registration step of the Hymex database as “Associated scientists†(http://mistrals.sedoo.fr/HyMeX/Data-Policy/HyMeX_DataPolicy.pdf). Additionally a bundling service was performed to facilitate the use of the data. The bundled data include the most commonly used data in hydrometeorological and hydrological studies. The bundled data presents the advantage of gathering data in ASCII and cartesian format, and in a single coordinate system. The bundled data are selected for the spatial and temporal windows presented in the paper since some individual datasets have different extents. 12 individual datasets out of 41 presented in the paper are not part of these bundled data since the effort to prepare the data was too heavy and their potential use is more restricted. These datasets remain accessible individually even though they are not necessarily in the same format and with the same extent (Polar versus Cartesian and coordinate system). The bundled data are organized in two zip files: the “zip1†file is for the data with “public†access while the “zip2†file is for the data subject to the registration step of the Hymex database as “Associated scientistsâ€.,HyMeX Data and Publication Policy / Associated scientists","A high space-time resolution dataset linking meteorological forcing and hydro-sedimentary response in a mesoscale Mediterranean catchment (Auzon) of the Ardèche region, France is released. This dataset spans the period 1 January 2011-31 December 2014. Rainfall data include continuous precipitation measured by rain gauges (5 min time step for the research network of 21 rain gauges and 5 min or 1h time step for the operational network of 10 rain gauges), S-band Doppler dual-polarization radars (1 km², 5 min resolution), disdrometers (16 sensors working at 30s or 1 min time step) and Micro Rain Radars (5 sensors, 100 m height resolution). Additionally, during the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Météo-France (including 2-m air temperature, atmospheric pressure, 2-m relative humidity, 10-m wind speed and direction, global radiation) at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge at a 2 to 10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity). Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously measures water level and water temperature in headwater subcatchments (from 0.17 km² to 116 km²) at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014.",,True,findable,0,0,1,0,0,2016-07-15T08:47:50.000Z,2016-07-15T08:47:55.000Z,inist.omp,jbru,"Rain,Soil Erosion,Runoff,Floods","[{'subject': 'Rain', 'subjectScheme': 'Parameter'}, {'subject': 'Soil Erosion', 'subjectScheme': 'Parameter'}, {'subject': 'Runoff', 'subjectScheme': 'Parameter'}, {'subject': 'Floods', 'subjectScheme': 'Parameter'}]",,['ASCII']
+10.5281/zenodo.10239162,NeoGeographyToolkit/StereoPipeline: 2023-11-30-daily-build,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,Recent additions log: https://stereopipeline.readthedocs.io/en/latest/news.html,api,True,findable,0,0,0,0,0,2023-12-01T02:09:08.000Z,2023-12-01T02:09:08.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.840877,FAU-Inf2/treedifferencing: Version of the ASE Publication 2016,Zenodo,2017,,Software,Open Access,No description provided.,mds,True,findable,0,0,1,0,0,2017-08-09T16:29:25.000Z,2017-08-09T16:29:26.000Z,cern.zenodo,cern,,,,
+10.25364/19.2021.5.2,Étude lexicale et aréale des désignations du pissenlit en domaine gallo-roman de France,Universität Graz,2021,,Text,,"Résumé : Depuis 2015 nous participons au projet Extraction automatisée des contenus géolinguistiques
+d'atlas et analyse spatiale : application à la dialectologie (ECLATS, ANR-15-CE-380002).
+Ce projet a pour objectifs de valoriser les atlas linguistiques anciens, tels que l'Atlas linguistique
+de la France (ALF), de faciliter l'exploitation et la diffusion des cartes de l'ALF, de définir des modèles
+combinant les dimensions linguistiques, spatiales et temporelles pour représenter les données
+géo-linguistiques et enfin de proposer des outils permettant le traitement et la géo-visualisation de
+ces données. Dans le cadre de ce projet, nous avons effectué le traitement lexical et aréal des désignations
+du pissenlit à partir de la carte ALF n°1022. Nous proposons ici de présenter les résultats
+de nos recherches.",fabricaForm,True,findable,0,0,0,0,0,2021-03-18T08:30:59.000Z,2021-03-18T08:30:59.000Z,ugraz.unipub,ugraz,,,,
+10.5281/zenodo.3628203,Terrestrial Laser Scanner observations of snow depth distribution at Col du Lautaret and Col du Lac Blanc mountain sites,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains snow depth distribution observations obtained in two high mountain experimental sites, Col du Lac Blanc and Col du Lautaret, both located in French Alps. The snow depth distribution maps were generated using a Terrestrial Laser Scanner (TLS) for 10 acquisition dates. Observations obtained in Col du Lac Blanc were acquired in the 2014-15 snow season while Col du Lautaret observations were acquired in 2017-18 snow season. The snow depth maps have a grid cell size of 1x1m. The two study sites have extensions comprised between 17 and 31 ha with elevations ranging from 2000-2100 m a.s.l. (Col du Lautaret)and 2600-2800 m a.s.l. (Col du Lac Blanc)and show a patchy distribution of bare soil and alpine grass. The dataset allows a better understanding of snow related processes in mountain areas.",mds,True,findable,0,0,0,0,0,2020-01-27T11:25:40.000Z,2020-01-27T11:25:41.000Z,cern.zenodo,cern,"snow depth distribution, mountain sites, terrestrial laser scanner observations","[{'subject': 'snow depth distribution, mountain sites, terrestrial laser scanner observations'}]",,
+10.5281/zenodo.8239429,"pete-d-akers/chictaba-nitrate: CHICTABA transect, Antarctica, snow nitrate analysis",Zenodo,2023,,Software,Open Access,"Release v1.2. This version contains the data and script to reproduce all major analyses and figures for the CHICTABA nitrate analysis project and its associated publication of ""Photolytic modification of seasonal nitrate isotope cycles in East Antarctica"" by Akers et al. in Atmospheric Chemistry and Physics. Changes in v.1.2 are limited to the addition of a license.",mds,True,findable,0,0,0,1,0,2023-08-11T14:36:22.000Z,2023-08-11T14:36:23.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3938956,Data: Crystallographic orientations of large hailstones,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The data are obtained from 6 hailstones, and are obtained from thin sections analyzed with an Automatic Texture Analyser (AITA).<br> The orientation data (c-axis orientations) are included in the file ""orientation.dat"", and the file ""orientation.bmp"" is a representation of the microstructure with a color-code related to the orientation. They can be easily treated with the open access too of Thomas Chauve (https://thomaschauve.github.io/aita/build/html/index.html) on Python. The author will provide any additionnal information required.",mds,True,findable,0,0,0,0,0,2020-07-10T15:31:39.000Z,2020-07-10T15:31:40.000Z,cern.zenodo,cern,"Hailstones,Crystallographic orientation,Texture,Microstructure","[{'subject': 'Hailstones'}, {'subject': 'Crystallographic orientation'}, {'subject': 'Texture'}, {'subject': 'Microstructure'}]",,
+10.5281/zenodo.5824568,MICCAI 2021 MSSEG-2 challenge demographics data,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This dataset will include all demographics and dataset constitution information for the MICCAI 2021 challenge.,mds,True,findable,0,0,0,1,0,2022-01-06T09:52:18.000Z,2022-01-06T09:52:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8076436,National forest inventory data for a size-structured forest population model,Zenodo,2023,,Software,"MIT License,Open Access","In forest communities, light competition is a key process for community assembly. Species' differences in seedling and sapling tolerance to shade cast by overstory trees is thought to determine species composition at late-successional stages. Most forests are distant from these late-successional equilibria, impeding a formal evaluation of their potential species composition. To extrapolate competitive equilibria from short-term data, we therefore introduce the JAB model, a parsimonious dynamic model with interacting size-structured populations, which focuses on sapling demography including the tolerance to overstory competition. We apply the JAB model to a two-""species"" system from temperate European forests, i.e. the shade-tolerant species Fagus sylvatica L. and the group of all other competing species. Using Bayesian calibration with prior information from external Slovakian national forest inventory (NFI) data, we fit the JAB model to short timeseries from the German NFI. We use the posterior estimates of demographic rates to extrapolate that F. sylvatica will be the predominant species in 94% of the competitive equilibria, despite only predominating in 24% of the initial states. We further simulate counterfactual equilibria with parameters switched between species to assess the role of different demographic processes for competitive equilibria. These simulations confirm the hypothesis that the higher shade-tolerance of F. sylvatica saplings is key for its long-term predominance. Our results highlight the importance of demographic differences in early life stages for tree species assembly in forest communities.",mds,True,findable,0,0,0,0,0,2023-06-27T02:56:15.000Z,2023-06-27T02:56:16.000Z,cern.zenodo,cern,"NFI,National Forest Inventory,Fagus sylvatica,JAB model","[{'subject': 'NFI'}, {'subject': 'National Forest Inventory'}, {'subject': 'Fagus sylvatica'}, {'subject': 'JAB model'}]",,
+10.5281/zenodo.5250828,MQ-GCM,Zenodo,2021,,Software,"GNU General Public License v3.0 or later,Open Access","The Quasi-Geostrophic Coupled Model (Q-GCM) was initially developed by Hogg et al. (2003) and has been substantially modified since: its latest distribution and source code are publicly available at http://www.q-gcm.org and are fully documented in the Q-GCM Users’ Guide, v1.5.0 (Hogg et al., 2014). The model couples the multi-layer quasi-geostrophic (QG) ocean and atmosphere components via ageostrophic mixed layers that regulate the exchange of heat and momentum between the two fluids. A new formulation of the model (MQ-GCM) includes an improved radiative-convective scheme resulting in a more realistic model mean state and associated model parameters, a new formulation of entrainment in the atmosphere, which prompts more efficient communication between the atmospheric mixed layer and free troposphere, an addition of temperature-dependent wind component in the atmospheric mixed layer and the resulting mesoscale feedbacks, and the most drastic change, the inclusion of moist dynamics in the model. Full description of MQ-GCM is presented in Kravtsov et al., 2021: A Moist Quasi-Geostrophic Coupled Model: MQ-GCM2.0",mds,True,findable,0,0,0,0,0,2021-08-26T16:19:42.000Z,2021-08-26T16:19:43.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4079190,Data Sheet of Color Conversion Measurements,Zenodo,2019,en,Other,"Creative Commons Attribution 4.0 International,Open Access","For MILEDI project, CEA-Leti has at its disposal several equipment for color conversion measurements.",mds,True,findable,0,0,0,0,0,2020-10-11T14:59:49.000Z,2020-10-11T14:59:50.000Z,cern.zenodo,cern,"LED, color conversion test","[{'subject': 'LED, color conversion test'}]",,
+10.5281/zenodo.6886498,Dynamic full-field imaging of rupture radiation: Material contrast governs source mechanism,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Datasets related to the research article 'Dynamic full-field imaging of rupture radiation: Material contrast governs source mechanism'. <br> A readme with the necessary Matlab code to load the data is included.<br> Tested on Matlab2020b For the analytic rupture radiation simulation code please check the linked github repository.,mds,True,findable,0,0,1,3,0,2022-09-19T12:40:22.000Z,2022-09-19T12:40:22.000Z,cern.zenodo,cern,"laboratory earthquake, rupture nucleation, supershear, bi-material contrast, near-field seismology, ultrafast ultrasound, shear wave imaging","[{'subject': 'laboratory earthquake, rupture nucleation, supershear, bi-material contrast, near-field seismology, ultrafast ultrasound, shear wave imaging'}]",,
+10.5281/zenodo.5649829,"FIG. 44 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIG. 44—Localities of Protonemura alexidis sp. n. in the southern part of the Massif-Central: a = (brook) and b = (spring), Saint-Maurice-de-Ventalon, Méjarié forest, Vérié tributary brook, 1430 m, 44.37137N, 3.8525E (photographs by Julien Barnasson).",mds,True,findable,0,0,1,0,0,2021-11-05T21:12:07.000Z,2021-11-05T21:12:07.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.5649801,"FIGS. 1–6 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIGS. 1–6—Protonemura lupina sp. n., male. 1, epiproct, dorsal and ventral sclerites, lateral view; 2, epiproct, lateral view; 3, tergites and epiproct, dorsal view; 4, epiproct, dorsal view; 5, terminalia, ventral view; 6, terminalia, ¾ dorso-ventral view, right side.",mds,True,findable,0,0,0,0,0,2021-11-05T21:11:15.000Z,2021-11-05T21:11:16.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.48380/dggv-h2gp-1860,"Geologicaly-sourced H2 exploration: pathfinders, tools, and methods",Deutsche Geologische Gesellschaft - Geologische Vereinigung e.V. (DGGV),2021,en,Text,,"Recently, the growing demand for carbon-free energy has sparked an unprecedented interest in naturally occurring H2, as it could represent a potential alternative resource to fossil fuels. Throughout the world, and since more than one century, numerous natural H2-bearing geological fluids have been discovered, but to date, there is neither exploration strategy nor any resource assessment, as practical guidelines for hydrogen targeting are still missing. Here, we lay the foundation of a preliminary exploration guide based on a global ‘source-transport-accumulation’ understanding of H2-concentrating process and a combination of techniques and data used for both conventional petroleum and mining exploration. Based on different case studies, belonging to contrasted geological settings, we will provide the first elementary bricks to evaluate the sources, migration and trapping of H2 in the Earth’s crust.",fabrica,True,findable,0,0,0,0,0,2022-09-06T12:04:43.000Z,2022-09-06T12:04:43.000Z,mcdy.dohrmi,mcdy,,,,
+10.6084/m9.figshare.c.6853693,Obstructive sleep apnea: a major risk factor for COVID-19 encephalopathy?,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background This study evaluates the impact of high risk of obstructive sleep apnea (OSA) on coronavirus disease 2019 (COVID-19) acute encephalopathy (AE). Methods Between 3/1/2020 and 11/1/2021, 97 consecutive patients were evaluated at the Geneva University Hospitals with a neurological diagnosis of COVID-19 AE. They were divided in two groups depending on the presence or absence of high risk for OSA based on the modified NOSAS score (mNOSAS, respectively ≥ 8 and < 8). We compared patients’ characteristics (clinical, biological, brain MRI, EEG, pulmonary CT). The severity of COVID-19 AE relied on the RASS and CAM scores. Results Most COVID-19 AE patients presented with a high mNOSAS, suggesting high risk of OSA (> 80%). Patients with a high mNOSAS had a more severe form of COVID-19 AE (84.8% versus 27.8%), longer mean duration of COVID-19 AE (27.9 versus 16.9 days), higher mRS at discharge (≥ 3 in 58.2% versus 16.7%), and increased prevalence of brain vessels enhancement (98.1% versus 20.0%). High risk of OSA was associated with a 14 fold increased risk of developing a severe COVID-19 AE (OR = 14.52). Discussion These observations suggest an association between high risk of OSA and COVID-19 AE severity. High risk of OSA could be a predisposing factor leading to severe COVID-19 AE and consecutive long-term sequalae.",mds,True,findable,0,0,0,0,0,2023-09-27T03:26:12.000Z,2023-09-27T03:26:13.000Z,figshare.ars,otjm,"Biophysics,Medicine,Cell Biology,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,Sociology,FOS: Sociology,Immunology,FOS: Clinical medicine,Cancer,Mental Health,Virology","[{'subject': 'Biophysics'}, {'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Mental Health'}, {'subject': 'Virology'}]",,
+10.5281/zenodo.7213408,Datacubes of InSAR time series for active volcanoes,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Datacubes of InSAR time series for the 20 volcanoes (*) flagged in the paper ""Large-scale demonstration of machine learning for the detection of volcanic deformation in Sentinel-1 satellite imagery"" by Biggs et al. (Bull Volc, 2022). Each file contains the time series of cumulative displacements for one volcano in the *.nc format. There are four fields with ""DATA"" : cumulative LOS displacements (unit=meters), ""lon"" : longitude (unit=degrees), ""lat"" : latitude (unit=degrees) and ""time"" : number of days since the first date. The first date can be found in the attribute ""units"" of the variable ""time"". (*) The five volcanoes: Sierra Negra, Fernandina, Cerro Azul, Wolf and Alcedo volcanoes are contained in the single file ""galapagos_128D_09016_110500.nc"".",mds,True,findable,0,0,0,0,0,2022-10-16T16:27:42.000Z,2022-10-16T16:27:43.000Z,cern.zenodo,cern,InSAR ground deformation volcanoes,[{'subject': 'InSAR ground deformation volcanoes'}],,
+10.6084/m9.figshare.23575384.v1,Additional file 9 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 8,mds,True,findable,0,0,0,0,0,2023-06-25T03:12:00.000Z,2023-06-25T03:12:00.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['87040 Bytes'],
+10.5281/zenodo.37476,Magellan/M2FS Spectroscopy of Tucana 2 and Grus 1,Zenodo,2015,,Dataset,"Creative Commons Zero v1.0 Universal,Open Access","supplementary data products, including all sky-subtracted spectra from individual targets, as well as random draws from posterior PDFs for model parameters (see enclosed README file)",mds,True,findable,1,0,0,0,0,2015-12-29T10:29:31.000Z,2015-12-29T10:29:31.000Z,cern.zenodo,cern,"Tucana 2, Grus 1, Magellan M2FS spectroscopy","[{'subject': 'Tucana 2, Grus 1, Magellan M2FS spectroscopy'}]",,
+10.5281/zenodo.35230,trunk 1.12.0,Zenodo,2015,,Software,Open Access,git-repository for Yade project,mds,True,findable,0,0,1,0,0,2015-12-11T12:32:15.000Z,2015-12-11T12:32:16.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6565895,Screening routine for integrative dynamic structural biology using SAXS and intramolecular FRET and DEER-EPR on hGBP1 (human guanalyte binding protein 1),Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Initial and selected ensemble for major and minor species of the human guanalyte binding protein 1 with scripts for the reading routine to combine and analyse jointly SAXS, EPR and FRET data.",mds,True,findable,0,0,0,1,0,2022-05-20T09:07:14.000Z,2022-05-20T09:07:15.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4760125,Figs. 1-5 in Contribution To The Knowledge Of The Capniidae (Plecoptera) Of Turkey.,Zenodo,2011,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 1-5. Capnioneura bolkari sp. n., 1. Male abdominal tip, dorsal view. 2. Male abdominal tip, lateral view. 3. Specillum. 4. Female abdominal tip, ventral view. 5. Female abdominal tip, lateral view.",mds,True,findable,0,0,4,0,0,2021-05-14T04:29:27.000Z,2021-05-14T04:29:28.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Capniidae,Capnioneura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Capniidae'}, {'subject': 'Capnioneura'}]",,
+10.5281/zenodo.7462516,Epitaxial La0.5Sr0.5MnO3 bipolar memristive devices with tunable and stable multilevel states,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data files (.txt) of the data presented in the publication DOI 10.1002/admi.202202496 File names are referred to as the reference of the Figure and number in the main manuscript and keywords of the figure. Regarding the series in a Figure, in the case there is very little data, the series are in a single file, arranged in columns. Otherwise, the series with large amounts of data have been split into single files named according to the series (legend). All the files include two headers (Name and Units) for each column. The files containing data from multiple series contain an extra header to precise the data series.",mds,True,findable,0,0,0,0,0,2023-04-19T10:23:38.000Z,2023-04-19T10:23:39.000Z,cern.zenodo,cern,"resistive switching,manganites,oxygen vacancies,memristive devices,metal-organic chemical vapor deposition (MOCVD),epitaxial thin films,valence change memories (VCMs)","[{'subject': 'resistive switching'}, {'subject': 'manganites'}, {'subject': 'oxygen vacancies'}, {'subject': 'memristive devices'}, {'subject': 'metal-organic chemical vapor deposition (MOCVD)'}, {'subject': 'epitaxial thin films'}, {'subject': 'valence change memories (VCMs)'}]",,
+10.5281/zenodo.5649817,"FIG. 27 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIG. 27—Protonemura risi, male. Paraproct median lobe and outer lobe with bifurcated sclerite, lateral view; FIGS. 28–30— Protonemura risi, female. 28, ventral view (Jura Mountains); 29, ventral view (Massif Central, northern flank); 30, cervical gills.",mds,True,findable,0,0,1,0,0,2021-11-05T21:11:43.000Z,2021-11-05T21:11:44.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.5549758,Glacier evolution projections in the French Alps (2015-2100),Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset describing the evolution of all individual glaciers in the French Alps for the 2015-2100 period under 29 different RCM-GCM-RCP combinations. The dataset includes annual topographical data (e.g. mean glacier altitude, surface area, slope...), climate data at the glacier's mean altitude (cumulative positive degree-days, winter snowfall, summer snowfall...) and annual glacier-wide mass balance data. The dataset is available in two formats: netCDF and CSV. The netCDF file is the recommended format, as it is well structured to be browsed across dimensions, particularly using tools such as xarray. A secondary dataset (.zip file) includes individual raster files for each glacier and year representing the evolving glacier ice thickness for each of the 29 climate scenarios.",mds,True,findable,0,0,0,0,0,2021-10-05T10:24:38.000Z,2021-10-05T10:24:39.000Z,cern.zenodo,cern,"glaciers,climate change,French Alps,glaciology,glacier evolution","[{'subject': 'glaciers'}, {'subject': 'climate change'}, {'subject': 'French Alps'}, {'subject': 'glaciology'}, {'subject': 'glacier evolution'}]",,
+10.5281/zenodo.6546702,"Data from the field experiment on katabatic winds on a steep slope (Grand Colon, French Alps), February 2019",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These are the data from the field experiment described in the paper 'Katabatic winds over steep slopes: overview of a field experiment designed to investigate slope-normal velocity and near surface turbulence' by CHARRONDIERE, C., BRUN, C., COHARD, J.M., SICART, J.E., OBLIGADO, M., BIRON, R., COULAUD, C. & GUYARD, H. (2022), Boundary-Layer Meteorol. 187, 29-54.",mds,True,findable,0,0,0,0,0,2022-05-13T15:04:25.000Z,2022-05-13T15:04:26.000Z,cern.zenodo,cern,"katabatic flow, steep alpine slope, stably stratified atmospheric boundary layer, in situ measurements, turbulent mixing","[{'subject': 'katabatic flow, steep alpine slope, stably stratified atmospheric boundary layer, in situ measurements, turbulent mixing'}]",,
+10.5281/zenodo.2641214,Dynamical charge density fluctuations pervading the phase diagram of a Cu-based high-Tc superconductor,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","[This repository contains the raw data for the manuscript ""<strong>Dynamical charge density fluctuations pervading the phase diagram of a Cu-based high-Tc superconductor</strong>"" (arXiv:1809.04949)]
+
+Charge density modulations are a common occurrence in all families of high critical temperature superconducting cuprates. Although consistently observed in the underdoped region of the phase diagram and at relatively low temperatures, it is still unclear to what extent they influence the unusual properties of these systems. Using resonant x-ray scattering we carefully determined the temperature dependence of charge density modulations in YBa<sub>2</sub>Cu<sub>3</sub>O<sub>7-δ</sub> and Nd<sub>1+x</sub>Ba<sub>2-x</sub>Cu<sub>3</sub>O<sub>7-δ</sub> for several doping levels. We discovered short-range dynamical charge density fluctuations besides the previously known quasi-critical charge density waves. They persist up to well above the pseudogap temperature <em>T*</em>, are characterized by energies of few meV and pervade a large area of the phase diagram, so that they can play a key role in shaping the peculiar normal-state properties of cuprates.",mds,True,findable,0,0,0,0,0,2019-04-16T12:30:28.000Z,2019-04-16T12:30:28.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23488967,Additional file 1 of 3DVizSNP: a tool for rapidly visualizing missense mutations identified in high throughput experiments in iCn3D,figshare,2023,,Dataset,Creative Commons Attribution 4.0 International,"Additional file 1. A table summarizing the features of 3DVizSNP, PhyreRisk, MuPit, and VIVID.",mds,True,findable,0,0,0,0,0,2023-06-10T03:21:52.000Z,2023-06-10T03:21:53.000Z,figshare.ars,otjm,"Space Science,Medicine,Genetics,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,80699 Information Systems not elsewhere classified,FOS: Computer and information sciences,Cancer,Plant Biology","[{'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '80699 Information Systems not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Computer and information sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",['29184 Bytes'],
+10.5281/zenodo.4581363,Pycewise,Zenodo,2021,,Software,"MIT License,Open Access",Python module to compute a segmented linear regression.,mds,True,findable,0,0,1,0,0,2021-03-04T15:52:53.000Z,2021-03-04T15:52:55.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5649811,"FIGS. 23–26 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIGS. 23–26—Protonemura risi, male. 23, epiproct, lateral view; 24, epiproct, lateral view; 25, epiproct, dorsal view; 26, terminalia, ventral view.",mds,True,findable,0,0,0,0,0,2021-11-05T21:11:37.000Z,2021-11-05T21:11:38.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.7119220,"FIGURE 1 in A new species, Bulbophyllum phanquyetii and a new national record of B. tianguii (Orchidaceae) from the limestone area of northern Vietnam",Zenodo,2022,,Image,Open Access,"FIGURE 1. Bulbophyllum phanquyetii Vuong, Aver. & V.S.Dang. A. Flowering plant. B. Pseudobulbs and pseudobulb bracts. C. Leaf apex. D. Floral bract, adaxial and abaxial side. E. Inflorescences. F. Flowers, side view. G. Pedicel, ovary and flower, side view. H. Flower, back view. I. Median sepal, adaxial and abaxial surface with magnified surface near the margin. J. Lateral sepal, adaxial and abaxial surface with magnified surface near the margin. K. Petal, adaxial and abaxial surface with magnified surface near the margin. L. Lip, views from different sides. M. Column and lip, side view. N. Pedicel, ovary and column, side view. O. Column apex, views from different sides. P. Anther cap, frontal view and view from back. Q. Pollinaria. Photos by Truong Ba Vuong (type specimen), design by Truong Ba Vuong, L. Averyanov, and T. Maisak.",mds,True,findable,0,0,0,3,0,2022-09-28T12:11:53.000Z,2022-09-28T12:11:53.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Bulbophyllum","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Bulbophyllum'}]",,
+10.5281/zenodo.4601172,RUSTInA: Automatically checking and Patching Inline Assembly Interface Compliance (Artifact Evaluation),Zenodo,2021,en,Software,"Creative Commons Attribution 4.0 International,Open Access","The main goal of the artifact is to support the experimental claims of the paper #992 “Interface Compliance of Inline Assembly: Automatically Check, Patch and Refine†by making both the prototype and data available to the community. The expected result is the same output as the figures given in Table I and Table IV (appendix C) of the paper. In addition, we hope the released snapshot of our prototype is simple, documented and robust enough to have some uses for people dealing with inline assembly. The artifact is made publicly available on Github at: https://github.com/binsec/icse2021-artifact992/, and more information on RUSTInA can be found at https://binsec.github.io/new/publication/1970/01/01/nutshell-icse-21.html.",mds,True,findable,0,0,0,0,0,2021-03-12T13:58:36.000Z,2021-03-12T13:58:37.000Z,cern.zenodo,cern,"low-level programming,inline assembly,compilation issues,program analysis","[{'subject': 'low-level programming'}, {'subject': 'inline assembly'}, {'subject': 'compilation issues'}, {'subject': 'program analysis'}]",,
+10.5281/zenodo.7898656,"GNSS data IGS and SOAM, GAMIT",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",GNSS data used to carry out the analysis of the submitted article DOI: 10.22541/essoar.168319853.39124142/v1. POS files are in ITRF 2008 reference frame.,mds,True,findable,0,0,0,0,0,2023-05-05T08:29:09.000Z,2023-05-05T08:29:09.000Z,cern.zenodo,cern,GNSS,[{'subject': 'GNSS'}],,
+10.5281/zenodo.7798143,Superconductor-ferromagnet hybrids for non-reciprocal electronics and detectors,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","# Data for the manuscript ""Superconductor-ferromagnet hybrids for non-reciprocal electronics and detectors"", submitted to Superconductor Science and Technology, arXiv:2302.12732. This archive contains the data for all plots of numerical data in the manuscript. ## Fig. 4 <br> Data of Fig. 4 in the WDX (Wolfram Data Exchange) format (unzip to extract the files). Contains critical exchange fields and critical thicknesses as functions of the temperature. Can be opened with Wolfram Mathematica with the command: Import[FileNameJoin[{NotebookDirectory[],""filename.wdx""}]] ## Fig. 5<br> Data of Fig. 5 in the WDX (Wolfram Data Exchange) format (unzip to extract the files). Contains theoretically calculated I(V) curves and the rectification coefficient R of N/FI/S junctions. Can be opened with Wolfram Mathematica with the command Import[FileNameJoin[{NotebookDirectory[],""filename.wdx""}]]. ## Fig. 7a<br> Data of Fig. 7a in the ascii format. Contains G in uS as a function of B in mT and V in mV. ## Fig. 7c<br> Data of Fig. 7c in the ascii format. Contains G in uS as a function of B in mT and V in mV. ## Fig. 7e<br> Data of Fig. 7e in the ascii format. Contains G in uS as a function of B in mT and V in mV. The plots 7b, d, and f are taken from the plots a, c and e as indicated in the caption of the figure. ## Fig. 8<br> Data of Fig. 8 in the ascii format. Contains G in uS as a function V in mV for several values of B in mT. ## Fig. 8 inset<br> Data of Fig. 8 inset in the ascii format. Contains G_0/G_N as a function of B in mT. ## Fig9a_b First raw Magnetic field values in T, first column voltage drop in V, <br> rest of the columns differential conductance in S ## Fig9b_FIT First raw Magnetic field values in T, first column voltage drop in V, <br> rest of the columns differential conductance in S ## Fig9c First raw Magnetic field values in T, first column voltage drop in V, <br> rest of the columns R (real number) ## Fig9c inset First raw Magnetic field values in T, odd columns voltage drop in V, <br> even columns injected current in A ## Fog9d Foist column magnetic field in T, second column conductance ration (real <br> number), sample name in the file name. ## Fig. 12<br> Data of Fig. 12 in the ascii format. Contains energy resolution as functions of temperature and tunnel resistance with current and voltage readout. ## Fig. 13<br> Data of Fig. 13 in the ascii format. Contains energy resolution as functions of (a) exchange field, (b) polarization, (c) dynes, and (d) absorber volume with different amplifier noises. ## Fig. 14<br> Data of Fig. 14 in the ascii format. Contains detector pulse current as functions of (a) temperature change (b) time with different detector parameters. <br> ## Fig. 17<br> Data of Fig. 17 in the ascii format. Contains dIdV curves as function of the voltage for different THz illumination frequency and polarization. ## Fig. 18<br> Data of Fig. 18 in the ascii format. Contains the current flowing throughout the junction as function time (arbitrary units) for ON and OFF illumination at 150 GHz for InPol and CrossPol polarization. ## Fig. 21<br> Data of Fig. 21c in the ascii format. Contains the magnitude of readout line S43 as frequency.<br> Data of Fig. 21d in the ascii format. Contains the magnitude of iKID line S21 as frequency.",mds,True,findable,0,0,0,0,0,2023-04-06T12:50:42.000Z,2023-04-06T12:50:43.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3483601,Virtual tide gauges for predicting relative sea level rise supporting data,Zenodo,2019,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data and results from the publication Hawkins R., Husson L., Choblet G., Bodin T. and Pfeffer J.,<br> ""Virtual tide gauges for predicting relative sea level rise"",<br> JGR: Solid Earth,<br> 2019 (submitted)<br> Software available from https://github.com/rhyshawkins/TransTessellate2D/",mds,True,findable,0,0,0,0,0,2019-10-12T12:57:17.000Z,2019-10-12T12:57:17.000Z,cern.zenodo,cern,Sea level,[{'subject': 'Sea level'}],,
+10.5061/dryad.7h44j100f,Data from: Reconstructing the complex colonization histories of lizards across Mediterranean archipelagos,Dryad,2023,en,Dataset,Creative Commons Zero v1.0 Universal,"Aim: The Mediterranean Basin is a global biodiversity hotspot and has one of the longest histories of human-biota interactions. Islands host a large fraction of Mediterranean diversity and endemism, but the relative importance of natural vs. human-mediated colonization processes in shaping the distribution and genetic structure of Mediterranean island fauna remains poorly understood. Here, we combine population genomics, demographic models and palaeoshoreline reconstructions to establish the island-colonization dynamics of wall lizards in Mediterranean archipelagos. Location: Four Mediterranean Archipelagos in Italy and Croatia Taxon: the wall lizard Podarcis siculus Methods: We used ddRAD sequencing to genotype 140 lizards from 23 island and mainland populations. Analyses of admixture and site frequency spectra were used to reconstruct population structure, demographic history, and variation of gene flow through time. Genomic results were integrated with paleogeographic reconstructions and were compared to archaeological evidence of human presence on these islands. Results: Although many island populations of this species are assumed to be non-native, we find that many islands were colonized long before any known human settlements (230,000–12,000 years ago). This natural colonization most likely occurred through land bridges during glacial marine regression or by over-sea rafting. On the other hand, islands distant from the continent were often colonized recently, and some of the estimated island colonization times match historical records of human arrival. We also determine that long-established island populations generally show lower genetic diversity compared to proximate mainland populations, contrary to recently colonized islands that must have experienced higher rates of post-colonization gene flow. Main conclusion: Our integrated approach provides us with the power to accurately quantify the origin, timing, and mode of island colonization. This framework helps to clarify the biogeographic and evolutionary history of island populations, with important implications for conservation and management of island biodiversity.",mds,True,findable,28,6,0,0,0,2023-09-28T15:46:04.000Z,2023-09-28T15:46:05.000Z,dryad.dryad,dryad,"FOS: Natural sciences,FOS: Natural sciences,Island biogeography,vicariance,Overseas dispersal,ddRAD Sequencing,demographic history,Podarcis siculus,wall lizards","[{'subject': 'FOS: Natural sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Natural sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Island biogeography', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'vicariance'}, {'subject': 'Overseas dispersal'}, {'subject': 'ddRAD Sequencing'}, {'subject': 'demographic history'}, {'subject': 'Podarcis siculus'}, {'subject': 'wall lizards'}]",['1614361 bytes'],
+10.5281/zenodo.7802745,The GRETOBAPE gas-phase reaction network: the importance of being exothermic,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Zip file containing all the network, codes and database used and/or obtained in our accepted article for publication in ApJS, 2023. The folder structure is illustrated in the ReadMe.txt file.",mds,True,findable,0,0,0,0,0,2023-04-05T15:12:08.000Z,2023-04-05T15:12:08.000Z,cern.zenodo,cern,"reaction network,astrochemistry","[{'subject': 'reaction network'}, {'subject': 'astrochemistry'}]",,
+10.5281/zenodo.4759486,"Figs. 1-4 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 1-4. Apex of the male's epiproct of the Protonemura corsicana group. 1: the terminal filament and the apical part of the dorsal sclerite, dorsal view; 2: the terminal filament and the apical part of the dorsal sclerite, dorsoapical view; 3: the terminal filament, the apical part of the dorsal sclerite and the spiny bulge of the ventral sclerite, lateral view; 4: the terminal filament, the dorsal sclerite and the spiny bulge of the ventral sclerite, apical view (1-2, 4: Protonemura berberica Vinçon & S{nchez-Ortega, 1999; 3: P. talboti (Nav{s, 1929); scale 0.02 mm).",mds,True,findable,0,0,6,0,0,2021-05-14T02:23:06.000Z,2021-05-14T02:23:06.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.5243277,Portuguese DBnary archive in original Lemon format,Zenodo,2021,pt,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Portuguese language edition, ranging from 26th August 2012 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br>",mds,True,findable,0,0,0,0,0,2021-08-24T10:59:52.000Z,2021-08-24T10:59:53.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.6977303,High resolution spectra of the spinning-top Be star Achernar,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Achernar, the closest and brightest classical Be star, presents rotational flattening, gravity darkening, occasional emission lines due to a gaseous disk, and an extended polar wind. It is also a member of a close binary system with an early A-type dwarf companion. We aim to determine the orbital parameters of the Achernar system and to estimate the physical properties of the components. We monitored the relative position of Achernar B using a broad range of high angular resolution instruments of the VLT/VLTI over a period of 13 years (2006-2019). These astrometric observations are complemented with a series of more than 700 optical spectra for the period from 2003 to 2016. The present dataset contains the high resolution spectra of Achernar that were included in our study. They were collected using the BESO, BeSS, CHIRON, CORALIE, FEROS, HARPS, PUCHEROS, and UVES instruments. The spectra are provided in the form of standard FITS files, with the continuum flux normalized to unity.",mds,True,findable,0,0,0,0,0,2022-09-15T17:38:33.000Z,2022-09-15T17:38:33.000Z,cern.zenodo,cern,"Stars: individual: Achernar,Astrometry and celestial mechanics,Techniques: high angular resolution,Techniques: interferometric,Techniques: radial velocities,Stars: binaries: visual","[{'subject': 'Stars: individual: Achernar'}, {'subject': 'Astrometry and celestial mechanics'}, {'subject': 'Techniques: high angular resolution'}, {'subject': 'Techniques: interferometric'}, {'subject': 'Techniques: radial velocities'}, {'subject': 'Stars: binaries: visual'}]",,
+10.5281/zenodo.3372756,Simulations of shallow water wave turbulence,Zenodo,2019,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>About</strong> This dataset curates all the simulations used to reproduce the paper: <em>Shallow water wave turbulence</em><br> DOI: 10.1017/jfm.2019.375 The source code and scripts necessary to generate the manuscript are archived at: https://github.com/ashwinvis/augieretal_jfm_2019_shallow_water See the README in the repository above to generate the manuscript <strong>Abstract</strong> The dynamics of irrotational shallow water wave turbulence forced at large scales and dissipated at small scales is investigated. First, we derive the shallow water analogue of the ‘four-fifths law’ of Kolmogorov turbulence for a third-order structure function involving velocity and displacement increments. Using this relation and assuming that the flow is dominated by shocks, we develop a simple model predicting that the shock amplitude scales as \((\epsilon d)^{1/3}\), where \( \epsilon\) is the mean dissipation rate and \(d\) the mean distance between the shocks, and that the \(p\)<sup>th</sup>-order displacement and velocity structure functions scale as \((\epsilon d)^{p/3} r/d\), where \(r\) is the separation. Then we carry out a series of forced simulations with resolutions up to 7680<sup>2</sup>, varying the Froude number,\(F_{f} = (\epsilon L_f)^{1/3}/ c \), where \(L_f\) is the forcing length scale and \(c\) is the wave speed. In all simulations a stationary state is reached in which there is a constant spectral energy flux and equipartition between kinetic and potential energy in the constant flux range. The third-order structure function relation is satisfied with a high degree of accuracy. Mean energy is found to scale approximately as \(E \sim \sqrt{\epsilon L_f c}\), and is also dependent on resolution, indicating that shallow water wave turbulence does not fit into the paradigm of a Richardson–Kolmogorov cascade. In all simulations shocks develop, displayed as long thin bands of negative divergence in flow visualizations. The mean distance between the shocks is found to scale as \( d \sim F_f^{1/2} L_f\). Structure functions of second and higher order are found to scale in good agreement with the model. We conclude that in the weak limit, \(F_f \rightarrow 0 \), shocks will become denser and weaker and finally disappear for a finite Reynolds number. On the other hand, for a given \(F_f\), no matter how small, shocks will prevail if the Reynolds number is sufficiently large.",mds,True,findable,0,0,0,0,0,2019-08-23T08:21:44.000Z,2019-08-23T08:21:45.000Z,cern.zenodo,cern,"Energy cascade,Energy spectrum,Fluid Dynamics,Shocks,Wave turbulence,FluidSim,FluidDyn","[{'subject': 'Energy cascade'}, {'subject': 'Energy spectrum'}, {'subject': 'Fluid Dynamics'}, {'subject': 'Shocks'}, {'subject': 'Wave turbulence'}, {'subject': 'FluidSim'}, {'subject': 'FluidDyn'}]",,
+10.5281/zenodo.7561767,"NEMO v4.2 eORCA1 data with RIS, FRIS and LCIS explicit",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>PROJECT OPEN</strong> https://www.katofthesea.com/project-open <strong>OBJECTIVES</strong> As a first step towards better representing AABW source waters in NEMO global ocean 1° (eORCA1), we explicitly simulate circulation beneath Filchner-Ronne (FRIS), Larsen C (LCIS), and Ross (RIS) ice shelves. These ice shelves were chosen due to their role in the formation and setting of properties of the parent waters of AABW. <strong>METHODOLOGY</strong> NEMO version 4.2 Beta Forced with 2 cycles of CORE forcing for a reference “Closed†cavity run and an “Open†run with FRIS, LCIS and RIS represented. Inform initial conditions using an idealized regional configuration of each ice shelf. <strong>PROVIDED HERE:</strong> <strong>NAMELISTS: </strong> - NEMO reference namelist (namelist_ref; also available with NEMO code), OPEN configuration (namelist_core_ia_cfg) namelist and sea ice namelists (namelist_ice_ref and namelist_ice_cfg). Unless stated otherwise in the “cfg†namelist, the simulation uses the namelist choices provided in the “ref†namelist. The namelist_core_ia_cfg is a namelist specific to a global ocean configuration (ORCA2, ORCA1, ORCA025 etc) forced by interannual core winds. For more information on all the namelist parameters included in these namelists, please refer to the NEMO reference manual available on Zenodo (10.5281/zenodo.6334656). <strong>DOMAIN FILES AND INITIAL CONDITIONS: </strong> - Initial conditions where data inside the cavity is informed using an idealized regional configuration with World Ocean Atlas (WOA; https://www.nodc.noaa.gov/OC5/woa18/woa18data.html) restoring at the boundaries. The data in the cavities is merged with WOA with a smoothing spline applied along the ice shelf front. - A domain file containing bathymetry and ice shelf draft with FRIS, LCIS and RIS open along with accompanying mesh mask file. - The adapted eddy viscosity files where viscosity varies south of 65 degrees South according to grid cell size. - A freshwater flux file where the melt rate from all cavities except FRIS, LCIS and RIS is prescribed. Inside the ""Open"" cavities, the melt paramaterization is turned off and the location of melt is moved to the grounding line in case in the future we would like to include the flux from grounding line rives. <strong>MODEL OUTPUT:</strong> The data uploaded in this zip file is split into the output from the ""Closed"" and ""Open"" runs and is listed under eORCA1_output. Here the temperature and salinity fields used for comparison with WOA are provided (1981-2009), along with specific sections extracted using the PAGO functions (https://www.whoi.edu/science/PO/pago/) along FRIS and RIS for certain dates that correspond to CTD sections in the area. To facilitate easy plotting of the example scripts provided, we have also extracted the thermohaline and velocity fields for FRIS cavity and adjacent continental shelf. The user can use these for a first try with the scripts provided and then move on to extracting their areas and dates of interest from the regional 1981-2009 files. <strong>EXAMPLE SCRIPS:</strong> To get the user familiar with the provided data, we have provided example scripts for extracting the data (open_eORCA_FRIS), plotting bathymetry and T-S (plot_bathy_T_S) and plotting the meridional overturning function and barotropic stream function in the cavity (plot_MOC_BSF_melt). In this same script the melt rate pattern is plotted and the net melt over various time periods corresponding to observational studies is calculated using calculating_net_melt. Additionally, a script plotting temperature and salinity across FRIS ice shelf front for the period February-March 1995 is provided and can be adapted and used to plot the other sections of data provided in this zip. <strong>ACKNOWLEDGEMENTS AND FINANCIAL SUPPORT</strong> Katherine Hutchinson received financial support of the European Union’s Horizon 2020 research and innovation programme Marie Skłodowska-Curie grant agreement No 898058 (Project OPEN). Nicolas Jourdain received support from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 101003536 (ESM2025). Pierre Mathiot acknowledges support from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 820575 (TiPACCs). This work was performed using HPC resources from GENCI–IDRIS (Grant 2021- A0100107451) and from the IPSL Mesocentre ESPRI. Project OPEN is a participant in the h2020 open access data pilot.",mds,True,findable,0,0,0,0,0,2023-01-23T14:59:13.000Z,2023-01-23T14:59:14.000Z,cern.zenodo,cern,"NEMO,eORCA1,Weddell,Ross,Ice Shelf","[{'subject': 'NEMO'}, {'subject': 'eORCA1'}, {'subject': 'Weddell'}, {'subject': 'Ross'}, {'subject': 'Ice Shelf'}]",,
+10.5281/zenodo.4760487,"Figs 2-7 in Contribution To The Knowledge Of The Moroccan High And Middle Atlas Stoneflies (Plecoptera, Insecta)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs 2-7. Amphinemura tiernodefigueroai sp. n. 2: male abdomen in dorsal view; 3: male abdomen in ventral view; 4: female abdomen in ventral view; 5: paraproct in lateral view (outer lobe on the left and median lobe on the right); 6: median lobe of the paraproct in dorsal view; 7: epiproct in lateral view. Figs 8-12. Amphinemura berthelemyi 8: detail of female abdomen in ventral view; 9: epiproct in dorsal view; 10: paraproct in lateral view (outer lobe on the left and median lobe on the right); 11: median lobe of the paraproct in dorsal view; 12: epiproct in lateral view (♂ Figs 2-3, 5-7, 9-12: scale = 0,5 mm, ♀ Figs 4, 8: scale = 1 mm).",mds,True,findable,0,0,2,0,0,2021-05-14T05:26:30.000Z,2021-05-14T05:26:31.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Amphinemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Amphinemura'}]",,
+10.5281/zenodo.10117556,"Companion documents of the article entitled ""State of the art of research towards sustainable power electronics"" from the workgroup CEPPS, research group SEEDS, CNRS, France.",Zenodo,2023,en,Dataset,Creative Commons Attribution Share Alike 4.0 International,"These documents accompany the article ""State of the art of research towards sustainable power electronics"", produced by members of the CEPPS working group, part of the SEEDS research group. These documents include: a list of keywords for bibliographic queries; a list of articles extracted; a list of journals, conferences and key players in the field; and a review of indicators.",api,True,findable,0,0,0,0,0,2023-11-13T09:47:07.000Z,2023-11-13T09:47:08.000Z,cern.zenodo,cern,"power electronics,eco-design,circular economy,sustainability,state-of-the-art,literature review","[{'subject': 'power electronics'}, {'subject': 'eco-design'}, {'subject': 'circular economy'}, {'subject': 'sustainability'}, {'subject': 'state-of-the-art'}, {'subject': 'literature review'}]",,
+10.5281/zenodo.2585908,Role of the quasi-particles in an electric circuit with Josephson junctions (Code and Data),Zenodo,2019,,Software,"Creative Commons Attribution 4.0 International,Open Access","This the codes and data used to produce results of the article Role of the quasi-particles in an electric circuit with Josephson junctions. It is a new algorithm to from self-consistent time dependent transport. Time dependent transport is compute by the software in development ""t-Kwant"". Both relies on Kwant package (Web page, article). Bound stats are found using a software in development (GitLab). The full code and data necessary to obtain the figure of the article are contained in this repository. The code is under development and not at all user friendly. Contents: - tkwant, new_tkwant: library used for simulations. - Scripts: python scripts used to run simulations. - Data_set: data produced by the scripts. - Post-process: jupyter notebook to transform Data_set/Raw into Data_set. - Plots: jupyter notebook producing figure of article from Data_set.",mds,True,findable,0,0,0,0,0,2019-03-06T16:22:33.000Z,2019-03-06T16:22:34.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.22609322,Additional file 2 of TRansfusion strategies in Acute brain INjured patients (TRAIN): a prospective multicenter randomized interventional trial protocol,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 2. SPIRIT Checklist for Trials.,mds,True,findable,0,0,0,0,0,2023-04-13T11:34:55.000Z,2023-04-13T11:34:56.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Neuroscience,Biotechnology,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['34625 Bytes'],
+10.5281/zenodo.8316094,Analysis of AaH-II effect in the axon initial of neocortical pyramidal neurons,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains data in HEK293 neurons expressing either human Na<sub>v</sub>1.2 or human Na<sub>v</sub>1.6 and whole-cell electrophysiological recordings and imaging data from neocortical layer-5 pyramidal neuron in brain slices of the mouse. This dataset is used in the paper: Abbas F, Blömer LA, Millet H, Montnach J, De Waard M, Canepari M. Analysis of the effect of the scorpion toxin AaH-II on action potential generation in the axon initial segment. bioRxiv, 2023. https://www.biorxiv.org/content/10.1101/2023.10.06.561226v1",mds,True,findable,0,0,0,0,0,2023-10-10T13:59:14.000Z,2023-10-10T13:59:15.000Z,cern.zenodo,cern,"sodium channels,toxins,patch clamp,imaging,neocortical layer-5 pyramidal neuron","[{'subject': 'sodium channels'}, {'subject': 'toxins'}, {'subject': 'patch clamp'}, {'subject': 'imaging'}, {'subject': 'neocortical layer-5 pyramidal neuron'}]",,
+10.5281/zenodo.8341374,JASPAR 2024 TFBS LOLA databases - Part 1,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the first part of the JASPAR 2024 LOLA databases used by the JASPAR TFBS enrichment tool. For each organism, we provide the LOLA databases for all JASPAR 2024 TFBS sets as compressed directories containing a set of .RDS R objects. Databases are organised by genome assembly. The repository is split into different parts due to file sizes. Below are listed the different parts and the genome assemblies for which they have TFBSs: Part 1: araTha1, ce10, ce11, ci3, danRer11, dm6, sacCer3. Part 2: hg38. Part 3: mm39.",mds,True,findable,0,0,0,0,0,2023-09-14T07:29:22.000Z,2023-09-14T07:29:22.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23822154,Dataset for the main experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,Data for the main experiment in CSV format.,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:26.000Z,2023-08-02T11:18:26.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['29026 Bytes'],
+10.5281/zenodo.4753279,Figs. 8-15 in A New Perlodes Species And Its Subspecies From The Balkan Peninsula (Plecoptera: Perlodidae),Zenodo,2012,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 8-15. Perlodes floridus floridus sp. n. (8-11) and P. floridus peloponnesiacus ssp. n. (12-15) eggs. 8, 12. Egg, lateral view. 9, 13. Egg, apical view. 10. Anchor, basolateral view. 11. Anchor, basal view. 14. Anchor, basolateral view. 15. Chorion detail.",mds,True,findable,0,0,4,0,0,2021-05-12T18:32:25.000Z,2021-05-12T18:32:26.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Perlodes","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Perlodes'}]",,
+10.5281/zenodo.1189443,huard/copula 1.0,Zenodo,2018,,Software,Open Access,Bayesian copula selection algorithms. Library of MatLab functions to estimate the probability of different copula models given a joint distribution of fractiles.,mds,True,findable,3,0,1,0,0,2018-03-06T14:11:25.000Z,2018-03-06T14:11:26.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.22613069.v1,Additional file 2 of Digital technologies in routine palliative care delivery: an exploratory qualitative study with health care professionals in Germany,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 2. Consolidated criteria for reporting qualitative research.,mds,True,findable,0,0,0,0,0,2023-04-13T12:27:56.000Z,2023-04-13T12:27:57.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}]",['492390 Bytes'],
+10.5281/zenodo.6324930,Code for Discrete analysis of SWR for a diffusion reaction problem with discontinuous coefficients,Zenodo,2022,en,Software,"Creative Commons Attribution 4.0 International,Open Access","Python3 code used to generate the Figures of the article ""Discrete analysis of SWR for a diffusion reaction problem"". A Jupyter Notebook simplifies the usage.",mds,True,findable,0,0,0,1,0,2022-03-03T08:33:03.000Z,2022-03-03T08:33:04.000Z,cern.zenodo,cern,"Schwarz methods,Waveform relaxation,Semi-discrete","[{'subject': 'Schwarz methods'}, {'subject': 'Waveform relaxation'}, {'subject': 'Semi-discrete'}]",,
+10.5281/zenodo.7866738,"Digital Elevation Models, orthoimages and lava outlines of the 2021 Fagradalsfjall eruption: Results from near real-time photogrammetric monitoring",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the data behind the work described in Pedersen et al (in review), specifically the Digital Elevation Models (DEMs), orthoimages and lava outlines created as part of the near-real time monitoring of the Fagradalsfjall 2021 eruption (SW-Iceland). The processing of the data is explained in detail in the Supplement S2 of Pedersen et al (2022). The data derived from Pléiades surveys includes only the DEMs and the lava outlines. The Pléiades-based orthoimages are subject to license. Please contact the authors for further information about this. <strong>Convention for file naming:</strong> Data: DEM, Ortho, Outline YYYYMMDD_HHMM: Date of acquisition Platform used: Helicopter (HEL), Pléiades (PLE), Hasselblad A6D (A6D) Origin of elevations in DEMs: meters above ellipsoid (zmae) Ground Sampling Distance: 2x2m (DEM) and 30x30cm (Ortho) Cartographic projection: isn93 (see cartographic specifications for further details) <strong>Cartographic specifications:</strong> Cartographic projection: ISN93/Lambert 1993 (EPSG: 3057, https://epsg.io/3057) Horizontal and vertical reference frame: The surveys after 18 April 2021 are in ISN2016/ISH2004, updated locally around the study area in April 2021 (after pre-eruptive deformations occurred). The rest of the surveys of late March and early April were created using several floating reference systems (see Supplement S3 for details), since no ground surveys were available during the first weeks of the data collection. The surveys of 23 March 2021, 31 March 2021 were re-procesed in Gouhier et al., 2022, using the survey done on 18 May 2021 as reference. Origin of elevations: Ellipsoid WGS84 Raster data format: GeoTIFF Raster compression system: ZSTD (http://facebook.github.io/zstd/) Vector data format: GeoPackage (https://www.geopackage.org/)",mds,True,findable,0,0,0,0,0,2023-04-26T09:55:33.000Z,2023-04-26T09:55:33.000Z,cern.zenodo,cern,"Photogrammetry, DEM, volcano monitoring","[{'subject': 'Photogrammetry, DEM, volcano monitoring'}]",,
+10.6084/m9.figshare.24447574.v1,Additional file 1 of Bacterial survival in radiopharmaceutical solutions: a critical impact on current practices,figshare,2023,,Dataset,Creative Commons Attribution 4.0 International,"Additional file 1. Raw data of Pseudomonas aeruginosa (ATCC: 27853), Staphylococcus aureus (ATCC: 25923) and Staphylococcus epidermidis (ATCC: 1228) survival rate in technetium-99m radioactive solutions at 1.85 to 11.1 GBq and non-radioactive technetium-99 solutions were reported.",mds,True,findable,0,0,0,0,0,2023-10-27T03:41:27.000Z,2023-10-27T03:41:27.000Z,figshare.ars,otjm,"Biophysics,Microbiology,FOS: Biological sciences,Environmental Sciences not elsewhere classified,Science Policy,Infectious Diseases,FOS: Health sciences","[{'subject': 'Biophysics'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Environmental Sciences not elsewhere classified'}, {'subject': 'Science Policy'}, {'subject': 'Infectious Diseases'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['353871 Bytes'],
+10.5281/zenodo.4761099,"Fig. 4. Main rheocrene springs and torrents where L in A New Stonefly From Lebanon, Leuctra Cedrus Sp. N. (Plecoptera: Leuctridae)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 4. Main rheocrene springs and torrents where L. cedrus occurs: a = Ouâdi Qâdîcha torrent, Abou Aali tributary, 1500m (type locality); b = El Ksaim spring, El Bared tributary, 1050; c= Rouais spring, Ibrahim tributary, 1300m; d = Aouali River at Jdaidet ech Choûf bridge, 710m.",mds,True,findable,0,0,2,0,0,2021-05-14T07:14:54.000Z,2021-05-14T07:14:54.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.8303080,Benchmark Lab for Hypercompliance Properties on Event Logs,Zenodo,2023,en,Software,"GNU General Public License v2.0 or later,Open Access","This LabPal experimental environment contains the benchmark for hypercompliance properties on event logs, as described in the paper <em>Hypercompliance: Business Process Compliance Across Multiple Executions</em>, published at the EDOC 2023 conference. <strong>Context</strong> Compliance checking is an operation that assesses whether every execution trace of a business process satisfies a given correctness condition. Our work introduces the notion of a hyperquery, which involves multiple traces from a log at the same time. A specific instance of a hyperquery is a hypercompliance condition, which is a correctness requirement that involves the entire log instead of individual process instances. This lab proposes a benchmark for an extension of the BeepBeep 3 event stream engine designed to evaluate hyperqueries on event logs. It evaluates various hyperqueries on event logs that are either synthetic or sourced from real-world online log repositories. Among the elements evaluated are the total and progressive running time needed to evaluate a query, as well as the amount of memory consumed. <strong>Description</strong> This archive contains an instance of LabPal, an environment for running experiments on a computer and collecting their results in a user-friendly way. The author of this archive has set up a set of experiments, which typically involve running scripts on input data, processing their results and displaying them in tables and plots. LabPal is a library that wraps around these experiments and displays them in an easy-to-use web interface. The principle behind LabPal is that all the necessary code, libraries and input data should be bundled within a single self-contained JAR file, such that anyone can download and easily reproduce someone else's experiments. All the plots and other data values mentioned in the paper are automatically generated by the execution of this lab. The lab also provides additional tables and plots that could not fit into the manuscript. Detailed instructions can be found on the LabPal website, [https://liflab.github.io/labpal] <strong>Dataset contents</strong> In addition to this Readme, the dataset is made of three files: hypercompliance-lab-1.0.jar is the runnable instance of the lab hypercompliance-lab-1.0-sources.jar contains the source code of the BeepBeep library and the benchmark hypercompliance-lab-1.0-javadoc.jar contains the documentation of the BeepBeep library and the benchmark <strong>Running LabPal</strong> To start the lab, open a terminal window and type at the command line: <pre><code>java -jar hypercompliance-lab-1.0.jar --autostart</code></pre> You should see something like this: <pre><code>LabPal 2.99 - A versatile environment for running experiments (C) 2014-2022 Laboratoire d'informatique formelle Université du Québec à Chicoutimi, Canada Please visit http://localhost:21212/index to run this lab Hit Ctrl+C in this window to stop</code></pre> Open a web browser and type `http://localhost:21212/index` in the address bar. This should lead you to the main page of LabPal's web control panel. <strong>Using the web interface</strong> A detailed explanation on the use of the LabPal web interface can be found in this YouTube video. A lab is made of a set of *experiments*, each corresponding to a specific set of instructions that runs and generates a subset of all the benchmark's results. Results from experiments are collected and processed into various auto-generated tables and plots. The lab is instructed to immediately start running all the expermients it<br> contains. You can follow the progress of these experiments by going to the<br> Status page and refreshing it periodically. At any point, you can look at<br> the results of the experiments that have run so far. You can do so by: Going to the Plots (5th button in the top menu) or the Tables (6th button) page and see the plots and tables created for this lab being updated in real time Going back to the list of experiments, clicking on one of them and getting the detailed description and data points that this experiment has generated Once the assistant is done, you can export any of the plots and tables to a file, or the raw data points by using the Export button in the Status page.",mds,True,findable,0,0,0,0,0,2023-08-30T20:54:07.000Z,2023-08-30T20:54:08.000Z,cern.zenodo,cern,"compliance checking,business process logs,BeepBeep,hyperqueries,hypercompliance,hyperproperties","[{'subject': 'compliance checking'}, {'subject': 'business process logs'}, {'subject': 'BeepBeep'}, {'subject': 'hyperqueries'}, {'subject': 'hypercompliance'}, {'subject': 'hyperproperties'}]",,
+10.5281/zenodo.4966918,PatricHolmvall/TFTSim: v0.9.1,Zenodo,2013,,Software,"GNU General Public License v3.0 only,Open Access","Latest release of TFTSim (Sep 13 2013). TFTSim is a tool to simulate (classically) trajectories of fragments produced in a Binary or Ternary Fission process, based on their Coulomb interaction right after fissioning. TFTSim can be used to simulate a wide range of basic starting configurations with varying geometrical and intial kinetic energy, based on energy and total momentum conservation. The program uses a simple ode solver to solve the equations of motion to produce particle trajectories, which are fit to experimentally confirmed angular and energy distributions, in order to extract information about what scission configurations are realistic.",mds,True,findable,0,0,0,0,0,2021-06-16T14:25:29.000Z,2021-06-16T14:25:30.000Z,cern.zenodo,cern,"Research Software,Nuclear Fission,Trajectory simulations,Runge-Kutta,Open source code,Ternary Fission,Monte-Carlo","[{'subject': 'Research Software'}, {'subject': 'Nuclear Fission'}, {'subject': 'Trajectory simulations'}, {'subject': 'Runge-Kutta'}, {'subject': 'Open source code'}, {'subject': 'Ternary Fission'}, {'subject': 'Monte-Carlo'}]",,
+10.5281/zenodo.4308510,Amundsen Sea MAR simulations forced by ERAinterim,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>MAR simulations produced by Marion Donat-Magnin at IGE, Grenoble, France.</strong> <br> This simulation is evaluated in the following article: Donat-Magnin, M., Jourdain, N. C., Gallée, H., Amory, C., Kittel, C., Fettweis, X., Wille, J. D., Favier, V., Drira, A., and Agosta, C. (2020). Interannual variability of summer surface mass balance and surface melting in the Amundsen sector, West Antarctica, The Cryosphere, 14, 229–249, https://doi.org/10.5194/tc-14-229-2020 <br> Here are provided the monthly means over 1979-2017. Daily outputs available on demand.<br> <br> See netcdf metadata for more information. Note that what is called runoff in the outputs is not actually a runoff (into the ocean) but more the net production of liquid water at the surface (which can either form ponds or flow into the ocean). Monthly files provided on MAR grid (see MAR_grid10km.nc). We also provide climatological (1979-2017 average) surface mass balance (SMB), surface melt rates and net liquid water production (""runoff"") on a standard 8km WGS84 stereographic grid (see files ending as mean_polar_stereo.nc). The following variables are provided: CC Cloud Cover LHF Latent Heat Flux LWD Long Wave Downward LWU Long Wave Upward QQp Specific Humidity (pressure levels) QQz Specific Humidity (height levels) RH Relative Humidity SHF Sensible Heat Flux SIC Sea ice cover SP Surface Pressure ST Surface Temperature SWD Short Wave Downward SWU Short Wave Upward TI1 Ice/Snow Temperature (snow-layer levels) TTz Temperature (height levels) UUp x-Wind Speed component (pressure levels) UUz x-Wind Speed component (height levels) VVp y-Wind Speed component (pressure levels) VVz y-Wind Speed component (height levels) UVp Horizontal Wind Speed (pressure levels) UVz Horizontal Wind Speed (height levels) ZZp Geopotential Height (pressure levels) mlt Surface melt rate rfz Refreezing rate rnf Rainfall rof Runoff (i.e. net production of surface liquid water) sbl Sublimation smb Surface Mass Balance snf Snowfall",mds,True,findable,0,0,0,0,0,2020-12-06T21:14:02.000Z,2020-12-06T21:14:02.000Z,cern.zenodo,cern,"MAR,Amundsen,surface mass balance,surface melting","[{'subject': 'MAR'}, {'subject': 'Amundsen'}, {'subject': 'surface mass balance'}, {'subject': 'surface melting'}]",,
+10.6084/m9.figshare.23822163,Dataset key for the main experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,Key for the dataset for the main experiment,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:29.000Z,2023-08-02T11:18:29.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['1240 Bytes'],
+10.5281/zenodo.2651652,Results of the initMIP-Antarctica experiments: an ice sheet initialization intercomparison of ISMIP6,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This archive provides the forcing data and ice sheet model output produced as part of the publication "" initMIP-Antarctica: an ice sheet model initialization experiment of ISMIP6"", published in The Cryosphere, https://www.the-cryosphere.net/13/1441/2019/ Seroussi, H., Nowicki, S., Simon, E., Abe-Ouchi, A., Albrecht, T., Brondex, J., Cornford, S., Dumas, C., Gillet-Chaulet, F., Goelzer, H., Golledge, N. R., Gregory, J. M., Greve, R., Hoffman, M. J., Humbert, A., Huybrechts, P., Kleiner, T., Larour, E., Leguy, G., Lipscomb, W. H., Lowry, D., Mengel, M., Morlighem, M., Pattyn, F., Payne, A. J., Pollard, D., Price, S. F., Quiquet, A., Reerink, T. J., Reese, R., Rodehacke, C. B., Schlegel, N.-J., Shepherd, A., Sun, S., Sutter, J., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., and Zhang, T.: initMIP-Antarctica: an ice sheet model initialization experiment of ISMIP6, The Cryosphere, 13, 1441-1471, https://doi.org/10.5194/tc-13-1441-2019, 2019. Contact: Helene Seroussi, Helene.seroussi@jpl.nasa.gov Further information on ISMIP6 and initMIP-Antarctica can be found here:<br> http://www.climate-cryosphere.org/activities/targeted/ismip6<br> http://www.climate-cryosphere.org/wiki/index.php?title=InitMIP-Antarctica Users should cite the original publication when using all or part of the data. <br> In order to document CMIP6’s scientific impact and enable ongoing support of CMIP, users are also obligated to acknowledge CMIP6, ISMIP6 and the participating modeling groups. Archive overview<br> ----------------<br> README.txt - this information dSMB.zip - Surface mass balance anomaly forcing data and description<br> dSMB/<br> dSMB_AIS_01km.nc<br> dSMB_AIS_02km.nc<br> dSMB_AIS_04km.nc<br> dSMB_AIS_08km.nc<br> dSMB_AIS_16km.nc<br> dSMB_AIS_32km.nc<br> README_dSMB_AIS.txt dBasalMelt.zip – Ice shelf Basal Melt anomaly forcing data and description<br> dBasalMelt/<br> dBasalMelt_AIS_01km.nc<br> dBasalMelt_AIS_02km.nc<br> dBasalMelt_AIS_04km.nc<br> dBasalMelt_AIS_08km.nc<br> dBasalMelt_AIS_16km.nc<br> dBasalMelt_AIS_32km.nc<br> README_dBasalMelt_AIS.txt <group>_<model>_<experiment>.zip - The model output per group, model and experiment (init, ctrl, asmb, abmb)<br> <group1>_<model1>_init/<br> acabf_AIS_<group1>_<model1>_init.nc<br> ...<br> <group1>_<model1>_ctrl/<br> acabf_AIS_<group1>_<model1>_ctrl.nc<br> ...<br> <group1>_<model1>_asmb/<br> acabf_AIS_<group1>_<model1>_asmb.nc<br> ...<br> <group1>_<model1>_abmb/<br> acabf_AIS_<group1>_<model1>_abmb.nc<br> ... <group1>_<model2>_init/<br> ...<br> <group1>_<model2>_ctrl/<br> ...<br> <group1>_<model2>_asmb/<br> ...<br> <group1>_<model2>_abmb/<br> ... <group2>_<model1>_init/<br> ...<br> <group2>_<model1>_ctrl/<br> ...<br> <group2>_<model1>_asmb/<br> ...<br> <group2>_<model1>_asmb/<br> ... The following script may be used to download the content of the archive.<br> #!/bin/bash<br> wget https://zenodo.org/record/2651652/files/README.txt<br> wget https://zenodo.org/record/2651652/files/dSMB.zip<br> wget https://zenodo.org/record/2651652/files/dBasalMelt.zip for amodel in ARC_PISM1 ARC_PISM2 ARC_PISM3 ARC_PISM4 AWI_PISM1Eq AWI_PISM1Pal CPOM_BISICLES_A_500m CPOM_BISICLES_B_500m DMI_PISM0 DMI_PISM1 DOE_MALI IGE_ELMER ILTS_SICOPOLIS1 ILTS_SICOPOLIS2 IMAU_IMAUICE JPL1_ISSM LSCE_GRISLI NCAR_CISM PIK_PISM3PAL PIK_PISM4EQUI PSU_EQNOMEC PSU_GLNOMEC UCIJPL_ISSM ULB_FETISH1 VUB_AISMPALEO; do<br> wget https://zenodo.org/record/2651652/files/${amodel}_init.zip<br> wget https://zenodo.org/record/2651652/files/${amodel}_ctrl.zip<br> wget https://zenodo.org/record/2651652/files/${amodel}_asmb.zip<br> wget https://zenodo.org/record/2651652/files/${amodel}_abmb.zip done",mds,True,findable,5,0,0,0,0,2019-07-22T10:02:20.000Z,2019-07-22T10:02:21.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3932935,Results of the AbuMIP experiments: The Antarctic BUttressing Model Intercomparison Project,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This archive provides the model result of the AbuMIP experiments: The Antarctic BUttressing Model Intercomparison Project.,mds,True,findable,0,0,0,0,0,2020-07-16T13:21:34.000Z,2020-07-16T13:21:35.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8091094,Data from 'Modeling and Solving Framework for Tactical Maintenance Planning Problems with Health Index considerations',Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Datasets used in the manuscript 'Modeling and Solving Framework for Tactical Maintenance Planning Problems with Health Index considerations' - bi-criteria-analysis-instances : instances corresponding to the experiments of section 4.3 - dedicated-matheuristic-instances : instances corresponding to the experiments of section 4.4 Format: CPLEX .dat data files,mds,True,findable,0,0,0,0,0,2023-06-28T13:28:39.000Z,2023-06-28T13:28:40.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7890462,Hydrological Response of Andean Catchments to Recent Glacier Mass Loss (data),Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Data related to the article in review (The Cryosphere journal),mds,True,findable,0,0,0,0,0,2023-05-03T10:31:42.000Z,2023-05-03T10:31:43.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.2789093,Seismic analysis of the detachment and impact phases of a rockfall and application for estimating rockfall volume and free-fall height,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Digital Elevation models of the Mount Granier and Mount Saint-Eynard. Mount Saint-Eynard DEMs were carried out using an Optech Ilris-LR laser scanner. Mount Granier DEMs were carried out by photogrammetry.,mds,True,findable,0,0,0,0,0,2019-05-14T10:03:04.000Z,2019-05-14T10:03:05.000Z,cern.zenodo,cern,"DEM,Mount Granier,Mount Saint-Eynard,TLS,photogrammetry","[{'subject': 'DEM'}, {'subject': 'Mount Granier'}, {'subject': 'Mount Saint-Eynard'}, {'subject': 'TLS'}, {'subject': 'photogrammetry'}]",,
+10.5281/zenodo.5835977,FIGURE 2. Bulbophyllum strigosum Garay. A. Flowering plant. B. Inflorescences. C. Floral bract. D in Bulbophyllum section Rhytionanthos (Orchidaceae) in Vietnam with description of new taxa and new national record,Zenodo,2022,,Image,Open Access,"FIGURE 2. Bulbophyllum strigosum Garay. A. Flowering plant. B. Inflorescences. C. Floral bract. D. Flowers, half side, side, and back views. E. Median sepal, adaxial and abaxial side. F. Median sepal margin. G. Lateral sepals, adaxial and abaxial sides. H. Lateral sepal margin. I. Petals, adaxial and abaxial side. J. Lip, views from different sides. K. Pedicel, ovary and column, side view. L. Column, frontal and side views. M. Anther cap, views from different sides. N. Pollinia. Photos by Truong Ba Vuong, correction and design by L. Averyanov and T. Maisak.",mds,True,findable,0,0,2,0,0,2022-01-11T09:00:34.000Z,2022-01-11T09:00:35.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Bulbophyllum","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Bulbophyllum'}]",,
+10.5281/zenodo.5242879,Finnish DBnary archive in original Lemon format,Zenodo,2021,fi,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Finnish language edition, ranging from 3rd September 2012 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br>",mds,True,findable,0,0,0,0,0,2021-08-24T10:11:12.000Z,2021-08-24T10:11:13.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.8421879,Inference of Robust Reachability Constraints,Zenodo,2023,,Software,"Creative Commons Attribution 4.0 International,Open Access","Characterization of bugs and attack vectors is in many practical scenarios as important as their finding.<br> Recently, Girol et al. have introduced the concept of robust reachability which ensures a perfect reproducibility<br> of the reported violations by distinguishing input which are under the control of the attacker (controlled input)<br> from those which are not (uncontrolled input), and proposed first automated analysis for it. While it is a step<br> toward distinguishing severe bugs from benign ones, it fails to describe violations that are mostly reproducible,<br> i.e., when triggering conditions are likely to happen, meaning that they happen for all uncontrolled input but<br> a few corner cases. To address this issue, we propose to leverage theory-agnostic abduction techniques to<br> generate constraints on the uncontrolled program input that ensure that a target property is robustly satisfied,<br> which is an extension of robust reachability that is generic on the type of trace property and on the technology<br> used to verify the properties. We show that our approach is complete w.r.t. its inference language, and we<br> additionally discuss strategies for the efficient exploration of the inference space. We finally demonstrate the<br> feasibility of the method with an implementation that uses robust reachability oracles to generate constraints<br> on standard benchmarks from software verification and security analysis, and its practical ability to refine the<br> notion of robust reachability. We illustrate the use of our implementation to a vulnerability characterization<br> problem in the context of fault injection attacks. Our method overcomes a major limitation of the initial<br> proposal of robust reachability, without complicating its definition. From a practical view, this is a step toward<br> new verification tools that are able to characterize program violations through high-level feedback.",mds,True,findable,0,0,0,0,0,2023-10-09T22:31:32.000Z,2023-10-09T22:31:32.000Z,cern.zenodo,cern,,,,
+10.7275/bp3n-mw53,Impact of Leverage on Financial Information Quality: International Evidence from the Hospitality Industry,University of Massachusetts Amherst,2020,,Text,,,fabricaForm,True,findable,0,0,0,0,0,2020-04-30T16:31:17.000Z,2020-04-30T16:31:18.000Z,umass.uma,umass,,,,
+10.5061/dryad.f4qrfj6wr,Effects of population density on static allometry between horn length and body mass in mountain ungulates,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Little is known about the effects of environmental variation on allometric relationships of condition-dependent traits, especially in wild populations. We estimated sex-specific static allometry between horn length and body mass in four populations of mountain ungulates that experienced periods of contrasting density over the course of the study. These species displayed contrasting sexual dimorphism in horn size; high dimorphism in Capra ibex and Ovis canadensis and low dimorphism in Rupicapra rupicapra and Oreamnos americanus. The effects of density on static allometric slopes were weak and inconsistent while allometric intercepts were generally lower at high density, especially in males from species with high sexual dimorphism in horn length. These results confirm that static allometric slopes are more canalized than allometric intercepts against environmental variation induced by changes in population density, particularly when traits appear more costly to produce and maintain.",mds,True,findable,152,15,0,1,0,2021-09-15T18:12:43.000Z,2021-09-15T18:12:44.000Z,dryad.dryad,dryad,"FOS: Natural sciences,FOS: Natural sciences,Density dependence,Alpine ungulates,horn","[{'subject': 'FOS: Natural sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Natural sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Density dependence'}, {'subject': 'Alpine ungulates'}, {'subject': 'horn'}]",['521318 bytes'],
+10.5281/zenodo.3354711,MaSS - Multilingual corpus of Sentence-aligned Spoken utterances,Zenodo,2019,,Dataset,"MIT License,Open Access","<strong>Abstract</strong> The CMU Wilderness Multilingual Speech Dataset is a newly published multilingual speech dataset based on recorded readings of the New Testament. It provides data to build Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) models for potentially 700 languages. However, the fact that the source content (the Bible), is the same for all the languages is not exploited to date. Therefore, this article proposes to add multilingual links between speech segments in different languages, and shares a large and clean dataset of 8,130 para-lel spoken utterances across 8 languages (56 language pairs).We name this corpus MaSS (Multilingual corpus of Sentence-aligned Spoken utterances). The covered languages (Basque, English, Finnish, French, Hungarian, Romanian, Russian and Spanish) allow researches on speech-to-speech alignment as well as on translation for syntactically divergent language pairs. The quality of the final corpus is attested by human evaluation performed on a corpus subset (100 utterances, 8 language pairs). Paper | GitHub Repository containing the scripts needed to build the data set from scratch (if needed) <strong>Project structure</strong> This repository contains 8 Numpy files, one for each featured language, pickled with Python 3.6. Each line corresponds to the spectrogram of the file mentioned in the file <em>verses.csv</em>. There is a direct mapping between the ID of the verse and its index in the list (thus verse with ID 5634 is located at index 5634 in the Numpy file). Verses not available for a given language (as stated by the value ""Not Available"" in the CSV file) are represented by empty lists in the Numpy files, thus ensuring a perfect verse-to-verse alignement between each file. Spectrogram were extracted using Librosa with the following parameters: <pre><code>Pre-emphasis = 0.97 Sample rate = 16000 Window size = 0.025 Window stride = 0.01 Window type = 'hamming' Mel coefficients = 40 Min frequency = 20</code></pre>",mds,True,findable,0,0,0,0,0,2019-07-30T10:39:20.000Z,2019-07-30T10:39:21.000Z,cern.zenodo,cern,"parallel speech corpus, multilingual alignment, speech-to-speech alignment, speech-to-speech translation","[{'subject': 'parallel speech corpus, multilingual alignment, speech-to-speech alignment, speech-to-speech translation'}]",,
+10.5281/zenodo.8348922,cta-observatory/pyirf: v0.10.1 – 2023-09-15,Zenodo,2023,,Software,"MIT License,Open Access",*pyirf* is a python3-based library for the generation of Instrument Response Functions (IRFs) and sensitivities for the Cherenkov Telescope Array (CTA),mds,True,findable,0,0,0,0,0,2023-09-15T12:52:25.000Z,2023-09-15T12:52:25.000Z,cern.zenodo,cern,"gamma-ray astronomy,Imaging Atmospheric Cherenkov Telescope,IACT,CTA,instrument response,irf,python","[{'subject': 'gamma-ray astronomy'}, {'subject': 'Imaging Atmospheric Cherenkov Telescope'}, {'subject': 'IACT'}, {'subject': 'CTA'}, {'subject': 'instrument response'}, {'subject': 'irf'}, {'subject': 'python'}]",,
+10.5281/zenodo.8226430,Geometrical frustration and incommensurate magnetic order in Na3RuO4 with two triangular motifs,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Auxiliary data for the frustrated magnet Na3RuO4: magnetic susceptibility, specific heat, lattice parameters, magnetic moments, and the results of DFT calculations for the magnetic exchange couplings",mds,True,findable,0,0,0,0,0,2023-08-08T19:46:39.000Z,2023-08-08T19:46:39.000Z,cern.zenodo,cern,"frustrated magnet,DFT,magnetic properties","[{'subject': 'frustrated magnet'}, {'subject': 'DFT'}, {'subject': 'magnetic properties'}]",,
+10.5281/zenodo.4764317,Data from: Phylogenomic analysis of the explosive adaptive radiation of the Espeletia complex (Asteraceae) in the tropical Andes,Zenodo,2021,,Other,"Creative Commons Attribution 4.0 International,Open Access","The subtribe Espeletiinae (Asteraceae) is endemic to the high-elevations in the Northern Andes. It exhibits an exceptional diversity of species, growth-forms and reproductive strategies, including large trees, dichotomous trees, shrubs and the extraordinary giant monocarpic or polycarpic caulescent rosettes, considered as a classic example of adaptation in tropical high-elevation ecosystems. The subtribe has long been recognised as a prominent case of adaptive radiation, but the understanding of its evolution has been hampered by a lack of phylogenetic resolution. Here we produce the first fully resolved phylogeny of all morphological groups of Espeletiinae, using whole plastomes and about a million nuclear nucleotides obtained with an original de novo assembly procedure without reference genome, and analysed with traditional and coalescent-based approaches that consider the possible impact of incomplete lineage sorting and hybridisation on phylogenetic inference. We show that the diversification of Espeletiinae started from a rosette ancestor about 2.3 Ma, after the final uplift of the Northern Andes. This was followed by two rather independent radiations in the Colombian and Venezuelan Andes, with a few trans-cordilleran dispersal events among low-elevation tree lineages but none among high-elevation rosettes. We demonstrate complex scenarios of morphological change in Espeletiinae, usually implying the convergent evolution of growth-forms with frequent loss/gains of various traits. For instance, caulescent rosettes evolved independently in both countries, likely as convergent adaptations to life in tropical high-elevation habitats. Tree growth-forms evolved independently three times from the repeated colonisation of lower elevations by high-elevation rosette ancestors. The rate of morphological diversification increased during the early phase of the radiation, after which it decreased steadily towards the present. On the other hand, the rate of species diversification in the best-sampled Venezuelan radiation was on average very high (3.1 spp/My), with significant rate variation among growth-forms (much higher in polycarpic caulescent rosettes). Our results point out a scenario where both adaptive morphological evolution and geographical isolation due to Pleistocene climatic oscillations triggered an exceptionally rapid radiation for a continental plant group.",mds,True,findable,0,0,0,1,0,2021-05-21T04:38:47.000Z,2021-05-21T04:38:49.000Z,cern.zenodo,cern,"Espeletiinae,caulescent rosette,Páramo,tropical high-elevation,explosive diversification","[{'subject': 'Espeletiinae'}, {'subject': 'caulescent rosette'}, {'subject': 'Páramo'}, {'subject': 'tropical high-elevation'}, {'subject': 'explosive diversification'}]",,
+10.6084/m9.figshare.22613069,Additional file 2 of Digital technologies in routine palliative care delivery: an exploratory qualitative study with health care professionals in Germany,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 2. Consolidated criteria for reporting qualitative research.,mds,True,findable,0,0,0,0,0,2023-04-13T12:27:56.000Z,2023-04-13T12:27:57.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}]",['492390 Bytes'],
+10.34847/nkl.2bad8uj6,Carte des mémoires sensibles de la Romanche - version finale,NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,PhysicalObject,,"Représentation cartographique par AAU-CRESSON (Laure Brayer, Ryma Hadbi, Rachel Thomas et alii) à partir des récits collectés dans la vallée de la Romanche (2018-2021) par AAU-CRESSON et Regards des Lieux.
+
+Les multiples récits collectés au cours des arpentages et des rencontres réalisés dans la vallée ont constitué la matière première d’une représentation cartographique dont l’ambition est de faire état de la polyphonie des expériences des lieux. En représentant les mémoires sensibles de la vallée par le bais de diverses opérations de traduction à l’origine de ce travail cartographique, l’enjeu sous-jacent est de questionner des formes possibles d’une écriture sensible critique. En tentant de mettre en partage les rapports pluriels et parfois contradictoires au paysage, la carte est interrogée comme potentiel lieu d’élaboration d’une critique concernée dont les expériences sensibles sont le terreau.
+
+Cette carte est la version finale d'octobre 2021 faite sur Illustrator (Adobe). Il s'agit de l'actualisation de la carte intermédiaire qui prend en compte les réactions et retours des habitants suite à la présentation lors de la journée ""Au fil de l'eau 2"" en juin 2021. Elle a été présentée lors de la journée d'études Les Ondes de l’Eau « Traduction cartographique des mémoires sensibles de la Romanche » en octobre 2021 pour être mise en discussion.",api,True,findable,0,0,0,0,0,2022-06-27T12:34:23.000Z,2022-06-27T12:34:23.000Z,inist.humanum,jbru,"enquêtes de terrain (ethnologie),Désindustrialisation,Patrimoine industriel,Pollution de l'air,Montagnes – aménagement,Énergie hydraulique,Rives – aménagement,Cartographie critique,Représentation graphique,Romanche, Vallée de la (France),Keller, Charles Albert (1874-1940,Ingénieur A&M),Histoires de vie,Cartographie sensible,Mémoires des lieux,histoire orale,patrimoine immatériel,Sens et sensations,Perception de l'espace,Récit personnel,carte sensible","[{'lang': 'fr', 'subject': 'enquêtes de terrain (ethnologie)'}, {'lang': 'fr', 'subject': 'Désindustrialisation'}, {'lang': 'fr', 'subject': 'Patrimoine industriel'}, {'lang': 'fr', 'subject': ""Pollution de l'air""}, {'lang': 'fr', 'subject': 'Montagnes – aménagement'}, {'lang': 'fr', 'subject': 'Énergie hydraulique'}, {'lang': 'fr', 'subject': 'Rives – aménagement'}, {'lang': 'fr', 'subject': 'Cartographie critique'}, {'lang': 'fr', 'subject': 'Représentation graphique'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'Keller, Charles Albert (1874-1940'}, {'lang': 'fr', 'subject': 'Ingénieur A&M)'}, {'lang': 'fr', 'subject': 'Histoires de vie'}, {'lang': 'fr', 'subject': 'Cartographie sensible'}, {'lang': 'fr', 'subject': 'Mémoires des lieux'}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'patrimoine immatériel'}, {'lang': 'fr', 'subject': 'Sens et sensations'}, {'lang': 'fr', 'subject': ""Perception de l'espace""}, {'lang': 'fr', 'subject': 'Récit personnel'}, {'lang': 'fr', 'subject': 'carte sensible'}]","['16654505 Bytes', '70369012 Bytes']","['image/jpeg', 'application/pdf']"
+10.5281/zenodo.6806404,pete-d-akers/scadi-d15N-SMB: SCADI nitrate and surface mass balance analysis,Zenodo,2022,en,Software,Open Access,Release v1.1. This version contains the complete R code for the SCADI project and associated publications as of 07 July 2022. Changes from v1.0 is removal of one plotted supplemental figure that was removed from linked publication.,mds,True,findable,0,0,0,1,0,2022-07-07T10:41:49.000Z,2022-07-07T10:41:49.000Z,cern.zenodo,cern,,,,
+10.7280/d1mm37,Annual Ice Velocity of the Greenland Ice Sheet (1972-1990),Dryad,2019,en,Dataset,Creative Commons Attribution 4.0 International,"We derive surface ice velocity using data from 16 satellite sensors deployed by 6 different space agencies. The list of sensors and the year that they were used are listed in the following (Table S1). The SAR data are processed from raw to single look complex using the GAMMA processor (www.gamma-rs.ch). All measurements rely on consecutive images where the ice displacement is estimated from tracking or interferometry (Joughin et al. 1998, Michel and Rignot 1999, Mouginot et al. 2012). Surface ice motion is detected using a speckle tracking algorithm for SAR instruments and feature tracking for Landsat. The cross-correlation program for both SAR and optical images is ampcor from the JPL/Caltech repeat orbit interferometry package (ROI_PAC). We assembled a composite ice velocity mosaic at 150 m posting using our entire speed database as described in Mouginot et al. 2017 (Fig. 1A). The ice velocity maps are also mosaicked in annual maps at 150 m posting, covering July, 1st to June, 30th of the following year, i.e. centered on January, 1st (12) because a majority of historic data were acquired in winter season, hence spanning two calendar years. We use Landsat-1&2/MSS images between 1972 and 1976 and combine image pairs up to 1 years apart to measure the displacement of surface features between images as described in Dehecq et al., 2015 or Mouginot et al. 2017. We use the 1978 2-m orthorectified aerial images to correct the geolocation of Landsat-1 and -2 images (Korsgaard et al., 2016). Between 1984 and 1991, we processed Landsat-4&5/TM image pairs acquired up to 1-year apart. Only few Landsat-4 and -5 images (~3%) needed geocoding refinement using the same 1978 reference as used previously. Between 1991 and 1998, we process radar images from the European ERS-1/2, with a repeat cycle varying from 3 to 36 days depending on the mission phase. Between 1999 and 2013, we use Landsat-7, ASTER, RADARSAT-1/2, ALOS/PALSAR, ENVISAT/ASAR to determine surface velocity (Joughin et al., 2010; Howat, I. 2017; Rignot & Mouginot, 2012). After 2013, we use Landsat-8, Sentinel-1a/b and RADARSAT-2 (Mouginot et al., 2017). All synthetic aperture radar (SAR) datasets are processed assuming surface parallel flow using the digital elevation model (DEM) from the Greenland Mapping Project (GIMP; Howat et al., 2014) and calibrated as described in Mouginot et al., 2012, 2017. Data were provided by the European Space Agency (ESA) the EU Copernicus program (through ESA), the Canadian Space Agency (CSA), the Japan Aerospace Exploration Agency (JAXA), the Agenzia Spaziale Italiana (ASI), the Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) and the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS). SAR data acquisition were coordinated by the Polar Space Task Group (PSTG). References: Dehecq, A, Gourmelen, N, Trouve, E (2015). Deriving large-scale glacier velocities from a complete satellite archive: Application to the Pamir-Karakoram-Himalaya. Remote Sensing of Environment, 162, 55–66. Howat IM, Negrete A, Smith BE (2014) The greenland ice mapping project (gimp) land classification and surface elevation data sets. The Cryosphere 8(4):1509–1518. Howat, I (2017). MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from Optical Images, Version 2. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. Joughin, I., B. Smith, I. Howat, T. Scambos, and T. Moon. (2010). Greenland Flow Variability from Ice-Sheet-Wide Velocity Mapping, J. of Glac.. 56. 415-430. Joughin IR, Kwok R, Fahnestock MA (1998) Interferometric estimation of three dimensional ice-flow using ascending and descending passes. IEEE Trans. Geosci. Remote Sens. 36(1):25–37. Joughin, I, Smith S, Howat I, and Scambos T (2015). MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. Michel R, Rignot E (1999) Flow of Glaciar Moreno, Argentina, from repeat-pass Shuttle Imaging Radar images: comparison of the phase correlation method with radar interferometry. J. Glaciol. 45(149):93–100. Mouginot J, Scheuchl B, Rignot E (2012) Mapping of ice motion in Antarctica using synthetic-aperture radar data. Remote Sens. 4(12):2753–2767. Mouginot J, Rignot E, Scheuchl B, Millan R (2017) Comprehensive annual ice sheet velocity mapping using landsat-8, sentinel-1, and radarsat-2 data. Remote Sensing 9(4). Rignot E, Mouginot J (2012) Ice flow in Greenland for the International Polar Year 2008- 2009. Geophys. Res. Lett. 39, L11501:1–7.",mds,True,findable,1196,207,0,3,0,2018-12-14T09:39:45.000Z,2018-12-14T09:39:46.000Z,dryad.dryad,dryad,,,['7913047164 bytes'],
+10.34746/cahierscostech48,Université Virtuelle Africaine (UVA) et universités partenaires en Afrique : Entretien commenté,Cahiers Costech,2018,fr,JournalArticle,Creative Commons Attribution Non Commercial Share Alike 4.0 International,"Cette publication qui n’a pas pour ambition de lancer un nouveau type d’entretien, se présente sous une forme originale structurée en deux parties. La première donne à voir la version initiale d’une proposition de publication dont l’objectif était de rendre compte d’un travail de terrain constitué par la transcription d’un entretien et de son analyse au regard du sujet de thèse. La seconde partie présente les améliorations apportées à la version initiale suite aux commentaires formulés par les deux enseignants-chercheurs responsables de la rubrique « Education et numérique » des Cahiers Costech sollicités pour la publication. L’intérêt de cette démarche est de mettre en évidence le travail de conscientisation du doctorant résultant des directives pédagogiques des relecteurs.
+",fabricaForm,True,findable,0,0,0,0,0,2022-07-06T12:43:45.000Z,2022-07-06T12:43:46.000Z,inist.utc,vcob,Education et technologie - Méthodologie de recherche - Simondon,[{'subject': 'Education et technologie - Méthodologie de recherche - Simondon'}],,
+10.5281/zenodo.4769825,"PrISM satellite rainfall product (2010-2020) based on SMOS soil moisture measurements in Africa (3h, 0.25°)",Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The PrISM product is a satellite rainfall product initially designed for Africa over a regular grid at 0.25° (about 25x25 km²) and every 3 hours. It is obtained from the synergy of SMOS satellite soil moisture measurements and CMORPH-raw precipitation product through the PrIMS algorithm (<em>Pellarin et al., 2009, 2013, 2020, Louvet et al., 2015, </em>Román-Cascón et al. 2017).",mds,True,findable,0,0,0,0,0,2021-05-18T12:58:13.000Z,2021-05-18T12:58:14.000Z,cern.zenodo,cern,Rainfall product (mm/3h) in Africa (2010-2020),[{'subject': 'Rainfall product (mm/3h) in Africa (2010-2020)'}],,
+10.5281/zenodo.3405119,Proteomic characterization of human exhaled breath condensate.,Zenodo,2018,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","datasets from 3 studies, for In-depth proteomics characterization of exhaled breath condensate (EBC). 1) Lacombe M. et al, 2018 2) Muccilli V. et al, 2015 3) Bredberg A. et al, 2012",mds,True,findable,367,0,0,0,0,2019-09-11T12:00:51.000Z,2019-09-11T12:00:51.000Z,cern.zenodo,cern,"proteomics, exhaled breath condensate","[{'subject': 'proteomics, exhaled breath condensate'}]",,
+10.5281/zenodo.3528068,DeepPredSpeech: computational models of predictive speech coding based on deep learning,Zenodo,2018,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains all data, source code, pre-trained computational predictive models and experimental results related to: Hueber T., Tatulli E., Girin L., Schwatz, J-L ""How predictive can be predictions in the neurocognitive processing of auditory and audiovisual speech? A deep learning study."" (biorXiv preprint https://doi.org/10.1101/471581). Raw data are extracted from the publicly available database NTCD-TIMIT (10.5281/zenodo.260228). Audio recordings are available in the audio_clean/ directory Post-processed lip image sequences are available in the lips_roi/ directory (67x67 pixels, 8bits, obtained by lossless inverse DCT-2D transform from the DCT feature available in the original repository of NTCD-TIMIT) Phonetic segmentation (extracted from NTCD-TIMIT original zenodo repository) is available in the HTK MLF file volunteer_labelfiles.mlf Audio features (MFCC-spectrogram and log-spectrogram) are available in the mfcc_16k/ and fft_16k/ directories. Models (audio-only, video-only and audiovisual, based on deep feed-forward neural networks and/or convolutional neural network, in .h5 format, trained with Keras 2.0 toolkit) and data normalization parameters (in .dat scikit-learn format) are available in models_mfcc/ and models_logspectro/ directories Predicted and target (ground truth) MFCC-spectro (resp. log-spectro) for the test databases (1909 sentences), and for the different values of \(\tau_p\) or \(\tau_f\) are available in pred_testdb_mfccspectro/ (resp. pred_testdb_logspectro/) directory Source code for extracting audio features, training and evaluating the models is available on GitHub https://github.com/thueber/DeepPredSpeech/ All directories have been zipped before upload. Feel free to contact me for more details. Thomas Hueber, Ph. D., CNRS research fellow, GIPSA-lab, Grenoble, France, thomas.hueber@gipsa-lab.fr",mds,True,findable,0,0,0,0,0,2019-11-04T14:03:16.000Z,2019-11-04T14:03:17.000Z,cern.zenodo,cern,"deep learning, computational model, multimodal, audiovisual, speech, predictive coding","[{'subject': 'deep learning, computational model, multimodal, audiovisual, speech, predictive coding'}]",,
+10.5281/zenodo.4639769,Upslope migration of snow avalanches in a warming climate: data and model source files,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Complete data and model source files corresponding to: Giacona, F., Eckert, N., Corona, C., Mainieri, R., Morin, S., Stoffel, M., Martin, B., Naaim, M. (2021). Upslope migration of snow avalanches in a warming climate. Proceedings of the National Academy of Sciences America, Nov 2021, 118 (44) e2107306118; DOI: 10.1073/pnas.2107306118",mds,True,findable,0,0,0,0,0,2021-09-21T09:49:24.000Z,2021-09-21T09:49:25.000Z,cern.zenodo,cern,"Natural Hazards,Cryosphere,Climate change,Historical Data,Hierarchical Bayesian Modelling","[{'subject': 'Natural Hazards'}, {'subject': 'Cryosphere'}, {'subject': 'Climate change'}, {'subject': 'Historical Data'}, {'subject': 'Hierarchical Bayesian Modelling'}]",,
+10.5281/zenodo.7307797,SolSysELTs2022 Part II: Discussion: Ice-Rich Small Bodies,Zenodo,2022,en,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access",Discussion: video recording,mds,True,findable,0,0,0,0,0,2022-11-09T12:28:01.000Z,2022-11-09T12:28:01.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7547644,Tarification des services AnaEE France,Zenodo,2023,,Other,"Creative Commons Attribution 4.0 International,Open Access","Guide méthodologique construit dans le cadre d’une réflexion collective sur les services AnaEE France n’engageant pas les organismes tutelles de l’infrastructure. Ce document propose une méthodologie et des principes de tarification pour les services de l'infrastructure nationale AnaEE-France. Nous rappelons que ces services couvrent l’accès aux plateformes expérimentales, la production d’analyses pour caractériser les écosystèmes, la mise à disposition d’instruments et d’échantillons, et l’accès aux plateformes de modélisation.",mds,True,findable,0,0,0,0,0,2023-01-18T13:23:22.000Z,2023-01-18T13:23:22.000Z,cern.zenodo,cern,"tarification,service,coût complet,audit","[{'subject': 'tarification'}, {'subject': 'service'}, {'subject': 'coût complet'}, {'subject': 'audit'}]",,
+10.5281/zenodo.888977,MB2017: Artificial spiking neural data with ground truth,Zenodo,2017,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset comprises simulated extracellular spiking neural signals, for which the activity of the active neurons is known. These data can thus be used to test spike sorting algorithms.
+
+This dataset has been generated for the study reported in:
+
+Bernert M, Yvert B (2018) An attention-based spiking neural network for unsupervised spike-sorting. International Journal of Neural Systems, https://doi.org/10.1142/S0129065718500594
+
+Please cite this paper as a reference.",mds,True,findable,0,0,0,0,0,2019-01-03T14:33:40.000Z,2019-01-03T14:33:41.000Z,cern.zenodo,cern,"microelectrode, action potentials, spike sorting, extracellular neural activity","[{'subject': 'microelectrode, action potentials, spike sorting, extracellular neural activity'}]",,
+10.5281/zenodo.8408515,Simulated hydrological effects of grooming and snowmaking in a ski resort on the local water balance,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset to reproduce Figure 9 in Morin et. al, 2023, Simulated hydrological effects of grooming and snowmaking in a ski resort on the local water balance, Hydro. Earth. Syst. Sci.",mds,True,findable,0,0,0,0,0,2023-10-04T22:22:16.000Z,2023-10-04T22:22:16.000Z,cern.zenodo,cern,"climate change, ski tourism, water, hydrology, snowmaking","[{'subject': 'climate change, ski tourism, water, hydrology, snowmaking'}]",,
+10.34847/nkl.76abr599,Parcourir la ville : un jeu d'enfants,NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,fr,Sound,,"Enregistrement sonore réalisé pour le Forum Mobi'Kids intitulé « l’enfant autonome au défi de la ville » (juillet 2022, Rennes) dans le cadre de la recherche Mobikids - Le rôle des cultures éducatives urbaines (CEU) dans l'évolution des mobilités quotidiennes et des contextes de vie des enfants. Collecte et analyse de traces géolocalisées et enrichies sémantiquement 2017-2021 (ANR-16-CE22-0009).
+Equipe :
+Responsable scientifique. DEPEAU Sandrine
+Laboratoires, entreprises impliqués : ESO-Rennes, UMR Pacte, UMR AAU, LIFAT, PME Alkante, PME RF Track,
+Pour l'équipe AAU-CRESSON : THIBAUD Jean-Paul, MANOLA Théa, MCOISANS juL, AUDAS Nathalie.
+
+Cette fiction s’inspire de l’enquête menée auprès des enfants ayant réalisé des parcours commentés entre l’école et le domicile. Les deux personnages ainsi créés, Camille et Sacha, évoquent des moments de vie, des anecdotes, des manières de faire, des formes d’attention, repérés chez différents enfants et sont racontés comme une histoire pour faire ressortir sous une forme originale les principales tendances et résultats obtenus au cours de cette recherche.
+
+Deux enfants racontent leurs déplacements quotidiens entre l’école et le domicile. A travers leurs échanges, nous découvrons la ville à hauteur d’enfants au travers des espaces parcourus, seul.e ou accompagné.e. Ils évoquent ce qu’ils aiment faire ou non sur ce trajet, ce dont ils ont peur, ce qui les attire ou les repousse. Apparaissent aussi les recommandations et autres conseils ou avertissements parentaux. Par le rythme de leurs déplacements, leurs choix de cheminements, le besoin d’être et de jouer avec les copains/copines, leurs descriptions des environnements traversés, se dessinent les expériences urbaines enfantines. Les ambiances sonores des lieux parcourus sonorisent les voix. Il s'agit d'extraits sonores du récit-fiction.",api,True,findable,0,0,0,0,0,2023-03-10T14:57:48.000Z,2023-03-10T14:57:48.000Z,inist.humanum,jbru,"mobilité spatiale,mobilité quotidienne,enfant,autonomie,récit personnel,amitié--chez l'enfant,sens et sensations,perception du risque,Villes -- Sons, environnement sonore,itinéraire,matériaux de terrain éditorialisés,récit-fiction,enregistrement sonore","[{'lang': 'fr', 'subject': 'mobilité spatiale'}, {'lang': 'fr', 'subject': 'mobilité quotidienne'}, {'lang': 'fr', 'subject': 'enfant'}, {'lang': 'fr', 'subject': 'autonomie'}, {'lang': 'fr', 'subject': 'récit personnel'}, {'lang': 'fr', 'subject': ""amitié--chez l'enfant""}, {'lang': 'fr', 'subject': 'sens et sensations'}, {'lang': 'fr', 'subject': 'perception du risque'}, {'lang': 'fr', 'subject': 'Villes -- Sons, environnement sonore'}, {'lang': 'fr', 'subject': 'itinéraire'}, {'lang': 'fr', 'subject': 'matériaux de terrain éditorialisés'}, {'lang': 'fr', 'subject': 'récit-fiction'}, {'lang': 'fr', 'subject': 'enregistrement sonore'}]",['17264818 Bytes'],['audio/mpeg']
+10.5281/zenodo.5554849,CSF18,Zenodo,2018,fr,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>CSF18 - Multimodal database of French Cued-speech (revised in 2022)</strong> Dataset used in ""Visual recognition of continuous Cued Speech using a tandem CNN-HMM approach"", by Liu, Hueber, Feng, Beautemps (submitted to Interspeech 2018) 476 sentences (i.e. 2 repetitions of 238 sentences) uttered by a professional French Cued-speech coder video/ PNG images, 576x720, 50fps (after deinterleave) audio/ WAV, 16kHz, 16bits prompt.txt: Text prompt of the recorded sentences corpus_mlf.txt: Phonetic transcription aligned on the audio signal (HTK format, Master Label File) obtained using the LiaPhon phonetizer and a forced-alignment HMM-based procedure (no manual check) corpus_mlf_updated_icassp2022.txt: Manually checked/cleaned version of corpus_mlf.txt (see Sankar et al., ICASSP 2022 paper) phonelist.txt: list of the 34 labels used to encode French phonemes at GIPSA-lab.",mds,True,findable,0,0,0,0,0,2022-05-13T14:50:52.000Z,2022-05-13T14:50:53.000Z,cern.zenodo,cern,"cued-speech, langue parlée complétée, LPC, recognition, multimodal, audiovisual, hand, sign language","[{'subject': 'cued-speech, langue parlée complétée, LPC, recognition, multimodal, audiovisual, hand, sign language'}]",,
+10.5281/zenodo.5999123,braidHymo: Morphometric indices for braided rivers.,Zenodo,2021,en,Software,Open Access,The package braidHymo allows to calculate two morphometrics indices that can be applied to braided rivers: the Bed Relief Index (BRI*) and the W* (normalised active channel width). Two datasets are included in the package to help and visualise the indices calculation. - - - Le package braidHymo permet de calculer deux indices morphométriques qui peuvent être appliqués aux rivières en tresses : le Bed Relief Index (Indice du relief du lit ou BRI*) et le W* (largeur de la bande active normalisé). Deux tableaux de données sont inclus dans le package pour aider et visualiser le calcul des indices.,mds,True,findable,0,0,0,0,0,2022-02-07T19:15:06.000Z,2022-02-07T19:15:07.000Z,cern.zenodo,cern,"Morphometric indices, braided rivers, BRI*, W*, R","[{'subject': 'Morphometric indices, braided rivers, BRI*, W*, R'}]",,
+10.5281/zenodo.7706208,cboschp/fsLaser_CMI: v1.0.1,Zenodo,2023,,Software,"MIT License,Open Access",Femtosecond laser preparation of resin embedded samples for correlative microscopy workflows in life sciences. Supporting data. --- Repo version at the time of paper publication.,mds,True,findable,0,0,0,1,0,2023-03-07T17:43:43.000Z,2023-03-07T17:43:44.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.jm58p,Data from: Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding,Dryad,2015,en,Dataset,Creative Commons Zero v1.0 Universal,"Global biodiversity in freshwater and the oceans is declining at high rates. Reliable tools for assessing and monitoring aquatic biodiversity, especially for rare and secretive species, are important for efficient and timely management. Recent advances in DNA sequencing have provided a new tool for species detection from DNA present into the environment. In this study, we tested if an environmental DNA (eDNA) metabarcoding approach, using water samples, can be used for addressing significant questions in ecology and conservation. Two key aquatic vertebrate groups were targeted: amphibians and bony fish. The reliability of this method was cautiously validated in silico, in vitro, and in situ. When compared with traditional surveys or historical data, eDNA metabarcoding showed a much better detection probability overall. For amphibians, the detection probability with eDNA metabarcoding was 0.97 (CI = 0.90-0.99) versus 0.58 (CI = 0.50-0.63) for traditional surveys. For fish, in 89% of the studied sites, the number of taxa detected using the eDNA metabarcoding approach was higher or identical to the number detected using traditional methods. We argue that the proposed DNA-based approach has the potential to become the next-generation tool for ecological studies and standardized biodiversity monitoring in a wide range of aquatic ecosystems.",mds,True,findable,821,168,1,1,0,2015-10-26T14:31:28.000Z,2015-10-26T14:31:29.000Z,dryad.dryad,dryad,"Batrachia,detection probability,wildlife management.,amphibian,Teleostei","[{'subject': 'Batrachia'}, {'subject': 'detection probability'}, {'subject': 'wildlife management.'}, {'subject': 'amphibian'}, {'subject': 'Teleostei'}]",['11226013657 bytes'],
+10.6084/m9.figshare.c.6712342,Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract High levels of arsenic in groundwater and drinking water are a major health problem. Although the processes controlling the release of As are still not well known, the reductive dissolution of As-rich Fe oxyhydroxides has so far been a favorite hypothesis. Decoupling between arsenic and iron redox transformations has been experimentally demonstrated, but not quantitatively interpreted. Here, we report on incubation batch experiments run with As(V) sorbed on, or co-precipitated with, 2-line ferrihydrite. The biotic and abiotic processes of As release were investigated by using wet chemistry, X-ray diffraction, X-ray absorption and genomic techniques. The incubation experiments were carried out with a phosphate-rich growth medium and a community of Fe(III)-reducing bacteria under strict anoxic conditions for two months. During the first month, the release of Fe(II) in the aqueous phase amounted to only 3% to 10% of the total initial solid Fe concentration, whilst the total aqueous As remained almost constant after an initial exchange with phosphate ions. During the second month, the aqueous Fe(II) concentration remained constant, or even decreased, whereas the total quantity of As released to the solution accounted for 14% to 45% of the total initial solid As concentration. At the end of the incubation, the aqueous-phase arsenic was present predominately as As(III) whilst X-ray absorption spectroscopy indicated that more than 70% of the solid-phase arsenic was present as As(V). X-ray diffraction revealed vivianite Fe(II)3(PO4)2.8H2O in some of the experiments. A biogeochemical model was then developed to simulate these aqueous- and solid-phase results. The two main conclusions drawn from the model are that (1) As(V) is not reduced during the first incubation month with high Eh values, but rather re-adsorbed onto the ferrihydrite surface, and this state remains until arsenic reduction is energetically more favorable than iron reduction, and (2) the release of As during the second month is due to its reduction to the more weakly adsorbed As(III) which cannot compete against carbonate ions for sorption onto ferrihydrite. The model was also successfully applied to recent experimental results on the release of arsenic from Bengal delta sediments.",mds,True,findable,0,0,0,0,0,2023-06-25T03:12:09.000Z,2023-06-25T03:12:10.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",,
+10.5281/zenodo.4776977,PACT-1D model version v1 for the CALNEX case study - output files,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","We provide model output files for the PACT-1D CalNex study discussed in Tuite et al., 2021 (DOI to follow). The PACT-1D source code used for this study are presented at: https://zenodo.org/record/4776419#.YKepky0Rpqs.",mds,True,findable,0,0,0,0,0,2021-05-21T00:47:18.000Z,2021-05-21T00:47:19.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3981252,Ultra-wideband SAR Tomography on asteroids : FDBP and Compressive Sensing datasets,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Our knowledge of the internal structure of asteroids is currently indirect and relies on inferences from remote sensing observations of surfaces. However, it is fundamental for understanding small bodies’ history and for planetary defense missions. Radar observation of asteroids is the most mature technique available to characterize their inner structure, and Synthetic Aperture Radar Tomography (TomoSAR) allows 3D imaging by extending the synthetic aperture principle in the elevation direction. However, as the geometry of observation of small asteroids is complex, and TomoSAR studies have always been performed in the Earth observation geometry, TomoSAR results in a small body geometry must be simulated to assess the methods’ performances. Different tomography algorithms can be adopted, depending on the characteristics of the problem. While the Frequency Domain Back Projection (FDBP) is based on the correction of the Fourier transform of the received signal by an <em>ad-hoc</em> function built from the geometry of study, it can only retrieve the true position of the scatterers when applied along with ray-tracing methods, which are unreliable in the case of rough asteroid surfaces. Meanwhile, the Compressive Sensing (CS) is based on the compressive sampling theory, which relies on the hypothesis that few scatterers lie in the same direction from the subsurface. The CS can be used to retrieve the position of the scatterers, but its application in the small body geometry is questioned. Thus, both performances of the FDBP and the CS in a small body geometry are demonstrated, and the quality of the reconstruction is analyzed.",mds,True,findable,0,0,0,0,0,2020-08-12T15:57:06.000Z,2020-08-12T15:57:07.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4916120,Quantum Information Scrambling in a Trapped-Ion Quantum Simulator with Tunable Range Interactions,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The data repository folder, "" OTOCPaperData.zip"" contains the data used in our manuscript <strong><em>Joshi et al., Phys. Rev. Lett. 124, 240505 (2020)</em></strong> and also available at arXiv:2001.02176. The folder contains further subfolders with self-explanatory names and description files to aid in reusing the data for any future purposes.",mds,True,findable,0,0,0,0,0,2021-06-09T14:58:59.000Z,2021-06-09T14:59:01.000Z,cern.zenodo,cern,,,,
+10.57726/nt1t-n566,Voyager dans les États autoritaires et totalitaires de l'Europe de l'entre-deux-guerres,Presses Universitaires Savoie Mont Blanc,2017,fr,Book,,,fabricaForm,True,findable,0,0,0,0,0,2022-03-14T09:55:00.000Z,2022-03-14T09:55:01.000Z,pusmb.prod,pusmb,FOS: Humanities,"[{'subject': 'FOS: Humanities', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['251 pages'],
+10.6084/m9.figshare.22735503,Additional file 1 of Healthcare students’ prevention training in a sanitary service: analysis of health education interventions in schools of the Grenoble academy,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Supplementary Material 1,mds,True,findable,0,0,0,0,0,2023-05-03T03:20:26.000Z,2023-05-03T03:20:27.000Z,figshare.ars,otjm,"Medicine,Biotechnology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}]",['19715 Bytes'],
+10.5281/zenodo.4067946,SGS scalar transport - homogeneous isotropic turbulence,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains filtered data (spectral cut) from three DNS simulations (train, tests, decay) of 3-dimensional homogeneous isotropic turbulence in a \(512^3\) periodic domain. More precisely, the following fields are available: Filtered velocities Filtered transported (passive) scalar Divergence of the SGS term from the transport equation obtained from DNS SGS fluxes (in the three directions) from the transport equation obtained from DNS The scalar is forced on the high spectral wavenumbers, such that filtered data is not impacted in train and tests, while the scalar forcing is removed in the decay simulation. Note that all three simulations are forced on the velocities with an Alvelius-type scheme. The dataset also provide with three different filter sizes: 8, 16 and 32 times from the initial DNS resolution, which give domain sizes of \(64^3, 32^3, 16^3\) respectively. This dataset has been used to train NN models available : https://github.com/hrkz/SubgridTransportNN.",mds,True,findable,0,0,0,0,0,2020-10-12T08:04:21.000Z,2020-10-12T08:04:22.000Z,cern.zenodo,cern,"turbulence,fluid dynamics,machine learning,subgrid-scale","[{'subject': 'turbulence'}, {'subject': 'fluid dynamics'}, {'subject': 'machine learning'}, {'subject': 'subgrid-scale'}]",,
+10.5281/zenodo.5243352,Russian DBnary archive in original Lemon format,Zenodo,2021,ru,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Russian language edition, ranging from 3rd March 2013 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br>",mds,True,findable,0,0,0,0,0,2021-08-24T11:44:17.000Z,2021-08-24T11:44:18.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.4679702,tomboulier/dcc-translation: First public release,Zenodo,2021,,Software,Open Access,"This is the source code as it was used for the publication, except minus details like some packages' features that have been deprecated (in <code>matplotib</code> and <code>rtk</code>). I also added a <code>requirements.txt</code> for the ease of installation.",mds,True,findable,0,0,0,0,0,2021-04-11T18:44:12.000Z,2021-04-11T18:44:14.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5723996,"XYZ files & Spin densities and Molecular Orbitals for ""Quantum mechanical simulations of the radical-radical chemistry on icy surfaces""",Zenodo,2021,,Other,"Creative Commons Attribution 4.0 International,Open Access","1. Structures of the optimized geometries obtained when investigating radical--radical reactions on the surfaces of amorphous water ices mimicking the chemical processes that take place in the interstellar medium. Structures in XYZ format, all together in a single PDF file. 2. Figures of the spin densities and molecular orbitals (the ones corresponding to the unpaired electrons) of each one of the stationary points on the PESs, the adsorbed geometries, and the isolated radicals for reference.",mds,True,findable,0,0,0,0,0,2021-12-08T14:45:30.000Z,2021-12-08T14:45:31.000Z,cern.zenodo,cern,"Interstellar molecules,Interstellar dust processes,Dense interstellar clouds,Surface ices","[{'subject': 'Interstellar molecules'}, {'subject': 'Interstellar dust processes'}, {'subject': 'Dense interstellar clouds'}, {'subject': 'Surface ices'}]",,
+10.5281/zenodo.4760497,"Fig. 16 in Contribution To The Knowledge Of The Moroccan High And Middle Atlas Stoneflies (Plecoptera, Insecta)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 16. High-Atlas, Middelt, Tattiouine spring where occurs Protonemura dakkii and P. talboti.",mds,True,findable,0,0,2,0,0,2021-05-14T05:27:29.000Z,2021-05-14T05:27:29.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.6084/m9.figshare.20235676.v1,Implementation of a biopsychosocial approach into physiotherapists’ practice: a review of systematic reviews to map barriers and facilitators and identify specific behavior change techniques,Taylor & Francis,2022,,Dataset,Creative Commons Attribution 4.0 International,"Our first objective was to map the barriers and facilitators to the implementation of a biopsychosocial approach into physiotherapists’ practice within the Theoretical Domains Framework (TDF). Our second objective was to identify the specific behavior change techniques (BCT) that could facilitate this implementation. We conducted a review of systematic reviews to identify barriers and facilitators to the use of a biopsychosocial approach by physiotherapists and we mapped them within the TDF domains. We then analyzed these domains using the Theory and Techniques tool (TaTT) to identify the most appropriate BCTs for the implementation of a biopsychosocial approach into physiotherapists’ practice. The barriers and facilitators to the use of a biopsychosocial approach by physiotherapists were mapped to 10 domains of the TDF (Knowledge; skills; professional role; beliefs about capabilities; beliefs about consequences; intentions; memory, attention and decision processes; environmental context; social influences; emotion). The inclusion of these domains within the TaTT resulted in the identification of 33 BCTs that could foster the use of this approach by physiotherapists. Investigating the implementation of a biopsychosocial approach into physiotherapists’ practice from a behavior change perspective provides new strategies that can contribute to successfully implement this approach.Implications for RehabilitationThe implementation of a biopsychosocial approach into physiotherapists’ practice is a complex process which involves behavior changes influenced by several barriers and facilitators.Barriers and facilitators reported by physiotherapists when implementing a biopsychosocial approach can be mapped within 10 domains of the Theoretical Domain Framework.Thirty-three behavior change techniques (e.g., verbal persuasion about capability, problem solving, restructuring the physical environment, etc.) were identified to foster the implementation of a biopsychosocial approach and specifically target barriers and facilitators.By using a behavior change perspective, this study highlights new strategies and avenues that can support current efforts to successfully implement the use of a biopsychosocial approach into physiotherapists’ practice. The implementation of a biopsychosocial approach into physiotherapists’ practice is a complex process which involves behavior changes influenced by several barriers and facilitators. Barriers and facilitators reported by physiotherapists when implementing a biopsychosocial approach can be mapped within 10 domains of the Theoretical Domain Framework. Thirty-three behavior change techniques (e.g., verbal persuasion about capability, problem solving, restructuring the physical environment, etc.) were identified to foster the implementation of a biopsychosocial approach and specifically target barriers and facilitators. By using a behavior change perspective, this study highlights new strategies and avenues that can support current efforts to successfully implement the use of a biopsychosocial approach into physiotherapists’ practice.",mds,True,findable,0,0,0,1,0,2022-07-06T02:40:05.000Z,2022-07-06T02:40:05.000Z,figshare.ars,otjm,"Space Science,Medicine,Genetics,FOS: Biological sciences,Neuroscience,Ecology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,19999 Mathematical Sciences not elsewhere classified,FOS: Mathematics,Cancer,Plant Biology","[{'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Neuroscience'}, {'subject': 'Ecology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '19999 Mathematical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Mathematics', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",['164588 Bytes'],
+10.5061/dryad.mw6m905tc,Examining the link between relaxed predation and bird colouration on islands,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Insular ecosystems share analogous ecological conditions, leading to patterns of convergent evolution that are collectively termed the “island syndromeâ€. In birds, part of this syndrome is a tendency for a duller plumage, possibly as a result of relaxed sexual selection and the reduced need for species recognition. Despite this global pattern, some insular species display a more colourful plumage than their mainland relatives, but why this occurs has remained unexplained. Here, we examine the hypothesis that these cases of increased plumage colouration on islands could arise through a relaxation of predation pressure. We used comparative analyses to investigate whether average insular richness of raptors of suitable mass influences the plumage colourfulness and brightness across 110 pairs of insular endemic species and their closest mainland relatives. As predicted, we find a likely negative relationship between insular colouration and insular predation whilst controlling for mainland predation and colouration, so that species were more likely to become more colourful as the number of insular predators decreased. In contrast, plumage brightness was not influenced by predation pressure. Relaxation from predation, together with drift, might thus be a key mechanism of species phenotypic responses to insularity.",mds,True,findable,267,35,0,0,0,2020-03-16T16:25:39.000Z,2020-03-16T16:25:40.000Z,dryad.dryad,dryad,"Insularity,colour volume,signal evolution","[{'subject': 'Insularity'}, {'subject': 'colour volume'}, {'subject': 'signal evolution'}]",['424675 bytes'],
+10.57745/nzfwp9,"Data supporting the article ""In-situ study of microstructures induced by the olivine to wadsleyite transformation at conditions of the 410 km depth discontinuity"" by Ledoux et al.",Recherche Data Gouv,2023,,Dataset,,"We provide here the data supporting our article entitled ""In-situ study of microstructures induced by the olivine to wadsleyite transformation at conditions of the 410 km depth discontinuity"". Raw diffraction images as well as files needed to process the data are given for the four datasets we present in the paper.",mds,True,findable,43,0,0,0,0,2023-01-23T17:42:35.000Z,2023-05-02T17:57:29.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.4761313,"Fig. 31 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 31. Dictyogenus muranyii sp. n., male, hindwing. Karstic spring of Bruyant, Isère dpt, France. Photo B. Launay.",mds,True,findable,0,0,4,0,0,2021-05-14T07:46:28.000Z,2021-05-14T07:46:29.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.34847/nkl.a5ae8y33,"En remontant la Romanche. Itinéraire de Mathieu Grenier, un agent du Symbhi, le 5 janvier 2021, Les Clavaux",NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Other,,"Itinéraire réalisé dans le cadre du projet de recherche-création Les Ondes de l’Eau : Mémoires des lieux et du travail dans la vallée de la Romanche. AAU-CRESSON (Laure Brayer, direction scientifique) - Regards des Lieux (Laure Nicoladzé, direction culturelle).
+
+Après plusieurs annulations suite aux confinements, le RDV est enfin fixé. En empruntant le chemin réalisé par le Syndicat Mixte des Bassins Hydrauliques de l’Isère, de la centrale des Clavaux jusqu’à la passerelle himalayenne, Mathieu Grenier nous présente les stratégies urbaines à l’origine du projet. Aux détours de la discussion, il évoque sa perception du territoire.",api,True,findable,0,0,0,0,0,2022-06-27T12:26:14.000Z,2022-06-27T12:26:14.000Z,inist.humanum,jbru,"Histoires de vie,paysage de l'eau,histoire orale,Marche,Sens et sensations,Mémoires des lieux,chemin,piéton,passerrelle,méthode des itinéraires,perception sensible,Romanche, Vallée de la (France),énergie hydraulique,aménagement du territoire,patrimoine industriel,tourisme,gestion du risque,Romanche, Vallée basse de la (France),matériaux de terrain éditorialisés,roman-photo,itinéraire","[{'lang': 'fr', 'subject': 'Histoires de vie'}, {'lang': 'fr', 'subject': ""paysage de l'eau""}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'Marche'}, {'lang': 'fr', 'subject': 'Sens et sensations'}, {'lang': 'fr', 'subject': 'Mémoires des lieux'}, {'lang': 'fr', 'subject': 'chemin'}, {'lang': 'fr', 'subject': 'piéton'}, {'lang': 'fr', 'subject': 'passerrelle'}, {'lang': 'fr', 'subject': 'méthode des itinéraires'}, {'lang': 'fr', 'subject': 'perception sensible'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'énergie hydraulique'}, {'lang': 'fr', 'subject': 'aménagement du territoire'}, {'lang': 'fr', 'subject': 'patrimoine industriel'}, {'lang': 'fr', 'subject': 'tourisme'}, {'lang': 'fr', 'subject': 'gestion du risque'}, {'lang': 'fr', 'subject': 'Romanche, Vallée basse de la (France)'}, {'lang': 'fr', 'subject': 'matériaux de terrain éditorialisés'}, {'lang': 'fr', 'subject': 'roman-photo'}, {'lang': 'fr', 'subject': 'itinéraire'}]","['32026948 Bytes', '1812592 Bytes', '118580 Bytes', '465262 Bytes', '1854736 Bytes', '2129438 Bytes', '2302607 Bytes', '2156906 Bytes', '1940530 Bytes', '1753696 Bytes', '1816563 Bytes', '1909197 Bytes', '1803205 Bytes', '1939709 Bytes', '1705826 Bytes', '2199505 Bytes', '1916736 Bytes', '1739695 Bytes', '2110370 Bytes', '1677783 Bytes', '2002296 Bytes', '1867477 Bytes', '1803582 Bytes', '1754599 Bytes', '2042487 Bytes', '1819595 Bytes', '955027 Bytes']","['application/pdf', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg']"
+10.5281/zenodo.5237269,Data Abstraction: A General Framework to Handle Program Verification of Data Structures,Zenodo,2021,,Other,"Creative Commons Attribution 4.0 International,Open Access","This archive represents the <em>artifact</em> submission for SAS 2021 research paper of the same title. It includes the compressed <em>docker image</em><strong> </strong>`data_abstraction_benchmarks.tar`. The README is reported below<br> # About<br> <br> This docker image contains benchmarks, installation tools and analysis tools for the verification of assertions in programs with arrays.<br> The paper *Data Abstraction: A General Framework to Handle Program Verification of Data Structures* accepted to SAS2021 uses this tool to generate its benchmark table.<br> <br> # Running the image<br> <br> - Load the image using `docker load -i data_abstraction_benchmarks.tar`<br> - Run the docker image interactively using : `docker run --name=""array-benchmarks"" -it jbraine/data_abstraction_benchmarks /bin/bash`<br> - Source .profile using within the container : `source .profile`<br> <br> Note : to retrieve files from within the docker container, you may use ` docker cp` from outside the docker image. An example is `docker cp array-benchmarks:Tools/array-benchmarks/README.md /tmp/README.md` . __This only works if you used ` --name=""array-benchmarks""` in the docker run command.__<br> <br> # Finding the tools<br> <br> Within the docker container, do :<br> `cd Tools`<br> <br> If you type `ls` here, you should get 4 folders:<br> - array-benchmarks<br> - DataAbstraction<br> - hornconverter<br> - CellMorphing<br> <br> hornconverter (respectively CellMorphing) is the converter (respectively abstraction tool) from SAS16 Gonnord and Monniaux paper. These are supplied as we use hornconverter as front-end and we compare ourselves with the CellMorphing abstraction. The DataAbstraction tool and the array-benchmarks are our contributions.<br> <br> ## The array-benchmarks<br> <br> The latest stable result build is available in the Latest folder. They currently correspond to the benchmarks used to generate the experiment table of the SAS2021 paper.<br> The README.md within the array-benchmarks folder contains the necessary information to understand the computed results, rebuild them and extend them.<br> <br> ## The DataAbstraction tool<br> <br> Our DataAbstraction tool is contained within the DataAbstraction folder and the current build implements Algorithm 7, page 16 of the SAS2021 paper.<br> The README.md within that folder contains the information on how the source code is build, ran, modified and constructed. It links the algorithms of the paper to specific functions of the source code.",mds,True,findable,0,0,0,0,0,2021-08-23T19:45:30.000Z,2021-08-23T19:45:31.000Z,cern.zenodo,cern,"static analysis,horn clauses,array benchmarks","[{'subject': 'static analysis'}, {'subject': 'horn clauses'}, {'subject': 'array benchmarks'}]",,
+10.5281/zenodo.3630439,Convergence in voice fundamental frequency in a joint speech production task - Dataset,Zenodo,2020,fr,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains fundamental frequency values for 30 pairs of participants performing an alternate reading task. Fundamental frequency in each speaker's speech was artificially modified in real-time during the task. We provide both the untransformed and transformed fundamental frequency values. Full description of the experimental setup is found in < insert paper DOI here > The data is organised as follows: data for each pair is stored in a separate folder with the pair ID as the folder name each folder contains two repetitions of the task, as produced in a zero-phase and pi-phase condition, respectively file names ending with '<strong>f0</strong>' contain fundamental frequency data, sampled every 10 ms file names ending with '<strong>turns</strong>' contain time onsets of speaking turns The format of '<strong>f0</strong>' files is as follows: '<strong>t</strong>': time in seconds '<strong>ch</strong>': channel of the recording, indicating the participant (<em>A</em> or <em>B</em>) '<strong>f0_unstransf</strong>': fundamental frequency values as produced by the participant (untransformed) in Hertz '<strong>f0_transf</strong>': fundamental frequency values as heard by the other participant (transformed) in Hertz The format of '<strong>turns</strong>' files is as follows: '<strong>ch</strong>': channel of the recording, indicating the participant (<em>A</em> or <em>B</em>), or both participants at once (<em>joint</em>) '<strong>turn</strong>': index of the reading turn '<strong>type</strong>': turn type. Either <em>speech</em> or <em>silence</em> for each participant, or <em>turn</em> for the joint description. '<strong>t</strong>': turn onset in seconds",mds,True,findable,1,0,0,0,0,2020-01-29T16:09:42.000Z,2020-01-29T16:09:43.000Z,cern.zenodo,cern,"Fundamental frequency,Voice transformation,Joint reading task,Phonetic convergence","[{'subject': 'Fundamental frequency'}, {'subject': 'Voice transformation'}, {'subject': 'Joint reading task'}, {'subject': 'Phonetic convergence'}]",,
+10.5281/zenodo.4655840,Eye-tracker data in information seeking tasks on texts (in French),Zenodo,2021,fr,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Description of eye-movement data from the reading task (so called “Paris experimentâ€)</strong> <em>File</em>: em-y35-fasttext.csv The experiment is described in Frey <em>et al.</em> (2013). To summarize the experiment: Twenty-one healthy adults participated in the experiment, all French native speakers. Data of six participants were discarded because they did not follow the rules of the experiment thoroughly or data was too noisy during the acquisition with the eye tracker. The whole experiment was reviewed and approved by the ethics committee of Grenoble CHU (“Centre Hospitalier Universitaireâ€) (RCB: n° 2011-A00845-36). 180 short texts were extracted from the French newspaper <em>Le Monde</em>, edition 1999. Texts were given a topic and were constructed around three types, those which were highly related (HR, f in French) to the topic, or moderately related (MR, m in French) to the topic, or unrelated (UR, a in French) to the topic. There were 60 texts of each type, hence 180 in total. The semantic relatedness of the text to the topic was controlled by Latent Semantic Analysis.<br> The goal of the experiment was to assess as soon as possible during reading whether the text was or not related to a given topic. First the topic was presented to participants and then they clicked to start the trial. Then a fixation cross was presented on the left of the first character at the first line, to stabilize the gaze location at the beginning of the text. When the text was displayed, participants read and had to mouse-click as fast as possible to stop reading and decide during another screen if the text was related or not to the topic. The trial was then repeated for the 180 texts with breaks in-between.<br> During trials, the eye tracker gave the position of each fixation on the screen, and the fixation duration. The minimum fixation duration threshold was set to be 80ms whereas the maximum duration was 600ms. All fixations outside these limits were removed for all analyses.<br> A posteriori it was necessary to know which word was being processed by the participant. First, the word identification span was defined as the necessary area from which a word can be identified. This span varies according to the direction of the reading, the alphabet, or the language, but can also be micro-context related. For simplicity, we used a fixed span that is considered for most of Latin languages (Rayner, 1998) : an asymmetrical window of 4 characters left and 8 characters right to the fixation. Moreover, a word may not entirely be located in the word identification span. We considered a word to be processed if at least 1/3 of its beginning or 2/3 of its end was inside the window. This result was obviously language sensitive, only valid in French. Finally, another hypothesis had to be made on the processed word within the window since several words might be captured. For this, we assumed that only one word could be processed during a given fixation and that this word was chosen as the closest to fixation centre, excluding stop words. Consequently, one word per fixation was selected. Thanks to this enhancement, features characterizing the reading strategy were defined.<br> Each fixation was associated to its outgoing saccade. Data associated at each fixation were the fixation duration, the fixed word, the saccade amplitude expressed in visual degree, the number of crossed words between two saccades and the saccade duration. The saccade was characterized by this number of crossed words, which would be negative for a backward progression, null for a refixation or positive for a forward progression. The texts are stored as .png files. The whole set of eye movements is stored in the .csv file. There is one line per fixation and the associated outgoing saccade (except for the last fixation). For each trial, a topic is proposed and then a text. Three possibilities arise: the text is closely related to the topic, from a semantic point of view (“f†category), the text is moderately related to the topic (“m†category), the text has nothing to do at all with the topic (“a†category). The subject had to decide as fast as possible the question “Is the text related to the topic?†For each topic, six texts were presented to him / her (2 “fâ€, 2 “mâ€, 2 “aâ€). The answer was positive with a very high frequency (> 95%) in the first case, it was negative in the third case, and positive / negative answers were equally likely in the intermediate case. In the .csv file, only the trials“xxx_f1†and “xxx-f2†with close semantic proximity to the topic are present. Not every fixation on the scanpath was considered: the first fixation is never considered, it has a particular status the last fixation is never considered, since the characteristics of the associated outgoing saccade are not defined, all fixations that are too short are not considered (duration less than 80ms: information is not recorded). The first column is the number of the fixation (starting from 0), the second column is the subject identifier, the third column is the text identifier (alphabetic ordering among the different texts), the fourth column is the text name. The other characteristics associated with each fixation are: ‘ANSWER’, ‘FIX_NUM’, number of the fixation within current scanpath, ‘FIX_LATENCY’, elapsed time since the beginning of recording in current scanpath, 'X', current x-axis coordinate of fixation (gaze) within text image, 'Y', current y-axis coordinate of fixation (gaze) within text image, ‘FDUR’, fixation duration in ms, ‘OFF_DUR’, 'SACAMP', outgoing saccade amplitude in pixels, 'SACOR', outgoing saccade amplitude in pixels, 'INEEG', 1 if some electro-encephalogram was recorded during the fixation, 0 otherwise, 'ISFIRST', indicates whether current fixation is the first within trial (Boolean), 'ISLAST' , indicates whether current fixation is the last within trial (Boolean), 'READMODE', reading mode categorized into 5 classes (see hereunder), 'WINC', increment in number of words required to reach next fixation from current fixation, 'CINC', increment in the number of characters required to reach next fixation from current fixation, 'FIXED_WORD', word in the text currently considered as being fixed, 'FIXED_WINDOW', set of words in the text currently being potentally fixed, 'WORD_FREQUENCY', frequency of current word being fixed with respect to a large corpus of French words, 'COSINST', measure of the LSA semantic similarity between the target topic and word currently being fixed. This is an instantaneous similarity for each fixated word. This comes from the computation of a cosine (between 0 and 1), 'COSCUM', measure of the LSA semantic similarity between the target topic and all the words read up to current fixation. This is a cumulative similarity, 'SACDIR', direction of outgoing saccade (forward, backward, upward, downward or last), 'NEW_READ_WORDS', number of words being read between two successive fixations, excluding words fixed during previous fixations, 'TEXT_TYPE', type of text among 'a', 'f', 'm', 'COS_INST_FASTTEXT_2016', same as COSINST but using FastText representation by Joulin <em>et al.</em> (2016) instead of LSA, 'COS_CUM_FASTTEXT_2016', same as COSCUM but using Fast Text representation by Joulin <em>et al.</em> (2016) instead of LSA, 'WFREQ_RANK_FASTTEXT_2016', rank of current word being fixed ordered by decreasing frequencies within training corpus in Joulin <em>et al.</em> (2016) 'COS_INST_FASTTEXT_2018', same as COSINST but using FastText representation by Mikolov <em>et al.</em> (2016) instead of LSA, 'COS_CUM_FASTTEXT_2018', same as COSCUM but using Fast Text representation by Mikolov <em>et al.</em> (2016) instead of LSA, 'WFREQ_RANK_FASTTEXT_2018', rank of current word being fixed ordered by decreasing frequencies within training corpus in Mikolov <em>et al.</em> (2016) 'WFREQ_RANK_FASTTEXT_1618', mean of 'WFREQ_RANK_FASTTEXT_2016' and 'WFREQ_RANK_FASTTEXT_2018' 'COS_INST_FASTTEXT_1618', mean of 'COS_INST_FASTTEXT_2016' and 'COS_INST_FASTTEXT_2018' 'COS_CUM_FASTTEXT_1618', mean of 'COS_CUM_FASTTEXT_2016' and 'COS_CUM_FASTTEXT_2018' 'TEXT_TYPE_2', refinement of text_type where 'f' texts are distinguished between 'f+' (at least one word of the target topic appears in the text) or 'f' (other 'TEXT_TYPE'-'f' texts) ReadMode is defined as 0 if WINC >=2 1 if WINC = 1 2 if WINC = 0 3 if WINC = -1 4 if WINC <=-2 <strong>References:</strong> Joulin, A., Grave, E., Bojanowski, P., and Mikolov, T. (2016b). Bag of tricks for efficient text classification. <em>arXiv preprint</em> arXiv:1607.01759. Mikolov, T., Grave, E., Bojanowski, P., Puhrsch, C., and Joulin, A. (2018). Advances in pre-training distributed word representations. In <em>Proceedings of the International Conference on Language Resources and Evaluation (LREC 2018)</em>.<br> <br>",mds,True,findable,0,0,0,0,0,2021-04-13T09:58:42.000Z,2021-04-13T09:58:43.000Z,cern.zenodo,cern,"eye movements,eye tracker,reading task","[{'subject': 'eye movements'}, {'subject': 'eye tracker'}, {'subject': 'reading task'}]",,
+10.5281/zenodo.7418361,Southwest Greenland Ice Sheet Yearly Ice Velocities dataset from 1984 to 2020,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The present dataset is published after the work of Paul Halas, Jérémie Mouginot, Basile de Fleurian and Petra Langebroek on the Southwest of the Greenland Ice Sheet. It provides ice velocity products derived using the processing chain developped by Jérémie Mouginot and collaborators, following the steps described in Romain Millan’s paper â€Mapping Surface Flow Velocity of Glaciers at Regional Scale Using a Multiple Sensors Approach†(https://doi.org/10.3390/rs11212498). In order to derive the velocity fields, we used all available imagery from Landsat 5, Landsat 7 and Landsat 8, from 1984 up to 2021, with less than 40% cloud coverage. Unfortunately, no data was collected for 1984, 1993, 1996, 1997 and 1998. Please also note that the spatial coverage is really limited before 1999. From 2016, satellite imagery from Sentinel-2 is also used, improving the spatial coverage of our velocity maps.<br> In this archive, we provide:<br> • Complete dataset of all velocity fields derived from every image pair;<br> • Yearly median results run through all data for every single pixel;<br> • Yearly GeoTIFF spatial aggregate of all previously computed medians;<br> • The shapefile â€cube grid.shp†describing the grid used for our area. For any question, please contact Paul Halas (paul.halas@uib.no).",mds,True,findable,0,0,0,0,0,2022-12-09T18:46:51.000Z,2022-12-09T18:46:52.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7516852,Serbian Translation of Researcher Mental Health and Well-being Manifesto - МанифеÑÑ‚ о менталном здрављу и добробити иÑтраживача - Manifest o mentalnom zdravlju i dobrobiti istraživaÄa,Zenodo,2023,sr,Other,"Creative Commons Attribution 4.0 International,Open Access","ReMO COST Action je mreža zainteresovanih strana na svim nivoima istraživaÄke zajednice koja je izradila Manifest o mentalnom zdravlju i dobrobiti istraživaÄa kojim poziva na procenu kako je najbolje negovati i održavati mentalno zdravlje i dobrobit istraživaÄa uz pomoć akcija i inicijativa na nivou politika, institucija, zajednice i pojedinaca. Ovaj manifest poziva sve zainteresovane strane u ekosistemu istraživanja da se angažuju u razvoju politika koje prate, poboljÅ¡avaju i održavaju dobrobit i mentalno zdravlje u oblasti istraživanja, odreÄ‘ujući obuhvatnije mere uspeha i kvaliteta, podržavajući ravnotežu izmeÄ‘u poslovnog i privatnog života, inkluzivnost i održive karijere istraživaÄa koje podržavaju porodiÄni život. РеМО ЦОСТ Ðцтион је мрежа заинтереÑованих Ñтрана на Ñвим нивоима иÑтраживачке заједнице која је развила МанифеÑÑ‚ о менталном здрављу и добробити иÑтраживача, који позива на процену како најбоље неговати и одржавати ментално здравље и добробит иÑтраживача уз помоћ акција и иницијатива на нивоу политика, инÑтитуција, заједница и појединаца. Овај манифеÑÑ‚ позива Ñве заинтереÑоване Ñтране у иÑтраживачком екоÑиÑтему да Ñе ангажују у развоју политика које прате, побољшавају и одржавају благоÑтање и ментално здравље у иÑтраживању, тако што ће дефиниÑати Ñвеобухватније мере уÑпеха и квалитета, подржавајући равнотежу између поÑловног и приватног живота, инклузивноÑти и одрживе каријере за иÑтраживаче који подржавају породични живот. The English Language Version of the Manifesto can be found at: https://doi.org/10.5281/zenodo.5559805",mds,True,findable,0,0,0,0,0,2023-01-09T19:22:23.000Z,2023-01-09T19:22:24.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3817443,"Search Queries for ""Mapping Research Output to the Sustainable Development Goals (SDGs)"" v4.0",Zenodo,2019,,Software,"Creative Commons Attribution 4.0 International,Open Access","<strong>This package contains machine readable (xml) search queries, for the Scopus publication database, to find domain specific research output that are related to the 17 Sustainable Development Goals (SDGs).</strong> Sustainable Development Goals are the 17 global challenges set by the United Nations. Within each of the goals specific targets and indicators are mentioned to monitor the progress of reaching those goals by 2030. In an effort to capture how research is contributing to move the needle on those challenges, we earlier have made an initial classification model than enables to quickly identify what research output is related to what SDG. (This Aurora SDG dashboard is the initial outcome as <em>proof of practice</em>.) The initiative started from the Aurora Universities Network in 2017, in the working group ""Societal Impact and Relevance of Research"", to investigate and to make visible 1. what research is done that are relevant to topics or challenges that live in society (for the proof of practice this has been scoped down to the SDGs), and 2. what the effect or impact is of implementing those research outcomes to those societal challenges (this also have been scoped down to research output being cited in policy documents from national and local governments an NGO's). The classification model we have used are 17 different search queries on the Scopus database. The search queries are elegant constructions with keyword combinations and boolean operators, in the syntax specific to the Scopus Query Language. We have used Scopus because it covers more research area's that are relevant to the SDG's, and we could filter much easier the Aurora Institutions. <strong>Versions</strong> Different versions of the search queries have been made over the past years to improve the precision (soundness) and recall (completeness) of the results. The queries have been made in a team effort by several bibliometric experts from the Aurora Universities. Each one did two or 3 SDG's, and than reviewed each other's work. v1.0 January 2018<em> Initial 'strict' version.</em> In this version only the terms were used that appear in the SDG policy text of the targets and indicators defined by the UN. At this point we have been aware of the SDSN Compiled list of keywords, and used them as inspiration. Rule of thumb was to use <em>keyword-combination searches</em> as much as possible rather than <em>single-keyword searches</em>, to be more precise rather than to yield large amounts of false positive papers. Also we did not use the inverse or 'NOT' operator, to prevent removing true positives from the result set. This version has not been reviewed by peers. Download from: GitHub / Zenodo v2.0 March 2018<em> Reviewed 'strict' version.</em> Same as version 1, but now reviewed by peers. Download from: GitHub / Zenodo v3.0 May 2019 <em>'echo chamber' version.</em> We noticed that using strictly the terms that policy makers of the UN use in the targets and indicators, that much of the research that did not use that specific terms was left out in the result set. (eg. ""mortality"" vs ""deaths"") To increase the recall, without reducing precision of the papers in the results, we added keywords that were obvious synonyms and antonyms to the existing 'strict' keywords. This was done based on the keywords that appeared in papers in the result set of version 2. This creates an 'echo chamber', that results in more of the same papers. Download from: GitHub / Zenodo v4.0 August 2019<em> uniform 'split' version.</em> Over the course of the years, the UN changed and added Targets and indicators. In order to keep track of if we missed a target, we have split the queries to match the targets within the goals. This gives much more control in maintenance of the queries. Also in this version the use of brackets, quotation marks, etc. has been made uniform, so it also works with API's, and not only with GUI's. His version has been used to evaluate using a survey, to get baseline measurements for the precision and recall. Published here: Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. Download from: GitHub / Zenodo v5.0 June 2020 <em>'improved' version.</em> In order to better reflect academic representation of research output that relate to the SDG's, we have added more keyword combinations to the queries to increase the recall, to yield more research papers related to the SDG's, using academic terminology. We mainly used the input from the Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. We ran several text analyses: Frequent term combination in title and abstracts from Suggested papers, and in selected (accepted) papers, suggested journals, etc. Secondly we got inspiration out of the Elsevier SDG queries Jayabalasingham, Bamini; Boverhof, Roy; Agnew, Kevin; Klein, Lisette (2019), “Identifying research supporting the United Nations Sustainable Development Goalsâ€, Mendeley Data, v1 https://dx.doi.org/10.17632/87txkw7khs.1. Download from: GitHub / Zenodo <strong>Contribute and improve the SDG Search Queries</strong> We welcome you to join the Github community and to fork, improve and make a pull request to add your improvements to the new version of the SDG queries. <strong>https://github.com/Aurora-Network-Global/sdg-queries</strong>",mds,True,findable,15,0,3,2,0,2020-05-14T15:27:11.000Z,2020-05-14T15:27:12.000Z,cern.zenodo,cern,"Sustainable Development Goals,SDG,Classification model,Search Queries,SCOPUS,Text indexing,Controlled vocabulary","[{'subject': 'Sustainable Development Goals'}, {'subject': 'SDG'}, {'subject': 'Classification model'}, {'subject': 'Search Queries'}, {'subject': 'SCOPUS'}, {'subject': 'Text indexing'}, {'subject': 'Controlled vocabulary'}]",,
+10.5281/zenodo.8388930,Sneaked references: Cooked reference metadata inflate citation counts,Zenodo,2023,en,Software,"Creative Commons Attribution 4.0 International,Open Access","Supplementary materials of the manuscript titled “Sneaked references: Cooked reference metadata inflate citation counts.""",mds,True,findable,0,0,0,0,0,2023-10-03T13:38:45.000Z,2023-10-03T13:38:46.000Z,cern.zenodo,cern,"sneaked references,undue citations,citation manipulation,metadata registration,bibliometrics,research evaluation","[{'subject': 'sneaked references'}, {'subject': 'undue citations'}, {'subject': 'citation manipulation'}, {'subject': 'metadata registration'}, {'subject': 'bibliometrics'}, {'subject': 'research evaluation'}]",,
+10.5281/zenodo.4761091,"Figs. 2a-c. L in A New Stonefly From Lebanon, Leuctra Cedrus Sp. N. (Plecoptera: Leuctridae)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 2a-c. L. cedrus sp. n.: male abdomen in dorsal view (a), lateral view (b), paraprocts in ventral view (c).",mds,True,findable,0,0,2,0,0,2021-05-14T07:14:18.000Z,2021-05-14T07:14:18.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.57745/joz1na,Long term monitoring of near surface soil temperature in the french Alps,Recherche Data Gouv,2023,,Dataset,,"Monitoring of near-surface soil temperature in seasonaly snow-covered, mountain ecosystems located in the French Alps. Data are part of several research projects and monitoring programs examining the impact of climate change on snow cover dynamics, microclimate, species distribution and ecosystem functioning. Data include a GPS position, a date and time in UTC and a near-surface soil temperature (in °C) measured at 5 cm belowground using stand-alone temperature data logger.",mds,True,findable,107,20,0,0,0,2023-03-15T11:45:22.000Z,2023-03-15T12:04:59.000Z,rdg.prod,rdg,,,,
+10.6084/m9.figshare.24447574,Additional file 1 of Bacterial survival in radiopharmaceutical solutions: a critical impact on current practices,figshare,2023,,Dataset,Creative Commons Attribution 4.0 International,"Additional file 1. Raw data of Pseudomonas aeruginosa (ATCC: 27853), Staphylococcus aureus (ATCC: 25923) and Staphylococcus epidermidis (ATCC: 1228) survival rate in technetium-99m radioactive solutions at 1.85 to 11.1 GBq and non-radioactive technetium-99 solutions were reported.",mds,True,findable,0,0,0,0,0,2023-10-27T03:41:27.000Z,2023-10-27T03:41:27.000Z,figshare.ars,otjm,"Biophysics,Microbiology,FOS: Biological sciences,Environmental Sciences not elsewhere classified,Science Policy,Infectious Diseases,FOS: Health sciences","[{'subject': 'Biophysics'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Environmental Sciences not elsewhere classified'}, {'subject': 'Science Policy'}, {'subject': 'Infectious Diseases'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['353871 Bytes'],
+10.5281/zenodo.8324811,"Data for ""False trends in Landsat-based vegetation greenness due to increased image availability over time""",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Raster data used in this following paper : ""False trends in Landsat-based vegetation greenness due to increased image availability over time"". The dataset includes observed greening trends for the European Alps, and sum of observations in the european alps and the arctic.",mds,True,findable,0,0,0,0,0,2023-09-07T08:19:10.000Z,2023-09-07T08:19:11.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4757638,"Figs. 5–8. Leuctra bidula, male. Segments IX and X in Morphology And Systematic Position Of Two Leuctra Species (Plecoptera: Leuctridae) Believed To Have No Specilla",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 5–8. Leuctra bidula, male. Segments IX and X, shown as transparent: 5, Lateral. 6, Oblique caudal view; open arrow in Fig. 5 indicates direction of view. 7, Dorsal. 8, Ventral. All to the same scale, semidiagrammatic: a, articulation; ab, attachment bulb; c, cercus and cercus attachment site, respectively; e, epiproct; ip, invaginated ventral portion of paraproct; lp1, lp2, lateral processes 1 and 2, respectively; os, open space; SIX, TIX,TX, sternites and tergites IX and X, respectively; sp, specilla with sperm ducts.",mds,True,findable,0,0,4,0,0,2021-05-13T16:06:42.000Z,2021-05-13T16:06:43.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.4765408,"Figs. 14, 15. Leuctra ketamensis, male. 14 in Morphology And Systematic Position Of Two Leuctra Species (Plecoptera: Leuctridae) Believed To Have No Specilla",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 14, 15. Leuctra ketamensis, male. 14, Terminal section of segment X and paraprocts in lateral view. 15, dorsal view of part of TIX and TX. Both to same scale, abbreviations as in Figs. 5–8, plus: bc, basal cone; dp1, dp2, dorsal paraproct processes 1 and 2; ic, insertion of cercus.",mds,True,findable,0,0,2,0,0,2021-05-16T03:24:47.000Z,2021-05-16T03:24:48.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.10201545,"Dataset for the paper ""Largest aftershock nucleation driven by afterslip during the 2014 Iquique sequence""",Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Dataset for the following paperÂ
+Yuji Itoh, Anne Socquet, and Mathilde Radiguet, Largest aftershock nucleation driven by afterslip during the 2014 Iquique sequence, Geophysical Research Letters, 2023GL104852
+See readme.txt files for details about the files and the contact informaton. Uncompressing produces files with ~ 500 MB in total.",api,True,findable,0,0,0,0,0,2023-12-05T12:30:45.000Z,2023-12-05T12:30:45.000Z,cern.zenodo,cern,"Afterslip,GPS,High-rate GPS,Iquique,Chile,Earthquake,subduction zone","[{'subject': 'Afterslip'}, {'subject': 'GPS'}, {'subject': 'High-rate GPS'}, {'subject': 'Iquique'}, {'subject': 'Chile'}, {'subject': 'Earthquake'}, {'subject': 'subduction zone'}]",,
+10.60662/7nek-jq08,"Favoriser l’innovation par le lean product development : le comportement humain, un indicateur pertinent ?",CIGI QUALITA MOSIM 2023,2023,,ConferencePaper,,,fabricaForm,True,findable,0,0,0,0,0,2023-09-12T15:19:12.000Z,2023-09-12T15:19:13.000Z,uqtr.mesxqq,uqtr,,,,
+10.5281/zenodo.7137482,Regional-Modeling-LATMOS-IGE/WRF-Chem-Polar: WRF-Chem 4.3.3 including mercury chemistry,Zenodo,2022,,Software,Open Access,"This is a development of the WRF-Chem 4.3.3 model which includes mercury gas-phase and heterogeneous chemistry, as well as mercury re-emission from snow and sea ice. This version was extended from the previously developed WRF-Chem version (published in Marelle et al., JAMES, 2021) which included halogen chemistry and bromine surface snow and blowing snow emissions. NOTE: This is an experimental version of the release and may not be compatible with particular model options.",mds,True,findable,0,0,0,1,0,2022-10-03T08:12:37.000Z,2022-10-03T08:12:37.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6498344,Dataset for 'Unveiling the charge distribution of a GaAs-based nanoelectronic device',Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","*********************************************************<br> This repository contains the raw experimental data associated with the manuscript<br> ""Unveiling the charge distribution of a GaAs-based nanoelectronic device: A large experimental data-set approach""<br> by Eleni Chatzikyriakou, Junliang Wang et al.<br> See Arxiv:2205.00846 for more details. <br> ********************************************************* ***************************************<br> Content of the different data files<br> *************************************** The data are stored in 5 different files in the csv format. * data_1D_4K.csv: current versus gate voltage data for all the samples at 4K. <br> The same gate voltage is applied on the Top and bottom gates. For sample X1Y3, X2Y3, X5Y3 and X6Y3 some additional measurements have been realised : * data_1D_mk.csv : top and bottom gates of each QPC have been swept at the same time at 50 mK temperature. * data_2D_4K_TB.csv : top gate has been swept for different values of the bottom gate at 4K.<br> * data_2D_mK_TB.csv : top gate has been swept for different values of the bottom gate at 50 mK temperature.<br> * data_2D_mK_BT.csv : bottom gate has been swept for different values of the top gate at 50 mK temperature. ***********************************<br> Format of the csv files<br> *********************************** --- All the data files are in the following format. * A given curve ""current versus gate voltage"" is stored in two consecutive raws. The first one contains the value of the measured current, the second one contains the values of the applied<br> gate voltages. * A 2D measurement ""current versus top gate and bottom gate"" is stored in three consecutive raws. The first one contains the value of the measured current, the second one contains the list of values of voltage applied on one of the gate. The third third raw contains the list of values of voltage applied on the other gate. --- Each row of a csv file has the following format: * The first column identifies the quantum point contact and the quantity. The format is Xx_Yy_QpcNb_Meas.<br> - Xx is the column on the chip (from X1 to X6).<br> - Yy is the row on the chip (Y1, Y2 or Y3).<br> - QpcNb is the number of the qpc (from 1 to 8 or from 9 to 16).<br> - Meas is the reported quantity, either the (measured) ""current"" or the (applied) ""voltage""<br> or the ""TopVoltage"" or ""BotVoltage"" for 2D scans. * The second column is the unit (A or V). * The third column is the number of sweeps (1, 2 or 3) performed. <br> For some measurements, the same sweep has been done multiple times. * The fourth column is the design of the quantum point contact (A, B, C, D or E). * All the following columns contain the measured value. For 2D scans the different values of the gate corresponding to the third raw are placed one after the other. *******************************<br> Python scripts for data analysis<br> ******************************* For convenience, we provide an example python scripts that can be used to load the data and plot them. extract.py : Extracts the data into a dictionary and plots the I-V characteristics<br> extract.ipynb : jupyter notebook using the different functions of extract.py type -h for help",mds,True,findable,0,0,0,2,0,2022-05-03T17:46:12.000Z,2022-05-03T17:46:14.000Z,cern.zenodo,cern,"quantum point contacts,measurements,semiconducting quantum technologies,GaAs,nanoelectronics","[{'subject': 'quantum point contacts'}, {'subject': 'measurements'}, {'subject': 'semiconducting quantum technologies'}, {'subject': 'GaAs'}, {'subject': 'nanoelectronics'}]",,
+10.5281/zenodo.7941512,cicwi/PyCorrectedEmissionCT: Release version 0.8.1,Zenodo,2023,,Software,Open Access,Hotfix release adding the following features and fixing the following bugs: Added Power spectrum calculation function. ### Fixed Pypi package creation.,mds,True,findable,0,0,0,0,0,2023-05-16T14:26:31.000Z,2023-05-16T14:26:31.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3902757,Data for: Fractional antiferromagnetic skyrmion lattice induced by anisotropic couplings,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Data for: Fractional antiferromagnetic skyrmion lattice induced by anisotropic couplings,mds,True,findable,0,0,0,0,0,2020-06-21T19:01:59.000Z,2020-06-21T19:02:00.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5724117,"Data supplement for ""Topological magnon band structure of emergent Landau levels in a skyrmion lattice""",Zenodo,2021,,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","Collection of the data sets for our paper, <em>Topological magnon band structure of emergent Landau levels in a skyrmion lattice</em>. (The source code supplement can be found here.) <strong>Contents</strong> Data files used for the paper's figures. Scan Figure File(s) (i) 2 ill_thales/exp_4-01-1621/rawdata/025280<br> ill_thales/exp_4-01-1621/rawdata/025281 (ii) S17 ill_thales/exp_INTER-436/rawdata/022169 (iii) 2 ill_thales/exp_4-01-1597/rawdata/023454 (iv) 3 mlz_reseda/* (v) 4 ill_thales/exp_INTER-413/rawdata/020778<br> ill_thales/exp_INTER-413/rawdata/020779 (vi) 4 ill_thales/exp_INTER-413/rawdata/020777 (vii) S16 ill_thales/exp_INTER-436/rawdata/022168 (viii) S16 ill_thales/exp_INTER-413/rawdata/020793 S10 ill_thales/exp_4-01-1597/rawdata/023488 S10 ill_thales/exp_4-01-1597/rawdata/023489 S11 ill_thales/exp_4-01-1597/rawdata/023453 S11 ill_thales/exp_4-01-1597/rawdata/023553<br> ill_thales/exp_4-01-1597/rawdata/023559 S12 ill_thales/exp_INTER-436/rawdata/022213<br> ill_thales/exp_INTER-436/rawdata/022216<br> ill_thales/exp_INTER-436/rawdata/022217 Overview of experimental data sets. Instrument Proposal Directory THALES (ILL) INTER-413 ill_thales/exp_INTER-413/ INTER-436 ill_thales/exp_INTER-436/ 4-01-1597 ill_thales/exp_4-01-1597/ INTER-477 ill_thales/exp_INTER-477/ 4-01-1621 ill_thales/exp_4-01-1621/ LET (RAL) RB1620412 <em>Impossible to include in archive due to size.</em> RB1720033 <em>Impossible to include in archive due to size.</em> TASP (PSI) 20181324 (part 1) psi_tasp/exp_20181324_1/ 20181324 (part 2) psi_tasp/exp_20181324_2/ 20151888 psi_tasp/exp_20151888/ MIRA (MLZ) 13511 mlz_mira/exp_13511 15633 mlz_mira/exp_15633 RESEDA (MLZ) P00745-01 mlz_reseda/ <strong>Acknowledgements</strong> We thank E. Villard and P. Chevalier for technical support and J. Locatelli for IT support during the <em>THALES</em> experiments; and J. Frank for technical support during the <em>MIRA</em> experiments. We thank J. K. Jochum for support with the <em>RESEDA</em> experiment. We thank M. Kugler for his early experiments on skyrmion dynamics in MnSi. â–º Please see the <strong>readme.txt</strong> file in the archive for details.",mds,True,findable,0,0,4,0,0,2021-11-24T13:02:28.000Z,2021-11-24T13:02:29.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3826146,A glimpse into rapid closed-system freezing processes in remoulded clay: dataset,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This is the data set,mds,True,findable,0,0,0,0,0,2020-09-21T12:52:55.000Z,2020-09-21T12:52:56.000Z,cern.zenodo,cern,tomography,[{'subject': 'tomography'}],,
+10.25384/sage.c.6567921.v1,Impact of a telerehabilitation programme combined with continuous positive airway pressure on symptoms and cardiometabolic risk factors in obstructive sleep apnea patients,SAGE Journals,2023,,Collection,Creative Commons Attribution 4.0 International,"BackgroundObstructive sleep apnea syndrome is a common sleep-breathing disorder associated with adverse health outcomes including excessive daytime sleepiness, impaired quality of life and is well-established as a cardiovascular risk factor. Continuous positive airway pressure is the reference treatment, but its cardiovascular and metabolic benefits are still debated. Combined interventions aiming at improving patient's lifestyle behaviours are recommended in guidelines management of obstructive sleep apnea syndrome but adherence decreases over time and access to rehabilitation programmes is limited. Telerehabilitation is a promising approach to address these issues, but data are scarce on obstructive sleep apnea syndrome.MethodsThe aim of this study is to assess the potential benefits of a telerehabilitation programme implemented at continuous positive airway pressure initiation, compared to continuous positive airway pressure alone and usual care, on symptoms and cardiometabolic risk factors of obstructive sleep apnea syndrome. This study is a 6-months multicentre randomized, parallel controlled trial during which 180 obese patients with severe obstructive sleep apnea syndrome will be included. We will use a sequential hierarchical criterion for major endpoints including sleepiness, quality of life, nocturnal systolic blood pressure and inflammation biological parameters.Discussionm-Rehab obstructive sleep apnea syndrome is the first multicentre randomized controlled trial to examine the effectiveness of a telerehabilitation lifestyle programme in obstructive sleep apnea syndrome. We hypothesize that a telerehabilitation lifestyle intervention associated with continuous positive airway pressure for 6 months will be more efficient than continuous positive airway pressure alone on symptoms, quality of life and cardiometabolic risk profile. Main secondary outcomes include continuous positive airway pressure adherence, usability and satisfaction with the telerehabilitation platform and medico-economic evaluation.Trial registrationClinicaltrials.gov Identifier: NCT05049928. Registration data: 20 September 2021",mds,True,findable,0,0,0,0,0,2023-04-07T00:07:22.000Z,2023-04-07T00:07:23.000Z,figshare.sage,sage,"111708 Health and Community Services,FOS: Health sciences,Cardiology,110306 Endocrinology,FOS: Clinical medicine,110308 Geriatrics and Gerontology,111099 Nursing not elsewhere classified,111299 Oncology and Carcinogenesis not elsewhere classified,111702 Aged Health Care,111799 Public Health and Health Services not elsewhere classified,99999 Engineering not elsewhere classified,FOS: Other engineering and technologies,Anthropology,FOS: Sociology,200299 Cultural Studies not elsewhere classified,FOS: Other humanities,89999 Information and Computing Sciences not elsewhere classified,FOS: Computer and information sciences,150310 Organisation and Management Theory,FOS: Economics and business,Science Policy,160512 Social Policy,FOS: Political science,Sociology","[{'subject': '111708 Health and Community Services', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cardiology'}, {'subject': '110306 Endocrinology', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '110308 Geriatrics and Gerontology', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111099 Nursing not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111299 Oncology and Carcinogenesis not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111702 Aged Health Care', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111799 Public Health and Health Services not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '99999 Engineering not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Other engineering and technologies', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Anthropology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '200299 Cultural Studies not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Other humanities', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '89999 Information and Computing Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Computer and information sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '150310 Organisation and Management Theory', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Economics and business', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '160512 Social Policy', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Political science', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Sociology'}]",,
+10.5281/zenodo.7030984,Local structure and density of liquid Fe-C-S alloys at Moon's core conditions,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This file includes the raw CAESAR and absorption data measured in each P-T condition and the Python codes for diffraction and absorption data analysis. Matlab codes for P-T calibration are also enclosed.,mds,True,findable,0,0,0,1,0,2022-08-30T14:33:46.000Z,2022-08-30T14:33:47.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4759491,"Figs. 7-15 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 7-15. Epiprocts of the North African species of the Protonemura talboti subgroup. 7-8: Protonemura dakkii sp. n.; 9-10: P. talboti (Nav{s, 1929); 11-12: P. berberica Vinçon & S{nchez-Ortega, 1999; 13-14: P. algirica algirica Aubert, 1956; 15: P. algirica bejaiana ssp. n. (7, 9, 11, 13: lateral view; 8, 10, 12, 14-15: dorsal view; scale 0.5 mm).",mds,True,findable,0,0,10,0,0,2021-05-14T02:23:41.000Z,2021-05-14T02:23:42.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.48390/0005-gz84,Les circuits courts distants approvisionnant Paris,"UMR CNRS 6266 IDEES, Université de Rouen Normandie",2021,fr,BookChapter,Creative Commons Attribution 4.0 International,,fabricaForm,True,findable,0,0,0,0,0,2021-09-20T12:59:19.000Z,2021-09-20T12:59:19.000Z,jbru.idees,jbru,,,,"['PDF', 'HTML']"
+10.5281/zenodo.5373490,"FIG. 3 in Le gisement paléontologique villafranchien terminal de Peyrolles (Issoire, Puy-de-Dôme, France): résultats de nouvelles prospections",Zenodo,2006,,Image,"Creative Commons Zero v1.0 Universal,Open Access","FIG. 3. — Position et représentation schématique des fossiles collectés durant les sondages de 1996 sur le site de Peyrolles près d'Issoire (Puy-de-Dôme, France).",mds,True,findable,0,0,0,0,0,2021-09-02T04:40:31.000Z,2021-09-02T04:40:32.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.5769631,Magnetic resonance imaging of the octopus nervous system,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Anatomical magnetic-resonance imaging of an octopus vulgaris with 0.5mm slice thickness and 0.25 by 0.25 mm in-plane resolution. The companion data paper details the acquisition procedure.,mds,True,findable,0,0,0,0,0,2021-12-17T17:15:46.000Z,2021-12-17T17:15:47.000Z,cern.zenodo,cern,"octopus vulgaris,MRI,cephalopod,https://species.wikimedia.org/wiki/Octopus_vulgaris","[{'subject': 'octopus vulgaris'}, {'subject': 'MRI'}, {'subject': 'cephalopod'}, {'subject': 'https://species.wikimedia.org/wiki/Octopus_vulgaris', 'subjectScheme': 'url'}]",,
+10.5281/zenodo.854619,Daily Gridded Datasets Of Snow Depth And Snow Water Equivalent For The Iberian Peninsula From 1980 To 2014,Zenodo,2017,,Dataset,"Creative Commons Attribution 4.0,Open Access","We present snow observations and a validated daily gridded snowpack dataset that was simulated from downscaled reanalysis of data for the Iberian Peninsula. The Iberian Peninsula has long-lasting seasonal snowpacks in its different mountain ranges, and winter snowfalls occur in most of its area. However, there are only limited direct observations of snow depth (SD) and snow water equivalent (SWE), making it difficult to analyze snow dynamics and the spatiotemporal patterns of snowfall. We used meteorological data from downscaled reanalyses as input of a physically based snow energy balance model to simulate SWE and SD over the Iberian Peninsula from 1980 to 2014. More specifically, the ERA-Interim reanalysis was downscaled to 10 ×10 km resolution using the Weather Research and Forecasting (WRF) model. The WRF outputs were used directly, or as input to other submodels, to obtain data needed to drive the Factorial Snow Model (FSM). We used lapse-rate coefficients and hygrobarometric adjustments to simulate snow series at 100 m elevations bands for each 10 × 10 km grid cell in the Iberian Peninsula. The snow series were validated using data from MODIS satellite sensor and ground observations. The overall simulated snow series accurately reproduced the interannual variability of snowpack and the spatial variability of snow accumulation and melting, even in very complex topographic terrains. Thus, the presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism and risk management .",,True,findable,0,0,0,0,0,2017-09-11T09:01:12.000Z,2017-09-11T09:01:13.000Z,cern.zenodo,cern,"SWE,Snow depth,WRF,FSM,Iberian Peninsula","[{'subject': 'SWE'}, {'subject': 'Snow depth'}, {'subject': 'WRF'}, {'subject': 'FSM'}, {'subject': 'Iberian Peninsula'}]",,
+10.5281/zenodo.4759493,"Figs. 16-21 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 16-21. Terminalias of the imago of Protonemura talboti (Nav{s, 1929). 16: male terminalia, dorsal view; 17: male terminalia, ventral view; 18: male terminalia, lateral view; 19: male paraproct, ventrolateral view; 20: female pregenital and subgenital plates, and vaginal lobes, ventral view; 21: female pregenital and subgenital plates, and vaginal lobes, lateral view (scales 0.5 mm; scale 1: Fig. 19, scale 2: Figs. 16-18, 20-21).",mds,True,findable,0,0,4,0,0,2021-05-14T02:24:03.000Z,2021-05-14T02:24:04.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.7148513,Co-seismic slip of the 18 April 2021 Mw 5.9 Genaveh earthquake in the South Dezful Embayment of Zagros (Iran) and its aftershock sequence,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This public repository contains INSAR and other processed data for the manuscript : ""Co-seismic slip of the 18 April 2021 Mw 5.9 Genaveh earthquake in the South Dezful Embayment of Zagros (Iran) and its aftershock sequence"" InSAR unwrapped and geocoded files, for the ascending track A101 and the descending track D35: GDM_Asc101_InU_geo_20210414_20210426_sd_4rlks.tiff GDM_Desc35_InU_geo_20210410_20210422_sd_4rlks.tiff Sampled quadtree data for the ascending and descending data with LOS vector: a101_okinv_input d35_okinv_input Slip distribution model for the fault dipping N and the fault dipping S: SDM_dipN_oksar.dat SDM_dipS_oksar.dat",mds,True,findable,0,0,0,0,0,2023-05-08T16:38:28.000Z,2023-05-08T16:38:28.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3903874,"Data for the article ""Long-distance spin-transport across the Morin phase transition up to room temperature in the ultra-low damping alpha-Fe2O3 antiferromagnet""",Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data for experimental magneto-transport and resonance measurements for the article "" Long-distance spin-transport across the Morin phase transition up to room temperature in the ultra-low damping α-Fe2O3 antiferromagnet "" (https://arxiv.org/abs/2005.14414)",mds,True,findable,0,0,0,0,0,2020-12-23T18:02:24.000Z,2020-12-23T18:02:24.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.000000046,Narwhals react to ship noise and airgun pulses embedded in background noise,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Anthropogenic activities are increasing in the Arctic posing a threat to species with high seasonal site-fidelity, such as the narwhal Monodon monoceros. In this controlled sound exposure study, six narwhals were live-captured and instrumented with animal-borne tags providing movement and behavioural data, and exposed to concurrent ship noise and airgun pulses. All narwhals reacted to sound exposure by reduced buzzing rates, where the response was dependent on the magnitude of exposure defined as 1/distance to ship. Halving of buzzing rate, compared with undisturbed behaviour, and cessation of foraging occurred at 12 and ~7-8 km from the ship, respectively. The effect of exposure could be detected > 40 km from the ship. At distances > 5 km, the received high-frequency cetacean weighted sound exposure levels were below background noise indicating sensitivity of narwhals towards sound disturbance and demonstrating their ability to detect signals embedded in noise. Further studies are needed to evaluate the energetic costs of disrupted foraging due to sustained disturbance but the observed sensitivity should be considered in the management of anthropogenic activities in the Arctic. The results of this study emphasize the importance of controlled sound exposure studies in the wild to explore the auditory capabilities of odontocetes.",mds,True,findable,210,15,0,0,0,2021-08-11T15:45:56.000Z,2021-08-11T15:45:57.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences,airgun,Foraging","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'airgun'}, {'subject': 'Foraging', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['50920791 bytes'],
+10.5281/zenodo.4761323,"Figs. 38-45 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 38-45. Dictyogenus muranyii sp. n., larva. 38. Head, pronotum and mesonotum, dorsal view. Karstic spring of Brudour, Drôme dpt, France. Photo B. Launay. 39. Head, pronotum, dorsal view. Karstic spring of Brudour, Drôme dpt, France. Photo A. Ruffoni. 40. Head, pronotum, mesonotum and metanotum, lateral view. Karstic spring of Bruyant, Isère dpt, France. Photo A. Ruffoni. 41. Pronotum, lateral view. Karstic spring of Bruyant, Isère dpt, France. Photo J.-P.G. Reding. 42. Abdominal segments, lateral view. Karstic",mds,True,findable,0,0,6,0,0,2021-05-14T07:47:49.000Z,2021-05-14T07:47:49.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.4964215,"FIGURES 29–32 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 29–32. Protonemura pennina sp. n., 29. female, ventral view. 30. female, lateral view. 31. female, ventral view. 32. female, cervical gills",mds,True,findable,0,0,5,0,0,2021-06-16T08:25:35.000Z,2021-06-16T08:25:36.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5061/dryad.c670tq2,Data from: On-demand sildenafil as a treatment for Raynaud phenomenon: a series of n-of-1 trials,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"Background: Treatment of Raynaud phenomenon (RP) with phosphodiesterase-5 inhibitors has shown moderate efficacy. Adverse effects decrease the risk–benefit profile of these drugs, and patients may not be willing to receive long-term treatment. On-demand single doses before or during exposure to cold may be a good alternative. Objective: To assess the efficacy and safety of on-demand sildenafil in RP. Design: Series of randomized, double-blind, n-of-1 trials. (ClinicalTrials.gov: NCT02050360). Setting: Outpatients at a French university hospital. Participants: Patients with primary or secondary RP. Intervention: Each trial consisted of a multiple crossover study in a single patient. Repeat blocks of 3 periods of on-demand treatment were evaluated: 1 week of placebo, 1 week of sildenafil at 40 mg per dose, and 1 week of sildenafil at 80 mg per dose, with a maximum of 2 doses daily. Measurements: Raynaud Condition Score (RCS) and frequency and daily duration of attacks. Skin blood flow in response to cooling also was assessed with laser speckle contrast imaging. Mixed-effects models were used and parameters were estimated in a Bayesian framework to determine individual and aggregated efficacy. Results: 38 patients completed 2 to 5 treatment blocks. On the basis of aggregated data, the probability that sildenafil at 40 mg or 80 mg was more effective than placebo was greater than 90% for all outcomes (except for RCS with sildenafil, 80 mg). However, the aggregated effect size was not clinically relevant. Yet, substantial heterogeneity in sildenafil's efficacy was observed among participants, with clinically relevant efficacy in some patients. Limitation: The response to sildenafil was substantially heterogeneous among patients. Conclusion: Despite a high probability that sildenafil is superior to placebo, substantial heterogeneity was observed in patient response and aggregated results did not show that on-demand sildenafil has clinically relevant efficacy. In this context, the use of n-of-1 trials may be an original and relevant approach in RP.",mds,True,findable,392,37,1,2,0,2019-01-25T15:09:07.000Z,2019-01-25T15:09:08.000Z,dryad.dryad,dryad,"Raynaud,sildenafil,n-of-1 trial","[{'subject': 'Raynaud'}, {'subject': 'sildenafil'}, {'subject': 'n-of-1 trial'}]",['498012 bytes'],
+10.5061/dryad.m905qftwt,Environmental and biotic drivers of soil microbial βâ€diversity across spatial and phylogenetic scales,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"Soil microbial communities play a key role in ecosystem functioning but still little is known about the processes that determine their turnover (β-diversity) along ecological gradients. Here, we characterize soil microbial β-diversity at two spatial scales and at multiple phylogenetic grains to ask how archaeal, bacterial and fungal communities are shaped by abiotic processes and biotic interactions with plants. We characterized microbial and plant communities using DNA metabarcoding of soil samples distributed across and within eighteen plots along an elevation gradient in the French Alps. The recovered taxa were placed onto phylogenies to estimate microbial and plant β-diversity at different phylogenetic grains (i.e. resolution). We then modeled microbial β-diversities with respect to plant β-diversities and environmental dissimilarities across plots (landscape scale) and with respect to plant β-diversities and spatial distances within plots (plot scale). At the landscape scale, fungal and archaeal β-diversities were mostly related to plant β-diversity, while bacterial β-diversities were mostly related to environmental dissimilarities. At the plot scale, we detected a modest covariation of bacterial and fungal β-diversities with plant β-diversity; as well as a distance–decay relationship that suggested the influence of ecological drift on microbial communities. In addition, the covariation between fungal and plant β-diversity at the plot scale was highest at fine or intermediate phylogenetic grains hinting that biotic interactions between those clades depends on early-evolved traits. Altogether, we show how multiple ecological processes determine soil microbial community assembly at different spatial scales and how the strength of these processes change among microbial clades. In addition, we emphasized the imprint of microbial and plant evolutionary history on today’s microbial community structure.",mds,True,findable,189,28,0,1,0,2019-10-17T18:55:29.000Z,2019-10-17T18:55:30.000Z,dryad.dryad,dryad,"bioclimate variables,Fungi phylogeny,plant phylogeny,phylogenetic scale,Archaea,Tracheophyta (vascular plants),phylogenetic beta-diversity","[{'subject': 'bioclimate variables'}, {'subject': 'Fungi phylogeny'}, {'subject': 'plant phylogeny'}, {'subject': 'phylogenetic scale'}, {'subject': 'Archaea', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Tracheophyta (vascular plants)'}, {'subject': 'phylogenetic beta-diversity'}]",['955128521 bytes'],
+10.5281/zenodo.10133203,"Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages",Zenodo,2023,en,Dataset,Creative Commons Attribution Non Commercial 2.0 Generic,"Introduction:
+On the 10th of July 2023, at 16:40, an eruption started in the Reykjanes Peninsula, Iceland, next to the mountain ""Litla-Hrútur"". As part of the response, the CIEST2 french initiative was activated (Gouhier et al., 2022). Once activated, Pléiades stereoimages were tasked and scheduled for fast delivery within the area of Interest. On the 20th of August 2023 an additional stereopair of images from Pléiades was acquired and processed after the eruption had stopped.
+Once acquired and delivered, the Pléiades images were processed following the methods described in the section below. This repository contains the near-real time results of DEMs, difference maps compared to a pre-eruption DEM, and lava outlines digitized from the difference map and the orthoimage.
+Â
+Methods:
+The Pléiades stereoimages were processed using the Ames StereoPipeline (ASP, Shean et al., 2016, see ASP branch in repository), yielding a DEM in 2x2m GSD and an orthoimage in 0.5x0.5m GSD. The processing was done using as only input the stereoimages and their orientation information, as Rational Polynomial Coefficients (RPCs). The parallel_stereo routine performs all the steps needed in the correlation of the stereoimages, yielding a pointcloud which is then interpolated using the routine point2dem. Besides default parameters, the parallel_stereo parameters used for creation of the DEMs were the standard parameters, plus the following ones:Â
+--stereo-algorithm asp_mgm --corr-tile-size 300 --corr-timeout 900 --cost-mode 3 --subpixel-mode 9 --corr-kernel 7 7 --subpixel-kernel 15 15
+Once the DEM was created, DEM co-registration was applying in order to align and minimize positional biases between the pre-eruption DEM and the Pléiades DEMs. We followed the co-registration method of Nuth & Kääb (2011), implemented by David Shean's co-registration routines (https://github.com/dshean/demcoreg, Shean et al., 2016). The co-registration involved a horizontal and vertical shift of the Pléiades DEMs, as well as a planar tilt correction. The horizontal offset obtained from the DEM co-registration was also applied to the Pléiades orthoimages.
+The pre-eruption DEM used for this study is a survey done on the 27th of September 2022, data collected Birgir Óskarsson and Robert A. Askew (Icelandic Institute of Natural History) and processed by Sydney R. Gunnarsson and JoaquÃn M.C. Belart (National Land Survey of Iceland). Metadata of this dataset is available here: https://gatt.lmi.is/geonetwork/srv/eng/catalog.search#/metadata/c59da6cf-18ee-44af-a085-afbad0de029a
+Lava outlines were manually digitized from the co-registered Pléiades orthoimages, The lava outlines are available as GeoPackages in the ""GPKG"" branch of the repository.
+At the moment, the results from Pléiades are used by the Institute of Earth Sciences of the Univesity of Iceland (Jarðvisindustofnun Háskoli Ãslands) to estimate lava volumes and effusion rate, following the methods described in Pedersen et al. (2022). Please contact the authors if these data are intended to be used for a similar purpose, in order to avoid conflict of interests or duplicate work. We encourage collaboration and data sharing for the purpose of the monitoring of the eruption and for research applications.
+Data naming convention:
+faf_YYYYMMDD_hhmmss_hhmmss_*align.tif: DEM obtained from the processing, co-registered to the reference pre-eruption DEM.
+faf_YYYYMMDD_hhmmss_hhmmss_*align_diff.tif: Difference of elevation between the Pléiades DEM and the pre-eruption DEM.
+faf_YYYYMMDD_hhmm.gpkg: Polygon containing the lava outlines, extracted from the Pléiades orthoimage and the map of elevation difference.
+0_faf_YYYYMMDD_hhmmss_hhmmss_*fig.png: A figure showing the latest map of elevation difference, overlaid with a hillshade of the latest Pléiades DEM and the latest lava outlines, result of the processing of the Pléiades stereoimages. The figure was created using the tool imviewer.py from the GitHub repository https://github.com/dshean/imview (Shean et al., 2016).
+Data Specifications:
+
+Cartographic projection: ISN93 / Lambert 1993 (EPSG:3057, https://epsg.io/3057)
+Origin of Elevation: meters above GRS80 ellipsoid (WGS84)
+Raster data format: GeoTIFF
+Raster compression system: LZW
+Vector data format: GeoPackage (https://www.geopackage.org/)
+Pléiades dataset includes only DEMs because the Pléiades ortho imagery is for licensed use only. Please contact the authors for further information on this.
+Acknowledgements:Â
+Pléiades images from July 2023 were provided under the CIEST² initiative (CIEST2 is part of ForM@Ter (https://en.poleterresolide.fr/). Pléiades images from August 2023 were provided under the CEOS Volcano Supersite (https://ceos.org/ourwork/workinggroups/disasters/gsnl/). Image Pléiades©CNES2023, distribution AIRBUS DS.
+Dataset Attribution:
+This dataset is licensed under a Creative Commons CC BY-NC 4.0 International License (Attribution-NonCommercial).
+Citation:
+Please cite this repository as described below:
+Joaquin M.C. Belart, Virginie Pinel, Hannah. I. Reynolds, Etienne Berthier, & Sydney R. Gunnarson. (2023). Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages (1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10133203",api,True,findable,0,0,0,0,0,2023-11-15T09:44:08.000Z,2023-11-15T09:44:08.000Z,cern.zenodo,cern,"DEM,Volcano,Emergency tasking,Pléiades","[{'subject': 'DEM'}, {'subject': 'Volcano'}, {'subject': 'Emergency tasking'}, {'subject': 'Pléiades'}]",,
+10.5281/zenodo.154083,By2014 Articulatory-Acoustic Dataset,Zenodo,2016,,Dataset,"Creative Commons Attribution Share-Alike 4.0,Open Access","This dataset contains synchronous articulatory and acoustic data, recorded in one male French subject.",,True,findable,1,0,0,0,0,2016-09-27T10:03:57.000Z,2016-09-27T10:03:58.000Z,cern.zenodo,cern,"speech production, speech synthesis, electromagnetic articulography, EMA, articulatory data, acoustic data","[{'subject': 'speech production, speech synthesis, electromagnetic articulography, EMA, articulatory data, acoustic data'}]",,
+10.5281/zenodo.6535396,Elmer/Ice repository for 3D Greenland Ice-Sheet initial states,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","initial states of the Greenland Ice-Sheet produced with the Elmer/Ice model. This initial states are obtained using a control inverse method that optimise the basal friction field to minimise the mismatch between model and observed velocities. Results used in N. Maier, F. Gimbert and F. Gillet-Chaulet, Threshold response to surface melt drives large-scale bed weakening in Greenland, submitted to Nature",mds,True,findable,0,0,0,0,0,2022-05-10T12:26:19.000Z,2022-05-10T12:26:20.000Z,cern.zenodo,cern,"Elmer/Ice ice flow model,Greenland ice-sheet,Basal condition","[{'subject': 'Elmer/Ice ice flow model'}, {'subject': 'Greenland ice-sheet'}, {'subject': 'Basal condition'}]",,
+10.5281/zenodo.5576201,PARASO source code (no COSMO),Zenodo,2021,,Software,"Creative Commons Attribution 4.0 International,Open Access","Source code for the PARASO Antarctic configuration, <strong>except the COSMO model </strong>(atmosphere), which is only accessible to CLM-Community members (not to be mistaken with the CLM model included in PARASO). A full version of these sources, including the COSMO part, has been uploaded to the CLM-Community RedC. Hence, these sources are provided for the sake of transparency, not for running the full model (which requires COSMO). <strong>Model description</strong>: Pelletier, C., Fichefet, T., Goosse, H., Haubner, K., Helsen, S., Huot, P.-V., Kittel, C., Klein, F., Le clec'h, S., van Lipzig, N. P. M., Marchi, S., Massonnet, F., Mathiot, P., Moravveji, E., Moreno-Chamarro, E., Ortega, P., Pattyn, F., Souverijns, N., Van Achter, G., Vanden Broucke, S., Vanhulle, A., Verfaillie, D., and Zipf, L.: PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5, Geosci. Model Dev., 15, 553–594, 10.5194/gmd-15-553-2022, 2022. <strong>Input data</strong>: Pelletier, Charles, Klein, François, Zipf, Lars, Vanden Broucke, Sam, Haubner, Konstanze, & Helsen, Samuel. (2021). Input data for PARASO, a circum-Antarctic fully-coupled 5-component model (v1.4.3) [Data set]. Zenodo. 10.5281/zenodo.5588468 <strong>Forcings</strong>: Pelletier, Charles, & Helsen, Samuel. (2021). PARASO ERA5 forcings (1.4.3) [Data set]. Zenodo. 10.5281/zenodo.5590053 <strong>References</strong> <strong>f.ETISh</strong> (ice sheet): Pattyn, F.: Sea-level response to melting of Antarctic ice shelves on multi-centennial timescales with the fast Elementary Thermomechanical Ice Sheet model (f.ETISh v1.0), The Cryosphere, 11, 1851–1878, 10.5194/tc-11-1851-2017, 2017. <strong>NEMO </strong>(ocean): Madec Gurvan, Romain Bourdallé-Badie, Pierre-Antoine Bouttier, Clément Bricaud, Diego Bruciaferri, Daley Calvert, Jérôme Chanut, Emanuela Clementi, Andrew Coward, Damiano Delrosso, Christian Ethé, Simona Flavoni, Tim Graham, James Harle, Doroteaciro Iovino, Dan Lea, Claire Lévy, Tomas Lovato, Nicolas Martin, … Martin Vancoppenolle. (2017). NEMO ocean engine. In Notes du Pôle de modélisation de l'Institut Pierre-Simon Laplace (IPSL) (v3.6-patch, Number 27). Zenodo. 10.5281/zenodo.3248739 <strong>LIM</strong> (sea ice): Rousset, C., Vancoppenolle, M., Madec, G., Fichefet, T., Flavoni, S., Barthélemy, A., Benshila, R., Chanut, J., Levy, C., Masson, S., and Vivier, F.: The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities, Geosci. Model Dev., 8, 2991–3005, 10.5194/gmd-8-2991-2015, 2015. <strong>COSMO </strong>(atmosphere): Doms, G., Förstner, J., Heise, E., Herzog, H. J., Mironov, D., Raschendorfer, M., ... & Vogel, G. (2011). A description of the nonhydrostatic regional COSMO model, Part II: Physical Parameterization. Deutscher Wetterdienst, Offenbach, Germany. 10.5676/dwd_pub/nwv/cosmo-doc_5.00_II <strong>CLM </strong>(land): Oleson, K.W., D.M. Lawrence, G.B. Bonan, B. Drewniak, M. Huang, C.D. Koven, S. Levis, F. Li, W.J. Riley, Z.M. Subin, S.C. Swenson, P.E. Thornton, A. Bozbiyik, R. Fisher, E. Kluzek, J.-F. Lamarque, P.J. Lawrence, L.R. Leung, W. Lipscomb, S. Muszala, D.M. Ricciuto, W. Sacks, Y. Sun, J. Tang, Z.-L. Yang, 2013: Technical Description of version 4.5 of the Community Land Model (CLM). Ncar Technical Note NCAR/TN-503+STR, National Center for Atmospheric Research, Boulder, CO, 422 pp, 10.5065/D6RR1W7M.",mds,True,findable,0,0,10,6,0,2021-10-27T10:12:34.000Z,2021-10-27T10:12:35.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.c.6584765,Efficacy and auditory biomarker analysis of fronto-temporal transcranial direct current stimulation (tDCS) in targeting cognitive impairment associated with recent-onset schizophrenia: study protocol for a multicenter randomized double-blind sham-controlled trial,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background In parallel to the traditional symptomatology, deficits in cognition (memory, attention, reasoning, social functioning) contribute significantly to disability and suffering in individuals with schizophrenia. Cognitive deficits have been closely linked to alterations in early auditory processes (EAP) that occur in auditory cortical areas. Preliminary evidence indicates that cognitive deficits in schizophrenia can be improved with a reliable and safe non-invasive brain stimulation technique called tDCS (transcranial direct current stimulation). However, a significant proportion of patients derive no cognitive benefits after tDCS treatment. Furthermore, the neurobiological mechanisms of cognitive changes after tDCS have been poorly explored in trials and are thus still unclear. Method The study is designed as a randomized, double-blind, 2-arm parallel-group, sham-controlled, multicenter trial. Sixty participants with recent-onset schizophrenia and cognitive impairment will be randomly allocated to receive either active (n=30) or sham (n=30) tDCS (20-min, 2-mA, 10 sessions during 5 consecutive weekdays). The anode will be placed over the left dorsolateral prefrontal cortex and the cathode over the left auditory cortex. Cognition, tolerance, symptoms, general outcome and EAP (measured with EEG and multimodal MRI) will be assessed prior to tDCS (baseline), after the 10 sessions, and at 1- and 3-month follow-up. The primary outcome will be the number of responders, defined as participants demonstrating a cognitive improvement ≥Z=0.5 from baseline on the MATRICS Consensus Cognitive Battery total score at 1-month follow-up. Additionally, we will measure how differences in EAP modulate individual cognitive benefits from active tDCS and whether there are changes in EAP measures in responders after active tDCS. Discussion Besides proposing a new fronto-temporal tDCS protocol by targeting the auditory cortical areas, we aim to conduct a randomized controlled trial (RCT) with follow-up assessments up to 3 months. In addition, this study will allow identifying and assessing the value of a wide range of neurobiological EAP measures for predicting and explaining cognitive deficit improvement after tDCS. The results of this trial will constitute a step toward the use of tDCS as a therapeutic tool for the treatment of cognitive impairment in recent-onset schizophrenia. Trial registration ClinicalTrials.gov NCT05440955. Prospectively registered on July 1st, 2022.",mds,True,findable,0,0,0,0,0,2023-04-13T12:04:23.000Z,2023-04-13T12:04:24.000Z,figshare.ars,otjm,"Medicine,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,69999 Biological Sciences not elsewhere classified,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.4603786,Atomic coordinates of the structures of iCOMs adsorbed at the surface of an amorphous ice model,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the atomic coordinates in the MOLDRAW format (.mol files) of the HF-3c optimized structures of iCOMs adsorbed at the surface of a periodic model of an amorphous water icy grain using the CRYSTAL17 computer code. Each file can be easily converted in input for the variety of quantum mechanical programs, like VASP, QE, etc.",mds,True,findable,0,0,0,0,0,2021-03-14T18:22:02.000Z,2021-03-14T18:22:03.000Z,cern.zenodo,cern,"Amorphous ice,HF-3c,Adsorption,iCOMs","[{'subject': 'Amorphous ice'}, {'subject': 'HF-3c'}, {'subject': 'Adsorption'}, {'subject': 'iCOMs'}]",,
+10.5281/zenodo.4764629,"Figs. 58-61 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 58-61. Dictyogenus alpinum, male and female adults. 58. Adult male, epiproct, dorso-caudal view. Nant Bénin River, Savoie dpt, France. Photo B. Launay. 59. Adult male, posterior margin of sternite 7 with ventral vesicle, ventral view. Nant Bénin River, Savoie dpt, France. Photo B. Launay. 60. Female, subgenital plate, ventral view. Ristolas – Mount Viso, Queyras, Hautes-Alpes dpt, France. Photo J.-P. G. Reding. 61. Adult female, subgenital plate, ventral view. Guiers vif, Chartreuse, Savoie dpt, France. Photo A. Ruffoni. pointing almost horizontally toward each other (Figs. 29, 32). Hemitergal lobes more",mds,True,findable,0,0,6,0,0,2021-05-15T14:18:13.000Z,2021-05-15T14:18:14.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.7280/d1wt11,Glacier catchments/basins for the Greenland Ice Sheet,Dryad,2019,en,Dataset,Creative Commons Attribution 4.0 International,"We divide Greenland, including its peripheral glaciers and ice caps, into 260 basins grouped in seven regions: southwest (SW), central west (CW), (iii) northwest (NW), north (NO), northeast (NE), central east (CE), and southeast (SE). These regions are selected based on ice flow regimes, climate, and the need to partition the ice sheet into zones comparable in size (200,000 km2 to 400,000 km2) and ice production (50 Gt/y to 100 Gt/y, or billion tons per year). Out of the 260 surveyed glaciers, 217 are marine-terminating, i.e., calving into icebergs and melting in contact with ocean waters, and 43 are land-terminating.The actual number of land-terminating glaciers is far larger than 43, but we lump them into larger units for simplification. Each glacier catchment is defined using a combination of ice flow direction and surface slope. In areas of fast flow (> 100 m), we use a composite velocity mosaic (Mouginot et al. 2017). In slowmoving areas, we use surface slope using the GIMP DEM (https://nsidc.org/data/nsidc- 0715/versions/1) (Howat et al. 2014) smoothed over 10 ice thicknesses to remove shortwavelength undulations. References: Mouginot J, Rignot E, Scheuchl B, Millan R (2017) Comprehensive annual ice sheet velocity mapping using landsat-8, sentinel-1, and radarsat-2 data. Remote Sensing 9(4). Howat IM, Negrete A, Smith BE (2014) The greenland ice mapping project (gimp) land classification and surface elevation data sets. The Cryosphere 8(4):1509–1518.",mds,True,findable,2250,296,0,11,0,2019-03-29T12:53:11.000Z,2019-03-29T12:53:12.000Z,dryad.dryad,dryad,,,['4137543 bytes'],
+10.5281/zenodo.4972594,"DeepOrchidSeries: A Sentinel-2 Dataset to inform convolutional SDMs with twelve-month Sentinel-2 image time-series, Orchid family",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Deep Species Distribution Modelling from Sentinel-2 Image Time-series: a Global Scale Analysis on the Orchid Family</strong> <strong><em>DeepOrchidSeries</em></strong> dataset gathers Sentinel-2 image time-series around geolocated orchid occurrences. Seasonal evolutions of the habitats are captured in the twelve-month RGB/IR time-series with 640x640m spatial resolution. It allows novel Species Distribution Models (SDMs) coupled with convolutional networks to take advantage of both spatial and temporal information. Our <strong>associated article</strong> is describing the modeling choices made to shape this ambitious dataset. It is submitted to https://www.frontiersin.org/research-topics/18336/plant-biodiversity-science-in-the-era-of-artificial-intelligence. We believe such global data, methods and scripts are valuable to the conservation ecology community and especially deep-SDMs users. To our knowledge, no similar ready-to-use dataset is available. In the article, the dataset's temporal dimension is proven to significantly improve SDMs performances. <strong><em>sen2patch</em></strong> is the gitlab project gathering the code to create such dataset. It is available at https://gitlab.inria.fr/jestopin/sen2patch. <strong><em>DeepOrchidSeries.csv</em></strong> contains all occurrences-level information. We advice to load it with: <pre><code class=""language-python"">import pandas as pd df = pd.read_csv(""path/to/DeepOrchidSeries.csv"", sep=';') df.columns ['gbifid', 'canonical_name', 'decimallatitude', 'decimallongitude', 'speciesKey', 'cell_index', 'bot_country', 'bot_code', 'lvl2_code', 'continent_code']</code></pre> 'gbifid' is the occurrences GBIF ID 'canonical_name', is the species canonical name 'decimallatitude', 'decimallongitude' are the species coordinates in decimal degrees 'speciesKey' is the species GBIF unique identifier 'cell_index' is a unique cell ID in a 0.0025° lon/lat grid partitioning the Earth (used to stratify train/val/test set by geographic blocks) 'bot_country', 'bot_code', 'lvl2_code', 'continent_code' are geographic subdivisions defined in https://github.com/tdwg/wgsrpd (code and string for WGSRPD level 1, the botanical countries) Initial GBIF query DOI is https://doi.org/10.15468/dl.4bijtu (26 August 2019). <strong><em>DeepOrchidSeries.tar</em></strong> file contains the satellite image time-series and is available at https://lab.plantnet.org/deeporchidseries/ <em>.tar</em> archive measure 286 GB and extends to 432 GB once decompressed. Image time-series relative tree paths are constructed from the occurrences unique GBIF IDs. For a given occurence <em>gbifid</em>, matching patches are located in: <em>final_dataset_by_gbifid/gbifid[-2:]/gbifid[-4:-2]</em>, <em>i.e.</em> in a first folder named with the <em>gbifid</em> last two numbers and a subfolder with the previous two ones. Example: the time-series files matching occurrence 2236837714 are located at <em>final_dataset_by_gbifid/14/77/</em>. Image time-series are composed of twelve 16 bits RGB <em>.png</em> and twelve 16 bits IR <em>.png</em> files containing data identical to the original L1C products, no lossy compression was made. There are one RGB and one IR .png file per month. Patches from month MM/YYYY of occurrence <em>gbifid</em> are named<em> </em><em>RGB_YYYY_MM_gbifid_.png</em> and <em>IR0_YYYY_MM_gbifid_.png</em>. <em><strong>models.zip</strong></em> is the archive containing the four PyTorch models weights described in our article and<strong><em> </em></strong><em><strong>inception_env.py</strong></em> the used Inception V3 architecture. <em><strong>index.json</strong></em> contains the dictionnary linking the models class indexes from 0 to 14128 with our labels <em>speciesKey</em>: {""class_index"":speciesKey}. <strong>ACKNOWLEDGMENTS</strong>: We warmly thank Alexander Zizka et al. for providing us the geographically and taxonomically curated set of Orchids occurrences. This dataset contains modified Copernicus Sentinel data and Copernicus Service information (2018). Sentinel-2 MSI data used were available at no cost from ESA Sentinels Scientific Data Hub.",mds,True,findable,0,0,0,0,0,2021-12-17T18:08:57.000Z,2021-12-17T18:08:59.000Z,cern.zenodo,cern,"Species Distribution Models,Deep Learning,Satellite Image Time-series,Sentinel-2 ESA mission,Environmental context,Predictive data,Deep-SDMs,Inception v3,Convolutional Neural Networks,Remote Sensing,Spaceborne Ecology","[{'subject': 'Species Distribution Models'}, {'subject': 'Deep Learning'}, {'subject': 'Satellite Image Time-series'}, {'subject': 'Sentinel-2 ESA mission'}, {'subject': 'Environmental context'}, {'subject': 'Predictive data'}, {'subject': 'Deep-SDMs'}, {'subject': 'Inception v3'}, {'subject': 'Convolutional Neural Networks'}, {'subject': 'Remote Sensing'}, {'subject': 'Spaceborne Ecology'}]",,
+10.5281/zenodo.4118790,Inducing micromechanical motion by optical excitation of a single quantum dot - experimental data and evaluation scripts,Zenodo,2020,en,Other,"Creative Commons Attribution 4.0 International,Open Access","This data set contains the raw data and the evaluation scripts applied to obtain the results published in ""Inducing micromechanical motion by optical excitation of a single quantum dot"". For details of the experimental procedure please refer to the main text of the article, as well as the supplementary information. The main archive (.zip) contains three Python / Jupyter notebooks: `cand3_modeV_induced_motion.ipynb` contains the analysis of the main results `cand3_modeV_optomechanical_coupling.ipynb` contains an analysis of the opto-mechanical coupling `cand3_modeV_thermal_motion.ipynb`contains an analysis of the thermal motion and effective mass Plots and data that were shown in the main text and supplementary information are written to a subfolder `exports`. Further subfolders contain the evaluated raw data. Two programs have been used to create the raw data. `LabOne` by Zurich Instruments has been used to acquire lock-in data from the micro-mechanical oscillator, as well as resonance-fluorescence data from the quantum dot. The data has been stored as comma separated values in (.csv).<br> Additional data, i.e, the gradient for the optical mechanical motion detection, as well as photo-luminescence spectra of the quantum dot, have been acquired by a selfmade python software `LABCO`. This data has also been stored as comma separeted values (.csv). All scripts were written using Python 3.6.9, and evaluated in Jupyter using IPython 5.5.0. The following non-standard packages (all available through pypi.org) were used during the evaluation: `lmfit` 0.9.7 `matplotlib`2.1.1 `numpy` 1.13.3",mds,True,findable,0,0,1,0,0,2020-10-22T21:33:01.000Z,2020-10-22T21:33:03.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4761321,"Fig. 37 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 37. Dictyogenus muranyii sp. n., larva. Karstic spring of Brudour, Drôme dpt, France. Photo A. Ruffoni.",mds,True,findable,0,0,4,0,0,2021-05-14T07:47:26.000Z,2021-05-14T07:47:26.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.832421,Data Of The Publication: Dispersive Heterodyne Probing Method For Laser Frequency Stabilization Based On Spectral Hole Burning In Rare-Earth Doped Crystals By O. Gobron Et Al.,Zenodo,2017,,Dataset,"Creative Commons Attribution 4.0,Open Access","Data corresponding to the figures of the publication ""Dispersive heterodyne probing method for laser frequency stabilization based on spectral hole burning in rare-earth doped crystals"" by O. Gobron et al. (https://doi.org/10.1364/OE.25.015539). A text file describes data in each compressed folder, please refer to the caption in the publication for more details.",,True,findable,0,0,0,0,0,2017-07-20T07:51:17.000Z,2017-07-20T07:51:17.000Z,cern.zenodo,cern,"rare earth,quantum technologies,nanoqtech,metrology,laser stabilization","[{'subject': 'rare earth'}, {'subject': 'quantum technologies'}, {'subject': 'nanoqtech'}, {'subject': 'metrology'}, {'subject': 'laser stabilization'}]",,
+10.6084/m9.figshare.23575360.v1,Additional file 1 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Composition of growth media and phylogenetic characterization. The data provided describe the both growth media and the phylogenetic affiliation of the pure strains which were isolated from the FR bacterial community. (DOC 76 KB),mds,True,findable,0,0,0,0,0,2023-06-25T03:11:45.000Z,2023-06-25T03:11:46.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['77312 Bytes'],
+10.5281/zenodo.8283641,TURRIS: an open source database and Python tools to compute the fundamental frequency of historic masonry towers,Zenodo,2023,en,Software,"Creative Commons Attribution 3.0 IGO,Open Access","TURRIS (<strong>T</strong>owers feat<strong>UR</strong>es & f<strong>R</strong>equenc<strong>I</strong>es databa<strong>S</strong>e) is a database collecting information of 244 historical masonry towers and information about the associated dynamic identification. Each tower is described by 23 parameters (identification, initial database, reference of the study, building name, country, town, latitude, longitude, height, effective height, shape of the section, regularity of the elevation, width, length, the minimum and maximum wall thickness, its relation with adjacent building, age, bells mass, Young modulus, mass density, Poisson ratio, and any information about the structural state of the tower). Each Operational Modal Analysis survey is described by 8 parameters (fundamental frequency, minimum, maximum, and standard deviation of the fundamental frequencies for long-term analysis, the type of sollicitation, duration of the records, sampling rate, and identification technique). The 244 historical masonry towers are located worldwide (mainly in Europe). The TURRIS database allows studying the relationship between geometrical, material parameters, and fundamental frequency. The database is regularly updated. Data can be transmitted by completing the following form: https://framaforms.org/turris-database-sharing-information-about-features-of-historical-masonry-towers-1692963128. The details of each metadata field of the TURRIS database are given in the following. <strong>Id</strong> : the identifier for each study <strong>database</strong> : the collection from where the study was taken into account <strong>references</strong> : the reference of the scientific study. The reference id maybe used with the associated bibtex file., <strong>building_name</strong> : the name of the historical building <strong>country</strong>, town, latitude, longitude : the four parameters describe the location of the building <strong>input</strong> : type of sollicitation <strong>f0</strong> [Hz] : the measured fundamental frequency <strong>H</strong> [m] : the height of the tower <strong>Heff</strong> [m]: the effective height of the tower computed as the difference between the absolute height of the building and the height of the any adjacent building <strong>shape</strong> : the shape of the tower section (SQ : square, REC : rectangular, CIR : circular) <strong>elevation_regularity</strong> : the regularity of section from bottom to the top <strong>width</strong> [m]: the shorter dimension of the section <strong>length</strong> [m]: the larger dimension of the section <strong>min_wall_thickness</strong> [m]: the minimum thickness of the wall of the tower <strong>max_wall_thickness</strong> [m]: the maximum thickness of the wall of the tower <strong>relation</strong> : the type of connection between the tower and adjacent building (Isolated or bounded) <strong>period</strong> : the age of construction <strong>bells</strong> [kg]: the mass of the bell system <strong>E</strong> [GPa]: the Young modulus <strong>density</strong> [kg.m-3]: the mass density <strong>Poisson_ratio</strong> : the Poisson ratio <strong>duration</strong> [minute]: the duration of the records <strong>sampling_rate</strong> [Hz] : the sampling rate of the records <strong>info</strong> : any information about potential damage or retrofitting actions <strong>OMA_technique</strong> : the technique used to identify modal parameters <strong>min_f0</strong> [Hz]: the minimum measured fundamental frequency measured over time <strong>max_f0</strong> [Hz]: the maximum measured fundamental frequency measured over time <strong>std_f0</strong> [[Hz]: the standard deviation of fundamental frequency measured over time Python scripts have been developped (@MArnaud, @CGcidou) to compute the fundamental frequency using empirical, physics-based formulations and a Ritz-Rayleigh approach. The <strong>TURRIS</strong> database is used as an input. The <strong>TURRIS</strong> database is a product of the <strong>ACROSS</strong> project (ANR-20-CE03–0003) founded by the French National Research Agency.",mds,True,findable,0,0,0,1,0,2023-08-25T14:30:15.000Z,2023-08-25T14:30:15.000Z,cern.zenodo,cern,"historical masonry towers,database,form,fundamental frequency,Cultural Heritage","[{'subject': 'historical masonry towers'}, {'subject': 'database'}, {'subject': 'form'}, {'subject': 'fundamental frequency'}, {'subject': 'Cultural Heritage'}]",,
+10.5061/dryad.wh70rxwnf,Simulation of sheared granular layers activated by fluid pressurization,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Fluid pressurization of critically stressed sheared zones can trigger slip mechanisms at play in many geological rupture processes, including earthquakes or landslides. The increasing fluid pressure reduces the effective stress, giving possibility to the shear zone to reactivate. Nonetheless, the mechanisms that dictate the mode of slip, from aseismic steady creep to seismic dynamic rupture, remain poorly understood. By using discrete element modeling, we simulate pore-pressure-step creep test experiments on a sheared granular layer under a sub-critical stress state. The goal is to investigate the micromechanical processes at stake during fluid induced reactivation. The global simulated response is consistent with both laboratory and in situ experiments. In particular, the progressive increase of pore pressure promotes slow steady slip at sub-critical stress states (creep), and fast accelerated dynamic slip once the critical strength is overcome (rupture). The analyses of both global and local quantities show that these two emergent slip behaviors correlate to characteristic deformation modes: diffuse deformation during creep, and highly localized deformation during rupture. Our results suggest that the fabric of pressurized shear zones controls their emergent slip behavior. In particular, rupture results from grain rotations initiating from overpressure induced unlocking of interparticle contacts mostly located within the shear band, which, as a consequence, acts as a roller bearing for the surrounding bulk.",mds,True,findable,146,8,0,1,0,2021-05-28T18:22:24.000Z,2021-05-28T18:22:26.000Z,dryad.dryad,dryad,"FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences","[{'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['11239505 bytes'],
+10.5281/zenodo.6683741,Scripts generating maps and boxplots for extracted propositions from the French Great National Debate (Grand Débat National),Zenodo,2022,fr,Software,"Creative Commons Attribution 4.0 International,Open Access","This floder provides scripts to build maps and draw boxplots, to represent extracted propositions from the French Great National Debate (Grand Débat National) : - Dicogeo.R is a script which build the socio-economic descriptions of municipalities, based on several other files, - génération_map_grand_débat.py is a script which build maps to represent extracted propositions from the French Great National Debate (Grand Débat National), - graphiques.R is a script which generates bowplots crossing extracted propositions and socio-economic features.",mds,True,findable,0,0,3,0,0,2022-06-22T08:40:54.000Z,2022-06-22T08:40:55.000Z,cern.zenodo,cern,"https://fr.wikipedia.org/wiki/Grand_d%C3%A9bat_national,https://fr.wikipedia.org/wiki/Transport","[{'subject': 'https://fr.wikipedia.org/wiki/Grand_d%C3%A9bat_national', 'subjectScheme': 'url'}, {'subject': 'https://fr.wikipedia.org/wiki/Transport', 'subjectScheme': 'url'}]",,
+10.5281/zenodo.8085467,Randomly stacked open cylindrical shells as functional mechanical energy absorber,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Experimental and simulation data for the paper entitled <em>Randomly stacked open cylindrical shells as functional mechanical energy absorber. </em> Download and unzip the AllFigureData.zip. Contact Experiments: sano@mech.keio.ac.jp Simulations: florence.bertails@inria.fr,mds,True,findable,0,0,0,0,0,2023-06-29T07:26:26.000Z,2023-06-29T07:26:26.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7580589,The hidden hierarchical nature of soft particulate gels,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains data for the manuscript ""The hidden hierarchical nature of soft particulate gels"".",mds,True,findable,0,0,0,0,0,2023-02-01T03:58:55.000Z,2023-02-01T03:58:56.000Z,cern.zenodo,cern,"Soft Particulate Gels,Linear Viscoelasticity,Ladder Model,Hierarchical Assembly,Linear Rheology","[{'subject': 'Soft Particulate Gels'}, {'subject': 'Linear Viscoelasticity'}, {'subject': 'Ladder Model'}, {'subject': 'Hierarchical Assembly'}, {'subject': 'Linear Rheology'}]",,
+10.6084/m9.figshare.23822163.v1,Dataset key for the main experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,Key for the dataset for the main experiment,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:29.000Z,2023-08-02T11:18:29.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['1240 Bytes'],
+10.5281/zenodo.8147580,"Digital elevation models of the paper: Holocene Earthquakes on the Tambomachay Fault near Cusco, Central Andes",Zenodo,2023,,Other,"Creative Commons Attribution 4.0 International,Open Access","Digital Elevation Models (DEM) of the paper: Holocene earthquakes on the Tambomachay Fault near Cusco, Central Andes. These DEMS were used for the morphometric and morphotectonic analysis of the Tambomachay Fault.",mds,True,findable,0,0,0,0,0,2023-07-14T19:15:06.000Z,2023-07-14T19:15:07.000Z,cern.zenodo,cern,"Paleoseismology, active faulting, historical seismicity, Cusco, Peru, Central Andes","[{'subject': 'Paleoseismology, active faulting, historical seismicity, Cusco, Peru, Central Andes'}]",,
+10.57745/w9n5z9,Habitants exposés au retrait-gonflement des argiles et/ou aux risques d'inondation,Recherche Data Gouv,2023,,Dataset,,"Nombre d’habitants exposés au phénomène de retrait-gonflement des argiles (Aléa faible, moyen, fort) et/ou aux risques d’inondation (niveau de risque moyen de débordement des cours d’eau, ruissellement, submersion marine). INSEE_COM : commune (édition Juin 2023) ALEA_Faible : nombre d’habitants (2017) dans une zone de retrait-gonflement des argiles à faible aléa ; ALEA_Moyen : nombre d’habitants (2017) dans une zone de retrait-gonflement des argiles à aléa moyen ; ALEA_Fort : nombre d’habitants (2017) dans une zone de retrait-gonflement des argiles à aléa fort debordement_02Moy : nombre d’habitants (2017) exposés à un niveau moyen de débordement debordement_NA : nombre d’habitants (2017) non exposés au débordement ruissellement_02Moy : nombre d’habitants (2017) exposés à un niveau moyen de ruissellement ruissellement_NA : nombre d’habitants (2017) non exposés au ruissellement submersion_02Moy : : nombre d’habitants (2017) exposés à un niveau moyen de submersion marine submersion_NA : nombre d’habitants (2017) non exposés à une submersion marine",mds,True,findable,26,6,0,0,0,2023-07-06T13:15:30.000Z,2023-07-06T13:18:20.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.10058946,Data used in 'Slumping regime in lock-release turbidity currents',Zenodo,2023,en,Dataset,Other (Open),"This repository contains the data used in the paper:
+
+Gadal, C., Mercier, M., Rastello, M., & Lacaze, L. (2023). Slumping regime in lock-release turbidity currents. Journal of Fluid Mechanics, 974, A4. doi:10.1017/jfm.2023.762
+where the slumping regime of turbidity currents is studied with respect to the initial volume fraction, the bottom slope and the particle settling velocity. The folder 'runs' contains 169 netcdf4 files corresponding to each experimental run used in the paper. For each run, the structure of the NetCDF file is the following:
+
+attributes:
+
+particle_type: particle type used (silica sand, glass beads or saline water)
+run_number: NetCDF file name
+expe_type: always lock-release here
+surface_type: can be 'open surface' or 'rigid lid'
+set_up: can be 'set-up 1' or 'set-up 2'
+run_oldID: run name corresponding to the experimental notebook
+groups:
+
+initial_parameters:
+
+dimensions(sizes):
+variables(dimensions):
+
+Bottom slope(): bottom slope
+Current density(): initial average (fluid + particle) lock density
+Grain density(): particle density (not measured, estimated)
+Grain diameter(): particle diameter
+Initial Reynolds number(): initial Reynolds number, [rho_0 * u_0 * h_0 / mu]
+Initial Rouse number(): initial Rouse number, [v_s / u_0]
+Initial volume fraction(): initial lock particle volume fraction
+Reduced gravity(): reduced gravity, [g*(rho_0 - rho_f)/rho_f]
+Settling velocity(): particle settling velocity
+Temperature(): water temperature (not measured)
+V0 (lock volume)(): lock suspension volume
+Water density(): water density
+Water dynamic viscosity(): water dynamic viscosity (not measured)
+h0 (lock height)(): suspension height inside lock
+u0 (velocity scale)():Â velocity scale, [sqrt(g'*h_0)]
+w0 (tank width)(): lock crosstream width
+x0 (lock length)(): lock streamwise length
+scalar_variables:
+
+dimensions(sizes): tuples(2), x(1181)
+variables(dimensions):
+
+Av. shape('x',): current average shape
+Av. shape head volume(): Volume per unit of width of the head part of current average shape
+Av. shape tail volume(): Volume per unit of width of the tail part of current average shape
+Av. shape volume(): Volume per unit of width of current average shape
+Bulk entrainment coefficient(): Bulk entrainment coefficient during slumping
+Current Froude number(): Current Froude number, [u_c/sqrt(g' * h_b)]
+Current Reynolds number(): Current Reynolds number, [rho_0 * u_c * h_b / mu]
+Current Rouse number(): Current Rouse number, [v_s / u_c]
+Current head height (log fit)(): current height h_h coming from log fit
+Current height (benjamin fit)(): current height h_b coming from fit of Benjamin's shape
+Current nose height (benjamin fit)(): current nose height h_n coming from fit of Benjamin's shape
+Current nose height (log fit)(): current nose h_n coming from log fit
+Geometrical Froude number(): Current Geometrical Froude number, [u_c/sqrt(g' * h0)]
+Geometrical Reynolds number(): Current Geometrical Reynolds number [rho_0 * u_c * h0 / mu]
+Times lock opening (tstart, tend)('tuples',): Start and end times of lock opening
+Times slumping regime (tstart, tend)('tuples',): Start and end times of constant velocity regime
+Velocity (slumping regime)(): Current velocity during slumping
+time_series:
+dimensions(sizes): time(3071)
+variables(dimensions):
+Volume('time',): current volume per unit of width
+contour time series (x)('time',): x coordinate time series of the current contours
+contour time series (y)('time',): y coordinate time series of the current contours
+position('time',): front position
+time('time',): time vector
+velocity('time',): front velocity
+Most variables possess the following attributes:
+
+unit: corresponding unit
+std: error(s) on the given quantity, calculated by error propagation from measurement uncertainties using the `uncertainties` module (https://pythonhosted.org/uncertainties/) in Python.
+comments: comments on the given quantity (definition, formulas, etc ..)
+Note that all variables related to the current shape are not available for experimental runs carried out in set-up 2.The script ReadPlotData.py shows how to display the structure of a NetCDF file, and gives examples of how to load some variables and plot them by reproducing some of the paper's figures.The CSV file 'dataset_summary.csv' offers a summary of all runs and corresponding experimental parameters, allowing for easier access for testing purposes. *Note that errors are not given in this file.*
+OpenData License: licence-ouverte-v2.0
+If you use this open data in your work (research or other), please cite in your bibliography the following reference doi:https://doi.org/10.1017/jfm.2023.762",api,True,findable,0,0,0,0,0,2023-10-31T17:04:29.000Z,2023-10-31T17:04:30.000Z,cern.zenodo,cern,"Experiments,Fluid dynamics,Geophysics,FOS: Earth and related environmental sciences,Gravity currents,Turbidity currents,Lock-release,Dam-break","[{'subject': 'Experiments'}, {'subject': 'Fluid dynamics'}, {'subject': 'Geophysics'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Gravity currents'}, {'subject': 'Turbidity currents'}, {'subject': 'Lock-release'}, {'subject': 'Dam-break'}]",,
+10.5281/zenodo.5654628,PACT-1D model version including polar halogen emissions - output files,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This dataset includes all output files created from the PACT-1D model (v1.0) developed with Arctic chlorine and bromine emission parameterizations. The PACT-1D source code used to create these output files is available at: https://doi.org/10.5281/zenodo.5654589.,mds,True,findable,0,0,0,0,0,2021-11-08T14:46:31.000Z,2021-11-08T14:46:32.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5145755,Functionally distinct tree species support long-term productivity in extreme environments,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset used for the article ""Functionally distinct tree species support long-term productivity in extreme environments"", submitted to <em>Proceedings of the Royal society B</em>. Contains raw output of simulations performed with the ForCEEPS forest gap model (http://capsis.cirad.fr/capsis/help_en/forceeps). For a description of the simulations performed and the dataset, see the associated GitHub (https://github.com/LDelalandre/Project-1_Distinct-sp_BEF) and the article. Simulations are grouped in 11 folders corresponding to the 11 environmental conditions used for simulating community dynamics. Subfolders group outputs by species richness gradients (30 random orders, plus ""decreasing"" order, which is from the most functionally distinct to the least functioonally distinct species, and ""increasing, which is the other way around, and monocultures). For each species richness level (from 1: all the species, to 30, the last species of the richness gradient), four different files were generated: - biomass data: 'complete' (every individual); 'mean' (aggregated at the community level each year); - productivity data: productivity (every individual); productitity_scene (aggregated at the species level each year).",mds,True,findable,0,0,0,0,0,2021-07-29T13:11:47.000Z,2021-07-29T13:11:48.000Z,cern.zenodo,cern,Functional rarity; Functional distinctiveness; Biodiversity and ecosystem functioning; Productivity; Virtual ecology; Forest gap model,[{'subject': 'Functional rarity; Functional distinctiveness; Biodiversity and ecosystem functioning; Productivity; Virtual ecology; Forest gap model'}],,
+10.5281/zenodo.5119079,Tortured phrases: A dubious writing style emerging in science. Evidence of critical issues affecting established journals.,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Supplementary materials to preprint https://arxiv.org/abs/2107.06751.,mds,True,findable,0,0,0,0,0,2021-07-21T12:12:01.000Z,2021-07-21T12:12:02.000Z,cern.zenodo,cern,"AI-generated texts,GPT,Misconduct,Research integrity,Tortured phrase","[{'subject': 'AI-generated texts'}, {'subject': 'GPT'}, {'subject': 'Misconduct'}, {'subject': 'Research integrity'}, {'subject': 'Tortured phrase'}]",,
+10.5281/zenodo.3557199,Global and regional glacier mass changes from 1961 to 2016,Zenodo,2019,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Supplementary data tables with the results from Zemp et al. (2019) entitled ""<em><strong>Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016</strong></em>"", Nature: <strong>Data Tables 1a-t | Temporal variabilities for glaciological clusters based on variance decomposition model. </strong>Annual results are made available as csv-files for all 20 cluster: Zemp_etal_results_clusters.zip <strong>Data Tables 2a-t | Regional and global mass balance and mass change results from 1961-2016. </strong>Annual results are made available as csv-files for all 19 regions (cf. RGI 6.0) as well as for the global sum: Zemp_etal_results_regions_global.zip <strong>Data Table 3 | Glacier mass changes for Central Europe from 1961-2016. </strong>Annual results as in Data Table 2 but with examples for multi-year error calculations are made available as Excel-file: Zemp_etal_results_region-CEU_errorcalcs.xlsx <strong>Note</strong>: The corresponding full sample of glaciological and geodetic observations for individual glaciers are publicly available from the World Glacier Monitoring Service: http://doi.org/10.5904/wgms-fog-2018-11 <strong>Version 1.1</strong><br> This version provides the results from the glaciological clusters (Data Tables 1a-t) as used by Zemp et al. (2019). In addition, it contains corrected results for region Iceland (Data Table 2, region_6_ISL) and correspondingly for the global sum (Data Table 2, global); the results for the other regions remain unchanged. For more details on the correction of the regional results for Iceland, see Zemp et al. (2019, Nature), Author Correction. <strong>Version 1.0</strong><br> Data tables containing the results for the 20 glaciological clusters (Data Tables 1a-t) as well as for the 19 regions and global sums (Data Tables 2a-t) related to the publication by Zemp et al. (2019, Nature). We note that this version erroneously contains pre-release versions of results for most of the glaciological clusters that were not used in Zemp et al. (2019, Nature).",mds,True,findable,13,0,0,0,0,2019-11-29T07:40:00.000Z,2019-11-29T07:40:01.000Z,cern.zenodo,cern,"glacier,mass balance,mass change,sea-level rise","[{'subject': 'glacier'}, {'subject': 'mass balance'}, {'subject': 'mass change'}, {'subject': 'sea-level rise'}]",,
+10.5281/zenodo.7693381,Long term mean Potential Evapotranspiration (PET) and Actual Evapotranspiration (EAT) estimates using World-Wide HYPE and different PET-formula,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data of the article ""<strong>Which Potential Evapotranspiration Formula to Use in Hydrological Modelling World-wide? </strong>"" (Pimentel et al. 2023, <em>Water Resources Research, </em>https://doi.org/10.1029/2022WR033447)",mds,True,findable,0,0,0,0,0,2023-03-02T20:14:03.000Z,2023-03-02T20:14:03.000Z,cern.zenodo,cern,"Evapotranspiration, Global Hydrological Model, PET-formula","[{'subject': 'Evapotranspiration, Global Hydrological Model, PET-formula'}]",,
+10.6084/m9.figshare.c.6712342.v1,Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract High levels of arsenic in groundwater and drinking water are a major health problem. Although the processes controlling the release of As are still not well known, the reductive dissolution of As-rich Fe oxyhydroxides has so far been a favorite hypothesis. Decoupling between arsenic and iron redox transformations has been experimentally demonstrated, but not quantitatively interpreted. Here, we report on incubation batch experiments run with As(V) sorbed on, or co-precipitated with, 2-line ferrihydrite. The biotic and abiotic processes of As release were investigated by using wet chemistry, X-ray diffraction, X-ray absorption and genomic techniques. The incubation experiments were carried out with a phosphate-rich growth medium and a community of Fe(III)-reducing bacteria under strict anoxic conditions for two months. During the first month, the release of Fe(II) in the aqueous phase amounted to only 3% to 10% of the total initial solid Fe concentration, whilst the total aqueous As remained almost constant after an initial exchange with phosphate ions. During the second month, the aqueous Fe(II) concentration remained constant, or even decreased, whereas the total quantity of As released to the solution accounted for 14% to 45% of the total initial solid As concentration. At the end of the incubation, the aqueous-phase arsenic was present predominately as As(III) whilst X-ray absorption spectroscopy indicated that more than 70% of the solid-phase arsenic was present as As(V). X-ray diffraction revealed vivianite Fe(II)3(PO4)2.8H2O in some of the experiments. A biogeochemical model was then developed to simulate these aqueous- and solid-phase results. The two main conclusions drawn from the model are that (1) As(V) is not reduced during the first incubation month with high Eh values, but rather re-adsorbed onto the ferrihydrite surface, and this state remains until arsenic reduction is energetically more favorable than iron reduction, and (2) the release of As during the second month is due to its reduction to the more weakly adsorbed As(III) which cannot compete against carbonate ions for sorption onto ferrihydrite. The model was also successfully applied to recent experimental results on the release of arsenic from Bengal delta sediments.",mds,True,findable,0,0,0,0,0,2023-06-25T03:12:09.000Z,2023-06-25T03:12:10.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",,
+10.5281/zenodo.5142591,Bayesian Archetypes: Energy signature inference from national data for statistical definition of buildings archetypes.,Zenodo,2021,en,Software,"Apache License 2.0,Open Access",Energy signature inference from national data for statistical definition of buildings archetypes. This project contains the code and data used for the paper <strong>Bayesian inference of dwellings energy signature at national scale: case of the French residential stock</strong>. It aims to infer energy signature of dwelling categories from national census and consumption data.,mds,True,findable,0,0,0,0,0,2021-09-07T16:49:50.000Z,2021-09-07T16:49:50.000Z,cern.zenodo,cern,"Bayesian Inference,Energy Signature,Urban Energy Modeling,Uncertainties,Open Data","[{'subject': 'Bayesian Inference'}, {'subject': 'Energy Signature'}, {'subject': 'Urban Energy Modeling'}, {'subject': 'Uncertainties'}, {'subject': 'Open Data'}]",,
+10.34847/nkl.aacad5y8,Bulletin franco-italien 1912 n°1 janvier - février,NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Book,,"1912/01 (A4,N1)-1912/02.",api,True,findable,0,0,0,0,0,2022-06-29T10:15:11.000Z,2022-06-29T10:15:12.000Z,inist.humanum,jbru,Etudes italiennes,[{'subject': 'Etudes italiennes'}],"['21511939 Bytes', '20908048 Bytes', '21034528 Bytes', '21036982 Bytes', '20976655 Bytes', '20863780 Bytes', '20901724 Bytes', '21007228 Bytes', '20950432 Bytes', '21051706 Bytes', '20663584 Bytes', '21281992 Bytes', '20952853 Bytes', '20689258 Bytes', '20872804 Bytes', '21019279 Bytes', '20934214 Bytes', '6436585 Bytes', '21037318 Bytes']","['image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'application/pdf', 'image/tiff']"
+10.5281/zenodo.1475283,SPARK_Stimulo_session_05072017_Grenoble,Zenodo,2018,es,Audiovisual,"Creative Commons Attribution Non Commercial 4.0 International,Open Access","Recording of a collaborative design session between designers and end-users.
+
+A design company invites a final consumer to provide feedback on the layout of user interface elements (lights, speakers, buttons) and the aesthetic design (colours, materials and finishes) of an industrial product. The session is conducted using a Spatial Augmented Reality (SAR) application which allows a real-time modification of the design contents. Language: Spanish.",mds,True,findable,0,0,0,0,0,2018-10-30T17:05:42.000Z,2018-10-30T17:05:43.000Z,cern.zenodo,cern,"SPARK,H2020,Collaborative design,Co-design,Spatial Augmented Reality,Augmented Reality,Mixed prototype,ICT,Creativity,Product design","[{'subject': 'SPARK'}, {'subject': 'H2020'}, {'subject': 'Collaborative design'}, {'subject': 'Co-design'}, {'subject': 'Spatial Augmented Reality'}, {'subject': 'Augmented Reality'}, {'subject': 'Mixed prototype'}, {'subject': 'ICT'}, {'subject': 'Creativity'}, {'subject': 'Product design'}]",,
+10.5281/zenodo.8308027,"Analysis of life span of H2 outgassing, volume of rock and porosity relationship",Zenodo,2023,en,Software,Closed Access,"Matlab Script where we plot three scenarios that could account for the observed native H2 flow rate, emphasizing the respective roles of the fault zone, the mine’s drainage volume, and the entire ophiolite massif.",mds,True,findable,0,0,0,0,0,2023-09-01T10:35:02.000Z,2023-09-01T10:35:02.000Z,cern.zenodo,cern,Geosciences; Native Hydrogen; Natural Hydrogen; Matlab;,[{'subject': 'Geosciences; Native Hydrogen; Natural Hydrogen; Matlab;'}],,
+10.5281/zenodo.4024414,Magnetization versus applied dc magnetic field data for Li0.7[Cr(pyz)2]Cl0.7·(THF),Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Magnetization versus applied dc magnetic field data in the –7 to 7 T field range from 1.85 K to 520 K for Li<sub>0.7</sub>[Cr(pyz)<sub>2</sub>]Cl<sub>0.7</sub>·(THF). The data are provided in a tab-delimited text format.,mds,True,findable,0,0,0,0,0,2020-09-11T14:22:17.000Z,2020-09-11T14:22:18.000Z,cern.zenodo,cern,"Molecule-based magnets,Metal-organic magnets,Coordination chemistry,Molecular magnetism","[{'subject': 'Molecule-based magnets'}, {'subject': 'Metal-organic magnets'}, {'subject': 'Coordination chemistry'}, {'subject': 'Molecular magnetism'}]",,
+10.5281/zenodo.6406158,"Data: Clouds drive differences in future surface melt over the Antarctic ice shelves (Kittel et al., 2022)",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Outputs used in: <em>Kittel, C., Amory, C., Hofer, S., Agosta, C., Jourdain, N. C., Gilbert, E., Le Toumelin, L., Gallée, H., and Fettweis, X.: Clouds drive differences in future surface melt over the Antarctic ice shelves, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2021-263, accepted, 2021.</em> MAR outputs with summer values of melt, surface energy budget components, and cloud properties over the Antarctic ice sheet (1980--2100) Grid file used in MAR simulations If you need other variables or output frequencies from MAR, write me (c2kittel@gmail.com) and I will be glad to help you. I will also be happy to share the scripts I have developed to analyse the outputs and make the figures in this paper if needed. Please cite the paper if you use these MAR outputs.<br> <br> Data usage notice: If you use any of these results, please acknowledge the work of the people involved in producing them. Acknowledgements should have language similar to the below that contained both informations related to MAR. In order to document MAR scientific impact and enable ongoing support of the model, users are likely encouraged to contact C. Kittel to add their works in the list of MAR-related publications. ""We thank C. Kittel and the MAR team which make available the model outputs, as well agencies (F.R.S - FNRS, CÉCI, and the Walloon Region) that provided computational resources for MAR simulations. "" You should also refer to and cite the following paper: <em>Kittel, C., Amory, C., Hofer, S., Agosta, C., Jourdain, N. C., Gilbert, E., Le Toumelin, L., Gallée, H., and Fettweis, X.: Clouds drive differences in future surface melt over the Antarctic ice shelves, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2021-263, accepted, 2021.</em>",mds,True,findable,0,0,0,0,0,2022-05-30T07:54:28.000Z,2022-05-30T07:54:28.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4303996,protopipe,Zenodo,2020,,Software,"CeCILL-B Free Software License Agreement,Open Access",Prototype data analysis pipeline for the Cherenkov Telescope Array (CTA) Observatory.,mds,True,findable,0,0,0,0,0,2020-12-03T13:18:57.000Z,2020-12-03T13:18:57.000Z,cern.zenodo,cern,"CTA,simulations,grid,pipeline,IACT,astronomy,gamma","[{'subject': 'CTA'}, {'subject': 'simulations'}, {'subject': 'grid'}, {'subject': 'pipeline'}, {'subject': 'IACT'}, {'subject': 'astronomy'}, {'subject': 'gamma'}]",,
+10.5281/zenodo.3514728,Interannual iceberg meltwater fluxes over the Southern Ocean,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Monthly Iceberg Meltwater Fluxes over the Southern Ocean (1972-2017) :</strong> Here is an update of the iceberg meltwater climatology initially provided by Merino et al (2016). This flux is still derived from NEMO's Lagrangian iceberg module developed by Marsh et al. (2015) and updated by Merino et al. (2016). It is run within a global ORCA025 ocean simulation running from 1958 to 2017, forced by the Drakkar Forcing Set (DFS-5.2; Dussin et al 2016). The 1958-1972 period is used to spin up the model, and the meltwater fluxes are provided over 1972-2017. The iceberg calving fluxes are constant, but their meltwater fluxes varies seasonally and interannually. Ice-shelf meltwater fluxes are reconstructed from glaciological observations (Merino et al. 2018), and here vary linearly from 1990 to 2010 (constant before and after). <strong>Known caveats:</strong> The ocean grid is the old ""ORCA025"" grid, which does not extend southward of 70°S, i.e. iceberg do not follow the southernmost ice shelf edges (e.g. Ronne ice shelf). <strong>References:</strong> Dussin, Raphael, Bernard Barnier, Laurent Brodeau, and Jean Marc Molines (2016). Drakkar Forcing Set DFS5. Marsh, R., Ivchenko, V. O., Skliris, N., Alderson, S., Bigg, G. R., Madec, G., and others (2015). NEMO-ICB (v1. 0): interactive icebergs in the NEMO ocean model globally configured at eddy-permitting resolution. <em>Geoscientific Model Development</em>, <em>8</em>(5), 1547-1562. Merino, N., Le Sommer, J., Durand, G., Jourdain, N. C., Madec, G., Mathiot, P. and Tournadre, J. (2016). Antarctic icebergs melt over the Southern Ocean: Climatology and impact on sea ice. <em>Ocean Modelling</em>, <em>104</em>, 99-110. Merino, N., Jourdain, N. C., Le Sommer, J., Goosse, H., Mathiot, P. and Durand, G. (2018). Impact of increasing antarctic glacial freshwater release on regional sea-ice cover in the Southern Ocean. <em>Ocean Modelling</em>, <em>121</em>, 76-89.",mds,True,findable,0,0,2,4,0,2019-10-21T10:25:34.000Z,2019-10-21T10:25:34.000Z,cern.zenodo,cern,"iceberg,Southern Ocean,Antarctica,meltwater,freshwater","[{'subject': 'iceberg'}, {'subject': 'Southern Ocean'}, {'subject': 'Antarctica'}, {'subject': 'meltwater'}, {'subject': 'freshwater'}]",,
+10.25384/sage.c.6837354.v1,Perceived Quality of Life in Intensive Care Medicine Physicians: A French National Survey,SAGE Journals,2023,,Collection,Creative Commons Attribution 4.0 International,"PurposeThere is a growing interest in the quality of work life (QWL) of healthcare professionals and staff well-being. We decided to measure the perceived QWL of ICU physicians and the factors that could influence their perception. <b>Methods:</b> We performed a survey coordinated and executed by the French Trade Union of Intensive Care Physicians (SMR). QWL was assessed using the French version of the Work-Related Quality of Life (WRQoL) scale, perceived stress using the French version of 10 item-Perceived Stress Scale (PSS-10) and group functioning using the French version of the Reflexivity Scale, the Social Support at Work Questionnaire (QSSP-P). <b>Results:</b> 308 French-speaking ICU physicians participated. 40% perceived low WRQoL, mainly due to low general well-being, low satisfaction with working conditions and low possibility of managing the articulation between their private and professional lives. Decreased QWL was associated with being a woman (p = .002), having children (p = .022) and enduring many monthly shifts (p = .022). <b>Conclusions:</b> This work highlights the fact that ICU physicians feel a significant imbalance between the demands of their profession and the resources at their disposal. Communication and exchanges within a team and quality of social support appear to be positive elements to maintain and/or develop within our structures.",mds,True,findable,0,0,0,0,0,2023-09-15T12:11:54.000Z,2023-09-15T12:11:54.000Z,figshare.sage,sage,"Emergency Medicine,Aged Health Care,Respiratory Diseases","[{'subject': 'Emergency Medicine'}, {'subject': 'Aged Health Care'}, {'subject': 'Respiratory Diseases'}]",,
+10.5281/zenodo.4761347,"Figs. 79-82. Dictyogenus fontium species complex, adults. 79 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 79-82. Dictyogenus fontium species complex, adults. 79. Female, head and pronotum. Inner-alpine upper Isère Valley. Col de l'Iseran, Savoie dpt, France. Photo A. Ruffoni. 80. Adult male, epiproct with frontal apical sclerite and lateral stylet, lateral view. Julian Alps, Slovenia. Photo J. -P.G. Reding. 81. Adult male hemitergal lobes, dorsal view. Rhaetian Alps, Switzerland. Photo J.-P.G. Reding. 82. Adult male, posterior margin of sternite 7 with ventral vesicle, ventral view. Rhaetian Alps, Switzerland. Photo J.-P.G. Reding.",mds,True,findable,0,0,6,0,0,2021-05-14T07:51:20.000Z,2021-05-14T07:51:21.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.6401829,"Data to the journal article ""The capping agent is the key: Structural alterations of Ag NPs during CO2 electrolysis probed in a zero-gap gas-flow configuration""",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This data set corresponds to the journal article ""The capping agent is the key: Structural alterations of Ag NPs during CO2 electrolysis probed in a zero-gap gas-flow configuration""",mds,True,findable,0,0,1,0,0,2022-03-31T18:39:34.000Z,2022-03-31T18:39:36.000Z,cern.zenodo,cern,"Power to value,Carbon dioxide electroreduction,Catalyst degradation,Scanning electron microscopy,Wide-angle X-ray scattering","[{'subject': 'Power to value'}, {'subject': 'Carbon dioxide electroreduction'}, {'subject': 'Catalyst degradation'}, {'subject': 'Scanning electron microscopy'}, {'subject': 'Wide-angle X-ray scattering'}]",,
+10.5281/zenodo.4759515,"Figs. 73-77 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 73-77. Larval terminalias and gills of the North African species of the Protonemura talboti subgroup. 73: Protonemura dakkii sp. n., matured female terminalia; 74: P. dakkii sp. n., matured male terminalia; 75: P. talboti (Nav{s, 1929), matured male terminalia; 76: P. algirica bejaiana ssp. n., male exuviae terminalia; 77: Protonemura dakkii sp. n. gills (ventral views; scale 0.5 mm).",mds,True,findable,0,0,6,0,0,2021-05-14T02:27:47.000Z,2021-05-14T02:27:48.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.6084/m9.figshare.22620895.v1,Additional file 1 of Critically ill severe hypothyroidism: a retrospective multicenter cohort study,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Figure S1. Flowchart of patient selection from participating ICUs. Table S1. Amount of Missing Data for Each Variable Included in the Analysis. Table S2. Characteristics of Severe Hypothyroidism Patients According to the Presence of a Circulatory Failure at ICU Admission. Table S3. Clinical and Biological Features at ICU Admission according to ICU survival. Table S4. Predictive Patient Factors Associated with 6-month Mortality in Critically ill Adults with Severe Hypothyroidism.,mds,True,findable,0,0,0,0,0,2023-04-13T14:55:40.000Z,2023-04-13T14:55:40.000Z,figshare.ars,otjm,"Medicine,Neuroscience,Pharmacology,Immunology,FOS: Clinical medicine,Cancer","[{'subject': 'Medicine'}, {'subject': 'Neuroscience'}, {'subject': 'Pharmacology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}]",['96335 Bytes'],
+10.34847/nkl.4540o25d,"Public space geopositionned ethnographic observations for the sites Quai de plantes, Jardin extraordinaire, Rideau place Graslin, Estrade rafraichissante, Ilot frais and Parc of La Defense",NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,en,Dataset,,"Jeu de données géospatialisées concernant les campagnes d'observation des usages dans le cadre du projet ANR Coolscapes.
+
+Campagnes d'enquête réalisées dans les étés 2020 et 2021 sur six sites : Quai des plantes (Nantes, 2020), Jardin extraordinaire (Nantes, 2020), Place Graslin avec installation Rideau sur la façade de l'opéra (Nantes, 2020), Estrade rafraîchissante sur le parvis de La Défense (Paris, 2021), Ilot frais skycooling sur le parvis de La Défense (Paris, 2021) et Parc de l'Axe de La Défense (Paris, 2021).
+
+Pour chaque site et année d'enquête, il y a 4 fichiers :
+- site_ville_année_moving.gpkg : données correspondants aux flux de déplacements des citadins sur format Geopackage (CRS 2154).
+- site_ville_année_moving.csv : idem sans géolocalisation en format Comma separated values à des fins statiques.
+- site_ville_année_static.gpkg : données correspondants aux lieux d'activités à l'arrêt des citadins sur format Geopackage (CRS 2154).
+- site_ville_année_static.csv : idem sans géolocalisation en format Comma separated values à des fins statiques.
+
+Chaque entité observée est une cellule d'activité, qu'elle soit composée d'une personne ou de plusieurs.
+
+Chaque entité a été renseignée selon les attributs suivant :
+- site : appellation du site
+- survey_id : identification de l'enquête
+- row_id : identification de l'entité
+- obs_type : type d'observation
+- timestamp : horodatage de l'entité en GMT +1 (Paris)
+- date : date
+- time : heure
+- X_lb93 et Y_lb93 : coordonnées spatiales en projection CRS 2154 Lambert-93, ceci est seulement renseigné pour les observations statiques.
+- X_wgs84 et Y_wgs84 : coordonnées spatiales en projection CRS 4326 WGS84, ceci est seulement renseigné pour les observations statiques.
+- row_total : nombre total de personnes intégrant la cellule observée.
+- gender_male : nombre d'hommes
+- gender_female : nombre de femmes
+- age_mean : âge moyen calculé selon le nombre de personnes par tranche d'âge ci-dessous
+- age_0_7 : nombre de personnes avec un âge perçu entre 0 et 7 ans (selon l'enquêteur)
+- age_8_17 : nombre de personnes avec un âge perçu entre 8 et 17 ans (selon l'enquêteur)
+- age_18_34 : nombre de personnes avec un âge perçu entre 18 et 34 ans (selon l'enquêteur)
+- age_35_50 : nombre de personnes avec un âge perçu entre 35 et 50 ans (selon l'enquêteur)
+- age_51_64 : nombre de personnes avec un âge perçu entre 51 et 64 ans (selon l'enquêteur)
+- age_65 : nombre de personnes avec un âge perçu supérieur à 65 ans (selon l'enquêteur)
+- posture : posture du corps prédominante dans la cellule (Tsay and Andersen, 2017)
+- engagement : forme d'interaction avec l'espace et l'effet rafraîchissant supposé dans l'espace
+- clothing : dégrée d'habillement (selon Fanger 1974)
+- exposure : exposition au soleil
+- activity : activité (Tsay and Andersen, 2017)
+- stay_time : temps de séjours perçu par l'enquêteur (les entités en déplacement sont par défaut entre 0 et 2 minutes)
+- geometry : identification des coordonnées de la géométrie spatiale.",api,True,findable,0,0,0,0,0,2023-04-14T15:03:47.000Z,2023-04-14T15:03:47.000Z,inist.humanum,jbru,"observation passive,rafraîchissement urbain,ethnographie urbaine,Espace public,urban ethnography,Public spaces,passive activity observation,urban cooling","[{'lang': 'fr', 'subject': 'observation passive'}, {'lang': 'fr', 'subject': 'rafraîchissement urbain'}, {'lang': 'fr', 'subject': 'ethnographie urbaine'}, {'lang': 'fr', 'subject': 'Espace public'}, {'lang': 'en', 'subject': 'urban ethnography'}, {'lang': 'en', 'subject': 'Public spaces'}, {'lang': 'en', 'subject': 'passive activity observation'}, {'lang': 'en', 'subject': 'urban cooling'}]","['204800 Bytes', '93258 Bytes', '299008 Bytes', '114155 Bytes', '221184 Bytes', '105863 Bytes', '131072 Bytes', '16589 Bytes', '225280 Bytes', '105233 Bytes', '278528 Bytes', '85698 Bytes', '118784 Bytes', '20414 Bytes', '114688 Bytes', '8580 Bytes', '118784 Bytes', '17355 Bytes', '163840 Bytes', '35876 Bytes', '143360 Bytes', '33617 Bytes', '122880 Bytes', '13864 Bytes']","['application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv', 'application/x-sqlite3', 'application/csv']"
+10.5281/zenodo.6674852,Biogenic signals from plastids and their role in chloroplast development,Zenodo,2022,,Dataset,Restricted Access,"<strong>Chloroplast Defective Mutants</strong> The mutant collection was done starting from the Myouga et al (2013) chloroplast database. All the genes in their list were confirmed or removed, depending on the updated and available information in literature.<br> Genes not present in the Myouga database were taken from literature, based on the tables from the two publications from Tadini et al (2020). Additional genes were searched in the literature. Table structure. Detailed information for the mutant characterisation were taken from the main plant databases (TAIR and UniProt) and the corresponding literature.<br> The table is structured in a way to give an insight into the molecular function of the gene and a description of the mutant phenotype (for both if information was available).<br> The worksheet ""Chloroplast Defective Mutants"" contains all the mutants sorted by locus.<br> The worksheet ""Mutants included in Fig.1"" depicts all mutants with impairment in essential processes for chloroplast biogenesis and their phenotype is schematically represented with coloured squares in Figure 1.<br> The last worksheet contains the pie charts, in which the impacts of the main biological functions on the phenotype are visualized. References: -Myouga F, Akiyama K, Tomonaga Y, Kato A, Sato Y, Kobayashi M, Nagata N, Sakurai T, Shinozaki K. The Chloroplast Function Database II: a comprehensive collection of homozygous mutants and their phenotypic/genotypic traits for nuclear-encoded chloroplast proteins. Plant Cell Physiol (2013) http://di.org/0.1093/pcp/pcs171<br> -Tadini L, Jeran N and Pesaresi P, GUN1 and Plastid RNA Metabolism: Learning from Genetics. Cells (2020), 9(10), 2307; https://doi.org/10.3390/cells9102307<br> -Tadini L, Jeran N, Peracchio C, Masiero S, Colombo M and Pesaresi P, The plastid transcription machinery and its coordination with the expression of nuclear genome: Plastid-Encoded Polymerase, Nuclear-Encoded Polymerase and the Genomes Uncoupled 1-mediated retrograde communication. Phil. Trans. R. Soc. (2020) http://doi.org/10.1098/rstb.2019.0399",mds,True,findable,0,0,0,0,0,2022-08-08T07:56:10.000Z,2022-08-08T07:56:10.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5835983,"FIGURE 5. Bulbophyllum truongtamii Vuong, Aver. V.S.Dang.A. Flowering plant. B in Bulbophyllum section Rhytionanthos (Orchidaceae) in Vietnam with description of new taxa and new national record",Zenodo,2022,,Image,Open Access,"FIGURE 5. Bulbophyllum truongtamii Vuong, Aver. V.S.Dang.A. Flowering plant. B. Leaf apex, adaxial and abaxial side. C. Inflorescences. D. Floral bract. E. Flowers, frontal and back views. F. Median sepal, adaxial and abaxial side. G. Lateral sepals, adaxial and abaxial side. H. Petals, adaxial and abaxial side. I. Lip, views from different sides. J. Pedicel, ovary and column with sepals removed (above), and with all tepals removed (below). K. Column, frontal view. L. Column, half side and side views. M. Anther cap, views from different sides. N. Pollinia. Photos by Truong Ba Vuong, correction and design by L. Averyanov and T. Maisak.",mds,True,findable,0,0,2,0,0,2022-01-11T09:00:56.000Z,2022-01-11T09:00:57.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Bulbophyllum","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Bulbophyllum'}]",,
+10.5281/zenodo.6384945,"Past, present and future of chamois science",Zenodo,2022,,Software,"MIT License,Open Access","The chamois <em>Rupicapra</em> spp. is the most abundant mountain ungulate of Europe and the Near East, where it occurs as two species, the Northern chamois <em>R. rupicapra</em> and the Southern chamois <em>R. pyrenaica</em>. Here, we provide a state-of-the-art overview of research trends and the most challenging issues in chamois research and conservation, focusing on taxonomy and systematics, genetics, life history, ecology and behavior, physiology and disease, management, and conservation. Research on <em>Rupicapra</em> has a longstanding history and has contributed substantially to the biological and ecological knowledge of mountain ungulates. Although the number of publications on this genus has markedly increased over the past two decades, major differences persist with respect to knowledge of species and subspecies, with research mostly focusing on the Alpine chamois <em>R. r. rupicapra</em> and, to a lesser extent, the Pyrenean chamois <em>R. p. pyrenaica</em>. In addition, a scarcity of replicate studies of populations of different subspecies and/or geographic areas limits the advancement of chamois science. Since environmental heterogeneity impacts behavioral, physiological and life history traits, understanding the underlying processes would be of great value from both an evolutionary and conservation/management standpoint, especially in the light of ongoing climatic change. Substantial contributions to this challenge may derive from a quantitative assessment of reproductive success, investigation of fine-scale foraging patterns, and a mechanistic understanding of disease outbreak and resilience. Improving conservation status, resolving taxonomic disputes, identifying subspecies hybridization, assessing the impact of hunting and establishing reliable methods of abundance estimation are of primary concern. Despite being one of the most well-known mountain ungulates, substantial field efforts to collect paleontological, behavioral, ecological, morphological, physiological and genetic data on different populations and subspecies are still needed to ensure a successful future for chamois conservation and research.",mds,True,findable,0,0,0,0,0,2022-05-26T17:31:41.000Z,2022-05-26T17:31:42.000Z,cern.zenodo,cern,,,,
+10.57745/izhdpc,Non-volatile electric control of spin-orbit torques in an oxide two-dimensional electron gas,Recherche Data Gouv,2023,,Dataset,,"Electrical measurement dataset of the 5 figures of the article. This includes temperature dependence of the sheet resistance, Hall effect, second harmonic measurements of the spin orbit torques, endurance and remanence as a function of the back gate voltage applied to the 2D electron gas. The ReadMe file explains the data files and the figures.",mds,True,findable,74,5,0,0,0,2023-02-20T16:36:06.000Z,2023-03-09T19:24:01.000Z,rdg.prod,rdg,,,,
+10.6084/m9.figshare.23822166,Dataset key for the replication experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,Key for the dataset for the replication experiment,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:29.000Z,2023-08-02T11:18:30.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['1002 Bytes'],
+10.5281/zenodo.4804617,FIGURE 1 in Review and contribution to the stonefly (Insecta: Plecoptera) fauna of Azerbaijan,Zenodo,2021,,Image,Open Access,FIGURE 1. Recent collecting sites on the map.,mds,True,findable,0,0,0,0,0,2021-05-26T07:54:49.000Z,2021-05-26T07:54:50.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.4753285,Figs. 17-24 in A New Perlodes Species And Its Subspecies From The Balkan Peninsula (Plecoptera: Perlodidae),Zenodo,2012,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 17-24. Perlodes floridus sp. n. habitats. 17. Gornji Mileš, Cijevna River, 65 m, Locus typicus. 18. Qukës Shkumbin, Shkumbin River, 380 m. 19. Borsh, Borsh River, 35 m. 20. Koman Lake, Mertur Stream confluence, 180 m. 21. Agios Georgios, Sperchios River, 365 m. 22. Aetia, Venetikos River, 975 m. 23. Eleftherohori, Venetikos River, 475 m. 24. Zakas, Venetikos River, 700 m.",mds,True,findable,0,0,2,0,0,2021-05-12T18:33:14.000Z,2021-05-12T18:33:15.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Perlodes","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Perlodes'}]",,
+10.5281/zenodo.5682604,"Fig. 41 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"Fig. 41—Distribution map of Protonemura alexidis sp. n., P. lupina sp. n., P. cf. lupina (hybrid), P. risi and P. spinulosa (drawn by Bertrand Launay with ArcGIS version 10.6.0.8321).",mds,True,findable,0,0,0,0,0,2021-11-12T16:00:42.000Z,2021-11-12T16:00:43.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.6303007,Development of a probabilistic ocean modelling system based on NEMO4.0: a contribution to the SEAMLESS project (deliverable 3.3),Zenodo,2022,en,Software,"Creative Commons Attribution 4.0 International,Open Access","This archive contains the technical implementation of a new probabilistic version of NEMO based on version 4.0 (NEMO website: https://www.nemo-ocean.eu). This includes two components: (i) stochastic parameterizations, to simulate uncertainties in the model (using the algorithm described in Brankart et al., 2015), and (ii) ensemble simulations, with several members running simultaneously in parallel within a single executable (and interacting if needed), as introduced in Bessières et al. (2017). The implementation is kept generic, but the stochastic parameterizations are here focused on uncertainties in the ecosystem component, consistently with the objectives of the SEAMLESS project. The code is based on a previous version by Bessières et al. (2017) based on NEMO3.5 (see zenodo link in the reference). As compared to this previous version, the new features here are: (i) the rewriting of the ensemble simulation code (to adjust to the new NEMO parallelization, which is very different in NEMO4.0 as compared to NEMO3.5), (ii) the inclusion and upgrade of the biogeochemical stochastic parameterizations proposed in Garnier al. (2016), and (iii) the stochastic parameterization of location uncertainties, as developed by Leroux et al. (2022) in NEMO3.6, in the context of the IMMERSE project. See the README file included in the archive for more details. This development has been produced in the framework of the SEAMLESS project (https://www.seamlessproject.org/), to provide a code for stochastic parameterizations to generate ensembles in 1D or 3D MFC configurations (deliverable 3.3). Cite as: Popov M., Brankart J.-M., Molines J.-M., Leroux S., Penduff T., Brasseur P. (2022). Development of a probabilistic ocean modelling system based on NEMO4.0: a contribution to the SEAMLESS project (deliverable 3.3), doi:10.5281/zenodo.6303007",mds,True,findable,0,0,0,0,0,2022-02-28T10:35:04.000Z,2022-02-28T10:35:06.000Z,cern.zenodo,cern,"SEAMLESS project,ocean model,Nemo-PISCES,stochastic parameterizations,ensemble simulations","[{'subject': 'SEAMLESS project'}, {'subject': 'ocean model'}, {'subject': 'Nemo-PISCES'}, {'subject': 'stochastic parameterizations'}, {'subject': 'ensemble simulations'}]",,
+10.5281/zenodo.5062314,"Data for paper ""Parametric analyses of attack-fault trees""",Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is the dataset for paper ""Parametric analyses of attack-fault trees"" published in the proceedings of the 19th International Conference on Application of Concurrency to System Design (ACSD 2019).",mds,True,findable,0,0,0,0,0,2021-07-02T16:08:16.000Z,2021-07-02T16:08:17.000Z,cern.zenodo,cern,"attack trees,model checking,parametric timed model checking,timed automata,parametric timed automata,IMITATOR","[{'subject': 'attack trees'}, {'subject': 'model checking'}, {'subject': 'parametric timed model checking'}, {'subject': 'timed automata'}, {'subject': 'parametric timed automata'}, {'subject': 'IMITATOR'}]",,
+10.5281/zenodo.7804590,WriteVTK.jl: a Julia package for writing VTK XML files,Zenodo,2023,,Software,"MIT License,Open Access",Main changes Transfer to JuliaVTK organisation. Move some definitions to VTKBase.jl package. Support FillArrays 1.0.,mds,True,findable,0,0,0,0,0,2023-04-06T07:32:38.000Z,2023-04-06T07:32:38.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.m0cfxpp06,Generalist plants are more competitive and more functionally similar to each other than specialist plants: insights from network analyses,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Aim: Ecological specialization is a property of species associated with the variety of contexts they occupy. Identifying the mechanisms influencing specialization is critical to understand species coexistence and biodiversity patterns. However, the functional attributes leading to specialization are still unknown. Similarly, there is contrasting evidence between the level of specialization and local abundance of species. We ask whether plant specialist and generalist species (i) are associated with distinct functional profiles, using core plant functional traits and strategies, (ii) show comparable functional variation, and how (iii) they perform at local scale. Location: France, Countrywide scale. Taxon: Herbaceous plants. Results: We identified five major modules in the bipartite network, related to different environmental conditions and composed of species displaying different functional attributes. Species that were more specialist were less competitive, had smaller stature, higher stress-tolerance and stronger resource conservation, while generalist species were taller. Generalists were also more similar among themselves than specialists. In addition, specialist species had higher local abundances and occurred in communities with plants of similar height. Main conclusions: We found distinctive functional signatures of specialist and generalist species in grassland communities across diverse environments at regional and community scales. Network metrics can benefit community ecology to test classical macro-ecological hypotheses by identifying distinct ecological unit at large scale and quantifying the links developed by species.",mds,True,findable,176,10,0,0,0,2020-03-07T01:04:08.000Z,2020-03-07T01:04:10.000Z,dryad.dryad,dryad,"bipartite network,generalist species,Specialist species","[{'subject': 'bipartite network'}, {'subject': 'generalist species'}, {'subject': 'Specialist species'}]",['390825783 bytes'],
+10.5061/dryad.3j9kd51j5,Live imaging and biophysical modeling support a button-based mechanism of somatic homolog pairing in Drosophila,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"3D eukaryotic genome organization provides the structural basis for gene regulation. In Drosophila melanogaster, genome folding is characterized by somatic homolog pairing, where homologous chromosomes are intimately paired from end to end; however, how homologs identify one another and pair has remained mysterious. Recently, this process has been proposed to be driven by specifically interacting 'buttons' encoded along chromosomes. Here, we turned this hypothesis into a quantitative biophysical model to demonstrate that a button-based mechanism can lead to chromosome-wide pairing. We tested our model using live-imaging measurements of chromosomal loci tagged with the MS2 and PP7 nascent RNA labeling systems. We show solid agreement between model predictions and experiments in the pairing dynamics of individual homologous loci. Our results strongly support a button-based mechanism of somatic homolog pairing in Drosophila and provide a theoretical framework for revealing the molecular identity and regulation of buttons.",mds,True,findable,141,7,1,1,0,2021-07-07T20:44:30.000Z,2021-07-07T20:44:31.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['1142294 bytes'],
+10.5061/dryad.qrfj6q5hv,Unique and shared effects of local and catchment predictors over distribution of hyporheic organisms: does the valley rule the stream?,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"This dataset describe the distribution of two hyporheic crustacean taxa (Bogidiellidae, Amphipoda and Anthuridae, Isopoda) in streams of New Caledonia. We sampled the two taxa at 228 sites. At each site, we quantified nine local predictors related to habitat area and stability, sediment metabolism and water origin, and eight catchment predictors related to geology, area, primary productivity, land use and specific discharge.",mds,True,findable,131,6,0,1,0,2022-02-17T19:46:34.000Z,2022-02-17T19:46:36.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences,Species distribution model,spatial scale,hyporheic zone,subterranean crustaceans,New Caledonia,Bogidiellidae,Amphipoda,Anthuridae,Isopoda,local,catchment","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Species distribution model'}, {'subject': 'spatial scale'}, {'subject': 'hyporheic zone'}, {'subject': 'subterranean crustaceans'}, {'subject': 'New Caledonia', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Bogidiellidae'}, {'subject': 'Amphipoda'}, {'subject': 'Anthuridae'}, {'subject': 'Isopoda'}, {'subject': 'local'}, {'subject': 'catchment'}]",['64550 bytes'],
+10.5281/zenodo.7649167,"Polarization dataset - Reflection, emission, and polarization properties of surfaces made of hyperfine grains, and implications for the nature of primitive small bodies",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This data are relative to the polarization measurements of the paper ""Reflection, emission, and polarization properties of surfaces made of hyperfine grains, and implications for the nature of primitive small bodies"" The dataset consists in 8 .txt files that represent the polarization measurements of mixtures of FeS and Olivine (ol) with different mass ratios. In the name of each file it is specified the mass percentage of the two components respect with the total mass of the sample (eg. data_ol_FeS_10-90_530.txt is the sample composed by 10% olivine and 90% FeS, measured at 530 nm). In each file, the data are organized in the following columns: #phase_angles[°] #Q/I #U/I #V/I #DOLP #DC #delta_Q/I #delta_U/I #delta_V/I #delta_DOLP #delta_dc ""delta"" refers to the standard deviation of the measurement upon rotation of the sample on the azimuthal axis. <br>",mds,True,findable,0,0,0,0,0,2023-02-17T11:56:25.000Z,2023-02-17T11:56:47.000Z,cern.zenodo,cern,"polarization,dust,asteroids,remote sensing","[{'subject': 'polarization'}, {'subject': 'dust'}, {'subject': 'asteroids'}, {'subject': 'remote sensing'}]",,
+10.5281/zenodo.8010223,Simulation-based Validation for Autonomous Driving Systems,Zenodo,2023,,Software,"Creative Commons Attribution 4.0 International,Open Access","The artifact for the paper ""Simulation-based Validation for Autonomous Driving Systems"" published on ISSTA 2023.",mds,True,findable,0,0,0,0,0,2023-06-06T12:30:44.000Z,2023-06-06T12:30:45.000Z,cern.zenodo,cern,,,,
+10.34847/nkl.ae94a74k,"Taciti et C. Velleii Paterculi scripta quae exstant; recognita, emaculata. Additique commentarii copiosissimi et notae non antea editae Paris e typographia Petri Chevalier, in monte diui Hilarii - II-0484",NAKALA - https://nakala.fr (Huma-Num - CNRS),2020,,Image,,,api,True,findable,0,0,0,0,0,2023-01-16T15:46:03.000Z,2023-01-16T15:46:03.000Z,inist.humanum,jbru,,,['52170234 Bytes'],['image/tiff']
+10.26302/sshade/experiment_op_20200212_001,Vis-NIR bidirectional reflection spectra of several ammonium salts mixed with graphite powder at 296 K,SSHADE/GhoSST (OSUG Data Center),2020,en,Dataset,"Any use of downloaded SSHADE data in a scientific or technical paper or a presentation is free but you should cite both SSHADE and the used data in the text ( 'first author' et al., year) with its full reference (with its DOI) in the main reference section of the paper (or in a special 'data citation' section) and, when available, the original paper(s) presenting the data.","Mixtures of graphite powder (<20 µm) and ammonium (NH4+) salts (chloride, sulfate, formate) were prepared by mixing manually these constituents in a mortar. Reflectance spectra (from 0.4 to 4 µm) of these mixtures were measured at 296 K under ambient air.",mds,True,findable,0,0,0,0,0,2020-02-12T11:12:11.000Z,2020-02-12T11:12:11.000Z,inist.sshade,mgeg,"mineral,commercial,elemental solid,Graphite,sulfate,Ammonium sulfate,organic salt,Ammonium formate,chloride,Ammonium chloride,laboratory measurement,bidirectional reflection,macroscopic,Vis,Visible,NIR,Near-Infrared,reflectance factor","[{'subject': 'mineral'}, {'subject': 'commercial'}, {'subject': 'elemental solid'}, {'subject': 'Graphite'}, {'subject': 'sulfate'}, {'subject': 'Ammonium sulfate'}, {'subject': 'organic salt'}, {'subject': 'Ammonium formate'}, {'subject': 'chloride'}, {'subject': 'Ammonium chloride'}, {'subject': 'laboratory measurement'}, {'subject': 'bidirectional reflection'}, {'subject': 'macroscopic'}, {'subject': 'Vis'}, {'subject': 'Visible'}, {'subject': 'NIR'}, {'subject': 'Near-Infrared'}, {'subject': 'reflectance factor'}]",['4 spectra'],['ASCII']
+10.34847/nkl.5bb02187,Bulletin franco-italien 1912 n°6 novembre - décembre,NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Book,,"1912/11 (A4,N6)-1912/12.",api,True,findable,0,0,0,0,0,2022-06-29T10:46:35.000Z,2022-06-29T10:46:35.000Z,inist.humanum,jbru,"Etudes italiennes,Etudes italiennes","[{'lang': 'fr', 'subject': 'Etudes italiennes'}, {'subject': 'Etudes italiennes'}]","['6036554 Bytes', '21797230 Bytes', '21498754 Bytes', '21658336 Bytes', '21954568 Bytes', '21816616 Bytes', '21709840 Bytes', '21664144 Bytes', '21657022 Bytes', '21577279 Bytes', '21667990 Bytes', '21719686 Bytes', '21847000 Bytes', '21846484 Bytes', '21619864 Bytes', '21711109 Bytes', '21842131 Bytes']","['application/pdf', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff']"
+10.5281/zenodo.3819313,Programmers manual FlexGripPlus SASS SM 1.0,Zenodo,2020,,Other,"Creative Commons Attribution 4.0 International,Open Access",This document describes the op-code of the assembly language SASS of the G80 architecture used in the FlexGripPlus model. Every instruction is compatible with the CUDA Programming environment under the SM_1.0,mds,True,findable,0,0,0,0,0,2020-05-10T13:51:41.000Z,2020-05-10T13:51:42.000Z,cern.zenodo,cern,"SASS, GPGPU, G80, FlexGripPlus, Assembly Language","[{'subject': 'SASS, GPGPU, G80, FlexGripPlus, Assembly Language'}]",,
+10.5281/zenodo.3613951,Winter snow depths for initializing a glacio-hydrological model in high mountain Chile,Zenodo,2020,,Dataset,Creative Commons Attribution 4.0 International,"The following dataset consists of the forcings, initial conditions, model grids and parameters used to run the TOPKAPI-ETH model (Finger et al., 2011; Ragettli and Pellicciotti, 2012) for the Rio Yeso catchment of central Chile (33.44°S, 69.93°W - Burger et al., 2018). The data and model grids were used to investigate the importance of accurate snow depth maps for initialising the physically-oriented model in a high elevation catchment - For a manuscript submitted to Water Resources Research (WRR) - January 2020.Â
+
+
+Â
+
+
+Data and file repository for the submitted article:
+%-------------------------------------------------------------
+%-------------------------------------------------------------
+
+
+Â On the utility of optical satellite winter snow depths for modelling the
+Â glacio-hydrological behaviour of a high elevation, Andean catchment.
+
+
+Thomas E. Shaw1, Alexis Caro1,2, Pablo Mendoza3, Ãlvaro Ayala4, Francesca Pellicciotti5,6, Simon Gascoin7, Â James McPhee1,3
+
+
+1 Advanced Mining Technology Center, Universidad de Chile, Santiago, Chile
+2 Univ. Grenoble Alpes, CNRS, IRD, Grenoble-INP, Institut des Géosciences de l’Environnement (IGE, UMR 5001), Grenoble, France
+3 Department of Civil Engineering, Universidad de Chile, Santiago, Chile
+4 Centro de Estudios Avanzados en Zonas Ãridas (CEAZA), La Serena, Chile
+5 Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
+6 Department of Geography, Northumbria University, Newcastle, UK
+7 CESBIO, Université de Toulouse, CNES/CNRS/INRA/IRD/UPS, Toulouse, France
+
+
+%-------------------------------------------------------------
+%-------------------------------------------------------------
+The following sub-folders are separated into forcings, grids, initial model conditions, model files and parameters.
+
+
+This file describes briefly the contents of each sub-folder.
+
+
+%-------------------------------------------------------------
+FORCINGS:
+
+
+CloudCover_TPK.csv - A timeseries of hourly cloud cover fraction (-) derived NASA POWER archives.
+Discharge_TPK.csv - A timeseries of hourly discharge (m3 s-1) from the outlet station F_TdP.
+Master_Data_TPK.mat - a Matlab structure (written in version 2017a) for all data availble to the catchment for the considered model period.
+Precipitation_TPK.csv - A timeseries of hourly precipitation (mm/hr) from AWS TdP.
+Temperature_TPK.csv - A timeseries of hourly temperature (degC) from AWS TdP.Â
+TemperatureGradient_TPK.csv - A timeseries of calibrated temperature gradients based upon forcing from AWS TdP.
+
+
+%-------------------------------------------------------------
+GRIDS:
+
+
+42 ascii files for various grids (primary or secondary) use to derive the .TES file (see TOPKAPI-ETH sub-folder) for running the model.
+Associated projection (.prj) files are given.
+Naming convention is provided in the manual (see TOPKAPI-ETH sub-folder) except:
+Â Â Â rdy_SoilDepth.asc - An adjusted top layer soil depth map based upon Ragettli et al. (2012).
+Â Â Â rdy_debris_v.asc - A debris thickness map for Piramde Glacier and the tongue of Bello Glacier. Values adjusted slightly from Ayala et al. (2016) to account for areas that are not debris, but bedrock (Bello Glacier).
+
+
+%-------------------------------------------------------------
+INITIAL_CONDITIONS:
+
+
+Sub-folder 'Albedo':Â
+   Albedo_Pleiades.asc - An albedo map derived from the model spin up and limited to the snow-covered pixels of the Pléiades snow depth map.
+Sub-folder 'Snow':
+   XXX_snow_mmwe.asc - A snow water equivalent map (mm w.e.) given by the initialisation method 'XXX' (Pléiades, TOPO or DBSM). TPK is derived solely from the model spin up (an input grid not required).Â
+Â Â Â XXXeq_snow_mmew.asc - As above, though considering the equal means approach described in the manuscript. TPK included here.
+Sub-Folder 'SpinUp_State':
+Â Â Â 201709040000.stt - The system state file that contains information on the equiblibrium state of catchment (as read by the model upon initialisation). Running the model with a spinup shuld call upon this file within the command prompt.
+
+
+
+%-------------------------------------------------------------
+PARAMETERS:
+
+
+Sub-folder 'Calibration'
+Â Â Â TPK_ParameterAllocation - A Matlab script for the establishing the Monte Carlo parameter simulation and running the model n times. The current script is considered for soil parameters.
+Sub-folder 'Sensitivity'
+Â Â Â TPK_Sensivity_Analysis - A Matlab script for establishing the upper and lower boundaries of parameter/forcing sensitivities for a one-at-a-time analysis.
+
+
+Â
+
+
+%-------------------------------------------------------------
+RESULTS:
+
+
+Model_Output_Comparison.mat - A matlab file with output grids and vectors for model intercomparisons (i.e. Pléiades (Pléiades-Uncertainty and Pléiades+Uncertainty), TOPO, TPK, DBSM + equal means equivalents). Files are:
+Â Â Â All_S - Daily snow mass balance grids (mm w.e.)
+Â Â Â Bias_Month - Monthly bias (row) of modelled vs measured streamflow at F_aP site for each model run (column).
+Â Â Â Date_Daily - Numeric date of daily grids
+Â Â Â DateTPK - Numeric date of hourly model simulations
+Â Â Â Gla_Map - Daily cumulative glacier modelled mass balance grids (mm w.e.) for x,y,t,MOD - such that the 4th dimension is the model simulation
+Â Â Â GMB_Bello - Cumulative modelled mass balance (mm w.e.) of Bello Glacier AWS grid cell
+Â Â Â GMB_Piramide - Cumulative modelled mass balance (mm w.e.) of Piramide Glacier AWS grid cell
+Â Â Â GMB_Yeso - Cumulative mass modelled balance (mm w.e.) of Yeso Glacier AWS grid cell
+Â Â Â KGE_Month - KGE values per month (row) and for each model run (column)
+Â Â Â M3AP - Measured streamflow at F_aP
+Â Â Â M3TP - Measured streamflow at F_TdP
+Â Â Â MeltG_Avg_all - Mean hourly ALL-glacier melt rate (mm w.e./hr) for each model run (column)
+Â Â Â MeltS_Avg_all - Mean hourly catchment-wide melt rate (mm w.e./hr) for each model run (column)
+Â Â Â MOD_SnowCC - Daily MODIS snow cover fraction
+Â Â Â Model_Name - .... well, its the name of the model run :=)
+Â Â Â MODIS_SLE - The calculated Snow Line Elevation (m a.s.l.) for each daily MODIS scene
+Â Â Â PlanetSLE - As above, but for PlanetScope images (17 days total)
+Â Â Â Planet_SnowObs - The numeric dates of the equivalent PlanetSLE data
+Â Â Â Q_Mod_aP - The modelled hourly streamflow at F_aP
+Â Â Â Q_Mod_TdP - The modelled hourly streamflow at F_TdP
+Â Â Â Q_Prc_Month - The percentage difference in monthly (row) modelled-measured streamflow by model run (column)
+Â Â Â R_Month - Correlation values per month (row) and for each model run (column)
+Â Â Â RelVar_Month - Relative variance per month (row) and for each model run (column)
+Â Â Â Snow_Map - Daily snow water equivalent grids (mm w.e.) for x,y,t,MOD - such that the 4th dimension is the model simulation
+Â Â Â SnowCC - The hourly modelled snow cover fraction for the catchment for each model run (column)
+Â Â Â TPKSLE - The daily modelled TOPKAPI-ETH model SLE from each model run (column)
+
+
+Â
+
+
+%-------------------------------------------------------------
+TOPKAPI-ETH:
+
+
+FIUME - A generic file type that is called by the model to ID the name of the study site. I this case 'rdy'.
+rdy.TES - A vectorised file of all grids required by the model to run.
+rdy.TPK - The TPK parameter and command file. This is adjusted to change input parameters and forcing files etc. The current file is the optimised version for this catchment.
+TManual_Aug2013.pdf - A PDF instruction file (semi-complete) for the model written by Stefan Rimkus (2013). The naming conventions and grid names are given here.
+
+
+Â
+
+
+Â
+
+
+CITED MATERIAL REGARDING THE MODEL
+
+
+Burger, F., Ayala, A., Farias, D., Shaw, T. E., Macdonell, S., Brock, B., McPhee, J., Pellicciotti, F. (2018a). Interannual variability in glacier contribution to runoff from a high †elevation Andean catchment: understanding the role of debris cover in glacier hydrology. Hydrological Processes, SI-Latin(January), 1–16. https://doi.org/10.1002/hyp.13354
+
+
+Finger, D., Pellicciotti, F., Konz, M., Rimkus, S., & Burlando, P. (2011). The value of glacier mass balance, satellite snow cover images, and hourly discharge for improving the performance of a physically based distributed hydrological model. Water Resources Research, 47(7), 1–14. https://doi.org/10.1029/2010WR009824
+
+
+Ragettli, S., & Pellicciotti, F. (2012). Calibration of a physically based, spatially distributed hydrological model in a glacierized basin: On the use of knowledge from glaciometeorological processes to constrain model parameters. Water Resources Research, 48(3), n/a-n/a. https://doi.org/10.1029/2011WR010559
+
+
+Â ",mds,True,findable,0,0,0,0,0,2020-01-20T20:55:53.000Z,2020-01-20T20:55:54.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5242829,German DBnary archive in original Lemon format,Zenodo,2021,de,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from German language edition, ranging from 30th August 2012 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T07:50:29.000Z,2021-08-24T07:50:30.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.6962616,On the formulation and implementation of extrinsic cohesive zone models with contact - codes,Zenodo,2022,en,Software,"Apache License 2.0,Open Access","This data set contains the codes necessary to run the simulations described in the paper ""On the formulation and implementation of extrinsic cohesive zone models with contact"", published in Computer Methods in Applied Mechanics and Engineering: https://doi.org/10.1016/j.cma.2022.115545 The codes are also available in a GitHub repository (which is the recommended method of obtaining them): https://github.com/nickcollins-craft/On-the-formulation-and-implementation-of-extrinsic-cohesive-zone-models-with-contact<br> <br> In order to run the codes, the user first requires a working installation of Python 3 (the codes were run on Python 3.8.13). We strongly recommend using Anaconda to manage the installation: https://www.anaconda.com/products/distribution<br> Then, the user must install meshio (the codes were run on meshio 5.3.0): https://github.com/nschloe/meshio<br> Separately, the user must also install gmsh (the codes were run on Gmsh 4.8.1): https://gmsh.info/<br> Finally, the user must also install Siconos (the codes were run on Siconos 4.4.0): https://nonsmooth.gricad-pages.univ-grenoble-alpes.fr/siconos/<br> <br> Then, those codes that call the Siconos software can be run by typing ""siconos <name_of_code.py>"" and pressing enter while in the working directory. All other codes can be run by typing ""python <name_of_code.py>"" and pressing enter while in the working directory.<br> <br> Users of this software should also cite each software listed above where appropriate.<br> <br> Two of the codes (""DCB_mesh_and_end_plot.py"" and ""Rhombus_mesh_and_end_plot.py"") also require images that are included in the related repository containing the output data: https://doi.org/10.5281/zenodo.6939154<br> <br> Contact: nicholas[dot]collins-craft[at]inria[dot]fr",mds,True,findable,0,0,1,1,0,2022-08-04T12:30:44.000Z,2022-08-04T12:30:44.000Z,cern.zenodo,cern,"Extrinsic cohesive zone,Finite element analysis,Dynamic crack propagation,Non-smooth mechanics","[{'subject': 'Extrinsic cohesive zone'}, {'subject': 'Finite element analysis'}, {'subject': 'Dynamic crack propagation'}, {'subject': 'Non-smooth mechanics'}]",,
+10.5281/zenodo.7507112,Adversarial Reachability for Program-level Security Analysis (artifact),Zenodo,2023,en,Software,"GNU General Public License v2.0 or later,Open Access","Many program analysis tools and techniques have been developed to assess program vulnerability. Yet, they are based on the standard concept of reachability and represent an attacker able to craft smart legitimate input, while in practice attackers can be much more powerful, using for instance micro-architectural exploits or fault injection methods.<br> We introduce adversarial reachability, a framework allowing to reason about such advanced attackers and check whether a system is vulnerable or immune to a particular attacker. As equipping the attacker with new capacities significantly increases the state space of the program under analysis, we present a new symbolic exploration algorithm, namely adversarial symbolic execution, injecting faults in a forkless manner to prevent path explosion, together with optimizations dedicated to reduce the number of injections to consider while keeping the same attacker power. Experiments on representative benchmarks from fault injection show that our method significantly reduces the number of adversarial paths to explore, allowing to scale up to 10 faults where prior work timeout for 3 faults. In addition, we analyze the well-tested WooKey's bootloader, and demonstrate the ability of our analysis to find attacks and evaluate countermeasures in real-life security scenarios. We were especially able to find a new attack on an incomplete patch.",mds,True,findable,0,0,0,0,0,2023-01-05T17:41:05.000Z,2023-01-05T17:41:05.000Z,cern.zenodo,cern,"Program analysis,Attacker model,Fault injection,Symbolic execution","[{'subject': 'Program analysis'}, {'subject': 'Attacker model'}, {'subject': 'Fault injection'}, {'subject': 'Symbolic execution'}]",,
+10.5061/dryad.hb3b5,Data from: Mutation rate dynamics in a bacterial population reflect tension between adaptation and genetic load,Dryad,2013,en,Dataset,Creative Commons Zero v1.0 Universal,"Mutations are the ultimate source of heritable variation for evolution. Understanding how mutation rates themselves evolve is thus essential for quantitatively understanding many evolutionary processes. According to theory, mutation rates should be minimized for well-adapted populations living in stable environments, whereas hypermutators may evolve if conditions change. However, the long-term fate of hypermutators is unknown. Using a phylogenomic approach, we found that an adapting Escherichia coli population that first evolved a mutT hypermutator phenotype was later invaded by two independent lineages with mutY mutations that reduced genome-wide mutation rates. Applying neutral theory to synonymous substitutions, we dated the emergence of these mutations and inferred that the mutT mutation increased the point-mutation rate by ~150-fold, while the mutY mutations reduced the rate by ~40-60%, with a corresponding decrease in the genetic load. Thus, the long-term fate of the hypermutators was governed by the selective advantage arising from a reduced mutation rate as the potential for further adaptation declined.",mds,True,findable,607,42,1,1,0,2012-11-28T15:51:22.000Z,2012-11-28T15:51:22.000Z,dryad.dryad,dryad,hypermutators,[{'subject': 'hypermutators'}],['2323548 bytes'],
+10.5281/zenodo.3550192,Rockfall localization routine,Zenodo,2019,,Software,Open Access,Algorithm for the localization of rockfalls by means of recorded seismic signals using simulated impulse responses.,mds,True,findable,2,0,0,0,0,2019-11-21T21:08:04.000Z,2019-11-21T21:08:04.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.1289969,Data Sets For The Simulated Ampi (Sampi) Load Balancing Simulation Workflow And Ondes3D Performance Analysis (Companion To Ccpe Paper),Zenodo,2018,en,Dataset,"Creative Commons Attribution Share-Alike 4.0,Open Access","This package contains data sets and scripts (in an Org-mode file) related to our submission to the journal ""Concurrency and Computation: Practice and Experience"", under the title <em>""Performance Modeling of a Geophysics Application to Accelerate the Tuning of Over-decomposition Parameters through Simulation""</em>.",,True,findable,3,0,0,0,0,2018-06-14T22:08:54.000Z,2018-06-14T22:08:55.000Z,cern.zenodo,cern,"Simulation,Load Balancing,Performance Analysis,Finite-Differences Method,Simgrid,MPI,Ondes3d,Iterative parallel application","[{'subject': 'Simulation'}, {'subject': 'Load Balancing'}, {'subject': 'Performance Analysis'}, {'subject': 'Finite-Differences Method'}, {'subject': 'Simgrid'}, {'subject': 'MPI'}, {'subject': 'Ondes3d'}, {'subject': 'Iterative parallel application'}]",,
+10.5281/zenodo.10020953,robertxa/Lutiniere: Final data,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,Données topographiques du système d'Huretières et de la grotte de la Lutinière,api,True,findable,0,0,0,0,0,2023-10-19T08:39:08.000Z,2023-10-19T08:39:08.000Z,cern.zenodo,cern,,,,
+10.48550/arxiv.2310.14831,Formation of interstellar complex organic molecules on water-rich ices triggered by atomic carbon freezing,arXiv,2023,,Preprint,Creative Commons Attribution Non Commercial Share Alike 4.0 International,"The reactivity of interstellar carbon atoms (C) on the water-dominated ices is one of the possible ways to form interstellar complex organic molecules (iCOMs). In this work, we report a quantum chemical study of the coupling reaction of C ($^3$P) with an icy water molecule, alongside possible subsequent reactions with the most abundant closed shell frozen species (NH$_3$, CO, CO$_2$ and H$_2$), atoms (H, N and O), and molecular radicals (OH, NH$_2$ and CH$_3$). We found that C spontaneously reacts with the water molecule, resulting in the formation of $^3$C-OH$_2$, a highly reactive species due to its triplet electronic state. While reactions with the closed-shell species do not show any reactivity, reactions with N and O form CN and CO, respectively, the latter ending up into methanol upon subsequent hydrogenation. The reactions with OH, CH$_3$ and NH$_2$ form methanediol, ethanol and methanimine, respectively, upon subsequent hydrogenation. We also propose an explanation for methane formation, observed in experiments through H additions to C in the presence of ices. The astrochemical implications of this work are: i) atomic C on water ice is locked into $^3$C-OH$_2$, making difficult the reactivity of bare C atoms on the icy surfaces, contrary to what is assumed in astrochemical current models; and ii) the extraordinary reactivity of $^3$C-OH$_2$ provides new routes towards the formation of iCOMs in a non-energetic way, in particular ethanol, mother of other iCOMs once in the gas-phase.",mds,True,findable,0,0,0,0,0,2023-10-24T03:25:43.000Z,2023-10-24T03:25:44.000Z,arxiv.content,arxiv,"Astrophysics of Galaxies (astro-ph.GA),Chemical Physics (physics.chem-ph),FOS: Physical sciences,FOS: Physical sciences","[{'lang': 'en', 'subject': 'Astrophysics of Galaxies (astro-ph.GA)', 'subjectScheme': 'arXiv'}, {'lang': 'en', 'subject': 'Chemical Physics (physics.chem-ph)', 'subjectScheme': 'arXiv'}, {'subject': 'FOS: Physical sciences', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'FOS: Physical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.6084/m9.figshare.23575360,Additional file 1 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Composition of growth media and phylogenetic characterization. The data provided describe the both growth media and the phylogenetic affiliation of the pure strains which were isolated from the FR bacterial community. (DOC 76 KB),mds,True,findable,0,0,0,0,0,2023-06-25T03:11:45.000Z,2023-06-25T03:11:45.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['77312 Bytes'],
+10.5281/zenodo.5508669,Effects of population density on static allometry between horn length and body mass in mountain ungulates,Zenodo,2021,,Software,"MIT License,Open Access","Little is known about the effects of environmental variation on allometric relationships of condition-dependent traits, especially in wild populations. We estimated sex-specific static allometry between horn length and body mass in four populations of mountain ungulates that experienced periods of contrasting density over the course of the study. These species displayed contrasting sexual dimorphism in horn size; high dimorphism in <i>Capra ibex</i> and <i>Ovis canadensis</i> and low dimorphism in <i>Rupicapra rupicapra</i> and <i>Oreamnos americanus</i>. The effects of density on static allometric slopes were weak and inconsistent while allometric intercepts were generally lower at high density, especially in males from species with high sexual dimorphism in horn length. These results confirm that static allometric slopes are more canalized than allometric intercepts against environmental variation induced by changes in population density, particularly when traits appear more costly to produce and maintain.",mds,True,findable,0,0,0,0,0,2021-09-15T18:15:53.000Z,2021-09-15T18:15:54.000Z,cern.zenodo,cern,"Density dependence,Alpine ungulates,horn","[{'subject': 'Density dependence'}, {'subject': 'Alpine ungulates'}, {'subject': 'horn'}]",,
+10.6084/m9.figshare.23575375.v1,Additional file 6 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 5,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:53.000Z,2023-06-25T03:11:53.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['67584 Bytes'],
+10.34847/nkl.2c0fj3ai,"Bande-annonce de la production Ciné-concert ""La mécanique des roches""",NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,fr,Audiovisual,,"C'est une histoire de crépitements de feux dans la nuit, une histoire d'usines et de corps cassés, de délocalisations et de filiations. Au début du XXe siècle, la vallée de la Romanche se développa massivement avec la construction de nombreuses centrales électriques et d'usines d'électrométallurgie. Les ouvriers venaient de partout pour offrir leur force de travail. Puis, en deux générations, les fermetures se sont enchaînées. Aujourd'hui, le futur de la dernière usine est incertain. C'est un récit du travail et de la condition ouvrière pris entre les falaises abruptes des montagnes, l'histoire d'une jeunesse face à son avenir.
+
+Cinéma-concert. Un film de Jérémie Lamouroux. Composition & interprétation musicale de Martin Debisschop. Création co-produite avec l'Heure Bleue, scène régionale de Spectacle Vivant, La scène Nationale Image Le lux, la Ville de Grenoble, le département de l'Isère, la Commune de Livet-et-Gavet et la communauté de communes de l'Oisans. Mai 2021. 70 min.
+
+Programme : Région & DRAC Auvergne-Rhône-Alpes - Programme ""Mémoires du XXe et XXIe siècles"".
+
+Autres liens :
+
+Vidéo disponible sur :
+https://vimeo.com/683223681
+Enregistrements sonores disponibles sur :
+https://soundcloud.com/user-145016407/sets/la-mecanique-des-roches""",api,True,findable,0,0,0,0,0,2023-10-03T09:01:13.000Z,2023-10-03T09:01:13.000Z,inist.humanum,jbru,"""Mémoires des lieux,histoire orale,histoires de vie,enquêtes de terrain (ethnologie),Désindustrialisation,Patrimoine industriel,Pollution de l'air,Montagnes – aménagement,Énergie hydraulique,Rives – aménagement,Romanche, Vallée de la (France),Keller, Charles Albert (1874-1940 , Ingénieur A&M),patrimoine immatériel,Conditions de travail,classe ouvrière","[{'lang': 'fr', 'subject': '""Mémoires des lieux'}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'histoires de vie'}, {'lang': 'fr', 'subject': 'enquêtes de terrain (ethnologie)'}, {'lang': 'fr', 'subject': 'Désindustrialisation'}, {'lang': 'fr', 'subject': 'Patrimoine industriel'}, {'lang': 'fr', 'subject': ""Pollution de l'air""}, {'lang': 'fr', 'subject': 'Montagnes – aménagement'}, {'lang': 'fr', 'subject': 'Énergie hydraulique'}, {'lang': 'fr', 'subject': 'Rives – aménagement'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'Keller, Charles Albert (1874-1940 , Ingénieur A&M)'}, {'lang': 'fr', 'subject': 'patrimoine immatériel'}, {'lang': 'fr', 'subject': 'Conditions de travail'}, {'lang': 'fr', 'subject': 'classe ouvrière'}]",['19334394 Bytes'],['video/mp4']
+10.5281/zenodo.10037954,FIG. 1 in Passiflora tinifolia Juss. (Passiflora subgenus Passiflora): resurrection and synonymies,Zenodo,2023,,Image,Creative Commons Attribution 4.0 International,FIG. 1. — Iconography of P. tinifolia Juss. from the original description by Jussieu (1805).,api,True,findable,0,0,0,0,0,2023-10-24T17:26:28.000Z,2023-10-24T17:26:28.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5061/dryad.9g5fp,Data from: Cophylogeny Reconstruction via an Approximate Bayesian Computation,Dryad,2014,en,Dataset,Creative Commons Zero v1.0 Universal,"Despite an increasingly vast literature on cophylogenetic reconstructions for studying host-parasite associations, understanding the common evolutionary history of such systems remains a problem that is far from being solved. Most algorithms for host-parasite reconciliation use an event-based model, where the events include in general (a subset of) cospeciation, duplication, loss, and host switch. All known parsimonious event-based methods then assign a cost to each type of event in order to find a reconstruction of minimum cost. The main problem with this approach is that the cost of the events strongly influences the reconciliation obtained. Some earlier approaches attempt to avoid this problem by finding a Pareto set of solutions and hence by considering event costs under some minimisation constraints. To deal with this problem, we developed an algorithm, called \Coala, for estimating the frequency of the events based on an approximate Bayesian computation approach. The benefits of this method are twofold: (1) it provides more confidence in the set of costs to be used in a reconciliation, and (2) it allows estimation of the frequency of the events in cases where the dataset consists of trees with a large number of taxa. We evaluate our method on simulated and on biological datasets. We show that in both cases, for the same pair of host and parasite trees, different sets of frequencies for the events lead to equally probable solutions. Moreover, often these solutions differ greatly in terms of the number of inferred events. It appears crucial to take this into account before attempting any further biological interpretation of such reconciliations. More generally, we also show that the set of frequencies can vary widely depending on the input host and parasite trees. Indiscriminately applying a standard vector of costs may thus not be a good strategy.",mds,True,findable,404,101,1,1,0,2014-12-26T20:33:05.000Z,2014-12-26T20:33:07.000Z,dryad.dryad,dryad,"host/parasite systems,likelihood-free inference,cophylogeny","[{'subject': 'host/parasite systems'}, {'subject': 'likelihood-free inference'}, {'subject': 'cophylogeny'}]",['1699826 bytes'],
+10.5281/zenodo.7567833,"Raw data files for ""A Simple, Transition Metal Catalyst-Free Method for the Design of Complex Organic Building Blocks Used to Construct Porous Metal-Organic Frameworks"" manuscript",Zenodo,2023,en,Dataset,"Creative Commons Attribution Non Commercial No Derivatives 4.0 International,Open Access","Raw data files for a manuscript ""A Simple, Transition Metal Catalyst-Free Method for the Design of Complex Organic Building Blocks Used to Construct Porous Metal-Organic Frameworks"". All files are organized by instrumental methods, except Figure 1 in the manuscript and Figure S1, S52 in the SI, plots for which are reported as separate files. The file headers contain the necessary information such as column designations, units, etc.",mds,True,findable,0,0,0,0,0,2023-01-25T17:31:12.000Z,2023-01-25T17:31:13.000Z,cern.zenodo,cern,"ligand,metal-organic framework,oragnic synthesis,scalability","[{'subject': 'ligand'}, {'subject': 'metal-organic framework'}, {'subject': 'oragnic synthesis'}, {'subject': 'scalability'}]",,
+10.5061/dryad.7wm37pvx5,High resolution ancient sedimentary DNA shows that alpine plant diversity is associated with human land use and climate change,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"The European Alps are highly rich in species, but their future may be threatened by ongoing changes in human land use and climate. Here, we reconstructed vegetation, temperature, human impact and livestock over the past ~12,000 years from Lake Sulsseewli, based on sedimentary ancient plant and mammal DNA, pollen, spores, chironomids, and microcharcoal. We assembled a highly-complete local DNA reference library (PhyloAlps, 3,923 plant taxa), and used this to obtain an exceptionally rich sedaDNA record of 366 plant taxa. Vegetation mainly responded to climate during the early Holocene, while human activity had an additional influence on vegetation from 6 ka onwards. Land-use shifted from episodic grazing during the Neolithic and Bronze Age to agropastoralism in the Middle Ages. Associated human deforestation allowed the coexistence of plant species typically found at different elevational belts, leading to levels of plant richness that characterise the current high diversity of this region. Our findings indicate a positive association between low-intensity agropastoral activities and precipitation with the maintenance of the unique subalpine and alpine plant diversity of the European Alps.",mds,True,findable,110,0,0,0,0,2022-09-16T16:00:05.000Z,2022-09-16T16:00:06.000Z,dryad.dryad,dryad,"metabarcoding,sedimentary ancient DNA,FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'metabarcoding'}, {'subject': 'sedimentary ancient DNA'}, {'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['190852725 bytes'],
+10.5281/zenodo.10208773,leonroussel/blood_on_snow: v1,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,Teledetection of red algal blooms using Sentinel-2 images,api,True,findable,0,0,0,1,0,2023-11-27T08:32:09.000Z,2023-11-27T08:32:09.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8083133,"MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Dataset overview</strong> This dataset provides data and images of snowflakes in free fall collected with a Multi-Angle Snowflake Camera (MASC) The dataset includes, for each recorded snowflakes: A triplet of gray-scale images corresponding to the three cameras of the MASC A large quantity of geometrical, textural descriptors and the pre-compiled output of published retrieval algorithms as well as basic environmental information at the location and time of each measurement. The pre-computed descriptors and retrievals are available either individually for each camera view or, some of them, available as descriptors of the triplet as a whole. A non exhaustive list of precomputed quantities includes for example: Textural and geometrical descriptors as in <em>Praz et al 2017</em> Hydrometeor classification, riming degree estimation, melting identification, as in <em>Praz et al 2017</em> Blowing snow identification, as in <em>Schaer et al 2020 </em> Mass, volume, gyration estimation<em>, as in Leinonen et al 2021</em> <strong>Data format and structure</strong> The dataset is divided into four <em>.parquet</em> file (for scalar descriptors) and a <em>Zarr</em> database (for the images). A detailed description of the data content and of the data records is available here. <strong>Supporting code</strong> A python-based API is available to manipulate, display and organize the data of our dataset. It can be found on GitHub. See also the code documentation on ReadTheDocs. <strong>Download notes</strong> All files available here for download should be stored in the same folder, if the python-based API is used <em>MASCdb.zarr.zip</em> must be unzipped after download <strong>Field campaigns</strong> A list of campaigns included in the dataset, with a minimal description is given in the following table <strong>Campaign_name</strong> <strong>Information</strong> <strong>Shielded / Not shielded</strong> <em>DFIR = Double Fence Intercomparison Reference</em> <em>APRES3-2016 & APRES3-2017</em> Installed in Antarctica in the context of the APRES3 project. See for example Genthon et al, 2018 or Grazioli et al 2017 Not shielded <em>Davos-2015</em> Installed in the Swiss Alps within the context of SPICE (Solid Precipitation InterComparison Experiment) Shielded (DFIR) <em>Davos-2019</em> Installed in the Swiss Alps within the context of RACLETS (<em>Role of Aerosols and CLouds Enhanced by Topography on Snow</em>) Not shielded <em>ICEGENESIS-2021</em> Installed in the Swiss Jura in a MeteoSwiss ground measurement site, within the context of ICE-GENESIS. See for example Billault-Roux et al, 2023 Not shielded <em>ICEPOP-2018</em> Installed in Korea, in the context of ICEPOP. See for example Gehring et al 2021. Shielded (DFIR) <em>Jura-2019 & Jura-2023</em> Installed in the Swiss Jura within a MeteoSwiss measurement site Not shielded <em>Norway-2016</em> Installed in Norway during the High-Latitude Measurement of Snowfall (HiLaMS). See for example Cooper et al, 2022. Not shielded <em>PLATO-2019</em> Installed in the ""Davis"" Antarctic base during the PLATO field campaign Not shielded <em>POPE-2020</em> Installed in the ""Princess Elizabeth Antarctica"" base during the POPE campaign. See for example Ferrone et al, 2023. Not shielded <em>Remoray-2022</em> Installed in the French Jura. Not shielded <em>Valais-2016</em> Installed in the Swiss Alps in a ski resort. Not shielded ISLAS-2022 Installed in Norway during the ISLAS campaign Not shielded Norway-2023 Installed in Norway during the MC2-ICEPACKS campaign Not shielded <strong>Version</strong> 1.1 - Two new campaigns (""ISLAS-2022"", ""Norway-2023"") added. 1.0 - Two new campaigns (""Jura-2023"", ""Norway-2016"") added. Added references and list of campaigns. 0.3 - a new campaign is added to the dataset (""Remoray-2022"") 0.2 - rename of variables. Variable precision (digits) standardized 0.1 - first upload",mds,True,findable,0,0,6,0,0,2023-07-05T09:42:40.000Z,2023-07-05T09:42:41.000Z,cern.zenodo,cern,"Snowfall,ice crystals,snow images,snowflakes,multi angle snowflake camera (MASC),image classification,meteorology","[{'subject': 'Snowfall'}, {'subject': 'ice crystals'}, {'subject': 'snow images'}, {'subject': 'snowflakes'}, {'subject': 'multi angle snowflake camera (MASC)'}, {'subject': 'image classification'}, {'subject': 'meteorology'}]",,
+10.57745/ktfzqd,Fichiers QGIS et Excel des cas d'étude d'application du protocole d'aide à la décision pour le traitement des embâcles (protocole de Wohl et al. 2019 adapté par Benaksas et Piton 2022),Recherche Data Gouv,2023,,Dataset,,"Chaque archive se rapporte à un cas d'étude du rapport de Benaksas & Piton (2022), à savoir: Le Bresson (Isère) Torrent de montagne et Alloix (Isère) Ruisseau de montagne, Le Lagamas (Hérault) Ruisseau méditerranéen, La Brague (Alpes-Maritimes) Rivière méditerranéenne, La Clamoux (Aude) Rivière torrentielle méditerranéenne. Chaque archive contient trois documents maîtres et les fichiers sources associés permettant de faciliter l'application du protocole de Wohl et al. (2019) tel que adapté par Benaksas & Piton (2022): Le fichier export_csv_vers_shp.qgz est un projet QGIS qui a facilité la transformation en données SIG des fichiers textes (format .csv) importés de l'application Epicollect 5 tel que décrit dans l'Annexe C du rapport de Benaksas et Piton (2023) , L'autre fichier "".gqz"" est un projet QGIS qui facilite l'affichage et l'interprétation des données SIG compilées préalablement aux missions de terrains et sur le terrain via l'application Epicollect 5 tel que décrit dans les Annexe C et D u rapport de Benaksas et Piton (2023) , ResultatsProtocole_epicollecte.xlsx est un tableur Excel qui a facilité la notation des indicateurs de l'approche multicritère, qui permet la modification éventuelle des pondérations entre sous-critères, et qui a mené le calcul des scores pondérés fournis dans le rapport et a préparé les sorties graphiques fournies dans le rapport. Nota: Le cas d'étude du Bréda (Isère) rivière de montagne affluent de l'Isère ayant servi à caler le protocole, les données associées à ce cas d'étude ne sont pas homogènes et ne sont ainsi pas mis librement à disposition. Elles peuvent éventuellement être mises à disposition sur demande directe à Guillaume Piton.",mds,True,findable,48,2,0,0,0,2023-03-06T13:05:38.000Z,2023-03-06T14:03:27.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.8131976,Prior information differentially affects discrimination decisions and subjective confidence reports,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Experimental data from a series of three human experiments described in the submitted article ""Prior information differentially affects discrimination decisions and subjective confidence reports"" by Marika Constant, Michael Pereira, Nathan Faivre, and Elisa Filevich (2023). This dataset includes all of the data needed to run the analyses in the article. Please consult the article for a full description of the data.",mds,True,findable,0,0,0,0,0,2023-07-10T15:37:26.000Z,2023-07-10T15:37:26.000Z,cern.zenodo,cern,,,,
+10.60662/x25q-yv27,Vers une approche générique du raisonnement par cas : application à la gestion énergétique dans le bâtiment,CIGI QUALITA MOSIM 2023,2023,,ConferencePaper,,,fabricaForm,True,findable,0,0,0,0,0,2023-09-11T15:17:26.000Z,2023-09-11T15:17:26.000Z,uqtr.mesxqq,uqtr,,,,
+10.5281/zenodo.8289247,Optimized structures of the stationary points on the potential energy surface of the OH(2Π) + C2H4 reaction,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This Zip file contains the cartesian coordinates of optimized stationary points of the OH(<sup>2</sup>Π) + C<sub>2</sub>H<sub>4</sub> potential energy surface published in our article “OH(<sup>2</sup>Π) + C<sub>2</sub>H<sub>4</sub> Reaction: A Combined Crossed Molecular Beam and Theoretical Study†(P<em>hys. Chem. A</em> 2023, 127, 21, 4609–4623), that can be found in https://doi.org/10.1021/acs.jpca.2c08662. All calculations have been performed with Gaussian 09, Revision D.01. All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.",mds,True,findable,0,0,0,1,0,2023-08-29T13:59:34.000Z,2023-08-29T13:59:34.000Z,cern.zenodo,cern,"Alcohols,Chemical calculations,Energy,Kinetics,Vinyl","[{'subject': 'Alcohols'}, {'subject': 'Chemical calculations'}, {'subject': 'Energy'}, {'subject': 'Kinetics'}, {'subject': 'Vinyl'}]",,
+10.5281/zenodo.5336853,Canopy and understory tree guilds respond differently to the environment in an Indian rainforest,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Questions. Changes in the functional composition of tree communities along resource availability gradients have received attention, but it is unclear whether or not understory and canopy guilds respond similarly to different light, biomechanical, and hydraulic constraints. Location. An anthropically-undisturbed, old-growth wet evergreen Dipterocarp forest plot located in Karnataka State, India. Methods. We measured leaf and wood traits of 89 tree species representing 99% of all individuals in a 10 ha permanent plot with varying topographic and canopy conditions inferred from LiDAR data. We assigned tree species to guilds of canopy and understory species and assessed the variation of the guild weighted means of functional trait values with canopy height and topography. Results. The functional trait space did not differ between canopy and understory tree species. However, environmental filtering led to significantly different functional composition of canopy and understory guild assemblages. Furthermore, they responded differently along environmental gradients related to water, nutrients, light, and wind exposure. For example, the canopy guild responded to wind exposure while the understory guild did not. Conclusions. The pools of understory and canopy species are functionally similar. However, fine-scale environmental heterogeneity impacts differently on these two guilds, generating striking differences in functional composition between understory and canopy guild assemblages. Accounting for vertical guilds improves our understanding of forest communities’ assembly processes.",mds,True,findable,0,0,0,0,0,2021-10-11T12:59:38.000Z,2021-10-11T12:59:39.000Z,cern.zenodo,cern,"Rainforest,Western Ghats,Leaf economics spectrum,Environmental filtering,Vertical strata,Wood economics spectrum","[{'subject': 'Rainforest'}, {'subject': 'Western Ghats'}, {'subject': 'Leaf economics spectrum'}, {'subject': 'Environmental filtering'}, {'subject': 'Vertical strata'}, {'subject': 'Wood economics spectrum'}]",,
+10.5281/zenodo.7269139,Catalog of P-wave secondary microseisms events,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Catalog of P-wave secondary microseisms events,mds,True,findable,0,0,0,0,0,2022-11-01T00:26:15.000Z,2022-11-01T00:26:16.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10013099,"Data and code for the article "" Dissimilarity of vertebrate trophic interactions reveals spatial uniqueness but functional redundancy across Europe""",Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,,api,True,findable,0,0,0,0,0,2023-10-17T09:29:23.000Z,2023-10-17T09:29:23.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3824264,Unmanned aerial system data of Lirung Glacier and Langtang Glacier for 2013–2018,Zenodo,2020,en,Dataset,Restricted Access,"This dataset contains the raw data as well as produced image mosaics, digital elevation models (DEMs) and data derivatives of optical (RGB) unmanned aerial vehicle surveys of the debris-covered Lirung Glacier (9 surveys, 2013–2018) and Langtang Glacier (7 surveys, 2014–2018) in the Langtang Catchment, Nepalese Himalaya. All data in this dataset are stored in tape archive (<code>tar</code>) or gzip-compressed tape archive (<code>tar.gz</code>) formats and require extraction before use. The projected coordinate system used in this dataset is <em>WGS 1984 UTM Zone 45N (EPSG:32645)</em>. Survey dates are always provided as <em>yyyymmdd</em>. <strong>File descriptions</strong> <strong><code>dems_<glacier>.tar</code></strong><br> 20 cm resolution DEMs that were derived from the raw UAV images. DEMs of all survey dates are included in the tar archives. File format is GeoTIFF.<br> <strong><code>orthomosaics_<glacier>.tar</code></strong><br> 10 cm resolution image mosaics of orthorectified source imagery (orthomosaics) that were derived from the raw UAV images. Orthomosaics of all survey dates are included in the tar archives. File format is GeoTIFF.<br> <strong><code>point-clouds_<glacier>.tar.gz</code></strong><br> Raw dense point clouds that were derived from the raw UAV images. Point clouds of all survey dates are included in the tar archive. File format is ASPRS LAS. Note that additional gzip-compression has been applied to the archives.<br> <strong><code>raw-data_<glacier>_<datestamp>.tar</code></strong><br> Raw data of each of the surveys that were performed over 2013–2018. The filename includes the glacier name and the survey date. Each tar archive contains directories for each UAV flight associated to that specific survey, indicated by <em>f1, f2, ..., fn</em>. The flight directories have the following contents: <code>img</code><br> Subdirectory that contains the individual images in JPEG format captured by the UAV camera. <code>*flight_path.kml</code> (not present for all surveys)<br> Keyhole Markup Language file that contains the flight path of the UAV recorded by the UAV's internal GPS+GLONASS sensor. <code>*image_geoinfo.txt</code><br> Table with coordinates (<em>x,y,z</em>) and UAV orientation (<em>roll, tilt, yaw</em>) for every image in <code>img</code>, which were recorded by the UAV's internal GPS+GLONASS sensor and gyroscope, respectively. <code>*drone_log.bbx</code> or <code>*drone_log.bb3</code><br> Binary flight log file from the UAV containing detailed flight information. Can be read by the proprietary eMotion software by UAV manufacturer senseFly.<br> <strong><code>supplementary-animation_<glacier>.gif</code></strong><br> Animations of Langtang Glacier (2014–2018) and Lirung Glacier (2013–2017) supplementary to Kraaijenbrink & Immerzeel (2020). The high resolution time lapse animations are constructed from composites of the orthomosaic and hillshaded DEM. Since the animations are in GIF format, they are best viewed in a web browser in which they can be zoomed and panned.<br> <strong><code>supplementary-data-to-article.tar</code></strong><br> Data derivatives as presented in Kraaijenbrink & Immerzeel (2020). The tar archive contains a README file with additional information and metadata for each of the datasets present in the archive. The archive contains: Independent error measurements of the Lirung Glacier UAV product Vector outlines of the area of interests of both glaciers Point cloud extracts of supraglacial ice cliff cross profiles Flow and gradient corrected DEMs (1 m resolution) Pixel-wise regression of the flow-corrected DEMs (1 m resolution) Surface velocity between survey pairs (8 m resolution) <strong>Reference</strong> For further information, e.g. about the UAV systems and cameras used, as well as detailed descriptions of the data and the applied data processing please refer to: <em><Insert reference></em> <strong>License</strong> This dataset is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).<br> (https://creativecommons.org/licenses/by/4.0/) <strong>Correspondence</strong> Dr Philip Kraaijenbrink (p.d.a.kraaijenbrink@uu.nl)<br> Prof Dr Walter Immerzeel (w.w.immerzeel@uu.nl)",mds,True,findable,0,0,0,0,0,2020-05-14T10:09:22.000Z,2020-05-14T10:09:24.000Z,cern.zenodo,cern,"Cryosphere,Glaciology,Remote sensing,Debris-covered glaciers,Unmanned aerial vehicles,Digital elevation models,Orthomosaics,Point clouds,High-resolution,Himalaya,Nepal,Langtang","[{'subject': 'Cryosphere'}, {'subject': 'Glaciology'}, {'subject': 'Remote sensing'}, {'subject': 'Debris-covered glaciers'}, {'subject': 'Unmanned aerial vehicles'}, {'subject': 'Digital elevation models'}, {'subject': 'Orthomosaics'}, {'subject': 'Point clouds'}, {'subject': 'High-resolution'}, {'subject': 'Himalaya'}, {'subject': 'Nepal'}, {'subject': 'Langtang'}]",,
+10.5281/zenodo.7865424,Raw and post-processed data for the study of prosodic cues to word boundaries in a segmentation task using reverse correlation,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The current dataset provides all the stimuli (folder <strong>../01-Stimuli/</strong>), raw data (folder <strong>../02-Raw-data/</strong>) and post-processed data (<strong>../03-Post-proc-data/</strong>) used in a prosody reverse correlation study with the title ""prosodic cues to word boundaries in a segmentation task using reverse correlation"" by the same authors. The listening experiment was implemented using one-interval trials with target words of the structure l'aX (option 1) and la'X (option 2). The experiment was designed and implemented using the fastACI toolbox under the name 'segmentation'. A between-subject design was used with a total of 47 participants, who evaluated one of five conditions, LAMI (N=16), LAPEL (N=18), LACROCH (N=5), LALARM (N=5), and LAMI_SHIFTED (N=3). More details are given in the related publication (to be submitted to JASA-EL in May 2023).",mds,True,findable,0,0,1,0,0,2023-04-25T22:48:56.000Z,2023-04-25T22:48:57.000Z,cern.zenodo,cern,"Reverse correlation,Prosody,Speech perception,Segmentation","[{'subject': 'Reverse correlation'}, {'subject': 'Prosody'}, {'subject': 'Speech perception'}, {'subject': 'Segmentation'}]",,
+10.6084/m9.figshare.23737431.v2,Supplementary document for Flexible optical fiber channel modeling based on neural network module - 6356438.pdf,Optica Publishing Group,2023,,Text,Creative Commons Attribution 4.0 International,Supplement 1,mds,True,findable,0,0,0,0,0,2023-08-10T20:33:56.000Z,2023-08-10T20:33:57.000Z,figshare.ars,otjm,Uncategorized,[{'subject': 'Uncategorized'}],['684917 Bytes'],
+10.15454/m7ok9e,Flux tower by Eddy Covariance and InfraRed scintillometry on ORACLE observatory,Portail Data INRAE,2020,,Dataset,,Observational data from flux tower and infrared scintillometry. Data are associated with micro-meteorological data. All data is measured at high-frequency. Data have been collected during CRITEX/EQUIPEX project on the Oracle-Orgeval observatory (INRAE). These data are free available from BDOH database (https://bdoh.irstea.fr/ORACLE/).,mds,True,findable,3490,0,0,0,0,2020-03-27T11:57:36.000Z,2020-03-27T11:57:37.000Z,rdg.prod,rdg,,,,
+10.6084/m9.figshare.21717750.v1,Neuroblast Differentiation-Associated Protein Derived Polypeptides: AHNAK(5758-5775) Induces Inflammation by Activating Mast Cells via ST2,Taylor & Francis,2022,,Text,Creative Commons Attribution 4.0 International,"Psoriasis is a chronic inflammatory skin disease. Mast cells are significantly increased and activated in psoriatic lesions and are involved in psoriatic inflammation. Some endogenous substances can interact with the surface receptors of mast cells and initiate the release of downstream cytokines that participate in inflammatory reactions. Neuroblast differentiation-associated protein (AHNAK) is mainly expressed in the skin, esophagus, kidney, and other organs and participates in various biological processes in the human body. AHNAK and its derived peptides have been reported to be involved in the activation of mast cells and other immune processes. This study aimed to investigate whether AHNAK (5758–5775), a neuroblast differentiation-associated protein-derived polypeptide, could be considered a new endogenous substance in psoriasis patients, which activates mast cells and induces the skin inflammatory response contributing to psoriasis. Wild-type mice were treated with AHNAK(5758–5775) to observe the infiltration of inflammatory cells in the skin and cytokine release in vivo. The release of inflammatory mediators by mouse primary mast cells and the laboratory of allergic disease 2 (LAD2) human mast cells was measured in vitro. Molecular docking analysis, molecular dynamics simulation, and siRNA transfection were used to identify the receptor of AHNAK(5758–5775). AHNAK(5758–5775) could cause skin inflammation and cytokine release in wild-type mice and activated mast cells in vitro. Moreover, suppression of tumorigenicity 2 (ST2) might be a key receptor mediating AHNAK(5758–5775)’s effect on mast cells and cytokine release. We propose a novel polypeptide, AHNAK(5758–5775), which induces an inflammatory reaction and participates in the occurrence and development of psoriasis by activating mast cells.",mds,True,findable,0,0,0,0,0,2022-12-13T16:00:06.000Z,2022-12-13T16:00:06.000Z,figshare.ars,otjm,"Biochemistry,Medicine,Microbiology,FOS: Biological sciences,Cell Biology,Genetics,Physiology,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,Developmental Biology,Cancer,111714 Mental Health,FOS: Health sciences,Computational Biology","[{'subject': 'Biochemistry'}, {'subject': 'Medicine'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cell Biology'}, {'subject': 'Genetics'}, {'subject': 'Physiology'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Developmental Biology'}, {'subject': 'Cancer'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Computational Biology'}]",['264022 Bytes'],
+10.5281/zenodo.3407127,Experiments on Grain Size Segregation in Bedload Transport on a steep Slope,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset is the basis of the publication: Frey, P., Lafaye de Micheaux, H., Bel, C., Maurin, R., Rorsman, K., Martin, T., Ducottet, C., 2020. Experiments on grain size segregation in bedload transport on a steep slope. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2019.103478. Experiments consisted in bedload of two-size spherical glass beads transported at equilibrium by a turbulent supercritical free surface water flow over a mobile bed. Two runs, one with a low rate of large black beads (S6), the other with a higher rate (S20), are considered. This dataset consists in: - temporal sequences of uncompressed tif images corresponding to figure 5 showing small particle concentration : 9 sequences for run S6 (BillesBaumerMicro) and 9 sequences for run S20 (BillesbaumerAmontSequence) - two ‘.mat’ file corresponding to runs S6 (trackData_Micro_S6.mat) and S20 (trackData_Amont_S20.mat) giving all the trajectories of all beads. Trajectories were obtained with a tracking algorithm developed by H. Lafaye de Micheaux et al. (2016,2018) building on Hergault et al. (2010). The code implementing the tracking algorithm is available on https://github.com/hugolafaye/BeadTracking. The files contain the variable 'trackData' being a cell array of tracking matrices. There is one tracking matrix for each image of the sequence giving in particular the coordinate and velocity of each bead. Complete information on data format is given in the file readme.txt in the github BeadTracking package. Parameter files necessary to replicate our results from the images are also available on the BeadTracking package as well as on https://doi.org/10.5281/zenodo.3454628 where a 1000-image ground truth is stored. Important note: Experimental images were grabbed with the flow from right to the left implying for instance negative values for the x-coordinate of velocities. To comply with a traditional convention, images and associated results in the publication are shown from left to the right.",mds,True,findable,5,0,0,0,0,2019-10-14T14:33:25.000Z,2019-10-14T14:33:25.000Z,cern.zenodo,cern,"Sediment transport, bedload, experimental, segregation, two-phase flow, granular flow, particle tracking","[{'subject': 'Sediment transport, bedload, experimental, segregation, two-phase flow, granular flow, particle tracking'}]",,
+10.5061/dryad.1s7v5,Data from: Evaluation of redundancy analysis to identify signatures of local adaptation,Dryad,2018,en,Dataset,Creative Commons Zero v1.0 Universal,"Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This paper aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. Additionally, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., 2013). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the northwestern American coast.",mds,True,findable,636,324,1,1,0,2018-06-15T04:58:08.000Z,2018-06-15T04:58:15.000Z,dryad.dryad,dryad,"RDA,Genome scans","[{'subject': 'RDA'}, {'subject': 'Genome scans', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['1307365306 bytes'],
+10.57726/j3mg-e206,Les Inscriptions latines de l'Ain (ILAIN),Presses Universitaires Savoie Mont Blanc,2005,fr,Book,,,fabricaForm,True,findable,0,0,0,0,0,2022-03-14T14:28:43.000Z,2022-03-14T14:28:43.000Z,pusmb.prod,pusmb,FOS: Humanities,"[{'subject': 'FOS: Humanities', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['300 pages'],
+10.5061/dryad.qrfj6q5h6,Designing industry 4.0 implementation from the initial background and context of companies,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Industry 4.0 is a promising concept that allows industries to meet customers’ demands with flexible and resilient processes, and highly personalised products. This concept is made up of different dimensions. For a long time, innovative digital technology has been thought of as the only dimension to succeed in digital transformation projects. Next, other dimensions have been identified such as organisation, strategy, and human resources as being key while rolling out digital technology in factories. From these findings, researchers have designed industry 4.0 theoretical models and then, built readiness models that allow for analysing the gap between the company initial situation and the theoretical model. Nevertheless, this purely deductive approach does not take into consideration a company’s background and context, and eventually favours one single digital transformation model. This article aims at analysing four actual digital transformation projects and demonstrating that the digital transformation’s success or failure depends on the combination of two variables related to a company’s background and context. This research is based on a double approach: deductive and inductive. First, a literature review has been carried out to define industry 4.0 concept and its main dimensions and digital transformation success factors, as well as barriers, have been investigated. Second, a qualitative survey has been designed to study in-depth four actual industry digital transformation projects, their genesis as well as their execution, to analyse the key variables in succeeding or failing. 46 semi-structured interviews were carried out with projects’ members. The interviews have been analysed with thematic content analysis. Then, each digital transformation project has been modelled regarding the key variables and analysed with regards to succeeding or failing. Investigated projects have consolidated the models of digital transformation. Finally, nine digital transformation models have been identified. Industry practitioners could design their digital transformation project organisation and strategy according to the right model.",mds,True,findable,139,15,0,0,0,2021-11-03T18:22:27.000Z,2021-11-03T18:22:28.000Z,dryad.dryad,dryad,Industrial engineering,"[{'subject': 'Industrial engineering', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['985101 bytes'],
+10.5281/zenodo.4022283,Topological Weaire-Thorpe models of amorphous matter,Zenodo,2020,,Software,"BSD 2-Clause ""Simplified"" License,Open Access","<strong>Abstract</strong> Amorphous solids remain outside of the classification and systematic discovery of new topological materials, partially due to the lack of realistic models that are analytically tractable. Here we introduce the topological Weaire-Thorpe class of models, which are defined on amorphous lattices with fixed coordination number, a realistic feature of covalently bonded amorphous solids. Their short-range properties allow us to analytically predict spectral gaps. Their symmetry under permutation of orbitals allows us to compute analytically topological phase diagrams, which determine quantized observables like circular dichroism, by introducing symmetry indicators for the first time in amorphous systems. These models and our procedures to define invariants are generalizable to higher coordination number and dimensions, opening a route towards a complete classification of amorphous topological states in real space using quasilocal properties. <strong>Contents</strong> Code to generate all data and figures in the manuscript: Plots.ipynb most plots, no calculations Figure2.ipynb figure 2 c) and d) including calculations kpm_weaire_thorpe.ipynb heavy calculations and some supplementary plots fourfold_model_plots.ipynb calculations and figures for fourfold coordinated model Data produced by the longer calculations. <strong>Requirements</strong> kwant >= 1.4",mds,True,findable,0,0,1,0,0,2020-09-10T10:56:45.000Z,2020-09-10T10:56:46.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5835995,Ultrafast imaging recordings from the axon initial segment of neocortical layer-5 pyramidal neurons.,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains imaging and whole-cell electrophysiological recordings from neocortical layer-5 pyramidal neuron from brain slices of the mouse. Electrophysiological recordings (at 20 kHz) are from the soma. Imaging data (10 kHz) are from lines along the axon initial segment (distal>proximal) with 500 nm pixel resolution. These correspond to: Sodium imaging (Figures 1 and S6). Voltage imaging (Figures 2,4,5,S4,S7) Calcium imaging (Figures 3,S3,S8). This dataset is used in the paper available online: Filipis L, Blömer LA, Montnach J, De Waard M, Canepari M. Nav1.2 and BK channels interaction shapes the action potential in the axon initial segment. bioRxiv, 2022. doi: 10.1101/2022.04.12.488116.",mds,True,findable,0,0,0,0,0,2022-10-20T13:43:28.000Z,2022-10-20T13:43:29.000Z,cern.zenodo,cern,"Nav1.2 channel,BK Ca2+-activated K+ channel,axon initial segment,action potential,neocortical layer-5 pyramidal neuron,calcium","[{'subject': 'Nav1.2 channel'}, {'subject': 'BK Ca2+-activated K+ channel'}, {'subject': 'axon initial segment'}, {'subject': 'action potential'}, {'subject': 'neocortical layer-5 pyramidal neuron'}, {'subject': 'calcium'}]",,
+10.5061/dryad.3ffbg79pv,National forest inventory data for a size-structured forest population model,Dryad,2023,en,Dataset,Creative Commons Zero v1.0 Universal,"In forest communities, light competition is a key process for community assembly. Species' differences in seedling and sapling tolerance to shade cast by overstory trees is thought to determine species composition at late-successional stages. Most forests are distant from these late-successional equilibria, impeding a formal evaluation of their potential species composition. To extrapolate competitive equilibria from short-term data, we therefore introduce the JAB model, a parsimonious dynamic model with interacting size-structured populations, which focuses on sapling demography including the tolerance to overstory competition. We apply the JAB model to a two-""species"" system from temperate European forests, i.e. the shade-tolerant species Fagus sylvatica L. and the group of all other competing species. Using Bayesian calibration with prior information from external Slovakian national forest inventory (NFI) data, we fit the JAB model to short timeseries from the German NFI. We use the posterior estimates of demographic rates to extrapolate that F. sylvatica will be the predominant species in 94% of the competitive equilibria, despite only predominating in 24% of the initial states. We further simulate counterfactual equilibria with parameters switched between species to assess the role of different demographic processes for competitive equilibria. These simulations confirm the hypothesis that the higher shade-tolerance of F. sylvatica saplings is key for its long-term predominance. Our results highlight the importance of demographic differences in early life stages for tree species assembly in forest communities.",mds,True,findable,104,7,0,0,0,2023-06-21T08:35:58.000Z,2023-06-21T08:35:59.000Z,dryad.dryad,dryad,"FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences,NFI,National Forest Inventory,Fagus sylvatica,JAB model","[{'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'NFI'}, {'subject': 'National Forest Inventory'}, {'subject': 'Fagus sylvatica'}, {'subject': 'JAB model'}]",['48025574 bytes'],
+10.5281/zenodo.8206446,"Data set for ""Tracking the as yet unknown nearfield evolution of a shallow, neutrally-buoyant plane jet over a sloping bottom boundary""",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data set for the paper titled ""Tracking the as yet unknown nearfield evolution of a shallow, neutrally-buoyant plane jet over a sloping bottom boundary"".",mds,True,findable,0,0,0,0,0,2023-08-01T19:39:16.000Z,2023-08-01T19:39:17.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6956953,Catalog of microseismicity related to the Alto-Tiberina Fault,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This template matching catalog contains information about new detected seismicity as the origin time (ot), latitude (lat_temp), longitude (lon_temp), depth (depth_tep), magnitude (mag), origin time of the template that can be used as the event_id (ot_template), the ratio between the average correlation coefficient (CC) and the daily median absolute deviation of the averaged CCs, as an indication for the quality of a detection (cc_mad_ratio), and an indication about the origin as some of the detection's seem to be related to human induced activity (hum_ind). Detailed information about the template matching processing can be gained from <strong>Spatio-temporal evolution of the</strong><strong> Seismicity in the Alto Tiberina Fault System revealed by a High-Resolution Template Matching Catalog</strong> by Essing & Poli (2022)",mds,True,findable,0,0,0,0,0,2022-08-03T09:20:55.000Z,2022-08-03T09:20:56.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23575381,Additional file 8 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 7,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:57.000Z,2023-06-25T03:11:57.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['24064 Bytes'],
+10.25647/liepp.wp.36,"Better residential than ethnic discrimination! Reconciling audit's findings and interviews' findings in the Parisian housing market (LIEPP Working Paper, n°36)",Sciences Po - LIEPP,2015,en,Other,,"This article investigates discrimination and the interplay of residential and ethnic stigma on the French housing market using two different methods, paired-testing au- dit study of real estate agencies and face-to-face interviews with real estate agents. The juxtaposition of their findings leads to a paradox: interviews reveal high levels of ethnic discrimination but little to none residential discrimination, while the audit study shows that living in deprived suburbs is associated with a lower probability of obtaining an appointment for a housing vacancy but ethnic origin (signaled by the candidate’s name) has no significant discriminatory effect. We have three priors po- tentially consistent with this apparent paradox and re-evaluate their likelihood in light of these findings: (i) agents make use of any statistical information about insolvency, including residency; (ii) there are two distinct and independent taste discriminations, one about space and one about ethnicity; (iii) these two dimensions exist and comple- ment each other.",fabricaForm,True,findable,0,0,0,0,0,2022-03-17T11:03:38.000Z,2022-03-17T11:03:38.000Z,vqpf.dris,vqpf,FOS: Social and economic geography,"[{'subject': 'FOS: Social and economic geography', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.4964205,"FIGURES 9–12. Protonemura auberti female. 9. cervical gills. 10 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 9–12. Protonemura auberti female. 9. cervical gills. 10. subgenital plate and vaginal lobes, ventral view. 11. vaginal lobes, lateral view. 12. subgenital plate and vaginal lobes, ventral view",mds,True,findable,0,0,7,0,0,2021-06-16T08:24:59.000Z,2021-06-16T08:25:00.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.2248525,MB2018: Artificial spiking STDP neural network,Zenodo,2018,,Software,"Creative Commons Attribution 4.0 International,Open Access","This software implements artificial STDP spiking neural networks with an attention mechanism, which was used for spike sorting in the following study: Bernert M, Yvert B (2018) An attention-based spiking neural network for unsupervised spike-sorting. International Journal of Neural Systems, https://doi.org/10.1142/S0129065718500594 Please cite this paper as a reference.",mds,True,findable,0,0,0,0,0,2019-01-03T14:34:42.000Z,2019-01-03T14:34:43.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4964217,"FIGURES 33–34. 33 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 33–34. 33. Protonemura aestiva, female, ventral view. 34. Protonemura aestiva, male terminalia, ventral view",mds,True,findable,0,0,3,0,0,2021-06-16T08:25:40.000Z,2021-06-16T08:25:41.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.2577796,lipids_at_airdes,Zenodo,2019,,Software,"Creative Commons Attribution Share Alike 4.0 International,Open Access","ESI for ""Bayesian determination of the effect of a deep eutectic solvent on the structure of lipid monolayers""",mds,True,findable,0,0,1,0,0,2019-02-26T08:10:30.000Z,2019-02-26T08:10:31.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7114168,Databases related to molecular biophysics 09-2022,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","A survey and comparative analysis of the technical provision of existing databases that provide for archival of data from molecular biophysics experiments and closely related areas has been carried out. The analysis demonstrates that for many methods provided by MOSBRI there is no specialist provision for data archival such as would adequately satisfy FAIR principles. In particular only a small number of databases containing molecular biophysics derived data use standard data formats with sufficiently rich metadata that enables interoperable data reuse. Where relevant molecular biophysics databases do exist, and in the closely related area of structural biology, there is a clear trend toward complete deposition of the experiment life cycle (i.e., primary experimental data, analysis procedure and interpretation), which will need to be incorporated into plans for the future MOSBRI data repository. The survey also highlights many resources that would have to be linked with any future MOSBRI data repository, to ensure findability and interoperability.",mds,True,findable,0,0,0,0,0,2022-09-26T19:06:57.000Z,2022-09-26T19:06:57.000Z,cern.zenodo,cern,"database,biophysics,fair,MOSBRI","[{'subject': 'database'}, {'subject': 'biophysics'}, {'subject': 'fair'}, {'subject': 'MOSBRI'}]",,
+10.5281/zenodo.6461645,protopipe,Zenodo,2022,,Software,"CeCILL-B Free Software License Agreement,Open Access",Pipeline prototype for the Cherenkov Telescope Array (CTA).,mds,True,findable,0,0,0,0,0,2022-04-14T15:43:06.000Z,2022-04-14T15:43:07.000Z,cern.zenodo,cern,"gamma-ray astronomy,Imaging Atmospheric Cherenkov Telescope,IACT,CTA,pipeline,simulations,grid","[{'subject': 'gamma-ray astronomy'}, {'subject': 'Imaging Atmospheric Cherenkov Telescope'}, {'subject': 'IACT'}, {'subject': 'CTA'}, {'subject': 'pipeline'}, {'subject': 'simulations'}, {'subject': 'grid'}]",,
+10.5281/zenodo.6645980,"Data related to ""Near-bed sediment transport processes during onshore bar migration in large-scale experiments. Comparison with offshore bar migration.""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Abstract: This paper presents novel insights into nearshore sediment transport processes during bar migration on the basis of large-scale laboratory experiments with bichromatic wave groups on a relatively steep initial beach slope (1:15). Insights are based on detailed measurements of velocity and sand concentration near the bed from shoaling up to the outer breaking zone including suspended sediment and sheet flow transport. The analysis focuses on onshore migration under an accretive wave condition but comparison to an erosive condition highlights important differences. Decomposition shows that total net transport mainly results from a balance of short wave-related, bedload net onshore transport and current-related, suspended net offshore transport. When comparing the accretive to the more energetic erosive condition, the balance shifts towards net onshore transport, and onshore migration, because the short wave-related transport does not decrease as much as the current-related transport. This is related to the effects of skewness and asymmetry combined with larger sediment entrainment and undertow magnitude under the erosive condition. Net transports from streaming in the wave boundary layer and from infragravity waves are noticeable but only play a subordinate role. Identified priorities for numerical model development include parametrization of wave nonlinearity effects and better description of wave breaking and its influences on sediment suspension. The present data, unique in their combination of high measurement detail with fully-evolving accretive beach profiles, help to improve numerical modeling of long-term morphological evolution. About the data: The folder “Beach Profiles†contains the measurements from the mechanical profiler before and after each test. To save time, only the morphologically active section of the profiles was measured. Additionally, the folder contains the initial profiles at the start of each sequence (after application of the benchmark waves). Here the full profile was measured. The structure “MobFrame†contains the absolute cross-shore position of the mobile frame (from which detailed measurements were taken) in the considered tests. The folder “ACVP†contains structures with ensemble-averaged velocity and concentration measurements in vertical reference to the undisturbed bed level or a few bins below it (zeta<sub>0</sub>-coordinate system as described in the paper). For better interpretation of the measurements, it also features the ensemble-averaged intrawave instantaneous bed elevation (erosion depth) and the upper limit of the sheet flow layer. The folder “ADV†contains structures with the ensemble-averaged ADV data of each test. Apart from the velocity components of each ADV they contain the vertical elevation of each ADV with respect to the ACVP transceiver. The ADV measurements were not subject to the same vertical referencing procedure that was described in the paper for the near-bed ACVP measurements. The folder “OBS†contains structures with the ensemble-averaged OBS data of each test. Apart from the concentration measurements in each OBS sensor they contain the vertical elevation of each OBS with respect to the ACVP transceiver. The folder “ETA†contains structures with the ensemble-averaged surface elevation data of each test (from different instruments as described in the paper). The location of each instrument is given in absolute cross-shore coordinates x. For visualizing the near-bed concentration data, which may not be as trivial as visualizing the rest of the data, an example of MATLAB code is given: %S=ACVP_xx; %to choose which ACVP file you want to look into con=S.c; con(con<1)=1; %to cater for the cells where the logarithm is not defined xphase=linspace(0,1,length(S.solbed)).*ones(size(S.c,2),size(S.c,1)); figure; hold on; box on; [C,h]=contourf(xphase,S.z,log10(transpose(con)),[0:0.1:3]); cbh=colorbar; caxis([0 3]); set(h,'edgecolor','none'); tt=get(cbh,'Title'); set(tt,'String','$log_{10}(c)$ $[kg/m^3]$','Interpreter','Latex'); plot(xphase(1,:),S.solbed,'k','Linewidth',1.5); plot(xphase(1,:),S.solflo,'r','Linewidth',1.5); xlabel('$t/T_r$','Interpreter','Latex') ylabel('$\zeta_0$ $[m]$','Interpreter','Latex') set(gca,'Fontsize',18)",mds,True,findable,0,0,0,0,0,2022-06-15T13:29:22.000Z,2022-06-15T13:29:23.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.24202747.v1,Additional file 1 of Obstructive sleep apnea: a major risk factor for COVID-19 encephalopathy?,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Supplemental Table 1. Comparison of patient demographic characteristics between definite OSA group and No OSA group.,mds,True,findable,0,0,0,0,0,2023-09-27T03:26:07.000Z,2023-09-27T03:26:07.000Z,figshare.ars,otjm,"Biophysics,Medicine,Cell Biology,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,Sociology,FOS: Sociology,Immunology,FOS: Clinical medicine,Cancer,Mental Health,Virology","[{'subject': 'Biophysics'}, {'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Mental Health'}, {'subject': 'Virology'}]",['31583 Bytes'],
+10.5281/zenodo.6787572,2D honeycomb transformation into dodecagonal quasicrystals driven by electrostatic forces,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the SXRD data measured for the 48-18-6 approximant in Sr-Ti-O on Pt(111). The data has been acquired at the SixS beamline of the Synchrotron SOLEIL in France on 19.09.2019. Monochromatic x-rays with photon energy of 11 keV were used to avoid Pt fluorescence (at 11.1 and 13 keV) and consequently reduced the background signal. The diffraction experiment was performed under grazing incidence at an angle of 0.2 °. The orientation matrix was defined relative to the Pt substrate lattice with its lattice constants of a = 392 pm. Additionally, the 3D voxel map generated from the raw data for further use in the binoculars software is provided as well as the input and output of SHELXL, which has been used for structure relaxation.",mds,True,findable,0,0,0,0,0,2022-07-22T09:10:33.000Z,2022-07-22T09:10:34.000Z,cern.zenodo,cern,"Oxide quasicrystals, 2D ternary oxide, quasicrystal approximant, SXRD","[{'subject': 'Oxide quasicrystals, 2D ternary oxide, quasicrystal approximant, SXRD'}]",,
+10.5281/zenodo.8314927,"Simulations and scripts for ""Glacier surges controlled by the close interplay between subglacial friction and drainage"".",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the model and scripts to reproduce the results presented in ""Glacier surges controlled by the close interplay between subglacial friction and drainage"" and submitted to the Journal of Geophysical Research - Earth Surface. It provides the running model files associated with each result figure of the manuscript as well as the Python script to generate them from the simulation output. The model is also described and updated at: https://github.com/kjetilthogersen/pyGlacier.",mds,True,findable,0,0,0,0,0,2023-09-04T10:53:19.000Z,2023-09-04T10:53:20.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.3r2280ggb,Lags in phenological acclimation of mountain grasslands after recent warming,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"1. In the current biodiversity crisis, one of the crucial questions is how quickly plant communities can acclimate to climate warming and longer growing seasons to buffer the impairment of community functioning. Answering this question is pivotal especially for mountain grasslands that experience harsh conditions but provide important ecosystem services to people. 2. We conducted a reciprocal transplant experiment along an elevation gradient (1920 m vs. 2450 m) in the French Alps to test the ability of plant species and communities to acclimate to warming and cooling. For three years, we measured weekly the timing of phenological events (e.g. start of flowering or greening) and the length of phenological stages linked to demographic performance (e.g. lengths of flowering or greening periods). 3. We found that warming (and cooling) changed the timing of phenological events strongly enough to result in complete acclimation for graminoids, for communities in early and mid-season, but not at all for forbs. For example, warming resulted in later greening of communities and delayed all phenophases of graminoids. Lengths of phenological stages did not respond strongly enough to climate change to acclimate completely, except for graminoids. For example, warming led to an acclimation lag in the community’s yearly productivity and had a strong negative impact on flowering of forbs. Overall, when there was an acclimation failure, responses to cooling were mostly symmetric and confirmed slow acclimation in mountain grasslands. 4. Synthesis. Our study highlights that phenological plasticity cannot prevent impairment of community functioning under climate warming in the short-term. The failures to acclimate after three years of warming signals that species and communities underperform and are probably at high risk of being replaced by locally better-adapted plants.",mds,True,findable,134,7,0,1,0,2021-06-22T17:02:43.000Z,2021-06-22T17:02:44.000Z,dryad.dryad,dryad,"reciprocal transplant,warming experiment,transient dynamics,mountain grasslands,Climate change","[{'subject': 'reciprocal transplant'}, {'subject': 'warming experiment'}, {'subject': 'transient dynamics'}, {'subject': 'mountain grasslands'}, {'subject': 'Climate change', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['11714487 bytes'],
+10.60662/pyvs-cj63,Intégration de connaissances du domaine et de l’apprentissage automatique pour l’estimation des paramètres de fabrication,CIGI QUALITA MOSIM 2023,2023,,ConferencePaper,,,fabricaForm,True,findable,0,0,0,0,0,2023-09-11T17:19:29.000Z,2023-09-11T17:19:29.000Z,uqtr.mesxqq,uqtr,,,,
+10.5281/zenodo.4761307,"Fig. 27 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 27. Dictyogenus muranyii sp. n., adult female habitus. Karstic spring of Bruyant, Isère dpt, France. Photo G. Vinçon.",mds,True,findable,0,0,2,0,0,2021-05-14T07:45:23.000Z,2021-05-14T07:45:24.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.6084/m9.figshare.24202750,Additional file 2 of Obstructive sleep apnea: a major risk factor for COVID-19 encephalopathy?,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 2: Supplemental Table 2. Comparison of patient characteristics at the time of COVID-19 onset and COVID-19 acute encephalopathy between definite OSA group and No OSA group.,mds,True,findable,0,0,0,0,0,2023-09-27T03:26:09.000Z,2023-09-27T03:26:10.000Z,figshare.ars,otjm,"Biophysics,Medicine,Cell Biology,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,Sociology,FOS: Sociology,Immunology,FOS: Clinical medicine,Cancer,Mental Health,Virology","[{'subject': 'Biophysics'}, {'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Mental Health'}, {'subject': 'Virology'}]",['28280 Bytes'],
+10.5281/zenodo.3899776,COP21: Results and Implications for Pathways and Policies for Low Emissions European Societies,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This database contains national and global level modelling scenario results produced under the COP21:RIPPLES project https://www.cop21ripples.eu/ The data is also hosted in the IIASA RIPPLES Scenario Explorer https://data.ene.iiasa.ac.at/cop21ripples/#/login The National Determined Contributions (NDCs) provide important indications regarding the future GHG emissions and related policies, in relation to the international energy market, technological, economic, trade and financial context. This key information on the development trajectories of major economies is essential for EU policy development as it will determine the global context in which EU policies will evolve. Nevertheless, the NDCs adopt a medium-term horizon and do not provide all the required information to fully characterize the detailed energy system pathways that meet the Paris Agreement (PA) goals. NDCs therefore fall short of characterizing the global trajectories at a sufficiently granular and long-term perspective for informing EU policies. To close this knowledge gap, COP21:RIPPLES aims at analysing the underlying transformations required in the different sectors of the economy to meet the PA mitigation targets. To this purpose, COP21:RIPPLES uses existing scenarios as well as a number of new national and global scenarios. These new scenarios are not conceived themselves as an output of the project but rather as methodological tool to answer specific questions across different Work Packages. For description of the models and scenarios included in each Excel file, see the documentation ""RIPPLES_ScenarioExplorer_Doc_v4.docx"". For more information on these models and scenarios, see the COP21:RIPPLES Deliverables D2.6, D3.2 and D3.5.",mds,True,findable,0,0,0,0,0,2020-06-18T08:20:59.000Z,2020-06-18T08:21:00.000Z,cern.zenodo,cern,RIPPLES,[{'subject': 'RIPPLES'}],,
+10.5281/zenodo.7982058,"FIGURES C16–C21 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,Open Access,"FIGURES C16–C21. Leuctra signifera, nymphs (Julian Alps, Slovenia). C16, wingpads on edge of meso-and metanotum, dorsal view; C17, head and pronotum, dorsal view; C18, pronotum, dorsal view; C19, hind leg, lateral view; C20, abdominal tergites, dorsal view; C21, abdominal tergites, lateral view.",mds,True,findable,0,0,0,3,0,2023-05-29T13:44:09.000Z,2023-05-29T13:44:10.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.34847/nkl.ca709965,Du village à l'écran,NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,fr,Audiovisual,,"Par un atelier de découverte de l'image, du son et du cinéma, les enfants des écoles ont construit un film avec le collectif Regards des lieux. De la maternelle au CM2, de Gavet à Livet, les enfants nous racontent comment ils habitent leur village. Comment vit-on à Livet quand on est enfant ? Comment regarde-t-on le village ?
+
+Production Regards des lieux, Laure Nicoladze, Jérémie Lamouroux (vidéaste), Martin Debisschop (musicien), Automne 2019. 13 min. 30 sec.
+
+Avec l'ensemble des élèves des écoles de Gavet et Rioupéroux, les équipes éducatives et deux témoins
+
+Soutien : DRAC Auvergne Rhône Alpes, Conseil général de l'Isère, DAAC Grenoble, L'archipel des Utopies, Fondation Grandir en Culture, Ville de Grenoble, Conseil départemental de l'Isère""",api,True,findable,0,0,0,0,0,2023-10-03T09:08:38.000Z,2023-10-03T09:08:38.000Z,inist.humanum,jbru,"Voix,Poèmes en prose,""Mémoires des lieux,histoire orale,histoires de vie,enquêtes de terrain (ethnologie),Désindustrialisation,Patrimoine industriel,Pollution de l'air,Montagnes – aménagement,Énergie hydraulique,Rives – aménagement,Romanche, Vallée de la (France),Keller, Charles Albert (1874-1940 , Ingénieur A&M),patrimoine immatériel,Conditions de travail,classe ouvrière,Entretien, photos d'archives (cartes postales), Enfants -- Loisirs,cours d'école,Aliments sauvages,Petits commerces","[{'lang': 'fr', 'subject': 'Voix'}, {'lang': 'fr', 'subject': 'Poèmes en prose'}, {'lang': 'fr', 'subject': '""Mémoires des lieux'}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'histoires de vie'}, {'lang': 'fr', 'subject': 'enquêtes de terrain (ethnologie)'}, {'lang': 'fr', 'subject': 'Désindustrialisation'}, {'lang': 'fr', 'subject': 'Patrimoine industriel'}, {'lang': 'fr', 'subject': ""Pollution de l'air""}, {'lang': 'fr', 'subject': 'Montagnes – aménagement'}, {'lang': 'fr', 'subject': 'Énergie hydraulique'}, {'lang': 'fr', 'subject': 'Rives – aménagement'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'Keller, Charles Albert (1874-1940 , Ingénieur A&M)'}, {'lang': 'fr', 'subject': 'patrimoine immatériel'}, {'lang': 'fr', 'subject': 'Conditions de travail'}, {'lang': 'fr', 'subject': 'classe ouvrière'}, {'lang': 'fr', 'subject': ""Entretien, photos d'archives (cartes postales), Enfants -- Loisirs""}, {'lang': 'fr', 'subject': ""cours d'école""}, {'lang': 'fr', 'subject': 'Aliments sauvages'}, {'lang': 'fr', 'subject': 'Petits commerces'}]",['450108772 Bytes'],['video/mp4']
+10.5281/zenodo.6760050,"Dataset related to the study ""Black carbon and dust alter the response of mountain snow cover under climate change""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the data of the manuscript ""Black carbon and dust alter the response of mountain snow cover under climate change"" under publication in Nature Communication. It is made of a dataset and information to reproduce the simulations presented in the study.",mds,True,findable,0,0,0,0,0,2022-06-27T13:41:35.000Z,2022-06-27T13:41:35.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7524580,Bulgarian Translation of Researcher Mental Health and Well-being Manifesto - МанифеÑÑ‚ за пÑихичното здраве и благоÑÑŠÑтоÑнието на изÑледователÑ,Zenodo,2023,bg,Other,"Creative Commons Attribution 4.0 International,Open Access","ДейноÑтта ReMO COST е мрежа от заинтереÑовани Ñтрани от вÑички нива на научноизÑледователÑката общноÑÑ‚, коÑто изготви МанифеÑÑ‚ за пÑихичното здраве и благополучие на изÑледователите, в който Ñе призовава за оценка на това как пÑихичното здраве и благополучие на изÑледователите могат да бъдат най-добре подхранвани и поддържани чрез дейÑÑ‚Ð²Ð¸Ñ Ð¸ инициативи на политичеÑко, инÑтитуционално, общноÑтно и индивидуално ниво. Този манифеÑÑ‚ призовава вÑички заинтереÑовани Ñтрани в научноизÑледователÑката екоÑиÑтема да Ñе включат в разработването на политики, които да наблюдават, подобрÑват и поддържат благоÑÑŠÑтоÑнието и пÑихичното здраве в научноизÑледователÑката Ñреда, като очертават по-обхватни показатели за уÑпех и качеÑтво, подкрепÑÑ‚ баланÑа между профеÑÐ¸Ð¾Ð½Ð°Ð»Ð½Ð¸Ñ Ð¸ Ð»Ð¸Ñ‡Ð½Ð¸Ñ Ð¶Ð¸Ð²Ð¾Ñ‚, приобщаването и уÑтойчивата кариера на изÑледователите, благоприÑÑ‚Ñтваща ÑемейÑтвата. The English Language Version of the Manifesto can be found at: https://doi.org/10.5281/zenodo.5559805",mds,True,findable,0,0,0,0,0,2023-01-11T10:03:38.000Z,2023-01-11T10:03:38.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.d2547d810,Adult survival in migratory caribou is negatively associated with MHC functional diversity,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"The genes of the major histocompatibility complex (MHC) are involved in acquired, specific immunity in vertebrates. Yet, only a few studies have investigated the fitness consequences of MHC gene diversity in wild populations. Here, we looked at the association between annual survival and body mass and MHC-DRB exon 2 (MHC-DRB) genetic diversity, obtained from high-throughput sequencing, in two declining migratory caribou (Rangifer tarandus) herds. To disentangle the potential direct and general effects of MHC-DRB genetic diversity, we compared different indices of diversity that were either based on DNA-sequence variation or on physicochemical divergence of the translated peptides, covering a gradient of allelic to functional diversity. We found that i) body mass was not related to MHC-DRB diversity or genotype and that ii) adult survival probability was negatively associated with PAM distance, a corrected distance that considers the likelihood of each amino acid substitution to be accepted by the processes of natural selection. In addition, we found no evidence of fluctuating selection in time on MHC-DRB. We concluded that direct effects were involved in the negative relationship between MHC functional diversity and survival, although the mechanism underlying this result remains unclear. A possible explanation could be that individuals with higher MHC diversity suffer higher costs of immunity (immunopathology). Further studies are needed to investigate this hypothesis. Our results suggest that genetic diversity is not always beneficial even in genes that are supposed to be strongly shaped by balancing selection.",mds,True,findable,184,20,0,0,0,2020-07-23T23:21:43.000Z,2020-07-23T23:21:45.000Z,dryad.dryad,dryad,,,['40773 bytes'],
+10.5281/zenodo.5647786,Kerr reversal in Josephson meta-material and traveling wave parametric amplification datasets,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains raw data for results presented in article ""Kerr reversal in Josephson meta-material and traveling wave parametric amplification"" (Preprint : arXiv:2101.05815). All data is stored in numpy(numpy.org) array format. <strong>Please site any usage to original publication.</strong> <br> # Gain data The data used for generating Fig. 3(a) of main text:<br> <br> - Gain_6_freq contains frequency axis, gain_6 contains corresponding gain data when the device is pumped at 6 GHz<br> <br> - Gain_8_freq contains frequency axis, gain_8 contains corresponding gain data when the device is pumped at 8 GHz<br> <br> - Gain_10_freq contains frequency axis, gain_10 contains corresponding gain data when the device is pumped at 10 GHz <br> # Saturation data The data used for generating Fig. 3(d) of main text: - saturation_6_pow contains input signal power at 6.05 GHz and saturation_6_gain contains gain as a function of the same when device is pumped at 8 GHz. - saturation_9.5_pow contains input signal power at 9.5 GHz and saturation_9.5_gain contains gain as a function of the same when device is pumped at 8 GHz. <br> # Noise data The raw data used for fitting noise performance of the TWPA as depicted in Fig. 4 of main text: - noise_without_TWPA_temperature : contains noise temperature of the amplification chain without TWPA, in<br> Kelvin.<br> - noise_without_TWPA_sys_gain_dB : contains gain of the amplification chain without TWPA, in dB. - noise_freq : contains frequency axis for the measured PSD. - noise_thermal_source_temperature : contains temperature data of the thermal noise source. - noise_with_TWPA_PSD_vs_thermal_source_temperature : contains PSD measured with 200 MHz RBW as a function<br> of frequency and temperature of thermal noise source. <br> # Transmission data Normalized transmission through the device. - transmission_flux : contains quantized flux axis for the measured transmission. - transmission_freq : contains frequency axis for the measured transmission. - transmission : contains transmission as a function of frequency and quantized flux, in dB. <br> # Dispersion data Dispersion through the device. - dispersion_freq : contains frequency axis for the measured dispersion. - dispersion_phase_PCB : contains phase accumulation when RF switch is in PCB position as a function of<br> frequency, in radians.<br> - dispersion_flux_mA : contains flux axis for the measured dispersion, in mA. - dispersion_phase_device : contains phase accumulation when RF switch is in device position as a function<br> of frequency and flux, in radians.",mds,True,findable,0,0,0,0,0,2021-12-02T18:17:16.000Z,2021-12-02T18:17:17.000Z,cern.zenodo,cern,,,,
+10.57745/52ht2l,BERGER-SPAZM,Recherche Data Gouv,2022,,Dataset,,Simulations hydrologiques du bassin de l'Arvan réalisées avec le modèle hydrologique semi-distribué J2000 et les forçages atmosphériques SPAZM. Pour le maillage du modèle hydrologique se référer au dépot : https://doi.org/10.57745/RZ1LWK,mds,True,findable,64,2,0,0,0,2022-09-10T09:31:06.000Z,2022-09-10T09:32:26.000Z,rdg.prod,rdg,,,,
+10.6084/m9.figshare.c.6592858,Critically ill severe hypothyroidism: a retrospective multicenter cohort study,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Severe hypothyroidism (SH) is a rare but life-threatening endocrine emergency. Only a few data are available on its management and outcomes of the most severe forms requiring ICU admission. We aimed to describe the clinical manifestations, management, and in-ICU and 6-month survival rates of these patients. Methods We conducted a retrospective, multicenter study over 18 years in 32 French ICUs. The local medical records of patients from each participating ICU were screened using the International Classification of Disease 10th revision. Inclusion criteria were the presence of biological hypothyroidism associated with at least one cardinal sign among alteration of consciousness, hypothermia and circulatory failure, and at least one SH-related organ failure. Results Eighty-two patients were included in the study. Thyroiditis and thyroidectomy represented the main SH etiologies (29% and 19%, respectively), while hypothyroidism was unknown in 44 patients (54%) before ICU admission. The most frequent SH triggers were levothyroxine discontinuation (28%), sepsis (15%), and amiodarone-related hypothyroidism (11%). Clinical presentations included hypothermia (66%), hemodynamic failure (57%), and coma (52%). In-ICU and 6-month mortality rates were 26% and 39%, respectively. Multivariable analyses retained age > 70 years [odds ratio OR 6.01 (1.75–24.1)] Sequential Organ-Failure Assessment score cardiovascular component ≥ 2 [OR 11.1 (2.47–84.2)] and ventilation component ≥ 2 [OR 4.52 (1.27–18.6)] as being independently associated with in-ICU mortality. Conclusions SH is a rare life-threatening emergency with various clinical presentations. Hemodynamic and respiratory failures are strongly associated with worse outcomes. The very high mortality prompts early diagnosis and rapid levothyroxine administration with close cardiac and hemodynamic monitoring.",mds,True,findable,0,0,0,0,0,2023-04-13T14:55:41.000Z,2023-04-13T14:55:41.000Z,figshare.ars,otjm,"Medicine,Neuroscience,Pharmacology,Immunology,FOS: Clinical medicine,Cancer","[{'subject': 'Medicine'}, {'subject': 'Neuroscience'}, {'subject': 'Pharmacology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}]",,
+10.5281/zenodo.3340631,Server-side I/O request arrival traces,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset generated for the ""<strong>On server-side file access pattern matching</strong>"" paper (Boito et al., HPCS 2019). The traces were obtained following the methodology described in the paper. In addition to the two data sets discussed in the paper, we are also making available an extra data set of server traces. <strong>Traces from I/O nodes</strong> IOnode_traces/output/commands has the list of commands used to generate them. Each test is identified by a label, and the test_info.csv file contains the mapping of labels to access patterns. Some files include information about experiments with 8 I/O nodes, but these were removed from the data set because they had some errors. IOnode_traces/output contains .map files that detail the mapping of clients to I/O nodes for each experiment, and .out files, which contain the output of the benchmark. IOnode_traces/ contains one folder per experiment. Inside this folder, there is one folder per I/O node, and inside these folders there are tracefiles for the read and write portions of the experiments. Due to a mistake during the integration between IOFSL and AGIOS, read requests appear as ""W"", and writes as ""R"". Once accounted for when processing the traces, that has no impact on results. pattern_length.csv contains the average pattern length for each experiment and operation (average number of requests per second), obtained with the get_pattern_length.py script. Each line of a trace looks like this: <code>277004729325 00000000eaffffffffffff1f729db77200000000000000000000000000000000 W 0 262144</code> The first number is an internal timestamp in nanoseconds, the second value is the file handle, and the third is the type of the request (inverted, ""W"" for reads and ""R"" for writes). The last two numbers give the request offset and size in bytes, respectively. <strong>Traces from parallel file sytem data servers</strong> These traces are inside the server_traces/ folder. Each experiment has two concurrent applications, ""app1"" and ""app2"", and its traces are inside a folder named accordingly: <code>NOOP\_app1\_(identification of app1)\_app2\_(identification of app2)\_(repetition)\_pvfstrace/</code> Each application is identified by: <code>(contig/noncontig)\_(number and size of requests per process)\_(number of processes)\_(number of client machines)\_(nto1/nton regarding the number of files)</code> Inside each folder there are eight trace files, two per data server, one for the read portion and another for the write portion. Each line looks like this: <code>[D 02:54:58.386900] REQ SCHED SCHEDULING, handle: 5764607523034231596, queue_element: 0x2a11360, type: 0, offset: 458752, len: 32768</code> The part between [] is a timestamp, ""handle"" gives the file handle, ""type"" is 0 for reads and 1 for writes, ""offset"" and ""len"" (length) are in bytes. server_traces/pattern_length.csv contains the average pattern length for each experiment and operation, obtained with the server_traces/count_pattern_length.py script. <strong>Extra traces from data servers</strong> These traces were not used for the paper because we do not have performance measurements for them with different scheduling policies, so it would not be possible to estimate the results of using the pattern matching approach to select scheduling policies. Still, we share them in the extra_server_traces/ folder in the hope they will be useful. They were obtained in the same experimental campaign than the other data server traces, and have the same format. The difference is that these traces are for single-application scenarios.",mds,True,findable,0,0,0,0,0,2019-07-18T08:17:36.000Z,2019-07-18T08:17:37.000Z,cern.zenodo,cern,"high performance computing,parallel file system,i/o forwarding,parallel I/O,traces,file access,I/O requests","[{'subject': 'high performance computing'}, {'subject': 'parallel file system'}, {'subject': 'i/o forwarding'}, {'subject': 'parallel I/O'}, {'subject': 'traces'}, {'subject': 'file access'}, {'subject': 'I/O requests'}]",,
+10.57745/qcvyg3,Long-term monitoring of near-surface soil temperature in mountain ecosystems of the LTSER Lautaret-Oisans,Recherche Data Gouv,2023,,Dataset,,"Monitoring of near-surface soil temperature in seasonaly snow-covered, mountain ecosystems located in the Lautaret-Galibier area of the French Alps. Data are part of a long-term monitoring programs examining the impact of climate change on snow cover dynamics, microclimate, species distribution and ecosystem functioning. Data include a GPS position, a date and time in UTC and a near-surface soil temperature (in °C) measured at 5 cm belowground using stand-alone temperature data logger.",mds,True,findable,20,1,0,0,0,2023-03-27T13:48:28.000Z,2023-07-18T08:18:09.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.1112342,"Database Of Weeds In Cultivation Fields Of France And Uk, With Ecological And Biogeographical Information",Zenodo,2017,en,Dataset,"Creative Commons Attribution 4.0,Open Access","The database includes a list of 1577 weed plant taxa found in cultivated fields of France and UK, along with basic ecological and biogeographical information.<br>
+The database is a CSV file in which the columns are separated with comma, and the decimal sign is ""."".<br>
+It can be imported in R with the command ""tax.discoweed <- read.csv(""tax.discoweed_18Dec2017_zenodo.csv"", header=T, sep="","", dec=""."", stringsAsFactors = F)""
+
+Taxonomic information is based on TaxRef v10 (Gargominy et al. 2016),<br>
+- 'taxref10.CD_REF' = code of the accepted name of the taxon in TaxRef,<br>
+- 'binome.discoweed' = corresponding latine name,<br>
+- 'family' = family name (following APG III),<br>
+- 'taxo' = taxonomic rank of the taxon, either 'binome' (species level) or 'infra' (infraspecific level),<br>
+- 'binome.discoweed.noinfra' = latine name of the superior taxon at species level (different from 'binome.discoweed' for infrataxa),<br>
+- 'taxref10.CD_REF.noinfra' = code of the accepted name of the superior taxon at species level.
+
+The presence of each taxon in one or several of the following data sources is reported:<br>
+- Species list from a reference flora (observations in cultivated fields over the long term, without sampling protocol),<br>
+* 'jauzein' = national and comprehensive flora in France (Jauzein 1995),<br>
+- Species lists from plot-based inventories in cultivated fields,<br>
+* 'za' = regional survey in 'Zone Atelier Plaine & Val de Sèvre' in SW France (Gaba et al. 2010),<br>
+* 'biovigilance' = national survey of cultivated fields in France (Biovigilance, Fried et al. 2008),<br>
+* 'fse' = Farm Scale Evaluations in England and Scotland, UK (Perry, Rothery, Clark et al., 2003),<br>
+* 'farmbio' = Farm4Bio survey, farms in south east and south west of England, UK (Holland et al., 2013)<br>
+- Reference list of segetal species (species specialist of arable fields),<br>
+* 'cambacedes' = reference list in France (Cambacedes et al. 2002)
+
+Life form information is extracted from Julve (2014) and provided in the column 'lifeform'.<br>
+The classification follows a simplified Raunkiaer classification (therophyte, hemicryptophyte, geophyte, phanerophyte-chamaephyte and liana). Regularly biannual plants are included in hemicryptophytes, while plants that can be both annual and biannual are assigned to therophytes.
+
+Biogeographic zones are also extracted from Julve (2014) and provided in the column 'biogeo'.<br>
+The main categories are 'atlantic', 'circumboreal', 'cosmopolitan, 'Eurasian', 'European', 'holarctic', 'introduced', 'Mediterranean', 'orophyte' and 'subtropical'.<br>
+In some cases, a precision is included within brackets after the category name. For instance, 'introduced(North America)' indicates that the taxon is introduced from North America.<br>
+In addition, some taxa are local endemics ('Aquitanian', 'Catalan', 'Corsican', 'corso-sard', 'ligure', 'Provencal').<br>
+A single taxon is classified 'arctic-alpine'.
+
+Red list status of weed taxa is derived for France and UK:<br>
+- 'red.FR' is the status following the assessment of the French National Museum of Natural History (2012),<br>
+- 'red.UK' is based on the Red List of vascular plants of Cheffings and Farrell (2005), last updated in 2006.<br>
+The categories are coded following the IUCN nomenclature.
+
+A habitat index is provided in column 'module', derived from a network-based analysis of plant communities in open herbaceous vegetation in France (Divgrass database, Violle et al. 2015, Carboni et al. 2016).<br>
+The main habitat categories of weeds are coded following the Divgrass classification,<br>
+- 1 = Dry calcareous grasslands<br>
+- 3 = Mesic grasslands<br>
+- 5 = Ruderal and trampled grasslands<br>
+- 9 = Mesophilous and nitrophilous fringes (hedgerows, forest edges...)<br>
+Taxa belonging to other habitats in Divgrass are coded 99, while the taxa absent from Divgrass have a 'NA' value.
+
+Two indexes of ecological specialization are provided based on the frequency of weed taxa in different habitats of the Divgrass database.<br>
+The indexes are network-based metrics proposed by Guimera and Amaral (2005),<br>
+- c = coefficient of participation, i.e., the propensity of taxa to be present in diverse habitats, from 0 (specialist, present in a single habitat) to 1 (generalist equally represented in all habitats),<br>
+- z = within-module degree, i.e., a standardized measure of the frequency of a taxon in its habitat; it is negatve when the taxon is less frequent than average in this habitat, and positive otherwise; the index scales as a number of standard deviations from the mean.",,True,findable,0,0,0,1,0,2017-12-18T19:02:27.000Z,2017-12-18T19:02:28.000Z,cern.zenodo,cern,"species pool,cultivated fields,specialization,biodiversity decline,sampling strategies","[{'subject': 'species pool'}, {'subject': 'cultivated fields'}, {'subject': 'specialization'}, {'subject': 'biodiversity decline'}, {'subject': 'sampling strategies'}]",,
+10.5281/zenodo.4680486,ARTURIA synthesizer sounds dataset,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains all data that have been used in:<br> Roche F., Hueber T., Garnier M., Limier S. and Girin L., 2021. ""Make That Sound More Metallic: Towards a Perceptually Relevant Control of the Timbre of Synthesizer Sounds Using Variational Autoencoder"". Transactions of the International Society for Music Information Retrieval.<br> <br> It is constituted of a .zip file containing 1,233 audio samples of synthesizer sounds generated using factory presets of ARTURIA software applications resulting in single pitched sounds (E3, ~165Hz) with a similar duration (between 2 and 2.5 seconds) and normalized in loudness.<br> <br> Audio files are monophonic in WAV format using a samplerate of 44.1kHz and a 32-bit encoding.",mds,True,findable,0,0,0,0,0,2021-04-12T12:32:45.000Z,2021-04-12T12:32:46.000Z,cern.zenodo,cern,"Machine Learning, music sound processing, timbre perception, psychoacoustics","[{'subject': 'Machine Learning, music sound processing, timbre perception, psychoacoustics'}]",,
+10.5281/zenodo.10037956,FIG. 2 in Passiflora tinifolia Juss. (Passiflora subgenus Passiflora): resurrection and synonymies,Zenodo,2023,,Image,Creative Commons Attribution 4.0 International,"FIG. 2. — Iconography of P. tinifolia Juss. from Guyana, according to Hooker et al. (1857).",api,True,findable,0,0,0,0,0,2023-10-24T17:26:29.000Z,2023-10-24T17:26:29.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5061/dryad.n230404,Data from: The regulation of emotions in adolescents: age differences and emotion-specific patterns,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"Two experiments addressed the issue of age-related differences and emotion-specific patterns in emotion regulation during adolescence. Experiment 1 examined emotion-specific patterns in the effectiveness of reappraisal and distraction strategies in 14-year-old adolescents (N = 50). Adolescents were instructed to answer spontaneously or to downregulate their responses by using either distraction or cognitive reappraisal strategies before viewing negative pictures and were asked to rate their emotional state after picture presentation. Results showed that reappraisal effectiveness was modulated by emotional content but distraction was not. Reappraisal was more effective than distraction at regulating fear or anxiety (threat-related pictures) but was similar to distraction regarding other emotions. Using the same paradigm, Experiment 2 examined in 12-year-old (N = 56), 13-year-old (N = 49) and 15-year-old adolescents (N = 54) the age-related differences a) in the effectiveness of reappraisal and distraction when implemented and b) in the everyday use of regulation strategies using the Cognitive Emotion Regulation Questionnaire. Results revealed that regulation effectiveness was equivalent for both strategies in 12-year-olds, whereas a large improvement in reappraisal effectiveness was observed in 13- and 15-year-olds. No age differences were observed in the reported use of reappraisal, but older adolescents less frequently reported using distraction and more frequently reported using the rumination strategy. Taken together, these experiments provide new findings regarding the use and the effectiveness of cognitive regulation strategies during adolescence in terms of age differences and emotion specificity.",mds,True,findable,383,55,1,1,0,2018-03-29T07:56:34.000Z,2018-03-29T07:56:35.000Z,dryad.dryad,dryad,"distraction,Adolescents,reappraisal","[{'subject': 'distraction'}, {'subject': 'Adolescents', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'reappraisal'}]",['87637 bytes'],
+10.5281/zenodo.7560290,Ressources for End-to-End French Text-to-Speech Blizzard challenge,Zenodo,2023,fr,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Here are 289 chapters of 5 audiobooks from Librivox (51:12) read by Nadine Eckert-Boulet (NEB): Madame Bovary (MB) by Gustave Flaubert (FL) - 3 volumes, 35 chapters<br> (original wavs; text) Les mystères de Paris (LMP) by Eugene Sue (ES) - 4 volumes, 83 chapters (original wavs1, wavs2, wavs3; text1, text2, text3) Les tribulations d'un chinois en Chine (TCC) by Jules Verne (JV) - 1 volume, 22 chapters (original wavs; text) La fille du pirate (LFDP) by Henri Émile Chevalier (EC) - 7 volumes, 121 chapters (original wavs, text) La vampire (VAMP) by Paul Féval (PF) - 1 volume, 28 chapters (original wavs, text) and 2515 utterances (2:03) read by another female French speaker Aurélie Derbier (AD): 1608 utterances extracted from various books (DIVERS_BOOK_AD*) 907 transcripts of the sessions of the French parliament (DIVERS_PARL_01*) Each .wav file (sampled at 22050Hz) corresponds to one entire chapter. The format of the filenames is:<br> {author's acronym}_{book's acronym}_{reader's acronym}_{volume's number}_{chapter's number} The NEB_train.csv file gives text and phonetic alignments (essentially for MB and LMP) for utterances in 4 fields separated by '|':<br> {filename}|{start_ms}|{end_ms}|{text or phonetic content}. Most utterances are separated by at least a pause of 400ms. The intervals [start_ms:end_ms] comprise leading and trailing silences of 130ms (since wavs are entire chapters, these silences are ""true"" ambient silences). Same for AD_train.csv. When phonetic alignment has been performed, 2 additional fields have been added: {aligned phones}|{durations in ms}. Each input character or phone has a corresponding aligned phone and a duration. Note that all aligned utterances start and end with an aligned phone of 130ms. The set of aligned phones comprises: The set of input phones The silence: '__' The symbol '_' for silent characters, e.g. ""chat"" is aligned with 's^ _ a _' 29 combined aligned phones ('a&i', 'a&j', 'b&q', 'd&q','d&z', 'd&z^', 'f&q', 'g&q', 'g&z', 'j&i', 'j&u', 'j&q', 'i&j', 'k&q', 'k&s', 'k&s&q', 'l&q', 'm&q', 'n&q', 'r&w', 'r&q', 's&q', 't&q', 't&s', 't&s^', 'w&a', 'z&q', 'p&q') that align to only one character, e.g. ""expatrier"" is aligned with 'e^ k&s p a t r i&j e _' Text is in UTF8. '«»','¬', '~','""""','()','[]' are respectively used for speaking quotes, turn switches, three dots, quoted expression, aside quotes, notes. Because of rare occurrences, 'ö' has been transcribed as 'oe'. Paragraphs (two consecutive carriage returns in the original text) are cued by a special character '§'. It usually ends an utterance but could be used within an utterance if its associated pause is too short. When available, phonetic content is given per word in curly brackets '{}'. We use 39 phonetic symbols: <strong>oral vowels</strong>: a (f<strong><em>a</em></strong>), e (f<em><strong>ée</strong></em>), e^ (f<em><strong>ait</strong></em>), x (f<em><strong>eu</strong></em>), x^ (c<em><strong>oeu</strong></em>r), i (r<em><strong>iz</strong></em>), y (f<em><strong>ut</strong></em>), u (f<em><strong>ou</strong></em>), o (f<em><strong>aux</strong></em>), o^ (p<strong><em>o</em></strong>rc) <strong>schwa</strong>: q (gag<strong><em>e</em></strong>) <strong>nasal vowels</strong>: a~ (r<strong><em>an</em></strong>g), e~ (f<em><strong>in</strong></em>), x~ (<strong><em>un</em></strong>), o~ (r<em><strong>on</strong></em>d) <strong>semi-vowels</strong>: h (h<em><strong>u</strong></em>it), w (<strong><em>ou</em></strong>ate), j (h<em><strong>i</strong></em>er) <strong>consonants</strong>: p (<em><strong>p</strong></em>as), t (<strong><em>t</em></strong>as), k (<em><strong>c</strong></em>as), b (<strong><em>b</em></strong>as), d (<em><strong>d</strong></em>os), g (<em><strong>g</strong></em>ars), f (<em><strong>f</strong></em>aux), s (<strong><em>s</em></strong>ot) , s^ (<strong><em>ch</em></strong>at), v (<strong><em>v</em></strong>u), z (<strong><em>z</em></strong>ut), z^ (<em><strong>j</strong></em>us), r (<strong><em>r</em></strong>iz), l (<em><strong>l</strong></em>a), m (<strong><em>m</em></strong>a), n (<strong><em>n</em></strong>on), n~ (oi<strong><em>gn</em></strong>on), ng (campi<em><strong>ng</strong></em>)",mds,True,findable,0,0,0,0,0,2023-01-23T09:41:39.000Z,2023-01-23T09:41:40.000Z,cern.zenodo,cern,"Audiobooks,text,phonetics,speech synthesis,end-to-end","[{'subject': 'Audiobooks'}, {'subject': 'text'}, {'subject': 'phonetics'}, {'subject': 'speech synthesis'}, {'subject': 'end-to-end'}]",,
+10.5281/zenodo.2581296,Dirac gaugino benchmark points from arXiv:1812.09293,Zenodo,2018,,Dataset,"Creative Commons Attribution Non Commercial Share Alike 4.0 International,Open Access","<strong>Benchmark points, in SUSY Les Houches Accord (SLHA) format</strong>, from the paper ""LHC limits on gluinos and squarks in the minimal Dirac gaugino model"", <strong>arXiv:1812.09293</strong>; for 2 TeV gluino and 2.6 TeV squark masses.
+
+We also provide the <strong>UFO</strong> and <strong>SPheno models</strong> (exported from SARAH), and the SPheno <strong>input files</strong> for creating the DG benchmark points. For usage in SPheno, expand DiracGauginos_SPheno.zip to a folder ""DiracGauginos"" in the SPheno root directory and compile with
+
+ <code>make Model=DiracGauginos</code>
+
+This produces the library <code>./lib/libSPhenoDiracGauginos.a</code> and the executable <code>./bin/SPhenoDiracGauginos</code>. (Tested with SPheno-4.0.3)
+
+Note that compared to the version exported from SARAH, we have changed <code>InputOutput.f90</code> to have an SLHA1-like ordering of the squarks, so that, for instance, PDG 1000006 is always the lighter stop.
+
+The two additional scripts provided serve to add the QNUMBERS blocks and change ""DECAY1L"" to ""DECAY"" in the SLHA files. This is necessary for event generation with MadGraph5 / Pythia.",mds,True,findable,0,0,0,0,0,2019-03-01T14:11:08.000Z,2019-03-01T14:11:08.000Z,cern.zenodo,cern,"LHC,supersymmetry,reinterpretation","[{'subject': 'LHC'}, {'subject': 'supersymmetry'}, {'subject': 'reinterpretation'}]",,
+10.5281/zenodo.3568739,Magnetism and anomalous transport in the Weyl semimetal PrAlGe: Possible route to axial gauge fields,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The file ManuscriptDataFiles.7z contains the raw experimental data from which the figures are made in the manuscript entitled ""Magnetism and anomalous transport in the Weyl semimetal PrAlGe: Possible route to axial gauge fields"" that appeared in npj Quantum Materials <strong>5</strong>, 5 (2020). Paper Abstract: In magnetic Weyl semimetals, where magnetism breaks time-reversal symmetry, large magnetically sensitive anomalous transport responses are anticipated that could be useful for topological spintronics. The identification of new magnetic Weyl semimetals is therefore in high demand, particularly since in these systems Weyl node configurations may be easily modified using magnetic fields. Here we explore experimentally the magnetic semimetal PrAlGe, and unveil a direct correspondence between easy-axis Pr ferromagnetism and anomalous Hall and Nernst effects. With sizes of both the anomalous Hall conductivity and Nernst effect in good quantitative agreement with first principles calculations, we identify PrAlGe as a system where magnetic fields can connect directly to Weyl nodes via the Pr magnetization. Furthermore, we find the predominantly easy-axis ferromagnetic ground state co-exists with a low density of nanoscale textured magnetic domain walls. We describe how such nanoscale magnetic textures could serve as a local platform for tunable axial gauge fields of Weyl fermions.",mds,True,findable,0,0,0,0,0,2020-01-17T14:00:06.000Z,2020-01-17T14:00:07.000Z,cern.zenodo,cern,"magnetism, semimetal, Hall effect, magnetization, Nernst effect, neutron scattering Weyl","[{'subject': 'magnetism, semimetal, Hall effect, magnetization, Nernst effect, neutron scattering Weyl'}]",,
+10.5281/zenodo.4603774,Atomic coordinates of the periodic crystalline ice grain model,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This dataset contains the atomic coordinates in the crystallographic interchange format (CIF) of the periodic model of a proton-ordered water icy grain surface as resulted from the geometry optimization at B3LYP-D3/A-VTZ * level with the CRYSTAL17 computer code. The crystallographic unit cell has the c-axis arbitrary defined to be 30 Ã… to simulate the void upper/lower the icy surface.,mds,True,findable,0,0,0,0,0,2021-03-14T17:57:10.000Z,2021-03-14T17:57:11.000Z,cern.zenodo,cern,"Crystalline ice,CRYSTAL17,B3LYP-D3","[{'subject': 'Crystalline ice'}, {'subject': 'CRYSTAL17'}, {'subject': 'B3LYP-D3'}]",,
+10.5281/zenodo.8430044,Signature of quantum criticality in cuprates by charge density fluctuations,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","[This repository contains the raw data for the manuscript ""<strong>Signature of quantum criticality in cuprates by charge density fluctuations</strong>"" (arXiv:2208.13918)] The universality of the strange metal phase in many quantum materials is often attributed to the presence of a quantum critical point (QCP), a zero-temperature phase transition ruled by quantum fluctuations. In cuprates, where superconductivity hinders direct QCP observation, indirect evidence comes from the identification of fluctuations compatible with the strange metal phase. Here we show that the recently discovered charge density fluctuations (CDF) possess the right properties to be associated to a quantum phase transition. Using resonant x-ray scattering, we studied the CDF in two families of cuprate superconductors across a wide doping range (up to <em>p</em>=0.22). At <em>p</em>*≈0.19, the putative QCP, the CDF intensity peaks, and the characteristic energy Δ is minimum, marking a wedge-shaped region in the phase diagram indicative of a quantum critical behavior, albeit with anomalies. These findings strengthen the role of charge order in explaining strange metal phenomenology and provide insights into high-temperature superconductivity.",mds,True,findable,0,0,0,0,0,2023-10-11T08:50:54.000Z,2023-10-11T08:50:54.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.7017137.v2,Numerical simulations of a fluid sphere undergoing precession,figshare,2019,,Dataset,Creative Commons Attribution 4.0 International,"We provide a dataset of numerical simulation of fluid flow in precessing spheres.Some include magnetic field to asses whether the flows are dynamos or not.The dataset includes the simulations from papers linked in refereces below. Please also cite them if you use this dataset.<br>We cover a wide range of the parameter space, pushing towards planetary values to the limits of current super-computer capabilities.<br>We include a python notebook (jupyter) to work with the dataset.<br><b>WARNING: </b>the first<b> </b>version of this database had some errors and inconsistencies. Please use the more recent revision.<br><b></b><br>",mds,True,findable,0,0,0,0,0,2019-01-29T14:10:51.000Z,2019-01-29T14:10:52.000Z,figshare.ars,otjm,"Planetary Science,40403 Geophysical Fluid Dynamics,FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences,91501 Computational Fluid Dynamics,FOS: Other engineering and technologies,FOS: Other engineering and technologies,40406 Magnetism and Palaeomagnetism","[{'subject': 'Planetary Science'}, {'subject': '40403 Geophysical Fluid Dynamics', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '91501 Computational Fluid Dynamics', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Other engineering and technologies', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'FOS: Other engineering and technologies', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '40406 Magnetism and Palaeomagnetism', 'subjectScheme': 'FOR'}]",['447069 Bytes'],
+10.5281/zenodo.6573845,Experiments on a single large particle segregating in bedload transport,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This depository contains all the data presented in ""Experiments on a single large particle segregating in bedload transport"" from H. Rousseau, J. Chauchat and P. Frey in Physical Review Fluids, as well as the code to read these data. There are 10 folders that each correspond to a configuration (i.e. size ratio and Shields number). These folders contain subfolders that correspond to the different repetitions we made for each configuration. In a subfolder, one can find:<br> - The first image of the experiment (t=0s).<br> - An hdf5 file called ""bedAndWaterLines.h5"" which contains the data for the waterline positions and the bedline positions with time.<br> - An hdf5 file called ""frame_0_to_3000_with_step_1_and_shift_1.hdf5"" which contains the granular bed velocity fields Ux and Uy interpolated over the time. These velocities have been obtained using the OpyFlow toolbox (https://github.com/groussea/opyflow.git).<br> - An hdf5 file called ""DataTracked.h5"" which contains the results from the detection of the intruder. Inside ""DataTracked.h5"", one can find one folder by timestep that includes the coordinates of the intruder. The total number of frame, the acquisition rate and the scale are also saved as datasets in ""DataTracked.h5"". The code ""plotData.py"" has been coded in python3 and allows one to read the data from the hdf5 files (make sure you installed the h5py package for python before). ""plotData.py"" is annotated and thus, it contains all the instructions to plot the data of a given repetition. It is based on the following classes:<br> - ""LoadResult"" that reads ""DataTracked.h5""<br> - ""loadWaterAndBed"" that reads ""bedAndWaterLines.h5""<br> - ""readOpyf"" that reads ""frame_0_to_3000_with_step_1_and_shift_1.hdf5"" The file ""listRepetitions.ods"" is also provided. It allows one to match a given experiment in the paper to its name in this depository. Feel free to contact us if you need more info.",mds,True,findable,0,0,0,1,0,2022-05-23T16:16:41.000Z,2022-05-23T16:16:42.000Z,cern.zenodo,cern,"Granular physics,Grain-size segregation,Bedload transport,Sediment transport","[{'subject': 'Granular physics'}, {'subject': 'Grain-size segregation'}, {'subject': 'Bedload transport'}, {'subject': 'Sediment transport'}]",,
+10.6084/m9.figshare.23575366,Additional file 3 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 2,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:47.000Z,2023-06-25T03:11:48.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['28672 Bytes'],
+10.5281/zenodo.4761301,"Figs. 11-19 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 11-19. Dictyogenus jurassicum sp. n., larva. Karstic spring of Côte au Bouvier, near Soubey, canton of Jura, Switzerland. All images credited to J.-P.G. Reding. 11. Head and pronotum, dorsal view. 12. Lacinia. 13. Pronotum, dorso-lateral view. 14. Mesonotum and metanotum, dorso-lateral view. 15. Abdominal tergites, lateral view. 16. Medio-dorsal row of setae on base of cerci, lateral view. 17. Paragenital lobes, ventral view. 18. Tergites 5, 6 and 7, dorsal view. 19. Separation of tergites and sternites, lateral view.",mds,True,findable,0,0,6,0,0,2021-05-14T07:44:41.000Z,2021-05-14T07:44:42.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.5243180,Indonesian DBnary archive in original Lemon format,Zenodo,2021,id,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Indonesian language edition, ranging from 2nd June 2015 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T10:17:23.000Z,2021-08-24T10:17:25.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.8275263,"EW-ino scan points from ""SModelS v2.3: enabling global likelihood analyses"" paper",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Input SLHA and SModelS output (.smodels and .py) files from the paper ""SModelS v2.3: enabling global likelihood analyses"". The dataset comprises 18544 electroweak-ino scan points and can be used to reproduce all the plots presented in the paper. <strong>ewino_slha.tar.gz</strong> : input SLHA files including mass spectra, decay tables and cross sections <strong>ewino_smodels_v23_combSRs.tar.gz</strong> : SModelS v2.3 output with combineSRs=True and combineAnas = ATLAS-SUSY-2018-41,CMS-SUS-21-002 (primary v2.3 results used in section 4, Figs. 2-6) <strong>ewino_smodels_v23_bestSR.tar.gz</strong> : SModelS v2.3 output with combineSRs=False and combineAnas = ATLAS-SUSY-2018-41,CMS-SUS-21-002 (used only in Fig. 2) <strong>ewino_smodels_v21.tar.gz</strong> : SModelS v2.1 output with combineSRs=False (used only in Fig. 2) Changes w.r.t. version 1: removed 13 SLHA input files, which had wrong neutralino2 decays due to a bug in softsusy 4.1.11; recomputed smodels_v23_combSRs results with sigmacut=1e-3 fb. See comments on https://scipost.org/submissions/2306.17676v2/ for details.",mds,True,findable,0,0,0,0,0,2023-08-23T09:37:05.000Z,2023-08-23T09:37:05.000Z,cern.zenodo,cern,"large hadron collider, beyond the standard model, simplified models, supersymmetry, reinterpretation","[{'subject': 'large hadron collider, beyond the standard model, simplified models, supersymmetry, reinterpretation'}]",,
+10.6084/m9.figshare.23983487,Additional file 2 of Aberrant activation of five embryonic stem cell-specific genes robustly predicts a high risk of relapse in breast cancers,figshare,2023,,Dataset,Creative Commons Attribution 4.0 International,"Additional file 2: Table S1. List of genes with predominant expression in testis, placenta and/or embryonic stem cells. Table S2. Frequencies of ectopic activations of the tissue-specific genes. Table S3. Results of the validation step in the biomarker discovery pipeline. Table S4. Datasets of normal tissues and breast cancers with corresponding sample sizes. Table S5. List of normal tissues and the corresponding sample sizes.",mds,True,findable,0,0,0,0,0,2023-08-18T03:20:43.000Z,2023-08-18T03:20:44.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Genetics,FOS: Biological sciences,Molecular Biology,Biological Sciences not elsewhere classified,Information Systems not elsewhere classified,Mathematical Sciences not elsewhere classified,Developmental Biology,Cancer,Plant Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Biological Sciences not elsewhere classified'}, {'subject': 'Information Systems not elsewhere classified'}, {'subject': 'Mathematical Sciences not elsewhere classified'}, {'subject': 'Developmental Biology'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",['174460 Bytes'],
+10.5281/zenodo.7573372,Raw data supporting: Augmenting the Performance of Hydrogenase for Aerobic Photocatalytic Hydrogen Evolution via Solvent Tuning,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Raw experimental data supporting the article ""Augmenting the Performance of Hydrogenase for Aerobic Photocatalytic Hydrogen Evolution <em>via</em> Solvent Tuning""",mds,True,findable,0,0,0,0,0,2023-02-07T21:31:26.000Z,2023-02-07T21:31:27.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.n5tb2rbx9,Plant community impact on productivity: trait diversity or key(stone) species effects?,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Outside controlled experimental plots, the impact of community attributes on primary productivity has rarely been compared to that of individual species. Here, we identified plant species of high importance for productivity (key species) in >29,000 diverse grassland communities in the European Alps, and compared their effects with those of community-level measures of functional composition (weighted means, variances, skewness, and kurtosis). After accounting for the environment, the five most important key species jointly explained more deviance of productivity than any measure of functional composition alone. Key species were generally tall with high specific leaf areas. By dividing the observations according to distinct habitats, the explanatory power of key species and functional composition increased and key-species plant types and functional composition-productivity relationships varied systematically, presumably because of changing interactions and trade-offs between traits. Our results advocate for a careful consideration of species’ individual effects on ecosystem functioning in complement to community-level measures.",mds,True,findable,195,25,0,1,0,2022-01-20T21:27:27.000Z,2022-01-20T21:27:29.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['180222293 bytes'],
+10.5281/zenodo.5496375,Diagnosing the Eliassen-Palm flux from a quasi-geostrophic double gyre ensemble,Zenodo,2021,,Software,Open Access,No description provided.,mds,True,findable,0,0,0,0,0,2021-09-09T02:38:28.000Z,2021-09-09T02:38:29.000Z,cern.zenodo,cern,"Quasi-geostrophy,Eliassen-Palm flux,Ensemble modelling","[{'subject': 'Quasi-geostrophy'}, {'subject': 'Eliassen-Palm flux'}, {'subject': 'Ensemble modelling'}]",,
+10.15454/8uia76,Harmonized_Tree_Microhabitat_Dataset_Version_2020.03.30,Portail Data INRAE,2021,,Dataset,,"The datset describes observation of presence/absence of 11 groups of tree microhabitats on trees scatterred over Europe and Iran. Tree covariables are :species, DBH, management (last logging more/less 100 years) and site name.",mds,True,findable,65,10,0,1,0,2021-07-19T09:26:03.000Z,2021-07-19T09:49:32.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.3816663,Diffraction Images for the Crystal structure of CYP124 in complex with SQ109 (PDB ID: 6T0J),Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The archive contains <strong>2</strong> folders: <strong>data</strong> contains 2400 raw X-ray diffraction images <strong>proc</strong> contains input data for integration (XDS.INP and x[y]_geo_corr.CBF), integrated dataset (XDS_ASCII.HKL), input and output for scaling (XSCALE.INP and XSCALE.LP, respectively), scaled dataset: merged and not merged (scaled_merged.HKL and scaled_nonmerged.HKL, respectively) and structure factors with utilized R-free flags (f_obs.mtz) General information about the data collection: Beamline: ESRF ID23-1 Detector: PILATUS 6M-F Flux: 3.2e+10 ph/sec Energy (Wavelength): 12.755 keV (0.9720 Ã…) Oscillation: 0.15<sup>o</sup> Total range: 360<sup>o</sup> Transmition: 8.0% Exposure time: 0.1 s Detector Distance: 155.00 mm Resolution (corner): 1.08 Ã… (0.93 Ã…)",mds,True,findable,0,0,2,0,0,2020-05-08T10:27:13.000Z,2020-05-08T10:27:15.000Z,cern.zenodo,cern,"CYP124,Mycobacterium Tuberculosis,Tuberculosis,CYP124A1,Rv2266,Cytochrome P450,CYP,P450,Omega hydroxylase,Hydroxylase,SQ109,MmpL3,antitubercular","[{'subject': 'CYP124'}, {'subject': 'Mycobacterium Tuberculosis'}, {'subject': 'Tuberculosis'}, {'subject': 'CYP124A1'}, {'subject': 'Rv2266'}, {'subject': 'Cytochrome P450'}, {'subject': 'CYP'}, {'subject': 'P450'}, {'subject': 'Omega hydroxylase'}, {'subject': 'Hydroxylase'}, {'subject': 'SQ109'}, {'subject': 'MmpL3'}, {'subject': 'antitubercular'}]",,
+10.5281/zenodo.7872343,Eomys/pyleecan: 1.5.0,Zenodo,2023,,Software,Open Access,Loss models rework + tutorial (#558) Rework winding GUI (#616) Add new winding plot linear and radial ( #612) Miscellaneous improvements and bug correction (#614) UML generator using mermaid-js (#549) Rework class csv files (#611),mds,True,findable,0,0,0,0,0,2023-04-27T19:09:56.000Z,2023-04-27T19:09:56.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23737431.v1,Supplementary document for Flexible optical fiber channel modeling based on neural network module - 6356438.pdf,Optica Publishing Group,2023,,Text,Creative Commons Attribution 4.0 International,Supplement 1,mds,True,findable,0,0,0,0,0,2023-08-10T20:33:32.000Z,2023-08-10T20:33:33.000Z,figshare.ars,otjm,Uncategorized,[{'subject': 'Uncategorized'}],['549948 Bytes'],
+10.5281/zenodo.7796264,Dataset for Manuscript: Comparing Urban Anthropogenic NMVOC Measurements with Representation in Emission Inventories - A Global Perspective,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Urban observations of individual NMVOCs and the calculated or reported emission ratios used for comparison to emission inventories.,mds,True,findable,0,0,0,0,0,2023-04-03T19:35:52.000Z,2023-04-03T19:35:53.000Z,cern.zenodo,cern,"volatile organic compounds,NMVOCs,air pollution observations,urban,emission inventories","[{'subject': 'volatile organic compounds'}, {'subject': 'NMVOCs'}, {'subject': 'air pollution observations'}, {'subject': 'urban'}, {'subject': 'emission inventories'}]",,
+10.5281/zenodo.3689678,'Learning the production cross sections of the Inert Doublet Model' training data set.,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Training data set used in the ''Learning the production cross sections of the Inert Doublet Model'' subproject, made of 50000 samples with 5 input values (MH0, MA0, MHC, lam2, lamL) and 8 target values (xsec_3535_13TeV, xsec_3636_13TeV, xsec_3737_13TeV, xsec_3537_13TeV, xsec_3637_13TeV, xsec_3735_13TeV, xsec_3736_13TeV, xsec_3536_13TeV) from a parameter space of the Inert Doublet Model chosen as: 50< MH0, MA0, MHC<3000GeV;−2π < lam2,lamL<2π. The cross sections were computed at leading order using MADGRAPH2.6.4 and the IDM UFO implementation from the FeynRules data base.",mds,True,findable,5,0,0,0,0,2020-02-27T16:00:55.000Z,2020-02-27T16:00:57.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.204818,Tutorial Dataset Of Mdanse 2016 Workshop,Zenodo,2016,,Dataset,"Creative Commons Attribution 4.0,Open Access","This dataset was distributed to delegates attending MDANSE (Molecular (and Lattice) Dynamics to Analyse Neutron Scattering Experiments) 2016 workshop, held at Abingdon, Oxfordshire, United Kingdom during 10-12 November, 2016.
+
+More information of this workshop will be found here: http://www.isis.stfc.ac.uk/news-and-events/events/2016/mdanse-201615848.html
+
+The tutorial document will be published here: https://epubs.stfc.ac.uk/index",,True,findable,0,0,0,0,0,2016-12-15T17:28:57.000Z,2016-12-15T17:28:58.000Z,cern.zenodo,cern,"Neutron Scattering,Molecular Dynamics,Lattice Dynamics,Inelastic Neutron Scattering,Quasi Elastic Neutron Scattering,INS,QENS,Electronic Structures,Density Functional Theory,Classical Force Fields,MDANSE,nMoldyn","[{'subject': 'Neutron Scattering'}, {'subject': 'Molecular Dynamics'}, {'subject': 'Lattice Dynamics'}, {'subject': 'Inelastic Neutron Scattering'}, {'subject': 'Quasi Elastic Neutron Scattering'}, {'subject': 'INS'}, {'subject': 'QENS'}, {'subject': 'Electronic Structures'}, {'subject': 'Density Functional Theory'}, {'subject': 'Classical Force Fields'}, {'subject': 'MDANSE'}, {'subject': 'nMoldyn'}]",,
+10.5281/zenodo.4759517,"Figs. 78-79 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access",Figs. 78-79. Ventral view of the thorax of Protonemura dakkii sp. n. 78: micropterous form; 79: macropterous form (scale 1 mm).,mds,True,findable,0,0,2,0,0,2021-05-14T02:28:11.000Z,2021-05-14T02:28:11.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.44754,Jessie environment,Zenodo,2016,,Software,"GNU General Public License v2.0 only,Open Access",Jessie environment for grid5000,mds,True,findable,0,0,0,0,0,2016-01-18T08:35:17.000Z,2016-01-18T08:35:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4759489,"Figs. 5-6 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 5-6. Distribution of the species of the Protonemoura corsicana group. 5: Protonemura corsicana subgroup; 6: P. talboti subgroup, P. consiglioi subgroup and P. spinulata subgroup.",mds,True,findable,0,0,10,0,0,2021-05-14T02:23:24.000Z,2021-05-14T02:23:25.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.34929/sep.vi06.151,Las Hijas de Eva de Santiago Serrano : douze personnages en quête de genre ,"Savoirs en prisme, Editions et presses universitaires de Reims",2017,,Text,,,fabricaForm,True,findable,0,0,0,0,0,2021-03-26T16:47:36.000Z,2021-03-26T16:47:36.000Z,inist.epure,vcob,,,,
+10.5281/zenodo.7780496,"Datasets supporting for ""Further insight into the involvement of PII1 in starch granule initiation in Arabidopsis leaf chloroplasts.""",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The folder contains data to support the paper entitled "" Further insight into the involvement of PII1 in starch granule initiation in Arabidopsis leaf chloroplasts."" The folder named ""MEB pictures"" contains all pictures that were used to determine starch granule size (only granules with visible major axis were measured. The folder named ""confocal microscopy"" contains the files used to determine starch granule number per plastid. it contains one folder for plants in Ws genetic background and another folder for plants in Col-0 genetic background.",mds,True,findable,0,0,0,0,0,2023-03-29T09:54:48.000Z,2023-03-29T09:54:49.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.2641965,X-ray diffraction images for coenzyme F420H2 oxidase (FprA) from M. thermolithotrophicus.,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Anomalous data collected at SOLEIL (Saint Aubin, France) using beamline PROXIMA-2. The crystal (Crystal form 1) was in the presence of the crystallophore Tb-Xo4.
+
+
+
+Related Publication: Engilberge et al. (2019)
+
+
+
+Partial XDS file:
+
+ OSCILLATION_RANGE= 0.10000000149
+
+ STARTING_ANGLE= 0.0
+
+ STARTING_FRAME= 1
+
+ X-RAY_WAVELENGTH= 1.648507
+
+ DETECTOR_DISTANCE= 102.540
+
+ DETECTOR= EIGER MINIMUM_VALID_PIXEL_VALUE= 0 OVERLOAD= 44419
+
+ DIRECTION_OF_DETECTOR_X-AXIS= 1.0 0.0 0.0
+
+ DIRECTION_OF_DETECTOR_Y-AXIS= 0.0 1.0 0.0
+
+ NX= 3110 NY= 3269 QX= 0.0750000035623 QY= 0.0750000035623
+
+ ORGX= 1509.33483887 ORGY= 1655.37805176
+
+ ROTATION_AXIS= 1.000000 0.000000 0.000000
+
+ INCIDENT_BEAM_DIRECTION= 0.0 0.0 1.0",mds,True,findable,0,0,0,0,0,2019-04-16T11:30:54.000Z,2019-04-16T11:30:54.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5775523,MICCAI 2021 MSSEG-2 challenge quantitative results,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This dataset includes all quantitative results of all metrics for challengers of the MICCAI MSSEG2 2021 challenge on new MS lesions detection. It also includes the ranking excel file obtained on the challenge day. Please refer to the README for more details. Second version adds missing SNAC team results and ITU team results update. Third version provides corrected results after correction of ground truth.,mds,True,findable,0,0,0,1,0,2021-12-13T08:24:09.000Z,2021-12-13T08:24:09.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5526763,robertxa/Pecube-Plot-Xav: Pecube plots,Zenodo,2021,,Software,Open Access,Python scripts to plot PECUBE modeling results,mds,True,findable,0,0,0,0,0,2021-09-24T14:41:32.000Z,2021-09-24T14:41:33.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3817433,"Search Queries for ""Mapping Research Output to the Sustainable Development Goals (SDGs)"" v2.0",Zenodo,2018,,Software,"Creative Commons Attribution 4.0 International,Open Access","<strong>This package contain machine readable (xml) search queries for Scopus to find domain specific research output that are related to the 17 Sustainable Development Goals (SDGs).</strong> Sustainable Development Goals are the 17 global challenges set by the United Nations. Within each of the goals specific targets and indicators are mentioned to monitor the progress of reaching those goals by 2030. In an effort to capture how research is contributing to move the needle on those challenges, we earlier have made an initial classification model than enables to quickly identify what research output is related to what SDG. (This Aurora SDG dashboard is the initial outcome as <em>proof of practice</em>.) The initiative started from the Aurora Universities Network in 2017, in the working group ""Societal Impact and Relevance of Research"", to investigate and to make visible 1. what research is done that are relevant to topics or challenges that live in society (for the proof of practice this has been scoped down to the SDGs), and 2. what the effect or impact is of implementing those research outcomes to those societal challenges (this also have been scoped down to research output being cited in policy documents from national and local governments an NGO's). The classification model we have used are 17 different search queries on the Scopus database. The search queries are elegant constructions with keyword combinations and boolean operators, in the syntax specific to the Scopus Query Language. We have used Scopus because it covers more research area's that are relevant to the SDG's, and we could filter much easier the Aurora Institutions. <strong>Versions</strong> Different versions of the search queries have been made over the past years to improve the precision (soundness) and recall (completeness) of the results. The queries have been made in a team effort by several bibliometric experts from the Aurora Universities. Each one did two or 3 SDG's, and than reviewed each other's work. v1.0 January 2018<em> Initial 'strict' version.</em> In this version only the terms were used that appear in the SDG policy text of the targets and indicators defined by the UN. At this point we have been aware of the SDSN Compiled list of keywords, and used them as inspiration. Rule of thumb was to use <em>keyword-combination searches</em> as much as possible rather than <em>single-keyword searches</em>, to be more precise rather than to yield large amounts of false positive papers. Also we did not use the inverse or 'NOT' operator, to prevent removing true positives from the result set. This version has not been reviewed by peers. Download from: GitHub / Zenodo v2.0 March 2018<em> Reviewed 'strict' version.</em> Same as version 1, but now reviewed by peers. Download from: GitHub / Zenodo v3.0 May 2019 <em>'echo chamber' version.</em> We noticed that using strictly the terms that policy makers of the UN use in the targets and indicators, that much of the research that did not use that specific terms was left out in the result set. (eg. ""mortality"" vs ""deaths"") To increase the recall, without reducing precision of the papers in the results, we added keywords that were obvious synonyms and antonyms to the existing 'strict' keywords. This was done based on the keywords that appeared in papers in the result set of version 2. This creates an 'echo chamber', that results in more of the same papers. Download from: GitHub / Zenodo v4.0 August 2019<em> uniform 'split' version.</em> Over the course of the years, the UN changed and added Targets and indicators. In order to keep track of if we missed a target, we have split the queries to match the targets within the goals. This gives much more control in maintenance of the queries. Also in this version the use of brackets, quotation marks, etc. has been made uniform, so it also works with API's, and not only with GUI's. His version has been used to evaluate using a survey, to get baseline measurements for the precision and recall. Published here: Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. Download from: GitHub / Zenodo v5.0 June 2020 <em>'improved' version.</em> In order to better reflect academic representation of research output that relate to the SDG's, we have added more keyword combinations to the queries to increase the recall, to yield more research papers related to the SDG's, using academic terminology. We mainly used the input from the Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. We ran several text analyses: Frequent term combination in title and abstracts from Suggested papers, and in selected (accepted) papers, suggested journals, etc. Secondly we got inspiration out of the Elsevier SDG queries Jayabalasingham, Bamini; Boverhof, Roy; Agnew, Kevin; Klein, Lisette (2019), “Identifying research supporting the United Nations Sustainable Development Goalsâ€, Mendeley Data, v1 https://dx.doi.org/10.17632/87txkw7khs.1. Download from: GitHub / Zenodo <strong>Contribute and improve the SDG Search Queries</strong> We welcome you to join the Github community and to fork, improve and make a pull request to add your improvements to the new version of the SDG queries. <strong>https://github.com/Aurora-Network-Global/sdg-queries</strong>",mds,True,findable,1,0,2,0,0,2020-05-15T13:11:17.000Z,2020-05-15T13:11:18.000Z,cern.zenodo,cern,"Sustainable Development Goals,SDG,Classification model,Search Queries,SCOPUS","[{'subject': 'Sustainable Development Goals'}, {'subject': 'SDG'}, {'subject': 'Classification model'}, {'subject': 'Search Queries'}, {'subject': 'SCOPUS'}]",,
+10.7280/d1gw91,Annual Ice Velocity of the Greenland Ice Sheet (1991-2000),Dryad,2019,en,Dataset,Creative Commons Attribution 4.0 International,"We derive surface ice velocity using data from 16 satellite sensors deployed by 6 different space agencies. The list of sensors is given in the Table S1. The SAR data are processed from raw to single look complex using the GAMMA processor (www.gamma-rs.ch). All measurements rely on consecutive images where the ice displacement is estimated from tracking or interferometry (Joughin et al. 1998, Michel and Rignot 1999, Mouginot et al. 2012). Surface ice motion is detected using a speckle tracking algorithm for SAR instruments and feature tracking for Landsat. The cross-correlation program for both SAR and optical images is ampcor from the JPL/Caltech repeat orbit interferometry package (ROI_PAC). We assemble a composite ice velocity mosaic at 150 m posting using our entire speed database as described in Mouginot et al. 2017 (Fig. 1A). The ice velocity maps are also mosaicked in annual maps at 150 m posting, covering July, 1st to June, 30th of the following year, i.e. centered on January, 1st (12) because a majority of historic data were acquired in winter season, hence spanning two calendar years. We use Landsat-1&2/MSS images between 1972 and 1976 and combine image pairs up to 1 years apart to measure the displacement of surface features between images as described in Dehecq et al., 2015 or Mouginot et al. 2017. We use the 1978 2-m orthorectified aerial images to correct the geolocation of Landsat-1 and -2 images (Korsgaard et al., 2016). Between 1984 and 1991, we process Landsat-4&5/TM image pairs acquired up to 1-year apart. Only few Landsat-4 and -5 images (~3%) needed geocoding refinement using the same 1978 reference as used previously. Between 1991 and 1998, we process radar images from the European ERS-1/2, with a repeat cycle varying from 3 to 36 days depending on the mission phase. Between 1999 and 2013, we used Landsat-7, ASTER, RADARSAT-1/2, ALOS/PALSAR, ENVISAT/ASAR to determine surface velocity (Joughin et al., 2010; Howat, I. 2017; Rignot and Mouginot, 2012). After 2013, we use Landsat-8, Sentinel-1a/b and RADARSAT-2 (Mouginot et al., 2017). All synthetic aperture radar (SAR) datasets are processed assuming surface parallel flow using the digital elevation model (DEM) from the Greenland Mapping Project (GIMP; Howat et al., 2014) and calibrated as described in Mouginot et al., 2012, 2017. Data were provided by the European Space Agency (ESA), the EU Copernicus program (through ESA), the Canadian Space Agency (CSA), the Japan Aerospace Exploration Agency (JAXA), the Agenzia Spaziale Italiana (ASI), the Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) and the National Aeronautics and Space Administration (NASA). SAR data acquisitions were coordinated by the Polar Space Task Group (PSTG). Errors are estimated based on sensor resolution and time lapse between consecutive images as described in Mouginot et al. 2017. References Dehecq, A, Gourmelen, N, Trouve, E (2015). Deriving large-scale glacier velocities from a complete satellite archive: Application to the Pamir-Karakoram-Himalaya. Remote Sensing of Environment, 162, 55-66. Howat IM, Negrete A, Smith BE (2014) The greenland ice mapping project (gimp) land classification and surface elevation data sets. The Cryosphere 8(4):1509-1518. Howat, I (2017). MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from Optical Images, Version 2. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. Joughin, I., B. Smith, I. Howat, T. Scambos, and T. Moon. (2010). Greenland Flow Variability from Ice-Sheet-Wide Velocity Mapping, J. of Glac.. 56. 415-430. Joughin IR, Kwok R, Fahnestock MA (1998) Interferometric estimation of three dimensional ice-flow using ascending and descending passes. IEEE Trans. Geosci. Remote Sens. 36(1):25-37. Joughin, I, Smith S, Howat I, and Scambos T (2015). MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. Michel R, Rignot E (1999) Flow of Glaciar Moreno, Argentina, from repeat-pass Shuttle Imaging Radar images: comparison of the phase correlation method with radar interferometry. J. Glaciol. 45(149):93-100. Mouginot J, Scheuchl B, Rignot E (2012) Mapping of ice motion in Antarctica using synthetic-aperture radar data. Remote Sens. 4(12):2753-2767. Mouginot J, Rignot E, Scheuchl B, Millan R (2017) Comprehensive annual ice sheet velocity mapping using landsat-8, sentinel-1, and radarsat-2 data. Remote Sensing 9(4). Rignot E, Mouginot J (2012) Ice flow in Greenland for the International Polar Year 2008- 2009. Geophys. Res. Lett. 39, L11501:1-7.",mds,True,findable,997,167,0,2,0,2018-12-15T22:37:49.000Z,2018-12-15T22:38:01.000Z,dryad.dryad,dryad,,,['7193679240 bytes'],
+10.5281/zenodo.6855728,Code for noise-based seismic velocity changes estimation with the Bezymianny volcano data set. Journal of Volcanology and Geothermal Research.,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This file contains all the data and the python scripts used to estimate seismic velocity changes for the Bezymianny volcano (Klyuchevskoy volcano group). It also includes a guideline README.pdf with the description how to reproduce all the results presented in the paper <strong>Berezhnev Y., Belovezhets N., Shapiro N., Koulakov I. (2022), Temporal changes of seismic velocities below Bezymianny volcano prior to its explosive eruption on 20.12.2017, Journal of Volcanology and Geothermal Research</strong>",mds,True,findable,0,0,0,0,0,2022-07-19T03:12:13.000Z,2022-07-19T03:12:14.000Z,cern.zenodo,cern,"Ambient seismic noise,Volcano monitoring,Mechanical model,Bezymianny,Kamchatka Peninsula,Volcano","[{'subject': 'Ambient seismic noise'}, {'subject': 'Volcano monitoring'}, {'subject': 'Mechanical model'}, {'subject': 'Bezymianny'}, {'subject': 'Kamchatka Peninsula'}, {'subject': 'Volcano'}]",,
+10.5281/zenodo.3701520,"DATA of 'Quantification of seasonal and diurnal dynamics of subglacial channels using seismic observations on an Alpine Glacier.' from Nanni et al. 2020,",Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset belongs to the study of <strong>Nanni et al., 2020</strong> ""Quantification of seasonal and diurnal dynamics of subglacial channels using seismic observations on an Alpine Glacier."" accepted for publication in The Cryosphere on March 9th 2020. You can find additional information on the ""<strong>README_data_NANNI_2020_glacier</strong>""",mds,True,findable,0,0,0,1,0,2020-03-09T15:29:10.000Z,2020-03-09T15:29:11.000Z,cern.zenodo,cern,"glacier,environmental seismology,subglacial hydrology,cryoseismology,water flow","[{'subject': 'glacier'}, {'subject': 'environmental seismology'}, {'subject': 'subglacial hydrology'}, {'subject': 'cryoseismology'}, {'subject': 'water flow'}]",,
+10.5281/zenodo.6223302,Unsupervised Multiple-Object Tracking with a Dynamical Variational Autoencoder,Zenodo,2022,,Dataset,"Creative Commons Attribution 1.0 Generic,Open Access","This is the public dataset of synthetic trajectories and MOT17-3T, which is used in paper Unsupervised Multiple-Object Tracking with a Dynamical Variational Autoencoder. The source code can be found here.",mds,True,findable,0,0,0,0,0,2022-02-22T12:38:53.000Z,2022-02-22T12:38:53.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4761327,"Figs. 52-53 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 52-53. Dictyogenus muranyii sp. n., biotopes. 52. Cave and Spring of Brudour river, Drôme dpt, France. Photo A. Ruffoni. 53. Spring of Adouin River, Vercors Massif, Isère dpt, France, in summer. Photo J. Le Doaré.",mds,True,findable,0,0,2,0,0,2021-05-14T07:48:23.000Z,2021-05-14T07:48:23.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.5905877,IC profile analysis V.1.0,Zenodo,2022,,Software,Open Access,"This R script performs a longitudinal analysis on the output of IC (Cavalli et al.,(2013), and its composing parameters according to Torresani et al., (2021). The analysis is performed on exported CSV table containing the IC and the selected parameters extracted along the channel profile. This tool aims to graphically represent the behaviour of the variables at different locations of the analysed channel.",mds,True,findable,0,0,1,0,0,2022-01-26T11:27:45.000Z,2022-01-26T11:27:46.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7590005,The representation of sea salt aerosols and their role in polar climate within CMIP6,Zenodo,2023,,Software,Open Access,"Plotting scripts and data for the paper ""The representation of sea salt aerosols and their role in polar climate within CMIP6"", JGR: Atmospheres, Lapere et al., 2023.",mds,True,findable,0,0,0,0,0,2023-01-31T14:09:59.000Z,2023-01-31T14:09:59.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5242859,Spanish DBnary archive in original Lemon format,Zenodo,2021,es,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Spanish language edition, ranging from 17th February 2014 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T07:55:01.000Z,2021-08-24T07:55:02.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.2636714,Kwant: a Python package for numerical quantum transport calculations,Zenodo,2019,en,Software,"BSD 2-Clause ""Simplified"" License,Open Access","Kwant is a free (open source) Python package for numerical calculations on tight-binding models with a strong focus on quantum transport. It is designed to be flexible and easy to use. Thanks to the use of innovative algorithms, Kwant is often faster than other available codes, even those entirely written in the low level FORTRAN and C/C++ languages.",mds,True,findable,4,0,0,0,0,2019-04-11T15:58:45.000Z,2019-04-11T15:58:46.000Z,cern.zenodo,cern,"python, tight-binding, quantum transport, scattering","[{'subject': 'python, tight-binding, quantum transport, scattering'}]",,
+10.57745/j2a44q,Numerical simulation of rainfall and runoff driven erosion at the hillslope scale: four rainfall events on the Pradel plot,Recherche Data Gouv,2023,,Dataset,,"This dataset correspond to rainfall and runoff measurement of a Mediterranean hillslope vineyard of 130 m² located in the region of Cevennes-Vivarais (south eastern France), which is part of the Mediterranean Hydrometeorological Observatory (OHMCV). The hillslope is 60 m long and 2.2 m wide. Its topography was measured at 15 cross sections and 6 points per cross section, with an uncertainty of 1 cm in the three dimensions. The average longitudinal slope is around 15%, and there is a rill that conveys all the surface runoff to the downstream outlet, with no runoff losses through the lateral sides. The soil is calcareous and covered by sparse vegetation, with an approximate composition of 34% clay, 41% silt and 25% sand. The soil erosion data monitored during the four storm events were used to calibrate and validate Iber+ models also provided in the dataset. These data sets and the DEM of the vineyard are described in detail and can be downloaded from Nord et al. (2017).",mds,True,findable,14,0,0,0,0,2023-04-04T14:29:07.000Z,2023-04-06T07:03:24.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.7119224,"FIGURE 2. Bulbophyllum tianguii K.Y.Lang & D.Luo. A. Flowering plant. B. Inflorescence. C in A new species, Bulbophyllum phanquyetii and a new national record of B. tianguii (Orchidaceae) from the limestone area of northern Vietnam",Zenodo,2022,,Image,Open Access,"FIGURE 2. Bulbophyllum tianguii K.Y.Lang & D.Luo. A. Flowering plant. B. Inflorescence. C. Floral bract, abaxial and adaxial side. D. Flowers, side and frontal view. E. Median sepal, abaxial and adaxial side. F. Lateral sepals, adaxial and abaxial side. G. Petals, abaxial and adaxial side. H. Lip, views from different sides. I. Lip median portion. J. Magnified lip margin. K. Pedicel, ovary and column, side view. L. Column apex, views from different sides. M. Anther cap, frontal view and view from back. N. Pollinaria. Photos by Truong Ba Vuong (A, C–N, VNM 00069943) and by Nguyen Van Canh (B, VNM 00069944), design by Truong Ba Vuong, L. Averyanov, and T. Maisak.",mds,True,findable,0,0,0,3,0,2022-09-28T12:12:03.000Z,2022-09-28T12:12:03.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Bulbophyllum","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Bulbophyllum'}]",,
+10.5281/zenodo.5500144,Radiative transfer modeling in structurally-complex stands: towards a better understanding of parametrization: Dataset,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository is linked to the paper ""Radiative transfer modeling in structurally-complex stands: towards a better understanding of parametrization"" submitted to Annals of Forest Science and written by Frédéric ANDRÉ (corresponding author), Louis DE WERGIFOSSE, François DE COLIGNY, Nicolas BEUDEZ, Gauthier LIGOT, Vincent GAUTHRAY-GUYÉNET, Benoit COURBAUD and Mathieu JONARD. The repository contains the two following archive files: RadiationDataset.zip: gather the HETEROFOR model input files containing the measured understorey radiation values, and the position and main characteristics (girth of the trunk at breast height, total height, height of largest crown extension, height of crown base and crown radii in four directions) of the trees in the surrounding of the radiation measurement locations GrowthDataset.zip: gather the following HETEROFOR model input files for each of the six plots considered for growth measurements: Inventory files at the beginning and at the end of the growth period Thinning file, containing the list of the trees harvested during the study period Fruit litter fall file: fruit litter fall (kgC/ha) measured each year, determined separatly for each of the main species Soil horizon file: containing the main physico-chemical characteristics of the soil horizons Meteorology file: containing hourly records of the main meteorological variables (total radiation, air temperature, soil surface temperature, rainfall depth, air relative humidity, wind speed, wind direction, diffuse/global radiation ratio) For more information concerning this repository or the study, please do not hesitate to contact Frédéric ANDRÉ (frederic.andre@uclouvain.be) or Mathieu JONARD (mathieu.jonard@uclouvain.be).",mds,True,findable,0,0,0,0,0,2021-09-10T12:38:56.000Z,2021-09-10T12:38:57.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3603072,"Bibliography of the Systematic Literature Review of the IPBES Global Assessment, Chapter 4",Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Bibliographies from the systematic literature review in Chapter 4 of the IPBES Global Assessment DOI: 10.5281/zenodo.3553579,mds,True,findable,0,0,1,0,0,2020-05-25T09:13:11.000Z,2020-05-25T09:13:13.000Z,cern.zenodo,cern,,,,
+10.18150/wyyjk6,Estimates for recombination coefficients from time-resolved luminescence - local and global approach explained on bulk gallium nitride: numerical data,RepOD,2022,,Dataset,,"This is a dataset of numerical data for experimental results of time-resolved cathodoluminescence and time-resolved photoluminescence of a HVPE-grown GaN sample, which are then de-noised and analyzed for estimating ABC recombination constants of this sample.The examined GaN sample was prepared from a bulk crystal grown by Halide Vapor Phase Epitaxy (HVPE) method. In order to obtain a thick crystal, a few consecutive HVPE processes were performed. An ammonothermally-grown GaN seed of a very high structural quality, with the gallium surface prepared to an epi-ready state, was used in the first run. After the crystallization process the gallium surface of the new-grown crystal was prepared by mechanical and chemo-mechanical polishing to an epi-ready state. The crystal was used as the seed for the next HVPE run. The surface preparation and growth process were repeated until the crystal reached the required thickness. Finally, the ammonothermal seed was removed by slicing. The nitrogen side of the free-standing HVPE-GaN crystal was prepared by mechanical and chemo-mechanical polishing to an epi-ready state. The prepared sample was 1700-um-thick and of high structural quality.The time-resolved cathodoluminescence measurements were conducted on an Allalin Chronos instrument from Attolight. In this tool, a focused electron beam scans the sample while the optical emission is collected and analyzed by a spectrometer. The spectrometer consists of a 320 mm monochromator (Horiba iHR320) fitted with a streak camera (Hamamatsu C10910) for TRCL measurements. During TRCL measurements, the electron beam is pulsed at 80 MHz using a laser focused on the Schottky field emission gun (FEG). TRCL measurements were performed at room temperature. Four beam energies were considered: 1.5 keV, 3 keV, 5 keV, and 10 keV. Ga-side and N-side surfaces were considered.The time resolved luminescence and decay profiles were measured using apparatus which consists of a PG 401/SH optical parametric generator pumped by a PL2251A pulsed YAG:Nd laser (EKSPLA) with 30 ps laser pulses and a repetition rate 20 Hz. The detection part consists of a 2501S grating spectrometer (Bruker Optics) combined with a C4334-01 streak camera (Hamamatsu). Data were recorded in the form of the streak images on a 640 by 480 pixels CCD array. Software based on photon counting algorithm transforms the result into a 2D matrix of photon counts versus wavelength and time (streak image). The time resolve spectroscopic study was done for both sides of GaN monocrystal: Ga-side and N-side. The laser energy able to obtain 300 nm pulsed excitation wavelength was 30 mJ.The experimental results are then de-noised by numerical scheme implemented in logpli software ( https://github.com/ghkonrad/logpli ). First, there is normalized luminescence intensity versus time, and then negative logarithmic derivative of the normalized luminescence intensity.",mds,True,findable,0,0,0,0,0,2022-04-21T14:17:28.000Z,2022-05-12T07:05:32.000Z,tib.repod,repod,,,,
+10.5281/zenodo.8124000,20230523-VBCE: Agents adapt ontologies to agree on decision taking. Introducing cultural values,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This archive contains the results of a multi-agent simulation experiment [1] carried out with Lazy lavender [2] environment. Experiment Label: 20230523-VBCE Experiment design: Agents adapt ontologies to agree on decision taking. Introducing cultural values (independece, novelty, authority, mastery) that influence which agent adapts in case of interaction failure. Experiment setting: Agents learn decision trees (transformed into ontologies); get payoffs according to cultural values; adapt by splitting their leaf nodes Hypotheses: Positive mastery is needed for increasing accuracy. Negative independence causes the success rate to converge faster. Negative novelty increases ontology distance. Positive authority increases accuracy when used with positive mastery. Detailed information can be found in index.html or notebook.ipynb. [1] https://sake.re/20230523-VBCE<br> [2] https://gitlab.inria.fr/moex/lazylav/",mds,True,findable,0,0,0,0,0,2023-07-07T11:57:13.000Z,2023-07-07T11:57:13.000Z,cern.zenodo,cern,"Multi-agent Simulation,Cultural Evolution","[{'subject': 'Multi-agent Simulation'}, {'subject': 'Cultural Evolution'}]",,
+10.5281/zenodo.8269305,Magnetic structure and field-dependent magnetic phase diagram of Ni2In-type PrCuSi,Zenodo,2018,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data sets for original figures in the article 'Magnetic structure and field-dependent magnetic phase diagram of Ni<sub>2</sub>In-type PrCuSi' published in J. Phys.:Condens. Matter 30 (43) 2018. The file name of each xls file corresponds to the figure number in the published article. The files can be opened using the Excel program. If there are sub-figures, or multiple frames in each figure, the data of each sub-figure is stored in separate sheets within one xls file. The files with the file extension 'vesta' can be opened using the freely available program VESTA.",mds,True,findable,0,0,0,0,0,2023-08-21T13:50:23.000Z,2023-08-21T13:50:23.000Z,cern.zenodo,cern,"antiferromagnet,magnetostructural effect,PrCuSi,field induced ferromagnetism","[{'subject': 'antiferromagnet'}, {'subject': 'magnetostructural effect'}, {'subject': 'PrCuSi'}, {'subject': 'field induced ferromagnetism'}]",,
+10.5061/dryad.d51c5b019,Early-wilted forest following the Central European 2018 extreme drought,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"During the summer of 2018, Central Europe experienced the most extreme drought and heat wave on record, leading to widespread early leaf-shedding and die-offs in forest trees. We quantified such early-wilting responses by associating Sentinel-2 time-series statistics of the Normalized Difference Vegetation Index with visually classified orthophotos, using a random forest classifier. The predictions of our classifier achieved a high accuracy of 0.90 ±0.014 and estimated the area of affected forest at 21’500 ±2800 km2. Early wilting was especially prevalent in eastern and central Germany and in the Czech Republic and it was related to high temperatures and low precipitation at large-scales, and small to medium-sized trees, steep slopes, and shallow soils at fine-scales. The present dataset includes spatial predictons of 2018 early-wilting presence/absence for entire Central Europe (c. 800'000 km2) at 10×10 m resolution. It may be used for high-resolution studies of early-wilting patterns, to study how factors like physiology or species identity relate to early-wilting patterns, and/or as testbed for alternative approaches quantifying water stress in forests.",mds,True,findable,172,8,0,0,0,2020-10-27T13:58:10.000Z,2020-10-27T13:58:12.000Z,dryad.dryad,dryad,"FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences,early senescence,European beech,Sentinel-2","[{'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'early senescence'}, {'subject': 'European beech'}, {'subject': 'Sentinel-2'}]",['847736758 bytes'],
+10.5281/zenodo.4790667,Dataset: Guided accumulation of active particles by topological design of a second-order skin effect,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Experimental data files used in the manuscript ""Guided accumulation of active particles by topological design of a second-order skin effect"". Collective guidance of out-of-equilibrium systems without using external fields is a challenge of paramount importance in active matter, ranging from bacterial colonies to swarms of self-propelled particles.<br> Designing strategies to guide active matter and exploiting enhanced diffusion associated to its motion will provide insights for application from sensing, drug delivery to water remediation.<br> <br> However, achieving directed motion without breaking detailed balance, for example by asymmetric topographical patterning, is challenging.<br> <br> Here we engineer a two-dimensional periodic topographical design with detailed balance in its unit cell where we observe spontaneous particle edge guidance and corner accumulation of self-propelled particles.<br> <br> This emergent behaviour is guaranteed by a second-order non-Hermitian skin effect, a topologically robust non-equilibrium phenomenon, that we use to dynamically break detailed balance.<br> <br> Our stochastic circuit model predicts, without fitting parameters, how guidance and accumulation can be controlled and enhanced by design: a device guides particles more efficiently if the topological invariant characterizing it is non-zero.<br> <br> Our work establishes a fruitful bridge between active and topological matter, and our design principles offer a blueprint to design devices that display spontaneous, robust and predictable guided motion and accumulation, guaranteed by out-of-equilibrium topology.",mds,True,findable,0,0,0,0,0,2021-05-27T09:45:45.000Z,2021-05-27T09:45:45.000Z,cern.zenodo,cern,"active particles,second order non hermitian skin effect,topological","[{'subject': 'active particles'}, {'subject': 'second order non hermitian skin effect'}, {'subject': 'topological'}]",,
+10.5061/dryad.cvdncjt2p,Phylogenetic signatures of ecological divergence and leapfrog adaptive radiation in Espeletia,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"PREMISE: Events of accelerated species diversification represent one of Earth’s most celebrated evolutionary outcomes. Northern Andean high-elevation ecosystems, or páramos, host some plant lineages that have experienced the fastest diversification rates, likely triggered by ecological opportunities created by mountain uplifts, local climate shifts and key trait innovations. However, the mechanisms behind rapid speciation into the new adaptive zone provided by these opportunities have long remained unclear. METHODS: We address this issue by studying the Venezuelan clade of Espeletia, a species-rich group of páramo-endemics showing a dazzling ecological and morphological diversity. We performed a number of comparative analyses to study both lineage and trait diversification, using an updated molecular phylogeny of this plant group. KEY RESULTS: We showed that sets of either vegetative or reproductive traits have conjointly diversified in Espeletiaalong different vegetation belts, leading to adaptive syndromes. Diversification in vegetative traits occurred earlier than in reproductive ones. The rate of species and morphological diversification showed a tendency to slow down over time, probably due to diversity dependence. We also found that closely related species exhibit significantly more overlap in their geographic distributions than distantly related taxa, suggesting that most events of ecological divergence occurred at close geographic proximity within páramos. CONCLUSIONS: These results provide compelling support for a scenario of small-scale ecological divergence along multiple ecological niche dimensions, possibly driven by competitive interactions between species, and acting sequentially over time in a leapfrog pattern.",mds,True,findable,141,6,0,0,0,2020-09-23T16:16:48.000Z,2020-09-23T16:16:49.000Z,dryad.dryad,dryad,,,['266719014 bytes'],
+10.5281/zenodo.7627946,Geometrical effects on the downstream conductance in quantum-Hall--superconductor hybrid systems (code),Zenodo,2023,,Software,Open Access,"Code used in the paper: A. David, J. S. Meyer, and M. Houzet, Geometrical effects on the downstream conductance in quantum-Hall--superconductor hybrid systems, Phys. Rev. B <strong>107</strong>, 125416 (2023). https://journals.aps.org/prb/abstract/10.1103/PhysRevB.107.125416",mds,True,findable,0,0,0,1,0,2023-02-10T09:06:08.000Z,2023-02-10T09:06:08.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7504469,GlScene,Zenodo,2023,,Software,"GNU General Public License v3.0 only,Open Access",Gl Scene Editor.,mds,True,findable,0,0,0,0,0,2023-01-04T19:13:48.000Z,2023-01-04T19:13:49.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6315226,Linear Kinematic Feature detected and tracked in sea-ice deformation simulationed by all models participating in the Sea Ice Rheology Experiment and from RGPS,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Linear Kinematic Features (LKFs) detected and tracked in sea-ice deformation fields simulated by sea-ice models participating in the Sea Ice Rheology Experiment (SIREx), a model intercomparison project of the Forum of Arctic Modeling and Observational Synthesis (FAMOS). These data are the basis of the feature-based evaluation of sea-ice deformation in Hutter et al., Sea Ice Rheology Experiment (SIREx), Part II: Evaluating linear kinematic features in high-resolution sea-ice simulations, Journal of Geophysical Research: Oceans (2022). This paper also provides further details on the parameters of the LKF extraction. The LKF data sets in this archive are stored in a csv-files for each year (1997 and/or 2008), which use semi-colons as delimiters. Each row corresponds to a pixel that was identified as LKF and the following information for this pixels is stored: Start Year, Start Month, Start Day, End Year, End Month, End Day, LKF No., Parent LKF No., lon, lat, ind_x, ind_y, divergence rate, shear rate. All pixels belonging to the same LKF have the same LKF number. Tracked LKFs are linked by the parent LKF number, where ""0"" denotes LKFs that newly formed. Detailed information on all variables is provided in the additional notes.",mds,True,findable,0,0,0,2,0,2022-03-01T00:34:48.000Z,2022-03-01T00:34:49.000Z,cern.zenodo,cern,"sea ice,deformation,sea ice modelling,satellite observations,fracture,Linear Kinematic Features,LKFs","[{'subject': 'sea ice'}, {'subject': 'deformation'}, {'subject': 'sea ice modelling'}, {'subject': 'satellite observations'}, {'subject': 'fracture'}, {'subject': 'Linear Kinematic Features'}, {'subject': 'LKFs'}]",,
+10.6084/m9.figshare.21550639,Self-compassion and emotion regulation: testing a mediation model,Taylor & Francis,2022,,Text,Creative Commons Attribution 4.0 International,"Self-compassion (SC) seems to play an important role in improving Emotion Regulation (ER). Nevertheless, the results of previous studies regarding the links between SC and ER are not consistent, especially facing diverse models of ER (strategy-based vs skill-based). The goal of this prospective study was to evaluate the links between these three concepts, by testing the predictive roles of SC and ER skills on both ER adaptive and maladaptive strategies, using standardised questionnaires and visual analogue scales. Results of regression analysis showed that self-compassion positively predicts cognitive reappraisal, acceptance, problem-solving, relaxation, self-support, tolerance and ER skills and negatively predicts behavioural avoidance, expressive suppression and ruminations. Results also showed that ER skills positively predict cognitive reappraisal, expression, acceptance, relaxation, self-support and tolerance and negatively predicts behavioural avoidance, expressive suppression and ruminations. Results from a mediation model are also promising regarding both the role of ER skills on the effect of SC on adaptive ER strategy use. Even if this study can be associated with common limits of self-report measures, it highlights the role of SC in a model of ER.",mds,True,findable,0,0,0,0,0,2022-11-14T09:00:05.000Z,2022-11-14T09:00:06.000Z,figshare.ars,otjm,"Medicine,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}]",['20085 Bytes'],
+10.5281/zenodo.8095047,"Data from: Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This data accompanies the paper entitled <strong><em>Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.</em></strong> The zip archive contains the results of molecular dynamics simulations of the 2 systems investigated in the paper: <em>S. rum</em> and <em>T. mar</em> LDHs. The systems have been simulated at 315 K for <em>S. rum </em>and 340 K for <em>T. mar</em>. Final configurations of the proteins after productions are provided for all the systems in GRO Gromos87 format. Trajectories with the positions of the proteins every 100 ps are provided for all the systems in XTC gromacs format.",mds,True,findable,0,0,0,0,0,2023-06-29T12:34:24.000Z,2023-06-29T12:34:25.000Z,cern.zenodo,cern,"Allosteric regulation,lactate dehydrogenase,crystal structure,molecular dynamics,quaternary structure","[{'subject': 'Allosteric regulation'}, {'subject': 'lactate dehydrogenase'}, {'subject': 'crystal structure'}, {'subject': 'molecular dynamics'}, {'subject': 'quaternary structure'}]",,
+10.5281/zenodo.7760251,A closer look at high-energy X-ray-induced bubble formation during soft tissue imaging,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast cineradiography with <em>operando</em> gas chromatography, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (2 to 3 times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gases remain unchanged. Coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical, yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation-matter interactions in these applications.",mds,True,findable,0,0,0,0,0,2023-03-24T09:00:21.000Z,2023-03-24T09:00:22.000Z,cern.zenodo,cern,"Synchrotron X-ray,Vacuum Degassing,Bubble Growth,Gas Chromatography,In Operando","[{'subject': 'Synchrotron X-ray'}, {'subject': 'Vacuum Degassing'}, {'subject': 'Bubble Growth'}, {'subject': 'Gas Chromatography'}, {'subject': 'In Operando'}]",,
+10.5281/zenodo.3634740,Complementary data for LH2019 contribution 'Determination of Independent Signal Regions in LHC Searches for New Physics'.,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Complementary documentation released by Andy Buckley, Benjamin Fuks, Humberto Reyes-González, Walter Waltenberger and Sophie Williamson complimentary to the contribution 'Determination of Independent Signal Regions in LHC Searches for New Physics' as part of the Les Houches 2019 proceedings.",mds,True,findable,1,0,0,0,0,2020-02-05T13:24:00.000Z,2020-02-05T13:24:00.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5717483,"Supplementary data files for JGR 2021JB022729R, Initial results from the Oman Drilling Project Multi-Borehole Observatory: Petrogenesis and ongoing alteration of mantle peridotite in the weathering horizon",Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These are the four supplementary data files for a paper accepted in the Journal of Geophysical Research (JGR), ""Initial results from the Oman Drilling Project Multi-Borehole Observatory: Petrogenesis and ongoing alteration of mantle peridotite in the weathering horizon"", 2021JB022729R, which are being uploaded here in conformance with JGR's requirement that data be placed in an open archive. The date of publication is not yet known, but JGR requires that the data be uploaded when the paper is accepted, so we have used the date of acceptance, November 20, 2021.",mds,True,findable,0,0,0,0,0,2021-11-22T02:03:33.000Z,2021-11-22T02:03:33.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5148640,Optimal Exclusive Perpetual Grid Exploration by Luminous Myopic Opaque Robots: The Animations,Zenodo,2020,,Audiovisual,"CeCILL-B Free Software License Agreement,Open Access","Animations of three optimal perpetual grid exploration algorithms. The published HTML pages allow the viewer to see the first 300 rounds of the algorithms, for different initial configurations. To view the animation without downloading them, they are also accessible at the following urls: https://bramas.fr/static/ICDCN2021/2-robots-3-colors-range-1.html https://bramas.fr/static/ICDCN2021/2-robots-2-colors-range-2.html https://bramas.fr/static/ICDCN2021/3-robots-1-color-range-2.html https://bramas.fr/static/TCS2021/4-robots-1-color-terminating.html https://bramas.fr/static/TCS2021/2-robot-7-colors-terminating.html",mds,True,findable,0,0,0,0,0,2021-07-30T14:34:04.000Z,2021-07-30T14:34:04.000Z,cern.zenodo,cern,"Mobile robots, distributed algorithms","[{'subject': 'Mobile robots, distributed algorithms'}]",,
+10.5281/zenodo.580042,Flow-Guided Warping for Image-Based Shape Manipulation,Zenodo,2017,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset relative to the following publication: Vergne, R., Barla P., Bonneau, G.-P. and R. W. Fleming (2016). Flow-Guided Warping for Image-Based Shape Manipulation. <em>ACM Transactions on Graphics (Proceedings of SIGGRAPH 2016), 35(4)</em>: 93. Each folder contains *.mat files with the data from the experiments presented in Figure 12 of the article (Experiment 1: cg results, Experiment 2: photo results) and a text file with comments.",mds,True,findable,0,0,0,0,0,2017-05-31T09:54:06.000Z,2017-05-31T09:54:07.000Z,cern.zenodo,cern,"Image warping,Enhancement,Shape perception","[{'subject': 'Image warping'}, {'subject': 'Enhancement'}, {'subject': 'Shape perception'}]",,
+10.5281/zenodo.5373496,"FIG. 6 in Le gisement paléontologique villafranchien terminal de Peyrolles (Issoire, Puy-de-Dôme, France): résultats de nouvelles prospections",Zenodo,2006,,Image,"Creative Commons Zero v1.0 Universal,Open Access","FIG. 6. — Diagramme de dispersion des mesures du pédicule (longueur totale et diamètre antéro-postérieur, en mm) des spécimens de « Cervus » rhenanus de Senèze et Saint-Vallier (voir Heintz 1970 et Valli 2001, respectivement), et « Cervus » perolensis de Peyrolles (voir Heintz 1970 pour les spécimens du Natural History Museum de Londres, et Tableau 3 pour les spécimens nouveaux).",mds,True,findable,0,0,0,0,0,2021-09-02T04:40:41.000Z,2021-09-02T04:40:42.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.4761339,"Fig. 62 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 62. Dictyogenus alpinum, larva. Rioufroid, Lus-la-Croix-Haute, Drôme dpt, France. Photo A. Ruffoni.",mds,True,findable,0,0,2,0,0,2021-05-14T07:50:16.000Z,2021-05-14T07:50:17.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.4760127,Figs. 6-11 in Contribution To The Knowledge Of The Capniidae (Plecoptera) Of Turkey.,Zenodo,2011,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 6-11. Capnioneura veronicae sp. n. 6. Male abdominal tip, dorsal view. 7. Male abdominal tip, lateral view. 8. Specillum. 9. Female abdominal tip, ventral view. 10. Female abdominal tip, lateral view. 11. Female pro, meso and methathoracic sternites.",mds,True,findable,0,0,2,0,0,2021-05-14T04:29:43.000Z,2021-05-14T04:29:44.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Capniidae,Capnioneura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Capniidae'}, {'subject': 'Capnioneura'}]",,
+10.5281/zenodo.3541149,"Extended Data for Publication ""Testing the Spectroscopic Extraction of Suppression of Convective Blueshift""",Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Efforts to detect low-mass exoplanets using stellar radial velocities (RVs) are currently limited by magnetic photospheric activity. Suppression of convective blueshift is the dominant magnetic contribution to RV variability in low-activity Sun-like stars. Due to convective plasma motions, the magnitude of RV contributions from the suppression of convective blueshift is roughly correlated with the depth of formation of photospheric spectral lines used to compute the RV time series. Meunier et al. (2017), used this relation to demonstrate a method for spectroscopic extraction of the suppression of convective blueshift in order to isolate RV contributions, including planetary RVs, that contribute equally to the timeseries for each spectral line. In this publication, we extract disk-integrated solar RVs from observations over a 2.5 year time span made with the solar telescope integrated with the HARPS-N spectrograph at the Telescopio Nazionale Galileo (La Palma, Canary Islands, Spain). We apply the methods outlined by Meunier et al. (2017) - as part of this analysis, we fit Gaussian line profiles to 765 iron lines measured over 457 exposures. Here, we provide the complete line list (Table 1; Table1_LineList.csv) used in our analysis, and the resulting RVs time series in their entirety (Table 3; Table3_TimeSeries.csv). Wavelengths are given in Angstroms, and RVs in m/s. We also include 4 CSV files with the line fit parameters of each line profile: Each row corresponds to a single exposure time (corresponding to the JDs in Table 3) and each column corresponds to a specific spectral line (with wavelength specified in Table 1). We fit each spectral line to a Gaussian of the form: \(f(\lambda) = p_1 - p_2 \exp \left[- {1 \over 2} \left({{\lambda - p_3} \over p_4}\right)^2 \right]\) p<sub>1</sub> is the continuum level in arbitrary units (LineProfiles_Continuum.csv)<br> p<sub>2</sub> is the line strength in arbitrary units (LineProfiles_Amplitude.csv)<br> p<sub>3</sub> is the line shift in Angstroms (LineProfiles_Shift.csv)<br> p<sub>4</sub> is the line width in Angstroms (LineProfiles_Width.csv)",mds,True,findable,0,0,0,0,0,2019-11-14T17:47:01.000Z,2019-11-14T17:47:01.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.22609319,Additional file 1 of TRansfusion strategies in Acute brain INjured patients (TRAIN): a prospective multicenter randomized interventional trial protocol,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Supplemental Table 1. List of participating centers.,mds,True,findable,0,0,0,0,0,2023-04-13T11:34:54.000Z,2023-04-13T11:34:54.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Neuroscience,Biotechnology,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['20300 Bytes'],
+10.5281/zenodo.4760485,"Fig. 1 in Contribution To The Knowledge Of The Moroccan High And Middle Atlas Stoneflies (Plecoptera, Insecta)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 1. Distribution of Amphinemura berthelemyi, A. chiffensis, A. tiernodefigueroai sp. n. and A. yasriarum.",mds,True,findable,0,0,4,0,0,2021-05-14T05:26:13.000Z,2021-05-14T05:26:14.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Amphinemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Amphinemura'}]",,
+10.5281/zenodo.5729532,Topological surface states in epitaxial (SnBi2Te4 )n (Bi2Te3)m natural van der Waals superlattices (data),Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the raw data files connected to the figures included in the paper ""T<em>opological surface states in epitaxial (SnBi<sub>2</sub>Te<sub>4</sub> )<sub>n</sub> (Bi<sub>2</sub>Te<sub>3</sub>)<sub>m</sub> natural van der Waals superlattices</em>"" by S. Fragkos et al., Phys. Rev. Materials <strong>5</strong>, 014203 (2021) https://doi.org/10.1103/PhysRevMaterials.5.014203 An Open Access version of the paper can be found here: https://zenodo.org/record/4563899#.YaDQ5NBBxPY",mds,True,findable,0,0,0,0,0,2021-11-26T12:29:30.000Z,2021-11-26T12:29:30.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.59146,linbox: linbox-1.4.2,Zenodo,2016,,Software,Open Access,"LinBox - C++ library for exact, high-performance linear algebra",mds,True,findable,0,0,1,0,0,2016-07-30T19:05:23.000Z,2016-07-30T19:05:24.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7307563,"Geochemical, timescales data in orthopyroxenes from Kizimen 2010 eruption and database of studies linking diffusion timescales with monitoring signals.",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset comprises the geochemical data on whole rock analysis, melt inclusions, residual glasses, magnetites and orthopyroxenes in samples from the 2010 eruption of Kizimen volcano (Kamchatka), as well as the timescales modelled in the orthopyroxenes and a database of studies linking diffusion timescales with monitoring signals, associated with the publication: Ostorero, L., Balcone-Boissard, H., Boudon, G. <em>et al.</em> Correlated petrology and seismicity indicate rapid magma accumulation prior to eruption of Kizimen volcano, Kamchatka. <em>Commun Earth Environ</em> <strong>3</strong>, 290 (2022). https://doi.org/10.1038/s43247-022-00622-3",mds,True,findable,0,0,0,0,0,2022-11-20T18:41:16.000Z,2022-11-20T18:41:17.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6822165,Repeating low frequency icequakes in the Mont-Blanc massif,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This dataset provides catalogs of low-frequency icequakes detected in the Mont-Blanc massif (Alps) between 2017 and 2022.,mds,True,findable,0,0,0,0,0,2022-07-12T13:30:52.000Z,2022-07-12T13:30:53.000Z,cern.zenodo,cern,icequakes glaciers seismology repeaters,[{'subject': 'icequakes glaciers seismology repeaters'}],,
+10.5281/zenodo.5649807,"FIGS. 17–18 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIGS. 17–18—Protonemura alexidis sp. n., male. 17, terminalia, ventral view; 18, terminalia, with median and outer lobe sclerites, lateral view; FIGS. 19–22—Protonemura alexidis sp. n., female. 19, ventral view; 20, ventral view; 21, ventro-lateral view; 22, ventro-lateral view.",mds,True,findable,0,0,0,0,0,2021-11-05T21:11:27.000Z,2021-11-05T21:11:27.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.5500499,"Code and experiment data for the ICAPS 2019 paper ""Lagrangian Decomposition for Optimal Cost Partitioning""",Zenodo,2021,,Software,"GNU General Public License v3.0 or later,Open Access","This bundle contains code, scripts and benchmarks for reproducing all experiments reported in the paper. It also contains the data generated for the paper. pommerening-et-al-icaps2019-code.zip contains the implementation based on Fast Downward. It also contains the experiment scripts compatible with Lab 4.2 for reproducing all experiments of the paper, under experiments/lagrangian. (Note that some adjustments to the scripts would need to be done because, e.g., the entire tree is not a repository anymore.) pommerening-et-al-icaps2019-benchmarks.zip contains the benchmarks. It consists of the STRIPS IPC benchmarks used in all optimal sequential tracks of IPCs up to 2018 (suite optimal_strips from https://github.com/aibasel/downward-benchmarks). pommerening-et-al-icaps2019-lab.zip contains a copy of Lab 4.2 (https://github.com/aibasel/lab). pommerening-et-al-icaps2019-data.zip contains the experimental data. Directories without the ""-eval"" ending contain raw data, distributed over a subdirectory for each experiment. Each of these contain a subdirectory tree structure ""runs-*"" where each planner run has its own directory. For each run, it contains: the run log file ""run.log"" (stdout), possibly also a run error file ""run.err"" (stderr), the run script ""run"" used to start the experiment, and a ""properties"" file that contains data parsed from the log file(s). Directories with the ""-eval"" ending contain a ""properties"" file - a JSON file with the combined data of all runs of the corresponding experiment. In essence, the properties file is the union over all properties files generated for each individual planner run.",mds,True,findable,0,0,0,0,0,2021-09-10T18:14:10.000Z,2021-09-10T18:14:11.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5243189,Italian DBnary archive in original Lemon format,Zenodo,2021,it,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Italian language edition, ranging from 27th August 2012 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T10:22:49.000Z,2021-08-24T10:22:49.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.6084/m9.figshare.c.6795368.v1,Aberrant activation of five embryonic stem cell-specific genes robustly predicts a high risk of relapse in breast cancers,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background In breast cancer, as in all cancers, genetic and epigenetic deregulations can result in out-of-context expressions of a set of normally silent tissue-specific genes. The activation of some of these genes in various cancers empowers tumours cells with new properties and drives enhanced proliferation and metastatic activity, leading to a poor survival prognosis. Results In this work, we undertook an unprecedented systematic and unbiased analysis of out-of-context activations of a specific set of tissue-specific genes from testis, placenta and embryonic stem cells, not expressed in normal breast tissue as a source of novel prognostic biomarkers. To this end, we combined a strict machine learning framework of transcriptomic data analysis, and successfully created a new robust tool, validated in several independent datasets, which is able to identify patients with a high risk of relapse. This unbiased approach allowed us to identify a panel of five biomarkers, DNMT3B, EXO1, MCM10, CENPF and CENPE, that are robustly and significantly associated with disease-free survival prognosis in breast cancer. Based on these findings, we created a new Gene Expression Classifier (GEC) that stratifies patients. Additionally, thanks to the identified GEC, we were able to paint the specific molecular portraits of the particularly aggressive tumours, which show characteristics of male germ cells, with a particular metabolic gene signature, associated with an enrichment in pro-metastatic and pro-proliferation gene expression. Conclusions The GEC classifier is able to reliably identify patients with a high risk of relapse at early stages of the disease. We especially recommend to use the GEC tool for patients with the luminal-A molecular subtype of breast cancer, generally considered of a favourable disease-free survival prognosis, to detect the fraction of patients undergoing a high risk of relapse.",mds,True,findable,0,0,0,0,0,2023-08-18T03:20:44.000Z,2023-08-18T03:20:45.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Genetics,FOS: Biological sciences,Molecular Biology,Biological Sciences not elsewhere classified,Information Systems not elsewhere classified,Mathematical Sciences not elsewhere classified,Developmental Biology,Cancer,Plant Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Biological Sciences not elsewhere classified'}, {'subject': 'Information Systems not elsewhere classified'}, {'subject': 'Mathematical Sciences not elsewhere classified'}, {'subject': 'Developmental Biology'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",,
+10.5281/zenodo.8431185,yt-project/yt_astro_analysis: yt_astro_analysis-1.1.3,Zenodo,2023,,Software,Open Access,"What's Changed MNT: bump dev version by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/173 MNT: bump github action versions by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/174 TST: upgrade all Python versions in tests by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/176 BLD: migrate metadata to pyproject.toml, and drop setup.cfg by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/175 STY: upgrade pre-commit hooks, bump minimal version for pyupgrade and reduce auto-upgrade frequency by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/177 BLD: drop dependency on more_itertools by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/178 STY: upgrade black to 23.1.0 by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/179 TST: ensure test dependencies are correctly installed in CI by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/184 MNT: enable dependabot autoupdates for GitHub workflows by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/181 STY: migrate linting to ruff, add basic pre-commit hooks, cleanup .pre-commit-config.yaml by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/180 Bump pypa/cibuildwheel from 2.11.4 to 2.12.0 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/185 BUG: handle deprecation warning from numpy 1.25 (np.product is deprecated in favour of np.prod) by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/186 MNT: upgrade pre-commit hooks, simplify ruff config, update blacken-docs url by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/188 Bump pypa/gh-action-pypi-publish from 1.6.4 to 1.8.4 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/189 Bump pypa/cibuildwheel from 2.12.0 to 2.12.1 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/190 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/yt-project/yt_astro_analysis/pull/191 Bump pypa/cibuildwheel from 2.12.1 to 2.12.3 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/192 Bump pypa/gh-action-pypi-publish from 1.8.4 to 1.8.5 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/193 DOC: migrate away from configuration key format deprecated in Sphinx 7.0 by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/195 STY: activate flake8-comprehensions (ruff) by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/196 Bump pypa/gh-action-pypi-publish from 1.8.5 to 1.8.6 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/197 Bump pypa/cibuildwheel from 2.12.3 to 2.13.0 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/198 TST: treat warnings as errors by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/201 Bump pypa/cibuildwheel from 2.13.0 to 2.13.1 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/202 Bump pypa/gh-action-pypi-publish from 1.8.6 to 1.8.7 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/203 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/yt-project/yt_astro_analysis/pull/204 DEP: set upper limit to runtime numpy by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/205 MNT: avoid usage of deprecated unyt API by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/207 DOC: fix RadMC3DWriter's docstring (compat with modern yt) by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/206 MNT: cleanup unused variables by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/212 MNT: cleanup free of uninitialized variable by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/213 Bump pypa/gh-action-pypi-publish from 1.8.7 to 1.8.8 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/214 Bump pypa/cibuildwheel from 2.13.1 to 2.14.1 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/215 BLD: stop building wheels for Windows 32 by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/217 BLD: switch to Cython 3.0, forbid deprecated Numpy C API in generated code by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/211 BLD: add wheels for CPython 3.12 by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/216 BLD: migrate from oldest-supported-numpy to NPY_TARGET_VERSION (Python >= 3.9) by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/218 Bump pypa/gh-action-pypi-publish from 1.8.8 to 1.8.10 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/220 Support installation of rockstar through conda by @cphyc in https://github.com/yt-project/yt_astro_analysis/pull/219 DEP: drop support for CPython 3.8 by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/222 Bump actions/checkout from 3 to 4 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/223 BUG: fix usage of deprecated (and removed) clobber argument from astropy by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/226 Updated ppv_cube.py to avoid deprecated function 'update_all_headers' by @spectram in https://github.com/yt-project/yt_astro_analysis/pull/225 [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in https://github.com/yt-project/yt_astro_analysis/pull/230 Bump pypa/cibuildwheel from 2.15.0 to 2.16.2 in /.github/workflows by @dependabot in https://github.com/yt-project/yt_astro_analysis/pull/231 BUG: fix a couple bugs in PPVCube notebook by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/228 DOC: pin doc requirements by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/235 DOC: upgrade sphinx to latest version and enable automated upgrades for doc dependencies by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/237 REL: prep release 1.1.3 by @neutrinoceros in https://github.com/yt-project/yt_astro_analysis/pull/239 New Contributors @dependabot made their first contribution in https://github.com/yt-project/yt_astro_analysis/pull/185 @spectram made their first contribution in https://github.com/yt-project/yt_astro_analysis/pull/225 <strong>Full Changelog</strong>: https://github.com/yt-project/yt_astro_analysis/compare/yt_astro_analysis-1.1.2...yt_astro_analysis-1.1.3",mds,True,findable,0,0,0,0,0,2023-10-11T12:34:04.000Z,2023-10-11T12:34:04.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7602897,Replication package for the paper: Compositional Verification of Priority Systems Using Sharp Bisimulation,Zenodo,2023,,Software,"Creative Commons Attribution 4.0 International,Open Access","This is an archive of the data used to conduct the experiments presented in the following paper: Frederic Lang and Luca Di Stefano. Compositional Verification of Priority Systems Using Sharp Bisimulation. Submitted to the International Journal on Formal Methods in System Design, April 2022. Its contents are the following: The RERS19 directory contains the data and scripts needed to reproduce part of the experiments about the RERS 2019 challenge (""parallel CTL"" category) of Section 5.5. The TOY directory contains the data and scripts needed to reproduce the experiments of Section 6. The LEADER-ELECTION directory contains the data and scripts needed to reproduce the experiments of Section 7. To run the scripts present in this archive, one needs to install the toolbox CADP (Construction and Analysis of Distributed Processes). In particular, the sharp minimization algorithm presented in Sections 5.1 and 5.2 is implemented in the BCG_MIN and BCG_CMP tools of CADP. CADP licenses are free for academics and can be obtained by registering at the following URL: https://cadp.inria.fr/registration Note that Section 5.5 refers to the VLTS benchmark, which can be obtained freely from the following URL and is therefore not included in this archive: https://cadp.inria.fr/resources/vlts",mds,True,findable,0,0,0,0,0,2023-02-06T09:05:33.000Z,2023-02-06T09:05:33.000Z,cern.zenodo,cern,"Concurrency,Congruence,Enumerative verification,Finite state processes,Model checking,Process algebra,Formal methods","[{'subject': 'Concurrency'}, {'subject': 'Congruence'}, {'subject': 'Enumerative verification'}, {'subject': 'Finite state processes'}, {'subject': 'Model checking'}, {'subject': 'Process algebra'}, {'subject': 'Formal methods'}]",,
+10.5281/zenodo.10050323,Observation of an Exotic Insulator to Insulator Transition upon Electron Doping the Mott Insulator CeMnAsO,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"VASP input and output for the computational part of the paper ""Observation of an Exotic Insulator to Insulator Transition upon Electron Doping the Mott Insulator CeMnAsO"".
+stoichiometric.tar.gz: Data for stoichiometric CeMnAsOdefective.tar.gz: Data for CeMnAsO0.94F0.06",api,True,findable,0,0,0,0,0,2023-10-28T18:53:53.000Z,2023-10-28T18:53:53.000Z,cern.zenodo,cern,"many body localisation,CeMnAsO,VASP","[{'subject': 'many body localisation'}, {'subject': 'CeMnAsO'}, {'subject': 'VASP'}]",,
+10.6084/m9.figshare.23575390.v1,Additional file 11 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 10,mds,True,findable,0,0,0,0,0,2023-06-25T03:12:05.000Z,2023-06-25T03:12:06.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['36864 Bytes'],
+10.6084/m9.figshare.c.6771537,"Supplementary material from ""Mirror exposure following visual body-size adaptation does not affect own body image""",The Royal Society,2023,,Collection,Creative Commons Attribution 4.0 International,"Prolonged visual exposure to large bodies produces a thinning aftereffect on subsequently seen bodies, and vice versa. This visual adaptation effect could contribute to the link between media exposure and body shape misperception. Indeed, people exposed to thin bodies in the media, who experience fattening aftereffects, may internalize the distorted image of their body they see in the mirror. This preregistered study tested this internalization hypothesis by exposing 196 young women to an obese adaptor before showing them their reflection in the mirror, or to a control condition. Then, we used a psychophysical task to measure the effects of this procedure on perceptual judgements about their own body size, relative to another body and to the control mirror exposure condition. We found moderate evidence against the hypothesized self-specific effects of mirror exposure on perceptual judgements. Our work strengthens the idea that body size adaptation affects the perception of test stimuli rather than the participants' own body image. We discuss recent studies which may provide an alternative framework to study media-related distortions of perceptual body image.",mds,True,findable,0,0,0,0,0,2023-08-02T11:18:30.000Z,2023-08-02T11:18:31.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",,
+10.6084/m9.figshare.22604164,Additional file 1 of Early management of isolated severe traumatic brain injury patients in a hospital without neurosurgical capabilities: a consensus and clinical recommendations of the World Society of Emergency Surgery (WSES),figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1. Appendix 1. Consensus participants.,mds,True,findable,0,0,0,0,0,2023-04-13T10:34:17.000Z,2023-04-13T10:34:18.000Z,figshare.ars,otjm,"Medicine,Genetics,FOS: Biological sciences,Molecular Biology,Ecology,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Ecology'}, {'subject': 'Science Policy'}]",['15123 Bytes'],
+10.57745/tvahuq,Long term monitoring of near surface soil temperature in the french Alps part of ORCHAMP observatory,Recherche Data Gouv,2023,,Dataset,,"Monitoring of near-surface soil temperature in seasonaly snow-covered, mountain ecosystems located in the French Alps. Data are part the ORCHAMP project. Data include a GPS position, a date and time in UTC and a near-surface soil temperature (in °C) measured at 5 cm belowground using stand-alone temperature data logger. The first sensors were installed in 2016. Data collection is still in progress and new sites are added every year since 2016.",mds,True,findable,41,7,0,0,0,2023-03-27T14:02:49.000Z,2023-07-18T07:43:40.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.6517730,Development and evaluation of a method to identify potential release areas of snow avalanches based on watershed delineation - source data,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Full data files for the paper: Duvillier, C., Eckert, N., Evin, G., and Deschâtres, M.: Development and evaluation of a method to identify potential release areas of snow avalanches based on watershed delineation, Nat. Hazards Earth Syst. Sci., 23, 1383–1408, https://doi.org/10.5194/nhess-23-1383-2023, 2023. Can be used to reproduce all the results of the paper and for further benchmarking of snow avalanche potential release area detection methods.",mds,True,findable,0,0,0,0,0,2022-05-04T16:42:51.000Z,2022-05-04T16:42:51.000Z,cern.zenodo,cern,"Snow Avalanches,Potential Release Area,,Validation,Confusion Matrix,Watershed,French Alps","[{'subject': 'Snow Avalanches'}, {'subject': 'Potential Release Area,'}, {'subject': 'Validation'}, {'subject': 'Confusion Matrix'}, {'subject': 'Watershed'}, {'subject': 'French Alps'}]",,
+10.5281/zenodo.8391579,Revealing trends in extreme heatwave intensity: Applying the UNSEEN approach to Nordic countries - Supplementary Material,Zenodo,2023,,Other,Creative Commons Attribution 4.0 International,"In this folder we gathered some additional material to our paper on UNSEEN applied to heatwaves in Northern Europe. You will find:
+
+
+- Codes:
+Â Â Â - Jupyter code used to compute region-averaged timeseries of both UNSEEN ensemble and reanalysis data. For downloading data from Copernicus CDS please refer to Timo Kelder's codes: https://unseen-open.readthedocs.io/en/latest/index.html
+Â Â Â - R markdown file including all the statistical analysis of the timeseries obtained from the jupyter code.
+- Data:
+Â Â Â - Gridded netCDF files of 3day running mean Tmax for both SEAS5 ensemble and MET Nordic LTC (based on NORA3 reanalysis). Archived SEAS5 seasonal forecast data are available at ECMWF MARS archive: https://apps.ecmwf.int/mars-catalogue/ . Description and availability of the MET Nordic long-term consistent product can be found at MET Norway's Github pages: https://github.com/metno/NWPdocs/wiki/MET-Nordic-dataset .
+Â Â Â - Gridded MJJ 2m temperature, mean for each year (also SEAS5).
+Â Â Â - Modified NUTS regions. Shapefiles of the NUTS dataset are available from Eurostat's webpages: https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units
+- Figures:
+Â Â Â Â The figures included in the paper as well as supplementary figures in high resolution.
+- Results:
+Â Â Â - Notebooks for all regions containing the detailed analysis with all the 'usual' (from UNSEEN-open) UNSEEN plots, return period plots, probability calculations etc.
+Â Â Â - An Excel-spreadsheet containing many of the resulting values. The maps were plotted on this basis.
+
+
+Â ",api,True,findable,0,0,0,0,0,2023-10-16T14:48:34.000Z,2023-10-16T14:48:34.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4591774,Data from the IRAM-30m Large Program `Astrochemical Surveys At IRAM' (ASAI),Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset for the ASAI IRAM-30m Large Program (https://www.iram-institute.org/EN/content-page-344-7-158-240-344-0.html) provided in zenodo within the framework of ACO (AstroChemical Origins): (H2020 MSCA ITN, GA:811312) The reference article is Lefloch et al. 2018, Monthly Notices of the Royal Astronomical Society, Volume 477, Issue 4, p.4792-4809 whose doi is: 10.1093/mnras/sty937 Fully reduced spectral line surveys are included for 10 young stellar objects. SOURCE SAMPLE: <br> ----------------------------------------------------------------------------------------------------------------<br> Sources alpha(2000) delta(2000) rms rms rms dnu Comment <br> (3mm) (2mm) (1.3mm) kHz<br> ----------------------------------------------------------------------------------------------------------------<br> L1544 05h04m17.2s 25d10'42.8"" 2.1-7.0 - - 48.8 Evolved prestellar core<br> TMC1 04h41m41.9s 25d41'27.1"" 3.0-6.3 4.2-4.2 - 48.8, 195.3 Early prestellar core<br> B1 03h33m20.8s 31d07'34.0"" 2.5-10.6 4.4-8.0 4.2-4.6 195.3 First hydrostatic core<br> IRAS4A 03h29m10.4s 31d13'32.2"" 2.5-3.4 5.0-6.1 4.6-3.9 195.3 Class 0: Hot corino prototype<br> L1527 04h39m53.9s 26d03'11.0"" 2.1-6.7 4.2-7.1 4.6-4.1 195.3 Class 0: WCCC prototype<br> L1157mm 20h39m06.3s 68d02'15.8"" 3.0-4.7 5.0-6.5 3.8-3.5 195.3 Class 0: WCCC<br> SVS13A 03h29m03.7s 31d16'03.8"" 2.0-4.8 4.2-5.1 4.6-4.3 195.3 Class I: Hot corino<br> AB Aur 04h55m45.8s 30d33'33.0"" 4.6-4.3 4.8-3.9 2.1-4.3 195.3 Protoplanetary disk<br> L1448-R2 03h25m40.1s 30d43'31.0"" 2.8-4.9 6.0-9.7 2.9-4.9 195.3 Outflow shock spot<br> L1157-B1 20h39m10.2s 68d01'10.5"" 1.1-2.9 4.6-7.2 2.1-4.2 195.3 Outflow shock spot<br> ------------------------------------------------------------------------------------------------------------------<br> i)spectral coverage, spectral resolution, and range of rms noise achieved in an element of 1 km/s for each spectral window. <br> The rms values (in TA*) are measured in the range 86-87 GHz and 113-114 GHz at 3mm, 132-133 GHz and 169-170 GHz at 2mm, <br> 220-221 and 260-261 GHz.<br> ii) No data were obtained at 2mm and 1.3mm for L1544, at 3mm and 1.3mm for TMC1. <br> iii) Complementary observations in the band 72-80 GHz have been obtained for L1544 and protostars IRAS4A, L1527, L1157mm, <br> SVS13A. The 72-80 GHz and 106-115 GHz data of L1544 will be made available in a forthcoming release<br> iv) The data of AB Aur will be made available in a forthcoming release <br> OBSERVATIONS AND SPECTRAL COVERAGE:<br> Details about the observing procedure and the calibration can be found in the article presenting ASAI: ""Astrochemical evolution <br> along star formation: Overview of the IRAM Large Program ASAI"" (Lefloch, Bachiller et al. 2017). L1544 80.0 - 106.0 GHz TMC1 130.0 - 164.9 GHz ; gap from 161.6 to 163.0 GHz Barnard1 80.5 - 112.2 GHz <br> 130.0 - 172.7 GHz <br> 200.5 - 276.0 GHz IRAS4A 71.7 - 79.6 GHz <br> 80.5 - 112.3 GHz <br> 125.5 - 133.3 GHz <br> 130.0 - 172.8 GHz <br> 200.5 - 276.0 GHz L1527 71.7 - 79.6 GHz <br> 80.5 - 112.3 GHz <br> 125.5 - 133.3 GHz <br> 130.0 - 172.8 GHz <br> 200.5 - 276.0 GHz L1157mm 71.7 - 79.6 GHz <br> 80.5 - 112.3 GHz <br> 125.5 - 133.3 GHz <br> 130.0 - 172.8 GHz <br> 200.5 - 276.0 GHz SVS13A 71.7 - 79.6 GHz <br> 80.5 - 116.0 GHz <br> 125.5 - 133.3 GHz <br> 130.0 - 172.8 GHz <br> 200.5 - 276.0 GHz L1448-R2 80.5 - 116.0 GHz <br> 130.0 - 173.3 GHz <br> 200.5 - 276.0 GHz <br> L1157-B1 71.7 - 79.5 GHz <br> 78.0 - 118.0 GHz; fts 390 kHz res;<br> 125.5 - 133.3 GHz <br> 128.2 - 173.7 GHz <br> 200.2 - 265.5 GHz; fts 781 kHz res;<br> 260.4 - 322.1 GHz; WILMA 2 MHz res: <br> 328.4 - 350.1 GHz; WILMA 2 MHz res; The data obtained for each source are located in the corresponding subdirectory: <br> source_f1_f2.fits : calibrated spectral band in the band f1 - f2 (in GHz) <br> source_72_80.fits : complementary data in the bands 72-80 GHz whenever observed. <br> source_125_133.fits : complementary data in the band 125.5-133.5 whenever observed. <br> UNITS:<br> The line intensity are expressed in units of antenna temperature corrected for atmospheric attenuation and the coupling with <br> the sky, TA*, by default. The interested user should to the IRAM webpage http://www.iram.es/IRAMES/mainWiki/Iram30mEfficiencies <br> to convert line intensities from antenna to main-beam temperature scale. <br> QUESTIONS and ACKNOWLEDGMENTS<br> If you have any questions about the data please contact us<br> (bertrand.lefloch@univ-grenoble-alpes.fr, r.bachiller@oan.es). We also like to hear about any<br> scientific use of the data and would appreciate acknowledgment in<br> publications or talks using the ASAI data. <br>",mds,True,findable,0,0,0,0,0,2021-03-10T10:28:31.000Z,2021-03-10T10:28:32.000Z,cern.zenodo,cern,"astrochemistry, protostars, star-forming regions, prestellar cores, radio-astronomy","[{'subject': 'astrochemistry, protostars, star-forming regions, prestellar cores, radio-astronomy'}]",,
+10.5281/zenodo.4923680,Data for chemical tuning of spin clock transitions in molecular monomers based on nuclear spin-free Ni(ii),Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Sets of data supporting all figures from the related publication. A list of files and information on how they have been processed are given in a separate sheet.,mds,True,findable,0,0,0,0,0,2021-06-10T15:16:06.000Z,2021-06-10T15:16:07.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8362722,PecubeGUI-beta,Zenodo,2023,en,Software,"Creative Commons Attribution 3.0 Germany,Open Access","PecubeGUI-beta is a newly developed user interface for Pecube that includes grain-specific kinetic parameters, additional diffusion model for apatite and zircon (U-Th)/He thermochronometry, and additional annealing models for apatite fission tracks. The interface is designed to help the users to check their input parameters before running a Pecube model, as well as to plot their results in a simple way.",mds,True,findable,0,0,0,0,0,2023-09-25T07:26:33.000Z,2023-09-25T07:26:33.000Z,cern.zenodo,cern,"Thermochronology,Pecube,Numerical modelling","[{'subject': 'Thermochronology'}, {'subject': 'Pecube'}, {'subject': 'Numerical modelling'}]",,
+10.6084/m9.figshare.c.6250158,Expiratory high-frequency percussive ventilation: a novel concept for improving gas exchange,figshare,2022,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Although high-frequency percussive ventilation (HFPV) improves gas exchange, concerns remain about tissue overdistension caused by the oscillations and consequent lung damage. We compared a modified percussive ventilation modality created by superimposing high-frequency oscillations to the conventional ventilation waveform during expiration only (eHFPV) with conventional mechanical ventilation (CMV) and standard HFPV. Methods Hypoxia and hypercapnia were induced by decreasing the frequency of CMV in New Zealand White rabbits (n = 10). Following steady-state CMV periods, percussive modalities with oscillations randomly introduced to the entire breathing cycle (HFPV) or to the expiratory phase alone (eHFPV) with varying amplitudes (2 or 4 cmH2O) and frequencies were used (5 or 10 Hz). The arterial partial pressures of oxygen (PaO2) and carbon dioxide (PaCO2) were determined. Volumetric capnography was used to evaluate the ventilation dead space fraction, phase 2 slope, and minute elimination of CO2. Respiratory mechanics were characterized by forced oscillations. Results The use of eHFPV with 5 Hz superimposed oscillation frequency and an amplitude of 4 cmH2O enhanced gas exchange similar to those observed after HFPV. These improvements in PaO2 (47.3 ± 5.5 vs. 58.6 ± 7.2 mmHg) and PaCO2 (54.7 ± 2.3 vs. 50.1 ± 2.9 mmHg) were associated with lower ventilation dead space and capnogram phase 2 slope, as well as enhanced minute CO2 elimination without altering respiratory mechanics. Conclusions These findings demonstrated improved gas exchange using eHFPV as a novel mechanical ventilation modality that combines the benefits of conventional and small-amplitude high-frequency oscillatory ventilation, owing to improved longitudinal gas transport rather than increased lung surface area available for gas exchange.",mds,True,findable,0,0,0,0,0,2022-10-16T03:12:42.000Z,2022-10-16T03:12:43.000Z,figshare.ars,otjm,"Biophysics,Space Science,Medicine,Physiology,FOS: Biological sciences,Biotechnology,Cancer","[{'subject': 'Biophysics'}, {'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Biotechnology'}, {'subject': 'Cancer'}]",,
+10.5281/zenodo.5998113,"PrISM satellite rainfall product (2010-2021) based on SMOS soil moisture measurements in Africa (3h, 0.1°)",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The PrISM product is a satellite precipitation product available for Africa over a regular grid at 0.1° (about 10x10 km²) and every 3 hours. It is obtained from the synergy of SMOS satellite soil moisture measurements and IMERG-Early Run precipitation product through the PrIMS algorithm (<em>Pellarin et al., 2009, 2013, 2020, 2022, Louvet et al., 2015, </em>Román-Cascón et al. 2017).",mds,True,findable,0,0,0,0,0,2022-02-07T16:46:53.000Z,2022-02-07T16:46:54.000Z,cern.zenodo,cern,Rainfall product (mm/3h) in Africa (2010-2020),[{'subject': 'Rainfall product (mm/3h) in Africa (2010-2020)'}],,
+10.5281/zenodo.4115984,Distant entanglement via fast and coherent electron shuttling,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","In the quest for large-scale quantum computing, networked quantum computers offer a natural path towards scalability. While recent experiments have demonstrated nearest neighbour entanglement for electron spin qubits in semiconductors, on-chip long distance entanglement could bring more versatility to connect quantum core units. Here, we employ the moving trapping potential of a surface acoustic wave to realize the controlled and coherent transfer of a pair of entangled electron spins between two distant quantum dots. The subsequent electron displacement induces coherent spin rotations, which drives spin quantum interferences. We observe high-contrast interference as a signature of the preservation of the entanglement all along the displacement procedure, which includes a separation of the two spins by a distance of 6 μm. This work opens the route towards fast on-chip deterministic interconnection of remote quantum bits in semiconductor quantum circuits.",mds,True,findable,0,0,0,0,0,2020-10-22T08:50:14.000Z,2020-10-22T08:50:15.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.8gtht76tq,Estimation of changes in behaviour of narwhals,Dryad,2023,en,Dataset,Creative Commons Zero v1.0 Universal,"Anthropogenic activities are increasing in the Arctic posing a threat to species with high seasonal site-fidelity, such as the narwhal Monodon monoceros. In this controlled sound exposure study, six narwhals were live-captured and instrumented with animal-borne tags providing movement and behavioural data, and exposed to 1) ship noise and 2) concurrent ship noise and airgun pulses.",mds,True,findable,108,6,0,0,0,2023-07-09T03:51:26.000Z,2023-07-09T03:51:27.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences,narwhal,Monodon monoceros,Sound exposure","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'narwhal'}, {'subject': 'Monodon monoceros'}, {'subject': 'Sound exposure'}]",['213268148 bytes'],
+10.5281/zenodo.2641812,X-ray diffraction images for Adenylate kinase from M. thermolithotrophicus.,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Anomalous data collected at ESRF (Grenoble, France) using beamline ID23-1. The crystal was in the presence of the crystallophore Tb-Xo4.
+
+
+
+Related Publication: Engilberge et al. (2019)
+
+Data collection:
+
+ Detector: PILATUS 6M.
+
+ OSCILLATION_RANGE= 0.1000
+
+ X-RAY_WAVELENGTH= 1.64862
+
+ DETECTOR_DISTANCE= 183.94",mds,True,findable,0,0,0,0,0,2019-04-16T10:05:35.000Z,2019-04-16T10:05:36.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.14754468,"Artifact and instructions to generate experimental results for the Euro-Par 2021 paper: ""Sustaining Performance While Reducing Energy Consumption: A Control Theory Approach""",figshare,2021,,Dataset,Creative Commons Attribution 4.0 International,"This artifact contains the code to reproduce experiments and data analysis of the paper ""Sustaining Performance While Reducing Energy Consumption: A Control Theory Approach"" by S. Cerf, R. Bleuse, V. Reis, S. Pernarnau and É. Rutten.This artifact also contains the data collected and used to produce the figures of the paper.<br>This artifact is provided as a tar archive.Scripts are provided as bash, Python and R programs.The data format is a compressed tar archive documented by the Python extraction code.<br>The dataset is licensed under CC-BY 4.0. See the source code for their respective licenses.<br>",mds,True,findable,0,0,1,0,0,2021-06-10T14:17:13.000Z,2021-06-10T14:17:13.000Z,figshare.ars,otjm,"10203 Calculus of Variations, Systems Theory and Control Theory,FOS: Mathematics,Applied Computer Science,80302 Computer System Architecture,FOS: Computer and information sciences","[{'subject': '10203 Calculus of Variations, Systems Theory and Control Theory', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Mathematics', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Applied Computer Science'}, {'subject': '80302 Computer System Architecture', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Computer and information sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['1328670720 Bytes'],
+10.5281/zenodo.7986836,Experimental dataset: SMART for reliable NN inference in a neutron-irradiated OS-based system,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",TBA,mds,True,findable,0,0,0,0,0,2023-06-02T10:31:46.000Z,2023-06-02T10:31:46.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3941193,"Electroweak-ino benchmark points from arXiv:2007.08498, Minimal Dirac Gaugino Model",Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Benchmark points from the paper ""Constraining Electroweakinos in the Minimal Dirac Gaugino Model"": - Input files for spectrum generation with SPheno (https://dx.doi.org/10.5281/zenodo.3945999) - Input files in SUSY Les Houches Accord (SLHA) format for MadGraph, Micromegas, and SModelS. For Micromegas and SModelS, also the output files are included. - Calchep model files for the MDGSSM for use in Micromegas; the UFO model for MadGraph is available at https://doi.org/10.5281/zenodo.2422746. In SModelS, one simply has to set <em>model=share.models.dgmssm</em> in the parameters.ini file.",mds,True,findable,0,0,0,0,0,2020-07-17T06:08:05.000Z,2020-07-17T06:08:06.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10005462,"Data for the paper: ""Folding a Cluster containing a Distributed File-System""",Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"Associated paper: https://hal.science/hal-04038000
+The repository containing the analysis scripts is available here
+
+NFS repo
+OrangeFS repo",api,True,findable,0,0,0,0,0,2023-10-15T23:10:54.000Z,2023-10-15T23:10:54.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5158465,Rule-based generative design of translational and rotational interlocking assemblies,Zenodo,2021,,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access",Video illustrating the ideas and limitations developped in our eponymous article.,mds,True,findable,0,0,0,0,0,2021-08-04T08:13:16.000Z,2021-08-04T08:13:17.000Z,cern.zenodo,cern,"Computational design,Shape partitioning,Interlocking assembly,Formal grammar,Turtle Graphics","[{'subject': 'Computational design'}, {'subject': 'Shape partitioning'}, {'subject': 'Interlocking assembly'}, {'subject': 'Formal grammar'}, {'subject': 'Turtle Graphics'}]",,
+10.6084/m9.figshare.22609322.v1,Additional file 2 of TRansfusion strategies in Acute brain INjured patients (TRAIN): a prospective multicenter randomized interventional trial protocol,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 2. SPIRIT Checklist for Trials.,mds,True,findable,0,0,0,0,0,2023-04-13T11:34:55.000Z,2023-04-13T11:34:56.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Neuroscience,Biotechnology,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['34625 Bytes'],
+10.5281/zenodo.4761341,"Figs. 63-71. Dictyogenus alpinum, larva. 63 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 63-71. Dictyogenus alpinum, larva. 63. Head and pronotum. Rioufroid, Lus-la-Croix-Haute, Drôme dpt, France. Photo A. Ruffoni. 64. Lacinia. Rioufroid, Lus-la-Croix-Haute, Drôme dpt, France. Photo A. Ruffoni. 65. Pronotum, mesonotum and metanotum, lateral view. Vorz river, Belledonne massif, Isère dpt, France. Photo B. Launay. 66. Detail of head. Rioufroid, Lus-la-Croix-Haute, Drôme dpt, France. Photo A. Ruffoni. 67. Medio-dorsal setae on cerci. Riau du Gros Mont, Les Planeys, canton of Fribourg, Switzerland. Photo J.- P.G. Reding. 68. Paragenital plates, ventral view. Riau du Gros Mont, Les Planeys, canton of Fribourg, Switzerland. Photo J.-P.G. Reding. 69. Stipe. Vorz river, Belledonne massif, Isère dpt, France. Photo B. Launay. 70. Femur and tibia of hind leg, lateral view. Riau du Gros Mont, Les Planeys, canton of Fribourg,",mds,True,findable,0,0,6,0,0,2021-05-14T07:50:35.000Z,2021-05-14T07:50:36.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.7755633,Python package for icequakes inversions,Zenodo,2023,,Software,"Creative Commons Attribution 4.0 International,Open Access","This package was used to process seismic data recorded on sea ice in Svalbard (Norway), in March 2019. The inversion determines the position of the icequake source and sea ice thickness. More details in: Moreau et al, Analysis of microseismicity in sea ice with deep learning and Bayesian inference: application to high-resolution thickness monitoring, The Cryosphere (2023): https://doi.org/10.5194/tc-2022-212",mds,True,findable,0,0,0,0,0,2023-03-21T09:36:31.000Z,2023-03-21T09:36:31.000Z,cern.zenodo,cern,"icequake inversion, sea ice","[{'subject': 'icequake inversion, sea ice'}]",,
+10.6084/m9.figshare.23983484,Additional file 1 of Aberrant activation of five embryonic stem cell-specific genes robustly predicts a high risk of relapse in breast cancers,figshare,2023,,Text,Creative Commons Attribution 4.0 International,"Additional file 1: Fig. S1. (A) Heatmap showing the expression of 1882 genes in normal adult tissues with predominant expression in testis (male germinal), embryonic stem cells (ES cells) or placenta, and not expressed in normal breast (female genital). The expression levels of all genes are normalized by scaling each feature to a range between zero and one. The genes are ordered according their normalized expression levels in the tissues of interest (testis, placenta and ES cells, respectively). (B) Venn diagram showing the distribution of 1882 genes according the tissue of predominance: testis, embryonic stem cells and/or placenta. Fig. S2. Flow chart representing the main steps of the biomarker discovery pipeline. Fig. S3. Expression profiles in normal tissues of the five genes in the GEC panel DNMT3B, EXO1, MCM10, CENPF and CENPE based on RNA-seq data from GTEX and NCBI Sequence Read Archive. All five genes have a predominant expression profile in embryonic stem cells. They are also expressed in testis (male germinal) at lower levels. These genes are not expressed in normal breast and female genital tissues. Fig. S4. Kaplan-Meier individual survival curves of the genes DNMT3B, EXO1, MCM10, CENPF and CENPE in the training (TCGA-BRCA) and validation (GSE25066, GSE21653, GSE42568) datasets.",mds,True,findable,0,0,0,0,0,2023-08-18T03:20:41.000Z,2023-08-18T03:20:41.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Genetics,FOS: Biological sciences,Molecular Biology,Biological Sciences not elsewhere classified,Information Systems not elsewhere classified,Mathematical Sciences not elsewhere classified,Developmental Biology,Cancer,Plant Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Biological Sciences not elsewhere classified'}, {'subject': 'Information Systems not elsewhere classified'}, {'subject': 'Mathematical Sciences not elsewhere classified'}, {'subject': 'Developmental Biology'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",['510839 Bytes'],
+10.5281/zenodo.4763381,[Artifacts] Sustaining Performance While Reducing Energy Consumption: A Control Theory Approach,Zenodo,2021,en,Dataset,Closed Access,"This archive contains the dataset and the code to reproduce the experiments of the publication ""Sustaining Performance While Reducing Energy Consumption: A Control Theory Approach""",mds,True,findable,0,0,0,0,0,2021-05-14T20:17:25.000Z,2021-05-14T20:17:26.000Z,cern.zenodo,cern,"power regulation,HPC,control theory","[{'subject': 'power regulation'}, {'subject': 'HPC'}, {'subject': 'control theory'}]",,
+10.5061/dryad.hmgqnk9hh,The tempo of greening in the European Alps: Spatial variations on a common theme,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"The long-term increase of satellite-based proxies of vegetation cover is a well-documented response of seasonally snow-covered ecosystems to climate warming. However, observed greening trends are far from being uniform and substantial uncertainty remains concerning the underlying causes of this spatial variability. Here, we processed surface reflectance of the moderate resolution imaging spectroradiometer (MODIS) to investigate trends and drivers of changes in the annual peak values of the Normalized Difference Vegetation Index (NDVI). Our study focuses on the above treeline ecosystems in the European Alps. The NDVI changes of these ecosystems are highly sensitive to land cover and biomass changes and are marginally affected by anthropogenic disturbances. We found a widespread greening for the period 2000-2020, a pattern that is consistent with the overall increase of summer temperature. At the local scale, the spatial variability of greening was mainly due to the preferential response of north-facing slopes between 1900 m and 2400 m. Using high resolution imagery, we noticed that the presence of screes and outcrops locally magnified this response. At the regional scale, we identified hotspots of greening where vegetation cover is sparser than expected given the elevation and exposure. Most of these hotspots experienced delayed snowmelt and green-up dates in recent years. We conclude that the ongoing greening in the Alps primarily reflects the high responsiveness of sparsely vegetated ecosystems that are able to benefit the most from temperature and water-related habitat amelioration above treeline.",mds,True,findable,153,3,0,0,0,2021-08-05T18:10:34.000Z,2021-08-05T18:10:35.000Z,dryad.dryad,dryad,"plant ecology; climate change,European Alps,alpine ecosystems,Greening trends","[{'subject': 'plant ecology; climate change'}, {'subject': 'European Alps'}, {'subject': 'alpine ecosystems'}, {'subject': 'Greening trends'}]",['101088493 bytes'],
+10.5281/zenodo.2585685,Data for Figs. 5 and 9 of arXiv:1812.09293,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","MadGraph5 <strong>parameter cards</strong> (i.e. SLHA files) and MadAnalysis5 <strong>CLs summaries</strong> for the scan points used to define the 95% CL exclusion contours in the gluino vs. squark mass plane, for scenarios DG1, DG2, DG3 and MSSM1 presented in Figure 5 as well as scenarios DG4 and MSSM4 presented in Figure 9 of the paper ""LHC limits on gluinos and squarks in the minimal Dirac gaugino model"", arXiv:1812.09293.",mds,True,findable,0,0,0,0,0,2019-03-07T10:59:12.000Z,2019-03-07T10:59:13.000Z,cern.zenodo,cern,"LHC,supersymmetry,reinterpretation","[{'subject': 'LHC'}, {'subject': 'supersymmetry'}, {'subject': 'reinterpretation'}]",,
+10.5281/zenodo.8144596,"Data for ""Chasing rainbows and ocean glints: Inner working angle constraints for the Habitable Worlds Observatory""",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data for the paper on ""Chasing rainbows and ocean glints: Inner working angle constraints for the Habitable Worlds Observatory""",mds,True,findable,0,0,0,0,0,2023-07-13T18:32:59.000Z,2023-07-13T18:33:00.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8171326,PAS: a Python Anesthesia Simulator for drug control,Zenodo,2023,en,Software,"GNU General Public License v3.0 only,Open Access","The Python Anesthesia Simulator (PAS) models the effect of drugs on physiological variables during total intravenous anesthesia. It is particularly dedicated to the control community, to be used as a benchmark for the design of multidrug controllers. The available drugs are propofol, remifentanil, and norepinephrine, the outputs are the bispectral index (BIS), mean arterial pressure (MAP), cardiac output (CO), and tolerance of laryngoscopy (TOL). PAS includes different well-known models along with their uncertainties to simulate inter-patient variability. Blood loss can also be simulated to assess the controller's performance in a shock scenario. Finally, PAS includes standard disturbance profiles and metric computation to facilitate the evaluation of the controller's performance.",mds,True,findable,0,0,0,0,0,2023-07-21T11:05:38.000Z,2023-07-21T11:05:39.000Z,cern.zenodo,cern,"Anesthesia SImulator,Automatic drug dosage,Pharmacokinetic,Pharmacodynamic","[{'subject': 'Anesthesia SImulator'}, {'subject': 'Automatic drug dosage'}, {'subject': 'Pharmacokinetic'}, {'subject': 'Pharmacodynamic'}]",,
+10.6084/m9.figshare.c.6842762.v1,Non-ventilator-associated ICU-acquired pneumonia (NV-ICU-AP) in patients with acute exacerbation of COPD: From the French OUTCOMEREA cohort,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Non-ventilator-associated ICU-acquired pneumonia (NV-ICU-AP), a nosocomial pneumonia that is not related to invasive mechanical ventilation (IMV), has been less studied than ventilator-associated pneumonia, and never in the context of patients in an ICU for severe acute exacerbation of chronic obstructive pulmonary disease (AECOPD), a common cause of ICU admission. This study aimed to determine the factors associated with NV-ICU-AP occurrence and assess the association between NV-ICU-AP and the outcomes of these patients. Methods Data were extracted from the French ICU database, OutcomeReaâ„¢. Using survival analyses with competing risk management, we sought the factors associated with the occurrence of NV-ICU-AP. Then we assessed the association between NV-ICU-AP and mortality, intubation rates, and length of stay in the ICU. Results Of the 844 COPD exacerbations managed in ICUs without immediate IMV, NV-ICU-AP occurred in 42 patients (5%) with an incidence density of 10.8 per 1,000 patient-days. In multivariate analysis, prescription of antibiotics at ICU admission (sHR, 0.45 [0.23; 0.86], p = 0.02) and no decrease in consciousness (sHR, 0.35 [0.16; 0.76]; p < 0.01) were associated with a lower risk of NV-ICU-AP. After adjusting for confounders, NV-ICU-AP was associated with increased 28-day mortality (HR = 3.03 [1.36; 6.73]; p < 0.01), an increased risk of intubation (csHR, 5.00 [2.54; 9.85]; p < 0.01) and with a 10-day increase in ICU length of stay (p < 0.01). Conclusion We found that NV-ICU-AP incidence reached 10.8/1000 patient-days and was associated with increased risks of intubation, 28-day mortality, and longer stay for patients admitted with AECOPD.",mds,True,findable,0,0,0,0,0,2023-09-20T03:22:51.000Z,2023-09-20T03:22:52.000Z,figshare.ars,otjm,"Medicine,Microbiology,FOS: Biological sciences,Genetics,Molecular Biology,Neuroscience,Biotechnology,Evolutionary Biology,Immunology,FOS: Clinical medicine,Cancer,Science Policy,Virology","[{'subject': 'Medicine'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Genetics'}, {'subject': 'Molecular Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Evolutionary Biology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}, {'subject': 'Virology'}]",,
+10.6084/m9.figshare.24202753,Additional file 3 of Obstructive sleep apnea: a major risk factor for COVID-19 encephalopathy?,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 3: Supplemental Table 3. Cerebrospinal fluid analyses at the time of COVID-19 acute encephalopathy.,mds,True,findable,0,0,0,0,0,2023-09-27T03:26:11.000Z,2023-09-27T03:26:12.000Z,figshare.ars,otjm,"Biophysics,Medicine,Cell Biology,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,Sociology,FOS: Sociology,Immunology,FOS: Clinical medicine,Cancer,Mental Health,Virology","[{'subject': 'Biophysics'}, {'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Mental Health'}, {'subject': 'Virology'}]",['19116 Bytes'],
+10.48380/dggv-p1k4-1p40,Hydrogen and organic molecules generation from water radiolysis: from grave to cradle,Deutsche Geologische Gesellschaft - Geologische Vereinigung e.V. (DGGV),2021,en,Text,,"Water radiolysis is a key process for hydrogen (H2) and abiotic organic molecules generation in the Earth’s crust. The aim of this presentation is to provide some insight into this process from a radiochemist viewpoint. We will transpose the knowledge we gain from water radiolysis in the context of radioactive waste disposal to natural geological settings and draw important conclusions for deep microbial ecosystems development and abiotic organic synthesis. Some examples will be given about: (i) the relationship between H2 production ant the nature of the emitted particle (α/β/γ) considered for water radiolysis, (ii) the boosted production of H2 observed when aqueous solutions are in contact with some mineral surfaces such as rutile (TiO2) and calcite (CaCO3), (iii) the scavenging role of carbonate anions onto hydroxyl radical and the amplified yield of H2, (iv) the switch from an inorganic world to an organic one through the carboxylate anions production from carbonate radiolysis. Radiation chemistry is often overlooked by geologists who consider the process as anecdotic (apart for the thermal budget of Earth) in term of mass balance. However, water radiolysis is a large-scale ubiquist process in the crust and it does not need specific conditions to occur. We will show that at geological time scale, water radiolysis leads to a very diverse, reactive, and fun chemistry able to sustain life and even to create the condition for its emergence.",fabricaForm,True,findable,0,0,0,0,0,2022-04-12T12:21:04.000Z,2022-04-12T12:21:30.000Z,mcdy.dohrmi,mcdy,,,,
+10.5281/zenodo.3909853,Étude de cas sociolinguistique et ethnographique de quatre familles indiennes immigrantes en Europe : pratiques langagières et politiques linguistiques nationales & familiales,Zenodo,2012,fr,Other,"Creative Commons Attribution 4.0 International,Open Access","Ce travail de recherche s’inscrit dans une approche pluridisciplinaire – monographique, ethnographique et sociolinguistique avec une dimension longitudinale. Il tente de décrire de manière approfondie les pratiques langagières familiales de quatre familles indiennes immigrantes installées dans quatre pays européens : la France, la Suède, la Norvège et la Finlande. Cette étude cherche également à cerner les enjeux des politiques linguistiques familiales, domaine dans lequel peu de recherches ont été entreprises et qui, de ce fait, reste à développer. Par ailleurs, les idéologies et attitudes concernant les langues se traduisent dans les décisions prises par les chefs de la famille, les parents, qui privilégient l’apprentissage de telle ou telle langue, pour eux-mêmes et surtout pour les enfants. Au plan macro, la politique linguistique nationale de chacun des pays concernés par notre étude est évoquée, y compris celle de l’Inde, avec un centrage sur la politique linguistique éducative et les modalités d’enseignement des langues migrantes. Le plurilinguisme des participants est analysé avec la notion de répertoire multilingue au sein duquel les compétences langagières sont segmentées par domaine. Les notions d’espace, de contexte, de mobilité, d’échelle, de polycentralité et d’ordres d’indexicalité ont été convoquées pour pouvoir appréhender ces compétences. La transmission linguistique intergénérationnelle est abordée par le biais d’une analyse critique de la politique linguistique familiale et nationale ainsi que la question de l’incidence du legs des valeurs culturelles et linguistiques du pays d’origine (ou de son absence) sur la construction de l’identité de la deuxième génération. L’apport principal de cette thèse est de porter un regard sur les questions de langues en lien avec la migration qui ne s’inscrit pas dans la perspective des pays d’accueil, mais celle des migrants eux-mêmes.f",mds,True,findable,0,0,0,0,0,2021-12-30T23:07:37.000Z,2021-12-30T23:07:38.000Z,cern.zenodo,cern,"politique linguistique familiale,politique linguistique nationale,familles migrantes d'origine indienne en Europe","[{'subject': 'politique linguistique familiale'}, {'subject': 'politique linguistique nationale'}, {'subject': ""familles migrantes d'origine indienne en Europe""}]",,
+10.6084/m9.figshare.20235676,Implementation of a biopsychosocial approach into physiotherapists’ practice: a review of systematic reviews to map barriers and facilitators and identify specific behavior change techniques,Taylor & Francis,2022,,Dataset,Creative Commons Attribution 4.0 International,"Our first objective was to map the barriers and facilitators to the implementation of a biopsychosocial approach into physiotherapists’ practice within the Theoretical Domains Framework (TDF). Our second objective was to identify the specific behavior change techniques (BCT) that could facilitate this implementation. We conducted a review of systematic reviews to identify barriers and facilitators to the use of a biopsychosocial approach by physiotherapists and we mapped them within the TDF domains. We then analyzed these domains using the Theory and Techniques tool (TaTT) to identify the most appropriate BCTs for the implementation of a biopsychosocial approach into physiotherapists’ practice. The barriers and facilitators to the use of a biopsychosocial approach by physiotherapists were mapped to 10 domains of the TDF (Knowledge; skills; professional role; beliefs about capabilities; beliefs about consequences; intentions; memory, attention and decision processes; environmental context; social influences; emotion). The inclusion of these domains within the TaTT resulted in the identification of 33 BCTs that could foster the use of this approach by physiotherapists. Investigating the implementation of a biopsychosocial approach into physiotherapists’ practice from a behavior change perspective provides new strategies that can contribute to successfully implement this approach.Implications for RehabilitationThe implementation of a biopsychosocial approach into physiotherapists’ practice is a complex process which involves behavior changes influenced by several barriers and facilitators.Barriers and facilitators reported by physiotherapists when implementing a biopsychosocial approach can be mapped within 10 domains of the Theoretical Domain Framework.Thirty-three behavior change techniques (e.g., verbal persuasion about capability, problem solving, restructuring the physical environment, etc.) were identified to foster the implementation of a biopsychosocial approach and specifically target barriers and facilitators.By using a behavior change perspective, this study highlights new strategies and avenues that can support current efforts to successfully implement the use of a biopsychosocial approach into physiotherapists’ practice. The implementation of a biopsychosocial approach into physiotherapists’ practice is a complex process which involves behavior changes influenced by several barriers and facilitators. Barriers and facilitators reported by physiotherapists when implementing a biopsychosocial approach can be mapped within 10 domains of the Theoretical Domain Framework. Thirty-three behavior change techniques (e.g., verbal persuasion about capability, problem solving, restructuring the physical environment, etc.) were identified to foster the implementation of a biopsychosocial approach and specifically target barriers and facilitators. By using a behavior change perspective, this study highlights new strategies and avenues that can support current efforts to successfully implement the use of a biopsychosocial approach into physiotherapists’ practice.",mds,True,findable,0,0,0,1,0,2022-07-06T02:40:05.000Z,2022-07-06T02:40:05.000Z,figshare.ars,otjm,"Space Science,Medicine,Genetics,FOS: Biological sciences,Neuroscience,Ecology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,19999 Mathematical Sciences not elsewhere classified,FOS: Mathematics,Cancer,Plant Biology","[{'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Neuroscience'}, {'subject': 'Ecology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '19999 Mathematical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Mathematics', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",['164588 Bytes'],
+10.5281/zenodo.7310803,pySICE: A python package for the retrieval of snow surface properties from Sentinel 3 OLCI reflectances,Zenodo,2022,en,Software,GNU Affero General Public License v3.0 only,"B. Vandecrux (1), A. Kokhanovsky (2), G. Picard (3) and J. Box (1)
+
+
+(1) Geological Survey of Denmark and Greenland (GEUS) Øster Voldgade 10, 1350 Copenhagen, Denmark (2) Max Planck Institute for Chemistry, Mainz 55128, Federal Republic of Germany (3) Institut des Géosciences de l'Environnement, Université de Grenoble, France
+
+
+This algorithm retrieves the snow surface properties using Sentinel-3's OLCI 865nm and 1020 nm bands and the theory developed by A. Kokhanovsky in:
+
+
+
+
+Kokhanovsky et al. (2018) On the reflectance spectroscopy of snow
+
+Kokhanovsky et al. (2019) Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument
+
+Kokhanovsky et al. (2020) The Determination of Snow Albedo from Satellite Measurements Using Fast Atmospheric Correction Technique
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+
+
+It includes the ozone retrieval from the OLCI 620 nm band developed in: Kokhanovsky et al. (2020) Retrieval of the total ozone over Antarctica using Sentinel-3 ocean and land colour instrument
+
+
+And the retrieval of impurity load and characteristics from OLCI 400nm and 490nm bands developed in: Kokhanovsky, A. A., et al., 2021a: Retrieval of dust properties from spectral snow reflectance measurements
+
+
+It is also the version that will be converted into a SNAP plug-in.",mds,True,findable,0,0,0,1,0,2022-11-10T13:37:27.000Z,2022-11-10T13:37:27.000Z,cern.zenodo,cern,"snow,ice,albedo,remote sensing,python,radiative transfer","[{'subject': 'snow'}, {'subject': 'ice'}, {'subject': 'albedo'}, {'subject': 'remote sensing'}, {'subject': 'python'}, {'subject': 'radiative transfer'}]",,
+10.5281/zenodo.6568218,"Data and Analysis Script for Cluster2022 Submission pap254: ""Painless Transposition of Reproducible Distributed Environments with NixOS Compose""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data and Analysis Script for Cluster2022 Submission pap254: ""Painless Transposition of Reproducible Distributed Environments with NixOS Compose"" The experiments repository is available at: https://gitlab.inria.fr/nixos-compose/articles/cluster2022",mds,True,findable,0,0,0,0,0,2022-05-20T22:25:05.000Z,2022-05-20T22:25:06.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3403088,Laboratory modeling of gap-leaping and intruding western boundary currents under different climate change scenarios,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Western boundary currents (WBCs), such as, the Kuroshio and the Gulf Stream, are very intense currents flowing along the western boundaries of the oceans.<br>WBCs -and their respective extensions- have an important effect on climate because of their huge heat transports, the corresponding air–sea interactions and the role they play in sustaining the global conveyor belt. It is therefore very relevant to analyze WBC dynamics not only through observations and numerical modelling, but also by means of laboratory experiments; to this respect several rotating tank experiments have been performed in recent years.<br>The new laboratory experiments proposed here for the Hydralab+ 19GAPWEBS project are aimed at analyzing the interactions of a WBC with gaps located along the western coast. Examples of such processes include the Gulf Stream leaping from the Yucatan to Florida and the Kuroshio leaping, and partly penetrating, through the South and East China Seas and through the wider gap separating Taiwan to Japan. In the experiments the WBC is produced by a horizontally unsheared current flowing over a topographic beta slope; along the western lateral boundary a sequence of gaps of different widths simulate the openings present in the above mentioned locations.",mds,True,findable,0,0,0,0,0,2019-09-11T07:23:51.000Z,2019-09-11T07:23:51.000Z,cern.zenodo,cern,,,,
+10.26302/sshade/experiment_op_20191119_001,Vis-NIR bidirectional reflection spectra of several ammonium salts mixed with pyrrhotite grains in sublimate residues at 173 K,SSHADE/GhoSST (OSUG Data Center),2020,en,Dataset,"Any use of downloaded SSHADE data in a scientific or technical paper or a presentation is free but you should cite both SSHADE and the used data in the text ( 'first author' et al., year) with its full reference (with its DOI) in the main reference section of the paper (or in a special 'data citation' section) and, when available, the original paper(s) presenting the data.","Dry mixtures (called ""sublimate residues"") of sub-micrometer size opaque pyrrhotite (Fe1-xS) grains with ammonium (NH4+) salts (chloride, sulfate, formate, carbamate, citrate) were prepared by sublimation of ice-dust mixtures. Reflectance spectra (from 0.4 to 4 µm) of these mixtures were measured at 173 K under high vacuum (pressure lower than 10^-5 mbar).",mds,True,findable,0,0,0,1,0,2020-02-12T11:12:51.000Z,2020-02-12T11:12:52.000Z,inist.sshade,mgeg,"natural terrestrial,sulfide,Pyrrhotite provided by Museum National d'Histoire Naturelle, Paris, France,commercial,chloride,Ammonium chloride,sulfate,Ammonium sulfate,Pyrrhotite from Alfa Aesar (ref. 042652),organic salt,Ammonium formate,Ammonium carbamate,Ammonium citrate dibasic,laboratory measurement,bidirectional reflection,macroscopic,Vis,Visible,NIR,Near-Infrared,reflectance factor","[{'subject': 'natural terrestrial'}, {'subject': 'sulfide'}, {'subject': ""Pyrrhotite provided by Museum National d'Histoire Naturelle, Paris, France""}, {'subject': 'commercial'}, {'subject': 'chloride'}, {'subject': 'Ammonium chloride'}, {'subject': 'sulfate'}, {'subject': 'Ammonium sulfate'}, {'subject': 'Pyrrhotite from Alfa Aesar (ref. 042652)'}, {'subject': 'organic salt'}, {'subject': 'Ammonium formate'}, {'subject': 'Ammonium carbamate'}, {'subject': 'Ammonium citrate dibasic'}, {'subject': 'laboratory measurement'}, {'subject': 'bidirectional reflection'}, {'subject': 'macroscopic'}, {'subject': 'Vis'}, {'subject': 'Visible'}, {'subject': 'NIR'}, {'subject': 'Near-Infrared'}, {'subject': 'reflectance factor'}]",['8 spectra'],['ASCII']
+10.5281/zenodo.7928522,Data Assimilation of realistic SWOT satellite observations,Zenodo,2020,en,Other,"Creative Commons Attribution 4.0 International,Open Access","For the past 25 years, satellite altimetry has produced Sea Surface Height (SSH) maps which have allowed oceanographers to study large-scale ocean dynamics (> 200km). However, the small scales of ocean circulation play a key role in a variety of natural phenomena. In order to research on finer scale ocean dynamics, the future SWOT mission will provide the capability of making measurements of SSH with unprecedented resolution. This will bring challenges to the current data processing techniques and therefore, more advanced techniques are being developed. One such technique is the Back-and-Forth Nudging (BFN) data assimilation<br> method which provides SSH maps consistent with both real-world measurements and the physics of a numerical ocean model. The objective of this project is to test and evaluate different strategies for implementing the BFN method with realistic SWOT observations accounting for both noise and errors. The results show that, for a low signal-to-noise ratio region, de-noising the SWOT observations<br> is essential for a good performance of BFN. Under de-noised observations, the best strategy was found to be by nudging only the relative vorticity (RV) term. This strategy reconstructed SSH fields with an effective resolution of 60 km and RMSE score of 0.81. For a region with high signal-to-noise ratio, the BFN method appeared robust to noisy observations. Once again, it was found that after denoising observations, the best strategy was nudging the RV term only. This strategy reconstructed SSH fields with an effective resolution of 89.9 km and RMSE score of 0.86.",mds,True,findable,0,0,0,0,0,2023-05-12T08:50:17.000Z,2023-05-12T08:50:18.000Z,cern.zenodo,cern,"Data Assimilation,Ocean Surface,Satellite Altimetry,Quasi-Geostrophic Model","[{'subject': 'Data Assimilation'}, {'subject': 'Ocean Surface'}, {'subject': 'Satellite Altimetry'}, {'subject': 'Quasi-Geostrophic Model'}]",,
+10.6084/m9.figshare.23822151,File 5 : Matlab file for part 1 and of the experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,File 5 : This matlab file corresponds to the baseline PSE measures and should be launched first.,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:25.000Z,2023-08-02T11:18:25.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['15465 Bytes'],
+10.6084/m9.figshare.24202750.v1,Additional file 2 of Obstructive sleep apnea: a major risk factor for COVID-19 encephalopathy?,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 2: Supplemental Table 2. Comparison of patient characteristics at the time of COVID-19 onset and COVID-19 acute encephalopathy between definite OSA group and No OSA group.,mds,True,findable,0,0,0,0,0,2023-09-27T03:26:09.000Z,2023-09-27T03:26:09.000Z,figshare.ars,otjm,"Biophysics,Medicine,Cell Biology,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,Sociology,FOS: Sociology,Immunology,FOS: Clinical medicine,Cancer,Mental Health,Virology","[{'subject': 'Biophysics'}, {'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Mental Health'}, {'subject': 'Virology'}]",['28280 Bytes'],
+10.5281/zenodo.10200663,DBnary - Wiktionary Lexical Data in RDF/Ontolex - All languages,Zenodo,2023,mul,Dataset,Creative Commons Attribution 4.0 International,"The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Since July 1st 2017, the lexical data extracted from Wiktionary is modelled using the Ontolex vocabulary.
+This dataset contains all language data (in 2023, 25 language editions are supported) and contains one version per Wikimedia dump (one version twice a month).",api,True,findable,0,0,0,0,0,2023-11-24T11:02:14.000Z,2023-11-24T11:02:14.000Z,cern.zenodo,cern,"Wiktionary,LLOD,Linguistic Linked Open Data,Ontolex,RDF","[{'subject': 'Wiktionary'}, {'subject': 'LLOD'}, {'subject': 'Linguistic Linked Open Data'}, {'subject': 'Ontolex'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.5950801,"DataMerge, a command line tool to interpolate data files of time series... and much more",Zenodo,2022,,Software,"GNU General Public License v2.0 or later,Open Access","<strong>DataMerge</strong> DataMerge is a linux command line which allows to merge a number of datafiles organised in columns indexed in a one-dimensional way into a single dataset. It can handle files of data tabulated on different grids, by using interpolation methods. E.g., data recorded every 10 seconds and data recorded every 15 seconds can be interpolated into either grid. Interpolation can be linear between adjacent points, or use a least-square approximation on a moving window. It also allows to process columns individually, perform cross-column calculations or change the unit in which quantities are expressed. Several other methods also allow to perform cross-row calculations, such as finite differences or normalisation by an automatically detected entry row. <strong>Functionalities</strong> Interpolate between datasets Select values Normalise data by value reached at some timepoint Multiple columns bulk management Multicolumn statistics (expanded in v1.1.0) Calculate finite differences Cumulate values across rows (new in v1.1.0) Interpolate between datasets with LOESS Calculate derivatives with LOESS <strong>See the DataMerge wiki for more!</strong> <strong>Example</strong> <pre><code class=""language-bash"">datamerge -f \ --reference example/dataset_sampling_3.tsv 'time_sampling_3' \ 'line_sampling_3 time_sampling_3 sinusoidal exponential' \ --input example/dataset_sampling_7.tsv 'time_sampling_7' \ 'line_sampling_7 time_sampling_7 cosinusoidal exponential_sampling_7' \ -o example/linear_interpolation.tsv 'time' \ 'sinusoidal cosinusoidal exponential exponential-exponential_sampling_7 sinusoidal^2+cosinusoidal^2'</code></pre> Sample from output: <pre><code>time sinusoidal cosinusoidal exponential exponential-exponential_sampling_7 sinusoidal^2+cosinusoidal^2 0 0 na 1 na na 3 0.187381 0.96325 1.03045 -0.000525714 0.962962 6 0.368125 0.911084 1.06184 -0.000524286 0.96559 9 0.535827 0.83509 1.09417 -0.00034 0.984485 12 0.684547 0.711437 1.1275 -0.00067 0.974748 15 0.809017 0.587785 1.16183 0 1 18 0.904827 0.416183 1.19722 -0.000717143 0.99192 </code></pre> Available from https://gricad-gitlab.univ-grenoble-alpes.fr/etiennej/datamerge (C) J Etienne 2012-2022 DataMerge is released under GPL 2 licence. DataMerge logo CC-BY 4.0 based on original work by Delapouite",mds,True,findable,0,0,0,0,0,2022-02-02T22:17:55.000Z,2022-02-02T22:17:56.000Z,cern.zenodo,cern,"time series,interpolation,data management,scripting,bash,command line,spreadsheet alternative","[{'subject': 'time series'}, {'subject': 'interpolation'}, {'subject': 'data management'}, {'subject': 'scripting'}, {'subject': 'bash'}, {'subject': 'command line'}, {'subject': 'spreadsheet alternative'}]",,
+10.5281/zenodo.4753283,"Figs. 16a-f. Perlodes spp. eggs, lateral view. a. P in A New Perlodes Species And Its Subspecies From The Balkan Peninsula (Plecoptera: Perlodidae)",Zenodo,2012,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 16a-f. Perlodes spp. eggs, lateral view. a. P. intricatus (France). b. P. jurassicus (Switzerland). c. P. dispar (Hungary). d. P. microcephalus (Hungary). e. P. floridus floridus sp. n. (Montenegro), 0,4 mm high. f. P. floridus peloponnesiacus ssp. n. (Greece).",mds,True,findable,0,0,4,0,0,2021-05-12T18:32:45.000Z,2021-05-12T18:32:46.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Perlodes","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Perlodes'}]",,
+10.5281/zenodo.3611936,Supplementary data for 'Results of the third Marine Ice Sheet Model Intercomparison Project (MISMIP+)',Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Datasets and model datasheets provided to the third Marine Ice Sheet Model Intercomparison Project (MISMIP+),mds,True,findable,0,0,0,0,0,2020-01-18T08:40:54.000Z,2020-01-18T08:40:55.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.22604164.v1,Additional file 1 of Early management of isolated severe traumatic brain injury patients in a hospital without neurosurgical capabilities: a consensus and clinical recommendations of the World Society of Emergency Surgery (WSES),figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1. Appendix 1. Consensus participants.,mds,True,findable,0,0,0,0,0,2023-04-13T10:34:17.000Z,2023-04-13T10:34:17.000Z,figshare.ars,otjm,"Medicine,Genetics,FOS: Biological sciences,Molecular Biology,Ecology,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Ecology'}, {'subject': 'Science Policy'}]",['15123 Bytes'],
+10.5281/zenodo.4264747,Vocal drum sounds in Human Beatboxing: an acoustic and articulatory exploration using electromagnetic articulography,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This dataset constitutes the supplementary material of a paper in review in the Journal of the Acoustical Society of America (JASA),mds,True,findable,0,0,0,1,0,2020-11-09T16:44:37.000Z,2020-11-09T16:44:37.000Z,cern.zenodo,cern,"beatbox,vocal drum sound,boxeme","[{'subject': 'beatbox'}, {'subject': 'vocal drum sound'}, {'subject': 'boxeme'}]",,
+10.5281/zenodo.3873088,Raw diffraction data for [NiFeSe] hydrogenase G491S variant pressurized with O2 gas - dataset G491S-O2,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","Diffraction data measured at ESRF beamline ID29 on October 2, 2017. Image files are uploaded as blocks of cbf files in gzip-compressed tar files.",mds,True,findable,5,0,0,0,0,2020-06-02T13:27:04.000Z,2020-06-02T13:27:05.000Z,cern.zenodo,cern,"Hydrogenase,Selenium,gas channels,high-pressure derivatization","[{'subject': 'Hydrogenase'}, {'subject': 'Selenium'}, {'subject': 'gas channels'}, {'subject': 'high-pressure derivatization'}]",,
+10.7280/d1595v,Annual Ice Velocity of the Greenland Ice Sheet (2001-2010),Dryad,2019,en,Dataset,Creative Commons Attribution 4.0 International,"We derive surface ice velocity using data from 16 satellite sensors deployed by 6 different space agencies. The list of sensors and the year that they were used are listed in the following (Table S1). The SAR data are processed from raw to single look complex using the GAMMA processor (www.gamma-rs.ch). All measurements rely on consecutive images where the ice displacement is estimated from tracking or interferometry (Joughin et al. 1998, Michel and Rignot 1999, Mouginot et al. 2012). Surface ice motion is detected using a speckle tracking algorithm for SAR instruments and feature tracking for Landsat. The cross-correlation program for both SAR and optical images is ampcor from the JPL/Caltech repeat orbit interferometry package (ROI_PAC). We assembled a composite ice velocity mosaic at 150 m posting using our entire speed database as described in Mouginot et al. 2017 (Fig. 1A). The ice velocity maps are also mosaicked in annual maps at 150 m posting, covering July, 1st to June, 30th of the following year, i.e. centered on January, 1st (12) because a majority of historic data were acquired in winter season, hence spanning two calendar years. We use Landsat-1&2/MSS images between 1972 and 1976 and combine image pairs up to 1 year apart to measure the displacement of surface features between images as described in Dehecq et al., 2015 or Mouginot et al. 2017. We use the 1978 2-m orthorectified aerial images to correct the geolocation of Landsat-1 and -2 images (Korsgaard et al., 2016). Between 1984 and 1991, we processed Landsat-4&5/TM image pairs acquired up to 1-year apart. Only few Landsat-4 and -5 images (~3%) needed geocoding refinement using the same 1978 reference as used previously. Between 1991 and 1998, we process radar images from the European ERS-1/2, with a repeat cycle varying from 3 to 36 days depending on the mission phase. Between 1999 and 2013, we use Landsat-7, ASTER, RADARSAT-1/2, ALOS/PALSAR, ENVISAT/ASAR to determine surface velocity (Joughin et al., 2010; Howat, I. 2017; Rignot & Mouginot, 2012). After 2013, we use Landsat-8, Sentinel-1a/b and RADARSAT-2 (Mouginot et al., 2017). All synthetic aperture radar (SAR) datasets are processed assuming surface parallel flow using the digital elevation model (DEM) from the Greenland Mapping Project (GIMP; Howat et al., 2014) and calibrated as described in Mouginot et al., 2012, 2017. Data were provided by the European Space Agency (ESA) the EU Copernicus program (through ESA), the Canadian Space Agency (CSA), the Japan Aerospace Exploration Agency (JAXA), the Agenzia Spaziale Italiana (ASI), the Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) and the National Aeronautics and Space Administration (NASA). SAR data acquisition were coordinated by the Polar Space Task Group (PSTG). References: Dehecq, A, Gourmelen, N, Trouve, E (2015). Deriving large-scale glacier velocities from a complete satellite archive: Application to the Pamir-Karakoram-Himalaya. Remote Sensing of Environment, 162, 55–66. Howat IM, Negrete A, Smith BE (2014) The greenland ice mapping project (gimp) land classification and surface elevation data sets. The Cryosphere 8(4):1509–1518. Howat, I (2017). MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from Optical Images, Version 2. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. Joughin, I., B. Smith, I. Howat, T. Scambos, and T. Moon. (2010). Greenland Flow Variability from Ice-Sheet-Wide Velocity Mapping, J. of Glac.. 56. 415-430. Joughin IR, Kwok R, Fahnestock MA (1998) Interferometric estimation of three dimensional ice-flow using ascending and descending passes. IEEE Trans. Geosci. Remote Sens. 36(1):25–37. Joughin, I, Smith S, Howat I, and Scambos T (2015). MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. Michel R, Rignot E (1999) Flow of Glaciar Moreno, Argentina, from repeat-pass Shuttle Imaging Radar images: comparison of the phase correlation method with radar interferometry. J. Glaciol. 45(149):93–100. Mouginot J, Scheuchl B, Rignot E (2012) Mapping of ice motion in Antarctica using synthetic-aperture radar data. Remote Sens. 4(12):2753–2767. Mouginot J, Rignot E, Scheuchl B, Millan R (2017) Comprehensive annual ice sheet velocity mapping using landsat-8, sentinel-1, and radarsat-2 data. Remote Sensing 9(4). Rignot E, Mouginot J (2012) Ice flow in Greenland for the International Polar Year 2008-2009. Geophys. Res. Lett. 39, L11501:1–7.",mds,True,findable,773,126,1,1,0,2019-03-29T10:37:23.000Z,2019-03-29T10:37:25.000Z,dryad.dryad,dryad,,,['7193679240 bytes'],
+10.5281/zenodo.4761351,"Fig. 84 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 84. Dictyogenus fontium species complex, female, subgenital plate. Rhaetian Alps, Switzerland. Photo J.- P.G. Reding.",mds,True,findable,0,0,6,0,0,2021-05-14T07:51:59.000Z,2021-05-14T07:52:00.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.7584063,Sea salt aerosol AOD at 550nm derived from MODIS,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset uses MODIS MOD08_M3 and MYD08_M3 data to derive monthly sea salt aerosol optical depth, using the Angstrom exponent as a filtering criterion. This dataset was created for the publication ""The representation of sea salt aerosols and their role in polar climate within CMIP6"", JGR: Atmospheres, 2023. The methodology for building this dataset is described in the publication, and the scripts used to do so can be found on GitHub at https://github.com/rlapere/CMIP6_SSA_Paper. The time period covered is 2005-2014, with a monthly time step. Warning: this dataset is only valid for polar regions, where sea salt dominate coarse mode aerosols. outside of 60-90N and 60-90S this product should not be used.",mds,True,findable,0,0,0,1,0,2023-01-30T10:48:43.000Z,2023-01-30T10:48:43.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4804627,FIGURES 7–10 in Review and contribution to the stonefly (Insecta: Plecoptera) fauna of Azerbaijan,Zenodo,2021,,Image,Open Access,"FIGURES 7–10. Habitats of Leuctra fusca ssp. (Linnaeus, 1758) in Azerbaijan—7: forest stream in the Talysh Mts, site 15; 8: forest brook in the Lesser Caucasus, site 38; 9: large stream in the Lesser Caucasus, site 41; 10: temporary, open brook in the Lesser Caucasus, site 45.",mds,True,findable,0,0,5,0,0,2021-05-26T07:54:58.000Z,2021-05-26T07:54:59.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.3454628,Bead tracking experimental ground truth for studying size segregation in bedload sediment transport,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Video sequences to study size segregation in bedload transport were recorded. Experiments consisted in mixtures of two-size spherical glass beads entrained by a turbulent supercritical free surface water flow over a mobile bed. The aim is to track all beads over time to obtain trajectories, particle velocities and concentrations, for studying bedload granular rheology, size segregation and associated morphology. This upload consists in : a 1000-frame experimental image sequence recorded at 130 fps with approximately 400 beads per frame (about 300 coarse and 100 small beads). The image resolution is 1280x320; the ground truth in the directory \result . It was obtained based on a tracking algorithm with subsequent expert modification. The tracking algorithm was developed by H. Lafaye de Micheaux et al. The code implementing the tracking algorithm is available on https://github.com/hugolafaye/BeadTracking. The ground truth is a '.mat' file containing in particular the variable 'trackData' being a cell array of tracking matrices. There is one tracking matrix for each image of the sequence. Complete information on data format is given in the file readme.txt in the github BeadTracking package. In addition it contains three files allowing the user to run the BeadTracking package specifically on the experimental sequence : sequence_param.txt : parameter file sequence_base_mask.tif : to remove the base template_transparent_bead_rOut10_rIn6.mat : a template for bead detection",mds,True,findable,1,0,0,0,0,2019-09-30T11:53:18.000Z,2019-09-30T11:53:19.000Z,cern.zenodo,cern,"sediment transport,bedload transport,segregation,two-phase flow,particle tracking,granular flow,Multiple targets tracking ·","[{'subject': 'sediment transport'}, {'subject': 'bedload transport'}, {'subject': 'segregation'}, {'subject': 'two-phase flow'}, {'subject': 'particle tracking'}, {'subject': 'granular flow'}, {'subject': 'Multiple targets tracking ·'}]",,
+10.5281/zenodo.10165854,Thickness map of the Patagonian Icefields,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Ice thickness field for the Patagonian icefields relying on mass-conservation approach, which assimilates both glacier retreat data as well as an abundant record of direct thickness measurements. The thickness map has a time stamp of 2000. This map is provided together with error estimates and the basal topography beneath the icefields based on c-SRTM (v2.1) (Farr, T. et al. The Shuttle Radar Topography Mission. Reviews of Geophysics 45 (2007), http://dx.doi.org/10.1029/2005RG000183.)",api,True,findable,0,0,0,0,0,2023-11-21T10:31:14.000Z,2023-11-21T10:31:14.000Z,cern.zenodo,cern,"Patagonia,glacier,icefield,thickness","[{'subject': 'Patagonia'}, {'subject': 'glacier'}, {'subject': 'icefield'}, {'subject': 'thickness'}]",,
+10.5281/zenodo.10063860,MIPkit-W (MISOMIP2),Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Observational data kit gathered and reprocessed to facilitate the evaluation of ocean simulations of the Weddell Sea as part of MISOMIP2.
+__________________________________________
+This entire dataset should be cited as:
+
+the MISOMIP2 MIPkit-W dataset (https://zenodo.org/doi/10.5281/zenodo.8316180) that includes data collected through multiple cruises of the Polarstern Research Vessel and originally provided by the Alfred Wegener Institute, Bremerhaven, Germany.
+For more specific use of some of the MIPkit-W data, we encourage people to cite the original data referenced below.
+__________________________________________
+Oce3d_MIPkitW_* : 3-dimensional temperature and salinity (horizontal slices every 100m)
+The hydrographic properties provided on horizontal sections at 15 depths come from the CTD measurements obtained from late December to early March during the Alfred Wegener Institute Polarstern cruises ANT-XII/3 (Schroeder, 2010), PS82 (Schroeder, 2014), PS96 (Schroeder, 2016) and PS111 (Janout, 2019), which cover years 1995, 2014, 2016 and 2018, respectively.
+__________________________________________
+OceSec<n>_MIPkitW_* : vertical sections
+The first vertical section (OceSec1) goes from the tip of the Antartic Peninsula to Kapp Norvegia (12.33°E). It is known as WOCE-SR04 and has been monitored since 1989. The data provided were collected during Polarstern cruises in Sep.-Oct. 1989, Nov.-Dec. 1990, Dec. 1992-Jan. 1993, Mar.-May 1996, Apr.-May 1998 (Fahrbach and Rohardt, 1990, 1991, 1993, 1996, 1998), Jan.-Apr. 2005 (Rohardt 2010), Feb.-Apr. 2008 (Fahrbach and Rohardt, 2008), Dec. 2010-Jan. 2011 (Rohardt et al. 2011), Dec. 2012-Jan. 2013 (Rohardt 2013), as well as Dec. 2016-Jan. 2017 and Dec. 2018-Feb. 2019 (Rohardt and Boebel, 2017, 2020).
+The second vertical section (OceSec2) is at approximately 76°S and covers the eastern side of Filchner Through. It was surveyed during some of the Polarstern cruises on 5-8 Jan. 2014 (Schroeder, 2014), 20-24 Jan. 2016 (Schroeder, 2016) and 4-23 Feb. 2018 (Janout, 2019).
+The third and fourth sections were obtained along the front of Ronne (OceSec3) and Filchner (OceSec4) ice shelves, respectively. The Filchner section was measured on 1-3 Feb. 1977 by the Norwegian Antarctic Research Expedition with Research Vessel Polarsirkel (Foldvik et al., 1985), 7-16 Jan. 1981 (Hubold and Drescher, 1982), 25 Jan.- 4 Mar. 1995 (Schroeder, 2010), 15-17 Jan. 2014 (Schroeder, 2014), 15 Jan. 2016 (only one vertical profile; Schroeder, 2016), and 14-23 Feb. 2018 (Janout, 2019). The Ronne section was measured by some of these expeditions on 25 Jan.- 24 Feb. 1995, 14-15 Jan. 2016, and 9-14 Feb. 2018.
+The files OceSec<n>_MIPkitW_model_lon_lat.csv contain the coordinates (longitude, latitude) at which model data should be interpolated to be compared to the observational sections.
+__________________________________________
+OceMoor<n>_MIPkitW_* : moorings
+Temperature, salinity and velocity time series are provided at three moorings placed along the 76°S vertical section and referred to as OceMoor1 (AWI252, 30.47°W), OceMoor2 (AWI253, 30.99°W) and OceMoor3 (AWI254, 31.48°W), and cover the period from Jan. 2014 to Feb. 2018 (Schroeder et al., 2017a,b,c, 2019a,b,c). Temperature, salinity and velocity data were obtained at two depths for AWI252 (335 and 421 m depth for a seafloor at 447 m) and AWI253 (349 and 434 m depth for a seafloor at 456 m), while a single depth is provided for AWI254 (553 m for a seafloor at 581 m).
+Â
+__________________________________________
+The archive example_routines.zip  contains example of Matlab routines that were used to prepare the MIPkit-W data.
+Â
+__________________________________________
+References
+Fahrbach, E. and Rohardt, G. (1990). Physical oceanography during POLARSTERN cruise ANT-VIII/2 (WWGS) on section SR02 and SR04, PANGAEA, https://doi.org/10.1594/PANGAEA.742580
+Fahrbach, E. and Rohardt, G. (1991). Physical oceanography during POLARSTERN cruise ANT-IX/2 on section SR04, PANGAEA, https://doi.org/10.1594/PANGAEA.735277
+Fahrbach, E. and Rohardt, G. (1993). Physical oceanography during POLARSTERN cruise ANT-X/7 on section SR04, PANGAEA, https://doi.org/10.1594/PANGAEA.742651
+Fahrbach, E. and Rohardt, G. (1996). Physical oceanography during POLARSTERN cruise ANT-XIII/4 on section S04A, PANGAEA, https://doi.org/10.1594/PANGAEA.738489
+Fahrbach, E. and Rohardt, G. (1998): Physical oceanography during POLARSTERN cruise ANT-XV/4 (DOVETAIL) on section SR04, PANGAEA, https://doi.org/10.1594/PANGAEA.742626
+Fahrbach, E. and Rohardt, G. (2008): Physical oceanography during POLARSTERN cruise ANT-XXIV/3, PANGAEA, https://doi.org/10.1594/PANGAEA.733414
+Foldvik, A,, Gammelsrød,T. & Tørresen, T. 1985: Hydrographic observations from the Weddell Sea during the Norwegian Antarctic Research Expedition 1976/77. Polar Research, 3:2, 177-193, https://doi.org/10.3402/polar.v3i2.6951
+Hubold, G. and Drescher, H. E. (1982). Die Filchner-Schelfeis-Expedition 1980/81 mit MS ""Polarsirkel"". Liste der Planktonfänge und Lichtstärkemessungen , Reports on Polar Research, Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, 4, https://epic.awi.de/id/eprint/26181/1/BerPolarforsch19824.pdf
+Rohardt, G. (2010). Physical oceanography during POLARSTERN cruise ANT-XXII/3, https://doi.org/10.1594/PANGAEA.733664
+Rohardt, G. (2013). Physical oceanography during POLARSTERN cruise ANT-XXIX/2, https://doi.org/10.1594/PANGAEA.817255
+Rohardt, G. and Boebel, O. (2017). Physical oceanography during POLARSTERN cruise PS103 (ANT-XXXII/2), https://doi.org/10.1594/PANGAEA.881076
+Rohardt, G. and Boebel, O. (2020). Physical oceanography during POLARSTERN cruise PS117, https://doi.org/10.1594/PANGAEA.910663
+Rohardt, G., Fahrbach, E., and Wisotzki, A. (2011): Physical oceanography during POLARSTERN cruise ANT-XXVII/2, https://doi.org/10.1594/PANGAEA.772244
+Schröder, M. (2010). Physical oceanography during POLARSTERN cruise ANT-XII/3, https://doi.org/10.1594/PANGAEA.742581
+Schröder, M. and Wisotzki, A. (2014). Physical oceanography during POLARSTERN cruise PS82 (ANT-XXIX/9), https://doi.org/10.1594/PANGAEA.833299
+Schröder, M., Ryan, S., and Wisotzki, A. (2016). Physical oceanography during POLARSTERN cruise PS96 (ANT-XXXI/2 FROSN), https://doi.org/10.1594/PANGAEA.859040
+Schröder, M., Ryan, S., and Wisotzki, A. (2017a). Physical oceanography and current meter data from mooring AWI252-1, https://doi.org/10.1594/PANGAEA.875931
+Schröder, M., Ryan, S., and Wisotzki, A. (2017b). Physical oceanography and current meter data from mooring AWI253-1, https://doi.org/10.1594/PANGAEA.875932
+Schröder, M., Ryan, S., and Wisotzki, A. (2017c). Physical oceanography and current meter data from mooring AWI254-1, https://doi.org/10.1594/PANGAEA.875933
+Schröder, M., Ryan, S., and Wisotzki, A. (2019a). Physical oceanography and current meter data from mooring AWI252-2, https://doi.org/10.1594/PANGAEA.903104
+Schröder, M., Ryan, S., and Wisotzki, A. (2019b). Physical oceanography and current meter data from mooring AWI253-2, https://doi.org/10.1594/PANGAEA.903315
+Schröder, M., Ryan, S., and Wisotzki, A. (2019c). Physical oceanography and current meter data from mooring AWI254-2, https://doi.org/10.1594/PANGAEA.903317",api,True,findable,0,0,0,0,0,2023-11-01T16:13:42.000Z,2023-11-01T16:13:42.000Z,cern.zenodo,cern,"Weddell Sea,Ocean model,Antarctica,MISOMIP","[{'subject': 'Weddell Sea'}, {'subject': 'Ocean model'}, {'subject': 'Antarctica'}, {'subject': 'MISOMIP'}]",,
+10.6084/m9.figshare.21430977.v1,Additional file 3 of Digitally-supported patient-centered asynchronous outpatient follow-up in rheumatoid arthritis - an explorative qualitative study,figshare,2022,,Text,Creative Commons Attribution 4.0 International,Supplementary Material 3,mds,True,findable,0,0,0,0,0,2022-10-29T03:17:16.000Z,2022-10-29T03:17:16.000Z,figshare.ars,otjm,"Medicine,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['493283 Bytes'],
+10.5281/zenodo.6526421,All-atom molecular dynamics simulations of Synechocystis halorhodopsin (SyHR),Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The trajectories of all-atom MD simulations of:<br> 1) Cl<sup>-</sup>-bound SyHR in the ground (GR) state (SyHR_monomer_GR_POPC_CHARMM36_200ns)<br> 2) Cl<sup>-</sup>-bound SyHR in the K state (SyHR_monomer_K_POPC_CHARMM36_200ns)<br> in the monomeric form in a POPC bilayer.<br> 3) SO<sub>4</sub><sup>2-</sup>-bound SyHR in the GR state (SyHR_trimer_GR_POPC_CHARMM36_500ns)<br> in the trimeric form in a POPC bilayer. Simulations have been performed using the CHARMM36 force field, running with the GROMACS 2022 package.",mds,True,findable,0,0,0,0,0,2022-05-24T19:12:49.000Z,2022-05-24T19:12:50.000Z,cern.zenodo,cern,"rhodopsin,molecular dynamics,all-atom,atomistic,GROMACS,CHARMM36,simulation","[{'subject': 'rhodopsin'}, {'subject': 'molecular dynamics'}, {'subject': 'all-atom'}, {'subject': 'atomistic'}, {'subject': 'GROMACS'}, {'subject': 'CHARMM36'}, {'subject': 'simulation'}]",,
+10.57745/enjadk,Bilinear magnetoresistance in HgTe topological insulator: opposite signs at opposite surfaces demonstrated by gate control,Recherche Data Gouv,2022,,Dataset,,DATASET associated to the figure of the paper entitled : Bilinear magnetoresistance in HgTe topological insulator: opposite signs at opposite surfaces demonstrated by gate control. README file describe the data associated to each figure.,mds,True,findable,95,7,0,0,0,2022-08-03T03:16:27.000Z,2022-09-28T07:38:55.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.8269855,Heterogeneous/Homogeneous Change Detection dataset,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"""Please if you use this datasets we appreciated that you reference this repository and cite the works related that made possible the generation of this dataset.""
+This change detection datastet has different events, satellites, resolutions and includes both homogeneous/heterogeneous cases. The main idea of the dataset is to bring a benchmark on semantic change detection in remote sensing field.This dataset is the outcome of the following publications:
+
+@article{Â Â Â JimenezSierra2022graph,author={Jimenez-Sierra, David Alejandro and Quintero-Olaya, David Alfredo and Alvear-Mu{\~n}oz, Juan Carlos and Ben{\'i}tez-Restrepo, Hern{\'a}n Dar{\'i}o and Florez-Ospina, Juan Felipe and Chanussot, Jocelyn},journal={IEEE Transactions on Geoscience and Remote Sensing},title={Graph Learning Based on Signal Smoothness Representation for Homogeneous and Heterogeneous Change Detection},year={2022},volume={60},number={},pages={1-16},doi={10.1109/TGRS.2022.3168126}}Â
+@article{Â Â Â JimenezSierra2020graph,title={Graph-Based Data Fusion Applied to: Change Detection and Biomass Estimation in Rice Crops},author={Jimenez-Sierra, David Alejandro and Ben{\'i}tez-Restrepo, Hern{\'a}n Dar{\'i}o and Vargas-Cardona, Hern{\'a}n Dar{\'i}o and Chanussot, Jocelyn},journal={Remote Sensing},volume={12},number={17},pages={2683},year={2020},publisher={Multidisciplinary Digital Publishing Institute},doi={10.3390/rs12172683}}Â
+@inproceedings{jimenez2021blue,title={Blue noise sampling and Nystrom extension for graph based change detection},author={Jimenez-Sierra, David Alejandro and Ben{\'\i}tez-Restrepo, Hern{\'a}n Dar{\'\i}o and Arce, Gonzalo R and Florez-Ospina, Juan F},booktitle={2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS},ages={2895--2898},year={2021},organization={IEEE},doi={10.1109/IGARSS47720.2021.9555107}}Â
+@article{florez2023exploiting,title={Exploiting variational inequalities for generalized change detection on graphs},author={Florez-Ospina, Juan F and Jimenez Sierra, David A and Benitez-Restrepo, Hernan D and Arce, Gonzalo},journal={IEEE Transactions on Geoscience and Remote Sensing}, Â year={2023},volume={61},number={},pages={1-16},doi={10.1109/TGRS.2023.3322377}}Â
+@article{florez2023exploitingxiv,title={Exploiting variational inequalities for generalized change detection on graphs},author={Florez-Ospina, Juan F. and Jimenez-Sierra, David A. and Benitez-Restrepo, Hernan D. and Arce, Gonzalo R},year={2023},publisher={TechRxiv},doi={10.36227/techrxiv.23295866.v1}}
+In the table on the html file (dataset_table.html) are tabulated all the metadata and details related to each case within the dasetet. The cases with a link, were gathered from those sources and authors, therefore you should refer to their work as well.
+The rest of the cases or events (without a link), were obtained through the use of open sources such as:
+
+Copernicus
+European Space Agency
+Alaska Satellite Facility (Vertex)
+Earth Data
+In addition, we carried out all the processing of the images by using the SNAP toolbox from the European Space Agency. This proccessing involves the following:
+
+Data co-registration
+Cropping
+Apply Orbit (for SAR data)
+Calibration (for SAR data)
+Speckle Filter (for SAR data)
+Terrain Correction (for SAR data)
+Lastly, the ground truth was obtained from homogeneous images for pre/post events by drawing polygons to highlight the areas where a visible change was present. The images where layout and synchorized to be zoomed over the same are to have a better view of changes. This was an exhaustive work in order to be precise as possible.Feel free to improve and contribute to this dataset.",api,True,findable,0,0,0,0,0,2023-11-05T15:26:39.000Z,2023-11-05T15:26:39.000Z,cern.zenodo,cern,"Remote sensing,Change Detection,Multi-Spectral,SAR","[{'subject': 'Remote sensing'}, {'subject': 'Change Detection'}, {'subject': 'Multi-Spectral'}, {'subject': 'SAR'}]",,
+10.5281/zenodo.4761315,"Figs. 32-35 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 32-35. Dictyogenus muranyii sp. n., male terminalia. 32. Hemitergal lobes, dorsal view. Karstic spring of Font Noire, Isère dpt, France. Photo B. Launay. 33. Epiproct, lateral view. Karstic spring of Font Noire, Isère dpt, France. Photo B. Launay. 34. Lateral stylet, lateral view. Karstic spring of Brudour, Drôme dpt, France. Photo B. Launay. 35. Epiproct, dorso-caudal view. Karstic spring of Font Noire, Isère dpt, France. Photo B. Launay.",mds,True,findable,0,0,6,0,0,2021-05-14T07:46:48.000Z,2021-05-14T07:46:49.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.5761723,20211206_JGRPlanets_H2GenerationTimescalesEnceladus,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset associated with the study: ""Theoretical considerations on the characteristic timescales of hydrogen generation by serpentinization reactions on Enceladus"" by Daval et al. The code used to provide the estimates reported in Section 7.1 is also available from this archive.",mds,True,findable,0,0,0,1,0,2021-12-16T13:50:29.000Z,2021-12-16T13:50:30.000Z,cern.zenodo,cern,,,,
+10.48380/evdd-zw82,Observing high pressure melting and crystallization of silicates utilizing MHz diffraction at the European X-ray free electron laser,Deutsche Geologische Gesellschaft - Geologische Vereinigung e.V. (DGGV),2022,en,Text,,"<p>The opening of the European X-ray Free Electron Laser near Hamburg (EuXFEL) offers promising new experimental opportunities for studying materials. It can deliver X-rays with energies up to 25 keV and its brightness is so large, that a single pulse exhibits enough intensity to generate a diffraction image. In combination with the 4.5 MHz (220 ns separation) rate of pulse delivery, and new detector technologies (AGIPD), the EuXFEL enables unique capabilities for time resolved diffraction experiments.</p>
+<p>Coupling these new capabilities with laser heated diamond anvil cells, enables the study of materials under planetary conditions with unprecedented time resolution, possibly overcoming previous issues with chemical reactions between the sample and its environment as well as the study of transient phenomena such as phase transformations.</p>
+<p>We will present first results and challenges of experiments investigating silicates under extreme conditions at the “High Energy Density†(HED) instrument of the European XFEL during two community proposals which brought together around fifty international participants (proposal numbers #2292 and #2605).</p>
+",api,True,findable,0,0,0,0,0,2023-05-31T14:45:33.000Z,2023-05-31T14:45:33.000Z,mcdy.dohrmi,mcdy,,,,
+10.5281/zenodo.6506583,"Action Planning Makes Physical Activity More Automatic, Only If it Is Autonomously Regulated: A Moderated Mediation Analysis",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Dataset used for analysis.,mds,True,findable,0,0,0,0,0,2022-04-29T20:45:18.000Z,2022-04-29T20:45:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5243209,Latin DBnary archive in original Lemon format,Zenodo,2021,la,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Latin language edition, ranging from 6th June 2015 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T10:32:45.000Z,2021-08-24T10:32:46.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5061/dryad.9w0vt4bd1,Power and limitations of environmental DNA metabarcoding for surveying leaf litter eukaryotic communities,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Leaf litter habitats shelter a great variety of organisms, which play an important role in ecosystem dynamics. However, monitoring species in leaf litter is challenging, especially in highly diverse environments such as tropical forests, because individuals may easily camouflage themselves or hide in the litter layer. Identifying species based on environmental DNA (eDNA) would allow us to assess biodiversity in this microhabitat, without the need for direct observation of individuals. We applied eDNA metabarcoding to analyze large amounts of leaf litter (1 kg per sample) collected in the Brazilian Atlantic forest. We compared two DNA extraction methods, one total and one extracellular, and amplified a fragment of the mitochondrial 18S rRNA gene common to all eukaryotes, to assess the performance of eDNA from leaf litter samples in identifying different eukaryotic taxonomic groups. We also amplified two fragments of the mitochondrial 12S rRNA gene to specifically test the power of this approach for monitoring vertebrate species, with a focus on anurans. Most of the eukaryote sequence reads obtained were classified as Fungi, followed by Metazoa, and Viridiplantae. Most vertebrate sequences were assigned to Homo sapiens; only two sequences assigned to the genus Phyllomedusa and the species Euparkerella brasiliensis can be considered true detections of anurans in our eDNA samples. The detection of taxa varied depending on the DNA extraction method applied. Our results demonstrate that the analysis of eDNA from leaf litter samples has low power for monitoring vertebrate species, and should be preferentially applied to describe active and abundant taxa in terrestrial communities, such as Fungi and invertebrates.",mds,True,findable,97,3,0,0,0,2021-03-23T17:40:28.000Z,2021-03-23T17:40:29.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['4618934791 bytes'],
+10.5281/zenodo.6653187,316L L-PBF fatigue dataset,Zenodo,2022,fr,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This file contains 316L Laser Powder Bed Fusion fatigue tests dataset. Experiments were carried on a MTS Landmark 100 kN servohydraulic fatigue test machine. This experimental campaign took place in the context of a PhD grant from the French region Pays de la Loire (see https://pastel.archives-ouvertes.fr/tel-03688021 for the thesis manuscript). Fatigue tests were carried : - in air or in salt-spray - on different batches (polished, pre-corroded, with artificial defects,...) - at R=-1 and R=0.1",mds,True,findable,0,0,0,0,0,2022-06-16T15:13:18.000Z,2022-06-16T15:13:19.000Z,cern.zenodo,cern,"Fatigue,316L,L-PBF,Additive Manufacturing,Defects,Salt-Spray,Corrosion","[{'subject': 'Fatigue'}, {'subject': '316L'}, {'subject': 'L-PBF'}, {'subject': 'Additive Manufacturing'}, {'subject': 'Defects'}, {'subject': 'Salt-Spray'}, {'subject': 'Corrosion'}]",,
+10.5281/zenodo.7225366,Videos of scenario executions on carla,Zenodo,2022,,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access",Videos of the executions on the simulator Carla of driving scenarios.,mds,True,findable,0,0,0,0,0,2022-10-19T13:03:58.000Z,2022-10-19T13:03:58.000Z,cern.zenodo,cern,,,,
+10.34847/nkl.3dbc2mtb,Bulletin franco-italien 1912 n°4-5 juillet - octobre,NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Book,,"1912/11 (A4,N6)-1912/12.",api,True,findable,0,0,0,0,0,2022-07-12T13:48:55.000Z,2022-07-12T13:48:55.000Z,inist.humanum,jbru,Etudes italiennes,[{'subject': 'Etudes italiennes'}],"['10539495 Bytes', '21558100 Bytes', '21840529 Bytes', '21062686 Bytes', '21714700 Bytes', '21445744 Bytes', '21836002 Bytes', '21825382 Bytes', '21214213 Bytes', '21303211 Bytes', '21876550 Bytes', '21499546 Bytes', '21614056 Bytes', '21780892 Bytes', '21669382 Bytes', '21654679 Bytes', '21598168 Bytes', '21779833 Bytes', '21611542 Bytes', '21629782 Bytes', '21183421 Bytes', '21241312 Bytes', '21237016 Bytes', '21224224 Bytes', '21229654 Bytes', '21175816 Bytes', '21237016 Bytes', '21138790 Bytes', '21129388 Bytes']","['application/pdf', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff']"
+10.5281/zenodo.4745568,robertxa/Topographies-Samoens_Folly: Zenodo DOI,Zenodo,2021,,Software,Open Access,"Base de données topographiques du massif du Folly (Samoëns, France)",mds,True,findable,0,0,0,0,0,2021-05-10T10:27:06.000Z,2021-05-10T10:27:07.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5243257,Dutch DBnary archive in original Lemon format,Zenodo,2021,nl,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Dutch language edition, ranging from 25th April 2015 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T10:51:42.000Z,2021-08-24T10:51:43.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.6084/m9.figshare.21430971,Additional file 1 of Digitally-supported patient-centered asynchronous outpatient follow-up in rheumatoid arthritis - an explorative qualitative study,figshare,2022,,Text,Creative Commons Attribution 4.0 International,Supplementary Material 1,mds,True,findable,0,0,0,0,0,2022-10-29T03:17:12.000Z,2022-10-29T03:17:13.000Z,figshare.ars,otjm,"Medicine,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['24235 Bytes'],
+10.6084/m9.figshare.22735503.v1,Additional file 1 of Healthcare students’ prevention training in a sanitary service: analysis of health education interventions in schools of the Grenoble academy,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Supplementary Material 1,mds,True,findable,0,0,0,0,0,2023-05-03T03:20:26.000Z,2023-05-03T03:20:27.000Z,figshare.ars,otjm,"Medicine,Biotechnology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}]",['19715 Bytes'],
+10.5281/zenodo.6402610,micrOMEGAs interface to SModelS v2.2,Zenodo,2022,,Software,"Creative Commons Attribution 4.0 International,Open Access","Interface files for micrOMEGAs_v5 series to work with SModelS v2.2 (see what's new). For an existing micrOMEGAs installation (in particular versions 5.2.7 to 5.2.10), the files <pre> include/SMODELS.inc include/smodels_parameters.ini sources/smodels.c sources/smodels.cc Packages/SMODELS.makef </pre> should be replaced by the ones provided here. The file <code>codesnippet_for_main.c</code> provides an example code snippet for calling SModelS v2.2 in any micrOMEGAs main program and printing the results; this is to replace the part <pre> #ifdef SMODELS { ..... } #endif </pre> in the default <code>main.c</code> files of micrOMEGAs. ++++++++++++++++++++++++++++++++++++++++++++++++++++++ <strong>NOTE: If you are using python ≤ 3.7, change</strong> <pre> char *VERSION=""2.2.0""</pre> to <pre> char *VERSION=""2.2.0.post1""</pre> in the <code>SMODELS.inc</code> file provided here ++++++++++++++++++++++++++++++++++++++++++++++++++++++",mds,True,findable,0,0,0,0,0,2022-03-31T17:33:46.000Z,2022-03-31T17:33:48.000Z,cern.zenodo,cern,"SModelS,simplified models,LHC,dark matter","[{'subject': 'SModelS'}, {'subject': 'simplified models'}, {'subject': 'LHC'}, {'subject': 'dark matter'}]",,
+10.5281/zenodo.7085313,maprdhm/SPACiSS: v1.0.0,Zenodo,2022,,Software,Open Access,Simulation of Pedestrians and an Autonomous Car in Shared Spaces https://github.com/maprdhm/SPACiSS/commits/v1.0.0,mds,True,findable,0,0,0,1,0,2022-09-16T10:02:08.000Z,2022-09-16T10:02:08.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5799465,GPS Time Series Kamchatka 2013,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","GPS time series presented in the article: ""Transient slab plunge prior to the Mw 8.3 2013 Okhotsk deep-focus earthquake"" The columns of the files correspond to Year ; Month ; Day ; Hour ; Minute ; Second ; East position (mm) ; North position (mm) ; Up position (mm) ; East uncertainty (mm) ; North uncertainty (mm) ; Up uncertainty (mm) ;",mds,True,findable,0,0,0,0,0,2021-12-22T17:43:30.000Z,2021-12-22T17:43:30.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.8cz8w9gqs,Can functional genomic diversity provide novel insights into mechanisms of community assembly? A pilot-study from an invaded alpine streambed,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"An important focus of community ecology, including invasion biology, is to investigate functional trait diversity patterns to disentangle the effects of environmental and biotic interactions. However, a notable limitation is that studies usually rely on a small and easy to measure set of functional traits, which might not immediately reflect ongoing ecological responses to changing abiotic or biotic conditions, including those that occur at a molecular or physiological level. We explored the potential of using the diversity of expressed genes—functional genomic diversity (FGD)—to understand ecological dynamics of a recent and ongoing alpine invasion. We quantified FGD based on transcriptome data measured for 26 plant species occurring along adjacent invaded and pristine streambeds. We used an RNA-seq approach to summarize the overall number of expressed transcripts and their annotations to functional categories, and contrasted this with functional trait diversity (FTD) measured from a suite of characters that have been traditionally considered in plant ecology. We found greater FGD and FTD in the invaded community, independent of differences in species richness. However, the magnitude of functional dispersion was greater from the perspective of FGD than from FTD. Comparing FGD between congeneric alien-native species pairs, we did not find many significant differences in the proportion of genes whose annotations matched functional categories. Still, native species with a greater relative abundance in the invaded community compared with the pristine tended to express a greater fraction of genes at significant levels in the invaded community, suggesting that changes in FGD may relate to shifts in community composition. Comparisons of diversity patterns from the community- to the species-level offer complementary insights into processes and mechanisms driving invasion dynamics. FGD has the potential to illuminate cryptic changes in ecological diversity, and we foresee promising avenues for future extensions across taxonomic levels and macro-ecosystems.",mds,True,findable,124,2,0,0,0,2021-07-22T01:16:51.000Z,2021-07-22T01:16:53.000Z,dryad.dryad,dryad,,,['1658389762 bytes'],
+10.5281/zenodo.10045256,preesm/preesm: ACM TRETS Artifact Evaluation,Zenodo,2023,,Software,CeCILL-C Free Software License Agreement,"Release for ACM TRETS Artifact Evaluation.
+""Automated Buffer Sizing of Dataflow Applications in a High-Level Synthesis Workflow""
+https://dl.acm.org/doi/10.1145/3626103",api,True,findable,0,0,0,1,0,2023-10-26T20:00:51.000Z,2023-10-26T20:00:52.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10050503,Data and code associated with the manuscript: Three centuries of snowpack decline at an Alpine pass revealed by cosmogenic paleothermometry and luminescence photochronometry,Zenodo,2023,,Dataset,GNU General Public License v3.0 or later,"This dataset contains the data as well as the Matlab codes needed to reproduce the results in the following manuscript:
+Guralnik, B., Tremblay, M.M., Phillips, M., Sellwood, E.L., Gribenski, N., Presl, R., Haberkorn, A., Sohbati, R., Shuster, D.L., Valla, P., Jain, M., Schindler, K., Hippe, K., and Wallinga, J., Three centuries of snowpack decline at an Alpine pass revealed by cosmogenic paleothermometry and luminescence photochronometry.Â
+This manuscript has been submitted to a peer-reviewed journal for publication. Briefly, this manuscript presents a novel combination of cosmogenic paleothermometery (quartz He-3) and luminescence photochronometery (feldspar IRSL), which jointly constrain the temperature and insolation history of three bedrock outcrops at the Gotthard Pass in Switzerland over the last ~15,000 years.Â
+The data include (1) measured concentrations of cosmogenic Be-10, C-14, and He-3 in quartz, (2) stepwise degassing experiments on proton irradiated quartz grains that are used to determine sample-specific He-3 diffusion kinetics, (3) best-fit multiple diffusion domain (MDD) models to the proton-induced He-3 diffusion experiments, (5) Natural radioactivity and calculated feldspar infrared stimulated luminescence (ISRL) dose rates, (6) feldspar ISRL depth profiles, and (7) high-resolution microrelief surface scans and analysis.
+The code includes scripts necessary to reproduce the figures and results associated with this manuscript. The code is organized by figure into subfolders, and any data needed to reproduce a figure should be included in that folder. All original codes are distributed under the GNU General Public License. Codes written by others and utilized here are redistributed under their original license according to the terms and conditions therein, and are provided in the folder 'external.'
+Any questions about original Matlab codes published here should be directed to Benny Guralnik, benny.guralnik@gmail.com.",api,True,findable,0,0,0,0,0,2023-10-28T22:58:22.000Z,2023-10-28T22:58:22.000Z,cern.zenodo,cern,"snow,cosmogenic,paleothermometry,luminescence,Alpine","[{'subject': 'snow'}, {'subject': 'cosmogenic'}, {'subject': 'paleothermometry'}, {'subject': 'luminescence'}, {'subject': 'Alpine'}]",,
+10.5281/zenodo.5588468,"Input data for PARASO, a circum-Antarctic fully-coupled 5-component model",Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Input data for running the PARASO experiments. These files should be extracted, and the folder containing them should be referred to in the `data.cfg` Coral configuration file. See also PARASO documentation from the PARASO sources. The ERA5 forcings (COSMO boundary files and NEMO surface forcings) are not provided herein as they are too large, but we provide: - scripts for downloading and post-processing the ERA5 NEMO forcings; - INT2LM configuration file, with the new Antarctic geometry, to generate COSMO lateral forcings. A 3-month sample of ERA5 data is also available (see <strong>Forcings</strong> below). <strong>Model description: </strong>Pelletier, C., Fichefet, T., Goosse, H., Haubner, K., Helsen, S., Huot, P.-V., Kittel, C., Klein, F., Le clec'h, S., van Lipzig, N. P. M., Marchi, S., Massonnet, F., Mathiot, P., Moravveji, E., Moreno-Chamarro, E., Ortega, P., Pattyn, F., Souverijns, N., Van Achter, G., Vanden Broucke, S., Vanhulle, A., Verfaillie, D., and Zipf, L.: PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5, Geosci. Model Dev., 15, 553–594, 10.5194/gmd-15-553-2022, 2022. <strong>Source code (no COSMO)</strong>: Pelletier, Charles, Klein, François, Zipf, Lars, Haubner, Konstanze, Mathiot, Pierre, Pattyn, Frank, Moravveji, Ehsan, & Vanden Broucke, Sam. (2021). PARASO source code (no COSMO) (v1.4.3). Zenodo. 10.5281/zenodo.5576201 <strong>Forcings: </strong>Pelletier, Charles, & Helsen, Samuel. (2021). PARASO ERA5 forcings (1.4.3) [Data set]. Zenodo. 10.5281/zenodo.5590053<br> <strong>Acknowledgements</strong> <strong>ORAS5: </strong>Zuo, H, Alonso-Balmaseda, M, Mogensen, K, Tietsche, S: OCEAN5: The ECMWF Ocean Reanalysis System and its Real-Time analysis component. 2018. 10.21957/la2v0442 downloaded from the ICDC (University of Hamburg) on 01-SEP-2019. <em>(The results contain modified Copernicus Climate Change Service information 2020. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.)</em> <strong>BedMachine: </strong>Morlighem, M. 2020. <em>MEaSUREs BedMachine Antarctica, Version 2</em>. Ice-shelf Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: 10.5067/E1QL9HFQ7A8M. Accessed 01-DEC-2019. Morlighem, M., E. Rignot, T. Binder, D. D. Blankenship, R. Drews, G. Eagles, O. Eisen, F. Ferraccioli, R. Forsberg, P. Fretwell, V. Goel, J. S. Greenbaum, H. Gudmundsson, J. Guo, V. Helm, C. Hofstede, I. Howat, A. Humbert, W. Jokat, N. B. Karlsson, W. Lee, K. Matsuoka, R. Millan, J. Mouginot, J. Paden, F. Pattyn, J. L. Roberts, S. Rosier, A. Ruppel, H. Seroussi, E. C. Smith, D. Steinhage, B. Sun, M. R. van den Broeke, T. van Ommen, M. van Wessem, and D. A. Young. 2020. Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet, <em>Nature Geoscience</em>. 13. 132-137. 10.1038/s41561-019-0510-8 <strong>Iceberg forcings: </strong>Jourdain, Nicolas C., Merino, Nacho, Le Sommer, Julien, Durand, Gaël, & Mathiot, Pierre. (2019). Interannual iceberg meltwater fluxes over the Southern Ocean (1.0) [Data set]. <em>Zenodo</em>. 10.5281/zenodo.3514728 Merino N., Jourdain, N. C., Le Sommer, J., Goose, H., Mathiot, P. and Durand, G (2018). Impact of increasing Antarctic glacial freshwater release on regional sea-ice cover in the Southern Ocean. <em>Ocean Modelling</em>, 121, 76-89. 10.1016/j.ocemod.2017.11.009",mds,True,findable,0,0,5,9,0,2021-10-27T12:20:30.000Z,2021-10-27T12:20:31.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23575378.v1,Additional file 7 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 6,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:55.000Z,2023-06-25T03:11:56.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['26112 Bytes'],
+10.5281/zenodo.7429639,"Data and Code for figures of ""Long-range transport and fate of DMS-oxidation products in the free troposphere derived from observations at the high-altitude research station Chacaltaya (5240 m a.s.l.) in the Bolivian Andes""",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This database includes the material to create the figures in ""Measurement Report: Long-range transport and fate of DMS-oxidation products in the free troposphere derived from observations at the high-altitude research station Chacaltaya (5240 m a.s.l.) in the Bolivian Andes"" and the analyzed time series of all atmospheric variables presented.",mds,True,findable,0,0,0,0,0,2022-12-12T18:12:14.000Z,2022-12-12T18:12:14.000Z,cern.zenodo,cern,"dimethyl sulfide,free troposphere,dimethyl sulfone,DMSO2,methane sulfonate,MSA,chemical ionization mass spectrometry,sulfur,marine,long-range transport","[{'subject': 'dimethyl sulfide'}, {'subject': 'free troposphere'}, {'subject': 'dimethyl sulfone'}, {'subject': 'DMSO2'}, {'subject': 'methane sulfonate'}, {'subject': 'MSA'}, {'subject': 'chemical ionization mass spectrometry'}, {'subject': 'sulfur'}, {'subject': 'marine'}, {'subject': 'long-range transport'}]",,
+10.5281/zenodo.2641991,X-ray diffraction images for coenzyme F420H2 oxidase (FprA) from M. thermolithotrophicus.,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Anomalous data collected at ESRF (Grenoble, France) using beamline ID23-1. The crystal (Crystal form 2) was in the presence of the crystallophore Tb-Xo4.
+
+
+
+Related Publication: Engilberge et al. (2019)",mds,True,findable,0,0,0,0,0,2019-04-16T11:51:57.000Z,2019-04-16T11:51:57.000Z,cern.zenodo,cern,,,,
+10.57745/mxemi4,X-ray scan of soft ball compression experiments - raw data - 3D DIC data - post-processed data,Recherche Data Gouv,2023,,Dataset,,"These data are associated with the results presented in the paper: Compacting an assembly of soft balls far beyond the jammed state: insights from 3D imaging They are scans of compressed millimetric silicon balls. Micro glass beads are trapped in the silicone so that 3D DIC can be performed. Post-processed data including displacement fields, strain fields, contacts to name a few are also available. More details about the experimental protocol and data post-processing can be found in this publication. How data are sorted The raw and post-processed data of 4 experiments are available here. For each experiment: - a 'scan' folder includes 'scan_XX' folders where 'XX' corresponds to the N compression steps. Inside each of these folders you can find 8-bit png pictures corresponding to the vertical slices of the density matrix of a given compression step. Not interesting slices, because particles are not seeable have been removed for the sake of saving space. - a 'result' folder contains all the data post-processed from the density images. More specifically: - 'pressure_kpa.txt' is a N vector giving the evolution of the applied pressure (in kPa) on the loading piston, where N is number of loading steps. - 'particle_number.txt' is a n vector telling to which particle a correlation cell belongs. n is the number of correlation cells. - 'particle_size.txt' is a m vector where m is the number of particle in the system. It gives the particle size : 1 for large particles, 0 for small ones. Particle numbering corresponds with 'particle_number.txt' - Following text files are Nxn matrices where N is the number of steps and n is the number of correlations cells. They give for each correlation cell, the evolution of an observable measured in the corresponding volume of the correlation cell: - 'position_i.txt' is the position of the cell along i axis - 'position_j.txt' is the position of the cell along j axis - 'position_k.txt' is the position of the cell along k axis - 'correlation.txt' is the evolution of the correlation value when performing the 3D DIC. This constitutes the goodness of measurement of the correlation cell positions - 'dgt_Fij.txt' is the evolution of the deformation gradient tensor for each of its ij components - 'energy.txt' is the evolution of the energy density stored in the material - 'no_outlier_energy.txt' is a boolean ginving, from the energy density measurement, if the observables can be considered as an outlier (0 value) or not (1 value) - Following text files are mxN matrices with self-expicit contents where N is the number of loading steps and m the number of grains (particle numbering corresponds with 'particle_number.txt'). They give for each grain, the evolution of an observable measured at the grain scale. The major direction is the direction in which the particle is the longest. The minor direction is the direction in which the particle is the shortest. Theta and phi are the azimutal and elevation angle respectively: - 'particle_asphericity.txt' - 'particle_area.txt' - 'minor_direction_theta.txt' - 'minor_direction_phi.txt' - 'minor_direction_length.txt' - 'major_direction_theta.txt' - 'major_direction_phi.txt' - 'major_direction_length.txt' - Following text files are N vectors with self-expicit contents where N is the number of loading steps. They give the evolution of a system observable during loading. If a second vector is given it is the evolution of the standard deviation of the observable. In the case of contacts 'proximity' et for contacts obtained only from proximity criterion and 'density' is for contacts obtained from scanner density criterion. 'std' stand for standard deviation: - 'global strain.txt' measured from the system boundaries evolution - 'packing_fraction.txt' measured from the system boundaries and particle volume evolution - 'average_contact_surface_proximity.txt' - 'average_contact_surface_density.txt' - 'average_contact_radius_proximity.txt' - 'average_contact_densitt_proximity.txt' - 'average_contact_outofplane_proximity.txt' - 'average_contact_direction_proximity.txt' - 'average_contact_direction_density.txt' - 'average_contact_asphericity_proximity.txt' - 'average_contact_asphericity_density.txt' - 'average_vonMises_strain.txt' - 'std_vonMises_strain.txt' - 'average contact direction_density.txt' - 'average_energy.txt' - 'std_energy.txt' - 'contact_proximity.txt' number of contact - 'contact_density.txt' number of contact - a 'contact_density' folder includes 'XX' folders corresponing to the N compression steps. Each of these 'XX' folders includes 'ijkP_AA_BB.txt' files which gives information about potential contact points between AA and BB grains. For each potential contact, 'ijkP_AA_BB.txt' gives the i,j and k position of the potential contact points in AA and the average local density value associated which gives the probability of contact. - a 'contact_proximity' folder includes 'XX' folders corresponing to the N compression steps. Each of these 'XX' folders includes 'ijkD_AA_BB.txt' files which gives information about potential contact between AA and BB grains. For each potential contact, 'ijkD_AA_BB.txt' gives the i,j and k position of the potential contact points in AA and the shortest distance between this point and grain BB boundary. - a 'grain_mesh' folder includes 'XX' folders corresponing to the N compression steps. Each of these 'XX' folders includes 'YY.stl' files each of them is the mesh of the borders of the YY particle of the packing. - a 'contact_mesh' folder includes 'XX' folders corresponing to the N compression steps. Each of these 'XX' folders includes 'AA_BB.stl' files each of them is the mesh of the contact between particle AA and BB.",mds,True,findable,51,1,0,0,0,2023-05-12T13:33:44.000Z,2023-09-01T10:05:03.000Z,rdg.prod,rdg,,,,
+10.57745/ovcwqn,"Data supporting ""Deformation mechanisms, microstructures, and seismic anisotropy of wadsleyite in the Earth's transition zone"" by Ledoux et al.",Recherche Data Gouv,2023,,Dataset,,"We provide here the data supporting our article entitled Deformation mechanisms, microstructures, and seismic anisotropy of wadsleyite in the Earths transition zone: raw diffraction images, multigrain indexing files, and VPSC and seismic anisotropy simulations.",mds,True,findable,38,5,0,1,0,2023-04-17T15:55:54.000Z,2023-10-22T15:05:39.000Z,rdg.prod,rdg,,,,
+10.57745/r1nikk,Fichiers modèles de QGIS et Excel pour l'application du protocole d'aide à la décision pour le traitement des embâcles (protocole de Wohl et al. 2019 adapté par Benaksas et Piton 2022),Recherche Data Gouv,2023,,Dataset,,"Ces données sont trois documents modèles et les fichiers sources associés permettant de faciliter l'application du protocole de Wohl et al. (2019) tel que adapté par Benaksas & Piton (2022): 2export_csv_vers_shp.qgz est un projet QGIS qui facilite la transformation en données SIG des fichiers textes (format .csv) importés de l'application Epicollect 5 tel que décrit dans l'Annexe C du rapport de Benaksas et Piton (2023) , 1NOM_PROJET.gqz est un projet QGIS qui facilite l'affichage et l'interprétation des données SIG compilées préalablement aux missions de terrains et sur le terrain, par exemple via l'application Epicollect 5 tel que décrit dans l'Annexe C u rapport de Benaksas et Piton (2023) , 3ResultatsProtocole_epicollecte.xlsx est un tableur Excel qui facilite la notation des indicateurs de l'approche multicritère, la modification éventuelle des pondérations entre sous-critères, mène le calcul des scores pondérés et préparent les sorties graphiques. Des conseils d'utilisations sont décrit dans l'Annexe B u rapport de Benaksas et Piton (2023) ,",mds,True,findable,24,2,0,0,0,2023-03-06T11:05:39.000Z,2023-03-06T14:03:34.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.10036360,"Data and code for the article "" Dissimilarity of vertebrate trophic interactions reveals spatial uniqueness but functional redundancy across Europe""",Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Research compendium to reproduce analyses and figures of the article: Dissimilarity of vertebrate trophic interactions reveals spatial uniqueness but functional redundancy across Europe by Gaüzère et al. published in Current Biology
+Pierre Gaüzère
+General
+This repository is structured as follow:
+
+data/: contains data required to reproduce figures and tables
+analyses/: contains scripts organized sequentially. A -> B -> C -> ..
+outputs/: follows the structure of analyses. Contains intermediate numeric results used to produce the figures
+figures_tables/: Contains the figures of the paper
+Figures & tables
+Figures will be stored in figures_tables/. Tables will be stored in outputs/.",api,True,findable,0,0,0,0,0,2023-10-24T08:17:46.000Z,2023-10-24T08:17:46.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4767203,Philosophical stances of the most influential social entrepreneurship papers in 2020,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access",Coding of the most influential papers of the social entrepreneurship field according to their main philosophical stances.,mds,True,findable,0,0,0,0,0,2021-05-17T10:20:38.000Z,2021-05-17T10:20:39.000Z,cern.zenodo,cern,"social entrepreneurship,political philosophy","[{'subject': 'social entrepreneurship'}, {'subject': 'political philosophy'}]",,
+10.5281/zenodo.4761095,"Fig. 3. L in A New Stonefly From Lebanon, Leuctra Cedrus Sp. N. (Plecoptera: Leuctridae)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access",Fig. 3. L. cedrus sp. n.: female subgenital plate in ventral view.,mds,True,findable,0,0,2,0,0,2021-05-14T07:14:38.000Z,2021-05-14T07:14:38.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.5555329,Sea Ice Rheology Experiment (SIREx) - Model output data,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Sea-ice model output analyzed in the Sea Ice Rheology Experiment (SIREx) Part I and Part II. There is one netCDF file per model, per year (1997 and/or 2008). Each netCDF file contains daily output (as means or instantaneous values -- as indicated in the name) for January-February-March of the given year. Please see below for more information on what is included and how to cite. <strong>1. Naming convention of the files</strong> ""Model simulation label"" + _ + ""year"" + _ + ""daily_means"" OR ""instant"" <strong>2. Variables included</strong> <em>U,V</em> : sea-ice velocity in the x,y directions (in m/s); <em>A</em>: ice concentration per grid cell (0 -- 1); <em>h</em>: mean ice thickness per grid cell (in m); Grid spacing information: centered on u-points (<em>DXU, DYU</em>), v-points (<em>DXV, DYV</em>), or t-points (<em>DXT, DYT</em>) (in m); Grid point coordinates: for u-points (<em>ULON, ULAT</em>), v-points (<em>VLON, VLA</em>T), or t-points (<em>TLON, TLAT</em>) (in degrees); <em>maskT</em>: land mask at t-points (0/1 = ocean/land); <em>time</em>: time axis (in days since 1901-01-01 00:00:00). <strong>3. Recommended citation usage</strong> If <em>all</em> simulations included in the current archive are used in a future study, we ask to cite this archive and the SIREx papers (Bouchat et al., 2022, Hutter et al., 2022 ). If only <em>selected </em>simulations are used, we ask to cite both this archive and the reference paper(s) applying to the selected simulation(s) (as stated indicated in Table 1 of the SIREx papers).",mds,True,findable,0,0,0,1,0,2022-03-04T20:14:15.000Z,2022-03-04T20:14:16.000Z,cern.zenodo,cern,"Sea-ice modelling,Sea-ice deformation,Rheology,Linear Kinematic Features,Model Intercomparison Project","[{'subject': 'Sea-ice modelling'}, {'subject': 'Sea-ice deformation'}, {'subject': 'Rheology'}, {'subject': 'Linear Kinematic Features'}, {'subject': 'Model Intercomparison Project'}]",,
+10.5281/zenodo.6580925,Database of social innovation in energy initiatives,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",A database of n = 500 social innovation in energy initiatives.,mds,True,findable,0,0,0,0,0,2022-05-25T13:44:36.000Z,2022-05-25T13:44:36.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.jq2bvq878,Bird abundance data for the period 2002-2014 from the French Breeding Bird Survey (STOC),Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Abundance data on breeding birds from the French Breeding Bird Survey (Suivi Temporel des Oiseaux Communs, STOC), for the period 2002-2014. The dataset comprises 7,115 bird communities. Only 107 common species were included in the study.",mds,True,findable,230,37,0,1,0,2020-08-31T21:04:09.000Z,2020-08-31T21:04:11.000Z,dryad.dryad,dryad,"bird communities,STOC,bird survey,France","[{'subject': 'bird communities'}, {'subject': 'STOC'}, {'subject': 'bird survey'}, {'subject': 'France', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['10182638 bytes'],
+10.25384/sage.c.6567921,Impact of a telerehabilitation programme combined with continuous positive airway pressure on symptoms and cardiometabolic risk factors in obstructive sleep apnea patients,SAGE Journals,2023,,Collection,Creative Commons Attribution 4.0 International,"BackgroundObstructive sleep apnea syndrome is a common sleep-breathing disorder associated with adverse health outcomes including excessive daytime sleepiness, impaired quality of life and is well-established as a cardiovascular risk factor. Continuous positive airway pressure is the reference treatment, but its cardiovascular and metabolic benefits are still debated. Combined interventions aiming at improving patient's lifestyle behaviours are recommended in guidelines management of obstructive sleep apnea syndrome but adherence decreases over time and access to rehabilitation programmes is limited. Telerehabilitation is a promising approach to address these issues, but data are scarce on obstructive sleep apnea syndrome.MethodsThe aim of this study is to assess the potential benefits of a telerehabilitation programme implemented at continuous positive airway pressure initiation, compared to continuous positive airway pressure alone and usual care, on symptoms and cardiometabolic risk factors of obstructive sleep apnea syndrome. This study is a 6-months multicentre randomized, parallel controlled trial during which 180 obese patients with severe obstructive sleep apnea syndrome will be included. We will use a sequential hierarchical criterion for major endpoints including sleepiness, quality of life, nocturnal systolic blood pressure and inflammation biological parameters.Discussionm-Rehab obstructive sleep apnea syndrome is the first multicentre randomized controlled trial to examine the effectiveness of a telerehabilitation lifestyle programme in obstructive sleep apnea syndrome. We hypothesize that a telerehabilitation lifestyle intervention associated with continuous positive airway pressure for 6 months will be more efficient than continuous positive airway pressure alone on symptoms, quality of life and cardiometabolic risk profile. Main secondary outcomes include continuous positive airway pressure adherence, usability and satisfaction with the telerehabilitation platform and medico-economic evaluation.Trial registrationClinicaltrials.gov Identifier: NCT05049928. Registration data: 20 September 2021",mds,True,findable,0,0,0,0,0,2023-04-07T00:07:22.000Z,2023-04-07T00:07:23.000Z,figshare.sage,sage,"111708 Health and Community Services,FOS: Health sciences,Cardiology,110306 Endocrinology,FOS: Clinical medicine,110308 Geriatrics and Gerontology,111099 Nursing not elsewhere classified,111299 Oncology and Carcinogenesis not elsewhere classified,111702 Aged Health Care,111799 Public Health and Health Services not elsewhere classified,99999 Engineering not elsewhere classified,FOS: Other engineering and technologies,Anthropology,FOS: Sociology,200299 Cultural Studies not elsewhere classified,FOS: Other humanities,89999 Information and Computing Sciences not elsewhere classified,FOS: Computer and information sciences,150310 Organisation and Management Theory,FOS: Economics and business,Science Policy,160512 Social Policy,FOS: Political science,Sociology","[{'subject': '111708 Health and Community Services', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cardiology'}, {'subject': '110306 Endocrinology', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '110308 Geriatrics and Gerontology', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111099 Nursing not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111299 Oncology and Carcinogenesis not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111702 Aged Health Care', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111799 Public Health and Health Services not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '99999 Engineering not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Other engineering and technologies', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Anthropology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '200299 Cultural Studies not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Other humanities', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '89999 Information and Computing Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Computer and information sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '150310 Organisation and Management Theory', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Economics and business', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '160512 Social Policy', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Political science', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Sociology'}]",,
+10.5281/zenodo.3759385,"Sense Vocabulary Compression through the Semantic Knowledge of WordNet for Neural Word Sense Disambiguation - Model Weights - SC+WNGC, hypernyms, single",Zenodo,2019,,Other,"Creative Commons Attribution 4.0 International,Open Access","This is the weights of the neural WSD model used in the article named ""Sense Vocabulary Compression through the Semantic Knowledge of WordNet for Neural Word Sense Disambiguation"" by Loïc Vial, Benjamin Lecouteux, Didier Schwab. This is a single model trained on the SemCor+WNGC corpora and using the sense vocabulary compression through hypernyms described in the paper.",mds,True,findable,11,0,0,0,0,2020-04-21T13:34:04.000Z,2020-04-21T13:34:05.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.1194786,Ultraspeechdataset2017,Zenodo,2018,fr,Dataset,"Creative Commons Attribution 4.0,Open Access","Ultrasound/Audio databases related to (Fabre et al., Speech Communication, 2017) ——————————————————————
+
+HOW-to-CITE:
+
+Fabre, D., Hueber, T., Girin, L., Alameda-Pineda, X., Badin, P., (2017) ""Automatic animation of an articulatory tongue model from ultrasound images of the vocal tract"", Speech Communication, vol. 93, pp. 63-75
+
+These databases are distributed in the hope that they will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
+
+CONTENT:
+
+- (unzip first) Ultrasound/Audio data (synchronized) for three native French speakers (2 male speakers (PB and TH), one female speaker (DF)), recorded using Ultraspeech software (www.ultraspeech.com). Data acquisition protocol is described in (Fabre et al., Speech Communication, 2017). More information on the Ultraspeech acquisition system can be found at www.ultraspeech.com and in (Hueber et al., ISSP 2008).
+
+- audio_capture/, ultrasound_capture/ directories contain audio/ultrasound data (one folder per sentence). Ultrasound data are 640x480 jpeg images (with 100% quality during compression) recorded at 60 fps. Audio files are in WAV format, 44.1 kHz, 32 bits. Text files in audio directory contain the text prompt for each recorded item.
+
+*** WARNING *** : Item 418 of speaker PB is missing.
+
+
+
+Thomas Hueber, Ph. D., CNRS researcher, GIPSA-lab (Grenoble, France), thomas.hueber@gipsa-lab.fr",,True,findable,0,0,0,0,0,2018-03-09T14:45:01.000Z,2018-03-09T14:45:02.000Z,cern.zenodo,cern,"ultrasound, speech, articulation, ultraspeech, biofeedback","[{'subject': 'ultrasound, speech, articulation, ultraspeech, biofeedback'}]",,
+10.5061/dryad.689110r,Data from: Deciphering the drivers of negative species-genetic diversity correlation in Alpine amphibians,Dryad,2018,en,Dataset,Creative Commons Zero v1.0 Universal,"The evolutionary and ecological importance of neutral and adaptive genetic diversity is widely recognized. Nevertheless, genetic diversity is rarely assessed for conservation planning, which often implicitly assumes a positive correlation between species and genetic diversity. Multiple drivers can cause the co-variation between the genetic diversity of one species and the richness of the whole communities, and explicit tests are needed to identify the processes that can determine species-genetic diversity correlations (SGDC). Here we tested whether intrapopulation genetic diversity (at neutral loci) and species richness co-vary in the amphibian communities of a southern Alpine region (Trentino, Italy), using the common frog (Rana temporaria) as focal species for the study of genetic diversity. We also analyzed ecological similarity, niche overlap and interspecific interactions between the species, to unravel the processes determining SGDC. The neutral genetic diversity of common frogs was negatively related to species richness. The negative SGDC was probably due to an opposite influence of environmental gradients on the two levels of biodiversity, since the focal species and the other amphibians differ in ecological preferences, particularly in terms of thermal optimum. Conversely, we did not find evidence for a role of interspecific interactions in the negative SGDC. Our findings stress that species richness cannot be used as a universal proxy for genetic diversity, and only combining SGDC with analyses on the determinants of biodiversity can allow to identify the processes determining the relationships between genetic and species diversity.",mds,True,findable,237,19,1,1,0,2018-10-02T20:39:12.000Z,2018-10-02T20:39:13.000Z,dryad.dryad,dryad,"species-genetic diversity correlation,Rana temporaria,Alpine amphibians","[{'subject': 'species-genetic diversity correlation'}, {'subject': 'Rana temporaria'}, {'subject': 'Alpine amphibians'}]",['31955352 bytes'],
+10.34847/nkl.a0fe865m,"Au pied des sources. Itinéraire de Marie-France, le 5 avril 2019 à Livet",NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Other,,"Itinéraire réalisé dans le cadre du projet de recherche-création Les Ondes de l’Eau : Mémoires des lieux et du travail dans la vallée de la Romanche. AAU-CRESSON (Laure Brayer, direction scientifique) - Regards des Lieux (Laure Nicoladzé, direction culturelle).
+
+Marie-France est née à Livet. Après avoir passé la moitié de sa vie ailleurs, elle y est aujourd’hui revenue.
+Elle a cofondé il y a deux ans l’association Marcheurs et Coureurs des Gorges de la Romanche qui rénove les chemins pédestres de la vallée. Ce jour d’avril ensoleillé il venait de neiger et nous nous sommes promenés dans les rues de la Renardière en direction du Fontario, où des sources anciennement captées jaillissent en pleine forêt pour retourner ensuite dans le cours tumultueux de la Romanche.",api,True,findable,0,0,0,0,0,2022-06-27T12:22:30.000Z,2022-06-27T12:22:30.000Z,inist.humanum,jbru,"méthode des itinéraires,environnement sonore,forêt,perception de l'espace,désindustrialisation,patrimoine industriel,pollution de l'air,Keller, Charles Albert (1874-1940 , Ingénieur A&M),Romanche, Vallée de la (France),énergie hydraulique,climat de montagne,montagnes -- aménagement,Perception sensible,Histoires de vie,paysage de l'eau,histoire orale,Marche,Sens et sensations,Mémoires des lieux,roman-photo,itinéraire,matériaux de terrain éditorialisés","[{'lang': 'fr', 'subject': 'méthode des itinéraires'}, {'lang': 'fr', 'subject': 'environnement sonore'}, {'lang': 'fr', 'subject': 'forêt'}, {'lang': 'fr', 'subject': ""perception de l'espace""}, {'lang': 'fr', 'subject': 'désindustrialisation'}, {'lang': 'fr', 'subject': 'patrimoine industriel'}, {'lang': 'fr', 'subject': ""pollution de l'air""}, {'lang': 'fr', 'subject': 'Keller, Charles Albert (1874-1940 , Ingénieur A&M)'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'énergie hydraulique'}, {'lang': 'fr', 'subject': 'climat de montagne'}, {'lang': 'fr', 'subject': 'montagnes -- aménagement'}, {'lang': 'fr', 'subject': 'Perception sensible'}, {'lang': 'fr', 'subject': 'Histoires de vie'}, {'lang': 'fr', 'subject': ""paysage de l'eau""}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'Marche'}, {'lang': 'fr', 'subject': 'Sens et sensations'}, {'lang': 'fr', 'subject': 'Mémoires des lieux'}, {'lang': 'fr', 'subject': 'roman-photo'}, {'lang': 'fr', 'subject': 'itinéraire'}, {'lang': 'fr', 'subject': 'matériaux de terrain éditorialisés'}]","['10680951 Bytes', '326384 Bytes', '110947 Bytes', '347698 Bytes', '1394463 Bytes', '1220074 Bytes', '1253240 Bytes', '1173528 Bytes', '1398574 Bytes', '1384255 Bytes', '1618130 Bytes', '1196287 Bytes', '1259731 Bytes', '1361277 Bytes', '1403907 Bytes', '1028221 Bytes']","['application/pdf', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg']"
+10.5281/zenodo.6221153,Non-local eddy-mean Kinetic Energy transfers,Zenodo,2022,,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access","Animation of eddy-mean Kinetic Energy transfers during the decorrelation phase of 120-day long, 20-member ensemble simulations of the Western Mediterranean basin. The three terms are associated with the kinetic energy equation of the ensemble mean flow (left), that of the turbulent flow (center) and that of the ensemble mean of the full flow (right). The latter is associated with non-local eddy-mean KE transfers.",mds,True,findable,0,0,0,0,0,2022-02-22T09:15:24.000Z,2022-02-22T09:15:24.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5682600,"FIGS. 7–8 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIGS. 7–8—Protonemura lupina sp. n., male. 7, terminalia, ¾ dorso-ventral view, left side; 8, terminalia with median and outer lobe sclerites (OLS1 and OLS2), lateral view; FIGS. 9–10—Protonemura lupina sp. n., female. 9, ventral view; 10, ventrolateral view.",mds,True,findable,0,0,0,0,0,2021-11-12T16:00:32.000Z,2021-11-12T16:00:33.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.7110117,mhmdjouni/AoAdmmAsc-python: v1,Zenodo,2022,,Software,Open Access,First working environment for tensor CPD based on AO-ADMM-ASC in Python,mds,True,findable,0,0,0,0,0,2022-09-24T12:49:59.000Z,2022-09-24T12:50:00.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3813574,"Data supplement for ""Thin-Film Modeling of Resting and Moving Active Droplets""",Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the data and source files for figures 4-10, 12, and 14-20 in the following publication: S. Trinschek, F. Stegemerten, K. John and U. Thiele <em>""Thin-Film Modeling of Resting and Moving Active Droplets""</em> published in 2020 in Physical Review E. Please follow the instructions given in 'Readme.txt'.",mds,True,findable,8,0,1,0,0,2020-06-07T12:34:13.000Z,2020-06-07T12:34:14.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4640463,Optimal Exclusive Perpetual Grid Exploration by Luminous Myopic Robots without Common Chirality: The Animations,Zenodo,2021,,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access","Animations of two optimal perpetual grid exploration algorithms. The published HTML pages allow the viewer to see the first 300 rounds of the algorithms, for different initial configurations. To view the animation without downloading them, they are also accessible at the following urls: https://bramas.fr/static/NETYS2021/range-1_3-robots_3-colors.html https://bramas.fr/static/NETYS2021/range-2_5-robots_oblivious.html",mds,True,findable,0,0,0,0,0,2021-03-26T17:53:10.000Z,2021-03-26T17:53:11.000Z,cern.zenodo,cern,"Mobile robots, distributed algorithms","[{'subject': 'Mobile robots, distributed algorithms'}]",,
+10.6084/m9.figshare.c.6771537.v1,"Supplementary material from ""Mirror exposure following visual body-size adaptation does not affect own body image""",The Royal Society,2023,,Collection,Creative Commons Attribution 4.0 International,"Prolonged visual exposure to large bodies produces a thinning aftereffect on subsequently seen bodies, and vice versa. This visual adaptation effect could contribute to the link between media exposure and body shape misperception. Indeed, people exposed to thin bodies in the media, who experience fattening aftereffects, may internalize the distorted image of their body they see in the mirror. This preregistered study tested this internalization hypothesis by exposing 196 young women to an obese adaptor before showing them their reflection in the mirror, or to a control condition. Then, we used a psychophysical task to measure the effects of this procedure on perceptual judgements about their own body size, relative to another body and to the control mirror exposure condition. We found moderate evidence against the hypothesized self-specific effects of mirror exposure on perceptual judgements. Our work strengthens the idea that body size adaptation affects the perception of test stimuli rather than the participants' own body image. We discuss recent studies which may provide an alternative framework to study media-related distortions of perceptual body image.",mds,True,findable,0,0,0,0,0,2023-08-02T11:18:30.000Z,2023-08-02T11:18:30.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",,
+10.5281/zenodo.7143466,Script Rmarkdown - Projet C-PED,Zenodo,2022,,Software,Restricted Access,Script Rmarkdown écrit avec R 4.0.5 dans le cadre du projet C-PED. Analyses statistiques en temps réel des données de l'étude C-PED en lien avec le fichier de saisie.,mds,True,findable,0,0,0,0,0,2022-10-04T14:04:17.000Z,2022-10-04T14:04:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7688636,A snippet from neXtSIM_DG : next generation sea-ice model with DG,Zenodo,2023,,Software,"Creative Commons Attribution 4.0 International,Open Access","<strong>A snippet from neXtSIM_DG : next generation sea-ice model with DG</strong> This archive contains the software described and required to reproduce the numerical results of the manuscript <em>""The neXtSIM-DG dynamical core: A Framework for Higher-order Finite Element Sea Ice Modeling""</em> by Thomas Richter, Véronique Dansereau, Christian Lessig and Piotr Minakowski. We strongly recommend that you access nextsim-DG's GitHub page https://github.com/nextsimdg/nextsimdg instead of this archive for the latest version of the code. The software is still under active development and this excerpt contains only a very small part of it. In the present form, it is provided for self-contained reproducibility. neXtSIM-DG is created as part of SASIP: The Scale-Aware Sea Ice Project which is funded by Schmidt Futures, a philanthropic initiative founded by Eric and Wendy Schmidt that bets early on exceptional people making the world better, particularly through innovative breakthroughs in science and technology. It is a project of Schmidt Futures' Virtual Earth System Research Institute (VESRI). <strong>Installation</strong> The main requirements for compiling the neXtSIM_DG and the test cases from the manuscript are the cmake build environment a C++17 compiler. We made best experience with gcc (but clang also works) the template linear algebra library Eigen version 3.4 or newer We assume that <code>.../nextsim/</code> is the path to the directory where this readme is located. To configure and compile neXtSIM_DG: create a build directory <code>mkdir BUILD</code> In <code>BUILD</code> configure neXtSIM_DG with <code>cmake .../nextsim</code>. You can adjust the settings by issuing <code>ccmake .</code> within the build directory. In particular, consider to set <code>CMAKE_BUILD_TYPE</code> to <code>Release</code> for optimal performance and turning <code>WITH_THREADS</code> to <code>ON</code> for OpenMP multithreading support. In <code>BUILD</code> compile neXtSIM_DG by calling <code>make</code>. The executables for running the numerical tests will all be located within the build directory at <code>BUILD/dynamics/tests</code>. Detailed <strong>installation instructions</strong> for the complete neXtSIM_DG project can be found here. <strong>Running the test cases</strong> The test cases do not depend on any external data and can be started from any working directory. <strong>Advection Testcase I</strong> This reproduces Testcase I specified in Section 5.1.1 of the manuscript. A smooth initial condition is advected in a rotational velocity field using discontinuous Galerkin DG(0), DG(1) and DG(2) discretizations on sequences of refined meshes. <code>BUILD/dynamics/tests/example1-sasipmesh</code> The output shows the number of DG degrees of freedom (1 for DG(0), 3 for DG(1) and 6 for DG(2)), the number of time steps and the number of grid cells in each grid direction. This is followed by the error in mass conservation as well as the discretization error and the discretization error stored in the program. The outputs correspond to Figure 4 of the manuscript (see also the documentation). vtk-outputs of the solution are written out in folders named <code>Example1_DG_NX</code>, where again DG is the number of DG degrees of freedom and NX is the number of mesh elements in each direction. <strong>Advection Testcase II</strong> This reproduces Testcase II specified in Section 5.1.2 of the manuscript. An initial condition that represents four shapes with different smoothness (see Figure 6 of the manuscript) is advected in a ring domain. The test is repeated using discontinuous Galerkin DG(0), DG(1) and DG(2) discretizations on sequences of refined meshes. <code>BUILD/dynamics/tests/example2-sasipmesh</code> The output is corresponding to Testcase I. The vtk's correspond to Figure 7 in the manuscript. <strong>LKF Benchmark</strong> This example reproduces the sea ice benchmark configuration that is described in Section 5.2 of the manuscript and that first has been introduced by Mehlmann and Richter in A modified global Newton solver for viscous-plastic sea ice models and that has been used for comparing different sea ice implementations in Simulating Linear Kinematic Features in Viscous-Plastic Sea Ice Models on Quadrilateral and Triangular Grids With Different Variable Staggering. <code>BUILD/dynamics/tests/example2-sasipmesh</code> The benchmark is defined on a domain of size <strong>512km x 512km</strong> for <strong>2 days</strong> simulation time. VTK output is generated every hour and stored in <code>Benchmark_CG_DG_NX</code> where <code>CG</code> stands for the degree of the velocity discretization (1 or 2) and <code>DG</code> for the number of DG degrees of freedom (1, 3 or 6). <code>NX</code> is the number of elements in each direction. These three parameters are adjusted in the file <code>benchmark_mevp.cpp</code> within the main function. <strong>Multithreading</strong> If configured with <code>WITH_THREADS ON</code>, neXtsim_DG will take the maximum number of available threads. You can control the number of threads by setting the environment variable <code>OMP_NUM_THREADS</code>.",mds,True,findable,0,0,0,0,0,2023-03-02T16:56:01.000Z,2023-03-02T16:56:02.000Z,cern.zenodo,cern,"sea ice,C++,SASIP,finite elements,discontinuous Galerkin","[{'subject': 'sea ice'}, {'subject': 'C++'}, {'subject': 'SASIP'}, {'subject': 'finite elements'}, {'subject': 'discontinuous Galerkin'}]",,
+10.5281/zenodo.7982064,"FIGURES E1–E6. Leuctra jahorinensis stat. nov., adults. E1 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,Open Access,"FIGURES E1–E6. Leuctra jahorinensis stat. nov., adults. E1, brachypterous adult male, dorsal view; E2–E3, posteromedial process on tergite VIII of adult male, dorsal view; E4, adult male, specillum and stylus, lateral view; E5, adult female, ventral view; E6, adult female, lateral view.",mds,True,findable,0,0,0,0,0,2023-05-29T13:44:21.000Z,2023-05-29T13:44:22.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.4761289,"Figs. 2-3 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 2-3. Dictyogenus jurassicum sp. n. 2. Adult female, head and pronotum. Spring of River Doubs, Mouthe, Doubs dpt, France. Photo A. Ruffoni. 3. Adult male, hemitergites, dorsal view. Karstic spring at Charabotte Mill, Ain dpt, France. Photo B. Launay.",mds,True,findable,0,0,6,0,0,2021-05-14T07:43:04.000Z,2021-05-14T07:43:04.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.34847/nkl.ca8dmbdh,Fragment de l'épaisseur sensible - détail de la carte des mémoires sensibles de la Romanche,NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,PhysicalObject,,"Représentation cartographique de la Romanche par AAU-CRESSON (Laure Brayer, Ryma Hadbi, Emmanuelle Pilon) dans le cadre du projet Les Ondes de l'Eau : Mémoires des lieux et du travail dans la vallée de la Romanche. AAU-CRESSON (Laure Brayer, direction scientifique) - Regards des Lieux (Laure Nicoladzé, direction culturelle).
+
+On peut faire l’expérience de la Romanche bien au-delà de son lit. C’est d’abord une rencontre sonore, thermique, aéraulique. Comment traduire sur la carte cette épaisseur sensible ? Cette tentative de représentation s’appuie sur l’itinéraire des jeunes filles (également sur Nakala : https://doi.org/10.34847/nkl.231c4067) et la recherche graphique menée par Emmanuelle Pilon lors de la production de sa version dessinée.
+
+Codification de la présence de la route nationale (son et mouvement en rouge) et de l'épaisseur sensible de la rivière (fraicheur et humidité en bleu, ambiance sonore en beige, et vent en rouge).",api,True,findable,0,0,1,0,0,2022-06-27T12:37:22.000Z,2022-06-27T12:37:22.000Z,inist.humanum,jbru,"Cartographie sensible,épaisseur sensible,ambiance,perception de l'espace,sens et sensations,Romanche, Vallée de la (France),fraicheur,humidité,ambiance sonore,émergence sonore,vent,air,carte sensible","[{'lang': 'fr', 'subject': 'Cartographie sensible'}, {'lang': 'fr', 'subject': 'épaisseur sensible'}, {'lang': 'fr', 'subject': 'ambiance'}, {'lang': 'fr', 'subject': ""perception de l'espace""}, {'lang': 'fr', 'subject': 'sens et sensations'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'fraicheur'}, {'lang': 'fr', 'subject': 'humidité'}, {'lang': 'fr', 'subject': 'ambiance sonore'}, {'lang': 'fr', 'subject': 'émergence sonore'}, {'lang': 'fr', 'subject': 'vent'}, {'lang': 'fr', 'subject': 'air'}, {'subject': 'carte sensible'}]","['2025688 Bytes', '21175362 Bytes']","['image/jpeg', 'application/pdf']"
+10.5281/zenodo.4757640,Figs. 9–13 in Morphology And Systematic Position Of Two Leuctra Species (Plecoptera: Leuctridae) Believed To Have No Specilla,Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 9–13. Leuctra ketamensis. Male abdomen: 9, Dorsal. 10, Ventral, sternite IX;.11, Paraprocts, dorsal. 12, Paraprocts, lateral. Female abdomen: 13, Ventral, showing the pregenital and subgenital plates (13 from Sanchez-Ortéga & Assouz, 1997).",mds,True,findable,0,0,2,0,0,2021-05-13T16:06:55.000Z,2021-05-13T16:06:55.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.4302006,"Supplementary material for ""A Partitioned Finite Element Method for power-preserving discretization of open systems of conservation laws""",Zenodo,2020,,Dataset,Open Access,"This archive contains supplementary material for the paper ""A Partitioned Finite Element Method for power-preserving discretization of open systems of conservation laws"", containing the source codes for the numerial results presented in the paper. An arXiv pre-print version of the paper is available here. The following codes are provided: <code>codes/simulation1D_small.jl</code>: small amplitudes (linear) 1D simulation <code>codes/simulation1D_large.jl</code>: large amplitudes (nonlinear) 1D simulation <code>codes/simulation1D_analytical_gradient</code>: large amplitudes 1D simulation, but using an analytical nonlinear Hamiltonian gradient expression <code>codes/simulation2D.jl</code>: large amplitudes (nonlinear) 2D simulation <code>codes/convergence1D.jl</code>: convergence analysis of the 1D linear case <code>codes/convergence2D.m</code>: convergence analysis of the 2D linear case A GitHub with the codes and a few instructions on usage is available here. <strong>Acknowledgements</strong> This work has been performed in the frame of the Collaborative Research DFG and ANR project INFIDHEM, entitled ""Interconnected of Infinite-Dimensional systems for Heterogeneous Media"", nº ANR-16-CE92-0028. Further information is available here.",mds,True,findable,0,0,1,0,0,2020-12-02T11:54:54.000Z,2020-12-02T11:54:56.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7342481,IMBIE software v3.0,Zenodo,2022,,Software,"Creative Commons Attribution 4.0 International,Open Access","The IMBIE processor version 3.0 is the python code developed to parse, aggregate and combine the satellite-based ice sheet mass balance estimates included in the IMBIE assessment described in the <em>Earth System Science Data</em> preprint 'Mass Balance of the Greenland and Antarctic Ice Sheets from 1992 to 2020' (https://doi.org/10.5194/essd-2022-261). More information on the Ice Sheet Mass Balance Inter-Comparison Exercise (IMBIE) can be found on the dedicated project website: http://imbie.org/.",mds,True,findable,0,0,0,0,0,2022-11-29T09:19:41.000Z,2022-11-29T09:19:41.000Z,cern.zenodo,cern,"ice sheets,Antarctica,Greenland,Earth Observation,sea level rise","[{'subject': 'ice sheets'}, {'subject': 'Antarctica'}, {'subject': 'Greenland'}, {'subject': 'Earth Observation'}, {'subject': 'sea level rise'}]",,
+10.5061/dryad.wh70rxwpz,"Consilience across multiple, independent genomic data sets reveals species in a complex with limited phenotypic variation",Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Species delimitation in the genomic era has focused predominantly on the application of multiple analytical methodologies to a single massive parallel sequencing (MPS) data set, rather than leveraging the unique but complementary insights provided by different classes of MPS data. In this study we demonstrate how the use of two independent MPS data sets, a sequence capture data set and a single nucleotide polymorphism (SNP) data set generated via genotyping-by-sequencing, enables the resolution of species in three complexes belonging to the grass genus Ehrharta, whose strong population structure and subtle morphological variation limit the effectiveness of traditional species delimitation approaches. Sequence capture data are used to construct a comprehensive phylogenetic tree of Ehrharta and to resolve population relationships within the focal clades, while SNP data are used to detect patterns of gene pool sharing across populations, using a novel approach that visualises multiple values of K. Given that the two genomic data sets are fully independent, the strong congruence in the clusters they resolve provides powerful ratification of species boundaries in all three complexes studied. Our approach is also able to resolve a number of single-population species and a probable hybrid species, both which would be difficult to detect and characterize using a single MPS data set. Overall, the data reveal the existence of 11 and five species in the E. setacea and E. rehmannii complexes, with the E. ramosa complex requiring further sampling before species limits are finalized. Despite phenotypic differentiation being generally subtle, true crypsis is limited to just a few species pairs and triplets. We conclude that, in the absence of strong morphological differentiation, the use of multiple, independent genomic data sets is necessary in order to provide the cross-data set corroboration that is foundational to an integrative taxonomic approach.",mds,True,findable,98,6,0,0,0,2023-02-14T19:25:59.000Z,2023-02-14T19:26:00.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['12793091 bytes'],
+10.5061/dryad.f7h12,Data from: Poor adherence to guidelines for preventing central line-associated bloodstream infections (CLABSI): results of a worldwide survey,Dryad,2017,en,Dataset,Creative Commons Zero v1.0 Universal,"Background: Central line-associated bloodstream infections (CLABSI) are a cause of increased morbidity and mortality, and are largely preventable. We documented attitudes and practices in intensive care units (ICUs) in 2015 in order to assess compliance with CLABSI prevention guidelines. Methods: Between June and October 2015, an online questionnaire was made available to medical doctors and nurses working in ICUs worldwide. We investigated practices related to central line (CL) insertion, maintenance and measurement of CLABSI-related data following the SHEA guidelines as a standard. We computed weighted estimates for high, middle and low-income countries using country population as a weight. Only countries providing at least 10 complete responses were included in these estimates. Results: Ninety five countries provided 3407 individual responses; no low income, 14 middle income (MIC) and 27 high income (HIC) countries provided 10 or more responses. Of the total respondents, 80% (MIC, SE = 1.5) and 81% (HIC, SE = 1.0) reported availability of written clinical guidelines for CLABSI prevention in their ICU; 23% (MIC,SE = 1.7) and 62% (HIC,SE = 1.4) reported compliance to the following (combined) recommendations for CL insertion: hand hygiene, full barrier precaution, chlorhexidine >0.5%, no topic or systemic antimicrobial prophylaxis; 60% (MIC,SE = 2.0) and 73% (HIC,SE = 1.2) reported daily assessment for the need of a central line. Most considered CLABSI measurement key to quality improvement, however few were able to report their CLABSI rate. Heterogeneity between countries was high and country specific results are made available. Conclusions: This study has identified areas for improvement in CLABSI prevention practices linked to CL insertion and maintenance. Priorities for intervention differ between countries.",mds,True,findable,422,97,1,1,0,2016-10-31T16:48:38.000Z,2016-10-31T16:48:39.000Z,dryad.dryad,dryad,"central line-associated bloodstream infection,healthcare associated infection,intensive care","[{'subject': 'central line-associated bloodstream infection'}, {'subject': 'healthcare associated infection'}, {'subject': 'intensive care'}]",['2869151 bytes'],
+10.5281/zenodo.61089,The Debsources Dataset: Two Decades Of Free And Open Source Software,Zenodo,2016,,Dataset,"Creative Commons Attribution Share-Alike 4.0,Open Access","This is the Debsources Dataset: source code and related metadata spanning two decades of Free and Open Source Software (FOSS) history, seen through the lens of the Debian distribution.
+
+The dataset spans more than 3 billion lines of source code as well as metadata about them such as: size metrics (lines of code, disk usage), developer-defined symbols (ctags), file-level checksums (SHA1, SHA256, TLSH), file media types (MIME), release information (which version of which package containing which source code files has been released when), and license informa-<br>
+tion (GPL, BSD, etc).
+
+The Debsources Dataset comes as a set of tarballs containing deduplicated unique source code files organized by their SHA1 checksums (the source code), plus a portable PostgreSQL database dump (the metadata).
+
+The Debsources Dataset is described in full in the paper The Debsources Dataset: Two Decades of Free and Open Source Software, published on the Empirical Software Engineering journal with DOI 10.1007/s10664-016-9461-5 . A preprint of the paper is available at https://upsilon.cc/~zack/research/publications/debsources-ese-2016.pdf .",,True,findable,1,0,0,0,0,2016-08-29T13:52:40.000Z,2016-08-29T13:52:40.000Z,cern.zenodo,cern,"debian,open source,free software,source code,software evolution","[{'subject': 'debian'}, {'subject': 'open source'}, {'subject': 'free software'}, {'subject': 'source code'}, {'subject': 'software evolution'}]",,
+10.57726/cbag-z376,Édifier l'État: politique et culture en Savoie au temps de Christine de France,Presses Universitaires Savoie Mont Blanc,2014,fr,Book,,,fabricaForm,True,findable,0,0,0,0,0,2022-03-14T08:40:42.000Z,2022-03-14T08:40:43.000Z,pusmb.prod,pusmb,FOS: Humanities,"[{'subject': 'FOS: Humanities', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['266 pages'],
+10.5281/zenodo.4761287,"Fig. 1 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 1. Dictyogenus jurassicum sp. n., adult female habitus. Spring of River Doubs, Mouthe, Doubs dpt, France. Photo A. Ruffoni.",mds,True,findable,0,0,2,0,0,2021-05-14T07:42:49.000Z,2021-05-14T07:42:50.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.4804629,FIGURES 11–14 in Review and contribution to the stonefly (Insecta: Plecoptera) fauna of Azerbaijan,Zenodo,2021,,Image,Open Access,"FIGURES 11–14. Mermithid infected Protonemura sp. (aculeata?) male from the Greater Caucasus—11: terminalia, ventral view; 12: same, lateral view; 13: same, dorsal view; 14: same, dorsocaudal view—scale 1 mm.",mds,True,findable,0,0,2,0,0,2021-05-26T07:55:03.000Z,2021-05-26T07:55:04.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5285/634ee206-258f-4b47-9237-efff4ef9eedd,"Polarimetric ApRES data on a profile across Dome C, East Antarctica, 2013-2014",NERC EDS UK Polar Data Centre,2021,en,Dataset,Open Government Licence V3.0,"The radar data collected in 2013-2014 at Dome C, East Antarctica, aims to understand bulk preferred crystal orientation fabric near a dome. We measure changes in englacial birefringence and anisotropic scattering in 21 sites along a 36 km long profile across Dome C. These optical properties are obtained by analysing radar returns for different antenna orientations. More details can be found in Ershadi et al, 2021. Funding was provided by BAS National Capability and IPEV core funding.",mds,True,findable,0,0,0,1,0,2021-09-16T11:17:15.000Z,2021-09-16T11:19:24.000Z,bl.nerc,rckq,"""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS"",""GLACIER MOTION/ICE SHEET MOTION"",""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS"",""ICE SHEETS"",ApRES,Dome C,fabric,polarimetric radar","[{'subject': '""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS"",""GLACIER MOTION/ICE SHEET MOTION""', 'schemeUri': 'http://gcmdservices.gsfc.nasa.gov/kms/concepts/concept_scheme/sciencekeywords/?format=xml', 'subjectScheme': 'GCMD'}, {'subject': '""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS"",""ICE SHEETS""', 'schemeUri': 'http://gcmdservices.gsfc.nasa.gov/kms/concepts/concept_scheme/sciencekeywords/?format=xml', 'subjectScheme': 'GCMD'}, {'subject': 'ApRES'}, {'subject': 'Dome C'}, {'subject': 'fabric'}, {'subject': 'polarimetric radar'}]","['81 files', '148.8 MB']","['text/plain', 'text/csv', 'application/x-hdf', 'application/netcdf']"
+10.5281/zenodo.7866962,"Time-of-failure prediction of the Achoma landslide, Peru, from high frequency Planetscope satellites",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Introduction</strong> This repository contains the data used for the study of the slope instability of Achoma, Peru, described in Lacroix et al. (submitted). Specifically, the repository contains a time series of horizontal ground displacements, obtained from high frequency PlanetScope satellite between 2017 and 2020. It also contains two Digital Elevation Models, one from before the Achoma failure obtained with Pléaides stero images, and the other from just after the Achoma failure obtained with drone imagery. The data and methods used for the elaboration of this data repository are described in detail in Lacroix et al. (submitted). In this repository we also provide a short summary and overview of the data and methods used. <strong>Data</strong> A total of 79 PlanetScope scenes were used to produce the time series of horizontal horizontal ground displacements maps. Table 1 provides an overview of these data. Table1: Data used for the creation of this repository Application Platforms Acquisition dates Pre-failure DEM Pléiades 2017/05/13 Post-failure DEM Drone 2020/06/19 Horizontal ground displacement PlanetScope 79 scenes from 2017/11/27 to 2020/06/17 <br> <strong>Methods</strong> The horizontal ground displacement maps, both along the NS and the EW directions (file names NSxxxxxxxx.tif and Ewxxxxxxxx.tif, where xxxxxxxx is the date in the format yyyymmdd) were created using the offset tracking methodology described in Bontemps et al. (2018), consisting of: (1) correlation of all the pairs of images using Mic-Mac (Rupnik et al., 2017), (2) masking the low correlation coefficient values (CC<0.7), (3) mosaicking correction, similar to stripe corrections (Bontemps et al., 2018), that we obtained by subtracting the median value of the stacked profile in the along-stripe direction, taking into account only stable areas, (4) least square inversion of the redundant system per pixel, weighted by the time separation between pairs (Bontemps et al., 2018), (5) correction of illumination effects (Lacroix et al., 2019), based on the 2 years of data between November 2017 and December 2019. The pre-failure DEM was computed from Ames Stereo Pipeline (Shean et al. 2016) and the methodology developed in (Lacroix, 2016) applied to the Pléiades stereo images (file name DEM_20170513_shifted_vertical2.tif ). The post-failure DEM was processed using the Structure from Motion-Multi View Stereo (SfM-MVS) methodology with the Agisoft Metashape Professional 1.5.5 software applied on 1824 pictures taken from the drone (file name Achoma_DEM_2020.06.20_UTM19S_50cm.tif ).<br> <strong>Acknowledgements</strong> P.L. acknowledge the support from the French Space Agency (CNES) through the TOSCA, PNTS, and ISIS programs. <strong>Dataset attribution</strong> This dataset is licensed under a Creative Commons CC BY 4.0 International License. <strong>Dataset Citation</strong> Lacroix, P., Huanca, J., Angel, L., Taipe, E.: Data Repository: Time-of-failure prediction of the Achoma landslide, Peru, from high frequency Planetscope satellites. Dataset distributed on Zenodo: 10.5281/zenodo.7866962",mds,True,findable,0,0,0,0,0,2023-04-26T13:03:38.000Z,2023-04-26T13:03:38.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.48170,"Experimental Data For The Publication: ""Evaluating Scintillator Performance In Time-Resolved, Hard X-Ray Studies At Synchrotron Light Sources""",Zenodo,2016,,Dataset,"Creative Commons Zero - CC0 1.0,Open Access","In accordance with the expectations outlined in <em><strong>Clarifications of EPSRC expectations on research data management</strong></em> (09/10/14) this data has been made publicly available to complement the open access publication ""Evaluating scintillator performance in time-resolved, hard X-ray studies at synchrotron light sources"".
+
+There are six data sets, corresponding to the six experimental data sets presented in the article. In each data set, which may be identified by their file names and reference to the article, the 1st column is the RF trigger - to - ICCD exposure delay in [ns], and the second column in the intensity recorded on the ICCD in [counts]. This intensity accounts for any online and offline processing outlined in the article, such as on-CCD exposures, dark frame correction etc.",,True,findable,0,0,0,0,0,2016-03-23T13:07:36.000Z,2016-03-23T13:07:37.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.22621187,"Additional file 1 of Promoting HPV vaccination at school: a mixed methods study exploring knowledge, beliefs and attitudes of French school staff",figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Additional Table 1. Teams conducting the PrevHPV program (The PrevHPV Consortium). Additional Table 2. COREQ (COnsolidated criteria for REporting Qualitative research) Checklist. Additional Table 3. STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) Statement — checklist of items that should be included in reports of observational studies. Additional Table 4. Characteristics of the middle schools invited to participate in the study and of those which accepted to participate. Additional Table 5. Additional illustrative verbatim of participants to the focus groups. Additional Table 6. Psychological antecedents of vaccination (5C scale) among participants to the self-administered online questionnaire and by profession. Additional Table 7. Public health topics discussed with pupils by participants to the self-administered online questionnaire and by profession. Additional Table 8. Appropriate period to propose HPV vaccination among pupils according to participants to the self-administered online questionnaire and by profession. Additional Document 1. Self-administered online questionnaire. Additional Document 2. Focus groups’ interview guide. Additional Document 3. Names of the PrevHPV Study Group’s members.,mds,True,findable,0,0,0,0,0,2023-04-13T14:58:32.000Z,2023-04-13T14:58:32.000Z,figshare.ars,otjm,"Medicine,Molecular Biology,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Molecular Biology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['77628 Bytes'],
+10.5281/zenodo.7655981,Data for Widespread detection of chlorine oxyacids in the Arctic atmosphere: Villum Research Station and Ny-Ã…lesund observations,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",The data includes: 1) Data for the time series of HClO3 and HClO4 together with relevant data from the Villum Research Station observations. 2) Data for the time series of HClO3 from Ny-Ã…lesund observation. 3) Data of the estimated cross-section and photolysis rate of HClO3 and HClO4. Data are also available from the corresponding authors upon request.,mds,True,findable,0,0,0,0,0,2023-02-20T08:12:38.000Z,2023-02-20T08:12:38.000Z,cern.zenodo,cern,chlorine oxyacids,[{'subject': 'chlorine oxyacids'}],,
+10.5281/zenodo.7458358,archive_image_correlation_robust_geometrical_design_of_2D_sequential_interlocking_assemblies,Zenodo,2022,en,Image,"Creative Commons Attribution 4.0 International,Open Access","Archive containing the X and Y deformation, obtained by image correlation, of several laser cut samples of assemblies generated using the method described in the article Robust geometrical design of 2D sequential interlocking assemblies (not published yet)",mds,True,findable,0,0,0,0,0,2022-12-19T16:15:35.000Z,2022-12-19T16:15:35.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4625619,org_attach,Zenodo,2021,,Software,"MIT License,Open Access",Add an entry with attachment in an org-mode file,mds,True,findable,0,0,1,0,0,2021-03-21T15:14:09.000Z,2021-03-21T15:14:10.000Z,cern.zenodo,cern,org-mode,[{'subject': 'org-mode'}],,
+10.5281/zenodo.8388918,Sources et modèles cités dans le manuscrit de thèse,Zenodo,2023,,Other,"Creative Commons Attribution 4.0 International,Open Access","Contient : yamass-src : le code du simulateur. model-checking : les modèles utilisés pour la vérification par modèle du système de l'infrastructure à clefs publiques. maki-src : le code du système de l'infrastructure à clefs publique, exécutée dans le simulateur. blockain-src : le code du prototype de Blockchain, exécutée dans le simulateur.",mds,True,findable,0,0,0,0,0,2023-09-29T09:00:58.000Z,2023-09-29T09:00:58.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4264162,Evolution of Physical Activity Habits After A Context Change: The Case of COVID-19 Lockdown,Zenodo,2020,,Dataset,Creative Commons Attribution 4.0 International,"Data set used for analysis.Â
+
+
+Sheet 1 : Data
+
+
+Sheet 2 : Description of the variables.Â
+
+
+Â ",mds,True,findable,0,0,0,0,0,2020-11-09T10:01:52.000Z,2020-11-09T10:01:53.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3543624,Ice front blocking in a laboratory model of the Antarctic ice shelf,Zenodo,2019,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Mass loss from the Antarctic Ice Sheet to the ocean has increased in recent decades, largely because the thinning of its floating ice shelves has allowed the outflow of grounded ice to accelerate. Enhanced basal melting of the ice shelves is thought to be the ultimate driver of change, motivating a recent focus on the processes that control ocean heat transport onto and across the seabed of the Antarctic continental shelf towards the ice. However, the shoreward heat flux typically far exceeds that required to match observed melt rates, suggesting other critical controls. By laboratory experiments on the Coriolis rotating platform, we show that the depth-independent component of the flow towards an ice shelf is blocked by the dramatic step shape of the ice front, and that only the depth-varying component, typically much smaller, can enter the sub-ice cavity. These results are consistent with direct observations of the Getz Ice Shelf system, as shown by Wahlin et al. (Nature 2019, in press). The selected data are velocity fields from a selection of 6 experiments, described in Wahlin et al. (2019), supplementary material, fig 4 and 9. EXP26,30,34 correspond to Fig. 4 a,b,c respectively (barotropic case) EXP44,50,51 correspond to Fig. 9 a,b,c respectively (baroclinic case) The velocity fields are measured by PIV from short image series (bursts) obtained by laser sheet illumination in several quasi-horizontal planes (for Fig 4, N=12 planes vertically separated by 6.2 cm, with 25 images per level, for Fig 9, N=7 planes vertically separated by 5.8 cm, with 19 images per level). The quasi-horizontal planes are parallel to the channel, slanted downward toward the iceshelf with an angle of 1.15 degree. For each experiment, the whole series of velocity fields is provided in /PCO1.png.sback.civ-PCO2.png.sback.civ.mproj (those are obtained by merging velocity fields from the images of two cameras denoted PCO1 and PCO2) velocity fields averaged inside each burst are provided in PCO1.png.sback.civ-PCO2.png.sback.civ.mproj.stat. Each velocity field is in a single netcdf file labeled by two indices denoting respectively the time and the index in the burst. Planes are scanned in a cyclic way, so that the same position is reached again after each increment of N in the first index. The average of these averaged velocity fields over 4 volumes when the current is fully established are provided in PCO1.png.sback.civ-PCO2.png.sback.civ.mproj.stat.stat. Details of the set-up and experimental conditions are provided in http://servforge.legi.grenoble-inp.fr/projects/pj-coriolis-17iceshelf",mds,True,findable,0,0,0,0,0,2019-11-15T16:26:23.000Z,2019-11-15T16:26:24.000Z,cern.zenodo,cern,"Stratified flow,Ice shelf,Oceanography,FOS: Earth and related environmental sciences,Barotropic flow","[{'subject': 'Stratified flow'}, {'subject': 'Ice shelf'}, {'subject': 'Oceanography'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Barotropic flow'}]",,
+10.5281/zenodo.4562706,Investigating the young AU Mic system with SPIRou: stellar magnetic field and close-in planet mass,Zenodo,2021,en,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access","Measuring the mean densities of close-in planets orbiting pre-main-sequence (PMS) stars is crucially needed by planet formation and evolution models. However, PMS stars exhibit intense magnetic activity inducing fluctuations in both photometric and RV curves that overshadow planet signatures. As a result, no close-in planet younger than 25 Myr has a well-constrained bulk density. In this study, we present a spectropolarimetric and velocimetric analysis of 27 near-infrared observations of the nearby active 22 Myr-old red dwarf AU Microscopii collected with SPIRou at the end of the year 2019. We jointly model the planet and stellar activity RV components, resulting in a 3.9σσ-detection of the recently-discovered close-in Neptune-sized planet AU Mic b, with an estimated mass of 17.1+4.7−4.5−4.5+4.7 M⊕⊕, implying a Neptune-like density for the planet. A consistent detection of the planet is independently obtained by simultaneously reconstructing the surface distribution of bright and dark inhomogeneities and estimating the planet parameters using Doppler imaging (DI). Using Zeeman-Doppler Imaging, we invert our time-series of intensity and circularly-polarized line profiles into distributions of brightness and large-scale magnetic field at the surface of the star and explore how these distributions are sheared by latitudinal differential rotation. Finally, we investigate the magnetic activity of AU Mic by computing various indicators and found that the disk-integrated magnetic flux density correlates best with the stellar activity RV signal, in line with recent solar observations.",mds,True,findable,0,0,0,0,0,2021-02-25T23:17:55.000Z,2021-02-25T23:17:56.000Z,cern.zenodo,cern,Young stars,[{'subject': 'Young stars'}],,
+10.5281/zenodo.7224878,First Test upload,Zenodo,2022,,Audiovisual,Closed Access,Videos of the executions on the simulator Carla of the scenarios used for the experiment of an article.,mds,True,findable,0,0,0,0,0,2022-10-19T12:12:06.000Z,2022-10-19T12:12:07.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8008238,Takin 2,Zenodo,2023,en,Software,Open Access,"This is <strong>Takin 2</strong>, an inelastic neutron scattering software suite. The source repositories for development can be found here:<br> https://code.ill.fr/scientific-software/takin.<br> A unified single repository for stable release versions is available here:<br> https://github.com/ILLGrenoble/takin, https://github.com/t-weber/takin2. The software documentation is available here:<br> https://github.com/ILLGrenoble/takin/wiki, https://code.ill.fr/scientific-software/takin/core/-/wikis/home. <em>Note: This is version 2 of the software; the final Takin version 1 source code (2014-2019) is available here: https://github.com/t-weber/takin and has the DOI 10.5281/zenodo.3961491.</em>",mds,True,findable,0,0,0,0,0,2023-06-05T23:53:47.000Z,2023-06-05T23:53:48.000Z,cern.zenodo,cern,"neutron scattering,triple-axis spectrometer,resolution convolution fitting","[{'subject': 'neutron scattering'}, {'subject': 'triple-axis spectrometer'}, {'subject': 'resolution convolution fitting'}]",,
+10.5281/zenodo.7628236,Raw sequencing data for studying the colonization of soil communities after glacier retreat,Zenodo,2022,,Dataset,Creative Commons Attribution 4.0 International,"Glaciers show a pattern of retreat at the global scale. Deglaciated areas are exposed and colonized by multiple organisms, but lack of global studies hampers a complete understanding of the future of these ecosystems. Until now, the complete reconstruction of soil communities was hampered by the complex identification of organisms, thus analyses at broad geographical and taxonomic scale have been so far impossible. The dataset used for this study represents the assemblages of Bacteria, Mycota, Eukaryota, Collembola (springtails), Oligochaeta (Earth worms), Insecta, Arthropoda and Vascular Plants obtained using environmental DNA (eDNA) metabarcoding. eDNA was extracted from soil samples collected from multiple glacier forelands representative of some of the main mountain chains of Europe, Asia, the Americas and Oceania. We investigated chronosequences of glacier retreat (i.e., the chronological sequence of specific geomorphological features along deglaciated areas for which the date of glacier retreat is known) ranging from recent years to the Little Ice Age (~1850). We used this newly assembled global DNA metabarcoding dataset to obtain a complete reconstruction of community changes in novel ecosystems after glacier retreat. Information on assemblages can be then combined with analyses of soil, landscape and climate to identify the drivers of community changes.",api,True,findable,0,0,0,0,0,2023-11-06T10:49:09.000Z,2023-11-06T10:49:09.000Z,cern.zenodo,cern,"environmental DNA (eDNA),Illumina sequencing,Fungi,Eukaryota,Bacteria,Collembola,Insecta,Oligochaeta,Spermatophyta,Vascular plants,Springtails,Earthworms,Glacier retreat,Deglaciated terrains","[{'subject': 'environmental DNA (eDNA)'}, {'subject': 'Illumina sequencing'}, {'subject': 'Fungi'}, {'subject': 'Eukaryota'}, {'subject': 'Bacteria'}, {'subject': 'Collembola'}, {'subject': 'Insecta'}, {'subject': 'Oligochaeta'}, {'subject': 'Spermatophyta'}, {'subject': 'Vascular plants'}, {'subject': 'Springtails'}, {'subject': 'Earthworms'}, {'subject': 'Glacier retreat'}, {'subject': 'Deglaciated terrains'}]",,
+10.5281/zenodo.7871187,"Automated processing of aerial imagery for geohazards monitoring: Results from Fagradalsfjall eruption, SW Iceland, August 2022",Zenodo,2023,en,Dataset,"Non-Commercial Government Licence,Open Access","<strong>1-</strong> <strong>Dataset Summary</strong><br> Here we present a dataset of DEMs (Digital Elevation Models), orthomosaics, and lava area outlines for the August 2022 eruption at Fagradalsfjall, SW Iceland. The dataset consists of: (1) five aerial surveys collected over the course of the August 2022 Fagradalsfjall eruption, (2) one survey carried out on 14 August 2022 using Pléiades satellite stereo images, and (3) a larger aerial survey, covering the 2021 and 2022 eruption sites in late September 2022 after the volcanic activity concluded. <strong>2- Background</strong> The volcano at Fagradalsfjall, SW-Iceland, began erupting on 3 August 2022 at 13:20 following 10 months of quiescence. As part of the response plan, a series of photogrammetric surveys were conducted in rapid, operational mode throughout the duration of the eruption. Subsequent production of data products for natural hazards monitoring (lava maps, lava volumes, effusion rates) were calculated within hours and reported to the Icelandic Civil Defense, following a similar approach that described in Pedersen et al., 2022a and in Gouhier et al., 2022. At the start of the 2022 eruption, GCPs had not yet been placed around the new fissure, but reference data (orthomosaics and DEMs) which had been georeferenced using targets measured with differential GNSS existed of the eruption site from September 2021 from Pedersen et al. (2022b) were available to use as a reference in the new workflow instead of GCPs. Due to the urgent need from authorities for information about the new eruption, a processing method that avoids the time-consuming task of manual GCP selection using a reference image for georeferencing was preferable in this instance. Besides the acquisition of aerial photographs, the CIEST2 initiative was also re-activated to collect Pléiades stereo images in emergency mode (Gouhier et al., 2022). <strong>3 – Overview of data collection</strong> Table 1 contains the overview of the surveys collected and presented in this repository. Table 1. Summary of surveys included in this dataset, by survey date. <strong>Date & Time</strong><br> <strong>YYYYMMDD HH:MM</strong> <strong>Sensor</strong> <strong>Platform</strong> <strong>Flight alt.</strong><br> <strong>(m asl)</strong> <strong>Images</strong> <strong>Surveyed</strong><br> <strong>km<sup>2</sup></strong> 20220803 17:05 A6D TF-203* ~ 850 46 4 20220804 11:00 A6D TF-203 ~ 2100 32 35 20220813 09:00 A6D TF-203 ~ 750 123 9 20220814 13:00 Pléiades PHR1B n/a 2 14 20220815 08:15 A6D TF-203 2100 20 23 20220816 10:06 A6D TF-203 2100 19 26 20220926 12:00 A6D TF-BMW** 2100 ~20 18 * TF-203: Savannah S aircraft ** TF-BMW: Vulcanair P68 Observer 2 aircraft, operated by Garðaflug ehf. <strong>4- Methods</strong> <strong>4.1 Processing of the aerial photographs from 3-16 Aug 2022</strong><br> Throughout the eruption, aerial surveys were conducted using a Hasselblad A6D 100 MP camera with 35 mm focal lens, from a height of 750 – 2,100 m above ground over the active lava field from an ultralight aircraft with a window in the bottom to allow for vertical photos to be taken (see supplement of Pedersen et al., 2022a for details and images of the setup). The camera was manually triggered to give ~70% overlap, and approximate flight lines were prepared beforehand for use with a handheld GPS during the flight to give ~30 % side overlap.<br> <br> An automated processing pipeline was created in python, which leverages tools from the Ames Stereo Pipeline (ASP, Shean et al., 2016) and Agisoft Metashape stand-alone Python API (v. 1.8.4). The processing and georeferencing of the aerial data were done in three steps, with all steps being automated except for the digitization of lava outlines. First, using a very high-resolution reference orthomosaic and DEM created in September 2021 and georeferenced with ground control points (Pedersen et al., 2022b), interest points (IPs) in each image were matched with the reference dataset, using the ASP routine <em>ipfind. </em>This created GCPs for each image over stable terrain. Second, hillshades were created from both the reference DEM and the source dataset DEM and matches in IPs were found in both, creating a second round of ground control points to refine the georeferencing of the entire block. Finally, the alignment of the source DEM was refined using the <em>dem_align</em> (demcoreg) protocol from Shean et al. (2016) by applying a bulk linear shift in X, Y and Z which minimizes the vertical difference in stable terrain between the source and reference DEM. <strong>4.2 Processing of the Pléiades stereo images</strong><br> The Pléiades stereo images were processed using the Ames Stereo Pipeline, using the general workflow of <em>mapproject </em>and <em>parallel_stereo </em>(e.g., Deschamps-Berger et al., 2020). The <em>parallel_stereo </em>routine used default arguments, plus the following arguments: <em>--stereo-algorithm asp_mgm -t rpcmaprpc --corr-seed-mode 3 --corr-max-levels 2 --cost-mode 3 --subpixel-mode 9 --corr-kernel 7 7 --subpixel-kernel 15 15</em> We used the DEM from 4 Aug 2022 as the reference for <em>mapproject </em>and for the final DEM co-registration applied to the produced Pléiades DEM. <strong>4.3 Processing of the 26 September 2022 dataset</strong><br> The survey from 26 September 2022 was collected and processed using direct georeferencing from an on-board GPS antenna. The final alignment of the block was refined using the dem_align (demcoreg) protocol from Shean et al. (2016) by applying a bulk linear shift in X, Y and Z which minimizes the vertical difference in stable terrain between the source and reference DEM. Because this survey covered a much larger area, the reference DEM for the final coregistration was the ÃslandsDEM v.1.0 (Landmælingar Ãslands, 2022). <strong>4.4. Maps of the lava outlines, lava thickness, lava volume, Time Average Effusion Rate (TADR)</strong><br> For each survey, a differential DEM (dDEM) showing elevation changes since the 2021 eruption was created by subtracting the reference DEM (ÃslandsDEM v.1.0, which includes the post-eruption DEM from Pedersen et al., 2022a) from the source DEM. Lava outlines, lava thickness lava volume, TADR and uncertainties were calculated using the methods described in Pedersen et al., 2022a. Table 2 summarizes calculations from this dataset. Table 2. Summary of survey results calculated from August 2022 Fagradalsfjall eruption DEMs and orthomosaics. <strong> Date Start</strong> <strong>Date End</strong> <strong>Time </strong> <strong>Difference</strong> <strong>Lava </strong> <strong>Area<sup>*</sup> End </strong> <strong>(km<sup>2</sup>)</strong> <strong>dh<sup>**</sup> </strong> <strong>(m)</strong> <strong>Volume<sup>+</sup></strong> <strong>End<br> (1e+6 m<sup>3</sup>)</strong> <strong>TADR<sup>++</sup><br> (m<sup>3</sup>/s)</strong> 20220803<br> 13:20 20220803<br> 17:05 0d 03h 45m 0.07 5.88 0.43 ± 0.03 32.1 ± 1.5 20220803<br> 17:05 20220804<br> 11:00 0d 21h 40m 0.14 11.13 1.57 ± 0.05 17.7 ± 0.8 20220804<br> 11:00 20220813<br> 09:00 8d 22h 00m 1.27<sup>#</sup> 6.90 10.33 ± 0.6 11.4 ± 0.7 20220813<br> 13:08 20220814<br> 13:00 0d 23h 52m 1.24 7.28 10.62 ± 0.70 2.8 ± 0.8 20220814<br> 13:00 20220815<br> 08:15 0d 19h 15m 1.26 7.46 10.99 ± 0.55 4.1 ± 0.8 20220815<br> 08:15 20220816<br> 10:16 1d 2h 01m 1.28 7.49 11.13 ± 0.53 2.0 ± 0.7 20220816<br> 10:16 20220821<br> 06:00<sup>##</sup> 4d 19h 44m 1.28 7.69 11.39 ± 0.44 0.653 ± 0.10 <sup>*</sup>Total area of the lava field since 2022-08-03 before activity started. <sup>**</sup>dh end is the mean thickness of the lava flow-field in the end of the given period. <sup>+</sup>Volume erupted since 2022-08-03 before activity started. <sup>++</sup>Time-averaged discharge rate for the given period <sup>#</sup>Extrapolated value. Survey does not cover entire active lava area. <sup>##</sup>End Time: 21 August 2022, 6:00. This time deduced from field observations from members of the Institute of Earth Sciences, University of Iceland. Values calculated from 26 September 2022 dataset. Figures and visual summaries of the processing method, resulting lava volumes, and uncertainties can be found in this poster: Fagradalsfjall August 2022.<br> <br> Orthomosaics from this dataset are viewable online at: https://atlas.lmi.is/mapview/?application=umbrotasja <strong>Data naming conventions:</strong> Data type: DEM, ortho, outline, diffDEM, lavafree, lava Acquisition date: YYYYMMDD_HHMM Platform/Sensor for data collection: Pléiades (PLE), Hasselblad A6D from aircraft (A6D) Resolution: 2x2 m (DEMs) and 30x30 cm (Orthomosaics) Folders (by survey): YYYYMMDD_HHMM_platform (during eruption) or 'posteruption'_platform (sensors/platform: A6D or PLE) <strong>Data Specifications:</strong> Cartographic projection: ISN93 / Lambert 1993 (EPSG:3057, https://epsg.io/3057) Origin of Elevation: meters above GRS80 ellipsoid (WGS84) Raster data format: GeoTIFF Raster compression system: ZSTD (http://facebook.github.io/zstd/) Vector data format: GeoPackage (https://www.geopackage.org/) Pléiades dataset includes only DEMs because the Pléiades ortho imagery is for licensed use only. Please contact the authors for further information on this.",mds,True,findable,0,0,0,0,0,2023-04-27T15:11:57.000Z,2023-04-27T15:11:57.000Z,cern.zenodo,cern,"Photogrammetry,Iceland,Remote Sensing,Volcano Monitoring,DEM,Orthomosaic,Pléiades","[{'subject': 'Photogrammetry'}, {'subject': 'Iceland'}, {'subject': 'Remote Sensing'}, {'subject': 'Volcano Monitoring'}, {'subject': 'DEM'}, {'subject': 'Orthomosaic'}, {'subject': 'Pléiades'}]",,
+10.5281/zenodo.5835975,FIGURE 1 in Bulbophyllum section Rhytionanthos (Orchidaceae) in Vietnam with description of new taxa and new national record,Zenodo,2022,,Image,Open Access,"FIGURE 1. Bulbophyllum nodosum (Rolfe) J.J.Sm. A. Flowering plant; B. Leaf apex, adaxial and abaxial side. C. Inflorescences. D. Inflorescence rachis. E. Floral bract. F. Flowers, side and back views. G. Pedicel, ovary and flower, side view. H. Median sepal, adaxial and abaxial side. I. Median sepal margin. J. Lateral sepals, adaxial and abaxial side. K. Lateral sepal margin. L. Petal, adaxial and abaxial side. M. Lip, views from different sides. N. Pedicel, ovary and column with sepals removed (above), and with all tepals removed (below). O. Surface of ovary and column foot base. P. Column, petals and lip, view from above. Q. Column, frontal and side views. R. Anther cap, views from different sides. S. Pollinia. Photos by Truong Ba Vuong, correction and design by L. Averyanov and T. Maisak.",mds,True,findable,0,0,2,0,0,2022-01-11T09:00:28.000Z,2022-01-11T09:00:30.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Bulbophyllum","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Bulbophyllum'}]",,
+10.5281/zenodo.4746349,"Raw data for ""X-ray studies bridge the molecular and macro length scales during the emergence of CoO assemblies""",Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Raw data for „X-ray studies bridge the molecular and macro length scales during the emergence of CoO assemblies“</strong> <strong>TEM and SEM</strong> SEM image of CoO assemblies after 90 min TEM images of CoO assemblies after 5, 10, 15, 20, 40, 60 and 90 min HR-TEM images of CoO assemblies after 90 min ED patterns of CoO assemblies after 10, 15 and 20 min <strong>HERFD-XANES</strong> In situ spectra for the CoO synthesis at 160°C were recorded at beamline ID26 at the European Synchrotron Radiation Facility (ESRF), Grenoble, France. Using a Si (111) double crystal monochromator, the incident energy was varied from 7.70 to 7.78 keV. The emitted fluorescence was measured with an emission spectrometer in Rowland geometry with five Si (531) analyzer crystals aligned at the Bragg angle of 77°. HERFD-XANES spectra were recorded in continuous scan mode every 80 s with average energy steps of 0.05 eV. The data set consists of one file containing a sequential set of energy scans, representing the pre- and main edge regions of the HERFD-XANES spectra. Important column identifiers: incident energy: “arr_hdh_ene†incident intensity: “I02†fluorescence intensity: “apd†<strong>X-ray total scattering</strong> Data was taken at beamline P21.1 of PETRA III at Deutsches Elektronen-Synchrotron (DESY), Hamburg, Germany. Diffraction patterns were recorded every 10 s at an X-ray energy of 102.92 keV (λ = 0.121 Ã…) with an XRD1621 detector (Perkin Elmer Inc., USA) with a pixel size of 200 × 200 μm² and a sample-to-detector distance of 0.411 m. The dataset consist of in situ data set of CoO nanoassembly synthesis at 160°C in situ data set of CoO nanoassembly synthesis at 140°C ex situ samples prepared at 160 °C at different times commercial reference compounds in powder and 0.1 M BnOH solution data format: 2D scattering patterns in .tif format The total scattering data is split into individual archives for the above subsets. <strong>SAXS and PXRD</strong> <strong>data set “laboratory_SAXS_dataâ€:</strong> Data were recorded with the laboratory molybdenum anode microfocus X-ray setup at LMU, Munich. SAXS data are multiple successive 20 min exposures. Transmission data are 10 s exposures with the beamstop removed. data format: .tif detector images recorded with a Dectris Pilatus 300K.<br> <em>X-ray wavelength:</em> 0.71075 Angstrom<br> Calibrant for sample-to-detector distance, beam center and detector tilt: Silver behenate (AgBeh) <strong>data set “synchrotron_SAXS_dataâ€:</strong> Data were recorded at beamline P03 at PETRA III, DESY, Hamburg. Data are recorded separately at a long and a short sample-to-detector distance. At the long distance, the exposure time is 5x0.1s. At the short distance, the exposure time is 1x0.5s. data format: .cbf detector images recorded with a Dectris Pilatus 1M.<br> X-ray wavelength: 0.961 Angstrom<br> Calibrant for sample-to-detector distance, beam center and detector tilt: Silver behenate (AgBeh) <strong>data set “laboratory_PXRD_dataâ€:</strong> Data were recorded with the laboratory molybdenum anode microfocus X-ray setup at LMU, Munich. The overlap for stitching is 10 px in both horizontal and vertical direction. The recording sequence is<br> 01 02 07<br> 03 04 08<br> 05 06 09<br> 10 11 12<br> 13 14 15<br> with 3 images at each position, to take the median. The exposure time per image is 1200 s. For LaB6 the sequence is<br> 01 02<br> 03 04<br> 05 06<br> 07 08<br> 09 10<br> with 5 images at each position, to take the median. The exposure time per image is 300 s. data format: .tif detector images recorded with a Dectris Pilatus 100K.<br> X-ray wavelength: 0.71 Angstrom<br> Calibrant for sample-to-detector distance, beam center and detector tilt: Lanthanum hexaboride NIST SRM 660c (LaB6)",mds,True,findable,0,0,0,1,0,2021-07-20T11:04:53.000Z,2021-07-20T11:04:54.000Z,cern.zenodo,cern,"non-classical crystallization,nanoassemblies,nanoparticles,cobalt(II) oxide,HERFD-XANES,total scattering,PDF,SAXS,ESRF,ID26,BM14,PETRA III,P21.1,P03","[{'subject': 'non-classical crystallization'}, {'subject': 'nanoassemblies'}, {'subject': 'nanoparticles'}, {'subject': 'cobalt(II) oxide'}, {'subject': 'HERFD-XANES'}, {'subject': 'total scattering'}, {'subject': 'PDF'}, {'subject': 'SAXS'}, {'subject': 'ESRF'}, {'subject': 'ID26'}, {'subject': 'BM14'}, {'subject': 'PETRA III'}, {'subject': 'P21.1'}, {'subject': 'P03'}]",,
+10.5281/zenodo.10005440,"Data for the paper: ""Simulating a Multi-Layered Grid Middleware""",Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"Associated paper: https://hal.science/hal-04101015
+Repo here",api,True,findable,0,0,0,0,0,2023-10-15T22:47:25.000Z,2023-10-15T22:47:25.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4964211,"FIGURES 21–24 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 21–24. Protonemura bispina sp. n., 21. female, subgenital plate and vaginal lobes, lateral view. 22. female, subgenital plate and vaginal lobes, ventral view. 23. Protonemura pennina sp. n., male, epiproct, lateral view. 24. male, epiproct, lateral view",mds,True,findable,0,0,5,0,0,2021-06-16T08:25:13.000Z,2021-06-16T08:25:14.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.4575211,3D Teeth Scan Segmentation and Labelling Challenge,Zenodo,2021,,Other,"Creative Commons Attribution No Derivatives 4.0 International,Open Access","Computer-aided design (CAD) tools have become increasingly popular in modern dentistry for highly accurate treatment planning. In particular, in orthodontic CAD systems, advanced intraoral scanners (IOSs) are now widely used as they provide precise digital surface models of the dentition. Such models can dramatically help dentists simulate teeth extraction, move, deletion, and rearrangement and ease therefore the prediction of treatment outcomes. Hence, digital teeth models have the potential to release dentists from otherwise tedious and time consuming tasks. Although IOSs are becoming widespread in clinical dental practice, there are only few contributions on teeth segmentation/labelling available in the literature [1,2,3] and no publicly available database. A fundamental issue that appears with IOS data is the ability to reliably segment and identify teeth in scanned observations. Teeth segmentation and labelling is difficult as a result of the inherent similarities between teeth shapes as well as their ambiguous positions on jaws. In addition, it faces several challenges:<br> 1- The teeth position and shape variation across subjects.<br> 2- The presence of abnormalities in dentition. For example, teeth crowding which results in teeth misalignment<br> and thus non-explicit boundaries between neighboring teeth. Moreover, lacking teeth and holes are commonly<br> seen among people.<br> 3- Damaged teeth.<br> 4- The presence of braces, and other dental equipment. The challenge we propose will particularly focus on point 1, i.e. the teeth position and shape variation across subjects. With the extension of available data in the mid and long term, the other points will also be addressed in further editions of the challenge. [1] Lian, Chunfeng, et al. ""MeshSNet: Deep multi-scale mesh feature learning for end-to-end tooth labeling on 3D dental surfaces."" International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2019.<br> [2] Xu, Xiaojie, Chang Liu, and Youyi Zheng. ""3D tooth segmentation and labeling using deep convolutional neural networks."" IEEE transactions on visualization and computer graphics 25.7 (2018): 2336-2348.<br> [3] Sun, Diya, et al. ""Automatic Tooth Segmentation and Dense Correspondence of 3D Dental Model."" International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2020.",mds,True,findable,0,0,0,0,0,2021-03-03T08:48:15.000Z,2021-03-03T08:48:17.000Z,cern.zenodo,cern,"3D Teeth segmentation,3D segmentation,3D object detection,3D intraoral scans,dentistry","[{'subject': '3D Teeth segmentation'}, {'subject': '3D segmentation'}, {'subject': '3D object detection'}, {'subject': '3D intraoral scans'}, {'subject': 'dentistry'}]",,
+10.5061/dryad.8290n,Data from: pcadapt: an R package to perform genome scans for selection based on principal component analysis,Dryad,2016,en,Dataset,Creative Commons Zero v1.0 Universal,"The R package pcadapt performs genome scans to detect genes under selection based on population genomic data. It assumes that candidate markers are outliers with respect to how they are related to population structure. Because population structure is ascertained with principal component analysis, the package is fast and works with large-scale data. It can handle missing data and pooled sequencing data. By contrast to population-based approaches, the package handle admixed individuals and does not require grouping individuals into populations. Since its first release, pcadapt has evolved in terms of both statistical approach and software implementation. We present results obtained with robust Mahalanobis distance, which is a new statistic for genome scans available in the 2.0 and later versions of the package. When hierarchical population structure occurs, Mahalanobis distance is more powerful than the communality statistic that was implemented in the first version of the package. Using simulated data, we compare pcadapt to other computer programs for genome scans (BayeScan, hapflk, OutFLANK, sNMF). We find that the proportion of false discoveries is around a nominal false discovery rate set at 10% with the exception of BayeScan that generates 40% of false discoveries. We also find that the power of BayeScan is severely impacted by the presence of admixed individuals whereas pcadapt is not impacted. Last, we find that pcadapt and hapflk are the most powerful in scenarios of population divergence and range expansion. Because pcadapt handles next-generation sequencing data, it is a valuable tool for data analysis in molecular ecology.",mds,True,findable,422,48,1,1,0,2016-08-11T17:32:14.000Z,2016-08-11T17:32:16.000Z,dryad.dryad,dryad,Bioinfomatics/Phyloinfomatics,[{'subject': 'Bioinfomatics/Phyloinfomatics'}],['14535625 bytes'],
+10.5281/zenodo.10049814,"Data and code for the article "" Dissimilarity of vertebrate trophic interactions reveals spatial uniqueness but functional redundancy across Europe""",Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Research compendium to reproduce analyses and figures of the article: Dissimilarity of vertebrate trophic interactions reveals spatial uniqueness but functional redundancy across Europe by Gaüzère et al. published in Current Biology
+Pierre Gaüzère
+General
+This repository is structured as follow:
+
+data/: contains data required to reproduce figures and tables
+analyses/: contains scripts organized sequentially. A -> B -> C -> ..
+outputs/: follows the structure of analyses. Contains intermediate numeric results used to produce the figures
+figures_tables/: Contains the figures of the paper
+The analysis pipeline should be clear once opening the code. Contact me if needed but try before please.Â
+Figures & tables
+Figures will be stored in figures_tables/. Tables will be stored in outputs/.",api,True,findable,0,0,0,0,0,2023-10-30T13:59:09.000Z,2023-10-30T13:59:09.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10014633,Mining tortured acronyms from the scientific literature,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,,api,True,findable,0,0,0,0,0,2023-10-17T19:30:51.000Z,2023-10-17T19:30:51.000Z,cern.zenodo,cern,,,,
+10.57745/7hf7kg,Qualify a near-infrared camera to detect thermal deviation during aluminum alloy Wire Arc Additive Manufacturing,Recherche Data Gouv,2022,,Dataset,,"Data presented here are the part of the study: Dellarre A, Béraud N, Villeneuve F, Tardif N, Vignat F, Limousin M : Qualify a near-infrared camera to detect thermal deviation during aluminum Wire Arc Additive Manufacturing process Date : November 2022 e-mail : anthony.dellarre@grenoble-inp.fr Please use appropriate citations and referencing while using this dataset by any means. Contributing authors: Anthony Dellarre, Nicolas Béraud, François Villeneuve, Nicolas Tardif, Frédéric Vignat, Maxime Limousin Any further information could be asked by making a legitimate request to: Anthony Dellarre (anthony.dellarre@grenobe-inp.fr) and Nicolas Béraud (nicolas.beraud@grenoble-inp.fr) The folder archetecture is : - Wall referenced by its idle time * Row data : + video of near frame (.mp4) + near_camera (*.bmp) + scan (scan.stl) * Process data : + width of the wall function of the x coordinate and layer number (width.csv) + height of the wall function of the x coordinate and layer number (height.csv) + the thermal metric (surface of the thermal processed area) in function of the layer (thermalMetric.csv) Please refer to the paper for any further scientific details.",mds,True,findable,79,3,0,1,0,2022-12-08T07:59:49.000Z,2022-12-16T19:58:06.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.4888804,"Code repository for 'Jarzynski equality and Crooks relation for local models of air-sea interaction', a ESD paper",Zenodo,2021,,Software,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the publicly-redistributable code used in the production of ``Jarzynski equality and Crooks relation for local models of air-sea interaction'' a paper by A. Wirth, and F. Lemarié published in Earth System Dynamics. The fortran code corresponds to the 1D2C model described in section 2.1 of the paper",mds,True,findable,0,0,0,0,0,2021-06-01T07:07:15.000Z,2021-06-01T07:07:16.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.c.6690029,3DVizSNP: a tool for rapidly visualizing missense mutations identified in high throughput experiments in iCn3D,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background High throughput experiments in cancer and other areas of genomic research identify large numbers of sequence variants that need to be evaluated for phenotypic impact. While many tools exist to score the likely impact of single nucleotide polymorphisms (SNPs) based on sequence alone, the three-dimensional structural environment is essential for understanding the biological impact of a nonsynonymous mutation. Results We present a program, 3DVizSNP, that enables the rapid visualization of nonsynonymous missense mutations extracted from a variant caller format file using the web-based iCn3D visualization platform. The program, written in Python, leverages REST APIs and can be run locally without installing any other software or databases, or from a webserver hosted by the National Cancer Institute. It automatically selects the appropriate experimental structure from the Protein Data Bank, if available, or the predicted structure from the AlphaFold database, enabling users to rapidly screen SNPs based on their local structural environment. 3DVizSNP leverages iCn3D annotations and its structural analysis functions to assess changes in structural contacts associated with mutations. Conclusions This tool enables researchers to efficiently make use of 3D structural information to prioritize mutations for further computational and experimental impact assessment. The program is available as a webserver at https://analysistools.cancer.gov/3dvizsnp or as a standalone python program at https://github.com/CBIIT-CGBB/3DVizSNP .",mds,True,findable,0,0,0,0,0,2023-06-10T03:21:53.000Z,2023-06-10T03:21:53.000Z,figshare.ars,otjm,"Space Science,Medicine,Genetics,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,80699 Information Systems not elsewhere classified,FOS: Computer and information sciences,Cancer,Plant Biology","[{'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '80699 Information Systems not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Computer and information sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",,
+10.5281/zenodo.4133866,SG_modelComparison,Zenodo,2020,,Software,"Creative Commons Attribution 4.0 International,Open Access","Jupyter notebooks to allow prediction of the solubility gap (SG) of CoxMn3-xO4 from two different methods for the configurational entropy: moment tensor potentials (MTP) and an extended mean field model (EMF) Alternatively, clone the git repository: https://github.com/nataliomingo/SG_modelComparison",mds,True,findable,0,0,0,0,0,2020-10-26T11:16:04.000Z,2020-10-26T11:16:06.000Z,cern.zenodo,cern,"solubility gap, machine learning, entropy, thermodynamics","[{'subject': 'solubility gap, machine learning, entropy, thermodynamics'}]",,
+10.5281/zenodo.6074472,Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809ma.s.l.) to encourage adaptation by mountaineers,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The file Mourey et al._NHESS_2021_128.xlsx gathers the data used in the article ""Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809ma.s.l.) to encourage adaptation by mountaineers"" at an hourly time scale.",mds,True,findable,0,0,0,1,0,2022-02-14T09:18:54.000Z,2022-02-14T09:18:55.000Z,cern.zenodo,cern,"Mountaineering,Monitoring,Adaptation,Climate change,High mountain","[{'subject': 'Mountaineering'}, {'subject': 'Monitoring'}, {'subject': 'Adaptation'}, {'subject': 'Climate change'}, {'subject': 'High mountain'}]",,
+10.5281/zenodo.8398772,Disentangling the drivers of future Antarctic ice loss with a historically-calibrated ice-sheet model,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"=========================================================================Disentangling the drivers of future Antarctic ice loss with a historically-calibrated ice-sheet model=========================================================================
+-----------------------INTRODUCTION-----------------------
+This dataset contains the data and scripts required to reproduce the figures and tables presented in the study:""Disentangling the drivers of future Antarctic ice loss with a historically-calibrated ice-sheet model"" in The Cryosphere.
+We perform an ensemble of simulations of the Antarctic ice sheet between 1950 and 3014, forced by a panel of CMIP6 climate models, starting from present-day geometry with the Kori-ULB ice-sheet model v0.9. We calibrate our ensemble in a Bayesian framework to produce observationally-calibrated Antarctic projections used to investigate the future trajectory of the Antarctic ice sheet related to uncertainties in the future balance between sub-shelf melting and ice discharge on the one hand, and the surface mass balance on the other. All simulations are performed at a spatial resolution of 16 km.
+Hindcasts of the behaviour of the AIS over the period 1950-2014 CE are reproduced using changes in oceanic and atmospheric boundary conditions derived from the CMIP5 climate model NorESM1-M. As of the year 2015 CE, climate projections derived from a subset of CMIP6 climate models (MRI-ESM2-0, IPSL-CM6A-LR, CESM2-WACCM and UKESM1-0-LL) are used as forcing until the year 2300 CE. Afterwards, no climate trend is applied. The forcing applied is derived from both the Shared Socioeconomic Pathways (SSP) 5-8.5 and 1-2.6 scenarios.Â
+------------------------------PROVIDED SCRIPTS:Â ------------------------------
+ - 'KoriModelAll.m' and 'KoriInputParams.m': Kori-ULB ice flow model (more info at https://github.com/FrankPat/Kori-ULB) - 'Compute_Bayesian_Weight.m': calculation of the ensemble likelihood weights used in the Bayesian calibration. - 'Plot_parameter_space_distributions.m': calculation and plots of prior and posterior parameter  probability distributions. - 'Plot_sea_level_distributions.m': calculation and plots of prior and posterior sea-level distributions. - 'Plot_mass_balance_components_distributions.m': calculation and plots of mass balance components distributions. - 'Plot_mean_thickness_change.m': calculation and plots of calibrated mean thickness change. - 'Plot_ungrounded_probability.m': calculation and plots of the marginal probability of being ungrounded. - 'Plot_SMB_sensitivity.m': Calculation and plots of surface mass balance sensitivity. - 'run_MISMIPplus.m' and 'MISMIPplus.m': run and compare MISMIP+ experiment
+-------------------------PROVIDED DATA:Â -------------------------
+
+'LHSensemble.mat': 100x9 matrices containing the values of the 100-member ensemble sampled (using maximin Latin Hypercube) within the parameter space in Table 1.
+
+1rst column ((:,1)) contains values of atmospheric present-day climatology (CLIMatm): MARv3.11 (1) - RACMOv2.3p2 (2)
+2nd column ((:,2)) contains values of oceanic present-day climatology (CLIMocn): Jourdain2020 (1) - Schmidtko2014 (2)
+3rd column ((:,3)) contains values of the atmospheric lapse rate (°C/km)
+4th column ((:,4)) contains values of the thickness of the thermally-active layer influencing surface refreezing (m)
+5th column ((:,5)) contains values of the contains values of the Degree day factor for the melting of ice (mm/PDD)
+6th column ((:,6)) contains values of the contains values of the Degree day factor for the melting of snow (mm/PDD)
+7th column ((:,7)) contains values of the applied Sub-shelf melt parameterisation: Quadratic-local Antarctic slope parameterisation (1) - PICO model (2) - Plume model (3) - ISMIP6 Nonlocal quadratic parameterisation (4) - ISMIP6 Nonlocal quadratic parameterisation including dependency on local slope (5)
+8th column ((:,8)) contains values of the effective ice-ocean heat flux: [0.1 x 10^-5 - 10 x 10^-5] m/s for gammaT* in PICO - [1 x 10^-4 - 10 x 10^-4] for Cd^1/2Gamma_TS in Plume - Â [1 x 10^-4 - 10 x 10^-4] for K in Quadratic-local Antarctic slope parameterisation - [1 x 10^4 - 4 x 10^4] m/yr for gamma0 in ISMIP6 Nonlocal quadratic parameterisation - [1 x 10^6 - 4 x 10^6] m/yr for gamma0 in ISMIP6 Nonlocal quadratic parameterisation with slope dependency
+9th column ((:,9)) contains values of the CMIP6 climate model applied for climate forcing: MRI-ESM2-0 (1) - UKESM1-0-LL (2) - CESM2-WACCM (3) - IPSL-CM6A-LR (4)'LHval' and 'LHS' contain the absolute values and the values of the parameters scaled linearly between 0 and 1 (0: minimum value, 1:maximum value) of the nine parameters, respectively.Â
+'HIST_ENSEMBLE_DATA.mat' contains the following variables describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014).
+
+H_ensemble: 4D matrix of dimension [X, Y, snap_time, ensemble member] with ice thickness field (in meters) for the 100 ensemble members at different years (snap_time). X and Y represent spatial coordinates on a grid.
+MASK_ensemble: 4D matrix of dimension [X, Y, snap_time, ensemble member] with grounded mask field (in meters) for the 100 ensemble members at different years (snap_time). X and Y represent spatial coordinates on a grid. It distinguishes grounded ice (1: grounded) from ocean or floating ice (0: ocean/floating).
+mbcomp_ensemble: 3D matrix of dimension [time, mbcomp, ensemble member] with timeseries (yearly values at years time) of various mass balance components for the 100 ensemble members (in gigatons per year, Gt/yr). The components mbcomp include the following ice-sheet aggregated and grounded ice sheet components:          (1) Ice-sheet aggregated surface mass balance          (2) Ice-sheet aggregated accumulation          (3) Ice-sheet aggregated surface melt          (4) Ice-sheet aggregated runoff          (5) Ice-sheet aggregated rain          (6) sub-shelf melt          (7) dynamic ice loss (calving)          (8) surface mass balance over the grounded ice sheet          (9) accumulation over the grounded ice sheet          (10) surface melt over the grounded ice sheet          (11) runoff over the grounded ice sheet          (12) rain over the grounded ice sheet                 (13) Net mass balance (rate of HAF change)
+SLC_ensemble: 2D matrix of dimension [ensemble member, time] with timeseries (yearly values at years time) of the ice-sheet sea-level contribution (in m)Â Â
+'HIST_ENSEMBLE_DATA_NO_ELEVATION_FEEDBACK.mat': same as 'HIST_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) when neglecting the melt-elevation feedback.Â
+'HIST_ENSEMBLE_DATA_HYDROFRAC.mat': same as 'HIST_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) when including surface melt-driven hydrofracturing of the ice shelves (estimated following Pollard et al., 2015).Â
+'CONTROL_ENSEMBLE_DATA.mat': contains the variables H_ensemble, MASK_ensemble, mbcomp_ensemble and SLC_ensemble (as in 'HIST_ENSEMBLE_DATA') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 when considering constant present-day conditions as of the year 2015.Â
+'SSP126_ENSEMBLE_DATA.mat': contains the variables H_ensemble, MASK_ensemble, mbcomp_ensemble and SLC_ensemble (as in 'HIST_ENSEMBLE_DATA') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP1-2.6 scenario.Â
+'SSP585_ENSEMBLE_DATA.mat': contains the variables H_ensemble, MASK_ensemble, mbcomp_ensemble and SLC_ensemble (as in 'HIST_ENSEMBLE_DATA') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP5-8.5 scenario. It also contains the variable Runoff_ensemble, a 4D matrix of dimension [X, Y, snap_time, ensemble member] with surface runoff field (in m/yr i.e.) for the 100 ensemble members at different years (snap_time). X and Y represent spatial coordinates on a grid, as used in Fig. 7.Â
+'SSP585_ENSEMBLE_DATA_NO_ELEVATION_FEEDBACK.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when neglecting the melt-elevation feedback.Â
+'SSP585_ENSEMBLE_DATA_HYDROFRAC.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when including surface melt-driven hydrofracturing of the ice shelves (estimated following Pollard et al., 2015).Â
+'SSP585_ENSEMBLE_DATA_ATM_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when considering constant oceanic present-day conditions as of the year 2015.Â
+'SSP585_ENSEMBLE_DATA_NO_ELEVATION_FEEDBACK_ATM_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when neglecting the melt-elevation feedback and considering constant oceanic present-day conditions as of the year 2015.Â
+'SSP585_ENSEMBLE_DATA_OCEAN_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario considering constant atmospheric present-day conditions as of the year 2015.Â
+'HIST_ENSEMBLE_DATA_BASIN.mat' contains the following variables describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) integrated over 27 drainage basins (http://imbie.org/imbie-2016/drainage-basins/).
+
+SLC_ensemble_basin: 3D matrix of dimension [basin, ensemble member, time] with timeseries (yearly values at years time) of the ice-sheet sea-level contribution (in m) by basin
+mbcomp_ensemble_basin: 4D matrix of dimension [basin, time, mbcomp, ensemble member] with timeseries (yearly values at years time) of various mass balance components for the 100 ensemble members (in gigatons per year, Gt/yr) by basin. The components mbcomp include the same ice-sheet aggregated and grounded ice-sheet components as in 'HIST_ENSEMBLE_DATA.mat'.Â
+'HIST_ENSEMBLE_DATA_BASIN_NO_ELEVATION_DATA.mat': same as 'HIST_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) when neglecting the melt-elevation feedback.Â
+'HIST_ENSEMBLE_DATA_BASIN_HYDROFRAC.mat': same as 'HIST_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) when including surface melt-driven hydrofracturing of the ice shelves (estimated following Pollard et al., 2015).Â
+'SSP126_ENSEMBLE_DATA_BASIN.mat': contains the variables SLC_ensemble_basin and mbcomp_ensemble_basin (as in 'HIST_ENSEMBLE_DATA°BASIN') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP1-2.6 scenario.Â
+'SSP585_ENSEMBLE_DATA_BASIN.mat': contains the variables SLC_ensemble_basin and mbcomp_ensemble_basin (as in 'HIST_ENSEMBLE_DATA') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP5-8.5 scenario.Â
+'SSP585_ENSEMBLE_DATA_BASIN_NO_ELEVATION_FEEDBACK.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP5-8.5 scenario when neglecting the melt-elevation feedback.Â
+'SSP585_ENSEMBLE_DATA_BASIN_HYDROFRAC.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when including surface melt-driven hydrofracturing of the ice shelves (estimated following Pollard et al., 2015).Â
+'SSP585_ENSEMBLE_DATA_BASIN_ATM_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when considering constant oceanic present-day conditions as of the year 2015.Â
+'SSP585_ENSEMBLE_DATA_BASIN_NO_ELEVATION_FEEDBACK_ATM_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when neglecting the melt-elevation feedback and considering constant oceanic present-day conditions as of the year 2015.Â
+'SSP585_ENSEMBLE_DATA_BASIN_OCEAN_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario considering constant atmospheric present-day conditions as of the year 2015.Â
+'GCM_SSPXXX_mean_aTs.mat': Timeseries of the regionally-averaged (between 90–60°S) annual near-surface (2-m) air temperature anomaly (°C) projected by the climate model 'GCM' from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) between 2015 and 2300 under the SSPXXX emission scenario, compared to the 1995-2014 reference period. SSPXXX may be 'SSP126' and 'SSP585' and GCM may be 'MRI-ESM2-0', 'CESM2-WACCM', 'IPSL-CM6A-LR', or 'UKESM1-0-LL'.Â
+'CALIBRATION DATA.mat': values ('val'), uncertainty ('sigma'), beginning ('year1') and end ('year2') of the average time period of the 12 regionally and temporally aggregated IMBIE data used in the Bayesian calibration (Table 2 in this study, coming from Table 2 from Otosaka et al., 2023)Â
+'INIT_MAR_aNorESM1-M_1950.mat' and 'INIT_RACMO_aNorESM1-M_1950.mat': Ice-sheet initial states at year 1950 obtained with the 1995-2014 atmospheric climatology from MARv3.11(Kittel eta l.,2021) or RACMOv2.3p2 (van Wessem et al., 2018), respectively, adjusted with a 1945-1955 anomaly from NorESM1-M. H is the ice thickness (in meters), B is the bedrock topography (in meters), and u is the surface velocity (in m/yr). These files were provided as input files to Kori-ULB to produce the projections. More info on the input files and their variables can be found here: https://github.com/FrankPat/Kori-ULB.
+----------------------------------------------------------MATLAB FUNCTIONS USED IN SCRIPTS:Â ----------------------------------------------------------
+- imagescn: imagesc with transparent NaNs, by Chad Greene (2023), downloaded from MATLAB Central File Exchange (https://www.mathworks.com/matlabcentral/fileexchange/61293-imagescn), - brewermap: provides all ColorBrewer colorschemes for MATLAB, by Stephen23. Downloaded from https://github.com/DrosteEffect/BrewerMap.- crameri: returns perceptually-uniform scientific colormaps created by Fabio Crameri (requires CrameriColourMaps8.0.mat)
+----------------------------------------------------------------------------------EXTERNAL DATA NOT CONTAINED IN THIS REPOSITORY:----------------------------------------------------------------------------------
+- BedMachine data used for the present-day grounding lines in Figures 2 and 7: It is BedMachine v2 (Morlighem et al., 2020) and can be found here: https://nsidc.org/data/nsidc-0756/versions/2.- The delineation of the 27 Zwally Basins used to identify and separate the West and East Antarctic ice sheets and the Antarctic Peninsula can be found at http://imbie.org/imbie-2016/drainage-basins/- Outputs from MAR(CNRM-CM6-1) and MAR(CESM2) used in Figures 7 and S10. The data can be downloaded at 10.5281/zenodo.4529004 and 10.5281/zenodo.4529002, respectively. It was then interpolated to the 16-km grid used by Kori-ULB.- CESM2-WACCM outputs used in Figure 7 were downloaded from the CMIP6 search interface (https://esgf-node.llnl.gov/search/cmip6/) and interpolated to the 16-km grid used by Kori-ULB.- The CMIP6 forcing data used in this study (and plotted in Figures S6 and S7) are accessible through the CMIP6 search interface (https://esgf-node.llnl.gov/search/cmip6/). They have been interpolated to the interpolated to the 16-km grid used by Kori-ULB.
+---------------------REFERENCES:Â ---------------------
+Kittel, C., Amory, C., Agosta, C., Jourdain, N. C., Hofer, S., Delhasse, A., Doutreloup, S., Huot, P.-V., Lang, C., Fichefet, T., and Fettweis, X.: Diverging future surface mass balance between the Antarctic ice shelves and grounded ice sheet, The Cryosphere, 15, 1215–1236, https://doi.org/10.5194/tc-15-1215-2021, 2021.
+Morlighem, M., Rignot, E., Binder, T. et al. Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet. Nat. Geosci. 13, 132–137 (2020). https://doi.org/10.1038/s41561-019-0510-8
+Otosaka, I. N., Shepherd, A., Ivins, E. R., Schlegel, N.-J., Amory, C., van den Broeke, M. R., Horwath, M., Joughin, I., King, M. D., Krinner, G., Nowicki, S., Payne, A. J., Rignot, E., Scambos, T., Simon, K. M., Smith, B. E., Sørensen, L. S., Velicogna, I., Whitehouse, P. L., A, G., Agosta, C., Ahlstrøm, A. P., Blazquez, A., Colgan, W., Engdahl, M. E., Fettweis, X., Forsberg, R., Gallée, H., Gardner, A., Gilbert, L., Gourmelen, N., Groh, A., Gunter, B. C., Harig, C., Helm, V., Khan, S. A., Kittel, C., Konrad, H., Langen, P. L., Lecavalier, B. S., Liang, C.-C., Loomis, B. D., McMillan, M., Melini, D., Mernild, S. H., Mottram, R., Mouginot, J., Nilsson, J., Noël, B., Pattle, M. E., Peltier, W. R., Pie, N., Roca, M., Sasgen, I., Save, H. V., Seo, K.-W., Scheuchl, B., Schrama, E. J. O., Schröder, L., Simonsen, S. B., Slater, T., Spada, G., Sutterley, T. C., Vishwakarma, B. D., van Wessem, J. M., Wiese, D., van der Wal, W., and Wouters, B.: Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020, Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, 2023.
+Pollard, D., DeConto, R. M., and Alley, R. B.: Potential Antarctic Ice Sheet retreat driven by hydrofracturing and ice cliff failure, Earth and Planetary Science Letters, 412, 112–121, https://doi.org/10.1016/j.epsl.2014.12.035, 2015. van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E., Amory, C., Birnbaum, G., Jakobs, C. L., Krüger, K., Lenaerts, J. T. M., Lhermitte, S., Ligtenberg, S. R. M., Medley, B., Reijmer, C. H., van Tricht, K., Trusel, L. D., van Ulft, L. H., Wouters, B., Wuite, J., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016), The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, 2018.",api,True,findable,0,0,0,0,0,2023-10-20T08:35:42.000Z,2023-10-20T08:35:43.000Z,cern.zenodo,cern,"Ice-sheet modelling, Antarctic ice sheet, Sea-level projections","[{'subject': 'Ice-sheet modelling, Antarctic ice sheet, Sea-level projections'}]",,
+10.6084/m9.figshare.21550639.v1,Self-compassion and emotion regulation: testing a mediation model,Taylor & Francis,2022,,Text,Creative Commons Attribution 4.0 International,"Self-compassion (SC) seems to play an important role in improving Emotion Regulation (ER). Nevertheless, the results of previous studies regarding the links between SC and ER are not consistent, especially facing diverse models of ER (strategy-based vs skill-based). The goal of this prospective study was to evaluate the links between these three concepts, by testing the predictive roles of SC and ER skills on both ER adaptive and maladaptive strategies, using standardised questionnaires and visual analogue scales. Results of regression analysis showed that self-compassion positively predicts cognitive reappraisal, acceptance, problem-solving, relaxation, self-support, tolerance and ER skills and negatively predicts behavioural avoidance, expressive suppression and ruminations. Results also showed that ER skills positively predict cognitive reappraisal, expression, acceptance, relaxation, self-support and tolerance and negatively predicts behavioural avoidance, expressive suppression and ruminations. Results from a mediation model are also promising regarding both the role of ER skills on the effect of SC on adaptive ER strategy use. Even if this study can be associated with common limits of self-report measures, it highlights the role of SC in a model of ER.",mds,True,findable,0,0,0,0,0,2022-11-14T09:00:05.000Z,2022-11-14T09:00:06.000Z,figshare.ars,otjm,"Medicine,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}]",['20085 Bytes'],
+10.5061/dryad.st350,Data from: Moving in the Anthropocene: global reductions in terrestrial mammalian movements,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.",mds,True,findable,778,124,1,1,0,2018-01-12T03:31:49.000Z,2018-01-12T03:31:50.000Z,dryad.dryad,dryad,"Eulemur rufifrons,Chlorocebus pygerythrus,Madoqua guentheri,Lynx lynx,Odocoileus hemionus,Euphractus sexcinctus,Panthera onca,Human Footprint,Cervus elaphus,Lepus europaeus,Chrysocyon brachyurus,Cerdocyon thous,Giraffa camelopardalis,Odocoileus virginianus,Antilocapra americana,Tolypeutes matacus,Martes pennanti,Odocoileus hemionus columbianus,Equus hemionus,Alces alces,Felis silvestris,Ovibos moschatus,Canis aureus,Canis latrans,Papio anubis,Papio cynocephalus,Rangifer tarandus,Canis lupus,Sus scrofa,Puma concolor,Gulo gulo,Connochaetes taurinus,Saguinus geoffroyi,Saiga tatarica,Capreolus capreolus,Cercocebus galeritus,Equus quagga,Tapirus terrestris,Myrmecophaga tridactyla,Aepyceros melampus,Anthropocene,Beatragus hunteri,Loxodonta africana,Dasypus novemcinctus,Loxodonta africana cyclotis,Procyon lotor,Ursus arctos,Equus grevyi,Tamandua mexicana,Syncerus caffer,Panthera pardus,Procapra gutturosa,Trichosurus vulpecula,Propithecus verreauxi","[{'subject': 'Eulemur rufifrons'}, {'subject': 'Chlorocebus pygerythrus'}, {'subject': 'Madoqua guentheri'}, {'subject': 'Lynx lynx'}, {'subject': 'Odocoileus hemionus'}, {'subject': 'Euphractus sexcinctus'}, {'subject': 'Panthera onca'}, {'subject': 'Human Footprint'}, {'subject': 'Cervus elaphus'}, {'subject': 'Lepus europaeus'}, {'subject': 'Chrysocyon brachyurus'}, {'subject': 'Cerdocyon thous'}, {'subject': 'Giraffa camelopardalis'}, {'subject': 'Odocoileus virginianus'}, {'subject': 'Antilocapra americana'}, {'subject': 'Tolypeutes matacus'}, {'subject': 'Martes pennanti'}, {'subject': 'Odocoileus hemionus columbianus'}, {'subject': 'Equus hemionus'}, {'subject': 'Alces alces'}, {'subject': 'Felis silvestris'}, {'subject': 'Ovibos moschatus'}, {'subject': 'Canis aureus'}, {'subject': 'Canis latrans'}, {'subject': 'Papio anubis'}, {'subject': 'Papio cynocephalus'}, {'subject': 'Rangifer tarandus'}, {'subject': 'Canis lupus'}, {'subject': 'Sus scrofa'}, {'subject': 'Puma concolor'}, {'subject': 'Gulo gulo'}, {'subject': 'Connochaetes taurinus'}, {'subject': 'Saguinus geoffroyi'}, {'subject': 'Saiga tatarica'}, {'subject': 'Capreolus capreolus'}, {'subject': 'Cercocebus galeritus'}, {'subject': 'Equus quagga'}, {'subject': 'Tapirus terrestris'}, {'subject': 'Myrmecophaga tridactyla'}, {'subject': 'Aepyceros melampus'}, {'subject': 'Anthropocene'}, {'subject': 'Beatragus hunteri'}, {'subject': 'Loxodonta africana'}, {'subject': 'Dasypus novemcinctus'}, {'subject': 'Loxodonta africana cyclotis'}, {'subject': 'Procyon lotor'}, {'subject': 'Ursus arctos'}, {'subject': 'Equus grevyi'}, {'subject': 'Tamandua mexicana'}, {'subject': 'Syncerus caffer'}, {'subject': 'Panthera pardus'}, {'subject': 'Procapra gutturosa'}, {'subject': 'Trichosurus vulpecula'}, {'subject': 'Propithecus verreauxi'}]",['585903 bytes'],
+10.6084/m9.figshare.22613066,Additional file 1 of Digital technologies in routine palliative care delivery: an exploratory qualitative study with health care professionals in Germany,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1. Interview guide.,mds,True,findable,0,0,0,0,0,2023-04-13T12:27:56.000Z,2023-04-13T12:27:57.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}]",['19572 Bytes'],
+10.5281/zenodo.8129629,Models & Simulation code and data for reproduction of results published in CoopIS,Zenodo,2023,en,Software,"Creative Commons Attribution 4.0 International,Open Access",Models & Simulation code and data for reproduction of results published in CoopIS,mds,True,findable,0,0,0,0,0,2023-07-12T15:05:07.000Z,2023-07-12T15:05:08.000Z,cern.zenodo,cern,,,,
+10.34847/nkl.ef903o6v,"Taciti et C. Velleii Paterculi scripta quae exstant; recognita, emaculata. Additique commentarii copiosissimi et notae non antea editae Paris e typographia Petri Chevalier, in monte diui Hilarii - II-0491",NAKALA - https://nakala.fr (Huma-Num - CNRS),2020,,Image,,,api,True,findable,0,0,0,0,0,2023-02-05T15:02:14.000Z,2023-02-05T15:02:14.000Z,inist.humanum,jbru,,,['52597290 Bytes'],['image/tiff']
+10.5281/zenodo.4761319,"Fig. 36 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 36. Dictyogenus muranyii sp. n., female, subgenital plate. Karstic spring of Brudour, Drôme dpt, France. Photo B. Launay.",mds,True,findable,0,0,4,0,0,2021-05-14T07:47:09.000Z,2021-05-14T07:47:10.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.57745/id1ls6,"Ice texture data from ice core, NEEM, Greenland, 2007-2012",Recherche Data Gouv,2023,,Dataset,,"NEEM (North Greenland Eemian Ice Drilling) was an international ice core research project in Greenland. As other projects like GRIP and NGRIP, this ice core had the goal to extract informations and data about the last interglacial period. The project was directed and organized by the Danish former Centre for Ice and Climate at the Niels Bohr Institute and US NSF, Office of Polar Programs. It was supported by funding agencies and institutions in Belgium (FNRS-CFB and FWO), Canada (NRCan/GSC), China(CAS), Denmark (FIST), France (IPEV, CNRS/INSU, CEA and ANR), Germany (AWI), Iceland (RannIs), Japan (NIPR), South Korea (KOPRI), the Netherlands (NWO/ ALW), Sweden (VR), Switzerland (SNF), the United Kingdom (NERC) and the USA (US NSF, Office of Polar Programs) and the EU Seventh Framework programmes Past4Future and WaterundertheIce The coring site was located in North West Greenland (camp position 77.45°N 51.06°W). The drilling took place between 2007 and 2012. For more information about the project: https://neem.dk/, NEEM community members (doi:https://doi.org/10.1038/nature11789 ). The data provided here is published in Montagnat et al., (2014) (doi:https://doi.org/10.5194/tc-8-1129-2014) The dataset contains texture data (crystallographic orientations) measured on thin sections of ice extracted along the 2540 m depth ice core. The ice core has been subdivided and stored into core sections (also called “bagsâ€) of 0.55 m long.",mds,True,findable,34,2,0,0,0,2023-03-27T12:10:05.000Z,2023-11-03T15:28:56.000Z,rdg.prod,rdg,,,,
+10.57726/pw2d-az70,Spolier et confisquer dans les mondes grec et romain,Presses Universitaires Savoie Mont Blanc,2013,fr,Book,,,fabricaForm,True,findable,0,0,0,0,0,2022-03-11T09:46:56.000Z,2022-03-11T09:46:56.000Z,pusmb.prod,pusmb,FOS: Humanities,"[{'subject': 'FOS: Humanities', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['511 pages'],
+10.5281/zenodo.5838249,ACAM - Apposed Cortex Adhesion Model,Zenodo,2022,,Software,"GNU General Public License v2.0 or later,Open Access","<strong>ACAM: an Apposed-Cortex Adhesion Model of an epithelial tissue.</strong> The <code>ACAM</code> library is an implementation of a mechanical model of an active epithelial tissue. See bioRxiv 10.1101/2021.04.11.439313 for the modelling and results. <strong>How is the cell cortex represented?</strong> Each cell cortex in ACAM is represented as an active, continuum morphoelastic rod with resistance to bending and extension. By explicitly considering both cortices along bicellular junctions, the model is able to replicate important cell behaviours that are not captured in many existing models e.g. cell-cell shearing and material flow around cell vertices. <strong>How are adhesions represented?</strong> Adhesions are modelled as simple springs, explicitly coupling neighbouring cell cortices. Adhesion molecules are given a characteristic timescale, representing the average time between binding and unbinding, which modules tissue dynamics.",mds,True,findable,0,0,0,0,0,2022-01-11T15:53:38.000Z,2022-01-11T15:53:39.000Z,cern.zenodo,cern,"mechanics,biophysics,living tissue","[{'subject': 'mechanics'}, {'subject': 'biophysics'}, {'subject': 'living tissue'}]",,
+10.5061/dryad.ksn02v75q,A multicentre study on spontaneous in-cage activity and micro-environmental conditions of IVC housed C57BL/6J mice during consecutive cycles of bi-weekly cage change,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Mice respond to a cage change (CC) with altered activity, disrupted sleep and increased anxiety. A bi-weekly cage change is, therefore, preferred over a shorter CC interval and is currently the prevailing routine for Individually ventilated cages (IVCs). However, the build-up of ammonia (NH3) during this period is a potential threat to the animal health and the literature holds conflicting reports leaving this issue unresolved. We have therefor examined longitudinally in-cage activity, animal health and the build-up of ammonia across the cage floor with female and male C57BL/6 mice housed four per IVC changed every other week. We used a multicentre design with a standardised husbandry enabling us to tease-out features that replicated across sites from those that were site-specific. CC induce a marked increase in activity, especially during daytime (~50%) when the animals rest. A reduction in density from four to two mice did not alter this response. This burst was followed by a gradual decrease till the next cage change. Female but not male mice preferred to have the latrine in the front of the cage. Male mice allocate more of the activity to the latrine free part of the cage floor already the day after a CC. A behaviour that progressed through the CC cycle but was not impacted by the type of bedding used. Reducing housing density to two mice abolished this behaviour. Female mice used the entire cage floor the first week while during the second week activity in the latrine area decreased. Measurement of NH3 ppm across the cage floor revealed x3 higher values for the latrine area compared with the opposite area. NH3 ppm increases from 0-1 ppm to reach ≤25 ppm in the latrine free area and 50-100 ppm in the latrine area at the end of a cycle. As expected in-cage bacterial load covaried with in-cage NH3 ppm. Histopathological analysis revealed no changes to the upper airways covarying with recorded NH3 ppm or bacterial load. We conclude that housing of four (or equivalent biomass) C57BL/6J mice for 10 weeks under the described conditions does not cause any overt discomfort to the animals.",mds,True,findable,169,4,0,0,0,2022-05-02T17:25:52.000Z,2022-05-02T17:25:53.000Z,dryad.dryad,dryad,"FOS: Animal and dairy science,FOS: Animal and dairy science","[{'subject': 'FOS: Animal and dairy science', 'subjectScheme': 'fos'}, {'subject': 'FOS: Animal and dairy science', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['80979400 bytes'],
+10.5281/zenodo.8379418,Synthetic along-track altimetry data over 1993-2018 from a NEMO-based simulation of the IMHOTEP project,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"""Synthetic observations"" of along-track SSH have been extracted online during the production of the global, NEMO-based experiment ** IMHOTEP-GAIc**, at every single time and locations where a true SLA observation exists in the AVISO database for the along-track altimetry from the TOPEX, Jason-1, Jason-2 and Jason-3 satellite continuous series over the period 1993-2018. This global ocean/sea-ice/iceberg simulation uses the NEMO model, and has a horizontal resolution of 1/4°. The atmospheric forcing applied at the surface is based on the JRA reanalysis (Kobayashi et al., 2015) and varies over the full range of time-scales from 6 hours to multi-decadal. The freshwater runoff forcing applied to the experiment is fully-variable (daily to multi-decadal) based on the ISBA hydrographic reanalysis for rivers (Decharme et al., 2019) and from altimeter data and regional GCM simulations for the liquid and solid discharges from the Greenland ice-sheet (Mouginot et al 2019). These runoffs are only climatological around Antarctica.This synthetic along-track SSH dataset from the model is available over the altimetry period (1993-2018). It is provided there along with a time-mean model SSH (gridded model field) over the same period that can be used as a proxy for mean dynamic topography (""MDT"").
+See the README file for more information. And online documentation is also available here: https://doc-imhotep.readthedocs.io/en/latest/6-Synthetic-Obs.html",mds,True,findable,0,0,0,0,0,2023-09-26T11:01:58.000Z,2023-09-26T11:01:59.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8368904,Environmental DNA highlights the influence of salinity and agricultural run-off on coastal fish assemblages in the Great Barrier Reef region,Zenodo,2023,,Other,"Creative Commons Attribution 4.0 International,Open Access","Agricultural run-off in Australia's Mackay-Whitsunday region is a major source of nutrient and pesticide pollution to the coastal and inshore ecosystems of the Great Barrier Reef. While the effects of run-off are well documented for the region's coral and seagrass habitats, the ecological impacts on estuaries, the direct recipients of run-off, are less known. This is particularly true for fish communities, which are shaped by the physico-chemical properties of the coastal waterways that vary greatly in tropical regions. To address this knowledge gap, we used environmental DNA (eDNA) metabarcoding to examine teleost and elasmobranch fish assemblages at four locations (three estuaries and a harbour) subjected to varying levels of agricultural run-off during a wet and dry season. Pesticide and nutrient concentrations were markedly lower during the sampled dry season. With the influx of freshwater and agricultural run-off during the wet season, teleost and elasmobranch taxa richness significantly decreased in all three estuaries, along with pronounced changes in fish community composition which were largely associated with environmental variables (particularly salinity). In contrast, the nearby Mackay Harbour exhibited a far more stable community structure, with no marked changes in fish assemblages observed between the sampled seasons. Within the wet season, differing compositions of fish communities were observed among the four sampled locations, with this variation being significantly correlated with environmental variables (salinity, chlorophyll, DOC) and contaminants from agricultural run-off, i.e., nutrients (nitrogen and phosphorus) and pesticides. Historically contaminated and relatively unimpacted estuaries each demonstrated distinct fish communities, reflecting their associated catchment use. Our findings emphasise that while seasonal effects (e.g., changes in salinity) play a key role in shaping the community structure of estuarine fish in this region, agricultural contaminants (nutrients and pesticides) are also important contributors in some systems.",mds,True,findable,0,0,0,0,0,2023-09-22T22:57:46.000Z,2023-09-22T22:57:47.000Z,cern.zenodo,cern,"eDNA,chemical analyses,species matrix","[{'subject': 'eDNA'}, {'subject': 'chemical analyses'}, {'subject': 'species matrix'}]",,
+10.5061/dryad.cz8w9gj06,"Using proxies of microbial communityâ€weighted means traits to explain the cascading effect of management intensity, soil and plant traits on ecosystem resilience in mountain grasslands",Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"1. Trait-based approaches provide a framework to understand the role of functional biodiversity on ecosystem functioning under global change. While plant traits have been reported as potential drivers of soil microbial community composition and resilience, studies directly assessing microbial traits are scarce, limiting our mechanistic understanding of ecosystem functioning. 2. We used microbial biomass and enzyme stoichiometry, and mass-specific enzymes activity as proxies of microbial community-weighted mean (CWM) traits, to infer trade-offs in microbial strategies of resource use with cascading effects on ecosystem resilience. We simulated a drought event on intact plant-soil mesocosms extracted from mountain grasslands along a management intensity gradient. Ecosystem processes and properties related to nitrogen cycling were quantified before, during and after drought to characterize ecosystem resilience. 3. Soil microbial CWM traits and ecosystem resilience to drought were strongly influenced by grassland type. Structural equation modelling revealed a cascading effect from management to ecosystem resilience through modifications in soil nutrients, and plant and microbial CWM traits. Overall, our results depict a shift from high investment in extracellular enzymes in nutrient poor soils (oligotrophic strategy), to a copiotrophic strategy with low microbial biomass N:P and low investment in extracellular enzymes associated with exploitative plant traits in nutrient rich soils. 4. Microbial CWM traits responses to management intensity were highly related to ecosystem resilience. Microbial communities with a copiotrophic strategy had lower resistance but higher recovery to drought, while microbial communities with an oligotrophic strategy showed the opposite responses. The unexpected trade-off between plant and microbial resistance suggested that the lower resistance of copiotrophic microbial communities enabled plant resistance to drought. 5. Synthesis Grassland management has cascading effects on ecosystem resilience through its combined effects on soil nutrients and plant traits propagating to microbial traits and resilience. We suggest that intensification of permanent grassland management and associated increases in soil nutrient availability decreased plant-microbe competition for N under drought through the selection of drought-sensitive microbial communities with a copiotrophic strategy that promoted plant resistance. Including proxies of microbial CWM traits into the functional trait framework will strengthen our understanding of soil ecosystem functioning under global change.",mds,True,findable,141,18,0,1,0,2019-11-22T18:54:31.000Z,2019-11-22T18:54:32.000Z,dryad.dryad,dryad,"extracellular enzymes,Mountain grassland,soil microbial community,Stoichiometry","[{'subject': 'extracellular enzymes'}, {'subject': 'Mountain grassland'}, {'subject': 'soil microbial community'}, {'subject': 'Stoichiometry', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['62792 bytes'],
+10.5061/dryad.2z34tmpjg,"Data from: Climate, soil resources and microbial activity shape the distributions of mountain plants based on their functional traits",Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"While soil ecosystems undergo important modi cations due to global change, the e ect of soil properties on plant distributions is still poorly understood. Plant growth is not only controlled by soil physico-chemistry but also by microbial activities through the decomposition of organic matter and the recycling of nutrients essential for plants. A growing body of evidence also suggests that plant functional traits modulate spe- cies’ response to environmental gradients. However, no study has yet contrasted the importance of soil physico-chemistry, microbial activities and climate on plant species distributions, while accounting for how plant functional traits can in uence species- speci c responses. Using hierarchical e ects in a multi-species distribution model, we investigate how four functional traits related to resource acquisition (plant height, leaf carbon to nitro- gen ratio, leaf dry matter content and speci c leaf area) modulate the response of 44 plant species to climatic variables, soil physico-chemical properties and microbial 100 decomposition activity (i.e. exoenzymatic activities) in the French Alps. Our hierarchical trait-based model allowed to predict well 41 species according to the TSS statistic. In addition to climate, the combination of soil C/N, as a measure of organic matter quality, and exoenzymatic activity, as a measure of microbial decom- position activity, strongly improved predictions of plant distributions. Plant traits played an important role. In particular, species with conservative traits performed bet- ter under limiting nutrient conditions but were outcompeted by exploitative plants in more favorable environments. We demonstrate tight associations between microbial decomposition activity, plant functional traits associated to di erent resource acquisition strategies and plant dis- tributions. is highlights the importance of plant–soil linkages for mountain plant distributions. ese results are crucial for biodiversity modelling in a world where both climatic and soil systems are undergoing profound and rapid transformations.",mds,True,findable,138,18,0,1,0,2020-08-12T05:06:58.000Z,2020-08-12T05:06:59.000Z,dryad.dryad,dryad,,,['14293 bytes'],
+10.5281/zenodo.7982034,"FIGURES A1–A2 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,License Not Specified,"FIGURES A1–A2. Leuctra signifera, historical material (Austria, Gutenstein Alps, Urgersbachtal). A1, Leuctra signifera sensu Kempny 1899, original drawings (figs. 4a and 4b = adult male, dorsal and lateral view); A2, Leuctra signifera sensu Mosely, 1932 (plate I, figs. 3 and 3a = male, dorsal view; female, ventral view).",mds,True,findable,0,0,0,11,0,2023-05-29T13:43:03.000Z,2023-05-29T13:43:04.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.6084/m9.figshare.22649273.v1,Additional file 1 of Predictors of changing patterns of adherence to containment measures during the early stage of COVID-19 pandemic: an international longitudinal study,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Supplementary Table 1. Measures used in the COVID-IMPACT study.,mds,True,findable,0,0,0,0,0,2023-04-18T04:38:30.000Z,2023-04-18T04:38:30.000Z,figshare.ars,otjm,"Medicine,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['25409 Bytes'],
+10.5281/zenodo.3384633,Data from: Improved STEREO simulation with a new gamma ray spectrum of excited gadolinium isotopes using FIFRELIN,Zenodo,2019,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Supplemental material to the article “Improved STEREO simulation with a new gamma ray spectrum of excited gadolinium isotopes using FIFRELIN†The files available are aimed to simulate the de-excitation cascade following neutron capture on<sup> 155</sup>Gd and <sup>157</sup>Gd. Therefore, the FIFRELIN simulation was done for the <sup>156</sup>Gd and <sup>158</sup>Gd isotopes, with the initial condition of an excitation energy of E* = S<sub>n</sub>, the neutron separation energy. Please cite this publication when using the files provided below:<br> H. Almazán et al., Eur. Phys. J. A 55 (2019) 183, arXiv:1905.11967 [physics.ins-det] Please see Zenodo 6861341 for an improved version of the provided data.",mds,True,findable,0,0,0,0,0,2019-09-03T09:07:29.000Z,2019-09-03T09:07:30.000Z,cern.zenodo,cern,"γ transitions and level energies,Neutrino Detectors,Neutron Physics","[{'subject': 'γ transitions and level energies'}, {'subject': 'Neutrino Detectors'}, {'subject': 'Neutron Physics'}]",,
+10.6084/m9.figshare.c.6851803.v1,Sonometric assessment of cough predicts extubation failure: SonoWean—a proof-of-concept study,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Extubation failure is associated with increased mortality. Cough ineffectiveness may be associated with extubation failure, but its quantification for patients undergoing weaning from invasive mechanical ventilation (IMV) remains challenging. Methods Patients under IMV for more than 24 h completing a successful spontaneous T-tube breathing trial (SBT) were included. At the end of the SBT, we performed quantitative sonometric assessment of three successive coughing efforts using a sonometer. The mean of the 3-cough volume in decibels was named Sonoscore. Results During a 1-year period, 106 patients were included. Median age was 65 [51–75] years, mainly men (60%). Main reasons for IMV were acute respiratory failure (43%), coma (25%) and shock (17%). Median duration of IMV at enrollment was 4 [3–7] days. Extubation failure occurred in 15 (14%) patients. Baseline characteristics were similar between success and failure extubation groups, except percentage of simple weaning which was lower and MV duration which was longer in extubation failure patients. Sonoscore was significantly lower in patients who failed extubation (58 [52–64] vs. 75 [70–78] dB, P < 0.001). After adjustment on MV duration and comorbidities, Sonoscore remained associated with extubation failure. Sonoscore was predictive of extubation failure with an area under the ROC curve of 0.91 (IC95% [0.83–0.99], P < 0.001). A threshold of Sonoscore < 67.1 dB predicted extubation failure with a sensitivity of 0.93 IC95% [0.70–0.99] and a specificity of 0.82 IC95% [0.73–0.90]. Conclusion Sonometric assessment of cough strength might be helpful to identify patients at risk of extubation failure in patients undergoing IMV.",mds,True,findable,0,0,0,0,0,2023-09-26T03:25:48.000Z,2023-09-26T03:25:48.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Physiology,FOS: Biological sciences,Immunology,FOS: Clinical medicine,Infectious Diseases,FOS: Health sciences,Computational Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Infectious Diseases'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Computational Biology'}]",,
+10.6084/m9.figshare.23575363,Additional file 2 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 1,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:45.000Z,2023-06-25T03:11:46.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['157184 Bytes'],
+10.5281/zenodo.7308352,An assessment of basal melt parameterisations for Antarctic ice shelves,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the data and scripts for the publication ""An assessment of basal melt parameterisations for Antarctic ice shelves"" in <em>The Cryosphere</em>. Before going into details, here is a reminder that the NEMO runs are called 'OPM+number'. These are the corresponding names given in the manuscript: OPM006=HIGHGETZ, OPM016=WARMROSS, OPM018=COLDAMU and OPM021=REALISTIC. The zipping has been made so that if you download and unzip everything you will have the following file structure: ===============<br> <strong>raw/</strong> <strong>Ant_MeltingRate.v2.2.nc</strong> <em>(from RAW_other.zip):</em> 2D observational estimates of melt rates updated from Rignot et al. (2013) by Jérémie Mouginot (used in Fig. B3) <strong>DUTRIEUX_2014/</strong> <em>(from RAW_other.zip)</em>: observational estimates temperature and salinity profiles for Pine Island Ice Shelf (inferred from Dutrieux et al., 2014 with 'find_click_position_T_from_article.py', used to produce 'T_S_profiles-dutrieux_2014_PIGL.nc') used for Fig. 8 <strong>MASK_METADATA/</strong> <em>(from RAW_other.zip)</em>: contains txt and csv files (prepared by N. Jourdain) needed for the masks, and 'IPCC_cryo_div.txt' used for the maps in Fig. 5 <strong>grid_eORCA025_CDO.nc</strong> <em>(from RAW_other.zip)</em>: grid info needed to interpolate eORCA025 grid to stereographic (provided by Fabien Gillet-Chaulet) <strong>NEMO_main/NEMO_eORCA025.L121_OPM0*_ANT_STEREO</strong><strong> </strong><em>(from RAW_nemo_OPM0*.zip)</em>: NEMO simulation output of OPM0* run, cut at 60°S on eORCA025 grid, contains: variables_of_interest: variables_of_interest_*_Ant.nc: variables of interest for the study cavity_melt_*_Ant.nc: ice-shelf melt eORCA025.L121-OPM0*_mesh_mask.nc: geometric constants and masks <strong>NEMO_appendix/NEMO_OPM0* </strong><em>(from RAW_nemo_appendix.zip)</em>: NEMO simulation output of OPM0* run used for the figures in Appendix B. The NEMO simulations were conducted by Pierre Mathiot. ===============<br> <strong>interim/</strong> <strong>ANTARCTICA_IS_MASKS</strong>/ (<em>from INTERIM_ANTARCTICA_IS_MASKS.zip</em>): contains 'nemo_5km_isf_masks_and_info_and_distance_new_oneFRIS.nc' for each NEMO run and for BedMachine, which contains masks and geometric information needed for the application of the parameterisation and computing plume and box characteristics<br> => produced with 'preprocessing/isf_mask_NEMO.ipynb' and 'preprocessing/isf_mask_BedMachine.ipynb' <strong>BOXES/</strong> (<em>from INTERIM_BOXES.zip</em>): contains 'nemo_5km_boxes_1D_oneFRIS.nc' and 'nemo_5km_boxes_2D_oneFRIS.nc' for each NEMO run and for BedMachine, which contains the variables needed to apply the box parameterisation<br> => produced with 'preprocessing/isf_mask_NEMO.ipynb' and 'preprocessing/isf_mask_BedMachine.ipynb' <strong>PLUMES/ </strong>(<em>from INTERIM_PLUMES.zip</em>): contains 'nemo_5km_plume_characteristics_oneFRIS.nc' for each NEMO run and for BedMachine, which contains the variables needed to apply the plume parameterisation<br> => produced with 'preprocessing/isf_mask_NEMO.ipynb' and 'preprocessing/isf_mask_BedMachine.ipynb' <strong>SIMPLE</strong>/ (<em>from INTERIM_SIMPLE.zip</em>) <strong>nemo_5km_06161821_oneFRIS/</strong>: contains netcdf-files summarising the tuned parameters resulting from the cross-validation over ice shelves (CVshelves), the cross-validation over time (CVtime), the tuning over all sample (ALL) and the bootstrap tuning (BT and clusterbootstrap*)<br> => summary of results from running the scripts in the folder 'tuning' - for simple parameterisations via 'tuning_cluster_ALL_CV_BT.ipynb' and for the others via 'run_generalized_tuning_from_bash_crossval.py', 'run_generalized_tuning_script.sh', 'group_CV_parameters.ipynb', 'group_BT_parameters.ipynb' <strong>nemo_5km_OPM0*</strong>: 'thermal_forcing_term_for_linreg_corrected_oneFRIS.nc', contains the term used for the tuning through linear regression of the simple parameterisations<br> => produced via 'prepare_2D_thermal_forcing_simple.ipynb' and 'prepare_1D_thermal_forcing_term_simple_for_linreg.ipynb' <strong>NEMO_eORCA025.L121_OPM*_ANT_STEREO/ </strong>(<em>from INTERIM_geometry_interp_OPM0*.zip</em>): for each NEMO run, <strong>corrected_draft_bathy_isf.nc</strong>: file containing ice draft and bathymetry corrected by ice draft concentration to account for the biased draft and bathymetry at the grounding line resulting from the interpolation from the native NEMO grid to the stereographic grid (values under ice shelf and NaNs over land<br> => produced in 'data_formatting/custom_lsmask.ipynb' <strong>custom_lsmask_Ant_stereo_clean.nc</strong>: land-sea mask giving 0 = ocean, 1 = shelf, 2 = land<br> => produced in 'data_formatting/custom_lsmask.ipynb' <strong>isfdraft_conc_Ant_stereo.nc</strong>: ice-shelf concentration resulting from the interpolation from the native NEMO grid to the stereographic grid<br> => produced in 'data_formatting/custom_lsmask.ipynb' <strong>other_mask_vars_Ant_stereo.nc</strong>: contains other variables used for the masks<br> => produced in 'data_formatting/custom_lsmask.ipynb' <strong>T_S_PROF/ </strong>(<em>from INTERIM_T_S_PROF.zip</em>) <strong>dutrieux_2014</strong>/: observational estimates temperature and salinity profiles for Pine Island Ice Shelf in one netcdf<br> => produced in 'pre_processing/T_S_profiles_Dutrieux14.ipynb' <strong>info_chunks.txt</strong>: contains corresponding NEMO run and start and end year for each time block used in cross-validation <strong>T_S_mean_prof_corrected_km_contshelf_and_offshore_1980-2018_oneFRIS.nc</strong> for each NEMO run, which contains temperature and salinity profiles averaged over 5 different regions in front of each ice shelf<br> => produced in 'pre_processing/T_S_profile_formatting_with_conversion.ipynb' and 'pre_processing/T_S_profiles_front.ipynb' ===============<br> <strong>processed/MELT_RATE/</strong> <strong>BedMachine_for_comparison</strong> <em>(from PROCESSED_BedMachine_for_comparison.zip)</em>: contains 'melt_rates_PIGL_dutrieux_time_mean_pattern.nc', which is the mean melt pattern of the melt parameterised using Dutrieux2014 observational temperature and salinity estimates<br> => produced in 'apply_params/apply_param_PIGL_dutrieux_BedMachine.ipynb' <strong>nemo_5km_OPM*</strong> <em>(from PROCESSED_nemo_5km_OPM0*.zip)</em>: for each NEMO run <strong>eval_metrics_1D*.nc</strong> : files containing 'melt_1D_Gt_per_y' and 'melt_1D_mean_myr_box1' for all parameterisations using parameters from the cross-validation over shelves (CVshelves), the cross-validation over time (CVtime), the original parameters (orig), and from Favier et al. 2019 (favier) and Jourdain et al. 2020 (lipscomb)<br> => produced in 'apply_params/evalmetrics_results_CV.ipynb' <strong>diff_melt_param_ref_box1_*.nc</strong>: files containing the difference between parameterised and reference melt in box1 for each point to create the left panel of Fig. F1<br> => produced in 'apply_pointbypointRMSE_box1_forFigF1.ipynb' <strong>melt_rates_1D_NEMO_oneFRIS.nc</strong>, <strong>melt_rates_2D_NEMO.nc</strong>,<strong> melt_rates_box1_NEMO_oneFRIS.nc</strong>: reference melt rates and integrated melt<br> => produced in 'prepare_reference_melt_file.ipynb' <em>additionally, only in nemo_5km_OPM021:</em> <strong>melt_rates_2D_NEMO_timmean.nc</strong>, <strong>melt_rates_2D_boxes_timmean_oneFRIS.nc</strong>, <strong>melt_rates_2D_plumes_timmean_oneFRIS.nc</strong>, <strong>melt_rates_2D_simple_timmean_oneFRIS.nc</strong>: files containing mean patterns used in Fig. 5 and Fig.<br> => produced in 'prepare_data_Figures_5_6.ipynb' ===============<br> <strong>ATTENTION! EXTERNAL DATA NOT CONTAINED IN THIS REPOSITORY:</strong> Observational estimates of melt rates for Pine Island Ice Shelf (from Shean et al., 2019, for Fig. 8a)<br> => This data is currently available upon request from D. Shean and will be soon made open access as well. The DOI will be shared here at that point BedMachine data used for Figure 8: It is BedMachine v2 (Morlighem, 2020) and can be found here: https://nsidc.org/data/nsidc-0756/versions/2. World Ocean Atlas data for comparisons in Appendix B. The data was downloaded here: https://www.ncei.noaa.gov/access/world-ocean-atlas-2018/bin/woa18.pl. It was then interpolated to the eORCA025 grid and converted to conservative temperature with TEOS10. ===================== The explanation around the scripts can be found in README.rst with the scripts in <strong>SCRIPTS.zip</strong>.<br> <em>Note that these are the scripts needed to produce the results in the paper. You can also find them on Github: https://github.com/ClimateClara/scripts_paper_assessment_basal_melt_param</em>, <em>find the most up-to-date version of the package 'multimelt' here: https://github.com/ClimateClara/multimelt and a version you can install via pip here: https://pypi.org/project/multimelt/ </em> Finally, if anything is unclear, check out the ""Methods"" section of the paper: https://doi.org/10.5194/tc-2022-32",mds,True,findable,0,0,0,0,0,2022-11-16T19:10:14.000Z,2022-11-16T19:10:14.000Z,cern.zenodo,cern,"Antarctica,Ice shelves,Basal melt parameterisation","[{'subject': 'Antarctica'}, {'subject': 'Ice shelves'}, {'subject': 'Basal melt parameterisation'}]",,
+10.5281/zenodo.7813697,Design of a triaxial compression cell for x-ray tomography,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"This repository contains the technical drawings of the triaxial compression setup developed and used in the PhD thesis ""Experimental investigation of the effects of particle shape and friction on the mechanics of granular media"" by Gustavo Pinzón (Université Grenoble Alpes).
+
+
+The setup is a modification of the traditional setup used in geotechnical testing, presenting a sliding base on one of the ends, which allows the creation of a singular strain localisation region. The experimental setup is designed for in-situ testing inside the x-ray tomography cabin of Laboratoire 3SR, Grenoble, France.
+
+
+ The Readme.md file contains further details on the structure of the repository and the materials of each component. Please refer to the PhD thesis for further details not found in the Readme.md file. Additional information/data not included in this repository is available upon request.",mds,True,findable,0,0,0,0,0,2023-04-10T15:08:02.000Z,2023-04-10T15:08:03.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7667342,Host symbiont gene reconciliation supplementary material,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Cinara aphids dataset was obtained from the data of article by Manzano-Marin et al. ISME, 2019, and we chose a representative subset of the species present in the gene trees. We used an exterior source for the phylogeny for the enterobacteria present in the gene trees using Annotree (Mendler et al., Nucleic Acids Research, 2019) (for the one that are not associated to Cinara aphids, and are thus ""free living"" in this setting). Helicobacter pylori dataset was constructed by Alexia Nguyen Trung, gathering available whole genome sequences on NCBI with assigned geo populations on NCBI or pubMLST. <br> A phylogenetic tree was built based on the concatenation of universal-unicopy genes (322 genes), and a sample of 113 strains representing the diversity of H. pylori in the old world (excluding strains from the Americas) was obtained using Treemmer (Menardo et al, BMC Bioinformatics, 2018).<br> Then, 6 non pylori strains were added (H. hepaticus, H. acinonychis, H. canadensis, H felis, H. bizzozeronii, H. cetorum), as an external group. <br> In this study we considered the 1034 gene families, including 322 universal unicopy family, which displayed strains from the external group and from at least 3 continents.<br> The taleoutput repository contains the recphyloxml outputs of the methods used in the paper, am stands for the approach with amalgamation of the universal unicopy genes to construct a strain tree, while nc refers to the results with the tree constructed from the concatenate, and then the repositories refer to the putative population trees 1, 2, 3 and 4. 0u_0 is the strains genes reconciliation in recphyloxml format. 0upper is the host strains reconciliation in recphyloxml format. Finally, the last repository contains the simulated dataset. It was generated using Sagephy https://compbio.engr.uconn.edu/software/sagephy/ https://doi.org/10.1093/bioinformatics/btz081<br> For each instance, a host tree, a symbiont tree, and 5 gene trees were generated. We used the parameters proposed in https://doi.org/10.1145/3307339.3342168 \cite{kordi_inferring_2019}, as representative of small (D 0.133, T 0.266, L 0.266), medium (D 0.3, T 0.6, L 0.6) and high (D 0.6, T 1.2, L 1.2) transfer rates, without replacing transfers. The software enables to specify an inter transfer rate, corresponding to the probability for a gene transfer between different hosts. When a horizontal transfer is chosen during generation of the gene tree (inside a symbiont tree and knowing a host/symbiont reconciliation), the transfer is chosen to be an inter host one with the inter transfer rate. So an inter transfer rate of 0 corresponds to only intra transfer, and of 1 corresponds to a case where transfers are only between symbionts in separate hosts. <br> We constructed two simulated datasets, one with a combination of the different rates for the DTL parameters (varrates), and one with only medium rates but with different rates of ""inter"" and ""intra"" transfers (coevol).<br> For the first dataset, we used all 9 combinations of small, medium and high rates for the symbiont generation and the gene generation, with only intra host gene transfer (i.e. an inter transfer rate of zero).<br> For the second dataset, we used only medium rates for both symbiont and genes generation, but we used 6 inter transfer rates going from 0 to 1. For both datasets, and for each set of rates, we generated 50 instances consisting of 1 host tree with 100 leaves, 1 symbiont tree and 5 gene trees, each generated in the pruned version of the other trees (branch that do not reach present are pruned before the generation of the next tree). We then kept each host leaves with a probability of 0.08 to simulate unexhaustive sampling, resulting in host trees with an average size of 8 leaves.<br> This ended up to 399 instances for the first dataset and 226 instances for the second one, and at least 29 instances of 5 genes for each set of parameters. Each repositiory is a simulation instance, varrates_k_l_i correspond to simulation number i with lower rate k and upper rate l. genes, symbiont, species are repositories containing the trees in newick of the genes, symbiont and host in newick. Gene trees are unrooted. Lower matching is a matching between gene and symbiont leaves, upper matching between symbiont and host leaves, gene_host_matching is a matching between gene and host leaves. Transfer list contains one file for each gene and with all transfers simulated, donor and receiver symbiont internal nodes.<br> Each instance also contains the output of tale used in the paper, with the three heuristic, the 2-level symbiont gene (_2l), the 3-level sequential heuristic (_dec) and the 3-level monte carlo approach (_mc) with 50 iterations. All the launch were with 5 rounds of parameters estimation (the default usage). The 0u_0 contain a sampled symbiont gene reconciliation in recphyloxml, and for the 3-level heuristics, 0upper a corresponding host symbiont reconciliation in recphyloxml (multiple ones for the montecarlo i_upper and iu_0 for i from 0 to 49). A known error in the recphyloxml transcription script, now corrected, has induced some errors in some of the recphyloxml files : for some transfers the indicated receiver species is the donor and not the receiver, however redundancy in the format makes it possible to retrieve the information by looking at the matching species in the next event of the gene, that will be the receiver species, we chose to leave it this way instead of relaunching all the computations, as it has no impact on the figures and results presented in our article (mostly constructed using the freq files). The files freq contains information on the frequencies of the different events summed up over gene symbionts reconciliation, lower_log_likelihood contains the log likelihood of the host and symbiont trees knowing the genes (the probability of the genes knowing the host and symbiont).",mds,True,findable,0,0,0,0,0,2023-04-12T14:38:46.000Z,2023-04-12T14:38:47.000Z,cern.zenodo,cern,"Helicobacter pylori,Aphids,Enterobacter","[{'subject': 'Helicobacter pylori'}, {'subject': 'Aphids'}, {'subject': 'Enterobacter'}]",,
+10.5281/zenodo.4761331,"Figs. 54-55. Dictyogenus alpinum, male. 54 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 54-55. Dictyogenus alpinum, male. 54. Head and pronotum. Vorz River, Isère dpt, France. Photo B. Launay. 55. Hemitergal lobes, lateral view. Vorz River, Isère dpt, France. Photo B. Launay.",mds,True,findable,0,0,2,0,0,2021-05-14T07:48:52.000Z,2021-05-14T07:48:53.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.6675912,Dataset: Halving of Swiss glacier volume since 1931 observed from terrestrial image photogrammetry,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is supplementary data for the article currently in review for The Cryosphere, titled ""Halving of Swiss glacier volume since 1931 observed from terrestrial image photogrammetry"". See the preprint here",mds,True,findable,0,0,0,0,0,2022-06-21T15:32:36.000Z,2022-06-21T15:32:37.000Z,cern.zenodo,cern,"Glacier,Photogrammetry,Switzerland,Digital Elevation Model,DEM","[{'subject': 'Glacier'}, {'subject': 'Photogrammetry'}, {'subject': 'Switzerland'}, {'subject': 'Digital Elevation Model'}, {'subject': 'DEM'}]",,
+10.57745/7rfnnp,"Replication data for the publication ""Knowledge coproduction to improve assessments of nature’s contributions to people""",Recherche Data Gouv,2023,,Dataset,,"This repository contains the auxiliary data to reproduce the results of the publication: Vallet et al., ""Knowledge coproduction to improve assessments of nature’s contributions to people"" (https://doi.org/10.1111/cobi.14182). The code can be found here: https://gitlab.dsi.universite-paris-saclay.fr/agata/medicinal_plants/medicinal_plants_coproduction. Please see the README document for a description of the files.",mds,True,findable,42,5,0,0,0,2023-08-03T16:13:00.000Z,2023-10-26T14:20:08.000Z,rdg.prod,rdg,,,,
+10.5061/dryad.dbrv15f06,"Rainfall continentality, via the winter GAMS angle, provides a new dimension to biogeographical distributions in the Western United States",Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Aim: Drought stress, and its effects on the biogeography of vegetation, has focused primarily on water availability during the growing season, thus focusing primarly on summer. However, variation in rainfall continentality (i.e., the continental interior being insulated from oceanic influences) can produce striking vegetation differences. We aim to disentangle summer water balance from the influence of rainfall continentality on winter rainfall, to better understand how climate regulated the distributions of woody plants in the Western USA. Location: Western USA. Time period: Actual. Major taxa studied: Angiosperms and Conifers. Method: We used Redundancy Analysis (RDA) to investigate correlations between rainfall continentality, summer water balance, minimum winter temperature and length of growing season on the distributions of 130 tree and shrub species in 467 plots. Rainfall continentality was calculated using the Gams (1932) index, modified for winter precipitation, and summer water balance with the ratio of summer precipitation to temperature. We estimated Actual EvapoTranspiration (AET), Deficit (DEF), mean annual temperature and rainfall from global gridded datasets and correlated them with RDA axes. Results: Rainfall continentality measured with the Gams index and minimum temperatures best explained the contrast between oceanic vegetation in the Pacific Coast Ranges and continental vegetation in the Intermountain Region and Rocky Mountains. Growing Season Length (GSL) was the second strongest factor correlated with vegetation distributions. Summer water balance, despite being the most widely used climatic factor to assess drought stress in biogeography, was the third strongest factor correlating with vegetation classes of the western US. AET was equally correlated with RDA axes 1 and 3, and, thus, could not discriminate between the contrasts in the RDA. Main conclusions: Rainfall continentality measured with the winter Gams index provides a more precise metric than summer water balance for understanding how the biogeography of woody plants in the western USA is regulated by climate. Broadly integrating the Gams index of continentality into plant distributions may improve our understanding of biogeographical distributions, the evolution of subspecies in species that span coastal to interior regions, and predictions of responses to climate change.",mds,True,findable,148,6,0,0,0,2020-10-12T22:48:58.000Z,2020-10-12T22:48:59.000Z,dryad.dryad,dryad,Biogeography,"[{'subject': 'Biogeography', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['175547 bytes'],
+10.5281/zenodo.4925909,Increased functional connectivity of the intraparietal sulcus underlies the attenuation of numerosity estimations for self-generated words,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Description of the dataset: Healthy participants imaging data (N=25). Data set includes MPRAGE, field map and 3 runs of task fMRI. Data is organized in BIDS format. Nifti zipped files are uploaded together with corresponding json and tsv files describing the sequence and task events. json files describing the study sample and details of the task are included. Abstract of the study: Previous studies have shown that self-generated stimuli in auditory, visual, and somatosensory domains are attenuated, producing decreased behavioral and neural responses compared to the same stimuli that are externally generated. Yet, whether such attenuation also occurs for higher-level cognitive functions beyond sensorimotor processing remains unknown. In this study, we assessed whether cognitive functions such as numerosity estimations are subject to attenuation in 56 healthy participants (32 women). We designed a task allowing the controlled comparison of numerosity estimations for self (active condition) and externally (passive condition) generated words. Our behavioral results showed a larger underestimation of self- compared to externally-generated words, suggesting that numerosity estimations for self-generated words are attenuated. Moreover, the linear relationship between the reported and actual number of words was stronger for self-generated words, although the ability to track errors about numerosity estimations was similar across conditions. Neuroimaging results revealed that numerosity underestimation involved increased functional connectivity between the right intraparietal sulcus and an extended network (bilateral supplementary motor area, left inferior parietal lobule and left superior temporal gyrus) when estimating the number of self vs. externally generated words. We interpret our results in light of two models of attenuation and discuss their perceptual versus cognitive origins.",mds,True,findable,0,0,0,0,0,2021-06-15T10:14:46.000Z,2021-06-15T10:14:47.000Z,cern.zenodo,cern,"fMRI, BOLD, numerosity, attenuation","[{'subject': 'fMRI, BOLD, numerosity, attenuation'}]",,
+10.5281/zenodo.1185426,CryoEM Maps and Associated Data Submitted to the 2015/2016 EMDataBank Map Challenge,Zenodo,2017,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Files and metadata associated with the EMDataBank/Unified Data Resource for 3DEM 2015/2016 Map Challenge hosted at challenges.emdatabank.org are deposited.
+
+All members of the Scientific Community--at all levels of experience--were invited to participate as Challengers, and/or as Assessors.
+
+Seven benchmark raw image datasets were selected for the challenge. Six are selected from recently described single particle structure determinations with image data collected as multi-frame movies; one is based on simulated (in silico) images. All of the raw image datasets are archived at pdbe.org/empiar.
+
+27 Challengers created 66 single particle reconstructions from the targets, and then uploaded their results with associated details. 15 of the reconstructions were calculated using the SDSC Gordon supercomputer.
+
+This map challenge was one of two community-wide challenges sponsored by EMDataBank in 2015/2016 to critically evaluate 3DEM methods that are coming into use, with the ultimate goal of developing validation criteria associated with every 3DEM map and map-derived model.",mds,True,findable,0,0,12,0,0,2018-02-27T23:32:49.000Z,2018-02-27T23:32:50.000Z,cern.zenodo,cern,"cryo electron microscopy,cryoEM,validation,challenge,benchmark,https://meshb.nlm.nih.gov/record/ui?name=Benchmarking,https://meshb.nlm.nih.gov/record/ui?name=Databases,%20Protein,https://meshb.nlm.nih.gov/record/ui?name=Cryoelectron%20Microscopy,https://meshb.nlm.nih.gov/record/ui?name=Imaging,%20Three%20Dimensional,https://meshb.nlm.nih.gov/record/ui?name=Microscopy,%20Electron","[{'subject': 'cryo electron microscopy'}, {'subject': 'cryoEM'}, {'subject': 'validation'}, {'subject': 'challenge'}, {'subject': 'benchmark'}, {'subject': 'https://meshb.nlm.nih.gov/record/ui?name=Benchmarking', 'subjectScheme': 'url'}, {'subject': 'https://meshb.nlm.nih.gov/record/ui?name=Databases,%20Protein', 'subjectScheme': 'url'}, {'subject': 'https://meshb.nlm.nih.gov/record/ui?name=Cryoelectron%20Microscopy', 'subjectScheme': 'url'}, {'subject': 'https://meshb.nlm.nih.gov/record/ui?name=Imaging,%20Three%20Dimensional', 'subjectScheme': 'url'}, {'subject': 'https://meshb.nlm.nih.gov/record/ui?name=Microscopy,%20Electron', 'subjectScheme': 'url'}]",,
+10.5061/dryad.9s4mw6mm3,Data and code from: The functional trait distinctiveness of plant species is scale dependent,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Beyond the local abundance of species, their functional trait distinctiveness is now recognized as a key driver of community dynamics and ecosystem functioning. Yet, since the functional distinctiveness of a species is always relative to a given species pool, a species distinct at the regional scale might not necessarily be distinct at the local or community scale, and reciprocally. To assess the importance of scale (i.e the definition of a species pool) when quantifying the functional distinctiveness of species, and how it might distort the ecological conclusions derived from it, we quantified trait distinctiveness of 1,350 plant species at regional, local, and community scales over ca. 88 000 grassland plots in France. We measured differences in functional distinctiveness of species between regional, local and community scales and tested the influence of environmental predictors (climate and nitrogen input) and contexts (environmental distinctiveness, frequency, and heterogeneity) on these variations. In line with theoretical expectations, we found large variations of functional distinctiveness (in particular between regional and community scales) for many species, with a general tendency of lower distinctiveness at smaller scales. We also showed that nitrogen input – a key aspect of high land use intensity – and environmental frequency partly explained the differences between local and regional scales only. These results suggest the role played by environmental filtering on species' distinctiveness at the local scale, but the determinant of distinctiveness variations at the community scale still needs to be elucidated. Our study provides robust empirical evidence that measures of ecological originality are strongly scale-dependent. We urge ecologists to carefully consider the scale at which they measure distinctiveness, as ignoring scale dependencies could lead to biased (or even entirely wrong) conclusions when not considered at the scale of interest for the respective research question.",mds,True,findable,129,18,0,1,0,2022-11-30T16:02:24.000Z,2022-11-30T16:02:24.000Z,dryad.dryad,dryad,"Ecological originality,Leaf traits,Community ecology,trait-based ecology,FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences","[{'subject': 'Ecological originality'}, {'subject': 'Leaf traits'}, {'subject': 'Community ecology', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'trait-based ecology'}, {'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['222453930 bytes'],
+10.5061/dryad.k98sf7m98,Data from: Caveolae and Bin1 form ring-shaped platforms for T-tubule initiation,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Excitation-contraction coupling requires a highly specialized membrane structure, the triad, composed of a plasma membrane invagination, the T-tubule, surrounded by two sarcoplasmic reticulum terminal cisternae. Although the precise mechanisms governing T-tubule biogenesis and triad formation remain largely unknown, studies have shown that caveolae participate in T-tubule formation and mutations of several of their constituents induce muscle weakness and myopathies. Here, we demonstrate that, at the plasma membrane, caveolae composed of caveolin-3 and Bin1 assemble into ring-like structures from which emerge tubes enriched in the dihydropyridine receptor. Overexpression of Bin1 leads to the formation of both rings and tubes and we show that Bin1 forms scaffolds on which caveolae accumulate to form the initial T-tubule. Cav3 deficiency caused by either gene silencing or pathogenic mutations causes defective ring formation and perturbed Bin1-mediated tubulation that may explain defective T-tubule organization in mature muscles. Our results uncover new pathophysiological mechanisms that may prove relevant to myopathies caused by Cav3 or Bin1 variants.",mds,True,findable,93,4,0,2,0,2023-04-26T16:47:50.000Z,2023-04-26T16:47:51.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['203816 bytes'],
+10.5281/zenodo.4546112,ROBO1 protein models predicted by Galaxy pipeline and from Aleksandrova et al. 2018,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This ZIP-file contains the files used for ROBO1 protein modelling and resulting PDB (Protein Data Bank) files from the GalaxyTBM-Refine-Pipeline bundled with the pseudoatomic model of the ROBO1 tetramer presented in PMID 29307485.<br> We always used standard parameters and the respective top model (""model_1"") for each algorithm/pipeline and/or downstream steps.",mds,True,findable,0,0,0,0,0,2021-02-17T17:59:55.000Z,2021-02-17T17:59:55.000Z,cern.zenodo,cern,"ROBO1,GalaxyTBM","[{'subject': 'ROBO1'}, {'subject': 'GalaxyTBM'}]",,
+10.5281/zenodo.5243248,Malagasy DBnary archive in original Lemon format,Zenodo,2021,mg,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Malagasy language edition, ranging from 2nd June 2015 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T10:49:23.000Z,2021-08-24T10:49:23.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.4745556,robertxa/pyRRIM: Zenodo Release,Zenodo,2021,,Software,Open Access,Red Relief Image Map generation,mds,True,findable,0,0,0,0,0,2021-05-10T10:19:52.000Z,2021-05-10T10:19:53.000Z,cern.zenodo,cern,,,,
+10.25384/sage.24147060.v1,sj-docx-1-jic-10.1177_08850666231199937 - Supplemental material for Perceived Quality of Life in Intensive Care Medicine Physicians: A French National Survey,SAGE Journals,2023,,Text,In Copyright,"Supplemental material, sj-docx-1-jic-10.1177_08850666231199937 for Perceived Quality of Life in Intensive Care Medicine Physicians: A French National Survey by Nicolas Terzi, Alicia Fournier, Olivier Lesieur, Julien Chappé, Djillali Annane, Jean-Luc Chagnon, Didier Thévenin, Benoit Misset, Jean-Luc Diehl, Samia Touati, Hervé Outin, Stéphane Dauger, Arnaud Sement, Jean-Noël Drault, Jean-Philippe Rigaud, Alexandra Laurent and in Journal of Intensive Care Medicine",mds,True,findable,0,0,0,0,0,2023-09-15T12:11:53.000Z,2023-09-15T12:11:54.000Z,figshare.sage,sage,"Emergency Medicine,Aged Health Care,Respiratory Diseases","[{'subject': 'Emergency Medicine'}, {'subject': 'Aged Health Care'}, {'subject': 'Respiratory Diseases'}]",['37585 Bytes'],
+10.5281/zenodo.6280986,Understanding monsoon controls on the energy and mass balance of glaciers in the Central and Eastern Himalaya (Data Sets and Codes),Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains AWS datasets for the modelling periods considered in the analysis presented in the research paper, together with ablation measurements, pre-processed forcing data, T&C model codes, outputs and scripts for analysing outputs. When previously published elsewhere, references and links to the full, original datasets are provided under References. Matlab scripts for executing the T&C model are provided and should work stand-alone on any machine with a Matlab version 2019b or later installed.",mds,True,findable,0,0,2,0,0,2022-03-03T21:27:19.000Z,2022-03-03T21:27:20.000Z,cern.zenodo,cern,"glacier, energy balance modelling, debris cover, glacier melt modelling","[{'subject': 'glacier, energy balance modelling, debris cover, glacier melt modelling'}]",,
+10.5281/zenodo.4759497,"Figs. 28-33 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 28-33. Terminalias of the imago of Protonemura algirica algirica (Aubert, 1956). 28: male terminalia, dorsal view; 29: male terminalia, ventral view; 30: male terminalia, lateral view; 31: male paraproct, ventrolateral view; 32: female pregenital and subgenital plates, and vaginal lobes, ventral view; 33: female pregenital and subgenital plates, and vaginal lobes, lateral view (scales 0.5 mm; scale 1: Fig. 31, scale 2: Figs. 28-30, 32-33).",mds,True,findable,0,0,2,0,0,2021-05-14T02:24:45.000Z,2021-05-14T02:24:46.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.6084/m9.figshare.21430974.v1,Additional file 2 of Digitally-supported patient-centered asynchronous outpatient follow-up in rheumatoid arthritis - an explorative qualitative study,figshare,2022,,Text,Creative Commons Attribution 4.0 International,Supplementary Material 2,mds,True,findable,0,0,0,0,0,2022-10-29T03:17:13.000Z,2022-10-29T03:17:14.000Z,figshare.ars,otjm,"Medicine,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['14460 Bytes'],
+10.5281/zenodo.10020919,robertxa/Mirolda: Release 2023,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,Cave survey data with 2023 additions,api,True,findable,0,0,0,0,0,2023-10-19T08:28:21.000Z,2023-10-19T08:28:21.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.4f4qrfjjc,Multiplexing PCR allows the identification of within-species genetic diversity in ancient eDNA,Dryad,2023,en,Dataset,Creative Commons Zero v1.0 Universal,"Sedimentary ancient DNA (sedaDNA) has rarely been used to obtain population-level data due to either a lack of taxonomic resolution for the molecular method used, limitations in the reference material or inefficient methods. Here, we present the potential of multiplexing different PCR primers to retrieve population-level genetic data from sedaDNA samples. Vaccinium uliginosum (Ericaceae) is a widespread species with a circumpolar distribution and three lineages for present-day populations. We searched 18 plastid genomes for intraspecific variable regions and developed 61 primers to target these. Initial multiplex PCR testing resulted in a final set of 38 primers. These primers were used to analyse 20 lake sedaDNA samples (11,200 cal. yr BP to present) from five different localities in northern Norway, the Alps and the Polar Urals. All known V. uliginosum lineages in these regions and all primers could be recovered from the sedaDNA data, where for each sample 28.1 primers containing 34.15 variant sequences were obtained on average. All sediment samples were dominated by a single lineage, except three alpine samples which had co-occurrence of two different lineages. Furthermore, lineage turnover was observed in the Alps and northern Norway, suggesting that present-day phylogeographical studies may overlook past genetic patterns. Multiplexing primers is a promising tool for generating population-level genetic information from sedaDNA. The relatively simple method, combined with high sensitivity, provides a scalable method that will allow researchers to track populations through time and space using environmental DNA.",mds,True,findable,93,1,0,0,0,2023-08-28T21:30:41.000Z,2023-08-28T21:30:41.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences,sedimentary ancient DNA,Environmental DNA,Multiplexing PCR,Phylogeography","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'sedimentary ancient DNA'}, {'subject': 'Environmental DNA'}, {'subject': 'Multiplexing PCR'}, {'subject': 'Phylogeography', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['28506432 bytes'],
+10.6084/m9.figshare.c.6583718,TRansfusion strategies in Acute brain INjured patients (TRAIN): a prospective multicenter randomized interventional trial protocol,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Although blood transfusions can be lifesaving in severe hemorrhage, they can also have potential complications. As anemia has also been associated with poor outcomes in critically ill patients, determining an optimal transfusion trigger is a real challenge for clinicians. This is even more important in patients with acute brain injury who were not specifically evaluated in previous large randomized clinical trials. Neurological patients may be particularly sensitive to anemic brain hypoxia because of the exhausted cerebrovascular reserve, which adjusts cerebral blood flow to tissue oxygen demand. Methods We described herein the methodology of a prospective, multicenter, randomized, pragmatic trial comparing two different strategies for red blood cell transfusion in patients with acute brain injury: a “liberal†strategy in which the aim is to maintain hemoglobin (Hb) concentrations greater than 9 g/dL and a “restrictive†approach in which the aim is to maintain Hb concentrations greater than 7 g/dL. The target population is patients suffering from traumatic brain injury (TBI), subarachnoid hemorrhage (SAH), or intracerebral hemorrhage (ICH). The primary outcome is the unfavorable neurological outcome, evaluated using the extended Glasgow Outcome Scale (eGOS) of 1–5 at 180 days after the initial injury. Secondary outcomes include, among others, 28-day survival, intensive care unit (ICU) and hospital lengths of stay, the occurrence of extra-cerebral organ dysfunction/failure, and the development of any infection or thromboembolic events. The estimated sample size is 794 patients to demonstrate a reduction in the primary outcome from 50 to 39% between groups (397 patients in each arm). The study was initiated in 2016 in several ICUs and will be completed in December 2022. Discussion This trial will assess the impact of a liberal versus conservative strategy of blood transfusion in a large cohort of critically ill patients with a primary acute brain injury. The results of this trial will help to improve blood product and transfusion use in this specific patient population and will provide additional data in some subgroups of patients at high risk of brain ischemia, such as those with intracranial hypertension or cerebral vasospasm. Trial registration ClinicalTrials.gov NCT02968654.",mds,True,findable,0,0,0,0,0,2023-04-13T11:34:57.000Z,2023-04-13T11:34:57.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Neuroscience,Biotechnology,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.3871603,Raw diffraction data for [NiFeSe] hydrogenase pressurized with Kr gas - dataset wtKr1A,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","Diffraction data measured at ESRF beamline ID29 on October 2, 2017. Image files are uploaded in blocks of gzip-compressed cbf files.",mds,True,findable,3,0,0,0,0,2020-06-01T15:52:13.000Z,2020-06-01T15:52:14.000Z,cern.zenodo,cern,"Hydrogenase,Selenium,gas channels,high-pressure derivatization","[{'subject': 'Hydrogenase'}, {'subject': 'Selenium'}, {'subject': 'gas channels'}, {'subject': 'high-pressure derivatization'}]",,
+10.5281/zenodo.4957517,Coda wave sensitivity kernels for non-uniform scattering media: the Monte Carlo simulation code,Zenodo,2021,en,Software,"GNU General Public License v3.0 only,Open Access","The ``kernels_volcano_FZ.c"" code performs Monte Carlo simulations to obtain coda wave sensitivity kernels (travel-time, decorrelation and scattering kernels) for media with non-uniform scattering strength (e.g. a volcanic, fault zone or two half-spaces setting). This code has been used to create the results in the accompanying paper ``Implications of laterally varying scattering properties for subsurface monitoring with coda wave sensitivity kernels: application to volcanic and fault zone setting"" by Chantal van Dinther, Ludovic Margerin and Michel Campillo, submitted to the Journal of Geophysical Research: Solid Earth, with DOI: https://doi.org/10.1029/2021JB022554<br> The details of the code are explained in the paper, including a graphical representation of the delta-scattering, a procedure specific to this code to speed up the calculations of the kernels for non-uniform media.",mds,True,findable,0,0,0,0,0,2021-09-21T13:32:55.000Z,2021-09-21T13:32:56.000Z,cern.zenodo,cern,"monte carlo simulations,sensitivity kernels,non-uniform scattering,travel-time kernel,decorrelation kernel,scattering kernel","[{'subject': 'monte carlo simulations'}, {'subject': 'sensitivity kernels'}, {'subject': 'non-uniform scattering'}, {'subject': 'travel-time kernel'}, {'subject': 'decorrelation kernel'}, {'subject': 'scattering kernel'}]",,
+10.5281/zenodo.5285177,New estimation of the NOx snow-source on the Antarctic Plateau - repository dataset,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Notebook and data set used to present the results. For more information, please, do not hesitate to contact the corresponding author to this study.",mds,True,findable,0,0,0,0,0,2021-08-27T13:13:55.000Z,2021-08-27T13:13:56.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8410346,Étude des applications Bag-of-Tasks du méso-centre Gricad,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data from the CiGri middleware running on the Gricad center: version 1: from Jan 2017 to Nov 202, analysis scripts are available here version 2: from Jan 2013 to Apr 2023, analysis scripts are available here This data has been used to produce the document https://hal.archives-ouvertes.fr/hal-03702246 SWH: https://archive.softwareheritage.org/swh:1:rev:7a249f4e726644ad119a29dffe42ff0075eaaecd;origin=https://gitlab.inria.fr/cigri-ctrl/compas22_etude_bot_gricad;visit=swh:1:snp:df9e28f8d6542d06b13f404bc1f47c457582cf64",mds,True,findable,0,0,0,0,0,2023-10-05T12:29:36.000Z,2023-10-05T12:29:36.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4761333,"Fig. 56 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 56. Dictyogenus alpinum, male, hemitergal lobes, dorsal view. Nant Bénin River, Savoie dpt, France. Photo B. Launay.",mds,True,findable,0,0,6,0,0,2021-05-14T07:49:19.000Z,2021-05-14T07:49:20.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5061/dryad.5x69p8d6v,Cophylogeny reconstruction allowing for multiple associations through approximate Bayesian computation,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Phylogenetic tree reconciliation is extensively employed for the examination of coevolution between host and symbiont species. An important concern is the requirement for dependable cost values when selecting event-based parsimonious reconciliation. Although certain approaches deduce event probabilities unique to each pair of host and symbiont trees, which can subsequently be converted into cost values, a significant limitation lies in their inability to model the invasion of diverse host species by the same symbiont species (termed as a spread event), which is believed to occur in symbiotic relationships. Invasions lead to the observation of multiple associations between symbionts and their hosts (indicating that a symbiont is no longer exclusive to a single host), which are incompatible with the existing methods of coevolution. Here, we present a method called AmoCoala (an enhanced version of the tool Coala) that provides a more realistic estimation of cophylogeny event probabilities for a given pair of host and symbiont trees, even in the presence of spread events. We expand the classical 4-event coevolutionary model to include 2 additional spread events (vertical and horizontal spreads) that lead to multiple associations. In the initial step, we estimate the probabilities of spread events using heuristic frequencies. Subsequently, in the second step, we employ an approximate Bayesian computation (ABC) approach to infer the probabilities of the remaining 4 classical events (cospeciation, duplication, host switch, and loss) based on these values. By incorporating spread events, our reconciliation model enables a more accurate consideration of multiple associations. This improvement enhances the precision of estimated cost sets, paving the way to a more reliable reconciliation of host and symbiont trees. To validate our method, we conducted experiments on synthetic datasets and demonstrated its efficacy using real-world examples. Our results showcase that AmoCoala produces biologically plausible reconciliation scenarios, further emphasizing its effectiveness.The software is accessible at https://github.com/sinaimeri/AmoCoala.",mds,True,findable,109,15,0,1,0,2022-10-25T22:13:01.000Z,2022-10-25T22:13:02.000Z,dryad.dryad,dryad,"reconciliation,cophylogeny,ABC method,spread,FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'reconciliation'}, {'subject': 'cophylogeny'}, {'subject': 'ABC method'}, {'subject': 'spread'}, {'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['6418 bytes'],
+10.5281/zenodo.4304466,pyirf,Zenodo,2020,,Software,"MIT License,Open Access",<em>pyirf</em> is a prototype for the generation of Instrument Response Functions (IRFs) for the Cherenkov Telescope Array (CTA). The package is being developed and tested by members of the CTA consortium. Documentation: https://cta-observatory.github.io/pyirf/ Source code: https://github.com/cta-observatory/pyirf,mds,True,findable,0,0,0,0,0,2020-12-03T14:55:40.000Z,2020-12-03T14:55:40.000Z,cern.zenodo,cern,"gamma-ray astronomy,cherenkov telescopes,CTA,instrument response,IRF,python","[{'subject': 'gamma-ray astronomy'}, {'subject': 'cherenkov telescopes'}, {'subject': 'CTA'}, {'subject': 'instrument response'}, {'subject': 'IRF'}, {'subject': 'python'}]",,
+10.5061/dryad.qv9s4mwf3,"Global maps of current (1979-2013) and future (2061-2080) habitat suitability probability for 1,485 European endemic plant species",Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Aims: The rapid increase in the number of species that have naturalized beyond their native range is among the most apparent features of the Anthropocene. How alien species will respond to other processes of future global changes is an emerging concern and remains largely misunderstood. We therefore ask whether naturalized species will respond to climate and land-use change differently than those species not yet naturalized anywhere in the world. Location: Global Methods: We investigated future changes in the potential alien range of vascular plant species endemic to Europe that are either naturalized (n = 272) or not yet naturalized (1,213) outside of Europe. Potential ranges were estimated based on projections of species distribution models using 20 future climate-change scenarios. We mapped current and future global centres of naturalization risk. We also analyzed expected changes in latitudinal, elevational and areal extent of species’ potential alien ranges. Results: We showed a large potential for more worldwide naturalizations of European plants currently and in the future. The centres of naturalization risk for naturalized and non-naturalized plants largely overlapped, and their location did not change much under projected future climates. Nevertheless, naturalized plants had their potential range shifting poleward over larger distances, whereas the non-naturalized ones had their potential elevational ranges shifting further upslope under the most severe climate change scenarios. As a result, climate and land-use changes are predicted to shrink the potential alien range of European plants, but less so for already naturalized than for non-naturalized species. Main conclusions: While currently non-naturalized plants originate frequently from mountain ranges or boreal and Mediterranean biomes in Europe, the naturalized ones usually occur at low elevations, close to human centres of activities. As the latter are expected to increase worldwide, this could explain why the potential alien range of already naturalized plants will shrink less.",mds,True,findable,272,14,0,0,0,2021-06-09T18:31:09.000Z,2021-06-09T18:31:10.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences,alien plant species,Climate change,climate change responses,species range shift,interacting effects of global change,Land-use change,macro-ecology,non-analogue climate","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'alien plant species'}, {'subject': 'Climate change', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'climate change responses'}, {'subject': 'species range shift'}, {'subject': 'interacting effects of global change'}, {'subject': 'Land-use change'}, {'subject': 'macro-ecology'}, {'subject': 'non-analogue climate'}]",['3040794130 bytes'],
+10.5281/zenodo.10005439,"Data for the paper: ""Simulating a Multi-Layered Grid Middleware""",Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"Associated paper: https://hal.science/hal-04101015
+Repo here",api,True,findable,0,0,0,0,0,2023-10-15T22:47:26.000Z,2023-10-15T22:47:26.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5527127,Imprints of Ocean Chaotic Intrinsic Variability on Bottom Pressure and Implications for Data and Model Analyses,Zenodo,2021,,Dataset,"Creative Commons Attribution 3.0 United States,Open Access","These data are used for the manuscript ""Imprints of Ocean Chaotic Intrinsic Variability on Bottom Pressure and Implications for Data and Model Analyses"" to be submitted to Geophysical Research Letter. Uploaded data include: [1] ext_int_quater_deg.nc: atmospherically driven and intrinsic variations for subseasonal, intra-annual and mean seasonal bottom pressure signals at model original resolution. [2] ext_int_3deg.nc: atmospherically driven and intrinsic variations for smoothed subseasonal and intra-annual bottom pressure signals at 3*3 degree resolution. [3] ext_int_10deg.nc: atmospherically driven and intrinsic variations for smoothed intra-annual bottom pressure signals at 10*10 degree resolution. [4] meanseason_timeseries.nc: Time series of mean seasonal bottom pressure signals from all 50 ensemble members over Agulhas Current region and Argentine Basin.",mds,True,findable,0,0,0,0,0,2021-09-24T19:20:00.000Z,2021-09-24T19:20:01.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4486376,GoldNet,Zenodo,2021,,Software,"Creative Commons Attribution 4.0 International,Open Access",Retrained BoxNet for gold bead masking in Warp.,mds,True,findable,0,0,0,0,0,2021-02-01T12:53:55.000Z,2021-02-01T12:53:55.000Z,cern.zenodo,cern,"cryo-et,boxnet,tomography","[{'subject': 'cryo-et'}, {'subject': 'boxnet'}, {'subject': 'tomography'}]",,
+10.5281/zenodo.4256801,An exploratory clinical trial on acceptance and commitment therapy as an adjunct to psychoeducational relaxation therapy for chronic pain.,Zenodo,2020,fr,Dataset,Restricted Access,The document contains the following documents used in the study: 1. Consent form 2. Dataset in the .sav format 3. The version of the questionnaire 4. Raw dataset in the .xlsx format 5. Workbook for the ACT treatment 5. Workbook for the PRT treatment,mds,True,findable,0,0,0,0,0,2020-11-12T11:01:44.000Z,2020-11-12T11:01:45.000Z,cern.zenodo,cern,"chronic pain,relaxation,psychotherapy,ACT,psychoeducation","[{'subject': 'chronic pain'}, {'subject': 'relaxation'}, {'subject': 'psychotherapy'}, {'subject': 'ACT'}, {'subject': 'psychoeducation'}]",,
+10.5281/zenodo.5373492,"FIG. 4 in Le gisement paléontologique villafranchien terminal de Peyrolles (Issoire, Puy-de-Dôme, France): résultats de nouvelles prospections",Zenodo,2006,,Image,"Creative Commons Zero v1.0 Universal,Open Access","FIG. 4. — Coupe stratigraphique du site de Peyrolles (120°N): F, fossile; cercle, prélèvement palynologique (modifié d'après Caron 2000). Coupe 1 sur la Figure 1.",mds,True,findable,0,0,0,0,0,2021-09-02T04:40:34.000Z,2021-09-02T04:40:35.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5061/dryad.060d2,"Data from: Genomics of the divergence continuum in an African plant biodiversity hotspot, I: drivers of population divergence in Restio capensis (Restionaceae)",Dryad,2014,en,Dataset,Creative Commons Zero v1.0 Universal,"Understanding the drivers of population divergence, speciation and species persistence is of great interest to molecular ecology, especially for species-rich radiations inhabiting the world’s biodiversity hotspots. The toolbox of population genomics holds great promise for addressing these key issues, especially if genomic data are analyzed within a spatially and ecologically explicit context. We have studied the earliest stages of the divergence continuum in the Restionaceae, a species-rich and ecologically important plant family of the Cape Floristic Region (CFR) of South Africa, using the widespread CFR endemic Restio capensis (L.) H.P. Linder & C.R. Hardy as an example. We studied diverging populations of this morphotaxon for chloroplast (cp) DNA sequences and >14 400 nuclear DNA polymorphisms from Restriction site Associated DNA (RAD) sequencing and analyzed the results jointly with spatial, climatic, and phytogeographic data, using a Bayesian generalized linear mixed modeling (GLMM) approach. The results indicate that population divergence across the extreme environmental mosaic of the CFR is driven by isolation-by-environment (IBE) rather than isolation-by-distance (IBD) for both neutral and non-neutral markers, consistent with genome hitchhiking during early stages of divergence. Mixed modeling of cpDNA and single highly divergent outlier loci from a Bayesian genome scan confirmed the predominant role of climate and pointed to additional drivers of divergence, such as drift and ecological agents of selection captured by phytogeographic zones. Our study demonstrates the usefulness of population genomics for disentangling the effects of IBD and IBE along the divergence continuum often found in species radiations across heterogeneous ecological landscapes.",mds,True,findable,289,57,1,1,0,2014-07-22T15:25:10.000Z,2014-07-22T15:25:11.000Z,dryad.dryad,dryad,"Restio capensis,Population Divergence,isolation by environment,Empirical Population Genetics,isolation by adaptation,Ppopulation divergence","[{'subject': 'Restio capensis'}, {'subject': 'Population Divergence'}, {'subject': 'isolation by environment'}, {'subject': 'Empirical Population Genetics'}, {'subject': 'isolation by adaptation'}, {'subject': 'Ppopulation divergence'}]",['24738988 bytes'],
+10.6084/m9.figshare.23575384,Additional file 9 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 8,mds,True,findable,0,0,0,0,0,2023-06-25T03:12:00.000Z,2023-06-25T03:12:01.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['87040 Bytes'],
+10.5061/dryad.3mv8v434,Data from: Tracking earthworm communities from soil DNA,Dryad,2011,en,Dataset,Creative Commons Zero v1.0 Universal,"Earthworms are known for their important role within the functioning of an ecosystem, and their diversity can be used as an indicator of ecosystem health. To date, earthworm diversity has been investigated through conventional extraction methods such as handsorting, soil washing or the application of a mustard solution. Such techniques are time-consuming and often difficult to apply. We showed that combining DNA metabarcoding and next generation sequencing facilitates the identification of earthworm species from soil samples. The first step of our experiments was to create a reference database of mitochondrial DNA (mtDNA) 16S gene for 14 earthworm species found in the French Alps. Using this database, we designed two new primer pairs targeting very short and informative DNA sequences (about 30 bp and 70 bp) that allow unambiguous species identification. Finally, we analyzed extracellular DNA taken from soil samples in two localities (two plots per locality, eight samples per plot). The two short metabarcode regions led to the identification of a total of eight earthworm species. The earthworm communities identified by the DNA-based approach appeared to be well-differentiated between the two localities, and are consistent with results derived from inventories collected using the handsorting method. The possibility of assessing earthworm communities from hundreds or even thousands of localities through the use of extracellular soil DNA will undoubtedly stimulate further ecological research on these organisms. Using the same DNA extracts, our study also illustrates the potential of environmental DNA as a tool to assess the diversity of other soil-dwelling animal taxa.",mds,True,findable,291,66,1,1,0,2011-11-11T16:03:03.000Z,2011-11-11T16:03:02.000Z,dryad.dryad,dryad,"Aporrectodea cupulifera,Octolasion cyaneum,Aporrectodea icterica,Octolasion tyrtaeum,Allobophora chlorotica,Aporrectodea rosea,Aporrectodea longa,Aporrectodea nocturna,Lumbricus castaneus,Population ecology,Lumbricus terrestris","[{'subject': 'Aporrectodea cupulifera'}, {'subject': 'Octolasion cyaneum'}, {'subject': 'Aporrectodea icterica'}, {'subject': 'Octolasion tyrtaeum'}, {'subject': 'Allobophora chlorotica'}, {'subject': 'Aporrectodea rosea'}, {'subject': 'Aporrectodea longa'}, {'subject': 'Aporrectodea nocturna'}, {'subject': 'Lumbricus castaneus'}, {'subject': 'Population ecology', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Lumbricus terrestris'}]",['19681195 bytes'],
+10.5061/dryad.sq67g,"Data from: Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria",Dryad,2018,en,Dataset,Creative Commons Zero v1.0 Universal,"Understanding the extreme variation among bacterial genomes remains an unsolved challenge in evolutionary biology, despite long-standing debate about the relative importance of natural selection, mutation, and random drift. A potentially important confounding factor is the variation in mutation rates between lineages and over evolutionary history, which has been documented in several species. Mutation accumulation experiments have shown that hypermutability can erode genomes over short timescales. These results, however, were obtained under conditions of extremely weak selection, casting doubt on their general relevance. Here, we circumvent this limitation by analyzing genomes from mutator populations that arose during a long-term experiment with Escherichia coli, in which populations have been adaptively evolving for >50,000 generations. We develop an analytical framework to quantify the relative contributions of mutation and selection in shaping genomic characteristics, and we validate it using genomes evolved under regimes of high mutation rates with weak selection (mutation accumulation experiments) and low mutation rates with strong selection (natural isolates). Our results show that, despite sustained adaptive evolution in the long-term experiment, the signature of selection is much weaker than that of mutational biases in mutator genomes. This finding suggests that relatively brief periods of hypermutability can play an outsized role in shaping extant bacterial genomes. Overall, these results highlight the importance of genomic draft, in which strong linkage limits the ability of selection to purge deleterious mutations. These insights are also relevant to other biological systems evolving under strong linkage and high mutation rates, including viruses and cancer cells.",mds,True,findable,430,100,1,1,0,2017-09-30T03:27:49.000Z,2017-09-30T03:27:51.000Z,dryad.dryad,dryad,,,['1138559234 bytes'],
+10.15454/d3odjm,"Colisa, the collection of ichthyological samples.",Portail Data INRAE,2018,,Dataset,,"The collection of ichthyological samples, Colisa, results from the merging of historical samples collected by 3 INRA units (U3E in Rennes, ECOBIOP in Saint Pée sur Nivelle and CARRTEL in Thonon les Bains) and AFB-INRA Pole Gest’Aqua. These samples come from long term monitoring and research activities conducted by these units and from a national catch declaration scheme (angling and professional fishery). It consists of more than 200000 scales or other tissue samples of fish from 26 species collected in France over 50 years. Beyond age and growth, these samples, carrying DNA, allow genetic characterization of individuals or populations. Via microchemistry, they alos allow to characterize the trophic status and the environmental conditions of life of animals. The conservation of these tissues allow to investigate retrospective changes (global and local). Colisa is a part of BRC4env, one of the 5 specialized pillars of the French Research Infrastructure ""Agricultural Resources for Research"" (AgroBRC-RARe, http://www.enseignementsup-recherche.gouv.fr/cid99437/ressources-agronomiques-pour-la-recherche-rare.html) federating BRCs: animals as CRB-Anim, plant as CRB-Plantes, micro-organisms as CIRM, environmental resources as BRC4Env, and forests as CRB-Forets. BRC4Env includes BRCs and collections hosted by INRA, IRD, CIRAD, CNRS, technical and higher education institutions. (2018-09-20).",mds,True,findable,150,0,0,1,0,2018-09-20T15:17:20.000Z,2018-09-20T15:18:21.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.3725624,Melting curve and phase relations of Fe-Ni alloys at high pressure and high temperature: implications for the Earth core composition,Zenodo,2020,,Dataset,"Academic Free License v3.0,Open Access",X-ray absorption data supporting results of the manuscript: Melting curve and phase relations of Fe-Ni alloys at high pressure and high temperature: implications for the Earth core composition submitted to Geophysical Research Letters,mds,True,findable,0,0,0,1,0,2020-03-24T11:18:04.000Z,2020-03-24T11:18:05.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5289201,"Veillon et al. (2020), Geoscientific Model Development : data and development",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","F.Veillon, M.Dumont, C.Amory, M.Fructus : A versatile method for computing optimized snow albedo from spectrally fixed radiative variables : VALHALLA v1.0, Geoscientific Model Development, in review, 2020. See README for a full description of the dataset content Please contact me at marie.dumont@meteo.fr if you need more details on the dataset",mds,True,findable,0,0,0,0,0,2021-08-27T12:25:31.000Z,2021-08-27T12:25:31.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5243268,Polish DBnary archive in original Lemon format,Zenodo,2021,pl,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Polish language edition, ranging from 23rd June 2014 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T10:56:50.000Z,2021-08-24T10:56:51.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.8060225,Ultrastructural details of resistance factors of the bacterial spore revealed by in situ cryo-electron tomography,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access",Cryo-electron tomograms reconstructed from data acquired on FIBM/SEM lamellae of <em>Bacillus subtilis</em> sporangia. Excel files containing measurements of various cellular ultrastructures observed by cryo-electron tomography and transmission electron microcopy of resin sections of B. subtilis sporangia.,mds,True,findable,0,0,0,0,0,2023-06-20T14:30:02.000Z,2023-06-20T14:30:03.000Z,cern.zenodo,cern,"Cryo-FIBM/electron tomography,cellular electron microscopy,sporulation,coat proteins","[{'subject': 'Cryo-FIBM/electron tomography'}, {'subject': 'cellular electron microscopy'}, {'subject': 'sporulation'}, {'subject': 'coat proteins'}]",,
+10.5281/zenodo.4292168,Model Counting Competition 2020: Full Instance Set,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The dataset contains all instances that the organizers of the competition received or collected during the preparation phase of the Model Counting Competition 2020. The dataset includes short benchmark descriptions by the submitters. For a more details, we refer to the report<br> Fichte, Hecher, Hamiti: The Model Counting Competition 2020 on ArXiv.",mds,True,findable,0,0,0,0,0,2020-11-27T08:19:42.000Z,2020-11-27T08:19:43.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23488967.v1,Additional file 1 of 3DVizSNP: a tool for rapidly visualizing missense mutations identified in high throughput experiments in iCn3D,figshare,2023,,Dataset,Creative Commons Attribution 4.0 International,"Additional file 1. A table summarizing the features of 3DVizSNP, PhyreRisk, MuPit, and VIVID.",mds,True,findable,0,0,0,0,0,2023-06-10T03:21:52.000Z,2023-06-10T03:21:53.000Z,figshare.ars,otjm,"Space Science,Medicine,Genetics,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,80699 Information Systems not elsewhere classified,FOS: Computer and information sciences,Cancer,Plant Biology","[{'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '80699 Information Systems not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Computer and information sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",['29184 Bytes'],
+10.5281/zenodo.6458203,Data supporting the preprint: Soot and charcoal as reservoirs of extracellular DNA,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","- Adsorption isotherms and kinetic data for adsorption of short and long DNA strands at soot and charcoal particles as a function of solution composition, pH and presence of competing compounds such as phosphates and alcohols. - Material characterisation analyses: XRD, XPS, Raman, water adsorption, zeta potential, mass titration",mds,True,findable,0,0,0,0,0,2022-04-13T13:36:48.000Z,2022-04-13T13:36:48.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7890953,Beamtime ES-1145,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains all the raw XRD data of beamtime ES-1145 at ESRF. A logbook describing samples, experimental conditions, scan numbers, etc. is included.",mds,True,findable,0,0,0,0,0,2023-05-03T12:22:46.000Z,2023-05-03T12:22:46.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.ttdz08ktn,Cold adaptation across the elevation gradient in an alpine butterfly species complex,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"1. Temperature acts as a major factor on the timing of activity and behaviour in butterflies, and it might represent a key driver of butterfly diversification along elevation gradients. Under this hypothesis, local adaptation should be found along the elevation gradient, with butterflies from high elevation populations able to remain active at lower ambient temperature than those from low elevation. 2. We recorded the warming-up rate and the thoracic temperature at take-off of 123 individuals of the Alpine butterfly species complex Coenonympha arcania - C. macromma - C. gardetta in controlled conditions. 3. Warming-up rate increased with elevation within C. arcania: high elevation males of C. arcania were able to warm-up more quickly, as compared to low elevation ones. 4. High elevation C. gardetta had a darker underwing pattern than low elevation ones. This high-elevation species was significantly smaller (lower weight and wing surface) than the two other species, and had a faster warming up rate. 5. Our results suggest that the ability to warm-up quickly and to take-flight at a high body temperature evolved adaptively in the high-altitude C. gardetta, and that low temperature at high altitude may explain the absence there of C. arcania, while the hybrid nature of C. macromma is probably the explanation of its elevation overlap with both other species, and its local replacement of C. gardetta.",mds,True,findable,157,5,0,1,0,2020-04-06T17:11:27.000Z,2020-04-06T17:11:30.000Z,dryad.dryad,dryad,"Thorax temperature,Coenonympha arcania,Coenonympha macromma,Coenonympha gardetta","[{'subject': 'Thorax temperature'}, {'subject': 'Coenonympha arcania'}, {'subject': 'Coenonympha macromma'}, {'subject': 'Coenonympha gardetta'}]",['271993187 bytes'],
+10.5281/zenodo.7389281,Ammonia Binding Energy distribution at Interstellar Icy Grains,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Zip file containing all the structures and input obtained in our article <em>ACS Earth Space Chem.</em> 2022, 6, 6, 1514–1526, https://doi.org/10.1021/acsearthspacechem.2c00040 To easily handle all these structures an online interactive page is created: https://tinaccil.github.io/Jmol_BE_NH3_visualization/",mds,True,findable,0,0,0,1,0,2022-12-02T09:44:59.000Z,2022-12-02T09:45:00.000Z,cern.zenodo,cern,"Adsorption, Ammonia, Grain, Molecular modeling, Molecules, Astrochemistry","[{'subject': 'Adsorption, Ammonia, Grain, Molecular modeling, Molecules, Astrochemistry'}]",,
+10.25384/sage.22573164,sj-docx-1-dhj-10.1177_20552076231167009 - Supplemental material for Impact of a telerehabilitation programme combined with continuous positive airway pressure on symptoms and cardiometabolic risk factors in obstructive sleep apnea patients,SAGE Journals,2023,,Text,Creative Commons Attribution Non Commercial No Derivatives 4.0 International,"Supplemental material, sj-docx-1-dhj-10.1177_20552076231167009 for Impact of a telerehabilitation programme combined with continuous positive airway pressure on symptoms and cardiometabolic risk factors in obstructive sleep apnea patients by François Bughin, Monique Mendelson, Dany Jaffuel, Jean-Louis Pépin, Frédéric Gagnadoux, Frédéric Goutorbe, Beatriz Abril, Bronia Ayoub, Alexandre Aranda, Khuder Alagha, Pascal Pomiès, François Roubille, Jacques Mercier, Nicolas Molinari, Yves Dauvilliers, Nelly Héraud and M Hayot in Digital Health",mds,True,findable,0,0,0,0,0,2023-04-07T00:07:22.000Z,2023-04-07T00:07:22.000Z,figshare.sage,sage,"111708 Health and Community Services,FOS: Health sciences,Cardiology,110306 Endocrinology,FOS: Clinical medicine,110308 Geriatrics and Gerontology,111099 Nursing not elsewhere classified,111299 Oncology and Carcinogenesis not elsewhere classified,111702 Aged Health Care,111799 Public Health and Health Services not elsewhere classified,99999 Engineering not elsewhere classified,FOS: Other engineering and technologies,Anthropology,FOS: Sociology,200299 Cultural Studies not elsewhere classified,FOS: Other humanities,89999 Information and Computing Sciences not elsewhere classified,FOS: Computer and information sciences,150310 Organisation and Management Theory,FOS: Economics and business,Science Policy,160512 Social Policy,FOS: Political science,Sociology","[{'subject': '111708 Health and Community Services', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cardiology'}, {'subject': '110306 Endocrinology', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '110308 Geriatrics and Gerontology', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111099 Nursing not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111299 Oncology and Carcinogenesis not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111702 Aged Health Care', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111799 Public Health and Health Services not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '99999 Engineering not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Other engineering and technologies', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Anthropology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '200299 Cultural Studies not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Other humanities', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '89999 Information and Computing Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Computer and information sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '150310 Organisation and Management Theory', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Economics and business', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '160512 Social Policy', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Political science', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Sociology'}]",['778615 Bytes'],
+10.5281/zenodo.4761359,"Fig. 93 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access",Fig. 93. Phylogenetic tree of Dictyogenus species. GenBank accession numbers of sequences are indicated before the code of species (start with MK).,mds,True,findable,0,0,0,0,0,2021-05-14T07:53:03.000Z,2021-05-14T07:53:04.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.6084/m9.figshare.22610681.v1,Additional file 1 of Efficacy and auditory biomarker analysis of fronto-temporal transcranial direct current stimulation (tDCS) in targeting cognitive impairment associated with recent-onset schizophrenia: study protocol for a multicenter randomized double-blind sham-controlled trial,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1. Ethical approval.,mds,True,findable,0,0,0,0,0,2023-04-13T12:04:22.000Z,2023-04-13T12:04:23.000Z,figshare.ars,otjm,"Medicine,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,69999 Biological Sciences not elsewhere classified,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['1737833 Bytes'],
+10.5061/dryad.4j0zpc8h2,Data for: A spatially explicit trait-based approach uncovers changes in assembly processes under warming,Dryad,2023,en,Dataset,Creative Commons Zero v1.0 Universal,"The re-assembly of plant communities during climate warming depends on several concurrent processes. Here we present a novel framework that integrates spatially explicit sampling, plant trait information and a warming experiment to quantify shifts in these assembly processes. By accounting for spatial distance between individuals, our framework allows separation of potential signals of environmental filtering from those of different types of competition. When applied to an elevational transplant experiment in the French Alps, we found common signals of environmental filtering and competition in all communities. Signals of environmental filtering were generally stronger in alpine than in subalpine control communities, and warming reduced this filter. Competition signals depended on treatments and traits: Symmetrical competition was dominant in control and warmed alpine communities, while hierarchical competition was present in subalpine communities. Our study highlights how distance dependent frameworks can contribute to a better understanding of transient re-assembly dynamics during environmental change.",mds,True,findable,120,14,0,0,0,2023-03-03T10:08:24.000Z,2023-03-03T10:08:24.000Z,dryad.dryad,dryad,"FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences,Community assembly,reciprocal transplant,environmental filtering,hierarchical competition,symmetric competition,spatial associations,warming experiment,Climate change,alpine grasslands","[{'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Community assembly', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'reciprocal transplant'}, {'subject': 'environmental filtering'}, {'subject': 'hierarchical competition'}, {'subject': 'symmetric competition'}, {'subject': 'spatial associations'}, {'subject': 'warming experiment'}, {'subject': 'Climate change', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'alpine grasslands'}]",['5357448510 bytes'],
+10.5281/zenodo.8269356,Microdialysis on-chip crystallization of HEWL and Thaumatin and in situ X-ray diffraction studies,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This deposition includes the mtz and pdb files for HEWL and Thaumatin crystal structures included in the article ""Microdialysis on-chip crystallization of soluble and membrane proteins with the MicroCrys platform and in situ X-ray diffraction case studies"".",mds,True,findable,0,0,0,0,0,2023-08-21T14:03:06.000Z,2023-08-21T14:03:06.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.4n5929c,Data from: A quantitative proteomic analysis of cofilin phosphorylation in myeloid cells and its modulation using the LIM kinase inhibitor Pyr1,Dryad,2018,en,Dataset,Creative Commons Zero v1.0 Universal,"LIM kinases are located at a strategic crossroad, downstream of several signaling pathways and upstream of effectors such as microtubules and the actin cytoskeleton. Cofilin is the only LIM kinases substrate that is well described to date, and its phosphorylation on serine 3 by LIM kinases controls cofilin actin-severing activity. Consequently, LIM kinases inhibition leads to actin cytoskeleton disorganization and blockade of cell motility, which makes this strategy attractive in anticancer treatments. LIMK has also been reported to be involved in pathways that are deregulated in hematologic malignancies, with little information regarding cofilin phosphorylation status. We have used proteomic approaches to investigate quantitatively and in detail the phosphorylation status of cofilin in myeloid tumor cell lines of murine and human origin. Our results show that under standard conditions, only a small fraction (10 to 30% depending on the cell line) of cofilin is phosphorylated (including serine 3 phosphorylation). In addition, after a pharmacological inhibition of LIM kinases, a residual cofilin phosphorylation is observed on serine 3. Interestingly, this 2D gel based proteomic study identified new phosphorylation sites on cofilin, such as threonine 63, tyrosine 82 and serine 108.",mds,True,findable,385,33,1,1,0,2018-12-12T16:55:02.000Z,2018-12-12T16:55:03.000Z,dryad.dryad,dryad,"Lim kinases,Leukemia,Mus musculus,cofilin,Proteomics,Homo Sapiens,Phosphorylation","[{'subject': 'Lim kinases'}, {'subject': 'Leukemia', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Mus musculus'}, {'subject': 'cofilin'}, {'subject': 'Proteomics', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Homo Sapiens'}, {'subject': 'Phosphorylation', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['130700552 bytes'],
+10.5281/zenodo.5841588,Relocated earthquakes along the Reeves-Pecos County Line in the Delaware Basin,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The files contain the relocated earthquakes in the study ""On the Depth of Earthquakes in the Delaware Basin – A Case Study along the Reeves-Pecos County Line"" by Yixiao Sheng, Karissa S. Pepin and William L. Ellsworth. The manuscript has been submitted to <em>The Seismic Record</em>.",mds,True,findable,0,0,0,1,0,2022-01-12T19:38:52.000Z,2022-01-12T19:38:52.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3361544,Exoplanet imaging data challenge,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Datasets for the Exoplanet imaging data challenge (https://exoplanet-imaging-challenge.github.io).,mds,True,findable,4,0,0,0,0,2019-08-06T13:28:55.000Z,2019-08-06T13:28:55.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23575366.v1,Additional file 3 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 2,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:47.000Z,2023-06-25T03:11:48.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['28672 Bytes'],
+10.5281/zenodo.5788695,"Buoyancy versus local stress field control on the velocity of magma propagation: insight from analog and numerical modelling, Supporting Data",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Experimental data and numerical codes used in the manuscript ""Buoyancy versus local stress field control on the velocity of magma propagation: insight from analog and numerical modelling"" by V. Pinel, S. Furst, F. Maccaferri and D. Smittarello.",mds,True,findable,0,0,0,0,0,2021-12-17T13:17:01.000Z,2021-12-17T13:17:02.000Z,cern.zenodo,cern,"Experimental data, numerical codes for fluid-filled crack propagation","[{'subject': 'Experimental data, numerical codes for fluid-filled crack propagation'}]",,
+10.6084/m9.figshare.c.6583718.v1,TRansfusion strategies in Acute brain INjured patients (TRAIN): a prospective multicenter randomized interventional trial protocol,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Although blood transfusions can be lifesaving in severe hemorrhage, they can also have potential complications. As anemia has also been associated with poor outcomes in critically ill patients, determining an optimal transfusion trigger is a real challenge for clinicians. This is even more important in patients with acute brain injury who were not specifically evaluated in previous large randomized clinical trials. Neurological patients may be particularly sensitive to anemic brain hypoxia because of the exhausted cerebrovascular reserve, which adjusts cerebral blood flow to tissue oxygen demand. Methods We described herein the methodology of a prospective, multicenter, randomized, pragmatic trial comparing two different strategies for red blood cell transfusion in patients with acute brain injury: a “liberal†strategy in which the aim is to maintain hemoglobin (Hb) concentrations greater than 9 g/dL and a “restrictive†approach in which the aim is to maintain Hb concentrations greater than 7 g/dL. The target population is patients suffering from traumatic brain injury (TBI), subarachnoid hemorrhage (SAH), or intracerebral hemorrhage (ICH). The primary outcome is the unfavorable neurological outcome, evaluated using the extended Glasgow Outcome Scale (eGOS) of 1–5 at 180 days after the initial injury. Secondary outcomes include, among others, 28-day survival, intensive care unit (ICU) and hospital lengths of stay, the occurrence of extra-cerebral organ dysfunction/failure, and the development of any infection or thromboembolic events. The estimated sample size is 794 patients to demonstrate a reduction in the primary outcome from 50 to 39% between groups (397 patients in each arm). The study was initiated in 2016 in several ICUs and will be completed in December 2022. Discussion This trial will assess the impact of a liberal versus conservative strategy of blood transfusion in a large cohort of critically ill patients with a primary acute brain injury. The results of this trial will help to improve blood product and transfusion use in this specific patient population and will provide additional data in some subgroups of patients at high risk of brain ischemia, such as those with intracranial hypertension or cerebral vasospasm. Trial registration ClinicalTrials.gov NCT02968654.",mds,True,findable,0,0,0,0,0,2023-04-13T11:34:57.000Z,2023-04-13T11:34:57.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Neuroscience,Biotechnology,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.7446362,silx-kit/silx: 1.1.2: 2022/12/16,Zenodo,2022,,Software,Open Access,"This is a bug fix version. What's Changed <code>silx.gui</code>: Fixed support of <code>PySide</code> 6.4 enums (PR #3737, #3738) Fixed OpenGL version parsing (PR #3733, #3738) <code>silx.gui.plot</code>: Fixed issue when <code>PlotWidget</code> has a size of 0 (PR #3736, #3738) Fixed reset of interaction when closing mask tool (PR #3735, #3738) Miscellaneous: Updated Debian packaging (PR #3732, #3738) <strong>Full Changelog</strong>: https://github.com/silx-kit/silx/compare/v1.1.1...v1.1.2",mds,True,findable,0,0,0,0,0,2022-12-16T10:23:45.000Z,2022-12-16T10:23:46.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3771710,"Companion for ""Measuring Phenology Uncertainty with Large Scale Image Processing""",Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is the software and dataset companion for the paper entitled ""Measuring Phenology Uncertainty with Large Scale Image Processing"". Further instructions can be found in the README.org file.",mds,True,findable,0,0,0,0,0,2020-06-12T14:18:08.000Z,2020-06-12T14:18:09.000Z,cern.zenodo,cern,"Phenology analysis,Parallel Workflow,Phenological visualization,Mathematical modeling,Uncertainty Quantification","[{'subject': 'Phenology analysis'}, {'subject': 'Parallel Workflow'}, {'subject': 'Phenological visualization'}, {'subject': 'Mathematical modeling'}, {'subject': 'Uncertainty Quantification'}]",,
+10.5061/dryad.93n5r,Data from: Decomposing changes in phylogenetic and functional diversity over space and time,Dryad,2015,en,Dataset,Creative Commons Zero v1.0 Universal,"1. The α, β, γ diversity decomposition methodology is commonly used to investigate changes in diversity over space or time but rarely conjointly. However, with the ever-increasing availability of large-scale biodiversity monitoring data, there is a need for a sound methodology capable of simultaneously accounting for spatial and temporal changes in diversity. 2. Using the properties of Chao's index, we adapted Rao's framework of diversity decomposition between orthogonal dimensions to a multiplicative α, β, γ decomposition of functional or phylogenetic diversity over space and time, thereby combining their respective properties. We also developed guidelines for interpreting both temporal and spatial β-diversities and their interaction. 3. We characterised the range of β-diversity estimates and their relationship to the nested decomposition of diversity. Using simulations, we empirically demonstrated that temporal and spatial β-diversities are independent from each other and from α and γ-diversities when the study design is balanced, but not otherwise. Furthermore, we showed that the interaction term between the temporal and the spatial β-diversities lacked such properties. 4. We illustrated our methodology with a case study of the spatio-temporal dynamics of functional diversity in bird assemblages in four regions of France. Based on these data, our method makes it possible to discriminate between regions experiencing different diversity changes in time. Our methodology may therefore be valuable for comparing diversity changes over space and time using large-scale datasets of repeated surveys.",mds,True,findable,296,24,1,1,0,2014-10-17T15:27:54.000Z,2014-10-17T15:27:56.000Z,dryad.dryad,dryad,"Apus pallidus,Luscinia svecica,Merops apiaster,Falco subbuteo,Sterna sandvicensis,Passer montanus,Lanius excubator subsp. meridionalis,Lanius excubitor,Lagopus mutus,Charadrius alexandrinus,Cinclus cinclus,Phylloscopus trochilus,Sturnus unicolor,Scolopax rusticola,Streptopelia turtur,Emberiza hortulana,Acrocephalus arundinaceus,Carduelis cannabina,Hirundo daurica,Buteo buteo,Ardea purpurea,Asio otus,Circaetus gallicus,Netta rufina,Milvus milvus,Parus cristatus,Jynx torquilla,Parus ater,Circus aeruginosus,Lanius senator,Acrocephalus schoenobaenus,Larus melanocephalus,Athene noctua,Dryocopus martius,Miliaria calandra,Lanius collurio,Sylvia hortensis,Cygnus olor,Erithacus rubecula,Corvus corax,Picus canus,Tyto alba,Phoenicopterus ruber,Pyrrhula pyrrhula,Motacilla flava,Prunella collaris,Delichon urbica,Luscinia megarhynchos,Haematopus ostralegus,Regulus ignicapillus,Larus ridibundus,Alectoris graeca,Anas querquedula,Tringa totanus,Perdix perdix,Turdus philomelos,Accipiter nisus,Phoenicurus phoenicurus,Sitta europaea,Cisticola juncidis,Troglodytes troglodytes,Carduelis spinus,Emberiza citrinella,Turdus merula,Anthus pratensis,Larus argentatus,Streptopelia decaocto,Nucifraga caryocatactes,Panurus biarmicus,Corvus frugilegus,Fringilla coelebs,Alauda arvensis,Phoenicurus ochruros,Aythya ferina,Clamator glandarius,Carduelis carduelis,Loxia curvirostra,Bonasa bonasia,Himantopus himantopus,Hippolais icterina,Pyrrhocorax pyrrhocorax,Prunella modularis,Carduelis flammea,Apus melba,Bubulcus ibis,Alcedo atthis,Parus major,Alectoris rufa,Dendrocopos minor,Sylvia conspicillata,Vanellus vanellus,Monticola solitarius,Accipiter gentilis,Dendrocopos major,Calandrella brachydactyla,Emberiza cia,Saxicola rubetra,Falco peregrinus,Garrulus glandarius,Columba palumbus,Picus viridis,Ardea cinerea,Aythya fuligula,Burhinus oedicnemus,Crex Crex,Podiceps cristatus,Riparia riparia,Oenanthe hispanica,Anthus spinoletta,Bubo bubo,Locustella luscinioides,Pyrrhocorax graculus,Cuculus canorus,Acrocephalus palustris,Chlidonias hybridus,Anthus campestris,Cettia cetti,Larus marinus,Milvus migrans,Anthus trivialis,Pica pica,Strix aluco,Tetrax tetrax,Upupa epops,Fulica atra,Gallinago gallinago,Passer domesticus,Porzana porzana,Coracias garrulus,Sylvia borin,Phylloscopus bonelli,Sylvia curruca,Acrocephalus scirpaceus,Hippolais polyglotta,Lullula arborea,Galerida cristata,Certhia brachydactyla,Certhia familiaris,Otus scops,Anser anser,Circus pygargus,Motacilla cinerea,Serinus serinus,Gyps fulvus,Saxicola torquata,Emberiza schoeniclus,Locustella naevia,Motacilla alba,Recurvirostra avosetta,Sylvia communis,Apus apus,Circus cyaneus,Casmerodius albus,Hirundo rustica,Phalacrocorax carbo,Gallinula chloropus,Ardeola ralloides,Coturnix coturnix,Larus graellsii,Limosa limosa,Platalea leucorodia,Sturnus vulgaris,communities,Turdus viscivorus,Parus palustris,Egretta garzetta,Oriolus oriolus,Rallus aquaticus,Sylvia atricapilla,Muscicapa striata,Phasianus colchicus,Anas crecca,Parus montanus,Turdus torquatus,Sylvia cantillans,Corvus monedula,Aegithalos caudatus,Botaurus stellaris,Ixobrychus minutus,Serinus citrinella,Petronia petronia,Regulus regulus,Corvus cornix,Falco naumanni,Numenius arquata,Columba oenas,Nycticorax nycticorax,Gelochelidon nilotica,Hieraaetus pennatus,Phylloscopus sibilatrix,Ptyonoprogne rupestris,Oenanthe oenanthe,Sterna albifrons,Ciconia ciconia,Ficedula hypoleuca,Phylloscopus collybita,Sylvia melanocephala,Monticola saxatilis,Coccothraustes coccothraustes,Tachybaptus ruficollis,Falco tinnunculus,Melanocorypha calandra,Dendrocopos medius,Pandion haliaetus,Tadorna tadorna,Columba livia,Pernis apivorus,Turdus pilaris,Sylvia undata,Caprimulgus europaeus,Charadrius dubius,Parus caeruleus,Anas platyrhynchos,Tichodroma muraria,Chloris chloris,Emberiza cirlus,Sterna hirundo","[{'subject': 'Apus pallidus'}, {'subject': 'Luscinia svecica'}, {'subject': 'Merops apiaster'}, {'subject': 'Falco subbuteo'}, {'subject': 'Sterna sandvicensis'}, {'subject': 'Passer montanus'}, {'subject': 'Lanius excubator subsp. meridionalis'}, {'subject': 'Lanius excubitor'}, {'subject': 'Lagopus mutus'}, {'subject': 'Charadrius alexandrinus'}, {'subject': 'Cinclus cinclus'}, {'subject': 'Phylloscopus trochilus'}, {'subject': 'Sturnus unicolor'}, {'subject': 'Scolopax rusticola'}, {'subject': 'Streptopelia turtur'}, {'subject': 'Emberiza hortulana'}, {'subject': 'Acrocephalus arundinaceus'}, {'subject': 'Carduelis cannabina'}, {'subject': 'Hirundo daurica'}, {'subject': 'Buteo buteo'}, {'subject': 'Ardea purpurea'}, {'subject': 'Asio otus'}, {'subject': 'Circaetus gallicus'}, {'subject': 'Netta rufina'}, {'subject': 'Milvus milvus'}, {'subject': 'Parus cristatus'}, {'subject': 'Jynx torquilla'}, {'subject': 'Parus ater'}, {'subject': 'Circus aeruginosus'}, {'subject': 'Lanius senator'}, {'subject': 'Acrocephalus schoenobaenus'}, {'subject': 'Larus melanocephalus'}, {'subject': 'Athene noctua'}, {'subject': 'Dryocopus martius'}, {'subject': 'Miliaria calandra'}, {'subject': 'Lanius collurio'}, {'subject': 'Sylvia hortensis'}, {'subject': 'Cygnus olor'}, {'subject': 'Erithacus rubecula'}, {'subject': 'Corvus corax'}, {'subject': 'Picus canus'}, {'subject': 'Tyto alba'}, {'subject': 'Phoenicopterus ruber'}, {'subject': 'Pyrrhula pyrrhula'}, {'subject': 'Motacilla flava'}, {'subject': 'Prunella collaris'}, {'subject': 'Delichon urbica'}, {'subject': 'Luscinia megarhynchos'}, {'subject': 'Haematopus ostralegus'}, {'subject': 'Regulus ignicapillus'}, {'subject': 'Larus ridibundus'}, {'subject': 'Alectoris graeca'}, {'subject': 'Anas querquedula'}, {'subject': 'Tringa totanus'}, {'subject': 'Perdix perdix'}, {'subject': 'Turdus philomelos'}, {'subject': 'Accipiter nisus'}, {'subject': 'Phoenicurus phoenicurus'}, {'subject': 'Sitta europaea'}, {'subject': 'Cisticola juncidis'}, {'subject': 'Troglodytes troglodytes'}, {'subject': 'Carduelis spinus'}, {'subject': 'Emberiza citrinella'}, {'subject': 'Turdus merula'}, {'subject': 'Anthus pratensis'}, {'subject': 'Larus argentatus'}, {'subject': 'Streptopelia decaocto'}, {'subject': 'Nucifraga caryocatactes'}, {'subject': 'Panurus biarmicus'}, {'subject': 'Corvus frugilegus'}, {'subject': 'Fringilla coelebs'}, {'subject': 'Alauda arvensis'}, {'subject': 'Phoenicurus ochruros'}, {'subject': 'Aythya ferina'}, {'subject': 'Clamator glandarius'}, {'subject': 'Carduelis carduelis'}, {'subject': 'Loxia curvirostra'}, {'subject': 'Bonasa bonasia'}, {'subject': 'Himantopus himantopus'}, {'subject': 'Hippolais icterina'}, {'subject': 'Pyrrhocorax pyrrhocorax'}, {'subject': 'Prunella modularis'}, {'subject': 'Carduelis flammea'}, {'subject': 'Apus melba'}, {'subject': 'Bubulcus ibis'}, {'subject': 'Alcedo atthis'}, {'subject': 'Parus major'}, {'subject': 'Alectoris rufa'}, {'subject': 'Dendrocopos minor'}, {'subject': 'Sylvia conspicillata'}, {'subject': 'Vanellus vanellus'}, {'subject': 'Monticola solitarius'}, {'subject': 'Accipiter gentilis'}, {'subject': 'Dendrocopos major'}, {'subject': 'Calandrella brachydactyla'}, {'subject': 'Emberiza cia'}, {'subject': 'Saxicola rubetra'}, {'subject': 'Falco peregrinus'}, {'subject': 'Garrulus glandarius'}, {'subject': 'Columba palumbus'}, {'subject': 'Picus viridis'}, {'subject': 'Ardea cinerea'}, {'subject': 'Aythya fuligula'}, {'subject': 'Burhinus oedicnemus'}, {'subject': 'Crex Crex'}, {'subject': 'Podiceps cristatus'}, {'subject': 'Riparia riparia'}, {'subject': 'Oenanthe hispanica'}, {'subject': 'Anthus spinoletta'}, {'subject': 'Bubo bubo'}, {'subject': 'Locustella luscinioides'}, {'subject': 'Pyrrhocorax graculus'}, {'subject': 'Cuculus canorus'}, {'subject': 'Acrocephalus palustris'}, {'subject': 'Chlidonias hybridus'}, {'subject': 'Anthus campestris'}, {'subject': 'Cettia cetti'}, {'subject': 'Larus marinus'}, {'subject': 'Milvus migrans'}, {'subject': 'Anthus trivialis'}, {'subject': 'Pica pica'}, {'subject': 'Strix aluco'}, {'subject': 'Tetrax tetrax'}, {'subject': 'Upupa epops'}, {'subject': 'Fulica atra'}, {'subject': 'Gallinago gallinago'}, {'subject': 'Passer domesticus'}, {'subject': 'Porzana porzana'}, {'subject': 'Coracias garrulus'}, {'subject': 'Sylvia borin'}, {'subject': 'Phylloscopus bonelli'}, {'subject': 'Sylvia curruca'}, {'subject': 'Acrocephalus scirpaceus'}, {'subject': 'Hippolais polyglotta'}, {'subject': 'Lullula arborea'}, {'subject': 'Galerida cristata'}, {'subject': 'Certhia brachydactyla'}, {'subject': 'Certhia familiaris'}, {'subject': 'Otus scops'}, {'subject': 'Anser anser'}, {'subject': 'Circus pygargus'}, {'subject': 'Motacilla cinerea'}, {'subject': 'Serinus serinus'}, {'subject': 'Gyps fulvus'}, {'subject': 'Saxicola torquata'}, {'subject': 'Emberiza schoeniclus'}, {'subject': 'Locustella naevia'}, {'subject': 'Motacilla alba'}, {'subject': 'Recurvirostra avosetta'}, {'subject': 'Sylvia communis'}, {'subject': 'Apus apus'}, {'subject': 'Circus cyaneus'}, {'subject': 'Casmerodius albus'}, {'subject': 'Hirundo rustica'}, {'subject': 'Phalacrocorax carbo'}, {'subject': 'Gallinula chloropus'}, {'subject': 'Ardeola ralloides'}, {'subject': 'Coturnix coturnix'}, {'subject': 'Larus graellsii'}, {'subject': 'Limosa limosa'}, {'subject': 'Platalea leucorodia'}, {'subject': 'Sturnus vulgaris'}, {'subject': 'communities'}, {'subject': 'Turdus viscivorus'}, {'subject': 'Parus palustris'}, {'subject': 'Egretta garzetta'}, {'subject': 'Oriolus oriolus'}, {'subject': 'Rallus aquaticus'}, {'subject': 'Sylvia atricapilla'}, {'subject': 'Muscicapa striata'}, {'subject': 'Phasianus colchicus'}, {'subject': 'Anas crecca'}, {'subject': 'Parus montanus'}, {'subject': 'Turdus torquatus'}, {'subject': 'Sylvia cantillans'}, {'subject': 'Corvus monedula'}, {'subject': 'Aegithalos caudatus'}, {'subject': 'Botaurus stellaris'}, {'subject': 'Ixobrychus minutus'}, {'subject': 'Serinus citrinella'}, {'subject': 'Petronia petronia'}, {'subject': 'Regulus regulus'}, {'subject': 'Corvus cornix'}, {'subject': 'Falco naumanni'}, {'subject': 'Numenius arquata'}, {'subject': 'Columba oenas'}, {'subject': 'Nycticorax nycticorax'}, {'subject': 'Gelochelidon nilotica'}, {'subject': 'Hieraaetus pennatus'}, {'subject': 'Phylloscopus sibilatrix'}, {'subject': 'Ptyonoprogne rupestris'}, {'subject': 'Oenanthe oenanthe'}, {'subject': 'Sterna albifrons'}, {'subject': 'Ciconia ciconia'}, {'subject': 'Ficedula hypoleuca'}, {'subject': 'Phylloscopus collybita'}, {'subject': 'Sylvia melanocephala'}, {'subject': 'Monticola saxatilis'}, {'subject': 'Coccothraustes coccothraustes'}, {'subject': 'Tachybaptus ruficollis'}, {'subject': 'Falco tinnunculus'}, {'subject': 'Melanocorypha calandra'}, {'subject': 'Dendrocopos medius'}, {'subject': 'Pandion haliaetus'}, {'subject': 'Tadorna tadorna'}, {'subject': 'Columba livia'}, {'subject': 'Pernis apivorus'}, {'subject': 'Turdus pilaris'}, {'subject': 'Sylvia undata'}, {'subject': 'Caprimulgus europaeus'}, {'subject': 'Charadrius dubius'}, {'subject': 'Parus caeruleus'}, {'subject': 'Anas platyrhynchos'}, {'subject': 'Tichodroma muraria'}, {'subject': 'Chloris chloris'}, {'subject': 'Emberiza cirlus'}, {'subject': 'Sterna hirundo'}]",['75236 bytes'],
+10.5281/zenodo.8104792,"Migration of mechanical perturbations estimated by seismic coda wave interferometry during the 2018 pre-eruptive period at Kīlauea volcano, Hawaii : Noise Cross-correlation Functions, Seismic catalog, and GNSS data",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","ARCHIVE_NCFs_KILAUEA_2018.zip : Compress folder with (1) the daily noise cross-correlation functions (in MSEED format) of the station pairs used in the paper and (2) the one hour noise cross-correlation functions (in H5 format) of the station pairs used in the figure 9 of the paper. Code_Data_HVO.ipynb : Code to download the seismic data, available on IRIS, used in this paper. GPS_data_AHUP.zip : Compress folder with the daily GPS data of the station AHUP used in the paper [Year, Month, Day, Day_of_the_year, Second_of_the_day, East_comp(mm), North_comp(mm), Vertical_comp(mm), Sig_East_comp, Sig_North_comp, Sig_Vertical_comp]. Radial_tilt_UWD.txt : Daily radial tilt measurement of the tiltmeter UWD [Year, Month, Day, Radial_tilt(µrad)]. Seismic_stations_Kilauea.txt : Name code and location of the seismic stations used in the paper [Station_code, Longitude, Latitude]. Seismicity_Catalog_Kilauea_2018_USGS.txt : Seismic catalog from USGS used in the paper [Date_Time, Latitude, Longitude, Depth, Magnitude].",mds,True,findable,0,0,0,0,0,2023-07-01T21:48:33.000Z,2023-07-01T21:48:33.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.ttdz08m16,Environmental DNA highlights the influence of salinity and agricultural run-off on coastal fish assemblages in the Great Barrier Reef region,Dryad,2023,en,Dataset,Creative Commons Zero v1.0 Universal,"Agricultural run-off in Australia’s Mackay-Whitsunday region is a major source of nutrient and pesticide pollution to the coastal and inshore ecosystems of the Great Barrier Reef. While the effects of run-off are well documented for the region’s coral and seagrass habitats, the ecological impacts on estuaries, the direct recipients of run-off, are less known. This is particularly true for fish communities, which are shaped by the physico-chemical properties of the coastal waterways that vary greatly in tropical regions. To address this knowledge gap, we used environmental DNA (eDNA) metabarcoding to examine teleost and elasmobranch fish assemblages at four locations (three estuaries and a harbour) subjected to varying levels of agricultural run-off during a wet and dry season. Pesticide and nutrient concentrations were markedly lower during the sampled dry season. With the influx of freshwater and agricultural run-off during the wet season, teleost and elasmobranch taxa richness significantly decreased in all three estuaries, along with pronounced changes in fish community composition which were largely associated with environmental variables (particularly salinity). In contrast, the nearby Mackay Harbour exhibited a far more stable community structure, with no marked changes in fish assemblages observed between the sampled seasons. Within the wet season, differing compositions of fish communities were observed among the four sampled locations, with this variation being significantly correlated with environmental variables (salinity, chlorophyll, DOC) and contaminants from agricultural run-off, i.e., nutrients (nitrogen and phosphorus) and pesticides. Historically contaminated and relatively unimpacted estuaries each demonstrated distinct fish communities, reflecting their associated catchment use. Our findings emphasise that while seasonal effects (e.g., changes in salinity) play a key role in shaping the community structure of estuarine fish in this region, agricultural contaminants (nutrients and pesticides) are also important contributors in some systems.",mds,True,findable,21,1,0,0,0,2023-09-22T22:57:33.000Z,2023-09-22T22:57:33.000Z,dryad.dryad,dryad,"eDNA,chemical analyses,species matrix,FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'eDNA'}, {'subject': 'chemical analyses'}, {'subject': 'species matrix'}, {'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['146859 bytes'],
+10.5281/zenodo.4759499,"Figs. 34-39 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 34-39. Terminalias of the imago of Protonemura algirica bejaiana ssp. n. 34: male terminalia, dorsal view; 35: male terminalia, ventral view; 36: male terminalia, lateral view; 37: male paraproct, ventrolateral view; 38: female pregenital and subgenital plates, and vaginal lobes, ventral view; 39: female pregenital and subgenital plates, and vaginal lobes, lateral view (scales 0.5 mm; scale 1: Fig. 37, scale 2: Figs. 34-36, 38-39).",mds,True,findable,0,0,2,0,0,2021-05-14T02:25:03.000Z,2021-05-14T02:25:04.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5061/dryad.c1jr3,Data from: Relationship between spectral characteristics of spontaneous postural sway and motion sickness susceptibility,Dryad,2016,en,Dataset,Creative Commons Zero v1.0 Universal,"Motion sickness (MS) usually occurs for a narrow band of frequencies of the imposed oscillation. It happens that this frequency band is close to that which are spontaneously produced by postural sway during natural stance. This study examined the relationship between reported susceptibility to motion sickness and postural control. The hypothesis is that the level of MS can be inferred from the shape of the Power Spectral Density (PSD) profile of spontaneous sway, as measured by the displacement of the center of mass during stationary, upright stance. In Experiment 1, postural fluctuations while standing quietly were related to MS history for inertial motion. In Experiment 2, postural stability measures registered before the onset of a visual roll movement were related to MS symptoms following the visual stimulation. Study of spectral characteristics in postural control showed differences in the distribution of energy along the power spectrum of the antero-posterior sway signal. Participants with MS history provoked by exposure to inertial motion showed a stronger contribution of the high frequency components of the sway signal. When MS was visually triggered, sick participants showed more postural sway in the low frequency range. The results suggest that subject-specific PSD details may be a predictor of the MS level. Furthermore, the analysis of the sway frequency spectrum provided insight into the intersubject differences in the use of postural control subsystems. The relationship observed between MS susceptibility and spontaneous posture is discussed in terms of postural sensory weighting and in relation to the nature of the provocative stimulus.",mds,True,findable,326,42,1,1,0,2015-11-30T15:51:48.000Z,2015-11-30T15:51:49.000Z,dryad.dryad,dryad,"posture,static posturography,spectral analysis,motion sickness","[{'subject': 'posture'}, {'subject': 'static posturography'}, {'subject': 'spectral analysis'}, {'subject': 'motion sickness'}]",['2590326 bytes'],
+10.5281/zenodo.3628018,"Data Accompanying ""Dynamics of Water Absorption in Callovo-Oxfordian Claystone Revealed With Multimodal X-Ray and Neutron Tomography""",Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These are the datasets analysed in the publication ""Dynamics of Water Absorption in<br> Callovo-Oxfordian Claystone Revealed With Multimodal X-Ray and Neutron Tomography"" by Stavropoulou <em>et al.</em> in 2020 in Frontiers in Earth Science, DOI: https://doi.org/10.3389/feart.2020.00006 File 1 contains the 3D reconstructed x-ray and neutron tomography volumes analysed in the paper. State 002 is taken as a reference and the greylevels of all images in the times series for both x-ray and neutrons are rescaled using two characteristic image features (top-cap and air in the case of x-rays) linearly to align with 002. Neutron volumes are rescaled to the same pixel size as 2-bin x-ray volumes, and a mean registration is applied to align neutrons with x-rays.<br> Furthermore, a bilateral filter is applied to the neutron tomographies (domain sigma = 1, range sigma=3000).<br> Full scale images are available at https://doi.ill.fr/10.5291/ILL-DATA.UGA-42<br> File 2 contains the joint histograms for registered pairs of images, as visible in Figure 4 and Figure 5.<br> File 3 contains the results of the digital volume correlation performed with the spam tookit.<br> The overall ""registration"" is used to create Figure 6<br> The global correlations available in ""gdic"" are used to create Figures 7, 8 and 9.",mds,True,findable,9,0,0,0,0,2020-02-01T13:10:52.000Z,2020-02-01T13:10:53.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4008396,"Data and Figures used in ""Fast Quasiâ€Geostrophic Magnetoâ€Coriolis Modes in the Earth's Core""",Zenodo,2020,,Dataset,"GNU General Public License v3.0 or later,Open Access","Data, plotting routines and analysis routines to reproduce all results from the article Fast Quasiâ€Geostrophic Magnetoâ€Coriolis Modes in the Earth's Core. The package uses the freely available code Mire.jl. <strong>Prerequisites</strong> Installed python3 with matplotlib ≥v2.1 and cartopy. A working Julia ≥v1.6. <strong>Run</strong> In the project folder run <pre><code>julia --project=.</code></pre> <br> Then, from within the Julia REPL run <pre><code>]instantiate</code></pre> at first time, to install all dependencies. After that, to compute all plots run <pre><code>using FastMCM allfigs() #or allfigs(true) to use LaTeX fonts</code></pre> If loading FastMCM fails, due to a missing cartopy in the python version. Run (within Julia)<br> <pre><code>ENV[""PYTHON""] = ""python"" #this should point to the python version that has cartopy installed ]build PyCall</code></pre> <br> To calculate data, run <pre><code>using FastMCM N=9 calc1dtm() calcLHSRHS(N) calcesol(N) postprocess(N) </code></pre> <br> for a given N. Note, for large N (e.g. 35) this may take a lot of memory and a long time (~13h). If there are any issues, please don't hesitate to get in touch.",mds,True,findable,0,0,0,0,0,2021-03-25T21:08:40.000Z,2021-03-25T21:08:41.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.999197,rmari/OscillatoryCrossShear: Codes implementing driving protocols for viscosity and dissipation reduction in granular suspensions,Zenodo,2017,,Software,Open Access,Codes for dense granular suspensions under OCS protocols,mds,True,findable,0,0,1,0,0,2017-09-29T09:12:47.000Z,2017-09-29T09:12:47.000Z,cern.zenodo,cern,"rheology,granular suspensions,soft matter,viscosity,dissipation","[{'subject': 'rheology'}, {'subject': 'granular suspensions'}, {'subject': 'soft matter'}, {'subject': 'viscosity'}, {'subject': 'dissipation'}]",,
+10.5281/zenodo.5783436,Non-collinear magnetic structures in the Swedenborgite CaBaFe4O7 derived by powder and single-crystal neutron diffraction,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","We have investigated the magnetic structures of the Swedenborgite compound CaBaFe<sub>4</sub>O<sub>7</sub> using magnetic susceptibility and neutron diffraction experiments on powder (FRM-II, Garching) and single-crystal samples (ILL, Grenoble). Below <em>T</em><sub>N1</sub> = 274 K the system orders in a ferrimagnetic structure with spins along the <em>c</em> axis and an additional antiferromagnetic component within the kagome plane which obviously cannot satisfy all exchange interactions. Competing single-ion anisotropy and exchange interactions lead to a transition into a multi-<strong>q</strong> conical structure at <em>T</em><sub>N2</sub> = 202 K.",mds,True,findable,0,0,0,0,0,2021-12-15T19:25:54.000Z,2021-12-15T19:25:55.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8319001,"Characterization, modelling, and optimization of high-performance nano-columnar micro–Solid Oxide Cell oxygen electrodes",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset containing all the data used in the article entitled ""Characterization, modelling, and optimization of high-performance nano-columnar micro–Solid Oxide Cell oxygen electrodes"".",mds,True,findable,0,0,0,0,0,2023-09-18T11:35:02.000Z,2023-09-18T11:35:03.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.c.6593063.v1,"Promoting HPV vaccination at school: a mixed methods study exploring knowledge, beliefs and attitudes of French school staff",figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background HPV vaccine coverage in France remained lower than in most other high-income countries. Within the diagnostic phase of the national PrevHPV program, we carried out a mixed methods study among school staff to assess their knowledge, beliefs and attitudes regarding HPV, HPV vaccine and vaccination in general, and regarding schools’ role in promoting HPV vaccination. Methods Middle school nurses, teachers and support staff from four French regions participated between January 2020 and May 2021. We combined: (i) quantitative data from self-administered online questionnaires (n = 301), analysed using descriptive statistics; and (ii) qualitative data from three focus groups (n = 14), thematically analysed. Results Less than half of respondents knew that HPV can cause genital warts or oral cancers and only 18% that no antiviral treatment exists. Almost 90% of the respondents knew the existence of the HPV vaccine but some misunderstood why it is recommended before the first sexual relationships and for boys; 56% doubted about its safety, especially because they think there is not enough information on this topic. Schools nurses had greater knowledge than other professionals and claimed that educating pupils about HPV was fully part of their job roles; however, they rarely address this topic due to a lack of knowledge/tools. Professionals (school nurses, teachers and support staff) who participated in the focus groups were unfavourable to offering vaccination at school because of parents’ negative reactions, lack of resources, and perceived uselessness. Conclusions These results highlight the need to improve school staff knowledge on HPV. Parents should be involved in intervention promoting HPV vaccination to prevent their potential negative reactions, as feared by school staff. Several barriers should also be addressed before organizing school vaccination programs in France.",mds,True,findable,0,0,0,0,0,2023-04-13T14:58:33.000Z,2023-04-13T14:58:33.000Z,figshare.ars,otjm,"Medicine,Molecular Biology,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Molecular Biology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.7565764,pyRiemann-qiskit,Zenodo,2023,en,Software,"BSD 3-Clause ""New"" or ""Revised"" License,Open Access","Quantum computing is a promising technology for machine learning, in terms of computational costs and outcomes. In this work, we intend to provide a framework that facilitates the use of quantum machine learning in the domain of brain-computer interfaces - where biomedical signals such as brain waves are processed. <strong>Repository URL:</strong> https://github.com/pyRiemann/pyRiemann-qiskit/ <strong>Version details:</strong> https://github.com/pyRiemann/pyRiemann-qiskit/releases/tag/v0.0.3",mds,True,findable,0,0,0,0,0,2023-01-24T14:37:52.000Z,2023-01-24T14:37:53.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4729758,Prevalence of nonsensical algorithmically generated papers in the scientific literature,Zenodo,2021,en,Software,"Creative Commons Attribution 4.0 International,Open Access",research integrity<br> publishing industry<br> misconduct<br> retraction<br> computer-generated papers<br> SCIgen<br> nonsense detection<br> citation manipulation,mds,True,findable,0,0,0,0,0,2021-05-19T14:11:14.000Z,2021-05-19T14:11:15.000Z,cern.zenodo,cern,"computer-generated papers,SCIgen,nonsense detection,research integrity,misconduct,publishing industry","[{'subject': 'computer-generated papers'}, {'subject': 'SCIgen'}, {'subject': 'nonsense detection'}, {'subject': 'research integrity'}, {'subject': 'misconduct'}, {'subject': 'publishing industry'}]",,
+10.5281/zenodo.7982052,"FIGURES C7–C9 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,Open Access,"FIGURES C7–C9. Leuctra signifera, adult female (Austria, Gutenstein Alps, Urgersbachtal). C7, ventral view; C8, ventral view; C9, lateral view.",mds,True,findable,0,0,0,0,0,2023-05-29T13:43:56.000Z,2023-05-29T13:43:57.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.34847/nkl.36ac9k92,"Urban climate measurements by mobile station for assessment of pedestrian thermal exposure. Sites of Quai de plantes, Jardin extraordinaire, Rideau place Graslin, Estrade rafraichissante, Ilot frais and Parc of La Defense",NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,en,Dataset,,"Jeu de données des mesures des variables climatiques en lien avec la perception thermique du piéton dans des parcours urbains. Les sites de ce jeu de données correspondent aux campagnes de mesures du projet ANR Coolscapes (cf. compte-rendu final pour plus de détail).
+
+Chaque fichier correspond à une séquence de mesures géololisées (CRS 2154) et horodatées. Le nom de fichier indique : site_ville_reference-station_parcours_date_heure-début
+
+Chaque fichier est composé des colonnes suivantes :
+- day_fileid : identifiant de la campagne de mesure
+- timestamp : horodatage de la mesure
+- RECORD : numéro de la mesure dans la séquence d'acquisition
+- AirTC_Avg (°C) : température de l'air mesurée par le capteur Vaisala HMP155A sous abri météorologique de type RAD14.
+- Temp_C_Avg(1) (°C) : température de l'air mesurée par le thermocouple type T Omega situé à 180 cm du sol
+- Temp_C_Avg(2) (°C) : température de l'air mesurée par le thermocouple type T Omega situé à 30 cm du sol
+- RH_Avg (%) : humidité relative mesurée par le capteur Vaisala HMP155A sous abri météorologique de type RAD14.
+- WindDir (degrée selon le nord) : direction du vent selon l'azimut variable de la station mobile mesurée par le capteur Gill 2D Windsonic.
+- WS_ms_Avg (m/s) : vitesse du vent mesurée par le capteur Gill 2D Windsonic.
+- SR01Up_1_Avg (W/m2) : rayonnement de courte longueur d'onde provenant du ciel mésuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- SR01Dn_1_Avg (W/m2) : rayonnement de courte longueur d'onde provenant du sol mésuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- IR01UpCo_1_Avg (W/m2) : rayonnement de grande longueur d'onde provenant du ciel mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- IR01DnCo_1_Avg (W/m2) : rayonnement de grande longueur d'onde provenant du sol mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- NR01TC_1_Avg (°C) : température de l'air à l'intérieur du capteur NR 01 Hukseflux 4-component Net Radiometer
+- NR01TK_1_Avg (°K) : température de l'air à l'intérieur du capteur NR 01 Hukseflux 4-component Net Radiometer
+- NetRs_1_Avg (W/m2) : rayonnement net de courte longueur d'onde calculé selon les mesures du NR 01
+- NetRl_1_Avg (W/m2) : rayonnement net de grande longueur d'onde calculé selon les mesures du NR 01
+- SR01Up_2_Avg (W/m2) : rayonnement de courte longueur d'onde provenant de la gauche de la station mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- SR01Dn_2_Avg (W/m2) : rayonnement de courte longueur d'onde provenant de la droite mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- IR01UpCo_2_Avg (W/m2) : rayonnement de grande longueur d'onde provenant de la gauche de la station mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- IR01DnCo_2_Avg (W/m2) : rayonnement de grande longueur d'onde provenant de la droite de la station mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- NR01TC_2_Avg (°C) : température de l'air à l'intérieur du capteur NR 01 Hukseflux 4-component Net Radiometer
+- NR01TK_2_Avg (°K) : température de l'air à l'intérieur du capteur NR 01 Hukseflux 4-component Net Radiometer
+- NetRs_2_Avg (W/m2) : rayonnement net de courte longueur d'onde calculé selon les mesures du NR 01
+- NetRl_2_Avg (W/m2) : rayonnement net de grande longueur d'onde calculé selon les mesures du NR 01
+- SR01Up_3_Avg (W/m2) : rayonnement de courte longueur d'onde provenant du devant de la station mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- SR01Dn_3_Avg (W/m2) : rayonnement de courte longueur d'onde provenant du derrière de la station mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- IR01UpCo_3_Avg (W/m2) : rayonnement de grande longueur d'onde provenant du devant de la station mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- IR01DnCo_3_Avg (W/m2) : rayonnement de grande longueur d'onde provenant du derrière de la station mesuré par le capteur NR 01 Hukseflux 4-component Net Radiometer
+- NR01TC_3_Avg (°C) : température de l'air à l'intérieur du capteur NR 01 Hukseflux 4-component Net Radiometer
+- NR01TK_3_Avg (°K) : température de l'air à l'intérieur du capteur NR 01 Hukseflux 4-component Net Radiometer
+- NetRs_3_Avg (W/m2) : rayonnement net de courte longueur d'onde calculé selon les mesures du NR 01
+- NetRl_3_Avg (W/m2) : rayonnement net de grande longueur d'onde calculé selon les mesures du NR 01
+- BattV_Min (V) : tension de la batterie mesurée par la centrale CR1000X de Campbell scientific.
+- site : identifiant du site de mesure
+- city : ville
+- curv_absc : abcise curviligne correspondant à l'avancement de la station mobile le long du parcours linaire de mesure
+- parcour : numéro de parcour
+- repetition : numéro d'itération journalière
+- TagName : identification des points spécifiques
+- geometry : identification géometrique du point spatial de la mesure en CRS 2154",api,True,findable,0,0,0,0,0,2023-04-14T15:02:02.000Z,2023-04-14T15:02:03.000Z,inist.humanum,jbru,"urban climate,mobile measurements,public space,thermal perception","[{'subject': 'urban climate'}, {'subject': 'mobile measurements'}, {'subject': 'public space'}, {'subject': 'thermal perception'}]","['55265 Bytes', '57510 Bytes', '46177 Bytes', '55231 Bytes', '59186 Bytes', '53137 Bytes', '57095 Bytes', '46907 Bytes', '52791 Bytes', '54007 Bytes', '54189 Bytes', '56910 Bytes', '62549 Bytes', '51908 Bytes', '53285 Bytes', '53154 Bytes', '56950 Bytes', '51649 Bytes', '40887 Bytes', '49850 Bytes', '8334 Bytes', '56302 Bytes', '43975 Bytes', '44773 Bytes', '49720 Bytes', '47134 Bytes', '58989 Bytes', '44402 Bytes', '9021 Bytes', '4176 Bytes', '6478 Bytes', '12664 Bytes', '9902 Bytes', '14306 Bytes', '11284 Bytes', '10140 Bytes', '12016 Bytes', '48483 Bytes', '10589 Bytes', '9452 Bytes', '9913 Bytes', '9455 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+10.5281/zenodo.8214711,tlibs,Zenodo,2023,,Software,"GNU General Public License v3.0 only,Open Access","Tlibs version 2, a physical-mathematical C++ template library.",mds,True,findable,0,0,0,0,0,2023-08-04T11:21:17.000Z,2023-08-04T11:21:17.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3648639,Results of the CNRS benchmark,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Raw results obtained by each partner performing the CNRS benchmark.,mds,True,findable,0,0,0,1,0,2020-02-07T18:07:02.000Z,2020-02-07T18:07:02.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3925378,A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967-2015,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Glacier mass balance (MB) data are crucial to understand and quantify the regional effects of climate on glaciers and the high-mountain water cycle, yet observations cover only a small fraction of glaciers in the world. We present a dataset of annual glacier-wide surface mass balance of all the glaciers in the French Alps for the 1967-2015 period. This dataset has been reconstructed using deep learning (i.e. a deep artificial neural network), based on direct MB observations and remote sensing annual estimates, meteorological reanalyses and topographical data from glacier inventories. The method’s validity was assessed through an extensive cross-validation against a dataset of 32 glaciers , with an estimated average error (RMSE) of 0.55 m.w.e. a<sup>-1</sup>, an explained variance (r2) of 75% and an average bias of -0.021 m.w.e. a<sup>-1</sup>. We estimate an average regional area-weighted glacier-wide MB of -0.71±0.21 (1 sigma) m.w.e. a<sup>-1</sup> for the 1967-2015 period, with negative mass balances in the 1970s (-0.44 m.w.e. a<sup>-1</sup>), moderately negative in the 1980s (-0.16 m.w.e. a<sup>-1</sup>), and an increasing negative trend from the 1990s onwards, up to -1.34 m.w.e. a<sup>-1</sup> in the 2010s. A comparison with ASTER-derived geodetic MB for the 2000-2015 period showed important differences with the photogrammetric geodetic MB used to train our model. When recalibrating our reconstructions with the new ASTER-derived geodetic MB, the estimated average regional area-weighted glacier-wide MB (1967-2015) is reduced to -0.64±0.21 (1 sigma) m.w.e. a<sup>-1</sup>. Following a topographical and regional analysis, we estimate that the massifs with the highest mass losses for the 1967-2015 period are the Chablais (-0.93 m.w.e. a<sup>-1</sup>), Champsaur and Haute-Maurienne (-0.86 m.w.e. a<sup>-1</sup> both) and Ubaye ranges (-0.83 m.w.e. a<sup>-1</sup>), and the ones presenting the lowest mass losses are the Mont-Blanc (-0.69 m.w.e. a<sup>-1</sup>), Oisans and Haute-Tarentaise ranges (-0.75 m.w.e. a<sup>-1</sup> both). This dataset provides relevant and timely data for studies in the fields of glaciology, hydrology and ecology in the French Alps, in need of regional or glacier-specific annual net glacier mass changes in glacierized catchments. The MB dataset is presented in two different formats: (a) A single netCDF file containing the MB reconstructions, the glacier RGI and GLIMS IDs and the glacier names. This file contains all the necessary information to correctly interact with the data, including some metadata with the authorship and data units. (b) A dataset comprised of multiple CSV files, one for each of the 661 glaciers from the 2003 glacier inventory (Gardent et al., 2014), named with its GLIMS ID and RGI ID with the following format: GLIMS-ID_RGI-ID_SMB.csv. Both indexes are used since some glaciers that split into multiple sub-glaciers do not have an RGI ID. Split glaciers have the GLIMS ID of their ""parent"" glacier and an RGI ID equal to 0. Every file contains one column for the year number between 1967 and 2015 and another column for the annual glacier-wide MB time series. Glaciers with remote sensing-derived estimates (Rabatel et al., 2016) include this information as an additional column. This allows the user to choose the source of data, with remote sensing data having lower uncertainties (0.35±0.06 () m.w.e. a<sup>-1</sup> as estimated in Rabatel et al. (2016)). Columns are separated by semicolon (;).",mds,True,findable,0,0,0,0,0,2020-07-01T11:14:14.000Z,2020-07-01T11:14:14.000Z,cern.zenodo,cern,"glacier,glacier mass balance,mountain glaciers,climate change,french alps","[{'subject': 'glacier'}, {'subject': 'glacier mass balance'}, {'subject': 'mountain glaciers'}, {'subject': 'climate change'}, {'subject': 'french alps'}]",,
+10.5281/zenodo.4761295,"Fig. 8 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 8. Dictyogenus jurassicum sp. n., adult male, venation of forewing (annotations by Dr. Olivier Béthoux). Karstic spring at Charabotte Mill, Ain dpt, France. Photo B. Launay.",mds,True,findable,0,0,4,0,0,2021-05-14T07:43:55.000Z,2021-05-14T07:43:56.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.10210416,blood_on_snow_data,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,,api,True,findable,0,0,0,0,0,2023-11-28T07:30:15.000Z,2023-11-28T07:30:15.000Z,cern.zenodo,cern,,,,
+10.34847/nkl.6caam3dp,Carte des mémoires sensibles de la Romanche - version intermédiaire,NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,PhysicalObject,,"Représentation cartographique par AAU-CRESSON (Laure Brayer, Ryma Hadbi, Rachel Thomas et alii) à partir des récits collectés dans la vallée de la Romanche (2018-2021) par AAU-CRESSON et Regards des Lieux.
+
+Les multiples récits collectés au cours des arpentages et des rencontres réalisés dans la vallée ont constitué la matière première d’une représentation cartographique dont l’ambition est de faire état de la polyphonie des expériences des lieux. En représentant les mémoires sensibles de la vallée par le bais de diverses opérations de traduction à l’origine de ce travail cartographique, l’enjeu sous-jacent est de questionner des formes possibles d’une écriture sensible critique. En tentant de mettre en partage les rapports pluriels et parfois contradictoires au paysage, la carte est interrogée comme potentiel lieu d’élaboration d’une critique concernée dont les expériences sensibles sont le terreau.
+
+Cette carte est la version intermédiaire de juin 2021 faite sur Illustrator (Adobe) à partir de la première carte dite ""Table et ciseaux"". Elle a été faite par l'équipe de recherche avant de la soumettre aux habitants de la Vallée de la Romanche lors de la journée ""Au fil de l'eau 2"", en juin 2021.",api,True,findable,0,0,0,0,0,2022-06-27T12:30:44.000Z,2022-06-27T12:30:45.000Z,inist.humanum,jbru,"carte sensible,Cartographie sensible,Mémoires des lieux,histoire orale,patrimoine immatériel,Histoires de vie,Sens et sensations,Perception de l'espace,Récit personnel,enquêtes de terrain (ethnologie),Désindustrialisation,Patrimoine industriel,Pollution de l'air,Montagnes – aménagement,Énergie hydraulique,Rives – aménagement,Cartographie critique,Représentation graphique,Romanche, Vallée de la (France),Keller, Charles Albert (1874-1940 , Ingénieur A&M)","[{'subject': 'carte sensible'}, {'lang': 'fr', 'subject': 'Cartographie sensible'}, {'lang': 'fr', 'subject': 'Mémoires des lieux'}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'patrimoine immatériel'}, {'lang': 'fr', 'subject': 'Histoires de vie'}, {'lang': 'fr', 'subject': 'Sens et sensations'}, {'lang': 'fr', 'subject': ""Perception de l'espace""}, {'lang': 'fr', 'subject': 'Récit personnel'}, {'lang': 'fr', 'subject': 'enquêtes de terrain (ethnologie)'}, {'lang': 'fr', 'subject': 'Désindustrialisation'}, {'lang': 'fr', 'subject': 'Patrimoine industriel'}, {'lang': 'fr', 'subject': ""Pollution de l'air""}, {'lang': 'fr', 'subject': 'Montagnes – aménagement'}, {'lang': 'fr', 'subject': 'Énergie hydraulique'}, {'lang': 'fr', 'subject': 'Rives – aménagement'}, {'lang': 'fr', 'subject': 'Cartographie critique'}, {'lang': 'fr', 'subject': 'Représentation graphique'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'Keller, Charles Albert (1874-1940 , Ingénieur A&M)'}]","[15311294, 73848650]","['image/jpeg', 'application/pdf']"
+10.5281/zenodo.4761337,"Figs. 58-61 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 58-61. Dictyogenus alpinum, male and female adults. 58. Adult male, epiproct, dorso-caudal view. Nant Bénin River, Savoie dpt, France. Photo B. Launay. 59. Adult male, posterior margin of sternite 7 with ventral vesicle, ventral view. Nant Bénin River, Savoie dpt, France. Photo B. Launay. 60. Female, subgenital plate, ventral view. Ristolas – Mount Viso, Queyras, Hautes-Alpes dpt, France. Photo J.-P. G. Reding. 61. Adult female, subgenital plate, ventral view. Guiers vif, Chartreuse, Savoie dpt, France. Photo A. Ruffoni. pointing almost horizontally toward each other (Figs. 29, 32). Hemitergal lobes more",mds,True,findable,0,0,0,0,0,2021-05-14T07:50:01.000Z,2021-05-14T07:50:02.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.3610615,robertxa/Mapas_Cavernas_Peru: Peruvian Cave Survey database,Zenodo,2020,,Software,Open Access,This repository contains survey's data from Peruvian caves.,mds,True,findable,0,0,0,0,0,2020-01-16T21:12:09.000Z,2020-01-16T21:12:10.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4759509,"Figs. 59-64 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 59-64. Terminalias of the imago of Protonemura dakkii sp. n. 59: male terminalia, dorsal view; 60: male terminalia, ventral view; 61: male terminalia, lateral view; 62: male paraproct, ventrolateral view; 63: female terminalia, ventral view; 64: female terminalia, lateral view (scales 0.5 mm; scale 1: Fig. 62, scale 2: Figs. 59 -61, 63-64).",mds,True,findable,0,0,2,0,0,2021-05-14T02:26:53.000Z,2021-05-14T02:26:54.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.4761297,"Fig. 9 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 9. Dictyogenus jurassicum sp. n., female, subgenital plate, ventral view. Spring of River Doubs, Mouthe, Doubs dpt, France. Photo A. Ruffoni.",mds,True,findable,0,0,4,0,0,2021-05-14T07:44:10.000Z,2021-05-14T07:44:11.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.5237279,English DBnary archive in original Lemon format,Zenodo,2021,en,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from English language edition, ranging from 31st August 2012 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br>",mds,True,findable,0,0,0,0,0,2021-08-23T21:01:11.000Z,2021-08-23T21:01:12.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.5747107,"Micromegas interface and IDM implementation used in ""Constraining new physics with SModelS version 2"" (arXiv:2112.00769)",Zenodo,2021,,Software,"Creative Commons Attribution 4.0 International,Open Access","- MO_smo_interface.tgz : contains the interface files for micrOMEGAs_5.2.7.a to work with SModelS v2.1; see appendix C of arXiv:2112.00769; - main_codesnippet_forSModelS.c : code snippet for calling SModelS v2.1 in any micrOMEGAs main program; - ScotoIDM.tgz : IDM implementation used in the paper ""Constraining new physics with SModelS version 2"". This includes the model files; an example main program (main.c), which demonstrates the functionalities and constraints used in section 4.1.1 of arXiv:2112.00769; and some sample test points, which may serve for illustration.",mds,True,findable,0,0,0,0,0,2021-12-03T06:39:14.000Z,2021-12-03T06:39:15.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7855146,Modelling and simulating age-dependent pedestrian behaviour with an autonomous vehicle,Zenodo,2023,,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access","Video ""1_SimulationWithoutAgel"" shows the simulation before the modifications of the model and the implementation. Video ""2_SimulationWithAge"" shows the simulation after the modifications of the model and the implementation depending on the age data. Videos of the article: ""Modelling and simulating age-dependent pedestrian behaviour with an autonomous vehicle"" Abstract: In shared spaces, autonomous vehicles (AVs) will have to move efficiently and safely, without normal road signage, and with other users such as pedestrians, cyclists and drivers. To achieve this, AVs need to anticipate the behaviours of other road users in order to adapt their navigation accordingly. This paper focuses on age-related pedestrian behaviours with an autonomous vehicle. Looking at age as one of the main factors determining behaviour, a literature review is conducted. The results are used to integrate age-dependent pedestrian behaviours into a model for simulating more realistic pedestrian behaviours in shared spaces with an AV.",mds,True,findable,0,0,0,0,0,2023-04-22T13:30:38.000Z,2023-04-22T13:30:38.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8161141,The Coq Proof Assistant,Zenodo,2023,en,Software,"GNU Lesser General Public License v2.1 only,Open Access","Coq is a formal proof management system. It provides a formal language to write mathematical definitions, executable algorithms and theorems together with an environment for semi-interactive development of machine-checked proofs. Typical applications include the certification of properties of programming languages (e.g. the CompCert compiler certification project, the Verified Software Toolchain for verification of C programs, or the Iris framework for concurrent separation logic), the formalization of mathematics (e.g. the full formalization of the Feit-Thompson theorem, or homotopy type theory), and teaching. Coq version 8.17 integrates a soundness fix to the Coq kernel along with a few new features and a host of improvements to the Ltac2 language and libraries. We highlight some of the most impactful changes here: Fixed a logical inconsistency due to <code>vm_compute</code> in presence of side-effects in the enviroment (e.g. using <code>Back</code> or <code>Fail</code>). It is now possible to dynamically enable or disable notations. Support multiple scopes in <code>Arguments</code> and <code>Bind Scope</code>. The tactics chapter of the manual has many improvements in presentation and wording. The documented grammar is semi-automatically checked for consistency with the implementation. Fixes to the <code>auto</code> and <code>eauto</code> tactics, to respect hint priorities and the documented use of <code>simple apply</code>. This is a potentially breaking change. New Ltac2 APIs, deep pattern-matching with <code>as</code> clauses and handling of literals, support for record types and preterms. Move from <code>:></code> to <code>::</code> syntax for declaring typeclass fields as instances, fixing a confusion with declaration of coercions. Standard library improvements. While Coq supports OCaml 5, users are likely to experience slowdowns ranging from +10% to +50% compared to OCaml 4. Moreover, the <code>native_compute</code> machinery is not available when Coq is compiled with OCaml 5. Therefore, OCaml 5 support should still be considered experimental and not production-ready. See the Changes in 8.17.0 section below for the detailed list of changes, including potentially breaking changes marked with <strong>Changed</strong>. Coq's reference manual for 8.17, documentation of the 8.17 standard library and developer documentation of the 8.17 ML API are also available. Ali Caglayan, Emilio Jesús Gallego Arias, Gaëtan Gilbert and Théo Zimmermann worked on maintaining and improving the continuous integration system and package building infrastructure. Erik Martin-Dorel has maintained the Coq Docker images that are used in many Coq projects for continuous integration. Maxime Dénès, Paolo G. Giarrusso, Huỳnh Trần Khanh, and Laurent Théry have maintained the VsCoq extension for VS Code. The opam repository for Coq packages has been maintained by Guillaume Claret, Karl Palmskog, Matthieu Sozeau and Enrico Tassi with contributions from many users. A list of packages is available at https://coq.inria.fr/opam/www/. The Coq Platform has been maintained by Michael Soegtrop, with help from Karl Palmskog, Pierre Roux, Enrico Tassi and Théo Zimmermann. Our current maintainers are Yves Bertot, Frédéric Besson, Ana Borges, Ali Caglayan, Tej Chajed, Cyril Cohen, Pierre Corbineau, Pierre Courtieu, Maxime Dénès, Andres Erbsen, Jim Fehrle, Julien Forest, Emilio Jesús Gallego Arias, Gaëtan Gilbert, Georges Gonthier, Benjamin Grégoire, Jason Gross, Hugo Herbelin, Vincent Laporte, Olivier Laurent, Assia Mahboubi, Kenji Maillard, Guillaume Melquiond, Pierre-Marie Pédrot, Clément Pit-Claudel, Pierre Roux, Kazuhiko Sakaguchi, Vincent Semeria, Michael Soegtrop, Arnaud Spiwack, Matthieu Sozeau, Enrico Tassi, Laurent Théry, Anton Trunov, Li-yao Xia and Théo Zimmermann. See the Coq Team face book page for more details. The 45 contributors to the 8.17 version are: Reynald Affeldt, Tanaka Akira, Lasse Blaauwbroek, Stephan Boyer, Ali Caglayan, Cyril Cohen, Maxime Dénès, Andrej Dudenhefner, Andres Erbsen, František Farka, Jim Fehrle, Paolo G. Giarrusso, Gaëtan Gilbert, Jason Gross, Alban Gruin, Stefan Haan, Hugo Herbelin, Wolf Honore, Bodo Igler, Jerry James, Emilio Jesús Gallego Arias, Ralf Jung, Jan-Oliver Kaiser, Wojciech Karpiel, Chantal Keller, Thomas Klausner, Olivier Laurent, Yishuai Li, Guillaume Melquiond, Karl Palmskog, Sudha Parimala, Pierre-Marie Pédrot, Valentin Robert, Pierre Roux, Julin S, Dmitry Shachnev, Michael Soegtrop, Matthieu Sozeau, Naveen Srinivasan, Sergei Stepanenko, Karolina Surma, Enrico Tassi, Li-yao Xia and Théo Zimmermann. The Coq community at large helped improve this new version via the GitHub issue and pull request system, the coq-club@inria.fr mailing list, the Discourse forum and the Coq Zulip chat. Version 8.17's development spanned 5 months from the release of Coq 8.16.0. Théo Zimmermann is the release manager of Coq 8.17. This release is the result of 414 merged PRs, closing 105 issues.",mds,True,findable,0,0,0,0,0,2023-07-18T17:17:12.000Z,2023-07-18T17:17:13.000Z,cern.zenodo,cern,"proof assistant,mathematical software,formal proofs","[{'subject': 'proof assistant'}, {'subject': 'mathematical software'}, {'subject': 'formal proofs'}]",,
+10.5281/zenodo.4306051,A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog - Supporting Data,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Description </strong> The following files are available : Simulated non-redundant Gene Catalog (SGC) composed of 128267 genes; Gene abundance profiles across 40 samples: raw read counts, gene length normalized base counts, depth file computed by the jgi_summarize_bam_contig_depth script provided by MetaBAT; Gold Standard (GS) and Gold Standard Single Assignment (GS_SA) binning results; Binning results obtained on the SGC with nine binning methods: MSPminer, MGS-canopy, DAS Tool, MaxBin2, MetaBAT2, SolidBin, CONCOCT, COCACOLA and MyCC. <strong>License</strong> These files are licensed under a Creative Commons Attribution 4.0 International License.",mds,True,findable,0,0,0,0,0,2020-12-04T18:36:11.000Z,2020-12-04T18:36:12.000Z,cern.zenodo,cern,"Metagenomics,Binning,Human gut microbiota,Gene catalog","[{'subject': 'Metagenomics'}, {'subject': 'Binning'}, {'subject': 'Human gut microbiota'}, {'subject': 'Gene catalog'}]",,
+10.5281/zenodo.5744160,Fabric evolution and strain localisation in inherently anisotropic specimens of anisometric particles under triaxial compresion,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the data and processed results of the work ""<em>Fabric evolution and strain localisation in inherently anisotropic specimens of anisometric particles (lentils) under triaxial compression</em>"", published in Granular Matter (https://link.springer.com/article/10.1007/s10035-022-01305-8). The study analyses five triaxial compression tests on cylindrical specimens made up of more than nine thousand lentils. Each specimen is prepared with a characteristic orientation (the orientation of the mould for the deposition of the lentils). Repeated x-ray tomography scanning is performed during deviatoric loading, and each scanned step is reconstructed into a 3D volume. Particles are identified in the first 3D volume (in the form of a labelled image) and tracked from the first image all the way through the test using a novel tracking algorithm, enabling the measurement of particle and contact fabric evolution, as well as strain localisation within the specimens. All the procesing is performed using spam (https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/intro.html) software. The <em>Readme.md</em> file contains further details on the experimental campaign, and the structure of the repository. Please refer to the paper ""<em>Fabric evolution and strain localisation in inherently anisotropic specimens of anisometric particles under triaxial compression</em>"" published on<em> Granular Matter</em> for further details not found on the <em>Readme.md </em>file . Additional information/data not included in this repository is available upon request.",mds,True,findable,0,0,0,1,0,2022-01-06T17:19:31.000Z,2022-01-06T17:19:32.000Z,cern.zenodo,cern,"Anisometric particles,Inherent anisotropy,Fabric,Lab testing,x-ray tomography","[{'subject': 'Anisometric particles'}, {'subject': 'Inherent anisotropy'}, {'subject': 'Fabric'}, {'subject': 'Lab testing'}, {'subject': 'x-ray tomography'}]",,
+10.6084/m9.figshare.22620895,Additional file 1 of Critically ill severe hypothyroidism: a retrospective multicenter cohort study,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Figure S1. Flowchart of patient selection from participating ICUs. Table S1. Amount of Missing Data for Each Variable Included in the Analysis. Table S2. Characteristics of Severe Hypothyroidism Patients According to the Presence of a Circulatory Failure at ICU Admission. Table S3. Clinical and Biological Features at ICU Admission according to ICU survival. Table S4. Predictive Patient Factors Associated with 6-month Mortality in Critically ill Adults with Severe Hypothyroidism.,mds,True,findable,0,0,0,0,0,2023-04-13T14:55:40.000Z,2023-04-13T14:55:40.000Z,figshare.ars,otjm,"Medicine,Neuroscience,Pharmacology,Immunology,FOS: Clinical medicine,Cancer","[{'subject': 'Medicine'}, {'subject': 'Neuroscience'}, {'subject': 'Pharmacology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}]",['96335 Bytes'],
+10.6084/m9.figshare.c.6250158.v1,Expiratory high-frequency percussive ventilation: a novel concept for improving gas exchange,figshare,2022,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Although high-frequency percussive ventilation (HFPV) improves gas exchange, concerns remain about tissue overdistension caused by the oscillations and consequent lung damage. We compared a modified percussive ventilation modality created by superimposing high-frequency oscillations to the conventional ventilation waveform during expiration only (eHFPV) with conventional mechanical ventilation (CMV) and standard HFPV. Methods Hypoxia and hypercapnia were induced by decreasing the frequency of CMV in New Zealand White rabbits (n = 10). Following steady-state CMV periods, percussive modalities with oscillations randomly introduced to the entire breathing cycle (HFPV) or to the expiratory phase alone (eHFPV) with varying amplitudes (2 or 4 cmH2O) and frequencies were used (5 or 10 Hz). The arterial partial pressures of oxygen (PaO2) and carbon dioxide (PaCO2) were determined. Volumetric capnography was used to evaluate the ventilation dead space fraction, phase 2 slope, and minute elimination of CO2. Respiratory mechanics were characterized by forced oscillations. Results The use of eHFPV with 5 Hz superimposed oscillation frequency and an amplitude of 4 cmH2O enhanced gas exchange similar to those observed after HFPV. These improvements in PaO2 (47.3 ± 5.5 vs. 58.6 ± 7.2 mmHg) and PaCO2 (54.7 ± 2.3 vs. 50.1 ± 2.9 mmHg) were associated with lower ventilation dead space and capnogram phase 2 slope, as well as enhanced minute CO2 elimination without altering respiratory mechanics. Conclusions These findings demonstrated improved gas exchange using eHFPV as a novel mechanical ventilation modality that combines the benefits of conventional and small-amplitude high-frequency oscillatory ventilation, owing to improved longitudinal gas transport rather than increased lung surface area available for gas exchange.",mds,True,findable,0,0,0,0,0,2022-10-16T03:12:42.000Z,2022-10-16T03:12:43.000Z,figshare.ars,otjm,"Biophysics,Space Science,Medicine,Physiology,FOS: Biological sciences,Biotechnology,Cancer","[{'subject': 'Biophysics'}, {'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Biotechnology'}, {'subject': 'Cancer'}]",,
+10.5281/zenodo.4761303,"Figs. 20-25 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 20-25. Dictyogenus jurassicum sp. n., egg characteristics. 20. Egg, lateral view. Karstic spring of Côte au Bouvier, near Soubey, canton of Jura, Switzerland. 21. Egg, lateral view. Karstic spring of Côte au Bouvier, near Soubey, canton of Jura, Switzerland. 22. Egg, lateral view, with ridge and micropyles visible. Karstic spring of Côte au Bouvier, near Soubey, canton of Jura, Switzerland. 23. Detail of egg chorion and micropyles. Karstic spring of Côte au Bouvier, near Soubey, canton of Jura, Switzerland. 24. Egg, collar. Karstic spring of Côte au Bouvier, near Soubey, canton of Jura, Switzerland. 25. Egg, collar and anchor. Karstic spring of Côte au Bouvier, near Soubey, canton of Jura, Switzerland.",mds,True,findable,0,0,2,0,0,2021-05-14T07:44:55.000Z,2021-05-14T07:44:56.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.6939154,On the formulation and implementation of extrinsic cohesive zone models with contact - data set,Zenodo,2022,en,Dataset,"Apache License 2.0,Open Access","This data set contains data relating to the paper ""On the formulation and implementation of extrinsic cohesive zone models with contact"", https://doi.org/10.1016/j.cma.2022.115545 , specifically:<br> 1. the meshes used to conduct finite element analyses,<br> 2. the results of those finite element analyses (in the form of vtk files and numpy pickles), and<br> 3. some images of the meshes and the total displacement at the end of the analyses.<br> <br> The corresponding code to generate and read the data is available at https://github.com/nickcollins-craft/On-the-formulation-and-implementation-of-extrinsic-cohesive-zone-models-with-contact (which is the preferred method), or alternatively via https://doi.org/10.5281/zenodo.6939391.",mds,True,findable,0,0,0,3,0,2022-07-29T13:50:36.000Z,2022-07-29T13:50:37.000Z,cern.zenodo,cern,"Extrinsic cohesive zone,Finite element analysis,Dynamic crack propagation,Non-smooth mechanics","[{'subject': 'Extrinsic cohesive zone'}, {'subject': 'Finite element analysis'}, {'subject': 'Dynamic crack propagation'}, {'subject': 'Non-smooth mechanics'}]",,
+10.5281/zenodo.8008173,TAS-Paths,Zenodo,2023,en,Software,"GNU General Public License v3.0 only,Open Access","<strong>TAS-Paths</strong> Pathfinding software for neutron triple-axis spectrometers, part of the Takin software package. The software's website can be found here, its development repository is available here.<br>",mds,True,findable,0,0,0,0,0,2023-06-05T22:51:08.000Z,2023-06-05T22:51:08.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5865001,Snow equi-temperature metamorphism described by a phase-field model applicable on micro-tomographic images: prediction of microstructural and transport properties,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset provides data described and used in the article submitted to Journal of Advances in Modeling Earth Systems ""Snow equi-temperature metamorphism described by a phase-field model applicable on micro-tomographic images: prediction of microstructural and transport properties"". It contains .csv files with different properties computed on outputs of the model Snow3D simulating equi-temperature metamorphism. This micro-scale model was used here with experimental micro-tomographic snow images as input and returns series of 3-D images of snow showing features of equi-temperature metamorphism at different time steps as output. In this dataset, you will find two types of files: - the microstructural properties (density, specific surface area, covariance lengths, mean curvature) computed on the simulated images at different time steps. - the transport properties (effective conductivity, normalizes effective vapor diffusion coefficient, permeability) of the simulated images at different time steps. Finally, metadata_simulations.csv gather the information relative to the simulations.",mds,True,findable,0,0,0,1,0,2022-01-24T10:40:22.000Z,2022-01-24T10:40:26.000Z,cern.zenodo,cern,"Snow,Model,Micro-scale,Microstructural properties,Transport properties","[{'subject': 'Snow'}, {'subject': 'Model'}, {'subject': 'Micro-scale'}, {'subject': 'Microstructural properties'}, {'subject': 'Transport properties'}]",,
+10.7914/wqvg-2272,San Jacinto FaultScan Project,International Federation of Digital Seismograph Networks,2022,,Dataset,,Deployment of 300 nodes on Piñon Flat in southern California,api,True,findable,0,0,0,0,0,2023-09-11T17:56:29.000Z,2023-09-11T17:56:29.000Z,iris.iris,iris,,,['10000000 MB'],['SEED data']
+10.5281/zenodo.3871493,Raw diffraction data for [NiFeSe] hydrogenase pressurized with Kr gas - dataset wtKr1,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","Diffraction data measured at ESRF beamline ID30A-3 on September 27, 2017.",mds,True,findable,0,0,0,0,0,2020-06-01T10:31:49.000Z,2020-06-01T10:31:51.000Z,cern.zenodo,cern,"Hydrogenase,Selenium,gas channels,high-pressure derivatization","[{'subject': 'Hydrogenase'}, {'subject': 'Selenium'}, {'subject': 'gas channels'}, {'subject': 'high-pressure derivatization'}]",,
+10.6084/m9.figshare.24202747,Additional file 1 of Obstructive sleep apnea: a major risk factor for COVID-19 encephalopathy?,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Supplemental Table 1. Comparison of patient demographic characteristics between definite OSA group and No OSA group.,mds,True,findable,0,0,0,0,0,2023-09-27T03:26:07.000Z,2023-09-27T03:26:07.000Z,figshare.ars,otjm,"Biophysics,Medicine,Cell Biology,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,Sociology,FOS: Sociology,Immunology,FOS: Clinical medicine,Cancer,Mental Health,Virology","[{'subject': 'Biophysics'}, {'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Mental Health'}, {'subject': 'Virology'}]",['31583 Bytes'],
+10.5281/zenodo.6319386,Structural Basis for the Inhibition of IAPP Fibril Formation by the Co-Chaperonin Prefoldin - Experimental Data,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Experimental data (EM, AFM, BLI, ThT and Cell viability assays, as well as docking models) used for the study : <strong>Structural Basis for the Inhibition of IAPP Fibril Formation by the </strong><strong>Co-Chaperonin Prefoldin</strong> by Ricarda Törner, Tatsiana Kupreichyk, Lothar Gremer, Elisa Colas Debled, Daphna Fenel, Sarah Schemmert, Pierre Gans<sub>, </sub>Dieter Willbold, Guy Schoehn, Wolfgang Hoyer, Jerome Boisbouvier",mds,True,findable,0,0,0,0,0,2022-03-01T08:03:24.000Z,2022-03-01T08:03:25.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.bnzs7h4dx,Dataset for: Buckling of lipidic ultrasound contrast agents under quasi-static load,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Collapse of lipidic ultrasound contrast agents under high-frequency compressive load has been historically interpreted by the vanishing of surface tension. By contrast, buckling of elastic shells is known to occur when costly compressible stress is released through bending. Through quasi-static compression experiments on lipidic shells, we analyze the buckling events in the framework of classical elastic buckling theory and deduce the mechanical characteristics of these shells. They are then compared to that obtained through acoustic characterization.",mds,True,findable,75,6,0,1,0,2023-01-09T09:39:59.000Z,2023-01-09T09:40:00.000Z,dryad.dryad,dryad,"FOS: Physical sciences,FOS: Physical sciences,Image analysis","[{'subject': 'FOS: Physical sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Physical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Image analysis', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['5484917 bytes'],
+10.5281/zenodo.7395343,Discrete Element Modelling of Southeast Asia's 3D Lithospheric Deformation during the Indian Collision,Zenodo,2022,en,Other,"Creative Commons Attribution 4.0 International,Open Access","The Python code and C++ files are for the set-up of the model. The model setup and model engine settings are in the file ""indenter_Batch.py"". The model parameters are in the file ""indentation.Table"". The ""BuoyancySimpleForceEngineOnly.cpp"" file implements the Buoyancy function. ""LPlasPM.cpp"" implements the constitutive law. After downloading the source code YADE from http://www.yade-dem.org/, follow the instructions from the web to install YADE, put all .cpp files into the YADE source folder, and compile them. Run ""yade-batch indentation.Table indenter_Batch.py"" in the Ubuntu system. Then, use Paraview (downloading from https://www.paraview.org/) to see the results of the model.",mds,True,findable,0,0,0,0,0,2022-12-05T00:43:19.000Z,2022-12-05T00:43:19.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4760465,"Fig. 1 in Two New Alpine Leuctra In The L. Braueri Species Group (Plecoptera, Leuctridae)",Zenodo,2011,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 1. Distribution areas of Leuctra braueri Kempny, L. juliettae sp. n. and L. muranyii sp. n. within the Alps.",mds,True,findable,0,0,2,0,0,2021-05-14T05:22:31.000Z,2021-05-14T05:22:32.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.10053092,COSIPY distributed simulations of Mera Glacier mass and energy balance (20161101-20201101),Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Creative Commons Attribution Share Alike 4.0 International","The four netCDF files contain outputs from COSIPY model (Sauter et al., 2020) for Mera Glacier for the period 20161101 to 20201101. The model is run on a 0.003°*0.003° grid, and forced with meteological variables collected locally and distributed with constant gradients. The ""constants.py"" is the python file that contains the specific model settings.",api,True,findable,0,0,0,0,0,2023-10-30T09:06:59.000Z,2023-10-30T09:06:59.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8057992,"Soil and meteorological data, and finite element simulation framework for heat transfer through shrubs in winter near Lautaret pass, French Alps",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The data allow the calculation using finite element modeling of heat transfer through shrub branches and snow between the atmosphere and the soil. The shrubs are green alders (Alnus viridis). The site where they are found is called Alnus-Nivus (45.034750°N, 6.413630°E, 2034 m asl) near Col du Lautaret, French Alps. The soil data consist in temperature and volumetric liquid water content at 5 and 15 cm depths. One spot is near the alder collar (ALNUS), the other spot is 6 m away, under grass (GRASS). The meteorological data were obtained from the FR-Clt station, 750 m away (45.041278°N, 6.410611°E, 2046 m asl). See (Gupta et al., 2023) for details. Only the data relevant for heat transfer simulations are given. The simulation framework gives the alder mesh used in the heat transfer simulations. Typical simulations use a wood thermal conductivity of 1 W m<sup>-1</sup> K<sup>-1</sup> and a snow thermal conductivity of 0.1 W m<sup>-1</sup> K<sup>-1</sup>. Based on observations, the snow height at Alnus-Nivus is likely to be at least twice the value at FR-Clt. Forcing uses the snow surface temperature, derived from upwelling longwave radiation using an emissivity of 1. The data allow testing thermal bridging through shrub branches. These data are used in a publication in preparation: Domine, Fourteau, Choler, Exploration of Thermal Bridging Through Shrub Branches in Alpine Snow. Reference Gupta, A., Reverdy, A., Cohard, J. M., Hector, B., Descloitres, M., Vandervaere, J. P., Coulaud, C., Biron, R., Liger, L., Maxwell, R., Valay, J. G., and Voisin, D.: Impact of distributed meteorological forcing on simulated snow cover and hydrological fluxes over a mid-elevation alpine micro-scale catchment, Hydrol. Earth Syst. Sci., 27, 191-212, 2023.",mds,True,findable,0,0,0,0,0,2023-06-20T00:57:54.000Z,2023-06-20T00:57:55.000Z,cern.zenodo,cern,"snow,shrub,soil,heat transfer,thermal bridging,Alnus viridis","[{'subject': 'snow'}, {'subject': 'shrub'}, {'subject': 'soil'}, {'subject': 'heat transfer'}, {'subject': 'thermal bridging'}, {'subject': 'Alnus viridis'}]",,
+10.5281/zenodo.6802738,Magnetic imaging with spin defects in hexagonal boron nitride,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Data relative to the publication arXiv:2207.10477,mds,True,findable,0,0,0,0,0,2022-07-19T13:31:24.000Z,2022-07-19T13:31:25.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4029598,"Supplementary material for ""Port-Hamiltonian modeling, discretization and feedback control of a circular water tank""",Zenodo,2020,,Software,Open Access,"This archive presents the source codes and numerical results of our paper ""Port-Hamiltonian modeling, discretization and feedback control of a circular water tank"", presented at the 2019 IEEE 58th Conference on Decision and Control (CDC), in Lyon, France. The paper is available here. https://github.com/flavioluiz/Circular-Tank-PFEM-CDC-supplementary-material The following codes are provided: <code>codes/Saint_Venant1D.py</code>: reduced model of the circular tank, considering radial symmetry (Figures 1 and 2 of the paper) <code>codes/Saint_Venant2D.py</code>: nonlinear 2D model with feedback control (Figures 3 and 4 of the paper) <code>codes/AnimateSurf.py</code>: auxiliary file used to obtain the animation. A GitHub with the codes is available here. <strong>How to install and run the code?</strong> The numerical FEM model is obtained thanks to FEniCS. Firstly, you need to install it. We suggest installing it from Anaconda, as described here (check the part FEniCS on Anaconda). Once installed, you need to activate the FEniCs environment: <pre>your@user:~$ conda activate fenicsproject</pre> Then, you just need to run the Python script on the environment: <pre>(fenicsproject) your@user:~$ python Saint_Venant2D.py</pre> The scripts were tested using Python 3.7, and FEniCS 2018.1.0. <strong>Acknowledgements</strong> This work has been performed in the frame of the Collaborative Research DFG and ANR project INFIDHEM, entitled ""Interconnected of Infinite-Dimensional systems for Heterogeneous Media"", nº ANR-16-CE92-0028. Further information is available here.",mds,True,findable,0,0,0,0,0,2020-09-14T23:14:43.000Z,2020-09-14T23:14:43.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3635402,Measurement of Absolute Retinal Blood Flow Using a Laser Doppler Velocimeter Combined with Adaptive Optics,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Data set of measurements related to the following:</strong> <strong>Purpose: </strong>Development and validation of an absolute laser Doppler velocimeter (LDV) based on an adaptive optical fundus camera which provides simultaneously high definition images of the fundus vessels and absolute maximal red blood cells (RBCs) velocity in order to calculate the absolute retinal blood flow. <strong>Methods: </strong>This new absolute laser Doppler velocimeter is combined with the adaptive optics fundus camera (rtx1, Imagine Eyes©,Orsay, France) outside its optical wavefront correction path. A 4 seconds recording includes 40 images, each synchronized with two Doppler shift power spectra. Image analysis provides the vessel diameter close to the probing beam and the velocity of the RBCs in the vessels are extracted from the Doppler spectral analysis. Combination of those values gives an average of the absolute retinal blood flow. An in vitro experiment consisting of latex microspheres flowing in water through a glass-capillary to simulate a blood vessel and in vivo measurements on six healthy human retinal venous junctions were done to assess the device. <strong>Results: </strong>In the in vitro experiment, the calculated flow varied between 1.75 μl/min and 25.9 μl/min and was highly correlated (r2 = 0.995) with the imposed flow by a syringe pump. In the in vivo experiment, the error between the flow in the parent vessel and the sum of the flow in the daughter vessels was between −25% and 17% (mean±sd −2 ± 17%). Retinal blood flow in the main temporal retinal veins of healthy subjects varied between 1.3 μL/min and 28.7 μL/min <strong>Conclusion: </strong>This adaptive optics LDV prototype (aoLDV) allows the measurement of absolute retinal blood flow derived from the retinal vessel diameter and the maximum RBCs velocity in that vessel.",mds,True,findable,0,0,0,0,0,2020-02-06T10:39:05.000Z,2020-02-06T10:39:06.000Z,cern.zenodo,cern,"laser Doppler velocimetry, ocular blood flow","[{'subject': 'laser Doppler velocimetry, ocular blood flow'}]",,
+10.5281/zenodo.7092357,Code for PhD thesis: Numerical Analysis for the reconciliation in space and time of the discretizations of the air-sea exchanges and their parameterization,Zenodo,2022,en,Software,"Creative Commons Attribution 4.0 International,Open Access","Python3 code used to generate the Figures of the PhD thesis ""Numerical Analysis for the reconciliation in space and time of the discretizations of the air-sea exchanges and their parameterization"". Each chapter has a Jupyter Notebook associated to it. Some scientific packages for python3 are necessary to run the code (progressbar, scipy, numba, matplotlib).",mds,True,findable,0,0,0,0,0,2022-09-26T08:29:49.000Z,2022-09-26T08:29:49.000Z,cern.zenodo,cern,"Schwarz methods,Waveform relaxation,Semi-discrete,Finite Volume methods","[{'subject': 'Schwarz methods'}, {'subject': 'Waveform relaxation'}, {'subject': 'Semi-discrete'}, {'subject': 'Finite Volume methods'}]",,
+10.60662/n581-qq67,A Systemic approach for Material Handling System Design,CIGI QUALITA MOSIM 2023,2023,,ConferencePaper,,,fabricaForm,True,findable,0,0,0,0,0,2023-09-01T18:16:51.000Z,2023-09-01T18:16:51.000Z,uqtr.mesxqq,uqtr,,,,
+10.5281/zenodo.4603535,Atomic coordinates of the periodic amorphous ice grain model,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This dataset contains the atomic coordinates in the crystallographic interchange format (CIF) of the periodic model of an amorphous water icy grain surface as resulted from the geometry optimization at HF-3c level with the CRYSTAL17 computer code. The crystallographic unit cell has the c-axis arbitrary defined to be 60 Ã… to simulate the void upper/lower the icy surface.,mds,True,findable,0,0,0,0,0,2021-03-14T08:50:39.000Z,2021-03-14T08:50:39.000Z,cern.zenodo,cern,"Amorphous ice,HF-3c,CRYSTAL17,DFT","[{'subject': 'Amorphous ice'}, {'subject': 'HF-3c'}, {'subject': 'CRYSTAL17'}, {'subject': 'DFT'}]",,
+10.5281/zenodo.5535624,"Seasonal evolution of basal conditions within Russell sector, West Greenland, inverted from satellite observations of surface flow",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","An annual set of model-inferred basal and surface properties of ice flow at Russell Gletcher sector in Western Greenland with half-month temporal resolution. Derived using the Elmer/Ice ice-flow model by inversion of satellite-observed ice surface velocity (10.5281/zenodo.5535532). The details on the data creatoin can be found in 10.5194/tc-15-5675-2021 . Dataset contains 24 independent NetCDF files (one per 2-weeks time step) with:<br> * alpha - inverted be model basal friction coefficient in log10 (log10(MPa m-1 a)<br> * base - basal topography altitude (m)<br> * lithk - ice thickness (m)<br> * orog - surface altitude (m)<br> * strbasemag - magnitude of basal friction tb (MPa)<br> * xvelbase, yvelbase, zvelbase - 3D basal velocity (m/yr)<br> * xvelmean, yvelmean - vertically average mean horizontal velocity (m/yr)<br> * xvelsurf, yvelsurf, zvelsurf - 3D surface velocity (m/yr)<br> * n - effective pressure (MPa) The additional WinterMeanState NetCDF file (inversion from the mean velocity of january, Febriary, Mars) contains the same set of variables (except the effective pressure), and in addition contains the <em>As</em> Weertman sliding coeffitient. The results have been interpolated from the native unstructured model grid to the regular grid used for the observed velocity (10.5281/zenodo.5535624).",mds,True,findable,0,0,1,0,0,2021-10-05T09:56:20.000Z,2021-10-05T09:56:21.000Z,cern.zenodo,cern,"ice flow modelling, seasonal, ELMER-Ice, Greenland, Russell","[{'subject': 'ice flow modelling, seasonal, ELMER-Ice, Greenland, Russell'}]",,
+10.60662/ydh4-8904,Approche intégrée basée sur l’intelligence artificielle pour la reconfiguration automatique des systèmes de production,CIGI QUALITA MOSIM 2023,2023,,ConferencePaper,,,fabricaForm,True,findable,0,0,0,0,0,2023-09-01T19:53:39.000Z,2023-09-01T19:53:39.000Z,uqtr.mesxqq,uqtr,,,,
+10.5281/zenodo.4442416,An Agent-Based Model to Predict Pedestrians Trajectories with an Autonomous Vehicle in Shared Spaces: Video Results,Zenodo,2021,,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access","A video illustrating the results presented in the paper: <em>""Prédhumeau M., Mancheva L., Dugdale J., and Spalanzani A. 2021. An Agent-Based Model to Predict Pedestrians Trajectories with an Autonomous Vehicle in Shared Spaces. In the Proc. of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021). IFAAMAS, Online.""</em>",mds,True,findable,0,0,0,0,0,2021-01-15T12:04:42.000Z,2021-01-15T12:04:42.000Z,cern.zenodo,cern,"Vehicle-Pedestrian Interaction,Trajectory Prediction,Multi-Agent Simulation,Human behavior,Social Force Model","[{'subject': 'Vehicle-Pedestrian Interaction'}, {'subject': 'Trajectory Prediction'}, {'subject': 'Multi-Agent Simulation'}, {'subject': 'Human behavior'}, {'subject': 'Social Force Model'}]",,
+10.25647/liepp.pb.11,"Les effets de la réglementation du cumul des mandats de 2001 : enseignements pour la nouvelle loi de 2014 (Policy Brief, n°11)",Sciences Po - LIEPP,2014,fr,Other,,"Le texte évalue les conséquences du changement de la réglementation française de 2001en ce qui concerne le cumul des mandats, qui a limité la possibilité de tenir simultanément plusieurs mandats électifs. La comparaison avant et après la mise en œuvre de la nouvelle loi permet de conclure que (i) les candidats aux élections législatives se sont adaptés aux nouvelles règles en réduisant les mandats locaux détenus; (ii) les candidats ont également montré une tendance à changer la nature des mandats exercés. Ces résultats mettent en lumière les modalités d'application de la loi qui lui donneront toute son efficacité.",fabricaForm,True,findable,0,0,0,0,0,2022-01-04T15:00:53.000Z,2022-01-05T13:25:39.000Z,vqpf.dris,vqpf,FOS: Social sciences,"[{'subject': 'FOS: Social sciences', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.4305929,DEM simulations of size-segregation during bedload transport,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This depository contains the data of all DEM simulations used in the publication Chassagne, R., Maurin, R., Chauchat, J., Gray, J., & Frey, P. (2020). Discrete and continuum modelling of grain size segregation during bedload transport. <em>Journal of Fluid Mechanics,</em> <em>895</em>, A30. doi:10.1017/jfm.2020.274, as well as post processing scripts to use the data. The simulations are located in two folders, fine/ (simulations for which the amount of fine particles is varied) and sizeRatio (simulations for which the size ratio between large and small particles is varied). The data of each simulations are contained in separate subfolders named after the simulation. For example, Fine2R1.5/ corresponds to a simulation with 2 layers of small particles and a size ratio of 1.5. For each simulation, the time data are saved in data.hdf5 and averaged data in average.hdf5. A GeomParam.txt file is also in each folder. It contains information of the simulation that the post processing programm will read. The python script used to initiate the YADE-DEM simulation is also given for information (it contains all parameters of the simulation). The post-processing program has been coded in python2.7 with an oriented-object procedure. The h5py package is necessary to read the .hdf5 files. The scripts do not work in python3, but can be very easily adapted if necessary (you only have to modify the ""print"" functions). The scripts are available in ScriptsPP/ and are organized as follow. A mother class in SegregationPP and two child classes SegFull (to load the full time data set) and SegMean (to load only average data). A script examplePP.py is proposed and shows how to manipulate theses classes and the data.",mds,True,findable,0,0,0,1,0,2020-12-04T14:22:25.000Z,2020-12-04T14:22:25.000Z,cern.zenodo,cern,"Granular flow,Sediment transport,Size-segregation,Coupled Fluid-DEM simulations","[{'subject': 'Granular flow'}, {'subject': 'Sediment transport'}, {'subject': 'Size-segregation'}, {'subject': 'Coupled Fluid-DEM simulations'}]",,
+10.5061/dryad.zw3r2286h,Do ecological specialization and functional traits explain the abundance–frequency relationship? Arable weeds as a case study,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Aim: The abundance-frequency relationship (AFR) is among the most-investigated pattern in biogeography, yet the relative contributions of niche-based processes related to ecological strategies, and of neutral processes related to spatial colonization-extinction dynamics, remains uncertain. Here, we tested the influences of ecological specialization and functional traits on local abundance and regional frequency, to determine the contribution of niche-based processes. Location: France and the UK. Taxon: Vascular plants. Methods: We used two arable weed surveys covering 1544 fields in Western Europe (France, UK), along with functional traits related to resource acquisition, flowering phenology and dispersal. We quantified specialization both to arable habitat and to individual crop types, and performed phylogenetic path analyses to test competing models accounting for direct and indirect relationships between traits, specialization, abundance and frequency. We performed the analyses for all species in each country, as well as for a subset of the most abundant species. Results: Local abundance of weeds increased with their regional frequency, but the relationship became negative or null when considering only the most abundant weeds. Specialization to arable habitat and to individual crop type either had a similar or opposite effect on regional frequency and local abundance explaining these positive and negative relationships, respectively. Regional frequency was not directly explained by any trait but indirectly by resource requirement traits conferring specialization to the arable habitat. Conversely, high local abundance was directly related to low seed mass, high SLA, early and short flowering. Main Conclusions: Direct/indirect effects of functional traits on local abundance/regional frequency, respectively, supports a significant role of niche-based processes in AFR. Neutral spillover dynamics could further explain a direct linkage of abundance and frequency. Similar causal paths and consistent influences of traits on specialization and abundance in the two studied regions suggest genericity of these findings.",mds,True,findable,124,4,0,1,0,2021-03-12T00:57:40.000Z,2021-03-12T00:57:42.000Z,dryad.dryad,dryad,"weed biogeography,Niche-breadth,path analysis,generalist-specialist,Neutral Processes","[{'subject': 'weed biogeography'}, {'subject': 'Niche-breadth'}, {'subject': 'path analysis'}, {'subject': 'generalist-specialist'}, {'subject': 'Neutral Processes'}]",['43356 bytes'],
+10.5281/zenodo.5649827,"FIG. 43 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIG. 43—Locality of Protonemura lupina sp. n. in the southern French Alps: Bouisse spring, Estéron tributary, Conségudes, near D1, 371 m, 43.8463N, 7.0284E (photograph by Gwenole Le Guellec).",mds,True,findable,0,0,1,0,0,2021-11-05T21:12:03.000Z,2021-11-05T21:12:04.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.10046054,MIPkit-Perturbations (MISOMIP2),Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"MISOMIP2's perturbation MIPkit
+Atmospheric forcing perturbation (A1vw, W1vw)
+Atm_*_anomaly_MISOMIP2.nc
+These data are described in Mathiot and Jourdain (2023) and were initially provided on https://doi.org/10.5281/zenodo.8139775. They correspond to the monthly anomaly of the 2260-2299 mean (SSP5-8.5) with respect to the 1975-2014 mean (historical) in member r1i1p1f1 of the IPSL-CM6-LR simulations (Boucher et al., 2020).
+The anomalies to add to the present-day reanalysis forcing in MISOMIP2's A1vw and W1vw experiments are provided as 3-hourly annual climatologies on the JRA55 lon-lat grid for the following variables:
+
+dhuss: Near-Surface Specific Humidity anomaly.
+dpr: Precipitation anomaly at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective).
+dprsn: Solid precipitation anomaly at surface; includes precipitation of all forms of water in the solid phase.
+dps: Surface Air Pressure anomaly.
+drlds: Surface Downwelling Longwave Radiation anomaly.
+drsds: Surface Downwelling Shortwave Radiation anomaly.
+dtas: Near-Surface Air Temperature anomaly.
+duas: Eastward Near-Surface Wind anomaly.
+dvas: Northward Near-Surface Wind anomaly.
+The anomalies are provided for a 365-day year. If the present-day forcing used in MISOMIP2 contains leap years, then the 28-February forcing should be repeated on February 29th.
+Â
+Ocean forcing perturbation (lateral boundary conditions) (A1vw, W1vw)
+Ocean_p_*_climatology_MISOMIP2.nc and Ocean_vw_*_climatology_MISOMIP2.nc
+These files are needed to prescribe an anomaly at the lateral boundaries of regional ocean and sea-ice models in the A1vw and W1vw experiments. The data come from the global 0.25° NEMO simulations described in Mathiot and Jourdain (2023), including a simulation forced by the aformentioned perturbation of the atmospheric forcing.Â
+Given that the method to do this is open and may be done either in the physical space or in the (T,S) space, we provide both the present-day (Oceanp) and the very warm future (Oceanvw) monthly climatologies rather than the anomalies. Variables are gathered in 5 types of files:
+
+seaice files: sea ice fraction, thickness, velocities, snow thickness on ice [at T points].
+bsf files: barotropic stream function [at F points].
+gridT files: temperature, salinity, SSH [at T points].
+gridU files: x-ward ocean velocity [at U points].
+gridV files: y-ward ocean velocity [at V points].
+The NEMO grid (eORCA025.L121) is not a regular lon-lat grid, it is stretched at high southern latitudes, uses partial steps for the deepest levels, and is on a C-grid. We believe that directly interpolating from the eORCA grid to the users grid will minimise the loss of information, so we do not provide a regridded dataset. Note that we only provide the southern hemisphere data to limit file sizes.
+The grid information is provided in Ocean_mesh_mask_eORCA025.L121.nc:
+
+glamt, glamu, glamv, glamf : longitude at T, U, V, F points (degree east).
+gphit, gphiu, gphiv, gphif : latitude at T, U, V, F points (degree north).
+e1t, e1u, e1v, e1f : mesh size along x for the 4 types of meshes (meters).
+e2t, e2u, e2v, e2f : mesh size along y for the 4 types of meshes (meters).
+e3t_0, e3u_0, e3v_0 : mesh size along z (meters).
+tmask, umask, vmask, fmask : mask values for the 4 types of meshes (=1 for ocean, =0 otherwise).
+Note that the x-ward velocity (vozocrtx) and the y-ward velocity (vomecrty) are on different grids (U and V points, respectively) and need to be rotated to the target grid directions. We recommend using the barotropic stream function (BSF) to derive barotropic velocities at the lateral boundary (volume transport between two points directly given by the difference in BSF between these two points, and velocity directions so that vertically integrated velocities are defined as U=∆_y BSF and V=-∆_x BSF) and using the 3d velocities only for the baroclinic component (note that we provide the full velocities). In case this is needed, NEMO is a Boussinesq model with an ocean density of 1026 kg m-3.
+Â
+Perturbed ice shelves geometry (Ocean-A2f, Ocean-W2f)
+MISOMIP2_Ocean-x2f.nc
+The future ice draft in A2f is based on a 200-year simulation of the coupled ice-ocean model Úa-MITgcm, starting from a present-day ice-sheet geometry and forced by constant, shallow thermocline conditions on the Amundsen continental shelf (DeRydt and Naughten 2023). For the W2f experiment, the future ice draft is based on an unpublished 300-year simulation of the coupled ice-ocean model Úa-MITgcm. The model configuration is identical to the abrupt-4xCO2 experiment described in Naughten et al. (2021), but extended from 150 to 300 years based on a new timeseries of atmospheric and ocean boundary conditions from the UKESM-1-0-LL CMIP6 ensemble. The bathymetry for the A2f and W2f experiments is identical to the A2p and W2p experiments, i.e. BedMachine-Antarctica-v3 (Morlighem 2022).
+The provided dataset is formatted exactly as BedMachine-Antarctica-v3 which is used for both the Ocean-A2p and Ocean-W2p experiments.
+NSIDC provides matlab and python scripts to interpolate these data onto longitude-latitude grids: https://github.com/nsidc/nsidc0756-scripts
+Â ",api,True,findable,0,0,0,0,0,2023-11-01T05:40:24.000Z,2023-11-01T05:40:25.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23575372.v1,Additional file 5 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 4,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:51.000Z,2023-06-25T03:11:51.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['24064 Bytes'],
+10.5281/zenodo.159474,"Experimental Data For The Publication: ""Probing The Early Stages Of Shock- Induced Chondritic Meteorite Formation At The Mesoscale""",Zenodo,2017,,Dataset,"Creative Commons Attribution 4.0,Open Access","In accordance with the expectations outlined in <em><strong>Clarifications of EPSRC expectations on research data management </strong></em>(09/10/14) this data has been made publicly available to complement the open access publication ""Probing the early staged of chondritic meteorite formation at the mesoscale using single-bunch X-ray phase-contrast radiography at ESRF"".
+
+There are three data sets. The folder entitled 'DarkFrames' contains the fitted median dark frame radiographs recorded on frames 1 and 2 of the camera. The folder entitled 'Flatfields' contains the mean flatfield radiographs recorded on frames 1 and 2 of the camera. The folder entitled 'Shots' contains the radiographs recorded on static and shock-compressed samples on frames 1 and 2 of the camera.",,True,findable,0,0,0,0,0,2017-03-09T18:25:50.000Z,2017-03-09T18:25:51.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4759513,"Figs. 67-72 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access",Figs. 67-72. Larva of Protonemura dakkii sp. n. 67: front angle of the pronotum; 68: hind femur; 69: outer apical part of the femur; 70: 5–6th tergal segments; 71: fore femur; 72: eye (scale 0.1 mm).,mds,True,findable,0,0,2,0,0,2021-05-14T02:27:29.000Z,2021-05-14T02:27:30.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5061/dryad.3216c,Data from: Peatland vascular plant functional types affect methane dynamics by altering microbial community structure,Dryad,2015,en,Dataset,Creative Commons Zero v1.0 Universal,"1. Peatlands are natural sources of atmospheric methane (CH4), an important greenhouse gas. It is established that peatland methane dynamics are controlled by both biotic and abiotic conditions, yet the interactive effect of these drivers is less studied and consequently poorly understood. 2. Climate change affects the distribution of vascular plant functional types (PFTs) in peatlands. By removing specific PFTs, we assessed their effects on peat organic matter chemistry, microbial community composition and on potential methane production (PMP) and oxidation (PMO) in two microhabitats (lawns and hummocks). 3. Whilst PFT removal only marginally altered the peat organic matter chemistry, we observed considerable changes in microbial community structure. This resulted in altered PMP and PMO. PMP was slightly lower when graminoids were removed, whilst PMO was highest in the absence of both vascular PFTs (graminoids and ericoids), but only in the hummocks. 4. Path analyses demonstrate that different plant–soil interactions drive PMP and PMO in peatlands and that changes in biotic and abiotic factors can have auto-amplifying effects on current CH4 dynamics. 5. Synthesis. Changing environmental conditions will, both directly and indirectly, affect peatland processes, causing unforeseen changes in CH4 dynamics. The resilience of peatland CH4 dynamics to environmental change therefore depends on the interaction between plant community composition and microbial communities.",mds,True,findable,527,86,1,1,0,2015-04-14T14:13:05.000Z,2015-04-14T14:13:07.000Z,dryad.dryad,dryad,"path analysis,Sphagnum magellanicum,Vaccinium oxycoccus,mid–infrared spectroscopy,Graminoids,Empetrum nigrum,Sphagnum spp.,Eriophorum vaginatum,Calluna vulgaris,methanotrophic communities,methanogenesis,CH4,PLFA,Sphagnum cuspidatum,Sphagnum–dominated peatlands,Rhynchospora alba,Eriophorum angustifolium,Andromeda polifolia,pmoA,Ericoids,Sphagnum rubellum,Erica tetralix,Holocene","[{'subject': 'path analysis'}, {'subject': 'Sphagnum magellanicum'}, {'subject': 'Vaccinium oxycoccus'}, {'subject': 'mid–infrared spectroscopy'}, {'subject': 'Graminoids'}, {'subject': 'Empetrum nigrum'}, {'subject': 'Sphagnum spp.'}, {'subject': 'Eriophorum vaginatum'}, {'subject': 'Calluna vulgaris'}, {'subject': 'methanotrophic communities'}, {'subject': 'methanogenesis'}, {'subject': 'CH4'}, {'subject': 'PLFA'}, {'subject': 'Sphagnum cuspidatum'}, {'subject': 'Sphagnum–dominated peatlands'}, {'subject': 'Rhynchospora alba'}, {'subject': 'Eriophorum angustifolium'}, {'subject': 'Andromeda polifolia'}, {'subject': 'pmoA'}, {'subject': 'Ericoids'}, {'subject': 'Sphagnum rubellum'}, {'subject': 'Erica tetralix'}, {'subject': 'Holocene'}]",['249924 bytes'],
+10.5281/zenodo.6861341,Data from: Improved FIFRELIN de-excitation model for neutrino applications,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","New FIFRELIN cascades for the isotopes 156,158Gd are distributed to the community, to be used for various applications. The new cascades feature an improved modeling of de-excitation. The main improvements are: 1) Inclusion of primary transitions from EGAF database. 2) Treatment of gamma-directional correlations 3) Improved physics for the Internal Conversion process and X ray emission. With the use of the files provided, please cite the following publication: H. Almazán et al, <em>The European Physical Journal A</em> <strong>volume 59</strong>, Article number: 75 (2023) DOI: https://doi.org/10.1140/epja/s10050-023-00977-x",mds,True,findable,0,0,0,0,0,2022-07-25T06:28:39.000Z,2022-07-25T06:28:40.000Z,cern.zenodo,cern,"FIFRELIN,gamma cascade,gadolinium,neutron capture","[{'subject': 'FIFRELIN'}, {'subject': 'gamma cascade'}, {'subject': 'gadolinium'}, {'subject': 'neutron capture'}]",,
+10.5281/zenodo.10046806,"Supported PdZn nanoparticles for selective CO2 conversion, through the grafting of a heterobimetallic complex on CeZrOx",Elsevier B. V.,2022,,Dataset,Creative Commons Attribution 4.0 International,"Supplementary material: Â IR, PXRD, N2 adsorption, EDS, TEM, XPS, EXAFS, testing data",api,True,findable,0,0,0,0,0,2023-10-27T09:53:53.000Z,2023-10-27T09:53:53.000Z,cern.zenodo,cern,"surface organometallic chemistry,in-situ IR,hydrocarbon production,palladium,light alkanes","[{'subject': 'surface organometallic chemistry'}, {'subject': 'in-situ IR'}, {'subject': 'hydrocarbon production'}, {'subject': 'palladium'}, {'subject': 'light alkanes'}]",,
+10.5281/zenodo.3773905,Erroneous Reagent Checking (ERC) benchmark,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The <strong>Erroneous Reagent Checking (ERC) benchmark</strong> assesses the accuracy of fact-checkers screening biomedical publications for dubious mentions of nucleotide sequence reagents. It comes with a test collection comprised of 1,679 nucleotide sequence reagents that were curated by biomedical experts.",mds,True,findable,0,0,0,0,0,2020-04-28T14:56:06.000Z,2020-04-28T14:56:07.000Z,cern.zenodo,cern,"scientific text,biomedical literature,fact-checking,errors,nucleotide sequences,reagents,genes,benchmark,PDF","[{'subject': 'scientific text'}, {'subject': 'biomedical literature'}, {'subject': 'fact-checking'}, {'subject': 'errors'}, {'subject': 'nucleotide sequences'}, {'subject': 'reagents'}, {'subject': 'genes'}, {'subject': 'benchmark'}, {'subject': 'PDF'}]",,
+10.5281/zenodo.4421252,The exercise paradox: Avoiding physical inactivity stimuli requires higher response inhibition,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Dataset related to the paper on Response inhibition to physical inactivity stimuli using go/no-go tasks. </strong> This dataset includes: <strong>1) A codebook (including the name of the main variables)</strong> --> ""code_book_Go_noGo_Miller.xlsx"" <strong>2) Raw data of the behavioral outcomes (i.e., reaction times) of the affective go/no-go task</strong> --> ""corrected.behavioral.data.csv"" --> ""correct_Order.csv"" <strong>3) Self-reported data </strong> --> ""Self_report_data.csv"" <strong>3) EEG data </strong> --> ""gng_data"" <strong>5) R script for the data management (i.e., from the raw data to data ready to be analyzed)</strong> --> ""Data_management_Self_report_go_no_go_Miller.R"" for the self-reported data (return the file: ""Data_SR_final.RData"") --> ""Data_management_behav_go_no_go_Miller.R"" for the behavioral outcomes (return the file: ""Data_GNG_behav.RData"") --> Data ready to be analyzed ""Data_GNG_final_all.RData"" <strong>6) Eprime script for the affective go/no-go task (""Go_no_go_task.zip"")</strong> --> Images depicting physical activity and physical inactivity stimuli were kindly Share by Kullmann et al. (2014) <strong>7) R script for the models tested</strong> <strong>--> ""</strong>Models_GoNogo_Miller_VZenodo.R"" for behavioral data --> ""Models_EEG_GoNogo.R"" for EEG data",mds,True,findable,0,0,0,0,0,2021-01-06T13:17:06.000Z,2021-01-06T13:17:41.000Z,cern.zenodo,cern,"Response inhibition,inhibitory control,go/no-go,energetic cost minimization,physical activity","[{'subject': 'Response inhibition'}, {'subject': 'inhibitory control'}, {'subject': 'go/no-go'}, {'subject': 'energetic cost minimization'}, {'subject': 'physical activity'}]",,
+10.5281/zenodo.4632200,Calibration data and analyses,Zenodo,2021,,Dataset,"MIT License,Open Access",This repository contains nearly all the data and notebooks that were used throughout my PhD thesis.,mds,True,findable,0,0,0,0,0,2021-03-23T19:51:46.000Z,2021-03-23T19:51:47.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8271248,Investigating the velocity of magmatic intrusions and its relation with rock fracture toughness: insights from laboratory experiments and numerical models,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository provides compressed folders containing the velocity profiles recorded during our oil-filled crack propagation experiments and the code used to simulate those experiments. In particular, the files in compressed folders <strong>10ml</strong>, <strong>30ml</strong>, <strong>50ml</strong> and <strong>others_ml</strong> contain two columns corresponding to the tracked cracks' depth [m] and velocity [m/s]. The two folders <strong>DYKE-CODE_constant-Ef</strong> and <strong>DYKE-CODE_variable-Ef</strong> contain the Fortran90 code, the input and output files, and all the scripts needed to reproduce the simulations and the plots displayed in Figure 3 and Figure 4 of the article <em>""</em>Investigating the velocity of magmatic intrusions and its relation with rock fracture toughness: insights from laboratory experiments and numerical models<em>""</em><strong><em> </em></strong> by A. Gaete, F. Maccaferri, S. Furst, and V. Pinel.",mds,True,findable,0,0,0,0,0,2023-09-06T19:09:03.000Z,2023-09-06T19:09:03.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6397629,"Mechanism of landslide induced by glacier-retreat on the TungnakvÃslarjökull area, Iceland",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Introduction</strong> This repository contains the data used for the study of the slope instability of TungnakvÃslarjökull, Iceland, described in Lacroix et al. (submitted). Specifically, the repository contains three time series in TungnakvÃslarjökull: Time series of Digital Elevation Models (DEMs) from ASTER, 2000-2020. Time series of horizontal ground displacements, 1999-2019. Time series of earthquakes, 1995-2019. Finally, we provide the map of the rate of elevation difference and the map of horizontal ground displacements for the whole period 2000-2019, as shown in Figure 1 of Lacroix et al. (submitted). The data and methods used for the elaboration of this data repository are described in detail in Lacroix et al. (submitted). In this repository we also provide a short summary and overview of the data and methods used. <strong>Data</strong> A total of 160 ASTER scenes were used to produce the time series of DEMs. A series of images from SPOT1, Landsat-7, ASTER and Landsat-8 was used in order to produce the horizontal ground displacements maps. The South-Iceland Lowlands (SIL) network (Jóndsdóttir et al., 2007) was obtained from Veðurstofan Ãslands (www.vedur.is). Table 1 provides an overview of these data. Table1: Data used for the creation of this repository Application Platforms Acquisition dates DEM ASTER 160 scenes from 2000-10-16 to 2020-08-27. Format for the date is YYYYMMDD Horizontal ground displacement SPOT1 1987-08-05 Landsat-7 1999-07-26, 2000-08-20, 2001-09-24, 2002-07-09 ASTER 2003-08-04, 2004-09-18, 2007-08-15, 2011-08-10, 2013-07-24, 2014-08-18, 2016-08-07 Landsat-8 2014-08-12, 2015-09-16, 2016-08-24, 2017-08-20, 2018-09-14, 2019-08-10 Seismicity SIL network 370491 events recorded between 1995-2019 in the Mýrdalsjökull (S-Iceland) area and surroundings <strong>Methods</strong> The DEMs were created using the Ames StereoPipeline (ASP, Shean et al., 2016) with the same setup as used in Brun et al., (2017). Each DEM was then co-registered to a lidar DEM acquired in 2010 (Jóhannesson et al., 2013), using the co-registration methods from Berthier et al. (2007), and adding an across-track fifth-degree polynomial correction (Gardelle et al., 2013). The stack of elevations obtained from the DEM time series was linearly fitted in order to produce the map of elevation difference (file name 20000101_20210101_30x30m_UTM27N_DHDT_Lacroixetal2022.tif) of the period 2000-2020. The horizontal ground displacement maps were created using the offset tracking methodology described in Bontemps et al. (2018), consisting of: (1) pairwise image correlation using Mic-Mac (Rupnik et al., 2017), (2) masking of areas with low correlation coefficients (3) correction of co-registration bias by subtracting the mean values of the NS and EW displacement fields and (4) pixelwise fit of the horizontal ground displacements by least squares, using the time interval between measurements as weights and obtaining the full horizontal ground displacement for the analyzed period (file name 19990726_20200101_15x15m_UTM27N_HGD_Lacroixetal2022.tif) The time series of earthquakes obtained from the SIL network was filtered, and 2089 earthquakes with depth <5 km and magnitude <1.7 were used in this study and data repository (file name 19950814_20181118_SILvedur_time_lon_lat_dep_mag.txt). <strong>Acknowledgements</strong> We thank BryndÃs Brandsdóttir for providing the seismic data used in this repository. E.B. and P.L. acknowledge the support from the French Space Agency (CNES) through the TOSCA, PNTS, SWH and ISIS programs. <strong>Dataset attribution</strong> This dataset is licensed under a Creative Commons CC BY 4.0 International License. <strong>Dataset Citation</strong> Lacroix, P., Belart, J.M.C., Berthier, E., Sæmundsson, Þ., Jónsdóttir, K.: Data Repository: Mechanism of landslide induced by glacier-retreat on the TungnakvÃslarjökull area, Iceland. Dataset distributed on Zenodo: 10.5281/zenodo.6388069",mds,True,findable,0,0,0,1,0,2022-03-30T15:24:22.000Z,2022-03-30T15:24:22.000Z,cern.zenodo,cern,"Slope instability,Remote Sensing,Iceland,TungnakvÃslarjökull","[{'subject': 'Slope instability'}, {'subject': 'Remote Sensing'}, {'subject': 'Iceland'}, {'subject': 'TungnakvÃslarjökull'}]",,
+10.5281/zenodo.4695961,"Underlying data of publication Bisello, A., Colombo, E., Baricci, A., Rabissi, C., Guetaz, L., Gazdzicki, P., & Casalegno, A. (2021). Mitigated Start-Up of PEMFC in Real Automotive Conditions: Local Experimental Investigation and Development of a New Accelerated Stress Test Protocol. Journal of The Electrochemical Society, 168(5), 054501. https://doi.org/10.1149/1945-7111/abf77b",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This data set contains the underlying data of the publication Bisello, A., Colombo, E., Baricci, A., Rabissi, C., Guetaz, L., Gazdzicki, P., & Casalegno, A. (2021). Mitigated Start-Up of PEMFC in Real Automotive Conditions: Local Experimental Investigation and Development of a New Accelerated Stress Test Protocol. Journal of The Electrochemical Society, 168(5), 054501. https://doi.org/10.1149/1945-7111/abf77b. The provided files contain data shown in Fig. 2, 3, 4, 5, 6, 7, 8, and 9.",mds,True,findable,0,0,0,0,0,2021-05-05T11:13:21.000Z,2021-05-05T11:13:22.000Z,cern.zenodo,cern,"Polymer Electrolyte Fuel Cells,Start-up/shut-down,Segmented-cell,Reference Hydrogen electrode,Accelerated Stress Test,Zero-gradient cell","[{'subject': 'Polymer Electrolyte Fuel Cells'}, {'subject': 'Start-up/shut-down'}, {'subject': 'Segmented-cell'}, {'subject': 'Reference Hydrogen electrode'}, {'subject': 'Accelerated Stress Test'}, {'subject': 'Zero-gradient cell'}]",,
+10.5061/dryad.490p9,Data from: Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme,Dryad,2013,en,Dataset,Creative Commons Zero v1.0 Universal,"Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, i.e. the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population-based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic datasets to investigate the efficiency of an individual-based sampling scheme (ISS) in detecting isolation-by-distance and isolation-by-barrier patterns. Provided that pseudo-replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of inter-individual measures of genotypic dissimilarity may efficiently replace inter-population measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.",mds,True,findable,322,86,1,1,0,2013-08-22T16:56:16.000Z,2013-08-22T16:56:18.000Z,dryad.dryad,dryad,"Habitat Degradation,Ichthyosaura alpestris","[{'subject': 'Habitat Degradation'}, {'subject': 'Ichthyosaura alpestris'}]",['4550442 bytes'],
+10.5281/zenodo.3463483,"Datasets for ""The hydro-climate and freshwater supply of High-Mountain Asia under warming climate conditions""",Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains ensemble-mean fields and corresponding standard deviations of post-processed outputs of CMIP5 models for three RCP scenarios (RCP2.6, RCP4.5 and RCP8.5) described in a manuscript ""The hydro-climate and freshwater supply of High-Mountain Asia under warming climate conditions"". Each netcdf file contains one field (either an ensemble mean of a standard deviation). The fields are the following: Positive Degree Days (PDD), Total Precipitation (Ptotal), Liquid Precipitation (PLiquiq), Frozen Precipitation (Pfrozen) and Glaciers Mass Balance (MB).",mds,True,findable,0,0,0,0,0,2019-10-02T13:14:17.000Z,2019-10-02T13:14:17.000Z,cern.zenodo,cern,"High Mountain Glaciers, climate","[{'subject': 'High Mountain Glaciers, climate'}]",,
+10.25384/sage.22573164.v1,sj-docx-1-dhj-10.1177_20552076231167009 - Supplemental material for Impact of a telerehabilitation programme combined with continuous positive airway pressure on symptoms and cardiometabolic risk factors in obstructive sleep apnea patients,SAGE Journals,2023,,Text,Creative Commons Attribution Non Commercial No Derivatives 4.0 International,"Supplemental material, sj-docx-1-dhj-10.1177_20552076231167009 for Impact of a telerehabilitation programme combined with continuous positive airway pressure on symptoms and cardiometabolic risk factors in obstructive sleep apnea patients by François Bughin, Monique Mendelson, Dany Jaffuel, Jean-Louis Pépin, Frédéric Gagnadoux, Frédéric Goutorbe, Beatriz Abril, Bronia Ayoub, Alexandre Aranda, Khuder Alagha, Pascal Pomiès, François Roubille, Jacques Mercier, Nicolas Molinari, Yves Dauvilliers, Nelly Héraud and M Hayot in Digital Health",mds,True,findable,0,0,0,0,0,2023-04-07T00:07:22.000Z,2023-04-07T00:07:22.000Z,figshare.sage,sage,"111708 Health and Community Services,FOS: Health sciences,Cardiology,110306 Endocrinology,FOS: Clinical medicine,110308 Geriatrics and Gerontology,111099 Nursing not elsewhere classified,111299 Oncology and Carcinogenesis not elsewhere classified,111702 Aged Health Care,111799 Public Health and Health Services not elsewhere classified,99999 Engineering not elsewhere classified,FOS: Other engineering and technologies,Anthropology,FOS: Sociology,200299 Cultural Studies not elsewhere classified,FOS: Other humanities,89999 Information and Computing Sciences not elsewhere classified,FOS: Computer and information sciences,150310 Organisation and Management Theory,FOS: Economics and business,Science Policy,160512 Social Policy,FOS: Political science,Sociology","[{'subject': '111708 Health and Community Services', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cardiology'}, {'subject': '110306 Endocrinology', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '110308 Geriatrics and Gerontology', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111099 Nursing not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111299 Oncology and Carcinogenesis not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111702 Aged Health Care', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '111799 Public Health and Health Services not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '99999 Engineering not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Other engineering and technologies', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Anthropology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '200299 Cultural Studies not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Other humanities', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '89999 Information and Computing Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Computer and information sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '150310 Organisation and Management Theory', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Economics and business', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '160512 Social Policy', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Political science', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Sociology'}]",['778615 Bytes'],
+10.57745/nohrhj,Spatial variability of rainfall driven erosion at the catchment scale: the June 23rd 2010 rainfall event on the Galabre catchment,Recherche Data Gouv,2023,,Dataset,,"This dataset is related to the Galabre basin, a 20 km² headwater catchment located in the French Alps that is part of the Draix-Bléone Observatory. Liquid and solid discharges are continuously monitored at the catchment outlet (Legout et al. 2021). Soil erosion was modelled for a rainfall event recorded on June 23rd 2010, prescribing the effective rainfall intensity in two different ways: 1) as spatially distributed rainfall fields defined from raster files with spatial and temporal resolutions of 1 km and 15 minutes respectively, and 2) as spatially uniform rainfall fields defined as the spatial average of the rainfall fields over the entire catchment, with a time resolution of 15 minutes. Both rainfall products are equivalent in terms of the spatial average of rainfall intensity at each time step. The only difference between both simulations was the spatial variability of rainfall. The dataset contains two Iber+ models with either options of modelling rainfall, including the rainfall data as .asc rasters, as well as a spreadsheets with the output results of the simulation. The Iber+ model should be run with the executables provided by CEA & GARCIA-FEAL 2023, ""Iber+ executables (V3.2b)"", https://doi.org/10.57745/UFEK4L.",mds,True,findable,13,0,0,0,0,2023-04-04T15:34:19.000Z,2023-04-04T15:57:23.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.6055786,Assessment of future wind speed and wind power changes over South Greenland using the MAR regional climate model : MAR ouptuts and KATABATA weather stations timeseries,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Daliy MARv3.12 outputs and KATABATA weather stations timeseries used in : Lambin, C., Fettweis, X., Kittel, C., Fonder, M. and Ernst, D. (2022), Assessment of future wind speed and wind power changes over South Greenland using the MAR regional climate model, [e-print in Orbi], https://orbi.uliege.be/handle/2268/288534?&locale=en",mds,True,findable,0,0,0,0,0,2022-03-08T16:19:05.000Z,2022-03-08T16:19:09.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4761325,"Figs. 46-51 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 46-51. Dictyogenus muranyii sp. n., egg characteristics. 46. Egg, upper view from one ridge with two faces and the micropylar region visible. Bruyant, Vercors Massif, Isère dpt, France. 47. Entire egg. Archiane, Vercors Massif, Isère dpt, France. 48. Egg collar. Archiane, Vercors Massif, Isère dpt, France. 49. Egg collar. Bruyant, Vercors Massif, Isère dpt, France. 50. Detail of micropyles. Bruyant, Vercors Massif, Isère dpt, France. 51. Detail of chorion and micropyles. Archiane, Vercors Massif, Isère dpt, France.",mds,True,findable,0,0,2,0,0,2021-05-14T07:48:08.000Z,2021-05-14T07:48:08.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.4767012,The top 100 most cited papers on social entrepreneurship in 2020 and their philosophical stances,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access",Bibliographic analysis database of the 100 most cited papers on social entrepreneurship in 2020.,mds,True,findable,0,0,0,0,0,2021-05-17T08:36:25.000Z,2021-05-17T08:36:27.000Z,cern.zenodo,cern,"social entrepreneurship,review,political philosophy","[{'subject': 'social entrepreneurship'}, {'subject': 'review'}, {'subject': 'political philosophy'}]",,
+10.5281/zenodo.7982060,"FIGURES D1–D6 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,Open Access,"FIGURES D1–D6. Leuctra papukensis sp. n., adults. D1, adult male, dorsal view; D2, adult male, dorsal view; D3, adult male, lateral view; D4, adult male, vesicle, ventral view; D5, adult female, ventral view; D6, adult female, lateral view.",mds,True,findable,0,0,0,0,0,2023-05-29T13:44:15.000Z,2023-05-29T13:44:16.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.4683985,Resolving subglacial hydrology network dynamics through seismic observations on an Alpine glacier.,Zenodo,2020,en,Other,"Creative Commons Attribution 4.0 International,Open Access","This is my PhD <strong>manuscript </strong>on "" Resolving subglacial hydrology dynamics through seismic observations on an Alpine glacier "". This file can be also uploaded from: https://hal.univ-grenoble-alpes.fr/tel-03191311v1. You can also find my PhD <strong>presentation </strong>PDF and the associated <strong>video </strong>can be found here or copy/paste this link: https://www.youtube.com/watch?v=IuEv7JKiYrg&t=475s or search for <em>Ugo Nanni</em> on youtube. <strong>Summary</strong>: The way in which water flows in the subglacial environment exerts a major control on ice-bed mechanical coupling, which strongly defines glacier sliding speeds. Today our understanding on the physics of the subglacial hydrology network is limited because of the scarcity of field measurements that yield a partial representation of the heterogeneous subglacial environment. The aim of my PhD work is to use passive seismology to help overcome common observational difficulties and quantify the evolution of the subglacial hydrology network pressure conditions and its configuration. Recent works show that subglacial turbulent water flow generates seismic noise that can be related to the associated hydrodynamics properties. These analyses were conducted over a limited period of time making it unclear whether such approach is appropriate to investigate seasonal and diurnal timescales, I.e. when subglacial water flow influences the most glacier dynamics. In addition, previous studies did not consider spatial changes in the heterogeneous drainage system, and until now, almost no study has located seismic noise sources spatially scattered and temporally varying. In this PhD work I address those seismological-challenges in order to resolve the subglacial hydrology dynamics in time and space.We acquired a 2-year long continuous dataset of subglacial-water-flow-induced seismic power as well as in-situ measured glacier basal sliding speed and subglacial water discharge from the Glacier d'Argentière (French Alps). I show that a careful investigation of the seismic power within [3-7] Hz can characterize the subglacial water flow hydrodynamics from seasonal to hourly timescales and across a wide range of water discharge (from 0.25 to 10 m3/sec). Combining such observations with adequate physical frameworks, I then inverted the associated hydraulic pressure gradient and hydraulic radii. I observed that the seasonal dynamics of subglacial channels is characterized by two distinct regimes. At low discharge, channels behave at equilibrium and accommodate variations in discharge mainly through changes in hydraulic radius. At a high discharge rate and with pronounced diurnal water-supply variability, channels behave out of equilibrium and undergo strong changes in the hydraulic pressure gradient, which may help sustain high water pressure in cavities and favor high glacier sliding speed over the summer.We then conducted a one-month long dense seismic-array experiment supplemented by glacier ice-thickness and surface velocity measurements. Using this unique dataset, I developed a novel methodology to overcome the challenge of locating seismic noise sources spatially scattered and temporally varying. Doing so, I successfully retrieve the first two-dimensional map of the subglacial drainage system as well as its day-to-day evolution. Using this map, I characterize when and where the subglacial drainage system is distributed through connected cavities, which favour rapid glacier flow versus localized through a channelized system that prevents rapid glacier flow. In addition, I also use high frequency seismic ground motion amplitude to study glacier features such as crevasses, thickness or ice anisotropy in a complementary way to what is traditionally done with seismic phase analysis.The first outcome of this cross-boundary PhD work is that one can analyse passive seismic measurements to retrieve the temporal evolution of subglacial channels pressure and geometry conditions over a complete melt-season. The second is that dense seismic array measurements can be used to resolve the subglacial drainage system spatial configuration and observe the switch from distributed to localized subglacial water flow. Such advances open the way for studying similar subglacial process on different sites and in particular in Greenland and Antarctica. This also concerns numerous sub-surface environment that host similar process such as volcanoes, karst, and landslides.",mds,True,findable,0,0,0,0,0,2021-04-13T17:10:38.000Z,2021-04-13T17:10:38.000Z,cern.zenodo,cern,"cryoseismology,subglacial hydrology,glacier","[{'subject': 'cryoseismology'}, {'subject': 'subglacial hydrology'}, {'subject': 'glacier'}]",,
+10.5281/zenodo.4759495,"Figs 22-27 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs 22-27. Larva of Protonemura talboti (Nav{s, 1929). 22: front angle of the pronotum; 23: hind femur; 24: outer apical part of the femur; 25: 5–6th tergal segments; 26: basal segments of the cercus; 27: 15th segment of the cercus (scale 0.1 mm).",mds,True,findable,0,0,2,0,0,2021-05-14T02:24:25.000Z,2021-05-14T02:24:26.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.8143305,ASCII files of f_abc coefficients for Li to Si (Z=3-14) GCR species,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Full ASCII tables of f_abc coefficients, ranking the most important reactions for the production of for Li to Si GCR species (one file per GCR element). These coefficients are defined and these files are used in the paper ""Current status and desired accuracy of the isotopic production cross-sections relevant to astrophysics of cosmic rays - II. Fluorine to Silicon (and updated LiBeB)"".",mds,True,findable,0,0,0,0,0,2023-07-13T12:07:35.000Z,2023-07-13T12:07:35.000Z,cern.zenodo,cern,"Astroparticle physics,Nuclear physics,Nuclear production cross-sections,Galactic cosmic-ray physics","[{'subject': 'Astroparticle physics'}, {'subject': 'Nuclear physics'}, {'subject': 'Nuclear production cross-sections'}, {'subject': 'Galactic cosmic-ray physics'}]",,
+10.6084/m9.figshare.c.6272373.v1,Digitally-supported patient-centered asynchronous outpatient follow-up in rheumatoid arthritis - an explorative qualitative study,figshare,2022,,Collection,Creative Commons Attribution 4.0 International,"Abstract Objective A steadily increasing demand and decreasing number of rheumatologists push current rheumatology care to its limits. Long travel times and poor accessibility of rheumatologists present particular challenges for patients. Need-adapted, digitally supported, patient-centered and flexible models of care could contribute to maintaining high-quality patient care. This qualitative study was embedded in a randomized controlled trial (TELERA) investigating a new model of care consisting of the use of a medical app for ePRO (electronic patient-reported outcomes), a self-administered CRP (C-reactive protein) test, and joint self-examination in rheumatoid arthritis (RA) patients. The qualitative study aimed to explore experiences of RA patients and rheumatology staff regarding (1) current care and (2) the new care model. Methods The study included qualitative interviews with RA patients (n = 15), a focus group with patient representatives (n = 1), rheumatology nurses (n = 2), ambulatory rheumatologists (n = 2) and hospital-based rheumatologists (n = 3). Data was analyzed by qualitative content analysis. Results Participants described current follow-up care as burdensome. Patients in remission have to travel long distances. Despite pre-scheduled visits physicians lack questionnaire results and laboratory results to make informed shared decisions during face-to-face visits. Patients reported that using all study components (medical app for ePRO, self-performed CRP test and joint self-examination) was easy and helped them to better assess their disease condition. Parts of the validated questionnaire used in the trial (routine assessment of patient index data 3; RAPID3) seemed outdated or not clear enough for many patients. Patients wanted to be automatically contacted in case of abnormalities or at least have an app feature to request a call-back or chat. Financial and psychological barriers were identified among rheumatologists preventing them to stop automatically scheduling new appointments for patients in remission. Rheumatology nurses pointed to the potential lack of personal contact, which may limit the holistic care of RA-patients. Conclusion The new care model enables more patient autonomy, allowing patients more control and flexibility at the same time. All components were well accepted and easy to carry out for patients. To ensure success, the model needs to be more responsive and allow seamless integration of education material. Trial registration The study was prospectively registered on 2021/04/09 at the German Registry for Clinical Trials (DRKS00024928).",mds,True,findable,0,0,0,0,0,2022-10-29T03:17:05.000Z,2022-10-29T03:17:06.000Z,figshare.ars,otjm,"Medicine,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.3870657,Data accompanying: Impacts into a porous graphite: an investigation on crater formation and ejecta distribution,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Reconstructed X-ray tomographies and python analysis scripts for the publication ""Impacts into a porous graphite: an investigation on crater formation and ejecta distribution"" Uses the spam python toolkit, which can probably be replaced by scipy.ndimage.center_of_mass if needed.",mds,True,findable,0,0,0,0,0,2022-10-03T07:27:54.000Z,2022-10-03T07:27:55.000Z,cern.zenodo,cern,"x-ray tomography,impact crater,porous graphite","[{'subject': 'x-ray tomography'}, {'subject': 'impact crater'}, {'subject': 'porous graphite'}]",,
+10.6084/m9.figshare.c.6579520.v1,Early management of isolated severe traumatic brain injury patients in a hospital without neurosurgical capabilities: a consensus and clinical recommendations of the World Society of Emergency Surgery (WSES),figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Severe traumatic brain-injured (TBI) patients should be primarily admitted to a hub trauma center (hospital with neurosurgical capabilities) to allow immediate delivery of appropriate care in a specialized environment. Sometimes, severe TBI patients are admitted to a spoke hospital (hospital without neurosurgical capabilities), and scarce data are available regarding the optimal management of severe isolated TBI patients who do not have immediate access to neurosurgical care. Methods A multidisciplinary consensus panel composed of 41 physicians selected for their established clinical and scientific expertise in the acute management of TBI patients with different specializations (anesthesia/intensive care, neurocritical care, acute care surgery, neurosurgery and neuroradiology) was established. The consensus was endorsed by the World Society of Emergency Surgery, and a modified Delphi approach was adopted. Results A total of 28 statements were proposed and discussed. Consensus was reached on 22 strong recommendations and 3 weak recommendations. In three cases, where consensus was not reached, no recommendation was provided. Conclusions This consensus provides practical recommendations to support clinician’s decision making in the management of isolated severe TBI patients in centers without neurosurgical capabilities and during transfer to a hub center.",mds,True,findable,0,0,0,0,0,2023-04-13T10:34:20.000Z,2023-04-13T11:00:31.000Z,figshare.ars,otjm,"Medicine,Genetics,FOS: Biological sciences,Molecular Biology,Ecology,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Ecology'}, {'subject': 'Science Policy'}]",,
+10.34847/nkl.748eqz51,"Dans le lit de la Romanche. Itinéraire de Gisèle, le 24 mai 2019, Livet",NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Other,,"Itinéraire réalisé dans le cadre du projet de recherche-création Les Ondes de l’Eau : Mémoires des lieux et du travail dans la vallée de la Romanche. AAU-CRESSON (Laure Brayer, direction scientifique) - Regards des Lieux (Laure Nicoladzé, direction culturelle).
+
+Depuis plus de 65 ans, Gisèle et son mari se sont installés ici, façonnant peu à peu ce petit coin de paradis. Chaque été, le temps des grandes vacances, le gigantesque jardin qui mène à la Romanche se transforme en terrain d’aventures. Le long de chemins escarpés, dans des sous- bois jonchés de branches, écartant les feuilles et enjambant les sources, nous sommes allées explorer les abords de cette rivière au lit changeant.",api,True,findable,0,0,0,0,0,2022-06-27T12:23:16.000Z,2022-06-27T12:23:16.000Z,inist.humanum,jbru,"Histoires de vie,paysage de l'eau,histoire orale,Marche,Sens et sensations,Mémoires des lieux,Perception sensible,méthode des itinéraires,environnement sonore,forêt,Romanche, Vallée de la (France),plantes sauvages,énergie hydraulique,perception de l'espace,loisirs de plein air,jardinage,déchets,roman-photo,itinéraire,matériaux de terrain éditorialisés","[{'lang': 'fr', 'subject': 'Histoires de vie'}, {'lang': 'fr', 'subject': ""paysage de l'eau""}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'Marche'}, {'lang': 'fr', 'subject': 'Sens et sensations'}, {'lang': 'fr', 'subject': 'Mémoires des lieux'}, {'lang': 'fr', 'subject': 'Perception sensible'}, {'lang': 'fr', 'subject': 'méthode des itinéraires'}, {'lang': 'fr', 'subject': 'environnement sonore'}, {'lang': 'fr', 'subject': 'forêt'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'plantes sauvages'}, {'lang': 'fr', 'subject': 'énergie hydraulique'}, {'lang': 'fr', 'subject': ""perception de l'espace""}, {'lang': 'fr', 'subject': 'loisirs de plein air'}, {'lang': 'fr', 'subject': 'jardinage'}, {'lang': 'fr', 'subject': 'déchets'}, {'lang': 'fr', 'subject': 'roman-photo'}, {'lang': 'fr', 'subject': 'itinéraire'}, {'lang': 'fr', 'subject': 'matériaux de terrain éditorialisés'}]","['19452166 Bytes', '955583 Bytes', '109809 Bytes', '315230 Bytes', '2014325 Bytes', '1762645 Bytes', '1586399 Bytes', '1523364 Bytes', '1930760 Bytes', '2358648 Bytes', '1819325 Bytes', '2114235 Bytes', '2202343 Bytes', '2182986 Bytes', '1875598 Bytes', '1911973 Bytes']","['application/pdf', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg']"
+10.5281/zenodo.7614856,Design and optimization of a Chloride Molten Salt Fast Reactor - dataset,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset used for the figures presented in the paper ""Design and optimization of a Chloride Molten Salt Fast Reactor"" for the ICAPP2023 conference",mds,True,findable,0,0,0,0,0,2023-02-07T15:23:35.000Z,2023-02-07T15:23:36.000Z,cern.zenodo,cern,"U238 capture rates, fertile blanket width, feedbacks, neutron spectrum map, reprocessing rates","[{'subject': 'U238 capture rates, fertile blanket width, feedbacks, neutron spectrum map, reprocessing rates'}]",,
+10.5281/zenodo.1476113,Confocal Fluorescence Microscopy Images Of The Lacuno-Canalicular Network In Bone Femoral Diaphysis Of Mice From The Bionm1 Project (Space Flight),Zenodo,2018,,Dataset,"Creative Commons Attribution 4.0,Open Access","This data set provides complementary measurements to a separate THG data set of the same study: doi: 10.5281/zenodo.1475906
+
+Data set for 1 sample of each of the 3 groups: Control, Space Flight and Synchro (ground control with space flight housing and feeding conditions). Contains confocal fluorescence microscopy images in tif format of 2D mosaic of selected samples and 3D stacks in selected anatomical regions of interest. See readme file for more information.",mds,True,findable,2,0,0,0,0,2018-10-31T17:59:18.000Z,2018-10-31T17:59:19.000Z,cern.zenodo,cern,"Confocal microscopy, fluorescence, bone, osteocyte, LCN, lacunae, canaliculi, space flight","[{'subject': 'Confocal microscopy, fluorescence, bone, osteocyte, LCN, lacunae, canaliculi, space flight'}]",,
+10.5281/zenodo.5189179,MICCAI 2016 challenge dataset demographics data,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This dataset contains supplementary material for the 2016 MS segmentation challenge data article. It contains the full demographic data for the datasets opened to the public.,mds,True,findable,0,0,0,0,0,2021-08-12T15:52:54.000Z,2021-08-12T15:52:55.000Z,cern.zenodo,cern,,,,
+10.57745/gzkuzs,Ventricular-fold dynamics in human phonation,Recherche Data Gouv,2022,,Dataset,,"This database of images, audio samples and highspeed videos have been established as a supplementary material to the paper : “Ventricular-fold dynamics in human phonation†Bailly L., Henrich Bernardoni N., Müller F., Rohlfs A-K., Hess M., JSLHR, Vol. 57 pp. 1219–1242, August 2014 (https://hal.archives-ouvertes.fr/hal-00998464). It completes Figures B1 and B2 in Appendix B. It includes 58 videos (avi format, without sound for highspeed videos), the 2*58 audio files in wav, ""short"" and ""long"" version (with context), 58 images of folds (png format) and 58 associated kymographic images (bmp format). The whole database is 1.66 GB. The largest files are the videos, from 6 to 102 MB.",mds,True,findable,119,7,0,0,0,2022-06-23T12:01:02.000Z,2022-07-08T08:35:24.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.2540773,Yam genomics supports West Africa as a major cradle of crop domestication,Zenodo,2019,,Dataset,"Creative Commons Attribution Non Commercial Share Alike 4.0 International,Open Access","167 yam samples were fully resequenced (WGS, Illumina HiSeq) and mapped (BWA) to the Dioscorea rotundata genome (BDMI01000001.1 to BDMI01000021.1). Calling_ALL_Rotundata_Allc05.vcf.gz is the result of the SNP calling (GATK). See associated publication for details;",mds,True,findable,2,0,0,0,0,2019-01-15T14:21:21.000Z,2019-01-15T14:21:22.000Z,cern.zenodo,cern,,,,
+10.34847/nkl.81dcdekj,Histoire de la Société d'études italiennes,NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Book,,,api,True,findable,0,0,0,0,0,2022-06-28T14:09:19.000Z,2022-06-28T14:09:19.000Z,inist.humanum,jbru,Etudes italiennes,"[{'lang': 'fr', 'subject': 'Etudes italiennes'}]","['9097465 Bytes', '7416683 Bytes', '9282460 Bytes', '8907544 Bytes', '8799070 Bytes', '8751142 Bytes', '8883043 Bytes', '8854078 Bytes', '9254668 Bytes', '8599864 Bytes', '8792680 Bytes', '8913379 Bytes', '9142621 Bytes', '9078376 Bytes', '8741896 Bytes', '8768425 Bytes', '9371872 Bytes', '10155217 Bytes', '8874292 Bytes', '8991184 Bytes', '9151126 Bytes', '9029416 Bytes', '8833840 Bytes', '8645749 Bytes', '8984503 Bytes', '9104779 Bytes', '9083704 Bytes', '9129640 Bytes', '8991916 Bytes', '8870686 Bytes', '8942368 Bytes', '8877484 Bytes', '8990458 Bytes', '8738002 Bytes', '9089236 Bytes', '8899528 Bytes', '9166045 Bytes', '8746906 Bytes', '8934232 Bytes', '9108013 Bytes', '8750344 Bytes', '8841088 Bytes', '9063529 Bytes', '8678512 Bytes', '9126250 Bytes', '8955814 Bytes', '9153598 Bytes', '9105520 Bytes', '8982352 Bytes', '9005464 Bytes', '9093784 Bytes', '8923579 Bytes', '8910184 Bytes', '8986132 Bytes', '8956915 Bytes', '8643076 Bytes', '8739199 Bytes', '8970193 Bytes', '8731336 Bytes', '8730004 Bytes', '8585428 Bytes', '8853844 Bytes', '9099775 Bytes', '8922001 Bytes', '9018292 Bytes', '8726236 Bytes', '8906944 Bytes', '8817862 Bytes', '8782159 Bytes', '8980324 Bytes', '9100354 Bytes', '8920492 Bytes', '8933611 Bytes', '9053359 Bytes', '8990599 Bytes', '8861440 Bytes', '9090760 Bytes', '9004756 Bytes', '9013276 Bytes', '9112240 Bytes', '9062704 Bytes', '9096484 Bytes', '9042016 Bytes', '9109333 Bytes', '8979859 Bytes', '9068872 Bytes', '9027544 Bytes', '8715541 Bytes', '8659984 Bytes', '8917960 Bytes', '8823898 Bytes', '8741800 Bytes', '8765539 Bytes', '9058498 Bytes', '8832010 Bytes', '9170812 Bytes', '9279169 Bytes', '9430825 Bytes', '10287784 Bytes', '75295 Bytes', '75304 Bytes']","['image/tiff', 'application/pdf', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'application/json', 'application/json']"
+10.57745/tor3sf,Caractérisation d’un poste de soudure Cold Métal Transfer pour le pilotage du procédé Wire Arc Additive Manufacturing,Recherche Data Gouv,2023,,Dataset,,Les données présentées ici font partie de l'article : Pilotage d’un poste de soudure Cold Métal Transfert pour le Wire Arc Additive Manufacturing Les données permettent produire les graphiques en 3 dimensions ainsi que la diffusion des résultats produits. Le jeu de données contient les fichiers suivant : - data.csv : ensemble des données utilisé dans cet article - graph.py : fonctions pour générer les graphiques de l'article en 3 Dimentions. - main.py : fichier principal pour lancer le code. Il permet de changer la valeur exemple de wfs_v consigne ainsi que les points aberrants.,mds,True,findable,89,10,0,0,0,2023-01-10T14:45:48.000Z,2023-01-26T13:29:24.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.1156633,Sheet Flow Data,Zenodo,2018,en,Dataset,"Creative Commons Attribution 4.0,Open Access","The netCDF files ""data_expe_mb1.nc"" and ""data_expe_mb2.nc"" contains the experimental results of intense sediment transport experiments (sheet flow) carried out in the LEGI tilting flume. Synchronised and colocated concentration and veclocity (wall-normal and streamwise components) measurements have been obtained by using the Acoustic Concentration and Velocity Profiler (ACVP - Hurther et al., 2011). Details about the experimental protocol can be found in Revil-Baudard et al. (2015) and Revil-Baudard et al. (2016). As there is no sediment recirculation in the flume, the same run has been repeated several times to perform ensemble averages. The results of two-phase flow numerical simulations performed using SedFOAM-2.0 are disseminated in two formats (i) the complete openFOAM case directories can be found in the repository ""data_num"" (ii) NetCDF files containing the concentration, velocity, shear stress and Turbulent Kinetic Energy profiles. The repository contains different combination of intergranular stress and turbulence models: the mu(I) rheology or the kinetic theory of granular flows and mixing length or k-epsilon turbulence models. All the details concerning the numerical results and the configurations can be found in Chauchat et al. (2017a) The SedFOAM-2.0 source code is distributed under a GNU General Public License v2.0 (GNU GPL v2.0) and is available at https://github.com/SedFoam/sedfoam/releases/tag/v2.0 or on Zenodo at https://zenodo.org/record/836643#.Wc47Yoo690s with the following DOI https://doi.org/10.5281/zenodo.836643 (Chauchat et al.,2017b).",,True,findable,0,0,0,0,0,2018-01-22T09:43:53.000Z,2018-01-22T09:43:53.000Z,cern.zenodo,cern,"Sediment transport,Sheet flow,Experiments,Acoustic measurements,Two-phase flow model,turbulence,numerical simulation","[{'subject': 'Sediment transport'}, {'subject': 'Sheet flow'}, {'subject': 'Experiments'}, {'subject': 'Acoustic measurements'}, {'subject': 'Two-phase flow model'}, {'subject': 'turbulence'}, {'subject': 'numerical simulation'}]",,
+10.48380/061t-ae68,Pressure anomaly of the ATP hydrolysis rate facilitates life of extremophiles,Deutsche Geologische Gesellschaft - Geologische Vereinigung e.V. (DGGV),2022,en,Text,,"<p>Life is prevalent on Earth even in extreme environments, e.g., near black smokers. This biological community has to face temperatures of up to 120 °C and pressures of 40 MPa. To maintain vital reactions, extremophiles have developed varies mechanisms to survive. The stability of the energy-storing molecules adenosine triphosphate (ATP) and adenosine diphosphate (ADP) are of essential importance because reactions involving these phosphates constrain the range of life. ATP is limited by the non-enzymatic hydrolysis, which is kinetically enhanced at high temperatures. If this abiotic process is too rapid, metabolism as we know won’t be possible anymore. The effect of elevated temperatures on the hydrolysis rate constants of ATP is widely known and is best described by an Arrhenius relationship. In contrast to previous studies, our first findings showed a decelerating effect from 0 – 60 MPa with a minimum in the reaction rate at 20 – 40 MPa at 100 °C. The rate constants of the non-enzymatic hydrolysis of ATP are decreasing from 5.8 x 10-4 s-1 at 0.1 MPa to 4.2 x 10-4s-1 at 20 MPa at 100 °C. The corresponding half-lives are 1195 s and 20 MPa. This observation is extremely fascinating as Takai et al. (2008) have seen a similar pressure anomaly at extreme temperatures for Methanopyrus Kandleri.</p>
+",api,True,findable,0,0,0,0,0,2023-05-31T13:59:01.000Z,2023-05-31T13:59:01.000Z,mcdy.dohrmi,mcdy,,,,
+10.5281/zenodo.10020955,robertxa/Pecube-Color_coding_Texwrangler: First release,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,Color coding file for Pecube input files in TextWrangler,api,True,findable,0,0,0,0,0,2023-10-19T08:39:59.000Z,2023-10-19T08:39:59.000Z,cern.zenodo,cern,,,,
+10.25384/sage.c.6837354,Perceived Quality of Life in Intensive Care Medicine Physicians: A French National Survey,SAGE Journals,2023,,Collection,Creative Commons Attribution 4.0 International,"PurposeThere is a growing interest in the quality of work life (QWL) of healthcare professionals and staff well-being. We decided to measure the perceived QWL of ICU physicians and the factors that could influence their perception. <b>Methods:</b> We performed a survey coordinated and executed by the French Trade Union of Intensive Care Physicians (SMR). QWL was assessed using the French version of the Work-Related Quality of Life (WRQoL) scale, perceived stress using the French version of 10 item-Perceived Stress Scale (PSS-10) and group functioning using the French version of the Reflexivity Scale, the Social Support at Work Questionnaire (QSSP-P). <b>Results:</b> 308 French-speaking ICU physicians participated. 40% perceived low WRQoL, mainly due to low general well-being, low satisfaction with working conditions and low possibility of managing the articulation between their private and professional lives. Decreased QWL was associated with being a woman (p = .002), having children (p = .022) and enduring many monthly shifts (p = .022). <b>Conclusions:</b> This work highlights the fact that ICU physicians feel a significant imbalance between the demands of their profession and the resources at their disposal. Communication and exchanges within a team and quality of social support appear to be positive elements to maintain and/or develop within our structures.",mds,True,findable,0,0,0,0,0,2023-09-15T12:11:54.000Z,2023-09-15T12:11:54.000Z,figshare.sage,sage,"Emergency Medicine,Aged Health Care,Respiratory Diseases","[{'subject': 'Emergency Medicine'}, {'subject': 'Aged Health Care'}, {'subject': 'Respiratory Diseases'}]",,
+10.5281/zenodo.7802771,Theoretical water binding energy distribution and snowline in protoplanetary disks,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Zip file containing all the structures and input obtained in our accepted article for publication in ApJ, 2023 To easily handle all these structures an online interactive page is created: https://tinaccil.github.io/Jmol_BE_H2O_visualization/",mds,True,findable,0,0,0,0,0,2023-04-05T15:17:36.000Z,2023-04-05T15:17:37.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5645545,Seismic source location with a match field processing approach during the RESOLVE dense seismic array experiment on the Glacier d'Argentiere,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This deposit contains the data set we used in our paper ‘<em>Dynamic imaging of glacier structures at high-resolution using source localization with a dense seismic array</em>’. The paper is in review for GRL and a preprint can be found here: 10.1002/essoar.10507953.1. The dataset present here contains 34 files named ‘<strong>beam_15423_jd***.h5</strong>’. These files correspond to the output of the matched field processing for each day. They are in .h5 format and we provide a matlab code (<strong>read_MFP_data.m</strong>) to read these files. These files can be read with any other language since they are in . h5. In linux you can use <strong>h5dump –A filename.h5</strong> and you can see the content of each files. More information on how the MFP process is conducted can be found in on the website dedicated to this aspect or on our paper. The whole procedure and associated codes is provided on the lecoinal.gricad-pages.univ-grenoble-alpes.fr/resolve/. We also deliver with this deposit one day of seismic data <strong>ZO_2018_121.h5 </strong>that can be used to test our MFP process. The data corresponds to the signal measured for 24 hours at each of the 98 sensors with a sampling rate of 500 Hz. More information on these seimsic signals can be found on our website and the whole seimsic dataset can be found here https://seismology.resif.fr/networks/#/ZO__2018. Detailed for downloading the dataset should be search on our website. Other dataset linked to this project are: Nanni, Ugo, Gimbert, Florent, Roux, Phillipe, & Lecointre, Albanne. (2020). DATA of ""Resolving the 2D temporal evolution of subglacial water flow with dense seismic array observations."" [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4024660 Nanni, Gimbert, Roux, Helmstetter, Garambois, Lecointre, Walpersdorf, Jourdain, Langlais, Laarman, Lindner, Sergenat, Vincent, & Walter. (2020). DATA of the RESOLVE Project (https://resolve.osug.fr/) [Data set]. In Seismological Research Letters (Version v0). Zenodo. https://doi.org/10.5281/zenodo.3971815 This dataset is also linked to two other study: <em>Observing the subglacial hydrology network and its dynamics with a dense seismic array: </em> https://doi.org/10.1073/pnas.2023757118 <em>A Multiâ€Physics Experiment with a Temporary Dense Seismic Array on the Argentière Glacier, French Alps: The RESOLVE Project</em> https://doi.org/10.1785/0220200280 Do not hesitate to contact us if you would like to try this approach an another dataset.",mds,True,findable,0,0,0,1,0,2021-11-11T16:15:49.000Z,2021-11-11T16:15:50.000Z,cern.zenodo,cern,"dense seismic array,cryoseismology,subsurface imaging,matched field processing MFP","[{'subject': 'dense seismic array'}, {'subject': 'cryoseismology'}, {'subject': 'subsurface imaging'}, {'subject': 'matched field processing MFP'}]",,
+10.5281/zenodo.7840469,"Consilience across multiple, independent genomic data sets reveals species in a complex with limited phenotypic variation",Zenodo,2023,,Other,"Creative Commons Attribution 4.0 International,Open Access","Species delimitation in the genomic era has focused predominantly on the application of multiple analytical methodologies to a single massive parallel sequencing (MPS) data set, rather than leveraging the unique but complementary insights provided by different classes of MPS data. In this study we demonstrate how the use of two independent MPS data sets, a sequence capture data set and a single nucleotide polymorphism (SNP) data set generated via genotyping-by-sequencing, enables the resolution of species in three complexes belonging to the grass genus <em>Ehrharta, </em>whose strong population structure and subtle morphological variation limit the effectiveness of traditional species delimitation approaches. Sequence capture data are used to construct a comprehensive phylogenetic tree of <em>Ehrharta </em>and to resolve population relationships within the focal clades, while SNP data are used to detect patterns of gene pool sharing across populations, using a novel approach that visualises multiple values of K. Given that the two genomic data sets are fully independent, the strong congruence in the clusters they resolve provides powerful ratification of species boundaries in all three complexes studied. Our approach is also able to resolve a number of single-population species and a probable hybrid species, both which would be difficult to detect and characterize using a single MPS data set. Overall, the data reveal the existence of 11 and five species in the <em>E. setacea</em> and <em>E. rehmannii </em>complexes, with the <em>E. ramosa</em> complex requiring further sampling before species limits are finalized. Despite phenotypic differentiation being generally subtle, true crypsis is limited to just a few species pairs and triplets. We conclude that, in the absence of strong morphological differentiation, the use of multiple, independent genomic data sets is necessary in order to provide the cross-data set corroboration that is foundational to an integrative taxonomic approach.",mds,True,findable,0,0,0,0,0,2023-04-18T14:50:45.000Z,2023-04-18T14:50:45.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.5s77q,Data from: Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 Genomes data,Dryad,2015,en,Dataset,Creative Commons Zero v1.0 Universal,"To characterize natural selection, various analytical methods for detecting candidate genomic regions have been developed. We propose to perform genome-wide scans of natural selection using principal component analysis (PCA). We show that the common FST index of genetic differentiation between populations can be viewed as the proportion of variance explained by the principal components. Considering the correlations between genetic variants and each principal component provides a conceptual framework to detect genetic variants involved in local adaptation without any prior definition of populations. To validate the PCA-based approach, we consider the 1000 Genomes data (phase 1) considering 850 individuals coming from Africa, Asia, and Europe. The number of genetic variants is of the order of 36 millions obtained with a low-coverage sequencing depth (3×). The correlations between genetic variation and each principal component provide well-known targets for positive selection (EDAR, SLC24A5, SLC45A2, DARC), and also new candidate genes (APPBPP2, TP1A1, RTTN, KCNMA, MYO5C) and noncoding RNAs. In addition to identifying genes involved in biological adaptation, we identify two biological pathways involved in polygenic adaptation that are related to the innate immune system (beta defensins) and to lipid metabolism (fatty acid omega oxidation). An additional analysis of European data shows that a genome scan based on PCA retrieves classical examples of local adaptation even when there are no well-defined populations. PCA-based statistics, implemented in the PCAdapt R package and the PCAdapt fast open-source software, retrieve well-known signals of human adaptation, which is encouraging for future whole-genome sequencing project, especially when defining populations is difficult.",mds,True,findable,446,51,1,1,0,2016-01-05T10:16:27.000Z,2016-01-05T10:16:28.000Z,dryad.dryad,dryad,"selection scan,1000 genomes,FST,Principal component analysis","[{'subject': 'selection scan'}, {'subject': '1000 genomes'}, {'subject': 'FST'}, {'subject': 'Principal component analysis', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['418960469 bytes'],
+10.5281/zenodo.4590885,Systematic Mapping Study of Security in Multi-Embedded-Agent Systems dataset,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The dataset used for in the article “Systematic Mapping Study of Security in Multi-Embedded-Agent Systems†submitted to IEEE Access. The dataset contains all the data manipulated during the mapping study, from the search exports to the full classification of selected papers. It should allow reproduction of the study.",mds,True,findable,0,0,0,0,0,2021-03-09T14:13:15.000Z,2021-03-09T14:13:16.000Z,cern.zenodo,cern,"Multi-agent system with embedded agents,security architecture,systematic mapping study","[{'subject': 'Multi-agent system with embedded agents'}, {'subject': 'security architecture'}, {'subject': 'systematic mapping study'}]",,
+10.5281/zenodo.8205153,CMB heat flux PCA results,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Results of the principal component analysis of the CMB heat flux for the five cases discussed in the publication ""On the impact of True Polar Wander on heat flux patterns at the core-mantle boundary"". For each case, the PCA results include for different files: - avg_pattern: Spherical harmonic decomposition of the CMB heat flux average pattern - patterns: Spherical harmonic decomposition of the PCA components patterns - sing_val: Singular value of the PCA components - weights: Time dependent weights of the PCA components",mds,True,findable,0,0,0,0,0,2023-08-01T14:18:18.000Z,2023-08-01T14:18:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4804639,FIGURES 18–21 in Review and contribution to the stonefly (Insecta: Plecoptera) fauna of Azerbaijan,Zenodo,2021,,Image,Open Access,"FIGURES 18–21. Protonemura sp. AZE-1 from the Talysh Mts—18: female terminalia, ventral view; 19: female inner genitalia, dorsal view; 20: habitus of matured male larva, dorsal view; 21: habitat (site 12)—scale 0.5 mm for Figs. 18–19, 1 mm for Fig. 20.",mds,True,findable,0,0,2,0,0,2021-05-26T07:55:10.000Z,2021-05-26T07:55:11.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.4943234,"Supplementary Data Set for ""Seeds of imperfection rule the mesocrystalline disorder in natural anhydrite single crystals""",Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Complete data sets: 1. DATA_SAXS_WAXS.zip - raw and reduced SAXS and WAXS measurements. NXS format and metadata 2. M-ERSC2020110901CT.zip - raw X-ray microtomography dataset. TIFF format and metadata. 3. Video_1_CT_3D_overview_XY_rotation.avi - uncompressed video 4. Video_2_CT_3D_overview_ZX_rotation.avi - uncompressed video 5. Video_3_CT_3D_internal_structure_XY_rotation.avi - uncompressed video,mds,True,findable,0,0,0,0,0,2021-06-17T05:00:44.000Z,2021-06-17T05:00:46.000Z,cern.zenodo,cern,"calcium sulfate,calcium sulphate,anhydrite,single crystal,mesocrystal,nucleation and growth,crystallisation,particle mediated","[{'subject': 'calcium sulfate'}, {'subject': 'calcium sulphate'}, {'subject': 'anhydrite'}, {'subject': 'single crystal'}, {'subject': 'mesocrystal'}, {'subject': 'nucleation and growth'}, {'subject': 'crystallisation'}, {'subject': 'particle mediated'}]",,
+10.6084/m9.figshare.c.6627480,Healthcare students’ prevention training in a sanitary service: analysis of health education interventions in schools of the Grenoble academy,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background The sanitary service is a mandatory prevention training programme for all French healthcare students. Students receive training and then have to design and carry out a prevention intervention with various populations. The aim of this study was to analyse the type of health education interventions carried out in schools by healthcare students from one university in order to describe the topics covered and the methods used. Method The 2021–2022 sanitary service of University Grenoble Alpes involved students in maieutic, medicine, nursing, pharmacy and physiotherapy. The study focused on students who intervened in school contexts. The intervention reports written by the students were read doubly by independent evaluators. Information of interest was collected in a standardised form. Results Out of the 752 students involved in the prevention training program, 616 (82%) were assigned to 86 schools, mostly primary schools (58%), and wrote 123 reports on their interventions. Each school hosted a median of 6 students from 3 different fields of study. The interventions involved 6853 pupils aged between 3 and 18 years. The students delivered a median of 5 health prevention sessions to each pupil group and spent a median of 25 h (IQR: 19–32) working on the intervention. The themes most frequently addressed were screen use (48%), nutrition (36%), sleep (25%), harassment (20%) and personal hygiene (15%). All students used interactive teaching methods such as workshops, group games or debates that was addressed to pupils’ psychosocial (mainly cognitive and social) competences. The themes and tools used differed according to the pupils’ grade levels. Conclusion This study showed the feasibility of conducting health education and prevention activities in schools by healthcare students from five professional fields who had received appropriate training. The students were involved and creative, and they were focused on developing pupils’ psychosocial competences.",mds,True,findable,0,0,0,0,0,2023-05-03T03:20:27.000Z,2023-05-03T03:20:27.000Z,figshare.ars,otjm,"Medicine,Biotechnology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}]",,
+10.5281/zenodo.7499314,VIP: A Python package for high-contrast imaging,Zenodo,2023,,Software,"Creative Commons Attribution 4.0 International,Open Access","VIP is a Python package providing the tools to reduce, post-process and analyze high-contrast imaging datasets, enabling the detection and characterization of directly imaged exoplanets, circumstellar disks, and stellar environments. VIP is a collaborative project which started at the University of Liège, aiming to integrate open-source, efficient, easy-to-use and well-documented implementations of state-of-the-art algorithms used in the context of high-contrast imaging.",mds,True,findable,0,0,0,0,0,2023-01-02T13:57:10.000Z,2023-01-02T13:57:11.000Z,cern.zenodo,cern,"Python,astronomy,exoplanets,high-contrast,direct imaging","[{'subject': 'Python'}, {'subject': 'astronomy'}, {'subject': 'exoplanets'}, {'subject': 'high-contrast'}, {'subject': 'direct imaging'}]",,
+10.5281/zenodo.4761309,"Fig. 28 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 28. Dictyogenus muranyii sp. n., male, head and pronotum. Karstic spring of Bruyant, Isère dpt, France. Photo B. Launay.",mds,True,findable,0,0,2,0,0,2021-05-14T07:45:44.000Z,2021-05-14T07:45:44.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.6084/m9.figshare.23575369,Additional file 4 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 3,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:48.000Z,2023-06-25T03:11:49.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['45056 Bytes'],
+10.5281/zenodo.7533669,"Dataset for ""Strong coupling between a photon and a hole spin in silicon""",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the raw data and its analysis code to generate the figures of the publication entitled : ""Strong coupling between a photon and a hole spin in silicon"". Please have a look at the readme.txt file for further information.",mds,True,findable,0,0,0,0,0,2023-01-13T10:33:01.000Z,2023-01-13T10:33:01.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7030107,"Dataset for "" 4D nanoimaging of early age cement hydration "" Nature Communications paper",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Abstract of the Nature Communications paper from this dataset is: ""Despite a century of research, our understanding of cement dissolution and precipitation processes at early ages is very limited. This is due to the lack of methods that can image these processes with enough spatial resolution, contrast and field of view. Here, we adapt near-field ptychographic nanotomography to in situ visualise the hydration of commercial Portland cement in a record-thick capillary. At 19h, porous C-S-H gel shell, thickness of 500 nm, covers every alite grain enclosing a water gap. The spatial dissolution rate of small alite grains in the acceleration period, ∼100 nm/h, is approximately four times faster than that of large alite grains in the deceleration stage, ∼25 nm/h. Etch-pit development has also been mapped out. This work is complemented by laboratory and synchrotron microtomographies, allowing to measure the particle size distributions with time. 4D nanoimaging will allow mechanistically study dissolution-precipitation processes including the roles of accelerators and superplasticizers. """,mds,True,findable,0,0,0,0,0,2023-05-02T08:31:40.000Z,2023-05-02T08:31:42.000Z,cern.zenodo,cern,"Nanotomography,Microtomography,Ptychography,Imaging,Portland Cement,Machine Learning,In situ Analysis","[{'subject': 'Nanotomography'}, {'subject': 'Microtomography'}, {'subject': 'Ptychography'}, {'subject': 'Imaging'}, {'subject': 'Portland Cement'}, {'subject': 'Machine Learning'}, {'subject': 'In situ Analysis'}]",,
+10.6084/m9.figshare.22649276.v1,Additional file 2 of Predictors of changing patterns of adherence to containment measures during the early stage of COVID-19 pandemic: an international longitudinal study,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 2: Supplementary Table 2. Number of the participants involved in the study from each country and geographical region.,mds,True,findable,0,0,0,0,0,2023-04-18T04:38:31.000Z,2023-04-18T04:38:31.000Z,figshare.ars,otjm,"Medicine,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['30771 Bytes'],
+10.5281/zenodo.4784408,FIGURE 1 in Delimitation of the series Laurifoliae in the genus Passiflora (Passifloraceae),Zenodo,2017,,Image,Open Access,FIGURE 1. Flowers of the series Laurifoliae. A: P. acuminata (photo: J. B. Fernandes da Silva); B: P. ambigua (photo: R. Aguilar); C: P. venusta (photo: D. Scherberich); D: P. cerasina (photo: M. Vecchia); E: P. crenata (photo: M. Rome); F: P. fissurosa (photo: M. de Souza); G: P. laurifolia (photo: F. Booms); H: P. nigradenia (photo: D. Scherberich); I: P. nitida (photo: M. Rome); J: P. popenovii (photo: G. Coppens d'Eeckenbrugge); K: P. rufostipulata (photo: C. Houel); L: P. gabrielliana (photo: M. Rome): M: P. ischnoclada (photo: C. Houel); N: P. kikiana in Cervi (2010); O: P. guazumaefolia (photo: J. Ocampo); P: P. odontophylla (flower of the type specimen).,mds,True,findable,0,0,0,0,0,2021-05-24T22:31:40.000Z,2021-05-24T22:31:40.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.6084/m9.figshare.c.6795368,Aberrant activation of five embryonic stem cell-specific genes robustly predicts a high risk of relapse in breast cancers,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background In breast cancer, as in all cancers, genetic and epigenetic deregulations can result in out-of-context expressions of a set of normally silent tissue-specific genes. The activation of some of these genes in various cancers empowers tumours cells with new properties and drives enhanced proliferation and metastatic activity, leading to a poor survival prognosis. Results In this work, we undertook an unprecedented systematic and unbiased analysis of out-of-context activations of a specific set of tissue-specific genes from testis, placenta and embryonic stem cells, not expressed in normal breast tissue as a source of novel prognostic biomarkers. To this end, we combined a strict machine learning framework of transcriptomic data analysis, and successfully created a new robust tool, validated in several independent datasets, which is able to identify patients with a high risk of relapse. This unbiased approach allowed us to identify a panel of five biomarkers, DNMT3B, EXO1, MCM10, CENPF and CENPE, that are robustly and significantly associated with disease-free survival prognosis in breast cancer. Based on these findings, we created a new Gene Expression Classifier (GEC) that stratifies patients. Additionally, thanks to the identified GEC, we were able to paint the specific molecular portraits of the particularly aggressive tumours, which show characteristics of male germ cells, with a particular metabolic gene signature, associated with an enrichment in pro-metastatic and pro-proliferation gene expression. Conclusions The GEC classifier is able to reliably identify patients with a high risk of relapse at early stages of the disease. We especially recommend to use the GEC tool for patients with the luminal-A molecular subtype of breast cancer, generally considered of a favourable disease-free survival prognosis, to detect the fraction of patients undergoing a high risk of relapse.",mds,True,findable,0,0,0,0,0,2023-08-18T03:20:44.000Z,2023-08-18T03:20:45.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Genetics,FOS: Biological sciences,Molecular Biology,Biological Sciences not elsewhere classified,Information Systems not elsewhere classified,Mathematical Sciences not elsewhere classified,Developmental Biology,Cancer,Plant Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Biological Sciences not elsewhere classified'}, {'subject': 'Information Systems not elsewhere classified'}, {'subject': 'Mathematical Sciences not elsewhere classified'}, {'subject': 'Developmental Biology'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",,
+10.5281/zenodo.5063001,Live imaging and biophysical modeling support a button-based mechanism of somatic homolog pairing in Drosophila,Zenodo,2021,,Other,"Creative Commons Attribution 4.0 International,Open Access","3D eukaryotic genome organization provides the structural basis for gene regulation. In Drosophila melanogaster, genome folding is characterized by somatic homolog pairing, where homologous chromosomes are intimately paired from end to end; however, how homologs identify one another and pair has remained mysterious. Recently, this process has been proposed to be driven by specifically interacting 'buttons' encoded along chromosomes. Here, we turned this hypothesis into a quantitative biophysical model to demonstrate that a button-based mechanism can lead to chromosome-wide pairing. We tested our model using live-imaging measurements of chromosomal loci tagged with the MS2 and PP7 nascent RNA labeling systems. We show solid agreement between model predictions and experiments in the pairing dynamics of individual homologous loci. Our results strongly support a button-based mechanism of somatic homolog pairing in Drosophila and provide a theoretical framework for revealing the molecular identity and regulation of buttons.",mds,True,findable,0,0,0,2,0,2021-07-07T20:44:56.000Z,2021-07-07T20:44:57.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.c.6900580.v1,Bacterial survival in radiopharmaceutical solutions: a critical impact on current practices,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background The aim of this brief communication is to highlight the potential bacteriological risk linked to the processes control of radiopharmaceutical preparations made in a radiopharmacy laboratory. Survival rate of Pseudomonas aeruginosa (ATCC: 27853) or Staphylococcus aureus (ATCC: 25923) or Staphylococcus epidermidis (ATCC: 1228) in multidose technetium-99 m solution was studied. Results Depending on the nature and level of contamination by pathogenic bacteria, the lethal effect of radioactivity is not systematically observed. We found that P. aeruginosa was indeed affected by radioactivity. However, this was not the case for S. epidermidis, as the quantity of bacteria found in both solutions (radioactive and non-radioactive) was rapidly reduced, probably due to a lack of nutrients. Finally, the example of S. aureus is an intermediate case where we observed that high radioactivity affected the bacteria, as did the absence of nutrients in the reaction medium. The results were discussed in the light of current practices on the sterility test method, which recommends waiting for radioactivity to decay before carrying out the sterility test. Conclusion In terms of patient safety, the results run counter to current practice and the latest EANM recommendation of 2021 that radiopharmaceutical preparations should be decayed before sterility testing.",mds,True,findable,0,0,0,0,0,2023-10-27T03:41:27.000Z,2023-10-27T03:41:28.000Z,figshare.ars,otjm,"Biophysics,Microbiology,FOS: Biological sciences,Environmental Sciences not elsewhere classified,Science Policy,Infectious Diseases,FOS: Health sciences","[{'subject': 'Biophysics'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Environmental Sciences not elsewhere classified'}, {'subject': 'Science Policy'}, {'subject': 'Infectious Diseases'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5061/dryad.2fqz612m4,Sequencing data from: High levels of primary biogenic organic aerosols are driven by only a few plant-associated microbial taxa,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Primary biogenic organic aerosols (PBOA) represent a major fraction of coarse organic matter (OM) in air. Despite their implication in many atmospheric processes and human health problems, we surprisingly know little about PBOA characteristics (i.e., composition, dominant sources, and contribution to airborne-particles). In addition, specific primary sugar compounds (SCs) are generally used as markers of PBOA associated with bacteria and fungi but our knowledge of microbial communities associated with atmospheric particulate matter (PM) remains incomplete. This work aimed at providing a comprehensive understanding of the microbial fingerprints associated with SCs in PM10 (particles smaller than 10µm) and their main sources in the surrounding environment (soils and vegetation). An intensive study was conducted on PM10 collected at rural background site located in an agricultural area in France. We combined high-throughput sequencing of bacteria and fungi with detailed physicochemical characterization of PM10, soils and plant samples, and monitored meteorology and agricultural activities throughout the sampling period. Results shows that in summer SCs in PM10 are a major contributor of OM in air, representing 0.8 to 13.5% of OM mass. SCs concentrations are clearly determined by the abundance of only a few specific airborne fungi and bacteria taxa. The temporal fluctuations in the abundance of only 4 predominant fungal genera, namely Cladosporium, Alternaria, Sporobolomyces and Dioszegia reflect the temporal dynamics in SC concentrations. Among bacteria taxa, the abundance of only Massilia, Pseudomonas, Frigoribacterium and Sphingomonas are positively correlated with SC species. These microbial are significantly enhanced in leaf over soil samples. Interestingly, the overall community structure of bacteria and fungi are similar within PM10 and leaf samples and significantly distinct between PM10 and soil samples, indicating that surrounding vegetation are the major source of SC-associated microbial taxa in PM10 on rural area of France.",mds,True,findable,167,16,0,0,0,2020-04-22T17:41:32.000Z,2020-04-22T17:41:33.000Z,dryad.dryad,dryad,,,['328527 bytes'],
+10.5281/zenodo.5649819,"FIGS. 31–35 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIGS. 31–35—Protonemura spinulosa, male. 31, epiproct, lateral view; 32, epiproct, dorsal view; 33, terminalia, ventral view; 34, median lobe of paraproct, lateral view; 35, paraproct median lobe and outer lobe with trifurcated sclerite, lateral view (cercus removed); FIG. 36—Protonemura spinulosa, female, ventral view.",mds,True,findable,0,0,0,0,0,2021-11-05T21:11:47.000Z,2021-11-05T21:11:48.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.6084/m9.figshare.23575363.v1,Additional file 2 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 1,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:45.000Z,2023-06-25T03:11:46.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['157184 Bytes'],
+10.5281/zenodo.6803257,3-D displacement field produced by the 1959 Hebgen Lake earthquake,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The dataset contains EW, NS and vertical displacement component associated with the 1959 Hebgen Lake earthquake. The displacement maps were calculated from the aerial images collected in 1947 (pre-earthquake) and 1977 (post-earthquake).",mds,True,findable,0,0,0,0,0,2022-07-06T16:53:19.000Z,2022-07-06T16:53:20.000Z,cern.zenodo,cern,"3-D displacement, Hebgen Lake earthquake","[{'subject': '3-D displacement, Hebgen Lake earthquake'}]",,
+10.6084/m9.figshare.c.6842762,Non-ventilator-associated ICU-acquired pneumonia (NV-ICU-AP) in patients with acute exacerbation of COPD: From the French OUTCOMEREA cohort,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Non-ventilator-associated ICU-acquired pneumonia (NV-ICU-AP), a nosocomial pneumonia that is not related to invasive mechanical ventilation (IMV), has been less studied than ventilator-associated pneumonia, and never in the context of patients in an ICU for severe acute exacerbation of chronic obstructive pulmonary disease (AECOPD), a common cause of ICU admission. This study aimed to determine the factors associated with NV-ICU-AP occurrence and assess the association between NV-ICU-AP and the outcomes of these patients. Methods Data were extracted from the French ICU database, OutcomeReaâ„¢. Using survival analyses with competing risk management, we sought the factors associated with the occurrence of NV-ICU-AP. Then we assessed the association between NV-ICU-AP and mortality, intubation rates, and length of stay in the ICU. Results Of the 844 COPD exacerbations managed in ICUs without immediate IMV, NV-ICU-AP occurred in 42 patients (5%) with an incidence density of 10.8 per 1,000 patient-days. In multivariate analysis, prescription of antibiotics at ICU admission (sHR, 0.45 [0.23; 0.86], p = 0.02) and no decrease in consciousness (sHR, 0.35 [0.16; 0.76]; p < 0.01) were associated with a lower risk of NV-ICU-AP. After adjusting for confounders, NV-ICU-AP was associated with increased 28-day mortality (HR = 3.03 [1.36; 6.73]; p < 0.01), an increased risk of intubation (csHR, 5.00 [2.54; 9.85]; p < 0.01) and with a 10-day increase in ICU length of stay (p < 0.01). Conclusion We found that NV-ICU-AP incidence reached 10.8/1000 patient-days and was associated with increased risks of intubation, 28-day mortality, and longer stay for patients admitted with AECOPD.",mds,True,findable,0,0,0,0,0,2023-09-20T03:22:51.000Z,2023-09-20T03:22:51.000Z,figshare.ars,otjm,"Medicine,Microbiology,FOS: Biological sciences,Genetics,Molecular Biology,Neuroscience,Biotechnology,Evolutionary Biology,Immunology,FOS: Clinical medicine,Cancer,Science Policy,Virology","[{'subject': 'Medicine'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Genetics'}, {'subject': 'Molecular Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Evolutionary Biology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}, {'subject': 'Virology'}]",,
+10.57745/b6psx0,Speckle-correlation imaging through a kaleidoscopic multimode fiber (experimental data and Python scripts),Recherche Data Gouv,2023,,Dataset,,"Data set of the paper : ""Speckle-correlation imaging through a kaleidoscopic multimode fiber"". This includes the intensity correlation function of the excitation field for the 10.5 cm long fiber, and the measured signal autocorrelation functions for this fiber under dynamic perturbations.",mds,True,findable,112,21,0,0,0,2023-06-05T15:31:34.000Z,2023-06-15T14:51:30.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.7982036,"FIGURES A3–A5. Leuctra signifera sensu Mosely 1932 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,Open Access,"FIGURES A3–A5. Leuctra signifera sensu Mosely 1932; adult male, dorsal view (coll. Kempny, NHMUK, specimens NHMUK010010308, NHMUK010010310, NHMUK010010309). Original images are released under a creative commons license CC-BY-4.0 https://creativecommons.org/licenses/by/4.0/ © The Trustees of the Natural History Museum, London. A3, Leuctra signifera (NHMUK010010308); A4, Leuctra austriaca (NHMUK010010310); A5, Leuctra cf. austriaca (NHMUK010010309). These specimens were presumably preserved in 2% Formalin and subsequently mounted in Canada balsam by Mosely (1932: 3).",mds,True,findable,0,0,0,0,0,2023-05-29T13:43:17.000Z,2023-05-29T13:43:18.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.7762439,"FIGURE 2. Bulbophyllum anderosonii. A. Flattened flowering plant. B. Leaf apex. C in Bulbophyllum sondangii (Orchidaceae), a new species from Da Lat Plateau, southern Vietnam",Zenodo,2023,,Image,Open Access,"FIGURE 2. Bulbophyllum anderosonii. A. Flattened flowering plant. B. Leaf apex. C. Apical portion of inflorescence, view from above and from below. D. Floral bract, adaxial and abaxial side. E. Flower, view from above, from below, and side view. F. Median sepal, abaxial and adaxial side. G. Apex of median sepal. H. Lateral sepal, view from above and from below. I. Petal, abaxial and adaxial side. J. Petal margin. K. Lip, views from different sides. L. Pedicel, ovary and column, with petal and with petals removed, side view. M, N. Apex of column, side and frontal view. O. Anther cap, view from above and from below. P. Pollinia. All photos by Truong Ba Vuong, made from the specimens BV 1671, photo correction and design by L. Averyanov and T. Maisak.",mds,True,findable,0,0,0,3,0,2023-03-23T07:56:22.000Z,2023-03-23T07:56:23.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Bulbophyllum","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Bulbophyllum'}]",,
+10.5281/zenodo.5642126,"FIGURE 1 in Notes on the genus Chamaeanthus (Orchidaceae, Epidendroideae, Vandeae, Aeridinae) with a new species from Vietnam",Zenodo,2021,,Image,Open Access,"FIGURE 1. Chamaeanthus averyanovii Vuong, Kumar, V.H. Bui, V.S.Dang: A & B. Plant habit; C. Leaf apex; D. Leaf sheath; E. Inflorescence; F. Flower; G. Floral bract; H. Dorsal sepal; I. Lateral sepals; J. Petals; K. Lip; L. Column and column foot; M. Stigma; N. Anher cap; O. Pollinia. All photo by Truong Ba Vuong from specimen BV 1194.",mds,True,findable,0,0,0,0,0,2021-11-03T06:44:17.000Z,2021-11-03T06:44:18.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Chamaeanthus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Chamaeanthus'}]",,
+10.5061/dryad.rjdfn2z7p,Data from: Landscape does matter: disentangling founder effects from natural and human-aided post-introduction dispersal during an ongoing biological invasion,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Environmental features impacting the spread of invasive species after introduction can be assessed using population genetic structure as a quantitative estimation of effective dispersal at the landscape scale. However, in the case of an ongoing biological invasion, deciphering whether genetic structure represents landscape connectivity or founder effects is particularly challenging. We examined the modes of dispersal (natural and human-aided) and the factors (landscape or founders history) shaping genetic structure in range edge invasive populations of the Asian tiger mosquito, Aedes albopictus, in the region of Grenoble (Southeast France). Based on detailed occupancy-detection data and environmental variables (climatic, topographic, land-cover), we modelled A. albopictus potential suitable area and its expansion history since first introduction. The relative role of dispersal modes was estimated using biological dispersal capabilities and landscape genetics approaches using genome-wide SNP dataset. We demonstrate that both natural and human-aided dispersal have promoted the expansion of populations. Populations in diffuse urban areas, representing highly suitable habitat for A. albopictus, tend to disperse less, while roads facilitate long-distance dispersal. Yet demographic bottlenecks during introduction played a major role in shaping the genetic variability of these range edge populations. The present study is one of the few investigating the role of founder effects and ongoing expansion processes in shaping spatial patterns of genetic variation in an invasive species at the landscape scale. The combination of several dispersal modes and large proportions of continuous suitable habitats for A. albopictus promoted range filling of almost its entire potential distribution in the region of Grenoble only few years after introduction.",mds,True,findable,127,5,0,0,0,2020-07-06T23:26:39.000Z,2020-07-06T23:26:41.000Z,dryad.dryad,dryad,,,['4074602 bytes'],
+10.15454/l7qn45,Soil Microbial Metagenomics Facility,INRAE,2018,,Service,,,fabricaForm,True,findable,43,0,0,0,0,2018-10-03T11:07:03.000Z,2018-10-03T11:07:03.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.7113144,Geothermal and structural features of La Palma island (Canary Islands) imaged by ambient noise tomography,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",These folders contain all the results obtained in the ambient noise tomography of La Palma for geothermal exploration.,mds,True,findable,0,0,0,0,0,2022-09-26T11:44:00.000Z,2022-09-26T11:44:01.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.g72v731,Data from: Plant DNA metabarcoding of lake sediments: how does it represent the contemporary vegetation,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"Metabarcoding of lake sediments have been shown to reveal current and past biodiversity, but little is known about the degree to which taxa growing in the vegetation are represented in environmental DNA (eDNA) records. We analysed composition of lake and catchment vegetation and vascular plant eDNA at 11 lakes in northern Norway. Out of 489 records of taxa growing within 2 m from the lake shore, 17-49% (mean 31%) of the identifiable taxa recorded were detected with eDNA. Of the 217 eDNA records of 47 plant taxa in the 11 lakes, 73% and 12% matched taxa recorded in vegetation surveys within 2 m and up to about 50 m away from the lakeshore, respectively, whereas 16% were not recorded in the vegetation surveys of the same lake. The latter include taxa likely overlooked in the vegetation surveys or growing outside the survey area. The percentages detected were 61, 47, 25, and 15 for dominant, common, scattered, and rare taxa, respectively. Similar numbers for aquatic plants were 88, 88, 33 and 62%, respectively. Detection rate and taxonomic resolution varied among plant families and functional groups with good detection of e.g. Ericaceae, Roseaceae, deciduous trees, ferns, club mosses and aquatics. The representation of terrestrial taxa in eDNA depends on both their distance from the sampling site and their abundance and is sufficient for recording vegetation types. For aquatic vegetation, eDNA may be comparable with, or even superior to, in-lake vegetation surveys and may therefore be used as an tool for biomonitoring. For reconstruction of terrestrial vegetation, technical improvements and more intensive sampling is needed to detect a higher proportion of rare taxa although DNA of some taxa may never reach the lake sediments due to taphonomical constrains. Nevertheless, eDNA performs similar to conventional methods of pollen and macrofossil analyses and may therefore be an important tool for reconstruction of past vegetation.",mds,True,findable,382,54,1,1,0,2018-03-23T21:54:37.000Z,2018-03-23T21:54:38.000Z,dryad.dryad,dryad,"biomonitoring,palaeobotany,Holocene","[{'subject': 'biomonitoring'}, {'subject': 'palaeobotany'}, {'subject': 'Holocene'}]",['3664863480 bytes'],
+10.5281/zenodo.10207869,"Link to data for the paper ""Diode effect in Josephson junctions with a single magnetic atom""",Zenodo,2023,,Other,Creative Commons Attribution 4.0 International,"The refubium repository contains the experimental data and the code used in the paper ""Diode effect in Josephson junctions with a single magnetic atom"" published in Nature 618, 625 (2023).",api,True,findable,0,0,0,0,0,2023-11-26T19:52:29.000Z,2023-11-26T19:52:29.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3606387,Poleless Exploration with Melomaniac Myopic Chameleon Robots: The Animations,Zenodo,2020,,Software,"Creative Commons Attribution 4.0 International,Open Access",Animations of two infinite grid exploration algorithms by robots without chirality. The published HTML pages allow the viewer to see the first 100 rounds of each algorithm.,mds,True,findable,0,0,0,0,0,2020-01-13T13:44:01.000Z,2020-01-13T13:44:01.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.2485983,Phenomenological study of BSM Φ→tt process,Zenodo,2018,,Software,Open Access,Supporting material for a phenomenological study of the production of a heavy Higgs boson decaying into a pair of top quarks. The code used to perform the scans over parameters of various signal models is included here.,mds,True,findable,0,0,1,0,0,2018-12-21T23:23:09.000Z,2018-12-21T23:23:10.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8421859,"Codes of the article ""evolutionary dynamics of plasting foraging and its ecological consequences: a resource-consumer model""",Zenodo,2023,,Software,Open Access,"The ""Codes"" folder contains the MATLAB codes used for all the simulations. In order to run some of these codes, you will need to download the simulation output (.mat format) from the ""Data"" folder and from the link in the README for this folder. The ""Figures"" folder contains all the figures in the paper and appendices. Finally, the appendices to the paper are in the Appendix.pdf file.",mds,True,findable,0,0,0,0,0,2023-10-09T13:51:19.000Z,2023-10-09T13:51:20.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6786833,Sensitivity of glaciers in the European Alps to anthropogenic atmospheric forcings: case study of the Argentière glacier,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This Zenodo repository contains all datasets (IPSL CMIP6 data, glaciological data, SAFRAN data), ElmerIce codes and Python Jupyter Notebook used in the study reported in the article <strong><em>""Sensitivity of glaciers in the European Alps to anthropogenic atmospheric forcings: case study of the Argentière glacier""</em></strong>",mds,True,findable,0,0,0,0,0,2023-02-17T14:34:31.000Z,2023-02-17T14:34:31.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8247362,Solar-powered Shape-changing Origami Microfliers,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Datasets used in the paper: ""Solar-powered Shape-changing Origami Microfliers"". This deposit contains the <strong>entirety</strong> of the raw datasets collected from real world experiments used to generate all of the figures and supplementary materials in the aforementioned paper. These also include the MCU's source code and PCB design files used to create the leaf-out origami robot prototypes. Please see the Readme for more information.",mds,True,findable,0,0,0,0,0,2023-09-13T18:09:22.000Z,2023-09-13T18:09:22.000Z,cern.zenodo,cern,"Origami Microfliers,Battery-Free Robotics,Wireless Sensor Networks","[{'subject': 'Origami Microfliers'}, {'subject': 'Battery-Free Robotics'}, {'subject': 'Wireless Sensor Networks'}]",,
+10.57726/grx4-f695,"Say It Again, Please",Presses Universitaires Savoie Mont Blanc,2015,en,Book,,,fabricaForm,True,findable,0,0,0,0,0,2022-03-14T14:54:06.000Z,2022-03-14T14:54:06.000Z,pusmb.prod,pusmb,FOS: Humanities,"[{'subject': 'FOS: Humanities', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['149 pages'],
+10.5281/zenodo.4964225,"FIGURE 40 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,FIGURE 40. Biotope of Protonemura bispina sp. n. (Sella Ciampigotto Sella di Razzo),mds,True,findable,0,0,3,0,0,2021-06-16T08:25:50.000Z,2021-06-16T08:25:51.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5285/3ea504d8-41c2-40dc-86dc-284c341badaa,"Ice radar data from Little Dome C, Antarctica, 2016-2018",NERC EDS UK Polar Data Centre,2022,en,Dataset,Open Government Licence V3.0,"The dataset consists of 14 selected lines of radar data, collected from the Little Dome C region close to Concordia Station in East Antarctica. The data were collected in austral field seasons 2016-17, and 2017-18, from within the search region for the planned European project Beyond EPICA - Oldest Ice, an EU-funded 10-nation consortium project to drill an ice core that spans up to 1.5 million years of climate and atmospheric history. Radar lines were recorded using the BAS DELORES sledge-borne, over-snow, ice radar system and geolocated with a precise GPS system. This data was generated within the project Beyond EPICA - Oldest Ice (BE-OI). The project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 730258 (BE-OI CSA). It has received funding from the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 16.0144. It is further supported by national partners and funding agencies in Belgium, Denmark, France, Germany, Italy, Norway, Sweden, Switzerland, the Netherlands and the UK. Logistic support is mainly provided by AWI, BAS, ENEA and IPEV. Collection of this data also benefited from support by the joint French-Italian Concordia Programme, which established and runs the permanent station Concordia at Dome C. We particularly acknowledge those who collected the data in the field, and assisted with the processing: Robert Mulvaney, Massimo Frezzotti, Marie Cavitte, Ed King, Carlos Martin, Catherine Ritz, Julius Rix.",mds,True,findable,0,0,0,0,0,2022-03-04T09:26:18.000Z,2022-03-04T09:29:51.000Z,bl.nerc,rckq,"""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS"",""GLACIER THICKNESS/ICE SHEET THICKNESS"",""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS"",""GLACIER TOPOGRAPHY/ICE SHEET TOPOGRAPHY"",""EARTH SCIENCE"",""CRYOSPHERE"",""SNOW/ICE"",""SNOW STRATIGRAPHY"",""EARTH SCIENCE"",""SPECTRAL/ENGINEERING"",""RADAR"",""RADAR REFLECTIVITY"",""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS"",""EARTH SCIENCE"",""SPECTRAL/ENGINEERING"",""RADAR"",DELORES,EPICA,Little Dome C,oldest ice,radar","[{'subject': '""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS"",""GLACIER THICKNESS/ICE SHEET THICKNESS""', 'schemeUri': 'http://gcmdservices.gsfc.nasa.gov/kms/concepts/concept_scheme/sciencekeywords/?format=xml', 'subjectScheme': 'GCMD'}, {'subject': '""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS"",""GLACIER TOPOGRAPHY/ICE SHEET TOPOGRAPHY""', 'schemeUri': 'http://gcmdservices.gsfc.nasa.gov/kms/concepts/concept_scheme/sciencekeywords/?format=xml', 'subjectScheme': 'GCMD'}, {'subject': '""EARTH SCIENCE"",""CRYOSPHERE"",""SNOW/ICE"",""SNOW STRATIGRAPHY""', 'schemeUri': 'http://gcmdservices.gsfc.nasa.gov/kms/concepts/concept_scheme/sciencekeywords/?format=xml', 'subjectScheme': 'GCMD'}, {'subject': '""EARTH SCIENCE"",""SPECTRAL/ENGINEERING"",""RADAR"",""RADAR REFLECTIVITY""', 'schemeUri': 'http://gcmdservices.gsfc.nasa.gov/kms/concepts/concept_scheme/sciencekeywords/?format=xml', 'subjectScheme': 'GCMD'}, {'subject': '""EARTH SCIENCE"",""CRYOSPHERE"",""GLACIERS/ICE SHEETS""', 'schemeUri': 'http://gcmdservices.gsfc.nasa.gov/kms/concepts/concept_scheme/sciencekeywords/?format=xml', 'subjectScheme': 'GCMD'}, {'subject': '""EARTH SCIENCE"",""SPECTRAL/ENGINEERING"",""RADAR""', 'schemeUri': 'http://gcmdservices.gsfc.nasa.gov/kms/concepts/concept_scheme/sciencekeywords/?format=xml', 'subjectScheme': 'GCMD'}, {'subject': 'DELORES'}, {'subject': 'EPICA'}, {'subject': 'Little Dome C'}, {'subject': 'oldest ice'}, {'subject': 'radar'}]","['16 files', '300.2 MB']","['text/x-fortranapplication/octet-stream', 'image/png', 'text/plain', 'text/csv', 'SEG-Y']"
+10.5281/zenodo.6035534,"Consilience across multiple, independent genomic data sets reveals species in a complex with limited phenotypic variation",Zenodo,2023,,Software,"MIT License,Open Access","Species delimitation in the genomic era has focused predominantly on the application of multiple analytical methodologies to a single massive parallel sequencing (MPS) data set, rather than leveraging the unique but complementary insights provided by different classes of MPS data. In this study we demonstrate how the use of two independent MPS data sets, a sequence capture data set and a single nucleotide polymorphism (SNP) data set generated via genotyping-by-sequencing, enables the resolution of species in three complexes belonging to the grass genus <em>Ehrharta, </em>whose strong population structure and subtle morphological variation limit the effectiveness of traditional species delimitation approaches. Sequence capture data are used to construct a comprehensive phylogenetic tree of <em>Ehrharta </em>and to resolve population relationships within the focal clades, while SNP data are used to detect patterns of gene pool sharing across populations, using a novel approach that visualises multiple values of K. Given that the two genomic data sets are fully independent, the strong congruence in the clusters they resolve provides powerful ratification of species boundaries in all three complexes studied. Our approach is also able to resolve a number of single-population species and a probable hybrid species, both which would be difficult to detect and characterize using a single MPS data set. Overall, the data reveal the existence of 11 and five species in the <em>E. setacea</em> and <em>E. rehmannii </em>complexes, with the <em>E. ramosa</em> complex requiring further sampling before species limits are finalized. Despite phenotypic differentiation being generally subtle, true crypsis is limited to just a few species pairs and triplets. We conclude that, in the absence of strong morphological differentiation, the use of multiple, independent genomic data sets is necessary in order to provide the cross-data set corroboration that is foundational to an integrative taxonomic approach.",mds,True,findable,0,0,0,0,0,2023-02-14T19:26:17.000Z,2023-02-14T19:26:17.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7043353,Replication Package for the paper: Compositional Verification of Stigmergic Collective Systems,Zenodo,2022,,Software,Open Access,"This package allows to replicate the experiments described in the paper “Compositional Verification of Collective Adaptive Systemsâ€. <strong>## Package contents</strong> `LICENSE`: licensing information `logs-baseline/published`, `logs-compositional/published`: log files used to compile figures and tables within the paper `ZENODO.md`: this document `replication.sh`: script to replicate the experiments `specifications`: LAbS source files The other files and directories are a slightly customized release of the SLiVER tool, available at https://github.com/labs-lang/sliver/. <strong>## Requirements</strong> This package has been tested under Debian and Ubuntu, but should run on most x86_64 Linux distributions. Python 3..8 or higher (experiments were performed using Python 3.10.4) A recent version of CADP (https://cadp.inria.fr). The experiments were performed using version 2022-f ""Kista"". If a newer version is used, please check the change list page (https://cadp.inria.fr/changes.html) and note that any breaking changes introduced since version 2022-f may affect the experiments. <strong>## Instructions</strong> Unpack the archive, give execute permissions to `replication.sh`, and execute it. Logs will be stored in `logs-baseline/YYY-MM-DD` and `logs-compositional/YYYY-MM-DD` where `YYYY-MM-DD is the current date. <strong>## Changelog</strong> <strong>### Changes between v1.1 and 1.0</strong> Starting from CADP 2022-g, the keyword for divergence-preserving sharp bisimulation changed from `sharp` to `divsharp`.<br> Version 1.0 of this package used the `sharp` keyword, and thus it may fail to replicate the experiments when used with newer versions of CADP.<br> Version 1.1 addresses this by using `divsharp`.<br> We also updated the published log files with those obtained by running our experiments with CADP 2022-h.<br> The present document (`ZENODO.md`) has similarly been updated to document these changes. <strong>## Disclaimer</strong> The authors of this repository do not endorse using its contents for ANY purpose besides replication of experiments presented in the paper “Compositional Verification of Stigmergic Collective Systemsâ€. Please enquire with the paper’s corresponding author (Luca Di Stefano) about software packages intended for generic usage.",mds,True,findable,0,0,0,0,0,2022-09-02T11:29:38.000Z,2022-09-02T11:29:38.000Z,cern.zenodo,cern,"formal verification,model checking,collective adaptive systems,cadp,labs,stigmergy","[{'subject': 'formal verification'}, {'subject': 'model checking'}, {'subject': 'collective adaptive systems'}, {'subject': 'cadp'}, {'subject': 'labs'}, {'subject': 'stigmergy'}]",,
+10.5281/zenodo.6532308,Micromagnetics of magnetic chemical modulations in soft-magnetic cylindrical nanowires,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Abstract: We analyze the micromagnetics of short longitudinal modulations of a high magnetization material in cylindrical nanowires made of a soft-magnetic material of lower magnetization such as Permalloy, combining magnetic microscopy, analytical modeling and micromagnetic simulations. The mismatch of magnetization induces curling of magnetization around the axis in the modulations, in an attempt to screen the interfacial magnetic charges. The curling angle increases with modulation length, until a plateau is reached with nearly full charge screening for a specific length scale, larger than the dipolar exchange length of any of the two materials. The curling circulation can be switched by the Å’rsted field arising from a charge current with typical magnitude 10<sup>12</sup>A/m<sup>2</sup>.",mds,True,findable,0,0,0,0,0,2022-05-09T13:36:09.000Z,2022-05-09T13:36:11.000Z,cern.zenodo,cern,"nanomagnetism, nanowire, micromagnetics, magnetization dynamics, magnetic microscopy","[{'subject': 'nanomagnetism, nanowire, micromagnetics, magnetization dynamics, magnetic microscopy'}]",,
+10.5281/zenodo.4090905,"Source Data of ""Coherent control of individual electron spins in a 2D quantum dot array""",Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Coherent manipulation of individual quantum objects organized in arrays is a prerequisite to any scalable quantum information platform.<br> The cumulated efforts to control electron spins in quantum dot arrays have permitted the recent realization of quantum simulators and multi-electron spin coherent manipulations.<br> While being a natural path to resolve complex quantum matter problems and to process quantum information, the two-dimensional (2D) scaling with high connectivity of such implementations remains undemonstrated.<br> Here, we demonstrate the 2D coherent control of individual electron spins in a 3x3 array of tunnel coupled quantum dots.<br> We focus on several key quantum functionalities: charge deterministic loading and displacement, local spin readout, and local coherent exchange manipulation between two electron spins trapped in adjacent dots.<br> This work lays some of the foundations for exploiting a 2D array of electron spins for quantum simulation and information processing.",mds,True,findable,0,0,0,0,0,2020-10-15T12:08:03.000Z,2020-10-15T12:08:04.000Z,cern.zenodo,cern,,,,
+10.7280/d1z69g,"Data for: Seasonal acceleration of Petermann Glacier, Greenland, from changes in subglacial hydrology",Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Petermann Glacier, a major outlet glacier of Northern Greenland, drains a marine-based basin vulnerable to destabilization. Using satellite radar interferometry data from the Sentinel-1a/b missions, we observe a seasonal glacier acceleration of 15% in the summer, from 1,250 m/yr to 1,500 m/yr near the grounding line, but the physical drivers of this seasonality have not been elucidated. Here, we use a subglacial hydrology model coupled one-way to an ice sheet model to evaluate the role of subglacial hydrology as a physical mechanism explaining the seasonality in speed. We model the basal effective pressure using the Glacier Drainage System model which then forces the Ice-sheet and Sea-level System Model. We find an excellent agreement between the observed and modeled velocity in terms of magnitude and timing, and conclude that seasonal changes in subglacial hydrology are sufficient to explain the observed seasonal speed up of Petermann Glacier. This data publication provides all of the scripts and data necessary to initialize and run the subglacial hydrology model and ice sheet model used in this work (Manuscript number 2022GL098009). We also provide the model output and the scripts used to create the figures in the manuscript and the animations in the supplemental document. Several data sets are also made available here, including integrated melt water runoff derived from the regional climate model, MAR (Modèle Atmosphérique Régional), which is used to force the hydrology model, and daily average effective pressure derived from the hydrology model output, which is used to force the ice sheet model. These files combined are sufficient to reproduce all results and figures presented in this work.",mds,True,findable,134,15,0,0,0,2022-12-21T07:21:16.000Z,2022-12-21T07:21:17.000Z,dryad.dryad,dryad,"FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences","[{'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['4043367766 bytes'],
+10.5281/zenodo.6818751,Dataset: Stochastic data-driven parameterization of unresolved eddy effects in a baroclinic quasi-geostrophic model,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset is used to reproduce the figures in the manuscript ""Stochastic data-driven parameterization of unresolved eddy effects in a baroclinic quasi-geostrophic model"" The figures can be created with the following Python scripts: .",mds,True,findable,0,0,0,1,0,2022-07-11T22:47:12.000Z,2022-07-11T22:47:13.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3549806,French Word Sense Disambiguation with Princeton WordNet Identifiers,Zenodo,2019,fr,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is a dataset for the Word Sense Disambiguation of French using Princeton WordNet identifiers. It contains two training corpora : the SemCor and the WordNet Gloss Corpus, both automatically translated from their original English version, and with sense tags automatically aligned. It contains also a test corpus : the task 12 of SemEval 2013, originally sense annotated with BabelNet identifiers, converted into Princeton WordNet 3.0.",mds,True,findable,19,0,0,0,0,2019-11-21T15:12:53.000Z,2019-11-21T15:12:54.000Z,cern.zenodo,cern,"French,Word Sense Disambiguation,WordNet","[{'subject': 'French'}, {'subject': 'Word Sense Disambiguation'}, {'subject': 'WordNet'}]",,
+10.5281/zenodo.3552787,fNIRS-DOT videos from David Orive-Miguel PhD thesis,Zenodo,2019,,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access",fNIRS Diffuse Optical Tomography videos. The experimental measurements were obtained during my secondment at Politecnico di Milano.,mds,True,findable,0,0,0,0,0,2019-11-25T16:55:12.000Z,2019-11-25T16:55:13.000Z,cern.zenodo,cern,fnirs;dot,[{'subject': 'fnirs;dot'}],,
+10.2312/yes19.15,What Peer-review Experiences Can Offer To Early Career Scientists And To The Scientific Community,"German YES Chapter, GFZ German Research Centre for Geosciences ",2021,en,Text,Creative Commons Attribution 4.0 International,,fabricaForm,True,findable,0,0,0,0,0,2020-12-11T07:53:58.000Z,2020-12-13T16:02:22.000Z,tib.gfzbib,gfz,"APECS,Peer-review,FOS: Educational sciences,IPCC,Early career scientist","[{'subject': 'APECS'}, {'subject': 'Peer-review'}, {'subject': 'FOS: Educational sciences', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'IPCC'}, {'subject': 'Early career scientist'}]",['pp 144-148 '],['pdf']
+10.5281/zenodo.8014905,Experimental investigation of the effects of particle shape and friction on the mechanics of granular media,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"This dataset corresponds to the raw data and experimental measurements of the PhD thesis ""Experimental investigation of the effects of particle shape and friction on the mechanics of granular media"" of Gustavo Pinzón (2023, Université Grenoble Alpes), available at: https://hal.science/tel-04202827v1.Â
+The experiments correspond to a drained triaxial compression test of cylindrical granular specimens, a common testing procedure used in soil mechanics to characterise the mechanical response of a specimen under deviatoric loading. Each specimen is 140mm in height and 70mm in diameter, and is composed of more than 20000 ellipsoidal particles of a given aspect ratio and interparticle friction. The dataset comprises the test of six specimens, as a result of the combination of 3 particles shapes (Flat, Medium, and Rounded) and 2 values of interparticle friction (Rough and Smooth). A naming system for the specimens is adopted to reflect the morphology of the composing particles (e.g., the test EFR correspond to the specimen with Flat and Rough particles). Further details on the experimental methods are found in Ch. 2 of the thesis.
+ The compression tests are performed inside the x-ray scanner of Laboratoire 3SR in Grenoble (France), where the specimens are scanned each 0.5% of axial shortening, at an isotropic voxel size of 100 micrometer per pixel. The obtained radiographies are reconstructed using a Filtered Back Projection algorithm, using the software given by the x-ray cabin manufacturer (RX Solutions, France). The series of obtained 16-bit greyscale 3D images are processed with the open source software spam, version 0.6.2. The coordinate system of all the images is ZYX, where Z corresponds to compression direction. Further details on the image analysis techniques are found in Ch. 3 of the thesis.
+Additional greyscale images, raw projections, and x-ray tomography files are available upon request. For visualisation purposes, the 3D images in .tif format can be opened using Fiji. ",mds,True,findable,0,0,0,0,0,2023-06-08T12:30:27.000Z,2023-06-08T12:30:28.000Z,cern.zenodo,cern,"Anisometric particles,Fabric anisotropy,X-ray tomography,Image analysis","[{'subject': 'Anisometric particles'}, {'subject': 'Fabric anisotropy'}, {'subject': 'X-ray tomography'}, {'subject': 'Image analysis'}]",,
+10.5281/zenodo.8408864,MARv312-albCor105-spinup6_daily,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"Modèle Atmosphérique Régional (MAR) version 3.12 simulations for Antarctic domain, 35 x 35 km spatial resolution, daily temporal resolution, for the 1979-2020 period, nudged with ERA5. The code for the regional atmospheric climate model MAR (Modèle Atmosphérique Régional) is available upon registration at https://gitlab.com/Mar-Group/MARv3
+This data is analyzed in a manuscript accepted for The Cryosphere:Â doi.org/10.5194/egusphere-2023-1903
+The link will be updated when the final version is online.",mds,True,findable,0,0,0,0,0,2023-10-05T02:04:34.000Z,2023-10-05T02:04:35.000Z,cern.zenodo,cern,"Antarctica,Snowfall,Temperature","[{'subject': 'Antarctica'}, {'subject': 'Snowfall'}, {'subject': 'Temperature'}]",,
+10.57745/grhrzj,Dry powders reflectance model based on enhanced backscattering: case of hematite α - Fe_2 O_3,Recherche Data Gouv,2023,,Dataset,,"Data associated to the paper entitled: Morgane Gerardin, Pauline Martinetto, and Nicolas Holzschuch, ""Dry powders reflectance model based on enhanced backscattering: case of hematiteα–Fe2O3,"" J. Opt. Soc. Am. A 40, 1817-1830 (2023) The appearance of materials is described by a function known as the Bidirectionnal Reflectance Distribution Function (BRDF). This function can be acquired through gonio-spectrophotometry, by measuring the scattering of light by a sample of study for multiple illumination directions and multiple observation directions. When it comes to the scattering of light in the back scattering direction (illumination and observation directions are coincident), a specific instrument allowing such configuration to be measured is required. This dataset provides complete BRDF measurements data acquired on numerous dry hematite powders, with different color and different grain morphology. The main part of the BSDF is measured using the Gonio-spectrophotometer SHADOWS (IPAG), and the back scattering is measured using an instrument designed at Institut Néel. These data were collected in the context of the Cross Disciplinary Program Patrimalp, supported by the French National Research Agency in the framework of the Investissements d’Avenir program (ANR-15-IDEX-02). See README file for a complete description of the available data.",mds,True,findable,34,0,0,0,0,2023-08-24T12:59:36.000Z,2023-10-17T11:38:57.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.10142460,Climate warming drives rockfall from an increasingly unstable mountain slope,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"This readme file provides all data and R codes used to perform the analyses presented in Figs. 2-4 of the main text and Supplementary Information Figures S1-S2-S3.
+
+
+
+FIGURE 2
+-Â Seasonally_dated_GDs.txt: Contains information on the timing (Season) of rockfall (GD) in a given tree (Id) and a given year (yr) over the past 100 years. Inv refers to the operators which analyzed growth disturbances in the tree-ring series. Lat / Long refers to the position of the tree in CH1903/ Swiss Grid projection. Intensity (1-4) refers to (1), intermediate (2)Â and strong (3) GD. Intensity 4 was attributed to injuries (I). Only the 408 GD rated 3 (strong TRD) and 4 (injuries) were used in Fig. 2. Acronyms used for Response_type read as follows: TRD: Tangential rows of traumatic resin ducts; I: Injuries. Acronyms used for Season refer to Dormancy (1_D), early (2_EE), middle (3_ME) and late (4_LE) earlywood, whereas a GD found in the latewood was attributed to either the early (5_EL) or late (6_LL) latewood.
+
+
+- Trends_in_seasonality_R1.R: The data contained in ""Seasonally_dated_GDs"" were processed with the R script ""Trends_in_Seasonality.R"". This seasonal trend analysis code is inspired by work published by Schlögl et al. (2021; https://doi.org/10.1016/j.crm.2021.100294) and Heiser et al. (2022; https://doi.org/10.1029/2011JF002262).
+
+
+
+FIGURE 3-4-S1
+- Tasch_GD.txt: Contains the raw data on rockfall impacts (GD) in a given year (yr) as found in all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year.
+- Rockfall_frequency_climate.R: The data contained in ""Tasch_GD.txt"" were processed with the R script ""Rockfall_frequency_climate.R"". Â
+- The temperature (Imfeld23_tmp.txt) and precipitation (Imfeld23_prc.txt) data used in Fig. 3 are from the Imfeld et al. 2023 (10.5194/cp-19-703-2023) gridded dataset (1x1 km lat/long) and were extracted at the grid point centered on the Täschgufer site.
+- The script set with temperature series enables to compute Fig. 4 (l.149:216) and Fig. 3 (l. 216:330); the script set with precipitation series enables to compute Fig. S1
+
+
+
+FIGURE S2
+- Tasch_GD.txt: Contains the raw data on rockfall impacts (GD) at the Täschgufer site in a given year (yr) as found in all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year.
+- Rockfall_frequency_borehole.R: is adapted from ""Rockfall_frequency_climate.R"" to work with the borehole dates. Â
+- Corvatsch0_6R1: Contains the Corvatsch borehole temperature series (2000-2020, 0.6m depth) (Hoelzle, M. et al. https://doi.org/10.5194/essd-14-1531-2022, 2022).
+
+
+
+FIGURE S3
+- Plattje_GD.txt: Contains the raw data on rockfall impacts (GD) at the Plattje site in a given year (yr) as found all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year.
+- - Rockfall_frequency_climate_Plattje.R: The data contained in ""Plattje_GD.txt"" were processed with the R script ""Rockfall_frequency_climate_Plattje.R"". Â
+- The temperature (Imfeld23_tmp_Plattje.txt) and precipitation (Imfeld23_prc_Plattje.txt) data used in Fig. 3 are from Imfeld et al. 2023 (10.5194/cp-19-703-2023) gridded dataset (1x1 km lat/long) and were extracted at the grid point centered on the Plattje site.
+
+
+Â ",api,True,findable,0,0,0,0,0,2023-11-16T11:01:26.000Z,2023-11-16T11:01:26.000Z,cern.zenodo,cern,"rockfall,dendrogeomorphology,cryosphere,climate change,reconstruction","[{'subject': 'rockfall'}, {'subject': 'dendrogeomorphology'}, {'subject': 'cryosphere'}, {'subject': 'climate change'}, {'subject': 'reconstruction'}]",,
+10.5281/zenodo.5993279,"Ressources comptables en Dauphiné, Provence, Savoie et Venaissin (XIIIe - XVe siècle)",Zenodo,2022,la,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Ce corpus, né d’un programme financé par l’Agence nationale de la Recherche, intitulé «Genèse médiévale d’une méthode administrative» (GEMMA), est le résultat d’une grande enquête sur l’évolution des techniques comptables dans les principautés du Sud Est de la France actuelle, Dauphiné, Provence, Savoie et Venaissin, entre le XIIIe et le début du XVIe siècle. Il tire avantage de l’expérience acquise par les équipes qui depuis plusieurs années travaillent à Chambéry et à Lyon sur les comptes des châtellenies de Savoie. Un grand nombre de médiévistes des universités d’Aix, Avignon, Chambéry, Grenoble 2, Lyon 2 et 3, Nice, Turin, Moncton et Montréal, mais aussi du CNRS et de l’EHESS y participent. Il consiste en quatre ans : à mener à bien une entreprise de numérisation en vue d’une publication sur le net des principaux éléments des séries comptables actuellement conservées pour ces principautés (les registres centraux en intégralité, ainsi qu’un échantillon représentatif des comptes des châtelains et clavaires) ; à multiplier par des voies différentes les transcriptions de ces sources pour les publier sur ce même site ; à développer d’un point de vue technique les modes d’accès et d’interrogation sur les corpus ainsi constitués ; à étendre enfin nos connaissances sur des pratiques en pleine évolution durant cette période, en les comparant entre elles et avec celles utilisées dans les espaces limitrophes (Empire, Italie, royaumes de France et d’Aragon), au travers de journées d’étude, de tables-rondes et de colloques organisés par chacun des partenaires. Format de fichier: XML Standards, conventions des données utilisées: XML TEI P5",mds,True,findable,0,0,0,0,0,2022-02-07T18:54:23.000Z,2022-02-07T18:54:24.000Z,cern.zenodo,cern,"histoire médiévale,comptabilité médiévale,comptes des châtelains","[{'subject': 'histoire médiévale'}, {'subject': 'comptabilité médiévale'}, {'subject': 'comptes des châtelains'}]",,
+10.5281/zenodo.6546795,breichl/oceanmixedlayers: v1.0.0,Zenodo,2022,,Software,Open Access,"This version of the software is used to generate all data in the description paper of the PE based MLD method: A potential energy analysis of ocean surface mixed layers by Brandon G. Reichl, Alistair Adcroft, Stephen M. Griffies, and Robert Hallberg in Journal of Geophysical Research: Oceans.",mds,True,findable,0,0,0,0,0,2022-05-13T14:56:05.000Z,2022-05-13T14:56:06.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4757642,Fig. 16 in Morphology And Systematic Position Of Two Leuctra Species (Plecoptera: Leuctridae) Believed To Have No Specilla,Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access",Fig. 16. Geographical distribution of Leuctra bidula and L. ketamensis.,mds,True,findable,0,0,4,0,0,2021-05-13T16:07:10.000Z,2021-05-13T16:07:10.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.7982040,"FIGURES B1–B6 in Notes on Leuctra signifera Kempny, 1899 and Leuctra austriaca Aubert, 1954 (Plecoptera: Leuctridae), with the description of a new species",Zenodo,2023,,Image,Open Access,"FIGURES B1–B6. Leuctra austriaca, adult male (Austria, Gutenstein Alps, Urgersbachtal). B1, dorsal view; B2, lateral view; B3, stylus and specillum, lateral view; B4, ¾ dorsal view; B5, dorsal view, indicating relative width of posteromedial process; B6, ventral view with vesicle.",mds,True,findable,0,0,0,0,0,2023-05-29T13:43:34.000Z,2023-05-29T13:43:34.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.7115984,"Supporting Information for ""Where does the energy go during the interstellar NH3 formation on water ice? A computational study""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Supplementary Material consisting of: The energetics of the gas-phase reactions for both the H-additions and H-abstractions, The evolution with time of the total, potential and kinetic energies of the studied processes Results of the NVE AIMD simulations for the NH<sub>3</sub> formation from Pos2",mds,True,findable,0,0,0,0,0,2022-11-22T14:13:21.000Z,2022-11-22T14:13:22.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3832094,Measurement of Absolute Retinal Blood Flow Using a Laser Doppler Velocimeter Combined with Adaptive Optics,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Purpose</strong>: Development and validation of an absolute laser Doppler velocimeter (LDV) based on an adaptive optical fundus camera which provides simultaneously high definition images of the fundus vessels and absolute maximal red blood cells (RBCs) velocity in order to calculate the absolute retinal blood flow.\newline<br> <strong>Methods</strong>: This new absolute laser Doppler velocimeter is combined with the adaptive optics fundus camera (rtx1, Imagine Eyes$^\copyright$,Orsay, France) outside its optical wavefront correction path. A 4 seconds recording includes 40 images, each synchronized with two Doppler shift power spectra. Image analysis provides the vessel diameter close to the probing beam and the velocity of the RBCs in the vessels are extracted from the Doppler spectral analysis. Combination of those values gives an average of the absolute retinal blood flow. An in vitro experiment consisting of latex microspheres flowing in water through a glass-capillary to simulate a blood vessel and in vivo measurements on six healthy humans were done to assess the device.\newline<br> <strong>Results</strong>: In the in vitro experiment, the calculated flow varied between 1.75µl/min and 25.9µl/min and was highly correlated (r<sup>2</sup>= 0.995) with the imposed flow by a syringe pump.<br> In the in vivo experiment, the error between the flow in the parent vessel and the sum of the flow in the daughter vessels was between -11% and 36% (mean±sd 5.7±18.5%). Retinal blood flow in the main temporal retinal veins of healthy subjects varied between 0.9 µL/min and 13.2µL/min. <strong>Conclusion</strong>: This adaptive optics LDV prototype (aoLDV) allows the measurement of absolute retinal blood flow derived from the retinal vessel diameter and the maximum RBCs velocity in that vessel.",mds,True,findable,2,0,0,0,0,2020-05-18T13:32:18.000Z,2020-05-18T13:32:20.000Z,cern.zenodo,cern,"laser Doppler velocimetry, retina vessel","[{'subject': 'laser Doppler velocimetry, retina vessel'}]",,
+10.57745/lutmne,Long-term global mining data to 2019,Recherche Data Gouv,2022,,Dataset,,"This dataset brings together several types of mining data for 50 mining elements* provided by the U.S. Geological Survey (USGS). Long trend global mining production to 2019 and global reserves data to 2021 and global resources when available are extracted from annual reports, documentation and raw data. *Aluminium, Antimony, Arsenic, Bauxite, Beryllium, Boron, Bromine, Cadmium, Cesium, Chromium, Cobalt, Copper, Gallium, Germanium, Gold, Graphite, Hafnium, Indium, Iodine, Iron, Lead, Lithium, Magnesium, Manganese, Mercury, Molybdenum, Nickel, Niobium, Phosphorus, Platinum group metal, Rare Earths, Rhenium, Rubidium, Selenium, Silica, Silicon, Silver, Strontium, Sulfur, Tantalum, Tellurium, Thallium, Thorium, Tin, Titanium, Tungsten, Vanadium, Yttrium, Zinc, Zirconium",mds,True,findable,95,10,0,0,0,2022-12-07T11:17:07.000Z,2022-12-09T19:55:08.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.4646678,Glacier Clusters identification across Chilean Andes using Topo-Climatic variables: DATA,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",These data correspond to the information published in Glacier Clusters identification across Chilean Andes using Topo-Climatic variables 10.5354/0719-5370.2020.59009 https://investigacionesgeograficas.uchile.cl/index.php/IG/article/view/59009 https://www.researchgate.net/publication/348049084_Glacier_Clusters_identification_across_Chilean_Andes_using_Topo-Climatic_variables,mds,True,findable,0,0,0,0,0,2021-03-30T07:28:43.000Z,2021-03-30T07:28:44.000Z,cern.zenodo,cern,"Chilean Andes, climatology, glacier clusters, topography","[{'subject': 'Chilean Andes, climatology, glacier clusters, topography'}]",,
+10.5281/zenodo.5501338,ATLAS Open Data 13 TeV analysis C++ framework,Zenodo,2020,en,Software,"European Union Public License 1.1,Open Access",A repository with 12 high energy physics analysis examples using the ATLAS Open Data 13 TeV dataset released in 2020. It is written in C++ and some bash scripts. * Documentation of the code: http://opendata.atlas.cern/release/2020/documentation/frameworks/cpp.html * Documentation of the analysis: http://opendata.atlas.cern/release/2020/documentation/physics/intro.html,mds,True,findable,0,0,1,0,0,2021-09-11T14:43:23.000Z,2021-09-11T14:43:24.000Z,cern.zenodo,cern,"ATLAS,HEP,physics,analysis,education,open source,LHC,outreach","[{'subject': 'ATLAS'}, {'subject': 'HEP'}, {'subject': 'physics'}, {'subject': 'analysis'}, {'subject': 'education'}, {'subject': 'open source'}, {'subject': 'LHC'}, {'subject': 'outreach'}]",,
+10.5281/zenodo.10207347,"Link to data for the paper ""Probing resonant Andreev reflections by photon-assisted tunneling at the atomic scale""",Zenodo,2020,en,Other,Creative Commons Attribution 4.0 International,"We provide all experimental data underlying the findings in the paper ""Resonant Andreev reflections probed by photon-assisted tunnelling at the atomic scale"" and the code generated for the simulations.",api,True,findable,0,0,0,0,0,2023-11-26T12:47:06.000Z,2023-11-26T12:47:06.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4014726,Supplement to : Accelerated Snow Melt in the Russian Caucasus Mountains After the Saharan Dust Outbreak in March 2018,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These datasets contains all the data used in Accelerated Snow Melt in the Russian Caucasus Mountains After the Saharan Dust Outbreak in March 2018 by Dumont et al., in Journal of Geophysical Research.<br> This dataset includes : Sentinel-2 cloud masks, snow depth measurements, snow surface impurity content estimated from Sentinel-2, Sentinel-2 surface reflectances and digital elevation models. Dumont, M., Tuzet, F., Gascoin, S., Picard, G., Kutuzov, S., Lafaysse, M., et al. (2020). Accelerated snow melt in the Russian Caucasus mountains after the Saharan dust outbreak in March 2018. Journal of Geophysical Research: Earth Surface, 125, e2020JF005641. https://doi.org/10.1029/2020JF005641",mds,True,findable,0,0,0,0,0,2020-09-04T09:24:13.000Z,2020-09-04T09:24:14.000Z,cern.zenodo,cern,"snow,light absorbing impurities,remote sensing","[{'subject': 'snow'}, {'subject': 'light absorbing impurities'}, {'subject': 'remote sensing'}]",,
+10.5061/dryad.6q573n621,Focal vs. faecal: Seasonal variation in the diet of wild vervet monkeys from observational and DNA metabarcoding data,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"1. Assessing the diet of wild animals reveals valuable information about their ecology and trophic relationships that may help elucidate dynamic interactions in ecosystems and forecast responses to environmental changes. 2. Advances in molecular biology provide valuable research tools in this field. However, comparative empirical research is still required to highlight strengths and potential biases of different approaches. Therefore, this study compares environmental DNA and observational methods for the same study population and sampling duration. 3. We employed DNA metabarcoding assays targeting plant and arthropod diet items in 823 faecal samples collected over 12 months in a wild population of an omnivorous primate, the vervet monkey (Chlorocebus pygerythrus). DNA metabarcoding data were subsequently compared to direct observations. 4. We observed the same seasonal patterns of plant consumption with both methods, however, DNA metabarcoding showed considerably greater taxonomic coverage and resolution compared to observations, mostly due to the construction of a local plant DNA database. We found a strong effect of season on variation in plant consumption largely shaped by the dry and wet seasons. The seasonal effect on arthropod consumption was weaker but feeding on arthropods was more frequent in spring and summer, showing overall that vervets adapt their diet according to available resources. The DNA metabarcoding assay outperformed also direct observations of arthropod consumption in both taxonomic coverage and resolution. 5. Combining traditional techniques and DNA metabarcoding data can therefore not only provide enhanced assessments of complex diets or reveal trophic interactions to the benefit of wildlife conservationists and managers but also opens new perspectives for behavioural ecologists studying whether diet variation in social species is induced by environmental differences or might reflect selective foraging behaviours.",mds,True,findable,123,19,0,1,0,2022-09-28T22:41:22.000Z,2022-09-28T22:41:23.000Z,dryad.dryad,dryad,"DNA metabarcoding,Vervet Monkey,Chlorocebus pygerythrus,FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'DNA metabarcoding'}, {'subject': 'Vervet Monkey'}, {'subject': 'Chlorocebus pygerythrus'}, {'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['5277538659 bytes'],
+10.5061/dryad.pp72j,"Data from: Is there any evidence for rapid, genetically-based, climatic niche expansion in the invasive common ragweed?",Dryad,2017,en,Dataset,Creative Commons Zero v1.0 Universal,"Climatic niche shifts have been documented in a number of invasive species by comparing the native and adventive climatic ranges in which they occur. However, these shifts likely represent changes in the realized climatic niches of invasive species, and may not necessarily be driven by genetic changes in climatic affinities. Until now the role of rapid niche evolution in the spread of invasive species remains a challenging issue with conflicting results. Here, we document a likely genetically-based climatic niche expansion of an annual plant invader, the common ragweed (Ambrosia artemisiifolia L.), a highly allergenic invasive species causing substantial public health issues. To do so, we looked for recent evolutionary change at the upward migration front of its adventive range in the French Alps. Based on species climatic niche models estimated at both global and regional scales we stratified our sampling design to adequately capture the species niche, and localized populations suspected of niche expansion. Using a combination of species niche modeling, landscape genetics models and common garden measurements, we then related the species genetic structure and its phenotypic architecture across the climatic niche. Our results strongly suggest that the common ragweed is rapidly adapting to local climatic conditions at its invasion front and that it currently expands its niche toward colder and formerly unsuitable climates in the French Alps (i.e. in sites where niche models would not predict its occurrence). Such results, showing that species climatic niches can evolve on very short time scales, have important implications for predictive models of biological invasions that do not account for evolutionary processes.",mds,True,findable,199,8,1,1,0,2016-04-05T13:32:34.000Z,2016-04-05T13:32:35.000Z,dryad.dryad,dryad,"2000-2010,Ambrosia artemisiifolia L.","[{'subject': '2000-2010'}, {'subject': 'Ambrosia artemisiifolia L.'}]",['1326414 bytes'],
+10.5281/zenodo.3382123,Adriatic-Ionian Bimodal Oscillating System - Coriolis Rotating Platform Experiment,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Numerical modelling has not yet offered satisfactory description of the functioning of the Adriatic/ Ionian and Levantine system.<br> So far, the explanation for the inversion of the near-surface circulation has been mainly sought in the wind stress curl.<br> Recent results have however suggested that the wind forcing cannot explain such inversions.<br> Scientific objective of this study is to show from physical modelling that the inversions of the NIG circulation<br> in an idealized Adriatic-Ionian/ Eastern Mediterranean circulation system can be generated<br> only bu changing the inflowing water density (from the Adriatic) with respect to the residing water in the Ionian basin.",mds,True,findable,1,0,0,0,0,2019-09-17T11:12:28.000Z,2019-09-17T11:12:28.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3715652,Learn2Reg - The Challenge,Zenodo,2020,,Other,"Creative Commons Attribution No Derivatives 4.0 International,Open Access","This is the challenge design document for ""Learn2Reg - The Challenge"", accepted for MICCAI 2020. Medical image registration plays a very important role in improving clinical workflows, computer-assisted interventions and diagnosis as well as for research studies involving e.g. morphological analysis. Besides ongoing research into new concepts for optimisation, similarity metrics and deformation models, deep learning for medical registration is currently starting to show promising advances that could improve the robustness, computation speed and accuracy of conventional algorithms to enable better practical translation. Nevertheless, there exists no commonly used benchmark dataset to compare state-of-the-art learning based registration among another and with their conventional (not trained) counterparts. With few exceptions (CuRIOUS at MICCAI 2018/2019 and the Continuous Registration Challenge at WBIR 2018) there has also been no comprehensive registration challenge covering different anatomical structures and evaluation metrics. We also believe that the entry barrier for new teams to contribute to this emerging field are higher than e.g. for segmentation, where standardised datasets (e.g. Medical Decathlon, BraTS) are easily available. In contrast, many registration tasks, require resampling from different voxel spacings, affine pre-registration and can lead to ambiguous and error-prone evaluation of whole deformation fields. <br> We propose a simplified challenge design that removes many of the common pitfalls for learning and applying transformations. We will provide pre-preprocessed data (resample, crop, pre-align, etc.) that can be directly employed by most conventional and learning frameworks. Only displacement fields in voxel dimensions in a standard orientation will have to be provided by participants and python code to test their application to training data will be provided as open-source along with all evaluation metrics. Our challenge will consist of 4 clinically relevant sub-tasks (datasets) that are complementary in nature. They can either be individually or comprehensively addressed by participants and cover both intra- and inter-patient alignment, CT, ultrasound and MRI modalities, neuro-, thorax and abdominal anatomies and the four of the imminent challenges of medical image registration: learning from small datasets estimating large deformations dealing with multi-modal scans learning from noisy annotations An important aspect of challenges are comprehensive and fair evaluation criteria. Since, medical image registration is not limited to accurately and robustly transferring anatomical annotations but should also provide plausible deformations, we will incorporate a measure of transformation complexity (the standard deviation of local volume change defined by the Jacobian determinant of the deformation). To encourage the submission of learning based approaches that reduce the computational burden of image registration, the run-time computation time will also be included into the ranking by awarding extra points. Due to differences in hardware, the computation time (including all steps of the employed pipeline) will be measured by running algorithms on the grand-challenge.org evaluation platform (where the whole challenge will be hosted) with the potential of using Nvidia GPU backends (this will not be a strict requirement for participants).",mds,True,findable,112,0,0,0,0,2020-03-19T07:40:10.000Z,2020-03-19T07:40:11.000Z,cern.zenodo,cern,"MICCAI Challenges,Biomedical Challenges,MICCAI,Registration,Brain,Thorax,Abdomen,Deformable,Multimodal,Realtime","[{'subject': 'MICCAI Challenges'}, {'subject': 'Biomedical Challenges'}, {'subject': 'MICCAI'}, {'subject': 'Registration'}, {'subject': 'Brain'}, {'subject': 'Thorax'}, {'subject': 'Abdomen'}, {'subject': 'Deformable'}, {'subject': 'Multimodal'}, {'subject': 'Realtime'}]",,
+10.5281/zenodo.7732341,pyxem/orix: orix 0.11.1,Zenodo,2023,,Software,Open Access,"orix 0.11.1 is a patch release of orix, an open-source Python library for handling orientations, rotations and crystal symmetry. See below, the changelog or the GitHub changelog for all updates from the previous release. Fixed Initialization of a crystal map with a phase list with fewer phases than in the phase ID array given returns a map with a new phase list with correct phase IDs.",mds,True,findable,0,0,0,0,0,2023-03-14T09:12:02.000Z,2023-03-14T09:12:02.000Z,cern.zenodo,cern,,,,
+10.57745/3vmb3y,Mobi-Switch : a boardgame about urban mobility sustainability,Recherche Data Gouv,2023,,Dataset,,"Mobi-Switch is a board game developed by a team from INRAE's UMR RECOVER, as part of the ANR SwITCh project. The aim of the game is to raise awareness of the sustainability of urban mobility and the challenges associated with it. Players take on the role of elected representatives wishing to improve the sustainability of mobility on their territory. In addition to the collective goal of sustainable mobility, each player is assigned a personal goal. In each round (6 in total, corresponding to the 6 years of a municipal mandate), each player chooses a project from the cards in his or her hand, and tries to convince the others to adhere to his or her project. Each project has an impact on the indicators shown on the game board. It's up to the players to make the right choices to steer mobility towards greater sustainability, while trying to achieve their personal goals.",mds,True,findable,71,2,0,0,0,2023-09-05T08:17:20.000Z,2023-09-05T08:48:43.000Z,rdg.prod,rdg,,,,
+10.25384/sage.24147060,sj-docx-1-jic-10.1177_08850666231199937 - Supplemental material for Perceived Quality of Life in Intensive Care Medicine Physicians: A French National Survey,SAGE Journals,2023,,Text,In Copyright,"Supplemental material, sj-docx-1-jic-10.1177_08850666231199937 for Perceived Quality of Life in Intensive Care Medicine Physicians: A French National Survey by Nicolas Terzi, Alicia Fournier, Olivier Lesieur, Julien Chappé, Djillali Annane, Jean-Luc Chagnon, Didier Thévenin, Benoit Misset, Jean-Luc Diehl, Samia Touati, Hervé Outin, Stéphane Dauger, Arnaud Sement, Jean-Noël Drault, Jean-Philippe Rigaud, Alexandra Laurent and in Journal of Intensive Care Medicine",mds,True,findable,0,0,0,0,0,2023-09-15T12:11:54.000Z,2023-09-15T12:11:54.000Z,figshare.sage,sage,"Emergency Medicine,Aged Health Care,Respiratory Diseases","[{'subject': 'Emergency Medicine'}, {'subject': 'Aged Health Care'}, {'subject': 'Respiratory Diseases'}]",['37585 Bytes'],
+10.5281/zenodo.7189647,Cophylogeny reconstruction allowing for multiple associations through approximate Bayesian computation,Zenodo,2022,,Software,"CeCILL Free Software License Agreement v2.0,Open Access","Nowadays, the most used method in studies of the coevolution of hosts and symbionts is phylogenetic tree reconciliation. A crucial issue in this method is that from a biological point of view, reasonable cost values for an event-based parsimonious reconciliation are not easily chosen. Different approaches have been developed to infer such cost values for a given pair of host and symbiont trees. However, a major limitation of these approaches is their inability to model the invasion of different host species by the same symbiont species (referred to as a spread event), which is thought to happen in symbiotic relations. To mention one example, the same species of insects may pollinate different species of plants. This results in multiple associations observed between the symbionts and their hosts (meaning that a symbiont is no longer specific to a host), that are not compatible with the current methods of coevolution. In this paper, we propose a method, called AmoCoala (a more realistic version of a previous tool called Coala) which for a given pair of host and symbiont trees, estimates the probabilities of the cophylogeny events, in presence of spread events, relying on an approximate Bayesian computation (ABC) approach. The algorithm that we propose, by including spread events, enables the multiple associations to be taken into account in a more accurate way, inducing more confidence in the estimated sets of costs and thus in the reconciliation of a given pair of host and symbiont trees. Its rooting in the tool Coala allows it to estimate the probabilities of the events even in the case of large datasets. We evaluate our method on synthetic and real datasets.",mds,True,findable,0,0,0,0,0,2022-10-25T22:13:45.000Z,2022-10-25T22:13:46.000Z,cern.zenodo,cern,"reconciliation,cophylogeny,ABC method,spread","[{'subject': 'reconciliation'}, {'subject': 'cophylogeny'}, {'subject': 'ABC method'}, {'subject': 'spread'}]",,
+10.6084/m9.figshare.c.6584765.v1,Efficacy and auditory biomarker analysis of fronto-temporal transcranial direct current stimulation (tDCS) in targeting cognitive impairment associated with recent-onset schizophrenia: study protocol for a multicenter randomized double-blind sham-controlled trial,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background In parallel to the traditional symptomatology, deficits in cognition (memory, attention, reasoning, social functioning) contribute significantly to disability and suffering in individuals with schizophrenia. Cognitive deficits have been closely linked to alterations in early auditory processes (EAP) that occur in auditory cortical areas. Preliminary evidence indicates that cognitive deficits in schizophrenia can be improved with a reliable and safe non-invasive brain stimulation technique called tDCS (transcranial direct current stimulation). However, a significant proportion of patients derive no cognitive benefits after tDCS treatment. Furthermore, the neurobiological mechanisms of cognitive changes after tDCS have been poorly explored in trials and are thus still unclear. Method The study is designed as a randomized, double-blind, 2-arm parallel-group, sham-controlled, multicenter trial. Sixty participants with recent-onset schizophrenia and cognitive impairment will be randomly allocated to receive either active (n=30) or sham (n=30) tDCS (20-min, 2-mA, 10 sessions during 5 consecutive weekdays). The anode will be placed over the left dorsolateral prefrontal cortex and the cathode over the left auditory cortex. Cognition, tolerance, symptoms, general outcome and EAP (measured with EEG and multimodal MRI) will be assessed prior to tDCS (baseline), after the 10 sessions, and at 1- and 3-month follow-up. The primary outcome will be the number of responders, defined as participants demonstrating a cognitive improvement ≥Z=0.5 from baseline on the MATRICS Consensus Cognitive Battery total score at 1-month follow-up. Additionally, we will measure how differences in EAP modulate individual cognitive benefits from active tDCS and whether there are changes in EAP measures in responders after active tDCS. Discussion Besides proposing a new fronto-temporal tDCS protocol by targeting the auditory cortical areas, we aim to conduct a randomized controlled trial (RCT) with follow-up assessments up to 3 months. In addition, this study will allow identifying and assessing the value of a wide range of neurobiological EAP measures for predicting and explaining cognitive deficit improvement after tDCS. The results of this trial will constitute a step toward the use of tDCS as a therapeutic tool for the treatment of cognitive impairment in recent-onset schizophrenia. Trial registration ClinicalTrials.gov NCT05440955. Prospectively registered on July 1st, 2022.",mds,True,findable,0,0,0,0,0,2023-04-13T12:04:24.000Z,2023-04-13T12:04:24.000Z,figshare.ars,otjm,"Medicine,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,69999 Biological Sciences not elsewhere classified,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.6506336,Data for Embryo-scale epithelial buckling forms a propagating furrow that initiates gastrulation,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is the data and code corresponding to Embryo-scale epithelial buckling forms a propagating furrow that initiates gastrulation, <em>Nature Comms.</em> <strong>13</strong>:3348. <strong>Code</strong> The file Surface_Evolver_script.txt is ... the Surface Evolver script, use with Ken Brakke's Surface Evolver <strong>Data sources</strong> The figure panels are based on the datafiles listed below, visualised either with Ken Brakke's Surface Evolver or with gnuplot 5. When the datafiles listed do not contain the primary data, they contain a commented last line which is the command line for the software datamerge to generate it from other datafiles found in the Data_sources subdirectory. <strong>Figure 1</strong> Fig. 1c : data provided in <code>data_for_Fig_1g.tsv</code> Fig. 1f : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp</code> Fig. 1g : <code>myosin_profile_us_only.pdf</code> generated with gnuplot script <code>myosin_profile.plot</code> <strong>Figure 2</strong> Fig. 2a : <code>strain_profile_100_0_time_013.pdf</code> generated with gnuplot script <code>strain_profile.plot</code> Fig. 2b : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp</code> Fig. 2c : <code>stress_profile_100_0_time_013.pdf</code> gnuplot script <code>stress_profile.plot</code> Fig. 2d : visualisation from Surface Evolver file <code>Young100dixPoisson000Step063.dmp</code> <strong>Figure 3</strong> Fig. 3a : <code>myosin_area.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. 3b : <code>area_stripes_t=-1.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. 3c : <code>only_AP_stripes_t=-1.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. 3d : <code>only_DV_stripes_t=-1.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. 3e : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp Young100dixPoisson000Step063.dmp Young100dixPoisson000Step163.dmp Young100dixPoisson000Step213.dmp</code> <strong>Figure 4</strong> Fig. 4a : visualisation from Surface Evolver file <code>Young100dixPoisson000Step213.dmp</code> Fig. 4b : <code>furrow_propagation.pdf</code> generated with gnuplot script <code>furrow_propagation.plot</code> Fig. 4c : <code>rate_of_furrowing_t=3.pdf</code> generated with gnuplot script <code>furrow_propagation.plot</code> Fig. 4f : <code>curvature.pdf</code> generated with gnuplot script <code>curvature.plot</code> <strong>Figure 5</strong> Fig. 5a : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp Young100dixPoisson000Step063.dmp Young100dixPoisson000Step113.dmp Young100dixPoisson000Step163.dmp Young100dixPoisson000Step213.dmp</code> Fig. 5b : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp Young100dixPoisson000Step140.dmp</code> Fig. 5d : <code>stress_laserablations_profile_100_0_time_063.pdf</code> generated with gnuplot script <code>stress_profile_for_laser_ablations.plot</code> Fig. 5e : <code>laser_ablation_recoil.pdf</code> generated with gnuplot script <code>laser_ablation_recoil.plot</code> <strong>Supp Figure 1</strong> Fig. S1a : <code>time_profile_FINI_100_0.pdf</code> generated with gnuplot script <code>time_profile_stress.plot</code> Fig. S1b : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp</code> Fig. S1d : visualisation from Surface Evolver file <code>Young100dixPoisson000Step063.dmp</code> Fig. S1e : <code>strain_profile_100_0_time_063.pdf</code> gnuplot script <code>strain_profile.plot</code> Fig. S1f : <code>stress_profile_100_0_time_063.pdf</code> gnuplot script <code>stress_profile.plot</code> <strong>Supp Figure 1</strong> Fig. S2a : <code>area_stripes_time_evolution.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. S2b : <code>area_stripes_time_evolution_SPIM.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> <strong>Supp Figure 3</strong> Fig. S3a : visualisation from Surface Evolver file <code>Young100dixPoisson000Step213.dmp</code> Fig. S3c : <code>AP_binned_strain.pdf</code> generated with gnuplot script <code>AP_binned_strain.plot</code> Fig. S3d : <code>furrow_propagation_experimental.pdf</code> generated with gnuplot script <code>plot_furrow.plot</code> Fig. S3e : <code>curvature_DV_indiv.pdf</code> generated with gnuplot script <code>curvature.plot</code> Fig. S3f : <code>depth_Gastrulation_ordi_Wild_Type_STITCHED_100_0.pdf</code> generated with gnuplot script <code>depth.plot</code>",mds,True,findable,0,0,0,0,0,2022-04-29T19:00:04.000Z,2022-04-29T19:00:05.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.2v1m1fj,"Data from: Differences in the fungal communities nursed by two genetic groups of the alpine cushion plant, Silene acaulis",Dryad,2018,en,Dataset,Creative Commons Zero v1.0 Universal,"Foundation plants shape the composition of local biotic communities and abiotic environments, but the impact of a plant’s intraspecific variations on these processes is poorly understood. We examined these links in the alpine cushion moss campion (Silene acaulis) on two neighboring mountain ranges in the French Alps. Genotyping of cushion plants revealed two genetic clusters matching known subspecies. The exscapa subspecies was found on both limestone and granite while the longiscapa one was only found on limestone. Even on similar limestone bedrock, cushion soils from the two S. acaulis subspecies deeply differed in their impact on soil abiotic conditions. They further strikingly differed from each other and from the surrounding bare soils in fungal community composition. Plant genotype variations accounted for a large part of the fungal composition variability in cushion soils, even when considering geography or soil chemistry, and particularly for the dominant molecular operational taxonomic units (MOTUs). Both saprophytic and biotrophic fungal taxa were related to the MOTUs recurrently associated with a single plant genetic cluster. Moreover, the putative phytopathogens were abundant, and within the same genus (Cladosporium) or species (Pyrenopeziza brassicae), MOTUs showing specificity for each plant subspecies were found. Our study highlights the combined influences of bedrock and plant genotype on fungal recruitment into cushion soils and suggests the coexistence of two mechanisms, an indirect selection resulting from the colonization of an engineered soil by free-living saprobes, and a direct selection resulting from direct plant-fungi interactions.",mds,True,findable,295,35,1,1,0,2018-11-23T13:20:20.000Z,2018-11-23T13:20:21.000Z,dryad.dryad,dryad,"Fungal community,nurse effect,Silene acaulis,soil ecosystem engineering,Pyrenopeziza brassicae,Holocene,community genetics","[{'subject': 'Fungal community'}, {'subject': 'nurse effect'}, {'subject': 'Silene acaulis'}, {'subject': 'soil ecosystem engineering'}, {'subject': 'Pyrenopeziza brassicae'}, {'subject': 'Holocene'}, {'subject': 'community genetics'}]",['12290810 bytes'],
+10.5281/zenodo.4759501,"Figs. 40-45 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access",Figs. 40-45. Larva of Protonemura algirica bejaiana ssp. n. 40: front angle of the pronotum; 41: hind femur; 42: outer apical part of the femur; 43: 5–6th tergal segments; 44: basal segments of the cercus; 45: 15th segment of the cercus (scale 0.1 mm).,mds,True,findable,0,0,2,0,0,2021-05-14T02:25:19.000Z,2021-05-14T02:25:20.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.4538745,Data from: Functional biogeography of weeds reveals how anthropogenic management blurs trait-climate relationships,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The dataset gathers information on the 954 cropland and 5619 grassland plant assemblages studied in the research article <em>Functional biogeography of weeds reveals how anthropogenic management blurs trait-climate relationships</em> by Bourgeois, B., Munoz, F., Gaba, S., Denelle, P., Fried, G., Storkey, J. and Violle, C. published in the <em>Journal of Vegetation Science</em>. A R script for analyzing data is also provided. Data include: <strong>SURVEY.ID</strong>: unique identifier of the plant survey; <strong>HABITAT</strong>: type of habitat (2 levels: cropland - grassland); <strong>CROP TYPE</strong>: type of annual crop cultivated for croplands (4 levels: maize - oilseed - sunflower - winter cereal); <strong>HERBICIDE TREATMENT</strong>: herbicide treatment for croplands (2 levels: herbicide-free - herbicide-sprayed); <strong>CWM SLA</strong>: Community-Weighted Mean of Specific Leaf Area (in m<sup>2 </sup>/ kg); <strong>CWM LDMC</strong>: Community-Weighted Mean of Leaf Dry Matter Content (in mg / kg); <strong>CWM LNC</strong>: Community-Weighted Mean of Leaf Nitrogen Content (in mg N / kg); <strong>CWV SLA</strong>: Community-Weighted Variance of Specific Leaf Area (in m<sup>2 </sup>/ kg); <strong>CWV LDMC</strong>: Community-Weighted Variance of Leaf Dry Matter Content (in mg N / kg); <strong>CWV LNC</strong>: Community-Weighted Variance of Leaf Nitrogen Content (in mg / kg); <strong>GSLtw</strong>: Growing Season Length (in days) accounting for both temperature and soil water limitations; <strong>Xcoord, Ycoord</strong>: coordinates of the plant survey. Please contact the authors for further information.",mds,True,findable,0,0,0,0,0,2021-02-15T16:17:03.000Z,2021-02-15T16:17:04.000Z,cern.zenodo,cern,"Agroecosystems,Arable weeds,Croplands,Environmental filtering,Functional biogeography,Grasslands,Leaf traits,Management intensification,Plant assemblages,Trait-environment relationships","[{'subject': 'Agroecosystems'}, {'subject': 'Arable weeds'}, {'subject': 'Croplands'}, {'subject': 'Environmental filtering'}, {'subject': 'Functional biogeography'}, {'subject': 'Grasslands'}, {'subject': 'Leaf traits'}, {'subject': 'Management intensification'}, {'subject': 'Plant assemblages'}, {'subject': 'Trait-environment relationships'}]",,
+10.5281/zenodo.4759505,"Fig. 52 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 52. Habitus of the matured larva of Protonemura berberica Vinçon & S{nchez-Ortega, 1999. (scale 1 mm).",mds,True,findable,0,0,2,0,0,2021-05-14T02:26:03.000Z,2021-05-14T02:26:03.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5061/dryad.c866t1g49,Ecological specialization and niche overlap of subterranean rodents inferred from DNA metabarcoding diet analysis,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Knowledge of how animal species use food resources available in the environment increases our understanding of ecological processes. However, obtaining this information using traditional methods is a hard task for species feeding on a large variety of food items in highly diverse environments. We amplified the DNA of plants for 306 scat and 40 soil samples, and applied an eDNA metabarcoding approach to investigate food preferences, degree of diet specialization and diet overlap of seven herbivore rodent species of the Ctenomys genus distributed in southern and midwestern Brazil. The metabarcoding approach revealed that species consume more than 60% of the plant families recovered in soil samples, indicating generalist feeding habits of ctenomyids. The Poaceae family was the most common food resource retrieved in scats of all species as well in soil samples. Niche overlap analysis indicated high overlap in the plant families and Molecular Operational Taxonomic Units consumed, mainly among the southern species. Interspecific difference in diet composition was influenced, among other factors, by the availability of resources in the environment. In addition, our results provide support for the hypothesis that the allopatric distributions of ctenomyids allow them to exploit the same range of resources when available, possibly because of the absence of interspecific competition.",mds,True,findable,489,322,0,0,0,2020-08-10T15:12:13.000Z,2020-08-10T15:12:14.000Z,dryad.dryad,dryad,,,['7824034241 bytes'],
+10.5281/zenodo.3862151,MGB hydrological model for Paraná Basin,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains model code, input and output data for the MGB hydrological model applied to the Upper Paraná Basin. Output files (QTUDO_XXX.QBI) are binary ones (single format) containing daily discharges for all model unit-catchments for each simulation scenario. Simulation scenarios are a combination of storage representation and operation rule types. Storage representation types: L=Lumped reservoir E=Equally distributed reservoir V=Variably distributed reservoir Operation rules: T=Three points rule Tg=rule T with global-based configuration R=regression-based rule Rg=rule R with global-based configuration S=inflow-based rule (based on Shin et al. 2019 WRR) Sg=rule S with global-based configuration Additionally, simulation scenarios with pristine conditions (i.e., without reservoirs) and without floodplains are also provided. For further details please contact Ayan Fleischmann at 'ayan.fleischmann at gmail.com'.",mds,True,findable,0,0,0,0,0,2020-05-28T10:42:08.000Z,2020-05-28T10:42:10.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.v475g,Data from: Integrating correlation between traits improves spatial predictions of plant functional composition,Dryad,2017,en,Dataset,Creative Commons Zero v1.0 Universal,"Functional trait composition is increasingly recognized as key to better understand and predict community responses to environmental gradients. Predictive approaches traditionally model the weighted mean trait values of communities (CWMs) as a function of environmental gradients. However, most approaches treat traits as independent regardless of known trade-offs between them, which could lead to spurious predictions. To address this issue, we suggest jointly modeling a suit of functional traits along environmental gradients while accounting for relationships between traits. We use generalized additive mixed effect models to predict the functional composition of alpine grasslands in the Guisane Valley (France). We demonstrate that, compared to traditional approaches, joint trait models explain considerable amounts of variation in CWMs, yield less uncertainty in trait CWM predictions and provide more realistic spatial projections when extrapolating to novel environmental conditions. Modeling traits and their co-variation jointly is an alternative and superior approach to predicting traits independently. Additionally, compared to a “predict first, assemble later†approach that estimates trait CWMs post hoc based on stacked species distribution models, our “assemble first, predict later†approach directly models trait-responses along environmental gradients, and does not require data and models on species’ distributions, but only mean functional trait values per community plot. This highlights the great potential of joint trait modeling approaches in large-scale mapping applications, such as spatial projections of the functional composition of vegetation and associated ecosystem services as a response to contemporary global change.",mds,True,findable,167,17,1,1,0,2017-10-05T16:00:32.000Z,2017-10-05T16:00:33.000Z,dryad.dryad,dryad,"generalized additive mixed effect models,Community weighted mean,response and effect traits","[{'subject': 'generalized additive mixed effect models'}, {'subject': 'Community weighted mean'}, {'subject': 'response and effect traits'}]",['16754 bytes'],
+10.5281/zenodo.10061547,FIG. 4 in Passiflora tinifolia Juss. (Passiflora subgenus Passiflora): resurrection and synonymies,Zenodo,2023,,Image,Creative Commons Attribution 4.0 International,"FIG. 4. — Passiflora tinifolia Juss., French Guiana (photos: Maxime Rome): A, young leaf with glands at the apex of the petiole and linear stipules; B, mature leaf with peduncles gathered in a pseudoraceme; C, flower bud with bracts; D, flower; E, longitudinal section of flower; F, immature and mature fruit.",api,True,findable,0,0,0,2,0,2023-11-01T12:50:46.000Z,2023-11-01T12:50:46.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Magnoliopsida,Malpighiales,Passifloraceae,Passiflora","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Magnoliopsida'}, {'subject': 'Malpighiales'}, {'subject': 'Passifloraceae'}, {'subject': 'Passiflora'}]",,
+10.5281/zenodo.7472518,"Dataset for ""Coulomb-mediated antibunching of an electron pair surfing on sound""",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","*********************************************************<br> This repository contains the raw experimental data associated with the manuscript<br> ""Coulomb-mediated antibunching of an electron pair surfing on sound""<br> by Junliang Wang et al.<br> See arXiv:2210.03452 for more details.<br> ********************************************************* ***************************************<br> Folder organization<br> ***************************************<br> Each figure in the manuscript which contains experimental data has assigned an unique folder.<br> In each folder, you will find:<br> - a 'data' folder containing the data files<br> - the figure in pdf format<br> - the jupyter notebook employed to generate the figure. There are two types of data files:<br> - .txt with comma separated values where the header contains the information for each column.<br> - .xlxs: standard Excel format.",mds,True,findable,0,0,1,0,0,2022-12-22T12:55:10.000Z,2022-12-22T12:55:10.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23575387.v1,Additional file 10 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 9,mds,True,findable,0,0,0,0,0,2023-06-25T03:12:02.000Z,2023-06-25T03:12:02.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['56320 Bytes'],
+10.5281/zenodo.290428,"Reproducible Workflow for the ""Tuning Backfilling Queues"" article.",Zenodo,2017,,Software,"ISC License,Open Access","Tuning EASY-Backfilling Queues reproducible build.<br> ================================================== This repository contains the data, code, and workflow<br> necessary to build the ""Tuning EASY Backfilling Queues""<br> paper by Lelong, Reis and Trystram. The workflow is managed using zymake.<br> http://www-personal.umich.edu/~ebreck/code/zymake/ The dependencies are managed via the NIX package manager.<br> https://nixos.org/nix/ Please read the file 'zymakefile' to see the workflow. DEPENDENCIES:<br> =============<br> * NIX: curl https://nixos.org/nix/install | sh<br> * Ocaml packages are not yet managed by NIX.<br> To be installed using OPAM: batteries oasis cmdliner See file default.nix for a list of the dependencies<br> that will be managed by nix. RUNNING:<br> ======== The build is obtained by running the command ""make"" and should<br> take half a dozen days on a recent 200-core machine.<br> This will build the zymake tool under /zymake and<br> the simulator under ocs/. A dry run can be obtained by ""make dummy"". CONTACT:<br> ========<br> We do not provide other documentation for this workflow system.<br> Feel free to contact tuningqueues@valentinreis.com for any inquiry<br> including troubleshooting of reproducing the results. LICENSE:<br> ========<br> All code under ocs/ and misc/ is copyright of Valentin Reis and<br> distributed under the ISC license (see LICENSE.md), except<br> file ocs/src/binary_heap which is copyrighted by Jean-Christophe<br> Fillatre (see file for license).<br> The Zymake workflow system is copyright of Eric Breck(see files<br> for license)<br> The workflows in gz/ obtained via the Parallel Workload Acthive<br> (http://www.cs.huji.ac.il/labs/parallel/workload/) remain<br> property of their respective owners.<br>",mds,True,findable,0,0,0,0,0,2017-02-12T10:08:26.000Z,2017-02-12T10:08:27.000Z,cern.zenodo,cern,Scheduling Backfilling EASY Reproducible Workflow Zymake,[{'subject': 'Scheduling Backfilling EASY Reproducible Workflow Zymake'}],,
+10.5281/zenodo.7516222,Portuguese Translation of Researcher Mental Health and Well-being Manifesto - Manifesto sobre a Saúde Mental e Bem-estar dos Investigadores,Zenodo,2023,pt,Other,"Creative Commons Attribution 4.0 International,Open Access","A ReMO COST Action é uma rede de stakeholders de todos os nÃveis da comunidade de investigação que elaboraram um Manifesto sobre a Saúde Mental e Bem-estar dos Investigadores. Este Manifesto apela à avaliação de como a saúde mental e o bem-estar dos investigadores podem ser mais bem nutridos e sustentados, por meio de ações e iniciativas nos nÃveis polÃtico, institucional, comunitário e individual.<br> <br> Este Manifesto apela a todos os stakeholders do ecossistema de investigação para que se envolvam no desenvolvimento de polÃticas que monitorizem, melhorem e mantenham o bem-estar e a saúde mental no ambiente de investigação, delineando métricas mais abrangentes de sucesso e qualidade, apoiando o equilÃbrio entre a vida profissional e pessoal, assim como a inclusão e as carreiras em investigação sustentáveis e favoráveis à famÃlia. The English Language Version of the Manifesto can be found at: https://doi.org/10.5281/zenodo.5559805",mds,True,findable,0,0,0,0,0,2023-01-09T14:31:23.000Z,2023-01-09T14:31:23.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.1475906,Third Harmonic Generation Images Of The Lacuno-Canalicular Network In Bone Femoral Diaphysis Of Mice From The Bionm1 Project (Space Flight),Zenodo,2018,,Dataset,"Creative Commons Attribution 4.0,Open Access","Data set for 11 samples in 3 groups of Control, Space Flight and Synchro (ground control with space flight housing and feeding conditions). Contains THG images in tif format of 2D mosaic of selected samples and 3D stacks in selected anatomical regions of interest. See readme file for more information.",mds,True,findable,0,0,0,0,0,2018-10-31T16:24:03.000Z,2018-10-31T16:24:04.000Z,cern.zenodo,cern,"THG, bone, osteocyte, LCN, lacunae, canaliculi, space flight","[{'subject': 'THG, bone, osteocyte, LCN, lacunae, canaliculi, space flight'}]",,
+10.5061/dryad.dv41ns1wf,Data from: Variability of the atmospheric PM10 microbiome in three climatic regions of France,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Air pollution is a major public-health concern and it is recognized that particulate matter causes damage to human health through oxidative-stress, being responsible for several million premature deaths worldwide each year. Recent findings showed that, airborne microorganisms/spores can modulate aerosol toxicity by altering the oxidative potential of PM10. Primary Biogenic Organic Aerosols (PBOA) appears to be produced by only few genera of microorganisms, emitted by surrounding vegetation in the case of a regionally-homogeneous field site. This study presents the first comprehensive description of the structure and main sources of airborne microbial communities associated with the temporal trends in PM10 SC concentrations at 3 French sites, under different climates. By combining sugar chemistry and DNA Metabarcoding approaches, we intended to identify PM10-associated microbial communities and their main sources at three climatically different sampling-sites in France during summer 2018. This study accounted also for the interannual variability of the structure of summer airborne microbial community associated with PM10-SC concentrations during a consecutive 2-year survey at one site. Our results showed that the temporal evolutions of SC in PM10 in the three sites are associated with the abundance of only few specific airborne fungal and bacterial taxa. These taxa differ significantly between the 3 climatic regions studied. The structure of microbial communities associated with PM10 SC concentrations during a consecutive 2-year survey remained stable in the rural area. The atmospheric concentration levels of PM10 SC-species vary significantly between the 3 studied sites, but with no clear difference according to site typology (rural vs urban), suggesting that SC emissions are more related to regional climatic characteristics. The overall microbial beta diversity in PM10 samples is significantly different from that of the main vegetation around the studied urban sites. This indicates that airborne microorganisms at such urban sites do not originate only from the immediate surrounding vegetation, which is contrasting with observations at the scale of a regionally homogeneous rural site made in 2017. These results improve our understanding of the spatial behavior of tracers of PBOA emission sources, which need to be better characterized to further implement this important OM-mass fraction into CTM models.",mds,True,findable,153,17,0,0,0,2020-11-17T19:51:29.000Z,2020-11-17T19:51:31.000Z,dryad.dryad,dryad,,,['4509672 bytes'],
+10.5281/zenodo.7064041,"Figure data sets for the paper ""Coherent optical-microwave interface for manipulation of low-field electronic clock transitions in 171Yb3+:Y2SiO5""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Figure data sets.,mds,True,findable,0,0,0,0,0,2022-09-09T08:55:06.000Z,2022-09-09T08:55:06.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5649823,"FIGS. 37–40—FIG. 37 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIGS. 37–40—FIG. 37—Protonemura auberti, male. Paraproct outer lobe with trifurcated sclerite, dorso-caudal view; FIG. 38—Protonemura pennina, male. Paraproct outer lobe with trifurcated sclerite, ¾ dorso-ventral view; FIG. 39—Protonemura auberti, female, ventral view; FIG. 40—Protonemura aestiva, female, ventral view.",mds,True,findable,0,0,0,0,0,2021-11-05T21:11:55.000Z,2021-11-05T21:11:55.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.6084/m9.figshare.23575387,Additional file 10 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 9,mds,True,findable,0,0,0,0,0,2023-06-25T03:12:02.000Z,2023-06-25T03:12:03.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['56320 Bytes'],
+10.5281/zenodo.4753273,Figs. 1-5 in A New Perlodes Species And Its Subspecies From The Balkan Peninsula (Plecoptera: Perlodidae),Zenodo,2012,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 1-5. Perlodes floridus floridus sp. n. (1-3, 4a, 5a) and P. floridus peloponnesiacus ssp. n. (4b, 5b) adults. 1. Female head and pronotum, dorsal view. 2. Female subgenital plate, ventral view. 3. Male paraproct, a: ventral view, b: ¾ ventrolateral view. 4a-b. Male paraprocts, ventral view. 5ab. Male paraprocts, ¾ ventrolateral view. Not to scale.",mds,True,findable,0,0,4,0,0,2021-05-12T18:31:45.000Z,2021-05-12T18:31:46.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Perlodes","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Perlodes'}]",,
+10.5281/zenodo.4632426,drguigui/ATMOCIAD: The ATMOCIAD database,Zenodo,2021,,Software,Open Access,"AtMoCiad (Atomic and Molecular Cross section for Ionization and Aurora Database is a database dedicated, as indicated by its name, to the cross sections of ionization, excitation, and dissociation of atoms and molecules. The main objective is to have a comprehensive database to study aurora and airglow, hence the first species included are the main components of solar system planetary atmospheres.",mds,True,findable,0,0,1,0,0,2021-03-23T22:38:40.000Z,2021-03-23T22:38:41.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4286111,"Sliding velocity, water discharge and basal shear stress time series at Argentière Glacier",Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The data set contains all data presented in: Gimbert, F., Gilbert, A., Gagliardini, O., Vincent, C., & Moreau, L. (2021). Do Existing Theories Explain Seasonal to Multi-Decadal Changes in Glacier Basal Sliding Speed? <em>Geophysical Research Letters</em>, <em>48</em>(15), e2021GL092858. https://doi.org/10.1029/2021GL092858 and also in: Gilbert, A., Gimbert, F., Thøgersen, K., Schuler, T. V., & Kääb, A. (2022). A Consistent Framework for Coupling Basal Friction with Subglacial Hydrology on Hard-bedded Glaciers. <em>Geophysical Research Letters</em>, <em>49</em>, e2021GL097507. https://doi.org/10.1029/2021GL097507 Files Description: ==================================<br> SlidingVelocities1989_2019.csv :<br> ================================== Contains daily values of recorded sliding velocities at the wheel. Column 1 = Date<br> Column 2 = Daily Values (cm/day) ================================<br> BasalShearStress1980_2019.csv :<br> ================================ Contains daily values of inferred basal shear stress at the wheel. Column 1 = Date<br> Column 2 = Daily Values (MPa) ================================<br> WaterDischarge1985_2019.csv :<br> ================================ Contains daily values of recorded water discharge at the glacier outlet Column 1 = Date<br> Column 2 = Daily Values (m3/s)",mds,True,findable,0,0,0,0,0,2020-11-23T11:05:16.000Z,2020-11-23T11:05:16.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6985564,Observation of non-Hermitian topology in a multi-terminal quantum Hall device,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",This repository contains our measurements and the codes used to produce the figures of the manuscript/supplementary information.,mds,True,findable,0,0,0,0,0,2022-08-12T15:48:48.000Z,2022-08-12T15:48:49.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6974319,Dataset - Warming-induced monsoon precipitation phase change intensifies glacier mass loss in the southeastern Tibetan Plateau,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Materials and data results needed to reproduce the findings of the study published in (PNAS) Proceedings of the National Academy of Sciences of the United States of America: ""<em>Warming-induced monsoon precipitation phase change intensifies glacier mass loss in the southeastern Tibetan Plateau""</em>. A. Jouberton, T. E. Shaw, E. Miles, M. McCarthy, S. Fugger, S. Ren, A. Dehecq, W. Yang and F. Pellicciotti It includes the meteorological forcing time-series, an exhaustive list of the model parameters, the outputs of TOPKAPI-ETH, and Matlab scripts allowing to reproduce the figures and compute the numbers given in the main manuscript as well as in the Supplementary Information. --------------- <strong>Contents</strong> : Folder : ""Matlab_scripts""<br> '<strong>Climate_import.m</strong>' : Organizes meteorological forcing and generates Figure S9<br> <strong> 'TOPKAPI_result_import.m' :</strong> Imports TOPKAPI's reference run outputs and prepares them for analysis<br> <strong> 'Experiment_analysis.m' : </strong>Analyses the results of the forcing experiments, generates Figure 4 and Figure S25<br> <strong> 'Main_text_results.m' : </strong>Analyses the results of TOPKAPI's reference runs, generates Figure 1D, FIgure 2 and Figure 3<br> <strong> 'TOPKAPI_validation.m' : </strong>Compares TOPKAPI's reference run results with several validation datasets, generates the figures and performance metrics of the model calibration and validation procedure.<br> <strong> 'Parlung_albedo_regional_analysis.m'</strong>: Computes the mean glacier albedo per elevation band for each glacier within the Southeastern Tibean Plateau and compares it to the albedo of Parlung No.4 glacier.<br> <strong> 'Parlung_GMB_regional_analysis.m'</strong>: Computes the mean glacier mass balance per elevation band for each glacier within the Southeastern Tibean Plateau and compares it to the glacier mass balance of Parlung No.4 glacier.<br> <strong> 'Precipitation_phase_sensitivity_analysis.m'</strong>: Performs a sensitivity analysis on the simulated monsoon snowfall ratio per elevation band and on the attribution of glacier mass loss to precipitation<br> phase change using Monte Carlo simulations.<br> <strong> 'TOPKAPI_MODIS_validation.m'</strong>: Compares the snow cover at Parlung No.4 catchment simulated by TOPKAPI-ETH and observed by MODIS, generates Figure S19. Folder : ""Remote_sensing"" : Sub-Folder: 'Hugonnet' = Glacier mass balance averaged over 2000-2020 covering the Southeastern Tibetan Plateau, 100m resolution, derived from Hugonnet et al. 2021<br> Sub-Folder: 'MODIS' = contains the snow cover at Parlung No.4 derived from the daily product MOD10A1 version 61, for the period 2000-2018<br> Sub-Folder: 'Regional_glacier_albedo' = contains the annual glacier surface albedo from 2000 to 2020, covering the Southeastern Tibetan Plateau, 500m resolution.<br> Sub-Folder: 'Shapefiles' = contains the Parlung No.4 glacier outlines in 1974 and from the RGI 6.0<br> <strong>'ASTER_Nyainqentanglha_15m_utm.tif'</strong> = ASTER Digital elevation model at 15m resolution covering the Southeastern Tibetan Plateau<br> <strong> 'parlung_mask_1974.mat' </strong>= Parlung No.4 glacier mask as a matlab file<br> <strong> 'dh_ASTER_SRTM_30m.tif' </strong>= Mean elevation change rate from 2000 to 2016 at Parlung No.4 catchment.<br> <strong> 'Geodetic_map.mat'</strong> = Elevation change maps for the periods 1974-2000 and 1974-2014, as a matlab file<br> <strong> 'GMB_geodetic.mat' </strong>= Geodetic mass balance (glacier-wide mean and profile per elevation band) used in Figure S13<br> <strong> 'parlung_30m_catchment_mask.tif'</strong> = Parlung No.4 catchment mask<br> <strong>'parlung_1974_30m_dem.tif' </strong>= DEM of Parlung No.4 catchment, 30 m resolution<br> <strong> 'parlung_1974_30m_gla.tif'</strong> = Parlung No. 4 glacier mask, 30m resolution<br> <strong>'parlung_1974_30m_glah.tif' </strong>= Reconstructed ice thickness of 1975 for Parlung No.4 glacier<br> <strong>'parlung_1974_2000_diff_24m.tif' </strong>= Elevation change from DEM differencing at Parlung No.4 catchment for 1974-2000<br> <strong> 'parlung_1974_2014_diff_24m.tif' </strong>= Elevation change from DEM differencing at Parlung No.4 catchment for 1974-2014<br> <strong> 'Parlung_1974_bedrock_dem_30m.tif' </strong>= Bedrock surface digital elevation model of the catchment, 30m spatial resolution<br> <strong>'RGI_KangriKarpo_100m_utm_id.tif' </strong>= Glacier mask covering the Kangri Karpo mountain region, 100m resolution, with glacier IDs in the attribute table<br> <strong> 'RGI_Nyainqentanglha_100m_utm_id.tif' </strong>= = Glacier mask covering the Southeastern Tibetan Plateau, 100m resolution, with glacier IDs in the attribute table Folder : ""TOPKAPI_forcing"" :<br> <strong> CCT_AWS4600_extended.csv : </strong>Hourly cloud cover transmissivity from 1975 to 2018 reconstructed at AWSoff location <br> <strong> Climate.mat : </strong>Organizes meteorological forcings, output from the matlab script '<strong>Climate_import.m</strong>'<br> <strong> LR_AWS4600_extended.csv :</strong> Hourly temperature lapse-rates from 1975 to 2018 reconstructed at AWSoff location <br> <strong> Precipitation_AWS4600_extended.csv : </strong>Hourly precipitation from 1975 to 2018 reconstructed at AWSoff location <br> <strong> Ta_AWS4600_extended.csv :</strong> Hourly air temperature from 1975 to 2018 reconstructed at AWSoff location<br> Sub-Folder: 'National_meteorological_stations' = Contains the daily air temperature and precipitation measured at the national meteorological stations of Bomi, Zayu, Zuogong and Basu<br> Sub-Folder: 'Reference_run_inputs' = Contains the input files necessary to run TOPKAPI-ETH to obtain the outputs from which the results of this study are based on. Folder : ""TOPKAPI_output"":<br> <strong> </strong> Sub-Folder : ""Forcing experiment"" = organized TOPKAPI outputs from the forcing experiment<br> Sub-Folder :"" Reference_run_outputs"" = raw TOPKAPI outputs from the reference run (catchment average, spatial and grid cells)<br> Sub-Folder : ""Reference_run_results"" = organized TOPKAPI outputs from the reference run<br> Sub-Folder : ""Snow_ice_cover"" = contains TOPKAPI-ETH derived snow cover maps (daily map outputs)<br> Sub-Folder : ""Regional_analysis"" =<br> 'Alb'= Table containing the mean glacier albedo (2000-2020) per normalized elevation band, for each glacier in the SETP (RGI 6.0)<br> 'GMB'= Table containing the mean glacier mass balance (2000-2020) per normalized elevation band, for each glacier in the SETP (RGI 6.0)<br> 'Hypso_xxm' = Table containing the percentage of glacier area per normalized elevation band, for each glacier in the SETP (RGI 6.0), resolution of 100/500m<br> 'NormEl_100m' = Table containing the elevation per normalized elevation band, for each glacier in the SETP (RGI 6.0), resolution of 100/500m<br> Sub-Folder : ""Semi_distributed_outputs"" = Precipitation phase and amounts resulting from TOPKAPI-ETH simulation per elevation band, for the reference run and for the Monte Carlo sensitivity analysis Folder : ""Validation_data""<br> <strong> 'topkapi.out_reference_discharge2016' </strong>= <strong> </strong>raw TOPKAPI outputs run in 2016 with AWSoff air temperature<br> <strong> </strong><strong> 'master_file_parlung.mat' </strong>=<strong> </strong>matlab structure containing AWS measurements, necessary for running <strong>'TOPKAPI_validation.m'</strong><br> <strong> 'Qdigit.mat' </strong>= Discharge measured at the Parlung No.4 glacier outlet, from Li et al., (2016)<br> <strong> 'Parlung_Q_1970.mat'</strong> = 'Discharge time-series used to run TOPKAPI-ETH (goes back to 1975, but filled with 0 when no measurements are available) In order to run the Matlab scripts, it is recommended to download all folders and gather them into the same folder. Any request about data or questions on how to run the Matlab scripts can be asked to the author of the paper (at achille.jouberton@wsl.ch).",mds,True,findable,0,0,0,0,0,2022-08-08T21:27:07.000Z,2022-08-08T21:27:07.000Z,cern.zenodo,cern,"climate change, glaciers, hydrological modeling, precipitation phase change","[{'subject': 'climate change, glaciers, hydrological modeling, precipitation phase change'}]",,
+10.34847/nkl.2404plkh,Parcourir la ville : un jeu d'enfants,NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,fr,Other,,"Livret réalisé pour le Forum Mobi'Kids intitulé « l’enfant autonome au défi de la ville » (juillet 2022, Rennes) dans le cadre de la recherche Mobikids - Le rôle des cultures éducatives urbaines (CEU) dans l'évolution des mobilités quotidiennes et des contextes de vie des enfants. Collecte et analyse de traces géolocalisées et enrichies sémantiquement 2017-2021 (ANR-16-CE22-0009).
+Equipe :
+Responsable scientifique. DEPEAU Sandrine
+Laboratoires, entreprises impliqués : ESO-Rennes, UMR Pacte, UMR AAU, LIFAT, PME Alkante, PME RF Track,
+Pour l'équipe AAU-CRESSON : THIBAUD Jean-Paul, MANOLA Théa, MCOISANS juL, AUDAS Nathalie
+
+Cette fiction s’inspire de l’enquête menée auprès des enfants ayant réalisé des parcours commentés entre l’école et le domicile. Les deux personnages ainsi créés, Camille et Sacha, évoquent des moments de vie, des anecdotes, des manières de faire, des formes d’attention, repérés chez différents enfants et sont racontés comme une histoire pour faire ressortir sous une forme originale les principales tendances et résultats obtenus au cours de cette recherche.
+
+Deux enfants racontent leurs déplacements quotidiens entre l’école et le domicile. A travers leurs échanges, nous découvrons la ville à hauteur d’enfants au travers des espaces parcourus, seul.e ou accompagné.e. Ils évoquent ce qu’ils aiment faire ou non sur ce trajet, ce dont ils ont peur, ce qui les attire ou les repousse. Apparaissent aussi les recommandations et autres conseils ou avertissements parentaux. Par le rythme de leurs déplacements, leurs choix de cheminements, le besoin d’être et de jouer avec les copains/copines, leurs descriptions des environnements traversés, se dessinent les expériences urbaines enfantines.",api,True,findable,0,0,0,0,1,2023-03-10T14:31:23.000Z,2023-03-10T14:31:23.000Z,inist.humanum,jbru,"mobilité quotidienne,enfant,autonomie,récit personnel,amitié--chez l'enfant,sens et sensations,perception du risque,Villes -- Sons, environnement sonore,mobilité spatiale,itinéraire,matériaux de terrain éditorialisés,récit-fiction","[{'lang': 'fr', 'subject': 'mobilité quotidienne'}, {'lang': 'fr', 'subject': 'enfant'}, {'lang': 'fr', 'subject': 'autonomie'}, {'lang': 'fr', 'subject': 'récit personnel'}, {'lang': 'fr', 'subject': ""amitié--chez l'enfant""}, {'lang': 'fr', 'subject': 'sens et sensations'}, {'lang': 'fr', 'subject': 'perception du risque'}, {'lang': 'fr', 'subject': 'Villes -- Sons, environnement sonore'}, {'lang': 'fr', 'subject': 'mobilité spatiale'}, {'lang': 'fr', 'subject': 'itinéraire'}, {'lang': 'fr', 'subject': 'matériaux de terrain éditorialisés'}, {'lang': 'fr', 'subject': 'récit-fiction'}]",['6347927 Bytes'],['application/pdf']
+10.5281/zenodo.5578340,Salem simulator 2.0,Zenodo,2021,en,Software,"GNU Library General Public License v2.1 or later,Open Access","Installer for the Salem simulator 2.0, including the source code. This version corresponds to the release r17186 on the Capsis repository (http://capsis.cirad.fr/capsis/home). Java Runtime Environment 1.8.xxx is required to run the simulator. Salem predicts the dynamics of pure and mixed even-aged forest stands and makes it possible to simulate management operations. Its purpose is to be a decision support tool for forest managers and stakeholders as well as for policy makers. It is also designed to conduct virtual experiments and help answer research questions. Salem is essentially calibrated with French National Forest Inventory for 12 common tree species of Eupore. The mixture effect on species growth is assessed for 24 pairs of these species. Salem runs on Windows, Linux, or Mac. Its user-friendly Graphical User Interface makes it easy to use for non-modellers.",mds,True,findable,0,0,0,0,0,2021-10-19T12:00:16.000Z,2021-10-19T12:00:18.000Z,cern.zenodo,cern,"Forest,Simulator,Growth,Mixture effect,Foret management,Silviculture","[{'subject': 'Forest'}, {'subject': 'Simulator'}, {'subject': 'Growth'}, {'subject': 'Mixture effect'}, {'subject': 'Foret management'}, {'subject': 'Silviculture'}]",,
+10.60662/re4y-6g57,Application d’un réseau de neurones artificiels auto-encodeur pour la détection de bourrages sur tapis convoyeurs en centre de tri de déchets,CIGI QUALITA MOSIM 2023,2023,,ConferencePaper,,,fabricaForm,True,findable,0,0,0,0,0,2023-09-01T19:18:09.000Z,2023-09-01T19:18:09.000Z,uqtr.mesxqq,uqtr,,,,
+10.5061/dryad.2j5s7,Data from: Are variations of direct and indirect plant interactions along a climatic gradient dependent on species' strategies? An experiment on tree seedlings,Dryad,2015,en,Dataset,Creative Commons Zero v1.0 Universal,"Investigating how interactions among plants depend on environmental conditions is key to understand and predict plant communities’ response to climate change. However, while many studies have shown how direct interactions change along climatic gradients, indirect interactions have received far less attention. In this study, we aim at contributing to a more complete understanding of how biotic interactions are modulated by climatic conditions. We investigated both direct and indirect effects of adult tree canopy and ground vegetation on seedling growth and survival in five tree species in the French Alps. To explore the effect of environmental conditions, the experiment was carried out at 10 sites along a climatic gradient closely related to temperature. While seedling growth was little affected by direct and indirect interactions, seedling survival showed significant patterns across multiple species. Ground vegetation had a strong direct competitive effect on seedling survival under warmer conditions. This effect decreased or shifted to facilitation at lower temperatures. While the confidence intervals were wider for the effect of adult canopy, it displayed the same pattern. The monitoring of micro-environmental conditions revealed that competition by ground vegetation in warmer sites could be related to reduced water availability; and weak facilitation by adult canopy in colder sites to protection against frost. For a cold-intolerant and shade-tolerant species (Fagus sylvatica), adult canopy indirectly facilitated seedling survival by suppressing ground vegetation at high temperature sites. The other more cold tolerant species did not show this indirect effect (Pinus uncinata, Larix decidua and Abies alba). Our results support the widely observed pattern of stronger direct competition in more productive climates. However, for shade tolerant species, the effect of direct competition may be buffered by tree canopies reducing the competition of ground vegetation, resulting in an opposite trend for indirect interactions across the climatic gradient.",mds,True,findable,303,37,1,1,0,2015-08-11T14:26:07.000Z,2015-08-11T14:26:10.000Z,dryad.dryad,dryad,"Abies alba,Larix decidua,Pinus uncinata,Quercus petraea,Fagus sylvatica","[{'subject': 'Abies alba'}, {'subject': 'Larix decidua'}, {'subject': 'Pinus uncinata'}, {'subject': 'Quercus petraea'}, {'subject': 'Fagus sylvatica'}]",['4698866 bytes'],
+10.5281/zenodo.10055461,Mont Blanc ice core data for NH3 source investigation in Europe,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,Dataset to interpret the δ15N(NH4+) in a Mont Blanc ice core,api,True,findable,0,0,0,0,0,2023-11-03T08:48:44.000Z,2023-11-03T08:48:44.000Z,cern.zenodo,cern,,,,
+10.57745/z3bg2u,Electrical measurement of the spin Hall effect isotropy in ferromagnets with strong spin-orbit interactions,Recherche Data Gouv,2023,,Dataset,,"Data set of the paper : Electrical measurement of the spin Hall effect isotropy in ferromagnets with strong spin-orbit interactions. This includes anisotropic magnetoresistance, spin signal and spin Hall effect, along with their temperature dependance, measured on NiCu and NiPd alloys.",mds,True,findable,47,0,0,0,0,2022-12-08T16:00:42.000Z,2023-03-14T13:34:43.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.4761345,"Fig. 78 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 78. Dictyogenus fontium species complex, adult female habitus. Inner-alpine upper Isère Valley. Col de l'Iseran, Savoie dpt, France. Photo A. Ruffoni.",mds,True,findable,0,0,2,0,0,2021-05-14T07:51:03.000Z,2021-05-14T07:51:04.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.45044,"Moca: An Efficient Memory Trace Collection System, Preliminary Experiments Results Analysis",Zenodo,2016,,Dataset,"Creative Commons Zero - CC0 1.0,Open Access","Every files required to replay the statistic analysis of the preliminary experiments for the artice: ""Moca: An efficient Memory trace collection system"" submitted at HPDC",,True,findable,0,0,0,0,0,2016-01-20T17:02:03.000Z,2016-01-20T17:02:04.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3873216,Raw diffraction data for [NiFeSe] hydrogenase G491A variant pressurized with Kr gas - dataset G491A-Kr,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","Diffraction data measured at ESRF beamline ID30A-3 on September 27, 2017.",mds,True,findable,4,0,0,0,0,2020-06-02T15:01:13.000Z,2020-06-02T15:01:14.000Z,cern.zenodo,cern,"Hydrogenase,Selenium,gas channels,high-pressure derivatization","[{'subject': 'Hydrogenase'}, {'subject': 'Selenium'}, {'subject': 'gas channels'}, {'subject': 'high-pressure derivatization'}]",,
+10.5281/zenodo.8104455,How Absence Seizures Impair Sensory Perception: Insights from Awake fMRI and Simulation Studies in Rats,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains measured and simulated data for the manuscript titled ""How Absence Seizures Impair Sensory Perception: Insights from Awake fMRI and Simulation Studies in Rats"" by Stenroos P. et al. Electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data was recorded simultaneously from awake GAERS; a rat model of absence epilepsy. Visual and whisker stimulation was experimentally applied, and visual stimulation was simulated during interictal and ictal states and whole brain hemodynamic and neural responsiveness was compared between states.",mds,True,findable,0,0,0,0,0,2023-07-01T20:11:53.000Z,2023-07-01T20:11:53.000Z,cern.zenodo,cern,"fMRI,EEG,AdEx mean-field model,GAERS,Sensory perception","[{'subject': 'fMRI'}, {'subject': 'EEG'}, {'subject': 'AdEx mean-field model'}, {'subject': 'GAERS'}, {'subject': 'Sensory perception'}]",,
+10.5281/zenodo.5835168,Ensemble statistics for modelled Eddy Kinetic Energy in the Southern Ocean,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains surface eddy kinetic energy over the Southern Ocean region, sourced from a 50-member ensemble of 0.25° ocean model simulations. It is used in the paper ""Circumpolar variations in the chaotic nature of Southern Ocean eddy dynamics"" published in Journal of Geophysical Research - Oceans. This dataset has been computed from the OceaniC Chaos – ImPacts, strUcture, predicTability (OCCIPUT) global ocean/sea-ice ensemble simulation. It is composed of 50 members with a horizontal resolution of 1/4° and 75 geopotential levels (Bessières et al., 2017, Penduff et al., 2014). The numerical configuration is based on the version 3.5 of the NEMO model (Madec, 2008). The 50 members were started on January 1st 1960 from a common 21-year spinup. A small stochastic perturbation is applied to the equation of state of sea water (as in Brankart, 2013) within each member during 1960, then switched off during the rest of the simulation. This 1-year perturbation generates an ensemble spread which grows and saturates after a few months up to a few years depending on the region. The 50 members are driven through bulk formulae during the whole 1960-2015 simulation by the same realistic 6-hourly atmospheric forcing (Drakkar Forcing Set DFS5.2, Dussin et al., 2016) derived from ERA interim atmospheric reanalysis. Data is for the period 1979-2015. The sea level anomaly is found according to Close et al (2020) and converted into surface geostrophic velocity anomaly using the geostrophic relation. This velocity field is then used to calculate the eddy kinetic energy (EKE). Data is averaged over calendar month, and restricted to the latitude range 40°-60°S. A full description of this process is included in the companion paper. The dataset includes EKE files (eke_0??.nc), with monthy EKE saved for the period 1979-2015 for each ensemble member, and a single file (tau.nc) for the monthly-averaged wind stress over the same period.",mds,True,findable,0,0,0,0,0,2022-01-11T07:44:36.000Z,2022-01-11T07:44:37.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4760467,"Figs. 2-4 in Two New Alpine Leuctra In The L. Braueri Species Group (Plecoptera, Leuctridae)",Zenodo,2011,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 2-4. Leuctra muranyii sp. n.: male abdominal tip in dorsal view (2), male genitalia in ventral view (3), female subgenital plate in ventral view (4).",mds,True,findable,0,0,2,0,0,2021-05-14T05:22:49.000Z,2021-05-14T05:22:50.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.6084/m9.figshare.21341628.v1,Additional file 1 of Expiratory high-frequency percussive ventilation: a novel concept for improving gas exchange,figshare,2022,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Details of the simulation study and additional data for respiratory mechanics.,mds,True,findable,0,0,0,0,0,2022-10-16T03:12:48.000Z,2022-10-16T03:12:49.000Z,figshare.ars,otjm,"Biophysics,Space Science,Medicine,Physiology,FOS: Biological sciences,Biotechnology,Cancer","[{'subject': 'Biophysics'}, {'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Biotechnology'}, {'subject': 'Cancer'}]",['86600 Bytes'],
+10.57745/69unam,Tracking of Gag-mCherry spots,Recherche Data Gouv,2023,,Dataset,,"Gag-mcherry spot tracking in individual HeLa CCL2 cells or HeLA Kyoto BST2- cells. The cells were transfected by Gag/Gag-mCherry alone or Gag/Gag-mCherry along with Vps4A E228Q, CHMP4B-NS3-green, and CHMP2A-NS3-green, and then treated or not by Glecaprevir, as indicated.",mds,True,findable,39,1,0,0,0,2023-11-20T15:36:29.000Z,2023-11-20T15:56:17.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.3966773,Data for: Historical earthquake scenarios for the middle strand of the North Anatolian Fault deduced from archeo-damage inventory and building deformation modeling,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset is associated to the article ""Historical earthquake scenarios for the middle strand of the North Anatolian Fault deduced from archeo-damage inventory and building deformation modeling "" published in Seismological Research Letters (link). It includes the following: The annotated photographs of the EAE (Earthquake Archeological Effects) inventoried in Iznik (""EAE_xxx.pdf""). The 3D displacement signals used as input for obelisk modeling (""Displacement_xxx""). The output obelisk displacement curves and final block shift values relative to base (""Obelisk_block_motion.pdf"").",mds,True,findable,0,0,1,0,0,2020-07-30T07:26:24.000Z,2020-07-30T07:26:27.000Z,cern.zenodo,cern,"earthquakes,North Anatolian fault,archeoseismology,historical seismicity,vulnerability","[{'subject': 'earthquakes'}, {'subject': 'North Anatolian fault'}, {'subject': 'archeoseismology'}, {'subject': 'historical seismicity'}, {'subject': 'vulnerability'}]",,
+10.5281/zenodo.10204743,"Supplementary material to ""SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme"" : Pleiades snow depth maps analysis",Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"This Folder contains :
+Â Â Â - necessary codes to reprduce Fig. 5, 12 and 13 of the third version of the submitted manuscript SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme""
+Â Â Â - necessary data to run these codes, including extracts of simulation outputs
+Â Â - A readme.txt which explains how to run everything
+Â ",api,True,findable,0,0,0,0,0,2023-11-24T18:50:44.000Z,2023-11-24T18:50:45.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6860555,JASPAR TFBS LOLA databases - Part 2,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the second part of the JASPAR 2022 LOLA databases used by the JASPAR TFBS enrichment tool. We provide the LOLA databases for the human (hg38) JASPAR 2022 TFBS sets as compressed directories containing a set of .RDS R objects. Due to file sizes, we had to split the repository into two different parts. Part 1 of the repository containing the rest of databases can be found here.",mds,True,findable,0,0,0,0,0,2022-07-25T12:25:34.000Z,2022-07-25T12:25:35.000Z,cern.zenodo,cern,,,,
+10.57745/hzdptt,Spin-orbit readout using thin films of topological insulator Sb2Te3 deposited by industrial magnetron sputtering,Recherche Data Gouv,2023,,Dataset,,"Data set of the paper : Spin-orbit readout using thin films of topological insulator Sb2Te3 deposited by industrial magnetron sputtering. This includes Sheet resistance versus temperature, and Hall effect and spin signal with their temperature dependance, measured on SbTe based devices and thin film.",mds,True,findable,28,0,0,0,0,2023-06-20T08:46:44.000Z,2023-07-25T09:15:57.000Z,rdg.prod,rdg,,,,
+10.7280/d1r085,"Impact of calving dynamics on Kangilernata Sermia, Greenland",Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Iceberg calving is a major component of glacier mass ablation that is not well understood due to a lack of detailed temporal and spatial observations. Here, we measure glacier speed and surface elevation at 3-minute interval, 5 meter spacing, using a portable radar interferometer at Kangilernata Sermia, Greenland in July 2016. We detect a 20% diurnal variation in glacier speed peaking at high spring tide when basal drag is high and lowering at neap tide. We find no speed up from ice shedding off the calving face or the detachment of floating ice blocks, but observe a 30% speedup that persist for weeks when calving removes grounded ice blocks. Within one ice thickness from the calving front, we detect strain rates 2 to 3 times larger than observable from satellite data, which has implications for studying calving processes.",mds,True,findable,178,30,0,0,0,2020-02-05T17:55:12.000Z,2020-02-05T17:55:13.000Z,dryad.dryad,dryad,"Interferometry,Glaciology,Iceberg,Radar remote sensing","[{'subject': 'Interferometry'}, {'subject': 'Glaciology', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Iceberg'}, {'subject': 'Radar remote sensing'}]",['12310648668 bytes'],
+10.5281/zenodo.4760489,"Figs. 13-14 in Contribution To The Knowledge Of The Moroccan High And Middle Atlas Stoneflies (Plecoptera, Insecta)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 13-14. Middle-Atlas, SE Khenifra, Sidi Yahia Ousaad brook, tributary of Oum er Rbia River. 13: main brook and lateral springs on the left side, 14: detail of one lateral spring. In the lateral springs both Amphinemura tiernodefigueroai sp. n. and Protonemura dakkii occur.",mds,True,findable,0,0,4,0,0,2021-05-14T05:26:52.000Z,2021-05-14T05:26:53.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Amphinemura,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Amphinemura'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.10204837,"I-MAESTRO data: 42 million trees from three large European landscapes in France, Poland and Slovenia",Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Here we present three datasets describing three large European landscapes in France (Bauges Geopark - 89,000 ha), Poland (Milicz forest district - 21,000 ha) and Slovenia (Snežnik forest - 4,700 ha) down to the tree level. Individual trees were generated combining inventory plot data, vegetation maps and Airborne Laser Scanning (ALS) data. Together, these landscapes (hereafter virtual landscapes) cover more than 100,000 ha including about 64,000 ha of forest and consist of more than 42 million trees of 51 different species.
+For each virtual landscape we provide a table (in .csv format) with the following columns:- cellID25: the unique ID of each 25x25 m² cell- sp: species latin names- n: number of trees. n is an integer >= 1, meaning that a specific set of species ""sp"", diameter ""dbh"" and height ""h"" can be present multiple times in a cell.- dbh: tree diameter at breast height (cm)- h: tree height (m)
+We also provide, for each virtual landscape, a raster (in .asc format) with the cell IDs (cellID25) which makes data spatialisation possible. The coordinate reference systems are EPSG: 2154 for the Bauges, EPSG: 2180 for Milicz, and EPSG: 3912 for Sneznik.
+The v2.0.0 presents the algorithm in its final state.
+Finally, we provide a proof of how our algorithm makes it possible to reach the total BA and the BA proportion of broadleaf trees provided by the ALS mapping using the alpha correction coefficient and how it maintains the Dg ratios observed on the field plots between the different species (see algorithm presented in the associated Open Research Europe article).
+Below is an example of R code that opens the datasets and creates a tree density map.
+------------------------------------------------------------# load package
+library(terra)
+library(dplyr)
+Â
+# set work directory
+setwd()        # define path to the I-MAESTRO_data folder
+Â
+# load tree data
+tree <- read.csv2('./sneznik/sneznik_trees.csv', sep = ',')
+Â
+# load spatial data
+cellID <- rast('./sneznik/sneznik_cellID25.asc')
+Â
+# set coordinate reference system
+# Bauges:
+# crs(cellID) <- ""epsg:2154""
+# Milicz:
+# crs(cellID) <- ""epsg:2180""
+# Sneznik:
+# crs(cellID) <- ""epsg:3912""
+Â
+# convert raster into dataframe
+cellIDdf <- as.data.frame(cellID)
+colnames(cellIDdf) <- 'cellID25'
+Â
+# calculate tree density from tree dataframe
+dens <- tree %>% group_by(cellID25) %>% summarise(n = sum(n))
+Â
+# merge the two dataframes
+dens <- left_join(cellIDdf, dens, join_by(cellID25))
+Â
+# add density to raster
+cellID$dens <- dens$n
+Â
+# plot density map
+plot(cellID$dens)",api,True,findable,0,0,0,0,0,2023-11-24T19:56:53.000Z,2023-11-24T19:56:53.000Z,cern.zenodo,cern,"forest,inventory,landscape,tree-level,airborne laser scanning,downscaling","[{'subject': 'forest'}, {'subject': 'inventory'}, {'subject': 'landscape'}, {'subject': 'tree-level'}, {'subject': 'airborne laser scanning'}, {'subject': 'downscaling'}]",,
+10.5281/zenodo.8116463,"Dataset, setups and scripts to numerically reproduce the breaching process",Zenodo,2023,,Dataset,"Creative Commons Attribution 2.0 Generic,Open Access","This dataset is part of the article: Numerical investigation of mode failures in submerged granular columns - E. P. Montellà , J. Chauchat, C. Bonamy, D. Weij, G. H. Keetels and T. J. Hsu. This file contains the numerical results obtained with SedFoam to model the breaching experiments of Weij (2020) (full thesis available at https://pure.tudelft.nl/ws/portalfiles/portal/84166231/2020_03_05_thesis_dweij.pdf ). The folder and files are set to reproduce the Experiments 8 and 16 in case the user wants to re-launch the numerical simulations. These simulations can be executed with ./Allrun. Two Python scripts are available for post-processing. The Python scripts require the fluidfoam package to be installed and it is freely available at https://github.com/fluiddyn/fluidfoam .",mds,True,findable,0,0,0,0,0,2023-07-05T10:23:18.000Z,2023-07-05T10:23:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8252180,"Multi-decadal analysis of past winter temperature, precipitation and snow cover data in the European Alps from reanalyses, climate models and observational datasets",Zenodo,2023,,Software,Open Access,"Source code for producing figures of the article : Multi-decadal analysis of past winter temperature, precipitation and snow cover data in the European Alps from reanalyses, climate models and observational datasets, Monteiro and Morin 2023",mds,True,findable,0,0,0,1,0,2023-08-16T10:55:53.000Z,2023-08-16T10:55:54.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7108355,QENS spectra of myoglobin in solution to be used with the analysis codes deposited under 10.5281/zenodo.7058345,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Quasielastic Neutron Scattering spectra of myoglobin in solution recorded on the IN5 spectrometer at the Institut Laue-Langevin in Grenoble, France. The data sets are to be used with the analysis codes deposited under DOI:10.5281/zenodo.7058345, which are in turn related to the publication A. Hassani, A. M. Stadler, and G.R. Kneller, Quasi-analytical resolution-correction of elastic neutron scattering from proteins, to appear in the Journal of Chemical Physics (DOI:10.1063/5.0103960). The data can be freely used, citing properly the reference concerning the original data, A. M. Stadler, F. Demmel, J. Ollivier, and T. Seydel, Picosecond to Nanosecond Dynamics Provide a Source of Conformational Entropy for Protein Folding. Phys. Chem. Chem. Phys., 18(31):21527–21538, 2016 (DOI: 10.1039/c6cp04146a).",mds,True,findable,0,0,0,1,0,2022-09-23T15:03:44.000Z,2022-09-23T15:03:45.000Z,cern.zenodo,cern,"Quasielastic neutron scattering, elastic neutron scattering, instrumental resolution correction","[{'subject': 'Quasielastic neutron scattering, elastic neutron scattering, instrumental resolution correction'}]",,
+10.5281/zenodo.5024655,Grid'5000 performance data,Zenodo,2021,,Dataset,"Open Data Commons Open Database License v1.0,Open Access",Collection of performance data on Grid'5000,mds,True,findable,0,0,0,0,0,2021-06-24T12:36:59.000Z,2021-06-24T12:37:00.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4310798,Amundsen Sea future MAR simulations forced by the CMIP5 multi-model mean,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Amundsen Sea future MAR simulation forced by the CMIP5 multi-model mean (RCP8.5)</strong> This future simulation is fully described in the following article: Donat-Magnin, M., Jourdain, N. C., Kittel, C., Agosta, C., Amory, C., Gallée, H., Krinner, G., and Chekki, M. Future surface mass balance and surface melt in the Amundsen sector of the West Antarctic Ice Sheet. <em>The Cryosphere</em>. The future is derived from the CMIP5 multi-model mean under the RCP8.5 scenario and covers the 2079-2108 period. The corresponding present-day simulation is available on http://doi.org/10.5281/zenodo.4308510 and was thoroughly evaluated in the following TC paper: https://doi.org/10.5194/tc-14-229-2020 See netcdf metadata for more information. Note that what is called runoff in the outputs is not actually a runoff (into the ocean) but more the net production of liquid water at the surface (which can either form ponds or flow into the ocean). Monthly files provided on MAR grid (see MAR_grid10km.nc). We also provide climatological (2079-2108 average) surface mass balance (SMB), surface melt rates and net liquid water production (""runoff"") on a standard 8km WGS84 stereographic grid (see files ending as mean_polar_stereo.nc). Daily snowfall and surface melt rates are provided in ICE*nc.<br> <br> The interpolation to the stereographic grid is done using interpolate_to_std_polar_stereographic.f90. The fields are extrapolated to the ocean grid points so that ice sheet models with various ice-shelf extent can use this dataset. To extrapolate the SMB and surface melt projections to other warming scenarios or period, see eq. (2,3) in Donat-Magnin et al. The following variables are provided: CC Cloud Cover LHF Latent Heat Flux LWD Long Wave Downward LWU Long Wave Upward QQp Specific Humidity (pressure levels) QQz Specific Humidity (height levels) RH Relative Humidity SHF Sensible Heat Flux SIC Sea ice cover SP Surface Pressure ST Surface Temperature SWD Short Wave Downward SWU Short Wave Upward TI1 Ice/Snow Temperature (snow-layer levels) TTz Temperature (height levels) UUp x-Wind Speed component (pressure levels) UUz x-Wind Speed component (height levels) VVp y-Wind Speed component (pressure levels) VVz y-Wind Speed component (height levels) UVp Horizontal Wind Speed (pressure levels) UVz Horizontal Wind Speed (height levels) ZZp Geopotential Height (pressure levels) mlt Surface melt rate rfz Refreezing rate rnf Rainfall rof ""Runoff"" (i.e. net production of surface liquid water) sbl Sublimation smb Surface Mass Balance snf Snowfall",mds,True,findable,0,0,0,0,0,2020-12-08T06:58:00.000Z,2020-12-08T06:58:01.000Z,cern.zenodo,cern,"MAR,Amundsen Sea,surface mass balance,surface melting,projections,CMIP5,RCP8.5","[{'subject': 'MAR'}, {'subject': 'Amundsen Sea'}, {'subject': 'surface mass balance'}, {'subject': 'surface melting'}, {'subject': 'projections'}, {'subject': 'CMIP5'}, {'subject': 'RCP8.5'}]",,
+10.34847/nkl.231c4067,"Sur les chemins et les ponts. Itinéraire des Jeunes Filles, le 19 juin 2019 à Rioupéroux",NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Other,,"""Itinéraire réalisé dans le cadre du projet de recherche-création Les Ondes de l’Eau : Mémoires des lieux et du travail dans la vallée de la Romanche. AAU-CRESSON (Laure Brayer, direction scientifique) - Regards des Lieux (Laure Nicoladzé, direction culturelle).
+
+Quatre jeunes filles habitent à Rioupéroux et se promènent ensemble sur les sentiers de la vallée. Terre de jeux, d’exploration, de découvertes... RPX for ever!
+Alors qu’au centre du village la fête battaît son plein, nous les avons accompagnées sur l’itinéraire d’une de leurs balades habituelles. Des Ponants à la montée des Clots, du vieux pont qui bouge à la mosquée bientôt en chantier, des champs de fraises des bois à la piste de luge, nous avons longé la Romanche au rythme de l’enfance et des souvenirs liés aux générations passées.""",api,True,findable,0,0,0,1,0,2022-06-27T09:51:43.000Z,2022-06-27T09:51:43.000Z,inist.humanum,jbru,"loisirs de plein air,Désertification,Énergie hydraulique,Plantes sauvages,Romanche, Vallée de la (France),relations familiales,saisons,roman-photo,itinéraire,matériaux de terrain éditorialisés,amitié -- chez l'adolescent,Glanage,Risque,milieu scolaire,habitudes,mode de vie,vie rurale,Fêtes religieuses -- Islam,Sports,Promenade,Repas,Histoires de vie,paysage de l'eau,histoire orale,Marche,Sens et sensations,Mémoires des lieux,Relations homme-animal,Relations homme-plante","[{'lang': 'fr', 'subject': 'loisirs de plein air'}, {'lang': 'fr', 'subject': 'Désertification'}, {'lang': 'fr', 'subject': 'Énergie hydraulique'}, {'lang': 'fr', 'subject': 'Plantes sauvages'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'relations familiales'}, {'lang': 'fr', 'subject': 'saisons'}, {'lang': 'fr', 'subject': 'roman-photo'}, {'lang': 'fr', 'subject': 'itinéraire'}, {'lang': 'fr', 'subject': 'matériaux de terrain éditorialisés'}, {'lang': 'fr', 'subject': ""amitié -- chez l'adolescent""}, {'lang': 'fr', 'subject': 'Glanage'}, {'lang': 'fr', 'subject': 'Risque'}, {'lang': 'fr', 'subject': 'milieu scolaire'}, {'lang': 'fr', 'subject': 'habitudes'}, {'lang': 'fr', 'subject': 'mode de vie'}, {'lang': 'fr', 'subject': 'vie rurale'}, {'lang': 'fr', 'subject': 'Fêtes religieuses -- Islam'}, {'lang': 'fr', 'subject': 'Sports'}, {'lang': 'fr', 'subject': 'Promenade'}, {'lang': 'fr', 'subject': 'Repas'}, {'lang': 'fr', 'subject': 'Histoires de vie'}, {'lang': 'fr', 'subject': ""paysage de l'eau""}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'Marche'}, {'lang': 'fr', 'subject': 'Sens et sensations'}, {'lang': 'fr', 'subject': 'Mémoires des lieux'}, {'lang': 'fr', 'subject': 'Relations homme-animal'}, {'lang': 'fr', 'subject': 'Relations homme-plante'}]","['132245194 Bytes', '2577933 Bytes', '115426 Bytes', '452844 Bytes', '1780735 Bytes', '1618527 Bytes', '1563980 Bytes', '1680070 Bytes', '1609421 Bytes', '2038826 Bytes', '1516891 Bytes', '1846355 Bytes', '1671284 Bytes', '1984303 Bytes', '1848460 Bytes', '1510106 Bytes', '1655433 Bytes', '1480786 Bytes', '2068889 Bytes', '1963623 Bytes', '1485998 Bytes', '1552189 Bytes', '1645940 Bytes', '1682036 Bytes', '1465582 Bytes']","['application/pdf', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg', 'image/jpeg']"
+10.5281/zenodo.8376503,"Data supporting 'Ice loss in the European Alps until 2050 using a fully assimilated, deep-learning-aided 3D ice-flow model'",Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The dataset supporting our publication '<strong>Ice loss in the European Alps until 2050 using a fully assimilated, deep-learning-aided 3D ice-flow model</strong>' in <em>Geophysical Research Letters.</em> The main .zip archive contains a set of NetCDF files detailing: Initial optimised glacier states (geology-optimized...) Simulation results (Prog20...) Initial states and results are given by cluster (see Figure 1 in the paper), as shown in all filenames (C1 through to C12). Prognostic simulation filenames additionally distinguish between runs between 1999 and 2019 (Prog2020) and between 2020 and 2050 (Prog2050). 'NV'/'NoVel' and 'NT'/'NoThk' refer to simulations using the partial optimisation (optimisation without including velocity/thickness observations) as detailed in the paper. 'AV' at the end of the filename denotes the integrated area/volume results file, as opposed to the 2D raster results file. A 'V' before the cluster designation shows that the simulation used the variable SMB as opposed to the fixed SMB (see the paper for details). 'ID' before the cluster designation shows that the simulation was using extrapolated SMB based on the trend in SMB since 2000, instead of assuming the continuation of the current SMB. 'ID' on its own denotes linear extrapolation and 'IDQ' denotes quadratic extrapolation. 'SMBF' in the filename shows that the simulation used the SMB-elevation feedback. The additional .zip archive contains the code of IGM v1.0 used to produce the model results. For details on installing and using IGM, please see the Github page at https://github.com/jouvetg/igm.",mds,True,findable,0,0,0,0,0,2023-09-25T12:11:09.000Z,2023-09-25T12:11:09.000Z,cern.zenodo,cern,"Glacier,Alps,Numerical modelling,Deep learning,Climate change","[{'subject': 'Glacier'}, {'subject': 'Alps'}, {'subject': 'Numerical modelling'}, {'subject': 'Deep learning'}, {'subject': 'Climate change'}]",,
+10.5061/dryad.78642,Data from: Controlling false discoveries in genome scans for selection,Dryad,2015,en,Dataset,Creative Commons Zero v1.0 Universal,"Population differentiation (PD) and ecological association (EA) tests have recently emerged as prominent statistical methods to investigate signatures of local adaptation using population genomic data. Based on statistical models, these genome-wide testing procedures have attracted considerable attention as tools to identify loci potentially targeted by natural selection. An important issue with PD and EA tests is that incorrect model specification can generate large numbers of false positive associations. Spurious association may indeed arise when shared demographic history, patterns of isolation by distance, cryptic relatedness or genetic background are ignored. Recent works on PD and EA tests have widely focused on improvements of test corrections for those confounding effects. Despite significant algorithmic improvements, there is still a number of open questions on how to check that false discoveries are under control and implement test corrections, or how to combine statistical tests from multiple genome scan methods. This tutorial paper provides a detailed answer to these questions. It clarifies the relationships between traditional methods based on allele frequency differentiation and EA methods, and provides a unified framework for their underlying statistical tests. We demonstrate how techniques developed in the area of genome-wide association studies, such as inflation factors and linear mixed models, benefit genome scan methods, and provide guidelines for good practice while conducting statistical tests in landscape and population genomic applications. Finally, we highlight how the combination of several well-calibrated statistical tests can increase the power to reject neutrality, improving our ability to infer patterns of local adaptation in large population genomic datasets.",mds,True,findable,321,59,1,1,0,2015-12-09T20:00:16.000Z,2015-12-09T20:00:17.000Z,dryad.dryad,dryad,"Natural Selection and Contemporary Evolution,Bioinfomatics/Phyloinfomatics","[{'subject': 'Natural Selection and Contemporary Evolution'}, {'subject': 'Bioinfomatics/Phyloinfomatics'}]",['9571616 bytes'],
+10.5281/zenodo.5060328,Bioinfo-LPCV-RDF/TF_genomic_analysis:,Zenodo,2021,,Software,Open Access,No description provided.,mds,True,findable,0,0,1,0,0,2021-07-02T12:01:34.000Z,2021-07-02T12:01:35.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5835981,FIGURE 4 in Bulbophyllum section Rhytionanthos (Orchidaceae) in Vietnam with description of new taxa and new national record,Zenodo,2022,,Image,Open Access,"FIGURE 4. Four observed forms of Bulbophyllum taeniophyllum var. denticulatoalatum Vuong & Aver. A, B [BV 1156 (VNM)], C, D [BV 1155 (VNM)], E, F [BV 1171 (VNM)], G,H [BV 1160 (VNM)]. All photos by Truong Ba Vuong.",mds,True,findable,0,0,2,0,0,2022-01-11T09:00:47.000Z,2022-01-11T09:00:47.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Bulbophyllum","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Bulbophyllum'}]",,
+10.5281/zenodo.5237198,Bulgarian DBnary archive in original Lemon format,Zenodo,2021,bg,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Bulgarian language edition, ranging from 24th February 2014 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-23T18:39:04.000Z,2021-08-23T18:39:05.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.15454/o93984,Cartographie indicative à l’échelle départementale des aléas rocheux et des forêts à fonction de protection,Recherche Data Gouv,2022,,Dataset,,Le LESSEM a développé un modèle (Sylvarock) de cartographie indicative à l’échelle d’un versant des aléas rocheux et des forêts susceptibles d’avoir une fonction de protection. Ce modèle a tout d'abord été appliqué sur l'ensemble de l'Arc Alpin (Projet Interreg Espace Alpin ROCKTheAlps) à partir de données disponibles à l'échelle européenne avant un déploiement sur l'ensemble de la France métropolitaine en utilisant des données nationales plus précises (action CADOC de la convention INRAE/DGPR du Ministère de la transition écologique et solidaire). Ce dataset rassemble les résultats de la cartographie à l'échelle de la France métropolitaine avec un prédécoupage par Département. LESSEM lab has developed a model (Sylvarock) for indicative mapping of rock hazards and forests likely to have a protective function. This model was first applied to the whole of the Alps (Alpine Space Interreg ROCKTheAlps project) from data available at the European level before being deployed throughout mainland France using more precise national data (CADOC action of the INRAE/DGPR agreement of the Ministry of Environment). This dataset gathers results of the mapping at the scale of metropolitan France with a pre-division by Department.,mds,True,findable,534,164,0,0,0,2022-04-14T12:30:30.000Z,2022-04-14T14:49:54.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.7298913,Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain – Dataset,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>Dataset of Hugonnet et al. (2022), Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain.</strong> The data is composed of: <strong>For the Mont-Blanc case study: </strong>the Pléiades reference DEM, the SPOT-6 DEM, the Pléiades–SPOT-6 elevation difference, and the forest mask generated from the ESA CCI landcover (delainey polygonization); <strong>For the Northern Patagonian Icefield case study: </strong>the ASTER reference DEM, the SPOT-5 DEM, the ASTER–SPOT-5 elevation difference, and the quality of stereo-correlation of the ASTER DEM from MicMac. The filenames correspond to those used in the <strong>associated GitHub repository</strong>: https://github.com/rhugonnet/dem_error_study. The shapefiles used for masking glaciers are available directly from the <strong>Randolph Glacier Inventory 6.0</strong> at https://www.glims.org/RGI/. The date of the DEMs is in their original format: <strong>year-month-day for all but ASTER</strong> that has the original naming of AST L1A products. <strong>Units are meters</strong> for the DEMs and elevation differences, <strong>and percentages</strong> for the quality of stereo-correlation.",mds,True,findable,0,0,0,1,0,2022-11-07T12:45:02.000Z,2022-11-07T12:45:02.000Z,cern.zenodo,cern,"digital elevation model,error propagation,spatial statistics,geostatistics,variogram,surface elevation,remote sensing","[{'subject': 'digital elevation model'}, {'subject': 'error propagation'}, {'subject': 'spatial statistics'}, {'subject': 'geostatistics'}, {'subject': 'variogram'}, {'subject': 'surface elevation'}, {'subject': 'remote sensing'}]",,
+10.5281/zenodo.8013233,A python package to help Coherent Diffraction Imaging (CDI) practitioners in their analysis,Zenodo,2023,,Software,Open Access,"New beamlines are now supported (P10 and SIXS2022). This release also corresponds to majors changes in the way data are processed. Among them, main part of orthogonalization procedure is done prior to phase retrieval. Then the parameters are saved and the orthogonalization is done on the phased data. New parameters are available, and useless parameters no longer exist. Centering data can now be done using multiple methods.",mds,True,findable,0,0,0,1,0,2023-06-07T08:41:53.000Z,2023-06-07T08:41:53.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4745564,robertxa/Th-Config-Xav: Zenodo DOI,Zenodo,2021,,Software,Open Access,Therion Config file to simplify *.thconfig files and associated (and commented) template files,mds,True,findable,0,0,0,0,0,2021-05-10T10:25:22.000Z,2021-05-10T10:25:23.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3672715,Data for A FinFET with one atomic layer channel,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains raw optical/SEM images of the nano fabrication, and electrical transport test, etc, which are related to the manuscript of A FinFET with One Atomic Layer Channel.",mds,True,findable,3,0,0,0,0,2020-03-05T10:32:54.000Z,2020-03-05T10:32:56.000Z,cern.zenodo,cern,"FinFET, monolayer TMD","[{'subject': 'FinFET, monolayer TMD'}]",,
+10.5281/zenodo.848277,Observations Of Snowpack Distribution And Meteorological Variables At The Izas Experimental Catchment (Spanish Pyrenees) From 2011 To 2017,Zenodo,2017,,Dataset,"Creative Commons Attribution 4.0,Open Access","We present a climatic dataset acquired at Izas Experimental Catchment, in the Central Spanish Pyrenees, from 2011 to 2017 snow seasons. The dataset includes information on different meteorological variables acquired with an Automatic Weather Station including precipitation, air temperature, incoming and reflected short and long-wave radiation, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface) and soil temperature; all of them at 10 minute intervals. Snow depth distribution was measured during 23 field campaigns using a Terrestrial Laser Scanner (TLS), and there are also available time-lapse photographs from which can be derived daily information of different variables such as the Snow Covered Area. The experimental site is located in the southern side of the Pyrenees between 2000 and 2300 m above sea level with an extension of 55 ha. The site is a good example of sub-alpine ambient of mid-latitude mountain ranges. Thus, the dataset has a great potential for understanding environmental processes from a hydrometerological or ecological perspective in which snow dynamics play a determinant role.",,True,findable,0,0,0,0,0,2017-08-25T07:06:53.000Z,2017-08-25T07:06:53.000Z,cern.zenodo,cern,"Snow distribution,Mountain catchments,Meteorological variables,Hydrometeorology","[{'subject': 'Snow distribution'}, {'subject': 'Mountain catchments'}, {'subject': 'Meteorological variables'}, {'subject': 'Hydrometeorology'}]",,
+10.5281/zenodo.7135091,spectralpython/spectral: Spectral Python (SPy) 0.23.1,Zenodo,2022,,Software,Open Access,"SPy 0.23.1 Release date: 2022.10.02 Bug Fixes [#143] Eigen{values,vectors} in a <code>GaussianStats</code> weren't sorted in descending order, which is inconsistent with <code>PrincipalComponents</code>. [#144] <code>SpyFile.load</code> was failing on Windows because numpy versions there did not support complex256. [#145] <code>unmix</code> was failing, due to an invalid reference to ""np.inv""",mds,True,findable,0,0,0,0,0,2022-10-02T16:01:03.000Z,2022-10-02T16:01:04.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10223402,"Pairing Remote Sensing and Clustering in Landscape Hydrology for Large-Scale Changes Identification. Applications to the Subarctic Watershed of the George River (Nunavik, Canada). Dataset and Code.",Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"For remote and vast northern watersheds, hydrological data are often sparse and incomplete. Landscape hydrology provides useful approaches for the indirect assessment of the hydrological characteristics of watersheds through analysis of landscape properties. In this study, we used unsupervised Geographic Object-Based Image Analysis (GeOBIA) paired with the Fuzzy C-Means (FCM) clustering algorithm to produce seven high-resolution territorial classifications of key remotely sensed hydro-geomorphic metrics for the 1985-2019 time-period, each spanning five years. Our study site is the George River watershed (GRW), a 42,000 km2 watershed located in Nunavik, northern Quebec (Canada). The subwatersheds within the GRW, used as the objects of the GeOBIA, were classified as a function of their hydrological similarities. Classification results for the period 2015-2019 showed that the GRW is composed of two main types of subwatersheds distributed along a latitudinal gradient, which indicates broad-scale differences in hydrological regimes and water balances across the GRW. Six classifications were computed for the period 1985-2014 to investigate past changes in hydrological regime. The seven-classification time series showed a homogenization of subwatershed types associated to increases in vegetation productivity and in water content
+in soil and vegetation, mostly concentrated in the northern half of the GRW, which were the major changes occurring in the land cover metrics of the GRW. An increase in vegetation productivity likely contributed to an augmentation in evapotranspiration and may be a primary driver of fundamental shifts in the GRW water balance, potentially explaining a measured decline of about 1 % (∼ 0.16 km3y−1) in the George River’s discharge since the mid-1970s. Permafrost degradation over the study period also likely affected the hydrological regime and water balance of the GRW. However, the shifts in permafrost extent and active layer thickness remain difficult to detect using remote sensing based approaches, particularly in areas of discontinuous and sporadic permafrost.",api,True,findable,0,0,0,0,0,2023-11-29T20:32:53.000Z,2023-11-29T20:32:53.000Z,cern.zenodo,cern,"landscape hydrology,remote sensing,clustering,Subarctic watershed,Arctic greening","[{'subject': 'landscape hydrology'}, {'subject': 'remote sensing'}, {'subject': 'clustering'}, {'subject': 'Subarctic watershed'}, {'subject': 'Arctic greening'}]",,
+10.6084/m9.figshare.c.6756888.v2,Flexible optical fiber channel modeling based on a neural network module,Optica Publishing Group,2023,,Collection,Creative Commons Attribution 4.0 International,"Optical fiber channel modeling which is essential in optical transmission system simulations and designs is usually based on the split-step Fourier method (SSFM), making the simulation quite time-consuming owing to the iteration steps. Here, we train a neural network module termed by NNSpan to learn the transfer function of one single fiber (G652 or G655) span with a length of 80km and successfully emulate long-haul optical transmission systems by cascading multiple NNSpans with a remarkable prediction accuracy even over a transmission distance of 1000km. Although training without erbium-doped fiber amplifier (EDFA) noise, NNSpan performs quite well when emulating the systems affected by EDFA noise. An optical bandpass filter can be added after EDFA optionally, making the simulation more flexible. Comparison with the SSFM shows that the NNSpan has a distinct computational advantage with the computation time reduced by a factor of 12. This method based on the NNSpan could be a supplementary option for optical transmission system simulations, thus contributing to system designs as well.",mds,True,findable,0,0,0,0,0,2023-08-10T20:33:57.000Z,2023-08-10T20:33:57.000Z,figshare.ars,otjm,Uncategorized,[{'subject': 'Uncategorized'}],,
+10.57745/ngc4j0,Long-term monitoring of near-surface soil temperature on the four high summits of Mercantour included in the GLORIA project,Recherche Data Gouv,2023,,Dataset,,"Monitoring of near-surface soil temperature on high summits. Data is part of the long-term monitoring program GLORIA https://gloria.ac.at/home and correspond to the FR-AME site located in Mercantour. Data include a GPS position, a date and time in UTC and a near-surface soil temperature (in °C) measured at 5 cm belowground using stand-alone temperature data logger.",mds,True,findable,43,5,0,0,0,2023-03-27T12:53:09.000Z,2023-07-18T08:20:24.000Z,rdg.prod,rdg,,,,
+10.6084/m9.figshare.c.6851803,Sonometric assessment of cough predicts extubation failure: SonoWean—a proof-of-concept study,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Extubation failure is associated with increased mortality. Cough ineffectiveness may be associated with extubation failure, but its quantification for patients undergoing weaning from invasive mechanical ventilation (IMV) remains challenging. Methods Patients under IMV for more than 24 h completing a successful spontaneous T-tube breathing trial (SBT) were included. At the end of the SBT, we performed quantitative sonometric assessment of three successive coughing efforts using a sonometer. The mean of the 3-cough volume in decibels was named Sonoscore. Results During a 1-year period, 106 patients were included. Median age was 65 [51–75] years, mainly men (60%). Main reasons for IMV were acute respiratory failure (43%), coma (25%) and shock (17%). Median duration of IMV at enrollment was 4 [3–7] days. Extubation failure occurred in 15 (14%) patients. Baseline characteristics were similar between success and failure extubation groups, except percentage of simple weaning which was lower and MV duration which was longer in extubation failure patients. Sonoscore was significantly lower in patients who failed extubation (58 [52–64] vs. 75 [70–78] dB, P < 0.001). After adjustment on MV duration and comorbidities, Sonoscore remained associated with extubation failure. Sonoscore was predictive of extubation failure with an area under the ROC curve of 0.91 (IC95% [0.83–0.99], P < 0.001). A threshold of Sonoscore < 67.1 dB predicted extubation failure with a sensitivity of 0.93 IC95% [0.70–0.99] and a specificity of 0.82 IC95% [0.73–0.90]. Conclusion Sonometric assessment of cough strength might be helpful to identify patients at risk of extubation failure in patients undergoing IMV.",mds,True,findable,0,0,0,0,0,2023-09-26T03:25:48.000Z,2023-09-26T03:25:48.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Physiology,FOS: Biological sciences,Immunology,FOS: Clinical medicine,Infectious Diseases,FOS: Health sciences,Computational Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Infectious Diseases'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Computational Biology'}]",,
+10.5281/zenodo.7141346,Crocus snowpack simulations across southwestern Canada and northwestern US,Zenodo,2022,,Dataset,"Open Government Licence - Canada,Open Access","The simulated snowpack properties (snow water equivalent, snow depth) were obtained from the detailed snowpack model Crocus (Vionnet et al., 2012; Lafaysse et al., 2017), implemented in the SVS land surface scheme version 2 (Soil Vegetation and Snow; Garnaud et al., 2019). Snowpack simulations were carried out from 1 September 2019 to 30 June 2020 over a grid covering southwestern Canada and northwestern US at 2.5-km grid spacing. The simulations were driven by short-meteorological forecast from the High-Resolution Deterministic Prediction System (HRDPS; Milbrandt et al., 2016) combined with precipitation estimates from the Canadian Precipitation Analysis (Fortin et al., 2018). Four precipitation-phase partitioning methods (PPMs) were used to derive the liquid and solid precipitation rates from the total precipitation available in the atmospheric forcing. More details about the simulations are and the PPMS given in the readme file included in the dataset. This dataset has been used in a study submitted to Water Resources Research (Vionnet et al, 2022). <strong>References: </strong> Fortin, V., Roy, G., Stadnyk, T., Koenig, K., Gasset, N., & Mahidjiba, A. (2018). Ten years of science based on the Canadian precipitation analysis: A CaPA system overview and literature review. <em>Atmosphere-Ocean</em>, <em>56</em>(3), 178-196. Garnaud, C., Bélair, S., Carrera, M. L., Derksen, C., Bilodeau, B., Abrahamowicz, M., ... & Vionnet, V. (2019). Quantifying snow mass mission concept trade-offs using an observing system simulation experiment. <em>Journal of Hydrometeorology</em>, <em>20</em>(1), 155-173. Milbrandt, J. A., Bélair, S., Faucher, M., Vallée, M., Carrera, M. L., & Glazer, A. (2016). The pan-Canadian high resolution (2.5 km) deterministic prediction system. <em>Weather and Forecasting</em>, <em>31</em>(6), 1791-1816. Lafaysse, M., Cluzet, B., Dumont, M., Lejeune, Y., Vionnet, V., & Morin, S. (2017). A multiphysical ensemble system of numerical snow modelling. <em>The Cryosphere</em>, <em>11</em>(3), 1173-1198. Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., ... & Willemet, J. M. (2012). The detailed snowpack scheme Crocus and its implementation in SURFEX v7. 2. <em>Geoscientific Model Development</em>, <em>5</em>(3), 773-791. Vionnet, V., Verville, M., Fortin, V., Brugman, M., Abrahamowicz, M., Lemay, F., Thériault, J.M., Lafaysse M., and Milbrandt, J.A. : Snow level from post-processing of atmospheric model improves snowfall estimates and snowpack predictions in mountains, <em>Water Resources Research</em>, 2022, Accepted with minor revisions",mds,True,findable,0,0,0,0,0,2022-10-05T15:38:21.000Z,2022-10-05T15:38:22.000Z,cern.zenodo,cern,"snow,precipitation phase,mountains","[{'subject': 'snow'}, {'subject': 'precipitation phase'}, {'subject': 'mountains'}]",,
+10.6084/m9.figshare.22621187.v1,"Additional file 1 of Promoting HPV vaccination at school: a mixed methods study exploring knowledge, beliefs and attitudes of French school staff",figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Additional Table 1. Teams conducting the PrevHPV program (The PrevHPV Consortium). Additional Table 2. COREQ (COnsolidated criteria for REporting Qualitative research) Checklist. Additional Table 3. STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) Statement — checklist of items that should be included in reports of observational studies. Additional Table 4. Characteristics of the middle schools invited to participate in the study and of those which accepted to participate. Additional Table 5. Additional illustrative verbatim of participants to the focus groups. Additional Table 6. Psychological antecedents of vaccination (5C scale) among participants to the self-administered online questionnaire and by profession. Additional Table 7. Public health topics discussed with pupils by participants to the self-administered online questionnaire and by profession. Additional Table 8. Appropriate period to propose HPV vaccination among pupils according to participants to the self-administered online questionnaire and by profession. Additional Document 1. Self-administered online questionnaire. Additional Document 2. Focus groups’ interview guide. Additional Document 3. Names of the PrevHPV Study Group’s members.,mds,True,findable,0,0,0,0,0,2023-04-13T14:58:32.000Z,2023-04-13T14:58:32.000Z,figshare.ars,otjm,"Medicine,Molecular Biology,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Molecular Biology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['77628 Bytes'],
+10.35088/hh7x-gr77,"Current status of putative animal sources of SAS-CoV-2 2 infection in humans: wildlife, domestic animals and pets",IHU Méditerranée Infection,2021,,Text,,,fabricaForm,True,findable,0,0,0,0,0,2021-04-06T13:12:21.000Z,2021-04-06T13:12:21.000Z,ihumi.pub,ihumi,,,,
+10.5281/zenodo.5649805,"FIGS. 11–16 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIGS. 11–16—Protonemura alexidis sp. n., male. 11, epiproct, lateral view; 12, epiproct, lateral view; 13, epiproct, dorsal view; 14, epiproct, dorsal view (detail); 15, terminalia, ventral view; 16, terminalia, lateral view.",mds,True,findable,0,0,0,0,0,2021-11-05T21:11:21.000Z,2021-11-05T21:11:22.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.6084/m9.figshare.22649276,Additional file 2 of Predictors of changing patterns of adherence to containment measures during the early stage of COVID-19 pandemic: an international longitudinal study,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 2: Supplementary Table 2. Number of the participants involved in the study from each country and geographical region.,mds,True,findable,0,0,0,0,0,2023-04-18T04:38:31.000Z,2023-04-18T04:38:31.000Z,figshare.ars,otjm,"Medicine,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['30771 Bytes'],
+10.5061/dryad.tdz08kq5j,Supporting information for: Accounting for the topology of road networks to better explain human-mediated dispersal in terrestrial landscapes,Dryad,2023,en,Dataset,Creative Commons Zero v1.0 Universal,"Human trade and movements are central to biological invasions worldwide. Human activities not only transport species across biogeographical barriers but also accelerate their post-introduction spread in the landscape. Thus, by constraining human movements, the spatial structure of road networks might greatly affect the regional spread of invasive species. However, few invasion models have accounted for the topology of road networks so far, and its importance for explaining the regional distribution of invasive species remains mostly unexplored. To address this issue, we developed a spatially explicit and mechanistic human-mediated dispersal model that accounts and tests for the influence of transport networks on the regional spread of invasive species. Using as a model the spread of the invasive ant Lasius neglectus in the middle Rhône valley (France), we show that accounting for the topology of road networks improves our ability to explain the current distribution of the invasive ant. In contrast, we found that using human population density as a proxy for the frequency of transport events decreases models’ performance and might thus not be as appropriate as previously thought. Finally, by differentiating road networks into sub-networks, we show that national and regional roads are more important than smaller roads for explaining spread patterns. Overall, our results demonstrate that the topology of transport networks can strongly bias regional invasion patterns and highlight the importance of better incorporating it into future invasion models. The mechanistic modelling approach developed in this study should help invasion scientists explore how human-mediated dispersal and topography shape invasion dynamics in landscapes. Ultimately, our approach could be combined with demographic, natural dispersal and environmental suitability models to refine spread scenarios and improve invasive species monitoring and management at regional to national scales.",mds,True,findable,50,1,0,0,0,2023-11-13T22:32:05.000Z,2023-11-13T22:32:07.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences,biological invasions,human-mediated dispersal,secondary spread,spatially explicit model,stochastic jump model,road network","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'biological invasions'}, {'subject': 'human-mediated dispersal'}, {'subject': 'secondary spread'}, {'subject': 'spatially explicit model'}, {'subject': 'stochastic jump model'}, {'subject': 'road network'}]",['25035773 bytes'],
+10.6084/m9.figshare.23822151.v1,File 5 : Matlab file for part 1 and of the experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,File 5 : This matlab file corresponds to the baseline PSE measures and should be launched first.,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:25.000Z,2023-08-02T11:18:25.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['15465 Bytes'],
+10.15146/zf0j-5m50,"Grounding line of Denman Glacier, East Antarctica from satellite radar interferometry",Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"Grounding line, elevation changes, and melt rates maps of Denman Glacier, East Antarctica. Using satellite radar interferometry from the COSMO-SkyMed mission we map the grounding line of Denman Glacier, East Antarctica. We complement these data with some historical interferometric radar acquisition from the European satellite ERS-1/2. We present new maps of elevation changes on the grounded and floating portions of Denman Glacier obtained by temporally differencing TanDEM-X Digital Elevation Models.",mds,True,findable,4536,2119,2,2,0,2019-09-05T17:38:15.000Z,2019-09-05T17:38:16.000Z,dryad.dryad,dryad,"Glaciers,Interferometry","[{'subject': 'Glaciers', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Interferometry'}]",['1323981608 bytes'],
+10.5281/zenodo.4761343,"Figs. 72-77. Dictyogenus alpinum, egg characteristics. 72 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 72-77. Dictyogenus alpinum, egg characteristics. 72. Egg, lateral view. Casset, Tabuc, Hautes-Alpes dpt, France. 73. Egg, lateral view. Below Lautaret Pass, Guisanne trib., Rif torrent, 'Pont de l'Alpe', Hautes-Alpes dpt, France. 74. Anchor. Below Lautaret Pass, Guisanne trib., Rif torrent, 'Pont de l'Alpe', Hautes-Alpes dpt, France. 75. Anchor. Casset, Tabuc, Hautes-Alpes dpt, France. 76. Detail of chorion and micropyles. Casset, Tabuc, Hautes-Alpes dpt, France. 77. Eggs. Casset, Tabuc, Hautes-Alpes dpt, France.",mds,True,findable,0,0,0,0,0,2021-05-14T07:50:48.000Z,2021-05-14T07:50:49.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.6084/m9.figshare.23983484.v1,Additional file 1 of Aberrant activation of five embryonic stem cell-specific genes robustly predicts a high risk of relapse in breast cancers,figshare,2023,,Text,Creative Commons Attribution 4.0 International,"Additional file 1: Fig. S1. (A) Heatmap showing the expression of 1882 genes in normal adult tissues with predominant expression in testis (male germinal), embryonic stem cells (ES cells) or placenta, and not expressed in normal breast (female genital). The expression levels of all genes are normalized by scaling each feature to a range between zero and one. The genes are ordered according their normalized expression levels in the tissues of interest (testis, placenta and ES cells, respectively). (B) Venn diagram showing the distribution of 1882 genes according the tissue of predominance: testis, embryonic stem cells and/or placenta. Fig. S2. Flow chart representing the main steps of the biomarker discovery pipeline. Fig. S3. Expression profiles in normal tissues of the five genes in the GEC panel DNMT3B, EXO1, MCM10, CENPF and CENPE based on RNA-seq data from GTEX and NCBI Sequence Read Archive. All five genes have a predominant expression profile in embryonic stem cells. They are also expressed in testis (male germinal) at lower levels. These genes are not expressed in normal breast and female genital tissues. Fig. S4. Kaplan-Meier individual survival curves of the genes DNMT3B, EXO1, MCM10, CENPF and CENPE in the training (TCGA-BRCA) and validation (GSE25066, GSE21653, GSE42568) datasets.",mds,True,findable,0,0,0,0,0,2023-08-18T03:20:41.000Z,2023-08-18T03:20:41.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Genetics,FOS: Biological sciences,Molecular Biology,Biological Sciences not elsewhere classified,Information Systems not elsewhere classified,Mathematical Sciences not elsewhere classified,Developmental Biology,Cancer,Plant Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Biological Sciences not elsewhere classified'}, {'subject': 'Information Systems not elsewhere classified'}, {'subject': 'Mathematical Sciences not elsewhere classified'}, {'subject': 'Developmental Biology'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",['510839 Bytes'],
+10.5281/zenodo.8353229,FRACAS: FRench Annotated Corpus of Attribution relations in newS,Zenodo,2023,fr,Dataset,Restricted Access,"A human-annotated corpus for French quotation extraction<strong> </strong>containing 1676 newswire texts with 10 965 annotated attribution relations (quotes attributed to its speaker). <strong>Data</strong>: 1676 newswire texts in French from Reuters annotated with 10 965 attribution relations <strong>Date: </strong>April 1995 to April 1996 <strong>Data structure</strong>: { ""text"": <em>text of the newswire,</em> ""entities"": <em>a list of each entity in the following format</em> [""id"": <em>unique_id</em>, ""text"": <em>text of entity</em>, ""label"": <em>entity label</em>, <em>""</em>gender"": <em>gender (if labelled</em>), ""char_span"": <em>a list of character index span</em>] ""relations""<em>: </em><em>a list of each relation in the following format</em> [<em>id of relation</em>, <em>label of relation</em>, <em>id of first entity</em>, <em>id of second entity</em> } <strong>Labels:</strong> Entities: <strong>Quotation</strong> (Direct, Indirect or Mixed) <strong>Speaker</strong> (Agent, Organization, Group of People, Source Pronoun) <strong>Cue</strong> Attributes: Speaker Gender (Male, Female, Mixed, Unknown, Other) Relations: Speaker <strong>Quoted in </strong>Quotation Cue <strong>Indicates </strong>Quotation Source Pronoun <strong>Refers</strong> to Speaker",mds,True,findable,0,0,0,0,0,2023-09-19T08:30:36.000Z,2023-09-19T08:30:36.000Z,cern.zenodo,cern,"source attribution, quotations, newswire, french","[{'subject': 'source attribution, quotations, newswire, french'}]",,
+10.5281/zenodo.2677907,tcompa/Data_2D_Fermi_dipoles: v1.0.2,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data_2D_Fermi_dipoles
+
+Here we report the supporting data for the manuscript ""Two-dimensional Mixture of Dipolar Fermions: Equation of State and Magnetic Phases"", by Tommaso Comparin, Raul Bombin, Markus Holzmann, Ferran Mazzanti, Jordi Boronat, and Stefano Giorgini (Phys. Rev. A 99, 043609 (2019), https://arxiv.org/abs/1812.08064). If you use these data in a scientific work, please cite the corresponding article [Phys. Rev. A 99, 043609 (2019)].
+
+For additional details, please contact Tommaso Comparin (tommaso.comparin@unitn.it, tommaso.comparin@gmail.com).
+
+The data described in the manuscript are organized as follows:
+
+
+ Data for Fig. 1 (EOS for P=0) are in the folder Energies_JS_small_density.
+ Data for Fig. 2 (pair distribution functions for P=0) are in the folder Pair_distribution_function_P0.
+ Data for Fig. 3 (pair distribution functions for P=0 at small density) are in the folder Pair_distribution_function_P0_small_density.
+ Data for Fig. 4 and Table I (Jastrow-Slater and Backflow energies, for different polarizations) are in the folder Energies_JS_and_BF.
+ Data for Fig. 5 (polaron energies at density n*r_0^2=40) are in the folder Energies_polaron.
+ Data for Fig. 6 and Table II (iterated-backflow energies) are in the folder Energies_iterated_bacfklow.
+
+
+Each folder contains a README file with a description of the data files and additional details on the simulations.
+
+NOTES
+
+Two sets of units are used for the energy (see README files in each folder):
+
+
+ Dipolar units, as in the manuscript, correspond to the energy scale epsilon_0=hbar^2/(m*r_0^2).
+ Density units correspond to the energy scale hbar^2/(2<em> </em>m<em> </em>a^2), where a=1/sqrt(pi*n) is the mean interparticle distance.
+
+
+
+
+New in v1.0.2: Updated license to CC BY 4.0.
+
+New in v1.0.1: Minor update to Energies_JS_small_density/data_energies_P0_N74_JS.dat.",mds,True,findable,0,0,0,0,0,2019-05-08T15:14:46.000Z,2019-05-08T15:14:46.000Z,cern.zenodo,cern,"quantum monte carlo,ultracold atoms,monte carlo","[{'subject': 'quantum monte carlo'}, {'subject': 'ultracold atoms'}, {'subject': 'monte carlo'}]",,
+10.5281/zenodo.4760475,"Figs. 8-10 in Two New Alpine Leuctra In The L. Braueri Species Group (Plecoptera, Leuctridae)",Zenodo,2011,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 8-10. Leuctra braueri kempny: male abdominal tip in dorsal view (8), male genitalia in ventral view (9), female subgenital plate in ventral view (10).",mds,True,findable,0,0,4,0,0,2021-05-14T05:23:35.000Z,2021-05-14T05:23:36.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.5835979,FIGURE 3. Bulbophyllum taeniophyllum var. denticulatoalatum Vuong & Aver. A. Flowering plant. B. Pseudobulbs. C in Bulbophyllum section Rhytionanthos (Orchidaceae) in Vietnam with description of new taxa and new national record,Zenodo,2022,,Image,Open Access,"FIGURE 3. Bulbophyllum taeniophyllum var. denticulatoalatum Vuong & Aver. A. Flowering plant. B. Pseudobulbs. C. Pseudobulb and leaf, adaxial side. D. Abaxial leaf surface. E. Inflorescence. F. Flowers, frontal view. G. Flowers, half side and side views. H. Median sepal, adaxial and abaxial side. I. Lateral sepals, adaxial and abaxial side. J. Petals, adaxial and abaxial side. K. Lip, views from different sides. L. Ovary, column, and lip, side view. M. Pedicel, ovary and column, side view. N. Column, frontal and side views. O. Anther cap, views from different sides. P. Pollinia. Photos by Truong Ba Vuong, correction and design by L. Averyanov and T. Maisak.",mds,True,findable,0,0,2,0,0,2022-01-11T09:00:40.000Z,2022-01-11T09:00:41.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Plantae,Tracheophyta,Liliopsida,Asparagales,Orchidaceae,Bulbophyllum","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Plantae'}, {'subject': 'Tracheophyta'}, {'subject': 'Liliopsida'}, {'subject': 'Asparagales'}, {'subject': 'Orchidaceae'}, {'subject': 'Bulbophyllum'}]",,
+10.5281/zenodo.7331741,OPEN-NEXT/wp2.2_dev: D2.5 dashboard backend with support for Wikifactory and GitHub,Zenodo,2022,,Software,Open Access,This release contains the Open!Next M36 D2.5 dashboard <strong><em>backend</em></strong> code that can retrieve metadata from repositories hosted on GitHub and Wikifactory. The sample implementation of the <em>frontend</em> is now in this repository. Please read <code>README.md</code> in this repository and the D2.5 report for more information. The only change in this version is an update to the link to the demo instance of the API.,mds,True,findable,0,0,0,0,0,2022-11-17T17:46:01.000Z,2022-11-17T17:46:01.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.21430974,Additional file 2 of Digitally-supported patient-centered asynchronous outpatient follow-up in rheumatoid arthritis - an explorative qualitative study,figshare,2022,,Text,Creative Commons Attribution 4.0 International,Supplementary Material 2,mds,True,findable,0,0,0,0,0,2022-10-29T03:17:13.000Z,2022-10-29T03:17:14.000Z,figshare.ars,otjm,"Medicine,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['14460 Bytes'],
+10.5281/zenodo.8272196,feelpp/feelpp: Feel++ Release V111 alpha.5,Zenodo,2023,,Software,Open Access,Packages 📦 Ubuntu packages 📦 Debian packages 📦 Docker images What's Changed add support for EigenRand #2131 by @prudhomm in https://github.com/feelpp/feelpp/pull/2133 resolves 2123: enable dim different from realdim in BVH by @prudhomm in https://github.com/feelpp/feelpp/pull/2129 resolves 2143: clean mor by @prudhomm in https://github.com/feelpp/feelpp/pull/2146 <strong>Full Changelog</strong>: https://github.com/feelpp/feelpp/compare/v0.111.0-alpha.4...v0.111.0-alpha.5,mds,True,findable,0,0,0,0,0,2023-08-22T09:27:53.000Z,2023-08-22T09:27:54.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6909792,"IODP Expedition -358, Site C0024 - LWD Data",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Drilling and Logging data acquired during drilling (Logging-While-Drilling, LWD) of the IODP expedition 358 site C0024.",mds,True,findable,0,0,0,0,0,2022-07-27T00:50:33.000Z,2022-07-27T00:50:34.000Z,cern.zenodo,cern,"IODP Expedition 358,Nankai Accretionary Prism,Site-COO24,Hole C0024A,Logging While Drilling (LWD),NanTroSEIZE,Hydraulic Properties,Décollement,Riserless Drilling","[{'subject': 'IODP Expedition 358'}, {'subject': 'Nankai Accretionary Prism'}, {'subject': 'Site-COO24'}, {'subject': 'Hole C0024A'}, {'subject': 'Logging While Drilling (LWD)'}, {'subject': 'NanTroSEIZE'}, {'subject': 'Hydraulic Properties'}, {'subject': 'Décollement'}, {'subject': 'Riserless Drilling'}]",,
+10.5281/zenodo.5013300,Radiative transfer modeling in structurally-complex stands: what aspects matter most?: Dataset,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository is linked to the paper ""Radiative transfer modeling in structurally-complex stands: what aspects matter most?"" submitted to Annals of Forest Science and written by Frédéric ANDRÉ (corresponding author), Louis DE WERGIFOSSE, François DE COLIGNY, Nicolas BEUDEZ, Gauthier LIGOT, Vincent GAUTHRAY-GUYÉNET, Benoit COURBAUD and Mathieu JONARD. The repository contains the three following files : CalibrationResults.csv: Bayes factors and summary statistics of parameter estimates for each calibration run ParameterPosteriorDistributions.csv: median values and 90% credible intervals for the parameter posterior distributions StatisticalComparison.csv: statistics (Fractional bias, Root mean square error, Paired Student test, Pearson correlation coefficient, Parameters of the Deming regression between observed and predicted values) used to compare the 'Best model configurations' For more information concerning this repository or the study, please do not hesitate to contact Frédéric ANDRÉ (frederic.andre@uclouvain.be) or Mathieu JONARD (mathieu.jonard@uclouvain.be).",mds,True,findable,0,0,0,0,0,2021-06-22T14:09:45.000Z,2021-06-22T14:09:46.000Z,cern.zenodo,cern,"Light interception,Heterogeneous,Crown asymmetry,Lambert-Beer,Porous envelope,Bayesian optimization","[{'subject': 'Light interception'}, {'subject': 'Heterogeneous'}, {'subject': 'Crown asymmetry'}, {'subject': 'Lambert-Beer'}, {'subject': 'Porous envelope'}, {'subject': 'Bayesian optimization'}]",,
+10.57745/ot1ifb,Water transit time tracing model using wetness adaptive StorAge Selection functions,Recherche Data Gouv,2023,,Dataset,,"A model using StorAge Selection (SAS) functions in order to estimate water transit time distributions through a mesoscale catchment under Mediterranean climate, prone to flash floods. This dataset contains the model code, forcing data as well as results of a sensitivity analysis. The article describing this model will be linked once published.",mds,True,findable,209,2,0,0,0,2023-04-20T12:52:05.000Z,2023-06-20T12:31:30.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.7275468,GNU Data Language 1.0: a free/libre and open-source drop-in replacement for IDL/PV-WAVE,Zenodo,2022,,Software,"Creative Commons Attribution 4.0 International,Open Access",GNU Data Language (github.com/gnudatalanguage/gdl) release for the Journal of Open Source Software manuscript.,mds,True,findable,0,0,0,0,0,2022-11-03T04:54:19.000Z,2022-11-03T04:54:20.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.2590150,"Snow properties measurements (in situ & retrived from satellite) at Dome C, East Antarctica Plateau",Zenodo,2019,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The dataset contains the data inputs for the electromagnetic model:
+
+
+ the snow density profile down to 20 m depth (measured in 2010)
+ the snow SSA profile down to 20 m depth (measured in 2010)
+ the snow temperature profile down to 20 m depth (measured from 1 December 2006 to 4 October 2011)
+
+
+The dataset contains also the data retrieved from satellite:
+
+
+ the retrieved surface snow density from AMSR-E satellite (obtained from 18 June 2002 to 4 October 2011)
+
+
+The dataset contains finally the data measured in situ to compare with the data retrieved from satellite:
+
+
+ the surface snow density from CALVA program (measured from 3 February 2010 to 4 October 2011)
+ the surface snow density from PNRA program measured in snow pits (measured from 18 December 2007 to 4 October 2011)
+ the surface snow density from PNRA program measured next to stakes (measured from 9 May 2008 to 4 October 2011)",mds,True,findable,0,0,0,0,0,2019-03-11T11:13:13.000Z,2019-03-11T11:13:14.000Z,cern.zenodo,cern,Surface snow density ; Profiles of snow properties,[{'subject': 'Surface snow density ; Profiles of snow properties'}],,
+10.5281/zenodo.3876052,Raw diffraction data for [NiFeSe] hydrogenase G491A variant pressurized with O2 gas - dataset G491A-O2-LD,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","Diffraction data measured at ESRF beamline ID30B on April 8, 2018. Image files are uploaded in blocks of gzip-compressed cbf files.",mds,True,findable,1,0,0,0,0,2020-06-04T08:24:45.000Z,2020-06-04T08:24:46.000Z,cern.zenodo,cern,"Hydrogenase,Selenium,gas channels,high-pressure derivatization","[{'subject': 'Hydrogenase'}, {'subject': 'Selenium'}, {'subject': 'gas channels'}, {'subject': 'high-pressure derivatization'}]",,
+10.5281/zenodo.4133862,complex_phase_diagrams,Zenodo,2020,,Software,"BSD 3-Clause ""New"" or ""Revised"" License,Open Access","This entry contains a program with self-explanatory jupyter notebooks for calculating a phase coexistence region (or solubility gap, SG) in CoxMn3-xO4. Otherwise, the latest version of the software can be obtained by cloning the git repository at: https://github.com/nataliomingo/complex_phase_diagrams",mds,True,findable,0,0,0,0,0,2020-10-26T11:15:28.000Z,2020-10-26T11:15:29.000Z,cern.zenodo,cern,"solubility gap,phase diagram,phase coexistence,transition metal oxide","[{'subject': 'solubility gap'}, {'subject': 'phase diagram'}, {'subject': 'phase coexistence'}, {'subject': 'transition metal oxide'}]",,
+10.5281/zenodo.3403082,The dynamics of bi-directional exchange flows: implication for morphodynamic change within estuaries and sea straits,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Environmental and geophysical flows, including dense bottom gravity currents in the ocean and buoyancy-driven exchange flows in marginal seas,<br> are strongly controlled by topographic features.<br> These are known to exert significant influence on both internal mixing and secondary circulations generated by these flows.<br> In such cases, uni-directional or bi-directional exchange flows develop when horizontal density differences<br> and/or pressure gradients are present between adjacent water bodies connected by a submerged channel.<br> The flow dynamics of the dense lower layer depend primarily on the volumetric flux and channel cross-sectional shape,<br> while the stratified interfacial flow mixing characteristics, leading to fluid entrainment/detrainment,<br> are also dependent on the buoyancy flux and motion within the upper (lower density) water mass.<br> For submerged channels that are relatively wide compared to the internal Rossby radius of deformation,<br> Earth rotation effects introduce geostrophic adjustment of these internal fluid motions,<br> which can suppress turbulent mixing generated at the interface and result in the development of Ekman layers that induce secondary,<br> cross-channel circulations, even within straight channels.<br> Moreover, recent studies of dense, gravity currents generated in rotating and non-rotating systems,<br> respectively, indicated that the V-shaped channel topography had a strong influence on both flow distribution<br> and associated interfacial mixing characteristics along the channel.<br> However, such topographic controls on the interfacial mixing and secondary circulations generated by bi-directional exchange flows<br> are not yet fully understood and remain to be investigated thoroughly in the laboratory.<br> Also the effect of mobile bed for bi-directional exchange flows generated in deformable channels along with the physical interactions<br> between the lower dense water flow and the erodible bed sediments<br> will have a strong influence in (re-)shaping the overall channel bed topography (i.e. bed morphodynamics).<br> Consequently, the resulting temporal changes in cross-sectional channel bathymetry (i.e. through erosion and deposition processes)<br> would also be expected to have associated feedbacks on transverse asymmetries in the bi-directional exchange flow structure,<br> as well as on the internal flow stability.",mds,True,findable,1,0,0,0,0,2019-09-11T07:24:01.000Z,2019-09-11T07:24:02.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8342388,JASPAR 2024 TFBS LOLA databases - Part 3,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the third part of the JASPAR 2024 LOLA databases used by the JASPAR TFBS enrichment tool. For each organism, we provide the LOLA databases for all JASPAR 2024 TFBS sets as compressed directories containing a set of .RDS R objects. Databases are organised by genome assembly. The repository is split into different parts due to file sizes. Below are listed the different parts and the genome assemblies for which they have TFBSs: Part 1: araTha1, ce10, ce11, ci3, danRer11, dm6, sacCer3. Part 2: hg38. Part 3: mm39.",mds,True,findable,0,0,0,0,0,2023-09-14T07:30:29.000Z,2023-09-14T07:30:29.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.pc866t1k5,Climate associated genetic variation in Fagus sylvatica and potential responses to climate change in the French Alps,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Local adaptation patterns have been found in many plants and animals, highlighting the genetic heterogeneity of species along their range of distribution. In the next decades, global warming is predicted to induce a change in the selective pressures that drive this adaptive variation, forcing a reshuffling of the underlying adaptive allele distributions. For species with low dispersion capacity and long generation time such as trees, the rapidity of the change could imped the migration of beneficial alleles and lower their capacity to track the changing environment. Identifying the main selective pressures driving the adaptive genetic variation is thus necessary when investigating species capacity to respond to global warming. In this study, we investigate the adaptive landscape of Fagus sylvatica along a gradient of populations in the French Alps. Using a double digest restriction-site associated DNA (ddRAD) sequencing approach, we identified 7,000 SNPs from 570 individuals across 36 different sites. A redundancy analysis (RDA)-derived method allowed us to identify several SNPs that were strongly associated with climatic gradients; moreover, we defined the primary selective gradients along the natural populations of F. sylvatica in the Alps. Strong effects of elevation and humidity, which contrast north-western and south-eastern site, were found and were believed to be important drivers of genetic adaptation. Finally, simulations of future genetic landscapes that used these findings allowed identifying populations at risk for F. sylvatica in the Alps, which could be helpful for future management plans.",mds,True,findable,407,105,1,1,0,2020-03-06T19:38:40.000Z,2020-03-06T19:38:41.000Z,dryad.dryad,dryad,"RDA,Fagus sylvatica,French Alps","[{'subject': 'RDA'}, {'subject': 'Fagus sylvatica'}, {'subject': 'French Alps'}]",['132729513 bytes'],
+10.5061/dryad.283pp,Data from: Large chromosomal rearrangements during a long-term evolution experiment with Escherichia coli,Dryad,2015,en,Dataset,Creative Commons Zero v1.0 Universal,"Large-scale rearrangements may be important in evolution because they can alter chromosome organization and gene expression in ways not possible through point mutations. In a long-term evolution experiment, twelve Escherichia coli populations have been propagated in a glucose-limited environment for over 25 years. We used whole-genome mapping (optical mapping) combined with genome sequencing and PCR analysis to identify the large-scale chromosomal rearrangements in clones from each population after 40,000 generations. A total of 110 rearrangement events were detected, including 82 deletions, 19 inversions, and 9 duplications, with lineages having between 5 and 20 events. In three populations, successive rearrangements impacted particular regions. In five populations, rearrangements affected over a third of the chromosome. Most rearrangements involved recombination between insertion sequence (IS) elements, illustrating their importance in mediating genome plasticity. Two lines of evidence suggest that at least some of these rearrangements conferred higher fitness. First, parallel changes were observed across the independent populations, with ~65% of the rearrangements affecting the same loci in at least two populations. For example, the ribose-utilization operon and the manB-cpsG region were deleted in 12 and 10 populations, respectively, suggesting positive selection, and this inference was previously confirmed for the former case. Second, optical maps from clones sampled over time from one population showed that most rearrangements occurred early in the experiment, when fitness was increasing most rapidly. However, some rearrangements likely occur at high frequency and may have simply hitchhiked to fixation. In any case, large-scale rearrangements clearly influenced genomic evolution in these populations.",mds,True,findable,222,16,1,1,0,2014-08-13T16:19:35.000Z,2014-08-13T16:19:36.000Z,dryad.dryad,dryad,"DNA rearrangements,IS elements","[{'subject': 'DNA rearrangements'}, {'subject': 'IS elements'}]",['814 bytes'],
+10.5281/zenodo.4574537,"The 2020 eruption and the large lateral dike emplacement at Taal volcano, Philippines: Insights from radar satellite data",Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","ALOS2_A138.zip : ALOS-2 ascending track 138 unwrapped, coherence, and baseline files covering Taal volcano, Philippines from 18 September 2018 to 10 December 2019. ALOS2_D027.zip: ALOS-2 descending track 27 unwrapped, coherence, and baseline files covering Taal volcano, Philippines from 102 December 2018 to 12 January 2020.",mds,True,findable,0,0,0,0,0,2021-03-02T22:56:44.000Z,2021-03-02T22:56:45.000Z,cern.zenodo,cern,"InSAR,Taal volcano","[{'subject': 'InSAR'}, {'subject': 'Taal volcano'}]",,
+10.5281/zenodo.6793401,Pycorr,Zenodo,2022,,Software,Open Access,"PYCORR v1.0 https://gricad-gitlab.univ-grenoble-alpes.fr/bouep/pycorr/ Python3.7 Ambient seismic noise correlation package Retrieve seismic station information from FDSN catalog : http://service.iris.edu/irisws/fedcatalog/1/ Retrieve waveforms from FDSN-webservices and/or personal archive Basic processing ""on the fly"": decimation, sensor response, gaps... Possible (pre-) processing before correlation Xcorr with flexible parameters for optimized tomography and/or monitoring applications Tensor rotation to retrieve RT information Basic toolbox to extract and plot correlations results from large output",mds,True,findable,0,0,0,0,0,2022-07-04T08:11:39.000Z,2022-07-04T08:11:40.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3817352,"Search Queries for ""Mapping Research Output to the Sustainable Development Goals (SDGs)"" v1.0",Zenodo,2018,,Software,"Creative Commons Attribution 4.0 International,Open Access","<strong>This package contain machine readable (xml) search queries for Scopus to find domain specific research output that are related to the 17 Sustainable Development Goals (SDGs).</strong> Sustainable Development Goals are the 17 global challenges set by the United Nations. Within each of the goals specific targets and indicators are mentioned to monitor the progress of reaching those goals by 2030. In an effort to capture how research is contributing to move the needle on those challenges, we earlier have made an initial classification model than enables to quickly identify what research output is related to what SDG. (This Aurora SDG dashboard is the initial outcome as <em>proof of practice</em>.) The initiative started from the Aurora Universities Network in 2017, in the working group ""Societal Impact and Relevance of Research"", to investigate and to make visible 1. what research is done that are relevant to topics or challenges that live in society (for the proof of practice this has been scoped down to the SDGs), and 2. what the effect or impact is of implementing those research outcomes to those societal challenges (this also have been scoped down to research output being cited in policy documents from national and local governments an NGO's). The classification model we have used are 17 different search queries on the Scopus database. The search queries are elegant constructions with keyword combinations and boolean operators, in the syntax specific to the Scopus Query Language. We have used Scopus because it covers more research area's that are relevant to the SDG's, and we could filter much easier the Aurora Institutions. <strong>Versions</strong> Different versions of the search queries have been made over the past years to improve the precision (soundness) and recall (completeness) of the results. The queries have been made in a team effort by several bibliometric experts from the Aurora Universities. Each one did two or 3 SDG's, and than reviewed each other's work. v1.0 January 2018<em> Initial 'strict' version.</em> In this version only the terms were used that appear in the SDG policy text of the targets and indicators defined by the UN. At this point we have been aware of the SDSN Compiled list of keywords, and used them as inspiration. Rule of thumb was to use <em>keyword-combination searches</em> as much as possible rather than <em>single-keyword searches</em>, to be more precise rather than to yield large amounts of false positive papers. Also we did not use the inverse or 'NOT' operator, to prevent removing true positives from the result set. This version has not been reviewed by peers. Download from: GitHub / Zenodo v2.0 March 2018<em> Reviewed 'strict' version.</em> Same as version 1, but now reviewed by peers. Download from: GitHub / Zenodo v3.0 May 2019 <em>'echo chamber' version.</em> We noticed that using strictly the terms that policy makers of the UN use in the targets and indicators, that much of the research that did not use that specific terms was left out in the result set. (eg. ""mortality"" vs ""deaths"") To increase the recall, without reducing precision of the papers in the results, we added keywords that were obvious synonyms and antonyms to the existing 'strict' keywords. This was done based on the keywords that appeared in papers in the result set of version 2. This creates an 'echo chamber', that results in more of the same papers. Download from: GitHub / Zenodo v4.0 August 2019<em> uniform 'split' version.</em> Over the course of the years, the UN changed and added Targets and indicators. In order to keep track of if we missed a target, we have split the queries to match the targets within the goals. This gives much more control in maintenance of the queries. Also in this version the use of brackets, quotation marks, etc. has been made uniform, so it also works with API's, and not only with GUI's. His version has been used to evaluate using a survey, to get baseline measurements for the precision and recall. Published here: Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. Download from: GitHub / Zenodo v5.0 June 2020 <em>'improved' version.</em> In order to better reflect academic representation of research output that relate to the SDG's, we have added more keyword combinations to the queries to increase the recall, to yield more research papers related to the SDG's, using academic terminology. We mainly used the input from the Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. We ran several text analyses: Frequent term combination in title and abstracts from Suggested papers, and in selected (accepted) papers, suggested journals, etc. Secondly we got inspiration out of the Elsevier SDG queries Jayabalasingham, Bamini; Boverhof, Roy; Agnew, Kevin; Klein, Lisette (2019), “Identifying research supporting the United Nations Sustainable Development Goalsâ€, Mendeley Data, v1 https://dx.doi.org/10.17632/87txkw7khs.1. Download from: GitHub / Zenodo <strong>Contribute and improve the SDG Search Queries</strong> We welcome you to join the Github community and to fork, improve and make a pull request to add your improvements to the new version of the SDG queries. <strong>https://github.com/Aurora-Network-Global/sdg-queries</strong>",mds,True,findable,0,0,1,0,0,2020-05-15T12:48:02.000Z,2020-05-15T12:48:03.000Z,cern.zenodo,cern,"Sustainable Development Goals,SDG,Classification model,Search Queries,SCOPUS","[{'subject': 'Sustainable Development Goals'}, {'subject': 'SDG'}, {'subject': 'Classification model'}, {'subject': 'Search Queries'}, {'subject': 'SCOPUS'}]",,
+10.5281/zenodo.7025633,A gate-tunable graphene Josephson parametric amplifier,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Data files of the figures (main and supplementary information),mds,True,findable,0,0,0,0,0,2022-08-26T15:03:04.000Z,2022-08-26T15:03:04.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.2625730,Infinite Grid Exploration by Disoriented Robots : The animations,Zenodo,2019,,Software,"CeCILL-B Free Software License Agreement,Open Access",Description of three infinite grid exploration algorithms The published HTML pages allows the viewer to see the first 100 rounds of the algorithms.,mds,True,findable,0,0,0,0,0,2019-05-24T09:05:44.000Z,2019-05-24T09:05:44.000Z,cern.zenodo,cern,"Mobile robots,Graph exploration","[{'subject': 'Mobile robots'}, {'subject': 'Graph exploration'}]",,
+10.5281/zenodo.7385933,ACO-FROST: generation of icy grain models and adsorption of molecules,Zenodo,2022,,Software,"Creative Commons Attribution 4.0 International,Open Access",Zip files containing the ACO-FROST set of codes at the time of publication of Germain et al. 2021. For a more up to date version see aurelegermain/ACO-FROST_grain_generator and aurelegermain/ACO-FROST_BE-grain. Require the xtb program developed by the Grimme group at the Bonn University and available here.,mds,True,findable,0,0,0,1,0,2022-12-01T11:23:38.000Z,2022-12-01T11:23:54.000Z,cern.zenodo,cern,"cluster,modeling,Interstellar icy grain","[{'subject': 'cluster'}, {'subject': 'modeling'}, {'subject': 'Interstellar icy grain'}]",,
+10.6084/m9.figshare.c.6586643,Digital technologies in routine palliative care delivery: an exploratory qualitative study with health care professionals in Germany,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Objective To explore health care professionals’ (HCPs) perspectives, experiences and preferences towards digital technology use in routine palliative care delivery. Methods HCPs (n = 19) purposively selected from a sample of settings that reflect routine palliative care delivery (i.e. specialized outpatient palliative care, inpatient palliative care, inpatient hospice care in both rural and urban areas of the German states of Brandenburg and Berlin) participated in an explorative, qualitative study using semi-structured interviews. Interview data were analyzed using structured qualitative content analysis. Results Digital technologies are widely used in routine palliative care and are well accepted by HCPs. Central functions of digital technologies as experienced in palliative care are coordination of work processes, patient-centered care, and communication. Especially in outpatient care, they facilitate overcoming spatial and temporal distances. HCPs attribute various benefits to digital technologies that contribute to better coordinated, faster, more responsive, and overall more effective palliative care. Simultaneously, participants preferred technology as an enhancement not replacement of care delivery. HCPs fear that digital technologies, if overused, will contribute to dehumanization and thus significantly reduce the quality of palliative care. Conclusion Digital technology is already an essential part of routine palliative care delivery. While generally perceived as useful by HCPs, digital technologies are considered as having limitations and carrying risks. Hence, their use and consequences must be carefully considered, as they should discreetly complement but not replace human interaction in palliative care delivery.",mds,True,findable,0,0,0,0,0,2023-04-13T12:27:58.000Z,2023-04-13T12:27:58.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}]",,
+10.5281/zenodo.8272736,"Data supplement for ""Molecular motors enhance microtubule lattice plasticity"" Lecompte, William; John, Karin",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the data and source files for figures 2 (a-e), 3(a-d), 4(b,c,e) and Supplementary figures 5, 7(a-e), 8 and 9(a-c) in the following publication: W. Lecompte and K. John ""Molecular motors enhance microtubule lattice plasticity"" published in 2023 in PRX Life (ArXiv https://arxiv.org/abs/2209.09161) Please follow the instructions given in 'Readme.txt'.",mds,True,findable,0,0,0,0,0,2023-08-22T10:58:26.000Z,2023-08-22T10:58:27.000Z,cern.zenodo,cern,"microtubuli, processive molecular motors, lattice dynamics, modelling","[{'subject': 'microtubuli, processive molecular motors, lattice dynamics, modelling'}]",,
+10.6084/m9.figshare.14216912,Exhumation of the Western Alpine collisional wedge: new thermochronological data,figshare,2022,,Dataset,Creative Commons Attribution 4.0 International,"<b>Table 1</b>: Raman spectroscopy of carbonaceous material data. GPS coordinates in WGS84 system, number of spectra (n), mean R2 ratio (Beyssac et al., 2002a) or RA1 ratio (Lahfid et al., 2010) reliant on best fit during post-processing using the software PeakFit following the methods described in Beyssac et al. (2002b) and Lahfid et al. (2010) with corresponding standard deviation, and calculated temperature with standard error (SE). Standard error is the standard deviation divided by √n. The absolute error on temperature is ±50 °C (Beyssac et al., 2002b). (a) Method from Lahfid et al. (2010) and (b) Method from Beyssac et al. (2002b). For very disordered graphitic carbon that is found in least metamorphosed rocks, we assign T < 200 °C.<br><b>Table 2</b>: Zircon fission-track data from Belledonne and Grandes Rousses massifs, western Alps. All samples were counted at 1250 x dry (x 100 objective, 1.25 tube factor, 10 oculars) by J.B. Girault using a zeta (IRMM541) of 120.42 ± 3.23 (± 1SE); all ages are reported as central ages (Galbraith and Laslett, 1993). GPS coordinates in WGS84 system. Massif: NBDi = North Belledonne internal unit; NBDe = North Belledonne external unit, CBD = Central Belledonne, SBD = South Belledonne, GR =Grandes Rousses; N = number of grains counted; Ïs = spontaneous track density; Ïi = induced track density; Ns, Ni = number of tracks counted to determine the reported track densities; P(χ2) = Chi-square probability that the single grain ages represent one population.<br><b>Table 3</b>: Apatite fission-track data from Belledonne massif, western Alps. All samples were counted at 1250 x dry (x 100 objective, 1.25 tube factor, 10 oculars) by M. Balvay using a zeta (CN-5) of 273.35 ± 12.05 (± 1SE); all ages are reported as central ages (Galbraith and Laslett, 1993). Latitude and Longitude in WGS84 reference frame. Massif: NBDi = North Belledonne internal unit; NBDe = North Belledonne external unit, CBD = Central Belledonne, SBD = South Belledonne, GR =Grandes Rousses; N = number of grains counted; Ïs = spontaneous track density; Ïi = induced track density; Ns, Ni = number of tracks counted to determine the reported track densities; P(χ2) = Chi-square probability that the single grain ages represent one population.<br><b>Table 4</b>: (U-T-Sm/He) on zircons data (ZHe) from Belledonne and Grandes Rousses massifs, western Alps. Latitude and Longitude in WGS84 reference frame. Massif: NBDi = North Belledonne internal unit; NBDe = North Belledonne external unit, CBD = Central Belledonne, SBD = South Belledonne, GR = Grandes Rousses<br><b>Supplemental data 1</b>: Age/elevation distribution of the thermochronological data (AFT, ZHe and ZFT) from (e) North External Belledonne (dark blue dots), (f) North Internal Belledonne (light blue dots) and (g) South Belledonne (yellow dots). One elevation range of LT thermochronological data was selected at ~1800m with, when possible, ZFT, ZHe and AFT data for thermal inversion modelling. (d) Grandes Rousses (purple dots) with full range scale. South Belledonne and Grandes Rousses: AFT data from Sabil (1995).<br><b><br></b><b>Supplemental data 2</b>: Termal histories modelled with HeFTy sofware for the (e) North Belledonne external unit at ~1800m, (f) North Belledonne external unit at 1800m and (g) South Belledonne massif at ~2200m. T–t paths are statistically evaluated and categorized by their value of goodness of ft (GOF). ‘Acceptable’ results, in green, correspond to a 0.05 GOF value and ‘good’ results, in purple, correspond to 0.5 GOF (Ketcham, 2005).<b><br></b><b>Supplemental data 3</b>: Age/elevation distribution of zircon fssion-track (ZFT) ages available for Aiguilles Rouges (Soom, 1990) and Mont Blanc (Glotzbach et al., 2011): gray diamond-shaped, Belledonne (this study): orange circle, Pelvoux – Meije massifs (van der Beek et al., 2010): yellow square, Grandes Rousses (this study): pink circle and Argentera (Bigot-Cormier et al., 2002): grey square.<br><br><br>",mds,True,findable,0,0,0,0,0,2021-03-15T15:40:01.000Z,2021-03-15T15:40:01.000Z,figshare.ars,otjm,"40312 Structural Geology,FOS: Earth and related environmental sciences,Geology,40399 Geology not elsewhere classified","[{'subject': '40312 Structural Geology', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Geology'}, {'subject': '40399 Geology not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}]",['1526061 Bytes'],
+10.6084/m9.figshare.22609319.v1,Additional file 1 of TRansfusion strategies in Acute brain INjured patients (TRAIN): a prospective multicenter randomized interventional trial protocol,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Supplemental Table 1. List of participating centers.,mds,True,findable,0,0,0,0,0,2023-04-13T11:34:54.000Z,2023-04-13T11:34:54.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Neuroscience,Biotechnology,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['20300 Bytes'],
+10.5281/zenodo.4964227,"FIGURE 41 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURE 41. Biotope of Protonemura pennina sp. n. (Trovinasse, near Mambarone lake)",mds,True,findable,0,0,3,0,0,2021-06-16T08:25:53.000Z,2021-06-16T08:25:55.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5061/dryad.6171j,Data from: Reconstructing long-term human impacts on plant communities: an ecological approach based on lake sediment DNA,Dryad,2015,en,Dataset,Creative Commons Zero v1.0 Universal,"Paleoenvironmental studies are essential to understand biodiversity changes over long timescales and to assess the relative importance of anthropogenic and environmental factors. Sedimentary ancient DNA (sedaDNA) is an emerging tool in the field of paleoecology and has proven to be a complementary approach to the use of pollen and macroremains for investigating past community changes. SedaDNA-based reconstructions of ancient environments often rely on indicator taxa or expert knowledge, but quantitative ecological analyses might provide more objective information. Here, we analysed sedaDNA to investigate plant community trajectories in the catchment of a high-elevation lake in the Alps over the last 6400 years. We combined data on past and present plant species assemblages along with sedimentological and geochemical records to assess the relative impact of human activities through pastoralism, and abiotic factors (temperature and soil evolution). Over the last 6400 years, we identified significant variation in plant communities, mostly related to soil evolution and pastoral activities. An abrupt vegetational change corresponding to the establishment of an agropastoral landscape was detected during the Late Holocene, approximately 4500 years ago, with the replacement of mountain forests and tall-herb communities by heathlands and grazed lands. Our results highlight the importance of anthropogenic activities in mountain areas for the long-term evolution of local plant assemblages. SedaDNA data, associated with other paleoenvironmental proxies and present plant assemblages, appear to be a relevant tool for reconstruction of plant cover history. Their integration, in conjunction with classical tools, offers interesting perspectives for a better understanding of long-term ecosystem dynamics under the influence of human-induced and environmental drivers.",mds,True,findable,608,130,1,1,0,2015-03-03T17:07:50.000Z,2015-03-03T17:07:51.000Z,dryad.dryad,dryad,"Anthropocene,Pastoralism,Landscape history,Holocene,Viridiplantae","[{'subject': 'Anthropocene'}, {'subject': 'Pastoralism'}, {'subject': 'Landscape history'}, {'subject': 'Holocene'}, {'subject': 'Viridiplantae'}]",['262448213 bytes'],
+10.5281/zenodo.4625676,peanut,Zenodo,2021,,Software,"MIT License,Open Access",Experiment engine for Grid5000,mds,True,findable,0,0,1,0,0,2021-03-21T16:53:16.000Z,2021-03-21T16:53:17.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6104368,Unique and shared effects of local and catchment predictors over distribution of hyporheic organisms: does the valley rule the stream?,Zenodo,2022,,Software,"MIT License,Open Access","This dataset describe the distribution of two hyporheic crustacean taxa (Bogidiellidae, Amphipoda and Anthuridae, Isopoda) in streams of New Caledonia. We sampled the two taxa at 228 sites. At each site, we quantified nine local predictors related to habitat area and stability, sediment metabolism and water origin, and eight catchment predictors related to geology, area, primary productivity, land use and specific discharge.",mds,True,findable,0,0,0,0,0,2022-02-17T19:47:15.000Z,2022-02-17T19:47:16.000Z,cern.zenodo,cern,"spatial scale,hyporheic zone,subterranean crustaceans,New Caledonia,Bogidiellidae,Amphipoda,Anthuridae,Isopoda,local,catchment","[{'subject': 'spatial scale'}, {'subject': 'hyporheic zone'}, {'subject': 'subterranean crustaceans'}, {'subject': 'New Caledonia'}, {'subject': 'Bogidiellidae'}, {'subject': 'Amphipoda'}, {'subject': 'Anthuridae'}, {'subject': 'Isopoda'}, {'subject': 'local'}, {'subject': 'catchment'}]",,
+10.57745/ywbdqq,"Transcriptions des brouillons du roman ""La Réticence"" de Jean-Philippe Toussaint",Recherche Data Gouv,2022,,Dataset,,"Les brouillons tapuscrits et annotés de la Réticence (Jean-Philippe Toussaint, Éditions de minuit, 1991) ont été confié par leur auteur à l’UMR Litt (UMR 5316 – Arts et pratiques du texte, de l’image, de l’écran et de la scène – Université Grenoble Alpes / CNRS), sous la responsabilité scientifique de Brigitte Ferrato-Combe. Réunissant la totalité des documents préparatoires du roman, depuis les premières notes jusqu’aux épreuves et correspondances avec l’éditeur, ce fonds d’archives se révèle particulièrement intéressant pour les études littéraires, stylistiques ou génétiques. Ces brouillons ont été numérisés par le Service Interuniversitaire de Documentation de l’Université Grenoble Alpes où ils ont été momentanément conservés, et font l’objet d’une transcription sur la plateforme collaborative TACT, opération indispensable pour leur donner une pleine lisibilité et permettre les analyses ou recherches automatiques sur le texte. Le schéma de transcription a été élaboré à partir d’XML-TEI avec des choix de balisage assez simples, qui pourront être enrichis ultérieurement. La transcription reproduit à l’identique le texte tapuscrit, en respectant la mise en page (alinéas, retours à la ligne, saut de ligne). Les erreurs éventuelles (orthographe, syntaxe, ponctuation, fautes de frappe) ne sont pas corrigées. Les annotations manuscrites, très nombreuses, sont déchiffrées (dans la limite de la lisibilité) et transcrites, avec un code couleur et une police de caractère permettant de les distinguer du texte tapé. Leur situation dans la page n’est pas reproduite à l’identique ; la diversité des emplacements a été réduite à deux cas de figure : Les ajouts dont l’emplacement dans le texte est clairement défini sur le brouillon sont transcrits au point d’insertion au-dessus du texte tapé (même lorsque leur longueur a contraint l’auteur à les écrire en marge et à les relier par une flèche) Les annotations marginales dont l’emplacement dans le texte n’est pas précisé sont transcrites en bas de la page. Le balisage a été limité à trois fonctions essentielles : Structuration du texte : identification du numéro figurant sur le feuillet, délimitation des paragraphes. Description précise des ratures, déplacements, soulignements, mises en relief, ajouts manuscrits.. Repérage des entités nommées : noms propres de personne ou de lieu (Biaggi, Sasuelo, etc.) noms communs correspondants à des personnages du texte (l’enfant, le chat, l’hôtelier, le pêcheur, etc. ). Les numérisations des fac-simile sont disponibles sur l’entrepôt Nakala, porté par la TGIR TGIR Huma-Num (lien vers l’entrepôt) La ressource contient aussi les feuilles de transformation XSLT qui permettent de transformer la transcription XML en HTML. Elle sont utilisées pour construire le site qui expose les fac-similés et leur transcription (exemple) ainsi que des expérimentations (exemple).",mds,True,findable,251,32,0,0,0,2022-06-22T12:23:30.000Z,2022-07-08T09:02:24.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.1462854,The Fharvard corpus,Zenodo,2018,fr,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access","The Fharvard corpus is a collection of 700 sentences in French, phonetically balanced into 70 lists of 10 sentences each. Each sentence contains 5 keywords for scoring. A detailed presentation and evaluation of this dataset can be found at: https://doi.org/10.1016/j.specom.2020.07.004 The list of sentences is contained in the file <strong>The Fharvard corpus.pdf</strong> with keywords in bold. The phonetic transcription is provided in <strong>The Fharvard corpus - phonetic.txt</strong>. The <em>ortho</em> column contains the orthographic representation of the sentence with keywords in capital letters. The <em>phono</em> column contains the phonetic representation in SAMPA coding, with words separated by two successive space characters. Note that the phonetic representation is provided on an individual word basis, that is, discarding word-to-word liaisons. This is to provide an unambiguous basis for phonetic balancing at the keyword level, as the realisation of some liaisons can vary from talker to talker. Audio recordings of the Fharvard sentences spoken by a female and a male talker are contained in the .zip archive files, and available with a 44.1 kHz and 16 kHz sampling rate. A sample sentence for the female and the male talker is also attached.",mds,True,findable,0,0,0,0,0,2018-10-30T15:23:07.000Z,2018-10-30T15:23:08.000Z,cern.zenodo,cern,"French,Speech in Noise,Speech Intelligibility","[{'subject': 'French'}, {'subject': 'Speech in Noise'}, {'subject': 'Speech Intelligibility'}]",,
+10.5281/zenodo.8314813,"Supplementary data for ""Ecological assessment of combined sewer overflow management practices through the analysis of benthic and hyporheic sediment bacterial assemblages of an intermittent stream""",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","<strong>Supplementary data for the Pozzi <em>et al.</em> paper entitled ""Ecological assessment of combined sewer overflow management practices through the analysis of benthic and hyporheic microbial assemblages and a tracking of exogenous bacterial taxa in a peri-urban intermittent stream"".</strong> # Created by Dr Adrien C. MEYNIER POZZI on June, 29th, 2023<br> # Part of DOmic research project funded by the Agence de l’Eau - Rhône Méditerranée Corse [AE-RMC, Project 2020 0702 DOmic, 2020-2023], and of the DOmic extension funded by the EUR H2O'Lyon [ANR-17-EURE-0018] of Université de Lyon<br> # Part of the Chaudanne river long-term experiment site belonging to the Observatoire de Terrain en Hydrologie Urbaine (OTHU)<br> # Part of the work conducted in the team on Opportinistic Bacterial Pathogen in the Environment (BPOE) led by Dr. Benoit Cournoyer<br> # Samples were obtained in 2 campaigns, corresponding to periods before (2010-2011) or after (2018) the implementation of the 91/271/EEC European Directive that limited Combined-Sewer Overflow (CSO) discharges to the Chaudanne river<br> # Samples consisted in surface water, benthic and hyporheic sediments taken in run, riffle and pool geomorphologic features, either upstream or downstream the CSO outlet, plus positive and negative controls <strong>Metadata. Name and description of data tables provided as supplementary information</strong> <strong>Data Name</strong> <strong>Description</strong> Data S1. River hydrology variables and hydraulic gradients at surveyed transects Array to describe the hydrologic variables and gradients at the studied transects. Top line is header, second line is metadata for each recorded variable, and third line is the unit of the variable, if any. Data S2. Environmental variables (water physical-chemistry, nutrients, FIBs, MTEs, PAHs) with metadata An array to list environmental variables for all true samples (n=90) included in the study. Sample identifiers and dates are provided. First 8 rows list the CAS number, SANDRE number, unit, method, limit of quantification and norm for each variable, if any. Data S3. Hydrological indices and synthetic variables computed with ClustOfVar Hydrological indices computed for the river flow, precipitations and CSO overflows computed over a 3-week period preceding each sampling date. Data S4. Discharge events selected to compute CSO dilution ratios An array to describe CSO events included for the computation of the CSO dilution ratio (SI Data 6A) together with 6 tables and 3 figures (SI Data 6B to 6J) describing the CSO event ratio all year round over the studied period, as well as for events that occurred before or after the CSO was modified and during low flow or high flow season. In SI Data 6A, top line is header and second line is metadata for each recorded variable. Data S5. Raw environmental matrix for use in R An array to list experimental design and environmental variables for all true samples and controls. Several environmental variables were synthetized using the ClustOfVar method (Chavent et al (2012) 10.18637/jss.v050.i13). Format is directly usable in R software.",mds,True,findable,0,0,0,0,0,2023-09-04T10:16:14.000Z,2023-09-04T10:16:14.000Z,cern.zenodo,cern,"intermittent stream,fluvial geomorphology,hydrology,microbiology,chemical pollutants,Combined-Sewer Overflow","[{'subject': 'intermittent stream'}, {'subject': 'fluvial geomorphology'}, {'subject': 'hydrology'}, {'subject': 'microbiology'}, {'subject': 'chemical pollutants'}, {'subject': 'Combined-Sewer Overflow'}]",,
+10.5281/zenodo.10080490,PxCorpus : A Spoken Drug Prescription Dataset in French for Spoken Language Understanding and Dialogue,Zenodo,2023,fr,Audiovisual,Creative Commons Attribution 4.0 International,"PxCorpus : A Spoken Drug Prescription Dataset in French
+Â
+PxCorpus is to the best of our knowledge, the first spoken medical drug prescriptions corpus to be distributed.
+It contains 4 hours of transcribed and annotated dialogues of drug prescriptions in French acquired through an experiment with 55 participants experts and non-experts  in drug prescriptions.
+Â
+The automatic transcriptions were verified by human effort and aligned with semantic labels to allow training of NLP models. The data acquisition protocol was reviewed by medical experts and permit free distribution without breach of privacy and regulation.
+Â
+Overview of the Corpus
+The experiment has been performed in wild conditions with naive participants and medical experts.
+In total, the dataset includes 2067 recordings of 55 participants (38% non-experts, 25% doctors, 36% medical practitioners), manually transcribed and semantically annotated.
+Â
+| Category       | Sessions | Recordings | Time(m)|
+|-----------------------| ------------- | --------------- | ----------- |
+| Medical experts  |   258    |    434    |   94.83  |
+| Doctors        |   230    |    570    |  105.21  |
+| Non experts     |   415    |    977    |   62.13  |
+| Total          |   903    |    1981    |  262.27  |
+Â
+License
+We hope that that the community will be able to benefit from the dataset which is distributed with an attribution 4.0 International (CC BY 4.0) Creative Commons licence.
+Â
+How to cite this corpus
+Â
+If you use the corpus or need more details please refer to the following paper: A spoken drug prescription datset in French for spoken Language Understanding
+Â
+@InProceedings{Kocabiyikoglu2022,
+ author =  ""Alican Kocabiyikoglu and Fran{\c c}ois Portet and Prudence Gibert and Hervé Blanchon and Jean-Marc Babouchkine and Gaëtan Gavazzi"",
+Â title = Â ""A spoken drug prescription datset in French for spoken Language Understanding"",
+Â booktitle = Â ""13th Language Ressources and Evaluation Conference (LREC 2022)"",
+Â year = Â ""2022"",
+Â location = Â ""Marseille, France""
+}
+a more complete description of the corpus acquisition is available on arxivÂ
+@misc{kocabiyikoglu2023spoken,
+Â Â Â title={Spoken Dialogue System for Medical Prescription Acquisition on Smartphone: Development, Corpus and Evaluation},
+   author={Ali Can Kocabiyikoglu and François Portet and Jean-Marc Babouchkine and Prudence Gibert and Hervé Blanchon and Gaëtan Gavazzi},
+Â Â Â year={2023},
+Â Â Â eprint={2311.03510},
+Â Â Â archivePrefix={arXiv},
+Â Â Â primaryClass={cs.CL}
+}
+Â
+Project Structure
+Â
+The project contains the following elements
+.
+├── LICENSE
+├── PxDialogue/
+├── PxSLU/
+├── readme.md
+Â
+PxSLU : Prescription Corpus for Spoken Language Understanding
+Â
+Directory Structure
+.
+├── LICENSE
+├── metadata.txt
+├── paths.txt
+├── PxSLU_conll.txt
+├── readme.md
+├── recordings
+├── seq.in
+├── seq.label
+├── seq.out
+├── Demo.ipynb
+└── verifications.py
+Â
+Recordings
+Â
+The recordings directory contains the 903 recording sessions. Each session can contain several recordings. For instance,
+the directory
+Â Â recordings/J7aVvWb67L
+contains the records  Â
+  recording_0.wav  recording_2.wav
+which represent two attempts to record a drug prescription
+Â
+All records are stored as mono channel wav files of 16kHz 16bits signed PCM
+Â
+Paths
+Â
+contains the list of all the .wav files in the recordings directory
+00MYcyVK0t/recording_0.wav
+00MYcyVK0t/recording_2.wav
+02Qp6ICj9Q/recording_0.wav
+02Qp6ICj9Q/recording_1.wav
+...
+Â
+All other files (metadata.txt, seq.*) refer to this list to describe the recording.
+Â
+Metadata
+Â
+contains the information about the participants:
+Â
+48,60+,F,non-expert
+48,60+,F,non-expert
+24,18–28,F,doctor
+24,18–28,F,doctor
+...
+Â
+The first column is the participant unique id, the second is the age range, the third is the gender and the final is the category of the participant in {doctor,expert, non-expert}. doctor correspond to a physician, (other)expert to a pharmacist or a biologist specialized in drugs while non-expert are other people not entering in these categories. The lines are synchronised with the paths.txt lines.
+Â
+Labels
+Â
+the three files seq.label, seq.in, seq.out represent respectivly the intent, the transcript and the entities in BIO format.
+Â
+   seq.label        |         seq.in                 |               seq.out
+medical_prescription | flagyl 500 milligrammes euh qu/ en... | B-drug B-d_dos_val B-d_dos_up O O ...
+medical_prescription |  3 comprimés par jour matin midi ...  | B-dos_val B-dos_uf O O B-rhythm_tdte B-rhythm_tdte O B-rhythm_tdte ...
+Â Â Â Â Â Â Â ... Â Â Â Â Â Â Â Â | Â Â Â Â Â Â Â Â Â Â Â Â Â Â ... Â Â Â Â Â Â Â Â Â Â Â Â Â Â | Â Â Â Â Â Â Â Â Â Â Â Â Â Â ...
+Â
+These lines are synchronised with the paths.txt lines.
+Â
+Another file ""PxSLU_conll.txt"" is provided in a format inspired by the conll format (https://universaldependencies.org/format.html). However, this one is *not* aligned with the acoustic records file paths.txt.
+Â
+Scripts
+Â
+verifications.py performs the checking of the alignement of all the seq.* paths.txt and metadata files. A user of the dataset does not need to use this script unless she plan to extend the datasets with her own data.
+Demo.ipynb is a jupyter notebook that a user can run to search through the dataset. It is intended to let the user have a quicker and smoother view on the dataset.
+Â
+Â
+Data splits
+In the data_splits folder, you can find a data split of this dataset organized as following:
+- train.txt: medical experts + non experts (80%) = 1128 samples
+- dev.txt: medical experts + non experts (20%) = 283 samples
+- test.txt: doctors (100%) = 570 samples
+Â
+Each file contains references to line numbers of the corpus. For example, first line of the test.txt is 904, seq.in file contains the utterance ""nicopatch"". Users can access the labels, slots, metadata using the same line number 904 in the parallel files (paths.txt,seq.out,seq.label,...).
+Â
+PxDialogue : Prescription recording corpus for dialogue systems
+Â
+PxDialogue corpus comes as an extension of the PxSLU corpus and provides additional information about the dialogues that was collected through spoken dialogue. This corpus includes two additional files:
+├── events.txt
+├── dialogue_annotations.txt
+Â
+Â
+Events.txt:
+Â
+For each dialogue session, all dialogue events are given in this text file
+which can be used to train/evaluate dialogue systems.
+Â
+Usage example:
+Â
+PxSLU (paths.txt)
+- 00MYcyVK0t/recording_0.wav
+- 00MYcyVK0t/recording_2.wav
+Â
+PxDialogue (events.txt)
+- (-1, 'START', 'APP', None, 0) (1, 'user', 'ASR', 'flagyl 500 mg en cachet pendant 8 jours', 30) (1, 'system', 'TTS', 'Choisissez le médicament correspondant à votre recherche', 34) (2, 'user', 'UI', 'listview_item_clicked', 40) (2, 'system', 'TTS', 'Pourriez vous préciser la posologie pour le patient?', 40) (3, 'user', 'ASR', '3 comprimés par jour matin midi et soir pendant 10 jours', 64) (3, 'system', 'TTS', ""Est-ce que vous confirmez l'ajout de cette prescription sur la liste?"", 66) (4, 'user', 'UI', '/inform{""validate"":""validate""}', 73) (4, 'system', 'TTS', 'Prescription validée avec succès. Traitement ajouté sur le dossier du patient', 73) (-1, 'END', 'APP', '', 73)
+- N/A
+Â
+For example, in this dialogue session (00MYcyVK0t), there are two recordings.
+The events are given in a single row for each dialogue session once in the
+first recording (recording_0). Dialogues are described in form of events
+where each action taken by the user or the system is considered as a dialogue
+turn in a tuple form.
+Â
+(-1, 'START', 'APP', None, 0)
+Â
+- First element of the event is the dialogue turn number. -1 means that the application
+is initialized.
+- Second element describes who initiated the event: user, system, START, END
+- Third element describes the type of the event: APP (start and end events)
+, ASR (automatic speech recognition), TTS (text-to-speech), UI (user interface)
+User clicks on buttons triggers sometimes explicit intent recognition. For
+example (4, 'user', 'UI', '/inform{""validate"":""validate""}') describes the
+explicit intent of validation of the prescription.
+- Fourth element is the timestamp (in seconds)
+Â
+Dialogue annotations
+Â
+We also include a manual annotation for dialogues (dialogue_annotations.txt) which indicates for each recording, if the system gave the correct answer given the utterance.
+Â
+Each line contains a keyword, either [Fail] or [OK]. The following example shows a dialogue sample with annotations:
+Â
+| dialogue_annotations.txt |  paths.txt                 | seq.in                                               |
+|----------------------------------|----------------------------------------|--------------------------------------------------------------------------------------|
+| OK                  | 14yHtAe555/recording_0.wav | oxytetracycline solution euh                              |
+| OK Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â | 14yHtAe555/recording_1.wav | oxytetracycline solution 5 gouttes matin et soir pendant 14 jours |
+| Fail                  | 14yHtAe555/recording_2.wav | oxytetracycline solution 5 gouttes matin et soir pendant 14 jours |
+Â
+For these 3 dialogues, the dialogue annotations are accordingly OK, OK and Fail.
+[Ok] means that the dialogue system reacted correctly to the input.
+[Fail] means that the action of the system after this utterance should not be used
+for evaluation or training. Â
+We can notice that in the first utterance, the information are missing, however
+after the second example the system normally have all of the required slots
+for the prescription validation.
+Â
+It is to note that free comments added using the ASR system were noted as
+Fail as these dialogues did not enter the dialogue state tracking. In this
+example, the last utterance is recorded as a free comment by the prescriber
+and was annotated as Fail.
+Â
+Linking audio records to ASR events
+In order to link audio records to ASR events, the user has to use both paths.txt and events.txt
+Â
+For example for the following dialogue session (lines 1:2 of paths.txt):
+00MYcyVK0t/recording_0.wav
+00MYcyVK0t/recording_2.wav
+Â
+Events.txt include two ASR events:
+(1, 'user', 'ASR', 'flagyl 500 mg en cachet pendant 8 jours', 30)
+(3, 'user', 'ASR', '3 comprimés par jour matin midi et soir pendant 10 jours', 64)
+Â
+These ASR events corresponds to the recording files that can be found in the recordings folder.
+Â
+Available user action annotations
+Â
+Events.txt include annotations such as below with the following explanation:
+Â
+- /inform{""validate"":""validate""} : User clicks on the validate button after seeing the prescription
+- /inform{""validate"":""refuse""} : User clicks on the refuse button after seeing the prescription
+- ASR : User clicks on the push-to-talk button to record an utterance
+- listview_item_clicked : User clicks on the list to choose a drug
+- listview_cancel_clicked : User clicks on the cancel button after seeing a list of drugs
+- FREE_COMMENT_ADDED : User clicks and records a free-form utterance by clicking ""add free comment"" button
+- EMPTY_UTTERANCE: Recording containing an empty utterance
+- APP_CRASH : An application crash that happened in the dialogue turn
+- EVAL_FINISH_APPROVED : User clicks on the final upload button to finish the experiment
+- RESTART_CONVERSATION_SESSION : User clicks on the restart conversation button
+- RESTART_CANCEL_CLICKED : User cancels the restart process by clicking on the cancel button
+- EVAL_FINISH_CANCELED : User cancels the final upload process by clicking on the cancel button
+Â
+** Free Comments: **
+The users had the possibility of recording a speech-to-text message upon viewing a prescription.
+These messages had not beed added to the dialogue state tracking but were visualized on the interface and saved in
+the database. Users can find free comments by searching for FREE_COMMENT_ADDED events in the events.txt to find out
+about these events.",api,True,findable,0,0,0,0,0,2023-11-08T07:53:40.000Z,2023-11-08T07:53:40.000Z,cern.zenodo,cern,"speech corpora,health informatics,biomedical nlp,spoken dialogue systems,natural language understanding","[{'subject': 'speech corpora'}, {'subject': 'health informatics'}, {'subject': 'biomedical nlp'}, {'subject': 'spoken dialogue systems'}, {'subject': 'natural language understanding'}]",,
+10.5281/zenodo.7928420,A climatological study of heat waves in Grenoble over the 21st century,Zenodo,2022,en,Other,"Creative Commons Attribution 4.0 International,Open Access","We investigate heat waves (HWs) affecting the valley of Grenoble in a future climate. In this study, heat waves are defined as periods of at least 3 consecutive days of daily maximum and minimum temperature exceeding the 92nd historical percentile. This definition has been chosen to select HWs that might impact human health. Even though only the strongest HWs are potentialy harmful, the definition allows to identify a suficient number of events to perform a statistical study. The HWs are characterised by their duration, peak temperature and mean daily maximum temperature. Additionally, each HW is studied per year using a framework measuring heat wave number, duration, participating days, and the peak and mean magnitudes. The HW characteristics are calculated with the results of simulations from the regional climate model MAR. MAR was forced by reanalysis and by a global model for the entire 21st century. The uncertainty of future anthropogenic forcing is taken into account by analysing results for the shared socio-economic pathways SSP2 and SSP5. The simulations are evaluated against in-situ measurements in the past period. MAR captures well daily maximum and minimum temperatures as well as observed HWs. Under future climate conditions, the increase in very hot daily maximum and minimum temperatures is mainly due to the shift rather than the broadening of their probability density functions. Additionally, the HWs become more frequent and have a longer duration, higher peak temperature and mean daily maximum temperature. Finally, a sensitivity analysis to the HW de ning threshold is carried out.",mds,True,findable,0,0,0,0,0,2023-05-12T08:33:13.000Z,2023-05-12T08:33:13.000Z,cern.zenodo,cern,"Regional Climate Change,Heatwaves,Grenoble Valley,Climate Data Analysis","[{'subject': 'Regional Climate Change'}, {'subject': 'Heatwaves'}, {'subject': 'Grenoble Valley'}, {'subject': 'Climate Data Analysis'}]",,
+10.5281/zenodo.4543403,Khöömii Mongol: diversité des styles et des techniques de l'art diphonique,Zenodo,2021,,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access","Illustrations audiovisuelles de l'article ""<em>Khöömii</em> Mongol: diversité des styles et des techniques de l’art diphonique"", par Johanni Curtet, Nathalie Henrich Bernardoni, Michèle Castellengo, Christophe Savariaux, Pascale Calabrese, Actes des Rencontres Nationales sur les Recherches en Musique, 2021",mds,True,findable,0,0,0,0,0,2021-02-16T13:41:10.000Z,2021-02-16T13:41:11.000Z,cern.zenodo,cern,"diphonic singing,mongolian Khöömii","[{'subject': 'diphonic singing'}, {'subject': 'mongolian Khöömii'}]",,
+10.5281/zenodo.5373494,"FIG. 5. — A in Le gisement paléontologique villafranchien terminal de Peyrolles (Issoire, Puy-de-Dôme, France): résultats de nouvelles prospections",Zenodo,2006,,Image,"Creative Commons Zero v1.0 Universal,Open Access","FIG. 5. — A', A'', fragment de bois gauche(?) de chute (Pey2 97 001) d'un jeune individu d'Eucladoceros cf. tetraceros en vue interne; A', le spécimen comme il a été trouvé sur le terrain: en noir, la partie du bois préservée et recueillie (voir A''), en rayures, l'empreinte de la fourche terminale; B, dents supérieures gauches d'Eucladoceros cf. tetraceros (Pey JLP 14) en vue occlusale; C, fragment de bois droit de massacre de « Cervus » perolensis (Pey JLP 18) en vue latérale; D, fragment de bois gauche de massacre de « Cervus » perolensis (Pey 18 JBC) en vue latérale. Échelles: 5 cm.",mds,True,findable,0,0,0,0,0,2021-09-02T04:40:37.000Z,2021-09-02T04:40:38.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.7941767,"Supplementary to ""A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion and settlement in dry snow (IvoriFEM v0.1.0)""",Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,"This folder contains the source code of the homemade python-based finite-element model at the version used to generate the results of (to be submitted) ""A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion and settlement in dry snow"".
+
+
+For setting up the environment and running the simulations, please follow the instructions described in the README file. We highly recommend that potential future users and developers access the code from its Git repository (https://github.com/jbrondex/ivori_model_homemadefem, last access: 16 May 2023) to benefit from the last version of the code. The version which has been saved here is tagged v0.1.0.",mds,True,findable,0,0,0,0,0,2023-05-16T15:37:56.000Z,2023-05-16T15:37:57.000Z,cern.zenodo,cern,"snow modeling,heat conduction in snow,vapor diffusion in snow","[{'subject': 'snow modeling'}, {'subject': 'heat conduction in snow'}, {'subject': 'vapor diffusion in snow'}]",,
+10.6084/m9.figshare.c.6756888,Flexible optical fiber channel modeling based on a neural network module,Optica Publishing Group,2023,,Collection,Creative Commons Attribution 4.0 International,"Optical fiber channel modeling which is essential in optical transmission system simulations and designs is usually based on the split-step Fourier method (SSFM), making the simulation quite time-consuming owing to the iteration steps. Here, we train a neural network module termed by NNSpan to learn the transfer function of one single fiber (G652 or G655) span with a length of 80km and successfully emulate long-haul optical transmission systems by cascading multiple NNSpans with a remarkable prediction accuracy even over a transmission distance of 1000km. Although training without erbium-doped fiber amplifier (EDFA) noise, NNSpan performs quite well when emulating the systems affected by EDFA noise. An optical bandpass filter can be added after EDFA optionally, making the simulation more flexible. Comparison with the SSFM shows that the NNSpan has a distinct computational advantage with the computation time reduced by a factor of 12. This method based on the NNSpan could be a supplementary option for optical transmission system simulations, thus contributing to system designs as well.",mds,True,findable,0,0,0,0,0,2023-08-10T20:33:33.000Z,2023-08-10T20:33:33.000Z,figshare.ars,otjm,Uncategorized,[{'subject': 'Uncategorized'}],,
+10.5281/zenodo.10005463,"Data for the paper: ""Folding a Cluster containing a Distributed File-System""",Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"Associated paper: https://hal.science/hal-04038000
+The repository containing the analysis scripts is available here
+
+NFS repo
+OrangeFS repo",api,True,findable,0,0,0,0,0,2023-10-15T23:10:52.000Z,2023-10-15T23:10:53.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7056694,Companion data for Communication-Aware Load Balancing of the LU Factorization over Heterogeneous Clusters,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is the companion data repository for the paper entitled <strong>Communication-Aware Load Balancing of the LU Factorization over Heterogeneous Clusters</strong> by Lucas Leandro Nesi, Lucas Mello Schnorr, and Arnaud Legrand. The manuscript has been accepted in the ICPADS 2020.",mds,True,findable,0,0,0,0,0,2022-09-07T08:36:26.000Z,2022-09-07T08:36:27.000Z,cern.zenodo,cern,,,,
+10.34847/nkl.a0db89n9,"Extraits audio Inharmonique (1977, 2019), Les cris sixième cercle (2019), Dans la nef de nos songes (2019), TêTrês (2001)",NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,,Sound,,,api,True,findable,0,0,0,0,0,2023-09-10T16:13:44.000Z,2023-09-10T16:13:44.000Z,inist.humanum,jbru,"Jean-Claude Risset,Composition musicale,analyse musicale","[{'lang': 'fr', 'subject': 'Jean-Claude Risset'}, {'lang': 'fr', 'subject': 'Composition musicale'}, {'lang': 'fr', 'subject': 'analyse musicale'}]","['6014630 Bytes', '2584436 Bytes', '448469 Bytes', '226950 Bytes', '10487966 Bytes', '3745840 Bytes', '8116646 Bytes', '4800736 Bytes', '350248 Bytes', '11090282 Bytes', '6877526 Bytes', '17959616 Bytes', '3605894 Bytes', '2584436 Bytes', '346069 Bytes', '484413 Bytes', '204381 Bytes']","['audio/x-wav', 'audio/x-wav', 'audio/mpeg', 'audio/mpeg', 'audio/x-wav', 'audio/x-wav', 'audio/x-wav', 'audio/x-wav', 'audio/mpeg', 'audio/x-wav', 'audio/x-wav', 'audio/x-wav', 'audio/x-wav', 'audio/x-wav', 'audio/mpeg', 'audio/mpeg', 'audio/mpeg']"
+10.6084/m9.figshare.c.6592858.v1,Critically ill severe hypothyroidism: a retrospective multicenter cohort study,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Severe hypothyroidism (SH) is a rare but life-threatening endocrine emergency. Only a few data are available on its management and outcomes of the most severe forms requiring ICU admission. We aimed to describe the clinical manifestations, management, and in-ICU and 6-month survival rates of these patients. Methods We conducted a retrospective, multicenter study over 18 years in 32 French ICUs. The local medical records of patients from each participating ICU were screened using the International Classification of Disease 10th revision. Inclusion criteria were the presence of biological hypothyroidism associated with at least one cardinal sign among alteration of consciousness, hypothermia and circulatory failure, and at least one SH-related organ failure. Results Eighty-two patients were included in the study. Thyroiditis and thyroidectomy represented the main SH etiologies (29% and 19%, respectively), while hypothyroidism was unknown in 44 patients (54%) before ICU admission. The most frequent SH triggers were levothyroxine discontinuation (28%), sepsis (15%), and amiodarone-related hypothyroidism (11%). Clinical presentations included hypothermia (66%), hemodynamic failure (57%), and coma (52%). In-ICU and 6-month mortality rates were 26% and 39%, respectively. Multivariable analyses retained age > 70 years [odds ratio OR 6.01 (1.75–24.1)] Sequential Organ-Failure Assessment score cardiovascular component ≥ 2 [OR 11.1 (2.47–84.2)] and ventilation component ≥ 2 [OR 4.52 (1.27–18.6)] as being independently associated with in-ICU mortality. Conclusions SH is a rare life-threatening emergency with various clinical presentations. Hemodynamic and respiratory failures are strongly associated with worse outcomes. The very high mortality prompts early diagnosis and rapid levothyroxine administration with close cardiac and hemodynamic monitoring.",mds,True,findable,0,0,0,0,0,2023-04-13T14:55:40.000Z,2023-04-13T14:55:41.000Z,figshare.ars,otjm,"Medicine,Neuroscience,Pharmacology,Immunology,FOS: Clinical medicine,Cancer","[{'subject': 'Medicine'}, {'subject': 'Neuroscience'}, {'subject': 'Pharmacology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}]",,
+10.5281/zenodo.7254133,Preprocessed rat brain voxel time series,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Preprocessed version of voxel time-series for three rats, originally described in Becq et al., Functional connectivity is preserved but reorganized across several anesthetic regimes, NeuroImage, 2020. Used in Achard et al., Inter-regional correlation estimators for functional magnetic resonance imaging, arXiv, 2022, arXiv:2011.08269. The files named ""coord_ROI_x.txt"" contain the coordinates of the voxels inside region x (each line corresponds to one voxel). The files named ""ts_ROI_x.txt"" contain the BOLD signal time series of the voxels inside region x (each line corresponds to one voxel, each column to one timepoint). The voxels with time series equal to zero have been removed The files named ""weight_ROI_x.txt"" contain the weights associated with the voxels inside region x (each line corresponds to one voxel). Indeed, when assigning voxels to regions, some voxels end up at the border of several regions. These weights characterize the proportion of a given voxel present inside a given region. Hence, some voxels are included in several different regions. So when we compute the voxel-to-voxel inter-correlation between two regions we sometimes end up with inter-correlations equal to 1. In the current dataset this issue has been resolved and each voxel has been assigned to a single region.",mds,True,findable,0,0,0,0,0,2022-12-23T10:06:03.000Z,2022-12-23T10:06:03.000Z,cern.zenodo,cern,"fMRI,rodent,functional connectivity","[{'subject': 'fMRI'}, {'subject': 'rodent'}, {'subject': 'functional connectivity'}]",,
+10.5281/zenodo.10013098,"Data and code for the article "" Dissimilarity of vertebrate trophic interactions reveals spatial uniqueness but functional redundancy across Europe""",Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Research compendium to reproduce analyses and figures of the article: Dissimilarity of vertebrate trophic interactions reveals spatial uniqueness but functional redundancy across Europe by Gaüzère et al. published in Current Biology
+Pierre Gaüzère
+General
+This repository is structured as follow:
+
+data/: contains data required to reproduce figures and tables
+analyses/: contains scripts organized sequentially. A -> B -> C -> ..
+outputs/: follows the structure of analyses. Contains intermediate numeric results used to produce the figures
+figures_tables/: Contains the figures of the paper
+The analysis pipeline should be clear once opening the code. Contact me if needed but try before please.Â
+Figures & tables
+Figures will be stored in figures_tables/. Tables will be stored in outputs/.",api,True,findable,0,0,0,0,3,2023-10-17T09:29:24.000Z,2023-10-17T09:29:24.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4759503,"Figs. 46-51 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 46-51. Terminalias of the imago of Protonemura berberica Vinçon & S{nchez-Ortega, 1999. 46: male terminalia, dorsal view; 47: male terminalia, ventral view; 48: male terminalia, lateral view; 49: male paraproct, ventrolateral view; 50: female pregenital and subgenital plates, and vaginal lobes, ventral view; 51: female pregenital and subgenital plates, and vaginal lobes, lateral view (scales 0.5 mm; scale 1: Fig. 49, scale 2: Figs. 46-48, 50-51).",mds,True,findable,0,0,2,0,0,2021-05-14T02:25:40.000Z,2021-05-14T02:25:40.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.12378,xraylib 3.1.0,Zenodo,2014,,Software,"BSD licenses (New and Simplified),Open Access","Quantitative estimate of elemental composition by spectroscopic and imaging techniques using X-ray fluorescence requires the availability of accurate data of X-ray interaction with matter. Although a wide number of computer codes and data sets are reported in literature, none of them is presented in the form of freely available library functions which can be easily included in software applications for X-ray fluorescence. This work presents a compilation of data sets from different published works and an xraylib interface in the form of callable functions. Although the target applications are on X-ray fluorescence, cross sections of interactions like photoionization, coherent scattering and Compton scattering, as well as form factors and anomalous scattering functions, are also available. xraylib provides access to some of the most respected databases of physical data in the field of x-rays. The core of xraylib is a library, written in ANSI C, containing over 40 functions to be used to retrieve data from these databases. This C library can be directly linked with any program written in C, C++ or Objective-C. Furthermore, the xraylib package contains bindings to several popular programming languages: Fortran 2003, Perl, Python, Java, IDL, Lua, Ruby, PHP and .NET, as well as a command-line utility which can be used as a pocket-calculator. Although not officially supported, xraylib has been reported to be useable from within Matlab and LabView. The source code is known to compile and run on the following platforms: Linux, Mac OS X, Solaris, FreeBSD and Windows.<br> Development occurs on Github: http://github.com/tschoonj/xraylib<br> Downloads are hosted by the X-ray Micro-spectroscopy and Imaging research group of Ghent University: http://lvserver.ugent.be/xraylib Version 3.1.0 release notes: - Database of commonly used radionuclides for X-ray sources added (new API: GetRadioNuclideDataByName, GetRadioNuclideDataByIndex, GetRadioNuclideDataList and FreeRadioNuclideData)<br> - numpy Python bindings added, generated with Cython. Performance basically the same as the core C library. (suggested by Matt Newville)<br> - docstring support added to Python bindings (suggested by Matt Newville)<br> - Windows SDKs now have support for Python 3.4.<br> - Windows 64-bit SDK now comes with IDL bindings<br> - Confirmed support for LabView (thanks to Dariush Hampai!)<br> - Universal Intel 32/64 bit Framework built for Mac OS X<br> - Perl support for Debian/Ubuntu<br> - Several bugfixes: thanks to those that reported them!",mds,True,findable,0,0,2,0,0,2014-10-24T08:03:54.000Z,2014-10-24T08:03:55.000Z,cern.zenodo,cern,"xraylib,X-ray fluorescence,quantification,fundamental parameters,software library","[{'subject': 'xraylib'}, {'subject': 'X-ray fluorescence'}, {'subject': 'quantification'}, {'subject': 'fundamental parameters'}, {'subject': 'software library'}]",,
+10.5281/zenodo.6448390,"Dataset for the paper ""Imaging evolution of Cascadia slow‑slip event using high‑rate GPS""",Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Slip and slip rate files for the preferred model of Itoh, Aoki, and Fukuda (2022, Scientific Reports, doi:10.1038/s41598-022-10957-8). Please see readme.txt for further details. The corresponding author information is also available there. Caution: the dataset has the size of 4.3GB after uncompression/extraction.",mds,True,findable,0,0,0,1,0,2022-04-19T13:23:52.000Z,2022-04-19T13:23:56.000Z,cern.zenodo,cern,"Slow slip,SSE,Cascadia","[{'subject': 'Slow slip'}, {'subject': 'SSE'}, {'subject': 'Cascadia'}]",,
+10.57745/qoa1qo,Data on Terminological Semantic Variation between the (US and British) Press and UN Institutions in Climate Change Discourses,Recherche Data Gouv,2023,,Dataset,,"The data set contains three spreadsheets, two of them being displayed in one single Excel file. The first file, entitled « Cosine_Similarity_UN-Press », represents the cosine similarity scores between the UN version and the press version of the most specific and widely distributed « climate terms » shared by these two communities. The second file, entitled « Collocates_UN-Press » contains two spreadsheets which respectively compares the collocates of the terms « adaptation » and « energy security » between two corpora on climate change, one representing UN institutions and one representing the US and British press.",mds,True,findable,46,5,0,0,0,2023-04-07T14:16:05.000Z,2023-05-23T12:32:05.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.7499383,"Trajectory files for ""Where does the energy go during the interstellar NH3 formation on water ice? A computational study""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","CP2K trajectory files for the N+H, NH + H and NH2 + H reactions on the amorphous water ice surface",mds,True,findable,0,0,0,0,0,2023-01-02T15:10:54.000Z,2023-01-02T15:10:55.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4760499,"Figs. 17-20 in Contribution To The Knowledge Of The Moroccan High And Middle Atlas Stoneflies (Plecoptera, Insecta)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 17-20. Capnioneura atlasica sp. n. 17: male abdominal tip in dorsal view, 18: paraproct shaft and specillum, 19: male abdominal tip in lateral view, 20: male abdominal tip in ventral view. Figs. 21-22. Capnioneura petitpierreae. 21: paraproct shaft and specillum, 22: male abdominal tip in lateral view.",mds,True,findable,0,0,2,0,0,2021-05-14T05:27:46.000Z,2021-05-14T05:27:47.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Capniidae,Capnioneura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Capniidae'}, {'subject': 'Capnioneura'}]",,
+10.5281/zenodo.8101891,"Data and code for publication ""The stability of present-day Antarctic grounding lines - Part B""",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data and code for the publication ""The stability of present-day Antarctic grounding lines – Part B: Onset of irreversible retreat of Amundsen Sea glaciers under current climate on centennial timescales cannot be excluded"" in The Cryosphere. Zip files contain data, python notebooks for analysis and PISM code. Please contact ronja.reese@northumbria.ac.uk if you have any further questions.",mds,True,findable,0,0,0,2,0,2023-07-03T17:51:58.000Z,2023-07-03T17:51:58.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5723606,Classification of blood cells dynamics with convolutional and recurrent neural networks: a sickle cell disease case study,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The fraction of red blood cells (RBC) adopting a specific motion under low shear flow is a promising inexpensive marker for monitoring the clinical status of patients with sickle cell disease (SCD). Its high-throughput measurement relies on the video analysis of thousands of cell motions for each blood sample to eliminate a large majority of unreliable samples(out of focus or overlapping cells) and discriminate between tank-treading and flipping motion, characterizing highly and poorly deformable cells respectively. These videos are of different durations (from 6 to more than 100 frames). This dataset contains four adult patients with SCD. They were enrolled in the study Drepaforme (approved by the institutional review board CPP Ouest 6 under the reference n°2018A00679-46) and were sampled weekly for several months. The movies were processed using in-house routines in Matlab (Matlab, R2016a) and RBC were detected individually and tracked over time. The database provided in this repository are already pre-processed sequences of tracked and centered RBC over time, each time step image being normalized to 31x31 pixels. Within the 32 experiments, the total number of sequences (or samples) is nearly 150 000. All sequences were semi-automatically labelled into 3 classes, depending on the dynamic of the cell: tank-treading, flipping and unreliable (140 000 are unreliable). The percentage of tank-treading cells with respect to all reliable cells (tank-treading+flipping) in every experiment is the final goal of this study. This dataset is very interesting to the community as it is a large database for cell dynamics classification: the class depends on the movement of the cell. An automatic processing of the database using a 2-stage deep learning model is available here https://github.com/icannos/redbloodcells_disease_classification For opening the data in python: from scipy.io import loadmat<br> x=loadmat('BG20191003shear10s01_Export.mat') * x['Norm_Tab'] is of size nb_samples x max_len_sequences x 31 x 31, where max_len_sequences is the length of the longest sequence of the series, typically ~150 to 180. The other sequences are padded with 31x31 zero matrices at the end in order to fill this maximal length. * x['Labels_Num'] is the corresponding label of each sequence, of size nb_samples. Label can be:<br> - 0 : ""tank-treading"" (or healthy)<br> - 1 : ""flipping"" (or tumbling, i.e. related to a SCD)<br> - 2 : ""unreliable""",mds,True,findable,0,0,0,0,0,2021-11-24T10:21:40.000Z,2021-11-24T10:21:41.000Z,cern.zenodo,cern,"blood cell,cell dynamics,cell classification,cell motion","[{'subject': 'blood cell'}, {'subject': 'cell dynamics'}, {'subject': 'cell classification'}, {'subject': 'cell motion'}]",,
+10.5281/zenodo.8139775,High-end projections of Southern Ocean warming and Antarctic ice shelf melting in conditions typical of the end of the 23rd century,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>High-end projections of Southern Ocean warming and Antarctic ice shelf melting in conditions typical of the end of the 23rd century</strong> To evaluate the response of the Southern Ocean and Antarctic ice shelf cavities to an abrupt change to high-end atmospheric<br> conditions typical of the late 23rd century under the SSP5-8.5 scenario, in Mathiot and Jourdain (2023, submitted soon), we conducted 2 experiments. Our reference experiment (called REF) is driven by present day atmospheric condition. In the 23rd century simulation (called PERT), the present day atmospheric forcing is perturbed by the anomaly (2260-2299 minus 1975-2014) extracted from monthly outputs of the IPSL-CM6A-LR projections under the SSP5-8.5 emission scenario. REF is run over the latest 40 years and PERT is run for 100y starting from PERT at year 1999. This data set contains: The atmospheric forcing anomalies used to perturbed our reference atmospheric forcing in the PERT simulation; 30y monthly climatologies of multiple variables (ocean temperature, salinity, ssh, velocities, barotropic stream function, sea ice concentration, thickness, velocities and snow thickness) for PERT and REF. All the details on each dataset have been added in separated README in ATMO_ANOMALIES and OCEAN_CLIMATOLOGIES directory. As stated in each README, all the detailed on the simulations and atmospheric perturbation are available in Mathiot and Jourdain (2023, submitted soon).",mds,True,findable,0,0,0,0,0,2023-07-12T16:48:55.000Z,2023-07-12T16:48:56.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.m1t32,Data from: Phylogenomic analysis of the explosive adaptive radiation of the Espeletia complex (Asteraceae) in the tropical Andes,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"The subtribe Espeletiinae (Asteraceae) is endemic to the high-elevations in the Northern Andes. It exhibits an exceptional diversity of species, growth-forms and reproductive strategies, including large trees, dichotomous trees, shrubs and the extraordinary giant monocarpic or polycarpic caulescent rosettes, considered as a classic example of adaptation in tropical high-elevation ecosystems. The subtribe has long been recognised as a prominent case of adaptive radiation, but the understanding of its evolution has been hampered by a lack of phylogenetic resolution. Here we produce the first fully resolved phylogeny of all morphological groups of Espeletiinae, using whole plastomes and about a million nuclear nucleotides obtained with an original de novo assembly procedure without reference genome, and analysed with traditional and coalescent-based approaches that consider the possible impact of incomplete lineage sorting and hybridisation on phylogenetic inference. We show that the diversification of Espeletiinae started from a rosette ancestor about 2.3 Ma, after the final uplift of the Northern Andes. This was followed by two rather independent radiations in the Colombian and Venezuelan Andes, with a few trans-cordilleran dispersal events among low-elevation tree lineages but none among high-elevation rosettes. We demonstrate complex scenarios of morphological change in Espeletiinae, usually implying the convergent evolution of growth-forms with frequent loss/gains of various traits. For instance, caulescent rosettes evolved independently in both countries, likely as convergent adaptations to life in tropical high-elevation habitats. Tree growth-forms evolved independently three times from the repeated colonisation of lower elevations by high-elevation rosette ancestors. The rate of morphological diversification increased during the early phase of the radiation, after which it decreased steadily towards the present. On the other hand, the rate of species diversification in the best-sampled Venezuelan radiation was on average very high (3.1 spp/My), with significant rate variation among growth-forms (much higher in polycarpic caulescent rosettes). Our results point out a scenario where both adaptive morphological evolution and geographical isolation due to Pleistocene climatic oscillations triggered an exceptionally rapid radiation for a continental plant group.",mds,True,findable,349,79,0,1,0,2019-10-04T22:00:33.000Z,2019-10-04T22:00:34.000Z,dryad.dryad,dryad,"Espeletiinae,caulescent rosette,Páramo,tropical high-elevation,explosive diversification","[{'subject': 'Espeletiinae'}, {'subject': 'caulescent rosette'}, {'subject': 'Páramo'}, {'subject': 'tropical high-elevation'}, {'subject': 'explosive diversification'}]",['74332765 bytes'],
+10.5281/zenodo.3876188,Raw diffraction data for [NiFeSe] hydrogenase G491A variant pressurized with O2 gas - dataset G491A-O2-HD,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","Diffraction data measured at ESRF beamline ID30B on April 8, 2018. Image files are uploaded in blocks of gzip-compressed cbf files.",mds,True,findable,0,0,0,0,0,2020-06-04T10:15:53.000Z,2020-06-04T10:15:54.000Z,cern.zenodo,cern,"Hydrogenase,Selenium,gas channels,high-pressure derivatization","[{'subject': 'Hydrogenase'}, {'subject': 'Selenium'}, {'subject': 'gas channels'}, {'subject': 'high-pressure derivatization'}]",,
+10.5281/zenodo.7969515,"Dataset related to the study ""Spatial variability of Saharan dust deposition revealed through a citizen science campaign""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the data and the measurements related to the manuscript ""Spatial variability of Saharan dust deposition revealed through a citizen science campaign"", by Dumont et al., submitted in December 2022 to the journal ""Earth System Science Data"".",mds,True,findable,0,0,0,0,0,2023-05-25T08:28:52.000Z,2023-05-25T08:28:53.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4964223,"FIGURE 39 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,FIGURE 39. Distribution map of taxa belonging to the Protonemura auberti species complex in the Italian Alps,mds,True,findable,0,0,5,0,0,2021-06-16T08:25:45.000Z,2021-06-16T08:25:47.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5061/dryad.wpzgmsbp2,Assessing environmental DNA metabarcoding and camera trap surveys as complementary tools for biomonitoring of remote desert water bodies,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Biodiversity assessments are indispensable tools for planning and monitoring conservation strategies. Camera traps (CT) are widely used to monitor wildlife and have proven their usefulness. Environmental DNA (eDNA)-based approaches are increasingly implemented for biomonitoring, combining sensitivity, high taxonomic coverage and resolution, non-invasiveness and easiness of sampling, but remain challenging for terrestrial fauna. However, in remote desert areas where scattered water bodies attract terrestrial species, which release their DNA into the water, this method presents a unique opportunity for their detection. In order to identify the most efficient method for a given study system, comparative studies are needed. Here, we compare CT and DNA metabarcoding of water samples collected from two desert ecosystems, the Trans-Altai Gobi in Mongolia and the Kalahari in Botswana. We recorded with CT the visiting patterns of wildlife and studied the correlation with the biodiversity captured with the eDNA approach. The aim of the present study was threefold: a) to investigate how well waterborne eDNA captures signals of terrestrial fauna in remote desert environments, which have been so far neglected in terms of biomonitoring efforts; b) to compare two distinct approaches for biomonitoring in such environments and c) to draw recommendations for future eDNA-based biomonitoring. We found significant correlations between the two methodologies and describe a detectability score based on variables extracted from CT data and the visiting patterns of wildlife. This supports the use of eDNA-based biomonitoring in these ecosystems and encourages further research to integrate the methodology in the planning and monitoring of conservation strategies.",mds,True,findable,143,14,0,0,0,2021-12-29T01:12:54.000Z,2021-12-29T01:12:55.000Z,dryad.dryad,dryad,,,['1367382692 bytes'],
+10.5281/zenodo.1307653,Miccai 2016 Ms Lesion Segmentation Challenge: Supplementary Results,Zenodo,2018,en,Dataset,"Creative Commons Attribution 4.0,Open Access","This package contains supplementary material for our article prepared for publication and under revision. It contains omitted results due to space limits of the article as well as detailed, patient per patient and team per team results for all metrics. Additional figures redundant with those of the article are also provided.
+
+The readme file Readme_SupplementalMaterial.txt provides details about each individual file content.",mds,True,findable,0,0,1,0,0,2018-07-13T09:25:11.000Z,2018-07-13T09:25:11.000Z,cern.zenodo,cern,"Multiple sclerosis,Image segmentation,Performance evaluation,Computing infrastructure,Distributed computing,MICCAI challenge","[{'subject': 'Multiple sclerosis'}, {'subject': 'Image segmentation'}, {'subject': 'Performance evaluation'}, {'subject': 'Computing infrastructure'}, {'subject': 'Distributed computing'}, {'subject': 'MICCAI challenge'}]",,
+10.5281/zenodo.200198,Mpi Load Balancing Simulation Data Sets (Companion To Ipdps 2017),Zenodo,2016,,Dataset,"Creative Commons Attribution Share-Alike 4.0,Open Access","This package contains data sets and scripts (in an Org-mode file) related to our submission to IPDPS 2017, under the title ""Using Simulation to Evaluate and Tune the Performance of Dynamic Load Balancing of an Over-decomposed Geophysics Application"".
+
+The following contents are included:
+
+
+ <em>IPDPS2017.org :</em> Org mode (Emacs) file containing the shell (Bash) and R scripts used to:
+
+
+ run the load balancing simulation;
+ process the traces of both real executions (Tau traces) and simulation (Pajé traces);
+ generate the graphics.
+
+
+ <em>lb_traces/:</em> this directory contains the raw traces from real executions and SMPI emulations of the Ondes3D application.
+ <em>processed_data/</em>: this directory contains the results of the processing of the traces in the form of CSV format data files which are be used to generate the graphics.
+ i<em>mg</em>/: this directory contains the generate graphics, in PNG format.",,True,findable,0,0,0,0,0,2016-12-13T12:25:44.000Z,2016-12-13T12:25:45.000Z,cern.zenodo,cern,"simulation,load balancing,SimGrid,Ondes3d,over decomposition,MPI","[{'subject': 'simulation'}, {'subject': 'load balancing'}, {'subject': 'SimGrid'}, {'subject': 'Ondes3d'}, {'subject': 'over decomposition'}, {'subject': 'MPI'}]",,
+10.5281/zenodo.3606016,Modifications of the plant-pollinator network structure and species' roles along a gradient of urbanization,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This file includes data and codes used in the article titled: "" Modifications of the plant-pollinator network structure and species’ roles along a gradient of urbanization"". Data include plant-pollinator interactions sampled in each site (1-12) at each sampling event (6 events) in the three urbanization classes (low, medium, high). Each row is a single insect pollinator X plant interaction. Full species names and abbreviations used in figures in the Supplementary Information are reported.<br> The data file is .txt with tab-separated values.",mds,True,findable,1,0,0,0,0,2020-01-13T10:19:33.000Z,2020-01-13T10:19:34.000Z,cern.zenodo,cern,"bees, beta-diversity, conservation biology, global changes, hoverflies, interaction diversity, land-use change, motifs, mutualistic networks, pollinators, plant-pollinator interactions, urbanization","[{'subject': 'bees, beta-diversity, conservation biology, global changes, hoverflies, interaction diversity, land-use change, motifs, mutualistic networks, pollinators, plant-pollinator interactions, urbanization'}]",,
+10.5281/zenodo.4964213,"FIGURES 25–28 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 25–28. Protonemura pennina sp. n., 25. male terminalia with epiproct, dorsal view. 26. male terminalia, ventral view. 27. male, paraproct median lobe and outer lobe with trifurcated sclerite. 28. male, paraproct median lobe and outer lobe with trifurcated sclerite",mds,True,findable,0,0,3,0,0,2021-06-16T08:25:17.000Z,2021-06-16T08:25:18.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.34847/nkl.adc04b9w,Bulletin franco-italien 1912 n°2 mars - avril,NAKALA - https://nakala.fr (Huma-Num - CNRS),2022,fr,Book,,"1912/03 (A4,N2)-1912/04.",api,True,findable,0,0,0,0,0,2022-06-29T10:30:34.000Z,2022-06-29T10:30:34.000Z,inist.humanum,jbru,Etudes italiennes,[{'subject': 'Etudes italiennes'}],"['5911653 Bytes', '36330 Bytes', '20948809 Bytes', '21088168 Bytes', '20945074 Bytes', '20995618 Bytes', '21018802 Bytes', '21114103 Bytes', '21203224 Bytes', '21063487 Bytes', '21032884 Bytes', '21059062 Bytes', '20963617 Bytes', '20835679 Bytes', '21114352 Bytes', '20978806 Bytes']","['application/pdf', 'application/json', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff', 'image/tiff']"
+10.5281/zenodo.6860527,JASPAR TFBS LOLA databases - Part 1,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the first part of the JASPAR 2022 LOLA databases used by the JASPAR TFBS enrichment tool. For each organism, we provide the LOLA databases for all JASPAR 2022 TFBS sets as compressed directories containing a set of .RDS R objects. Databases are organised by genome assembly. Due to file sizes, we had to split the repository into two different parts. Part 2 of the repository containing the databases for human can be found here.",mds,True,findable,0,0,0,0,0,2022-07-25T12:25:26.000Z,2022-07-25T12:25:27.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8052969,Garaffa_et_al_OE_2023_Supplemental_Information,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"Supplemental Information. Garaffa et al., Stocktake of G20 countries' climate pledges reveals limited macroeconomic costs and employment shifts, One Earth (2023), https://doi.org/10.1016/j.oneear.2023.10.012Â
+List of policies included in the scenarios (CurPol, NDC-LTS and 1.5C)",mds,True,findable,0,0,0,0,0,2023-06-19T12:55:33.000Z,2023-06-19T12:55:34.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8271121,Artifact for Dynamic Program Analysis with Flexible Instrumentation and Complex Event Processing,Zenodo,2023,,Software,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the source code for the integration layer between <code>BISM</code> and <code>BeepBeep</code>. For more about these tools, BISM is a lightweight bytecode instrumentation tool for Java programs and BeepBeep is a complex event stream query engine. The repo also contains the examples analyses that we implemented and the experiments we conducted. The tool and experiments presented in this repository are discussed in the following publication: C. Soueidi, Y. Falcone, and S. Hallé. (2023). Dynamic Program Analysis with Flexible Instrumentation and Complex Event Processing. Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE 2023). IEEE.",mds,True,findable,0,0,0,0,0,2023-08-21T23:14:32.000Z,2023-08-21T23:14:33.000Z,cern.zenodo,cern,"dynamic program analysis,instrumentation,JVM-based languages,complex event processing","[{'subject': 'dynamic program analysis'}, {'subject': 'instrumentation'}, {'subject': 'JVM-based languages'}, {'subject': 'complex event processing'}]",,
+10.5281/zenodo.3707930,Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the estimate of the atmospherically-forced contribution to sea level variability described in Close et al, 2020, and derived from the Ssalto/Duacs altimeter products produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS) (http://www.marine.copernicus.eu). The files contain successive 5-day averages of sea level anomaly, with the same global coverage and 0.25° grid as the Ssalto/Duacs altimeter products. The estimate is created using a spatial bandpass filter, with cutoff scales of ~1.5° and 10.5°. Zeros in the mask file indicate regions in which it has not been possible to evaluate the quality of the estimate. The cutoff scales applied to the altimetry data were determined through analysis of output from the OceaniC Chaos – ImPacts, strUcture, predicTability (Penduff et al, 2014) experiment, comprising a 50-member ensemble of ocean-sea ice model hindcasts with 0.25° horizontal resolution (Bessières et al., 2017). The spatiotemporal coherence between the model-based estimates of the atmospherically-forced (ensemble mean) and total simulated sea surface height signals was analysed, and found to exhibit distinct partitioning between the atmospherically-forced and intrinsic contributions in a spatial (but not temporal) sense, thus suggesting that meaningful estimation of the two components can be achieved based on simple spatial filtering. Verification of the method using the model data indicates good accuracy, with a global mean correlation of 0.9 between the estimate based on spatial filtering and the ensemble mean sea surface height. Full details of the methodology and verification may be found in Close et al, 2020. ---- <strong>References</strong>: Bessières, L., Leroux, S., Brankart, J.-M., Molines, J.-M., Moine, M.-P., Bouttier, P.-A., Penduff, T., Terray, L., Barnier, B., and Sérazin, G., 2017. Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution, Geosci. Model Dev., 10, 1091–1106, doi: 10.5194/gmd-10-1091-2017. Close, S., Penduff, T., Speich, S. and Molines J.-M., 2020. A means of estimating the intrinsic and atmospherically-forced contributions to sea surface height variability applied to altimetric observations. Progr. Oceanogr. doi: 10.1016/j.pocean.2020.102314 Penduff, T., Barnier, B. , Terray, L., Bessières, L., Sérazin, G., Grégorio, S., Brankart, J., Moine, M., Molines, J., Brasseur, P., 2014. Ensembles of eddying ocean simulations for climate, CLIVAR Exchanges, Special Issue on High Resolution Ocean Climate Modelling, 19.",mds,True,findable,3,0,1,0,0,2020-03-25T08:50:08.000Z,2020-03-25T08:50:10.000Z,cern.zenodo,cern,"ocean,sea level anomaly,altimetry","[{'subject': 'ocean'}, {'subject': 'sea level anomaly'}, {'subject': 'altimetry'}]",,
+10.5281/zenodo.4761357,"Fig. 92 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 92. Distribution map of Dictyogenus species in the Central and Western Alps. Legend: Dictyogenus jurassicum, yellow dots; D. muranyii, black dots; D. alpinum, red dots; D. fontium species complex, blue dots. Distribution data are those of the authors and Opie-Benthos. Map data: SRTM V4 (http://srtm.csi.cgiar.org), generated with ArcGIS version 10.3.0.4322.",mds,True,findable,0,0,4,0,0,2021-05-14T07:52:50.000Z,2021-05-14T07:52:50.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.4761293,"Figs. 6-7 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 6-7. Dictyogenus jurassicum sp. n., adult male. 6. Epiproct and lateral stylet, lateral view. Karstic spring at Charabotte Mill, Ain dpt, France. Photo B. Launay. 7. Posterior margin of sternite 7 with ventral vesicle, ventral view. Karstic spring at Charabotte Mill, Ain dpt, France. Photo J.-P.G. Reding.",mds,True,findable,0,0,6,0,0,2021-05-14T07:43:39.000Z,2021-05-14T07:43:40.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.5084367,"Data and code used in ""Satellite magnetic data reveal interannual waves in Earth's core""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Eigen mode solutions and code to obtain them for the results presented in Satellite magnetic data reveal interannual waves in Earth's core. The package uses the freely available code Mire.jl. <strong>Prerequisites</strong> Installed python3 with matplotlib ≥v2.1, cmocean and cartopy. A working Julia ≥v1.7. <strong>Run</strong> In the project folder run <pre><code>julia --project=.</code></pre> <br> Then, from within the Julia REPL run <pre><code>]instantiate</code></pre> at first time, to install all dependencies. After that, to compute all plots, run <pre><code>using QGMCSat allfigs()</code></pre> They're automatically saved in the ""figs"" subfolder of the repository. If loading QGMCSat fails, due to a missing cartopy or cmocean in the python version. Run (within Julia)<br> <pre><code>ENV[""PYTHON""] = ""python"" #this should point to the python version that has cartopy installed ]build PyCall</code></pre> <br> To calculate all data, run <pre><code>using QGMCSat calculate_data()</code></pre> This will take several hours/days depending on the machine (needs enough memory). Individual data can be accessed directly through the .jld2 files from Julia. You can check out the individual figure functions to get an idea where which data is stored. If there are any issues or questions, please don't hesitate to get in touch!",mds,True,findable,0,0,0,1,0,2022-02-28T19:22:58.000Z,2022-02-28T19:23:00.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5500364,Data and scripts from: A new westward migration route in an Asian passerine bird,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Contains relevant datasets and code for niche modeling analyses performed in ""A new westward migration route in an Asian passerine bird"" by Dufour P<sup>*</sup>, de Franceschi<sup> </sup>C, Doniol-Valcroze P, Jiguet F, Maya Guéguen M, Renaud J, Lavergne<sup>†</sup>S, Crochet<sup>†</sup> PA (<sup>†</sup>co-senior authors)",mds,True,findable,0,0,0,0,0,2021-10-22T15:02:48.000Z,2021-10-22T15:02:49.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.c.6604292.v1,Predictors of changing patterns of adherence to containment measures during the early stage of COVID-19 pandemic: an international longitudinal study,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Identifying common factors that affect public adherence to COVID-19 containment measures can directly inform the development of official public health communication strategies. The present international longitudinal study aimed to examine whether prosociality, together with other theoretically derived motivating factors (self-efficacy, perceived susceptibility and severity of COVID-19, perceived social support) predict the change in adherence to COVID-19 containment strategies. Method In wave 1 of data collection, adults from eight geographical regions completed online surveys beginning in April 2020, and wave 2 began in June and ended in September 2020. Hypothesized predictors included prosociality, self-efficacy in following COVID-19 containment measures, perceived susceptibility to COVID-19, perceived severity of COVID-19 and perceived social support. Baseline covariates included age, sex, history of COVID-19 infection and geographical regions. Participants who reported adhering to specific containment measures, including physical distancing, avoidance of non-essential travel and hand hygiene, were classified as adherence. The dependent variable was the category of adherence, which was constructed based on changes in adherence across the survey period and included four categories: non-adherence, less adherence, greater adherence and sustained adherence (which was designated as the reference category). Results In total, 2189 adult participants (82% female, 57.2% aged 31–59 years) from East Asia (217 [9.7%]), West Asia (246 [11.2%]), North and South America (131 [6.0%]), Northern Europe (600 [27.4%]), Western Europe (322 [14.7%]), Southern Europe (433 [19.8%]), Eastern Europe (148 [6.8%]) and other regions (96 [4.4%]) were analyzed. Adjusted multinomial logistic regression analyses showed that prosociality, self-efficacy, perceived susceptibility and severity of COVID-19 were significant factors affecting adherence. Participants with greater self-efficacy at wave 1 were less likely to become non-adherence at wave 2 by 26% (adjusted odds ratio [aOR], 0.74; 95% CI, 0.71 to 0.77; P < .001), while those with greater prosociality at wave 1 were less likely to become less adherence at wave 2 by 23% (aOR, 0.77; 95% CI, 0.75 to 0.79; P = .04). Conclusions This study provides evidence that in addition to emphasizing the potential severity of COVID-19 and the potential susceptibility to contact with the virus, fostering self-efficacy in following containment strategies and prosociality appears to be a viable public health education or communication strategy to combat COVID-19.",mds,True,findable,0,0,0,0,0,2023-04-18T04:38:34.000Z,2023-04-18T04:38:34.000Z,figshare.ars,otjm,"Medicine,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.5535532,"Satellite-observed surface flow speed within Russell sector, West Greenland, bi-weekly average of 2015-2019",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","An average horizontal surface ice velocity of Russell sector (Greenland) with 2-week temporal and 150m spatial resolution. Derived from satellite images collected between 2015 and 2019 by Landsat-8, Sentinel-1, and Sentinel-2. The details on the data processing can be found in https://doi.org/10.5194/tc-2021-170. <br> Dataset contains 24 independent NetCDF files (one per 2-weeks time step) with maps of vx and vy velocity components, maps of associated uncertainties per velocity component (STD of the 2-weeks averaged raw satellite measurements), and map of number of averaged measurements.",mds,True,findable,0,0,0,0,0,2021-10-05T10:02:05.000Z,2021-10-05T10:02:07.000Z,cern.zenodo,cern,"ice flow speed, seasonal, satellite measurements, Greenland, Russell","[{'subject': 'ice flow speed, seasonal, satellite measurements, Greenland, Russell'}]",,
+10.5281/zenodo.4804635,FIGURES 15–17 in Review and contribution to the stonefly (Insecta: Plecoptera) fauna of Azerbaijan,Zenodo,2021,,Image,Open Access,"FIGURES 15–17. Mermithids from Protonemura sp. (aculeata?) male from the Greater Caucasus—15: mermithids as seen by transparency through the abdominal sterna; 14: four mermithid specimens dissected from the male stonefly, according to mm scale; 17: abdomen of the stonefly opened at segments 2 and 3, with mermithids protruding.",mds,True,findable,0,0,2,0,0,2021-05-26T07:55:06.000Z,2021-05-26T07:55:07.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.6078514,Earthquake Archaeological Effects documented in the Cusco area in 2019 (RISC project),Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","In 2019, the RISC project led to the implementation of an unprecedented archaeoseismological survey in the Cusco area, Peru. The main objective was to identify and map the earthquake-induced damage on the stone architecture of famous Inca archaeological sites. This spreadsheet summarizes all the observations. Each row corresponds to an Earthquake Archaeological Effect (EAE). For each strain structure, the columns contain information relative to the geographical and architectural contexts, the measurements and the level of confidence. The data were extracted from the RISC database, which supported the fieldwork. For more details about the design and structure of the RISC database please read: Combey et al. (2021) Monumental Inca remains and past seismic disasters: A relational database to support archaeoseismological investigations and cultural heritage preservation in the Andes, Journal of South American Earth Sciences, Volume 111, 103447,<br> https://doi.org/10.1016/j.jsames.2021.103447. The file is in support of the paper submitted to Quaternary International.",mds,True,findable,0,0,0,0,0,2022-07-10T10:37:48.000Z,2022-07-10T10:37:49.000Z,cern.zenodo,cern,"Archaeoseismology,Earthquake damage,Seismic Hazard,Cusco,Inca","[{'subject': 'Archaeoseismology'}, {'subject': 'Earthquake damage'}, {'subject': 'Seismic Hazard'}, {'subject': 'Cusco'}, {'subject': 'Inca'}]",,
+10.5281/zenodo.7382840,"DBnary in Ontolex, All Languages Archive 2017",Zenodo,2017,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Since July 1st 2017, the lexical data extracted from Wiktionary is modeled using the ontolex vocabulary. This dataset contains the archive of all DBnary dumps of 2017 in Ontolex format containing lexical information from wiktionary dumps of 2017 (post July 1st).",mds,True,findable,0,0,0,0,0,2022-11-30T16:23:54.000Z,2022-11-30T16:23:54.000Z,cern.zenodo,cern,"Wiktionary,Ontolex,Lexical Data,RDF,Bulgarian,German,Modern Greek,English,Spanish,Finnish,French,Indonesian,Italian,Japanese,Latin,Lithuanian,Malagasy,Dutch,Norvegian,Polish,Portuguese,Russian,Serbo Croatian,Swedish,Turkish","[{'subject': 'Wiktionary'}, {'subject': 'Ontolex'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}, {'subject': 'Bulgarian'}, {'subject': 'German'}, {'subject': 'Modern Greek'}, {'subject': 'English'}, {'subject': 'Spanish'}, {'subject': 'Finnish'}, {'subject': 'French'}, {'subject': 'Indonesian'}, {'subject': 'Italian'}, {'subject': 'Japanese'}, {'subject': 'Latin'}, {'subject': 'Lithuanian'}, {'subject': 'Malagasy'}, {'subject': 'Dutch'}, {'subject': 'Norvegian'}, {'subject': 'Polish'}, {'subject': 'Portuguese'}, {'subject': 'Russian'}, {'subject': 'Serbo Croatian'}, {'subject': 'Swedish'}, {'subject': 'Turkish'}]",,
+10.5281/zenodo.6400739,InLang: task-related language connectomes,Zenodo,2022,,Dataset,Closed Access,.,mds,True,findable,0,0,0,0,0,2022-03-31T15:23:33.000Z,2022-03-31T15:23:33.000Z,cern.zenodo,cern,"fMRI,Language,Connectome","[{'subject': 'fMRI'}, {'subject': 'Language'}, {'subject': 'Connectome'}]",,
+10.5281/zenodo.1489533,Brainstorm software 15-Nov-2018,Zenodo,2018,,Software,"Creative Commons Attribution 4.0 International,Open Access","Brainstorm snapshot from 15-Nov-2018, for replicability of a published analysis pipeline",mds,True,findable,0,0,0,0,0,2018-11-16T08:51:59.000Z,2018-11-16T08:52:00.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8046630,Melissa: coordinating large-scale ensemble runs for deep learning and sensitivity analyses,Zenodo,2023,en,Software,"BSD 3-Clause Clear License,Open Access","Melissa is a file avoiding, fault tolerant and elastic framework, generalized to perform ensemble runs such as <em>large scale sensitivity analysis</em> and <em>large scale deep surrogate training</em> on supercomputers. Some of the largest Melissa studies so far employed up to 30k cores to execute 80 000 parallel simulations while avoiding up to 288 TB of intermediate data storage. These large-scale studies avoid intermediate file storage due to Melissa's ""online"" (also referred to as in-transit and on-the-fly) data handling approach. Melissa's architecture relies on three interacting components, the launcher, the server, and the client: Melissa client: the parallel numerical simulation code turned into a client. Each client sends its output to the server as soon as available. Clients are independent jobs. Melissa server: a parallelized process in charge of processing the data upon arrival from the distributed and parallelized clients (<em>e.g.</em> computing statistics or training a neural network). Melissa Launcher: the front-end Python script in charge of orchestrating the execution of the study. This piece of code interacts directly with <code>OpenMPI</code> or with the cluster scheduler (<em>e.g.</em> <code>slurm</code> or <code>OAR</code>) to submit and monitor the proper execution of all instances. The Melissa server component is designed to be specialized for various types of ensemble runs: Sensitivity Analysis (melissa-sa) Melissa's sensitivity analysis server is built around two key concepts: iterative (sometimes also called incremental) statistics algorithms and asynchronous client/server model for data transfer. Simulation outputs are never stored on disk. Instead, they are sent via NxM communication patterns from the simulations to a parallelized server. This method of data aggregation enables the calculation of rapid statistical fields in an iterative fashion, without storing any data to disk. Avoiding disk storage opens up the ability to compute oblivious statistical maps for all mesh elements, for every time step and on a full resolution study. Melissa comes with iterative algorithms for computing various statistical quantities (<em>e.g.</em> mean, variance, skewness, kurtosis and Sobol indices) and can easily be extended with new algorithms. Deep Surrogate Training (melissa-dl) Melissa's deep learning server adopts a similar philosophy. Clients communicate data in a round-robin fashion to the parallelized server. The multi-threaded server then puts and pulls data samples in and out of a buffer which is used for building training batches. Melissa can perform data distributed parallelism training on several GPUs, associating a buffer to each of them. To ensure a proper memory management during execution, samples are selected and evicted according to a predefined policy. This strategy enables the online training method shown in. Furthermore, the Melissa architecture is designed to accommodate popular deep learning libraries such as PyTorch or Tensorflow.",mds,True,findable,0,0,0,0,0,2023-06-16T09:40:23.000Z,2023-06-16T09:40:24.000Z,cern.zenodo,cern,"supercomputing,sensitivity analysis,deep learning,distributed systems,orchestration,ensemble runs","[{'subject': 'supercomputing'}, {'subject': 'sensitivity analysis'}, {'subject': 'deep learning'}, {'subject': 'distributed systems'}, {'subject': 'orchestration'}, {'subject': 'ensemble runs'}]",,
+10.5281/zenodo.163632,Trust 3D Dust Rt Slab Benchmark Data,Zenodo,2017,,Dataset,"Creative Commons Attribution 4.0,Open Access","Output global SEDs and images at selected wavelengths for the Slab benchmark of the TRUST collaboration. TRUST is a suite of benchmarks for 3D dust radiative transfer codes in astronomy.
+
+Paper describing the TRUST Slab benchmark is Gordon et al. (2017, A&A, 603, 114; http://adsabs.harvard.edu/abs/2017A&A...603A.114G)
+
+More details on TRUST at http://ipag.osug.fr/RT13/RTTRUST/.
+
+Code to make plots using this data at: https://github.com/karllark/trust_slab",,True,findable,1,0,0,0,0,2017-03-17T19:27:29.000Z,2017-03-17T19:27:29.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23822157,Dataset for the replication experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,Data for the replication experiment in CSV format.,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:27.000Z,2023-08-02T11:18:27.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['3105 Bytes'],
+10.5281/zenodo.5649825,"FIG. 42 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from Southern France",Zenodo,2021,,Image,Open Access,"FIG. 42—Localities of Protonemura lupina sp. n. in the southern French Alps: a = (spring) and b = (harnessed spring), tributaries to the Loup River, on the road to Courmes, 43.753N, 7.005E (Alpes-Maritimes) (photographs by Gilles Vinçon).",mds,True,findable,0,0,1,0,0,2021-11-05T21:12:00.000Z,2021-11-05T21:12:01.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.4244325,"Configurations and scripts to reproduce the numerical simulations of ""A two-fluid model for immersed granular avalanches with dilatancy effects"" article",Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This directory contains the main data to reproduce the results presented in the article ""A two-fluid model for immersed granular avalanches with dilatancy effects"" by Eduard Puig Montellà , Julien Chauchat, Bruno Chareyre, Cyrille Bonamy and Tian-Jian Hsu.<br> <br> The numerical results and experimental data extracted from Pailha et ad (2008) can be found inside ""NumericalData"" and ""ExperimentalData"" folders respectively. The script ""PressureVelocityPlot.py"" displays the evolution of the surface particle velocity and the excess of pore pressure with time for cases ranging from loose to dense granular avalanches. The input files needed to reproduce a dense granular avalanche (phi=0.592) in 1D and 2D are found in the following folders: ""1D_DenseCase"" and ""2D_DenseCase"". To accelerate the simulation, the files are given after 200 seconds of sedimentation in order to reach an equilibrium state. Please read the corresponding README.txt files to launch a 1D and/or a 2D simulation. Additionally, python scripts in each configuration are provided to evaluate the evolution of the main parameters during the avalanche.",mds,True,findable,0,0,0,0,0,2020-11-04T12:48:03.000Z,2020-11-04T12:48:04.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4761349,"Fig. 83 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 83. Dictyogenus fontium species complex, female, subgenital plate. Inner-alpine upper Isère Valley. Col de l'Iseran, Savoie dpt, France. Photo A. Ruffoni.",mds,True,findable,0,0,6,0,0,2021-05-14T07:51:45.000Z,2021-05-14T07:51:45.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.34847/nkl.5bcck3cz,"Moi, la Romanche",NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,fr,Audiovisual,,"Au fil du temps, la Romanche s'est transformée, ses courbes aménagées, sa puissance exploitée, son destin capté. Mais cette rivière qu'a t-elle de singulier ?
+En partant de l'histoire de la rivière, en adoptant le point de vue des éléments naturels, en réinterrogeant l'usage des anciens habitants et en imaginant un futur à leur cours d'eau, les élèves ont construit une fable contemporaine sur leur territoire et son devenir.
+
+Ce film a été réalisé par le collectif ""Regards des lieux"", Printemps 2021, 15 min. 35 sec
+
+Film écrit et tourné par les élèves et les équipes pédagogiques des écoles de Livet-et-Gavet. Voir aussi le film ""Du village à l'écran"", réalisé avec les écoles en 2019.
+
+Merci à Bastien Bourdon, EDF Hydro, Christophe Séraudie, Mélanie Chiazza.
+
+Avec la participation de Fondation de France - Programme Grandir en culture, Communauté de communes de l'Oisans, Caisse d'allocation familiale de l'Isère.
+
+Regards des lieux est soutenu par Ville de Grenoble, Conseil départemental de l'Isère, Région Auvergne Rhône-Alpes, DRAC Région Auvergne Rhône-Alpes.",api,True,findable,0,0,0,0,0,2023-10-03T09:15:55.000Z,2023-10-03T09:15:56.000Z,inist.humanum,jbru,"""Mémoires des lieux,histoire orale,histoires de vie,enquêtes de terrain (ethnologie),Désindustrialisation,Patrimoine industriel,Pollution de l'air,Montagnes – aménagement,Énergie hydraulique,Rives – aménagement,Romanche, Vallée de la (France),Keller, Charles Albert (1874-1940 , Ingénieur A&M),patrimoine immatériel,Conditions de travail,classe ouvrière,Torrents,Risque,Chansons enfantines,enfants,voix,Attachement à un lieu","[{'lang': 'fr', 'subject': '""Mémoires des lieux'}, {'lang': 'fr', 'subject': 'histoire orale'}, {'lang': 'fr', 'subject': 'histoires de vie'}, {'lang': 'fr', 'subject': 'enquêtes de terrain (ethnologie)'}, {'lang': 'fr', 'subject': 'Désindustrialisation'}, {'lang': 'fr', 'subject': 'Patrimoine industriel'}, {'lang': 'fr', 'subject': ""Pollution de l'air""}, {'lang': 'fr', 'subject': 'Montagnes – aménagement'}, {'lang': 'fr', 'subject': 'Énergie hydraulique'}, {'lang': 'fr', 'subject': 'Rives – aménagement'}, {'lang': 'fr', 'subject': 'Romanche, Vallée de la (France)'}, {'lang': 'fr', 'subject': 'Keller, Charles Albert (1874-1940 , Ingénieur A&M)'}, {'lang': 'fr', 'subject': 'patrimoine immatériel'}, {'lang': 'fr', 'subject': 'Conditions de travail'}, {'lang': 'fr', 'subject': 'classe ouvrière'}, {'lang': 'fr', 'subject': 'Torrents'}, {'lang': 'fr', 'subject': 'Risque'}, {'lang': 'fr', 'subject': 'Chansons enfantines'}, {'lang': 'fr', 'subject': 'enfants'}, {'lang': 'fr', 'subject': 'voix'}, {'lang': 'fr', 'subject': 'Attachement à un lieu'}]",['596667242 Bytes'],['video/mp4']
+10.5281/zenodo.5506676,Bragg ptychography inversion package for paper - Revealing nano-scale lattice distortions in implanted material with 3D Bragg ptychography,Zenodo,2021,,Software,"Creative Commons Attribution 4.0 International,Open Access","This repository contains Matlab code and data to achieve 3D Bragg ptychography inversion as described in the paper [1].<br> It includes the following items:<br> 1/ data_for_inversion folder, it contains 3D diffraction patterns ordered sequencially in positional numbers. For an example, dps_pos_*.mat means the 3D diffraction pattern taken at position number *. The first two dimensions of the 3D diffraction pattern are the two axes from the detector, and the third dimension is the angular rotation axis. It also contains the mask (i.e. mask.mat) for the detector, since detectors can have modular gaps, and hot and dead pixels. Moreover, it has two masks (i.e. probe_ft_up1.mat and probe_ft_up3.mat) for the 2D probe function in reciprocal space. up1 and up3 respectively means the angular upsampling of 1 and 3 times.<br> 2/ initial_probes folder, it contains 3 different probes that were used as the initial probe guesses for the inversion codes. ptycho_characterisation.mat is the probe characterised from forward ptychography. probe_ft_50%wrong.mat is the Fourier transform of the nominated NA of the KB but 50% bigger. GauFunc_50%wrong.mat is a probe with Gaussian profile whose FWHM is 50% bigger than the nominated probe size.<br> 3/ codes folder, it contains all the codes for the inversion.<br> 4/ reconstruction.m file, it is the entry point of the inversion package and contains all the parameters related to the experiment and the reconstruction.",mds,True,findable,0,0,0,0,0,2021-09-23T11:37:30.000Z,2021-09-23T11:37:31.000Z,cern.zenodo,cern,"coherent diffraction imaging,x-ray 3D imaging,crystalline microscopy","[{'subject': 'coherent diffraction imaging'}, {'subject': 'x-ray 3D imaging'}, {'subject': 'crystalline microscopy'}]",,
+10.6084/m9.figshare.22649273,Additional file 1 of Predictors of changing patterns of adherence to containment measures during the early stage of COVID-19 pandemic: an international longitudinal study,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Supplementary Table 1. Measures used in the COVID-IMPACT study.,mds,True,findable,0,0,0,0,0,2023-04-18T04:38:30.000Z,2023-04-18T04:38:30.000Z,figshare.ars,otjm,"Medicine,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['25409 Bytes'],
+10.5281/zenodo.8333896,Seeds of Life in Space – SOLIS,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Life on Earth is based on carbon chemistry, likely because of the C atoms ability to form long chains and polymers and its relatively large cosmic abundance. The same chemistry holds everywhere in the Universe and it starts in the interstellar clouds, from where the progenitors of Suns and Solar-like planetary systems are born. As the Nobel Laureate C. de Duve (2005) wrote: “The building blocks of life form naturally in our Galaxy and, most likely, also elsewhere in the cosmos. The chemical seeds of life are universal.†As a matter of fact, out of more than 270 species detected in the ISM, about 80% contain C atoms, and all species with more than five atoms are C-bearing ones. The latter are known as interstellar Complex Organic Molecules (iCOMs) and may represent the foundational organic chemistry underlying terrestrial life. SOLIS is a NOEMA Large Program which has the overall goal of understanding the organic chemistry during the first steps of the formation of a Solar-like planetary system. To this end, the immediate SOLIS objective is to provide a homogeneous data set of observations of five crucial iCOMs in seven targets representative of Solar-like systems in their first evolutionary stages. The observations are designed to map several lines from each of the targeted iCOMs and, hence, determine their abundance as well as the physical conditions of the region where the lines are emitted, with a precision on 10000—100 au scales. Thanks to the NOEMA capabilities, several more iCOMs are detected that complement the primary species targeted, allowing for a more comprehensive chemical study of the observed regions. SOLIS has observed the following seven sources: L1544, representative of prestellar cores; L1521, a VeLLO (Very Low-Luminosity) source at the very early stages of protostellar evolution; NGC 1333-IRAS4A, a low-luminosity Class 0 binary system; CepE-mm, an intermediate-luminosity Class 0 source; NGC 1333-SVS13A, a low-luminosity Class I binary system; OMC-2 FIR4, a protocluster analogue of the one where the Solar System was born; L1157-B1, a molecular shock close to a Class 0 source. SOLIS has targeted the following five iCOMs: methanol (CH3OH), considered the mother of many other iCOMs; dimethyl ether (CH3OCH3; DME), methyl formate (HCOOCH3: MF) and formamide (NH2HCO), three commonly observed iCOMs that have been predicted to be formed both in the gas-phase and on the grain surfaces; methoxy (CH3O), a crucial precursor of several iCOMs. In addition, the SOLIS observations have provided information on acetaldehyde (CH3CHO), methyl cyanide (CH3CN), the two smallest cyanopolyynes (HC3N and HC5N), among other iCOMs, as well as simpler molecules such as S-bearing ones or rarer isotopologues of hydrogen, nitrogen and silicon. The official SOLIS repository is at IRAM, and it includes various types of data, such as uv-tables, continuum emission maps, and continuum-subtracted data cubes. Please do not hesitate to contact Cecilia Ceccarelli (cecilia.ceccarelli@univ-grenoble-alpes.fr) and Paola Caselli (caselli@mpe.mpg.de) for further questions or to inform them about the use of the data for further scientific analysis or publications. For a complete list of publications please visit the SOLIS publication web page. The following acknowledgment would be appreciated: “This work made use of data from the NOEMA Large Program SOLIS (Seeds Of Life In Space), Ceccarelli & Caselli et al. 2017, ApJ 850, 176.â€",mds,True,findable,0,0,0,0,0,2023-09-11T09:50:33.000Z,2023-09-11T09:50:34.000Z,cern.zenodo,cern,"astrochemistry, star forming regions, radio observations, telescopes","[{'subject': 'astrochemistry, star forming regions, radio observations, telescopes'}]",,
+10.5281/zenodo.8384883,Glacier runoff projections and their multiple sources of uncertainty in the Patagonian Andes (40-56°S),Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the catchment scale results of the study: ""<strong>Assessing the glacier projection uncertainties in the Patagonian Andes (40-56°S) from a catchment perspective</strong>"". The results are disaggregated in the following files (for more details, please read the README file): <em>- basins_boundaries.zip:</em> Contains the polygons (in .shp format) of the studied catchments. Each catchment is identified by its ""basin_id"". <em>- dataset_historical.csv: </em>Summarises the historical conditions of each glacier at the catchment scale (area, volume and reference climate). <em>- dataset_future.csv: </em>Summarises the future glacier climate drivers and their impacts at the catchment scale. <em>- dataset_signatures.csv: </em>Summarises the glacio-hydrological signatures for each catchment. The metrics are calculated for the variables ""total glacier runoff (tr)"" and ""melt on glacier (mg)"". The main source of uncertainty in each catchment was the source that accumulated most RMSE loss.",mds,True,findable,0,0,0,0,0,2023-10-05T18:35:16.000Z,2023-10-05T18:35:17.000Z,cern.zenodo,cern,"glacier runoff,Patagonia,uncertainty,Open Global Glacier Model,GlacierMIP,Andes,random forest,Patagonian Icefields","[{'subject': 'glacier runoff'}, {'subject': 'Patagonia'}, {'subject': 'uncertainty'}, {'subject': 'Open Global Glacier Model'}, {'subject': 'GlacierMIP'}, {'subject': 'Andes'}, {'subject': 'random forest'}, {'subject': 'Patagonian Icefields'}]",,
+10.5281/zenodo.10069275,The Effect of Typing Efficiency and Suggestion Accuracy on Usage of Word Suggestions and Entry Speed,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Data collected during our experiments investigating the effect of suggestion accuracy and typing efficiency on usage of word suggestions, and entry speed",api,True,findable,0,0,0,0,0,2023-11-03T12:54:51.000Z,2023-11-03T12:54:51.000Z,cern.zenodo,cern,"writing,word suggestions","[{'subject': 'writing'}, {'subject': 'word suggestions'}]",,
+10.5281/zenodo.4760505,"Fig. 25 in Contribution To The Knowledge Of The Moroccan High And Middle Atlas Stoneflies (Plecoptera, Insecta)",Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access",Fig. 25. Distribution of Capnioneura atlasica sp. n. and C. petitpierreae in western Maghreb.,mds,True,findable,0,0,2,0,0,2021-05-14T05:28:24.000Z,2021-05-14T05:28:25.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Capniidae,Capnioneura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Capniidae'}, {'subject': 'Capnioneura'}]",,
+10.5281/zenodo.8155231,compute-NPQ,Zenodo,2023,,Software,"MIT License Modern Variant,Open Access",This Python script performs various image processing operations on a set of images from confocal microscopy to compute NPQ (Non-Photochemical Quenching). The script is named compute_npq.py and requires Python 3 or later. A sample of input '.png' files is available in the data folder and can be used as described in READM.md file. compute-NPQ.zip,mds,True,findable,0,0,0,1,0,2023-07-17T13:51:07.000Z,2023-07-17T13:51:07.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7828494,X-ray Fluorescence Ghost Imaging - CuSn mask - Three Wires (Fe & Cu),Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","X-ray Fluorescence Ghost Imaging (XRF-GI) dataset of three wires (one Fe, and two Cu) in a plastic capillary. The capillary contains trace elements like Zn, Zr, etc. The GI scan is presented in the following article <insert doi here>. A total of 896 GI realizations were taken, organized in 16 vertical translations and 56 horizontal translations of the structuring element (CuSn mask).<br> The dataset contains both the sample transmission images, and the masks plus sample transmission images. No images of the masks are provided (they need to be computed). The data is organized in a HDF5 file, under the following structure: <pre><code>dataset_CuSn-mask_3wires.h5 │ ├data │ ├flat_panel │ │ ├dark [float32: 16 × 170 × 350] │ │ ├empty_beam [float32: 170 × 350] │ │ ├sample [float32: 16 × 170 × 350] │ │ └sample_and_masks [float32: 16 × 56 × 170 × 350] │ └xrf [float32: 16 × 56 × 4096] │ └metadata └xrf ├bias_keV [float64: scalar] ├gain_keV [float64: scalar] └ranges ├Ca [int64: 2] ├Cu [int64: 2] ├Fe [int64: 2] ├Si [int64: 2] ├Ti [int64: 2] ├Zn [int64: 2] └Zr [int64: 2] </code></pre> The meaning of the paths is: <code>/data/xrf</code> contains the XRF spectra for each GI realization <code>/data/flat_panel/dark</code> contains the dark images of each scan line (no beam) <code>/data/flat_panel/empty_beam</code> contains the empty beam (no sample & no masks) intensity distribution <code>/data/flat_panel/sample</code> contains the transmission images of the sample at each scan line <code>/data/flat_panel/sample</code>_and_masks contains the transmission images of the sample and masks at each GI realization <code>/metadata/xrf/bias_keV</code> contains the bias in keV of the XRF spectrum <code>/metadata/xrf/gain_keV</code> contains the gain in keV of each XRF energy bin <code>/metadata/xrf/ranges/</code> contains the bin ranges for interesting K<sub>alpha</sub> elemental emission lines in the XRF spectrum For further information we refer to the associated publication.",mds,True,findable,0,0,0,1,0,2023-06-28T09:55:33.000Z,2023-06-28T09:55:33.000Z,cern.zenodo,cern,"ghost imaging,x-ray fluorescence,xrf,xrf-gi,single-pixel","[{'subject': 'ghost imaging'}, {'subject': 'x-ray fluorescence'}, {'subject': 'xrf'}, {'subject': 'xrf-gi'}, {'subject': 'single-pixel'}]",,
+10.5281/zenodo.5237188,Serbo-Croatian DBnary archive in original Lemon format,Zenodo,2021,,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Serbo-Croatian language edition, ranging from 16th April 2015 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-23T18:31:03.000Z,2021-08-23T18:31:05.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.4759511,"Figs. 65-66 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access",Figs. 65-66. Habitus of the micropterous form of Protonemura dakkii sp. n. 65: male imago; 66: not matured larva (scale 1 mm).,mds,True,findable,0,0,2,0,0,2021-05-14T02:27:13.000Z,2021-05-14T02:27:14.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.7307793,SolSysELTs2022 Part II: Observing asteroids and trans-Neptunian objects with MICADO/MAORY,Zenodo,2022,en,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access",Contributed talk: presentation and video recording,mds,True,findable,0,0,0,0,0,2022-11-09T12:23:20.000Z,2022-11-09T12:23:21.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.1199545,Voter Autrement 2017 - Online Experiment,Zenodo,2018,en,Dataset,"Open Data Commons Open Database License 1.0,Open Access","In March and April 2017, we have run a voting experiment during the French presidential election. During this experiment, participants were asked to test several alternative voting methods to elect the French president, like scoring methods, instant-runoff voting, Borda with partial rankings. The experiment was both carried out <em>in situ</em> in polling stations during the first round of the presidential election (using paper ballots), and online during the month preceding the first round, and until the second round of the election (using a web application). A total of 6358 participants took part to the <em>in situ</em> experiment and 37739 participants took part to the online experiment. This dataset contains the answers provided by the participants to the online experiment, with no other processsing than a basic transformation to a set of CSV files.
+
+
+
+The companion paper available on this repository describes the experimental protocol, the format of the files, and summarizes the precise conditions under which this dataset is available.",legacy,True,findable,0,0,0,0,0,2018-07-25T17:16:23.000Z,2018-07-25T17:17:45.000Z,cern.zenodo,cern,"Election,Social Choice,Experimental Voting","[{'subject': 'Election'}, {'subject': 'Social Choice'}, {'subject': 'Experimental Voting'}]",,
+10.5281/zenodo.3552836,Rekyt/ssdms_saturation_richness: Accepted version,Zenodo,2019,en,Software,"MIT License,Open Access","Is prediction of species richness from Stacked Species Distribution Models biased by habitat saturation? This repository contains the data and code for our paper: Grenié M., Violle C, Munoz F. * Is prediction of species richness from Stacked Species Distribution Models biased by habitat saturation?<em>. accepted in </em>Ecological Indicators*. How to cite Please cite this compendium as: Grenié M., Violle C, Munoz F., (2019). <em>Compendium of R code and data for Is prediction of species richness from Stacked Species Distribution Models biased by habitat saturation?</em>. Accessed 02 déc. 2019. Online at https://doi.org/10.5281/zenodo.3552836 🔧 How to download or install You can download the compendium as a zip from from this URL: Or you can install this compendium as an R package, `cssdms.saturation.richness, from GitHub with: <pre><code># install.packages(""devtools"") remotes::install_github(""Rekyt/ssdms_saturation_richness"")</code></pre> 💻 How to run the analyses This compendium uses <code>drake</code> to make analyses reproducible. To redo the analyses and rebuild the manuscript run the following lines (from the <code>ssdms_saturation_richness</code> folder): <pre><code># install.packages(""devtools"") pkgload::load_all() # Load all functions included in the package make(saturation_workflow()) # Run Analyses</code></pre> Beware that some code make time a long time to run, and it may be useful to run analyses in parallel. ##You can run the analyses by clicking on the <code>Binder</code> badge: Dependencies As noted in the <code>DESCRPTION</code> files this project depends on: <code>virtualspecies</code>, to simulate species; <code>drake</code>, to execute a reproducible workflow; the <code>tidyverse</code> (<code>dplyr</code>, <code>ggplot2</code>, <code>purrr</code>, and <code>tidyr</code>) for data wrangling; <code>ggpubr</code> to customize plot",mds,True,findable,0,0,0,0,0,2019-11-25T17:36:15.000Z,2019-11-25T17:36:16.000Z,cern.zenodo,cern,"habitat saturation,stacked species distribution model,species richness,predicted presence probabilities,threshold-based presence prediction","[{'subject': 'habitat saturation'}, {'subject': 'stacked species distribution model'}, {'subject': 'species richness'}, {'subject': 'predicted presence probabilities'}, {'subject': 'threshold-based presence prediction'}]",,
+10.57745/bywea3,Long-term monitoring of near-surface soil temperature in high-elevation alpine grasslands,Recherche Data Gouv,2023,,Dataset,,"Monitoring of near-surface soil temperature in European mountain meadows. Data are collected as part of the ANR project ODYSSEE (Projet-ANR-13-ISV7-0004). Data include a GPS position, a date and time in UTC and a near-surface soil temperature (in °C) measured at 5 cm belowground using stand-alone temperature data logger.",mds,True,findable,20,0,0,0,0,2023-03-27T13:30:34.000Z,2023-07-18T07:52:17.000Z,rdg.prod,rdg,,,,
+10.6084/m9.figshare.21341628,Additional file 1 of Expiratory high-frequency percussive ventilation: a novel concept for improving gas exchange,figshare,2022,,Text,Creative Commons Attribution 4.0 International,Additional file 1: Details of the simulation study and additional data for respiratory mechanics.,mds,True,findable,0,0,0,0,0,2022-10-16T03:12:48.000Z,2022-10-16T03:12:49.000Z,figshare.ars,otjm,"Biophysics,Space Science,Medicine,Physiology,FOS: Biological sciences,Biotechnology,Cancer","[{'subject': 'Biophysics'}, {'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Biotechnology'}, {'subject': 'Cancer'}]",['86600 Bytes'],
+10.5281/zenodo.5793694,Nitrate δ15N values and surface mass balance reconstructions from East Antarctica,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Geographic information, surface mass balance (SMB) data, and sub-photic zone (>0.3 m) nitrate concentration and nitrogen isotopic composition (δ15NNO3) for 135 sites across East Antarctica. This database was used to examine and define the relationship between δ15NNO3 and SMB in Antarctica as part of the SCADI (Snow Core Accumulation from Delta-15N Isotopes) and EAIIST (East Antarctic International Ice Sheet Traverse) projects. Of these 135 sites, 92 are newly reported here while the other site data were previously published and are cited accordingly. Snow bearing nitrate was sampled from snow pits and firn/ice cores at different dates depending on the original scientific campaign, but predominately between 2010 and 2020, with the earliest sampling occurring in 2004. Nitrate was later extracted from the snow, concentrated, and analyzed for δ15NNO3. Surface mass balance data comes from a combination of previous ground-based observations (e.g., stakes, ice core data) and the output from Modèle Atmosphérique Régional version 3.6.4 with European Centre for Medium-Range Weather Forecasts “Interim†re-analysis data (ERA-interim) data, adjusted for observed model SMB biases. Elevation data were extracted from the Reference Elevation Model of Antarctica (REMA, https://doi.org/10.5194/tc-13-665-2019). Also contains nitrate concentration and isotopic (δ15NNO3) data, ice density, and surface mass balance estimates from the ABN1314-103 ice core. This 103 m long core was drilled beginning on 07 January 2014 as one of three ice cores at Aurora Basin North, Antarctica (-71.17, 111.37, 2679 m.a.s.l), in the 2013-2014 field season. The age-depth model for ABN1314-103 was matched through ion profiles from an annually-resolved model (ALC01112018) originally developed for one of the other ABN cores through seasonal ion and water isotope cycles and constrained by volcanic horizons. Each 1 m segment of the core was weighed and measured for ice density calculations, and then sampled for nitrate at 0.33 m resolution. Nitrate concentrations were taken on melted ice aliquots with ion chromatography, while isotopic analysis was achieved through bacterial denitrification and MAT 253 mass spectrometry after concentrating with anionic resin. Using the density data and the age-depth model’s dates for the top and bottom of each 1 m core segment, we reconstructed a history of surface mass balance changes as recorded in ABN1314-103. Additionally, we also estimated the effect of upstream topographic changes on the ice core’s surface mass balance record through a ground penetrating radar transect that extended 11.5 km against the direction of glacial ice flow. The modern SMB changes along this upstream transect were linked to ABN1314-103 core depths by through the local horizontal ice flow rate (16.2 m a-1) and the core’s age-depth model, and included here for comparative analysis.",mds,True,findable,0,0,0,0,0,2021-12-20T14:57:45.000Z,2021-12-20T14:57:45.000Z,cern.zenodo,cern,,,,
+10.57726/9c6a-cb74,"La Maison de Savoie et les Alpes: emprise, innovation, identification",Presses Universitaires Savoie Mont Blanc,2015,fr,Book,,,fabricaForm,True,findable,0,0,0,0,0,2022-03-14T08:25:25.000Z,2022-03-14T08:25:25.000Z,pusmb.prod,pusmb,FOS: Humanities,"[{'subject': 'FOS: Humanities', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['439 pages'],
+10.5281/zenodo.61611,Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution,Zenodo,2016,,Software,"GNU General Public License v2.0 only,Open Access","<strong>This sources presents the technical implementation of a new, probabilistic version based on NEMO 3.5 ocean/sea-ice modelling system (Bessières et al., 2017).</strong> Ensemble simulations with N members running simultaneously within a single executable, and interacting mutually if needed, are made possible through an enhanced MPI strategy including a double parallelization in the spatial and ensemble dimensions. An example application is then given to illustrate the implementation, performances and potential use of this novel probabilistic modelling tool. A large ensemble of 50 global ocean/sea-ice hindcasts has been performed over the period 1960-2015 at eddy-permitting resolution (1/4 o ) for the OCCIPUT project. This application is aimed to simultaneously simulate the intrinsic/chaotic and the atmospherically-forced contributions to the ocean variability, from meso-scale turbulence to interannual-to-multidecadal time scales. Such an ensemble indeed provides a unique way to disentangle and study both contributions, as the forced variability may be estimated through the ensemble mean, and the intrinsic chaotic variability may be estimated through the ensemble spread. <strong>Reference</strong>: Bessières, L., Leroux, S., Brankart, J.-M., Molines, J.-M., Moine, M.-P., Bouttier, P.-A., Penduff, T., Terray, L., Barnier, B., and Sérazin, G.: <em>Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution</em>, Geosci. Model Dev., 10, 1091-1106, doi:10.5194/gmd-10-1091-2017, 2017.",mds,True,findable,0,0,0,0,0,2016-09-06T09:54:06.000Z,2016-09-06T09:54:07.000Z,cern.zenodo,cern,"NEMO,Ocean Modelling,Eddy-permitting,Probabilist ocean,Intrinsic variability,Ensemble simulation,OCCIPUT project","[{'subject': 'NEMO'}, {'subject': 'Ocean Modelling'}, {'subject': 'Eddy-permitting'}, {'subject': 'Probabilist ocean'}, {'subject': 'Intrinsic variability'}, {'subject': 'Ensemble simulation'}, {'subject': 'OCCIPUT project'}]",,
+10.5281/zenodo.4573897,Nanoscale Dynamics of Peptidoglycan Assembly during the Cell Cycle of Streptococcus pneumoniae,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Raw phase contrast images to analyze the shape of <em>Streptococcus pneumoniae</em> cells in the presence of aDA-DA. Raw phase contrast and diffraction-limited images to determine the aDA-DA concentration to use for peptidoglycan labeling in <em>S. pneumoniae</em>. Raw phase contrast and diffraction-limited images to determine the effect of D-cycloserine on aDA and aDA-DA incorporation in <em>S. pneumoniae</em>. Raw bright field, diffraction-limited and dSTORM images to determine the duration of the incubation period with aDA-DA for peptidoglycan labeling in <em>S. pneumoniae</em>. Raw western blot images to analyze the depletion level of PBP2b in <em>S. pneumoniae</em>. Raw bright field, diffraction-limited and dSTORM images to analyze peptidoglycan synthesis in <em>S. pneumoniae</em>.",mds,True,findable,0,0,0,0,0,2021-03-09T14:53:30.000Z,2021-03-09T14:53:31.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3817437,"Search Queries for ""Mapping Research Output to the Sustainable Development Goals (SDGs)"" v3.0",Zenodo,2019,,Software,"Creative Commons Attribution 4.0 International,Open Access","<strong>This package contains machine readable (xml) search queries, for the Scopus publication database, to find domain specific research output that are related to the 17 Sustainable Development Goals (SDGs).</strong> Sustainable Development Goals are the 17 global challenges set by the United Nations. Within each of the goals specific targets and indicators are mentioned to monitor the progress of reaching those goals by 2030. In an effort to capture how research is contributing to move the needle on those challenges, we earlier have made an initial classification model than enables to quickly identify what research output is related to what SDG. (This Aurora SDG dashboard is the initial outcome as <em>proof of practice</em>.) The initiative started from the Aurora Universities Network in 2017, in the working group ""Societal Impact and Relevance of Research"", to investigate and to make visible 1. what research is done that are relevant to topics or challenges that live in society (for the proof of practice this has been scoped down to the SDGs), and 2. what the effect or impact is of implementing those research outcomes to those societal challenges (this also have been scoped down to research output being cited in policy documents from national and local governments an NGO's). The classification model we have used are 17 different search queries on the Scopus database. The search queries are elegant constructions with keyword combinations and boolean operators, in the syntax specific to the Scopus Query Language. We have used Scopus because it covers more research area's that are relevant to the SDG's, and we could filter much easier the Aurora Institutions. <strong>Versions</strong> Different versions of the search queries have been made over the past years to improve the precision (soundness) and recall (completeness) of the results. The queries have been made in a team effort by several bibliometric experts from the Aurora Universities. Each one did two or 3 SDG's, and than reviewed each other's work. v1.0 January 2018<em> Initial 'strict' version.</em> In this version only the terms were used that appear in the SDG policy text of the targets and indicators defined by the UN. At this point we have been aware of the SDSN Compiled list of keywords, and used them as inspiration. Rule of thumb was to use <em>keyword-combination searches</em> as much as possible rather than <em>single-keyword searches</em>, to be more precise rather than to yield large amounts of false positive papers. Also we did not use the inverse or 'NOT' operator, to prevent removing true positives from the result set. This version has not been reviewed by peers. Download from: GitHub / Zenodo v2.0 March 2018<em> Reviewed 'strict' version.</em> Same as version 1, but now reviewed by peers. Download from: GitHub / Zenodo v3.0 May 2019 <em>'echo chamber' version.</em> We noticed that using strictly the terms that policy makers of the UN use in the targets and indicators, that much of the research that did not use that specific terms was left out in the result set. (eg. ""mortality"" vs ""deaths"") To increase the recall, without reducing precision of the papers in the results, we added keywords that were obvious synonyms and antonyms to the existing 'strict' keywords. This was done based on the keywords that appeared in papers in the result set of version 2. This creates an 'echo chamber', that results in more of the same papers. Download from: GitHub / Zenodo v4.0 August 2019<em> uniform 'split' version.</em> Over the course of the years, the UN changed and added Targets and indicators. In order to keep track of if we missed a target, we have split the queries to match the targets within the goals. This gives much more control in maintenance of the queries. Also in this version the use of brackets, quotation marks, etc. has been made uniform, so it also works with API's, and not only with GUI's. His version has been used to evaluate using a survey, to get baseline measurements for the precision and recall. Published here: Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. Download from: GitHub / Zenodo v5.0 June 2020 <em>'improved' version.</em> In order to better reflect academic representation of research output that relate to the SDG's, we have added more keyword combinations to the queries to increase the recall, to yield more research papers related to the SDG's, using academic terminology. We mainly used the input from the Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. We ran several text analyses: Frequent term combination in title and abstracts from Suggested papers, and in selected (accepted) papers, suggested journals, etc. Secondly we got inspiration out of the Elsevier SDG queries Jayabalasingham, Bamini; Boverhof, Roy; Agnew, Kevin; Klein, Lisette (2019), “Identifying research supporting the United Nations Sustainable Development Goalsâ€, Mendeley Data, v1 https://dx.doi.org/10.17632/87txkw7khs.1. Download from: GitHub / Zenodo <strong>Contribute and improve the SDG Search Queries</strong> We welcome you to join the Github community and to fork, improve and make a pull request to add your improvements to the new version of the SDG queries. <strong>https://github.com/Aurora-Network-Global/sdg-queries</strong>",mds,True,findable,3,0,2,0,0,2020-05-15T13:26:26.000Z,2020-05-15T13:26:27.000Z,cern.zenodo,cern,"Sustainable Development Goals,SDG,Classification model,Search Queries,SCOPUS","[{'subject': 'Sustainable Development Goals'}, {'subject': 'SDG'}, {'subject': 'Classification model'}, {'subject': 'Search Queries'}, {'subject': 'SCOPUS'}]",,
+10.5281/zenodo.5763672,Dataset for Spatial Heterogeneity of Uplift Pattern in the Western European Alps Revealed by InSAR Time Series Analysis,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",ZIP file with InSAR raw and smoothed final velocity solution values,mds,True,findable,0,0,0,0,0,2021-12-07T10:30:20.000Z,2021-12-07T10:30:21.000Z,cern.zenodo,cern,"Insar velocities,Western Alps","[{'subject': 'Insar velocities'}, {'subject': 'Western Alps'}]",,
+10.5281/zenodo.7961207,A new inventory of High Mountain Asia surging glaciers derived from multiple elevation datasets since the 1970s,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Glacier surging is an unusual undulation instability of ice flow and complete surging glacier inventories are important for regional mass balance studies and assessing glacier-related hazards. Glacier surge events in High Mountain Asia (HMA) are widely reported. Through the estimated elevation changes from multiple DEMs sources that acquired from 1970s to 2020, and morphologic changes from 1986 to 2021, here we present a new surging glacier inventory across HMA. The inventory has incorporated 890 surging and 336 surge-like glaciers, each glacier is assigned with indicators of surging feature and surge possibility. Compared to previous surging glacier inventory in HMA, our inventory is theoretically more complete because of the much longer observation period. This data repository contains the surging glacier inventory and glacier elevation change maps. The inventory is stored in the format of GeoPackage (.gpkg) and ESRI Shapefile format (.shp), which is represented by glacier polygon (from GAMDAM2) or surface point with geometric attributes. The multi-temporal elevation change maps of identified surging glaciers were divided into 1×1° tiles, storing in the format of GeoTiff(*.tif). Detailed description of the dataset including the file contents and attributes information can be found in the metadata file (README.txt).",mds,True,findable,0,0,0,0,0,2023-05-24T04:24:15.000Z,2023-05-24T04:24:16.000Z,cern.zenodo,cern,"High Mountain Asia, Surging glacier inventory, Elevation change, Digital Elevation Model (DEM)","[{'subject': 'High Mountain Asia, Surging glacier inventory, Elevation change, Digital Elevation Model (DEM)'}]",,
+10.5281/zenodo.4048589,Sources of particulate matter air pollution and its oxidative potential in Europes,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data presented in the manuscript ""Sources of particulate matter air pollution and its oxidative potential in Europe"" (https://doi.org/10.1038/s41586-020-2902-8) by Daellenbach et al. (2020).",mds,True,findable,0,0,0,0,0,2020-11-18T16:07:33.000Z,2020-11-18T16:07:34.000Z,cern.zenodo,cern,"particulate air pollution,health effects,oxidative potential","[{'subject': 'particulate air pollution'}, {'subject': 'health effects'}, {'subject': 'oxidative potential'}]",,
+10.5281/zenodo.10053093,COSIPY distributed simulations of Mera Glacier mass and energy balance (20161101-20201101),Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Creative Commons Attribution Share Alike 4.0 International","The four netCDF files contain outputs from COSIPY model (Sauter et al., 2020) for Mera Glacier for the period 20161101 to 20201101. The model is run on a 0.003°*0.003° grid, and forced with meteological variables collected locally and distributed with constant gradients. The ""constants.py"" is the python file that contains the specific model settings.",api,True,findable,0,0,0,0,0,2023-10-30T09:06:58.000Z,2023-10-30T09:06:58.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4282267,SPEECH-COCO,Zenodo,2017,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>SpeechCoco</strong> <em>Introduction</em> Our corpus is an extension of the MS COCO image recognition and captioning dataset. MS COCO comprises images paired with a set of five captions. Yet, it does not include any speech. Therefore, we used Voxygen's text-to-speech system to synthesise the available captions. The addition of speech as a new modality enables MSCOCO to be used for researches in the field of language acquisition, unsupervised term discovery, keyword spotting, or semantic embedding using speech and vision. Our corpus is licensed under a Creative Commons Attribution 4.0 License. <em>Data Set</em> This corpus contains <strong>616,767</strong> spoken captions from MSCOCO's val2014 and train2014 subsets (respectively 414,113 for train2014 and 202,654 for val2014). We used 8 different voices. 4 of them have a British accent (Paul, Bronwen, Judith, and Elizabeth) and the 4 others have an American accent (Phil, Bruce, Amanda, Jenny). In order to make the captions sound more natural, we used SOX <em>tempo</em> command, enabling us to change the speed without changing the pitch. 1/3 of the captions are 10% slower than the original pace, 1/3 are 10% faster. The last third of the captions was kept untouched. We also modified approximately 30% of the original captions and added <strong>disfluencies</strong> such as ""um"", ""uh"", ""er"" so that the captions would sound more natural. Each WAV file is paired with a JSON file containing various information: timecode of each word in the caption, name of the speaker, name of the WAV file, etc. The JSON files have the following data structure: <pre><code class=""language-json"">{ ""duration"": float, ""speaker"": string, ""synthesisedCaption"": string, ""timecode"": list, ""speed"": float, ""wavFilename"": string, ""captionID"": int, ""imgID"": int, ""disfluency"": list }</code></pre> On average, each caption comprises 10.79 tokens, disfluencies included. The WAV files are on average 3.52 seconds long. <em>Repository</em> The repository is organized as follows: CORPUS-MSCOCO (~75GB once decompressed) <strong>train2014/</strong> : folder contains 413,915 captions json/ wav/ translations/ train_en_ja.txt train_translate.sqlite3 train_2014.sqlite3 <strong>val2014/</strong> : folder contains 202,520 captions json/ wav/ translations/ train_en_ja.txt train_translate.sqlite3 val_2014.sqlite3 <strong>speechcoco_API/</strong> speechcoco/ __init__.py speechcoco.py setup.py <em>Filenames</em> <strong>.wav</strong> files contain the spoken version of a caption <strong>.json</strong> files contain all the metadata of a given WAV file <strong>.sqlite3</strong> files are SQLite databases containing all the information contained in the JSON files We adopted the following naming convention for both the WAV and JSON files: <em>imageID_captionID_Speaker_DisfluencyPosition_Speed[.wav/.json]</em> <em>Script</em> We created a script called <strong>speechcoco.py</strong> in order to handle the metadata and allow the user to easily find captions according to specific filters. The script uses the *.db files. Features: <strong>Aggregate all the information in the JSON files into a single SQLite database</strong> <strong>Find captions according to specific filters (name, gender and nationality of the speaker, disfluency position, speed, duration, and words in the caption).</strong> <em>The script automatically builds the SQLite query. The user can also provide his own SQLite query.</em> <em>The following Python code returns all the captions spoken by a male with an American accent for which the speed was slowed down by 10% and that contain ""keys"" at any position</em> <pre><code class=""language-python""># create SpeechCoco object db = SpeechCoco(train_2014.sqlite3, train_translate.sqlite3, verbose=True) # filter captions (returns Caption Objects) captions = db.filterCaptions(gender=""Male"", nationality=""US"", speed=0.9, text='%keys%') for caption in captions: print('\n{}\t{}\t{}\t{}\t{}\t{}\t\t{}'.format(caption.imageID, caption.captionID, caption.speaker.name, caption.speaker.nationality, caption.speed, caption.filename, caption.text))</code></pre> <pre><code>... 298817 26763 Phil 0.9 298817_26763_Phil_None_0-9.wav A group of turkeys with bushes in the background. 108505 147972 Phil 0.9 108505_147972_Phil_Middle_0-9.wav Person using a, um, slider cell phone with blue backlit keys. 258289 154380 Bruce 0.9 258289_154380_Bruce_None_0-9.wav Some donkeys and sheep are in their green pens . 545312 201303 Phil 0.9 545312_201303_Phil_None_0-9.wav A man walking next to a couple of donkeys. ...</code></pre> <strong>Find all the captions belonging to a specific image</strong> <pre><code class=""language-python"">captions = db.getImgCaptions(298817) for caption in captions: print('\n{}'.format(caption.text))</code></pre> <pre><code>Birds wondering through grassy ground next to bushes. A flock of turkeys are making their way up a hill. Um, ah. Two wild turkeys in a field walking around. Four wild turkeys and some bushes trees and weeds. A group of turkeys with bushes in the background.</code></pre> <strong>Parse the timecodes and have them structured</strong> <strong>input</strong>: <pre><code>... [1926.3068, ""SYL"", """"], [1926.3068, ""SEPR"", "" ""], [1926.3068, ""WORD"", ""white""], [1926.3068, ""PHO"", ""w""], [2050.7955, ""PHO"", ""ai""], [2144.6591, ""PHO"", ""t""], [2179.3182, ""SYL"", """"], [2179.3182, ""SEPR"", "" ""] ...</code></pre> <strong>output</strong>: <pre><code class=""language-python"">print(caption.timecode.parse())</code></pre> <pre><code>... { 'begin': 1926.3068, 'end': 2179.3182, 'syllable': [{'begin': 1926.3068, 'end': 2179.3182, 'phoneme': [{'begin': 1926.3068, 'end': 2050.7955, 'value': 'w'}, {'begin': 2050.7955, 'end': 2144.6591, 'value': 'ai'}, {'begin': 2144.6591, 'end': 2179.3182, 'value': 't'}], 'value': 'wait'}], 'value': 'white' }, ...</code></pre> <strong>Convert the timecodes to Praat TextGrid files</strong> <pre><code class=""language-python"">caption.timecode.toTextgrid(outputDir, level=3)</code></pre> <strong>Get the words, syllables and phonemes between</strong> <em>n</em> <strong>seconds/milliseconds</strong> <em>The following Python code returns all the words between 0.2 and 0.6 seconds for which at least 50% of the word's total length is within the specified interval</em> <pre><code class=""language-python"">pprint(caption.getWords(0.20, 0.60, seconds=True, level=1, olapthr=50))</code></pre> <pre><code>... 404537 827239 Bruce US 0.9 404537_827239_Bruce_None_0-9.wav Eyeglasses, a cellphone, some keys and other pocket items are all laid out on the cloth. . [ { 'begin': 0.0, 'end': 0.7202778, 'overlapPercentage': 55.53412863758955, 'word': 'eyeglasses' } ] ...</code></pre> <strong>Get the translations of the selected captions</strong> <em>As for now, only japanese translations are available. We also used</em> Kytea <em>to tokenize and tag the captions translated with Google Translate</em> <pre><code class=""language-python"">captions = db.getImgCaptions(298817) for caption in captions: print('\n{}'.format(caption.text)) # Get translations and POS print('\tja_google: {}'.format(db.getTranslation(caption.captionID, ""ja_google""))) print('\t\tja_google_tokens: {}'.format(db.getTokens(caption.captionID, ""ja_google""))) print('\t\tja_google_pos: {}'.format(db.getPOS(caption.captionID, ""ja_google""))) print('\tja_excite: {}'.format(db.getTranslation(caption.captionID, ""ja_excite"")))</code></pre> <pre><code> Birds wondering through grassy ground next to bushes. ja_google: é³¥ã¯èŒ‚ã¿ã®ä¸‹ã«èŒ‚ã£ãŸåœ°é¢ã‚’抱ãˆã¦ã„ã¾ã™ã€‚ ja_google_tokens: é³¥ 㯠茂㿠㮠下 㫠茂 ã£ ãŸ åœ°é¢ ã‚’ 抱㈠㦠ㄠ㾠㙠。 ja_google_pos: é³¥/åè©ž/ã¨ã‚Š ã¯/助詞/㯠茂ã¿/åè©ž/ã—ã’ã¿ ã®/助詞/㮠下/åè©ž/ã—㟠ã«/助詞/㫠茂/å‹•è©ž/ã—ã’ ã£/語尾/㣠ãŸ/助動詞/㟠地é¢/åè©ž/ã˜ã‚ã‚“ ã‚’/助詞/ã‚’ 抱ãˆ/å‹•è©ž/ã‹ã‹ãˆ ã¦/助詞/㦠ã„/å‹•è©ž/ã„ ã¾/助動詞/ã¾ ã™/語尾/㙠。/補助記å·/。 ja_excite: 低木ã¨éš£æŽ¥ã—ãŸè‰æ·±ã„グラウンドを通ã£ã¦ç–‘ã†é³¥ã€‚ A flock of turkeys are making their way up a hill. ja_google: 七é¢é³¥ã®ç¾¤ã‚ŒãŒä¸˜ã‚’上ã£ã¦ã„ã¾ã™ã€‚ ja_google_tokens: 七 é¢ é³¥ 㮠群れ ㌠丘 ã‚’ 上 㣠㦠ㄠ㾠㙠。 ja_google_pos: 七/åè©ž/ãªãª é¢/åè©ž/ã‚ã‚“ é³¥/åè©ž/ã¨ã‚Š ã®/助詞/㮠群れ/åè©ž/むれ ãŒ/助詞/㌠丘/åè©ž/ãŠã‹ ã‚’/助詞/ã‚’ 上/å‹•è©ž/ã®ã¼ ã£/語尾/㣠ã¦/助詞/㦠ã„/å‹•è©ž/ã„ ã¾/助動詞/ã¾ ã™/語尾/㙠。/補助記å·/。 ja_excite: 七é¢é³¥ã®ç¾¤ã‚Œã¯ä¸˜ã®ä¸Šã§é€²ã‚“ã§ã„る。 Um, ah. Two wild turkeys in a field walking around. ja_google: 野生ã®ã‚·ãƒãƒ¡ãƒ³ãƒãƒ§ã‚¦ã€é‡Žç”Ÿã®ä¸ƒé¢é³¥ ja_google_tokens: 野生 ã® ã‚·ãƒãƒ¡ãƒ³ãƒãƒ§ã‚¦ 〠野生 㮠七 é¢ é³¥ ja_google_pos: 野生/åè©ž/ã‚„ã›ã„ ã®/助詞/ã® ã‚·ãƒãƒ¡ãƒ³ãƒãƒ§ã‚¦/åè©ž/ã—ã¡ã‚ã‚“ã¡ã‚‡ã† ã€/補助記å·/〠野生/åè©ž/ã‚„ã›ã„ ã®/助詞/㮠七/åè©ž/ãªãª é¢/åè©ž/ã‚ã‚“ é³¥/åè©ž/ã¡ã‚‡ã† ja_excite: ã¾ã‚ã‚Šã§ç§»å‹•ã—ã¦ã„るフィールドã®2ç¾½ã®é‡Žç”Ÿã®ä¸ƒé¢é³¥ Four wild turkeys and some bushes trees and weeds. ja_google: 4本ã®é‡Žç”Ÿã®ã‚·ãƒãƒ¡ãƒ³ãƒãƒ§ã‚¦ã¨ã„ãã¤ã‹ã®èŒ‚ã¿ã®æœ¨ã¨é›‘è‰ ja_google_tokens: 4 本 㮠野生 ã® ã‚·ãƒãƒ¡ãƒ³ãƒãƒ§ã‚¦ 㨠ã„ã 㤠㋠㮠茂㿠㮠木 ã¨ é›‘è‰ ja_google_pos: 4/åè©ž/4 本/接尾辞/ã»ã‚“ ã®/助詞/㮠野生/åè©ž/ã‚„ã›ã„ ã®/助詞/ã® ã‚·ãƒãƒ¡ãƒ³ãƒãƒ§ã‚¦/åè©ž/ã—ã¡ã‚ã‚“ã¡ã‚‡ã† ã¨/助詞/㨠ã„ã/åè©ž/ã„ã ã¤/接尾辞/㤠ã‹/助詞/ã‹ ã®/助詞/㮠茂ã¿/åè©ž/ã—ã’ã¿ ã®/助詞/㮠木/åè©ž/ã ã¨/助詞/㨠雑è‰/åè©ž/ã–ã£ãㆠja_excite: 4ç¾½ã®é‡Žç”Ÿã®ä¸ƒé¢é³¥ãŠã‚ˆã³ã„ãã¤ã‹ã®ä½Žæœ¨æœ¨ã¨é›‘è‰ A group of turkeys with bushes in the background. ja_google: 背景ã«èŒ‚ã¿ã‚’æŒã¤ä¸ƒé¢é³¥ã®ç¾¤ ja_google_tokens: 背景 㫠茂㿠を æŒ ã¤ ä¸ƒ é¢ é³¥ 㮠群 ja_google_pos: 背景/åè©ž/ã¯ã„ã‘ã„ ã«/助詞/㫠茂ã¿/åè©ž/ã—ã’ã¿ ã‚’/助詞/ã‚’ æŒ/å‹•è©ž/ã‚‚ ã¤/語尾/㤠七/åè©ž/ãªãª é¢/åè©ž/ã‚ã‚“ é³¥/åè©ž/ã¡ã‚‡ã† ã®/助詞/㮠群/åè©ž/むれ ja_excite: 背景ã®ä½Žæœ¨ã‚’æŒã¤ä¸ƒé¢é³¥ã®ã‚°ãƒ«ãƒ¼ãƒ—</code></pre>",mds,True,findable,0,0,0,0,0,2020-11-23T13:46:36.000Z,2020-11-23T13:46:37.000Z,cern.zenodo,cern,"MSCOCO,VGS,Speech,Visually Grounded Speech,audio,captions","[{'subject': 'MSCOCO'}, {'subject': 'VGS'}, {'subject': 'Speech'}, {'subject': 'Visually Grounded Speech'}, {'subject': 'audio'}, {'subject': 'captions'}]",,
+10.6084/m9.figshare.c.6586643.v1,Digital technologies in routine palliative care delivery: an exploratory qualitative study with health care professionals in Germany,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Objective To explore health care professionals’ (HCPs) perspectives, experiences and preferences towards digital technology use in routine palliative care delivery. Methods HCPs (n = 19) purposively selected from a sample of settings that reflect routine palliative care delivery (i.e. specialized outpatient palliative care, inpatient palliative care, inpatient hospice care in both rural and urban areas of the German states of Brandenburg and Berlin) participated in an explorative, qualitative study using semi-structured interviews. Interview data were analyzed using structured qualitative content analysis. Results Digital technologies are widely used in routine palliative care and are well accepted by HCPs. Central functions of digital technologies as experienced in palliative care are coordination of work processes, patient-centered care, and communication. Especially in outpatient care, they facilitate overcoming spatial and temporal distances. HCPs attribute various benefits to digital technologies that contribute to better coordinated, faster, more responsive, and overall more effective palliative care. Simultaneously, participants preferred technology as an enhancement not replacement of care delivery. HCPs fear that digital technologies, if overused, will contribute to dehumanization and thus significantly reduce the quality of palliative care. Conclusion Digital technology is already an essential part of routine palliative care delivery. While generally perceived as useful by HCPs, digital technologies are considered as having limitations and carrying risks. Hence, their use and consequences must be carefully considered, as they should discreetly complement but not replace human interaction in palliative care delivery.",mds,True,findable,0,0,0,0,0,2023-04-13T12:27:58.000Z,2023-04-13T12:27:58.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}]",,
+10.6084/m9.figshare.c.6604292,Predictors of changing patterns of adherence to containment measures during the early stage of COVID-19 pandemic: an international longitudinal study,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background Identifying common factors that affect public adherence to COVID-19 containment measures can directly inform the development of official public health communication strategies. The present international longitudinal study aimed to examine whether prosociality, together with other theoretically derived motivating factors (self-efficacy, perceived susceptibility and severity of COVID-19, perceived social support) predict the change in adherence to COVID-19 containment strategies. Method In wave 1 of data collection, adults from eight geographical regions completed online surveys beginning in April 2020, and wave 2 began in June and ended in September 2020. Hypothesized predictors included prosociality, self-efficacy in following COVID-19 containment measures, perceived susceptibility to COVID-19, perceived severity of COVID-19 and perceived social support. Baseline covariates included age, sex, history of COVID-19 infection and geographical regions. Participants who reported adhering to specific containment measures, including physical distancing, avoidance of non-essential travel and hand hygiene, were classified as adherence. The dependent variable was the category of adherence, which was constructed based on changes in adherence across the survey period and included four categories: non-adherence, less adherence, greater adherence and sustained adherence (which was designated as the reference category). Results In total, 2189 adult participants (82% female, 57.2% aged 31–59 years) from East Asia (217 [9.7%]), West Asia (246 [11.2%]), North and South America (131 [6.0%]), Northern Europe (600 [27.4%]), Western Europe (322 [14.7%]), Southern Europe (433 [19.8%]), Eastern Europe (148 [6.8%]) and other regions (96 [4.4%]) were analyzed. Adjusted multinomial logistic regression analyses showed that prosociality, self-efficacy, perceived susceptibility and severity of COVID-19 were significant factors affecting adherence. Participants with greater self-efficacy at wave 1 were less likely to become non-adherence at wave 2 by 26% (adjusted odds ratio [aOR], 0.74; 95% CI, 0.71 to 0.77; P < .001), while those with greater prosociality at wave 1 were less likely to become less adherence at wave 2 by 23% (aOR, 0.77; 95% CI, 0.75 to 0.79; P = .04). Conclusions This study provides evidence that in addition to emphasizing the potential severity of COVID-19 and the potential susceptibility to contact with the virus, fostering self-efficacy in following containment strategies and prosociality appears to be a viable public health education or communication strategy to combat COVID-19.",mds,True,findable,0,0,0,0,0,2023-04-18T04:38:34.000Z,2023-04-18T04:38:34.000Z,figshare.ars,otjm,"Medicine,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.10276253,3D roughness computation from XCT data - Data and Python & ImageJ implementations,Zenodo,2023,en,ComputationalNotebook,CeCILL Free Software License Agreement v2.1,"Data provided in supplement of the research article ""A methodology for the 3D characterization of surfaces using X-ray computed tomography: application to additively manufactured parts"", F.Steinhilber, J.Lachambre, D.Cœurjolly, J.Y.Buffière, G.Martin, R.Dendievel.
+Â
+It contains 3 folders:
+- ""data"": a dataset used to present the roughness computation methodology in the article (= the XCT scan of a 2 mm cylinder fabricated by Electron Powder Bed Fusion, with a voxel size of 5 µm). The results of the roughness computation are also provided in this folder.
+- ""Python"": the Python implementation of the roughness computation methodology presented in the article, as well as some other calculations, such as the computation of the triangle threshold for bimodal histograms introduced in the article.
+- ""ImageJ"": the ImageJ implementation (simple macro) of the roughness computation methodology presented in the article, as well as some other calculations, such as the computation of the triangle threshold for bimodal histograms introduced in the article.
+Â
+Each folder contains a README file that further details the different files provided.",api,True,findable,0,0,0,0,0,2023-12-06T09:53:00.000Z,2023-12-06T09:53:00.000Z,cern.zenodo,cern,"Surface roughness,X-ray Computed Tomography,Python,ImageJ,3D","[{'subject': 'Surface roughness'}, {'subject': 'X-ray Computed Tomography'}, {'subject': 'Python'}, {'subject': 'ImageJ'}, {'subject': '3D'}]",,
+10.6084/m9.figshare.23822160.v1,File 6 : Matlab file for part 2 and of the experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,File 6 : This matlab file corresponds to the adaptation and post adaptation PSE measures and should be launched second.,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:28.000Z,2023-08-02T11:18:28.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['20342 Bytes'],
+10.5281/zenodo.4883250,"Search Queries for ""Mapping Research Output to the Sustainable Development Goals (SDGs)"" v5.0.2",Zenodo,2020,,Software,"Creative Commons Attribution 4.0 International,Open Access","<strong>This package contains machine readable (xml) search queries, for the Scopus publication database, to find domain specific research output that are related to the 17 Sustainable Development Goals (SDGs).</strong> <strong>[ SDG QUERIES PAGES ] [ PROJECT WEBSITE ] [ FORK ON GITHUB ]</strong> Sustainable Development Goals are the 17 global challenges set by the United Nations. Within each of the goals specific targets and indicators are mentioned to monitor the progress of reaching those goals by 2030. In an effort to capture how research is contributing to move the needle on those challenges, we earlier have made an initial classification model than enables to quickly identify what research output is related to what SDG. (This Aurora SDG dashboard is the initial outcome as <em>proof of practice</em>.) The initiative started from the Aurora Universities Network in 2017, in the working group ""Societal Impact and Relevance of Research"", to investigate and to make visible 1. what research is done that are relevant to topics or challenges that live in society (for the proof of practice this has been scoped down to the SDGs), and 2. what the effect or impact is of implementing those research outcomes to those societal challenges (this also have been scoped down to research output being cited in policy documents from national and local governments an NGO's). The classification model we have used are 17 different search queries on the Scopus database. The search queries are elegant constructions with keyword combinations and boolean operators, in the syntax specific to the Scopus Query Language. We have used Scopus because it covers more research area's that are relevant to the SDG's, and we could filter much easier the Aurora Institutions. <strong>Versions</strong> Different versions of the search queries have been made over the past years to improve the precision (soundness) and recall (completeness) of the results. The queries have been made in a team effort by several bibliometric experts from the Aurora Universities. Each one did two or 3 SDG's, and than reviewed each other's work. v1.0 January 2018<em> Initial 'strict' version.</em> In this version only the terms were used that appear in the SDG policy text of the targets and indicators defined by the UN. At this point we have been aware of the SDSN Compiled list of keywords, and used them as inspiration. Rule of thumb was to use <em>keyword-combination searches</em> as much as possible rather than <em>single-keyword searches</em>, to be more precise rather than to yield large amounts of false positive papers. Also we did not use the inverse or 'NOT' operator, to prevent removing true positives from the result set. This version has not been reviewed by peers. Download from: GitHub / Zenodo v2.0 March 2018<em> Reviewed 'strict' version.</em> Same as version 1, but now reviewed by peers. Download from: GitHub / Zenodo v3.0 May 2019 <em>'echo chamber' version.</em> We noticed that using strictly the terms that policy makers of the UN use in the targets and indicators, that much of the research that did not use that specific terms was left out in the result set. (eg. ""mortality"" vs ""deaths"") To increase the recall, without reducing precision of the papers in the results, we added keywords that were obvious synonyms and antonyms to the existing 'strict' keywords. This was done based on the keywords that appeared in papers in the result set of version 2. This creates an 'echo chamber', that results in more of the same papers. Download from: GitHub / Zenodo v4.0 August 2019<em> uniform 'split' version.</em> Over the course of the years, the UN changed and added Targets and indicators. In order to keep track of if we missed a target, we have split the queries to match the targets within the goals. This gives much more control in maintenance of the queries. Also in this version the use of brackets, quotation marks, etc. has been made uniform, so it also works with API's, and not only with GUI's. His version has been used to evaluate using a survey, to get baseline measurements for the precision and recall. Published here: Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. Download from: GitHub / Zenodo v5.0 June 2020 <em>'improved' version.</em> In order to better reflect academic representation of research output that relate to the SDG's, we have added more keyword combinations to the queries to increase the recall, to yield more research papers related to the SDG's, using academic terminology. We mainly used the input from the Survey data of ""Mapping Research output to the SDGs"" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. We ran several text analyses: Frequent term combination in title and abstracts from Suggested papers, and in selected (accepted) papers, suggested journals, etc.found in this data set Spielberg, Eike, & Hasse, Linda. (2020). Text Analyses of Survey Data on ""Mapping Research Output to the Sustainable Development Goals (SDGs)"" (Version 1.0) [Data set]. Zenodo http://doi.org/10.5281/zenodo.3832090 . Secondly we got inspiration out of the Elsevier SDG queries Jayabalasingham, Bamini; Boverhof, Roy; Agnew, Kevin; Klein, Lisette (2019), “Identifying research supporting the United Nations Sustainable Development Goalsâ€, Mendeley Data, v1 https://dx.doi.org/10.17632/87txkw7khs.1. And thirdly we got inspiration from this controlled vocabulary containing closely related terms. Duran-Silva, Nicolau, Fuster, Enric, Massucci, Francesco Alessandro, & Quinquillà , Arnau. (2019). <em>A controlled vocabulary defining the semantic perimeter of Sustainable Development Goals</em> (Version 1.2) [Data set]. Zenodo. doi.org/10.5281/zenodo.3567769 Download from: GitHub / Zenodo <strong>Contribute and improve the SDG Search Queries</strong> We welcome you to join the Github community and to fork, improve and make a pull request to add your improvements to the new version of the SDG queries. <strong>https://aurora-network-global.github.io/sdg-queries/</strong>",mds,True,findable,0,0,2,5,0,2021-05-31T13:11:12.000Z,2021-05-31T13:11:13.000Z,cern.zenodo,cern,"Sustainable Development Goals,SDG,Classification model,Search Queries,SCOPUS,Text indexing,Controlled vocabulary,http://metadata.un.org/sdg/","[{'subject': 'Sustainable Development Goals'}, {'subject': 'SDG'}, {'subject': 'Classification model'}, {'subject': 'Search Queries'}, {'subject': 'SCOPUS'}, {'subject': 'Text indexing'}, {'subject': 'Controlled vocabulary'}, {'subject': 'http://metadata.un.org/sdg/', 'subjectScheme': 'url'}]",,
+10.5281/zenodo.4964207,"FIGURES 13–16 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 13–16. Protonemura bispina sp. n., 13. male, epiproct, lateral view. 14. male, epiproct, lateral view. 15. male terminalia with epiproct, dorsal view. 16. male terminalia, ventral view",mds,True,findable,0,0,5,0,0,2021-06-16T08:25:02.000Z,2021-06-16T08:25:05.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.1443459,Parrot,Zenodo,2018,en,Dataset,"Creative Commons Attribution 4.0,Open Access","The netCDF files ""SF*.nc"" that can be found in the repository ""Parrot_experiment"" contain the experimental results of intense sediment transport experiments (sheet flow) carried out in the LEGI tilting flume with two sizes of uniformly distributed acrylic particles having median diameters of 1 mm (S1 experiment) and 3 mm (S3 experiment). The data contained in this repository are presented in Fromant et al. (2018). The files contain :
+
+ 1/ Synchronised and colocated concentration and veclocity (streamwise component) profiles measurements collected with an Acoustic Concentration and Velocity Profiler (ACVP - Hurther et al., 2011). <br>
+ 2/ Concentration profiles time series collected with Conductivity and Concentration Profilers (Lanckriet et al., 2013), with two different vertical resolutions, 1 mm (CCP1mm) and 2mm (CCP2mm).
+
+Details about the experimental protocol can be found in Revil-Baudard et al. (2015). More details regarding the experimental protocol and flow conditions can be found in Fromant et al. (2018).",mds,True,findable,0,0,0,0,0,2018-10-03T15:42:14.000Z,2018-10-03T15:42:15.000Z,cern.zenodo,cern,"Sediment Transport,Sheet-flow,Concentration measurement,ACVP,CCP","[{'subject': 'Sediment Transport'}, {'subject': 'Sheet-flow'}, {'subject': 'Concentration measurement'}, {'subject': 'ACVP'}, {'subject': 'CCP'}]",,
+10.5281/zenodo.10062356,MIPkit-A (MISOMIP2),Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"MIPkit-A (Amundsen Sea in MISOMIP2)
+Observational data kit gathered and reprocessed to facilitate the evaluation of ocean models as part of MISOMIP2.
+This entire dataset should be cited as:Â
+
+the MISOMIP2 MIPkit-A dataset (http://doi.org/10.5281/zenodo.10062356) that includes data collected through multiple cruises of Nathaniel B. Palmer (United States Antarctic Program), James C. Ross (British Antarctic Survey and Natural Environment Research Council), Araon (Korea Polar Research Institute), Oden (Swedish Polar Research) and Polarstern (Alfred Wegener Institute, Germany).
+For more specific use of some of the MIPkit-A data, we encourage people to cite the original data referenced below.
+__________________________________________
+Oce3d_MIPkitA_* : 3-dimensional temperature and salinity (horizontal slices every 100m)
+The hydrographic properties provided on horizontal sections at 15 depths come from the CTD measurements obtained during cruises of the following icebreaker research vessels: Nathaniel B. Palmer (United States Antarctic Program), James C. Ross (British Antarctic Survey and Natural Environment Research Council), Araon (Korea Polar Research Institute), Oden (Swedish Polar Research) and Polarstern (Alfred Wegener Institute, Germany). In this MIPkit, we have gathered data for the first months of 2009 (Jacobs 2009), 2010 (Swedish Polar Research Secretariat 2010; Gohl 2015), 2012 (Kim et al. 2012), 2014 (Heywood 2014; Ha et al. 2014), 2016 (Kim et al. 2016), 2017 (Gohl 2017), 2018 (Kim et al. 2018), 2019 (Larter et al. 2019) and 2020 (Wellner, 2020).
+__________________________________________
+OceSec<n>_MIPkitA_* : vertical sections
+The first vertical (OceSec1) section where we provide hydrographic data in the Amundsen Sea starts across the continental shelf break and follows the Eastern Pine Island Trough southward until Pine Island Ice Shelf. This section was monitored by the following cruises: N.B. Palmer in January 2009, Polarstern in March 2010 and Araon in February-March 2012 (Jacobs et al. 2011; Gohl 2015; Dutrieux et al. 2014). The second vertical section (OceSec2) starts across the continental shelf break and follows the Dotson-Getz Trough southward until the Dotson Ice Shelf. It was monitored by the aforementioned Araon expeditions in 2010–2011 and early 2012 (Kim et al. 2017).
+The files OceSec<n>_model_lon_lat.csv contain the coordinates (longitude, latitude) at which model data should be interpolated to be compared to the observational sections.
+__________________________________________
+OceMoor<n>_MIPkitA_* : moorings
+The first mooring site (OceMoor1) is located near the northern part of the Pine Island ice shelf front (102.07°W, 74.87°S) and captures the thermocline variability from 2012 to 2018 (""iSTAR-8"" in NERC iSTAR program, and ""pig-n"" in NERC Ocean Forcing Ice Change Program). The second mooring site (OceMoor2)is located near the southern part of the Pine Island ice shelf front (102.15°W, 75.05°S), was monitored between 2009 and 2016, then in 2019–2020 through the following moorings: ""BSR-5"" (Buoy Supported Riser; Jacobs 2009), ""iSTAR-9"" (NERC iSTAR Program), and ""pig-s"" (NERC Ocean Forcing Ice Change Program). This second site experienced a strong deepening of the thermocline in 2012–2013 (Webber et al. 2017), then a more moderate deepening in 2016. These two mooring sites are located only 20 km from each other, show distinct mean thermocline depth and more consistent variability (Joughin et al. 2021).
+The third mooring observation (OceMoor3, ""trough-e"" in NERC Ocean Forcing Ice Change Program) used in MISOMIP is at the eastern Pine Island trough (102.55°W, 71.33°S). The eastern trough is considered to be the entrance of mCDW reaching the Pine Island Ice Shelf (Jacobs et al. 2011; Nakayama et al. 2013; Webber et al. 2017) but only two years of mooring observation was conducted from 2014-2015 due to important sea ice cover. The fourth mooring site (OceMoor4) used in MISOMIP is at the western Pine Island trough (113.05°W, 71.56°S). Several mooring observations were conducted within 2 km of each other, allowing us to observe thermocline variability from 2009 to 2016 with one year gap in 2011: ""BSR-12"" (Jacobs 2009), ""iSTAR-1"" (NERC iSTAR Program), and ""trough-w"" (NERC Ocean Forcing Ice Change Program).
+Â
+__________________________________________
+The archive example_routines.zip contains example of Matlab routines that were used to prepare the MIPkit-A data.
+Â
+__________________________________________
+References
+Dutrieux, P., De Rydt, J., Jenkins, A., Holland, P. R., Ha, H. K., Lee, S. H., Steig, E. J., Ding, Q., Abrahamsen, E. P., and Schröder, M.: Strong sensitivity of Pine Island ice-shelf melting to climatic variability, Science, 343, 174–178, 2014.
+Gohl, K.: Station list and links to master tracks in different resolutions of POLARSTERN cruise ANT-XXVI/3, Wellington - Punta Arenas, 2010-01-30 - 2010-04-05, Tech. rep., Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, https://doi.org/10.1594/PANGAEA.847944, 2015.
+Gohl, K.: The Expedition PS104 of the Research Vessel POLARSTERN to the Amundsen Sea in 2017, Reports on polar and marine research, Tech. rep., Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, http://doi.org/10.2312/BzPM_0712_2017, 2017.
+Ha, H. K., Kim, T. W., Lee, H. J., Kang, C. Y., Hong, C. S., Wåhlin, A. K., Rolandsson, J., Karen, O., and Miles, T.: The Amundsen Sea Expedition (ANA04B): IBRV Araon, 24 December 2013 – 25 January 2014 – Chapther 1: Physical Oceanography, Tech. rep., Korea Polar Research Institute, Incheon, https://repository.kopri.re.kr/handle/201206/4605, 2014.
+Heywood, K. 690 J.: JR294/295 Cruise Report, Ice Sheet Stability Programme (iSTAR), RRS James Clark Ross, 26th February – 8th March 2014, Amundsen Sea, Tech. rep., Natural Environment Research Council (NERC), https://www.bodc.ac.uk/resources/inventories/cruise_inventory/report/13405/, 2014.
+Jacobs, S.: Cruise NBP0901, RVIB Nathaniel B. Palmer, Jan 05 – Feb 26 2009, Tech. rep., United States Antarctic Program, http://doi.org/10.7284/905547, 2009.
+Jacobs, S. S., Jenkins, A., Giulivi, C. F., and Dutrieux, P.: Stronger ocean circulation and increased melting under Pine Island Glacier ice shelf, Nature Geoscience, 4, 519–523, 2011.
+Joughin, I., Shapero, D., Smith, B., Dutrieux, P., and Barham, M.: Ice-shelf retreat drives recent Pine Island Glacier speedup, Science Advances, 7, eabg3080, 2021.
+Kim, T. W., H, H. K., and Hong, C. S.: The Amundsen Sea Expedition (ANA02C): IBRV Araon, 31 January 2012 – 20 March 2012 – Chapther 1: Hydrographic Survey, Tech. rep., Korea Polar Research Institute, Incheon, https://repository.kopri.re.kr/handle/201206/4603, 2012.
+Kim, T. W., Cho, K. H., Kim, C. S., Yang, H. W., La, H. S., Lee, J. H., Kim, D. K., Jung, J. H., Wåhlin, A. K., Assmann, K. M., Darelius, E., Abrahamsen, E. P., and Waite, N.: The Amundsen Sea Expedition (ANA06B): IBRV Araon, 6 January – 23 February 2016 – Chapther 1: Physical Oceanography in Amundsen Sea, Tech. rep., Korea Polar Research Institute, Incheon, https://ftp.nmdc.no/nmdc/UIB/Mooring/20181213/ANA06B_cruise_report.pdf, 2016.
+Kim, T.-W., Ha, H. K., Wåhlin, A. K., Lee, S., Kim, C.-S., Lee, J. H., and Cho, Y.-K.: Is Ekman pumping responsible for the seasonal variation of warm circumpolar deep water in the Amundsen Sea?, Continental Shelf Research, 132, 38–48, 2017.
+Kim, T. W., Cho, K. H., Park, T. W., Yang, H. W., Kim, Y., Assmann, K. M., Rolandsson, J., Dutrieux, P., Gobat, J., Beem, L., Richter, T., Buhl, D., and Durand, I.: The Amundsen Sea Expedition (ANA08B): IBRV Araon, 21 December 2017 – 13 February 2018 – Chapther 1: Physical Oceanography, Tech. rep., Korea Polar Research Institute, Incheon, https://repository.kopri.re.kr/handle/201206/9441, 2018.
+Larter, R., Barham, M., Boehme, L., Braddock, S., Graham, A., Hogan, K., Mazur, A., Minzoni, R., Queste, B., Sheehan, P., Spoth, M., Wåhlin, A., Bortolotto-d'Oliveira, G., Clark, R. W., Fitzgerald, V., Karam, S., Kirkham, J., Stedt, F., Zheng, Y., Beeler, C., Goodell, J., Rush, E., Snow, T., Welzenbach, L., Andersson, J., and Rolandsson, J.: Cruise NBP1902, RVIB Nathaniel B. Palmer, Jan 29 – Mar 25 2019, Tech. rep., United States Antarctic Program, http://doi.org/10.7284/908147, 2019.
+Nakayama, Y., Schröder, M., and Hellmer, H. H.: From circumpolar deep water to the glacial meltwater plume on the eastern Amundsen Shelf, Deep Sea Res. I, 77, 50–62, 2013.
+Swedish Polar Research Secretariat: Oden Southern Ocean 2009/10 - Conductivity-Temperature-Depth (CTD) Data Collected Onboard Icebreaker Oden during February through March 2010, Tech. rep., Swedish Polar Research, http://snd.gu.se/en/catalogue/dataset/ecds0220-1, 2010.
+Webber, B. G. M., Heywood, K. J., Stevens, D. P., Dutrieux, P., Abrahamsen, E. P., Jenkins, A., Jacobs, S. S., Ha, H. K., Lee, S. H., and Kim, T. W.: Mechanisms driving variability in the ocean forcing of Pine Island Glacier, Nature Communications, 8, 1–8, 2017.
+Wellner, J.: Cruise NBP2002, RVIB Nathaniel B. Palmer, Jan 25 2020 – Mar 08 2020, Tech. rep., United States Antarctic Program, http://doi.org/10.7284/908803, 2019.",api,True,findable,0,0,0,0,0,2023-11-01T14:53:42.000Z,2023-11-01T14:53:42.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.mgqnk98wm,Data from: Shells of the bivalve Astarte moerchi give new evidence of a strong pelagic-benthic coupling shift occurring since the late 1970s in the NOW Polynya,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Climate changes in the Arctic may weaken the currently tight pelagic-benthic coupling. In response to decreasing sea ice cover, arctic marine systems are expected to shift from a ‘sea-ice algae-benthos’ to a ‘phytoplankton-zooplankton’ dominance. We used mollusk shells as bioarchives and fatty acid trophic markers to estimate the effects of the reduction of sea ice cover on the exported food to the seafloor. Bathyal bivalve Astarte moerchi that lives at 600 m depth in northern Baffin Bay reveals a clear shift in growth variations and Ba/Ca ratios since the late 1970s that we relate to a change in food availability. Fatty acid compositions of tissues show that this species feeds mainly on microalgae exported from the euphotic zone to the seabed. We thus suggest that changes in pelagic-benthic coupling are likely due to either local changes in sea ice dynamics, mediated through bottom-up regulation exerted by sea ice on phytoplankton production or to a mismatch between phytoplankton bloom and zooplankton grazing due to change in their phenology. Both possibilities allow a more regular and increased transfer of food to the seabed.",mds,True,findable,148,8,0,0,0,2020-07-08T21:02:01.000Z,2020-07-08T21:02:02.000Z,dryad.dryad,dryad,,,['1544756 bytes'],
+10.5281/zenodo.7978514,Danaroth83/irca: v1.1,Zenodo,2023,,Software,Open Access,Added wavelength axis to spectra and transmittance responses.,mds,True,findable,0,0,0,0,0,2023-05-28T06:40:25.000Z,2023-05-28T06:40:26.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.23737431,Supplementary document for Flexible optical fiber channel modeling based on neural network module - 6356438.pdf,Optica Publishing Group,2023,,Text,Creative Commons Attribution 4.0 International,Supplement 1,mds,True,findable,0,0,0,0,0,2023-07-26T14:48:51.000Z,2023-08-10T20:33:33.000Z,figshare.ars,otjm,Uncategorized,[{'subject': 'Uncategorized'}],['684917 Bytes'],
+10.5281/zenodo.5849861,agnpy: an open-source python package modelling the radiative processes of jetted active galactic nuclei,Zenodo,2022,,Software,Open Access,This repository contains the scripts to generate the figures included in the paper 'agnpy: an open-source python package modelling the radiative processes of jetted active galactic nuclei'.,mds,True,findable,0,0,0,1,0,2022-01-14T13:52:28.000Z,2022-01-14T13:52:29.000Z,cern.zenodo,cern,"radiative processes,blazars,radio galaxies,AGN,jets,MWL,astropy,numpy,python","[{'subject': 'radiative processes'}, {'subject': 'blazars'}, {'subject': 'radio galaxies'}, {'subject': 'AGN'}, {'subject': 'jets'}, {'subject': 'MWL'}, {'subject': 'astropy'}, {'subject': 'numpy'}, {'subject': 'python'}]",,
+10.5281/zenodo.7249512,CMB heat flux PCA results,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Results of the CMB heat flux PCA from the Coltice et al. (2019) mantle convection model in the numpy (.npy) format. The PCA is computed on the snapshots of the simulations between 300 Myr and 1131 Myr in the simulation time. -avg_pattern.npy: Spherical harmonic decomposition of the CMB heat flux average pattern -patterns.npy: Spherical harmonic decomposition of the PCA components patterns -sing_val.npy: Singular value of the PCA components -weights.npy: Time dependent weights of the PCA components,mds,True,findable,0,0,0,0,0,2022-10-26T07:18:01.000Z,2022-10-26T07:18:02.000Z,cern.zenodo,cern,,,,
+10.57745/lxtwng,Terahertz cyclotron emission from two-dimensional Dirac fermions,Recherche Data Gouv,2023,,Dataset,,"Data associated to the following publication: Gebert, S., Consejo, C., Krishtopenko, S.S. et al. Terahertz cyclotron emission from two-dimensional Dirac fermions. Nat. Photon. (2023). https://doi.org/10.1038/s41566-022-01129-1",mds,True,findable,125,7,0,0,0,2023-02-01T21:02:44.000Z,2023-02-09T15:07:59.000Z,rdg.prod,rdg,,,,
+10.6084/m9.figshare.23822157.v1,Dataset for the replication experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,Data for the replication experiment in CSV format.,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:27.000Z,2023-08-02T11:18:27.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['3105 Bytes'],
+10.5281/zenodo.7195152,Data Used in [~Re] Setting Inventory Levels in a Bike Sharing Network,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data used to reproduce the publication ""Setting an Inventory Levels in a Bike Sharing Network"" by Datner et al. This data correspond to the scenarios generated from the parameters given by the authors.",mds,True,findable,0,0,0,0,0,2022-10-13T17:53:59.000Z,2022-10-13T17:53:59.000Z,cern.zenodo,cern,"Reproduction,FOS: Medical biotechnology,Bike Sharing System,Optimization","[{'subject': 'Reproduction'}, {'subject': 'FOS: Medical biotechnology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Bike Sharing System'}, {'subject': 'Optimization'}]",,
+10.5281/zenodo.7485725,"Datasets for ""Observation of universal Hall response in strongly interacting Fermions""",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This submission includes the datasets shown in the figures of journal article ""Observation of universal Hall response in strongly interacting Fermions"" by T.-W. Zhou et al., Science (2023). The naming of the files corresponds to the figure numbering in the published article:<br> FIG-x for figures in the main text<br> FIG-Sxx for figures in the Supplementary Materials",mds,True,findable,0,0,0,0,0,2023-07-13T06:50:55.000Z,2023-07-13T06:50:56.000Z,cern.zenodo,cern,"Hall effect,Quantum simulation,Quantum technologies,Condensed Matter Physics,FOS: Physical sciences,Atomic Physics","[{'subject': 'Hall effect'}, {'subject': 'Quantum simulation'}, {'subject': 'Quantum technologies'}, {'subject': 'Condensed Matter Physics'}, {'subject': 'FOS: Physical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Atomic Physics'}]",,
+10.5281/zenodo.5838139,Data for Imaging tunable quantum Hall broken-symmetry orders in graphene,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Data plots in spreadsheet form,mds,True,findable,0,0,0,1,0,2022-01-12T14:28:17.000Z,2022-01-12T14:28:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8296848,Cophylogeny reconstruction allowing for multiple associations through approximate Bayesian computation,Zenodo,2023,,Other,"Creative Commons Attribution 4.0 International,Open Access","Phylogenetic tree reconciliation is extensively employed for the examination of coevolution between host and symbiont species. An important concern is the requirement for dependable cost values when selecting event-based parsimonious reconciliation. Although certain approaches deduce event probabilities unique to each pair of host and symbiont trees, which can subsequently be converted into cost values, a significant limitation lies in their inability to model the <em>invasion</em> of diverse host species by the same symbiont species (termed as a spread event), which is believed to occur in symbiotic relationships. Invasions lead to the observation of multiple associations between symbionts and their hosts (indicating that a symbiont is no longer exclusive to a single host), which are incompatible with the existing methods of coevolution. Here, we present a method called AmoCoala (an enhanced version of the tool Coala) that provides a more realistic estimation of cophylogeny event probabilities for a given pair of host and symbiont trees, even in the presence of spread events. We expand the classical 4-event coevolutionary model to include 2 additional spread events (vertical and horizontal spreads) that lead to multiple associations. In the initial step, we estimate the probabilities of spread events using heuristic frequencies. Subsequently, in the second step, we employ an approximate Bayesian computation (ABC) approach to infer the probabilities of the remaining 4 classical events (cospeciation, duplication, host switch, and loss) based on these values. By incorporating spread events, our reconciliation model enables a more accurate consideration of multiple associations. This improvement enhances the precision of estimated cost sets, paving the way to a more reliable reconciliation of host and symbiont trees. To validate our method, we conducted experiments on synthetic datasets and demonstrated its efficacy using real-world examples. Our results showcase that AmoCoala produces biologically plausible reconciliation scenarios, further emphasizing its effectiveness.The software is accessible at https://github.com/sinaimeri/AmoCoala.",mds,True,findable,0,0,0,0,0,2023-08-29T15:29:58.000Z,2023-08-29T15:29:58.000Z,cern.zenodo,cern,"reconciliation,cophylogeny,ABC method,spread","[{'subject': 'reconciliation'}, {'subject': 'cophylogeny'}, {'subject': 'ABC method'}, {'subject': 'spread'}]",,
+10.6084/m9.figshare.23575378,Additional file 7 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 6,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:55.000Z,2023-06-25T03:11:56.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['26112 Bytes'],
+10.5281/zenodo.8412455,SpectralGPT: The first remote sensing foundation model customized for spectral data,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","SpectralGPT is the first purpose-built foundation model designed explicitly for spectral RS data. It considers unique characteristics of spectral data, i.e., spatial-spectral coupling and spectral sequentiality, in the MAE framework with a simple yet effective 3D GPT network. We will gradually release the trained models (SpectralGPT, SpectralGPT+), the new benchmark dataset (SegMunich) for the downstream task of semantic segmentation, original code, and implementation instructions.",mds,True,findable,0,0,0,0,0,2023-10-06T03:38:29.000Z,2023-10-06T03:38:29.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4616357,Raw Data for manuscript submitted to PCI as 'Early Spring Snowmelt and Summer Droughts Strongly Impair the Resilience of Key Microbial Communities in Subalpine Grassland Ecosystems',Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Raw Data for manuscript submitted to PCI Ecology as 'Early Spring Snowmelt and Summer Droughts Strongly Impair the Resilience of Key Microbial Communities in Subalpine Grassland Ecosystems',mds,True,findable,0,0,0,0,0,2021-03-18T08:31:21.000Z,2021-03-18T08:31:22.000Z,cern.zenodo,cern,"climate change, grasslands, (de)nitrification, weather extremes, snowmelt, N2O","[{'subject': 'climate change, grasslands, (de)nitrification, weather extremes, snowmelt, N2O'}]",,
+10.5281/zenodo.10050502,Data and code associated with the manuscript: Three centuries of snowpack decline at an Alpine pass revealed by cosmogenic paleothermometry and luminescence photochronometry,Zenodo,2023,,Dataset,GNU General Public License v3.0 or later,"This dataset contains the data as well as the Matlab codes needed to reproduce the results in the following manuscript:
+Guralnik, B., Tremblay, M.M., Phillips, M., Sellwood, E.L., Gribenski, N., Presl, R., Haberkorn, A., Sohbati, R., Shuster, D.L., Valla, P., Jain, M., Schindler, K., Hippe, K., and Wallinga, J., Three centuries of snowpack decline at an Alpine pass revealed by cosmogenic paleothermometry and luminescence photochronometry.Â
+This manuscript has been submitted to a peer-reviewed journal for publication. Briefly, this manuscript presents a novel combination of cosmogenic paleothermometery (quartz He-3) and luminescence photochronometery (feldspar IRSL), which jointly constrain the temperature and insolation history of three bedrock outcrops at the Gotthard Pass in Switzerland over the last ~15,000 years.Â
+The data include (1) measured concentrations of cosmogenic Be-10, C-14, and He-3 in quartz, (2) stepwise degassing experiments on proton irradiated quartz grains that are used to determine sample-specific He-3 diffusion kinetics, (3) best-fit multiple diffusion domain (MDD) models to the proton-induced He-3 diffusion experiments, (5) Natural radioactivity and calculated feldspar infrared stimulated luminescence (ISRL) dose rates, (6) feldspar ISRL depth profiles, and (7) high-resolution microrelief surface scans and analysis.
+The code includes scripts necessary to reproduce the figures and results associated with this manuscript. The code is organized by figure into subfolders, and any data needed to reproduce a figure should be included in that folder. All original codes are distributed under the GNU General Public License. Codes written by others and utilized here are redistributed under their original license according to the terms and conditions therein, and are provided in the folder 'external.'
+Any questions about original Matlab codes published here should be directed to Benny Guralnik, benny.guralnik@gmail.com.",api,True,findable,0,0,0,0,0,2023-10-28T22:58:22.000Z,2023-10-28T22:58:23.000Z,cern.zenodo,cern,"snow,cosmogenic,paleothermometry,luminescence,Alpine","[{'subject': 'snow'}, {'subject': 'cosmogenic'}, {'subject': 'paleothermometry'}, {'subject': 'luminescence'}, {'subject': 'Alpine'}]",,
+10.5281/zenodo.8392608,CSF22,Zenodo,2023,fr,Dataset,Restricted Access,"1087 French sentences cued by a professional French Cuer with typical hearing CSF22 - video aspects 1920x1020, 30-60 fps - audio/ aspects 44.1 kHz |---→CSF22_test |---→test_labels: 108 csv files |---→test_videos: 108 webm files |---→CSF22_train |---→train_labels: 949 csv files |---→train_videos: 949 webm files |---→ phonelist.csv: list of the 36 labels used (including start and end tokens) to encode French phonemes at GIPSA-lab. |---→ prompts.csv: Text prompt of the recorded sentences",mds,True,findable,0,0,0,0,0,2023-09-29T14:15:23.000Z,2023-09-29T14:15:24.000Z,cern.zenodo,cern,"Cued Speech, French, LFPC,","[{'subject': 'Cued Speech, French, LFPC,'}]",,
+10.5281/zenodo.4628245,HPL (modified for Simgrid/SMPI),Zenodo,2021,,Software,"BSD licenses (New and Simplified),Open Access","This is a modified version of High Performance Linpack, intended to be used on top Simgrid/SMPI simulator.",mds,True,findable,0,0,1,0,0,2021-03-22T19:58:34.000Z,2021-03-22T19:58:35.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3696502,Pretrained parsing model for french with FlauBERT,Zenodo,2020,,Other,"Creative Commons Attribution 4.0 International,Open Access",Pretrained parsing models for French to use with https://github.com/mcoavoux/self-attentive-parser fork of https://github.com/nikitakit/self-attentive-parser parser. These are retrained models (results are slightly different from those reported in Flaubert paper https://arxiv.org/abs/1912.05372).,mds,True,findable,0,0,0,0,0,2020-03-04T09:38:15.000Z,2020-03-04T09:38:15.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.24165071.v1,Additional file 1 of Non-ventilator-associated ICU-acquired pneumonia (NV-ICU-AP) in patients with acute exacerbation of COPD: From the French OUTCOMEREA cohort,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1. Members of the OutcomeRea Network.,mds,True,findable,0,0,0,0,0,2023-09-20T03:22:50.000Z,2023-09-20T03:22:51.000Z,figshare.ars,otjm,"Medicine,Microbiology,FOS: Biological sciences,Genetics,Molecular Biology,Neuroscience,Biotechnology,Evolutionary Biology,Immunology,FOS: Clinical medicine,Cancer,Science Policy,Virology","[{'subject': 'Medicine'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Genetics'}, {'subject': 'Molecular Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Evolutionary Biology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}, {'subject': 'Virology'}]",['107186 Bytes'],
+10.5281/zenodo.5217997,Raw data : Observation of two-mode squeezing in a traveling wave parametric amplifier,Zenodo,2021,en,Dataset,"MIT License,Open Access","The raw data used to generate figures presented in the articles is available as qcodes datasets. Fig 2<br> The 100 million quadrature points used to construct statistics in figure 2 are stored at 10 datasets with ids 1 to 10, each containing 10 million points. The data was split in multiple databases to ease storage and processing. Fig 3<br> The pump phase sweep in figure 2 was recorded at 25 points from 0 to pi. Each sweep step is stored as a dataset in the database starting from run id 11 to 35, corresponding to 0 to pi in order. Fig 4<br> The quadratures recorded at delta values 20, 50, 100, 150 and 200 are stored with run id 36 to 40, respectively. Fig SNTJ gain calibration<br> The noise spectrum as a function of voltage applied to SNTJ is stored for frequencies corresponding to the delta values 20, 50, 100, 150 and 200, from run id 41 to 45, respectively.",mds,True,findable,0,0,0,0,0,2021-11-08T19:02:16.000Z,2021-11-08T19:02:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5727127,"Data related to ""Near-bed sediment transport during offshore bar migration in large-scale experiments""",Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Abstract: This paper presents novel insights into hydrodynamics and sediment fluxes in large-scale laboratory experiments with bi-chromatic wave groups on a relatively steep initial slope (1:15). An Acoustic Concentration and Velocity Profiler provided detailed information of velocity and sand concentration near the bed from shoaling up to the outer breaking zone including suspended sediment and sheet flow transport. The morphological evolution was characterized by offshore migration of the outer breaker bar. Decomposition of the total net transport revealed a balance of onshore-directed, short wave-related and offshore-directed, current-related net transport. The short wave-related transport mainly occurred as bedload over small vertical extents. It was linked to characteristic intrawave sheet flow layer expansions during short wave crests. The current-related transport rate featured lower maximum flux magnitudes but occurred over larger vertical extents. As a result, it was larger than the short wave-related transport rate in all but one cross-shore position, driving the bar's offshore migration. Net flux magnitudes of the infragravity component were comparatively low but played a non-negligible role for total net transport rate in certain cross-shore positions. Net infragravity flux profiles sometimes featured opposing directions over the vertical. The fluxes were linked to a standing infragravity wave pattern and to the correlation of the short wave envelope, controlling suspension, with the infragravity wave velocity. About the data: The data on beach profile (from mechanical profiler), velocity (from ACVP and ADV), sand concentration (from ACVP and OBS) and water surface elevation (from RWG, AWG and PT) measurements is given in .mat (MATLAB) files. The folder “Beach Profiles†contains the measurements from the mechanical profiler before and after each test. To save time, only the morphologically active section of the profiles was measured. Additionally, the folder contains the initial profiles at the start of a sequence (after application of the benchmark waves). Here the full profile was measured. The structure “MobFrame†contains the absolute cross-shore position of the mobile frame (from which detailed measurements were taken) in the considered tests. The folder “ACVP†contains structures with ensemble-averaged velocity and concentration measurements in vertical reference to the undisturbed bed level or a few bins below it (zeta0-coordinate system) sampled at 50.5051Hz. For better interpretation of the measurements, it also features the ensemble-averaged intrawave instantaneous erosion depth (bed elevation) and the upper limit of the sheet flow layer. The folder “ADV†contains structures with the ensemble-averaged ADV data of each test sampled at 100Hz. Apart from the velocity components of each ADV it contains the vertical elevation of each ADV with respect to the ACVP transceiver. The ADV measurements were not subject to the same vertical referencing procedure that was described in the paper for the near-bed ACVP measurements and a more or less constant distance to the bed was assumed. The folder “OBS†contains structures with the ensemble-averaged OBS data of each test sampled at 40Hz. Apart from the concentration measurements it contains the vertical elevation of the OBSs with respect to the ACVP transceiver. The folder “ETA†contains structures with the ensemble-averaged water surface elevation measurements in many different absolute cross-shore locations in the flume sampled at 40Hz. For visualizing the near-bed concentration data, which may not be as trivial as visualizing the rest of the data, an example of MATLAB code is given: %S=ACVP_xx; %to choose which ACVP file you want to look into<br> con=S.c;<br> con(con<1)=1; %to cater for the cells where the logarithm is not defined<br> xphase=linspace(0,1,length(S.solbed)).*ones(size(S.c,2),size(S.c,1));<br> figure; hold on; box on; <br> [C,h]=contourf(xphase,S.z,log10(transpose(con)),[0:0.1:3]); <br> cbh=colorbar; caxis([0 3]); <br> set(h,'edgecolor','none'); <br> tt=get(cbh,'Title'); set(tt,'String','$^{10}log(c)$ $[kg/m^3]$','Interpreter','Latex');<br> plot(xphase(1,:),S.solbed,'k','Linewidth',1.5);<br> plot(xphase(1,:),S.solflo,'r','Linewidth',1.5);<br> xlabel('$t/T_r$','Interpreter','Latex')<br> ylabel('$\zeta_0$ $[m]$','Interpreter','Latex')<br> set(gca,'Fontsize',18)",mds,True,findable,0,0,0,0,0,2021-11-25T12:32:45.000Z,2021-11-25T12:32:46.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3813230,"Survey data of ""Mapping Research Output to the Sustainable Development Goals (SDGs)""",Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>This dataset contains information on what papers and concepts researchers find relevant to map domain specific research output to the 17 Sustainable Development Goals (SDGs).</strong> Sustainable Development Goals are the 17 global challenges set by the United Nations. Within each of the goals specific targets and indicators are mentioned to monitor the progress of reaching those goals by 2030. In an effort to capture how research is contributing to move the needle on those challenges, we earlier have made an initial classification model than enables to quickly identify what research output is related to what SDG. (This Aurora SDG dashboard is the initial outcome as proof of practice.) In order to validate our current classification model (on soundness/precision and completeness/recall), and receive input for improvement, a survey has been conducted to<strong> capture expert knowledge from senior researchers in their research domain related to the SDG</strong>. The survey was open to the world, but mainly distributed to researchers from the Aurora Universities Network. <strong>The survey was open from October 2019 till January 2020, and captured data from 244 respondents in Europe and North America.</strong> 17 surveys were created from a single template, where the content was made specific for each SDG. Content, like a random set of publications, of each survey was ingested by a data provisioning server. That collected research output metadata for each SDG in an earlier stage. It took on average 1 hour for a respondent to complete the survey.<strong> The outcome of the survey data can be used for validating current and optimizing future SDG classification models for mapping research output to the SDGs</strong>. <strong>The survey contains the following questions (see inside dataset for exact wording):</strong> <strong>Are you familiar with this SDG?</strong> Respondents could only proceed if they were familiar with the targets and indicators of this SDG. Goal of this question was to weed out un knowledgeable respondents and to increase the quality of the survey data. <strong>Suggest research papers that are relevant for this SDG (upload list)</strong> This question, to provide a list, was put first to reduce influenced by the other questions. Goal of this question was to measure the completeness/recall of the papers in the result set of our current classification model. (To lower the bar, these lists could be provided by either uploading a file from a reference manager (preferred) in .ris of bibtex format, or by a list of titles. This heterogenous input was processed further on by hand into a uniform format.) <strong>Select research papers that are relevant for this SDG (radio buttons: accept, reject)</strong> A randomly selected set of 100 papers was injected in the survey, out of the full list of thousands of papers in the result set of our current classification model. Goal of this question was to measure the soundness/precision of our current classification model. <strong>Select and Suggest Keywords related to SDG (checkboxes: accept | text field: suggestions)</strong> The survey was injected with the top 100 most frequent keywords that appeared in the metadata of the papers in the result set of the current classification model. respondents could select relevant keywords we found, and add ones in a blank text field. Goal of this question was to get suggestions for keywords we can use to increase the recall of relevant papers in a new classification model. <strong>Suggest SDG related glossaries with relevant keywords (text fields: url)</strong> Open text field to add URL to lists with hundreds of relevant keywords related to this SDG. Goal of this question was to get suggestions for keywords we can use to increase the recall of relevant papers in a new classification model. <strong>Select and Suggest Journals fully related to SDG (checkboxes: accept | text field: suggestions)</strong> The survey was injected with the top 100 most frequent journals that appeared in the metadata of the papers in the result set of the current classification model. Respondents could select relevant journals we found, and add ones in a blank text field. Goal of this question was to get suggestions for complete journals we can use to increase the recall of relevant papers in a new classification model. <strong>Suggest improvements for the current queries (text field: suggestions per target)</strong> We showed respondents the queries we used in our current classification model next to each of the targets within the goal. Open text fields were presented to change, add, re-order, delete something (keywords, boolean operators, etc. ) in the query to improve it in their opinion. Goal of this question was to get suggestions we can use to increase the recall and precision of relevant papers in a new classification model. <strong>In the dataset root you'll find the following folders and files:</strong> <strong>/00-survey-input/</strong> This contains the survey questions for all the individual SDGs. It also contains lists of EIDs categorised to the SDGs we used to make randomized selections from to present to the respondents. <strong>/01-raw-data/</strong> This contains the raw survey output. (Excluding privacy sensitive information for public release.) This data needs to be combined with the data on the provisioning server to make sense. <strong>/02-aggregated-data/</strong> This data is where individual responses are aggregated. Also the survey data is combined with the provisioning server, of all sdg surveys combined, responses are aggregated, and split per question type. <strong>/03-scripts/</strong> This contains scripts to split data, and to add descriptive metadata for text analysis in a later stage. <strong>/04-processed-data/</strong> This is the main final result that can be used for further analysis. Data is split by SDG into subdirectories, in there you'll find files per question type containing the aggregated data of the respondents. <strong>/images/</strong> images of the results used in this README.md. <strong>LICENSE.md</strong> terms and conditions for reusing this data. <strong>README.md</strong> description of the dataset; each subfolders contains a README.md file to futher describe the content of each sub-folder. <strong>In the /04-processed-data/ you'll find in each SDG sub-folder the following files.:</strong> <strong>SDG-survey-questions.pdf</strong> This file contains the survey questions <strong>SDG-survey-questions.doc</strong> This file contains the survey questions <strong>SDG-survey-respondents-per-sdg.csv</strong> Basic information about the survey and responses <strong>SDG-survey-city-heatmap.csv</strong> Origin of the respondents per SDG survey <strong>SDG-survey-suggested-publications.txt</strong> Formatted list of research papers researchers have uploaded or listed they want to see back in the result-set for this SDG. <strong>SDG-survey-suggested-publications-with-eid-match.csv</strong> same as above, only matched with an EID. EIDs are matched my Elsevier's internal fuzzy matching algorithm. Only papers with high confidence are show with a match of an EID, referring to a record in Scopus. <strong>SDG-survey-selected-publications-accepted.csv</strong> Based on our previous result set of papers, researchers were presented random samples, they selected papers they believe represent this SDG. (TRUE=accepted) <strong>SDG-survey-selected-publications-rejected.csv</strong> Based on our previous result set of papers, researchers were presented random samples, they selected papers they believe not to represent this SDG. (FALSE=rejected) <strong>SDG-survey-selected-keywords.csv</strong> Based on our previous result set of papers, we presented researchers the keywords that are in the metadata of those papers, they selected keywords they believe represent this SDG. <strong>SDG-survey-unselected-keywords.csv</strong> As ""selected-keywords"", this is the list of keywords that respondents have not selected to represent this SDG. <strong>SDG-survey-suggested-keywords.csv</strong> List of keywords researchers suggest to use to find papers related to this SDG <strong>SDG-survey-glossaries.csv</strong> List of glossaries, containing keywords, researchers suggest to use to find papers related to this SDG <strong>SDG-survey-selected-journals.csv</strong> Based on our previous result set of papers, we presented researchers the journals that are in the metadata of those papers, they selected journals they believe represent this SDG. <strong>SDG-survey-unselected-journals.csv</strong> As ""selected-journals"", this is the list of journals that respondents have not selected to represent this SDG. <strong>SDG-survey-suggested-journals.csv</strong> List of journals researchers suggest to use to find papers related to this SDG <strong>SDG-survey-suggested-query.csv</strong> List of query improvements researchers suggest to use to find papers related to this SDG <strong>Cite as:</strong> <em>Survey data of ""Mapping Research output to the SDGs""</em> by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385 <strong>Attribute as:</strong> <em><strong>Survey data of ""Mapping Research output to the SDGs</strong>""</em> by Aurora Universities Network (AUR); Alessandro Arienzo (UNA); Roberto Delle Donne (UNA); Ignasi Salvadó Estivill (URV); José Luis González Ugarte (URV); Didier Vercueil (UGA); Nykohla Strong (UAB); Eike Spielberg (UDE); Felix Schmidt (UDE); Linda Hasse (UDE); Ane Sesma (UEA); Baldvin Zarioh (UIC); Friedrich Gaigg (UIN); René Otten (VUA); Nicolien van der Grijp (VUA); Yasin Gunes (VUA); Peter van den Besselaar (VUA); Joeri Both (VUA); Maurice Vanderfeesten (VUA);<strong> is licensed under a Creative Commons Attribution 4.0 International License.</strong> https://aurora-network.global/project/sdg-analysis-bibliometrics-relevance/",mds,True,findable,0,0,0,1,0,2020-05-07T09:14:10.000Z,2020-05-07T09:14:10.000Z,cern.zenodo,cern,"Sustainable Development Goals,SDG,Mapping Research,Matching Research,Recision,Recall,Survey,Questionnaire,Aurora Universites,Classification model","[{'subject': 'Sustainable Development Goals'}, {'subject': 'SDG'}, {'subject': 'Mapping Research'}, {'subject': 'Matching Research'}, {'subject': 'Recision'}, {'subject': 'Recall'}, {'subject': 'Survey'}, {'subject': 'Questionnaire'}, {'subject': 'Aurora Universites'}, {'subject': 'Classification model'}]",,
+10.5061/dryad.b8gtht78h,Global gradients in intraspecific variation in vegetative and floral traits are partially associated with climate and species richness,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Aim Intraspecific trait variation (ITV) within natural plant communities can be large, influencing local ecological processes and dynamics. Here, we shed light on how ITV in vegetative and floral traits responds to large-scale abiotic and biotic gradients (i.e. climate and species richness). Specifically, we tested if associations of ITV with temperature, precipitation and species richness were consistent with any of from four hypotheses relating to stress-tolerance and competition. Furthermore, we estimated the degree of correlation between ITV in vegetative and floral traits and how they vary along the gradients. Location Global. Time period 1975-2016. Major taxa studied Herbaceous and woody plants. Methods We compiled a dataset of 18,112 measurements of the absolute extent of ITV (measured as coefficient of variation) in nine vegetative and seven floral traits from 2,774 herbaceous and woody species at 2,306 locations. Results Large-scale associations between ITV and climate were trait-specific and more prominent for vegetative traits, especially leaf morphology, than for floral traits. ITV showed pronounced associations with climate, with lower ITV values in colder areas and higher values in drier areas. The associations of ITV with species richness were inconsistent across traits. Species-specific associations across gradients were often idiosyncratic and covariation in ITV was weaker between vegetative and floral traits than within the two trait groups. Main conclusions Our results show that, depending on the traits considered, ITV either increased or decreased with climate stress and species richness, suggesting that both factors can constrain or enhance ITV, which might foster plant-population persistence under stressful conditions. Given the species-specific responses and covariation in ITV, associations can be hard to predict for traits and species not yet studied. We conclude that considering ITV can improve our understanding of how plants cope with stressful conditions and environmental change across spatial and biological scales.",mds,True,findable,257,44,1,1,0,2020-02-04T15:41:47.000Z,2020-02-04T15:41:48.000Z,dryad.dryad,dryad,"functional plant traits,flower trait,Leaf trait","[{'subject': 'functional plant traits'}, {'subject': 'flower trait'}, {'subject': 'Leaf trait'}]",['2467474 bytes'],
+10.5281/zenodo.4804641,FIGURES 22–27 in Review and contribution to the stonefly (Insecta: Plecoptera) fauna of Azerbaijan,Zenodo,2021,,Image,Open Access,"FIGURES 22–27. Larval characters of Protonemura sp. AZE-1 from the Talysh Mts—22: pronotum, dorsal view; 23: terga 4–7, dorsal view; 24: hind femur and tibia, lateral view; 25: cercus and hind tarsus, lateral view; 26: male terminalia, ventral view; 27: female terminalia, ventral view.",mds,True,findable,0,0,2,0,0,2021-05-26T07:55:14.000Z,2021-05-26T07:55:17.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.4753291,Fig. 25 in A New Perlodes Species And Its Subspecies From The Balkan Peninsula (Plecoptera: Perlodidae),Zenodo,2012,,Image,"Creative Commons Attribution 4.0 International,Open Access",Fig. 25. Known localities of Perlodes floridus floridus sp. n. (dot) and P. floridus peloponnesiacus ssp. n. (circle).,mds,True,findable,0,0,2,0,0,2021-05-12T18:33:54.000Z,2021-05-12T18:33:55.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Perlodes","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Perlodes'}]",,
+10.57757/iugg23-4534,Deep-learning-based phase picking in SeisComP using SeisBench,GFZ German Research Centre for Geosciences,2023,en,ConferencePaper,Creative Commons Attribution 4.0 International,"<!--!introduction!--><b></b><p>The open-source, seismological software package SeisComP is widely used for seismic monitoring world-wide. Its automatic phase picking module consists of an STA/LTA-based P-wave detector augmented by an AIC onset picker. With proper configuration, it allows detection and accurate onset picking for a wide range of seismic signals. However, it cannot match the performance of experienced analysts. Especially broadband data are often challenging for phase pickers due to the enormous variety of the signals of interest. <br><br>In order to optimize quality and number of automatic picks and reduce time-consuming manual revision, we chose to develop a machine-learning repicker module for SeisComP based on the SeisBench framework. SeisBench supports several deep-learning pickers and comes pre-trained for different benchmark datasets, one of which was contributed by GFZ Potsdam.<br><br>The repicking module consists of several submodules that interact with both SeisComP and SeisBench via their Python interfaces. The current workflow is based on existing locations generated with a classical SeisComP setup. Shortly after event detection and preliminary location, our repicker (1) starts to repick previously picked onsets and (2) attempts to generate additional picks.<br><br>Preliminary results are encouraging. The deep-learning repicker substantially improves pick quality over a large frequency range. The number of picks available per event has approximately doubled and the publication delay is often reduced, especially for small events. The total number of published events has increased by about 20 per cent.</p>",fabricaForm,True,findable,0,0,0,0,0,2023-07-03T19:58:01.000Z,2023-07-11T19:19:09.000Z,gfz.iugg2023,gfz,,,,
+10.5281/zenodo.7147022,CaliParticles: A Benchmark Standard for Experiments in Granular Materials,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Granular materials are discrete particulate media that can flow like a liquid but also be rigid like a solid. This complex mechanical behavior originates in part from the particles shape. How particle shape affects mechanical behavior remains poorly understood. Understanding this micro-macro link would enable the rational design of potentially cheap, light weight or robust materials. To aid this development, we have produced a set of standard particle shapes that can be used as benchmarks for granular materials research. Here we describe the collection of benchmark shapes. Some part of the particles are modeled on superquadrics, others are custom designed. The particles used so far were made from polyoxymethylene (POM) whose specifications are also listed. The benchmark shapes are available as molds in a plastics manufacturing company, whose contact information is also included. The company is capable of making other molds as well, giving access to more particle shapes. The same particle shapes can thus also be made in different types of (colored) plastic, and in amounts of 50.000 particles or more, larger than conveniently be produced with a 3D printer. We also provide the associated .step and .stl files in the repository in which this document is included.",mds,True,findable,0,0,0,0,0,2022-10-17T08:50:34.000Z,2022-10-17T08:50:34.000Z,cern.zenodo,cern,"Particles,Macaroni,Ellipsoid,Tetrapod,Hexapod,Sphereotetrahedron,Caliper","[{'subject': 'Particles'}, {'subject': 'Macaroni'}, {'subject': 'Ellipsoid'}, {'subject': 'Tetrapod'}, {'subject': 'Hexapod'}, {'subject': 'Sphereotetrahedron'}, {'subject': 'Caliper'}]",,
+10.5061/dryad.3bk3j9kph,"Diet composition of moose (Alces alces) in winter, Sweden",Dryad,2023,en,Dataset,Creative Commons Zero v1.0 Universal,"1. Differences in botanical diet compositions among a large number of moose fecal samples collected during winter correlated with the nutritional differences identified in the same samples (Mantel-r = 0.89, p = 0.001), but the nutritional differences were significantly smaller (p < 0.001). 2. Nutritional geometry revealed that moose mixed Scots pine Pinus sylvestris and Vaccinium spp. as nutritionally complementary foods to reach a nutritional target resembling Salix spp. twigs, and selected for Salix spp. browse (Jacob’s D > 0). 3. Available protein (AP) and total non-structural carbohydrates (TNC) were significantly correlated in observed diets but not in hypothetical diets based on food availability. 4. The level of Acetoacetate in moose serum (i.e., ‘starvation’) was weakly negatively associated with digestibility of diets (p = 0.08) and unrelated to increasing AP:TNC and AP:NDF ratios in diets (p > 0.1). 5. Our study is the first to demonstrate complementary feeding in free-ranging moose to attain a nutritional target that has previously been suggested in a feeding trial with captive moose. Our results add support to the hypothesis of nutritional balancing as a driver in the nutritional strategy of moose with implications for both the management of moose and food resources.",mds,True,findable,100,7,0,0,0,2023-02-03T23:45:47.000Z,2023-02-03T23:45:48.000Z,dryad.dryad,dryad,"FOS: Animal and dairy science,FOS: Animal and dairy science,Alces alces,Herbivory,nutritional ecology,Nutritional Geometry,ungulate diets","[{'subject': 'FOS: Animal and dairy science', 'subjectScheme': 'fos'}, {'subject': 'FOS: Animal and dairy science', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Alces alces'}, {'subject': 'Herbivory', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'nutritional ecology'}, {'subject': 'Nutritional Geometry'}, {'subject': 'ungulate diets'}]",['53329 bytes'],
+10.6084/m9.figshare.c.6690029.v1,3DVizSNP: a tool for rapidly visualizing missense mutations identified in high throughput experiments in iCn3D,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background High throughput experiments in cancer and other areas of genomic research identify large numbers of sequence variants that need to be evaluated for phenotypic impact. While many tools exist to score the likely impact of single nucleotide polymorphisms (SNPs) based on sequence alone, the three-dimensional structural environment is essential for understanding the biological impact of a nonsynonymous mutation. Results We present a program, 3DVizSNP, that enables the rapid visualization of nonsynonymous missense mutations extracted from a variant caller format file using the web-based iCn3D visualization platform. The program, written in Python, leverages REST APIs and can be run locally without installing any other software or databases, or from a webserver hosted by the National Cancer Institute. It automatically selects the appropriate experimental structure from the Protein Data Bank, if available, or the predicted structure from the AlphaFold database, enabling users to rapidly screen SNPs based on their local structural environment. 3DVizSNP leverages iCn3D annotations and its structural analysis functions to assess changes in structural contacts associated with mutations. Conclusions This tool enables researchers to efficiently make use of 3D structural information to prioritize mutations for further computational and experimental impact assessment. The program is available as a webserver at https://analysistools.cancer.gov/3dvizsnp or as a standalone python program at https://github.com/CBIIT-CGBB/3DVizSNP .",mds,True,findable,0,0,0,0,0,2023-06-10T03:21:53.000Z,2023-06-10T03:21:53.000Z,figshare.ars,otjm,"Space Science,Medicine,Genetics,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,80699 Information Systems not elsewhere classified,FOS: Computer and information sciences,Cancer,Plant Biology","[{'subject': 'Space Science'}, {'subject': 'Medicine'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': '80699 Information Systems not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Computer and information sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",,
+10.6084/m9.figshare.23575375,Additional file 6 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 5,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:53.000Z,2023-06-25T03:11:53.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['67584 Bytes'],
+10.6084/m9.figshare.c.6593063,"Promoting HPV vaccination at school: a mixed methods study exploring knowledge, beliefs and attitudes of French school staff",figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background HPV vaccine coverage in France remained lower than in most other high-income countries. Within the diagnostic phase of the national PrevHPV program, we carried out a mixed methods study among school staff to assess their knowledge, beliefs and attitudes regarding HPV, HPV vaccine and vaccination in general, and regarding schools’ role in promoting HPV vaccination. Methods Middle school nurses, teachers and support staff from four French regions participated between January 2020 and May 2021. We combined: (i) quantitative data from self-administered online questionnaires (n = 301), analysed using descriptive statistics; and (ii) qualitative data from three focus groups (n = 14), thematically analysed. Results Less than half of respondents knew that HPV can cause genital warts or oral cancers and only 18% that no antiviral treatment exists. Almost 90% of the respondents knew the existence of the HPV vaccine but some misunderstood why it is recommended before the first sexual relationships and for boys; 56% doubted about its safety, especially because they think there is not enough information on this topic. Schools nurses had greater knowledge than other professionals and claimed that educating pupils about HPV was fully part of their job roles; however, they rarely address this topic due to a lack of knowledge/tools. Professionals (school nurses, teachers and support staff) who participated in the focus groups were unfavourable to offering vaccination at school because of parents’ negative reactions, lack of resources, and perceived uselessness. Conclusions These results highlight the need to improve school staff knowledge on HPV. Parents should be involved in intervention promoting HPV vaccination to prevent their potential negative reactions, as feared by school staff. Several barriers should also be addressed before organizing school vaccination programs in France.",mds,True,findable,0,0,0,0,0,2023-04-13T14:58:33.000Z,2023-04-13T14:58:33.000Z,figshare.ars,otjm,"Medicine,Molecular Biology,Biotechnology,Sociology,FOS: Sociology,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Cancer,Science Policy,110309 Infectious Diseases,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Molecular Biology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}, {'subject': '110309 Infectious Diseases', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.1035485,Code and data from: Global conservation of species' niches,Zenodo,2020,en,Software,"GNU Affero General Public License v3.0 or later,Open Access","This digital archive contains code and data associated with the publication ""Global conservation of species’ niches"" by Hanson et al. (2020). Note that many of the raw data files (e.g. extent of suitable habitat maps, protected area data) are not available in this archive, and must be obtained from the original sources (see README files for more information).",mds,True,findable,34,0,0,0,0,2020-03-19T21:03:35.000Z,2020-03-19T21:03:36.000Z,cern.zenodo,cern,"protected areas,evolution,biodiversity,Key Biodiversity Areas","[{'subject': 'protected areas'}, {'subject': 'evolution'}, {'subject': 'biodiversity'}, {'subject': 'Key Biodiversity Areas'}]",,
+10.5281/zenodo.3345743,"Companion code for ""When and how can Stacked Species Distribution Models predict local richness?""",Zenodo,2019,en,Software,Restricted Access,"<strong>When and how can Stacked Species Distribution Models predict local richness?</strong> This repository contains the data and code for our paper: Grenié M., Violle C, Munoz F.<em> When and how can Stacked Species Distribution Models predict local richness?</em>. submitted to <em>Ecological Indicators</em>. <strong>How to cite</strong> Please cite this compendium as: Grenié M., Violle C, Munoz F., (2019). <em>Compendium of R code and data for When and how can Stacked Species Distribution Models predict local richness?</em>. Accessed 29 july 2019. Online at <https://doi.org/10.5281/zenodo.3345743> <strong>How to download or install</strong> You can download the compendium from Zenodo https://doi.org/10.5281/zenodo.3345743 Or you can install this compendium as an R package, `comsat`, from<br> GitHub with: <pre><code># install.packages(""devtools"") remotes::install_github(""Rekyt/comsat"")</code></pre> <strong>How to run the analyses</strong> This compendium uses drake to make analyses reproducible. To redo the analyses and rebuild the manuscript run the following lines (from the `comsat` folder): <pre><code># install.packages(""devtools"") pkgload::load_all() # Load all functions included in the package make(comsat_drake_plan()) # Run Analyses</code></pre> Beware that some code make time a long time to run, and it may be useful<br> to run analyses in parallel.",mds,True,findable,0,0,0,0,0,2019-07-29T11:28:01.000Z,2019-07-29T11:28:02.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8223563,InGaN/GaN QWs on Si,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"Dataset for the project of high TD density QWs grown on Si, published here.
+The different sub-datasets are named after:
+
+the measurement technique, from [ Atomic Force Microscopy (AFM) ; Cathodoluminescence (CL) mapping ; Power-dependent photoluminescence (PL) series (P-series) ; Scanning Electron Micrographs (SEM) ; Temperature-dependent P-series (T-P-series) ; Transmission Electron Microscopy (TEM) ; Time-resolved PL (TRPL) ];
+the sample name, from [ R = A4286 ; U = A4287 ; V = A4289 ].
+Further relevant information can be found in the .zip folders, in README files.",mds,True,findable,0,0,0,0,0,2023-09-18T19:41:32.000Z,2023-09-18T19:41:33.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4273949,A Schwarz iterative method to evaluate ocean- atmosphere coupling schemes. Implementation and diagnostics in IPSL-CM6-SW-VLR. GMD-2020-307,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These files are associated with an article submitted to Geoscientific Model Development (https://www.geoscientific-model-development.net) with reference GMD-2020-307 : A Schwarz iterative method to evaluate ocean- atmosphere coupling schemes. Implementation and diagnostics in IPSL-CM6-SW-VLR.<br> By Olivier Marti, Sébastien Nguyen, Pascale Braconnot, Sophie Valcke, Florian Lemarié, and Eric Blayo It contains :<br> - The model code used for the study<br> - The model outputs used for the study<br> - The script used to produce the figures. Contact : Olivier Marti - olivier.marti@lsce.ipsl.fr",mds,True,findable,0,0,0,0,0,2020-11-15T19:21:53.000Z,2020-11-15T19:21:54.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5899162,Materials synthesis at terapascal static pressures,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Extended Data for manuscript ""Materials synthesis at terapascal static pressures"".",mds,True,findable,0,0,0,0,0,2022-01-24T20:00:12.000Z,2022-01-24T20:00:16.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10222606,"Spectral albedo and summer ground temperature of herbaceous and shrub tundra vegetation at Bylot Island, Canadian High-Arctic",Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"These data are in support of a preprint:Â
+Comparing spectral albedo and NDVI of herbaceous and shrub tundra vegetation at Bylot Island, Canadian High-Arctic
+Florent Domine, Maria-Belke-Brea, Ghislain Picard, Laurent Arnaud, and Esther Lévesque
+To be submitted in 2023.Â
+The spectral albedo of several vegetation assemblages on Bylot Island and in Mala River valley on nearby Baffin Island were recorded between 10 and 18 July 2015. The spectral range covered was 346 to 2400 nm. Surfaces were classified according to the main vegetation types. Classes used are graminoids, moss, Salix arctica, soil, and Salix richardsonii. S. richardsonii is the only truly erect species on Bylot Island. Transmission spectra of radiation through the S. richardsonii canopy were also recorded. S. richardsonii spectra were different depending on the location where they were measured and we present spectra for sites in active parts of an alluvial fan (Salix-G2), an inactive part of an alluvial fan (Salix-D1) and in a mesic area on Mala River Valley (Salix-M). We also present typical relative solar irradiance spectra recorded at Bylot Island during the campaign, under clear and overcast conditions. In conjunction with spectral albedo data, these irradiance spectra allow the calculation of the broadband (BB) albedo of the vegetation types and to compare BB albedo values under identical irradiance conditions. 83 spectra were recorded: 39 for S. richardsonii and 44 for low vegetation and soil. 17 transmission spectra under S. richardsonii were recorded. We present here only averages for each vegetation type. We also present averages for all low vegetation types and for all S. richardsonii spectra, to allow the calculation of the radiative impact of erect shrubs at Bylot Island.Â
+We also present soil temperature data at 15 cm depth for the spots GRASS (mostly Salix Arctica), TUNDRA (Mostly moss), SALIX-D1 (Salix richardsonii) and SALIX-F (Salix richardsonii). SALIX-F is similar to SALIX-G2. The data are during summer 2020.Â
+The locations of the various spots investigated are:Â
+Spot name  Latitude  Longitude Vegetation types found
+TUNDRA 73.150° -80.004° Humid and moist polygons with low vegetation dominated by mosses, graminoids, S. arctica and S. herbacea.
+PLAINE 73.167° -79.915° Low vegetation and bare soil patches caused by cryoturbation (mudboils) with mosses, graminoids and S. arctica.
+GRASS 73.158° -79.907° Low vegetation between patches of S. richardsonii dominated by S. arctica, with litter, mosses, graminoids and occasional bare soil. Â
+SALIX-D1 73.158° -79.907° Scattered patches of S. richardsonii <35 cm tall. Understory is mosses, graminoids, litter, S. arctica and bare soil.
+SALIX-M 73.006° -80.685° Mesic area with patches of S. richardsonii 35 to 40 cm tall. Understory includes moss, graminoids and litter. Between patches: herb tundra with graminoids and mosses. The area is not within an alluvial fan.
+SALIX-G2 73.168° -79.812° Extended area in an alluvial fan with S. richardsonii >40 cm. Understory includes litter, mosses, graminoids, bare soil, S. arctica and S. reticulata.
+SALIX-F 73.182° -79.745° Similar to SALIX-G2. Ground temperature is monitored there. No spectral data were recorded at that site. Â
+Â
+Â ",api,True,findable,0,0,0,0,0,2023-11-29T16:34:14.000Z,2023-11-29T16:34:14.000Z,cern.zenodo,cern,,,,
+10.57745/xhq7tl,Annual glacier surface flow velocity product from Sentinel-2 data for the European Alps,Recherche Data Gouv,2023,,Dataset,,"Glacier ice flow velocity is an important variable to document the past and current status of the glacier worldwide. The aim of the ESA AlpGlacier project is to create innovative products for glaciers and their environments from remote sensing data for the European Alps mountain range. The data set proposed here includes maps of annual glacier surface flow velocities for the period 2015-2021, created from Sentinel-2 optical data with the work-flow presented in Mouginot et al., 2023. It can be used for the monitoring of glacier dynamics or for hazards detection associated to glaciers destabilization, as well as an input of models calibration and validation. These products are distributed in both netCDF and GeoTiff formats, georeferenced under the UTM-32N projection.",mds,True,findable,277,28,0,0,0,2023-03-01T09:50:30.000Z,2023-03-02T14:05:25.000Z,rdg.prod,rdg,,,,
+10.5061/dryad.bnzs7h4ds,Gait behavioral and neuromuscular characterization in response to increasing working memory load while walking under optic flow perturbations in young adults,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"The precise role of cognitive control on optic flow processing during locomotion has rarely been investigated. Therefore, this study aimed to determine whether coping with unreliable visual inputs during walking requires attentional resources. Twenty-four healthy young adults walked on an instrumented treadmill in a virtual environment under two optic flow conditions: normal (NOF) and perturbed (POF, continuous mediolateral pseudo-random oscillations). Each condition was performed under single-task and dual-task conditions of increasing difficulty (1-, 2-, 3-back). In all conditions, subjective mental workload was estimated (raw NASA-TLX). For kinematic variables, mean, standard deviation, statistical persistence and step-to-step error correction were computed from gait time series in mediolateral and anteroposterior directions. For EMG variables of soleus and gluteus medius, the full width at half maximum and the variance ratio were calculated. Performance on N-back tasks was assessed using mean reaction time and d-prime. Cognitive performance was not affected by simultaneous walking in any optic flow condition. Gait variability was altered under POF compared to NOF, so that young adults sought to counteract those perturbations by adopting an effortful gait control strategy, independently of concurrent working memory (WM) load. Increasing WM load led changes first at the neuromuscular level, then at the behavioral level, with a prioritization of gait control in the mediolateral direction. Interestingly, dual-tasking lowered the effects of POF but in the anteroposterior direction only. These findings and their theoretical implications provide valuable insight into the complex interaction effects of cognitive and visual constraints on gait control during treadmill walking.",mds,True,findable,140,5,0,1,0,2022-08-15T15:25:42.000Z,2022-08-15T15:25:42.000Z,dryad.dryad,dryad,"gait,lateral balance,muscle activity,FOS: Health sciences,FOS: Health sciences,variability,Nonlinear dynamics,executive function","[{'subject': 'gait'}, {'subject': 'lateral balance'}, {'subject': 'muscle activity'}, {'subject': 'FOS: Health sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'variability'}, {'subject': 'Nonlinear dynamics', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'executive function'}]",['2515659 bytes'],
+10.5281/zenodo.8037856,konstantinos-p/europepolls: Europepolls first release.,Zenodo,2023,,Software,Other (Open),A dataset of country-level historical voting-intention polling data for the European Union (+Switzerland and UK).,mds,True,findable,0,0,0,1,0,2023-06-14T12:34:43.000Z,2023-06-14T12:34:43.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.3631244,"Data and figures used in ""Pressure torque of torsional Alfvén modes acting on an ellipsoidal mantle""",Zenodo,2020,,Dataset,"GNU General Public License v3.0 or later,Open Access","Data, plotting routines and analysis routines to reproduce all results from the article ""Pressure torque of torsional Alfvén modes acting on an ellipsoidal mantle"". The package uses the freely available code Mire.jl. <strong>Prerequisites</strong> Installed texlive, python/python3 with matplotlib >v2.1 for support of latest colormaps. A working Julia >v1.3. <br> <strong>Install</strong> Open the repository directory and run <pre><code class=""language-bash"">julia install_local.jl</code></pre> to install the package. <strong>Run</strong> To run the calculations and the plots you simply run <pre><code>using Elltorque Elltorque.run(true)</code></pre> <br> from within the Julia REPL (takes around 2-3h). To run without calculating the data use <pre><code>Elltorque.run(false)</code></pre>",mds,True,findable,0,0,0,0,0,2020-04-21T20:00:11.000Z,2020-04-21T20:00:12.000Z,cern.zenodo,cern,,,,
+10.57745/ruqljl,"Draix-Bleone Observatory spatial data: catchment boundaries, instrument locations and DEM",Recherche Data Gouv,2023,,Dataset,,"This dataset contains spatial information for Draix-Bleone Observatory, including catchment boundaries for the Laval, Moulin, Brusquet, Roubine, Francon, Bouinenc and Galabre catchments, instrument locations, and high-resolution topographic data (DEM) for the Laval, Moulin, Roubine, and Brusquet catchments.",mds,True,findable,15,0,0,0,0,2023-07-03T14:42:16.000Z,2023-07-17T09:46:47.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.4947841,PACE 2021 Kernelization track,Zenodo,2021,,Software,"Creative Commons Attribution 4.0 International,Open Access",These are the sources of the PaSTEC solver for the kernelization track of the PACE 2021 challenge.,mds,True,findable,0,0,0,0,0,2021-06-14T19:09:05.000Z,2021-06-14T19:09:06.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7387170,Satellite-derived melt assimilation MAR simulations over the Antarctic Peninsula daily data,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The Modèle Atmosphérique Régionale (MAR), is a regional climate model designed to simulate poles' climate. here is provided a data set of MAR simulations in which microwave sensor date have been assimilated. The files contain snow and athmosphere related variables over the Antarctic Peninsula for the 2019-2020 period. MAR is a polar-oriented regional climate model mostly used to study both the Greenland and Antarctic ice sheet. Its atmospheric dynamics are based on hydrostatic approximation of primitive equations originally described in Gallée and Schayes (1994) and on a radiative transfer scheme adapted from Morcrette (2002). The model has been parameterized to resolve the topmost 20 meters of the snowpack, divided into 30 layers of time varying thickness. Layers maximum water content holding capacity is fixed at 5%. Beyond it, the water freely percolates through the snowpack or runoffs above impermeable layers. For this work, MARv3.12 was run at a 7.5 km resolution over the Antarctic Peninsula March 2017 and May 2021. Snowpack was initialized in 2017 with a previous MAR simulation (Kittel et al., 2021). Finally, the simulations with assimilation were started in January 2019, restarting from the simulation without assimilation. Simulation for the 2020-2021 season are available on demand. Contact tdethinne@uliege.be",mds,True,findable,0,0,0,0,0,2022-12-02T10:30:49.000Z,2022-12-02T10:30:50.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8269854,Heterogeneous/Homogeneous Change Detection dataset,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"""Please if you use this datasets we appreciated that you reference this repository and cite the works related that made possible the generation of this dataset.""
+This change detection datastet has different events, satellites, resolutions and includes both homogeneous/heterogeneous cases. The main idea of the dataset is to bring a benchmark on semantic change detection in remote sensing field.This dataset is the outcome of the following publications:
+
+@article{Â Â Â JimenezSierra2022graph,author={Jimenez-Sierra, David Alejandro and Quintero-Olaya, David Alfredo and Alvear-Mu{\~n}oz, Juan Carlos and Ben{\'i}tez-Restrepo, Hern{\'a}n Dar{\'i}o and Florez-Ospina, Juan Felipe and Chanussot, Jocelyn},journal={IEEE Transactions on Geoscience and Remote Sensing},title={Graph Learning Based on Signal Smoothness Representation for Homogeneous and Heterogeneous Change Detection},year={2022},volume={60},number={},pages={1-16},doi={10.1109/TGRS.2022.3168126}}Â
+@article{Â Â Â JimenezSierra2020graph,title={Graph-Based Data Fusion Applied to: Change Detection and Biomass Estimation in Rice Crops},author={Jimenez-Sierra, David Alejandro and Ben{\'i}tez-Restrepo, Hern{\'a}n Dar{\'i}o and Vargas-Cardona, Hern{\'a}n Dar{\'i}o and Chanussot, Jocelyn},journal={Remote Sensing},volume={12},number={17},pages={2683},year={2020},publisher={Multidisciplinary Digital Publishing Institute},doi={10.3390/rs12172683}}Â
+@inproceedings{jimenez2021blue,title={Blue noise sampling and Nystrom extension for graph based change detection},author={Jimenez-Sierra, David Alejandro and Ben{\'\i}tez-Restrepo, Hern{\'a}n Dar{\'\i}o and Arce, Gonzalo R and Florez-Ospina, Juan F},booktitle={2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS},ages={2895--2898},year={2021},organization={IEEE},doi={10.1109/IGARSS47720.2021.9555107}}Â
+@article{florez2023exploiting,title={Exploiting variational inequalities for generalized change detection on graphs},author={Florez-Ospina, Juan F and Jimenez Sierra, David A and Benitez-Restrepo, Hernan D and Arce, Gonzalo},journal={IEEE Transactions on Geoscience and Remote Sensing}, Â year={2023},volume={61},number={},pages={1-16},doi={10.1109/TGRS.2023.3322377}}Â
+@article{florez2023exploitingxiv,title={Exploiting variational inequalities for generalized change detection on graphs},author={Florez-Ospina, Juan F. and Jimenez-Sierra, David A. and Benitez-Restrepo, Hernan D. and Arce, Gonzalo R},year={2023},publisher={TechRxiv},doi={10.36227/techrxiv.23295866.v1}}
+In the table on the html file (dataset_table.html) are tabulated all the metadata and details related to each case within the dasetet. The cases with a link, were gathered from those sources and authors, therefore you should refer to their work as well.
+The rest of the cases or events (without a link), were obtained through the use of open sources such as:
+
+Copernicus
+European Space Agency
+Alaska Satellite Facility (Vertex)
+Earth Data
+In addition, we carried out all the processing of the images by using the SNAP toolbox from the European Space Agency. This proccessing involves the following:
+
+Data co-registration
+Cropping
+Apply Orbit (for SAR data)
+Calibration (for SAR data)
+Speckle Filter (for SAR data)
+Terrain Correction (for SAR data)
+Lastly, the ground truth was obtained from homogeneous images for pre/post events by drawing polygons to highlight the areas where a visible change was present. The images where layout and synchorized to be zoomed over the same are to have a better view of changes. This was an exhaustive work in order to be precise as possible.Feel free to improve and contribute to this dataset.",api,True,findable,0,0,0,0,1,2023-11-05T15:26:41.000Z,2023-11-05T15:26:41.000Z,cern.zenodo,cern,"Remote sensing,Change Detection,Multi-Spectral,SAR","[{'subject': 'Remote sensing'}, {'subject': 'Change Detection'}, {'subject': 'Multi-Spectral'}, {'subject': 'SAR'}]",,
+10.5281/zenodo.7603489,"Model outputs and species-level data for ""Functional traits and climate drive interspecific differences in disturbance-induced tree mortality""",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository is divided in three sub-directories: <em><strong>sensitivity </strong></em>contains the posterior of each parameter estimated by the bayesian mortality model in a rdata file. This file was generated by the script https://github.com/jbarrere3/SalvageModel/tree/withFinland <em><strong>climate </strong></em>contains for each tree species the climatic variables (mean annual temperature, minimum annual temperature and annual precipitation) extracted from CHELSA and the disturbance-related climatic indices (Fire Weather Index, Snow Water Equivalent and Gust Wind Speed) <em><strong>traits </strong></em>contains the traits calculated directly with NFI data (bark thickness, height to dbh ratio, maximum growth), and a text file with the Species and Trait ID to request to TRY database. The content of this repository can be used to reproduce the analyses of the paper, with the script stored in in https://github.com/jbarrere3/DisturbancePaper <strong>Edit (19/09/2023):</strong> A minor coding error was found in the pre-formatted data of the paper, which did not affect the main results but led to minor change in the value of the posterior estimates. An updated version of the posterior estimates of this dataset was made available at https://zenodo.org/record/8358921.",mds,True,findable,0,0,0,0,0,2023-02-03T16:23:20.000Z,2023-02-03T16:23:21.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.1qt12,"Data from: Extracellular DNA extraction is a fast, cheap and reliable alternative for multi-taxa surveys based on soil DNA",Dryad,2017,en,Dataset,Creative Commons Zero v1.0 Universal,"DNA metabarcoding on soil samples is increasingly used for large-scale and multi-taxa biodiversity studies. However, DNA extraction may be a major bottleneck for such wide uses. It should be cost/time effective and allow dealing with large sample volumes so as to maximise the representativeness of both micro- and macro-organisms diversity. Here, we compared the performances of a fast and cheap extracellular DNA extraction protocol with a total DNA extraction method in retrieving bacterial, eukaryotic and plant diversity from tropical soil samples of ca. 10 g. The total DNA extraction protocol yielded more high-quality DNA. Yet, the extracellular DNA protocol provided similar diversity assessments although it presented some differences in clades relative abundance and undersampling biases. We argue that extracellular DNA is a good compromise between cost, labor, and accuracy for high-throughput DNA metabarcoding studies of soil biodiversity.",mds,True,findable,339,58,1,1,0,2016-01-20T19:13:51.000Z,2016-01-20T19:13:52.000Z,dryad.dryad,dryad,"multi-taxa,DNA extraction protocol,Soil biodiversity,present,Holocene,Viridiplantae","[{'subject': 'multi-taxa'}, {'subject': 'DNA extraction protocol'}, {'subject': 'Soil biodiversity'}, {'subject': 'present'}, {'subject': 'Holocene'}, {'subject': 'Viridiplantae'}]",['18072078 bytes'],
+10.5281/zenodo.10014634,Mining tortured acronyms from the scientific literature,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,,api,True,findable,0,0,0,0,0,2023-10-17T19:30:51.000Z,2023-10-17T19:30:51.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5237575,French DBnary archive in original Lemon format,Zenodo,2021,fr,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from French language edition, ranging from 27th August 2012 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br>",mds,True,findable,0,0,0,0,0,2021-08-24T07:05:18.000Z,2021-08-24T07:05:19.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.5842110,"InSAR Displacements in the Delaware Basin, TX",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These data are the vertical and east-west horizontal cumulative displacements in the Delaware Basin, between 2015-03-05 through 2020-03-31. They are presented in ""Shallow Aseismic Slip in the Delaware Basin Determined by Sentinel-1 InSAR"", submitted to <em>JGR: Solid Earth</em> on September 1st, 2021. The format of both files is [longitude, latitude, X, Y, displacement (cm)]. For vertical displacements, negative values indicate subsidence and positive values indicate uplift. For horizontal displacement, negative values indicate westward displacement, and positive values indicate eastward displacement. Version 2 (_v2) were updated Dec. 28th, 2021.",mds,True,findable,0,0,0,1,0,2022-01-12T19:37:46.000Z,2022-01-12T19:37:47.000Z,cern.zenodo,cern,"InSAR,Delaware Basin,induced seismicity,aseismic slip","[{'subject': 'InSAR'}, {'subject': 'Delaware Basin'}, {'subject': 'induced seismicity'}, {'subject': 'aseismic slip'}]",,
+10.6084/m9.figshare.21717750,Neuroblast Differentiation-Associated Protein Derived Polypeptides: AHNAK(5758-5775) Induces Inflammation by Activating Mast Cells via ST2,Taylor & Francis,2022,,Text,Creative Commons Attribution 4.0 International,"Psoriasis is a chronic inflammatory skin disease. Mast cells are significantly increased and activated in psoriatic lesions and are involved in psoriatic inflammation. Some endogenous substances can interact with the surface receptors of mast cells and initiate the release of downstream cytokines that participate in inflammatory reactions. Neuroblast differentiation-associated protein (AHNAK) is mainly expressed in the skin, esophagus, kidney, and other organs and participates in various biological processes in the human body. AHNAK and its derived peptides have been reported to be involved in the activation of mast cells and other immune processes. This study aimed to investigate whether AHNAK (5758–5775), a neuroblast differentiation-associated protein-derived polypeptide, could be considered a new endogenous substance in psoriasis patients, which activates mast cells and induces the skin inflammatory response contributing to psoriasis. Wild-type mice were treated with AHNAK(5758–5775) to observe the infiltration of inflammatory cells in the skin and cytokine release in vivo. The release of inflammatory mediators by mouse primary mast cells and the laboratory of allergic disease 2 (LAD2) human mast cells was measured in vitro. Molecular docking analysis, molecular dynamics simulation, and siRNA transfection were used to identify the receptor of AHNAK(5758–5775). AHNAK(5758–5775) could cause skin inflammation and cytokine release in wild-type mice and activated mast cells in vitro. Moreover, suppression of tumorigenicity 2 (ST2) might be a key receptor mediating AHNAK(5758–5775)’s effect on mast cells and cytokine release. We propose a novel polypeptide, AHNAK(5758–5775), which induces an inflammatory reaction and participates in the occurrence and development of psoriasis by activating mast cells.",mds,True,findable,0,0,0,0,0,2022-12-13T16:00:06.000Z,2022-12-13T16:00:06.000Z,figshare.ars,otjm,"Biochemistry,Medicine,Microbiology,FOS: Biological sciences,Cell Biology,Genetics,Physiology,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,Developmental Biology,Cancer,111714 Mental Health,FOS: Health sciences,Computational Biology","[{'subject': 'Biochemistry'}, {'subject': 'Medicine'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cell Biology'}, {'subject': 'Genetics'}, {'subject': 'Physiology'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Developmental Biology'}, {'subject': 'Cancer'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Computational Biology'}]",['264022 Bytes'],
+10.5281/zenodo.8115575,napari: a multi-dimensional image viewer for Python,Zenodo,2023,,Software,"BSD 3-Clause ""New"" or ""Revised"" License,Open Access","napari 0.4.18 We're happy to announce the release of napari 0.4.18! napari is a fast, interactive, multi-dimensional image viewer for Python. It's designed for browsing, annotating, and analyzing large multi-dimensional images. It's built on top of Qt (for the GUI), vispy (for performant GPU-based rendering), and the scientific Python stack (numpy, scipy). This is primarily a bug-fix release, addressing many issues from 0.4.17 (see ""Bug Fixes"", below). However, it also contains some performance improvements and several exciting new features (see ""Highlights""), so read on below! For more information, examples, and documentation, please visit our website: https://napari.org Highlights Drawing polygons in the Shapes layer can now be done much faster with the new lasso tool (napari/napari/#5555) Surface layers now support textures and vertex colors, allowing a whole new type of dataset to be visualised in napari. Have a look at <code>surface_multi_texture.py</code> and <code>surface_texture_and_colors.py</code> in the <code>examples</code> directory for some pretty demos! (napari/napari/#5642) Previously, navigating an image required switching out of whatever drawing mode you might have been using and going back to pan/zoom mode. Now you can use the mouse wheel to zoom in and out in any mode. (napari/napari/#5701) Painting labels is now much, much faster (achieving 60fps even on an 8k x 8k image) (napari/napari/#5723 and napari/napari/#5732) Vectors layers can now be displayed with two different styles of arrowheads, instead of just plain lines. This removes a longstanding limitation of the vectors layer! (napari/napari/#5740) New Features Overlays 2.0 (napari/napari/#4894) expose custom image interpolation kernels (napari/napari/#5130) Add user agent environment variable for pip installations (napari/napari/#5135) Add option to check if plugin try to set viewer attr outside main thread (napari/napari/#5195) Set selection color for QListView item. (napari/napari/#5202) Add warning about set private attr when using proxy (napari/napari/#5209) Shapes interpolation (napari/napari/#5334) Add dask settings to preferences (napari/napari/#5490) Add lasso tool for faster drawing of polygonal Shapes (napari/napari/#5555) Feature: support for textures and vertex colors on Surface layers (napari/napari/#5642) Back point selection with a psygnal Selection (napari/napari/#5691) Zooming with the mouse wheel in any mode (napari/napari/#5701) Add cancellation functionality to progress (napari/napari/#5728) Add arrow display styles to Vectors layer (napari/napari/#5740) Improvements Set keyboard focus on console when opened (napari/napari/#5208) Push variables to console when instantiated (napari/napari/#5210) Tracks layer creation performance improvement (napari/napari/#5303) PERF: Event emissions and perf regression. (napari/napari/#5307) Much faster FormatStringEncoding (napari/napari/#5315) Add parent when creating layer context menu to inherit application theme and add style entry for disabled widgets and menus (napari/napari/#5381) Add correct <code>enablement</code> kwarg to <code>Split Stack</code> action, <code>Convert data type</code> submenu and <code>Projections</code> submenu (napari/napari/#5437) Apply disabled widgets style only for menus and set menus styles for <code>QModelMenu</code> and <code>QMenu</code> instances (napari/napari/#5446) Add disabled style rule for <code>QComboBox</code> following the one for <code>QPushButton</code> (napari/napari/#5469) Allow layers control section to resize to contents (napari/napari/#5474) Allow to use <code>Optional</code> annotation in function return type for magicgui functions (napari/napari/#5595) Skip equality comparisons in EventedModel when unnecessary (napari/napari/#5615) Bugfix: improve layout of Preferences > Shortcuts tables (napari/napari/#5679) Improve preferences genration (napari/napari/#5696) Add dev example for adding custom overlays. (napari/napari/#5719) Disable buffer swapping (napari/napari/#5741) Remove max brush size from increase brush size keybinding (napari/napari/#5761) Explicitly list valid layer names in types (napari/napari/#5823) Sort npe1 widget contributions (napari/napari/#5865) feat: add <code>since_version</code> argument of <code>rename_argument</code> decorator (napari/napari/#5910) Emit extra information with layer.events.data (napari/napari/#5967) Performance Return early when no slicing needed (napari/napari/#5239) Tracks layer creation performance improvement (napari/napari/#5303) PERF: Event emissions and perf regression. (napari/napari/#5307) Much faster FormatStringEncoding (napari/napari/#5315) Fix inefficient label mapping in direct color mode (10-20x speedup) (napari/napari/#5723) Efficient labels mapping for drawing in Labels (60 FPS even with 8000x8000 images) (napari/napari/#5732) Disable buffer swapping (napari/napari/#5741) Bug Fixes Warn instead of failing on empty or invalid alt-text (napari/napari/#4505) Fix display of order and scale combinations (napari/napari/#5004) Enforce that contrast limits must be increasing (napari/napari/#5036) Bugfix: Move Window menu to be before Help (napari/napari/#5093) Add extra garbage collection for some viewer tests (napari/napari/#5108) Connect image to plane events and expose them (napari/napari/#5131) Workaround for discover themes from plugins (napari/napari/#5150) Add missed dialogs to <code>qtbot</code> in <code>test_qt_notifications</code> to prevent segfaults (napari/napari/#5171) DOC Update docstring of <code>add_dock_widget</code> & <code>_add_viewer_dock_widget</code> (napari/napari/#5173) Fix unsortable features (napari/napari/#5186) Avoid possible divide-by-zero in Vectors layer thumbnail update (napari/napari/#5192) Disable napari-console button when launched from jupyter (napari/napari/#5213) Volume rendering updates for isosurface and attenuated MIP (napari/napari/#5215) Return early when no slicing needed (napari/napari/#5239) Check strictly increasing values when clipping contrast limits to a new range (napari/napari/#5258) UI Bugfix: Make disabled QPushButton more distinct (napari/napari/#5262) Respect background color when calculating scale bar color (napari/napari/#5270) Fix circular import in _vispy module (napari/napari/#5276) Use only data dimensions for cord in status bar (napari/napari/#5283) Prevent obsolete reports about failure of cleaning viewer instances (napari/napari/#5317) Add scikit-image[data] to install_requires, because it's required by builtins (napari/napari/#5329) Fix repeating close dialog on macOS and qt 5.12 (napari/napari/#5337) Disable napari-console if napari launched from vanilla python REPL (napari/napari/#5350) For npe2 plugin, use manifest display_name for File > Open Samples (napari/napari/#5351) Bugfix plugin display_name use (File > Open Sample, Plugin menus) (napari/napari/#5366) Fix editing shape data above 2 dimensions (napari/napari/#5383) Fix test keybinding for layer actions (napari/napari/#5406) fix theme id not being used correctly (napari/napari/#5412) Clarify layer's editable property and separate interaction with visible property (napari/napari/#5413) Fix theme reference to get image for <code>success_label</code> style (napari/napari/#5447) Bugfix: Ensure layer._fixed_vertex is set when rotating (napari/napari/#5449) Fix <code>_n_selected_points</code> in _layerlist_context.py (napari/napari/#5450) Refactor Main Window status bar to improve information presentation (napari/napari/#5451) Bugfix: Fix test_get_system_theme test for <code>name</code> to <code>id</code> change (napari/napari/#5456) Bugfix: POLL_INTERVAL_MS used in QTimer needs to be an int on python 3.10 (napari/napari/#5467) Bugfix: Add missing Enums and Flags required by PySide6 > 6.4 (napari/napari/#5480) BugFix: napari does not start with Python v3.11.1: ""ValueError: A distribution name is required."" (napari/napari/#5482) Fix inverted LUT and blending (napari/napari/#5487) Fix opening file dialogs in PySide (napari/napari/#5492) Handle case when QtDims play thread is partially deleted (napari/napari/#5499) Ensure surface normals and wireframes are using Models internally (napari/napari/#5501) Recursively check for dependent property to fire events. (napari/napari/#5528) Set PYTHONEXECUTABLE as part of macos fixes on (re)startup (napari/napari/#5531) Un-set unified title and tool bar on mac (Qt property) (napari/napari/#5533) Fix key error issue of action manager (napari/napari/#5539) Bugfix: ensure Checkbox state comparisons are correct by using Qt.CheckState(state) (napari/napari/#5541) Clean dangling widget in test (napari/napari/#5544) Fix <code>test_worker_with_progress</code> by wait on worker end (napari/napari/#5548) Fix min req (napari/napari/#5560) Fix vispy axes labels (napari/napari/#5565) Fix colormap utils error suggestion code and add a test (napari/napari/#5571) Fix problem of missing plugin widgets after minimize napari (napari/napari/#5577) Make point size isotropic (napari/napari/#5582) Fix guard of qt import in <code>napari.utils.theme</code> (napari/napari/#5593) Fix empty shapes layer duplication and <code>Convert to Labels</code> enablement logic for selected empty shapes layers (napari/napari/#5594) Stop using removed multichannel= kwarg to skimage functions (napari/napari/#5596) Add information about <code>syntax_style</code> value in error message for theme validation (napari/napari/#5602) Remove catch_warnings in slicing (napari/napari/#5603) Incorret theme should not prevent napari from start (napari/napari/#5605) Unblock axis labels event to be emitted when slider label changes (napari/napari/#5631) Bugfix: IndexError slicing Surface with higher-dimensional vertex_values (napari/napari/#5635) Bugfix: Convert Viewer Delete button to QtViewerPushButton with action and shortcut (napari/napari/#5636) Change dim <code>axis_label</code> resize logic to set width using only displayed labels width (napari/napari/#5640) Feature: support for textures and vertex colors on Surface layers (napari/napari/#5642) Fix features issues with init param and property setter (napari/napari/#5646) Bugfix: Don't double toggle visibility for linked layers (napari/napari/#5656) Bugfix: ensure pan/zoom buttons work, along with spacebar keybinding (napari/napari/#5669) Bugfix: Add Tracks to qt_keyboard_settings (napari/napari/#5678) Fix automatic naming and GUI exposure of multiple unnamed colormaps (napari/napari/#5682) Fix mouse movement handling for <code>TransformBoxOverlay</code> (napari/napari/#5692) Update environment.yml (napari/napari/#5693) Resolve symlinks from path to environment for setting path (napari/napari/#5704) Fix tracks color-by when properties change (napari/napari/#5708) Fix Sphinx warnings (napari/napari/#5717) Do not use depth for canvas overlays; allow setting blending mode for overlays (napari/napari/#5720) Unify event behaviour for points and its qt controls (napari/napari/#5722) Fix camera 3D absolute rotation bug (napari/napari/#5726) Maint: Bump mypy (napari/napari/#5727) Style <code>QGroupBox</code> indicator (napari/napari/#5729) Fix centering of non-displayed dimensions (napari/napari/#5736) Don't attempt to use npe1 readers in napari.plugins._npe2.read (napari/napari/#5739) Prevent canvas micro-panning on point add (",mds,True,findable,0,0,0,0,0,2023-07-05T05:01:21.000Z,2023-07-05T05:01:22.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4288857,din14970/TVIPSconverter: tvipsconverter v0.1.3,Zenodo,2020,,Software,Open Access,"GUI converter for 4D-STEM or PED data from TVIPS cameras into .blo files, tiffs, or .hspy files.",mds,True,findable,0,0,0,0,0,2020-11-24T14:48:06.000Z,2020-11-24T14:48:07.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.rb0qk13,Data from: Cold adaptation in the Asian tiger mosquito’s native range precedes its invasion success in temperate regions,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"Adaptation to environmental conditions within the native range of exotic species can condition the invasion success of these species outside their range. The striking success of the Asian tiger mosquito, Aedes albopictus, to invade temperate regions has been attributed to the winter survival of diapause eggs in cold environments. In this study, we evaluate genetic polymorphisms (SNPs) and wing morphometric variation among three biogeographical regions of the native range of A. albopictus. Reconstructed demographic histories of populations show an initial expansion in Southeast Asia and suggest that marine regression during late Pleistocene and climate warming after the last glacial period favored expansion of populations in southern and northern regions respectively. Searching for genomic signatures of selection, we identified significantly differentiated SNPs among which several are located in or within 20kb distance from candidate genes for cold adaptation. These genes involve cellular and metabolic processes and several of them have been shown to be differentially expressed under diapausing conditions. The three biogeographical regions also differ for wing size and shape, and wing size increases with latitude supporting Bergmann’s rule. Adaptive genetic and morphometric variation observed along the climatic gradient of A. albopictus native range suggests that colonization of northern latitudes promoted adaptation to cold environments prior to its worldwide invasion.",mds,True,findable,255,14,2,2,0,2019-06-17T17:42:21.000Z,2019-06-17T17:42:21.000Z,dryad.dryad,dryad,"Aedes albopictus,cold adaptation","[{'subject': 'Aedes albopictus'}, {'subject': 'cold adaptation'}]",['9913223 bytes'],
+10.5281/zenodo.7689499,Code and Data Presented in JFSMA 2023,Zenodo,2023,,Software,Closed Access,Code of the simulation<br> Graphs and raw data obtained through simulations Models used for model checking,mds,True,findable,0,0,0,0,0,2023-03-01T18:01:45.000Z,2023-03-01T18:01:45.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7056781,Companion data of Exploiting system level heterogeneity to improve the performance of a GeoStatistics multi-phase task-based application,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is the companion data repository for the paper entitled <strong>Exploiting system level heterogeneity to improve the performance of a GeoStatistics multi-phase task-based application</strong> by Lucas Leandro Nesi, Lucas Mello Schnorr, and Arnaud Legrand. The manuscript has been accepted for publication in the ICPP 2021.",mds,True,findable,0,0,0,0,0,2022-09-07T11:24:38.000Z,2022-09-07T11:24:39.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.612jm643q,Photosynthesis from stolen chloroplasts can support sea slug reproductive fitness,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Some sea slugs are able to steal functional chloroplasts (kleptoplasts) from their algal food sources, but the role and relevance of photosynthesis to the animal host remain controversial. While some researchers claim that kleptoplasts are slowly digestible ‘snacks’, others advocate that they enhance the overall fitness of sea slugs much more profoundly. Our analysis show light-dependent incorporation of 13C and 15N in the albumen gland and gonadal follicles of the sea slug Elysia timida, representing translocation of photosynthates to kleptoplast-free reproductive organs. Long-chain polyunsaturated fatty acids with reported roles in reproduction were produced in the sea slug cells using labelled precursors translocated from the kleptoplasts. Finally, we report reduced fecundity of E. timida by limiting kleptoplast photosynthesis. The present study indicates that photosynthesis enhances the reproductive fitness of kleptoplast-bearing sea slugs, confirming the biological relevance of this remarkable association between a metazoan and an algal-derived organelle.",mds,True,findable,168,17,0,1,0,2021-10-08T00:26:52.000Z,2021-10-08T00:26:54.000Z,dryad.dryad,dryad,"kleptoplast,Fatty acid","[{'subject': 'kleptoplast'}, {'subject': 'Fatty acid'}]",['48249 bytes'],
+10.5281/zenodo.8362750,"Raw Data for Ultrashort Electron Wave Packets via Frequency-Comb Synthesis. Aluffi et al, 2023",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This compressed files contains all the raw data and the python analysis scripts used to generate the figures in the paper Ultrashort Electron Wave Packets via Frequency-Comb Synthesis, Aluffi et al, 2023. 10.1103/PhysRevApplied.20.034005 Preprint available at https://doi.org/10.48550/arXiv.2212.12311",mds,True,findable,0,0,0,0,0,2023-09-20T17:09:28.000Z,2023-09-20T17:09:29.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8420459,Datasets for 2D Vertical Convection: Base States and Leading Linear Modes using Snek5000-cbox,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains two types of datasets related to 2D vertical convection analysis, generated using the snek5000-cbox simulation framework. The first dataset includes base states computed with the Selective Frequency Damping (SFD) method, considering various aspect ratios and Prandtl numbers. The second dataset provides the decomposed amplitude, phase, frequency, and omega of the leading linear mode, accompanied by the corresponding base states for different aspect ratios and Prandtl numbers. All datasets are stored in the .h5 file format for easy access and analysis. The scripts used to produce the datasets are provided in the repository https://github.com/snek5000/snek5000-cbox/tree/main/doc/scripts/2022sidewall_conv_instabilities.",mds,True,findable,0,0,0,0,0,2023-10-09T09:09:02.000Z,2023-10-09T09:09:02.000Z,cern.zenodo,cern,"Vertical convection,Linear stability,Snek5000-cbox","[{'subject': 'Vertical convection'}, {'subject': 'Linear stability'}, {'subject': 'Snek5000-cbox'}]",,
+10.6084/m9.figshare.c.6272373,Digitally-supported patient-centered asynchronous outpatient follow-up in rheumatoid arthritis - an explorative qualitative study,figshare,2022,,Collection,Creative Commons Attribution 4.0 International,"Abstract Objective A steadily increasing demand and decreasing number of rheumatologists push current rheumatology care to its limits. Long travel times and poor accessibility of rheumatologists present particular challenges for patients. Need-adapted, digitally supported, patient-centered and flexible models of care could contribute to maintaining high-quality patient care. This qualitative study was embedded in a randomized controlled trial (TELERA) investigating a new model of care consisting of the use of a medical app for ePRO (electronic patient-reported outcomes), a self-administered CRP (C-reactive protein) test, and joint self-examination in rheumatoid arthritis (RA) patients. The qualitative study aimed to explore experiences of RA patients and rheumatology staff regarding (1) current care and (2) the new care model. Methods The study included qualitative interviews with RA patients (n = 15), a focus group with patient representatives (n = 1), rheumatology nurses (n = 2), ambulatory rheumatologists (n = 2) and hospital-based rheumatologists (n = 3). Data was analyzed by qualitative content analysis. Results Participants described current follow-up care as burdensome. Patients in remission have to travel long distances. Despite pre-scheduled visits physicians lack questionnaire results and laboratory results to make informed shared decisions during face-to-face visits. Patients reported that using all study components (medical app for ePRO, self-performed CRP test and joint self-examination) was easy and helped them to better assess their disease condition. Parts of the validated questionnaire used in the trial (routine assessment of patient index data 3; RAPID3) seemed outdated or not clear enough for many patients. Patients wanted to be automatically contacted in case of abnormalities or at least have an app feature to request a call-back or chat. Financial and psychological barriers were identified among rheumatologists preventing them to stop automatically scheduling new appointments for patients in remission. Rheumatology nurses pointed to the potential lack of personal contact, which may limit the holistic care of RA-patients. Conclusion The new care model enables more patient autonomy, allowing patients more control and flexibility at the same time. All components were well accepted and easy to carry out for patients. To ensure success, the model needs to be more responsive and allow seamless integration of education material. Trial registration The study was prospectively registered on 2021/04/09 at the German Registry for Clinical Trials (DRKS00024928).",mds,True,findable,0,0,0,0,0,2022-10-29T03:17:05.000Z,2022-10-29T03:17:05.000Z,figshare.ars,otjm,"Medicine,Immunology,FOS: Clinical medicine,69999 Biological Sciences not elsewhere classified,FOS: Biological sciences,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.4753275,Figs. 6-7 in A New Perlodes Species And Its Subspecies From The Balkan Peninsula (Plecoptera: Perlodidae),Zenodo,2012,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 6-7. Perlodes floridus floridus sp. n. larva. 6. Head and pronotum, dorsal view. 7. End of abdomen, ventral view.",mds,True,findable,0,0,2,0,0,2021-05-12T18:32:05.000Z,2021-05-12T18:32:06.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Perlodes","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Perlodes'}]",,
+10.25647/liepp.wp.38bis,"Better residential than ethnic discrimination! ( LIEPP Working Paper, n°38 bis)",Sciences Po - LIEPP,2015,en,Other,,"Access to housing is difficult for minorities in France. An audit study we run in the Paris area showed that minority applicants do not face a strong disadvantage in the first step of the application; however, the fact that applicants come from a deprived area leads to more frequent unfavorable outcome (we call this residential discrimination as opposed to ethnic discrimination). The puzzle and paradox come from the fact that face-to-face interviews with real-estate agents in the city of Paris and the Parisian region DO NOT confirm this result. If anything, all discrimi-nation arise from ethnicity and agents dis-miss residential discrimination. Our paper, forthcoming in Urban Studies, documents this contrast between quantitative and qualitative methods and proposes interpretations.",fabricaForm,True,findable,0,0,0,0,0,2022-04-07T13:11:39.000Z,2022-04-07T13:11:40.000Z,vqpf.dris,vqpf,FOS: Social sciences,"[{'subject': 'FOS: Social sciences', 'valueUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'schemeUri': 'http://www.oecd.org/science/inno', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",,
+10.5281/zenodo.4603782,Atomic coordinates of the structures of iCOMs adsorbed at the surface of a crystalline ice model,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset contains the atomic coordinates in the MOLDRAW format (.mol files) of the B3LYP-D3/A-VTZ* optimized structures of iCOMs adsorbed at the surface of a periodic model of proton-ordered crystalline water icy grain using the CRYSTAL17 computer code. Each file can be easily converted in input for the variety of quantum mechanical programs, like VASP, QE, etc.",mds,True,findable,0,0,0,0,0,2021-03-14T18:13:58.000Z,2021-03-14T18:13:59.000Z,cern.zenodo,cern,"Crystalline ice,B3LYP-D3,Adsorption,Modeling","[{'subject': 'Crystalline ice'}, {'subject': 'B3LYP-D3'}, {'subject': 'Adsorption'}, {'subject': 'Modeling'}]",,
+10.5281/zenodo.1068339,Data Sets For The Simulated Ampi (Sampi) Load Balancing Simulation Workflow And Ondes3D Performance Analysis (Companion To Ccpe - Euro-Par 2017 Special Issue),Zenodo,2017,en,Dataset,"Creative Commons Attribution Share-Alike 4.0,Open Access","This package contains data sets and scripts (in an Org-mode file) related to our submission to the special Euro-Par 2017 issue of the journal ""Concurrency and Computation: Practice and Experience"", under the title ""Performance Modeling of a Geophysics Application to Accelerate Over-decomposition Parameter Tuning through Simulation"".",,True,findable,0,0,0,0,0,2017-11-29T18:49:05.000Z,2017-11-29T18:49:06.000Z,cern.zenodo,cern,"Simulation,Load Balancing,Performance Analysis,Over-decomposition,Finite-Differences Method,Simgrid,MPI,Ondes3d,Iterative parallel application","[{'subject': 'Simulation'}, {'subject': 'Load Balancing'}, {'subject': 'Performance Analysis'}, {'subject': 'Over-decomposition'}, {'subject': 'Finite-Differences Method'}, {'subject': 'Simgrid'}, {'subject': 'MPI'}, {'subject': 'Ondes3d'}, {'subject': 'Iterative parallel application'}]",,
+10.5281/zenodo.8269409,Data Artifact: Rebasing Microarchitectural Research with Industry Traces,Zenodo,2023,,Dataset,Creative Commons Attribution 4.0 International,"Data Artifact of the paper ""Rebasing Microarchitectural Research with Industry Traces"", published at the 2023 IEEE International Symposium on Workload Characterization. It includes the original CVP-1 traces used in the paper.
+Note: the improved converted traces used in the paper are available at https://doi.org/10.5281/zenodo.10199624.
+Abstract:Â Microarchitecture research relies on performance models with various degrees of accuracy and speed. In the past few years, one such model, ChampSim, has started to gain significant traction by coupling ease of use with a reasonable level of detail and simulation speed. At the same time, datacenter class workloads, which are not trivial to set up and benchmark, have become easier to study via the release of hundreds of industry traces following the first Championship Value Prediction (CVP-1) in 2018. A tool was quickly created to port the CVP-1 traces to the ChampSim format, which, as a result, have been used in many recent works. We revisit this conversion tool and find that several key aspects of the CVP-1 traces are not preserved by the conversion. We therefore propose an improved converter that addresses most conversion issues as well as patches known limitations of the CVP-1 traces themselves. We evaluate the impact of our changes on two commits of ChampSim, with one used for the first Instruction Championship Prefetching (IPC-1) in 2020. We find that the performance variation stemming from higher accuracy conversion is significant.",mds,True,findable,0,0,0,0,0,2023-08-23T07:41:12.000Z,2023-08-23T07:41:12.000Z,cern.zenodo,cern,"ChampSim,CVP-1 traces","[{'subject': 'ChampSim'}, {'subject': 'CVP-1 traces'}]",,
+10.5281/zenodo.7438422,X-ray radiography 4D particle tracking of heavy spheres suspended in a turbulent jet,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This database report 3d trajectories of heavy spheres suspended in a turbulent upward jet. A cylindrical tank is filled with water and the jet nozzle is placed on its axis on the bottom wall, and a constant flowrate (Q) of water is fed through the nozzle. Conditions at 1700 and 2200 mL/min are considered, and the number of spheres is varied between 1 and 12 (Nsphere). The spheres are glass and are detected using X-ray radiography at 60Hz. The 4d kinematics are obtained with this setup using radioSphere (E. Ando et<br> al., Measurement Science and Technology, 32(9), 095405, 2021). Each condition has a series of files named based on the number of spheres in the tank Nsphere and the flowrate Q, with each sphere of index isphere having its own file. Each file is 3 columns of doubles representing the 3d coordinates x, y, and z of the sphere, in mm, where z is the axis of the cylinder and the points up, against gravity. Results from this database are published here: https://doi.org/10.1016/j.ijmultiphaseflow.2023.104406<br> O. Stamati, B. Marks, E. Ando, S. Roux, N. Machicoane, X-ray radiography 4D particle tracking of heavy spheres suspended in a turbulent jet, <em>International Journal of Multiphase Flow</em> 162, 104406, 2023.",mds,True,findable,0,0,0,0,0,2022-12-14T16:48:44.000Z,2022-12-14T16:48:45.000Z,cern.zenodo,cern,"particle-laden flow, turbulence, jet, X-ray radiography, 4d kinematics","[{'subject': 'particle-laden flow, turbulence, jet, X-ray radiography, 4d kinematics'}]",,
+10.5281/zenodo.7457613,"Video related to the study ""Spatial variability of Saharan dust deposition revealed through a citizen science campaign""",Zenodo,2022,,Audiovisual,"Creative Commons Attribution 4.0 International,Open Access","This video is related to the manuscript ""Spatial variability of Saharan dust deposition revealed through a citizen science campaign"", by Dumont et al., submitted in December 2022 to the journal ""Earth System Science Data"". It illustrates the timeline of dust deposition, simulated by the atmospheric transport model MOCAGE.",mds,True,findable,0,0,0,0,0,2022-12-19T12:34:01.000Z,2022-12-19T12:34:01.000Z,cern.zenodo,cern,,,,
+10.57745/cm2woi,"Bichromatic melt pool thermal measurement based on a Red, Green, and Blue camera: application to additive manufacturing processes",Recherche Data Gouv,2023,,Dataset,,"The data presented here are related to the research article : ""Bichromatic melt pool thermal measurement based on a Red, Green, and Blue camera: application to additive manufacturing processes"". https://doi.org/10.1016/j.optlastec.2023.109799 Date : Feburary 2023 e-mail : loic.jegou@insa-lyon.fr The measure of temperature fields during additive manufacturing processes usually requires bulky expansive equipement such as infrared cameras. A compact full field thermal sensor was developped in order to accurately measure the temperature and the morpholgy of the melt pool during these processes. It is based on a dual-wavelength radiometrioc model and designed to measure temperatures ranging from 1000K to 2500K. The system is calibrated on a blackbody and a tungsten ribbon lamp. This method is validated with two distinct experiments: -Induction heating of a 316L stainless steel tube in a controlled environnement. The temperature is measured with type K thermocouples and compared to the one measured with the camera. In a first experiment, the tube is placed in an open environnement (with oxygen). In a second experiment, the tube is place in an environnement filled with argon that delays its oxidation. -Fusion of a vanadium rod (with a purity of 99.8%) with a laser impulsion of 350 W for 2 seconds. The fusion temperature of pure vanadium is 2183K, and the camera was used to assess the position of the solidifcation front during the experiment. The camera is then used on two different additive manufacturing processes to identify thermal gradients and highlight the melt pool contours. -Laser metal deposition with powder (LMDP). It consists in melting a small section of a substrate with a highly focused energy source, and continuously delivering feedstock material in this melt pool in the form of powder, layer by layer. The camera captures uspide views of the melt pool. -Wire arc additive manufacturing (WAAM). It is based on Gas Metal Arc Welding processes and consists of melting a metal wire onto the substrate with an electric arc as the heat source. The camera captures side views of the melt pool. Please use appropriate citations and referencing while using this dataset by any means. Contributing authors: Loïc Jegou, Joel Lachambre, Nicolas Tardif, Mady Guillemot, Anthony Dellarre, Abderrahime Zaoui, Thomas Elguedj, Valerie Kaftandjian and Nicolas Beraud. Any further information could be asked by making a legitimate request to: Loïc Jegou (loic.jegou@insa-lyon.fr) and Nicolas Tardif (nicolas.tardif@insa-lyon.fr) The folder contains 4 subfolders for every experiments described in the article. Each subfolder contains one folder (image) with the raw images in the format tiff, and a csv file (images_informations.csv) with every informations about the pictures (identification, exposure time, gain, timestamp). - Subfolder 1: Induction_heating, induction heating of a 316L stainless steel tube, - Subfolder 2: Fusion_vanadium, fusion of a Vanadium rod, - Subfolder 3: LMDP, laser metal deposition (with powder), - Subfolder 4: WAAM, wire arc additive manufcaturing. Please refer to the paper for any further scientific details.",mds,True,findable,35,2,0,0,0,2023-02-24T08:50:05.000Z,2023-07-19T10:14:35.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.6390598,PB2007 French acoustic-articulatory speech database,Zenodo,2022,fr,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<strong>PB2007 acoustic-articulatory speech dataset</strong> Badin, P.,Bailly G., Ben Youssef A., Elisei F., Savariaux C., Hueber T. <br> Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, 38000 Grenoble, France<br> <br> LICENSE:<br> ========<br> This dataset is made available under the Creative Commons Attribution Share-Alike (CC-BY-SA) license <br> CREDITS - ATTRIBUTION:<br> ======================<br> If using this dataset, please cite one of the following studies (all of them exploit this dataset) <br> - Ben Youssef, A., Badin, P., Bailly, G. & Heracleous, P. (2009). Acoustic-to-articulatory inversion using speech recognition and trajectory formation based on phoneme hidden Markov models. In Interspeech 2009, vol., pp. 2255-2258. Brighton, UK.<br> - Ben Youssef, A., Badin, P. & Bailly, G. (2010). Can tongue be recovered from face? The answer of data-driven statistical models. In Interspeech 2010 (11th Annual Conference of the International Speech Communication Association) (T. Kobayashi, K. Hirose & S. Nakamura, editors), vol., pp. 2002-2005. Makuhari, Japan.<br> - Hueber T., Bailly G., Badin P., Elisei F., ""Speaker Adaptation of an Acoustic-Articulatory Inversion Model<br> using Cascaded Gaussian Mixture Regressions"", Proceedings of Interspeech, Lyon, France, 2013, pp. 2753-2757. DATA FILES DESCRIPTION:<br> =======================<br> /_seq/: <br> Electro-magnetic Articulography data, recorded at 100Hz<br> Sensors :<br> PAR01 : LT_x (lower incisor, x coordinate)<br> PAR02 : tip_x (tongue tip, x coordinate)<br> PAR03 : mid_x (tongue dorsum, x coordinate)<br> PAR04 : bck_x (tongue back, x coordinate)<br> PAR05 : LL_vis_x (lower lips, x coordinate)<br> PAR06 : UL_vis_x (upper lips, x coordinate)<br> PAR07 : LT_z (lower incisor, z coordinate)<br> PAR08 : tip_z (tongue tip, z coordinate)<br> PAR09 : mid_z (tongue dorsum, z coordinate)<br> PAR10 : bck_z (tongue back, z coordinate)<br> PAR11 : LL_vis_z (lower lips, z coordinate)<br> PAR12 : UL_vis_z (upper lips, z coordinate) /_wav16: <br> subject audio signal, synchronized with the EMA data<br> Format: PCA wav, 16kHz, 16bits /_lab: phonetic segmentation using the following set<br> __ (long pause), _ (short pause), a, e^ (as in ""lait""), e (as in ""blé""), i, y (as in ""voiture""), u (as in ""loup""), o^ (as in ""pomme""),x (as in ""pneu""), x^ (as in ""coeur""), a~ (as in ""flan""), e~ (as in ""in""), x~ (as in ""un""), o~ (as in ""mon""), p, t, k, f, s, s^ (as in ""CHat""), b, d, g, v, z, z^ (as in ""les Gens""), m, n, r, l, w, h, j, o, q (schwa)<br>",mds,True,findable,0,0,0,0,0,2022-03-28T14:22:53.000Z,2022-03-28T14:22:54.000Z,cern.zenodo,cern,"speech, articulatory, EMA","[{'subject': 'speech, articulatory, EMA'}]",,
+10.5281/zenodo.4761353,"Figs. 85-87. Dictyogenus fontium species complex, larva. 85 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 85-87. Dictyogenus fontium species complex, larva. 85. Pronotum, lateral view. Inner-alpine upper Isère Valley. Col de l'Iseran, Savoie dpt, France. Photo Alexandre Ruffoni. 86. Pronotum, lateral view. Inneralpine upper Swiss Rhône valley, Anniviers Valley, canton of Valais, Switzerland. Photo J.-P.G. Reding. 87. Hind leg, lateral view. Inner-alpine upper Swiss Rhône valley, Anniviers Valley, canton of Valais, Switzerland. Photo J.-P.G. Reding.",mds,True,findable,0,0,6,0,0,2021-05-14T07:52:15.000Z,2021-05-14T07:52:16.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.34847/nkl.bafagy29,"Figure 8 : Extrait vidéo ""Prendre la pose pour la caméra""",NAKALA - https://nakala.fr (Huma-Num - CNRS),2023,,Audiovisual,,"Figure 8 : Extrait vidéo ""Prendre la pose pour la caméra""
+
+Dans le chapitre : Participer au quotidien d’enfants d’âge préscolaire. Saisir l’expérience sensible de la ville par un dispositif d’immersion filmique",api,True,findable,0,0,0,0,0,2023-10-13T12:52:25.000Z,2023-10-13T12:52:26.000Z,inist.humanum,jbru,"enfant,méthode","[{'subject': 'enfant'}, {'subject': 'méthode'}]",['38408502 Bytes'],['video/quicktime']
+10.5061/dryad.k31d4,"Data from: Replication levels, false presences, and the estimation of presence / absence from eDNA metabarcoding data",Dryad,2014,en,Dataset,Creative Commons Zero v1.0 Universal,"Environmental DNA (eDNA) metabarcoding is increasingly used to study the present and past biodiversity. eDNA analyses often rely on amplification of very small quantities or degraded DNA. To avoid missing detection of taxa that are actually present (false negatives), multiple extractions and amplifications of the same samples are often performed. However, the level of replication needed for reliable estimates of the presence/absence patterns remains an unaddressed topic. Furthermore, degraded DNA and PCR/sequencing errors might produce false positives. We used simulations and empirical data to evaluate the level of replication required for accurate detection of targeted taxa in different contexts and to assess the performance of methods used to reduce the risk of false detections. Furthermore, we evaluated whether statistical approaches developed to estimate occupancy in the presence of observational errors can successfully estimate true prevalence, detection probability and false-positive rates. Replications reduced the rate of false negatives; the optimal level of replication was strongly dependent on the detection probability of taxa. Occupancy models successfully estimated true prevalence, detection probability and false-positive rates, but their performance increased with the number of replicates. At least eight PCR replicates should be performed if detection probability is not high, such as in ancient DNA studies. Multiple DNA extractions from the same sample yielded consistent results; in some cases, collecting multiple samples from the same locality allowed detecting more species. The optimal level of replication for accurate species detection strongly varies among studies and could be explicitly estimated to improve the reliability of results.",mds,True,findable,256,33,1,1,0,2014-10-23T19:31:38.000Z,2014-10-23T19:31:40.000Z,dryad.dryad,dryad,"Octolasion cyaneum,Aporrectodea icterica,2011,Occupancy Modelling,Aporrectodea rosea,Aporrectodea longa,Lumbricidae,Lumbricus castaneus,replication levels,Environmental sequences,Lumbricus rubellus,Aporrectodea caliginosa,Dendrodrilus rubidus,species occurrence,Lumbricus terrestris","[{'subject': 'Octolasion cyaneum'}, {'subject': 'Aporrectodea icterica'}, {'subject': '2011'}, {'subject': 'Occupancy Modelling'}, {'subject': 'Aporrectodea rosea'}, {'subject': 'Aporrectodea longa'}, {'subject': 'Lumbricidae'}, {'subject': 'Lumbricus castaneus'}, {'subject': 'replication levels'}, {'subject': 'Environmental sequences'}, {'subject': 'Lumbricus rubellus'}, {'subject': 'Aporrectodea caliginosa'}, {'subject': 'Dendrodrilus rubidus'}, {'subject': 'species occurrence'}, {'subject': 'Lumbricus terrestris'}]",['13212 bytes'],
+10.6084/m9.figshare.23575381.v1,Additional file 8 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 7,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:57.000Z,2023-06-25T03:11:58.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['24064 Bytes'],
+10.5281/zenodo.6798922,Binding Energies of Interstellar Relevant S-bearing Species on Water Ice Mantles: A Quantum Mechanical Investigation,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This Supporting Material contains: Fractional coordinates of DFT optimized adsorption complexes for crystalline periodic ice models in .mol format, editable with MOLDRAW, using CRYSTAL17 computer code; Fractional coordinates of HF-3c optimized adsorption complexes for amorphous periodic ice models in .mol format, editable with MOLDRAW, using CRYSTAL17 computer code; Images of the adsorption features at crystalline periodic ice models, in which electrostatic potential maps, spin density maps (when available) and vibrational features are displayed; A pdf file with a thorough guide to the computation of BEs and the basis sets employed for the calculations.",mds,True,findable,0,0,0,0,0,2022-08-26T09:55:11.000Z,2022-08-26T09:55:12.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.5570297,Seasonal trajectories of plant-pollinator networks differ along an urbanization gradient - Data and code,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset and code used in the article ""Seasonal trajectories of plant-pollinator networks differ along an urbanization gradient"".",mds,True,findable,0,0,0,0,0,2021-10-14T15:59:49.000Z,2021-10-14T15:59:50.000Z,cern.zenodo,cern,"network,urbanization,diversity,plant-pollinator interactions,temporal variability,spatial variability","[{'subject': 'network'}, {'subject': 'urbanization'}, {'subject': 'diversity'}, {'subject': 'plant-pollinator interactions'}, {'subject': 'temporal variability'}, {'subject': 'spatial variability'}]",,
+10.5281/zenodo.5801251,Sedimentary structure discrimination with hyperspectral imaging in sediment cores,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The LDB17_P11Ax (IGSN: TOAE0000000243); Datation Age 1040 +/- 30 to 2017 CE by core correlation, 14C, lamina counting) core from the Bourget Lake (France) was analyzed in 2018 by hyperspectral imaging. We studied the potential of hyperspectral sensor to image a sediment cores and created machine learning models. The hyperspectral images were acquired in order to develop quantitative (estimating particle size and loss on ignition) and qualitative (detection of instantaneous events or lamina) methods.<br> All these methods allow to reconstruct the past environment and climate at high resolution (pixel size: 50-250 microns) and without destroying the sample for archiving for future analysis.<br> These images have been valorized in publications for the detection of instantaneous events with hyperspectral and combined with XRF data, for the combination of the two images into a composite image.<br> image (.hdr, .dat, .jpg)",mds,True,findable,0,0,0,2,0,2021-12-23T10:16:43.000Z,2021-12-23T10:16:44.000Z,cern.zenodo,cern,"Hyperspectral imaging,Machine learning,Discrimination methods,Visible and near-infrared spectroscopy,Automatic detection,Sedimentary deposits","[{'subject': 'Hyperspectral imaging'}, {'subject': 'Machine learning'}, {'subject': 'Discrimination methods'}, {'subject': 'Visible and near-infrared spectroscopy'}, {'subject': 'Automatic detection'}, {'subject': 'Sedimentary deposits'}]",,
+10.5281/zenodo.4629216,Deglacial ice sheet instabilities induced by proglacial lakes,Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This archive provides the GRISLI ice sheet model outputs as part of the manuscript ""Deglacial ice sheet instabilities induced by proglacial lakes"". Contact: aurelien.quiquet@lsce.ipsl.fr",mds,True,findable,0,0,0,0,0,2021-03-23T08:23:24.000Z,2021-03-23T08:23:25.000Z,cern.zenodo,cern,"ice sheet,deglaciation,proglacial lake,grounding line","[{'subject': 'ice sheet'}, {'subject': 'deglaciation'}, {'subject': 'proglacial lake'}, {'subject': 'grounding line'}]",,
+10.6084/m9.figshare.22610681,Additional file 1 of Efficacy and auditory biomarker analysis of fronto-temporal transcranial direct current stimulation (tDCS) in targeting cognitive impairment associated with recent-onset schizophrenia: study protocol for a multicenter randomized double-blind sham-controlled trial,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1. Ethical approval.,mds,True,findable,0,0,0,0,0,2023-04-13T12:04:21.000Z,2023-04-13T12:04:22.000Z,figshare.ars,otjm,"Medicine,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,69999 Biological Sciences not elsewhere classified,Science Policy,111714 Mental Health,FOS: Health sciences","[{'subject': 'Medicine'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Science Policy'}, {'subject': '111714 Mental Health', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['1737833 Bytes'],
+10.5281/zenodo.8319672,WRFChem MOSAiC run,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",WRFChem MOSAiC run - April 2020. From https://doi.org/10.1525/elementa.2022.00129,mds,True,findable,0,0,0,0,0,2023-09-05T16:33:07.000Z,2023-09-05T16:33:08.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.1009122,Esa Seom-Ias – Measurement Database 2.3 Μm Region,Zenodo,2017,,Dataset,"Creative Commons Attribution Share-Alike 4.0,Open Access","The database contains measurements performed within the framework of the esa project SEOM-IAS (Scientific Exploitation of Operational Missions - Improved Atmospheric Spectroscopy Databases), ESA/AO/1-7566/13/I-BG. Details on the project can be found at http://www.wdc.dlr.de/seom-ias/.
+
+Measurements for retrieval of absorption line parameters of H<sub>2</sub>O, CO and CH<sub>4</sub> in the spectral range 4190-4340 cm<sup>-1</sup> within the esa project SEOM-IAS were performed by means of Fourier-Transform Spectroscopy (FTS) at the German Aerospace Center (DLR) and Continuous Wave Cavity Ring-Down Spectroscopy (CRDS) at Université Grenoble Alpes. The aim of the measurements was an improved line parameter database according to the needs of the TROPOMI instrument aboard the Sentinel 5-P satellite. The database contains all used molecular spectra used for Parameter retrieval.",,True,findable,0,0,0,1,0,2017-10-11T14:59:37.000Z,2017-10-11T14:59:38.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.c.6853693.v1,Obstructive sleep apnea: a major risk factor for COVID-19 encephalopathy?,figshare,2023,,Collection,Creative Commons Attribution 4.0 International,"Abstract Background This study evaluates the impact of high risk of obstructive sleep apnea (OSA) on coronavirus disease 2019 (COVID-19) acute encephalopathy (AE). Methods Between 3/1/2020 and 11/1/2021, 97 consecutive patients were evaluated at the Geneva University Hospitals with a neurological diagnosis of COVID-19 AE. They were divided in two groups depending on the presence or absence of high risk for OSA based on the modified NOSAS score (mNOSAS, respectively ≥ 8 and < 8). We compared patients’ characteristics (clinical, biological, brain MRI, EEG, pulmonary CT). The severity of COVID-19 AE relied on the RASS and CAM scores. Results Most COVID-19 AE patients presented with a high mNOSAS, suggesting high risk of OSA (> 80%). Patients with a high mNOSAS had a more severe form of COVID-19 AE (84.8% versus 27.8%), longer mean duration of COVID-19 AE (27.9 versus 16.9 days), higher mRS at discharge (≥ 3 in 58.2% versus 16.7%), and increased prevalence of brain vessels enhancement (98.1% versus 20.0%). High risk of OSA was associated with a 14 fold increased risk of developing a severe COVID-19 AE (OR = 14.52). Discussion These observations suggest an association between high risk of OSA and COVID-19 AE severity. High risk of OSA could be a predisposing factor leading to severe COVID-19 AE and consecutive long-term sequalae.",mds,True,findable,0,0,0,0,0,2023-09-27T03:26:12.000Z,2023-09-27T03:26:13.000Z,figshare.ars,otjm,"Biophysics,Medicine,Cell Biology,Neuroscience,Physiology,FOS: Biological sciences,Pharmacology,Biotechnology,Sociology,FOS: Sociology,Immunology,FOS: Clinical medicine,Cancer,Mental Health,Virology","[{'subject': 'Biophysics'}, {'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Pharmacology'}, {'subject': 'Biotechnology'}, {'subject': 'Sociology'}, {'subject': 'FOS: Sociology', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Mental Health'}, {'subject': 'Virology'}]",,
+10.6084/m9.figshare.23575372,Additional file 5 of Decoupling of arsenic and iron release from ferrihydrite suspension under reducing conditions: a biogeochemical model,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Authors’ original file for figure 4,mds,True,findable,0,0,0,0,0,2023-06-25T03:11:51.000Z,2023-06-25T03:11:51.000Z,figshare.ars,otjm,"59999 Environmental Sciences not elsewhere classified,FOS: Earth and related environmental sciences,39999 Chemical Sciences not elsewhere classified,FOS: Chemical sciences,Ecology,FOS: Biological sciences,69999 Biological Sciences not elsewhere classified,Cancer","[{'subject': '59999 Environmental Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '39999 Chemical Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'FOS: Chemical sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Ecology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': '69999 Biological Sciences not elsewhere classified', 'schemeUri': 'http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E', 'subjectScheme': 'FOR'}, {'subject': 'Cancer'}]",['24064 Bytes'],
+10.5281/zenodo.5648316,Raw Data and Scripts for manuscript submitted to Oikos as 'Early Spring Snowmelt and Summer Droughts Strongly Impair the Resilience of Key Microbial Communities in a Subalpine Grassland Ecosystems',Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Raw Data and Scripts for manuscript submitted to PCI as 'Early Spring Snowmelt and Summer Droughts Strongly Impair the Resilience of Key Microbial Communities in Subalpine Grassland Ecosystems',mds,True,findable,0,0,0,0,0,2021-11-05T16:32:43.000Z,2021-11-05T16:32:44.000Z,cern.zenodo,cern,"climate change, grasslands, (de)nitrification, weather extremes, snowmelt, N2O","[{'subject': 'climate change, grasslands, (de)nitrification, weather extremes, snowmelt, N2O'}]",,
+10.5281/zenodo.5913708,Supplementary data for the publication of Characterization of Emissions in Fab Labs: an Additive Manu-facturing Environment Issue,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Datasets for the publication of the article ""Characterization of Emissions in Fab Labs: an Additive Manufacturing Environment Issue"": - Ultrafine Particles: UFP per Zone and mode; - VOC emissions: VOC per Zone and mode.",mds,True,findable,0,0,0,0,0,2022-01-28T13:07:09.000Z,2022-01-28T13:07:10.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7937759,Quantum mechanical modeling of the on-grain formation of acetaldehyde on H2O:CO dirty ice surfaces,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This Supporting Material contains: Cartesian coordinates of HF-3c optimized minima and transition state for the reaction in gas phase, in .xyz format, computed using Gaussian16 code; Fractional coordinates of HF-3c optimized minima and trasition state structures for crystalline periodic models in .mol format, editable with MOLDRAW, computed using CRYSTAL17 computer code.",mds,True,findable,0,0,0,0,0,2023-08-12T07:23:25.000Z,2023-08-12T07:23:26.000Z,cern.zenodo,cern,,,,
+10.2312/yes19,Proceedings of the 5th International Young Earth Scientists (YES) Congress “Rocking Earth’s Futureâ€,German YES Chapter & GFZ German Research Centre for Geosciences,2021,en,Text,Creative Commons Attribution 4.0 International,,fabricaForm,True,findable,0,0,0,0,0,2020-09-10T09:36:58.000Z,2021-08-31T19:11:27.000Z,tib.gfzbib,gfz,"Conference Proceedings,Young Earth Scientists (YES),International Young Earth Scientists (YES) Congress,Geosciences","[{'subject': 'Conference Proceedings'}, {'subject': 'Young Earth Scientists (YES)'}, {'subject': 'International Young Earth Scientists (YES) Congress'}, {'subject': 'Geosciences'}]",['148 pages'],['pdf']
+10.5281/zenodo.2575055,robertxa/pyswath: Second release of pyswath,Zenodo,2019,,Software,Open Access,Python module to extract swath profiles from a raster. This is the second release.,mds,True,findable,0,0,0,1,0,2019-02-21T19:49:43.000Z,2019-02-21T19:49:44.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7007289,2D honeycomb transformation into dodecagonal quasicrystals driven by electrostatic forces,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the key input and output files used for the density fucntional theory calculations of the paper ""Mechanism of 2D Oxide Quasicrystal formation from honeycomb structures"" by Sebastian Schenk, Oliver Krahn, Eric Cockayne, Holger L. Meyerheim, Marc deBoissieu, Stefan F""orster, and Wolf Widdra (2022). The calculations were performed using the DFT code VASP, version 5.4.4 [Commercial software is mentioned in this README file to adquately described the procedure. This does not imply an endorsement or recommendation by the National Institute of Standards and Technology, nor that the software used is necessarily the best for the given<br> purpose.] The subfolder large_approximant contains the files for the large Sr<sub>48</sub>Ti<sub>132</sub>O<sub>204</sub> approximant on a Pt monolayer. Subfolders honeycomb/Pt<sub>N</sub> and sigma/Pt<sub>N</sub> contain the files for honeycomb and sigma Ba<sub>8</sub>Ti<sub>24</sub>O<sub>36</sub> structures on Pt trilayers with N Pt per layer per periodic cell. Subfolders honeycomb/Pt<sub>N</sub>/substrate contain the corresponding files<br> for the Pt substrate alone. The honeycomb and sigma structures are at the equilibrium strain as determined by matching interpolated stress results, as described in the Supplementary Information associated with the main Article. The input files are the standard VASP input files: POSCAR (structure information), POTCAR_TITEL (pseudopotential information. Because the VASP pseudopotential files are proprietary, only the titles of the pseudopotentials used are given), KPOINTS (k-point generation) and INCAR (most calculation details). To accelerate the DFT van der Waals calculation, the file vdw_kernel.bindat from the VASP package (not included here) should also be used. The output files are OSZICAR (summarizes energy at each iteration) and OUTCAR (full ouput).",mds,True,findable,0,0,0,0,0,2022-08-18T13:54:16.000Z,2022-08-18T13:54:17.000Z,cern.zenodo,cern,"Oxide quasicrystals, 2D ternary oxide, quasicrystal approximant, DFT","[{'subject': 'Oxide quasicrystals, 2D ternary oxide, quasicrystal approximant, DFT'}]",,
+10.6084/m9.figshare.23983487.v1,Additional file 2 of Aberrant activation of five embryonic stem cell-specific genes robustly predicts a high risk of relapse in breast cancers,figshare,2023,,Dataset,Creative Commons Attribution 4.0 International,"Additional file 2: Table S1. List of genes with predominant expression in testis, placenta and/or embryonic stem cells. Table S2. Frequencies of ectopic activations of the tissue-specific genes. Table S3. Results of the validation step in the biomarker discovery pipeline. Table S4. Datasets of normal tissues and breast cancers with corresponding sample sizes. Table S5. List of normal tissues and the corresponding sample sizes.",mds,True,findable,0,0,0,0,0,2023-08-18T03:20:43.000Z,2023-08-18T03:20:44.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Genetics,FOS: Biological sciences,Molecular Biology,Biological Sciences not elsewhere classified,Information Systems not elsewhere classified,Mathematical Sciences not elsewhere classified,Developmental Biology,Cancer,Plant Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Genetics'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Molecular Biology'}, {'subject': 'Biological Sciences not elsewhere classified'}, {'subject': 'Information Systems not elsewhere classified'}, {'subject': 'Mathematical Sciences not elsewhere classified'}, {'subject': 'Developmental Biology'}, {'subject': 'Cancer'}, {'subject': 'Plant Biology'}]",['174460 Bytes'],
+10.5281/zenodo.5243356,Swedish DBnary archive in original Lemon format,Zenodo,2021,sv,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Swedish language edition, ranging from 7th April 2015 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.",mds,True,findable,0,0,0,0,0,2021-08-24T11:50:12.000Z,2021-08-24T11:50:13.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.18709/perscido.2021.09.ds353,PAirMax-Airbus,PerSCiDo,2021,en,Dataset,,"This archive contains 5 panchromatic and multispectral bundles (at both both full and reduced resolution). These images are part of the PAirMax dataset (*). This dataset is provided as a password protected folder as data can be accessed only after accepting the Airbus license. Description: The images were derived from original acquisitions by the Pléiades and Spot7 satellites and are provided courtesy of Airbus. The original images full scenes can be accessed at: https://sandbox.intelligence-airbusds.com -> Pansharpening dataset. The 5 images in this archive are listed below. Please refer to [1] for more details on the images and the preprocessing done. - Pl_Hous_Urb - Pl_Sacr_Mix - Pl_Stoc_Urb - S7_Napl_Urb - S7_NewY_Mix Instruction for retrieving the password: - Go to https://sandbox.intelligence-airbusds.com - Fill the form for requesting the Pansharpening dataset (need to accept the Airbus license) - The password will be provided in the confirmation email. ---------------------------------------------------------------------------- (*) The PAirMax dataset is a collection of data with the aim of assessing the performance of pansharpening algorithms. The data collection includes 5 test cases selected at full resolution (FR), acquired by two sensors belonging to the Airbus' constellation of high-resolution imaging satellites. Moreover, 5 related test cases at reduced resolution (RR), simulated according to the Wald’s protocol, are included, thus resulting in 10 challenging test cases for pansharpening performance assessment. For further details, please, refer to the paper: [1] G. Vivone, M. Dalla Mura, A. Garzelli, and F. Pacifici, \""A Benchmarking Protocol for Pansharpening: Dataset, Pre-processing, and Quality Assessment,\"" IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021.",fabrica,True,findable,0,0,0,0,0,2021-09-21T14:31:17.000Z,2021-09-21T14:31:17.000Z,inist.persyval,vcob,"Environmental science and ecology,Information technology","[{'lang': 'en', 'subject': 'Environmental science and ecology'}, {'lang': 'en', 'subject': 'Information technology'}]",['500 MB'],
+10.6084/m9.figshare.23822154.v1,Dataset for the main experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,Data for the main experiment in CSV format.,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:26.000Z,2023-08-02T11:18:26.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['29026 Bytes'],
+10.5281/zenodo.7537055,"Spectral data associated to the publication: ""Reflectance study of ice and Mars soil simulant associations—II. CO2 and H2O ice"" by Z. Yoldi et al. (Icarus 386, 2022)",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is the complete set of experimental VIS-NIR reflectance data collected by Z. Yoldi and co-authors for the article ""Reflectance study of ice and Mars soil simulant associations—II. CO2 and H2O ice"" published in Icarus 386 (2022). doi: https://doi.org/10.1016/j.icarus.2022.115116. A pre-print of the article is also freely available on ArXiv: https://arxiv.org/abs/2207.13905 The article provides the methodology for the spectral aquisitions, discussion of the errors and uncertainties, analysis of the spectra and implications for the composition of Solar System surfaces. The spectral data are organised in folders corresponding to the different types of experiments detailed in the article. In case both hyperspectral and multispectral data were acquired, they are organised in subfolders. The spectral files inside these folders and subfolders have the following naming convention: spectrum_YYYYMMDD_experiment_name_TYPE_XX_YYY.csv Where TYPE is either multi (multispectral) or hyper (hyperspectral), XX indicates different samples within the experiment (see paper, figures and tables) and YYY is a sequential number in case of a temporal evolution (sublimation experiment in ""20180207_ternary_mixture"" with 12 timesteps). The files are in csv format (columns separated by comma) and the content of each column is indicated in the first line (header).",mds,True,findable,0,0,0,0,0,2023-01-14T14:41:33.000Z,2023-01-14T14:41:34.000Z,cern.zenodo,cern,,,,
+10.6084/m9.figshare.c.6756888.v1,Flexible optical fiber channel modeling based on a neural network module,Optica Publishing Group,2023,,Collection,Creative Commons Attribution 4.0 International,"Optical fiber channel modeling which is essential in optical transmission system simulations and designs is usually based on the split-step Fourier method (SSFM), making the simulation quite time-consuming owing to the iteration steps. Here, we train a neural network module termed by NNSpan to learn the transfer function of one single fiber (G652 or G655) span with a length of 80km and successfully emulate long-haul optical transmission systems by cascading multiple NNSpans with a remarkable prediction accuracy even over a transmission distance of 1000km. Although training without erbium-doped fiber amplifier (EDFA) noise, NNSpan performs quite well when emulating the systems affected by EDFA noise. An optical bandpass filter can be added after EDFA optionally, making the simulation more flexible. Comparison with the SSFM shows that the NNSpan has a distinct computational advantage with the computation time reduced by a factor of 12. This method based on the NNSpan could be a supplementary option for optical transmission system simulations, thus contributing to system designs as well.",mds,True,findable,0,0,0,0,0,2023-08-10T20:33:33.000Z,2023-08-10T20:33:33.000Z,figshare.ars,otjm,Uncategorized,[{'subject': 'Uncategorized'}],,
+10.6084/m9.figshare.24196813.v1,Additional file 1 of Sonometric assessment of cough predicts extubation failure: SonoWean—a proof-of-concept study,figshare,2023,,Text,Creative Commons Attribution 4.0 International,"Additional file 1. Supplemental Fig 1: Description of the Pulsar Model 14® Sound Level Meter and method for measurement. The Model 14 is a general purpose digital sound level meter which meets the full requirements of IEC 61672 to Class 2. Before each inclusion the Sound Level Meter was calibrated acoustically using an external reference, i.e the Sound Level Calibrator Model 106, which is placed over the microphone. The calibrator generates a stabilized Sound Pressure Level of 94dB (+- 0.3dB) at a frequency of 1 kHz. Using a Low range (Low = 35dB to 100dB), maximum sound level was measured pressing the MAX HOLD button for at least ½ second and was ultimately noticed. A level of sound in decibels (L) is defined as ten times the base-10 logarithm of the ratio between two power-related quantities I (i.e cough-volume related sound) and Io (i.e the human hearing threshold) as follows: L = 10 * Log 10 (I/ Io). Thus, an apparent mild increase from 73 to 76 dB in sound level results in multiplying acoustic energy by a factor two.",mds,True,findable,0,0,0,0,0,2023-09-26T03:25:47.000Z,2023-09-26T03:25:47.000Z,figshare.ars,otjm,"Medicine,Cell Biology,Physiology,FOS: Biological sciences,Immunology,FOS: Clinical medicine,Infectious Diseases,FOS: Health sciences,Computational Biology","[{'subject': 'Medicine'}, {'subject': 'Cell Biology'}, {'subject': 'Physiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Infectious Diseases'}, {'subject': 'FOS: Health sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Computational Biology'}]",['117717 Bytes'],
+10.5281/zenodo.10020983,robertxa/pytherion: First realease,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,Python code to convert Visual Top .tro file to Therion files (.th and .thconfig),api,True,findable,0,0,0,0,0,2023-10-19T08:43:17.000Z,2023-10-19T08:43:17.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4757636,Figs. 1–4 in Morphology And Systematic Position Of Two Leuctra Species (Plecoptera: Leuctridae) Believed To Have No Specilla,Zenodo,2014,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 1–4. Leuctra bidula. Male abdomen: 1, Dorsal. 2, Lateral. 3, Ventral, Sternite IX. Female abdomen: 4, Ventral, showing the pregenital and subgenital plates (1-4 after Aubert 1962).",mds,True,findable,0,0,2,0,0,2021-05-13T16:06:29.000Z,2021-05-13T16:06:30.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.60662/0yc3-e898,Vers un service générique d’aide à la décision pour gérer un logement basé sur des techniques d’apprentissage interactif et coopératif,CIGI QUALITA MOSIM 2023,2023,,ConferencePaper,,,fabricaForm,True,findable,0,0,0,0,0,2023-09-01T19:58:37.000Z,2023-09-01T19:58:37.000Z,uqtr.mesxqq,uqtr,,,,
+10.5281/zenodo.3257654,Microscopy image sequences and annotated kymographs of laser ablation experiments in Drosophila embryos,Zenodo,2019,en,Dataset,"Creative Commons Attribution Non Commercial Share Alike 4.0 International,Open Access","<strong>Content</strong>
+
+This dataset contains 15 2D time-lapse fluorescence microscopy image sequences recorded with confocal laser-scanning microscopy. Each movie shows an epithelial tissue laser nanoablation experiment conducted in a Drosophila embryo.
+
+For each sequence, the dataset contains kymographs (one-dimensional space-time plots) of a supracellular cable that is cut during the ablation, and manually created tracks of visible features, such as the resulting cut ends. These tracks allow to estimate, for instance, recoil velocities of the cut tissue and may be used to evaluate automated methods for estimating said velocities.
+
+This dataset is used in the manuscript to evaluate various variational approaches for joint motion estimation and source identification:
+
+L. F. Lang, N. Dutta, E. Scarpa, B. Sanson, C.-B. Schönlieb, and J. Étienne. Joint Motion Estimation and Source Identification using Convective Regularisation with an Application to the Analysis of Laser Nanoablations. 2019.
+
+<strong>Description</strong>
+
+The movies depict a square region of approximately \(42.2 \times 42.2 \, \mathrm{\mu m}^{2}\) at a spatial resolution of \(250 \times 250\) pixels. A typical sequence contains between 60 and 100 frames. They temporal interval between recorded frames was \(727.67 \, \mathrm{ms}\).
+
+Each sequence features cell membranes labelled with E-cadherin:GFP and shows a single plasma-induced laser nanoablation. The destructed tissue region is roughly of \(2 \, \mathrm{\mu m}\) length. This ablation is expected to have a width of the order of the size of one pixel. During the ablation the acquisition is paused, resulting in a black image.
+
+For the used microscopy techniques and for the preparation of flies, as well as for the details of the laser ablation method, see the paper:
+
+E. Scarpa, C. Finet, G. B. Blanchard, and B. Sanson. Actomyosin-driven tension at compartmental boundaries orients cell division independently of cell geometry In Vivo. Dev. Cell, 47(6):727–740.e6, December 2018. URL: https://doi.org/10.1016/j.devcel.2018.10.029
+
+The kymographs and the manually created annotations (tracks) of features were created using Fiji (https://fiji.sc/).
+
+<strong>Content</strong>
+
+The dataset contains 15 sequences placed in the following folder structure:
+
+
+ SqAX3_SqhGFP42_GAP43_TM6B
+
+ 190216E4PSB1
+ 190216E5PSB1
+ 190216E5PSB2
+ 190216E6PSB1
+ 190216E8PSB1
+ E2PSB1
+ E5PSB2
+ E8PSB1
+ PSB1E1
+ PSB4
+
+
+ SqhGFP40
+
+ e1_PSB8
+ e3_PSB9
+ e3_PSB10
+ e4_PSB11
+ e4_PSB12
+
+
+
+
+Each folder contains:
+
+
+ The sequence itself in TIF format, e.g. ""190216E4PSB1PMT - PMT [560-] _C1.ome.tif"".
+ A file ""reslice.roi"" that indicates the location/direction of the cut supracellular cable.
+ 3 different kymographs for each sequence obtained by taking avg/max/sum projections in Fiji orthogonal to the line specified in ""reslice.roi"", e.g.
+
+ ""AVG_Reslice of 190216E4PSB1PMT.tif"",
+ ""MAX_Reslice of 190216E4PSB1PMT.tif"",
+ ""SUM_Reslice of 190216E4PSB1PMT.tif"".
+
+
+ Text files that state the time/space coordinates of manually tracked features in the kymographs, e.g.
+
+ ""cutend_L.txt"" (coordinates of the left cut end after the ablation),
+ ""cutend_R.txt"" (coordiantes of the right cut end),
+ ""feat_X.txt"" (coordinates of additional features, where X is a number and L or R).
+
+
+ A ZIP file ""manual_ROIs.zip"" that contains all the coordinates of tracked features of the kymograph in ROI format (e.g. ""cutend_L.roi"").
+
+
+<strong>Usage</strong>
+
+The sequences, kymographs, and the tracks can be viewed using, for example, Fiji.
+
+For the automated analysis, see the Python code that accompanies the manuscript above. It is available at https://dx.doi.org/XXX
+
+<strong>License information</strong>
+
+This dataset is released under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. See CC BY-NA-SC 4.0.
+
+<strong>How to cite this dataset</strong>
+
+If you use this dataset in an academic publication, please consider citing the paper:
+
+L. F. Lang, N. Dutta, E. Scarpa, B. Sanson, C.-B. Schönlieb, and J. Étienne. Joint Motion Estimation and Source Identification using Convective Regularisation with an Application to the Analysis of Laser Nanoablations. 2019.
+
+To cite solely the dataset, please use:
+
+L. F. Lang, N. Dutta, E. Scarpa, B. Sanson, C.-B. Schönlieb, and J. Étienne. (2019). Microscopy image sequences and annotated kymographs of laser ablation experiments in Drosophila embryos [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3257654",mds,True,findable,0,0,0,0,0,2019-06-30T16:48:56.000Z,2019-06-30T16:48:57.000Z,cern.zenodo,cern,"Drosophila,cell membrane,laser ablation,microscopy,image sequence,tracking,kymograph","[{'subject': 'Drosophila'}, {'subject': 'cell membrane'}, {'subject': 'laser ablation'}, {'subject': 'microscopy'}, {'subject': 'image sequence'}, {'subject': 'tracking'}, {'subject': 'kymograph'}]",,
+10.5281/zenodo.4607934,lmarelle/WRF-halogens: WRF-Chem 4.1.1 version including polar bromine chemistry and emissions,Zenodo,2021,,Software,Open Access,"Version 1.0 corresponds to WRF-Chem 4.1.1 + halogen gas-phase chemistry and heterogeneous chemistry on aerosols, also including bromine emissions from surface snow and blowing snow. Version used to perform the runs presented in the paper submitted to JAMES: ""Implementation and impacts of surface and blowing snow sources of Arctic bromine activation within WRF-Chem 4.1.1"" Louis Marelle, Jennie L. Thomas, Shaddy Ahmed, Katie Tuite, Jochen Stutz, Aurelien Dommergue, William R. Simpson, Markus M. Frey, Foteini Baladima",mds,True,findable,0,0,1,0,0,2021-03-16T13:57:31.000Z,2021-03-16T13:57:33.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7970338,"CliffEBM - A Gridded Ice Cliff Energy Balance Model (first public release, v01.1)",Zenodo,2023,en,Software,"Creative Commons Attribution 4.0 International,Open Access","<em>CliffEBM </em>is a model that calculates the distributed surface energy balance and backwasting (melt) rates for ice cliffs, i.e. steep ice surfaces with complex, heterogeneous topographies. The model is validated and described in Buri, P., Pellicciotti, F., Steiner, J., Miles, E., & Immerzeel, W. (2016). <strong>A grid-based model of backwasting of supraglacial ice cliffs on debris-covered glaciers.</strong> <em>Annals of Glaciology,</em> <em>57</em>(71), 199-211. https://doi.org/10.3189/2016AoG71A059 See most update version here: https://github.com/pburi/CliffEBM In this repository we provide example input data (digital elevation models, shapefiles, meteodata) to run <em>CliffEBM </em>on one supraglacial cliff on the debris-covered Lirung Glacier (Nepal). Working example: to run the model, download the entire repository on your machine and adjust the paths in the model code (<em>CliffEBM.R</em>, section ""<em>primary definitions</em>"") according to the paths on your machine. Software: R (R version 4.3.0 (2023-04-21 ucrt) -- ""Already Tomorrow""). The model should also run on older versions. Packages: <em>cleaRskyQuantileRegression, doParallel, foreach, grDevices, iterators, methods, parallel, raster, rgdal, rgeos, sf, sp, stats, utils, zoo</em>",mds,True,findable,0,0,0,0,0,2023-05-25T11:41:22.000Z,2023-05-25T11:41:22.000Z,cern.zenodo,cern,"Ice cliffs,Debris-covered glaciers,Energy balance,Backwasting","[{'subject': 'Ice cliffs'}, {'subject': 'Debris-covered glaciers'}, {'subject': 'Energy balance'}, {'subject': 'Backwasting'}]",,
+10.5061/dryad.rxwdbrvbg,"Genomic shifts, phenotypic clines and fitness costs associated with cold-tolerance in the Asian tiger mosquito",Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Climatic variation is a key driver of genetic differentiation and phenotypic traits evolution, and local adaptation to temperature is expected in widespread species. We investigated phenotypic and genomic changes in the native range of the Asian tiger mosquito, Aedes albopictus. We first refine the phylogeographic structure based on genome-wide regions (1,901 double-digest restriction-site associated DNA single nucleotide polymophisms [ddRAD SNPs]) from 41 populations. We then explore the patterns of cold adaptation using phenotypic traits measured in common garden (wing size and cold tolerance) and genotype–temperature associations at targeted candidate regions (51,706 exon-capture SNPs) from nine populations. We confirm the existence of three evolutionary lineages including clades A (Malaysia, Thailand, Cambodia, and Laos), B (China and Okinawa), and C (South Korea and Japan). We identified temperature-associated differentiation in 15 out of 221 candidate regions but none in ddRAD regions, supporting the role of directional selection in detected genes. These include genes involved in lipid metabolism and a circadian clock gene. Most outlier SNPs are differently fixed between clades A and C, whereas clade B has an intermediate pattern. Females are larger at higher latitudes yet produce no more eggs, which might favor the storage of energetic reserves in colder climates. Nondiapausing eggs from temperate populations survive better to cold exposure than those from tropical populations, suggesting they are protected from freezing damages but this cold tolerance has a fitness cost in terms of egg viability. Altogether, our results provide strong evidence for the thermal adaptation of A. albopictus across its wide temperature range.",mds,True,findable,87,1,0,0,0,2022-11-18T18:12:59.000Z,2022-11-18T18:13:00.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences,Aedes albopictus,ddRAD Sequencing,thermal adaptation,Common garden,fitness,cold tolerance,Wing Size","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Aedes albopictus'}, {'subject': 'ddRAD Sequencing'}, {'subject': 'thermal adaptation'}, {'subject': 'Common garden'}, {'subject': 'fitness'}, {'subject': 'cold tolerance'}, {'subject': 'Wing Size'}]",['10516046 bytes'],
+10.5061/dryad.jm63xsj7b,Data from: Tetra-EU 1.0: a species-level trophic meta-web of European tetrapods,Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"Motivation Documenting potential interactions between species represents a major step to understand and predict the spatial and temporal structure of multi-trophic communities and their functioning. The metaweb concept summarises the potential trophic (and non-trophic) interactions in a given species-pool. As such, it generalises the regional species-pool of community ecology by incorporating the potential relationships between species from different trophic levels along with their functional characteristics. However, while this concept is theoretically very attractive, it has rarely been used to understand the structure of ecological network, mostly because of data availability. Here, we provide a continental scale, species-level, metaweb for all tetrapods (mammals, breeding birds, reptiles, amphibians) occurring in Europe and in the Northern Mediterranean basin. This metaweb is based on data extracted from scientific literature, including published papers, books, and grey literature. Main type of variable contained For each species considered, we built the network of potential 2-way trophic interactions. Spatial location and grain We considered all species occurring in the entire European sub-continent, from Macaronesia (including only the islands politically belonging to Spain and Portugal) to the Ural Mountains (west to east), and from Fennoscandia and UK islands to the Mediterranean (north to south). We included Turkey, geographically part of Asia, to provide a complete picture of the north-eastern Mediterranean coast. Time period The data represent information published and/or collected during the last 50 years. Major taxa studied and level of measurement We focused our metaweb on terrestrial tetrapods occurring in the study area. Only species introduced in historical times and currently naturalized were considered; novel introductions were excluded. In total we included 288 mammals, 509 regularly breeding birds, 250 reptiles, and 104 amphibians. Software format Data are supplied as semi-colon separated text files.",mds,True,findable,656,251,1,2,0,2020-05-21T07:58:22.000Z,2020-05-21T07:58:23.000Z,dryad.dryad,dryad,"breeding birds,Reptiles,metaweb,Trophic interactions","[{'subject': 'breeding birds'}, {'subject': 'Reptiles', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'metaweb'}, {'subject': 'Trophic interactions', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}]",['16596876 bytes'],
+10.5061/dryad.27qf3,Data from: Landscape-scale distribution patterns of earthworms inferred from soil DNA,Dryad,2016,en,Dataset,Creative Commons Zero v1.0 Universal,"Assessing land-use effect on the diversity of soil biota has long been hampered by difficulties in collecting and identifying soil organisms over large areas. Recently, environmental DNA-based approaches coupled with next-generation sequencing were developed to study soil biodiversity. Here, we optimized a protocol based on soil DNA to examine the effects of land-use on earthworm communities in a mountain landscape. This approach allowed an efficient detection of earthworm diversity and highlighted a significant land-use effect on the distribution patterns of earthworms that was not revealed by a classical survey. Our results show that the soil DNA-based earthworm survey at the landscape-scale improves over previous approaches, and opens a way towards large-scale assessment of soil biodiversity and its drivers.",mds,True,findable,328,48,1,2,0,2015-02-05T15:21:48.000Z,2015-02-05T15:21:49.000Z,dryad.dryad,dryad,"earthworm,Spatial distribution,Land-use,Soil biodiversity,Holocene","[{'subject': 'earthworm'}, {'subject': 'Spatial distribution'}, {'subject': 'Land-use'}, {'subject': 'Soil biodiversity'}, {'subject': 'Holocene'}]",['62066006 bytes'],
+10.5281/zenodo.4761335,"Fig. 57 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Fig. 57. Dictyogenus alpinum, male, epiproct, lateral view. Nant Bénin River, Savoie dpt, France. Photo B. Launay.",mds,True,findable,0,0,6,0,0,2021-05-14T07:49:44.000Z,2021-05-14T07:49:45.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.8025653,Accelerated exploration of multinary systems,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This repository contains the datasets produced from the characterizations of the quinary Nb-Ti-Zr-Cr-Mo, and predictions made by Machine Learning models. <strong>Experimental work</strong> Gradients of composition were characterized by: EDX for composition evaluation, with an error of 1% on atomic and mass composition nanoindentation for the measurement of the elastic modulus (E) and hardness (H) EBSD : from each map we extract the Confidence Index CI and Image Quality IQ that are indicator of crystallinity. CI is also used to define phase classes (0 for amorphous, 1 for crystalline) XRD: from each diffractogram we extract a phase class (0 for amorphous, 1 for crystalline): raw data are available in XRD.zip Different datasets are built: Raw_data associate to each composition the EBSD CI, IQ, EBSD phase class, and the elastic modulus (E) and hardness (H) computed by the software TestWork Analysis without any correction. For each composition, 5 measurement replications were performed. Raw_data_corrected contains the EBSD CI, IQ, EBSD phase class, and the 5 replications per compositions of E and H corrected through Oliver and Pharr model. Compo_E_H_threshold correspond to Raw_data_corrected in which we have thresholded values of E and H. We removed all composition such that E < 10 GPa and all H < 2 GPa, as they correspond to nanoindentation test failures. Compo_E_wo_outliers and Compo_H_wo_outliers: Dixon test allows to identify outliers on E replications and H replications, that are removed to give each dataset. Each composition is associated to replications of E or H that were not identified as outliers. Averaged_data: each composition is associated to EBSD CI, IQ, EBSD phase class, and with average values of E and H replications without outliers. Data_averaged_mechanical_model: add to previous data the other mechanical properties computed with Galanov model from E and H experimental results: relative characteristic size of the elastic-plastic zone under the indenter \(x = \frac{b_s}{c}\), the constrain factor \(C\) – linking yield strength and hardness – and the ductility characteristic \(\delta_H\) – ratio of plastic deformation and total deformation. It also contains \(\frac{E²}{H}\). Database_XRD: each composition is associated to phase class defined from XRD diffractograms The dataset_initial.zipl contains the experimental results with an initial 20-gradients sets which screen preferably the center of Nb-Ti-Zr-Cr-Mo. It contains all the kind of datasets. The dataset_adding_binaries.zip contains the experimental results for the initial 20-gradients + additional binary gradients Nb-Ti binary 1), Nb-Cr (binary 2) and Cr-Mo (binary 3). It contains the data without outliers, averaged data and XRD database. <strong>Predictions of Machine Learning Models from experimental datasets</strong> Machine Learning models are trained to predict properties from compositions: Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN) models. Model assessment (i.e. choosing best hyper-parameters for each model) was performed on Compo_E_wo_outliers for E prediction, Compo_H_wo_outliers for H prediction, and on Averaged_data and Database_XRD for phase prediction. Results of model trainings are given in ModelAssessment.tar.gz. The best model of RF, NN and SVM are trained on all datasets: results are given in Train_model_xx.tar.gz. Training the same model with datasets with more or less outliers for E and H predictions allows to see the effect of outliers on the results. The best models of RF and NN are then trained adding iteratively the binaries: results are in tarball Train_model_xx_adding_binaries.tar.gz <strong><em>These tarball are to be used with PyTerK modules available here. </em></strong> The models then predict, for all atomic compositions of Nb-Ti-Zr-Cr-Mo, with 2%at steps, the associated properties: predictions_XX contain atomic compositions associated to predicted CI, IQ, EBSD phase class, XRD phase class, E, H, for each kind of model. Predictions_XX_mechanical_model contain the same data with other mechanical properties computed with Galanov model from E and H predictions: relative characteristic size of the elastic-plastic zone under the indenter \(x = \frac{b_s}{c}\), the constrain factor \(C\) – linking yield strength and hardness – and the ductility characteristic \(\delta_H\) – ratio of plastic deformation and total deformation. It also contains \(\frac{E²}{H}\). The prediction_initial.zip contains the predictions made for all the model families with initial datasets. The predictions_adding_binaries.zip the predictions made with the best model (determined with the initial dataset) trained with the initial dataset+ binaries",mds,True,findable,0,0,0,0,0,2023-07-02T19:43:27.000Z,2023-07-02T19:43:27.000Z,cern.zenodo,cern,"High Entropy Alloys,Combinatorial,Mixture Design,Multinary,Machine Learning","[{'subject': 'High Entropy Alloys'}, {'subject': 'Combinatorial'}, {'subject': 'Mixture Design'}, {'subject': 'Multinary'}, {'subject': 'Machine Learning'}]",,
+10.5281/zenodo.3625778,Database rockfills,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Data compilation from large drained compression triaxial tests on coarse crushable rockfill materials. With the aim of enlarging and consolidating the database on the mechanical behavior of coarse rockfills, this file compiles 158 drained triaxial compression tests conducted on 33 different materials, performed on samples of about 1000 mm in diameter and with maximum particle size between 100 and 200 mm.",mds,True,findable,0,0,0,0,0,2020-01-23T13:16:04.000Z,2020-01-23T13:16:04.000Z,cern.zenodo,cern,"rockfill, large triaxial tests, particle crushing, shear strength, secant stiffness","[{'subject': 'rockfill, large triaxial tests, particle crushing, shear strength, secant stiffness'}]",,
+10.5281/zenodo.7993122,"Nano bubbles: how, when and why does science fail to correct itself?",Zenodo,2023,en,Other,"Creative Commons Attribution 4.0 International,Open Access","<em>The document is the part B2a (State-of-the-art and objectives) and B2b (Methodology</em>) <em>of the NanoBubbles ERC Synergy grant application submitted 05/11/2019 for the ERC-2020-SyG call. It was funded and started on 01/06/2021. The abstract of the submitted proposal is copied below.</em> Science relies on the correction of errors to advance, yet in practice scientists find it difficult to erase erroneous and exaggerated claims from the scientific record. Recent discussion of a “replication crisis†has impaired trust in science both among scientists and non-scientists; yet we know little about how non-replicated or even fraudulent claims can be removed from the scientific record. This project combines approaches from the natural, engineering, and social sciences and the humanities (Science and Technology Studies) to understand how error correction in science works and what obstacles it faces, and stages events for scientists to reflect on error and overpromising.<br> The project’s focus is nanobiology, a highly interdisciplinary field founded around the year 2000 that has already seen multiple episodes of overpromising and promotion of erroneous claims. We examine three such “bubblesâ€: the claim that nanoparticles can cross the blood-brain barrier; that nanoparticles can penetrate the cell membrane; and the promotion of the “protein corona†concept to describe ordinary adsorption of proteins on nanoparticles. Findings based on error (non)correction in nanobiology should be generalizable to other new, highly interdisciplinary fields such as synthetic biology and artificial intelligence.<br> We trace claims and corrections in various channels of scientific communication (journals, social media, advertisements, conference programs, etc.) via innovative digital methods. We examine error (non)correction practices in scientific conferences via ethnographic participant-observation. We follow the history of conferences, journals, and other sites of error (non)correction from the 1970s (before nanobio per se existed) to the present. And we attempt to replicate nanobiological claims and, in case of non-replication, document obstacles to correcting those claims. Finally, we will spark a dialogue within the nanobiology community by organizing workshops and events at conferences for practitioners. Through the study and practice of nanobiology, we will analyse how, when and why science fails to correct itself, and explore ways to improve the reliability and efficiency of the scientific process.",mds,True,findable,0,0,0,0,0,2023-06-02T11:21:01.000Z,2023-06-02T11:24:51.000Z,cern.zenodo,cern,"Grant application,ERC Synergy,Machine learning,Science and technology studies,History of science, medicine and technologies,Nanobiotechnology,Statistical data processing,Digital social research","[{'subject': 'Grant application'}, {'subject': 'ERC Synergy'}, {'subject': 'Machine learning'}, {'subject': 'Science and technology studies'}, {'subject': 'History of science, medicine and technologies'}, {'subject': 'Nanobiotechnology'}, {'subject': 'Statistical data processing'}, {'subject': 'Digital social research'}]",,
+10.5281/zenodo.7795898,Calibration methodology of low-costs sensors for high-quality monitoring of fine particulate matter,Zenodo,2023,,Software,"Creative Commons Attribution 4.0 International,Embargoed Access","This repository contains the code used to extract dusts as mentioned in the manuscript “Calibration methodology of low-costs sensors for high-quality monitoring of fine particulate matterâ€. Important preliminary steps : 1. If you don't have a CDS account, register here : https://cds.climate.copernicus.eu/user/register?destination=%2F%23!%2Fhome<br> 2. follow all instructions here : https://cds.climate.copernicus.eu/api-how-to<br> (as explained, you should install cdsapi and the CDS API key) Documentation for the dataset here: https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-europe-air-quality-forecasts?tab=overview In case of issue downloading data, it is recommended to make a larger number of requests with smaller date ranges. Credits : Météo-France, Institut National de l'Environnement Industriel et des Risques (Ineris), Aarhus University, Norwegian Meteorological Institute (MET Norway), Jülich Institut für Energie- und Klimaforschung (IEK), Institute of Environmental Protection – National Research Institute (IEP-NRI), Koninklijk Nederlands Meteorologisch Instituut (KNMI), Nederlandse Organisatie voor toegepast-natuurwetenschappelijk onderzoek (TNO), Swedish Meteorological and Hydrological Institute (SMHI), Finnish Meteorological Institute (FMI), 2020. CAMS European air quality forecasts, ENSEMBLE data. Copernicus Atmosphere Monitoring Service (CAMS) Atmosphere Data Store (ADS). https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-europe-air-quality-forecasts?tab=overview (accessed 2023.04.03).",mds,True,findable,0,0,0,0,0,2023-04-04T07:42:59.000Z,2023-04-04T07:43:30.000Z,cern.zenodo,cern,"PM1,PM2.5,PM10,sensors calibration,dusts,machine learning","[{'subject': 'PM1'}, {'subject': 'PM2.5'}, {'subject': 'PM10'}, {'subject': 'sensors calibration'}, {'subject': 'dusts'}, {'subject': 'machine learning'}]",,
+10.57745/5o6qih,The EVE Pilot: Usage Data from an Electric Car in France,Recherche Data Gouv,2023,,Dataset,,"This dataset contains the usage data of a single electric car collected in as part of the EVE study (Enquête des Vehicles Electrique) run by the Observatoire du Transition Energétique Grenoble (OTE-UGA). This dataset includes the following variables for a single Renault ZOE 2014 Q90: - Speed, distance covered, and other drivetrain data variables; - State of charge, State of health and other battery characteristics; as well as - external temperature variables. The Renault ZOE 2014 Q90 has a battery capacity of 22 KWh and a maximum speed of 135 KM/h. More information about on the specifications can be found here The electric car is used for personal use exclusively including occasional transit to work but mostly for personal errands and trips. The dataset was collected using a CanZE app and a generic car lighter dongle. The dataset spans two years from October 2020 to August 2022. A simple Python notebook that visualises the datasets can be found here. More complex usecases for the datasets can be found in the following links: - Comparison of the carbon footprint of driving across countries: link - Feedback indicators of electric car charging behaviours: link There is also more information on the collection process and other potential uses in the data paper here. Please don't hesitate to contact the authors if you have any further questions about the dataset.",mds,True,findable,33,0,0,0,0,2023-08-31T07:08:06.000Z,2023-10-13T07:32:19.000Z,rdg.prod,rdg,,,,
+10.15778/resif.fr,"RESIF-RLBP French Broad-band network, RESIF-RAP strong motion network and other seismic stations in metropolitan France",RESIF - Réseau Sismologique et géodésique Français,1995,en,Dataset,"Open Access,Creative Commons Attribution 4.0 International","The FR network code embraces most of the permanent seismic stations installed in metropolitan France and operated by academic research institutes and observatories. In 2014, it includes 1) about fifty broadband stations of the RLBP (Réseau Large Bande Permanent) network, 2) about fourty short period stations of the historical RéNaSS (Réseau National de Surveillance Sismique) network, 3) six broadband stations installaed at the LSBB -low noise underground multidisciplinary laboratory-, 4) some broadband stations on landslides managed by OMIV (Observatoire Multidiciplinaire des Instabilités de Versants) and 5) the ANTARES seafloor broadband station in the Ligurian sea. Some of these broadband stations also host a strong motion sensor of the RAP French strong motion network. Broadband stations of the RLBP are part of the national RESIF (Réseau Sismologique et géodésique Français) Research Infrastructure. Within this framework, this network is planned to evolve toward a denser and more homogeneous network of ~150 broadband stations by 2018. Each broadband station is equipped with a wide band seismic sensor, usually having a flat response at periods lower than 120s, and a high dynamic acquisition system. Data are collected in near real-time via DSL, satellite or cellar links. Emphasis is put on the continuity of the records and the noise level at the sites to provide high-quality data to the end users. The RESIF Information System manages the data from the broadband stations and collocated accelerometers and freely provides both real time and consolidated data. Quality control of waveforms and metadata updating are performed by EOST (Strasbourg) and OCA (Nice) for the RLBP, RéNaSS, LSSB and ANTARES stations and by OSUG (Grenoble) for the OMIV and RAP stations. Archiving and distribution of every data are carried out by the RESIF datacentre hosted by the University of Grenoble Alpes. Data from short period stations are expected to integrate the system in 2015. All together, these data are used for a wide variety of fundamental and applied studies including seismic imaging of the deep earth, monitoring of the seismic activity in metropolitan France and adjacent regions, source studies of local, regional and teleseismic earthquakes or monitoring of seismic signals related to subsurface processes.",mds,True,findable,0,0,0,25,0,2014-12-05T15:20:35.000Z,2014-12-05T15:20:35.000Z,inist.resif,vcob,"Broad Band,Short Period,Strong motion,France","[{'subject': 'Broad Band'}, {'subject': 'Short Period'}, {'subject': 'Strong motion'}, {'subject': 'France'}]",['Approximately 155 active stations; greater than 7.5 GB/day.'],"['Miniseed data', 'stationXML metadata']"
+10.5281/zenodo.4761291,"Figs. 4-5 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 4-5. Dictyogenus jurassicum sp. n., adult male. 4. Hemitergal lobe, lateral view. Karstic spring at Charabotte Mill, Ain dpt, France. Photo B. Launay. 5. Epiproct and lateral stylet, lateral view. Karstic spring at Charabotte Mill, Ain dpt, France. Photo B. Launay.",mds,True,findable,0,0,4,0,0,2021-05-14T07:43:23.000Z,2021-05-14T07:43:24.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Perlodidae,Dictyogenus","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Perlodidae'}, {'subject': 'Dictyogenus'}]",,
+10.5281/zenodo.10069276,The Effect of Typing Efficiency and Suggestion Accuracy on Usage of Word Suggestions and Entry Speed,Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Data collected during our experiments investigating the effect of suggestion accuracy and typing efficiency on usage of word suggestions, and entry speed",api,True,findable,0,0,0,0,0,2023-11-03T12:54:50.000Z,2023-11-03T12:54:50.000Z,cern.zenodo,cern,"writing,word suggestions","[{'subject': 'writing'}, {'subject': 'word suggestions'}]",,
+10.5281/zenodo.1475271,SPARK_Artefice_session_05072017_Grenoble,Zenodo,2018,en,Audiovisual,"Creative Commons Attribution Non Commercial 4.0 International,Open Access","Recording of a collaborative design session between designers and clients.
+
+A design company receives its clients to discuss/contribute/co-design together. They develop new graphical layout options for the packaging of a tomato sauce product using an ICT application based on Spatial Augmented Reality, which allows for a real-time modification. Language: English.",mds,True,findable,0,0,0,0,0,2018-10-31T09:52:51.000Z,2018-10-31T09:52:52.000Z,cern.zenodo,cern,"SPARK,H2020,Collaborative design,Co-design,Spatial Augmented Reality,Augmented Reality,Mixed prototype,Creativity,ICT","[{'subject': 'SPARK'}, {'subject': 'H2020'}, {'subject': 'Collaborative design'}, {'subject': 'Co-design'}, {'subject': 'Spatial Augmented Reality'}, {'subject': 'Augmented Reality'}, {'subject': 'Mixed prototype'}, {'subject': 'Creativity'}, {'subject': 'ICT'}]",,
+10.5061/dryad.brv15dvcj,The generality of cryptic dietary niche differences in diverse large-herbivore assemblages,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Ecological niche differences are necessary for stable species coexistence but are often difficult to discern. Models of dietary niche differentiation in large mammalian herbivores invoke the quality, quantity, and spatiotemporal distribution of plant tissues and growth-forms but are agnostic towards food-plant species identity. Empirical support for these models is variable, suggesting that additional mechanisms of resource partitioning may be important in sustaining large-herbivore diversity in African savannas. We used DNA metabarcoding to conduct a taxonomically explicit analysis of large-herbivore diets across southeastern Africa, analyzing ~4,000 fecal samples of 30 species from 10 sites in 7 countries over 6 years. We detected 893 food-plant taxa from 124 families, but just two families—grasses and legumes—accounted for the majority of herbivore diets. Nonetheless, herbivore species almost invariably partitioned food-plant taxa; diet composition differed significantly in 97% of pairwise comparisons between sympatric species, and dissimilarity was pronounced even between the strictest grazers (grass eaters), strictest browsers (non-grass eaters), and closest relatives at each site. Niche differentiation was weakest in an ecosystem recovering from catastrophic defaunation, indicating that food-plant partitioning is driven by species interactions, and stronger at low rainfall, as expected if interspecific competition is a predominant driver. Diets differed more between browsers than grazers, which predictably shaped community organization: grazer-dominated trophic networks had higher nestedness and lower modularity. That dietary differentiation is structured along taxonomic lines complements prior work on how herbivores partition plant parts and patches and suggests that common mechanisms govern herbivore coexistence and community assembly in savannas.",mds,True,findable,242,43,0,1,0,2022-08-08T16:58:42.000Z,2022-08-08T16:58:43.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences,African savannas,large herbivores,food webs,Resource partitioning,dietary niche,niche partitioning,species coextistence,optimal foraging,niche differences,niche differentiation,DNA metabarcoding,DNA barcoding,fecal samples,ecological networks,ecological network analysis,African ungulates,African elephant (Loxodonta africana),dik-dik (Madoqua guentheri),klipspringer (Oreotragus oreotragus),common duiker (Sylvicapra grimmia),oribi (Ourebia ourebi),Thomson's gazelle (Eudorcas thomsonii),Cape bushbuck (Tragelaphus sylvaticus),impala (Aepyceros melampus),Grant's gazelle (Nanger grant),southern reedbuck (Redunca aurundinum),puku (Kobus vardonii),warthog (Phacochoerus africanus),nyala (Tragelaphus angasii),topi (Damaliscus lunatus),bushpig (Potamochoerus larvatus),Hartebeest (Alcelaphus buselaphus),blue wildebeest (Connochaetes taurinus),East African oryx (Oryx beisa),waterbuck (Kobus ellipsiprymnus),greater kudu (Tragelaphus strepsiceros),sable antelope (Hippotragus niger),roan antelope (Hippotragus equinus),plains zebra (Equus quagga),Grevy's zebra (Equus grevyi),common eland (Tragelaphus oryx),Cape buffalo (Syncerus caffer),giraffe (Giraffa camelopardalis),black rhinoceros (Diceros bicornis),hippopotamus (Hippopotamus amphibius),white rhinoceros (Ceratotherium simum),Mpala Research Center,Laikipia,Kenya,Serengeti-Mara Ecosystem,Serengeti National Park,Nyika National Park,Tanzania,Malawi,Niassa National Reserve,Mozambique,Hwange National Park,Zimbabwe,Kafue National Park,Zambia,Gorongosa National Park,Kruger National Park,South Africa,Addo Elephant National Park,Modern coexistence theory,Species interactions,competition,diet selection,grasses (Poaceae),legumes (Fabaceae),grazing mammals,browsing mammals,mixed feeders,environmental DNA sequencing (eDNA sequencing),taxonomic dietary diversity,dietary plasticity,Food-web structure,network rewiring,nestedness and modularity,functional redundancy,functional complementarity,rangelands","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'African savannas'}, {'subject': 'large herbivores'}, {'subject': 'food webs'}, {'subject': 'Resource partitioning'}, {'subject': 'dietary niche'}, {'subject': 'niche partitioning'}, {'subject': 'species coextistence'}, {'subject': 'optimal foraging'}, {'subject': 'niche differences'}, {'subject': 'niche differentiation'}, {'subject': 'DNA metabarcoding'}, {'subject': 'DNA barcoding', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'fecal samples'}, {'subject': 'ecological networks'}, {'subject': 'ecological network analysis'}, {'subject': 'African ungulates'}, {'subject': 'African elephant (Loxodonta africana)'}, {'subject': 'dik-dik (Madoqua guentheri)'}, {'subject': 'klipspringer (Oreotragus oreotragus)'}, {'subject': 'common duiker (Sylvicapra grimmia)'}, {'subject': 'oribi (Ourebia ourebi)'}, {'subject': ""Thomson's gazelle (Eudorcas thomsonii)""}, {'subject': 'Cape bushbuck (Tragelaphus sylvaticus)'}, {'subject': 'impala (Aepyceros melampus)'}, {'subject': ""Grant's gazelle (Nanger grant)""}, {'subject': 'southern reedbuck (Redunca aurundinum)'}, {'subject': 'puku (Kobus vardonii)'}, {'subject': 'warthog (Phacochoerus africanus)'}, {'subject': 'nyala (Tragelaphus angasii)'}, {'subject': 'topi (Damaliscus lunatus)'}, {'subject': 'bushpig (Potamochoerus larvatus)'}, {'subject': 'Hartebeest (Alcelaphus buselaphus)'}, {'subject': 'blue wildebeest (Connochaetes taurinus)'}, {'subject': 'East African oryx (Oryx beisa)'}, {'subject': 'waterbuck (Kobus ellipsiprymnus)'}, {'subject': 'greater kudu (Tragelaphus strepsiceros)'}, {'subject': 'sable antelope (Hippotragus niger)'}, {'subject': 'roan antelope (Hippotragus equinus)'}, {'subject': 'plains zebra (Equus quagga)'}, {'subject': ""Grevy's zebra (Equus grevyi)""}, {'subject': 'common eland (Tragelaphus oryx)'}, {'subject': 'Cape buffalo (Syncerus caffer)'}, {'subject': 'giraffe (Giraffa camelopardalis)'}, {'subject': 'black rhinoceros (Diceros bicornis)'}, {'subject': 'hippopotamus (Hippopotamus amphibius)'}, {'subject': 'white rhinoceros (Ceratotherium simum)'}, {'subject': 'Mpala Research Center'}, {'subject': 'Laikipia'}, {'subject': 'Kenya', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Serengeti-Mara Ecosystem'}, {'subject': 'Serengeti National Park'}, {'subject': 'Nyika National Park'}, {'subject': 'Tanzania', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Malawi', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Niassa National Reserve'}, {'subject': 'Mozambique', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Hwange National Park'}, {'subject': 'Zimbabwe', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Kafue National Park'}, {'subject': 'Zambia', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Gorongosa National Park'}, {'subject': 'Kruger National Park'}, {'subject': 'South Africa', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Addo Elephant National Park'}, {'subject': 'Modern coexistence theory'}, {'subject': 'Species interactions', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'competition'}, {'subject': 'diet selection'}, {'subject': 'grasses (Poaceae)'}, {'subject': 'legumes (Fabaceae)'}, {'subject': 'grazing mammals'}, {'subject': 'browsing mammals'}, {'subject': 'mixed feeders'}, {'subject': 'environmental DNA sequencing (eDNA sequencing)'}, {'subject': 'taxonomic dietary diversity'}, {'subject': 'dietary plasticity'}, {'subject': 'Food-web structure'}, {'subject': 'network rewiring'}, {'subject': 'nestedness and modularity'}, {'subject': 'functional redundancy'}, {'subject': 'functional complementarity'}, {'subject': 'rangelands'}]",['465555599 bytes'],
+10.5281/zenodo.7755650,"Catalog of icequakes recorded in March 2019, in the Van Mijen Fjord, in Svalbard (Norway)",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","The files contain a catalog of icequakes waveforms recorded in March 2019, at Vallunden lake, in the Van Mijen Fjord, in Svalbard (Norway). The three components of velocity are available.",mds,True,findable,0,0,0,0,0,2023-03-21T09:43:11.000Z,2023-03-21T09:43:11.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.4761355,"Figs. 88-91. Dictyogenus fontium species complex, egg characteristics. 88 in Two New Species Of Dictyogenus Klapálek, 1904 (Plecoptera: Perlodidae) From The Jura Mountains Of France And Switzerland, And From The French Vercors And Chartreuse Massifs",Zenodo,2019,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 88-91. Dictyogenus fontium species complex, egg characteristics. 88. Egg, upper view from one ridge with two faces and the anchor visible. Gougra, Val de Moiry, inner-Alpine upper Rhône Valley, canton of Valais, Switzerland. 89. Egg, upper view from one ridge with two faces and the anchor visible. Campello",mds,True,findable,0,0,0,0,0,2021-05-14T07:52:31.000Z,2021-05-14T07:52:32.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.57745/lpj2s2,GNSS position solutions in Japan,Recherche Data Gouv,2022,,Dataset,,"This dataset includes solutions processed by ISTerre for all Japanese GNSS stations. These products are daily position time series (North, East and Vertical), in the ITRF14 reference frame, calculated from RINEX files using the double difference method with GAMIT software.",mds,True,findable,192,10,0,0,0,2022-06-23T09:59:39.000Z,2022-07-06T12:38:55.000Z,rdg.prod,rdg,,,,
+10.5281/zenodo.4305970,DEM simulations of bi-disperse beds during bedload transport,Zenodo,2020,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This depository contains the data of all DEM simulations used in the publication Chassagne, R., Frey, P., Maurin, R., and Chauchat, J. Mobility of bidisperse mixtures during bedload transport. Physical Review Fluids, 5(11):114307. doi:10.1103/PhysRevFluids.5.114307, as well as post processing scripts to use the data. The simulations are located in seven folders, Monodisperse/ (mondisperse simulations where the fluid forcing is varied), N0.5/ (simulations with 0.5 layer of large particles above a small particle bed and or different fluid forcing), N1/ (simulations with 1 layer of large particles above a small particle bed and or different fluid forcing), N2/, N3/, N4/ and sizeRatio (2 layers of large particles, fixed fluid forcing but the diameter of the underlying small particles is varied). The data of each simulations are contained in separate subfolders named after the simulation. For example, H8Sh0.45/ corresponds to a monodisperse simulation with a bedheight of 8dl (dl is the large particle diameter) and a shields number of 0.45. H10N2R2Sh0.7/ corresponds to a bidisperse simulation with a bed height of 10dl, 2 layers of large particles, a size ratio of 2 between large and small particles and a shields number of 0.7. For each simulation, the time data are saved in data.hdf5 and averaged data in average.hdf5. A GeomParam.txt file is also in each folder. It contains information of the simulation that the post processing programm will read. The python script used to initiate the YADE-DEM simulation is also given for information (it contains all parameters of the simulation). The post-processing programm has been coded in python2.7 with an oriented-object procedure. The h5py package is necessary to read the .hdf5 files. The scripts do not work in python3, but can be very easily adapted if necessary (you only have to modify the ""print"" functions). The scripts are available in ScriptsPP/ and are organized as follow. For bidisperse simualtions, a mother class in SegregationPP and two child classes SegFull (to load the full time data set) and SegMean (to load only average data). For monodisperse simualtions, a mother class in MonodispersePP and two child classes MonoFull (to load the full time data set) and MonoMean (to load only average data). Two scripts examplePP1.py and examplePP2.py are proposed and show how to manipulate theses classes and the data.",mds,True,findable,0,0,1,0,0,2020-12-04T14:23:08.000Z,2020-12-04T14:23:09.000Z,cern.zenodo,cern,"Granular flow,Sediment transport,Bi-disperse mobility,Coupled fluid-DEM simulations","[{'subject': 'Granular flow'}, {'subject': 'Sediment transport'}, {'subject': 'Bi-disperse mobility'}, {'subject': 'Coupled fluid-DEM simulations'}]",,
+10.5281/zenodo.7790110,Oxygen-induced chromophore degradation in the photoswitchable red fluorescent protein rsCherry,Zenodo,2023,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Source data for figure 1, figure 3a, and supplementary figure 1.",mds,True,findable,0,0,0,0,0,2023-03-31T21:37:12.000Z,2023-03-31T21:37:12.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7015277,"Supplemental information data from: ""Evidence for amorphous sulfates as the main carrier of soil hydration in Gale crater, Mars""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This dataset includes the target name and chemical composition of each ChemCam sequence used in the above-mentioned article. The quantification for each ChemCam spectrum in the soils of the Bradbury, Rocknest and Yellowknife Bay area are in percentage mass fractions (wt.%) for most major oxides (i.e., SiO2, TiO2, Al2O3, FeOT , MgO, CaO, Na2O, K2O). Sulfur and hydrogen abundances are expressed respectively in peak area (normalized) and ICA H scores.",mds,True,findable,0,0,0,0,0,2022-08-22T16:01:22.000Z,2022-08-22T16:01:22.000Z,cern.zenodo,cern,"Mars,ChemCam,Laser-Induced Breakdown Spectroscopy,Soils","[{'subject': 'Mars'}, {'subject': 'ChemCam'}, {'subject': 'Laser-Induced Breakdown Spectroscopy'}, {'subject': 'Soils'}]",,
+10.5281/zenodo.6380887,"Data from: Protein Conformational Space at the Edge of Allostery: Turning a Non-allosteric Malate Dehydrogenase into an ""Allosterized"" Enzyme using Evolution Guided Punctual Mutations",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This data accompanies the paper entitled <em>Protein Conformational Space at the Edge of Allostery: Turning a Non-allosteric Malate Dehydrogenase into an “Allosterized†Enzyme using Evolution Guided Punctual Mutations</em> The zip archive contains the results of molecular dynamics simulations of the 4 systems investigated in the paper: wt of A. ful MalDH and three mutants. Each system has been simulated at two temperatures, 300 K and 340 K. Starting configurations of the proteins after equilibration are provided for all the systems in GRO Gromos87 format. Trajectories with the positions of the proteins every 100 ps are provided for all the systems in XTC gromacs format.",mds,True,findable,0,0,0,0,0,2022-03-24T10:53:28.000Z,2022-03-24T10:53:28.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7180985,Code and data presented in ICAART 2023,Zenodo,2022,en,Software,"Creative Commons Attribution 4.0 International,Open Access",The code used to obtain the graph presented in the paper.<br> Additional data such as the trust fluctuation of all the agents and the data in CSV format. Read the REAMDE.md for more information.,mds,True,findable,0,0,0,0,0,2022-10-10T11:09:19.000Z,2022-10-10T11:09:19.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.8225005,Introduction: Extending the reach of English pronunciation issues and practices,Zenodo,2023,en,Other,"Creative Commons Attribution 4.0 International,Open Access","This chapter is the Introduction to the Proceedings of the 7th International Conference English Pronunciation: Issues and Practices (EPIP 7) held May 18–20, 2022 at Université Grenoble-Alpes, France.",mds,True,findable,0,0,0,0,0,2023-08-08T13:50:08.000Z,2023-08-08T13:50:08.000Z,cern.zenodo,cern,English pronunciation,[{'subject': 'English pronunciation'}],,
+10.5281/zenodo.3048780,2_Changri Nup Data,Zenodo,2019,en,Dataset,Restricted Access,"This is the dataset from North Changri Nup (5470 m asl, Everest region) on a debris-covered site in 2015 to 2017. Please look at the metadata file (CN-5470_20152017_AWS_metadata.docx) and the data ""Readme"" file (https://zenodo.org/record/3362374) for more information about the content of the files.",mds,True,findable,4,0,0,0,0,2019-05-20T11:58:06.000Z,2019-05-20T11:58:07.000Z,cern.zenodo,cern,"Changri Nup,Glacier,Debris","[{'subject': 'Changri Nup'}, {'subject': 'Glacier'}, {'subject': 'Debris'}]",,
+10.5281/zenodo.10020967,robertxa/pyVertProf: BIC Release,Zenodo,2023,,Software,Creative Commons Attribution 4.0 International,New release with BIC analysis,api,True,findable,0,0,0,0,0,2023-10-19T08:42:31.000Z,2023-10-19T08:42:31.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.6505500,ThoFeOne: Python 1D tools for the Thomas-Fermi self-consistent problem,Zenodo,2022,,Software,"BSD 2-Clause FreeBSD License,Open Access",First working version of the simulator. Contains fixed (constant) mesh. See github website for latest version and documentation.,mds,True,findable,0,0,1,0,0,2022-04-29T15:50:07.000Z,2022-04-29T15:50:07.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.20031,Crystallization And X-Ray Diffraction Studies Of A Complete Bacterial Fatty-Acid Synthase Type I,Zenodo,2015,,Dataset,"Creative Commons Attribution Share-Alike 4.0,Open Access","These are X-ray diffraction data from the publication<br>
+Enderle, M.E, McCarthy, A, Paithankar, K. S, and Grininger, M
+
+Crystallization and X-ray diffraction studies of a complete bacterial fatty-acid synthase type I.
+
+Acta Crystallogr F Struct Biol Commun. 2015 Nov;71(Pt 11):1401-7
+
+CC-BY-SA license
+
+MD5SUMS
+
+a774aabcd316b5b200ef5c08b109ba9a crystal-form-II_part-1.tar.lzma
+
+3596da75621648cc0ac5ee84b26deab0 crystal-form-II_part-2.tar.lzma
+
+8a5410ce3178c814d7a127491e68ca0a crystal-form-I_part-1.tar.lzma
+
+259614e1b2cfe089141fb7baa846af7e crystal-form-I_part-2.tar.lzma",,True,findable,0,0,0,0,0,2015-07-13T08:26:55.000Z,2015-07-13T08:26:56.000Z,cern.zenodo,cern,macromolecular crystallography,[{'subject': 'macromolecular crystallography'}],,
+10.5061/dryad.6c886,Data from: Present conditions may mediate the legacy effect of past land-use changes on species richness and composition of above- and below-ground assemblages,Dryad,2018,en,Dataset,Creative Commons Zero v1.0 Universal,"1. In forest ecosystems, the influence of landscape history on contemporary biodiversity patterns has been shown to provide a convenient framework to explain shifts in plant assemblages. However, very few studies have controlled for present human-induced activities when analyzing the effect of forest continuity on community structures. By cutting and removing trees, foresters substantially change stand ecological conditions, with consequences on biodiversity patterns. Disentangling the effect of past and present human activities on biodiversity is thus crucial for ecosystem management and conservation. 2. We explored the response of plant and springtail species richness and composition to forest continuity (ancient vs recent) in montane forests, while controlling for stand maturity (mature vs overmature). We established 70 sites in landscapes dominated by unfragmented ancient forests where we surveyed plants and assessed springtails by analyzing environmental DNA. 3. Neither plant nor springtail species richness was influenced by forest continuity or by stand maturity. Instead, site-specific characteristics, especially soil properties and canopy openness, were of major importance in shaping above- and below-ground richness. 4. For plant and springtail species composition, the effect of forest continuity was mediated by stand maturity. Thus, both plants and springtails showed a convergence in assemblage patterns with the increasing availability of overmature stand attributes. Moreover, soil and stand-scale factors were evidently more important than landscape-scale factors in shaping above- and below-ground species composition. 5. Synthesis. We clearly demonstrated that biodiversity patterns are more strongly influenced by present human-induced activities than by past human-induced activities. In the Northern Alps where our study sites were located, the colonization credit of most species has been paid off and the transient biodiversity deficit usually related to forest continuity has moved toward equilibrium. These findings emphasize the necessity to better control for local-scale factors when analyzing the response of biodiversity to forest continuity; we call for more research into the effects of forest continuity in unfragmented mountain forests.",mds,True,findable,294,29,1,1,0,2017-04-25T13:35:49.000Z,2017-04-25T13:35:51.000Z,dryad.dryad,dryad,"ancient forest,secondary succession,Community dynamics,habitat quality,mountain forest,Plant–soil interactions","[{'subject': 'ancient forest'}, {'subject': 'secondary succession'}, {'subject': 'Community dynamics'}, {'subject': 'habitat quality'}, {'subject': 'mountain forest'}, {'subject': 'Plant–soil interactions'}]",['59412 bytes'],
+10.5061/dryad.jwstqjqbr,Data from: Above- and belowground drivers of intraspecific trait variability across subcontinental gradients for five ubiquitous forest plants in North America,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Intraspecific trait variability (ITV) provides the material for species adaptation to environmental changes. To advance our understanding of how ITV can contribute to species adaptation to a wide range of environmental conditions, we studied five widespread understory forest species exposed to both continental-scale climate gradients, and local soil and disturbance gradients. We investigated the environmental drivers of between-site leaf and root trait variation, and tested whether higher between-site ITV was associated with increased trait sensitivity to environmental variation (i.e. environmental fit). We measured morphological (specific leaf area: SLA, specific root length: SRL) and chemical traits (Leaf and Root N, P, K, Mg, Ca) of five forest understory vascular plant species at 78 sites across Canada. A total of 261 species-by-site combinations spanning ~4300 km were sampled, capturing important abiotic and biotic environmental gradients (neighbourhood composition, canopy structure, soil conditions, climate). We used multivariate and univariate linear mixed models to identify drivers of ITV and test the association of between-site ITV with environmental fit. Between-site ITV of leaf traits was primarily driven by canopy structure and climate. Comparatively, environmental drivers explained only a small proportion of variability in root traits: these relationships were trait-specific and included soil conditions (Root P), canopy structure (Root N) and neighbourhood composition (SRL, Root K). Between-site ITV was associated with increased environmental fit only for a minority of traits, primarily in response to climate (SLA, Leaf N, SRL). Synthesis. By studying how ITV is structured along environmental gradients among species adapted to a wide range of conditions, we can begin to understand how individual species might respond to environmental change. Our results show that generalizable trait-environment relationships occur primarily aboveground and only accounted for a small proportion of variability. For our group of species with broad ecological niches, variability in traits was only rarely associated with higher environmental fit, and primarily along climatic gradients. These results point to promising research avenues on the various ways in which trait variation can affect species performance along different environmental gradients.",mds,True,findable,122,9,0,1,0,2022-04-18T18:16:17.000Z,2022-04-18T18:16:18.000Z,dryad.dryad,dryad,"environmental matching,Plant nutrient concentration,specific leaf area (SLA),specific root length (SRL),functional ecology,edaphic conditions,canopy structure,biotic interaction,Understory plants,Aralia nudicaulis,Cornus canadensis,Maianthemum canadense,Trientalis borealis,Vaccinium angustifolium,FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'environmental matching'}, {'subject': 'Plant nutrient concentration'}, {'subject': 'specific leaf area (SLA)'}, {'subject': 'specific root length (SRL)'}, {'subject': 'functional ecology'}, {'subject': 'edaphic conditions'}, {'subject': 'canopy structure'}, {'subject': 'biotic interaction'}, {'subject': 'Understory plants'}, {'subject': 'Aralia nudicaulis'}, {'subject': 'Cornus canadensis'}, {'subject': 'Maianthemum canadense'}, {'subject': 'Trientalis borealis'}, {'subject': 'Vaccinium angustifolium'}, {'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['784242 bytes'],
+10.5281/zenodo.5243218,Lithuanian DBnary archive in original Lemon format,Zenodo,2021,lt,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Lithuanian language edition, ranging from 6th April 2015 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br>",mds,True,findable,0,0,0,0,0,2021-08-24T10:44:17.000Z,2021-08-24T10:44:18.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.7969434,Sample Tomography Image,Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",Sample Tomography Image,mds,True,findable,0,0,0,0,0,2023-05-25T08:05:35.000Z,2023-05-25T08:05:36.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.10211920,"Dataset for ""Reduced ice loss from Greenland under stratospheric aerosol injection""",Zenodo,2023,en,Dataset,Creative Commons Attribution 4.0 International,"Dataset for the paper ""Reduced ice loss from Greenland under stratospheric aerosol injection""(Journal of Geophysical Research: Earth Surface, 128 (11), e2023JF007112, doi: 10.1029/2023JF007112).
+Please see the README for details.
+V1.1.1: README and metadata updated.V1.1: Scripts related to the ISIMIP-method downscaling, SEMIC code, as well as configuration and input files for SICOPOLIS and Elmer/Ice added.V1: Results of new simulations that include both atmospheric and oceanic forcing.V0.9.1: Crucial bug fix in the files ElmerIce_MIROC-ESM-CHEM-{RCP85,RCP45,G4}_2D_final.nc (those in V0.9 were faulty).V0.9: Scalar variables: now distinguished between state and flux variables. 2D variables added.V0.5: Scalar variables as functions of time.
+* * * * * * *
+The following script may be used to download the entire content of the archive on a Unix/Linux system:
+#!/bin/bash# --- download_all.sh ---repodir=""https://zenodo.org/record/10211920/files""files=(""_README.pdf"" \      ""Output_SICOPOLIS_Scalar.zip"" ""Output_ElmerIce_Scalar.zip"" \      ""Output_SICOPOLIS_2D.zip"" ""Output_ElmerIce_2D.zip"" \      ""Repo_ISIMIP_downscale.zip"" ""Repo_SEMIC.zip"" \      ""Repo_SICOPOLIS.zip"" ""Repo_ElmerIce.zip"")for file in ${files[@]}; do   wget ""${repodir}/${file}""doneecho ""--- Done! ---""
+Â ",api,True,findable,0,0,1,1,0,2023-11-28T03:30:42.000Z,2023-11-28T03:30:43.000Z,cern.zenodo,cern,"Greenland,Ice sheet,Modelling,Ice-sheet modelling,Arctic glaciology,Climate change,Ice and climate,Sea-level rise,Geoengineering","[{'subject': 'Greenland'}, {'subject': 'Ice sheet'}, {'subject': 'Modelling'}, {'subject': 'Ice-sheet modelling'}, {'subject': 'Arctic glaciology'}, {'subject': 'Climate change'}, {'subject': 'Ice and climate'}, {'subject': 'Sea-level rise'}, {'subject': 'Geoengineering'}]",,
+10.5281/zenodo.4964201,"FIGURES 1–4. Protonemura auberti, male. 1–2. epiproct, lateral view. 3. male terminalia with epiproct, dorsal view. 4 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 1–4. Protonemura auberti, male. 1–2. epiproct, lateral view. 3. male terminalia with epiproct, dorsal view. 4. male terminalia, dorsal view",mds,True,findable,0,0,7,0,0,2021-06-16T08:24:45.000Z,2021-06-16T08:24:46.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.5281/zenodo.5243199,Japanese DBnary archive in original Lemon format,Zenodo,2021,ja,Dataset,"Creative Commons Attribution Share Alike 4.0 International,Open Access","The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary. This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Japanese language edition, ranging from 11th October 2013 to 1st July 2017. After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br>",mds,True,findable,0,0,0,0,0,2021-08-24T10:26:51.000Z,2021-08-24T10:26:51.000Z,cern.zenodo,cern,"Wiktionary,Lemon,Lexical Data,RDF","[{'subject': 'Wiktionary'}, {'subject': 'Lemon'}, {'subject': 'Lexical Data'}, {'subject': 'RDF'}]",,
+10.5281/zenodo.3872130,Raw diffraction data for [NiFeSe] hydrogenase pressurized with O2 gas - dataset wtO2,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Embargoed Access","Diffraction data measured at ESRF beamline ID29 on October 2, 2017. Image files are uploaded in blocks of gzip-compressed cbf files.",mds,True,findable,0,0,0,0,0,2020-06-01T20:15:39.000Z,2020-06-01T20:15:40.000Z,cern.zenodo,cern,"Hydrogenase,Selenium,gas channels,high-pressure derivatization","[{'subject': 'Hydrogenase'}, {'subject': 'Selenium'}, {'subject': 'gas channels'}, {'subject': 'high-pressure derivatization'}]",,
+10.5281/zenodo.4751241,X-ray diffraction tomography dataset of archaeological ceramic,Zenodo,2021,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","<br> This dataset contains a subset of processed data that was acquired using X-ray diffraction tomography (XRD-CT) at the ID15A beamline at the European Synchrotron (ESRF), Grenoble, France. The imaged object is an archaeological ceramic, whose fragments are kept at the University of Milan. High-energy X-ray diffraction measurements were taken at the ID15A beamline using a monochromatic pencil beam (90 keV energy). Data was collected of 3 horizontal slices, spaced 7 mm apart, and acquisition of each slice took 20 minutes. Acquisition was performed in 273 translation steps over a scan range of 12 mm and in 225 rotational steps over an angular range of 180 degrees. Sinograms were computed from the acquired images using the pyFAI library. A subset of the sinograms was selected, containing 3 horizontal slices with 11 channels each. The provided HDF5 file contains two subdatasets: - omega: 225 elements<br> - rotation angle in degrees<br> - sinograms: 11 x 3 x 225 x 273 elements<br> - 11 channels (corresponding to diffraction angle)<br> - 3 horizontal slices<br> - 225 rotation angles<br> - 273 horizontal pixels",mds,True,findable,0,0,0,1,0,2021-05-14T10:33:00.000Z,2021-05-14T10:33:01.000Z,cern.zenodo,cern,"Synchrotron,X-ray diffraction tomography","[{'subject': 'Synchrotron'}, {'subject': 'X-ray diffraction tomography'}]",,
+10.5281/zenodo.5108951,"Spatial slip rate distribution along the SE Xianshuihe fault, eastern Tibet, and earthquake hazard assessment",Zenodo,2021,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access",<strong><em>Table 2: </em></strong><em><sup>10</sup></em><em>Be surface-exposure ages of Zheduotang (ZDT) and Moxi (MX) sites of the SE Xianshuihe fault.</em>,mds,True,findable,0,0,0,0,0,2021-07-16T02:27:16.000Z,2021-07-16T02:27:17.000Z,cern.zenodo,cern,"Xianshuihe fault,eastern Tibet,cosmogenic dating,tectonic-geomorphology,late Quaternary slip rates,active pull apart basin,earthquake hazard","[{'subject': 'Xianshuihe fault'}, {'subject': 'eastern Tibet'}, {'subject': 'cosmogenic dating'}, {'subject': 'tectonic-geomorphology'}, {'subject': 'late Quaternary slip rates'}, {'subject': 'active pull apart basin'}, {'subject': 'earthquake hazard'}]",,
+10.48649/asdc.1201,Caen vu par les médias. L'exemple de Ouest-France.,Atlas Social de Caen - e-ISSN : 2779-654X,2023,fr,JournalArticle,Creative Commons Attribution Non Commercial Share Alike 4.0 International,"Comment l'agglomération de Caen est-elle représentée dans les médias ? Pourquoi certains lieux font-ils l'actualité et pas d'autres ? Quels sont les lieux qui ne sont jamais évoqués ? Quelle géographie des sujets médiatiques se dessine et quel en est le sens ? Pour répondre à ces questions, nous avons dépouillé tous les numéros du journal quotidien Ouest-France pour l'année 2019 puis réalisé une cartographie thématique ?",fabrica,True,findable,0,0,0,0,0,2023-06-23T12:32:59.000Z,2023-06-23T12:32:59.000Z,jbru.eso,jbru,"médias,conflit,aménagement,actualité","[{'subject': 'médias'}, {'subject': 'conflit'}, {'subject': 'aménagement'}, {'subject': 'actualité'}]",,
+10.5281/zenodo.4759507,"Figs. 53-58 in Contribution To The Knowledge Of The Protonemura Corsicana Species Group, With A Revision Of The North African Species Of The P. Talboti Subgroup (Plecoptera: Nemouridae)",Zenodo,2009,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 53-58. Larva of Protonemura berberica Vinçon & S{nchez-Ortega, 1999. 53: front angle of the pronotum; 54: hind femur; 55: outer apical part of the femur; 56: 6th tergal segment; 57: basal segments of the cercus; 58: 15th segment of the cercus (scale 0.1 mm).",mds,True,findable,0,0,2,0,0,2021-05-14T02:26:30.000Z,2021-05-14T02:26:30.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Nemouridae,Protonemura","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Nemouridae'}, {'subject': 'Protonemura'}]",,
+10.6084/m9.figshare.24165071,Additional file 1 of Non-ventilator-associated ICU-acquired pneumonia (NV-ICU-AP) in patients with acute exacerbation of COPD: From the French OUTCOMEREA cohort,figshare,2023,,Text,Creative Commons Attribution 4.0 International,Additional file 1. Members of the OutcomeRea Network.,mds,True,findable,0,0,0,0,0,2023-09-20T03:22:50.000Z,2023-09-20T03:22:50.000Z,figshare.ars,otjm,"Medicine,Microbiology,FOS: Biological sciences,Genetics,Molecular Biology,Neuroscience,Biotechnology,Evolutionary Biology,Immunology,FOS: Clinical medicine,Cancer,Science Policy,Virology","[{'subject': 'Medicine'}, {'subject': 'Microbiology'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Genetics'}, {'subject': 'Molecular Biology'}, {'subject': 'Neuroscience'}, {'subject': 'Biotechnology'}, {'subject': 'Evolutionary Biology'}, {'subject': 'Immunology'}, {'subject': 'FOS: Clinical medicine', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Cancer'}, {'subject': 'Science Policy'}, {'subject': 'Virology'}]",['107186 Bytes'],
+10.5281/zenodo.4265431,Ecological effects of stress drive bacterial evolvability under sub-inhibitory antibiotic treatments,Zenodo,2020,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Code and data for our publication ""Ecological effects of stress drive bacterial evolvability under sub-inhibitory antibiotic treatments""",mds,True,findable,0,0,0,0,0,2022-07-20T11:13:17.000Z,2022-07-20T11:13:18.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.7602827,Military Air Defense System Requirements,Zenodo,2023,en,Dataset,"GNU Lesser General Public License v3.0 or later,Open Access","This repository contains the military air defense system requirements described in ""Automatic requirements extraction, analysis, and graph representation using an approach derived from computational linguistics"" by Faisal Mokammel, Eric Coatanéa, Joonas Coatanéa, Vladislav Nenchev, Eric Blanco, and Matti Pietola.",mds,True,findable,0,0,0,0,0,2023-02-03T12:38:28.000Z,2023-02-03T12:38:28.000Z,cern.zenodo,cern,"contradiction analysis,network representation,requirements management,similarity","[{'subject': 'contradiction analysis'}, {'subject': 'network representation'}, {'subject': 'requirements management'}, {'subject': 'similarity'}]",,
+10.7280/d11h3x,Annual Ice Velocity of the Greenland Ice Sheet (2010-2017),Dryad,2019,en,Dataset,Creative Commons Attribution 4.0 International,"We derive surface ice velocity using data from 16 satellite sensors deployed by 6 different space agencies. The list of sensors is given in the Table S1. The SAR data are processed from raw to single look complex using the GAMMA processor (www.gamma-rs.ch). All measurements rely on consecutive images where the ice displacement is estimated from tracking or interferometry (Joughin et al. 1998, Michel and Rignot 1999, Mouginot et al. 2012). Surface ice motion is detected using a speckle tracking algorithm for SAR instruments and feature tracking for Landsat. The cross-correlation program for both SAR and optical images is ampcor from the JPL/Caltech repeat orbit interferometry package (ROI_PAC). We assemble a composite ice velocity mosaic at 150 m posting using our entire speed database as described in Mouginot et al. 2017 (Fig. 1A). The ice velocity maps are also mosaicked in annual maps at 150 m posting, covering July, 1st to June, 30th of the following year, i.e. centered on January, 1st (12) because a majority of historic data were acquired in winter season, hence spanning two calendar years. We use Landsat-1&2/MSS images between 1972 and 1976 and combine image pairs up to 2 years apart to measure the displacement of surface features between images as described in Dehecq et al., 2015 or Mouginot et al. 2017. We use the 1978 2-m orthorectified aerial images to correct the geolocation of Landsat-1 and -2 images (Korsgaard et al., 2016). Between 1984 and 1991, we process Landsat-4&5/TM image pairs acquired up to 1-year apart. Only few Landsat-4 and -5 images (~3%) needed geocoding refinement using the same 1978 reference as used previously. Between 1991 and 1998, we process radar images from the European ERS-1/2, with a repeat cycle varying from 3 to 36 days depending on the mission phase. Between 1999 and 2013, we used Landsat-7, ASTER, RADARSAT-1/2, ALOS/PALSAR, ENVISAT/ASAR to determine surface velocity (Joughin et al., 2010; Howat, I. 2017; Rignot and Mouginot, 2012). After 2013, we use Landsat-8, Sentinel-1a/b and RADARSAT-2 (Mouginot et al., 2017). All synthetic aperture radar (SAR) datasets are processed assuming surface parallel flow using the digital elevation model (DEM) from the Greenland Mapping Project (GIMP; Howat et al., 2014) and calibrated as described in Mouginot et al., 2012, 2017. Data were provided by the European Space Agency (ESA), the EU Copernicus program (through ESA), the Canadian Space Agency (CSA), the Japan Aerospace Exploration Agency (JAXA), the Agenzia Spaziale Italiana (ASI), the Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) and the National Aeronautics and Space Administration (NASA). SAR data acquisitions were coordinated by the Polar Space Task Group (PSTG). Errors are estimated based on sensor resolution and time lapse between consecutive images as described in Mouginot et al. 2017.",mds,True,findable,755,110,0,3,0,2019-03-29T12:53:36.000Z,2019-03-29T12:53:37.000Z,dryad.dryad,dryad,,,['5035575468 bytes'],
+10.5061/dryad.wm37pvmkw,"Forest inventory data from Finland and Sweden for: Demographic performance of European tree species at their hot and cold climatic edges, plus ancillary climate data",Dryad,2020,en,Dataset,Creative Commons Zero v1.0 Universal,"1. Species range limits are thought to result from a decline in demographic performance at range edges. However, recent studies reporting contradictory patterns in species demographic performance at their edges cast doubt on our ability to predict climate change demographic impacts. To understand these inconsistent demographic responses at the edges, we need to shift the focus from geographic to climatic edges and analyse how species responses vary with climatic constraints at the edge and species’ ecological strategy. 2. Here we parameterised integral projection models with climate and competition effects for 27 tree species using forest inventory data from over 90,000 plots across Europe. Our models estimate size-dependent climatic responses and evaluate their effects on two life trajectory metrics: lifespan and passage time - the time to grow to a large size. Then we predicted growth, survival, lifespan, and passage time at the hot and dry or cold and wet edges and compared them to their values at the species climatic centre to derive indices of demographic response at the edge. Using these indices, we investigated whether differences in species demographic response between hot and cold edges could be explained by their position along the climate gradient and functional traits related to their climate stress tolerance. 3. We found that at cold and wet edges of European tree species, growth and passage time were constrained, whereas at their hot and dry edges, survival and lifespan were constrained. Demographic constraints at the edge were stronger for species occurring in extreme conditions, i.e. in hot edges of hot-distributed species and cold edges of cold-distributed species. Species leaf nitrogen content was strongly linked to their demographic responses at the edge. In contrast, we found only weak links with wood density, leaf size, and xylem vulnerability to embolism. 4. Synthesis. Our study presents a more complicated picture than previously thought with demographic responses that differ between hot and cold edges. Predictions of climate change impacts should be refined to include edge and species characteristics.",mds,True,findable,601,39,0,3,0,2020-10-19T20:59:17.000Z,2020-10-19T20:59:18.000Z,dryad.dryad,dryad,"FOS: Natural sciences,FOS: Natural sciences,vitale rate","[{'subject': 'FOS: Natural sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Natural sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'vitale rate'}]",['26769397 bytes'],
+10.5061/dryad.j6q573n7x,Continued adaptation of C4 photosynthesis after an initial burst of changes in the Andropogoneae grasses,Dryad,2019,en,Dataset,Creative Commons Zero v1.0 Universal,"C4 photosynthesis is a complex trait that sustains fast growth and high productivity in tropical and subtropical conditions and evolved repeatedly in flowering plants. One of the major C4 lineages is Andropogoneae, a group of ~ 1,200 grass species that includes some of the world's most important crops and species dominating tropical and some temperate grasslands. Previous efforts to understand C4 evolution in the group have compared a few model C4 plants to distantly related C3 species, so that changes directly responsible for the transition to C4 could not be distinguished from those that preceded or followed it. In this study, we analyse the genomes of 66 grass species, capturing the earliest diversification within Andropogoneae as well as their C3 relatives. Phylogenomics combined with molecular dating and analyses of protein evolution show that many changes linked to the evolution of C4 photosynthesis in Andropogoneae happened in the Early Miocene, between 21 and 18 Ma, after the split from its C3 sister lineage, and before the diversification of the group. This initial burst of changes was followed by an extended period of modifications to leaf anatomy and biochemistry during the diversification of Andropogoneae, so that a single C4 origin gave birth to a diversity of C4 phenotypes during 18 million years of speciation events and migration across geographic and ecological spaces. Our comprehensive approach and broad sampling of the diversity in the group reveals that one key transition can lead to a plethora of phenotypes following sustained adaptation of the ancestral state.",mds,True,findable,392,69,0,1,0,2019-10-11T12:58:01.000Z,2019-10-11T12:58:02.000Z,dryad.dryad,dryad,"adaptive evolution,Herbarium Genomics,Jansenelleae,leaf anatomy","[{'subject': 'adaptive evolution'}, {'subject': 'Herbarium Genomics'}, {'subject': 'Jansenelleae'}, {'subject': 'leaf anatomy'}]",['5579649 bytes'],
+10.5281/zenodo.7054555,"Dataset of ""PEMFC performance decay during real-world automotive operation: evincing degradation mechanisms and heterogeneity of ageing""",Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is the underlying dataset of ""PEMFC performance decay during real-world automotive operation: evincing degradation mechanisms and heterogeneity of ageing""",mds,True,findable,0,0,0,0,0,2022-10-18T16:12:00.000Z,2022-10-18T16:12:01.000Z,cern.zenodo,cern,"Polymer Electrolyte Membrane Fuel Cell,Dynamic load cycle,Local degradation,Automotive,Catalyst layer durability,Degradation mechanism","[{'subject': 'Polymer Electrolyte Membrane Fuel Cell'}, {'subject': 'Dynamic load cycle'}, {'subject': 'Local degradation'}, {'subject': 'Automotive'}, {'subject': 'Catalyst layer durability'}, {'subject': 'Degradation mechanism'}]",,
+10.5061/dryad.jq2bvq8bm,Metabarcoding data reveal vertical multitaxa variation in topsoil communities during the colonization of deglaciated forelands,Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"Ice-free areas are increasing worldwide due to the dramatic glacier shrinkage and are undergoing rapid colonization by multiple lifeforms, thus representing key environments to study ecosystem development. Soils have a complex vertical structure. However, we know little about how microbial and animal communities differ across soil depths and development stages during the colonization of deglaciated terrains, how these differences evolve through time, and whether patterns are consistent among different taxonomic groups. Here, we used environmental DNA metabarcoding to describe how community diversity and composition of six groups (Eukaryota, Bacteria, Mycota, Collembola, Insecta, Oligochaeta) differ between surface (0-5 cm) and relatively deep (7.5-20 cm) soils at different stages of development across five Alpine glaciers. Taxonomic diversity increased with time since glacier retreat and with soil evolution; the pattern was consistent across different groups and soil depths. For Eukaryota, and particularly Mycota, alpha-diversity was generally the highest in soils close to the surface. Time since glacier retreat was a more important driver of community composition compared to soil depth; for nearly all the taxa, differences in community composition between surface and deep soils decreased with time since glacier retreat, suggesting that the development of soil and/or of vegetation tends to homogenize the first 20 cm of soil through time. Within both Bacteria and Mycota, several molecular operational taxonomic units were significant indicators of specific depths and/or soil development stages, confirming the strong functional variation of microbial communities through time and depth. The complexity of community patterns highlights the importance of integrating information from multiple taxonomic groups to unravel community variation in response to ongoing global changes.",mds,True,findable,79,3,0,2,0,2023-01-19T15:23:50.000Z,2023-01-19T15:23:51.000Z,dryad.dryad,dryad,"Environmental DNA,Insects,glacier retreat,Hill’s number,beta-diversity,soil depth,springtails,Earthworms,micro-organisms,FOS: Earth and related environmental sciences,FOS: Earth and related environmental sciences","[{'subject': 'Environmental DNA'}, {'subject': 'Insects', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'glacier retreat'}, {'subject': 'Hill’s number'}, {'subject': 'beta-diversity'}, {'subject': 'soil depth'}, {'subject': 'springtails'}, {'subject': 'Earthworms', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'micro-organisms'}, {'subject': 'FOS: Earth and related environmental sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Earth and related environmental sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['22185076 bytes'],
+10.5281/zenodo.6941739,Dataset of publication: Deposit-feeding of Nonionellina labradorica (foraminifera) from an Arctic methane seep site and possible association with a methanotroph,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This file contains all TEM (Transmission Electron Microscopy) images of the foraminifera <em>N. labradorica </em>(foraminifera)<em> </em>used in a feeding experiment for the publication DOI: https://doi.org/10.5194/bg-2021-284 Samples were collected at Gas Hydrate Pingo 3 (GHP3), app. 50 km south of Svalbard at 382m water depth at the mouth of Storfjordrenna, Barents Sea. Blade corer (BLC18) used for sampling was taken at following location 76°6'23.7""N 15°58'1.7""E. After sampling a feeding experiment was performed using the marine methanothroph<em> Methyloprofundus sedimenti</em>. More details can be fount in the methods paper. The file contains",mds,True,findable,0,0,0,0,0,2022-08-12T18:51:39.000Z,2022-08-12T18:51:40.000Z,cern.zenodo,cern,"TEM, Transmission electron microscopy, feeding, foraminifera","[{'subject': 'TEM, Transmission electron microscopy, feeding, foraminifera'}]",,
+10.5281/zenodo.7057257,Companion data of Multi-Phase Task-Based HPC Applications: Quickly Learning how to Run Fast,Zenodo,2022,en,Dataset,"Creative Commons Attribution 4.0 International,Open Access","This is the companion data repository for the paper entitled <strong>Multi-Phase Task-Based HPC Applications: Quickly Learning how to Run Fast</strong> by Lucas Leandro Nesi, Lucas Mello Schnorr, and Arnaud Legrand. The manuscript has been accepted for publication in the IPDPS 2022.",mds,True,findable,0,0,0,0,0,2022-09-07T12:02:35.000Z,2022-09-07T12:02:36.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.ksn02v746,DNA metabarcoding data: Altitudinal zonation of green algae biodiversity in the French Alps,Dryad,2021,en,Dataset,Creative Commons Zero v1.0 Universal,"Mountain environments are marked by an altitudinal zonation of habitat types. They are home to a multitude of terrestrial green algae, who have to cope with abiotic conditions specific to high elevation, e.g., high UV irradiance, alternating desiccation, rain and snow precipitations, extreme diurnal variations in temperature and chronic scarceness of nutrients. Even though photosynthetic green algae are key primary producers colonizing open areas and potential markers of climate change, their overall biodiversity in the Alps has been poorly studied so far, in particular in soil, where alga have been shown to be major components of microbial communities. Here, we investigated whether the spatial distribution of green algae followed the altitudinal zonation of the Alps, based on the assumption that algae can spread via airborne spores and settle in their preferred habitats under the pressure of parameters correlated with elevation. We did so by focusing on selected representative elevational gradients at distant locations in the French Alps, where soil samples were collected at different depths. Soil was considered as either a potential natural habitat or temporary reservoir of algae. We showed that algal DNA represented a relatively low proportion of the overall eukaryotic diversity as measured by a universal Eukaryote marker. We designed two novel green algae metabarcoding markers to amplify the Chlorophyta phylum and its Chlorophyceae class, respectively. Using our newly developed markers, we showed that elevation was a strong correlate of species and genus level distribution. Altitudinal zonation was thus determined for about fifty species, with proposed accessions in reference databases. In particular, Planophila laetevirens and Bracteococcus ruber related species as well as the snow alga Sanguina genus were only found in soil starting at 2,000 m above sea level. Analysis of the vertical distribution in soils further highlighted the importance of pH and nitrogen/carbon ratios. This metabolic trait may also determine the Trebouxiophyceae over Chlorophyceae ratio. Guidelines are discussed for future, more robust and precise analyses of environmental algal DNA in soil in mountain ecosystems, to comprehend the distribution of green algae species and dynamics in response to environmental changes.",mds,True,findable,165,12,0,0,0,2021-06-03T23:05:45.000Z,2021-06-03T23:05:47.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences,Chlorophyta,mountain environment,soil,Biodiversity,Sanguina,Snow Algae","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}, {'subject': 'Chlorophyta'}, {'subject': 'mountain environment'}, {'subject': 'soil'}, {'subject': 'Biodiversity', 'schemeUri': 'https://github.com/PLOS/plos-thesaurus', 'subjectScheme': 'PLOS Subject Area Thesaurus'}, {'subject': 'Sanguina'}, {'subject': 'Snow Algae'}]",['49624412 bytes'],
+10.5281/zenodo.4964221,"FIGURES 35–38. Protonemura risi, 35 in Two new species of Protonemura Kempny, 1898 (Plecoptera: Nemouridae) from the Italian Alps",Zenodo,2021,,Image,Open Access,"FIGURES 35–38. Protonemura risi, 35. male, epiproct, lateral view. 36. male, paraproct median lobe and outer lobe with bifurcated sclerite. 37. female, ventral view (Jura Mountains). 38. female, ventral view (Massif central, northern flank)",mds,True,findable,0,0,0,0,0,2021-06-16T08:25:42.000Z,2021-06-16T08:25:43.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
+10.5281/zenodo.6638442,A single hole with enhance coherence in natural silicon,Zenodo,2022,,Dataset,"Creative Commons Attribution 4.0 International,Open Access",A single hole with enhance coherence in natural silicon,mds,True,findable,0,0,0,0,0,2022-06-13T13:50:58.000Z,2022-06-13T13:50:59.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.4rr39,Data from: Highly overlapping winter diet in two sympatric lemming species revealed by DNA metabarcoding,Dryad,2015,en,Dataset,Creative Commons Zero v1.0 Universal,"Sympatric species are expected to minimize competition by partitioning resources, especially when these are limited. Herbivores inhabiting the High Arctic in winter are a prime example of a situation where food availability is anticipated to be low, and thus reduced diet overlap is expected. We present here the first assessment of diet overlap of high arctic lemmings during winter based on DNA metabarcoding of feces. In contrast to previous analyses based on microhistology, we found that the diets of both collared (Dicrostonyx groenlandicus) and brown lemmings (Lemmus trimucronatus) on Bylot Island were dominated by Salix while mosses, which were significantly consumed only by the brown lemming, were a relatively minor food item. The most abundant plant taxon, Cassiope tetragona, which alone composes more than 50% of the available plant biomass, was not detected in feces and can thus be considered to be non-food. Most plant taxa that were identified as food items were consumed in proportion to their availability and none were clearly selected for. The resulting high diet overlap, together with a lack of habitat segregation, indicates a high potential for resource competition between the two lemming species. However, Salix is abundant in the winter habitats of lemmings on Bylot Island and the non-Salix portion of the diets differed between the two species. Also, lemming grazing impact on vegetation during winter in the study area is negligible. Hence, it seems likely that the high potential for resource competition predicted between these two species did not translate into actual competition. This illustrates that even in environments with low primary productivity food resources do not necessarily generate strong competition among herbivores.",mds,True,findable,396,62,1,1,0,2015-02-03T16:24:46.000Z,2015-02-03T16:24:47.000Z,dryad.dryad,dryad,"arctic bryophyte,Diet Analysis,lemming,Lemmus trimucronatus,bryophyte reference library,Boreal,trnL (UAA) intron,Bryophyta,c-h primer pair,Dicrostonyx groenlandicus","[{'subject': 'arctic bryophyte'}, {'subject': 'Diet Analysis'}, {'subject': 'lemming'}, {'subject': 'Lemmus trimucronatus'}, {'subject': 'bryophyte reference library'}, {'subject': 'Boreal'}, {'subject': 'trnL (UAA) intron'}, {'subject': 'Bryophyta'}, {'subject': 'c-h primer pair'}, {'subject': 'Dicrostonyx groenlandicus'}]",['9873653 bytes'],
+10.5281/zenodo.4760471,"Figs. 5-7 in Two New Alpine Leuctra In The L. Braueri Species Group (Plecoptera, Leuctridae)",Zenodo,2011,,Image,"Creative Commons Attribution 4.0 International,Open Access","Figs. 5-7. Leuctra juliettae sp. n.: male abdominal tip in dorsal view (5), male genitalia in ventral view (6), female subgenital plate in ventral view (7).",mds,True,findable,0,0,4,0,0,2021-05-14T05:23:11.000Z,2021-05-14T05:23:12.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy,Animalia,Arthropoda,Insecta,Plecoptera,Leuctridae,Leuctra","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}, {'subject': 'Animalia'}, {'subject': 'Arthropoda'}, {'subject': 'Insecta'}, {'subject': 'Plecoptera'}, {'subject': 'Leuctridae'}, {'subject': 'Leuctra'}]",,
+10.5281/zenodo.3367347,Dataset for ISMIP6 CMIP5 model selection,Zenodo,2019,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","Dataset associated with the manuscript entitled ""CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica"" for publication in The Cryosphere. This dataset was used to select CMIP5 models as forcing for the ISMIP6 stand-alone Greenland and Antarctica projections.",mds,True,findable,0,0,0,0,0,2019-08-14T14:33:26.000Z,2019-08-14T14:33:26.000Z,cern.zenodo,cern,"climate,CMIP5,Antarctica,Greenland","[{'subject': 'climate'}, {'subject': 'CMIP5'}, {'subject': 'Antarctica'}, {'subject': 'Greenland'}]",,
+10.6084/m9.figshare.23822160,File 6 : Matlab file for part 2 and of the experiment from Mirror exposure following visual body-size adaptation does not affect own body image,The Royal Society,2023,,Dataset,Creative Commons Attribution 4.0 International,File 6 : This matlab file corresponds to the adaptation and post adaptation PSE measures and should be launched second.,mds,True,findable,0,0,0,0,0,2023-08-02T11:18:28.000Z,2023-08-02T11:18:28.000Z,figshare.ars,otjm,"Cognitive Science not elsewhere classified,Psychology and Cognitive Sciences not elsewhere classified","[{'subject': 'Cognitive Science not elsewhere classified'}, {'subject': 'Psychology and Cognitive Sciences not elsewhere classified'}]",['20342 Bytes'],
+10.5281/zenodo.1256648,Ripple Complex Experiments Data Set At Ciem Large Scale Wave Flume Within Hydralab + Project.,Zenodo,2018,,Dataset,"Creative Commons Attribution 4.0,Open Access","The RIPCOM experiments (RIPple COMplex experiments) are presented in order to study the ripple growth conditions on large wave flume tests under fine unimodal, coarse unimodal and mixed sands conditions. The main objectives of the experiments is to improve and understand the protocols to perform mixed sediment experiments within the ripple regime and use/improve the equipment developed at Task 9.1 of the COMPLEX Joint Research Activity within Hydralab+. The experiments were carried out in the large scale wave flume CIEM at Universitat Politècnica de Catalunya (UPC), Barcelona.
+The experimental plan is divided in three steps:
+1. Find the optimum wave conditions that ensure ripples (based on measured velocities and previous literature studies) on the study area. Test the targeted waves with unimodal fine sediment (d 50 =0.250 mm) and measure the obtained ripples under the tested conditions. From the obtained measurements, the waves to be used on the next two steps are selected in order to fix the best conditions to produce ripples within the experimental constrains.
+2. The 13 upper cm of the fine sediment is removed and replaced by the coarser sediment (d 50 =0.545 mm). Once that is done the selected waves to be tested are reproduced and the bottom bedforms are measured.
+3. Mix both sediments fine and coarser sand homogeneously in order to repeat the selected wave conditions and measure the ripples growth and evolution under mixed sediment conditions.
+Due to its size, the data set can not be placed on this repository and will be provided on demand. Please contact with the authors or with the data manager of the CIEM installation.",,True,findable,0,0,0,0,0,2018-05-31T13:26:34.000Z,2018-05-31T13:26:34.000Z,cern.zenodo,cern,"large scale experiments,wave flume,mobile bed,ripples,sediment transport","[{'subject': 'large scale experiments'}, {'subject': 'wave flume'}, {'subject': 'mobile bed'}, {'subject': 'ripples'}, {'subject': 'sediment transport'}]",,
+10.5281/zenodo.4776419,PACT1D/PACT-1D-CALNEX: PACT-1D model version v1 for the CALNEX case study,Zenodo,2021,,Software,Open Access,"We present a new one-dimensional chemistry and transport model which performs surface chemistry based on molecular collisions and chemical conversion, allowing us to add detailed HONO formation chemistry at the ground. The model is called Platform for Atmospheric Chemistry and Transport in 1-Dimension (PACT-1D), which is used here for used CALNEX data interpretation as discussed in Tuite et al 2021 (DOI to follow).",mds,True,findable,0,0,0,0,0,2021-05-20T16:15:44.000Z,2021-05-20T16:25:53.000Z,cern.zenodo,cern,,,,
+10.5281/zenodo.1173088,Results of the ice sheet model initialisation experiments initMIP-Greenland: an ISMIP6 intercomparison,Zenodo,2018,en,Dataset,"Creative Commons Attribution Non Commercial 4.0 International,Open Access","This archive provides the forcing data and ice sheet model output produced as part of the publication ""Design and results of the ice sheet model initialisation experiments initMIP-Greenland: an ISMIP6 intercomparison"", published in The Cryosphere, https://www.the-cryosphere.net/12/1433/2018/ Goelzer, H., Nowicki, S., Edwards, T., Beckley, M., Abe-Ouchi, A., Aschwanden, A., Calov, R., Gagliardini, O., Gillet-Chaulet, F., Golledge, N. R., Gregory, J., Greve, R., Humbert, A., Huybrechts, P., Kennedy, J. H., Larour, E., Lipscomb, W. H., Le clec´h, S., Lee, V., Morlighem, M., Pattyn, F., Payne, A. J., Rodehacke, C., Rückamp, M., Saito, F., Schlegel, N., Seroussi, H., Shepherd, A., Sun, S., van de Wal, R., and Ziemen, F. A.: Design and results of the ice sheet model initialisation experiments initMIP-Greenland: an ISMIP6 intercomparison, The Cryosphere, 12, 1433-1460, 2018, doi:10.5194/tc-12-1433-2018. Contact: Heiko Goelzer, h.goelzer@uu.nl Further information on ISMIP6 and initMIP-Greenland can be found here:<br> http://www.climate-cryosphere.org/activities/targeted/ismip6<br> http://www.climate-cryosphere.org/wiki/index.php?title=InitMIP-Greenland Users should cite the original publication when using all or part of the data. <br> In order to document CMIP6’s scientific impact and enable ongoing support of CMIP, users are also obligated to acknowledge CMIP6, ISMIP6 and the participating modelling groups. <br> *** Important note ***<br> For consistency with future ISMIP6 intercomparison exercises and some observational data sets, we have re-gridded all output to a diagnostic grid following the EPSG:3413 specifications, which differs from the grid originally used to distribute the forcing data. We also provide the forcing data conservatively interpolated to the new grid. <br> Archive overview<br> ----------------<br> README.txt - this information dSMB.zip - The original surface mass balance anomaly forcing data and description<br> dSMB/<br> dsmb_01B13_ISMIP6_v2.nc<br> dsmb_05B13_ISMIP6_v2.nc<br> dsmb_10B13_ISMIP6_v2.nc<br> dsmb_20B13_ISMIP6_v2.nc<br> README_dSMB_v2.txt dSMB_epsg3413.zip - The surface mass balance anomaly forcing data and description, interpolated to the new grid on EPSG:3413<br> dSMB_epsg3413/<br> dsmb_01e3413_ISMIP6_v2.nc<br> dsmb_05e3413_ISMIP6_v2.nc<br> dsmb_10e3413_ISMIP6_v2.nc<br> dsmb_20e3413_ISMIP6_v2.nc<br> README_dSMB_v2_epsg3413.txt <group>_<model>_<experiment>.zip - The model output per group, model and experiment (init, ctrl, asmb)<br> <group1>_<model1>_init/<br> acabf_GIS_<group1>_<model1>_init.nc<br> ...<br> <group1>_<model1>_ctrl/<br> acabf_GIS_<group1>_<model1>_ctrl.nc<br> ...<br> <group1>_<model1>_asmb/<br> acabf_GIS_<group1>_<model1>_asmb.nc<br> ... <group1>_<model2>_init/<br> ...<br> <group1>_<model2>_ctrl/<br> ...<br> <group1>_<model2>_asmb/<br> ... <group2>_<model1>_init/<br> ...<br> <group2>_<model1>_ctrl/<br> ... <br> <group2>_<model1>_asmb/ ... The following script may be used to download the content of the archive. #!/bin/bash<br> wget https://zenodo.org/record/1173088/files/README.txt<br> wget https://zenodo.org/record/1173088/files/dSMB_epsg3413.zip<br> wget https://zenodo.org/record/1173088/files/dSMB.zip<br> <br> for amodel in ARC_PISM AWI_ISSM1 AWI_ISSM2 BGC_BISICLES1 BGC_BISICLES2 BGC_BISICLES3 DMI_PISM1 DMI_PISM2 DMI_PISM3 DMI_PISM4 DMI_PISM5 IGE_ELMER1 IGE_ELMER2 ILTS_SICOPOLIS ILTSPIK_SICOPOLIS IMAU_IMAUICE1 IMAU_IMAUICE2 IMAU_IMAUICE3 JPL_ISSM LANL_CISM LSCE_GRISLI MIROC_ICIES1 MIROC_ICIES2 MPIM_PISM UAF_PISM1 UAF_PISM2 UAF_PISM3 UAF_PISM4 UAF_PISM5 UAF_PISM6 UCIJPL_ISSM ULB_FETISH1 ULB_FETISH2 VUB_GISM1 VUB_GISM2; do wget https://zenodo.org/record/1173088/files/${amodel}_init.zip<br> wget https://zenodo.org/record/1173088/files/${amodel}_ctrl.zip<br> wget https://zenodo.org/record/1173088/files/${amodel}_asmb.zip done",mds,True,findable,4,0,1,0,0,2018-05-25T09:34:51.000Z,2018-05-25T09:34:52.000Z,cern.zenodo,cern,"Model output,ISMIP6,intercomparison,Ice sheet model,Greenland ice sheet,initMIP","[{'subject': 'Model output'}, {'subject': 'ISMIP6'}, {'subject': 'intercomparison'}, {'subject': 'Ice sheet model'}, {'subject': 'Greenland ice sheet'}, {'subject': 'initMIP'}]",,
+10.5281/zenodo.7741947,"Data for: ""Land-use intensity influences European tetrapod food-webs""",Zenodo,2023,,Dataset,"Creative Commons Attribution 4.0 International,Open Access","These .Rdata files enable to reproduce results from our article "" Signatures of land use intensity on european tetrapod food-web architectures"" along with the R code provided at: https://github.com/ChrisBotella/foodwebs_vs_land_use - raw_data : Raw data including GBIF and iNaturalist occurrences and IUCN enveloppes used to select sites and generate species presence/absence. We provide this file for transparency and reproducibility of our methodology. - preprocessed_data: preprocessed data (obtained from raw_data) used to generate our article Figures along with the next file. - TrophicNetworksList : .Rdata containing a list of igraph objects, each igraph is a foodweb associated to a site identify by the list element name. - MultiRegMatrices: .Rdata containing especially the pre-computed matrix Y of cells (rows) by food web metrics (columns) and the covariate design matrix X (for the linear regressions) in order to facilitate and accelerate the reproduction of the analyses.",mds,True,findable,0,0,0,0,0,2023-03-16T17:16:19.000Z,2023-03-16T17:16:20.000Z,cern.zenodo,cern,,,,
+10.5061/dryad.fbg79cnx2,"Past, present and future of chamois science",Dryad,2022,en,Dataset,Creative Commons Zero v1.0 Universal,"The chamois Rupicapra spp. is the most abundant mountain ungulate of Europe and the Near East, where it occurs as two species, the Northern chamois R. rupicapra and the Southern chamois R. pyrenaica. Here, we provide a state-of-the-art overview of research trends and the most challenging issues in chamois research and conservation, focusing on taxonomy and systematics, genetics, life history, ecology and behavior, physiology and disease, management, and conservation. Research on Rupicapra has a longstanding history and has contributed substantially to the biological and ecological knowledge of mountain ungulates. Although the number of publications on this genus has markedly increased over the past two decades, major differences persist with respect to knowledge of species and subspecies, with research mostly focusing on the Alpine chamois R. r. rupicapra and, to a lesser extent, the Pyrenean chamois R. p. pyrenaica. In addition, a scarcity of replicate studies of populations of different subspecies and/or geographic areas limits the advancement of chamois science. Since environmental heterogeneity impacts behavioral, physiological and life history traits, understanding the underlying processes would be of great value from both an evolutionary and conservation/management standpoint, especially in the light of ongoing climatic change. Substantial contributions to this challenge may derive from a quantitative assessment of reproductive success, investigation of fine-scale foraging patterns, and a mechanistic understanding of disease outbreak and resilience. Improving conservation status, resolving taxonomic disputes, identifying subspecies hybridization, assessing the impact of hunting and establishing reliable methods of abundance estimation are of primary concern. Despite being one of the most well-known mountain ungulates, substantial field efforts to collect paleontological, behavioral, ecological, morphological, physiological and genetic data on different populations and subspecies are still needed to ensure a successful future for chamois conservation and research.",mds,True,findable,96,2,0,1,0,2022-05-26T14:27:11.000Z,2022-05-26T14:27:12.000Z,dryad.dryad,dryad,"FOS: Biological sciences,FOS: Biological sciences","[{'subject': 'FOS: Biological sciences', 'subjectScheme': 'fos'}, {'subject': 'FOS: Biological sciences', 'schemeUri': 'http://www.oecd.org/science/inno/38235147.pdf', 'subjectScheme': 'Fields of Science and Technology (FOS)'}]",['1890 bytes'],
+10.5281/zenodo.10037960,FIG. 3 in Passiflora tinifolia Juss. (Passiflora subgenus Passiflora): resurrection and synonymies,Zenodo,2023,,Image,Creative Commons Attribution 4.0 International,"FIG. 3. — Pictures and drawings of P. laurifolia L., P. oblongifolia Pulle, P. gabrielleana Vanderpl. and P. favardensis Kuethe: A, P. laurifolia from Guadeloupe (photograph F. Booms); B, C, P. gabrielleana from Montsinery, near its locus classicus in French Guiana (photograph M. Rome); D, drawing of P. oblongifolia from the holotype Versteeg 652 (from Pulle 1906); E, drawing of P. gabrielleana by J. Vanderplank in Vanderplank & Laurens (2006); F, picture of P. favardensis by Christian Houel in Kuethe (2011). Scale bars: 1 cm.",api,True,findable,0,0,0,0,0,2023-10-24T17:26:34.000Z,2023-10-24T17:26:34.000Z,cern.zenodo,cern,"Biodiversity,Taxonomy","[{'subject': 'Biodiversity'}, {'subject': 'Taxonomy'}]",,
diff --git a/run-all-codes.py b/run-all-codes.py
index 405ca3a..c53b525 100644
--- a/run-all-codes.py
+++ b/run-all-codes.py
@@ -1,7 +1,6 @@
import subprocess
-
def execute_python_file(fila_name):
"""
excute a py program
@@ -20,4 +19,4 @@ file_names = [
"rdg.py"
]
-execute_python_file(file_names[1])
\ No newline at end of file
+execute_python_file(file_names[1])
--
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