diff --git a/1-enrich-with-datacite/all_datacite_clients_for_uga.csv b/1-enrich-with-datacite/all_datacite_clients_for_uga.csv
index 156221e618dd74e4556a413b8ffe9db7e42da6db..55f6fc8605f00269b40eefbf440d51987d4b4539 100644
--- a/1-enrich-with-datacite/all_datacite_clients_for_uga.csv
+++ b/1-enrich-with-datacite/all_datacite_clients_for_uga.csv
@@ -1,13 +1,13 @@
 client,count,name,year,url
-cern.zenodo,752,Zenodo,2013,https://zenodo.org/
-inist.sshade,480,Solid Spectroscopy Hosting Architecture of Databases and Expertise,2019,https://www.sshade.eu/
+cern.zenodo,756,Zenodo,2013,https://zenodo.org/
+inist.sshade,481,Solid Spectroscopy Hosting Architecture of Databases and Expertise,2019,https://www.sshade.eu/
 figshare.ars,352,figshare Academic Research System,2016,http://figshare.com/
 inist.osug,238,Observatoire des Sciences de l'Univers de Grenoble,2014,http://doi.osug.fr
 dryad.dryad,162,DRYAD,2018,https://datadryad.org
 inist.resif,92,Réseau sismologique et géodésique français,2014,https://www.resif.fr/
 inist.humanum,59,NAKALA,2020,https://nakala.fr
+inist.persyval,57,PERSYVAL-Lab : Pervasive Systems and Algorithms Lab,2016,
 rdg.prod,57,Recherche Data Gouv France,2022,https://recherche.data.gouv.fr/en
-inist.persyval,56,PERSYVAL-Lab : Pervasive Systems and Algorithms Lab,2016,
 fmsh.prod,28,Fondation Maison des sciences de l'homme,2023,
 mcdy.dohrmi,12,dggv-e-publications,2020,https://www.dggv.de/publikationen/dggv-e-publikationen.html
 figshare.sage,6,figshare SAGE Publications,2018,
diff --git a/1-enrich-with-datacite/nb-dois.txt b/1-enrich-with-datacite/nb-dois.txt
index cbeb43bd7f531e328a352e16734dfbc16dbe8a76..9f0eb1a9203f6668a4822a9ffd8fd27001d93764 100644
--- a/1-enrich-with-datacite/nb-dois.txt
+++ b/1-enrich-with-datacite/nb-dois.txt
@@ -1 +1 @@
-2333
\ No newline at end of file
+2339
\ No newline at end of file
diff --git a/2-produce-graph/hist-evol-datasets-per-repo.png b/2-produce-graph/hist-evol-datasets-per-repo.png
index 373940158daec115c3d1f80098dd0870f2dc9066..559fe786fa5a53143e7ca9d2ac784792599cc23e 100644
Binary files a/2-produce-graph/hist-evol-datasets-per-repo.png and b/2-produce-graph/hist-evol-datasets-per-repo.png differ
diff --git a/2-produce-graph/hist-last-datasets-by-client.png b/2-produce-graph/hist-last-datasets-by-client.png
index dd7a605a5a97b36d38283953a051739da5b8473d..4e52f7eeaf9de5f77d26815524b0fb0c7ca6ed4d 100644
Binary files a/2-produce-graph/hist-last-datasets-by-client.png and b/2-produce-graph/hist-last-datasets-by-client.png differ
diff --git a/2-produce-graph/hist-quantity-year-type.png b/2-produce-graph/hist-quantity-year-type.png
index a419fe131b6b5d1b49afcbf882bef8a1c3d388de..af0de8f7b6e8cc8c3d3e9e700f6f444f19987c01 100644
Binary files a/2-produce-graph/hist-quantity-year-type.png and b/2-produce-graph/hist-quantity-year-type.png differ
diff --git a/2-produce-graph/pie--datacite-client.png b/2-produce-graph/pie--datacite-client.png
index 3e7cd16f028d711159d33169a9ab691edfb2cc9d..8e60a2885a4fda2022c005a77de15d30e5d4247c 100644
Binary files a/2-produce-graph/pie--datacite-client.png and b/2-produce-graph/pie--datacite-client.png differ
diff --git a/2-produce-graph/pie--datacite-type.png b/2-produce-graph/pie--datacite-type.png
index d5876c79cfaa13aed5c3f9d47a0cb273ce4ac57e..49d298eeb2cb3603828f8233ddefed6f81cc3590 100644
Binary files a/2-produce-graph/pie--datacite-type.png and b/2-produce-graph/pie--datacite-type.png differ
diff --git a/dois-uga--last-500.csv b/dois-uga--last-500.csv
index 82c5e50cd482644cb05763bf58902e6d79fcecd0..d4a89c09c0d7141dd54518880f4752dc42cb8f41 100644
--- a/dois-uga--last-500.csv
+++ b/dois-uga--last-500.csv
@@ -1,4 +1,10 @@
 doi,client,resourceTypeGeneral,created,publisher,rights,sizes
+10.5281/zenodo.13621502,cern.zenodo,Dataset,2024-08-31,Zenodo,Creative Commons Attribution 4.0 International,
+10.5281/zenodo.12783623,cern.zenodo,Dataset,2024-08-30,Zenodo,Creative Commons Attribution 4.0 International,
+10.26302/sshade/experiment_hm_20240726_001,inist.sshade,Dataset,2024-08-29,SSHADE/DOCCD (OSUG Data Center),"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.",['2 spectra']
+10.5281/zenodo.13381664,cern.zenodo,Dataset,2024-08-27,Zenodo,Creative Commons Attribution 4.0 International,
+10.5281/zenodo.12732929,cern.zenodo,Dataset,2024-08-27,Zenodo,Creative Commons Attribution 4.0 International,
+10.18709/perscido.2024.08.ds370,inist.persyval,Dataset,2024-08-27,PerSCiDO,,['10 Mo']
 10.5281/zenodo.13365447,cern.zenodo,Dataset,2024-08-23,Zenodo,Creative Commons Attribution 4.0 International,
 10.34847/nkl.d5bba83q,inist.humanum,Dataset,2024-08-22,NAKALA - https://nakala.fr (Huma-Num - CNRS),,"['15226654 Bytes', '20956020 Bytes', '33317487 Bytes', '8771290 Bytes', '3671478 Bytes']"
 10.5281/zenodo.11961695,cern.zenodo,Dataset,2024-08-22,Zenodo,Creative Commons Attribution 4.0 International,
@@ -81,8 +87,8 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.6084/m9.figshare.26635410,figshare.ars,Text,2024-08-14,figshare,Creative Commons Attribution 4.0 International,['39961 Bytes']
 10.6084/m9.figshare.c.6905671,figshare.ars,Collection,2024-08-14,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.26633925,figshare.ars,Text,2024-08-14,figshare,Creative Commons Attribution 4.0 International,['557382 Bytes']
-10.6084/m9.figshare.c.6889784,figshare.ars,Collection,2024-08-14,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.26629135,figshare.ars,Text,2024-08-14,figshare,Creative Commons Attribution 4.0 International,['792543 Bytes']
+10.6084/m9.figshare.c.6889784,figshare.ars,Collection,2024-08-14,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.c.6880688,figshare.ars,Collection,2024-08-14,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.26626966,figshare.ars,Text,2024-08-14,figshare,Creative Commons Attribution 4.0 International,['4519412 Bytes']
 10.6084/m9.figshare.c.6683920,figshare.ars,Collection,2024-08-13,figshare,Creative Commons Attribution 4.0 International,
@@ -98,8 +104,8 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.6084/m9.figshare.26585823,figshare.ars,Text,2024-08-13,figshare,Creative Commons Attribution 4.0 International,['11099 Bytes']
 10.6084/m9.figshare.c.6596504,figshare.ars,Collection,2024-08-13,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.26577821,figshare.ars,Dataset,2024-08-13,figshare,Creative Commons Attribution 4.0 International,['56397 Bytes']
-10.6084/m9.figshare.c.6586928,figshare.ars,Collection,2024-08-13,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.26567603,figshare.ars,Text,2024-08-13,figshare,Creative Commons Attribution 4.0 International,['360541 Bytes']
+10.6084/m9.figshare.c.6586928,figshare.ars,Collection,2024-08-13,figshare,Creative Commons Attribution 4.0 International,
 10.15778/resif.z42022,inist.resif,Dataset,2024-08-12,RESIF - Réseau Sismologique et géodésique Français,,"['98 stations, 280Go (miniseed format)']"
 10.12686/eshm20-output,ethz.sed,Dataset,2024-08-12,EFEHR (European Facilities of Earthquake Hazard and Risk),Creative Commons Attribution 4.0 International,['529MB']
 10.5281/zenodo.7447726,cern.zenodo,Dataset,2024-08-12,Zenodo,Creative Commons Attribution 4.0 International,
@@ -113,8 +119,8 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.5281/zenodo.13234729,cern.zenodo,Text,2024-08-06,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13194009,cern.zenodo,Image,2024-08-03,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13194007,cern.zenodo,Image,2024-08-03,Zenodo,Creative Commons Attribution 4.0 International,
-10.5281/zenodo.13189234,cern.zenodo,Image,2024-08-03,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13189238,cern.zenodo,Image,2024-08-03,Zenodo,Creative Commons Attribution 4.0 International,
+10.5281/zenodo.13189234,cern.zenodo,Image,2024-08-03,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.13189236,cern.zenodo,Image,2024-08-03,Zenodo,Creative Commons Attribution 4.0 International,
 10.5061/dryad.wdbrv15xr,dryad.dryad,Dataset,2024-08-02,Dryad,Creative Commons Zero v1.0 Universal,['482590 bytes']
 10.5281/zenodo.13164857,cern.zenodo,Dataset,2024-08-02,Zenodo,Creative Commons Attribution 4.0 International,
@@ -387,8 +393,8 @@ doi,client,resourceTypeGeneral,created,publisher,rights,sizes
 10.5281/zenodo.10469399,cern.zenodo,Dataset,2024-01-08,Zenodo,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.24953169,figshare.ars,Text,2024-01-06,figshare,Creative Commons Attribution 4.0 International,['48627 Bytes']
 10.18150/vbwcr1,tib.repod,Dataset,2024-01-05,RepOD,,
-10.6084/m9.figshare.24946445,figshare.ars,Text,2024-01-05,figshare,Creative Commons Attribution 4.0 International,['20755 Bytes']
 10.6084/m9.figshare.c.7009820,figshare.ars,Collection,2024-01-05,figshare,Creative Commons Attribution 4.0 International,
+10.6084/m9.figshare.24946445,figshare.ars,Text,2024-01-05,figshare,Creative Commons Attribution 4.0 International,['20755 Bytes']
 10.6084/m9.figshare.c.7007130,figshare.ars,Collection,2024-01-04,figshare,Creative Commons Attribution 4.0 International,
 10.6084/m9.figshare.24940485,figshare.ars,Text,2024-01-04,figshare,Creative Commons Attribution 4.0 International,['399440 Bytes']
 10.5281/zenodo.10440363,cern.zenodo,Software,2024-01-04,Zenodo,,
@@ -531,9 +537,3 @@ This research has made use of spectroscopic and collisional data from the EMAA d
 10.6084/m9.figshare.24483508,figshare.ars,Text,2023-11-02,figshare,Creative Commons Attribution 4.0 International,['61375 Bytes']
 10.5281/zenodo.10061546,cern.zenodo,Image,2023-11-01,Zenodo,Creative Commons Attribution 4.0 International,
 10.5281/zenodo.7487189,cern.zenodo,Dataset,2023-10-31,Zenodo,Other (Open),
-10.5281/zenodo.10053092,cern.zenodo,Dataset,2023-10-30,Zenodo,"Creative Commons Attribution 4.0 International,Creative Commons Attribution Share Alike 4.0 International",
-10.5281/zenodo.10050502,cern.zenodo,Dataset,2023-10-28,Zenodo,GNU General Public License v3.0 or later,
-10.5281/zenodo.10048443,cern.zenodo,Text,2023-10-27,Zenodo,Creative Commons Attribution 4.0 International,
-10.6084/m9.figshare.c.6900580,figshare.ars,Collection,2023-10-27,figshare,Creative Commons Attribution 4.0 International,
-10.6084/m9.figshare.24447574,figshare.ars,Dataset,2023-10-27,figshare,Creative Commons Attribution 4.0 International,['353871 Bytes']
-10.26302/sshade/bandlist_abs_calcite,inist.sshade,Dataset,2023-10-26,SSHADE/BANDLIST (OSUG Data Center),"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.",
diff --git a/dois-uga.csv b/dois-uga.csv
index 2e2791075fb9a32164fe5164720858c9c38c2c2d..fab859937099d575e5367d782a0e96ec778be729 100644
--- a/dois-uga.csv
+++ b/dois-uga.csv
@@ -10757,3 +10757,59 @@ Temperature.",api,True,findable,0,0,0,1,0,2024-08-16T20:49:28.000Z,2024-08-16T20
 10.5281/zenodo.11961695,Making Control in High Performance Computing for Overload Avoidance Adaptive in Time and Job Size,Zenodo,2024,en,Dataset,Creative Commons Attribution 4.0 International,This zenodo deposit contains the data and the code to reproduce the figures of the work published in the CCTA'2024 conference under the title Making Control in High Performance Computing for Overload Avoidance Adaptive in Time and Job Size.,api,True,findable,0,0,0,0,0,2024-08-22T09:18:00.000Z,2024-08-22T09:18:00.000Z,cern.zenodo,cern,"adaptive control,control for computing,high performance computing (HPC)","[{'subject': 'adaptive control'}, {'subject': 'control for computing'}, {'subject': 'high performance computing (HPC)'}]",,,,,['HasVersion'],"[['IsVersionOf', '10.5281/zenodo.11961695']]"
 10.5281/zenodo.13365447,Preliminary data and analysis from ultrafast calcium or voltage imaging recordings at 8-bits resolution using a Kinetix camera,Zenodo,2024,,Dataset,Creative Commons Attribution 4.0 International,"This dataset was obtained from brain slices of the mouse. Data are from transversal hippocampal slices from 30-40 postnatal days old C57Bl6 mice (of both genders), stained with the Ca2+ indicator Fluo-4 AM; or from layer-5 pyramidal neurons loaded intracellularly either with the Ca2+ indicator Oregon Green BAPTA-5N or with the voltage sensitive dye JPW1114.  Details are in the Read_me file. This dataset cannot be used for publications without permission of the contact person.",api,True,findable,0,0,0,0,0,2024-08-23T12:30:21.000Z,2024-08-23T12:30:21.000Z,cern.zenodo,cern,,,,,,,['HasVersion'],"[['IsVersionOf', '10.5281/zenodo.13365447']]"
 10.34847/nkl.d5bba83q,Fichiers audio et video utilisés dans l'article Mycelium Garden (2024) publié par la Revue Francophone Informatique et Musique,NAKALA - https://nakala.fr (Huma-Num - CNRS),2024,,Dataset,,"Ce projet, développé dans le cadre de l’appel à projet de recherche « Symbiose » de l’EUR ArTec, se concentre sur l’interaction entre l’humain et un réseau de mycélium. Il cherche à comprendre et utiliser les expressions électriques du mycélium dans une perspective musicale. La méthodologie repose sur une recherche de « connaissance objective » (Popper, 1985), étudiant les interactions avec le mycélium par un processus expérimental. Le projet explore la création d’assemblages pour rendre cette interaction sensible et audible. Il interroge les interfaces et les transductions dans des interactions interspécifiques, mettant en lumière l’importance de reconnaître l’altérité des êtres non-humains. L’installation souligne la nécessité de développer des protocoles de recherche guidés par un principe de « verisimilitude » dans le contexte d’un projet écologique d’attention au vivant.",api,True,findable,0,0,0,0,0,2024-08-22T15:39:22.000Z,2024-08-22T15:39:23.000Z,inist.humanum,jbru,"Écosystème,Informatique musicale,intelligence artificielle,Composition,Ambisonie,Ecosystem,Computer music,Artificial intelligence,Composition,Ambisonics","[{'lang': 'fr', 'subject': 'Écosystème'}, {'lang': 'fr', 'subject': 'Informatique musicale'}, {'lang': 'fr', 'subject': 'intelligence artificielle'}, {'lang': 'fr', 'subject': 'Composition'}, {'lang': 'fr', 'subject': 'Ambisonie'}, {'lang': 'en', 'subject': 'Ecosystem'}, {'lang': 'en', 'subject': 'Computer music'}, {'lang': 'en', 'subject': 'Artificial intelligence'}, {'lang': 'en', 'subject': 'Composition'}, {'lang': 'en', 'subject': 'Ambisonics'}]","['15226654 Bytes', '20956020 Bytes', '33317487 Bytes', '8771290 Bytes', '3671478 Bytes']","['audio/x-wav', 'video/mp4', 'application/zip', 'audio/x-wav', 'audio/x-wav']",,,,
+10.5281/zenodo.12732929,Serial synchrotron crystallography dataset and 3D-ED dataset - HEWL crystals obtained by instant crystallization with TbXo4,Zenodo,2024,,Dataset,Creative Commons Attribution 4.0 International,"Data sets related to the publication ""Nucleating Agent Crystallophore Induces Instant Protein Crystallization"" by Sauter et al.
+
+3D-Electron Diffraction data: The raw data obtained on the protein Hen Egg-White Lysozyme is contained in the file RAW-Data_3D-ED_deposition.tar.bz2.
+
+Results of first rounds of model refinement are contained in 3D-ED-affi_4-5sets files
+
+Synchrotron Serial Crystallography data: The raw SSX data obtained on the protein Hen Egg-White Lysozyme can be accessed through https://doi.org/10.15151/ESRF-DC-1823716276.
+
+Results of first rounds of model refinement are contained in SSX-Xo4-supernatent files",api,True,findable,0,0,0,0,0,2024-08-27T14:24:51.000Z,2024-08-27T14:24:51.000Z,cern.zenodo,cern,,,,,,,['HasVersion'],"[['IsVersionOf', '10.5281/zenodo.12732929']]"
+10.5281/zenodo.12783623,Seismicity patterns and multi-scale imaging of Krafla (N-E) Iceland with local earthquake tomography: Raw event waveforms and manual picks for temporary network,Zenodo,2024,,Dataset,Creative Commons Attribution 4.0 International,"This Data and Software were used in the submitted paper  ""Seismicity patterns and multi-scale imaging at Krafla (N-E Iceland) wih local earthquake tomography"" by Glück et al.The data and software provided here are used to compute the high-resolution velocity model with TomoTV (The same workflow was used for the industrial data)This code was used to prepare the manual picks as the input files for a localisation with NonLinLoc by weighting and quality checking the data. This resulting localsitations and the weighted traveltimes are then used for the LET
+
+Data:- Raw data (\WaveformsNodes): 5s waveform snippets of the events listed in the ISOR catalogue on http://lv.isor.is:8080/events/browse/2022 recorded with the temporary network of 98 temporary nodes in June and July 2022- Pickfile (ManualPicks_100Nodes_Kafla2022.txt): Manual picks of the events listed in the ISOR catalogue
+
+Software (Hyp_format.py):-  Weighting: The picks are weighted according to their Signal-to-Noise ratio (described in more detail in Section 2.3 in the main text of the paper)-  Writing the inputfile for NonLinLoc (with the selecting the mode option ""PorS"" in line 118), including all picks, also for those stations where not both phases were picked. The file ""endfile.txt"" is needed to write the picks to the NonLinLoc input format.-  Quality check of the picks: Computing a modified Wadati diagram from the traveltime differences of P and S phases for all the events available (with the selecting the mode option ""PandS"" in line 118)-  Python packages needed: numpy, scipy, matplotlib, pandas, obspy",api,True,findable,0,0,0,0,0,2024-08-30T14:02:37.000Z,2024-08-30T14:02:37.000Z,cern.zenodo,cern,,,,,,,['HasVersion'],"[['IsVersionOf', '10.5281/zenodo.12783623']]"
+10.5281/zenodo.13621502,A Dataset of Metadata of Articles Citing Retracted Articles,Zenodo,2024,en,Dataset,Creative Commons Attribution 4.0 International,"This dataset comprises of metada of articles citing retracted publications. Originally, we obtained the DOIs from the Feet of Clay Detector of the Problematic Paper Screener (PPS - FoCD). Additional columns that were not provided in PPS were added using Crossref & Retraction Watch Database (CRxRW) and Dimensions API services. This detector flags publications that cite retracted articles with additional metadata. 
+
+By querying the Dimensions API with the DOIs of the FoC articles, we acquired information such as more detailed document types (editorial, review article, research article), open access status (we only kept open access FoC articles in the dataset since we want to access the full-texts in the future), and research fields (classified according to the Australian and New Zealand Standard Research Classification (ANZSRC) Fields of Research (FoR), comprising of 23 main fields such as biological sciences, education.
+
+To get further information about the cited retracted articles in the dataset, we used the joint release of CRxRW. Using this dataset, we added the retraction reasons and retraction years. 
+
+The original dataset was obtained from the PPS FoCD in December 2023. At this time there were 22558 total articles flagged in FoCD. Using the data filtering feature in PPS, we had a preliminary selection before downloading the first version of the dataset. We applied a filter to obtain:
+
+
+
+non-retracted citing articles at the time of data curation*
+
+open-access citing articles since we need the whole text to go forward with natural language processing tasks
+
+cited retracted articles with at least one scientific content related reason of retraction 
+
+only articles (not monographs, chapters) to retain a unified text type
+
+
+More information about the usage of this dataset will be updated. 
+
+*Current retraction status of the citing articles can be different since this is a static dataset and scientific literature is dynamic. ",api,True,findable,0,0,0,0,1,2024-08-31T09:39:34.000Z,2024-08-31T09:39:35.000Z,cern.zenodo,cern,,,,,,,['HasVersion'],
+10.18709/perscido.2024.08.ds370,test2-2708,PerSCiDO,2024,,Dataset,,test test,api,True,findable,0,0,0,0,0,2024-08-27T08:02:04.000Z,2024-08-27T08:02:05.000Z,inist.persyval,vcob,Medicine,"[{'subject': 'Medicine', 'subjectScheme': 'http://www.radar-projekt.org/display/Medicine'}]",['10 Mo'],,,,,
+10.26302/sshade/experiment_hm_20240726_001,Optical constants of troilite and pyrrhotite from VUV to 2 mm wavelength,SSHADE/DOCCD (OSUG Data Center),2024,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.",,mds,True,findable,0,0,0,0,0,2024-08-29T14:36:25.000Z,2024-08-29T14:36:26.000Z,inist.sshade,mgeg,"laboratory measurement,specular reflection,macroscopic,VUV,Vacuum Ultraviolet,UV,Ultraviolet,Vis,Visible,NIR,Near-Infrared,MIR,Mid-Infrared,FIR,Far-Infrared,sub-mm,optical constants,Troilite,Pyrrhotite-4M,extraterrestrial,natural terrestrial,sulfide","[{'subject': 'laboratory measurement', 'subjectScheme': 'main'}, {'subject': 'specular reflection', 'subjectScheme': 'main'}, {'subject': 'macroscopic', 'subjectScheme': 'main'}, {'subject': 'VUV', 'subjectScheme': 'variables'}, {'subject': 'Vacuum Ultraviolet', 'subjectScheme': 'variables'}, {'subject': 'UV', 'subjectScheme': 'variables'}, {'subject': 'Ultraviolet', 'subjectScheme': 'variables'}, {'subject': 'Vis', 'subjectScheme': 'variables'}, {'subject': 'Visible', 'subjectScheme': 'variables'}, {'subject': 'NIR', 'subjectScheme': 'variables'}, {'subject': 'Near-Infrared', 'subjectScheme': 'variables'}, {'subject': 'MIR', 'subjectScheme': 'variables'}, {'subject': 'Mid-Infrared', 'subjectScheme': 'variables'}, {'subject': 'FIR', 'subjectScheme': 'variables'}, {'subject': 'Far-Infrared', 'subjectScheme': 'variables'}, {'subject': 'sub-mm', 'subjectScheme': 'variables'}, {'subject': 'optical constants', 'subjectScheme': 'variables'}, {'subject': 'Troilite', 'subjectScheme': 'name'}, {'subject': 'Pyrrhotite-4M', 'subjectScheme': 'name'}, {'subject': 'extraterrestrial', 'subjectScheme': 'origin'}, {'subject': 'natural terrestrial', 'subjectScheme': 'origin'}, {'subject': 'sulfide', 'subjectScheme': 'compound type'}]",['2 spectra'],['ASCII'],,,"['IsPartOf', 'IsPartOf']",
+10.5281/zenodo.13381664,Experimental online quantum dots charge autotuning using neural networks - Output data,Zenodo,2024,,Dataset,Creative Commons Attribution 4.0 International,"Outputs of the model training and the online autotuning experiments presented in the paper: ""Experimental online quantum dots charge autotuning using neural networks"".
+
+Each folder in the zipped files represent a run that includes:
+
+
+
+log file
+
+plots / images
+
+run settings
+
+performance results
+
+pytorch model parameters
+
+
+See README.txt for more information about the file strucutre.",api,True,findable,0,0,0,0,1,2024-08-27T22:01:42.000Z,2024-08-27T22:01:42.000Z,cern.zenodo,cern,,,,,,,"['IsDerivedFrom', 'HasVersion']",