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"<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
"\n",
"# <!-- TITLE --> [SYNOP1] - Time series with RNN - Preparation of data\n",
"<!-- DESC --> Episode 1 : Data analysis and creation of a usable dataset\n",
"<!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
"\n",
"## Objectives :\n",
" - Undestand the data\n",
" - cleanup a usable dataset\n",
"\n",
"\n",
"SYNOP meteorological data, available at: https://public.opendatasoft.com\n",
"\n",
"## What we're going to do :\n",
"\n",
" - Read the data\n",
" - Cleanup and build a usable dataset\n",
"\n",
"## Step 1 - Import and init\n",
"### 1.1 - Python"
]
},
{
"cell_type": "code",
"execution_count": 1,
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"data": {
"text/markdown": [
"**FIDLE 2020 - Practical Work Module**"
],
"text/plain": [
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"metadata": {},
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"text": [
"Version : 0.6.1 DEV\n",
"Notebook id : SYNOP1\n",
"Run time : Saturday 19 December 2020, 10:43:18\n",
"TensorFlow version : 2.0.0\n",
"Keras version : 2.2.4-tf\n",
"Datasets dir : /home/pjluc/datasets/fidle\n",
"Running mode : full\n",
"Update keras cache : False\n",
"Save figs : True\n",
"Path figs : ./run/figs\n"
]
}
],
"source": [
"import tensorflow as tf\n",
"from tensorflow import keras\n",
"from tensorflow.keras.callbacks import TensorBoard\n",
"\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import pandas as pd\n",
"import h5py, json\n",
"import os,time,sys\n",
"import math, random\n",
"\n",
"from importlib import reload\n",
"\n",
"sys.path.append('..')\n",
"import fidle.pwk as pwk\n",
"\n",
"datasets_dir = pwk.init('SYNOP1')\n",
"\n",
"pd.set_option('display.max_rows',200)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 2 - Read the data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"data_filename = 'origine/donnees-synop-essentielles-omm-LYS.csv'\n",
"schema_filename = 'origine/schema.json'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2.1 - Read columns code"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"with open(f'{datasets_dir}/SYNOP/{schema_filename}','r') as json_file:\n",
" schema = json.load(json_file)\n",
"\n",
"synop_codes=list( schema['definitions']['donnees-synop-essentielles-omm_records']['properties']['fields']['properties'].keys() )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2.2 - Read data"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"<br>**Raw data :**"
],
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" <td>2020-02-15T16:00:00+01:00</td>\n",
" <td>102190.0</td>\n",
" <td>-160.0</td>\n",
" <td>6.0</td>\n",
" <td>180.0</td>\n",
" <td>6.9</td>\n",
" <td>290.15</td>\n",
" <td>273.75</td>\n",
" <td>33.0</td>\n",
" <td>...</td>\n",
" <td>5.077833</td>\n",
" <td>45.7265</td>\n",
" <td>Colombier-Saugnieu</td>\n",
" <td>69299</td>\n",
" <td>CC de l'Est Lyonnais (CCEL)</td>\n",
" <td>246900575</td>\n",
" <td>Rhône</td>\n",
" <td>69</td>\n",
" <td>Auvergne-Rhône-Alpes</td>\n",
" <td>84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29162</th>\n",
" <td>7481</td>\n",
" <td>2020-01-25T22:00:00+01:00</td>\n",
" <td>102030.0</td>\n",
" <td>20.0</td>\n",
" <td>1.0</td>\n",
" <td>140.0</td>\n",
" <td>4.9</td>\n",
" <td>281.45</td>\n",
" <td>278.55</td>\n",
" <td>82.0</td>\n",
" <td>...</td>\n",
" <td>5.077833</td>\n",
" <td>45.7265</td>\n",
" <td>Colombier-Saugnieu</td>\n",
" <td>69299</td>\n",
" <td>CC de l'Est Lyonnais (CCEL)</td>\n",
" <td>246900575</td>\n",
" <td>Rhône</td>\n",
" <td>69</td>\n",
" <td>Auvergne-Rhône-Alpes</td>\n",
" <td>84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29163</th>\n",
" <td>7481</td>\n",
" <td>2020-01-26T19:00:00+01:00</td>\n",
" <td>102010.0</td>\n",
" <td>80.0</td>\n",
" <td>3.0</td>\n",
" <td>170.0</td>\n",
" <td>3.7</td>\n",
" <td>282.85</td>\n",
" <td>279.15</td>\n",
" <td>78.0</td>\n",
" <td>...</td>\n",
" <td>5.077833</td>\n",
" <td>45.7265</td>\n",
" <td>Colombier-Saugnieu</td>\n",
" <td>69299</td>\n",
" <td>CC de l'Est Lyonnais (CCEL)</td>\n",
" <td>246900575</td>\n",
" <td>Rhône</td>\n",
" <td>69</td>\n",
" <td>Auvergne-Rhône-Alpes</td>\n",
" <td>84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29164</th>\n",
" <td>7481</td>\n",
" <td>2020-02-08T19:00:00+01:00</td>\n",
" <td>102540.0</td>\n",
" <td>150.0</td>\n",
" <td>2.0</td>\n",
" <td>190.0</td>\n",
" <td>6.2</td>\n",
" <td>283.75</td>\n",
" <td>277.65</td>\n",
" <td>66.0</td>\n",
" <td>...</td>\n",
" <td>5.077833</td>\n",
" <td>45.7265</td>\n",
" <td>Colombier-Saugnieu</td>\n",
" <td>69299</td>\n",
" <td>CC de l'Est Lyonnais (CCEL)</td>\n",
" <td>246900575</td>\n",
" <td>Rhône</td>\n",
" <td>69</td>\n",
" <td>Auvergne-Rhône-Alpes</td>\n",
" <td>84</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10 rows × 81 columns</p>\n",
"</div>"
],
"text/plain": [
" ID OMM station Date Pression au niveau mer \\\n",
"29155 7481 2019-11-16T01:00:00+01:00 100640.0 \n",
"29156 7481 2019-11-16T19:00:00+01:00 101090.0 \n",
"29157 7481 2020-02-12T16:00:00+01:00 102460.0 \n",
"29158 7481 2020-02-13T04:00:00+01:00 102100.0 \n",
"29159 7481 2020-02-14T01:00:00+01:00 102080.0 \n",
"29160 7481 2020-02-14T07:00:00+01:00 102430.0 \n",
"29161 7481 2020-02-15T16:00:00+01:00 102190.0 \n",
"29162 7481 2020-01-25T22:00:00+01:00 102030.0 \n",
"29163 7481 2020-01-26T19:00:00+01:00 102010.0 \n",
"29164 7481 2020-02-08T19:00:00+01:00 102540.0 \n",
"\n",
" Variation de pression en 3 heures Type de tendance barométrique \\\n",
"29155 130.0 1.0 \n",
"29156 90.0 3.0 \n",
"29157 -180.0 6.0 \n",
"29158 -240.0 8.0 \n",
"29159 230.0 1.0 \n",
"29160 210.0 2.0 \n",
"29161 -160.0 6.0 \n",
"29162 20.0 1.0 \n",
"29163 80.0 3.0 \n",
"29164 150.0 2.0 \n",
"\n",
" Direction du vent moyen 10 mn Vitesse du vent moyen 10 mn \\\n",
"29155 190.0 1.0 \n",
"29156 130.0 3.5 \n",
"29157 360.0 2.3 \n",
"29158 150.0 4.9 \n",
"29159 280.0 4.5 \n",
"29160 140.0 3.4 \n",
"29161 180.0 6.9 \n",
"29162 140.0 4.9 \n",
"29163 170.0 3.7 \n",
"29164 190.0 6.2 \n",
"\n",
" Température Point de rosée Humidité ... Longitude Latitude \\\n",
"29155 272.75 272.75 100.0 ... 5.077833 45.7265 \n",
"29156 276.95 274.65 85.0 ... 5.077833 45.7265 \n",
"29157 283.45 271.75 44.0 ... 5.077833 45.7265 \n",
"29158 274.75 271.15 77.0 ... 5.077833 45.7265 \n",
"29159 283.15 276.15 62.0 ... 5.077833 45.7265 \n",
"29160 280.15 278.45 89.0 ... 5.077833 45.7265 \n",
"29161 290.15 273.75 33.0 ... 5.077833 45.7265 \n",
"29162 281.45 278.55 82.0 ... 5.077833 45.7265 \n",
"29163 282.85 279.15 78.0 ... 5.077833 45.7265 \n",
"29164 283.75 277.65 66.0 ... 5.077833 45.7265 \n",
"\n",
" communes (name) communes (code) EPCI (name) \\\n",
"29155 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"29156 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"29157 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"29158 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"29159 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"29160 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"29161 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"29162 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"29163 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"29164 Colombier-Saugnieu 69299 CC de l'Est Lyonnais (CCEL) \n",
"\n",
" EPCI (code) department (name) department (code) \\\n",
"29155 246900575 Rhône 69 \n",
"29156 246900575 Rhône 69 \n",
"29157 246900575 Rhône 69 \n",
"29158 246900575 Rhône 69 \n",
"29159 246900575 Rhône 69 \n",
"29160 246900575 Rhône 69 \n",
"29161 246900575 Rhône 69 \n",
"29162 246900575 Rhône 69 \n",
"29163 246900575 Rhône 69 \n",
"29164 246900575 Rhône 69 \n",
"\n",
" region (name) region (code) \n",
"29155 Auvergne-Rhône-Alpes 84 \n",
"29156 Auvergne-Rhône-Alpes 84 \n",
"29157 Auvergne-Rhône-Alpes 84 \n",
"29158 Auvergne-Rhône-Alpes 84 \n",
"29159 Auvergne-Rhône-Alpes 84 \n",
"29160 Auvergne-Rhône-Alpes 84 \n",
"29161 Auvergne-Rhône-Alpes 84 \n",
"29162 Auvergne-Rhône-Alpes 84 \n",
"29163 Auvergne-Rhône-Alpes 84 \n",
"29164 Auvergne-Rhône-Alpes 84 \n",
"\n",
"[10 rows x 81 columns]"
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" text-align: left;\n",
" }</style><table id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >Code</th> <th class=\"col_heading level0 col1\" >Description</th> <th class=\"col_heading level0 col2\" >Na</th> </tr></thead><tbody>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row0_col0\" class=\"data row0 col0\" >numer_sta</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row0_col1\" class=\"data row0 col1\" >ID OMM station</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row0_col2\" class=\"data row0 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row1_col0\" class=\"data row1 col0\" >date</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row1_col1\" class=\"data row1 col1\" >Date</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row1_col2\" class=\"data row1 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row2_col0\" class=\"data row2 col0\" >pmer</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row2_col1\" class=\"data row2 col1\" >Pression au niveau mer</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row2_col2\" class=\"data row2 col2\" >17</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row3_col0\" class=\"data row3 col0\" >tend</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row3_col1\" class=\"data row3 col1\" >Variation de pression en 3 heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row3_col2\" class=\"data row3 col2\" >2</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row4_col0\" class=\"data row4 col0\" >cod_tend</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row4_col1\" class=\"data row4 col1\" >Type de tendance barométrique</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row4_col2\" class=\"data row4 col2\" >2</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row5_col0\" class=\"data row5 col0\" >dd</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row5_col1\" class=\"data row5 col1\" >Direction du vent moyen 10 mn</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row5_col2\" class=\"data row5 col2\" >3</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row6_col0\" class=\"data row6 col0\" >ff</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row6_col1\" class=\"data row6 col1\" >Vitesse du vent moyen 10 mn</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row6_col2\" class=\"data row6 col2\" >2</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row7_col0\" class=\"data row7 col0\" >t</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row7_col1\" class=\"data row7 col1\" >Température</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row7_col2\" class=\"data row7 col2\" >14</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row8_col0\" class=\"data row8 col0\" >td</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row8_col1\" class=\"data row8 col1\" >Point de rosée</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row8_col2\" class=\"data row8 col2\" >17</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row9_col0\" class=\"data row9 col0\" >u</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row9_col1\" class=\"data row9 col1\" >Humidité</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row9_col2\" class=\"data row9 col2\" >17</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row10_col0\" class=\"data row10 col0\" >vv</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row10_col1\" class=\"data row10 col1\" >Visibilité horizontale</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row10_col2\" class=\"data row10 col2\" >31</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row11_col0\" class=\"data row11 col0\" >ww</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row11_col1\" class=\"data row11 col1\" >Temps présent</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row11_col2\" class=\"data row11 col2\" >1</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row12_col0\" class=\"data row12 col0\" >w1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row12_col1\" class=\"data row12 col1\" >Temps passé 1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row12_col2\" class=\"data row12 col2\" >542</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row13_col0\" class=\"data row13 col0\" >w2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row13_col1\" class=\"data row13 col1\" >Temps passé 2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row13_col2\" class=\"data row13 col2\" >552</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row14_col0\" class=\"data row14 col0\" >n</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row14_col1\" class=\"data row14 col1\" >Nebulosité totale</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row14_col2\" class=\"data row14 col2\" >801</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row15_col0\" class=\"data row15 col0\" >nbas</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row15_col1\" class=\"data row15 col1\" >Nébulosité des nuages de l' étage inférieur</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row15_col2\" class=\"data row15 col2\" >2381</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row16_col0\" class=\"data row16 col0\" >hbas</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row16_col1\" class=\"data row16 col1\" >Hauteur de la base des nuages de l'étage inférieur</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row16_col2\" class=\"data row16 col2\" >8861</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row17_col0\" class=\"data row17 col0\" >cl</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row17_col1\" class=\"data row17 col1\" >Type des nuages de l'étage inférieur</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row17_col2\" class=\"data row17 col2\" >3377</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row18_col0\" class=\"data row18 col0\" >cm</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row18_col1\" class=\"data row18 col1\" >Type des nuages de l'étage moyen</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row18_col2\" class=\"data row18 col2\" >6912</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row19_col0\" class=\"data row19 col0\" >ch</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row19_col1\" class=\"data row19 col1\" >Type des nuages de l'étage supérieur</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row19_col2\" class=\"data row19 col2\" >8494</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row20_col0\" class=\"data row20 col0\" >pres</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row20_col1\" class=\"data row20 col1\" >Pression station</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row20_col2\" class=\"data row20 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row21_col0\" class=\"data row21 col0\" >niv_bar</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row21_col1\" class=\"data row21 col1\" >Niveau barométrique</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row21_col2\" class=\"data row21 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row22_col0\" class=\"data row22 col0\" >geop</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row22_col1\" class=\"data row22 col1\" >Géopotentiel</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row22_col2\" class=\"data row22 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row23_col0\" class=\"data row23 col0\" >tend24</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row23_col1\" class=\"data row23 col1\" >Variation de pression en 24 heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row23_col2\" class=\"data row23 col2\" >14443</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row24_col0\" class=\"data row24 col0\" >tn12</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row24_col1\" class=\"data row24 col1\" >Température minimale sur 12 heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row24_col2\" class=\"data row24 col2\" >21883</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row25_col0\" class=\"data row25 col0\" >tn24</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row25_col1\" class=\"data row25 col1\" >Température minimale sur 24 heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row25_col2\" class=\"data row25 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row26_col0\" class=\"data row26 col0\" >tx12</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row26_col1\" class=\"data row26 col1\" >Température maximale sur 12 heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row26_col2\" class=\"data row26 col2\" >21883</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row27_col0\" class=\"data row27 col0\" >tx24</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row27_col1\" class=\"data row27 col1\" >Température maximale sur 24 heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row27_col2\" class=\"data row27 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row28_col0\" class=\"data row28 col0\" >tminsol</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row28_col1\" class=\"data row28 col1\" >Température minimale du sol sur 12 heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row28_col2\" class=\"data row28 col2\" >27364</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row29_col0\" class=\"data row29 col0\" >sw</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row29_col1\" class=\"data row29 col1\" >Méthode de mesure Température du thermomètre mouillé</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row29_col2\" class=\"data row29 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row30_col0\" class=\"data row30 col0\" >tw</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row30_col1\" class=\"data row30 col1\" >Température du thermomètre mouillé</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row30_col2\" class=\"data row30 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row31_col0\" class=\"data row31 col0\" >raf10</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row31_col1\" class=\"data row31 col1\" >Rafale sur les 10 dernières minutes</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row31_col2\" class=\"data row31 col2\" >14127</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row32_col0\" class=\"data row32 col0\" >rafper</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row32_col1\" class=\"data row32 col1\" >Rafales sur une période</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row32_col2\" class=\"data row32 col2\" >9</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row33_col0\" class=\"data row33 col0\" >per</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row33_col1\" class=\"data row33 col1\" >Periode de mesure de la rafale</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row33_col2\" class=\"data row33 col2\" >8</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row34_col0\" class=\"data row34 col0\" >etat_sol</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row34_col1\" class=\"data row34 col1\" >Etat du sol</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row34_col2\" class=\"data row34 col2\" >12278</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row35_col0\" class=\"data row35 col0\" >ht_neige</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row35_col1\" class=\"data row35 col1\" >Hauteur totale de la couche de neige, glace, autre au sol</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row35_col2\" class=\"data row35 col2\" >12083</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row36_col0\" class=\"data row36 col0\" >ssfrai</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row36_col1\" class=\"data row36 col1\" >Hauteur de la neige fraîche</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row36_col2\" class=\"data row36 col2\" >2914</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row37_col0\" class=\"data row37 col0\" >perssfrai</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row37_col1\" class=\"data row37 col1\" >Periode de mesure de la neige fraiche</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row37_col2\" class=\"data row37 col2\" >4489</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row38_col0\" class=\"data row38 col0\" >rr1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row38_col1\" class=\"data row38 col1\" >Précipitations dans la dernière heure</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row38_col2\" class=\"data row38 col2\" >95</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row39_col0\" class=\"data row39 col0\" >rr3</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row39_col1\" class=\"data row39 col1\" >Précipitations dans les 3 dernières heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row39_col2\" class=\"data row39 col2\" >73</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row40_col0\" class=\"data row40 col0\" >rr6</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row40_col1\" class=\"data row40 col1\" >Précipitations dans les 6 dernières heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row40_col2\" class=\"data row40 col2\" >10869</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row41_col0\" class=\"data row41 col0\" >rr12</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row41_col1\" class=\"data row41 col1\" >Précipitations dans les 12 dernières heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row41_col2\" class=\"data row41 col2\" >10919</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row42_col0\" class=\"data row42 col0\" >rr24</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row42_col1\" class=\"data row42 col1\" >Précipitations dans les 24 dernières heures</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row42_col2\" class=\"data row42 col2\" >12730</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row43_col0\" class=\"data row43 col0\" >phenspe1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row43_col1\" class=\"data row43 col1\" >Phénomène spécial 1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row43_col2\" class=\"data row43 col2\" >14818</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row44_col0\" class=\"data row44 col0\" >phenspe2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row44_col1\" class=\"data row44 col1\" >Phénomène spécial 2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row44_col2\" class=\"data row44 col2\" >14826</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row45_col0\" class=\"data row45 col0\" >phenspe3</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row45_col1\" class=\"data row45 col1\" >Phénomène spécial 3</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row45_col2\" class=\"data row45 col2\" >15515</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row46_col0\" class=\"data row46 col0\" >phenspe4</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row46_col1\" class=\"data row46 col1\" >Phénomène spécial 4</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row46_col2\" class=\"data row46 col2\" >28869</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row47_col0\" class=\"data row47 col0\" >nnuage1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row47_col1\" class=\"data row47 col1\" >Nébulosité couche nuageuse 1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row47_col2\" class=\"data row47 col2\" >4753</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row48_col0\" class=\"data row48 col0\" >ctype1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row48_col1\" class=\"data row48 col1\" >Type nuage 1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row48_col2\" class=\"data row48 col2\" >5699</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row49_col0\" class=\"data row49 col0\" >hnuage1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row49_col1\" class=\"data row49 col1\" >Hauteur de base 1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row49_col2\" class=\"data row49 col2\" >5439</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row50_col0\" class=\"data row50 col0\" >nnuage2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row50_col1\" class=\"data row50 col1\" >Nébulosité couche nuageuse 2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row50_col2\" class=\"data row50 col2\" >16112</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row51_col0\" class=\"data row51 col0\" >ctype2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row51_col1\" class=\"data row51 col1\" >Type nuage 2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row51_col2\" class=\"data row51 col2\" >16643</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row52_col0\" class=\"data row52 col0\" >hnuage2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row52_col1\" class=\"data row52 col1\" >Hauteur de base 2</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row52_col2\" class=\"data row52 col2\" >16317</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row53_col0\" class=\"data row53 col0\" >nnuage3</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row53_col1\" class=\"data row53 col1\" >Nébulosité couche nuageuse 3</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row53_col2\" class=\"data row53 col2\" >25387</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row54_col0\" class=\"data row54 col0\" >ctype3</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row54_col1\" class=\"data row54 col1\" >Type nuage 3</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row54_col2\" class=\"data row54 col2\" >25642</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row55_col0\" class=\"data row55 col0\" >hnuage3</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row55_col1\" class=\"data row55 col1\" >Hauteur de base 3</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row55_col2\" class=\"data row55 col2\" >25431</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row56_col0\" class=\"data row56 col0\" >nnuage4</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row56_col1\" class=\"data row56 col1\" >Nébulosité couche nuageuse 4</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row56_col2\" class=\"data row56 col2\" >28850</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row57\" class=\"row_heading level0 row57\" >57</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row57_col0\" class=\"data row57 col0\" >ctype4</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row57_col1\" class=\"data row57 col1\" >Type nuage 4</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row57_col2\" class=\"data row57 col2\" >28780</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row58\" class=\"row_heading level0 row58\" >58</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row58_col0\" class=\"data row58 col0\" >hnuage4</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row58_col1\" class=\"data row58 col1\" >Hauteur de base 4</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row58_col2\" class=\"data row58 col2\" >28850</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row59\" class=\"row_heading level0 row59\" >59</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row59_col0\" class=\"data row59 col0\" >coordonnees</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row59_col1\" class=\"data row59 col1\" >Coordonnees</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row59_col2\" class=\"data row59 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row60\" class=\"row_heading level0 row60\" >60</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row60_col0\" class=\"data row60 col0\" >nom</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row60_col1\" class=\"data row60 col1\" >Nom</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row60_col2\" class=\"data row60 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row61\" class=\"row_heading level0 row61\" >61</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row61_col0\" class=\"data row61 col0\" >type_de_tendance_barometrique</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row61_col1\" class=\"data row61 col1\" >Type de tendance barométrique.1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row61_col2\" class=\"data row61 col2\" >2</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row62\" class=\"row_heading level0 row62\" >62</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row62_col0\" class=\"data row62 col0\" >temps_passe_1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row62_col1\" class=\"data row62 col1\" >Temps passé 1.1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row62_col2\" class=\"data row62 col2\" >542</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row63\" class=\"row_heading level0 row63\" >63</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row63_col0\" class=\"data row63 col0\" >temps_present</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row63_col1\" class=\"data row63 col1\" >Temps présent.1</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row63_col2\" class=\"data row63 col2\" >1</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row64\" class=\"row_heading level0 row64\" >64</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row64_col0\" class=\"data row64 col0\" >tc</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row64_col1\" class=\"data row64 col1\" >Température (°C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row64_col2\" class=\"data row64 col2\" >14</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row65\" class=\"row_heading level0 row65\" >65</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row65_col0\" class=\"data row65 col0\" >tn12c</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row65_col1\" class=\"data row65 col1\" >Température minimale sur 12 heures (°C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row65_col2\" class=\"data row65 col2\" >21883</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row66\" class=\"row_heading level0 row66\" >66</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row66_col0\" class=\"data row66 col0\" >tn24c</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row66_col1\" class=\"data row66 col1\" >Température minimale sur 24 heures (°C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row66_col2\" class=\"data row66 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row67\" class=\"row_heading level0 row67\" >67</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row67_col0\" class=\"data row67 col0\" >tx12c</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row67_col1\" class=\"data row67 col1\" >Température maximale sur 12 heures (°C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row67_col2\" class=\"data row67 col2\" >21883</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row68\" class=\"row_heading level0 row68\" >68</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row68_col0\" class=\"data row68 col0\" >tx24c</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row68_col1\" class=\"data row68 col1\" >Température maximale sur 24 heures (°C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row68_col2\" class=\"data row68 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row69\" class=\"row_heading level0 row69\" >69</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row69_col0\" class=\"data row69 col0\" >tminsolc</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row69_col1\" class=\"data row69 col1\" >Température minimale du sol sur 12 heures (en °C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row69_col2\" class=\"data row69 col2\" >27364</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row70\" class=\"row_heading level0 row70\" >70</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row70_col0\" class=\"data row70 col0\" >altitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row70_col1\" class=\"data row70 col1\" >Altitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row70_col2\" class=\"data row70 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row71\" class=\"row_heading level0 row71\" >71</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row71_col0\" class=\"data row71 col0\" >longitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row71_col1\" class=\"data row71 col1\" >Longitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row71_col2\" class=\"data row71 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row72\" class=\"row_heading level0 row72\" >72</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row72_col0\" class=\"data row72 col0\" >latitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row72_col1\" class=\"data row72 col1\" >Latitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row72_col2\" class=\"data row72 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row73\" class=\"row_heading level0 row73\" >73</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row73_col0\" class=\"data row73 col0\" >libgeo</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row73_col1\" class=\"data row73 col1\" >communes (name)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row73_col2\" class=\"data row73 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row74\" class=\"row_heading level0 row74\" >74</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row74_col0\" class=\"data row74 col0\" >codegeo</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row74_col1\" class=\"data row74 col1\" >communes (code)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row74_col2\" class=\"data row74 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row75\" class=\"row_heading level0 row75\" >75</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row75_col0\" class=\"data row75 col0\" >nom_epci</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row75_col1\" class=\"data row75 col1\" >EPCI (name)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row75_col2\" class=\"data row75 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row76\" class=\"row_heading level0 row76\" >76</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row76_col0\" class=\"data row76 col0\" >code_epci</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row76_col1\" class=\"data row76 col1\" >EPCI (code)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row76_col2\" class=\"data row76 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row77\" class=\"row_heading level0 row77\" >77</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row77_col0\" class=\"data row77 col0\" >nom_dept</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row77_col1\" class=\"data row77 col1\" >department (name)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row77_col2\" class=\"data row77 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row78\" class=\"row_heading level0 row78\" >78</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row78_col0\" class=\"data row78 col0\" >code_dep</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row78_col1\" class=\"data row78 col1\" >department (code)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row78_col2\" class=\"data row78 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row79\" class=\"row_heading level0 row79\" >79</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row79_col0\" class=\"data row79 col0\" >nom_reg</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row79_col1\" class=\"data row79 col1\" >region (name)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row79_col2\" class=\"data row79 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row80\" class=\"row_heading level0 row80\" >80</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row80_col0\" class=\"data row80 col0\" >code_reg</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row80_col1\" class=\"data row80 col1\" >region (code)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row80_col2\" class=\"data row80 col2\" >0</td>\n",
" </tr>\n",
" </tbody></table>"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x7f79fa772ed0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape is : (29165, 81)\n"
]
}
],
"source": [
"df = pd.read_csv(f'{datasets_dir}/SYNOP/{data_filename}', header=0, sep=';')\n",
"pwk.subtitle('Raw data :')\n",
"display(df.tail(10))\n",
"\n",
"# ---- Get the columns name as descriptions\n",
"synop_desc = list(df.columns)\n",
"\n",
"# ---- Set Codes as columns name\n",
"df.columns = synop_codes\n",
"code2desc = dict(zip(synop_codes, synop_desc))\n",
"\n",
"# ---- Count the na values by columns\n",
"columns_na = df.isna().sum().tolist()\n",
"\n",
"# ---- Show all of that\n",
"df_desc=pd.DataFrame({'Code':synop_codes, 'Description':synop_desc, 'Na':columns_na})\n",
"\n",
"pwk.subtitle('List of columns :')\n",
"display(df_desc.style.set_properties(**{'text-align': 'left'}))\n",
"\n",
"print('Shape is : ', df.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 3 - Keep only certain columns"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"<br>**Our selected columns :**"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>date</th>\n",
" <th>pmer</th>\n",
" <th>tend</th>\n",
" <th>cod_tend</th>\n",
" <th>dd</th>\n",
" <th>ff</th>\n",
" <th>td</th>\n",
" <th>u</th>\n",
" <th>ww</th>\n",
" <th>pres</th>\n",
" <th>rafper</th>\n",
" <th>per</th>\n",
" <th>rr1</th>\n",
" <th>rr3</th>\n",
" <th>tc</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2015-06-12T17:00:00+02:00</td>\n",
" <td>101050.0</td>\n",
" <td>-230.0</td>\n",
" <td>6.0</td>\n",
" <td>140.0</td>\n",
" <td>3.6</td>\n",
" <td>286.25</td>\n",
" <td>50.0</td>\n",
" <td>2.0</td>\n",
" <td>98330.0</td>\n",
" <td>5.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.1</td>\n",
" <td>24.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2015-06-05T17:00:00+02:00</td>\n",
" <td>101590.0</td>\n",
" <td>-220.0</td>\n",
" <td>8.0</td>\n",
" <td>190.0</td>\n",
" <td>3.9</td>\n",
" <td>286.95</td>\n",
" <td>32.0</td>\n",
" <td>3.0</td>\n",
" <td>98930.0</td>\n",
" <td>9.9</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>32.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2015-06-15T11:00:00+02:00</td>\n",
" <td>101420.0</td>\n",
" <td>90.0</td>\n",
" <td>1.0</td>\n",
" <td>270.0</td>\n",
" <td>1.5</td>\n",
" <td>286.85</td>\n",
" <td>64.0</td>\n",
" <td>3.0</td>\n",
" <td>98660.0</td>\n",
" <td>4.5</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>20.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2015-06-15T14:00:00+02:00</td>\n",
" <td>101430.0</td>\n",
" <td>20.0</td>\n",
" <td>1.0</td>\n",
" <td>10.0</td>\n",
" <td>2.5</td>\n",
" <td>286.45</td>\n",
" <td>55.0</td>\n",
" <td>1.0</td>\n",
" <td>98680.0</td>\n",
" <td>5.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>22.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2015-06-20T05:00:00+02:00</td>\n",
" <td>102030.0</td>\n",
" <td>0.0</td>\n",
" <td>4.0</td>\n",
" <td>50.0</td>\n",
" <td>0.7</td>\n",
" <td>282.95</td>\n",
" <td>82.0</td>\n",
" <td>2.0</td>\n",
" <td>99170.0</td>\n",
" <td>2.4</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>12.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2015-06-22T05:00:00+02:00</td>\n",
" <td>101680.0</td>\n",
" <td>-120.0</td>\n",
" <td>6.0</td>\n",
" <td>180.0</td>\n",
" <td>0.7</td>\n",
" <td>286.15</td>\n",
" <td>80.0</td>\n",
" <td>1.0</td>\n",
" <td>98870.0</td>\n",
" <td>4.7</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.1</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>2015-06-23T02:00:00+02:00</td>\n",
" <td>101270.0</td>\n",
" <td>150.0</td>\n",
" <td>2.0</td>\n",
" <td>20.0</td>\n",
" <td>4.5</td>\n",
" <td>282.95</td>\n",
" <td>54.0</td>\n",
" <td>0.0</td>\n",
" <td>98490.0</td>\n",
" <td>10.2</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>19.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2015-06-25T14:00:00+02:00</td>\n",
" <td>102180.0</td>\n",
" <td>-40.0</td>\n",
" <td>8.0</td>\n",
" <td>10.0</td>\n",
" <td>2.3</td>\n",
" <td>283.25</td>\n",
" <td>38.0</td>\n",
" <td>1.0</td>\n",
" <td>99430.0</td>\n",
" <td>7.5</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>25.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2015-07-05T20:00:00+02:00</td>\n",
" <td>101410.0</td>\n",
" <td>50.0</td>\n",
" <td>3.0</td>\n",
" <td>190.0</td>\n",
" <td>8.3</td>\n",
" <td>288.05</td>\n",
" <td>33.0</td>\n",
" <td>3.0</td>\n",
" <td>98760.0</td>\n",
" <td>13.4</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>33.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2015-05-14T17:00:00+02:00</td>\n",
" <td>101070.0</td>\n",
" <td>-150.0</td>\n",
" <td>6.0</td>\n",
" <td>20.0</td>\n",
" <td>6.2</td>\n",
" <td>284.95</td>\n",
" <td>60.0</td>\n",
" <td>3.0</td>\n",
" <td>98300.0</td>\n",
" <td>11.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>19.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>2015-03-16T22:00:00+01:00</td>\n",
" <td>102150.0</td>\n",
" <td>40.0</td>\n",
" <td>1.0</td>\n",
" <td>50.0</td>\n",
" <td>1.7</td>\n",
" <td>275.05</td>\n",
" <td>62.0</td>\n",
" <td>1.0</td>\n",
" <td>99240.0</td>\n",
" <td>4.6</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2015-03-26T01:00:00+01:00</td>\n",
" <td>101140.0</td>\n",
" <td>100.0</td>\n",
" <td>1.0</td>\n",
" <td>330.0</td>\n",
" <td>5.9</td>\n",
" <td>275.45</td>\n",
" <td>82.0</td>\n",
" <td>1.0</td>\n",
" <td>98220.0</td>\n",
" <td>8.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>5.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>2015-04-03T17:00:00+02:00</td>\n",
" <td>101690.0</td>\n",
" <td>-250.0</td>\n",
" <td>7.0</td>\n",
" <td>340.0</td>\n",
" <td>3.5</td>\n",
" <td>278.15</td>\n",
" <td>55.0</td>\n",
" <td>1.0</td>\n",
" <td>98850.0</td>\n",
" <td>6.4</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>13.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>2015-04-05T20:00:00+02:00</td>\n",
" <td>101850.0</td>\n",
" <td>140.0</td>\n",
" <td>3.0</td>\n",
" <td>10.0</td>\n",
" <td>7.8</td>\n",
" <td>268.45</td>\n",
" <td>38.0</td>\n",
" <td>1.0</td>\n",
" <td>98950.0</td>\n",
" <td>13.5</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>2014-10-22T17:00:00+02:00</td>\n",
" <td>102670.0</td>\n",
" <td>-70.0</td>\n",
" <td>8.0</td>\n",
" <td>20.0</td>\n",
" <td>4.6</td>\n",
" <td>275.35</td>\n",
" <td>55.0</td>\n",
" <td>1.0</td>\n",
" <td>99770.0</td>\n",
" <td>7.2</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>2015-02-08T16:00:00+01:00</td>\n",
" <td>102570.0</td>\n",
" <td>20.0</td>\n",
" <td>3.0</td>\n",
" <td>350.0</td>\n",
" <td>12.3</td>\n",
" <td>271.55</td>\n",
" <td>68.0</td>\n",
" <td>0.0</td>\n",
" <td>99590.0</td>\n",
" <td>19.9</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>2015-02-11T07:00:00+01:00</td>\n",
" <td>102670.0</td>\n",
" <td>-10.0</td>\n",
" <td>7.0</td>\n",
" <td>290.0</td>\n",
" <td>2.0</td>\n",
" <td>267.55</td>\n",
" <td>88.0</td>\n",
" <td>10.0</td>\n",
" <td>99610.0</td>\n",
" <td>3.3</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-3.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>2015-02-07T04:00:00+01:00</td>\n",
" <td>101900.0</td>\n",
" <td>160.0</td>\n",
" <td>1.0</td>\n",
" <td>310.0</td>\n",
" <td>2.0</td>\n",
" <td>268.65</td>\n",
" <td>74.0</td>\n",
" <td>2.0</td>\n",
" <td>98900.0</td>\n",
" <td>3.2</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>2015-02-13T04:00:00+01:00</td>\n",
" <td>102140.0</td>\n",
" <td>-50.0</td>\n",
" <td>8.0</td>\n",
" <td>140.0</td>\n",
" <td>2.1</td>\n",
" <td>273.55</td>\n",
" <td>74.0</td>\n",
" <td>0.0</td>\n",
" <td>99190.0</td>\n",
" <td>4.9</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>4.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>2015-02-16T19:00:00+01:00</td>\n",
" <td>102060.0</td>\n",
" <td>100.0</td>\n",
" <td>3.0</td>\n",
" <td>20.0</td>\n",
" <td>3.2</td>\n",
" <td>275.65</td>\n",
" <td>88.0</td>\n",
" <td>1.0</td>\n",
" <td>99110.0</td>\n",
" <td>5.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>4.3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" date pmer tend cod_tend dd ff td \\\n",
"0 2015-06-12T17:00:00+02:00 101050.0 -230.0 6.0 140.0 3.6 286.25 \n",
"1 2015-06-05T17:00:00+02:00 101590.0 -220.0 8.0 190.0 3.9 286.95 \n",
"2 2015-06-15T11:00:00+02:00 101420.0 90.0 1.0 270.0 1.5 286.85 \n",
"3 2015-06-15T14:00:00+02:00 101430.0 20.0 1.0 10.0 2.5 286.45 \n",
"4 2015-06-20T05:00:00+02:00 102030.0 0.0 4.0 50.0 0.7 282.95 \n",
"5 2015-06-22T05:00:00+02:00 101680.0 -120.0 6.0 180.0 0.7 286.15 \n",
"6 2015-06-23T02:00:00+02:00 101270.0 150.0 2.0 20.0 4.5 282.95 \n",
"7 2015-06-25T14:00:00+02:00 102180.0 -40.0 8.0 10.0 2.3 283.25 \n",
"8 2015-07-05T20:00:00+02:00 101410.0 50.0 3.0 190.0 8.3 288.05 \n",
"9 2015-05-14T17:00:00+02:00 101070.0 -150.0 6.0 20.0 6.2 284.95 \n",
"10 2015-03-16T22:00:00+01:00 102150.0 40.0 1.0 50.0 1.7 275.05 \n",
"11 2015-03-26T01:00:00+01:00 101140.0 100.0 1.0 330.0 5.9 275.45 \n",
"12 2015-04-03T17:00:00+02:00 101690.0 -250.0 7.0 340.0 3.5 278.15 \n",
"13 2015-04-05T20:00:00+02:00 101850.0 140.0 3.0 10.0 7.8 268.45 \n",
"14 2014-10-22T17:00:00+02:00 102670.0 -70.0 8.0 20.0 4.6 275.35 \n",
"15 2015-02-08T16:00:00+01:00 102570.0 20.0 3.0 350.0 12.3 271.55 \n",
"16 2015-02-11T07:00:00+01:00 102670.0 -10.0 7.0 290.0 2.0 267.55 \n",
"17 2015-02-07T04:00:00+01:00 101900.0 160.0 1.0 310.0 2.0 268.65 \n",
"18 2015-02-13T04:00:00+01:00 102140.0 -50.0 8.0 140.0 2.1 273.55 \n",
"19 2015-02-16T19:00:00+01:00 102060.0 100.0 3.0 20.0 3.2 275.65 \n",
"\n",
" u ww pres rafper per rr1 rr3 tc \n",
"0 50.0 2.0 98330.0 5.1 -10.0 0.0 -0.1 24.2 \n",
"1 32.0 3.0 98930.0 9.9 -10.0 0.0 0.0 32.6 \n",
"2 64.0 3.0 98660.0 4.5 -10.0 0.0 0.0 20.8 \n",
"3 55.0 1.0 98680.0 5.1 -10.0 0.0 0.0 22.8 \n",
"4 82.0 2.0 99170.0 2.4 -10.0 0.0 0.0 12.8 \n",
"5 80.0 1.0 98870.0 4.7 -10.0 0.0 -0.1 16.5 \n",
"6 54.0 0.0 98490.0 10.2 -10.0 0.0 0.0 19.3 \n",
"7 38.0 1.0 99430.0 7.5 -10.0 0.0 0.0 25.5 \n",
"8 33.0 3.0 98760.0 13.4 -10.0 0.0 0.0 33.4 \n",
"9 60.0 3.0 98300.0 11.1 -10.0 0.0 0.0 19.8 \n",
"10 62.0 1.0 99240.0 4.6 -10.0 0.0 0.0 8.8 \n",
"11 82.0 1.0 98220.0 8.1 -10.0 0.0 0.0 5.1 \n",
"12 55.0 1.0 98850.0 6.4 -10.0 0.0 0.0 13.9 \n",
"13 38.0 1.0 98950.0 13.5 -10.0 0.0 0.0 8.9 \n",
"14 55.0 1.0 99770.0 7.2 -10.0 0.0 0.0 10.9 \n",
"15 68.0 0.0 99590.0 19.9 -10.0 0.0 0.0 3.8 \n",
"16 88.0 10.0 99610.0 3.3 -10.0 0.0 0.0 -3.9 \n",
"17 74.0 2.0 98900.0 3.2 -10.0 0.0 0.0 -0.4 \n",
"18 74.0 0.0 99190.0 4.9 -10.0 0.0 0.0 4.6 \n",
"19 88.0 1.0 99110.0 5.1 -10.0 0.0 0.0 4.3 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/markdown": [
"<br>**Few statistics :**"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>pmer</th>\n",
" <th>tend</th>\n",
" <th>cod_tend</th>\n",
" <th>dd</th>\n",
" <th>ff</th>\n",
" <th>td</th>\n",
" <th>u</th>\n",
" <th>ww</th>\n",
" <th>pres</th>\n",
" <th>rafper</th>\n",
" <th>per</th>\n",
" <th>rr1</th>\n",
" <th>rr3</th>\n",
" <th>tc</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>29148.000000</td>\n",
" <td>29163.000000</td>\n",
" <td>29163.000000</td>\n",
" <td>29162.000000</td>\n",
" <td>29163.00000</td>\n",
" <td>29148.000000</td>\n",
" <td>29148.000000</td>\n",
" <td>29164.000000</td>\n",
" <td>29165.000000</td>\n",
" <td>29156.000000</td>\n",
" <td>29157.0</td>\n",
" <td>29070.000000</td>\n",
" <td>29092.000000</td>\n",
" <td>29151.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>101753.552902</td>\n",
" <td>0.255118</td>\n",
" <td>4.306930</td>\n",
" <td>204.088197</td>\n",
" <td>3.39653</td>\n",
" <td>280.027865</td>\n",
" <td>71.021614</td>\n",
" <td>10.106158</td>\n",
" <td>98894.598320</td>\n",
" <td>6.299005</td>\n",
" <td>-10.0</td>\n",
" <td>0.092886</td>\n",
" <td>0.279008</td>\n",
" <td>12.688261</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>798.093804</td>\n",
" <td>111.438232</td>\n",
" <td>2.716149</td>\n",
" <td>115.422508</td>\n",
" <td>2.46898</td>\n",
" <td>5.857534</td>\n",
" <td>18.275755</td>\n",
" <td>19.404573</td>\n",
" <td>761.586766</td>\n",
" <td>3.852478</td>\n",
" <td>0.0</td>\n",
" <td>0.605673</td>\n",
" <td>1.414611</td>\n",
" <td>8.146390</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>97960.000000</td>\n",
" <td>-750.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.00000</td>\n",
" <td>249.250000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>95170.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-10.0</td>\n",
" <td>-0.100000</td>\n",
" <td>-0.100000</td>\n",
" <td>-12.100000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>101300.000000</td>\n",
" <td>-70.000000</td>\n",
" <td>2.000000</td>\n",
" <td>130.000000</td>\n",
" <td>1.50000</td>\n",
" <td>275.825000</td>\n",
" <td>58.000000</td>\n",
" <td>2.000000</td>\n",
" <td>98480.000000</td>\n",
" <td>3.600000</td>\n",
" <td>-10.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>6.600000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>101740.000000</td>\n",
" <td>0.000000</td>\n",
" <td>3.000000</td>\n",
" <td>190.000000</td>\n",
" <td>2.90000</td>\n",
" <td>280.250000</td>\n",
" <td>74.000000</td>\n",
" <td>2.000000</td>\n",
" <td>98920.000000</td>\n",
" <td>5.300000</td>\n",
" <td>-10.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>12.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>102240.000000</td>\n",
" <td>70.000000</td>\n",
" <td>7.000000</td>\n",
" <td>330.000000</td>\n",
" <td>4.60000</td>\n",
" <td>284.550000</td>\n",
" <td>86.000000</td>\n",
" <td>3.000000</td>\n",
" <td>99360.000000</td>\n",
" <td>8.200000</td>\n",
" <td>-10.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>18.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>104280.000000</td>\n",
" <td>810.000000</td>\n",
" <td>8.000000</td>\n",
" <td>360.000000</td>\n",
" <td>18.80000</td>\n",
" <td>295.950000</td>\n",
" <td>100.000000</td>\n",
" <td>97.000000</td>\n",
" <td>101210.000000</td>\n",
" <td>30.200000</td>\n",
" <td>-10.0</td>\n",
" <td>19.000000</td>\n",
" <td>45.000000</td>\n",
" <td>38.900000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" pmer tend cod_tend dd ff \\\n",
"count 29148.000000 29163.000000 29163.000000 29162.000000 29163.00000 \n",
"mean 101753.552902 0.255118 4.306930 204.088197 3.39653 \n",
"std 798.093804 111.438232 2.716149 115.422508 2.46898 \n",
"min 97960.000000 -750.000000 0.000000 0.000000 0.00000 \n",
"25% 101300.000000 -70.000000 2.000000 130.000000 1.50000 \n",
"50% 101740.000000 0.000000 3.000000 190.000000 2.90000 \n",
"75% 102240.000000 70.000000 7.000000 330.000000 4.60000 \n",
"max 104280.000000 810.000000 8.000000 360.000000 18.80000 \n",
"\n",
" td u ww pres rafper \\\n",
"count 29148.000000 29148.000000 29164.000000 29165.000000 29156.000000 \n",
"mean 280.027865 71.021614 10.106158 98894.598320 6.299005 \n",
"std 5.857534 18.275755 19.404573 761.586766 3.852478 \n",
"min 249.250000 2.000000 0.000000 95170.000000 0.000000 \n",
"25% 275.825000 58.000000 2.000000 98480.000000 3.600000 \n",
"50% 280.250000 74.000000 2.000000 98920.000000 5.300000 \n",
"75% 284.550000 86.000000 3.000000 99360.000000 8.200000 \n",
"max 295.950000 100.000000 97.000000 101210.000000 30.200000 \n",
"\n",
" per rr1 rr3 tc \n",
"count 29157.0 29070.000000 29092.000000 29151.000000 \n",
"mean -10.0 0.092886 0.279008 12.688261 \n",
"std 0.0 0.605673 1.414611 8.146390 \n",
"min -10.0 -0.100000 -0.100000 -12.100000 \n",
"25% -10.0 0.000000 0.000000 6.600000 \n",
"50% -10.0 0.000000 0.000000 12.500000 \n",
"75% -10.0 0.000000 0.000000 18.500000 \n",
"max -10.0 19.000000 45.000000 38.900000 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"columns_used=['date','pmer','tend','cod_tend','dd','ff','td','u','ww','pres','rafper','per','rr1','rr3','tc']\n",
"\n",
"# ---- Drop unused columns\n",
"\n",
"to_drop = df.columns.difference(columns_used)\n",
"df.drop( to_drop, axis=1, inplace=True)\n",
"\n",
"# ---- Show all of that\n",
"\n",
"pwk.subtitle('Our selected columns :')\n",
"display(df.head(20))\n",
"\n",
"pwk.subtitle('Few statistics :')\n",
"display(df.describe())\n",
"\n",
"# ---- 'per' column is constant, we can drop it\n",
"\n",
"df.drop(['per'],axis=1,inplace=True)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 4 - Cleanup session : Let's sort it and cook up some NaN values"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"<br>**Before :**"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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" <th></th>\n",
" <th>date</th>\n",
" <th>pmer</th>\n",
" <th>tend</th>\n",
" <th>cod_tend</th>\n",
" <th>dd</th>\n",
" <th>ff</th>\n",
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" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>396</th>\n",
" <td>2010-02-19T16:00:00+01:00</td>\n",
" <td>99760.0</td>\n",
" <td>180.0</td>\n",
" <td>3.0</td>\n",
" <td>330.0</td>\n",
" <td>4.6</td>\n",
" <td>275.85</td>\n",
" <td>79.0</td>\n",
" <td>21.0</td>\n",
" <td>96890.0</td>\n",
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" <td>0.0</td>\n",
" <td>1.0</td>\n",
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" <tr>\n",
" <th>434</th>\n",
" <td>2010-02-24T10:00:00+01:00</td>\n",
" <td>100310.0</td>\n",
" <td>60.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>279.25</td>\n",
" <td>77.0</td>\n",
" <td>2.0</td>\n",
" <td>97470.0</td>\n",
" <td>NaN</td>\n",
" <td>0.2</td>\n",
" <td>0.2</td>\n",
" <td>9.9</td>\n",
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" <tr>\n",
" <th>477</th>\n",
" <td>2010-03-01T19:00:00+01:00</td>\n",
" <td>101400.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>340.0</td>\n",
" <td>2.6</td>\n",
" <td>275.45</td>\n",
" <td>61.0</td>\n",
" <td>2.0</td>\n",
" <td>98520.0</td>\n",
" <td>5.7</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>9.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>734</th>\n",
" <td>2010-04-03T02:00:00+02:00</td>\n",
" <td>101550.0</td>\n",
" <td>50.0</td>\n",
" <td>0.0</td>\n",
" <td>190.0</td>\n",
" <td>7.7</td>\n",
" <td>277.55</td>\n",
" <td>64.0</td>\n",
" <td>2.0</td>\n",
" <td>98680.0</td>\n",
" <td>12.3</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>10.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1061</th>\n",
" <td>2010-05-13T23:00:00+02:00</td>\n",
" <td>NaN</td>\n",
" <td>60.0</td>\n",
" <td>2.0</td>\n",
" <td>330.0</td>\n",
" <td>4.6</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>98220.0</td>\n",
" <td>7.7</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>9.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1063</th>\n",
" <td>2010-05-14T05:00:00+02:00</td>\n",
" <td>NaN</td>\n",
" <td>-50.0</td>\n",
" <td>5.0</td>\n",
" <td>350.0</td>\n",
" <td>4.1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>98110.0</td>\n",
" <td>7.2</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1064</th>\n",
" <td>2010-05-14T08:00:00+02:00</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>5.0</td>\n",
" <td>350.0</td>\n",
" <td>4.6</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>98110.0</td>\n",
" <td>6.7</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2268</th>\n",
" <td>2010-10-11T20:00:00+02:00</td>\n",
" <td>NaN</td>\n",
" <td>150.0</td>\n",
" <td>2.0</td>\n",
" <td>10.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>98060.0</td>\n",
" <td>3.1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2269</th>\n",
" <td>2010-10-11T23:00:00+02:00</td>\n",
" <td>NaN</td>\n",
" <td>130.0</td>\n",
" <td>3.0</td>\n",
" <td>80.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>98190.0</td>\n",
" <td>2.6</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>2270</th>\n",
" <td>2010-10-12T02:00:00+02:00</td>\n",
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" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>98260.0</td>\n",
" <td>1.5</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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],
"text/plain": [
" date pmer tend cod_tend dd ff \\\n",
"396 2010-02-19T16:00:00+01:00 99760.0 180.0 3.0 330.0 4.6 \n",
"434 2010-02-24T10:00:00+01:00 100310.0 60.0 1.0 NaN NaN \n",
"477 2010-03-01T19:00:00+01:00 101400.0 NaN NaN 340.0 2.6 \n",
"734 2010-04-03T02:00:00+02:00 101550.0 50.0 0.0 190.0 7.7 \n",
"1061 2010-05-13T23:00:00+02:00 NaN 60.0 2.0 330.0 4.6 \n",
"1063 2010-05-14T05:00:00+02:00 NaN -50.0 5.0 350.0 4.1 \n",
"1064 2010-05-14T08:00:00+02:00 NaN 0.0 5.0 350.0 4.6 \n",
"2268 2010-10-11T20:00:00+02:00 NaN 150.0 2.0 10.0 1.0 \n",
"2269 2010-10-11T23:00:00+02:00 NaN 130.0 3.0 80.0 1.0 \n",
"2270 2010-10-12T02:00:00+02:00 NaN 70.0 1.0 0.0 0.0 \n",
"\n",
" td u ww pres rafper rr1 rr3 tc \n",
"396 275.85 79.0 21.0 96890.0 NaN 0.0 1.0 6.1 \n",
"434 279.25 77.0 2.0 97470.0 NaN 0.2 0.2 9.9 \n",
"477 275.45 61.0 2.0 98520.0 5.7 0.0 NaN 9.4 \n",
"734 277.55 64.0 2.0 98680.0 12.3 NaN NaN 10.9 \n",
"1061 NaN NaN 2.0 98220.0 7.7 0.0 0.0 9.9 \n",
"1063 NaN NaN 2.0 98110.0 7.2 0.0 0.0 8.1 \n",
"1064 NaN NaN 2.0 98110.0 6.7 0.0 0.0 8.1 \n",
"2268 NaN NaN 2.0 98060.0 3.1 NaN NaN NaN \n",
"2269 NaN NaN 2.0 98190.0 2.6 NaN NaN NaN \n",
"2270 NaN NaN 2.0 98260.0 1.5 NaN NaN NaN "
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"output_type": "display_data"
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"data": {
"text/markdown": [
"<br>**After :**"
],
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"<IPython.core.display.Markdown object>"
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" <th>date</th>\n",
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" <th>cod_tend</th>\n",
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" date pmer tend cod_tend dd ff \\\n",
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"477 2010-03-01T19:00:00+01:00 101400.000000 195.0 4.0 340.0 2.60 \n",
"734 2010-04-03T02:00:00+02:00 101550.000000 50.0 0.0 190.0 7.70 \n",
"1061 2010-05-13T23:00:00+02:00 101020.000000 60.0 2.0 330.0 4.60 \n",
"1063 2010-05-14T05:00:00+02:00 101040.000000 -50.0 5.0 350.0 4.10 \n",
"1064 2010-05-14T08:00:00+02:00 101040.000000 0.0 5.0 350.0 4.60 \n",
"2268 2010-10-11T20:00:00+02:00 100786.666667 150.0 2.0 10.0 1.00 \n",
"2269 2010-10-11T23:00:00+02:00 100863.333333 130.0 3.0 80.0 1.00 \n",
"2270 2010-10-12T02:00:00+02:00 100940.000000 70.0 1.0 0.0 0.00 \n",
"\n",
" td u ww pres rafper rr1 rr3 tc \n",
"396 275.85 79.000000 21.0 96890.0 8.25 0.0 1.0 6.10 \n",
"434 279.25 77.000000 2.0 97470.0 6.65 0.2 0.2 9.90 \n",
"477 275.45 61.000000 2.0 98520.0 5.70 0.0 0.5 9.40 \n",
"734 277.55 64.000000 2.0 98680.0 12.30 0.0 0.0 10.90 \n",
"1061 281.25 86.500000 2.0 98220.0 7.70 0.0 0.0 9.90 \n",
"1063 279.15 80.666667 2.0 98110.0 7.20 0.0 0.0 8.10 \n",
"1064 279.35 79.333333 2.0 98110.0 6.70 0.0 0.0 8.10 \n",
"2268 284.75 83.333333 2.0 98060.0 3.10 0.0 0.0 14.45 \n",
"2269 284.45 84.666667 2.0 98190.0 2.60 0.0 0.0 13.90 \n",
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# ---- First of all, we have to sort on the date\n",
"\n",
"df.sort_values(['date'], inplace=True)\n",
"df.reset_index(drop=True, inplace=True)\n",
"\n",
"# ---- Before : Lines with NaN\n",
"\n",
"na_rows=df.isna().any(axis=1)\n",
"pwk.subtitle('Before :')\n",
"display( df[na_rows].head(10) )\n",
"\n",
"# ---- Nice interpolation for plugging holes\n",
"\n",
"df.interpolate(inplace=True)\n",
"\n",
"# ---- After\n",
"\n",
"pwk.subtitle('After :')\n",
"display(df[na_rows].head(10))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 5 - Final dataset\n",
"### 5.1 - Summarize it"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"<br>**Dataset columns :**"
],
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" text-align: left;\n",
" }</style><table id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >Columns</th> <th class=\"col_heading level0 col1\" >Description</th> <th class=\"col_heading level0 col2\" >Na</th> </tr></thead><tbody>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row0_col0\" class=\"data row0 col0\" >date</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row0_col1\" class=\"data row0 col1\" >Date</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row0_col2\" class=\"data row0 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
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" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row1_col1\" class=\"data row1 col1\" >Pression au niveau mer</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row1_col2\" class=\"data row1 col2\" >0</td>\n",
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" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row2_col1\" class=\"data row2 col1\" >Variation de pression en 3 heures</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row2_col2\" class=\"data row2 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row3_col0\" class=\"data row3 col0\" >cod_tend</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row3_col1\" class=\"data row3 col1\" >Type de tendance barométrique</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row3_col2\" class=\"data row3 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row4_col0\" class=\"data row4 col0\" >dd</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row4_col1\" class=\"data row4 col1\" >Direction du vent moyen 10 mn</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row4_col2\" class=\"data row4 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row5_col0\" class=\"data row5 col0\" >ff</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row5_col1\" class=\"data row5 col1\" >Vitesse du vent moyen 10 mn</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row5_col2\" class=\"data row5 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row6_col0\" class=\"data row6 col0\" >td</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row6_col1\" class=\"data row6 col1\" >Point de rosée</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row6_col2\" class=\"data row6 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row7_col0\" class=\"data row7 col0\" >u</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row7_col1\" class=\"data row7 col1\" >Humidité</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row7_col2\" class=\"data row7 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row8_col0\" class=\"data row8 col0\" >ww</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row8_col1\" class=\"data row8 col1\" >Temps présent</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row8_col2\" class=\"data row8 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row9_col0\" class=\"data row9 col0\" >pres</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row9_col1\" class=\"data row9 col1\" >Pression station</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row9_col2\" class=\"data row9 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row10_col0\" class=\"data row10 col0\" >rafper</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row10_col1\" class=\"data row10 col1\" >Rafales sur une période</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row10_col2\" class=\"data row10 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row11_col0\" class=\"data row11 col0\" >rr1</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row11_col1\" class=\"data row11 col1\" >Précipitations dans la dernière heure</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row11_col2\" class=\"data row11 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row12_col0\" class=\"data row12 col0\" >rr3</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row12_col1\" class=\"data row12 col1\" >Précipitations dans les 3 dernières heures</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row12_col2\" class=\"data row12 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row13_col0\" class=\"data row13 col0\" >tc</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row13_col1\" class=\"data row13 col1\" >Température (°C)</td>\n",
" <td id=\"T_a028327a_41de_11eb_aa99_e3cf125b8da3row13_col2\" class=\"data row13 col2\" >0</td>\n",
" </tr>\n",
" </tbody></table>"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x7f79f9511390>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/markdown": [
"<br>**Have a look :**"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>date</th>\n",
" <th>pmer</th>\n",
" <th>tend</th>\n",
" <th>cod_tend</th>\n",
" <th>dd</th>\n",
" <th>ff</th>\n",
" <th>td</th>\n",
" <th>u</th>\n",
" <th>ww</th>\n",
" <th>pres</th>\n",
" <th>rafper</th>\n",
" <th>rr1</th>\n",
" <th>rr3</th>\n",
" <th>tc</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>29145</th>\n",
" <td>2020-02-24T13:00:00+01:00</td>\n",
" <td>102380.0</td>\n",
" <td>-220.0</td>\n",
" <td>8.0</td>\n",
" <td>120.0</td>\n",
" <td>1.6</td>\n",
" <td>281.15</td>\n",
" <td>59.0</td>\n",
" <td>0.0</td>\n",
" <td>99540.0</td>\n",
" <td>3.7</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>16.0</td>\n",
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" <tr>\n",
" <th>29146</th>\n",
" <td>2020-02-24T16:00:00+01:00</td>\n",
" <td>101990.0</td>\n",
" <td>-350.0</td>\n",
" <td>6.0</td>\n",
" <td>110.0</td>\n",
" <td>1.6</td>\n",
" <td>281.55</td>\n",
" <td>50.0</td>\n",
" <td>3.0</td>\n",
" <td>99190.0</td>\n",
" <td>3.3</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>19.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29147</th>\n",
" <td>2020-02-24T19:00:00+01:00</td>\n",
" <td>101800.0</td>\n",
" <td>-220.0</td>\n",
" <td>6.0</td>\n",
" <td>150.0</td>\n",
" <td>2.9</td>\n",
" <td>280.05</td>\n",
" <td>55.0</td>\n",
" <td>3.0</td>\n",
" <td>98970.0</td>\n",
" <td>4.1</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>15.9</td>\n",
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" <tr>\n",
" <th>29148</th>\n",
" <td>2020-02-24T22:00:00+01:00</td>\n",
" <td>101740.0</td>\n",
" <td>-80.0</td>\n",
" <td>6.0</td>\n",
" <td>170.0</td>\n",
" <td>1.8</td>\n",
" <td>280.35</td>\n",
" <td>67.0</td>\n",
" <td>2.0</td>\n",
" <td>98890.0</td>\n",
" <td>4.3</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>13.2</td>\n",
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" <tr>\n",
" <th>29149</th>\n",
" <td>2020-02-25T01:00:00+01:00</td>\n",
" <td>101640.0</td>\n",
" <td>-150.0</td>\n",
" <td>8.0</td>\n",
" <td>170.0</td>\n",
" <td>2.5</td>\n",
" <td>278.85</td>\n",
" <td>83.0</td>\n",
" <td>2.0</td>\n",
" <td>98740.0</td>\n",
" <td>4.7</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29150</th>\n",
" <td>2020-02-25T04:00:00+01:00</td>\n",
" <td>101450.0</td>\n",
" <td>-200.0</td>\n",
" <td>6.0</td>\n",
" <td>150.0</td>\n",
" <td>3.7</td>\n",
" <td>277.75</td>\n",
" <td>87.0</td>\n",
" <td>2.0</td>\n",
" <td>98540.0</td>\n",
" <td>4.8</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>6.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29151</th>\n",
" <td>2020-02-25T07:00:00+01:00</td>\n",
" <td>101530.0</td>\n",
" <td>60.0</td>\n",
" <td>3.0</td>\n",
" <td>30.0</td>\n",
" <td>4.0</td>\n",
" <td>276.95</td>\n",
" <td>92.0</td>\n",
" <td>3.0</td>\n",
" <td>98600.0</td>\n",
" <td>6.1</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29152</th>\n",
" <td>2020-02-25T10:00:00+01:00</td>\n",
" <td>101490.0</td>\n",
" <td>-20.0</td>\n",
" <td>8.0</td>\n",
" <td>200.0</td>\n",
" <td>1.8</td>\n",
" <td>277.55</td>\n",
" <td>87.0</td>\n",
" <td>3.0</td>\n",
" <td>98580.0</td>\n",
" <td>5.5</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>6.4</td>\n",
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" <tr>\n",
" <th>29153</th>\n",
" <td>2020-02-25T13:00:00+01:00</td>\n",
" <td>101330.0</td>\n",
" <td>-140.0</td>\n",
" <td>8.0</td>\n",
" <td>150.0</td>\n",
" <td>3.8</td>\n",
" <td>278.95</td>\n",
" <td>85.0</td>\n",
" <td>21.0</td>\n",
" <td>98440.0</td>\n",
" <td>7.1</td>\n",
" <td>0.6</td>\n",
" <td>2.0</td>\n",
" <td>8.2</td>\n",
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" <tr>\n",
" <th>29154</th>\n",
" <td>2020-02-25T16:00:00+01:00</td>\n",
" <td>100990.0</td>\n",
" <td>-290.0</td>\n",
" <td>6.0</td>\n",
" <td>140.0</td>\n",
" <td>4.4</td>\n",
" <td>279.55</td>\n",
" <td>69.0</td>\n",
" <td>3.0</td>\n",
" <td>98150.0</td>\n",
" <td>7.2</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>11.9</td>\n",
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" <tr>\n",
" <th>29155</th>\n",
" <td>2020-02-25T19:00:00+01:00</td>\n",
" <td>100910.0</td>\n",
" <td>-90.0</td>\n",
" <td>5.0</td>\n",
" <td>260.0</td>\n",
" <td>4.3</td>\n",
" <td>278.95</td>\n",
" <td>69.0</td>\n",
" <td>25.0</td>\n",
" <td>98060.0</td>\n",
" <td>8.4</td>\n",
" <td>-0.1</td>\n",
" <td>-0.1</td>\n",
" <td>11.3</td>\n",
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" <tr>\n",
" <th>29156</th>\n",
" <td>2020-02-25T22:00:00+01:00</td>\n",
" <td>100980.0</td>\n",
" <td>60.0</td>\n",
" <td>3.0</td>\n",
" <td>280.0</td>\n",
" <td>8.0</td>\n",
" <td>273.65</td>\n",
" <td>51.0</td>\n",
" <td>1.0</td>\n",
" <td>98120.0</td>\n",
" <td>11.3</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29157</th>\n",
" <td>2020-02-26T01:00:00+01:00</td>\n",
" <td>101040.0</td>\n",
" <td>30.0</td>\n",
" <td>2.0</td>\n",
" <td>230.0</td>\n",
" <td>2.8</td>\n",
" <td>275.65</td>\n",
" <td>69.0</td>\n",
" <td>25.0</td>\n",
" <td>98150.0</td>\n",
" <td>10.7</td>\n",
" <td>-0.1</td>\n",
" <td>-0.1</td>\n",
" <td>7.8</td>\n",
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" <tr>\n",
" <th>29158</th>\n",
" <td>2020-02-26T04:00:00+01:00</td>\n",
" <td>101060.0</td>\n",
" <td>-10.0</td>\n",
" <td>8.0</td>\n",
" <td>230.0</td>\n",
" <td>3.0</td>\n",
" <td>275.85</td>\n",
" <td>86.0</td>\n",
" <td>25.0</td>\n",
" <td>98140.0</td>\n",
" <td>13.6</td>\n",
" <td>0.4</td>\n",
" <td>1.8</td>\n",
" <td>4.8</td>\n",
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" <tr>\n",
" <th>29159</th>\n",
" <td>2020-02-26T07:00:00+01:00</td>\n",
" <td>100940.0</td>\n",
" <td>-110.0</td>\n",
" <td>6.0</td>\n",
" <td>210.0</td>\n",
" <td>3.3</td>\n",
" <td>274.85</td>\n",
" <td>78.0</td>\n",
" <td>21.0</td>\n",
" <td>98030.0</td>\n",
" <td>7.4</td>\n",
" <td>-0.1</td>\n",
" <td>-0.1</td>\n",
" <td>5.2</td>\n",
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" <tr>\n",
" <th>29160</th>\n",
" <td>2020-02-26T10:00:00+01:00</td>\n",
" <td>101100.0</td>\n",
" <td>160.0</td>\n",
" <td>3.0</td>\n",
" <td>230.0</td>\n",
" <td>6.8</td>\n",
" <td>274.45</td>\n",
" <td>74.0</td>\n",
" <td>1.0</td>\n",
" <td>98190.0</td>\n",
" <td>10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>5.6</td>\n",
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" <tr>\n",
" <th>29161</th>\n",
" <td>2020-02-26T13:00:00+01:00</td>\n",
" <td>101200.0</td>\n",
" <td>100.0</td>\n",
" <td>3.0</td>\n",
" <td>310.0</td>\n",
" <td>10.3</td>\n",
" <td>270.55</td>\n",
" <td>52.0</td>\n",
" <td>1.0</td>\n",
" <td>98290.0</td>\n",
" <td>19.5</td>\n",
" <td>0.0</td>\n",
" <td>-0.1</td>\n",
" <td>6.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29162</th>\n",
" <td>2020-02-26T16:00:00+01:00</td>\n",
" <td>101290.0</td>\n",
" <td>100.0</td>\n",
" <td>3.0</td>\n",
" <td>310.0</td>\n",
" <td>8.9</td>\n",
" <td>270.55</td>\n",
" <td>47.0</td>\n",
" <td>1.0</td>\n",
" <td>98390.0</td>\n",
" <td>14.3</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29163</th>\n",
" <td>2020-02-26T19:00:00+01:00</td>\n",
" <td>101550.0</td>\n",
" <td>230.0</td>\n",
" <td>2.0</td>\n",
" <td>300.0</td>\n",
" <td>2.8</td>\n",
" <td>272.05</td>\n",
" <td>64.0</td>\n",
" <td>1.0</td>\n",
" <td>98620.0</td>\n",
" <td>7.4</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>5.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29164</th>\n",
" <td>2020-02-26T22:00:00+01:00</td>\n",
" <td>101780.0</td>\n",
" <td>200.0</td>\n",
" <td>2.0</td>\n",
" <td>50.0</td>\n",
" <td>3.2</td>\n",
" <td>274.05</td>\n",
" <td>84.0</td>\n",
" <td>1.0</td>\n",
" <td>98820.0</td>\n",
" <td>8.2</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.3</td>\n",
" </tr>\n",
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],
"text/plain": [
" date pmer tend cod_tend dd ff \\\n",
"29145 2020-02-24T13:00:00+01:00 102380.0 -220.0 8.0 120.0 1.6 \n",
"29146 2020-02-24T16:00:00+01:00 101990.0 -350.0 6.0 110.0 1.6 \n",
"29147 2020-02-24T19:00:00+01:00 101800.0 -220.0 6.0 150.0 2.9 \n",
"29148 2020-02-24T22:00:00+01:00 101740.0 -80.0 6.0 170.0 1.8 \n",
"29149 2020-02-25T01:00:00+01:00 101640.0 -150.0 8.0 170.0 2.5 \n",
"29150 2020-02-25T04:00:00+01:00 101450.0 -200.0 6.0 150.0 3.7 \n",
"29151 2020-02-25T07:00:00+01:00 101530.0 60.0 3.0 30.0 4.0 \n",
"29152 2020-02-25T10:00:00+01:00 101490.0 -20.0 8.0 200.0 1.8 \n",
"29153 2020-02-25T13:00:00+01:00 101330.0 -140.0 8.0 150.0 3.8 \n",
"29154 2020-02-25T16:00:00+01:00 100990.0 -290.0 6.0 140.0 4.4 \n",
"29155 2020-02-25T19:00:00+01:00 100910.0 -90.0 5.0 260.0 4.3 \n",
"29156 2020-02-25T22:00:00+01:00 100980.0 60.0 3.0 280.0 8.0 \n",
"29157 2020-02-26T01:00:00+01:00 101040.0 30.0 2.0 230.0 2.8 \n",
"29158 2020-02-26T04:00:00+01:00 101060.0 -10.0 8.0 230.0 3.0 \n",
"29159 2020-02-26T07:00:00+01:00 100940.0 -110.0 6.0 210.0 3.3 \n",
"29160 2020-02-26T10:00:00+01:00 101100.0 160.0 3.0 230.0 6.8 \n",
"29161 2020-02-26T13:00:00+01:00 101200.0 100.0 3.0 310.0 10.3 \n",
"29162 2020-02-26T16:00:00+01:00 101290.0 100.0 3.0 310.0 8.9 \n",
"29163 2020-02-26T19:00:00+01:00 101550.0 230.0 2.0 300.0 2.8 \n",
"29164 2020-02-26T22:00:00+01:00 101780.0 200.0 2.0 50.0 3.2 \n",
"\n",
" td u ww pres rafper rr1 rr3 tc \n",
"29145 281.15 59.0 0.0 99540.0 3.7 0.0 0.0 16.0 \n",
"29146 281.55 50.0 3.0 99190.0 3.3 0.0 0.0 19.1 \n",
"29147 280.05 55.0 3.0 98970.0 4.1 0.0 0.0 15.9 \n",
"29148 280.35 67.0 2.0 98890.0 4.3 0.0 0.0 13.2 \n",
"29149 278.85 83.0 2.0 98740.0 4.7 0.0 0.0 8.4 \n",
"29150 277.75 87.0 2.0 98540.0 4.8 0.0 0.0 6.6 \n",
"29151 276.95 92.0 3.0 98600.0 6.1 0.0 0.0 5.0 \n",
"29152 277.55 87.0 3.0 98580.0 5.5 0.0 0.0 6.4 \n",
"29153 278.95 85.0 21.0 98440.0 7.1 0.6 2.0 8.2 \n",
"29154 279.55 69.0 3.0 98150.0 7.2 0.0 0.0 11.9 \n",
"29155 278.95 69.0 25.0 98060.0 8.4 -0.1 -0.1 11.3 \n",
"29156 273.65 51.0 1.0 98120.0 11.3 0.0 0.0 10.2 \n",
"29157 275.65 69.0 25.0 98150.0 10.7 -0.1 -0.1 7.8 \n",
"29158 275.85 86.0 25.0 98140.0 13.6 0.4 1.8 4.8 \n",
"29159 274.85 78.0 21.0 98030.0 7.4 -0.1 -0.1 5.2 \n",
"29160 274.45 74.0 1.0 98190.0 10.0 0.0 0.0 5.6 \n",
"29161 270.55 52.0 1.0 98290.0 19.5 0.0 -0.1 6.6 \n",
"29162 270.55 47.0 1.0 98390.0 14.3 0.0 0.0 8.0 \n",
"29163 272.05 64.0 1.0 98620.0 7.4 0.0 0.0 5.2 \n",
"29164 274.05 84.0 1.0 98820.0 8.2 0.0 0.0 3.3 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape is : (29165, 14)\n"
]
}
],
"source": [
"# ---- Count the na values by columns\n",
"dataset_na = df.isna().sum().tolist()\n",
"dataset_cols = df.columns.tolist()\n",
"dataset_desc = [ code2desc[c] for c in dataset_cols ]\n",
"\n",
"# ---- Show all of that\n",
"df_desc=pd.DataFrame({'Columns':dataset_cols, 'Description':dataset_desc, 'Na':dataset_na})\n",
"pwk.subtitle('Dataset columns :')\n",
"display(df_desc.style.set_properties(**{'text-align': 'left'}))\n",
"\n",
"pwk.subtitle('Have a look :')\n",
"display(df.tail(20))\n",
"print('Shape is : ', df.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 5.2 - Have a look (1 month)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div class=\"comment\">Saved: ./run/figs/SYNOP1-01-one-month</div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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ClrY5NTE8AM9fO6PXBeC+kO35nHPOQWZmZo9et8tLHQmCcBEAO4AzAPhJwq8gCJEAjgH4C4CfAPwLwFxRFGe07b8PwO8ADgBIA7AawP2iKH7Rtr8AwF9EUfxd45oZALYBOBvAHgBvA9CJonhF2/5/A5gD4DwAsQDWggneq1x9DxJ+CaJ7OFxUiye+2uXkSstj8NZjYkoE7jhrDKKC+0e9vIGGKIqobzGjocWMhIgAhdCZVVSLjzfkOFyle4r4cH8smZOOU8bGo7yuFZ9vysXvB4pdCto8cWH+WDwxCfNGxyMuzL8HWksQBNF12EURxdXNCPT1Rligof0Tepi88gY8vWIPiqqbNfenRgdh4Zh4nDkxGSH+g68M4a5jlXj0i52wtSkEEsID8Pw1MxReUz0NCb8KTr7OryAITwFI5ITfW8AEzllt7wPALLwTRVHM1jj/lbZr/rXtfQFcC7/PAEgRRXFJ2/s0AFkAIkRRbBQEoRjADaIorm7b/y8A6ZJwrAUJvwTR9azLLMGLP+531J7VCcCQqCAMiwtBemwwhkQFISEiAJFBvuTm2g/Ym1+Fd3/PcqpzKACIC/dHZJAvwgN94eujR1ltC4qqm1HVaGz3c1Ojg7AgIx6ldS3440CxU63iyCBf1DSZPBJ6tUiODMT09GhkJIUjISIAcWH+8O4HdSUJguj/lNe14JMNOdhXUA29ToC/jxf8DF6IDfVzZOePCvZDXZtHTGldCzILq3HgeI0jLGXuqDhcPS8dKdFBvfxtmKL0170n8MZvh5y8dobFBmN6egzmZ8RhSFTvt7W32ZxdhqdX7FEIwGdOTEKr2QqjxYbIIF+MTQ5HWmywk5dTd9Dbwm9v0ZPC7/8B8BFFcSl3TCaAx0RRXKE6VwCz4L4liuKbbdsKAPgB0AHYC+Afoijub9v3A5gb9HPcZzQBmA8gD0ANgFhRFMvb9l3Sdt2xGu2+BcAtS5cunQyQ8EsQ7qhuNOKbrXnYm1+FkAAfpMeyiXtIVBDCAw0I8vNGs8mKzdllWHeoBHvy5JJFwX7eePSyKRibHN6L34A4WeyiiHWZJdh1rBIh/j4YNyQCY5LDEeSnnXiixWTFsfIG5JTWI7e0Hg2tZoQHGhAe6IuIIAPGJkcoFnS1TSb8tKsQP+zMV9Qo5hmdGIaRiaFIDA9AXFgAfLzYosFis2PrkXL8fqDI4cKthU4AhseH4q+Lx/TJRCQEQfR/Glst+HJzLr7fUeCk0Ossc0fF4vLZwzxyITaarSiqbkZpbQtCAw3ISAo76VCQxlYL/vdrJtYdKnFsM3jrcd2C4Zg3Oo48tzRQC8Ba+Bu8MH5IBJbMHYbh8aHd1pasrCyMHDlyUBkbRFFEdnZ2jwm/7wGoFEXxAe6YzQDeEUVxuercJwBcAGCaKIqmtm2zwQRiAcBdbX8jRVGsEwThDwBfS4Jy2/HFAK4Cc7U+DuaCbWzbd3rbdVNctZ8svwThmupGI77emoeVuwudNL083nodRFF0ivtJigjAk1dMRXx416WjJwY2zUYLfthZgBXb8h3ZQiekRuDqecPbVaAYLTZsPFyKjVml2Jtf5bLPBvl544VrZiA1JrjL208QxODl4PEaPPnVLjRwCQU7Q6CvtyJbssS4IeG4eMZQDI0JRnWjETVNJpTVMW+b4ppmFGt43SRHBuKiGak4dWwCfLyUSYKOltThi83HUFbbguSoQIdFOi02GAEGptjcm1+FF3/cj6oG+XNTooLw8CWTkExVANziiQAMMMXsRTOG4pr5w+Hr3bWJnAAgPz8fQUFBiIiIGBQCsCiKqK6uRmNjI1JTU9W7u83y6y2K4jLumIMAHuctv20Js/4OFg9c5Obzs8Gsvz+1WX43i6L4PLe/EcACyJbfGFEUK9r2Xdx2XSfLrwQJvwThjNlqw7fb8vHZplyYLM5ZgD1h9shY3HPuOAT6dn1KemLg02yyYPvRCsSHB2BkQmiHzzdabNhfUIU9eVUorGRJsirqWx37QwN88OK1M6mEE0EQXcLO3Ao8+fVuhdJteHwIblg4EtEhvmg129BktKCgohE5paz6QWOrBWGBBoQHGhARZEB6XAjGDYlAcmQgcssa8OmGHGw9Wt4l7Qvx98HUYVEYNyQCQ6IC8d32AoUlV01ieABiwvydcj6cOTEJS8/I6BYhbSBy8HgNNh4uhZdegJ+PF3y89CioaMCBwhonRUVcmD/uOXccxg2J6NI2WCwWFBUVwWhsPxxpoODr64vExEStskjdFvN7nSiKs9veBwCoBDBJivkVBOFGAE8CmCeKYl47n58FlhDrx7aY3yGiKF7Vtm8ogGzIMb8lbdde07b/SQDDKeaXIFxjs4sorm5yaCZLa1vw7h/ZiuL0AJAeF4IrZqdBBJBTUo/csnqU17eiptGEFjNzNR0WG4wFY+Ixf3Q8okPIDYroWxwtqcP9n2x3ZOKMDPLFS9fNRGw/T4xVVteC45VNGDskHH4+VK2QIHqajYdL8ex3ex3eT2EBBiw9YzTmjY47aUtbbmk9vt6ahw2HSz3Kf6DXCYgL80dMqD+yTtQ65ueTJdjPG3edPXbAly3qKURRRGFlE9747RD2FVQ7tgsArpqXjiVz06HXDXwrbS9wUtmevcBqAj8GIBHAzQCsAMIA5AK4EcBKAE8AmM9le74KwEsAFoqimKX6zGQASQB2gsX8/hXAfWBuz9Vt2Z63Qs72/BYALy7b87MAZoK5UseAZXu+gbI9E4Q2u/Mq8crKgyira3V5TGp0EG44ZQSmDYt2OYm3mq2w2OwI9ht8mR2J/sWhEzV48NMdDo+GyGBfPHn5FKTFOsfSma02ZBfX4dCJWpyoampzLWyCIAiYmBqJGenRmDosGsFcRlO7KOJYWQO2Hy1HVaMRiyclY4SbWK5jZfXYk18FPx+vNuuPL4L9fODno4efjxe89DoYzVa0mK1t9ZitaDVZ0WKyIru4DttyylFY2QQAiA31w6OXTkFaLLlzE0RPsXr/Cbz80wFInq0xIX7499XTkdDF4T4V9a34YSez1trtomO8iAz2RWJ4ABIiApAYHojYMD9HEqVmowW/7j2B73fko7JB2+o3e0QMzpo8BMU1zY4cDYWVTQpBe9qwKNx97jiEB1LN2q5GFEX8tu8E3l6TpchZMT4lAvdfMKHXyyQNQE5K+H0cTPDleUIUxccFQTgNwP/AavlKdX4L2s7LBxOWTdx5n4iieFubcPs5WAkkI4B9YFbfXdx1lwB4FkAEWMmkG1zU+W0F8Fx/r/P7484CHDpRi0tmDh1UtdKI7qWh1Yy312RhzX6XEQcIMHjhugXDcc6UIT2SjZAgeop9+VX45+c7HclofL31ePCiiZgxPAYV9a1Yd6gEO3MrkFVU127CGgFwuC2GBhiQV96AmiaTYv+ZE5NwwykjFWU/ckrr8cmGHGzrIpdGCYOXDnefOw4LxyRo7jdabNiXX4XtORXYdawSRrMVQ2OCkR4XguHxoZiWHk3ujAThIT/syMfrvx12vE+MCMCzV0/vcwmgbHY7ckrrsb+gBgcKq5Ff0YCkyEBcO384MpKccymYLDbklTfgWHkDwgMMmDkiZlDEivYm1Y1GPPf9PuznrMAh/j64cHoqzp6cTMaFruPk3Z77O31Z+LXZ7bjhtXUob7PKSYkOpqVHn3TmPmJwUlbbglX7TuCXPcdR3yLX3/U3eCG6bbIWBGBMcjiumpveJ2sMEkRXsCevCv/6ZrfDBVoAMCwuBDml9d1yvSA/b4xJCkerxYqmVotT2aiTwVuvg04nKOLzz5mcjPOnpiC5rexIYWUjvt2Wj7WZxTC5SV4XF+aPf5w/XnNBTBAEQxRFfLH5GJavPeLYNjQmGP++ahpCA2jeJDqHzS7is405+HRDDnhJzOCtx2njEjAkKoiVzPLRY3h8KIWXdQ4Sfvuy8Ls3vwoPfLLdaXtyZCD+ft44jEwI64VWEf2F4ppmHCtrcGSEzC2rx968Kqif7vmj47D0jAwSdIlBR2FlIx79Yqdbt//E8ACMS4nAsNhgJEYEIjEiAA0tZmzPqcC2nHIcKa6DOpFnsJ83pg6LRmOrGTtyK7U/mGPWiBgE+/mgpsmI6kYTmkwWtJqYm7PFZne4QPu1LXr8Dex1ZLAvpqZFY2JqBCrqW/HE17tRVK2M1R8aE4zQAB9F+bH20AnA5bOH4ap56VQXmSA4TBYbsoprsTazBKv2nnBsH5UYin9dMc1l6TeC6Aj72jJsu3JVB5hA/NzV0zEqkWSBDkLCb18WfgHmGrdiWx7WH1ImOtAJApbMHYYr5wyDV1uZmUajBQEGL3JRHcRUNrRi/aFSrM0sbteyFBXsi2VnZmDWiNgeah1B9D3qmk148uvdOHSiFgAbWycOjcSCjDhMHhrVbryVxWZHbZMJNU1MyRQaYMCI+FBHopJtR8vxxm+HNAXsuaPicNXcYW5LLomi6LG7YbPRgud/2N+uK3VyZCCmp0djxvAYRAb5IqesHkdL6rFyd6Ei5iwlKgiXz07DvNFx8CIhmBjEFFQ04u01h3GgsMYpFGJCSgQev3wKJZsjuhSLzY51mSVYsS0P+RWNmseEBRjwyk2zyQLcMUj47evCr0RFfSt+3FmAn3cXotUsu7YNiQqEwUuPoppmtJis8PHSOeK3MpLCMHcULVoGCz/vLsTrqw65rScnAJicFoWzJyVjWno09Q2CAEtstWZ/EQRBwKwRMV3utmi22rC/oBomi41Zbw1eiAnx65ZEJnZRxLYj5fjjYDG251Q4FuoCmIX54plDMToxTFOgrqhvxYs/7lfEnAEsKdg5k4dgZEIoEiMCEBHkS6E3xKDhWFkDHvhkm2bt3hnp0Xj4kklO9XMJoqsQRRH7C6qxJ78KzUYLWs027MitQGNbfxwaE4z/XD+TlC+eQ8JvfxF+JcrqWvDCD/uRebzGo+OHxQbj7nPGYZgHybLK6lqwv6Aa9S1m5nJnsSHYzxunjUt0q1WyiyIEgJIh9CLbc8rx2Be7FC7N3nodxqdEIDbUD+GBLCMke9+/y7oQBOEZzUYLth0tR5PRginDoj3KPmsXRXy7LR8frTviMjbY11uPxZOScevpo2jcJwY0x8rqcf8n2x2CBgAkRbBQiMlDozBzRAwpgoge52BhNR74ZLujtNbM4TF49LLJ1Bc9g4Tf/ib8AiwgfsW2PHy49oij4wOAj5dOUVxdQicIuHTWUCyZMwy+nGZIFEUcKanHluwyRbkMrfPnjY7DBdNSEBHkixaTFc0mC46W1ONgYTUOHK9Bq8mK6enRbq0KzSYLsovrkNtW3L2gohERbRaFWSNiqZ5ZJymoaMTfPtjs8AhIiQrCRTNSMXtkLAJ9Kf6IIIiOU9dswsrdx/HjrgLUNZs1j3n00smYPZLCJoiBSW5pPR74VBZ8AwxeeHrJNIqxJPoEq/Yex8s/H3S8XzJ3GK5bMKIXW9RvIOG3Pwq/EuV1LcgurkN4oAEJEQEICzCgvsWMnNJ6HCyswXc78hXCsI+XDhNSIzFtWDSqG41Yd6gEpbUtXd6ukQmhmJAS4UjKUlHfiv2F1cgtrXdKDCMRF+aP86YMwajEMCREBFBKdw+pazbhzvc2o7yexRNGh/jh1ZtmU7ZJgiC6BLPVhnWHSrC/oBrFNc04UdWEJiOLC44L88fbt80jl88BSlWDEQZv/aBM4lTXbMKtb21wKH4CDF7499XT3dbsJoie5u01h7FiWz4Alqjw+WtmYOyQiF5uVZ+HhN/+LPy2R3F1M/678gAOFHrmIu2t12FCagSSIwPh7+MFH289dh2rdIr/6gmC/bwRHeKH8EADwgN9YfDWo9VsRavZCr1Oh1PGxmN6ekyPt6svYbOL+MdHWx2Jevx89Hj5+lluk+cQBEGcDA0tZtzw2jo0GZk17MZTRuLy2Wm93Cqiq7CLInbkVGDFtjwcKKyBv48XHrp4IqYOi+6R61c1GHGgsBqVDa0YnRSOMUnanmQA0GS0YNexStS3mGE0W9FisiI80ICFYxIQ7H9yCvSnvtmDjVmlAIBAXy/8+6rpGE6CL9HHsNlFPPTpduxrW6dHBfvijVvmDUqFVQcg4XcgC78Am8hW7T2B77bn43iVs1uzv8ELs0fGYtaIGExKjVS4RUvkltbj2+352JtfBZ0gsLIbBi/Ehvpj3JAIjBsSDlEEvtuejz8OFjtlQpQQwALzRySEIj0uBEOiArEjpwI/7z7uWEh1hDMmJOK2RRnwNwzOIP8fdxbgtVWHALB7+/jlUzBj+OBWCBAE0f38sCMfr/92GABTur1/+wKEB3Z98i6i57CLIv48WIwvNuXihKpclpdOwAMXTsTc0XHdcu2GFjM+25SL7TnlKKlReqMlRQRg8aRkR2Zyg7ceZbUt+G5HPn7bd0KRAFTC4KXDoglJuGBaiiPHhdh2nZomE6obWfmYjKRwTSFh/aESPPPtXsf7p66c2mPCP0F0lKoGI257e4PDPX/uqFg8fPEkysfgGhJ+B7rwy1Na24IdOeXYV1ANX2895oyKw9RhUV3qslbbZMKWI2Woazaj1WxFi9kKPx8vjEkKx5hk7YnGaLZizYFi7C+oQnFNC4qrm1wmWlETG+qH+y6YgIyk8C77Dv2BmiYj/vL6ekdZkqvmpuPaBcN7uVUEQQwGrDY7lr690aFQPWNCIu45d3wvt4roLLvzKvHu79nIK3ddHk8nAHefOw6Lxid12XVFUcTGrDK8tirTZVy5mkBfL7SYrC5DqDqCThAwJjkMM4bHYHp6NBIjAlHbZMItb653ZHY+c0IS7j533MlfjCC6kS3ZZXji692O99ctGI4zJyaRUlIbEn4Hk/DbX7CLImoaTahqNKKm0YjqJiMsNhH+Pnr4+nhh65FyrDtU4jherxPwxOVTBpVm9vnv9+GPg8UAgITwALx561yKuyMIosfYdawSD3+2AwBbSbx0/cxBp4TszzQbLdhypByr959wCo3yN3hh8cQkzBkVh5d+3I8izhJ873njcfr4xJO+fl2zCf+38iC2HFHWpPbx0mF0Yhgignyx9Ug5WsxWF5/ASI4MxLgh4fDz8YKPlx5bj5a7FeLdkRgeAF8fPXLL2PlRwb5469Z5CKDEkUQ/4P9WHsQve44rtiVGBGDasGhcPjuNcsHIkPBLwm//ZG1mMV79JdNh+fTz0ePFa2d6VNKpv7O/oBr3fbzN8f6ZJdMwOS2qF1tEEMRg5JEvdmJHTgUAINDXGy9cOwNDKedAn6TZZEFuaQNySutx6EQNduZWOoUoGbz1uHhGKi6ZMdQh8NU1m/DgpzscAqWfjx5v3zbfbfnD9rCLIv6+fCsOF9U6tkUG+eK2M0Zjenq0Q5HbarZi/aES/JlZgpKaZtQ2mRwVLiamRuLiGamYkhalcO+UaqKu2J6P/flViooYgb7eLI9IkC8aW8w4Wlrvtp00txL9CaPFhr++u0kzxDHA4IXrFgzHOVOGQK/T9ULr+hQk/JLw23+pqG/F3z/cioq2TMfhgQb8342zERXsi9yyBmQV1SI0wID0uBDEhvoNiPgHi82OZZy74bzRcXj44km93CqCIAYjpbUtuPO9TQ4X0RB/H7x43UwkRwb2cssICbPVhv/8dABrM0tcHqMTgEUTknDt/OGICHJ2k2xsteDuDzY7YoFnDo/B45dP6XSb/jhQhOd/2O94f9akZPzl1JHtWljtooiGFjN0gnDSCa0AFj60I6cC23MqsDuvCiaLHD981qRk3HX22JO+BkH0JM1GC77bno99BdXILq5zUnANjQnGBdNSMD09ejBbgkn4JeG3f1NY2Yi7P9jisABHh/jBZrejutGkOC7Q1xsTUiJw66LRJ6Wx7k1qmox47rt9jqx+fj56vLt0ASKDKaaDIIjeIae0Hvd/vM0xBkcEGTB7ZCyqG02obTLBx0uHiCBfhAcaMCQqCPMz4ihEo4cQRREv/LDfESKjZlhsMBZkxGN+Rny78+LB4zW498OtjvePXToZszpR49lotuKm19ejqi3p1GWz0nDTqSM7/Dldjdlqw/6CauzJq0KAwQuXzU6jfkr0a0wWG3Yfq8Q7f2Q5JZITAIxICMVp4xJx9uRk6AaAcagDkPBLwm//Z19BFR7+dIfCvckVYQEGPH75ZIxM6F9F6vfmV+G57/ahtlkW6m9dNBoXTU/txVYRBEEAh4tq8eAn22G0OGfeVTMyIRRPXjEVIV1guSPc8/mmXCxfe8TxPjU6CMPjQ5AeF4LxKZEdttC//PMBrNp7AgBzU3576TwEGDoWD/vhuiP4bGMuAOat9d6yBYO2YgNB9ARmqw0rtuXj8405mslkJ6dF4b7zx5+0JdhmF7E3vwpT+n6oAAm/JPwODP48WIznvt/neB/k542JqZFobLUgp7ReUUrJx0uHe88bj/kZ8d3eLovNjrLaFoQHGVwuEmx2OzZmlWFLdhl8ffSYNiwak4ZGwdtLh125lVibWYwNh0shPZUCgCVz03HN/PQB4cpNEET/Z19BFR75fCfMHmTqTwwPwNNLpiE2zL8HWjY42ZRVin99s8fxfvHEJNx19tiTmjMaWy34yxvrHJmZz5+agmVnZnh8fnldC/7yxnpHH7nn3HE4Y0LXZY8mCMI1VQ1GrD1UjO1HK3DoRC3snKwXEWTAgxdOxNghEU7nWW12tJit8PfxgpdeO164oKIRL/98ANnFdXjmqmmYPLRPC8Ak/JLwO3DYnVeJ3NIGjEkOw8iEMOh1rH+Looh9BdV4esUeRx00ALhyzjBcPS/d5cN8MhRVN2HV3hNYvb8I9S1mGLx0mJ8Rj8WTkjEqIRSNRgtqGk3Yk1eJ73cUoLwtblnCSyfA4K13uBJKhAUYcN8FEzBpaGSXt5kgCOJkyCmtx5YjZQjy9UZ4m6uz2WpHdaMRBZWN+G5bvkOJFx5owL+umDookhTySEmcfj9QjIZWM8YNicD09GiMT4lo183WarOj1WyDt57ND1qCbHWjEav3F+HzTbmOGNZxQ8LxzFXT4d0Fc93azGI8+90+AGwF+dSSaR5bep5ZsQfrD5cCANLjQvDKTbMHm7slQfQJGlrN+HpLHr7acsyxTScA80bH45KZQ5EeF4KSmmZ8tyMfq/cVObx6vPU6BPt7Y9LQKCzMiEdGcji+2XIMn2/KdXhfxoT64e1b58HXp896dJDwS8Lv4KG4uhmPfrETRTVy2YbhcSG474IJSDrJBC2iKKKwsgnbcyqw7Wi5IoulGi+d4JGLtprJQyNx7/njqW4bQRD9ko2HS/Hc9/scSVhC/H3w7tL5XZK8qK9TUd+KLzbnYu3BEs3yPQZvPaanR2NhRjymDIuCxWbHluxyrD9cgqMl9WgxWRXJa3QC4OvjxRQNgQaEBxpgsYvYlVupsOjEhfnjlRtnd9k9FkURj3yxEztzKwEAwX7eeO3mue3GDO/Nr8IDn2x3vH/pupkYk0ylsQiiN9mZW4EXftiP+hZlne0hUYE4XtmE9laq6vWst16HK+cMw2Wz07pE2dZNkPBLwu/gorHVgqdX7MHe/CrHNoOXDqePT9TUuut0AkYnhmF6erSmhVgURaw/XIrla4+gtLbFaT/AElO1mt3HwgX7eeOcyUMAANtzKnCsraxETIgfFmTEY8GYeKRGB5GbM0EQ/ZqDhdV47MtdDq+WC6en4rZFo3u5Vd2HXRSxcvdxvP9Hdrs1ayUCDF6w2OweuZC7IyrYF89cNb3Ls2/XNpmw7J2NqGliOShGxIfixetmuLRcG81W3PrWBpTVMQ+n+aPj8BBVKSCIPkFVgxEv/3wAu45VujzG11sPs9UGd3abUYmhuPuccRgSFdQNrexSSPgl4XfwYbOL+HZ7Hj5ce9QpDbwrwgIMWDQhEaeMSUBiRAC89DpUNRjx6q+Z2Ha03Ol4nQBMS4/BWZOSMCUtGjmldfhlz3GsO1QKk8UGPx89IgJ9ERnii3mj4nDauEQYvOWFQ3WjES0mKxIjAkjgJQhiQMHHo3rpBLy9dD4SwgN6uVUnhyiK2F9YjbWZJWg2WhERxKyxO3IrkXm8RnFsUkQAFk9KRmp0MHYeq8COoxUKjyRXSNZeazuC8bgh4Vg8MRlzRsV2W8biQydq8I+PtsHWtho+c2ISzp6UDADw8dIjKTLQEXr01prD+HZbPgAg0NcL7yydTx5MBNHHyCmtx7fb8rD+cKnjuZ6SFoWLZwzFxFQWC2y22pFf0Yh1h0qw/lAJappM8PXW48ZTRuCcKSmOZ76PQ8IvCb+Dl7zyBjz33T4UVDZ26Dy9TkBcqD9qmk1o4WJy/X28MDktEtPTYzB1WJRm5jyb3Q6TxU7ZLQmCGLSIooh7P9rmEApnj4zFo5dO7uVWdY4mowW/7j2OX/ecQHE7AmxSRACWnTkGE1MjnJSaBW0LyrWZxQ4LaWp0EBaOiceckXGICPaFwUvnOM9mZ/G/9S1m1DSZUNNoRKvZitFJ4T1WZ/nbbXl4a02W5r6kiADcdOoohAX64O4PtjgsRn8/bxwWjackVwTRV6lsaMXe/CoMjwtFSrRrK67NLiKvvAExIX79LXSFhF8Sfgc3ZqsNW46Uo7qt5qCa2iYT/jhY7HDvcsXZk5Nx0ykjEeDbsbIPBEEQg5EjJXW4873NjvcvXjcTY/tZDOimrFK8tupQu/ODXifgsllpWDJ3WLuWWFEUcaKqCV56HeL7uDVcFEU8vWIPNmaVuTzGx0vnsFJPGhqJZ5ZMI28mgiB6E80BiExSxKDBx0uPBe2UPLrhlBHYnlOB1fuKkFNWj6oGWVBOCA/A384Zi3Ea6eEJgiAIbUbEh2LhmHiszSwBALy95jD+78b+kf23utGI11YdwuZspdDnb/DCqWMTMDIhFLXNJtQ0maAXBJwyNgFDY4I9+mxBEJDc92PmALC23nPuePgbvJBXLntQFVc3O+KbJcHX11t/0qWWCIIgugsSfgmCQ6/TYdaIWMwaEQuAJe8ormmBxWZDWmxIX85oRxAE0We5YeEIbMoqg8Vmx9GSeqzZX9Tn675uOVKGl348oKgdHx5owHULhmNBRnxfLu/RLfgbvHDPueMV2+qaTfhsYy5+3l3oiB28fuEIxIZSXWeCIPomg2vkJogO4uvjhbRYz7T4BEEQhDYxof64aHoqvmyrNfnm6sOYkBKBmB4WkkRRRHZxHbYeLYfdLiIjKRxjksMR5CeHsVhsdrz/Rza+3Z6vOPfMiUm4+bRRCKSQFwehAQYsOzMD509LwZr9RYgO8cPiiX1bqUEQxOCGhF+CIAiCILqdJXOHYWN2KUpqWtBisuLFH/fjuWtmnLT7c0OrGbtyK7E9pwL7Cqpgtdnh5+MFPx8vBLbVxo0I8oVeJ2DLkTJHkikA+HprHgQAQ6KCEBLgAz8fL5TXtSC/QnbtjQr2xb3njceE1MiTaudAJiE8ANcvHNHbzSAIgmgXEn4JgiAIguh2fH28cN/5E3DPcpYR+EBhDb7bno+LZwzt1OfVNpnw5urD2HC4FHZV8s4mo2d1dgFABFglAI3SlzPSo/H388cj2K9fZTglCIIgXEDCL0EQBEEQPcKoxDBcMXsYPtuUCwD44M8jmJQaiVQPk0QBzHV5zYEivLU6SxGP6ykBBi/MGRWLID8fHCisRm5pg5PwrNcJuOnUkbhoeiolbiIIghhAkPBLEARBEESPcdW8dOzIrUBuWQMsNjv+/uFWXLdgOM6ZMgR6nfukgnXNJjz//T7szqtSbB8RH4oZw6MxPT0aUcF+aDFb0WqyotFoQU2jCdVNRjQZLUiPC8GUtChFGaJmkwUnqprR2naO2WrHqMTQHo9HJgiCILofqvNLEARBEESPcryyEbe/u8lRHgcAUqOD8NezxiAjSbsGcGltCx76bDtKaloc22JD/XDX2eMwaSjF4xIEQRAKNN12qG4LQRAEQRA9SnJUEJ5ZMg3x4bJ1Nb+iEfd+uBXf78iHWjGfU1qPv32w2SH4CgAump6Kt26dR4IvQRAE4THk9kwQBEEQRI8zdkgE3rp1HlZsy8fnG3NgstphF4E3fjuMoupmLD1jNBpaLFh/uATL1x5Bq9kGAPDW6/DgRRMxe2RsL38DgiAIor9Bwi9BEARBEL2Cj5ceV84ZhlPHJuDpFXuQXVwHAPhpVyF25lagor4Vds4IHOjrhScun4oxydqu0QRBEAThDo/cngVBuEMQhF2CIJgEQViu2neqIAjZgiC0CIKwVhCEIdw+QRCE5wRBqG77e17g0iYKgpDSdk5L22ecpvrsJYIgFAqC0CwIwveCIIRz+wyCILwvCEKDIAhlgiDc0+m7QBAEQRBErxEd4ofnr5mBBRnxjm1ldUrBNyrYF/+5fhYJvgRBEESn8TTmtwTAUwDe5zcKghAJ4FsAjwAIB7ALwJfcIbcAuADAeADjAJwD4FZu/+cA9gKIAPAwgG8EQYhq++wMAG8BuAZADIAWAHymqscBpAMYAmAhgPsEQTjTw+9DEARBEEQfwuCtxwMXTsBVc9MV28ckh+OOxWPw1q3zMCQqqJdaRxAEQQwEPHJ7FkXxWwAQBGEKgERu10UADomi+HXb/scBVAmCMFIUxWwA1wF4SRTForb9LwG4GcCbgiAMBzAJwCJRFFsBrBAE4W8ALgbwJoCrAPwkiuKGtnMfAZAlCEKQKIqNAK4FcIMoirUAagVBeAfA9QBWdfZmEARBEATRewiCgGsXDMfE1AicqG7GlLQoRIf49XazCIIgiAHCycb8ZgDYL70RRbFZEIRjbduz1fvbXmdw5+a1CbKu9m/hPvuYIAhmAMMFQcgDEK/x2RdoNVIQhFsA3LJ06VIAwLJlyzr0JQmCIAiC6Hl+7u0GEARBEP0V8fXXX3cqd3SypY4CAdSrttUDCHKxvx5AYFvcb0fP5fcHcu+1zlUgiuLboihOcftNCIIgCIIgCIIgiAHLyVp+mwAEq7YFA2h0sT8YQJMoiqIgCB09l9/fxL03apyriZb0T3QcQRB2kTKB6OtQPyX6A9RPif4A9VOir0N9lPCUk7X8HgJLZgUAEAQhAEBa23an/W2v+X1DBUEIcrOf/+yhAAwAjrbF+Za6+WyCIAiCIAiCIAiCcOBpqSMvQRB8AegB6AVB8BUEwQvAdwDGCIJwcdv+RwEcaEt2BQAfAbhHEIQEQRDiAfwdwHIAEEXxKIB9AB5r+7wLwTJCr2g791MA5wqCMLdNqH4SwLdcjPBHAP4pCEKYIAgjwRJpLe/0nSAIgiAIgiAIgiAGLJ5afv8JoBXAAwCubnv9T1EUK8GyMz8NoBbAdABXcOe9BeAnAAcBZAJY2bZN4goAU9rOfRbAJW2fCVEUDwG4DUwIrgCL5+UzVT0G4BiAQgDrAbwgiiJleu4Z3u7tBhCEB1A/JfoD1E+J/gD1U6KvQ32U8AhBFMX2jyIIgiAIgiAIgiCIfszJxvwSBEEQBEEQBEEQRJ+HhF+CIAiCIAiCIAhiwEPCL0EQBEEQBEEQBDHgIeGXIAiCIAiCIAiCGPCQ8EsQBEEQBEEQBEEMeEj4JQiCIAiCIAiCIAY8g0r4XbZsmbhs2TKq7UQQBEEQBEEQBDHI8OrtBvQSJAATBEEQBEEQBEEMTAStjYNV+CUIgiAIgiC6A7MJOLwXOHoQOHoAKCoAxk8HbnsYEDTXowRBED0CCb8EQRAEQRBE12AxA48vBSpKlNt3bwKK8oGkob3TLoIgCAyymF+CIAiCIAiiG8k95Cz4ShTl9WxbCIIgVJDwSxAEQRAEQXQNtdXy6+Q0YPIc+X1RQY83hyAIgofcngFYLBYUFRXBaDT2dlO6FV9fXyQmJsLb27u3m0J0htXfAns2AedeDWRM6u3WEARBEIQz9TXy6xHjgLRRzOUZAIoLeqVJBEEQEiT8AigqKkJQUBBSUlIgDNBEDKIoorq6GkVFRUhNTe3t5hAdpbIM+PodQBSBd54Fnl0O+Pr3dqsIgiAIQgkv/IZGAAncmqOvCr9fvgVs+R04/xrglPN6uzUEQXQjver2LAiCQRCE9wRBKBQEoVEQhL2CICxu25ciCIIoCEIT9/cId64gCMJzgiBUt/09L3RScjUajYiIiBiwgi8ACIKAiIiIAW/dHrAcPcAEXwBoagD++LF320MQBEEQWtRxbs8h4UB0PODV5nFWWwU0NfZOu1xRXwus+Q5obgS+fBuoLu/tFhEE0Y30dsyvF4ATAOYDCAHwCICvBEFI4Y4JFUUxsO3vX9z2WwBcAGA8gHEAzgFwa2cbMpAFX4nB8B0HLDmZyve/fQO0NPdOWwiCIAjCFbzlNyQc0OuB+GR5W3F+z7fJHVWl8mubFVj5Re+1hSCIbqdXhV9RFJtFUXxcFMUCURTtoij+DCAfwGQPTr8OwEuiKBaJolgM4CUA13djcwmi9ziqEn5bmoA/vu+VphAEQRCES+pUwi/Qt12fqyuV7zevZqFGBEEMSHrb8qtAEIQYAMMBHOI2FwqCUCQIwgeCIERy2zMA7Ofe72/bpvW5twiCsKvLG9xF1NXV4fXXX++SzyooKMCYMWO65LOIPkJ9jXbZiNXfMiGYIAiCIABg1dfAyw8DBUd75/qi6BzzCwCJKfK2oj5m+a2uUL632YCVn/VOWwiC6Hb6jPArCII3gE8BfCiKYjaAKgBTAQwBswQHte2XCARQz72vBxCoFfcriuLboihO6a62nyxdKfwSAxDe5TltFBCTwF63NrM4JYIgCIIozAG+eQ84tBv4/I3eaUNrC2A2sdc+BsCvLTFjQop8TF+z/NZUOG/b8jtQ7qJWMdE+Viuw/GXgwRuAgzt7uzUEoaBPZHsWBEEH4GMAZgB3AIAoik0AJGttuSAIdwAoFQQhWBTFBgBNAIK5jwkG0CSKUlagTvKXM0/qdLe8u0pz8wMPPIBjx45hwoQJOP300xEdHY2vvvoKJpMJF154IZ544gkUFBRg8eLFmDNnDrZs2YKEhAT88MMP8PPzw+7du3HjjTfC398fc+bM0bwG0Y/hXZ5HjGexU+8+z96v+Q447QIgIKhXmkYQBEH0EfZvl1/nHwFMRsDg27NtUMf7SvaIRN7tuZBZiPtKHhLe8mvwA0ytgN3OrL833tt77erP/PolsOk39vqLN4GxU3u3PQTB0euW3zZL7XsAYgBcLIqixcWhklArjZaHwJJdSYyH0l263/Dss88iLS0N+/btw+mnn46cnBzs2LED+/btw+7du7FhwwYAQE5ODm6//XYcOnQIoaGhWLFiBQDghhtuwCuvvIKtW7f25tcguoscrlsPHwNMmw/EJrH3xhblgocgCIIYnPAWNru9d1yf+UzPoeHy65BwILDNXmFs6VsZlXnL7wXXyq+3/glUljofT7jn+DHgZ85tvLyYYqiJPkWvC78A3gAwCsC5oii2ShsFQZguCMIIQRB0giBEAHgFwDpRFCVX548A3CMIQoIgCPEA/g5geQ+3vctZvXo1Vq9ejYkTJ2LSpEnIzs5GTk4OACA1NRUTJkwAAEyePBkFBQWor69HXV0d5s+fDwC45ppreqvpRHfQ0gwU5bHXgo65Pev0wKzT5GPIpYggCGJw01DnLOweO9zz7VBbfiUEQen6XFTQUy1qH97yO30hMGoiey3agT2be6dN/RWrBXj/RRY3zXN4T++0hyA06FW3Z0EQhoCVJzIBKOPCdW8FYAfwDIBoAA0A1gC4kjv9LQBDARxse/9u27aTw4Vrck8hiiIefPBB3HqrsmpTQUEBDAaD471er0draytEUaQSRgOZY4fl+r5JqYBfAHs9dirw7Qfs9aHdbKLR63unjQRBEETvcmiXPFdI5Gb1fDtcCb8AE36PHGCviwuACTN6qlWuaWlm+TMAwNsHCAphAnDWXrbt4E7gjEvk47P3Ays/Z7HNEnHJwJVLAf+Anmt3X+WnT7UTmh3eA8w/q+fbQxAa9Hapo0JRFAVRFH25Wr6Boih+Kori56IopoqiGCCKYpwoiteKoljGnSuKonifKIrhbX/3nXS8by8RFBSExkZW9P2MM87A+++/j6YmlsW3uLgYFRUayRjaCA0NRUhICDZt2gQA+PTTT10eS/RD+GRX6VwW78RUIKwt+XlLE5DXC4scNcYW4OWHgEdvdZ/QRBSBz14H/nkzuWwTBNExGuqAZ+8Bnv8HuaTyaHkA5WU5C8TdjcLtOUK5j4/77SsZn3mX5/AoZqEew1XbzMmUhWObDXjnWSBrH7OyS39bfwe+fqdHm90nKcgBfv1Kfj+Xy6GTtQ+w25xOIYjeoC+4PQ96IiIiMHv2bIwZMwZr1qzBkiVLMHPmTIwdOxaXXHKJQzB2xQcffIDbb78dM2fOhJ+fXw+1mugRXAm/gqBMIOGp67PJCJQUds8k9PsPwKE97PO/+9D1cUcPAn/+CJSdAN7+d+cXsE0NwIm8nl/cEQTRe/zyJZB7mI0jrz7OlG6DHZsNyNwtv5e8gJoaWLxlT9Ke5VeiuA8KvxEx7H9oBJA8jL222YDDbVbgQ7uA+lrtz9n0G8u2PRAxGZlg2+x+LYqfP2Ox5gAwfCxwzV+BkDD2vqUJKMzt3nYShIf0iWzPBPDZZ8qacnfddZfTMZmZsiB0771yBsLJkydj/3655PHjjz/e9Q0keh6LGcjnYrjSVfWbx04DNvzKXh/YAVx0g/vPa2oEnr0bKCsCFl0MXHZz17XVbgM2/iq/z9zFtOV+Gm5ge7nEbCYj8MF/gHufA3Qe6uJqq5h2ecOvLL7orCuAi64/qeYTBNFPOLhDfl1SCLz3IrD0n56PHwORvCy55ntYJLOwSgrRY1lAbGLPtaXOnfA7RH5dVsTmOG+fnmmXK6pVll+JcVOB423C2sEdwOQ5wJY/5P1zzwTmLgZ++JApfUWRZTW+78W+k8X6ZCg7AWxew5RMBUeZEiA8GnjkFSAo1Pn4mkqlJ9fVf2X5SUZPAra23bfDe4HUET3SfIJwxyCeLQiiEzQ3spiWnRu6/1r5R5lwB7DavpIGVWLUBEDfpr8qymeTjzs+e40tOABg3c9yLUaJbX8CK79g1oKOkrlbuYiwWoB9GtnHRRHYt0W57ehB4I8f2r+GxczcpR+8gVmOpXuz4RdypyKIwUB5sbMlc+8WNiZ3F7s2At9/yBIfeTo21tcCP3wMbF4tj1PdCe/5M3YqMCxDft/TSa94y2+oSvj19QciY9lru12ej3oTft6KiJZfqz2rmhuVc9ppFwBDR7BYX8nSnnOoZ9YGJ8O2P4FfvmCKZ1e0NAFP/40pmY9lycmraiqAVV9rn7PpN5YgDABGtpVkBIDRE+VjKOnVwKCpAXjmb6yW+K4+3t9dQJZfgugI37wHbGxLiubnD4yZ0vHPqKkEvlsOJA1lFlhX7Fgnv07PcN7v68dci6TEHJm7gHmLtT9r9ybl55lNTOiU2n9ot1w7eN3PwM0PsLJKnrJ+pfO2nRuBmacptxXlA1UaJS6+/QAYO0Uu4aTFZ6/L956nqYEpCtJGed5egiD6H7yQ52OQFXg/fcrG00mzu/Z62fuBN59WbktIAU45F5h3lmsL32evsTEXYELw4suBOYu6z8qpFn55j5tjPZwPQmH5jXDen5gCVLWlbynKZ79bb6KI+eWE39QRrDRTUwNTZny7XFZkJA+TXbhjk4BTLwBWs9KT+OZdYPz0nq+v7AnZ++V5vrkJuPQv2sdl7ZPjnNWs/ZmtW3irvs2mnJvnny2/HsUJv7mHAWMrW7sQ/ZeCo0BeNvs7lgVMmdfbLeowZPlto5/myuoQg+E7ditWK7MCSHz/UcfjTe024H+PMzegr95hQqcW2fuZECox3kVWTE/ifhvqgI9fdd5+gHMf3PK7/Lq2Cnjhvrb4HQ8sqtUVwAGNax/a7RwjtJez+k6eIy98LGbg/ZdcX68gh2mWJYaOZIK/RHeWe7LbgR8/AR69RXmfCILoWfjn/JKblAvr5S8rky11BZtXO28rLmDj6ev/YqEkakxG5dhaUwl8+j/goRtZjoKuprZK/ly9F/MIShkuu4GXFLKMxj2BsRUwtVWs9PIGAgKdj+GTXm1f17E5VBS7PseDK8uvTg9kcImveAXvLJVS95wlLEs0wH7v377p2jZ2FbzletcG1/cy55D8etZpwMtfAMlp7L3ZBPyqsv4e2MH6IcBcoifOlPeFRsiKApuVKd2JvovVKsdtuyIvW349dGT3tqebIOEXgK+vL6qrqwe0cCiKIqqrq+Hr2we1kf2FoweU2tCCo8pFjidsWs0KwEtsX+t8jLEFWP4f+f3YqcCEmc7HASwuSeLwXiZE8ogiW3g1tZXH5i0PB3ey/WYTsG+b6jw7E+6Xv9z+d9q4SnZ3khZeAJvo1K7PfLzvlHnAjffKrtt52douY6IIfPGGPFGPmwY8+DJw6vnK79Id2O3AJ68y4bfkOLuX6ntMEET3YzLKZXIAphC89UEgsi1JUUsT8OF/PReOaquULrpqLGbl+JWcpiwnt3cL8OTtzm7FRw5ojxG1VUyh2NXwY9/wMcy12NcPSGxTLIoikJ/tfF5LE1MqdqVgrHZ51rKM83NZ5k4WV+oJa38CbjuXKR3UNWRPBj5ciBd+ATbXqNHrgWkLlNv8A4ALr5ff//lj3wzFyZZzw6C6Aig9rn0cn2hzylwm0J53jbxt3c9KRROvGJh7BlN88IyeJL+WkofxiCJzgW9P6CK6l5LjwD+uBv5xlfuQhLwj8ut+GsNNbs8AEhMTUVRUhMrKdmIm+zm+vr5ITDzJxBdVZcxVKWNy7yeq6Gn2asSw/vARmyA9SXDR0szcndWfqU768dU7smuwfyBw3d9cf35MIhAVxzImm1qB3ENKa8jujbL7HQDc+hAr1WAysnPKi5klQ9LWR8ayhCnS5Lfld6bVjo7Xvr7V6uzuVF3OFAMAE2ZnL2Kvq8uBE22Cv5c3KyfhF8BqKP7yBdv+06fA1HlM6y6xYx1zlwKYoHzZLex+jJrIFiI2G8uyWV/jnGDlZLDbgY/+yxQWEiYjc7HuiEt4X8ZmY8lcouOB+CHtH09oU17CsteOnep+XGxpYi6FI8YDgUGdu1Z9LbOeZExi48NgIWuf7HaakCILKtffA7x4P3t9cCez1s45o53P2gv852FAJwAP/hdISXc+JnO3XMs1Kg545H9snPx2ORNuAOYy+/x9TBknfQYvjC44h7Vzxfvs/aE9bMz06sKlF+9Nw3sCpY2SEzblHmYCSNZe5qVz9ICcKV/QMQ+cEWOBqQtYHGtn4QUiV2NxynDglPPke/jlmywulE82pcbYykKObFb2fdevZJ9xslgtcpsFQS4fKJExmW3nFSpjpgDBoc6fNWcRWw/U1/bNUJymBufyUgd3Oo/7xhZZQS8Icvz4+OmsjxfksPv2y5fAkmVAZZnswSYILAmYmoxJwJpv2Wt13K/ZBPzfI0xpFJ/M1ih8VnCi51j7E9BYx15//yFw28POx4giUEDC74DA29sbqamp7R842Mk/wtxhzSZg4TnAVXf0dot6DlHUTuB0/BjbPnEWuz8HdrAszFoLiJ8/Axrrldtam9mCaEKbW3PmLjmDM8AmF3WtRB6p5JG0kNi+VhZ+TUbgy7flY+ctZtcZNVH+Lgd3KmPCZiwEzr0aePlhIHsf27Zvq+vY5APbZW1/SBjT6tdXA1+/y7Zl7WWTbmCwUnkwcoIcl3bGxcDaH9lCs6yIucLNPFX+Dt+8J5932vly5lL/ADYxS9agzF2yoH2ytDazGGMpSyXPkf2uhd/6GmbJGD1RtoD3Zb77EFj1FVNG/OsdICq2+65lMTNFgo8PMOt09wqjXRuZsmTOGUBAJ4XEnqK2Cnj6TibYzlsMXOucqR8A61NP3QlUlABD0oGH/6tU8niCychq3FaWAmmjgQf/0/45AwV1XKvEyPHMC0RKmvfFW2yMU1vxeH76jHmr2ACs+4kJ0Gr4RC5T57H+6uvPxuRRE1iW+pYmJpCt+ootFEVRmY168hzWvvUrmULT2MIUlCPHd+YOONPUqBQmJnIxz8NGs8UswJSgB3Zol+IR7UxIPp4LrPkOeORV1j87g7syRzwX38jG64oSNu4vfxm4+2nXY8LezcoETd9/xKyvgcGda6dEbbUs2IaEO1ssA4OZWyc/R846XfuzdHpgzFTZVf7gTs+EX7sd2LKGKXZnnNJ9maJ5rwmJgzuZ8pnnWJbsyZWQIivYBAE4/1omqAJsnSKKTHku3cOMKdpzSPoYdm+tFuaGn7mLKRFEEfjo/+S2lRxnY+SVS1k2bU/vhSiy9crRTNYv4tzkDiFcw3ux7N7MFBvq37OyVE785x/IkrH2Q8jtebBhMbMB4qdPgTeeYkKTJ25iddXAa0/KCUY2r2Ha2MFCYa4c0+IfyDI9Sny7HPjvP4Gn72L39eUH5bITEmUngD++l9/zST6kRZbZBHz0irx94ixg+sL228bH12xazSwkAMvKyMfhXNKW3IJ35dq1kQmwElPnM2vqDO66WhZvCT5L8+wzmEUjIkaOA7HZWJZUQKk8mMjFMAcEAadfJL//6VPZre2nz5Tf4ewlyut3ptaxO1qamZLi/uuUgq+UuRLQXkRIvP0sS97173uU7u19EWOLvDi2WpQWpK7GYmbjx6f/Y0KDlru/xNGDLMnQ1++2uZX2cMKejvLHD/Lzvmuja9e9r95hi32ACSF8WRBP+fUruS72scMsnt8VhTnAW/9mXhXq8ai/IYquhV+AlXmTFmHGNmHK1bxWUqiMO9y33dlFVR0KMnW+cv/EWcC9z8rv925hgl9Zkey1Y/BjiQo7W5PdE/ZtkcfK1BHKhepQTvAqOe4s+Ao6ZtEWVMtALbdUT+GTXblT2hp8gRv+Lgs3h/ewrP2u2KJSQrY0sURiJ0s1l3zRlbKE/+38A7VdobWO9fR3/ulT1l/fe8H9uHiyaM1bOZnOia14l2d1ecUxU+S53Wph8wf/LM0/S/vaBl+l6/P/nmDKmNXfsuzTPBYzE4jfekYe61whikyQfvYe4KUH2b185dGujwsfDBhbgROcZ4BoV65ZJfJVVt9+WtaLhN/BgigyS9adlwDP38smjt2b2DY+sZIWFjMTlHmXJrOpY/Gudnv3xnN0xWe7GzD58jzjp7Pasj4G9r70OBuAJVpbnAWJr96RFynpGcD1d3OfvY3d49++kTNPBgYD19zp2cAycgIwbrr8fvl/mDaWL0lw8Q3MUgooM1QfOywrNOKSZReo8dPlRVHuYdkVhid7vzyh6nTAvDPlfXz2v1+/YgtwfpJUJ/A67UJZw1xRwiwl77/ILCpa30GCX2xILoWe0tTABLF/XA38fQn7u3cJsyrwwsKcRcDdz8jvcw9rx/SVl8j3w2Zl7e9MmZPdm4B//ZW5lXUn29fJ7u4As2i7w27r3KLCbAJefVz5jPCu5Gp2rpdfV1ew8erXrzv2jFvMwJvPMCVEe+VUvngTeOQW4O1/A+tWMkHB0+9pbAHWc4v2libtOLqDO50zlXc0KU5VmfM5/EKERxSBd55n9/Lb5UyZ88PH2gma+gMlhfLY6OfPrN48DmGqbczK2qsM9+BZrxKymuqBXJWC5eBO+dmISVAmaZJIHiZn4bfZmMWPt/qOnihbErtL+OWfFXXG1cgY5/J43j7Ma+vOJ4H/+xr49wfsP2/9Kz3R+fbUe+D2LJGeASzilJ7ffaQ9ftdUyl5IPOtWOrvxdhR38b4SU+fLv+P8s9yHNYyeJCcak0Jx3FFZxuZHia0dTKhoMTOFrfTnbtzi432l72CzOSs7jroRfgWBKZq01iWxSe4VA0uWyvfYamHKUN6ra8pcpQv2ro3AwzexeVRd3gxgY+2L9zPDA68grSxl44U7uiNxWn+n4Khs8ZfYuMo5aala+O2nkPA7WMjex6y8Wov2L950bc0SReDT17StL/zE64q6avb5d14CPH6b84PkDruNDXrtDVJrfwaWnc8SYXQ2ycTKL4Cl57EFsNYim7d+TpjJYn7cxRzt5LJCH8+VFQWCAFxxG1s48ZaKDb8qJ8ELr9eOK9JCEIBr75SFx+oK4Jm75d96SLrSVSs8SnsxJ7n2AczKOqxtgSnagf0qRYcosiRQErNOl+s3Amwik6gsZQtw6b4OHelsFfAPUC6EPntdmVk5PUPb3Sx+iFyeorXZ85qWOZnAE8vYglVKfFNfo6x9HBXH3CGv/RuLBZPcra0W7edhtypZV1F+x+uPHjnA+mBhDrMgl5d07HxPEUXn8lRHM10/P6UnmJLgniuZZdzTJDkmI/DKY85xXkcOsNg4rXaphQObDVjxHrMEePp8r/+FeVQcOwys/Nz1cSfygN+/ZwLrjvUsudmjtwDP/V1b4aNm42/OlhN+8QiwMe/D/zqfm3tYmTWzPb5+13n81kpkBLDPLeOEmNZm1hcf7qaMw90N3ydGT9KOmR02moVFSPz4ifNYbjJqhzKolZV84r2p810rIedxlq4Nvyqt+bzAO2K8LECVFCotjur2lZ3wTGnWWC97+QDKMRdgbZ7dFvvsY2ChK88uZ+FK46bJikT/AKVCtOwkhF9FmSMP8i9ccJ0cZ9tUry3kbvtTXgOMmiiH9Yh25uLe3vrAZHSdBZz/HcJdCL8xCcDD/wcs/Sdz+3WHFIojwSv8tPjmXeVvnb3fMy8Nu419979eDNzJ/T14gzJ7tURDnSwQ6r2ABVwpIv7ZspiVwo1WeM/I8cAD/2GuydLftXcB/3hOmRBOTWQs8I/n5XWCzSoLW2mjgZv+we4zX67RbmfrgH/erAwHA5jg7Grd6s47a/Ma4I6LmEGnJ2pw9xdyNdZOJqPzfVdkeibht1cQBCFcEITvBEFoFgShUBCEJe2fNQCwWtikdzTT88yzvNtQeBSLp0hqS11vswFvPK09Ie9Ypywxs+Ac+fXBnUxw06KmkgnND1zPFpfGFmZRcWfx4TmRBzy2lGn+pLp0rlj5ObsnezZ3rsD8lt9ZIiqrhS2AJTddifISZkkFmMZUWiiceRlLAOHlzWJ17ubqQWbtka0svKVh6jwmjAqCcrHyxVuy4JU0lGVM7AihEcBVt8vveYveFbfJ2mgJtdsg4Gw54LNy7lMtDrP3yZZcvR4450rl/vAoZmHQYuIs7e2nnq8d3znzNOCup5y/A8DuI69t1rKqGFvZ77rpN/a34n0Wuy65U6uJSWBWpKfeZVZf6bojuDg9rclVq+/9+pVr65ya6nL2HPKZTLUWg11B/lFnt+zWZteu2r99w4TVxjpmGX+gzZLIx+GpsdmYQor/DpKCRrQDezQsc6UnZLdRX39lGYXdm9i1PYFXnLhbCLkSPnMPAy8+4N6t2GYDfv/OeXuOSvj94k158R0UwrwqJKTaoO2RvV/bkumqb/ECHh/H2NzIFEtdbfWw29h4UFnWtZ8rwT/X7qxLZ13B3I0BttjnS9MBTCEiCRf8fdm3Vb4nJqMqFMRNDcspc+Uxq6pc2df4Mdbgq4zz1SoN19LMYsf/eTNTFr/0AFM0SXOPmj2bZeE+bZS25fLC64DH3wBe/BS47GbXAikfI1lW1Pn+wSu0Qj0Qfr19lPOOegwVRWVfnnUacMWt8picvQ/Yr6pU4GhLDfO4uvtyprhTW/wBzyy/AJuTJ8/xLFHZ2HbmIwmtZ9pma98zwG5jHku/f+csvGl5hwDKfpk6XLn2kKo+ACy8S1pTRsW5dl1PG8Xma+lv3mLPlB2SABwVJ28LiwSW/ZP1BYMvE6Tve4F5tEmIdjZuSc/C8WPOiTbPulx+z1u5eew2pkQ0tbLnpzuyr3c1djtLKNaeB9PJwhsO+LHqjx/kfma1KNcIZPntNV4DYAYQA+AqAG8IgpDh/pQ+iijKVh/eFUSL7z5kE+Pz97JJ8oX72CKbt1rxGFuVC81lj7AMwn99nFn4AKZ1/d+TzotZfsKYcQoTsKR4VavFuUROdQWrgfjQjSweRD04Z7YzsIsic2d6+i7ZfXD7WuUkxdNQp9Tq/vhJx8og5B1h8SU8P36stDDxsaqjJ8rF6wODgIf+D3jjR+Av97HMkHys697NTOjfxsXx8MoDPo6Mdze54raOJ8IBWKKHyXOU26YvlF3zeMaqFpAJKcq4VkAp/B7aI/cNUQS+5+KtZi9SWn0lrroDePp9NpnNOIUJleOmubaYS5mfJXwMTAi96V5WusMV7lwKy4qAR25mz9Xyl9nfr1/Ji8aAIKbRf/FT9vfS50zonX26sxZ7xDj5tXpyLTshW9S8vGW3TLud1S9uT0llMrLnTypJJdGeK3Jn2bBSe7vWosFuc15gtjTJ8VWurLHfvKesY33h9cAFnOVES1nA/34Zk4D7XlQ+M798yRQZ7igukLPcAmzscGVp4+Mgx01jfV5ynS0uAF68T9tCDbCFq2Rl4QWpnEx5MZm9X7l4v+ZOZu1yfMbm9gVGk5EJ0BJ8fev8o87WTYuZKS0l/vYUG5+kkmI5mcwt2BPqqtnzUqCRKInnjx+B5//BnrVDe9wf21HMJqVVgq+9qiYoRFkC7adPlf2Tn8/OWcIULIDSVfLADnkujU92n3nW20c7yV7SUOfMwe25Pq/8jCmIAXb9rH1M2fPYbcxFlO/TgCohlyomWUIQmJdPe1nBQ8Lle9HS5F7pw1NynIW0SLHsnmR7VsO3fe8W5ZqhMEdeBxh8gUmz2e/Bjwm/f6/8PIuZJXp84HqmXDKb2PP49bvObv+8ldSV5bej8OUHD+3WduW22ZTPtJ+//Fq9plKf996LyjHF4CsrfAD27KvXXfy4PnI8E1qkZGH1NXIVBnfxvl1FRDQTgEeOZ8/JXx937ivDx7KY+vtflF2hrRY2l1qt7N5JY+yYKcDVdyjzoxw5oO3Bl5ulnGN/+dJz5XRnMJvYepafBzvKT5+yBKSPL+0+5aLdrlQEX7lUDpmoq5a9PIvy5b4VGSvLD/2Qfiv8CoIQAOBiAI+IotgkiuImAD8CuMb9mX2UIweYELtjPXMzcCXI2m1KjZfFzM5d8b5rF8s9XKbEuGQ5k2N4FNO4SYuiE8eAX7k4w8Z6udi5IACX3sz+85pwPlnTp/9jQu/6lcrBN3mY/PpopmtrscnIXBs/edV58N6lsVAGnF34youBHR4mjairBl5/0vlaJceVFgPe6qm2Wup0Spe4Kap7s22tbIWNS1ZOKAkpLE6GZ8pcpZDVEQSBTQJBIey9wZdl1dQibZScbRnQtm7ExMsLP4tZHsAP75G1hHov4Owrnc/lP2PeYrb4fvo9FmsmKQ+0WHQRSyY2dT4rLTLbRWZNnpGcS2FxAdMQW8zMiujOwpueATz2OlMYhEawv5Aw1y6O/O+Sl61UFPGC3NipwF/+IX/P0uOsX7sSgEWRCeXSAoS/fvaBrrfStTQpBci5XKx2toaV9FiWnKU8IEiZ3fHIAefFJ8Asr1JpCwA4+wr2N3mOLFzmZDq7I6qTGnl5sVixMdyCcvl/3CcT462+EmpXZAleqDv9IuCOx9hvJ7Wx5DjrQ+rYPVFUWm3PuFgWHmqrZOs1L2xNW8AW70lD5eQvop0JD3s2swXd2/9mlpv8I8wSuOprtoiXYht9DOxZCmx7xluaZMFD4sAO2boZGcMWkjNOYV4MEj983H6/EkUmdK14nylb1e7dPNLiyGphfV3dppMh/whzkQRY6IG7REoAc++VfovS4/KzeTxXXuB5eQPzFyvdffdukXMvSKi9YbTg3TQl1MpFQGmxzt6nHA/KioDff3A6RdG2J+8AXn2MxebV18rPqiA4Kz07iiDIYR2AZ67PdhuLt/x2OesfFrNznV9PSB2urNXMh0jwz/LkOfKYuvgyzvq7X9neT19jY496vDW2OHta1HDCrzvLb0dQhOK0aIfirP1JfqYNvqy8j8TBndpzhd0GvPe8MinWvMXAq98Cr66QS0U1NQAHVe7WvOV3xHimXOeVSJInAp+XozvL+YVHAfc+x+Zffn2oJn0McNtD8vxemAP892Gl19nlt7L+Gz9EXvs0N2p7TKjDGzxVTneWlZ+z9ezLDzu7D3tCSxNLCgawsdWVl8PJUl4shyQGhrB7eQqnRPzlK6Z4GSAuz0A/Fn4BDAdgE0XxKLdtPwAnM5cgCLcIgtBO8EUvM3ys7ArS0uTafbcgV17YqLM0bvhV+yHmkyjMOk25uE4fA1x+i/x+8xpZU35gOxeTMUrWBE3mFgSZu9kC9tXHWeyttEgBmBX0b0+x0gkOF2urMk5JwtjKrEi80Mlrq13djyKN+LWfPmvf+iu5ekuLb/9AubwOAPzYZjFY851SAcAnltKCdyfK2qcUAOafpbz3akWCtw9w6V/cf357BIUC97/EFgf3Pue6diKf0dnHwBbHWvCZpPduZQKlVMYIYEmuumrRALBJ7orbgFsf9LxcgcFXufj780cW88wLLT4G1vdnL2J/19wJ3Pu8+9qSakLCZOu4zapc1PD9dspc9ixfdrO8bd82FmOk9Xwe3quMn7/6DrnvN9SeXAIaLbb+oXSx593FcjKdLRV8vPvkOcCTbzNhT+Lb5co25qu8KSbMlGPlQsJZPVGACVe8219rM5DDLb4kwUSnB265Xxa6zSaWLVQqt8BjszlnD5W+lxqLWblAGtK2CJu+ELj5fnlxXXaCCYH8b3fkgFzL2ssbOPUCZVmTnEw2TvOLLf4+8/HtG1cx9/Dfv2dKia/fZZ4vd17MrOd87PG5V7E+mzpc3qaO+92yRn498zT5e5x1hbyIPJbVvjUie59sFWltZi6RWthtysRDLU3s93Gl5OwoHbVGBQYps/H/+Amzvnz8qrxt8hw2VvLj254t7Bjpd9XpgOkuxkWe2ERW+ohHK6wkKk4WMM0mpUDy1Tvy3Jk2GnjuIxYDyXvfACym+Kk7mdeXNDcPy3C2MncGheuzB2NORYksPFZXsP4rKUj0XkCAh2WIBEHb9VntwcDnfAiLVM7F69sEi7IitoaRGJKuLNP3x/eyIk8UlR5lXWX5dZfd22plzzdv9T3rCiaISus/Y4t2qMbqb5VKywXnAFf/lfVTnU45h/NjQF21/Ht6ecvjFK+M2bme3Qvew6K7LL8dJX6I0mOIt2Kfcp7cbwVBqaBW30N1uUppLVZ63PNwGvXntQc/d376mryW9JT1vypD2LrLSs2vZdJGsnsz/2zZo6D0ODNq5XPiVgoJv71FIACVjyDqATgFDYqi+LYoilPU2/sUOp0yeYY6GY0ErxWdcQpz1ZS0ps2NzjFONZXyYCEI2qVz5i2WLQm1VfLx/IPLWzxj4mVtndXCMtPybnTpGcA9zwAPvswWsO2VejC2yEXOJRacAzz5lux6mn+ExbOo0UreUlECbNNIasKzd7P8wAs6JmxdfpvsflR2grmhfvmWfM6k2e0noQqPkhNF2e1ylkIfg1K4lph7pqytvOgGViboZIlNZBbf9uIxLvkLW+Q/+LK22zIATOB+953rWTIgaaHr5Q0svlz7vJ7mqjuUffTEMSY4Akw4vutfwI33Ajfcw/7mn+U+OYcrtOJ+SwqVMeFSJut5ZzElhMSBHc5CFKDMtj7rNDbpKCZxN67PddXu427ViKLSGjn/bPbbSws/U6vSFVgUlQLcxFnsvl14vazQslpYRk6ziQlyrz4ue1PEJzO3dT5eW8tzBGBKAElplZymtPD5BwJ3PC4/nzUVLCGYmqy9ssKDVw5qLTqK8mWBIyZBqWybNh+45QH5M/KygU/+x+7H8WOsFJPEzFPZuMAvFnMy2Vgs3YekNGWSuYzJ7t1p1YRHMYXNmZey93wsdB63IGqoUybZmcGNORHRSit/e9bf375VvncVe1pR6uypVFLI3DO7Igt/Z1wxT79Q9mwpL2bWF37hOL8t4c/YabLn0/FcpdBw6c1srvME6fMA1o/434dHax7M3CXHGAsCczmMiGb96o7HZO8UHj77rbuY5I7AeyGVehBfWFSgfM97noWEaedocAUv/O7bKrsuSwqu8Ciluz+gTNq0ZQ3rgz99KisFRk8C/vkKcMlN8rNmMsqW/aZ6ud/6BThXEjgZ+N953zY2puZkMqUF71kQl8wUYYKgVHSoLZQlhUoBbcE5LASNv8czT5NfH9gh3zt+XTV0pFylImOyLAAWF7A8DpLyIjgMiPaw7/cEiy5yrpkcGMKUgTz8/KwO4SkukEsn+fozi7HE6hXaCZ9c8eePwF2XMi8kV2NoS5My67TNyhTgrkL41FgtwJ8qb5BuE365BJ5SyFZgkDKXy/cfOfelfkx/Fn6bAKhVi8EA+mktB7TFGbZNxHnZ2oIdL/yOnsgWiLzblVpo5jMljpygbeny8gamL5Dfb/2DTRL8tdQaaD5Oh3d1uuBaFqc3epLSyqme9KU2tTYz1yl+gXPJTcz6FRoBjJokb9+pEuwB5T3iXSN/+sx92Rs+AdgZl7CJIDCIldyR4JOeDBvNhCZP0HKVmzpfO5lTeBQT8v/1Dluw9SQGX6YM4WsOqxkyTLYqWC3Kgf7C6zpmOe1O/ANYLPuSZcr4S4MfS5bVWVdyNXwiCMntkPdKGDdNjk+WykKcfYW8P3OXMoFbXbXSlUlSJrjTYEts+b0tA/MVzELoSZxe9j55Qjb4sudeEICRLq5XUigvGAx+8vf38mZCrTRe5R9hpaI+/K+sdPAPBG5/XOleDzAlkrRoyzkkLwbc1XEFmIb/hr/L7zeucnZ/5mPh5p8lt6/0uGzxkeBdniWrL8+UeUpPjM2rmTLsxfvlhaVfgGzRHa4SfnmPG7XiS8r67uXNlAlpo5ii5Ko7mFJTeuYiY5jQ+8z7Ss8RXrHFL4h2rJMVCGmjnYW3sy6Xn4/8I8rSPDzFBc75GVwJv7z3jaREBdgC/o8fnI/vCDabsgyRp8JvQJDSus4zbrqcB8E/QNn3JWadprQet8eEmUw4EwT2vLtSrPH9et1K4Ll7lbXdZ5/OkijyJA1leQmeeJMpZdTeQyfr8iyhcHv2QPhV9wdeAeJpvK/EkGGy5bO1hY2RvFLwjEuchenRk5SK/58/V1qKz7+G3R+dDjjvann7nz+ysVIR79vF89ioCfJzVnaCGQieu1fpNjpmKnDf83LZIV55u2+rrDiy2ZRl84aks7FDHZ4TlySPCzYrU1aLotIgws9fgcFKZRivqJLqU/cVdHo29kuCO8DWH+pYdv77HT2ojPfnFQpjp7LcAI7wExH44CXPFMlSidCWJpbAVR2LL6GVTLGhlinAXYU18uzc4ByyVVHSPeXqFJZfTslw2gVKj1TJ00OvZwrqfkx/Fn6PAvASBIGfKcYD6KBfQR8iOBSYPFt+r85OaGxVamhGt6X8n71InmxzD8uWOVFUxszM4jSDanit4e5NLAbNkfRjiDLOD3AuqwCwhf45S7QHzaEj5YGqtoq1URSBt59Vatwuu1m2bgCurUQA0w7z7lnX3cVl3ixzbf1tqFMu7OZzygPeYiAxfCzwt6flOLL2mDLX+R64Kv4OMPc7T118expBYMIKz9ipzFrMJ6fqCwgCc4N66GX2myWlAfc83bWxS7z1oeAIsz5u5jKYq60wgsASHPEa6t2bZEFv4yp50TF8rNwP1MKvlnZ5zXdsu8nYFht6HXOfdOdu+hsX8zbrdLmvu7I0894fY6cqa1wmpgLnc4tKPiY0MJgpI7QsZ0GhykyeOzc4lzjSipkEWF+UlFyiqEx80tqsXODMP0spSOSqpoZCzoVryHBocvqFyrHx9+/lsBP/QObhIi0OUkdwC94i2dqs02l73IyaAPzvOxaz9+DLzFtj4Tkspvf5j9m+fy9n34NX6ABKl7MTebI3QXvjfVikciz68RMXfetb522uaqryCsg5i5QKxI2diHNTf7bk9hcWKQs7nrDoYpZZOzyKCRaX3wo8+j+WYIcfn9WK3dQRntdYl/DyYkl8XvnG/biYPkb2XrBZmZJEWlD6+gMX3uD63IQU4JYHgSfeYv0pNIIJAB0VNF3R0ZhfdzV2O9omdQgQHw4xbb52kkS1t9wvX3BJkKYqF/ETZ8lKXrOJxc6u4iywXeFxxWPwdXaFl9DrmVLtzieUCYOGjZKVR/W1svv9r1/Kijovb+DGv7vOOs0r2TavYa62/Jg4epLy+GvuZKFpaisePz73FWITWShAZCwbZ7QqYsQmyuF5LU3KsYlPJDZxJutz198tP4/lxdreRDxF+UwRwePKlVltTZXW6IU5LI+CO9Q5JXgKutj629woJ9rT6YAUbi709gEuu8X5nIRUpSKiH9JvhV9RFJsBfAvgSUEQAgRBmA3gfAAfuz+zj8O7T239Q7mQPXpAdtNLSJEnmJBwpdZQEprzj8iTmJQp0RVDhsnxjGYT8NXb8r6JM52Pj4pVCgKX3KSMaVOj1wNjuAQLB3eyhT+/4L38VmV8jnRtPtkBX/e09Lhs5YiKY4sjPhbxtxXabnfb18rb0zOUaff9A5WLlxHjmMusu2zDakIjlBaKpLR+nRIe51zJBPrpC1kdvrv+5eyC1JdIHsZKJTz2muzC01UEhcgudDYbyxYpWS59DNpCmyAwKwSfFfbLt5jAwifB4N34ElLkbJyN9Ur3KYApkE6orJ5mE5swX7xfu552cYHsEisISk8DXmOec0i2MiiSvWmMA2dcqlw4BQYzJdizy5WfqYZXnn3zHov3lzxIAoLcJ9O4/BZ5IXH0ILC7zbKx8TdZYZeYyha7/HOoTnrFW37V1jYJqYZ2iko49g8E/v5v5XPt7aP9OWOmyAsyNV5e2osIQWBjjisBLJBLPGazskXekQOyFcLLW1tBCTALs6TEKMhx9iyor1FmqJcoLtAeT/kFZtJQJpBJn19yXDtcxVMULs8dtEYZfIG/PsEUCbc/yvp78jDnz5g4S/4NQsLZsbySx1MEwVlxqsbbh4VfqBMdAsC5S1z3E574ZBau8uKnLF60q4iOl938q8vbt07xwq+6D7eXlEwLrYzVyWnAdXe7/t15xT8Pr5QD2qy/XC7UQ3uUyvSIbvBguvwW5gmUnCb/jZ/OcnJoWbJ1emUZtA//y2Lnf/pM3nb+Ne7DJaYtkL1dCo4qrefTFzrP24LAxqcHXwbufoatEecsUibH60tMnsPmluvv0a6IIQgq1+e2sa2mUg7n0XvJCtTwKBbuJvHHD67LJDU1sN9DbR3WyicBKI06p56ndLNet1K7HrOj3fvkcdXHwH5XiY7UhpcoL2YJaddphFPynkPJac4JSSfMcFaa9HOXZ6AfC79tLAPgB6ACwOcAloqi2H8tvwATKKWJ0dQKbF8n7zvMxdWqyz3wQvO2P5jl9tXH5G18pkQtBAGYySWU4F0EXdVlveleJqze8ZjSWusK3uVr2x8spkfitAu13X79A1nJE4nd3ITFL7qkeLoF5yozfWoVmVe4I2pYR866DLj4JhbX2F52Ylfw7kSLLuxbLkQdJSgUuO1htuDqz0J8V+GqrMiMU9z3lYtv5GLKi5j7k+TWFBSifM50Ovellfh+HZcsx98CTKB56UFn96jVnDVv4ixlTFdEjBz3bTaxxBY1lbKAqPfSFuz1evaMnHU5czl/9kP2uj0viUlzWFwZwGL0FCWOJrsv9RWXpLQEffUOK7PDK+yk51odhythMsoKBUFw78Ll7cMEIkkwCQhiZTiGaAi6Wm65WmNMV8A/i1n7WO1PiclztMMsACaY8FZhvl8AzC1UUn4MHSlbo0xG7ZJR6nHY4KtcgKozz3aEnii9EhrB5rAzLgYeeKlzgltHmDgLeOod4KXPWJbf0y9ibqynu3DT7im8fZhSG2CWJz6uWI3JKCs1dDqm8OLxRIhXk5iq9DALDGHPnbsxNSQMmKhS6o+frj1PTZjhWmnbHZbO2CQ2Nj76mvz31yfcCw68grG4gLk/SwaPoSOVyn0tAoO162BPX8iULq7WIYLA1lnLHmGCZWeUP30FLS8mPtHVyPHK+O7ZpyuTpy3/j7P3lMUMvPmM3Of1nOX9aKaz94xdlRk5bRSw8FxZGW+zskzQruDzLcw+HRjLpSzqaNzvtj9Zpvi1P7PcB7w3F6AU0odqPB+CwBQ5vLJmAKwD+7XwK4pijSiKF4iiGCCKYrIoip+1f1YfRxCUFqD1K+UHSx3vyzNyvDxxtLaw7KGSAKvXK2sfumLGQucM0mGR2os8gC2YL7vZ2W3MFVLyK4BZBCR3tthE4KLrXZ+nlQkSAE5wmmfJpck/QCl4qhd2RflynKCXt3Z8rk4PLL6UxW51RvAFmCC09J9s8uaTzhD9nzMvYa6pF1wn/117l1Kzq0VwqNL9mRdgZ5/hvOBwJ/zywuKcM5g755Jl8rbjuaz8iBSbWl+jLJGh9rAAlLGPn78OfPaacp+rhDCStfeU8zz3kAgMYpbTjEnO+7TifdWce5WcKK6mUlmiIzwKmNX2zA0bLY85x3NZ6AjA4lQlK2ZMYvsWu7BI4OFX2D12V55DLaD5BbBFd3fAL0B+/ERemPkHMk8cd5zOKeQObJezdbc0K60Diy4GElPk9+okR02NsgLHy1tW3PK1TrVq2rrC2CIL3qLYM8IvwCwbl96s9ALqbkLCmavv5bew2LqOJIjqLniLtLu43+JCeV0SncDWLHzW/85knxYE2evKxwAsfdgzd2R+vQQo43vVn3/H40zRwI/df33CvVdcT5Ix2TnEDGDjyI1/d68UlOCzYgPMFfqmezuX4LE/ooj7zWRKBH7dqDbmSN49UlheVTkrPShZeC1mtp7O3iefc+uD8vGNdc6KouJCeX0bGsESSgoCcAHnfbB5tbZXTGGOHJYnCMBpFwGpnMIk/4h2qEp9LfDk7cDfr2SK9TXfMYXou88rM0b/+LHSg4eP9x3mwlMuIUU2cPn5ezZH93FcBA4QvcrMU1lMgMXMBLWDO5hlR/LL9/J2XggIAovl+uod5faQMOAv97sWYHnCIoHRE5hLkMSEGV1ntQwKZQs2XiMm6JhG0l38wIQZ7DtbLczKUHqCWX94t0/e8nXaBaykgd3OBqzjufJilbf6TpzVtRkeeboyEQnRt/Dydl0aqj1OOY+FJagnSz7uXMIpeYedLZCtFqUXyNipcryzj4G5y4kiez6evJ0l0aoqlYWKtFHak9zICSyBB8DGHT6ZlKcKro6QkMJc7Y5lAT9/xoSk2CTXniY8/oHMM4MvqaTXs4XfOUvkWLqAIHadonx2/45lMYHbE5dnNeFR2rGHPJKwLS1Ops7rPisKvyDiS8xdeVv7wkdsErOQSXFwa75lZVPefV52mY+MBSbNYrHSkvKlOF9pneKTXSWkyAtsfnGUvY95E7QXI7Z7E7OuRMUCdz/NvpOkwPUPZLkniO4lLlFO9Ogu7reYUzwnprAxccntwOtPsmePd9/tCHPPZGuEwGDPBegR45jwumczU9a4W+sEhXQskVlP4+3DlGw5mfIzLQjsO3malGvsVBYikHOIZYVestQzoXmgEB3P+k5tFVOmPXabcr+WMjI0gmXPfuc59n7XRrbevule4LsPlYrqC65l/W3TbyyrNsB+Lz5mXhHvO0peQ4+cwNbuOZksbOrnz1ncMc+Pn8ivJ81meTPsdjYGtjQxhXZVmbOibvUKec7eu8U5Y7jEiTy2b/Ictq7gFevuwsQuvJ5VsoiMab/qST+gD6gaCScCgpSulW88zR5AiWEZ2hbJWacrF1oZk4HH3nCdeEELtYveBA8Woh1BrTE685L24wf8ApTnrf2pbXHPx5qlyq8jopXxblKSH3UNUK3SQwTRnXh5O1uIMyZpW5zikmUhrrlRjrHLPSy7ZUXGKJOlzTmDua1Jk21NJYv14RNdaVl9ATYZqsuJAEzgHt9N1kuALQ7u+hfw369ZRltPrcdzFrHvGx7NFH/PvA9c9zfnutNars8K4ddFsqvO4B+ozByttsJ0JUmpzomwJsz03NOE7wdbfmcZTPkM9xffyBbNfIyh2vLragxW17TlLfOuWPU1c4GvKGGxdQc4i3F6Rt+wjA50FOWO3Am/BfJrqX+Mnw68soI9h3wip44gCMyLqyOWY0FgYTn/+1aZnb2/4h/A7uWk2exv4qyOZaP28mIVN/7va1Y1YzAJvgDrD+oYVYmhI12HNUxboEwGWFLIsnTzgu85VwJnt5X/cRVSA7jOnizl/5DYsoaNdxL5R1gtb+lYyYtBp1PWdteK+3U3xk5fqFTc/vAxSxD5/kuyonbcNOe5k0cQ2HfpqgR7vQzNJn2VC66VJwCLWVl/UO3yLBEYzNLBDx/LXHvu+lfHNTQTZ8mxYkGhwAiNxfDJMHGW7FqdkOLaRUkN79q0eTUTBKSsq34Bzu5R/MJu53qmBf31K+YaArB4Q3XcNEH0BOOmKctyLXRhTRQEpeuzVLKCL08jWX15Zp/O3LIkt2CeqDjtxFUAU5zd9wLw3EdM4z3nDGZ9vu5vPVPSKjCoY655Oj3Tmj//Ecta6spFUmuRosj07KHl11OuXMYUjhdd79qNrCvw9lGWKQsM7liW4vQxsuBvtTiXlpGy7yZwQq26vI0i3ldVMo1XWB7YAbcYVfWliwuAFe8p20p0Pwq3ZzfCL68E4etXG3x7JwusTsfyDPTn3BpdiSC4jvkfDJx/DZtn45PlvxHjmDLAFYLAvF+uvUu7D593NXOTl/qYYl5RpRri42jV1tSR42WvLrtdWR/7B87qO2WeUvGocH3m5i+AuWjzJZcuv5UZ0IaOZJ6Vf7mPhQoZ2hTLJYUsTwYfKnPNnc7feQBDbs99lfAothB94X65FIKEK60WwMoCTHORkMcTDL4sLmbbnyxuTm1ZOFkSU4FbHmCaqzMv8dwlcPQkNhAUF7AH/bPXlZ+pnvRShjMlgOQu+tzflfunLxw8MTBE3+PWB4CVXzKXJncxoeOnyVlJf/uaeTTwFjFXsTdT5rEEVetXspIeUu3dxZe1bwmIiGYeIN2VqKmn4UtdHTnALOGSVUvQdX29wrRRwN+f7drPdMWkOXIClKvv6FiiIUFgSsK3/63cPmYKcDGXwChhiOzKXV7ElLHSuM27PavrhY+dyuLOALm2uyvhJC/LOZO0lMkfIOG3p+C9SMqK5FALHlFUZnrmhV+C6AuER7FkYx1FEIB5i9kY/tYzcqjh+dco83UALFzG24eNh5WlQF01syo31LH3AFs/a80v510juxtLtelnnKqM9VVfT1HbXWX5zcuSx8uEFO3ksUEhLPfPL1+w97zi0pNQmQEGCb99mag4VgT9hfvktOiBwd1fXDo9g/11F1PnOddDbQ9BABZdJGc05d1M1IsuiUUXa7uCeHlrx1gSRE/hFwBccmP7x01fyBIQHWub3N54Sp5YvX2UWXXVGHzZM7DgHGY1dlVvdqATGsGUZ1LCwLWchTM+ufNJ7foCiy4CwiPZd+S9BDxl8hym7JDml5gEltWdV5AYfFn8b2UpE4ZKT7A5yGqVF4eAsxCUPoadazKyc8uLlXFxPLzlRIptk/AxKF3Jie4jMJhlWW6qZ+7qtVXOrpANtWw/wH7frq6RSxC9TUIKi73evYkJhVqhg17ezLIqlYo7mskMT3y875B0bQPP8DFM6S3lXNj6hzIkb9oCufSoBF/+rzCXeetIxim+jJ87ReGii1k2fz6bdUdCZQYQ5Pbc14mMZRZg6UHQqg83WJi2QDvewJXmedw0ZsUAmLvHmCksK+3jb2jXWSSIvoZOz0IZJDcsSfAFmODrieDmY2ClbWacMnjdAm95UNvC3t+FKr2eKTQ6I/hK5192C+sXYZHA7Y9pu0vyY6yU7KjshJxELTza+TxvH2AUF6LjLuszr8y88jZl6Zmho7reA4lwTRynoNByfeZdnhNSBu96hBjYGHzZvOkuZ45WSI0ie7KL0loAcPMDypwQUuytoHO2+gIsDFEqR2i1KJ9DXnnoznAVGKS0Cnc0VGYAQZbf/kBEDPD4myzL2wDIstZpvH1YsfBvlyu3u7L86nTAnU8wN5SgUHJzJvonsYlMafPFm8rt41y4PBPOBAYxwe6PH4Cv35Uzqbqq+zmYmDyHJcfRe7lWpiSkyNlDpUUX7zaX7GIMHjdNrrF5cKe2O57VokzgMmI8c9l/6xlmLeYTxBDdT2ySvJguK3LOjcFneuZjEglisNGe8Osue7LBl5WvGjWB1d+VSivNOMW1h0zqCDlONz+buV5brcztWatNWpxxMcvgX3qCXb8zNbkHACT89hd0usEt+ErMO5ulhzeb2HtB534C1uldZ/cjiP7CKeexUh68G/8AqLXXowgCK3MyLAP4/iMgILB7szH3J6Sala5Q1PptE374eF91sisJyfMGYH3X2OqczbswVx7PI2Pk5Gr3/HtQWiR6nfaSXqktvwQxWEkbxdbmdjvLR/PqY0orrCfK1ZmnMqH263cAEcBlbjKWp45gCVwB4MhBYOG5LNGV1vjpCl//nstJ0YchfxWifxEYxLLQSsQm9k52SYLoSXQ65v7s68/ep43SLo9EtE9KOvC3f7HY1u6qwTvQ0Mr4fIKzALryvgmPkuvzWi1KC4VEjot4NRJ8ewfe6qQubQUoM35TsitiMOPrJ+fgEUW5TBHAFEOelgWKTQT++gTzVHRXJmwkF96yZxPzjHE1fhJuIeGX6H8suoglDAJY6SSCGAxExQKP/I+VMVv6z95uDTGYiI6XFQV11SxTaQFXbsOV5RdQ1o5WlwQBaPHW1+Dj4I8dZjXGJew2ViZFgiy/xGBHa8yaPAe447Guv1byMDmPgt0O/PwZjZ+dhNyeif5HZCzw2GusOPhIN9luCWKgERMPxFzQ260gBht6PRCXLNeSfPF+eZ/BjylmXJGeIdcQ5hdqAFvAKZK10OKt1wmNYFls87LZ73NgB3PNBICKUlbaBWBWLa1a4gQxmJhzBrD+F/ZcTJ4LnHNl93pEnH8NkLWXvd62FvDhvJdo/PSYXrH8CoJgEAThPUEQCgVBaBQEYa8gCIu5/SmCIIiCIDRxf49w+wVBEJ4TBKG67e95QSAfqUFFZCwrX9JezVKCIAji5OHjfnkWX+o+4y+/IMvLljNEA0DpcbmsUVCI60QvRM8yYab8WkpYBqjivFN6rDkE0WdJSAGe/xj4z+fAbQ91fyjAsNFyEjrRLifKovGzQ/SW27MXgBMA5gMIAfAIgK8EQUhRHRcqimJg29+/uO23ALgAwHgA4wCcA+DW7m40QRAEQQxK1MlbJs8BHn0NOGeJ+/PCo1giFoAlZinMlffx9SmHZVCcb1+BF34zd8nW3i1/yNuT+3mZMILoKgKD3cfqdjVaGfBp/OwQveL2LIpiM4DHuU0/C4KQD2AygAIPPuI6AC+JolgEAIIgvATgZgBvuj2LIAiCIIiOM+t0FmpiNgMLzu5YvGf6GKCqnL3OyZQFaYpX65vEJQExCSyhjsnI3Cyj4oEDbQl9BAGYTZnSCaJXGDqSVXvga6fT+Nkh+kTCK0EQYgAMB6DOhlEoCEKRIAgfCIIQyW3PALCfe7+/bZurz79FEIRdXdZggiAIghhMePsAl94MXHV7xxMdadXDFEWl8DucFm99BkFQJpPcuxVY8638fvx0ZUkkgiB6FrX1l8bPDtHrwq8gCN4APgXwoSiKUqX7KgBTAQwBswYHtR0jEQignntfDyDQVdyvKIpvi6I4RWsfQRAEQRDdiEL4PcQSKR09CNRWsW0GPyAprXfaRmgzkXN93rMZ2PK7/H7RxT3fHoIgZFKGA3MWya+TafzsCN3i9iwIwjqweF4tNouiOKftOB2AjwGYAdwhHSCKYhMAyVJbLgjCHQBKBUEIFkWxAUATgGDuM4MBNImiKHbpFyEIgiAI4uSITWQJWRrrWYKrkkLgh4/l/VPnsozSRN8hdSQQHAY01CrLHaWkk4slQfQFrr0LWHQJK0VHyV87RLdYfkVRXCCKouDiTxJ8BQDvAYgBcLEoihZ3H9n2X7LsHgJLdiUxHs4u0wRBEARB9DaCwBKySPz0KbP8AkzoPbudpFlEz6PTARNmOG9fdDEl1iGIvoBOD8QnA15Utbaj9Kbb8xsARgE4VxTFVn6HIAjTBUEYIQiCThCECACvAFgniqLk6vwRgHsEQUgQBCEewN8BLO/BthMEQRAE4SnDx8qvd2+SX89e5L5OMNF78FmfASA8mtUyJQiC6Mf0Vp3fIWCliSYAKONq+V7VdshQAKsANALIBGACcCX3EW8B+AnAwbb9K9u2EQRBEATR19ByldV7AWdf0fNtITxj1AQWjy1x2gXknk4QRL+nt0odFUJ2Ydba/zmAz93sFwHc1/ZHEARBEERfJmkoE6RMnKPX3DOBiJjeaxPhHm8fYMFZwG8rWFzhvDN7u0UEQRAnDTmKEwRBEATRvej1wLBRwKE97L2XN3DW5b3bJqJ9LvkLq/EcEQ34+vd2awiCIE6aXi91RBAEQRDEIGDURPn1vMVAeFTvtYXwDEFgdZ1J8CUIYoBAll+CIAiCILqfhecCZUVMoLroht5uDUEQBDEIEQZTadxly5YNni9LEARBEARBEAQxSHn99dedckyR2zNBEARBEARBEAQx4BlUll+iaxAEYZcoilN6ux0E4Q7qp0R/gPop0R+gfkr0daiPEp5Cll+CIAiCIAiCIAhiwEPCL0EQBEEQBEEQBDHgIeGX6Axv93YDCMIDqJ8S/QHqp0R/gPop0dehPkp4BMX8EgRBEARBEARBEAMesvwSBEEQBEEQBEEQAx4SfgmCIAiCIAiCIIgBDwm/BEEQBEEQBEEQxICHhF+CIAiCIAiCIAhiwEPCL0EQBEEQBEEQBDHgIeGXIAiCIAiCIAiCGPAMKuF32bJl4rJly6i2E0EQBEEQBEEQxCDDq7cb0EuQAEwQBEEQBEEQBDEwEbQ2Dlbht9/xQ+4P2Fa6DTeOuRHpYekuj9tZthPf5nyL84edjxlxM7q1TcfqjuGDzA8wPW46zk071+PzVhxdgTXH18ButwMA9Do9zkw5E+cPO9/lOVWtVXhj3xtICErADRk3QBA0+7MT606sw4qjK2CymQAAgiBgRtwMXJ9xvcvPMNlMeH3f6xBFEcsmLIOvl6/H320w8OOxH7G1ZGu7fXGgIvXF+MB43DjmRo/7YmcwWo14ff/rsNltuHPSnTDoDR6dd6jqEN7PfB+N5kbN/SGGEFw/5npkRGQ4tomiiI8Of4T8+nzcPuF2RPlHdcl3cMWq/FXYULQB12VchxHhI7r1WrvKdmFFzgqcm3YuZsXP6tZr5dXn4YPMDzAtdlqHxkWe3NpcLD+0HDPjZ+LsoWe7PE7qi3GBcbhpzE0e98VNxZvw5ZEvYbLK4+K02Glu+7M0Llrt1o71xepDeP+gsi8OCxuGuybd5fYzPj78MY7VHcNt429DbECsR9fikfrzlpItEEWm7zZ4GXDp8EsxL3Ge4tjfCn7DhqINuHb0tZ3ui7/m/4rNxZtxXcZ1bsfF3eW78c3Rb3Du0HMxK6FzfbG75/nvc7/HqoJVijn6rNSzOt2f+wqHqw/jk8Of4JTkU3DakNO69VqlTaV468BbGB42HEtGLVHsO1B5AF9kf4EzUs7A/KT5in2/FfyG9SfWn9S4+HPez9hUvAk3jbnJbV/cU74HXx/9GucMPQezE2Z36lp9kerWaryx/w3E+MfgL2P/4nJMs9qteHP/mzhQecCxzdfLF9eMvgZTY6d2ebs+y/oMWTVZWDp+KeID4x3bLTYLXtn7Cqx2K+6adJfbNecnhz9Bbl0ulo5fipiAGJfH/V74O77L/Q4Wm6Xddhn0Blwy/BKnvjiQIeG3H3Cw8iD+ufmfAIDK1kq8u+hdzeNEUcSDGx9EeUs5NhZvxJ+X/gkfvU+3teuFnS9gc8lm/Jz3M6bGTvVogVLYUIjHtz7utH1T8SYMDxuOURGjNM/7IPMDfHX0KwBAemg65ibObfdajeZG3LfhPrRaWxXbt5RswYjwES4Xwb/k/YL3M98HAMQFxuHKkVe2e63BwqGqQ3h408MAgIqWCrx3xnu93KKeZ3nmcrkvhqU7LaS7kl/zf8UHmR8AACL9InHDmBs8Ou/BTQ8ivz7f7TEnGk/gi3O+cLw/WHUQL+56EQBgsVvw9JynO9nq9qkz1uGhTQ/BYrcgrz5P0Y7u4KFND6G0uRTri9Zj7WVrPRbcOsOLO1/ExuKN+OnYTx6Pi2pe2PUCtpRswcq8lZgaOxXR/tGax3146EPFuOjJ4sVkM+H+Dfejwdyg2C6Ni3MS5mietyp/lWNcDPcNx01jb/Louzy88WEcqz+m2La1dCti/GNwXcZ1mufsLNuJ53c+D4AJ5o/NfMyja/EcqDrg6M88u8t2Y+3lch+oN9XjoY0PwWw3o6ChAJ+e9WmHr1XdWo2HNj0Eq92K0uZSt+PiQxsfQklzCdafWI8/L/uzw8pVq92Ke9ffixpjDbaWbMWfl/0JndB1EWzFTcV4dPOjEFUOcltKtmBC1AQkBSd12bV6mqe2PYWDVQfxW8Fv+O2S3xDpF9lt13p9/+v4Pvd7AMC4qHEYEznGse+fm/+J/Pp8rD2xFmsvW+voA3xfzK3LxVfnftXh69YYa/DIpkdgFa3YX7EfP134E7x02kv9hzc9jKKmImwo2oC1l63t1vViT/LR4Y/w5ZEvAQBpoWk4JfkUzePWFK7BWwfectq+q3wXVl+8GoE+gV3WpsPVh/HvHf8GADRbmvGfBf9x7Pv66NdYfmg5ACDKPwo3jrlR8zOyqrPw3M7nAACt1lY8N+85zeNqjbW4f8P9MNvNHrdvZ/lO/Hnpn/D39vf4nP7MoIr57a+8lylPpPl1rhe0JpsJ5S3lANggerj6cLe2S1pc20Sbx9fKrct1uU9aWGlR2FDoeL2lZItH19pfud9J8JXYVrLN5Xm80JBdk+3RtQYLfF/Mq8/rxZb0Hvz33lqytVuvld8g90VP+31Zc1m7gi8Ap2MKGgocr7eWbHVYy7qD4uZiWOxMI32o+hDqjHXddq1WaytKm0sBMIXYoapD3XYtQDkuevI7aFFQXwAAsIpWHKs71u5xgOf9o6KlwknwlXDXn/kx2NN+X95c7iT4evIZ/D53398d/L3habQ0orq12vG+pKnEsUg8XH3Y0S87wvHG47DarQDcz3EtlhaUNJc42pFZldnhax2pOYIaYw0AoNpYjSZLU4c/wx2F9YVOgi8A2EU7dpTt6NJr9TRSnzDbzdhTvqdbr8XPEwerDjpeN5obHeNCk6XJ8VsCbOyW+mJWTZZin6eUNJXAKrK+WNRUhNUFqzWPs9gtKGoqAgA0mBtwvOF4h6/VV/F0XMypzdHc3mhuxDdHv+nSNvHP+rbSbbCLdsd7frzryBjsao7eU76nQ4IvwATyspayDp3TnyHht4+TV5eHP47/4XhfbaxWPDQ86klwb8Xebm0bv4DydJHHLzrmJsxVWJdWF652OQDzLnOefi9+cls0ZBHunHinvK/C9cTHf6/SplKPrjUYyK/Px++Fvzve1xhrYLPberFFvUOdqc7x2l0/6goaTHJf3F+537HAdgf/fIyJGIO3TnvL8ffmaW86rEQt1hbFQp+/VmVrpWNh1B3w1wKAfZX7uu1atcZaxftu/8248aOqtapTn9Fokce7smbXCxL+Wp6Oi/wYPDRkKO6adJdHn8GPwQeqDngkJO6tlD8vIyIDz8973vF+X+U+l+MH/xt19h7y8+HCpIVIDEx0vOfvG//aareiuLG4w9eqbKl0vK411rq8N/y9Bzo3R6v7r/pZOln4+zE5ZjIuH3G5y2v3J2x2m+K56u71ET/u8OsjtVKGf666Yg2n7g/vZb6nKSSpj+MVrf0dT8fFaqP8PF496mrcMu4Wx/uPDn8Es61jAqQ7+D7QaG50KPXsol0xTrqb5/n+W2uqVSisefjn9Jyh5yjWAOo/3i1ePT4NZEj47eOoraE20ea0mJNQx/d150RltVsVA7Wnwm9lq7xIGBUxCuelnYfZ8SzWxC7a8cGhDzTP46+VXZONFktLu9fiB71FKYtw8fCLHe8PVR+C0WrUPK/eVO94LVmMCOZ6zlsE7KIdtSbtvjiQ4bXx2TXZaLY0d9u1+Em81dqKI7VH2j2HV/rMSZyDWQmzHH+zE2YjyCfIsZ8fM9TWwO5cHNab6xXvu3OsUvfR7vxedtGuuKedWUyIoqjoU+7GIH6sOlJ7BE3m9q2A/BicHJyMS4df6nifVZ3lcmzlx+BWayuO1LTfF/eWy/d6dsJsnJlyJqL9mAt3s6UZOXXOlhezzaywklS1VnXKC0ERYxw6TBEfx983db/vjLWeF9BFiKhp1bbY8fce6Fy/V/df9bN0svD3JiU4BecMPcfltfsTasGyuwV53puF71NqIZNvl/r57Yx1Wt0fjtYexcbijU7HdUW/76vw9yCnNselpwv/3E6NnYpbx92KKD+W66KytRI/Hvuxy9qkvr/Ss5Rfn6945tzN8+r+4ep55LefmXKmYg2g/ksJTnEcyyvxBjok/PZhyprLsDJvpdN2V5pw9YOxr2KfSyvxyaIWtD3VGvJtl+Jt+NixH3J/0HwA+e9mE204UHXA6Rges82scDWaFD0J4b7hjgfdare6dDnjB8qy5rJudf/sL5Q1l+GnvJ+ctnfWKtOf4S2/dtGO/ZX7u+1aau28J4shflE3MXqi0/5gn2DHa37S5V97eq3O0pnv1VnULtV7K/Z267jIK4jUwo4ntFhbFO1zJ/zyY5VdtCsSt7hCPQaHGEIwLHQYAOZm7WpcVM8vu8t3t3stvi9Oip4EQRAwMUbuk1qfcbj6sCNBIcAWgy3W9pWd7tob5BOk6Pf8fVP3+86Ec6jHwSqj9rioPm5/xf4Oec+Iouj0rHSn5TfYEIyMiAxHfPSJxhP9doGs/p27U3FpsVsUVjqF8KsSgvh+yp8DdI3lFwDeO+gcg66+HwNJ+OXvgQgR+yr2aR7H9+VIv0j46H1w7ehrHds+yPygy7zb1PdXGvu0lDC80pBHve7WGj9bLC3Iqs5yvJ8QPcFtu/i498G0niPhtw/z4aEPHbEbPK6sCeqBs85U5zLu6WTR0hp6IiRqCb9TYqZgXNQ4AGzS+Pjwx07nOU0KLgYHCX4BlRSU5MhcOzlmsuMYV5pf/rsZbUaFsDNY+fjwx5quOINpsASYUkW9YOpOa0hHrbEN5gZHHJNe0GN81HinY0J8QjQ/X32t7rSMqK/lzhPjZFFbfhvNjW7jMk8G9ffqzPOhXuB4KvwCwO6K9gVSrTF4UvSkdj+jowvzRnMjjtYeBQDoBJ2jL/LX0voMrX7XmfvIW9QCfQIRYuD6vcl1v++MEMC7TwKu52j192i0dKwvHm887nQtV1atzsJ/XohPCLz13hgbOdaxrb+6PqvvU3cqLtWCZXlLuWPeUPcv/rlSK5jceWK4Qqs/7KnY4/SsDWTLr6fzJv+cSmPhpSMudXhHHW88jjXH15x0e1qtrY5Yf3WbtNayrp4xT9ziD1YddMgNw0KHKcY9LRTCrwul3UCEhN8+Sp2xDityVjjeS65igOsOquXy5sliqDOotYuN5kanSVkLrcFGEATcNEa2/n555EvF5GEX7c5Wh3a+Fz8o8NYv/rVL4Vf13Qa763O9qR5fH/3a8V7RFweZ8KulCGlPESNRUF+AT7M+RXlzudO+fRX7sOLoCqcEbU4Cafket0qm/RX7HZbHEeEjEOAd4HRMsIGzgLUjBHiScKXF0oJvc77Fa/tec/z9kPuDwnqnRn0td54YPDa7DSvzVmL9ifXtHiuhlUzL09+so6i/V2fcntXCr6uYX5PN5HSPPVHEKMZgXzYG89ZYV/dGy+XOXV88UHnAYcEeETbCkTl1Ugwn/JY7f4bW9U9WiRDk7dry2xWxj06WXxft1dreEWFSy0OiO4Vfaazg583+6vqsZRHtru+iFZomGSLUngX8c6UWbtx5YriC//18dHL25vcPvu/yOMBzA0Zfx2K3OM2jWs+NXbQr1qwRfhEAgADvAEWFj/cPvt/ufdlQtAFrCte4PI5PVCVR2lyK0qZSzeff1TyvHoO1PDHU3jbtwQu/FPNL9DorcuSF8PCw4ViUssixz9XEqlXTs6cWeYBnmkOF1cFXfugWJC1AWkgaAOb2x8datFhanLJPHqh0n3DF1QDAv3blcqb+boNd+P0+93tHX0wPS8eZqWc69g024VdrUeNJ8h+LzYKbVt+EZ3c8i9t+v03R77Kqs3DDbzfg8a2P45U9ryjOUy/Yqo3VONF4wuV1+MWcq4nPUyEAgEt3MZ43D7yJx7Y8hjf3v+n4++fmf2J55nKX53R2Ifpd7nd4YOMDuOPPO7CqYFW7xwPOll+g+6xX6u91shZLgCXd8yRhDcDK4rVX17E9y6+rhCvq+aXGWKO5qJNw5X6fHpruUMpUtFaguElOMKVO/qLVZk/h2xvoE+i633eBEOCp8KulIO7IHK31jHS52zP3edI94xUW3Z0lubvQWrN01/pIS0maV58Hi92CEw3K8Zt/3rXWcB0dq/jvefnIyyGA1bhdV7ROMXeo+02LtcVRLaQ/o/U8ZFZlOiWvqjPVwSayeTjIJ0hR/u6qUVfBV8/KT2XVZLnNGL0ybyVu/+N23LPuHnyW/ZnmMXl12qEUvxX85hj/fPW+CPJmFmdX87zmGl81JvB9mldquoLcnok+xbZSuRTP1aOudrjtAm5ifjVKHnTbIq8Twq8oioq2S5o2gLnFXZh+oeM9766t9b1ara04WnNU8zp20a5YtPMDQGJQouNhb7I0ObmcqRN5Ae6zrQ4G+HJPlw2/zJEQAhhcmkJAe1HTam1FdrX7kliHqg+hoqUCACuF8vtxOWv2OwffcQgbfJy6OjuphLtnur14X8CN8Ku1OPRAIHUlIHuaUd2T4x3HcAvvt/a/5VHsrqblt5ssPk5uz51wI1MvcMx2s6YFXuseGm1GZNVkOW1XtEljDI4LiEOMP0sI1WJtcbgrK9ql0Rfd3UeF9w03But1ekyImqB5nDr5i1abPUXh9uwdqPB4cJfwylMvJnft64jld3fFbo+FbU3htzstv21jxfio8Q4h6kjtkW5N8tddaN0nT7OWdxQtJWl+fT6KGoucQtn4dmkKvx1UNvDC3/io8YpQL36N1lkDRl9H63uZ7WancpxaSkCJcN9wXJR+keM9X+KRx2a34c39bzrev3PgHU2PJ96bhLfG8yF+46LGKeJztebD9sZgq92qcOX3xPLLr8NJ+CV6FXUHnhk/0yPtjNbAWdxUrOlmebJoLVDaGzgbzA2Oicbfy9+pmDb/HdubEADXi+X8+nyHkBJmCENqcKpjnyAIbl2fta412Msd8ZbvIcFDEOk/ODWFgLYVEWhfcFPvf+8gKz9RUF+gKB/FC9eu6ne6EjjUWXJ5aw2PKyFA65n2ZOHFL7YWDWnfQ0V9jsS+CtelbyT4vphbl4sNRRvabZ/Wbya5nHU16ntYb6rvcLkMrfAVLe8Trd8LaF+w11r0CYLgNhZXnYFawlXSK4vNoki+pV6EuRqDXT1HJ+s+3pGEV0DHhAC7aHfK7twR4beipcIj76Lq1mrN0iau+kFn4T9PGiuCfIIwPGw4gO5P8tddaN0nTxSXnUFLSVrQUKDZrxRuzxrPvqcl7iT4TMfBPsGKLOd8uwaq8OvqeVCPVe6EXwC4LuM66AU9AGBn2U7NPv/niT8Vz2S1sRo/5P7gdBx/X09POd3xuqK1wvF6YvREZUiIxjiu1T/4MfNo7VFHcsAY/xjEBcQ5Ha+G98AcTOs5En77IEdqjjjcTOMC4hAbEOuRX77LxbKGG9nJ0pmBk283b8mW4APz+QGso0KA2volCIJiP68JVbs9aX2vwe72zFu+4wLiBq2bDKC0IkpuUUD7Aoe6n2XVZGFr6VZ8cEhZPoq3GLiaxF0JpHySt+SgZM0JHdC2/IqiqNn3D1cfdoqfUsMvtq7PuN7x2q3wq3EtLU8MNepn8d2D77ZrNeMXfPxv1h1eMVrfy5O4aR6t8U5rDHJl8XOnsHAV5wYorbPqz1BnoJZw1e8P18h9MTEwEdH+0Yr9rtxo+dd8CY6usPx6mvAK6JgQUG+qd7LmeZLwiv9+nvRFVx4WPWH5Bfp/3K/L56UbxgFXlt/2hF8ty54rTwxXKNzWDcEIM4RptutklT59FVe/s7rPauU+4IkPjMdZqWc53qszZouiiHcPvut03geZHzgpK/j7el7aeQ6hmmdS9CSlUlBjHNeaG/is5fw5k2ImOa19tQj3C3d4ddQaazukaOnPkPDbB9FyXeyo5ZdfbHRHXIuW5aa9gVPhbucb4bTflWbe1fdylRSA/75a1i9+gFG7nGl9r8Hs9myz2xSeA7EBsYNWUwgorYiz4mc5XrtL/uMqjvG/u//rVEewwdzgmHz4ZyAtJA3eOm8AzIKgtbj2xOUZgKYQYLQZHV4Z3jpvDA0ZCsCzhCv8M5MSkuLRRMp/t1HhozS/gxqb3eYUk7a/cn+7JXf4BZ/6N+tqtBZeHX1GPPU+cXUP3fXFBpPcvwK9A+Hn5efYp7b88p/BtynUEOpw3TveeFzz+7U3Bo+JHAMvnRcAFgsp/Ub8b3L6ENlC0inh18NSR52Zy3i02qa1TW0h5r+fJ3M0/2zwv3e3Znvmxgp3SuP+gLvnpavRsvwWNhRqKvdcZXtWrOE60Ea18iLUEKrZLk2lTyeSvfU13P3OvALPVQgez41jbnS8XntiLY7VHXO831a6zeFKbdAbHBmii5qKsKZQzhBts9sUuREyIjIwMnyk4jo6QYdxUeMwJnKMYp5XK0611sK8J0ZHk10BbL4P82UKEhGipuJmIELCbx+EH+ikCccT4ZcfOOclztP8vK5Ca+AsaS5xayVqz83E1eKE/17jo8Y7BhlXSQHaEwKGhw2HvxdzuVa7nLn6XoOVqtYqh1Uj3Dccvl6+gzY7IKC0/E6KmeTos+6S//BxjAHeAQ6tb1ZNlqZwKB3LL8oj/SMxJnKM472WFag9gUNC6znjrxViCPE4wY3RaoTZztx6vXXeCPQO9Ggi5a+3IGmB5ndQU22s1rxf72Y6a995+AXfKcmnOF53i+VXQ5DqqODmseVXFdsnLXJrTbWa7rHqtqjH4GGhwxwJVypbK1HUVCS3iRuDw3zDFH2xvXJFWmOwn5cfRkeMdrzfV7EPZc1liuQvcxLmaLbbEyx2C4w2VjpLL+jh5+Xnsr71yVp+PRV+eQtxkE8QZsTNcOzzpC/y95l/Zroy4ZXVbnVYkQQICPQOdOzj4xG7K1a2O3E55rSTtbwzaIVaWOwWzcRJrrI982s4T2pqS6iVF9J4DCgVgSer9Omr8N9rbORYhPuGs+3mBkXiqfbWowAwLGyYoq+8nylnzOYtwRcOuxBXjbpKsU/qU6XNpQ4vmHDfcIQYQpzGRCkbvkFvcDm2qkNP1Gt8URRdVjlpj8EY90vCbx9DXcRe6sChhlDHornB3KAZR8YPnHPi50AnsJ/3SO0RzVgBV9jsNhypOeI2/s6Vttld9s92hV+DC+GX+17BPsFuY3bLm8sVCyhe8yfhpfNS1D/lJxZXlpuOxu0BzGLcHfHWPQm/6I4NiAXAfifJatNoaey2+qx9EX5RE+4b7lHpLH77tNhpWJy62OkY6VkFZGFNrcHnr7WqYBU2F29W/PHWZXcTn6bwq7pWe7VY1edL5wmC0O5Eqk7kpVjkuUn+w/fFSL9Ih4V5c/Fm/HjsR2wu3oytJVsVdTFFUVQoLOYlznOMo7m1uR2KlzTbzNhVtktxz9XCfXdZfrW8T9SLXEWyFBcKCz4Bl9raodfpMT5aHhf5z+DH4CDvILfKEfUizJUFgt++qmAVvs351vF+bNRYRbxaR5Vs/HwX4B0AQRA05xe7aNe83ycr/LZYW5zqs6rnvzGRY+AlsHE0t859X2yxtCCrWk5kxj8zXWn5VcdJ8+NSbEAsEgITAHRfrCzAPAE6+syYbSyhkbtM5/x9mhA9wSPFZWfhxxz+HmqFQLjK9jwvwVm4aQ+L3eKkvOiI5beipaJPJzMTRRFHa4+6XXOox0VXc7Qnwi8ARRnOX/J+wZrCNfgu5ztsL9sOgCnXrsu4DktGLnF40hypPYJNxZsAKMcSyaNKrZx2WY6TG1tbra2O7NS+el9Mi53m2LepaBNW5q90fKcg7yAMCx3m8jupGYzefCT89jH4IvZBPkFIC2Xlf3SCTuEqrLUY4AfOmIAYjAgbAaDjCSruXHsnLvnpEty97m6Xx/ATNa8ddrdo4BdeWoONZNEF2HeRXFTUE7K7uAheABgbNRbeem/NtijqWnILNVcLkI4Ksfsr92PRN4uwaMUiHKw82P4JfRR+0R0fEA9Aoy92MDNqf4Zf1IT5hild6F1o5/k+OjlmssKVCmAWN17bKwlU7gTSVQWrcNvvtyn+pL4bZghTxBOq0RIC3Ana+ypdJ6JSx5cB7U+k6vqrI8NHKjwxXHla8MLvuMhxCrfRhzc9jNt+vw23rLkF535/rsMDpcnS5LC2+Xn5Icw3zKEQEyF6PC6Kooilvy/FDb/doLjnp319mqJUT09afhWJiVT9w5Uipr0Fnyulh7pskDulT36DnHAw1BCK1JBUaMF/xi/5v+CN/W8o9vHCebWx2qPM3hJql2f+v/R97KIdTZYmR8y9r97XoRhpz4uJx2VZI9Ucrb73/t7+GBUhK2fdlRU7WHXQ0Y+HhQ5DYmCiY19XWn7VfUqNJ8q+k+GH3B9w/vfn47zvzlNUfHCHKIq44bcbcPnPl+OBjQ+4PM5Toagr4JWkahdXNfyzxT/7E6MnOjwxqlqrPBLQtZQXLi2/3P3g13Ce3vfe4NW9r+LiHy/GRT9e5NLzQN2HXf3OiphfN8LvhOgJmBIzBQALA7pn3T14dMujjv1npp6JxKBEhPmG4eL0ix3bpQzR/JpYGgvVyml+PdqZMTizOhMPbnzQ8X589Hjodc5xxa4YjHlcSPjtY6itvrzWsD2LijrBx7iocY73fLkadxitRkcG1bUn1rq0GPMD59jIsY7X7oTf9gYbb523YxEsLUwA5+/FW23V34vXRvPlNNSMi5TvDV903pUWvaNJr37J+wUiRNhFO34t+LVD5/YleEFEsvwCg3OwBJSa8zBDmOIZ4+OBeNSuSOlh6QpXqpvG3uRwzeKvoRBIDcGYED1BkbDJFTPiZ7hNdKHl/qnO8JoQmOD4jZstzQoXWB51ZlGg/b6h/l5eOi+MjZLHEFdjVVkTl3gtMA43jb1J87iKlgrHOKpQVrQlfuGtm56Oi5uKN2FH2Q6n7Wa7GWuPr3W87wrLr6fZntX3ke+LObU5mp+tSDro55x0kFfC8GO5uzE4pzZH4Y7Oj8Hjo8a77IuToicpamvyzIqfBR+9j6NP2USbZhylK3jPAmlh763zdtQXFiGiydKk6PdhvmFICkpyvPfUGugys7OqzJVWjXt3cxkPP7aMixqnFOQtje1mSfcUdZ9S46p/dBW/5rO5stHSiLcPvO3RORUtFY7M4qsLV7tUaKmFIk/vfWdQhMdoeD7wyknp2bLZbQqra5CP0sPiq6NftXtdrRrNriy/vDDFr+H49VBf4+e8nwEAJxpPOJUuktCaNyWO1BxxvPbU8gsAfxn7F83tAgTckHGD4/21o691eHPsLt+NfRX7FHHUkvAb6RfpyJ7urfN2CNeA52NwbECsw5KsZmbcTLffR40ilG2QGDO8ersBhBJ3PvvtLSr5RVOgT6DC7cHTiUrtxlfQUKB4GCX4AWZ89HhsLd0KwP3AWdlS6XjtKsFAiCHEkaq9wdSAYJ9gJ40X/70KGgpgF+0OJQH/PSWruRZSTUtAuSB0pUXvqPDLt6M/x9HwiXZ4N8TBKvzyGv1Q31BECHI/1nJNVccxSlbHp2Y/hVf3vorkoGScnXo2dpTKgpV0DfViLcQQgufnPY9vc751xNmqifGPwbIJy9x+Bz6JjfRsabkvp4WmOX7b/Pp8DAke4vRZWoutDgm/becMCx2G7aXbHdfSgn8G4wLiMDpiNJ6e8zRW5a+CTbThWN0xR0Is6bdQ/16Aclzw9Nnk6zymhaTBKlodwhH/HbWE34667Gq54dYYa2C0GuHrJSs/1PeRtwaqE4NJtJfkhf/t+HuntiiFGEIQ5ReFytZKWOwWlDSVIDk4GYAyaY67MTjUNxTPzXsO3+d87+jPAgTMTpityHUhfc+q1iqFksgd6rlQItgn2CFgNJganO5hXGCcI146vz6/Xaud1C4t+PlOfZx07xV90U2yIf7cGP8Y6HV6BHoHKhTE/HPdWRTWUR/nz+P7R1eXWAKUz+Mv+b/gjol3ID4w3u05aiXDewffwyunvOJ0nPq37sw44Cn8szMxeiI+yfpEsT8jMsPRz5otzUzwtcqCr7+XP/Q6PS4bcRnWF60HAHxz9BvcMvYWxzimhZbygrf8SsKv2WZ2eDboBT0yIjMca7i+ul5psbQo5gBXz53T7xwi/86FDYWw2q3w0nm164nIMzthNh6c9iA2FG9wuJ/rBT3OGnoWRoSPcBwXFxiHs4ae5Uhk+d7B9xSKON4L5qnZT+Hjwx9jQdICxfXDfMOgF/SwiTY0WZpgsVngrfd2GoMB4Jk5z+CDQx8o9qWHpuOKkVe4/T5qBmPMLwm/fQx3sVKKRaVqwBdFUfGQBfkEKR40j4VfVaKG/Pp8beGXW/TyFtaTcXsG2GAlDXDSIKaIN/MJQphvGEINoagz1aHV2ory5nLEBTLBTEvLpoWrBbraNUqa4Dss/DYMDOFXUeYoUFv4HUxJr9SWRB+9j2OiqjZWw2QzKaxZvCsj74YfYgjBP2f807GPX9BI19ASEhcmL8TC5IUn9R38vfwdbW61tsJis2gKsanBqQqBlLdWS2hlhm1vInV1LQlPhF/JC+H/2bvOMDeqs3tGvaxW23e967Lr3jtggymGEFNMC90G25gWCCFAChDgCyGQhJAECL1X03sLHQKmY4xtbONedl22V6265vsxO1f3ju6MRlppV2vmPI8fr6TRNN259y3nPe/xI47H8SOOByBR4uRskbytMlOvPJaeLMf3Dd8TSrtFsODeI+/F8l3L8ecv/pxwjdmiPQOSQ0sHIJT3scRZAotgQUSMcJ1l5bnw5mDGUKbGujLrAEjza6NfcvC2tW+LO78cmp8ajhh6BI4YeoTq5yXOEvIbNfmbSLYkGZi10BrPktLrS3uoPUHorcZbg49rP064Di3Q819VXhUJdil/d969p+8PLcaTcIxAImsq35ZPfpeOYEdmnF9OGQMNOviQaguvZPBH/AzTKCpG8ejaR/HHA/6o+T3l+iOr8tLOrVLIK137SA8CkQBxLC0mC5NVlTGyYCTcVjc5J1/Exw3YHFx1MEYVjsKm1k3wR/x4esPTuGjKRarH5gUv6HHRFmxDTIwlzNt0BjFX7RUlE0PN7lDOi3m2PJQ5y9DgbyCBugp3BbHtzIKZyY6rYcG4BVgwbkHS7c6deC5xfj+u+5hha9FjblzxOPz14L8mfN8kmOC1e8nz1RZsQ6mrlDsHTyiZgH8e+s+k55QMP8VkhkF7ziE0+ZtINNBqsmJCyQTmc60BGowGCfXMarLCbrYnTO56BBNog0f+nhLhWJhkZ02CiXGOd3TsUKVg6amx4NUjMosCZXgpzzEcC6O2I67+rFX36LV7iWhTV7iLLFb0oiDXTAOptTvqDncz2+/u2j1gRaGU2TYZP8VIoT/iJwqyNpMNTosTFpOFaUmhHCd62w8xvRh7AlBKwzxTEASBpT6H2rlOLGOYqziJPAc9Vdqz8lhqxpey37QS9HvyuKWZLHKAIdV5kVb1PHb4sQl91+WgnlLIi3zeC9ozPbaUATjlb2Y2mVHujjNaeHNWMueX6bUeaidzOc8wVxsf9N/JnN9kSHeeUc380usLJ/ObamBEeV70mpGq8yuzmJIdQ/4u07IsQ6JXaj1+ZahRaDMBHs38pU0vJQ2u8sYFrcoL8GthB3sGE4pqfXd9xoSelAG3cnc501IMkAJwdJ1tV6grQQsBkOZqWnDpqfVPJQip0eAFL6wmK9mfLPCmdBCzFQjIJJTnpSfzq7aW0YGbIkdRSvWxyTC8YDgOHxLvKiDbDHaznbtu8cCzB9TmtEzAcH4HGARB+FgQhIAgCF09/zYk/1bugskSlUxKqIdiBEAUC4IyOwpINV1yjVNnuFMXl5+X+VWCnjhlCpwsgBSMBrlZ0nAsTAxRAQKTYaDBKNH2HIdH92Am654sa21nLREFqXBXwGV1qV0mBEHgZi9pKhedZUgl86tsMyJCzLiaZF+Bl20DfpqTJR0YKnAUkFpGntMlg2lbVjYDaqCNSjXBq0xCGWTiHUuPQcRzZJONDZ6ojh6HlM4KJXN+ZcePl/ktchSR4/ojflWKMCDVs35c9zEAad6Sxcp4cwc9T8mBNUDK2qXSSoV2oJk5SNHrl3cf6WeUN2clc36tJiuZY2kl5KRzcM/4iMai2NEen+u0ApB6kO48w8uSAIlK58rxm44TQDOaaJq0cr3lBX+LHEXk2fdH/GjobuAfg/O7KQNYmUCyOYdHoc0UePc7GA1i2fplmt/jjYu3tr6F3V3x+YJ3XVaTlbAVgMwJPdH3pcBRAJNgSngOarw1CQJszJilnJt51fOIynZbsI1RRVdC7fejmUUtgZaE7ejz29G5Q7U/e39CWRagl/YMSP3nyX7at6VU75sOeHoU1fnVjIaPFnhMMCWzM5P4KTL5BrTz24NLRFHM6/k3JvnmuYtkWSItQ4Cpi+1Z7AVB0EUnpKFc0LjObxqGcmuglahqFjoKSSNvJXgLOpdyx7kuhm6XnzzjwFOlpa+NNmRScX5515+rzeO1FFR9YR+5HzaTjaG80WNRpj7mEkRRzGrvRjoyyzgclIPSGeokAhtyE3s10PeWZH6TiM/0Bsogk1LwCtDnkPIcsGTiGWoOs/xsd4W7Eua37nA3OZbFZOHWqybN/PY4GYIg6HZy6AzS4UMPx/CC4QnXyJs7yl3lhO7mj/gJU0aJmBhj7quyl+OoglEJ1yRvx7uPvAAADT1GHzfroHMO3u3bTep3ix3FvWYspOv88px1IDFbqhy/9LjQYjHJCEVDZB8mwYRRhfHfS0/mF9DHsOA6v/bEQHFvwZsHaPAotDRSUeRWgn4OaWfsmQ3PaLZqpO+N3P4sIkbw+LrHyftqdG499z5V0FlFUmpBHccsmDHEM4TN/Ia7VDN7FpMFSyYsIa8fW/eYaksnNbVu+pluC7Yxc4fH7pGowT0sk0gswijY5wqUZQGqzi/nt1bO98m0D3qLyaWTmVZEynNIhqSZX2rsZAJ659nePN+5hn3B+d1nsLKeqvdV9AEDtB0OtYlTNtYAfc6vUvCKFwVMx/nVO9nwMr+8a+NdF9NPjfpcDbxoF0N7LmJpz3qdKd4iuq0t95zfD3d+iDlPz8EF717AjfTSxnOFu4KJWuZypLAt0IZfvPYL/Oz5n6mq3qa7Xxl0ZFbN4VjVuIoEfOQm9mrg1vxyamMzBc0MWM9n5a5yor7eEerg1vj1mvbc8x1BEDTrzpix6KrgRtDpIMRe317ExBgbsKCyVnpq3HZ17SLqswDb75Fu9dUSaEE0Fk24rmSU3bXNa3HE80fg1NdPJXNcd6SbGBhOixODPXERK9r5DUQDpNWH1WQljrYWCyEcDZPgpkkwMQYWDWYs9myfbA7e2r4VoiimPAcnQ9qZXw3BKxk82rPX7iWBKDUWEw36mSh2FDM09QTnV6XHcrK1MybG0OKnjtPzXV6/7t4iWeaXR6GVsbpxNQ5/7nCc9vppms6qGuh1c8mEJRjqkbKynaFOvLDxBdXv0fdZrv8HgBc3vkjsGZ4qPaCP3ZIqmHWiJ+BGH2eIZwisZiszLrtCXap16gBw4sgTybjc69uLt7a9xT22WsCUfqZbA6262De5BmUCgWd3hKIhQjM2C2ayfinn+2xnfgF2vQBSc365mV+F8GsmkW/L55YB0li+azkOffZQnPfueTnJDEgV+4Lz+zdBEJoEQfhMEITDeBsIgnCBIAjf9u1ppYbucDfWt8Sb2NMy/DK0HA61iTPVCU2Z+Y3EIqjrZNuccAVrqONsaE1kn/PaPPDAq2PiXRuvNivVzC/POKWvrSqvitDG/RG/bnVLbuY3BxeTe1bdg85wJ77Y8wU+2/VZwudq9b5AbjdFf3v729jcthkN/gY88sMjGdtvSzAxog+AUSOl79kPTT+Qv+l2CzwoI/OAusGWCdCGUXuwXdUhTTZ/8OqS6YXUF/Yl1KipGdhKahoNZizm8eumXFYXOYdwLIyWQAs38wvomxff3/E+oqKU+du/Yn+mHZPVbCX7k51sZcYhmeP20JqH0ORvwobWDXh/5/sAEhk8as6scg4mFHzq3tC0T4DNwhfaC1Xr3JisQ8/9483BZa4yUsvYEepAa7A15Tk4GdINsumhPSsFr7hrWYt2JZXSiFb7zekMsVkwM/c4GTurPdhOynk8Ng8ph8qK86tDZ0DpSMl4dsOzaA40Y33Lery+9fWUj63s1HDOxHgLGa12gfS4OH7E8aTuOhAN4Ku9kmCfWiBRWXOdCfACbjQjQP6bttM6w52aNZ0OiwMLxy0kr2UFaCVUac+KWm1uAoMah5lu/dRbKMspAH2BVXleVGb46eRRtpzf2ZWzSXcHAEyXkmRIxr5RBkd6C2UZIO/ePrHuCbQF2/DVnq+Y7hQDFQPd+b0SwHAAVQDuB/C6IAgJvRVEUbxfFMWZyvdzCS2BFkwvnw6H2YGRBSO5C49ycNKZSLWJM1XaszLzy/seT1CAVjSk6xxlMP0lXYn9JWUoF3QlDdBtk5zRyrxKQp1u8jehI9TB1OzoibIpRWuUQl5uq1szk6KGgUB77gx1YmPrRvJ6RcOKhG3U6n2BxMBBpinGvQFdw0mXEvQWvIg+oF5nSY+DZCq1SoOSp06aSSRkflWMXl5tPQ01p1mL+pzOsbQCMTSY57VrD1vzS2V+k10XwPZcP6rmqITPlY6Z8l5oGROiKBIFaQCo90ljVjmPq7EKeHMwoE171iM4CPBFjXjri7KWcVv7tpSUnvUg07RnrcyvfB/pHvC8tYyGktFEz4st/haSxdcS2GEcME7dqVqWKhu0Zz06A7xAHRAfwwDLYtODaCzK6GLUeGtw5LAjCY15Q8sGVaEn5v64SjCzIm7qyWUoas9LqvaRHjA1vz3P0qGDD8WRw47EqMJRpGesMvObzLnZr2I/8rcysCVDbW5VBrR429FlObT+TC6ALqeQwbM71K6/3FXOBOo2t24mn2XL+RUEAdcfeD1GeEfg0MGHYu4Q/V0a9M7BmQSd0OAFGun1pK6rLuHzgYYB7fyKoviVKIqdoigGRVF8DMBnAI7p7/NKB4M9g/HwvIfx+Zmf464j7uJu47a6yQMcjAaZyVIt0t3bzC+QaBzyKDMTiieQiHRtZ62uHoc8KBd0JQ1QdnjNJjPT9iMdw4uhkXc3chUhkwnIKKFcxGVsb1dX8uwPrGpcxZwPz1hhevwqsm0uq4tkxcOxcMYyD5kAPdZ2de1KSalbC2oUWjWHI5Xx6LF6YBYkg7g70s0sPvJYzCT00J6B5POH2ve0FtJ0KIhagRgaymBVuplfURQ1284BiQGgVJzfnZ07GYdI/lyZYVXWk8vGntp91wrW6aX60WNbvn9qhrnyPuaK86ua+dUh9EbrbaTi/JY4S2A324mzHREjZK3UuveplAwxzm8/0J4B9cwvfZ4rGlakFBDd49uDYDQIQAoOeO1eeO1ejCyUsmVRMYpVjau431XeH/oZkJ1EPWwTuQdsb0HfE/lZspgs+Pdh/8ZLx7+E8cXjASic33BXUlqrnkC8HsErtcwvPe6/b/w+ab17X4L3XIRioQR1fbXrV7KYvq2PE0GzUfMrY3zxeLxy4iu484g7SZtDPeDNwVq0+Ewg2VxLv5dq689cxIB2fjkQgZ5Q4QCF1WzVbOquNkDVIt1DPEOIUb3bt5vL5aehVHsGtDO/RE7fbGWyv8qMm17as5KWxhPyksFMZnu/JZNDnjVPVzRPmbnhOfWVbj6lVQ27u3aTWrwSZwmp0wlEAxlzwjIBOqsFAD80/5DQjilZti1X636VE3emothMj18V53ePT3JQYmKModElcwQEQWCcs52dO8nfmaY8A4ryAmXto4ogTDLaM/09rYVUj/iMVs0v/Uwqofwt1DK/VXlVhJrd0N2Q0OZke8d2MhfK/V+VUF6jUixIS51f+fzJ2XGlAZxnyyPzeSgWIg6zmjARr+6ZPkcZWgYfL+ugZpgrf7NUxrweFNgLyPrVEepAKBpK8g0JdJaEEbyysWU1vLFIOwHrmtdprpk8+iRv7Gvde5rF1OBvYO618rv02qksXcgEkgleAertjuia5obuBkadPRmYWnGqPpMOOvECEd3hbsLWspls8Fg93GCk2pzjsXlQ6pSYaHIP2N6Cl/nlgaE9hzqTChqVOkvJsyD38VZCLbCYkPnlOIlVeVWkZt0X9jHMsP6GWuJGubbQ49djZx1Eej6iA49a9mh/oV8yvy71NTsUDTFjxnB++xGCIBQIgjBPEASHIAgWQRAWAjgEwDv9fW7ZhJpRqSaTbzVbMcQzhLxOJuev7PMLJHF+qQlWK2KuN+ugpKVpRUPpyezD2g+Z9+VaDy0o7yWvQTyd8VS2GuGBzpLXeGsSaIG5AuXvE4lFsLZ5LfNesmwbLfqTS3W/CY5GhqjPamrPebY8YsgEo0G0BlvR0N1AjGav3asqLkSDds5o9kCmlZ4B9jmr764nGQ+72c60WNOiBYqiqGpsaYk9qc0fQzxDSN/NPb49DM0xHdrzrq5djDFEO/wWkwXDPCxzhAb9fEwrncbNvCvr3rUyv0qBQrX5kWcAc415lXvotrrJa9pZpo8BpJb5VZaeqDm/3zd8T47nMDs0M/R6YRJMzDyjN8hGZ0lUM78cwStAypKN8ErVUxExwtTuK8GjkidzfpX33mKyMCwm5RpNH4N+rvor88urR6RrmmUoAzxaUGMM0DYFbx5X3n9BELgZUq3r0iN+lwqYIKnGvK8peMUpczGbzCh3affxVnPyEzK/nO0EQWCCDZksGeot1H4X5Xyg9TuraRBki/bcGyRj32TF+dUIWCvvsx5bONcxYJ1fAFYANwJoBNAE4NcAThRFcUD3+k0GtWybVtRQS0iGhiiKqplfmsKkJh5BK1QrFz69hpdS8EqrDoZeJFc3rua+rwXGQA80cReEVGnPSsGXXFRQDEfDWNO0JuF9pUGeLNuWq71+kzka6ULZv5FGRR5LT6WVS2vy9QVjmMxvR3Yzv7RhRAvaKY81NH8ocfx2d7HMEX/ET5xmm8kGh8VBPtPM/KoYKFaTlVE3prOI9GJL32sl6M82tGwgatsemyehvZrWs0nPX9PKp4EHreBZvi1fUxRO1fnl9GvnGvMaSuBqNHy9c7Ay6+CP+Inwl8PsYO4jMwc3xefgaq/+npbJkEw1mwddas/KzC8dyKV+cy0njpfR5f3uye69Vg262neVWezeIhwLk+fbLJhV26nwlGh5QYlU5l1l0FgG7YytblxNWFUy6GyzfG+YgHXP86LWAgjQbx/pBW1DKdcJGvT9TRC8Urn3yewRtblVGbBIJ4HRn6B/F9oO1Lu2AOp2YS46v8nYN1mhPWusV8rXucRiTBcD1vkVRbFRFMX9RFH0iKJYIIriLFEU3+vv88o21LJtarRnQJ+4CyBRXWRj1mlxqrY5UROPmFI6JS5Q0bqByRbQoje6M78h/ZlfPe8robyXvCxWsr6ZSigj2Lno/K5rWUfqq2jQRl40FmUETHhZnFx0fqOxaEJLno2tGxOohOmAqeVSRPSVDko6LV/oaC/t+PW2VyoP9HNW21mreiyb2YbBeZJDKkJknHK1eQBQHxvJhLx4z0tMjGFvN9vqSA3070ArlvIyMFrPZrJ6XwAJtGal2IpaoLLZ35ygLEtqfjllHjyDV+veq9UG6p2DmaxDsFVzDh6WP4zM+TQyofQsI515hhdEANhx3xpoVc226c2A8SjJPLp7Ss6vYiyqKdNmWvCK3ofH5lEN2PEyv7zfJSXnVyXzOyhvEBnP/ogfG1tYKi6tLSLf9yJHEQnQdIQ6mH71QOLzkulev3ozv/R4UwpeqWX2aMdeaY9oBS+UAQs1RgydwFhZvzJnhCzp8TGjfAb5W6ukRut3luEwO4h2SS6BnoMJ7bkPM7/KYJbyPtd31+dUTXg6GLDO708Vemp+E2pjdSoaKmmdaguyWhTVY/MQVduYGGMEKniLFA/KBYFetLSuS8/7StCiTcqWTjznd0v7lqT9CzWd3xxRfKbFraaWTiV/f98QF7lo8jeR9hpFjiImqydDqZadC2gNtiYIiynHYrrQquXScn71jsc+zfxS+6QXVd6x1OYBrSi72kLKE5VLdqxmfzMJyhXYC+CyutQui/kd5FpAgJ+BUbuuJn8Tqbm2m+1EoEYJ5fjXK3jFcwr8ET+6w91cA0dJ5Qa0771SJIt3Drozv4E2zbXFbrajKq8qYR+ZqPeVkeo8QzsBJsFEgrgAu77Q48Nj9TAKzIz4T8P3qkJIvHvKo7snq7fWcn7VVLozTXvWQ3kG+JlfnvO7uW1zWu0BlWNHi/rMu/9Kocq9vr26M4K9DVAr2XN6M79KwSs1dX8t0Sut4IXezO+oglHkvBr8DWS+6U+0BlrJPXWYHZhQMoF8lkrml2YxySh2FutiZfU1XBYXCeD4I374I35WxyALmV8tho1y3o2K0QSG3UCD4fwOMKRa8wvon9yZVi6OAlXHTU0cB+BTn2lRCqvJqrmwmk3xiKUIkYluKhcEl9XF1MDISMXwou/n1rZ41Fe+rkHuQaRu1xf24YWNL2juTyncwUSV23ofVc4E6LZGJ4w8gWTAO8Od2NwmtQDQo66bi4JXaueRSv0ZD6IoJjwfNJTZuVTbbgGs00FnY7MteEUjJedXpb4MUJ+ntOiHasfSW+8rH1cWsqKRSuaXHisTSybCZrapHktGMsGrlkALCSypZRKb/E1cA3ho/lDynpwx1hIm4tE+5f3L0ApAKg1ltSyqDN74zprzqyPzSxuJbqubMW7NJjPXcFTeQ1r8pzvSjU2tmxK+I4piejW/HIEdrTVaLWjhsXlI1r0r3NVrpWK9zi8386sSlNAjNtgebCdsHbvZnvCMM1l4neVUSidRy2aha363tm/tVbazO9JNqNkOs4N05+CBfpY6Q52qCuU0NJ1fjd8v35ZPxkpnqJMJ5NLbmk1mTCmbQl7nAvWZZslUe6vJcwmk5vzyAnW5SHkGpPpr+jnb07WHlJ7YzfaUlKP1QivI2NSd+HwPdOqz4fwOMKgNUK16AHph3dGxQ5WuoJX5pR03rQmGp87IE6XQAr1POvLIWxDohQsALIIFQ/KHJGynBpr6TFOe6J6lSyYsIe8/vu5xVcVROkLptDhR7i5HpbuSCAg1B5ozpsqZLmJijDFIppdPZ6lOPb8ZPbGpORzp1OJlG/R50FHe3i7iXeEukgl3WVyMKBSQSI9Pp+ULTXWiexpmW/CKeZ9zLDVBGDWxK0B9ntIyQhOO1ZHo/CYTUTIJJm5AjKe6ysyLnfE2J3ooz0Dyml+b2UbuS1SMEoOTZl7QY7TJ38Q1gGnmgBxU0ZqDe1vzS2fklYaynjkYyKzzq6WazQPt/PLGOW/cKbfTI/7jC/sQiEqKuzR9khcUTEp7pn7jnZ07mdpW+vmh74VJMDGB7t6WduhRegYSxZMA9XlXj2gSPadU5yfWijP11w3fMc6pGpVfGYzUqpEvc5UxPWB5uid6wbRW08j6AomtjtQUymlo1fxqBRbNJjMT8JTHl8VkSXDQ6XFP9yLvLyhZVFpB92RjWDlX5arzC7Djhw6GqwVGegulPUc/Zzz7bqArPhvO7wCDquCVRubXa/cSJy8YDaoOWqWgj1rml15klZPs1LKp5G9ZoIInSqEFetKiWw/w6hyURtZgz+AEYRst0OejVmd53IjjUOaUoo2N/ka8tuU17r54i7iyH7Gy1q+vsb19O/mdC+wFqMmv4Rp5erJtuVjzS5/HzPKZ5O81TWsQjoZ5X9EFtTZHMuh7tKl1Exr8DQAkpoNW6zIaam0xspH5dVqcRFk52bFUGSAaBqXaQposu8T03WyXAnV6AjE0eNvwfjO31U2yCJFYhATaaIOdplwq4bV7yT3sDHUy87F8bcpnpDvcjfUt68l79LPX5G/iCjUNzR8ab1fXIzqm1/mVn+PucDehAsstYdRgNpkZMSW6HETPHCxAYOa83kLZjz0Z1JSeZXAdYs57ycR/lJl0Oair/M3VMsQ0aBYTXYJDqyibBFMCgyGT1Oe0Mr89zh59ffS8qyfomCxQOLJgJHEGWwItTBs4NTYDPefWdtYS5plJMCXUeJoEU8a6MjCt1ZIo/NNjsyPYwWikqNWhammQJAss8ubAfFt+QjIi10SvmPFRUJNWJwHyfcX4ymXnlx4/tPOrFhjpLZwWJxmTkViEuZeG82ug36H24CeLGuqhPisFfegomZxxCEdZUQXlJF3hriDUkkA0gB+bf9RNt5NBG16086uHcpdqxoGe/GgRKHritJltWDRhEXn9yA+PcLPnjPNLGfG5JHqlNOwFQWAi6/JilyrtORed33FF44hYUzAaxLqWdWnvl6nj4jiptFFCBziG5Q/j0nB54BknQHYErwRB4GfAOO/RhuH29u2kplpLREa5kMoGvJYgCcDWyoZiIez27U6J9qy2jVpgQfls+sI+IpQlQGAogEqYBBOKnEXktZytp4W8lMHKNU1rCH1tZMFIZo5NoD33OKg2s42oYMuiY1r3kZcdUmYek7Fv1LIOeubgyrxKrkZAuki15jdZP0y92eBk4j9q2VxlFwG1DLESvHWCFu8rchQxdclAYr/u3iDZsymDptB2hDoQiUWYe3HksCPJ3z80/cAVV6SRzPk1CSa27peiPuuhPdMiWfm2fK4KOS1K2Js1msn8avT4BVjntzvSTZTpnRan6prBBLa69rBdODitGmnwnHHe7zyxZCI5/tb2rcw19QeU40NLlTjZGFaOLz32aH+hrzO/gLpNx5t3B3q7I8P5HWCgabpyHZkoikl7xOlRNFRO3EM8QxIyDkqqI8+IUgpU6KXbkf2qZH6z4fyWukr556AwkE4ZfQp5b2fnTry3M1FYXG0RzyXnl0fpHFM4hojC7PXtxe6u3czEpuZwFDoKiRHUGmjtdc1ZJqAca1rtt1KBVpsjQBpH8rNCI5XxqJYpyEbmV22/vPcKHAUockhOXiAaSNprVgZvIdWTXVI+L/QcoNXmiGzDCdaoBRZouunW9q1Y1biKOPejCkclvfe8+YymDSsdIXoMTi+bjhIXe4/UGDxK0UKt+1jqLCUZ6ZZACwKRQMpzMD0W6UwbL2Pc2zk4GVLVFmDWQh31vQB/LCYT/1FjNBXaC8nv3x5sx25ffPxqCezwygvo363UmbhW9UfmV0mhbQ+2M+c5qnAUCZiFY2HNPslAok4GD2rZSLVxTc8BtOq76pyjUxQ0GZKtEzTMJjMjxiZDK7NH95RX9vHW0mAA+M447344LU5G5E9P3XY2oWwbSAccW4OtTCJiX8r8MgKY9BycpcwvoJ5c4827A73mV19KwkDOwGq2osBegLZgG2JiDK3BVuRZ84jjYTVZE+oRAfahf2XzK9jWvg0WkwVHDD0CsytnA1BQdhyFJOOwo2MHyTjQlGK1uqDp5dPxxtY3AAAvbHyBUWfV5fxSkxZd+8iLePXW8KKDCcw5KK7NbXXjzLFn4r7V9wEAHl7zMOYNm8cYMmq9CjO1sH6791t8vvtz/GLUL5h+qKmA17/UYrJgSukUfLHnCwDADV/cwFAz1Zxfq8mKQkchWgItECGiNdCqGkwIRAJ4dsOzzPUXOYpw+pjTUe5OrNGUsaFlA97e/jaOqj4KY4rGJL0+epIudhbDY/MQmvqLm17Ejo4dCd8pdhbjzLFnMmNTFEU8t+E5+CN+LBy/ULPNESDdwzJXWQIViM6aJoOasZQ151enEwBI1yEbWlvbt6IyrzKpsVXsLCZZ8KZAE0ZiZFLBK0B6Xr7Z+w0A4ME1DzK/mZ7ML49mrifz+9rm1/CB7QPyWqveVwZvPqOvi/782Q3PMuNzevl0RnG4OdCsquhZ463Bx3UfA5Duv9a9N5vMKHeXE2etvrs+ZfYNfb+S0Z4LHYVkTZLPNZPg0YjpeXdlw0p8tusznDjyRAz2DM5Y5lcW//ls12fkOPS8q0ZlNpvMKHIUkXv+r2//xd1OCV6QNNnvlorzK4oiXtn8ClqDrVgwdkFCdl6v8wuA+b3bgm3coKP87N/+3e0Y7h0Oi8mCedXzsF/Ffsy+1NZNGjwtkZgYQ4s/7vypZX7pumC9ATct1HbU4uXNL+OQwYcwZV6Adjs8Hjw2DzMHAMmVfCvyKtDZKgV49vr2knGR7PdToz3zMKNsBlY3Sn27VzasxNyhc8ln8jjS6qAwuXQyThp5km4l5Q0tG/DK5leYPvIy5HlMLqewmqwotBeSzg6twVby2yd1fhWdF3jic7kC+vdKNgdnCryAtSiK+yTt2XB+ByBKnCVk4WnsbgSo4KFaVIie3De3bSaqvi9vehlvn/w2Sl2lXMpOTX4NMT63tG1hDEu1iZNeqJQ1rnomG7X98q6t1FkKt9VN6mV6Q3tOdg4Lxi3AY2sfQyAawPqW9VjVuIpZ/NTa22Qi87u7azcufO9ChGIhrKhfgceOfizlfTR0N6CuS5pEHWYHxhfFo7vTyqcR5/ez3Z8x36PVY5UodhYTp2hHxw5V5/eZH5/Bv1b8K+H9Ta2bcMcRd3C/0x3uxgXvXYCWQAve2PoG3jn5HS5ljYYyG0M71js6dnCdX0BqLXTLobeQ1+/ueBc3fnUjAGlBpTMdao7UIPeghAUhI5nfLAheAfwxrkZ3rPHWEMr8tvZtmFM1R1PwCtCR+VW5LvqeKWvOMlnzqzzWlvYtzGc0a0AN3GwcdV3057IxSfZfNp3JSjX5m9h6VTrzS53nuuZ1RHzNbrZzg50V7gpiNO7x7WEyB7xzVoK+X3TGU2t9kX+rTDu/LosLTosT/ogfwWiQeR7bg+24+P2L0RXuwrf13+LRox5NqpqbStBnetl04vwu37Ucx404jnxGzyVKx7TEWULG/Oe7P2feVwOPnZUsY09fSzIxxU/qPsH/ff5/AKRShAsmX8B8rlfwCpDGh7y2twRaEs5zWtk0vLTpJQDSMyyPjde2vIb//uK/5H4Fo0Fi2AsQGGVzGhNKJsBqsiIcC2N7x3Y0+ZtgFszkOfDYPMxzoFaqo2fO+bHlR0RiEVXq8e8/+T3WNq/FMxuewbsnv8s8p6lkfuXzru+uZ95L5twMcg8i6uN7fHtI659kgUVu5lflfkwrm4ZH1j4CAFi+ezkuFy8njuw7O94h40gNL256EUWOIhw25DDN7QAgGovikg8vSZpJpMspip3FTI/pEmcJApEAodjzhLwA6TeRHWdAnfmXC6B/Lz1zcCbA01foCneR+ypAIPT8ge78GrTnAQjauKvtrNXswyhjaulUrnEdioWwpmkNgMTMLyBRmGSsblqtm7Y4pjAxS2cSTJhVOYv7HRpqEzLv2gRBwNwhUlSywl2BsUVjk+6fhpoxwnMCihxF+Nmwn5HXdHY0GA0mRChl0H/XddYxSp568djax0gWfGXDyrQobnS976TSSYxc/s+H/ZwrgDSuaJxqdlz+XMbTPz6tut239d9y3/9izxeq6tnPb3yeONZ7fXtJwEYLSiOsJr+GOUc1LN+1nKFPfVL3Cfn76R+fZmpu1BwpnsGlRuPjwWlxwmZKbKvT37RngB/ASYX2LGfJ9Mwfc6rmcMfi2KKxupgjqdT8Ti6dTCjdNLx2L2YPmp30WMmycQdWHsj93tTSqRiUNyjB2KBFb9ScXzrjonYPlWvEcxueI6/HFiefI+kxTs9XauuLPAfbTDbVa04XgsDOp2ub15K/VzasJM7uqoZVCMfCSfulpjLuD6o8iPz97vZ3STlIZ6gTr295nXxGBxIBaQxz91d1EPd9gF1r17es10VXTyXzS89p9N+87yebc2hboq6zjhjHTosTLosLc6rmcDOY/oifsDoAYG3TWlIDPyx/mGprILvZjoklE8nr7xu+17w3TouTa++oMlu81WTNb/Q34t3t73K3a/I3kfHXGepMyH4qO2YkA+950uP8yqAdkHQFr3iYUTGDBBM2tW4igXFRFPHA6gc0z08Gb4zxsKltky4KrTzHAHwnTTl+1bLOhw89nOxjZMFIXefYH6DXJT1zcCagXDcA1qaqzKskNkpHiBVpG2gwMr8AwuEw6urqEAgE+vtUdGFRySKc7D0ZAOBp96CjqwO3jb8NgESLXr9+Pfd7d0+6G8FoECJEJkrmafVgvW89lpYtxaISSdjJ3mzH+tb1ONh6MCaMlyKLVpMV7hY3OZbT4iTHcjgcGDx4MKxWK0yCCQ/+/EF8uutTIvQBADPKZ+hSAVWbkNUWhT/N/hPmVc/DhOIJ3CyIFngGhVng1+IArIFCZ3F3duwktYJVeVUMpcxldZGsYESMoLajlhHYSIaWQAuJogOS6M2qhlU4ePDBuvcBsC1WlCq2IwpG4LnjnsP3jd+T9xxmBw4ZfIgmdens8WcTWvF7O97Djo4d3N+YvlcXT70YL258EfXd9ZIQVfO6BPpYKBrC42sfZ977rv47jC4crXmNPGGf+4+8P2Esyrhz5Z1oCbSgK9yFzW2bCbWazjh2hbvwyuZXyGutzK8SqWTBBEFAgaMADd0N5D2eOmmmoCY4xQPP+e0MUqrvHGOLm/nVUIiWUe2txovHvyi1NemJMstjMVnmH1Cp+VUxRN1WN56d/yy+2P0FySKZBTMOGHSArswNb/6g7+uYojF46fiXmOfKZXGRZ5f+fm1nLZlDnBYnU2JC0+fVenTSoMfi42sfJ0Zyob0Q84fPT3pdamNcbQ5eNH4RxhSNQaW7MqGXZiYwrWwayZJ/V/8dcbDpgF5ElFSS06E9qzEeJpRMwIzyGVhRvwIRMYLH1z2OK/e/Es9teI443dX51Qlz8cVTL8a0smlMVm+YZxhmVsyEGoocRajOr8b2ju2IxCJY27w2Nec3ieAVfa/WNq9FIBJg1im9glcA60jRQclih1TTXOIswXPHPYev936NqBjF57s+x/s73yfncVTNUQnnpKWsLn8uz8vfNXzHzIu8e1PhrkhoW6T2vFhNViwYuwD3rLoHAPDQDw/h6JqjE9Y+JRNlRf0KJqCRSqsjgD8+k9GedTm/OjO/Wv3eTxp5Ep7Z8AwAqczrwMoD8emuT7GxVRIQc1qc+N3M3zH3aHfXbjy45kEA+pWi6VKsqaVTcfzI4xO2KXYUMwGldNcWALj6gKsxd8hcTCiZkFFhvkwj1Tk4E+B1dlDqDpgFM2ES7enag5GFuRtA0ILh/AKoq6uDx+NBdXW17hqF/kRLoIVEoL12LwrsBbB0SD+l2+pmlIZV9+FvIRNngb0AVZ4qCC0CyX6NLhoNq8mKaCzKUPPKXGVwdEsTRqGjEJV5lVIrh+Zm1NXVoaZGengKHAUMRSwVqGV+1RYFh8Whi17DgyzaJBvZgHbUUK1+N5liZY23htzvbe3bUnJ+l61fluC4fdfwXerOb5L+paMKRzHOvR6MLRqLg6oOwme7PoMIEY/88AiuP/B6ZptQNETo1gIEnDPhHOzq3IVXt7xKrkXp/L659U3SLkjGdw3f4YyxZ6ieSzAaJFkfi2AhC7vWWPxqz1d4Z/s7ACRDZkzRGDR2NzKZXnnfMtQyv0rnt9xVztS760GhvZBxftXUSTMBvbWPQPLML09dlGYM8GjPWgb28ILhKT0jNFxWF7x2L9MiRosqVuGuwEmjTkrrWMkcEkD7uaIzx1p0XVl0jBa4AdTvIR0AoEtPFo5bqJpdo6E2xtXmYLPJnPGML43pZdMJs4Sex5QidtvatyWlPacS9AGAcyeeS/qdvrjpRSyesBhPrHuCfL504tKEZ9RqsuKQwYdoXRIXdK3syoaVCRoGSjBqzxqZ3/ZgO+OkRmIRrGlaw9TfplrzK4PeL/08DPYMJjXSVe4q4vzSvx/9dzLnd0b5DDz8w8PS9+pXMoweXjnVIPcghp0FaM85C8YuwKNrH4U/4sfG1o34dNenCb+hcrwpHTza+S2yJzJKlOA9T6lkfumMabLgRSqZXwBYMnEJnt/4PKJiFF/t/QprGtfgoTUPkc9PGX0KThtzGvMdf8SPR394FBExgs1tm9EWaEsaBKADIEfVHIVTR5+quT2gYBUFEllFWr+z3WzHoUMOTXqM/kaqc3AmwFvnldoGdrM97vz6Bq7za9CeAQQCARQXq6sw5hro7GYwGiS0IQC6DWVmH7EgRFFkaJ+ycq3ZZGaiY3RNmryNIAgoLi7OWOZcbUJ22zKfAbOYLAmTjFa9k1r9rh7nl2xLCXwkgy/s49KJU1Uu7gp1YUPrBgDSGJlSqt7CJVWcN/E88verW15FvY+tYaKz4nLdjrKNCI1oLEqMHBrJIsn0JF3kLNL1LPBURJMdRzXzq6iNTqf2MWEsZonyrLZvnhMLAJXuON2pOdCM9mB7UpodLzqfrE44U6ANRK/Nm9AiJlPQ4/xqwWa2cbfnGcA88TQ9mV8ZLotLM3hEoz+yDlrg9Y8PRAIMBRqQ5uG0aM8ac/6cqjmkjMcf8ePC9y4kBneZq0xXJl0vmJ7r9YpOCRwHTy/tmafYq5znUqI905nfVr7zS2Ny6WQyH29s3YjOUCdiYow5hxnlMzSPSa9Z61vWMyJAvMAAT6tC67oKHAU4edTJ5DXt6MlQ3jNl//hUa37TyvxS10V3ZUgn86t1P6ryqnB0zdHk9bWfXUscVYvJgkXjFyV8J0EpmmK88CCKIrP+6xEZBNLvJDCQ0B9zML3ON/mb0BHqSBDd47XSG4gwnN8eDBTHF2Ad11A0RBwLANx2KzzYzPHawmAk0YGmHQeaAuwPx9X4aIMyk/ePZ4AraYCZhHLB1lwQPFVECKO+u57UPDBy/DznN03F5xc2vkCMuTJXGXn/h6YfVGtleVjduJqMk9GFozM6gc4on0EMk0gsgifXP8l8zrs3jNPZuJIZwx/WfkiyH3nWPJKp2uvbq9lbrtHfSP7W28JAaWyKosgYOPQ9l6FGoVXSbdNyfu196PwqDH6nxcnUgdMwm8wY5o3T2be1b0tKM0tKTcuSkBfA/hZ6jNB0wXVIUrwubrskHS2FtI7Fc35PG3Oa7p7RamM8m1kHLfD6x//Q9ENCezU9md9UBK8AaW07d9K55DU9ny0ev1j1mUkH9Hz0fcP3Sec0+lq0nF86u6b2Hh00SDaGacOcZuioKYnn2fJIACEmxrC6cTU2t20mxyx2FGOIZ4jmMb12L6nRjIpRfFT7EfmMd294z0Cy61o8YTHRG/iu4TtmLegOdzMsOCCxfzyjm6Kn5pezDmek5pen9pxCDbSMcyaeQ/6mx/1xw49TFRVTtrrUwq6uXWT8uK1u3cwzXksePWKKAwlqzm8252DeOq+kPdPBl4Hc7shwfgcgLCYLcTxjYoyhxJpM+n5Si8lCHNyYGGNonUqVQzXqpl5HO1VwMyF91Nhb7fgyrCYrhnriipTb27cDSJ75pSmcWs5vd7gb7+94H69sfgWvbH6FqXu9aMpFxEAIxUJY17xObTcJSKW2KlUIgoDzJsWzv89teI5RnuTdm+r8arIYtwfbyTaiKJKaIQA4Y+wZTMRfazFNtZcpIFFS5dqxBn8Ddvt2E4ojAPxhvz8kOAx6ac/pOL9KRy2bi7hynCdTkaTFu9Y2ryU1sg6zgwmmyUhX8CoToH8LPUZoukgmeKUHvLHKM4C5zq/KsZSGqdVkxdnjz9Z9TmoBg/7K/AKKQJXCMZGxrWMb2y6ql4JXMo4cdmSCc+a1e3HK6FOSnncqGOwZTMZDZ7iTUXlNxjLQUnvm3atVDasI2ysUDZE2M1qaFzLU5kCteZded1bUr2AzfuXTdQXQ6TFAU5p1O79JfucKdwWOHX4seU1nf1c3rWaSBDLk64iJMTbzq+K80ODSnpPYOiXOEmJ7NQeaie2WtM8v55lOtr6MLhyNQwezFGEBApZMXKL6HbmFIpDI6lKCHpdTSqeoKmwrwWUV6WijN5DgsDi4JSrZnoOV/caVdpVa8GWgwXB+Byjk7O9+w/ZjeqPRDun27dvx1FNPcb8vCAKTQe4Ox3vNKSmC8kL49Wdf4+IFF3OPlUnwJuS+6m2mdnwaypYUMTHG1NUlpT23b4MoignbAMCVn1yJyz++HNd9dh2u++w6EhUtdZbi+BHHpxRVpUFvq5dalAoOGXwIicp3R7rx/MbnyWe8Po6CIHCv5cs9XxKn3m62Y+G4hdwejzyo9d3UgtzjWMbyuuWEHi5AwOzK2Vg4diHzHbXsmcfmYQyXnM/8Kvad7FipKg7L9fSApILaFeoic1U2hbwAhfOrYqhnAi6rK8FRSPU34znQenqaax0rz5bHOH7Hjziey2JQg1rAoD+dX9qo/q7+O+78t619G9suipf5VdwzAULSwI/FZMGSCUuY9xaMXZByTX8yKOdFGQ6zg/u86KE9B6NB/ND0A3ktO1yyyJ/yu1qaFzLUHDtN55d2ihpWphWQpfeR7LjpOL+AVMMtz1v/q/sfEXiiHTl6vMjX0RpoJQymPGueLkYAl/asYyzSz/Je316EoiGSBFELXuRZ8xJU9PXcDzqwDQBHDD1Cs4sB/Vv+0PwDAhH1crh0g/I046avA6t9Cd48nO05WGmrKttHGrRnA/0KOtNCTy40XVnL+QVY+jTdaF05QVrNVu5Enq06ujxrHll8ZGST6qE0PlNxAra1b0NDdwMx6r12L3fCKnYUM0YHr2l4e7Ad/6v7H/eYiycshs1sY+qikkVVZYSjYaxpXENeZzrzC0jjjq4BkntjAur9j3l1vw/9EI+0nzjyRJQ4S5jt6KysEkxtikZ7JiVo5/rxdY8z9PB8Wz4WjFtAjOgR3hGa0elJJZMASBRiPS2WlFBG5/XSVNOBct/JjkX/dnTPWrVgkcVkYbJly9Yvi38ni0JegFRjKCPV9mepQml4p/qbcWnPHAOYZ3BqBeomFEsq/RaThaEv6oHb6k4Y5w6zI2ulJ3qgDIKtaogHYORAbGeoE7s649lSNeeCXl88No+usXjCyBNQ7pL6hudZ83Dm2DNTvwgd4AUni518TRJG8EpF7Xlt01rSKqU6vxqzK+MtvOT5NBWlZ0A9OKLl/NLXtaZpDdP+Tm9AVm07rvPLqfnVc23DC4aTdjgA8MgPUr9b2lGjf/uVDSshiiLe2PoGeU8W+koGbqsjHSw3ZfZNKfbEGytyNwEaeu7H1LKp2L9ifwDSOq90hpWQVcsBENVyNdA2TLKabxrJSmqyuW72JXjZ+myXnihL9JRJBTXBtYEGQ+1ZgUmPTcravtcsXqP62eOPP45//vOfEAQBkydPxo033oilS5eisbERpaWleOSRRzB06FBs27YNCxYsQCAUwAGHHQAATBaRzsZeddVVWL9+PaZOnYrFixfj0ksvxVVXXYWPP/4YwWAQi85fhKPPPBpff/Y17vnHPSgoKsDmHzdjyrQpeOnZlyAIAt5++21cdtllyC/Mx6iJbD1GtjK/ZpMZebY8tn9xNjO/irq9ZM4vbYRu79jO1rTm16guPDXeGqxukpyGbe3bEhqsr2pcRVSnS52lxEgZXTgaZ407CwC/VjaZ4ba+ZT2JClflVaHcXa65fbqgWz7IQiAWk0WVEq6kMf7Q9AO+2vMVAGlsyZmWSSWTYBbMiIpRbG7bjPZgO3dxS4f2DLBOuKxiCMTvtdfuxf1H3o/3dryH40cktmGg8X+z/w8vbnoRswfNTmsBHiiZX5qOqfW908achn9++08AwCNrH9F9rN5iRvkM3HjQjWjobsCCcQuyeqwSZwkzbjJCe+YYwIPcg2A325kSFa1jXX/g9Xh2w7OYNWiWrhZzNARBQKG9kKk57c+sLyCNP1nFm25hU+IsQbmrnBjZcj90gB9EkNW/ZYdB7+9lN9vx0LyH8OrmV3HEsCOyxijgZTfV5jO31Q2TYEJMjKE70o1wLJwQoFBm18YUjcG7O6Q+tisbVmLBuAUpZ83UaPFa826ZqwyD8wajrkvqCyyr2jstTtJiLhkq8ypR4a5IMLp57IkiRxGsJivTI1Xvb33uxHPxwc4PAAD/3fZf/HLKLxm2y8mjTsZzG55DW7ANbcE2bGzdyJQoKVWQ1cAbn3qeMyb71rUHZc54JlhT1MtewKyTeu/Hvw/7N55Y9wQml07GhJIJSbdXqpbzHNu2QBu2tG8BICVc6D7OyZBvz4fFZEEkFkFXWGIUGZnfzECZ3KE1FIqdxQzro95Xj2gsmrVEWDZhZH5zAGvXrsVNN92EDz/8EKtWrcLtt9+OSy65BIsWLcLq1auxcOFCXHrppQCA3/zmN7jooovwyRefoKQscaGhHaG///3vOPjgg/H999/j8ssvx0MPPQSv14tvvvkG33zzDZY9ugx1OyTFxPVr1uPKm67Eq5+9itodtfjss88QCARw/vnn4/XXX8d/P/wvmhuamWNly/kFEievvqz5TZoBU0wOtHOn1Z6FbkHFq/ulKb3zqufhpjk34aY5N2HxhMVkclGrldVCshZHmYJs3ABxIZD67nomK043bh9bPBYOs6QkvqtrF27++mby2VE1R5HoucvqYrKotBFCI13nd2LJxAS2A8A6xZNKJ+GKmVcklfUf7BmM30z/DfYftL/u49NIqPntQ8GrZMdSc6C0so+njD6F7FcWh9NzrEzghJEn4PzJ52eVXg1wmCMZELziGThmkznhN9Caq6ryqnDFjCvSbkGkHIvZnIP1wCSYMK000TGcVjaNmxU3CSbV2lV6/KXyew3LH4ZLp19KsurZwJjCMQm1fmrzmbKNFx0wlqFsJ8QT+aMdB489eWaJR6HVOk8Z9JwqY3LpZN21nkAic8kkmLhOgkkwJdS+6/2tJ5VOwgEVUnIhKkZx7fJryTpW4a5AZV4lcx43fnkjKVEqcZYkDZLK4D1TyWjPQGK7I72OHx2wsZlsuvvceu1eXDLtEt3tu5iSJpXOFLQS9Pji8bpasMkwCSaG3dXsb94nnd/+yPzSa0xtZy3TXq/YUQyHxUHsuIgY4bIYBwIM5zcH8OGHH+KUU05BSYm0cBQVFeGLL77AggVSxuLss8/G8uXLAQCfffYZzjzzTNjMNhx3WmLvUi2H9N1338Xjjz+OqVOn4oADDkBrSyt2bN0BAJg4fSIqKitgMpkwcfJEbN++HT/++CNqamowapQkCjT/VLalQzZpi6mK8fQGqQheAWzLkR0dO5g+hzRlRAllrbAS9CLBMxIA9VpZLdD7VauZyhSUVGYl5ZnOiltNVoaeSi+GSycuZfarrPfjgabnKLPqWlC2ZyDHzAI9PBkSMr9ZFLxS0liTHctldaVcR+e2urn00H1BjVNGqvNHwvc5itFq852y7jebRp5yLGZzDtYL3vw1vWw6tx7abXWr1q7S4y/XDGWlDgGg7VRqiV4p2wlNL5/OFflLVSyIR6EFkpeb8ObUVAOyyu2LHEWqmSd6vtIj5EVj6aT4GkSvTfI1MMrc1OeLxi9iSsq0wM38pkF7pn8/reAFnbXL5hysVC2nuznI6K0Ip5L6zIzhfWR9Uc7BdrM9o+ryPNDrfFSMkt+uwF5Ajr0v1P0atGcFtKjJ2YIoikkFJujPBUGAzWTjfkfLIRVFEXfccQfmzZsHQFoY1zevx9effQ2bLV5DbDVbEYlEmOPazXZm3wKE7Dq/iskrV9SeASkrU+YsQ4O/AeFYmKlv1RI5UusRDEhqm7QoidZiML18Oj6s/RCA5GBqNYVXtu7JZuZX3v9rW14DIC1u9ETNuzfTyqbh671fM+8dMvgQjC4cnbDfJ9Y9AUBd9CpZT0wtTCubRijpgNTvTq2VQzahFJLJpmEuCALybfmkZ6meY9V4axIWu2TfWzBuAR5b+xijSp9rDkdvQM8f6Qh56RW8AvrW+VWOxf7O/AL8+Wta+TRuCzStDAmT+c3BsTi9bDq+3PMlea3WQgjQFr3a0raFZIOLHEUY6hkKQRAwpXQKPt/9OQApmJhO1kxJoaWNYzVwf78UHR/l9lqBAXoO1yPkRWP2oNkYXzw+oauCfA28QIzH6tFcj5VIR/AKUPT6VdT8amZ+KWcqm+N+iGcIih3FaA40ozPcic1tmxPWdLreN52gfKkzHuDeZzO//TQH89Z5+jkb5B5EnouBWvdrZH5zAEcccQSee+45NDdLRmhLSwsOPPBAPPPMMwCAZcuWYc6cOQCAgw46CM888wwEQcB/X/xvwr7ozK/H40FnZ5wGNW/ePNxzzz0Ih6UamM2bNiMSiCTsQ14gxo4di23btmHLli0QBAHvvPwO2cZkMmW1N3IC7TmbNb+u1NSeAdYIpScJ3c5vB+v8rmteR2rVhnqGptQyYnv7dtV/X+75ktTHee3etBSIU4FS0TNZCyieMcQT1JhaNpX8vaZpDba0bcH29u2EkiOKYkIz9nTPm/e6r9CXglfK/es5Viq9ZmUUOYrwi1G/UD3uQAdthKUj5KWX9gwkMkuymeFQ1rT2d80vINEjbaZ4oNZlcWFM4RjuuNQ631THfV9DOf/QY0wJ+vzleVH+R/fCnVE+g6zZ9BqyfNdy1HbWcvenBeX40FNqUuOtYQx6s2BOyHInw8iCkUxgQ+u4dIY01d9ZEAScO/HchPdldtP4ovEJGd4zxp6R0nPCc2b0BM9op762sxY7OnaQ116b+nXS60s2x70gCAwL7MOdHzLjcnPrZvzQrC/YrwZ6jd/YupHJ/ObiM50OlM9YX7FvePMpfb/3hXZHRuY3BzBhwgRcc801OPTQQ2E2mzFt2jT85z//wdKlS3HLLbcQwSsAuP3227FgwQLcfvvtOGL+EQn7ovv8Tp48GRaLBVOmTMGSJUvwm9/8Btu3b8f06dMhiiJKS0txx+N3JO6jx3hzOBy4//77ceyxx6KkpATTZ01H2+o2ANmt9wUSJ69sPvQeqwc2k404n3qihtXeany19yvmPavJisq8StXvDPEMgUWwICJGsNe3F93hbtIqIxUK0LjicXCYHQhEA9jt243jXkmkv/MwrWxaVrP1gGScF9gLiBDIx7Ufxz/jTKhTyqYQwRZAcoZ511/iLEF1fjW2d2xHOBbGia+eSD77/czf48RRJ5Lfz2VxpdyCRHnMbGfI1WA32+GyuIj6erYj2KlmwHi0fi1jS8biCYvx3IbnSG/gfSUyD7BGQTrXVWAvIIJuMtSylspnSM+9TxfKrEMu0J5tZhsmlU4iKsVyb9ChnqEJ91ArS5Lrmd/JJZOZ69FLe/7T539S3Y6e4+j57a1tb6nuTwvK8aEn4CiX7chO+diisSnP1WaTGVPKpmD5LqkUTOve0OtxOr/zEUOPIOsOID2Xcks/q9mKSSWTiGq13JovFSjHqNPi1FX/XOmOX9eurl24b/V95LVWQKyvMr+ANMbe2/EeAOCu7+/CXd/fxd2uxlvDaIHoBf27373qbuazXHym00G/ZX456zx9vw3as4GMYfHixVi8eDHz3ocffpiwXU1NDb744gsAktLa2b86m/mcdkqtVis++OAD5vO//vWv+Otf/0pe1/vqsf9B+2P/g+ICPbf/53bYLVJE86ijjsKPP/4IAPCH/aRWlW61lA30peCVIAgYmj8Um9s2wyJYSDsLLfAcuWH5wzQXLqvJisGewWQh3d6xndSa0nWsyST/rSYrppVNwxd7vkh6njT2K98vpe3TgdK4qe+uJ5+p1eVNKJ6ANU1SucG5kxIj7TJmVsxk+inLuOv7u5ja4VTErmQUOYowsmAkqd+eWTEz5X1kCkM8Q7ChdQMsgiWl3qzpoMpTRerVqvKqkm6fTuYXkIzQY4YfQyjx/UEpzxaGeoaSv7WCX2owm8wochTpUlau9laTwFepszSr9V8Jmd8coD0DwH4V+xHnd78KaU6zmq0Y4hnCzA9azjo91tP5zbINl9WFSSWTyLNJjzEl9Dy3QPxeAZKgkzyO0t2fsh5R77y7X8V+ZH2gzykVHFBxAHF+te4NLYSW7rN5zsRzSFBhRvkMJoC8f8X+xPk9ceSJKTOOzCYzE+zUK2ZEl14pofX70a3nsj3u9f626dolagKMRY4i3UJeuY7+Yt/w1nm6lIzJ/HJKTgYCDOd3AEN2UGUIgpDQHzcZeE6smniE0+pEqasU3eFuRlo/G+hL2jMAXLn/lbhv1X34efXPVds40OBNDnooxcO9w4mBtq19G8YXj08QJdFDAfrtzN/i71//nTGYtTC+aDxOHaO/Fqk3mF42naHbAZKIi9qi/If9/oBbV9yKmRUzcXDVwar7vXDyhdjj24O6TkmhvMnfBF/Yh+5IN+5ceSfZLh3nFwCuOeAa3LHyDhwy+BCuemxf4ff7/R73rb4PPxv6s6y1U5Fx/qTz0RZow6jCUbrohzw1c71R9t/N/B06Q52wm+04uubolM81V1Htrcavp/0aX+/5GpdOuzStfZQ4S5hnWc0IdlqcpJ3W2ePP5m6TKSRkHXKA9gwAZ48/GxtbNsJsMjNtrKq91Yzzq3W+J486Geua18FqtmL+8Pmq2/Unrtz/Sty64lbMKJ+h2UXgzLFnYmv7Vq6IIiAFxI+qOYrpd+20OPGnA/+ER394lHGAZ5bPxGFDDtN1fsp1Uq/OwimjT8GaxjXwR/wp95+WcfrY07GuZR1C0RBOHn2y6nZTSqfgnInn4MfmH3HB5AvSOtYJI07AhpYN2Ny2GZdOZ5/vBeMWYH3LepgFc8JnepFnyyPObyrP2LWzrsV9q+9jWtFMKpmkObfOqZqD08ecjj2+PVg0flFa56sXY4rG4JKpl+CtbW8xjAwaQzxD0v5d5lXPw5d7vmS6P7itbpw/6fy09peL6C/2DW++Udb8eqweVORV5GTwUA8M53cAQ6432bhuI66++GoIgkDes9vt+Oqrr7S+zuyDhhalOduZKBnKbFK25d1nDZqFWYNm6d6e5xzRKtBqqPHWAD3lVXI97Na2rUSsochRpKsn55iiMXjkqEeSbtcf4ClVD/OoZ8Wnlk3FY0c/lnS/Fe4K3Puze8nr17e8jj8u/yMAMBT0VKPvMmZWzNR1HtnGAYMOwAGDDuiTY40oGIF7j7w3+YY9KHYUw2P1oDMc1xLQ6/wWOgrxn8P/k/I5DgRcMPmCtI04IHHMahnBx404DseN0Ffq0BskqD1neQ7Wi3xbPm4//PaE92u8NUyZhVamusBRgH8d9q8snF3mMLFkIh6a91DS7crd5Wk9V/OHz++V459u5tdpceIfh/4j7eOSfRySfB+CIOCKGVf06lhmkxlXH3A19zOv3dvrOc1j9aABUgY3Fed37tC5mDt0bkrHMpvMuHbWtSl9pze4cMqFuHDKhVnZt81sw01zbsrKvnMF/cW+4a3z9Bo1sWQiPl/weZ+cS7ZgOL890KO4nGuQhT9Gjx+NFz9+ETazDaMKR6W2D0Xm12wyp3UfRFFM+Tta6OvMb6ood5XDaXGS3n+Ado9fGTzFZ2W970Abh0qMKxqXQKnTc29SxVE1R+HOlXdit2838366mV8DySEIAmq8NYwy9r7SVqI/oRyzuTDfJfT5zYFz0oKyTi0XapT3ZSjHR7pBx5866OcqVwJMBnIDSu2bvpqDees8vUYNdBsVGOBqz4IgFAmC8LIgCD5BEHYIgrAg+bcS4XA40NzcnHEHLtswm8xMNi0dMSOLycLsIx0hK1EU0dzcDIcjc3UWCYJXObYoyJMDDT20Z57ic6qU51yH1WzFpNJJzHt6suIpH8dkxeIJixPeN5zf7KLaW828zqbo0k8F9JhV9l/uL+Rq5lcNyvk3V2qU91Wkm/k1wIJ2aHI9wGSgb2E1WZl5ty/nYOU6v6893wM983sXgBCAcgBTAbwpCMIqURTXprKTwYMHo66uDo2N+uoncwnN/mYEo0EAEoU55AylvI8mfxNCUel7NrMNkb2J7Y+SweFwYPDgwSl/Tw25nvkFJGOL7gHIU8hTgp5QdrTvQDQW7dM+vH2FaWXT8M3eb8jrbLVYOmnUSbhv9X2k5RGw703SuYaEXrNG5rfXoMdsrsx1Ay7z6zUyv32JdFodGUgE7dAYARsDShQ6Cgn9uC/nYOV8uq893wPW+RUEwQ3gZAATRVHsArBcEITXAJwN4KpU9mW1WlFTk93+p9nCX7/6K57+8WkAkiz/bdNvS3kfN3xxA57f+Hyv9pFpDAjnl3J2y13lulo25NvyUeIskQIOsRAOfvZgdIakic1hdmBs8dgkexgYUDrx2RKQclqcWDhuIe5YGW/Zta9N0rkGelF0Wpw5kaUc6KApo7nitDktTqa0I1fOSw1euxdFjiISCMv18x3oMDK/mQE9TveVFj0GMocCRwF2du4E0LdzGr3OWwTLPtM7WcZApj2PBhAVRXEj9d4qABP66Xz6BSO8I8jfSmU43fsoiO8jVxawQkchoXF7rJ6cNLDp+5aKc0f/ZrLjCwCTSyfn5HWmgymlU8jvJ0BIoNBkEqePOR0uSzzw0FeibD9V0OM3nf6MBhJR4Yq3flI6Ff0Jej3IpfNSAz0np7seGtCHAkcBKZOym+37nHHcV6Az6Ho6TRj4aaHUWUr+7ss5mF7ny1xlaZVV5jIG8tXkAWhXvNcOICE0IgjCBYIgfNsnZ9XHOGb4MRhZMBJFjiKcPEpd8l8L84fPR423BiXOEvxi1C8yfIbpwW11Y8HYBXCYHVg6aWl/nw4Xhww+BJNLJsNj83BrT9WweMLihNoNj9Wj2eN2oCHPlodzJ54Lq8mKReMXwW11Z+1YXrsXf9jvD7CarDio6iCMKRyTtWMZkKj784fPh8PswJIJS/r7dPYJTC6djIMqD4Lb6sbCcQv7+3QIlkxYAqfFifnD52NQ3qDkX+hnLJmwBB6rB9PKpvVrr+6fApwWJ84efzbsZjvOnXTuPmcc9xWOH3E8BrkHYXDeYBxTc0x/n46BHMMZY8+A1+7FpJJJmF05u8+OS6/z6bYky2UIA03kSYYgCNMAfCaKoot677cADhNFkdsH4uKLLx6YF2vAgAEDBgwYMGDAgAEDBnTj7rvvTpCnHsihuo0ALIIg0L19pgBISezKgAEDBgwYMGDAgAEDBgzs+xiwmV8AEAThGQAigPMgqT2/BeDAVNWeDaQGQRC+FUXR4JQZyGkY49TAQIAxTg0MBBjj1ECuwxijBvRiIGd+AeBiAE4ADQCeBnCR4fgaMGDAgAEDBgwYMGDAgAElBmyrIwAQRbEFwIn9fR4GDBgwYMCAAQMGDBgwYCC3MdAzvwb6B/f39wkYMKADxjg1MBBgjFMDAwHGODWQ6zDGqAFdGNA1vwYMGDBgwIABAwYMGDBgwIAeGJlfAwYMGDBgwIABAwYMGDCwz8Nwfg0YMGDAgAEDBgwYMGDAwD4Pw/k1YMCAAQMGDBgwYMCAAQP7PAzn14ABAwYMGDBgwIABAwYM7PMwnF8DBgwYMGDAgAEDBgwYMLDPw3B+DRgwYMCAAQMGDBgwYMDAPo+flPN78cUXixdffLHR28mAAQMGDBgwYMCAAQMGfmKw9PcJ9BMMB9iAAQMGDBgwYMCAAQMG9k0IvDd/UplfA5lFLBhEx1tvIbRjR0rfC+3cic7330csFMrSmfU/RFFE97ffovvbbyGKRqwlFgqh45130bX8M4ixWH+fjgED/YJoWxs63n4H0Y6OtPcRaWpC++tvILx7dwbPbGDB9+VX8H31tTG3GjCQJYRqa9H+xpuItLb296kYMJBx/FQzvwYygL3X/xntL78Mk8uF6heeh3348KTfiba1YdtJv0DM50PRuUtR/vvf98GZ9j18n36K2gsuBAAMefBB5M05qJ/PqH8Q8/nQ+tzzaHnkEUQaGgAAtpEjUHzeefAeeywEq7Wfz9CAgb5B4McfsXPpuYi2tMBSWoqhDz8E+6hRKe3Dv3Ytas89D9G2NsBigXf+fBSffx7sI0Zk56RzEB1vv41dl10OAChcdDbKr7oKgsmI4xswkClEu7qw7ZRTEWtvh+B0ouDUU1B8zjmwDhrU36dmwEBGYDi/AxxiJIL6v/0d3d98Q94TrFa4DzkYRWefDUtRUdaO7f/uOwBArLsbu3/3e1Q/8zQEmw0A0Pbii+h48y0UnnUWPIfPjX9n9WrEfD4AgO+LL7J2bv0N32efxf/+9NOfpPPb/vobqL/xRkTb25n3Q5u3YM9VV6PpP3eg6NylKDj5ZJgcjn46y9QRqq3F3j/fQJx5ADDle+A94QR4TzgBpp5nIBOIdnVhz3XXQQyGUHjmGXDPmQNB4LJ4Mo7O999Hy6OPMVlK+6hRqPjzn2HOc/dq32IshuYHHoTv88+RN/cwFJ56Kkzu3u0zl9G9ciVqL/wlYj33MtLYiB1nL8KQBx+Ec+IEfftYsULaR1eX9EYkgvZXXkH7q6/CNmI4BJMZQM9YPP54eE88MaNjMVfQ+uSy+N+PP4GYz4dBN9wAwWzux7MyYGDfgf+77xDrWbdFvx+tjz+B1qefgb26GuhZfywlJSg47VR4jjwy5Wcv2t6OhttuQ7StDeVXXw1rWRl3u+C2bWh5/HGEd9ai9LLL4Jw0sVfXZcCADMP5HeDo+vhjtC5blvB+YO1atDzyKApOPRXFS7MTsYt2dsaPt24dGu+8C6WXX4bGf9+K5gcekN7ftBF5cz8hBnukqTn+/ZZ9l04TaWwif4f37MnIPsVYDJH6+pR/y0hzM2AywVJYmJHz0AP/6tXYfdVVQDRK3jOXlEDs7kasuxsAEN69G/V/uRFNd9+DokWL4D5gf2ZhtVZVJew3vGsXBJcr4VpEUUR4125YSktgstuzdl2iKGLP1X9E97ffJnzm/3YFmu68C0VLlqDw9NNgcrl6fbzme+9F53/fBgB0ffgh7OPHoeT88+GZNy+r2a6WZctQ/5cbE94PbtwI66AKlP3ud2nvW4xEsOeaa9H+6qsAgO6vvkLzPfei8OyzUXTWQpgLCtLedy7C98UXqP3VJRB7xr2MaFsbdi5ZgiH33gPXzJma++ha/hnqLrkEYiAAQApwiuGw9KEoIrR5C7N9wljsRWAhvHs3LBUVOZFdDe/enfDstb/4EmLd3ai6+WYSfDVgwED6CKxbn/hmOIzgpk3kZXDjRvg+/xy26moUnbsUjtGjufsyud2wjRgRtwGbm7Hz3PMQ/PFHAIBtyFCUXXG54vjr0HT/A+h85x2AKm0Y+tCDvb00AwYAGM7vgEeotk71MzEQQOsTT6D9pZckWnJNTcaOK4oi4/wCQPMDDyC4ZQu6PviAvBdtbEKsqwtmjweAVK9GPmtuhiiKfZbJ6ktEGhvJ35lwfkVRxI6zzob/u+9QcvFFKL30Ul3f61r+GWovugiCxYKa555NmWaZDmI+H3b9/vfE8bVWVqL4ggvgPelEaUw+9RRaHn8C0Z5aomhzMxpvvRWNiv24Dz4YJRecD+fMmej+5hs03/8AfMuXA1YrvMcdh+LzzoNt6BB0vP2ONPY2bIBt5AgMf+UVCJbsTG2+5cu5jq+MSH09Gm6+GW0vvoDhL73UK2M8Fgig7fkXmPeC69Zj1+VXwHvyL1B5001p71sLTffdj8Zbb1X9vO35F1ByySVpZetjoRB2//Z36HzvPeb9aHs7mu68E20vvIDhb7zR68xyLiC4eTOaH3gQ7W++CUQiAABzURHKfvc71N98M2Lt7Yh1dWHHOUvhPV4az8o5OrhpE5oeeAAdb75FnidzSQmGPvQQYt0+NN//ALo++oh7/EhDAxr+8Q+0v/wSal5+Oa1nouHW29B8331wTp2KYU8t63cHuOOtt8jfgtMJ0e8HAHT+921s/XGDVE5x3HzDCTZgoBcIrI87vwWnnoLg1m3wr1jB3Ta0fTv2Xvd/mvuzjxuHkvPPg3PKFOw873yEtm0jn4XrWBu288MPUXfJrwGFNkimkggG+AiHw6irq0OgJ8A60OBwODB48GBYdZbSGc5vjiLm86H1+edh9kh0SjXDJdYZpyQWnHE6Cs88E6EtW9D04IMI9kTvYj4ffJ99nlnnNxAA5MwDeVNkHF8ZkcYmyvmNuzhiOMw4xlqIdnWh9emnYauqQv4xx/Tu5PsAmXZ+wzt3Epp52yuv6HJ+xUgE9TfdBITDEMNhtL/+RkKENRuo//vNCO/YCUCK+g59/DHYBg+WPrTbUXLRRShavBhtL7yI5kceQUTl/vg+/RS+Tz+Fpbwckfr6+AfhMNpfegntL78MS0kJc69Dm7cg8OMG3VTSVCDGYmignELviSei6JwlgCjC99lnaH70UUR7Mv6hzVvg++pr5B08J+3jdbz5FqGMm7xeiMEgyfy1v/gSCk4+Ga7p09O/IAVEUUTjrbeh+f77yXvOKVNQft11ECxm1P3qEoR37UK0vR0db76FgpN/kdL+Y6EQ6i7+lRTA6EHe3LkIbtpEDKDI3r3wr/oeeQcNrDKBruWfofO99yBGJSc30tAA3yefMttYKiqkOt/hw+GYMAE7zz0X0aYmaTy/+BLaX3oZeYceCnNJsbSP+gb4PlXso3IQhj38MGzV1QAA1z13I9zQQAJJ0lj8HM2PPkLGYnDTZgTW/5gWZbDt+ecBAP7vv0dw82bV7E5fof2NN8nfFdddh8C6dWh98kkAQGjbNuy55ho03nkn3AfOJiwS2+AhKDj9NIYtIgeWBKsVBaeeYlCmDWii4+13ENyyGUUL9z1mCg+BdevI3wWnnwHnxAnS3C+XXESj6HjnXbQ+9RRiiiQID8H167Hrit8CJlOCU6tMonS++17CNtJ26YsEGkiOuro6eDweVFdXD7iElCiKaG5uRl1dHWp0+jmG85uDiLa3o/aCC+FftQoA0PW/T1D5z1u49VvRjvjEYa+pgWPMGDjGjIHn6KOx94Yb0Pb0Mz37bMvsOVLHNbndgNlM6tkASIZHD10l0tgI+3BpQEYp2jMARFtadDm/LQ8/gqa77wYAWIcOy4pzk0kwGe6mJsSCwV7Rcem6y1g7fxFQZtHbX3mFibDS0dxsofP994nBDAAV/3dd3PGlYHK5ULTobBSecTra33wLHa+/hmiXVAuOSEQ6V3n80I4vDVFkHF8ZmR7rMjrffpsElASHA6WXXw5ruVSr5Bg7FoVnnYU9116HjtdfBwB0ffRR2s6vKIpoWfYkeV1ywQXw/uIk7LnqanT9738AgIZ//xvDnngiYwtV+yuvMo6va9YsDLnrTkKZLVxwJhpu+ScAoGXZk/D+4qSUjt3+6quM41u0ZAnKrvwDEI2i9oIL4fv8cwAgtWYDBeH6etRddFGchsyB64ADMOimm2AbLFH5HWNGo3rZk9j9x2viGRVRRNfHH6vuw33gbAy68UZYKyuZ961lZUzNnDQWF6L2ggvR/dVXAIDQ9m0pO7/Rzk5EW1ri11m3q1+d3+CmTYQqKdjt8Pz8SHhPOhHWQYPQdM89pBY6smcP2l98iflu+2uvYejDD8FaUYFoVxfqfnkRYXCYiwqR//Of9+3FGBgw8H31NXZddhkAINrahoprr+nfE8oyop2dCNfWSi8sFthHS2wxa1UV6JyaY/x4FJ9/Hlqffhpd//sfxBBn/hNFBDdvJgwNnlMbUyjf07ZO+TXXSAF8ALGO5E62gfQRCAQGpOMLAIIgoLi4GI0ce1AN/V/EY4BBpKkJOxYtJo4vAHS++y7qLv4VYvIEQiHaETcUTZ588rcgCLANHkJeKyeY3iLWFZ+ILOXlGHTDDSTSXnDqKfD87AjyOZ3tpZ1CAIg0t0APaMctsH6dxpb9j5jfHxel6UFk795e7ZNxfn0+iD00SgAQQyHsXLoUW34+D509mfdYMIjGO+9i9pFN5zcWDKL12eew55pryXv5xxyN/OOP1/yeYLOh4KQTMfThh1Hz3LPSv5dexIj/voWCU08BeigsUobmVIx4+78YtuxJ5B16KNmHyeuFhaqDzvRYBySWQuPt/yGvi84+izi+5DzsdhScfDJ53fnRR2m3YvGv/D7uaNvtKDj5F7AUFqL8mj8CPSwQ/7crEjKD6SJUW4v6v/yFvM479FAMue9epla04OSTIfQEcILr1sO/8vuUjhGkqXRnnI6yK/8AQRAgWCxMfXdv2gD1B/yrV6s6vnlz52LY009h2GOPEsdXhm3YMFQvexLDnnwC7kMOVt1/3s+OQPWzz2Doww8nOL5qMNntcE6eRF6Htm3X9T0aoZ07mdfhutqU95FJ0FnfvLlzYc7Lk4yec5di5EcfovTyy2FWEXgMbd2KHQvPgn/NGuxccg5TutAXQUEDAxctjz9O/g5u3NiPZ9I3oJ8H+8iRmqJ55rw8lJx/PqqffDK+ftP/nn8OIz/8ACUXXwRTvmSfCg4Hyq68kuxDmfmlbVr7qFHEBhCDQcSCwYxcowE+BqLjKyPVczcyvzmE8O7d2Ln0XIS2b0/4zLd8OXaefz6G3HMPkymlo2Fmbz7zHfp1VCVbmC5oA9XkyUP+UfNgHfw8Yj4fXPvvh/ob4/WIdHYu0qzM/LKv9Rwv1zNDSgcfkKjPtmHD0t6nkloU6+oi9KuuTz6B73NJObvu0t9g0E03ItraluBwR5uaEG5oUFVWTAdiKISWJ5dJrYyo39lSUYGKP/0p7cnUVl2NQX/5C0ouuQT+776Dc/oM4mzaqqvhum+GlAnaiZoN9gABAABJREFUug3ugw5Cw81/J/WxmR7rAND28sukn7XJ40Hxeedxt3PNmA6Tx4NYZycie/YguGEDHGPHpnw8mcoJAPnHzSe/tW3oUBSedipan3oagFST6Z4zp1e1mGIkgt1/uJIIkdmqq1F1678TmArmggLkHzcf7S+8KJ3jsmVwTZ+m+zj07+KaNo0ZG8xc1Zbbz7cStGPpPuggeI6SxMicU6fqakHkmjkTQ2fORGDjRgTWrCF9sAWTGc5p0whrJlXI1GhAyvymirDC+dXSl8g2RFFExxtvkNfe4+Yzn5s9HpRceAGKFi9C1yefkHKBaHMLGu+8E4hEEN61C9tPPS1h32pMGgMGQnW7mJr6gRaYSwd0kNIxblyv92cpLETppZeiaOm56P7qS2k9tFjRcPPNABLpzEqb1uzxEAZKrLMzq4KWBn46MJzfHEFo+3bsWLoUkd099Y8mEwb99SaE63ah6c47AUiZnoZ//QuDrr+efI91Qln6sBxpU26XCdDOmLkn40xTkS2lpeRvxvlVZn5b9GV+6WxetK0tpXPta/CouOHdvav7Vf5+0c5O4hCFqZY7iEax56qrIdBKwxYLEdwJrl+fUee3/uZ/JKiNmwsLUXXrv2H2enu9f2t5OaxHH839zD5qFBHwolkPmRzrjOBQD4rPO0/12gSrFXmHHIKON6UsVddHH6Xs/IYbGtDx7rvkddHChcznxb/8JdpeehliIIDg+vXo+O9/4T322JSOQaPp/vvhX7lSemGxoPKWW1SVqosWLCDOb8c776Dsyj/oHk+0kUPPTYCUvSfbDTADkw5W5h0+F4WnnprWfhyjR2eUVmyjap+C6WR+dygyv7X9l/n1f/89wrt2AZDGjvtgfqbc5HAkUJgd48ai7tLfQFTJGg208Wag79D27DMMVZfOSu6roJWeM+H8yjDnueE5QmIE0ixGJZ2ZzgSbPPkwefKI8xvt6ISlpCRj52Qgt3H99dcjLy8Pv6O6S2zfvh3z58/HDz/80Kt9G7TnHEG0owMxOeNhtaLqtltRcOKJKL3kVyj73W/JdsreuLTgldIgN+fTBmVmJ2265tecn1izaymNT1DRHoc3FgolZG2jOp1f2kBR9o3NNUQaOM7vnt292qcy88tkwjm1MHJbFWtVFQp+ERcmooUstND16XLU/vIixgnjobtHhAsALGVlKLvySox8/z24punPCGYCZsqZimVgrMe6u7Hriiuw9bjj0fHa60Rp11JWhqKzz9L8bt7ceF/rzg/5SrxaaHvueRKscM6YkWCAWMvKUHT22eR143/+o1lvqgX/mjVouutu8rr0kl9p1oY6xo+HUxbZikSY+u5koDNsZoXzy8xVWarZzhbouvpMigr2FrTzG9q+PWUKvsx0IK/7kfbc8Xo865s/7+cp9S/OO/RQDHng/nhAx2yG94R4OYZybQxu2YLaSy5B0733pl22YGDgIxYISHMx/d5PgCVA2wiO8ZlzfmkIDocqnZm2EaXML7W2G6JXBjIEw/nNETgnT8bge+6B2evFkLvvZqLXXsp5UVICGSdUkfmlqYSZnrTpSYjOusngZX6jzYkUZ701v3Q0MNdpkWq0594gqnBwaWeYdoQFhcx76aW/hnPKZPKa27+Pgz3XXYeujz/GnmuuRSwUUj8vylEZ9sTjKD5nSa96iqaLTFP8O/77Njre+i/znmvWLAx95OGk/XvzDp4D9KjHBtasYTPzuo4dP27RwgXcbYrPO5dkT8M7dqJTQyhJC80PP0wce+f06Sg+//yk3yk6K56JpjPiyUA/wwnOLxW4y0bNdjZBO7801bi/YS4oIBl10e9XF45TQULNb21dvzmDnVQXgfxj52tsyYd7//1R/cILKPnVr1D9zNMoOC1Of1aujY3/uQNd73+AxttuR9dHH6d9zv2FWDCIwIYNCKxfz/1nZLr1gVbbl6HU29jXEAsEENy6lby2j82S8ysIbPlez9ogRiKk/AaCAJPbzSRXlHYQDVEUEa5vMAJWAxw33XQTxowZg5/97GfYsGEDAGDFihWYMmUKZs+ejbvuuivJHvTBoD3nENwH7I8RH3yQ0OOSzWp1QIxGSWsGhvackE3JHu05eeY30fmNNCU6v3oyv2I4TDKZwADI/HJoz5Fe0p6VEU8mE05lLkovvxy+zz+Hb/lyuA44APnz5yPYM4EA+sRdYn4/qReOdXYi0tCYINZDtqUCEWpiM32BTFP8w7vjmXrHlMmo+OMf4ZwyRdd3zV4vXDNnEqXdrv/9LyUqLO2kuA88UPUYhaefjuYHHpCO8eFHyD/ySN3HkBHaHs/ulf32Cl0tX2jKaXj3bt29urVozwO15jfS2krKMASHA5aKiv49IQqCIMBeXU3EE0PbtsGawvmFdrKZXzEYRKSxMaNlE3oQaW0lz4Rgt8O138y09mMfXoPSX18CAAhQwkXK+YJ2+luXLYPn8LkYCIi0tqL1yWVoffJJzTVSsNsx9MEH4Npvvz48u4EFpdo+jWhnJ9M2a19CcNMmEgy1DRuW1X7rPDozQ3nOz4dgMjHJFa3M767LLkfnO++g4NRTMegvN2TtvH8KWJ+loAcAjPtR3QZdsWIFnnnmGaxcuRKRSATTp0/HjBkzcM455+COO+7AoYceit///vcZOQ8j85tj4E02gsUSNxZFkSzWYigUl5A3mRIybtmso0ua+aXqMiI9/SZp1WfymQ7BqwQ1wFx3fjnXmc3ML525sA6qwJAH7seI99/D0AcfgGA2wz5yJKEYhevqkt4/ZUAiopK5FEOheJTWbIYpL0/39WQaNG02E9Qo+h55jzlGt+MrI2/uYeTvrhSoz2IoFFcKN5kSnEQatKJ61//+B7HHaEkFdI9lK6UOrwVTXp5EW4PU7zvm8+n6nibteYDW/NL1vrbq6l4Jj2UDSuqzXsR8PtInmEa4blcmTislBDfEHVX7yJEZ6cnLjLeE9aWN/O377DMEt6YuFtaXiAWDqL/lFmw+4mdouuuupPO7GAyi/bXX+ujsBia6v/qaUds30z2iB9D8lCpoZpg9S5RnGQyduad7CH1v5cywnsxvcNs2dL7zDgCg7aWXiGiggYGFTz/9FCeddBJcLhfy8/Nx/PHHw+fzoa2tDYf2dPg4myr56g1ya6U2oApmse7JNDA0Qo8nIfticrulpuKQaG+iBn01VSTL/JqLisixo21tEEMhLu05qoP2nNAHLtedX57g1Z49vaLjKBUR6fuvzP5Lba4GEwq0YLPBPmok2Saw/kfNYylFyHjXozyuuee4/YVM057pMWZKQ7jLc/jh5G/fF18gFgikfFyz16vpTDkmTYK5J8gUbWmBf/XqlM4xFgjExeMsFlhKinV9TxAEltnBqXFPOFYwGJ9/rFbiPMsw5Q9Q55cSksolyrMM+pyC2/Q7cSEVcav+aHdEt5exZ0gQjGFTtbczc7OSedD61FMZOWa20PLww2h56GGGHWUpLYV97FjmH91OLNLa2h+nmvMI/Pgjdl3xW+xcupS8l3/cfFgGxRkTA2l+ShV0G0nHuPFZPRbPqaXtGlPP5yaOk6wEU54Qje7TAYp9HUo70u12Z8W2NGjPAwTmggKitkmcX9rp4Rjocl0FafvQ2QlLsT4DNxkYCqMn0fkVzGaYi4tI9iDS3MythY20Jnd+E5SOc975TbxOMRBAtLUVljSpwUpRKzq7yTqhfEfNMW4ciWQH1q+He9YBqsdStqNSy/wqHbX+RKYp/nT2J51rsw0dCtuIEQht2QIxEIDviy/gmZucPkkrmZuTUOsEkwl5hx6C9hdfAiBlmFMRGqNbYVnKSlPKqFlKSsh8FGlsTNqOhxkrnECducDL3TbXwWR+a6r77TzUwGR+U1B8Vio9k/f7QfE5uCnzzq/gcECwWqWSmnAYYiAAwelELBRinEgAaH/5ZZRedlnGKaDRri60Pv002l94EaYCL4bedx9R8E8F/jVx1VP7qJEovuBC5B99FAQLa975vvwKO5cskY6d4x0T+gN7/vxntD39DPOe4HSiePFi7L3pr+S9bLTSyxVkS+mZBx6dmS7hkm0ZPZnfrg8/ZF5H29rSepYMSNCiJmcThxxyCJYsWYKrrroKkUgEr7/+Oi688EJ4vV4sX74cc+bMwTJFd5F0YWR+BwjoB1k2DmOKzC8PDPU5g5M204tNhZqprPvl1/y2JqWoKCc80e/P6WbnNO2Zpq32pt2RVuZXqY7IAx3FpaO73GO1sFmBgeD8Zpriz15bQVr7yDvsUPK3f8UKXd+hMzJ6Fm86w9z1cWrK0uG98dpia3lqtarMs82h+SsR0xC7AnpYKj3Ot9jdnVGWSjaRq0rPMmiHPBXaM13vSwu8hfuh12+AyfyOysg+BUHgzhk8pzDm86H9tVeT7jPS1ISuTz9NujZFmpvRcOtt2Dz3cDT+698I7diBwKrVaKcUrVMB/VsN+vvf4T1ufoLjCwDmwgLyt7Lrwk8dgY0bExxf95w5GPb4Y7CPGpXxbgK5CDESYfRBsqX0LIPn1PJsWjq5orSDAGnN7JZb9VHvGRh4mD59Ok4//XRMnToVJ598Mg7u0Rd55JFH8Ktf/QqzZ8+G0+nMyLH6NfMrCIIdwN0AfgagCMBmAH8URfG/giBUA9gGgC4ou1kUxb/0fFcA8HcA5/V89hCAK8V9VOqNS3uma+hUnB5zfj7kJiiZnLSVlGseLKWlCEKKIEnOb2JGFNEoou3tmgISvPOOtrfD1MfCK3ogRqMMlds5cSJ8n38OQGp3RPdCTgX6M78qzu/4uPMbTCJ6FW3Rmfml6IGmgn7O/NLKkR0dEGOxXtVfMkJeaV6bffgI8rcadVwJJvOrw/l1z54NwWaDGAohuGkzQrW1sA3RV7sb3kvV+w7qhfOr49rouYpXx0xYKhSrZSD0cwxtz02lZxm2oUMBQQBEEeFduxALhXS1CQpTok+uWbNIZqWv2x2JsRiCmzaT15nsg2zOzydt+KLt7bCWl6tmRFuXPYXCM89Upd/FfD5sO/kUROrr4T3hBFTe/PeEbcK7dqH54UfQ9sIL3J7DwS2bE95LBjEWQ3hn/DexDR2qui1tQ0SMzC8DupWWY+JEVFx/PbNWM2U1+yilNrRtGxmXlvLyjLEE1cDN/NLrRM89ZwMPiZlf36efEpEuGQazYeDimmuuwTXXXJPw/qoe4UZA6v/bW/R35tcCoBbAoQC8AK4D8FyP4yujQBTFvJ5/f6HevwDAiQCmAJgMYD6AC/vipPsDTOa358FOJjoFZE/xOaahMi1DKXoV5Tm/AKJJonQ8qkuuRq6jLS1ATybbXFAA67C4MRLphehVgihLzz0Ro9G4QBL4FHQAcIwZLRnBAIJbtjJN5pWIKDO/jbmf+RUslrjgmygy9yQdZOLazMVxirvull4pOr8mlwvu2bPJ666P9Gd/I1Tm15Jy5jexj7cWmH7kKvPFQBO9EqNRhh5sy8HMr8nhgLWyUnoRiyGs6N2rBloF3H1QXHG8rzO/4V27CA3ZXFhIatwzAWUXBYB9/uxjxpCsd2jLFnR/+aXqvnxffkkUqdvfeIPRTRBjMdT/7W/YPO8otC5bxji+9JhPhZYuI1JfT1gS5qIi1UA0oLQh2vu0JYz/h7WoveQStD73XJ8dUy/EWAwdb75JXpdcfFFCkJrpJrCP0p7pThDZpjwDaplfWvBKuufJMr+dnDVvIHUMMNA/6FfnVxRFnyiK14uiuF0UxZgoim9AyvbO0PH1xQD+JYpinSiKuwD8C8CSLJ5uv4JHe04mOgXEo2fS9zI3aevN/MpQZn6ZCY0jhMUeK/G8c7UukM6CWUpLYB1USV6nS3tmVL17ECU1MmzttVrdpsntjmemYjFGREYJ5e+hKnjF1MUWqO6vr2DKUHRejMV0ZdOTwVJMBX+SjHEZ0da2+HEpmqIW8qhaYp4hoIY+zfzqmqtodktuPt80wnv2xB2PkhJNx6M/QTvlQZ3UZ7rdj3vWLCJeGKmv79OSE6XYVSaFT3jzBb2uWKuq4D3pJPJabivGg+8LyjGORtHx9tvkZduLL6LlsccBqj+sffw4VN12K4Y9/TR5L5SCIBn5DhXM0Mr6AlIghAjNKdoHZhNiNIpdV1yBrvc/wN4/XZ+S8FpfwP/996S1ncnrRd6cOQnbmBlBvtyfm9JB4Me+ozwDfKeWWSd0ZH7FUAi+T5cn7DtZQsWAgf7O/DIQBKEcwGgAa6m3dwiCUCcIwiOCINBh3wkAVlGvV/W8x9vvBYIgfJvxE+5DcGnPOrKv2Zq06doMtWyjpUTh/FIOAC1ckiwrxlPuy1nnl3LwLaWlsA4aRF6n2+4oyslixjq7ev5PXnstg6Y+a/X7Vao9h1XUfHMp8wsoxnovxkesq4tk7015eUQ1O1VYqMxvsgAP2S7FzC/AtlXq/ubbBJaAGnqX+U3V+aUo8mosFe/AMjDpTJ09BynPMmg6tp7sYszvj/eaNpthGzqU6Q8c3rVb5ZuZB+P8jskc5RlQzheJmV+z14uis88itei+z7+ATyX76/viC+a1TKMVRRGtT8T7xTqnTcOQBx9EzYsvIv+oo2AbOoS0oYs0NOhuGyaDYR4M03Z+5WuS0VfU0K5PPonT6EUxQZyov9HxRpzynD9vHgROWQBNe95XlYTDu+JtzGw1w7N+PJ5Ty64TPa2OGCeZXdu6v/2Wy/IyaM/pYSBXjaZ67jnj/AqCYAWwDMBjoij+CKAJwH4AhkHKBHt6PpeRB4C2kNoB5Amc0LAoiveLojgzW+feF0hGezbroD1natKm25YIVisEu527HW0gh3ftijtqVisjxBJNovjMoz3namaIzfyWwlqZ3Pnt/PAjND/yqGo7nBjHmYlq1MiogY7m0qqOCftWOL+x9nbuucVyzflV1P2mi0w59WaqZirS0qKr92A6zq+1vByOCT1xv0gEvuWJkXAewpTac8qZX04fby3oCdIo28/kOuhMXS4qPctgRK90ZN1oRWdrVRUEqxVWqo68L9sd0WJXmaz3BZRrY4+IJP3sFxTAVl0N70knkvca/n1rgpEVrq9HaMsW5j3/ypUI1dXB/+23xIEXnE4Mue9e5M05iGSwBYuFqdHXm5mXQYtdWZNkfuVrktFXdb+ty9hWUamwU7INMRxGx3/jWfr8+cdytzP/BGjPtH1C2y3ZAi/zyxNSNWnYsJ1UiyNS9gTD+U0HDocDzc3NA9IBFkURzc3NcChaKGohJ1odCYJgAvAEgBCASwBAFMUuAHK2tl4QhEsA7BEEIV8UxQ4AXQBoKyofQNc+K3jFcX51CV5lgfasrPdVo6LRzm/gx3hvWUtxsYISmsz55Qte5SJo59dcUqLI/CZmTALr16Pu4osBAMEff+QKpXBrnjmRUrU2RzLoOp5UMr+AdF1KIaVoBkShMolMUfyZ6+qF82uy22HKy5Mi05FIUmE3gKVrJduWRt7cuQislQgzrc88C8+8eUkFv5hWR9nO/DKCV3ymiDlLyvTZAit2lXv1vjJoFWo9is+02JVMpbUOGQx89ZW0jz5sdxTcuIn8nak2RzJ4ayMv+FT6q1+h47XXIYZCCKxeja4PPoDnZz8j26nVAne8+RYzz3qPP54b+LFVVyO0dSsAKTPvnKBfFJH9rYYl3Z62I/oiwBTcti0hGOf/biUira0pzW/Zgu/zz8mca6mogGsmP0cyUPuQpwKZ+g2AsVuyBW7mlxMkNeflkffoz0UFiyD/mGPQ9vzz0nYG7TllDB48GHV1dWjUKc6Za3A4HBg8eLDu7fvd+e3J1D4EoBzAMaIohlU2lZ1a2dNaC0ns6uue11PA0qX3KfD6YEZ1CF6ZsiB4pafeF1CI4lC0T8n5pSihLdqUUJ7CX+46vyzt2VJWJtXLxWKINjYlqK36Po/T5dpfew1FS8+BY8wYZp8xTs1zrKtLEruia1OT1BzaRowkf4fr+MI1oihyKbpc5zfXMr+0gcK5Z3rBXFcvnXpLcTFCPbSsaEtLcuc3jcwvAOQfNQ9Nd90FiCK6v/oKrU8+iaJFi1S3j/n98WNZLLCUpKbsaS4qio/rtjaIoRCXLigjyghe8e8pG7zIzeebBtvjN3edX7bXr47M745E59c2mMr89pHoVSwYjN9jQYB95EjN7VMFb22MKGjPgOQIFC5YgJZHHwUANNx2G/LmziX6CvQcbh8zhrSLaXv2WYTr46UFhQsXcM9DTzuqmN+Pukt/g0hjI6r+/S/Yh0u0VOa3qtbh/PYx7bmVqmkmiMXg++QTeE84IevHT4b2N+JCV/nHHqMaMGTVnnN/bkoVsWAwLlxoMkl2S5bBozPzymMEl0sqPYhGIQYCxIYKbtpEqNqmvDx4fn5k3Pk1Mr8pw2q1oiaH17FMIxdoz/cAGAfgOFEUiaqPIAgHCIIwRhAEkyAIxQD+A+BjURTlp+NxAFcIglAlCEIlgN8CeLSPz73PwKU9c8QBEr6XhZpfPUrPAFRblVhKSmAuoimhSdSeebRfSmwpl8DQnktKIVgssJSXxz+nsm2AIgMrimi89baEfao1do91daVEe7aUFJP6tWhrK2KcXqoxH7/HKq/dUe45v5mh+NNjy9TL66LVaXl9rhOOnabzax85EsXnLiWvG/75L4YyqkSEMsotZaWqQmlqEMxmhZq1/gCWmuDVQFN7DlL1s7nY5kiGpbycCB1F29qS9sCkxa5kh8o6JB5R76t2R6EtW0gLE+uQIUy/4UyAtzYqac8yii+8gNAqQ5u3oP211wFIwUK63rf86qvJvQ7v3k3O37X//qq0bbuO4ETbiy/B9+mnCP74I5rvu48cO8TJ0muhL2nPMZ8P7S+9TF67Zs8if9N0Vb0QIxH4vviCy0xKB7HubnR+8AF57Z0/X3XbZO12BjpYFlA5t090pmHilCnxbFq5DR7Ztsce7P42LuPjPuggxt40nF8DydCvzq8gCMMgtSeaCmCvIAhdPf8WAhgO4G0AnQB+ABAEcCb19fsAvA5gTc/nb/a8t09C2aYAYA1EtawfK9SQmUlbb+bX5HTCRFFWyHdKimEpimfAkokB8ehZuZoZUgpeASyFSKn4HFi3jnnd9fHH6P7uO+Y9tSxmtLNToUqs7agJZjNbq8lzaFWy8Emd3xQctWwhUxR/pehNb2Ap0s9wAFi6ljlFWmDppZfC3kNtF0Mh7P79H7gBDkBR71uRHsUtFepzyuJ8ORrckhHr7o63LrNYYBuin27V1xBMJlb0Kgn1mVdHaqPoZH2V+Q0wSs+jMr5/3trIqK1Tc5qlsBBF55xDXjf+5z+IdnUhtHUrmRtN+flw7TcTnsMPTzhW4cKFqufBCpLxnV+5VzwgidoBQKShEWKPFoPZ69U1V/Ul7bn9tdeIGJGtpgblV11NPvN9+ik3yKqGaFsbdiw8CzvPWYptp5zSazX/jvfew45Fi4nitW3ECNjHjlX9TjYYdLkEpt63DyjPgFrml+1eQf7msTQowUb76FHMehlpM2jPBrTR362OdoiiKIii6KB6+eaJorhMFMWnRVGsEUXRLYriIFEUF4miuJf6riiK4h9EUSzq+feHfbXeF5BoHXLWTuzuRiwU0pWBzQrtmTmuNtWWNpDJeyWlCWJAmsfjZH5zVRBHKXgFIN5nE+wiE+vu5ho7Df/6NyM6oBa0iHV0EKEWQF9LHiYLTWX/yHsqgQiu85tBJzETYMd6+uODzWgX9OaUYKboxMkyv2I0ygYzUryngs2Gqn/eQgToghs2YO/1f+Y+96zzW57wuR4wgZQkvX5jOlpH0RTzWI7X/DIZt8GD01YE7yuwolfbNbdl2+fImV+a9lzbJ6IodL1vpsWuAIXgDml11EbeU5Y8FC1ZItH9IfVsr//LjUyLI/cB+0Mwm5GvyCBaKirgOSLRIZZhU9RkK++tGImg++uvyevw7t0I79mDMB2kGJac8ixdUwH5O5vZMTEWQ8uyuD5p4cKFsI8eBWtPECXm88H3zTe69hVpasKOxUvgXyU194js3oPmhx9O/ZzCYbS9/Aq2Hnc8dv36UgR++IF85j3+eM02Wkzmt7NTl3jhQAIdlO8r55fQmQFCZ1ZbJ3iZX9omsZSV9WsfawMDD7lAezagA4IgJNTr8MQBlMhG+xBGuVWl1lgG1/ktLlZkxNSdX1EUucZ7Lqo9i6KY0OcXgKroVWDDBqBngjaXlpCWF/4VK+D75BOynWrmt6NTl+gZDWt5vJaH5/yqCUWEFc6vGInEx4EgqLa76kvQmcPe0J4zqWJtYej9SfpZd3SQ8WDyeNKintlHjEDZH35PXre/9BI2H34EGv71L8ZBZWhumcj8qrTDkqGLpcIoqmb3+Y4FgxCpvqupglF6zmHKswz6HLXE7mLBICJ7esaGyQTr4CoAEgtBph3HurulOm9RRHjPHoTq6rj/eC3aUgHb43eMxpbpgbc2siJ+Bez2eW5UXHsNed3+6qtM71/XLInWmzfnIGbfhWecofksm4uKSOAu1t2d8CwFfvghoZ1L94rvUurxS47VBzW/YiSCPVdfjdBmSQHb5HLBe+IJEASB6UnepYP6HN69GzsWnkXqqGW0PPZ40oCbjJjfj5YnnsTmefOk86KUuQWbDYULF6Josbo+AiCxpgiLTRQZGygWCqWUxc5F0HZJXyg9A4l05mhjI8SwJPkj2GwwUcq9dJJFLgOjnV9rWVlCH+uYr2/6WA8URDs6yP2lIdutavM4+29Xr9bNXEK/C14Z0A9zQQFxFKNtbTqphHT7kExlfpPX78ng1f1aSksSItBiJMI1EES/H+A8bLlIe475fISGJjgcZLGkF5MIlfmljVD3AbNgzs9H61NSW4iG22+H+5BDIAiCauY32tmhawzQsJTFs3zh+sRsLp35NZeWINoj4KWktdKBF1N+fso1o9lA5mjPGXR+qcxvNEnml6Fc9kIJtXDBAnR/+SU633sfgFQb3vzAg2hd9hSGPvE4nBMmZCjzSzm/SQxRZryo3NO+qvltf/117P3LjTC5XKi65R9w7bdfyvsIMm2Ocl8kxDV9OuTR1/nOOyi/6kruMxuuqyMBGOugQUScTxAEWIcMIU5I84MPouuDD7Up1BYLKm/+O7zH8tvHJAPr/GY+86tcG0VRTFpzn3/MMej8+GN09NT80gFE9+wDAfQ4VIsXoek/d8BSXo6C00/TPA9BEGCrrkZg9WoAUvaXDlIqewgDgP+7FTC54yVFup3fwvg1ZSOAHAuFsPu3v0Pne++R9wrPPpso9nrmHobWJ54AAHR99BHEa/7IzbhGOzvR+vQzaHn00Xhw3GyGpbgYkYYGiH4/mu65FxXXXat5PsGtW1F73vmMkjEgtcUpPPMMFC1ezA3Q82DK95AgRLSjA2avF8Gt27BjgSRkVv3M0wMiEMYDzUiz9FHmF5BsB/mZC1F9hpW2DJ1kkQVAmURDj0CXubCQ2FjRtlaY89z4qcO/ejWa7r8fXe9/AHNhIQrPPgtFCxfC5PGg66OP0HT//QisWq17f+aiIhQtWoTCBWfqYhvmKgzndwCBNg4je/cSp1BwOBgFYRqmvDxAEKRopc+n6mSmgpgOlWkZvIXFXFwMwWqF2euVnNgeo4PnKNNGsOBwEOcyF51fOmJvKSkhi7pFpeaXrvd1jB8P73Hz0fbiixCDQQTXrUekoRHW8jKW9t2jeghIdOhUWh0ByWnPUartlGPsOPgaP024NiD3KM+AInNIjZvQzp3oePNNxPzxXsWu/faDm+q3SSOTas+ssFsSen+aYldKCIKAqltvRftrr6P5wQdJG5VYdzfann8ezgkT4tk9SLTMdKC35leMxVg6G0cHAOibdiKtTz+NvX++AYDEDth53vkYfOcdyDv44JT2E94ZF32y6aSc9ifcs2bBXFiIaGsrIg0N6P52BdwH7J+wXdf/4owTpSFvHTKYOL8tD+mgnUYiaLrjTuQfc4wmpVRGzO9H23PPSa3vYlGS2RHsdtiG6XPuUoFyvhC7u+OZJ7udyTzRqLjuOvi/XcE4VJaKCoZaXnLRRcg/8khYKiqSqvADgL2Gcn63bWN+G1pNWkb3iu+Y30fv/ckm7Tnm96Pu15cyrY0KTj0VpZf+mrx2zZxJ2r+Fd+1CcOMmOMbEAxux7m403X8/Wpc9xWRXBasVlf/+FwSLBXUXSa0BW597DkXnLGHq0WkE1q3DzvPOZ5hl5sJCFC1ehMIFC1I23M35XkR61u9oewcwBGh/+WVyH9teehllV1ye0j5zBZF+oD0DEgtIzkWGd8WfJ+VvkyzzK69F5oKCuPPb2gak0PqmN+h47z2IgSDy5x+ra67rC/hXr0bDrbeimyrNiLa2ouk/d6DlwYdgKSvT1fpOiWhLCxpvuw3NDz6IwjPPRNHiRaritrkMw/kdQKAXrhBlfGktroLJBJPHQ4zPaGdnr/vrpZT5LeVkfnsyRubiYuJoRFpakjq/1kGDpIdVFKVWP+FwTtXaRZoS630BwDooXvNL98gMrotnfh3jx8FSWgrbiOHk/cjePbCWlzGOg7Wigsj7Rzs7dCl+02Bozw082jPt/I6B71PZ+WWzxJmkBmcKJo56qxiLofaCCxMm+eb770fRkiUou/IPCYtVJlWs2cxvkuwo4/z27riCxYKCX5wE74knoPWZZ1B/w18AgCyEdAsWa5ad35jPF6dzu1yqz6xZ0epIFMWMGhJNDzyAxn/9m3lPDAZRe/GvUPXPfyJ/3s9174vJnFdVamyZGxCsVuQffRRan5Jaz3S88UaC8ytGo4R5AgD5xxzNfE63OyL7dbm460m4vh6IRBDavh2BH9bCOWli0nPce/31aH/1tYT37SNGZIVZIrhcgMUCRCIQg0GmtEMr+GT2eFD5j5uxY9FioKf20z1rFjNWBUGAfZR+kS61dlSx7m74v/8+vmFPe7Hgxo3Sc9UDaw7Qnvf86U+M48ubXwWbDe6D56Dzv28DABr++U8MvuM/MDkciHZ0oPaCC9nrhRRYqPzrTXAfeCBEUYRz+nT4v/sOCIfRdMedqLz57wnn0r1yJWovuJA40ILLhbLLLkPBqafA5HSmdX2s4rO0RoSpbCVNQx9oYASvKvtuPqOdWrr9otKmZTK/XZ1SayZ5nTabSS0+0xK0j0Sv2l54AXuuvQ4AEN67ByXnn98nx9VCx3vvYfcVv+XSnIEevRnKJhKsVl3traJdXcT2kxhlD6D1uecw6n8fqwYLcxWG8zuAwDq/8Yk2Gd3VnJ8fl5Jvbwd66fwymd+8dASvJIfAXFQISEkp1bpfpr64oADm/Hyqz3EnUzucbUS7utD69NPoeO012EaORNU//sEY8jyxKwCwDR0CwW6XDKydOxHctAm26moEN1GCLj1Kk9byCuL8hvfWwzmFpYxaq6rIgitlfpMLCdGgM7982nP8d7ANHyHVIYfDiHV2Iub3E8Mh19ocAQr11vY4NUotutny6KOI+bpQcf31jHGdyWszU+MzWTsgut66twEqGYLJhIKTT0bDP26BGAggtGMHwrt3M/T79DO/+gSv9LZGMzkc5DlBOAzR75cclAyg6d570Xjb7eS1Y9IkRJubpexdOIxdl18O4c474Tl8rsZe4lC2BhkIyJ8/P+78vvsuyq+7lmEMdX3yCTFAzV4v8hV0Zdf++5Net+aSEimDdsYZ3ODr7iuvQvurr0rHeuONpM5vYP16ruMLAHmHHarvAlOEIAjSetKz9oSpwGQy5oVr5kyU/PJCNN19DwAg/zj1Njl6oKbG3b3iO2LA2keNhGB3SEJNosg4C3rZB0zmN4PsqfY33yRUcAAoueQSlPzqYm7wynvcccT59X36KWovuBCDbvwL6i79DYI//ki2s9XUoPi88+A9bj7pIS4IAsquuBw7zjpbOu6rr6KL0scg19bZSZhxpvx8DL3/PjinTu3VNbK9fqU5jXYaaRG8gQS5dl9GXzq/tFMb1qI9KzK/SltL7s9Mr5t90e4o5vej8fb/kNfN992PglNOydj6nXC8QAB7rr0OwS1bUPF/18E1bVrCNu2vvYbdV/+RMARhNiP/mGNQvPQcBDduRNMDDzD1+AVnSPR/OjGiBjEUQvsbbzKMMu+xxw44xxcwnN8BBdoQp9tNJHN6zPn5hFqSCTphaplf1vkVbDYijsSIAak4Bkwf23wPTAXeuPPb1t4nzm+ktRUtjz3GULGCmzaj/dBDUXDiifHtGlnaMzlvpxN5c+ei821pwW9/803kH3UUMWqsVVXEKLEOijsikb3SgkQHG6xVVeRvZasjPT1p6ZpfLu2ZEmWylBTDUlpCKFGRxkZSW5aTzq+idYIoioxBa62sRMFpp6H7uxXwfSJltNuefwExXzcqb/47CWTQ19bbPr+MInIf0Z6VMNntcM2YAd9nnwEAOj/6KH6NFgsslPJ6KtCb+dUjdkU+z88n+4q2t2ekt2tw2zY03nEnee064AAMvusuxLo6sfOcpVKmLRZD0z336HJ+RVFkM799SBPsDZzTppHgWay9Hb7ly5m2PK3L4llf7yknJxg0eXMPw+B774Ho9yNv7lxNgyd//vy48/vWWyj7w+81s7cNt90WP8+pU5F32GEAJL0Ez7x5KVxlaqCd39COuPOiZ04r+fWv4Zg0CSanE+5Zs5JurwU68xvcHs/80vW+rlmzIZgERqUYkEqb9GoEKOvqxViMOA7pIrx7N/Ze/2fy2nviiSi95Feq2+fNnYviCy8k/Yq7v/4aW446mmTRAaDsqitRdPbZ3DHjmjkT7kMOJnO4mkgjILHLhj70IAku9wZMN4H2ROc3vGNHxtkqmYAoigisWQNrZSWfXdfaSsrJTHl5umj6mQKT+aWc3wTas6LmlykxozKWTHCH0tDIFlqefJJZ+2R9jXJKdJJGtK0NoV274Bg/PmGchOrqmOCPKT8frhkzmGeg4Z//QscbbwAA6n59KYa/9ipjA9NlPYAUFBt87z2kl7hj3DjkH3ccfMuXI7x3L/LnzUvJfhNsNsIo63z/fbQ89DCKli7V/f1cgqH2PIDAZH5r4wt1snZDpgwJAcmgs7HJan7NisnWXFJMHnpzMa34zF/AaMfP7MlXRK7b9J5y2ghu2YJtJ56E5nvvY64bADpef4N5TdNaLWWs0++dH8+idLzxJgJr15LXjvHj4t8rjzu/4Z4+dnSwgXF+29vYWkodi5ZS7VnZDiBC/Q7mwiJYS2madDxTnElRqExBsNkgyJS2aBQxnw8hKkjknDoFJb+8EEPuvhveE04g73e89Raa7pEyOKIoZtSxN+XlEada7O5GrFtdgTJbzi8AuGfHjfP2V14lf1vLytKmlCpbHam1lqDHrykJNZ+hrWWo7rfxP/8hUXDntGkYct+9MOe5Ya2owBBKrTe0bZuu9hix9va4sehycXuZ5yIEQWCyubIRBUgBAkJZFQQUnnkm9/ueww5D/tFHJ430u2fPIu3sIo2N6NZoa9P97bfwybXGgoCKG/6Mkl9eiJJfXgjv8cfD1NO6KxugxyOdudPz/AmCAM/cub12fAE2cxuu20XUg31fxp1f9+zZcE6fkfjdoUN1O1yCxRIfr4pa/HQgRqPYfdXVZG20Dh6MckoRm3sOgoCyyy9D6W+viL8pO74mEwb97W8oXrJEc14qv+rqpEJV9nHjMOyJJzLi+AKspka0ox1iOMysibHubkSTsHv6A/U33oTtp52OrfOP47Kg+qPNkQw68xvaFV+rlTZtQuaXaXMUHwfmAjrzm13ac7S9Hc0PPJjwfuuyZUxwNH4+bdg87yhsP/kUtDz8CPOZf/VqbPnZkai75Nfk385Fi7H9jDMR6QnudH36KVqffDK+v6Ym7Ln2OrJmNT3wAOP42kePxrBlTxLHV4ZgMiHvkENQeNppads3gsmE/J//HNXPPgPb4KrkX8hBGJnfAQR6QaYFV5IJHSkn7d6CbbGUWuaXVoi1FFKUUJU2MEwrn/z8PmnVIMO/di1qzzufiSxbhw1FuCdD4PviC0SamogToJb5BQD3IYfA1EM/D9fVofWZZ8ln9nFx55fJ/NZLE6iS9kw+37M3XkvpdusSMjO53VINeGcnxHAY0dZWtu0UtXhbiouYqCrj/GZQFCqTMOfnI+L3A5Dotkzmt6dmUbBYMOhvf4XJ7SI00M733kfppZdK7RFkITmns9eGtyAIMJeUEJpxpKUFNpVsJr1Y90btmQfX7Nnk78CaNeTvdCnPgMRokMVrEA5LonWc82ZE2ZIEy5i67Qyo0frXriUUSwAov/oqxnGzVlVCcDoh+v2IdXUh1qPiqgXasLEMGpRzmR4t5M8/Fs333w8A6PzwI0S7fDDnudH69NNkm7y5c1VFhPRCsFiQf/TRxFhrf/11rpMoiiIa/n0ree09/ris9PRVA702hlN0fjMJk8MBS+UgiWUTjSJUVwdzYWFcF8Jshmv//aTuBwpYUxQDMxcUxFWL29ulLhJtbWi8++6U61ZjHZ3wr1zZcxEmVP7jZlVBOyVKzj8fJreb6BHAakXVLbcg/6jkmX778BqM/Pgjdeq2IMBcUJDRZ5Mpq+nokNZDRb/f0M6d/SL+E1i/Hm3PvwCT242Si35JGDMd772H1p5+y9G2Nuz6w5WoXvYkU65Ftzmy9FGbIxm0/RjZW0+9z87BTE/uzg6u2BWQXUE3JZofepgEj6zDhsKc50Fg7VqIwSCa7robg/5yA7O97/PPSb1sx7vvoPjceMa08913uccIrFmDHWefjap//Qu7//jHhM+7PvwQbc89j/Du3YRJAQCOyZMx9P77+nweG0gwnN8BBNrJoPvK6aESyuhtpBdg+84mzfwWFJC6UYB1CpnMbzOfEsocK98Ds7cg/lkWFZ+7v/tOEszoMRIElwuD/vxn5B9zNHYsXgz/tyuAWAwd/30bRWefBQCINFKZX4XTb7LZkD/v52h7/gUArAPiGKeS+d2zF2I4DFHOFppMTFsaJlKqQ+wqfowyhORG8fX1xPkVRZFEGQGpXpV2fsNqzm+OZH6BHue3Xs6YdyBURzm/Q+IGvWAyoeTXvybOb6iuDqIoIkaxCTJ1XZaiorgCZVOTqgJlNjO/jnHj4urqFNIVu5JhKS1FqOcZiTQ2cp1fRpQtWYlGhvuSN956G/nbc+SRcE6ezHwuCAKslZWk92d4927mHMRYDIhESM0hoBC7GiD1vjIco0fDPno0ghs3QgwE0P7aq8g7+GC0v/Qy2aZw4YKMHMs7/1ji/Ha++x5i//d/MNntEEMhRHooif4V30riRQBgtaLk179W2Vt2QI9HJvPbD3OavbqGlJiEtm2DSPW2dU6eLDmVeXlMABYAbENTUxs3FxSQeuFoWxswbBiaH34ErY8/0avzL77wArimT0/pO0ULFsA2dBg6P3gf3uOP59YwqkEwm/tU84OhPXd0MpRnGaEdO1O+B6lAjMUYOyO0YzuaH3yQUMABiUkx5L57EfMHsPe6/2O+H1i9Gk333MsocNP6D32d+WXsRyqQoEyq0DZurKMTkUa2xy/Zjmnl1abrHMRIhNE6UcJSUpzAQgg3NKDl8cfJ69JLL4W5oAC1554HAGh76SUULT2HyboGqaw7XbYIgGGoOSZNgqWoSKplF0WENm/BtpN+Qe6PubQEeQceRMpK9v75z8y9c+2/PwbffbfR5ikJDOd3AEHNIE5KJfSyk3ZvEUuh5lcQBFiozBddX0j/TasMqx7Lk4+YN65wGcuC8xuur0fLI4+i9Zln4tRGhWCGd/58yfmFRB2MO7/8aKSM/GPnE+eXhmP8BPI3nfkN1+9FtMexAKToJ9vuSj1SqgVrWTkRPAjX1xPnO9bRERcJcbthsttV6zozWRebSSgp/vQiYxvCqtWaCwpI5lL0+xFtbs6KU2+mFJ+16n6ZPr8Zdn4FkwmuWbPQ+c47zPu9yfwCUjBLVqeNNjUBnKwdG8BKrk8go7fPt++rr+NUXpMJpZf9hrudtYpyfnftIs9DpLUV2087HdGODgy9717y/DNiV4N6d//6A/nz56Px35Lqdf0NfwFd+W+rqYGbYgn0Bo4pU2AdMgTh2lrEOjvR9sILCNfWoe2557j0/8LTTut1xjlV0GsjozbbDxkTW00NfJ9/DkBiogR7xiQA5jdxTZ+Bdtr5TbHVFo89FfhhjcrW+uCcMQOlF1+c1nfz5hyEvDkH9er4fQElg47v/G7P2vEjra3YccaZSbPz/pUrsWPxEinY2fP7CjYbSZg03Xsv3HPmwDVdCjSwtOe+Va43e1Ta3ikSOrSTnJD5ZWp+48HXiEYtuIxQbS12LFioqVlhLipC0dlnoXDBApjy89H91ddovO02Yh/ax41D/tFHA4IA16xZ6P7ySyAaRdOdd6HqX/+MH2vb9vg1tLQg5vPB5JYcVJqhVn711XBNn4b2N9/E7iuvkmwyyrmt/Otf4dpvP/jX/iDZcdRneYceiqrbbxuQAlR9DcP5HUBQW5BTohL2MpsSCwYlNVYAsFoh6HjILKWlceeXUog107RntcwvXdPqzWeMJj2Z39COHej6dDncB86Gffhw8r4Yi6Hrk0+k2tueMr/wrl3oeOMNRh7eXFyMoQ8/BMeYMeQ9z7x52HvjTUAkAv+qVQjV1iK4YQOCmzZLGwgCt1G8a7+ZsJSVMRO3ubiYqVlh+/A2sNlAj4d1HphIaSqZX/YY5G/qN5Dr9VjaM+38UueVQ86v0kBhMr8Kw1oQBFiHDEFwfY+6dl0dYhStMGOZ32J9qsjMPc2CWqR79uwE5zcTmV8ZagZEKnXpjGHeC30CURSJgwcA3hNOgH3ECO62dCkBLbrS8eZbxChpffpp4vyymd+B5/x6jz2GuTc0Chcs6LUAkgxBECSa9T33AgDq/3Kj+rZOJ0ou+mVGjpsK6PmUmff7w/mlFJ/bX3mF+cx9IOX8zpiO9pfjmfpUeyDzqKG02FfFDX/W1fZEhsnhgHPq1JxqO5gNKLsJ0E6jjHAWFZ9bHn9c3fEVBLj23x/dX30FAGRNkz8bct+9aLrnXnR//TUQi2H3H/6AmldegTnPrVB67sfMLwVlMJ9OssSUas9qglc6ymaa7r1X0/EFevra3v4fND/wIKzDhrH3FkDZZb8hc2bZFZdj+2mnAwA6338fYjRKssZ0CzMACNXtIj2uQ9S6Y+thqHmPPRYmpwu7LruMBC4KFy4kPemrbrkF2047nbAqPUcfhaqbb2ZYSgbUYTi/Awhqxniy7Gsmac9M6yGPR1dNDUt1pjO//FpTGkqKtbk77pwkm9zEcBg7Fi2WaLCCAM/PjkDR0qUIbd8hSbVTkXUe7GPHourf/4Z9OCsYYCksRN6cOej6+GMAQMsjj6LjrbfI5/nHHsulfwo9kvNyuxBAoqPS99Bkt8NcVCQpkEajTLTQlO9RdR6SiZ4x568QvZLBKD33nL+uml+Kit7foMd6pKEBUZkiZjZzHT3b4MFkMQvV1kGwxqfETBnAesY5AEIFzeSxadCiVzJ6m7lknF8Vxz6aQi9qk6LXb7ro/upr+FetAiD1MNRSn7VRzi9thMitHAAguDVuuET2DOzMr7WqCmVXXYnWJ5fFA5mCANd++6Hg9NMyeizv/PnE+aVh9nqJkWZyuVBy6a/7pVZSjTHTHzoGNoUwjQzvL34B54y40JVS9Mqms8evDGW7o1goFHeABAHeE07IqsjYQIWZoT13SG3SFKCDCJlELBRC23PPx8+lqEhyqqwW5B10EIqWLoW9pgZtL76IPdf9HxMYL1p6DtyzZ8M2bBi2nnAiYp2dCNfVofm+e1H229+yzm9fC16p2C3K99nMbydTgmVJk/YcaW1Fxxtvxr9bWgIBrD0bCwSIzRvr7mYdX5MJxecuhfuQQ8hbzsmTSYJDDAYR2rET9uE1EEUxQWwsXFcLx5jR0jPYs9YJDgcjEus5fC6GPPgAGm75J2zV1Sj7/e/IZ45x41D5979JXQrmHo7Sy36TlX7o+yoM53cAQZX2nLSOLnNqz4whq1MS37Xffuj68EPpb2oRpx1hNYpKrJ3N/IrBQPxckhjHwW3b4s6dKKLzvffR+d77Sc/XOXUqii+4AHmHHaqaBcmfP584v61PxVuEWCoqUHHdtar7zp8/n3V+x49P2MZSUU7abwQ3biTvmz35qsqyKdGe6V6/DXHnl6bkxjO/lHNDK1vSas+5JHhFjfXAunXkb2tlJVcQzEpRocN1tQwbIWO0Z3qcqzAcRFHMas0vAFiHDoW1spIx2nqf+aWy2g38CDrNNkmqEZChml/Z8QWA/OOPY7K7SrCZ3/i9CVEtZ2QlaEEQEKYCRr29f/2F4iVLULxkSdaPYx8xAs7p00ldr3PaNBRfcD7yDjssJ4TC1IIx/ZH5dU6aCMHlkjQezGZ45x+L4vPOg33UKGY7W0017KNGSf3iR4xI6KiQDErac7huF3GWLIMqDMdXBSal87uH4/zu3JmVdkedb79NAqeWigqMfP897npWcPLJMLlc2PX7PwCRCOzjx6H0N1K5h7WyEhXXXiNRaSGp/pdedhlzHf1a80u/rxS8crsAkwmIxSD6/UzWnRW8otSek9Ce2196iQT/HOPHo/rFFxJ+NzEclrpBUL1xBasV3pNOQvG5S7klB/bRo4mtFNy4AfbhNYg2NRH9GBmhHlZRiCq3sA6uSjgH9/77o+b557jX4D32WHgV/dgN6IPh/A4gmJxOCHZ7PFrfg2SUV+Wk3RvEUqjfk1G0cIHUM7asnGk7YPZ6yYQW6+iAGAolUDaiTFslD8zUtSdzfpNldk1uN7wnnBA3dCxmuPffH84ZM5IuXp7D58YNFRmCgMq//13TaXJMGA9bdTWJAtJtjmRYKwYRlc/gpk3x8/XkQTCbYXK7EfP5mO9kgvYcpZxfOVvJZPYGgOAVPSYDa+POr20Iv5aQfj9UWwebKR45zZRTb2GcX352NObzxVWmXa6sGKCCIMA1exbaX3yJvNc3tGf9mV+Gtt6LzG9wy2byt3PSJM1t1WjPtEBJrKsL0eZmRr8AGLjOb19i8O23oePtd+AYPw7O6dNzwumVoawtlNEfzq/Z60X1k0+g+7uVyDvsMNUWIkIPjbXz44/hOfTQlO+nkvYc2hmn0qYqnvVTAr3OxdrbmXmAvN/Zqap6rxexQAChbdtgHzuW/LYtPYrNAFB4xhmanR3yjz4atupqdH/zjZTFp2yq/GOPRf0/bkG0uRmRxkb4Pvsszo4ymVKiu2cCejO/giDA7PGQNYHYXVYrM55NbhcRWBUDAcQCAW79qxiNErFLACg86yzucyRYrfCecILUG/fTTxHasQOeeUcxLSOVsI8eTbQmghs3AkcdhaCC8gzERa8YXZLBQxK2M5AdGM7vAIPZ62WcEECHgmoGa37TyfwKNhu8xx2X+L7JBHNhIYloRpqaYK1kBReYNin5+aS+AdCR+d0cd3498+ZBsNnQ8dZbMHu9KFq0CIULzkzJaaRhcrngOeIIdLz+OnmvaOk5cM86QPN7giCg9PLLsfv3v4etpgZ5hx2WsA2t6KzM/AKSg5fg/Kai9lxGO79U5pei5MoZUHNBAQSrFWI4jJjPh5jPB8HpZGux07yH2QA91oOb4w6QVWVRod8P19YyC2nman4pYTe12nZaZTuLmXT37APjzq/VymSl04G5JHk9Mz1W1JwNsr8C2sBMP1AXop59tVpfGfScIzu/Mb+fKO+SfW7bBnNxMZP57a1g2E8BltJSIgqYa1ClPfdTQM8xfjyXDaSEtbISRQvSU+VmqaHtTJ1qqhTqnxLMTLudTqZG3FJeTtbS8I4daTu/YjiM7aeehuCmTXDNmoXBd96J0LatCKxaDUByxgpOPSXpfhzjxjFdJGQoW5A1P/hQ/BrKyvq8blu95jfxfVN+foLNZyktYdh5giDAXOAlDn20rQ0mzhzd9b//kbneXFCA/GOO1jxPwWRC3qGHal9MD+yj40yNQI/9xuuvLOuRhJmOFIbz21fIjLKFgT4DLyKdCu25NwYlkF7mVwu0umfbC4lKyMo2KSav/sxQcGvcAM475BBU3fIPjPnma4z69BOU/PLCXjtt3hNPIH/bx44l9KJkyJ/3c4z+5mvUvPwSNypJtzuiI4ZyNJQXdEjlt7Cq1vzGHTA58ysIAlv329go0Xd6aHImtzunhE6YIEBPJhVg2xzRsA6m6z3rGOpxplSsWdqzSm17linPMtyzZ0HoySo7Ro3qtbiRrsxvJ126kKwnee9rfsVYjHlubCNHah+zuJjck1hnp9QiiyMsE9y2DdG2trgKvNutOwBoIDehSnvOITZLpqGkPYe2U5nfFMWzfkoQrFYIco/2WIyIbwoOB9NCLaRD9Cq4aRP23vAX+L78knnfv+YHwvbq/vJL7Fy6lPTlBoD8Y45mgqnpwDs/TpPt/vpr8rcy8dAXIHRm5fuc8i7eXGstTczAWnRQn1ufjGfSC049JaPqyHSf8uBG6bektVtkyBnfENORom/V7n/KMJzfAQbeopyU9kxHLHtJe2Yzv/qa2WuhcMGZ5O/mRx9jnAMxGmXqJEx5eQliHVpgsj8jpeyPyeXKmChA3kEHofy6a1Fw5hkYcv99DL0oGUx2u6rjQbc7oh04E8n8Ji4CqdT8mouLgR7aVLS9HbEeYz5CCV6ZiyhhMkWvX8ZRyzEjUS0IoNZCxVpVBfTQnSJ79iLSFHfgspP5Te780ot3pmEpLkbVrf+G96STUPGXG3q/v1QFr1JRe05zrgrv3gOxR7XbXFiYNAsjCAJLfd69O0GZEwBC23ewbY6MrO+ABzfDlJeXUwG9TCOR9px+26SfGnjjxTpoEGzV8fuWTPQqvHcvtp91Nlqfegp1v76UaWcYWLOa2TawejWjU1K4cGG6p07gmDIlofMB0Pf1vkCczkzD5HZzad28tZ1H0+apmdMIbt1KWorBZELB6WekdtJJYBsxAuixMcO1tYh1d3PXk3BdHcRYjGlzpMZQM5B5GM7vAENCVkgQVEWQyHdotefOTojRaNrHV6ov9xb58+fDPkrKzIjd3Wi67z7yWUxR7yuYzYpm5x2q1yJGIkzNno1qc5RJFC1ciEF/+hPTaL23sKi0T4lnfhPveyq0Z8Fk4tby0pRcc1HcYVC2O2J6/OaQ2BWgHgRQW1RMNlvciRFFBCg1x0ypWJsLCoiDHW1rY+hyMljac2aOqwbP4Yej8m9/hXPChOQbJ4G5oECqsYL0vMqBFBoM7TlZoC4Dzm+IqvdNRnmWoaz75dLUtm1j2xwZzu+AB4/dkWsBvUxDGUCmnV+rQXvWBNf5raxk7ptW5leMxbD76quJum+ssxP+ld+Tz/2r1fstOyZPZjLM6UJuQaZEX7c5kqFcE0xqbAxO4JS2Y8h2SZxfutY3b+5c1dr6dGGy2+NBJFFEcPNm7noihkKINDYygldG5rfvYDi/AwxKw9iUl5eUuiiYzYyDTDuVqYKlIfee8ieYzSi9/HLyuu3pZ0gtRrQzMWMkWCzxTLYoql5LqLaW1AdbyssHFD3RqtI+RQ428O57qhRu2lmXqc/RVlrwKp6tpGuQQ1u3MC2mcs1QVBuTWosKnRUm4h/IXO2tYLEwfXt5yuZ9RXvONARBYFrUKKnPYihEsrAwmWByuzX3lxDcolp26EVwS7xFkW2kXueXrfvlCZSEtm1TZH7LE7YxMLBgcrtJlkbGQHr+0gE9Z0daWhiRN5tRc6gJvvM7iBEKowXElGh57HF0f8FSnbu/W0H+9q+JO79FixczY7NoYXo13jx4589PeM/SD5lfINGp5QX3AT7jjZv51VhrRVFEx9tvk9eZvKc07BT1ObBuHevgUgHZ0I4dbPcFja4EBjILw/kdYFAa5HqdHmWPunTBZn4z41DmzZ0L59SpACTBh8Y775KO1c7PGJl11P3SSs/2EdnJ+mYLtBozDdmx42Xcla0BUjlGuEfxOcJkfuMtf+TfBgB8X3yZsz1+AX5m0eTxaNbvqolMZNKxT9brl3F+e6EU2h9QUwQHEgNYyZRpBYslHqjTCG5pgVZ6tg9PM/PLqdEK1dWxbSkq+sdYNJA58GiX+7rza/J4SJ2l6PcDPewpS3k5TE5nf55azoO3jlgUtOewCu05sGEDGv/974T3/d9Kzm+ktZWIjwlWK0p/ewUG33kH7KNHw3vSScjPYEsb+8iRsCsEsfqD9gwkrtlqNi3PKU6V9hzctAnRnvIcs9cL1wHaAqXpwjEm7vx2fvghKV+zDBrECGJ1f/st+cxcUgKTXFNuIOswnN8BhoTMr07nl6UT9iLz2xmvT8mUyq8gCCi9Ip79bX/1VQQ3b2aFclJ0fpnszwhtwZtcg8luZ5xP8n6PkcbN/KZAewaU7Y7qIUajDPWWrpN0zZpF/vavXs1kCnIu88s5H+uQwZpOl1pWOJPXZi6mVZETnd9IH9KeMw06W6Sk7TGUZ533s7eiV7xa/2SgxV5CCtozEbmJRCRjpQdG5nffgJJmmWtzWqYhmEzcazSUnpODX/NbCUtpKYQe0aRoW1vCvBULhbD7d78nJS90GZZ/9WqIoRACP/xA3rOPGweTzQbP3LkY/tqrqPzbXzXbG6UDr4L63B+CV0Bi5lfNpk0n86t0fru/+IL87Zo1K2P6L0rQmV8flem3VQ9j2hl1fx4/HzVdEgPZgeH8DjAoDeN0Mr+xXrQ7ykbmF5AaebvnzJFexGJofeopReY3fix9zm/qdX+5BJ5hLf+GvMxvyrRnWvG5oV66j6Io7d/rZQRfLIWF8ShxNIrODz6IHzfHDEWT3U6Ue2XYqrQXFV49sGCzEWMmE7BQwYxoS5LM7wBzfl1Uey/fF58zn8Xollg65wu6jjyaojq9KIoIbk098GWjMr+B1WtIxtnkcsE5JV5nF1gTN1CNzO++AaVOwEB7/tIB7xqthtJzUqgJXgkmExMEVNb9dr73HlFxFhwODL7zDsI4EoNBBNatg391XOwqWW/yTCD/mGOY1/2W+U2gPav0/s1Lo+a3tY35zEc5m+7Zs1M4y9RAO790e057TQ3TeaJ71Sryt9HmqG9hOL8DDEpnQ2/dbaZoz8rWQ5lE8Xnnkr87P/pY0eM3ft009ZuuP6XB9vkcWLRngG9Ym1Uyv4LLlbI6qZL2TFNxLZysM71QBKhFOtecXyBxXCZbVKwcwQuz15uUopvSOZVQ7Y44md+BTHumx0b3N99CDIXIa5plwovc88D0JU8x8xtpaIw7rnl5sJQlGkc80LRnmrptq6mBvaYmviFVg2w1Mr/7BJTzRTb7bOcK+JlfQ+k5GXhiTLJQFB08UCo+d334Efm7eOk5sA8fDtf06eS97hXfIUCxZpyTs+/8WgcNQuFZUv9t70knZdye04uEsgMVFhs/88tzftlWXjLEcBjd33xDXrtnz0K2YK2qijOGKNiqa9i6esoxNsSu+haG8zvAkEB71qm4TE/aqWZTaPBEqDIF14wZJAoY2bOHoRjSx1L2+g1u3oy9f/0ruj79FEDqfT5zETzD2kQyv4rFIo1Fy1LG0p7V6n1lqEVJc9FQVBooyRYVnshLpq/LQtOeeZlfKkI90DJPtsGD41kMv5/JYLClCzppz9TznSpLRan0rDeAYS4pSWAMAJLza6uu5n7HaHW0b0BpbA+05y8d8K7RoD0nB28Ok+cBNdErMRwmtgkAeH7+cwCAcwbt/K5g5k1HBlSd9aDi2msw+ttvUPm3v/bJ8XhQOrVqNq3SzhGsVu44tqjQnv1r1pDezEqF7kxDMJlIFxMatppqbpspwGhz1NcwnN8BhvRpz3TNr2RQpqOkGkuhbUmqEKxW5B18MHlN97dToz13ffoJtp9+BloffwK1F/8Kobo6ts9nUVHSPp+5CIsy8ysIRCk3IVORxu9A057Du3ej9em4/L+lKPF+uWZMJy1tmGPnZOaXPadki4q5uBiCQuhFb32qXjCCV8kyvwPQ+KaDIzS1jGaZpMVSSTHzy9b66y93EASBW/Nmq66Gjc789sDkdg8oBXkD6kgQ3BmAz1+q4Dq/Bu05KRICJaUlMNlsANjgAS161b3iO2I3WQYNgn3MGABSsF+Gb/lyorlhys/v037L5iStMrN+fI8+e0Y531rKyrjBTZb2HNfSoNcl14GzM8rs4sFBU597YKupkVrkcWqNeQw0A9mD4fwOMCidDf1UQrrmtwPNDz2MDTP3w84LL2RoismQzcwvAOQdfjj5m7RIgYL2TCkM+/73CWI+n/QiHEbrU08jtJWiPGepv2+2ocz8mjwe0tJKmfnVOwZoKAWvOt95h7zOO+ywhO1NLhdclOqzjNx0flPL/AqCkCA2kWkVazPVOirS0pLwOe38Wgoze+y+AE0h831BO7807VlnoK4XNb+9qfXntZmw1fCdXyPru+8goeY3B+e0TMMQvEoPCSU1g+IBMxtDe45nfrs+ilOePXMPI06Xbfhw4qjRNphz4sSk7Sv3JSRkflXsGeX6wRO7AtTVnn1fUvW+s7JX7yvDPop1fgWbTaoPt1q59dVGm7G+xU/nCdtHkFjzq5dKGJ842l54EQ233AKxuxu+/32C1uee17WPWCgEMRCQXlgsCdmyTCDv4DncqJhZJfOrRNuLL8JPqSbq7fOZa1Aa13R0NqFGJsU2RwBgcjq52c3Cs86C96STuN9xH5i4YGQ6Q5oJMNF5lYyeEsq64EwbwHTf5EhzE/NZzO8nz5VgtXJrhXIdSkXwaJekCk/TltX6Nyph6kXmN0RlfvUqPcvgjRN7TY1ksPRkd8i2hvO7z+AnSXtWBNjMpSVJe3AbSHTA6DmDDpL5f/gBoZ07IYoiOinnN2/uXPK3IAhwUnW/Mhx9UO+bS9DLZEvI/HLEroCe36gneBDr6oIYDiPm88H/fVxcyj0rOy2OaNgVmV/bsKFEXdqqCMgLVquqM28gOzCc3wEGwWZjFim9VELGoFQ0/m66915SC6GFWIo9O9OB2etl6EAymD6/inpMa2UlLD2iE7H2drQ89jj5TG+fz1yD0rimrz8TNb8AYFVMtsW/vBDl1/xRNepMOzjk2DloKNI9jy0VFQmOCw/K7HA2nd/gjxuw+8qrENwsZSmVlOds07GyAUthIezj44rgsrBIWoJX1L0P1fJ7ZqohSPX3ToX2DKhkfocNg2A2J1BCjTZH+w4S5tMcnNMyDeU1GmJX+qBcF+gMnrWiAq6ZM6UXkQga77gToa1bSe9ek8uV0FfWNSPR+XX2Ub1vriAxmK8meKUv86ts5RVta2P66drHjIGlpIT73UzCPkbh/FbHgyM2RSmWtaoqa22XDPBhOL8DEPSDrZtKqJEdjDY1oeXxJ5Lug+nZmcV6t7zD5ya8R0+IjnHjgJ6ed7bqagxb9iSKzjqbfB6jskWpZn9yBTQtGWAXCL3qiMlAR51Lf3sFyi67TNPxck6alJAdyEWKID1W9PbOU9YFZ9oAtpSVxfcZi6H91Vexdf5x2HL0MdixaHHWjtuXoKlkMvU5mobglX3kKPJ31/sfMJkTLURaWxHtoZQLDkfKfSuVzq+lvJyMd6XoldHmaN+BQXs2KM96oVx7lfTV0isuJ393vPEGmu67j7x2H3QQqQ+Wwcv89kWbo1yC0oZVE7wyuVwkowuoO79AIvWZ7rWbzRZHNCyFhUx2ml5DlEwzo81R38Nwfgcg6PpBvQu1sn1K/vz5qLj+T+R180MPJTQEpxELBtHwj1vi+8uike6Zm+j80s62ddAgDH3oIZT/8WpUP/M0rIMGoeAXJ3H7surt85lrMNntjOoyvUAIFou0EHA+SwVlV1yOsquuxNDHHkPJ+ecn3V6wWODaf//4a6cTJo5Cbn+DHut6FxWl2ESmDWDBasWQBx+Ea7/9mPdD27YhXFsbPy71bA80MC2PeoyNWHvqglfOaVPhOfJI8nrPNdci0tSk8Q0JoS1srX+qdXPWKtZZpmmMdNQeMDK/+xKY4KHJlHEhx1xEQubXELvSBWWZj9zmSIZr+vS4ZoYoouO118lneRy7xjlhAqMyb6kcpErn3VehN5gvmEyMHajVxo62Abq//ZZR285miyMlaOozs54o7A1D7KrvMaCdX0EQigRBeFkQBJ8gCDsEQVjQ3+fUFyg47VTAbIZj/HjdFBnH+HFwTJkMmM0oPOssVN78dxSccgqJRsU6O9H84IPc78Z8PtRe+EtGuMF74gm9vg412IYNS6AsKp0R9wH7o2jRIrKImwsK4D3uOGabVPp85iJo6rNygWBo4GnU/ALSPS1esgTuA/ZPvnEPaAcnVzMkniOPhLmoCILTiYJTT9H1HaXYRDZaODknTsCwJx7HsKef4hpCsFp1n28uwjVjOuk3Hdy0CZHGRlYgT6dTIQgCKm74MzECoy0t2HPNtRBFUfN7wc3pU56BxMyvrTpOBVWKXhmZ330H7Fya/5MQG0qkPRvOrx6YbDYmyG7hCBeVXn4ZoGRQCQLyDjs0YVvBZmNsOOeknxblGeCorWuwCunPlGVbzHbU+N775xvigVGLJU5N7wMULlwIWK2wVA6C58ifkfeVQXklDdpA9mHp7xPoJe4CEAJQDmAqgDcFQVgliuLafj2rLKPw1FOR//Ofw5Sfr7s+UDCZUP3MM4h1dDBOS+llv8GuyySqTssTTzL9XmUE1q1DcMMG8rr4ggtQeOaZvbwKbXjmHoZmKpOjR1m6cOECtD0fF+9Kpc9nLsJSUQGsWwcgsV7S7PEgsnev9HeatOd04D54jrSwi2LOGkzW8jKM/PgjIBzWLeKidHyy6di7pk2D6567EWlqYut9i4sHZFsuGSaXC86pU0m97+4rr0Jo+/b45ylk1CyFhRj097+h9tzzAABd//sf6i7+lSbjJNDzrACpKz0DgKWkBILNRpRX7Uzmt5rZlteH28DAhLWyEoLVCjEcVu3pvK8hoXbVqPnVDduwYQhu2ADB4eCugY4xY5A/fz46Xo9nfZ1Tp8JCMblouGbPInNmXzpmuQKTywVzSQmiTU0wl5ZoCj7ahg5FuK4OMJm4Kvxku5pq7vuumTP7VNjNc/hcjP78M5icTgiWuLul7PWrFMAykH0MWOdXEAQ3gJMBTBRFsQvAckEQXgNwNoCr+vXk+gDpGOeCICR8z/Pzn8MxfjwC69ZBDAbR/vLLmvsoveIKlFyQnCLbW+TNnYvmBx+SXuhUlnaMHQvnzBnwf7sCwMBVepbBZH7z1DO/fUnTs9fUoOKGP8P36XKU/PLCPjtuqjDZbIAOoSuyvdMJS2kpIo2N0us+uKeWkpI+Ed7oS7gPnE0MOd/nnzOfpdoaLe+gg1C0eBERsOvSWfsLpFfrL5hMsFZWEoedoakpjClexsfAwISlsBCDbvwLOj/8CMXnndffp9MnSMz8Gpknvaj405/Q8uijyD9qnuqcVvrrS9Dx3/8SkSUu06cHxYsXI7JnD2CxSKy+nxgEkwmVf/sr2p57HgWnnaaZsCi78g9ouvdeuGfP5rYLklG8ZAmizS1M8NVcUoyyyy7L4JnrA2+MmAsKYMrLQ6ynK4LR5qjvMZD5PaMBREVR3Ei9twrABOWGgiBcIAjCt312Zv/P3l2HR3WlDxz/3pm4uxEXEgIhwd1pS6EUWqCuW6fb/rZ0K9ut7G63st26t1sXqFBKgWLF3YmRAHF392Rm7u+PSW5miJBAQoTzeR6eJ+NnwuTOfc95z/sOIJJKhduTTxoVEuiI+3PPXpLAF/QzpS3N4K270ZDc5YEHlZSj9vYODyQ2s2YqP1tPnWp829QpQHMFyVGjLuGo9JkH3u++g0V4+CV93d5mM0ffY9rEzQ3zkJDz3Ftoj93VV7dbXdt82DDUFxDou65YgfmwYd16jMrevs3e6q5q2a+ndnQ0KkZj4uiI5Vh9FXrL0aONWo8JA5/9okV4v/M2lhEj+nool4TKykr5fFuNH3/BHQMuR1ajR+H97jvYzZ/f4X3MfH1x/tOfAP3xyP6aBR3eV2VtjeeLL+L5wgv9sobGpWAzbRre772rb3XZCYvQULzfegvHG27o9H4mrq54vfoK/j+sUv75vP8+5sH9owaMJElKYVdTH58LylQSLo50vn1U/ZUkSdOAn2VZ9jC47j7gVlmWZ7b3mOXLl8sAH3744SUZ40BSn5BAfeLpDm+3GjsGM79LmxqlKSujPi4OqwkTuvWlUHfqFDQ1YRkV1XuDuwRkWaYhMRHUJlicUzZf1umoPXIUs4AATN1Ff7ieIDc2UnP0KBbh4QM6/bivNaSlUXcyGpq/WyQLc2xmzLjggFFbVUX1nj3I9Q3nv7NapV8VcL+wtGRZo6Hm8GHMQ0La7CnTVtdQd+I4VmPGiJ6owoCnq62l9vhxLEeNRm0jPs89TZZl6o4dw8TTs8tdB4TLh66xkdrDR7AYMVycb/SudlfOBnLwOwrYL8uylcF1jwMzZVle2N5jWoJfQRAEQRAEQRAEYfD68MMP2wTAAznt+SxgIkmSYX5iJDCoi10JgiAIgiAIgiAI3TdgV34BJEn6AZCBe9FXe94ITB7s1Z77miRJx2RZvvzKEgoDivicCgOB+JwKA4H4nAr9nfiMCl01kFd+AZYDlkAhsAp4SAS+giAIgiAIgiAIwrkGbKsjAFmWS4HFfT0OQRAEQRAEQRAEoX8b6Cu/Qt/4tK8HIAhdID6nwkAgPqfCQCA+p0J/Jz6jQpcM6D2/giAIgiAIgiAIgtAVYuVXEARBEARBEARBGPRE8CsIgiAIgiAIgiAMeiL4FQRBEARBEARBEAY9EfwKgiAIgiAIgiAIg54IfgVBEARBEARBEIRB77IKfpcvXy4vX75clLcWBEEQBEEQBEG4zJj09QD6iAiABUEQBEEQBEEQBiepvSsvq5VfQRAEQRAEQRAEARrrNX09hEvucl35FQRBEARBEARBuCwd+i2F45syCBrlylX3j0CS2l0oHXTEyq8gCIIgCIIgCMJlorFOw8mtmQCknCyiNLemj0d06YjgVxAEQRAEQRAE4TKRcaoEnba1BFJWYmkfjubSEmnPQFNTE9nZ2dTX1/f1UDplYWGBt7c3pqamfT0UQRAEQRAEQRAGoLSYYqPLWYmlRM317aPRXFoi+AWys7OxtbXF39+/3+a7y7JMSUkJ2dnZBAQE9PVwBEEQBEEQBEEYYLQaHRnxJUbX5Z4tR9OkxcRU3UejunRE2jNQX1+Ps7Nzvw18ASRJwtnZud+vTguCIAiCIAiC0D/lni2nsc64yrOmSUdeSkUfjejSEsFvs/4c+LYYCGMUBEEQBEEQBKF/SospUn6WVK2xRVbC5bHvVwS/giAIgiAIgiAIg5wsy6TFtu73jZg5RPn5cil6JYLffuLdd99l2LBh3HzzzcydO5eoqCh+/PHHvh6WIAiCIAiCIAiDQFFmFdVlDQCYW5kwbkEAqubV3+KsamorG/tyeJeECH77iQ8//JCNGzfyf//3fzQ1NREdHc2NN97Y18MSBEEQBEEQBGEQMKzy7BfhjIW1Ke6Bdsp12acH/+qvCH77gQcffJDU1FTmz5/PlClTiI6OJioqipSUlL4emiAIgiAIgiAIg4Bh8BsY6QqAzzAn5brLIfVZtDo6xwcP7ui1537449ntXv/xxx+zefNm9u7dS3x8PK+//jobNmzotXEIgiAIgiAIgnD5qCiqpSSnGgC1iQqfcH3Q6xPuxJH1aYC+6JUsy4O6yK5Y+RUEQRAEQRAEQRjETmzJVH72HuaImYV+DdTNzw5zK/3PNRWNlObV9Mn4LhUR/AqCIAiC0C2yTm7TJ1IQBEHon8oLakk8kKdcjpzlo/ysUkl4hzoqlxP35zGYibTnc3SUmiwIgiAIgj7w3fhxHOmxxUTO9mHqDSF9PSRBEAShE4fXpSLrZACGhDoqKc8tgsa4kXJS3/83dkcWQ8e74+Zn1+Z5BgOx8isIgiAIQpelxRaT3twnMmZHFmkxRX08IkEQBKEjRZlVJB8vVC5PWhzU5j7BY9wY0rz6K8uw87vTaLW6SzbGS0kEv/1Eeno6Li4uzJw5UxS7EgRBEPolWZY5vjnD6Lrdq86KFGhBEIR+6tBvrd1jAqNccQ9ou6IrSRKzbgtFbaoPDYuzqon+I7PN/QYDEfwKgiAIgtAlOWfKKEyvNLqupryBg2tFaz5BEIT+JudsGZmn9O2LJAkmXBvY4X3tXa0YvzBAuXx0QzrlBbW9PsZLrV8Hv5Ik/VmSpGOSJDVIkvTVObfNkSTptCRJtZIk7ZQkya+PhikIgiAIlwXDVV8nL2vl5/jdOeQml/fBiARBEIT2aJq07F51VrkcOtHD6Ljdnqg5Prj62gKg1ejY8W0iuua9woNFvw5+gVzg38AXhldKkuQCrAGeA5yAY8CPF/NCstz//2MHwhgFQRCEwakwo5Ls02WAfgVh/kMR+EU4K7fv+CaRsvzB3SJDEARhoDj0WyplzW2LTMxUjLsm4DyPAJVaxazbw5BU+j6/eckVxGzL6tVxXmr9OviVZXmNLMtrgZJzbroeOCXL8s+yLNcD/wAiJUkKu5DXsbCwoKSkpF8Hl7IsU1JSgoWFRV8PRRAEQbgMGa76Bo91x97Vihk3h2JqoQagorCOVf86wu5VZ6itbOyrYQqCIFz2cs6UEbO9NWidsiQYO2fLLj3W1ceWMVe3JtQeWpdCSU51j4+xrwzUVkfDgZiWC7Is10iSlNJ8/elz7yxJ0v3A/Q899FC7T+bt7U12djZFRf27YqWFhQXe3t59PQxBEAThMlOWX0NqdOt35Oir9CdGtk4WzLg5lG1fJYCsb4MUvzuHM4fzmf9gBN5hTh09pSAIgtALGuo0bPtaf0wG8B3uxPDpQ7r1HGPn+5MZX0JhRhU6jcwfXyaw7KmxSkGsgWygBr82wLmRagVg296dZVn+FPh0+fLl7S7tmpqaEhBw/lQAQRAEQbgcpcUUKydSfhHOuHjbKLeFTvDAydOa/b8kk3NGnxbdVK/l5B9ZIvgVBEG4xPb9nER1aQMA5tYmzL59GJIkdes51GoVc+8O58eXjqJt0lGSXc2RDalMui64N4Z8SQ3U8L0aOLdOtx1Q1QdjEQRBEIRBrbq0XvnZu7kXpCFXX1sW/SWKuXeHK9dVFA6+KqGCIAj9WU1FA6cP5imXZ94ShrWD+QU9l6OHNZOua+0JfGJrJuWD4Lg+UIPfU0BkywVJkqyBoObrBUEQBEHoQTUGe3it7ds/kZIkicAoV+VyVUn9oKsSKgiC0J8VZVYpWTpu/nYEj3G7qOcbOdMbz2B7/QUZshJKL3KEfa9fB7+SJJlIkmQBqAG1JEkWkiSZAL8CIyRJWtJ8+/NArCzLbfb7CoIgCIJwcWorGpSfrezNOryfqbkaSzv97TqdTHVZfYf3FQRBEHpWcXZrYSp3v3Z3g3aLpJKMAujB0NKuXwe/wLNAHfA0cFvzz8/KslwELAFeAsqACcBNfTVIQRAEQRjMairOv/Lbwt6ltStBVfGFBb/1NU2U5FT36y4MgiAI/U1xVmvw6+Jz8cEvgGeQg/JzXlL5gD8u9+uCV7Is/wN9G6P2btsGXFBrI0EQBEEQukaWZWoNgt/OVn4B7FwsyU+tBKCiuI4h7ewR7kxWQikbP4lD06Bl+k1DiZgpuhwIgiB0RXF2a/kjFx+bTu7Zdc7eNphZqGms11JT0UhVST12Ll1rm9Qf9feVX0EQBEEQ+lBDrQatRgeAibkaM4vO580NT4oqi+u69VpZiaX8/lEsmgYtAGeP5HdztIIgCJenxnoNFUX6Y66kknDytO6R51WpJDyC7JXLAz31WQS/giAIgiB0yHDV19qu81VfADuDtOfKbqQ9ZyWW8vuHsWibdMp1JTk1yKJoVr/X1Kjl8LpUTu3NGfApkYIwUJXk1CjFrhw9rDAxU/fYcxulPidX9Njz9oV+nfYsCJeb5OOFHN+cTthETyLn+PT1cARBEKip7FqxqxYXsvKbl1zeJvAFaGrQUllSj73rwE2xuxwcWJ1M/J4c5fLwaUP6cDSCcHkqMUx59u6ZlOcWXiGtK795YuVXEISeIMsye344Q3FWNQd+Saa+pqmvhyQIgmC88nueYlfQ/eBXlmX2/HhWCXxtHM1xHtKarleSU93RQ4V+oKlByxmD9PTD61JprNf04YgE4fJUZFDp2cW7Z4pdtXDzs0OllgAoy6+lrqrxPI/ov0TwKwj9REVRHXVV+oBXp5O7vVduoKqpaODg2hTS44r7eiiCILSjpottjlpYO5ijMtGfJNVVNZ03EMo5W65UKDUxVbF4xSi8Q52U20Xw27+lRhfRVK9VLtdVNXFiS0Yfjqh9sk6mLL+Gpkbt+e8sCAOQcaXnnl35NTFT4+Znp1zOSxm4qc8i+BWEfqIoo8roclXJ4O+PqWnU8ttbJzmxOYNNH8VRmlvT10MSBOEc3V35Vakk7JxbV3/PdyyL3pap/Bw6yRN7VyucvQ1WfrNF8NufnT6Y1+a66G1ZVJX2r++wPT+cZeU/DrP2jRNomkQALAwuOq3OaKKwp9OeATyDB0fqswh+B5nU6CLWvRvN2jdPKP8Ork1BJwqG9HuFGZVGl/vbiUNvOLQ2lbL8WkC/2p3YzkmUIAh9q7abK78Ads6tRa9aqo+2pzSvhoy4Ev0FCaKaax04D2k9cSsWK7/9VmVJHdlnyvQXJH2RHQBtk45Da1P6cGTGSnKqlT3JhRlVnDkkqogLg0t5YZ2ydcTa3gxL264dq7vDK9hB+Tl3ABe9EsHvIJIeW8zmT+PJSigl52y58u/E5gySjxf09fCE8yg8Z+W3cpCv/GafLiVmR5bRdWcO56PT6trcV9bJ5CWXc3hdKgn7c0U1UUG4hGqMqj2ff+UXur7vN2Z76zHAP8IFB3d98OTkaY2kz5ymoqiOpgaxUtcfnT2cr1SX9RnmxMxbQ1tvO1JAQVplB4+8tM5Nwz6xNbPd75r2NNZpLpttSMLAZdzft2f3+7YwbHdUnFk1YI/LotrzIJGfWsGW/8V32BIi92w5Q8d5XOJRCV2l08kUZV4+ac8NtU1s/zqxzfV1lY1kJpTiH+ECQE15Aye2ZpByooia8gaDx2sYdYXvJRuvIFzOaitbg98ur/waBb/tH8tqKxuNVuBGXdFa4d7ETI2Du5U+M0SG0twa3APs2nsaoY/Isszpg63/f2GTPPAKcSRwlCupJ4sAOL45nfkPjeyrIQL6yZekY4XG1xXVkXKiiJBx7p0+trqsgZ9eOUpdZSMzbgllxHRRxborijKriNmRRXlBLSNmDCF0ggdSy2yW0CuM9vv2QsozgIW1KU5e1pTm1qDTyRSkVeAd5nT+B/YzIvgdBMrya9jwQQya5nQHOxcLZtwSSlleLft+TgKgIL1/zL4K7SsvqG0zg3Zu8NtQ20RxVjUewfao1QMraaOhTsOBNcnKe6oua6C6TB/MWlib4hfhrJwEnz6Yh3+EC/XVTaz+zzHlfoYO/ZaCb7iTUWqkIAi9w7DgVVf2/ALYuRr2+m1/1SxudzZajf57y83PFk+DlDrQpz63bIsoyaluN/itr2miNLcajyAHVCpxcn0p5adUKCntZhZqAiNdAZiwMFAJfnPOlKHTyX36f3Nya6ayMKAykdBp9D8f35xB8Fi3ToOy6O2Z1DVP/sTuyBLB73mkxxVzcmsmuUnlynUFaZWkHC9k5q1hWDt07fghdF+xYaXnXlr5BX3qc0t9ltzkgRn8DqwzaKGN+pom1r8bQ0ONvpqmhY0pCx+JwjfcmbBJrSu9pTk1aESFw36rKKPt5IThnl+tRsfPrxxj7Vsn2fXd6Us5tB5x4JdkEvbmkpVQSlZCKWV5rYWtZt4ayugr/ZTLabHF1Fc3sXvVGaPA18LaFBsn/RenTiPzx5cJyomzIHQmZkcWXz+zn8PrUtukzOu0OqrLBm+WxcVqatAqlXxVJhLm1l2bM+8o7bmqtJ4TWzL4+ZWjHPs9Xbk+aq5vmyDkfPt+tRoda14/wa9vnGTdOyfF8QB98HHot5Q2NSR6g2Ghq+Bx7piYqQFw9LRSgpzGem2fFiyrqWgg8UDrOOfeFY6Jmf7UtySnmoz4kg4f21CnIWFfrnK5LL+W8sLa3hvsABe7M5vfP4g1CnxbpMeVsOpfhzl7VOy17g2yLFOc1Xs9fg0NhqJXYuV3gEvYn6sESSZmKq55OFLZM2VuZYqDuxXlBbXodDLF2dV4BNp39nQXrLFew/6fk2io0zDz1jAsrE175XUulrZJh0otIfWzFYKCc/b7gn6fUUNtE+ZWphRlVSkz7Ckni5h9hzxgUohqKxs5faj9QlbhUzwJGu0GgJu/HYXpleg0Mls/jycrsUy536zbwwib6EF5QR0/vXwUrUZHSXY1RzekMXFx0CV5H8LAVFfVyIHVyeh0Msc2pgMw4dpAQH/yu/GjWCqL65m4OJAx8/x7fTw6rQ7VAMrcMGpzZGfW5eOOUfBbUo+sk8lPrWDtWyfRaY0nIGydLQga7drmOZwNTuDaC6CKMquUibScM+Xs+eEsM28NHTDHxp4kyzJHN6RxtHlC4fimDLxCHIic44P/SJceX3nNT63gzJHWWiLDJnkqP0uShFeIA0lH9bfnJpXj6qtfidI0atn5/Wma6rXMui2sx4vylOXXsPenJCTAPcCOiuI6o+yC4DFuFKRWKvUmTmzOULbZnCthX65RCyeAjLgSHOZY9eiYB4OKoloOrklWLqtUEkFj3DCzUHNqr34CoaFWwx+fJ1CWX8v4awKUv9OKojpyzpbhG+6MjaNYGb4QtZWNSqtME3M19q6W53nEhWvJ0LFztVTijYFGBL8DXMrx1n0sU5aGtEkLc/O3pbxAP1NZkF7Za8HvoV9TSNivD3DMLE2YffuwXnmdC6XV6Di+OYMTWzIwNVMTOMqV4NFuDAl16Bcnou2t/IJ+lcTcytSoBVBTvZbqsgZsnSzafUx/E7crW0kzc/W1ZeIifeBhZmmCu3/r53XYJA8Km9PzDQPfYVM8CZ/iBYCTlzWTrgtS0vlPbMlAbarCK8QBNz87TM3Vl+Q9CQNH8vFCo2r3xzamY2VnhpOXNRs/iqOxTp81E78np1eDX61Gx45vE0k6UkDELG+m3TC0116rJ3W3zVELc0sTzK1NaKjRoG3SUVvZyLFN6UaBr0ot4RPuxMRFge0eh52HGLQ7yqlGlo0n/c5d3UzYl4uLtw0RM727PM7BQKfVsWvlGRL3G08y5iaVk5tUjneYI9c8HInatGe+60rz9FutWirLOnvbtDn3ODf4jWyu4h27M5uzh/XX27tlMmVJsPIYWdbXvrC0NWvz/VaQXkn8rmx8RzgTMrb9fbpNjVo2fhSnnPNkJpQa3T5mnj+SJBF1hQ9xu7PRaWXyUirITSrHK8TB6L5arY7Ycwoygj4zqeW9CHqyLLPr+zPK1jvnIdYseDhS+T8MHuvOzm8Tlb3/x35Pp6a8gYmLgji+OZ34XTnodDIO7lbc/Pz4fnFONtAY7fcdYtOrCzy2Thbc9Z8p3fo+6G9E8DuAVRbXKRWCVWqJ4DFube7j7m+nfNEU9tK+36KsKqWFAEDysUKm3TC03wQiRVlVbP86UVk50DbpSNiXS8K+XNQmKlQm+oOESiUxdJw7024aeklXDnRaHUXnNCZvOZBVFtfj4m1LaZ5x/9uSnOoBEfw2NWqJ39362Rh9lR++w53bvW/wWHf2/pykBMqg378+dVmI0f1GzvImLbaYnDNlyDIcWZ8GgKTS/w3MvDUUMwtxaBP0zhxum2a358ezqNSS0WeturSBhjoN5pY9/9nRanRs/jSe9NhiAGJ3ZBMY6cqQUMcefZ3MUyUUZ1cTPtWrx7Jvzl357Q57F0sKa/TfURmnSsg81RyMSDDrtjCCRrlibtXxOG2dLDCzUNNYr6WhVkNNeQM2jq3HvXMr5APs/SkJRw+rAbkP7UI0NWrZ8r/41nZRgIO7FZVFdcqkT/bpMhIP5DJixsVPClSXNbD+vWhlq5WlrSnz7hvR5jvTMJjMTSpXJi6SjrWuFmefNg5OT+3NZffKM0gqiSlLghk52xtJkkg5Wcgfn+u3uZw+lI+1vXmbYBXg4C/JSuB7LkcPKwIi9Su8No4WhE7wUNKhY7ZntXm+lBOFyrYbcysTGmr17zcvqbzXjhMD1emDeWSf1k9YSxLMvmOY0fmJd6gjNz47XulGApC4P4/TB/ONirSWF9SSFltM0Ki257JC57IMJnpcfHq/FspADnxB7Pkd0JJPtK76eoc5tXuy4+bXOhvb3onCxZJ1MntWncVwG11Tg5bUk4UdP+gSStify+pXjnW450ir0dFUr9/T1lCrIW53DtHb2s72tijJqeb3D2LY/0tyl9sknE9pXo0yg27jaG60GtqS0m648tvymIHgzKF86mv0qTi2zhYERrWfXgb6Pb0BIw1SHyWYc2d4m0BWUknMuXNYm8IZsk4m6WgBa988aVSdVrh8lRfWKq1WVCpJSb1ExijwbVHSC/1kzw18W+xbndRhdf7ukmWZQ7+lsP69GA7+msLuVWe69/hOxnGhK79gnPp8eF2q8rN/hAvhU7w6DXxBnz5rmPpcfM5x3PA7raUKtayT2fy/+F75v+xvtFodWz41DnxDJ3pw03Pjuf2lSYRNbK37cXxzhvI90xW6dj4T9TVNbHg/mupSfVBoYq5mgcFWK0OOHlZY2JgqjyvNq6G8sNZohao4u1r5fgA4tVc/USrrZPb9nMTWz08RvS2TzZ/GG+3n3vndaTRNxunImQklxBlMtEbO9SFixhBcfW1x8bFhzl3hRqthUXNbuwWkxRRRWdK6L12WZaL/aD0PGDnbRzl26HQymac63id8uampaGD/6tZ058g5PkbnnS3MLExY8PBIQg0+k+0dd2J3ZPfOQAex6rJ64ve2fvZ9hl0eE38XQ0xdDWCGKc/BY9rulwL9DJBKJaHTyZQX1Cp7SHvK6UP55Ke2bXSdeDCf0Ime7Tzi0qmvaWLPqrPKl7jaVMXERYG4+9uRcqKI5BOFRu1zWhz6NQXPIPs2KeIVRbX89vZJ/b6KuBKs7c2MvkBLcqqJ351DQJQLvuHtr262x/AEzs3fDlvn1hnTlurI5wa/Zbn9P/iVdbJRD8/I2T7nTWeKnO1NanQRsk5mzDy/dmf3Qb8idPPz40k5WURBagX5aZXK76gos4pfXjvGwkeiBux+lP5Aq9FRmFGF8xDrAbuSftZgT6LvCGdm3x7GL/89TkWh/kTX0UNfmKdl1aIkuxqvcyoOd1d5YS0nNmcoK0VVpfXGbcwkQNanqZ05nE/YpM6Pk1qNjuKsamqrWoNQlUrCeYg1No4WaLU6dn17mtMGLYNSTxRRV92Ipc35V2pTThay87vT2Dlbcu3/RbWZRK2tNFj57WKboxaGwa9hED1ydtdXIJ2H2JCXrP+OKcmpVvZnNtZrKMvX/81LEly3YjS/vnGC2spGGmo0rH3rJIsfGzVoK8LLssyu704bFWwaM8+PCYsCkSQJG0cLpt8SSkZCKXWVjVSXNXRp9beiqJbtXydSnF1N1Bwfxi4IQKWSqK9pYt070ZTk6H/nKpXEvPtHGE3WGmrZ99tS9bllxdT4TehXhQOjXKmpaDAKjEGfRZZ8rO1EenlBLcc3ZSh79+trmthh0DrPf6QLU5YEd5rB5eRljXeYI9mn9RlE8btzmHy9PgU7N6lc+ZtVm6qImKGv8NxyXUZcSYep14OdTqsjfk8uaTFF+q4NpfVGnUbGLwzs8LFqtYo5dw7DxtGc45v0fZft3SwZfaUfu1eeQaeTyU0qpzi7ulcLNg02R39PVya2XH1tlQwHoWMD84xGaJPyHBDZfvBrYqrG2dtGOWgXZlT12KxQQ20TB39tnfELm+jBmcP5yLK+vUFlSR12zr236f58CtIqldliW2cLFj4SiaOHfg+ZZ7ADU5YF69sLyfrZ3A3vx1CQVolOJ7Pls3hu/Pt45USwtrKR9e/GKAUFAI5sSCNknDvW9uZUldbz65snaKjRkHAgl1v/ObHL790o+PWzNQ5+S+tpqG1qE6SXDIDgNz2uWElBM7M0YdiU80+GeAY7sOTJMTTUNOET3vnn1NzKlPApXsp+4FN7c9i98gyyrE8X/+W/x1nyxBgRAF+AvJQKdnyTSHlBLZa2psy4OVQpTDZQyLLMWYOU59AJHljamrHoL6M49FsK5pamjL8mgMQDrSl7F7taKOtkNn/S8arj6Kv8kFQoJ36H1qYQNNqtzRaRiqJaTu3NJS+5gqLMqg6rGNs4mmNmadJmckynk0k5XnjeQCf7dClbPzuFTitTVFPFyT8ymXROAbmai1r5bbs1w9HTGu9upHsbBq8tgRegr2wqtz6ng7sV85ePZN3bJ2ms11Jf3TTgA+D6mibMLE3aLVZ1+LdUox67Y+f7K8FgC1MzNaOv9FVW5o5vzmDYZK8O9/6mxRaz7csEZR/80d/TyU+rZPpNQ9n62SmjSZzZd4Th18EWlhZewa3Bb25SOWXtpCS3BL9Zia1pm6YW6jaFptwD7PCPcObwOv02lxObMwge44amScfBNcnK59TS1pRZt4V1aevSyFneyt9+wv5cxl0TgCSh1JQA/Uq6pa0Z/hHOHN2gf+2M+JI+b9/UVw6sSTGa1DY089aw8253kySJiYuC8BvuTH1NE74jnFGrVWSdLlUmOuJ2ZjGrn9WN6a/KC2qNqplPWhx0WRb86y6R9jyAGKaIdCXluYWbwcxsT/b7Pfp7uhIM2jiaM/3mUKPA+mw7e+0upfy01hXpgJEuSuDbQpIkzCxMMLM0wcLalCvvGY65lX4+qLq0gT++OEX26VJKcvWpzi3Vlls01Ws58EsyWq2OrZ+dUvZA6TQysTu7nrpjuBfbzdcOW6fWoLmqpL7NiS1AWV5Nj6VM9obSvBoO/pqiXB4+1avLq4fu/nb4Dnfu9gF8+LQhXP1gBCbNJ3b11U0c+i31PI8SDGkatexfncSa148rExd1VU1s/jSeLf+Lp65q4KSTF6RVGvUg9Y/Qn6jbOllwxd3DmX7TUCxsTHH2Ni6qdDFSo4s6Dnzn+TFxcSCjr/JT9s7WVDRy8o9M5T71NU3s+ymJlf84zMmtmeSnVnTavqe6rMHo+ODo0TrRc+ZwQXsPURRlVbHx4zijAlTxu7LbrM7VVlzEym87FUdHzvLu1t+24QqQ4e/23IwZ0B87Fj4ahZmF/gS8JQBuWSEeSGJ3ZvP543v54V+H2/RJjtmexfHNGcrlYZM9Gb8woN3nGT59CJbNn7eW1d9zyTp92vzGD2OVwLdFVkIp379wyCjwnXVbWJcyuwwzd9LjS9qs7ALknNUHn8p+cPQr2HPuGqYE6f4jXVj02CjGzPPHM0ifkaXTyfzy2nFWv3qMnLPlymNn3hrW5b3pfhEuygRNQ42GpCMFHFidrIxTZSIxqjm7y9XXFuvmz399TVO7GW8J+3LZ8H6M8p4GsoqiOpKOFRgdD04fzGs38DW1UDN+YUC3FlY8gx0IiHRF3ZwNNtKgSN2ZIwXUVzd19NBeU13WQNyubA78kszWz+JZ++YJDqxJ7tfnWofXpyrjGxLqiPewnq0jMViJld8BoCy/ht2rzlCYXkX4NC8mXBvYpZTnFm5+tpxq/rmnil5pNTqjHn9TloZgaq4mbJKnUmEx8WA+Y67277NZqJa9fgDuge2nZhmyc7Fk9h3D2PRxHKD/Mjb8QgZ9el3UXF/lhPXsEf2Xw7lfhAn7chm/IACz8xTF0DbpjE7oXP1sjfZlVZbUtbu/V9Oko7KkDnvX/rWqqdPJRP+RyZH1acpJu0oldSvN8WIERLpyzSORrH3zJKDfy9XV9M+ekJtcTsrxQnyGOeE/8sJSj05syeDYxnScvKyJnO1D4OjWE4TeVF1Wz7p3oinLb79gTPLxQnKTylny1Jg+zejoKsPJt6DRbkoP0nOdu7Io6+QLqpQp62SO/p6mXA6d6KGknzl5WiuTb2YWJkxYFMjOb/X9uo/9nsaZQ3nYOFpQklOtpEsbsnOxwNHDmpZDaWO9lsLMKjQNratj4xb4EzHTm6+e2o+uua1QRVFduy0vKovr2PBeTJvVtcZ6LfG7s42qXl/Myq+9i/Frm1maMHR899JFnbxaJyfK8mtpatRiaqY2Dn5b9nIDHoH2LHw0ivXvRisrwAd/TWH+QyO79HqyTqaiqA4LG9M+a9mn1eqUVcay/Fp+ffME160Yja2zBUfWpyktuwD8I5w7be/UldXf+D05SjYCgI2TOQERLq17aA3O/WfdFkb4VK8uvQ9nbxulYJnhZ23IUIfmIljN+36rm4wK9vgOd8bVxxa/Ec5UFtfj5mervL9Zt4fxw7+PoNPI+swtA6Ou9CUwqvPzIUMqlUTETG/ld3NwbYpR0DVlSYiSOSRJEn4RLkrf34y4YqMtEkWZVez8Tv83XZZfw20vThqwK3C1lY38/OpRGmo0WFibMu6aAFy8bdj5/WnlPgGRLky4NhBrB3PMrUwu+r16BNnj6murz3Rp0pGwP5fRV/ld7FvpstrKRn557ZhS5KxFztlynIfYEDrBo4NH9p2izCqjbQETFwcO2M/cpSaC335Mp5OJ3pbJkXWtgUTMtizSoouUkvEqVccpzy0M9+T0VPCbc7ZMOUmzcTJXejQGRLpgZmlCY52GyqI68lIqLnoP3YWQdbJR8OsR0LUWT4FRrkTO8ekwrWfGLaEMnzaEqtJ6kpsnIAyLjahNVEoRrYT9uUZ7gtuTcrJQWXmxc7XEwtoUWSejMtFXom2o0ZCf1v7/WWluTb8JfnU6mbToIo5vzjBaIVCpJWbcHGpUobW3DRnqiHuAnT6FXStz5lD+ef8fLlZ5QS0Hf00hNVqf4he7M5u5d4d3+wszdmeWsmJekFbJ1s9PYbPGnKAxbqhN9CerpmZqQid69Gi17+qyen598ySVBtkNPsMcmbI0hJjtWUpaVW1lIyc2ZzDz1jDlfgVplexaeRpXX1tm3Rp2wS0WqkrryUsuJz+1koK0CtSmKubcGX5B/Qq1Wh1JBicFQzv5f7CyM8PS1pS6qiaaGrRUltRf0GvqV331E1Um5mqmLAnusIdp2CRPYndkN7fv0afptxzTW3gG2RM11xePIPt2V7J0Wh0luTUUZVZh72KpVI72He5EevMx6eyRfMYtMF4R1OlkNn4UqxSFM7M0YfhUL2VCL2Z7FpGzfZTJAsO9ut1d+bVxNEdSScrKxLApnt3eP25mYYKjp7WS7ZJ6opDQiZ7GGTPnFNjxCLTnmj9Hsub1E4D+GN2VSbDcpDL2r06mMKMKG0dzljw55pIeu1pknSo1KgRVXdrAr2+ewDOotX0QgEegHVfeN+K8tRSGTx/Cia2ZrXt/D+YxYvoQ5XbDiWyfYY5ccc9wLG3M8BnubJQG3Z3AF/TnJ57BDkb7kgGGTfGiqUGrn8CQIWZHlvJ+Le3McGmekLK0MWvzf+boYc24+QFKATWVSiJknDuRc1qLUnXHsMmeHF6XiqZRZxT4Bo1yJWLmEKP7+o9sDX7TYkuYaJBiajjxVVlcT3lBbZtss4Eibne2kslWX9PE3h/PGt3uPMSauXe3LUZ5MSRJYuQsb7Y3792O251N1Nzz1wnpCbJOZttXCW0C3xZnjxT0WfCbm1TOod9ScHCzYsqyEKXKuLZJZ/T/Ehjl2uXzXEGkPfdbhRmVrPnvcQ6uSWmT9mZ4kuQ9rPOUZ9DvhzJp3odRU9HY4R94d7Ts4wEIinJTvgBMzNSEjG3dG3j6QF6bx/aE8sJa0mOL261ICVBWUKt8YVvamhrtoz2fydcHMWVpMCHj3PEMtsfW2QILG1OmLA1m+DT9l+GUpcHK77SF73Bnpt7Q2pYnZkdWpxWh4/fksO3LBOVyS4qYpJKwNTjhyjQ4cTB8H/1h36+mUUvMjiy+f/4gmz+NNwp8XX1tueGZcd06Weophq+ZsC8XWb64tKX6miZSo4uMTkhB/wW0f3USq/55WAl8W+z4OpHMhK5XBU0+Xsjen5LaXF9d1kDMtixObM7gxOYMDq9L5be3T6Jp1LbzLN13buCrUkvMvDWUhY9G4TzEhtl3DOOKe8KV+ycdK1ReW5Zldn53muKsahL355EWU9zua3SmoqiWzZ/G8c0zB/jjiwTidmVTmFFFXnIF+1e3/X10RVZCa/Bg42jOkA4Kp0FzReEh7afWdpV+1TdduTxy5pAOA1/Qn7DPviOs3eOSvasl8x4YwXV/HU3gKNcOUzhVahWuPraET/EyaplkGOifPVLQ5rOfc6ZMCdLVJirmPxTBhEWB2DjqV3XrqpqUyQ6tRqf8HiWJTt9TR2Ns6dUrqSSlcFB3hU5oXS1O2J9HfU2TktKuUkvtFsfxDHZQes+27IHuSHlBLRs/iuXXN04qK8rVZQ0cWts32ybOHGm7Zai6tMEo8PUd7szCR6Mw7SCjwZCpmZpRV7ROABo+T11VI4XNx21JJXHVfSOUgDNgpAs3/n0cE64NYPGKURd0LD+3aKHKRMJ/pAtDhrZ+ZqO3tab++4Y7nXcCbczVfsy6PYwpS4O5/aXJzL07/IICX9DXjjg3hdvOxYJZdwxrs4rmHeaorJiX5dUov8eizKo2x75zewwPFJpz2hOey8LalPkPjeyVIojBY92UCuHVpQ3EXKLKz8e3ZBhlHoy+yo/pN7X2Yc9OLKWu+tJv+ck+U8b6d6PJS64g8UAe69+NpqFOowTreSn6jENJos1+f6FzYuW3n6kqrefQbylKb94WLj42hIxz5/jGdBoN0ofOl/IM+hMtN19bcpPKAX1gbePY9dSgc+l0MqkGB/rAUcbPFTbJk1N79bOjiQfz8BrqQFgPVn5Ojy1m06dx6DQyYRM9mHNXeJv7GKYhuwfYdysVRKVWnXel0MbRgnHz/ZVVOmsHc+bePQxTMzVH1qdSV9VEdWkDKSeKCBlnnOYny3Kb1DU7FwsmGOzZsnW2UE7uDNv2hIx148QW/YlCe3uBW56/vKAWezerNgU5NI1a0uNKyE+roCC1gtLcGryGOnLVfcMxMe1eX+b81Aq2f53Ypq+iykRi3PwARl3le0nSddsTPMaNfT8l0dSgpSy/lvzUSmWvWHcVpFfy+wf6YmcWNvriT8Fj3KgqrWfzp/FtsilaVhF1OplNn8Rz3YpR7bZ+MJRzpow/vjylpBe6B9jhG+5E/J4coyJrLSoK6zj6exqTrgu+oPfUorqsoU3gO+/+EW2ySULGunN4XRqVRXU01mlIiykmZJw7uUnlRsFiSnRhm+OBMuaiWn7/IJa66ibc/OzwCLSjvqaJ+N05RvtODWWeKqWxXtPtE61kg0AnZKz7eU+mnYfYGBW96k7qJEBqTOteXxNzdZcyDdz87Ljjpck01uv711aXNSBJ+qCtZZX/QgSMdFEKBpUX1FKYUWWU/WO4yhc+zUsJQqLm+iqFfk5uzSR8mpfRscfSzuyCCvzMui2M2B3ZBES6XHCmStgkTw6vS0NurgabbNAr1nmITYcFnEIneCgZQGcOF7QpAFZX3cjRDemc2pPT7kTqmcP5jJztfd6/34401mtIPJDHqT051FQ04uJtg0dzJ4EhQx3a/Vy3/H21mLI0mENrU40mwcMmezLz1tBuHV9DJ3hwYE0yyJCXXK6shGcllirHHY8AuzbdIOxcLBk7v/39xF1xbvDrG+6MuaUJXkMdlGwDTWPre/Mdfv59o5IkKYUOe8LImd6c2qMP+FQm+gmA9vr4mpqpGTbJk/jm++754SxeIQ5Gq74tshJLiZzt02NjbKHV6CjKqqIgtZLywlqCR7v1aL/w04fylRVwWycLRswYwvHNGTTWaVCpJK66f4RRFfeeZGKqJmLGEGUi8eCaZJyHWHere0Z35SaVc8SgDdvoeX5K0b+zR/LJT9UXQU05UWSULdEeWZbZ+2MSZ4/k4+JjS/AYNwKjOp7A7Ez2mTJ+fz9GqaQN+iyr9e9G4+pja/QdN2FRoNH2EOH8RPDbTzTWaTi+JYOY7VlGez5Vaomx8/0ZPc8PtVpFyFh3dn53mqyEUmydLbrcDNzNzyD4Ta/s9smdofyUCuqaT4os7czwOCeocA+wwzPYXt+eQkZJY+mJANgw8AX9gdp3hHObtgNGKc9d2O97ISLn+ugLzuTVMHVZsDJbPmJ668E7elsmwWPdjILvg7+mcHJr60y3m58tCx6ONDpAtrciZGKqwm+ES6fBb2VxnbIC6+Zny6K/jFL2HddUNPDr6yfaFO5Kjy0mbleO0cpAZzSNWg6vTyNmW6ZRf2dzaxNGTB9CxEzvPm+AbmZhQshYNxL260/0E/bnXlDwmx5XzJb/xSsnZ/XVTWz5XzxnDruQn1phlCbnFeLAlKXBWNmZ8ctrx6kua0DToGXD+zEsfWpshycMpXk1bPwoVvlMO7hbcc3DkVjYmDJ6nh+pBtscqkrqlbS7k39kETzG/YJXPHQ6mS3/iz9v4Av6k82wiR4cWa8/yTt9MI+Qce5tCrulx5ag1ejaDd4O/Zaq7CfOPFXSbq/MIaEOeAbrUzsrCuvQanRknioleEzXK01rm3RGwUPw2PM/1mjlt4Oe4B3JT60wWiE836rvucwsTDDzMOmxFEkTMzVBo92UrJuzh/OV4LehTmOUtTPMoM1S+FQvjm1Mp76mSb+t42gB9gaV0i/0b9rNz465d7edoOwOa3tz/COclf/XQwYnq65+HX/+WybBzt0DLetkordncWxjepsCT0MnuFNX1boHdd/PSVz3+OhuTaDWVzdxYksGp/blGj1/blK58j2sNlHhO9yJ4LFu+Ee4KIFwyski5RzA2duGqLm+OHlZs+XTeJoatIy52p/xCwO6vbfPys4MjwB78lMrkGV9KnjYJE+juhZdCTy7y9XXFhMzlXIMbflb9gp2QJIw+g5B6psepU5e1ky/aShJRwsYdZVfp5Mdk64PIjOhhMriehpqNWz4ILbdY0bO2fIOj4UXoqlBy54fzpB0tNBoIiRhXy7XPBypdEfQanUc/DWF7MQyvILtCRrjhmewQ5cmrs5tTzhytjdRc30ZNsWTjPgSXH1se71y+ph5/mQmlFKQVoksw9bPTrH0qbHd6tpQll/Djm8SqTbokmFuacKUpSFGn6/ayka2fhavfAY9g+2NFiFCxrmTn6o/l0w+VnDe4DdhXy5xu/TfiTlnysg5U8aeVWfwi3Bh2o0hndbK0DRqKSuopbqsgYrCWg7/lqoEvuZWJso2w4K0SqPz24iZ3pd0b/RgIdKe+4nCzCpOnNOEPiDShZueG8+4BQHKDK+tk75lz63/msgtL0w4b0GlFoYVn9PjijutIHo+hidPgZEubQ6qkiRx9YMROLekojUHwIkHjNNPZVkm9WQRWz8/ZVSqvSPnBr4tdq8806YVUIFBpefe2gehVquYftNQFj82Chfv1hOwETO8lS+8wowqoxm604fyjAJf3+HOLHpsVJuZQbt2gl9HT2slhRCgrKDGKK06I76En14+atTW6o8vE5B1MtomHZs/iWsT+LY40Tyzez61lY2s/s9xov9oDXxNzdVMXRbCna9MYeKioD4PfFsMM0jRSz5W0KX3Zyhhfy4bP4ozWpVokR5brAS+KpXE1GUhLG5e4bVxtGDhI1FK5fC6qiZ2fJvYbup1fU2TvsJqczaHlb0ZCx+NVFK/TEzVDB3nwdir/Rl7tT8zbw1lyFAHQH+isuPbxE5T6ztzcmuGkiHR0rOzs/oBoRNb02mzEkvJT60g7ZxU78Y6DTln2lY6ratubJMWbsgzyJ4lT45h8WOjmbAwkKHjW18r9WTH6artyTpdqvxf2zpbdGlywDBttriLac+pJ4tY/Z9j/PJaa2Xsrq769rZQg6JSSccKlDT1lOOFygmV8xAbXHxa37epudqoMN3hdWlGVYa7u9+3pxmu9LXsRwRw7yRQsbQ1MwrozjanE+/7OYkDvyQbHRO8QhxY9rex+krgNw5Vvtfykiva/ezKskxuUhm5SWVGf4Op0UWs/NdhTv6R2ekxR6vRT9L88XkC3z13UElhPGuQ8hza/HfgG+7Mna9O4c5XpzDh2gsvamPY/zMtphhZJ5OZaBj89vwKm9pERXDz5LSNozkBzYUAzSxN2vxtuvnZXbLihOeKmOnN9U+MUcbXETMLE322WfN/gWHgGzjKVakerWnQtlsR+kLtWXWG0wfz25y76bQymz6JoyizisZ6Db9/EEvMtixKcqqJ253D2jdP8vXT+zm2Me28VYvT40ta2xNaqJW/OUsbM8Imel6SlmFqUxVXPxiBtYP+PKKhVsPGj9pWIe+ITifzxxcJ5KdWUl3aoPwryalh44exSheQxnoNG96PUQr6tXT8MNxjHDTaTSkymJNU3umWwYqiWvatTm5zvSzrzxd++NcR4vfktHseUJJTzVdP7+enl46y8cNY9q9OVo7T1vZmLH1qrFEaduv4XJl6Q4gocnUBRPDbT3iHOiqtOFx9bVm8YhTzHxrZ7mqAJEk4uFl1WL20PV4hDqjU+j+QkpwaDq5NOc8j2ifLMinRrSejHaU4WtqYsegvUa0HSxl2fHOa1f85TtKxAvJSKvj1jRNs+iSOpKMF7PgmkYT9bVswtMg+U2YU+Nq5WGDj1Hpw3PFNa3DRWK9R9sNKUucrA73Bys7MKFD44/NTxO/JIT+tgl3fnVGu9x/pwvzlEe2mvrVXzMjJyxpzK1PlS0Gn0VcllWV9ldkNH8S0qRSbHlvM4XWp7Fp1RpnBlCSIusKXqx+MUL6o62uaOGmw76o9tZWNrH3rpFGaq3eYIzc9P57IOT5d2nt2Kbn72ympQJpGHUnHOm/9Yig9rpid355WThZsnSxY8tSYNr2KrezMWLRiFJFzfIy+gJy8rJm/fKSSbptzprzNBI9Oq2PrZ/HKhISJmYpr/hzZ6eywJEnMvDVMSfMszqrm2KaMNu1pzqcoq0pZxQUYu8D/vIXz7JxbiyrJMmz6JI72tlKntBMonD1coPztuvjYMOeuYQyfPoSh492Zd79+f6tHYOskVZDBcSU9rgRNU9f3NxtONgWPduvSiYGjp5VyklNRVNemiuy5YndmsemTOKMZeKDTIleXktdQR+U4UVfVpKxMnz7U+hkMm+TR5nczcpa3UkOiqrTeaEXb+gJS93qS73AnpdWMofMd38/dA52wP9coY8HB3YqrH4xQJq9aroswaL1yYE2K0cR0dVkDv3+g3yP86xsn+fKp/ez8/jRbP4tn08dxSmYU6PdwT79pKLe9OJGr7htB5FyfNkFEXVUT69+LJvl4Idktk0cSRltmzCxMLnpi0TD4zUwoIT+tUhmrhY0prj6981058+ZQFj4SydKnxxpN2Bvu+4XeWXnuDV7BDoy+su0k17gF/vgYpOhm9dC+38QDeZw+1DopYudiwdAJ7so+/aYGLevfi+bXN060+5q1lY0cXpfGru9PdxoARxu0XQufNqTLiys9zdrenPkPRbTur86vZcP7MW1qbrQnYV+uUe0RQ5omHb+/H0tJTjWbPo5T7idJMPdP4W2K21nbm7emlMuQcqIQWZY5uTWTL57cx4b3YyjOrkKnk9n2ZaJSfd/Rw4ppN4bgGWyvTJI0NWjZvfIM696JNtpOAnDgl+R2q/xb25uxeMVo5XhkGAAPGerA3LvDL8te0z1BpD33I5OXBBM81p2h486/R627rO3Nmbg4iAO/6GemYrZl4RXs0O3056LMKqpL9bNf5lYmbb68DFnamLHosSh+eytaCZgK0yvZ+tmpdu+/e+UZHN2t8DynOrSmUcvObxONAt/FK0ZTWVTH2rdPgqwvLnFqTw4jZnjr92A2H9+dhtj0SmGG8xm/MIDs06VUFtcjy/r3ZmquVmZtnbysueJP4R3u2bJtJwBqCeScvayVle7S3BryUyuNAhkbR3O8Qhw4e0Qf7Bn2gwT956xldaqpQasU3YrelkXEDG9lFbqxXoOJqQqVWqUEvmV5rZMK024cyogZQ/rtrGPLvrCWfYyHfkulrrqJEdOGKCur7dFqdMpjQB+sXfPnSKztzfEIsCdotBvHN6Vj42DOlGUhHZ6QegU7EDXHR9nXduCXZPxGOCv3P7AmhazE1lXSOXeGd+nk08HdivHXBCj7zY9uSOPohjRMLdRY2ph2+P9h7WBOYJQr/iP1FVxb9tm6B9gxZl7X0qaGTfJQVnYNqwCPuqK1/VdadBEzbg5VvpRlWTaa2BoxfQhhEz073Qbh5GWNvaulEohmny7DP+L8raMuJOUZ9CvsDu5W+rRsWf935R5gh06rQ9ZhtKe0trLRqH+0ykRi6HgPoua0DWr6ikolMW6BP7u+10+2xezIwtHTSr8Vpfl2w9X1FuZWpky6Lkhp2VJV0lpc0aqPMzpUahVhkz2NWvKoTVXn3evmf84e6F3ftbZrCRzlypX3Dm/3ODx2gT+nD+XRUKvvXLDyn4cIGu2GjaM5h9elGa1E1Vc3kbDXePLWyt6MaTcMJWiUq/J9bu9qpaT9lhfUkny8kNidWfpK4/VatvwvXnm8d6ijEtz0FEcPaxw99J9zTaNOOR+ArhWaulBqU1W7q8qG+34B/Hph5bm3jL8mkIz4UuXcJnCUKy7etvgOc1L2D2clljKxef+oTifTVK/BzLJ7bYFKcqvZs6p10jx0ogdz7tQX4yrNrWHN68dpqNVQV9VkVB8icq4P2kYdKScLletbtgHNPKcqf2VxHWcO5ysp+SqVvvJyX3Lzs2P27WH88YX+/CQvpYI1/z3ONY90PEFcV93IIYOFndFX+TF8uhd1lU1s+CCG+uom6mua+Omlo0Z7/GfeGtbhZy9krLtSD+LskXzK8muUmjYZ8SVknCrB3d9OmQhVqSTm3h2Om58dI2f5kJ9awY5vEpUtP9mny9j8aRzXrRiNpJLIT61QiqNJzWn/1o7m2LtaMmyyl1FWYMRMbxw9rSkvqCVsoke367QIrUTw24/ov5h6b9N61FwfcpPKSY/Vnxzu+CYRF2+bbhUvMEx59o9wOe9+FksbMxavGMXBNcmcPpzfJmVZpZawsjOjuqxBSd9Z9rdxRiufJ7ZkKHseza1MWLxiNLZOFtg6WejbEm3T71HZvzoZ9wB7o9ZAHgG9s9/3fKztzVny5Fh+/yBGqR7asppkbm3C/IfaX/Ft0d6eXydP/WfD0ctaOVhmnykzqtw5JNSRq+4djrm1KfU1mjb7KkMnehA5p7UIR8g4d05syaA0twZNg5Zjv6fhGeJAzPYsCtIqkST96qZOJytfoJIEV/xpeJtCXv1R6AQPDq1NQdOkb2Nx+LdUjm9MZ+h4d4LHuTMkxKFNK4X4PTlUFOpXY80sTbj20Sij1Ty/4c5dPkkbtzCAlOgiKovqaKjVsPfHs4y+yo/oPzKNWvGMne/frX2tkXN9SDpWQHFW6yp80zm9NM9VUVRHblK5UWBvYqpi7l3hXW4nETjKDdNVZ41WRm2dLZiwOJDTh/Opq2ykrqqJ/JRyvEL0E2MFaZXK/nQTc3WXPjeSJBE4ylXZIpBysqhLwe+FpDy3cPa2UU5QSnKqMTFT6bMpajTMvTtcmSg8siFN+T07elix6LFR/SbV31D4VC/SYoqVNjMtgTCA7wjnDouwDJvsyal9uW0KubW36nqpDZvsZRT8unjbnLfok6mZmqBRrpw+qF85a8lWcB5iw5w7h3X4eAtrU8YtCFD+XiqL6422rLRoKXBnKHSiB1OXhXTaicHB3Yqx8/0JiHLht7dOtnmO9iYnekJApAtl+fr3YZiW6xt+6VddvYIdlP3AlramuF3iLK2LoTZVcdV9w9n8aTySpM/6AH3dgpb2XoWZVdRVN9JUr2XdO9FUFNWhNlVh42COtYO50aSambkaa0dzbBwssLJvLS53dGO6kgLr6GHFjJtbezo7eVmzYPlIfnsnWslMkFT6av0tKcvTbgxh57enlZXjhP15NDZocXCzorq8gZLs6jYrpUFj3Hq0ld6FGjreg7qqJuVvsCy/ll9eO07kbB9qKxqpLq/HzNKEsEmeeAbZc2htqrKCaudiwbgF/piYqbFztuSaP0ey9s0TaBp1RoHv+IUBnVYxDxzlyu5VZ9BpZQozqoz6iwMgG9eYGbvA32jPuEegPTc8M44j69P02XWyfivFqX25+vowG1oXLoaO9zhvfQTvUEe8e7DA2eVKBL+XEUmSmHPnMH789xGqyxpoqNWw+dN4Fj4S2aVUPVmWjfY+dZTyfC4La1Nm3T6MCYuCiN+dTdzuHOqrmwga5crE64JQqSVWv3pMmbnc9HEcix/TF2qqKKpTCjwBTFwcZHRQnrgokKyEUn3w1qRj40exRre792HfMys7MxY9Noot/zulBKEtrSTOV/XUuvnLz/Ag3bKq5Gyw0mHYksDOxYIFy0di2tyC6cp7wln9n9b9iO4Bdsy8NdRo1lmlkpi4KJCNH8UBELc7hziD55RllD0xMLACX9Cn8s17IIId3yYqK5WaJh0J+/NI2J+HhY0pQaPdGH2lL3YultTXNBlV7hw73/+i0lhNzdTMujWU396OBiDlRBEpJ4zTggMiXRh/TfeqqarVKubdP4J9PydTll9DdVmDUVpmV01eEtytQiKm5mqCx7gZpXBHzPBGrVYRGOWqrHiknCxSgl/DVd+QMW5dzsQIGuWmBBtpMUXotKHnDdJTLiDluYXzEBuSmyckMuJLOLIhTcmw2PJZPNc+GoWFjSkJe1v/PiYvCe6XgS/oj/ezbg/jh38daZMuGDap48BKUknMuHkoP796TMmggb5f+QV9CrF3mKOyEtPVKsxDJ3gowS+0tGvpfAISIGKWN3VVjcTtyjbqsgD64+2cO4fhGeRAXmoFKccLqSiuY8S0IfifZ9+oIWcvGxY9NsooAFabqoxS/3tSQKSr0XdqC59erKjbETNLE664ezhnDucTMXPIJenp2pMcPay5+fkJRteZW5ni7m+r32YkQ9JR/ep+y/YWbZOOiqK6DutvdMTEVMVV941Qvt9beAY7cNV9I9jxdSKSCmbfMcxoolClVjHrjmEASgCcfKzjOgrmViaMne/frbH1psg5PljZm7HtqwR0GpnaikYl66lF4v48XHxsKDbYfz3thqFGWwPd/e2Y90AEGz+IVc6rhk8fct73amFtim94a+/0FkGj3dA0ackwuL6jLCoTMzWTlwQjqSVONGfiHVyTjKWNqdGqb3/6vQ92Azr4lSTJCfgcuBIoBv4my/LKvh1V/2ZhbcpV943g19dPoNPJFGVW8dPLR7nq/hGdFoaqLmtg18rTysqIiZmq2zPFVnZmjF8YyJj5/jTVaY1ST+fdH8Fvb51UxrTqxcPMvn0YsTuylFRhV1/bNjN0JqZq5t0/gtWvHqOxXkt1WYNRUYLeqvTcVWYWJsxfHsGhtalkxBUzdr4/PmHn/72p1CqsHc2VtENTC7WSAufk2X5q5cxbwoy+GM2tTFnw8Eh2fXcatamK2XcMazdNxn+kCx6Bdsqe4BYts9fKmFQSc+4eNmAC3xZ+I5y546XJJB8rIHp7ltFqaX11E6f25HD2cD6TlwRTXlCrFNOxc7Fg5MyLT/3yDnNi2GTPdou6+Y90Ye7d4ReUbmjvasWC5SMB/cRUQ42mwz1RsiyTl1xB8vECss+UI+tkAqNcGXEBfVfDJrW+FxMzlbIPOsgg+E09WcTUZSE0NWiNVri70yfUzc8WG0dz/URdjYbcpHK8O/nb0Wp0Ri3Ygrqxkg7gYpCyfG6BI51GZuNHcTh6WCkrhz7DHPEb0b/TNK3tzZlxS6hROq2Ftel5V9Hd/OwYPtVLSe+Dvi941WLMPD8l9X7o+K4di4YMdcTOxYLK4nqluFtXMp5UKomJi4MYtyCArMRSko8XUpBeiV+EMxMWBirHW69gB7zO2a7THS0B8Lp3oqmtaCRipnev7bd097fD0s7MaF+yq6/tBbVj6QmBo1y7PJE+UPgMc1K+T/f+dNZoEulCTb95aIfbKgJGunDHK5NRq6V2JxBUKqlNAGx0u1rCJ9yJ4NFuBES6tGl31ddCxrpjZWvGxo/jOix8Zfi97h/h3O4ElN9wZ668bzhH1qfhHerIlGVdKxYVMs7dKPgddYUvk64LQlJJZJ0uJXprJjL6tm6dTeCMW+BP6skiygtqaTxnm0PIePduTUQLF2dAB7/AB0Aj4A5EAb9LkhQjy3L7m0oFQJ+GMe3GEHavOgs09/p8/QTjFwa0+8dXXdbA0Q1pRhvywyZ6dqvgliG1WoXaxvgA4RXiwPSbhyqpedWlDax7J9roPtNvHtru5n5HD2uuuGc4v38Ya/QlY25lgoNb3x9M1GoVU5YEK2lRXWXnbKEEv06e1spB2tGz7XsKm+ihtDow5OBmxeIVozt9HUmSmLwkhLVvnUCnkbGwMWXEjCFEzPDG3MpE34O0vAEbB/Ne6+/X29QmKkInejJ0ggf5KRUkHS8k5UShshrcUozC0KTrgjvsH9pdk5cEk3W6lOrSBlQqiZBx7kTO8bngNkXnkiQJCxvTTvcyO3pYEz7Vi7rqRqpK6nH1sb2g/dqewfaETvAgJbqISYuDlNROr1AHpSVDdVkDcbuyqSqpV4qAOHlZ496NbQiSSiIgypW45uJEcbtyOi3sVZZXY5Ty3N0USmfvtieWKrWEuZUJdVVNNNZpWtPbJJi8ZGBU2Qwe40ZarLvSO37oBPcutV+ZuCiI5BOFNNRokFQS9v3kb987zInb/j0JSZK6nJqpUknMf2gkCftyCRrtqmQldJXaVIX/SJdureh2l7OXDbf9axIVRbU4efXe3nFJJREw0kVpmQZ9k/I8mPmEOyvtDpVzEgnm3T8CnzAnqsrqqa1oVCaXZaCxVkNVWT3VZQ3UVzUaPgzvYU6ETeq4RgJw3oKTLQGws7cNJbk1WNubYeNogY2jOR6B9p2m6PcHQ0IdWfLkGGK2Z6E2UWHjqE8dzz1bxpnDBcoiidpExdQb2lZGbhE0yq3LLUKVx4x248zhfArSK5mwMNCoGJ5PmFOXFjRAv1gz67ZQfn3jJNC6BUOSYOzV/t0ak3BxBmzwK0mSNbAEGCHLcjWwT5KkdcDtwNN9OrgBYMQMb2ycLNj2ZQINtRp0WtmosmdnImZ5M/m6oB4f0/Dm6oK7V50xamUBED7Fs9OVaf8IFyYtDjJKh3H3t+u1Ah6XguGJnWFRFzMLE2wNAmNLW1OmLA25qNfyDLLnhr+No7q8gSEhDkYTG3YulgM26D2XJEl4But7yU5bFkL22TL2/nBWyWho4RlkT9DonluNsLA25YZnxpGXVIGbv12PF7LpDksbs4tqJyJJ+oIec3Sy0d+XWq0iYKSLsrKw98cko8eFT/HqdrAYZBD8pkYXddouyVB3U55BXyjOzNLEaGVh7l3hOHpa8evrJ4zSXsMnexq1R+rvZtwcirmFCU1NOiZcG9ilx1jYmLLgoZEc25RBQKRLv6hi3aKziugdcR5iw7QbOz4p7g9MzdVGbfN6S0DkOcHvACo0NRC4+9tiZqE2OmbMuGmoEnQ5W9rg3PUkmB6jUkn9ohXbhXLytGbWbWFG14VO8NBvqduTQ1FmFSNmDMHetWfPV9QmKhY+EoUsyxc94ekV4sjwacZZNSHj3Xu13o/Q1sDaYGFsKKCVZfmswXUxwPBz7yhJ0v2SJB27ZCMbIPwjXFj2t3FGvR47o6+yPIrpNw694FXf8wkZ684tL0w0qkJtbmXCxC4E26Ou9DVKg2tvJXQgcTXYz+YZ5GB0m2FbmGk3DO10xa+rnIfY4Dfcudf+b/sbSSXhE+bEDX8fx6grfDH8TpuytOdX9SxtzAgc5dqngW9Pam9iqaOUeBMzFUMndD9d3jPYXmnZ0x0XkpovSRJeIQ7K5anLQggZ546Lty1XPzQSlYn+/ZqaqxnfxQCyvzCzMGH6zaHMuWNYt6rfewY7sPCRSEZM7356vNB/eYc5Kit9lramuPfx9qDBRqVW4WewtWDsfH9GzOjb6smDmZWdGeOvCWDB8pG9WjG8p84JJl0frBQQlFSSWPXtA1J7DZcHAkmSpgE/y7LsYXDdfcCtsizPbO8xy5cvlwE+/PDDSzLGgULTqCVmRxaF6e33RgP9nqDIOT5tii30FlmWST1ZRMapEsKnenW66mtI26QjensmWo3MmHl+XUrv6680TVqOb85ArVYx+ipfo70k1WX1nNiSiYu3DcOmeA6I9Mv+Lj+tgsQDeXiHOhIydmDta+5P4nZl63uVNn+1qE0khk32uuDJqIL0SuJ2Zp+39y6ApNIX9AmdcGGVciuL64jZnoVHkH2bz0BucjlnDuUTNtGjTTs2QRhocpPLOXM4n7CJ+kq5Qs+qrWzkxOYMnLysxXe00EZ5QS0xO7Lwj3Dp97UjBrh2//AGcvA7Ctgvy7KVwXWPAzNlWV7Y3mNagl9BEARBEARBEARh8Prwww/bBMADd1kMzgImkiQZbnaMBESxK0EQBEEQBEEQBMHIgF35BZAk6Qf0yXX3oq/2vBGYLKo99y5Jko7Jsjy2r8chCJ0Rn1NhIBCfU2EgEJ9Tob8Tn1Ghqwbyyi/AcsASKARWAQ+JwFcQBEEQBEEQBEE414BtdQQgy3IpsLivxyEIgiAIgiAIgiD0bwN95VfoG5/29QAEoQvE51QYCMTnVBgIxOdU6O/EZ1TokgG951cQBEEQBEEQBEEQukKs/AqCIAiCIAiCIAiDngh+BUEQBEEQBEEQhEFPBL+CIAiCIAiCIAjCoCeCX0EQBEEQBEEQBGHQE8GvIAiCIAiCIAiCMOiJ4FcQBEEQBEEQBEEY9C6r4Hf58uXy8uXLRW8nQRAEQRAEQRCEy4xJXw+gj4gAWBAEQRAEQRAEYXCS2rvycg1+BWFAqK0opyA1Wf8vLZm6qkomXn8T/pGj+3pogiAIgiAIgjCgiOBXEPqRyuJCEvbsJD8liYK0ZKpLitvc57fXX+KWl97A1de/R15Tp9VSkpNFYVoKWk0TvsMjcfDw7JHnFgRBEARBEIT+QgS/gtAPaBobObZ+DYfX/oymseE8921g/Zsvc+vLb2NuZdXl15BlmZwzCWQnxFNdVkpNWSlVJcWUZGWgaWo0uq/TEB/8I0cjyzpqysqoKS/F0taOgKixBI4eh42TMwBajYbGulosbe26/6YFQRA6kJ+SRHl+LiETJqM2Me3r4QiCIAiDhAh+BaEPybJM6okj7Pr6M8oL8trcbmJqhqt/AO6BwTh6erN31VdoGhooy8tly0dvs3DF32hqqCczPpbGulq8hw3HzsXN6DlqKytI3LuT2G2bKc3N7tK4SnOyKM3JanN98tFDADh4eNJYV0dtZQXIMq5+Acz/8+O49NBqtCAIlydZljm2fg17vv8SgAnX3cDUm+7o41EJgiAIg4Uky5dP7aeWSs8ffvih0fVNTU1kZ2dTX1/fJ+O6EBYWFnh7e2NqKmbEByJZlkmLPsbB1avITz5rdJurXwCjr74W96AQnIf4oFKrldsS9+1i43uvK5fdA4MpzkxHq9EYPd43IoqaslIKUpMoy8s973hsnV1xDwxCp9WSGRfTZiW4K0zNLbjqob8QOmlqtx8rCIIg63Ts+uYzTmxap1xn7eDIAx99jaS6rJpTCIIgCBdPFLzqSHZ2Nra2tvj7+yNJ7f6e+hVZlikpKSE7O5uAgIC+Hs5lR9bpAC74ZCw/+Szbv/iI/JQko+vNra2ZcuPtRM692ijgNTRs6kxyz54messGAApSk9vcpygjjaKMtHYfb2phSeikqbj6+mPt6IS1gyNOXt5Y2Tso92lZSc5POYuZpRU2Do5Y2TtSnJVB6onDZCeeQqfV6u8sSUiShKzT0dRQz4a3XyX3zLX4RY7CxtEZGydnrOzsL+C3JAjC5UTT1MSmD97k7MG9RtfXlJeRl3wGr6HD+mhkgiAIwmAigl+gvr5+wAS+AJIk4ezsTFFRUV8P5bLSUFvLwdUriduxBScvbxY/+TzWDo5dfrxOq+Xwrz9x8JdVSgANoDY1JWL2VUxacpNRENqRmXfcQ0FqEnlJZ5TrXH39sbR3ICcx3mgVGPRBukdQCCNmXUHY5OmYWXa+T9jU3IKgMeMJGjPe6Hq/kVGMWbCIhtoaKgoLsLS1w8regbK8HH57/d+U5+vTtk9sWte6ciNJhE+dyRUPPIqJyFIQBKEdsk7Hpvde5+zh/cp1ZpaWNNbVAfrtFiL4FQRBEHqCCH6bDZTAt8VAG+9AJssyp/ftYvf3X1JTVgroi7FseOc/LHv2pQ5XaQ2V5eey6b03yEtuDVjVpqaMnDOPcYuWYOvk0uXxqE1MWfLMv4jeuhFzK2sCR43FzlW/z7exrpaM2GjyU5OwdXLBPTAYFz9/TM3Mu/muO2ZuZY2bf6By2cXHj1tffouN771O2sljxneWZRL27qS+ppqFK54RAbAgCG0cWL3SKPCNuuoa/EaO4rf/vghA8tGDTLvlLvG9JwiCIFw0EfwKQie0Gg3r33qVlGOH2tyWnRDPvh+/Zfotd3X6HLWVFfzw/JPUVpQr13mFhnP1wytwcPe4oHGZW1kzYfGyNtebWVoRMmEyIRMmX9DzXigLaxuue/J5Tu3eTlZCHNVlpVSXFCsFtlJPHGX9my+LAFgQBCOJ+3Zx6JcflMuj5i1k1l33o21qwtTcgqaGesrycinNycLZ27cPRyoIgiAMBqKCRD9QXl7epghXi7vuuovVq1df4hEJoF/x3fnVJ0aBr7WjE6GTpyuXj/62mqSjBzt9nj3ffaEEviq1CVNvvpMb//HKBQe+/ZWkUjFi1hVc/fAKlj37b+568yMmXHeDcnvqiaOse+MlGmpr+3CUgiD0FzlnEtny8TvKZf/I0cy8414kScLEzIyAqDHKbUlHOj/OCoIgCEJXiOC3H+gs+BX6zsnNG4j5Y5NyeeTcedz95scseOSvBIwaq1y/+YO3yDmT2O5zZMbHcGr3duXywhV/Y8LiZahU50+VHugkSWLKjbcz4boblevSTh7jmycfITsxvg9HJgjCpdJYX0da9HEyYqMpzsqgtrKCpMMH+OXl5/nhhSfRNjUB+t7i1/zlKaNtJMHjJyk/t7RZEwRBEISLIdKez/HGjdf02nM//uOGdq9/+umnSUlJISoqiiuuuIK6ujp27NhBQEAAl1Mrqv4kLfo4u77+n3I5bMoM5t77sLLn7Oo/P853T/+FyqICGutq+eH5J/CPHM2kpTcrhVk0jY1s++wD5TmGTpxK8NgJl/aN9DF9AHwbkgSH1vwIQGVRAT/+82+Mv3YJk2+4FbWJSIMWeldTYwO5ZxLxCgnD1MKir4dzWWisq+Xk5g0c2/Ar9dVVnd7XwsaW6558HnMra6PrA0aNRaVWo9NqKUhNorK4CDsX194ctiAIgjDIieC3H3j11VeJj48nOjqaNWvW8NFHHxEXF0dBQQHh4eH86U9/6ushXlbK8nPZ8PZ/kGV9RWbP4FCufPBRo2Irlja2XLvib/z4j6dpatD3h06POUF6zAncA4MJHD2e2ooypceuuZU1s+66/9K/mX6gZQXYyduX7Z9/SENNDcgyR35bTX5qMoufeBZTcxGQCL1D09jIjy88TUFqEk5e3tz04n+xtLHt62ENanE7trLn+y/PG/QiSfiPHMX02/6Eg4dnm5strG3wGT6SjNiTAKQcO8SoeQt7Y8iCIAjCZUKkPfcze/bs4eabb0atVuPl5cXs2bP7ekiXnQM/fU9jnX5fqq2zK4ueeLbdasnugcHc/p93GDZ1JpLU+qdUkJrMwdUrjVKmp91yJzaOTr0/+H5s2JQZ3PHa+/iOiFSuy4yLZu1rLyoTCILQ0/au/IqCVH1P7dLcbNa/+UqbdmBCz8k5ncDWT941CnztXN3wDh+Bo+cQTC0ssXN1Z+L1N3Lvu5+x5Jl/4err3+HzBY8Tqc+CIAhCzxErv+foKDX5UhLtHPpOWX4uZw7sVS5f85cnO+3l6+g5hPmP/JWJS27i0JofOXNgDzqt1ug+nkPDGDlnXq+NeSCxc3Fl6d9f5OAvqzi4ehWg3xe99rV/sfjJ58UKsNCj0k4ea+053SzrVCw7vviYuffptzFUFhdRWVSAk5d3l/psC52L3/WH8rOdqzsTl9xI+LTZqE0u7HQjaOx4tn+ur4mRGR/DsfVrGLvw+h4ZqyAIgnD5EcFvP2Bra0tVlX6WfPr06XzyySfccccdFBYWsnPnTm655ZY+HuHl4+hvq5V0Z7+Ro5T9u+fj5OXN/D8/zuy7HyA95gSpJ46SEXsSC2sb5j30GJJKJFm0kFQqJi+7FZXahP0/fgtAZnwsP7zwFGOvuY6Q8ZMxMTPr41EKA11NeRmbP3pbuWzj7EJ1STEAsds3U19bQ1lOFkWZ6Ub3cQ8IZviM2YSMv7TtwgaDpsYGzh5q7dd7zf89iWdI6EU9p62TC4Gjx5F64igAu7/7guqyUmbc9idxXBUEQRC6TQS//YCzszNTpkxhxIgRXH311YSEhBAREcHQoUOZMWNGXw/vslFVUsyp3TuUyxMNqhR3lYW1DWGTpxNm0A5JaN/E629EkiT2/fANAIVpKWx873UsbGwZPmMO4xcvw8rOvo9HKQxEsiyz5aO3lRZj1g6O3P7K2+z8+n+c3r8bgLMH97Z5XHVJMdUlxaQcP8xtL7+Fe2DwpRx2v6bTaoneuhFZp2XUvIVGVZlbpB4/qmwZcfDwxCN4aI+89ryHV/Dbf18k53QCAMd/X0tNeRnzlj92wSvKgiAIwuVJfGv0EytXruzrIVz2jm34FZ1WvxfQKzScIcOG9/GIBr8J192A2tSUvSu/UtLF66urOP77WuJ3/cGUG28n8oqrL4vWUELPyYg5QVr0ceXyvIdXYGXvwFUP/h8VBfnkJZ9RblObmODk5U1Zfh6axgb9lbLMkbU/s3DF37r0eg21NWTGxVCQlkxBajKluTn4hEcw997lgyaL4fSBPez86hMAKosK2y3gl7hvp/LzsKmzemwLj6WNLUv+/iIb332d5Oa+6qf378bF158Ji5f1yGsIgiAIXadpakLb1IS5lVVfD6XbRPArCEBtZQWx2zYrlydct0zsvb5Exl5zHWFTZnBq1zZit2+hsqgAgIaaGnZ88TFxO7Zyxb0PX3T6pHD5yE06rfw8fMZc/EeOAsDEzIzFTz3PgZ9XotNqCIgcg9/IKMwsrdBptWSeiuWXl54D4OyRA5RkZ+Hs7dPpa9VWVvDtU49SXVpidP2p3QXUVpRx7eN/HxQBsGFv7hOb1hEyfjLe4SOU6+qqKkk72TrhMGzazB59fVMzcxaueJrtn3+kHKuPrltN5NyrsbCx6dHXEgRBuNzUVVdxaucfVBYXKddJKhVW9g7YODphZe9ARWEBBanJFKQlU5KVwaSltzDx+u5nSfY1EfwKAnBi42/Kqo+rfyABUWP7eESXFxtHJyZcdwPjFy0l5fgRdn/7OeUFeQAUpaey6rknmHD9DUy8/qZupzlqNU2U5+fj6OUlVpANVBYXEb/zD1KOHUZlosY9IAi3gGA8gkJw9vYd0OmkJVmZys/e52RwWNnZM/eeh9o8RqVW4z9yVOv+Ulnm6LrVzFv+WKevtfubz9oEvi3Soo/z2xsvsWgQBMDFWRlGlzd//DZ3vva+0jf57KF9SuaMZ0gojh5ePT4GlUrN7LsfJOtULGV5uTTU1HB03Wqm3XJXj7+WIAjC5aCuqpLjv//Gyc3raKyr69ZjC1KTe2lUvWvgnt30MFmWB9RKnyzLfT2EQSP3bCJH161RLk9YfMOA+iwMJpJKRfC4ifhHjubY+jUcXvszmsYGZFnHoV9+IO3kca7+8wqch3S+Ggf6lJz4HVs5/NvPVJcU4+Tlzew/PYhfRFTvv5F+qr6mmvTo4yTu20XayeNKcTeA/OSzys9qU1Ncff1xDwwmZMIUfEdEDqi/CcNAzcXHr1uPHb/4BqW4UsLenUxaegv2bu7t3jcjNpqEva2pvlFXLWBIaDiFGWkc/W01AOnRx1n73xdZ/MRzAzYAlmWZknOC34qCfPas/Io5f3oQgIS9u5Tbhk2b1WtjUZuYMPmG2/j9ndcAOLFpPaOuvvaybyUnCMLgVJ6fR/bpU8qKq+Fkq9rEhOBxk5i89BZlIrKFLMtUlRRRkJpMSXYW7oHBBESNMbpP4t6dbPv8w24HvS0aaqov6HF9TQS/gIWFBSUlJTg7Ow+IEzxZlikpKcHCQrSFuVi1lRWsf+tVZcXCIyiEkAmTzvMoobeZmJkxcclNDJs2k80fvq2kXBakJvH1Xx8maMwERs6dh9/IqDaruTqdlrjtWzj0609KdV/Q93hd/e9nGTpxKjPvuBdbZ5dL+p56W2NdLUUZ6dSUl1JdVkptRQWyTr+PWpZl8pPPkn36FLJOd55nAm1TE/kpSeSnJBHzxya8QsOZtPRm/CKi+v0xUtPURFl+rnLZ6Txpy+caEjoMn/AIshLikHU6jq5f0+5KcVNjA9s+/0C5HDppGnP+pL9f2JQZmJiaKu28MmJPsu+Hr5l5x30X8pb6XFVxUevJkSRB8+Rr9JYNWNs7YO3oRO4ZfTEqlVpN6KRpvTqe0IlTOfrbLxSmp6BpbODQLz8w997lvfqagiAIl9qJTevY9c1nnX5vH1u/hpRjh7n6zyvwCBpK7plE4nZsIfXkMeoqK4zuu+D/nlQKsuanJLH5o7eN2nM6DfFhxMy5qE1NAdBqNNSUl1FTVkptRRmWdg64BwbjHhCMW0AgFtYDc8uJCH4Bb29vsrOzKSoqOv+d+wkLCwu8vb37ehgDmk6n5fd3XlNm0SysbbjmL0+L1Nh+xN7Ng2XPv8TxDWvZ98O36LQaZJ2O5KMHST56EDtXN8YsWEzEnKswNTOnsqiQTR++SXZCfIfPefbQPjLiTnLzv/6Ls7fvJXw3vUOfsrSWk5vXd3v21ndEJBFzrsLCypqCtBRlZrmyqNDofrlnEvjlpefwGjpMHwSPHNWjQXB1aQkpx4/g5h940Xu7y3KzlRMFezd3zCwsu/0c46+7gayEOADid25l4vU3tllZPLzmJ8rz9an55lbWbQpATV52K4ASAJ/YtJ4Rs67s9kp0f2C4ku4dNhwzS0tldXz/T98Z3dc/cnSvV2mXVCqm3nwHa155AYC4HVsYe811OHh49urrCoIgXIiizHSOrvuF4ow0LO3ssXZ0wtbJmfAZczrMZMuMj2HX158ZZWh1pCwvh1XPPYGDuwdlebkd3m/rx+/i6huArYsLG9/7rxL4Orh7MuWm2xk6ccplcQ4sgl/A1NSUgICAvh5GvyfLMgd++o7s06cYffW1A6IPZklOFslHDqLVNLVzWzaZ8TH6C5LE/Ef+2mF6o9B3VCo1465dgt/IUez8+lOjwLayqJCdX33Kkd9WEzZ5OnE7tiqtVgCs7B0Yv2gpQWMncuDn70lsTlFtqKlh0wdvccu/X2+3ZUtXNdXXc2D1SrJOxWFhY4ONoxPWjk54BA/FLyLqggKvrtI0NnJozQ+c2LSepvquB70eQSEEjh5P2NQZRvsy/Q3SoWorKyhMSyHpyAHid25TMiNyzybyy8vP4xkSyuSlt+AXOfqiguCq0mKO/vYLsds3o21qQpJULH32RXxHRF7wcxoGas4XGGj6RUThERRCfkoS2qYmvv/7Cmbefg9DJ06lqb6OxH27OLruF+X+0265C2sHxzbPM2npLWQnniLrVCyyTseOLz9h2XMvIUkSmsZGzhzcS0VhvnJ/Cxs7hs+Y0++qZxqlkfv6MWHxDXz9xJ+pr65qc9/eTHk25B85Gu/wEWQnxKPTatn93edc+/jf+31mgiAIlwdZlilMT+Xwrz+SdPhAu/c5vvE3lj7zolHxQNB/N2545zUl8HXx8WPopKm4Bwbj5OmtnLdkxEez6+v/0VhXh6zTtQl8za2scQsIorwgj6riIpoa6ln35su4BwQp9zWztGTJ31/Ewd2jp38F/ZZ0Oe0dXb58uQzw4Ycf9vVQBqS06OPKTDvA8BlzmHXXA/3uRK1FbUU5Xz6+nPqqyvPed+KSm5lyw62XYFTCxSrJySJu+xZO7dnR4f+tJKmYcN0yxi9ehql56/aAzPgY1rzyAlqNPpibetMdTLjuBgCSjx7i2IY1WNjY4R4YhHtAMO6Bwe0GNQBl+bmse/2lNoWAWqhNTfEZPhLP4FBUKhUAKhMTvEKH4RUSdlFBtyzLrH/zFZKOGH+h2rt74OLj11yZ0dGoaJW1oxP+kaO7vTeysriQI2tXE7djqxIEtxh99bVtVjw1jY1oGhs7rcDbUFvDwdUrid66EW2T8cSUjaMTd/z3fSxt7ZTraisrsLS161Jgs++Hbzj8608AjF+09IKLIaWePMqvr/7T6Dq3gCDKcnNoaqhXrvMaOoyb/vkfpOb/43MVZ6bzzVOPKqvR1/zlaTxDQln3xssUpCa1uf/QCVO63GLpUtn43usk7tsFwNx7lxN5xXxKc3M4e2gf1aUlVJeVUldZwZCwcKbdfGeHv4uelns2kVXPPaFcnnLDbUxcctMleW1BEIRzlefnEbdjC/mpyRSmpbQ7QXguM0srbvzHq7j5BwL6Ip0//vNv5J3Vdy2wsnfg9lffwcbJud3HVxTms+mDN5U+6KbmFoRNnUHE7CvxCAxBUqkoykhj5bN/bW3nZ+Dqh1cQPn32hb7l/q7dk4Y+DX4lSTIHPgTmAk5AMvCMLMubmm+/Afgn4A1kNd+2tvk2CXgVuLf56T4HnpI7eUMi+L04v7z8POkxJ4yus3N148oHHu2XRYS2fPwu8Tu3nvd+fiNHcf3f/nFZpHoMJk2NDcRt38KR31ZTU1aqXO/g7snVf34cr6Fh7T7u8Nqf2bfqawBUahNufflNzhzcy5G1P7d7fxtHJ9wCg3EPCMLOxQ1rRycaaqrZ9vmHNNTUXNDYLWxsCRg1Fq+QMKwdHbFxdMbO1a3DQPtcsds388en7yuXnb19mbjkpl5NWaosLuLIb6uJ37FFmTwAuO6pFwgcPQ6A0twcVr/0LFXFRbj4+hM0ZjwBo8bh6uuHmaUVsiyTsGcHe77/ktqKcqPnlySVMssdPG4i1z7+d6pKitjy0TtkxscQOHoci5947ryB1dr/vkjKscMAzP/z4xe1Epm4fze7vv5fm7G2sLJ34IbnXzlvO6QdX33CyU3rAf0khE6rbbMXy9Bdb3x03ue8lL558hGKMtIAuPGf/8E7rP/0QN/2+UfEbP1dubzwsacZOnFqH45IGCgaamsxNTe/qIlIQWiRczqBX155ocNMrKCxExk17xp0Wi3VpSXs/+k75dzFyt6Bpc/+m4qCfP1+3eZtJZJKxbLnXsInPKLT19bptJw9uA+dVkvwuImYWbZdlDq1ezubP3zL6LqwKTOY/8hfB3PGTL8Mfq2BJ4CvgExgPrAKiACagDRgEbC5+bafAX9ZlgslSXoAWAHMAWTgD+BdWZY/7uj1RPB74UqyM/nq8Y4LivgMH8mkpTef9w/0UslPPsv3zz6uFGYZNW9huytRFja2RMy+0mh1UBhYNI2NxG7fwpmDe/EMHsrkG27tNN1Yp9Wy6vknlOrGalPTNquP3aE2NWXG7fdg7+pOdVkJZXm5pMecoDgzvdvP5TN8JCPnXEXw+MmYNBecOFdJThbfPf0XZQZ35Jx5zL13+SVbbasqKWbrp++RHq3v6Wrt6MRdr+uPqSuffZyyvJx2H2dqYYmZpaXRRAWAZ3Aok5bdgk6rZe1r/1KuHz5jLklHDhilsV/10F8YMXNup+P7/NH7lDZZt//nXWU2/ULV11Rz8OeVnNyyQVm9dfb2ZeScqxg2fTaWNrZdeo4v/vJAm4BXpVYTeeV8LKxtSDt5jPwU/UrwiFlXctWDj17UuHuKTqvl3TuWKBMeD3/xQ78qcqLVaFjzygvKFhYTM3Nu/MereASF9PHIhP6mPD+Ps4f3U5CSREFaMhWFBW1W3QThQmSfPsWaV/7RJvA1t7bGb+RoJixe1uYzVpSZzo//eKrTSfTpt97NuGuX9Ng4//j0fWK36/uk27m6c8dr72JuZd1jz98P9b/gtz2SJMWiX+3NBtbLsuxmcFsRcK0sywclSToAfCXL8qfNt90D3CfL8sSOnnsgBL/9teXSH/97n9ht+j+Y4HGTCJ08jW2ffdDmj9YnPIIZd9yLe0BQXwwTAFmnY+Vzf1WCm8Ax47nuyef7bDxC/1OSncW3Tz/aJuj1jxxN6OTpFDSnLBVmpKJpaJsm1MLG2YVFK57BI3hom9sqCgtIiz5u1JagpryM9OhjVJ8TAJ7LwtaO0IlTCBwzHt/hkUqLHE1TE6ue/SuF6SmAPgi79ZW3MDUz7/J77wm1lRV8/deHlRXRYVNnUlNe1rqHvgtsnJyZece9DJ04VTnmbf/iY6K3bOjwMVb2Dvzp7U86/LJuqq/n3buWgSwjSSoe/WZ1j7UXKs7KIO3kMbyGDsMrdFi3j9NxO7ey9eN3lctW9g4s/MvTyl6v7NOn+PGFpwB9+4p73/+iX7TvKcnO4qvH9VWsbZxdeODDr/p2QO2or642mnixcXTi9v+8i5W9Q98OTLgkCtNTKcvLwS0gqE1/aa2mieSjh4ndvpnMuOh2Hx8QNYbr//bPdm8ThPPJPn2KNS+/oGyHsbJ3YOad9+EZHIq9m3un3xXZp0/xy7+fQ9PU2Oa28GmzmPfwih6NCTSNjez8+lPK83OZdef9uPj699hz91P9P/iVJMkdyACigCRgB/AG8DuwEHgfCJVluUaSpArgSlmWDzc/diywU5blNtPwkiTdD9z/0EMPjYH+G/yW5GSx6f03mP/IX3Hy6nol5/yUJOoqK/CPGtPtP5K6qkrSoo+THnMClUrF9Nv+1KZSZ11VJZ8uv1tZabrxhVfxDh9BVWkx+3/8joQ9O4zKsEuSipFXXM3UG2/vdN9fbzE8yVSbmnLX6x+KKqBCG0fX/cKe779ULk+47gYm33CrUdqwTqelNCe7uU9eJtVlpdSUlVBbWYlHUAjTbr6z2yfYsixTmJZCeswJKooKqCkrpbq0lKKMtHarOpqYm+Pq64+kUtNQU01Jdiag/2zf+tKbuPr1TbG+pCMHWPfGy+3edvXDKzC1tCT1+BGyE+KpLi1RvtxVahPGXLOYidff2GaFvqmxgZXPrDDaR23v7oG2sVGZMBizYFGHLYPyU5L4/pnHAHD08uZPb3WYCHTJyToda179B+kxJ/AMCWXhY38zarclyzKrnvsreUlnABi/eBnTbr6zr4arOHNwHxvefhXQF0Vb0k+DhNLcHFY+u0KZkA0YNZbrnnqhX04mCxevsb6O0/v3ELd9s5IxAa0V7HVaLSnHj5Aefdwoe6Qjd7/1cbfOuwQB9FWWv33q/4wC3xuef7lbnSRSjh9mwzuvoWlowMXHj8DR4wgcMwGvoWHi+HXx+nfwK0mSKbAJSJFl+YHm6+4B3gEsgEZgmSzLvzffpgWGy7J8uvlyCHAWUHW077c/r/xWl5aw6vknqCwqxMLGluueeh6vocPO+7ikwwdY/9aryLKOWXfex+j5izq8b2luNmkn9atO1aUlVBTmk5+cZHTC7TdyFEue+ZfRH5zhHkk3/yBue/Vto9vLC/I5/OtPJOzZbtQvzNLWjqGTpinFg1x8/Hpkb011aQnHN/5GRWE+o666Bp/hI5XbKgoL+P7vK5T0wgnX3cjUm26/6NcUBh+dTsvOrz4lL+ksE65b1ufVy6tKi4nf+QdxO7ZSVXz+tmuz7rqf0VdfewlG1rHf3/0vp/fvNrquvaJDsizTUFNDTXkZNk7OnRbJK85MZ/XLz1NTVkrE7CuZeed9pB4/wu/v/hfQ74G647X32m0ZZLinKWT8ZK59/JmLfYs9SqfVUllc1OFqQNLhA6x7Uz+hYG5tzf0ffNnu3q1Laf9P33PoF327prELr2fGbX/q0/F0Jj36OL8YFGWcddcDjL56YR+OSOgNRRlp/PLy89SUl3XrcZKkImDUGILGTMA9MJgDP3+v7K2MvHJBu/28L1eyLCPrdGI/9Hns/u4Ljq1fA3S9BkR76qoq0Wo0/SLbZ5BpN/jtF62OJElSAd+iD3D/3HzdXOA1YCZwAhgDrJMk6WpZlqOBasDO4GnsgOrOCl71Z2V5OdQ2B2z11VX8/OKzXPOXJwkaM6HDx1QWF7H1k3eV4PXYhrVEzbum3YI3lcWFfP/MY+ftA5oRe5LT+3czbOpMQL+fyjANcfT8a9uctDm4e3DVg48y7tol7PzqE6UoVl1VpVEhEhcfPxY/+fwFtxOqLi3hyLrVxG7brKSrJh0+QOjk6Uy98XYS9+3iyNqflRUmW2dXJixedkGvJQx+KpWaOX/qPyc7tk4uTFpyMxOuu4Gc0wmkHD9C6omjlOVmt7lvyPjJjJrX9yf1s+9+gKxTscpJaNiUGUy4/sY295MkCQsbmy5lgrj4+vOntz5Gq9Uq+2lDJ08nZtsmshPikXU6dn71CUuffanNsagn2hz1JpVa3Wk7iaBxE3Dw8KQ8P4+GmhridvzBmAUdT2heCoZ71/t7j2L/qDGMueY6jm/4FYA933+Bz/AIXAd/at9lo6m+ng1v/8co8FWbmuIWEER+0tl2s2fsXN0YPmMOI2ZdgZ2LspOOMQsWK8Hvqd3b+ixbrb+pq65i3RsvkZ14Cr+IKEbOuYqgsRNQm7Rfh+JylmFQBPaK+/58wYUKDbsbCL2vz4Pf5qrNnwPuwHxZlls24UUBe2RZPtZ8+agkSYfRV4aOBk4BkcCR5tsjm68bkHyGj+SG51/m11f/SV1VJZrGBn7770tMvfmO1oqwTs5KYSadTsumD96gvqZaeY6qkiIyY6ON+nW2OPDzyvYDX0nCMyQUU3MLZT/Mrm8+wz9qDJY2tpzctE7Zs2hl70Do5OkdvgcnryFc/7d/knz0IDu//l+b1avirAzWv/UKN/3ztW7tw5NlmZitG9n97eft7os4c2APZw7sOedtqZhzz4OYWohCVsLAolKp8QmPwCc8gpm330N5QT7VZa37hk3NzHH1D+gX6VCWtnYsXPEMO774GBdfP+be93CPjOvc1U5Jkph994N829wyKDM+lpOb17dZ+S4x7EfbzwO19qhUasZecx3bPtNnJ+3+9nOObViDtYMTLj6+jLr62kteT6Ek27DHr/8lfe0LMfWmO8iMj6EoPRVtUxO/v/Mat778pihqOEjs+uYzSpsnBE3NLZhy4+2ET5+Fpa0dVSX67JnkY4cwNTcnIGosgWPG4+Lj1+5xyWf4SFx8/SnOTEfT0EDcji09WlxoIKqrquTnfz9LUXoqoF8QyYg92Xz+N42g0RPwDh8uAmH0NTyKmicHVWoTfCMuvD+9cGn1edqzJEkfow9058qyXG1w/Qzgl+broyVJGgVsA26WZXmrJEkPAv+HPhhuqfb83kCv9lyWl8MvLz9PRWFBm9sklYqAUWMZOWcehekpHPjp+zb3GTppGgv/8pTRdSXZWXz914eVGdFxi5biPMQHawdH3AKCsLKzp7Guli9XPKQEusNnzMXE3Nxo5XbS0luYvOyWLr0PTWMjWQlxFKQmU5CaTOqJI0pK9Mi587jivj93+Xm2ff4hp3ZtM7reIygEO1d3zh7a1+Yxbv5BzLnnwS6ljQuCMHAYtgwCmP/oEwybMkO5/Onyu6kq0U+63fXGh93ad9VfNDU28L+H/9RhK6SgsROYtORm3AODL8lY3r1jqVJA7JFvfr7kxdUuxLkV0W1d9FlAw2de0WEVdaF3yLJM8rFDJB3aj1doOCPnXnXB7djOrTNw1YP/x4hZV1zU+AxrhNi6uHLvu5+hUqv7bfHR3nRu4NsRM0tLgsdNYsbt97SpEXM5Sdi7k03vvwGAd/gIbnzh1T4ekdCO/pf2LEmSH/AA0ADkGxxoHpBl+XtJkv4BrG4uhFUEvCzLckvj1k+AQCCu+fJnzdcNaI6eQ7j5xddZ8+o/KExLMbpN1ulIPX6E1ONHjK4PmzJD2XeXcvQgdVWVRikU+3/8Vgl8/UaOYvotd7V5XTNLK2b/6UHWvf4SoE8BMuTq68+YBYu7/D5MzMwIiBpDQPMq9IlN69n5lf6/J3bbZryGDmP4jDmdPkdVSTHr3njJqJiFi68/0265k4CosUiSRNapWLZ/8TEl2ZlYWNsw5aY7LurLVRCE/mvazXeSn5JE3tnTAGz+4E0srW3wjxpDQ22tEviq1CY4nFP1daAwNTPnivseZseXnxhVCm+RcuwwKccOM2bBImbcfm+vnqCXZmcp7eIcPDwHROAL4DzEh1l33af0wq4qLmLbZx9y+NefGTppKu6BwbgHBOPo4XnJWoRdbmSdjuRjhzi4epXSIzpx3y7OHNzD1ctXYOfqdp5nMFZVUszWT95TLg+dNI3h52l71hXDpsxk7/dfUVdVSVVxEWv/+yLVZaWUZmfi6h/IdU8+P+irhjfU1pAec4JDa35s3eYgScy8/V4aaquJ27HV6FjUWFdHwp4dlOXncuMLr1y2q8AZsSeVn/0iRvXhSITu6vOV30tpIKz8tmisq+Xk5g0UpCZTXVZCTXkZlUWFbe7nNXQYN/7jVaO+pYaFr/KTz/L931co97/tlbc7XTH47fV/k3z0kNF1QydNY96D/3dRKcSyLPP7u/9V0pNNzMy55d+vd1iptjA9lTWvvGC0ryd8+mzm3vdwmxMwnVZLUUYaDh5enRbSEQRh4KurruLHF55Sql6bmJuz+InnMDU3Z9VzTwD6lOc7X/+gL4fZIzSNjdSUl1FRWEDM1t85e3i/0e0zbr+Hsddc12uvb1RAbMJkrl3RvwqIdUaWZWL+2MTB1SuVllznsnFyZtzC64mYO2/ABPYDgaaxkV//888OW5+ZWVox8857GTZlZpe2QOUlnWHj+69Tnq/v323r4sod/3mvx/bn7v/xWw6t+bHd27xCw1n23EuDMmMgOzGeg6tXkp14yqhYKZKkX1VvnlzQabVknool9fgRUo4fobKoNTNx1NULmX3XA5d66H1OlmU+eehOpW/9rS+92W7LQ6HP9e9qz5fCQAp+21OWn0vcjq2c2rWN2opyrOwduOXfb2Dv5k7sts388T/9LLeLrz93vPYekiTx87+fVfbyDp04lYWPPd3pa1SVFPPV4w/RWFeHJKmYdsudjF14fY+sLjTW1/H9MysozckCwMnLm9teebtNUJ0ZH8Nvr/9b2aOsUquZcfu9jJp3zWWXhiQIQltVJcWsev4Jo7oCzt6+SkAcOnk61/zfk301vF5TnJnO7u++UIoKIkksfuI5gsaM75XXM6xkOmnpzUxedmuvvE5vaqqvJ+aPjRxdv6bDINjawZFx1y4l6qoFqE36vBTKgGfYIQL0E1QBkWNIPnrIqCCVqbkFfiOjCBw9Hq/QYTh5DjFaiddqNBz+9UcOrflRaacoSSpueOFlvIeN6LHxVpeV8vmj9ylp8ucKnz6becsfQ5IkGmprKcnOwM7VfUBX5m2oreGzP99jVDcG9Nvrrnrw/zrMzJNlmaPrfmHvyq+U6xb835OEdVIPZjAqzkzn6yf02/csrG146LPvRcZh/ySC34Ee/LbQapooSk/Dzs1d2W/RUFvLxw/ejqZBf/Ce/+gT5J09zcnN+v1xkkrFXW982KU+drlnT5O4bxehk6b26BcM6Pcff//MY0pPtJFz5nHF/a37f0/v382mD95Cp9UAYG5lzbWP/x3fESPbfT5BEC5PpbnZ/PDCU+3ujZ1y4+1MbKfq9GCgaWri5xf/Tu6ZBABMLSy5+cX/9kpF419eeYH06OMALHzsaYZOnNrjr3GpNDXUkx57koKUZArSkslPOtPmxD9i9pVc+cCjfTTCwaG2opzP/+8+ZfI6YvaVTL3pDqzsHcg9e5pN779BeUFeu481tbDEzT8QEzMzqktLqC4toaG2RrndzNKSK+5/pFcCrayEOJIOH8DWxRX3gGDykk6z74dvlNvHLFhEQ20tpw/sQdPQgKRSETh6PCPnXoV/5OgBF/gc/GWVUd0Y98BgAkePI3TydJyHdF6xWJZl1r/5CklHDgD6SYzJy26hrrqKmvIybJ1dCJ82C0fPIb36HvrSsQ2/svvbz4GuLSwJfUYEv4Ml+O3I5g/f4tTu7e3eNmLWlVz1YP/4Uo/f+QdbPn5HuXztimfwHzWGvSu/MipmY+PkzPV/+6doUyEIQruqSorZ9c1nbQrfXfvXvxMyblIfjar31VZW8P0zK1rTDyVJOfm2tLUl6soFjF14fbeq6p+rsriQL//yoFJh/+63PsHJa/CczGoaG4nbuZUja39W9jNKkor7P/wSGyfnPh7dwLXtsw+J+WMjoM/uuvP1D4x6xTbW13Fk7c+cObhXSWPuiiFhw7n64RUX3Cqxu2RZZusn7xK/84/z3tfO1Y3xi5YOmIJq9TXVfPbIPTTU6CcWLqRwWENtDd/97S+d/h/6jhjJ8JlX4DzEBxsnZyzt7AbcJEFHDCcGr7j/z4ycM6+PRyR0QAS/gz34zU6M58d/tJ19cvMPYskz/+w3RRtkWWbDO69x9uBeQJ8yYuXgqKRDgz6F8fq//RM7F9e+GqYgCANERlw0O778hNKcLCysbbjn3c8Gfb/O4sx0Vj3/RIe92x3cPZl19/0Ejhp3Qc+/8b3XSdy3C9BX17/lpTcH5bYTTWOjfiX9bCIA0265i/GLlvbxqAamkuwsvn7iYSVFefGTz3eYki/LMmV5OaQeP0JmfAwFaSntpqWbW1szftEyxi687pIHTlpNE6v//RzZifFG19s4ObdbjM7W2ZXxi5YSMeeqC06fb6itpaIwH1df/14rxnZw9SoO/Kxf9XX09OKuNz4ymqDoqqKMNFY++9cO08XPpV8tH8ecPz2ErbNLt1+vv9A0NvLBPTcr7/ve9z6/ZJMyQreJ4HewB7+yLLPy2cfJTz6LpFIRNGYCI+fOw29kVL+bbauvruabJx9RqrMaChw9jnkPr8DSxrYPRiYIwkCk1WjIPZuIk5c31g6OfT2cSyI95gS/v/c69VWVHd4neNwkrrjv4W5Nfp5bKPHGf7za41tg+pP4XdvY8tHbgH7i9c7XPxiUgX5v+/U//yT1xFFAv+q39NmXuvx7lGWZ6rISitLTQAIbR2esHRyxsrPv04rctZUVrHvjZUpysggaM56Rc+bhGRJKWV4ucTu2cGrXNurO+fsLHDOexX99ttvjbqyvY+XfH6ckO7PXsvXqa6r57M/3KOnkVz+8gvDpsy/4+bIS4ojbsRVTc3NsHJ2xsLUlI/YkqcePGu3vNmRubc2ce5YbtakbSDLjY/j5xb8D+smDP739aR+PSOiECH4He/AL+lnD7MR43AOC+n3qVnZiPD/98xnlAGlibs6sO+4jYs5V4sRDEAShC2SdDp1O2/yzTPzOP9j34zdKSiOAlb0DVz7waJcKY8myzI//eJqc06cAffC86K9/753B9xONdbV89EBrzYxbX34Lj6CQPh7VwJIRF83qfz+rvyBJ3P7qO7j5B/btoC6Bjgqqzbzj3m61hwQ49MsP7P/pO+XyzS/+F6+hw3popHoHfl7JwdUrgYtb9T2fqpJiTu3aRvbpU9SUlVJdXtZmkm7opGlEXTmfIaHhvTKGLo2ztBhNQ0O39ifv+vZzjm/4FYDIKxcw956Hemt4wsXrf31+hZ5nbmXVa5U/e5r3sBHMuech9q78CvegEObeuxzHAdqbUxAEoS9IKhVqgxWmqKsWMHTSVPau/ErZr1hbUc7a1/5F+PTZBI0Zj3tgMFb2DmSdiiP1xBGyEuIxt7QiYNRYzCwtlcBXpVYz/da7+uJtXVJmllYMnTCFhD07AH2LJ8PgV5ZlGuvqqCkvpbaiHMNFA+chPp2uqms1TSTu3UVtZQWjrrrmoloG9leapia2f/Gxcnn4jDmXReALYGphwdiF1xN55Xx2ff0Zsds3A7Dn+6/wDo/APSCoS89TV1XJ0ebK6i32rfqGZc+/fMGLAU2NDdSUlVFdUkxhRioFqckkHT6g3D5xyc29FnTaOrswcclNRtdlnz7F5g/epKJQX6vg7MG9nD24F3NrawKixjJi1hX4joi8ZIsfpw/sYfMHb6LVaHALCGLknHmETZnRYcvMvKQzHFy9krTmvb4A/iNFf9+BSKz8Cn1OlmWx0isIgtDD0qKPs+Wjt436pSskCc7z/T/66muZddf9vTS6/sUwldHCxpYHPv6GuqoKtn/+MZlx0UqHgnNJKhUTr7+Jidff2CaQyIiLZscXH1Oamw3A+EVLmXbLXb36PvqC4WqimaUld7/5cb/PPOsNWk0TK5/9K4VpKUBzO8dX38bU/PwTHoZtxQwteeZf+EeObnO9TqelJCsTe3cPzCwsleuLM9M59OtPpMccN8r+OJej5xDuevPDS74lrqG2ll3f/K/DQmJeoeFMWnozfhFRvXpemLh/N5vee6NNarba1BRzK+t2H3PunnQLWzvue+8zzCzbD5aFfkGkPYvgVxAEQbic1FVV8sf/3jda8ekKc2tr7nnnf1ja2vXSyPoXWafjf4/co/SOHrdoKad2beuwN/C5PINDmffwCiQJClKTOXt4f5vfuZOXN3e/9XEHz9B1OWcSyYqPwcrBAfeAYFx8/VCb9E2V4ZKcLL598hG0Gn17wtl/epBRV13TJ2PpD0pzc/j26UeVFPrAMeMJGjMeawcnnL19cXD3aPOYqtJivnj0fqWyuouPH8VZGQC4BQRx28tvGe0fLsnOZON7b1CYnoLaxASf4SMJiBpDzukEzh7ef94xmppbcO2Kv+EfNaYn3vIFyU6I5/SBPaSeONpu7RffEZFc+/gzHQaiFyNx3y42vf9mh3uSz0uSCJs8nck33CqyFfs/EfyK4FcQBEG43MiyTEZcNJlx0RSk6vvcNtTU4OjlTdCY8QREjaW2spzU40dIO3mMxvp6rv7zil7pp9qf7fvhWw7/+mO7t5mYmmHt6IiVgyNqtX7HWG1FubKq21X3f/QVtk4XVuk2OzGeg6tXkRkfY3S92sQEz6FhRMy6kpCJUzA1M7+g5+8uWZb56V9/IztBXw3ZMziUm158rd8V2LzU4nZuZevH77Z725UPPErE7CuNrvvj0/eVdGn3wGAWPfEsX/zfA0o14Wv+8jShk6Yi63Sc3LyePSu/QtvUdN5xqNRqrB2csHZ0xNFzCO4BwbgHBuEWEGS0WtyXZFmmKCONmD82Er9zGzqtRrlt+Iw5zFv+WI++XuLenWz64C0l8HX29uXax58hPeYkcds3K5MO7ZFUKkInTWPi9Tfh7N15L2Sh3xDBrwh+BUEQhMudLMtoGhra3X/a0qamLyvs9pXS3By+fOwBo+ssbe1Y8H9PtrsXUafTcnTdGg789L3RSbuhYdNmUZaXQ37yWQDmLX+M4TPmdGtcjXW1/P7uf5VKyp0xt7Zm2NRZ+AyPwD0gGDtXNyRJoqm+nuryUswtrXqs7WH8zj/Y8vE7gP7zcvur7+DqF9Ajzz2QndvO0ZCdqzv3vvs/5e+rLC+HL1c8pPzdLfn7i/iPHMWelV9x9LfVgH6l1sreHk1TEzVlpcpzSSqV8jhDQWMnMPG6G3EPDB5Qf8eVxYUcWvMjcdu3KNctfvI5gsZM6PZz1ZSXYWpubpSSnLB3J5sNAl8XHz+WPfeS0d9DXVUlOq223ec0s7AclHv2BzlR8EoQBEEQLneSJHV4EjeQTpZ7mpPXELxCw8k9kwDoV+GuffwZ7Fzc2r2/SqVmwuJl+EeOZvMHb1KclYGlrR3ugcG4BwYTNGYCniGhHF77sxL8ZsZFdzv43fb5R0aBr6RSMXTiVHRaDQWpKVQWFSi3NdTUEL1lA9FbNgBgYW2DTqejsa5WP2a1mvmPPEHopKndGsO5mhob2PP9l8rlsddcJwLfZpIkcfXDKwiIHE1Zfi41ZWUkHdlPY10dlUUFZJ6KxS8iCoDDa39WAlif4SOV68dfu5TYPzbRUFtDU0M9FYXGe85d/QKY/+fHMbO0IvXEUbJOxWJubU3klQu6XGSrv7FzcePK+x+hqb6e0/t3A/DH/z7AKzS8y60vmxob2LvyK05u3oCJiSmRV17NuGuXkhEX3Tbwff5lrOzsjR5/uWzzuNyJ4FcQBEEQBAG48v5H2PP9F7j4+jNxyU1dSiF2Dwjijtfeo666CktbuzYrxH4jItnX/HNGfEy3ijwm7N1J4t6dyuXw6bOZuOQmo72G1aUlnNqzg7gdW6goyDd6fH1NtdFlnVbL1k/ewT0wuN39p111Zv8epb+trbMrk5befMHPNRiZmJoyYtYVymVTCwtlQiJ+5x/4RURRXVpC4t5dyn2m3HCb8rmwsLFhxh33sPWT94wK06nUJoy5ZjGTl92Kial+n3fUVQuIumpB77+pS2T23Q+QGR9DbUU5NWWl7PzqU+b/+fHzPq4gNZmN779BaU4WAJqmRo7//hsxWzeh0TQpv0cXX3/9iu85ga9w+RDBryAIgiAIAuDs7cN1T73Q7cdJKlWHJ9NugUGYW1vTUFNDTVkppTnZXdozWF6Qz/bPW7dpDZ8xl3nL/9LmfjZOzkxYvIzx1y4hMz6W9NgTFKQmU5iWQkOtvuKvSm2CSq1G09hAY10dG9/7Lzf+4z+oTbp/GijLMiebAzmAUVcv7FJF48tZxOwrleA36cgB6qurObF5vZIu7zV0GEPCwo0fM+tKQsZNNprAsLKzG/TVhS1t7bjivj/z2+v/BvT7dEMmTCZk3KQOHxPzx0Z2fPlJuynLLYXEQAS+gp4IfgVBEARBEHqJSqXGd3gkSUf01Z8z4qLPG/zqtFo2vvdfGuvqAHBw92T23Z23nZJUKvxGRuE3MgrQ79+uKi3B1NwcCxtbClKSWPX8E+i0WvKSznBozQ9MueG2br+fvKQzSjsfE1MzoxVOoX1u/oG4BQRRmJaCtqmJmG2biP1jk3L72Guvb/dxFjY2WNjYXKph9hvB4yYybNosJeth8wdv4fRv73b/bgpSk9n++cdKSrOJuTmz7rgPa0dHDq5eRUFqMgCuvv4sFYGvgAh+BUEQBEEQepXviNbgNzM+mtFXL+zwvrIss/u7L8hLOgM079N99K/dXvGTVCrsXFyVyx7BQ5ly4+3sXfkVAIfX/ERteTn11VVUl5ehVquxdnTC2tEJF29fwqbOVFJrDUVv/V35OXTK9C7vx7zcRcy6ku1pHwGw/8dvlb2+jp5eBF9AUafBbtZd95OdEE9VSRGNdbX8+to/ufWlN4325eq0WrZ++p4S+Lr6B7LwsaeVbQGBo8eTGRdDRWE+YVOmD/pVc6FrRPArCIIgCILQi3ybCxkBZJ2KQ6fVolK3bQkkyzJ7vv+SExt/U66bfMNteAaH9sg4xi28nozYE2TGxyLLOqXFTntit29m2bMvGRVHq60oN6pifDn39O2usKkz2P3t52iaGo2qNI9ZcN1lXWiuI5Y2tix+8jlWPf8EmoYGKgryWffmyyz9+4tKX+uTm9cbZSEYBr6gLz7WkgkhCC3EX5sgCIIgCEIvcvT0wtZZvwrbWFdLfkpSm/u0rPgeW79GuS543ETGdZASeyEklYp5D6/AogtVbfOSzrDurVfQalrbOMXt2Kpc9gwOxT0wuMfGNthZWNsQMmGy0XWWdvaEz5jdRyPq/9z8A5n/yF+Vy9kJ8fz+zn8pyc6ksriQ/T9+p9x2biE4QeiIWPkVBEEQBEHoRZIk4TsiklO7twH6lkdeQ8OM7rPn+y85vuFX5XLwuElc85cnUanarhBfDFsnF276x384c3AvZhYWWDs5Y+PgiFarpaaslILUZE5uXg9AevRxtnz0NvMefozKoiJitrXuUx1MFYYvlRGzriRx3y7l8qh513SpovjlLGTcJKbefCf7Vn0N6AuGJR05gIWtHU0N+hZQzt6+jF14XV8OUxhARPArCIIgCILQy/wiDILf+BgmLrlJuS1x3y6jFd+Q8ZNZ8H9PXlA15q5w9vZh8rJb2r1t+Iw5mFtbc+iXH5SxJR09iKahQbmPpa0dQydeXK/gy5FP+AhcfP0pzkzHwtqGqCvFBEJXjF+0lIqCPOJ2bFWuq29utQVwxf2PKKnQgnA+IvgVBEEQBEHoZUb7fhPjOXNwL6GTplFRmM+2z1pbGgWNndirgW9XTF52K7UV5cRu0+8JNgx8ASKvnI+JmVlfDG1Ak1Qqrn/6H5zevxv/qDFGxZuEjkmSxBX3P8LQiVOJ3b6ZlGOHlbZGkVfMZ0josD4eoTCQiOBXEARBEAShl1k7OOIfNYb06OMgy2x87w3MLa048MsqGutqAbB392D+n1f0aeAL+mBjzj0P0VBTw5nmAlcW1ja4B4XgEx7BmAWL+3R8A5mtswvjrl3S18MYcCRJwj9yNP6Ro6kpL1M+l2L1XOguSZblvh7DJbN8+XIZ4MMPPzzfXQVBEARBEHpUbWUFP7zwFGW52forJAmaz8NUajU3/eu1Hqvs3BNkWaYwLeX/2Xvv+DbOO8//86B3gJ0iKYpiUSclWS5yjbsdx47tOMXpZRMnUbzZTfbut3u7t9ns3d7e7l2yud3NehOnOHGKHcdx3OPI3XKRbdmyqC6KVCElNoANvc3z+2OAwQwwAAEQIAHq+3699BKBGQwGg8HzPJ9vhclmg6OhCYyxpT4lgiCIfFEdsKjaM0EQBEEQxCJgcTjx4b/5H7DV1olPyBwQl3zkkxUlfAHR29bU2Q1nYzMJX4IglgVLKn4ZY0bG2E8YY6cYY17G2F7G2PsT2z7JGPPJ/gUYY5wxti2xnTHG/pkx5kn8+z+MRmaCIAiCICoYR30jPvw3/xMmq016rm3DJlxwK4XCEgRBlJul9vzqAAwDeB8AJ4C/BfAQY6yDc/4rzrkt+Q/ADgBDAN5NvPYuALcB2AygD8DNAL68yOdPEARBEARREHVt7fjQX/89altXYkXPWtz0p/+l5C2NCIIgiEwqLueXMdYP4O85579Le/5FAC9xzv8+8fh1AD/jnN+bePwnAL7EOd+e7djJnF+CIAiCIAiCIAhi+XLPPfdkRAUvtedXAWOsCcAaAAfTnl8F4AoA98ue3ghgn+zxvsRzase9izG2p7RnSxAEQRAEQRAEQVQLFeP5ZYzpAfwBwCDn/Mtp2/4WwDWc8ytlz8UBbOScH0k87gFwDICGV8qHWqYwxvZwzs9f6vMgiFzQfUpUA3SfEtUA3adEpUP3KJEvFeH5ZYxpAPwCQATA3Sq7fAbAz9Oe8wGQdwd3APCR8CUIgiAIgiAIgiDSWXLxm6jQ/BMATQDu4JxH07ZfCqAFwMNpLz0IsdhVks1IC5cmCIIgCIIgCIIgCKACxC+A/wSwHsAtnPOgyvbPAvgd59yb9vz9AL7JGGtljLUA+AsAPyvrmRJJ7l3qEyCIPKD7lKgG6D4lqgG6T4lKh+5RIi+WNOc3UcjqJIAwgJhs05c5579ijJkAjEH0CD+f9loG4J8BfDHx1I8B/CWFPRMEQRAEQRAEQRDpVEzBK4IgCIIgCIIgCIIoF5UQ9kwQBEEQBEEQBEEQZYXEL0EQBEEQBEEQBLHsIfFLEARBEARBEARBLHtI/BIEQRAEQRAEQRDLHhK/BEEQBEEQBEEQxLLnnBK/O3bs4Dt27KDy1gRBEARBEARBEOcYuqV8c8bY3QA+B6AXwAOc88/Jtl0D4D8AtAN4E8DnOOenEtsYgH9CqsfvT1BYj18SwARBEARBEARBEMsTpvbkUnt+zwL4BwA/lT/JGKsH8AiAvwVQC2APgN/IdrkLwG0ANgPoA3AzgC+X/3SJxUKIxBE85IH35RHEZkJLfToEQVQR8dkw/G+PwffWKHhMWOrTIQiCIAiiQlhSzy/n/BEAYIydD6BNtulDAA5yzn+b2P5tAG7G2DrO+REAnwXwXc75SGL7dwF8CcAPFvH0iRITn4sgeMSD0OEphAZmgMSiNfDeBJr+7LylPTkCgGiUCA/MIDrmB5KBFoxB12iBaY0LGuOSDilEBRA6PoPYVBCWzQ0luR9is2EE35sEj8bn3ZdHBYSOzyB6xic9J/iicFzdvuDzIAiCKDVc4AjunwTTamDaWAcxsJEgiHJSqSvVjQD2JR9wzv2MscHE80fStyf+3pjtYIyxuwDc9dWvfrU8Z0sUjRCMwbf7LIKHphAd9qruEx31QwhEobHoF/nsCACIz4URPDwlGiWOz0hGiQy0DMYuFyyb6mHZ1gimXerAknOHpFEi5g6mnmSAvsUG42qH9F3wuIDwiTnEpoIwb6yH1lra31RocAbun+wHOOB97jSct3TCvKkejDHEvRGEh2agtRtg7HTl97nCcUz+sB/xqeKjPyIjvvl3IgiCWGR4TMDUb44iuN8NALBf0w7ndauW+KwIYvlTqeLXBmAy7blZAHbZ9tm0bTbGGFPL++Wc3wvgXip2VVnEpkJw//SAcsEuRwMgobMio36YulyLdWpVR/j0XFbjAQDoV9phbHfkdSzOOaJjAYQOeRA87EE0X/EQ5wgfm0b42DQCB9yo+9R6aAza/F5bAUTdQUSGvTC226GrMy/16cwLjwsIvDuB4AE3QoMzQEx9eGMmHUzragAOhI5OgYdED6r3hWHU/8km6BsspTkfgWP2qSGpokJ8LoKpXx2BsdMJHhUQkd2fdZ/fCPPa2nmPOfvMiQUJXwAQvJEFvZ4gCKLUCKEYPPcfQngotZT1Pn8a+mYrLL31S3hmmcSmQoicnoPGZlAYU4ni4JwjNplYb3Q4qmK9sdyoVPHrA5C+UncA8GbZ7gDgK6DglYJoNIqRkRGEQpWbW2oymdDW1ga9fnG9n1zgCA9MQ2PRw7DSPv8L8iQ65sfkTw4oF6YawNjhhGl9HczrazH34jAC74yL+5P4VSU2E8bsE4MIHvTMu6/t8lY4378aTKMeVhU540PgnXEED3kQnwlnPY6uyQJTTw2YIeFNjAoIH59BdNQv7RM+Ng33j/aj7nMbS+5dLCVRdxD+t8cQOuRBbFI0wjCDFg1f6YOhxVa29+UCR3hoBrEswo5pGIzdNdC5jFmPMfvHU/C9MjL/e4ViCL6XbksE4jNhTP5gH+o/t6kkv+3AvklEz/oznpcv7pL4d4/OK37DQ7PwvzEqPbZe2AyNbZ57iTHoG83Q1Vsw8e97AQDxZSB+I2d84NE4jB3OpT6VJUEIxRA6OgUhnAp9N7TYoG+1UZgoUXXEvRG47zugOl5OP3QUujpTWeeffIhNhcS58bAH0bGA9DwzaWFaWwvzpnqYN9ZlXU8QmUTdQfjfHEXo8JTk9GEGDeo+tQGmNTXSfvHZMCIjXhh7aqrKgVBNVKr4PQgxrxcAwBizAuhKPJ/cvhnAW4nHm2XbCmZkZAR2ux0dHR0VOZFyzuHxeDAyMoLVq1cv2vtGhr2YfvS4lD9n3lQH581dORfk+RA+OQv3zw6Bh2LiEzoG181dsPTVK0Kb9Sus0t9yYUWIXj/fq2cx9/wp8Eh+BX18u85A8EVR8+GeDMtt8KAbnl8eVq+DrgGMq1NGiWxWyth0CL43zsL3yhkA4v0z+cN9qP9C74LvmXIQPj0H94/2g0eV149H4vDcfwiNd2+B1mYo+fsKkTimfn0EoSNTOffTWPVo+rPzoHVknoMQjsP/5qjiOV2TBcZOJ5g+YZQIxRE6Np1hyNA6jRACUfCoAMEfw+SP+jMm30LhUQFzfzwpPbZd2gIucPh3j6buKVkkR2hgGkIoBo1JfQoSInFM/+6Y9Ni0rhau27vzHp+FSEokxb0RcM4rcmzPh+ABNzy/En+bNXf0wHpB81KfUkHwqIDwyVlonUboGsxFfQ+eXx9B+Nh0xvPzGfQIopLgAkdgzzhmnzkBIRCTnrdf047gexOIeULgUaGs808+CKEYxv99L3gwlrGNh+II7ptEcN8kzH31qP3oWjBdYs7hHJFhLzQmHfSNpYkoWi5EJwKY+I/3wMPK2hU8IsD984Oo/cgamDfVw/vyCOZeHAZiAnR1JtT/SS90taYlOuvly1K3OtIlzkELQMsYMwGIAfg9gP/LGLsDwFMAvgWgP1HsCgDuB/BNxtjTEJdWfwHg34s9j1AoVLHCFwAYY6irq8PkZKb3phwIgShm/3gS/rfGFGIoeMCD0LFpOK5dBdulrWDawq6XEI5h7rnT8L12RloEM6MW9Z/doJoDqBC/YyR+kwjhODy/OpyxGDRtrFMVSrHxgOR9C+ydgBCIovaTqZDkyKgfU785qviuJevu+lqY1tTklW+tqzHBdVMndC4TZp4YBDgQmwjC/eP9aPz61oqyYMZnw/D84rBC+EqiMSogPhOG55eH0fDFXmliLwVCIAr3zw8hcmpu/n39UUw/ehx1n16fMTYF3puQJlFdvRn1X9ikOkFyzhEd9SM8IN4rxp4a6FdYERn2wvOzgxACMXHyvf8gmr+xrejwK9/rZyWRrbHq4bhuFTQmHaznNyO43w19kwWmtTWY/NF+0ZAV4wgdmYJlS6Pq8eZ2nkLMI3rFmUmLmgKELwBoDFowo1a8RnEOIRCr6AiEbMT9UUz//rj025x77hQsWxtLek+WG8+DRxBKRKZo60wwr6+DubcexlX5pWFEJwOqwhdIGPT8UdTcIRr0hHAckREvtFY9dE0WxT0T90UQcwehb7ZmNboQRDngnCNy2ovZp4YQOS1LT2JAzYdEg5Zlc4MkjuIzYcw8Noi6T67Pfsy4mEpiaLWB6Us7t4aOTSuFr47B2OFEzB1UGFOD/W64AzHUfXo94tNhTD96HJGTc4AGqL1zHSx9DSU9r3RiniB4VIC+2Tr/zkvM7NMnFMKX6TVgBg0EfwyIc0w9eBRa50nEZ1PXN+YJYeI/96H+C5tgWFH5n7GaWOoZ4L8D+DvZ408B+HvO+bcTwvf7AH4Jsc/vnbL9fgigE8D+xOMfJ54rmkoVvkkW6/yEYAwTP9iH2IQsD1fLgLi4+uIRAbNPn0B8NgzXLV15HzewfxKzTwwhPpcKQdTY9OKPOkt4j/zHHh33g8d5wYJ7uRH3R+H+2UFFfq++2QLXbd1ZQyK5wDHz6HHRmAEgdHQa4//6Lmo+2AV9qw2enx+UvMfaWhNqPiQeq9gFtu2SFmisekw9dBSIc8TcQcztPAXXzZ1FHa/U8Ggc7l8ckkLumVmH2g/3wNhTg/DQLDw/PwhwIHJyDjOPDcL1ocKEVzbis2FM/vQAYuOpEDLThroMUcZjAgJ7JwBAzLvud8OyObWI4DzhUU1g3b4iq2WYMQZDiy3jN2Zsd6DhK5vh/skBcbKNcfjfHofzxo68PosQjCEy7AWPC4DAMffiaWmb49p2SVwYWm0wtKbe29xbL0VxBPe7VcVvdNwvGsgSuD7QCa2z8MgBrd2AWFgcxwRfpOLFb8wTRNwbgaHdIXkyZx4fhOCPSvvEZyMIvDcB6/nV4f0Nn5qThC8AxD0h+F49A9+rZ2DeWAfnLfNHEgXenZD+1jVaYFzlQHQyIC6yE9vjs2EwnUaR+651GWHeUAeNXY/QkWlETs8BHNC32tC4Y8s5P5eUAh6NIzoRhH6FlbzvKoQGZxDc70bosAfxWWX6hbbGiJrbe6SIG32jBbUfXwfPz8QgxtDRaXCBq17X2GxYrJcyHoDWaUD9FzZB31Q6cRSSGZusFzXDeVMnNEatVA/E99oZBPaIKWnh4zMY/9e9iM+EJKcGBGD6t8egqzMrxv9SEjzghueBI0Cco+5T62HeVFl50nJCgzOpSC8G1H58Hczr6xAPROH+yQHEJsQ1gVz4JhG8ETGC7rMbYVx9bqa9lIOlbnX0bQDfzrLtOQDrsmzjAP6/xD+iRHCBw/PAEYXwNa2rheuWTsRnI5h+7Li0cA9lscSr4d87genfHFU8Z1jtRO1H1uQM59BY9NA6DeKkEeOIuQMlHeCrjdhMSBwoJ1Pfj/2qlXBc256zAAXTMLhu74bGpof3hWEA4iLUfd9BaGx6CD5xcc0Mohe+FNfYsrkBPBzH9CMDAADfa2dg7qvPu+hWNmJTITCjtmghwznH1O8GUkW8NEDdJ9fD1O0CAJjX1cJ5Ywdm/3ASAOB/ewwamx6O61ctSADH/VFM3tsveTMBwHlzJ+yXtaruz/QayVgx8/hxGLucUghcZNgrCUim18B6nrr3dD70jRa4PtgFzy8OARCjAhzXr8q5iOUCh//NUcz+8aRUOEuOrt4M64XZhZm5tx5zO08BAIJHpyGE49AYlV6L4KEpydNp7HLCcn5ToR8NAKCxG4BEXlV8LlLWsYNHBcSmQwWH+kXO+hDsdyN42CONrfpWG2pu6xZbv+3LjPbxvjwCy3lNJRUbMU9QkX+useihb7Eu2OjjfTl7TnrwoBhJZL+mHfbLWlWNbVzgkiEIAJw3rIJ5Yz14PGHQe1v8jYQHM/PK4zNh+F4/m/F89IwPoYFpmNfNX3CNyA7nHO6fH0L4+AyM3S7Uf34TGRRkzL00jLlnTmZu0DLYr2iD/aqVGdFQprU10Fh1EPwx8IjoAU5fI0UnAimjJUSD2MQP+lH/uY1SNEXcF4Hgi2ZEP+QD5xzhgRnpseW8JmmMZozBsMKKmjt6oKsxYe5ZcSxXK0oohm8fROPdW6G1lzZ8O3LWJ0arJZwyvjdHK1b8coFj9g8npMeWrY2SR1znNKLxK31w/+ygFBHATFo4b+iArsEsRqeF4+ChONz3HUTz/3f+koXCLzeW2vNLVBCzT59QhJfV3NEDy/lNYIxBV2dG41c34+y33wAgipBsVsl05EV5NDY9XB/ohHlLQ16Dsn6FDfFZ0WIWHfVXtPjlnCPuCUHrMpY8LJHHOdz3HUwJXwa4bu2CbXtLXq9njMF5fQd0tSbMPHlCyrdOCl8woPbOtSW9vpYLmhDYPylOpFy0BDd9/TwpvLhQfK+dwcyTQwADbJe2ih7GAvvI+nePKoo/uW7pkoRvEtsVbYiOBaRFt/fFYQj+KFy3dhe1uONxAVO/PpwSvhqG2o+sgWVrdtHqvGk1QkenEJ+NQPDHMPP4IOo+IYbAyYtAmTc3LKgFmGltDTQWHYRADPHZMMInZrMWlkuvAaCG44aOnIYYfYMFuiaLKPRiAkJHpzJC4yInU0LGsrWpaAEmTwEoZ9GryLAX7p8fhOCLwrSxDnV3rs0rDNH/9phoHErLs4+e8WHinvcUxzBvqkNoYAY8HEdsMojQIU9JFntc4Jh9ckhVJNqvXgnn9R1FHzs67kfoUMrr2/inWyH4owi8O45A4jfIowLmnjmJyGmvanh/+MRsKpzeooMpUSSNaRlcH0oY9F4cVrxG12AW87xVjDNJAnsnSPzmgEfjiHujOY3TcU8I4eMzAETvn+/VEdjft3KRzrA4uCCmgch7huvqzCUXZ7GpkCQMkzCzDuZ1tbBfvTJrhX3GGPRNVilNKTrmV3wHkWEv3PcdUOQLAwAPxuD+8X5YL25B5OSsWFmfi1FBNbd1F3buk0FJWDOjFoa2zGKIjDE4rmmHxqbHzKOptAzDaifsl7di6qGj4KE44rMReH5xCA1f6it63hfCccTnwtDVmsG0DHFfBJ77DylSlsInZsGj8ZKHf5eCYP9kytiu08CRNqZqLHrUf7EXvldGwOMctktapPux4ct9cP/0AARfFDwSR2hgBtYc6wYif0j8EgAA/55x+F5NhRrar1qZUVhFY9JBY9WLYXhxLg5IrtyJ+FF3MFWsSsfQ9I1tBXnt9CusUrhIdNQPbMn7pYsKFzimHjiC4H43DKscaLirr6RW8OiYPxUuq2Wo/djaovJprOc3w7SuFrNPn1CEEzpu6IB5Q12pTheAOEHWfKgH4997FzwiLtpn/3ACFjVPJWPQ1Zmy5uIFj06JwpcD4GKuX3DfJJw3d8LcW5+XQBKCMcWCxHphM6zbV2Q9byEQReioaAzyvzWGuC+Kuo+vy5jEeTSOeCAGrcOgeh4zTw4pPFO1H18LS2/u705j0qHmQz1w3yeGwAX73Zg2DcB2RRsC+1Pi3aZy/oXAdBqYNzdIgjrw7oSq+A0NTMN934FUWBvEEHm5p9PU44J50/z3kKW3HnPjYph0cL9bcR9zgSMsy4c2dhQfKaCVVYYutt2REI4jNpkKU4eGQd9okYxboWPT8PzykJQ2EDroweRPDqD+sxuhMWefXmOeIGYeH1QKX50GYqI8B7hYeA0ANHY9aj7UA+8rI/C+JBoS514ahmlj3YI8szwmYOqhowj2u1W3e18chmldbdHRGnKvr2lDnRT+aFpTA+v2FZh59LhURTZ0yIPAOxOwpnn55V5fc1+DwqjIGIPzhg7omywIHpmCYaUd5vV10NWapH7WoSNTEIIxGDud0LqMcP9IzJQKHvTkLLh2rsIFDv9bo5h95hR4KAbbZa1wfmC16n0WPqmsWzD77CmYNtSVrHXafAjBGHhMyFu4yudoBRqg4Yt9MHaWLqR0budJySupX2GF8+ZOGDvyaxGkb5aJ3/GANC/H5yKY/PF+KW+UGUQhlTTO8qiQUf3fv3sU1m1NBVXzl0f1GbtdOdcxtotWQFdnQmDvJExrXOJvlDHUfWK9OF9wIHLai9H//SZMa2thWi/WEclXpMZ9EUzcsw/xqZBo/FpXm5F3DACIcYRPzC2oaGM54DEBs7JCkPbLWlTTPDQGLRzXZvZ3NrTYYNnSKK3Nc3XhIAqDRv4K4eTJk7j55ptx4MABAMB3vvMd+Hw+fPvb3y77ewcPeTD9+wHpsWlDHRxZGq3r6kyIJHLQYp7QvOI3eCA10Zh6agoOV5UXvYqUuOIzjwngkfiCPGdJZp85KU2qkVNzCB+flrwUpUC+ADetrV1QIQmtzYDaj66F9YJm+PeMw9Bqg/XihYmobOhqTHDe1IGZRwcBiIWR1LxM4okxGDudMK+vg2l9LXQ14r0VnQhg6tdHMjxk8bkIpn59BI5r21UnjnS8Lw1LFnNtrQmuD3ZlFQ9Mr0HdZzZg+uEBRf7t1INHUPfpDalz8Ecx+Z/7EHMHoXUaYEqee2KCCx2bUXhqHdetmlf4JjGtrYVlW5PU7sv/1hj8e8YkAapvs6la5QvFel6TdI7B/W4It3YpwvF4XMDMY4Mp4avTwHHVStivaCvKmm/urcfcc6L4DR2ZghCJS+8XmwhIHjuNTQ9tXfFVLpWe32iOPdWJeYJixdM0DyIzamFaUwNdowXel4alRW6SyMk5TP6wH/Vf2KRagI4LHNO/G5A8F7oGM5w3roaxxwXBG8HME0OKSuA1t3VDY9HDdmkrvK+eAWIc0REfwoOzGVEL+SKEY/D84rDkuQPEsVZj1SM2FRLDGDkw/fAxNP1p4dEasemQ5N0FAPuVbYrtxg4nGv/0PMw8lqpFMPPkEExrXNA6xN+OEIkrhIqq0QyAZUtjRu4402pg6nZlXB/9Cmui4JqA4H73gitnC4EooGUFR6BUIpGRRGSHrK+779Uz0NWZYLs4M8IofDIt1DzGMf3wABq+3DdvRBiPCohNpdJ3mF4LbY0xb2NOZNgrCUFdk0WcMzbUwrDSnvUYc8+eyhS+ACAAcy+cRkNnb17vPe+5jXgV977rg10F5WrqmlLGg+h4as0T2D8pCV+NRYf6z4st6kxra8Qw6CzCaObpE2i4qzfva5ssjgiIa7b5MHXXwNSt3M+0pgbOmzrFvu8AhEAMgb0TCOydgMASFAkAAQAASURBVK7JgsYv9+W17pp5bFAKqRYCMYXBHkxMEUner6GB6YoTv77do4hPpyJX7FcWHhmhrUmJ5fhM5bZjrTaqf8QuMSN/tatsx277p8vLduxi8e8Zx/Qjx6SFra7JgtqPrck6eelqTVJuQtwTEhtQ5UA+2ZiLaNwur+JXynZHcX8Ukz/Yh5gnCNet3bBdVLz48787nmlx3TtRUvEbnUiJX31DaRqiG1c7F6WAgvXCFQjscyNyIjMvT0FczDUKD8wAjw9Cv8IK0/paBPvd0qSvdRphv2ol5p47JYVsz704DMvWxpyVimMzIXhlRZScN3TMG5rOtBrUfGQNNDY9fLvE1wYPesQKmwlLuu/1s1K/vvhsBP7do4piVHLMvfWwX13Y5Of6YCcEfzQlhmSe14V6fZPo22zQNZgRmwyKoVWHPAox4X97LNWT0KhF059uha6++HtQ32SFrtGM2IRYqTN8bFoK4ZUvqI0djgV5NjX2hYU9+147qxo6y8PxjEW01mmEZUuD5O2MjvkxeW+/apVz/1tjqd7HGqD2Y2slI4amzoy6z25A6NAUAv2TMHW7YN4oXhut3QDr+c3S/eV9ebgo8ZtMoYjIPHfWi1fAdUsXmIYhNhXC+P97BzwiIDYRxNzzp/MuhJbEt+sMIIhGAWOnU9V7zLQMzps7ETo+g/hUCDwUw/Tvj6PuMxvAGEPosEdR0bwUvagt5zVi9ikx/87/7sSCxK//7TFMPzYIptOg/nMbqroHc+j4NNw/OaDa6m7miUHoGiwZ91okzfMLiIZf3+tns9YyABLG9oePZYTuWs5vQu2H18x7rpxzTD92XLo3YuMBeMcD8L40DNP6WtR+fF3Gby7w3oQiPF7fbAEz6qQiaOHjM4hOBhbsteacY/bpVH6naUNdwXOsfM0Tk/XXlVeJdlzTLv0e9A0WNO7YjNlnToLHOUxra6CrN2PyB/2AwBE5MYvQ4am8Irt4TFD0ZV+ImLRd1gKAw7frjKLQaWw8gJknh1D70bU5Xx/Y71Y3ViRw3tgBXZNVKhAmF+3lgAscPBrP29DFBa4w9Nuvbi8q0kTuKSbPb+monn4JhAIejUOs+1U83pdHMP1wSvhqa01iuF6OH7dWJjDklls1Yp5gKj9Qy4oKq9XVmyWvg+CNIO4rTe6e79UzYv6sIFZUlYvLQgifnpOKOskJHfRACGf2yCsWeZEr3SKFlZUKpmGo+/haMSSu1ab6T6ci6KOjfnhfGE4Jr4Q31rZ9BZr/4vzUYjjOFaFFasztPCVVgdW32WDuy88QwzRMzFGXVVuee0lcRAnheHYvdhr6FitqPrKmYDGnMepQ99kNqPvUekXFY2bSwVyiNhKMMUX+sV9mXU+2J0tiv2rlgoRvEnm+akC2wJGHUhoWKCbk4ZDyxVc+8LiAgKzYlK7JAn2rDVqVkDVdowUNOzbD+f7VqPnIGmlWjbmDUkGmJLHpkGJxbL+iLcN7zxiDeWMd6j6+LkOc2S9PiYrw4IxYbbtAvLtGFMLFcd0qMQoiYfDU1ZrgfH+qn7z3lWFERrwZx8lG3B9VfO5c3g6NQYuaO3qkx6HDUwi8PY74bBj+RDVZQCwSU4qK65bNjUDiMJETs4oiX/nCOcfci8OY/t0AEBPAQzF4fnkYsTSvTCnm6JznES/dseeeH04JXx2D/Zp26NsSVXoFJGoWpOagZNsoAGIBp/elPPtzfzyZdT717xmD55eHMoQvAAT2jCNyNns9gSTBfrfCOy0ndHgK7h/vFz3yCSIjXkw9LItsW1uDxq+fh8avboZJlvftf1P5Wy2G0LFphWGrUKMRAOjlnt/JgPQbj8g6PBjS2oRpHUbUfnStOGac1wRju0NhHJ195kRe90v41FwqIqXOtKD+sowx2C9vQ/N/uxCNf7oVtitS90jg3QkEc/S5j/ujmHnsuPTYsq0JjXdvgf2adhh7XHDc0AHbFW1iqHoiLDs6FkB8rjziMDoRwPj33sHZb7+RMaZnIzQwLXmtmVkH20XFGdq0sujKGInfkkGe3wpBp9NBEFILmVAo+6Tsf3sM078/DsNKOxq+VFwfUu/LI4oKdPoVVjFMb578GflgKK9cq0bwQKrYiamnpiirF9Mw6Jos0mQXHfND272w4hRCKAafLBQVcY7ph4+h4SubC6qgGpsNi5VyE6JK12QBOJc8WsH9nowctmKRhz3rGkvj+V1MtA4j6j+zIec+sZkwQoc9CB6eQnhwJiOctOYja6S8QY1ZB+ctnZi8Zx8AcUEUudyr6h2KnPUpcgddN6nnsOXCcdVKqfJu6KAH0YmA2IoimAqjrrmjB6HDU4niG6nfsq7WhJrbu4vuc8wYg3lTPYxrauB9aRjhoVnYr8ysFLoQLFsbpSrM4YFpxL0RaO0GeF85I3nYtU4j7JfmV2BtPsy9DVLl8eBBD4RAFBqLHpETpcn3BZTit9Cc39CxaanFkNZhQNOfnQemYeCcIzYRQPDQFMLHp6F1GOG6pVMK4bNua4IQjGH2STHcz/fKGdi2rwDTakSP1SMDUi6vrsEMxzXzh+vL0dWZobEbxM8jiJ6AQnozRycCmHsulffuuLYdjmvaM/azXrQCgf5EtIYATP9uAI1f35rX7yYiu//1K6ww9rhy7m/qcsG6fYXk0VYzJuYqDlcIWodBbGmWyGsMvDcBx9WZnz8bXOCYfWoIvteURi/BF4Xn54fQ8NXN4FEBs38QayroW6xouKuv5D3OZ54YhO+1s7Be2AxXgT2w04l7I6kicwxo+vp50DdaYLuwGePffw+CNwIhEIP7/kNo+tOtYDqNwnhiaLPDcd0qhI5OIToWEKv8/vwgGr+2RfpdcM7he2VEqqIPiGGgGpsBQiAqjTHel4alwn5qpOdQ2i5pgbHLiUC/WxqfI6e9mPhBP+zva0Po2LQYNRNLpRjUfnydNM/btq9A6LAowvzvjMNx/aqCvysejSN0fAahw1OKNC/rBc0FV38HxHoPWpdR9PIlWgVqLPpURWWdJq++tvarV8L/zrhYJG8iCP+esXkj3OQFT415hDznA2NMankXnwtLBSdnHhmA8ZvbVNeFs08OSfeExmGA6+ZOaMy6TEOhQQvjKodkcAgNzMC6rTRrriTpRcZm/3AC5r6GjC4F6cjTnaznNxVdjEtLnt+yQOI3jaUKTW5qasLExAQ8Hg9sNhuefPJJ3HjjjRn7JSdWCByRU3MIHZsu2KMamw1jVlb4x7DaIXp88xCnujq5+M3t+Q3IJoKFVCY1rEjldURH/Rn5JelwzhXig2mZotCE/60xqdpxkshpL3yvnYH9cmVuWtb3iMbhuf8QhEQuocaiQ/1nNiB40CN5dgLvjpdE/HKBI+pOXWt9CTxvlYjOZYTt4hbYLm6BEI4hdGwGocMeRMcDsF7UnJHnbGx3wNxbL4VGzTw9JBYaky0Eo5MBMbohoaNN62th7HQVfG76ZitM62ql8OO5F04jIgsPs7+vDaYuV9ZKyaVAY9AuqPpuLnQ1JhhWO0WxwwH3zw/C0luvCOd3XL+qZNU09c2iJzV6xgfEBPjfGYe5tz5VZdSggX7FwvpDLiTsWVFoaWujtFhOVmPVN1mBq9Q9mtYLm6UiNPHZMALvTcKayN2WWogwoObDa4rKmdbVmhBJfJ7YdChv8csF0cgnRUC02mC/Sl34MQ1D7R09GP/Xd8GjAqKjfsQm8ms1J/emGvIMXXe+vwOhI1OqizvDaseCPFDpWM9rTInfdydgv2pl3uJx5olBxaJW32YT03HiYhVhsRVdQFooR0dEw9tC0mrSiU4EJPHtf2sMhnbHguaZ4EF3qlpvh1MSbFqnEXWfXo/Je/vFVoPjAQQPumHZ3KiI0DCudoDpNKj56FpM/uc+MZ/XE4Ln10dQ//lNEIJRzD51QvGbkhvbI2d8mPj3veK57Hcj5g5mjS7x7R5VeNMc17ZDY9HDvLEevnY7Zp4QjU6xiQCmf3tM8Vpm0qEubZ1j7KmBttYkht0HYwj2TxbUQzuZ3pDuyWYGTV51KLKhb7JIv4XoeEDh4DC02vJyeGhtBtivbMPcH8W13tyzp8SQ6LQ6LfKuHaEC830LxXVLF8LHZyD4oojPRTDz5BBcHxRz55LpPcFDHkWrpZrbu3MWDzSuqZGJ3+mSit/0goaAmHvsf3ssZ2h/bDqE0NGUZ9u6gN+/xqID02vAowJ4OE6F+koEXcEKQa/X41vf+hYuuugirF69GuvWqbY4RuCAWzHQhgYKF79iCGjCMt9iRcMXevNehMkXWjFPCJxz1YVDbDqEaDJMR8Ng3lB8/qu+WRYGNE/eb3QyAPdPD0hFBoBEL9TtK8RQPoHDuyuV+yktwAHM/vEUTOvr5hWXnHNMPTyQCunWALWfXA9dnRmWLQ2icYID4aFZxGbmLwo2H/HpkLRg1dj0JSnQVelojDpYeuthmSdP3HFDB4IHPYncpjmEDk3BtL4WPCrA+9IwvK+MpDzIrLgwtCT2q1ZK4lfeLklj18N6XmmtzUuB9bxGKS87OuLDrCy0UL/CWjLvGyCKSNtFKyQvn3/3KDSy/oWGdseCq6VrLDoxJC7OxUWDrLBWLoRgDEFZi55CW0toDFrYLm2RPOnel4dh7HaJ1coT2C5tlXpyFoqu1oRIoiJ2IWG7vtfOpvIGtWK7rVzXWFdvhrHTKVU8j47nKX6nU+eUr2jVGHWo++R6TD8ygLg/FbKqdRjgumWewhIFYtpQB2bQihXo3UFETnvz+i4iw15lm7FNdaj92DoE9k5I93HkVGYerP+NUVgvbC5J2DaAjJoC6YXCCkVRVCwtHcTY7oDjypVS6oNv92hC/KYMf8n0BEOLDTUfXYupXx0GIObRun8u9i+VG5uNnU7UfWaDtIA3tNpg7HFJLfG8u0ZQc3sqFD6JEIzB+0IqBcNxdbtiLrRd2gqNVY+p3x7LiBrS1plQ+5E1GXM704jjUDIKzrd7tCDxO/vMyQzhq7HqUfORNQtqn6RvtqZ+d2N+Ra0HQ3v+ue+2S1vhf2MU8Tmx7+/kf+5D/Rc2Qd9kFZ0gTw0heMANfaMVxrU1iJ5NrK80DMau0uewa616uG7twtSvjgAQQ90DsvSGdCxbGmBen3t9a+qpkfophwdm8m7BmY34XATBIx6EDk2Jla8TtQuggfQ9+HaNiBE9WYwQ/rfGUr3qe1wLclgwxqB1GaXUt9h0GIYVJN0WCl3BCuLrX/86vv71r+fcx/+GMtxKbiHLh8ioH4F3U4ON8wOdBXkfNDY9mEEDHklYoQIx1QrO8vAfY7drQYJN7gHKJX65wDH90DGF8AVEb7lv1xnEp0IwdjqlEEiNw4CGu/ow+YN9UgXQqQeOiP1uc+TVel8akUKsgESv2ITHT+swwtjtkr6XwN5JOLJ4iPIlWsX5vuVGX2+GbfsKKffW84tD6jsywHlT54L6GBtXOWDocGQUerFf1lp0D8NKwrK1EcGDHkWl4STOm1YvaEGhhnlLA2aeHgIPxRHzhBQFaRYa8gwkFg12g+RBEbwRaPLwkgb3u1Pe0RZrXiGG6dguboH35REp5HDyh/1S8SxdnQmO64v3CmllgjKep/iNTYXE9isJHFetzOtz6ZosQGIRHsuzLoL8nArx2BpW2tH0Z+flvX+xaAxamHvrpSrqs08NzZvywjnHjLyQ0bpa1H5iPZiGwXphM6JjfkX+v7bGKPbmjAqIjvnzFtjzIUTi8L+jFAvphcIKIe6LpHJUGWDemCk0rBc2Y+6FYcnAGBn2IirLzTXKxJiltx7Ra9rhfV4UqfIwWkAUMzV3ZEY82K9cKc2Z/j3jcFyzSlEpXQjGMP37AUW1fptKhwLLlkZorHrMPDkEjUEL0zqxvY5+hTXrtbGc34TZZ09KVdQjI968quhHx/ypsZIBtstbYd5QJxruFjhW6uSFPscCCuNBIeJXY9DCdUcPPPcfEttTzkYw+cN+WC9ohu+Ns5JHMzrmF0W27D3K5V209DYguGlSkRanhmltjeQVzkWySr3gj0LwRxEd9UvpUYXAYwKmf39cGhfkaJ1G1H12g9RzNz4bQeC9CVjPb0bkjE/saxwT4LhqJSxbGhV5waWI+pCL3/hMCFhR/DqmVIRPzopRCBXYWzkfqn/Fdg7B44Ki4h8gFlUpxPqf9EoC4uBSaJgmYywt71c99FlhTS6iyrMcebuj6EQAPKZe5MX32hlFUQim1wC61CQUPOiRwqIAUbRojFrUfDhVpCZ6xofx//cuZneehBDJrPQaPDKlWERaL2rOaAMh9wIG3h1fcNETeb6vvgrzfcuN/eqVYDnybwztdjT+6VZFsaCi3yuteA8zaRcU0lRJiFVrN2LFX1+Emg/1wLS+FlqXEfYrV5YlBE5j0Cp+K3JxZSiB+AXSil7lGfrslxkHLUV69DVmneK+kAvCmjvWLCgHVDH+5jn2+94cTeXhNlvzbrkhz1nMtyig/Jy0NaULVy4l9itapUI5yZSXXIQOT6Wq1WvEKtVygeP8QCes28Wep/arV6LpG9sURfKyVYAvlOB7snY31pQ4CR2eUhhk8z7eIU8q5HmVQ9V7rHUYFaJ4+ncDiu4Q6YZtxzXtGf2+tXUm1H9+I2rvzOyTDojeYHkBw+T3wTmHf+8Exr67R9GP2nnDqqxeN1NPDZq/sQ2NX9siVkVuseU0CmitekX7uenfDcC3+yxis7nzK70vpYx15g11cN3UCWOHsyRGQkXRq1GfouCcocC+2+a1taj//EawxJgjBGKiYS6ivo4CyhPyLMd1W7eYEqHXpP4ZtTCuqYHr1i40/9UFqP/8prycJkzDFHUFQkVUfRbCMbh/dlBV+Bo6HGjYsRmGFhtsslBn78sjCA1MY/LefsTGA4h7Qph+eABj//JOqk6GQ2x/uFDkxS4rIe9XCEQx+eMDOPuPb2HmyaGsa/JKhjy/VURy0ksnNDCdl3UpNDCdssQyKCp6FoK21oxoogR/fCoEpA3GQiCaEukaMcxsIWjMmQUg0r0WUXcQs3+UFXK5bhUc17SLBUqePiE1CU/CzDpYE9X3DK02uD7QKYYlcgBxDu8Lwwi8N4n6z2+UvMBxf1SRP2rsdKpaJk0b6yTveGwyiMiwV7XVR75Uc6XnxUBrM6Dm9m5MPzaosJBrXUY4rm6HZVtTybyWprU10DdbJSu5bXvLssu/0ToMsF7YDOuFC+uBmg9WmddeQgMYVpZG/GoKrPgcmwqlPPsawLK5+Ira9staxEW8LATTevEKsULpAihU/HLOFcZIx/XZhUPGe8nF7/j84pcLvKiw58VG32SF4+p2zCVqX+RKeeFxjtlnUl5f60XNmeGzWoaa27oVz9m2r5BCOgP9k3De3Flwn3vFeXAO325Z65QrVyLmCUnCeubxQWhdxoJaLilaEeaoy2G9aIW0r9xDqBahwTQMNR9dC+AoIiM+WM9vgv19K3NGxzDGYL+yDZ5fiCHT3ldG4Ns9CnBIBeKk89zcAHOevdLzxbp9hZSTHB31i33pHx2EaW0N6j69IeP3EpsKIdAv72O9sOiudPQNFinMVh7JpnUYoHMWHt5u6q5Bw129cN93UCrkB4jGC9fNnWL7tkMehAZmoLXppbVRudDaDGj8yuaSHc/UUyOlIoWPTQMFfB9xXwTu+w6m0tggCl7zpnqY19cqUv1s21fA++KwGNEzGYT7p5ntweSGTuuFzQtO3wEWr91R8JAH3peGxRz+D6/JOn773xkXK93HBIRPzEqGxGpiea3aFkC23NVKQYgLCvFr2liH0EExbCSch/hNisAklm1NRYXzAelFrzIXXxF5rmCLbUETvnScFVbpRx8Z9irOPVXIJVVh1H6lWLiKaRicH1gNjU0v5YUAgO3iFYqWTrZLW2HocGLmseOpPsZTIXh+fgiNOzZDY9ErKxDaDaj95HpFIa0kGoMW5k31UkP26YePoXHHlqJFkqLHbxHVI88FLFsaFb1pywVjDDV39MDzq8PQ1hgVLT6IwtE3WmDsdCp6S+pbbPNW0swXrT019uRT8VlelMfUU7OgvD2twwjrtiYx/wuiMcZ5Y3EGR8VxCwx7jp71p4oEGbUF9e6UjzcxdxA8LqiOeUkEbyRVn8Cqq2jDkP3KNgQPuKWUl+mHj4kF89IMZf53xhCbSPW5VquOrYahzQ79SrtY+yLOEdgzBvv7ihdJYrhxQnjqNGJhHy2TCoUJgRgmf9APy7YmON/fAa0t970b90fFqvoJzDkitIxdTqkXuOL5LEJbY9Ci7lO5q/unY1pfJ/X/Bs809msdBjhv6YR5U33J12qGdjssiaJ0ckJHp6UiX3K8u0Yk77ex21WSHtRymF4DXV3m9U5vcVQIhjY7Gr66GVMPHEF8Lgz75W2wXdoi/Z4XUpR0qTHJPL/hU3N513eI+6OY/EF/qm0XRONgtiJ4GpMOtotXwPtSohBkMh3YYYBlU71osJHlCJfKgFzudkexqRBmnhiUKp8DYtHLxh2bM1qfcoErIlls21dUtHbKBoU9AzCZTPB4PGXtybcQOOdwj05AM5Mo199kgVOWMxY6PjNvD7fomF/Kl2V6DZzXFZ9zpix6lRn2HJYV/SjVpCAf9OULZQDwvzkq89YwsYqqbIHGGIPjypXi82Yd9G021Up9hlYbGr6yGTUf6pGs1DF3EJ4HjiB40KNYGNfc3p1T1NuvaJNCrmMTQUw9eBRcKO7+Unp+Kex5qTGstGPFX12Ixi9vzlmFksgP63al4a4UuZFJlGHP0Rx7Jvo2y2oqFBvyLMdx7SoxNNRuQO3H15VE1GvtBsnSLgRiENIq16ej8O5tqCuoNZ7GpIPWmbiGcT5ve7tqCHlOwrQaRcpL5OQc/G8qw5OFSFzyDgNiVff5RKUcuVHa9+ZY0XMAoAydtmxugMaih8aoQ+1H14IZUt9p4J1xjH3nnXnDP0OHPJKAM7Tbc3oUGWOq6R2lSk8AEj3VP9idkcLC9BrYLmtF019sg6W3oSwLbcbEAnDNf3kBXB/sgl6WMxo6NqPYN+6LwP92SiSXywCq5pxY6HpKX29G491bsOKvL4L9irachqxqQuswivUJACDOM9aI2fDtGkkJXwa4bu+G4+r2nPeY7dJWRTqdrt6Mxq9shuuDXWj68/PEEGwtg+Pq9qKL0KVTznZHwYNujH/vHYXwBYDYeEB13RoenJHmAWbSKtI7qglauQFoa2vDyMgIJicLz5lZLNjZEGxvih5A2/YV0DVaoHUYEJ+LgIfiiIzkLqght2wZu1yKHIJCUXh+VTwP8rzbhYT7ypGHCoaHZiVPPedckXtjv7Ita7ED6/lNsJzXmDMENlnAhJm0mPq1WJEwPDCjtJBvaZi3wra+2YraO9Zg6jdHAQChI1OY/eNJuAoMNY8nijgA4iJgId8bQVQi5o110Nj1UtswQwFhm/OhceSf8+t9ZUTW09hQcBV9NbQOA5q/sW3Bx5HDNGLdBan651QIhhb1MU8MeU7Na8V4d3SNFsRnE62VJgI5o09iRRa7WioMrTbY37dSKrbme+2sooZD6PBUqp2dw6DI+csHy+Z6zDw1BB6MIT4VErszrC2880HcH1WE2dpkBiNjpxNN3zwfs08OSkWEeCiGqYeOovm/XJDV4CIvSpnL65vEuq0Jc388KeWOa50GxaK8FJi6XWj51sXg0ZTXl+k0BRlsFoKuxgTbJS3Qt9mkHvKhgWlFZKDvtbOpKLNWG4zdrrKci77JguB+5XOFFLvKRjV66fLB1FMDXyI1IzwwDfO63L8zHhMUhalqPtQD6wXze2q1dgOcN3Rg9g8nYOxwovYT6ySDmL7RgoY/6V1wxel0dDXlEb88zjH9uwFFa1DjmlQf9NDhKcw9ewrOGzqk7T6ZEc56XlPJe5gvFiR+IbYZWr164eFo5UCIxDH16yMIHRFDiZlBA8vWRjDGYOypkcJ0wgPTucWvfFFSt7BFibLglVL8coErinKVYrAGAEOrHcyoBQ/HEZ8NIz4l9reMnvVLCzNm1sFxde6QtHwHJEtfA6JjfnhfSAjrxNigsenzbr1h2dooHuNlMUTG9/II9M3WglqnyI0WunpzySvuEsRSw7QaOG9cjenfHYO+2TrvoqUQ5F66XOI3PheBb5e8p3FHRVfw1takxG98KgRkEb/RsUDKSm8oLOQ5ib7RIlXijY4HYN6UfV+l+K2OKBXH1SvhfXkYEMTxVh4yKe8uYD2vseCFHtNrYd3WJNWcCPa7ixK/gfcmFP2Z9W3K71vnMqLuUxsQPDqF6YeOiZVvvVH4do2o9psNn54T27gkyMcoojHrYN7cIOUxGzqc5fHCahmYdmmXpoZWO5hJBx6KQZiLSD2ueUxQRAfYr8y/R3ShZHh+NayoKsbnCqY1NdLvLHRs/qJXwQNuCP5E9XCnoaBIH/vlbbBd3JLVKFPqdZqi4NVcGDzOS5JLHDk1K1VQ11j1qPvMBhhXOTDz1BB8iZag3heHoWsww3peE2KzYTFiJEF61FY1UbmzOwEhEIX7JwcUrUdsl7dJeVSmNS7p+dA8LY/i06ULR9O6TEDixy14I4qqyDF3UCo6pLHqFflpC4FpmaK4Rngw0dT8cOqHaF5bU1ILsePaVTCltX5w3dpVUA6z44YOmGSL+enfHUP4dGYvyGzIK+DqKN+XWKZYtzWh5duXoPHurSUVnYp2KTkKXs09d0qqfqpvLm1P43KgMEBOZw9Flnt9Tetri7q2uqb8Kz7Lc5C1tdURpcL0WuhkBaxissJe0fGU+C22Robc4BCbUu+OMB/J+hEAcvYMNq+tVfQy974ykmH04VFBUbjRtLYGujzXBI4rV0Jj0YmhyCqthpYLTMtg6k5FoCRDn0NHp1LtllxG1dZQpUL+uwPEtmvV2lZmMTCudqRSzSaDiM3kTtFQeDAvXFGwmFysaITke2mS9Ss4EPeWxvsblIU6m3vrJQea8/2rYVqbGremf3sMvt1nlf2LO51VXYOGxG8FMfmT/Zj4Yb/0b/zf9iIiy5+1X7kSjmtTnk1jdw2Q+L1GhucgBLPnfpUyHI1pGbTyMAzZsSMyYWdot5fUKmqUtWUKDc0AEFsPJSlFSXk5TMNQ+9G1Ur6x9cJmRUuEvI9x59qUcI1xeH5xGPF52igkicrbHFG+L7GM0Ri0pbeYy3N+feriNzoRUIS/laOncanJp+JzepXnYlvOKYpezSN+qy3sOYm8/7e8mrH872LFr7JAWeGL1ui4P1WJVsvm/R4t25ok4cQjAuaeO6XYPvf86VQBL4MWrrQq1bnQ1Zux4q8vwoq/uaigqtLViFHW7ieZP+2XGSEsW3OnUC0UXZ0ZkAmsUhfVWm4wvRbG1bL0uBwOoeiYX1EnZjE6GywUedEreQXwfIjPhjH122PwvjKiqG0kd6zJnTRMw1D78XUpAwwHZh4dlKIYger2+gIkfiuK8IlZRGT/5LH9zps74byxQyEmtVZ9qjCDAEVeajqlDHsG0kOfU9bscoQ8J1Hk/Q7OIj4XQTRZWVrDigrpmw+NUYuGL/eh+b9dCNft+S8SFMcw6VD/2Q1gieJIgjcC9y8OKfKaspFcpADU5oggCkVj00sGQsEfVS0MKO99bux2KXpGViq6PCo+xyYCUmg002tgLHJ8VPT6nQzkLNqkbHNUPcY6RV/VhOdXCMdSi0wNU3iHC0HRpmQuXHBPTHmhRfOGunl7nzINg/OmVBqX/+0xyWMfGfHC+0qqRobzpo68vb7S8XWaiq7iXSrkvW4jJ2YRnwsrxEK5o0OYhinuy1LVT1nOmFQMFmrIvb7mjXULquq/WBTb7ohzDs8vDyPwzjhmnz4h5fpH3UHF/GCSOZcAcd3acFcf9HKjS2Ls0tj1ZY16WAxI/FY6Og1qP7ZWtToxkPZjzyJ+ucCVveJKUIVTWfFZ7vmVid8S9epMom+xgZkSjdq9EXhfS/XuNXY4ylZ5l2kYdE7jgrzYujoz6j65XvrFRUd8mPrdwLwVxmMyzy9VeiaIwmBaTUoscEBI8/5G3cFUlctE7/NqKAijzcPzK/f6mtbVFl2YRGPRp/olx3hWsc2j8VRouQZVVZxP7tVNhjrL+xrr6s1FhzkynSZVeI0j76gfQJy75eI3X8FlWlOTKsQkAJ5fHIL7/kPw/PJwqsLzaiesF1a396ac6GpNksGDRwXMPD4o9ezWt9kWJeTTuk3MQ9XYDQrPHKGO3FsfPj6jaqgTwjFlGkGVeDDl46lauyMe55h77hTmnjulSEUM7ncritB6XxK9v/KUQWO3SzUlRmvVo+GLvRmGU+sFzVVfKXz5m++qiIYv9GaIIcMKa05Lr9y7mi0kLT4blnqPaWz6klRnUwu7E8KxVI4UAwwrS1ucgWkYjKud0mLVJxO/pvWVPzGYul1w3dKFmccGAQDB9yYRvbQ1azgTjwmphS1D0Z4HgjiX0doNUsX0uDeiWERETqZaYpjW1FRNQZn0nF+16qLJyr9AftV8c6FvsiCcyB2NTgRUx6KY3MDqMpWkIMtioWvODHuOjclSTpoXJnR0NSZEEoaB2HRIYTzORXhoViroqLHq8o5uYozB+f7VmPj3veJ7TgYVLfOYXoPaO3oqPrx/qTH2uKSik/Lfk7UEbdDywXZJC0xraqBxGKq2qu5iom+2SJ0DhEAM0TO+jPVVYO8keEIc6hrNiojCSkbZ7ijTAOnffRZzz50GAERG/aKzReCY/eNJxX7RMz6Ej88oWhuZc6QMaoxa1H9mA6YfPobAe5PQ2PSwbW/Jun+1UN3SfZlh7HTC1OVS/JsvxElRqMOtXkyjHHlYinZHibDnyIhPCh/UN1kzmmOXAmOnK/UgljIUlDrft1xYt69QCPVIjuJXMU9Qup5al5EmP4IoglztjhSRKlWUw6gx6aCxJMbXGIeQ9rnic5FUvqqWwVREhWE5itDnLEbWas33BcTzTXo+BG8UcX9UWeyqqbh8X+n48hoZBeTrBd5N9ZM19zUU5H02tNpgvUg9l9F502oypuaBPLJOQsMWtbeprt5Mc3+eMMaU0ZAqVZ/9e1L1HWwXraiKSB9g/rBnef2b0EEP5p47Bd+bo4ir9Gaf3XkK4ZOpted8UQVMp0HtnevQ9Ofnoekb2xSFJKsV8vxWObraROVlgSM+G1G0aUgSL4v4lYnuxPHTi12VA2NX5gJVV2+GvkomcsaU3mt5aF06UVm+bzVX1SOIpURR9CqX+C3TmFUutLUmCAGx5kFsOqTwaMvz3YyrHFl7veaLvNJ8LMuYpZhnSpBas5gwDYOu0SIVloqN+xVj80I9v9o8q3PLESLxBXsbXR/shrmvAVxWDFPrMsLQVl33+lJh7HJK66skprU1BXV8IBYXU0+NFNYcGpiG45pUkdi4L5IqHqcpf952KZF7ftPDnnlMSBXwSuB9YRjMkDKW2S5pgW/3WUAAorIwaH2bLW8xW2zRv0qEPL9VDtNqlCFwKt7fmKL9RGkWJYoKltNi37HFWEjqm60pj0eCagh5lqNXCbFTQ9HmiIpdEURRaO2phaq83VFGmkZbdYQ8J8nVbz0sF78lKARYqOe3VPPMYqIoejUWUFZ6XrDnd/4CZemEDnpS4ZkN5ozevvnAtAymLhfMm+qlfyR880dj1MGwSnm9CukHSyw+Uq47ROOmEEoZfsKDM1I0nWGlY97IykpCm8PzGxnxgkczC+kl2/dpa4xw3rQals2ZYt98juaSk/hdBswX+lyOcDSNQZvqOyZweO4/qGjLZChTZUKmYTCsVnp/q60QhNyLEB0PZC16FZblI+pXLB+LG0EsJposnt/IcPnTNMqJXFDJx3gucISOz0iPVUM3C30vmTCMTahXfK7msGdAaZQMDc5A8Il54kyvWbCYl7cGjOUR9sw5h+/NVEVay3mNVROeudyQ51kzkw7mKjO2n2to7YbUekngCMvGwmS/ZgBl6Q5STjRWvZSawcPxNFEvq12xsS4jpcF5QweYTgP7+9oyjlstKYOlhsTvMkAhficzxW98ujyLEnlPtdDRaan5OzPpyppPJC9QwEw6GDuqqwWAxm6Q2h7xcFw1fyM9jKVaijIQRKWhDHuOSn9HhsufplFOlNE3qTE+OuqXhJvGqiuJ4Uxr1UOTCPXkUUF1zCpHes1iohC/R1P5c7omy4ILQyk8v3mEPYcOTyn6kFZTeOZyw7ypHkgUb7Ne1Fx01W9i8ZA7RALviSHQnHNlOkgVtLSTwxjL6v0Nn0iJX/PGOtR9dgNYoh2ZYZUD5j4xR13fbFVESmocBuhbzk3HCv2KlwHyFjiLFfYMADUf6hELaqStCwzt9rJWkTSvrwN04vEtWxqqruQ6YyzD+5uOPIxFW2uquhw6gqgU5PlM8sJQ1ZzvC6hX3AfS8n27a0o2FutyhD5zzpdV2LO8mOJCQ56BRMhi4muIeyM5e/3yOMfsMyekx9aLmqFzVd/1XC7oGyxo3LEFtZ9YB+d1q5b6dIg8kBuLgoenIASiiE0EpLQXZtJVZfi/Wt4vjwmK4lXGLhf0DRY0feM81HxsLeo/v1ExBziubpeUn3XruRtRUl1xXoQqci9rNE38CuG45AWAlkHrKF3vRY1Jh5rbe2A9vxnTjx6XCgmUOyxIV2tC41c2IzoeWHALj6VC32RF5IQ4YEXH/Bl5F/IwFvL6EkTxqBW84jy9RkF1RY8A2cWvPN+3FCHPSfRNFkQSHobIsFcxZgn+qJSfyozajLoM1YDGYQAz6cBl4YTAwotdAWJtDq3TKHpruLhwzVak0b9nDLFEsUNm1CoK9hBLg6HVVjVt0AixRoG+zYboiA+IcwT63YqcWFOPqyrbfMmLGiYjSCKnvUDCmKarM0GX2EfnNEKnEjFiWGlHw5c3I+YOwtK3eFXLK43qm6GIDPQNyrBnzrlkzVGEPNeYyvKDN6y0o/FrWxA65IEQiasm1Zf8PdvsVWm5SyJfUMVUil6Fh2akv41drkU4I4JYnqTn/PJoHPG5iNT7t9xpGuVC8iZysZAXjwrgnCtbWKxxlez9DCvt8O8W81B9r5+F/dIWqWBMLK3SczV6E5IROelVU0vh+QXEvN9kqGJ8OqQqfoVwHHPPnZIe29/XBq2t+tuKEMRiY9naiNkR0SET2DsBJqt4X20hz0nU2h0Vs1Y0rnLAuKr6DL6lpLriRQlVNHYDWKK9EQ/FpEUdkBbyXFM6r286TMNg3lQP63lNYNrqW/gsNoqKz2lhzzwmIHwq5ZUizy9BFI/GoE2NfXEO72tnERlWhjxXoxeAaTXKMLjpkJj7FRdDdnVNlpJG+lg2N0jhzDwYw9zLI9I2uZG1GkOek6i18iiF5xfIXqBMjm/XCIREXrrGYYDtstaSvDdBnGtYNjeIbaoARE7NiZWeE5QyImYx0crSHyIjXtHYOURRgsVA4ncZwBjLmvdb7RU4lyvprUN4PJVjFjk9pxrGQhBEcdivXCn97X1xGMHDqYJGhpXVG0EiF1Rzz51C8L1J6XGpF3hMp4Hzxg7pse+1M1LP2uUyzyjyfgFoLDpF5MBC0CqKXmUWDBNCMXhfSRkUnNetgsawsP7MBHGuorUZYForGwOTRsEGc9XWUNHLQu/Dg7OYe/YUwqflhVFdS3BW1QmJ32VCtorPygqc1Rfat1zRWPSpQjxxjpgn9Z0pLHkU8kwQC8Z6frNkIOThOIL7UiLRWIXFrpLoW1KLoWC/G4G9E9LjcrTyMPfWQ580FsQ45naeQuSMD4G9qetZ1eI3zfOra7KULIRb4flVqfgcGfFJfTl19WZYtlE/WYJYCGpV0qvV6wsAhhVWschsAu8Lw1JxPl2DWVHckcgNid9lQrZev8oKnORBrCR08tBnWd5viIpdEURJYVoG542rVbdVs+fXcU07zJtU+jTqGAxlaAHHGIPr/anrGNg7gYnv70VMVv25VGHCS0G657dU+b4AoKvNLFYjR34NDascVRmKTxCVhHl9HZhJGT1Rrfm+SVwf7FJdF9JasTBI/C4T5EWvolnDnsnzW0motTvi0bgY9pyAwlgIojSYNtRmCEJdg1kq2lSNaMw61H1qA+o+vxHaupRn0dRdU7aQWWOnU9ErEsmMDS2D4/pVMKyu3kWYIiIH6jnAxaKdx/Mrbx+VLsIJgigcptcoKxprWdWvqZhWg9pPrs+orUBRgoVB4neZoBb2zDlXVnuu4nC05Yjcq5D0/IZPeRW5KRTGQhClgTEG501K7281e33lmNfWovnPt8F502pYL2yG64NdZX0/5/tXK1YPxh4Xmr6xDY6r26uy0rMcg6wKain7P2sdRumaCd4oeDSu2C4vfCjvqUwQRPHI0weMnU5ojNWfR6+16lH/mQ1SoVvoNOT5LRBqdbRMUIhfTxBc4GLvxURvM2bWQWOmr7uSkHsVYomFj6JsPQ1mBFFSjO0OmHvrEdzvFh9XuRdADtNrYL+ibVHeS99oQe3H1yHY74a5rx7mTfVVL3qTOG/sADNoYWizwdBSut6uTMugdZmkOhyx6bCi8GFsIpX6oifxSxAlwbjKAddtXYic8sK+jHpm65utaPhSL3yvn4V5Ux21RCsQUkPLBI1JB41ND8EXBeIc8Zkw4t6ItJ28vpWHvtEs9emMeYKI+6MIHfJI2ymMhSBKT83t3WB6DTQmHSxbG+Z/AaGKpbcBlt7ld/10dWbUfmRNeY7tMkriNz4dkkRu3BeB4I8BEI0Y8hZWBEEsDNv2FmD7Up9F6TGstKP2Y2uX+jSqEhK/ywhdgxkRn9gjMDYZQDwQS20j8VtxML0WujqzWKCMAxP3vIe4JxGmriHPL0GUA41Fj9qP0oKBWHy0tSYgUc1fnvcrL3ala7JQsSuCIIgyQjm/ywh9vayAkjuI6Fmf9Dg9OZ6oDOSFTSThC8BxXQeFsRAEQSwjlO2OUr1+FcWuKOSZIAiirJDndxkhz/v1vX5WIab0DTShViK6Zitw0KN4znlLJ+yXti7RGREEQRDlQFuj3u6Iil0RBEEsHiR+lxE6WbsjhfBttsCyefnlZi0HDC2yVhoahtqProFlS2ZjdoIgCKK6kacfydsQxsjzSxAEsWiQ+F1GyD2/SQwdDtR/diOYniLcKxHT+jqYtzQgNhmE88YOmHpqlvqUCIIgiDIg7/Ubzxb2TD1+CYIgygqJ32WErtYE6BgQE/vEmtbXou4T68D01d/XbLnCNAx1d65b6tMgCIIgyozWbpDmaMEfRcwThMasg+AVC1VCp1EIZIIgCKL0VLw7kDH2EmMsxBjzJf4dlW27hjF2hDEWYIy9yBhbtZTnutQwnQbOGzqgsRtgu6wVdZ/aQMKXIAiCICoApmEwdaeiewJ7J5Re3wYzVXomCIIoMxUvfhPczTm3Jf6tBQDGWD2ARwD8LYBaAHsA/GYJz7EisF/ehpa/uQiumzvBtDSJEgRBEESlYDkvVdPBv3dCWeyKQp4JgiDKTrWIXzU+BOAg5/y3nPMQgG8D2MwYoxhSgiAIgiAqDvP6WjCTGJEV94Tgf3tM2kb5vgRBEOWnWsTv/2aMuRljrzHGrkw8txHAvuQOnHM/gMHE8woYY3cxxvYsxokSBEEQBEGowfRaWHpT3ReiIz7pb6r0TBAEUX6qQfz+JYBOAK0A7gXwBGOsC4ANwGzavrMA7OkH4Jzfyzk/v9wnShAEQRAEkQt56LMc6vFLEARRfipe/HLO3+SceznnYc75zwG8BuAmAD4AjrTdHQC8i32OBEEQBEEQ+WBY5YC2Nq2qs5ZBV5vZrpAgCIIoLRUvflXgABiAgwA2J59kjFkBdCWeJwiCIAiCqDiYhsGypUHxnL7BTEUqCYIgFoGKFr+MMRdj7AbGmIkxpmOMfRLAFQD+COD3ADYxxu5gjJkAfAtAP+f8yFKeM0EQBEEQRC4s5zUpHlPIM0EQxOJQ0eIXgB7APwCYBOAG8KcAbuOcH+WcTwK4A8D/AjAN4CIAdy7ViRIEQRAEQeSDvt4MQ3uqRAkVuyIIglgcdEt9ArlICNwLcmx/DgC1NiIIgiAIoqqwX7kSnvsPAVoGc2/9Up8OQRDEOUFFi1+CIAiCIIjliHlDHZr/6/lgeg20DuNSnw5BEMQ5wTkpfnfs2LHUp0AQBEEQBEEQBEGUB37PPfdkVBKs9JxfgiAIgiAIgiAIglgwjHO+1OdAVBmMsT2c8/OX+jwIIhd0nxLVAN2nRDVA9ylR6dA9SuQLeX4JgiAIgiAIgiCIZQ+JX4IgCIIgCIIgCGLZQ+KXKIZ7l/oECCIP6D4lqgG6T4lqgO5TotKhe5TIC8r5JQiCIAiCIAiCIJY95PklCIIgCIIgCIIglj0kfgmCIAiCIAiCIIhlD4lfgiAIgiAIgiAIYtlD4pcgCIIgCIIgCIJY9pD4JQiCIAiCIAiCIJY955T43bFjB9+xYweVtyYIgiAIgiAIgjjH0C31CSwRJIAJgiAIgiAIgiCWJ0ztyXPK80sQ5yKBQADBYHCpT4MgCIIgCIIglpRz1fNLEOcEw8PDuO+++6DVavHlL38Z9fX1S31KBEEQBEEQBLEkkOeXIKoEv9+PY8eOIRaL5f2avXv3QhAERKNRHDlypIxnRxAEQRAEQRCVDXl+CaIKiMfj+NGPfoSZmRls3rwZt99+e16vc7vd0t8U+kwQBEEQBEGcy5D4JYgqYGpqCjMzMwCAwcHBvF83OTkp/R0Oh0t9WgRBEARBEESVEY1GMTIyglAotNSnsmBMJhPa2tqg1+vz2p/EL0FUAfLBKV8R6/f7Fd7e5TDAEQRBEARBEAtjZGQEdrsdHR0dYEy1KHJVwDmHx+PByMgIVq9enddrKOeXIKoAuXCNRqOIx+Pzvkbu9U0/BkEQBEEQBHFuEgqFUFdXV9XCFwAYY6irqytojUvilyCqgPQfdT4/cnm+L0BhzwRBEARBEIRItQvfJIV+DhK/BFEFFCN+yfNLEARBEARBEClI/BJEFVAKz+98r+GcF9RGiSAIgiCWI/F4HIIgLPVpEARRBqjgFUFUAeUOew6Hw/jxj38Mn8+HO++8E6tWrSruRAmCIAiiihkYGMBDDz2Euro6/Mmf/EneFWQJgqgOyPNLEFVAutidL383HA5jdnZW8VwkEslaKOvo0aOYnJxEMBjEO++8s7CTJQiCIIgq5aWXXkI0GsXY2BiGhoaW+nQIYlnyf/7P/8G//du/AQC+8Y1v4OqrrwYAPP/887BYLPjmN78JAPjXf/1XdHZ2AhBbfV522WULfm/y/BJEFVCo59fj8ag+Hw6HYbFYMp73+XzS336/v4gzJAiCIIjqJhAI4MyZM9Jjmg+Jc4Fvf/vbi37sK664At/97nfx9a9/HXv27EE4HEY0GsWrr76Kv/zLv8STTz4JANi1axfq6upw5swZvPrqq7j88ssXfE7k+SWIKqBQ8Zte7CpJNo+xvB9wIBAo8OwIgiAIovpJ9/TK50aCIErHtm3b8M4778Dr9cJoNOLiiy/Gnj17sGvXLnzkIx+Bz+eD1+vF8PAwPvGJT+CVV17Brl27SPwSxLlCoeI3Pd93vtfJJ3ia7AmCIIhzkePHjyse03xIEOVBr9ejo6MD9913Hy655BJcfvnlePHFFzE4OIj169fj4osvxn333Ye1a9fi8ssvx65du/DGG2/g0ksvXfB7U9gzQVQBJH4JgiAIonxwzjE4OKh4juZD4lygnGHPubjiiivwne98Bz/96U/R29uLb37zm9i2bRsYY7jiiivwrW99C9/61rewdetWvPjiizCbzXA6nQt+X/L8EkQVsJCwZ5vNNu/r5BN8OBzOWhiLIAiCIJYjExMT8Hq9iudI/BJE+bj88ssxOjqKiy++GE1NTTCZTFJY8+WXX47h4WFcccUV0Gq1WLlyZUmKXQHk+SWIiodzXpD4jcfjmJqakh63trbi6NGjAPLL+U0+lotmgiAIgpBz4MAB7N27FxdccAHWrVu31KezYNJDngESvwRRTq655hpEo1Hp8bFjx6S/u7q6wDmXHu/cubNk70ueX4KocGKxWIYnNlero6mpKQiCAABwOBxwOBzStnw8v2qPCYIgCCJJPB7H448/jsHBQTz00EMYGxtb6lNaMCR+CeLcgMQvQVQ4aoI1l+dXnu9bX18Pk8k07+vSKzzThE8QBEFkw+/3IxKJAAAEQcAjjzyi8OBUG5FIBKdPn854nuZCglh+UNgzQVQ4CxG/DQ0NCvGr5jGOx+PSIiYJtTsiCKJY3njjDRw9elQKWdNoNOjq6sKFF14Ig8FQ8PFOnTqFN954A/X19ejr60NjYyMAYHx8HPv378fU1BTa2tqwadMmRaQLUT7S+99OTEzghRdewA033LBEZ7QwTp48KUVYOZ1OzM7OAiDxSyxvOOdgjC31aSwYeXh0PpD4JYgKp1DxKy92VV9frxjY1F6nNrkXO+EfO3YMPp8Pvb290Ov1RR2DIIjq5ezZs/jjH/+Y8fyJEyewe/duXHnlldi6dSu0Wm3ex3ziiScko96rr76K5uZmcM4xPj4u7XPo0CE8++yzWL16NS6++GL09PQs/MMQWUkXv4Bo9Ojp6UFnZ2dZ3pNzDq/Xi/HxcYyPjyvmKaPRiM2bNxddCVYe8rxhwwbs3r0bnHNEIhHEYjHodMtvuTwzM4PDhw9jzZo1qKurW+rTIRYZk8kEj8eDurq6qhbAnHN4PB6Fo2c+lt+vmSDygHOOxx9/HKOjo7jlllvQ2tq61KeUFTXBGg6HIQgCNJrMzIX0sGf5IqWc4ndkZAS//vWvpdeXohcbQRDVhdz4lo7P58OTTz6J3bt349Of/nReQiUajWa0bsuWX8o5x9DQEIaGhnD33Xejvr6+sJMn8kZN/ALAo48+ih07dhS0EFWDc44nn3wShw8flrw6alFKcgYHB/H5z38+6/bDhw/jhRdewKZNm/C+971PsU0ufru7u7Fv3z4pAioUCi3LApAPPfQQzp49i7fffht333236nqCWL60tbVhZGQk55hdLZhMJrS1teW9P4lf4pzk1KlT2Lt3LwBg165duPPOO5f4jLKTzcsbDodhNpsVz3HOM8SvvFiWWthzqcTvqVOnpL+Hh4cLfj1BENWPz+eT/t64cSPOP/98uN1uvPLKK1IbGbfbjffeey9DgKgxMzMj/Z30FifHNJ1Oh7Vr16KtrQ1Hjx7FyZMnpX1HRkZI/JYRufjduHEjhoaGEAwGMTc3h6NHj2Lz5s0LOv7IyAjeeeedgl4zPDyc1SgMAM899xw8Hg9efPFFnHfeebDb7QDEz5LskKDT6dDe3g6z2SyJ3+XY/SAWi+Hs2bMAxCKZfr9fuh4A8N577+HEiRO45JJL0NTUtFSnSZQRvV6P1atXL/VpLAkkfolzEvmCanp6eulOJA+yCVE18evz+STLuNFohM1mU3zWfD2/xeT8yt9HvgAmCOLcQf7bX7FiBVavXo3Vq1dj8+bN+MMf/iAZHefm5vI6nnx8bm9vx0c/+lEMDg4CED10SQ/jxRdfjGeffRavvfYaACjavRGlRy5+m5qaUFtbi127dgEQ838XSrZ52Wg0oqmpCU1NTXA4HGCM4eWXX0Y0GoUgCAiFQrBYLBmvEwRBcczZ2VlJ7Ml7+9bU1ECv1yvm1uWY95s+R8vFr9frxWOPPQbOOY4fP4677rqr6HBygqhESPwS5yTyya7ShVo2z6/a8/IFX21tLRhj81Z7VhO6xUz2yQIhQOVfU4IgyoP8ty/3lhkMBvT09EjiVz4G50IuWGpqamA2m7Fp0ybVfeV5iyR+y4tc/FqtVkWNh/Qw9WKQ3x/btm3DNddcAwAwm80Z+Yl79+6Fx+MBIN5/auI3GAxKLQCT+6n9nbxnl7v4Tf/9ya+B2+2WQs39fj8eeughfO5zn6M6HsSygQL8iXMS+UDv9/sz+uhWEgsRvwDmrfZcqrDndM9vodX3CIKofrKJ3/TH+RrI0sVvLpJjXvrriNKTLn4bGhqkx6XIIZTfHy6XCxaLBRaLRbUwTz73VS6xN5/4XY7dD9KvU7brAQBnzpzB008/TXM6sWyoeM8vY+wlANsBxBJPneGcr01suwbAfwBoB/AmgM9xzk+pHYcg5KQP7oFAQJHvUkkUIn6T1m8g5QUxGo05X1MK8cs5V3h+Y7EYwuHwgouenCuMj49jaGhIWlxotVqsWbNm3sU+QVQaucSvfIwtt/glz295SRe/cq/79PT0gisky++P+ebmfMSvWpiv2rZzxfOb7/VIsnfvXjidTmzcuBG1tbUFVWsniEqj4sVvgrs55z+WP8EYqwfwCIAvAngCwP8E8BuIQpkgcqJm9awG8avRaKTQrXw9v3q9XnpdPB5HNBpVhC+VIuc3FApleJV9Ph+J3zyYm5vDj370I8RiMcXzr776Kr7+9a9nDTVzu9145plnFB53h8OB97///QovTCgUwhNPPAEAuOWWW+g7IcqKfGy1Wq2KbfLHyeiQ+VpsFCJ+bTYbdDodYrEYgsEggsFgRl0EojSki1+DwQCXy4WZmRmp9chCCiXJPbXzFZsqt+d3OYrfXNdDvs1oNEpz+0svvYSXXnpJKgp2yy23kIE2TzjnePbZZzE2NoZLLrkE3d3dS31K5zTVHPb8IQAHOee/5ZyHAHwbwGbG2LqlPS2iGkifIPPNP1sK5CLX5XKpPp9ETfym5/2mi9RSeH7lAiwJ5f3mx8mTJzOELyDek6Ojo1lf98orr+D48eNwu93Sv6GhIbz00kuK/d555x0cPHgQBw8eLLh6KkEUQjwel8YOxliG+DUYDFIkiiAI844znPOCxK9Go1HsQ97f8sA5zxC/ABTVtRea95srgiCdYjy/57r4zfd6XHPNNWhublbsG4vFMDQ0hDfeeKO8J7mMGB4exuuvv46hoSH88pe/xDPPPINoNLrUp3XOUi3i938zxtyMsdcYY1cmntsIYF9yB865H8Bg4nkFjLG7GGN7FuNEicLhnOPs2bN45pln8C//8i/43ve+V5JqkbnINfBXGnKRK6+4mC5+k9b2JPIwtFyhz2oTezQaLWhgloc8J6nka1pJyBf3ra2tCm/J+Ph41tdlW1ymv0b+ONfxCGKhyAWRxWJRbTlTSN6v3++XxiGj0ZiXF5dCn8tPJBKRDHY6nQ4GgwFA+cRvKcKeK8nzGwqFsH//fgwODi7ZPJmv+HW5XPjc5z6HK6+8Et3d3YprXYrCZucK6XPv7t278eMf/3hZ9NitRqoh7PkvARwCEAFwJ4AnGGNbANgApN81swAyRknO+b0A7t2xYwdl61cYhw8fxvPPP58xiL722mu4/fbby/KekUhENUS3Usnm+VX7DPKForziZa6Kz9km9mAwmHd1RzXPbyV70ysJufjdsmULwuGwNFHmEqtyg8MnP/lJ/OpXv5KOJ+91KRcA1SgGjh8/jldffVW1WBsgLlKvvvrqghrcE+UhH2+dzWZTVOZtbGzMerx0r+98IdIAid/FIN3rm/xeSlX0KhqNSvOURqOZ1+hRDs+vfP4stfh96KGHMDQ0JD22Wq3o7u7GTTfdpDBUl5N8c37tdjtMJhOuvPJKAMDY2Bh+8IMfAFA3ehPqqI1F4+PjuO+++/CNb3yDKmkvMhUvfjnnb8oe/pwx9nEANwHwAXCk7e4AQCvuKiASieCZZ57Bu+++q7r9+PHjOZvVLwT5IJ+kGsVvuohVa3OUJFfYszy/N5kvB4gTvsOR/hNThzy/xSP/3mpqahQVNbOJ31gsJt3HjDF0dnbCYrEgEAggHo9jbm5OulfkAqLaKuByzvHYY4/Na0iZm5vD1772tbzEEVE+8hW/avurUUjIcxISv+VHLeQZKJ3nNz1vfL51wEI9v2qfp1yeX0EQcPLkScVzfr8f+/btQ2trKy688MKSvVcu8s35Tf8dy6PP5ubm8srbJ5Rj2bp16zAwMIB4PI5AIICJiQm0trYu4dmde1RL2LMcDoABOAhgc/JJxpgVQFfieaKCGR0dxQ9/+EOF8NXr9ejr65MmHL/fj7Nnz5bl/dUmx0oVapzzvMVvtpBnIP+wZ/nCUf78yMhITi9kteb8er1enDhxQtH/cbGRT4q1tbUZYc9q5zY3Nyf9bbfbodVqVRf9oVBIsbDz+/1Zq4cXiyAIOHHiRFmEdTAYzCuCwO12lz1VgpifShO/1WbsqRayiV+559ftdhc9rhYS8gwUJ36j0SjC4bBUHA0QDYlJj2+5xO/c3Jx0XTQajcLjt1hjmCAIGU6ApOE0/Xqk5+2bTCbpnKPR6LLMhy4HckPc5Zdfjp6eHukxhY8vPhXt+WWMuQBcBOBliK2OPgbgCgB/DmAKwP9ljN0B4CkA3wLQzzk/siQnS+SFz+fDfffdh0gkIj23ceNG3HzzzTCbzfj973+PffvEVO6BgYGyhDKqLaYrVahFo1FpotRqtYpJfj7Pr5xsYc/xeFz6LhhjcLlc0gScnNQOHDiAhx9+GIwxfPazn0VHR0fGeVaj5zcYDOKee+5BMBjEZZddhmuvvXbRzyEajUr3I2MMTqcTGo1G8uJGIhHMzs5mLPzl1ztpia+trcXIyAgA8V7o7OxUXfxPT09jxYoVJfsMr7zyCl566SUYjUZ85StfKWn1z3TDwB133KHY/vLLL+PYsWMAgEOHDi2ouiyxcAoVv/MZNsjzW5lkE7/JXryBQACxWEx17MqHQio9J983SVLEyVvxcM6zGr3l7ZjkXuZyiV/5Pd3S0oJLL70Uv/nNbwCoG5HLQTAYVDVMBAIBxfNqXvfkPJUUbHNzc4rrT2TCOc9Yn8mjJOSOC2JxqHTPrx7AP0DM7XUD+FMAt3HOj3LOJwHcAeB/AZiGKJLvXKoTJfJjZGREElt6vR633norPvzhD0sTzZo1a6R9k4vaUlNNnl+5UDWbzTlzd/MVv/KwZ/mkbjKZMhYRAHD06FEA4gC+a9cu1fOsRs/v6dOnpc9/5MjS2MzkCyGXywWtVgvG2LxFr+Se32RoutqiX23xX2pBkLw/wuEwdu/eXdJjy++r+vp6tLa2Kv5t3iwF/+DQoUMlfW+icCrB8+twOKQFu8/ny5orThRPNvELZHp/i6GQSs+AaBiWz13pXs1QKKRaUd/n82V9L3m0VDgcRjwez+/k5yF9zJdHcy2W+M1mdPL5fHkZHuTpUJT3Oz9er1e6/8xmM8xmc0mLwxGFU9Hil3M+yTm/gHNu55y7OOfbOefPyrY/xzlfxzk3c86v5JyfXMLTJfJAbuHasmULtm7dqsgX6erqkhYuo6OjZSmaVK3i12Qy5QxflouafMOe5eLXYrGoWrvlxx0cHMwoZBKJRFT7AlfqNU2SXghqKUKf0/N9k8wnfrN5fpMkF1jlFr/pFcb37t1bUrExn/jp6emRQvAmJycp9HmJyUe0yMNYyyF+tVqtYl8KfS49ucSvfFFfbNGrQsOeAeX9li5+cxXBynbPphfaKlW6iFzg1tTUZIhfec2HclHM9ZCTnvdL5EbNMUHid2mpaPFLLD9yeScBUeC1t7dLjwcGBkp+DmoDv1oF6EogXfxm8/ymi5B8w57l4tdsNmdUuEw/LgC89dZbisdyISZfqPj9/pJZy8uBfFEsCMKiWd2znUOx4ncpPb8+n0+RwhCJRKS0hVIwn/gxGAyK3KnDhw+X7L2Jwiml5zcWiykW1vIF93xQr9/ykq/4LXZRX2jYc/p+6fdVNiO63+/Pec+WI/Q5fUyTR3TFYrFFMRrnK36zGR7I81sYakZuuYPC4/Esad2RcxESv8SiMp/4Bcof+pxvK4RKIJf4DYfDkpU4V5uj5Gvlr0uSLn7lk30gEEAgEMiweL/33nuK5+STX21trWrodCWSviheikVyek5rErn4HRsby3idmihIF7/peUbybaVC7VhvvvlmySZyuUFC7iGRs2HDBulvCn1eWkopfuXfvdPpVORmzgfl/ZaXfMOeS+H5LYX4LdbTWQ7xqzamLXbocy5jQD6GB7khisTv/Kite81ms3R94/H4khjfz2VI/BKLSq6KxEnknpyhoSHVXJ2FIJ/s5MUcqkH86nQ6aREoCIIkeHO1OQKyhz3LxWm6+A0Gg6qFGKLRKPbu3Ss9Tp/MC8npW0rSF8VLUXQiW9hzQ0OD9B1OTU0pvKuAuudX7kGIRqPw+XxZC16VCrVr5vF4FD0sF0I+Ya89PT3Sb2J8fJxCyJaQ9BY1algsFuneDgaDWcf3YkKek5D4LS+FeH6LCeNdaNhzLs+v3IiyFOJX7b5ebPGb7XdKYc/lIZuRm0Kflw4Sv8SiEY1GpYEyWVlYjfr6emlSiEQiOHXqVEnPQz64NzY2qj5fKaSLX/n/8u3zGRWKDXuWH1fekuGtt96SvHtyIZYufsuRs10K1CytSyF+s02Ker1e8T2m57KqeX4ZYwqRMDExofi9JQXH3NycZDRZKNnujzfffFNt94JID0XPNl4YjUZ0d3dLjyn0eWmIRCKSkSY9X1KORqNRLLjV+q4DpRO/lPNbenKJX6fTKY0FwWAw6/ebi1KHPcsfy6NqFlv8Jo2SgDgmJw2X8vt7scVvc3Oz4nkKey492SIe00OficWDxC+xaMgXIbnC2BhjCu9vKfN+BUHIORFWGvmK33xyqZPkG/YcDAYVx922bZt0nOnpael7SQ9PrAbP7+zsbEZo7mJPPoIg5FzgZ8v7DYfD0veu1WoVi0/5dz84OCj9nV5VtFSCQH7NLr30UunvgYGBBV9Pr9crfUcWi0URvZAOhT4vPXKRY7PZMqJP5OQzRpDntzIRBEERMZSeYsMYW5BHK70HbalzfuVt3hZb/KbPlcl2TOUYm3Mhvx5y8VtM2LO8bzGRiVqboyTk+V06SPwSi0auasTpyPN+Syl+Q6GQNFAbjUbFoqoShVqpxG8+1Z7Vcn7lAqa5uRnnnXee9Djp3avGsGe1BfFii1/5okFN3GUTv+khz3KRIf/ujx8/rni+HEWA5Nesp6dHYbR6++23F3TsQsTPmjVrpIXk6OgoefuWgELyNMstfl0ul/S7mJ2dLVmkA5EqhAikUnHSWUi7o0AgMO/x1cjX85vL05nuxS61+M12Ty9l2HOu65Htd2wwGKR1SLqxglASCAQkh4PBYFDcYyR+lw4Sv8SikasacTodHR3SYtbj8ZRscE23ala6UFMTv2pCthRhz2qtjtKPe8EFF0iLyqGhIUxMTGS03an0awqoi7/Z2dmS55fnIlvIc5Js4jdXBVz5ceSh0rW1tSX3hgmCkGF0ufDCC6XHhw8fXlDbjnxCnpOYTCZ0dHRIj0+fPl30+xLFUaz4zZYasRDxq9PpFL8NKiZTOnKFPCeRL+rfeust/P73v8djjz2mMMhlQ34/5JvvC+Tv+S1E7KmJX7fbjZ07d+LkyZN5n1uSbGNapYrfXNef8n7zI1c9FhK/SweJX2LRyKfScxKdTqcYlM+ePVuSc0if6CpdqOXj+c0VVpP+WkBZJTrd82swGCRLezweV1TrrKurQ01NDdauXSs9t3v3bsXColrEr5pnkHO+qB7DbMWukqSL3+R3plbsKkm231U5xO/c3JzUyippOOns7JSMM7Ozs6qVqvOlUPHT1tYm/V2q8YLIn1J6ftN/i4WKX4BCn8tFoeJ3YmIC+/btw969e/Hggw/OWweimErP6fvm8vzW1tbCYDAAUBaN1Gq1inkSUBe/v/vd7/D666/jgQceKLj3b76e33KGEYfDYSk3X6vVKgRZMBhURMbJ6zikQxWf8yPXPC9P//P7/SUrqkbMD4lfYtEoJOwZAFpbW6W/yyF+7XZ7xQu1+cRvOByet80RIE5yyYmMcy5NfunVnuX/A5AmQpPJJB33oosukrbv3btXEmU2mw06nU5hLa7EawpkXwwvZujzfJ5fp9MpCclQKCRZ1/P1/MqpqakpeREgtWgDrVarSFk4cuRI0ccvVPy0tLRIf585c6bo9yWKoxDRMt8YEQgEpDHKYDCojmnzsdi9fgVBOCdEQD7it6OjI0NIAmIf2xMnTuQ8frHi12QySd0bwuGwNCdGIhEp7FSr1SpazMhRy1NPF79erxejo6PSewwPD+d9fkD2MU0+bwuCUPJCkV6vVzJUpl9frVar+vua79rLDa/k+c1Ornleo9Eo1sJL5f1Vq4ECLO8xjcQvsWgUEvYMlGcxuxw9v+kiJFuhGbVw6XTPr/x/OfIBuqOjQ6qSLQ9rTVqvK/2aAsrFsNxjuJjidz7PL2NMNfQ5Pcxcjs1mU7XWl8Pzmy3UXh4ZcPTo0aKPX0jYM6A0lo2NjUmLPWJxKKXnN10k5CqelY3F9PzGYjH86Ec/wve+9z288MILZX2vpSYf8WuxWLBjxw7cfvvtuO2227Bp0yZp23zdG4ppcwRkVhFPHic91YkxllX8ppMuftPFbqHpFbnGtHKFPr/55pv47ne/i+9///sIhUKq11fts8937dU8v7FYDK+//rrCKH6uM19U3lKHPj/99NP43ve+h1/84hcKASwIAu677z5873vfw7PPPrvo51VuSPwSi0K+bY7kyMXv2bNnSzKYzid+K61qYT7iV24YyOVRV6v4rCZ+1azA8uMyxhTe3yTJybDSxW96rqq8TU4leX4BZehz0uOQK+yZMaZ6rJqamox2GgvNb84mfru7u6V8/bGxsaK9zIV6fm02m3Q9YrFYRnsooryUUvzKRUY+hlI15PdkuSMBhoaGpN/n7t27F7V2wGKTj/gFxLFp8+bN2LJlC84//3zp+fnEbzFtjtT2T56n2n1ZjPgNBAIZYrdQ8ZtrTCuH+OWc47XXXpPe+/Dhw6rXQ+17LMTzm5yTXnvtNezcuROPPfYYtZxLMJ/4Xcp2R+FwGHv27AEAnDhxQlFbZGRkRBqH33rrrWVXNJDEL7EoyAd9l8uVVwXH+vp6KTfH5/OVJLQmfeDX6XSSKOScK8KAK4F8xK+8pc3q1auzHiv9dfF4XAotZIxJnuH5PL8A0Nvbm7FfcvI2mUyS+JGHnFUK8hAwi8Wi8BguVm5gep52NnEnP7fk95wr7FntWA6HA3q9Hnq9XlqwcM4XHM6ULY3BZDIp7sNivL/RaFRaBDPGVD+nGuVIlSDyo5TiV37PyI1ThbBq1SrJY3z27NmyVqSVh/dHIpF5Q3urmXzFr5zW1lZpTnC73TmNosWGPafvr+b5zeXpzMfzmy52z5w5k7ehIxgMSnOhXq/PuHbl6PU7OjqqmC+OHDmialzI93rIUSt4deDAAem5/v7+4k56mVHJnt8TJ04oHD5DQ0Oqf0ej0WVXRJLEL7EoFBryDIhhTPKefKVYzM5nBa4kTyXnXCF+k+JUHr7s9XoVlvSurq6sx0sPe073+ibzpfIRvwaDQdH2CEhNhulhZZV0TYHMyUh+Py6W5TV9IZRtoSFf+A8PDyMYDOb0/AKZvy/541LmQeb6Ta9bt076u5i83/TPmFw4zwfl/S4dCxG/8qieQCCgGNPkOeSFYDabFcYQ+WKulAiCkGHgWUiue6VTjPjV6/WK7yLXQrrYsGdAfS5fiOc33WCc9O4nicVieRf1S3cApIfyl6PXb/p9ODg4qDj2QsKe0z2/MzMzigKZAwMDFWf4XmxCoZDkUNFqtarXdCnFb3r19WziF4DCybIcIPFLLAqFVHqWI58wS7GYVZsIK7VAUzQalaxyOp1OyuWUT8hDQ0OSF7OxsTGnhyw97Fkt5Dn97yRq35m87RGgnLyrRfzW1NTA5XJJwt/r9S7KhJ1vTqPNZpN+A5xz7N+/X/I0yHstysklfkuVBxmPx3OGbcsFy6lTpwqOqCi20i95fpcGznnOfqnpyCvJxmIxxW/u2LFjkhhua2srWADJkRuP8mmzUwxnzpzJ8CofPXq04lJoSkUx4hcQPfFJcoU+lyrsuRSeX61WqzAaq6Ve5esRm29MK0fYc7r4jcViCu9sqcKefT5fxnvF43EMDAwUfM7LifR1b3KdIUfuWJiamlq0WhWc84wx8dSpU9J4PDIyothWrvFzqSDxSywKhVZ6TpKe97tQqsnzqxbynP63POQql9c3/XVqnt8k8+X8JnG5XOjr6wMginO58KjUawpk5tpqtdpFrwybT8hzkp6eHunvZH4OIC4+1ETzYojf6elpaSHocDik9AT5uclFe6GLoHQvSb7II0UmJiaWXZ5SpRIOh6VFm16vVwiGbGQbI+SLaHkEQTHIxe/g4GBZivCoeXl9Pt+yNb6UU/ymG1FKIX4X4vkF1I3B8vs7X/E7XwG/Uovf6elp1boH8u9vIWHPOp1O2odzjnfffTdjn0OHDhV0zsuNfJw+RqNRMiQIgrBo7RanpqYy7rNYLIbh4WGcOnUqw3g3MTGxrKp6k/glFoViwp6BTE/OQhYvsVhMEnyMMUnkVapQy0f8ypkvNy497FmtzVH634B4fbItZm+++WbcfvvtuOuuuxQLoUq9poD6hLTYRSfyKXaVRO5FlS9msnn5048nF9elaneUrdiVHLlw2b17N1588UW8+OKLOHjw4Ly/Y/mkXIjn12w2S+cjCMKC+gwXwtmzZ/H2229LOfTnGsUIFvl+Se9cNBpVhNctVPy2tLRI45nP51MUdCkV8pBn+W9yuYY+Fyt+V65cKRnrxsbGVHuaRiIRyWAlr8eRL/l6fgvxdKqJX3kBr+Hh4bzWJYV4fmdnZ+f1AHq9XuzevTvrfCW//7LNFQsJewaU3l81oT0wMLDgMfHMmTNVO7bmG8EkD31+5ZVX8OKLL+LVV18tq9jM5skdGhrKmiKynLy/JH6JRaHYsGeXyyVNPqFQaEHeqvSwvGQISqUKtULEr06nQ3t7e87jFRv2nMtTr9frsXnzZqn1UZJKvaaA+r24mG1RBEFQFMSZT9w1NzerLk6yLWjSc2SzeX5HR0eLXlDkE8khb3k0OjqKl19+GS+//DJ++9vfKjzYahTr+QVKHy0yH2fOnMGPf/xjPPXUU3jggQfOyRYfCxW/ydcPDQ1J4qeurk6xKCwGjUaDzs5O6XGpF29ut1vK09Pr9bj22mulbctR/MpD1BljBYlTo9GoiMxQ65Gr1paoEBbi+c3Vtimdbdu2SZ/d7/fnNWfMZ9CT137gnOfs9evz+fCjH/0IzzzzDO69915VASw3ylx++eU5vbvFeH4B9Tmovr5e+t1Go9EFhT6fOHFCGlsffPDBqhtb5VEBuda98nGuv78fL7/8Mp577jncf//9ZascLx8L5QUq08WvfNtyyvsl8UuUnWLaHCVhjJUs7zfbAq1ShVoh4rejo0O1v6ucfMOeCxG/2ajUa5peZXkpPL+7du1SiN+VK1fm3F+j0ShCn5OoFbtK7p+csOx2u2Jira+vl+4Dr9eL5557ruDzB/Lz/DY0NCiEqJznnnsu5+KuWM8vUPo6AbmIRCJ45JFHpBCxEydOYN++fWV9z0qkVOK3lCHPScqZ9ys/366uLqxdu1bqZOB2uxe9dUm5Sff6quUw5kIe+nzy5MmM7QsJeU5/Tbk8vzabDTU1NYpxO5/Q53wMevkUvYrH4/jtb38rranC4TAefPBBRd58etG4tWvXKoyRSZLXIf16aLVaVY93Ompz0Jo1a7BhwwbpcbGhzzMzM/jtb38rCd6hoaGqqiC9f/9+hfBva2vLum+2lDW3241XX3215OcWi8UUv7/rrrtO+vvs2bOSF1+r1eLqq6+Wtg0ODi6bWgYkfomyIxcb+bY5klMqT062KpKVKtSyiV+9Xp+x6MinHUiuas9y63a6pbuYPpuVWkTM7/dL3k6j0Sh91sUSv0ePHsWLL74oPd6+fbvCG5INtYq3uYqb3X777bj55pvx2c9+VmEU0ev1uP7666XHb731VlGCIJ80BsYY7rzzTlx//fW48sorceWVV0pCNhwO45lnnsl6/GILXgGL6/l99tlnM+6XnTt3VlzLtHJTjGhJHyMEQcCxY8ek50olfuULy9OnT5e0oJ3cu7Zu3ToYDAbF+y0372+xIc9J5sv7XUil5/Rz8vl8GalOye06nU4h7gwGQ0bdgiTpIrC9vR2MMUWk1XziVxCEvAx6+eT97ty5M+PaTU5O4tFHH5WEolrRuHTxa7VapQghi8Wi8LLn63VXm4PSxe+xY8cKrr0QjUbxm9/8JmMc/eMf/1gVY+vs7CyefPJJ6fHWrVuzGoIB8Zrdeeed0jyZrKUCiMbyUq9JTp8+LX0ntbW1aGlpkc5P7l1fuXKlouhgKBRaNl0UClMhREXAOcfk5CQcDkfBOTHZmJ2dzZkDWFNTkzHQxeNxjI2NKQY2q9WK+vp6xcBZbMhzkvk8OWrnIUen06G5uTkvz2/SSjw7OwvOeUFe6lgshomJCUV/4iSRSARjY2MFWc3kC3f595zsySsXr/mI36X0/EajUXg8HpjN5rx7tqoxOzuLSCQiFarKxtzcHOLxeEZLifR7MbltIeLX7/cjGAyqVnOcnp6W2vaEw2E88sgj0raOjg6FxTUXnZ2d0Gg0ivsnm+cXEH+H8rw0OVu3bsXRo0elhfujjz6KHTt2wGQyYXp6OqdHNom8pUWu+8PhcOCSSy6RHre3t+P+++8HABw8eBBbt27NuHeDwaBk+JEXVcmX5uZmMMbAOYfb7UYoFMo5TgYCAUxOTiomfafTqdqORM7AwADefvtt6bFer0c0GkUgEMCzzz6LW2+9Ned5Jsdx+WLOYDCgubk54z6amZlRLIa1Wi2am5szoj0CgQACgUDWyqJqRCIRuN1uRQi8Xq9HfX29wmAWi8Xg8XhUczXlY1Wxnt+RkRFJXFmtVsW4vxAcDgcaGxsxMTEBQRBw8uRJVS9YPkSjUYyNjSEejyMajUqhu4wxKTpj7dq10m/r6NGjuPTSS/M+fjAYxMTERNbwTrvdXtR4XAiCIGB2dla1D7j8ey5G/MoF4+joKMLhMCKRCGZnZ1FTU7OgSs+AaNDU6XSIxWLS/So/X/lvwmazSfdyrvdSE78AVD2/oVAIXq8XNTU1CiO/z+eTcnjNZnPWGhrz9frdt28f3nzzTelxV1eXFIp6+PBhPP/88+ju7lZ4SJNGpNWrV0tjVPpn1mg0sFqt0hop32ufPgcZjUasXLkSGo0GtbW1mJqakkKf5YI4F5xzPPnkk1JbKY1GA7PZDL/fj0AggOeeew4f/OAHcx4jGo3C7XZDp9PlXCvE43F4PJ6iBDVjDI2NjRn3hyAIePTRRyUjm8vlwo033jjvsdatWyd9V4IgwO124+zZs4jH43jyySfxmc98puA0gGzIDd7J+bezszPDWNzZ2QnGGLq6uvDee+9Jr50vWq0aqGrxyxirBfATANcDcAP4b5zzXy/tWRXPY489llHkwOVyYdOmTVJO5YkTJ/Dss8/i7NmzMBgMuPTSS7F9+/asg6kgCFkFVygUwuHDh9Hf36+af5NOe3s7ent70dTUhEOHDmH//v0ZLR4AMdyxr68P69atQyAQUIS9FCN+5RazZJ4iYwzj4+Po7+/HgQMH5h28TCZTVm+v/O/Z2Vn88Ic/lAbe5uZm9PX1YePGjaqTPecco6Oj6O/vx8GDBxEMBmGxWPC+970P27ZtAyBW6H3llVcWZLFMX7ybTCZp4nY6nXktiOTHGB0dVfSUK6f4HRsbwz/+4z9KC7qVK1eit7cXXV1dmJmZwfj4ONxutyK3xWq1Yv369VKRlPHxcTz//POSZ0ir1aKxsRFNTU3S/y6XC4ODg+jv75fK9CfvxU2bNsFutys+s3yhYbfbpUVTMBjEgw8+iL6+PnR1dalOnLFYDMeOHUN/f79URdbhcKC3txfr1q3DmTNn0N/fn9Xz6HQ68ZGPfCTv/rVGoxEdHR2KXJxijQiMMdxyyy2S2PD5fPjP//xPBIPBgvOLGGMFeWY7OzvR19cnLc6eeuopfPnLX4ZOp4MgCPB4PIrPOJ8AVcNgMKCxsVEqbjQyMoKOjg7FPvF4HMePH0d/fz8GBgZUx0iDwSDdV2rnIF9ArFu3Dlu3bsUDDzwAANi7dy/6+vpUFwlzc3PYv38/+vv7VQ0tdrsdvb29WL9+Pc6ePYv9+/dntJ0AxHtiw4YN6O3thc/nU70XN23aBEEQMD4+jomJCcUYFI1GMTExkdPYU1NTg7q6Oni9XkxOTuZlvCtG/A4NDSlSAdauXVtwSG0uuru7pVC+gYEByTur1WpVv1v5vMk5l37PBw8eVPUct7e3S/PD2rVrJePL6dOn8atf/Qq9vb1Ys2aNatRTPveinJ6eHlx77bVoampSPV+143s8HukeiMfjaGhoQFNTE2pqajA1NSVtGx8fx/j4eF61AIoRvxaLRWGI+O53v6t4L/l4WIz4TfaYTwrHRx99NOvxbDabZMQrRvy2trZKBkmPx4Pf/OY3OHbsGOLxOMxmMzZt2oSNGzdienoae/fulV6fa7yUG9unpqYQi8UQiURw5MgR9Pf3K0JV161bh49+9KN45pln8NZbbwEAXn311Yww2aSg0uv16OnpkdZj6Z+5GPGbPgd1d3dL3+GGDRukc3nooYfgdDrR1NSk+CcfW+fm5nDgwAH09/cr5ukbb7wRDocDDz74IADg3XffRV9fH9ra2qTq4Mn7NvlvampKWm/odDo0NDSgrq5OGlOSv4nJyckFtRbSarVYs2YN+vr6pPt6YGBAGssYY/jQhz6UV/V7ORqNBjfffDN+9KMfgXMupdNs2rQpY99YLAa32y39hg0GAzZs2CAZgdWQz13JsbCzszPj3knWS+ju7pbE79GjR1FbWytd6w0bNkhr3WqiqsUvgP8AEAHQBGALgKcYY/s45weX9KyKpL+/X/WH+Morr6C5uRlms1mxQIhEInjxxRfx1ltv4cILL5QG6Wg0isnJScVkVwpOnz6dV27L5OQknn/+eTz//PMZ24oRUna7HXa7HV6vF7FYDP/4j/9Y8DFCoZAijFg+uJvNZmkSi8Viikb2Y2NjGBsbw86dO/N+r0AggD/84Q944403AJSmbUH6dZML2e7u7rwEgnwATjdayCd4nU4Hl8uFmZkZGI3GgsNOAeXCKN2LMTw8nJex5Y033oDL5UJTU5MivBAQJ6/R0VHFd6VGrntRbojRaDRobm6WRMaRI0cKDlmcm5vDa6+9htdeey3nfjqdDh/72McKXjz29PQohGEuz+982Gw2fPCDH5TEWj7eXjWam5vzFvBJrr/+ehw7dgyhUAjT09P4p3/6p6z7FnPvAaLBLCl+f/nLXxZ1jEgkkte9arVaccstt8BqtWLdunXSffPzn/+8qPf1er14/fXX8frrr+fcLxwOY+/evYqFdZJ878X5mJ6eLrgqeENDQ177qUXcJFm/fn1B7zkf3d3d0vXcs2ePVHBNr9dLC/GkcSxpjCukuI7cq2W1WtHe3i6Fpg4MDJS032nyeJs2bYJOpyv5PJ8vxRYjW7VqlWSISBfZ8s9QbH9nufiVzw/p55vNAJ6OfG5M3i/Jv1taWqQ54/Dhw9J+wWAQb7/9tiIyJEl6cUg5cvG7f/9+7N+/X3W/+vp63H777dBoNLjhhhswNjamujZraGhQfO4NGzZI4jf9d2qz2aQxM99rny5+5bUpNm3apBBTyWgCeWrDfGzZsgUXXHABGGOKiIqf/exneR8juaabb61QDPF4HIcPH1Z893Iuu+yyeQuRZqOlpQUXXXQRdu/eDUA05MiNObnYtWsX6uvrFU4bQRAUhi5AFO9Jw/DKlSslBwCgLFCX9ABzzjE2Nobf//730nvZbDYSv4sJY8wK4A4AmzjnPgCvMsYeB/BpAH+1pCdXBnK17PD7/Yo8wmJgjKGlpUV1IRuPx7O2GbJarZIwS/4wsoUfJ8MniqGtrS3rAAOIg3W2hbJaCJd80NZoNHA6nYpFXvI6FLqgkIempoveXOeYi9bW1gyLn3yyzifkGRAnO6fTmXEtjEZjRjGGW2+9FW+//Ta2bNkybyEtNfR6Pdrb2xUTssvlwtzcXEGh3+nhnoD42efLI9ZoNNBoNDk9memT/0033YQnn3yyqDxRg8Gg6i3RaDRoaWmRLM56vR7bt2/Pmf+TjTVr1uCPf/wjAPEaZMtRy5e1a9fiwgsvlLwGyePW1NTkZUwxm8244oorCn5fm82G6667Dk888cS8+6oV+sqHtrY2VVGYjcbGRsmglPTkqIX3psMYw2233SYtMN7//vdjaGgo7yrayTDnJG63WzVCJP0+mpuby2pUy3Yv5voMtbW1CmNMMBhUFYBOpzNrxAFjDN3d3XmHxKkZb0wmE84///y8x7R8aW9vV4R8JolGoxgZGVH1rGcj/RqsWLEiI8XgAx/4AJ588sm8e8DKkd+LcgRBUJzngQMHCj52viRbhmXzvjc2NuLCCy8s6tibN2/Gnj17pHvLYDBI829yvNZoNEWLBqfTmfF9rl69GldddZXiuXzFr1wIrly5UrFGam9vz3gvo9GYNa+8q6sL73vf+7K+13zOgeQa6uabb5aM2VqtFh/72Mewc+dOxRrGbDZnvNfGjRsxOTmJ2dnZjHD8fK9H+mvkvyv5eN3c3Iz3v//9ePfdd/OOGkmi1+uxdetWXHfdddJclBxb880frq2tRTQandewm2tMy0UwGFSk/6SzcuXKnN91Plx11VU4ePBgUcZpt9uNl19+Oec+7e3t0n2UXLMlDeyrV69W5IS3traqjpPlaB+3GLBqKx2ehDG2FcDrnHOz7Ln/AuB9nPNb0va9C8BdX/3qV7cBwD333LOo55ov+/btUyw2BEHA8ePHcfToUUmEMcawZcsWXHHFFTh58iRefPHFeXuBaTQa1cUsYwzNzc3o7e3Fxo0bcw54Pp8PBw4cwP79++Hz+dDR0YHe3l7FDwQQvRHJEJ2zZ8/C4XBIlvU1a9bk7RVIZ3R0FA8//LBiwWcwGLB27Vr09fWho6Mj60QtCAKGh4el6nt1dXX4+Mc/rhB1+/btw3PPPYfa2lr09fVhw4YNYIzh0KFDUhhttt+K0WjEunXr0NfXh9bWVrz99tvYtWuXtHhOioQLLrig4GJf2Th58iQef/xxrFixAnfccUfeIYLBYBDHjx+X7qdkZeBirey5CIVCOHnyJGw2GxobG2EwGOD3+3Hw4EEp5LO2tlYKXU4u+DjnGB4ezggx7OnpwTXXXIPm5mYEAgFFmF4y1Km+vl66n3U6nXQvnj59WjH5rlq1KuMeSOJ2u6VwerW8tyR1dXXYtGkTent7YbfbpZDr4eFhuFwu6T5Sa5VRLM8//zz27duHq666Clu3bl3w8Tjn0mTX1NRUVKhhMQiCgCeeeAIHDhzIyGNOjhft7e2SxblQIpEIHnzwQdWiOkmSKSV9fX0Zi85kq5Hx8XHV1I4kzc3NCvEKiKLk6aefzroA1mg06OjoQF9fH9auXaswYsTjcQwODmL//v04deoUnE6ndB+lR1OMjIxIobJGoxEbN25Eb28vHA6HFEZ74sQJmM1m6ZqmG/3q6+vR0NCg+juIxWKYnJzE1NQUbDYbmpqaSlZjIsnOnTvR39+PlStXoq+vDz09PSUbI9PZs2cPXnjhBel74ZznXJDL5zWz2Yz169ejt7dX0a92PqanpyUPXq52OMl7sbe3N6dHdWxsDM8//7yqJznbPA9AEXKa9BaPj49jdnZWiq6R/yumzVAhTE5OYnp6WjLIJo3GU1NTcLvdqKurK3qtMDIygkceeQQGgwGbNm3Cpk2bVGt3HDhwAA8//DAAsUDg5s2bVY+XrK48OTmJ22+/XWEonpmZwQMPPIBoNCqlIDQ0NOD06dNSGoLFYpG+23yidXbu3Ik9e/YoDO+NjY1SGsNCIn5y8fbbb+Opp54CAHzyk5/M2/C4e/duvP7667jwwgtx2WWXqe4Tj8elqAp5iL18bNVoNFi1ahU2b96cMS4m2b9/P/7whz8oxlaj0SilPiX/NTQ0SK8PBALSvZ4k2XVELWe3ECYnJ9Hf349Dhw4hHA5L6QQrVqzApk2bCo6KUuPkyZN45JFHss5Dyc+SXEd5PB4cPnx4XiOB3W7HRz7yEYWRSX4P3HbbbdiyZYu07fTp01JqpvxaNzc3l70OwQJRHciqWfxeDuC3nPNm2XNfAvBJzvmVaq/ZsWMHBypX/GYjmZs7NTWF3t5eRdhMNBrFvn37FNYXxhjq6uqkH0MpF99EfoRCIbz77rtgjGHr1q0lXzSeCyQLZZw5cwY9PT0ZeZsEQRALQZ4v6PV6FfNmoXl6i8mpU6cwODgIq9VK83yRCIKA9957D5xzbNmypSRCpZqJxWJ49913YTQa0dfXV1bjB1FewuEwjh49muG0sdvtCkNo+ncsCAL27NkDjUaD8847r6R1F5aQZSd+twJ4jXNukT33FwCuTPf8JkmKX4IgCIIgCIIgCGL5cs8992QI4GqW9ccA6Bhj8tiMzQCqstgVQRAEQRAEQRAEUT6q1vMLAIyxBwFwAF+EWO35aQCXVGu152qBMbaHc67eRJQgKgS6T4lqgO5Tohqg+5SodOgeJfKlmj2/ALADgBnABIAHAHyVhC9BEARBEARBEASRTtW2OgIAzvkUgNuW+jwIgiAIgiAIgiCIyqbaPb/E0nDvUp8AQeQB3adENUD3KVEN0H1KVDp0jxJ5UdU5vwRBEARBEARBEASRD+T5JQiCIAiCIAiCIJY9JH4JgiAIgiAIgiCIZQ+JX4IgCIIgCIIgCGLZQ+KXIAiCIAiCIAiCWPaQ+CUIgiAIgiAIgiCWPSR+CYIgCIIgCIIgiGXPOSV+d+zYwXfs2EG9nQiCIAiCIAiCIM4xdEt9AksECWCCIAiCIAiCIIjlCVN78lwVvwRBEHkRDJ7ByVP/gbm5fbCYV6Oh4XrU1V0Jvd6x1KdGEARBEARBFACJX4IgCBUiETdOnLwHZ848AM4jAACf7wgmJv8AxvSoqdmOhobr0VB/LfT6WszO7sHE5E7MzLyJeDwkHUevd8Fh74XD0QuHYwsslk4wpmqMJAiCIAiCIMoIiV+CIIgE4fAEJt3PYXJyJ6and4PzqOp+nEcxNbULU1O7cPTo30KrtSEe96nuGwwCc3PvAWfExy7XRVjT899ht28o06cgCIIgCIIg1CDxSxDEOUk8HoLXdxBzc/2Jf/sQDJ5S3dfh2IpV7V+CP3Ack5M74fUeSDuWuvBVY2bmTbz19gfR0vJRrFz5eej1NdBprYjF/fDO9WN2bh/CobNwus5Hy4oPgzHtgj4nQRAEQSxHYjEvPJ6XMTn5LIKhM3C5tmFV+5dhMNQu9akRFQzj/Nyp/ZSs9HzPPfcs9akQBLEA4vEgTpz8PqY8u8ARTzzLYDQ2wWrpgsXSCYOhFrGYH/G4H7G4H/GYF7G4H7GYF37fMfj8R8F5LOf7OBxb0NGxA/V1VytClUOhs5ic3InJyWcxM/s2OI/DaGhCfcN1aGi4DmZTKwCAc45QaEQS156pV+Z9T8X72/uwbt3/Ii8xQRAEcU4Qi3nh9w/A7x9CIDCIaHQGZvMqWK2dMJnbEQqexlzCUDwzs0dKS0qi1drQ3v4naF/5Beh0tiX6FJVDNBrFyMgIQqHQ/DtXKSaTCW1tbdDr9embVHPMSPwSBFFV+HzHcODg1+H3D5T82Izp4XJuE3N5G66DydQy72ui0ZnE5NwOxnJ3j/P7BzFw/H/B43m5gHPSYuXKL6Cr85vQaAx5v44gCIIgKh1BiGJm5i1MTb+OqanX4PUeBCAs+Lh6fS06Vn0Fra2fhFZrWviJViknTpyA3W5HXV3dsqw3wjmHx+OB1+vF6tWr0zdTtWeCIKoXzjnOnv0Njg38TwhCaSyYFksXHI4+OByb4XD0wW5bB43GWNAx9HoX9HpXXvtarV3YsvmncLtfxOnTP0YodBaxuC8RNq2B3b4BDsdmaJgewyM/gyBEwHkcp0//CH7/MfRu+g9otebCPyhBEARBVBDh8DjOnHkAZ84+iEhksujj2Gwb0NBwPcymVpw89UMEAscBANHoFAaO/yNOD/8Uba2fQiw2B39gCMHgaRj0tbBYu2C1dMLu6IXTcd6yFIYAEAqF0NHRsWw/H2MMdXV1mJzM/x4i8UsQRMUTDA7jyNG/xdTULuk5jcaEnu6/htN5HgCA8xiCoREE/IPwBwYRj/uh1Vqh09nE/7VWaHU26LQ2mEwtcDj6oNPZl+Tz1Ndfhfr6qxTPcc4Vk1NLy0dx+MjfYGbmTQCAx/My3tv3BWzuu3fJzpsgCIIgCoXzOObm9sHnOwZ/YBB+3zFMz+zOkgakgdXaLf6zdEGvr0EgeBIB/xCCodMwGpoko7XTuVURodXcfCvGxh7F0Il/RSgkVpkMh8cwOPQdxTv4AUzP7JYe2+0bsWrVV9HYcP2yrLOxXIVvkkI/H4lfgiAqFkGIYHj4Zxg68a8Kb6/VugabNv0bbNYexf4OR+9in2LJSB+8LZbVOG/rrzB04v/h5MnvAwBmZt7Cu3s/jQ3r/xlWa/eynKQJgiCI5YHPdwyjY49gfOxxhCPjWfczGBrR2HgDamsugcu1HXq9o6j3Y0yLFSvuQFPTzThz9jc4efI/EIm4532d13sQBw7cDYtlNTo7/wKNDTcue8F4LpOX+GWM3Q3gcwB6ATzAOf+cbNs1AP4DQDuANwF8jnN+KrGNAfgnAF9M7P4TAH/JE4nGjLEOAPcBuAjAaQB3c86fkx37EwD+N4B6AM8C+ALnfCqxzQjgPwF8GEAAwP/hnP9LoReAIIjKQBDCCIcnEA6PY25uH6amX8fMzNuIx/2yvRja2j6N7q6/PCdyeBhj6Or8BnQ6G44f/ycAgNe7H2++dRO0Whsc9k1wuS5EQ8N1sNnW02RNEARBLDnxeAgHDv4Z3O7ncu7ncl2ItrZPo6H+Omg0GcWKikajMWJl22fQsuLDOHP2N/B5D8FkaoXF0gmLpQORiAf+wHH4vEcwMfkHCEIYABAInMCBA3ejvu5qrF3793nV/SCqj3w9v2cB/AOAGwBICWeMsXoAj0AUt08A+J8AfgNge2KXuwDcBmAzAA5RwA4B+EFi+wMA3gBwU+Lfw4yxHs75JGNsI4AfAvgAgHcB3AvgHgB3Jl77bQA9AFYBaAbwImPsEOf8mbw/PUEQS0os5sPp4ftw9uyDCIfHcu5rs63DurX/C07nlsU5uQpiVfuXoNPacOTo30IcSsX2StMzuzE9sxsnTv4bTKY2NDbcgLa2z8Jsbl3aEyYIgiDOSTgXcPDQX2QIX72+DrW1l4gdGazdsNvWw2LpKOu5aLUWtK/8vOq2eoipR92R/4bh4Z9hZOQXUttCt+cFTL+5G6s77kZr6yco1WgRiMfj0GoXJ5qtoGrPjLF/ANCW9Pwyxu6C6Om9JPHYCsANYCvn/Ahj7HUAP+Oc35vY/icAvsQ5384YWwNgP4B6zrk3sX0XgF9xzn/AGPtHAB2c808ktnUBOAygjnPuZYydAfB5zvnOxPb/CaCHc54UxxlQtWeCqAzi8TDOnPkVTp76T0SjUzn3NZna0Nb2Kaxs+1xJLcPViMezCyNnfom5uX1ZC4QwZkBr68fR0bEDRkP9Ip8hQRAEcS4zcPx/4/TpH0uPGxpuQMuKj6C29rKKnsOj0TkMDn0HZ878SvG8VmtBc/NtaG35BGy2tfN2dag0Dh8+jPXr1wMAnn+hq2zvc83Vg1m3nTx5EjfeeCMuuugi7N27F2vWrMH999+PDRs24Atf+AJ27tyJu+++G7W1tfi7v/s7hMNhdHV14b777oPNZsNf/dVf4fHHH4dOp8P111+P73znOxnvIf+cMspS7XkjgH3JB5xzP2NsMPH8kfTtib83yl47lBS+Wba/Ljv2IGMsAmANY2wIQIvKsW9TO8mESL/rq1/9aqGfjyCIEuP3D6J//5cRCJxQPM+YFgZDA4zGJpjN7ahxXYTa2kthNrcv0ZlWHnV1l6Ou7nJwzhEOj2F29h1Mup+H2/2CZLHmPIKRkZ9jdPS3aG//EjpWfbngCtYEQRAEUSgjI79SCN+VbZ/DmjV/u4RnlD96vQPr1v4PNDffiiNH/kZqpxiPB3DmzK9x5syvodGYYLGshtXShZaWj6G29pIlPuvq4ejRo/jJT36CSy+9FF/4whckR6TJZMKrr74Kt9uND33oQ3juuedgtVrxz//8z/iXf/kX3H333fj973+PI0eOgDGGmZmZBZ/LQsWvDUC6+2EWgF22fTZtmy2RC5y+Lbm9Nctr5ce2yR6rva+ChOf53qTnlyCIpWFq6jXsP/A1xGIpm5fJ1IrO1X+GpqZbodFQDb58YIzBZFoBk+lmNDXdDEGIYGrqNZw8+R+YndsLQJywT5z4V4yPP4F1a/8BNTUXZRwnHg9ieno3TKYW2GxrF/tjEARBEMuEsbHHcPTYt6XH9fXXoqfnr5fuhIrE5dyGCy94HGdHH8bIyC/g9x+TtglCCD7fYfh8hzE+8RQ2bvgumptvXcKzrR5WrlyJSy+9FADwqU99Cv/2b/8GAPjYxz4GANi9ezcOHTok7ROJRHDxxRfD4XDAZDLhi1/8Ij7wgQ/g5ptvXvC5LHSl6QOQXpLNAcCbZbsDgI9zzhljhb5Wvt0nexxK20YQRAXBOUck6sHE+JMYOP6P4DwOANBozOju+q9obb2TPJMLRKMxoL7+KtTVXQm35wUMDX4XPv9RAEAgMIR3934CjY03wek8D1ZLFxjTYmz8cUxM/EEqKFZbezk6Vu2Ay3UBFc4iCIIg8oJzIdGV4D+k5+z2Xmza+L2q7Uig0RjQ1voJtLZ8HDMzb2HkzC8xPb07LU2L49Dh/wqN1oTGhhuW7FwLIVdocrlJX1ckH1utVgDiWvG6667DAw88kPHat956C88//zwefPBBfP/738cLL7ywoHNZqPg9COCzyQeJnN+uxPPJ7ZsBvJV4vDltWydjzC4Lfd4M4Ndpr00euxOAEcCxRM7vaGL7syrHJghiCeBcQCAwhLm5fszN9cPrPQB/YAixmDKIw2hoQt/me+Gwb1qiM12eMMbQUH8N6uuuxMiZX2Nw8DtSOPTExNOYmHg662unpnZhamoXnM7z0Ln6z1Fbe+linTZBEARRhcTjARw69P9hYvIP0nMWSzc29/0IWq1lCc+sNDDGUFNzkRQ5FY3OwO8/jiNH/xZ+/zFwHseBA3+OzX0/RF3dFUt8tpXN6dOn8cYbb+Diiy/GAw88gMsuuwx79+6Vtm/fvh1f+9rXcPz4cXR3dyMQCGBkZAQtLS0IBAK46aabsH37dnR3dy/4XPJtdaRL7KsFoGWMmQDEAPwewP9ljN0B4CkA3wLQzzk/knjp/QC+yRh7GmKJ0r8A8O8AwDk/xhh7D8DfMcb+O4D3A+gDcEfitb8C8AZj7HKI1Z7/B4BHZEL5fgD/nTG2B0ATgC8BUC/pRhBE2fF6D+LAwT/LyOVNx27fhM1998JobFqkMzv3YEyLlW2fRkPDdTh27O8xObkz674mUytCoVEAAgBgdvZd7H3vM6ipuRhdnd+EXl+HQGAI/sAgIhE34nE/YjEfwAU4HH2oqb0UNuuanEVA4vEQpqZfw5RnF8A0qK+7EjU126HRGEr90QmCIIgyEot54Xa/iEn3s/B4Xla0I6ytvRy9m/592VZH1utdcLnOx9Yt9+Odd+9EMHgSnEfQv/+r2Nx3LxmNc7B+/Xr8/Oc/x5e//GX09PTgq1/9Kv793/9d2t7Q0ICf/exn+PjHP45wWGw99Q//8A+w2+249dZbEQqFwDnH9773vQWfS17Vnhlj3wbwd2lP/z3n/NuMsWsBfB9iy6Fkn9+TidcxAP+MVJ/fHyOzz+/PkOrz+zWVPr//BKAOwHMQqzur9fkNAvjn+fr8UrVngigPk5M7ceDgNyEIQdXtWq0VFksnamsvw+qOr0GrNavuR5SHmdl3MDu7FwH/IPyBQUSjs6ituRjNK26Hw96HYPAkTp26F6Njvwfn0YKPr9fXwunYAou1C1ZLF/R6V6Jn8xj8gUFMTe1CPB5QvEartaG+/mq0rPgwamouUYREBYMjmPP2w+8fRCAwiFDoDHQ6B4zGJhiNzbDbN6K+7sqqDakjCIKoJsLhyf+fvfsOb6S6/gb+HfVmufdub+8NWJYOoYbeE3pN2AAhQAghQCCBvPxoKZCl9xY6BBJq6Gzva697l7slW73Pff+QPJ6xZa+7JPt8nmeflUYj6dqWZubce+656O75At3dn6O3d3PE80Re3iWYO+fOWVO7w+Npw44dF8DjbQMQSpVesuRxpKcdF+WWSQ1TBXlaNTY24tRTT0VZWdmUvcdYqj2PaamjeEfBLyGjwxgPr7cDSmXyiIEqYwzNzU+jtu4h9K8/K5frkJy0FkbjMhiNy6A3zIdalUnzSOOAx9OOhsbH0N7+jjA3ezrodKXIzf0ZAn4bunu+gMNRccDnaLVFKCr8BbKyzqQRZEIImQI870Nd/SNoaXlh2HOCVluAosL1yMk5b5pbF30uVyN27roIXm8HgFDW1aKFDyMr6/Qot2wABb9DUfBLCBHwvA8dHR+gqflpuFwN4Dg59Pr5MBqXwqCfD7U6C2p1JoK8Gz3dX6K75wt4PK3C87WaAixf/gz0+onPySDR43I1oL7+b+gxfyWM2uv1c6BRZ0OhSIBcrkeQd6O3d1OEIiCR6XTFSE87Hjzzo7v7c8nnZiLU6izkZJ+HrKwzodMVAQB43h8q+MUYEhKWUMcLIWTK2e37YbXthlaTD6NxKZTKpGg3aULc7maUlf0aNvveIY8lGBYjPf14pKefAL1+3qw+xrrdJuzadQncnubwFg46XanwO9FocpGcfChSkg+LyjrBsRD8TgcKfodBwS8hkfF8AK2tr6Gp+WmhB3OskhIPwtKlG6BSpUxy60i0MMYOeFHDGA+nswZOZy2crjo4nbUIBh1QqzKhUmdAo85CYtIa6HVzhNdijMHh2I+29rfR3v6+UJSrH8epkJx0MAyG+dDpS6HVFiAYsMPj7YTL1YCOjvcRCNiGtCXRuBIMgMNRDp73AQDS00/Egvl/hkqVOjm/FEIIEXE4a1Bf/+iQ2gpabSGMxuVCFpRBvwByuQ4cx4GxIKzWXeju/hxmy3fgOCUyMk5CdtZZ0GhyovSTDOjo/AiVlXdKjs1G4wpkZp6K9LQToNXmjvDs2cfr7cSu3ZcJawMPR6VKR2nJzcjOPm/aOgwqKiqwYMGCGd1BwRhDZWUlBb+RUPBLyFA2215UVP4BDsd+yXaZTB0OIEY+RigUCcjJPh+lpbfQkkVkzAIBBzo6PkCP+WsoFYlIS/8JUlOOhEJhGOE5drS2vo7mlufh8/Uc8D2UyhQsXHA/0tNPmMymE0JmsUDAjurqP6O94z0c6DzZj+MUkMv1AHjJevdiyUlrkZV9FjLSTxrxOAiEOh89nla4XI1QqVJgMCwaMchxu1vgdNZCpUqFWp0FlSpVUjvB7+9FVdU96Oz6WNRmJeaU/hb5+VdM+6hlPPH5LNhXdj36+rYccN/U1GOwcMFfoFZnTHm7GhoakJCQgNTU1BkZADPGYDabYbfbUVxcPPhhCn4p+CWzncvVALPlezA+EL5fj9a2N9Ff6RcAVKo0FORfidzcnwMAbPYy2Gx74XG3wOvthNfbiSDvRXLyIUhPPwHJSYdAJlNG48chsxzPe9Hd8xU6Ot6H2fwtGAsIj6nVWUOyGHJyLsD8effQHGFCyIR4vZ3YvedKOByVku0pKUfA7++Dw1E5ruKBYjKZFhnpJyIxaTUUcj3kcj143gOnq14oXuhy1YPnvcJzDIaFyMu7BFmZp0vqdQQCdtTVPwKT6VWIA3WOU0CvnwujcRl02qJwh2K38LhWU4AlS/4Oo3HZhH6W2cTtbkYw6AEAMBaAzbYXlt6N6O3dJJkipFAkYeGC+5GRcdKUtsfv98NkMsHj8Uzp+0STRqNBXl4elMoh16IU/FLwS2Yrxni0tLyA2rqHhj0hy2RqFBfdiPz8KyCX0wguiS8+nxm9vZsgl+thNC6DSpUKs/k7VFTcDq+vU9gvKelgLF3yzyHp+YGAEy5XPdzuJoCTCRebanX2qFL8RpMiPlmm870IIVJOZy12775CqPILAKmpR6G05BYkJCwGEOqYszsqYbPtCf/bC7fbBMZ8wnNUqjSkpf0E6enHI+C3ob3jPVgsP0LcGT1eCkUCkhIPgtG4DEpVKhob/znmKU3Z2edi3tw7Z+yyRdMtGHSjru5htJhelGwvLroBxcW/pmP61KDgN9aD30DAAYDRgYZMKp/PjP0Vt8Fs/mbYfVKSD8f8+X+CTlc4fQ0jZBr4/VZUVd0tSePTagtQWnIrXK562Gx7YXfsH/HCUK+fi/T0E5Ce9hPo9fOFziGvtxMdnf9GR8cHcLtbkJ19NooKfwW1Oj1CO2zo6voPrNZdUCgShGWblMpkKBQGyOV6KJRGqJRpEZcKCQTs6Oz8D9o73ofdXo7MjJMxZ87tNJeZkGnUZ92BPXuuRSDQByBU3XfBgr8gJ/vcUT2f570IBJzgmQ9qVcaQNGKvtxMdHR+iveO9A84f7adUpkCnLYTdUQGeP/DonsGwCGBBeH1d8Pt7hzyuUqVhwYK/xNySPTOFpXcTKvbfJuk8ycg4BYsWPgS5XBPFls1IFPzGevBbV/cIWtveQGHhL5CXewl9CciE+P29aGt7C80tL0jSmBISFiMp6WAAAAcZkpIOQlraT6jXkcxYkZbkmgilMhlKZQpcrgYMHqWRybTIz78MyUmHIBB0IBCww2L5AT09XwpFuEYmg0qVBrU6Y2AOPeNhFxXx6qdQJGHu3N8jO+ucEb+/PO+D290MjpNDqy2i7zoh49Dd/QXKyn8tpBnL5TosXfI4UlOPmvT36i8K2NX9OXy+bgQDTgSCTnCcDDpdMfS60vC66iVQKpMBhDr62tvfhan1FbjdzUNeU6lMxbx5dyEz41ThGBAI2GGz7Qt1AtrLoFKlobj4RipcOcX8fhvKym+ExfK9sC0hYQlKS3+LlOR1NLd68lDwG8vBr9fXg02bjkEw6AIAqFWZKCq+HjnZ59F8SjKi0EmyAg5nNYIBBwJBJ5zOGnR1/WfIxXJBwdUoLbmF5jySWam7+3OUld8MnncPeYzjFNBqi6DTFYHjFOHvkgMOR4VkTl0sEldh1Wiy4XBUobd3I/r6tsHpqoXb3Sys0alSZSAl+VAkp6xDRvrJUCj0UW49IbHP1Po6qqr+iP7OLqUyBSuWPxeTc2EZY3C56mCz7YXNthcuVz0MCQtRVHhd3C+/NJPwfAA1NffB1PqKZLtOV4ycnAugkBsQCDoQDLphTFiKtLRjotTSuEbBbywHv1bbHpSV/RoeT4tku05XjEWLHkGicXmUWkZiVSg96gO0d7w/ivL6aVi44AE6eJJZz24vR3X1n8EzH4wJoSVIEoxLodMWRexoDAZdMJu/R3fP5+jt3QKfr0sIJIGByqxKRRLqG/4+pGq6WELCYmRm/BQAJxSP8wesCAadCAQc8Pv74Pebh3++YTGyss+CRp2Nmtq/RFwrWS43DFk6ajgaTT6WLPk7nV8IiYAxBqerFq2tb8BkeknYrtUWYMXyF2maEJkULaZXUFPzZ8l5JZKS4t+gqOhXlLkzNhT8xnLwC4RS09ra3kJD4+OSNFWOU6C09LcoyL+SUiEIAMBkeg3VNX+SVLeNJCFhCfLyLkFmxqmURk/IJGAsCJ/PDK+vC2pVOtTqTNFjPLq6/ov2jg/AeB/kCgMUcj3UmhxkZpwCg2H+AV+f533weruHBNkqVSp0uoFlHIJBF+ob/o6WlhcOeNEEABpNLgIBBwIBq2R76PxyKwryr6LzCyEIpQI3NT+Drq7/hqc2DEhIWIoVy5+FSpUWpdaRmcjlaoDJ9Cra2t8ZsfOyoOAazCn9HQXAo0fBb6wHv/2CQTdMppfR0LhB8iVIST4MBsOCcBqES3LBo1ZlIC/vYsnFEZmZOjr+jfL9v5Fsk8m0SE09AiplKuQKA5QKI5KT18FoXE4HSUJmMK+3G909X6C7+3P09m4GY34olSlITl6LlOR1oSVMdCWQy7VgLAi7vRwWyw9obHpKcn5JTl6H0pKbkZi4Moo/DSHRFQjYsWvXpbDZ9w55LDXlSCxZ8jhNFSBTJhBwoqPzQ1itOyDjVJArDLDb9qHPuk3YJzf355g/717qrBwdCn7jJfjt53a3oKz817DZ9oxqf46TIzv7XBQXXQ+NJmfEfXneD4ejUjKXTa3OglabN6E2k6llNn+PPXuvEZYrMujno6DgKqSnn0QnZEJmuUDADr+/DxpN7gEvjIY7vyQlHYL8/MugUoaqSHOcDAbDQsmaoYTMRMGgG7t3XyEJNORyHVJTjkJ6xonIzDgFHCePYgvJbMTzXpSV/RrdPV8I2wryr8LcuXdEsVVxg4LfeAt+gVAKXF39o2hufmbUz5HJVMjMPAPZWWchKekgcJwMPO+Fw1GFvr5tsPT+iL6+bUJxLbGMjJ9i7pzbhwTPPO9FT8836Oj8AB53KwwJi5CSvA7JKeugHib9h+e9cLka4XTVw+NuhlZXhPS0n9DJY5xstr3Yuesi4e+m18/F6lX/ogIWhJBx4Xk/6usfRVPzMxipCrZOV4zVq96kZZXIjMXzXuzZ+wtJ9d25c+5Abu5FNGWIRB3P+1FR8Tt0dH4obFu+7BmkpR0bxVbFBQp+4zH47We17YHF/D1kMpUwj6w/iORZAO3t76K3d+OQ52k0eVApU2B3VEoWVx+JTKZBQcFV0Gry4PF2wONuQXfP/4bMFesnl+uhkBsgV+gByBAMOhAIOBAMOjH4giohYTHmzb0bSUlrxvTzz3Y+nxlbtp4Cn68HAKBWZ2PN6reh0WRHuWWEkHjncFSjqfkpdHZ+NOz84aSkg7FyxUtUKZ7MOIwxlJXdgK7uT4Rtc+fcgYKCq6LYKkKkGOOxd+8v0GP+CkBoyb2DD/4YGnVWlFsW0yj4jefgdzQslh9RV//IqNOkNZo8oVgLz3tht5dNZfMkMjJOQXb2OUhKPIjSdUehrPwmdHZ+BCC0tuea1W9Cr58T5VYRQmYSt9uEFtOLsNn2IdRxyWC17kJ/J2ZOzgVYMP9+qiNAoioQcMDr7YJCaRw282wsWlvfQGXVncL94uJfo6T4xgm/LiGTzeezYOu20+D1dgAITVNZtfIVyqgcHgW/Mz34BUI9mDbbHrR3vIfOzo8lo7VabSGMxuVITjoEKSnroNUWSJ7b27cNNdV/ht1RHvG1NZpcZIVTqa3WXejt3QirdZcw/3QoDhpNLvT6UqiUaejs+njIepkcp4DRuAJabT4UCgPkcgMY7xOWAeGZD2mpxyA//wooFIYJ/W7iVXf3F9i775fC/eXLn0Na6tHRaxAhZNZobHwSdfUPCffnzb0b+fmXRbFFZDIxxqO3dzO6e76ERp2J/PyrIJMppvx93W4Tens3wtK7EW63CYnG5cjOPhsGw6IhnSuBgB0m02vo7Pw33J5WSaG21JQjkZd3CVJTjxoSADDGEAjYALBhpwe53S3YsvUUYTpRbu5F4WJC1MFDYlNv7xbs3HUx+tecLsi/CiUlt0AuV0e3YbGJgt/ZEPyK8bwXvX3bAMZgNC6BUpl8wOcwFkR7x/sw93wDmVwDtToLanUmEgwLkZi4akgRFcaCCAZd4SU07AAYFIoEyOV6yOV6yUnU42lDTe0D6Or6z5h/FqUyBUVF65Gb8/NZ9QX3+63YvOUk+HxdAIDsrLOxaNFDB3gWIYRMDsYY9u+/RTTXTIbly5+hDrg453I1ob39bbR3fACvt13YnpFxChYv+uuUBcA9PV+jru4hOJxVER/X6+chNfXI8LVHFuz2cphMrxxw7WqNOkfIZGMA/H5LqAOd9wAIrZGdnn480tNPgF4/DxzHgTEeO3ddjL6+LQAAna4UBx/0b5rjS2Jeff3f0dD4D+G+SpWOgvwrkJv7cygUCVFsWcyh4He2Bb+xymrdhc6u/6LX8uOwJ8DhhBaXfwE6XdHUNC7G7K/4Hdrb3wEQOritPeRTKnBFCJlWwaAXO3f9TJhSI5NpsWrlq0hMXBHdhpExYYyH2fwtTK2vwGz+DsMVOZuKANjprENN7f0wm7+d8GvJZCqoVOnweNowUqG24Wi1BUhPPwEA0Nz8LIDQahmrV7+NROPyCbePkKnG8wHs3nM5ens3SbYrFIkoLLgW+fmXQi7XRal1MYWCXwp+Y4/P1wOrdRf8fisCQTuCAQc4TgG1OhNqdSY8njY0NPwDHm+b8By1OgurVr42owPgYNCLxsbH0Nj0hLBt2dInhBM2IYRMJ6+3C9t3nAuPpxVAqNjK6lVvQq8vjXLLyIG4XI3o6PgA7R3vw+MxDXlcqUyGQT8fvX2bhW2hAPhRyGTKCb9/W/s7qKz8AxgLCNtkMg2Skg5CSvI6aHWF6O76DF3dnwkjtYPpdCUoLPgF0tOPg0KRBI7j4HY3w9T6Gtra3h6hIKcOPO8fYXpWSFHRr1BacvP4f0hCplkw6EVr66tobn4OXl+n5DGVKh1FRb9CTvb5sypbMgIKfin4jU8870Vr679QW/egcGIUB8CBgAMeTxs0mpwZMS/YYtmIyqo74XY3CdsyMk7B0iWPRbFVhJDZzuVqwPYd58PvtwAIpZrm51+OQNCJYMABlTodxoRlSEhYQoUMo4jnA7Db98HSuxFm8zewWndG2ItDaupRyM25AKmpR4PjlKiu+TNMppeEPfLyLsH8efdMqC0eTzs2bT4ePO8W3jcn5wKUltw8ZOmsQMABs/kbuNxNQt0PjpMhK/MMpKcfP2xRn2DQA4ezShJcKxRGaNRZkMsNCAYd6DF/g+7uz2E2fxteiWKAwbAQB615jyqZk7jE8150dHyIxqYn4HY3Sx5TKBJCBWazzkZi4urZOJedgl8KfuObpXcT9uy5WgiAFYokyOUaoeodx8lhTFiG5JR1SEs7LqbTlwIBO4JBV3hutA4ejwld3Z+ju/sLWK3bJfsmJq7B8mVPUbozISTqrLY92LXr4ojrxA+QwZiwBHPn3YmkxNXT1rbZjjEedfWPjjhHVqFIRE72ucjNvQg6XeGg57NBATCHg9a8B6Nx2bjbVL7/FnR0fAAgtF70ksX/QELConG/3kQFg1709m4MBcKW7yCXG7Bs6QbKYCBxj+f9aG9/Fw2NjwnXxWIGwyIsWfx36PUlUWhd1FDwS8Fv/BscAI8kJ+cCzJt7F+Ry7TS0bHS83k7U1j2Ejo4P0V+pL/TdHPo9VCgSUFp6G3JzLhxSaIwQQqLFbP4Oe/ZeIxlpi0Qm02DZ0g1ITT1qmlo2u9XVPSyZKtOP4xRITT0a2VlnIS3tGMhkw6dBMsawZ+/VMJu/AQAYjSuwZvXb4zoH2Wx7sW37WcL9lStfRUryoWN+HULI6AWDHrS2vgZT66tDRoLlcgMWL3powlPoXK4mNLc8j3lz75yUqRFTiIJfCn5nhlAAfI2QRsVxSqjVGcJcNDG9fi6WLP4HDIZ5U9omnvejr28r7PYyaLVFSE09QlJsIBh0oaXlZTQ2/fMAIyYAIENGxsmYN/dOqNUZU9puQggZD0vvJnR1fQKZTBXKYJFp4XY3wWbbA4ezBv2dexynxJLFf0NGxknRbfAM19Hxb5Tv/41wX63OQkryOiQnr0Nq6pFDUoxH4nI1YvOWk8GYDwCwcMEDyMk5b0ztYYxhx84LYLXuAACkpx2PZcueHNNrEELGjzEGq20nOtrfR3vHe5KlRosK16O4+EZJ4MoYg9W6I1xILkQmVyM5aS2UykQAoWvd5ubn0ND4D/C8F6Wlt6Go8BfT90ONHQW/FPzOHB5PG5zOGmi1BdBo8iCTKeHzWdDbtxkdHR+ip+dLYV+ZTIO5c/+A3JyfTdp8B8YY3O5m2Gx7YLZ8h56eryQFN2QyNVJSjoBKlQqbbR+cziowFpS8hlKZgmDQDZ53QyZTISX5cKSnn4C0tGPHdKFCCCGxxOVqxK7dl4o6JGVYtOghZGedGc1mzVhW2x7s3HkheD4UrKamHoXly54Zdo7saNTVPYLGptC1klKZgkPXfilcAI9GZ+d/UFZ+I4BQB8jaQz6d0UUqCYlldns59u5bLyl4p9HkoqDgamRnnY0e89doanoKDkfFkOdynAppacciLfUotLS8KFmlRS7X47B134/p2DDNKPil4Hd2YIyhrf0tVFf/SZIenZJyBBYufAAadda4X9tq24PGxg3o69uOQKBvXK+h18/FvLl3ISXlsHB7Q0HxRC5UCCEklng8bdi1+1K4XA0AQqm3oQCoOMotm14Wy49oanoaHm8r9Pr5SDQuQ4JxGRKNKyY8JYcxhr6+rSgrv0lYC16nm4OD1rwz4bU+g0EXNm0+QVgDOC/vUsyf98dRPteLzVuOFzo/CvKvwty5d0yoPYSQifH7e1FW/htYLN9LtnOcfMjgzGgYDIuwcMH9E6oJMA0o+KXgd3ZxOKpRVn4jnM4aYZtCYURhwbXQ6gqhVmdCxinhdNbB5aqDx9MOra4QKcnrYDQul6SDBAIO1NU/ApPpFQy3rmB/mpnNvk/yniEc9Po5yMu9GDk5F07q+omEEBKLvL4e7Np1CZzOagBARvrJWLr08Si3anpYrbtQV//IkHU4+3GcComJK5GSvA4qdXq4unEHfD4zggEHAkEHgkGXkFauUBigVKZAryuBTlcKgKG5+VlYbbuE11QoknDQmncnbYS1q+tT7Cv7VfieDMuXP4O01KMP+LzGxidQV/8wgP5R4/9BqTROSpsIIePHWBDNzc+hqfkZoWq/mEymRWrqkULlc5erAXZ72ZB9SkpuQn7e5fFwLUvBLwW/s08w6EV9/SNobnkewwWtkcjlOhgMC6BQJEAu18Nq3Tmkep5CkQhjuAc/Le1YJCQsFdKqXa4G9Ji/AeP9SEhYAqNx6YR74gkhJN5Yrbuxfcc5wv01q99FYuKK6DVoivl8ZtTU/AUdnR9M6/vKZGosX/YsUlLWTdprMsawe88VwkiRXG7AQWveG7EystfbjU2bjxOWE5o/70/Iy7to0tpECJm4YNCNtrY30dT8LLzedigURuTlXYr8vMugUqVI9nU4a9DR8QF6ev4HvW4O5sy5HVptXpRaPmYU/FLwO3v19m7F/orb4PG0TPi1UlKOwNw5v4deP282rplGCCFjsq/sBnR1/RcAkJR0MFatfD3uj52MBdHXtwOBgBVqdSbU6kyYLd+jpub/SabEcJwc2dnnIjvrbDidtbDZ9sBq2xUhO2h8OE6F7OyzUFhw7ZTMqfV6u7Ft+1lC+rNWW4iD1rw37NJ7FRW/R1v7WwBCU3wOPujjeBgdImRW4nkfHI4q6HQlM3Vtdgp+Kfid3QIBB9o73ofTWQuvtwNebycY74NWVwS9rgRqTQ7stn2w9G6UFAXop1SmYN7cu5CZeVrcX7gRQsh0CVUPPlFYGmn5smeQlnZslFs1Pn5/L9ra3oap9bWI5wmxjPSTUVp6S8R5zl5vJyy9m9DXtxU874NanRUKolXpoYwjhQFyuQ6M9yMQcCAYdMDj7YDLVQ+Xsw4+vwXJSYcgv+DKCdWxGA27vRzbd1wgrLCQmLgaaWnHAUCoWGPK4TDo58JuL8fWbWegP8tqxfIXkZp6xJS2jRBCRkDBLwW/ZLTcbhM8njYEgw4EAg5wnBwpKUfQvCVCCBmHqqp7YGp9BUB8jgj6/TY0ND6G1tbXJEuGRKLR5GL+/D+Nan5svOjs+gRlZdcP+3hy8qEIBOzC/MDU1KOxYvlz09U8QgiJJGLwGz9nHkKmkVabF09zGgghJKYVF1+P9o73EAw64XTWoLX1NeTnXxbtZh0QY0G0tr2J+vq/DikQo1AkwWhcCp+vG15vqNpydvbZKCn+tWSd95kgM+NkOItvQkPD3yI+Li7sxXFyzJ3z+2lqGSGEjA0Fv4QQQgiZUipVGgoLrkF9OHiqrfs/pKQcBr1+TnQbNgKrbQ8qK++Ew7Ffsj0hYTHy8i5FZsapkMs1UWrd9Csuuh46bQEcjkphW6i441eSpVJycy+K6b8rIWR2o+CXEEIIIVOuoOBadHV9AoezCjzvRXn5zViz5h1hWY2JYozB42mFTK6BSpkasTYDYwxW6w50dP4bjPcjKekgJKesk8ybHW5pO40mF3Pm/B4Z6SfNyroPHMchK+sMAGdItns8bWhtfQNd3Z9Bq81HacnN0WkgIYSMAs35JYQQQsi0cDiqsHXbmWDMBwAoLPwl5pT+dtyv5/f3obvnS/RaNsHSuxE+Xyj9WKFIDK+JWxyuxpwFBh5tbW8PGckFAI0mH3K5FgDg83XD7+8VHpPJNCgqvA4FBVfPqpFeQgiJczTnlxBCCCHRYzDMx5zS36Km9n4AQFPTU0hOOgSpqUeO6XV43g9T66toaPg7AgH7kMcDASustl2w2naN6vWGWwYvJeUILJj/Z2i1+WNqHyGEkNgkm4wX4ThuIcdxX3EcZ+U4rpbjuLPC2y/iOM4h+ufiOI5xHLc6/Pg9HMf5B+1TInrdIo7jvg4/r5LjuJ8Met+fcxzXxHGck+O4DziOk67MTAghhJCYkp9/OVKSDwvfY9i95wrs3fcrOJ21o3q+2fwdtmz9KWpq7hsS+CoUCZDLR16vUibTICf7fJSW3ILk5HUR066VylQsXvRXrFj+AgW+hBAyg0w47ZnjOAWA/QCeBPB3AEcB+AjASsZY9aB9LwdwF4A5jDHGcdw94dsXD/PamwBsAvAHAKcAeA7AXMZYN8dxiwFsBvBTADsBPA1Axhi7cLi2UtozIYQQEn0ebwe2bj1tUAVlGXJyzse8uX+IWC2ZsSBq6x5Cc/Mzku1abSFyci5ASvKhSEhYDEAGr68TLmcd3O4WeL2d8Ho7EAjYkZi4EtnZ50KpTBSeHwx64HY3Y2B+LwedrhgymXLSf25CCCHTZsrSnhcAyAHwVxaKpL/iOO5HAJcgFOiKXQbgZTaKiJvjuHkAVgE4gTHmBvAux3E3ATgHoUD7IgAfMca+C+9/F4AKjuMSGGNDc6AIIYQQEhM06iwctOZd1NY+iK7uT8JbebS1/Qs26y4sXboBOl2RsH8g4ET5/pvR0/OlsE0uN6C4+Abk5106ZPRWo86SFLEaiVyugcEwb6I/EiGEkDgwGWnPkaJqDsASyQaOKwRwJICXB+17GsdxFo7jyjmOu060fTGA+kGB7J7w9v7H9/Q/wBirA+ADMOQMxnHctRzHbR/lz0MIIYSQKabVFmDp0sdx0JoPkJJyhLDd4azCtu1noqPzI1gsP6K9/V3s2Hm+JPBNSzsOhx76PxQWXD1p1aIJIYTMfJMR/FYC6ALwW47jlBzHnYBQ6vPgnKVLAXzPGGsQbXsLwEIA6QCuAXA3x3E/Cz9mAGAd9BpWAAmjfFzAGHuaMbZmTD8VIYQQQqac0bgUK1e8iIUL/p8QyAYCdpSX34Rduy/F/orbJGvLFhRcg2VLn4BalRatJhNCCIlTEw5+GWN+AGciNPe2A8AtCAW1pkG7XgrgpUHP3c8Ya2OMBRljGxGaM3xu+GEHAOOg1zACsI/ycUIIIYTEiZyc87F61ZtQq7MjPs5xCixc8ADmzrkdHCef5tYRQgiZCSZlqSPG2F6ERnsBABzHbYQo0OU47jCE5gW/c6CXwkAadTmAkkFzeJcDeF30+HLRe5QAUAOQFNkihBBCSHwwGpfh4IM+RG3dQ7Bad0GlSoFanQmNOhuZmacjIWFhtJtICCEkjk242jMAcBy3DKGgUwZgPYBfAVjAGPOGH38agIYxdumg550B4DsAfQAOAvA+gDsYYy+FH98M4AcAdwI4GcALkFZ73oSBas9PAVCMptozIYQQQgghhJCZa8OGDUNqU03KOr8IVXZuR2ju73EAjhcFvhoA52NQynPYhQBqEUpVfhnA//UHvqLH1wDoBfAAgHMZY90AwBgrB/BLAK+F3zcBocCbEEIIIYQQQgiRmJSRXzK7cBy3nQqIkVhHn1MSD+hzSuIBfU5JrKPPKBmtyRr5JYQQQgghhBBCYhYFv4QQQgghhBBCZjwKfsl4PB3tBhAyCvQ5JfGAPqckHtDnlMQ6+oySUaE5v4QQQgghhBBCZjwa+SWEEEIIIYQQMuNR8EsIIYQQQgghZMaj4JcQQgghhBBCyIxHwS8hhBBCCCGEkBmPgl9CCCGEEEIIITMeBb+EEEIIIYQQQma8WRX8rl+/nq1fv57WdiKEEEIIIYSQWUYR7QZECQXAhBBCCCGEEDIzcZE2zqqRX0IIIYQQQgiZ7WqcHtxb24otfY5oN2VaUfBLCCGEEEIIIbPIteWNeKKlGxfuqUO71xft5kwbCn4JIYQQQgghZJZocntR4fQAANw8w2NNXVFu0fSh4JcQQgghhBBCZokfB6U6v9pmRptndoz+ztaCVxJ+vx8mkwkejyfaTYkajUaDvLw8KJXKaDeFEEIIIYQQMkU29kqDXx9j+EdzFx6YlxelFk2fmA5+OY5TA9gA4CcAUgDUAriDMfZJ+PHjAPwTQAGALQAuZ4w1jfV9TCYTEhISUFRUBI6LWBhsRmOMwWw2w2Qyobi4ONrNIYQQQgghhEwBxhh+6B1a5Or1NjNuKMhArkYVhVZNn1hPe1YAaAFwFIBEAHcBeIvjuCKO49IAvBfelgJgO4A3x/MmHo8HqampszLwBQCO45CamjqrR74JIYQQQgiZ6ercXnT4/AAAo0KG1UYdgPDob1NnNJs2LWI6+GWMORlj9zDGGhljPGPsYwANAFYDOBtAOWPsbcaYB8A9AJZzHLdgPO81WwPffrP95yeEEEIIIWSm+1E06ntokgG3FWcL919vt8A0w+f+xnTwOxjHcZkA5gEoB7AYwJ7+xxhjTgB14e2Dn3ctx3Hbp6udhBBCCCGEEBJrxCnPhycl4MhkAw4y6gEAfsbwvKknWk2bFnET/HIcpwTwGoCXGGOVAAwArIN2swJIGPxcxtjTjLE1U9/Kqff9999j8eLFWLFiBdxud7SbQwghZJZhjOHe2las+LEcTzbPnuUxCCEk3vGM4cc+u3D/8GQDOI7DDYUZwra3Oizw8Xw0mjct4iL45ThOBuAVAD4A14c3OwAYB+1qBGBHnGOMgR/mQ/faa6/h1ltvxe7du6HVaif0PsFgcELPJ4QQMvt8abbhiZZudPj8uKeuDc+buqPdJEIIIaNQ5fTA4g9d/6cqFZiv1wAAjk0xIlsdWvGlxx/A5z22qLVxqsV0tWcA4EKTUZ8DkAngFMaYP/xQOYDLRPvpAZSGt49b1te7J/L0EXUcs2LYxxobG3HyySfjmGOOwaZNm7BixQrs27cPbrcb5557Lu699148++yzeOutt/DZZ5/hyy+/xDXXXIO7774bqampqKqqwpFHHokNGzZAJpPh888/xx//+Ed4vV6UlpbihRdegMFgQFFREa688kp8/vnnuP7663HhhRdO2c9LxocxRnOwCSExyc8z3FPbJtn2h5pWpKuUOC0jKTqNIoQQMirilOd1SQbIwtebChmHC7NS8NdwwavX2s04dYYe0+Nh5PcJAAsBnMYYE+f5vg9gCcdx53AcpwFwN4C94ZTouFRVVYVLL70Uu3btwiOPPILt27dj7969+Pbbb7F3715cffXVOP300/HQQw/htddeAwBs3boVjzzyCPbt24e6ujq899576OnpwX333Ycvv/wSO3fuxJo1a/Doo48K76PRaPDDDz9Q4BuDXmnrwdIfy/GXurYD70wIIdPsxdYe1Lm9km0MwK/2Nw1ZN5IQQkhs+WFQyrPYz7JT0D/08o3FjpYZWvgqpoNfjuMKAfwCwAoAHRzHOcL/LmKMdQM4B8D9AHoBHAIgrqO5wsJCrF27FgDw1ltvYdWqVVi5ciXKy8uxf//+iM85+OCDUVJSArlcjp/97Gf44YcfsHnzZuzfvx+HHXYYVqxYgZdeeglNTQPLH19wwQXT8vOQsXugvgM9/gAeb+5Crz8Q7eYQQojA7Avg4cYO4f6NBRko1aoBhJbIuLysfsZXCSWEkHhi9gXwp9o23FLZjPvr2iSdlIOD3wKtGkclh0onMQBvtJuns6nTJqbTnhljTQCGzf9kjH0JYFxLGw1npNTkqabXhyqtNTQ04OGHH8a2bduQnJyMyy+/fNg1eAenx3IcB8YYjj/+eLzxxhsjvg+JLVZ/AOZwwMsD6PIFkKyM6a8oIWQWebixA9ZAaK5YsVaFW4uzcHFOKk7dWYMuXwC2AI9HGjvw1wUFUW4pIYQQAPhjbSve6ewdsj1LpURJuPNS7KKcVHzTGxod/le7BbcUZUE+w6bixfTI72xls9mg1+uRmJiIzs5OfPLJJ8Puu3XrVjQ0NIDnebz55ps4/PDDsXbtWvz444+ora0FALhcLlRXV09X88k4mbx+yX2zj0Z+CSGxocbpwcttA8tf3DMnFyqZDAVaNTYsKhS2v9luQa0rcmctIYSQ6ePleXzSM3hhnJCT0hMj1pc5Mc2I1PDAS5vXj68tcV9HeAgKfmPQ8uXLsXLlSixevBhXXnklDjvssGH3PfTQQ3H77bdjyZIlKC4uxllnnYX09HS8+OKL+NnPfoZly5Zh7dq1qKyM26nQs8bgdEEzpT0TQmLEpz1WBFno9uFJBpyQOrDYwuHJCUKqHA/gwYaOCK9ACCFkOm3uc8IZDK0ek6NW4nfFWbg6Lw2/LcrC74uzIj5HJZPh/Kxk4f7LrTNvzV/KqYwRRUVFKCsrE+6/+OKLEfcbvF2n0+HNN98cst+xxx6Lbdu2Ddne2Ng4kWaSKTS4sAAFv4SQWNHpG8hMOT7NOGTE4PaSbHy7IzRC8O+uPtxQ4MLSBN20tpEQQsiAz0Wjvj9NT8RviiIHvINdlJOKJ1pCS9h9brZhp9WJVYkzZ8okjfwSEiOGBL+U9kwIiRE9ouNRWoRaBCuNOpySlijcf6CeRn8JISRaGGP43DywVu/xqYkj7C01R6fBqekD+/+prg2MsUltXzRR8BvHjj76aHz88cfRbgaZJJT2TAiJVZLgV6WMuM9tJVlChcr/WWzY0kdLHxFCSDRUuTzCoEqCXIa1SWMbub2jJAeK8AF9s9WJL0SBdLyj4DdsJvVojMds//ljAaU9E0JiVY9fHPxGnjG1QK/FOZkDc8Wem4FzxQghJB580TMQrB6dYoRKNraQr0SnxqU5acL9++raEeBnRqxAwS8AjUYDs9k8awNAxhjMZjM0Gk20mzKrDRn5pbRnQkiMOFDac7+r8tKF2+V295S2iRBCSGSfi4Lf49OMI+w5vN8UZcIgD4WK1S4P3uywTErboo0KXgHIy8uDyWRCd3d3tJsSNRqNBnl5edFuxqzlDARh8Qcl22jklxASC4KMwSI6HqWMEPzO12vAAWAAGj1eeHke6jGOOBBCCBk/sy+A7TYnAIADcFzK+ILfdJUS1xdk4IFwBf8HG9pxZkYS9Ar5ZDU1Kij4BaBUKlFcXBztZpBZrMXrG7KNgl9CSCzo9QfBh28nK+RQyoauDdlPJ5chT6NCi8eHIAPqXV4sNGinp6GEEELwP4sN/bmsa4x6pA4zVWU0rs3PwIutZnT4/Oj0BfBgYwfunZM7OQ2NEuqOJSQGtLiHBr8Wf2DWpuITQmJHj39gmaPh5vuKzdWphds1Lu+43rPL60eFw03HwAngGcNOqxN91JFKyKwiXuLohHGmPPfTyWW4ozRbuP9MSzf22l0Tes1oo+CXkBhg8vqHbAswwBYIRtibEEKmj3i+b+oIKc/95ukH6kfUOD1jfr8qpwdHba3EMduq8AIVzRqXbp8fZ++qxSk7a3Dstio46FxCyKzg43l8Y7EL98c731fsvMxkHJ5kAADwAG6taonr4lcU/BISAyKN/AKA2U8XLISQ6BIHv+nDLHMkNk83EPxWu8YW/PKM4dbKFvSGg7UnWrpp9HeMdlqdOGF7NTZbQ3P+2rx+/M8yc5YpIYQMr9zhgSMYmqiSq1Zivm7ixWw5jsOD8/OhDk952Wt34/nW+K2TRMEvITHAFGHOL0Dzfgkh0TeaZY7E5k5g5PfVNjO2hQu1AKEl4PY5qGr0aL3VYcGZu2rRPiib6FvRSBAhZObaJTp+HpSoB8cNX6NhLEp0atxUmCncf6ChY8gqJfGCgl9CYoB45NeoGPha0nJHhJBoG+0yR/3Ec37r3F4ERzly2+X14776tiHb/9ttjbA3GazV48OtlS3whX/fGlFhsm8t9ikfQW92e9E7Aztsf+i144XWHjgpdZzEgZ22gfm4q4y6SX3tXxVkCJk9riCPO6pNcZmZQ8EvITFAPPK7zDBwsKKRX0JItEmC31GM/CYpFcgI7+flGVpGOTpwV20rbIFQup5WFLj9p7tvDK2dvTb1OYTAt1irwv8Omo+E8BqdrV4/asdZfGw0XmrtwdrNFTh0cwWa3FP3PtOtyunB+bvr8PtqEx5s7Ih2cwg5oN2iYlQrjfpJfW2VTIaH5g8si9rq9cVlbRoKfgmJMneQR3f44lLOAYsTBpYFoeCXEBJtY632DABzxfN+R5H6/JXZhg+7+oT7Ty0ugja8PnCNyzuq15jtxBe9Z2Umo1SnwRHJCcK2b3unJvW5wuHGXTWt4AH0BYJ4cQYVKfuf2SYs8/UJZSCQGNfnDwidXAoOWDIFy8wdkmTAL/LScXdpDj5bPR+Jo8gGijUU/BISZa2iUd8ctQoZooIysz3tucHlxeNNnTNqJIGQeDPWtGdAOu93NIHr481dwu3zspJxQloijk0dCNxo9PfA9tgG5kavSAhlEB2VMvA7/GYK5v16eR7r9zcJI84A8GFXH/g4TIWMZIdo/mSzx4f2YepzEBIL9tgHjgGLDFpo5VMT5t07NxfrCzKgGGHN91hGwe8MVmZ34aaKZvypti2uS5LPdOL5vvkaFVKUcuH+bB75dQd5nLO7FvfVt+P0nTWwx2FqDSEzwVgLXgFjW+vX7Atgc58DAMAB+ENJDgDgp+lJwj4073dkAZ6hzDEw8tsf/B4tCn5/7HXAy/NDnjsRD9S3o2JQ50ab148tVucwz4gfjDHssErXM93SF/8/F5m5doo6a1YmTO5835mEgt8ZqM3jw40VTTh+ezX+1WHBhpYufNjVG+1mkWGI5/vmaZSSdTRnc/D7docFbeGKpZ2+ADaIRoYImSwfd/XhjmoTGim7YFjjGfmdP4aR3y/MViG1dI1Rjyx1KPvl+FQjVOFKpfscbsoAGUGVywN3uJM7R61ERvh3WKhVo0irAgC4eR7bJzEo/bHXjidbBpY7ydMMZC293xn/1xxtXj86fNKq2TMhqCcz1y5JsavJne87k1DwO8O82W7BYVsq8FZHL8RjvRvDveok9gwe+RVfXM7UtOevzDbcUtmMy/fV47QdNTh6ayXurW0VUuV4xvC0SbqG3JMt3egYtHwHIROxy+bCNeWNeL61B7+rMkW7OTHJHeSFNSOVHAejQn6AZ4SI5/zWuDwjVgT9tGdgVPek9EThdoJCLpmzOpWjv/GeprvbNnTUt99R4nm/k5T67ON5/KayRbjOOCYlAY8tLBQe/7i7D/44zzjbbhsa6G6haykSoxhjkkrPKye50vNMQsHvDNLq8eHWqhah91dsu80V4RkkFphEAV2eRoVU1cwe+f3eYsdFe+vxWrsFn/bYsM3mRKXTgydauvGcKVQo5UuzbUhlUjfP4+EGqrZJJs8D9e3CxfsWqyPuL9angnlQyvNo14zMUCmEZdscQX7ICFo/ZzAomYt6clqi5PGfZgzcn4p5v4wx3FDRhLnf78OrbeZJf/3pskdU7GrFoItecerzN5NU9Or9zj40h6t4Jyvk+OuCAhySqEdueMTZ4g9OWYGt8erw+vFMSzcqRrlu9E7r0OumCqcH1hl4Xibxz+T1C1NUEuQyzBFNPSFSFPzOIBuau+AXLXPw8tJi4Q9c7fTEZTny2WDwyK847dkyw06y3T4/flXRhOFCjPvq21DpdEtS6Q5OHEjdeb3djCqq+komwQ+9dsnFuYdnqHbRZ2uw8aQ8AwDHcdLRX2fklOVvLXZ4wp0O8/UalAy6YDsxNRHycLy93eaa9GNipdODtzt64Qzy+Et9W9yOAI808ntYcoLwO9xnd0v+puPBM4Z/iqahXFeQgSy1EjKOwxkZycL2WEp9/qHXjmO3VeKu2lacsqNmVEXYxCO/ivDvjwHYRoMJJAaJ5/uuMOogG2VH5WxEwe8M0eX147X2gV7r++fm4YS0RCwKlzlnkM4FILFDvAZmvkYFvVwGdbiCnptncAZnRqcFzxhu2N+MrvCFV5pSgacXF+G9FXOEcvxenuGSvQ1Cmr6CA55YVIijw2l7PID769qi0n4yczDG8EB9+5Dte+gYOcR4il31myee9ztMx4I4lXnwqC8ApKoUWCxarmP/KEftRks8YmrxB7Fvkl9/OniCPPY7B9q9LEG6vIlRIcfq8Pw/hlAgOBFfmG3C39Mgl+GynFThsbMyk4Tbn/RY4QpOboGtsWKM4cnmLpy/uw4Wf+hc6uZ5XFveCPcIbfPyPPaJKueeKQrqKfWZxKKdNN931Cj4nSGebOkWes+XJWhxTDjNabUo/WlHhPkrJLq8PI/OcDqgDEC2WgmO46RFr2bIvN9/NncJKXccgH8uKsTpGUlYl2zA44sKhIBf3BlwekYycjUq3Fmajf4+zM/NtglfvJHZpdHtxWNNnfjeYgfPGL4w2yJOBREHQiSkR5SunDrG9RwHr/Vb4/Rg/f4mrN/fBJPHBz/P8KXZJuxzcvrQ4BeQrlVZZp/c4HTfoNebrDmx02m/w41AeMC6WKtCUoS/05Gieb8TrQHyeNPAqO8lOamSdT6XGLRCpW9XkJfM5x6rH3rteLqlC73jGO1njGFLnwNXlDXgnro2DA5zK50e/LG2ddjnl9ndwvJNxVqV5LNJRa9Gx+IPoNLpHnG+P5k84uwPqvQ8Mgp+ZwCLP4CX2gYWlf9NYaYwL2u1KGV0cMn+yeYIBGk5mjFq8/iFFOBstRIqWegrKa34PHm/0yBjUSkatd3qxAMNAyNtNxRkSNafXKDX4s7w8iZiv8xPBwAsSdDh3KyBnvfbqkzwRHlEgcSHIGP42Z463F/fjvP21GHdlgr8oWbgolccWO2Z5MAKCFXE/birL26Xm5OkPY9x5Fe83NF/uq04blsV3uvsxXudvThhexX+1tSBvvA5I1etxDKDNuLrLBJtL3dK/0Y8Y+icwDFt8EjvVKyFO9V22YdPee4n7givnMDUkS19DmwLd6QrOQ7Xho/R/TiOk4yS3lDRhBsqmkaVZiy2tc+B83fX4e7aNhy/vQr7RtkxFWQMz5q6ceTWSpyxqxaf9gx0rqw26nB7cZZw/+U287ArYYgHC1Yb9ZLpN7ttLjr/DINnDN9b7Li2vBHLfyzH0VurcGtVCwXAU8zPM+y1U7Gr0aLgdwZ41tQNZ/hAvECvwYmi1LE1otSHnTbnlB2AdttcOHjzfiz+oYxG5cZgk3WgBz5PoxJuD7fc0UROuD6ex0931GDFxnL8X4SUz6niDvL4dUUzguGP3kFGPW4rzh6y31V5aTgi2SDcX5dkwDLRhdydJTlCAZ16txd/b+qc2oZPgiBjk76uJhmbjb0ONIjm1Te6fUJ2gU4uw4ZFAxVq9zvc8E3i3+uT7j6cs7sOV5c34md760adxRFkDN9Z7GgXLYMWLZK05zGO/IrTns3+gDCSBoRSjB9pHPgOn5SWOGwxreHSnnnGcPauWizfWI6f7akbcxAcZAxlg4LfbVYnnHHWiTtSsat+4qWnJjIa97horu95WcnIVquG7HN+dgoS5KFjdZABb3f04qitlbitqgXBUbxvgGe4vdokjNaaPH6ctrMGb3dYDvjc31WZcGdN65C1pS/NScV7K+fg14WZOD0jSdh+a2VLxCW0xJkhqxP1SFcpUaoNdeb4GMNuyhIZosXjw7HbqnDenjr8u6tPqEHzWrsFz7X2HODZZCKqnG6h2G2uWolMtfIAz5jdKPiNE481deLsXbXYOihdyRYIChVyAeCmwkzJJPdirQopytDSFL2BIOqnYJ1Eqz+Aa8sbYfEH4WMM99a2xV0vX6XTjb82dmDHKNKZKhxudI3iIqvJ7R1xXco9dhf+UD2wvIq4p05S8dkXAM8YLttXj9Lv90oKjYzF1xa7cMJ+sqULjmm6wHuwoR114d+DQS7DhsWFUMiGXuTKOA6PLSzEGqMOxVoV7p+bK3k8U63EH0Sjw483d8V08as6lwcrNpZj2Y/lox61IJPvnRGK7lybl455eg0Kwx1PPsYmNCom5gnyuLt2YH76970OnLijStI7H0nou96A8/fU4ZBNFXi0sWNSA/KxmsjIb55GBc2g7/ryBC3SI7zOcCnPgDT4rXZ6hd/HbrsLm8PH7K8tdhyzrRKfjyHNts7lHTIn1c8YfoyzOZ27bQMB/HAjv9lqpdB5aAsMX317JJVON74Ip6lzANYXZETcL1+jwlsr5uCwpIHOTIbQSOv9dQfueH2xrQf7B30PPTzDDRXN+MsINR++Mtvwqqj2iV4uw6U5qfh8zTw8OD8fapkMHMfh4fn5wnfeHgzN/x38HRNfC6wJn5sPSRoYTNjSR6nPg91W1TLs8fOe2taIc6V9PI/Hmzpxxs4avBdDBdLijTgVn0Z9D4yC3ziw0+bE/fXt2NjnwE2V0vSRtzsssIaDmBKtGqeJejSBUAqSeOL79klOfWaM4ZaqFmHJAyCURhaLFw/uII/X2814u8OCJrcXjDF0ef24tbIFx26twv81dOC0nTV4cYQeygcb2nHMtiocubUSlc7hUyRfbO3BoZsrsG5LBb6PkEbX7vXhsr0NQk9dsVaFXxdmCo/3d1gAoRGT3XYXPuuxIciARxs7xjWaKD6xuHmG/05gLtZo7bA68ZSocvM9c3KRrxk6UtAvS63Ex6vnYdPaRVgYIQXykpxU4ULEzxhuq2pBjdODT7r78JypGztjaC7Wn+ra0O0LwBoI4omW7gM/gUw6V5CXLI/z/so5+MfCApyUZsRlOam4KfydWy66WJiseb9Pm7ol89eB0AjW6Ttr8FFXX+QnIdSp0z8P1scYHmzowE+2VePjrj78u6sPL7b24KmWLpRNU4eKdKmjsY0myDlOyETSyWX485xc/Hf1PHy+Zp4kDTdZIcchiYbhXgZGhVw4bvgZE0b1Ng0KQCz+IC7d14BryhrxepsZ9S7viB2xw3VKxdO8X0cgiJpw8SkZgCUJkVPHOY7DfN3AY5WOsXfyiDvaT05LxBzRnO7BVhp1eHflHHy8aq5QgwQANrR04Y324ZeU6vb58aBoiszluWmS9Pl/NHdhe4TjvC0QxK1VLcL9U9ISsXfdYjw4P1+SQQSEPk9PLS6CMjxQsMfulgTlHV4/WsMd3FqZDAv1od+b+DO6xRp71zjRtMfuwtfh740MwFW5afh09TwsD38eAwy4prxRkp2xw+rECdurcV99O7ZYnbiponlUAwtEysfzkuustUnDH0tJyNi6cUlUvNMxELTUu73YZXNhVXj+ybuigOaa/HTII6SNrTHqhIupHTYnLshOmbS2vdxmxsfdQ4OoJ1u6cbiowEa0dfv8uGxfg6QaXrZaCWsgKOn55wHcXm1Ci8eHP5RkS0bR/2e24dFwml5fIIibKlrw8aq5Q0YxX2834/b+EV0G/KW+Hf9NNggpfa4gj8v2NQg974kKOV5ZVoJkUUrh4LTn70QXY84gj+97HfhJqnHUP78zEBwyIvJuRy/Oz5q8z8JgniCPmyqbhdS1I5MNuGiCnz0Zx+Gh+fk4fnsVAizU23nE1krJPiemGXFXac6IF2ZTbU+4s6Lfl2YrfDwvzOkm0+PzHisc4e93qVaNtYl6HJpkGPK5X56gw7/DAekemxuXDJ1+PiadXr8kLf/8rGR80m2FPcjDwzPcWNGE1UYdcgZ1BG3tc+D/GoaOjFW7PLi6vHHI9hUJOlySkwqjQo4tVge29jlDAfO8PBw8SRdA413qqN9jCwvw8+xULDJokB4OnrPVKry3cg4ebOjANxYbbi7KgjJCNojYYoNG6Ewod7ix2KDFJlEnq5LjhDTLj7r78FG40yNPo8TTi4qEc6bYXlHK82qjDjvC54dYW592JHvtbqFuxDy9Bnq5fNh95+s1wnzdKqcHx4zhHGL1ByTXIoPn+g5nTaIery4rwZVlDcIx8bYqE4q0ahwa4TN6X107bIHQd7ZEq8a9c3Lg5xmuLGvAd72hv/ffmjrx6rISyfP+VNuGtnDglKKU48H5+dArhv9drDDqcGdpNv4Yzs54ytSNw5INOCEtUTLfd4VRK5zj14pGfrdZnQgyFvGaazb6u2gKw+kZSbh/Xh4A4LklxThhexUs/iC6fAEcvbUSeeFVLbZYnZJlD32M4fnWHtxeMnRaFBnea+0WYQAqRSnHBVN4XTdT0JVYjPPzDB8OGiXoT+Ord3mFYE7BAWcMGvXtt1o08juZFZ/LHW7cLaqWeGLawIn0S7NtzAUupkqdy4NTd9RIAl8AaPf6JYGveLT1n81duG5/k7CYfYfXjxsqmiTP32134ckWaQryux0W3FLZItm2y+6SVNe8q8aEveHCOnIOeGZx0ZBAbXDac/9Jv9+nETocRvJpj1UYZe73fa99SotfPdzYIYzQ6OUyPLKgYNg5fWOx0KDF+vzI6XYA8FmPDUdtrcSdNaaoFRl6pKFDct8W4CdcYZWMnbhz8Jys5GE/f8sTxEWvJj6i+kBDu1CHYb5eg0fnF+DTNfNQpA0Fu26e4f5B8+57/QFct79JMjf+T3NyoJMPf5rebXfhlqoWXFPeiGdNPdjrcKPS6cGtVaZJm3oykaWOAEAlk+GolAQh8O2nlslwV2kO/nfQAvw0PemAryNOfS53uBEMV/Pt9+GqOTglwlJJJo8f9w6TKitOQb8mL11I0a51eYeM2scq8Vq0w6U891tgEM/7Hdv5+a2OXrjDGUcL9RocEqEzYThyjsOGhYVYHH5/P2O4qqxhyLSgrX0OvCma13v/3FyoZTIYFHLcPzdPqPj/pdkmGbX/zmKXpDv/v3l5o/qsXpuXjuNFHQC/rmjGjRVN+EP1wHWN+PqpQKNCdngupT3IS6rrzmYVDrckk0ycxZanUeGpRUVCsNEbCC0ntlkU+MpFh+WXWntmzPKO08EV5PHXxoHrjRsKMpEwQqcPCaHgN8Z922uXpJ0BwAddvfDzDO92Dpwkjks1ImWYXvmVRp1w0qhweCatmMfdNa3whoOLRXoNnlpUhBNEJ5KnYyDVc7vViVN31KApfCEjA3Bokh560QXlAr0GbywrwbZDF0na/2FXHw7dUoFnTd1Yv79JWCNQITpQP9TYgRqnB+4gjyebu3BDRbNwQBfv118kZGOvA6+1i0/ueTgyZegIuXjk1+TxYdugNK9Pe6yjKhzS731RB0r/T84D+GCK5ths7XNgg2hu8l2lOSOmO4/Vb4qycHiSARxCxR2OSk6Q/O2CDHjW1IMNLeObHz0Ru20ufC5avqXfJ2PssIi2hxs6kPfNbvyyvBH+OKxU3OML4GvLwN/hnMzkYfcVp0VWON0TKiy31+7Cv0Tf8T/NyYVCxqFUFwqC+73b2SvMKwzwDDdVNguplkkKOZ5YXIhr8zPw7cELcHF2KtYm6nFKWiIuzk7FaelJUI3QkVTt8kxK5WrGmGTkd6xLHU0mSfBrd6PM4YY9/HfKUimxMkGH55YU4dPV83BnSTaOTzUKx7otVifqBxVA4hmTLJt0UKIea0Vprd/FQepztdMjyTBYnThy8Dtf1Mk6lnoJPGN4QTQd6Mq8tDF3ZOoVcry0tESY723xB3FlWYPQAW32hTp/+v00PVEyMj1Xr5FM6/pb+Odudnvx68pmyfNOH0VnChBKBf/7wgLkhAPa3kAQb3X0SuZDi6s8cxyHo0Xn6y8jHOdno3+IPoMnpyUOmbJ0REoC7pubK6SZix2TkoAfD1mIgvD1Qf/fgIzO86ZudIWP0VkqJS7PTYtyi+IDBb8x7t0I1Q0t/iC+ttikoxqZw6c5GBRyLAhXeuQhXRZhvMy+gJByxgF4anERNHIZfikakXu704LucRTVmCyeII8ryxrQGw72tTIOLywtxvsr56Lq8KX4bM08fLp6Hv530Hwck2qEXi7HC0uLcYXo4GHxB3FnTaswaicD8PqyUmFJDi/PcEVZAw7atF+yluBCvQYfrpwrdDp8bbFjp82J26qlc5KGO1CJLzI3Wx1COl+/Hn9gVMW5Qj9DAN+IgoAbRb2y705B8GsPBHF9xUC68+FJBlyakzqp76GVy/DOyjkwHb0cO9YtxpsrSvHyshJ8vmYeDhWlpr0zDSdRnjFY/AFhpO1hUS/sHNFctU97rOAnMBq33erEZfvqsWpjOZ4zTW3H0lsdFjzc2IEAAz7o6sNdI6yHGav+3dUrrH16kFGPQq162H2NCjlKwo8HGLB/hPn8I2GM4Y+1rUIH2PGpRsmSXuuSDfipqLDTXbWtcASCuGxfgyRN/u8LC4Tq7/kaFR5ekI8PVs3F80uL8fCCfDyzpAi71i3GvXNycEiiHmsT9fh1YSaOFk01eWsUlXEPxBYICsceg1wG7Qij0FNNUvHZ6cYmUTbMoUl6cBwHjuOwwqjD9YWZeGVZiWRqyJuDfh9Nbp8QPKco5chRKyV/q1hf8sgeCAWP/RkGhRoVzsoYvoMHkI78Vrk8wx6PgoM6Pb7rtQvFMo0KGc4eoSNpJHkaFV5cUix03JQ7PLitqgUBnuG6/Y1C549RIcO9c3KHPP8m0bnrP91WfGux49zddWgPPy9ZIccD8/LGFJinKBXYsKhwyMWwRsbhgqwUHDcoNVz8mZrq4HdLnwPrNlfg2vLGmFpaaWufA/9qN2NrnwM7bU5JdqJ41Ffsyrx0VB+xFFvXLsQnq+fh1fD5+vVlJSjSqiVp9E+3dAmd+xUONz7o7B1SmI6EpiKIq6/fXJQZ1WN0PKHfUgxzBIKSBeLFRSP+XNeGxvDyHQlymSR1J5I1ieIljyYe/P7PYhOCmzVGPeaGg+tDk/RYljAQGI5UPGoiQr32Ljxr6sY1ZY04flsVHhu09M1Wq1PoEUtSyPHuyjlC8RWFjMPyBB1WGHWSOTtyjsNf5ubi6cVFQk+k2M1FWTgyJQF/W1gg9GLWuryS1MB5Og3eWlGK1Yl6nCrqgb5oTz1qXQNVj++fN/Tk3k+c9hwQXZ+Iv7CjLVj1cVef8BqrjDqsL8iAOpzet8/hHrFw13jcXdsqzD9JVMjx94UFkrnTk2nwfKtlCTq8uqxESF+sdnnQ4Jr8CudAaLTupdYeLN9YjkU/lGH5xnJcurdeuCDiEEpp70+n7/QFRkyT6/UHYPaF/nX7/KhxerC5z4EPOntx9q5anLqzBp/12NDm9eMPNa1TVhlzn92F26qkqfsvtvZMecA92QanPB+INPV5fN+JL8w2oQiTggPumTN08vDdpTnCxf9OmwuHb6nE/0SdU7/IT5csVzecVJUCv8jPwIer5uKDVXPx+5Js/EpUffeDrt5RVYn+odeOs3fV4tcVzUPWaZ9oyvNkyteohOVzLP4g3hOtzxpp7igA/ExUY+CtDoskW2avY+C7uDxBN2RU7/te+5iya0Zrv8ONP9a24vU2syTAHAvGQpkC/eeT/o5dwwHSHdOUCuF45AryMEVI7f6024qDNu3Hkh/LcE1ZI7q8fsmo7wVZKSPOKz6Q1Yl6/CU8HxQITeM6Y1eNZGrP4wsLJUv/9Vtk0EoyfC7cUyeca1QchycXFw1Jrx+NtUkGvLS0GBdmpeDOkmx8vGouqo9Yir8vLBhyjjkqOUE49+9zuCVTh/7Z3IWTt1dPSlDMM4abK1tQ7/bi3119kiAnmp43deP0XbW4qbIFp++qxSk7aoRrwWNSEoZdagsIdVoXaNVYadThJ6lGLAt/7wDgZ1kpSAx/fhvcPrzf2Ys7qk04dlsVfrm/Cb8XrYwRbQ0uL+6pbcVXUR75f7y5S1gnvUirws+yJ3eQYSaj4DeG/Vc0T3OhXoO7SwcupMRr2J2akXTA3p5VogPSZKRzfSEapThBNNeX4zhcJxr9faG1Z9xp1tVODzY0dw1Z69IWCOLsXbX4yfZq3FnTio+6+7DP4cb99e2oEBUwEffcn5OZLKl6PRKO43B6RhK+P2QB7i4dWFv22JQE/KYo1Ku5yKCV9EIDQI5aifvm5uLTNfOEE/D1hQO/i17R7+H3JdkR10fsN1x64WWikeJPe6yjmtf3vugi8ezMZBgVcpyQOnBx/d4kjo5+0t2HN0Qpnw/My0PuJKY7j4ZeLseRohGwzya5qjVjDJ/3WHHMtkr8rtqE7vAFbJcvIEl3PjMjCQsNWsnvOlKHRYPLixO3V2HhD2VY/GPo39Ify3HE1kqcuasWv9zfFHG+8G8qmyNWPZ2IXn8AV5Y1whM+7ojT1O6qaZVkEExEgGd4qKEdp+2owXXljXikoQMfdPbixdYe3FljwoW763DZvvpxz7tscHmF4kUKDpJ1PYezXJT6vGccHYQBnuE+UcXYS3PSUBqh6FrhoFEOcYrlTYWZuKd0/NW2Dks2IDecwmnxB/G/ES7OGGN4orkL5++uw8bwXMsryxokAXP3BItdTSYZx2GRaPR3r6iDYrjg9yepicKxtN3rl1RxFj9/afh1F+g1yAgH+X2BINbvbxr1/MPdNheebO5Cr3/4gLbe5cUZO2vwVEs3bq5qwbIfy3Dmzhq83m4eciyvcXpwxb4G/LaqBTutTuHxJrcXt1Wb8B/RNIqH5+dLfjfD4Thu0Hq/A6nPnV4/riprwOVlDULhqI+6+3DE1krJ+X4y0iovzknFz0UdEztE37ebizJxwgidP+LzrniK0bNLiiQj92N1fFoi/rawANcXZmJNon7Y4oQGhVxS+Kr/O7bT6sSf69qwy+7CdeWNQr2Q8fq+1yEsEQgAjzd3jrh04nR4rc2MO2qGzwIafE00FnqFHJeIMsSur2jG8609wt/43U7LuDqLgozhk+4+PGvqPuDosZ9n+NJswz+bu/CbymacubMGN1c2S/6WVU4PfrqzGk+2dOOivfUjVu6fSq+3mfGYqEPktuLsAxYNJAMo+I0hVlHqJBCqxtvvnMxkLDRosUg/9GJqpLls/daJLg5+6HMIlU3Hw8fzkrl0g6sOn5qehDzNwAXY8+MY/e0PcP9U14aTt9dIDnr31LYKazsO9okouPi2d6CN4zkpqmUyrC/IwI5DF+PTcJqOuBf4xsJM/CI/HUcnJ+DRBfnYvHYhrs5LlxSoWZ6gwxHJ0guzVUbdAS8gEhVySREIIBSI/LY4C4bw6ze6fQcsWtLm8WFzeCRKBghzoc4VjYS909mLOtfEipMxxvDf7j7cIhoxPDMjCWeNMz1uosQjZ5+ZJyf4NfsCeKK5C0dsrcSl+xokHVCDD6RyLjQvGQBOEaW5fjoo+N1udeKnO6tHNdIo54DzspIxLxxQeXmGy/c1TEphHj/P8K3FjitEr2eQy/DpmnlYGQ4KeQDXlDVGHEk3+wKjXn6rxxfAhXvq8EhjJ7bZnHi/qw8PNXbgl/ubcHu1Cc+aevBNrx2f9dhwY0XTuAo3vSYqfnNsyvD1EMTEyx1tszrxWpsZv65oxi2VzZLlOYbzZocF1eHvkUEuEzrKIvl1YaZkrVs5Fwpgbi/JnlBROBnH4dws8Whn5I4tZzCI6/Y34V7RVA0gdMH964pmIR1WfNwdz4jaZIsU4KWrFJLpBWJKGSc51ok75sQFk5aGP+Mcx0kqgX/Y1YdTd9Sg8QBBR5Pbi7N21eCeujacsbM24kW2MxhKU7YPWl1gs9WJmytb8G/RklyMMfyivBGf9FjxSpsZp+yswbHbqnDurlocsrkCr7QNfL6vyk3DOWOo7jpfP/A77J/3W2Z34YitFZKAup81EBQ+I0cnJ0Ts0BmPv8zNk2RbAKEO5lvDx83hrErU4yhR56acA55cVDRiwDzZjksZmvosHpm1B/lxXfeIvdAqzbTx8ExSYHSqvd5uxrXhjskfeu14o90sWUqqVKvGEoMW2nDA9bPsFBwywQrzV+WlSWqliAUY8F7n6Kdy+Hger7eZccSWSlxR1og7a1pxxb6GYc8n3T4/jt9ehYv31uPPdW14o92CzVYnXm+34KQd1ah0ulHv8uK83bVC/RcG4Ff7m/BjuDq8P5zteF15I36Yworx73ZYJNdahyTqceYoOnjJAFrqKIacuasWJo8Pc3QalOrU+D785eEAIYg4JysF+0WVK3PUSklgO5xCrRoXZacIxZZur27BuiTDuFLZtvQ5heVD8jUqYT5xP6WMw02FWcKB8omWLlyZmzbisgODvdzaI6Tcdfj8uLGiCa8uK8G3FjteF13AnJyWiGSlXNj2SbcVNxdlocvrR3l4HUMlx+GwCRyUExTyiKk8ShkXcV7SYDcUZOL7cEpX/0XugZZHkHEcUpQKycjLaqMOKUoFjks1CnNsPumxRlwPFwita3xHjUnoOT082YCM8KjQMSkJSFbI0RsIos3rx2FbKnFokh7nZKYgV61EqkqBDJUSWWrpBS9jDPfUtuFLsw1z9WockmhAiU6NJ5q7JB0SOWolHhCltk23E9KM4KpCJ6etVics/sCoAqDBev0BfN5jw397+vC12Q7foBOnQS7DjYWZuCovDU1uHzb3OVDr8uInqUbMC38vjkhOgE4ugyvIo9blRbXTg3l6DT7u6sP1FU3CKKuCC8097ZeokCNVqUCKUoG5eg0uy0lFgVaNJrcXJ++ohsUfRI8/gDN31uCU9EQckmjA2jF+p+2BIO6tbcNH3X3CeuH9HltYgMUGLV5cWoyTd1SjzeuHPcjjvvo2PLekWNjvpdYe3F5tQolWjY9Wzx3x97zX7sIV+xqEuX0HsqnPiS/MtjFd2HrC63n3u3iU882XGrTgEPrM1Lm9kouLLVYn3l85Z9gA0BkMStYmvb4gY8RgMUEhx/+bm4dryxuRoJBjw6LCIXMLx+u8rGShCNKXZhvMvgBSVQo4A0F8ZbHjv919+NJskwRhuWql8Dd5v6sPGWol7p2TG1NpzwCwJMKxbm2iYcQOgwuzUoQ1MD/rscLiDyBZIcc+UYfTMlEQdltxFmyBIF4OB5gVTg9O3F6Nl5YWD7t+5t+bOoUsrWqXB3fWmPDogoHiZowx3FLZInRWqsPTbraJKt4+b+rBGeE5u7tsLuwf1LFZEaGj86jkBPwxQmr9SMTn6/7g94+1bcLyQkAokDkxNRH31LUK06sA4Iq8ySumo5HLJMvgFGpU+OeiwlFNkbmzNBvbdznBM4ZHFxTg1Gm+8P9JmhH3hK/Dvu21o9zhlnS8A6GCn9fmpY/puqdfi8eHz3uGZm181mPDFz1WHJmSgE+6rfjaYpdkaszRaXBFXtq4znViX/RYcfOgVSvElhm0eHtFKRKVCvCMwR3kx/VzDpatVuGszGS8He60S1UqcHRKgjCF5Y12C67JSz9gB2GN04Of7x2aOfRtrx0fdvXhzEGd8hZ/AOfvrht2MKHB7cMpO2qQIJcJU+n6+VioE/r3Jdl41tQjzI3/d3cf/rmwcMh7jZWfZ/iu146ucIZQlzeA/2toF44bywxavLy0eMqmls1U0T+bEQCh1Ix6txdenmGX3SUpSrUuySCkjp6VkYT76tqED/5Zmcmj/tD/cU4uvrbY0eb1w+IP4g81Jjy1uGjMbf1cNJJ2Qqox4oHo/Kxk/K2pAyaPXxj9vSFCSkyAZ9jvdKNUpxbmEXl5Hs8Mml/4lcWOhxs78KYo8D0tPQnPLCmCPRDEOx298DGGfQ43Wjw+yRIYaxJ1k3JgHq8jkg24MjcNH3X34XfF2aNKTwMwJPjtrwp9clriQPAbDvYHM/sCuGxfPbaL0snE80FUMhmuyEsT1i0GQoFG/3zFfqelJ+HpxYXC3/g/3VY8Ff7b1Lm9+DTCCTpRIceTiwqRFMU0yXSVEqvC63YGWSg17bwxjI70+gO4taolXFV76OMGuQwXZKXgpqJMIchZZNBG/Ntq5TIck5IgjKrcVBmaWykeOU5RyvHK0hKsHsXyIYVaNZ5bUozzd9fBzxhavX48Y+rBM6YeyACclpGEGwszJQWChvOL8kZ8FWEaxK1FWTg5nCWQqVbi2cVFOGVnDYDQZ2C3zYUVRh2a3F6hwFOd24sXW3sifh4B4GuzDVeUNQjBPhAaAS3QqFDt8qDR7YVRIcdcnQZ77S5h/fD76tpxbIpxyHraw/mwq0/omc/TKEcdVBoUcszRqSV/l361Li/O212Hd1fMkczHB0KBzYbmLnSKKm5eO8JSXP1OzUjC3qQl0Mi4A87VHIs5Og1WGXXYaXPBzxj+2tQBV5DHB119EUckL81JxZ/n5uKPtW1CjYanWrqRplQI1fyB6Kc9A5FHfsUF7iJZaNBiRYIOu+0u+BjDe529ODEtUZiGkqiQS+o7qGQyPDg/H8sTdPh9tQk+xmANBHHR3nq8tbx0yHe0ye0dUkzr9XYLjkhOEDqtnzF14wNRttUD8/Lws+xUNLm9OGxLhbBmeYXDjYUGrSRzoVirQoc3ICwzJANwTIoRl+Sk4vg045jXmZ0/KPitcnrwo6ig47+WlwrnmqNSEvDXxg682m7GUckJY1pbfjTyNCp8sWY+vrHYcVJaomSt+5EsTdBhz7rF8DM26udMplKtGkVaFRrdPriCPH5Z3ojBp4neQBAvtZmxvuDAx4LBXm7tEUbbj0w2IE+jEjr4b65qQZAx4Rg32NOmbtxUmIkr89KgHse68lZ/AL+tGn5+7UK9Bv8KB75AqKN+Mq+v/jQnVBU6SaHA9YUZUHIc/tvdBzfPUOH0YK/DLZmiMhhjDL+ubJYEvjJA+H3eW9eG41ONQput/gAu3F0ndC7JAPw8OxULDBrIANxX3w5XkBf+AaE59g/Nz8ef69rQ6QvAHuSHpIMHGXDd/ia4eB4/H+dc3D12F26pbEGZI3Jm2OC/BRk9+o3FiG5fAGoZJ7nY6CeeG5OjUeGYlAR8ZbFDhlAv/2gZFXI8ND8fF+2tBxC6SDw9o29Uayz2C813FM/3jTwio5LJ8JvCLGH05ImWLlyRmya5yNtpdeLmqlBveK5aiQ9WzUW+RoV3OnqFC8n+kRgAkkAtRSnHX8IFoxIUchyebBAu4j/ttkrW6jw6eXJP2GPFcRz+Mi9PUuRjNAbP++1P9Tou1Qglx8EfDvaP3lqJU9ITcXCiHvYAD7M/gKdautAg6rG/Ni99SFrMb4uysMaoxyttZnxujhzkfdTdh/e7EnF2ZjKCjOH/GtqH7hSm4IArctPwm6KsCfc8T4aT0hKFuWSf9ViF4Nfk8UHOYdg51z6ex1VljRHn2a4y6nBxTirOyEgaU9GXk9MSheB3cMG5Eq0ary8PVbwcrUOTDPjHwgLcUtUiCWh4hL7XH3b14fhUI35XnIUlw1wobOx1SALfXLUSp6Qn4oyMZEmBPCCUanhqeqIQkP5fQzveWF6Ku2tbJcHsi609uL4gY8h8uV02F64qH5hLnCCX4Z+LCoc9fnT7/PjGYocjyKPa5cGbHRZcNMoRXHFxnsty0sYUHPyqIAO3VLUgQS7HwYl6FOvUeNbUjSALzY+8cE8dbinKgiUQQI8vgD12F7b0OSUjpLcVZ424Nq/YVI2mnp+VInzOnjVFTr8s0KhwS1EWLgifX+6fm4tun1/4nN5f3y5MXwEwJOiPhgV6jeRCFhh+vq/Yhdkp2B0+J9xb24ZHRRXZlxq0ETtwL8pJxUK9BpeVNaDbF4AzyONne+vwzoo5kqWx/trYKRw7FdxAgcJbq1pg9gfw764+bBVlxVyakyp0RBZq1Tg5LQkfhVOeX2kz446SbMnSdI8tLMQ8vQafdFvh4nkcn2qMWAxqtMTBb43LIylkd3J6omTpPa1chjtKc3DHBOahH0iuRjXq77bYZHYYjRXHcfhJqlH4bok7zM7PShamGzwZvu7RymXo8wfgCPIH/Nt5gryk8+OK3DQclGjAf7qtsAaCkg7xSKyBIO6ta8MLrT24JCcVp6QnjilV/Y+1bUIdgjSlAqekJ2KL1YkqpwfLE7R4dVnJlJ7fk5UKSdYEEOoo7B8NfqPdMmLw+7nZJhz7VOGpYmdnJuOkHdXo9gXQ7vXj0aZO3FWag0a3F+v3N2FvOLjkAPxjYYFk6sihSQZcUdYgZECoZRxeWlqCI1MSsNCgxZk7ayRZNEaFDMkKBZo8PjAAN1eGztFX5w3UeTgQRyCIhxo78ExLN4Z2V4bM1anx1orSmLjWikfceOZTxav169czANiwYUO0mxIRYwzdvgCqXR7UurxocHlRqlPjkpxUycm5w+vHc6ZurEnUj6oq6GC/rmgWeqpTlHK8ubxUmPM0WKfXjydaupCqVOCqvHSYPD4cubUSAKCXy7D/8CXD9i76eYZ1WyqEHrg7wtVIe3wBPNbciedMPZLe0oV6DT5cNRcnb68WCj38vjgbn5mtQwKGJxdJ00leaesReisPTdKj1uUVThKfrp43YgXCWHVNWaNwUWRUyLD/sKXC6Ncle+vxxSgqDXIA/jw394AH3g6vH293WFDmcKPXH0Czxycc7DNVCvxwyEL8t9sqrKdokMtwR0k2dthcqHJ6sECvwc1FWSgZZu5dNFQ5PThK9Fnde9hiPNzQgSfCKZB5GiXWJhqwLsmA0zKSkKCQgzGG31aZ8Kro4mO1UYeT0xJxSnrSuH8+qz+AVZv2C8uSAKF0/BPSjHhwXv64AwtbIIhtVie29Dmwsc8hGekHQifqxxYWDin4xBjDGbtqhYvyczOT8djCghHTyaqdHhy9tVI4GV9fkBGxAuk/FxZI5iA2uLw4dWeNsF55rlqJt1aUHvCC7G+NHXigIRSkZKoU2Lh24QE7HHbanDhlR43ws+88dPGYf7d+nkHOQcioea+zF7/a3zRkZCeSeToNvjpo/qhHqadKrz+A5T+WD0nTn6tT47SMJPw0PQmL9Johf29PkMfP99ZH7PgZfMyNliO2VAjBRopSjrLDlhww+8nqD2D5xnJJR02/9fkZuHuE1OEqpwdn7aoRRtqSFXK8vaIUSxJ0aHB5cfjWCiH4fWVpMe6qlaYKi60y6vD+yjmSc+YPvaHleoBQp9BtxdnC0mLzdBp8e/D8Cc0Dj2TZj2VC+qY4YH9nRSkOTx5/0ajZ5BuLDRfuqZdsOzhRj7dXlGLt5gph+aUrctPQ4wvg0x4r/IzhxoIM/F40t58xhp02F0ze0JS3XTaXMGUsV63ElrWLoJBxeDE8vaRfrlqJn2enojh8TrIHgnhyUKd3v3k6DS7LTcWVuSOvz/yV2Yaf7x34mZ5bUiQMjvh4HsrwcmLT7cdeO84Jf0cSFXLsWbcYmggdjDxjOHZblZC+fG1eOv40NzRI8naHBTdUhK5fFFwoE+5f7RbJMpKPzs/HzyN0xFj9Afy5rh2VTjd+V5yNI0QdRD/22nFNeSNsgSAuz03DzUVZ4Bnwsz112Ccasf1DSXbE7Md+ff5QwcxPuq34xmITplEAoWW3fpqeBEX4d5+klB9wag0RRPzAUvA7C/X5Azh6a5XQu6eXy/DM4iIcOyilaZvViavLGoRR2Lk6NdYk6oWiIT9NT5TM/Yvk9TYzbg4fyGUIjeKO9Ikr0aol6wnuOHQxev0B/GR7lTAn6ZS0RDy3pEhyEO7y+rF8Y/mQ105RyrHvsCVjTg2LBbdXm4Q0xJPTEvHC0oHfdZPbi3tr2/A/iy1itgAQOmBuWFSIU8Ywst/PHgji8C0Vwt/+qtw0fG62CR0Zvy3Kwi3FIxcmiTbGQp0v/RcDpVq1pHqmWKJCjitz06CScfi/hoFRod8XZ+PXIxQuGovvLHa839WLfI0KhyTqsdKoH/UI4Wjttbvwj6ZO/KfbKvku3F2ag+vyB+ZKfWm24eLwRY6S4/DjIQtQMIqRZ3HHmViqUiEEtysSdPhk9VxwHIdunx+n7qhBU/hzk6yQ48NVc4X50CNxBXms21whHKduKcrEb4uzR3zODRVNwgjBeVnJeGxh4QHfZzRebzePOAcuSSHHuiQDbi/JHtXPNh3+UG3Cc6090Mo4nJ6RjEtyUrHaqDvgxaszEMSFe+qxzSadAhErgdEvyxuFFOJT0hLx/NKRz0H9XmjtwV/q2iSjNEqOwxcHzcMC/chTBModbpyzq1ZYVkSG0JQjeyAoVHg/PMmAd1bOwR67C6fuqJFcVCs44KfpSbhvbu6QC1bGGA7fUikcm8QZYH+akzOqFPqxOn93rWRpISB0fv/u4AVRCW7ikZfnseD7MiEdHQBeXlqME9IS8UxL94hro1+Zm4b75ubC4g/i5spmySoBYneUZOPGcMDEGMMzpm7Uurw4KS0RR6UkDLmu8fE8Xm4z45GGDsnqEv3OzUzGowvyI1aybvP4cOrOGqHS9+kZSXh6HNPipgLPGA7dXCGcR4briHuvsxfr9zcBAHRyGbasXSh83xhjOHNXLbYMUyz1L3NzceUYRmfFnIEg5BwnCcit/gAu2iudenZTYSZ+V5w15Dv2pdmG68obJcemfkckG/DQ/PwxZYYRCQp+KfgdsLXPgYv31QsBpZwLzbU4JsWIVKUcH3T14c6aVskJfLC/LygQUuaG4+cZDt8ycNAa7JiUBKxLMuD++qHptDcUZOAP4XSrr8w2/Gp/U2juy/KSiD1ep+2oGXLBdkZG0rjmNccC8QX344NScfr1F7H5rMcKk8eHlHCBpAy1AmdnJmPOBCpzik8kYilKObauXRTVtLPR+mNtq1DsRkw82jGc0YyGxqpKpxtXlzUK64ACwGU5qbi9JBuJCjlO2F4tzCO6Mjdt1Cn5zW4vDttSKTkuJCrk+PequThhe5Vw0f7xqrnIUivx8z31QgVkrYzD2yvmDEmpHom48wwI/U3unZMbcTS3xxfA6k3lQhs+WT0PKycx4+P9zl680maGViZDiipUjKxIq8YhiXrM12tiruAIYwxVLg9y1SokjPG7agsEcd7uWkkV8m8Onn/AIHE6iD8TozkHiTHG4AyGpoZY/EEUa1Wjrk2wy+bC+btrI16gAsAHK+cIBbHe6bDg9moTMlVKXJidgguzU0YcpXmiuQv3igpZAqGUzV3rxp65MBp31ZjwzKB0+Ilc/M9Wl+2rx2fhaWDzdBp8c/B8yDgOriCPgzbtFzoEIzkpzYidNteQAkr9VByHnesWj2tqhD0QxKc91nBRLOko4uFJBjy/tFgortjg8uKfzV14q8MiZIqkKOX47uCFMVHkrt+jjR14MNwxfUSyAW8tL5Wcm/08wxFbK4Ssi98UZuJ3JdLO0v0ON47fXiWZ4nWQUY975uSMqt7GWDkDQVy6r0GYUw8A1+Sl4d45ucL54uOuPly3v2nItfZ8vQa/KsjAeZnJcXkNEkMo+KXgV6rS6cZFe+oPWHk1SSGHl2eSHk4OwN7DFo8q7eJLsw1X7GsQvtxJ4QIjv8hPx9nhL/afatuwoWUghVIt47Bt7SKhOvFobGjuwp8GXUA8uiB/3MUGos3H83i1zQyljMPF2anTfgBkjOHs3bVDimDdU5qDX46jiEc0bOpz4KxdtZJtvy3Kwg2FGShzuLGx14HX2s1DUsUOMobS1yKlVsULiz+AK/Y1SHq61TIOa4x64WSslXHYMsbv2R3VJskyHv9vXh6uyE3DTRXN+Fd4VHhtoh4Nbq+QOSAD8GJ4VGQsgozh5O3VwpwsIHRhds+cXJyTmSyMfPh5hjtrTHgpXKF3RYIOn66ZN6b3IlK9/gDO212HMocb+RoVNh6yMCbWkQzwDC+19UDOcbg0J3VaOx32O9y4t7YN3w5axuSIZAPeXjFn3K9r9gWwStRxA4SWintyijpuX2szS6qZ6+Uy7F63eMydJLPdJ919uKKsEQDwzOIinCaaXvLvrj6s398Ig1yO87KScWF2Kh5r6pQUPhM7NEmPDq8fTW4feAC/K84SlsubCGcwiD/WtEmm8uSqlTAq5DD7A+j2BYZkzD27uGjaK2gfiMnjw0Gb9gttXWzQ4MbCTJyclohWjx9vd1qEujBJCjm2rF0YsRDUk+GOpiKtCneU5ODU9MQpvbZyB3lcXdaI/4mWBy3RqvHz7BQYFHLcUW0SphLlqpW4PDdtzPO0yYgo+KXgd6gOrx+X7K2XzE0QW2LQ4vklRfAxhvXlA4UB1ibq8cGquaN+H2cwCFeQR7JCEXE+XJAxXFnWIPSiXpqTigfn54/pZ2lweXHolgrJth2HLhIqZZOxq3C48RNRT2m2WomNhyyENk6CwkC4N7jB7Ru2yFKQMXzU1Yd/NHViv9ODuTo13hthWZt44gnyuLGyedh1vcXZFaPV5fXjyK2V6AsEsTJBh49Xz4Wc41DucOO4bVVD9ldxHP6xsGDc80V7fAHcWWMactFYqlXj+sIMlGrVuL3aJFkaZqwjgiQyH8/jG4sdK426GfF9mCw7bU481tSFT3qskjnAE3H9/ia80zmwLvPby0slcwsn03arE6eGq7cDwOW5aVFdmi6ebepzQA7g4AiF13w8DznHCZ10QcZwa1WLZL3pdJUCf19QIEw78/I8/Dyb1Mwqxhj+0dSF/zdCwUoAWGPU4bfF2Thqij53EyWug9JPXBS134Hm17qD/LRew/h4Htftb4q4jna/Uq0ab68oRQ5dr042Cn4p+I3MEQji4cYObO5zhtPBQj2B54RTDPvnJfp4Hk+1dKPM4cbNRVmSqpGTwRkI4sHGDriDPO4uzRnXwf/orZVCsYO5OjW+P2ThpLZxNrqnthVPhlOH43EkvcXjw9dmG45LNY7YEcIYQ4vHhyy1MuKcqHjFM4Y3Oyx4obUHe0VprEaFDFvWLhrXUiF1Lg+29DlxekaS5Ht61q4aSaZAokKOF5YUY13y+NfZ7vel2YbfVbUcMFPlsCQD3lheMqP+hiQ29fkD4IBJWWpka58Dp4ezVAo1Kmxau3DKRrXtgSDmfr9PuP/twQsm/XxOIuMZw4MNHXixtQdHJCfgL/OGzgOfKu92WPCbyhZJITwOwJHJCbixMAPrkkZeMzvanMEgHqzvwMttZkkmoliWSokf1y4Y02oM0yHAMzzU2IHnTd1Dpk4s1Gvw1opS6mCcGjMv+OU4LgXAcwBOANAD4PeMsdeH25+C39FjjMX0QXA4/1ffjr82hVJfxJX+yPgFGcPr7WYkyOUxUe2VjN9euwuvtZlR7/bi14WZk17A6PMeKy7d1wAgVE37tWWlk3pR7QwE8XhzF55r7RbqFfTTymS4rTgL1+SlR73aMiHj8ffGTnzTa8Ptxdk4ZBRLOE3EHdUmvNDag8tz0/D/aNR32kXrGqvF40ODy4sUpVyoERJv03t6fAE8Z+rG8609sAaCyFQpMFenwXy9BpflpsVM0cFIXEEeH3X14dU2M7bZnDg0SY/nlxRHZb3qWWJGBr9vIDSd7CoAKwD8B8A6xlh5pP0p+J35rP4Ari1vgpfn8fTiojHNZSSETNzr7WY0ury4Oi99yr5/tkAQL7X24MmWbpj9ARyTkoAH5uWhkCpiEjJqniAfd4EPIf14FqpFE2ujvKPlCvLQyqKzfNQsMrOCX47j9AB6ASxhjFWHt70CoJUxdnuk51DwSwghM4eP59HtC9C8fkIIIYQMNuOC35UANjLGtKJttwI4ijF22qB9rwVw7XXXXbd6mptJCCGEEEIIIWSabdiwYUgAHM/5LgYAg0unWQEMmcTGGHuaMbZmWlpFCCGEEEIIISTmxPMMawcA46BtRgD2CPsCiBz9k7HjOG47dSaQWEefUxIP6HNK4gF9Tkmso88oGa14HvmtBqDgOE682OxyABGLXRFCCCGEEEIImb3iNvhljDkBvAfgTxzH6TmOOwzAGQBeiW7LCCGEEEIIIYTEmrgNfsPWA9AC6ALwBoDrhlvmiEyqp6PdAEJGgT6nJB7Q55TEA/qcklhHn1EyKnFb7ZkQQgghhBBCCBmteB/5JYQQQgghhBBCDoiCX0IIIYQQQgghMx4Fv4QQQgghhBBCZjwKfgkhhBBCCCGEzHgU/BJCCCGEEEIImfFmVfC7fv16tn79eipvTQghhBBCCCGzjCLaDYgSCoAJIYQQQgghZGbiIm2cVSO/hBBCCIkvQZ6hwtQLXyAY7aYQQgiJc7N15JcQQgghceCvH+3FF3tNmJNlxONXHw6Oi9iZTwghhBwQjfwSQgghJGZtqu4EANR22NBt80S5NYQQQuIZBb+EEEIIiUmMMbi8fuG+3e0fYW9CCCFkZJT2TAghhJCY5PYFwYtKVNo9vug1hhBCZhC/3w+TyQSPJ74zajQaDfLy8qBUKke1f0wHvxzHXQ/gcgBLAbzBGLtc9NhxAP4JoADAFgCXM8aaotBMQgghhEwBp1c60mt30cgvIYRMBpPJhISEBBQVFcVtLQXGGMxmM0wmE4qLi0f1nFhPe24DcB+A58UbOY5LA/AegLsApADYDuDNaW8dIYQQQqaM0xOQ3Ld7KPglhJDJ4PF4kJqaGreBLwBwHIfU1NQxjV7H9MgvY+w9AOA4bg2APNFDZwMoZ4y9HX78HgA9HMctYIxVTntDCSGEEDLphoz8uintmRBCJks8B779xvozxPrI73AWA9jTf4cx5gRQF94+BMdx13Ict32a2kYIIYSQSeDyDhr5pYJXhBBCJiBeg18DAOugbVYACZF2Zow9zRhbM+WtIoQQQsikGZL2TMEvIYTMGn/4wx+Qn58Pg8Ewaa8Zr8GvA4Bx0DYjAHsU2kIIIYSQKUBpz4QQMjswxsDzvOT2aaedhq1bt07q+8Rr8FsOYHn/HY7j9ABKw9sJIYQQMgM4B6c9U8ErQgiZMRobG7Fw4UKsX78eKSkpKC0txfr167Fq1Sq0tLRg7dq1yM7OntT3jOmCVxzHKRBqoxyAnOM4DYAAgPcBPMRx3DkA/gPgbgB7qdgVIYQQMnM4PYNHfin4JYSQyXbin/8zZa/92V0/HfHxqqoqvPDCC7jttttQUlKCSy+9FBs2bJiy9sT6yO+dANwAbgdwcfj2nYyxbgDnALgfQC+AQwBcGK1GEkIIIWTyDR75tVHaMyGEzCiFhYVYu3btkNtTJaZHfhlj9wC4Z5jHvgSwYDrbQwghhJDpQ9WeCSFkZtPr9RFvT5WYDn4JIYQQMnsNTnv2BXh4/UGolfIotYgQQmaeA6UmzySxnvZMCCGEkFnKMWjkF6DRX0IImS1uu+025OXlweVyIS8vD/fcc8+EX5NGfgkhhBASkwaP/AKh5Y7SjJootIYQQshkKioqQllZ2ZDb/R588EE8+OCDk/qeNPJLCCGEkJg0eM4vQMsdEUIIGT8KfgkhhBASk5zeSCO/FPwSQggZHwp+CSGEEBJzGGMRR35puSNCCJkcjLFoN2HCxvozUPBLCCGEkJjj9gXBR7imoZFfQgiZOI1GA7PZHNcBMGMMZrMZGs3o60BQwStCCCGExJxIKc8ABb+EEDIZ8vLyYDKZ0N3dHe2mTIhGo0FeXt6o96fglxBCCCExx+kZmvIMhKo9E0IImRilUoni4uJoN2PaUdozIYQQQmIOjfwSQgiZbBT8EkIIISTmiItdKWSccJuWOiKEEDJeFPwSQgghJOaI054zkrTCbRr5JYQQMl4U/BJCCCEk5ojTnrOSdMJtmvNLCCFkvCj4JYQQQkjMcYrSnsXBr41GfgkhhIwTBb+EEEIIiTlO0dzetAQN5OF5v15/EL5AMFrNIoQQEsco+CWEEEJIzBGP/Oo1CiRolcJ9mvdLCCFkPCj4JYQQQkjMEVd71quVSNBQ8EsIIWRiKPglhBBCSMwRpz3r1QokaFXCfVruiBBCyHhQ8EsIIYSQmCNOe9YNSXumis+EEELGjoJfQgghhMQc5+C0Z5rzSwghZIIo+CWEEEJIzBGv86tXK2AUpz1T8EsIIWQcKPglhBBCSMxxesTVnqUjvzZKeyaEEDIOFPwSQgghJKYwxgZVe6aljgghhEwcBb+EEEIIiSkefxA8YwAAtUIGhVyGBA2lPRNCCJkYCn4JIYQQElMGpzwDkI78eijtmRBCyNhR8EsIIYSQmCIudqVTKwBIg18HjfwSQggZBwp+CSGEEBJTBi9zBAAJVO2ZEELIBFHwS0icaOi04cNtjehzeqPdFEIImVJOj2iZI83QkV8KfgkhhIyHItoNIIQcmNPrx22vbIbN7cfWmi7c//ODo90kQgiZMpFGfnVqBWQcwDPA5QsgEOShkFMfPiGEkNGjswYhcaDC1AdbeKRjV0MPPP5glFtECCFTR7LMUXjkV8ZxktRnm9uHp77Yj8sf/xrflLdNexsJIYTEHwp+CYkDFaZe4XaQZ6hpt0axNYQQMrUkac/qgSS1BM1A6vOLX1fhvc0NaO914Z+flCHIs2ltIyGEkPhDwS8hcaCitU9yv1IUDBNCyEwTKe0ZkM77/Wy3Sbhtc/tR3dY3LW0jITa3D5uqOiUdFYQQEuso+CUkxvGMoapVGuwODoZjhcnsQHmLBYzRCAwhZPzESx31pz0D0uB3sG213VPaJjKAZwy/e2UL7nlrO+761zY65hNC4gYFv4TEOJPZCYcnINlWYeod9cWGyexAm8U5FU2TqO+04RdPfoebX9yET3a1TPn7EUJmLqdnuJFfVaTdAQDbarumtE1kQHWbFfWdNgBAeUsvmrodUW4RIYSMDgW/hMS4ytahKc4WhxfdNs8Bn7uttgtXb/gW1z75HXY39ExF8wSf7GpGIDzn7t/bGqf0vQghM9uwc34HjfzecMoSyDgOAFDdbqWl4KbJlupOyf3v9rdHqSWEEDI2FPwSEuMqTH0Rt1eOIvX5rY11YAD8QR4bPitHkOcntW39eMbwQ0WHcL+hyw6TmUYCCCHjI57zqxOlPeel6oXbJ67Iw6mrC7EoP1nYtr2OUp+nw5Ya6Sj79xUU/BJC4gMFv2TWcnkD6La5o92MAxIHuQtzk4TbFQcoetVj82Bfk0W439TtwBd7TCM8Y/wqTL2wOKQjLuJgmBAyOzHG0NLjgC8wtuXZhit4dfzyfPz88Dm4+Mi5uP7kJQCAg0rThcdp3u/U67K6URdOee7X3ONAU7d92tpgc/nQ66BRfkLI2FHwS2Yls92DXz79HS7++1f4MIZTdF3eABq7QhcZHIDTDyoSHquIkA4t9l1FOwbPCn7pm2p4fIGI+09EpJQ3GgkgZHbjGcMD7+/G1U98ixuf+xF29+irAksKXonSnjVKOS47Zj4uOWoeVAo5AOCgOQPB7476blryaIoNHvXtN10dnpWtfbj0sa9w6WNfYeswbSGEkOFQ8EtmpZe+qUJnX2jU97n/VcJsP/D82Wiobu9D/3VcUUYCVpWkCY/VtttGHE35pqxtyDaLw4v3tjRE3N/rD8IxjiUreMbwQ+XQi57aDtu0FNoihMSml7+pxjfloeNQQ5cdf3lv56inXkgKXmmGr/AMACWZRqQY1AAAu9uPKlryaEptrRmY77tYlHI+HR2ejDE8/cV+uH1B+AI8Hv1oL2wu35S/LyFk5qDgl8w6DZ02fC5aH9LrD+Llb6uj2KLhVYrm+y7ITUKSXo3sZB2A0Dze+s7IaWZtFqdwAaiQcbjquAXCY29trBuSLtbYZccV//waFzzyxZhTo6ta+9ATLr5l1CqxWpSCGCkoJoTMfN+UteGNH2ol23bW9+CZLysP+FzGGFyStGfFCHsDHMdhjST1mUYDp4rHF8CuBrNw/8ZTlkKlCF1KNnTZ0dIztbUedjb0oLxlIOup1+nFk5/vn9L3JITMLBT8klnnua8qh6QDf767BY1d0zdfabTE6/kuzAv1sIvn/UaqBA0A34rSkFeXpuOctcUoTDcAANy+oKT4lc3lwz1vbYfZ7kWAZ/jrx3uxr8kc8XUj+U7U279ufhaOWZwj3P+eKoASMuvUtFvxyEd7hPupCWrh9vtbGvDZ7pGXQvP4g+DDS7mpFTIo5Ae+VDloToZwm+b9Tp2dDT3wB0PnjsJ0A4oyEiRzrqeyw5Mxhle+GdpR/b99rdg8qPr0RPkCQVq7mJAZKq6DX47jUjiOe5/jOCfHcU0cx/082m0isW1XQ49wYcQhlC4HADwLBcWxhDEmCW77g94FeQNpZsNVghanPB+9OAdymUwy+vvd/nbc985OuLwB3PfuTrT3uoTHgjzDn9/ZiY4+Fw6EDaryfPjCLKydlwmFbGDpkdG8DiEk/jHGsLGyA3f/axt8gVCAlJeqx1O/OAqHLcgS9vvbx/tw5xtb8fGOJnT0ueDw+OHw+OH0+MEYG1PKc79VJWnCkkc17dZhOwbJxIjn+66dmwkAOHxhtrBtuA7PQHDiKw1sr+sWOoSVcplktP8f/903qmk7/dN7+v8Nnh/OM4bXvqvBuQ99jssf/xo/VLRTEEzIDDNyLlHs+ycAH4BMACsA/IfjuD2MsfKotmqcxloNk4wNY8CzX1YI949fnoczDy7Gr575HgzA1pou7KjvxtKClOg1UqSzz40+Z2guk16tQF5aaORWUvE5wgVeY5cdjeGqm2qFDIfOD12gHDwnAyetzMenu0KjLhurOnH541/DKpovpVcr4PQGYHX5cM+b2/HgpWuhUcqHbWNNuxVd1tDcaYNGgRXFaVDKZVhZkiZ0Mnxb3o6zDika529hZlPKZeDCF+zD4RmTXDjKOG5UI2E8Y0IwMBgda8hk67Z68OQX+yUFiAwaBe69YA0StEr89ozlaLM40dBlB88YttV2RxyhzUzS4rD5A4Gy7gApzwPvpcTi/GTsaw5VuL/1pc34xQkLcerqwojfsSDPIOMQ8TGeMXCI/FggyAuj0sDw3+Egz09K4a3RHCOCPJuyZezEGIPk73vIvAzhf6VcBn+QR12nDa9/X4PT1hQhQatEeYsF72yqx+bqLhSmG3DO2hIcvSQHStExzB/kJQFmpJ+ZMSaZnnTyqnxccuQ8XPPkt+hz+mC2e3HT8z/iyEU5OHR+JuZkGYXXYIxhX7MFb2+qx7aaLknml0GjwMkrC3DWIcWQyzg8+MFu7KjvAQB09Lnx53d24qA56Vh/4mLkpOgx2ODjc6wY6TzBGMP2um68s6ke5S29yErSYu28TBw6PxMLcpMhl438eRsLOtcM/x0efCyZTnKZbFR/5wP9/TiOk3yX4wUXrz1aHMfpAfQCWMIYqw5vewVAK2Ps9kjPWb9+PQOADRs2TFs7x+LUv3wipBORqaVWyPDcr45GulGLhz/cgy/2Ts0SQJNldUka/nLRIQBCFwpnP/iZMLIyLycR+akGpBs1kHEcqtqt2BFe6/LIRdn4wzmrhNdhjOG5/1Xi7U31Q97jsqPnYXlRKm57eTMC47hoO35ZHm49YzkA4LPdLXj0o71jfo3ZRqdSIDdVj7xUPTIStZCHT5ABnqG91wmT2Yk2ixPegPS4kGbUIC9Vj/xUAxJEI2N2jx8msxMmswPdNg8SdSphPwBoMTtgMjslHR6ETAWjVok7z12N5UWpwrYuqxsPvL9LMmfzQObnJOEfVx02qn0rW/vw+9e2SOYLHzwnHYl6NewuH6xuH2wuP2xuHxxuP1QKGXJS9MhLNSDZoEJHrwstZic6+1zQqhTISzUgL1UPjUqOVnPo+9gzqDiiWiFDbqoBuSl6JBtUaO91wRR+jckoOm3QKJGfGmpjaoJtLlWLAABsoUlEQVRa6NDyBXm0WQaOEeM5Zk9Eok6FN37zE+EC+o//2obNosBYq5IjN0WP2g7bkOemJqixqiQdHeHfVa9TWoMi0nGxz+XDf3c2AwgFEy/dcAxSEzT4fn877nt355D3EL9Gq8WJ6jbriD+PQsZBr1EOe2yUcUBWsg55qQZkJWlhsXthMjvRanHG5HUbByAjUYu88Genf958kDFsqe4SOsgHUytDf7e8VD2yk3RjDoQZgB67B6bwuWYsFd5nKvFn0aBRojX8ve0fOIgGGcchO1mHvFQ9clP10IQr5zMAFocnfB1x4GuFIxZm4c5zV09Di8ct4gc4noPflQA2Msa0om23AjiKMXbaoH2vBXDtddddtxqg4JcAFx5WiiuODaUBd1nduGrDN0IwGYsuPnIuLjlqnnD/lpc2oazZMsIzQv543mqsE6Ub9nt7Yx2e/d9AmveRi7Jxx9krwXHcuAPXey9Yg7XzQqPMNpcPF/71S1pyhJBZhgNw8qoCXHHsfBi1qoj7dPS5sKW6ExurO1HXYQMfPk74AvyQc+CqkjT8v3DH32i0Wpy4/52dQ9ahJZPrJ8ty8dszVgj3a9ut+OOb24d0DkyFMw8uwnUnLhbuv/ptNd74oXZUHQAcBrIJgjyDxx95ZOuCdaVw+QL4eHvTkBohhJCQeA1+4znt2QBgcFeeFUDC4B0ZY08DeLp/5DdWKRXxlzoQbzgOWFqQggsPnyNsy0jU4lcnLcbzX1VJRgxiRWmWUbK+LwBcctRc/N/7u2EZVLVZLM2owRrR+pdi560rRWqCBi98XYXSTCNuOX25kJZz4op8mO0evLOpflQdAjIZh8MXZOHguQMFZ4w6Fa4+bgFe/6EWHh+lPUXCGBv1aI04rSjI8xMeUZJx3KSmthHCcaFR2qt/sgALcpNH3DcrSYczDi7GGQcXS7Z7/UF8sdeEdzfXo80SqhUwLztxTO3ITdHjr1esw5Of7xdGCieTjAulDPYbrsOaA0Y1PWEkPGOj7kCcztTDnBQdLjpirmTbnOxEvHD90fimvA3vbKpHU7dDaNexS3NwyqoC7Gk044OtjUPOW+Lj0YGOizq1AuevK5Vsu/ioeThrbTF21PVgc3Unttd1DxmxUsplOH55Hs5ZW4y8cCYMzxg2V3cK6b8AkKBV4ndnrhAKqB2/PA9Pfb5/xGyFWEz7DAT5EYN2jVKOk1cV4KerCtBqcWJzdSe21nbBbB/+mmI85DJu2Ok3s8FIn+fJOEaM12gH2g50rSA+FsaTeB/5/ZExphNtuwXA0YNHfvvFetozIWPBGIPF4RXSXPvnBwOASiHDYQuyIs5RIrGBMQary4eW8N/PIrro4Dgg3TiQspagHUhtDgR5IbWy1eKEVzRyoVLKwilr4dQ8hzeUrmlxAowJaZzpidpZfUFCYluQZ9gRDmAGzw8di7JmCypb+2DQKGDUqpCgUyFRq4RRp0KCVgmnNyCkM/c5vchMCqUB5qTo4RRNIfD6g8hJCU0fyErWSi74bG6fsJ/V6UOW6DXUI9RLGA3GGMx2L0xmB1rMTsl6tjIZh8xELfLTQinXo50bPR0YY9hZ3wOTxYnDF2QhNUEjPOYLBLG5ugu9Do/wO01P1EqC3+GOi3IZh7XzMlGUMWSMY8j79zl9wu8NANbNz0SSXj3scypbe1HTbsW6+dL29vP4g+HPigNdVjeS9Grkp4WOtYZRFmWbTv4gj/Zwem2rxSnpyE7Sq3DkohzJeaWfzeVDi9mBVosTPTYPxhMiGHVK4VyTlqA54Jz1mWzw59nlDYTTjQ3ITtZFrePE4wug1eJEi9mJjl6XpJPNoAlN+chPMyAtPJ0ujs24tOf+Ob+LGWM14W0vA2g70JxfQgghhBBCCCEz14YNG4YEwPE5Xg2AMeYE8B6AP3Ecp+c47jAAZwB4JbotI4QQQgghhBASa+J25BcIrfML4HkAxwMwA7idMfZ6dFs183Ect50xtiba7SBkJPQ5JfGAPqckHtDnlMQ6+oyS0YqdSSLjwBizADgz2u0ghBBCCCGEEBLb4jbtmRBCCCGEEEIIGS0Kfsl4PB3tBhAyCvQ5JfGAPqckHtDnlMQ6+oySUYnrOb+EEEIIIYQQQsho0MgvIYQQQgghhJAZj4JfQgghhBBCCCEzHgW/hBBCCCGEEEJmPAp+CSGEEEIIIYTMeBT8EkIIIYQQQgiZ8Sj4JYQQQgghhBAy482q4Hf9+vVs/fr1tLYTIYQQQgghhMwyimg3IEooACaEEELiBWMAx0W7FYQQQuJHxJPGrBr5JYQQQkic+e4T4DcXAG8+He2WEEIIiXMU/BJCCCEkdn38OuCwAV+8B/T2RLs1hBBC4hgFv4QQQgiJTYwB1t6B+23N0WsLIYSQuEfBLyGEEEJik98HBAMD99sp+CWEEDJ+s7XgFSGEEEJincshvd/eEp12EELIDOP3+2EymeDxeKLdlAnRaDTIy8uDUqkc1f4U/BJCCCEkNrld0vsdFPwSQshkMJlMSEhIQFFREbg4rabPGIPZbIbJZEJxcfGonhPTac8cx13Pcdx2juO8HMe9OOix4ziOq+Q4zsVx3NccxxVGqZmEEEIImQo08ksIIVPC4/EgNTU1bgNfAOA4DqmpqWMavY7p4BdAG4D7ADwv3shxXBqA9wDcBSAFwHYAb0576wghhBAyddxO6X1bL+C0R6cthBAyw8Rz4NtvrD9DTAe/jLH3GGMfADAPeuhsAOWMsbcZYx4A9wBYznHcgmluIiGEEEKmyuC0Z4BSnwkhhIxbTAe/I1gMYE//HcaYE0BdePsQHMddy3Hc9mlqGyGEEEImw+C0ZwBoN01/OwghhEy7k046CcuXL8fixYvxy1/+EsFgcMKvGa/BrwGAddA2K4CESDszxp5mjK2Z8lYRQgghZPIMTnsGaLkjQgiZgRhj4Hlecvutt97Cnj17UFZWhu7ubrz99tsTfp94rfbsAGActM0IgCYCEUIIITOFK1LwS2nPhBAyqa4+aepe+9lPh32osbERJ598Mo455hi88cYbSEpKwsknn4xNmzbhgw8+QGFhqJ5xIBCAz+eblDnK8TryWw5gef8djuP0AErD2wkhw2msBj57B7Baot0SQgg5sEgjvzTnlxBCZoyqqipceuml2LVrF5qamoTb/YHviSeeiIyMDCQkJODcc8+d8PvFdPDLcZyC4zgNADkAOcdxGo7jFADeB7CE47hzwo/fDWAvY6wymu0lJKa5ncAjvwfefhZ49fFot4YQQg4s0pzf7g7A75v+thBCCJl0hYWFWLt27ZDb/T777DO0t7fD6/Xiq6++mvD7xXra850A/ii6fzGAexlj93Acdw6AxwG8CmALgAuj0D5C4kd7y8AoSj31ExFC4kCkas+MB7ragNyiaW8OIYTMSCOkJk81vV4f8baYRqPB6aefjg8//BDHH3/8hN4vpkd+GWP3MMa4Qf/uCT/2JWNsAWNMyxg7mjHWGN3WEhLjrL0Dt512gLHotYUQQkZDnPas1g7cpqJXhBAyozkcDrS3twMIzfn973//iwULJr6qbayP/BJCJotNNM834Ae8bkCji157CCHkQMRpz8XzgcrdodtU9IoQQmY0p9OJ008/HV6vF8FgEMceeyx++ctfTvh1KfglZLYQj/wCgMNGwS8hJLaJ055LFlDwSwghM0hRURHKysqG3AaAzMxMbNu2bdLfM6bTngkhk2hI8EsrgxFCYpxbNPJbIkp3o4rPhBBCxoGCX0Jmi8HLGzms0WkHIYSMBs8DHvfAfUnwawo9TgghhIwBBb+EzBa2QSO/Thr5JYTEMI9roDCfRgcYk4CExNB9nxewdEWtaYQQMhOwGVD8dKw/AwW/hMwWg0d+7TTySwiJYeJKz9pwfYKs/IFtHabpbQ8hhMwgGo0GZrM5rgNgxhjMZjM0Gs2on0MFrwiZDRgbOueXRn4JIbHMJQp+dYbQ/9n5QE24IMq3/wUWrgTk8ulvGyGExLm8vDyYTCZ0d3dHuykTotFokJeXN+r9KfglZDZwO0PLG4k5bNFpCyGEjEakkd+lBwHffRK6vWsj8PzDwFW3AjIKgAkhZCyUSiWKi4uj3YxpR2nPhMwGfZah2yj4JYTEMvHIr1Yf+n/FocBPzhzYvuVr4MW/UfErQggho0LBLyGzweBiVwAFv4SQ2CZe5qg/7ZnjgAt+ARx96sBjG78A3n9xWptGCCEkPlHwS8hsMLjYFQA4KfglhMQwt2vgdv/ILxAKgH++HjjipIFtX34gTZMmhBBCIqDgl5DZYHCxK4BGfgkhsc0lHvnVSx+TyYBLbgRyi0L3/T5g58ZpaxohhJD4RMEvIbMBpT0TQuKNO8KcXzGZDDj0uIH7m7+a+jYRQgiJaxT8EjIbREp79nlD/wghJBZJljqKEPwCwMFHh9KgAaByN9BnnupWEUIIiWMU/BISj+xW4IOXgB0/jG7/SGnPAI3+EkJi14FGfgEgJR2Yvyx0mzFg6zdT3ixCCCHxi4JfQuLR6xuAj98Anrwf6DAdeH/xyC8n+to77ZPfNkIImQzi4Le/2nMka48duE2pz4QQQkZAwS8h8cblAHaFC7swBjTVHPg54jm/GdkDtx3WyW0bIYRMFsk6v7rh91t1OKBQhm431wGtjVPaLEIIIfGLgl9C4s2uTUDAP3C/p3Pk/QOBUJo0EJobl50/8JiDRn4JITFKkvY8wsivTg+s+P/t3Xd4FNXXwPHvTS+EQCDU0HvvRToI0puICvgi2FBs2FBR7P0n2LGDghRBpBelgyBNeu8EQkmBNEjf+/4xyWSX9L4bzud5fNyd3Zm9CTezc+aee2771Oc7NhRcm4QQQjg0CX6FcDS7Ntk+D8si+I0KT31cwhdKlk59LiO/Qgh7lZ2CVynaWac+bwCLpWDaJIQQwqFJ8CuEI4mOhKN7bbdlFfxaF7vyLQ0lStoeTwgh7FF2Cl6laNIavH2Mx9eC4ezxgmuXEEIIhyXBrxCOZM9WSEqy3ZZV2nOkVbErXz/wtgp+peCVEMIeJcQb/wE4O4Obe+bvd3GFxq1Tn2enFoIQQojbjgS/QjiSnZvSbgsLzjzFL83Ir0/q8yhJexZC2KGYm6mPPb1T1/LNTNVaqY8vns3/NgkhhHB4EvwK4SgirsPxA8ZjpVJHQhITbKs5p9nPauS3pJ8x7zeFjPwKIexRTlKeUwTUSH0swa8QQoh0SPArhKP4bwvo5BHeOo2hglXV5rDgjPfLbORX5vwKIezRzejUx7kJfoPOS9ErIYQQaUjwK4Sj2LU59XGbLlCmXOrzzIpeRd4S/HpLwSshhJ2zHvn1ymSZI2slS6dmtsTFZF0MUAghxG1Hgl8hHEFkOJw8ZDxWTtCqM5Qtn/p6ZkWvIm4peGWT9izBrxDCDlkvc+Tplb19lJLUZyGEEJlyKeoGCCGywXrZjpr1oGQpKGMV/OYk7dnL2wigtcUoKpOYYFRKFUIIe5GbkV8wgt9j+4zHF89Ciw752ixh5eRh2LIK4uNTt9VtDN0HZq9AmRBCFAEJfoVwBNbLdlSva/zfeuQ3o/Q+rdMWvHJyMtbDjE6u9HwjyhgRFkIIe3EzFwWvQEZ+C0tCPHzzTur3SIrdm8G/IjRpUzTtEkKILEjasxCOwDr4rVbH+H+ZbKQ9x8VAfJzx2NUtNX2wIIpeaQ1rF8Mf0400bSGEyK2YXKQ9gwS/hSXwdNrAN8W+7YXbFiGEyAEJfoVwBOdPpT6uVtv4v3XBq2vBRvB5q1tTnlNS0Qqi6NW+7TDvO1g9Hz6YAFcu5s9xhRCOK+gc/PY17P03Z/vlNu25UlVjWgdA8CWIi83Z54rsOX0k9XGD5jB0TOrzlLRzIYSwQxL8CmHvwsOM/8BY27di8hJHXiVSLwrj4yAqnbvwNsGvVWqzTwEEv3u2pj4OvQIfPQ+njmT8fiFE8aY1fPcBbFwO37wNi2emf5MuPblNe3Zzh/KVUz8/6Hz29xXZd/po6uPWneGuu1PXnr8aBNdCiqZdQgiRBQl+hbB31qO+VWuBk3Pq86xSn23m+5ZOfZzfI78WCxzabbstOhKmvAL7d+T9+EIIx3P+JFwOTH2+fA7MmAKJiVnvazPym4PgF25JfT6Ts31F1rSGU4dTn9dqaEyrqd0oddvRvQX3+RYLrJoPy2YbBRuFECIHJPgVwt6lN983RVZr/d66zFGKElbBb34sdxR4GqLCjcdeJcAneTmlhHj46RNJPRTidrRzU9pt29bCl29kfU64GZ36OCcjvyDzfgta6NXUrCJPLyPVHIz05xRH9xXc529eBQunw5JZMP/HgvscIUSxJMGvEPbOptLzLcFvVhWfgy+lPva1Gvm1Dn6jo/LWPrAd9W3aFl79DEqXNZ7H3ICDO/P+GUIIx2GxGJV/U9RqkPr4yB74/fvM94+5mfo4LyO/Qedytq/ImvV835r1U7ORbILfvdlPcc+p7etSH29cDpcktV0IkX0S/Aph785lNvKbSfAbFwvb16c+r1Ev9bG3dbXnDCp25sShXamPG7eGcpWgU+/Ubbs2p91HCFF8nTmWOu/TqwS89AkMeiD19c2r4EAmN8Vi8jDyW+WWkd+CCsJuV9bBb62GqY+r1kqtQxFx3TblPb+Eh9nON7ZYYP5P+f85QohiS4JfcfvashrmTEtN17VH4WGpqcvuHlAhwPZ167TnW+f87tiQmjroXxEatkh9LSUtGfI+8nsjCk4fMx4rBY1aGY/bdE19z4GdEHsz7b5CiOJpl1XKc6tO4OIKA0cZxZFS/Pp5xuefm7ms9gzgVy51eaQbUakFA0X+OGUVfFoHv07OUK9p6vOCSH3euy3tzYxDu9LWnBBCiAxI8CtuT7u3GBde65fCt+/b78iAdbGrKjVti11BxmnPWsO6JanPuw+03dem4FUeR36P7AVtMR5Xr5saWFeqmpp+mBAvaz8KcbuwJBnn2BRtuhj/VwpGPZVafC/iGsz5Ju3+WtumPXvkYJ3flM+Reb8FI/Zm6u9TOUHNeravF/S83/+sVhWwnsoz/wdISsr/zxNCFDsS/IrbT0I8/GGVJnXiIBz+r+jak5lzJ1IfV6+b9nWbtGertX5PHEyd6+bmDp3ust2vhFXa840o46Jh5e/wy1SjIE1ORsOt77g3bm37mvXo7650it8IIYqfE4dSM1Z8fKFes9TXfHxh9DOpz3duhH/+st0/Lib1hpq7B7i45LwN1sGvdd0EkTdnj6f+2wRUT5uS3sAqw+j4gfwNSKMi4MSB1OfPvgvunsbjS4GwaUX+fZYQotiS4FfcftYuTpsi/Ocv9jn6az3yW6122te9SqSm98XFpi5btH5p6nvu6Jk2bbCEddpzpFF85s8Z8M/fMP1TeH4EfDDBdu3e9GidRfDbJfXxof+MQFsIUbxZz/Fv1Rmcb8lYaX4HdOiV+vyXz+CLyXDlovE8t2v8WqtsFfwu+c2Y4pIfxf1ud6cymO+bokKAbbFD6++wvNr3rzHHN+Wzq9aG/venvv7797D17/z7PCFEsZSL26lCOLCI67BiXtrtgaeMQK9Vp8JvU2YyW+YIjPQ+v3Kpo7xhV42R7b3bUt/TY2Da/bxvGfm1DpbBCGrPHINp78LdY6DvfcZn3erCmdQRHm8fqHHL6HS5SkaF6nMnISkR9v6bdhRaCFF8xMbAnn9Sn7ftmv777n8cTh6CkMvG84O7jCkUnftA5eqp78tt8NuolZH1Eh9njFSuX2qMMg8dA517p51CIrLHJvhtkPZ1paB+c/h3rfF843IjPdm6PkVu/WfVr1p1NP7fa6gR8F4NMkaZZ0w1Cq0NGJn+d9atLBbj++ngTuM6wPomeLlK0KQN1G1irGN8uwo8BWuX2E6RKlMe+txjm30mig+tjSzAEweh411Qt3FRtyhfOXTwq5TyA34G7gJCgVe11nOKtlXCri2ZmVp4qUIVY6Ry7SLj+aJfocUd9nNRlFWxqxRly6cGv5cvGFVUU+6O129ueyGZwtnZGA22XksTjC95S5JRwColte3PX4yU6pFP2o7ghF21nVfcqGX6v7s2XVMrVu/aJMGvEMWR1kZwueAnIz0VoFQZqN0o/fd7ecOkz2HRL0bxQa2NG2Qbl6d9X274V4DXv4S536bOPY2OhFlfGumxI8ZDnQzaZs/iYuHfdcZUncSE1O1+/tC4jVHY0N2jYD7bYoEzVsWuaqcz8gvGvN+U4HfbGuO/ytWhbTfo0je1LkTsTdi6xrjJW7GqsUxepWrpB603o23nELdMDn5d3eDFj43MgZS5yEtmGRlJWRVK09oYmc5sms/axcbvs2FL6NrPuKmSnaDaHgVfMvr+Jasq3M4uRp/p0As8PG3fn1I7ZMFPxt/mrXZsgAcn2N+ggcib6EhjClxKnZZta6D/CKNg4a1ZPA5KaXtM9cwmpdRcjNTth4HmwAqgg9b6cHrvHz9+vAaYNm1aYTUxZ75+CxKlYEPB0XB4T2pQ9+y7xvI/r4xJDYh7DjW+AIKD4GYRVye+GWWMvoJxkfbylPTfN2da6sitckr9+QCefANadEh/v1fHpo66gLFe44sfG6MlkeHww4dwbH/q61Vqga+f8fhacNq1FR96ETr0TPs5YcHw8mjjsZMTNGyVfntuRz4loXxlKB8AfmVBpffFoo1/j6tBRr+MDDfSCisEGCMTXj7p7JOF+FjjQuhqkPH/hISs9xEiMxFhRiaItXsfg7vuznrfcydh7jTbJWxSNG4NE97Lfbu0NrJ65v9gnIusNW1nTCcpXxl8SkHoFeNvLOSKUWSrQvLfpruH8bdyNciYMmOxOsd6eRv7VwgwppOEXjHeF3I5f/6uSpWGcpWNzzh/EjatzHz6iIurcS53K4AAODEBju0zHpcsDVPmpB8IRkfB64+kX0zR1Q3uuNOYq/vPatvCZmBkMtVtnHx+qwxl/I3z4rF9xtQcMLKgJn9lu1/MDaN45ZE9ef0pM1epKtw5xPg+BIzz8/XU/hEVYdyIKF/ZOD/H3LR9rSCl9MXylY0RWefk8a0bkUa/2b894+ldnt7QpQ+06GjcxNbJdUD278j6c7sNSP7uV4A2btyn/Mzh1/Lrp3NcGX3PJyUmn3MuwdWLhXvN6eZm9M+U/1LOFylFCK+Hpt2nTiPj3zrkcuq/b+vOcNewwmt3zqV7p8phg1+llDdwHWistT6RvG0WEKS1fiW9few++H18oO2dXFFwGrWC5943Hi+bbdwptmc9hxhpgun5eyHM/zHt9loN4eX/ZTyS/cGE1OC6TDmY9IVt9cyEeGMu3o4NWbfPxxfe+8k2ndrah8/brg0phCi+fEvD3Q8ZF8TZHSXT2ghw9u8w/ku5MTdyPPQYlPc2xcfBX38YF/QJ8Xk/3u2uRQfj5mpGIq4bmT4Hd8Lxg/l7bXP3GOh3f9rtiYnGyH5O5/36+BrpzQ1bpqbZJyYYafkHdhrBye2uWh1jfrWzizFY8OeMtDeTRPFTISC1FkN62nWHR18uvPbkXLpfQI6c9lwXSEoJfJPtB9JMMFJKPQY89sQTTxRW24Q98/CC+8alPu81FNYtzfuSPwVFORknmIxUqmb73K8c3DkIuvbPPIW7dWcj+PUpBc+8Yxv4gnGH/uGXjMB45e9p93dxhfrNjFS1Nl0yDnzBGP35VoJfIYo1ZxfjRt2AETmfq6uUUSm4QQvj/Bx8yQhYq9TMn7a5uRtpex16GjcLreePOpqyFYxaDilTYZIsxqj5wZ2pU2AKWscspq/4ljb6Qs8hxjzwvVthzWJj/qi18pWNkeCLZ41U7ltHgm+llFFELT0uLjD2eeP7Juxq+u+5VUk/qFrLyEq6VatOxk3nyxeMdOEtfxmVyB1Z4zbG34BH8khfyBUjc+xqUMb79Lobho01vvNTNGljLBfpyH9HImPePsbfUtO2sHI+LJ1lm/GSIrN+Y8cceeS3M7BAa13BatujwCitdbf09rH7kd9Du9PvXCL/KGVcTJUqY7v9xCFYOc+4QEpJTynpSwY3jQpXQA0jjSojFgv88bMxUtK2mzEXKjvzMrQ2vtT9/NPO9blVyGXjvSnc3I2U8ZzMLbt8wTbN+nanNYSHwpXkdOaI6xm/19PL6JPlKxsXlWEhRppUSoCQU87OxgV0SopcbosKCZEio3Orvbp41lhKLuXvLyrcSBVNSVe9GQ1XLxmjHglxxrbylcG/olXxI2383V5NTluMjjRqMKQcI6frE9/KYjGmmKSkGKakDDdvn/GNzbCrxpzOgry2Kx8A5SvlfD+tjdHUjSuM0ffOfYy09pTAMzERzh4z2n81yPidWp8XnV2gYy9j3nBRuHnDSNXet932vOvpnZoiX7KUkRofHATBl43v1pRzd+myBThfOHl6zJXk31t4WGofUMooPNl9kJG2fSuLxSg4t2W1sV+KEiXhzsFGoJvuR+rkOd1rjbnoKbx9UqcC+PnbTx2VopDZ97xSRp8oimvOmBtWUzmu2C5JFlAdBv2f7XXnqSOwfonx71yucmp/T+nX9qvYpT23ALZqrb2str0AdNNap1PeNjX4FUIIIYQQQghRfE2bNi1NAOzI6/yeAFyUUtbrvzQD0i12JYQQQgghhBDi9uWwI78ASql5gAYewaj2vJJMqj2L/KGU2q21bl3U7RAiM9JPhSOQfiocgfRTYe+kj4rscuSRX4DxgCcQDMwFnpDAVwghhBBCCCHErRy52jNa62vAkKJuhxBCCCGEEEII++boI7+iaPxQ1A0QIhuknwpHIP1UOALpp8LeSR8V2eLQc36FEEIIIYQQQojskJFfIYQQQgghhBDFngS/QgghhBBCCCGKPQl+hRBCCCGEEEIUexL8CiGEEEIIIYQo9iT4FUIIIYQQQghR7EnwK4QQQgghhBCi2Lutgt/x48fr8ePHy9pOQgghhBBCCHGbcSnqBhQRCYCFEEIIIYQQonhS6W28XYNfIezG7KOz2Re8jwreFahasirVS1anebnmuDq5FnXThBBCCCGEKDYk+BWiCO24vIOPdn6UZnvTsk2Z2Xcmzk7ORdAqIYQQQgghip/bas6vEPZm44WN6W4/EHogw9eEEEIIIYQQOSfBrxBFaOeVnebjwbUG07JcS/P5zCMzi6JJQgghhBBCFEuS9ixEEQmLCePE9RMAuCgXJrWbRHRCNL0X9ibRksie4D0cDDlIE/8mRdxSIYQQQghR3CUkJHDx4kViY2OLuinZ5uHhQUBAAK6u2auVI8GvEEVk15Vd5uMm/k3wcvXCy9WLvtX7suzMMgBmHZnFJ10/KaomCiGEEEKI28TFixfx8fGhevXqKJVusWS7orUmLCyMixcvUqNGjWztI2nPQhSR7Ze3m4/bVWxnPh7daLT5+O/zf3M5+nKhtksIIYQQQtx+YmNjKVOmjEMEvgBKKcqUKZOjkWq7Dn6VUu5KqZ+VUueVUlFKqb1Kqb5Wr9+plDqmlLqplNqglKpWlO0VIies5/u2q5Aa/Nb3q28+T9JJzDk2p9DbJoQQQgghbj+OEvimyGl77Tr4xUjLvgB0BXyBycB8pVR1pVRZ4M/kbX7AbuD3omqoEDlxKfoSF6IuAODh7EFT/6Y2r1uP/v5x4g9uJNwo1PYJIYQQQghR3Nh18Ku1vqG1fktrfU5rbdFaLwfOAq2Au4HDWusFWutY4C2gmVKqfhE2WYhs2XF5h/m4ZfmWuDm72bzeqXInqpesDkB0QjRLTy8tzOYJIYQQQghR6MLDw5k2bVqBHd+ug99bKaXKA3WBw0AjYH/Ka1rrG8Dp5O237veYUmp3YbVTiKzsuJIa/FrP903hpJwY1WCU+XzFmRWF0i4hhBBCCCGKSkEHvw5T7Vkp5QrMBn7VWh9TSpUAQm55WwTgc+u+WusfgB/Gjx+vC76lQmROa20z8ms939dan+p9+HjnxyTqRPaH7OdC1AWq+FQprGYKIYQQQojbVJNfC26pzYMPHszwtVdeeYXTp0/TvHlzevXqhb+/P7NmzcLJyYm+ffvy0Ucf5emzHWLkVynlBMwC4oGnkjdHAyVveWtJIKoQmyZEjp2JOENoTCgAPm4+1PdLP1O/lEcpOlbuaD5feWZlobRPCCGEEEKIovDRRx9Rq1Yt9u3bR48ePVi8eDE7duxg//79TJw4Mc/Ht/vgVxklvH4GygPDtNYJyS8dBppZvc8bqJW8XQi7ZT3q27ZCW5ydnDN8b/+a/c3HK86uQGtJXhAip7TWHAw5yKwjs5i4aSIDFw3kyXVPEh0fXdRNE0IIIUQG1q5dy9ixY/Hy8gLAz88vz8d0hLTnb4EGQE+tdYzV9kXA/5RSw4AVwBvAAa31sSJooxDZEh4bzuyjs83n6c33tdY1oCueLp7EJMZwNuIsx64do0GZBgXdTCGKlde3vp6maNy5yHNMPzSdZ1o+U0StEkIIIexXZqnJhUVrne9LL9n1yG/yur3jgObAFaVUdPJ/o7TWIcAw4H3gOtAOuL/IGitEFuKT4nl2w7MERgUC4O7sTvcq3TPdx8vVizur3mk+l8JXQuTMzYSbLDu9LN3XFpxYQGxibCG3SAghhBAZ8fHxISrKmMV61113MX36dG7evAnAtWvX8nx8uw5+tdbntdZKa+2htS5h9d/s5NfXaq3ra609tdbdtNbnirjJQqRLa83krZPZE7zH3PZBpw+o4F0hy32tU59XnV1FkiWpQNooRHF0Ovw0GmO6QBmPMkxqN4mK3hUBCI8LZ9XZVUXZPCGEEEJYKVOmDB07dqRx48asW7eOQYMG0bp1a5o3b86nn36a5+M7QtqzEEXqbMRZtgZtpYpPFZr4N8HPI+fzDb7Z9w0rz6YWrHq+1fPcVf2ubO3bvmJ7/Dz8uBZ7jeCYYHZf3Z1lurQQwnDi+gnzcesKrRlRfwSxibFM/W8qAL8d/Y0htYfke1qVyD2tNdsvb+fyjcv0rdEXTxfPom6SEELYlfWB61lxZgW9qvWiT40+Rd2cfDdnzhyb56+88kq+HVuCXyEyERQdxKgVo4hKSC0iHlAigGF1hzG20dhMi1WlOBR6iO8PfG8+H153OGMajcl2G1ycXOhdvTdzj80FYOnppRL8CpFNJ8NPmo/rlKoDwN117ubb/d8SkxjDiesn2H11N20qtCmqJjqE67HXGbdmHKfCT+Hr7ouvmy9lPcvSvWp3htQegrerd758TvDNYN7b/h4bLmwA4Ez4GV5s82K+HFsIIRxdaEwoH+z4gDXn1wCwLnAdTf2bUqlEpSJumeOw67RnIYqSRVt4/Z/XbQJfgIvRF/lizxc2hasyorXm450fm8/bVWjHpHaTcjzK1K9GP/PxstPL2Bq0NUf73yrRksje4L38evhXVp1dxc2Em3k6nhD26uR1q+C3tBH8+rr7MqDmAHP7nKNz0uwnbC08uZCj146SYEkgNCaU0xGn2XFlBx/t/Ig7F9zJxzs/5lL0pVwfX2vNopOLGLJ4iBn4gjHVQ6rcCyEErDm/hiFLhpiBL0CSTsqwroVInwS/QmRg1pFZ7L66GwAn5UTTsk1xdXI1X/9q71cERgZmeoxVZ1exL2QfYIzgTr5jMi5OOU+4aObfjPYV2wOg0byy5RWu3LiS4+Nsv7ydiZsm0vX3roxeNZpPd3/KxM0T6T6/O6/98xrbgraRkJSQ9YGEcABaa5u057ql65qPRzUYZT5ef2E9QdFBhdo2R3M24myGr91IuMFvR39j+LLhnIk4k6vjf7v/W97Y9kaam43BMcE2/4ZCCHE7OhN+hombJxIRF5HmtaWnl+brTUJHu+GY0/ZK8CtEOk5eP8kXe74wnz/S5BFm95/NthHbqFe6HgCxSbG8se0NLNqS7jFiEmPMeYUADzR4gGolq+WqPUopPuz8If6e/oBRqOeFjS9kO1ANjw1n0pZJPPr3o6w6t4rI+Eib128m3mTp6aWMWzuOTvM6MWHDBP448Qc7L+/k+LXjXLlxhURLYq7aLkRRCY0JJTwuHAAvFy+btLBapWqZN5Qs2sL0g9OLookOw/pG3yddPmHhoIW83u51avjWMLdHxkfywfYPcnwhcjj0MD8c+MF8XsWnCk39m5rPtwRtyUPLhRDC8W24sMG8DqvoXZGvenxFCdcSAARGBZoDLXnl4eFBWFiYwwTAWmvCwsLw8PDI9j4y51eIWyQkJTDpn0kkWIzAsoFfAx5v9jgAHi4evNPxHUauGEmSTuK/q/8x//h87q+fdpWtXw79wtWbVwHw8/DjsaaP5aldZT3L8mnXT3nor4dI0kkcCD3Ak+ueNANqb1dvGpVtRNOyTSnvXZ5ESyKXoi+xN3gvU/+byrVY2/Lw5bzK0a5COw6FHbIZ1bmZeJN1getYF7jO5v1eLl7cUekOOlfuTKvyrYhLiiMyPpIbCTeo71c/W5WrhShM1inPtUvXxknZ3u8d1WAU2y9vB2D+iflU8K7Ao00fLdQ2OooLURfMx838m1GpRCXqlq7L8HrD2XBhAy9sfIEkncSOKzv46/xf9KmevQIsCUkJTN42mSRtVLFvVb4V3/b8lrXn13Ig5AAAWy5u4ZEmj+T/DyWEEA7iv6v/mY+faPYE3ap0o3f13iw8uRCAJaeW0KJcizx/TkBAABcvXiQkJCTPxyosHh4eBAQEZPv9EvwKcYuZR2Zy7NoxANyc3Piw84c26c4NyzTkocYP8ePBHwGY+t9UOlXuRIBP6h/ehagLTD+UOpL0dIun8XHzyXPbWpZvyXOtnuPT3Uap938v/8u/l/9N877S7qWJio8iUacdre1Xox8PNX6IuqXropRCa82RsCMsP7OcDRc2ZJj+mVFQDOCsnBlUaxCPNX2MAJ8ArsVeY2vQVo5eO4qfhx/VSlajqk9VavjWwM3ZLY+/BSGyx7rYlXXKc4ouAV3oXLmzObL45d4vcVJOPNzk4UJroyO4kXCDsNgwwJi+Ud6rvPmak3Lizqp3MqL+CH47+hsA/9v5PzpX7pytIlg/HvzRvEnh6eLJux3exdPFk46VO6JQaDT7Q/YTEReBr7tvAfx0Qghh35IsSewN3ms+b12+NQCDaw82g9+/zv3FK21fwd3ZnV8P/8rmoM3cXedum/oW2eHq6kqNGjWyfqMDk+BXCCvXYq/x08GfzOfPtHyGWqVqpXnfuGbjWBe4jjMRZ4hJjOGRvx9hWs9p1PStybmIczy65lFik2IBqFe6HkNrD823No5uOJp9wftYG7g2w/dcj7ueZls5r3JMbj+ZblW62WxXStGobCMalW3ExDYTORt5li0Xt7AveB/XYq8RGR/JtdhraUaOrSXpJBadWsSy08uoVaoWJ66fMNdWtVbSrSQPNnqQUQ1G5Vt1WCEyYj1XNKXSszUn5cTUblN5av1T7Li8A4DP93yOi5MLDzZ6sNDaae+sR30DSgSkW+V+fPPxrDq7irDYMIJjgvl+//c83/r5TI97/Npxfjzwo/n8mRbPUKVkFcDIlmlctjEHQw+SpJP49/K/2R5NFkKI4uTE9RNEJ0QDUM6znDnY0ty/OVV9qhIYFUh0QjRrzq9h15VdLDq1CIBdV3axL3gfL7d5GVdn1wyPn5GEpAT+C/6PLRe3sDd4L3VL1+Xlti87/PJzEvwWM0tPL2Xu0blUKVmFzpU707Fyx1ytS3u7+n7/9+YJpnrJ6oxsMDLd97k7u/Nux3d5cNWDJOpEgqKD+L+V/8dzrZ7jq71fmYGii5MLr7d/PVtLImWXUopPunzC3+f/til8cPXmVQ6GHuRQ6CFiEmMA4yRZtWRVWpRrwdjGY7McfVZKUdO3JjV9a9pc/GutzaB4y8UtnI08i4+rD77uvsQnxXMo7BAAiTqR49ePZ3j8yPhIvtr7FTOPzGRMozGMajDK4U+iwn6lV+n5Vh4uHnzV4yueXPcku67sAmDK7il0rtyZmqVqFko77Z118Fu1ZNV03+Pj5sMLrV9g0j+TAKNgYJeALrSu0Drd9++8vJO3/33bzE5p7t+cEfVH2LynU+VOHAw9CBipzxL8CiFuR9Ypz63KtzJXDFFKMajWIL7e9zUAb217i3hLvM2+vx//nRPXTzCu6Tgu3bhEYGQg7s7uDK49mCo+VdL9vGux1/hm7zcsP7Ocm4mpq4EcDD3I2YizfHPnN5RwK5HfP2ahUY4yoTk/jB8/XgNMmzatqJtSIM5GnGXokqHm3CkAhaJD5Q5M6Tol30faYhNj2XppK/FJ8fi6+1LKvRRVfKrkS3pvUTgXcY6hS4aaF2Nfdv+S7lW7Z7rPpgubeGnzS2awac3D2YMvun9Bh8odCqS9GUm0JHL15lVKu5fGy9WrUD5z95XdfLPvG5vq2M39m9O2Ylui46M5H3me49eOExwTbLNfTd+afNLlE+r51SuUdorbR6IlkXaz25kXAv/c/0+mabM3E27y6JpHzXmmYxuNzXLk8nbx88Gf+XzP54AxT/qVtq+k+z6tNWNWj2FP8B5zW3P/5oxqOIr6pesDxvSJnw7+ZLNUh5uTGwsGLaCmr+3NhoMhBxm50rgBWcajDOvvXZ9m3rYQQhR3z214zsz2e73d69xX/z7ztcvRl+m9sHeabLuUEeGMuDm58WCjB3mkySPmtWJCUgJzj83lu/3fpam8b61RmUZ82/NbSnuUzsuPVRjSXVdURn6Lkc/++8wm8AVjWZytQVuZe2xuvhcMeXf7uyw9vdRmm5uTG9/1+o42Fdrk62cVhs/3fG4Gvq3Lt06THpyerlW6MqPPDJ5a9xShMaHm9hKuJZjWc1q+FB/IKRcnFyqXqFyon9m6Qmtm9JnB0bCjhMSE0My/WZpAI9GSyPIzy/lu/3fmvOIzEWcYuWIkL7R+gRH1R+R4/WMhMhIYGWgGvuW8ymU5X9TL1YtxTcfx5LonAVh+ZjnPtHwmV0uTFTfWI78ZjRSAMQrxWvvXeGDlA+YNwX0h+9i3aV+G+3i6ePLmHW+mCXwBGpVtRGn30lyPu05YbBhHrx2lUZlGuf9BhBDCwWit04z8WqtYoiJtK7Rlx5Ud5rYHGjzAS21e4tfDv/L5ns/TXZUk3hLPjwd/ZPGpxdQqVYuIuAiu3ryaZopb5RKV6RLQBQ8XD2YcmgHA4bDDjF09lh/u+oFyXuXy88ctFHILtZjYfWU3Gy5sMJ+PbTSWxmUam88Xn1qcr2XLQ2NCWXFmRZrt8ZZ4vt//fb59Tkbik+LTXesst/Zc3WNTyOnF1i9mOxBrVKYRs/vNppavMTfYz8OP6b2nF0ngW9QalGlAl4Au6QYaLk4uDKk9hGVDlzGp3SQz3TneEs+HOz9k0OJBTNgwgan/TWX5meVExWd811GIrJwIt5rvm0HK8606VOpAGY8yAITEhPDvpbTF5LIrPDac/SH7WXZ6GZsvbnaYZSPSY5P27JN+2nOKuqXrMrf/XAbWHJjljYMBNQewbMgy+tfsn+7rTsqJjpU7ms+3XJQlj4QQt5ezEWfNOi6l3EulOx3Hepra480eZ2KbiTgpJ8Y2Hst3Pb+jSdkmNC3blIE1BzK+2XialG1ivj8kJoTtl7dz9NpRm8C3esnqfHPnN6y6exWT2k3i+VbP88Ydb6CSB1NPR5xm9KrRmdaDsVdyS7sYsGgLU3ZPMZ8PqDmA51s/T0xiDD3m9yA6wUg73Ru8l5blW+bLZ644s8IcZS7vVZ7qJauz6+ouLNrCjis7uBh10ab6cX6KiIvgwVUPcibiDG/e8SbD6g7L0/GSLEl8susT83m/Gv1oVDZnowuVSlRi/sD57AneQ+MyjR16LkRBc3VyZUT9EbSr2I6XN79sVtY+F3mOc5HnzPe5O7vTrUo3BtYcSKfKnXI1b1prTXhcOBFxEVTxqZKvc6+Lo+j4aC7fuIyPmzGfu7DmY1+9cZWfD/1M47KNGVRrUL4c03q+b3qVntPj4uTCgJoD+PXIr4BRQ6FzQOdsf2ZsYiwzj8xkztE5ZnXkFC+0eoExjcdk+1j2xDp1LqM5v9ZqlarFB50/4LlWzzH/xHw2BG4wCwCCMXo8ruk4mpdrnuWxOlfuzPIzywHYfHEz45qOkwwRIcRtI2U6GUDLci3TnfrROaAzCwYuAKC+X32b1+6odAd3VLrDZtu4ZuNYfmY5n/33mU3WIhj1G8Y1HcfI+iPTFMkaXnc43i7evPbPayTqRNpXbE9pd7tPfU5Dgt9i4K9zf5kFh9yc3Hi6xdOAkU7Wt0ZfFpww/iD+PPlnvgS/WmuWnF5iPn+y+ZMMrTOUJ9Y+wT9B/wCw5PQSnmz+ZJ4/Kz3zjs3jdMRpAD7d/Sk9q/XM9hIYl6ONC3vr4HTe8XkcDjsMGL+/Z1o+k6t2uTm70b5i+1ztezuq6VuT2f1m8/mez5l7dG6aZZnikuL469xf/HXuL1qXb83Xd36drXnrl6MvM/PITPaH7Odc5DlzBLlz5c580eMLm2WrRKr9Ift5at1ThMeFm9u8Xb25r959PNvy2QKba5ky1zZlremqPlWzFRRlJatKzxkZVHuQGfyuD1yfrSV2tNasDVzLlN1TMlwq7PsD3zOk9hBKeZTKdltyKjo+mtikWMp6ls23Y8YmxnLlxhXAGImt5F0p2/v6e/nzZPMn8/Rd0KFSB5yUExZt4WDoQR5d8yhv3vFmpunXQghRXGSW8mzt1qA3M07KiUG1BtGzak+zRkMp91L4uvlSwbtCppWh+9Xsh7erN2vOr2Fy+8kOeTNS0p7tSFR8VI7TuuKT4vlizxfm8wcaPkClEqkXJ9ZL7Px9/m9uJNzIczuPXTtmjqp4OHvQq1ovAO6uc7f5nsWnFpNkSUp3/7yIT4pn7rG55vPohGjmHJ2T6T4JlgRWnV3FqJWjuGvhXfT5s495Mrly4wpf7f3KfO8jTR8p9PmytzM3ZzcmtpnI5vs3M6ffHD7s/CHjmo6jXmnbAli7r+5m/Nrx3Ey4mcGRjNHD97a/R79F/fjt6G8cDD1okzq9JWgLn+76tMB+Fke2/fJ2Hv37UZvAF4z1Xacfms6HOz4ssLTdT3Z9Yga+YJw78kNuRn5T3tuwTEPASMn/69xfmb7/Wuw1nlj7BM9vfN4m8PVw9qBu6bpmtf3ohGh+PvRzTn6EbIlPimfd+XVM2DCBLr93ofv87sw7Ni/fjm/9M1X0rpir5TLyopRHKfrV6Gc+33F5B8OWDuO3I785dCq5EKL4sWgLgZGB+XZu0lrbjPy2qpBx8JsbXq5edKrciU6VO9G4bGOqlKySrXN81ypdea/Tew6bTSfBrx2ZsnsK49eN5+XNL3M9Nu06relZcWaFeXFSyr1UmqJWjcs2pnap2gDEJMZkeSGXHdZFrnpW62mOonYL6GamP1y5ccVcNzM/rTy7Mk064ayjszKcH7rizAr6LOzDxM0TzSquEXERPL7mcf4J+oePdn5k3hCo4VuDhxs/nO9tFlnzcfOhiX8TBtQcwFMtnuKPQX+wcNBCm6VP9gTv4an1T9lU1k6wJLD54mYmbppIvz/78fvx30m02I4guzm5mY/nHJvDopOLCv4HciDrA9czfu148/fq5eKFv6e/zQj5vOPz+G7/d/n+2avPrWbhyYU22/4+9zdxSXF5Ou6NhBvmedFFuVDDt0aO9rdOvbbOcrnV4bDD3L/8frZe2mpuK+Veitfbvc6/I/9l4aCFvN7+dfO1OUfnmKOo+WF/yH56/dGLCRsnsC5wHQmWBAC+3PtluhXocyMn830Lypt3vMnYRmPN7IOYxBg+3vUxH+z4QAJgIYRduHrjKsOXDaf/ov6MXjWa4JvBWe+UhaDoIPM43q7eaQYGRO5I8Gsndl7eaV4Erjy7ksGLB7Pq7Kosv9itR0nSW8dVKcWQ2kPM53m98E9ISrApdGV9kejq7GpTuCRlke38orVm5pGZ5vOUSfdR8VE2o8EpNl7YyCtbXkn3BBSbFMtT656yKXL1Rvs3cHN2S/NeUTTqlq7LpHaTeLH1i+a2XVd2MXzZcMasHsOY1WPouaAnT657klXnVtmsbdfcvzlf9fiKtfesZdcDu8zsBDCqlO8L3pfrdq06u4oe83vQZ2Ef3tv+HpsubOJGwg0SLYkkWhILJOOhICRZkvjl0C88v/F5M2gq71WeuQPmsv7e9ex+YDd9q/c13z9t/7QssyxyIig6iHe2vZNme1RCFJsubMrTsU+FnzIfV/etnuO/6341+pnFmg6EHODU9VM2r2utWXJqCaNXjubyjcuAcT4aWX8ky4cu577695n796za06xQHG+Jz9ebCF/u+TLdYiNR8VGsPLMyXz4jMDJ1vm9RpRp7uHjwfOvnmd1vtnkzF4ybMp/s+kQCYCFEkboQdYEHVz9oTrfZF7KP+5bfx97gvXk6rnXKc/NyzWX1gXwiwa+dqFu6LgNrDjSfX4+7zsTNE3lm/TNpLrxSXIi8YObqOyvnDAvFDKw1EBdl/MHsC9nHmYgzuW7nlqAtZtW5Ct4VaFuhrc3rQ+ukplmvC1yXrxWZt1/ebqYyerp42gRFM4/MtEnpPhN+hle2pK5F6efhx/hm45nVd5aZ1my9LNTdde6mdYXW+dZWkX8ebPQgz7dKXW/1fOR5/rv6H/9d/S/NhX/Tsk35rud3zOw7k25VulHeuzxOyon3Or5npr4mWBJ4buNzaYo8ZCXRksinuz5l4uaJhMSEEBQdxO/Hf+ep9U/Rfk57WsxqQYtZLWg+q7mRbbBpIr8d+c0s6GVPTl4/yQMrH2DKf1PMv4OqPlWZ2XemueSMk3Li/U7v07FSarXdD3d+yOStk3P8u7tVkiWJVza/Yq4jWLlEZR5o8ID5+rIzy/J0/CNhR8zHOZnvm6K0R2m6BnQ1n9+/4n7e2vYWu67s4tv93zJw8UBe3/q6ecPFx9WHr+/8mlfbvZpmfrBSigmtJpjPF51alKdzcIoLURfYeWUnYPxbPdrkUUY3HG2+Pu/4vHwJCnNa7KogNS7bmPkD5tvclPnt6G98uvtThw2AL0ReIORmSFE3QwiRS6eun+LBVQ+mqfcQGhPKQ6sf4pdDvxAdH53j41q0xWawqXV5uUbNL3ILwU6U8ijFB50/oE+NPrzz7ztcvXkVgI0XN7Lp4ib61OjD480et1kLcemZ1PTjTpU7ZVjkxM/Dj25VupkLZP9w4Afe7fhurgr/LDmVmgI4sObANPn+dUvXpVGZRhwOO0yCxRglHtlgZI4/Jz3Wo75Dag9hZIORzD02l4vRF4mIi2DmkZk83vRxIuMjeWbDM2YwXMm7EvMGzDMX4/6lzy88tuYxc56hn4efTXAl7M/YxmOxaAuf7/k8zWvlPMvRv2Z/BtQakOHcTi9XL77o/gUjVowgPC6c0JhQ3v33XT7v/nmWxRq01lyMusjb/75ts45eZoKigwiKDmLVuVUANCnbhFENRnFXtbsKZc6k1prohGguRF0gMDKQ85HnCYkJISIugvC4cHZf3W2THt7ArwHTek5Lcw5xdXZlarepPLrmUXPawOJTi1lzfg2PNX2M/2vwf7n6eeYdn8e+kH2AcePu4y4fU8q9FL8d/Q2Afy7+w/XY6+bfbE7tubrHfNzUv2mujjG87nAzMyQuKY6FJxemSdEGqOVbiy96fEG1ktUyPFb7iu1pX7E92y9vx6It3LP0Hkq7l8bXw9csMuLrbhQaub/e/dkqimV9Lu5UuRPPtHyGiLgIfj/+O3FJcRy7doz9IfvzXDzsYtRF87E9FJlydXblg84fkKST+Pv834Dx3eCsnHmu1XMOVXxl5uGZfLr7U9yc3Zjdbzb1/CSl0d7EJMbw44EfCYwK5PGmj1O7dO2sdxK3jYtRFxn711izXoa7szuPN3ucmYdncj3uOok6kSn/TeHrfV/TvUp3+tfsT8vyLSnpVjLLY08/NJ1/L6cut9epcqeC+jFuO8pR75bmxvjx4zXAtGnTiropmYqOj+bzPZ/z+/HfbbY7KScmtpnIqAajsGgL/f7sZ95pmtptqk1q5602X9zMk+tSK2429W/Kx50/ztFyRKExofT6o5d50bxsyDKq+1ZP877fj/3OezveA4yKvgsGLshzOvHp8NMMWTIEMNILlw9dTtWSVVl0chFvbHvDfJ+vuy8lXEuYvxdPF09m9Z2V5qLiWuw1Jm2ZxKnwU7zT8R06VOqQp/aJwnEu4hwhMamjJF6uXtQvXT/bRRe2BW1j3Npx5vP/df0ffar3SfO+qzeusvrcanZf3c2BkANpRpi7VenGyPoj+ffSv2wJ2sK5iHNojHOpRVvMx7cq51mOh5s8zL317s239KXQmFC2Bm1lS9AWTl0/RUR8BBFxEWYqc2ZcnVx5vNnjjG08NtObYRFxEUzeOtlmLXGAdhXb8c2d3+Du7J7t9l65cYXBiwdzM9EoXja+2XieaP4EAKNWjjKD7EntJtnM+c4urTU9F/QkOMaY7vD7gN/NAlY59fe5v/n50M82I8kpvF29GVhzIBNaTchWFfJDoYcYsSLrn6epf1N+6fNLpv8eSZYk+vzZx5w//Fm3z+hZrScAb257kz9P/gkY6dsfd/k4y8/MTL8/+5nzfhcNWmQ3F/8JlgQmbppo3tQFeKTJIzzT4pk8BcD7Q/bz44EfaVimIU80e6LAgulbv7uG1h7KOx3TTgMQ2RMRF8G12GtExBnnv4j4CMJjw4mIjyDJkkSATwDVSlajconKhMaEcj7yPBejLlKpRCX61uib7jXKxaiLTNgwgePXjwPGfP6fe/+cowJ6onh7a9tb5k1RLxcvvr7za9pUaMOl6EtM2DCBo9eOprtfDd8aNC3blO5Vu9MtoFuaa5idl3fy6JpHsWgLAA82fJAX27yY3qFE5tI9gUvwa8cOhx3m233fsuli6vw3heL7Xt/j4uTCQ389BEBJt5JsuHdDpgGmRVt4bsNzrL+w3txWwrUEoxuOpmapmlQrWY3qJavj4eKR4TE+3PEhc44Zc/6a+Tfjt36/pfu+yPhIei7oaRZcua/efTZFX3Ljve3vmTcDelTpwRc9jArXCZYEBi4amOHyIp92/ZTe1Xvn6bNF8WL9ZeXn4ceiwYvw8/AjJjGGNefXsOz0MnZc3pFhADu++XjGNR2X4dI/CUkJnLh+gv0h+9kTvIf1gevTBKK1S9Xm5bYvZ3tprARLAievn+RgyEFOhp801y4OjQm1md+aE838m/F2h7epVapWtvfZGrSVT3Z9YpO227NqTz7t+mm2b0A8u/5Z8zxUw7cGfwz8wzx3zTs2j/d3vA8YKeyz+8/OdttSXIy6SN8/jbRYb1dvtt6/NU8VKbXW7AvZx6wjszh27Rg1fGswsOZAulXplun5Mj3f7vuWGYdnZFmM6tEmj2a65NrWoK08vvZxwOjDa+9Za47AHw07yr3L7wWMdYvX3LMm10sfJVgSaPNbGzM1fteoXTn+mQtSQlICL2x6weamzLim43iqxVO5Ot7qs6t57Z/XzHT2z7t/zp1V78yXtlpbH7ie5zY+Z17YgvF9vPG+jTm6kXS7i0+KZ/W51cw+OjvdG1TZVd+vPh93+dgms27bpW1M3DwxzdQtPw8/fr7rZ7u5CSSKTkRcBD0X9DTXMP++5/d0qJw6kBKbGMv84/NZenqpeQMlPZVLVGZE/RH0rt4bN2c3IuIiGLN6jHnTvWW5lvzU+ydZpjF3JPh1tOA3xcGQg7y34z3z5O7n4UejMo3YEmQsi3R/vft5rf1rWR7Hoi3MODSDr/d+nWZNVTDuWn3V4yvaVmyb5rULURcYtHiQOer7zZ3f0CWgS4afNfvobD7a+ZH5/MPOHzKg5oAs25ieuKQ4uv/e3ZwfOL33dNpUaGO+fjTsKN/s+4Z9IftsvqiyuoAUt6eo+CiGLhlqTi24s+qdVC9ZnT9O/pHhHPUSriVoUrYJYxqNsflyy47QmFAWnFjA/OPz08yVrVe6HmU9y1LSvSTlPMvRrmI72lRog4eLB1HxUaw9v5aVZ1eyL3if+QWbXe7O7lQqUYlqPtWoWrIqlUpUwtfdSLP19/Snbum6uRrVSrAk8O2+b/nx4I/mtmF1hvHmHW+ilCI+Kd7m96iUorR7aZydnFkXaCzJk+KXPr/YrFt4PfY6Peb3MM9Pn3X7jCo+VSjjWSbbAdzS00t57R/jfNixUke+65X/VarzQmtNTGKMmYIeEZ+cin5lt3mDT6H48a4faVexXbrHeHHTi2bl/tENR/NSm5dsXn9g5QPsD9kPwNMtnuaxpo/lqq0XIi/Qb5GxzFA5r3KsG74uiz0KX0KSMYff+ibxE82eyNGordaa6Yemp5lW0bJcS37t+2t+NpddV3bx+JrHbQr0pcgqg0sY1zGHQw+z4cIG/jz5Z5rVH3LL08WTZ1o8Q0xiDFuCtrAveJ95A9TVyRU3ZzdzKpWfhx8zes+gZqmamR1S2IFESyKf//c5h8MO82zLZ/NlDfkUMw/P5H+7/wcYU/7+GPhHhuecE9dPsPzMcrZfMmrXpHcNnh4/Dz8WDFxAOa9y+dbu24wEv44a/AKE3Axh+LLh6Z7o5/afS+OyjbN9rIMhB3l5y8s2S1ikqORdiUWDF+Hl6mWz/dUtr7L8zHLAuCD4pc8vmV5YaK15afNL5gWap4snc/vPzdEoU4rVZ1fz0mbj4i6gRAAr716Z7mdrrQmMCuRQ6CF83HzoXLmzQ83/EoVny8UtjF83PsPXFYq2FdrSu0ZvWpZrSQ3fGhmO9GZXXFIcvx35jR8O/GCm/KbH3dmdhmUaciTsSLaW/HFWzjQv15zOlTvTrmI7ynqWpZR7qQIdodNa87/d/2PWkVnmtoZlGhIeG87lG5fTjJq7OrlSxacKYbFhZmA8rM4w3urwVppjP73+aTZe2Jhme48qPZjSbUqW6eLWI/t5CfwKm0VbGLdmHNsvbwfA39OfhYMWppn3HB4bTo8FPcxsgj8H/Umd0rZFvZafWc6rW14FjAreq4atytWogfUIc+vyrZnRZ0aOj1EY4pPimbBhgnlDGIyMo1favpJhf7mRcIMDIQc4EHKAXVd3Zbg0X06/XzNzKfoS9y6/1/wbqOJThfYV27PgxALAyKL4rPtn+fJZRe1i1EX+CfqH85HnCYwK5OqNq3So1IGnWz6do76YZEniVPgpDoYeZM/VPWy9tDXdCueuTq6U9ypvzKH38MXXzbjRV8q9FBrj2iAwMpBL0Zfw8/Sjmk81SnuUZsmpJeneiEhRzrMcU7tPRaF4bM1jZgDs7+nPnP5zqOBdIee/HDsTFhPG6nOrWXt+LSXcSvBcq+dsRsEdldaayVsnm8vVlXAtwcy+M9OcL3PDoi0MXDTQLAj4xh1vMLzu8GztG5MYw9Gwo2y6uImFJxdmeNPdSTnxY68f0x2QEtkmwa8jB79g3DF+5O9HbFKlavnWYtHgRTkO8m4m3OSvc39x4voJAqMC2X1lt3lBPqbRGF5o/YL53uPXjjN82XDzgvbXPr/SsnzLLD/jRsIN7l9+P+cizwFGiuPc/nOzNT/O2hNrn+CfoH8AI+X0iWZP5Gh/IdLz2j+v2axZDUb60T1172FAzQEFdlETcjOEL/Z8ken6semp5F2JJv5NaFymMf5e/sZFnrsv1UpWS7PEWWGwaAuTt05O8zvMDj8PP5YOWZqmMjLAhsANPLMh/YyN/2v4f0xsMzHTYw9cNNA858zoPcOhqriH3AzhnmX3mBf37Su259Oun9r8nqyzapqUbcKc/mmXn4pPiqfXH73M4+R2/vTcY3P5YMcHgP3PSY1LiuPZ9c/arLncJaAL/+vyvzQ3c9cFrmPyP5PNbCJrrcq3wtfN10zN71ujL590+STP7YtPiufBVQ9yKOwQAGU9yzKr7yziLfEMXjwYMAK4jfdtzFYxHHt2Meoi9yy7x2YFhhQdKnVgStcplHArkea10JhQZh+dzbmIc2ZGRFBUUKY3C8t5lWNE/REMqzMsVwXyjl87zsTNE9NUYFcoOgd05u0Ob5tZJ/uC9zFuzTizPXVK12Fmn5np/iyO4GjYUb7a+xXbLm2zWf3CzcmNJ5o/wZhGYxx6aZ0pu6fwy+FfbLZV9K7InP5zcj0VJIX1jUEfVx/WDl+b5jyTHTGJMaw4s4KFJxbaTN/zcPHgsaaPcU/de/LUTiHBr8MHvwA/H/zZJjXruVbP8VDjh/J83CWnlvD6VmNerrNyZt6AedT3qw/AU+ueMlPKugZ05es7v872cU9dP8XIlSPNOW49qvTgs+6fZXsULfhmML3+6GUG/KuHrTaXKhIiLyLiInjk70c4du0YbSq0YVSDUekWnigooTGhXIq+ZM7fPXbtGFuCtphVyMGYizag5gB6V+9tlyMMCZYEnt/4vM1IrUJR2qO0+TeeYElIc2c7o0JjYNytn3tsLtsvbyciLoKw2DDOR543X3+v43sMrj043X3DYsLoNr8bYAQS/4781+HmUN5anLCsZ1leb/c6d1S6g6Wnl/L9ge/N9PnJ7Sdzb7170z3OjEMzmPrfVMC42bBi6IocX6R/vPNjswL3sy2f5ZEmj+TmRyo0cUlxTP5nslllHYxK5h91/shMUV12ehmTt062udhPMajWIN68401OhZ/ivuX3Acb34ephq/P89/f+9veZd3weAC7KhRl9ZpgpmPcuu9csjPNOh3dslgx0RBM3TbT5N7hVndJ1mHbnNJvf6ZaLW3h96+vpjureys/Dj06VO9GtSje6VemW57mQMYkxfLnnS7YEbaFhmYZ0CehCx0od0w2md17eybi148wpYB0qdeDrO792uPmYx68d58HVD6Z7gyJFA78GPNfqOdpXbO9wWXTTD03ns//Sz6JoVKYR03tPz1WwmuLpdU+z8eJGAB5o8AAvt30518cSBUqC3+IQ/Fq0hRc2vsDawLX4efixcNDCPN/BAuOC85G/HzHXjWxcpjEfdfmIJaeWmHP7FIoFAxfkeDkG6xQ8MOZjjW+eccqpNesLuDYV2jC99/QcfbYQmUmwJJCQlJCnL8H8diHqAsevHadayWr5kp5V0BItiWy6uAknnKhWshoBPgFpiu9Fx0dzPuo8F6IuUMm7Uo6WH7q1WJ+bkxsz+sxI9xhrz6/luY3PAdCiXAtm9p2Z5j2O4Ms9X9rMqQbwcPawmfft4ezB+nvXZzjqH5cUx6BFg7h04xKQuxoI1hd4jlI80KItfLnnS34+9LO5TaHoW6MvNX1r8vW+1Ju35bzK0b1Kd5qUbULzcs1tlqt66K+H2HVlFwBjG43l+da5Xw5vxZkVNuvOv9zmZR5omLqu9a+Hf+XT3Z8C0K5CO37q/VOuP6uoHQw5yMiVqcsbPtrkUer51eP4teM2fTolgG3m34yzEWfNmyzpKedZjqb+TWni34Q25dvQqGyjPE9DyQvrugJgTOF44443irRNORF8M5iRK0aadS/AmM7Wq1ovlp1ZlqZ4WO1StRnZYCSdK3fG190XD2cPuw6Grb8HwBh0ubvO3Ty74Vnzpldz/+Y80PABulXpluMbpEHRQfRd2NfMhlw+dHmmS92JIiXBb3EIfsH4ct9+eTs1StagYomK+XbccxHnGLZ0WIbzXwbUHMCHnT/M1bH/t+t/Nuv0Wi/NkRGtNUOXDOV0xGkg8xEfIUTxdSPhBg+sfMCsbO3v6c/PvX+mhm8Nm/dZj1Q+3PhhJrSaUNhNzTfrAtfx3vb30hRJA2Pu2sQ2E7McIbS+8eju7M7yocuzPYKZkJRAnz/7EHzTWDJq/oD5NCjTIIc/RdFZcGIB729/P90RXjBGH3/o9UOGN483XtjI0+ufBoy0xjXD1+R4yg4Y36v3Lr/XzH7qVa0XU7pOsQkegm8G03NBTzQahWLNPWso710+x5+VEYu2EBUfRURcBL7uvulON8gPWmvGrB7DnmBjne1e1XoxtdtU8/XFpxbz9ra3My32U9azLM+0eIaKJSri6+ZLWc+y+Hv5F0h78+Kbfd/w3f7UYnq1S9XmyeZP0qNqD7sOgm8m3GTM6jFmpoG3qzc/3/Uzjco2AoybmTOPzOSbvd9keC3o5uRGdd/q5s9rTyzawuDFg82pL20qtOHbnt/i7uxuswxnCh9XH/rU6MP45uOzPZA0dfdUZhw26h90qNSB73t9n68/g8hX6Qa/9vsXKjLkpJzoUKlDvga+ANV9q/No00fTfa1ayWo82/LZXB/7uVbPcUfFO8znk/6ZxInrJzLd50jYETPw9XTxlCqYQtymvF29+bL7l+ZcyJCYEEauGMmGQNt1h1MuuoFs1SWwZ3dWvZPFgxcztHZqgFvVpyqvtH2FtcPXZis1tl+NfuYax3FJcXy196tsf/7CkwvNwNfX3dfhKtsOrzucOf3n0Lly5zSvNS3blBm9Z2R6sdsloIs5mhOVEMUnuz4hPinjwkjpSbQkMumfSWbgW71kdd7p8E6aUbNyXuVoW8EoaqPRfLHnC3Zd2cXNhIznumYlyZLEzMMz6f1Hb1rMakGneZ3ov6g/XX/vyqYLm7I+QC5suLDB/Bt0US5prhmG1B7Ct72+xc/DL939uwR0YeGghQytM5T2FdvToEwDuwx8wVif3HoFi1Php3hu43Pct/w+jl/LeFmbnLgQdYH3tr/HwhML8+V4UfFRvLT5JTPwdVbOTO061Qx8wVge7aHGD7F4yGJG1B+Bp4tnmuPEW+I5cf0Ez254lpc2vURYTPYrbidYEgiLCeNM+BkuRF0gvwfgNl7YaAa+JVxL8Fm3z8yR3fvq35emZkxUQhQLTixg8OLBLDm1JMv27Lqyy6bQ4/317s/X9ovCISO/wkZ8UjyjV43mcNhhXJQLHSt3ZECtAXQLyPmalreKiItgxIoRZpXpqj5VmTdgXoZpe9ZzpAbVGsT7nd7P0+cLIRzbjss7eHLdkzZVsJ9o9gSPN3ucmMQYOsztgEVbUCj+GfGPwxcOSnH82nFuJNygebnmOR5V2nVll7kmvELx010/ZVk99GbCTfr92c9cXeCFVi8wpvGYXLXdHuwP2c+0fdPYfnk7XQO68mHnD7M1invrSFF9v/p80uWTNBkHGfl2/7dM22dcb7g4uTCv/7wMpw0tOrmIN7a9YbPNSTlRu1Rtmvo3pWnZprQq34qqJatm+bmnrp/ijW1vcDD0YLqvl/cqz9IhS/N1ukeCJYG7l9xtBh6jGozilbavpPveuKQ4joQd4UDIAfaH7OdS9CUG1x7M/fXut+t02lslJCXw3YHvmHVkls3a3eU8y7Fs6LI8/X6PXzvOY2seM+dAf93ja7pW6ZqrYyVZklh8ajFf7v3SZk71m3e8mWVBpaj4KBadXMTKsysJvhlMeFx4mnXrS7mXonf13lQvWZ2qJauSkJTA+ajzBEYGcvnGZbOuRURcBNEJ0Tb7+rr70qRsE5r6N6VfjX55Th8evWo0e4P3AjC28Vieb5V2ukJgZCDLzyxn+ZnlaVY96VipI8PqDqOqT1WqlqxqE/xfir7E/cvv53rcdcCYOzy73+xCqxMickXSniX4zZ6YxBgOhR6iVqlaGd6hza1T108xauUos1piz6o9mdptqs0XXkRcBN/t/465x+aaKWs/3/WzlHsXQnA07CgTNkww57KCUUm+bYW25jq59UrX449BfxRVE+2OddFCF+XCK21f4d5692YYaPx44Ee+3PslYIxKrhi6okCXziosCUkJuDpnvzBRgiWBFze+aM43ByML6YEGD9C1Slcal2mc4YXv4dDDjFo5yvwOm9ByAg83eTjDz4qOj2bQ4kGExIRk2qZ+NfrxXKvnqOBdAa01u6/uZvGpxebom0Vb2HV1l1mQKUUJ1xLEJ8Wbqaw5qb2RHdaVwUu4lmDl3StzVX3ZEV2LvcYvh39h7tG55rz83MyxT7EveB/j140nKj61Gnmd0nX4Y+AfOb75dSTsCG9te8sc7U3xSJNHcpXNp7Xmetx1pu6emuMVC7LirJwZUHMA45qNo4pPlRzvvzd4L6NXjQaMm01/Dfsr0/VxtdZsvbSV97a/Z1Np2Vqd0nXoX6M/Par2YOLmiRy7dgww5qz/PuB3uyxEKWxI8CvBr32wXrcX4MXWL/JgoweJio9i2ellfLf/O/POGhjLOf05+E+7nkcjhCg812Ov89LmlzJcm3VE/RFMajepkFtlvwIjA3lg5QM259UhtYcwuuFoc8mslCJl4bHh9P2zrzlC89YdbzGs7rAiabc90Foz59gcpu6emmYOZGn30jQu25jSHqWNubTJa8v6uvsybf80s3J7y3Itmd57epYjRNdjr7M+cD0HQw+yP2Q/p8NPp1kzG4wAfFidYey+utu8GE+Pi5ML45qOY2zjsbg7u/PnyT95c9ubgDEHfNmQZfkyfSoiLoIBiwYQHhcO5N8qFI5m8anFTN46GTDmxS4dujTHq1Nsv7ydZ9Y/YzOSnOLDzh/apFpnxqItzDoyi8/3fG5zI6SCdwVeaPUCvav3zvMo+9agrbz979tcvnE52/solDnvPGVE+FbOypn76t3Hi21ezFEV7WfWP8OGC8ZUmJwszXYz4SZf7f2K2Udnp/v3disXJxd+vutnh59ac5uQ4FeCX/vx4Y4PmXPMWJ/SWTnTJaALW4O2prm4aF2+Ne90fCdXdwGFEMVXoiWR7w98z6wjs9Is15HZUkq3q0vRl5iwYUKaEaAU5bzK0cy/GTGJMea66tVLVmfR4EUOvdZnfsloPdiseLp4snDQwlx9h0XHR3M47DAHQw+y8/JO/r38b7b3bVq2KW93eJvapWub25IsSYxYMcLsA32r9+WTrnlfw9i60FzlEpVZMmSJwy0xlh8s2sLIFSM5HHYYSFvwKytXb1xl0OJBZmacn4cf7Su2Z+XZlYDxu102ZFmW2QtXb1zlzW1v2qx57eHswUONH2JM4zHpzuPNrZjEGHZc3sG5iHOcizzHxaiLuDi5ULVkVaP6f4kASnuUNm8K+bj5mAMZWmsCowI5EHKAZaeXpenfTzV/inHNxmWrHWcizpjrZQMsGbwkx3UKDoUeYsWZFZyLPEdgZCBB0UHpFszLTrq4sBsS/Erwaz8SkhIYs3oMB0IPpPt6Je9KvND6BXpV6+VQc4CEEIUrOj6aJaeXMPvobC5EXcDf058lQ5ZkWEvgdhabGMu7299l6eml2Xr/lK5TuKv6XQXcKscRnxTPxgsb2RK0hS0Xt5hzojOTnxfKu67s4qOdH9kUi/Rw9mBgrYF0q9LNDCp83XxpWKZhuiPN/139jzGrx5jPZ/adSYtyLXLdpjPhZ7h76d1mkDC129TbujjlvuB9/N+q/zOfT+89nTYV2mRr38lbJ7P41GLAmJf9w10/4O/pT78/+5mj6pPaTWJE/RGA0R/D48IJjwvneux19lzdw5agLRwKPWQzgtmoTCM+6fJJtuaLF6X/rv7H13u/ZvfV3YDRtxcPWZyt0fM3t73Jnyf/BKBbQDe+ujP7xf0yciPhBusC17H89HJ2XNmBRVv4v4b/x8Q2E/N8bFFoJPiV4Ne+XI6+zL3L7zVP6mAUFBlcazD31L2nWMwxE0IUDou2cPL6SSqVqCSBbya01iw5vYQlp5ZwLfYa4XHhRMZFpll+pmGZhszrP09uPmYgpb8FRQeZxXzC48KJiE8u7BMfTbuK7Xio8UP5+jtMtCSy6NQiNl3YRMvyLRlWZ1iOly56cdOL/HXuL8CY0/hb399yXZzp8bWPszXIGGFsXb4103tPv+37zMTNE1l1dhVgjNb2qNqD6iWrU9+vPk3KNkn393P82nGGLxtuBq0/3vUj7Su2B2zXgfbz8KNLQBcOhBzgbMTZLNN0xzYey9PNn87RXPeilGhJZMSKEWY6f48qPfiixxeZ7hMeG06PBT3MQly/9vk131OSQ2NCiYiLoFapWvl6XFHgJPiV4Nf+HA07yoxDM6hYoiIDag6gTuk6Rd0kIYS4rSRaEjkdfpoDoQc4EHKAREsiT7d4mkolKhV100QBuBR9iUGLB5lV07sFdOPz7p9nq2qtRVsIiwkjPC6cvcF7eXf7u4BRmfr3Ab9T369+gbbdEVy5cYWBiwaaxa+spdQ4udXjax4305Q7V+7MtJ6p16lxSXH0/7M/V29ezdbnOytnmpdrzuPNHjcDaEdy6+j5tDun0Tkg7ZJlKWYfnc1HOz8CjFHuuf3n3vY3YIRJgl8JfoUQQghxu1t4YiFv/fuW+Xxk/ZG82u7VTPc5HX6alza/xMnrJ9O8dk/de3jzjjfzu5kOy3q01lpJt5L8fc/fNkttbQvaxri1xtxWJ+XEwoELbeZqAzbFylI4KSdKuxvF1kq5lyLAJ4DOlTtzR6U7cpwNYG+sU8Cr+FRh0eBFGc4jH75suDlSPLn9ZO6td29hNVPYv3SDX6liIYQQQghxGxlWdxiBUYFMPzQdgDnH5lDBuwKjG45OdwQ4NCaU8WvH2ywxlqKEawmeav5UgbfZkTzY6EE6B3TmxPUTBEYGMv/4fK7evEpkfCQLji8w181OsiQx5b8p5n5Daw9NE/imbI+Kj+LYtWPUK12Ppv5NaVCmQb4Wr7InE1pOYF3gOqLio7gQdYEPdnzAa+1eM6vSpzgadtQMfN2d3elbo29RNFc4GAl+hRBCCCFuM8+2fJag6CBz/u/U/6by86Gf6VipI10CutCtSje8Xb2JSYzh6XVPm4Gvq5MrAT4B+Lr5UtazLKMajKKMZ5mi/FHsUk3fmtT0NSoOl/EoY460/3rkV0Y0GIG7sztzjs0xC5h5unjyZPMn0z2WUirddOniqoxnGZ5u8bS5dvSfJ//kaNhRPu7yMTV8a5jvW3Rqkfm4V7VeUu9BZIsEv0IIIYQQtxkn5cR7Hd/jyo0r7A/ZDxhr9q48u5KVZ1fi4exB96rdiYyP5FDYIXOfz7t/TpeALkXZdIczsNZApu2fRvDNYEJjQllyagnVS1Znyu7UUd8xjcbg7+VfhK20L/fWvZddV3ax5vwaAI5eO8p9y+/j1bavMrTOUOKS4lhxZoX5/qG1hxZVU4WDcSrqBuSFUspPKbVIKXVDKXVeKTWyqNskhBBCCOEIPFw8+ObObxhRfwT+nraBV2xSLKvOrjKrOQO82vZVCXxzwc3ZjQcbpo7c/njwR17Y9IK5RFTjMo15uMnDRdU8u+Ts5MyUrlN4pe0ruDoZ1apjEmN4Y9sbvPvvu/x17i8i4yMBo6p26wqti7K5woE4dMErpdRcjAD+YaA5sALooLU+nN77peCVEEIIIURaWmuOXTvG5oubWX1uNafCT9m8PrrhaF5q81IRtc7x3Uy4Se+FvW2WdwQo61mWef3nUd67fNE0zAEcv3aclza/xNmIs+Y2Z+Vs3jx4qvlTjGs2rqiaJ+xXugWvHHbkVynlDQwDJmuto7XW/wBLgf/LfE8hhBBCCGFNKUWDMg0Y12wciwYv4o+BfzCm0RgalmnImEZjeL7V80XdRIfm5erFqAajbLa5OrnyWbfPJPDNQj2/eszrP4++1VMLWqUEvgrF4NqDi6ppwgE58pzfukCS1vqE1bb9QNdb36iUegx47IknniistgkhhBBCOKx6fvWo51evqJtRrIyoP4JfDv/CjYQbgLE0T/NyzYu2UQ7Cy9WLj7t8TKOyjZj631Qs2gJAh0odqOBdoYhbJxyJw478AiWAiFu2RQBpSr1prX/QWstkACGEEEIIUSR83X35uPPHtCzX0izcJLIvper1dz2/o4J3BXzcfHiqhSyzJXLGYef8KqVaAFu11l5W214AummtB6a3T8qcXyGEEEIIIYQQxde0adPSzPt15JHfE4CLUqqO1bZmQLrFroQQQgghhBBC3L4cduQXQCk1D9DAIxjVnleSSbVnkT+UUrsljVzYO+mnwhFIPxWOQPqpsHfSR0V2OfLIL8B4wBMIBuYCT0jgK4QQQgghhBDiVo5c7Rmt9TVgSFG3QwghhBBCCCGEfXP0kV9RNH4o6gYIkQ3ST4UjkH4qHIH0U2HvpI+KbHHoOb9CCCGEEEIIIUR2yMivEEIIIYQQQohiT4JfIYQQQgghhBDFngS/QgghhBBCCCGKPQl+hRBCCCGEEEIUexL8CiGEEEIIIYQo9iT4FSalVHWlVFullEdRt0WIjEg/FY5A+qmwd9JHhSOQfirymwS/AmX4FtgPfAEsV0rdWcTNEsKG9FPhCKSfCnsnfVQ4AumnoqBI8CsA7gAaAjWAYcBWYL5SqmaRtkoIW9JPhSOQfirsnfRR4Qikn4oCIcHvbeqW9JFmgL/W+hpwRWv9JsadtteVUj5F0kAh0mqO9FNhh+R8KhxMc6SPCjsk51JRGCT4vc0opaoqpZYBr1htvgIcU0rV01pbkrc9AwwAmhR2G4VQSlVRSj2slGpntfkScFz6qbAXcj4V9k7OpcIRyLlUFCYJfm8jSqkpwCEgUGv9ltVLl4ESQJuUDVrrQ8BGYELyvqqw2ilub0qpZ4FjQH9gqVJqqlKqAnASKIn0U2EH5Hwq7J2cS4UjkHOpKGwS/N4mlFJzgUeBO7TWT1q/prXeDpwF7lJKtbR6aSngr5Ty1lrrwmutuF0ppVyAHsBorfXdwN1AfeAl4AhGylMf6aeiKCml5iHnU2HHlFLOyLlU2Dml1BzkXCoKmQS/xZhSqqZSqmry01nAeeCaUqqLUup3pdS7Sqlxya//DygNjFFKBSRvawrs0FrfKNyWi9uJUqqlUqpb8tM6GHd5dwJorbdi9N06wD3AJ0AppJ+KQpbcT3smP/0NOZ8KO6OUcrV6Whc5lwo7dEs/nY2cS0Uhk+C3GFJKlUmeO7EEaKKUUlrrlcBx4DAwM/mxM/C+UuoJrfUpYCpQDVitlPobeAhYXyQ/hCj2lFL+Sqn5wG7gSaWUs9b6KBCBcXGWYhlwFOgLhGNctEk/FYXiln46LrmfLgdOIOdTYQeS++hPwPdKqceUUu7J59Io5Fwq7EQG/XQFcAo5l4pCpCRjoHhRSnlhBL3BwGNa6xvJF2tJSqlqwGTgZa11WPL7HwHGAP211hHJ+3cFagI/aq3ji+QHEcWaUuoD4CngV0ABnlrrh5PTnp8C7gV6a62jkt8/CHgOGKW1viT9VBSGjPpp8mtVgTeQ86koQkqp3sB0jO/9S8BgYK3W+lWl1PMYwa+cS0WRyqCfbtRav6SUqgG8hpxLRSGR4LeYSU4ffV9r3TH5eWvgNBCjtY5VSvlrrUOUUl5a65vJF3BHgY5a631F1W5x+1BKvQV0Ap7VWh9WSnXFmMNTQWsdkzy3523gsNb6leR9SmAUv+iutd5dRE0Xt5Gs+mnye0prra/L+VQUFaXUx4Cv1vpxpZQTxvzJXsBwoAXwLnBQzqWiKKXTTx/B6KcPJp87/bTW1+RcKgqDpD07uFvmTgAkJm9voJRahzGfYgHwE4DWOiT5/zeT398JWIWRaiJEgbiln07VWvdMDiicgVhgH5BS0OIQMAN4XCmVkrLXEvgXOFNITRa3oWz20xYpb9BaX0/+v5xPRaGw7qNKKW+MebsqufiPBaiNkZLvpLXegzHa9rhSanjybnIuFQUuG/20DsZ50gKQvJavnEtFoXAp6gaI3Em+e/sZUEIptQv4JfnkUR7jru4EYDPwHtAOWKaUelpr/ZVSqjxGMYxxGHfeXkgZyRAiP2XST1FKuWqtE5RSQUANjOCC5HSmP5VS1YHXlFIvAQ2B11L2FSI/5bCfxiVvd9JaW5RSZTD6p5xPRYFJp4/+qrUOU0ptBu7CmEfpjTGfdyVwVCn1ntZ6plKqFjBJKfUici4VBSgX/XSfUupjrfUMuTYVhUXSnh1Q8tzdxRgFAv4FRgNJwJ2AK7AGaA300lqvT95nDPC61rp28v5fAZHAeK11ZGH/DKL4y6CfJgCDrAKLlADiH4z5P68nF2jTya/7Aa2Af7XW0UXxc4jiLbf91Gr/GsAXyPlUFJAM+qgF4zs+WinlCXyAEdj2Te6rjwBTtNa+yccoQ/Kor5xLRUHIQz/9VGtdKjnV+WvkXCoKmIz8Oqa2QJjW+gEApdTPQAjwgdb6OaXU1xgXY/VIrYgXCRxJLhpwEfg/rXVE4Tdd3EYy6qevKqXe11qHJ3/5uQG7AHellIvWOiV1XyUHH2uK6gcQt4U89VOt9VmllJxPRUHKqI++mTyXMgIIAJYnp5SCMX3kuDKWhwlKLiQk51JRkHLbT08qpSoCF5BrU1EIZM6vA1BKVVZKtbpls5NSqiyA1joW2AMMV0q11FrPAlYA9ymlnk0emXge2Ke1vqm1TpKTi8hvOein92LcmEkJcOMxUklbaa0Tk4thkDL6K0R+yu9+mryPnE9FvslBH70PqKG1TgDKApWVUnWT00enYizPdUnOpaIg5GM/3QVc1QY5l4oCJ8GvHVOGtzGqNb+dfKIA4wIsBBiV/L6SGGkmCcCI5Pe8CswHhgDrgK1a6zcKr/XidpGLfmrB6JdgpOkDbAWqK6V8rO4IC5FvpJ8Ke5eLPpqEcZMG4COMdNIZwF5gs9Z6vPRTkd+knwpHJ3N+7Zgy1kUbg1GVsRqwR2s9VRlV9B4GJgE7MIoIvI2xtu/TQHurOZMlgSSt9Y3C/wnE7SCf+mklIEonr0UpRH6TfirsXS776DNAO621Vkq5A42AsymVyIXIb9JPhaOT4NeOJc/PbYYxJ2JC8uN3tdb7lbH0Rj2ME8hFrfW/SqmJGKklTyilnLXWSUXVdnH7kH4qHIH0U2HvpI8KRyD9VDg6KXhlx7Sx3tm/AEqp1RgnlPuB/cknjyPJ/5GcdjIQI5UEObmIwiL9VDgC6afC3kkfFY5A+qlwdDLn10ForXdhnGwaKKX6pGxXSpVQSn2HkX6yR2s9vajaKIT0U+EIpJ8Keyd9VDgC6afCEUnw6wCUUir54V/AVaB38vZugCewDGiktX62KNonBEg/FY5B+qmwd9JHhSOQfioclcz5dRBKKZVcKKAX8D7GHIujwECt9YWibZ0QBumnwhFIPxX2TvqocATST4UjkuDXgSilvDHusDUBXtVaTyviJgmRhvRT4Qiknwp7J31UOALpp8LRSMErx9IH2A/00lrHFHVjhMiA9FPhCKSfCnsnfVQ4AumnwqHIyK8DSUkvKep2CJEZ6afCEUg/FfZO+qhwBNJPhaOR4FcIIYQQQgghRLEn1Z6FEEIIIYQQQhR7EvwKIYQQQgghhCj2JPgVQgghhBBCCFHsSfArhBBCCCGEEKLYk+BXCCGEEEIIIUSxJ8GvEEIIIYQQQohiT4JfIYQQQgghhBDF3v8DkMF35Dp2AMYAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 1152x1440 with 13 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"i=random.randint(0,len(df)-240)\n",
"df.iloc[i:i+240].plot(subplots=True, fontsize=12, figsize=(16,20))\n",
"pwk.save_fig('01-one-month')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 3 - Save it"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Dataset saved. (3.0 Mo)\n",
"Synop description saved.\n"
]
}
],
"source": [
"dataset_name = 'synop-LYS.csv'\n",
"dataset_desc = 'synop.json'\n",
"output_dir = './data'\n",
"\n",
"# ---- Save it\n",
"#\n",
"\n",
"pwk.mkdir(output_dir)\n",
"\n",
"filedata = f'{output_dir}/{dataset_name}'\n",
"filedesc = f'{output_dir}/{dataset_desc}'\n",
"\n",
"df.to_csv(filedata, sep=';', index=False)\n",
"size=os.path.getsize(filedata)/(1024*1024)\n",
"print(f'Dataset saved. ({size:0.1f} Mo)')\n",
"\n",
"with open(filedesc, 'w', encoding='utf-8') as f:\n",
" json.dump(code2desc, f, indent=4)\n",
"print('Synop description saved.')\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"End time is : Saturday 19 December 2020, 10:43:22\n",
"Duration is : 00:00:04 776ms\n",
"This notebook ends here\n"
]
}
],
"source": [
"pwk.end()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"<img width=\"80px\" src=\"../fidle/img/00-Fidle-logo-01.svg\"></img>"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.7"
}
},
"nbformat": 4,
"nbformat_minor": 4
}