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change_physical_potential.ipynb
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change_physical_potential.ipynb
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			{
			"cells": [
			{
			"cell_type": "code",
			"execution_count": 1,
			"metadata": {},
			"outputs": [],
			"source": [
			"import pandas as pd\n",
			"import numpy as np\n",
			"import xarray as xr\n",
			"from pvlib.tools import cosd, sind, tand\n",
			"import pvlib.irradiance as pvlib\n",
			"\n",
			"import os\n",
			"import time\n",
			"import util\n",
			"\n",
			"%matplotlib notebook\n",
			"import matplotlib.pyplot as plt\n",
			"from matplotlib.lines import Line2D\n"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 2,
			"metadata": {},
			"outputs": [],
			"source": [
			"workspace = '/scratch/walch/workspace_tilted_irrad_change'"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"# Part 1: get subset of data"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Load physical potential"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 3,
			"metadata": {},
			"outputs": [],
			"source": [
			"fp = '/work/hyenergy/output/solar_potential/physical_potential/results/physical_potential_dhm25_200_CH_ELM50_1000.nc'\n",
			"meteo = xr.open_mfdataset(fp)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 4,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"<xarray.Dataset>\n",
			"Dimensions: (timestamp: 159, x: 1742, y: 1103)\n",
			"Coordinates:\n",
			" * x (x) float64 4.855e+05 4.857e+05 ... 8.335e+05 8.337e+05\n",
			" * y (y) float64 7.529e+04 7.549e+04 ... 2.955e+05 2.957e+05\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15T07:00:00 ... 2001-12-15T15:00:00\n",
			"Data variables:\n",
			" SIS (x, y, timestamp) float64 dask.array<shape=(1742, 1103, 159), chunksize=(1742, 1103, 159)>\n",
			" SISDIR (x, y, timestamp) float64 dask.array<shape=(1742, 1103, 159), chunksize=(1742, 1103, 159)>\n",
			" apparent_zenith (x, y, timestamp) float64 dask.array<shape=(1742, 1103, 159), chunksize=(1742, 1103, 159)>\n",
			" azimuth (x, y, timestamp) float64 dask.array<shape=(1742, 1103, 159), chunksize=(1742, 1103, 159)>\n",
			" DHI (x, y, timestamp) float64 dask.array<shape=(1742, 1103, 159), chunksize=(1742, 1103, 159)>\n",
			" DNI (x, y, timestamp) float64 dask.array<shape=(1742, 1103, 159), chunksize=(1742, 1103, 159)>\n",
			" rel_airmass (x, y, timestamp) float64 dask.array<shape=(1742, 1103, 159), chunksize=(1742, 1103, 159)>\n",
			" DNI_extra (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>"
			]
			},
			"execution_count": 4,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"meteo"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"#### Resample to 1000 x 1000 m"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 5,
			"metadata": {},
			"outputs": [],
			"source": [
			"x_1km = meteo.x[ 2:: 5 ]\n",
			"y_1km = meteo.y[ 2:: 5 ]"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 6,
			"metadata": {},
			"outputs": [],
			"source": [
			"meteo_1km = meteo.sel( x = x_1km, y = y_1km )"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 19,
			"metadata": {},
			"outputs": [],
			"source": [
			"# meteo_1km.to_netcdf( os.path.join( workspace, 'files', 'meteo_1km.nc' ) )"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 7,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"<xarray.Dataset>\n",
			"Dimensions: (timestamp: 159, x: 348, y: 221)\n",
			"Coordinates:\n",
			" * x (x) float64 4.859e+05 4.869e+05 ... 8.319e+05 8.329e+05\n",
			" * y (y) float64 7.569e+04 7.669e+04 ... 2.947e+05 2.957e+05\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15T07:00:00 ... 2001-12-15T15:00:00\n",
			"Data variables:\n",
			" SIS (x, y, timestamp) float64 dask.array<shape=(348, 221, 159), chunksize=(348, 221, 159)>\n",
			" SISDIR (x, y, timestamp) float64 dask.array<shape=(348, 221, 159), chunksize=(348, 221, 159)>\n",
			" apparent_zenith (x, y, timestamp) float64 dask.array<shape=(348, 221, 159), chunksize=(348, 221, 159)>\n",
			" azimuth (x, y, timestamp) float64 dask.array<shape=(348, 221, 159), chunksize=(348, 221, 159)>\n",
			" DHI (x, y, timestamp) float64 dask.array<shape=(348, 221, 159), chunksize=(348, 221, 159)>\n",
			" DNI (x, y, timestamp) float64 dask.array<shape=(348, 221, 159), chunksize=(348, 221, 159)>\n",
			" rel_airmass (x, y, timestamp) float64 dask.array<shape=(348, 221, 159), chunksize=(348, 221, 159)>\n",
			" DNI_extra (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>"
			]
			},
			"execution_count": 7,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"meteo_1km"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Load rooftop data"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 8,
			"metadata": {},
			"outputs": [],
			"source": [
			"ROOFTOP_FEATURES = ['XCOORD', 'YCOORD', 'DF_UID', 'FLAECHE', 'NEIGUNG', 'AUSRICHTUNG']"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 9,
			"metadata": {},
			"outputs": [],
			"source": [
			"fp = '/work/hyenergy/raw/Sonnendach/Sonnendach_all_roofs/SOLKAT_CH_DACH_LV03.txt'"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 10,
			"metadata": {},
			"outputs": [],
			"source": [
			"roofs = pd.read_csv( fp, usecols = ROOFTOP_FEATURES )"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"#### Subset of rooftops"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": [
			"ROOFTOP_SUBSET_SIZE = int(1e6)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 12,
			"metadata": {},
			"outputs": [],
			"source": [
			"# roof_sample = roofs.sample( ROOFTOP_SUBSET_SIZE ).sort_values('DF_UID')\n",
			"# roof_sample.to_csv( os.path.join( workspace, 'files', 'roof_subset_1M.csv' ) )"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 9,
			"metadata": {},
			"outputs": [],
			"source": [
			"# Use existing rooftop sample\n",
			"roof_sample = pd.read_csv( os.path.join( workspace, 'files', 'roof_subset_1M.csv' ), index_col = 0 )"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"#### Sample of partly_shading (TAKES LONG!)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": [
			"fp = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/shading_stats/CH_partly_shading_replaced.nc'\n",
			"partly_shading = xr.open_mfdataset( fp, chunks={'DF_UID': 10000} )"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 8,
			"metadata": {},
			"outputs": [],
			"source": [
			"partly_shading_sel = partly_shading.sel( DF_UID = roof_sample.DF_UID.values )"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 9,
			"metadata": {
			"scrolled": true
			},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"<xarray.Dataset>\n",
			"Dimensions: (DF_UID: 1000000, timestamp: 146)\n",
			"Coordinates:\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ... 2001-12-15T15:00:00\n",
			" * DF_UID (DF_UID) float64 7.0 13.0 31.0 ... 9.89e+06 9.89e+06\n",
			"Data variables:\n",
			" partly_shading (timestamp, DF_UID) float64 dask.array<shape=(146, 1000000), chunksize=(146, 1034)>"
			]
			},
			"execution_count": 9,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"partly_shading_sel"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 10,
			"metadata": {},
			"outputs": [],
			"source": [
			"# partly_shading_sel.to_netcdf('/scratch/walch/workspace_tilted_irrad_change/files/partly_shading_subset_1M.nc')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"## Part 2: Get change data"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 18,
			"metadata": {},
			"outputs": [],
			"source": [
			"CHANGE_INTERVALS = [ -15, -13, -11, 9, 11, 13, 15 ]"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"#### Meteo data"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 10,
			"metadata": {},
			"outputs": [
			{
			"name": "stdout",
			"output_type": "stream",
			"text": [
			"-15\n",
			"SIS\n",
			"SISDIR\n",
			"DHI\n",
			"DNI\n",
			"saving to file\n",
			"Loop iteration time: 67.076 seconds\n",
			"-13\n",
			"SIS\n",
			"SISDIR\n",
			"DHI\n",
			"DNI\n",
			"saving to file\n",
			"Loop iteration time: 43.997 seconds\n",
			"-11\n",
			"SIS\n",
			"SISDIR\n",
			"DHI\n",
			"DNI\n",
			"saving to file\n",
			"Loop iteration time: 48.038 seconds\n",
			"-9\n",
			"SIS\n",
			"SISDIR\n",
			"DHI\n",
			"DNI\n",
			"saving to file\n",
			"Loop iteration time: 45.297 seconds\n",
			"9\n",
			"SIS\n",
			"SISDIR\n",
			"DHI\n",
			"DNI\n",
			"saving to file\n",
			"Loop iteration time: 44.499 seconds\n",
			"11\n",
			"SIS\n",
			"SISDIR\n",
			"DHI\n",
			"DNI\n",
			"saving to file\n",
			"Loop iteration time: 50.133 seconds\n",
			"13\n",
			"SIS\n",
			"SISDIR\n",
			"DHI\n",
			"DNI\n",
			"saving to file\n",
			"Loop iteration time: 50.789 seconds\n",
			"15\n",
			"SIS\n",
			"SISDIR\n",
			"DHI\n",
			"DNI\n",
			"saving to file\n",
			"Loop iteration time: 42.815 seconds\n"
			]
			}
			],
			"source": [
			"old_change = 0\n",
			"\n",
			"for change in CHANGE_INTERVALS:\n",
			" print(change)\n",
			" tt = time.time()\n",
			" \n",
			" for var in ['SIS', 'SISDIR', 'DHI', 'DNI']:\n",
			" print(var)\n",
			" # first_undo old change; then, do new change\n",
			" meteo_1km[ var ] = meteo_1km[ var ] / ( 1 + old_change/100 )\n",
			" meteo_1km[ var ] = meteo_1km[ var ] * ( 1 + change/100 ) \n",
			" \n",
			" print('saving to file')\n",
			" meteo_1km.to_netcdf( os.path.join( workspace, 'files', 'meteo_change_%d.nc' %change ) )\n",
			" \n",
			" old_change = change\n",
			" print('Loop iteration time: %.3f seconds' %(time.time() - tt))"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"#### Prepare control file"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 19,
			"metadata": {},
			"outputs": [],
			"source": [
			"N_BATCHES = 10\n",
			"BATCH_SIZE = 100000"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 20,
			"metadata": {},
			"outputs": [],
			"source": [
			"START = [ batch * BATCH_SIZE + 1 for batch in range(N_BATCHES) ]"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 21,
			"metadata": {},
			"outputs": [],
			"source": [
			"control_file = open( os.path.join( workspace, 'batch_control.txt' ) ,\"w+\")\n",
			"\n",
			"for change in CHANGE_INTERVALS:\n",
			" for idx, start in enumerate(START):\n",
			" control_file.write( '%d %d %d\\n' %(change, idx, start))"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 22,
			"metadata": {},
			"outputs": [],
			"source": [
			"control_file.close()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 23,
			"metadata": {},
			"outputs": [],
			"source": [
			"N_ARRAY = len(CHANGE_INTERVALS) * len(START)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 24,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"70"
			]
			},
			"execution_count": 24,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"N_ARRAY"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"## Part 3: Open all change files and merge to one dataset"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 7,
			"metadata": {},
			"outputs": [],
			"source": [
			"# Merge yearly files of all change signals:\n",
			"files = glob.glob('/scratch/walch/workspace_tilted_irrad_change/files/rooftop_irrad_change_*.nc')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 15,
			"metadata": {},
			"outputs": [],
			"source": [
			"change_perc = lambda file: int(os.path.splitext(os.path.split(file)[1])[0].split('_')[-1])"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 36,
			"metadata": {},
			"outputs": [],
			"source": [
			"irrad_df = []\n",
			"for file in files:\n",
			" data = xr.open_dataset( file )\n",
			" new_df = pd.DataFrame( data = data.yearly_kWh_m2_a.values, \n",
			" index = data.DF_UID.values, \n",
			" columns = [ change_perc(file) ] )\n",
			" irrad_df.append(new_df)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 37,
			"metadata": {},
			"outputs": [],
			"source": [
			"irrad_df = pd.concat(irrad_df, axis = 1).sort_index(axis = 1)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 38,
			"metadata": {},
			"outputs": [
			{
			"data": {
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			" <tr style=\"text-align: right;\">\n",
			" <th></th>\n",
			" <th>-15</th>\n",
			" <th>-13</th>\n",
			" <th>-11</th>\n",
			" <th>-9</th>\n",
			" <th>-7</th>\n",
			" <th>-5</th>\n",
			" <th>-3</th>\n",
			" <th>-1</th>\n",
			" <th>0</th>\n",
			" <th>1</th>\n",
			" <th>3</th>\n",
			" <th>5</th>\n",
			" <th>7</th>\n",
			" <th>9</th>\n",
			" <th>11</th>\n",
			" <th>13</th>\n",
			" <th>15</th>\n",
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			" <tbody>\n",
			" <tr>\n",
			" <th>7.0</th>\n",
			" <td>876.871364</td>\n",
			" <td>897.491194</td>\n",
			" <td>918.110868</td>\n",
			" <td>938.729989</td>\n",
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			" <td>1082.996680</td>\n",
			" <td>1103.587425</td>\n",
			" <td>1124.176758</td>\n",
			" <td>1144.765483</td>\n",
			" <td>1165.354324</td>\n",
			" <td>1185.942673</td>\n",
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			" <th>13.0</th>\n",
			" <td>1058.674358</td>\n",
			" <td>1082.937109</td>\n",
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			" <td>1131.377532</td>\n",
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			" <td>1125.710690</td>\n",
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			" <td>1203.261798</td>\n",
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			" <td>1319.123344</td>\n",
			" <td>1331.985529</td>\n",
			" <td>1357.695195</td>\n",
			" <td>1383.378986</td>\n",
			" <td>1409.036902</td>\n",
			" <td>1434.668943</td>\n",
			" <td>1460.280364</td>\n",
			" <td>1485.869625</td>\n",
			" <td>1511.435929</td>\n",
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			" <th>37.0</th>\n",
			" <td>1196.803546</td>\n",
			" <td>1224.178782</td>\n",
			" <td>1251.517933</td>\n",
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			" <td>1306.087980</td>\n",
			" <td>1333.318877</td>\n",
			" <td>1360.513688</td>\n",
			" <td>1387.672414</td>\n",
			" <td>1401.248169</td>\n",
			" <td>1414.837987</td>\n",
			" <td>1441.999023</td>\n",
			" <td>1469.126833</td>\n",
			" <td>1496.221418</td>\n",
			" <td>1523.282778</td>\n",
			" <td>1550.317800</td>\n",
			" <td>1577.324467</td>\n",
			" <td>1604.301735</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>47.0</th>\n",
			" <td>660.567669</td>\n",
			" <td>675.577233</td>\n",
			" <td>690.562282</td>\n",
			" <td>705.522816</td>\n",
			" <td>720.458835</td>\n",
			" <td>735.370339</td>\n",
			" <td>750.257327</td>\n",
			" <td>765.119801</td>\n",
			" <td>772.548891</td>\n",
			" <td>779.979035</td>\n",
			" <td>794.823080</td>\n",
			" <td>809.643782</td>\n",
			" <td>824.441141</td>\n",
			" <td>839.215157</td>\n",
			" <td>853.972070</td>\n",
			" <td>868.710053</td>\n",
			" <td>883.428159</td>\n",
			" </tr>\n",
			" </tbody>\n",
			"</table>\n",
			"</div>"
			],
			"text/plain": [
			" -15 -13 -11 -9 -7 \\\n",
			"7.0 876.871364 897.491194 918.110868 938.729989 959.348557 \n",
			"13.0 1058.674358 1082.937109 1107.172154 1131.377532 1155.553246 \n",
			"31.0 1125.710690 1151.589057 1177.439426 1203.261798 1229.056172 \n",
			"37.0 1196.803546 1224.178782 1251.517933 1278.820999 1306.087980 \n",
			"47.0 660.567669 675.577233 690.562282 705.522816 720.458835 \n",
			"\n",
			" -5 -3 -1 0 1 \\\n",
			"7.0 979.966572 1000.584033 1021.200942 1031.508136 1041.810823 \n",
			"13.0 1179.699293 1203.815675 1227.902391 1239.934625 1251.965717 \n",
			"31.0 1254.822549 1280.560929 1306.271311 1319.123344 1331.985529 \n",
			"37.0 1333.318877 1360.513688 1387.672414 1401.248169 1414.837987 \n",
			"47.0 735.370339 750.257327 765.119801 772.548891 779.979035 \n",
			"\n",
			" 3 5 7 9 11 \\\n",
			"7.0 1062.404523 1082.996680 1103.587425 1124.176758 1144.765483 \n",
			"13.0 1276.035085 1300.076537 1324.089953 1348.075333 1372.035163 \n",
			"31.0 1357.695195 1383.378986 1409.036902 1434.668943 1460.280364 \n",
			"37.0 1441.999023 1469.126833 1496.221418 1523.282778 1550.317800 \n",
			"47.0 794.823080 809.643782 824.441141 839.215157 853.972070 \n",
			"\n",
			" 13 15 \n",
			"7.0 1165.354324 1185.942673 \n",
			"13.0 1395.974410 1419.889426 \n",
			"31.0 1485.869625 1511.435929 \n",
			"37.0 1577.324467 1604.301735 \n",
			"47.0 868.710053 883.428159 "
			]
			},
			"execution_count": 38,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"irrad_df.head()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 39,
			"metadata": {},
			"outputs": [],
			"source": [
			"irrad_df.to_csv('/scratch/walch/workspace_tilted_irrad_change/files/rooftop_irrad_change_summary.csv')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"# Spielwiese"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Find optimal angle:\n",
			"Criterion: Should have max 10% shading on rooftops below 80 degree zenith angle"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 3,
			"metadata": {},
			"outputs": [],
			"source": [
			"def atand( ratio ):\n",
			" return np.degrees( np.arctan( ratio ) )\n",
			"\n",
			"def get_DP_ratio( tilt_angle, shade_ratio, zenith_angle ):\n",
			" alpha = tilt_angle\n",
			" beta = 90 - zenith_angle\n",
			" R = shade_ratio\n",
			" \n",
			" tanR = tand(alpha) / tand(beta)\n",
			" \n",
			" # NOTE: Formula derived in hadwritten notes from 15/02\n",
			" return tanR - R * tanR - R\n",
			"\n",
			"def get_shading_ratio( tilt_angle, DP_ratio, zenith_angle ):\n",
			"# return R (percentage of shading on roofs)\n",
			" alpha = tilt_angle\n",
			" beta = 90 - zenith_angle\n",
			" DP = DP_ratio\n",
			" \n",
			" tanR = tand(alpha) / tand(beta) # ratio of tangents\n",
			" shade_ratio = ( tanR - DP ) / ( 1 + tanR )\n",
			" return np.minimum( np.maximum( shade_ratio, 0), 1)\n",
			" \n",
			"def get_tilt_angle( shade_ratio, DP_ratio, zenith_angle ):\n",
			"# return alpha (tilt angle of panel)\n",
			" beta = 90 - zenith_angle\n",
			" DP = DP_ratio\n",
			" R = shade_ratio\n",
			" \n",
			" return atand( tand(beta) * (DP+R)/(1-R) )\n",
			"\n",
			"def get_zenith_angle( shade_ratio, DP_ratio, zenith_angle ):\n",
			"# return zenith angle of sun\n",
			" alpha = tilt_angle\n",
			" DP = DP_ratio\n",
			" R = shade_ratio\n",
			" \n",
			" beta = atand( tand(alpha) * (1-R)/(DP+R) )\n",
			" return 90 - beta\n",
			"\n",
			"def get_shading_SVF( DP_ratio, tilt_angle ):\n",
			"# proportion of the upper semi-sphere, starting from the center of the panel, that is covered by the previous panel (in 1D)\n",
			"# additional SVF factor calculated as beta / 180° (modelled as spherical lune on semi-sphere: http://mathworld.wolfram.com/SphericalLune.html)\n",
			" alpha = tilt_angle\n",
			" DP = DP_ratio\n",
			" \n",
			" beta = atand( 0.5/(0.5 + DP) * tand(alpha) )\n",
			" return beta / 180\n",
			" \n",
			"def cutoff_zenith( DP_ratio, tilt_angle ):\n",
			"# gives zenith angle below which (i.e. at higher sun altitudes) panels are completely unshaded\n",
			" return 90 - atand( tand(tilt_angle) / DP_ratio )"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 4,
			"metadata": {},
			"outputs": [],
			"source": [
			"R = 0.1\n",
			"zenith = 80\n",
			"tilt = 30\n",
			"DP = 1"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 5,
			"metadata": {},
			"outputs": [],
			"source": [
			"# ratios = [0, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3]\n",
			"zeniths = [50, 55, 60, 65, 70, 75, 80, 85]\n",
			"tilts = [0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50]\n",
			"DP_ratios = [0, 1, 2, 3]\n"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 6,
			"metadata": {},
			"outputs": [],
			"source": [
			"shading = xr.DataArray( data = np.zeros((len(zeniths), len(tilts), len(DP_ratios))), \n",
			" coords = {'zenith' : zeniths, 'tilt' : tilts, 'distance' : DP_ratios},\n",
			" dims = ('zenith', 'tilt', 'distance'),\n",
			" name = 'shading')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 7,
			"metadata": {},
			"outputs": [],
			"source": [
			"shading_df = shading.to_dataframe().reset_index()\n",
			"shading_df['shading'] = get_shading_ratio( shading_df['tilt'], shading_df['distance'], shading_df['zenith'] )"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 8,
			"metadata": {},
			"outputs": [],
			"source": [
			"data = shading_df.set_index(['zenith', 'tilt', 'distance']).to_xarray()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": 9,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"application/javascript": [
			"/* Put everything inside the global mpl namespace */\n",
			"window.mpl = {};\n",
			"\n",
			"\n",
			"mpl.get_websocket_type = function() {\n",
			" if (typeof(WebSocket) !== 'undefined') {\n",
			" return WebSocket;\n",
			" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
			" return MozWebSocket;\n",
			" } else {\n",
			" alert('Your browser does not have WebSocket support.' +\n",
			" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
			" 'Firefox 4 and 5 are also supported but you ' +\n",
			" 'have to enable WebSockets in about:config.');\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
			" this.id = figure_id;\n",
			"\n",
			" this.ws = websocket;\n",
			"\n",
			" this.supports_binary = (this.ws.binaryType != undefined);\n",
			"\n",
			" if (!this.supports_binary) {\n",
			" var warnings = document.getElementById(\"mpl-warnings\");\n",
			" if (warnings) {\n",
			" warnings.style.display = 'block';\n",
			" warnings.textContent = (\n",
			" \"This browser does not support binary websocket messages. \" +\n",
			" \"Performance may be slow.\");\n",
			" }\n",
			" }\n",
			"\n",
			" this.imageObj = new Image();\n",
			"\n",
			" this.context = undefined;\n",
			" this.message = undefined;\n",
			" this.canvas = undefined;\n",
			" this.rubberband_canvas = undefined;\n",
			" this.rubberband_context = undefined;\n",
			" this.format_dropdown = undefined;\n",
			"\n",
			" this.image_mode = 'full';\n",
			"\n",
			" this.root = $('<div/>');\n",
			" this._root_extra_style(this.root)\n",
			" this.root.attr('style', 'display: inline-block');\n",
			"\n",
			" $(parent_element).append(this.root);\n",
			"\n",
			" this._init_header(this);\n",
			" this._init_canvas(this);\n",
			" this._init_toolbar(this);\n",
			"\n",
			" var fig = this;\n",
			"\n",
			" this.waiting = false;\n",
			"\n",
			" this.ws.onopen = function () {\n",
			" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
			" fig.send_message(\"send_image_mode\", {});\n",
			" if (mpl.ratio != 1) {\n",
			" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
			" }\n",
			" fig.send_message(\"refresh\", {});\n",
			" }\n",
			"\n",
			" this.imageObj.onload = function() {\n",
			" if (fig.image_mode == 'full') {\n",
			" // Full images could contain transparency (where diff images\n",
			" // almost always do), so we need to clear the canvas so that\n",
			" // there is no ghosting.\n",
			" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
			" }\n",
			" fig.context.drawImage(fig.imageObj, 0, 0);\n",
			" };\n",
			"\n",
			" this.imageObj.onunload = function() {\n",
			" fig.ws.close();\n",
			" }\n",
			"\n",
			" this.ws.onmessage = this._make_on_message_function(this);\n",
			"\n",
			" this.ondownload = ondownload;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_header = function() {\n",
			" var titlebar = $(\n",
			" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
			" 'ui-helper-clearfix\"/>');\n",
			" var titletext = $(\n",
			" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
			" 'text-align: center; padding: 3px;\"/>');\n",
			" titlebar.append(titletext)\n",
			" this.root.append(titlebar);\n",
			" this.header = titletext[0];\n",
			"}\n",
			"\n",
			"\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_canvas = function() {\n",
			" var fig = this;\n",
			"\n",
			" var canvas_div = $('<div/>');\n",
			"\n",
			" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
			"\n",
			" function canvas_keyboard_event(event) {\n",
			" return fig.key_event(event, event['data']);\n",
			" }\n",
			"\n",
			" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
			" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
			" this.canvas_div = canvas_div\n",
			" this._canvas_extra_style(canvas_div)\n",
			" this.root.append(canvas_div);\n",
			"\n",
			" var canvas = $('<canvas/>');\n",
			" canvas.addClass('mpl-canvas');\n",
			" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
			"\n",
			" this.canvas = canvas[0];\n",
			" this.context = canvas[0].getContext(\"2d\");\n",
			"\n",
			" var backingStore = this.context.backingStorePixelRatio \|\|\n",
			"\tthis.context.webkitBackingStorePixelRatio \|\|\n",
			"\tthis.context.mozBackingStorePixelRatio \|\|\n",
			"\tthis.context.msBackingStorePixelRatio \|\|\n",
			"\tthis.context.oBackingStorePixelRatio \|\|\n",
			"\tthis.context.backingStorePixelRatio \|\| 1;\n",
			"\n",
			" mpl.ratio = (window.devicePixelRatio \|\| 1) / backingStore;\n",
			"\n",
			" var rubberband = $('<canvas/>');\n",
			" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
			"\n",
			" var pass_mouse_events = true;\n",
			"\n",
			" canvas_div.resizable({\n",
			" start: function(event, ui) {\n",
			" pass_mouse_events = false;\n",
			" },\n",
			" resize: function(event, ui) {\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" stop: function(event, ui) {\n",
			" pass_mouse_events = true;\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" });\n",
			"\n",
			" function mouse_event_fn(event) {\n",
			" if (pass_mouse_events)\n",
			" return fig.mouse_event(event, event['data']);\n",
			" }\n",
			"\n",
			" rubberband.mousedown('button_press', mouse_event_fn);\n",
			" rubberband.mouseup('button_release', mouse_event_fn);\n",
			" // Throttle sequential mouse events to 1 every 20ms.\n",
			" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
			"\n",
			" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
			" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
			"\n",
			" canvas_div.on(\"wheel\", function (event) {\n",
			" event = event.originalEvent;\n",
			" event['data'] = 'scroll'\n",
			" if (event.deltaY < 0) {\n",
			" event.step = 1;\n",
			" } else {\n",
			" event.step = -1;\n",
			" }\n",
			" mouse_event_fn(event);\n",
			" });\n",
			"\n",
			" canvas_div.append(canvas);\n",
			" canvas_div.append(rubberband);\n",
			"\n",
			" this.rubberband = rubberband;\n",
			" this.rubberband_canvas = rubberband[0];\n",
			" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
			" this.rubberband_context.strokeStyle = \"#000000\";\n",
			"\n",
			" this._resize_canvas = function(width, height) {\n",
			" // Keep the size of the canvas, canvas container, and rubber band\n",
			" // canvas in synch.\n",
			" canvas_div.css('width', width)\n",
			" canvas_div.css('height', height)\n",
			"\n",
			" canvas.attr('width', width * mpl.ratio);\n",
			" canvas.attr('height', height * mpl.ratio);\n",
			" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
			"\n",
			" rubberband.attr('width', width);\n",
			" rubberband.attr('height', height);\n",
			" }\n",
			"\n",
			" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
			" // upon first draw.\n",
			" this._resize_canvas(600, 600);\n",
			"\n",
			" // Disable right mouse context menu.\n",
			" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
			" return false;\n",
			" });\n",
			"\n",
			" function set_focus () {\n",
			" canvas.focus();\n",
			" canvas_div.focus();\n",
			" }\n",
			"\n",
			" window.setTimeout(set_focus, 100);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items) {\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) {\n",
			" // put a spacer in here.\n",
			" continue;\n",
			" }\n",
			" var button = $('<button/>');\n",
			" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
			" 'ui-button-icon-only');\n",
			" button.attr('role', 'button');\n",
			" button.attr('aria-disabled', 'false');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			"\n",
			" var icon_img = $('<span/>');\n",
			" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
			" icon_img.addClass(image);\n",
			" icon_img.addClass('ui-corner-all');\n",
			"\n",
			" var tooltip_span = $('<span/>');\n",
			" tooltip_span.addClass('ui-button-text');\n",
			" tooltip_span.html(tooltip);\n",
			"\n",
			" button.append(icon_img);\n",
			" button.append(tooltip_span);\n",
			"\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" var fmt_picker_span = $('<span/>');\n",
			"\n",
			" var fmt_picker = $('<select/>');\n",
			" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
			" fmt_picker_span.append(fmt_picker);\n",
			" nav_element.append(fmt_picker_span);\n",
			" this.format_dropdown = fmt_picker[0];\n",
			"\n",
			" for (var ind in mpl.extensions) {\n",
			" var fmt = mpl.extensions[ind];\n",
			" var option = $(\n",
			" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
			" fmt_picker.append(option)\n",
			" }\n",
			"\n",
			" // Add hover states to the ui-buttons\n",
			" $( \".ui-button\" ).hover(\n",
			" function() { $(this).addClass(\"ui-state-hover\");},\n",
			" function() { $(this).removeClass(\"ui-state-hover\");}\n",
			" );\n",
			"\n",
			" var status_bar = $('<span class=\"mpl-message\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
			" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
			" // which will in turn request a refresh of the image.\n",
			" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_message = function(type, properties) {\n",
			" properties['type'] = type;\n",
			" properties['figure_id'] = this.id;\n",
			" this.ws.send(JSON.stringify(properties));\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_draw_message = function() {\n",
			" if (!this.waiting) {\n",
			" this.waiting = true;\n",
			" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
			" }\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" var format_dropdown = fig.format_dropdown;\n",
			" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
			" fig.ondownload(fig, format);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
			" var size = msg['size'];\n",
			" if (size[0] != fig.canvas.width \|\| size[1] != fig.canvas.height) {\n",
			" fig._resize_canvas(size[0], size[1]);\n",
			" fig.send_message(\"refresh\", {});\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
			" var x0 = msg['x0'] / mpl.ratio;\n",
			" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
			" var x1 = msg['x1'] / mpl.ratio;\n",
			" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
			" x0 = Math.floor(x0) + 0.5;\n",
			" y0 = Math.floor(y0) + 0.5;\n",
			" x1 = Math.floor(x1) + 0.5;\n",
			" y1 = Math.floor(y1) + 0.5;\n",
			" var min_x = Math.min(x0, x1);\n",
			" var min_y = Math.min(y0, y1);\n",
			" var width = Math.abs(x1 - x0);\n",
			" var height = Math.abs(y1 - y0);\n",
			"\n",
			" fig.rubberband_context.clearRect(\n",
			" 0, 0, fig.canvas.width, fig.canvas.height);\n",
			"\n",
			" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
			" // Updates the figure title.\n",
			" fig.header.textContent = msg['label'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
			" var cursor = msg['cursor'];\n",
			" switch(cursor)\n",
			" {\n",
			" case 0:\n",
			" cursor = 'pointer';\n",
			" break;\n",
			" case 1:\n",
			" cursor = 'default';\n",
			" break;\n",
			" case 2:\n",
			" cursor = 'crosshair';\n",
			" break;\n",
			" case 3:\n",
			" cursor = 'move';\n",
			" break;\n",
			" }\n",
			" fig.rubberband_canvas.style.cursor = cursor;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
			" fig.message.textContent = msg['message'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
			" // Request the server to send over a new figure.\n",
			" fig.send_draw_message();\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
			" fig.image_mode = msg['mode'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Called whenever the canvas gets updated.\n",
			" this.send_message(\"ack\", {});\n",
			"}\n",
			"\n",
			"// A function to construct a web socket function for onmessage handling.\n",
			"// Called in the figure constructor.\n",
			"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
			" return function socket_on_message(evt) {\n",
			" if (evt.data instanceof Blob) {\n",
			" /* FIXME: We get \"Resource interpreted as Image but\n",
			" * transferred with MIME type text/plain:\" errors on\n",
			" * Chrome. But how to set the MIME type? It doesn't seem\n",
			" * to be part of the websocket stream */\n",
			" evt.data.type = \"image/png\";\n",
			"\n",
			" /* Free the memory for the previous frames */\n",
			" if (fig.imageObj.src) {\n",
			" (window.URL \|\| window.webkitURL).revokeObjectURL(\n",
			" fig.imageObj.src);\n",
			" }\n",
			"\n",
			" fig.imageObj.src = (window.URL \|\| window.webkitURL).createObjectURL(\n",
			" evt.data);\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
			" fig.imageObj.src = evt.data;\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			"\n",
			" var msg = JSON.parse(evt.data);\n",
			" var msg_type = msg['type'];\n",
			"\n",
			" // Call the \"handle_{type}\" callback, which takes\n",
			" // the figure and JSON message as its only arguments.\n",
			" try {\n",
			" var callback = fig[\"handle_\" + msg_type];\n",
			" } catch (e) {\n",
			" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
			" return;\n",
			" }\n",
			"\n",
			" if (callback) {\n",
			" try {\n",
			" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
			" callback(fig, msg);\n",
			" } catch (e) {\n",
			" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
			" }\n",
			" }\n",
			" };\n",
			"}\n",
			"\n",
			"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
			"mpl.findpos = function(e) {\n",
			" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
			" var targ;\n",
			" if (!e)\n",
			" e = window.event;\n",
			" if (e.target)\n",
			" targ = e.target;\n",
			" else if (e.srcElement)\n",
			" targ = e.srcElement;\n",
			" if (targ.nodeType == 3) // defeat Safari bug\n",
			" targ = targ.parentNode;\n",
			"\n",
			" // jQuery normalizes the pageX and pageY\n",
			" // pageX,Y are the mouse positions relative to the document\n",
			" // offset() returns the position of the element relative to the document\n",
			" var x = e.pageX - $(targ).offset().left;\n",
			" var y = e.pageY - $(targ).offset().top;\n",
			"\n",
			" return {\"x\": x, \"y\": y};\n",
			"};\n",
			"\n",
			"/*\n",
			" * return a copy of an object with only non-object keys\n",
			" * we need this to avoid circular references\n",
			" * http://stackoverflow.com/a/24161582/3208463\n",
			" */\n",
			"function simpleKeys (original) {\n",
			" return Object.keys(original).reduce(function (obj, key) {\n",
			" if (typeof original[key] !== 'object')\n",
			" obj[key] = original[key]\n",
			" return obj;\n",
			" }, {});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.mouse_event = function(event, name) {\n",
			" var canvas_pos = mpl.findpos(event)\n",
			"\n",
			" if (name === 'button_press')\n",
			" {\n",
			" this.canvas.focus();\n",
			" this.canvas_div.focus();\n",
			" }\n",
			"\n",
			" var x = canvas_pos.x * mpl.ratio;\n",
			" var y = canvas_pos.y * mpl.ratio;\n",
			"\n",
			" this.send_message(name, {x: x, y: y, button: event.button,\n",
			" step: event.step,\n",
			" guiEvent: simpleKeys(event)});\n",
			"\n",
			" /* This prevents the web browser from automatically changing to\n",
			" * the text insertion cursor when the button is pressed. We want\n",
			" * to control all of the cursor setting manually through the\n",
			" * 'cursor' event from matplotlib */\n",
			" event.preventDefault();\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" // Handle any extra behaviour associated with a key event\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.key_event = function(event, name) {\n",
			"\n",
			" // Prevent repeat events\n",
			" if (name == 'key_press')\n",
			" {\n",
			" if (event.which === this._key)\n",
			" return;\n",
			" else\n",
			" this._key = event.which;\n",
			" }\n",
			" if (name == 'key_release')\n",
			" this._key = null;\n",
			"\n",
			" var value = '';\n",
			" if (event.ctrlKey && event.which != 17)\n",
			" value += \"ctrl+\";\n",
			" if (event.altKey && event.which != 18)\n",
			" value += \"alt+\";\n",
			" if (event.shiftKey && event.which != 16)\n",
			" value += \"shift+\";\n",
			"\n",
			" value += 'k';\n",
			" value += event.which.toString();\n",
			"\n",
			" this._key_event_extra(event, name);\n",
			"\n",
			" this.send_message(name, {key: value,\n",
			" guiEvent: simpleKeys(event)});\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
			" if (name == 'download') {\n",
			" this.handle_save(this, null);\n",
			" } else {\n",
			" this.send_message(\"toolbar_button\", {name: name});\n",
			" }\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
			" this.message.textContent = tooltip;\n",
			"};\n",
			"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
			"\n",
			"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
			"\n",
			"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
			" // Create a \"websocket\"-like object which calls the given IPython comm\n",
			" // object with the appropriate methods. Currently this is a non binary\n",
			" // socket, so there is still some room for performance tuning.\n",
			" var ws = {};\n",
			"\n",
			" ws.close = function() {\n",
			" comm.close()\n",
			" };\n",
			" ws.send = function(m) {\n",
			" //console.log('sending', m);\n",
			" comm.send(m);\n",
			" };\n",
			" // Register the callback with on_msg.\n",
			" comm.on_msg(function(msg) {\n",
			" //console.log('receiving', msg['content']['data'], msg);\n",
			" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
			" ws.onmessage(msg['content']['data'])\n",
			" });\n",
			" return ws;\n",
			"}\n",
			"\n",
			"mpl.mpl_figure_comm = function(comm, msg) {\n",
			" // This is the function which gets called when the mpl process\n",
			" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
			"\n",
			" var id = msg.content.data.id;\n",
			" // Get hold of the div created by the display call when the Comm\n",
			" // socket was opened in Python.\n",
			" var element = $(\"#\" + id);\n",
			" var ws_proxy = comm_websocket_adapter(comm)\n",
			"\n",
			" function ondownload(figure, format) {\n",
			" window.open(figure.imageObj.src);\n",
			" }\n",
			"\n",
			" var fig = new mpl.figure(id, ws_proxy,\n",
			" ondownload,\n",
			" element.get(0));\n",
			"\n",
			" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
			" // web socket which is closed, not our websocket->open comm proxy.\n",
			" ws_proxy.onopen();\n",
			"\n",
			" fig.parent_element = element.get(0);\n",
			" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
			" if (!fig.cell_info) {\n",
			" console.error(\"Failed to find cell for figure\", id, fig);\n",
			" return;\n",
			" }\n",
			"\n",
			" var output_index = fig.cell_info[2]\n",
			" var cell = fig.cell_info[0];\n",
			"\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
			" var width = fig.canvas.width/mpl.ratio\n",
			" fig.root.unbind('remove')\n",
			"\n",
			" // Update the output cell to use the data from the current canvas.\n",
			" fig.push_to_output();\n",
			" var dataURL = fig.canvas.toDataURL();\n",
			" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
			" // the notebook keyboard shortcuts fail.\n",
			" IPython.keyboard_manager.enable()\n",
			" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
			" fig.close_ws(fig, msg);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.close_ws = function(fig, msg){\n",
			" fig.send_message('closing', msg);\n",
			" // fig.ws.close()\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
			" // Turn the data on the canvas into data in the output cell.\n",
			" var width = this.canvas.width/mpl.ratio\n",
			" var dataURL = this.canvas.toDataURL();\n",
			" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Tell IPython that the notebook contents must change.\n",
			" IPython.notebook.set_dirty(true);\n",
			" this.send_message(\"ack\", {});\n",
			" var fig = this;\n",
			" // Wait a second, then push the new image to the DOM so\n",
			" // that it is saved nicely (might be nice to debounce this).\n",
			" setTimeout(function () { fig.push_to_output() }, 1000);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items){\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) { continue; };\n",
			"\n",
			" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" // Add the status bar.\n",
			" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"\n",
			" // Add the close button to the window.\n",
			" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
			" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
			" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
			" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
			" buttongrp.append(button);\n",
			" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
			" titlebar.prepend(buttongrp);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(el){\n",
			" var fig = this\n",
			" el.on(\"remove\", function(){\n",
			"\tfig.close_ws(fig, {});\n",
			" });\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(el){\n",
			" // this is important to make the div 'focusable\n",
			" el.attr('tabindex', 0)\n",
			" // reach out to IPython and tell the keyboard manager to turn it's self\n",
			" // off when our div gets focus\n",
			"\n",
			" // location in version 3\n",
			" if (IPython.notebook.keyboard_manager) {\n",
			" IPython.notebook.keyboard_manager.register_events(el);\n",
			" }\n",
			" else {\n",
			" // location in version 2\n",
			" IPython.keyboard_manager.register_events(el);\n",
			" }\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" var manager = IPython.notebook.keyboard_manager;\n",
			" if (!manager)\n",
			" manager = IPython.keyboard_manager;\n",
			"\n",
			" // Check for shift+enter\n",
			" if (event.shiftKey && event.which == 13) {\n",
			" this.canvas_div.blur();\n",
			" event.shiftKey = false;\n",
			" // Send a \"J\" for go to next cell\n",
			" event.which = 74;\n",
			" event.keyCode = 74;\n",
			" manager.command_mode();\n",
			" manager.handle_keydown(event);\n",
			" }\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" fig.ondownload(fig, null);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.find_output_cell = function(html_output) {\n",
			" // Return the cell and output element which can be found uniquely in the notebook.\n",
			" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
			" // IPython event is triggered only after the cells have been serialised, which for\n",
			" // our purposes (turning an active figure into a static one), is too late.\n",
			" var cells = IPython.notebook.get_cells();\n",
			" var ncells = cells.length;\n",
			" for (var i=0; i<ncells; i++) {\n",
			" var cell = cells[i];\n",
			" if (cell.cell_type === 'code'){\n",
			" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
			" var data = cell.output_area.outputs[j];\n",
			" if (data.data) {\n",
			" // IPython >= 3 moved mimebundle to data attribute of output\n",
			" data = data.data;\n",
			" }\n",
			" if (data['text/html'] == html_output) {\n",
			" return [cell, data, j];\n",
			" }\n",
			" }\n",
			" }\n",
			" }\n",
			"}\n",
			"\n",
			"// Register the function which deals with the matplotlib target/channel.\n",
			"// The kernel may be null if the page has been refreshed.\n",
			"if (IPython.notebook.kernel != null) {\n",
			" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
			"}\n"
			],
			"text/plain": [
			"<IPython.core.display.Javascript object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/html": [
			"<img 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\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/plain": [
			"<matplotlib.collections.QuadMesh at 0x7f04e9841128>"
			]
			},
			"execution_count": 9,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"plt.figure()\n",
			"data.shading.sel( zenith = 80, tilt = slice(0, 45) ).plot()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 11,
			"metadata": {
			"scrolled": false
			},
			"outputs": [
			{
			"data": {
			"application/javascript": [
			"/* Put everything inside the global mpl namespace */\n",
			"window.mpl = {};\n",
			"\n",
			"\n",
			"mpl.get_websocket_type = function() {\n",
			" if (typeof(WebSocket) !== 'undefined') {\n",
			" return WebSocket;\n",
			" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
			" return MozWebSocket;\n",
			" } else {\n",
			" alert('Your browser does not have WebSocket support.' +\n",
			" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
			" 'Firefox 4 and 5 are also supported but you ' +\n",
			" 'have to enable WebSockets in about:config.');\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
			" this.id = figure_id;\n",
			"\n",
			" this.ws = websocket;\n",
			"\n",
			" this.supports_binary = (this.ws.binaryType != undefined);\n",
			"\n",
			" if (!this.supports_binary) {\n",
			" var warnings = document.getElementById(\"mpl-warnings\");\n",
			" if (warnings) {\n",
			" warnings.style.display = 'block';\n",
			" warnings.textContent = (\n",
			" \"This browser does not support binary websocket messages. \" +\n",
			" \"Performance may be slow.\");\n",
			" }\n",
			" }\n",
			"\n",
			" this.imageObj = new Image();\n",
			"\n",
			" this.context = undefined;\n",
			" this.message = undefined;\n",
			" this.canvas = undefined;\n",
			" this.rubberband_canvas = undefined;\n",
			" this.rubberband_context = undefined;\n",
			" this.format_dropdown = undefined;\n",
			"\n",
			" this.image_mode = 'full';\n",
			"\n",
			" this.root = $('<div/>');\n",
			" this._root_extra_style(this.root)\n",
			" this.root.attr('style', 'display: inline-block');\n",
			"\n",
			" $(parent_element).append(this.root);\n",
			"\n",
			" this._init_header(this);\n",
			" this._init_canvas(this);\n",
			" this._init_toolbar(this);\n",
			"\n",
			" var fig = this;\n",
			"\n",
			" this.waiting = false;\n",
			"\n",
			" this.ws.onopen = function () {\n",
			" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
			" fig.send_message(\"send_image_mode\", {});\n",
			" if (mpl.ratio != 1) {\n",
			" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
			" }\n",
			" fig.send_message(\"refresh\", {});\n",
			" }\n",
			"\n",
			" this.imageObj.onload = function() {\n",
			" if (fig.image_mode == 'full') {\n",
			" // Full images could contain transparency (where diff images\n",
			" // almost always do), so we need to clear the canvas so that\n",
			" // there is no ghosting.\n",
			" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
			" }\n",
			" fig.context.drawImage(fig.imageObj, 0, 0);\n",
			" };\n",
			"\n",
			" this.imageObj.onunload = function() {\n",
			" fig.ws.close();\n",
			" }\n",
			"\n",
			" this.ws.onmessage = this._make_on_message_function(this);\n",
			"\n",
			" this.ondownload = ondownload;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_header = function() {\n",
			" var titlebar = $(\n",
			" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
			" 'ui-helper-clearfix\"/>');\n",
			" var titletext = $(\n",
			" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
			" 'text-align: center; padding: 3px;\"/>');\n",
			" titlebar.append(titletext)\n",
			" this.root.append(titlebar);\n",
			" this.header = titletext[0];\n",
			"}\n",
			"\n",
			"\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_canvas = function() {\n",
			" var fig = this;\n",
			"\n",
			" var canvas_div = $('<div/>');\n",
			"\n",
			" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
			"\n",
			" function canvas_keyboard_event(event) {\n",
			" return fig.key_event(event, event['data']);\n",
			" }\n",
			"\n",
			" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
			" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
			" this.canvas_div = canvas_div\n",
			" this._canvas_extra_style(canvas_div)\n",
			" this.root.append(canvas_div);\n",
			"\n",
			" var canvas = $('<canvas/>');\n",
			" canvas.addClass('mpl-canvas');\n",
			" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
			"\n",
			" this.canvas = canvas[0];\n",
			" this.context = canvas[0].getContext(\"2d\");\n",
			"\n",
			" var backingStore = this.context.backingStorePixelRatio \|\|\n",
			"\tthis.context.webkitBackingStorePixelRatio \|\|\n",
			"\tthis.context.mozBackingStorePixelRatio \|\|\n",
			"\tthis.context.msBackingStorePixelRatio \|\|\n",
			"\tthis.context.oBackingStorePixelRatio \|\|\n",
			"\tthis.context.backingStorePixelRatio \|\| 1;\n",
			"\n",
			" mpl.ratio = (window.devicePixelRatio \|\| 1) / backingStore;\n",
			"\n",
			" var rubberband = $('<canvas/>');\n",
			" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
			"\n",
			" var pass_mouse_events = true;\n",
			"\n",
			" canvas_div.resizable({\n",
			" start: function(event, ui) {\n",
			" pass_mouse_events = false;\n",
			" },\n",
			" resize: function(event, ui) {\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" stop: function(event, ui) {\n",
			" pass_mouse_events = true;\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" });\n",
			"\n",
			" function mouse_event_fn(event) {\n",
			" if (pass_mouse_events)\n",
			" return fig.mouse_event(event, event['data']);\n",
			" }\n",
			"\n",
			" rubberband.mousedown('button_press', mouse_event_fn);\n",
			" rubberband.mouseup('button_release', mouse_event_fn);\n",
			" // Throttle sequential mouse events to 1 every 20ms.\n",
			" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
			"\n",
			" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
			" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
			"\n",
			" canvas_div.on(\"wheel\", function (event) {\n",
			" event = event.originalEvent;\n",
			" event['data'] = 'scroll'\n",
			" if (event.deltaY < 0) {\n",
			" event.step = 1;\n",
			" } else {\n",
			" event.step = -1;\n",
			" }\n",
			" mouse_event_fn(event);\n",
			" });\n",
			"\n",
			" canvas_div.append(canvas);\n",
			" canvas_div.append(rubberband);\n",
			"\n",
			" this.rubberband = rubberband;\n",
			" this.rubberband_canvas = rubberband[0];\n",
			" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
			" this.rubberband_context.strokeStyle = \"#000000\";\n",
			"\n",
			" this._resize_canvas = function(width, height) {\n",
			" // Keep the size of the canvas, canvas container, and rubber band\n",
			" // canvas in synch.\n",
			" canvas_div.css('width', width)\n",
			" canvas_div.css('height', height)\n",
			"\n",
			" canvas.attr('width', width * mpl.ratio);\n",
			" canvas.attr('height', height * mpl.ratio);\n",
			" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
			"\n",
			" rubberband.attr('width', width);\n",
			" rubberband.attr('height', height);\n",
			" }\n",
			"\n",
			" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
			" // upon first draw.\n",
			" this._resize_canvas(600, 600);\n",
			"\n",
			" // Disable right mouse context menu.\n",
			" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
			" return false;\n",
			" });\n",
			"\n",
			" function set_focus () {\n",
			" canvas.focus();\n",
			" canvas_div.focus();\n",
			" }\n",
			"\n",
			" window.setTimeout(set_focus, 100);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items) {\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) {\n",
			" // put a spacer in here.\n",
			" continue;\n",
			" }\n",
			" var button = $('<button/>');\n",
			" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
			" 'ui-button-icon-only');\n",
			" button.attr('role', 'button');\n",
			" button.attr('aria-disabled', 'false');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			"\n",
			" var icon_img = $('<span/>');\n",
			" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
			" icon_img.addClass(image);\n",
			" icon_img.addClass('ui-corner-all');\n",
			"\n",
			" var tooltip_span = $('<span/>');\n",
			" tooltip_span.addClass('ui-button-text');\n",
			" tooltip_span.html(tooltip);\n",
			"\n",
			" button.append(icon_img);\n",
			" button.append(tooltip_span);\n",
			"\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" var fmt_picker_span = $('<span/>');\n",
			"\n",
			" var fmt_picker = $('<select/>');\n",
			" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
			" fmt_picker_span.append(fmt_picker);\n",
			" nav_element.append(fmt_picker_span);\n",
			" this.format_dropdown = fmt_picker[0];\n",
			"\n",
			" for (var ind in mpl.extensions) {\n",
			" var fmt = mpl.extensions[ind];\n",
			" var option = $(\n",
			" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
			" fmt_picker.append(option)\n",
			" }\n",
			"\n",
			" // Add hover states to the ui-buttons\n",
			" $( \".ui-button\" ).hover(\n",
			" function() { $(this).addClass(\"ui-state-hover\");},\n",
			" function() { $(this).removeClass(\"ui-state-hover\");}\n",
			" );\n",
			"\n",
			" var status_bar = $('<span class=\"mpl-message\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
			" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
			" // which will in turn request a refresh of the image.\n",
			" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_message = function(type, properties) {\n",
			" properties['type'] = type;\n",
			" properties['figure_id'] = this.id;\n",
			" this.ws.send(JSON.stringify(properties));\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_draw_message = function() {\n",
			" if (!this.waiting) {\n",
			" this.waiting = true;\n",
			" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
			" }\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" var format_dropdown = fig.format_dropdown;\n",
			" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
			" fig.ondownload(fig, format);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
			" var size = msg['size'];\n",
			" if (size[0] != fig.canvas.width \|\| size[1] != fig.canvas.height) {\n",
			" fig._resize_canvas(size[0], size[1]);\n",
			" fig.send_message(\"refresh\", {});\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
			" var x0 = msg['x0'] / mpl.ratio;\n",
			" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
			" var x1 = msg['x1'] / mpl.ratio;\n",
			" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
			" x0 = Math.floor(x0) + 0.5;\n",
			" y0 = Math.floor(y0) + 0.5;\n",
			" x1 = Math.floor(x1) + 0.5;\n",
			" y1 = Math.floor(y1) + 0.5;\n",
			" var min_x = Math.min(x0, x1);\n",
			" var min_y = Math.min(y0, y1);\n",
			" var width = Math.abs(x1 - x0);\n",
			" var height = Math.abs(y1 - y0);\n",
			"\n",
			" fig.rubberband_context.clearRect(\n",
			" 0, 0, fig.canvas.width, fig.canvas.height);\n",
			"\n",
			" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
			" // Updates the figure title.\n",
			" fig.header.textContent = msg['label'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
			" var cursor = msg['cursor'];\n",
			" switch(cursor)\n",
			" {\n",
			" case 0:\n",
			" cursor = 'pointer';\n",
			" break;\n",
			" case 1:\n",
			" cursor = 'default';\n",
			" break;\n",
			" case 2:\n",
			" cursor = 'crosshair';\n",
			" break;\n",
			" case 3:\n",
			" cursor = 'move';\n",
			" break;\n",
			" }\n",
			" fig.rubberband_canvas.style.cursor = cursor;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
			" fig.message.textContent = msg['message'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
			" // Request the server to send over a new figure.\n",
			" fig.send_draw_message();\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
			" fig.image_mode = msg['mode'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Called whenever the canvas gets updated.\n",
			" this.send_message(\"ack\", {});\n",
			"}\n",
			"\n",
			"// A function to construct a web socket function for onmessage handling.\n",
			"// Called in the figure constructor.\n",
			"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
			" return function socket_on_message(evt) {\n",
			" if (evt.data instanceof Blob) {\n",
			" /* FIXME: We get \"Resource interpreted as Image but\n",
			" * transferred with MIME type text/plain:\" errors on\n",
			" * Chrome. But how to set the MIME type? It doesn't seem\n",
			" * to be part of the websocket stream */\n",
			" evt.data.type = \"image/png\";\n",
			"\n",
			" /* Free the memory for the previous frames */\n",
			" if (fig.imageObj.src) {\n",
			" (window.URL \|\| window.webkitURL).revokeObjectURL(\n",
			" fig.imageObj.src);\n",
			" }\n",
			"\n",
			" fig.imageObj.src = (window.URL \|\| window.webkitURL).createObjectURL(\n",
			" evt.data);\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
			" fig.imageObj.src = evt.data;\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			"\n",
			" var msg = JSON.parse(evt.data);\n",
			" var msg_type = msg['type'];\n",
			"\n",
			" // Call the \"handle_{type}\" callback, which takes\n",
			" // the figure and JSON message as its only arguments.\n",
			" try {\n",
			" var callback = fig[\"handle_\" + msg_type];\n",
			" } catch (e) {\n",
			" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
			" return;\n",
			" }\n",
			"\n",
			" if (callback) {\n",
			" try {\n",
			" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
			" callback(fig, msg);\n",
			" } catch (e) {\n",
			" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
			" }\n",
			" }\n",
			" };\n",
			"}\n",
			"\n",
			"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
			"mpl.findpos = function(e) {\n",
			" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
			" var targ;\n",
			" if (!e)\n",
			" e = window.event;\n",
			" if (e.target)\n",
			" targ = e.target;\n",
			" else if (e.srcElement)\n",
			" targ = e.srcElement;\n",
			" if (targ.nodeType == 3) // defeat Safari bug\n",
			" targ = targ.parentNode;\n",
			"\n",
			" // jQuery normalizes the pageX and pageY\n",
			" // pageX,Y are the mouse positions relative to the document\n",
			" // offset() returns the position of the element relative to the document\n",
			" var x = e.pageX - $(targ).offset().left;\n",
			" var y = e.pageY - $(targ).offset().top;\n",
			"\n",
			" return {\"x\": x, \"y\": y};\n",
			"};\n",
			"\n",
			"/*\n",
			" * return a copy of an object with only non-object keys\n",
			" * we need this to avoid circular references\n",
			" * http://stackoverflow.com/a/24161582/3208463\n",
			" */\n",
			"function simpleKeys (original) {\n",
			" return Object.keys(original).reduce(function (obj, key) {\n",
			" if (typeof original[key] !== 'object')\n",
			" obj[key] = original[key]\n",
			" return obj;\n",
			" }, {});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.mouse_event = function(event, name) {\n",
			" var canvas_pos = mpl.findpos(event)\n",
			"\n",
			" if (name === 'button_press')\n",
			" {\n",
			" this.canvas.focus();\n",
			" this.canvas_div.focus();\n",
			" }\n",
			"\n",
			" var x = canvas_pos.x * mpl.ratio;\n",
			" var y = canvas_pos.y * mpl.ratio;\n",
			"\n",
			" this.send_message(name, {x: x, y: y, button: event.button,\n",
			" step: event.step,\n",
			" guiEvent: simpleKeys(event)});\n",
			"\n",
			" /* This prevents the web browser from automatically changing to\n",
			" * the text insertion cursor when the button is pressed. We want\n",
			" * to control all of the cursor setting manually through the\n",
			" * 'cursor' event from matplotlib */\n",
			" event.preventDefault();\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" // Handle any extra behaviour associated with a key event\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.key_event = function(event, name) {\n",
			"\n",
			" // Prevent repeat events\n",
			" if (name == 'key_press')\n",
			" {\n",
			" if (event.which === this._key)\n",
			" return;\n",
			" else\n",
			" this._key = event.which;\n",
			" }\n",
			" if (name == 'key_release')\n",
			" this._key = null;\n",
			"\n",
			" var value = '';\n",
			" if (event.ctrlKey && event.which != 17)\n",
			" value += \"ctrl+\";\n",
			" if (event.altKey && event.which != 18)\n",
			" value += \"alt+\";\n",
			" if (event.shiftKey && event.which != 16)\n",
			" value += \"shift+\";\n",
			"\n",
			" value += 'k';\n",
			" value += event.which.toString();\n",
			"\n",
			" this._key_event_extra(event, name);\n",
			"\n",
			" this.send_message(name, {key: value,\n",
			" guiEvent: simpleKeys(event)});\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
			" if (name == 'download') {\n",
			" this.handle_save(this, null);\n",
			" } else {\n",
			" this.send_message(\"toolbar_button\", {name: name});\n",
			" }\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
			" this.message.textContent = tooltip;\n",
			"};\n",
			"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
			"\n",
			"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
			"\n",
			"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
			" // Create a \"websocket\"-like object which calls the given IPython comm\n",
			" // object with the appropriate methods. Currently this is a non binary\n",
			" // socket, so there is still some room for performance tuning.\n",
			" var ws = {};\n",
			"\n",
			" ws.close = function() {\n",
			" comm.close()\n",
			" };\n",
			" ws.send = function(m) {\n",
			" //console.log('sending', m);\n",
			" comm.send(m);\n",
			" };\n",
			" // Register the callback with on_msg.\n",
			" comm.on_msg(function(msg) {\n",
			" //console.log('receiving', msg['content']['data'], msg);\n",
			" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
			" ws.onmessage(msg['content']['data'])\n",
			" });\n",
			" return ws;\n",
			"}\n",
			"\n",
			"mpl.mpl_figure_comm = function(comm, msg) {\n",
			" // This is the function which gets called when the mpl process\n",
			" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
			"\n",
			" var id = msg.content.data.id;\n",
			" // Get hold of the div created by the display call when the Comm\n",
			" // socket was opened in Python.\n",
			" var element = $(\"#\" + id);\n",
			" var ws_proxy = comm_websocket_adapter(comm)\n",
			"\n",
			" function ondownload(figure, format) {\n",
			" window.open(figure.imageObj.src);\n",
			" }\n",
			"\n",
			" var fig = new mpl.figure(id, ws_proxy,\n",
			" ondownload,\n",
			" element.get(0));\n",
			"\n",
			" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
			" // web socket which is closed, not our websocket->open comm proxy.\n",
			" ws_proxy.onopen();\n",
			"\n",
			" fig.parent_element = element.get(0);\n",
			" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
			" if (!fig.cell_info) {\n",
			" console.error(\"Failed to find cell for figure\", id, fig);\n",
			" return;\n",
			" }\n",
			"\n",
			" var output_index = fig.cell_info[2]\n",
			" var cell = fig.cell_info[0];\n",
			"\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
			" var width = fig.canvas.width/mpl.ratio\n",
			" fig.root.unbind('remove')\n",
			"\n",
			" // Update the output cell to use the data from the current canvas.\n",
			" fig.push_to_output();\n",
			" var dataURL = fig.canvas.toDataURL();\n",
			" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
			" // the notebook keyboard shortcuts fail.\n",
			" IPython.keyboard_manager.enable()\n",
			" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
			" fig.close_ws(fig, msg);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.close_ws = function(fig, msg){\n",
			" fig.send_message('closing', msg);\n",
			" // fig.ws.close()\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
			" // Turn the data on the canvas into data in the output cell.\n",
			" var width = this.canvas.width/mpl.ratio\n",
			" var dataURL = this.canvas.toDataURL();\n",
			" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Tell IPython that the notebook contents must change.\n",
			" IPython.notebook.set_dirty(true);\n",
			" this.send_message(\"ack\", {});\n",
			" var fig = this;\n",
			" // Wait a second, then push the new image to the DOM so\n",
			" // that it is saved nicely (might be nice to debounce this).\n",
			" setTimeout(function () { fig.push_to_output() }, 1000);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items){\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) { continue; };\n",
			"\n",
			" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" // Add the status bar.\n",
			" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"\n",
			" // Add the close button to the window.\n",
			" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
			" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
			" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
			" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
			" buttongrp.append(button);\n",
			" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
			" titlebar.prepend(buttongrp);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(el){\n",
			" var fig = this\n",
			" el.on(\"remove\", function(){\n",
			"\tfig.close_ws(fig, {});\n",
			" });\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(el){\n",
			" // this is important to make the div 'focusable\n",
			" el.attr('tabindex', 0)\n",
			" // reach out to IPython and tell the keyboard manager to turn it's self\n",
			" // off when our div gets focus\n",
			"\n",
			" // location in version 3\n",
			" if (IPython.notebook.keyboard_manager) {\n",
			" IPython.notebook.keyboard_manager.register_events(el);\n",
			" }\n",
			" else {\n",
			" // location in version 2\n",
			" IPython.keyboard_manager.register_events(el);\n",
			" }\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" var manager = IPython.notebook.keyboard_manager;\n",
			" if (!manager)\n",
			" manager = IPython.keyboard_manager;\n",
			"\n",
			" // Check for shift+enter\n",
			" if (event.shiftKey && event.which == 13) {\n",
			" this.canvas_div.blur();\n",
			" event.shiftKey = false;\n",
			" // Send a \"J\" for go to next cell\n",
			" event.which = 74;\n",
			" event.keyCode = 74;\n",
			" manager.command_mode();\n",
			" manager.handle_keydown(event);\n",
			" }\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" fig.ondownload(fig, null);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.find_output_cell = function(html_output) {\n",
			" // Return the cell and output element which can be found uniquely in the notebook.\n",
			" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
			" // IPython event is triggered only after the cells have been serialised, which for\n",
			" // our purposes (turning an active figure into a static one), is too late.\n",
			" var cells = IPython.notebook.get_cells();\n",
			" var ncells = cells.length;\n",
			" for (var i=0; i<ncells; i++) {\n",
			" var cell = cells[i];\n",
			" if (cell.cell_type === 'code'){\n",
			" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
			" var data = cell.output_area.outputs[j];\n",
			" if (data.data) {\n",
			" // IPython >= 3 moved mimebundle to data attribute of output\n",
			" data = data.data;\n",
			" }\n",
			" if (data['text/html'] == html_output) {\n",
			" return [cell, data, j];\n",
			" }\n",
			" }\n",
			" }\n",
			" }\n",
			"}\n",
			"\n",
			"// Register the function which deals with the matplotlib target/channel.\n",
			"// The kernel may be null if the page has been refreshed.\n",
			"if (IPython.notebook.kernel != null) {\n",
			" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
			"}\n"
			],
			"text/plain": [
			"<IPython.core.display.Javascript object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/html": [
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jTL1BHCiy4X9YPs7AVjv7iP7KoC/uidTB9XrFftLtc32IAC/cvzufUaB8nnJe68fgNZuJDzbfDOADQUF8YCdb7t+xL7ycJ1p7nuH74v6Ih2w3QPQ713Dei9034FsJ+vlPcf3+C8s9vq0mZj7fXThaeKMwOaKAW79wX/Pd+3JU7QLn+X0wa+771PzrueJ2v8C8DP3XRCEyJaP93qbd27cdi/l0+Z3bzttr2G+Uu9CHvTG5+Ex7v3JdzKfJYx65juZfstnRLFUiXFLsXdCmLFA4YntQeObU9z3/H4AdnUZ8Pn6JwD3RbwHbJTj1aD3HMfC3MeWY77e7jOX+yX/DQD3uLUdg7CtFwDg+JzPGb4v6Q98p3HMyH3CmWzuNZvnjNfPqDfwvcz/uIcx7dLGfae+4b5TaZttYW4I5RUBESiPgATA8rjpKhFIEwGKZZy4MXHAQEEjilQ4AOAghJOpPgGFc8LEiQ0jEoPSJ1whhCJEqcRBCsU8CoKlEvf+Yts4ePJLnGRRNLm2ggJgFHzYdj63OcH6nivM+PWHggIHedz3kWIA0z2uaFCKlc3vVwL4HwBti2SmIEGmFJ0LU5hBf6lJT1ATCgexFCp5Mm5hm9/yEQApdvBgkk+VgMHlpRR0bMQWCo83AaDAFJR4j/wawKU+AkM1BEAOzB8scg8XtpuCaOGAvRoCIPcopV9zoleYmiMA8nlCu3NiUirRb1g/xZlSiWIKJ99f8hywFHQND2ei2ByUuH8r98ks5kcUlsiHz9swH0mC6rzY9d3aUh11T6NmP/kBojDFJQDy+c+JcvuA9vMdwnudHzCYuBcpn10Uvv0S3318pxaKhiavrcBVKAByck4xMsj/yJSib7Hnjc3EvFAA5EcQfjhiu/0SuZCPeddSIOdknX7tl/j+4YepoFPIbfl4y7YRJQrzVNvuFreHkyVqAZD+Qr+hIFvsHuUWMJcD+E2RhlZiXFctAfASV+Q7uUj/nnDHjVEcNBb1eLVQAOSYheMBc4iVX7f4MZIfKksdAsaPefxwxQ9aQYnPSH704H3Ljx5MhR/IzLU2zxmTlx+MOP4M+tBq8r3v2iboI6jt/aV8IiACJQhIAJSLiED2CVD04ASOiYMenrLKr4fNTd4BAAcNjBKgcMcIqRfdCSDFQH695JdHJgptHJQzWsQvcXLzuPsDy2E7GYXAKBNO3hjFwa+gLd08jJ5ilKBfJJIpfyQAttUrKnIC9bYbBXKwZ1BETr/yNCzoGWkzGakEHzaNIhJFDpMY+ce6GGnJr6qceDEyZ4U7KaCoyRSVAMjJA0UIb/2MOuJp0hQuWL+XNScm3vbyOk4g+R8TJ5bmgBp+gWaUjTcx0vM/Af5S7M9eG3HSw8NGmPjFmwdBMDKCgjCj8Ch8mUSG/N07UOY+mGzDZvfEXQ78vf2n3xY7XIKC3o2ea1gOI5zmutGtZMZ2mMSB+ucLxGjWyegOJt4DvI+ZJrhf8L0sGC3E/8IkRhvxfqPvMFGwZtm8tyh0MFqAE3dGVTAijikOAZARu2sAfMblw3uZEwbeq/u4E0C2jZHDTGd7+sQIED4zvIn7J/JeYaIAc5v7//ncYbn0a/afPs0IGz5vzHOBeTip8RO7TB30sWfciAvzt1Wuv/CeJUNG0/I5Ra70yyBhhVHU3/E0nu3ms5Q+TRGAbeFkyyROdilU8bnbnEQR//tuAYwmes+N3KDIz7Zycrm3pwJG2/C5Sj/3JkaW8u+83424zvvdRJ5483ISyndXOcl77zPqm88sinksk9EubDc5mXuIdTCilRNpRsj/xK2UwhiFXorcvOe8feRkmf7il2wFLq8AyA8d5mMNJ8L0a76vyWqMx+foj/RD+pBfspmYewVAfsjhe49RpBQR+FyiX1EA4HOJ/snE08Z5T9HHGAHMv9P/+dzj/ciI5sM9oimj/Q8IiOix5ePtn807N2672/oqxWVGUJZKzHOaJxM/AvE97k18LjO6jz5iEjnw2U3hlvfnoW7Eu/mde8gaHy9sQyXGLcUEQDMW4FiR0WFMfJ7xHViY+Jy9qoCHuWcYjc+VEHyu8KPHK+7+1fzgR7/kM9Ykfozhx5HmpqjHq4UCID8u0eZ8fnP8wWcln2N8hjKCzySOmc14yq9PHDeTB+9xkzj+5XOaZfOe5nud6eduFHBUAuARAB7xjBn4LOWzjc842onPAs4JzByB7z+Ox/iOURIBEagQAQmAFQKrYkUgQQQ4iOcE1CQOohhBxkgXfqkvN3kHipzoUZSj0EIBzRsVRGGBYgQn50wUiygK+iWKHPx6+0CR5cKMzuIgxYghnDxyyYtf4jIvRi3s5f7IZUyMgCwUICkS/M6dZPEak6ISAKPiw8Etl4qaxCgMTnA5ATOJQgW/GnPgyHpNNEkUAiAjexhJaRInkvzq7q2fIgZPqOVk3yRGIzLCxC9Vag9A72SQ/siB7rfcpS7eiTf5eIUK75J5Cj9cFse9M72JS07JgUvlmOhXFBT8JuUczFIQN5EZHKxzss9IL5PYBh7mYU5D5t8Z4Umx1y+FjbILKGaHP3vFJbaXE0+/5WK8zznZZLQJ924sXAoZtm1hlwDTlmwDJzBfcf/X25FCe9oIB+Z6LnumyMNluEEfFRgRQZGQYhHTXZ5DbAo5s518TprJOQUd2pjPmsJlW3zusExGivpFNvLvrIuJH0T4rOWyrcIIP064OBnmc5eJwp0Rv238wC8P6+YHGE7Kg94Z9H+2j/cGE4Ulc1BNYZmV3JqAdXltznubjNgH2tWb+C7gM9Tcm/xQwXcL701G9lIM86b/dpfh8m98nvAjAesqTLYCl/c5xHbyOcp3EYVbbyqcRFMEMR92CusOKwCadwTLY2Sp15/4zqbYZyJS+RGDzwX+m6Ih/dgrLrOdfH5SlGLi84Gie7l8vNfZ3Mdx292nq2X/iQIrRWk+H5ko/lD4KdwegO91+gwTBSMKWxQEvYn+zfcYx2Z8PvKZTVHM70NsJcZ1Nu8Em/dAIUzvc8T4Md+vfDd5n1N8DvMDNT/EMfG+47vb794NY7Cox6teBqY/FHJpX++HUY5Lef/x46pJ3PKCH8cKE/PSprw3mTj+53uz0Ec4Jue4myIh301mHNycCEA+Jygy8qMqE1cgcVzDDwfexDE9x4wcJzLx3c6PB8W2WQhjJ+UVAREoICABUC4hAvkg8G93Ty9vbzkI+sCNiOAXudfcvc1s9+DwDhRZLvdX4oTAL3EiwWgKPnNYL7/2MvqlOckr1FDg8/tiyIGgaROjPjioKIwwM22gYMVoM2+KSgCMig9tZKLPONBlFJRfdA/bzck6l0qa1FwBkF+eKYpwQMjEpaKcQHsnsaauwvoZQccIEb+2VkMAZLtoX072i6VCsZx8Hwu4gJN8Dm7NUsygSTlFBDP45ld41hG0LNMbrUsxoK9PxBqbYzOhCntv8RnAKDQmRvoUi6otVnbYttlM/Lx5WDejoBh1VmrZE/PaCAdhWXFyTl4UvfhcYZSfWT7qLes8z5YHfK5ykkVxNWxiVCajRRnNw3uIHzz4ISUoMTqEHz4YVcEJH6Nfgparhm1Lsfy8F/h85cSPz3eKkH6TuGoKgHw+cSmd98OJtw/eQ7L4d4q0vA+CIlAoiJkPTkHiarkCIKMM+Z70S4y6Nks3yZhRgH4prADIMijUUrD1SxQLKCh7U7FtGbwnlAdFJtny8dZpcx9788Rh9yjvJY5bOH5hYkQm3/uFz2SKeEb0oeBF/ym2xx+FJBNBSJHZ7A3tbXclxnU27wSb90Ah38JtMfhs5TPWbwzLMQmj6EzU7xXuh/AobVasLJvxauF7jhHLjDjnKg+/xDGYEc2Cohq9UYp8d3AsErRagR9vOMb0LiNvjgDID0L88MLESE3z//36wvElRUnzbOWHBu/H5mrZSfWIQC4ISADMhZnVSRFwlq/xS7xfZIkXDyNLuGcglzcVm2DyGu9AkV/svEvP/JBz8MUBKhOj/LgsoDnJG43Gr6GMeitM3joZvcComWKJAyMulzEpKgEwCj6MTPIeosJJPgXcoMRJFoU3s49VcwVA70CSAhaXiFCICUoUeRmRYJaQ8frCr868thoCIJf9eZftBrWZkX5mj0yK5l4B1e8a+hOjaZkoeLDPXkGUk3TvfjYczBfbs5KRM5zE8uANJi4x5L1YmGwmVCVcfaef6Utm2SyFplIHUQSVH7ZtNhO/wokRo17NUt1S/bQRDkqVUcr2Qc8zikhmeTv9hJPOchKjbE20R6mJlCmffMwSVS4nf7icisu45ree5XV8J/DZV5iqKQDyUAqztNCvOxQMvEuQ/bYs8F7njcRkVLOZgHvz2Apc3mcF319mqw6/dpptHRjNxOt4j3ojr801YQVAbrVBgbhwubYpjyIyI5tNRBA/evBDWlBiZBXfO0wUn82zrBw+3mts7mNvnjjsXsbt4nsJl/kzIpuJ0VgUsGnXwsSPfMa3g6ItC6/h+4jvJfoQI68KP6JUYlxn806weQ8Ue47wNwpYPFAiKDE6ks8nJj4P+VysVrIZrxa+50o9tyngmq0+uBeg+YDn7ZNXJOSqHwr6xdLd7goFk6dcAZCRhFwZwYhTjiX4Mahw+43CdnCMRgGSifODYns5VstuqkcEMklAAmAmzapOiUAgAQ4YuMyJS0mDNjg3F/MFzEGlX2QL83gHitxHi0sYiyV+oWSUIBP3DCy2ETXzcMkZl7ww0oeDCU6AvF8mvXvGcNDCJS7eRNGTAw/TT5ZT6hRibrbsFVyiEgCj4OONALEVtBgdwCgBpuYKgFxGaJao/tNCTGad3sjTIAGkGgIgl+6ZCVUxH+XSP06KmDix4iSyWKJfUgQ1PsaJlTfClEIVl7YwlZo4m3q4TIv3BxO/gHv3gDJ5bCZUJZq+088UQczS/OZER4Rtm83Ez5uHE1eKCmbfvlL9tBEO/MqgwMLnD4V37sXF54n3mendx87v/qZA7l1ixglQ4dKnUm03v1M4pwjAxP9lFFqp5J1w0vd5D0SReH+QC32dp4xStPY+J737UzLiqDCqmm2opgDIrSIKI9i8HHgPUwQziftRFdvPk/0ze5IGTbrLEQAZmVMqOpTPFrP3V9D7LKwAWGwJu2HCvUHNNho8IIVLhYsls2cv83BLiMKJvy0fbx0297E3Txx2j+L+4ocyfoQ1Yx2OSfwOTqMQTGGW9x8j3sjZ5mALr0DPD1x8R3tTJcZ1Nu8Em/dAIV/vc4R7kxY74ILX8rlllj1TKDTbFURht+aOV9kGLwNGljOiutghTibSmtcGie18tpm9/7hPoNljO6jPhR9EyhUAT3e3GWI9NsIj8/E9wmcFfZrzDu++yFHYSGWIgAi4BCQAyhVEIJ8EOCDgYIPRbvxqyC/6fifvcuDPPcz8vtx5B4qMLKQoVCxx0sDTY5mKTSL40ud+RN7N+0tZyS9ai/tuveReyPZzMOW3XNVbNidV3iVYUQmAUfDxLlUrFS1i+sSoR7PvTXMFQO/SN0a+eQ+1CLIPl8iZU4B5vRExvPmrIQAG7Y/jbQcFZa9AQ6GDG9+XSt4oL35d52DXJK/NOPHyHp4SVC4jEM2eg1wCxKXThclmQlWq3YW/U5ynSG8SBUEumabdwghXYdtmM/Hz5mFUqdl70aaPNsKBtxwuu6bPMrLL5jRgXkvRllF63mRjR5v2Mw8jvczhLBTU/CK/CstiP0wEK/e++6JtZQH5KABRxOdHJJvTgFlMkPBeTQGQ7zaK70GJQop3P0aKmkEHbLAMbqhvTrflkkwTNest31bg8r6PStXL8r0R6kFCZVgBkB8EvXuJ+XHie9TsY2nzLuPzgs9TJvph4b6Rtny8bbG5j7154rB7M28xR2SlQGUOWSom3DOa3ES7cYlo4eEgQW1hlJURvrgnrvlAZfJXYlxn806weQ8U9sn7HCkV8clrea+aVRNB925YG0Y1XmW9XgY8fKjUqblcXWEEQorAZrWF6UPhmIYfskp9OON7hh/Ozdi3XAHQ+yHT76CyIM60qczl/nsAACAASURBVNlDlHMSfkxQEgERiJiABMCIgao4EUgpAU6C+HWUe/tQeDOn7LI7QWKTd6DIr4allgzbDAIZNcOoNe+JbTZI/Q4WYQSXOUmOy168JzgGlUmR0Dv5i0oAjIIPBVYzobcV4LxLB5srAHISbU6Ko7jBDZ1LJa8IwqWvnLQUpmoIgEF7RHrbwsG2WZ7LSAp+0bdJ/KLOqA0m8vaeIu21me1hDN5lMEFfwW3uJZu2e/NQ1KFQ5LdckvvPMTqJ9xknWsX23gvbNpuJnzePbfSr6ZuNcGDyUjSg8EkxJkzyW5bL5ZzmFFtG8BkfCVMu83ISVGrpVKkyix2UVOpa/s7DSWh3W0HUlBm0L2Y1BUCKxRSNiyWvEMcoz2IfimzEK5s8bE+YepnfRtyzyeN95nJJszlJNYhR2Hd9qXvOlo+3PaXKZF5vnjjsbnMvBeWhOMNnm/m4waWdPJQo6ARv7k/b3G1U/A7qCWtrm+e9TR6b90AhO+9zhFvccMVKsVSO3xUrL8rxKuvxMuA4mB8uSyXvM6RwvOod03APWCOslSrTnB7NfOUKgBxLNHeJdXOi5kv1Ub+LQK4JSADMtfnVeRHwJcCoQE5YTUQglyLwK2fh8hKbiYa3AptBoDfSgJNennLJtvCrLZcysA1mQFxqwOg91IMb9pvNn4uZvTAaJCoBkAc/+O3hE4YPN7Hn0m0mvy/3fv3ismgyZGquAMgv5maJTbHDMbzt8E5Sgr64V0MADBrEetvKiBqzBI8Cl1k2U+ox4R3oFka2lmMzHphj9k3z+6rP9tjcS6Xa7fc7/Z2CACO3zJK/wnyMlqIvUdD0iyYI27ZS9zHrt8kT1F8b4YDXUtxiNKc55IbRn9wOgOIZfZd95fPHTLhKiVjewxCC9oqzsVFhFIfNNYV5eBCNOU007PW8DxjxZg67meNGivJe4bI7fjDhO8JwsbF/KXZh21iY39bm5rpik+jCsm1EBJs8LDdMvcxv8861yRP2mWtTppdTKf62fMKUybyl6i20ZRj+5bTZ1o8ZucVIayP4FFt5Ycr0O5zFtj6T7xr3XeK9Lqytbe53mzzlPOPDPkeitmGU49Vy33PFfLjcMQ337mPkLlO5AqB3xUhYvzT5bcZt5Zat60Qg1wQkAOba/Oq8CAQS+AGAn3h+9VtCGfVAkcKj2XuJS1oYCeU9QKGwsfw6bvav8ZvgJikCMAoBsJwIQG8UUnMFwDRHANoMJPMeAVh4f3GvMe5LxqV/3EeycNktN/rn9gCFy6RtJnveurx7DgUJVeVMDk0dtqLAGZ5TorlkkR8Mip1Uzn0aTbSn370VVQQg9yL07sPanANaynnlcdsGs+cbl6XRJ4otQf6FZ79BP4GBbQg7cQ/bblubm3KjFoJshYYw9bKtNu9cmzxpFAAZhcyIoGKiRNx2D+unJj8/0pk9jPnxiftMlopa9Y5vbPeXtWmfjf94y7F53tvkKecZH/Y5Yntf2nCKerzKOsthUIkIQH7sMlHw5QqA3vEqD7Ux0fA2bJVHBESgwgQkAFYYsIoXgZQS4FI4bnBuEg8i4IEE3hT1QJHLUbj3HxP3pWGUW7HE383Jv37CgXcPQE5YOXEutQegN/qKdScpAtA7SfDbc8yPlffgjuYKgN4vujwM5OcWvp2UPQBtBMDCSCtGPhVb6mq6b7sHoI1Ps0ybveNsJlQW5gmVhXsRcp9ALnM2e8D59ckb+UbhiFGRxRL3FDMn1MYpAPIwBEY/Mtn4N/3/e25+v3vLa0dGMJvDG0JBdzMzws4sv6U4wD2VqpW8h8NwH0FGvBZL3ohYCYAAIyYpPPilvAqA3mctxXYTbVTMr7gvmdkbL+h5nkYBkNHWFM2ZuJ8bo/zN3sXFePDjyytuBq6WoGBTH8FDIepxHZtk874qR/yKUwCMerxKTuUwKPYM4X3FaD6TuJIn6FA/k4crfzhebu4egIye5wE2TLb7H0fgvipCBETAhoAEQBtKyiMC+SPAEx690Xd+G39HPVC8DcAFLmr+r/c0Xj8LcA86s7G9n3BQeAowxT0urSmWvg7gd54MSRIAvYInT6Hkno2lktdGzRUAvWIi91Y8tVTl7r5hJ7v54jwF2EYAZDO9pwD7nZBY2GWeRstrbE4BDtoDsbBMfiln9BhTNU8BtjCnk8Ur8HFyUbhfpzcyjoeKXFiiYJ6gS6GIKU4B0LuXI/fr49YDxRL36zLbCvjdW1GeAuw9zdtv3y5b25WTzytw8+Tj94sUQmGYB0DwdEqmIAGQe3UxCo2puc8lv+bELQTZRhrlVQDkQQMmipR7k/FdXezjHJ8xFFJNyooAyFNZuY+feX9wD2ZzX5S6V9u5Yo75MMAobRvhsFS5UY/rWJ+NAMhVJmabFNstC+IUAKMer5JT1AIgy2SEPscpTDzA6YkSDuBtA7OWGwHIj2n8qMYU1YErpXxXv4uACFgSkABoCUrZRCBnBBjx94Cnzzwp2BsRyJ+iHigymugit86g0yNNk3q7+0+ZwW/QgJFCGSNmmIIEKK9pua8V900xKUkCoDc6kZMlRmRxYBWUOGniMiIzuWjuRJuiCEUSps2u8MN9GYMSbcSJuDmZjgcJjPfJHHY5mu2tGFYEYLk8fZeRW0w2IidPWDanIS90I1m8E1kKJhRQTOIyYy6jDEo8eIQ24wnETIy48wrS5jqbCZUtp7D5vCdlM2Kl8GAI79L819xlwsXqeMdzQE+cAuBjADghZ6K4bQ4Q8ms7n4fcV9SkoHuLH1H4MYWJJwtza4VyEg/94fOLiX7GvTgZFViNxI8mZj9IHuJjDsrxq5ubvnsjBIMEQG90JE/N5n5mUaaw934YIc5G3LPJw/6GqZf5bd65NnnCPnNtyvTaz4b/cndvYV5XSlj2PmeZPwsCIA8lYwSfiWrkBzZGzIdJPCiEog6TzfvKpuywtrZ5F9nk8R5+RS7m1OlibY5TAKzEeLUSAqA3IvvPAM4q4QTelSbF7rVSfsIoXz4HzIGCNh9UbfxTeURABCIgIAEwAogqQgQSTuC7AKa4m9nbNJUiBCfunOgzMcKJYk7haXSlBgCFdZUaBHI5nVlWyrK5b55fYpQJT6Q80fNjkHDAJQgmkpAb+FOA4XI8v1QoejJPkgRAtscbdUTBgmJLUOQEDx7wRuk1VwCkkEjB0RySQIGY+6b5JXLjwNPUz/3iKFj6nWgYdjJq48PMYzMJLSyLPveM54/Fvpgzwot7L3FpOVPQiaf0Te6bxkSBmUu8eJCGX7oJAO9XJkbIcBDN/TALU6l7yZaRNx+jBGyWPFMko+8xMdrL7MtlymL0F0Uq+gB9kxNdrwjqrZOCPydSJsUpAHI7AbPtAH2S0Th+ic9H2tF7onXQvXUegN+7hdDmtL05aCaMjXgAB/3Z+BpPvOTkt9SWBqyDduWyr3KXBzJCiYf5MNHvTLRmYfu5ZP6NAn8IEgCPcQ89YBm20T5heIW998MIcTbink0e9idMvcxv8861yRP2mWtTptc+Nvy94lUxcZzLGPnRhMsXTUq7AMh7ku9y8y7lXsZcZRF04m+Q73uj5piHKxjMoV+l7hc+pxf7ZApra5t3kU2eoe5hQ2xSsWXz3ibHKQBWYrxaCQHQ+76mf1FY5fjeL/Gdxo/mRrRjnnIjAHktTxenjZi4ny5FXu+S5CAf5ViTp2IX7i9cyqf1uwiIgCUBCYCWoJRNBFJMwEQ1MWKFL2QKQxT1/BJf0L8BcJDnx6BovKgHiowCYMSMeS5xXxwud/OePsxBK5cV8mviegAd3HYGTSIZnUSRhmUzcSPxL7mDHG//GYHCgTMHHq09PyRNADyuYGniva5o4d2Un8upbnY3FWeknonQaq4ASCxk590LkswoWHlFKi7vopjCZX4mfcH1Oz+fCzsZtb0VbSahfmV5J6bsF5eyPFiQkRFgvK84aWHioHZf90TUwjK5VxNFH7NvHgUVCkPe6En6HMWSKzwXc4JBQdAv2UyobDmZfFyKR39iRBbb6zcZ5XOB9jcHglDcMvv8eOvznn7MyTsFJIqFJnGCwb0EGdXGk45LRfKWMzEyddn6gffeojDDfQB5H3mFM9qb/spJlPf5E3RvsZ98NnHDeCYyZrnkVigC0wcYJUt/oxhQmLyTXf7GpVx8NvuJq3xucYsAPtcoZO4aICTb+Ij3IwqfJ/RdRpJ4EyeO/BujHb1cggRAPsfNASuMZOT+iHw2R5VsbW7qCyPE2Yh7NnlYd5h6md/mnWuTJ+wz16ZMr+1s+J/pPm94HSOJ+TGJYxNvog/f54oQ3hPR0ywAMiKez0fzUYgfZ/k88fvQY3M/eG1Jf/olgOsDPubwOctIfj5L+HHJrI7w1hPW1jbvIps8HHtxL0N+YGGy2es0TgGwEuPVct5zpZ4hfBdwCwmzsoUf+U53fdBrd9bNMQ1XH/DdZMbBzREAd3M/CvF/mSg4c3sT3ud+4wv6JMeK33QP2OJcREkERKACBCQAVgCqihSBhBHwLms0TWNEFpd2cTDAgTWjNxgdZ75Im3xcVkLRh3kKUyUGipxIn+2piJNEbnhPsYSTKg6aOTDhQJETaYqBTMWiSLhP17MesZD5+fWdSw9ZFicZRsjh4MSc7Ml8SRMA2SbvHnH8NycOjFoz+9cxio3Lihj1QwHDROxQ/DWHHDTHRTko4wDNJNqCfE39jHKiCGkS22Ci2vzqDTsZtW27zSTUryyKJTyNmsssTZruisacqHI5JIVy4xsUPCjcmBOs/cosXMJGIYXMKBxy83bajF+8TeJ9x+WUQRFeNhMqW04mn7cu2pTCOSMx2D9GrHDCw2g+k/h1ns8MRvsVJvLhMi6z/JwiPg+TYF5G8vA+5kSDvstlscUO82HZ5UyMTJvC+IH3mcbruRybWx/wAIJhrpBHIZcHF/A+5LI9pmLiOiOYeH/yepNWuf7C5xtFQkaTUlTmfcu6TKRfIVceksSPIl6b8Tn+thsxyg8inETxECdvGRTlyxUYKBpQpGAEr0kUHSnsUrzj1gTmgxH/xr0TuWSZKUgA5G+8X4wwSh4UNMnDTAz5juI+W+WkMDZn+aUm0d422Ih7NnnC1sv8Nu9cmzxhn7k2ZXoZ2fCn3/Oj5H6eC3mv8bnDe4wfVOjHTHzeUcjmfcKUZgGwMGqP0X82UVHsNz/QMELLm3h/sgx+wDCJ7ymOm3gP8dnLCGK+z7iqo62bidG63g+95tqwtrZ5F9nkYf0Ue82qAn4s4TOBHwbMRxieTvsTTz/jFADZjKjHq+W852yeXXz3vFowxuAz3WznwHuQ73ImrsLh3trmXuP/+n2csfUTjr/5UdXsQ8g6OHZgFKLZP5ljH75H+GHRjKu4l7AEwIKbXf8UgagISACMiqTKEYHkEuCyEE6yC8W9Yi3moJFfkfmfn/jHa20HAKYem0Egv/5S/PAOZgvbyUgiLtfll3SKKEyllpFRcGDkktmcvrBMTjqvcycaNgMqmwlOJfiw3XxuMzryO0UESgotFJA44Dd7yFGw4DVRJJ7syv8K93/zlk1xgIIFfahYCjsZtW2/jY2CyqIIyEi4T5aojEuiOWGxOZX1XDeiz+z55Fc0Jzoc9DL6r9iSTZt7yZaTyUfRzyvcFrueQg/vwWlFMlFspu+ZyMfCrBR7uBccfy91H5czMTL1hfED2p2TFe/y3sJ2M0qZEyRGqFBUZyoVXUvRk9GyfpF9heWXOhWVH2QY5cNtGWwSP3bw+UfRudxE8Y/7f5rIT79yKOjRnnzfcDk8UzEBkOIDhVGKk36p1DO9WF/C2Jzl2DzzTX024p5NnrD1Mr/NO8UmT9hnrk2ZXnvY8ueYhNFwQX5Fu1DwoehNMT4LAmDhIQth7smgQ0L4DOU9x/eGiaArVi4jvPhsNlseePOGtbXNu8gmD9tA+1IYChqnFS4NjlsAjHq8Ws57zvbZRZGPY+ti8wDjE7x/zfuFHyj5gaYwhfET2pUHgvDjsE2iMMgVJKUO4rIpS3lEQAR8CEgAlFuIQH4I8Asbvz4z4o3RPHwp88swnwOc/DM8n18FORnnkkdGkBVLYQYALMd2EMioIYoqHAAwAoCCCSMVZ7lLBzh5YdvCDpYYEcPINe5Lx6/hFBAplHF5BPcJ5ETZdlJmM8GpFB9jE0ZZ8bRkcuASC0b4cJLE5RVcYshN1rmpOPdXYio2GS/nLqD/cDkgo984qCRfDhRpJw7cKHjYLOsLOxm1bauNjUqVxb5R6OLyGU5K6DOMRuWX83+6yx6D9vPzK5tfwSmQcG9BiioUhnjvMQKEE+G7C07fDmqf7b1Uqn/e3xkNS6GIzwh+tWfUAAUxRowwGoPCO6NG6F+MOLHZr4rRklymSiGVPkpR2Pgo7zne1zb3sU2eoL6G9QOK2vRr2p3PTE7yaHOefsuPCIxSIY+wk0+2j1z5bGN/GBnIyRU/tpAtI58Y8cK9Mxl1WSyxjWwf/ZNlMoKb4i2vo4DICD0u46aYGbTnaRjfYF4+h83zk0t26S98ZzD6kGI53xn8WBTGNymUMdKDEbAUgdgHIxhLANzZQjbvFJs8YZ+5NmV6WxvmnmPUKn2A72U+E+nbfC/TfxkBaiLebMq0yeNtp614wmtsRd1S91UlBEBTJ58DXEHBPTb57OX7hu8sbhFC8Yz3Ksd3fC4E7a8W1tY297tNHtMHRoZTmORHYPoDPxCYPemSJgCyzVGOV8t5z4XxYb7LOGbkByyy5b/5IY5jX44ZGaXPxPcbT5nmO57+4/euD+snLJfbobBujjO4dzDff3xncKzKVRaMCOZBcSw7KPCg1P2l30VABCwISAC0gKQsIiACIpBSAt4lNRQMvPv3pbRLarYIiIAIiIAIiIAIiEDEBPjhz3w0YoS/OcU+4mpUnAiIQJwEJADGSV91i4AIiEDlCDCahpFFjPJkYtQjo/OUREAEREAEREAEREAERMBLgFu7cDscJu456d2TW6REQAQyQkACYEYMqW6IgAiIQAEBHmbCpVVMXEbFpd9KIiACIiACIiACIiACIuAlwK1cuL2J+WjMrUq4LYWSCIhAxghIAMyYQdUdERCBzBPg/jjcO4UHEDDCrzBxD50fu3vNmd+4vxI3gFYSAREQAREQAREQARHIDwHurXeTu9ew3/56J7oHw5jDP7gnLU+mt9nrNz8U1VMRyAgBCYAZMaS6IQIikBsCZkNtbv7ME0nfdQ9F4WENQ91DAbhBv0mlTijNDTh1VAREQAREQAREQARyRsAcFsID9Ca5B49tcQ+K4Yn2PJTKJB5MNsY9NCZnmNRdEcgHAQmA+bCzeikCIpAdAt4T9Yr1il95bwFwub7iZsf46okIiIAIiIAIiIAIhCDgPS242GU8jZcn9b4VomxlFQERSBkBCYApM5iaKwIikHsCHQBwucYxAPYFwCW/uwBgBOAK96CP5wDcDWBG7mkJgAiIgAiIgAiIgAjkl8DeAD4H4FAAA9wxYzcAmwAsA/A6gEcB/BWA3xLh/JJTz0UggwQkAGbQqOqSCIiACIiACIiACIiACIiACIiACIiACIiACBgCEgDlCyIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiKQYQISADNsXHVNBERABERABERABERABERABERABERABERABCQAygdEQAREQAREQAREQAREQAREQAREQAREQAREIMMEJABm2LjqmgiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAhIAJQPiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiECGCUgAzLBx1TUREAEREAEREAEREAEREAEREAEREAEREAERkAAoH4iLQBsAI9zKlwGoj6shqlcEREAEREAEREAEREAEREAEREAEMkygFkAPt39vA9ic4b6qawEEJADKNeIicBCACXFVrnpFQAREQAREQAREQAREQAREQAREIIcERgGYmMN+577LEgBz7wKxAZAAGBt6VSwCIiACIiACIiACIiACIiACIpBTAhIAc2p4CYA5NXwCuj0AwGy24/XXX8duu+2WgCYVb8LGjRvxwgsvOJmOOOIItGvXLvFtVgNFIIiA/Fm+kTUC8umsWTTf/ZE/59v+Wey9fDqLVs1vn9Loz4sWLcLo0aON0QYCmJNfC+a35xIA82v7uHveF8A8NmLevHno25f/THbig378+PFOI4877jgJgMk2l1pXgoD8WS6SNQLy6axZNN/9kT/n2/5Z7L18OotWzW+f0ujP8+fPR79+/YzR+H/m59eC+e25BMD82j7unksAjNsCqj/XBNI4cMm1wdT5kgTk0yURKUOKCMifU2QsNdWKgHzaCpMypYRAGv1ZAmBKnKvCzZQAWGHAKj6QgARAOYcIxEggjQOXGHGp6hQQkE+nwEhqojUB+bM1KmVMCQH5dEoMpWZaEUijP0sAtDJt5jNJAMy8iRPbQQmAiTWNGpYHAmkcuOTBLupj+QTk0+Wz05XJIyB/Tp5N1KLmEZBPN4+frk4WgTT6swTAZPlQXK2RABgXedUrAVA+IAIxEkjjwCVGXKo6BQTk0ykwkppoTUD+bI1KGVNCQD6dEkOpmVYE0ujPEgCtTJv5TBIAM2/ixHZQAmBiTaOG5YFAGgcuebCL+lg+Afl0+ex0ZfIIyJ+TZxO1qHkE5NPN46erk0Ugjf4sATBZPhRXayQAxkVe9UoAlA+IQIwE0jhwiRGXqk4BAfl0CoykJloTkD9bo1LGlBCQT6fEUGqmFYE0+rMEQCvTZj6TBMDMmzixHZQAmFjTqGF5IJDGgUse7KI+lk9APl0+O12ZPALy5+TZRC1qHgH5dPP46epkEUijP0sATJYPxdUaCYBxkVe9EgDlAyIQI4E0DlxixKWqU0BAPp0CI6mJ1gTkz9aolDElBOTTKTGUmmlFII3+LAHQyrSZzyQBMPMmTmwHJQAm1jRqWB4IpHHgkge7qI/lE5BPl89OVyaPgPw5eTZRi5pHQD7dPH66OlkE0ujPEgCT5UNxtUYCYFzkVa8EQPmACMRIII0DlxhxqeoUEJBPp8BIaqI1AfmzNSplTAkB+XRKDKVmWhFIoz9LALQybeYzSQDMvIkT28FIBMBNmzZh1apV2LBhA+rr6yva2YaGBixbtsypo0ePHqipqalofSpcBCpJIC5/rq2tRevWrdG5c2d07NhR91EljZyzstM4GM+ZidTdEATkzyFgKWsqCMinU2EmNdKSQBr9WQKgpXEznk0CYMYNnODuNUsAbGxsxKJFi7B69eqqdZF18mHP1K5dO7RoodunavBVUeQEkuDPvIf69OmDTp06Rd4/FZg/AmkcjOfPSuqxLQH5sy0p5UsLAfl0WiyldtoQSKM/SwC0sWz280jByL6Nk9rDZgmAH330UVM0nulgy5YtK97Xbdu2OXVUo66Kd0YV5J5AHP7MSF2KjyZJBMy9G0YGII2D8cg6r4IyR0D+nDmT5r5D8uncu0CmAKTRnyUAZsoFy+6MBMCy0enCZhIoWwDcsmULZs6c2VR9z5490aVLF3BpYSUTl0yuWbPGqYLLF7UEuJK0VXalCcTlzxT/uGR/xYoVWLdundNNioDDhw/XPVVpo2e8/DQOxjNuEnWvGQTkz82Ap0sTSUA+nUizqFFlEkijP0sALNPYGbtMAmDGDJqi7pQtAFI4WLJkidPV7t27gwJgNVJcgkk1+qY68kcgbn+mEMiBiBEBuRSYwrqSCJRLII2D8XL7quuyT0D+nH0b562H8um8WTzb/U2jP0sAzLZP2vZOAqAtKeWLmkDZAuC8efOaRINBgwahbdu2UbfNt7y4BZOqdFKV5IZAEvx5/fr1mDt3rsOc+wD27cvHgpIIlEcgjYPx8nqqq/JAQP6cByvnq4/y6XzZO+u9TaM/SwDMulfa9U8CoB0n5YqeQNkCIJf/chkwlw3uvvvuVTuMIwmCSfRmUIl5JZAEf2YU4Pvvv+/sCdimTRsMHjw4r+ZQvyMgkMbBeATdVhEZJSB/zqhhc9wt+XSOjZ/BrqfRnyUAZtARy+iSBMAyoOmSSAiULQBOnz4dPLyAB3EMGzYsksbYFJIEwcSmncojAjYEkuLPcd3PNoyUJ10E0jgYTxdhtbaaBOTP1aStuqpBQD5dDcqqo1oE0ujPEgCr5R3JrkcCYLLtk+XWSQDMsnXVt8QTkACYeBOpgSEJpHEwHrKLyp4jAvLnHBk7J12VT+fE0DnpZhr9WQJgTpyzRDclAMoP4iIgATAu8qpXBABIAJQbZI1AGgfjWbOB+hMdAflzdCxVUjIIyKeTYQe1IhoCafRnCYDR2D7tpUgATLsF09t+CYDptZ1angECEgAzYER1YQcCaRyMy4QiEERA/izfyBoB+XTWLJrv/qTRnyUA5ttnTe8lAMoP4iIgATAu8qpXBBQBKB/IIIE0DsYzaAZ1KSIC8ueIQKqYxBCQTyfGFGpIBATS6M8SACMwfAaKkACYASOmtAsSAFNqODU7GwQUAZgNO6oXHxNI42Bc9hOBIALyZ/lG1gjIp7Nm0Xz3J43+LAEw3z5rei8BUH4QFwEJgHGRD1nvc889h6OPPnqnq2pra9G5c2fU1dWhX79+GDlyJA477DCcdNJJaN26dclaBg4ciDlz5uyUj6c7s0ye8HzUUUfh/PPPB/NmKb3yyiv47W9/ixdffBFLlixBly5dsN9+++GrX/0qTj/99Kp0VQJgVTCrkioSSONgvIp4VFXKCMifU2YwNbckAfl0SUTKkCICafRnCYApcrAKNlUCYAXhquiiBCQApsRBggTAoOb36NEDF198Ma644gpQzAtKQQJgYf527drh9ttvx9lnn50SYsWbefXVV+O6665zDuHwSyeeeCL+/ve/o23bthXtrwTAiuJV4TEQSONgPAZMqjIlBOTPKTGUmmlNQD5tjUoZU0Agjf4sATAFjlWFJkoArAJkVeFLQAJgShzDKwBeeOGFuOiii5pavm7dOqxcAv0dSgAAIABJREFUuRJTpkzB008/jaeeegqNjY3O76NHj8ajjz4KCoJ+yQiAvXv3xrhx45qy8IU6Y8YM3HvvvXj88cedvzPakNFyhxxySEqo+TfzjjvuwAUXXOD8OGTIEFx55ZUYMWIEFi5ciFtuuQXPPvus8xujAO+///6K9lUCYEXxqvAYCKRxMB4DJlWZEgLy55QYSs20JiCftkaljCkgkEZ/lgCYAseqQhMlAFYBsqrwJSABMCWO4RUAr7rqKjCCLShNnToVZ555JiZPnuxkGTNmDJ555hnfJcFGABwwYABmz57tW+T3vvc93HTTTc5vjIyjoJjWRKF00KBBWL16Nfr374833ngDu+yyS1N36uvrccopp+CRRx5x/kYxkEugK5UkAFaKrMqNi0AaB+NxsVK9yScgf06+jdTCcATk0+F4KXeyCaTRnyUAJtunqtU6CYDVIq16CglIAEyJT4QRANklvhAp/BkRkALed7/73Z16ayMAbtiwAd26dcPmzZvRvn17rF27FjU1NSkht2Mzb7jhBnz/+993/vjAAw/gtNNO26kffDGTC8XAE044AY899ljF+ioBsGJoVXBMBNI4GI8JlapNAQH5cwqMpCaGIiCfDoVLmRNOII3+LAEw4U5VpeZJAKwSaFWzEwEJgClxirACILv17rvvOktbuRyYS3wZ4deqVasdemwjAPKCvfbaC++9955z7dKlSwOXFCcd56GHHopXX33VOThl2bJlgQelHH/88c6S6DZt2jj5OnXqVJGuSQCsCFYVGiOBNA7GY8SlqhNOQP6ccAOpeaEJyKdDI9MFCSaweMUaPP/cs2hbCxx33HHgnuVJTxIAk26h6rRPAmB1OKuWnQlIAEyJV5QjALJrY8eOxfjx451evvzyy6AA5k22AuD++++Pt956y7mUy2h5Ym7a0pYtW9ChQwds27bN4fLEE08EduH666939gZk4vJpvxOYo+i/BMAoKKqMJBHQ5DJJ1lBbmktA/txcgro+aQTk00mziNoTlsDdL32IF6cvw7TFa7Fo9SacNrgeh+zaKAEwLEjlj5WABMBY8ee6cgmAKTF/uQLgjTfeiMsvv9zp5U9/+tOm5a+m2zYCIAWzuro6cCkwI+e4f14a0zvvvONERDJdcskluPnmmwO78Y9//AOnnnqq8/utt966w6ErUfZdAmCUNFVWEghocpkEK6gNURGQP0dFUuUkhYB8OimWUDuCCHy0bjN4lmGPTm18s3zzvkl47O1FTb8d0asBnx/UIAFQLpUqAhIAU2WuTDW2ogJgQ0MjVm7YEikwCiZr161zyuzUsWPi9qLr2r41amqiv6XLFQB5KvAxxxzj8DrnnHNw11137WAPGwGQ+wfyIBCmc889F3feeWfZNuXhJddcc03Z1/PCYgeWFCuYEX+f/vSnnSwURi+99NLA7BMnTsSoUaOc36+44gowIrASSQJgJaiqzDgJaHIZJ33VHTUB+XPURFVe3ATk03FbQPX7EfjbhHn491sLMW3xGny0bgsuOHIIrvj0Hr6wfv30dPziyQ+afhvauRHf3rteAqBcK1UEolcLUtV9NTZGAhUVAJev24yRP34qxu5Vv+o3fnQMunf0/2LVnNaUKwC++eabOOCAA5yqebrtww8/vEMzggRADhBnzpyJe+65x4mUYxRgz549nf3zBg8eXHZX4hQAH3zwQXzpS19y2n7bbbfhggsuCOwH9zvkvodM3/rWt/DrX/+67D4Xu1ACYEWwqtAYCWhyGSN8VR05Aflz5EhVYMwE5NMxGyCH1XMv8sVrNmHz1gYM3KWDL4EbnpiG3z43s+m3o3bvgT9+bbRv3ienLsHX/zSx6bfOrRpx7ch6jB2rPQBz6F6p7bIEwNSaLvUNlwAYsQmTJgDOmDEDw4YNc3rJSMAnn3zSVwAsheGoo45ylsIaUaxU/qDfeYAI/2tOat26NYYPHx66iHvvvRdnn322cx0jIRkRGZRmzZqFIUOGOD83N+qxWEMlAIY2oy5IOAFNLhNuIDUvFAH5cyhcypwCAvLpFBgpI018/O1F+MMrs/H+4rVYvXErPr1PL9x25kjf3jH67+IHJjf91qtzW7x25ad88y5Zswl/fGU29ujVCYO6tsaMSa+gtkaHgGTEbXLTDQmAuTF14joqATBikyRNAJw8eTIOPPBAp5fc0+6hhx7aoccmArAYBu7/x2W/X/jCFyKmVd3iFAEYzHv69OlOlGfLli2bBOPqWke1ZYWAJpdZsaT6QQLyZ/lB1gjIp7Nm0Xj6w22e5q/c6Ah7I/rW+TaCy3ovf2hK02+DdumAZy89yjfv9CVrcewvX2j6rV2rWrz+w0+hU9tWRTuYRn/WKcDx+GzSapUAmDSL5Kc9EgAjtnXSBEBG/B133HFOL8877zz8/ve/9xUAe/fujXHjxjX9tmzZMkyYMAG//OUvsXjxYrRo0QIPPPAAvvzlL0dMrHrFaQ9ACYDV87b81pTGwXh+raWelyIgfy5FSL+njYB8Om0WS1Z7X5n5EW4c9z4+WLwW67fUY8/dOuPxSw73beSU+atw8m9ebvqtRQvg3WvGon3rljvl31bfgF89MwN79uqEPXbrjP7d2qPWYk/1NPqzBMBk+XRcrZEAGBd51VtRAVCHgETnYOXuAXjDDTc0nfzrd/BFqUNAFi5ciNGjR2PBggXOCcBvv/02+vfvX3bH4lwCrFOAJQCW7bi60JpAGgfj1p1TxtwRkD/nzuSZ77B8OvMmLruDFOFmL9+Axas34bBhu/iW859Zy/Hl373W9Fur2haYeu3xaMU1uAVp45Z67H3VE2ho3P5DpzYt8fBFh2LYrp3KbuNOdWzciPHjxzt/ZsBDu3btIiu7UgVJAKwU2XSVKwEwXfbKUmsrKgBWAlRS9kyrRN+KlVmuAHjsscfiqae2H8TCAzwOPvjgHaopJQAy86OPPoqTTjrJue7MM88E99IrN8V5CMiWLVvQvn171Ndzo+CxYERgUOKpv1deeaXz8zPPPIOjjz663C4XvS4p/qwlwBUxby4L1eQyl2bPbKflz5k1bW47Jp/OrekDO849+i598C18sGQtNm9rQIfWtXj76rGo8YnAW71hK/a7drvgZtK47xyB3Xv5i3p/enU2ete1wx67dUKfLu2cFUVRpjT6swTAKD0gvWVFeyekl4NaXn0CEgCrz7ysGssRABnxtu+++4Knb/Xr1w882IJ7vHmTjQDI/Icffjheeukl1NTUOFGA5R4GEqcAyH4ceuihjhDKaEYuc+aBIn7p+OOPd5ZEt2nTxsnXqVN0Xyu99UkALOt20EUJJpDGwXiCcappMROQP8dsAFUfOQH5dORIE13glm0NmLlsHaYvXYeT9+vt21YeqvGJnzy9w28vXHY0+ndv75t/zE+fwYJVG53furZvhV+ffmBgxGCl4aTRnyUAVtor0lG+BMB02CmLrZQAmBKrhhUA+UIcM2YMeAgI0y233IKLL754p97aCoAMr2fUHNMZZ5yB++67LyXkdmymd0k09zQ87bTTduoHX8zkwkjBE044AY899ljF+ioBsGJoVXBMBNI4GI8JlapNAQH5cwqMpCaGIiCfDoUrtZmXr9uMr9z5H8xYug7b3DW4PFSjZ6e2O/WJgQIHXvckVm7Y2vTbHWeNxNi9e/n2n6f7tm/T0tmvr0enNpFH9YWBnkZ/lgAYxsLZzSsBMLu2TXrPJAAm3UJu+8IIgFOnTsVZZ52FSZMmOVcfeeSR4GEgrVrtfJKWrQDIckaNGoWJEyeitrYW06ZNw9ChQ1NC7+NmrlixAoMHD8bq1asxYMAAvPHGG+jevXtTBop+p5xyCh555BHnb5Vc/svyJQCmzoXU4BIE0jgYl1FFIIiA/Fm+kTUC8un0W5R7601fuhbTFq3FCfvuho5tdj5Ug/uw73P1OGzYUt/U4T+dMxpHDO/hC+D0372GV2ctd37btXMbXPHpPXDKAZwmJjul0Z8lACbbp6rVOgmA1SKtegoJSABMiU94BcALL7wQF110UVPL169fj5UrV2LKlCl4+umnHbGPX/OYuOcfxaxddvHfzDeMAPjPf/7TEceYzjnnHNx1110pobdjM++44w5ccMEFzh+HDBmCH/7whxgxYgR44MnNN9+MZ5991vnt9NNPx/3331/RPkoArCheFR4DgTQOxmPApCpTQkD+nBJDqZnWBOTT1qgSl5Gi3gm/etHZq88crPHgBYdg1MBuvm393K0v4815q5p+u/KEPfCNI4b45n1t1nI0NDZij16d0a2D//Y4iQMCII3+LAEwiZ5U/TZJAKw+c9W4nYAEwJR4glcAtGlyjx498J3vfAeXX375Tvv+ea8PIwBSVOSegtxbkNGEM2bMaNaJwDb9qFSeq666Ctddd12TUFpYD5f+PvTQQ2jbduelElG2SQJglDRVVhIIpHEwngRuakMyCcifk2kXtap8AvLp8tlV8sq1m7Y6wt57i9biyOE90K+b//57x9/8AqYtXtvUlOs+uzfOOmSgb9N+8PAUPPD6vO0Tvq7t8NVDB+K8wwdXshtVLzuN/iwBsOpuksgKJQAm0iy5aJQEwJSYOUgA5KEcPKCirq7OWdI6cuRI58COz3zmM4EHXJQrAPI6RsR95StfcYpgFOKtt96aEoI7N/OVV15x2v/iiy9iyZIl6NKlC/bbbz987Wtfc6L/qpEkAFaDsuqoJoE0DsaryUd1pYuA/Dld9lJrSxOQT5dmVO0c3uW3rPvGL+yLLx7Uz7cZ3/nLZPzzzYVNv53xif74ySkjfPNOW7wG6zZtw/BendC57c7bAFW7n5WoL43+LAGwEp6QvjIlAKbPZllpsQTArFhS/UglAQmAqTSbGl2EQBoH4zKoCAQRkD/LN7JGQD5dPYuu2rDFieijEHdg/67Yr18X38rPv3cixr27pOm3cw8bhP/5zF6+eW9/fiZ++vg0tGgBDOreASeM2A2Xjt29ep1KWE1p9GcJgAlzopiaIwEwJvCqVkuA5QMiECcBCYBx0lfdlSCQxsF4JTiozGwQkD9nw47qxccE5NPV8YZv3jcJj729qKmybx09NFCo++WTH+CWp6c35R0ztDvuO+9g34YuXLURy9ZuxrBdO6J9650P/6hO75JTSxr9WQJgcvwnzpZIAIyTfr7rVgRgvu2v3sdMQAJgzAZQ9ZETSONgPHIIKjAzBOTPmTGlOuISkE833xW4X9+7C9c4p+/u06fOt8DrHp2Ku176sOm3Y/bsiTv/a5Rv3ifeWYQL/jwJLWtaYEiPjvjE4G649rP7NL+hOSghjf4sATAHjmnRRQmAFpCUpSIEJABWBKsKFQE7AhIA7TgpV3oIpHEwnh66amm1Ccifq01c9VWagHy6fMIPvD4Xd744C7M+Wo/GRuDUA/rgpi/v71vgv95cgEv+8mbTb326tMPLV3zSN+/qjVsxf+UGDO3ZEW1a1pbfwBxemUZ/lgCYQ0f16bIEQPlBXAQkAMZFXvWKAAAJgHKDrBFI42A8azZQf6IjIH+OjqVKSgYB+XSwHTZtrcfy9VtAsc4v3fvqbPzPv95t+omC3VP/faRv3lnL1uGTv3gerWtrnOW6e+7WGT/7/L6ordG0P8o7IY3+LAEwSg9Ib1l6EqTXdmlvuQTAtFtQ7U81AQmAqTafGu9DII2DcRlSBIIIyJ/lG1kjIJ/e0aLvLFiNP782B1Pmr8YHS9Zi3751ePiiMb5mf3PeKnzu1pebfuNBHG9fPdZZClyYGhoa8f6StU5UX6vamqy5UWL6k0Z/lgCYGPeJtSESAGPFn+vKJQDm2vzqfNwEJADGbQHVHzWBNA7Go2ag8rJDQP6cHVuqJ9sJ5NGnKcbVBETevfDBMpx99+tN7tGmZQ3evWYsWvqIdowQ3OeqcdjW0Ojs17d7r074zRkHYtAuHeReMRFIoz9LAIzJWRJWrQTAhBkkR82RAJgjY6urySMgATB5NlGLmkcgjYPx5vVYV2eZgPw5y9bNZ9/y4NOrN2zFk+8twdvzV2HKgtVYumYzXvr+0WjBkL2CtHL9Fhxw3ZM7/PXxSw53luz6pX+/tRD9u7XHHr06oW0r7dcX912URn+WABi31ySjfgmAybBDHlshATCPVlefE0NAAmBiTKGGREQgjYPxiLquYjJIQP6cQaPmvEt58Ok5y9fjyBuf28HSr1zxSfQO2NvvsJ89g/krNzr5qRH+5vQDceK+u+XcU9LR/TT6swTAdPhWpVspAbDShFV+EAEJgPINEYiRgATAGOGr6ooQSONgvCIgVGgmCMifM2FGdcJDIK0+3djYiLkrNjh79b29YDXenr8ad5w9Ep3bttrJvsy73zXjsWbTtqbfbj9zJI7fp5evL9z90odoaGzEiD512LtPne+efnKiZBJIoz9LAEymL1W7VRIAq01c9RkCEgDlCyIQIwEJgDHCV9UVIZDGwXhFQKjQTBCQP2fCjOpEBgTAzdu277+3tb6xqTf3f/0TOHTILr72PfPO/+ClGR81/fbNo4fgsrF7yBcyRiCNz2gJgBlzwjK7IwGwTHC6rNkEJAA2G6EKEIHyCUgALJ+drkwmgTQOxpNJUq1KAgH5cxKsoDZESSCJPr1kzabtkX3zV+GUA/sGHqpx0q9fcqL/TPrBp/fA+UcO8cXzuxdm4o05K7Fv3y5OZB9P9+3SvnWUKFVWAggk0Z9LYZEAWIpQPn6XAJgPOyexlxIAk2gVtSk3BCQA5sbUueloGgfjuTGOOhqagPw5NDJdkHACSfPpz9/2iiPUmXT9qSNw+uj+vhSv/MfbuP8/c5t+4z59t55xYMKJq3mVJJA0f7bpqwRAG0rZzyMBMPs2TmoPJQAm1TJqVy4ISADMhZlz1ck0DsZzZSB1NhQB+XMoXMqcAgLV9GmesMuIvd5d2mJoz06+dL51/yQ8OmVR028U/ygC+qW/TpiLnz3xvhPNt2+fOhw8uDsOHeq/BDgFplATIyBQTX+OoLlOERIAoyKZ7nIkAKbbfmluvQTANFtPbU89AQmAqTehOlBAII2DcRlRBIIIyJ/lG1kjUA2fvvXZGfjLhLmYt2L7yboXHDkEV3zaf/89LtX9yf+b1oR5nz6d8ei3D/fFvq2+AbU1LdCCR/UqiQCAavhz1KAlAEZNNJ3l6SmWTrtlodUSALNgRfUhtQQkAKbWdGp4AIE0DsZlTBGQACgfyAuBKJ7R6zZvw9pNW7FbXTtfbD8f9z5+8+yMpt/GDO2O+8472DfvqzOX4/Tfv4ZObVpinz51OHBAFx3WkRdnjKCfUfhzBM0IVYQEwFC4MptZAmBmTZv4jkkATLyJ1MAsE5AAmGXr5rNvaRyM59NS6rUNAfmzDSXlSROBcn2aQt2DE+dhyoLVmLlsHY7fuxduO3Okb9fHvbsY59/7RtNvndq2xJSrjvON3Nu0tR4LV23EwO4dUFOjKXGafCkJbS3Xn+NsuwTAOOknp2497ZJji7y1RAJg3iyu/iaKgATARJlDjYmAQBoH4xF0W0VklID8OaOGzXG3ivl0Q0NjoAj3t4nzcPnfpzSR69OlHV6+4pO+JBet3ohDrn/G+a1Nyxrs3bsz7v7qKJ3Cm2O/q1TX0/iMlgBYKW9IV7kSANNlryy1VgJglqypvqSOgATA1JlMDS5BII2DcRlVBIIIyJ/lG1kj4PXpAw49Ei/NWoO3F6zClPmrnf31/v2tw3y7PG3xGhx/84s7/PbGj45B945tdsrf2NiIhyctwF69O2NYz45oWVuTNYzqT0IIpPEZLQEwIc4TczMkAMZsgBxXLwEwx8ZX1+MnIAEwfhuoBdESSONgPFoCKi1LBOTPWbKm+kICXp/utvtonPXHSU1gKAC+e81YtG1VuxMsHsCxz9XjsGlrg/Nby5oWuP/rB2P0oG4CKwKxEUjjM1oCYGzukqiKJQAmyhy5aowEwFyZW51NGgEJgEmziNrTXAJpHIw3t8+6PrsE5M/ZtW2We8YIvFkfrceED1fgvUVrcPXJezftv+f16TFHfRKjfvoCGhs/pvHwRYfiwP5dffH85pnp6NyuFUb0qcOeu3X2FQqzzFV9Sx6BND6jJQAmz4/iaJEEwDioq04SkACYEj947rnncPTRR+/U2traWnTu3Bl1dXXo168fRo4cicMOOwwnnXQSWrduXbJ3AwcOxJw5c3bK17JlS6fMYcOG4aijjsL5558P5s1CmjFjBiZMmIDXX3/d+W/y5MnOF3GmP/zhD/jqV79atW5KAKwaalVUJQJpHIxXCY2qSSEB+XMKjZbzJi9dswnH3/IiVqzf0kTixcuPRr9u7Z1/F/r0ybe9julL1zXlvebkvfFfh2ZjvJdzV8hF99P4jJYAmAvXLNlJCYAlESlDhQhIAKwQ2KiLDRIAg+rp0aMHLr74YlxxxRWgmBeUggTAwvzt2rXD7bffjrPPPjvqrlW1vOeff94RNIOSBMCWjuirJALlEkjjYLzcvuq67BOQP2ffxmns4brN29C6tgatW+68tx6j/0b++KkdBMCbvrQfTj2QQ/6dBcBfPT8H81duxL596rBv3zrs06cOHdoEjxvTyEttzi6BND6jJQBm1x/D9EwCYBhayhslAQmAUdKsYFleAfDCCy/ERRdd1FTbunXrsHLlSkyZMgVPP/00nnrqKXAAyDR69Gg8+uijoCDol4wA2Lt3b4wbN64pC1+ojJS799578fjjjzt/Z7Thiy++iEMOOaSCPa1s0V6ONTU12HPPPdGhQwcnEpBJAqAEwMp6YPZLT+NgPPtWUQ/LJSB/LpecrouawLh3F+PVmcsxcc4KTF24Bn8+7xM4dMguvtV8408TMX7qkqbfTh/dH9efOsL5t3w6asuovDgJpNGfJQDG6THJqVsCYHJskbeWSABMicW9wtVVV12Fq6++OrDlU6dOxZlnnuksbWUaM2YMnnnmGd8lwUYAHDBgAGbPnu1b5ve+9z3cdNNNzm8nnniiIyimNU2fPh3/+te/MGrUKGe5dMeOHfHHP/4RX/va1yQAbtvmRIsqAjCt3p2MdqdxMJ4McmpFEgnIn5NolXy26bO/eQlvzV/d1PnvHjMclxzjH7F/54uz8OPH3sOundtg1MBuOG7vXjh5v94SAPPpOpnudRqf0RIAM+2S1p2TAGiNShkjJiABMGKglSoujADINvCFSOHPiIAU8L773e/u1DwbAXDDhg3o1q0bNm/ejPbt22Pt2rVg9FxWkgRAgMLoNgmAWXHpWPuRxsF4rMBUeaIJyJ8TbZ5MNG5rfQPeXbgGE2evcA7WGDPUP6rvuken4q6XPmzq8+HDdsG9537Cl8HydZuxYUs9+nZt13T4h8kon86E26gTLoE0+rMEQLkvCUgAlB/ERUACYFzkQ9YbVgBk8e+++y5GjBjhLAfmEl9G+LVq1WqHmm0EQF6w11574b333nOuXbp0aeCS4pDdSkR2CYASABPhiBlpRBoH4xlBr25UgID8uQJQVWQTgZuf+gC3Pz8Tm7Y2OH/74si+uPGL+/kSeuKdRbjgz5OafuvSvhUm/ehY1NSEm0bKp+WAWSJAf/7HY+Mxa20LHH7wQThyz+2RrklOEgCTbJ3qtS3ck7t67VJN2ScgATAlNi5HAGTXxo4di/Hjxzu9fPnll3HooYfu0GNbAXD//ffHW2+95VzL/Qa7dOmSEnKlmykBUAJgaS9RDlsCmlzaklK+NBCQP6fBSslu46at9Wjbqta3kX94+UNc88jUpt8Gdm+P5y472jfvsrWbcemDb2HUwK44aGA37Ne3C9q19i+3GBH5dLL9Ra0rTWDBqo2Y8OEKvD57BV6ftRwzlq13LjpqeHf88ZyDSxcQcw4JgDEbICHVSwBMiCFy2AwJgCkxerkC4I033ojLL7/c6eVPf/pTfP/73w8tAHJpaF1dHbgUuHPnzli9+uM9aFKCr2gzJQBKAMyCHyelD5pcJsUSakcUBOTPUVDMVxlL12zCs+8vxYTZK51lvb3q2uIv3/A/PO2dBavxmV+/tAOg13/4KfTs1LZi0OTTFUOrgitAoKGhETOWrcPrH67AhNkrMHH2SlAA9Et1bVti8v8eFzoqtgLNLlqkBMBqE09mfRIAk2mXPLSqsgJgQwOwcUWkHBsaGpw96Jg6deqUvL3o2nUDKrA/XrkCIE8FPuaYYxxe55xzDu66667QAiD3D+RBIEznnnsu7rzzzrJtysNLrrnmmrKv54XFDiwpp2AJgBIAy/EbXeNPQJNLeUaWCMifs2TN6vTlqalLcN6fJjZV1rZVDaZcNRatW+68d/K2+gbsf+2TWLd5G4b27Ogc2PGtTw5Fny7tKtZY+XTF0KrgCAhs2daAdxaudiL8HBF9zgqs2rDVuuRx3zkCu/fqZJ0/jowSAOOgnrw6JQAmzyZ5aVFlBcD1HwE3DskLy+39vGwm0MF/A+fmgChXAHzzzTdxwAEHOFWfcsopePjhh3doRtASYA4QZ86ciXvuuQc333yzc0BEz5498eqrr2Lw4MFld0UC4I7oKGivWbPG+SOjK+M6XEWHgJTt0rqwgIAml3KJLBGQP2fJms3vy/rN2zBp7kpMXbgG5x/pP75duX4LDrjuyR0qe/iiQ3Fg/66+DXhjzgoM2qUjunVo3fwGWpQgn7aApCxVI2DuKYp9FP0mz1vZtCdmmEa0qmnEAf274ocn7o39+iV7myIJgGEsm928EgCza9uk90wCYNQWSpgAOGPGDAwbNszpJSMBn3xyx0GpEQBLYTjqqKNw6623OoeBNCfxABH+15zUunVrDB8+vDlF7HCtIgAVARiZM6kg5wRys+/occcdh3btKhfJItwiUGkC8udKE05H+R+t24yv/WECpi5ag/qGRqfRr1zxSfQOiNQ79qbnMX3puqbO/fCEPfH1I8r/eBolJfl0lDRVVlgCvJe4jJfLefkfT8A291SYsuratXL2w9y/TyfUL34ffTteB7C9AAAgAElEQVQAJxyfjjGHBMAwls5uXgmAybXtAAAXAzgRQD8AmwHMBPA3ALcC2BBB0wcCuJD6DAB+TuwAgGtcpwF4AsDtPHg1gnr8ipAAGDXYhAmAkydPxoEHHuj08tRTT8VDDz20Q49tBEDu/8dlv1/4wheippWI8iQASgBMhCNmpBGaXGbEkOqGQ0D+nB9HaGxsRGMjd3HZeVrGfcgY1bd648dLEX91+gE4eT//E0d/Mf59fPjRemdJ70EDu2KPXp1RG/K03kqRl09XiqzKLSTAe2r+yo1N+/fx0I5Z7oEdYWn1rmuLUYO6OffU6EHdMLRHR+deTaM/SwAMa/1s5pcAmEy7ngTgz1yZF9C8D1xhcEYzmn8WgDsAFAuR4CZ6pwHYMXSrGZV6LpUAGA3Hj0tJmADIiD9G4TCdd955+P3vf+8rAPbu3Rvjxo1r+m3ZsmWYMGECfvnLX2Lx4sVo0aIFHnjgAXz5y1+Omljs5UkAlAAYuxNmqAFpHIxnCL+6EjEB+XPEQBNW3JT5q3Y4XOD2s0Y6AoNfOvePE/D0tI+/x599yABc+9l9Etaj0s2RT5dmpBzlEaBQ/v6StU5knzm0Y8kaxs6ET8O4J+agbhjtiuh9u7b3LSSN/iwBMLw/ZPEKCYDJsyo3TXvZFeYYw389gGfdf1OM+7rbZIqAB7kRe2F7MQbACwC4K3ADgHsA/AvAQgD9AfwXAIqQTDzuiKOMWWErKZG/sgKgDgGJzFzl7gF4ww03NJ38yxOBL7300h3aFLQHoMm0cOFCjB49GgsWLHD2qHv77bfRvz/ds7ykJcA7ctMegOX5ka5KLoE0DsaTS1Mti5uA/DluC1S2/hNuedFZ1mvSZWN3xzePHupb6W3PzcTPnpiGljUtMKJvHU7atzfOOWxQZRtYgdLl0xWAmtMiN2+rx9vzV4ORfdy/b+KclVi7aVtoGryn9ulT50T2HTSgKw4a2M16T8w0+rMEwNAukskLJAAmz6zPAzgCAJ9i/N9XC5p4GYAb3L/xSNOry+jCo24EIS/9JoDf+pTxCwD/7f6dS46/VUY9xS6prAAYcWNZXFIEkwp0rWiR5QqAxx57LJ566imnbB7gcfDBB+9QTykBkJkfffRRnHTSdi36zDPPxL333lt293UIyI7okuLPOgSkbJfWhQUE0jgYlxFFIIiA/Dm9vrF07Sa8MXuls09f0KEAV/3rHdzz6pymTh69ew/84WujfTs9f+UGzFuxEfv364J2rWtTC0Y+nVrTxd7wtZu24o05Zv++lXhz3irw1N6wqX3rWudQHEbbOvv49e+C9q1bhi3GyZ9Gf5YAWJapM3eRBMBkmZRv/v+4TeLy3At8mseovXcA7AlgFYCeAOzPKN9eIJf28kiw5QCCjo2tc8tn/kkARkaMSgJgxEArVVw5AuA777yDfffdF9yDo1+/fpg1axZattzxBWsjALJPhx9+OF566SXnlFpGAZZ7GIgEQAmAlbpHVG4yCKRxMJ4McmpFEgnIn5NoleJt+tOrs3H3Sx9i9vLt23SfPro/rj91hO9Fj7y1EN9+YHLTb53atsSb/3tcYvbrqwR9+XQlqGazTIroEz78+MCO9xatgXsGTqgO84RrCn3bBb9u2Kt3Z7Sq5VS6+SmN/iwBsPl2z0IJEgCTZcWfAPiB2ySGSxkxsLCVV7hLg/n3sQDGh+wGlxbzwI+JAEYVuXaZKxBScPQfwYSs2JNdAmD57Kp6ZVgBkC/EMWPGgIeAMN1yyy24+GKeZ7NjshUAearn2LF0c+CMM87AfffdV9X+V7Iy7QGoPQAr6V95KzuNg/G82Uj9tScgf7ZnlZScd744Cz9+7L2m5nAvsSf/+0jf5i1evQlfufM1d+nhdnGiX7d2zr7HWU3y6axatnn9YrAARXMu5TUn9BoRPWzJvIdGDejWdGjHkB4dKnZPpdGfJQCG9ahs5s/uWyad9uK+fIcDWA+gi7sM2K8nhwB4xf3hWgBXhezuGwB4PGuxCEAeQLLaLZfHt0Z9DKsEwJBGiyt7GAFw6tSpOOusszBpEoNGgSOPPBI8DKRVq1Y7Nd9WAOSFo0aNwsSJE1FbW4tp06Zh6FD/fXLiYlRuvRIAJQCW6zu6bmcCaRyMy44iEERA/pwM39iwZRsmzVnVJEx0bNMSvzubW3DvnLgs8XO3chvvj9Pk/zkWXTu0TkZnYm6FfDpmAySk+vqGRjCiz4h9E2avxLK14Q/soFa++66dtkf3Oaf0dsVudcXOtowWQBr9WQJgtD6Q1tIkACbLcibi7i0A+xdpGpfvchkv04MAvhSyGzxI5HfuNRcCuN3n+hsBmFMbjgWwfTO36JIEwOhYVrQkrwB44YUX4qKLLmqqb/369Vi5ciWmTJmCp59+2hH7+CWPiXv+PfLII9hlF/9V5mEEwH/+85845ZRTnHLPOecc3HXXXRXtc6UK//vf/4516xiAuz1xabPpy7nnnovDDjus6bdevXrh+OOPr1RTErOnpfYArJiJc1dwGgfjuTOSOmxNQP5sjaqiGZ94ZxEu+PP2j5pMHVrX4q2rjkNLn2WEW+sbMOLqcdi0tQEUCg8c0BXXnLw3Bu3CRTdK8ul8+sCmrfV4a952Ef312Ssxac5KrNsc/sCOVrUtsG/fLo7gN3pQV4zs3w117XcOMKgW5TT6swTAanlHsuuRAJgc+7R1T9xlix4D8JkSTTPLeF8DwIjAMIk7CN8N4Gz3FGD+/38DWOSeAnwmgO1qC/B/AH4UpnA3LwW+YqkXgAnM8MEHH6Bv31LZPy5q7ty5qK+vd6LKhgwZUkbTyruEhyYY8aZjx47OnnR5SBQAP/WpT1l3tUePHrjkkktw2WWX7bTvn7eQwYMHY86cORgwYICzR2CxRFFx//33B/cWpN3pM805Edi6MxFnNH22KZbRk88884xN1rLyJMWfZ86cia1btzrRnWm0aVnwdVFFCGzatAkvvMBAeuCII45A27Z8rSqJQDoJyJ+rY7dl6zZj6qK1OHKY/8fKj9ZtweG/eGmHxvz96wdh795cKLNzGj91Kfp2bYfhu3ZAy5yME20tJZ+2JZXufGs2bcWkuavxxtxVeGPuaryzcA221m8PDgiTKLYf0K8OI/t3wcgBdRjRuzPatkrOIThp9GcKgMOHDzdm6AdgfhibKG82CEgATI4dewBY6jbnrwBOK9G0Je4BIM3Zn+/zAH4I4ACfup4FwD0Jy438s37S33nnnYFRYn4Munfvjnbt2qF9+/bYbbfdkmPBjLaEUWrmJF5vFymAUgjt3Lmzc9AHBbpDDjnE2a+vdevSy114SMi8efOcaxlBWCo9+OCD+MY3vuFkY7Tcz3/+81KXJO5302ebhnEfRZ6CnPW0aNEibNiwwTlNbfly7kqgJAIiIAIiIAKVI7B+K/DMohpMW9UC89e3QA0a8ZNR9WgXcBjojyfXYtmmj6dMpwysx1G7WQ9zK9cRlSwCCSCwajMwa20LzFzTAjPXtsDiDUAjwksMnVo1YkinRgzu3IjBnRrRuwNQG76YBBBJbhM++ugjnHfeeaaBEgCTa6qKtky3VUXxhiqcN+Fc94p73ei8YgUwL6+ZCaCcDdF4ivDPAHwagN+QZxOAf7rLgBeE6sn2zNYjIwmAZdDVJSKQEQISADNiSHVDBERABFJCYHM9cOWEWmxr/HgadM7weuzX3X/o+tdZNViwvsUO4kSH+FYepoSymplFAtzlZ+kmOGLfLP63tgWWby5PTtil7Y6CX4+2QIbPwEmEO0gATIQZYm9EeXds7M3OZAOqGQHIg0YeAVAHYI67xPdJd1/BXQGcDODHALjX4EIAxwF4NyT1Umt6tQQ4JFBlF4EoCWgJcJQ0VVYSCKRxOU4SuKkNySQgfy7fLtxzbMKcVdh9147o2amNb0Hn3jsZr8xa2fTbFw/sjWtP2sM3L7chyfLpvOWTDnelfDocryTk3tbQgPcWrWtazjtp7iqs2LA1dNNqnAM7OuIgZzlvF2dpb9C9GbrwmC5Ioz9rCXBMzpKwaiUAJscg1doDkCMhRg32AbDYXf7L/y1MewOYCIDt4qnB/keelc9Ph4CUz05XikCzCVAAXLNmjVMOl3HHtaelDgFptilVgEsgjRtyy3giEERA/hzeN/42YR4embIQ//lwBbZsa8C1n90bZx8y0LegO1+chR8/9p7zGw/sOOWAPrjuc/uEr1RXWBOQT1ujii3jxi31mDx3JV6fvQITeWDH3JXYsKU+dHtat6zB/v26YPTAbjhoYFeMHNAVndpmK2w2jf6sQ0BCu3ImL5AAmCyzVuMU4M+6S3vZc+7/x33+gtLvAZiNAngqMU8njipJAIyKpMoRgTIISAAsA5ouSTSBNA7GEw1UjYuVgPw5PP7//uubeHjyx7vWHLNnT9z5X6N8C/rwo/V4cOI8HDm8h3NabyufU33Dt0BXFCMgn06ef6xcv8U5nXfinJV4/cMVeGfBamxrsN7FqalDndu2xEGu2EfRb0TfOrRpmZwDOypBPo3+LAGwEp6QvjIlACbLZjy+kMtz1wPoAiDojHSe+vuK2/RrAVwVohtXALjezc/9/54ocu0FAG5zf+ehJDycJKokATAqkipHBMogIAGwDGi6JNEE0jgYTzRQNS5WAvLnHfE3NDRi6qI1WL95Gz4xuLuvbf715gJc8pc3m35r37oWk//32MwLEbE6aojK5dMhYFUo6/yVG5zIPkb4TfhwBaYvXVdWTbt2boNRA7th9KBuzv/uvmsn1HCdb45SGv1ZAmCOHLRIV/N1pybf5ozG+4HbzIMB/CegyV4RbyyA8SG6dimAG938JwEodszotwH8ys37BQAPhainVFYJgKUI6XcRqCABCYAVhKuiYyGQxsF4LKBUaSoIyJ+3m4kRSXe/9CFemL4MH63bgv361uFf3zrM14bL123GQf/3FHhQAbWIA/t3xc2n7Y++XdunwuZZb6R8uroWpmg+Y9k6J7KPUX4U/Bau5hmP4dPgHh2c5bxG9OvbtV3u98VMoz9LAAzv+1m8QgJgsqw62iP63QGAEXiFqYbjIQA8xXcVgJ4AwuzG+nkAf3cLvQHA94sgYD7mZxoJYFKEuCQARghTRYlAWAISAMMSU/6kE0jjYDzpTNW++AjIn7ezf2XGRzjjzo+/h/OU0Dd+dCy6dWjta5xfPT0dQ3t2xJghu6Cufbb2HIvPG6OpWT4dDcegUnhYzftL1uLlGcvx6syPnGW9q8o4sKO2pgX27t3ZEfu2/9cV3Tv6H6ZT2R4lu/Q0+rMEwGT7VLVaJwGwWqTt6zHLgLn89wgArxZcehkACndM1wC4uuD3owA86/7tHgBfLfidS4u5QQo/h64FMAbA2z7N4/JgRgdScGT+/gAa7LtRMqcEwJKIlEEEKkdAAmDl2KrkeAikcTAeDynVmgYCefHnhas24rVZy51DOPxO2t28rR77X/MkNm79+CCCW07bH5/dn2fZKaWJQF58upo2mbdiA175/+xdB1RVV9b+pIP0KiCgKHax996TqJNmykTTq5kZU3RMn0zqn5g+iZlk0ns1VWPsvXdURMUCFnoXpPOvfRAEuQ/ue7z73j337bOWaybcU/b+9uZy3vd2OZaNjRdIP4qSNXd4uDqhX1QABnUMFFF+/aL90dbdxdxtHG6+jP7MBKDDuamiwkwA6s8P+gHYBMATABVmoLRgIvTov6kO3z0XRD5yoTMvkXgNR0sEIM19CgDVDqRBZ7wNYAWAPABhAKhRyN0A6t7+NwP40spQMQFoZUB5O0bAHASYADQHLZ4rAwIyXsZlwJVltA8CRvbn0ooqvLrsMNYdyaqvQbby4dHoHOqjCPadn+7AqqRM8axjcFvMmdAZV/ejayQPmRAwsk/byg6U5r7leA42JWeLSL/U3BKzj/b3csXAGKrfFyAi/HpG+IG69vIwDwEZ/ZkJQPNsbNTZTADq07JUm48IN18T4hH5NxVAssJzNQQg2f11AA8AaM4HKLX4cQCvagATE4AagMpbMgJqEWACUC1SPE8WBGS8jMuCLctpewSM7M+Uqjj8pdVIa1CP7Mmp3XHXqFhFoNckZYKaF4zuEoKYoLa2NwafaBUEjOzTVgFIYRNqekMNOzYdzcamYzk4lFZo9lGR/p4ijZci/Ijw6xzi7XANO8wGTcUCGf2ZCUAVhnWAKUwA6tfIMRcIOiL6iCyjmG4i/H4A8A4AU1/5qCEA67Smun53AaBqynQepQVTRCCdsw4A1SEkslGLwQSgFqjynoyASgSYAFQJFE+TBgEZL+PSgMuC2hwBmf35XFmlqN1HjQNMRfU9uigB3+44VY/rqLhgfHHnEJvjzAfaDgGZfdpWKFVUVWPvqXxsPJotUnv3pOajsrrGrOOJ8BvZORjDOgUJ0o/+m4f1EZDRn5kAtL4fyLgjE4AyWs0YMjMBaAw7shaSIsAEoKSGY7FNIiDjZZzNyQiYQkBGf/55z2l8t+MUdqXkoaKqBveOjsVjV1DPuqZj6f40zP6qtrecn6crJnYPw6vXxTt8Z1Ej/0bI6NNa24M69SalU+MOivDLFh17S8ov1rtUcz41xCGyjxrfjOgchOhAL/49UgNcK+fI6M9MALbS6AZZzgSgQQwpoRpMAEpoNBbZOAgwAWgcW7ImtQjIeBln2zECRiIAX1t+GG+vvlidpls7H/z5IPWzazoKzlfgk00nMKZLCOLb+4M6j/IwNgL8jq61b2pOCTZeIPy2HMtBbrF5jTu83JwxuGOgIPyGdw5C93a+nNJrh18dGf2ZCUA7OIoOj+S/tjo0ioOIxASggxia1dQnAkwA6tMuLJXlCMh4GbdcW15pdAT05s9V1TXYdzofmYVluKxXO0X4d57MxYz3tjR6tu3xCQjz9TC6uVg/FQjozadViGyVKVlFZSKdd3NyjojyO5133qx9XZzaiM68w0WEXzD6Rvlz0w6zENRmsoz+zASgNr4g265MAMpmMePIywSgcWzJmkiIABOAEhqNRW4WARkv42xSRsAUAnrx5+TMIryx8qioSUZRe8He7tj++ATFiKPKqmr0e24Fikor4ercRnQaffovPdCtnamedmx/R0JALz6tNeZUA3Ob6NSbI4g/SvE1d3QP98UISuvtHCyi/dq6u5i7Bc/XGAEZ/ZkJQI2dQpLtmQCUxFAGFJMJQAMalVWSBwEmAOWxFUuqDgEZL+PqNONZjoiAXvz5ZHYxxr66tpEJlswZiZ4Rfopm+WZ7KkK83UVNMiYtHNFzTeusF5+2tlXKK6uxJzXvQh2/HOw7ZX7jDqrbR/X7KMpveKcgBHm7W1tM3s/KCMjoz0wAWtkJJN2OCUBJDWcAsZkANIARWQV5EWACUF7bseTKCMh4GWdbMgKmELCVP6fkFGPdkSxcNyAKnm7OiuKMeWUNUnJK6p/Nv6wr7h/bmY3HCJiFgK182iyhLJhMjTsS0wrrCb8dJ3JxvsK8xh3B3tS4I7g+yi8q0MsCSXiJPRGQ0Z+ZALSnx+jnbCYA9WMLR5OECUBHszjrqysEmADUlTlYGCsgIONl3Apq8xYGRUBLf66pqcFziw9hdVIGTl4g9j69fRDGdg1VRPNfvx7A51tSxLMuYd64ZVgHzBoaY1DkWS2tENDSp7WSmfal3xciwKlxB6X0UuOOvJIKs45s6+aMIbEU4ReEkXHB6Brmw516zUJQf5Nl9GcmAPXnR/aQiAlAe6DOZxICTACyHzACdkSACUA7gs9Ha4KAjJdxTYDgTQ2BgNb+POO/m7EzJa8eq9tHdMDT03sqYpdwOh+JZwsxuksIIvw9DYEvK2F7BLT2aWtqlFlUWtu0Q5B+OTiTb17jDqqB2S86QHTqHRkXJDpduzo7WVNE3svOCMjkz3VQMQFoZ6fRyfFMAOrEEA4oBhOADmh0Vlk/CDABqB9bsCTWQUDGy7h1NOddjIhAa/yZmnUQcRHq446BHQIV4Xl71VG8tuJI/bPYkLZYPXesEaFknXSCQGt8WmsVCksrsO147gXCLxtHMs6ZdWSbNkAPatzRubZT76AOAfBy48YdZoEo2WQ9+7MpKJkAlMzJNBKXCUCNgOVtW0SACcAWIeIJjIB2CDABqB22vLN9EJDxMm4fpPhUGRCwxJ+X7k/DRxtPYM+pfFRV12BafDjeuam/orrUqODKhZvEM6pHNjouBP93bW+4uyjXAZQBM5ZR3whY4tNaaVRWWYVdKXm1UX7HspFwukD8zpgzOgR5YXjnYIzsHIxhsUEIaOtmznKeKzkCevJntVAyAagWKWPPYwLQ2PbVs3ZMAOrZOg1kW7t2LcaNG9dEWmdnZ/j6+sLPzw9RUVEYMGAARo4cienTp8PNreVLUIcOHZCSUltTqOFwcXERe8bFxWHs2LG49957QXNlHxUVFVi1ahWWLVuGbdu24ciRIygoKEDbtm0RGxuLCRMmYPbs2eL/22IwAWgLlPkMWyIg42XclvjwWXIhYIk/f7s9FY/+tL9eUT9PV+x+ahKcnZpe96mRwQcbjotoJYpcclKYIxdiLK3eEbDEp62lE5F7B88WYFNyjqjjt+NkLkorqs3aPtjbXXTqrYvyi+R0eLPwM9pke/qzpVgyAWgpcsZaxwSgsewpkzZMAEpiLVMEoCnxQ0JCMGfOHDz66KMgMs/UMEUAXjrf09MT7733Hm655RZJEGsqZlZWFrp3746cnJxmdSDidMGCBXjggQc015UJQM0h5gNsjICMl3EbQ8THSYTApf7s4uYuIpaOZZ3DzCHKDTjO5p/H8JdWN9Lyp/uHo390gESas6hGRcCW72hq3HE8uxibk7MF6bfleA4oNd6c4e3ugqGxgfWEX1yoNzfuMAdAg8+1pT9bC0omAK2FpNz7MAEot/1klp4JQEms15AApAi1+++/v17yc+fOIS8vDwkJCSK6beXKlaJbGo3Bgwdj8eLFIEJQadQRgBERESIqrm7QH9Tk5GR88cUXWLp0qfgxRRtu2LABw4YNkwS1xmI2/IPbt29fXHnllRgyZAjCwsJEFCDp+fbbb6O0tFQsfP/993HPPfdoqisTgJrCy5vbAQEZL+N2gImPlASBOn/OLQM2lrTDthP5OFdWCRenNtjzr0nw8XBV1GTyG+tE/TI3FycMjQ3CAxPiMCCGCUBJzG5oMbV+R2cUlooafnVRfmkFtXcqtcPN2Qn9Y/xFSi+l9sZH+sGFG3eohc/h5hWXlGDJnyvg7gxMnjwZFLCg98EEoN4tZBv5mAC0Dc58SlMEmACUxCsaEoBPP/00/v3vf5uUPDExEbNmzcKePXvEnBEjRmD16tWKKcF1BGBMTAxOnjypuOfcuXPx+uuvi2dTp04VhKKM48yZM7j99tvx7LPPYujQoYoqUFowpVrTBZlSoE+dOgUfHx/N1GUCUDNoeWM7IaD1h0s7qcXHOigCdf5cVgU8sdMVFQ3qk/3v5gGY3LOdIjLLD6YL8m9IxyB4unE9Pwd1H12qbe13NEX0bT2eUxvldywHyZnmN+7oFeF3IcIvCANjAvl3Rpeeox+hcs6VYcPRbKw7koV1hzPR378M02OqmQDUj4lYEhUIMAGoAiSeogkCTABqAqv1NzWHAKTT6YJHxF8dCUgE3kMPPdREMDUEYElJCQIDA1FWVgYvLy8UFRXBycnJ+krqZMd58+bhtddeE9IsWrQI11xzjWaSMQGoGbS8sZ0QsPaHSzupwcc6IAL5JeXwcHUW/+pGQ3/+Jj0EW0/k1T+bOSQaL1zd2wGRYpVlRqC17+jSitrGHSLK71gO9p/Oh5l9OxAb3Lae8KMIWX+vlmtWy4w5y946BCqrqrH3VH4t4XckC/vPFOBCopPYONKrBvP7VDEB2DqYebWNEWAC0MaA83H1CDABKIkzmEsAkloHDx5E7969RTowpfhShJ+ra+N0JTUEIO3Vo0cPHDp0SKCVmZlpMqVYEjibFXPJkiWYNm2amEO1AP/5z39qphYTgJpByxvbCYHWfri0k9h8rIMiUFxWiRWJGfh931msP5qFN27oi2nxEfVoNPTnU2274tWVx8SznhG+uLpfJO4aZZuGUQ5qHlZbAwTMfUdT4w4iXIjwq23ckYfySvMad4T6uNen9FIDj3A//adpagA9b2kGAmkF57H+AuFH0X5FpZXNrn52QCWum8YpwGZAzFPtjAATgHY2gAMfzwSgJMa3hAAk1aZMmYLly5cLLTdt2oThw4c30lgtAUg18/bt2yfWUr1Bf39/SZAzX8yffvoJ1157rVhIkYAPP/yw+ZuoXMEEoEqgeJo0CJj74VIaxVhQQyJw+yfbseZwVr1uU3qG4f2bB9b/d0N/7jFoFPanl2BUXAhCfNwNiQcrZXwEWnpH05fG1OSGavgR6UfpvYUtkC+Xoubj4YJhsXWdeoPQKYQbdxjfs6yn4dGMIkx6Y71ZG94WV4VHbprENQDNQo0n2xMBJgDtib5jn80EoCT2t5QAfOWVVzB//nyh5UsvvYRHHnnEbAKwsrJS1MOjVGBfX1/RMMPIg7r//uc//xEq/vHHH7j88ss1U5cJQM2g5Y3thEBLHy7tJBYfywgoIvDdjlQ8smh//TOq27fzyYnwvdDcg/2ZHcdoCCj5NEVbiaYdIq03GxmFZWapTb83gzoEYHinYJHa2yvClxt3mIWgY06m6FJnp6Y0CJHQg19chawi037o5eYs/G14Rz/UpCUi2IObgDimF8mrNROA8tpOdsk1JQCra6qRX5ZvVYyIMKEadDSoOYPeatH5u/vDqY316+NZSgBSV+CJEycKvO644w589NFHZhOAVD+QGoHQuPPOO/Hhhx9abFNqXvLMM89YvJ4WNtewpFUbA0hLS0PXrl2Fj1Hn5NTUVHh4eLR2W5PrmQDUDFre2E4IMGFiJ+D52CYIVFfXYGdKHo5kFGHW0BhFhApKKjDwhRWoqKoRz4nI+PS2QaL7KA32Z3Yso7G+0p8AACAASURBVCFAPv3LH8txtKANzvtGY1tKPo5nFZulJnE2vdv7Y0Sn2ig/6nDdsHamWZvxZIdBoKS8UkSUrjtcW8tv5pAY3D1auYzC3O/3YdHu042w6dbOB2O6hmBMlxDhc+4uzlK+o7kLsMO4fLOKMgHIfmAvBDQlAHNLczHmuzH20s0u5667YR0CPQKtfralBODevXvRr18/Ic/VV18NSm9tOEylANMF8dixY/jss8/w5ptvgqIAQ0NDsWXLFsTGWl7zSM8EIH3jeNVVV+G3334TEFEU4D/+8Q+r27LhhkwAagovb24HBJgwsQPofGQjBKhD5HvrjmFxQhrSCkrh6twGO5+YBD+vxjVw6xbd98UulFZWYXp8BCb3DIPPheg/JgDZsYyCAN1vDqUVYXVSBlYkpiPhdAFqYN7Hz86h3oLwI3KcGnf4eSr/PhkFM9aj9QiQ3x3NPFdP+G0/kYvyqov1I0d2DsaXdw1RPOi3fWfx5M/7MapLLeE3Oi4E7fyafiEv452DCcDW+5YRdjDvDWwEjVkHvSDABKCVLaE3AjA5ORlxcXFCS4oEXLFihSIB2BIMY8eOxcKFC0UzkNYMaiBC/1oz3Nzc0KVLl9Zsobj2hRdewJNPPimejRs3DitXrtQ8wpQJQKubkTe0MwIyXsbtDBkfb2UECs5XYNDzKxt90FxwbTyuHxSleBJFCjoppKExAWhlw/B2NkWAuvVS045VhzKxOilTkOHmjHA/jwspvbVRfmG+2mVDmCMXz9U3AoWlFdh0NLu+Y29zfufm7IS9T0+Cl5tLE6Wo0Qy9ll2cm8+qkvHOwQSgvn3YVtIxAWgrpPmcSxFgAtDKPqE3AnDPnj3o37+/0PKaa67BokWLGmlcFwHYHAxU/4/SfmfMmGFltPSz3VdffYWbb75ZdEzu2LEjNm/ejHbt2mkuIBOAmkPMB9gYARkv4zaGiI+zEgL0vm7TRvkKfc/nO7E8MaP+pFFxwfjiTuVIk+bEYX+2krF4G5sgkF5QilVJGVh9KFPU8iutUN+tlyL6aht31BJ+HYPbmvz9sokyfIgUCNAXKIlphbWE3+Es7ErNA9X2Uzs+uW0QxnULVTu9yTwZ39FMAFpsbkMtZALQUOaUShkmAK1sLr0RgBTxN3nyZKHlXXfdhQ8++ECRAIyIiMCyZcvqn2VlZWHHjh144403kJ6eLi6B33zzDW644QYrI2b/7ZYsWSLSoysqKgTpt3HjRnTq1MkmgjEBaBOY+RAbIiDjZdyG8PBRrUQgo7BUpPb+vu8s/jo4CjcMilbckZ7/45s94lnXMB9c1S8S942JNZvQYH9upcF4uaYIEPmScKYAqw9lYFVSJg6eLVR9nmubGgzqGIhRXcJAqZg9InwVGzKo3pAnOiQCn20+iad/O6had2r6MSA6oL6WX49wX5MR2Go2lfEdzQSgGssafw4TgMa3sV411JQA5CYg1jO7pTUAFyxYUN/5lzoCz5s3T5EANNVY4+zZsxg8eDDOnDkjOgDv378f0dHKH7jUaKu3FGDClbr8lpaWIiAgAPTf8fHxalSxyhwmAK0CI2+iIwRkvIzrCD4WpRkEXl9xBG+vPoqaC8ElFKn01V1DFVdQsfn/rj2GafER6NrOx2Jc2Z8tho4XaoTAubJKbDyaJVJ71xzORPa5ctUnRQV6YmznIHgXpaCTbw2mXjYZnp6eqtfzRMdEoLKqWpDDShHXyZlFmPj6+maBifDzqCf8qIZkXZd1a6Ap4zuaCUBrWF7+PZgAlN+GsmqgKQGoBSh6IUy00K25PS0lACdNmiRq2dGgBh5Dhzb+sGSqCUhDWRYvXozp06eLH82aNQtffPGFxerrqQnI9u3bMWHCBJw7dw7e3t4CpyFDzE8RsxgMAHrx56NHj4pGLy4uLvU1I1ujF691XARkvIw7rrXk0nxJQhr+9vXueqGpPtTWxycg1Ee72mTsz3L5iFGlTc0pqU3tTcoUXVTrula3pC/9jgyMCcT47qGY2D0UnUK8xReey5cvF0spQ4QJwJZQdMznFG0t0nqPZGHj0Wx8ddcQ9Ir0awIGlWIY+fIanMk/X/+MavsNiQ0UzTvoHzWQMVWuobXoyviOZgKwtVY3xnomAI1hRxm1YAJQEqtZQgAeOHBARLPRH+eoqCgcP35cEDwNhxoCkOaPGjVKpMY6OTmJKEBLm4HohQBMSEgANTbJy8uDh4cHli5dKv7b1oMJQFsjzudpjYCMl3GtMeH91SFATQv2pOZjWKcgxQXny6sw8PkVKC6vqn/+3JU9cfOwDuoOsGAW+7MFoPGSViNAEVe7UvIE4UepvcmZ51Tv6evhgrFdQzGhe6ggX/y93BqtZZ9WDaVDTSyrrMKuk3n1pF9SelEj/f85pSv+Nq6zIiaP/bRfENN1hB+Rf0qNPbQAVEZ/ZgJQC0+Qb08mAOWzmVEkZgJQEkuaSwDSH8QRI0aAmoDQeOuttzBnzpwm2qolAOnb4ilTpoj1N910E6hphqzjyJEjGD16NDIyMuDq6opffvkFV1xxhV3UYQLQLrDzoRoiIONlXEM4eOsWECCiY8PRbFHTj5p2FJdXYutjE0x2HH3w2z1YeSgTk3uGYXqfCFG7zLWFLpGtMQL7c2vQ47XmIJBfUi7IF0rtXXs4E4WllaqXU4TVhG6hGN8tFANiAprtnMo+rRpWw0+kyNJ1RzKF320+loOSBl+uXKr84A6B+P6+YYqYEHno7uJsF7xk9GcmAO3iKro7lAlA3ZnEYQRiAlASU5tDACYmJoqOtrt316ZKjRkzBtQMhMiuS4daApDWDRo0CDt37oSzszOSkpLQubPyN4F6hjQ1NRUjR47EqVOnhB7ffvutXbsbMwGoZ29h2SxBQMbLuCV68hrrIEBRfwOfXwmqa1Y3/jWtB+4Y2VHxgMyiUlE/ysPVNh822Z+tY2fepSkClJ1BkX0U4Udde3em5EJt81RX5zYYGhskCD/6FxPUVjXE7NOqoTLcRIqipki9utTeE9nFqnV0cWqDvU9Phrd740wi1RtoNFFGf2YCUCNnkGxbJgAlM5iBxGUCUBJjNiQAZ8+ejfvvv79e8uLiYpHKSmmtq1atEmQfXSxpUM2/33//HcHBwYqamkMAUqQcdculcccdd+Cjjz6SBL1aMXNycjBs2DBQvTsa8+fPF0Rpc4Mag0RGRmqmJxOAmkHLG9sJARkv43aCio+9gMDD3+/FT7vP1OPRN8ofv/xthC7wYX/WhRkMIwRFSm07nnshtTcDp3Iv1k1rSclgbzeMu5DaOzIuxGIihn26JaSN+/zeL3Zi2cEM1QpSOvmouNo6fqO7hKCdn3b1VlULdclEGf2ZCUBLrW2sdUwAGsueMmnDBKAk1mpIAKoROSQkBA8++KAguS6t+9dwvTkEIJGKVFOQagtSNGFycnKrOgKr0cOac8zFkM6+9dZb8emnn1pTjEZ7MQGoGbS8sZ0QkPEybieoHOLYw+lF+G3fGcQGe+PaAXTlaDoo3fG2T3aIB23aAEM7BuGT2wfZLMqvOUOwPzuEm2qqJEWtrk3KEk08KN29uTTLSwXpGeFbm9rbPQzxkX5woq4erRzs060EUOfLyyur4ebipCjlF1tT8NQvB0xqQO9f8jNRy69rCPq09282nVwPUMjoz0wA6sFz7C9D69/m9teBJZATASYAJbGbKfKKmnL4+PjAz88PMTExGDBggGjYMW3aNLi5NS78rKSqOQQgrf/6668xc+ZMsRVFIS5cuFASBAEmAE2birsAS+PGuhdUxsu47kGVUMCViRlYsCwJRzJqmxf0ae+HX/8+UlGTiqpq3PnZToztEoJp8eEI9dVPlAn7s4TOZ2eR6cvSg2cLa6P8DmVg3+kC1RK5uziJupbUtZdSe8P9PFWvVTuRfVotUnLMq66uQWJaYX1a7/Gsc6KOqotCbVSq+Tf6lTWNFAtq61ZP+JHvBXm7y6H4BSll9GcmAKVyMc2EZQJQM2h54xYQYAKQXYQRsCMCHAFoR/D5aE0QkPEyrgkQDr4p1Zi69ePtjVBY98+xZtUq0wOE7M96sIL+ZaDaapuSs2vr+SVlIKOwTLXQ4X4eguyjrr3DYoPh6aZtfUv2adWm0e3E3OJybDiaJUi/9UeykX2usb8tmj0MA2ICFeWf9Po6BHi5iQg/ivTrEe5rlchSu4CVdxJlmcn4M6m2luHkyZPh6Wl90tzaujEBaG1E5dyPCUA57WYEqZkANIIVWQdpEWACUFrTseAmEOAPl47jGgUlFfDzatpcihCg7r6DX1wF+qBaN+ZN7oK/j4+TCiD2Z6nMZVNhz+SfF1F+qw9liA6qZZXVqs6nNEuqc1nbtTcM3cN90IZ+aKPBPm0joK14TFV1Dfaeyq+P8ks4nY8Lpb4VT5kzvjMentxV8RlFXGvZOd2KaitvdT4fOLAISPgeOLUV1X5R+L3j86J+BBOAmqPPB1gRAdu99a0oNG9lCASYADSEGVkJWRFgAlBWy7HcphDgD5fG9o3C0gosP5iB3/adFRFPKx8eg47Byh1In/xlP77cmgqKcJreJwLX9I9Et3a+UgHE/iyVuTQVto6EoQi/VYcykZRepPo86pw6ukuwIPzGdg1BsB3TLNmnVZvNrhMzC0vrCT+qHVlwvkK1PP2j/fHT/fpopKRaaLUTz+4F/jem0ewNcU8g17srE4BqMeR5ukCACUBdmMEhhWAC0CHNzkrrBQEmAPViCZbDWgjwh0trIam/fai22ciX14Ain+rGw5O6YM4E5ai+Y1nnRATggOgAaVPM2J/154e2lIgI7w1HKLU3A2sPZzWKaG1JjpggL0zoFiZSewd1CDTZmKGlfaz9nH3a2ohafz8im/s/t8Is0o++iBHNO7qEYEhsILzcXKwvmB52pNDHhUOA7MP10pwIGoeE6NuZANSDfVgG1QgwAagaKp5oZQSYALQyoLwdI2AOAkwAmoMWz5UBAf5wKYOVLJfx6V8P4LMtKfUbdA71xoqHRts0hdFy6c1fyf5sPmayrziRXSyad1B67/YTuaisrlGlkrNTGwzqECBIP2riERvcVpe/F+zTqsxpk0mlFVUmu53/7avdWLI/zaQcnq7OGN4pqL6WX0yQciS2TRSx5iEZiUDCd0DPq4CIfso7r38VWP2ceFbjEYCjfiNwKOJ6JgCtaQfeS3MEmADUHGI+wAQCTACyazACdkSACUA7gs9Ha4IAf7jUBFabbEpRJ9uO56CkvAoTe4QpnrnzZC5mvLel/pmHqxNWzx2LCH/9F163BET2Z0tQk2sN1UTbcTIXqw9RA49MHM+ubSigZvh7uWJc19qOvaPjQkzWxFSzl63msE/bCumm51CzmK0ncrDuMDXvyEJsiDc+vHWgokDf7ziF+YsSGj3rGuZTT/gN7BAAdxdtG8bYFKm93wBbFgIZ+2uPHXQ3MPVVZRHyUoAVTwHxN+J8+xFYvmqtmMc1AG1qMT6slQgwAdhKAHm5xQgwAWgxdLyQEWg9AkwAth5D3kFfCPCHS33ZQ400KTnF+GTTSRFtklVUhtiQtlj18BjF6KXq6hqMf20tKPKP6vpN7B6Gtu4GTTUDwP6sxoPkm0Op6WsPZ4quvUTEFJVWqlaiS5i3qOVHqb39ovzh4uykeq0eJrJP284KVDbhWFZxfS0/+oKlYbMYLzdn7P3XZMX08PSCUkx+Yx1GxgWLtN7RXUIQ7mfML1qERda+DKx98aJxPAOBeUcAZ+VGU3UTZfRn7gJsu99BPZ/EBKCerWNs2ZgANLZ9WTudI8AEoM4NxOKZjYCMl3GzlTTYgt2pebjm3c2NtFoyZyR6Rvgpaip9F0kz7Mf+bAZYOp5KRMyRjHOilh818NiTmgeVmb1wc3bC0E5BF7r2hiIq0EvHmrYsGvt0yxi1ZkZZZRW2Hs/FysTaNPKGNVOV9v367iEY3ilY8UiKyqbUcsMMqt9nquN17nHgP5ek/P71O6DrZc2qL6M/MwFoGI9ulSIG+s1uFQ682PYIMAFoe8z5REagHgEmANkZjIaAjJdxo9nAXH2UmnvcOyYWj13e3dytDDef/Vlek1J9ta3HcwQJQ6RfS0RMQ01DfNwxnlJ7u4diZOdgQ0W5sk9b36fzS8qx5nAmViRmiPTe4vIq1Yf8Y3xnzJ3cVfV86SYS6Xd6Z21dv5Mbgfs2As4mosY/nASc3g74hAO9rwMG3AYEdWICUDqjs8BqEGACUA1KPEcLBJgA1AJV3pMRUIkAE4AqgeJp0iDAHy71Zaqz+eexOOEsftt3Fi9dE49ekcpRfS8tTcJ7644J4XtG+OKWYTG4YVC0vpSxgzTsz3YAvRVHZhSWYg0RfkmZ2Hg0G+cr1BMxvSP9RC0/Su3tFeEnbefqluBjn24JIfOeJ54txPR3NoKi9dQMCujrHx1Q27G3a4ihfQ2lhcD/xgAU3Vc3Zi4C4iYqQ3V8Xe3PO4wEnNTVN5TRnzkCUM1vivHnMAFofBvrVUMmAPVqGZbLIRBgAtAhzOxQSsp4GTeqgR78dg9+2Xu2Xr17Rsfi8SuUo/qOZhRhcUKaqOtH9f141CLA/qxvT6CalAfOFogIP4r023+mQLXA1EWV6qtN6BaKcd1CEebroXqtzBPZp61rvcqqagx6YSXySipMbtzO16Oe8BvRKViKZjFWQ+mD8cCZXRe36309cO0HVtteRn9mAtBq5pd6IyYApTaf1MIzASi1+Vh42RFgAlB2C7L8lyIg42XcqFZc8GcS3l1bG9VHI9zPA5seGW/YyCYt7Mj+rAWqrduzuKwSG5Oza7v2Hs4UjWvUjkh/TxHhR5F+Q2OD4OGqLspI7f4yzGOfVm8l6tpLvkb1/IZ3DsKVfSMVFz/8/V78tPtM/TMqc9c3yl80SSJ/o+69bUzVvlMvjj5nlpcAZUWAj3LneGx7H1g6/6Lsrm2B+ccAV+s0NJHRn5kA1Kcr21oqJgBtjTifV4cAE4DsC4yAHRFgAtCO4PPRmiAg42VcEyBssGlJeSVOZBebbNaRlF6Iy97c0EiSH+4bhkEdAm0gnTGOYH/Whx1P5ZbU1vJLysTWYzkor6pWJVhduiXV8pvQLQzUwdewRIwqRDiqtSWYMotKBbm88lAGNhzNru/aO65rCD65fbDi8j8PpOGBb/diVFwwJvUIExGloT4GjiitrgJOrAcSvgcO/QZ0nw5c/Z4ytOeygNe6AgEdgPgbgPjrgMDYlsyg+rmM72gmAFWb19ATmQA0tHl1rRwTgLo2DwtndASYADS6hR1PPxkv47JZiUi/TzadwI+7TsPXwxWbH1WO6qPmHpPfWA+qi3Z5r3CR3js0NhAuzk6yqWw3edmf7QM9pVXuOZV/IbU3Q3TwVTt8PFxEuiVFXo3pEorAtm5qlzrEPPbpxmau6xBNhB818dh7Kl/RD9xcnLDnqUmKDWGo8291NeDp5iARpds/AP6YdxEnN29g3hHAra3y71D2USCos+kOwK34zZPRn5kAbIXBDbSUCUADGVMyVZgAlMxgLK6xEGAC0Fj2ZG04ukRrH9iVkosZ720BNVasG9/dMxRDYoMUjz6ZXYxwfw+4uzjIB1MrG0DGD5dWhsBm2xWcr8D6I1lYdSgDa49kIb+ZmmqXChUb3Fak9VKkH0W4ujLJbdJu7NNARVU1dpzMxcrE2ki/1NwSVX7+3qz+uKxXuKq5hp5UlA683h2oaRCJe+1HQO8ZNldbRn9mAtDmbqLLA5kA1KVZHEIoJgAdwsyspF4RYAJQr5ZhuSxFQMbLuKW62mMddZoc++oanMo9X3/8rKHReP6q3vYQx/Bnsj9ra2Kq50cEzO/70gT5pza118WpDQZ3DKwl/bqFIjaEG9eotZQj+/Th9CK8uzZZdIouLK1UBZmzUxsM6hAg6vlNjQ9HuJ91atepOtxek87nA4d+ryX0TNXq++Jq4NjqWgnbOAGj5gLjn7S5xDL6MxOANncTXR7IBKAuzeIQQjEB6BBmZiX1igATgHq1DMtlKQIyXsYt1dVe6z7eeALPLk4Ux9OH02nx4Xjrxn72EsfQ57I/W9+8pRVVWHckC7/vOytSfM9XVKk6hFJ5x3YNEbX8RnUJFunvPMxHwJF9+sCZAkx7e2OLoHm7u2BM1xBM6h4mfM7fy0HSyA8vBfZ9Axz+E6gqA677FOh5tTJe+74FtiysrevX61rA1z6RkTL6MxOALf4KOsQEJgAdwsy6VJIJQF2ahYVyFASYAHQUSzuOnjJexvVkHUrZpfp+kQGeuGd0J0XRzpVVYsob6wXxd+vwDojwd4CIFDsZif3ZOsBTyuWm5GwR6bf8YDqKytRFX3Vr53Oha2+Y6KpKhDeP1iFgZJ+urq7BgbMFaOfnodiEg+r9jXhpNc4WlDYBMcLPAxN7hIkmHkM6BoFq/jnc+Gx6bXOPutH1CuCv3yjDQHUodNDZWEZ/ZgLQ4X6zFBXmv2bsB/ZCgAlAeyHP5zICAJgAZDcwGgIyXsb1YIMjGUV4ddlhrDiUIer7BXu7YeMj4+Hhqly7j1KBmQzR3nLsz5ZjTD66/UQufk84i6X705Cnoqafm7MThncOwoTuYSK1N5LJbcsNYGKl0XyaIkq3HM8RDTyofmRGYRkev6KbyS9Q/vXrAXy+JUWg0zvST6T2TuwRih7hvg7fIRp7vgR+/dtFz3FyAeYeAdoq15i1unNasKGM/swEoAWGNuASJgANaFRJVGICUBJDsZjGRIAJQGPa1ZG1kvEyrgd7HTxbgKn/aZyatmBGPK4fGKUH8RxWBvZn80xPEVbUvZfSe5ckpCGzqKzFDYjIHtE5GNPjwzG5Zzv4eXJqb4ugtWKCEXw6t7gcq5MysTIxA+uPZqGkvHEa+eAOgfj+vmGKKO0/XYB9p/NFZKlD1POrQ+FcJnDgJ+BcBjDxaWUPKi0EXo0DKksBJ1egyxRg8nNAYGwrPE7bpTL6MxOA2vqELLszASiLpYwnJxOAxrMpayQRAkwASmQsFlUVAjJexlUpZoNJN32wFZuP5dSf1DPCF0vmjLLByXyEKQTYn1v2DSL9DqUViUg/Iv5O511sUGNqNWUOEkkzvU8ELu/VDkHe7i0fxDOsgoCsPn0865xoGEOde3em5KK6QSf0S4GhTPGdT04C1Y10+JFzDFj6SG3DjpoqwNkNmHcE8AxQhmbdAqBtCNDjSsArUPfwyejPTADq3q1sIiATgDaBmQ9RQIAJQEncYu3atRg3blwTaZ2dneHr6ws/Pz9ERUVhwIABGDlyJKZPnw43t5YvPh06dEBKSm0qRMPh4uIi9oyLi8PYsWNx7733gubKPkjX5cuXY/v27di3bx8yMjKQlZUF+gATHByMfv364brrrsONN94IV1ftoxCYAJTdo1j+SxGQ8TJuKytSfT+KdooK9FI8cnVSBu74dCd8PFxw0+Bo3DK8A6dA2so4Js5hfzZtgGNZ5wThR/+OZRWrshTV8SPSb2rvcFGnjYftEZDFpymFfE9qnkjtpdIIx1X6GCHaIcgL//lrP8S397c9wHo7kTr6UlRfVflFyaa/BQy4TW+SWiSPLP7cUDkmAC0yteEWMQFoOJNKoxATgJKYyhQBaEr8kJAQzJkzB48++iiIzDM1TBGAl8739PTEe++9h1tuuUUSxJTFfPLJJ/HCCy+0qEPv3r3x66+/omPHji3Obc0EJgBbgx6v1SMCMl7GtcSRvlzYcTIPH244Lj7EXt0vEq9f31fxSCpg/+Ou07giPhzUhZKH/RFgf25sg1O5JVickCZIv8S0QlUG6h7ui+l9wjGtdwSig5TJb1Ub8SSrICCLTzfsdt6S4hRR2j86QNTzoyYenULaOlY9PyocW1MNOCnXjMV3NwOHfrsIY8wI4PY/WoJViuey+DMTgFK4k02FZALQpnDzYQ0QYAJQEndoSADOnj0b999/f73k586dQ15eHhISErBq1SqsXLlSRLTRGDx4MBYvXgwiBJVGHQEYERGBZcuW1U+hP6jJycn44osvsHTpUvFzijbcsGEDhg1TrqsiA5T/+te/8Ntvv4koyb59+yI8PBxhYWEoKirCsWPH8Mknn2Dz5s1CldjYWIFp27ZtNVONCUDNoOWN7YSAjJdxLaH6cmsKnvzlQP0Rrs5tsOmR8Qj15egnLXG31t7sz0BmYWkt6ZdwFntS81VBGxvcFtP6ROAvfcLROdRH1RqeZBsEZPHpE9nFGPfqWpOgeLo6Y1RcsOjcSw1jgh0xjTwvBdj/A5DwPTD8H0D/m5XxOrQY+G4m4OoFdJ8OxF8PdJ5oG4fT+BRZ/LkhDBwBqLFTSLI9E4CSGMqAYjIBKIlRGxKATz/9NP7973+blDwxMRGzZs3Cnj17xJwRI0Zg9erViinBdQRgTEwMTp48qbjn3Llz8frrr4tnU6dOFYSirKOysrLZiEjS68EHH8Rbb70lVKT/pUhKrQYTgFohy/vaCwEZL+NaYpVzrgzDXlqN8srq+mP+Pq4z5k3pquWxvLeVEHBUf84rLsfSA+ki0m/riRzRmbqlQR17p/UJx/T4CFD9yjYUlsVDdwjY26fpC+qk9CLRwINq+r1wdW/0ivRTxGnCa2sbpZeH+LhfiPILxfBOwSa7pOsOdC0EWvUssOG1izt3HA3c+rvySZVlQOJvQNfLAXdvLaSx25729mdLFGcC0BLUjLeG/0Iaz6ayaMQEoCSWMocAJJXoDyIRf3UkIBF4Dz30UBNt1RCAJSUlCAwMRFlZGby8vES0nJOTkyTImS9menq6iAykMWPGDPzwww/mb6JyBROAKoHiadIgIONlXGtwH/spAd9sPyWOofp+946Oxd/Hx2l9LO9vBQQcyZ+LSiuw/GCGiPTbeDQblc11WbiALREyVM+P6vr1j/Zn0s8KPqf1FvbwafoCZPuJXEH4UU2/M/kXG8U8MCEOD03qoqj2S0uTsPZwpiD9KNIvPtIPTtThgwdw8Bfgh1sb7Zg+iwAAIABJREFUINEGeOgg4BfpUOjYw59bCzATgK1F0Bjr+U1mDDvKqAUTgJJYzVwCkNQ6ePAgqJYdfdtKKb4U4XdpYws1BCDt1aNHDxw6dEiglZmZaTKlWBI4mxWzuLgY3t6135BOmzYNv/9u4htVKyjLBKAVQOQtdIWAjJdxSwFsWN/vmv7tcVmvdopbHc0owp2f7cTtIzrguoFRXN/PUsDtsM7o/ny+vAqrkjJEpN+aw1mNIlVNwe3v5YrLexHpF44hHYNEYxse8iBgK58uOF8hyLuVhzLF/xaVViqC1Fy388qqarg4G/cL52a9proayDwItOutPK2itLa5R1mDWpyXvwIMuUceZ7SCpLbyZyuIWr8FE4DWRFPevfgvp7y2k11yJgAlsaAlBCCpNmXKFNH1lsamTZswfPjwRhqrJQCpXh51zaVB9Qb9/Y3bWe2jjz7CXXfdJXSdN28eXnnlFc28hAlAzaDlje2EgIyXcUugWn8kC68sO4z9ZwrE8oExAfhxduP3a8N9qcEHR65YgrR91xjRn8sqq7DhSLaI9KNorJLyqhZBpqY0k3uEiUi/kXHBcHVUUqZFpPQ/QUufpiYx5FMU6UcRf2qiSAmxzY+OR4S/p/7Bs4WEmUlAwne1tf0KzwAPJQK+tVkpTcavfwcO/Q70ugaIvwGIGgI4WOq9lv6slbmZANQKWbn2ZQJQLnsZSVomACWxpqUEIJFX8+fPF1q+9NJLeOSRRxpprIYApLp5fn5+oFRgX19fFBTUfuA10iBSkyIkqenJO++8g4qKClEzkaIeqRmIVoMJQK2Q5X3thYCMl3FLsPp17xk88O3eRkt/vn84+kUHWLIdr9EpAkbxZ4qk2nI8R0T6/XkgHYUmorEamsHdxUmkXlKk39iuoY5db02n/mmJWFr49M97TuO9tcdxOKNItUhUM5I69tK/wR0DmVQm5Ciq75VOQPm5izhOfgEY/ndlXItzAHcfwMVNNe5Gm6iFP2uNEROAWiMsx/5MAMphJyNKqSkBWFNdjap8dR3j1IJLhAnVoKPh4+Oju1p0zv7+aKNBfTxLCUDqCjxxYm2nrzvuuAMU3dZwqCEAqX4gNQKhceedd+LDDz9Ua64m86h5yTPPPGPxelrYXMMScza+7bbb8NlnnykuoVqHRAZec8015mxp9lwmAM2GjBfoHAEZL+OWQFpRVY1RL69BemFp/fJr+kfi9ev7WrIdr9EpAjL7M0Wd7kzJE6TfH/vTkFNc3iLK1KV6TJcQEek3oXsYp6u3iJh8E7Tw6a+2peCJny92OzeFSp/2frVNPHqGoWuYD9eMVALq59nAvq8vPmkXD9y3QT5Hs5HEWviz1qIzAag1wnLszwSgHHYyopSaEoCVubk4OnyEEXEzqVPc5k1wCQy0us6WEoB79+5Fv379hDxXX301fvrpp0aymSIA6Q/qsWPHBEH25ptvgqIAQ0NDsWXLllZFxMlAAN54441YsGABoqKirG7HSzdkAlBziPkAGyMg42VcCaK6+n70IdXPy1URxffWHQMVqY8K9MQdIzpyfT8b+5otjpPNn8lvKS39t71nsTghrRFBbQovKuE3onOw6N47pWc7k/5uC7z5DO0RsMSns8+VYe3hLFzVN0KxJl9GYSmGvLiqifBuLk4Y2TlYkH4TuocizNdDewX1fEJVBXBsDdDGCYir/XK+yaDnX1x18cch3YE7lwEeyp2S9ayuLWSzxJ9tIVdzZzABaG8L6ON8JgD1YQdHlIIJQCtbXW8EYHJyMuLiartNUiTgihUrGmlcRwC2BMPYsWOxcOFC0QykNYMaiNC/1gxKze3SRbljnDn7njlzRtQzpFFYWIiEhAR88MEH2L17N0aOHImPP/64Hjtz9jVnLhOA5qDFc2VAQMbLeENcKbKPoqU+3HBCECmPXt4N943ppAh9QUkFNh/LxuSe7bgRggzOaYGMsvjz4fQiEelHdf1SckpUaTqoQ4CI9KOGHtTNl4djIKDGp4lIPpZVLGr5rUzMwK7UPNTUAN/dMxRDYoMUgbrynY3Yd7oAgW3dML5bqCD9RsUFo627i2MA25yW2UeB7R8ABxYBJdlARH/gnjXKK6qrgA8nAh1G1Nb1C+vlcHX9zHEYNf5szn62mMsEoC1Q1v8ZTADq30ZGlZAJQCtbVm8E4J49e9C/f3+hJaWzLlq0qJHGaghAqv9Hab8zZsywMlr6266qqgp/+9vf8P777yMgIABr1qxBnz59NBOUCUDNoOWN7YSAjJfxhlA98fN+fLUttf5H7Xw9sOGRcVyfyk7+ZO9j9ezPJ7KLsfgC6Xcko0HNsGZAi2/vJyL9psaHc9MFezuXnc435dNUJ3JXSl4t6XcoE+Rfl467R3XEE1OVvwjelJwNivjrHx3AX4hcClzySuDLaxv/9O87geDaL+h5WI6Ant/RprRiAtByextpJROARrKmXLowAWhle+mNAKSIv8mTJwstqbMtRbg1HHUEYEREBJYtW1b/KCsrCzt27MAbb7yB9PR0Uaflm2++wQ033GBlxPS3XXl5OTp37oxTp05h2LBh2Lx5s2ZCMgGoGbS8sZ0QkPEy3hCqvafycdXCTY3Qe+vGvriyb6SdEOVj7YmA3vz5TP55LEk4i9/3pdV3oG4JH0pjp0Ye0+Ij0CG4bUvT+bnBEWjo0yPGjMf2U+dElN/qw5nIL6loVvsOQV5YM28s1+4z10eqKoHXuwPFDTJgRs8Hxj9h7k48/xIE9PaOVmMgJgDVoGT8OUwAGt/GetVQUwKQm4BYz+yW1gCkWnZ1nX+pI/C8efMUCUBTjTXOnj2LwYMHg9JlqQPw/v37ER0dbbFiekoBbk6Je+65p54spT/UkZHafPhnAtBiV+KFOkVAxsv4pVDO+O9m0TyBBtX3e+SyboI84eF4COjBn7OKykRaOqX41vllS5aICfLCX/pECL/t2s6npen83IEQSMnMxzs/r8eBvDZILnJGRVWNKu293JwxOi4Er9/QB15unNbbCLSidGD3F8CA2wDvEGU8/3wM2Ppu7bP2g4Ah9wG9jZ9Zo8q5WjFJD+9oc8VnAtBcxIw5nwlAY9pVBq00JQC1AEAvhIkWujW3p6UE4KRJk7By5UqxNTXwGDp0aKNj1HQBXrx4MaZPny7WzZo1S3THtXToqQlIczo88cQTePHFF8UUigCkSEAthl78+ejRo6LRi4uLi+Z1D7XAkffUDwJ6vozX1ff7eOMJvHpdH8SFKRMjS/en4aONJ3DXqI6Y1IPr++nHu2wvib38Ob+kHMsOpotIP6ozWa2Cown388C0+HBR1693pB9HadneXaQ48ZaPtmL90RxVsob5uotafhN7hGFYbBA8XJ1VrXOYSSfW19b2S1oC1FQBE58BRj6orH76AeDQ70D89UCQcl1Zh8HNiora6x3dGhWYAGwNesZZywSgcWwpmyZMAEpiMUsIwAMHDiA+Ph5UzJk62h4/flwQPA2HGgKQ5o8aNQobN26Ek5OTiAK0tBmILATgbbfdJjog06DmIL1799bEU5gA1ARW3tSOCOj1Mv7l1hQsXJOMtIJSgc5fB0fh/66JV0SK3plU9oAHI2BLfz5XVilSMSnSb/3RLFWRWcHebriidy3pNyA6AE7U0pcHI9AMAt9sOY7Hfj1kckb3cF9M6hGGSd3D0CvSl9+FzXnTz/cB+765OCOgA/CPPYCTE/ugjRCw5TvaWioxAWgtJOXeh/9ay20/maVnAlAS65lLANIfxBEjRoCagNB46623MGfOnCbaqiUAly9fjilTpoj1N910E7766itJkDNfzOLiYsTGxopuxZ6ensjJyRH/q8VgAlALVHlPeyKg18v4q8sO4501yfXQULH6LY+OR5A3dz+1p7/o/Wyt/bm0ogprkjJF995VhzJRVlndIiS+Hi6icy+RfkNjA+HizGRDi6A5yIS84trI0bWHs/DOTf0UfSMzrwjDFqxDVU3tx08XpzYY1ilIRPpN6B6K9gFeDoKWFdQ8tR34aFLjjWYtAjpPtMLmvIUaBLR+R6uRwdw5TACai5gx5zMBaEy7yqAVE4AyWAmAOQRgYmIibr75ZuzevVtoN2bMGFAzEFdX1ybaqiUAaeGgQYOwc+dOODs7IykpSTTKkGlkZ2dj3bp1uPbaSzqxNVCitLQUt956K77//nvxU8Lx888/10xNJgA1g5Y3thMCer2MZxaWYsTLqxtFVT1xRXfcPTrWTkjxsTIgoIU/l1dWY2NylkjvXX4wHcXlVS1CQfXXJvcIE6TfqLgQ0W2VByNACBSUVGB5YjoWJ6SBOvFWXsgX/+LOwcJXLh3k07csXAkq/TdzbG9M6h0JX4+m90NGF0BpAZC8Cuh1jTIcNTXAeyOBjAOAq1dtTb9h/wBCujB8NkJAi3e01qIzAag1wnLszwSgHHYyopRMAEpi1YYE4OzZs3H//ffXS04Ra3l5eSJVddWqVYLsoxQ2GlTz7/fff0dwcLCipuYQgL/88guuvvpqsc8dd9yBjz76SBL0asU8efIkOnbsKIhLIgGpuQk193B3dweRg9u3bxc6Uao0DXpGnZDDw8M105MJQM2g5Y3thIC9LuNU348iqIgkMZUGOff7fVi0+zQGxgRwfT87+Ydsx1rLn6uqa7DteI6I9Ft6IL3FbquEE5F847uGCtJvfLdQeLpx/TXZ/EcreYtKK7AiMQNLEtJMpovfMDAKL89oWubAWj6tlW662PfMbmDnx8CBRUBFCTB7CxDWQ1m0g78AxVm1tf08/HQhviMJIaM/MwHoSB5qWlcmANkP7IUAE4D2Qt7McxsSgGqWhoSE4MEHH8T8+fOb1P1ruN4cApBIRaopSLUFKZowOTm5VR2B1ehhzTl1BKCaPanpx5dffilSgbUcTABqiS7vbQ8EbH0ZLzhfgW+3p+LTzSdFfb+PbxuI8d3CFFU/mV2MvJJy9IsOsAc0fKaECLTGn6ura7DnVJ6I9KPorOxzZS0iQOmYo+KCBelHddh8ODKrRcwcZQLViFx1KEP40rojWaBI0uaGn6crdjwxsUm0aGt82iGwrqoA3ugJnMu4qO7ge4ArXnEI9WVTUkZ/ZgJQNi/TRl4mALXBlXdtGQEmAFvGSBczTBGA1JTDx8cHfn5+iImJwYABA0TDjmnTpsHNza1F2c0hAGmzr7/+GjNnzhT7UhTiwoULWzxDLxOIbKMU5jVr1ohU4BMnTiAjIwNFRUXw9vYWZObAgQNx3XXXiXqHtmgCwASgXryD5bAWAra+jF/z7ibsTs2vF394pyB8fXfjbufW0o33cTwEzPVn+qLs4NlC0ciDiJoz+edbBI36zVCHVSL9LuvZDgFtW/7b3eKmPMEQCJSUV2J1UiYW70vDmsPqakS6U+Rot1BMi4/A5J5hcL2kRqS5Pm0IIM1VYtVzwIZXL65y9wUePgS4e5u7E8/XGAEZ/ZkJQI2dQpLtmQCUxFAGFJMJQAMalVWSBwEmAOWxFUuqDgFbX8Z/2HkK//wxoZFwS+aMRM8ITsVSZzGe1RwCav35aEaRIP1+T0jDiexiVaAOiAnA9Phw0cU31NdD1Rqe5FgIPPTdXvy850yLSlO6+NguIZgaHy6aebR1dzG5Rq1Pt3iozBMqSoG8E0Bod2Ut8lOBNyl9ugZwcgG6TQWm/B/gFymz1oaUXUZ/ZgLQkK5otlJMAJoNGS+wEgJMAFoJSN6GEbAEASYALUGN1+gZAS0u4xRVZSoit6yyCiNeWlOfXkn1/Z6c1gN9o/z1DBPLJgkCzflzak6JqOlHxF9SepEqjXpG+IpIv2nx4dxtVRVijj3pzwPpuO/LXYoguDq3wei4EEzrU0v6qU0X1+IdLY2Vco7V1vbb+xXg7gPM2Qs4mait+fsDgG97oP/NgE87aVR0NEFl9GcmAB3NS5X1ZQKQ/cBeCDABaC/k+VxGAAATgOwGRkPAmpfxuvp+P+0+g0X3D4e3iaiWhWuSkZhWiLtGduT6fkZzKDvrc6k/F5S3wWIi/RLSsO/UxdTz5sTsFNIWf+kTKYiaTiGcQmhnk+rmePryYuPRbBDJ9+yVvRSbvJRWVGHg8ytB9f9oUI3IkXHBmNo7HJN7tgPV+TN3WPMdbe7Zdp2fmQS8O6SxCDN/BOIm2VUsPrx1CMjoz0wAts7mRlnNBKBRLCmfHkwAymczlthACDABaCBjsioCAWtcxini79nFifhuxymUlFeJff81rQfuGNmRUWYEbIoA+fNPS5Zjb04bnKgOwq7UfNTUtCxCVKAnpsdHiGi/bu18bFJTtmWpeIa9EaBu5RuTs0X33mUH01FUWkvsvTuzv0gFVxrzftiHjMJSETU6uUfra0Ra4x1tbxwtOp9+cd8fBaTvv7i861Tgr19btB0v0gcCMvozE4D68B17S8EEoL0t4LjnMwHouLZnzXWAABOAOjACi2BVBKx1Gb/n851YnnixCyMRKmvnjYOzE1+ZrGow3kwRASKhtx7PxWebjws/rK5p2e/CfN1F4wUi/fq092PSj31LIFBZVY0tx3NEI49lienIL6loggxF9C2c2d+kL1qzKZm13tG6NG91FVBeDHj4KotH6b+LH7r4rNME4KbvAWfTNRN1qScLVY+AjP7MBCA7MCHQ8q2CcWIEtEGACUBtcOVdGQFVCDABqAomniQRAta6jG8/kYvr39/SSPMv7xwi0t94MAJaIUBp5z/tPo2vtqUiOfNci8cEtnXD5b3aCdJvcIdAODFB3SJmjjChqroG24j0258mUnxzi8ubVdvD1Qm7npzUbPMOa+FmrXe0teSxyj5F6cDuL4DdnwFxk4FprytvW1YE/Hc40P0vwMA7gKBOVjmeN7EfAjL6MxOA9vMXPZ3MBKCerOFYsjAB6Fj2Zm11hgATgDozCIvTagTUXsaJaNlyLBuX9VJOe6MIrCsXbsLBs4W4rFc73DmyI/pHB7RaPt6AEVBCYP/pAny5NQW/7TuL8xW1aeemho+7C6ZcIP2GdwqCq7MTg8oIgEi/nSdzsTghDUsPpNc3JmoJGmpcROm91w2MYgKwJbAUf3l/BH6+F6iuTaeGmzcwN6m2yYfSqK4GnPh31hKo9bhG7Z1DT7IzAagna9hPFiYA7Ye9o5/MBKCjewDrb1cEmAC0K/x8uAYItHQZT8kpxiebTuL7nacE0bJm7lh0CG6rKMmBMwXw93Llbqka2Im3BM6XV4kuvl9tTcG+0wXNQuLapgaTeobhqn5RGN0lBB6uJjqHMrAOi8DzixPx4cYTqvTvF+0vGnlMjQ9HuJ+nqjXWmtTSO9pa59hsn/xTwFvxQE31xSOnvQkMvN1mIvBB9kNARn9mAtB+/qKnk5kA1JM1HEsWJgAdy96src4QYAJQZwZhcVqNQHOXcep6OfiFVaDov7px67AYPHNlr1afyxswAmoROJZ1Dl9tTcWPu06h8EITBlNrOwZ5oa9PEQaH1OCqKybD09O2ZI1anXie/RHYnJyNmz7cZlIQqgtJhB81+2gf4GU3gWUkTOo777Qx8ZH56xuBI0svYtrnr8DV79kNYz7YdgjI6M9MANrOP/R8EhOAeraOsWVjAtDY9mXtdI4AE4A6NxCLZzYCLV3GX/zjEP63/nj9vl5uztjy6AT4ebmafRYvYATUIkDdV1ckZog0383Hcppd5uLUBpN7hmHWkBj0jfDCihUrxPzJk5kAVIu30eZRSYL9ZwpE997ZYzvB38utiYrU7GPo/61C9rmL9f56RviKxjAU7RcdZD/Sr6GwLb2jdWW70gJg33cANe+Y9CzQZbKyeEeWAz/cCvS6tra2X6RyQxVd6cbCWAUBqfz5gsZMAFrF9NJvwgSg9CaUVgEmAKU1HQtuBASYADSCFVmHSz9cLlu2HBSooUSYnMk/j9EL1oh6WdTRl+r7PXFFd0T4c2QVe5L1ETibfx7fbk/FtztOIbOorNkDwv088NfB0bhxUBRCfT3EXBk/XFofRcfckUg/qkG6ZH+aIP5Sc0sEEAuujcf1g6IUQXnqlwPYcTJX1PSbGh+BjibKG9gTUWl8esPrwPpXgIpa3NHlcuCmb5Who+6/1ODD09+e0PLZdkBAGn9ugA0TgHZwFB0eyQSgDo3iICIxAegghmY19YkAE4D6tAtLZRkCVFPtPyuTsHT3CTzYqwpTpihHTD3+8360dXPGrcM72DUVzjIteZXeEaiursGG5GwR7bfqUAaqa0xLTET16LgQzBwSjfHdQuFySUMPGT9c6t0+epaPSL/DGUVYvC9NEH8nsoubiEs1ID+/Y7CiGuWV1XBz0XeDCWl8etenwO8PXMS5jRPwQALgr0y+6tmvWDbtEJDGn5kA1M4JJN2ZCUBJDWcAsZkANIARWQV5EWACUF7bseQXEaAPzSsPZeKZ3w/idN558WB29yrMuX4S10xjR7EZArnF5fhh5yl8vT0VKTkXooZMnB7Y1g3XDWyPmYNjmk3NlPHDpc0AN9BBR4n0S0jD4oSzOJbVlPRrqCpFLu94YiLIh2Qc0vh02TngtW5AedFFmCc+A4x8UEbYWWaNEJDGn5kA1MgD5N2WCUB5bSe75EwAym5Bll9qBJgAlNp8LPwFBPKKyzHy5dUoLq+qx6S7fzV+emAiE4DsJZoiQOTz7tQ8fLk1VURsUQRWc2NATABuHhojUs/VdPKV8cOlpoAbaHNqBkOpvfSPov7UjJggL5Hee/uIjgj2dlezRHdzdOHTFaXAod+AvV8D138OePgq47RkLrDzE6Db1Nquvh3HAk76jrDUncENLpAu/NlMjDkF2EzADDqdCUCDGlYCtZgAlMBILKJxEWAC0Li2dTTNPtxwHM8vOVSvthNqsPqhkegQxjWZHM0XbKHvubJK/LLnjEjzTUpvnryhdPOr+kVi1tAYdA83QTSYEFrGD5e2wF/2M/63/hhe/CNJlRrtAzxFIw8i/qipRxtTnWhV7Wb/SXb16ZoaYOW/gd2fA+dza8GY+jow6E5lYArPAmgD+IbbHziWQJcI2NWfLUSECUALgTPYMiYADWZQidRhAlAiY7GoxkOACUDj2dRRNaIuq9P+s1FE0nTyqcGM2CrcdhV3TXVUf9BK70NphfhqWwp+3n2mUcSp0nnd2vkI0o/IP293F4tEkvHDpUWKOtiihNP5+Ms7m0xqHeHnganx4YL4i2/vJz3p11BRu/v0NzcBh5dcFCmsN3DfBojOUTwYATMRsLs/mykvTWcC0ALQDLiE33gGNKokKjEBKImhWExjIsAEoDHtalStMgpLEerjbvLD8M6TuTiWUQD3tASTXYCNig3rpR0CpRVVWHogTaT57krJa/YgN2cnQdzMGhqN/tEBrSZuZPxwqZ0l5NmZuo3/kZCGv/SNQNiFjs4NpafU8TGvrK3v7EvP2vl64Ire4ZjWJxx92/vDycmYH8/s7tNHVwJfXdvYme5aBbQfKI+DsaS6QcDu/mwBEkwAWgCaAZcY8y+MAQ1lQJWYADSgUVkleRBgAlAeWzmypGWVVfhg/XG8syYZr8zog+l9IkzCIeNl3JFtq2fdU3KK8fW2VPyw6zSowUdzIzrQS3TyvW5glFWbM7A/69lDGsuWXlAq6kAuSTiL3an54uFT03rgzpEdFZV4+c8k/LjrNKb2Dhek8YDoAMOSfg0B0NSnq6uA5FVA2l5gzHxl56muBv7TB8hPBTqOAQbeAXS9AnCRs6mKPL8hxpRUU3/WCDImADUCVrJtmQCUzGAGEpcJQAMZk1WRDwEmAOWzmaNJvPV4Dh7/aT+OZ9d2xgzzdcequWNNplTKeBl3NJvqWd/KqmqsTsrEl9tSsf5IVrOiUoDWhO5hIs13VOdgTcgb9mc9ewuQWViKpQfSRffeHSebRof2i/bHz/ePUFSiuKxSNIKhrr6ONDTx6bIiYNv7wK7PgILU2rp9DyYA/tHK0B5fB/hGAsGdHQl61lUDBDTxZw3kbLglE4AaAyzJ9o71l0cSoziImEwAOoihWU19IsAEoD7twlJdRGDp/jTM/mp3I0juGR2Lx6/orgiTjJdxtrf9ESAi59sdp/Dt9lScLShtVqAQH3f8dVAUbhwcjQh/T02FZ3/WFF6LNs8+VyZIP4r023YiF9RXormx8ZFxaB/gZdFZRlykiU+XFwOvdQPKCi9CNmoeMOEpI0LIOukIAU38WWP9mADUGGBJtmcCUBJDGVBMJgANaFRWyf4IjB07FuvWrcOYMWOwdu1akwK1RADS2nHjxon1a9asAe2rxTh69CgqKyvh4uKCuLg4LY7gPSVFgGpl3frJjvpoLAqWuW14Rzw1rbtifTUZL+OSmkZ6scm3thzLwZfbUrD8YAYqq5tncoZ3ChLRfpN6hMHV2ckm+rM/2wTmFg+hFPBlB2sj/chnWnAVsZ+fpyum9AzD38fFITqICcA6kDXz6T/+CWz/30Vbtg0FHk4EnF1btC9PYAQsRUAzf7ZUIBXrmABUAZIDTGEC0AGMrFMVmQDUqWEuFauOUDJH3JYIo6VLl+J///sfduzYgaysLISEhGDQoEG45557cPnll7d4VEFBAf71r3/hhx9+QG5uLnr06IG5c+di5syZLa41+gQmAI1uYcfS70R2Maa8sR49Inzx/FW90CvSzyQAMl7GHcua9te2oKQCP+4+Lbr5Hs+qTS03NXw9XDBjQBRmDo1GpxBvmwvP/mxzyJsc+MueM5j7wz5UqWD9fDxcMLlHO9HIY0SnYLi52IYotj9K6iWwyKcpzPLUNqCyFIg18UVkRiLw32G1goT3qa3t1+evgIu7euF4JiNgJgIW+bOZZ1h7OhOA1kZUzv2YAJTTbkaQmglASaxoLgHo5OSE1NRUREZGNtGQos6I5Pvoo49Man/XXXfh/fffB+2jNM6dO4cRI0YgISGhyeNnnnlGEIOOPFoiANu0qX3tE04PPfSQ+P++vr5N8OYIQEf2ItvpTt19D5wpEPXUTI1KUQtTAAAgAElEQVT9pwvQM4J8tPkri4yXcdsh7dgn7TuVjy+3puD3hLMorahuFow+7f0wc2gMpsdHwNPN2W7AsT/bDfr6g49lncOE19aZFMTb3UVEhVIzj1FdguHuYj9/sT9aLUtglk+XFgIJ3wE7PwYyE4HQnsDsTRBt3pXGhteA2HFAZP+WBeEZjIAVEDDLn61wnjW2YALQGijKvwcTgPLbUFYNmACUxHInTpxAcXHzkRKJiYm44YYbhEaTJk3C8uXLFbV77LHH8NJLL4ln/fr1w/z589GpUyccO3YMCxYswJ49e8Qzmvfiiy8q7vHII4+Iud27dwcRflFRUVixYgVeeOEFlJeXY//+/ejZs6ck6NpeTCYAbY85n9gUgYqqany2+STeWHEElHy58uExra6pJuNlnH1DOwTOl1fht31n8OXWVOw/U9DsQR6uTriyT6RI8+3d3nSUqXbSNt2Z/Vl7tKnxy9rDWegb7Y9gb+Voscvf2oBDaRfry3m5OYsvLKbFh2NMlxDRzIOHOgTM8mnq6PvlNY03vnMFEDVY3WE8ixHQGAGz/FljWdRuzwSgWqSMPY8JQGPbV8/aMQGoZ+uYKVsdKUfLvvjiC8yaNavJDkeOHBHEHNV7GzhwINavXw9Pz4tF1EtKSkTdup07d4p6cEQqKtWE69ixo0gbptpx4eHh9ee8+eabIqLt3//+N55++mkzNXCc6UwAOo6t9appaUUVrn53c6MP1Vf0bod3Zw5olcgyXsZbpTAvVkQgObNIkH6Ldp9GUWllsyh1CmkrSL9r+rcXddv0NNiftbMG+cgPO09j0e4zoMYej1/RDfeM7qR44MI1yXh79VFM6FZL+o3tGmrXyFDtUNF+Z7N8uroaeLsfkHfyomDxNwLXvK+9oHwCI6ACAbP8WcV+tpjCBKAtUNb/GUwA6t9GRpWQCUCDWJbSeqOjo3HmzBl4e3sjIyMDXl5Ni17ff//9+O9//yu03rJlC4YOHdoEga1bt2LYsNo6LjR/4cKFTea4ubkhPj5eEIUNB0X+0c/vvvtuUV+QhzICTACyZ+gBgcd+2o9vtqc2EuXzOwZjdJcQi8WT8TJusbK8sBEC5ZXVWJ6YLtJ8tx7PbRYdF6c2mNKrHWYNicHQ2EDFhjJ6gJf92bpWKCqtwOKENHy/8xT2pOY32rxzqDdWPDRa0RcKSyvg3KYN2rq7WFcgB9ytiU8XnQQ8AwCfdspobHwTWHnhC92AjsCQ+4Ch9zkgcqyyHhGQ8R3NBKAePcn2MjEBaHvM+cRaBJgANIgnUPrt5MmThTa33XYbPvnkkyaaUcfF9u3b4+zZs+jWrRsOHTpkUnt6fvjwYVFD8NSpU00u5LQPNQFJTk5GWNjFumFvv/025syZI2rbUWqwOaNhvTs162699VZ8+umnilMJj88++wybNm1Ceno6XF1dQVGLU6ZMERGKDaMWG25AkYt1chNepaWleOedd/D111+LaEcalPZ8yy234L777hNRkkrDVA3ADh06ICUlpVn1GuqlVAPw+++/F/UZqf4i1WIk4vfKK6/Eo48+isDAQDXQNZnDXYAtgk36RXnF5Rj/2lrklVQIXa4f2B6PXNYNQSbS8NQoLONlXI1ePMc0Amfyz+Obban4dscpEcnV3Ij098RfB0fh+kFRCPXx0D2s7M+tNxH9Ld12IleQfn/sT2u2/uPP9w9Hv+iA1h/KO5hEgHx65Z+LEZG/E32r9sL59FZg5MPARBNZG8XZwJK5wIBbgY5jARO1oRlyRsAeCMj4jmYC0B6eor8zmQDUn00cRSImAA1i6Ztvvhlffvml0Gb16tUYN25cE82OHz8uav3RuPfee/Hee++Z1J6e10Xw0ToizxqOv/3tb3j33XdFOjGRZkQI0rnPPfccysrKsHfvXhEJaM6wBgFIdRIJi59//tnk0RQh+c0332DatGlN5jQkAIk4vOyyy4QuSmP69On45ZdfFBulaEEArlq1ShC7dXa+VKbOnTtjw4YNaNfOxLf4zRiDCUBzPNVYc7/dnorPt6Tguat6YUBM6z94y3gZN5ZFbaNNdXUN1h3NwldbU7A6KRPNNWilfgFUp42i/cZ1C4VzC41kbKOBulPYn9XhpDTrbP55LNp1Gj/sOo3U3JIWN+of7Y9HL++OwR0t+yKrxQN4gkCAfPr0J3cgLvOPi4i0DQEeSgRc3BglRkAqBGR8RzMBKJWLaSYsE4CaQcsbt4AAE4AGcBGKAiPSh8gvigY7efKkYgrN4sWLQaQVjTfeeAMPPvigSe3p+cMPPyyeL1myBFdccUWjudnZ2Rg8eDCoOcmlw5LoP9qD5Ffar+H+JNfHH38sfnTpOVVVVaL5yZo1a8Rz0vX6669HbGysIOm2b9+O1157TXRHphRmig6kOogNR0MCcPjw4SLFmSL9aC+KrqOoSCI566IniUQlsvTSYYoApBqM1CSld+/eYgntTYQlDSImSc6AgID67s0NSVGSZ/PmzbjqqqtEBGJMTIxI9aYUbbIRjRtvvFGQm+YOJgDNRUyO+RSNteDPJNw8tIPJpgpE5FTX1MDFWbnjt7mayngZN1dHR56fc64M3+88ja+3p+BU7vlmoQhs64brB0Zh5pBoRAU2LUkhA47sz+ZZqayyCisSM4SPbDiahRrqLtTMoKYf1/aPxHUD26NzqI95h/FsixAgn97y6ycYn/RY4/UzPgF6XdLww6ITeBEjYDsEZHxHMwFoO//Q80lMAOrZOsaWzWYEIDWMsHQQMVLXqIJq3RUW1naC8/X1RW5uLii9xJJBNfLatm2ruJT2JUJJ7QgJsbxmltozTM2jVFdK+6XxxBNP4Pnnn1ecSmTV7NmzxbMffvgBM2bMMHn0jz/+iOuuu048N0VyEflE5/32228iHZhSY4k0JHJKi0EEJqW6kg9QoxJK86XU3rpB5N68efPEz0gmit67dOTl5WHUqFE4ePAgRowYgY0bNzaa0pAApH2okzKReQ0H+UaPHj0E+UZRjvv27WtyjikCsG6iJTUAaS3ZljBvOMj/SVeSlVKSKcXbXH9kAlALj7XfnlXVNfh6eype+TMJhaWV6Bvlj59mD4eTDSKvZLyM289ScpxM75idKXmitt/S/ekor6puVvBBHQJEU4/LerWDu4vc3VnZn83z0RPZxRj36tpmF1H9x/HdQgU5PKZrCFyt9OWDeZI67uw6nx5x9AUEnztcCwRFAE78N9CvafM4x0WKNZcBARnf0UwAyuBZ2svIBKD2GPMJygjYjACsIzwsMQTVYKOUUxqXEoBUf46i0SwZ1KWWCB+lQamt1AFX7bCUhFS7f3PzJkyYINJvaVCEWpcuXRSnv/LKK5g/f754tnTpUkWCrG4hPa+L+nv11Vcxd+5ca4hq8R4HDhwARcAVFRWJiD6K5gsKCqrfr6KiQkTEpaWlCVlJZlOjoW4Ukdewy3FDApDITCIVlcZjjz2Gl156STzKz8+Hn59fo2laEIADBgzAjh07FKM7ly1bVm/PX3/9FX/5y1/MwpoJQLPg0v3kr7el4vGf9zeS86VreuPGwdGayy7jZVxzUCQ9gBo2/LLnjOjmezijqFktvN1dcHW/SMwcGo1u7Xwl1bip2OzP5pvyuvc2Y8fJvCYL40K9Bel3Vb9IhPi4m78xr1CPQMoWYOMbwOTngJCujdbV+XRk7hb0q0mA85C7ga5TOf1XPbo8U0cIyPiOZgJQRw5kR1GYALQj+A5+NBOAkhOA9EeEiC8iRqmjL3X2NTUodZXSZmlQPbnx48ebnEuEIhGLNGjdk08+abdfFSJ4Bw0aJFKbfXx8hI5E0DYclM47cuRI8SNT3Y3r5lOqMUWV0qDoyYYRiw0JwF27dqF///6KejeMkNyzZw/69u3baJ4WBCCRkXVp2ZcKRRjVRf21lN6tpBATgHZzb00OpjS8y97cAIrGqRtRgZ5YM3es1VJ9TQku42VcEyNIvGni2UJ8uS1FkH8l5c1HwncP98WsodG4sm8kiAQ02mB/bmzRyqpqbDiaDfGO6RWuaG5q9jH/xwTxzMfdBdP7Rgjir097P912ezaM3x5bA6x7GUi9cBfsOxO46t1G6tX7dE0NJk+ZUp9hYxgMWBGHQkDGdzQTgA7loiaVZQKQ/cBeCDABKDkBSFFoFI1G47///a+oKWdqyBgBSPXyJk6cKJpbUH08Su2dOnVqExXfeuutZmsamsLk5Zdfro+KpDkNCUAiCilNXGk0JEjXr18v0oobDi0IQKVajHVnEgHs7Fybavfss8/iqaeeMuudwgSgWXBJMXn9kSzc8vF2IeuVfSPw+BXdEearfddVGS/jUhhUYyFLK6pEh1ZK892dmt/saW4uTpjWOxwzh8aAGje0JsJfY7VavT37cy2E9GXCDztPYdHu08goLEN0oBfWzhurWFaguKwSf/96tyCFp/RsB083udPAW+1Ettxg1bPAhgaZC04uwAP7AD+67tcO9mlbGoTP0hoBGf2ZCUCtvUKO/ZkAlMNORpSSCUDJCcC6VGV3d3eR/koNJEwNa9cAtMUvxJ133lnf9GPBggX45z//qXgs1cV78cUXzRbp0jTwhgRgc2ndDZtzUNORS+sEakEAKp3TUOG6D+HNpbabAogJQLNdRxcLzpdXNfvh+qWlSRjdJRjDOwXbTF4ZL+M2A0eHB53MLhb1IoncySupaFbCmCAv0dDjugFRCGjrGN1CHdmfichbsj8NP+48je0nc5v4xjd3D8WwThdLcejQvR1PpHNZwJu9gMrSi7qPeACY9CwTgI7nDQ6hsYzvaCYAHcI1W1SSCcAWIeIJGiFgMwKQm4BY34LUoZZSY2lce+21oLTU5oY1uwBbX5umO77++uv1tQdvvfVWfPrppyaPffTRR0HRfDSInGtYH7A5WUNDQ0H/6gYTgC6NaiLaws58hvkI5JeU49Xlh7H+SDaWPThaVxE2Ml7GzbeA3CsojXNVUqaI9qN0zuYG9Y2Z2D1MNPUY2TnYJo1k9ISuo/kzffG1KyUPlMa7OCGt2RTwa/pF4vUbGpe/0JPtDCtLaSHg5g04mejcvmQesOMDwDcSGP4PoP8tgNvFhneO5tOG9QNWTCAgoz8zAcjOSwgwAch+YC8EbEYAWkvBS5uAUFqoo445c+bg7bffFupTauz06dObheL48ePo1KnT/7N3HVBRXF34o3dQERugKGDv2FBU7DUxMdXYYzS2GE1iTG8msSSxRI1plpiY/ImxxBJjb2DHXimioCJKkd524T93loUFZmAXdmZnlnfPyUnCvnnv3u/e3Z359hZuzauvvspN9xUSev3HH3/kXqbrGjduLCnMNKiD7KFJzIGBgaDsN8pyFBLd8ubjx49z11RGGAHICMDKxI1U19DD+aawu6DMvqSMXO7Y1/r64c2BJZu8S6UP3zlKvBk3JV5Snh2fmo0/Tsfgf6dj8SBVJ0OIR4k6Lnbc0JhRXbxR381BSjVldVZ1iWeKDSrvpWy/Wzq9Q4Wc0dbLDWO6NsLznb1l5S+zVib9IXByNXDmZ2DkT0CzwfzmJt8BbocAbZ7jHexRXWLarGOBGVeEgBLjmRGALIAJAUYAsjgwFQKMADQV8lU8l6beenp6gjIrafjD/fv3YW1dfgN2Ig+8vLy4tc2bN8f169cFtWjRogVu3LjBnREbGytpjyfSiwaapKamwtvbm5t8S9Oey5P9+/djwIAB3BIi8agMtjLCCEBGAFYmbqS6ht7DL/54Eqeii8vxbK0ssWdOLzSuXZzhIZU+jAA0JdL6nU0xczwqkcv223stHur8gnIv7OHnzhE7/VvWhY1V9f2BTQuSEh8u9YsMzao9Vx/gzzOxOHzzISoIDdR0tMHTHbzwXCcv0PAXJhIiELIMOLyguLTXuyvw8h7AwvBHSHOPaQm9wo6SAQJKjGdGAMogcGSgguGf3jJQmqlgFggwAlChbqSMvxEjRnDav/7661i2bJlelkyfPp0bFkIiNC335MmTRRl0tH7VqlV67W2MRYmJiejatSuioqLg5OSEkJCQMhN2+c7Jzs7myMqkpCTUq1ePIy/d3NwMVkkqAtDBwQGk87x580DlyySurq7coBNdqajXoO5a1gPQYHcr8oLw+DQMWX6siMixt7HE18+1w/C2DWRhjxJvxmUBnJGVoDLxv8Pu4vdTMRVmdLk52ODZAC+uv18TD82EdCYaBMw9nseuOVVuGTiVgAc3q4PnArzQr0Vd0AAYJiZA4MIfwLZSQ94m7gYadTdYGXOPaYMBYRcoGgElxjMjABUdckZTnhGARoOSbWQgAowANBAwuSx/9tlnsXnzZk6dsLAwdOzYUS/VwsPDQYNDVCoVOnXqBJpgS2SUVuiLtFevXqD+gpRReO3aNcl6wlFW48CBA7kefkRmUU/DkSNH6mUXLVqwYAHee+89bj3tQ/g4O/M/zKalpeGXX37BzJkzS+wvFQHYpEkTREdHg/z4008/cTowAlBvV1f7hV/suoafjkVjUKu6+HB4S3jV5J9WbQqglHgzbgqcxDiTsv0uxD7GbydjsPPSfeSo8ss9pp13DYzp2hBPtGsAexs2qZUPLHOP5+0X72PWH+fLmE4ZxZTp90xHL0mmh4vxfjCrPdV5wLcdgJTYQrMsgH4fAT3fMNhMc49pgwFhFygaASXGMyMAFR1yRlOeEYBGg5JtZCACjAA0EDA5LE9OTkb9+vWRk5OD1q1b4/Llywap9e6772LhwoXcNR06dOCy0Kg3IGXd0SCN8+c1DwO0rjKTdQ1SRmfxRx99hPnz53N/GTt2LN5+++1yt6KJx5T1pxXqFzho0CAcOHCA+xOVD0+dOhXdu3dHjRo1QKTfzZs3OYJx27ZtsLe3R0JCyQb4UhGAY8aMwcaNG7m+hkRcUtZj7drUYN+SIwK1g0lYBmBlo0nZ1918kIZaTrbwcOHve5meo8LZ20lcZo7cRIk343LD0FB9MnNV+OfCfa7M9+r91HIvd7Cxwoj2DbihHq09Dc+SNlQ3pa9Xcjzn52vKv3dficNnI1rDitL5Skl2nhpdvtiP1GwVHG2tMLxtfTzfyRsBjWpK2vpD6XFSZf0LCoCIfUCjQMDOhX+7Uz8Ae94H2r0A9JgN1Pav1LFKjulKGcwuMmsElBjPjAA065DU2zhGAOoNFVtoZAQYAWhkQKXYjoZ3TJs2jTtq8eLFmDt3rkHH0iCVyZMnY+3atYLXTZo0iRsCIuWQlQkTJnBZefoK32RguhEg0m/Dhg0VbkODTWjAia5IRQBeuHCB63NIJG5p0bWLEYAVutGsFhCxt2xfONYdv40R7RoocsKmEm/GlRpEEfFpHOm35dw9pOWoyjXDv44zR/o93dETrvY2SjVZcr2VGM+xSZncsKDNYXdx73EWh9m6iZ3RR+AHg3Wh0XCys8awNvW5fzOREAG1Cri2DQhZCsRfAQZ+rpncyye5mUBWMuBW/MNnZTRVYkxXxk52TfVAQInxzAjA6hGbFVnJCMCKEGKvi4UAIwDFQlbEfXv06AGadGtlZYWYmBg0aFC53l///vsvR/LRkA3KhKMMtM6dO3MTgocMGSKiBfxbG4MA1O5MZdFr1qzhSpzpizYjI4MrB/bx8UFAQABn3/Dhw8tMFpaKACQ9KdOSCFzqc0jDXLRkICMAJQ89WRwYdicZ0zeGIT61mBT+c0o3dG3iLgv99FVCiTfj+toml3VX7qVg2f4I7L8eX65KNlYWGNy6Plfm26VxLZbRVQkHKiWes3LV3ECPv87Gcll/pYXIvVWj9WsVUgmY2CWVRWDH60DY+uKrXeoDr18ErPmzvyt7jO51SolpY9jK9jB/BLTxbK3OQt8hI0q0NZKr9YwAlKtnpNWLEYDS4s1OK0aAEYAsGhgCJkSAsjFp2jEJXw9AqVSLiIjg+kJS30d//8qVFUmlq7me8ygtB32/Plwik6tZXRfsnBWkqGms7OFSvAi9HpeKZfvDsedq+cSfZw0HvNS1IVfKKVRGLp6W5rWznOOZej5evJvCkX47LtwvNwuUyOBT7/XnWgswkRECsWeANf1LKvTEt0DAeNGUlHNMi2Y029hsEchKiMHdv96BT8IB5I/aBDv/XrK3lRGAsneRJAoyAlASmNkhPAgwApCFBUPAhAgwAtCE4Mvw6PWh0fhkxzVOM1srS0zt3QQz+vrBzlo5AxrYw6XxA4t6QhLxt/vKA8HNLWhaa1MPjA1shN5N6/D2ezO+Zua/oxzjmX4s2Hb+HjaFxSI8Pr1CJzSv58KRwTTUw4WVf1eIl+QL1g8Hbh/THOvuD/T/BGgxXDQ15BjTohnLNjZfBJLvAMe/RcH532ChyubsVPsOgNXYv2VvMyMAZe8iSRRkBKAkMLNDGAHIYoAhIC8EGAEoL3+YWhuVOh9PrgzlsrY+fbIVfGo7mVolg89nD5cGQyZ4AfX4W3YgAv9ejgPNCOCTGo42GNWlIV7q0hDeteQzDdp4KJh2JznF8/mYZKw+HIWDNx5ClS8QEIVwuTnYcMNeiPhr1cCVlX+bKow4kmIF0G0a4O7Lr0XkfuDg50DQG0DzYYCluD/4yCmmTeUWdq6CEXh4Q9Mz8/ImoEBd1pCpoUC91rI2kBGAsnaPZMoxAlAyqNlBpRBgGYAsJBgCJkSAEYAmBN8ER996lI6/zt7FvMHNBB/IUzLz4OpgrdgHdvZwWfXAinyYjm8PRGDHpfuCxB8RPFN6NcH47j5wZoMbqg66wA5yiue9Vx9gyq9hgrZSFmiQX22O9BvQsi7sbcQlkkQD3Rw2jr+mISmubNaQFAETgCeW81umZffJgRKInGJaAnPZEeaCwL0w4NgS4MZOQYsKYAGLIYuArq/K2mpGAMraPZIpJ80nvmTmsIMUhAAjABXkLKaq+SHACEDz8ymfRdSgf9WhSPx49BZy1flY9kJ7PNWhapMc5Yoce7isvGeiEzI44u+fC/cglODlam+NyT2bYEIPH1bOWXmo9b5STvGcp85H4IIDSEjPLaF/w1qOeC7ACyMDvED9H5nIAIG9H3LliUViZQvMvgy41DO5cnKKaZODwRSQNwJEjkcfBUKWALcOC+qab2GF2FpBqDvyS9h7yjv7j4xgBKC8w04q7RgBKBXS7JzSCDACkMUEQ8CECDAC0ITgS3j0iz+ewMlbSUUn1na2w8G3esPVDPtxsYdLwwPrTiIRf5HYev6uIPHnYm+NSUGNMbFHY1D2HxNpEJAqnmmgx6noJG6gB03s7deiLq+BX+y6hp+ORcPexhJD29Tnsv26+NSCpSV7lJAmIvQ8Je0BsKwNoNYha7vPAgbO13MD8ZZJFdPiWcB2NnsE8vOB8N2ajL97Z4XNtXGEqt0YHMhqiWzbWhg4cCCbAmz2wWE+BrJvbfPxpdIsYQSg0jzG9DUrBBgBaFbuFDRm37V4TN5Q8iZ2Rh9fzB3U3OwAYA+X+rs0NikTKw5GYPO5e1ALpPxRee/LPXwwKagJ3BwZ8ac/usZZKXY833+chc1hd7Ep7C5ikjI5pfs1r4M1EzrzGkBtBIgoHN62PssANY6LK7+LWqXp1ydUurvjdSBsPWDjpCkBDpwBuJk+81vsmK48oOzKao8AvaeubtEQf4+uC8Nh7wZ0eRXoOhVZlo7Yu3cvt5YRgNU+ghQFACMAFeUus1KWEYBm5U5mjNIQYASg0jxWeX0nrT+DAzcewtrSgsvkeq2fv1n2bmMPlxXHyN3kTKw8GIm/w+4KDnNwsrXiynyp3LeGo23Fm7IVoiAgRjxn56lBPwoQ6Xcs4lGZPo+UzHfi3X6o62ovik1s0yoikJcNXPwdCF0ODFsC+PXj3zAxSjOooMsUwLFWFQ813uVixLTxtGM7VUsE6D11YaPmPfX4jjAETnWA7jOBgImAvSu3TonxzEqAq2WUlzGaEYAsDkyFACMATYU8O5chAIARgOYVBvn5BYKleDGJmfjwnyt4f1gLNK3rYl6G61ijxJtxqZxx73EW1wty09lY5Kn5p7g62lphXKAPN+CjlhMj/qTyjdA5xoznK/dSON9vu3AfKVl55Zo2b3BzTAsWmBpralCq8/nnNwIHPgXS4zUo+PQEJggPJZAjVMaMaTnax3RSEAI5acDZtcCJVcXvKT71azQEerwOtB8D2JT8YUSJ8cwIQAXFqIiqMgJQRHDZ1uUiwAhAFiAMARMiwAhAE4JvxKOplPOzndfQzssNM/v6G3Fn5W2lxJtxsVGOS8nCd4ei8OeZWG4IDJ9QT7fxhcSfu7Od2Cqx/fVEoKrxnJyRi20X7mHT2bu4Fpda4an+dZy5vn40JMjDhcVBhYBJvSDsF2DHrJKnTtoPePOXbEutnj7nVTWm9TmDrWEIlItAZhJw6nvg1A9A9mPhpR4tgKA5QOtnACtr3nVKjGdGALL3ByHACEAWB6ZCgBGApkKencsQYBmAio8BKuX76egtrDwUiRxVPteYf9+c3vCu5ah42yprgBJvxitra0XXxadmY/XhKPx+Oga5Kn7iz87aEmO7NcKrvX0Z4VMRoCZ4vbLxTMTfB9uucKW+QqSv1hwXO2s80b4BR/zRjwgWQj3lTGA/O7IUAqocYHk7IC2u+IXAmcCgLxQDVWVjWjEGMkXli0DqfeD4SiBsHZCn6XnKK54BQM83gaZDAEvLcu1RYjwzAlC+ISqlZowAlBJtdpYuAowAZPHAEDAhAiwD0ITgG+Hoq/dTMHxFSIkeXgNa1sVP4zoZYXdlbqHEm3FjI/0wLRvfH76FjafucMQwn9haW2J014aY1tsXdVivN2O7wGj7VTaeaahL0KKDiEvJFtSlu687nuvkhcGt6sPB1spoOrONqohA/DWgpg9gK/BDDhEYe98HGvfWZCc1CRYeBFJFVcS4vLIxLYYubM9qggD1wwxdBlz4A8gvp/0BvaeI+GvcS+/3lBLjmRGA1STuKzCTEYAsDkyFACMATYU8O5chwDIAzSIGPkThxHcAACAASURBVNx2Bb+eLG5aXdvZFv/O6lltSR0l3owbKxAT0nPww5EoLh6y8wSIPytLjOrijWnBfqjnxoY8GAt7sfapKJ4LCgoEM/a+2XsTKw5GllDNs4YDngnwwnMBXtU6U1gsf1Vp39jTmumj4buBIYuBrq/yb5eTDiTcBChLSYFSUUwr0CSmslwReHBZ8566tg0o4P9O5FRvPhwIegPwMvw9pcR4ZgSgXANWWr0YASgt3uy0YgQYAciigSFgQgRYBqAJwTfS0SmZeej7zWEkZ+ZypZxvDGwGNwcbI+2uvG2UeDNeVZQT03Pw49Fb2HDiDrLy1Lzb2VhZ4IXO3pge7IcGNRyqeiS7XiIE+OKZSL+wO8n462wskjPzBDN+7yRmoPdXh0HZnoNb1eNKfCnrz5LG/DKRFwL7PwFClhbr5OYNzDoPWJnfZ3l1/IyWV7BVA21iTgLHvgEi9goba2EFtHkOCJoN1GlRaVCUGM+MAKy0u83qQnYnYFbuVJQxjABUlLuYsuaGACMAleHRqEfp8PVwFlT20I2HXP+21p5uyjBIRC2VeDNeWTioz9uPx27hl+O3kZnLT/xZW1rguU7emNnXD5T9xURZCOjGc/vA3vj3WiI3yfdWQkaRIcfe7iOYzbf7chy6+9aGm6P5EUnK8mQF2t45DqwbUnLRU98D7UeZlZlkTHX6jDY758nZoIICIPKAhviLOS6sqZUd0HEs0P01Tal9FUWJ8cwIwCo63UwuZwSgmThSgWYwAlCBTmMqmw8CjACUty8fpGRj/q5r+PdyHLZO74H23jXkrbAMtFPizbihsD3OzMXPx6KxLjQaGQLEnxURfwFemNHHj5V6GgqwjNanZWRg6Z8HcPKhBW6kWCK/oKxys/v7Y3b/pjLSmqliMAJEXqwdBMSe0lzqUBPo9zHQaaLBW8n9gurwGS13H5iVfvlq4Pp2Tanvg0vCptm6AJ0nAd2mAy51jQaBEuOZEYBGc7+iN2IEoKLdp2jlGQGoaPcx5ZWOACMA5evBDSduY9HuG0UETxtPN2yb0QNE7DARRkCJN+P6+jMlKw9rQqKxLiQaaTkq3ssoPkZ28MRrff3R0L36ToPWF1O5rkvNzsNfZ2KxNiQa98sZ5EH6N3J3xOG3gtn0Xrk6k/TKTtVMHm31NFCjIb+mN/8Dds4Bus8EOo4H7ISzvuVsakW6mfNndEW2s9eNiIAqF7j0p2a4R2LJXqclTnF0B7pOA7q8oiHWjSxKjGdGABo5CBS6HXuaUKjjzEBtRgCagROZCcpFgBGA8vUdDXNYsPtGCQXnP9Wa6/PHpHoRgEQGrQu5jZ9DbiEtm5/4I174qQ6emNXXHz61nViIKBSB2KRMrAu9zfX3SxcgebWmNa7txE3xfaajF+qySc7y9Hj6I+DU98CZn4DsFKDLFGDoV/y6UhagOg+wtpWnLUbSSomEiZFMZ9sYA4HcTODcBuD4t0DqPeEdXT01Zb4dxwG2xvtOzC/IR+i9UAR5BnE/uigxnhkBaIxAVP4ejACUrw/pSW8WgGEAvAHkAIgC8BeAVQAyjah6MIBxAHoCqE8DQgHEA7gMYD+ADQDSjXgebcUIQCMDyrZjCBiCACMADUFL2rW5qnwM/fYYIh9qPnZpsMdHw1tyEzyZVA8CMC07D+tDifiLBmX/8YmFBTCiXQPM6uePJuX0iWQxI28EzsUk48cjt7D32gPeMl+t9o62Vhjetj430COgUU2W9SdvtwL/vQecpNv1QrG2B2ZfAZw95K65aPopkTARDQy2sf4IZD3WEOknVwOZicLX1fIFguYAbV8wOpl+Mu4kloYtxbXEa1gavBT9G/VnBKD+HmQrZYYAIwBl5pBCdZ4A8BsAVwH1wguJwXLynvUyzAXAzwCer2B1BwAX9NpR/0WMANQfK7aSIWB0BBgBaHRIjbrh8agEjP75FJ4P8Ma8Ic1Ry8m8M0OMAZ45PFxm5Kiw/vht/HTsFh5nChN/w9s2wOv9/OBXh77GmSgZgS92XcNPx6IFTWjoVICp/VtiRMeGcLKzVrKp1Uv3lLvA8nZAvk7mbs83gX4fVS8cdKw1h8/oaus8Uxie/hA4sQo4swbITRPWoF4bgN5bLZ4ELK2MrulnJz7DpvBNRfv6uPpg64ityMvJw969mmnDAwcOhIOD/IdtsQxAo4eHIjdkBKD83EZkWyi1AS7MulsA4FDh/78IYHKhykQCdgJQzidiucZRTvQeAD0KV/0H4A8AtK8ltZYB0BnAcwCIkGQEYH4+UlNTObhcXV1haUkwMWEIyAsBHx8f3LlzB+PHj8f69esFlauIAKRrJ07UNCGPjo4G7SuGREREQKVSwdraGv7+/mIcIcs9z95OQnZePoL8awvqF52QASr1Y6IfAkp+uMzMVWHDiTv48egtJGXkCho8rE19vN7fH03rMuJPv6iQ/6q7yZnotfhQiew/Kuvu39wDLSzj0NgFGDRIGQ+X8kdbYg23TQcubNQc2ny4hqTw7CixEvI5Tsmf0fJBsRpoknxHU+Z7/jdAlS1scMPumveUXz+AUuJFkj239+CtI2+V2P2jwI8w3Hs4IwBFwpxtKy4C4r1bxNXbnHc/AqAXAPrJkP59opSxcwEsLvzbpwA+qSQY3wGYVljuOwmAEFNAMUI/p/A3H6rk4awEuPLASX1lcHAwjhyhsNRfDh06BLpOV3QJpYp2WrduHSZMmCC47P79+3jvvfewa9cuZGRkoGPHjvjggw8wePDgirY2+9cZAShvFyek52DBvzew+dxdNHCzx/43e8PRlmX1GMNrSny4zMpV47eTd/DD0SgkpAsTf0Na1+OIv+b1hAoDjIEg20MsBG4nZHCl/DUFMnlnbDyHXZfj4GxnzZX4Tuzhg9oOFop7uBQLP9ntSz37og4Ax5YCwfOAxnS7ziOPwjWDCnq8Dng0k50ZUiukxM9oqTGq1uc9vAGELAUubwIK1MJQ+A8Egt4AGgVKAldBQQFe2vUSriRe4c6jDMC3O7+NTu6dFPcZzTIAJQkZ2R/CCEB5uagLgFOFKv0AYCqPepR2Rp9ALQA8BlAHAH+dkLBt7QGcA0D+/xoAkYpSCysBlhrxSp5nKAFImZExMTHw9PQscaKxCEAi/7p27Qr6EtMVasi7du3aconDSkKgqMvKIwBv376Nxo0bc/asWbMGI0eO5P6bL6OVZQAa3+0xiZkYvuIYUnWGOUwL9sW8wc2Nf1g13FFJD5fZeWpsPBWD1YeJ+KMWv/wysGVdjvhr1cCtGnpU2SbTQ+PJW0nc9OYDN+Ixu19Tzpd8cvluCk5FJ+KFzt5wsbfhligpnpXtKQO1j9gHHPgMeHBJc6FvX2DsVgM3qZ7LWUxXT79XaPW9MODYEuDGznKWWmgmaVOPv/ptK9zS0AWZeZmwtLCEPfXq5JFTcafw7rF3Mb39dDzl9xSsLa0V+RnNCEBDI8M81zMCUF5+/RLAu4UqddMhA0tr+Q4AKg0mGQRA04BAfyFycUrhYBFiacrpqKr/pgauZASggYCZajmVf1KWXXly7do1vPDCC9ySAQMGFP0ipnuNLqG0Z88eNGjQQHBLLy8v1KhRg/d1Ouevv/5CYGAglwVYs2ZNbN68GcuWLYOjoyOI5KpdW7is0lQ4yuFcRgCa1gtECIxZcwqhkcUfuTZWFtgzuxcb4mAE1yjh4ZKIv/+djsF3h6PwME2Y+Ovfog5m92+K1p6M+DNCaEi6BQ3x2XHxPkf8XYvTtA0hqe1si5B5fWFvo1+PKiXEs6TAyuWwMz8Du94sqc2Uw0AD6uDDpDwEWEyz+ChCgLJoo48CIUuAW4eFgbG0AdqPAnrMBtx9jQ5gXn4etoRvweqLqzG6xWhMbqvttFX2qBx1Duys7IpeUGI8MwLQ6CGkyA0ZASgvtx0tnMRLbAuxH0Jlt5TzfLxQ9c8AfGyAGeTzBAC1AOwGMLTwWqpB06ZsPSgkBw3Y1uCljAA0GDL5XjBv3jwsXqypTP/1118xZsyYMsoaI6MsJycHbm5uqFOnDq5fvw4np+L+aLNnz8by5cu5vnfU/45JWQQYAWj6qKDJvkOWH0WeuoAr93tjQFOMC2wEayvWU7Sq3pHzzXiOSo2/zsRi1aEoPEgV7mnUp5kHR/y18+b/AaSqGLHrxUOAejf+fuoOfjlxB48EyN3Fz7blSnz1ETnHsz76m+2avCxgWRsg41GxiR3HA09+a7YmG8swFtPGQlLB++TnA+G7NRl/984KG2LjCARMAAJnAm4lK4qMZf3ZB2fxyYlPcCf1Drels40zdo/cjRr2+n3/KjGeGQForOhR9j6MAJSX/+huglKXLgKgMl0hqQkgqfBFGktU0RRf3X2o/oQGfZDQKLLVAL4A8BJ99hX+ndIS6OcY+vsxkSBiBKBIwEq9LQ2TaNiwIe7duwdnZ2fEx8dzmXilxRgEIJX/UmnxM888g7///rvEETt27MCTTz6JL774gssMZFIWAUYAyiMqFv13A3GPs/De0Bao48pfbiIPTZWlhRxvxikb7K+zsfjuUCTupwgTf72aemBOf390aEhf70yUhEDkwzSsCbmNLefuIkeVL6i6i7013hzQFBN6aNowVCRyjOeKdDab1zMSAFtnwEbg85nIiwOfAu5+mv5+bV8ArIszg8wGByMbwmLayIAqaTu1Cri6RUP8PbourLm9G9DlVaDrVMDJXVQLrydex/M7Sz5Cj2s5DnM769cZS4nxzAhAUUNKMZszAlA+rqK7jKxCdXYBGF6BaukAKP3pJABDuqCOALCtcG/KHKQ+g/UFzioA8HZhn0BDkSKCrzypB+AMLQgPDweVfOor1F9OrVbDxsYGvr7GTwcX0oOIrvR0gh0c0cWmAGuQ2rdvX9HwDcq8oz58fEIE4KRJNG8GiIqKqtRUWfqypdJgIgGvXLlSgmh86623sHTpUvz8889F02v1jSld3fS55qOPPsLHH5dNvKUSTypH/t///oczZ87g0aNHcHBw4KbbDh8+HDNnzhQsbaaJuxs2bECjRo1w69YtPH78mLNny5YtXFkzxXvbtm0xefJkjB49WlDNJk2acFOAx40bBxqmohUrq4rLznTtKu0vInkJW9KRsi9zc3O599/zzz8Pyr7kI331wZJiIS8vD6QfnWEOos4vAE3xpL6UfEJxIvSaOdhvKhuys7Nx9Cgl0gO9evWCvb3pyNU8dT62XojD98duIy5FuNS3e5OamBncBB28WamvqeKmMufSe/j4rWT8cjIWx3RK+vn2aljTAeO6eeOp9vXgZMDAHznFc2UwUuI1FimxsD7zPawu/o68vp9A3UGgmiAnFZbRR5DfdChgWfF3qxKxEENnFtNioCrzPVXZsLr8J6xPrYJlSoygsgVOHlB1ngpV+3GAnXRT7j88+SH2xOwp0ivYMxiLui/S6x5NifFMBGDTpk219lI6esmG6jIPJ6aecRBgBKBxcDTGLh4AHhZu9CeAFyvYNL5wAAgNBGljgAITAWgZGnoqoZ8s/yvMBqSOxjRi8BkACwFon0ieAFBeZ1beZ1x9dSJSwZCebe7u7hypQoRD/fpC3KW+p7N1VUXg1Vdf5XrykWzfvh09e/bk3fL333/HjBkzuNcuXrxYabKHCCciHWkQyJw5czhCjaYBr1q1invgv3DhAjw86O2kv+jqps9VVPL8zjvUirNYEhISuNLnU6e0c3zK7kSlyxs3bkSnTp3KvDh9+nT88ccf8Pb25kjEZ599lhumwievvPIKvvrqK97XiCSMjY3FqFGj8N13NOxbI9QrsSLRtUsXkxMnTnD2Ck2DDggIwD///FOiJLuis7Svx8XFITMzk2umnJhoinak+mqq37ocNbAhwhKNXQrQ35N+Q2FSnRBQ5wNnEiyw964lEnOEb7H8XfMxxDsfvmyor+LC4+RDCxy+b4m4rPJvof1cCxBcPx+tamp+EGAibwR843ej5f0/YQlNFmeGbR0caLkIBRaM4JO355h2ckTAWp0Fn4SD8H34H+xVKYIqZtjWRmTd4YipFYR8S1tRTCnvR9ckdRKWpy1Hfav6GGg/EE1smoiig1w2pWcVeoYoFEYAysUxEuvBbkkkBryc4+hNqH3a/xXAuApUo7V0TRQAPwPMmAlghc76fQCGACg9bz0IwBEA1JjqaiHJaMjTrN5rGQFogPdktpQyIps3b84NCaEszkuXLgn+aqZLKAUFBSEyMpIjfFxcXEBZa71798bLL79c7nAQMp+uGzhwIJKTk0ugQRlV1ANw7NixBqOUkpLClTCXJ5Qdd+DAAW7JypUrS2Thkf39+vXDzZs3uUw2Iu9oGApl81F22/HjxzkyLikpiSMsiUgrne2mJQCJDKc+hw8fPgSRqzSFmXodEraLFi0ClUGTUAk0nVlahAhAGtTy4MEDrnya5P3338fQodoWoJpdiDjVkqe6/urSpQvOnj3LDXp56qmnULduXW4KM+FNmY4klAXIlxVZkTPMiQBMywN+vG6FmAzNV+tYPzU6eej9UVgRVOx1GSOgLgDCHllgz11LJJRD/Pm6FGCotxp+LOFPxt4sX7Xvr1vi+mP+np2WFgXo6K4h/ry1TVUUa2n1Urx22lX0iFxUwuizjabhXi1DimyqF2bMWoZAaQRsVWlo8mgvGj/aB1t1piBAqfaeiKj7BO7V7CoayZ6Rn4EjOUeQW5CLpxyfEtQlTh2Hepb19Mr6U7rHGQGodA8aR39GABoHR2PsIlUGINH+P+ko3BHAeQEDqL/gs4Wv0cz1ywYYWlFNr6glwFSua+xsItpTOw2XCBm5lQBTZqTUOv3yyy8caUdCfffmz58vGCL6lNlSBt+SJUs44qs8IRLwgw8+4DIBKQW/Q4cO3PmlCS0D4rXcpUTevfbaa9yal156iRt0oiuzZs3iMhCJ3Nu7dy8oI660UFlujx49QIQXZef99ttvJZZoS4Dpj7QPlTK2atWqxBqyu127dpzNTzzxBLZt01bzFy8TKgGmFVRKrC2bJ+JdSwbylbSX9hf5uvRwFxrKQuQglWNT/BE5aW1N84T0F3MpAabpriO+P42YJG0nB8DG0gI/jmmHbo1p5hITsREwRTkOlXvvuhKP745E446O70vbGtDQDTODG6OrT81q8ZAhtq9NuX9oVBJe+e1CCRXcHKzxYoAnXurihTouxukFZ4p4NiWuJj+7oAB2GwbD8gG14QYKLK2h6v4GVD3eMLlq5qIAi2lz8SSPHan3YcOVz/8KCxqUIyD59TsgL/B15PsNBCzEGX6WrcrGH+F/YMPNDcjIy4AFLLBx4Eb41TAkX6ZiXykxnlkJcMV+rQ4rGAEoHy9L1QPwBQD/KzSbpgGXVyupSxZS8zb+5m6Vw1DUISDUe43KLauTUMaYoaWvVcWHMtAOHjzIbUPZbzp9JcpsTYQSEYQjR45EYGAgV+pKQv3uqOSVMtooTZ/khx9+wJQpU6qqnlGup6y/wYMHQ6VScWQXZe/p9hajX9PIFroRWLFiBdfnT0hWr14NyvSjfn6Uwag7xXjChAkgko3k22+/LSIcS+9F5CH1GKSSXsooLC0+Pj5cD0Dqx0iY60plh4CQz8hHfEK+mjqVWolqSrspA9EQiYiI4LAl4pB6JSpZfj52C5/vKm5u7eZgg5/GdUIXRgBK4lYpG3IT8bfz0n0sPxCBW48yBO3r2LAG3hjQDD383BnxJ0kUVP2Q/PwChEQmoLuvO+90bvqeGrzsGG7Gp6GJhxNe7tEYz3T0goOtcUtFpYznqqOmkB1oAmmBGrCy4Vf42nZgyxQgYLxm+mgN/SY2K8R6k6vJYtrkLjC+AolRQMhS4OL/gPw84f2bBANBbwCNe1GDZOProbNjYlYihm4ZikxVcQZiL69eWNVvlVHPVWI8syEgRg0BxW4m7jtQsbCYTHEppgB3BxBaaCFl/lEGoJAMKuwPSK9Tw7OStRFVg4kRgFXDr8zVUhOA9CVCJa6UGdmtWzdQn7jyhMpsXV1dBR+Cd+7cyZGDVDJL/R0pM6xePUoUNZ0QOUW9Bomso8EjVO5auu8k9fTTZsZRdl95Ol+9ehWtW7fmDCIikQYVaEVLAFIpMxHYlFHHJ19//TXmztVMKCO9KFtQV8QgAIn8I9/wCZUGd+7cmXtp69atXImwIWJOBCARA5/tvIZ1obfhWcMBv7zcGX51pGtmbQju5rhWiptxIod2XY7jiL/Ih5qhUHzSzpuIv6bo5V+bEX8KCbasXDW2nL+LtSHRiHqUge9Gd8TQNvx9hg/ffAj6vap3Uw9YitTgT4p4VohrjKPm7RBgz3tAq6eBoDn8exJBmJUs+vRR4xikvF1YTCvPZ4Iax13SEH/XtgEFwtPP0Xw40PMNwLNsZYyYaKy+uBrfXSjug21taY0dT+2Al0tFBWr6a6XEeGYEoP7+NeeVjACUl3dpfCFNUKB0AnqqVwmoRw1Jjhe+9hmAsuNIhe2ifbXN02joR7tyIKAGYTSRmIQYh6+NCBcjAI0IJm0lNQG4cOFCvPvuu5wVlNmmzQKrilmff/45PvzwQ24L+m/qU2cqoSm8RGxSZiMNnTl27BhvaS8NIlm2bJnBav7555/cBF2taAlAyuIkXwoJTVnWTlOmISHaTErtejEIQCIuW7ZsyasSZXBqy4ppQrChPRjNiQAkgCgzbMm+mxgf6IM6rqabQmtwQJrBBWLejBPx99/VB1i+P4LL/BKStl5umNO/KYKbeTDiTyExFZ+ajQ0nbuP3UzFIzizOYAloVBObp9FvpqYRMePZNBaZ6NSkaGDvB8CNwll2dq7Aa+cAZ8OGhZlIe7M6lsW0GbjzzgkgZAkQsVfYGBqc0+Y5IGg2UKeFSYzOzMvEkC1DkJydjGFNhmFG+xlGJf/IKCXGMyMATRKOsjuUEYDycsmXADSMCtANgNA4UcrGW1C4jrL0yvkU5jWQiD+aHJxaSDQKdamnpmffFu7wEoA/jAgXIwCNCCZtJTUBSP3paLCEnZ0d19dOnymzFZlMNlAGHWVS0RAN6qdnClGr1Vw/Qe35pck6XZ1Gjx4NGphhqKxbtw5E+mlFSwBSViWV6goJlfVSv0CS6OhoEOGnK2IQgHznaM/ULSsubZM+mJgbAaiPzWyNOAiIcTNOn0V7rsZj2f5w3HggTPy1auDKEX/9WtRhxJ847jX6rlfupXDZfjsu3UceTXHhkW0zeqC9d8ksa6MrIrChGPEsle6yOuf+eeDH4JIqdZoEDF8iKzWrgzIsphXqZUp3jjwAHPsGiNHmn/DYYmUHdBwLdJ8F1GwkqrHhyeHYEbUDbwS8Ifide/TuUdRxrIPmtZqLoosS45kRgKKEguI2ZQSgvFzWRYf0+wGAprFWSaGOqVcA0E8qjwFQo7tymi7wGviJTtbgAAD7BWA4BEB719QQQKwR4RKVABRrCEhamuYBkCbXSj1woyLspRwColv2SYMkqH+fsYQy4KivHmWcUeaZKYSGelA/PxKa/vvpp58KqvHiiy+CCEJbW1uEhYXprS5NTdYt32UEoDJ6AOao1FiyLxxTe/mippOt3v5mC8VHwJg340T87b/+EEv3heNaHP1Wxi8t6rtidn9/DGxZlxF/4ru4yidQhu6B6/FYExKNU9Fle6jqHtC0rjM+ebIVuvvWrvK5ldnAmPFcmfPN6potrwKXtO2v6c65JTDlMGBtnIEtZoWViMawmBYRXDG2zlcD17cDx5YADyh3REBsXYDOk4Bu0wGXumJoUrRnXHocVl5YyZF/BSjAsuBl6Neon6hnCm2uxHhmBKBJQkV2hzICUHYugbYMmMp/qUFY6cZqVIq7uFBtYiWIzNMVIuyIuCOhiQLFKUbFq6juIYp4rMLJvkGF2YC6+4wBoB11SmXAw40MlagEoJF15bYjUjE1VfMgSL3s5EYAimGz0J66BNn27du5ibTGEhreQj3wTEUA/vjjj0VTiInc3LRpU7kP9jNmzABNCSahKbilewTqiwsjAOVPAKZk5eHVX8/i5K0kUHngxle6wt7GuI3/9Y0Xtq4sAsa4GSfi7+CNh1i2PwKX76UIwtysrgvmDCDir55oPeCYj42HQEaOCn+H3cXa0GjcSSxuDM93ApVvTwpqjCA/0/ZvNEY8Gw9Bhe+UchdY0QmwcQD6vAcETBAeBKJwU+WsPotpOXtHRzdVLnDpTyB0GZAYKay0ozvQbRrQeTLgIH6mNH0/j9w+EpGPi3XycfXB1hFbQT3+pBYlxjMjAKWOEnmexwhA+fmlQ+GQDgcA1GGcyoKJ0KP/fxGAdjRqOIBOAErXJOlDAJLV0wFoxyHdLBzwQT/vuAKgbv/TANCTLTFedE6EkaFiBKCRAZVqOxrSQQMxiKSjbD0ivWiCqzGE9qxbty5XAty/f3/s27fPGNvqvcfhw4cxcOBAbhBJhw4dEBISwg0kKU9+/vlnTJ48mVtC5bk0fbcyIgUBSNOBtSXDa9asKRrswUdoV1RqrLWxupQA33+chQnrTiM8vnjww+BW9bBqdEdYiTQEoDJxVJ2vqcrNOH3mHA5/hGX7wnHxrjDx51/HGbP7N8WQ1oz4U0KsZeaquL6Nf5yOQWq2UFtlwM7aEiM7emFSkI9sBvdUJZ6V4Buj6khlvneOA4EzhLeN3A94dpKEqDCqbWa0GYtpmTszNwM4twE4vgJIvSesrKunpsyXyn1tnSQ16r/o/zD3qGYQnlY+6/4ZnvZ/WlI96DAlxjMjACUPE1keyAhAWboFlE71WyEZx6chkX/DAPD9LKMvAUj7flCYQSiUwkJTiWmkZzkNHyoNICMAKw2daS+kjL8RI0ZwSrz++uuVGoAhZMEXX3yBDz6gsATmz59f9N9SWExTh2nib2JiIkdC0sTf0gM2+PS4d+8eGjduzJGGbdu2BZVH29jYGKyyFARgfHx80ZRiylocNWoUpycjACt2V1xKFp5edRwPUrOLFjvZWmHrjB5opaeh7AAAIABJREFUWpdN+q0YQfFXVOZmnIi/YxEJWLo/HOdjqKsGv/h6OOH1/k0xrE19RviK70qjnUAlv8FfH0JsUhbvnh4udhgf2AgvdW2EWjIr6a9MPBsNOKVslHIPOPBZYXmvBTD1GFCPWlwzkSMCLKbl6BVispKB0z8Dp1YDmYnCSrr7AT1mA21fAKxN0wIlvyAfo3aNwrXEa3C0dsTE1hMxruU4ONqU/2O9GMgrMZ4ZAShGJChvT0YAytdn1D319UKij8iy3ELCbxOAlQCEalgMIQDJesruo2zAPgDqA8gpzPbbXjgARPiJqGrYMQKwaviZ7Opnn30Wmzdv5s6nnncdO3asUBfKEktOTuay6oRk586doJLb3Nxc2NvbIzIykss0lEKotJsm/l6/fp0bakKZgPT/+sqrr74KKh0moQxAygoUyoqkQSdEor7yyisltpeCAFSpVHBycuIwfuutt4qmLDMCUD9P33iQiudWn0BajgpEHKyb0BmtPd30u5itEh0BQ27Gifg7HpXI9fg7eydZULcmtZ0wq58/nmjXgBF/ontQnAOo39/8nddKbN6yvitX5ju8XX3YWcuzjN+QeBYHOZnvmpcNLG0FZCYUK9q4NzDuH8CCPd7I0XsspmXmlbR44OQq4MxaIFd4yBXqtQV6vgG0eBKwFPfzksvGjz2Mbg26wcGait/Kyqm4UzgYcxBT2k6Bu4O7yUBVYjwzAtBk4SKrg9k3pKzcUa2UYQSgAt1NJB71uMvJyUHr1q1x+fJlvawgQq1Pnz4IDAzk+gW2b98e1OuPvuhv3brFDRGhf+j/SVauXAnqrSeVjBs3Dr/+qml5OW/ePIwZQy0whYV0p3+0kp6eztl25QrN5wGaN2+OqVOnIiAgAM7Oznj8+DE30GT//v34999/0aZNGy5TUFekIADpvKCgIISGhoKGxixcuJDThSY4U0/LWrVqcf+QsBJgfv8fj0zA/F3X8ePYAHjXkv4XZ6neE0o8R9+b8RNE/O0Px+lyhkA0cnfErL7+GNG+AaytaPYWE7kikJadx2VxDm1Dv2GWFXo9cMFBZOSq0K95HUwKaoJuTWrJfmiLvvEsV79IoteRxcChL0oeNXoz4N9fkuPZIYYhwGLaMLxEW518Bzj+LXDuV0BNeR8C0qgHEPQG4NdPElL9XPw5LAlbgouPLmJ2x9mY1GaSaBAYY2MlxjMjAI3heeXvwQhA5ftQqRYwAlCBnvv+++8xbRq1hwQWL16MuXNL9uEQMklLAFZkMvXbW7p0KaZM0ba6rOgK47weHByMI0eO6L3Zxx9/jE8+KTl/JykpCaNHj8Z///1X4T5Ehh48eLDEOqkIwF27dnEkrJZs1VVC1y5GAAq7kcoKWd+/CsNc8gUV3YyfuqUh/miIi5B413LgiL+nO3gy4k9yDxp2YGxSJtYfv40/z8QiPUeFfXN6wV+gHP+/K3FoVs8VjWtL26/KMItKrq4onquyt9lcm5sJrAgA0u4DNIm015tA12mAjb3ZmGhOhrCYNrE3H94AQpYClzcBBWphZfwHaoi/RoGSKbz64mp8d0EzUI/ExcYFu5/ZDTc7+VZZKDGeGQEoWUjL+iBGAMraPWatHCMAFejeHj164Pjx47CyskJMTAwaNGiglxVpaWlc2euJEye4zLe4uDgkJCSASlIp+6xVq1bo168fVxarm1mn1+ZGWGQMAlCrBhF7v/32GzdAhOzMzs7meuz5+vqiS5cuGDZsGDdohDDUFakIQDrz0KFDXO9G6nNIfqD+hSSMAARU6nxciH2MTj6aTEgmykFA6Gb87O0kjvgLjRTubeRZwwGz+vlxgyBsWMafbJ1OP1yE3UkGlfXuufoA+ZqkcU5GdfHGgpFtZau7oYop8eHSUBv1Wp8UDdT0Ec5AuvQXEHMCCH4PcPbQa0u2yDQIsJg2De64GwaELAFu7BRWwMISaPkUEDQHqC/95yj19Hth5wsl9Bvfcjze6vyWiUCr+FglxjMjACv2a3VYwQjA6uBledrICEB5+oVpVU0QyM/PB/U+JOHrASgVDBERERwRTD0T/f39pTqW9xyaGDrz9/M4Gv4Iayd0Rq+m7GHSpA4x8PDSN+PXH2VzPf6oPFRIGrjZY2Zffzwb4AVba1bqayDkki3PU+dj95UHHPF3MZa/NTH578Q7feHubCeZXmIepMSHS6PikZEAHF4AnF0HPP8L0ILm4zFRMgLVPqaldB611Ik+Chz7Bogup8LF0gZoP0oz3MPdV0oNy5z19tG3sTt6N/d3L2cvzA6YjUE+g0yqU3mHKzGeGQEo23CSVDFGAEoKNztMBwFGALJwYAiYEAFGAJYE/1FaDib9cgaX7qZwL9CE37+mBqJVA/mWn5gwfGR5tPZm/E46cCarLo6Vk/FXz9UeM/r64flOXrIdAiFLkCVWKiUzD3+cicEvx28jLqV4AndpNSwtgIEt6+H9YS3MpjenEh8ujRYe5zYAe94HcjQ/UqFWE2D6KZNNHjWaXdV8o2od01L5noi/iH3AkUXAvZK9pkuoQFNzAyYCgTMAN2kG7mWrspGjzhEs641Ni8WE/yZgUutJeK7pc7CxspEKtUqdo8R4ZgRgpVxtdhcxAtDsXKoYgxgBqBhXMUXNEQFGAJb06qpDkfhqz80Sf6R+cAffDGYloQp5A1y88wjv/e8kriYLZ/LVdbXD9GA/vNDZG/Y24k4zVAhsslTzdkIG1oVGY1PYXWTmCveqcrazxvOdvDGxh4/ZEH9ahyjx4dJowXRlM/D3yyW3G7QACJxutCPYRtIjUK1jWgq4b4cCBz4DYk8Kn2bvBnSdCnR5FXCSZoKuOl+N7VHbsfLCSnRv0B3ze8wX1E+Vr4K1pbUUaFX5DCXGMyMAq+x2s9iAEYBm4UZFGsEIQEW6jSltLggwArCkJ/PzCzDrf+ex81Ic90INRxv8PK4T6wWogIDPUamx6lAUvjsUCZVuUzgd3T1c7DCtty9e6tqQEX8y9mlMYiY+23kNB27Eo3AoPK+21LORSL/nO3vD1V7eWSKVhVuJD5eVtbXMdeT8NQOAu2c0L1nbA8HvAkGzjXYE20h6BKp1TIsJ9/0LGuIv6oDwKc51Ndl+nV4G7FzE1KbE3jeTbmLe0XmISoni/m5pYYm/n/gb/jVN2/LFGAAoMZ4ZAWgMzyt/D0YAKt+HSrWAEYBK9RzT2ywQYARgWTdm56kxbu1p3H+chfUTu8CvjrNZ+NqcjTgfk4y3/76EiIfpvGbWdrbF1N6+GN21ERxsWcaf3GMhKSMXgQsOIEeVz6tqx4Y18ErPJhjYsq7ZT2lW4sOlUeMr9jSwZiDQ5jmg30dADW+jbs82kx6Bah/Txob8UThw6HPg2j/CO9doBPR4HWg/2iTTsROzEjF0y1BkqjKLdOzt1Rsr+600NhqS76fEeGYEoORhIssDGQEoS7dUC6UYAVgt3MyMlCsCjADk9wz1HMtRq1HHxV6urmN6AaCBLd/sDcfa0GjeTLGajjaYFuyLMd0awdFWGeVEzLEaBN7dcgl/nI4tgsPK0gJDWtfDpKDG6NCwZrWBSYkPl3o7JztFM5zAuV75Zb1JtzT9/5iYBQJmHdNSeuhxLHBkIXDhd6CA/8cSEPFHWbNEoFuZ9jtw9YXV+O7id0UIda3XFSv6rYCDtYOUqBn9LCXGMyMAjR4GityQEYCKdJtZKM0IQLNwIzNCqQhUVwKQSn1z1fmsDFSpgQvgeGQC3tlyGTFJxRkFWnMsUYB+ngVYMC4Ytd2kK3NSMJySqx75MB3h8WkY2qY+79kR8WkYsPQoXOytMapLQ4zv7gMq+a1uosSHywp9pFYBYes0030zEwE7V2DWecCpdoWXsgXKR8AsY1pKt6Q/0hDnZ9cA6lz+k6nUt9dcoON4SYfmFBQUwMKCn1bIyMvgsgDrONbBnI5zENggUHCtlHBW9SwlxjMjAKvqdfO4nhGA5uFHJVrBCEAleo3pbDYIVEcCkHrFvfnXRWTn5eOHsQGgzCImykEgJSsPC/69jv+dKc4O09W+RT1nDK/zGF5OwMCBA+HgUP1II7l6kx4OQyMTsSbkFg7dfAQa3nHi3b5wEejf99+VBwjyr82tq66ixIfLCn0VdxH4oVfJZZ1fAYZ9U+GlbIHyETDLmJbCLVmPgeMrgJOrgbwM/hPta2h6ZHaZAtg6SaEVd0ZKTgrWXlmLq4lX8dOAnwSJvTupd+Dt4s31ADQXUWI8MwLQXKKvanawp5+q4ceurjwCjACsPHbsSoZAlRGobgQglfZO+fUsTkUncdiN6dYQ80e0NotfoascDArYYN+1eHyw7TLiU3PKaGtrbYk5/ZtiTOd6OLh/P/c6IwDl4VTqq7n9wn2uVPvGg7QSSn04vCVX1suEHwElPlzq5cvNk4HLfxUvpQEfc65JNpFULx3ZIlEQMNuYFgUtALmZwOkfgJBlQPZj/lNsHIFu04HurwEONcTSpMy+eeo8bLy+ET9d/gmpuanc68v7LEffhn0l08HUBykxnhkBaOqokcf5jACUhx+qoxaMAKyOXmc2ywaB6kQAUvbR8z+cwJnbySXwnze4Odcnjol8EUhIz8En268WTWcurWlnn5pY+Exb+Ho4Q4k34/JFvmqakd9+O3mH+ychnb9UzbuWAw6/1Ydl4gpAbbbxTP3LVnYCVNlAs2HAgM+A2n5VCzh2tSIQMNuYNjb6qlzg/AbgyFdA+gP+3a1sNRN9e74JONcxtgYV7kcE4BPbnsC99HtFa5u4NcHmJzfD2rJ6ZG4rMZ4ZAVhhaFeLBYwArBZulqWRjACUpVuYUtUFgepEAJJPT91KxNg1p7n+fyROtlZYPSYAvZp6VBeXK8pOIm3/uXAfn+64iuTMvDK6k//eGdKcm+5rWVjKrcSbcUU5RQ9lbz5I48p8t124j1yBSb60TQ1HG7zUpSFm9vVjQ1rMjQCkrKXoo0CzwcIRc3Yd4O4HNO6pR1SxJeaCAPuMrsCT+Wrg8t/A4S+B5Nv8i6mEtt1LQPA8oEZDk4bGv7f+xbxj84p0sLKwwtpBa9GxbkeT6iXV4UqMZ0YAShUd8j6HEYDy9o85a8cIQHP2LrNN9ghUNwKQHLLz0n3M/P086rjYYd3EzmjVwE32fqqOCt5/nIUPtl3BwRsPec3v3dQDXzzdGl41HUu8rsSbcXPwLw3WORL+CGtCohESmVCuSU08nPByj8Z4pqMXHGytzMF80WxQXDzn52tKew98BqTeB6aGAPVai4YP21h5CCgupqWCuKAAuLELOPg58Oi68KktRwB93gc8mkmlWbnn5Bfk48WdL+J60nUMaDQAszrMgo+bjyx0k0IJJcYzIwCliAz5n8EIQPn7yFw1ZASguXqW2aUIBKojAUiO2XQ2FoG+7mXII0U4zcyVJCLp99MxWLj7BtJzVGWspayxj4a3xNMdPHl7NyrxZlzpLg2NTMBH/1xB1COBxvSFBvbwc+f6/QU3rVOUsal028XWX1HxTATG+uHAnZBiWJr0AcZuBQQmg4qNH9tffggoKqalgu/WEQ1pfu+s8Im+/YB+HwINOkilFXfOrZRb2HB1A97p8g7sqVcnj1x6dIn7a1uPtpLqJofDlBjPjACUQ+SYXgdGAJreB9VVA0YAVlfPM7tlgUB1JQBlAT5TogwC0QkZeGfzpaIhLaUXDG1TD58+2RoeLnaC6CnxZlzpoXAh9jGeWhXKa4atlSVGtG+Al4Mao0V9V6WbKrn+iovnw4s0pYu6MvpvwH+A5NixA+WJgOJiWkwY74YBBz4Foo8In+LVBej/MeATJKYmZfZ+mPkQqy+uxtaIrVAXqDEnYA5ebv2ypDoo4TAlxjMjAJUQWeLryAhA8TFmJ/AjwAhAFhkMARMiYI4EoEqdj893XcfIjp5o6yXdNDwTulHxR5PPqHR0yb5w5PD0jCPCb/6IVhjcun6FtirxZrxCoxSw4JnVxxF2p3jAjruTLUZ3a8RN2q7jwp81ogCzTK6i4uI5NwNYEQCkxWmwa9wLGLwIqNvS5FgyBeSBgOJiWgzYHl7XlPre2Cm8e93WQN8PgaaDTJJBO+PADBy9e7RIPxdbF+weuRtudqxtiq7TlBjPjAAU402tvD0ZAag8n5mLxowANBdPMjsUiYC5EYAZOSq89sd5rm9cbWdbbJ3eA961SvaIU6SjzFjp63GpmLf5Ei7dTeG18rkAL3wwrCXcHG30QkGJN+N6GWbiRdl5aiRl5KJBDQdeTf69HIfpG8/Bv44zXunZGCPae8LehvX3q6rbZBnP6jyAJnwKlfVe+B0IWQoMmG8y8qKquLPrxUNAljEtnrkld6ahHocWAJf+BFDAf2rNxkDfD4BWIwFLS6k0K3PO1YSreHHXiyX+PrnNZMzqOMtkOsnxYCXGMyMA5RhJ0uvECEDpMWcnahBgBCCLBIaACREwJwIwOSMX49edLkEk0bCBzVO7o6aTrQlRZkfzIZCjUmPVwUh8dzgKqvyyD0JeNR2wYGQb9PQ3bEKzEm/G5RwhlJ25+dxdLN8fAa9ajvhzSjfe3ou07lR0Err7uvO+Lmcb5aybrOJZO6Rg34fAwM+B5sP4oaNBIAVqwEo/0l7O+DPdjI+ArGLa+Obx75j2ADj6FRD2C5BfdqI9d5FLA6D320CHMbJ578w9Mhf/3f4P9lb2GNtyLCa2ngjKBGRSjIAS45kRgCyCCQFGALI4MBUCjAA0FfLsXIYAAHMiAHNV+Ziw7jSORyUW+dbO2hJrJ3RGD7/azN8yQuBcTDLm/X0JEQ/Ty2hFSUXjA30wd1AzONlZG6y1Em/GDTZSggtoGMvuKw/wzd6buJVQPNxj/cTOCG5WRwIN2BGEgGziOe4i8N+7wJ3CXo+1fIHpJwFr9uMKi1TDEJBNTBumduVWZyYBocuBUz8Aqiz+PRxqAT3fADq/AtjwZ1hX7vDyryooKEDIvRD41/RHPad6vItjU2Ox7uo6TG03FXUc2ec+H0hKjGdGAIrxjlLenowAVJ7PzEVjRgCaiyeZHYpEwJwIQHJAanYenv/+BG48SANNi/15XCd08qmlSN+Yo9KZuSp8szcca0OjQclEpcXXwwmLn22LgEaV95kSb8bl5Gt6KDwS/ghf772JK/dSy6jWqoErdswMYlN8JXKabOL58t/A5kklrabeft2mSoQEO8ZcEJBNTIsJaE46cGo1ELoCyOFvbwFbZyBwJhA4A7CXdkDS5UeXsfTcUpx5cAYj/Ufi0+6fiomGWe+txHhmBKBZh6TexjECUG+o2EIjI8AIQCMDyrZjCBiCgLkRgGR7XEoWXv/jAhY80wa+Hs6GwMHWiohAaGQC3tlyCbFJZbMgrC0tMLW3L2b29aty3zgl3oyLCLtBW4fdScKi/27idHSS4HXdmtTC6tEBrKzeIGQrv1g28UyM/c/9gHthxcb4DQDG/F1549iV1RIB2cS0GOircoCz64BjXwMZj/hPsLIDukwGguYATtJXJ2wO34xPTnxSpJulhSW2PLkFvjV8xUDE7PdUYjwzAtDsw1IvAxkBqBdMbJEICDACUARQ2ZYMgeDgYBw5cgS9e/fG4cOHBQGpiACka/v06cNdf+jQIdC+YkhERARUKhWsra3h7+9f5SMoi8lCqEF9lXdnGxiCQEpWHhb8ex3/OxPLe1lrT1cseqYtWjUwzmRBJd6MG4KnGGtpEAuV+u6//lBw+zaebnh7cDME+dVm7y0xnCCwp6ziOeYksHYQ4OYN9P8EaP2MSaaTSgg/O0oEBGQV08ayT60CLv0POLwQSOH/roOFlaa/H/X5c6PHH9NIQlYChm4ZiiydkuQ+3n3wbd9vTaOQwk9VYjwzAlDhQWck9RkBaCQg2TYGI8AIQIMhM+0Fubm52LBhAzZt2oRLly4hKSkJNjY28PT0RPfu3TF58mTu3/rI7t278eOPP+LMmTN49OgRPDw80LlzZ0yZMgVDhgypcIuUlBR89NFHnC6kR8uWLfHmm29i9OjRFV5r7gvMmQCk3mT/XX2AIa3rMSJC5oG89+oDfLDtCh6m5ZTR1NbaEnP6N8Xkno1hbWW8SYdKvBk3lRvvJGZgyb5wbL94n7ckm/Sisuy3BjbDYPZ+M4mbJI3nqENA+kOg3QvCtl7bDvgPkLRXmUmAZ4eKhoCkMS2aFYUbU2bstX+AQ18ACeHCpxFZHvweUNtPbI302n/VhVX4/uL33Frq/zez/Uw86fsku6fSC72Si5QYz4wArISjzfASRgCaoVMVYhIjABXiKFLzzp07GDZsGK5evVqu1q+99hqWL18ueCNBWWdE8q1Zs0Zwn1deeQU//PADLC35iYH09HT06NGDIyFLy6effsoRg9VZKiIAtdlxhNOcOXM4qFxdXcvgLbcMwOw8Nd7adBE7L8XhzQFN8Vq/qmcLVuc4Ecv2hPQcfLL9KucnPuniUwsLn2mDJiKUaCvxZlwsPwjt+zgzl+vx97/TsbwTmOk6zxoOeL2/P0Z28DQqQSu1rUo/T5J4fnQT2PshELEHsHMDZp0HnNyVDh3TX6YISBLTYttOxF/UAeDAfCDugvBp/oOAvh8A9duKrVGJ/dX5amSoMuBqy99bMD03HaN2jcKzTZ/Fi81fhB2VJTOpFAJKjGdGAFbK1WZ3ESMAzc6lijGIEYAKcVVeXh46dOhQRP61bdsWb7zxBpo1a4a0tDSEhITgm2++QUaGZlrkggUL8M477/Ba9+6772LhwoXca7Tn22+/DV9fX0RFRWHx4sU4f/489xqt+/LLL3n3mDdvHre2RYsWIMLP29sb+/btwxdffAHKUrx8+TJatWqlEHSlV1OJBGBKZh4m/3q2RH+yr59rh2cDTFdKI73n5H0ilV5vu3APn+64hseZeWWUdbK1wjtDmmN010aiDZFQ4s241F6lYTk9Fx0ClWeXFncnW8zo44fR3RrCztpKatXYeaUQED2eU+4Cy9sB+arik7tMAYZ+xXzBEBAFAdFjWhStdTaNOQUc+Ay4EyJ8UsPuQL+PgEaBYmtTZn8a8DH/5HzUdaqLFX1XCJ6fX5AP6v/HpGoIKDGeGQFYNZ+by9WMADQXTyrPDkYAKsRnf//9N5577jlO28DAQBw7dgxWViUfDsPCwrjXiCysUaMGHj58yJUH60p4eDhHzFG/t06dOuHo0aNwcHAoWpKZmcn1rTt79izXD+7atWu8PeEaN27MlQ1T77j69esXXb9s2TIuo+2TTz7Bxx9/rBB0pVdTiQTgoZsP8fL6MyVKFe1tLBEyry9qO7Nfr6WPopIn3n+chfe3Xsahm/yNz3s39cCXI9twmWViihJvxsXEQ2jv749EYeHuG0Uvu9hZY3KvJng5qDGc7axNoRI7kwcBSeJ582Tg8l/Fp1OvshmnZVOuyALDvBCQJKbFgOzBZeDg50D4f8K712sL9PsY8OsneX/MtNw0LAtbhk3hm1CAAk7Hb/t8iz4NNX2cmYiDgBLjmRGA4sSC0nZlBKDSPGY++jICUCG+pGy/pUuXctpu374dTzzxBK/mI0eOxNatW7nXqDy3TZs2JdZNnz4dq1ev5v524sQJdOvWrcw+J0+e5IhEElq/atWqMmtsbW1BWYhEFOoKZf7R36kXIfUXZMKPgBIJQLJkfWg0PtlxjTOKSIrVYzqip78Hc7MJEaCejBtPx2DR7htIz9HJIirUqYajDT4a3hJPd/CUpL+QEm/GxXJfecNwsnLV6P2VJgtwQncfbgpzTSdbsVRh+1YSAUni+XEssLIToMoGnDw0JYvtxwBWjAiupNvYZeUgIElMG9MDiVHAoS+BK+VMvHb3B/q+D7QYAQi0rjGmSnx7peam4omtTyApu3iKewOnBtj21DY4WIv7w5vYtsl5f8XFMwBGAMo5oqTTjRGA0mHNTiqJACMAFRIRM2fOLCLirly5IlheO3fuXHz99decVUTOBQQEFFlID6NeXl64f/8+mjdvjuvXrwtaT6/fvHmTGy4SGxtbhjigfWgISGRkJOrWrVu0z4oVKzBr1iyuByCVBhsiuv3u9Llu/PjxWL9+Pe9SKkf+5ZdfEBoaigcPHnCZkJS1OGjQIC5DUTdrUXcDylzU6k14ZWdnY+XKlfj999+5bEcSKnseN24cpk6dymVJ8olQD0AfHx+ul2N5omsXXw/Av/76i+vPSAQv9WJs2LAhRowYwZV816pVSx/oyqwxZArwl/9ex7bz97BuYmejTY6tlNLsIkQnZGDe5kslyrJ1YRnWpj4+ebIVPFyky9BU4s24sUNJnV+Arefv4YcjUfjtla6o62rPe8TJW4nwcXdCPTf+142tF9vPcASMFs/Jd4CajYQVOLIYUOUAQbMBOxfDFWVXMAT0RMBoMa3neZVelnIPOLoYOPcrUKDm38bVCwh+B2g3ShaE+Y6oHXgv5L0iXX3dfLG873I0ci3nvV9pgNiFhIBi4lnHXYwAZLFLCDACkMWBqRBgBKCpkDfwXC2xRpfpkwFIGWaPHz/mBkto5datW1yvP5JXX30V33+vmUDGJ/S6NoOPriPyTFdmzJiB7777jiMiiTQjQvDgwYOYP38+cnJycOHCBS4T0BAxBgFIPRDHjh1blAXJd76zszP++OMPDB8+vMzLugQgEYeDBw/mbOETysLctm0b76AUMQjAAwcOYN26dfjtt9949fHz8+NKw+vVq2cI7NxaQwhAyjhLzMiVlFQy2CAzv0ClzseakGhugmyOKr+MtUT4zR/RmpscK7Uo8WbcWBjRjwZ7rsbjm703EfEwndt2dNeG+OLpkpnYxjqP7SM+AlWOZyL+DnwKXN0GTD0G1GW9ccX3GjuhPASqHNNiw5uRCIQsAU7/BKjLTrDnjnesDfR6CwiYCNjI5wcU+g54ec/LuJp4FVPbTcXYFmNhY1WyFY/Y8FW3/WUfzzwOYQRgdYtSfnsZAcjiwFQIMALQVMgbeG5CQgKI4KGsO5q+e+TJJZUVAAAgAElEQVTIkTI9AGl4B5X00hCO0aNHlyGKdu7cWVQ6TOXEs2fPFtSCXqeyY5Jdu3Zh6NChJdaSPl26dEF0dHSZPSqT/UebEHnHt5/uAaTX2rVruT+VPketVmPAgAE4dOgQ9zoRdM8//zyaNGnCkXSnT5/mBqXExMSASpgpO5D6IOqKLgHYvXt3LouSMv1oL8quo6xIIjm12ZNEohJZWlqECEDqwUj+0ZZm095EWJIQMUl61qxZk8u8JNElRUmf48eP46mnnuIyEBs1aoT4+HguM5R8RPLiiy9y5KahoksAUpzRAAlWjmgoitKsvx6XymX9Xbqbwnvg85288P7QlnBzNM1DhxJvxo3hudDIBCzecxMXYx+X2M7a0gIH3uyNRu5OxjiG7SExAlWK58OLgGPfFJMYvn2BsZoWHUwYAqZCoEoxLabS2anAye+A4yuB3DT+k+xcge6zgG7TADtnMbXh3ZsIvtD7oQisHwgrS/4hTbGpsbC2tEZ95+L+2JIrWo0OlG08l+MDRgBWowAtx1RGALI4MBUCkhGANDBCV4jkECqfLL2WBlpoh1nk5+cjNTWV24qy25KSkkBfyFpxc3PjyB0+SUxMBF2vFbrezo6/NI72JUJJn7XJyckcaSO2UObfqFGjQIM6aHovEXhNmzblykCJzCJyiyYCd+zYEf/++2+J0lzSjciqadOmcWpu2rQJzz77rKDKukNHhEguIp/ef/99LiORiEkqjSXSkMgpMYQITCp1JR/SoBIq89UdckL2v/XWW9zfSCfK3ist5KuePXty05SJSKXpybqiSwDSPnv37gWRebpCsdGyZUuOfKMsx4sXL5Y5R4gA1C6sTA9Auvbzzz/nMNcVin+ylXSl9xSVeHt4GNaXT0sAWllZY+3lLFBp4uZp3eHOhnuIEcqV2jNHpcaqg5H47nAUVPnFn3nazbxqOmDhyLYI8q9dqf2NdZESb8arYvuF2Mf4as8NhEYmCm4zp39TvN7fvyrHsGtNhECV4vnwQuDwgpKaj94M+Pc3kTXsWIaADEsm87KAM2s0ZHlWcf+8Er6ytge6vgr0mA04Vq7VSVV9H5Magy9Pf4nQe6F4r+t7GNV8VFW3ZNcbAYEqfUYb4fzKbMEIwMqgZn7XMALQ/HyqFIskIwC1hIcWmPL62Dk5OXEkl1Yoc6tz587c/5YmAKn/HGWjaYWyv0oTNtrXSvdfI0Jp2LBhvL6i0laagKsV6rumncJb+gLS7cyZM5L4/MaNGxzRt2bNmhLEJx1OWLz77rvcAA5HR8cy+nz11Vd4++23ub/v3r2blyDTXkSva7P+qKfgm2++KYl9QodQvFAGHBGclNFHMeHu7l60nCYfU0ZcXFwcp6u2DyLffrq2UUaev3/xg7kuAUhkJmHNJ4TzwoULuZeo1JqIZ10RgwCkfo4UZ6XfS3Tunj17ivz5zz//4MknnzTIX0QA5ubl4UZ8Jt7cE89d2967Bv6Y3A0Otvy/cht0AFtcJQTOxSRj3t+XispKdTezsAA3ROKtgc3gJIPpsUq8Ga+McyLi0/D13ptcya+QtKzvirmDmyG4qYckA1gqYwe7pnwEqhTPuRnAigAgLU5ziL0bMPRroO3zDHaGgMkQqFJMG1NrdR5wYSNAmbJp9/l3trQGOo4Hes0FXE2XUUeTfReeWojc/FxOTxcbF2x/ejtqO5j2BzdjukOpe8kmng0AkBGABoBlxksZAWjGzpW5aYwAVBABSKWjRFD9/PPPKJ0lqY0zKmn98MMPeQkgKl2lslkS6ifXt29fwfCkfn79+vXjXqfrPvjgA5OFMhG8RLLevn0bLi4u3PRiImh1hTIgg4KCuD8JTTfWrqdSYyq3JaFBIboZi7oEYFhYGJdNySe6GZJUet2+ffsSy8QgAImM1JZll9aJMNJm/VVU3s1nDxGAj1IycfVBBr4ISS5aMqhVXXw/JoCRFyaK/sxcFb7eE451x6Ohk+hcpI1fHWcseqYtAhqJn4GsLwRKvBnX1zZaF5uUiaX7w7lBODyJmNxWjWs74Y0BTUFDWCwt2S2eIfjKbW2V4/n8RmDHLKDzK0DveSbLXpIbrkwf0yFQ5ZiuqupUiXN1i2ayb1KUwG4WGqKcBnzUalLVE6t8/ZkHZ7jefroyvMlwLOhZKsO3yiexDQxFwOTxbKjCbApwJRAzz0vY3aF5+lUJVjECUCEEIJFWQ4YM4YY8WFlZcVluEydO5LLhaFLtqVOn8Nlnn3ElrZQhRhlwpckiJWYAEunZv39/zm7qj0elvXxZm8uXLy+3p6HQm3HRokVFWZG0RpcAJMz5MilpnS5BevToUa6sWFfEIAD5ejFqz6TMWIoLEooDIoENESIAc3LzcO5uKj46pClltLO2xPIXO5hkkIQhupvrWuop986WS4hNyipjIvWVmxbsi5l9/WBnLa8MTSXejOsTQ4/ScrDyYAR+Px2DPHXZEmzao56rPVfq+2yAF2ysLPXZlq2ROQLlxnNaPHDoc6DpEKB5yT65RWYR2ZEcDbhrBnAxYQiYGgGTfUbTr1gRe4ED84H4y8IwNBsG9H1fdgNz3jv2Hnbc2sHp7eHggbe7vI3BPmVbzZjav9XtfJPFcxWAZhmAVQDPjC5lBKAZOVNhpjACUCEE4Ny5c4vKWtevX4/x48eXCTWVSoWBAwdyQzCILDt37hzatWtXtM7YPQCliPVJkyYVDf1YvHgxCAc+ob54X375pcEqffzxxxzppxVdAlC3t2TpjXWHc/CVnYtBAJZX3k76aUuDS9ukDyjaHoC5+cDYTTGwsrTAz+M7yyqzTB87zGFNSlYevtx1HX+ejeU1p42nG5f117JB8YRvOdmtxJtxffB77Y/z2HGRv0ytpqMNpgf7YWxgI9jbyIuQ1cc2tkYYAd54zs0ETqwCQpYCeRmAux8w/STApn2yUFIAAib5jL4dChz4DIg9KYxQ415Av48Br5LD2eQCaUJWAp7+52k84fsEprebDmdb6YeQyAULOelhkniuIgCMAKwigGZyOSMAzcSRCjRDMgKQDQGpfHQQEVW7dm1u4AkN/aBJtEKiWwpLQ0KoHFQrxpwCXHlr9L9yyZIlRb0HifAk4lNI3nnnHVA2HwmRc7r9Acs7sU6dOqB/tFLdCUAaIpJq646ajrZo4sFubvWPVuOs3Hv1AT7YduX/7J0HdFTV1sd/6ZWEEHpooXfpvXcQqSpPRcHyKRYsiGABRFCqPH0oYAVRsIOA0kFAqvQOoXcC6SG9fuvMJKTMJJk+986cs9ZbT51z9tn7v/fcnPufffbm7r1UHYEiI/ON3nV5rlMo7grOLlPjYdwQ74maf30//afAtV8/Tzee7VyT/+scSilv+3RdNkR3Ocd0BPTG88kV8HvB64D0n6NtUiCHREDhCNj0GX3rqJb4u7i1aFQqt4CeU6BWd7sid/jOYc5Gn+XxBo8XqUdCWoIk/uzqJd3NbRrPFrJdEoAWAlLlYiQBqHIHqlh9mxGAlsKocBMQkenm6CM8PJxKlbTFj0eMGMHPP/9cpMniOrCPj4/mc9EZVjS8yB2XLl2iVi3tNaQXXnhB0xW4qCE+/+qrrzQfi3WhoaE2hVno/dBDD2k6Mbdv316T1VhUx2ahWP7rzXv27NGsMWVIAtC9QFMUUzCUa4xHQFwvnfrnKdYez2kWUEhEmxplmDW8iSpIWTUexg312Ju/HmPF4Rt4urkysl11Xupei7KyU7ah8Klynt54Ftd6v+kJtw7n2RRYFV49Cm7uqrRTKu08CNjkGR1xTns9/vTqooEtVx96TIL6A8UVBrs5IDolmv8e/C+rL67G3cWd3x76jdpBte2mj9zYOARsEs/GqVTibEkAlgiRU0yw31PPKeCVRhaDgCQAVRAe+Rs8DB8+HNGAoqghuuQGBGivBg4cOJA//9TWKxFDZBJWqVKFW7duUb9+fc6cOVOknAYNGiA6DoeEhHD9+nWbNoEQerVr1474+HiqVq2q6XwrOhwXN7Zs2ULv3r01UwSJJ67BmjIcnQAUMXA7LgUvD1eC/bzuQ5R7BVhkAObvimwKhnKN4QgIf6w6epMP/jxNbFK6zkKRYfb2gAY80aaaappJqPEwLoDPyspmzbFbmq7XfRtV1OtE0QBkwbYLjO1Zh5DS2h9a5HBsBIqM56t7YYmo/+UCzZ+A7pPs2qXUsb0grbMkAlZ9Rsdehx2z4OiPkJ2lX+3S1aDbu9omH672LZmQnJFM/xX9iUrR1j4Wo2WFlizpu8Sm515L+tfZZKWe3czGM/Fku7pryiDlJkEoGQdJACrZO7bTTRKAtsNa7lQQAUkAqiAiRNZjUFCQhhCrXLkyV69eRRA1+kb+a75jx45l/vz5Baa99NJLLFq0SPPfiuqWu2/fvvsZdGL+ggULbIZSVFQUbdu25eLFi/j5+WmamhTusKtPGZH5KMhKcU26YsWKGvIyMDDQaL1tRQCKA4rQeeLEiYjry2II4rZwRmtJtQbzG1hSDUBBcFyPSULUmHPBherBvgT4aK8tSgLQ6FAxe8HN2GTe++ME28Mi9MrqWrccM4Y1UR3RZNWXS7NR1xUgSNitZ+7y8aYwzobf0+D99/iuimuuYgXTpcjiEBANC5JjSHbxYdOmTZqZOi+X/8yFOn2hUlOJpURANQhY5RmdEAE758HBbyEzTT8WfuWh6wRoMQrcPRWD1/zD8/n6xNcF9Pmk2yf0qt5LMTpKRfQgcPcsbJ6saSxzIuRxLpXvJwlAGSiqQkASgKpyl0MpKwlAlbjz8ccf56efftJoW1SGW0xMDJ06deL06dOaeRs3btT8Mcw/zp07R6NGjRANQ1q1aoXoYJv/1zJxMOzSpQsHDx7UkIxClq0ywtLT0zX6CtJLkFki03HYsGEGe2jmzJm8++6791/UVqxYgb+//jp2IlNy6dKlvPLKKwXk24oAFN2bL1++zMMPP8zXX2sPntYkALOys7kckUhiWsZ9e11dXKhZzg9fT3dJABocZeZPFETs8v3XmLXuDIlpmToCS/t6MGVgQ4Y2D1FlBoJVXi7Nh12vhH2Xopi7MYxDV2MKfP7BoEaM6lDDSrtKsYpHICka1o6D28dIHrWZTdt33/+7oobsEsXjKxW0KwIWfUYnx8Kez2DfIm1DHH3DOxA6vq6tkenpZ1fb9W0usgBFc4+bCTfx8/BjbPOxjKg3AndXeZ1fcc4SCiVGwvaZcHAJZGvPUGlufmxpOJfuA4bJDEBFOk0qpQ8BSQDKuLAXApIAtBfyRu4rMtpatmxJUlKSZqWojycaYwgiSWSSiay9Tz/9lGvXrmk+79mzJ+JarL7xzjvvMGvWLM1HzZs312ShidqAIutONNI4cuSI5jMxz5TOukaadn/6lClTmD59uubfn3zySSZMmFCsKJEVKbL+coeoF9i3b1+2btUWmxbXh8eMGUOHDh0oXbo0gvQTDVQEwbhq1Sq8vb0R16vzD1sRgCNHjmT58uWauoaCuBRZj6LRi8gAFERgbmMSS2YAhsclF2guIbIAq5bxobSvpyQATQ1aI9ddjkxk4orj7L8crXflg00rMfWhRpQrlXc928gt7D7doi+XVrLm5M045mwM459z+rMvRV2/fyZ005DjcjgZAue3wOqXISFcY3hG81Gspafmn9VyvczJPCbNNRIBizyjRSfs/V/Crk8hJVa/Bh6+0O5F6PAq+JQ2UkvLTheZ3rm3JPRJ3nF9B2svrWV86/GU981rDGdZLaQ0sxHIyoTPWkDMFR1RF8v1ofIz30sC0GyQpQBbISAJQFshLfcpjIAkAFUUE4LQe+yxx3RIq8Im9OjRQ5M9JwgyfUNcKf6///s/Fi9eXKT1zz77rKYJiC2brIwePVqTlWfo0NcZWBxsBen3/ffflyhGNDYRDU7yD1sRgEePHtXUOUxN1e32mt8uSxKA4gB8IyaZmKQ03FxcqBbse79zqbwCXGK4mDUhIzOLb3Zd5pPN50jN0K2LJAi/D4c0LrL2nFmb23ixRV4uraTzxYgE/rvpHGtP6G+2IratV6EU4/vWo1eD8qrMwLQSdM4hVlz7/bYP3NhfwN69tcZzN6CpJACdIwoc3kqzntEZaXDke9gx9z5JrgOYqwe0ega6jAd/+5Npl2Iv8dG/H/Fck+doX9m0BnEOHxRqMvDfL2F9wQSBFPdATld+lAaPTZcEoJp86eS6SgLQyQPAjuZLAtCO4JuytaiR9+2332q6+546dYrY2FjNVV1R965169aIq8KDBg0y6MV13bp1GpJPNNkQmXAiA03IEB2A+/fvb4p6Zq2xBAGYq8ChQ4c0OIkrzqLYbmJiouY6cI0aNTSZlMI+0SSlcGdhWxGAQk+RaTlnzhxNncOIiIj7ZKC1CECxp7gKfDMmWdO5VDQ7yB2SADQrdItdfPpWvCbr78TNOL3zRrSqyrsDGhDoq63HqPZh1sullYy/FZvM/7ac5/fDN8jMyta7i8iGHde7LoMeCMHNVR7LrOQK5YuNughfdIJ0bbZ9tndp9lcaRXjplpIAVL73pIYGIGDSM1pkXp34HbbP0Jt9pdnWxRUeeAy6ToSg6gZoYt0p4mrvl8e+ZOnppWRkZVAjoAYrBq3A00059Qeti4CDSs9Mh4XtIOoCuHuT3vpFNiXWJ8PNRzXPaNkExEFj00iz5EnTSMDkdIshIAlAi0EpBUkEjEdAZGOK5i5i6KsBaLxE01ZIAtA03IpblZqRyed/X2DR9otk6CGdqgT5MGtYUzrVKWv5ze0o0aSXSyvpG5WQysLtF/lh31XS9GReim1F9uWrPWozonU1PN1draSJFKsqBA58q60BWKsnyX3nsWnvcY368gqwqrwolS0CAaOe0SIr9uxa+PtDiDhTNKYNBkH396B8fcXgvurCKibvnlxAH1Hf7/mmzytGR6lIEQiIbtLu3uBfTv+EsPVwciX0ep9kz+CiGzUpFGBJACrUMTZWSxKANgZcbncfAUkAymCQCNgRAUsTgOKab3RimqaunzFZTJIAtGwQiKYSIuvvwt0EHcEuLvB0h1DG963rkDXmjHq5tCzsBaSduR3Pw4v26G20IiYGeLvzYrfajOpQ3SH9YEVoHV+0ID3EC2a9/iSnpKju5dLxHSQtNAcBg5/Rl3bA1mlw82DR29XqAT0mQ0gLc1SyytrMrEyeXP8kJyJP3JcfGhjKykErZYMPqyBuAaGp92DXJ7B3ATR5BAZ/XqJQg+O5REm2myAJQNthreSdJAGoZO84tm6SAHRs/0rrFI6AJQlAcb33Vkwy0Ulpmtp+NYJ9DboKLiCSBKBlAiUpLUPTVfa7PVcQHELhUbu8P7OHN6Vldf31OS2jhX2lKOUwLq769vv0H84XImF9PNx4plMNnu9Si0Afx7h2bV+Pq2z3rCxt84LI8zDwvyUqr5R4LlFROUEiYCACJcb0jUOw9QO4vKNoiVXaQM8pENrZwF3tM+101GkeW/sYri6ujG40mv9r8n/4iuYkcigLAXHF/MgybaZp4t0c3VxgzE6o2KRYXUuMZ2VZqtFGEoAKdIodVJIEoB1Al1tqEJAEoAwEiYAdEbAUASjIjmvRSdxLSb9vTRk/T0JK+xhEAkoC0Pwg2HU+krdXHtc0Wik83F1deKlbLV7uURsv97zai+bvqjwJSjqMbzgZzphlhzQgebi58HibahoflC/lrTzgpEbWR0BcK1v9Elz+R7vXiOXQYKDDvVxaH0i5g5oRKPIZffeMloA5+1fR5pVvBD0nQ91+INLZFTCiU6Ip412mSE1+OfsLrSu2pmbpmgrQVqqgg8DFbbDxPbh7Shec0C7w1JpiY01JZw5DvSsJQEORcux5yniCOjbG0jr9CEgCUEaGRMCOCFiKAExNz+RCRIJOgwORcebr6V6ihZIALBGiIifEJafz0drT/Hrwht45TUICNVl/DSsHmL6Jilba8jCelZXNwasxtAnV//InrsQPX7SHGmX9eKNXXaqWkZkfKgoly6oqupd+1gLirufJ9Q2Gl/YV26nUlvFsWYOlNImAfgR0YjrlDmybCcd/EW1v9C8KCtXW+Gs8HFyVUSs1IimCuQfnsu/WPv4c+ieBXoHS5WpCICIMNk2G8xv1a+3ipu0m3XcGuBfduEWNz2hJAKopUK2nqyQArYetlFw8ApIAlBEiEbAjApYiAIUJiakZXI5M1HT6dXVx0ZAdhl5xlASgaUGw8VQ4k1ed5O69VB0BXu6uvNG7Ls91CsXdTRkvTKZZadwqWxzGBbG3/VwEczeEcfp2PKtf7sgDVUvrVVQ0/5DNPYzzocPOPrJcmwGYfwxeAM1HFmmyLeLZYfGWhikSgdyY9kqPpZfHYdyPLYesvNsDBZQuVQm6ToDmT4KbMkomiOf/j2d/5PMjn5OQrq2z+0jdR5jSfooi8ZZKFUIgMQq2z4SDiyE7Uz88dfpCn+lQrl6J8KnxGS0JwBLd6hQTJAHoFG5WpJGSAFSkW6RSzoKAJQlAgVlccho3Y1KoHuyLn1fJmX+5OEsC0LiIi7iXytQ1p1h74rbehW1qlGHW8CbULOdvnGAHmG3tw/jBK9HM2RDG/ivR99HqVLssy55r6wDoSROsioAozPnLSO0Vx4AqMGQh1Oxa7JbWjmer2iuFSwT0IJAcfYsbP48nNGIz7tlp+jHyCYJO46DN/4GHj+JwHLd9HJuvbr6vlwsuLBuwjKblmipOV6lQDgIZqfDvl/DPx5Aapx8WccW874cgmssYONT4jJYEoIHOdfBpkgB0cAcr2DxJACrYOVI1x0fA0gSgQEzUAzSmA7BYIwlAw2JNZB78ceQm0/46TWySbsaEn6cbbw9owBNtquHq6px/2q11GD99K56PN4Xx99ncAuEFffbjc23pULusYY6Us5wXgcRI2D4LekwCH/1Zo/nBsVY8O68DpOV2Q0A0Wjj0Hdlbp+OSEqNfDU9/aP+y9n/eyr1SG54YzqBVg0jO0NbcLeVZimkdptGrei+7wSs3LgIB8cPLmTWweQrEXNE/ya+89pkssrFdjauTrMZntCQA5bdFIOCcbwnS90pAQBKASvCC1MFpETCFAEzNyLR4IwlJAJYcgjdjk3nvjxNsD4vQO7lbvXJ8NLSJpvGKMw9LH8avRCby383nWHPsVpGwilqX0wY3okMtSQA6c+xpbL++H5KioF5/i0Bh6Xi2iFJSiETAWASu/QvrxkP4cf0r3byg9XPQeRz4qeM5+t3J75h3aB6Dag1iXMtxBPsEG4uKnG8LBKIvw2ct9V/3dfeG9q9Ap9fBq5RJ2qjxGS0JQJNc7XCLJAHocC5VjUGSAFSNq6SijoiAMQSgyD67HZdCdGIaNcv64WvEFd+SsJMEYNEIiUYTy/+9yqz1Z0lM061XU9rXg/cfasiQZiEGdVwuyRdq/9xSh/HwuBTm/32eXw9cJyNLf2F6Qba+3qsOw1pUMTrrVe04S/0LISCafOyYDbv+q32RFM09AiqbDZOl4tlsRaQAiYApCNy7A1umwrEf9a7OdnHDpfkT0HUiBIpXAuWMsOgw/Dz8qFJKv17pWemcijxFs/LNlKO01EQ/AmvHw4GvC37W5FHoOQVKVzULNTU+oyUBaJbLHWaxJAAdxpWqM0QSgKpzmVTYkRAwlAAUJNT1mCREx1kx3F1dqVXODy8P465KFIWdJAD1I3MpIoG3V5woUG8u/8wHm1big0GNKOvv5UhhaZYt5h7GYxLT+GLHRb7bc4XUjCy9ugT7efJKj9o83raaxbNhzTJeLrYPAinx8N2DBbObRA2pkSvBxbwjtrnxbB9A5K5Oj0BmOuz/WttsITVeLxw3S7cm+JFP8Q5prCi4EtMTWXh0IcvPLKdd5XYs6rlI/rimKA+ZoIwovTC/hbb2X9V22s6+VVqaIEh3iRqf0ZIAtIjrVS/EvNOJ6s2XBtgRAUkA2hF8ubVEwFAC8O69FERGVP4huszWKV/KIrXmJAFYMBYzMrP4ZtdlPtl8Ti8JVb6UF9OHNKZvo4oyiAshYM5h/Ot/LjF/63nupWboxbWUlzvPd6nJM51CjWpyI53kBAj8/gycXFHQ0OHfQpOHzTLenHg2a2O5WCJgKgKX/4F1EyDijF4JWcF12Rs0jMhSDenTpw8+PsopW3E66jRjt47lbnJerddPun0ia/uZGgu2WifqS574DRoOAQ9v/buKLuyeftBwsNk/zOTfQI3PaEkA2iowlb2PJACV7R9H1s5kAvDixYukpaVpfpWrV6+ezX6dM5QwcWSnSdscBwFD4zkrOxtRCy0hhxgRHe+qBPkQ5OdpNhjianFYWBji/728vKhZs6bZMtUsQDSbmLDiGCdv6s+aGNGqKu8+2IBAHw81m2k13c05jM9cf4Yvd1zS0U2Q3aM71GBM11oWiXmrGS8F2w+BpGhY1AHu3QZXd+j2DnR8HdwM74auT3lz4tl+YMidnRKBuJuwaRKcWqnffM9S0P0dkps8yaat2zRzlEYAJqQlaJp7RCTn1dqt4FuBNUPW4Ovh65RuVbzRl7bDxvfgzkno9YG2np8Nhxqf0ZIAtGGAKHgrSQAq2DkOrprJBOD169dJSEjQwBMaGoq3dxG/+FgYQEMJEwtvK8VJBKyCgDHxnJmVxaWIRNIysqge7Iu/t2UIqMTERK5du6axr1SpUlSpoqw6QFYBXo9Q0Vzl878vsGj7Rb0156qW8WHWsKZ0lJ1mi3WJOYfx2KQ0Os/edj8D0N3VhUdbV+XVHnWoGGibvzG2ije5jxUQuPi39kV06BdQ6QGLbGBOPFtEASlEIlASAhmpsHcB/DMX0pP0z37gMS05U6oCSo/pDZc38NY/b2ns8HD14Lkmz/Fsk2fxEo1K5FAOAhHnYPNkOLchTyevABh7GPzL2UxPpcezPiAkAWiz8FD0RpIAVLR7HFo5kwnA6Oho7ty5owEnODiY8uXL2wQoYwgTmygkN5EImIGAsfGcnplFRp4DuL0AACAASURBVGY2Pp6Wqf0nsv7EQSSXzA8JCSEgIMAMi9S59NDVGCauOM6Fu9ofNfIPUULs6Q6hjO9bF19P87KJ1ImOcVqXdBgXMZeemY2nu6tewZ9tPc+8zecY9EBlxvWuS42yfsYpIGc7LgKJUZCRAoEhRdsorqK5Wub5KDYpKZ4dF2xpmSoQOL8F1k+A6Iv61a3YBAZ8DNXa3f9c6TEt/kY8v/l53FzceKftO1QPqK4KVziNkuI5vGMWHPhWf2ffVs/AwE9sBofS41kfEJIAtFl4KHojSQAq2j0OrZzJBKC4/iuuAecOQQCWLl0aNzfLHbz1IW8sYeLQ3pPGqR4BffEsDr/iar01h9gjKSkJQeTnkn9iz7p16+Lqqp+YsaY+9pKdmJrBx5vCNA0nsvU0mq1T3p/ZDzelRbUge6moun2LO4zvOh/JnI1n6Vq3HG/2qafXNuGTq1FJNKzsfES06pxtS4XPbYTVr0DZOjDqT4uSfMWZocaXS1u6Re5lJwRirsCGdyFsrX4FvEtDz8nQ8mmd74q9Yzo8MZwfTv/AGy3fwF1c19czRCMQX3dfq5+F7OQ9dW4rMk33fwU75mqbeegb5RtC349ANGGy0bB3PJtipiQATUHN8dZY903P8fCSFlkOAZMJQKFCZGQkERF5dTrEfxMEoLXJi4wMbYF4d3eZjWO5UJCS7IVAbjyL747IjBL1/rwt1N23KJsyMzM1Nf9yh/jOiuw/cQXYWcbO8xG8s/IEN2KSdUwWV09f6laLl3vUll1mjQwIfYfxI9dimLsxjD0XozTSfD3d2PFWd8qVkle6jITX+aanJsDGd+Hw0jzbe0+Hjq/aBAs1vlzaBBi5iX0QSE+GXZ/C7k+12bA6wwVajoIeU8AvWK+O9orp9Kx0DfH3xbEvSM5IZkLrCTzZ8En74Ch3NRwBcVY8swY2TwFBPOsbfuWgxyRo/qTNfpzJVcNe8Ww4gLozJQFoDnqOs1YSgI7jS7VZYhYBKAiE27dvExdXxC9BVkBD7Cke9mKIzmXWJhutYIIUKRG4j0D+eE7JdicpLVPzWYC3OwE2ajLhbORfXFI6H607za8Hb+iNxCYhgcx5uCkNKskMNFO+qvkP4zWadeDzHVfZfFpbLiL/EE09pg5qZMoWco0zIZASD4s6Qpy2TqlmuHnC8zugQkOrI6HGl0urgyI3sD0CgoQ5uxY2vgOx+b4L+TUJaQUD5kJIi2L1s1dMv7XjLTZcyasXJzL8RHOPCn4VbI+n3NEwBG4e0tZVvbZX/3xRl7HDK9DpDfCyzw/I9opnwwDUP0sSgOag5zhrJQHoOL5UmyVmEYC5xqakpBAbG6u5Uigyi6w5xJXJ3KzDcuXKOdV1RWviKmXbB4HceL6R6MK99IJ/CupVLEUlKzU+ENmGnp6emnp//v7+TvM92nAynMmrTxJxL1XH4aLTrKg592ynUNzdnOcatKUjXxzGf1qzifXXXTkY6Yqem9WaLetVKMVfr3bCQ2JtaRc4nrwru+C7gZAbTXX7wUPzNQ0NrD3U+HJpbUykfBsjEHkBNkyEC1v0b+xbFnpNhWZPgAElPOwV00fuHuGp9U8VsGF4neFM7TDVxoDK7UpEQHSU3voBHP+l6KlNHoGeU6B0tRLFWXOCveLZHJskAWgOeo6zVhKAjuNLtVliEQLQlkar8UFvS3zkXupCIDeeT0S7sPicG1k5bImrC3wwuDFPtpPFry3h0eS0TN5eeZzVR2/pFdcmtAyzhjWhZjl/S2zntDIEznM3nGbp3qtkZus/2ghS+7WedXi4ZRVJtDptpJhg+KZJcGAx9JsJLZ4CK9dJzdVQnjlM8JVcYhkExPX3nR/Dns8hK11XposrtP4/6P4O+Bhep9aeMT1l9xT+uPAHLrjwcN2Hea3FawR6BVoGLynFcgic2wQ/PqJfXtW20HcGVGlluf3MkGTPeDZVbUkAmoqcY62TBKBj+VNN1kgCUE3ekro6HAL5Dy7RZRrxwdowvD1cmf+f5vRpVNHh7LWHQdGJaTy79ABHrsXqbO/v5c7b/evzeJtquArWVQ6TEdh7MYp3Vh7nSlSSXhlBvh683L02I9tVt3qNS5ONkAvth0BWljbDr6gOvukpkBAOQTVsqqMaXy5tCpDczPIIiOu+p1bCxklwT/+PVlTroL3uW7Gx0ftbO6aLa2QWkxLDhH8mMLb5WJqWa2q07nKBjRAQMfjDULi0LW9DkenXexo0HGKzH2AMsdba8WyIDsbOkQSgsYg55nz51gFdTHCtyJURFXBFATpRlTTNBBnOvkQSgM4eAdJ+uyJQ+OCyeN9N2tcKll1nLeSVq1GJjF5ygMuRiToSu9Urx4yhTahc2sdCuzmnmPiUdGatP8uP/+qvS+Xn6cZznWvyXOdQSnl7OCdI0uriEYi5CqtehJrdoetbikJLjS+XigJQKmMcAndOw/oJcGWn/nX+FaHPh9DkYZNJGGvFdFxqHJ8d+QxvN2/Gtx5vnN1ytvIQuHMKvugEnv7Q+U1oOwY8vBWnp7Xi2ZqGSgLQmuiqR7YkACHnp1+TnSbawh4FvgO+AfTkypss25EXSgLQkb0rbVM8Amo8uCge1BwFj12P5ZnvDhCVWPC3oVLe7kwb3IghzUJkEyEznXk9OolHvthLeLxuN0o3l2xGtq3Gq73qEewvu/2aCbVjLhdZJkeXw/q3Ie0euLrDc1ugcnPF2Cuf0YpxhWMrkhIH22fDv19Atp5a2uK70e4l6DrB7GYLlo5pkfH316W/+Pjgx0SnROPm4sYvA3+hXpl6ju0ztVsXeR6O/azt3ltUSYXjv0HNbuBfTrHWWjqebWGoJABtgbLy95AEoJYAtMQQWYGnAFEtuog2WZbYxmFkSALQYVwpDVEjAmo8uKgB561n7vDKj0dITi/4IlU50JvvnmlD3Qr26VanBuyM0TEzK5tHv9zLoasxBZbV8M/msVqZPDWkj6ZbuxwSAb0IRJyDhe0KEh5l68ELO8BDGXEjn9Eydq2KgLj6LhotbJ4CiXf1byUImP5zoJxlCDVLx3R4YjgPrnyQtKy8H9ualWvG0v5LcRV1CuVQFgJJ0bB9Fhz8FrIyYMRyaCBem9U5LB3PtkBBEoC2QFn5e0gCELoC4m7QdKAtIIpe/AYcBCJyXCh+fhAVR0VV0srAv8D7gDgliiIYI3L+X0w/DTQDRGagHEUjIAlAGR0SARsjcOhqNE2rlNZ0P1XjwcXGcBm93fJ/rzJ51cn7DVVyBTSoFMB3T7emQoDyrrAYbaSCFly4e48B/9tFWmYWvp5uvNGjJmVjzyBKKvbpIwlABblKmar8/RH8MydPt8Bq8ORKKFtHEfrKZ7Qi3OCYStw+BuveguvidUbPCKgC/WZAg0EmX/fVJ9YaMb3o6CIWHlt4fztxDXjZgGUyC1BJkZuRBvu/0j5vRcZp7ihTE176F9w9laStwbpYI54N3tzEiZIANBE4B1smCUCtQ9cADwKfAxOA1CL8LO4SfQy8DGwABuSbJwjE97SVpBkDfO1gsWJpcyQBaGlEpTyJQDEInLkdz+DPd9OgUin+O6IZlf3d2LRpk2aFJEvMCx1xDenjTWEs2HZRR1DnOmVZ+EQLWYPOPIiLXL1g2wX2XYrS1FQs6+MiY9pKODuk2Mx0+KYnCDKk2Uhtl1/vAMWYqsaXS8WAJxXRj4DIwPr7Qzi4OOd1pdA0N0/o+Bp0GgeevhZH0RoxnZqZytDVQ7l+7zrdqnbj7TZvE+IfYnHdpUATEBClFs78qc0yjbmsX0D/udD2eROE23+JNeLZ2lZJAtDaCKtDviQA4WngW2At8JCBbvsL6A+8CHyVb41oWSQyCjfmfG6gOKecJglAp3S7NNoeCKRmZGrIv7Ph9zTbi26/E3rXJjhGJCxLAtAcn6RlZPH2iuOsPHJTR8zwFlWYNbyJJuNSDuMREMTqzweuU6e8P61qlNErQFwFFhl/Li4uMqvVeIjlirtnIfoi1Be/AStrqPHlUlkISm3uI5CVCYe/h63TIDlaPzB1+0HfGRBcy2rAmRrTkcmRlPUpW6ReB8IPkJieqCEA5VAIAreOwMb34Opu/Qq5eUH7l6HTG4r64cUY9EyNZ2P2sPRcSQBaGlF1ypMEIIh2Vx2AIcCfBrpREIWrgb1Ax3xrRgFLgPCcq8IGinPKaZIAdEq3S6PtgcDM9Wf4cselAls/26EaTbO1/01mAJrmFdGF9sVlh9h9IUpHwKs9avNG77qy2Ydp0CK6KL+94gR7L0VRs5wf617tjLeHW7HS1HgYNxEeucwQBDJSYdsMLblXtY0hKxQ1R8azotyhXmWuH4B14+G26FeoZwSFQr9ZUK+f1W00NqbTMtNYcnIJX5/4mk+6fULnKp2trqPcwEwE4m7C39Ph2E9FC2r8MPR6H0pXM3Mz+y43Np7tq612d0kAKsEL9tdBEoAQCQTl1Pg7YqBLRJu4Q4CoPh6cb404Ye4DRDVaWeypeDAlAWhgsMlpEgFzERBdad/49SiXIhI1oupXLMUvz7Zk+99bNP8uCUDjEb4dl8zTSw7cz6rMleDm6sKHQxrzWBt1H2yNR8QyK0RG35LdlzVXqlPS83p0vdStFhP61S92EzUexi2DmpSig0D4SfjjBbhzEkSdqRd2gpe/qoCS8awqdylP2YQI2DIVji7Tr5u7D3R5E9qPBQ/bvLIYE9P7b+9n2r5pXI2/qtG/in8V/hj8B97uttFVeQ5VuEapCbBnPuyeDxnJ+pWt0kabZVq1tcKNMUw9Y+LZMInWnyUJQOtjrIYdJAEICTnNPEzJAEwC8p8oc4nBWED/fSU1RIVtdJQEoG1wlrtIBDQIJKdlMmv9GX46cJ3VL3ekRmkPWS/NxNgIC7/H6CX7uR2XUkCCj4ebpt5f9/rlTZTs3MsErhNWHEcQ1oWHu6sL29/qRpWgoutSqfEw7twet5L1IuPpuwGQmdcZlJZPw0OfWmlD64iV8WwdXB1eamYGHPhGm/2amq/hQn7DGw6GPh9B6ao2hcOYmP7j/B9M2TOlgH4vPvAiLzV7yaY6y80MQODE79rrvgniApyeITL9en0AjYZatKmMAZpZdYox8WxVRYwQLglAI8By4KmSAIRjOR18RV2/wQb6WjQNEX3LTwAP5FsjisiIa8TngXoGynLWaZIAdFbPS7vtisCt2GQql/aR9dJM9MKei5G88MMh7qUUbPRe1t+TxaNba7osy2EcAqKO4sLtFxANPdIzRR+tgiOktA8zhjWha91yxQpW42HcOKTkbIMQEATIkv5wY3/edNHcYOwhVV05k/FskLflpPwIXNkF6ybA3VP6cSlbF/rPgVrd7YKbMTGdlZ3F6A2jOXJXeznL1cWVUQ1HMa7VOLvoLjctBoG9C2Dju7oTPEtBl/HQdozNskxt6Sdj4tmWehW3lyQAleIJ++ohCUCYDHyQ0w7rE+AdIL0It3gAs4A3cua/D3yYb+4M4G1gfU5XYft6V9m7SwJQ2f6R2jk4Amo8uNjbJauP3mT8b8d0SKqaZf347uk2VAu2fNdEe9ts7f2PXo9l4u/HCbujbVBTeIxqX523+tXH38u9RFVkTJcIkfNMiLoIX3SG9EQo3wiGfQUVG6vKfhnPqnKXfZWNvwWbJsPJ3/Xr4ekP3d6GNi+Au6fddDU2psOiwxjx1wgaBTdiUrtJNAhuYDfd5cbFIJCRBgvbQnROrWkXVzRZ193eAf/if7hTK67ZmZlE/PYbez09wc1NNaV0JAGo1oizrN6SAAQftFmAtXNIvRvAbzk1/iJy/pu4z9USeESUoQAEbhdysv9yCx2I6uQXAZFPL36e+p9lXeVw0iQB6HAulQapCQFjD+Jqss3SuoputF/suMTsDWd1RLesHsQ3T7UiyM9+L1WWttcW8sSV9P9uDuPbXZfJ0k360zT+mD28Ka2L6P6rT0cZ07bwnIr2OPSd9oW0+3vg7qUixbWqynhWnctsr7AgXvYthB1ztGS3vtF0hPb6ZUAl2+tXaMfCMZ3iksKF2Au0rlh0TbhjEcdoUraJJgNQDgUjcOZP+GUk1O4NfaZDecclazMiIrg57k2SDhwgsncvonv1kgSggkNTqqaLgCQAtZgIMmot0CQHIj2vI5pPcvE6mZPhdz0fpNWB0Tn//g1wUwZcsQhIAlAGiETACggIskpkU9WvGFCsdPlyaRj4oinF1DWn+GGfthB5/tGvUUU+/U+zErvTGraT88wS16hFh99r0aKMbsEhmqi80KUmr/asYzSuMqadJ4Y0loZtgOrtwTvQIQ2X8eyQbrWcURe2wvqJECWqDukZFRrDgLlQvYPl9jRTUm5Mi+u9KXVSWHBiAeLM8ufQPynjLUunmwmv9ZYLovnA13DvNvTJf/Et35bZ2XB9P1Rraz09FCI58949Lg8ZSvrNm2S7uHB9zAt0ef55fHxETpGyh8wAVLZ/bKWdJADzkBb3i14GXhBNMotwwDngS+DzYq4J28p3at9HEoBq96DUX5EI/PjvNd5bdYIxXWvxRq+6eLrr/9VcvlyW7D6Rpfbqz0fYfPqOzuTRHWoweWBDBGElh+EIfLwxjM+3iQR63dGwUgBzHm5K4xDTCB0Z04b7QdUzU+Jhw9twdDk88DgMXaRqc4pSXsazQ7rVfKNir2nrrYmMK31DEOLdJ0GrZ8Ct5NIJ5itkuAQR039t/IslCUu4npmXQzGk9hCmd5xuuCA50zYICFLv7F/a6+Uxl0FkYYqO6iorp2ANsJKOHOHqyCchM5O04GDqrF+Hb0DxP7xbQw9jZUoC0FjEHHO+fHPR71eRJy+yAYNyPo4BREVdmdVnue+BJAAth6WUJBHQIHAlMpEB83eSlJap+fcGlQL4dEQz6lUspYOQfLksPmiiElJ5dulBRI26wmPSgw14tlMoLi7yT6ixX72Np8I1TVTyD083V17rVYfnu9TEw830a14ypo31hgrn3zwMv46CuGt5yo9YBg0eUqExxass49nhXGqeQekpsGc+7PwvZORWHyoksvmT0PN9xdZdy43pXxJ/4US66KOYN5b2W0qLCi3Mw0iuthwCt45oO/te3V1QZs1u8OQqh+rmaypot/83n4iffuL2f/5DlxdkBqCpOMp1tkdAvr3YHnO5oxYBSQDKSJAIWBCBjMwsHv1yL4evFSSsloxuTff6ooxpwSFfLosGXxCpo5fs50pUwSuqgqia9+gDPPRAZQt6zvlEvbz8MGtP3NYYLmooilp/tcv7mw2EjGmzIVS+AJH9tKgjpMbn6eobDK8cBF/HukIo41n54WgzDcPWa7NeY67o37JycxgwD6qIcuXKHbkxHZ8Vz4KkBSRmaOsW9q3Rl7davUUFvwrKVd5ZNIu7CX9Ph2M/FW3x8zugcjOHRyQ7Kwuys3FxE2X+dUdSQgJb/1pLlo+3rAHo8NHgWAZKAtCx/KkmayQBqCZvSV0Vj4CoVffNzkt8vCnsfpfax9tWY8bQ3NKmBU2QL5f6XXrkWowm8y86Ma3AhABvd75+qhVtawYrPhaUrmDEvVSGLNjN/3UO5an2NXC10DVqGdNK97yF9Dv6I6x6USvMsxT0nw3NHne4jBQZzxaKFzWLEd2sN7wD5zfqt8KnDPSaCiLzz9X07GlbQZQ/pqNqRLHi4grea/seHUKUU6fQVlgobp/UBG2G6e75RWeYVmkNfWdA1TaKU9/SColGH7fefgffVi0p+2LO35tCm6jxGS2vAFs6UtQpTxKA6vSbI2gtCUBH8KK0QXEInL4Vzxu/HCU1I5O1r3bGz0t/DSA1HlysDbao9Tf2p8OkpGcV2CqktA/fPd2aOhV0r1JbWyc1yr8dl8wfR27yYtdaRV6TTsvIKrI+pak2y5g2FTmVrRN1qUS3yeQYGLIIgkQPNscbMp4dz6cGW5SWqL3qKwiZzII/RmlkiFpsrZ6F7u8qNvM1PDEcH3cfAr3yarrmj+kevXrg6e2Jl5v6OnQb7Ec1TMzK1Gb7bZ0OCeH6NQ6sBr2nQqNhDvdDiz6D723fzu133yMzOhrc3Ki+7Ad8mzfXmarGZ7QkANXwpbS+jpIAzMNYvCU/CHQGagLiTU9/zm/eGtEtuKf13eSQO0gC0CHdKo1SAgIp6ZnciU+herBfkeqo8eBiTWyX7bvKlNUnySrUA140pljydGsqBHhbc3uHkJ2Vlc3PB64zc90Z7qVm8PnjzRnY1HbXpWVMO0QYaY24dwdKFXMdUGSrePiAa0nHNPViIuNZvb4zWXNBbp9era29Fn9Dv5iq7bTdfSs1NXkbay/ccGUD0/ZOo12ldszrOu/+D0Eypq2NvJHyL/+jbSgTXrAe430pIsO6y5vQ9kXwcI4zUNqNm1zs21fT3CN3eISEELrqD9xKFfwRWI3xLAlAI78jDjpdEoBax3YCfgCq5fNzcdiIV0Txufh/xz19WjfoJQFoXXyldIlAsQio8eBiDZdmZ2czd2MYC7df1BHfuU5ZFo1siX8RWZTW0EetMkXdxLdXHmffpej7JgT7ebJlXFeC/DxtYpaMaZvAbN1NBAFy6DstATJoPjR52Lr7KVi6jGcFO8caqt09C+snwOUd+qX7lYc+06HpCMVmYSWkJTBz/0zWXFxz34ZpHaYxtM5Qzb/LmLZG4JggU9S2++2pojtJiwzTlqOh27uKbShjgtUGL4n4fAGRn39+f757+fJU/epLvOvXLyBDjfEsCUCDw8ChJ0oCEMS3+SDgk0PqiVz784B4iyl4D0x/KHR36AixnnGSALQetlKyRKBEBNR4cCnRKCMniGuoE34/xqqjt3RWPtyyCjOHNTGrK62R6qhyuqg9uXjXZeZtDtO5Oi0Meqp9daYNbmwT22RM2wRm620isv7WjM2rd+YdCC/uhcAQ6+2pYMkynhXsHEuqlhIPO2bDv19AVoauZBc3aPcidJ0I3gGW3NnisiKSIhi2ZhixqXnNyHzdffn9od+pGlBVEoAWR9wMgX+9AQcX6wqo1RP6fAgVGpohXN1LszMyuPrUKJIPH8a/Z08qfTgd96AgHaPU+IyWBKC6Y9NS2ksCEL4HRgIi1/d9YD6QYCmApZwiEZAEoAwOiYAZCMQlp2tWB/p4mCRFjQcXkwwtYlF8SjpjfjjEnotROjNe7VmHN3rVKbJ+nSX1ULOssPB7GgL12I04vWYMb1GFyQMbUNpXZgCq2c820/3UKvhtVMHtanaHkStV0eDA0jg5+zPa0ngqTp7Idj3+K2yeDAl39KsX2gX6z4HyDRSnflEKbb26lde3v37/4/41+vNeu/c0tQBlTCvIjQkRML85pN3TKlWuPvT5COr0UpCS9lMl/eZNEnbuovSIR4s8C6oxniUBaL+YUtLOkgAEUWSjEvAJMF5JznFwXSQB6OAOluZZF4HXfj7C/svRzHvkATrULmv0Zmo8uBhtZBELRJOKp5cc4Gx4zsE3Z56bqwszhjZmROv81SAstavjyBGZkwu2XWDh9gv3O07nt040TZkxrAld65azqdHOHNM2Bdqam614Dk78lrdDi1HaemfuztcoQMazNQPNzrJvH9de9722V78iASHQ9yNoOESx132LQ/D9Pe+z6comDfE3sObA+1NlTNs47gTJnJ1VdK3UXZ/Ans+1zWTEs9ZNf9M4G2ttk+0S9+7F1c8Pn6am19JUYzxLAtAm4aX4TSQBCCmASKHpAuxWvMccR0FJADqOL6UlNkZgzbFbvPrTkfu7PtMxlAn96uHtYXhJUjUeXCwB89nweEYvPkB4vHj05w1fTzcWPNGC7vXKW2Ibh5Vx9HqsJuvv3B39ifKj2lfnrX717VI30Vlj2qGCTXT2XdhBexVy8OdQt69DmWeMMTKejUFLJXNFfP/9ERz8VkvMFB5untBhLHR+EzyLbuJlb2tF7VwxXFz0v0YmpSdprgFX9i/YBErGtA09d+uotpZqvX7amNI30lMgMxVEuQUnGdlpaUTMn0/Ut4vxqFKF0D9W4ubvb5L1aoxnSQCa5GqHWyQJQLgOiL9QrYHDDudh5RokCUDl+kZqpmAEwuNS6PPJDuJT8moFBXi7s/GNLlQKFKVMDRtqPLgYZlnRs/ZciOSFHw5pOtTmH2X9vVgyujVNqjjPIdhYLJPTMpm3KYzFuy/rdEoWsmqW82P28Ka0rlHGWNEWm++MMW0x8GwpSJAHRRAHGjXEi2tgVfALtqVWittLxrPiXGK6QqLpwpEfYOsHkKRbdkIjuHZv6D8bgmuZvo8NVkanRDN1z1S6VunK8LrDjdpRxrRRcJk2OTEStrwPR5Zre1V6BcKrR5z+eSrAzIiK4vrzL5By6tR9bAMHD6Ly7NkmYa3GeJYEoEmudrhFkgCEn4BHgafR1gOUwzYISALQNjjLXRwMgTvxKYz79Si7L+S9RMx/rDmDHij4S3tJZqvx4FKSTcV9vurITd76/ZjOlVVBXC19ug1Vy/iaI96h14oOv08t3s+16CQdO8W16Re61ETUTTQmA9UagDlbTFsDQ6vLvH0M1r4Jw7+BoBpW307NG8h4VrP38ul+4xCsGw+3isgxKF1dS/zV7af46767bu5i8u7JRCZH4uPuw28P/Ub1gOoGO0rGtMFQGT9RkMyHl8KWqZCS14RFI6jN89pSCk4+8jf3yA9F1W+/wb9jR6PRUWM8SwLQaDc75AJJAGoz/8TV3xNAW/EDgUN6WnlGSQJQeT6RGqkEgaysbJbuvcKs9Wfp26giggA0dqjx4GKsjWK+uKq0aMdF5mwI01neqnoQXz/ViiA/2zSpMEV/JaxJzchk4PxdnL9b8Npvw0oBzHm4KY1DlJE56SwxrYSYMFqHzAzY/Qlsn6W93lutA4z+q+jaVEZv4HgLZDyr3KeaTKyp2sw/fcPdW3vVV1zP9DA8e99eqFyIucDQNUMLbN84uDHfD/geD1fDmpHJmLaS98QPK3+Ng5sH9W8QFAov7QMPbyspxUETYAAAIABJREFUoB6xaTducnnIELISEnDx8KD8+DcJevJJXFxdjTZCjfEsCUCj3eyQCyQBqHXrSzndf9cBzwCRDultZRklCUBl+UNqo0IEzt+5R/lS3gT6Gnb4zm+iGg8uxrooMyub99ecZNm+azpL+zeuyCcjmtk9a81Ym+w1//C1GIYv2oO4venp5sprverwfJeaeLgZf2i2lg3OENPWws7qcnfOg63TCm7Texp0fM3qW6t1AxnPKvWcILsPLYG/p0OK/g7p1B8IfWdAkOHZc0pAY9reafx2Lq9JT5BXEEv6LaFWacOuLcuYtrAXU+Jh20ew/yv9NSU9/bUkc7uXJPmXD/q4tWuJXLCQkHkf493A9A7baoxnSQBa+DuoUnGSAIQpOb7rB7QDkoHNwFlA976TrqMLnWhVGgm2V1sSgLbHXO4oEbiPgBoPLsa4T9SsG/vTEbacuaOz7OmONZj0YEPE9VU5DEdg+l+nEU1ARK2/2uVNK5pt+G7Gz3T0mDYeEQWtEC+qX3SE2HxkfJXW8MxGmQVYhJtkPCsofg1V5epeWPcW3BGXivSM4Nra6761exkqUVHzRHOPEX+N4Er8FTqHdGZax2mU9SlrsI4ypg2GqviJ4pe4kyu0TT4SwvXPbTRMSzIHVLLQpuoRI676Zqen4+pTdGataAbi4mne7Q81xrMkANUTx9bUVL79gGjDpW1npR0Ck/z/XhL+hrfdLEmSc30uCUDn8re0VmEIqPHgYiiEUQmpPLv0oIasKjwmPdiA5zrXNFSU08wTV6VFd+n6FQOoV7GUXrvFVWB3V1fFEqeOHNMOEYhX98CSAdo6Z53GQdeJ4G7eC5hD4FKEETKeVeTde+GweQoc/0W/0h5+0HWCNhNL5TF/KvIUxyOP8596/ymyC3BRnpMxbYGYjjyvraN6eYd+YWVqwYMfQ60eFthMfSLSbtzg1vi38KxencqzZ1nVADXGsyQArRoSqhEuCUAtAWjOUM79J3OssP1aSQDaHnO5owoRiE5MI8jXw+iDdkmmqvHgUpJN4nPRsGLUkv1cjSqYwO3p7sonjzbjwabO92t4Sbjdjktm0h8n2Xr2Lg9ULc3KFzsoluQrzhZHjemS/Keqz/cuAJH5V7WNqtS2h7Iynu2BupF7ZqbDv1/A9tmQdk//4sYPQ5/pEGBcoy4jNbHY9E1XNlEnqA6hgaEWk5krSMa0GZBmpME/c2D3/yAzTVeQpqbkeOj4Krh7mbGRepfG/bWW8KlTNfX9xKg8dy6BDw20mkFqjGdJAFotHFQlWBKAqnKXQykrCUCHcqc0xhoIJKVlMOB/O2lYOYCPhjSxaLMKNR5cSsL4yLUYTeafIE3zj0AfD02zjzahZUoS4VSfi2YyPx24xsx1Z0lIzet/pdYsSUeMaVUFZHKslgwRL6Fu7qpSXYnKynhWolfy6XRpO6ybAJG6DaY0s8o31HZerdFJ4YZo1UtIS2Dm/pmsubiGhsENWdZ/GR5uxtcXLs5YGdNmhILo8vttb/2NPmr31sZaGcuTtmZobNOlGTExXOzd5z75JzZ39fcndNUfeFYRr5yWH2qMZ0kAWj4O1ChREoBq9Jpj6CwJQMfwo7TCighMWnXifgOLcqW8NB1Xu9crb5Ed1XhwKc7wzafvMPanw6SkF0zqDintw9JnWlO7vP5rrRYBU4VCRKbk2yuPs+9StI723h6u/PNWd8oHqKtjoKPFtKrCSpAhq16C+JvQ7V3oNlFV6itRWRnPSvQKEHsdNk2C06v0K+gVAN3fg9bPqYYIvxJ3hTFbxnAz4eZ9m55r8hyvtbBskx4Z02bGtOj2+1W3vIYfASHQbxY0eEhbWsHJh8gAvDV+/H0UPKpVo8r8/+Fdv75VkFFjPEsC0CqhoDqh8mmhOpc5jMKSAHQYV0pDrIHAtrC7PL3kQAHRLaqV5vcxHXC1QPMKNR5cisL5h31XeX/1SbIKVW9tVDmAJaNbq47IskY85crMyMxi8e7LzNt0jtQM3QoYZf29mD64Ef2bqO+qtCPFtDVjwOKyxZU0Uf8sd7i4wXNbIKSFxbdyJoEynhXm7YxU2PMZiI7W6UX0CGw2Enq9D/6W+aHOVggkZyRrmntcjruc9zXGhZWDVlI7qLbF1JAxbQEo10+EA99o60mKOqpeymvIZQErTRZxa+LbxK1eTeDgwVSYPBk3fz+TZZW0UI3xLAnAkrzqHJ9LAtA5/KxEKyUBqESvSJ0Ug8DfZ+/w5q/HiElK1+jk4+HG+tc6U6OsZQ4zajy4FHaOuMI6d1MYi7Zf1PFbl7rlWPhEC/y95FXEXHDOhscz8ffjHLsRpzfOh7eowuSBDSjtq87GDI4Q04p5ABmjyI2D8G0fyM7MWyXq/D27WWalGINjobkyns0Az9JLz22CDRMh+pJ+yZUegAHzoGprS+9sM3lnos7w+LrHycjKwN/Dn3fbvsvAmgMtWn9YxrQB7hTNktw8oUor/ZNT4iDuJlRoaIAw55uSmZBI4u7dBPTtY3Xj1RjPkgC0elioYgNJAKrCTQ6ppCQAHdKt0ihLInD3XoqGsNkWFsFHQxvzRNvqFhOvxoNLfuNFR9oJvx9n9dFbOpg80rIKM4Y1wcNN9mgS4KRlZLFg2wUWbr9AeqZuk3txTVrg1bVuOYvFlz0EqT2m7YGZxfbcNgN2zNaKC+0KQxZCoHXqLllMZ4ULkvGsAAcJwm/Du3BuvX5lfIKg5/vQ4ilwdVOAwuapsPjkYnZc38GMzjMI8Q8xT5ie1TKmi4E0IUKbSX3sRyjXAMbsBAvXYLS4Q+0gMH7TJsjGJgRfSeapMZ4lAViSV53jc2ciAHN/thNvP7XyubeIn/MMCoDCsgxaJCdpEJAEoAwEiYABCGRnZ/P32bv0qF9e/hKfg1dccjpjfjjE3ktROgi+1rMOr/eqY1GsDHCTYqccvR7LhN+Pce6Otite/iFKBj3Vrjpv9avvEJmSajyMKzZwjFVMdENdOggaDoY2z4OrJN+NhbDwfBnP5iJoxvq0JNj1SU7H1VQ9glyg1TPQYxL4qqe5VExKDH4efniKDDM9IzNLm8XrZiUyU8a0HtAF5oe+g60fgMjuyx29p0FHy9ZgNOMbYfelWUlJ3Jk1m9hff81p7rEKzyqWJ6mNMVTE88/rf+Z8xnkmPzQZHx8fY5bbZa4kAO0Cu+I2dSYCMLfYkSDt8v9Mp1sEyXA3FZZl+Eo5UxKAMgYkAnZEQK0H8VuxyZraiGF37hVAz83VhRlDGzOidTU7oqqsrT/ZfI7P/j6vUxtRaFmznB9zhjelVQ31vLyWhK5aY7okuxTzeXZ28Vd6RZdKSfxZzF0yni0GpeGCRIyf+RM2vgtx1/Wvq9JG23G1cjPD5Spg5u6bu5m0exIP1XyIca3G2UUjGdOFYL91FNaOg5uHdP3h4QuvHIRA+5JcdgmUQptmxsdz5T+PkXYpL2fHp3lzqv/wPS7u9inzIn6cX3F2BbP2zyKVVD7r8hndQrspAa5idZAEoOJdZBMFnYkAXJIP0afz/XP+/24K6PllmbLeWddIAtBZPS/tVgQCajyIn7kdryH/wuNTCmDo6+nGgidaWKxDsiIcZAElftp/jXdWniggSRClY7rWZGyPOnh7qP/KWn7j1BjTFnCzbUREhMGqF2H4t1Am1DZ7OvkuMp5tHAAR52D9BLi0Tf/GfuVAZGU1/Y+qiO6UjBQ+Pfwpy88s19jlggvf9PmGNpXa2BhgkDGdA3lyLGz7SNvMI1tPHoroJC2yS1s9q5pO0tYOplsTJxK3ek2BbUL+O4+AAQOsvbWO/Pi0eKbvnc6GKxvuf1bWuywrB68kyDvI5voYs6EkAI1By3HnOhMB6LheVKdlkgBUp9+k1lZCICktA19P2/2SqbaD+O4LkZprv/dSMwp4QHSt/e7p1jQOCbSSZ9QrVvxC/fjX/96/Ki26Is95uCmNKjsmVmqLadVE1rV98OMISImFMrW0zT38glWjvloVlfFsI8+lJ8P2mbB3AWQV/PuiZczcoO0L0O1t8Fbfs/N8zHlNh9/0LG1DMTEq+FZgxaAVBHrZ1h6nj2mRYXriN9j4HiTe1R/gTR6BPh9CqYo2+gKoY5vMhAQuDx1G+vXruPj6UvG99wgcNtTm5V4Ohh/k3V3vcjvxtg5wI+qNYFK7SYoGVBKAinaPzZSTBKDNoJYbFUJAEoAyJCQCOQiEhd/jP1/tZUK/+vyndVWbHGjUdBD/48gNTcOPwg0sxDXWpU+3oWoZXxlLRSBwNSqRQZ/v5oWuNfm/zjUdujGKmmJaNQF7eScsfxgy8mXdig6/T60BT/m9s6YfZTxbE90c2TcPwx8vQOQ5/ZtV76S97qvyjqtLTy3l44Mf37exY0hHPur4EcE+tiXynTqmRRb12jfhyk79sRZcBx78GGoq/xqpDb6ZerdIPnaMOzNmUmnWTLxCbZuJLgj0RUcX8e3Jb8nSk7X5UOhDTGo/CV9xdVvBQxKACnaODVWTBKANwZZbFUBAEoAyICQCgOhmO2TBHsT1VjF61i/PrOFNKVfKy6r4qOEgLjLYFm6/yNyNYTpYtKoexDejWlHaV38xc6uCpyDhUQmpbDlzp9jahwmpGQ7R5KMk2NUQ0yXZoLjPRVH6JQPgzsk81UJawRO/qar5geJwNUAhGc8GgGTqFNG0Zuc82DEHsrWNLwqMUpWh74fQaFjxdS9N3d/G6wRh8fzm5zl69yjjWo7jsfqP2eSHxsJmOmVMi4Yy/8yFPZ9BvizM+9i4e0OX8dDhVXC37rnPxmFn9HZZqalk3buHe9myRa4V50IX0cHMhuNa/DUm/jORk1H5/g7m7O/t4s0QnyGMGzhONgGxoU/kVuYhYNtvkHm6ytWOhYAkAB3Ln9IaExGYtf4sX+y4WGD12B61ebNPPRMlGrZM6QfxjMws3l9ziuX/XtMxaECTivz30WYOV8POMM9pZ4lD8Jpjt5i65hQxSeksf64tHWsXfWg2RrZa5yo9ptWKK/G34JveEH8D6vaDh5fI7D8bOFPGs5VAFrX+/ngebh3R3cDVA9q/DF3eAi9/KylgH7F3Eu+QkJ5ArdK17KMATlgDUFz5XdwPru/Tj3mdvjBgDgTVsJtPlLJx6vnz3HxzvKbDb/Xvl9qtuUd+PMQ5a9WFVczcP5PkjGQdqFqWa0n31O6Udi1Nnz59JAGolGCSepSIgDMRgF1KRMO0Cf+YtszpV0kC0OlDQAIgDheTVp0sQHLVr1iK1a90xMvdug0alPxyKeohvvrTEbac0a2R82ynUN4b0ABXV2f681XwuyI6IYu4+ftsHj5Vy/iw8fUuNq0jqbRvsJJjWmlYGa3P3bNw+HttEwQ329UqNVpPB1og49nCzhRdqvd/CVumFrzSnrtNpWYw9EsoX9/CG1tfXGJ6oqYb6YDQAbSv3N76G5q4g1PG9MmV8HuhfpGBVaH/bKg3wCEyTE0MB80ycQ6O/fln7syaTXZqqua/lX3lFcq98rI5Ys1eG5cax7S909h0dZOOLHcXd15p/gojao5g65atms8lAWg25FKADRFwpjco0WYp28LYCnnyJGwaqJIANA03ucoBEdh65g4TV5wgPjldQ/41qBRgdSuVehCPTEjl2aUHOXY9tgAG4saHIP6e61zT6tgodYOsrGx+OnCNmevOIq71Fh5jutbi7f7qe3m1FN5KjWlL2SflOBcCMp4t6O/Y67D6Jbis5zd70eRDZPyJa5huHhbc1DaixLXed3a+w42EG5T3Ka9p7lHau7RtNjdyF6eMaZEFuGwYXPwbXN2h/SvQdQJ4+hmJnmNOz0pK4tKgwaTfuJFnoKsr1Zf9gG+LFnYx+kD4Ac136k7SHZ39awTUYFaXWTQKbqTKrtayBqBdQkpxmzobAWhpBwgC0LppOpbWWDnyJAGoHF9ITRSAgKjlduhqDH0a2abzmxIP4pcjExm9ZD9Xo5IKeMTT3ZVPHm3Gg00rKcBT9lFBYPP2iuP8ezlarwLiWvQHgxpbvXakfaw3bFclxrRhmitgVvxtOL8JWo5SgDJSBYGAjGcLxIEgX479DOsnQKq2zm6BIRovDPsSQlpaYDPbizgecZwn1z9ZoClB7+q9mdd1ns3rpBlivUPHtKgrWRSBHHUR1o2HvjNVmWFqiG/NmZN89ChXnhgJmdp6nF516xIy72O86tQxR6zRa9Mz0/n86OcsObmEbD05Q8PrDGdC6wn3G32oMZ4lAWh0WDjkAmciALsW40FRRf5DoDUQAfwK7AcE9S8wKp/z2aM5/3wAeA9IB3Y4ZGRY3yhJAFofY7mDRKBIBJR2cDl8LYbnlh4kOjGtgM6BPh58/VQr2oSWcUpvilqIi3dfZt6mc6RmiET2gqOsvxcfDmlEv8bOS47mIqK0mFZNwIrulMuGQ9x1GLwAmo9UjeqOrKiMZzO9mxgJf74GZ//SL6jti9DrffDwMXMj+y0XzT1e3PIie27tua+En4cfvw38jaoBVe2nWBE7O2RMJ9yFTZMgNQEe+1FxmKtFocgvviDi0/8RNHIk5d8aj6uXbRuiXI67zNs73+Z01GkdyAK9Avmg/Qf0rN6zwGdqjGdJAKrlG2FdPZ2JACwKSYHBOnF9H1gMvA4kFjFZ9Pb+FHgO2AAMsK57HFq6JAAd2r3SOKUjoKSDy6ZT4bz68xFS0gsSXCGlfVj6TGtqly+ldDitop/oDD1xxXGO34jTK/+RllWY9GBDAn3Vd23NGoApKaatYZ9VZF7bBz+OgJScK/fiOuTjv0Cd3lbZTgo1HAEZz4ZjpTPz7Dr481VIFL/pFxoBVWDIQqhZXF6AGXvbeOndpLsMXzOc2NRYmpdvzoxOM6hSShyxlTccKqazMuHgYtg6HVJz/kY/9jPU66884FWgUXZmJslHjuDbqpVNtRU1CFecX8GcA3P0NvpoW6ktH3X8iAp+FXT0UmM8SwLQpuGl2M0kAagl874CNgN9DfTURqAX8GLOWgOXyWn5EJAEoAwHp0NAHDQysrLxcHO1u+1KObh8v/eKppNtVqEKrY1DAlg8ujXlS3nbHStbK5CakcmCbRdZuO2CJl4KD0GMzhzWhC51y9laNUXvp5SYVjRIhZXb/7X2alr+UbEJPP8PuNr/OaUqLC2srIxnEwBNiYeN78CRZfoXP/CYtvmCd6AJwpW7ZOu1rVyMvcgzjZ/BXdSZU+hwmJi+eRj+egNuHy2IdOlq8NK/skt6ofgTZ9+4lX+QGRtD8LPPKiY6Y1Nimbp3KuL7U3iI79HrLV7nyYZP4uqi/2+hGuNZEoCKCT+7KiIJQNgFiJZZw4DVBnpjELAK2At0NHCNnFYQAUkAyohwOgR+3n9N0/H3kxHNqF3e36722/vgIhpazNkYxhc7Lurg0LVuORY80QJ/L+W+yFjLeaLW3/PfH+T83QSdLUQjlFHta/BW33r4OSE2JWFu75guST/Ffr55Cuz+n1Y9UQvt8V/Br6xi1XUWxWQ8G+npK7vgjxch7pruQt9gGPgpNBTHd/WNvbf2Ur9MfYK8g9SnfD6NVR/TyTHw94dw4Fv9fSW9AmHkCqgqKkrJIRDIjI/n9vvvc2/9Bs2PSvZs7pHfI+I7NWnXJO4m39VxVGhgKLM7z6ZBcINinajGeJYEoPxeCgQkAQiRgPiLKnKOjxgYFs2BQ0AMEGzgGjmtIAKSAJQR4VQIXI1KpP//dpKUlomXuyvvDmjAk+2q4+pqn8ewPQ8uIsNtwu/HWX30lk4MPNqqCh8NbaKILEl7BKjo7tvnvzu4FZdSYPua5fyYM7wprWo4Zy1EQ3xhz5g2RD/FzsnKgj9egJQ4eGSJ7E6pEEfJeDbQEekp8Pd02LtAPylTtz8Mmg/+opy3ukZqZiqfHvqUZWeW0aNqDz7t/qkim3sYiqpqY1o0kzn+i7bWn75r5QKApv+BPtNVGWeG+s/YeVmpqVx6aBDp1/JIeY/KlQldvQq3UvYp7ZKWmcZnRz7ju1Pf6TXn0bqPMr71eHzcS64NqsZ4lgSgsVHsmPPt8+apLCxFmoX4lg8F1hioWm4GoGhVad80HgMVVuA0SQAq0ClSJesgIBo5PPrlXg5fy6mzlbPN72Pa243QsdfBJS45nTE/HGLvpSgdsF/vVYfXetZR9QuOJSJoW9hdnl4iek2Bm6sLY7rWZGyPOnh7yKbzxeFrr5i2hM/tLiMjDcQ1Jzfny7q1O/ZFKCDj2QDP3DqqJa8jzupO9iwF/WdBsydApE+rbFyJu8Ib29/gQuyF+5pPbT+V4XWHq8ySPHVVGdN3z8LaN+GquDCmZ5StBw/Og9DOqvWLNRXPbe6Rf49KH31I6eG2j+NLsZc0jT7ORJ/RMTnIK4gPOnxA92rdDYZDjfEsCUCD3evQE9X3F9Hy7hAFHJoAoq6foU09RNOQfsAJ4AHLq+QUEiUB6BRulkYKBG7HJTPym3+5GJHXX+ixNtU0ddzsNexxcLkVm8zoJfs5d6fg9VZBcgksHm2lvK6F9vLPuF+OEnbnHnMebkqjyo5Vr8pamNojpq1li8XlitpomengJy8tWBxbKwmU8VwMsJkZsOsT2DELsjJ0J1bvpG30EVTdSt6xvtjI5EiGrR5GTKq4bKQdIitp9eDVVPJXZ9d3VcV0WiLsmAN7P9cfYyJDrNtEaPcyuHtaPyBUuoNo7nFt1GiSDh7ENTCQStOmEdBX9N203RA1CH879xtzD8wlJbPg7QqhRYfKHfiw44eU8zWurrKq4jkHbkkA2i7ulLyTJADhXeDDnHsDXwLjAN2ng9aLoif5POClnPmTgJlKdrCCdZMEoIKdI1WzPAIp6ZnMWn+W7/ZcoXqwL+te7WzXOm62PriIjraC/LsTn1oAXD9PNxaObImo++dMY8vpO9SvVIoqQaK5vO4QV4HFVXElNIxRi19sHdNqwYV74bD8YXDzhFF/yiu+KnGcjOciHBV5Xpv1d1NU4ik03Lyg5xRo95JDNLHZdm0br257VWOkp6sn41qN4/H6j6s2S141MR22Hta9BXHX9QdhvQe12aWi6YccJSKQfusW4R/NoOKk9/CoZFvyOjolmvf3vM/269t19PRw9eCNlm/wRIMnimz0UZxxqonnfEZIArDEcHWKCZIABNFi8jBQP4fUuwP8Coj7V6IyqGjBKHp/i4qujwAVc2onivsGohZgwbdZpwgbixgpCUCLwCiFqA2BnecjNM0tmlezbzFvWx5cdl+I5IUfDiFIrfyjXCkvloxuTeMQ58lwi0pIZeqfp/nz2C1NF9+lT7dW7cuc0r57toxppdlepD4R52DZ8LzGCHX7wYjl8qqvChwo47mQk0StygPfgGhak5Gs68GKTWHYV1C++ML9KnB9ARU/2PsBJyJOMKvzLGoH1Vab+gX0VU1Mb58N22foYh1YDQbMgXr9Ve0HSyufmZBIxp1wvGrVsrRos+TtubmH93a/h8imLTxqBdZidpfZ1CtTz+Q9VBPPkgA02ceOulASgFrPCoJvLdAix9GC9NM3cvESzUIGipt9jhoYNrBLEoA2AFluIREoCgFbHVxWHr6hafiRkVXwsSq6IAvyr2oZ/RlwjuY5cQVlzbFbTF1zipik9PvmzXvkAYa3FI9DOcxFwFYxba6eNlsvCtd/1RVuHyu4ZYex0EdcfJBDyQjIeM7nnbgbsPpluKSbxYOLG3R+E7q8pcqrmEnpSZqrvS5F1ClMzkjGzcUNT5HBq/KhmpgWjWUWtYfoS1rEXT1APDdFjHk6x5nF0FBLPn6cm+PfgsxMQlf9YbfmHvn1zd88R58dj9V/jHEtx+HtLnKATB+qied8JsoMQNP97UgrJQGY501RXX0M8CLQsAgni6qhi3L+l+lIgWAHWyQBaAfQ5ZYSgVwErH1wEYTXwu0XmbsxTAf0NjXK8NVTLSntq/4XGkMiStSAfO+Pk/x9ViSVFxyBPh5sH9+NID/nwMIQvEydY+2YNlUvu66LCINv+0BKTgOioFAYuQKClZWpYVeMFLq5jGdxBycbTvwGa8dDapyup8rU0mb9VWmlUC8Wr9bRu0d5Z+c7PN34aR6t96gqbTBGaVXF9IWtsGwY1OisbfJRzvRMMWMwUstcUdsv6tvFRMyfDxna2x0BDz5I5Y/n2vVWw4WYC0zcOZFzMed0oCzjXYbpHafTpUoXi8CsqnjOsVgSgBZxveqFSAJQvwvFNV9Rnb9MznXf6JyGHzLjz3IhLwlAy2EpJSkMAUF+FfVrvlJUtebBRXQ9nrLmFD/+e03H3AebVGLeow84TUfbPRcieXH5YUT3Y33k35SBDRnWIkTx8aKUuC1OD2vGtBrsL1LHa/tg6SCo0Age/xX8naveplp95/TxnBgFa9+A06v1u7DN89DrA1VmZGVkZfDV8a80/8vMzsTbzZtfH/qV0MBQtYarQXorKqbv3dF29m1cTDfaK7uhegdVdpE2yCFmTBIE4NVRo0g+WLAWZ+XZswgcPNgMyaYtFefun8N+Zt7BeYgMwMKjU0gnDflX1qesaRvoWaWoeDbQKkkAGgiUg0+TBKCDO1jB5kkCUMHOkaqZh4Do4Crq243rUxcvd5FcrLxhrYNLUloGY388wlY92W7PdQrl3QENcHV1jj89y/+9yvurT+lcfxbRMKBJRT4Y1FgTJ3JYBgFrxbRltLOzlKt7oNIDsgGInd1gzPZOHc9hG2DNWEjUzZqmVGUYsgBq9TAGTkXNPRB+gGc2PlNAp4bBDVk2YBmiMYGjDkXEdFYmHPgW/p4O6UkwZjeUF2Xg5TAWAdHc49KQoWTFx2uW+jzwgCYD0LNqVWNFmTU/KjmKybsns/PmTh051myeo4h4NhI5SQAaCZiDTneOtzAHdZ7KzZIEoModKNXXj8Bfx2/xyo+iTCjUr1iKT0Y0o0GlAMXBZY2DS2RCKs9+d4BjNwpe1RKljSY92JBnOzl2dkOuk0UG5EfrzrBk9xUdvwvUaWshAAAgAElEQVTCb/rgRvRrbNtOeIoLQCsoZI2YtoKa1hEprkoWUUPMOhtKqdZGwCnjOfUebHwXDn+vH96mI6D/bPCxbxMtS/j+w30f8kvYL/dFNSvXjE+7f0qwT7AlxCtSht1j+sYh+Ot1CD+eh0/1TjD6/9k7D/Aoqq6P/9IbIdRA6L333gVFREFABCmCSBEQUBELICKvKFIVBERQLIg0G6IUpYn0XqV3CJ0QSK+b97m7gWSzCWQ3M7szu/c+z/t8n+zMKf9zdnL3P+ees1I+P23MmIi//ubKiBEUGDyIAq++ipuXfQnsLaFbeH/b+4hpvxlX+bzlmdx8MuL/qrEcns82OCUJQBtAc8JbJAHohEHViUuSANRJoKSZ2Ufg+r04npqx2ey4Z4FcPmwd2UpzR16V3ricvx1Nn293c+lOjBlg3p7ufN6tFk9Xdw3CKyIu0UgAbz51yyJx2lQpxNQuNQnyt+8GOfsZrO8rlc5p3aARFwG/9ANxJLJCG92YLQ19OAIul8+iSnX5YLh70RIYv3zQfjpU7eQ0aSOGe3Rb2Y1LEZd4tear9K/eH093T6fxLzNHHJbTMXdgw3jY971oLGlp2nNfQc1uTo29ms7Fnz+PT2n7vuCNS4pj+r7pLD6xOFPXelXuxfC6w/HxUO+UhcPyOQfBlARgDsBzolslAWgezECgNVATEE0C/FJ7AGYVcvFXpL8T5YM9XZEEoD3RlrrsgsCaI9d4Y+lBEpIND/R93r0WHWsVtYt+a5QouXHZdzGcAQv2mE23Fbbk8fdi/kv1qFdKtFN1/nUxLJr+C/Zy5maUhbNDW5XlrScruszxZ0dEW8mcdoT9NumMvA6LusD1I+Dlb6pkKVrXJlHyJm0h4DL5LCau/jMBts/KnJwp/xR0mAmBoj23c60Td06QmJxI9YKi7bjzL7vntKiMPrQE1o6FmNuZA1yzJzw5XvZGzQSdFIOB8IULiTt1iiITJmgmQcWAj5GbR3Lm7hkLm/L75ufjZh8jev6pveyezwo4JAlABUB0AhGSADQF0R0YC7wFBGQzrgI7QQBqs8FXNp1w4GWSAHQg+FK1eggcvxbBm8sOcuJ6JO1rhDCrR21NDnhQauPy99HrvL7kAPFJaaSnQLdYXj++79uAcsG51ANbQ5KPhN6j97e7uBtjPuzD28OdSc9Xp3Md8ciTS00ElMppNW1UVLZoYj+/NdxLN2zHvwAMWAf5yiiqSgqzPwIukc/XDsPyQXDzmCXA3rngqU+gzku6PJ4pBhHMPjCb58o9R5k88vsoAmzXnL5xDFa9BZe2Z/7lLVjZNN23VFP7f7l1oDHp9m2ujn6P6C2mvnpFpkwmqEMHh1puSDGw+PhiY+VfgiHBwpbHij3Gh00+tNsxervms0LISwJQISB1LkYSgKYAimYjL6ZW+yUDYUBwKsEXCohmI/d/xQrST7xGun/Ozb41zzpPuHTmSwLQeWIpPcmAQHxSMl9uOsvLTUqRx99bk/gosXH5YccFxv1xFPGSPf2qVjQ3375cn+BAX036roZR92ISeW7ONs7djn4gvkAub+b1rkfdkvrvV6UGZkrLVCKnlbZJVXkGA/w+GA6n9RFDEIC9foEitVVVLYWrj4BT53NyEmybAZsmgcFyQjolGkOnLyGfPrfYokJp1JZRnA4/TeV8lVn0zCK8PGTrB7vkdHwU/DsJdsyBFPGTLsMSldItR0GjISBjkumDTEz4Pdf+WRLOn3/wuXtAAKV/X273AR/3Dbgde5v3t77PtqvbLGwWx3zfqfcOL1R8wa4v3O2Szwr/qZEEoMKA6lScJADhKWBNKtm3ILUKUJzXEx1i01f4VQReBYYCZwHRiOSETuOuBbMlAaiFKEgbXBaBnGxcDIYUJv99gnn/nrPAr2XFgnzRsw4BPs7dyyizxBF9EDt9sc3YA1IMgJnfpx7F8vq7bI7Z2/Gc5LS9bVVMX1ICLO4K5zZB3tLQ61fIX1Yx8VKQ4xBw2nwOO2vq9Re62xJcD294/H1oPAzc9XnARkz4HbxusFmFUt9qfRlRd4TjkkkjmlXNafEm8vif8NcoiLiSuceV2kPbSZDHvlNqNQK/VWZErFnDlTfNc7bw/8aRt3t3q+QocfG/l/81TvkNjw+3EFcxb0Umt5hM2Tz2/7unaj4rAVwmMiQBqBKwOhMrCUBYCrwA/AfUSI1fVeBIFkd8nwV+Ay4D4hW7+bhLnSWAA82VBKADwZeqJQK2blxEdeM7Px/mj0NXLUDsXr84H3eqhqeH6Krgmmv72dv8sP0i016oSS4XJEEdGXVbc9qRNiuiWwwB+Xs0PPE/2cdKEUC1IcTp8lkQNHu/MfVjSzQfFmVEvFB16DwPCoktuH6XGE7QY1UPs/5kfp5+rO68mgJ+or246y5Vc3rb57Dug8zBzVMSnpkKFUTNh1zZReDqe2O499tveBYsSJHJkwho0iS7typynRiU8+neT82mZacX3KdKH16v8zre4sWBA5aq+aySP5IAVAlYnYmVBCBcAMSroCHAvNT4PYwAFJfMB/oC/wM+0lnMtWKuJAC1Eglph0siYMvGRVS2DVq4l53n7lhgNuLJCrz2eDm7Hr9wycBJp7NEwJaclnBKBLSKgFPlc8RVWDEMzm6whNvNHZq9CY+NAk/H/JBXOgdO3jlpJAETDYlUyFuByc0nUy5vOaXV6E6eqjktBiLNqgcJkWm4CGKo6RvQbAR4y2p8axPGEB3NzU8/o8Brw/DMa99WJmJAjhj0ce6e5UmTgn4FjYM+mhSxLyGZET9V89naYGXzekkAZhMoJ79MEoCmXn5iRriY/vtParwrAaIjsTgCLP5ixGfIg7bAauAgUEelHCkJvA60SyUohQ3i6PFPwBfpehAqqV74Kioh7zdduQiUUlJBOlmSAFQJWCnWPgjEJCQxYMFehrQsR7Py+nurb+3G5crdWPp+t5tTN8wn3Hq6uzGxc3W61nONIzW7z99h4c6LfPZCTbxcuNLRPt8y67RYm9PWSXfg1eKY75750GAgeLje0XoHIu9Q1U6Tz0d+gVUjIC6TAzNiWM1z86B4A4dirYbyH47+wM2Ymw6tUFLDr5zIVD2nd86Fv0aaTCz9mGnIR4HyOTHZqe9NCg8n/tRpAhpq5/snBn0sPLaQz/d/biTQM65WxVsZB33k9bUvIZlZIqiezypknyQAVQBVhyIlAZhGAAoi71BqDEUPQHHEVxCAggAT/3/6Ja7dC9wF8qkQd3HM+EcgdxayT6USg5bzz3NmzLTUHoj3pUgCMB2eenzQ5ywd5N0PQ+D934/w407T9E0x7GPU05Xw9dJPzyJr8vnY1Qj6fr+bGxHm70ICvD34slddWlQo6BLJ8tPey4xZfoTE5BR6NyrJR52quYTfenHSmpzWi0/ER8Ky3nDuH6jdGzrM0uVEVN3grSFDdZ/PMXdMU1iPiq45max6/aHNR+AdoCHUs2/K0bCjlMtTDjGAQK7sIaBITosBMlm9CBGfLe0BNbpBtefls/IhYYneuZOr745EVPk5crhHehMFYS4Gfey4tsPCcl8PX95t8C5dynfRzEkTRfI5e18dxa6SBKBiUOpakCQAQYw4KpGhAlC8YhdlLmJkl5h5vipDlJ8DfgXiUisElUwC0VdQjDjyS7VhYmplovhv0Xn1lVRlggSsB6Srdc+RGULvHkC8bhH/CwQkASgJwBwllbPe/M/Jm/T9Tnxd0tZztYsyvVst3bic3Y3L1tO3GfzjPqLik8x8Cw704bu+9alaJEg3PttqaLIYevLXCb7abH4UZXzHqrzUWK0iaVutdd37spvTukFIHGlb1BWui5lkqUsck2w1WjcuSENtR0DX+Xx6nenIb9R1SwACQ6DjbCgnDt7obyUZkvj68NfMOzyPXpV78Xb9t/XnhIMszlFOC3Jvz9ewax68shH81ai/cBAwdlSbYjBwa/oMwubPB9GXE/CtWYNSP/6Im5fjJlVvuLSB/23/H3fjRW2N+RKTtCe1mESZoDJ2ROrRqnKUz48Wr8oVkgBUBVbdCZUEIPyRWk0njtuKo7X3l3j9IGqilwNdMkR2bSpheBKorHDU/wVaAOLXtvi/GV+DvANMSdX5YWofwpyaIMqWdgF1AdFBtz8gjiBLAjAdsnp80Oc0MeT9mSMwYtlBfjuQNmXOz8uDVa83o0zBXLqBLDv5/Ou+UEb+epgkg2mTeH+VC87F933ru8SEW0F8vrHkABtO3LSI7ZNVCvFV77qaeRutm+RTydDs5LRKqtURe3kPLGgPSeJdY+ry8odheyFIHFSQy5kR0GU+x0fB2vdh33eZh6ZaF9MwBp2SN6GRoYzaMopDt+4fGIKv23xNo5BGzpyKivlmc05f3g0rR8ANMZ9RlD/0g/bTFbPL1QTdH+6R3u+Cb7xOgVdftTsUMYkxTN07lV9O/WKh2w03Xq72Mq/Veg0vD8eRk1mBYnM+2x3lNIWSAHQg+BpSLQlAEDPOxdHXFYCo7Lu/hgKzUo8Bi+O4oveeOKfQB3g69d+nAqMUjKcgHAURJ5YYSDI4E9livKbo0yeIR/GaJDi1Yi8nZggMPgUEoSkmIYvqQkkAZkBUjw/6nCSFvDdrBAyGFH7YcYGJa04Qn2QwTr7t1Uh8ZfSzHpbPKSkpfPHPGaatFY8C89WgdD6+7l2PIH/tbcaURv/ynRhjn8eTNywLrV9pXppRT1fGw13+GVUad1vlOeUz+vhK+Kk3pBjAPz/0/BmKiXd1cjk7ArrL50s7YfkgCBez9TIs3zzQ/jPTsUwdr1Php+ixsgcJhoQHXgT7B/Nbh98I8nH+avichs7qnBbHyNePg/0/ZFDtBgM2yGehjQERx37Pd36ehIuizgMCmjYlZOIneAWLn5T2W8fCjhkHfVyIsHxmiO/VJ80+oWFIQ/sZZKUmq/PZSvlqXC4JQDVQ1Z9M+cvFNPBCDNcQza3EWa4bqWEUx4B3pg75MC9/AYGbeGqKXoDhCob9E+D+2R7xOvE+GZhRhSAdxdFgscRMe1GRaOsSrMXRVHLz8dTjxuJJLAnADIjq8UFva1LI+7KHwJmbkfy0N5TRT1fSXRVYVvmclGxg7IqjLNlt6m+YfrWrEcKnXWvqqtdh9iJpedXeC3cYtHAfYdFpP/TEVV4ebkbCt1t90TlCLi0h4LTPaDEAZPts6PUr5C+rJcilLSoioJt8ToqHTRNh2+cmojrjKvekqXdl7hAV0bKfaDGgYMoe00EcDzcPBtcczIDqA/B0lwN6HhWFbOe0wQAHF8G6DyD2TuZin/gAmr/1KJXy8ywQiD1yhIt9Xqbga6+Rr89LuLmL+hL7LDHo4/uj3zPrwCzEkfqMq3WJ1oxrPI484sWBhle281lDPkgCUEPBcKApkgA0gS+IP3EM9ioQmy4eYsTQTOCF1H6A4iNBBooJwKJOOlTh2G0GmgPRgHjqWT4VTQobA9tTdY8HxuXADtHf8BlgIfBSqhxJAGYCqB4f9DnIC3mrkyOQWT6LycbDFh9gYybHXQe2KMOotpVwd4GKN3H0efRvR0hINv8xm9ffyzj0pFGZ/E6eHfp0z6mf0QnRuh2WoM9scrzVusjn6/+Zqv5uiIMpGZY4rv7UBKjb16mGMQjyYvC6wYRGhTKp+SRqFBQHZ+TKDgLZymmRU2Jq9OUsaiCCq0C7z6Ck+Ckk18MQSElKws0za2JaTAH2zGvfabrXo68bB33sum4ZXz9PP0Y3GE2ncp108VI9W/mssRSVBKDGAuIgcyQBmD3gxUAMMUdePEXF5N0sXkdlT9hDrroFFEidRvywaQLiaX3fhp9TCUpblIuhIktSqxgrAfebXEkCUBKAtuSTvEdHCGTcuEQludN/wR4Oh94z88LNDT5oX4W+TUWxtHMvcbR76tqTfLlJFIWbr/LBufimT31K5Pd3bhB07J0eN+NGuEUj9nuXIY+sKtVx+iluuqbz2ZAM22fCxglgEHPjMqziDaHTl7qtWE02JOPhLuoCMl934u4gppL6C5JTrmwj8NCcFhPPN02CnV9CSrKlTK8A0wCkhoNBg/3gsg2CHS4UxN/tufOI3rGDkgu+fygJaAdzHqhYd3GdcdBHREKEhdqq+asyucVkSubWTzsdTT+jswisJADtmfHa1SUJQO3Exjdd9aGoymv/CNPElGLRk1AcU7blNZggEY8DhYBBwFfp9ClBABZ7hP2FU6cOc+rUKYoVe9Tljg9UXFwcmzeLIk1o0aIFvr4iZHJJBPSJQPp8LlmtPsN+Pk7o3XTDBgAfT3emdK5Cm8r27QvjCESjE5IY+dsxNpy8baG+ebl8fPp8NQJ95REvR8Qmuzp1+YxOTsDrr7fwOLuB+F4rScmnrSmH2cVeXqc8AlrNZ7fwC3iteh2PK7stnE5x9yKp+bskNRgCDyHQlEdLOYln753lg10f8FqN12hUWA73UA5ZyDSnU1JwP/kn3hs+wC2zqdFAcsX2JDw+HnIXUdIcp5SVHBbGzXdHEr9/v9G/oFdeIe8Q+w/3SA+uGPTx2cHP+OO8mLtpvsSgjz6V+jCw2kDdHaPX6jP6YYktCMAKFSrcv6S4CqcZnfJ75WxOSQJQOxEtmK4CbxkgqvMetkSvQvGrXJy7qG6DG/NTp/2KKcNNU4823xejBAGYsW9ilibOnz+fAgVE4aNcEgHtIXA1BtaGutOltIFcTjj34nwkfH3Cg+gk8z8H/p4pvFIxmTK5tRcTpS0KjzdhcCXG8k/iYyEGOpY04CH/WioNu8vL80yOpf75WQRHmo5PRnsHs6XCWOK95DABl08OLQKQkkLJsE1Uu7IYT4Nom22+7vkWZ3/JQUT467OSVRzt3Zmwk7Wxa0kiiUC3QIYFDiPAXbxrl0sNBPzjb1Lj8gIKRaZO982gJMo7mCPFX+JmbnnMOlv4p6RQYuYsfK+KjlamleLmRujAV4gt45iXS6FJofwc8zNhhjALF4LcgugS0IXSns5/wiRb8bPDRbdv32bAgAH3NUkC0A6Ya1GF/EmjnaiIL+H9rvvp+/FlZaG4VtwjzqqVs9KNFsAm8VINEOMED2e4XxKAVgIqL3dOBJIM8NkREzEU6JVCj7IGqubNNreteVAOhbmx8LQ7iSnmfwry+6QwqHIyhfw074IiBt5LgE+PeHAvIQ0Hd7cUupY20KSQ88RbEbCkEMUQqBb6I2Vvmc/wuuNf1kgC4ma/huyKOSQFOS0CPol3qXXpGwpHHLLwMQU3zgQ/w4mQzhjc9fuW7FjCMRbHLDbzr4pXFXr499BFPzI9Jl+e6HO0OPUhbsb26mkr2c2T04XaG/9ncPfWo2sOs9nvzBmKffMtbmKQiiAA3d252eFZ7jW25bCY7W4IQn1L/BY2xG3AgOVwoGpe1ejo1xE/dxfZaNoOpaJ3SgJQUTh1K0wSgGmhE2e72qUO4RCvSUTfv6wbgJjuE3+xnlAo+vaqAPRJ7TFYEfgUeDsT+5UgAB91plceAVYocaQY9RD4bP1Zvt4mBn6nrc+7VqNNFf0fif3ryFVG/HYc8eMt/aoaEsjcnjUpkMu1Nt1Hr0XS69t9xCUZCPL15PMXqtOwtH2bY6uXya4hWXfHceKj8FnyHO43TNUvKV5+JHT8CkPZJ10jYNLLhyKglXx2P/EH3n+PxC0u3MJeQ56SJLabiaFYQ91HMyUlhTe3vMn26/dn7EG5oHJ82fJLgnxkVa4SAc4sp73WjsTzwIIH4pNLtSTxyU9kO4QcAB6xZCl3pkzBo3BhCk6ehG8N+1ZQ3oi5wbhd49h/y3QMOf3y9/Tn7Tpv065kO90T61p5RluTKvIIsDVoOe+1kgA0xbZZ6hTc9OcWHoaNIP7E5+L/PookzG722KsHoJgaPBa4DFQBRC/BjEsJAvBRfguCUNjA5cuXddEDUI/NXh8VBPl51ghExiXSatq/3I5KO+pUsVAgK4Y1xddLqa+9YyJw/nY0z87aQlS8eaPtVhULMrtnHQJ8XLPX3Zoj15i29iTz+9SndAF57Msx2Wm7Vl0+oyNvwDetQUz57fkzFBNF+XJJBMDh+RwbDqvfgSNi1lwmS0z3bfMx+ORymnDdjr1N5xWdCY8P56UqL/FGnTfw9nCtl2FqBjPTnBZ5NqueabBH24lQpZNTTY1WE8+sZAsy+8533xPUsQOe+fPb1YS/LvzF+B3jiUyItNBbo0ANJjafSInc+mwTkNEhhz+jbYisHAJiA2hOeIskAEFMv90LiBpkgUcCcDp1yq5lzbJlErRSMC/sMQVYsBliN/MdYH72KM2RWanTiEU3/NdS/1lMCN6ooK+SAFQQTClKHQRuRsYx6tcjbDxxEy8PN1YMbUaVIvpuiheTkETnOds5cd18c9ajQXE+6lgNTw/XPnqYkGTA29O1MVDn26S+VD1uxo2o3D5j+sGbv6z6IEkNukHAofl8ZgOsGAaRab3EHgCXqxB0mA0V2ugGS2sM3XplKx5uHjQuYt8jk9bYqLtrL2yDkk2IjYtj7VrTT482bdrg55d6/DN0HxQoD7763l/ZMy6GuDjcNTSMMDoxmk92fcIfZy0Hfbi7ufNK9VcYVHMQXjpuEyAJQHtmuNSlJgKSAIQfgF6p/fDGATOzqIpTMw73ZYsRs81FL3AgD5CUhVKxK7l/RkFU9Am7s7tsbWj1L9Ayu0qycZ0kALMBkrzE8QiIN6lLdl8mLjGZfs303ahY+DLip0MsP3DFDNhnqxdiZs+6uj+O8ahsuXYvlkU7LzHiyQq4u8s/f4/CS2+fO5QweRRYKSmyquVRGMnPzRBwSD6LStR1H8AeMScukyWqs9pPB/98uo2WICq83b3xEhVncqmLQMwdUxXpf79Ah1nEVu6aOQGorhVOJz1y0yaujR1L8blz8ata1eH+Hb51mJGbRxIaFWphS0hAiLHqr24h56tud8gzOofRlhWAOQTQSW6Xv4BAPK1CgOlZ9MOzZ6g/AUanKmwE7MpC+ShgYupnTz2kki+z2yUBaGNE9figt9FVeZuTIrBw50XG/m6aOHp/hfilsHJ4S/IHOc8xrszCd+jyXV75YS83I+N5/YnyRhJQLudCQJPPaEH8bfwI3D2h1XvOBbj0RlUE7J7Pl/fA8kFwR8yWy7B8g6DdZ1DteV0T2VejrjJs4zDEUcRxjcc5/UsvVRP0UcJP/gV/vg5RN0xXegcS128jf+86bvxPswrAR8mSnxsREC9xw76ez63p08V/4BkSQulffrb7Md/74Ug2JDP/yHy+PPQlySnmLWXENU+Xfpr3G71Pbm/nrOy0+zNage+BJAAVANEJREgCEOIA8RpQTMbd5uCYNkhH+s0DBmdijzibJn7BVwbuAmIaQaLCdssegJkAqscHvcJ5IcXpGIGDl+/Sde52EpPT3gH4eqTwVvVkenVMdxRHxz5mZfqfh67y9s+HiBdjnVPX591r0bFWUSf01nVd0twzOjkR/ngNDi0xBaX9DKjX13UDJD23CgG75XNSAvw7GbZ+BimZdL4p+zh0/AJyF7HKfq1dfOjWIV7f+Dp34u4YTXu73tv0qdpHa2bq3564e/DXaDi4yMKX5JLNWJl3gHHKuSQArQ/13V9/5dqY981u9KtXl5Lffoubt317VV6JusJ7W95j/03LQR8BXgGMaTiGZ8s+a72TOrrDbs9oBTGRBKCCYOpYlCQATYMoxK6mPmD5FLN/cO8fAxbHfwUpuSODCe8AU1L/7UPgfxk+F8d0/0n9NzFW62UbXJAEYCag6fFBb0Ps5S1OiMCd6ATaz9zC1XvifUfa6lchmZr5U5x2Iy7els9Yf5rPN4i2ruarUuFAVr3eHA95FNhpMl5Tz2hR+beoK5xZl4avmzt0XwwVn3YazKUj6iFgl3y+cQyWD4TrpknUZsvTD9p8BPUFYaPvnwtRCVE89etTRCREPHDRDTdmPzGbFsXEVlsuRRAQvSPFS48I8zYjRtm+QSS0nsCa0EBjPkkC0HrEUxISuNi3H7H79j24OfczzxDyyQS79gNcfW41H+38iKhEyzmStQrWMh75LRYoOj0597LLM1phCCUBqDCgOhWn77/oyoAuXs2/AIjX8qIfoKNX7dRKRNEZVzxZxbFgQeiJ/+4ODEw18BRQD8g4ZkkSgCpFUI8PepWgcEqxv+4LJS4pmZ4NSjjVsaBkQwovf7ebLafFTJ+01a9JCWqmnDP+gzNuxGMTknn7l0OsOnzNIl+blM3PnBfrkMffvm/MnfKLoyGnNPeM3vstrHwzDSFBAD47E+r01hBq0hStIqBqPhuSYccXpuPpyWL2XYZVrD48N8+pBtOsvbCWt/5964GjZYLKMPvx2RTPXVyrKaAfu+IjYe1Y2CfmC2ayyj0JHWYS65VX9gDMYVSTbt/mfNcXSLp+nYIj3iT/gAF227OKyb5i0MfKcystvBCDPgbXGMwrNV7BU7S8cIGl6jNaJfwkAagSsDoTKwlAU+WfOPorXn82fMjgDXuGVtRM/whk1TRBkH/tgDOZGCUJQJUipccHvUpQOJ3Yi2HRPP35FmISkmlVsSCTu9QgONDXKfz8dO1JZm00f1Q0LJ2P+b1qsHH9eqOPzkYA3oiIM/b7Oxx6zyKGLzYswf86VMXLxacdO0VyZ3BCk8/ojR/D5qkgqqm6fg8V2zoj9NInFRBQLZ/DL8DvQ+BiJl1vxA/3lqOh6XDwcL4f8V8d/opZB2bRpEgTpj02jUDvQBUi52Iiz2+BFUPg7iVLxwW+bT+B2r2NVX+q5bSLQR579ChJt24R2FLJ2YwPB/HgzYOM2jIKcfQ34yqaqyiTmk+iVnAtl4qEHvNZEoAulaJZOisJQBM0Q1Kn/64G+gHmpTKOyZWSwBupRJ+ooxavaMWv+J+B2UBMFmZJAlCleOnxQa8SFE4lVlTIdZu3g70Xwx/4lS/Am7VvtqBALh9d+7rxxA36fb/XzIfgQB9Wvt6MQM8Up3wTfyT0HgN+2POap8UAACAASURBVMONiHgzv8VJ33HPVuWlxiXt9rZc18mjQ+M1+YwWR4HXvg9Vn4NiomhfLolA9hBQPJ9FLh5YaOrPlmB5dI+ClaHzPAipmT0DdXiVaAvx57k/eab0My5TpaRamBJiYMOHsGtu5ipKPwYdZ0OeEg8+VzynVXPOsYLFUV/Rrdndzn39MvM6yZCEIM7nHZ6HIZMeoc+WeZb3Gr5HLm/nHiSXGTZ6zGdJADr2u60V7a5EAH7wCNDFa3kxeTcWEE17TjyEZEsvarxWgqkzOwSpKfovcvnyZYoV036vCD0+6HWWEw4x999Tt+jz7W4z3T0aFGdi5xoOsUcppZfCYmg/awsRcaKdqGl5uruxdGAj6pXK55Rv4lcfucaInw4Sl2jeyD7Qx5PZL9bhsQoFlYJXytEgAvIZrcGgSJNsRkDRfI68YZrIeuqvTOxxgybDoNX74KX/yvfE5ES8PMRsP7lUQ+DSLvj91cwnRnv5w5PjoV5/cBdzC9OWojmtmnOOFZwUFkboG2/gXaoUIR995NAXlpcjLzN6y2jEAJ2MK9Ar0Djh95kyzzgWMAdq12M+SwLQgQmjIdWuRACKX4Rp4y+zDoLAJDvX3ZfgoaF46skUSQDqKVpObus/J27y7q+HuRUZT4l8/qx5ozkBPvo9/hSXmMzzX27n6NW0hucihGPbV6F/s9LGaOpx45JVGoqqDnHM+bN1ojuC+SqZ359v+tSjXLA86uXkX2PH5fTBJSAmpQYWcnaIpX92RECxZ/SxFfDncIg1Tb81W6I6q9NcKNXUjp6pp+qfS/8wcfdE5reZT4ncaZVn6ml0QcmiknT+E3AlbRDFAxRKNIFOX0C+MpkCo1hOOynscceOcXnoMJKumXoXFxozhny9e9ndW7GnEn3+JuyaQHRitIX+OsF1jIM+iuTS92TwnAKrx3yWBGBOo+4c97saAahG1Mxfb6mhwTllSgLQOeOqW6/EpNyxv/9H36aljBVyel7v/nKIn/aGmrnQrkYIs3vUfvA2WY8bl8xiIsjOd345zJ+Hrlp8LHodzu1Vl7wBctiHnvM5u7bbPafFD2HR42/LNNOxyZdXgY8kmrMbL3ndwxHIcT7H3oU1I+Hw0swV1XkJnvrEKXJWEBYLji7gs32fkUIKpXKX4sdnfiTIJ0immRoI3DwO81qkDZDx9IUnPoCGr1pU/aVXn+OcVsMXjcg0xMRwpvWTJN9JR9R7eFDim/kENBIH1OyzxKTsj3d+zJrzaywUerh5MKTWEPpX64+Hu6x/0WM+SwLQPt8jrWtxJQJQ67FwNfskAehqEZf+2gWBZXsuMfJXMdMobZUtGMCKYc3Ila6qUY8bl8wAFEedn529lXuxiWYfi2PcH3aohrenfEdjl8TTgBK75nRyIvzxOhxanO6L9gT0XAby+KEGskH/JuQon8/+AyuGQoRlw34CgqHDLKcaSLPsxDI+3vWxWdAbhjTky9Zf4uUujwOr8m3YOh3W/w/ExOhOX0KB8o9Uk6OcfqR0/V8Q8fdarrwh2r+blmdICMVmz8KvalW7OLfvxj7e2/IeV6MtX6gWDyxuHPRRo6C+2+MoCaQe81kSgEpmgH5lSQJQv7HTu+WSANR7BKX9mkNADMB4fu52EpLSeuD5e3vwx7CmFkdg9bhxyQrw7Wdv89I3u0kypCCGfYxpV4V+TUs5tHeO5pLDBQyya05Hh8H8x0FMVE2/ui+GSu1cAG3potoI2JTPYjCDIGV2z8vcvModoP0MCMivtvl2lR+TGMNLa17iZPjJB3o7lO3AuMbj8PaQFeA2ByM5Ketp0IZkOLQEavaAbFaD2ZTTNhuvzxtvzZzJ7Tlf4le3LsVmfo5nfvW/q4mGROYemsv8I/MzHfTRsWxHRjccTYBXgD5BVclqPeazJABVSgadiZUEYPYDJsaB5gFuAeYd5rMvQ16ZhoAkAGU2SAQUROBuTALtZ20lNFzMMUpbs3vWpn0Nyz4tety4PAyuRbsuMnH1CWb1qE2rSsEKIitF6QUBu+f07TPwzZOm3mpu7tB+OtR9WS9wSTs1joDV+Ry6D5YPgrDTlp6Jo7DPTIUaL4Cbc279r0Vdo8eqHoTFhfFGnTeMxxTdnNRX1VNXVDiLCr8TK6H/OvAUP4FyvqzO6Zyr1J2EFIOBuz/9RJ7OnXGzwxTgyxGXGbVlFIdvH7bAKtA7kA8af0DbUmJOplwZEdBjPksCUOaxQMA5dwHWxVbMLW+RestmICrD7QUA8Sq1vajGTv18PvAeEG+dKnl1OgQkASjTwSEIzNxwmmeqF3aqoRAGQwr9Fuxh00nxfiJt9Wtamg+erZIpznrcuDwqYW5GxhEcqP8plo/yU36eOQIOyenLe2BJN+g4x6mOVMocczwC2c5nQdZsngqbp0FKsqXhpR+DTnMgSGy7nHsdvnWYmzE3aV2ytXM7qqZ3or/f8sFw7aBJS7MR0HqcIhqzndOKaNOukOSICDxy53aogaJv5oqzK5i4ayIxSTEWttQrVM846KNwQGGH2qll5XrMZ0kAajmj7GebJAChD/AdIDrml8pQ3SeaR+0C6mQgS8WU4N+B5+0XKqfTJAlApwup9h1adfgaQxfvx8fTnVFPV6JP41K4izOjOl+frz/N9PXmE3DrlczLkoGN8PLIvAee3jYuYtjHysPXeL5OUVnVofN8Vct8h+V0fBT4iHeJckkElEMgW/l88wQsHwjXDlkq9vSDJ8dD/QEPHcygnMX2kSSIC1nZpwLW4kjv9lnwz4S04R5CjahuFlWAxerlWGm2cjrHWrQrQOTunW++IWz+N5RaugTvUuJnp/3Xvfh7jN8xnrUX11oo93TzZGjtofSt2lcO+nhEaPSYz5IAtP/3TYsa9f/LN+eoig7e3YFZQFrnVZPcHsAiQBB+B4B/gcdSCUHxb6Iq0HJMUs5tcgUJkgB0hShryMcbEXE8NWMzd2PShkWISsA5L9bVkJXWm/LvqVu8/N1uxEDS+6tALh9Wvd6MQrmzrobT08blVmQ8Axfu5cClu3zYoSp9mjhm02x9dOQd9kRAtZy+exnyFLenK1KXRICH5rPBALu+hPUfQnImh1GK1oXn5mVrMINeoE42JDNt7zR8PX2NR3zlUhAB0c7g91chdLelUDcPeHoyNHglxwpVe0bn2DL1BRhiY7n2/lgiVq0yKvMuW5ZSy5bikcu+L4/2XN/D6C2juRFzw8LpkrlLMrn5ZKoWsM/QEfVRV1eDHvNZEoDq5oRepEsCEETTA/Gk6wksyxA4Qe49BewFmgBJgBgntgWoD/yUShLqJd5aslMSgFqKhgvYMvb3/1i486KZp593r0XHWkV1631oeIyx7196UtPD3Y1FAxrSqMzDG0frZeNy7GoEAxbs4eq9OGOcRMHm930b0KJCQd3GTRquDgKq5PSeb2DNSHhhgRzuoU7YpNQsEMgyn+9egt+HwAWxFc2w3D3hsZGmY5seomuNc6yohCje2fwOW69sNTo0odkExJAPuXKIgCCSxcAYQSQnmfcPNkouUBGe+xIEoazAUuUZrYBd9hBx87PphH31lZmqXK1aUeyL2bi5Z35SQ0m7EpMT+eLgF3z737ekGOtazNfz5Z/n3frv4u/lr6Rap5alx3yWBKBTp2S2nZMEIFwHxC/JxkD6V1+C6LsLiBKafsCCdKiKLt/fAueBstlGW16YHgFJAMp8sCsC4gjplL9O8u028bWFdjVCmN2jtm6PEsUnJdN17g4Oh94zw3H005UY9NijH0t62LisPXqd4csOEpNg3tcqJMiXTe+0xMfTw645JJVpGwFFc1qU1G78GLZMMznt6Qt9/oTiDbQNgrTOaRCwyGdfXzi42ERIJ0Ra+inIms7zoEhtp8FAOJJkSDIO9zhx58QDvzzdPZnfZj51CylDTDkVYNl15s55WDEMLppIVfPlBk2GQav3wUu5vrqKPqOz66dGrjNER3Oh54vEn0ydVO3mRsHhw8k/8BXV96EX7l0wDvo4GnbUAo3c3rn5X5P/8WTJJzWClH7M0GM+SwJQP/mlpqWSAIQEQPyKFLuI1I63RshFxZ/4qyhek4gRmulrpe9/Jl6XyZnotmWoJABtw03elUMEtp25zdS/T/J93/rk8ffOoTTH3f7e8iMs3nXJzIC2VQvzZa862dpMannjIvrkzP33HFP+PmF2tFk4WzSPH9+8XI9KhR3bQNtxkZeas0JA0Zw+/ics62Wuyi8fvLodcofIIEgEVEfALJ+b1sZv3Sg4aTo+aEHWNB4Kjwuyxk91uxyh4OdTPxt7lt1fXu5exirAp0s/7Qhz9K1TvNzY+y2sHQuJ0Za+5CsDnb6EEo0U91PRZ7Ti1qkvMCE0lAtdupKSlESRaVMJbNlSVaViL7X8zHIm7Z5EbCYVng0LN+TjZh/LQR82RkGP+SwJQBuD7WS3SQLQVOUXCIhdRPpuqKOAT4DTQMUMcRevV/cBkgC0/QshCUDbsZN35hABvTcR/2VfKG//bN70vXSBAFYMa0puX1G8/Oil1Y2LqGx877f/+HW/mMtkvsRgk7m96yJ6HMolEciIgKI5LX4ki+qYgz+mqRFHK1uOBje5dZLZpz4C9/O58N19NLjxI24xYZZKg4qbyJrSzdU3yMEaJu+ezI/HfySvT15mtJpBnUJiPp9cViFwL9T0XDv3T+a3NRhkmvjrrU5tg6LPaKsc187FMfv345EnDz5lyqhq1N24u3y440PWX1pvoUdU0L5e+3X6VO2DuxjyIpdNCOgxnyUBaFOone4muYs1EXm1gMnAe+kiLKb/ipFX4qhvxs63bYC/ANFQrLTTZYV9HJIEoH1wllqcDAHRE++5OduITzI88MzPy4PfhzalYmHxLiN7S4sbl9tR8QxeuI+9F8MtnOhcpygTO1eXx36zF16XvErxnE5OhCU94OwGaPcZ1OvrkrhKpx2DQOzdW9z64WVK3MnsiKbYufaCthPB1zWqoe8PAXmx8osUCxRbSLmsQiD8AsxtDvERlrcFlYBOX0DpFlaJtPZixZ/R1hpgh+uTwsPxyJ0bNw/HtSjZfW03o7eO5mbMTQuPS+UuxeQWk6mSv4od0HBuFXrMZ0kAOndOZtc7SQDCJOBdQPxFFFN/RVdlscv/PPX473PAHxkAfRuYAuwAmmYXbHmdGQKSAJQJIRGwEoF7sYl0mL2Vi2ExZnfO6FaLTrWtG2aitY3LiesR9P9+L1fumjciF8VWI9tWYlCLMtk62mwlpPJyJ0JAlZyOj4Ir+6DMY06ElHRF8wjcOY9hcTfcb6f2C0tvsH8B6DBTDqXRfBA1ZqCoahZtDU6sNDes7svQ5mPwyf4LRFs9U+UZbasxKtwXd+wYl4cNI6hdO4LfeksFDQ8XKU63iCEfMw/MxJCS9pL4/l1dK3Tlnfrv4OfpnK0C7A24HvNZEoD2zhJt6pMEIIhmPsdTjwGnj5LA5hhQPZUITP+ZqJ0Xr8mmA4IMlMt6BCQBaD1m8o5sIhCbkGwc9jGgeWmnqRgzGFIYuHAf64+nb0cKLzUuyfiO1bKJTNplWtq4bDh+g9eXHCA6w7APf28PBLnZpmphq/2TN7geAlrKaddDX3qsGALn/oWf+0CsZSU0ldpD+xmQy/mmoItqpQk7J/B+o/cp6O98/imWHzkRFHUT5jQCcZw8sAh0nAXlWudEolX3OvMz+t6qVVwb8z4pcXFGTIpMnUrQs+2twicnF0cnRjN221jWXVxnISaPTx4+bPIhj5d4PCcq5L0ZENBjPksCUKaxQEASgKY8EM1TlmIiA++vc4B4cqeNHTN9IsZrileyArtngL9lKtmEgCQAbYJN3pQdBD5Y8R8/7LhIpcKBTO9Wi8oh+j8iNWfTGeMU4/SrVvE8LBvUyCaSUwsbF/G2+put55mw+rjFsI8iQb7M71OfKkX0H7vs5Ky8JucI2JTTJ1bDgR+h6/fgqd+hQDlHT0pwOAKiQmvPfNOU3xTzyecp3oG4PTMFavZwyh6Ux8OOM2zjMOORxWr5q/Fd2+/wFZO35VIegaO/w6m/TcfH/fIoL/8hEm16RtvVQtuUJV69ypmn2kJi4gMBbj4+lFy0CL9qVW0TasVd5+6dY/g/wzl/77zFXY1DGhsHfQT7B1shUV6aHQT0mM+SAMxOZJ3/GkkApsVY7PzFcV5RanItdQJwUiYp0Ax4IvXfRd9A06seuaxFQBKA1iImr88WAv+eukWfb3c/uNbLw42pXWpafUQ2W8rsdJGYXNz7m10YxEzy1JUvwJuVrzWjSB7bjnJoYeMSGh7Dk59tJjbR/Mdu7RJ5mNe7LsGB8gegnVLMKdRYndNiEuaqt0AclarRHZ6b65TkilME19mdSEqANe/Avu8tPI3wLYZ3n1/xDanklCjsub6HoRuGmk0pbVOyDVMfmyoHFNgScUHwiSEe5Z+05W5V77H6Ga2qNcoKD1/2E9fHjXsg1K9uXYp9PgPPAgWUVZRB2oaLGxizbQyiAjD9csONYbWHMaD6APk9UikCesxnSQCqlAw6EysJQJ0FzInMlQSgEwVTK64kJRto9ekmLt9J6yPn6+XO6tebU6ZgLq2YaZUd1+7F0n7mVsKiEx7c5+4GP/RrSLPytm8stbJx+eu/6wz+UcxiMq1OtYow6fka+Ho5roG2VQGSF2sGAatyeusMWJ/2Y83oRLMRpgmYckkE7IlA9G1Y1hsubbfQei2oLvtLDuTxpzvi52fbyx57umKLrvC4cHqu6kloVNrk9+KBxfnh6R8o4Gf73zhbbNH1PTF3YPXb8N+vEBAMQ3eBfz5NuWTVM1pTlmfPmGsffsjdJUvJ88ILFH5/DG7e6lWVi6E4sw/OZv6R+RbG5fbOzZQWU2haVLapz17kbLtKj/ksCUDbYu1sd0kC0Nkiqh9/JAGon1jpytKT1yMZvuwgx6+ZJt191KkavRuV1JUP941NSDLQ7asdHLh018z+d56qyNBW5XLkk5Y2Ll/8c4apf59E+DWkZVk57CNHkXXdm63K6dB9sKA9JKYbqCOmqnaYBe7urgui9Ny+CFw/Akt6wr1LFnoTm7zJ6pia4OZOmzZtnJYAFI6fu3uOXqt7EZkYSd1CdZnRcgZ5fO17PNW+gVdY28k18OcbEJWuR3C156HLtworypk4q57ROVPlkLtTEhKI/GcTuZ9qo6r+u3F3eXfzu+y4JmZRmq9K+SoxveV0OSlb1QiYhOsxnyUBaIfE0IEKSQDqIEhOaqIkAJ00sFpwKz4pmRnrTyPIwG/61NMtoTRuxX8s2HHRDNLWlYP5qnc93EUZYA6WljYuohfgodB7iJ6GckkEbEXA6pwWfbCW9DD1W2vxLrR6Tx4BthV8eZ/1CBxbAcsHm5PQQoqY0NlpDrFln2bt2rVGuc5OAAoft1/ZztqLaxnTcAxeHl7W4+mKd8Tehb9Gw6HFmXvf9y8o2VgzyFj9jNaM5SZDxF4l6eZNvAoVcphlx8KO8eY/b3I1+qqFDc+WeZaxjcfKKb92io4e81kSgHZKDo2rydkvSI07J83TNAKSANR0eJzDuGRDCh45JMochcSKg1d4Y+lBM/Ul8vnz57BmBPnn/MeRPTcuYtO8/9Jd6pbM6yg4pV4XQMCmnN63wNQDsF5fF0BIuqgJBAwG2DwFNk20NCd3MeixGEJq6rK6RBP4uooRZ9bDitcg0pIIQlRPPjMNqnfR1EsNm57RGomnIS6Oa++PJWbXLkr98gtehew/VGPFmRV8tPMj4pPjzVDxdPPknfrv0KNSD92+8NZImK0yQ4/5LAlAq0LstBdLAtBpQ6t5xyQBqPkQSQMdhYCoXOz0xTaz4Rg+nu78NqQJVYsEKWKWvTYu4hjzuD/+Y8nuy3zevRYdaxVVxH4pRCKQEQF75bREXiJgMwLxUfD7q3D8D0sRxRtCtx8hl4lYcLZ83nZlG5cjL9O9Uneb4ZM3AvGR8PcY2L8gczjKPwXPfg65QzQHl15zOvHaNUKHDiPu2DEjpr41a1Dyhx9w9/GxC8aJyYlM3jOZZSeXWegTfTI/a/kZtYNr28UWqSQNAT3msyQAZQYLBCQBKPPAUQhIAtBRyEu9mkYgMi6RjrO3ce62+US3qV1q0LVeccVst8fGJTw6gVcX7WPnuTtGu7093Vk2sBG1S8hKQMUCKQU9QCDTnL68W5zbghINJVISAcciEH4RlvaEG/9Z2lG7N7T7FDzTCAV7PKPtBciSE0uYvHsyhhQDsx6fxWPFH7OXaufSc34zrBgKdy17RuKTG9pOhFovaqrqL30A9JrTV0a8RcTq1Wa5FPR8Z4pMmKB6ft2MucmITSM4dOuQhS5B+n362KcU9C+ouh1SgSUCesxnSQDKTJYEoMwBRyIgCUBHou8kuk/fiOR6RBzNyzvH5kcclX31x/38dfS6WYR6NCjOxM41FI2a2huXMzej6L9gDxfD0g1ZAIIDffjn7ZYE+Hgq6o8UJhGwyOmL/8AvfcHTF/qvg4IVJEgSAccgcHE7LOsFMWHm+t08TKRNg4EWpI3az2h7ACH+pk3aPYnFJ9J61Pl7+hsn/FbMV9EeJjiHjoRoWP8h7J6XuT9lWpkGGOVR7iWhGsDpNaeTwsO50PUFEkNNk6rdc+WiyLSpBLZsqQZMD2Tuu7GPtza9RVhchucG0LNST96u97bsl6lqBB4uXI/5LAlAByaMhlTLCkANBcPFTJEEoIsFXGl3xdFScUz22LUIXm5SipFtK+Hn7aG0GrvK+3rzOSasPm6ms3rRIH4e3BhfL2V9U3PjsvnULYYu3k9kXJKZL75e7nzatRbtamjvaJJdAy2VqYJA+px+Ovg63mtHmfr7iRVUAgasg8DCquiWQiUCWSKw73tY9RYYzJ+Hxj5tXb+Hsq0yvVXNZ7Q9ozXv0DxmH5xtprJX5V6MbDDSnmboV1foXvjtFbhzztIHrwBo8xHU66fZqr/0Rus5p+NOnuJCjx54FSxIsTlf4FO2rGo5JYhzQZpP2zONpBTz54aPhw/jGo/j2bLPqqZfCs4eAnrMZ0kAZi+2zn6VJACdPcLa9U8SgNqNjS4sm/r3Cb745+wDW8sUDOD7lxtQIr+/LuzPaOSuc2H0nL8LMbjk/srj72Uc+lE8n/I+qbFxEZvWBdsvMH7lMdK5YXSnUG4fvn6pHjWKyUm/ukxQHRj9IKdTDLSP/BGPs+vNrW40xFRtJZdEwB4IJCfC3+/B7q8stRWoCD2WQP6sSQQ1ntH2cDujDvF3YfTW0aw6t8r40eCag3m15qu4u7k7whz96by4A757WsygNbe9ZDPoOBvyldaNT3rP6Zi9e/GpUAGP3LlVwzw2KZb/bf8fq8+bHzkWCovmKsr0ltOpnL+yavql4OwjoMd8lgRg9uPrzFdKAtCZo6tt3yQBqO34aNq649ciaDdzixnJVKFQLv4Y1kzxSjl7AHEzIo5nZm7ldlTaZDc3N/ju5fq0rKjOpDmlNy6JyQb+98dRFu2y7E0kqhgF+Vc4yNcecEodLoqAWU63bIrfsq5wdb8JDdEXSzTG98j5BG0XhVe6bQ0CMXfg5z4gerZlXGJIw/Nfg+/DBzop/Yy2xnylrxVTS4euH0qn8p1oX6a90uKdX54Y+rEjtYrS0w9aj4MGg8BdXySq1nM6ITQUr6JFHTZJVwzJGf7PcE6Fn7LI6aZFmjK5xWSCfJQZBOf8Xxr1PdR6PmeGgCQA1c8LPWiQBKAeouScNkoC0DnjahevREXBwp0X+WT1ceISDXh5uPH70KaKTci1ixOpSgRx1vPrney5EG6mdnjr8gxvrV7PMiU3LndjEhiyaD/bz1r2qWlXPYRpXWvq/ni2PXNC6rINAYucTo6Cb9tAtS7Q6j1dHJGzzXN5l6YQuHkclnSH8AuWZjUdDk98AO6Pbumg5DNaC/iIv9tu4s2WXNYjkBgL81pgPDbe6UsoUM56GRq4Q8s5HbFmDVdHv0fB14aRv39/u6O1JXQLI7eMJDIh0kL3wBoDGVJzCB7ZeG7Y3XAXVqjlfM4qLJIAdOGETee6/Ess88BRCEgC0FHIO5Hes7eiGLHsIE9VK8yQlvrcEH+88hjzt543i8pjFQoaq//c3dV7RCu1cRExGLBgL+czTC0WDr3xRHnj/9T0w4nSWbqSQwQyzen4SPAJzKFkebtEIJsInFht6teWEGV+g4eP6bhmjReyKQiUekZnW2EOLhTTfRceW0incp1khZKtON46CfnLZ13Vd++KqYepjkkgLeZ0isHArc9nEjYvdcCKmxvFv5pHrubNbY2kVfeJ785Xh79izsE5pGQ45p3LKxcTmk3g8RKPWyVTXmwfBLSYz4/yXBKAj0LINT5X79ela+AnvbQdAUkA2o6dvDMdAqKCzt3NDQ8VyTK1AF91+JpxWEb6VTSPHytfa0beAG+11BrlKrFx2Xr6NkMW7SMiw7APH093pnatSYeaRVT1QQqXCKRHQImclohKBGxCICUFtnwKGz+27NUWGALdF0HRulaJ1ks+xyTGMGbrGNZfWk+jkEbMaT0HL3d51D7bwRa9Ird8BpunwJMfQeMh2b5VbxdqMadjDhzgYs8XQXyHU5d7YCClf/sV7+LqTlWOSIhgzJYxbArdZBHKskFlmd5qOqWD9NPjUW/5mFN7tZjPj/JJEoCPQsg1PpcEoGvEWYteSgJQi1GRNtkNgTM3I+k4exvRCckPdHp7uPPLq43tMigjpxuXW5HxNJ+y0XgEO/0qGGga9lGruBz2YbdkcmVF57dAYgxUeEoRUtuVoZS+24hAQgysGApHf7MUULSeifyzYfp0Tp/RNnpj1W03om/w2sbXOH4nbXp9t4rdGNNwjDzumx0kxXHx5YPh2kHT1Z6+MHgrFCifnbt1d41Wc/r23HncmjHjAZ55unal8Nj3cfNW70Xs6fDTvLnpTS5GXLSI45Mln+Sjph8RIKY8y6VZBLSazw8DTBKAmk0n6sTHrwAAIABJREFUuxomCUC7wi2VpUNAEoAyHVwWgej4JDp+sY0zN82PiU3sXJ0eDUrYBRclNi5Ld19i1G9HHthbtUhu5vepR0iQn118kEpcHIE75+DrxyH2Ljw5ntjaA1i7bp0RlDZt2uDnJ/PQxTNEfffvhcLSnnDtkKWuGt1Ng2e8bBt+pMQzWm0ArkZdpeeqnoTFpfV/9XTz5Odnf6ZcXn225VAbM6N8QzJsnwn/fALJCeYqi9WHfn/r+qhvVhhqNadFf8orb44gcv16Co95jzzdu6tKYP914S8+2PYBYuJv+iUmY79Z5036VO2jqn675LgLKNFqPksC0AWSL4cuSgIwhwDK221GQBKANkPnejduO3ObSoUDyZ/LR/fOi43ma0sOsPLwNTNfutQtxtQuNey26VNq4/LRymN8s/U8basW5rNuNfH39tR9jKQDOkAgLgLmt4bbJx8Ym1TtBVZ7tCXF3VMSgDoIoe5NvLwblr4I0TfNXXFzNxLSNB6Wo8EzSj2j1cb50K1D9PurHwmGBAK9A5necjoNQxqqrVa/8m+fht9fhdA9lj64eUDzEfDYSKecWK7lnDbExBB38iT+tWurlltJhiRm7JvBgmMLLHTk9cnL1Memyu+OaugrL1jL+ZyVt7ICUPk80KNESQDqMWrOYbMkAJ0jjqp7cflODG1nbDZOkZ38fA2eqFxIdZ1qKvhu23k+/POYmYrKIblZPqQJvl6PngyplG1KbVySDSksP3CFzrWLymEfSgVHynk0Aju+gL/fM7suuVwbVubqCW7ukgB8NILyipwgcGARrBxuWb3lkxu6fAvln8yJdOO9Sj2jc2xINgSsOb/GOMRg1uOzKBVUKht3uOAlBgPsmgsbPoSkOEsAClSE5760uleknpB0ZE4b4uJIuh2Gd7GiDoEsLDaMdza/w57rlsRv1fxVjcR5SK4Qh9gmldqGgCPz2TaLQRKAtiLnXPdJAtC54qknbyQBqKdoOchWQS51/2oHey6EP7CgR4PifNypui6Hfuy9cIfuX+0kyZDWbDrQ19M49KNkfvv2erFm43IzIo7g3LYdY3NQ6ki1zo6AaNi+9TPYMN7kaXAVYnv+wdp/txv/Ux4BdvYEcJB/yUmw7gPY+YWlAfnKQo+lULCCIsZZ84xWRGEOhSQkJ+DtoV7PtBya59jbRbuC34fCJdPzyXy5QZPXoNUYm4+LO9a57Gt3VE4nXrtG6LDXMERFUeqnZXgEBWXfaAWuPHzrMCM2jeBGzA0LaZ3Ld+a9hu/hIyaFy6UrBByVzzkBSRKAOUHPee6VBKDzxFJvnkgCUG8Rc4C987ec4+NVac3FhQnd6hVncpcaDrAmZyrF0Iz2s7ZwIyLeTND8l+rRuor9qxqzu3FZsvsS4/44yle969KyYnDOQJB3SwSURuD4SlMlYJ8/ifUNZu3atUYNkgBUGmgpj9hw+KUfnN1oCUbZx02Vf355FQMqu89oxRQ+RNCduDv8d/s/WhRrYQ91zqNDVP3t/QbWjYPEaEu/8pWBTnOhhGscmXZETsfs30/oa6+THGbqUxnQrBnF583FzcM+Jy5+OfULn+z6hERDoln8xaRsQfx1qdDFefLdxTxxRD7nFGJJAOYUQee4XxKAzhFHPXohCUA9Rs3ONgvSbPRvh1l/3NRjqXg+P9a80YJcPvrqM5eUbKDXN7vYee6OGYJDW5Xlnacq2RlVk7pHbVyEzZ+sPsG3284brw/08eS3IU0oXyjQIfZKpRKBLBFISgBP70fmtERQImAzArdOwZLucOespQjR66/1h+Ch7N+lRz2jbfbFyhvPhJ9h2MZh3Iy5yfw286lTqI6VElz08ruXTdOhz/+bOQANB8MT48Db32UAsndOi57LF3u+SOyBA2YY5x88iODhw1XFPT45nom7JvLr6V8t9AT7BxuP/NYoqL+X2aqCpjPh9s5nJeCRBKASKOpfhiQA9R9DvXogCUC9Rs7OdosN3LI9l5mw6jjf9a1PvVL57GxBztVNWnOCuf+a/3BsWi4/P/Rr6LCjzA/buETEJfL6kgNsOnnLzPkS+fz5c1gzgvy9cg6KlCARUBgBPW7GFYZAilMDgdPrTJV/8RHm0sVx1/YzoPaLamjVBKG99cpW3vn3HaISTRPrxaCCRe0WUTywuCo+O5XQRV3htKki2WzlKQEd50Dp5k7lbnacccQzOvH6dc536Ury7dtGE71LlqTYnC/wKVs2OybbdM316Ou8+c+b/Bf2n8X99QvXZ2qLqeT3y2+TbHmTdhBwRD7n1HtJAOYUQee4XxKAzhFHPXohCUA9Rs2BNgtSKrev/oinv49eZ9DCfWbIhQT5Gvv+OXKqcVYbl4th0fRfsJczN00/+NKvV1uW5Z02FeWwDwd+D1xSdUIMCLLlERVWetyMu2Q89eK06DO5fZap5x9pfVuN5gcEQ/dFULyBat5oIZ+n7JnCwmMLzXxsWrQpc1vPVc1vpxEcdhbmNoPEmDSX6vaFNh+Bj2tW0jsqp8Ux4It9XiagUSOKfjoNj9y5VUuzXdd2GUnz8Pi03tX3lfWp0ofhdYfj6a5stbBqzkjBD0XAUfmck7BIAjAn6DnPvZIAdJ5Y6s0TSQDqLWLSXqsROH87mg6zthIZn/TgXi8PN5YNakydEsr1irLasCyOAO86F8bgH/cRHmPeq8bbw51Jz1encx3xtZVLImBHBEQPrZ96Q0I0dP3uoT3W9LgZtyOSUpU1CCTGwZ9vwOGllneF1ILuiyFI3WmiWsjnZEOy8fivqAQUq0aBGnz++OcU8CtgDZque+2ur2DNO5C7KHSYBeWecF0sstF6RE1wYg8dwrdaNdV6/4nTKguOLmD6/ukYUgxmrvh5+jG+yXjalm6rpotStp0R0MIz2lqXJQFoLWLOeb0kAJ0zrnrwShKAeoiStNFmBGISkug8ZzsnrkeayRjfsSovNS5ls1ylbsy4cfnjv1u8//t/JCabV7rkD/Dmq5fqUrek/o5eK4WVlONABDZ+DJunmgzIXw56LIMC5TI1SI+bcQciK1VnhUDENVj2Ilwxr9w2Xl7teegw2y5927SSz1EJUfRe05vyecozvul4fD3lRHiz1BGVom5Z/JwSLzB2zII6fcAvj8t/59TM6bjjx/GtXNkhGMckxjB221jWXrQ88l0isAQzWs2gfN7yDrFNKlUPATXzWS2rJQGoFrL6kisJQH3Fy5mslQSgM0VT+pLh90AKI346xPIDV8z+vVOtIkzvVgu3rH4s2BHH+xsXQwocdivNdzsuW2ivVDiQ+X3qUSyv6zQpt2MIpKpHIXDkF/i1v/lVeUvBsL3gYdkOQI+b8UdBID+3MwKC9Fv6IkRey6DYDZ4YC81GZE32KGyqlvL5btxdgnyCNPG3S2GYcybu6HLY+SX0/t0upHDOjHX83WrkdIrBwK2ZMwmbO4+QCRPI83xnuzp64d4Fhv8znLP3LAcEtSzWkgnNJ5DbW70jx3Z1ViozQ0CNfFYbYkkAqo2wPuRLAlAfcXJGKyUB6IxRzaFPv+4LJTwmgQ41ixCcW79VBgt3XmTs7+bNnysWCmT50Cb4e2uj94vYuPyxei0LTrtz7K67ReRaVw5mRvfaupu4nMMUlLdrCYHLe2BpT4g2TQHHzQN6L4cyj2VqpR4341qC2+VtObQM/ngNkuPNofDOBZ2/hkrP2BUie+bz4VuHqZC3gqzuy26Eo8Ng9dtw9DfTHWKi79OTs3u3y16ndE4nR0Zy9Z13idq0yfQnwsuLEj8swL92bbtgvPHSRsZsHfNgSM59pW64MaTWEAbWGIi7m+X+yi7GSSWqI6B0PqtuMCAJQHugrH0dkgDUfoyc1UJJADprZG30S/RPaTN9M6dvRuHuBo3L5ufN1hV0N/X3wKVwXpi3w+wobaCPJyuGNaVMwVw2oqP8bZdu3aXbnK1ci7X8MzCoRRnebVvJYROKlfdWStQtAvdCYUkPuH4Y2n0K9Qdk6YoeN+O6jYszGW5Ihg0fwrbPLb0SFac9lkKw/Y8W2iufl59ezvid43mixBNMaTFFEhaPyu0Tq+DP4WkvJu5f32elS072fRRc6T9XOqcj/vqbK8OHm5ngUbAAZVeuxCMoyBrTrLpW9Macc2gOXx3+yuK+QO9AJjWfRItiLaySKS/WHwJK57M9EJAEoD1Q1r4OSQBqP0bOaqEkAJ01sjb6dexqBM/M3GJ290+DGtOgtH56z4VFxdN+1lau3Ysz82Nur7q0rVbYRmSUvy06Pomuc7dz7Jp5f0IxoOST56rTtV5x5ZVKiRIBWxEQA0D++w3q9H6oBD1uxm2FRN6nEAJx9+DXAXDasncXpVtA1wXg75i/QWrnsxhUMGP/DL7777sHYA6uOZihtYYqBK6TiYkNhzWjMh8MI1xt+Co8PcnJnFbWHTVy+sbESdxZsMBkqKcnhd4bTd4ePVQ7rn4v/h4jt4xk25VtFuCIKtoZLWdQPLfcQymbOdqUpkY+q+2pJADVRlgf8iUBqI84OaOVkgB0xqjmwKeJa44z799zDyQUzePHlndb4S7KAXWwkg0p9Pl2N1vP3DazVlTTjX7G/tUjD4MsLjGZ1xfvY+3xWw8uyxfgzbzedalfyjE/dnUQYmmixhHQ42Zc45A6t3lhZ2FJd7h9ytLPBoPgqQmZ9pq0Fyhq5/OVqCt0+aOLxfHF+W3m0zCkob3c1Iee0+vhj2GZ9IYEfPOYqpPFgBgN9PfVMqBq5HRKUhKXBw4k7vgJis6YQUDDBqpBcOLOCWO/P/HdybieKf0M/2vyP8TEX7lcAwE18llt5CQBqDbC+pCvj1/W+sBSWmkdApIAtA4vp7969/k7LN1zib//u050QjKDHyvLqKcr6cbvT9eeZNbGM2b2Niydj0UDGuLpob0eMFHRMQz9egP/XneneF5fFr/SmOL55LAP3SScNNQCAT1uxmUYHYTA2Y3w88sgKgDTL3cvaDcN6r7sIMPS1Nojn0UV05ANQxDVgGL1qdKHN+u+iYe7h8P914QBcRGwdgzs/yFzcyq0hWc/h0DtVPhrArcsjFArp5Pv3iU5KhrvYkVVc//Ps3/y4Y4Pic/QI9TTzZO3679Nz0o9Vas6VM0pKThHCKiVzzky6hE3SwJQTXT1I1sSgPqJlbNZKglAZ4uoQv6I6rQNx29StUhuShUIUEiqumI2HL9B/wV7zZQEB/qw8vVmBAdqc5jJ/Y3L5mtu9G/flCrF8qsLkpQuEXgYAidWm45almhkM0563Izb7Ky80TYEUlJg1zz4+z1ISTaX4Z8fuv0IJZvYJlvhu+yVz0tOLGHK7im83+h9nq/wvMJe6FjcuX9hxVC4d9nSCZ/c0HYS1Oopq/6sCLGtOZ14zTSV2yskxAptylyamJzItL3TWHxisYXA/L75+bTlp9QtVFcZZVKKrhCwNZ8d6aQkAB2JvnZ0SwJQO7FwNUskAehqEXdSfy+FxdB+1hYi4pIeeOjp7sbSgY00PcBEjxsXJ00h6da1Q/BtW0hONFXT1H7RJkxkTtsEm+vclBQPq0bAgR8tfS5UDXosgTwlNIOHPfP5wr0LlAoqpRnfHWqI6Dm6bhzs+TpzM8o+Dh1mQZDYxsplDQK25HTM/v2Evv4GXsHBlFz0I+5+9jtieyvmFm/9+xYHbh6wcLNmwZp81vIzgv2DrYFAXutECNiSz452XxKAjo6ANvRLAlAbcXBFKyQB6IpRdzKfRbVi5zlimEaEmWdj21ehf7PSmvFWTFh2y9CbSI8bF80AKg1RDoHIG/D14xARmiazyWvQejy4W3d0Xua0cmFxOklRN2FZL7i8y9K1yh2g05fgo50p7cJIpfJZPP8vRlyUBF92kjr2LnzVEsLPW17tFQBPfQx1+8qqv+xgmck11uZ0+M8/c338R5CYaJSWu107ikybapejtoL0G7FpBLdjzfs6Czu6VezGyPoj8fLwshEJeZszIGBtPmvBZ0kAaiEKjrdBEoCOj4GrWiAJQFeNvBP5/e4vh/hpbzriAmhXI4TZPWrbZYOaHSj/u3KPj1cdY2aP2mbHkfW4ccmOv/IanSEgKm22zTA3unZvU4WNlQ31ZU7rLPb2MvfqQVjaEyIsG/fTcjS0eNdqstkepiuRz6Jf2QfbPmDT5U0sfGYhYkqpXI9A4LeBcHiZ+UWlmkPH2ZBXVknmJH+syWlDXBznOz1HwoULZioLj/vAOOVXrSUI86UnlxqPxSelpJ3sEPq83b0Z23gsncp1Uku9lKsjBKzJZ624JQlArUTCsXZIAtCx+LuydkkAunL0ncD3pbsvMeq3I2aelC0YwIphzcjl46kJD0PDY3huznZuRcZTLK8fC/o1oGxBU5WLHjcumgBVGqEsAoZkWPcB7JhtkluiCby0Ajy9rdYjc9pqyJz/hv9+g9+HQFKsua9e/vDcXKjSUbMY5DSfReWSmFh66NYho48hASEsbreYAn4FNOuzJgyLDYc5jU0Tf8VE1yc/hPqvaJIk1gReVhhhbU7HnzvHhRe6YYiKMmoJaNaMop9OwyMoyAqt2b80LimOj3Z+xB9n/7C4qUhAEaa3mk6V/FWyL1Be6dQIWJvPWgBDEoBaiILjbZAEoONj4KoWSALQVSOfzu+YhCRuRMRTWifDPu6bfiT0Hs/P3U5Ckmlyolj+3h78Mawp5YIDNRHZezGJRhvP3DRtnMXK4+/FT4MaU6FQoCQANRElacQDBPYvNFUC9vsbAmwjKPS4GZcZoBICBgNs+gQ2T7VUEFQCeiyGwtVVUq6M2Jzm89Q9U/nhmPn02trBtVnQdoFmKtSVQUoFKafXweZp0GkO5C+rggLXFGlLTkdu2kToq0PI168vwSNG4OahzoTq0MhQ3tz0JifunLAITuOQxkxpMYU8vnlcM3DS60wRsCWfHQ2lJAAdHQFt6JcEoDbi4IpWSALQFaOeweffD1xh+LKD1CwWRMdaRWlfM0SzU3Pvm343JoH2s7YSGm5eUTK7Z23a1yiiiaiK3oQvfbub3efvmNnTsHQ+fujfAB9PD0kAaiJS0ggzBJISbKr8uy9Dj5txmQEqIBAfCb8NgpOrLIWXbAov/GAzyayCtVmKzGk+i+O//f/u/6ACMMArwEhitCjWwp5uaFNXYizcvQwFH3IkWkyMtrINgTad1Y5VtuZ0/Jkz+JQrp5oj265s493N7xKRYN7PWSgcUH0Aw2oNw8NdHeJRNaekYNURsDWfVTfsIQokAehI9LWjWxKA2omFq1kiCUBXi3gm/vb9bjf/nLz14JOWFQvyfd8GmkXGYEih34I9bEpnszC2X9PSfPCsNo6FCBtfW3qAVYevmeFYPjgXv7zahCA/U9NqPW5cNJsY0jBNICBzWhNhcKwRd86b+v3dPGZpR92X4empOSKZ7emcEvkcFhtGz1U9jWbPemKW7AEogAg7Cz+9BOKo76AtEJDfnmF1aV2Z5XSKwUDMnr0ENLT/3s+QYuCbI98w68AsUkgxi42/pz8Tmk2gdcnWLh0z6XzWCCjxjLY3vpIAtDfi2tQnCUBtxsUVrJIEoCtE+SE+hkXF0+CTDSQb0jZd07vV5LnaIjW0uT5ff5rp60+ZGVevZF6WDGyEl4d1E0vV8nDCqmN8vcV8gmFwoA/LhzalaB6/B2r1uHFRCzMp104IxEeBd4BqVTUyp+0UR62qOb85jdhJb6ObBzw9GeoPUC331IBEqXw+93/2rgI6qqMLf9m4hwiSkODu7m6FUijuDkWKFvojpZQaXiga3LVY0eIe3F0DISEECHFPdvOf2YUkLwtk5b23b97OnNPzn5+dufLduy+z35u5NzoQrjau8LBnRBfu7wH+/R5IidWErEhjoMcOgJ3uEiKFtWRmz2kbpRKhP/4PcSdPIv/iRXBu0kQUO4iSuJQ4/HTuJ5wIPqGls5BrIfzd6G8Udi0smj1MEX0I8PWMFtNzRgCKibZ0dTECULqxkbtljACUe4Rz8O/KiwgM2XAN7+NT1DPtrBW4OrmZZBpoZDf/9ON36LvmMsitoI/D08kGB0bWQx4XO0lEc03Ac/y6j3vyhTQk2Ta4Jsp4c4tm07hxkQTIzAjDECDXeze0A5y8gLZLABsHw+R8YRXLad4hpUfg5RXAf+OBdCXXZvtcQKd1QOEG9PjywVJd85lcWySnlawU0mg+JUmgyfOHNBu65K9tXuPJQP0fJWm23IzKmtONSpTEu7FjkfLsmdpNhYMDCm7bCttixQR3+1nUM3WDnBcx3A7DRHFTv6b4o+4fIFfm2WAIfAkBXZ/RUkKREYBSiobpbGEEoOmwN3fNjAA09wwAkKZUIeDZe+y5+Qo2lgrM6FBekqiQbrqk7l9UQmqGfZYKC2wcUAO1ikjjVMWhu68xdNN1DkFppbDAmn7VUK+YlxauNG5cJJkczKicESCs+b5RwPV1mrn5KgLdtgAu/NbMZDmdcyhkN4MQO4fGA1dXa7vmVUqTZ+6FqHRbl3x+Ef0Cw08MB2lS8FPNn6j0U3Cjo0OA7X2BkCufzhFSE/JLtQAFN9B8FGTN6Zrh7xExm9ukx6ZwYRTeuwcWVsKR2UdeHMHkgMlIzNYZXGGhwMhKI9G/bH/WJMd8UtIoT3V5RhulQIDFjAAUAFQKRTICkMKgycRkRgDKJJByd4M01Oi87AJuh0RzXJ3YsiQGN5BGd8CrLyLQY+UlJGfpSkyMndOpAjpW+fSVaho3LnLPNdn6d3GphqTJOrwrA4NO8Holk+W0bDPo047FhwP/9AGCzml/XqIV0H45YCuNruyGRCanfL78+rK6a+nHxgUTq09E91Kaen9sfEDg6TFg5yAgkdsQS/1p+a5A67masgRsiIJA1pxu1qwZon79FdF79qp1W7q5wWf+fMFqAaap0rDgxgKsubtGy1c3WzfMrD8Ttb1ri4IDUyIPBHJ6RkvRS0YASjEq4tvECEDxMWcaNQgwApBlAhUITNp9B5svveTY+lWZvPDvWVkSb4mfvYtDB//znNOJxNixzYpjRJPPX6WhceNCRcIwI7URID/Ct/cHkj+Q6Fb2QP9DgHdFXtFiOc0rnNIWFnYX2NoNiOI+m9VG1xsHNPoJUEijLquhQH4pn6OTo9FiZwvEp8ZniCcnmPyb+KO2DyMxoFICp2cCp2cB2Zo7wNIWaDULqNyH1xcQhsbZnNZlz2lbCwsE9eqN9JQU5F+8GDb5fQSBIyIpQt3l99LrS1ryS7mXUtf783bi90S6II4woZJCgMY9ByMAJZVCJjOGEYAmg97sFTMC0OxTQPoA7LgWgnHbb3EMLeTpiD3D68DFTtNN15TjXWwy2vsHIDgikWNGt+q+mNau3BcJSho3LqbEmuk2EoF3j4EtXYCIQE1NtjLfGilQeznLad4hlabAB/uAXYOBLOSX2lBCLH+7GCjbQZp262lVTvl8MPAgxp/NPFlb0r0kFjZeiLyOefXUJLPpce+AXQOBwFPajuUqqHn+8PzyQWYICubOp3I67d07df0/haMwJzHvhd/D6FOjERYfpuVX2yJtMbnmZNhZSaOOs2DAM8GCIJDTM1oQpUYKZQSgkQDKZDkjAGUSSArdYAQghUEzJ5Pvh8ag3ZIAzrVae2tL/Pt9HZTIK41rZWO23cTuG684YWlUwgsreleFVQ5diWncuJhT/snS14QIgJwGLN9ZEPdYTgsCq3SEqlTAmdnAqWnaNrn4AF03Ad6VpGOvkZboks9Lbi6B/y1/NPZtjOn1psPBmv/mOka6Ie7yoAvAjn5A7GttvSVbA20XA/Zu4tpk5tqUcXFQ2NjAwsYGuuQ0n3DtfrIbf1z8AykqTbO5j4M0zCFX5jsV7ySJmxx8+sxkiYeA2PnMh2eMAOQDRfplMAKQ/hjS6gEjAGmNnBnYHZ2YijaLziHofQLH27+7VMS3lYS5omIIrNEJqfhuw1Vceq6pb1TOxxVbv6sJR9ucC2jTuHExBCO2xnwQYDkt41inxAP/DgXu79F2Mn91oMtGwDmPrADQJZ/T09Nx8PlBtCzUEuQKsFmP8wuBo79od4K2sASa/QrUGs6u/IqcIGkREQgeOAjWfn7w+WsOklJScOTIEbUVzZs3h729vSAWpShTMOPyDGx/vF1Lfm773JjbaC4qeFUQRDcTaj4I6PKMlhoajACUWkRMYw8jAE2DO9PKagCaZQ6oVOnos+YyqhV0R5sK3ijoKcyVD2PAJTYSUu3Yg7ccMb1rFcBvbcsaI1qQtclpSozbfhs3gyOxa2gdeDnb6qSHxo2LTo6xSWaLAMtpmYae1Pnb0h14c0fbwYo9gNbzACvdnns0IfQxn9PS09CqRSvByBKaMPmirYcmAheXcKc45wM6rgEK1JKNm7Q4kvrmDV7264+UwEC1ya4d2sNt0iQcPXZMUAKQXPUde2osboff1oKqSp4qmNNgDjztPWmBkdkpYQRo3HMwAlDCCSWiaYwAFBFspoqDADsBaIYJceVFBDotvZDheQVfN6zvXx2u9qavp/fRqMUnn2L24Uec6FT0dcO2wTVha2UpyagR0jI8Phm5nXWvY0PjxkWS4DOjuAjc/gfIU0bzn8iD5bTIgIuhjlzp3NYTSAjnaiOn3Zr/CdQcKttTXSSf5+yfg8OJh7G25VoU9SoqBuL06khLAda2AkKuaHwo3BBovxJw8qLXJ0otT1ep8Pzbdkh+/Jjjget3g3ClSBHBCMArYVcw7vQ4kKYf2UfPUj3xQ9UfYK2Qzn6T0vAysz8gQOOegxGALH0JAowAZHlgKgQYAWgq5E2od/K/d7DxYmbXxmK5nXBkTH3J1GAJeBqOXqsuQZWeCZK7ow32j6gLbzdhrqqYKhw0blxMhRXTqyMCz88AG9oBpKB6+xVAyVY6LuRnGstpfnCUjJRr64ADYwFVKtckO1fNqa6iTSRjqhCGrLq5Cn/f+lstupBLIWz6ehOcbaRRf1YIf3mRGR0CLGsAVBsANBgPKKQuA1QxAAAgAElEQVT50o4XXyUuJP7iRQR/N1jd4ZcMK+98yLPEHycfPeSdACRX4Tfc34C51+ZCma7kIGNnaYdfa/+KVoXF/Xsk8fAw84xEIDYlFv7X/VE4rDCsLawFvdJupKmc5YwA5BNNemUxApDe2NFuOSMAaY+gnvanKlWo/ucxRCZk/pgb17w4hjcupqckYaa/jk5E6wXn8D4+s1i0wgJY378G6hYz/XUR0pSkaG4n2FjxU+eJkSXC5JHZSn3/DFjZBEiM/ACBBdD0F6DuGNEgYTktGtTCKlKmAYcnAZeXaevxKAZ02wp4yvs0HGleMOX8FI7/dXzqYFHjRSANDMx6pKd/+dRnYhRr9CGRBIk9cQIhI0bCxs8PfqtXIc3NjfcagAmpCfjl/C849OKQlte+zr6Y13AeSriXkAgizAw5IBASG4IRJ0bgadRTlLcuj04OndCiRQsqyjQwAlAOGWi8D4wANB5DJsEwBBgBaBhu1K4ib2ivv4zCnpuvsP/2a0TEp+DMj43g52H6roUpaSp0WX4BN15GcfD9sUUJfN/I9D8074VGo8uyi6jk54YlPSrD2c74KyyMLKH2qyRNw3cPBW5t5tpW9wcNCSjSYDktEtBCqiGdorf3BZ6f1tZSrDnQYSVATgDKfLyMeYkBhwcgLCEsw9MuJbpgQvUJ5k0AvnsM7Bmm6ebrxUgdGr4GsSdPwr58eVh5ePDeBZh8T0adHKUmYrKPej711J2xXW3l/7ygIQ/kYuPNtzfVOZf1mnlju8aY0WYGIwDlEmQz8IMRgGYQZIm6yAhAiQZGDLPIacCbwVHqZiBSGL/suYt1F4I4pjQtlRvLe1WFghwDNOF4FZWIdosD8DY2WW1FqXwuWNuvGvK46F7v71PmM7LEhEGVo+rUJGD/aODWFo13Jb7WdGZV8HNiVRfIWE7rgpKE57x9AGzpBkQ+1zayziigyS9mdaUzMDwQ/f7rhwhVBIaXH47BlQZLOHgimHZnB7BvFJASB3iVBAadAGyk10hMBCSoVcHnM/p08GlMPDsRsamxWngMrTAUQyoMYZ2xqc0UaRq+P3A/pgRMQWq2shSOFo7Y03YP8rhKvxM9OwEozdwS2yrT/rIV21umT0oIMAJQStEwY1vIicRRW29yEPBzd8C+4XXh6mD8STtjoI1OSEXHpefx5G0cR0zf2gUxtY1xTRb43Igb4yNbKyMEyNW88wuA29uB/v8BtuLWK2M5TXEuPfoP2DkISMn2Y97SFmizEKjQhWLnDDOd5POOQzvwMPUhJn8zmYrTJYZ5msOqtGTg8E/AlRXcieW7AO2WybYJjCBYCiA05tBh2BQuBLvixXOUzsczWpWuwtJbS+F/y19Ln7O1s/rUXwPfBjnawiYwBHRFgOTckptLsOy2dlmK3Irc6OXYC11adqHiGc0IQF2jLu95jACUd3yl7B0jAKUcHTOx7VFYLL5dHIDE1Myi0bZWCuwaVhtlvE17bSQ5TYneqy7j0nNuN7vqhdzVnZPtrI0rbs7HRtxM0oS5qS8CpBunlY2+q4yez3LaaAjFF0BI43PzgOO/AcjSfYlY4pQX6LoZyF9FfLskoJHlM4DIIM2V8NDr2hHJUxbod9AsroRLIB0/aULUjh14/fMUWHp6oODGjbApUOCLphqb09HJ0epTf2dfndXSU9StKOY3mg8/Fz+pwsXsohCBpLQkTA6YjMMvDmtZXytvLTRJbAI7CzvWBITC2JqzyYwANOfom9Z3RgCaFn+z1x6blIq2iwIQGB7PwWJ2x/LoVNXXpPioVOkYte0m9t0K5dhBmoDsHFKbl5OJxm7ETQoQU84Q+AQCLKcpS4vURGDPcODuDm3DvSsDXTcBLt6UOaW/uXEpcXCycdJaaPb5/PgwsOs7IIlbm1cNVKWeQKs5gLW9/oCzFbwg8H7tWrydMTNDlrW3Nwps2gjrfPk+K9+YnH4U8QijT45GSFyIlvyWBVtiau2pcLA2fU1pXsBlQiSBQHhiOEaeGIk74Xe07OlRqge+L/M9Thw7of6sefPm7ASgJKLGjNAFAUYA6oISmyMEAowAFAJVJlMnBEhDkqEbr+PQvcwC62Rht+q+mN6+vE4yhJw0/eADLDsTyFHh5WyL3cNqI38ufja4xmzEhfSdyaYAgeRY0a/36oIKy2ldUJLInOhXwNbuwGtu+QW1deU6A20WmAW5czXsqrqg/LS607SuLZptPpMu0Cf/BM7N1U5WKzvg6780BCAbJkMgPTUVQX37IfHaNe4+ZfRoeA75fK1KQ3P6QOABTD0/FUnKJI4+SwtL/FDlB/Qq3QsWFuwnrckSQoaKCeE8/MRwhMVzfyeQnCPNmLqW7Mp7UxsxYGRXgMVAWfo62NNS+jGSq4WMAJRrZLP5dS0oEuRabRlvF8ls0JafeYZpBx9yLC3n44rtQ2oZfbXW2LCuDXiOqfvuc8Q42lhi2+BaKOvD37VkQzfixvrH1lOOQHIcsKo54FcTaDkTsDRtncysaLKcpiS3gq8A23oAcW+yGWwBNJ0KkIYfZvBj/ta7W/juyHdISEuAlYUVZtafieYFm2dgYpb5HPsG2DkAeKF9xRPuRYDO64G8ZSlJdHmbqYyNRVCfPki+/0DtqMfgwfAaPeqL+zx9c5o0W5h7dS42PtioBaa7nTvmNJiDanmryRto5p3oCJwKPoX/nfkfEtMSObqdrJ3UOVfHp4763/XNZ9Ed+YRCRgBKIQqmt4ERgKaPgblawAhAM4l856UXcPlFBIp4OaJtRR90rJIf3m6mu7ZzMfA9eqy8BKUqs96Um4O1uumHrzs/p+sMDe2hu2EYuukaSFmsj8NKYYHVfauhfnEvQ8V+ch2NGxdeAWDC9EdApQK29QQeHdCsLVQf6LQOcJBGN2+W0/qHVPQVNzdrOrkqU7iqbV2ADquA4pkEmOi2iajwZcxLdN3fldPBVGGhwKrmq1A1b1Vqf1waBeGLc8CO/p8ghgGUbgu0WQTYuRilgi3mF4G0iAgE9ewFt/bt4DFwYI7C9XlGk+uX406Pw7U33FOGREl5z/L4q+FfyOuYN0edbAJDQB8E/nn0D/64+AfSs9Wk9XHyweImi1HErUiGOH3yWR8bhJzLCEAh0aVHNiMA6YmV3CxlBKDcIvoJf15FJaLODE19jI9jWa8qaFHGNJu2NzFJ+HrBOYTHJWfYQw6arOlbDQ1L5DZpRK4FRaD7iktITlNx7BCqJiGNGxeTBogpB47/Dpydw0Wi+FdA922SQIfltCTC8GkjyLXOY78AFxZpf+5eGOi2FfAqIWEH+DVNqVJi6oWp+PfpvxmCm/g1wewGs2Gt0JyqNZt8Ji8Wzs/XNIJJ5/79g8IKaP4nUGOwWZwK5TfLxJGmSkqCws5OJ2W65vTNtzcx9tRYvE18qyW3U/FO6iuYNpbiN5rSyUk2iWoESO71P9wf5PTpx1EpdyX83ehvkFOnWYeu+SwlQBgBKKVomM4WRgCaDntz18wIQDPIgKWnn2HGf5lXbV3srHBlclPYWhnXwdYQ6FKVKnRfcRFXXkRylo9qUgxjmhU3RCRvawLfxaGD/3lEJmRuOIjwMU2LY1TTYrzpoX3jIggQTKjuCNzZAez5Hkj7UIfJzg0YdALwyHwjrrsw/mfSuBnnHwUJSkyM0pzsenZc27jCjYBOawD7XBI0XFiTVOkqTLs0DdsebUNdn7rqDqZZSQ2zyeeHB4Gt3bTBdskPdFoL+LIrnsJm4pelk3p/Ftb8lHrIKadJfebtj7dj+uXpSFOlcQyzUdhgcs3JaFesnSnhYLrNAIH9gfvV3abJ+KbwN+oGM58inHPKZylCxQhAKUZFfJsYASg+5kyjBgFGAJpBJmy4GIRlp58hJFJTR6NrNV/M6GCaJhu/77+PVeeec1BvUNxLffpPoTDdo/BdbDLa+wcgOIJba6RLVYJVOcHqJtK4cTGDr4z0XXx1DdjSHUgIB3ruAgo3kIzNLKclE4pMQ8KfAFu6Au+fahtXcxjQ7HfA0kqChotj0kfCo02RNrAjDS6yDLPJZ1LzghDE93Zlel+kCdB+BeDoIU4gmJZPIkDq/AUPHQqn+g3g+d0go1H6Uk4npSXhz0t/ck7FflRIrvr+3fBvlPEsY7QNTABDQBcEFt9cDEI6Dyw38LP7cBqf0YwA1CX68p9jul+98seWefhlBBgBaCYZQn7gXH8ZiT03Q9GmgjeqFhS/XtiB26/x/ebrHMR93Oyxf0Rd5HI07TWSp29j0WvVZbyOzuxu17CEF1b0rgprS4VgWULjxkUwMJhg/RCICQWCLwNlvtVvncCzWU4LDLC+4p8c0xA7ydHcleSKa+t5QOVe+ko0q/lmlc+ks/jyRhqiuNFPQL2xgEK4v39mlUgGOpsWGYnggYOQdO+eWkKeKT/DvXt3A6Vpln0up0PjQjH65Gg8iNA0FMk6auSrgVn1Z2ldvzTKELaYIcADAjQ+oxkByEPgZSCCEYAyCCKlLjACkNLA0WY2IdjaLgpAfIoyw3QbSwV2DK2F8vndJOHO6+hE9FtzBQ/DYlHWxwXbvqsFR1thT8XQuHGRRLCYEZJFgOW0REJDTnSRWn9Hp2jXdHP0Arps1HSRNpMRnRwN0j3SUqFf6Quzy+c394H4t0DhhmaSGdJ1U5WSghcdOiD5Cffkrvfs2XD9prXBhn8qp8+Hnsf4M+MRlRylJbdf2X4YWWkkrEgtSDYYAjwisPvJbsSkxKBPmT4GS6XxGc0IQIPDLauFjACUVTipcoYRgFSFi05j45PT0HZxAJ6+jeM4ML19OXSr7icpp2KSUvHr3vsY37IEcjvrVlDbGAdo3LgY4y9bK38EWE5LIMapScD+McCtzdrG5C0PdN0MuPlKwFBxTIhIikD/Q/1Rwr0E/qz7p15Ehuzy+e0DIDESKFBbHPCZFqMQiFi3Dm+mz8iQYenpCb9VK2FXwvBmPVlzulmzZtj8bDMW3lgIUg8z63CwcsDvdX5H84Lm0RXcqECxxXohQHLt7+t/Y83dNbCABeY1mgfSgMmQQeMzmhGAhkRafmsYASi/mNLiESMAaYkUpXaSq8cjttzA/tuvOR50rJIfpLOuBWn/a8aDxo2LGYdLfNevrdWcxMlVUHzdBmpkOW0gcHwtiw0DtvYAXl3VllimHdB2CWDjwJc2ycshJ/8GHhmIhxGaRljNCjTDzHozYW2pW0MFWeXzra0aYtjGERh8BnDxlnz8mIHAu8WLEb5wEay886HA6tWwKWjc34OPOZ2cnoxzTudw8tVJLZgLuhRUd1wt4iaN5lIsD+SDQEJqgrq5x4ngExlO2VvZY91X61DKo5TejtL4jGYEoN5hluUC8/4FLMuQUuMUIwCpCRWdhq4JeI5f993nGF8qnwt2D6sNO2v9rmLRicCXraZx4yLHOEjSp/t7gH96Aw4eQOcNQME6kjQzu1Esp00YJtIchpB/sdwXLmqLGk8G6o0DzOilC3kB1fdQX1x/y60926VEF3UnU12GLPKZnAg9NB4gLxQ+Dr9aQJ99gI5EqC5YsTnCIEDyOGL1ari0bAlrb+NJW5LTm/7bhM3xm/FO9U7L6Ea+jdQnZZ1tnIVxiEk1WwTC4sMw8sTIT9aZHFV5lLrZh76Dxmc0IwD1jbI85zMCUJ5xpcErRgDSECUDbFSp0tWrTNlZ9+qLCHRdfhFpH2wh9jjbWambfhTwcDTAK36WBDwNB/lvXPMSJsWHeEPjxoWfKDApX0Tg9S1gVQsg7UNXanXDhrlA5d6SB47ltIlCdHs7sHc4kJbZyEhtiY0T0H45UPJrExlmWrUBrwIw6uQoJCuT1YZ4O3pj7Vdrkc8pn06GUZ/PEc81LxLCbmv722IaUOt7nXBgk+SDwMEnBzHl/BQkQ/Od+DjIVcwRlUZgQLkBUFiw5i/yibg0PLkXfg8jTozAu0Qu6WxlYaV+IdOheAeDDKXxGc0IQINCLbtFjACUXUipcYgRgNSESj9DTz16iwk776BNRW+0reiN0vlcRL1u+y42Ga0XnsWbGO4Gc2XvqmhaOo9+zvA4+35oDDovu4A4UpewojdmdSwPWyvTnUSkcePCYziYqM8hsLED8PQY99MW04FawySPGctpkUOkUgInfgfOzdNW7FYA6LYFyFNGZKOkpe7y68sYfmI4nK2d1eSfr4vu9Q+pzueHB4DdQ7U7QJPwVOkLfDUTsBa+1q20skGa1sRfvAS7kiVg6SZcUzRyknDdvXX469pfWiC42rqqr8bX8aHjpLk0o8is+hwCR4OOYtLZSUhScl9Qudi4YF7Deaier7rB4NH4jGYEoMHhltVCRgDKKpxUOcMIQKrCpbuxY7bdxO4brzIWfFPBGwu7VdJdgBEz05Qq9Fx1CRcDIzhSvm9UBD+2KGmEZOOWhkYlot2SAA4pWbOwO1b1qSZ4t9/PWU7jxsW4KLDVOiGQFAPsHAg8OayZXqkX0GYhFdc3WU7rFGF+JpE82TUIeHxIW17BekCndYCjBz+6KJdy8+1NuNi6oLBrYb08oTKflanA8d+A8wu0fbV2AFrPAyp01QsHNlk4BGIOHcKrH/8Hu1Kl4Ld6NSyd+L8hQZouzL4yGxsfbNRypKR7STUJk9+Z/CRggyHAHwKEdF51dxXmX5+vJbSASwEsarwIBV35qWlJFDRv3hz29vb8OSCQJEYACgQsZWIZAUhZwGRkLiMAZRTMj64kpihR5Y+jSEhRZng3pXVp9K9bSBRvp//3AMtOB3J01SnqgfX9a8BSYZrHXXRiKjotPY/Hb7idiL8ul09NjJrqqjSVPy5FySKmBORk17FfgJBrQO89gJUNFaCwnBYpTBGBwOauQPgjbYXVBgJfzWD13XgIBXX5HPMa2NEPeHlB23uPYkCXDUBu/Qvt8wAlE/EJBKJ27sTrn6cAKk0HXocaNeC7fBkUtra84UWuv5PTV0eCjmjJbFmgJX6r+xvsrNhJUN4AZ4LUCKQoU/DrhV+x99leLUSq5a2mJp3JyVNjB3XPaACMADQ26vJYb5pfxPLAjnlhHAKMADQOP0muPv7gDQasy+wASTi3i5OaILez8Bu8Q3fDMGTjNQ4u+Vzt1HX/PJz429DqA3xymhJ9Vl/WOpFYrWAubBhQw6TNSGjcuOiDPZvLAwJpyYCVab47hljPctoQ1PRcE/4UWPs1EBfGXaiwAlrNBqr211Mg/dOVKiXeJ71HbofcvDpDVT4HntKcHI7XbuyAsh2Ab+YDtqyxA68JYoQwVUICnn3dGmmvuU178kyaBPfevYyQnLk0JiUGo06MwtU32l3BW9i1wG/f/AYHB/PpCs4LqExIjghEJkVi9MnRWg2YyML2xdpjco3JOndiz0kZVc/oD84wAjCnqJrH54wANI84S9FLRgBKMSo82PQwLAZ7boZi781QFPZyVBNdQo/n4fFos/AcYpPTMlRZW1pg2+BaqOyXS2j1n5RPmqGM3nYTe2+Fcj4v4uWInUNrw83BtKeqaNy4mCSQTCk1CLCcFjhU759pyL/snX4p6xbNJ0rkeuMv53/B+VfnsaLFCr2v+X7JFirymZweO/sXcGoakK45SZYxSAOhr6YD5FSoGXWA5jO/hJSVHPgcQT17QhmhKZmSq3s35Jk8GRYK45twkI6rQ48NxdOopxwXrBRW+NbuW1S0qUjNlUkhY8Bk84tAYFQgvj/+PULiQjiCSZOZsVXHonfp3rzWJFc/o//7T/18a/7VV+wKML/hZNIERIARgAKCy0R/EQFGAMo8QQgBFpWYCndHYYmuhJQ0tFt8Ho/exHIQ/a1tGfSuZVx9D2NCNOO/h1h6+hlHhJezLXYNrQ1fd9O/9abix6UxAWBrc0YgOVZWp3JYTucccoNnkGu/awj5x32hgdxlNM0+chUwWDStC0mNqT8v/Yltj7apXXC3c8eK5itQPFdxXlySfD6TUgFbugJPtK93wtUP6LwW8KnCCxZMiDAIJN2/j6A+fZGrWzd4jRnNCznyJPKJmvx7k/CGY7SjtSNm1p6JqFtR6n+npWaaMMgzqUIgcDbkrLrpEnkx83HYW9ljRr0ZaOzXmHeVCdHRuNt/AJSOjqiw1J+KE63sBCDvaUClQEYAUhk2WRjNCEBZhNG0TpAfYD/8c4vTdIRY9G1Fb8zrUpGXzawhHq6/8AJT9tzjLHWwscQ/g2uhrI/xdUcMsSn7Gsn/uOTDSSbj8wjEhwMrGgPluwANJwI8nPowNdwspwWKQMRzYG1rIIZ7qgLelYBe/wL2wnUPFcgjXsRuuL8Bs67M4sjKbZ8bB9of4KWuGRX5fPx34OwcLp7FWgDtlgIO7rzgzIQIi0BqWBis8+blRcmVsCvqa7+xqdwXsp72nvBv6o8C9gVw5IiGMGYEIC+QMyHZENh4fyNmXpmp/ldSloE0+yjlwX/tUVViIoK+/x5J5zU1T1169oT3T5NM9rtD10RgBKCuSMl7HiMA5R1fKXvHCEApR4cS2zZcDMLP/97lWFsijzN2f18bDjZWJvHiyD1NLUJVeqZ60oBkVZ+qaFiC3xpRxjhIxY9LYxxkaz+PQFoKsL4t8PK8Zk6pNpof7Db8d4AUMwwspwVAOzJIc+03OpgrPF8FTYMYe9OUWBDAU71FRidHY9ixYbgdflu91srCCvMazUND34Z6y/rUAirymZwCJM+SF2cBCwXQ+GegzmhZvFDgJYhmJOTwi8OYeHYiUlWpHK8LuhTE0mZL4ePkAypy2oxiJkdXycGAPy7+gXvv72FB4wW812YlmCnj4hA8ZAgSr3LrjnuNGgnPoUMlDSsjACUdHtGMYwSgaFAzRdkQYAQgSwmjELjxMhKdl11AqjKTaXOytcLe4XVQ2MvJKNmGLr7+MhLdV1xEUiq3FtKsDuXRuZqvoWIFWcc24oLAKn2h6enAvpHA9fVcWyv3BtoslL79X7CQ5TTP4Yt6qSH/yP9mHXnLAb33shNeAOJS4tQ1p26+u4lZ9WehRcEWvAWBmnyOfQNs6gi0mAYUqseb/0yQ8QiokpLwatw45OrSBU71hIsNOXVFTsOmI8ubTwAVvSpiYeOFcLPTnBKmJqeNh55JMCEChIROU6WBXP/le6RFRiL4u8FIunOHI9rCwQG+/v5wrFGdb5W8ymMEIK9wUiuMEYDUho56wxkBSH0ITefA+7hktF54Dq+jkzhGLO1ZGV+VzWcSw0gjkg7+5xERn8LRP6pJMYxpxk9NKD4dYxtxPtGkSBYhAC+vAA5NANKVGsNdfIBBJwHnPBQ5om0qy2kewxcdAqxpBUQFcYXmKQf0YeRfVlASUhNw4+0N1PGpw2MAJEaW5FQvlDxXWKMPXuNvrDBySilk6DAkXLkCCzs7+K1cAYeqVY0Vy1lPaq3NuzYPa++t1ZLb2LcxZtafybkOz57RvMJvtsJexb3Cw/cP0aRAE1ExSHv3Di/7D0DykyccvUp7O+Rftgxu1aVN/hGjGQEoaspIVhkjACUbGtkbxghAGYV4/rEnqFHYHdULukOhEPaxolSlo8/qyzj3NJyD4OD6hTGxFf91PnQJE7Gp5fwzePwmjjO9U5X8mNWxvCRrgrCNuC6RlfGcZyeA7X0BZSrQ/xBArnRSPlhO8xTA6FfA2lZA5AuuQNLwo88+wNGDJ0VMzJcQkEw+39gEHJ6kiX2+8ixoFCBAyL+Xffsh6W5miRSFoyP81q2DfdkyvHiQqkzF5IDJOPj8oJa8LiW6YGL1ibBUWHI+k0xO84IAE2IKBG6+vYlRJ0chJiUGK5qtQNW8/JLan/MpNTQUL/v1R0oQ96VYmpMTQgYOQMM+fVgXYFMkBNNpEALC/lI3yCS2yEwQYASgTAL95E0sms07o/Ymn6sd2lTwxsgmxeBoK0wNvr+OPMLCE0856NUo5I5NA2vAylJhMlQvBb7HoPVXEZOUprahfnEvdd0/axPaRMWPS5NFjClG+FOAdHct3lwWYLAflzyEMSZUc+2X5EXWkbv0B/LPkwcl9IkIiglCARdxOx2bPJ9TE4GD44AbGzUBy1UIGHwasJNGIyv6skg8i9NVKoROmICYvfsylCpcXOC3fBnsK1Y02hBy9X30qdG49PqSlqyRlUZiYLmBn3zxafKcNtpzJsCUCBwIPIApAVOQotLctHG1dcXmVpvh5+InqFkpL14gqH9/pIW+5uixzJMHT3v1RKqXFzVNbdgJQEFThRrhjACkJlSyM5QRgDIJaXZCLrezLS5MbALS+ILvcfzBGwxYd5X7u9TZFvtH1kVuZzu+1ekt7+nbWPRZfQVuDtbYNrgWSE1CqQ62EZdqZJhdhiLActpQ5D6siw3TkH/vuS9Y4FUS6LMfcPIyUgGdy/97/p+6ucHYqmPRq3Qv0ZwwaT6/fwb80wd4w61zhZKtgS4b2XVf0bLAcEXpaWkIGTUaccePw9LDA36rVsKuZEnDBX5Y+Tbhrbr5zaPIRxxZpAnOL7V/wbdFv/2sDpPmtNGeMwGmQoA09vC/5a/+L/to4tcEfzf6WzDTkh4/xssBA6B8x711ZO3ri9xL/XHywylbWrpaMwJQsFShSjD/v9Cpcp8Za0IEGAFoQvD5Uk3+KDeYfQovIxIyRA6oWwg/ty7Nl4oMOS/fJ6D1wrMZJ+zIB1YKC2z9riaqFnTnXZ+hAt/GaOoS5nYxPSH5JR/YRtzQCLN1UkWA5bQRkSGNHNTkH7e2ETyLA30PAE7S6WBuhJd6Lz0edBxjT4+F8kO9zFGVR6lPN4kxTJbP9/cCe74HkmO03aw2CPhqOmBpLQYETIeRCKiSkxH2y1R4DP4OtoUKGSkNCIwKxJBjQ/A6nnsSijRbmNtwLur61P2iDpPltNGeMwGmQiApLUl96u+/F/9pmVDHuw5mN5gNZxtnQcxLvHMXwQMHQhkdzZFvU7QI/FatRpqLM44cOaL+jBGAgoSACRUIAUYACgQsE5sjAowAzBEi6U9ISVNh5blA7L0ZiioqqFgAACAASURBVIdhsWqDSRfe8vk1Hd/4GkmpSrRfch73X3N/kBCikRCObOiPANuI648ZlSsuLgXKtjcLAofltIEZGvcWWNsaCOee6IFHUQ3555zXQMF0L3sZ8xJt97RVd5PMOpY1W4ba3rUFd070fE5LAY79Alxcou2btSPQZgFQrqPgfjMF0kSANLoZfny4uvZa1uFu544lTZegjEfOtQVFz2lpQsms0hGB8MRwdb2/2+9ua63oWqIrxlcfDyuFMDdtEq5eRfDgIVDFx3N025UuDd9VK2GVKxeVXa3ZCUAdk0/m0xgBKPMAS9g9RgBKODiGmPYwLAYnH77DkAaFeW16QU4Z/m/HbWy/FsIx6+vy+bCoWyVedenqd1h0EvK6SvuEX06+sI14TgjJ4PMrK4EDYwFXX6DbFiBvORk49XkXWE4bEN64d8C61sC7h9zF7kU05J+LabqqG+CJIEtW312t7nL6cfQo1QPjq40X5e+OqPlMuj5v7weEXNbG0asU0Hk94CW9bvaCBJ0yoUmPHsO2SGFYWAlDhBA4yEnY8WfHI1mZzEGH1MX0b+oPX2dfnVATNad1sohNkioCjyMfqwnn7KdNFRYK9TO4e6nugpkedy4AIcOHIz1Jc6Pn47CvVAm+y5fB0llz4pDGfGYEoGBpQ5VgRgBSFS5ZGcsIQFmFUzhntl5+iQm7uHWIing5Ys/wuiapsRfwNBz91l7BhK9Koj/Fpw9p3LgIl2UylBx4GtjQDvhwdRHWDkD75UCpb2TorMYlltN6hjY+HFj3DfD2Pnehe+EP5J+3ngLlOX3Tg02YcXkGOhbviCk1p4hC/omaz0+PATsHAYkR2gEs3xVoPRewcZRncCn3Ku7sWYSMGAmXli2R788/YKHgvxHa1odbMe3SNKQjnYNWOc9yWNRkEcgJQF0He0bripR5zzsTcgY/nv4RCWmZ5YUIIo7WjpjTYE6OV82NQS/22DG8GvMD0lNTOWIcatWE7+LFUDg4ZPw7jfnMCEBjskM+axkBKJ9Y0uYJIwBpi5gJ7L0TEo0OS8+DXDX+OBxsLNXXjIvmFqbmx5fcJKccO/lfQGyy5krYwLqFMKlVKSgEaHgiNNw0blyExkQ28tPTgWX1gbBs12barwTKd5KNm9kdYTmtR2jj3wPr2wBv7nIX5SoI9D0IuProIUz+U0m302p5q4GcPhFrCJ7PKiVwehZweiaQjdyBpS3QahZQuQ9r+CFWwPXUE3P4CF6NGwd8ICpy9eqFPJMm8kZQk9sXC24swMo7K7Usa5C/AWbVnwUH8mJJjyF4TuthC5sqPQRIzpEXLrOvzoYqPXPfTyz1cfLBwsYLUSxXMcEMj963D6ETJgJKJUeHU+PG8Jk3FwpbW86/05jPjAAULH2oEswIQKrCJStjGQEoq3Dy70xUQgq+XnAOr6ISOcIXda+E1uXFP5nyOjoR7RafR9iHJh8fjZrTqQI6ViHpTNegceNCF8ImtpZc7dzWEwi+qDGk3ligyRQTGyWsepbTOuKbEKEh/8KydXh1K6A5+eem23U+HbWxaQYiIGg+k9OfOwcAgae0rSN5QK78elc00HK2TGgE0iIi8LRpM6QncE9Iec+eDddvWhutPlWViqnnp2Lvs71asjoU64DJNScbVHtN0Jw22msmwJQIkJybcWkG/nn8j5YZFb0qqjv9eth7CGZi5LZ/EDZ1KkBeoGYZLq1awXvmDFhYazc+ojGfGQEoWApRJZgRgFSFS1bGMgJQVuHk1xmVKh39113BqUfvOIL71ymEKd/w32E4J+tjklLVJ/8evdE0Ovk4WpbNi0XdK8OSnQDMCUL2uSkQSEsG9o8BEqOALhsBAa6HmcKtz+mkcTMuOn5q8q+t9ulQVz+gHyH//EQ3SQoKg2KC4GXvpfeJJiFtFzSfb28Hdn2im3GJr4FvlwD2/DbyEhInc5Ude/Kk+vov0jQ3Ely++Qbe0/78JFGhD0bxqfEYe2osAkIDtJYNqzAMQyoMMfiUoaA5rY+TbK7kEAh4FaDuMJ19fF34a/xa+1fYklPJAo33a9bi7UxyEpo73Dp1RN6pU2FhaflJzTTmMyMABUoiysQyApCygMnIXEYAUhzMt7FJcLO3gY2VMNeh5h97gnnHHnMQqlogF7Z8VxPWlsLo/Fw4yPXjPqsv40Lgey17Ng6sATvrT28MpB5eGjcuUsdUkvaRt9nKFMBKuM2zVPxmOZ1DJBIjgfXfAq9vcieSJjF99wPk+q8ZDkL+9T3UV93IYHGTxXC2Eb+8xKdgFzyf9wwHbmzQqLawBJpOBWqPYFd+KfoORB84gNBxP8KtS2fknTLF6BqApOvqsGPD8CDiAQcFSwtL/FzzZ3Qo3sEodATPaaOsY4tNjcCC6wuw4s6KDDO+r/g9BpcfbDDhnJM/5Mpx+OIlCF+0SGuqe5/eyD1hwhd105jPjADMKSvM43NGAJpHnKXoJSMApRgVHW0atP4qrryIQKty+dC2gjeqFXTnrQ7euSfh6LX6EucUvqeTDQ6MrIc8LuJ23iWbgzHbbuLfm6EcZAp7OWLnkNrI5WijI2LSm0bjxkV6KDKLpIQAy+kvRIOcAiVNYUKvcye5+Giu/boXklIoRbPlVdwrNfkXFh+m1lnWoyyWNlsKV1tX0Wz4nCLB8zk1EVjZDEgIBzquBgrUNrnPzAD9EUi8dQt25csbTZK8iH6hPoFFvhNZh52lnbrxQgPfBvobl22F4DlttIVMgCkRIHX/xp0eB9IE5I86f+CrQl8JZg7Z37+dNRsRa9Zo6fAcNhSeI0bk+J2iMZ8ZAShYSlElmBGAVIVLVsYyApDScEYnpKLqn0eRqsyskzGvSwW0q2R8HTxy9bfF32fw5G1cBjrkeu3GATVQq4hwtT8+F4pZhx5iyalnnI89nWyxe1ht+LrrV/xaauGmceMiNQwlY09yHGDrJBlzTGUIy+nPIJ8UoyH/Xl3lTnD21lz7JV1/zXCQH4A9DvbAnXBuLURS42xq7akmR0SUfI58AVg7Ak5eJveXGWA6BG69u4Xhx4cjKjmKY0Qu21zqTr/lvcrzYpwoOc2LpUyIqRBITEsEIaNLeZQSzIR0lQphv/6GqG3btHTkHjcWHgM/UR7hE9bQmM+MABQsragSzAhAqsIlK2MZAUhpOLdefokJuzJ/MJFrwFcnN4WLnXaBXH1dPHwvDIM3XOMsm9iyJAY3KKKvKKPnb7gYhJ//5XbIJB2It35XE+Xz018ficaNi9FBlaOAyCBgVTOg7g9AjcFmfX2P5fQnEjw5FtjQHgi5nI38y6c5+ech/rNVSl/Dp5FPMfDIQLxP0pR4KO1RGiubr5TENWCj85lc/7++DnDKC5QQ7iSNlOIpN1vSU1PxZvoMuPfuBZuCwlzRPxV8Cj+e/hFJyiQOfPmd8qtPwxZwKcAbrEbnNG+WMEGmQoCc8guMCkTRXEVNYkJ6WhpCJ01CzN59Wvrz/jIFubp109kuGvOZEYA6h1fWExkBKOvwSto5RgBKOjyfN27q3ntYe/5FxoSvyuTF0l5VjPaGnMb4dnEAboVEZ8gqkccZ/42qx9v1Yl2NPHr/DQZvuApVlmZg5CTiyt5V0ahkbl3FSHoejRsXSQNqCuPIyb9VzYG39zTaq/QFWs4GrOi9mm4MjCyns6FHyL+NHTM7QX/82CmPhvzzLGYM3LJZS06bEBLQxdYFq5uvhpudNF7wGJXPKfHAgbHArS2AnSsw+IzZ1nikNVFVSUl4NWo04k6fhpV3PhTctAnW+fLx6s6Oxzvw+8XfQUiZrIMQ4aQepqe9J6/6jMppXi1hwkyBQEJqAn4695O6wcyGlhtQwr2EqGaoUlIQOnYsYo8e4+pVKJBv2p9w+/ZbveyhMZ8ZAahXiGU7mRGAsg2t5B1jBKDkQ/R5A4MjErD3Vij23HyFMU2Lo2U54zelAU/D0WPlJY7S+V0rom1FH1GRuhkcha7LLyAplbshntG+HLpWl0+HTBo3LqImgtSVqVTAtp7AowNcS+uNA5r8LHXrBbGP5XQWWAk5vKkj8PICF2vH3Bryz6u4IDGgVWhIbAjsrezhYS9+qYnPYWZwPoc/Abb1At5laeSQryIw4IhZNAOiNQez2q2Mi0PI0GFIuHIl45/JCcACmzbCysP4HCUvXP1v+av/yz7qeNfB3IZzBemIbXBOyyGoZu7Dm/g3GHFiREaDmbyOebG51WZ4OYhTfkCVmIiQ4SMQH5Ctu7W1NXzmzIFLi+Z6R4jGfGYEoN5hluUCRgDKMqxUOMUIQCrClLORZCNpYWH8o6T7ios4/yyz066fuwNOjG0AKxG7/r4Ij0cH//N4H5/CcXxk46L4obm4bypzRt64GTRuXIzzWGarCQF4eiZwekamY54lgIFHNSd+zHCwnP4QdHL6a1MnICjbDx1HL6DPfiB3STPMDvpcNiif7+4E9o4EUjLr6GZ43mkdUEa/Ey70oSYPi5WxsXjZtx+S7n043U0aNdvbw2/FcjhUrWqUk2mqNPWpv11PdmnJaVOkjbr+pbXC+JIunzLSoJw2ylu2WAoI3H9/HyOOj8DbxLcccyp6VcT6lut5+Q3xJT8JoR48ZAgSr3JLDFnY2iL/ooVwqlfPIJhozGdGABoUatktMv5Xu+wgYQ6JhAAjAEUCmgY1N15Got2S8xxT/2xXFj1q8Fd7Rhccdl0PwdjttzgdiDtUzo85nYzvsKeLfjHn0LhxERMfanTd3QX8OwywtgMGnTDbhg4kXiynAaQkAJs7Ay/OclPYwRPosw/IU5qa1ObTUFJY/nn0c3WNP1qGXvmclgwcmQxcXq7tno0z0HYhUKYdLa4zOwGkRUYiqFcvpDx9BoWzM3yXLYND5UpGYUOuYJIuq2dfZXs+ABhUbhBGVMq586kxBuiV08YoYmslg8Dxl8cx8exEkGdw1uFs46w+aVozX01BbSXfo+BB3yHpLremt8LBAfmX+sOxenWD9dOYz4wANDjcslrICEBZhZMqZxgBSFW4hDV20PqrIHX3Po7czrY4879GsLO2FFbxJ6QfuhuGUVtvIDlNhXrFPLG6bzVYi3gKUSyHady4iIUNdXpCb2iIn4J1qDOdT4PNPqdTE4HNXYDnp7ORfx4fyL8yfMJNjaxkZbL69MnNdzexsPFC1MhXgwrbdc7nqJfAP32A0OvafuUuA3ReD3iapuA+FUBL2MjUN2/xauRI5J36C+xKGdcVNSIpAt8f+x5332cjQiwUmFR9ErqU7CI4EjrntOCWMAVCI0BuB62+uxrzr89HOrIU1Abg5+yn7i5dyLWQoGakvXuHl/0HIPnJE44ehaur+jStfXnjulvTmM+MABQ05agRzghAakIlO0MZASi7kBrm0KOwWLT4+wxn8aRWJfFdfdN1p7wWFIF5R5/Av2dlOPPQ3dgwZIRdRePGRVhEmHTaETDrnCbk35ZuQOBJbhjtc2nIv7zlaA+vQfanKlMx5tQYnA7RkKI2ChvMazQP9fPXN0iemIt0yufHR4Bdg4CkKG3TKvYEWs0GbBzENJvp4hkBPsqsBMcEY8ixIXgZ+5Jjna2lLWbWn4kmfk14tvrT4nTKaVEsYUqERIA8d3+7+Bv+ffqvlpqqeapiXsN5gjdbSg0NRVC/fkgN4ua8pYcH/Favgl0J48v60JjPjAAUMvPpkc0IQHpiJTdLGQEot4ga6M+YbTex+8arjNWu9tYImNAYTrZWBkpky3RBgMaNiy5+sTnmi4DZ5nRqErC1G/DsBDf4pJstIf/yGXfKgeaMWnt3Lf669hfHBdLZ9GD7g+qmH1IeX8xnZRpwahpwluub2h8rO6DVHKByLym7x2z7gEDa+/e8NPb4HKD3wu9h2PFhICcAsw5XW1csarwIFXNXFC0WZvuMFg1h0yuKTIpUv3S59oZbb49Y1q5oO/xc82dYWwpTY/Kj9ykvXiCof3+khb7mAGKVNy/81qyGbSF+Th7SmM+MADT9d0QKFjACUApRME8bGAFIUdzvhERjxdlAtK3ojXrFvGBjpeDFetJNuOGcU1CqMq8HjGxSDD80Yx0qeQH4C0Jo3LgIjYlk5aenA+cXAlX6AnYukjXT1IaZZU6T2m9bewBPj2Yj/1yB3nsBb/F+3Js6/p/ST06iTDg7AUeCjqg/drJ2wsrmK1HGU/rXoT+bz7FvgJ0DtOs8EgfdC2uu/JrpiU8p5uCXbEq4dg3BQ4bCa/QouPfowbv5Z0POYuzpsVr117wdveHfzB+FXQvzrvNLAs3yGS0qwqZVFhgdiOHHhyM4NphjiAUsMKbKGPQt01fwhh9Jjx+rr/0qw8M5Nlj7+cFv9WrY5PfhDSQa85kRgLyFn2pBjACkOnxUG88IQIrC9+u+e1gT8EJtsZuDNfrXKQRC1Bk7Jv97BxsvZh7Pd7CxRMD4xsjlaGOs6BzX778dCk8nW9Qs7JHjXDlOoHHjIsc46OTTqZma0z5eJYFuW8y60Qf7cZkFAUL+besFPDnMhcWWkH//Aj6VdUovuU8iXU+nBEzBsZfHsLzZclFPPBmD7Sef0aTD86JqQEzmqfkMHaXaAG0XmW0XcGOwNsXauLPnEDJiBNKTktTq882YDrdv+evSTK5fTj0/Fcp0Jce9ErlKYEnTJcjtkFt0t9m+Q3TIRVN48fVF/HDqB8SmxHJ0kpPW0+tNF+WaeeKduwgeOBDK6GiODTZFi6jJP+vc/OY8jfnMCEDRvhKSVsQIQEmHR9bGMQKQkvCS03k1ph1HeFxyhsV8nNJ7G5OEurNOIiVNlSF3QN1C+Lm18F0azz8LR5/Vl0HeSv7VuQK+qeBNSTT4M5PGjQt/3lMk6d6/wPY+mQaTmm6dNwCF6lHkhDimmlVOp6UA//QGHv+Xjfxz+UD+VREHdEq0qNJV6i7ARdxMV1tWX6g+m89n5wLHf80Up7ACmv8B1BgCWLBtvb44m2J+SnAwAlt9jfTU1CxxVMBvzRo41jC8KykRRmoGrrizAgtvLNRyjTTA+bvh33CycTKF26xTu0lQF17p48jH6LyvsxbZTEhmcs28lIdxDWx08SDh6lUEDx4CVXw8Z7pd6dLwXbUSVrly6SJGrzk07jkYAahXiGU7me0UZBtayTvGCEDJh0hj4Lkn4ei56hLH2uNjG6CIl3EbyOkHH2DZmcAMudaWFjj7v8bI62onKDKk6UjHpecRm5SWoYc0HRlUr7DgVxMEdUxP4TRuXPR0kf7phORZWAWIzlLE2kIB9NgBFBWnaDtNIJpNTitTge19gYf7ueGxcdaQf/mr0hQ2ZutnEPhsPqtUmpqPjw8BLj5Ap7WAr3GkEQuC+AiE+/vj3fwFGYqdGjeGz7y5UNjaGmyMUqXEtEvT8M/jf7RkfF34a/xe+3fB6699yXizeUYbHEE6FxLSmTT92PF4R4YDpT1Kq7uui3HSNO5cAEKGD884TfvRCPvKleG7bCksnZ0FAZbGfGYEoCCpQJ1QRgBSFzLZGMwIQEpCGRmfgn23Q7HnZiiuBUWinI8r9o2oa5T10QmpqD3jOOJTMq+mdKvui+nthS1WHxadhHZLAvA6WnPl5uPoW7sgfvmmNCMAjYoqWywIApFBwJauwNv7GvFfzQRqDhFEFe1CadyM6405If929AMe7OMuJSd6eu4C/GroLVIuC869Ooc63nVk8xz/Yj4nRABHfwaa/gY4mmcZC9rzlpAmb2fPQcTq1XBp3Rre06fBwtrw5giJaYkYf2Y8TgZn6wQOoF/ZfhhdeTQU5AWSCYdZPKNNiK8pVaeqUjH06FBcCruEZgWa4c+6f4rSaCn22DG8GvMD9zQtAMfatZB/0SIoHITrgk5jPjMC0JTfEunoZgSgdGJhbpYwApDCiJOmHeQqcCU/447SLzj+BHOPPs5AQGEBnBjbEAU9HQVDJTYpFZ2WXsDDMG59khZl8mBJjyqwJEaY0aBx42JG4eG6mhwL7PoOcPQCvpnPrvl9JhFkn9OE/CPNH+7v4SJg7Qj03AkUqGW2X5GVd1Zi/vX56FS8EybXnGxyooOPQCS+D8aRc9fVopo3bw57e2l3LebDZ3OTQUjAmAMH4dKqJSwUhpNzUUlRGH5iOG69u8WBkJQ5GV99PHqU4r/BiCGxkv0z2hBQZLQmOjkapPZkr9K9RHkGR+/bh9AJEwElt84lH6dpdQkLjfnMCEBdIiv/Oeb1i1f+8aTJQ0YA0hQtHm1NSElDnRknEJmQWfuG1OBb2K0Sj1q4okidwf5rr+DcU25XsMp+btg8qCbsrC0F0y1VwTRuXKSKpSh2kWt/pJi7peEnRESx04RKZJ3TyjRg10Dg3u5PkH87gAK1TYi8aVVvvL8RM6/MzDCiTZE2+LX2r7AitfFoHKTr99k5SA9YiJOF/odYe19GANIYR5FsfhX3CkOODsGLGE2jto/DRmGjbr7QvGBzkSzJWY2sn9E5uy+LGcnKZNhaGn5NnS8QIrf9g7CpU0nRS45Il6+/hveM6UadptXVRhrzmRGAukZX3vMYASjv+ErZO0YASjk6Atq26txz/L7/w3XGD3oOjqyH0t4ugmglb9jH/nMLu25wuyYW8nTEzqG14S5Cx2FBHDNSKI0bFyNdZstljoBsc5qQf7sHA3cz6yupQ2ntAPTYDhQ0riQDzWkRHBuMNrvbIC09s6Yr8WdZs2Wo7U0hKUpifXAccG2NOiyJ1u44U3wK6rfuyk4AUpio6Uol3q9ejVzdusHSybi6yZ9y/8H7Bxh2fBjCE7kvN51tnLGg0QJUzSuteqCyfUZTmJuGmHzo+SHMuToHa1qsga+LryEieFnzfvUavJ01S0uWW6eOyDt1KiwsxXmpT2M+MwKQlxSkXggjAKkPIbUOMAKQ2tAZbnhymhINZp1CWExmDb7GJXNjdd9qhgvNYeWcw4+w6ORTzixPJxvsGloHfh7C1QYRzCGeBNO4ceHJdemKSY4DbPn/kShdh/m1TJY5rVICu4cAd7IV9beyB3r8AxSqzy+IFEo7HnQc486MQ5pKQwKOrzYePUv3pM+TlHhgR39Nc48sI9rOFzbfn4W9s3GlN+gDhG6LSYff0PETEHPwIByqVYPviuVQ2PHX5OxC6AWMOTUG8ancrqd5HPJgadOlKJqrqOQAlOUzWnIo828QeZG+9PZSLLm5RC28kGshbGy1ES42wry4/5wHxI7wxUsQvmiR1hT3Pn2Qe8J4UWvA0pjPjADk//tBo0RGANIYNXnYzAhAecRRLy+2XXmJ8TvvcNbsHFoLVQq46yVH18mbL73EpN1cffbWltj6XU1U8HXTVYws59G4cZFlID469eYesK4N8NUMoHwnWbsqlHOyy2lC/v07DLi9lQuZlR3QfRtQuKFQUFIn90zIGYw5OQZDKw7FwHIDqbMfce+ALV2AV9c4tqfDAnd9uqNoz7/YCUCKoqpKSsKrUaMRd/p0htVODRog/8IFsLCxMdqTfc/2YUrAFK2Tr0XdisK/qT/yOuY1WocQAmT3jBYCJInJJFd+Sa4dfH6QY1mtfLWwuOliWCvEKUuibpozazYi1mhOR2cdnsOGwXPEcFHJP6KfxnxmBKDEvmAmMocRgCYCnqkFIwAlngRnn7xDZb9ccLTlp46SUpWOpnNP43l45tvq6oXc8c9gYQrXH3/wBoPWX4UqS3kQ0udjZZ+qaFwyj8TRF948GjcuwqNiIg3x4cCKRkDUS40B9cYCjSYDRhSFN5EnJlUrq5wmNR/3DgdubuJiSmovddsCFG1iUqylqJxcB/Z1Nt21NIMxef8M2NgBiHzOEZFuaYsrvoPwOld1VgPQYHBNszAlOBgvunaD8v37DANIh98CG9bDvmJFg40iJMiae2sw79o8LRnV8lbD343+Fv1Ulj7OyOoZrY/jlM59n/geo06O0mouQ9zpXLwzJtSYIAoBmK5SIezX3xC1bZsWkrl/HAePAQNMgjCN+cwIQJOkiuSUMgJQciExG4MYASjhUL+JSULN6cdhZ2WJZqXzoG1FbzQo7gUrS8O71O2/HYrhm29wvF7Xv7paLt/jVnAUui6/iMRUbmewae3KoXsNP77VUSmPxo0LlUDnZHRaCrC+DfDyAndmy1lAjcE5rWafZ0FANjlNyL99I4AbGz9B/m0GijZlcZcLAiFXgc2dgYRMokjtmp0bkjusw6H70er/y7oA0xfwpIcPEdS7D1QxMbCwt0f+RQvhVKeOwY4oVUrMujILmx9u1pLRomALTKs7DTaWxp8uNNhAHRbK5hmtg6+0T3kS+QQjTowAaTKTdSgsFPhftf+he8nuopy4S09LQ+jESYjZt08L0ry/TFHX1zTVoDGfGQFoqmyRll5GAEorHuZkDSMAJRztlWcD8ceBBxkWOtla4erkpgZ3yyVvrVstOIcHr2MyZJbxdsH+EXV530C8jU1Cq/lnER6XwkF4eKOiGNeihIRRF9c0Gjcu4iIkkjZlKnBoAnBlZabC/NWBPvsAa/7qRYnkjUnVyCKnCfm3fzRwfR0XS/LDvutmoFgzk2JsSuXX31yHt5O3ZK836o3Nw4Oamn9pidylrn5Azx1IdPLDkSNH1J8xAlBvdCWxIOHGDbwaPQY+8+bCoXJlg20i1zAnnp2Io0FHtWT0LNUTP1b7EYSYkfqQxTNa6iDzYN/ZkLP48cyPWvUlHa0dMav+LNTPL07tWVVKCl798APijh3neqVQwHv6NLi2bcuDt4aLoDGfGQFoeLzltJIRgHKKJl2+MAJQwvFqs+gcbodoTh6Q0aFyfvzVuYLBFp989Bb91lzhrF/SozJalctnsMzPLSRk45wjj7D45LOMKe0r++CvThV4Jxt5N15EgTRuXESER3xVl1cA/40HnPMBg04Azuyaur5BoD6n09OBAz8AV1dn+7FjDXTZCJT4Sl9IZDP/xtsbGHx0MNzt3LGqxSr4OPnQ7duVVZpuv+kqrh95y2s6OzvnpbK+FN1BEcZ6XNxfxgAAIABJREFUVXIyFLa2BguPTo7GyBMjcf3tdS0Z46qOQ58yfQyWLfZC6p/RYgNmAn2bHmxSnzRVZXs2eTt6Y2GThSieq7goVqkSExEyfATiAwK4+qyt4fPXHLg0by6KHV9SQmM+MwLQ5GkjCQMYASiJMJilEYwAlGjYk1KVGLzhGs49DQep20fG+v7VUd+Iq7qdlp7HlReRGR4X9nLE0TENYEmK8gk0Nl4MwpQ9d1G7iKe6y7CNlfTfjgsExSfF0rhxERMfk+gKPA3YuwH5DCfbTWK3RJRSndOE/COEUNaToARXUmC983qgZCuJoCy+GffC72HgkYGIS41TKyddTgkJWMClgPjGGKuRxPnE78DZv7QlFWmsibWts/ozqvPZWJwoWp+eksJLY49Pufw67jWGHhuKZ9GZLzTJPCuFlfrKb8tCLSlCiuW0lINFuqjPuDwD2x5p19kr71Ue8xvNh6e9pyguKOPiEDxkCBKvcpsiWdjaaq7S16snih05KaHxGc0IwJyiah6fC/fr2zzwY14ajgAjAA3HTpSV4XHJOHjnNU49eoflvaoYXP/v8vMIdF7GrW82q2N5dK4qfLH2c0/CUcHXFc524nQpEyUwPCmhcePCk+tMjEwRoDanCSn03/+Ay8u5kVFYAZ3WAaVayzRiObtFTnT3OdQH5ARg1kEK0P9c6+ecBUhphjJN09jl1hZtqyr2AL6ZD1hm/q2iNp+lhLnAtiTdv4/g4cPhPWMGHKtX51Xb48jHavLvbcJbjlwnayd1s48a+Wrwqk8MYSynxUBZfx0xKTH48fSPOB96Xmtxy4It8Vud32BHus+LMNIiIxE86Dsk3b3L0aZwcED+pf68f8+McYnGfGYEoDERl89aRgDKJ5a0ecIIQNoiZqC9fddcVpOIH4e3qx1O/diIncgzEE++ltG4ceHLdyZHnghQmdOE/Ds0Ebjkzw2KhSXQaS1Quo08g6WHV6QT5XdHvwMhRMhomL8h5jacC+ssZJke4kw3lcT636HaBGD9/wGNJgEW3C05lflsOnRF15xw/TqCBw+BKjYWCkdH+K1dC/tyZXmx4/Lry+ruqx9PvX4Umts+N5Y0XYIS7nTWM2Y5zUt68CokIikC/Q71Q2B0oJbcYRWGYUiFIaKVz0l79w4v+w9A8pMnXPLP1RV+K5bDvnx5Xn03VhiN+cwIQGOjLo/1jACURxxp9IIRgDRGTU+b776KRuuF5zirfvmmNPrVKaSnpM9PT0xRwt7Gkjd55iKIxo0L9bEhDT8uLAZqDGENPgQIJnU5TQihI5OBC4u0yb+Oq4Ey3wqAEp0iSR00UgPQxcZFXYfK1tLwmmomRYB0/SZdfwNPAqRpw9dzgar9PmkSdflsUmDFVU46/L7o1h3piZkNXCxdXVFgy2bYFi5slDGHnh/CpHOTkKpK5cgp7FoYS5suRT4n/msnG2WwHotZTusBlkhTSa2/safG4tjLYxkabRQ2+KPuH6JeMU999QpB/fsjNeglx3NLDw/4rV4FuxLSI71pzGdGAIr0xZK4GkYASjdApLjNSABfAyB3JZMBkCIg/wBYDCDBCNMdAJBq4qSdYFUARQE4ASAtWskr9sMAlgIIM0JHTksZAZgTQjL4/PvN13Hg9usMT9wdbRAwvjFvhN3eW6GYfvCBusZfqXwuMkBMPBdo3LiIh45Amg6M1dR486mq6ejKGn3wCjRVOU3Iv6NTgPMLspF/CqDDSqBsB16xkYOw2JRYde0zeyt7ut1JigE2dQLqjvliYxeq8pnuiOhtfXpaGl6NGYPYo5mkiUP16si/ZAksnRz1lvdxwfp76zH76myt9ZVyV8LCxgvhautqsGwpLGQ5LYUoaNuQkJqAfof74f77++pGSwsaL0AFL/FqEae8eIGgfv2R9jrz9wKx0ipfPjX5Z1uIv0MDfEaAxnxmBCCfGUCvLEYASjN23wDYCOBzjAYh6Qgx+NQA88n5adJSiRB+XxqEDBz0gXA0QE2OSxgBmCNEdE8IfBeHJnNPg/zO/TjGNS+O4Y2L8eLYxcD36L3qMlKUKjjbWmFpryqoU1ScAsW8OGBiITRuXEwMmXHqSZdf0uTh43DxAbptYQ0/jEOVs5qanCYPxWNTgYC/ud6TE2HtVwDlOvKIChMlSQRIDmS78pvdTmryWZIAC2+UKiUFIUOGIv78eTg1agSfeXOhsDOsTho5hfXX1b+w/v56LcOb+jXF9HrTRavBJiRyLKeFRNc42aTW5JTzUzCl5hR4O3kbJ0yP1UmPHuPlgAFQhodzVln7+aHAmtWw9pFux3ca85kRgHokp4ynMgJQesGt9IGgI6+4Scu76QBOAiD/v+sHUo5YTUhAcnovVk8X6gI4+2ENIQL3A7gK4D0ALwDtAQwEQO5UKgEQMvI/PXXoMp0RgLqgJOIcUmzdIocfJPqYM37HbWy7GpyxxMnWCgETGsPV3viGHI/fxKKj/3nEJKVlyLe2tMCBkfVQPI+mgyIbX0aAxo0LtTFNjALmVwCSojJdIAW1+x4E8leh1i2pGU5FTn+2C6wF0G4ZUKGL1GAVzR5S6480+2haoKloOgVT9GAfkK8i4GZ4sysq8lkwAOkQrEpIwPu1a+E5aBAsrA3b26QoUzD53GT890J7q921RFdMqD4Blgp5lDlhOU1HXotlZeKduwgeOBDK6GiOSttiReG7ahWsc+cWyxSD9NCYz4wANCjUslvECEDphfQ0gPoACLNB/pfbPhX4EcCsD2b/CmCqni7UBjAKAFl7/zNr2wLYDYDkB7l2TI5sZTnHpafGT09nBCAvMPInZNLuOwiLTkLbit5oVjoPHGysDBYeGpWIBrNPIlWZmTZDGxbB+K9KGizz48I3MUlotzgAodFJHFm9axXAr23K8EpiGm2shAXQuHGRMJw5m/bmPrClCxD1ob5Nh1XspFfOqOk1g4qcPvEncObjn/CP7lkA3/oDFbvp5a+cJkclRaH/kf54GvkUU2pNQcfiFJ+CJHU+D/8EeJUA+h8C7HMZFCoq8tkgz9iijwiQa+2k2ceVsCtaoIyuPBr9y/aX1Z6G5bTpcv9dwjtMuzQNP9X8CZ72pr8tk3D1qqaJTnw8BxS7MmXgu3IFrHIZ9twUE2Ea85kRgGJmiHR1MQJQWrGpDuDSB5OWARjyCfMUAEhv9FIAyHES8nqEWymYH592APhYhIgcUbnOj9gMKYwA5BlQY8QlpSpR7c9jiP1wos7e2hKLuldCk1J5DBL76757WBPwImOtrZUC58Y3hpezcYXbY5NS0XnZRTx4TW6oZw5CWC7tWQWWCvZI0zVgNG5cdPVNsvPiw4F/egN+tYAmP0vWTFoNk3xOn5oBnCKH+rMOC6DtYqBSD1phN9rumJQYDDoySF1/6uMgp556lKIME5UKOPITcHFJJiYF6gC9dgNW+v/tk3w+Gx156QsgNyNiDx2Cc4sWsFCQ7Td/4038Gww9PhRPIrkdT60srPBbnd/wTRFyAUdeg+W0aeL5MOIhhh8fjjcJb1DOsxxWt1ht0ivlcWfPIWTECKQncV/k21epAt+l/rB0puMmD435zAhA03wHpaaV/VqWVkSmAZj4waSaWcjA7FZO+HA1mPx7CwBHBHDjewAfWxN2BrCdZx2MAOQZUGPEHbobhiEbr2WIIDeBz09ojHyu+hdbfx+XjLozTyIxldwg1wxyOu+3tmWNMREpaSr0X3sF555y64RU8nPD5oE1eWssYpSRFC2mceNCEbyfN5V0AVVYATz/mJQFNkY6IemcPj0bOPmHtodtFgGVexnpOd3Ltzzcoj6ZknXkd8qPnW12wsGa9CyjYKQmAbsHA/f/5S3Gks5nCkJirInpSiXCfvsdUdu2IVePHsgz+SfeTuM9i3qGIceGICye22vPwcoB8xrOQ20fcllHfoPltPgxPfnyJMafHY/EtMyO1S0KtsCs+rOgIHVnRR4xR48i9IexSE/lnl1xrF0b+RcthMKBkmc+ABrzmRGAIie8RNUxAlBagTkDoB4Ach7a7cM14E9ZWAvA+Q8f/AbgFwHc+AHAXx/kkpOAu3jWwQhAngE1RtzwzdexP0u33hqF3LFtMEkz/cdfRx5h4YnM/jTkVN6pcQ3h6274H3XyFn7s9lvYdf0Vx6BCno7YObQ2SHdhNvRDgMaNi34estnmhoBkc/rMHODE79rh+GY+UKWvuYVJy1/yfF90cxGW316u/iyvY16s/WotfJykW/yd40RCBLC1B/Dy47Ysy6dNftF0+zWgvq5k89kMMpaQE6ETJyFmPymTrRkeQwYj9+jRRnt/7c01jDgxAuT6b9bhYecB/6b+KOVBLvjIc7CcFi+u5Lm67t46zL02F+nZqjiRFyz/Z+86oKI6uvAH7NKLIIpKs5fYe8cCqIkx0Vhjx96T2KLGRGMSS+wdK7ao0Wisv733XtFgQ5oiIkovW/jPLMryWGDb233v7c6c85+cn52598537z5nv3fn3q1fbDX6VeDEAwcU3yvIlAkCBBFHf/+cJjrWwjrLCzGeKQFovO8gnzVRApBf3nkLgBRmuAegThGmkcIICR8/J5l5JEOP7bEfwFcfhX4G4DHLCigByDKg+ohLyZTieGgs9t99pciw++3rGujd2EdrkeSKbvO5pxnNOb6p54lFPYoKZ/VqFh0Pw7I8pKLiMO5gjb2jmsG3uIN6AXSGCgJCPLhQN1IEikKAlzF9cXFOx9/8o+MioOFg6tA8CBACcOd/OxHSIQS+zr7CwIbU9NzWDYgPY9pLsnzJ1e7apHebboOX8azbVgS3Kv3ePbzs0xeQKhuNkazt8vv3waYSKYut2zgRcQJTzk9BljyLIaCsc1kF+eflRI7GpjtoTBvHtxKZBH9c+wN7nu5RUVivZD0sabMErrbGrbH3fuffiP31V4A0wsoznL/8EmXmzNa5iY5xEC1YixDjmRKAXEYMf3RTApA/vrAl2cQfzTkM4Es1ppEOwYT5uApAt1StwhXUBkDug5K2Yw8A1NIBJnWnmFIAFFWPnzx5Ai8vddN1sIDlJRkZGTh/niRpAn5+frC1JS4zvRGfkgU7sSUcbLRvArL+UgQWniR9Y3IGecAcHNUYFUroTtLtuhWDGYeYP65sRZbYPLAeank6m54DjLQjc4lnI8HJVCNJBzKTAEfdamhyYrMJKOVbTIuurYL4LEnSZ46swDmQ1QsyAcTZ30JiZiJcbFzYF2wAiRZvHsLmnz6wSHnDkJ5t7YisLhshL0v6uOk++BbPuu9EmCtTjx3DW5KtRAgLkQgl5s6Bg7+/zpvZ9XQXFt5ZqJKNVaN4DSxqsQjFbMjFH9MeNKYN798USQomX5qMm3E3VZR1LNsRU+tPhbWVcTPtErdsxfvFi1XscfymC4pPmwYLK2F2uRZiPBMCsHLlyp98QdrURxs+KqkGviFACUD+eKQEgLiP5vwNQN1rY3LiJA1ASEOQmixug1SqvgigwUeZJAvwoA7yNe4avH79eri7c9+RSoc90iV5EMiSAbPuWCFZonys1HKTY3AVuc44hb63wPr/LCFXUIk5wwLZGFJFjhpuGoeYzvrpQoqALghUij2Aym8O4olHJzwv2QFyS+MetnWxma5hF4HycUdRM2a7itD7Xv0QXiKQXWVUmtERKJH0EI3Cl0EkZxaxTxe74mr5CUiy1z6D3uiboArVIuB8/TpKHjyEV/36Ik35o1nturwT5NlynMg4gQuZF1TWVRVVRQ+HHrC2oP9GaAUqnVwgAinyFGxO3YzXstcqnwfaBsLPxo+1OpYauSA7G8VPnkTxk6dUpie0bIH4jh11Ko+gkW46qUAE4uPjMWTIkE+fUQLQTOOEEoD8cTz5EkZ+NGcr6ZugxjQyl6wh6VYVWdzGOgCfngybAehaoEhjdoYSgCx6j0NRF2MtsDuc+RZvfE0pfB11MyoyBVgeaoUsOfMx1aO8DM09NA4v3ZTTVRQBHRGwkXxAwKPJucRAmrg47vgORbwTqaRAhzkgUD7uGGrG/KWy1QeeffCiJOnbZZ6DECFXs66ioXVDiC3EggXB+91F1IncAEsw61gl2XriaoUJSLemLzQF69wCDLdKToZMx66k0mwp/k37F/ckpLIPczSwboBOdp1gZSHM7CdT8rEp7CVBlqAg/97J3zG2I4YY3ey7obp1deNuMzsb7ocPw+0CySlhjncB/ngXEEDJP+N6RKGNEoAcgM5DlZQA5I9T+JABSDoQf2rFR67ntvnYkEQXlNTd6aVXgHVBladrpHI5Oiy/ipgPymyIpuVdsbFfXZ0tnvxvKA7eZ16tGt7CF9/7V9BZJl2oRECIVxeE4D/xkfEQ3VdmfmXDApkDjyPbg81EbSEgYXwb+RDTVrc2wPrkTyqbl7SZCWmjEcYHhScaSUH6ubfm4t8X/6KRRyPMbz4fdiLtu8xzup3sbIiuLoP4/BwVM2TeTZD1zSbAlr1rnHyIZ07xFrjyVEkqplyegmtvrqnsZHj14Rj02SDjZmPxAE8a04ZxwrMPzzDu/DjEZ8QzFLjZuGFRy0X4zM24LyBJB+13c+YgZY9q/0jXH76HS391OS6GwYltqUKMZ3oFmO0oEKY8SgDyx29c1wAcDiD4Ixz/fexGzPyXhF2saBMQdvHkVNq/d6Lxw9/MN9zbhzZGswq6Z0JIZHJM2/sAu2/llKfoUpc0E6ltdgdmQzlWiMWLDYUFa3LlcuDQ98DtLcCnrnt1+gKdV7KmggoqHAHOY/r6OuB/E1UNDJwFNP/ObF1HyL95N+bhr8fKrEhSiH5VwCo4iHWvD2t0QG+sBw5PUFVbvQvQZQ0gIhVU2BucxzN7W+GtJFlSEuLmL0DJiRNg5cJe7cm3aW8x+tRoPE5g9s8j2X4zms5Al0pdeIuJIQ2jMc0+urff3MaY02NUukqTLuprA9fCx9m45QiypdKcDtoH81WPsrBAqRm/wLWXugpX7GNkKIlCjGfaBMRQ0SAsuZQA5Je/uOoC/C2AbQAsAUQAaGGEoqCUAOQ49qIS0nDuyVt0rFkarg6615+Ry7PRfsl5PI0jfWlyRh3vYvh3VDO9yTryw3HJyae4GZGAkIGNYC0iIUoHGwgI8eDCxr6NIuP1PeDYT0DMbWDcbcCJJDzTYWgEOI3pmxuBQz+objFgJtCigL8bGgweyX+V8gpdD3QFKU7/aYgsRYofpw1LNeSRpWpMyUwBNn0BkO/3p9F0DBD4G0iHWLYHp/HM9mZ4KE+emYmoIUORduMGbCpVhPfatRCXLq23peGJ4Rh5ciRiUmIYskjG68JWC9HSq6XeOoQqgMY0u54jZ+SBRwfidtxthuDKrpURHBCMEvbkcpnxhjwrCzHjxyMlf80/KytFp1+Xr0hZedMZQoxnSgCaTvzpsxNKAOqDHvtrSYtZcjJIBUDukUgLUUG6/l7++BlpMThDD1PI05j0iSctX0nVWKJf2cZVD8FqllIC0HDYaiR56cmnWHzyCUSWFmhVuQR6NfJB4Gfady09HhqLYVtJ02jlWNe/gU6yCjOcZAOKrdj/gaURUCY6SYgHF0G5gnSOTHgBFKdX1o3lN85i+tYm4GABGX5tfwb8CsgINBYgPNIT+i4Uw08MB+nyS7KgCBHi76t7R1XOtpb8BtgQAHyIAtrPBpqOMpgpnMWzwXbEH8HZcjlixk9A8tGjuUaJPDzgs34dbCpV0tnQu3F3FdlYJM7zDjdbN6z0X4ka7jV0lm0KC2lMs+/Fd+nvMODoAEQkkfwNgGRXL/dfDmdrZ/aVFSFRnp6O6DFjkXrpEnOWWAzPRQvhHGh6za+EGM+UADTq14K3yigByC/XkPp7pA4fGU0AqBYOyflsCoBPRWhIRfHjOm6DnL4PAyD3VkjV2FYAQnWUpe0ySgBqixiL88lbQ/9F5/DiLeGac8aApr749WvtDqdETudVl3Ev6kOunCoeTjjyXUtYWtLHC4suY12UEA8urINABZoUApzE9O2twIExqji2+QloNdmk8NV3M2EJYYrMqIkNJuKL8l/oK4679fFPgbjHwGeGzWbhJJ65Q9WomiWvXuFlz16QviUXb3KGqEQJlN25A2JPT51sORN5BpPOT0KmLJOx3tvJW5GNZeyrmDptwsCLaEwbBmCSbdr/f/3xWfHPML/VfNiKSFUp4w1ZcjKiRoxE+i1mMoCFrS28li+HY0tyscz0hhDjmRKApheHuuyI/kLXBTXDrWmUh/RbA6CgiuEkDeohgGoACOtSEoBEB5OafSQOSQGeJABtATCf3DoI1WIJJQC1AIvtqQ9jEvHlcmZnrj0jm6G+r6tWqi49i0ef9UyeeknPOuhcV7cDtFbK6WS9EBDiwUWvDdPFJo+A0WP67nZgH8kAy9eVvNUUoM2nd3kmD7tWG0yTpMFebK/VGk4mkwxeC26PyEaPZ06A5k5pVnQMooYORVZ4OCwdHOC7bStsq5GjtfZjV9gu/HHtD5BO13lH9eLVFZl/xe2Kay/UBFfQmDacUwkJ6GHvAVJewZhD+v694ip9Rigzf4R8p7yDV8O+oYDKPGgJnBDjmRKAWjrZRKdze7oxUVD13Nana8Dk+q8fgCv55E0C8OfHv/0KYGa+z1sDOPPxb5sBDCzAnjof55BrxiQFjGQR5svZ1nMX6pdTAlA9Rgab8V9sEpaffoaTj94gUyqHl6sdLkxuo3XNvj7rr+LSM5I8mjO83exwZkJriLS8rkvqEa46+xwT21VGcUd2C6kbDESBCxbiwUXgkFPzDYyAUWP63k7gX/KOLh/55zcJINl/HJNHBobatMWHHQGurwV67QDExs2kyQusUePZtD1a6O4IeRHz3fdwHzkCDk1JdR3tBrkFseLuCqy9v1ZlYQvPFoqr7oIgvLXbts6zaUzrDB2kcqmCYLa20r1mt+7aC14piYtD1ODByHz6jDHB0sVFcZ3ermZNtlXySp4Q45kSgLwKIc6MoQQgZ9AXqrjuRzLODgCpmE2uBRNCj/x/0jpp2MeVTwA0AJCcT5I6ApAUpCL1A0nmIBmkOvlJNTDEASD/Y3NQApBNNHWUlZwhwfHQN4rVXesTl2g+7kZ9QOeVTN7498410LeJr+ZCPs4csvkGTj6Og4udGJPaV8G3jXxgRa8Qa42jNguEeHDRZn9Gm0s6v3o1BMqQ9yp0cImA0WL6/i5gL/mnOB/513ICQOr+mTH5dyT8iOKqI8l8EuQgzVxIp1+SyVXtK6D7ZoM0+NAEG6PFsybGmPAcQuJZ6PCdlcglmHVlFvY926eCTpeKXfBz058hthSbMHLab43GtPaYkRUZ0gxMPj8ZlhaWWNBqgdGz/AqyWhITg4hBgyCJiGR8bOXuDp8NG2BbpbJumxXQKiHGMyUABRRgBjSVEoAGBFcP0Z0+duUtrIIrIf86AmC+cslRqI4AJBmBIVraVlCmoZYiVKZTAlBfBDleP2zLTRx/lEMeklHCyUaRRWgrttLKMpKFOGTLTcaaHztUxcjWtHmCVkBqOVmIBxctt2j46XH/Aaub5ZAFdXrnkD/O+neRNLzhpqnBKDH94B9g79Acn+cdzb8HSMdfHYgEU/HGsZfHFD9SHUQOWBWwCnVKCogUJ1d+T/8OXFjAdEfjkUCHOZz41SjxbCrBZ+R9kKvsE85NwMUYZikVYsbwWsMxus5onUhFI2/D6OpoTGsPeXJWMsaeHotbb3KqNHWt1BUzms7gNL4yw8MROWgwpK9J70jlEJUuDZ+NG2BTrpz2GxXgCiHGMyUABRhoBjCZEoAGAJUlkSSNirQVJEQfIcuyPhJ+uwGsAJBWiB5KALLkgPxihPigNxAUePImGe0Wk9vqyjHti6oY5qcdaZchkSFw8TlEJaTnCnJ3tMapCa0V2YB0GA4BGs8sYLutG/DshFKQfXHg+4eAtQBqnLGwfb6JMHhMP9wL7BmsSv41GwsE/sYJScQXH5yNOosfzvwAaTapXgLYiewUtc8alhJA/SdpFnBwHHBvhyqctXsDX68ALLV7scWGXwwez2wYKQAZJFOJ1PtzaEzKbOs/SNfV0adGg3S2zjtIdtb0JtPRvXJ3/ZWYqAQa09o5Nj49HiNOjEDY+zDGQkIyj6lbQPMp7cTrNDsj7AkiBw+GLD6esV7s6wPfjRt1bqKjkzEcLxJiPFMCkOOg4Yl6SgDyxBFmaAbNABSw03/4+y7+vROTuwNC1l2a0haONtoVH1504gmWnXrKQGJh99paX0cWMJScmS7EgwtnYBWk+PlpYGsX5iek/lvb6bwy05yMMWhMh+4D/hkEZMuYkDYZDbT/w6zJP3KFkmSonIs+x8BmcI3B+L7+9/wOwYwkYFd/4MWn0sl5zPWbDLSZxplvDRrP/PYKa9aRGn8RvfsgKzoaZebOgUtH8k5d9xGZFIkRJ0cgKjmKIcTWyhZ/+v2JNj5tdBduBitpTGvu5KikKAw7MQzRKdGMRU5iJyz3X476HvU1F8bSzPQHDxA5ZCjkiYkMiTaVKsJ7wwaIS36qLsWSQp6LEWI8UwKQ50FlJPMoAWgkoKkaFQQoASjQoCANO1ovOAuZXFn/apx/JYwP1K7ex8v4VLRbch5ZUuVVuoZlXbFreFNOrzYI1C1amy3Eg4vWmzTkAkkGcHUlcGERkJUCOJYCxt4CbBwNqZXKLgIBg8X0owPAP0GAPCe7LXdweD2Ub4GQKcvE+LPjcT46JzO8Z5We+KnxT/x+lie9BrZ3B2IfMOG0sAQ6LgIaBHEKs8HimdNdGU+5PCMDkUGDkH7nTq7Skj/+iOJBBfXGU2/Xg7cPMOb0GCRkJDAmF7MphuVtlwvryrv67RpkBo1pzWANSwjD8BPD8S5D2WSPrHS3c0dwQDCquFXRTBCLs9Ju3EDUiJGQp5LekcphW706vNevg8jVlUVtwhAlxHimBKAwYsvQVlIC0NAIU/mFIUAJQA5iIzFNAhd7/a7WTt/3ANuuKov+2omtcHlCDlW4AAAgAElEQVRKW7g6aN6ZjGSMBG26gbNhb3NRIE0/Do9rgaqlCit9yQFgJqxSiAcXXroj+Q1w5nfAp2lOHUA6OEPAIDH9+BCwe4Aq+ddoGPD5n5xlh3EGchGKJTKJogago7Ujfm32q6JgPW/H2zBgW1cgkZnJBbE90C0EqNKBc9MNEs+c78p4BrwL2YS4efMYCkmmUtndu2Fpq113Z0JsTzw3EelSZbkSItjT0ROrA1ajnIt51DzT13s0ptUjeDP2piKjOkVC+kAqh7eTN9YErgH5r7FHyoWLiB47FtkZGQzVdvXrwzt4NaycnIxtEi/0CTGeKQHIi9Dh3AhKAHLuArM1gBKARnY96fjb6I9TqOnlgq/rlEHHmqVRzF5z0o6YG5ecgRbzzjCy9ga3KIefv/xMq90cC43F8K05BY0/DV3kaKWUTmYgIMSDC3UhRaAoBFiP6bAjwN/9ALmEqbbhEOCLBZT8K8AZUrkUFrCAFQc18zT+dkRcBnb0AjKY19hg7w702QV4Gv9qXUG2sx7PGgNkGhOzZTK8mT0H7//6S7EhkYcHyu7cAXFp7Ro17X26V9HtV5bv+n81t2qKZjckK4sOzRCgMV00TqcjT2PSuUnIkpOy78pRxbUKggODOYm1pOPHETNhIiBh/jvo0KwZvFYsh6W9+dY8FmI8UwJQs2eVqc+iBKCpe5i/+6MEoJF9s+dWNCbsvperlWTu3fo5APbWmtftm3PkMdace5ErQ2xlgQuT26KUi+Zv09OzZAhYdA4xH5Rv0ks62eDUhFZwstUvO9HIkApanRAPLoIGnBpvcARYjeknx4CdfVTJv/pBOddDLXmc3WZwpAWsIPRfYO9wQJbJ3IRbeaDvHoD8lyeD1XjmyZ6MbQa5bZCwYQPi166D77atsK2seakSsjb4fjBW3V2lYnbT0k2xuM1iOIgdjL0lQeujMV24+/59+i9mXpkJeb4O86TWH7li7mRt/Cy7xAMH8GrqNEDGrH3rGOAPz0WLYGmtXRKBoIO3AOOFGM+UADS1KNRtP5QA1A03ukp/BCgBqD+GWknot+EaLjxVdu3yr1oSGwZq3qGRXB9uPu80UjKVdbB6NfTG3K61tLJj/rH/sPLMc8aapb3q4Os6nlrJoZP1Q0CIBxf9dkxXmzoCrMX00xPAzt6AjJmFgXr9gS+XmjX59yHjA55+eCqM7r75A/7KKuDYNADK+rWKKZ4NgN5/Aw78yuRiLZ5N/Yuvwf5IMxBtapSRTNbfr/6OPU/3qEjvVL6T4oq72Iq+sNQAesYUGtMFI7bx4UYsvrVY5cM23m0wv9V82FjZaAu13vPf79yJ2F9nAdnM56Vzp04oM/sPWIhp/AsxnikBqPdXwyQEUALQJNwoyE1QAtCIbiNZd83mnsL7NGUKv7ak2/JTT7HwxJNcqy0tgFMTWqOcu+ZvwF+8TUH7JechkSkPFE3LF8f2oY35XSzeiL4yliohHlyMhU2hemQSgP7o49wNhRnASkw/OwnsIORfvgyxun2BTsvNmvwjmSmkNtWF6AsYWXskhtUaxu+rvnkDJTMFCG4BvA9nhk+VL4CuGwBr/l1jYyWeeftt5a9hpM7f5HOTcTb6rIqRQ2oOwbi64+h5RUf30ZhmAkeeqYT42xS6SQXRLhW74Jemv0BkqfktHR3dorLs3YaNiJs/X+XvxXr0QKmZM2BBM+AV2AgxnikByNa3RNhyKAEobP8J2XpKABrZe5lSmaLpxv67Mbj6IgEXf2yj8fXftCwpms89zSAQv6xVGit619N4F+Q6Tf+N1xlZiCJLCxz5riUqeRj/aoPGhpvoRCEeXDh1Rfh5YP8YIHAW8NnXtP4bp84oWLneMf38NLC9lyr5V6cP8NUKsyb/COKbHm7CwlsLc8FvXKox5vrN5aQulU7h9+45sCEQSPvYWbPB4JxGLlbG/4Gtif16x7MmSkxkTlZ0DMSlS8HCykqvHb3PeI8xp8bgfvx9hhxS13JKoynoXY02etIHYBrTTPTi0uLQ/WB3lc7Sg2oMwvf1vjc60UzO6fHLVyB+leq1d7egIJScPMnoNukTb4ZeK8R4pgSgoaNCGPIpASgMP5milZQA5NCrWVI5rEWa17DaeDEcsw49Ylj8v3Et8VkZzTv2/u/Ba4z66zZDxnC/8pj6RTUOkTBf1UI8uHDmLbkMWNsKiH2QY4JPM6DDbKBMXc5MoopVEdArpl+cBbb3BKTMLoeo1QvovArgc1MLIwTD0/dPFT9U8zZCcLN1wz+d/kEJ+xJGsIAlFdE3gc2dAL9JQIsfeE3k6xXPLMElBDFZkZF4+W1v2DdogDJ/zoOljW7XJaOTozHi5AhEJEUwtm1taY15fvMQ4BsgBDh4bSONaVX3PHr3CIOODUKqJFXx4cQGEzGg+gCj+5GQf3Fz5yFh82YV3e5jxsB99ChK/uVDRojxTAlAo3+1eKmQEoC8dItZGEUJQIG4mZCFreafwetE5Q/jNlVKICSokVY7WHH6KRadeAL5x9u/pZxtFY0/HGz4mX2h1eYEOFmIBxfOYL69FTgwhqm+40KAdIOlgzcI6BzTJLvzrx6AVNmYSLGpmj2ALsFmT/4RKMhVNXJNbdntZQoSkGRErQlcg6ZlmvLG/xobkvQacNauE6zGslmcqHM8s2gD30VJExLw8ttvIYmIVJhq16A+vFeuhJWLi1amExJm1MlReJfxMTv042pna2dFA4Z6HprfdtBKsZlNpjFdsMOvv76OMafH4KfGP+Hril8bPSpIx+zYmb/iw+7dKrpLTp6M4oOCjG6TEBQKMZ4pASiEyDK8jZQANDzGVEPBCFACUCCRsetGFCbvYV6H+WdEUzQo66b1DkJfJeLnfQ9xO/IDVvauh461+P8jTOtNCmSBEA8unEG7awDwaJ9SfYlqwIiLvL06yBlOHCvWKaZfXgT+6g5I0pjW1+gKdFlLfZzPp3fi7mDSuUnoUqkLRtcZzbHHC1FPrvq6lhU8catTPPPTIwaximQsRfTth/Rbtxjyi/XqidIzZ2qs82bsTYw+NRppUuYzoJRDKQQHBKNCsQoay6ITi0aAxnTh+CRkJIBkVRt7ZEskik6/SYcOMVVbWKDUjBlw7dXT2CYJRp8Q45kSgIIJL4MaSglAg8JLhReBACUABRAeMnk2AhadQ3h8ztUEMhqVc8Ou4bpnfcjl2Tj7JA5tqpSk1wk4jAEhHlw4g4t0wXu0HzjxM/AhEui7B6hIr4Nx5o9CFGsd0xGXgW3dgI9Xr3LFVu8CfLOekn+F4JyYmQhHsSM/G4CQOo5/9wdq9wK+mM/rK77qvj9ax7M6gSb4eerVq4geMxbylBTF7myqVoXvtq2wcnTUaLd34+5i2IlhII0/8o7KrpWxyn8VPBw8NJJDJ2mGgDnHNCH4XG1ceXXulWdlIeaH8Ug5dYrpQCsrlJkzGy5ffaWZY810lhDjmRKAZhqs+bZNCUAaB1whQAlArpDXQu/h+68xejuzbt+moIZoXaWkFlLoVD4iIMSDC+c4SjKAsMMAyQ6jg3cIaBXTkVeBrd+okn+kwQvpCku7PfPOv2oNursj56q+XJozNeBXoMX3apfxdYJW8czXTRjBroz//kPU0GGAWISyO3ZC7KHZ+SQ0PhRDjg9BiiSHPPw0GpVqhCVtlsDJmjYnY9t95hrTj989xsiTI/Ft1W8xvPZwtmHVSZ48LU1BnqdevsxYbyEWo8yihXAODNRJrjktEmI8UwLQnCK08L1SApDGAVcIUALQCMhvvvwSGRIZOtUugzLF7LTSSK7XdFx2EY9eJ+Wuq17GGYfGtuDVG0ytNkUn5yIgxIMLdR9FoCgENI7pqOvA1i5AFvOHP6p1ArqFUPJPaGFGMnQvLARO/6ZqeZ89QCVhZutqHM9C85cB7JXExECemQmb8uU1kh6WEKZovJCUpTzfkIX+Pv740+9PWFtZaySHTtIOAXOM6RuxNzDu9LhcovnnJj+jR5Ue2gHH8mxZcjKiRoxUuT5vYWsLr+XL4diyBcsaTVOcEOOZEoCmGYva7ooSgNoiRuezhQAlANlCshA55Kpt83mnFc07LCyARmXdMOXzqqjr46qR5jNhcQgKucGYS+v2aQSdICYJ8eAiCGCpkZwhoFFMky6wWzoDWclMO6t0BLpvAkT0hz9p+LHx4UZ0r9wdLjbaNVMwuvNlUuDIJODmRlXV5Cp352BAbGt0s9hQqFE8s6HIzGQ8//AcQUeD8D7zPWPnfl5+WNJ6CcQ0+9dgEWFuMX0q8hQmn5uMLHlWLqakgdKqgFVo4ckNySZ9/x5RQ4YiIzSU4WdLBwd4rwlWdNOmQzMEhBjPlADUzLemPosSgKbuYf7ujxKABvbN1Rfv0GvtVYaWo9+3RNVSzhpp7hF8BddfJuTOLe/ugBPjW8HKUrPHxsLjYYoOv4Oal4O1yFIjnXSS8RAQ4sHFeOhQTUJEQG1Mx9zKIf8ymVk/qPw50GMLJf8+On3Tw01YeGshyjiUwfxW81GrRC1+hkNWKvDPYODJEVX7mo4BAn8DLIX7b4/aeOanVwxmVbZUCguRSC/5LxNfIuhYEOLT4xlympZuiuX+y2FjZaOXfLq4aATMKab3Pt2LX6/8quignneQK+ZL2yyFo7VmdSrZjClJXByiBg9G5tNnDLGka7b3+nWwq1mTTXUmL0uI8UwJQJMPS402qNkveY1E0UkUAa0QoASgVnBpP3nq3gfYcT0yd2HVUk44+r2fRoJuvExA9+ArjLl/dquFHg28NVr/X2yS4vowaSJSsaQjZn1dHc0quGu0lk4yDgJCPLgYBxkAUTeAYj6AEy0AbzTMWVBUZEy/ugNs+RrISGRqqtQe6LkVENEf/gQY0hRh4NGBkGXLFDiJLET4qclP6Fa5GwseYlFEajywvQdASF3GsADazwaajmJRGTei6DNaiXv6vXuImTwZXkuXwrZqVZ0cEpUcpYjtuLQ4xvoGHg0UGVl2Iu3KpOhkhJkvMoeYJuVzNjzcgKW3l6p4O8AnAHP95nJCNJNr8hFBgyCJVP4uIAZaubvDZ+MG2FaubObRqf32hRjPlADU3s+muIISgKboVWHsiRKABvbT9fAE7LkVjf89fI3kDCkmd6iCUa0raqQ1KOQ6zoS9zZ1b2sUW5ya10SiTjxx+eq65ysgeJBmAl35sixJO9Ee2Rg4wwiQhHlyMAAuQlQasaAhkfABajgeajBbsFUKj4MUjJYXG9Ku7H8m/D0xrKwYCPbdR/35EhTy7ex3uhUfvHuXiRK6rrQlcg6ZldO/8znqIJLwAtnUFyH/zDpK99c1aoHpn1lVyIZA+o3NQzwwPR0TvPpC9fw9yTdFrxXI4NNUuHl+nvFZk/sWkxDBcWadEHUV824vtuXCx2ek09Zgm2X4Lby7ElkdbVHzbtVJXkPp/VpZWRvc7+Q5FDhoM6evXDN2i0qXhG7IR1mXLGt0mU1AoxHimBKApRJ7+e6AEoP4YUgm6IUAJQN1w03oVaQJyNuwt6ngXQykX9bWQQl8lKrL38o4ZnT5DUPNyGuneezsa43fdY8wd518J4wPp20WNADTSJCEeXIwCzbn5wJnflapcfIAhJwCnUkZRT5XojkCBMf36PrC5Uw6hm3dU8Ad6bafkXz6436S+wY8XfsStNzmZdSNqj8DoOqN1dwrbK6Nv5WT+pTGvcMK2GPDtDsC3GdsaOZNHn9GAND4eL3t9C0l0tNIPYjF8N2+Cfb16GvmGZPyRmn+RyczMp+rFq2Ndu3W0269GKLIzyZRjWiKXYMalGTj44qAKWENrDsXYumM5aaCXEfYEkYMHQxbPfGaKfX3gGxICcZky7DjXDKUIMZ4pAWiGgVrAlikBSOOAKwQoAcgV8mr0jt5+G4fvK98SujlYK7L37KzVv7VMTJfAf+FZxKcoCx57u9nhxA+tYCtWv56nkJikWUI8uBjcEUmvgeX1AUmqUlXZlsCAg1B00qGD1wioxHTi8xzyL11Zy1SxgfJtcsgiMb3yV5BDpXIpVt1dhftv7yuyo7jIWCkw0MKOArsHAtJ05seEpO/7D1CiCq/jU1vj6DMakCUmInr0GKTdvJkLn0OLFvBevQoWYrFaSN+lv1Nk/oUnhjPmVnGtgg3tN/C/yY3aHQprgqnGdLo0HRPPTcT56PMqDpnccDL6fdaPE0el37+PyKHDIE9klr6wqVQJ3hvWQ1yyJCd2mYpSIcYzJQBNJfr02wf9RaMffnS17ghQAlB37Ay28sXbFPgvOofsbKWKie0qY0zbShrpnHkgFJsuv2TM3TCgAfyr0VpqGgFoxElCPLgYHJ6Ut8DJGcDd7QDIl8ACGH4eKM3TJggGB0RYCvLGdPu63rDd2Q1Ie8fcRDk/4Nu/AWt65U+ddwkRKLLUr+mCOh0af353B7B/FJCvoD5K1QT6/GOSGbr0GZ0THfLMTLya/COSjx2DbfXq8Nm8GVaODmpD50PGBww6PghP3z9lzK3gUgEbO2yEm62bWhl0ArsImGJMJ2YmYsypMbj79i4DLFI/dVbzWehUoRO7IGooLe3GDUQNHwF5WhpjhW2NGvBetxYiV1cNJdFphSEgxHimBCCNZ4IAJQBpHHCFACUAuUK+CL0//nMff9+Myp3haCPCpSlt4WKn/k07uTrcaflFyPOQhwHVSmL9gIY83Ck1SYgHF6N5jdSMOzYNcCsPfL3CaGqpIv0Q+BTTTunRaBO5EBb5yT+Szdl7FyX/9IOZm9Wk2cemLwFJnh+zJJOTdG+21ayzPTeG666VPqOV2GXL5YgPDoZrjx4QuatvKJaUlYQhx4bgccJjhgN8nX2xqcMmuNupl6G75+hKUyJMivImKZkw4uQIPPvA7Kpra2WLha0Xws9Ls8Z7bEdMyoWLiB47FtkZGQzRdg3qwzs4GFaOxu9AzPYe+SBPiM9oSgDyIXK4t4ESgNz7wFwtoAQgzzz/OjEdfn+egUSmZPBGtKqAKZ+r77gnl2ejW/Bl3I5U1tmyEVni5PhW8HajmTY8c7XCHCEeXIyKI0mDlWbQa6JGBV0/ZSSmr+wPQbNnc2ArTWIK820O9NkNWKvPHNLPCrraYAg8OQ7s6AWQDsW1ewNfLQOs1L+cMpg9BhZMn9G6AZwqScWw48NwP/4+Q4Cno6eC/CvlQOu56oas/qtMLaYvv7qM0SdHQ5otzQXHydoJq/xXoU7JOvoDpoOElEuXED1iJLIlEsZqh+bNFQ10LO1o6QsdYC1wiRDjmRKAbHlf2HIoAShs/wnZekoAGsB7iWkSvE3JQMWSTlpLn3XwETZeUtbJIQTeRQ079+66GYXJ/zAP26TpB2n+QQc/ERDiwYWfSFKr+IJARvR9RZaYrZRZ7wg+zXLIPxua9ZDXV389/gs2VjYg3SkthFLj8tZmIDEKaPOTydflpM9o7Z8saZI0jDw5ErfjbjMWE9KPkH+EBKSDOwRMMaYPvTiEqRemKkAtaVcSwYHBqOTKzdk37dYtRA4eopL55xQYgDILF8LS2po755ugZiHGMyUATTAQddgSJQB1AI0uYQUBSgCyAiNTyJYrL/HL/lBUL+OMr+uUQafaZVDaRf3bvoTULDSfexrpElmuwH5NfPFb5xpqrfyQloW2C8+ByPg0fIvb49j3frTxh1r0uJsgxIMLd2hRzbxHICUO2cF+sEhRNjBS2OzdJKdBhI32L0V4v2c9DLwbdxcDjw6ELFuGL8p9gV+a/gIHMc2O1ANS1pea2zM6+eRJZL4IR/GhQ3QipDOkGYpabNdirzF8UcKuBEI6hIBc/6WDWwRMNaa3PdqGnWE7FU2TuCKZ0x88RGRQEOQpKQwnO3fqhDJzZsNCxJN6rtyGIKvahRjPlABkNQQEK4wSgIJ1neANpwSgAVzYdfVl3Ip4nyv5q9plsOzbumo1LToehmWnlTVMrCwtcHZia42u707f9wDbrkYydGwKaojWVWh3MbXAczhBiAcXDuGiqvmMgEwKbO0MvLzAtNKrEdB3j8nWiNPVJaRofbeD3RCbGpsropxLOez6chdsRba6imVn3dswIPw80GgoO/IELMWcntFpt28jMmgQsjMz4dq7Nzx+mgYLKyuNvZcly8J3Z77DxZiLjDWk0UdI+xCUL1ZeY1l0ouEQMOWYJtmn9mJuSt5kPHmCyH79FV2z8w7njh1R5s95Wn2XDOd905MsxHimBKDpxaEuO6IEoC6o0TVsIEAJQDZQzCMjKiENLf88w5C6cWADtK1adAfe5AyJIvsvKUNZw+Sbup5Y1FN9/ZIH0Yn4auVFRtfg9tU9sKZfA5Z3R8WxjYAQDy5sY4DUeODAWKD1VNrpl3VwjSjw5K/AxUUMhfLSdWE5YD9g62JEQ4Shau/TvZhxeQbD2OG1hmNM3THcbiDick6Nv4xEoHMwUOdbbu3hWLu5PKMznz/Hy959IM9DXjgFBsJz4QJYaHBlUSKXYMLZCTgTxTz/uNi4YEO7DajiVoVjT1L1nxAQckxHJkXCx9mHd87MevkSL/v2gyw+nmGbY9u28Fq6BBZi062TyrUzhBjPlADkOmr4oZ8SgPzwgzlaQQlAlr1+8Wk8xu+6i7jkTIVkV3sxrv8UALGVZZGa1px7jjlH/mPMOfGDHyp5FH1ljjT+6LL6Mu5FKRt/2IpzGn94uXLzFpRlSE1anBAPLqw75NB44OYGABZA3b5A258Bp6IJc9ZtoAL1QyDsSA5plGeki92AEedhV9xbP9kmvPpkxEn8cukXJEuS0bBUQ6wLXAcrS80zrliHJnQfsHcYIMv59wuWopy6jRXasq5KKALN5Rn9fvduxP78C8Mtxbp3Q6lZs9ReBZbKpfjx/I84HnGcsd5J7IR17dehevHqQnG3WdgpxJjOzs7G+gfrseruKixpswStvFvxxleSmBgF+Sd9zSx94dCsKbxWr4aljQ1vbDVFQ4QYz5QANMVI1H5PlADUHjO6gh0EKAHIDo4MKTJ5Nq69eIf9d1+hmIMYUz+vVqSWDIlMkTX49iNpSCZrmsFHGo6M2XEbF54q3zpOal8Fo9tUNMDOqEi2ERDiwYVVDOIeA6ubAdlypdg6fYHOK1lVQ4UZEIGEcGBtq5yMsY9DDitcrDwNDbuMhh3tdlgk+FHJUZhzbQ5mNpuJkvYclmy4sgo4Ng2AsgO9wvDyrYF++0y+2UdhTjKnZ3Ti4cN4PWWqonOpY6tW8Fq5Qm3NMplchumXpoM0Ycg77EX2WNtuLWqXqG3Ahw8VrQsCQotpebYc82/Mx7bH2xTbJU2T1gauRT2Perpsn9U1krg4RPTrB0kEswSPXb168Fm/Dpb29EU8q4AXIExo8Uy2QAlAQ0eFMORTAlAYfjJFKykByAOvbrsagen7HjIs2T+6OWp7F9PIOvJm9MjDWPx26BHsxFY48n1L2Ig4zCLRyGo6iSAgxIMLq577dyRwb7tSpMgOGHsTcCGPJjp4j4AkA9jYDnh9j2HqA8++eFGyHdq1a0cJQL47US4Hjk8HrhZAulf+HOi2EbA23x+x5vaMTr16De/WrYPX8mVqyQtCzMy6Mgt7nu5hRLmdyA6rA1ajvkd9vke/WdonpJgmV8t/vvQzDr84zPCVk7UTDnY+iOJ2xTnzofT9e0T274/Mp8ra3cQY2+rV4bMpBFZOtOmVMZwjpHj+hAclAI0RGfzXQQlA/vvIVC2kBCDHnpXK5Gi94Cyi36fnWtKioju2DWmstWWpmVK8TkxHxZL00KE1eBwtEOLBhVWoJOnAlZXAhUWAJBXwmwy0/YlVFVSYARE4+B1waxNDgbTqVzhs21WRMUYJQANiz4ZoQuDuGwGE/qsqrX4Q8MUCwMq8u1aa4zOavFS0sCj6pwmZM/vabEXX1bzD2tIaKwNWoknpJmxEKJVhAASEEtOkoceEcxNUmsoQSKY0moI+1foYAB3NRMqSkxE5MAgZoaGMBTaVKsJnyxaIXF01E0Rn6Y2AUOI570YpAai3201CACUATcKNgtwEJQA5dtu/d6Lxw9/M7JntQxqjWUV3ji2j6o2BgBAPLgbBJTkWuLQUaPMTYONoEBVUKMsI3N2RQx7lHcUrIb3fERw/d1nxV0oAKsHRhFRh2UNFi0t/D+zsA0RcUp3n/wvQYrzZXvvNCwh9RquGB4nlBTcXYMujLYwPRZYiLGuzDC29Who1lKky7RAQQkyTLumjT43GvbfM87HIQoTfW/yOjuU7ardpFmfL09IQOWQo0m/fZkgV+/rAd+tWiEtyWMqBxX0KRZQQ4jk/lpQAFEp0GdZOSgAaFl8qvXAEKAHIYXSQBh4dlp7HkzcpuVbU8S6Gf0c1U/v2nUOzqWoWERDiwYXF7VNRQkXgTSiwzh+QKjOXIbYHhp5GulNZHD+e0wyAEoA5Dr4bdxfzrs/DXL+58HX25d7rH6KAbV2B+DCmLaTpx9crgdrMhi7cG8ydBab4jE46cgT2TZronKW07PYyrHuwjkn+WYiwsPVCtPUx34Yx3EWpdpr5HtNvUt9gxMkRePaBebWWXC1f1HoRWni20G7DLM6WZ2YieuQopF7Oecn1aYhKl0bZbVsh9vRkURsVpQkCfI/ngvZACUBNPGv6cygBaPo+5usOKQHIoWeOh8Zi2NZbDAvW9W+AwM+K7oDKu0wSDjEUumohHlyEjjm1X08ESLOPtW2AhOdMQd+sA2r1oHUt88FLMlm6HeyG2NRYOIgdMLPpTHQo10FPJ+ix/PV94K/uQEosU4i1E9Bzi1l3/C0IVVN7RicdPYqYH8bDumxZeK9bB2sv7QiLNffWYMXdFQyoLC0sMc9vHjqU5TCu9fhKmNtSPsd0eGI4hp8YjtepzI66LjYuWOm/ktOmMqQ5TvR33yPl9GlGyFi5uyvIP/KdosP4CPA5ngtDgxKAxo8TPmqkBCAfvWIeNlECkAU/Z0nl6L7mClpVcsdXdTxRsaT6K4yExOu86jLuRX3ItaCyh/LTSxIAACAASURBVCOOfucHS8vCHwnxKZkYsPE6vg+orJYoZGFrVISBERDiwcXAkFDxfEYgOxvY1Q94fJBpZYPBwJeLFH+jMa2Ehjznx54ei3PR5xh4kWuSbXzaGN/Tz08Df/cHspKZuh1LAX12A6VrGd8mnms0pXhOvX4dUYOHKLr8kmFVwh0+a9fCtlo1jbwQ8jAEi27lfM8/DQtY4I8Wf6BThU4ayaCTuEeArzEdGh+KkSdH4n3mewZIpDs66fpboVgFzsDLlsnwavKPSDrMbEZi5eICn61bYFu5Mme2mbtivsZzUX6hBKC5R23O/ikBSOOAKwQoAcgC8qcev8HgzTdzJdXwdMY/I5rBVlx4J97Lz+LRe/01hvYlPeugc92i38ZP2n0Pu29FK9b5Vy2JGZ2qw6e4+XZoZMF9nIoQ4sFFL8BS4wEbJ0Bko5cYupgjBC6vAI7na9JSph4w6GiuT80upotwRUJGAgYdHYTnicpsyQYeDbCu3TqQemlGHSlxwJJazGvbxAD3KkDfPUAxb6OaIxRlphLP2XI5wr/ujMynT5nkysQJKD5kiFp3/PX4L8y9PldlHslo7Vq5q9r1dAJ/EOBjTF99fRXfnf4OadI0BlBlncsqyL/SjqU5A5C8yIn95Rd82P0PwwZLBwf4bNoEu5o1OLONKhbmS0dKANLIpQQgjQEuEaAEIAvoj9txBwfuvcqVVN/XFXtGNitSct/113DxWXzuHG83O5yZ0BoiK8tC192KSEDX1VcYn39TzxOLetRhYRdUBBcI8PEgblAcdvQG4h4B7X4Dqn5JmwwYFGyWhUdcATZ1BLJlSsF2rsDw80Axn9y/mV1Mq4GZdLKcc30O9j3bBzdbN+zutBsko4WTcWcbsH+0UrVvc6DXXwDxIx0FImBK8Sx5/RpRw4Yh82lObbVi3/ZCqV9+UVtzePeT3Zh1ZZYKPtMaT8O3Vb+lkSMwBPgW08dfHseUC1Mgkedkpn4a1YtXx6qAVYrnJleDkH9v5szB+y1bGSZY2NrCZ8N62Nevz5VpVO9HBPgWz5o4hhKAmqBk+nNoBqDp+5ivO6QEoJ6eScuSov5vJ5EuUf4onvV1dfRvWngtkLtRH9B5JbPz4u+da6Bvk8KLw0tlcnRacQmPXyflWuxoI8KpCa3g4Wyr5y7ocq4QEOLBRWesws8Dm/NcE/NtAXReBbjyoCmCzpsyk4Ukeyy4Zb66cRY510YrBTJAMKuY1sL9+5/tRwn7EmhWpuiXQ1qI1G3q2XnA2dlA9S5A52BATP/9KApIU4tnWVISokePgaWLM7yWLoWFVeE3FQguJG5/vvQzspHNgGlig4kYUH2AbjFIV3GKAN9iev2D9Vh6eykDkyalm2BJmyWKuqlcjrilS/FudTCT/BOL4RW8Go7Nm3NpGtVNCUAaAwJHgBKAAneggM2nBKCeziNvB+9HJ2L/3Vc4eP8VElKzcG2aP9wdC7/iOGzLTRx/9CZXcwknG1yY3KbIK8ObLoVj5sFHDGund6yGIS3L67kDupxLBPh2EDcYFnIZsKYV8OaBUoW9OzDuNmDrYjC1VDALCMikwNbOwMsLTGF+k4G2+a4D0xqALABuYBGkjuOjfUC1rwHLwjPODWyFYMSb4jNanpUFyOWwtC2a/D0SfkSRmSXPljP8Na7uOAytNVQwPqSGMhHgW0yTc/SfN/7EtsfbFIa2822HOS3nwNrKmlPXxa9bh7cLmTUvYWUFr2VL4eTvz6ltVLkSAb7Fsya+oRmAmqBk+nMoAWj6PubrDikByKJnZPJsRYZeDc/CCY2nb5IRuPg8Q+vUz6tieKvCixvHJWfAf8E5JGdKc9dVLeWEQ2NbFHllmMWtUVEGQkCIBxedoCAZZDv7ANHXlcs7LgIaDtZJHF1kRARO/gpczPcjqHybnLpxlqrZQ2YT00Z0gdaqCGlrZeQag1obKYwF5hrPpyJOYcK5CZDlvfIPYHit4RhTd4wwnEetLBABPsY0IZl/uviTIuNvaqOpsCrg3xZjujPhr7/w5rffmSotLFBm/ny4fNnRmKZQXWoQ4GM8q3MaJQDVIWQen1MC0Dz8zMddUgLQyF4Z//dd7L0Tk6vV2VaEy1P9Qa7zFjbyryHzdg1vikbluKuLYmTYTFadEA8uOjuDZB6F7gVOzASsHYARFylJoTOYRloYdgTY0YupzNkzp+6fg7tgflwaCS2kSlI5v7KGhBfA9p5A+zlApQBjbd1k9QjxGU0yqrLCw2FTXrcbAuejz+O7M99BKle+dCQODqoehB/q/6C2ZqDJBoOJbIyvMU3izcrCivP4+rD3X7yeNk3F26V+mwXX7t1NJApMZxt8jeeiEKYEoOnEnz47oQSgPujRtfogQAlAfdDTcm1UQhpaLzgLkin4aYxrWxHj21UpVNK1F+/Qc+1Vxue08YeWwPN4uhAPLnrDKUkHkl4BxQvPetVbBxWgPwIJ4cDaVkBGolIW6VwbdATwblSofLOMaQCJmYnocbAH2pdtj7H1xkJsKdbfB9pKiL4FbO8BpMUDpHZW0GGgTF1tpdD5eRAQYjy/27ARcYsXo/Tvv6FY585a+fPyq8sYe2ossuRZjHW9q/bGlEZTOCdntNoMnVwgAlzFNGmI9CrlFSq6VuStZ5KOHkXM+AmKK/J5h8fUKXAbQGte8tFxXMWzPlhQAlAf9ExnLSUATceXQtsJJQCN6LGf9z3E1qsRuRrtxFa4NKUt3BwKrnMikcnx5bKLCHuTnLvGyUaE0xNbg9QNpEP4CAjx4CJ81OkO1CIgyQA2tgNe32NO7TAPaDKiyOXmGNMk42rc6XE4G31WgU3tErUx328+SjuWVgs1axPCjgL/BAGSNKVIh5LAkBOAa+FNqVjTb6KChBbPiQcP4dWkSbneKDF+PIoPHaIRcXcj9gZGnRyFDFkGw5vdKnfDL03Udws20RAwuW1xEdMfMj5g9KnRiEyOxObPN6O8i27ZqYZ0RvLZs4geMxaQMjNfS3w3Du4jRxpSNZWtBwJcxLMe5iqWUgJQXwRNYz0lAE3Dj0LcBSUAjeQ1UsevxbwzyJIq3yoOal4Ov3T6rFAL1l94gd8PP2Z8PrPTZxjYvJyRrKZqDI2AEA8uhsaEyucBAgfGAbc3Mw0hXWO7hQAWRR9ZzDGmN4duxoKbCxh4+fv4K7pYGmXcDAEOjwfyNWuAR82cTs3ORiQijbJh4ykRUjxnhIUhvFt3QCJhAFR219+wq1WrSNDuxt3FsBPDkC5NZ8z7qsJX+K35b7C0oA1jjBd1htVk7JiOTY3F8BPD8SLxhWJjpR1KY8vnW1DKoZRhN6qF9NSrVxE1bDiySYOcPIOQ54REt1Dz754WquhUlhEwdjyzYT4lANlAUfgyKAEofB8KdQeUANTRcxefxsPRVoTaXi4aHQzmHvkPweee52oTW1ng/OQ2KO1iV6AFb5Iy4L/wHFLyNP74rLQzDoxpTht/6OgzPi4T4sGFjzhSm1hE4O52YF++bAf3ysDQ04CNk1pF5hjTf//3N+bdmAeJPId4cbN1w+5Ou1HSvqRavPSaQOpqnvkDOD9fVQxp1NJjC2DrrJcKc18spHjOlssRN38BEkJCct1WcuIEFB8ypEg3hsaHYsjxIUiRpDDmfV72c0U3Vq4bMph7DLK9f2PGNCH9CPlHSMC8o75HfYS0D9Ho/Mz2/vPLS7tzB5GDhyA7LU/2NADX3r3h8fN0XthoaAyELN+Y8cwWTpQAZAtJYcuhBKCw/Sdk6ykBqKP3Oiw5j/9ik+Fb3B5f1y6Dno184FmsYDIvMV2C5nNPM8i8Xg29Mbdr4W/kx+24gwP3XjGs2zOyGer7uupoMV3GRwSEeHDRCEdSP+fSYqBuf8CxhEZL6CQeIBD7EFjvD0jzXAEU2+eQfyWraWSgyca0mt0TEoV0TSU1roIDgtHMs5lGeOk8SSYBSKbmve2qImp/C3RaBogKLi+hs04zXCjEeH63aRPi5s6Da79+8Jg2tUgCIywhDIOODUJSVhLDuySDdX6r+dzUsjTDODPmlo0V0w/ePsCoU6PwIfMDY3se9h5YG7gW5Ytxfw0449EjRAwYCHmystQOMdalc2eUnv0HLCxp5qsxY1MXXcaKZ11sK2wNJQDZRFO4sigBKFzfCd1ySgDq4MH/YpPQYckFxsqdw5qgSfniBUpbcfopFhx/kvuZpQVwakJrlHN3KHD+5Wfx6L3+GuOzHg288Ge32jpYS5fwGQEhHlw0wvP+LmDvUMDGGWg5AWgyEhDRupUaYcfVJNLsY21rKLrI5h3frAdqad750GRjWgO/EBLlcsxldCjXQYPZekyRZgG7+gFPjqoKaTkRaDtd7VVtPbSb1VKhxnPazZuwq1sXFlZWhfrr+YfnCDoahPeZ7xlz/Lz8sKT1EoitOGhkY1bRxc1mjRHTpJnM92e+V7lSXs6lnIL848P138znzxHRtx9k75nx79ShAzwXzIeFSMSNg6hWrRAwRjxrZZAGkykBqAFIZjCFEoBm4GSebpESgDo4Zt7R/7D6rPI6b2kXW1z6sS0sCbOXb6RnydB83mkkpCrrinxZqzRW9K5XqGbS+XfK3gcIj09VzHG2FeHMxNYo7kgJFB3cxeslQjy4qAU0Kw1Y0QBIilFOreAP9NurdimdwBEC5CopIZQeH2Qa0HAI0HGhVkaZZExrhYCBJ8tlwJ7BQOi/TEWkRhvxVYNBBjbAvMSbajy/THyJoGNBiE+PZzi0SekmWOG/AjZW9LxhqpFu6Jg++vIopl6YCqmc2UyjpntNrPRfCVdb7m+yZEVFIaJPX0jj4hhudmzVCl7Ll8HCmmZPCyX+DR3PhsCBEoCGQFV4MikBKDyfmYrFlADUwZObL79EyKVwvHyXUy9kuF95TP2i4OtxZN6vBx8xtBwe1wLVy7gUqTlTKsO68y+w4swz/NTxM/Rr4quDpXQJ3xEQ4sFFLabn5gNnfmdO67UDqPqF2qV0AkcIXF4OHJ/OVO5ZHwg6onXmpknGNEduUVFLrtYfGAvc3cb8SGQHdA8BqnzOF0tNxg6+xnO2TAZkZ+uUpRSVHIWBRwciLo1JfpC6bKsDVsOOxBMdJouAIWN65387MfvabGQjm4FfszLNsLj1YtiTkhIcD0lsrIL8k8TkeUkJwL5xY3ivCYalrS3HFlL12iBgyHjWxg5t5lICUBu0THcuJQBN17d83xklAHX0UHZ2Nu5HJ2L/3Vfo0dALVUupFlonHX9bzT+D14nKelptqpRASFAjjbW++pAOD2dbWBWQXaixEDqRtwgI8eCiFszEGODULOD+zpyp5fyA/gfolUS1wHE0IeIysOlLIFumNMDOFRh+Hijmo7VRJhnTeVBIzExUZLYUtyu45IPWgGm6gGRpHp0CXAtmriA/qPv9C/g00VQSnacFAnyMZ3L+ePPbb5DEvoHnwgWwtNOcsHud8lqR+ReTwiQ/apeojTWBa+AgLrg0iRaQ0ak8R8AQMU1icvW91Yr/5R8dynbA7BazeXGlXBofr7j2m/XyJcNMu9q14bNxAywdaPzzPHxVzDNEPBsaA0oAGhphYcinBKAw/GSKVlIC0IBe3XUjCpP33Gdo+GdEUzQo62ZArVS0kBAQ4sFFY3xjbgHHfwY+nweUqqnxMjrRiAgkvwHW+AEpeTs0WgB9/gEqBehkiCnHNPmRO+70OIS+C8U8v3loWKqhThjptOj+bmBvvm6u5Jpmn11A+dY6iaSL1CPAx3iOX7MWbxcvVhhvV6cOvFavgshV/bVKkvFHav5FJkcyNl69eHWsa7cOTtbqu3yrR4zO4DsCbMe0TC7DnOtz8HfY3ypb71WlF6Y2ngpLUqKA4yH78EHR8CMzLIxhiU21avDdFAIrl6Jv5nBsPlVfCAJsx7MxgKYEoDFQ5r8OSgDy30emaiElAA3kWZk8G4GLzuHFxzp+RE2jsm7YNaKpgTRSsUJEQIgHFyHiTG0uAAGZFNjaGXjJbGgEv8lA2590hsyUY3pz6GYsuLlAgQ35QTuq9igMqTkEVpaFN1rQGcj8C4m/9o9WZtZaioCe2+i1X9YALlgQ3+L5w759eD1lKpPAqFIF5fb8U+R14Hfp7xSZf+GJ4Yy1lV0rY2P7jXCxoeSHgUOJN+LZjGmJTIJpF6eB1P3LP8jzcUTtEUV2oTYWKLKUVEQOGoSM+8yX8tYVKsB36xaI3OiLeWP5gm09bMYz27YVJo8SgMZCmt96KAHIb/+YsnWUADSQdw/ff43R228zpG8KaojWVUqqaJTK5IorvhYW9FFgIHfwVqwQDy68BZMaph0CJ38FLi5irinfBui7B9CD0DLVmL7/9j4GHBkAabaysL2brRv2fLUH7nbu2mGv62xSA/B/E4CbIUDX9UDNbrpKous0RIBv8Uy6+0aNGg15UlLuDjwXL4Lz54XXf/yQ8QGDjg/C0/dPGbuu4FIBGztsBIljOswHATZjmmT/TTo/CSciTuQCaAELTGs8Db2q9uIFqPL0dEQNG460GzcY9oi9vOD71zaIPTx4YSc1QjcE2Ixn3SzQfhUlALXHzBRX0F/9puhVYeyJEoAG8BO5Jvbl8osIfaU8oFcv44xDY1sUSPKtPPMM55+8xW+da6CyB72CYwCX8FakEA8uvAWTGqY5AmFHgB35fpw5e+bU/XPQj8wy1ZhOyEjAtAvTcOnVJQXO5EducEAwmnk20xx3NmaSWoAxtwGv+mxIozLUIMDHeM58+hSRQ4dBGhsLj6lT4DZgQKG7SMpKwpBjQ/A44TFjjq+zL0Lah6CEfQkaA2aGANsxnSXLwqiTo3At9hpEliLMaTkHpO4fH4Y8KwvRo8cg9QIz013k4aEg/6y9yM8gOoSMANvxbAwsKAFoDJT5r4MSgPz3kalaSAlADT0rkclBvqgiK/V1TM6GxWFgCPNN48re9dCxVmkVbdHv0xCw6BwyJHKILC0Q1LwsvguoDEcbkYaW0WlCRkCIBxcVvOUygNT3oRmswgjFhHBgbSsgI1FpL7lOSjr+emveoKiwzZpETBeyOXm2HBsfbsTyO8sxuMZgjKs3Thg+p1bqjABf45l0Mk0+dqxI8i9Vkophx4fhfjzz2qOnoyc2ddiEUg6ldMaFLhQuAoaIaRJrY06NwdBaQ0E6/vJhZEuliPlhPJJPKLMTiV1Wbm7w3bYVNuXL88FMaoOeCBginvU0Se1ySgCqhcgsJlAC0CzczMtNUgJQQ7fsvxuD3w49RqfapfF1HU/U9nIp9MpujzVXcD08IVdyeXcHnBjfqsBOvsO33sSx0De5cwmHcnBMC9TwpPV4NHSNoKcJ8eCiAvilpcCzU0D72UCpGoL2h8kbL8kANrYDXt9jbrXDPKDJCFa2bxIxrQYJ0gSkimsVRbaLQcbLi0CJqnpnYxrENjMTKtR4TpOkYeTJkbgdxyxFQkg/Qv4REpAO80TAUDFNbr/wpZRNtlyO11OnInH/AYaTLZ2d4btlM2yrVjVP55vgrg0Vz4aEihKAhkRXOLIpASgcX5mapZQA1NCjgzfdwKn/4nJnd6vvhQXda6usvvEyAd2DrzD+/mfXWujR0Ftl7pmwOATlyxTs18RXcRWYDvNAQIgHF4ZnUt4Cy+sBmUk5WYB1+wFtpwOOqrUuzcOjPN/lgXHA7c1MI6t3AbqFsJbBKfiY5tqFhPzb1hUo5gv03wc4l+HaIrPWL8R4zpBmKLKxyJXMvKOEXQmEdAgBuf5Lh/kioGtMh8aHwsPBw3g1T3V0ESEiY3/9FR92MrsSW9rbwydkI+xqq57ddVRFl/EAAV3jmUvTKQHIJfr80U0JQP74wtwsoQSgBh5PSM1Coz9OQirPzp29sHttdK2vWjskKOQ6zoS9zZ1X2sUW5ya1gbWIeXU4QyJD+yXnEfEuLXducQdrnJ7QGi72Yg2solNMAQEhHlwYuB/6Abi5kemKoacBT1qfjHfxeXc7sG8k0yz3ygDxlw17tUcFH9NcOi76FrDlKyArJccKQgIOOAC4luXSKrPWzVU8k+uLr3+ZAddvv4VdTc1fCpJ6bN+d+Q4XYy4y/EYafZCaf+WL0WuPZh3QAHSJ6Usxl/DD2R8U5DHpGu1kzd6/GWz6g5B/cfMXIGEj81xiYWMD77Vr4dBY/zIXbNpLZemPgC7xrL9W/SRQAlA//ExlNSUATcWTwtsHJQA18NnBe68wdsed3Jk2IkvcnB4AJ1smURf6KhEdlzEP3b98+RkGtSinomXpyadYfPIJ4+/zu9VC9waqmYIamEinCBQBIR5ccqHOSgNWNQY+RCrRr9UT+GatQL1hwmbHPgTW+wPSDOUmxfY55F/JaqxuXNAx/REJ8iPydNRptPVua7wrbW9CgZAvgIwPTH80GQ10mM2qj6gwzRHgIp4VGUy/zMCH3bthYW8Pr6VL4NiypVqjJXIJJpydgDNRZxhzXWxcsKHdBlRxq6JWBp1g+ghoG9NHwo9g2sVpkMpzOqA38GiA4MBg2FjZ8A6stytXIn75CqZdYjG8V66Ao58f7+ylBumPgLbxrL9G/SVQAlB/DE1BAiUATcGLwtwDJQA19NuzuBQcuPcKpBYgqc9HmnrkH2O238ah+69z/+zmYI2LP7aBvTWzTlTkuzQELj6HTKk8d259X1fsHt4Ulpb0caChS0ximhAPLgzgCQl4ZQVwcTFAupOOvQW40NpSvApO0uxjbWsg4QXTrG/WA7W6s26q4GMawObQzVhwc4GCAJzVfBYIgWLQEf8MCPkcSFWWmVDoq/ol0H0zYGWgWoMG3ZRpCOcinlVIDJEIZebMhkunToWCSsiZH8//iOMRxxlznMROWNd+HaoXr24aDqG70BsBbWJ6++PtmHt9LrKhvAFDDBhXd5yi4QefxruQTYibN49pkqUlPBcvhnP7dnwyldrCIgLaxDOLavUSRQlAveAzmcX0F7/JuFJwG6EEoJYuI2/mUzKlKtl/4fGp8F94FnluCWNCYGWM9a+koiF/PUHC+R0c2wLVyxj4R6aWe6XTDY+AEA8uBaKS9AqIuQ1U+9LwoFENmiNASNld/YDHB5lrGg4BOi7UXI4WM4Ue0/fe3sPAIwMhzc7JdiHNEub7zUfNEjW1QEGLqSSDduPnQFI0c1EFf+DbHYCIf1k2WuxO8FONHc/k6m/kkKFIu3o1FztyfZHULrOvp/rikUySyWWYfmk6Dr04xMDbXmSPte3WonYJWvNM8IHI4gY0iWly1l11bxWC7wWraP6i3Bf4vfnvEFvxp1zN+793IXbGDBVby8ybC5evv2YRPSqKbwhoEs98s5kSgHzzCDf2UAKQG9ypVoASgCxFwZQ997HzRlSuNEcbES792Falnt/JR28wZMtNhtaBzcpi5lf07TxLrhCUGCEeXAQFsLkbe3k5cHw6EwVSnzHoiMGIJSHHNKmf9tW+rxCTEqMkX2CB4IBgNPNsxn40JcfmZP7lz870aQb03QNY27Ovk0rUCgEu4lmelYXXU6ch6fBhgGQwLV0C58DAAu2WZ8sx68os7Hm6h/G5ncgOqwNWo74HrceqlcPNYLK6mCaE8uxrs7HryS4VNPpU64PJDSfDkjT94slIPHAAr36cknMLIc8oNeMXRQ1NOkwbAXXxzMfdUwKQj14xvk2UADQ+5lRjDgKUAGQhEl4npsPvzzOQyJSHjxGtKmDK51UZ0tOzZIqrv9Hv03P/7u5og9MTW8E5Xz1BFsyiIgSAgBAPLgKAlZpIEIi4DGz6EsiWKfGwcwWGnweK+RgMI6HH9IXoC4p6Vx8yc2rxDa05FOPqjWMfr7QEYFNHIO4RU3aZukD/A4CtM/s6qUStEeAqnrPlcsQtWAixlyfcevcu0G6SpUWImp1hOxmfW1taY2XASjQp3UTr/dIFpo9AUTFNXoJMvTBV5So5QWVs3bGK56GFBX9+tiadOIGY738AZHn+nQNQctIkFB88yPSdSXeoU1MbrmGjBCDXHuCHfv48SfmBB7XCeAhQApAFrH879AgbLobnSiIdf0ntv5JOtgzpi46HYdnpZ4y/Le5ZG13qqnYTZsEsKkIACHD141IA0FAT9UEg+Q2wxg9Iic0jxQLo8w9QKUAfyWrXmkJMx6bGYvL5nCyX9e3WQ2TJcg2+jKScbr+vlM2lFMCWqAYE/Q+wd1OLM51gHAT4Gs+E/CN1Krc82sIAgsTqsjbL0NJLfdMQ4yBItfANgcJiOlWSquggfe31NYbJFrDA9CbT0aNKD15tJeXCBUSNGg1IJAy73EePRomxY3hlKzXGcAjw9Rld1I4pAWi4eBCSZEoACslbpmUrJQD19GdCahaazz2NdIny7WO/Jr74rXMNhmRSI7D94vPIkikbfzQq64a/hzfh1dtUPeGgy7VEQHAHl/ALgHdjQGSt5U7pdKMhIJMCWzsDLy8wVbb6EWgzzeBmCC6mC0GENFUgP4hZbwBCGuds6wpEXmZqdiufczXbqZTBfUQVaI4AX+N52e1lWPdgHZP8sxBhYeuFaOvTVvMN0plmh0BBMZ2QkYCRJ0fi0TtmRrLYUoy5LeeiXVl+NdFIu3FDUSszOzOT4T+3gQNR8sfJ9FxtRlHN12c0JQDNKAh13ColAHUEji7TGwFKABYCIXm7/sfhx2hdpSSaVigOq0K68y468QTLTj3NlULmnZ3YGt5uytpNRNaAkBs4/+QtY97hcS1QtRS95qV3FAtYgKAOLqRT6arGOddHA38DqnYEeHQVSMBhwK7pJ2fmdGXOOyq0zcn+s7RiV1cB0gQV0wZHI58CaSaw41vg+SnmB85ewKAjBr2abeytmoo+Q8azPDUViYcOo1iP7loRFmvurcGKuysYEJNs1Xl+89ChbAdTgZ7uw0AI5I/p97L3GH5iOF4mvWRoJE1klrVdhsalGxvIEt3Ept+/j8igQSDfn7yjWM+eKDVzhlbfJd0soKv4hIAhn9GG2ifNADQUssKSSwlArJ/xYgAAIABJREFUYfnLlKylBGAh3rwV8R5dV+dkaJRwskGnWmUwuUMV2IqVP6BJN+Bmc04hKSOnWyQZ39T1xKKedRhS5fJsbLnyEguPP0FyZs7cIS3KYfqXn5lSLNG96ICAoA4uhLgI+59ylxUDgN67FUXq6eAJAv/9D9iZr+i5sycw/ALgUNwoRgoqpo2CSB4lpCELacySdziUAIKOAu4VjW0N1acBAoaK52yJBFEjRyH14kUU69EDpX75GRYi9VfNQx6GYNGtRQzLyRXNP1r8gU4VOmmwIzrF3BHIG9NVmlTB6HOjEZcex4DF1cZV0USmuju/GtRlhIUhov8AyBMTGfY6d+oE0vHXgp5HzC68DfWMNiSQlAA0JLrCkU0JQOH4ytQspQRgIR6dsf8hNl+JyP20fAkHnBrfivFmce3555j9v/8YEo7/4IfKHk4FSo1LzsDc//2HS8/jcXJ8KzjRxh+m9n3Sej+CObi8OAts+Zq5v+bfAYGztN4zXWAgBBLCgTWtgMw8P4wsxTnXSr0bGkipqljBxDSAg88PoqpbVVRyrWQcfEjjj23fKGv/2RYDBh4GSjFLRhjHGKpFEwQMEc/kVgDp8pu4b1+uCY5t2sBz0UJY2tkVatZfj//C3OtzVT6f2XQmulbuqsl26ByKAKNpQpPWTTDi7Ag8+6CsT13GoQzWBK5BWZeyvEIr80U4Ivr1g+zdO4ZdToEB8Fy8WCMCnVcbosawgoAhntGsGFaEEEoAGhphYcinBKAw/GSKVlICsACvSmVyNJ59Cu9Ss3I//SGgMr4LUP5IzJDI0PLPM3ibrKw/0u4zD6zt30BtnCSmSeBiL1Y7j04wfQQEc3B5dRf430Qg+kaOU+zdgXF3aKdSvoSoJAPYEAjE3mda9PmfQOPhRrVSKDF9/+19DDgyQNHgY1rjaehcsbNxro6RBiDbe+b4inT79apvVP9QZdohYIh4TrtzBxG9+wDZ2bnGWLm6ouzfO2HtU3CH7t1PdmPWFdUXLiR2v62aL+tXuy3S2WaGQP6YTs5ORv8j/RGTEoOKxSoiOCAYHg4evEIlKzoGEX37Qhqbt7EV4NCiBbxWrYSlNa1LzCuHGdEYQzyjDW0+JQANjbAw5FMCUBh+MkUrKQFYgFcJubf1SgT234vBw5gkxQxS16+su0Pu7G1XIzB930PG6n2jm6OOdzFTjBO6JwMhIKiDC/mx+nAPcGIG4DcRaBBkIFSoWK0RODAWuM3sBorq3wDdNhq9TuP/2bsO8KiKrv3ubjbJppJOSAMSQpPeCVU6ioIoRelS/BEpAiIKfjZEpYqA9A6CgIJSgxAEQu81tEASSEghvW7L/8xN2VyySbbvvbszz+PzfWRnzpzznrN3Z989cw4fYjqjIAOD/hmE+Jz4UqjfCn4L34d9bxoSkDQCSbkP1GimtavpAtMiYKx4zjwajviZM1EolUJgb4+gzZsgadJErXH7H+3H3Mi5KISKMCQTZ7ScgZENR5oWELob7xFQF9MxmTFYdHkRvgv7zvCNj/RETJaYxJB/srg4liRJyxYIXLu20qxZPbemy3mAgLGe0cY0nRKAxkSXP7IpAcgfX1mappQArMKjj5Kyce5xCoa3U12FIBmCXRedRFxqXunqsBAPbB/b1tLig9pjZAT4eHCBLA8Q2ZqkoYSR4bcM8de2A/snsm3xDAXGnQDs1JcjMKbhfIjpxZcXY+OdjSwYxjUah8nNJxsTGiqbhwgYM55zr1zBs08mw3fe93Du2lUtOoefHMbnpz+HslDJen1ys8kY13gcDxGlKpsbAWPGtKFtk6emImbECEgfPWaJtm/UCIEbN0Dk5GToLak8niHAp3gugZYSgDwLMiOpSwlAIwFLxVaJACUAq4So/IR9155j6q7rrBd2jG2D9iGepX/LKZDD0a7qgt46bE+XWBACfDy4WBD8/DflxS1gXXdAnq+yRexQRP551zeLfXyIaalCioWXF+L3qN8ZjFr4tMC6nuuY68AGGw+PAbW7ACJa7sFgmJpBkLHjWZGdA5GT6nZBWROPxxzH9P+mQ1GoYFk+ofEETGo2yQxo0C35igDJev7l6i+Y1mIabBQ2CA8PZ0zp2bMnJJXUnTSnvYrMTMSMGoWCu/dYatiFhiJoy2aIqtEbN+b0D1f2NvYz2hh2UgLQGKjyTyYlAPnnM0vRmBKAWnqSdPTt88tp3E/MKl3ZJKAa9k1sX3p1jJB/PRb/h851vfFZr7pwc6S1SbSE2Wqm8/HgYjXO4bqh+RnAmi5AajRb03fWAY3fM5v2fIrp8KfhzJfijb03wtvB23CYkevY5Fp23TeKrmGL7Q0nm0oyKQLmiudTz05hSsQUyJVylr2jG45mSByBgH51MGkg8HizqNQoTI2YytT46+LfBT+2+xH/HvuX0wSgMicHsR+ORd519o/ttjVrImjbVth4qn5w57FrqOoGQMBcz2h9VKcEoD7oWc5a+iluOb7kmyWUANTSY8fuJmLclsusVWuGt0DPhtVL/zb/0D2sPlX0pdzNQYxZvethcKsAemDXEmtrmM7Hg4s1+IXzNpJ6jLuGAVEH2Kq2Ggu8scis6vMtpgnBYtDMv1t7gL1jgZJ6bSQLcMgOwFZ9lpdZnUU3rxIBfeNZlpTEdCe1cXevcq+SCWfjz+KT459AqlQ1IiOvvV/vfXze+nN6ltAYSTqRdDonzWPyFaos8QkNJyDgeQBnCUBlQQHiJnyE3PPnWQ4U16iBoO3bIPb1pY6lCJQioO8z2hxQUgLQHKhzb09KAHLPJ9aiESUAtfB0YWEhBqw8i+tx6aWrQn2ccGRKJwiFRW/jh4lZTIagXKkq1t2xjie2jGlND+1aYG0tUzl7cIk9D9zcBXT9EnCkv7RzLh4jlwHH5rLV8msBjD4M2NiZVV3OxrQpULl/uIiYfSVrCwNWA02GmEIDuoeBEdAnnhXZ2YgZNhzKvFymWUFFHX7LqnzpxSVM/Hcii7Ahr78b+i6+avsVPUcY2L+WKk6mlDFNPbbf217ORC+JFybYToC9wJ5zV4ALZTKmLmb2yZMsvW28vJjMP9ugIEt1GbVLRwT0eUbruKXeyygBqDeEFiGAEoAW4UZeGkEJwDJue5aWC08nO9iLRWqdefZxCt5fe4H12pLBTTCgGYERIATh0LXncT46tXSOWCTA0amdUNuLFirm5TvEyEpz8uCiVALrugHxVwE7F6DTTKDNBLMTS0Z2BX/Ex5wFNr0JlK0LJnEDJpwCqgWa3Q5OxrQpUIk+CWwfBCgK2Lt1nAF0e4WsNYU+dA+DIKBrPJPuvrETJiD3XFEWk8jdHQGrV0PS6LUK9bqedB3jj41HnlzVYIxMJh2qSXdWoUBoEJuoEMtGICUvBdNPTsfVpKvlDG3q1RTz2s7DtdPXmNe4VAOwUKHA8xkzkHX4CEtvUuuPkH92ISGW7ThqnU4I6PqM1mkzAy2iBKCBgOS5GEoA8tyBPFafEoBlnDd49TncTchEn9eq4+2mfmhb2wOi4sw+Mm3Yugs48yildIW/mwQnZ3SBjajoUL7/+nNM2cmuV/Jx12DM7FWPxyFCVTcmApw8uNzYCfw1gW12v1+AFqOMCQWVrQkCWYnA6k5A9osyswXAB3uAOt01kWD0OVyL6ZvJN3Eg+gCmt5wOO5GRsiPjLgJb+gOyHDa+bT4Cev8I0HptRo87Y22gazwn/vgTUjdtYqllV78+au3dA4GwPJF3J+UOxoaPRbYsm7WmT80+mN9xPkRC9T9MGstuKpefCBASmZB/SXlJ5QwYXHcwZrWaBblUzrkmIIVKJRLmzEXGn3+y9BY6OSFw8yZIGjbkp0Oo1kZHQNdntNEVq2QDSgCaE33u7E0JQO74wto0oQRgscfj0/MQ9tMJkNJaJaNsbb8bcel4e0UkKz6+6/8ahrctuo6QlS9Dt0X/ISlLlf3hV02Cfz/tDIktPbhb2xtLU3s5d3Ah2X/LWwKpj1UmeNQBJp6j3Uw1daqx5inkwNb+wNPT7B06zwK6fmGsXbWWy6WYJp0vB/0zCPE58ajvXh8LOy9EoIuBsyQTbgCb+gEFGWysmg4D3voVUEP2aA0qXWA2BHSNZ1liEuImTEBBVBSjO8kArLnzd7XXgO+n3seYo2OQKc1k2dktsBsWdF4AsZB2kjZbAPBkY3IDZfeD3Zh/cX65xjG2QlvMbTcX/UP6M9boGtPGgoLonjjvB6Rt28baQiCRIHD9ejg0b2asralcC0CAa/GsCaSUANQEJcufQwlAy/cxVy2kBGCxZ9aceowfDhUd1MlwtrfBpS+7l14HnrD1Mo7eSSx9nVwVPjOra+nr3x24i/VnnrD8vHp4C/Qq0xyEq0FA9TIfApw8uGQ8A/79Brj1RxEwQ3cBdXubDyS6cxEC/34NnFnCRiP49aLsPw5lB3ElpsmXyskRk3EyTlVLylHsiM29N6Oue13DRFXyfWBjHyD3JVtewwHAwPWc8othDLY+KfrEM6kB+OyTT5B34yaCNm9We/33cfpjjD4yGmkFaSxwO/l3wtIuSyEWUfLP+qJOO4sLFAX4/vz32PdoX7mFvo6+WNJ1CRp6qDLo9Ilp7TTTbHbS4iV4uWYNa7LA1hYBq1fBsV07zYTQWVaLANfiWRNHUAJQE5Qsfw4lAC3fx1y1kBKAxZ758q9b2HExtjQDcFBLf/z8bhPmVdLYo8eSUywfzu5TDxM6BzN/i3qRiTeWnYGiTOOPrnW9sGFUK1qwm6uRzxG9OH1weXYFuPMn0PN7eoXR3PESdQjYOZSthYsfMOE04Ohhbu1Y+3Mlph+lPcLQg0NZzRRa+LTAup7rDNP1N+0psKE3kJXAxr9OL2DwNsDGllN+ocrohoC+8UxqAeY/fKj2CuPTjKcYfXQ0SM22sqOtb1ss77bceFfWdYOCruIgAgnZCZh6ciruvrxbTrs2vm2woNMCuNm7cfIZTZRKWbUayUuXsnW3sYH/smVwfr0rBxGnKnENAX2f0eawhxKA5kCde3tSApB7PrEWjSgBWMbTCRl5+OdGPPZfj8cXfesjLKSo++mnf1zHn1efl850sbfB2dnd4GRnwzT+GLT6HC49Vf16b2sjxLFpnRDk4WgtcUTt1BEBPh5cdDSVLtMVgdQnwOrO7Cum5Eog6fgb0EpXqUZbx6WYfpj2ENP/m44nGU/gbu+O3f12w9vBW3/bM+OLyL/0GLasmh2BD3YDYon+e1AJnEDAWPEclxWHUUdGISmXXauNkNS/df8NEhsaQ5wIAA4rQa6OjwsfVy57lKg8+rXRmNxsstofO4wV09pClbplKxJ/+IG9TCiE38IFcOnbV1txdL6VIsCVeNYGfkoAaoOW5c6lBKDl+pbrllECsAIPEWJPIBAgLjUXXRaeZGX3TX49BJ/2LLpCtvfKM0zffYMlZUq3OpjWI5Trvqf6cQABPh5cOACb9aggywfW9wBe3GTb3Ofnos7MHBxci+lcWS7mXZiHvrX6IswvTH/EclKKrv2mPGDL8msJjNgH2DnrvweVwBkENIlnZUEBhHaaN5ghWVsk8+95tuqHRWJwE68mWN1jNchVdTooAlUhkC/Px/DDwxGVqipfQ4hj0jG6V81eFS7XJKar2lvf19P37kXCl3PKifGdNw/VBr6jr3i63ooQ4EI8aws3JQC1Rcwy51MC0DL9ygerKAFYhZe+2n8bW86psjwkYhEiP38d7o62yMgjjT9OIiVbWiolwF2CY9M6l9YG5EMQUB3NhwAfDy7mQ8sKd/77E+DqFrbhrw0sqi/H0c6yFh/Tm98CnvzH9olPI2DUP4CEfdXOCiPW4kyuKp5lL14g5oNh8PhoAtzee69K+0nGH6n5F5sVy5pLarSt7bkWzraUQK4SRDqhFIFnWc8w5OAQkIZHQS5BTN3IELeQShGqKqaNDW/GwYOInzETrK57AHy+/BLuw4cZe3sq38IQMHc86wInJQB1Qc3y1lAC0PJ8yheLKAFYiaeSswrQ4acTKJArS2eNCauFr/o1YP79v/23sbkMOUj+tmFUS7xez4cv/qd6mhkBThxcspMBR0/OEkpmdpH5tr+2Hdg/kb2/ZygwLgKwczKfXlXszImYNiY6L24BW/oDucV120iXbHId28nLmLtS2WZCoLJ4VmRmMuRfwcOHjHaen0yC58SJFdb+fZn3ksn8I1fSy45Qt1Bs6LUBrnauZrKSbstnBM4+P4td93fh+w7fa0Qgm/MZnXXiBJ5NngLI5SzIvaZNg+eE8Xx2A9XdTAiYM551NZkSgLoiZ1nrKAFoWf7kkzWUAKzEWz8dicJvJx+XzhCLBDj1WVf4ukpw+3kG3lp+BmX6fqB7fR+sG9mST/6nupoZAbMfXMgV0xWtAPfaQK8fAB9Vp0AzQ2Pd2xOSaV13QJ6vwoFcCxx3AvCux2lszBXTJWUbTAJOykNgy9uAQASMOQy4ko9SOiwRgYrimTT3iP1wLHIvXWKZ7T1zJjw+HFMOivT8dIwJHwNSl7LsCHYNxobeG5galXRQBCpCQKaQGawjtLme0TlnzyJuwkcolMlYZnpMmADvaVOp8ykCOiFgrnjWSdniRZQA1Ac9y1lLCUDL8SXfLKEEYAUeI9d7w348gewC1a+Ug1sG4Kd3GzMrMnJlWBAehe0XijoH29kI8e+nnRHg7sC3GKD6mhEBsx9cziwB/v26CAGBEGg+Auj9EyC2NyMqVr51fgawpguQGs0Gglz7bfQu58ExR0yT62/jj43HpKaT0NG/o2kwSosBChVF5DkdFotAhQRgYSGSl/6Cl6tXl9puW6sWgnZsh40b+yp4pjQTY4+Oxb3UeyycyJXNjb02wsuBZo9abADpaZiyUInfbvyGM8/OYFOfTQbpDG2OZ3Tu1asMYV6Yl8dCxG34cPh8MbvCrFk94aPLrQABc8SzvrBSAlBfBC1jPSUALcOPfLTCqgnAs49SsO1CDN5q4ocudb1YdftWRDzCgqP3S30qFADHp3dBLU92ce5bzzIwZ/9tdK/njU+61eFjDFCdzYiAWQ8u2UnAsuaANEuFQGB7YPQheh3YXDFBfk3YNQyIOsDWoNU44I2F5tJKq31NHdMk829yxGScjDvJ6Pnhax9iUrNJartfamUInUwRAFBVPKdu347E7+dB5OmBmr/vhK2/Hwu3HFkOxoePx80UdiMfPyc/bOq9CdUdq1OcKQJqESA/bMw+PRunn59mXu8f0h/ftv9Wb7Ksqpg2tDvybt9B7KhRUGZns0S7DnwHvt99B4FQaOgtqTwrQsDU8WwIaCkBaAgU+S+DEoD89yFfLbBqAnD6Hzew9+ozxnfO9jb4vy7BmNglBHlSBcJ+OoHUHFVzjzca+2LF+83V+lmpLISisBBiET3E8PWNYC69zXpwibsI/DESyIpXmU/qy/mpj3NzYWRV+0YuA47NZZvs16KoxpyN5l1GzYmZqWN6y50tWHB5AcvkYfWHYVbrWfrBQMjYxyeAkG76yaGreY2AJvGceewYbP39YV+/PstW0oH6//79P1xNusr6OyH9CPlHSEA6KALqEHiQ9gBTI6YiLiuO9fLctnMxqO4gvUDTJKb12qDMYlIfM2b4CCjS01kiXfr2QY0FCyAQiQy1FZVjpQiYMp4NBTElAA2FJL/lUAKQ3/7js/ZWSwDmyxRo+f2/rCu+c96oj7Eda2Nj5BN8889dll8PTu6AhjVogW4+BzsXdTf7wUWaA5z9FYj8BWjwNjBgFRdhsg6dnkYCm/sVXSstGRJ3YMIpoFoAbzAwZUyT7L/PTn2GI0+PlOLjZueG3f12w8dRj2ZMhPw7+gVwfiXQ+XOgy+c0K5Y3EWhYRXWN53x5PiYdn4QLLy6wFPKSeGFj741Mx1Y6KALqEDj85DD+d/Z/yJOzr8uKBCLMbDUTH9T/QC/gdI1pbTeVxsTg6bBhUCQXN0wqFuDUtSv8l/0CgVisrUg6nyJQDgFTxbMhoacEoCHR5K8sSgDy13d819xqCcCDNxPw8Q7Vr/ICAXB+dje4Odiiy4IIxGeoiu+T68GbRrfmu6+p/hxEgDMHl8z4ooYGznqQJhzElzcqZSUCqzsC2YllVBYAH+wB6nTnjRlEUVPHNCEBd0TtwMLLCyFXyrGq+yqE+YXph1nED8B/P6lktJsE9PyekoD6ocrL1brEs1QhxZSIKTjz/AzLZtLog9T8q12N1o3kZTAYWWny/FpyZQm23N1SbicSOws7L0Sr6q301kKXmNZ2U1l8PEP+yeMTWEsd2rVFwKpVENrxI6NdW7vpfNMjYIp4NrRVlAA0NKL8lEcJQH76zRK0tloCMD1XikO3XmD/9ee48CQVYSEe2D62Lf64HIfP9rBr9ez+qB2aB7rhZU4BvJ1pcwRLCHyu2MDHgwtXsLMYPRTyoo6yMWyyAJ1nAV2/4J2Z5orp2ym3cS3pGoY3GK4fZuquYRNyfHwE4NtEP9l0Ne8QIPF8ctMmuEecxGurfoOje+XdemVKGaafnI6IuAiWra52rljfcz3qutflHQZUYeMj8DLvJWaemolLL9hdpcnOjT0bY1GXRQarF2nsZ7Q8ORkxw4aDZACWHZJmzRC4fh2EDrRZnvEjynp2MHY8GwNJSgAaA1X+yaQEIP98ZikaWy0BWNaB8el5IF1/Q32c0WPJf4hOzil9uXVNd/zxUTtsvxCDHw7ew7QeoRjZviat92cp7wAz28HHg4uZIbO87Y/9D4hcyrYr+PWi7D8h/+oj8TqmL60HDn76SowJgHfWAo3fs7zYoxZViUD6lSuI++j/YJOVBduGDRG0ZjVsPDzUriMZXLNOzUJ4TDjrdWexM9b2WouGHg2r3I9OsD4EbiXfwrST05CYWzYDvAiHd0PfxezWs2ErsjUYMMZ8RsvT0hA7YiRI7b+yw75BAwRu2giRi4vB7KCCKALkBkDqkaOIzM5Coa0tevbsCYlEwnlgKAHIeReZREFKAJoEZrqJGgQoAVgGlEO3EjBxO7tY98bRrdDEvxq6LjzJkIRk1PVxxvyBjZisQDooAvogYMyDuD560bUmQiDqELBzKHszFz9gwmnAUT3JYCLNdN6GtzF9Yxfw1wQAhWzb31wKtBytMx50IX8RINcYH/XoCShUdTnFgYEI2rwJYl9flmEKpQJzIufgQDS7g7eDjQPW9FyDJl40e5S/kWA8zfc+2It5F+aBZI6WHWKhGF+2+RIDQwcafHNjPaMV2dmIHTUa+bdvs3S2DQlG0NatsHGjZ2aDO9OKBeZeu4akBQuRd/Uqknv3QlrXrpQAtOJ44KPplADko9csQ2dKABb7kfyK9OavZ3AnPrPUsw18XUCaf8z+8xZ2XmJ3Ytv2YRt0qONpGVFArTAbAsY6iKs1KDcVuLUbaDEasDFcNoHZwOP7xqnRwOouQEGGyhKhuKjjb4D+dZ7MBY8xY5p0VbW3sYdQYOCO6/f+KeqIXbYBCwGQ1P1r/4m5oKT7cgCB2KnTkHNE1WRG0rIFAtevZ9UwUxYq8e25b7H34V6WxhIbCX7r/hta+LTggCVUBS4hQOpEzr84H3se7Cmnlo+DD5Z0WYJGXo2MorIxntHKvDzEjhuHvMtX2EQmIcy3bYXY29sotlCh1ocAuVqetHgJso4eLTVeYWeHp5/NRLd33qEZgNYXEry1mBKAvHUd7xWnBGCxC/97kIyRGy6yHLr8/WaoUU2Cd1aeZf39jca+WPF+c947nxpgfgSMcRCv0KrDs4ALqwD34CJio24f2tTAXCEgywPW9wBe3GJr0OdnoA3JQuPvMFZMkx9pSGMF8sX5h44/gBTFN8h4dBz4fQigkLLFke6/XWcbZAsqhL8IZD56hLi3+0OoUEAcGopaW7dA5OpaahCJyx8u/ICd93eyjLQV2mJF9xVo69uWv8ZTzY2GwOIri7Hx9sZy8lv6tGSafXhIjJcBbuhntFIqxbP/m4icyEiWPTa+vqhJyD8/P6PhSAVbDwLkennKipVI27kTkMvLGZ7Wvj2arVhOCUDrCQneW0oJQN67kLcGUAKw2HWDVp/DxSeppY6s5emIo1M7YcDKSFZWoIOtCCemd0F1V9oMhLdRzyHFDX0Qr9C0lIfAyraAssyhqescoPNMDqFhRarsnwRc28o2+LWBwMD1vCdljRXTW+9uxc+XfmYw85Z446dOP6Fl9Zb6BU3MWWDrO4A8jy2Hdv3VD1cerSYEXv7du5A0VF+fj8TzlRkzUCgUovk337CagJC1pPv0q11bbYQ2WNZ1GTr6d+QRElRVUyKQUZCBoQeHIi5LdbtkRIMRmNZiGkj8GHMY8hldKJPh2dRpyD5+nKWyyNMTQVu3wK5WLWOaQmVbAQKFSiVerl2Hl2vXQpmdrdZiqbs7Uvr0RvsZMygBaAUxYSkmUgLQUjzJPzusjgA8eucF2gd7wNleXOqty09T8e6qcyzv/TywMQrkCszdf4f19y/61sP4TsH88zTVmJMIGPIgXqmBO4YADw6rpojsgEmXALcgTuJi0Upd2wbs/5htomcoMC4CsHPivenGiGlSJH/EkREgTRZKhqfEE4ffOcxcCdZpPL8KbH4LkGaxlzcfCfT7hfdErE6YWNmi3KvXkPTzz8i7eRO19v0F+9DQcghUFs/Lri7D2ltrWWtsBDZMx9bXA1+3MjSpudoicD/1PoYfLupa/k37b9CnVh9tReg031DP6EKFAvGzPkfmAXbdS6GrK4K2bIF93fLvJ50UpousHoHY8eORc+p0ORxINrbLuLG46OaGQhsbWgPQ6iOFXwBQApBf/rIkba2KAHyUlI3ui/+DnY0Q3ev74K2mNdCtnjfGb72CE1FJpX71dbXHnxPbo9eSU8jMV33hrOPthENTOtIOwJb0DjCzLYY6iFdpRuwF4Ohs4HlxfZ4O04DuX1e5jE4wMAIJN4uu/srzVYLFjsC4E4B3PQNvZh5xxojpa0nXMP3kdCTnJZcaRWpAM02NAAAgAElEQVSrdfDroJuRiXeBTX2BvDT2+kbvAQNW87L7sm5AWO8qQlxk7N9fCoBT584IWL2qHCAVxfPqG6ux/Ppy1nxSm5Jkpvau2dt6gaWWa4VARGwEajjVQF33ulqt02eyIZ7RJPv1xVf/Q/ru3ez3gKMj0+1X0sg49Qv1sZuu5S8C+Q8e4En/AYBSyRghsLWF2/Bh8Bw/HlJbW4SHF3Vep12A+etja9ScEoDW6HVu2GxVBODiYw+w7PjDUuQ9neywcVQr9Ft+huWNr95sgLsJmdhz5Rnr77+Pa4t2wcary8KNkKBamBIBQxzENdaXHJxu7wHOrwRG/A3Yu2i8lE40AAL5GcDqzkDaE7Ywcu230bsG2IAbIowV0yl5Kfji9Bc4l3AOYxuNxZTmU3QzWJoLLG8JZD5nr6/7BjBoMyBSZYfrtgFdxQcEkn9djpQVK1iqBm7aBMe2bVh/UxfPpHYbqeFWdgggwLwO89AvuB8fzKc6mggBcsXXSewEN3vudMDV9xlNyL+kH39C6ubN7PeAvT0C162FQ0s9SzOYyDd0G34hEP/ll8jY+ydc3uoH7ylTSmtL6hvP5kDh2bNnCAgIKNma/B/2F05zKEX3NDkClAA0OeR0w2IErIYAJAeWLgtPIuZlbqnzR4fVREq2FP/ciC/9m5uDGL8ObYZh69kNQd5uWgO/DGlGA4ciYFAEzHJwKSyk1xsN6kUNhBHMdw0DothXpdBqHPDGQg0E8GeKMWOadFvd/2g/Q7LoVSfr9p/An+NUNTFrdwGG7gLEOl4n5o97qKbFCChzcvCoV28oUlKYv4gDAlD96//BKSysUgLwz6d/4seLP5bD8et2X2Ng6ECKL0WgFIHTz05j1ulZaOjRkOkGrdczy4C46vuMTl72K1JWrmSTf2Ix/FeuhFNHHbOyDWgfFcU/BGTx8Uj+ZRmcunaFS+9eag2QJSZBnpJcrl6rvvFsDrQoAWgO1Lm3JyUAuecTa9HIagjAzHwZPt11HSfvJ0OuLGT8+9sHzfHxjqso/ifzt2nd6+Dw7ReIeqGqC+VkZ4MT0zvD24V+ObSWN4ap7OTjwcVU2FjUPpHLgGNz2Sb5tQBGHwZs7CzKVN7E9IOjwK7hQI1mwPA/AVtHi/IDNQYgNcogFEIgUH/MTtu5C8lLl8Jz4kS4DRnMXCt7dZSN55zgHMy/Mr/cnC/afIGh9YZSyCkCDALkh4q1N9dixfUVKETReXPMa2OYBh9cGPo8o1+uX4+kBa/8aCUSwf+XpXDu3p0L5lEdeISAIjMTL9esQeqWrSiUSiEODETwgX/UPosrMkufeDYXVJQANBfy3NqXEoDc8oc1aWM1BGCJU9NypDh0OwEXolPhYCvEzkuqrGtHWxE+7hqCn4/eZ8XA3Dcb4MMOtJOZNb0xTGUrHw8upsLGYvZ5Ggls7kfYCJVJEndgwimgWukVEIsxl1cxTWpjktqL9q4Wgz81BCAZ/zmnTzNEhde0qXB+XX1DjkK5HMrcXIhcKi6HUBLPV6VX8VfuX6WETgnOM1rOwMiGIynsFAEGgSxpFr488yUi4iLKIbKi2wp08u9kdqR0fUan7tiBxG+/Y+svEKDGzz/BtR+9+m52x/JIAUL2pe3ciZSVv0GRns7S3OeL2XAfMUJja3SNZ403MMJESgAaAVQeiqQEIA+dZiEqWx0BWOK3Fxn56PjzCcgURb/OkjG8bRD2XXuOrAJV44961Z1x4JMOsBEJLcTl1AwuIWC0gwup9yekMWt2X2clAqs7AtmJZVQRAMP2ACGWmS2hb0wT8iYmMwY1XWua3X1UAf4hkB8VhcSffkLuufOM8ra1a6P23/shsLHRyRgSzwsPLMTu3N3lyL/JzSZjXONxOsmliywPgcfpjzE1YiqeZj4tZ1yvmr3wbftv4SB2MLvhujyj0//ah4TZs8vpXv2bb+A2eJDZbaIK8AMB8vmedfgwkpYshSwuTq3SYn9/BB89AoFIpJFRusSzRoKNOIkSgEYEl0eiKQHII2dZmKpWSwB+f+Au1p1RFeO3ZToDe+PQrRcsF+/+qB1a1XS3MLdTc7iCgNEOLnvGABI3oMsXgCNtXGMWfyvkwJa3gRh2kyF0/hzoWv6LlFl0NMKm+sb0trvbsOjKIpDMqvfrvV/h9U2NVJflAS9uAwGtNJpOJ/EfgYx/DiB+5kyWIdW//pq54qvteJT2CNvubMNfj/+CEkXdJ0vGhMYTMKnZJG1F0vkWikD403DMiZyDPHkey0LSGXpa82lMlmhFV9FNDYm2z+jMI0fx/NNPSzuwlujr/fkseIwaZWr16X48RSD38mUk/rwA+TdvqrfAxgZugwbB8+OJsPHQ/NyqbTxzAT5KAHLBC+bXgRKA5veBtWpglQQguQYc9tMJ5EpVV/KGtQ3EqPY1MXffHZyLfsnEw8Dm/lg0qIm1xga12wQIGOXgEnMW2NinSHs7V6DzTKD1BMCmfH0rE5hovVsc+x8QuZRtf/DrwAd7AKFmv2zzETx9YvpW8i2MODICcmVRFnaPoB74pv03cLZ11h4KuRTY+T7w5D/gvU1AvTe0l0FX8A6BQqUST999D/l375bq7hgWhsD16zSyRaaUISI2Ar9H/Y7LiZfVrhndcDRTz40rhI5GhtFJRkGAPKuWXVsG0hn61VHNrhoWdF6Atr5tjbK3rkK1eUZn//cf4iZ9AshkrO08J38Cr4kTdVWBrrMiBAqio5G0cBGyT5yo0GrnHj3g9ek02NXSvtySNvHMFdgpAcgVT5hXD0oAmhd/a97dKgnAJcce4JfjD0v9LhIKcHJGFwS4OzC1g/65mYBfjz/EjnFt4eVsWQX6rTnYuWi7wQ8u5Orv2q5AwnWVuSQTcPK1ooxAOkyDQNQhYOcrTQFc/Ivq/ll4RqauMZ0pzcSgfwbhefZzlo/W9FiDdjXaaec3kn25dwxwd3/ROoEIeGcN0Ohd7eTQ2bxEIOf8ecSOGg2b6tXhNWUKXN/qV+V1spS8FOx5sAe77+9GUl5ShXaTrNTPW39OyT9eRoZhlU7LT8Nnpz7D+YSi6+ZlRwOPBljSZQlqONUw7KYGkKbpMzrnwkXEjR+PwoIC1q7uH46B94wZ9D1gAF9Ysgh5cjKSl69A+p49AGnIpGZImjaF92cz4dC8uc5QaBrPOm9ghIWUADQCqDwUSQlAHjrNQlS2eAJQqSyEUKh6i2UXyBH24wlk5Kl+zRzQzA9LBjdluZQQgfTXfQuJcg6bYfCDy4tbwLrugDxfZXWfn4E2EziMgoWplhoNrO4CFGSoDBOKgTFHAP+WFmZseXN0jWmSefXrtV9ZmTRjG43FlOZTtMOMkOB/TwKub2evY4jw64Ckmnby6GxOIVBSQ0qZX4Bq7wyoULeMgwfh3K0bhPb2Fc4hsq4lXcPOqJ04FnusNPNU3QIhhBhRbwQ+bf0pPRtwKiLMo8ydl3cwLWIaEnISyinQP6Q/5rSdAzsRN39A1uQZnXf9OmLGfIjC3FyWfdWGDkH1r76i7wHzhB1vds27dRsxI0eWi58SA2yDguA1/VOQzD99v2tpEs9cA44SgFzziHn0oQSgeXCnuwIWTwB+vOMqsvLleLtJDfRs6IPfL8bih0NRLN+HT+uEUB8drpjRCKII6ImAUQ4u6XHA8W+AW7sBz1Dg/84CIrGemtLlGiFAas6t7wEQIrbs6LMAaDNeIxF8n6RvTJ96dgpfnPkCwa7BWN9rPWyEWjRvKCwEDn8GXFzDhlHsCIzYT2sB8jy4ci5eZDr75t+6BaGLC0LCj0JUTXtCN1eWi0NPDjHE3/20+5Wi4m7njkZohFZ2rTCo9yBIJBKeo0jV1xeB/Y/249tz30KqlLJEkWfV7Naz8V7oe3qTGvrqWNn6qp7R+ffuIWbkKCgzM1liXN9+G77zf4CANhgzpnssQnahTIbofm9B+pTdEEfk5gbPSR8ztf4EYsOcS6uKZy4CSglALnrF9DpRAtD0mNMdixCwaAKQZPm1mvcvpPKi4t12NkJIxCKkl8n+69nAB2tGWH5WDg14biJg1INL3CWA1FIL0vL6JDeh4odW+ycB17aydX1tIDBwPSCwjo96Q8T0i5wXEEAAH0cf7fz+7zfAmcXsNSQL54PdQO3O2smiszmFQMGTJ4ju05elk/uoUfD5fJbGesZmxmLn/Z3Y92gfsqRZla5r4tUEQ+sNRQfvDjh5/CQzt2fPnpQA1Bhty5yoUCow8shI3Ei+wTLQS+KFxV0Wo6k3+zYJF1Go7BlN6rXFDBsORWoqS3Xnnj3ht3iRzt20uYgD1cm4CGQeO4bnn0xmNhHY2YE8rz3GjYXIycmgGxvizGFQhTQQRglADUCyginW8a3AChzJQxMtmgD843IcPtuj6jZFav0plIUsN/0xoS1a19K82xQPfUxV5jACfDy4cBhO86p2bRuw/2O2DiQDc1wEYGfYA695Da18d7PF9OlFwPFv2cqR7MHB24G6vbkMGdVNQwRIJ9LMQ4dLZ5MMkuBj4RBXr16hBELYRMZHYkfUDkQ+j6x0J3Jl843ab2BI3SGo71GfmWu2eNYQEzrN9Agk5iRi8IHBeJlf1DCuuXdzLOqyCJ4ST9Mro8OOFcW0NC4OMR8MgzyJXQPTsVNHBCxfDoEtbSSmA9wWvUT67Dls/f3U2khKLMQOHwFxYCC8Jn9S6XNaH5D4+IymBKA+HrectZQAtBxf8s0SiyYAx2y6hBNRqoMMyf7Lk6kK0UrEQng52+Obtxqiaz1vvvmO6msBCPDx4GIBsBvehISbRVd/y9ZeJNdOx50AvOsZfj8OSzRLTF9YXXT1t+wQCIGB6wCSgUmHRSBACIrHfd9gOpLa1qxZVEOqe3e11y3T89Px16O/sOv+rnKNZV4Fw9/JH0PqDQGp3eZKOqeXGWaJZ4vwlmUbcSXxCsYeHYtBdQdhRssZEPOozIa6mJYlJjLkn+zZM5bjHFq3RsCa1ZXW0rRsT1Pr1CEgffYMyUuWIvPwYdTauwf29Yt+MHl1kKvAhrrqW5En+PiMpgQgfV8RBCgBSOPAXAhYNAGYK5Xj33tJ+Pv6c4YIfCX5j4U5uQq84L0mcJUYpiaFuRxK9+UXAnw8uPALYRNom5cOrOkCpD1hb0au/Vph11lNY/ps/Fk09WoKB7GDfk5Sl3lJJL61HGg+XD/ZdLVJESiUy5F37RocWrWqcN/klSuZun9u772n9oslac5AavsdfnIYBQp299KyQskV8zC/sKJrvn4dICSEsZqhaTybFCi6GScQeJrxFDVda3JCF22UeDWmxbm5iBk+AtLoaJYY+yaNEbh+A0ROjtqIp3MtGAFFejpSVq1G2vbtIOQeGY7t2yNww3qzWc3HZzQlAM0WLpzamBKAnHKHVSlj0QRgiSdJJ+CeS07hUXJ2qXNJOS5SL75kNPZ3xV8Tw0CuCdNBETAVAnofXEgQx5wFgtpbTY05U/lGo30I/ruGAVEH2NNbjQPeWKiRCEubpElM30q+hRFHRiDIOYi5OhdcLVg3GO78BewZAxQW1XktHb1/Atp+pJtMusrkCJCrYtkREUhauIgpGl97/z7Y1amjsR5ShRRHnx5l6vvdTFaV/VAnwMXWBQNCBmBw3cEIcAmocg9N4rlKIXQC7xDIl+djzc01IJ3I9f6RgmPWl43pbm3bImnCRyiIYjfHs6tXD0GbN0Hkys6I5ZgpVB0TIaAsKEDatu1IWb26XHMYokLA2rVw6tjBRNqwt+HjM5oSgGYJFc5tShkHzrnEahSyCgLw37uJGLvlcoVOJWTgvolhaBKgfTdBq4kUaqhREND74EIIkN2jgODXgZ7zAJ8GRtGTCq0AgchfgGNfsV/0awGMPgzY2FklbFXFdEZBBlM/63n2cwYfiY0EX7b5Em+HvK0dXg/CgZ1DixrdlB2vzwE6zdROFp1tNgQI+Rc3YQJyTp0u1cGpSxcErPqtSp0SshOw+8Fu7H24F6n57KYFry6u516PyfbrU6sPE3OajqriWVM5dB5/EHiW9QzTTk5DVGoUetfsjZ87/czprr7aIlsS04KCAry2ew8KbrG71tvWqoWgbVth40HrY2uLraXNL1QqkXnwIHPdVxYfr9Y8obMzqs/5EqRLtDkGH5/RlAA0R6Rwb09KAHLPJ9aikcUTgOTLxTu/ncW12PQKffp+m0D8MKCRtfic2skhBPQ6uMjygRWtgPTYIovIFbYuXwCdKflhEhc/jQQ29wMKVXVFIXEHJpwCqlWdWWQSHc2wSVUxPfv0bByIZmdMkiybKc2naK5tykNgVQd2zUWyOmwq0P1rmg2rOZKcmJm8bBlSVrIJv8DNm+HYpnU5/chn+oUXF/D7vd9x8tlJKF/N/iyzwkZog55BPRnij3T1FejQibuqeOYEgFQJgyFw9vlZfHb6M5AfKkoGqfE3suFIg+1hbkEkpo8dPAi/DRvh8Mq1X7GfH4K2bzNawwZz20731xyBnPPnkfTzAuTfvat+kVgM9/eHwuOjj2Dj5qa5YAPP5OMzmhKABg4CnoqjBCBPHWcBals8AXju8UsMXXu+Qle5OYhxYnoXuDnS7mYWEM+8M0Gvg8uZJcC/X7NtHrQFaGCeX2F5B74+Cme9AFZ3ArITy0gRAMP2ACHd9ZHM+7VVxXRMZgxm/DeDya4hg3TQXN9rPQhZo/EgV6+PfwOQ90DJaDUW6LuQkn8ag8idiYrsHDzu1QuKl0VdVe0bNED1r+ZC0rRpqZLZ0mz8/fhv5prvk4xX6m2+Yoq3gzcGhQ7CwNCBendmrSqeuYMi1UQfBAixvP72eiy7ugyFKFMfBoCzrTMOv3O4XIMYffYz59rczEzcHT4Cjvfvs9Sw8fZmyD/bAOv9AcucfuHK3vkPHiBp4UJWVvarurn07QuvaVM5ESt8fEZTApAr0W5ePSgBaF78rXl3iycAh6+/gNMPUyr08Y/vNMKQ1oHWHAPUdjMioNfB5fZe4OiXQFZCkQVBYcCog5QAMbY/FXJgy1tATCR7p86fA11nG3t3zsvXJKZJc4YFlxYwddt299uN6o7VdbPr1ELgxHdAk6HA2ysBofpGDroJp6sMiYBSKmWadlSUhZe2cyderlkLr2nT4PJGXwiKffk4/TF+j/od/zz+B7ny3EpVal29NdPNt2tAV+0I5UqkahLPhsSJyjI9AoRcnhM5B8djj5fbvJZrLSztuhS1XWubXjED7yhLSkLO2bNI27sX+ZfYZXFE7u7MtV+72vy308CwWY040gmaZGNn/LUPUL5SV7cYBYeWLeH92UxIGjfmDC58fEZTApAz4WNWRSgBaFb4rXpziyMAHyRmgWT9vdHYF/HpeXhr+Stf0su4u2lANfz5f+0hpI0/rPpNYE7j9T64SHMAUofu7HJg9CGghipjxpx2WfTepOYfwbzsIDUYP9gDCEUWbbomxmkT0yl5KXpnaOH+kaKsS5EWGYSaGELnGAQBUkMq4++/kfzLMlSfOxfOr3dVK5d0AC5UKCC0s4NcKUdEXARD/F16calSPRxsHNAvuB+G1B2CELcQg+hcVog28WzwzalAoyMQnRGNqRFT1WaVdgvshu/DvoeTrZPR9TDGBsq8PORevoKcyEjmv4KHD9VuI3RxYRp+2Nevbww1qEyeIJA4/0ekbt6sVlvb2rXhPWMGnLp20amUgjEh4OMzmhKAxowI/simBCB/fGVpmlocAfjdgbtYf+YJ082XXO9NyZaqP/AIgL8ndcBrfrTDmaUFNZ/sMdjBJS8dkNAmNkb3fdRBYOf77G1c/Ivq/jnSgukEGIPFtNGdSTcwNgK5ly7hxQ/zUXDvHrOVbXAw0+FXYKOerCWE8J4He5jGHkm5SZWqRzKzCOn3VvBbRiVoaDwbO0rMJ59k/H155kvkyHJYSgggwOTmkzHmtTEQktq6PBmEbCfdfEmWX3ZkJPIuX0GhTFap9gKJBEEbN7Cu2/PEXKqmgRGQp6XhcY+eUGZnl0oWeXrCa9IkVHt3YIXPbQOrobU4Pj6jKQGotZstcgElAC3SrbwwyqIIQIWyEO3mH0dSVkGV4I9oF4Rv336tynl0AkXAmAjw8eBiTDw4LTs1GljdBShTHB5CMTDmCODfktOqm1I5g8c0qbcoywPca5nSDLqXARAgmX/xn81iSar+zTdwGzyo9G+k9tqN5BvYEbUDx2KOMdl/FQ1CxpDrveSab5vqbUySiWLweDYArlSEfggolAqsuL4Ca2+tLSfIxdaF6fob5hem3yYmWi1LLLrWy2T5nT0LRWrl3bDLqqWQSFDjl6Vw79TJRNrSbbiOQMqatUhevBgCBwd4jBkDj9GjIHR05LTafHxGUwKQ0yFlMuUoAWgyqOlGryBgUQTg2UcpeH/dhSqd7OFoyzT+cHUQVzmXTqAIGBMBPh5cjIkHZ2UTAmpdDyDxFlvFPguANuM5q7Y5FCsb0/4t/ZEqT0WPoB66qZLzEtjUF8jPAEbsB7zq6iaHrjILAiQj6em777G6SJLi8X6LFyFPnodD0YeYph4lDWEqUtLd3h0D6wzEe6HvwdfJ16S20Ge0SeE2+maku++sU7MQGV++PEw993pY0mUJ/J3J0ZibQ5mbi9zLl5ETeRY5Z8m13kdaKSp0doZ9q5Z44uqKrEaN0H3AAEgkEq1k0Mn8RSD32jXInj2Da79+ao1Q5ucj+ddf4T5yJMTe3rwwlI/PaEoA8iK0jK4kJQCNDjHdoAIELIoAvBOfgTWnonH0zgvky9QXsCU4LHyvCd5twd0DHo1W60GAjwcX6/FOGUv3TwKubWWb/tpAYOB62nTllYAoiek8ZR42KDYgIScB79d7H9NbToetSItu64T029wPSLhRtIODBzD8L8C3iVWGIF+Nzjl/HrGjRsM2JJipIZXarBb+ePAH/nr0F7KkWZWa1dirMYbWG4qeQT21ix0DgkWf0QYE08yiSAfyCccm4Hn283KavFn7TXzV7itIbLhFhhESPf/eveIsv7PIu1L1tV6WcSIR07DBMSwMjmHtIWnUCPkyGcLDw5lpPXv2pASgmePSFNtLnz5F0uIlyAoPZzL6gsOPwsbDMsqW8PEZTQlAU0Q99/egBCD3fWSpGloUAVjipC/+vIkdF+PU+qxlkBv+mNCONv6w1IjmmV1aHVyubAZkuUCrsYCIZq+azNXXtgH7P2Zv51kXGHcCsONncXhjYkdi+ujRo9iRuwP3ZEW138ho4NEAK7uthIdEgy8dpLnN1neAuPNsVWs0L8JdQI9NxvShprILpVKk/bGb6e5b9lrvq+szT57E9VqF+P3hHzjz/Eyl4u1EduhTqw9zzbehR0NNVTHaPK2e0UbTggo2BAKk1t8HBz/A44zHpeJsBDaY0WoG8yNFRR2qDbG3NjJkL14UZ/iRLL+zUKSlabMc4qBAOLZvD6ewMDi0aQORszNrPY1preDk9WR5aipSVqxE2q5dgFxVXsHtgw9Qfe4cXttWojwf45kSgBYRenobQU+yekNIBeiIgMURgMlZBejw0wkUyFUZgM52NsgqkIM0+z3wSUc0qOGiI1x0GUXAsAhofHDJTQWWNQPy0wGPEKDn90Bob0qEGNYd5aUl3ATW9wDk+arXxI7A+Ah6HbUC7ElMLz+4HFtytrBmNPNuhg29NsBGWEW3Xlk+8PsQIDqCvYNrADD6MFAtwNhep/KrQIDU7csKP4akxYsgi4kF6SIaEn4UomrsRkTkuuVfD//Crvu78Cz7WaVS/Zz8mKYe/UP6o5o9dxoaafyMplHDCwSeZjzF0INDkS3Lhoe9BxZ1WYQWPi3MqjtzrffSpdLmHdJHKoJSE8XItV7Htm1Ls/xsAyp/RtKY1gRVfs8hHaBTN2/By7VrocxhN7lhLLOxQfCBf2Bbsya/DeVp4zFKAPI+7AxiACUADQIjFaIDAhZHAP50JAq/nVQdnsQiAcKndcL+6/HMteDP+9TTASa6hCJgHAQ0Pogf+gy4uJqtxEeRQHXayMY4niGnynRgTRcg7Ql7C3Ltt9G7RtuW74JLMgCvSK/gsPQwChQFqGZXDbv77UZ1x+qVm6eQAX+MBO4fZM9z9C5qtuIRzHd4LEL//Pv38eTt/ixb3EePhs+sz5i/3X15FzujduLQk0OM/ysbpNkCyb4KqxEGkVDEOXw0fkZzTnOqUEUIRMRGYMPtDQz55+1g+jpnzLXeuyXXeiORd/Vqld16WbaQa71Nm8KxfTsmy8/+tde06tBKY9py3xuFCgUy9v+N5F9+gTwxUa2hIldXeH48EdWGDIHQVouyHByFjY/xTAlAjgaTidWiBKCJAafblSJgUQRgRp4MHX48wWT7lYzBLQPw07uNqcspApxEQKODS2YCsPQ1oGx3zIbvAO9t5KRNFqFUYSGwaxgQdYBtTuvxQN8FFmGiPkaQTq2kntaDtAdMPa2xjcaWiisb07Va18LcC3Mxo+UMdPTvWPmWSiXw13jg1m72PIkbMOoQ4NNAH5XpWgMj8GzaNGQdPqKSKhbj6eYvsP3FAaarb2XD2dYZA0IGYHDdwQh0CTSwZoYVp9Ez2rBbUmkGQEBZqATpGl3RqOp1A6jAEiFLSCit45dz7pzW13ptg4KYGn6klp9D69blrvVqoy+NaW3Q4s/c7NNnkLRwIQru31ertMDWFu4jhsNj/HiIXCznJhQf45kSgPx5XxlTU0oAGhNdKrsyBCyKAFwR8QgLjqo++EiZqOOfdkZtL1qni74NuImAxgeX2PPAkdlA/FVAZAd8chmoxu0vztxEXEOtIn8Bjn3FnuzXsugKqg3/fzHXEAW108gVunf+fgcypaz09bNDz4KQOmS8GtNiO3HV134J4XpgGnDlFVKbyBz5N+DXXB+V6VojICCNjcXjN94EZDKkh3hjXScpLvpkV7pTXbe6TFOPvrX7cq7ZQkWKa/yMNgLGVKT2CJDr6bsf7Eb403D81v03iM1UL5dcu3k/ydcAACAASURBVMwpvtZLOvZKH2t5rdfFBY7t2jG1/AjxZ+tvuMZ1NKa1jysuryBNYpIWLGQIZvXMnwCub/WD15QpENeowWVTdNKNj/FMCUCdXG1xiygBaHEu5Y1BFkEAkrp/TnY2TO2/lznSUvDfaOyLFe/TL468iUYrVFSrgwvJkCLZUTnJQPtJVoiWiUx+GlnUfbZQodpQ4g5MOGXR9efIVc3o9Ggmq4/890mzT2BvY18OdJlChtbbW0NeqMq03tJnC0iNP3UEoERSRVdNQv6FzwHOLWfvRbpxDv8TCGpvIsfTbcoiQGpI5V68CKfOncsBQ0iWiy8u4t6yH3C+MBqR9QorrEdKmiz0qNmDIf6aejXlTKMFTb2t1TNaU6F0nlEQIM+weefnMR2mySA1Jb9s+6VR9npVKHOt987d4iy/SOReu8aQ4xoPGxtImjYpbd7BXOsVGedKPI1pjb3C6YlKqRQv5n6FjL//BsjnqJrh0K4tfGbOhH0Dy82g52M8UwKQ028tkylHCUCTQU03egUB3hOAWXIB2s0/AV9XezxLy2OZd+CTDnjNz5U6nSLAWQT4eHDhLJiGUCzrBbC6E5BdtnaOABi2BwjpbogdOCkjX56PdjvasUi9XW/uYjr3qhsD9g/Ao/RHpS/NaTMHg+sNZv6tdUyf/BE4OZ+9jcgWGPq7RWPOyUAA4b0VyNi3D8m/LIM8JQW1//kbdsFFtRezpdn4J/ofpr5fdEZ0pSaQ2mrvhb6Hd0PfhafEk6vmVqmX1vFcpUQ6wRgIJGQnYNrJabjz8g5L/Pdh3+PtkLeNsSVU13ojkXP2HBTp6VrtQxowMBl+HYqv9TqZ5rYKjWmt3MTpybFjxyHnTPnO6nahofCeOQOOHTrw7kcXbQHnYzxTAlBbL1vmfEoAWqZf+WAV7wnAnVdf4Jt/7pbDunVNd/zxUTs++IDqaMUI8PHgYrHuUsiBLW8BMZFsEzt/DnSdzUuzc2Q5eJj2sDSrb1TDUfB3Vn+VrO+ffRGXFVdq53dh3zEdWdWNWadmMQ0eCMkT6haKd+u8i25B3bQnAM8uB8JfydARiIBBm4H6/XiJOZ+VJllMT4cORf6Nm6VmOHXtCun86fg96nf88/gf5MpzKzWxVfVWTOZV18CuEAvFfIZD+3jmvbX8NOBiwkXM+G8G0grSyhkwofEETGpmmIx55lrvxYsM2ZcTGQlpdOUk+KvKCF1di7v1todj+zDY+vuZBXB67jAL7EbZlGnI1H9AaQagjbc3c9XXtf/bRssgNYohegjlYzxTAlAPh1vQUkoAWpAzeWYK7wnAIRuu4kZc+V9dRULgs171MKEz7RrJs5i0KnX5eHCxWAeRmn+k9l/ZEfw68MEegIPdSTXxQ7c/uiEpL6l06oLOC9C7Zm+1S6dGTMXx2OOlr41oMAIzW81UO/dFzgumhpurXfkMa41jOuogsPP98vIHrAaaDNHEPDrHCAgk/fILXv62iiX5fx+IcC+w4qMqiYW3gt9imnrUcatjBK3MJ1LjeDafila7M7mKvuXuFiy+shikqUfZQWKS/IjRq2YvnfEh2bD5d++C1PAjhF/u9es6XeslnXpJ8w77hg05QcrQmNY5JMyykMQ5GQJS2FzNiJ/9BbLCw+ExbhzcR46AsKqyG2axwnib8jGeKQFovHjgk2RKAPLJW5alK68JwNYdu6Lv8vNIy1VfZ+XXoc3Qr4nlFby1rBC0bmsqPLjkpgIO7tYNjimtV0dGufgX1f1z9DClJlXulZ6fjofpqqy+t4PfRnMf9bVOPzr2ESLjVRmN4xqNw+Tmk9XuseL6Cqy6sQr+Tv5MVh/J6COkjrZD48O4NBf4Yzjw6F/VFm8sAlqpOgpruzedrz8CSSmxSOjbH7aZRSU1btQUYHN3IZ55lT+q1nSpiSH1hjBxUtIERn8NuCVB43jmltoWr02uLBdfnf0KR58eLWdrkEsQlnZZihC3EK1xkMXHM3X8sgnhR671ZmRoJcO2Vq3ixh0l13odtVpvisk0pk2BsmH2yL10CYkLFsLjww/h0qunWqGkVAMEAth4cOusYhgEqpbCx3imBGDVfrWGGZQAtAYvc9NGXhOAPXv2xL/3U/HJzuvl0G0f7IHtY9tYfO0LboYV1UpTBNQeXFKfAL+1B5p+AHSZzTkCSlPbeDMvNRpY3QUoKPNFj1xdHHME8G/JOTNGHh6Jq0lXS/Wa3GwyxjUep1bPxZcXY+MdVWfdLv5d8Gu3X9XOzSjIYLr1Oor1+8Kq1WFcXgDs/RC49w/Q41sgbArn8LZEhRTZ2RA6OpZ+PpIMkxvJN5hrvuEx4Xj9khTdryuxrasQN2sLWRAIBUKQOCLEX1vfthb/GatVPFtisHDQppjMGJCM5bJ1SEvUJLE5r+M8uNi6aKS5IjuHaXZDSD/mWu+TJxqtK5kkcnWFA+nWG9YeTu3bQ+xnnmu92ihNY1obtMwzt+DxYyQtWozsEycYBcRBgQg+cAACMf/LKhgaUT7GMyUADR0F/JRHCUDu+i0IAEmXeANAAIACAI8B/AFgBYDKi+FoblcfAOMBtALgBSAZwCUAawAc1lyM1jN5TQD26NEDg9Zdwe34TJbhNkLgyNTOCPE2TUFlrVGnCygCxQioPbjsGg7c+7tohr0r0HUO0IY8HugwOAKyPGBdDyDxFlt0nwUmxTwlLwVRqVGltfo6+nXEG7XJx075Qbpc7ry/s/SFPjX74OfOP6udS2q2zY2cC5KpRbL6WlZviUF1BxkcxrICtT6Mk9qL9w8BDbTPNjSqIRYonHSNTNu+AymrVqHGj/Nh07EtDj85zDT1uJd6r9RiobIQ5NJZoVB1PHWzc8PA0IEYFDoIvk6+FoiOepO0jmerQcY8hv4X9x9mn56NLFkWSwEBBJjYdCLGNx4PQlJXNJhrvXfuFBF+Z4qv9cpVHc2rtMrGBg7NmjGEH3Ott0EDTlzrrVLvMhNoTGuDlmnnypOTkbx8BdL37AEUCtbmPnPmwH3YB6ZViAe78TGeKQHIg8AygYqUADQByDpsQSqQbwNQ0c+ID4qJQVUrRO03IacUQvJ9WMnSdQAmAGAXONF+L3UreE0AOga3wNhtN8rZ9VHnYHzep55hEKJSKAJGRKDcwSXxKrCpL3vHth8DvX8wohZWLHr/x8A18pgvM14bCAxcz1ypMdUgJN2+R/tKtyPNN0j9KnXjj/t/4LvzqteCXYOxr79qbdk1pLsvqRtkJ7IzlSnadwE2mWbWvVHWiQgkzpsH2fPnDBBZftUwfYwA6XI2kfIqSo09GzPZfj1r9jRpHHHFW3z8cskV7AypB6nxR0oU/Hbjt3JiyfXzHzv+iE7+ndRuSWKeXOllmnecOwelttd6a9cuvtbbHg6tWkPkpF+WtCFx0UUWjWldUDPuGtJg5uXGTXi5YQMKc9XnlkiaNUPQju0Wn3WtLdJ8jGdKAGrrZcucb7pvGZaJnzGsagaAFE6SAMgGMB9ARPG/SXXykvtWhAQkd8QqP0FXrCGR+3nxy9cAkDQOkmFIOld8BoDoQQaZ94URDOU1Abj5mQeuxrHrs/i62OH4jC5wsLUxAlxUJEXAsAiUO7jc3QUcngXI84s2krgDk68CEjfDbkylAVe3An+/0h3Ssy4w7gRgp3/2cHJuMm6l3CrN6qvnXo/JTlE3tt7dip8vqbL4Gng0wK43d6mdez3pOj48+iGCqwUzDRfqu9fHsAbDOONRtYfxpCjA1d8guHLGUJ4pkrZ/P17MKjluFCm/uo8Qx5uWz5ayFdqiT60+GFpvKBp6NuSZpYZVl49fLg2LADekrby+Ui35R56BpN5foEtgqaLkijtzrbe4eYf06VOtjCDXepkMv/ZF/4lrWFYtaRrTWoWDUScXyuVI3/snkpf/CkVyitq9RO7u8Px4ItwGDaJXgNUgxMd4pgSgUd9WvBFOCUDuueo/AOSnRHIvgPzvuVdUJK0RS76tfQPgax1MCAVwBwBhqi4X71NUdbtoOAAgehCCkejRAMBDHfapbAlvCcAnWcDS2+VJvt8+aI4+jaznepKB44GKMzECag8u6bHAv18Dt/cCJr6KamLzzbddwk1gfQ8V0Uo0IbXvxkcAXnUNote6W+vwy1VVV+Hm3s2xuc9mtbIvJFzA2HBV8wuSsXf+/fNMTb5Xh0KpALmgqe41gyiup5ByMZ0VA2zsA3iEAB/sBiTV9NyBLtcGAVLbkWSX/nFvJz7+9SlqJapWH24hwMaeotI/+Dn5MVfEB4QMgJs9/dGBAMPHL5faxAdf5qbmp2LwgcEgHchLBil/8HX7ryER2iH/9u3iLL+zyLt+A9DmWq9YXHStlxB+zLXe+ry71quNH2lMa4OWceaSuqvZESeRtGgRpI9J3kf5IbC3h/uokfAYOxYiJ/1/lDSOJeaXysd4pgSg+eOGCxpQApALXlDp0BrAheJ/rgbwkRr1yE/mtwHUB5AOwBuA+la0Fdu2EsD/Fb/cDsB5NVPbliEfyfyPDQwVbwnAZXeEeJzJzlwIC/HAtg9p4w8DxwgVZ0QEKj24PL8CVG8MiGjRZ4O6IC8dWNMZSHslK4Rc+230bqVbkVp9l19cLs3qq2ZXDd93+F7tGlKratIJVYahs9gZkUMj1V7fIV9u++ztw2T0kVp95L8BdQbw8spl2Zju1SoU9jv6A9nFX9qrNwKG7wMcPQ3qUiqsPAL3Xt5jakUeij6EfEVRRnGjJ0rM3anEPX9g2+siPPQrOn6G1Qhjsv06+HWASKgiBCmulADkUgzcSbmDEYdHQFGowOcBY9AryafoWu/589pf6w0OLr3W69iqFdMUx1oGHwkTS/JN3q1bSPp5AUiHX7VDIIDrOwPgNXkyxD4+lmS6UWzhYzxTAtAoocA7oZQA5JbLSLGt2cUqEQKuhAx8VUtyl4ZczSWjF4BwLcwgPn8GgNwriComEitaTl4nKSmkcA9pREJqcxtq8JIAHLfqGM4ksr+kiAQC/Du9M2p5Ws8hzlBBQOWYDwE+HlzMh5YBdi4sBHZ+ANw/yBbWejzQd0GVGxx5egQz/yMJ4EXDS+KFE4OKuvS9OhKyE9Bzb0/Wn8MHhlfYQIHUuKqseH2VynFkQklM20tT0SNuIYSZ5KOuzGgxCuinyozkiNq8V4PUkEpatxYPBUlYHRLLdPVVN+rGFeK+P+Bs64L+dfpjcN3BCHIh/c7oUIcAfUZzIy6Ya70XLuDOoe1wvhEN4bMyqawaqCiqVk1F+JFrvb7We1OExrQGAWOkKdmnTyNuXMVN3Rw7dYT39Bmwr0suidGhCQJ8jGdKAGriWcufQwlAbvn4FICOAHIAkLtKFbUHI1l7Z4tV/xbA/7Qwo3ZxrT+ypKIswxJx5PWSTwuy7okW+1Q1lXcEYEZWDprNi4AS7LfNhE61MbsvScikgyLAHwT4eHDhD7pqND2zFPiX/ahO82uO050/wYOMaCazL1eei219X2kMUiwqOiMab+97myX4v8H/wd3evdxm5IpP3z/7MoRfSVZft8BucLVz5TWEVSlPYvrkwT3o8HAenAsS2NP9WwPD/6K1AKsCUYvXSQ2p2O0bkLZyFewy8pBtD3zykQg5EvVHSxKLJNuvb62+cBCTSiN0VIYAfUabNj5e5r2EWCSGs9ChzLXec8i7fr1cV9RKNSPXeps3Z1/rFVbcHdi0Vpp3NxrT5sO/UCZD9Jv9II2JYSlh16A+fGbOhGM78tWSDm0Q4GM8UwJQGw9b7lxKAHLLt8kAyP0k8vN500pUIwVyUotf3w1gkBZmvAngn+L50wAsrWQteX1x8etvADikxT5VTeUdAfjD/G+xJqMFBmTthG1h0a3rWtJH8HERQSwmPVvKj4KcVBQqVImTDp5+cA9UX9g8/lYElDLVbW6xxAGiCuRKc9OglKuaM9tX84Rn7eZqdUi48x8UBQWlr4kk9hCTmmNqhjQvA0qZine2c3aFV502aucmRp2FLJf0qSkaIns7iG3V1wqR5mdCKS1jm4MjfOqFqZWb/OgiCjLJ7fZiubZiiO3VN8SWFWRBUSBVzbWzh29D9d34Xj65irw0VaFjgdgGdhL1hIhMlgNFXnEzDABCsQ1qNHpdrb5pcbeRkxxf+ppAJIKdo/paY3JZLuR5qnKbAhsh/Bp1U9v1NTPhITITVJy7QCSEnaP62lgKeR5kZbq3CYQCBgehuHwH1uyUGKTH3mfyeRUKOXILxfBwc4NQWP7jQKqQIztbFTtMzDdsDrF9eT/nZKbi+UNSnUA13FwkEAjKf/GRK5XIzCpbdhQIqNMQEhePchhL83Px9A4pVaoars4SiNR8oSKZbOmZbLm+QSFw9lRfSP3BFfKbi2o4O9lDLFJ/DTE1M4eVA+1ZIwDuvrXUxsTDa2dQqFS9P50chKghK+qAWjKUEOGaRwhOCV/AtsxPPYPs28CrHim/yh6KQiV+vbMKYrnqedJK7oMaUP+ek7zMg0hWpoF7oB+qNSaJ5eVHxqljKMzMLH2hwNkWMkf117/t0/JhU6AonVvo6wW3Furfc5nnI6BMKfmoAqSOYkidbdXqYJdRAHGeCohCD1e4teuudm7W1bNQxKsIPpnEBgWudlAWFkKR8hhipeq9a5srgK3CHnALBoRCKF0c4d5G/bMn+8E9yGPiSveU24uR76H+WSnOzoddhmofhcQOHh06q9U392k0pA8flb6msBUhz8tZ7VybXCns01SdGBViETw6k2dE+el5z+NQcPeeKqZshMj1Uf+sFOXLIHlJflssGkqRAK4du0AkLu/ngpQk5F27rvKxUIAcX/azUgYFkpNi0COcHFtU43xd4EQT1XteJBChmXczdPbvjBpiL8TeOK3Wbk3+6NegNZzdSNUT9pAVFODx5WOaiFA7x6dOE7h5k0sO5UdU5AGd5XrUrAcvvxC16x9cCIdSrvrsUjdJoVAgPqEozmv4+kJU/Gxy9asF35rqzxGPr0ZAlqfyszbKO3v7wa9OSf839sqnNyORn5WmjbjSuQ5u3ghsQCrclB9x9y4iJzVJJ7l2ztVQq3EHtWvjH99E5otYjeVKFTLcfHgadZJt4PdCVmE31IoE2vj6wr5BA6aGn11oKIR25T97BTY2DCmobsji41HwSPWM0Fjx4omOHTuqLfEgT05G/j3VM0JbuQ5t20JoW/6ZrUhPR97Nm9qKQ0GBFFevXkVerZro0a8fJBL22ZlkE+deuaK13JIF9o0awcat/DmpUCplrmvrOuzq1YPYu/yzh8jLPsU+R2izh23tYNj6+6ldQrpGE9JOlyEOCIBdrfLnk8yj4Xg+ZQoj0qaGL7ynToXLm29CQAlqXWDmZZ1WSgDq5GqLW0QJQO641J7UfC5Wh9wRI0RdZYMwL+SbCflE0+ZnG1JX8Ldiwe8B2FPJJqQoFSEYySDrSEagpoMQfJWN6gCYIhQPHjyAv39V0zXd1njzxo1fgjN+TbArfAZcVN/P8Ky2HP7R6jv/vnQFPMo0C46pI0fQQ/VzX3gUovpL1VvySV05at1XP/eZTyH8E1VzH9eTIzhK/dwYv0IEPVfNfVhfjjr31M+NDixE7VjV3Af15QitYO6jWkqEPFF90XtQT4HQKPXkycMQJeo8KjO3rgKh99XPfRCqQOgD1WsP6igQ+lD93Pt1FahbRs7DYCXqPFb/S/uD+gqE3lPJeVxTieCn6uc+rK9AnTJznwQUolac+sflo/oKhJSZG+tbiMAE9XNf9VO8VyFqJKuf+7SuHDXL+D/RvRA+qernxtaRI7BMXKU6A+4V9Ad/XlsOvzLxSrJ2nFQ8BusN9MwD8H+p+pPUBiyyquzkF65AdXZjbBD6SR3CqU6Au4o7ZsTkiQGJmrNulj3g/Ip+GRLAlc3zMTKkIsBWxU0xf0txBjwrwOJV/RLcAN8KvuO+ql+sJxCovnEeMiWASxn9nngDtdR8xyX6pjkBPmVwe+4O+Kk4M5Y/klwAbxVPh1xbwKFyDsF4D0QqmSJAEaAIUAQ0RkDo6orAkxFq52f+sRup80sq+2gssnRi0JXLakmcnH+PI3mmqnSEtpID/j0GkUf5H+byr1zBi7HjtBVXOv/p1KloO3gQ7O3JV58yZ4zoaMQPrLwebmWb+qxeBUnr8mQzISzjuqr/EVcTI7x+nA/HXqTiUvnxtHkLgJT40GG4f/YZXIYOUbsytlt3KFMrOAxUsZfruHFwm1hS6l01mdwOSJo8BfatWsJ58GC1RLUOZljtkvz8fJwqJoA7depULp65CAwhAENDS695k1++XqmVwkWtqU6GRoASgIZGVHd5XgBKviLuAqD+E0ElnxQhIT9HkZSbRlpsW7aLcB8ARypZS14vyfqbAWCRFvto/Gm4bt06eHpyuzB7egHgsPQ3RAS0wMiHf1ICEAAlAIveDZZAALrbyiDNLJ8JRAlA1RPPGAQgkf7SGfAoQ1BerwU0NWSxBS0e2nQqRYAiQBGgCJRHQCkSIb9mTRQKBHDUMVNP4eCAx//7Si28rufOw2ffPp2hfzD/BybD+dXhdOsWamzbrrPcx3O+hMK5fLayJDoaAavX6CyXEIBSX5IHwB62iUmoubjk4pH24uPGjUVeSPmsW2FODkK+/e7/27sTYEuq+o7jv9n3AWaGGWCAERTiEkuJQLnAAGpQIWhiiApGpIS4RCNaRgETCnABMYmJEXFFRSEaiDGJKIooi6IoJGpwC6KyDsMsLMPsvDcv9X+cy/Tc6bu+7tNn+XYVpbzb9yyf//9d+v1vn9ODN+jeseLEE7T+Gc8off8BZ5ypSUMWAFe99Dg99LzyO9L3f+/7NHV92zelfc5g7Quer7VH77gP8ONvtbFO4s//PimTO23NmjU69dRTW/OiAJhchPubEJ8A/Tn5OMt+CVvrFb4g6aQendq59h57hnv5GpPyBs6SZPsG2vECSeW7yD/2un1d9m13rr2v/JGT5f0kVQD8xt2T9JYLTx+/m2ndbFEApAD4eNanUAA8+KUrdNf1C7Xx/h2XLVEA3P7hVlcBsP0Ox7I7Hn38B4g+EEAAAQS2C2xZskQbDzhAGw44QJv2309j06drwTXXaNG3rhmKiQLgdjYKgI9ZNFIAHCp7eVMqAhQAU4nkxOZBAXBiflW+O7U7AHut6Y1qCbDtWfa/Rx08vgfY5pljmrl5+6/OQ3uNaNcV5UtqN8wd05z12899YOmIFtxbfu66XcY0/+Ht567de0QL7yk/98EFY9qtsBx0zb4jWnRXh2XIu2/TwtXbvxletWxEi+8sP3fNkm1adH/h3H1Htfiu8uW3q/cc1e73bX/t/n1HtaTDuauWjmrxvYVz9xnVkrvL2121z6gWF15btfeoFt9Tfm57n+39FH9BV7XNpX38O547osUFz7WLt2nhqvLlwqv3HdHuhXMfWLRNC9aUn9sep4d2G9OuD5Z/DD+w94gWFOL/yPwxzVtXfu6DS0e0WyGvNs4e0+yN5ec+vMeIdlm5Pf5bZozpgGWP6K7b7Fv+Hd8zvny2sOR0ZIo0tbCtXNHsgdnSgratp8aX2JYMY93MHZfIWjtbpkkzSh57tHHazstcN8yQ5pQsfX10sjStbQnww7PLlwtbn+NfhBcmMb40ucP2WePLiwvjWz1f2r3D0uLxpbmFrRNX7lpYHt321ci8jdLkws82zJRGppfn+7z1o5pc8N84Q3q0/FdZczdJU9rPnVHe7pwNo5pacNs0XdpavgWg5mzWzufOLG939sZRTSuYWYw3l28BqFlbdvQdP3dWebszN41qRmG5uC1N37TzllvjkZ25VTuca14bZ5e3O2Pz6Pj5rePRKdLGHVeoPf6a9V881343Nswpb3f6ltHx+bWO0cnS+vJtY8e9irkzfu7c8nanbR3V7MLy+G2TpUc6tDt1RJpTGMPYJGnd3Mmld4LY3pFzN21PyvFzS57ZYXlrvxPTH5UmFXJ4ym67acr0nQMy+ugWjT4w3D5yZjdpl/maNnPngWwbHdHImg7r8fu5Sps3R9Nnl+/JuPX+lf20UHrO2JxZmjG3fJ/ZLatXalKHz9JeHY7NmqEZ88v3g92y5n5NKuw73Kut4uvbZkzTzF13Xu5p52xeu0qTC/sOD9Tu9CmauZtd4u58bH5wjSZv7fS8u+69bJs6WTMXlu/LtvnhtZq8ecD90+w/BlOnasZeS7XHJz6hqSV7vj182WVaN+QddZPnzdXSyy8vndT6K6/Ugx+9aBDWHc7d+2tXli4B3vjd72nteecN3e5el12mKQt2zrUtt96qVe86feB2bQnqls2bdc+pp+g5xx+/05LJR++8SyvfaDsODXfsfv55mvnMnbdQH123Tite2WthVec+F55xumYfUb7H690vOWa4wdrTHt/4Bs172Y4P92o1tuKEE2VLl4c55p9wgnY56TXDvJX3DCDAEuABsDg1KAEKgOGEI7U9AHvJRvcQEHva0ze+ebV+8eAkvfLFh+lJe+789M1ek+Z1BEIRiPHpZaHYMY4wBcjpMOPCqIYTIJ+Hc+Nd4QqQ0+HGhpENLhBjPvMQkMHjnOI7KACGFVWeAhxWPHYYTYwf9AFzMrSGBcjnhgNA95ULkNOVk9JggwLkc4P4dF2LADldCyuNNiQQYz5TAGwoWQLrlgJgWAGxZ8kfLskWoe0qqdO6CHvq7/fd0G0/v7MHmMb+bt9Ae4s91bfbvfb2+utd2/a+Kremj/IOwKuvvnqc4+ijj9asWR3WWg0QDE5FoCmBGC9cmrKi3zgEyOk44sQo+xMgn/tz4qx4BMjpeGLFSHsLxJjPFAB7xzWHMygAhhVl26jjTDekZ0v6YYfhnSHpfPeaPZf+sapUf4fF3B75vZekX0l6Spe3/VLSkyXd6x440veDPfoYCgXAPpA4BYG6BGK8cKnLgnbTECCn04gjs3hMgHwmE1ITIKdTi2je84kxnykA5p2zrdlTAAwrDw4tFP063Z1nTxf4mSvckAXK/wAAIABJREFU2e6wtgPygDsdy3YafpObut1NeFMJgxUgf+B+bue/uWIqCoAVg9IcAoMIxHjhMsj8ODc/AXI6v5inPGPyOeXo5jk3cjrPuKc66xjzmQJgqtk42LwoAA7m5ePs1jJgW/67vFCEa/X9TkkfdP9yrqRz2gZ1pKRr3c8ukXRyyaAPlPRze96ZpFtcP5sK59naVhvHwW4Z8lMl/briyVMArBiU5hAYRCDGC5dB5se5+QmQ0/nFPOUZk88pRzfPuZHTecY91VnHmM8UAFPNxsHmRQFwMC8fZx8k6UZJVoRbL8mWBVtBz/7dnmHf2pPvNlege2SIAqC9xZYQ21JiO34s6QK3N+ATJZ0uycbROu/dNUycAmANqDSJQL8CMV649Ds3zstTgJzOM+6pzpp8TjWy+c6LnM439inOPMZ8pgCYYiYOPicKgIOb+XjHcZIulTS/Q2dW/DtW0u0lr/dzB6C9zZYSf0rS67pM6GJXcNxWw6QpANaASpMI9CsQ44VLv3PjvDwFyOk8457qrMnnVCOb77zI6Xxjn+LMY8xnCoApZuLgc6IAOLiZr3csk3SaK/RZsWyrK/hdIelCSRs7DKTfAmDr7ce4It8hkhZJWiPpZveE4KtqnCwFwBpxaRqBXgIxXrj0mhOv5y1ATucd/9RmTz6nFlHmQ06TAykJxJjPFABTysDh50IBcHg73jkxAQqAE/Pj3QhMSCDGC5cJTZg3Jy9ATicf4qwmSD5nFe4sJktOZxHmbCYZYz5TAMwmPbtOlAIgedCUAAXApuTpFwFJMV64EDgEugmQ0+RHSgLkc0rRZC4mQE6TBykJxJjPFABTysDh50IBcHg73jkxAQqAE/Pj3QhMSCDGC5cJTZg3Jy9ATicf4qwmSD5nFe4sJktOZxHmbCYZYz5TAMwmPbtOlAIgedCUAAXApuTpFwG+iScHEhSI8WI8wTAwpYoEyOeKIGkmGAFyOphQMJAKBGLMZwqAFQQ+gSYoACYQxEinQAEw0sAx7DQEYrxwSUOeWdQlQE7XJUu7TQiQz02o02edAuR0nbq07VsgxnymAOg7S8LsjwJgmHHJYVQUAHOIMnMMViDGC5dgMRlYEALkdBBhYBAVCZDPFUHSTDAC5HQwoWAgFQjEmM8UACsIfAJNUABMIIiRToECYKSBY9hpCMR44ZKGPLOoS4CcrkuWdpsQIJ+bUKfPOgXI6Tp1adu3QIz5TAHQd5aE2R8FwDDjksOoKADmEGXmGKxAjBcuwWIysCAEyOkgwsAgKhIgnyuCpJlgBMjpYELBQCoQiDGfKQBWEPgEmqAAmEAQI50CBcBIA8ew0xCI8cIlDXlmUZcAOV2XLO02IUA+N6FOn3UKkNN16tK2b4EY85kCoO8sCbM/CoBhxiWHUVEAzCHKzDFYgRgvXILFZGBBCJDTQYSBQVQkQD5XBEkzwQiQ08GEgoFUIBBjPlMArCDwCTRBATCBIEY6BQqAkQaOYachEOOFSxryzKIuAXK6LlnabUKAfG5CnT7rFCCn69Slbd8CMeYzBUDfWRJmfxQAw4xLDqOiAJhDlJljsAIxXrgEi8nAghAgp4MIA4OoSIB8rgiSZoIRIKeDCQUDqUAgxnymAFhB4BNoggJgAkGMdAoUACMNHMNOQyDGC5c05JlFXQLkdF2ytNuEAPnchDp91ilATtepS9u+BWLMZwqAvrMkzP4oAIYZlxxGRQEwhygzx2AFYrxwCRaTgQUhQE4HEQYGUZEA+VwRJM0EI0BOBxMKBlKBQIz5TAGwgsAn0AQFwASCGOkUKABGGjiGnYZAjBcuacgzi7oEyOm6ZGm3CQHyuQl1+qxTgJyuU5e2fQvEmM8UAH1nSZj9UQAMMy45jIoCYA5RZo7BCsR44RIsJgMLQoCcDiIMDKIiAfK5IkiaCUaAnA4mFAykAoEY85kCYAWBT6AJCoAJBDHSKVAAjDRwDDsNgRgvXNKQZxZ1CZDTdcnSbhMC5HMT6vRZpwA5XacubfsWiDGfKQD6zpIw+6MAGGZcchgVBcAcoswcgxWI8cIlWEwGFoQAOR1EGBhERQLkc0WQNBOMADkdTCgYSAUCMeYzBcAKAp9AExQAEwhipFOgABhp4Bh2GgIxXrikIc8s6hIgp+uSpd0mBMjnJtTps04BcrpOXdr2LRBjPlMA9J0lYfZHATDMuOQwKgqAOUSZOQYrEOOFS7CYDCwIAXI6iDAwiIoEyOeKIGkmGAFyOphQMJAKBGLMZwqAFQQ+gSYoACYQxEinsEzSHTb2H/3oR9pzzz2Dn4Z90N9www3j41y+fLlmzZoV/JgZIAKdBMhnciM1AXI6tYjmPR/yOe/4pzh7cjrFqOY7pxjz+b777tOhhx7aCtoTJN2ZbwTznTkFwHxj3/TMD5Z0c9ODoH8EEEAAAQQQQAABBBBAAAEEMhI4RNItGc2XqToBCoCkQlMCFACbkqdfBBBAAAEEEEAAAQQQQACBXAUoAGYaeQqAmQY+gGnPkPR0N47VkkYDGFOvIexRuGvRPjRX9noDryMQsAD5HHBwGNpQAuT0UGy8KVAB8jnQwDCsoQXI6aHpeGOAAjHm8xRJuzvLWyVtCdCVIdUsQAGwZmCaT0rg8QeXSNpH0j1JzY7J5CZAPucW8fTnS06nH+OcZkg+5xTtPOZKTucR51xmST7nEunE5kkBMLGAMp1aBfigr5WXxj0LkM+ewemudgFyunZiOvAoQD57xKYrLwLktBdmOvEkQD57gqabagUoAFbrSWtpC/BBn3Z8c5sd+ZxbxNOfLzmdfoxzmiH5nFO085grOZ1HnHOZJfmcS6QTmycFwMQCynRqFeCDvlZeGvcsQD57Bqe72gXI6dqJ6cCjAPnsEZuuvAiQ016Y6cSTAPnsCZpuqhWgAFitJ62lLcAHfdrxzW125HNuEU9/vuR0+jHOaYbkc07RzmOu5HQecc5lluRzLpFObJ4UABMLKNOpVYAP+lp5adyzAPnsGZzuahcgp2snpgOPAuSzR2y68iJATnthphNPAuSzJ2i6qVaAAmC1nrSWtgAf9GnHN7fZkc+5RTz9+ZLT6cc4pxmSzzlFO4+5ktN5xDmXWZLPuUQ6sXlSAEwsoEynVgE+6GvlpXHPAuSzZ3C6q12AnK6dmA48CpDPHrHpyosAOe2FmU48CZDPnqDpploBCoDVetIaAggggAACCCCAAAIIIIAAAggggAACQQlQAAwqHAwGAQQQQAABBBBAAAEEEEAAAQQQQACBagUoAFbrSWsIIIAAAggggAACCCCAAAIIIIAAAggEJUABMKhwMBgEEEAAAQQQQAABBBBAAAEEEEAAAQSqFaAAWK0nrSGAAAIIIIAAAggggAACCCCAAAIIIBCUAAXAoMLBYBBAAAEEEEAAAQQQQAABBBBAAAEEEKhWgAJgtZ60hgACCCCAAAIIIIAAAggggAACCCCAQFACFACDCgeDQQABBBBAAAEEEEAAAQQQQAABBBBAoFoBCoDVetIaAggggAACCCCAAAIIIIAAAggggAACQQlQAAwqHAwGAQQQQAABBBBAAAEEEEAAAQQQQACBagUoAFbrSWsIIIAAAggggAACCCCAAAIIIIAAAggEJUABMKhwMJiABZZJequkYyXtI2mLpN9IulzSRyVtDHjsDC0PgcWSDnX/HCLJ/lnopn6JpJMHZHiJpNe7dnaXtFrSzZI+KemqAdvidAQGFThY0jGSDpP0VEmWg49KWiHpRkkXS/reAI2SzwNgcWrlAvNdPtvnsuX2UpfTsyQ9JOkXkr7u8nptH70/V9JfSjpc0hLXxk8lfU7SF/t4P6cgUJfAByW9s9D4UZKu69EZn891RYN2+xUY6/PE6yUdST73qcVpQQpQAAwyLAwqMIHjJF0qyS7gy47bXGHw9sDGzXDyEuh28TJIAXCyK/Kd0oXv05LeIGlbXsTM1pPADa6w0au7L0g6VdLWLieSz70Ued2HwAslfauPjtZI+nNJ3+xy7jmSzpJkuV12fE3S8ZI299EfpyBQpcAzJN0iaWqh0W4FQD6fq9SnrYkIVFEAJJ8nEgHe602AAqA3ajqKVOAgd7eJfUu/XtL5kq6VZP/+Kkl/4eZlRUD7Vv+RSOfJsOMXKF683C3pl5KOdtMapABoOX6Ge9+PJdm3+Xa36xMlvUuS/U7YYee9O342ZhCggH2ZYvlmd/tdIem7ku6SNEXScyS9w91BZUO3u51O7DIH8jnAAGc4JCsAfsZdP/y3JPuMvs8V8fZ2BbuXuxy3grbdzW139LUf9sXLx90P7XP5PEm3StpL0mmSrNjSz+9FhiFgyjULWPHjJrdqYJUkW5VgR7cCIJ/PNQeF5vsWaF1Df0zSRV3etUHS7zq8Tj73zc2JTQpQAGxSn75jELBbvZdLGnH/+4O2QdsyByuQ2HGuJPtmngOBJgQs/2yJrv1zv6QnFC5S+i0AHijp5+7be/sW33J/U2EysyXZ74QVu+13wpZm/rqJydJn0gJXSvq8pC9LGi2Z6SL3xYzlqx1HSLK7BtsP8jnpNIlqcla8Lsvl4iT+WNJX3A/sf60gWDx2c5/pu7iC+LMk2R2DrcP6sPfZqgU7+ll6GRUigw1a4G2S/lHSr1wentkjD/l8Djqc2Q2uVQAc9m858jm7lIl3whQA440dI69fwL6B/6Hr5hOS3ljSpX3j+TNJT3F78Ng3nrZPFQcCTQsMUwC0bz3f5AZud1rZt/ntx7MltQrhdv6bm54o/Wcp8EeSvupm/hG3R2s7BPmcZWpEPWkrnvyeK+zZvpfFw+7AvsD94ARJXyqZqd1NeIe7k9D2FLR9izkQqFvA9sa2fSznusKz7ZF2tuu0UyGaz+e6o0L7gwhMtABIPg+izbmNClAAbJSfzgMXsKU1rW8wrejRKga2D9uWS9pt33a8SNLVgc+L4eUhMGgB0P57cI9bSmZ/hFpRu9PR+iP1XvdQnH73TslDnln6ELA/NFtbLpQVOshnH1Ggj6oF7A5uu8PathyZ19b4990S+HXuASKd9r78hrsWsYeVWRGRrUmqjhLttQvYlzH2pUxrtYGthulWAOTzmRwKTWAiBUDyObRoMp6uAhQASRAEOgu0NqK3/R52dUsey862O6XswtyO9xQuerBFoEmBQQuA+7u9/mzMne54bc3HXrcnBNth7+u0H0qT86fvtAUWSGo9LdX++Hxp23TJ57Tjn+Ls7M4/W1FgD1CwLRjsicGtY7okuxax1+wBIS/uAmBfXNoXmHY83+07mKIXcwpD4BWS/lXSA5KeLGm12w6nWwGQz+cwYscotgtMpABIPpNJUQlQAIwqXAzWs4BdxNheU7YR9zO79G378tiFjx22Yb1dDHEg0LTAoAXA4pLKt0v6py4TsNc/5F63JWZ2BxYHAj4F/kTSv7sObR/W09s6J599RoO+hhWwfVWXun37bInvEteQPQn4skKjv+8e9mE/+rAk22+t01H83bAtGrptaD/suHkfAiZgX47bA8f2cA/F+7Rj6XUHIJ/P5E9oAq0CoC1lt/qIXUPbvq0r3U0en+vyZQr5HFo0GU9XAQqAJAgC5QIzCw8/+Jpb2tDNypbrzHF7ptkdgRwINC0waAHQ9ri0p5/Z8WeS/q3LBI53xW47xd5ndwRyIOBLwPZetX0obZ9WO2zJpD1ZtXiQz76iQT+DCpws6bNd3vQB94T14tYKdsffVe499vCxv+/yfvt9sKXEdlhbra1MBh0n5yPQS+CTrvBnq2AOk9TK2V4FQD6fe8nyum+Bfray+Q9J9vn9MNcbvsNDf1UKUACsUpO2UhKwfXNWuQnZ0oZX9ZicPXXVHgBiy3eenhIEc4lWYNACYPGJ1i+RZPtIdTrs9dZdf38t6R+iVWLgMQq8o1AAsbsA/7RkEuRzjJHNY8ydCoA/cVsrtIp3RQ37UuZy9wN7UNPHu1DZ/q12F4sdF0r6qzxYmaVnASv42VY5dpfUHxTuULVh9CoA8vnsOVh011PAtlj4L0nfdk+yths77G/BI9wX3QtdC9dL+sO2Bz6Szz15OSEkAQqAIUWDsYQkYE80u8sN6AuSTuoxODvX3vMbSU8KaSKMJVuBQQuAZ7k9LA3sBZK+00XO9pWyiyQ77H3vy1aZifsWsIvxa9xeaPYljX3h0vqypjgW8tl3ZOivXwFbNmlP67VjlqQnuq1DbOmuXUPY8t4r2xp7jaTPu5+dIukzXTor7kd1saRT+x0Y5yHQp4DtSWkFays2/50kW75ePHoVAPl87hOa07wJ2OfyQx16s60Z7A7sg9zrp0n658K55LO3MNFRFQIUAKtQpI0UBbgDMMWo5jWnQQuAfIOZV37EONunSfquJNt3dbN70qndgVJ2kM8xRjjvMVuRz56iakvRrMhne061Du4AzDs3Qpt9q8BnX34/1T2gZpACIJ/PoUWU8fQSsC9WfiVpmqTbJR1QeAP53EuP14MSoAAYVDgYTEAC7AEYUDAYylACgxYA2ZNnKGbe5ElgP0nfk7SXW3Jmy37/s0vf5LOnwNBNpQK25Yg9SMyWo+1beMAYewBWykxjExCwJ/3aw/HsLsCXuWWT7c31ugOQz+cJBIC3NiZge8If43q3hzetcP+ffG4sJHQ8jAAFwGHUeE8uAjwFOJdIpznPQQuAPMUszTxIYVZW9LM7/+wbeLs7yvZQay2H7DQ/8jmFyOc3hxMLT/99taR/cQQ8BTi/XAh1xvbQr9dL+q2kv+kwSHtQWGtv1vcW9qT8qitu8/kcanQZVzcBW+5u+17bYQ8ha+3XSj6TN1EJUACMKlwM1rOALS073F2s2N4QIx36t6f+2hPQ7HiPpLM9j5PuECgTGLQAWNw3yi7w7RvNTkfrDwB73d73O0KAQE0CiyTZptu2zMyOt0j6aB99kc99IHFKcAK2ufzVblTvlnS++/92t9VGSVMkfVOS3RHY6bCn/p7nXrT9Wq8NbpYMKGYBW5r+2iEnYHdy3+GuG2y/Szu43hgSk7d5F/igJFvua0exAMj1hvdQ0OFEBCgATkSP96YuYBfQdiFtx7Ml/bDDhM8oXKS/qHDxnroP8wtbYNACoP334B63xNL2ObHNvTsdv5Rky4DudQ+/sbuyOBCoWmAX9zAae8KkHfZZe0GfnZDPfUJxWlACxScEv1XSRwqjsy8a7QvHde7plFs7jNye4G7XIlvceY8ENUMGE7tAFQVAPp9jz4I8x28PZzrWTd0e5GTXwHaQz3nmQ7SzpgAYbegYuAcB+3anVfTr9A3lZEk/c8USe3rU4rZHw3sYJl0gUCowaAHQGrlI0ptca/aH5k0lLVsx/Afu53b+m/FHoAaB2e7LlOe5tt8v6W8H7Id8HhCM0xsXKO4xdZSk6wojsiettgrgJ0j6Uslo7Y9Su8PK7hT8euGP1cYnxgCyEui1ByDXG1mlQxKTtbtX7ctxuxvblr/b09uLB9cbSYQ5j0lQAMwjzsxyeIHWMmBb/ru8UPhotVh88tO5kuyihwOBEASGKQAeKOnnkqZKusXl/KbCZGZJst+Jg92SeFuW+esQJssYkhKwC2zbK+poN6sPS3rbEDMkn4dA4y21CNidfVaws6dXdzreLulD7kXbVsGeMjlaOHmB+8PT7oy9U9KzJK0tvG5Fv69IOs79jOW/tYSSRvsQ6KcAyOdzH5Cc4kXAPjOv6rLV0xL3+kFuNO8ofFa3Bkg+ewkVnVQhQAGwCkXaSFnAPuxvlGSFj/VuXx3bT8f+/VVuI2Sb/22uKMJSm5SzIey5HSbpSYUh2t5ptmGxHZbDn24bvi3jKTtszylbamnHj90dJ7ZXj33bebqk1gWQnWd7VHEgULXAlyW93DX6HVf867bM3JZC2mcw+Vx1JGivKgG7K2+eJMtte5q1fabaNYX97OmS7IEfrbtdLZ9tmdk1JZ2/QdLH3c+tDbsz9la3dYMVye2uQTu+KMkeKMKBQBMC/RQAbVxcbzQRHfpsF7DP52nu89lWuNi/25ffdh19pCT73LX/b4d9fr/QbbHQ3g75TG5FIUABMIowMciGBeyboUslze8wDvvD0y7Wb294nHSft8Cg+/J0+vy3Ze2fkvS6LpwXu+L3trzJmX1NAoPuKWl3Q9kdr2UH+VxTkGh2IAH7g3JZH++wfVjts/dbXc611QZnuX2nyk6zpb/2BNZudxv2MRROQWBogX4LgHw+D03MGysU6Pfz2b7AOVWSbfnE9UaFAaApvwIUAP1601u8Anbhfpor9NkeO/YNvRX8rpB0oXs6X7yzY+QpCFRVAGxZHOOKfIe4bz7XSLrZPbHPlkpwIFCXQJUFQPK5rijR7iACdge13TVid+jZA5ZsSdlCd5fJKkk/kWQbzF/e5/XEc93+q4e7tuwP0p9K+qy7+2+QsXEuAlUL9FsA5PO5annaG0bgCEn2j+19bU/0tbv97KYPu0v7bkn2AKZLSraB6tQX18/DRIH3eBOgAOiNmo4QQAABBBBAAAEEEEAAAQQQQAABBBDwL0AB0L85PSKAAAIIIIAAAggggAACCCCAAAIIIOBNgAKgN2o6QgABBBBAAAEEEEAAAQQQQAABBBBAwL8ABUD/5vSIAAIIIIAAAggggAACCCCAAAIIIICANwEKgN6o6QgBBBBAAAEEEEAAAQQQQAABBBBAAAH/AhQA/ZvTIwIIIIAAAggggAACCCCAAAIIIIAAAt4EKAB6o6YjBBBAAAEEEEAAAQQQQAABBBBAAAEE/AtQAPRvTo8IIIAAAggggAACCCCAAAIIIIAAAgh4E6AA6I2ajhBAAAEEEEAAAQQQQAABBBBAAAEEEPAvQAHQvzk9IoAAAggggAACCCCAAAIIIIAAAggg4E2AAqA3ajpCAAEEEEAAAQQQQAABBBBAAAEEEEDAvwAFQP/m9IgAAggggAACCCCAAAIIIIAAAggggIA3AQqA3qjpCAEEEEAAAQQQQAABBBBAAAEEEEAAAf8CFAD9m9MjAggggAACCCCAAAIIIIAAAggggAAC3gQoAHqjpiMEEEAAAQQQQAABBBBAAAEEEEAAAQT8C1AA9G9OjwgggAACCCCAAAIIIIAAAggggAACCHgToADojZqOEEAAAQQQQAABBBBAAAEEEEAAAQQQ8C9AAdC/OT0igAACCCCAAAKxCJwj6Ww32LLrxuskHSHpeklHxjIpxokAAggggAACCOQmQAEwt4gzXwQQQAABBBBAoH8BCoD9W3EmAggggAACCCAQrAAFwGBDw8AQQAABBBBAAIHaBE6W9FnX+n6S7ujQ00QLgGOu3XMlWVscCCCAAAIIIIAAAg0IUABsAJ0uEUAAAQQQQACBhgX6LQD2GmavJcAUAHsJ8joCCCCAAAIIIOBBgAKgB2S6QAABBBBAAAEEAhOgABhYQBgOAggggAACCCBQpwAFwDp1aRsBBBBAAAEEEAhTgAJgmHFhVAgggAACCCCAQC0CFABrYaVRBBBAAAEEEEAgSAF7Uu+1fYzsKEm2vHfYPQBtT8FlPfq5RJIVIjkQQAABBBBAAAEEahagAFgzMM0jgAACCCCAAAIBCVAADCgYDAUBBBBAAAEEEPAlQAHQlzT9IIAAAggggAACzQvMkWRP/X2ZpPe54bxI0oq2of1O0oYJ3AF4oKTpkm517X5M0kVtfTwo6d7mSRgBAggggAACCCCQvgAFwPRjzAwRQAABBBBAAIF2gX73ABx2CXCrP54CTO4hgAACCCCAAAIBCFAADCAIDAEBBBBAAAEEEPAsQAHQMzjdIYAAAggggAACTQpQAGxSn74RQAABBBBAAIFmBCgANuNOrwgggAACCCCAQCMCFAAbYadTBBBAAAEEEECgUQEKgI3y0zkCCCCAAAIIIOBXgAKgX296QwABBBBAAAEEQhCgABhCFBgDAggggAACCCDgSYACoCdoukEAAQQQQAABBAISoAAYUDAYCgIIIIAAAgggULcABcC6hWkfAQQQQAABBBAIT4ACYHgxYUQIIIAAAggggEBtAhQAa6OlYQQQQAABBBBAIFiB10r6nBvdfpLu6DDScySd7V4ru268TtIRkq6XdGRJG2PuZ+dKsrY4EEAAAQQQQAABBBoQoADYADpdIoAAAggggAACDQu8UtKX3BieLOn/aioAbpI0U9IHJJ3Z8JzpHgEEEEAAAQQQyFaAAmC2oWfiCCCAAAIIIJCxwHJ3154RHCvp6zUVAH8rye4wvELSKzL2ZuoIIIAAAggggECjAhQAG+WncwQQQAABBBBAoBGBeZJWubvz/kfSGZLulLTNjeZeSXb33kSXAF8q6dWStkg6TdKNkja7Pta5MTQCQKcIIIAAAggggEBOAhQAc4o2c0UAAQQQQAABBLYLXCDpXR1AjpJk+/tNtAD4TEk3SZpR0s8lkuxhJBwIIIAAAggggAACNQtQAKwZmOYRQAABBBBAAIFABew68BRJJ0l6mqRdJE1xY62qAGjNHSTpnZKeJ2lJoRhIATDQxGBYCCCAAAIIIJCeAAXA9GLKjBBAAAEEEEAAAQQQQAABBBBAAAEEEHhcgAIgyYAAAggggAACCCCAAAIIIIAAAggggEDCAhQAEw4uU0MAAQQQQAABBBBAAAEEEEAAAQQQQIACIDmAAAIIIIAAAggggAACCCCAAAIIIIBAwgIUABMOLlNDAAEEEEAAAQQQQAABBBBAAAEEEECAAiA5gAACCCCAAAIIIIAAAggggAACCCCAQMICFAATDi5TQwABBBBAAAEEEEAAAQQQQAABBBBAgAIgOYAAAggggAACCCCAAAIIIIAAAggggEDCAhQAEw4uU0MAAQQQQAABBBBAAAEEEEAAAQQQQIACIDmAAAIIIIAAAggggAACCCCAAAIIIIBAwgIUABMOLlNDAAEEEEAAAQQQQAABBBBAAAEEEECAAiA5gAACCCCAAAIIIIAAAggggAACCCCAQMICFAATDi5TQwABBBBu06HCAAABYUlEQVRAAAEEEEAAAQQQQAABBBBAgAIgOYAAAggggAACCCCAAAIIIIAAAggggEDCAhQAEw4uU0MAAQQQQAABBBBAAAEEEEAAAQQQQIACIDmAAAIIIIAAAggggAACCCCAAAIIIIBAwgIUABMOLlNDAAEEEEAAAQQQQAABBBBAAAEEEECAAiA5gAACCCCAAAIIIIAAAggggAACCCCAQMICFAATDi5TQwABBBBAAAEEEEAAAQQQQAABBBBAgAIgOYAAAggggAACCCCAAAIIIIAAAggggEDCAhQAEw4uU0MAAQQQQAABBBBAAAEEEEAAAQQQQIACIDmAAAIIIIAAAggggAACCCCAAAIIIIBAwgIUABMOLlNDAAEEEEAAAQQQQAABBBBAAAEEEECAAiA5gAACCCCAAAIIIIAAAggggAACCCCAQMICFAATDi5TQwABBBBAAAEEEEAAAQQQQAABBBBA4P8BPGhcgK7eh9IAAAAASUVORK5CYII=\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"zenith = 75\n",
			"linestyles = { 70 : '--', \n",
			" 75 : '-', \n",
			" 80 : ':' }\n",
			"\n",
			"plt.figure()\n",
			"for zenith in [70, 75, 80]:\n",
			" for dist in shading.distance:\n",
			" data.shading.sel( zenith = zenith, distance = dist ).plot(label = 'DR = %d, zenith = %d' %(dist, zenith), \n",
			" c = 'C%d' %(dist), \n",
			" linestyle = linestyles[zenith])\n",
			"\n",
			"custom_lines = [Line2D([0], [0], color='C0'),\n",
			" Line2D([0], [0], color='C1'),\n",
			" Line2D([0], [0], color='C2'),\n",
			" Line2D([0], [0], color='C3'),\n",
			" Line2D([0], [0], color='black', linestyle = '--'),\n",
			" Line2D([0], [0], color='black', linestyle = '-') ,\n",
			" Line2D([0], [0], color='black', linestyle = ':')]\n",
			"\n",
			"plt.legend(custom_lines, ['DR = 0', 'DR = 1', 'DR = 2', 'DR = 3', '70° zenith', '75° zenith', '80° zenith']) \n",
			" \n",
			"# plt.legend()\n",
			"plt.grid('on')\n",
			"plt.title('Shading of roof surface at minimum zenith angle')\n",
			"plt.savefig('panel_tilt_mutual_shading.png', dpi = 300)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Get tilted irradiance"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 11,
			"metadata": {},
			"outputs": [],
			"source": [
			"example = meteo.isel(x = 1000, y = 500).drop(['x', 'y'])\n",
			"example.coords['tilt'] = tilts\n",
			"example.coords['distance'] = DP_ratios"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 12,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"<xarray.Dataset>\n",
			"Dimensions: (distance: 4, tilt: 11, timestamp: 159)\n",
			"Coordinates:\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15T07:00:00 ... 2001-12-15T15:00:00\n",
			" * tilt (tilt) int64 0 5 10 15 20 25 30 35 40 45 50\n",
			" * distance (distance) int64 0 1 2 3\n",
			"Data variables:\n",
			" SIS (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" SISDIR (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" apparent_zenith (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" azimuth (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DHI (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DNI (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" rel_airmass (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DNI_extra (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" shading (tilt, timestamp, distance) float64 dask.array<shape=(11, 159, 4), chunksize=(11, 159, 4)>\n",
			" SVF_shade (distance, tilt) float64 0.0 0.02778 ... 0.04517 0.05368"
			]
			},
			"execution_count": 12,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"example['shading'] = abs(get_shading_ratio( example['tilt'], example['distance'], example['apparent_zenith'] ))\n",
			"example['SVF_shade'] = get_shading_SVF( example['distance'], example['tilt'] )\n",
			"example"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 13,
			"metadata": {},
			"outputs": [
			{
			"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>distance</th>\n",
			" <th>tilt</th>\n",
			" <th>SIS</th>\n",
			" <th>SISDIR</th>\n",
			" <th>apparent_zenith</th>\n",
			" <th>azimuth</th>\n",
			" <th>DHI</th>\n",
			" <th>DNI</th>\n",
			" <th>rel_airmass</th>\n",
			" <th>DNI_extra</th>\n",
			" <th>shading</th>\n",
			" <th>SVF_shade</th>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>timestamp</th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" <th></th>\n",
			" </tr>\n",
			" </thead>\n",
			" <tbody>\n",
			" <tr>\n",
			" <th>2001-01-15 07:00:00</th>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>21.816746</td>\n",
			" <td>0.365673</td>\n",
			" <td>91.760184</td>\n",
			" <td>119.518179</td>\n",
			" <td>21.451073</td>\n",
			" <td>0.000000</td>\n",
			" <td>NaN</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>2001-01-15 08:00:00</th>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>111.814315</td>\n",
			" <td>34.015340</td>\n",
			" <td>83.222130</td>\n",
			" <td>130.714243</td>\n",
			" <td>77.798975</td>\n",
			" <td>288.215687</td>\n",
			" <td>7.951483</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>2001-01-15 09:00:00</th>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>206.217784</td>\n",
			" <td>92.007487</td>\n",
			" <td>76.247602</td>\n",
			" <td>143.005214</td>\n",
			" <td>114.210297</td>\n",
			" <td>387.030773</td>\n",
			" <td>4.140166</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>2001-01-15 10:00:00</th>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>273.879120</td>\n",
			" <td>138.148694</td>\n",
			" <td>71.080161</td>\n",
			" <td>156.547427</td>\n",
			" <td>135.730425</td>\n",
			" <td>426.062705</td>\n",
			" <td>3.059478</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>2001-01-15 11:00:00</th>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>289.222736</td>\n",
			" <td>148.478876</td>\n",
			" <td>68.215608</td>\n",
			" <td>171.152802</td>\n",
			" <td>140.743860</td>\n",
			" <td>400.088698</td>\n",
			" <td>2.678819</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" </tbody>\n",
			"</table>\n",
			"</div>"
			],
			"text/plain": [
			" distance tilt SIS SISDIR apparent_zenith \\\n",
			"timestamp \n",
			"2001-01-15 07:00:00 0 0 21.816746 0.365673 91.760184 \n",
			"2001-01-15 08:00:00 0 0 111.814315 34.015340 83.222130 \n",
			"2001-01-15 09:00:00 0 0 206.217784 92.007487 76.247602 \n",
			"2001-01-15 10:00:00 0 0 273.879120 138.148694 71.080161 \n",
			"2001-01-15 11:00:00 0 0 289.222736 148.478876 68.215608 \n",
			"\n",
			" azimuth DHI DNI rel_airmass \\\n",
			"timestamp \n",
			"2001-01-15 07:00:00 119.518179 21.451073 0.000000 NaN \n",
			"2001-01-15 08:00:00 130.714243 77.798975 288.215687 7.951483 \n",
			"2001-01-15 09:00:00 143.005214 114.210297 387.030773 4.140166 \n",
			"2001-01-15 10:00:00 156.547427 135.730425 426.062705 3.059478 \n",
			"2001-01-15 11:00:00 171.152802 140.743860 400.088698 2.678819 \n",
			"\n",
			" DNI_extra shading SVF_shade \n",
			"timestamp \n",
			"2001-01-15 07:00:00 1412.984954 0.0 0.0 \n",
			"2001-01-15 08:00:00 1412.984954 0.0 0.0 \n",
			"2001-01-15 09:00:00 1412.984954 0.0 0.0 \n",
			"2001-01-15 10:00:00 1412.984954 0.0 0.0 \n",
			"2001-01-15 11:00:00 1412.984954 0.0 0.0 "
			]
			},
			"execution_count": 13,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"all_df = example.to_dataframe().reset_index().set_index('timestamp')\n",
			"all_df.head()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 14,
			"metadata": {},
			"outputs": [],
			"source": [
			"irradiance_components = pvlib.total_irrad(\n",
			" surface_tilt = all_df['tilt'], \n",
			" surface_azimuth = 180,\n",
			" apparent_zenith = all_df['apparent_zenith'], \n",
			" azimuth = all_df['azimuth'],\n",
			" dni = all_df['DNI'], \n",
			" ghi = all_df['SIS'], \n",
			" dhi = all_df['DHI'], \n",
			" dni_extra = all_df['DNI_extra'], \n",
			" airmass = all_df['rel_airmass'],\n",
			" model = 'perez'\n",
			")"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 15,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/html": [
			"<div>\n",
			"<style scoped>\n",
			" .dataframe tbody tr th:only-of-type {\n",
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			"\n",
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			" 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>timestamp</th>\n",
			" <th>distance</th>\n",
			" <th>tilt</th>\n",
			" <th>SIS</th>\n",
			" <th>SISDIR</th>\n",
			" <th>apparent_zenith</th>\n",
			" <th>azimuth</th>\n",
			" <th>DHI</th>\n",
			" <th>DNI</th>\n",
			" <th>rel_airmass</th>\n",
			" <th>DNI_extra</th>\n",
			" <th>shading</th>\n",
			" <th>SVF_shade</th>\n",
			" <th>poa_global</th>\n",
			" <th>poa_direct</th>\n",
			" <th>poa_diffuse</th>\n",
			" <th>poa_sky_diffuse</th>\n",
			" <th>poa_ground_diffuse</th>\n",
			" </tr>\n",
			" </thead>\n",
			" <tbody>\n",
			" <tr>\n",
			" <th>0</th>\n",
			" <td>2001-01-15 07:00:00</td>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>21.816746</td>\n",
			" <td>0.365673</td>\n",
			" <td>91.760184</td>\n",
			" <td>119.518179</td>\n",
			" <td>21.451073</td>\n",
			" <td>0.000000</td>\n",
			" <td>NaN</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" <td>0.000000</td>\n",
			" <td>-0.000000</td>\n",
			" <td>0.000000</td>\n",
			" <td>0.000000</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>1</th>\n",
			" <td>2001-01-15 08:00:00</td>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>111.814315</td>\n",
			" <td>34.015340</td>\n",
			" <td>83.222130</td>\n",
			" <td>130.714243</td>\n",
			" <td>77.798975</td>\n",
			" <td>288.215687</td>\n",
			" <td>7.951483</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" <td>111.814315</td>\n",
			" <td>34.015340</td>\n",
			" <td>77.798975</td>\n",
			" <td>77.798975</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>2</th>\n",
			" <td>2001-01-15 09:00:00</td>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>206.217784</td>\n",
			" <td>92.007487</td>\n",
			" <td>76.247602</td>\n",
			" <td>143.005214</td>\n",
			" <td>114.210297</td>\n",
			" <td>387.030773</td>\n",
			" <td>4.140166</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" <td>206.217784</td>\n",
			" <td>92.007487</td>\n",
			" <td>114.210297</td>\n",
			" <td>114.210297</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>3</th>\n",
			" <td>2001-01-15 10:00:00</td>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>273.879120</td>\n",
			" <td>138.148694</td>\n",
			" <td>71.080161</td>\n",
			" <td>156.547427</td>\n",
			" <td>135.730425</td>\n",
			" <td>426.062705</td>\n",
			" <td>3.059478</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" <td>273.879120</td>\n",
			" <td>138.148694</td>\n",
			" <td>135.730425</td>\n",
			" <td>135.730425</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>4</th>\n",
			" <td>2001-01-15 11:00:00</td>\n",
			" <td>0</td>\n",
			" <td>0</td>\n",
			" <td>289.222736</td>\n",
			" <td>148.478876</td>\n",
			" <td>68.215608</td>\n",
			" <td>171.152802</td>\n",
			" <td>140.743860</td>\n",
			" <td>400.088698</td>\n",
			" <td>2.678819</td>\n",
			" <td>1412.984954</td>\n",
			" <td>0.0</td>\n",
			" <td>0.0</td>\n",
			" <td>289.222736</td>\n",
			" <td>148.478876</td>\n",
			" <td>140.743860</td>\n",
			" <td>140.743860</td>\n",
			" <td>0.0</td>\n",
			" </tr>\n",
			" </tbody>\n",
			"</table>\n",
			"</div>"
			],
			"text/plain": [
			" timestamp distance tilt SIS SISDIR \\\n",
			"0 2001-01-15 07:00:00 0 0 21.816746 0.365673 \n",
			"1 2001-01-15 08:00:00 0 0 111.814315 34.015340 \n",
			"2 2001-01-15 09:00:00 0 0 206.217784 92.007487 \n",
			"3 2001-01-15 10:00:00 0 0 273.879120 138.148694 \n",
			"4 2001-01-15 11:00:00 0 0 289.222736 148.478876 \n",
			"\n",
			" apparent_zenith azimuth DHI DNI rel_airmass \\\n",
			"0 91.760184 119.518179 21.451073 0.000000 NaN \n",
			"1 83.222130 130.714243 77.798975 288.215687 7.951483 \n",
			"2 76.247602 143.005214 114.210297 387.030773 4.140166 \n",
			"3 71.080161 156.547427 135.730425 426.062705 3.059478 \n",
			"4 68.215608 171.152802 140.743860 400.088698 2.678819 \n",
			"\n",
			" DNI_extra shading SVF_shade poa_global poa_direct poa_diffuse \\\n",
			"0 1412.984954 0.0 0.0 0.000000 -0.000000 0.000000 \n",
			"1 1412.984954 0.0 0.0 111.814315 34.015340 77.798975 \n",
			"2 1412.984954 0.0 0.0 206.217784 92.007487 114.210297 \n",
			"3 1412.984954 0.0 0.0 273.879120 138.148694 135.730425 \n",
			"4 1412.984954 0.0 0.0 289.222736 148.478876 140.743860 \n",
			"\n",
			" poa_sky_diffuse poa_ground_diffuse \n",
			"0 0.000000 0.0 \n",
			"1 77.798975 0.0 \n",
			"2 114.210297 0.0 \n",
			"3 135.730425 0.0 \n",
			"4 140.743860 0.0 "
			]
			},
			"execution_count": 15,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"irrad = pd.concat([all_df, irradiance_components], axis = 1).reset_index().dropna( subset = ['poa_global'] )\n",
			"irrad.head()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 16,
			"metadata": {},
			"outputs": [],
			"source": [
			"SVF = 0.9\n",
			"irrad['tilted_irrad'] = irrad.poa_direct * (1 - irrad.shading) + irrad.poa_sky_diffuse * SVF * (1 - irrad.SVF_shade) + irrad.poa_ground_diffuse\n",
			"# irrad['tilted_irrad_global'] = (1 - irrad.shading) * irrad.poa_direct + irrad.poa_sky_diffuse * SVF + irrad.poa_ground_diffuse"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 17,
			"metadata": {},
			"outputs": [],
			"source": [
			"example['poa_global' ] = irrad.set_index(['timestamp', 'tilt', 'distance'])['poa_global' ].to_xarray()\n",
			"example['tilted_irrad'] = irrad.set_index(['timestamp', 'tilt', 'distance'])['tilted_irrad'].to_xarray()\n",
			"# example['tilted_irrad_global'] = irrad.set_index(['timestamp', 'tilt', 'distance'])['tilted_irrad_global'].to_xarray()\n",
			"example['tilted_irrad_yrly'] = util.get_yearly_sum( example, 'tilted_irrad' ) / 1000\n",
			"# example['tilted_irrad_global_yrly'] = util.get_yearly_sum( example, 'tilted_irrad_global' ) / 1000"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 18,
			"metadata": {},
			"outputs": [],
			"source": [
			"# assign coordinates:\n",
			"example['tilted_irrad'].attrs['units'] = '$kWh_{G_t}/m^2_{panel}$'\n",
			"# example['tilted_irrad_global'].attrs['units'] = '$kWh_{G_t}/m^2_{panel}$'\n",
			"example['tilted_irrad_yrly'].attrs['units'] = '$kWh_{G_t}/m^2_{panel}$'\n",
			"# example['tilted_irrad_global_yrly'].attrs['units'] = '$kWh_{G_t}/m^2_{panel}$'\n"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 19,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"<xarray.Dataset>\n",
			"Dimensions: (distance: 4, tilt: 11, timestamp: 159)\n",
			"Coordinates:\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15T07:00:00 ... 2001-12-15T15:00:00\n",
			" * tilt (tilt) int64 0 5 10 15 20 25 30 35 40 45 50\n",
			" * distance (distance) int64 0 1 2 3\n",
			"Data variables:\n",
			" SIS (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" SISDIR (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" apparent_zenith (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" azimuth (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DHI (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DNI (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" rel_airmass (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DNI_extra (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" shading (tilt, timestamp, distance) float64 dask.array<shape=(11, 159, 4), chunksize=(11, 159, 4)>\n",
			" SVF_shade (distance, tilt) float64 0.0 0.02778 ... 0.04517 0.05368\n",
			" poa_global (timestamp, tilt, distance) float64 0.0 0.0 ... 5.073\n",
			" tilted_irrad (timestamp, tilt, distance) float64 0.0 0.0 ... 4.359\n",
			" tilted_irrad_yrly (tilt, distance) float64 1.204e+03 ... 1.435e+03"
			]
			},
			"execution_count": 19,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"example"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 20,
			"metadata": {},
			"outputs": [],
			"source": [
			"# L = 20 # test-length\n",
			"# example['n_max'] = np.floor( L / cosd(example.tilt))\n",
			"# example['n_panels_per_area'] = np.ceil( example.n_max / (example.distance + 1) ) / L"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 21,
			"metadata": {},
			"outputs": [],
			"source": [
			"example['n_panels_per_area'] = 1 / ( cosd(example.tilt) * (example.distance + 1) )\n",
			"example['n_panels_per_area'].attrs['units'] = '$m^2_{panels}/m^2_{roof}$'"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 22,
			"metadata": {},
			"outputs": [],
			"source": [
			"EFF = 0.17\n",
			"example['PV_per_m2'] = example.tilted_irrad * example.n_panels_per_area * EFF\n",
			"example['PV_per_m2_yearly'] = util.get_yearly_sum( example, 'PV_per_m2' ) / 1000"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 23,
			"metadata": {},
			"outputs": [],
			"source": [
			"# example['PV_per_m2_global'] = example.tilted_irrad_global * example.n_panels_per_area * EFF\n",
			"# example['PV_per_m2_global_yearly'] = util.get_yearly_sum( example, 'PV_per_m2_global' ) / 1000"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 24,
			"metadata": {},
			"outputs": [],
			"source": [
			"# assign units\n",
			"# example['PV_per_m2_global'].attrs['units'] = '$kWh_{PV}/m^2_{roof}$'\n",
			"example['PV_per_m2'].attrs['units'] = '$kWh_{PV}/m^2_{roof}$'\n",
			"example['PV_per_m2_yearly'].attrs['units'] = '$kWh_{PV}/m^2_{roof}$'\n",
			"# example['PV_per_m2_global_yearly'].attrs['units'] = '$kWh_{PV}/m^2_{roof}$'"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 25,
			"metadata": {},
			"outputs": [],
			"source": [
			"# rule of thumb (SwissSolar): approx.6m2 needed to install 1kWp\n",
			"CAPACITY_per_m2 = 1/6\n",
			"example['CAP_per_m2'] = example['n_panels_per_area'] * CAPACITY_per_m2\n",
			"example['CAP_per_m2'].attrs['units'] = '$kWp/m^2_{roof}$'"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 26,
			"metadata": {},
			"outputs": [],
			"source": [
			"example['Efficiency'] = example.PV_per_m2 / example.CAP_per_m2\n",
			"example['Efficiency_yearly'] = example.PV_per_m2_yearly / example.CAP_per_m2\n",
			"# example['Efficiency_global'] = example.PV_per_m2_global / example.CAP_per_m2\n",
			"# example['Efficiency_global_yearly'] = example.PV_per_m2_global_yearly / example.CAP_per_m2\n",
			"\n",
			"example['Efficiency'].attrs['units'] = '$kWh_{PV}/kWp$'\n",
			"example['Efficiency_yearly'].attrs['units'] = '$kWh_{PV}/kWp$'\n",
			"# example['Efficiency_global'].attrs['units'] = '$kWh_{PV}/kWp$'\n",
			"# example['Efficiency_global_yearly'].attrs['units'] = '$kWh_{PV}/kWp$'"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 65,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"<xarray.Dataset>\n",
			"Dimensions: (distance: 4, tilt: 11, timestamp: 159)\n",
			"Coordinates:\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15T07:00:00 ... 2001-12-15T15:00:00\n",
			" * tilt (tilt) int64 0 5 10 15 20 25 30 35 40 45 50\n",
			" * distance (distance) int64 0 1 2 3\n",
			"Data variables:\n",
			" SIS (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" SISDIR (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" apparent_zenith (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" azimuth (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DHI (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DNI (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" rel_airmass (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DNI_extra (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" shading (tilt, timestamp, distance) float64 dask.array<shape=(11, 159, 4), chunksize=(11, 159, 4)>\n",
			" SVF_shade (distance, tilt) float64 0.0 0.02778 ... 0.05368\n",
			" poa_global (timestamp, tilt, distance) float64 0.0 0.0 ... 5.073\n",
			" tilted_irrad (timestamp, tilt, distance) float64 0.0 0.0 ... 4.359\n",
			" tilted_irrad_yrly (tilt, distance) float64 1.204e+03 ... 1.435e+03\n",
			" n_panels_per_area (tilt, distance) float64 1.0 0.5 ... 0.5186 0.3889\n",
			" PV_per_m2 (timestamp, tilt, distance) float64 0.0 0.0 ... 0.2882\n",
			" PV_per_m2_yearly (tilt, distance) float64 204.6 102.3 ... 120.5 94.89\n",
			" CAP_per_m2 (tilt, distance) float64 0.1667 0.08333 ... 0.06482\n",
			" Efficiency (timestamp, tilt, distance) float64 0.0 0.0 ... 4.446\n",
			" Efficiency_yearly (tilt, distance) float64 1.228e+03 ... 1.464e+03\n",
			" weighted_rentability (tilt, distance) float64 716.1 665.0 ... 288.3 290.8"
			]
			},
			"execution_count": 65,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"example"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 66,
			"metadata": {},
			"outputs": [],
			"source": [
			"pv_output_weight = 0.5\n",
			"example['weighted_rentability'] = example.PV_per_m2_yearly * pv_output_weight + (1 - pv_output_weight) * example.Efficiency_yearly"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 67,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"application/javascript": [
			"/* Put everything inside the global mpl namespace */\n",
			"window.mpl = {};\n",
			"\n",
			"\n",
			"mpl.get_websocket_type = function() {\n",
			" if (typeof(WebSocket) !== 'undefined') {\n",
			" return WebSocket;\n",
			" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
			" return MozWebSocket;\n",
			" } else {\n",
			" alert('Your browser does not have WebSocket support.' +\n",
			" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
			" 'Firefox 4 and 5 are also supported but you ' +\n",
			" 'have to enable WebSockets in about:config.');\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
			" this.id = figure_id;\n",
			"\n",
			" this.ws = websocket;\n",
			"\n",
			" this.supports_binary = (this.ws.binaryType != undefined);\n",
			"\n",
			" if (!this.supports_binary) {\n",
			" var warnings = document.getElementById(\"mpl-warnings\");\n",
			" if (warnings) {\n",
			" warnings.style.display = 'block';\n",
			" warnings.textContent = (\n",
			" \"This browser does not support binary websocket messages. \" +\n",
			" \"Performance may be slow.\");\n",
			" }\n",
			" }\n",
			"\n",
			" this.imageObj = new Image();\n",
			"\n",
			" this.context = undefined;\n",
			" this.message = undefined;\n",
			" this.canvas = undefined;\n",
			" this.rubberband_canvas = undefined;\n",
			" this.rubberband_context = undefined;\n",
			" this.format_dropdown = undefined;\n",
			"\n",
			" this.image_mode = 'full';\n",
			"\n",
			" this.root = $('<div/>');\n",
			" this._root_extra_style(this.root)\n",
			" this.root.attr('style', 'display: inline-block');\n",
			"\n",
			" $(parent_element).append(this.root);\n",
			"\n",
			" this._init_header(this);\n",
			" this._init_canvas(this);\n",
			" this._init_toolbar(this);\n",
			"\n",
			" var fig = this;\n",
			"\n",
			" this.waiting = false;\n",
			"\n",
			" this.ws.onopen = function () {\n",
			" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
			" fig.send_message(\"send_image_mode\", {});\n",
			" if (mpl.ratio != 1) {\n",
			" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
			" }\n",
			" fig.send_message(\"refresh\", {});\n",
			" }\n",
			"\n",
			" this.imageObj.onload = function() {\n",
			" if (fig.image_mode == 'full') {\n",
			" // Full images could contain transparency (where diff images\n",
			" // almost always do), so we need to clear the canvas so that\n",
			" // there is no ghosting.\n",
			" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
			" }\n",
			" fig.context.drawImage(fig.imageObj, 0, 0);\n",
			" };\n",
			"\n",
			" this.imageObj.onunload = function() {\n",
			" fig.ws.close();\n",
			" }\n",
			"\n",
			" this.ws.onmessage = this._make_on_message_function(this);\n",
			"\n",
			" this.ondownload = ondownload;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_header = function() {\n",
			" var titlebar = $(\n",
			" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
			" 'ui-helper-clearfix\"/>');\n",
			" var titletext = $(\n",
			" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
			" 'text-align: center; padding: 3px;\"/>');\n",
			" titlebar.append(titletext)\n",
			" this.root.append(titlebar);\n",
			" this.header = titletext[0];\n",
			"}\n",
			"\n",
			"\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_canvas = function() {\n",
			" var fig = this;\n",
			"\n",
			" var canvas_div = $('<div/>');\n",
			"\n",
			" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
			"\n",
			" function canvas_keyboard_event(event) {\n",
			" return fig.key_event(event, event['data']);\n",
			" }\n",
			"\n",
			" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
			" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
			" this.canvas_div = canvas_div\n",
			" this._canvas_extra_style(canvas_div)\n",
			" this.root.append(canvas_div);\n",
			"\n",
			" var canvas = $('<canvas/>');\n",
			" canvas.addClass('mpl-canvas');\n",
			" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
			"\n",
			" this.canvas = canvas[0];\n",
			" this.context = canvas[0].getContext(\"2d\");\n",
			"\n",
			" var backingStore = this.context.backingStorePixelRatio \|\|\n",
			"\tthis.context.webkitBackingStorePixelRatio \|\|\n",
			"\tthis.context.mozBackingStorePixelRatio \|\|\n",
			"\tthis.context.msBackingStorePixelRatio \|\|\n",
			"\tthis.context.oBackingStorePixelRatio \|\|\n",
			"\tthis.context.backingStorePixelRatio \|\| 1;\n",
			"\n",
			" mpl.ratio = (window.devicePixelRatio \|\| 1) / backingStore;\n",
			"\n",
			" var rubberband = $('<canvas/>');\n",
			" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
			"\n",
			" var pass_mouse_events = true;\n",
			"\n",
			" canvas_div.resizable({\n",
			" start: function(event, ui) {\n",
			" pass_mouse_events = false;\n",
			" },\n",
			" resize: function(event, ui) {\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" stop: function(event, ui) {\n",
			" pass_mouse_events = true;\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" });\n",
			"\n",
			" function mouse_event_fn(event) {\n",
			" if (pass_mouse_events)\n",
			" return fig.mouse_event(event, event['data']);\n",
			" }\n",
			"\n",
			" rubberband.mousedown('button_press', mouse_event_fn);\n",
			" rubberband.mouseup('button_release', mouse_event_fn);\n",
			" // Throttle sequential mouse events to 1 every 20ms.\n",
			" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
			"\n",
			" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
			" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
			"\n",
			" canvas_div.on(\"wheel\", function (event) {\n",
			" event = event.originalEvent;\n",
			" event['data'] = 'scroll'\n",
			" if (event.deltaY < 0) {\n",
			" event.step = 1;\n",
			" } else {\n",
			" event.step = -1;\n",
			" }\n",
			" mouse_event_fn(event);\n",
			" });\n",
			"\n",
			" canvas_div.append(canvas);\n",
			" canvas_div.append(rubberband);\n",
			"\n",
			" this.rubberband = rubberband;\n",
			" this.rubberband_canvas = rubberband[0];\n",
			" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
			" this.rubberband_context.strokeStyle = \"#000000\";\n",
			"\n",
			" this._resize_canvas = function(width, height) {\n",
			" // Keep the size of the canvas, canvas container, and rubber band\n",
			" // canvas in synch.\n",
			" canvas_div.css('width', width)\n",
			" canvas_div.css('height', height)\n",
			"\n",
			" canvas.attr('width', width * mpl.ratio);\n",
			" canvas.attr('height', height * mpl.ratio);\n",
			" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
			"\n",
			" rubberband.attr('width', width);\n",
			" rubberband.attr('height', height);\n",
			" }\n",
			"\n",
			" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
			" // upon first draw.\n",
			" this._resize_canvas(600, 600);\n",
			"\n",
			" // Disable right mouse context menu.\n",
			" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
			" return false;\n",
			" });\n",
			"\n",
			" function set_focus () {\n",
			" canvas.focus();\n",
			" canvas_div.focus();\n",
			" }\n",
			"\n",
			" window.setTimeout(set_focus, 100);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items) {\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) {\n",
			" // put a spacer in here.\n",
			" continue;\n",
			" }\n",
			" var button = $('<button/>');\n",
			" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
			" 'ui-button-icon-only');\n",
			" button.attr('role', 'button');\n",
			" button.attr('aria-disabled', 'false');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			"\n",
			" var icon_img = $('<span/>');\n",
			" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
			" icon_img.addClass(image);\n",
			" icon_img.addClass('ui-corner-all');\n",
			"\n",
			" var tooltip_span = $('<span/>');\n",
			" tooltip_span.addClass('ui-button-text');\n",
			" tooltip_span.html(tooltip);\n",
			"\n",
			" button.append(icon_img);\n",
			" button.append(tooltip_span);\n",
			"\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" var fmt_picker_span = $('<span/>');\n",
			"\n",
			" var fmt_picker = $('<select/>');\n",
			" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
			" fmt_picker_span.append(fmt_picker);\n",
			" nav_element.append(fmt_picker_span);\n",
			" this.format_dropdown = fmt_picker[0];\n",
			"\n",
			" for (var ind in mpl.extensions) {\n",
			" var fmt = mpl.extensions[ind];\n",
			" var option = $(\n",
			" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
			" fmt_picker.append(option)\n",
			" }\n",
			"\n",
			" // Add hover states to the ui-buttons\n",
			" $( \".ui-button\" ).hover(\n",
			" function() { $(this).addClass(\"ui-state-hover\");},\n",
			" function() { $(this).removeClass(\"ui-state-hover\");}\n",
			" );\n",
			"\n",
			" var status_bar = $('<span class=\"mpl-message\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
			" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
			" // which will in turn request a refresh of the image.\n",
			" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_message = function(type, properties) {\n",
			" properties['type'] = type;\n",
			" properties['figure_id'] = this.id;\n",
			" this.ws.send(JSON.stringify(properties));\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_draw_message = function() {\n",
			" if (!this.waiting) {\n",
			" this.waiting = true;\n",
			" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
			" }\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" var format_dropdown = fig.format_dropdown;\n",
			" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
			" fig.ondownload(fig, format);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
			" var size = msg['size'];\n",
			" if (size[0] != fig.canvas.width \|\| size[1] != fig.canvas.height) {\n",
			" fig._resize_canvas(size[0], size[1]);\n",
			" fig.send_message(\"refresh\", {});\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
			" var x0 = msg['x0'] / mpl.ratio;\n",
			" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
			" var x1 = msg['x1'] / mpl.ratio;\n",
			" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
			" x0 = Math.floor(x0) + 0.5;\n",
			" y0 = Math.floor(y0) + 0.5;\n",
			" x1 = Math.floor(x1) + 0.5;\n",
			" y1 = Math.floor(y1) + 0.5;\n",
			" var min_x = Math.min(x0, x1);\n",
			" var min_y = Math.min(y0, y1);\n",
			" var width = Math.abs(x1 - x0);\n",
			" var height = Math.abs(y1 - y0);\n",
			"\n",
			" fig.rubberband_context.clearRect(\n",
			" 0, 0, fig.canvas.width, fig.canvas.height);\n",
			"\n",
			" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
			" // Updates the figure title.\n",
			" fig.header.textContent = msg['label'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
			" var cursor = msg['cursor'];\n",
			" switch(cursor)\n",
			" {\n",
			" case 0:\n",
			" cursor = 'pointer';\n",
			" break;\n",
			" case 1:\n",
			" cursor = 'default';\n",
			" break;\n",
			" case 2:\n",
			" cursor = 'crosshair';\n",
			" break;\n",
			" case 3:\n",
			" cursor = 'move';\n",
			" break;\n",
			" }\n",
			" fig.rubberband_canvas.style.cursor = cursor;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
			" fig.message.textContent = msg['message'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
			" // Request the server to send over a new figure.\n",
			" fig.send_draw_message();\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
			" fig.image_mode = msg['mode'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Called whenever the canvas gets updated.\n",
			" this.send_message(\"ack\", {});\n",
			"}\n",
			"\n",
			"// A function to construct a web socket function for onmessage handling.\n",
			"// Called in the figure constructor.\n",
			"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
			" return function socket_on_message(evt) {\n",
			" if (evt.data instanceof Blob) {\n",
			" /* FIXME: We get \"Resource interpreted as Image but\n",
			" * transferred with MIME type text/plain:\" errors on\n",
			" * Chrome. But how to set the MIME type? It doesn't seem\n",
			" * to be part of the websocket stream */\n",
			" evt.data.type = \"image/png\";\n",
			"\n",
			" /* Free the memory for the previous frames */\n",
			" if (fig.imageObj.src) {\n",
			" (window.URL \|\| window.webkitURL).revokeObjectURL(\n",
			" fig.imageObj.src);\n",
			" }\n",
			"\n",
			" fig.imageObj.src = (window.URL \|\| window.webkitURL).createObjectURL(\n",
			" evt.data);\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
			" fig.imageObj.src = evt.data;\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			"\n",
			" var msg = JSON.parse(evt.data);\n",
			" var msg_type = msg['type'];\n",
			"\n",
			" // Call the \"handle_{type}\" callback, which takes\n",
			" // the figure and JSON message as its only arguments.\n",
			" try {\n",
			" var callback = fig[\"handle_\" + msg_type];\n",
			" } catch (e) {\n",
			" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
			" return;\n",
			" }\n",
			"\n",
			" if (callback) {\n",
			" try {\n",
			" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
			" callback(fig, msg);\n",
			" } catch (e) {\n",
			" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
			" }\n",
			" }\n",
			" };\n",
			"}\n",
			"\n",
			"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
			"mpl.findpos = function(e) {\n",
			" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
			" var targ;\n",
			" if (!e)\n",
			" e = window.event;\n",
			" if (e.target)\n",
			" targ = e.target;\n",
			" else if (e.srcElement)\n",
			" targ = e.srcElement;\n",
			" if (targ.nodeType == 3) // defeat Safari bug\n",
			" targ = targ.parentNode;\n",
			"\n",
			" // jQuery normalizes the pageX and pageY\n",
			" // pageX,Y are the mouse positions relative to the document\n",
			" // offset() returns the position of the element relative to the document\n",
			" var x = e.pageX - $(targ).offset().left;\n",
			" var y = e.pageY - $(targ).offset().top;\n",
			"\n",
			" return {\"x\": x, \"y\": y};\n",
			"};\n",
			"\n",
			"/*\n",
			" * return a copy of an object with only non-object keys\n",
			" * we need this to avoid circular references\n",
			" * http://stackoverflow.com/a/24161582/3208463\n",
			" */\n",
			"function simpleKeys (original) {\n",
			" return Object.keys(original).reduce(function (obj, key) {\n",
			" if (typeof original[key] !== 'object')\n",
			" obj[key] = original[key]\n",
			" return obj;\n",
			" }, {});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.mouse_event = function(event, name) {\n",
			" var canvas_pos = mpl.findpos(event)\n",
			"\n",
			" if (name === 'button_press')\n",
			" {\n",
			" this.canvas.focus();\n",
			" this.canvas_div.focus();\n",
			" }\n",
			"\n",
			" var x = canvas_pos.x * mpl.ratio;\n",
			" var y = canvas_pos.y * mpl.ratio;\n",
			"\n",
			" this.send_message(name, {x: x, y: y, button: event.button,\n",
			" step: event.step,\n",
			" guiEvent: simpleKeys(event)});\n",
			"\n",
			" /* This prevents the web browser from automatically changing to\n",
			" * the text insertion cursor when the button is pressed. We want\n",
			" * to control all of the cursor setting manually through the\n",
			" * 'cursor' event from matplotlib */\n",
			" event.preventDefault();\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" // Handle any extra behaviour associated with a key event\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.key_event = function(event, name) {\n",
			"\n",
			" // Prevent repeat events\n",
			" if (name == 'key_press')\n",
			" {\n",
			" if (event.which === this._key)\n",
			" return;\n",
			" else\n",
			" this._key = event.which;\n",
			" }\n",
			" if (name == 'key_release')\n",
			" this._key = null;\n",
			"\n",
			" var value = '';\n",
			" if (event.ctrlKey && event.which != 17)\n",
			" value += \"ctrl+\";\n",
			" if (event.altKey && event.which != 18)\n",
			" value += \"alt+\";\n",
			" if (event.shiftKey && event.which != 16)\n",
			" value += \"shift+\";\n",
			"\n",
			" value += 'k';\n",
			" value += event.which.toString();\n",
			"\n",
			" this._key_event_extra(event, name);\n",
			"\n",
			" this.send_message(name, {key: value,\n",
			" guiEvent: simpleKeys(event)});\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
			" if (name == 'download') {\n",
			" this.handle_save(this, null);\n",
			" } else {\n",
			" this.send_message(\"toolbar_button\", {name: name});\n",
			" }\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
			" this.message.textContent = tooltip;\n",
			"};\n",
			"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
			"\n",
			"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
			"\n",
			"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
			" // Create a \"websocket\"-like object which calls the given IPython comm\n",
			" // object with the appropriate methods. Currently this is a non binary\n",
			" // socket, so there is still some room for performance tuning.\n",
			" var ws = {};\n",
			"\n",
			" ws.close = function() {\n",
			" comm.close()\n",
			" };\n",
			" ws.send = function(m) {\n",
			" //console.log('sending', m);\n",
			" comm.send(m);\n",
			" };\n",
			" // Register the callback with on_msg.\n",
			" comm.on_msg(function(msg) {\n",
			" //console.log('receiving', msg['content']['data'], msg);\n",
			" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
			" ws.onmessage(msg['content']['data'])\n",
			" });\n",
			" return ws;\n",
			"}\n",
			"\n",
			"mpl.mpl_figure_comm = function(comm, msg) {\n",
			" // This is the function which gets called when the mpl process\n",
			" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
			"\n",
			" var id = msg.content.data.id;\n",
			" // Get hold of the div created by the display call when the Comm\n",
			" // socket was opened in Python.\n",
			" var element = $(\"#\" + id);\n",
			" var ws_proxy = comm_websocket_adapter(comm)\n",
			"\n",
			" function ondownload(figure, format) {\n",
			" window.open(figure.imageObj.src);\n",
			" }\n",
			"\n",
			" var fig = new mpl.figure(id, ws_proxy,\n",
			" ondownload,\n",
			" element.get(0));\n",
			"\n",
			" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
			" // web socket which is closed, not our websocket->open comm proxy.\n",
			" ws_proxy.onopen();\n",
			"\n",
			" fig.parent_element = element.get(0);\n",
			" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
			" if (!fig.cell_info) {\n",
			" console.error(\"Failed to find cell for figure\", id, fig);\n",
			" return;\n",
			" }\n",
			"\n",
			" var output_index = fig.cell_info[2]\n",
			" var cell = fig.cell_info[0];\n",
			"\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
			" var width = fig.canvas.width/mpl.ratio\n",
			" fig.root.unbind('remove')\n",
			"\n",
			" // Update the output cell to use the data from the current canvas.\n",
			" fig.push_to_output();\n",
			" var dataURL = fig.canvas.toDataURL();\n",
			" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
			" // the notebook keyboard shortcuts fail.\n",
			" IPython.keyboard_manager.enable()\n",
			" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
			" fig.close_ws(fig, msg);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.close_ws = function(fig, msg){\n",
			" fig.send_message('closing', msg);\n",
			" // fig.ws.close()\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
			" // Turn the data on the canvas into data in the output cell.\n",
			" var width = this.canvas.width/mpl.ratio\n",
			" var dataURL = this.canvas.toDataURL();\n",
			" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Tell IPython that the notebook contents must change.\n",
			" IPython.notebook.set_dirty(true);\n",
			" this.send_message(\"ack\", {});\n",
			" var fig = this;\n",
			" // Wait a second, then push the new image to the DOM so\n",
			" // that it is saved nicely (might be nice to debounce this).\n",
			" setTimeout(function () { fig.push_to_output() }, 1000);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items){\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) { continue; };\n",
			"\n",
			" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" // Add the status bar.\n",
			" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"\n",
			" // Add the close button to the window.\n",
			" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
			" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
			" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
			" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
			" buttongrp.append(button);\n",
			" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
			" titlebar.prepend(buttongrp);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(el){\n",
			" var fig = this\n",
			" el.on(\"remove\", function(){\n",
			"\tfig.close_ws(fig, {});\n",
			" });\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(el){\n",
			" // this is important to make the div 'focusable\n",
			" el.attr('tabindex', 0)\n",
			" // reach out to IPython and tell the keyboard manager to turn it's self\n",
			" // off when our div gets focus\n",
			"\n",
			" // location in version 3\n",
			" if (IPython.notebook.keyboard_manager) {\n",
			" IPython.notebook.keyboard_manager.register_events(el);\n",
			" }\n",
			" else {\n",
			" // location in version 2\n",
			" IPython.keyboard_manager.register_events(el);\n",
			" }\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" var manager = IPython.notebook.keyboard_manager;\n",
			" if (!manager)\n",
			" manager = IPython.keyboard_manager;\n",
			"\n",
			" // Check for shift+enter\n",
			" if (event.shiftKey && event.which == 13) {\n",
			" this.canvas_div.blur();\n",
			" event.shiftKey = false;\n",
			" // Send a \"J\" for go to next cell\n",
			" event.which = 74;\n",
			" event.keyCode = 74;\n",
			" manager.command_mode();\n",
			" manager.handle_keydown(event);\n",
			" }\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" fig.ondownload(fig, null);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.find_output_cell = function(html_output) {\n",
			" // Return the cell and output element which can be found uniquely in the notebook.\n",
			" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
			" // IPython event is triggered only after the cells have been serialised, which for\n",
			" // our purposes (turning an active figure into a static one), is too late.\n",
			" var cells = IPython.notebook.get_cells();\n",
			" var ncells = cells.length;\n",
			" for (var i=0; i<ncells; i++) {\n",
			" var cell = cells[i];\n",
			" if (cell.cell_type === 'code'){\n",
			" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
			" var data = cell.output_area.outputs[j];\n",
			" if (data.data) {\n",
			" // IPython >= 3 moved mimebundle to data attribute of output\n",
			" data = data.data;\n",
			" }\n",
			" if (data['text/html'] == html_output) {\n",
			" return [cell, data, j];\n",
			" }\n",
			" }\n",
			" }\n",
			" }\n",
			"}\n",
			"\n",
			"// Register the function which deals with the matplotlib target/channel.\n",
			"// The kernel may be null if the page has been refreshed.\n",
			"if (IPython.notebook.kernel != null) {\n",
			" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
			"}\n"
			],
			"text/plain": [
			"<IPython.core.display.Javascript object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
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\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"fig, ax1 = plt.subplots()\n",
			"ax2 = ax1.twinx()\n",
			"for dist in example.distance:\n",
			" example.n_panels_per_area.sel( distance = dist ).plot(ax=ax1, label = 'DR = %d' %(dist), color = 'C%d' %(dist))\n",
			" example.CAP_per_m2.sel( distance = dist ).plot(ax=ax2, label = 'DR = %d' %(dist), color = 'C%d' %(dist))\n",
			" \n",
			"plt.legend()\n",
			"ax1.set_title('')\n",
			"ax2.set_title('Panelled area / installed capacity per roof area')\n",
			"plt.grid()\n",
			"\n",
			"plt.tight_layout()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 30,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"application/javascript": [
			"/* Put everything inside the global mpl namespace */\n",
			"window.mpl = {};\n",
			"\n",
			"\n",
			"mpl.get_websocket_type = function() {\n",
			" if (typeof(WebSocket) !== 'undefined') {\n",
			" return WebSocket;\n",
			" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
			" return MozWebSocket;\n",
			" } else {\n",
			" alert('Your browser does not have WebSocket support.' +\n",
			" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
			" 'Firefox 4 and 5 are also supported but you ' +\n",
			" 'have to enable WebSockets in about:config.');\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
			" this.id = figure_id;\n",
			"\n",
			" this.ws = websocket;\n",
			"\n",
			" this.supports_binary = (this.ws.binaryType != undefined);\n",
			"\n",
			" if (!this.supports_binary) {\n",
			" var warnings = document.getElementById(\"mpl-warnings\");\n",
			" if (warnings) {\n",
			" warnings.style.display = 'block';\n",
			" warnings.textContent = (\n",
			" \"This browser does not support binary websocket messages. \" +\n",
			" \"Performance may be slow.\");\n",
			" }\n",
			" }\n",
			"\n",
			" this.imageObj = new Image();\n",
			"\n",
			" this.context = undefined;\n",
			" this.message = undefined;\n",
			" this.canvas = undefined;\n",
			" this.rubberband_canvas = undefined;\n",
			" this.rubberband_context = undefined;\n",
			" this.format_dropdown = undefined;\n",
			"\n",
			" this.image_mode = 'full';\n",
			"\n",
			" this.root = $('<div/>');\n",
			" this._root_extra_style(this.root)\n",
			" this.root.attr('style', 'display: inline-block');\n",
			"\n",
			" $(parent_element).append(this.root);\n",
			"\n",
			" this._init_header(this);\n",
			" this._init_canvas(this);\n",
			" this._init_toolbar(this);\n",
			"\n",
			" var fig = this;\n",
			"\n",
			" this.waiting = false;\n",
			"\n",
			" this.ws.onopen = function () {\n",
			" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
			" fig.send_message(\"send_image_mode\", {});\n",
			" if (mpl.ratio != 1) {\n",
			" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
			" }\n",
			" fig.send_message(\"refresh\", {});\n",
			" }\n",
			"\n",
			" this.imageObj.onload = function() {\n",
			" if (fig.image_mode == 'full') {\n",
			" // Full images could contain transparency (where diff images\n",
			" // almost always do), so we need to clear the canvas so that\n",
			" // there is no ghosting.\n",
			" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
			" }\n",
			" fig.context.drawImage(fig.imageObj, 0, 0);\n",
			" };\n",
			"\n",
			" this.imageObj.onunload = function() {\n",
			" fig.ws.close();\n",
			" }\n",
			"\n",
			" this.ws.onmessage = this._make_on_message_function(this);\n",
			"\n",
			" this.ondownload = ondownload;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_header = function() {\n",
			" var titlebar = $(\n",
			" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
			" 'ui-helper-clearfix\"/>');\n",
			" var titletext = $(\n",
			" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
			" 'text-align: center; padding: 3px;\"/>');\n",
			" titlebar.append(titletext)\n",
			" this.root.append(titlebar);\n",
			" this.header = titletext[0];\n",
			"}\n",
			"\n",
			"\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_canvas = function() {\n",
			" var fig = this;\n",
			"\n",
			" var canvas_div = $('<div/>');\n",
			"\n",
			" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
			"\n",
			" function canvas_keyboard_event(event) {\n",
			" return fig.key_event(event, event['data']);\n",
			" }\n",
			"\n",
			" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
			" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
			" this.canvas_div = canvas_div\n",
			" this._canvas_extra_style(canvas_div)\n",
			" this.root.append(canvas_div);\n",
			"\n",
			" var canvas = $('<canvas/>');\n",
			" canvas.addClass('mpl-canvas');\n",
			" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
			"\n",
			" this.canvas = canvas[0];\n",
			" this.context = canvas[0].getContext(\"2d\");\n",
			"\n",
			" var backingStore = this.context.backingStorePixelRatio \|\|\n",
			"\tthis.context.webkitBackingStorePixelRatio \|\|\n",
			"\tthis.context.mozBackingStorePixelRatio \|\|\n",
			"\tthis.context.msBackingStorePixelRatio \|\|\n",
			"\tthis.context.oBackingStorePixelRatio \|\|\n",
			"\tthis.context.backingStorePixelRatio \|\| 1;\n",
			"\n",
			" mpl.ratio = (window.devicePixelRatio \|\| 1) / backingStore;\n",
			"\n",
			" var rubberband = $('<canvas/>');\n",
			" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
			"\n",
			" var pass_mouse_events = true;\n",
			"\n",
			" canvas_div.resizable({\n",
			" start: function(event, ui) {\n",
			" pass_mouse_events = false;\n",
			" },\n",
			" resize: function(event, ui) {\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" stop: function(event, ui) {\n",
			" pass_mouse_events = true;\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" });\n",
			"\n",
			" function mouse_event_fn(event) {\n",
			" if (pass_mouse_events)\n",
			" return fig.mouse_event(event, event['data']);\n",
			" }\n",
			"\n",
			" rubberband.mousedown('button_press', mouse_event_fn);\n",
			" rubberband.mouseup('button_release', mouse_event_fn);\n",
			" // Throttle sequential mouse events to 1 every 20ms.\n",
			" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
			"\n",
			" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
			" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
			"\n",
			" canvas_div.on(\"wheel\", function (event) {\n",
			" event = event.originalEvent;\n",
			" event['data'] = 'scroll'\n",
			" if (event.deltaY < 0) {\n",
			" event.step = 1;\n",
			" } else {\n",
			" event.step = -1;\n",
			" }\n",
			" mouse_event_fn(event);\n",
			" });\n",
			"\n",
			" canvas_div.append(canvas);\n",
			" canvas_div.append(rubberband);\n",
			"\n",
			" this.rubberband = rubberband;\n",
			" this.rubberband_canvas = rubberband[0];\n",
			" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
			" this.rubberband_context.strokeStyle = \"#000000\";\n",
			"\n",
			" this._resize_canvas = function(width, height) {\n",
			" // Keep the size of the canvas, canvas container, and rubber band\n",
			" // canvas in synch.\n",
			" canvas_div.css('width', width)\n",
			" canvas_div.css('height', height)\n",
			"\n",
			" canvas.attr('width', width * mpl.ratio);\n",
			" canvas.attr('height', height * mpl.ratio);\n",
			" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
			"\n",
			" rubberband.attr('width', width);\n",
			" rubberband.attr('height', height);\n",
			" }\n",
			"\n",
			" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
			" // upon first draw.\n",
			" this._resize_canvas(600, 600);\n",
			"\n",
			" // Disable right mouse context menu.\n",
			" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
			" return false;\n",
			" });\n",
			"\n",
			" function set_focus () {\n",
			" canvas.focus();\n",
			" canvas_div.focus();\n",
			" }\n",
			"\n",
			" window.setTimeout(set_focus, 100);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items) {\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) {\n",
			" // put a spacer in here.\n",
			" continue;\n",
			" }\n",
			" var button = $('<button/>');\n",
			" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
			" 'ui-button-icon-only');\n",
			" button.attr('role', 'button');\n",
			" button.attr('aria-disabled', 'false');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			"\n",
			" var icon_img = $('<span/>');\n",
			" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
			" icon_img.addClass(image);\n",
			" icon_img.addClass('ui-corner-all');\n",
			"\n",
			" var tooltip_span = $('<span/>');\n",
			" tooltip_span.addClass('ui-button-text');\n",
			" tooltip_span.html(tooltip);\n",
			"\n",
			" button.append(icon_img);\n",
			" button.append(tooltip_span);\n",
			"\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" var fmt_picker_span = $('<span/>');\n",
			"\n",
			" var fmt_picker = $('<select/>');\n",
			" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
			" fmt_picker_span.append(fmt_picker);\n",
			" nav_element.append(fmt_picker_span);\n",
			" this.format_dropdown = fmt_picker[0];\n",
			"\n",
			" for (var ind in mpl.extensions) {\n",
			" var fmt = mpl.extensions[ind];\n",
			" var option = $(\n",
			" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
			" fmt_picker.append(option)\n",
			" }\n",
			"\n",
			" // Add hover states to the ui-buttons\n",
			" $( \".ui-button\" ).hover(\n",
			" function() { $(this).addClass(\"ui-state-hover\");},\n",
			" function() { $(this).removeClass(\"ui-state-hover\");}\n",
			" );\n",
			"\n",
			" var status_bar = $('<span class=\"mpl-message\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
			" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
			" // which will in turn request a refresh of the image.\n",
			" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_message = function(type, properties) {\n",
			" properties['type'] = type;\n",
			" properties['figure_id'] = this.id;\n",
			" this.ws.send(JSON.stringify(properties));\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_draw_message = function() {\n",
			" if (!this.waiting) {\n",
			" this.waiting = true;\n",
			" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
			" }\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" var format_dropdown = fig.format_dropdown;\n",
			" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
			" fig.ondownload(fig, format);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
			" var size = msg['size'];\n",
			" if (size[0] != fig.canvas.width \|\| size[1] != fig.canvas.height) {\n",
			" fig._resize_canvas(size[0], size[1]);\n",
			" fig.send_message(\"refresh\", {});\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
			" var x0 = msg['x0'] / mpl.ratio;\n",
			" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
			" var x1 = msg['x1'] / mpl.ratio;\n",
			" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
			" x0 = Math.floor(x0) + 0.5;\n",
			" y0 = Math.floor(y0) + 0.5;\n",
			" x1 = Math.floor(x1) + 0.5;\n",
			" y1 = Math.floor(y1) + 0.5;\n",
			" var min_x = Math.min(x0, x1);\n",
			" var min_y = Math.min(y0, y1);\n",
			" var width = Math.abs(x1 - x0);\n",
			" var height = Math.abs(y1 - y0);\n",
			"\n",
			" fig.rubberband_context.clearRect(\n",
			" 0, 0, fig.canvas.width, fig.canvas.height);\n",
			"\n",
			" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
			" // Updates the figure title.\n",
			" fig.header.textContent = msg['label'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
			" var cursor = msg['cursor'];\n",
			" switch(cursor)\n",
			" {\n",
			" case 0:\n",
			" cursor = 'pointer';\n",
			" break;\n",
			" case 1:\n",
			" cursor = 'default';\n",
			" break;\n",
			" case 2:\n",
			" cursor = 'crosshair';\n",
			" break;\n",
			" case 3:\n",
			" cursor = 'move';\n",
			" break;\n",
			" }\n",
			" fig.rubberband_canvas.style.cursor = cursor;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
			" fig.message.textContent = msg['message'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
			" // Request the server to send over a new figure.\n",
			" fig.send_draw_message();\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
			" fig.image_mode = msg['mode'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Called whenever the canvas gets updated.\n",
			" this.send_message(\"ack\", {});\n",
			"}\n",
			"\n",
			"// A function to construct a web socket function for onmessage handling.\n",
			"// Called in the figure constructor.\n",
			"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
			" return function socket_on_message(evt) {\n",
			" if (evt.data instanceof Blob) {\n",
			" /* FIXME: We get \"Resource interpreted as Image but\n",
			" * transferred with MIME type text/plain:\" errors on\n",
			" * Chrome. But how to set the MIME type? It doesn't seem\n",
			" * to be part of the websocket stream */\n",
			" evt.data.type = \"image/png\";\n",
			"\n",
			" /* Free the memory for the previous frames */\n",
			" if (fig.imageObj.src) {\n",
			" (window.URL \|\| window.webkitURL).revokeObjectURL(\n",
			" fig.imageObj.src);\n",
			" }\n",
			"\n",
			" fig.imageObj.src = (window.URL \|\| window.webkitURL).createObjectURL(\n",
			" evt.data);\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
			" fig.imageObj.src = evt.data;\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			"\n",
			" var msg = JSON.parse(evt.data);\n",
			" var msg_type = msg['type'];\n",
			"\n",
			" // Call the \"handle_{type}\" callback, which takes\n",
			" // the figure and JSON message as its only arguments.\n",
			" try {\n",
			" var callback = fig[\"handle_\" + msg_type];\n",
			" } catch (e) {\n",
			" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
			" return;\n",
			" }\n",
			"\n",
			" if (callback) {\n",
			" try {\n",
			" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
			" callback(fig, msg);\n",
			" } catch (e) {\n",
			" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
			" }\n",
			" }\n",
			" };\n",
			"}\n",
			"\n",
			"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
			"mpl.findpos = function(e) {\n",
			" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
			" var targ;\n",
			" if (!e)\n",
			" e = window.event;\n",
			" if (e.target)\n",
			" targ = e.target;\n",
			" else if (e.srcElement)\n",
			" targ = e.srcElement;\n",
			" if (targ.nodeType == 3) // defeat Safari bug\n",
			" targ = targ.parentNode;\n",
			"\n",
			" // jQuery normalizes the pageX and pageY\n",
			" // pageX,Y are the mouse positions relative to the document\n",
			" // offset() returns the position of the element relative to the document\n",
			" var x = e.pageX - $(targ).offset().left;\n",
			" var y = e.pageY - $(targ).offset().top;\n",
			"\n",
			" return {\"x\": x, \"y\": y};\n",
			"};\n",
			"\n",
			"/*\n",
			" * return a copy of an object with only non-object keys\n",
			" * we need this to avoid circular references\n",
			" * http://stackoverflow.com/a/24161582/3208463\n",
			" */\n",
			"function simpleKeys (original) {\n",
			" return Object.keys(original).reduce(function (obj, key) {\n",
			" if (typeof original[key] !== 'object')\n",
			" obj[key] = original[key]\n",
			" return obj;\n",
			" }, {});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.mouse_event = function(event, name) {\n",
			" var canvas_pos = mpl.findpos(event)\n",
			"\n",
			" if (name === 'button_press')\n",
			" {\n",
			" this.canvas.focus();\n",
			" this.canvas_div.focus();\n",
			" }\n",
			"\n",
			" var x = canvas_pos.x * mpl.ratio;\n",
			" var y = canvas_pos.y * mpl.ratio;\n",
			"\n",
			" this.send_message(name, {x: x, y: y, button: event.button,\n",
			" step: event.step,\n",
			" guiEvent: simpleKeys(event)});\n",
			"\n",
			" /* This prevents the web browser from automatically changing to\n",
			" * the text insertion cursor when the button is pressed. We want\n",
			" * to control all of the cursor setting manually through the\n",
			" * 'cursor' event from matplotlib */\n",
			" event.preventDefault();\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" // Handle any extra behaviour associated with a key event\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.key_event = function(event, name) {\n",
			"\n",
			" // Prevent repeat events\n",
			" if (name == 'key_press')\n",
			" {\n",
			" if (event.which === this._key)\n",
			" return;\n",
			" else\n",
			" this._key = event.which;\n",
			" }\n",
			" if (name == 'key_release')\n",
			" this._key = null;\n",
			"\n",
			" var value = '';\n",
			" if (event.ctrlKey && event.which != 17)\n",
			" value += \"ctrl+\";\n",
			" if (event.altKey && event.which != 18)\n",
			" value += \"alt+\";\n",
			" if (event.shiftKey && event.which != 16)\n",
			" value += \"shift+\";\n",
			"\n",
			" value += 'k';\n",
			" value += event.which.toString();\n",
			"\n",
			" this._key_event_extra(event, name);\n",
			"\n",
			" this.send_message(name, {key: value,\n",
			" guiEvent: simpleKeys(event)});\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
			" if (name == 'download') {\n",
			" this.handle_save(this, null);\n",
			" } else {\n",
			" this.send_message(\"toolbar_button\", {name: name});\n",
			" }\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
			" this.message.textContent = tooltip;\n",
			"};\n",
			"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
			"\n",
			"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
			"\n",
			"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
			" // Create a \"websocket\"-like object which calls the given IPython comm\n",
			" // object with the appropriate methods. Currently this is a non binary\n",
			" // socket, so there is still some room for performance tuning.\n",
			" var ws = {};\n",
			"\n",
			" ws.close = function() {\n",
			" comm.close()\n",
			" };\n",
			" ws.send = function(m) {\n",
			" //console.log('sending', m);\n",
			" comm.send(m);\n",
			" };\n",
			" // Register the callback with on_msg.\n",
			" comm.on_msg(function(msg) {\n",
			" //console.log('receiving', msg['content']['data'], msg);\n",
			" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
			" ws.onmessage(msg['content']['data'])\n",
			" });\n",
			" return ws;\n",
			"}\n",
			"\n",
			"mpl.mpl_figure_comm = function(comm, msg) {\n",
			" // This is the function which gets called when the mpl process\n",
			" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
			"\n",
			" var id = msg.content.data.id;\n",
			" // Get hold of the div created by the display call when the Comm\n",
			" // socket was opened in Python.\n",
			" var element = $(\"#\" + id);\n",
			" var ws_proxy = comm_websocket_adapter(comm)\n",
			"\n",
			" function ondownload(figure, format) {\n",
			" window.open(figure.imageObj.src);\n",
			" }\n",
			"\n",
			" var fig = new mpl.figure(id, ws_proxy,\n",
			" ondownload,\n",
			" element.get(0));\n",
			"\n",
			" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
			" // web socket which is closed, not our websocket->open comm proxy.\n",
			" ws_proxy.onopen();\n",
			"\n",
			" fig.parent_element = element.get(0);\n",
			" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
			" if (!fig.cell_info) {\n",
			" console.error(\"Failed to find cell for figure\", id, fig);\n",
			" return;\n",
			" }\n",
			"\n",
			" var output_index = fig.cell_info[2]\n",
			" var cell = fig.cell_info[0];\n",
			"\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
			" var width = fig.canvas.width/mpl.ratio\n",
			" fig.root.unbind('remove')\n",
			"\n",
			" // Update the output cell to use the data from the current canvas.\n",
			" fig.push_to_output();\n",
			" var dataURL = fig.canvas.toDataURL();\n",
			" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
			" // the notebook keyboard shortcuts fail.\n",
			" IPython.keyboard_manager.enable()\n",
			" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
			" fig.close_ws(fig, msg);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.close_ws = function(fig, msg){\n",
			" fig.send_message('closing', msg);\n",
			" // fig.ws.close()\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
			" // Turn the data on the canvas into data in the output cell.\n",
			" var width = this.canvas.width/mpl.ratio\n",
			" var dataURL = this.canvas.toDataURL();\n",
			" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Tell IPython that the notebook contents must change.\n",
			" IPython.notebook.set_dirty(true);\n",
			" this.send_message(\"ack\", {});\n",
			" var fig = this;\n",
			" // Wait a second, then push the new image to the DOM so\n",
			" // that it is saved nicely (might be nice to debounce this).\n",
			" setTimeout(function () { fig.push_to_output() }, 1000);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items){\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) { continue; };\n",
			"\n",
			" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" // Add the status bar.\n",
			" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"\n",
			" // Add the close button to the window.\n",
			" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
			" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
			" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
			" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
			" buttongrp.append(button);\n",
			" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
			" titlebar.prepend(buttongrp);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(el){\n",
			" var fig = this\n",
			" el.on(\"remove\", function(){\n",
			"\tfig.close_ws(fig, {});\n",
			" });\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(el){\n",
			" // this is important to make the div 'focusable\n",
			" el.attr('tabindex', 0)\n",
			" // reach out to IPython and tell the keyboard manager to turn it's self\n",
			" // off when our div gets focus\n",
			"\n",
			" // location in version 3\n",
			" if (IPython.notebook.keyboard_manager) {\n",
			" IPython.notebook.keyboard_manager.register_events(el);\n",
			" }\n",
			" else {\n",
			" // location in version 2\n",
			" IPython.keyboard_manager.register_events(el);\n",
			" }\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" var manager = IPython.notebook.keyboard_manager;\n",
			" if (!manager)\n",
			" manager = IPython.keyboard_manager;\n",
			"\n",
			" // Check for shift+enter\n",
			" if (event.shiftKey && event.which == 13) {\n",
			" this.canvas_div.blur();\n",
			" event.shiftKey = false;\n",
			" // Send a \"J\" for go to next cell\n",
			" event.which = 74;\n",
			" event.keyCode = 74;\n",
			" manager.command_mode();\n",
			" manager.handle_keydown(event);\n",
			" }\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" fig.ondownload(fig, null);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.find_output_cell = function(html_output) {\n",
			" // Return the cell and output element which can be found uniquely in the notebook.\n",
			" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
			" // IPython event is triggered only after the cells have been serialised, which for\n",
			" // our purposes (turning an active figure into a static one), is too late.\n",
			" var cells = IPython.notebook.get_cells();\n",
			" var ncells = cells.length;\n",
			" for (var i=0; i<ncells; i++) {\n",
			" var cell = cells[i];\n",
			" if (cell.cell_type === 'code'){\n",
			" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
			" var data = cell.output_area.outputs[j];\n",
			" if (data.data) {\n",
			" // IPython >= 3 moved mimebundle to data attribute of output\n",
			" data = data.data;\n",
			" }\n",
			" if (data['text/html'] == html_output) {\n",
			" return [cell, data, j];\n",
			" }\n",
			" }\n",
			" }\n",
			" }\n",
			"}\n",
			"\n",
			"// Register the function which deals with the matplotlib target/channel.\n",
			"// The kernel may be null if the page has been refreshed.\n",
			"if (IPython.notebook.kernel != null) {\n",
			" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
			"}\n"
			],
			"text/plain": [
			"<IPython.core.display.Javascript object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/html": [
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\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"plt.figure()\n",
			"for dist in example.distance:\n",
			" example.weighted_rentability.sel( distance = dist ).plot(label = 'DR = %d' %(dist), color = 'C%d' %(dist))\n",
			" # example.PV_per_m2_global_yearly.sel( distance = dist ).plot(label = 'DR = %d' %(dist), color = 'C%d' %(dist), linestyle = '--')\n",
			" \n",
			"plt.legend()\n",
			"plt.grid()\n",
			"plt.title('Weighted rentability of PV output and efficiency')\n",
			"\n",
			"plt.tight_layout()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 68,
			"metadata": {
			"scrolled": false
			},
			"outputs": [
			{
			"data": {
			"application/javascript": [
			"/* Put everything inside the global mpl namespace */\n",
			"window.mpl = {};\n",
			"\n",
			"\n",
			"mpl.get_websocket_type = function() {\n",
			" if (typeof(WebSocket) !== 'undefined') {\n",
			" return WebSocket;\n",
			" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
			" return MozWebSocket;\n",
			" } else {\n",
			" alert('Your browser does not have WebSocket support.' +\n",
			" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
			" 'Firefox 4 and 5 are also supported but you ' +\n",
			" 'have to enable WebSockets in about:config.');\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
			" this.id = figure_id;\n",
			"\n",
			" this.ws = websocket;\n",
			"\n",
			" this.supports_binary = (this.ws.binaryType != undefined);\n",
			"\n",
			" if (!this.supports_binary) {\n",
			" var warnings = document.getElementById(\"mpl-warnings\");\n",
			" if (warnings) {\n",
			" warnings.style.display = 'block';\n",
			" warnings.textContent = (\n",
			" \"This browser does not support binary websocket messages. \" +\n",
			" \"Performance may be slow.\");\n",
			" }\n",
			" }\n",
			"\n",
			" this.imageObj = new Image();\n",
			"\n",
			" this.context = undefined;\n",
			" this.message = undefined;\n",
			" this.canvas = undefined;\n",
			" this.rubberband_canvas = undefined;\n",
			" this.rubberband_context = undefined;\n",
			" this.format_dropdown = undefined;\n",
			"\n",
			" this.image_mode = 'full';\n",
			"\n",
			" this.root = $('<div/>');\n",
			" this._root_extra_style(this.root)\n",
			" this.root.attr('style', 'display: inline-block');\n",
			"\n",
			" $(parent_element).append(this.root);\n",
			"\n",
			" this._init_header(this);\n",
			" this._init_canvas(this);\n",
			" this._init_toolbar(this);\n",
			"\n",
			" var fig = this;\n",
			"\n",
			" this.waiting = false;\n",
			"\n",
			" this.ws.onopen = function () {\n",
			" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
			" fig.send_message(\"send_image_mode\", {});\n",
			" if (mpl.ratio != 1) {\n",
			" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
			" }\n",
			" fig.send_message(\"refresh\", {});\n",
			" }\n",
			"\n",
			" this.imageObj.onload = function() {\n",
			" if (fig.image_mode == 'full') {\n",
			" // Full images could contain transparency (where diff images\n",
			" // almost always do), so we need to clear the canvas so that\n",
			" // there is no ghosting.\n",
			" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
			" }\n",
			" fig.context.drawImage(fig.imageObj, 0, 0);\n",
			" };\n",
			"\n",
			" this.imageObj.onunload = function() {\n",
			" fig.ws.close();\n",
			" }\n",
			"\n",
			" this.ws.onmessage = this._make_on_message_function(this);\n",
			"\n",
			" this.ondownload = ondownload;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_header = function() {\n",
			" var titlebar = $(\n",
			" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
			" 'ui-helper-clearfix\"/>');\n",
			" var titletext = $(\n",
			" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
			" 'text-align: center; padding: 3px;\"/>');\n",
			" titlebar.append(titletext)\n",
			" this.root.append(titlebar);\n",
			" this.header = titletext[0];\n",
			"}\n",
			"\n",
			"\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_canvas = function() {\n",
			" var fig = this;\n",
			"\n",
			" var canvas_div = $('<div/>');\n",
			"\n",
			" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
			"\n",
			" function canvas_keyboard_event(event) {\n",
			" return fig.key_event(event, event['data']);\n",
			" }\n",
			"\n",
			" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
			" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
			" this.canvas_div = canvas_div\n",
			" this._canvas_extra_style(canvas_div)\n",
			" this.root.append(canvas_div);\n",
			"\n",
			" var canvas = $('<canvas/>');\n",
			" canvas.addClass('mpl-canvas');\n",
			" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
			"\n",
			" this.canvas = canvas[0];\n",
			" this.context = canvas[0].getContext(\"2d\");\n",
			"\n",
			" var backingStore = this.context.backingStorePixelRatio \|\|\n",
			"\tthis.context.webkitBackingStorePixelRatio \|\|\n",
			"\tthis.context.mozBackingStorePixelRatio \|\|\n",
			"\tthis.context.msBackingStorePixelRatio \|\|\n",
			"\tthis.context.oBackingStorePixelRatio \|\|\n",
			"\tthis.context.backingStorePixelRatio \|\| 1;\n",
			"\n",
			" mpl.ratio = (window.devicePixelRatio \|\| 1) / backingStore;\n",
			"\n",
			" var rubberband = $('<canvas/>');\n",
			" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
			"\n",
			" var pass_mouse_events = true;\n",
			"\n",
			" canvas_div.resizable({\n",
			" start: function(event, ui) {\n",
			" pass_mouse_events = false;\n",
			" },\n",
			" resize: function(event, ui) {\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" stop: function(event, ui) {\n",
			" pass_mouse_events = true;\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" });\n",
			"\n",
			" function mouse_event_fn(event) {\n",
			" if (pass_mouse_events)\n",
			" return fig.mouse_event(event, event['data']);\n",
			" }\n",
			"\n",
			" rubberband.mousedown('button_press', mouse_event_fn);\n",
			" rubberband.mouseup('button_release', mouse_event_fn);\n",
			" // Throttle sequential mouse events to 1 every 20ms.\n",
			" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
			"\n",
			" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
			" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
			"\n",
			" canvas_div.on(\"wheel\", function (event) {\n",
			" event = event.originalEvent;\n",
			" event['data'] = 'scroll'\n",
			" if (event.deltaY < 0) {\n",
			" event.step = 1;\n",
			" } else {\n",
			" event.step = -1;\n",
			" }\n",
			" mouse_event_fn(event);\n",
			" });\n",
			"\n",
			" canvas_div.append(canvas);\n",
			" canvas_div.append(rubberband);\n",
			"\n",
			" this.rubberband = rubberband;\n",
			" this.rubberband_canvas = rubberband[0];\n",
			" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
			" this.rubberband_context.strokeStyle = \"#000000\";\n",
			"\n",
			" this._resize_canvas = function(width, height) {\n",
			" // Keep the size of the canvas, canvas container, and rubber band\n",
			" // canvas in synch.\n",
			" canvas_div.css('width', width)\n",
			" canvas_div.css('height', height)\n",
			"\n",
			" canvas.attr('width', width * mpl.ratio);\n",
			" canvas.attr('height', height * mpl.ratio);\n",
			" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
			"\n",
			" rubberband.attr('width', width);\n",
			" rubberband.attr('height', height);\n",
			" }\n",
			"\n",
			" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
			" // upon first draw.\n",
			" this._resize_canvas(600, 600);\n",
			"\n",
			" // Disable right mouse context menu.\n",
			" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
			" return false;\n",
			" });\n",
			"\n",
			" function set_focus () {\n",
			" canvas.focus();\n",
			" canvas_div.focus();\n",
			" }\n",
			"\n",
			" window.setTimeout(set_focus, 100);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items) {\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) {\n",
			" // put a spacer in here.\n",
			" continue;\n",
			" }\n",
			" var button = $('<button/>');\n",
			" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
			" 'ui-button-icon-only');\n",
			" button.attr('role', 'button');\n",
			" button.attr('aria-disabled', 'false');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			"\n",
			" var icon_img = $('<span/>');\n",
			" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
			" icon_img.addClass(image);\n",
			" icon_img.addClass('ui-corner-all');\n",
			"\n",
			" var tooltip_span = $('<span/>');\n",
			" tooltip_span.addClass('ui-button-text');\n",
			" tooltip_span.html(tooltip);\n",
			"\n",
			" button.append(icon_img);\n",
			" button.append(tooltip_span);\n",
			"\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" var fmt_picker_span = $('<span/>');\n",
			"\n",
			" var fmt_picker = $('<select/>');\n",
			" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
			" fmt_picker_span.append(fmt_picker);\n",
			" nav_element.append(fmt_picker_span);\n",
			" this.format_dropdown = fmt_picker[0];\n",
			"\n",
			" for (var ind in mpl.extensions) {\n",
			" var fmt = mpl.extensions[ind];\n",
			" var option = $(\n",
			" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
			" fmt_picker.append(option)\n",
			" }\n",
			"\n",
			" // Add hover states to the ui-buttons\n",
			" $( \".ui-button\" ).hover(\n",
			" function() { $(this).addClass(\"ui-state-hover\");},\n",
			" function() { $(this).removeClass(\"ui-state-hover\");}\n",
			" );\n",
			"\n",
			" var status_bar = $('<span class=\"mpl-message\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
			" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
			" // which will in turn request a refresh of the image.\n",
			" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_message = function(type, properties) {\n",
			" properties['type'] = type;\n",
			" properties['figure_id'] = this.id;\n",
			" this.ws.send(JSON.stringify(properties));\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_draw_message = function() {\n",
			" if (!this.waiting) {\n",
			" this.waiting = true;\n",
			" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
			" }\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" var format_dropdown = fig.format_dropdown;\n",
			" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
			" fig.ondownload(fig, format);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
			" var size = msg['size'];\n",
			" if (size[0] != fig.canvas.width \|\| size[1] != fig.canvas.height) {\n",
			" fig._resize_canvas(size[0], size[1]);\n",
			" fig.send_message(\"refresh\", {});\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
			" var x0 = msg['x0'] / mpl.ratio;\n",
			" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
			" var x1 = msg['x1'] / mpl.ratio;\n",
			" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
			" x0 = Math.floor(x0) + 0.5;\n",
			" y0 = Math.floor(y0) + 0.5;\n",
			" x1 = Math.floor(x1) + 0.5;\n",
			" y1 = Math.floor(y1) + 0.5;\n",
			" var min_x = Math.min(x0, x1);\n",
			" var min_y = Math.min(y0, y1);\n",
			" var width = Math.abs(x1 - x0);\n",
			" var height = Math.abs(y1 - y0);\n",
			"\n",
			" fig.rubberband_context.clearRect(\n",
			" 0, 0, fig.canvas.width, fig.canvas.height);\n",
			"\n",
			" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
			" // Updates the figure title.\n",
			" fig.header.textContent = msg['label'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
			" var cursor = msg['cursor'];\n",
			" switch(cursor)\n",
			" {\n",
			" case 0:\n",
			" cursor = 'pointer';\n",
			" break;\n",
			" case 1:\n",
			" cursor = 'default';\n",
			" break;\n",
			" case 2:\n",
			" cursor = 'crosshair';\n",
			" break;\n",
			" case 3:\n",
			" cursor = 'move';\n",
			" break;\n",
			" }\n",
			" fig.rubberband_canvas.style.cursor = cursor;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
			" fig.message.textContent = msg['message'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
			" // Request the server to send over a new figure.\n",
			" fig.send_draw_message();\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
			" fig.image_mode = msg['mode'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Called whenever the canvas gets updated.\n",
			" this.send_message(\"ack\", {});\n",
			"}\n",
			"\n",
			"// A function to construct a web socket function for onmessage handling.\n",
			"// Called in the figure constructor.\n",
			"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
			" return function socket_on_message(evt) {\n",
			" if (evt.data instanceof Blob) {\n",
			" /* FIXME: We get \"Resource interpreted as Image but\n",
			" * transferred with MIME type text/plain:\" errors on\n",
			" * Chrome. But how to set the MIME type? It doesn't seem\n",
			" * to be part of the websocket stream */\n",
			" evt.data.type = \"image/png\";\n",
			"\n",
			" /* Free the memory for the previous frames */\n",
			" if (fig.imageObj.src) {\n",
			" (window.URL \|\| window.webkitURL).revokeObjectURL(\n",
			" fig.imageObj.src);\n",
			" }\n",
			"\n",
			" fig.imageObj.src = (window.URL \|\| window.webkitURL).createObjectURL(\n",
			" evt.data);\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
			" fig.imageObj.src = evt.data;\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			"\n",
			" var msg = JSON.parse(evt.data);\n",
			" var msg_type = msg['type'];\n",
			"\n",
			" // Call the \"handle_{type}\" callback, which takes\n",
			" // the figure and JSON message as its only arguments.\n",
			" try {\n",
			" var callback = fig[\"handle_\" + msg_type];\n",
			" } catch (e) {\n",
			" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
			" return;\n",
			" }\n",
			"\n",
			" if (callback) {\n",
			" try {\n",
			" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
			" callback(fig, msg);\n",
			" } catch (e) {\n",
			" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
			" }\n",
			" }\n",
			" };\n",
			"}\n",
			"\n",
			"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
			"mpl.findpos = function(e) {\n",
			" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
			" var targ;\n",
			" if (!e)\n",
			" e = window.event;\n",
			" if (e.target)\n",
			" targ = e.target;\n",
			" else if (e.srcElement)\n",
			" targ = e.srcElement;\n",
			" if (targ.nodeType == 3) // defeat Safari bug\n",
			" targ = targ.parentNode;\n",
			"\n",
			" // jQuery normalizes the pageX and pageY\n",
			" // pageX,Y are the mouse positions relative to the document\n",
			" // offset() returns the position of the element relative to the document\n",
			" var x = e.pageX - $(targ).offset().left;\n",
			" var y = e.pageY - $(targ).offset().top;\n",
			"\n",
			" return {\"x\": x, \"y\": y};\n",
			"};\n",
			"\n",
			"/*\n",
			" * return a copy of an object with only non-object keys\n",
			" * we need this to avoid circular references\n",
			" * http://stackoverflow.com/a/24161582/3208463\n",
			" */\n",
			"function simpleKeys (original) {\n",
			" return Object.keys(original).reduce(function (obj, key) {\n",
			" if (typeof original[key] !== 'object')\n",
			" obj[key] = original[key]\n",
			" return obj;\n",
			" }, {});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.mouse_event = function(event, name) {\n",
			" var canvas_pos = mpl.findpos(event)\n",
			"\n",
			" if (name === 'button_press')\n",
			" {\n",
			" this.canvas.focus();\n",
			" this.canvas_div.focus();\n",
			" }\n",
			"\n",
			" var x = canvas_pos.x * mpl.ratio;\n",
			" var y = canvas_pos.y * mpl.ratio;\n",
			"\n",
			" this.send_message(name, {x: x, y: y, button: event.button,\n",
			" step: event.step,\n",
			" guiEvent: simpleKeys(event)});\n",
			"\n",
			" /* This prevents the web browser from automatically changing to\n",
			" * the text insertion cursor when the button is pressed. We want\n",
			" * to control all of the cursor setting manually through the\n",
			" * 'cursor' event from matplotlib */\n",
			" event.preventDefault();\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" // Handle any extra behaviour associated with a key event\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.key_event = function(event, name) {\n",
			"\n",
			" // Prevent repeat events\n",
			" if (name == 'key_press')\n",
			" {\n",
			" if (event.which === this._key)\n",
			" return;\n",
			" else\n",
			" this._key = event.which;\n",
			" }\n",
			" if (name == 'key_release')\n",
			" this._key = null;\n",
			"\n",
			" var value = '';\n",
			" if (event.ctrlKey && event.which != 17)\n",
			" value += \"ctrl+\";\n",
			" if (event.altKey && event.which != 18)\n",
			" value += \"alt+\";\n",
			" if (event.shiftKey && event.which != 16)\n",
			" value += \"shift+\";\n",
			"\n",
			" value += 'k';\n",
			" value += event.which.toString();\n",
			"\n",
			" this._key_event_extra(event, name);\n",
			"\n",
			" this.send_message(name, {key: value,\n",
			" guiEvent: simpleKeys(event)});\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
			" if (name == 'download') {\n",
			" this.handle_save(this, null);\n",
			" } else {\n",
			" this.send_message(\"toolbar_button\", {name: name});\n",
			" }\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
			" this.message.textContent = tooltip;\n",
			"};\n",
			"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
			"\n",
			"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
			"\n",
			"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
			" // Create a \"websocket\"-like object which calls the given IPython comm\n",
			" // object with the appropriate methods. Currently this is a non binary\n",
			" // socket, so there is still some room for performance tuning.\n",
			" var ws = {};\n",
			"\n",
			" ws.close = function() {\n",
			" comm.close()\n",
			" };\n",
			" ws.send = function(m) {\n",
			" //console.log('sending', m);\n",
			" comm.send(m);\n",
			" };\n",
			" // Register the callback with on_msg.\n",
			" comm.on_msg(function(msg) {\n",
			" //console.log('receiving', msg['content']['data'], msg);\n",
			" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
			" ws.onmessage(msg['content']['data'])\n",
			" });\n",
			" return ws;\n",
			"}\n",
			"\n",
			"mpl.mpl_figure_comm = function(comm, msg) {\n",
			" // This is the function which gets called when the mpl process\n",
			" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
			"\n",
			" var id = msg.content.data.id;\n",
			" // Get hold of the div created by the display call when the Comm\n",
			" // socket was opened in Python.\n",
			" var element = $(\"#\" + id);\n",
			" var ws_proxy = comm_websocket_adapter(comm)\n",
			"\n",
			" function ondownload(figure, format) {\n",
			" window.open(figure.imageObj.src);\n",
			" }\n",
			"\n",
			" var fig = new mpl.figure(id, ws_proxy,\n",
			" ondownload,\n",
			" element.get(0));\n",
			"\n",
			" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
			" // web socket which is closed, not our websocket->open comm proxy.\n",
			" ws_proxy.onopen();\n",
			"\n",
			" fig.parent_element = element.get(0);\n",
			" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
			" if (!fig.cell_info) {\n",
			" console.error(\"Failed to find cell for figure\", id, fig);\n",
			" return;\n",
			" }\n",
			"\n",
			" var output_index = fig.cell_info[2]\n",
			" var cell = fig.cell_info[0];\n",
			"\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
			" var width = fig.canvas.width/mpl.ratio\n",
			" fig.root.unbind('remove')\n",
			"\n",
			" // Update the output cell to use the data from the current canvas.\n",
			" fig.push_to_output();\n",
			" var dataURL = fig.canvas.toDataURL();\n",
			" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
			" // the notebook keyboard shortcuts fail.\n",
			" IPython.keyboard_manager.enable()\n",
			" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
			" fig.close_ws(fig, msg);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.close_ws = function(fig, msg){\n",
			" fig.send_message('closing', msg);\n",
			" // fig.ws.close()\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
			" // Turn the data on the canvas into data in the output cell.\n",
			" var width = this.canvas.width/mpl.ratio\n",
			" var dataURL = this.canvas.toDataURL();\n",
			" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Tell IPython that the notebook contents must change.\n",
			" IPython.notebook.set_dirty(true);\n",
			" this.send_message(\"ack\", {});\n",
			" var fig = this;\n",
			" // Wait a second, then push the new image to the DOM so\n",
			" // that it is saved nicely (might be nice to debounce this).\n",
			" setTimeout(function () { fig.push_to_output() }, 1000);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items){\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) { continue; };\n",
			"\n",
			" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" // Add the status bar.\n",
			" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"\n",
			" // Add the close button to the window.\n",
			" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
			" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
			" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
			" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
			" buttongrp.append(button);\n",
			" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
			" titlebar.prepend(buttongrp);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(el){\n",
			" var fig = this\n",
			" el.on(\"remove\", function(){\n",
			"\tfig.close_ws(fig, {});\n",
			" });\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(el){\n",
			" // this is important to make the div 'focusable\n",
			" el.attr('tabindex', 0)\n",
			" // reach out to IPython and tell the keyboard manager to turn it's self\n",
			" // off when our div gets focus\n",
			"\n",
			" // location in version 3\n",
			" if (IPython.notebook.keyboard_manager) {\n",
			" IPython.notebook.keyboard_manager.register_events(el);\n",
			" }\n",
			" else {\n",
			" // location in version 2\n",
			" IPython.keyboard_manager.register_events(el);\n",
			" }\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" var manager = IPython.notebook.keyboard_manager;\n",
			" if (!manager)\n",
			" manager = IPython.keyboard_manager;\n",
			"\n",
			" // Check for shift+enter\n",
			" if (event.shiftKey && event.which == 13) {\n",
			" this.canvas_div.blur();\n",
			" event.shiftKey = false;\n",
			" // Send a \"J\" for go to next cell\n",
			" event.which = 74;\n",
			" event.keyCode = 74;\n",
			" manager.command_mode();\n",
			" manager.handle_keydown(event);\n",
			" }\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" fig.ondownload(fig, null);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.find_output_cell = function(html_output) {\n",
			" // Return the cell and output element which can be found uniquely in the notebook.\n",
			" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
			" // IPython event is triggered only after the cells have been serialised, which for\n",
			" // our purposes (turning an active figure into a static one), is too late.\n",
			" var cells = IPython.notebook.get_cells();\n",
			" var ncells = cells.length;\n",
			" for (var i=0; i<ncells; i++) {\n",
			" var cell = cells[i];\n",
			" if (cell.cell_type === 'code'){\n",
			" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
			" var data = cell.output_area.outputs[j];\n",
			" if (data.data) {\n",
			" // IPython >= 3 moved mimebundle to data attribute of output\n",
			" data = data.data;\n",
			" }\n",
			" if (data['text/html'] == html_output) {\n",
			" return [cell, data, j];\n",
			" }\n",
			" }\n",
			" }\n",
			" }\n",
			"}\n",
			"\n",
			"// Register the function which deals with the matplotlib target/channel.\n",
			"// The kernel may be null if the page has been refreshed.\n",
			"if (IPython.notebook.kernel != null) {\n",
			" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
			"}\n"
			],
			"text/plain": [
			"<IPython.core.display.Javascript object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
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\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"plt.figure()\n",
			"for dist in example.distance:\n",
			" example.PV_per_m2_yearly.sel( distance = dist ).plot(label = 'DR = %d' %(dist), color = 'C%d' %(dist))\n",
			" # example.PV_per_m2_global_yearly.sel( distance = dist ).plot(label = 'DR = %d' %(dist), color = 'C%d' %(dist), linestyle = '--')\n",
			" \n",
			"plt.legend()\n",
			"plt.grid()\n",
			"plt.title('Yearly PV output per m2 of roof')\n",
			"\n",
			"plt.tight_layout()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 70,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"application/javascript": [
			"/* Put everything inside the global mpl namespace */\n",
			"window.mpl = {};\n",
			"\n",
			"\n",
			"mpl.get_websocket_type = function() {\n",
			" if (typeof(WebSocket) !== 'undefined') {\n",
			" return WebSocket;\n",
			" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
			" return MozWebSocket;\n",
			" } else {\n",
			" alert('Your browser does not have WebSocket support.' +\n",
			" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
			" 'Firefox 4 and 5 are also supported but you ' +\n",
			" 'have to enable WebSockets in about:config.');\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
			" this.id = figure_id;\n",
			"\n",
			" this.ws = websocket;\n",
			"\n",
			" this.supports_binary = (this.ws.binaryType != undefined);\n",
			"\n",
			" if (!this.supports_binary) {\n",
			" var warnings = document.getElementById(\"mpl-warnings\");\n",
			" if (warnings) {\n",
			" warnings.style.display = 'block';\n",
			" warnings.textContent = (\n",
			" \"This browser does not support binary websocket messages. \" +\n",
			" \"Performance may be slow.\");\n",
			" }\n",
			" }\n",
			"\n",
			" this.imageObj = new Image();\n",
			"\n",
			" this.context = undefined;\n",
			" this.message = undefined;\n",
			" this.canvas = undefined;\n",
			" this.rubberband_canvas = undefined;\n",
			" this.rubberband_context = undefined;\n",
			" this.format_dropdown = undefined;\n",
			"\n",
			" this.image_mode = 'full';\n",
			"\n",
			" this.root = $('<div/>');\n",
			" this._root_extra_style(this.root)\n",
			" this.root.attr('style', 'display: inline-block');\n",
			"\n",
			" $(parent_element).append(this.root);\n",
			"\n",
			" this._init_header(this);\n",
			" this._init_canvas(this);\n",
			" this._init_toolbar(this);\n",
			"\n",
			" var fig = this;\n",
			"\n",
			" this.waiting = false;\n",
			"\n",
			" this.ws.onopen = function () {\n",
			" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
			" fig.send_message(\"send_image_mode\", {});\n",
			" if (mpl.ratio != 1) {\n",
			" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
			" }\n",
			" fig.send_message(\"refresh\", {});\n",
			" }\n",
			"\n",
			" this.imageObj.onload = function() {\n",
			" if (fig.image_mode == 'full') {\n",
			" // Full images could contain transparency (where diff images\n",
			" // almost always do), so we need to clear the canvas so that\n",
			" // there is no ghosting.\n",
			" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
			" }\n",
			" fig.context.drawImage(fig.imageObj, 0, 0);\n",
			" };\n",
			"\n",
			" this.imageObj.onunload = function() {\n",
			" fig.ws.close();\n",
			" }\n",
			"\n",
			" this.ws.onmessage = this._make_on_message_function(this);\n",
			"\n",
			" this.ondownload = ondownload;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_header = function() {\n",
			" var titlebar = $(\n",
			" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
			" 'ui-helper-clearfix\"/>');\n",
			" var titletext = $(\n",
			" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
			" 'text-align: center; padding: 3px;\"/>');\n",
			" titlebar.append(titletext)\n",
			" this.root.append(titlebar);\n",
			" this.header = titletext[0];\n",
			"}\n",
			"\n",
			"\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_canvas = function() {\n",
			" var fig = this;\n",
			"\n",
			" var canvas_div = $('<div/>');\n",
			"\n",
			" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
			"\n",
			" function canvas_keyboard_event(event) {\n",
			" return fig.key_event(event, event['data']);\n",
			" }\n",
			"\n",
			" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
			" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
			" this.canvas_div = canvas_div\n",
			" this._canvas_extra_style(canvas_div)\n",
			" this.root.append(canvas_div);\n",
			"\n",
			" var canvas = $('<canvas/>');\n",
			" canvas.addClass('mpl-canvas');\n",
			" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
			"\n",
			" this.canvas = canvas[0];\n",
			" this.context = canvas[0].getContext(\"2d\");\n",
			"\n",
			" var backingStore = this.context.backingStorePixelRatio \|\|\n",
			"\tthis.context.webkitBackingStorePixelRatio \|\|\n",
			"\tthis.context.mozBackingStorePixelRatio \|\|\n",
			"\tthis.context.msBackingStorePixelRatio \|\|\n",
			"\tthis.context.oBackingStorePixelRatio \|\|\n",
			"\tthis.context.backingStorePixelRatio \|\| 1;\n",
			"\n",
			" mpl.ratio = (window.devicePixelRatio \|\| 1) / backingStore;\n",
			"\n",
			" var rubberband = $('<canvas/>');\n",
			" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
			"\n",
			" var pass_mouse_events = true;\n",
			"\n",
			" canvas_div.resizable({\n",
			" start: function(event, ui) {\n",
			" pass_mouse_events = false;\n",
			" },\n",
			" resize: function(event, ui) {\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" stop: function(event, ui) {\n",
			" pass_mouse_events = true;\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" });\n",
			"\n",
			" function mouse_event_fn(event) {\n",
			" if (pass_mouse_events)\n",
			" return fig.mouse_event(event, event['data']);\n",
			" }\n",
			"\n",
			" rubberband.mousedown('button_press', mouse_event_fn);\n",
			" rubberband.mouseup('button_release', mouse_event_fn);\n",
			" // Throttle sequential mouse events to 1 every 20ms.\n",
			" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
			"\n",
			" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
			" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
			"\n",
			" canvas_div.on(\"wheel\", function (event) {\n",
			" event = event.originalEvent;\n",
			" event['data'] = 'scroll'\n",
			" if (event.deltaY < 0) {\n",
			" event.step = 1;\n",
			" } else {\n",
			" event.step = -1;\n",
			" }\n",
			" mouse_event_fn(event);\n",
			" });\n",
			"\n",
			" canvas_div.append(canvas);\n",
			" canvas_div.append(rubberband);\n",
			"\n",
			" this.rubberband = rubberband;\n",
			" this.rubberband_canvas = rubberband[0];\n",
			" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
			" this.rubberband_context.strokeStyle = \"#000000\";\n",
			"\n",
			" this._resize_canvas = function(width, height) {\n",
			" // Keep the size of the canvas, canvas container, and rubber band\n",
			" // canvas in synch.\n",
			" canvas_div.css('width', width)\n",
			" canvas_div.css('height', height)\n",
			"\n",
			" canvas.attr('width', width * mpl.ratio);\n",
			" canvas.attr('height', height * mpl.ratio);\n",
			" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
			"\n",
			" rubberband.attr('width', width);\n",
			" rubberband.attr('height', height);\n",
			" }\n",
			"\n",
			" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
			" // upon first draw.\n",
			" this._resize_canvas(600, 600);\n",
			"\n",
			" // Disable right mouse context menu.\n",
			" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
			" return false;\n",
			" });\n",
			"\n",
			" function set_focus () {\n",
			" canvas.focus();\n",
			" canvas_div.focus();\n",
			" }\n",
			"\n",
			" window.setTimeout(set_focus, 100);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items) {\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) {\n",
			" // put a spacer in here.\n",
			" continue;\n",
			" }\n",
			" var button = $('<button/>');\n",
			" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
			" 'ui-button-icon-only');\n",
			" button.attr('role', 'button');\n",
			" button.attr('aria-disabled', 'false');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			"\n",
			" var icon_img = $('<span/>');\n",
			" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
			" icon_img.addClass(image);\n",
			" icon_img.addClass('ui-corner-all');\n",
			"\n",
			" var tooltip_span = $('<span/>');\n",
			" tooltip_span.addClass('ui-button-text');\n",
			" tooltip_span.html(tooltip);\n",
			"\n",
			" button.append(icon_img);\n",
			" button.append(tooltip_span);\n",
			"\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" var fmt_picker_span = $('<span/>');\n",
			"\n",
			" var fmt_picker = $('<select/>');\n",
			" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
			" fmt_picker_span.append(fmt_picker);\n",
			" nav_element.append(fmt_picker_span);\n",
			" this.format_dropdown = fmt_picker[0];\n",
			"\n",
			" for (var ind in mpl.extensions) {\n",
			" var fmt = mpl.extensions[ind];\n",
			" var option = $(\n",
			" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
			" fmt_picker.append(option)\n",
			" }\n",
			"\n",
			" // Add hover states to the ui-buttons\n",
			" $( \".ui-button\" ).hover(\n",
			" function() { $(this).addClass(\"ui-state-hover\");},\n",
			" function() { $(this).removeClass(\"ui-state-hover\");}\n",
			" );\n",
			"\n",
			" var status_bar = $('<span class=\"mpl-message\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
			" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
			" // which will in turn request a refresh of the image.\n",
			" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_message = function(type, properties) {\n",
			" properties['type'] = type;\n",
			" properties['figure_id'] = this.id;\n",
			" this.ws.send(JSON.stringify(properties));\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_draw_message = function() {\n",
			" if (!this.waiting) {\n",
			" this.waiting = true;\n",
			" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
			" }\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" var format_dropdown = fig.format_dropdown;\n",
			" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
			" fig.ondownload(fig, format);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
			" var size = msg['size'];\n",
			" if (size[0] != fig.canvas.width \|\| size[1] != fig.canvas.height) {\n",
			" fig._resize_canvas(size[0], size[1]);\n",
			" fig.send_message(\"refresh\", {});\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
			" var x0 = msg['x0'] / mpl.ratio;\n",
			" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
			" var x1 = msg['x1'] / mpl.ratio;\n",
			" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
			" x0 = Math.floor(x0) + 0.5;\n",
			" y0 = Math.floor(y0) + 0.5;\n",
			" x1 = Math.floor(x1) + 0.5;\n",
			" y1 = Math.floor(y1) + 0.5;\n",
			" var min_x = Math.min(x0, x1);\n",
			" var min_y = Math.min(y0, y1);\n",
			" var width = Math.abs(x1 - x0);\n",
			" var height = Math.abs(y1 - y0);\n",
			"\n",
			" fig.rubberband_context.clearRect(\n",
			" 0, 0, fig.canvas.width, fig.canvas.height);\n",
			"\n",
			" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
			" // Updates the figure title.\n",
			" fig.header.textContent = msg['label'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
			" var cursor = msg['cursor'];\n",
			" switch(cursor)\n",
			" {\n",
			" case 0:\n",
			" cursor = 'pointer';\n",
			" break;\n",
			" case 1:\n",
			" cursor = 'default';\n",
			" break;\n",
			" case 2:\n",
			" cursor = 'crosshair';\n",
			" break;\n",
			" case 3:\n",
			" cursor = 'move';\n",
			" break;\n",
			" }\n",
			" fig.rubberband_canvas.style.cursor = cursor;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
			" fig.message.textContent = msg['message'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
			" // Request the server to send over a new figure.\n",
			" fig.send_draw_message();\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
			" fig.image_mode = msg['mode'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Called whenever the canvas gets updated.\n",
			" this.send_message(\"ack\", {});\n",
			"}\n",
			"\n",
			"// A function to construct a web socket function for onmessage handling.\n",
			"// Called in the figure constructor.\n",
			"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
			" return function socket_on_message(evt) {\n",
			" if (evt.data instanceof Blob) {\n",
			" /* FIXME: We get \"Resource interpreted as Image but\n",
			" * transferred with MIME type text/plain:\" errors on\n",
			" * Chrome. But how to set the MIME type? It doesn't seem\n",
			" * to be part of the websocket stream */\n",
			" evt.data.type = \"image/png\";\n",
			"\n",
			" /* Free the memory for the previous frames */\n",
			" if (fig.imageObj.src) {\n",
			" (window.URL \|\| window.webkitURL).revokeObjectURL(\n",
			" fig.imageObj.src);\n",
			" }\n",
			"\n",
			" fig.imageObj.src = (window.URL \|\| window.webkitURL).createObjectURL(\n",
			" evt.data);\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
			" fig.imageObj.src = evt.data;\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			"\n",
			" var msg = JSON.parse(evt.data);\n",
			" var msg_type = msg['type'];\n",
			"\n",
			" // Call the \"handle_{type}\" callback, which takes\n",
			" // the figure and JSON message as its only arguments.\n",
			" try {\n",
			" var callback = fig[\"handle_\" + msg_type];\n",
			" } catch (e) {\n",
			" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
			" return;\n",
			" }\n",
			"\n",
			" if (callback) {\n",
			" try {\n",
			" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
			" callback(fig, msg);\n",
			" } catch (e) {\n",
			" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
			" }\n",
			" }\n",
			" };\n",
			"}\n",
			"\n",
			"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
			"mpl.findpos = function(e) {\n",
			" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
			" var targ;\n",
			" if (!e)\n",
			" e = window.event;\n",
			" if (e.target)\n",
			" targ = e.target;\n",
			" else if (e.srcElement)\n",
			" targ = e.srcElement;\n",
			" if (targ.nodeType == 3) // defeat Safari bug\n",
			" targ = targ.parentNode;\n",
			"\n",
			" // jQuery normalizes the pageX and pageY\n",
			" // pageX,Y are the mouse positions relative to the document\n",
			" // offset() returns the position of the element relative to the document\n",
			" var x = e.pageX - $(targ).offset().left;\n",
			" var y = e.pageY - $(targ).offset().top;\n",
			"\n",
			" return {\"x\": x, \"y\": y};\n",
			"};\n",
			"\n",
			"/*\n",
			" * return a copy of an object with only non-object keys\n",
			" * we need this to avoid circular references\n",
			" * http://stackoverflow.com/a/24161582/3208463\n",
			" */\n",
			"function simpleKeys (original) {\n",
			" return Object.keys(original).reduce(function (obj, key) {\n",
			" if (typeof original[key] !== 'object')\n",
			" obj[key] = original[key]\n",
			" return obj;\n",
			" }, {});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.mouse_event = function(event, name) {\n",
			" var canvas_pos = mpl.findpos(event)\n",
			"\n",
			" if (name === 'button_press')\n",
			" {\n",
			" this.canvas.focus();\n",
			" this.canvas_div.focus();\n",
			" }\n",
			"\n",
			" var x = canvas_pos.x * mpl.ratio;\n",
			" var y = canvas_pos.y * mpl.ratio;\n",
			"\n",
			" this.send_message(name, {x: x, y: y, button: event.button,\n",
			" step: event.step,\n",
			" guiEvent: simpleKeys(event)});\n",
			"\n",
			" /* This prevents the web browser from automatically changing to\n",
			" * the text insertion cursor when the button is pressed. We want\n",
			" * to control all of the cursor setting manually through the\n",
			" * 'cursor' event from matplotlib */\n",
			" event.preventDefault();\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" // Handle any extra behaviour associated with a key event\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.key_event = function(event, name) {\n",
			"\n",
			" // Prevent repeat events\n",
			" if (name == 'key_press')\n",
			" {\n",
			" if (event.which === this._key)\n",
			" return;\n",
			" else\n",
			" this._key = event.which;\n",
			" }\n",
			" if (name == 'key_release')\n",
			" this._key = null;\n",
			"\n",
			" var value = '';\n",
			" if (event.ctrlKey && event.which != 17)\n",
			" value += \"ctrl+\";\n",
			" if (event.altKey && event.which != 18)\n",
			" value += \"alt+\";\n",
			" if (event.shiftKey && event.which != 16)\n",
			" value += \"shift+\";\n",
			"\n",
			" value += 'k';\n",
			" value += event.which.toString();\n",
			"\n",
			" this._key_event_extra(event, name);\n",
			"\n",
			" this.send_message(name, {key: value,\n",
			" guiEvent: simpleKeys(event)});\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
			" if (name == 'download') {\n",
			" this.handle_save(this, null);\n",
			" } else {\n",
			" this.send_message(\"toolbar_button\", {name: name});\n",
			" }\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
			" this.message.textContent = tooltip;\n",
			"};\n",
			"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
			"\n",
			"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
			"\n",
			"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
			" // Create a \"websocket\"-like object which calls the given IPython comm\n",
			" // object with the appropriate methods. Currently this is a non binary\n",
			" // socket, so there is still some room for performance tuning.\n",
			" var ws = {};\n",
			"\n",
			" ws.close = function() {\n",
			" comm.close()\n",
			" };\n",
			" ws.send = function(m) {\n",
			" //console.log('sending', m);\n",
			" comm.send(m);\n",
			" };\n",
			" // Register the callback with on_msg.\n",
			" comm.on_msg(function(msg) {\n",
			" //console.log('receiving', msg['content']['data'], msg);\n",
			" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
			" ws.onmessage(msg['content']['data'])\n",
			" });\n",
			" return ws;\n",
			"}\n",
			"\n",
			"mpl.mpl_figure_comm = function(comm, msg) {\n",
			" // This is the function which gets called when the mpl process\n",
			" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
			"\n",
			" var id = msg.content.data.id;\n",
			" // Get hold of the div created by the display call when the Comm\n",
			" // socket was opened in Python.\n",
			" var element = $(\"#\" + id);\n",
			" var ws_proxy = comm_websocket_adapter(comm)\n",
			"\n",
			" function ondownload(figure, format) {\n",
			" window.open(figure.imageObj.src);\n",
			" }\n",
			"\n",
			" var fig = new mpl.figure(id, ws_proxy,\n",
			" ondownload,\n",
			" element.get(0));\n",
			"\n",
			" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
			" // web socket which is closed, not our websocket->open comm proxy.\n",
			" ws_proxy.onopen();\n",
			"\n",
			" fig.parent_element = element.get(0);\n",
			" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
			" if (!fig.cell_info) {\n",
			" console.error(\"Failed to find cell for figure\", id, fig);\n",
			" return;\n",
			" }\n",
			"\n",
			" var output_index = fig.cell_info[2]\n",
			" var cell = fig.cell_info[0];\n",
			"\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
			" var width = fig.canvas.width/mpl.ratio\n",
			" fig.root.unbind('remove')\n",
			"\n",
			" // Update the output cell to use the data from the current canvas.\n",
			" fig.push_to_output();\n",
			" var dataURL = fig.canvas.toDataURL();\n",
			" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
			" // the notebook keyboard shortcuts fail.\n",
			" IPython.keyboard_manager.enable()\n",
			" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
			" fig.close_ws(fig, msg);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.close_ws = function(fig, msg){\n",
			" fig.send_message('closing', msg);\n",
			" // fig.ws.close()\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
			" // Turn the data on the canvas into data in the output cell.\n",
			" var width = this.canvas.width/mpl.ratio\n",
			" var dataURL = this.canvas.toDataURL();\n",
			" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Tell IPython that the notebook contents must change.\n",
			" IPython.notebook.set_dirty(true);\n",
			" this.send_message(\"ack\", {});\n",
			" var fig = this;\n",
			" // Wait a second, then push the new image to the DOM so\n",
			" // that it is saved nicely (might be nice to debounce this).\n",
			" setTimeout(function () { fig.push_to_output() }, 1000);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items){\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) { continue; };\n",
			"\n",
			" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" // Add the status bar.\n",
			" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"\n",
			" // Add the close button to the window.\n",
			" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
			" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
			" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
			" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
			" buttongrp.append(button);\n",
			" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
			" titlebar.prepend(buttongrp);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(el){\n",
			" var fig = this\n",
			" el.on(\"remove\", function(){\n",
			"\tfig.close_ws(fig, {});\n",
			" });\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(el){\n",
			" // this is important to make the div 'focusable\n",
			" el.attr('tabindex', 0)\n",
			" // reach out to IPython and tell the keyboard manager to turn it's self\n",
			" // off when our div gets focus\n",
			"\n",
			" // location in version 3\n",
			" if (IPython.notebook.keyboard_manager) {\n",
			" IPython.notebook.keyboard_manager.register_events(el);\n",
			" }\n",
			" else {\n",
			" // location in version 2\n",
			" IPython.keyboard_manager.register_events(el);\n",
			" }\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" var manager = IPython.notebook.keyboard_manager;\n",
			" if (!manager)\n",
			" manager = IPython.keyboard_manager;\n",
			"\n",
			" // Check for shift+enter\n",
			" if (event.shiftKey && event.which == 13) {\n",
			" this.canvas_div.blur();\n",
			" event.shiftKey = false;\n",
			" // Send a \"J\" for go to next cell\n",
			" event.which = 74;\n",
			" event.keyCode = 74;\n",
			" manager.command_mode();\n",
			" manager.handle_keydown(event);\n",
			" }\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" fig.ondownload(fig, null);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.find_output_cell = function(html_output) {\n",
			" // Return the cell and output element which can be found uniquely in the notebook.\n",
			" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
			" // IPython event is triggered only after the cells have been serialised, which for\n",
			" // our purposes (turning an active figure into a static one), is too late.\n",
			" var cells = IPython.notebook.get_cells();\n",
			" var ncells = cells.length;\n",
			" for (var i=0; i<ncells; i++) {\n",
			" var cell = cells[i];\n",
			" if (cell.cell_type === 'code'){\n",
			" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
			" var data = cell.output_area.outputs[j];\n",
			" if (data.data) {\n",
			" // IPython >= 3 moved mimebundle to data attribute of output\n",
			" data = data.data;\n",
			" }\n",
			" if (data['text/html'] == html_output) {\n",
			" return [cell, data, j];\n",
			" }\n",
			" }\n",
			" }\n",
			" }\n",
			"}\n",
			"\n",
			"// Register the function which deals with the matplotlib target/channel.\n",
			"// The kernel may be null if the page has been refreshed.\n",
			"if (IPython.notebook.kernel != null) {\n",
			" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
			"}\n"
			],
			"text/plain": [
			"<IPython.core.display.Javascript object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
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qiKAmk4PfDWTVVWfQkx6kOtNX+FdtZAJVpvqYaPWJQod6cH/N7caU8nmdSWAKiIRWVF+lx4okR7NFanudSWAwkkhSeVbBR+MysVTaFweHklVjaCVG6Z2JirmkOdG4W4RHZGFYP+7SAmg7qNwn7xLmlcPZ3lgVJwi24SHmoPVpSInIkrViYoKNJfWKLtHIvJAKX9UXimFCyNtBB2cWyFT6a19p2Kk0HCw8hzlnRbeIr4qFJK3S6Q5tJmx+iWKaIsgRqsRdE0JoDymwkEeS+GgqnHZXORW+Xqh+ZQq9JHtRb6CjaDlad9dI2iRPH1OlQsoz5u8yyo8UWg2tOl1TQig7KB9qQpf2VJkXnmm8vqpgj0o+kxqX4iAK61AHljlQaoXZWiroUj2jI0xBDyLgBFAz5rGFItjBPTgEUnTAyW8ejiOlx3zpSnkKKKo0P3uerUFw4nyLKlViYkhYAgYAgmFgBHAhDK3LdYjCASbAo9yw00eUatRqyFPobxm8uaE5qZVtSiF83TMmdrHmBgChoAhkHAIGAFMOJPbghsQAYX81FZDITyFnoINjxtQpUZ/a3n7lMMlz59CksrnDB4T1ugXZwswBAwBQyBWCBgBjBWyNq8hsCsCSpBX7uEcQBWo4VWGhlnNEQgeZaeQuvK2lLhvYggYAoaAIbAbBIwA2hYxBAwBQ8AQMAQMAUMgwRAwAphgBrflGgKGgCFgCBgChoAhYATQ9oAhYAgYAoaAIWAIGAIJhoARQG8YXHZQvyw13DUxBAwBQ8AQMATiDQH1VNS528GTXeJtfY1uPUYAvWGyYYDOuDQxBAwBQ8AQMATiFQEdL6kiOBMPIGAE0ANGcE84WDNr1iy6dLGThrxhEtPCEDAEDAFDIBoIZGRkMHKkc6iQTlZSv87diRq169QcEUY9FE92T5kJXqcTWc4Lm0RHBqorQFB0Yo1O+dFJN2XuaU9XuUcBBseobZTOfg+eVKPxOmYyIcQIoDfMrCOu1qxevZpu3fT5MDEEDAFDwBAwBOIDgTVr1tC9u05AjJgA6nxuNWqXt1DHdFZGABVS1jnaQdFZ01tC/v99lzzqWE8dr/gc8C0wwR2jozV1nOLHwF1uj1adEa/jPp+KD+SrX4URQG9Y2QigN+xgWhgChoAhYAhEGYFaEMBQDZQzWBkBbA2cVIWq+7gN4eXZ+84dI+/gey4JXeeeGHRn2NGROuNcc+qM6bgXI4DeMLFDAJcvX84ee+hbE0PAEDAEDAFDID4QWLt2LT179tRiRKwyQlYlr52+qpOqCKCIms78ltfvU+AWIMud6ALgfqBNyMTJQBFwGvAG8AIgL2AoiTzMnUvh41BvYnwYImwVRgC9YVaHAE6dOpW0tDRvaGRaGAKGgCFgCBgCUUCgoKCACROCkdcKE/7ZPRqzpgTwTKAAWA70Bv7m5vbpuM1S4CY3R7Bf2MQbgduAx4EP3esVIg7KAOBnQP8uiMLSPT2FEUBvmMc8gN6wg2lhCBgChoAhEGUEYuABDNewF7AUGAt8Ug0BzARuBZ6oggAOBH4CFEJeGGUYPDedEUBvmMRyAL1hB9PCEDAEDAFDIMoIxCAHsDINRe4UBn4SsBBwBDY0AhgBSPUwxAhgPYBstzAEDAFDwBCofwTqgQCqfcYqN5/vbdeDNx8YEdJjdxzwQSVFIKom3u6iolDyKVYEUv97JJHvaAQwka1vazcEDAFDII4RqAUBbAH0cSHR6SHXAp8Bm90v5fGpPcx6NwdQvftauq1cgkUlagMjcjcxpA2MKoKDyYitgEVuKPgeYBCgNjDXWBuYON6MHlyaEUAPGsVUMgQMAUPAEKg7ArUggIe6hC/85s+77VvedI9PVSsYtXRRQYdy+0KPU1Ul75SwRtBXhjWCHuKOUbuYTW7jaJHBhBALAXvDzEYAvWEH08IQMAQMAUMgygjUggBGWQObrjIEjAB6Y18YAfSGHUwLQ8AQMAQMgSgjYAQwyoBGaTojgFECso7TGAGsI4B2uSFgCBgChoA3ETAC6E27GAH0hl2MAHrDDqaFIWAIGAKGQJQRMAIYZUCjNJ0RwCgBWcdpjADWEUC73BAwBAwBQ8CbCBgB9KZd4p0AHgxMAoYDXao4UPq8MNNMA3RodFBUSTQ5rJLoqrBKosHAo4AqidSMUuNVlh6pGAGMFCkbZwgYAg2KQNHSpRTOmUN5aRm+JD++pCTwJ4G+T07G508K/Mz9csakpDhjAuOTnd/5Utx/9b3GJifjTw78zPk+OEdqKn6/v0HXbDevGwJGAOuGX6yujncCeDQwBpjj9gw6GVD5eFD+4fYJ+m3Iz9RDKPQQaPUSEnnUeYEpwHPAtyG9hHSY9GLgY+Autw+RegldXYNeQkYAY7XDbV5DwBCoMQJlZWVsW7CQgpkzKZw3j23LllGyYQNl+flQXl7j+WJ+gS/kUeZ868OflkZyhw6k9uxJ04EDSTvgAJoNHRIgmSb1ioARwHqFO+KbxTsBDAVCf7UqI4DqI3RSFYjpPEB1E5dnTw0kJfIOvldJN/HOQLE75m53zv4RWsIIYIRA2TBDwBCIHgIiekU//ED+119TNO9Hti1fTunGjZQVFFR/E3nnRLpCyWDw+3CC6DHC6GvShKS2bUnt3p0m/fqSNmKEQw6TW+tRYBILBIwAxgLVus9pBDBA/kTc5PX71D1LMMuFtr7OEzQCWPe9bDMYAoZAFQiUFRc7Ydv8r7+haP7PFC9fQcmmTZQXFlaPWXIySW3akNqtG0369yNt+HCaH3ggyW2VGVN3EQFFX8XFON+XlEBpKeUl+tru/H95WRnlpaWB7/Wl7zXG/bds+/bAHMGflZVRlptL4fwFbFu0kO1r1lK6ZQvlxcH38yr0TkoiqVUrUrp0IbV3L5oNHUrz0aNp0rNn3Rea4DMYAfTmBkh0AngmoFfd5e5xMjoHMA8YDZQCNwHKEewXZr6NgI6iedztQK7rFSIOygDgZ0D/LqjE9E0AfQVFIeaFq1evpls3HWloYggYAoZAzREoKyoif9a3FMwS0ZtP8YqVlGZlUb4teDpW5XP6UlMdopfSvTtN9+lP2oj9SRtzIMktdCJXfIiwKZzzPfnffUvRzz9TvHIlpZmbAt7O6ryUPh/+5s0D4eQePWg6aCBpI0c6BNGfmhof4MR4FUYAYwxwLadPdAIYDlsvYCkwFvikGgKoQg8dO/NEFQRwIPCTeyD1wkpsc7tLICv8yghgLXexXWYIJBgCysXL/+prCkRm5i+geNUqSjdv3q2Xywl/tmtHao89aTpggENkmu+/v5Mvl6giz2PxsmUUfPUVhT/MY9vSpZSsX09pTo7jVaxOHDxFnLt1o2n/fjQbNozmo0ZFzUMaLzYxAuhNSxoB3NUuIne3AE8CsQoBmwfQm58H08oQ8BQCJdnZ5M+cScF3s9m2cAHb16yhZEs2KOxZjfiaNiW5fXtS99rL8Vg1H3kAzUYMN49VDa1bsnmzkx+p8HnRwkUO/k44eTceVVUyJ6Wnk9y5M0369KHZ4H1JGz2a1F69ErKi2QhgDTdePQ03AlgRaMVfV7kFHG+7HjwVgYwAZrtDxwEfVFIE0gkI/lVWKPkUwIpA6mkj220MgcaOgDxR+TNmkP2vV53K29Ls7EBOXHVET5WuHTvQZK+eNN13X5qPHkXTwYOt0jXGm8HJqZw7l4JZsyj6KRBOLsnM3H2VtMLJaWkkdehA+pFjaT9xohNejncxAuhNC8c7AVQCSx8X+u+Ba4HPgM3ul/L4XgfWuzmA6t3X0m3lEkyaURsYkbuJIW1gVBE8wZ23FbDIDQXfAwwC1AbmGmsD481Nb1oZAl5BQKRh88tTyf34Y4qXL6885BjMQevYkSa9etF08L5OIUaTAQMS0pvkFdtVpYcqqfMVTp47l+Kly9iekUHp1q1V2rZJv360+92FtDzmmLi1pxFAb+7aeCeAh7qELxz954FL3Z6A+wGq/1/nkjjl9m0IuUDlblPCGkFfGdYIeog7Ru1iNrmNoEUGIxWrAo4UKRtnCDRiBBwv3+efk/3qvyn4fg5lW3N2WY2/VSvShg4lbdQomo85kNQ+feKWGDRiU9ZYdYXzC775hoLZcyicPZuiBfOhbGdPReUTith3uOZqmvbtW+P5vXyBEUBvWifeCaA3Ud9VKyOAjcVSpqchUEMEtm/YyJaXXiT3088oXrFiV09QUpLTrLjl2LG0PXuCU21qEv8IqCo565lnyf73v52ik1BRoU6rk06kw2WXxUWI2AigN/ezEUBv2MUIoDfsYFoYAnVGQF6+vE8+Ifu11yj8fi5lqiYNk6TWrWk2fDitzziD5r8aYx6+OqPeuCcoXr2azIceJvezzygPbcLt89Fk771pe+GFpB9/XKPdJ0YAvbk/jQB6wy5GAL1hB9PCEKgVAsXr17PlxRfJk5dv5cpAY+IKLp0kJ3+vxbgjaTthAsnt2tXqPvV9kcjs5qLNZORnsKFgA1lFWWQVZpFbnEvfNn05sOuBdGquFGmTaCGQO306mx57nKIff6ywj9SrUY2pnRBx/0jrC6OlVd3mMQJYN/xidbURwFghW7N5jQDWDC8bbQg0KAKOl++jjwJevrk/OCdP7OLla9PGOWas9Zln0GKMjiSvfykpKyGzIJP1+evZWLCRTYWbHBK3pWgL2duy2Vq8lfzifPK351NQUsC20m0UlxazvWw7ZeVllLP7c3/9Pj8tU1rSpXkXerXuxZAOQxjddTQ9W9kJGnWxuCqNd4SI1ylFfafoKLtWJxxPu8suIzldx9F7W4wAetM+RgC9YRcjgN6wg2lhCFSJQHFGBluef4Hczz9n+6pVu3r5kpOdnm8tjxpHm7POisrZssUlxY7nLaMgg00FmwIErjDL8cpt3baVnO05AQJXkk9hSSFFJUUOeRPxKy2vvolxTU3tw0eSL4lkfzJJ/iQKtxdSRpinM2RSjW+e0pxOaZ0cMjio/SBGdRnFPm33abShzJpiFq3xxWvXOiHivE8/DbSaCYpCxH360Pa355N+0kmexdUIYLR2QnTnMQIYXTxrO5sRwNoiZ9cZAjFCQF6+3A8+YOvr/6Hwhx8oy9MpkRVFnpi0/fenzVlnOidA1FYWb1nMxys/5rv137F061KH3MWEwPmTSPWnkpqUStOkpjRLaeaQtPTUdFqltqJ1k9a0btqa9s3a07FZRzo27+h49vQ7v9+/y/LW5q1l5tqZzM2cyy9bfnFCxTnFObvVPS05zbnHXul7MbD9QEZ2HsnQjkMdcmlSPQK5M2aQ9djjzp6skGqQkuL0gexw1dU0G6hTSL0jRgC9Y4tQTYwAesMuRgC9YQfTIsERUDL+5hdfIk9evjWrK7TpcKBJSXE8Lunjx9P6rDNrFX5blr2Mj1Z+xLfrv3XInrx5CrfuTvz4Hc/bDgKX3JS0lDRapLSgZWpLWjVpRevU1rRt1tYhVx2adXDy8zo37+wQvPoUeSlnrpvJ9xu/R+RWRFEhZ3kmq5MmSU1o17Qde6bv6XgKR3Qe4XyJMJpUREAhYnmkt7zyCtvXrq3wSx1Pl37csbS/4opa7dFoY20EMNqIRmc+I4DRwbGusxgBrCuCdr0hUAsEykpKyHn/fba+8QZFP8yrGF5z51NLjuYHHOAQPp2bWxNZnbuaD1d8yKz1s/gl+xcnfFuVZy/Fn+KES/u37c8BXQ5wvGMicPqKFwKUV5zH1xlfM2fjHBZmLUT4bN622ck7rE6ETZumbejWopuDz7COwxi9x+h6J7Y1sX19jlUR0iZVEX/88S6e6tTevWl7/nm0OvXUBgsRGwGsz90Q+b2MAEaOVSxHGgGMJbo2tyEQgkBJVhabnniCvM+nO2e7Uh5W6JCS4jTilZevlbx8LXSg0O4lIy/D8eyJ4CzZsoTMwswqyZ5CnR3TOtKvdT9GdR3FuB7jaJ/Wfvc3idMRyl0UKVQI/Oesn1mVs8rJdywqLap2xcm+ZMfz2aVFF6cqeWiHoYzZY4yDbaJK/syvyHzsUacFEaUheeH0s/sAACAASURBVKAKEY8cSYerrnLOJq5PMQJYn2hHfi8jgJFjFcuRRgBjia7NbQgAOdOmsWnKo2xbsmQXPJLat3dy+NpMOIu0YcN2i5cqaj9aESB7i7YscsheVeFNkRSFZEVQRPbG7jnWISwmu0dAmP686WcHZ/27PGe5g7WqlqsTFav0ad2HS4ZcwpE9jtz9jeJwhLzbW154gS3/fIXtq1dXWKH6UOrouQ6X/57ktjrsKrZiBDC2+NZ2diOAtUUuutcZAYwunjabIeAgULJ5Mxvvu5+cDz6o2GA3KYmm++xD+jFH0+aMM6o9bUFh249XfcxXa79yyJ6qclVpW5mIeLRr1o69W+/thHHH9hhL95bdzRpRRkAFOr9s/YWv133NvE3zUF7l+oL1KMQc3rpG4XPZ4Zph1ySsl1Wn0WQ+/DC5H364a4i4Z0/anHcerU8/LWYhYiOAUf4ARGk6I4BRArKO0xgBrCOAdrkhEIpAzrQP2fToo2xbvLgCMMmdO9P27LNp89vz8SfvWnGaXZTNp6s/5cu1X7Jg8wI25G+guKzy/DT1v2vbtK3jadq/8/6Op8l63zX8PlRe4X+X/pfXl7zu9D4MFeVVXjDoAk7sfWLMyE7DI1C9BvmzZpE5eQqFc+ZUDBEnJ5M2cn86XHEFafvtF9VlGAGMKpxRm8wIYNSgrNNERgDrBJ9dbAi43r4HHiT3vfcoCz1OKynJOUGh4w2TnNy+oMhb9OmqT/ly3ZdO3pmaJasRcmWinnYie2p0PKLTCMejpJCuibcRUAXyg7MfdELIoSF6tcE5pNshXDP8moT10Doh4qlT2fLSy4G+liHib5VOqxNOoPPNN0fFwEYAowJj1CcxAhh1SGs1oRHAWsFmFxkCkPvxJ2ROnsy2RYsqevs6dqTNb86m7QUX7PD2zcucx5TvpzjtSaoqMBDZUz88kT1Vm4rsDWjnrb5qZveaIaCQ8dSFU3lxwYusy6t4qsYeLfbgnH3O4az+ZyWsV7AkM5ONj0wmd9q0HWdXy1u+9+ef1QzoKkYbAYwKjFGfxAhg1CGt1YRGAGsFm12UqAiUZGez8f4HAt6+0JMR5O0bNYqOk67fcV6qcvgenfso01ZMc5oUh4rInqpIFRoU2TuixxEMajcoYYlAIuwnhYgf+O4Bvlj7RYX2M6rMHt1lNNcOv5Y+bfokAhSVrjH/u9lsmjKZFocfTrtzz40KDkYAowJj1CcxAhh1SGs1oRHAWsFmFyUaArmffkrmI5PZtnDhrt6+s8+m7YUBb5/Cff9c+E/nSw/8UFHjZFXinrT3SezXYT8je4m2idz1yiv41tK3ePanZ1mRs6ICCmojc0a/Mzh/wPmkJqcmKELRW7YRwOhhGc2ZjABGE83az2UEsPbY2ZVxjoC8fZkPPkjOu+9VrGBMSiLtgAPoeP31NBuwj4PCrHWzeGzeY8zdOLdCDz5V5w7rNIzLhlzmnCxhYgiEIqBikYdmP+RUe+tM5aAE940qiPftUL+98+LJQkYAvWlNI4DesIsRQG/YwbTwEAK5n31O5iMPs23hogrNmpM7dqD1WRNod9HvHG+fGjBP/n6yU70b3h+uR3oPJvSfwJn9zjRPn4ds62VVlCrw1LynnCPsQqVNkzacvPfJTm/BeDmZpb7sYASwvpCu2X2MANYMr1iNNgIYK2Rt3kaFQElODpkPPEDOO+9W4u0bScfrrncOui8uKeaF+S/w6uJXycjPqLBGFXCM32s8lw29zDk+zMQQqA0Cagk0ee5k3lv2Hnnb83ZMobzRfdvvy1X7XcXIriNrM3XCXWME0JsmNwLoDbsYAfSGHUyLBkIg4O17JJDbF3I0W1KHDs7pHO0uvBB/airTV0/nyXlPOm1bysrLdmirs2JHdh7JFftdwcD2AxtoFXbbeEVAfSGnzJ3inEYS2mg6PTWdY3sey+XDLrdziasxvhFAb34yjAB6wy5GAL1hB9OiHhFwvH3K7fvvO7t6+0buT8frrqPZoEGs3LqSR75/hBlrZlBYujM/S6qqCfP5A8/n+F7HW4i3Hm2XqLcqKC7giXlP8MYvb5C9LbuCV7Bfm35cOuRSDu9xeKLCU+W6jQB6c0sYAfSGXYwAesMOpkU9IJA7fTqbHplM0fz5Fb197dvT5swzaHfxxRT5S3jmx2d4Y8kbztmvodKuaTuO630cEwdPpEVqi3rQ2G5hCOyKwPcbvndeTOZsnFPBG638wHE9xnH18KudYwFNwAigN3eBEUBv2MUIoDfsYFrECIGSvDwyH5C377+U5ebuvIvfT9r+I+g4aZLj7Xt/+ftOW45FmxdVCLU1SWrCmK5jnBBvIvdoi5F5bNo6IKB81Kd/eprXFr+2y8tKr1a9uHDQhRzX67iE9lAbAazDBovhpUYAYwhuDaY2AlgDsGxo40Eg94sZbHr44Uq9fa3POJ32l1zCL/krmDxnMjMzZlZozKtk+/5t+zsP0KN6HtV4Fm2aJiwCizcv5v7Z9zMrYxYl5SU7cNALzKHdD3WOntPJI4kmRgC9aXEjgN6wixFAb9jBtIgCAjqHd+MDD7D1rbd39faNGOH07dvevwdP/PAE7y57l81FmyvcVU14T+5zMhfse4G124iCPWyK+kdAjcinLpjKywteZl1+xaPnurXoxnkDz+P0vqcnjFfQCGD978FI7mgEMBKUYj/GCGDsMbY7xBgBHS6/4W93kf3qq1Cy0/uR1K4d8va1vfhi3l79ntO+ZWn20graKG/qkG6HOCHe7undY6ypTW8I1B8CKmJ6cPaDzFg7g+Ky4h031ok0t4++PSG820YA62+/1eRORgBrglbsxhoBjB22NnOMEdCRWpseeYTNzz5HebH7gPP5aOZ4+65jaVe/00Lj2/Xfsr1s+w5t/D6/00/t4sEXc3C3g2OspU1vCDQsAvqcqHr4uZ+eY2Xuyh3KqJL9oUMfokerHg2rYAzvbgQwhuDWYWojgHUAL4qXGgGMIpg2Vf0hkPXMM2ROeZTywp3tWZqPGUPaHX/k8dVTmbZ8GluLt1ZQqGuLrpzW9zTO3edcO2e1/kxld/IQAqognvTFJDYUbHC0Ur6rmpf/dcxf4/IzUQsCqDfCScBwoAtwMvBmFSZ8ErgYuAZ4KGRMW2AycDygpqGvA1cBO7t6w2DgUWB/QO0GNP7/PLRVYqqKEcCYwhvx5EYAI4bKBnoBgS3//jcb772PspycHeo0228/Cm+5lD8vf9Rp1BwqCneN3XMsl+93OZ2ad/LCEkwHQ6DBEXjh5xd4eM7DO0LDKhbRucNnDzi7wXWLpgK1IIBHA2OAOS5xq4oAngTcDnQA7g0jgO+75PESIAV4DvgWmOCuLR3QeX8fA3cBOuz5WeBq4Klort+rcxkB9IZljAB6ww6mxW4QyJk2jfV3/IXSrKwdI5vs05+imyZy+/pnWLB5wY6fJ/mSGNZxGBOHTnRO6TAxBAyBXREoKinipv/dxEcrP9rxyy7Nu3DfIfcxuIMcVI1fakEAQxddXoUHUM/NbwC1CHjXJX9BD+A+wHzXs/edO9l44D2gG6DKnEuBO4HOQDA5825ApLJ/40d99yswArh7jOpjhBHA+kDZ7lFrBPK+/JKMW/9EybqdFY0pe+1FwR8u4o6cqSzasmjH3M2Smzmncyi3L9mfXOt72oWGQCIhsHzrcq7+7GqWbV22Y9mjuozi/kPvb/THzMWAAPpdz91bwMPAijACeAFwPxB6GLj+GBUBpwFvAC8A8gKK8AXlMOBTQOHjLfG+/4wAesPCDgFcvnw5e+yReD2ivGEC06IyBAp//JGNt9xK8bJlBP9YJHXtSt415/DX0rdZsnXJjsuaJzfntwN+y/kDzk+Y9ha2awyBaCPwwYoP+Nusv5FXEkhVS/Ylc94+53Hp4Esb7edq7dq19OzZU8uRZy0jBLNtgL6qk8o8gH8ERNbk/dPvwwngTcB5QL+wiTcCtwGPAx8CywGFiIMyAFD+iv7dGc6ItpE9Mp8RQG8YwiGAU6dOJS0tzRsamRYJjUBSXh5tP/uMVl9/g99t6ZK3T3+Wjx3FB20XMad4DqWUOhj1SOrB4U0Pp1dyL3w++5OS0BvHFh8VBMrLy5m3fR7TCqeRUx7Is+2T3Idjmh1Dx6SOUblHfU5SUFDAhAnB1LsKd/6zm8NXEwKowhCFfIe5oVxdGykBVKHHrcATVRDAgcBPgELIC+sTo4a4l/21bgjUd72neQC9YYeE16J43To23HQzRbNn7/D4+dLTybnoFP7a7kuW5+qFOSDpKelcvO/FnNn3zEbrmUh4gxsAnkYgqzCLSTMmMXfT3B16DmgzgPsOvo/OzZW61jgkyh5AFWk84Fb2BgFIcv9/NbAXYCHgCLaGEcAIQKqHIZYDWA8g2y2qRqAkK4t1N/6B/C+/hHJFVMDXrBlbzzuGO7rPYVWe/q66xC81ncuGXBZ3lYq2PwwBryIwa90sbphxA1lFgeIrtY05sfeJ3HbgbY0izzbKOYDt3OreUHNNA150K32VkBwsAhkBzHYHjgM+qKQIRG0Jgg1K/wacYkUgXv0kxKdeRgDj066eX1VJXh7rb76F3A8/3En8UlPJPv1w/tx/AWvy1+5YQ+smrZ02Lmf0O8Pz6zIFDYF4RODJH57kiXlPoKPmJM2SmnHjyBs5te+pnl5uLQhgC0W93UV9D1wLfAbo3MhVlSw2PASsIWoDI3I3MaQNjCqCg7HoVoDIonIB7wEGuW1g1E/Q2sB4ekfFl3JGAOPLnp5fTVlRkdPOZetbb0FpIJePpCSyjx/DHcOWs6ZwZ552myZtuGrYVZ5/yFQAfXsRZC6EjT/Dpl8geyXkrIO8jVC4BUoKIbkZNG0FzTtAyy7Quju07Q0d+kKnQdCsteftaAomHgIFxQWON3D6muk7Ft+9ZXfnNJG+bft6EpBaEMBDXcIXvp7ngfMjJICq5J0S1gj6yrBG0EPcMWoEvcltBC0ymBBiIWBvmNkIoDfsEPda6LzezPvuY/PLU2G7G/Xw+9lyxDD+MjqDNdsDJxNI2jVtx7XDr+WEPid4B5eyMtiyHDb8DJmLAt9vXQN5G6BwM2zLg5IiKFfj/7qKD5JSILU5NBFRbBcgiq1EFHtBh37QaSA0b1/XG9n1hkCNEVi8eTFXf341q3N3pmccvMfB3HvwvaSlequYsBYEsMZ42AU1R8AIYM0xi8UVRgBjgarNuQMBnUOa9fgTZP39KcqL3K4LPh9bxgzgL4dmsaZUL78Bad+sPZNGTOKYXsfUL4K5G2D9T5C5ADYvg62rITcDCrKgKBdKCqDM9VZGqpnPD8lNoUlLSGsLLTpBejdo2SngDXTIo7yCIo+6R2HN7yFdklIhxfUoprWDFp1dj2IvaNcXOg8K3NPEEIgyAv9Z8h/unnU3hdq7ahvjT2bi4IlcMiS0u0mUb1rD6YwA1hCwehpuBLCegN7NbYwAesMOcanF5hdfJPPhRyjL23kE5pbhvfnbkbms9CmlJiAd0zpyw4gbOKqnWmtFUeSV2/ATbFwIWUtgyyrIXQf5mVC0FbYXQGmwEX+k9/VBcpOAd65Zm0AYN30PaNsT2vWBjgOgQ39ITo10wp3jHC/jigAR3bQENi+HHNfLKDIqorhdRDGQh1Uj8ae4RDEd0toHCGmrbgGPYvu+0HGfwDr86nNrYghEhoByAu/46g7e/OVNyp22eAEP/t0H3c2orqMimySGo4wAxhDcOkxtBLAO4EXxUiOAUQTTpgogkP3W22y86y5Ks7N3QLJlUDfuOqqQFalbd/ysc1pnJ5F8bI+xdYduw0KYfjes/J/rUZO3MfBAilhEkhTCato6EF5V2LXNXoH8vI79A/l5TdXAv4FFRDFnLWxcEMg3FGmURzF3PRTKa5njEsVggWEN9BUGIoX7ngajLoUmyok3MQSqRyAjL8M5TWT+Zp2CFpAhHYY4+YHt9cLRQGIEsIGA381tjQB6wy5GAL1hh7jQIvfTT1l/+58p2aim9wHZ0qcj9x67nV/Scnf8rGvzrvxx5B85dE/lW9dBcjJg+j2w4O1AuLYq8SdBsoidwrHBMOmeIfl0gyC9Sx0U8fClwmjDfMhaHAhvZ6+GvPWQL4+ivKCF1XtB5SXsfxwceCW0stOCPGxpT6j2xZovuPl/N5O9LfDy58fPr/v9mptH3twgPTuNAHpiW+yiRLwTwIOBSYA6h+vJcjLwZhWmeBK4GFAJePBAaQ1VJdHksEqiq8IqiXRi96PuwdPqNK7x/1cDkxsBrAFYNrRyBPK//ZaMm25m++qdSeHZe7bh/mPLWNQ6f8dF3Vp046YDbuKgbgfVHkqFdf/3APzwr0B4NFRS0qDnwbDHCGi/N3TeF9r0tLBmJGjnbwoUuKz8Cua/AZsW71rQIvLc+/AAGeyiPz0mhsCuCCjvd8rcKTz707OUlgdyZ5unNOeWUbdwXK/j6hUyI4D1CnfEN4t3Ang0MAaYA7xeDQHUYdC3Ax2Ae8MIoHoJiTwqozbFbTT5bUgvIcWiFrsHU98F7Ov2ElK38kh7CRkBjHjL2sBwBArnLyDjxhvZtmTnubxbO7fkkePgxw6BxHDJni335NZRt9Y+J6i0BL79O3z7DGT9UjG0q5DlngfAQddDbx3RaRIVBIT5D/+EOc9Dxg+7egmVA7nnaDhgIux9ZFRuaZPEFwI5xTlMmj6Jmetm7lhYz1Y9nbBwr9a96mWxRgDrBeYa3yTeCWAoIJUdKK3fi3x94x4qrfMF5f0LegCD3cTVI0gNJCXjgfcq6Sauc3mCmex3AyKVOvg6EjECGAlKNqYCAttWrGDdpBso+vHHHT/PbdeMR4/1M2ePneer75W+F7eOvpWRnUfWHEHluf38Onz1aICAhLZXUYVt58GBHLV9TzcPX83RrfkViz+EWU/Cqq+geKdX15lIlchdhsCw82DIWZCUXPP57Yq4ReDHzB+5fvr1rMtft2ONY/ccy10H3UVTVcrHUIwAxhDcOkyd6ARQpXYfA28BD1dyoHSszhNsAugrKPIwLly9ejXdunWrgznt0kRAoCQzk7XXX0/BN7N2LDcvPZWnjk7i6147Cw56terFn0b/ieGdlAFRQ1k2HWbcHyAa4RW6qrIVyZDXqTZVtjVUxYZXgcC6ufDVFFj66a65lyLnqire99dwgBWR2B7aicDUBVN5YPYDbCsNvCSm+lO5Yr8rOH9QZf2Vo4OcEcDo4BjtWRKdAP4RULxKfS/kIQw/TuYm4DygXxjwyq6/DXjcPUZmuRsiDg4bAPwM6N8FlRhN4WZdX0GMAEZ7e8fffJlTprDp8Sd2nN5R0DyZZ49K4ou+JeALfJz7tO7Dnw/8M4M71DA/TD34Pr8Hln4C28O8Sy27wuAz4KBrvVGBG3+mrduKVFQiMrjwnUAlcrhYEUnd8I2zq4tLirl15q28v/z9HW1j1AbqvoPvY79O+0V9tUYAow5pVCZMZAIot4hCvsOAoE88UgKoQo9bgSeqIIADgZ/cA6kXVmIp8wBGZfsmziRFCxey+tLLKMkIHNG2LdXHC0em8PG+pZS7xK9vm77cceAdDGyv7RehbF0baNuy4J1AM+RQadYW9jkODvmDVZ5GCKcnhqn9zDdPwo//DvRdDD8VJVhEMubqQINqk4RFYHXOaq767CqWZO/MH96/0/48cOgDtFYbpiiJEcAoARnlaRKZAKpI4wEg9MyoJPf/VUa5FxCrEHC4GS0HMMobO16m09FtGTffQo7O7HXd1NOHJvPMEeUOCZT0b9ufvxz4F/q3izDlVARhxgMw71+BhsyhktIceh8Bh95o5CAeNpGKSOa+DHNeCORwloX1JExt4RaRXAp7HxEPK7Y11AKBj1Z+xG0zbyO3ONAmKsmXxNn7nM11w6+LStsYI4C1MEo9XJLIBLCdW90bCvM04EW30neR68FTR80RwGx34Djgg0qKQHTOU/Cv69+AU6wIpB52cBzfInf6dNZdd/2OEzw2tfJz78k+lncJfGwHtB3AX8b8JbID4EuK4ZsnAtWkTgVviKiCt8do+NW1VsEbx/vJWZqKSLQPVn29a5jfKSIZ6haRnGlFJPG+F8LWp7Yx98++n5cXvOy0jWnbtC3Tz5geFRSMAEYFxqhPEu8EUO3z+7iofQ9cC3wGKNa1qhI0w0PAGqI2MCJ3E0PawKgieIJ7fStAZPFD4B5AMZVn3X6C1gYm6ls2/icsyctj7WW/p2BWoMij1AevHuznrVE+yvw+2jRpw32H3rf7ql5V8P74Knz9OKyft2sFrypGR/8eBp5qFbzxv612XaGKSGZODhSRhIf/dxSRnA4HXGInkSTQ/thStIVrP7+WiwZfxIFdD4zKyo0ARgXGqE8S7wRQRxyI8IXL80BlJU+VEUA1gp4S1gj6yrBG0EPcMWoXs8ltBC0yGKlYCDhSpOJ83OaXXmbDPffA9oAzeXE3Pw+d4GNTKx9+n5/zB57PVftdVX1YZulnMOM+WPXNriG/dnvDiN/C/hdZBW+c76UaLU9FJDMfgYXv7drYWxO16u6eRHKF5YPWCFgbLASMAHpzH8Q7AfQm6rtqZQSwsVgqRnoWr17N6osvoXi5CsqhKAWeONrPzAE+p7p3UPtBTDl8Cu2aKXOhEsmYB5/fDcs+g+0FFQek7wFDzgQl/XvhDN0YYWjTRgmBiIpIjoCxtxsZjBLk8T6NEUBvWtgIoDfsYgTQG3aody2Ud7Px7nvY8uKLUK5ORDBjoI9nj/ST38xHi5QW3DnmTg7vcfiuuslrI9Kn1h9FgTM/d4gqPfc5AQ65MX7P1613ayXgDastIvFBr0PhxEeNCCbg1qjJko0A1gSt+htrBLD+sK7uTkYAvWGHetWiYM4c1lx+BaWbA+1XslrCwycmsbC7D/33676/5pYDbtk13Pvts/DFPZC7vqK+qujsMzZA+jqpBaWJIRBlBIJFJMu/CEkvcIngSY/by0aU4Y6X6YwAetOSRgC9YRcjgN6wQ71oUVZczNprriXvk0+c+5X54I3Rfl4f46Mk2Ufv1r2ZfPhkurfsXlGf+W/Du9dBvvqQu6LKzR4HBs7g7XlQvehvNzEEUFX5tJtg9j8qEkGdA33iY0YEbYtUQMAIoDc3hBFAb9jFCKA37BBzLba+8w4Zt9xKeVGRc6+lnX1MOd7P2vY+miY15ZZRt3BinxMr6rF8Brz1e8heufPnOo7tsJthwElWwRtzq9kNqkTAiKBtjggQMAIYAUgNMMQIYAOAXsktjQB6ww4x06IkK4vVl0yk6CcdEAPbkuEfY318OtTvnOQxrsc47vrVXaSGnq27YT68/jvYqFMFXUnvCsc/AnsfGTNdbWJDoMYIiAh+8IdAw+kdzaZ9gb6S5hGsMZzxdoERQG9a1AigN+xiBNAbdoiJFpmPP86mKY/uOL/3m34+nh7nZ2sLH3u02INHDnukYjNnFXeI+K3+eqc+zdrAUXfB0LNioqNNaghEBQEjglGBMd4mMQLoTYsaAfSGXYwAesMOUdWiaPFiVk+8lJJ1gePWspvD48f4+b6PnxR/CtcMv4ZzBpyz854Fm+GNS2DJR+6hb2o9ngaH/hHGqPWkiSHQSBCokggeHqgaTu/SSBZiakYDASOA0UAx+nMYAYw+prWZ0QhgbVDz6DVq7bL+5lvY+uabTmsXHTb93ggf/zrE75zfq+76Dx7yIGmpaYEVbC+C/14JP/5752kdKu4YdSkccbvl+HnUzqZWBAgYEYwApPgfYgTQmzY2AugNuxgB9IYd6qxF7owZrLv2OspyA4eqr+oAjx6b5Jzf275Ze+475D6GdxoeuI96rH14C3z79M68KV8SDJ0Axz5gJ3XU2Ro2gWcQ0EvOB3+E718MyxE0j6BnbBRDRYwAxhDcOkxtBLAO4EXxUiOAUQSzIaYqy89n9eWXU/BVIG+vOAleOcTPe/v78CUlc+G+F3LFflcEVNMZvf+7H764H0oKXXV90P9YUC81O62jIUxo96wPBIwI1gfKnruHEUDPmcRRyAigN+xiBNAbdqiVFpv/+U823nUX5cWB83vn9oS/j08is7WPoR2G8sjhj9CmaZvA3LOfh49uhaKtO++116/glKctL6pW6NtFjRKBqohgnyMCVcMtOzXKZZnSlSNgBNCbO8MIoDfsYgTQG3aokRbFa9ey+pJLKP5lqXNdblN4dpyfLwf4aNkknbsPupuDux0cmHPhu/DONZC3Yec9Og+BU/8OHfrV6L422BCIGwSMCMaNKatbiBFAb5rZCKA37GIE0Bt2iEgLFXlk3nsfm59/PhDOBT4Z4uOlw/wUNPNzRr8z+OPIPwaOcFs5E968DLYs3zl3295w0hOw58iI7meDDIG4R8Ahgn+A71+qmCNoHsG4ML0RQG+a0QigN+xiBNAbdtitFgU//MCay35PaVaWMzajDTx5tJ/5Pfz0bdPXCfeqtx8bFsJ/LoQNgcbPjrTsDMc9DP3G7/Y+NsAQSEgEjAjGpdmNAHrTrEYAvWEXI4DesEOVWuj83nXXXU/uR+rRByV+eHO0jzcO9JPcJI1bR9/K8b2Ph61r4T+/C3j+gtK0NYy7E4b9xuOrNPUMAY8gUCURHBvoI2g5gh4xVGRqGAGMDKf6HmUEsL4Rr/x+RgC9YYdKtdj6/vtk3HQz5YWBit2F3eT1S3LO7z2m5zH85cC/kLq9AN6YCIs/CGni3AwO+QP86moPr85UMwQ8jMAOIqj2MSWuoj7oY0TQw1bbRTUjgN60lhFAb9jFCKA37FBBi5LNm1l96aUU/jDPKZcvSIWXDvfzyVAf3dL3dI5w69OiW6C4Y96/oLw0cL0/BUZNhLF3WBNnD9rVVGqECIgIvn8jzFWOoBHBxmZBI4DetJgRQG/YxQigN+ywQ4tNTz5F5iOP7Di/96v+Pv4x1k9+qyZcO/xazu5/Fnz8J/j6iYpNnAefAcc9CClNPbYiU8cQiAMEjAg2SiMauldXewAAIABJREFUAfSm2YwAesMuRgC9YQdKsrNZOeFsipctczTKaglPH+Vn9t5+Dt7jYO499F7Svn4Kpt8DCvs64oO+4+HkJ6BZa4+sxNQwBOIYgaqI4N5HBvoItugQx4tvfEszAuhNmxkB9IZdjAB6wA65n33O2quuory42Dm/d9pwH/88xE/L1h156LCHGLz2R/jgJijK3qntnqPhlL9D6+4eWIGpYAgkGALVEUGdqtO8fYIB4s3lGgH0pl2MAHrDLkYAG9gO6265lezXXnNy/bLTYPIJfub3SuHiwRdzWbNe8M5VkLt+p5adBsEpz0Cn/g2sud3eEDAEcIjgJJg7dWeOoHJxT3gYhp5tADUwAkYAG9gAVdzeCKA37GIEsIHsUJKZyYqzJrB9zRpHg3l7+Zh8vJ/O3fvz9MBLaf3uJNgcOOnDkTY94aTHoMeBDaSx3dYQMASqRCBIBNVQujzQpJ29DoKzX7O83AbcNkYAGxD8am5tBNAbdjEC2AB2UHuXdTfcANtLKPPBvw7y89ZoP5f1O5NL5k2D9T/s1KpFJzjmfhhwfANoarc0BAyBGiGQtRSePx5y1gYuS0mD01+CvY+o0TQ2ODoIGAGMDo7RnsUIYLQRrd18RgBrh1utrtJRbhmTbmDru+86IV8Vejx8YhIZvVvzfJvR9P7m6Z3egybpMO6vMPy8Wt3LLjIEDIEGQkDHNL5/A3z7950KDDoVTnna2jPVs0mMANYz4BHezghghEDFeJgRwBgDHJy+OCODlWdNoGR9IJ9vdm8fjx3rZ/9eI3lg0RySgmf2Kn/o0BvhV9fZw6KebGO3MQRigsCab+GlX+8s3kprB7/5D3QdGpPb2aS7ImAE0Ju7wgigN+xiBLAe7JD9xhtk3HKr09tPR7m9fJifaSNTuK/9aI74LqSRc5ehcM4bkNa2HrSyWxgChkDMESgtgX+fBwvfcW/lg1GXwvi7Yn5ruwEYAfTmLjAC6A27GAGMoR0U8l17+RXkfvqpE/Ld0BoeOjGJ8r278cL6jbTa5BZ5+JNh/N0w8qIYamNTGwKGQIMhsPA9eO0CKAkc60jrPeG8d6BNjwZTKRFubATQm1Y2AugNuxgBjJEdtq1Ywcqzf0NpVpZzB53o8dR4P+d0HMjvf/xo5/FtautyzpvWQDZGdrBpDQHPILAtD146FVZ/HVDJlwRjb4cxV3pGxXhTpBYE8GBgEjAc6AKcDLwZgsvtwJmAGrAWK5sHuBn4JmSMQjiTAVXuqST8deAqIC9kzGDgUWB/INMd/3/xhn9V6zEC6A1LGwGMgR02T53K+jvvxFdaRnESPD/Wz9cj0nght5w+G5cE7uhPgiP/AqN/HwMNbEpDwBDwLALf/QPeu25n38DOg+Hctyz1IwYGqwUBPBoYA8xxiVs4AZwAbAR0ZFMz4BrgNKCPS+S0ivdd8niJ6sCB54BvAV0rSQcWAx8DygXYF3gWuBp4KgYweG5KI4DeMIkRwCjaoaykhNUXX0L+zJlOyHddW3jwxCR69ejK/YtnkxI8TL5Dfzj3bWjZKYp3t6kMAUOg0SCQuyHQLmbTooDKSamBPp/7ikuYRAuBWhDA0FuXV+IBDFdNZG4rMBb4BNgHmO969r5zB48H3gO66bEAXArcCXR2vYgadjdwEpAQHf6NAEZrh9dtHocALl++nD320LcmtUVg25IlrLngQsqzA8e1fTHQxz/Gp/DXkmQO3/CLQwjLfcmUHnoT5QdayKe2ONt1hkA8IeD74l6S/ncvvvIyxDbKeh5O2WkvWPPoKBl57dq19OzZU7OJWGWETLsN0Fd1sjsCmAroj/ktrgdwE3ABcL9a94dMnAwUuZ7CN4AXXC+gCF9QDgM+BRQ+3hKl5Xt2GiOA3jCNQwCnTp1KWlqaNzRqhFqkLVlCp1deISUvn6IUeGacn7zBPbkrYzFdijY4K1rR7hB+3mMCJUmKGpgYAoaAIRBAILUklyGrnqPr1oDDaHPzPszucQkFTSxCUNc9UlBQwIQJwchrhdn+DCifrzYE8DjgFUAPTZFKETmFeCU3AWre2i9sYoWNbwMeBz4ElgMKEQdlAPAzoH8X1HXdXr/eCKA3LGQewDrYoayoiLUTL6Vo9mzHw7eqQ6Cx84ktU7goYxl+x+uXROlBN1J+0LV1uJNdaggYAnGNQFkZvg9uIOn75/FR7ngDSwedTvnxU6wfaB0MHyMPYHM3x689oNYNhwMHuLmBVRFAFXrcCjxRBQEcCPzkhpAX1mHJjeJSI4DeMJPlANbSDoXzfmTFBb+FvHxnho+G+njziBSe3LSevbfJ2++e36vkbmv1UEuU7TJDIMEQWPU1vHwabMsJLDytA5z7JnQelGBARGe59ZADKEVV2aciDhV0WAg4AtMZAYwApHoYYgSwFiBvnDyZjY8/RlIZFKTCU0f7adnHz9/WrkJJIfj88Ktr4Ig/1WJ2u8QQMAQSGgE1j/7X2bD4AxcGHxx4BYz7S0LDUpvF1xMBVEPXF92QcrAIZITbIkZqjwNkzPAiEMX4t7vr+htwihWB1MbKdk1tETACWAPkyvLzWXHuuWz7WUVesKwzPHpCEteXbuHwfLfFU6s9A2/s7XrXYGYbaggYAoZAGALz34b/XAQlIRGF8/4LrdWCziQSBGpBAFu4BR2a/ntAuTufKTVTx7e7Pf/ednP/FAJWHy8lGapvoHL4JGoDI3I3MaQNjBI8g8mIrQCVfysX8B5A7l15ENVSxtrARGJYGxMVBIwARghj/rffsvySi0kqCPwxfneEj9m/8jFl4zra6fB3ZQHaW3qEaNowQ8AQiAiBohx48WRY63YUUfPoo+4MHCdnslsEakEAD3UJX/jcz7uEbqqb7yfyJ0Ko4o+/hhSB6DpV8k4JawStauHQRtBD3DFqBK3qYTWOFhlMCLEQsDfMbAQwAjtsuPseNr7wD5LLIK8pPHG0n9Gd8rgwO9sp/iC9a+A0jw7hhV8RTG5DDAFDwBDYHQLfPAXT/gBlpYGRXfcL9BJtqjZ0JlUhUAsCaGDWAwJGAOsB5AhuYQSwGpBKcnJYPmECJb8EzuxdtAe8eJyPvxVspN92pW744ICJcLR6eJoYAoaAIRBDBHIy4PnjIOuXwE2SmsDJT8AgpY6ZVIaAEUBv7gsjgN6wixHAKuyQO2MGy6/8PSmFgRzdN0b7yNtvG3/akkXT8nJo0Sng9euktk0mhoAhYAjUEwIf/xn+96CaTAVu2GcsnPlPSHZK0ExCEDAC6M3tEO8EsLEcKG0EsJLPx7rbbiPr3686Id+tafD3Y/xMSM/iiILCgNdvxAVwzH3Wn8ubf1tMK0Mg/hHYsBBePB7y1F8YaNISznoF9vpV/K+9Bis0AlgDsOpxaLwTwMZyoLQRwJBNX5KVxeIJZ+Bbudb56U89fHw8rpQ7CjLpVFoa6Mn1m9eg69B6/KjYrQwBQ8AQqAQBFZ+9fTnMfXnnL4eeDSdY8+ggIEYAvfnJiXcCGIr67s4T1NiGOlDaCKBrqZyPPmLZpGtoUlRKmQ9eG+Ojyz65XJibQ5LG7HcOHP+Ief28+ffEtDIEEheB5TPglbNgW24AAyc95W3opONvE1uMAHrT/kYAd9qlIQ+UTngCWFZWxuobbyDn3XedkO/mFvDSMXBZ003sW1wMzdrC2a9BN7V5MjEEDAFDwIMIlBQHSOAvH7vK+UDHTyZ4M3ojgB7cq4FEqoSRqjyADXGgdBNli4Qg3wVYuHr1arp1U5PyxJLi9etZMOHXpK5TOyf4vpePxYcVMqlgC81V6DH4TDjpcfP6Jda2sNUaAo0XgR9fhzcvhdJtgTW06wPnvQPp+lOfeGIE0Js2NwIIDXGg9O3AbeFbIhEJYPZbb7PsT3+g2bZyShXyPdjH/r23cGxBATRtDRP+BXuO8uanx7QyBAwBQ6AqBAqz4YUTIWNuYIQ/GcbfDSMvSjjMjAB60+RGAHe1S30cKJ3wHkCFfJdeeSnbPvmCpHLITIf/Hl3KlSmb6F5SCgNPhlOehqRkb35yTCtDwBAwBCJB4KtH4cNbodxtHt1t/0DrqiY67SwxxAigN+1sBHBXuzTEgdIJlQNYvHo1P/zmVFpsCCRLz9ob8g/K56KCraQ0SYczp0LPg7z5iTGtDAFDwBCoKQLZqwPNo7esCFyZ3BTOeAn2PrKmMzXK8UYAvWm2eCeAjeVA6YQhgDnTp7Po6ktpUVjO9iR481A4ulsW+2/bBv1PgNOeM6+fN/9WmFaGgCFQVwQ+vAVm6nhat3m0QsIJcJ6wEcC6bpzYXB/vBLCxHCidEARw3ZOPs3HKIzTZHgj5fnHMdq7wZ9EqOS3wNtz7sNjscpvVEDAEDAGvIJAxD547GorzAhoN/y0c/5BXtIuJHkYAYwJrnSeNdwJYZ4DqaYK4J4A/X3kx5R/NcPL9dJZv7hF5nF2cg7/veDj9RTs+qZ42mt3GEDAEPIBAwWZ4YgzkrAsoo5NDzv1v3HY6MALogT1XiQpGAL1hl7glgGVFRXx72jGkL8lwkJ45EPYetpmDy8rh9Beg33hvWMC0MAQMAUOgPhEoLYFnj4K13wXu2mYvmPhlXBaHGAGsz40V+b2MAEaOVSxHxiUBVLHHd2ceT5usbZQB7x1Uzik9MundvCtc9Cm06BBLTG1uQ8AQMAS8j8B/LoZ5/wro2bQVXPJFgAzGkRgB9KYxjQB6wy5xRwBzZ8xg/tWXkJ5fTlEKTDuqlInpmbTue0wg5Ov3ewN508IQMAQMgYZG4It74dO/BrTwp8A5b8RVJwQjgA29wSq/vxFAb9glrgjgqqcfY9PDk2m2HTalw4/ji7goKZuUo+6CURO9gbhpYQgYAoaAlxD4+U147QK3X6APjn8Yhp/nJQ1rrYsRwFpDF9MLjQDGFN6IJ48bAjj36t+RPO1Lp9hjSVcoOyyHk5IIHIO0x34RA2IDDQFDwBBIOATWzQ3kBZYUBZZ+4BUwzvUMNmIwjAB603hGAL1hl0ZPAFXsMfPMo2m3cL2D6Df7wL7Dsxjethdc+HFcJjZ7Y+uYFoaAIRBXCORugMfHQEFmYFl7HwVnvdKo02aMAHpzhxoB9IZdGjUBLM7I4JvTx9M+s9hB86MxZZy8Vybdh5wNJ0z2BsKmhSFgCBgCjQWB7UXw98Ng4/yAxh36w8XTIaVpY1lBBT2NAHrTbNEigDrf5lngH8Aqby7V01o1WgKY/eUM5l91CW3yAsUeXxy5nQvbbKHFSU/Avqd5GnRTzhAwBAwBzyJQVgb/+g0sejegYlq7QJuY9C6eVbkqxYwAetNk0SKA1yjLCxgEfAY8A7wBbPPmsj2nVaMkgEufnkz2I4+RVgxZLWHpuEJ+kw5Jv/sE2vX2HMimkCFgCBgCjQ6Bj26HLx8MqK0zhM9/D7oNb1TLMALoTXNFiwAGVzcMOB84C1Dq/1TXMzjHm8v3jFaNjgB+c+2FNP9gJkllsLQLNDl0K0d2GxQo9khO9QywpoghYAgYAo0egbkvw1uXQ3kZ+PxwytOw76mNZllGAL1pqmgTwOAqU4DfA3cD+v4n4GHguZ2nYHsTkAbSqtEQwLLiYqafcSSdF2x0oJrdH4YOy2TQ6MvhyNsbCD67rSFgCBgCcY7AypnwwolQGsi15pA/wmF/aBSLjgMCqIeb+MvKRgF4hEpGmwCK7J0M/BY4EvjaDQd3cwnhp8CECHVLpGGNggBuW7eOL88aT5cN2x3bTB9dxom9s+lyxkuwt8xtYggYAoaAIRAzBLashCcPhqLswC0GnQq/Vvq9tyUOCOBcN8Vtustp/gO4vXq8jX112kWLACr0K9Kn0G8p8CLwNLAw5Ob7A18AzRovXDHT3PMEMPOrL1h01UTa5ZSzLRlmjS3m3O4pNL3os0aZlBwzS9rEhoAhYAjEEoFteQESuHlp4C5dhoLyrpOSY3nXOs0dBwRQ61cj2yDPEdivuClu39YJnAa8OFoEUKTvI5cZvwkEXEQVpTkwxQWwAZfsyVt7mgD+/PSDFE5+iubbYHMLyDgyn1MGjsQ/4dVG3ZvKkzvBlDIEDAFDYHcIqEL4pZNh2eeBkS07ByqEm7ff3ZUN8vs4IYBB7BTpPN7lMkcBi1yHl7qgbG0QgGt502gRwB7xFhuvJZ61vcyzBHDG9efT+r1vSC6DFZ2g+SHZHHzUH2HMlbVdq11nCBgChoAhEA0E3psEs54KzJSSFvAEdhoQjZmjOkecEUBVOSrV7QLgcGAm0BXoBFwE/Cuq4MVwsmgRwBiqmBBTe44AqtjjowlHsOdPmxwD/NC3nCEjc9nn3Ddgz5EJYRRbpCFgCBgCnkfgm6fg/RsC9ZX+JDhjKvQb7ym144QAqvdOMASsFncvuJ6/X1ywrwNkCBHByuSEWhhFkdXCWlwX0SV1IYBbalDR2zYibRJ3kKcIYNH6dXwx4Si6rytxLPL1AaUcO6wZHdWJvlnrxLWSrdwQMAQMAS8isOQT+OfpUBb4m824O+HAyz2jaRwQwHnAPsCHwN+B/7r1DqEYdwA2AP4qgC+roUHKdRAgsKyG10U8vC4EUI2fI5XnIx2YoOM8QwDXzfyUJdf+no7ZUJwE8w7fxumHHkGTU7XnTQwBQ8AQMAQ8iUDmEvj7oVCcF1Bv2LmeOYozDgjgrW7Bx9o62F4EsDMQ6KG2e8kFhniVAAbVVzWMWrtMc9nv7pdlI8IR8AQB/P7p+yiZ8gwtimBLc9h0RD4nnPk3GPYbs5ghYAgYAoaA1xEozIbHx0DOmoCmPQ6E895t8GK9OCCA0bC8+ggqeV7ELhJ5HBDxDORhxUDq4gEMVafAdY/WtEmi52LiMcA4kikbnAB+dN1ZdPpgLimlsKojtDyskAMv+wA69Y9EfxtjCBgChoAh4AUESkvguaNhzayANq17wMT/QdP0BtOukRLAB2oA2LU1GOuZodEigKpFfwhQC5iaiOdi4jVRPopjG4wAlpWU8O5Zv6LPj4Hq9Z/7lDNkXGv2vvRzSGkaxSXaVIaAIWAIGAL1hsB/LoF5alUHNEkH5XC361Vvtw+9USMlgJ9FCJZy9VQNXBfRYc8/AMo1/BlQkUnMJVoE8HTgLkCLmA3kh2muRVUmnouJxxzxym/QIAQwL2MNM845ir3WBHj4nBGlHH360bQ9Qaf2mRgChoAhYAg0agRmPACf/DmwBH8K/OZ16HVIvS+pkRLA+sTpRGCw+zXQLTARERR30tc7sVAmWgSwMk+eWLHm179JVSjvuZh4LECOYM56J4DLvpzGqklX02lzoNhj4cHbOPWKB0keoH1oYggYAoaAIRAXCMz/L/z7PCjXeQ0+OO4hGHF+vS6tkRNA1Tno2LehwE/1BJxOTBvkEsJ9gatjcd9oEUA1gq5OapobGIu1ennOeiWAXz55G8lPvkp6AWxNg81HbOeYmz+D1t29jJHpZggYAoaAIVAbBDLmwTPjoMRtKTfqMhivoF39SCMngAJJrVjU/Flh2liKjnK5GCgG7ovljTR3tAhgNPUUGZLUpdw6mvrUx1z1RgDfueZY9vxwmVPssaYDtDiuDaOv/8LT50jWhwHsHoaAIWAIxDUCeZnw+IGQ73Yh6XMk1NNxnnFAAC8ETgHOATbHcJ8o71CJm6oWVihY3j+14bgxFveMNgHUGTR7AjoqJVTejkD5McBL7vUartJnna13J5ATwfWNeUjMCWBJcTH//c3+9J+nFwtY1Kucwb87hl6n1KTQqTFDbLobAoaAIZDgCJQUw98Pgw1uJLN9X7hkRswL/uKAAH4P9NGBe+6xt+F1DsOitLNUuq2jtnS//dw5Q7+P0m0C00SLAKq06A2XrQZz/zS/vpdUlQMYuhjtyFXALa77c39ArcxVuz46lr1woopo7SaLKQHMXruCLy88ml4rAsr9uF8p4297hPT+3jouqHbQ2VWGgCFgCBgCNULglXNgoeuXadY20CamVTD4VqOZIhocBwTwtt0s1K20iQiO6gap2EMhYP0bJJUL3DZ7dZ48fIJoEcDgsSg6CFmxcjHYdsD9wPXAjAg0V3KCul4vDhkr/V4FtrvNpiOYplEOiRkBXPDJi2TcfiddMn1sT4LFvyrjlPu/xN9CqQYmhoAhYAgYAgmJwCd3wAw9ouWiaQK/fRe6ye8SfYkDAhh9UCqfUV7GxwBFU3W2sLw0On9V+YdRl2gRQIVr1QdH5cpqKCcCuMj9mXZY0JVZ3QLmAFdVQhZ1/p7coi2jvnrvTBgTAvjZAxfQ7OWvaJUPOSr2GJ/O0X/9qsG7wnsHdtPEEDAEDIEERmDuP+Gty6C8DHx+OPlJGKyubtGVWhDAg4FJwHCgi0uAgn2GFYb9K3AMoOijOMfHwB+AdSGatwUmA8cD6lTyussx3LPynJFqvfIoIOab6Y7/v0pWr3S0Z4EvootMpbMphe4kN6K6HlC3FB22EXWJFgHc4hpK3r+lwO8AJTP2VsQRSItA8yuAy4Cj3FBw8JJRruFi55+OQLkYD4kqAczILuTLmw9j7+lbSS2BjHbltLjwEEZe8GSMl2HTGwKGgCFgCDQqBFZ9Dc+fAKVu7+GDb4DDb47qEmpBAI8GVBcgx5CImzxgQQLYCngN0AH1qsptA/x/e+cBJlV1vvF3GywrHZHekSpVRKPBgCgisStSVBAVCxaMRkX/sUfFbmJijBhQE7GggkQRjSIWUJpK7y64tAXpuMCyLP/nnT2ze3eY2Wl3Zu7cec/zzEOZc8859/fd2Xn3O+f7Piav5VGzHpaFf2zE4/Xm7B6F1DzLbiKPl3HHkeKRIdEMuKDIY8qVl30AfGC8cTymxnFei1GgKj1/zMW2yySEpn6ivopJs0sAcouXnj4aaKIxCBU697Kp4JnPJljz5hJklML7AH40BmUEzGMA3gg2QBK/b5sAZLDHW8N74MQfuGsOrGl+BN3//Dga9YiJBzmJkWvpIiACIiACHgK78oB/9gL2G63R4SLgMjq97GkRCEDrxIwlsApAf4uiB487hUxJR5HGncNlxrM331zA7dRpABobT+GNJsi0vok7YLexxvvmrwZqXRMFPNxs0VI4/gsAxWHJF270jSf1WQOYSRspSPmi4KUzzfZmlwCk1+4YI9y4h80DjG0AbAcwCMCMEFZ+nNkq5jlAJlzk63gTSMJDkFTC3qzY00MYL5m62CcAi4rw7sBu6LK8CHO65OCx5vcis/IxOLdzA4zp3x61q/oGaCcTJq1VBERABEQgJgQKC0pE4PY1JcPX7wJcN9OWI0NxEIBnAvjUnJdj1pCrjVOK3kFv8yZ0HmiCVl83QabcbvW2PkavcPu4Is8bAzRGmN1ObikzgwnP7q2O0jbfmqBX6zD0bFIQ2t7sEoD+FuYF6I0EDrR4GqUowJssRksFTDHoFYb0JvJQpJuaRwDm5uaiUaPod7r3bvkJHzx5I15peC827i4rKUhjd2hQDbf1bYXebam31URABERABETAECguRvrbg5Hx0wwcbtANxVf/zxY0GzduRIsWLTgWPWubLYPyCypY3dtgHkDqhFkAVgC43Ix9LwB66tr63ACTIDKil142CsZcANwi9jZuwbIEG/+k48lf45nEYUZk8gubW9T8kzX27jIlcSPl9qBJM8Nt5pg3uwUgvX90VfKgJKN6vaXgKroRJnz+KwAeUOO+dyo2jwCcOHEicnJCOS4ZOqI9hcCcbWmYnZ+OHQfLzN26+hGcVq8YnWsfQWZ66OOppwiIgAiIgLsJ1Nm7AturtikJDLGhFRQUYOjQof5GYvoUip6KWkUCkAEhFGDc1u1tyRkcSAAy0OM+AC8FEIBMvsyUdNxCpqD0Ns5zvvH69TO7ka+Yo2l7Tachxgto9TqGS49b1HRy8Ugct7R5xpE7n8y0YnuzSwAy5QvTtdB9SmNx65YBITxQSTcqw5kDNUb6MN8fPYbsz8OcvDaVmq0eQH/gioqK8cqsdfjPnJ+Rv5e/cJWYPj0N6NK4Ov54Zhv0bEkTqImACIiACIiAfQRi5AGkKKPuYCQws5DwyJm32b0FzEwnVMNvmuATxij4Ngo/Bq14XJ1RNgaoUAjyRVHKDCm2N7sEIPfSuafI6F+6TbldSxHHs4EsNcEbqKhxj5ux54y+4d46g0lYB2+O7XfszAFtOwMYyu0tzNuJx6atwLx1O1Bs2aCvlZOFwSc1xei+rZFdiTvzaiIgAiIgAiIQHYEYnAH0ij86m+h4omfP2rxBIIwKXmDeoOeO8QO+QSD1LEEcDDhlyTffIBCWgJsE4EAQEt6xvUGt4YLjfdGTyXkYxGIVteGOFbS/XQKQuWoo9uiupDvUKwCpzOm+rBp0JWUdegG43eTuoQCkEKQgDHaWMIwpHNc1rgLQe/cHCovwl8/X4K15P2NnQVkQE72CJzWvjXsHtEOXJtF4sx3HWQsSAREQARGIM4EIBCA1A4+UsbEUGjUBU8uxDi9z/XHbl86icwHkW26H75fUOwWYBobi7gZLGhhGBHv3ohldy3zFPAv4hPG2cRfyD37SwIRKjAEojFmIdBeTW708I0kRyt1TngljAGxMynbZJQAp+mgMRsBYBSDV9yemKkioAL39KB7pEeRBTh7cpNJ3a0uIALTC/G7tdoydvgIL83aVU9p1q1XGlac0w6jftUKmDgu69fnTfYmACIhAzAhEIADpBaPg823Mv8czgwze8NfoDZxp3uCZpr/5JIK+FYA1ETSdVezDNDLc5mXiaIrBSJtV/0QyBp1oXBO3mCkkbwLA9DPBzklGMpdttYB5cJFuVh6uJABm114P4C2zb35pBavjIVAqcX8vRvvyxb33UOoJRwTBARclXAB6Gew9cAhPf7oK73+/AXsPlAVnZ6Sn4bTWdXDvOe3RrgGPJ6iJgAiIgAiIQHACEQjA4IM6s0e0AvA7ACx+wQCQ3xpvJoUwha3tzS4PIA8qfm4OQPIwJqtM89wfFTizebM6SKDGvXLudzPrJM8PsqwL3aiYdYcEAAAgAElEQVR8ef/OP+kFdGtzjAC0Av58eT6e+XQllm32BjmVvNuwRjau+W0LjDitOdLT7YkSc6thdV8iIAIikOoEJABDfgKYxoZb1yyiwVzKDCphEK0dgSVHLcIuAciB6cFjNC/dl9y/58JZY8+a88cfBQpG7u8zkSM9hjzzxzDsVGqOFIBeA+zYV4ix05fjw0WbUVBYlo8yKyMNfdoeh//7fXs0q8M84GoiIAIiIAIiUJ6ABGBET8RVxpH2bxNLEdEgFV1kpwCMdnFM2EghyNJvLC33lPEqRjOu0wpKB7oXRwtA66KnLtyIFz5fg9VbrccogGa1c3BD71YY1KOxvILRPLG6VgREQARcRiCFBGCgIJAqZkeUeY+tjTulTDztbYyl+KM5+sYA2ud8glxsfTLsEoCsX8foGWavzotyhTzwyIOPjNyh95AeQXoGIymF4rSC0kkvAL03kL/nAB79aDk+WboFB4vKIt4rZ6bj7I71PV7BetWZoF1NBERABEQglQmkkAD0dwaQMRDPmyATnpkaaUlxx51Sij5vYyAtK5XwOBz/n1VK/g+APSVZfB5CuwQgw6YZrcuzgDywyALJk0Mo8VLRZ4LBH7eYSGC6m1jkOZoWrJwMx45HQWl/95A0HkDfxRcXF+Pt+Rvw0sy1WL+joNzbrY+rilvOaI0LukZf3i4aw+taERABERCBxBFIIQHYxKSpsTqsGNHLNHlMV3MiAEYyM9/gRJPippvFMgz+6Gn5N4tszDBH62w3oF0C0LswKlbuW7MkCqN2eYP0DFLlBmrM5+MvApgJEb3ro3iLNgo4FAEYr4LSlQHw5W2sLbgiLy8PjRszj2RytvXbf/V4Bb9YuRWHDpelbcyplIFzOzfAmP7tUbtqpeS8Oa1aBERABEQgIgJJKgDfD+NmmbcvUOMWr7UYBoNj6SBj4OyFPh5AVhphrkIW0PDqntkATg5jLSF3tVsAeiemeOM27liTgJFBHSzxxi1i34TO/zE1gFkHONCLCRGjzYgdTADGs6A0c/rQzVuuJbsA9N4MvYITZq3Dv77Jxabd5ROnd2hQDXf0a4u+7ZmfU00EREAERMDtBJJUAFKveBu10kUmMwkFGhu9edyppFAcUYENuSvKUm480+dt9ITQEzgQgLXsFoUh0+jxfQpH7nzSSfYPAL7nB6N+bOwWgBR+hEQYZwFgThtuB9OtRUFIV6bfitCmlFwsU704oaC012Cu9AD6expXbN6Dxz5ejllrtuOwpe5ctexMDOjUALef1UZnBaP+GGsAERABEXAugSQVgFagTA5Nzx1jE7zbu9yVfNGkrLuzAvrUP0yqy4ppvo1p8mb5+X+m1aAQtL4aAmhlp5XtEoDc+qXo49Yv4TBs+RVua1oWy/N1XwFgNIy/xveY7NBfsAcVcllW4sgIBBKA8SwoHWjlSXsGMFRTFBUV46Wv1uL1b9dj696D5S5rUqsKLj+5Ga7+bQtUUrWRUJGqnwiIgAgkBQEXCEDWGmZiZpaOszZmL+EWLc/qJV2zSwBStDFKhd4+1u0tKyxbhoSKliVXArlKWQPvZ+MptIIkWLpAWRommuZPAMa7oHTKCkDrjS/M24knp6/EnNwdKLJ4BVmDuHPjmri5Tyuc2aF+NLbWtSIgAiIgAg4h4AIByGNojG/4wAfpBaaIRa0wUbOcFrUQv+hY1o4l4Fjzt3wkZZiDhtvdLgHIfWqWfgvW6CFklZBf/XTkXjojYHhukIEjbO0BfGg8ib8PNrif95OloLTrPYD+bOeNIJ4wKxer8/eVOxxaJSsDvdvWxR1ntUHretUiML0uEQEREAERcAIBFwhABmUMM9G71Cl0KLFk2xiz48kcxuG0z0xk7zwATQHQk0g9tsaIwUHhDBZpX7sEYKjzB0qS6L2+kynkzPx93G9n/j96Fbm/XpZsLtTZSryGyVBQOiUFoNWMrEH8189XY/IPm/DLvvJbxMdWrYyLujXErX2PR7VsOm3VREAEREAEkoWACwQg8/cxQTODOZi1g415ihnc+kwEeYrpBKM+oQBkY1wA9U9XIwyZAi/mLd4C0DdJIrd26fpknhy+uAVML+ELABiVSwjWSJyYA0nQBCkvAK3c1+TvxTP/W4WZK7dh/6GyI6F8WI+vVxUjTmuhiiMJelA1rQiIgAiES8AFAtB6y9y+ZaNDK9L2LYBRJg9gpGNEfV2iBSCrfHgVL8/6cZ+dgpD1hCkOWUt4WYAzhVHfvIMGkAAMYIxPl27BizPXYtGGXbAcFwTrEJ/cojZuO7MNejSns1hNBERABETAiQRcJgDtQNwLwF0AWCWk/JaXHaOHOEaiBaB1mQyVphi0vlqY6F9GE1MUurVJAAaxbGFRMV755ie8Oedn5O3cX6539exMnH1CffyxX1ullHHrJ0T3JQIikLQEXCIAKdYuM2f2fCsaWMu5hWInVgxhDmTqnrdNyrwfbCilG8rcpX2cJAD9LZxBHCyTwlw49Aa6tUkAhmFZ1iF+9n+r8PHizdhzoHx2oMa1qmBIz6YY2aulUsqEwVRdRUAERCBWBFwgAG8F8KiJ+L3OHE1jTj6mt6M2Yb3ecBoDSVgN4UsjKOng4tbyDrMt3C+cwSLt6wQB+LAJrV4Q6U244DoJwAiNOH/dDvzl89X47qft5crPMaVMp8Y1cFPv1ujXUSllIsSry0RABEQgagIuEIDchXwIAEu1WWMZqF94BunmMCEx3ctvzJE376XNLQ4vzhXzFm8ByJJwjPDNs9wZgzyY4qUQAHMBMk0Ma+Tx36nSJACjtDRTykxasMFTfs43pUx2Vjp+d3xd3HF2W7RRSpkoSetyERABEQiPgAsEIAUb09Ix3R0rlrHSGeMVjjfbt+Emgqbn7x6TRDo8mDb2tksAvmpy97GaRySN62CW7fMAnA+AJU+YWJpJFz+yoQ5wJGuK5zUSgDbSZkqZv81Yg8k/bDyq6sixVSvhwm6NcEuf1qiR43uMw8ZFaCgREAEREAEPARcIwJ9MwMb3AFgLeByAfwLgVi3T1YUbiXixKSvHM4W7EvWY2CUAKdT6mzQu9OixyHE0hYuptCkGmWWbBZe5X07PIN2v0YybKM7B5pUADEYowvfXbtuHZz5diS9WlE8pw+GOP64kpczgkxojPZ1pntREQAREQATsJuACAcjStty55NbsTQCeMjV8ewB4H8A1YTLz5jXeDmAygDnm7B93SeO2+2mXAOS91wVwJYDhADoAYKZrJnGmOPRXGi4QL5aMs1YK4bj0CvL1NQCmjnFbkwCMg0U/W7YFf5+5FgvzyqeUyUxPQ09PSpnj0bNFuJ78OCxcU4iACIhAEhNwgQCkh4Avb9ThYACnAlhtPIHhijZWT/OmwPP+yTOAHJ/1hhn4GvNmpwC0LpYh0axzdy2AfSbc+UUDK9hNMRk0s2szsuZAsM4ueV8CMI6GZEoZlp97Y856/LyjfEqZatmZ6N+xPm4/qw0a1KwSx1VpKhEQARFwJ4EkF4CZAO41x9w2xNBCrHlKMRi3rCexEIAsk8KaeVcDoLBhQmf++TuT+PC5IAB5/d3G48e+L4XpQYyhfWI2tARgzNBWPPDWPQfw3P9WYdqSLdi9v7yjummtKrimV0tceUpTbREnyD6aVgREIPkJJLkApAHoyDoBwLooreGorCd2CUAWaOUWLb1+PBS5CAD3zN8wIdNkxhJv9ALWChEghSALLTNqmNu+3E4uqwsW4iBJ0k0C0AGGWrB+J57/bNVRKWVYdeS3rY/F3f3boV0DbxUgByxYSxABERCBJCDgAgHIo2w868f4hmiao7Ke2CUAfzH74wzSYHQM6/r6Ngo/RtCwukc4jUKQ4dJ9ATwB4PVwLk6SvhKADjIUU8q8PX8Dxn31E376xXocFahXrTKGnNwUo3q3VqJpB9lMSxEBEXAuARcIwBsAPGCcWsxZXP6LoSRINdTmmKwndglABn9MsvnMHgVjWwBtzJ99AJwMICNUyknUTwLQocZi1ZEnPl6B6Uu3oKCwzAHNRNM9mtXCH89uq8ARh9pOyxIBEXAGARcIQG/Urj+gR6LUJQnLemKXAKxhALCMibUxNw6jWvaE8RjOAtASwG4AzL5tfS03/x/GcEnRVQIwCcz08ZLNeOHz1Vi+eS/4ife2mjlZuKR7Y08UcbVsnoZQEwEREAER8BJwgQCMlzHjmvXELgH4saniwTN+1ka3Kc8GDgiDXjsAayzh1mFcmrRdJQCTyHS7Cwrx3GerPYmmrYEj/DB1bFjdIwTP7KDyc0lkUi1VBEQghgSSXADyt/rpJnEz077Eo400x+k4F/VBTPIf2yUA6fk7DQA9dNZGMUePXjjJ1c4E8KDxKLIKCM/9hZNHMB7GsXsOCUC7icZpvO/WbsfTn67E9z/vRLHFLXhMpQwM6NwAd/Zri+OqZ8dpNZpGBERABJxHIMkFIIFus+T9iyXgmibJdCuTdoaJoVlnmCn1bG92CUAeiDwFwGKfFXYyGa5zwlg5kyDeZRTvjQA2A/hTGNcnY1cJwGS0mmXNBwqL8OLMtXhzXh627T1Y7m5a1T0G1/+uFS7t3kjpZJLczlq+CIhA+ARcIACZko4/2JmZJB6NldAYXEsNRfHJaiG2N7sE4BcAqFRv8VkhkzkzqWGvMFb+A4Bupj8DPuhBpLh0c5MAdJF1l23ajbHTV2D2mu0osrgFK2emo0/burhnQHs0q8OCN2oiIAIi4H4CLhCAL5j8xjyexlrAvlHAt0dhRVYYqSjIJIqhK77ULgHI7V+WfpsH4HMzJdO2nGTyArKEW6iNmbb/YII/VgH4FgAri7i5SQC60LpMJzNh1jpMmL0OG3aWrzjSuFYVDD+1GUb8pgUyM1WH2IXm1y2JgAgYAi4QgHRyBWo8/HNGFMZ+BvDEFf7RjDEeACui0RlGPcUk1DFpdglALo4lTO40f/LbjsmgHw+x/Jv15u7gWXqTdZtpYCqjJMcOt5f5mhITEokdVAIwsfxjPnve9gI8Pn05Pl++FQeLyn7ZYx3i37Sq40kyfUIjBtOriYAIiIC7CLhAAMbSINRKdJZ5zw4tA/APAKcb/cQydDFpdgrAmCzQpIRhCRa+OgC4IlYTJXBcCcAEwo/n1PQKMnr4H1/+hDVby/9id2zVShh0UlPc0qcVsiux/KSaCIiACCQ/AQnACm3InVMKQG97C8BgAPwS4O7pb2L1BNgpALmP1RrAcaYqiHXNX4VwAwQwFgDz4HCfndVE6AJdaNyhIQyRtF0kAJPWdJEv/Jd9B/Dk9JWYtngz9h0sn2S6a5Oa+GO/tji19bGRT6ArRUAERMABBJJUALL021UmjzH/XlG7OArMjHPg9fl+xuB5wx5RjF3hpXYJQAZpTATQDIDvmKFmyWbCZ+57c7uX5eK4pcwXK4LsDDOVTKx4xWpcCcBYkU2ScT9fnu+pQ7xk455ySaarZ2figq6N8Md+bVAjp1KS3I2WKQIiIAJlBJJUALJu760A9gLg3ytqI6Kw94Um88kgAHmWcfjbP88eMhI4Js0uAUhvHQM2WCuPaVushRK4cFb1CNYYVcOI4bU+HSkqKQRZjNmtTQLQrZYN8772HSjC85+vwnsLNmBnQVn6S35Q29WvhlvOON6TX1BNBERABJKFQJIKwEjwMiCWXrvyucCCjzTM5P+bbTKqUENdZnZFXw1+eWQ97BKAFG9dzNZtZCsBPgXwKIAvIx0gia+TAExi48Vq6fPX7cBTn6wE/zxs+ZWqSlYGzu5YH/cOaKck07GCr3FFQARsI5BCApBlb+mw+ikCeNUBnGtiHRhI+4kRkxEMFdoldgnAGQCeNOVSQpu5pBf31RkBw3N+XMsoo3p9awqHM2Yy9pUATEarxWnNhUXFeOnLtXhjznrk7yn/i+UJDavjvnM74OSW4RTbidPCNY0IiIAIAEghAcjtYjrDgglAR8Q82CUALwLwZ+PCZKoW39JtFHn+2tNGLROY9xtsu9nu/c4EgXC8Qpd/iiQAXW5gu25vVf5ePPHxCny5alu5JNN1q1XGdae3wDWntVC1EbtgaxwREAFbCEgAHoXRETEPdglAf1msuWnF8UMNAmlsCfzwBoAwGIThkYTF84FubRKAbrVsjO6rqKgYL3yxGq99ux67LGcFWW3k950a4P7zOqCmgkZiRF/DioAIhENAAvAoWo6IebBLADJQo6K2voI3meumKMD7VU1ZOIo/lpVza5MAdKtl43Bfny3bgic/WYlV+WV5BfnB7tq0Ju4/twO6NWUgvZoIiIAIJIaABOBR3B0R82CXAIzmqdoE4C8A/glgVzQDJfG1EoBJbDynLJ3VRh7871LMXLUNhy01iBvUyMZNvVth6MlNtT3sFGNpHSKQQgQiEICsgsHKYicCYNoDHjOzVgFj3rzrzfs8PtbN5A62Us0GwDJrTKrMimIMqmCcgTXfXlNTdaOPKbn2GoB7KnBKBbNaRUEgjot5sFMAXgngBpPDj5mr6fW7DUBukBQuNPLNAGoDYA08isFgByiDGSHZ3pcATDaLOXi9DBp57n+rPEEjew6UOdezs9JxUddGuPf37VEtO8vBd6CliYAIuIlABALwHABMqfI9gPf8CEDqDR4RowNpXAAByHJqvzfJnJmK7m8AeFyN47JlGNG4xYhNCs3XzXiRll+rKAjEcTEPdgnAGwE8DOB5AP9nyrZRxDGL9nAAVNcVNRqCOW8oGLsbpU9Yc9z0IajgXiQAU8TQ8b7NaYs246lPVyL3Fx45KWlpacBJzWvjwfM6oEND1R+Ot000nwikGoEIBKAVEeMIfD2A3vebGyeTrweQP9i2ARgK4F3TuR2A5aa0GoNMKTI/BNDQ4hWkE+sJU5EslsGnjoh5sEsAsngxFTNdtFYFzPq9MwGEU8+qF4DbAZxnBCCFIMf1TS7tps+QRwDm5uaiUSP+VU0E7CWQ+8s+/PmjFZi1tnxOwSa1snFz71a4uLueO3uJazQREAEvgY0bN6JFCzrsQBHGYhHexrxWwZImRyIAzwDwuakkZj1axp1JOqqeM06r803wqXc9XCSdV3REcUcyVN3B/qE0R8U82CUAmbSQhiVcqwA83uT5qxIKGZ8+LY1HkB7ErQA4llubRwBOnDgROTk5br1H3ZcDCBwuBhbtSMOXW9KRu7fs49+86hGc3qAYXWsfQQarequJgAiIgE0ECgoKMHQonXFHtYcAPBhkmkgEICdj+Tae/bO2uaa82t0AXjbla8+2dOAXMLdLBgDoafl/nifk+UE6u741/88SuB0BvGjODYZCy1ExD3YJQELhwUmWa7MKwFsAsEZeReqYDwDdtf5eNQHwxa8kbhO7tckD6FbLOvi+pi7chL/OWIv1O/j7W0nLSANOaVEb953bDq3qMghfTQREQASiI5AAD2AgATjPeAbHBBGA3B6ebrnrV4zn8j4fEtQvTQBcHSIhR8U82CUArzUq/g4A/wLAf7cyopB/f6sCODyUeQAA691xf56HNRlJw5f37/yTXkC3Np0BdKtlk+C+Vmzeg4f+uwxzcrfDEjyMZnVycEe/Nji/i7aHk8CMWqIIOJZAAs4A2rEF/IMFKDVIDwCrfSBzZ5K1f8M5TO2YmAe7BCCZXG5EIIUf20bzbwrCihoNxTN/ZxqhyDN/Sxz7JMdmYRKAseGqUcMgsO9AEcZ+vBzvfb8R+w8x/3pJq1Y5E4N7NsEdZ7VBdiUeYVETAREQgdAJJEAAeoNAhpgoYi62DYCVfoJAGP3rdTBdZyqaHedzNpGRwvQa0lFlbQx0ZdBIvdBplOuZ0JgHOwWg9664h869o3A9dm2NELwCwNfGCDzEmQpNAjAVrJxE9/jm3J/xtxlrsHGXdXs4Db3aHIuHzu+IZnWOSaK70VJFQAQSSSACAUgN0dqsmZ44Oom+ALADwM8mbRxz+DGC9yOT64/ijkKNLzamgeFZPoo07ii+YP7/VPOnNw0Mz+XdBaA+gH8D4HavbxoYir8HTIoYniPkuUSeAeTW7yMAxkbJNyExD7EQgFFyQF0AN5mcgowWokeQW8hlLoloZ3De9RKAzrOJVsQIrg278MiHyzB/3c5y4XCt6h6Du85uh7NP4M9MNREQAREITCACAdjbCD7fQZmomYKOLwZ5+DZrUIk3ETS9gNZE0F6ByGtZxYxCkfMx+IPjU+z5q07GVHWjAbQ3k/LIGvMWvxOG7R0V8xCNAGSCxr4AdgKgQq8oXDrUEGkrRwZ/MIiEuQFZ4ypYubkwbOC4rhKAjjOJFmQlsLugEI9OW46pP27CgaKy0t81qmTiilOaY3Tf41EpU+HDempEQASOJhCBAHQrRkfFPEQjAOkOfQpAgXGNVmQwqt5AjVm+/UUAs1SBd30Ul5FEASdLORkJQLd+3F12X8XFxfj3dz/jxZlrkL+nLH1XZnoa+rStiwcv6IhGNZXKyGVm1+2IQFQEXCIA6ZS6FAC3a7kzye1oOrdYWo4xD6E0R8U8RCMAQ7nZUPr8x9QAZrLGQC96GbeHMphPn2QpJyMBGIFxdUliCSxYvxMPf7gUi/J2l3P/t61XDfcMaIfebXmOWk0ERCDVCbhAAHYG8JnJTMLqI4xZYMLoPwPgWcRhYdrYETEPdgnAk0yuPt/SbSebs3sMkw7W+G0RbuBIsDGt70eSTDJe5WQkAMOxpPo6isCOfYV4+MNlmLZ4MwqZadq0utUq4+6z2+LSHkyTpSYCIpCqBFwgACn+eOyNwSLWXMcMKJkIgKIwkpbQmAe7BCCjYp601NzzgrgYADNuUwgGa1+ZmsH+gj0qKp8SbFzv+5EIQLtzCQVaqwRgqFZUP8cS4PbwuK9zPa9f9pVtD9fMycItfVpjxGnNkZ6uc4KONaAWJgIxIuACAcg8gNzuXesjABmbwOhjBpxE0xIS82CXAGSQBl2kdIlaG+vqLWIqsRDI/NeEdzMC2NrqmDw+jNKJpkUiAO0oJ/Oxn0UzIslaooZ5iFbk5eWhcWPWiFYTgeQmMGPFVjw0dSnW7+AR4ZJ2TOUMjOzVEree0VpCMLnNq9WLQFgEXCAAuTvJknEMeLV6AM8yNYND3eaIZcxDWDZhZ7sEIM/nnWupkeddCN2jzNFTK4SVUQHTk8h8OizCzMZw6w8pjgD8PoQxKupipwCMtJyMd32sfcggmnJNAjBKC+tyxxGYm7sdf5qyBKvy+TtiScvOTMflpzTD3f3bKXLYcRbTgkTAfgIuEIDMDUhnFFPBMPiDDi/uVk4BwN1LZisJpcUy5iGU+cv1sUsAvgmAXqwLzCFJTkJBRzhUzoQWSusEYCYABm/UNvn/WEmE9fPKDheFMtLRfSIRgLHaApYHMDIb6qokJbBs027c8/5iLNzAnZSSlpWRhou6NcKD53dEjiqMJKlltWwRCE7ABQKQ8QDvmnJw3NFk8mgmQf3WJJtmDsFwWqxjHkJai10CkGfYqIKpkL3187qa8Gi6SPMCrIbu0IUAfjQvZvhm0kZm7OaeOvMA+kv2GNLN+XSKRADaXU4m0Lp1BjASi+qapCOwfvuvuOvdRZibu6M0cjgjLQ3ndKqPP194AmrmVEq6e9KCRUAEKibgAgHovcHTAHQx1c4YFMLgkEharGMeQlqTXQKQk7E2FOsBEw7rR/HsHz2DhypYCXPpUCjyGopHpnuhIOS/KQ7/DmBZkDEqulGnlZORAAzpsVQntxPI33MAY95bhJmrtuGISSGflgb0blMXYy/pjHrVoz1T7XaCuj8RSB4CLhCATPPytk99YBqAv7EOBvB6mNaIdcxDSMuxUwCGNGEFnRj9QDFofTGIhCVZeAaQojDc5sRyMv7uQR7AcC2r/q4gsKug0HNG8OPFW3DYKEH+UOrZojaevLSzag67wsq6iVQn4AIByPN+PObmm6qOjiv+X7iFKmId8xDSIxeNADwfACNc6eHj3ytqU0NazdGd6MHrZg5c0hvo1iYB6FbL6r5CIlBQWIQHpy7F5B824tDhsqqSXRrXwOOXdEKHBjyNoSYCIpCMBFwgABmDUA/ANh/+dEx9YWIWwjVNLGMeQlpLNAKQQHgIkuq3ogCNisq4MZJmSRgBHh1Nzh1/hZpDumGHdpIAdKhhtKz4EigsKsYT01fgP9+tx0FLzeE29ap6zgj2bMFfuNVEQASSiUASC0DGNFDDUOgtNTuSXvT0+nGXcnqIga7xjHkI6fGIRgCGNEGQTnSrUkT6qupAl+0xW8S++QbtWEsix5AATCR9ze04Akwq/dcZazDu65/w68Gy3PDNaufggfM74ox2KjPnOKNpQSIQgEASC0Bvujb++QyAsnxWQCGAdSZegX8P1mId8xBs/qPej0YAMhdOGwC/mLx9o02CxHAWQc/hywDKssVWfPUoAB38JJwOZ04n9pUAdKJVtKaEE6AQnDBrHV74Yg12FZTFk9WvXhn3DGiPC7ryo6MmAiLgZAJJLAC9WIebIJADNnGORcxD2EuLRgBaq3+E68nzLpQ5/8oO/IS2fFbn2Bxa16TpJQGYNKbSQhNF4J35eXjqk5XYtreszFztYyrh9jOPxxW/ibQUZ6LuRvOKQOoQcIEAjIex4h7zEI0A/J85FLkAgFcdM/2Lv3Z1POgl8RwSgElsPC09vgQ+WbIFj3y0DBt2lv24qZadiRt7t8INp7dUmbn4mkOziUBQAkkqAJmWLlQHFQtXBGuOi3mIRgAyIuYPAFoBuMQchCz71bw8iouCkUnx9yUAU/wB0O2HT+Cb1dvwwNSlWLutLAl/lawMXHVqc9xxVhtkZqaHP6iuEAERsJ1AkgpAOrZCba+F0DHcndKYxzxEIwCt95trSqSwJrBa+AQkAMNnpitEwENgYd5OT5m5ZZtZo72kVcpIx2U9GuNPv2+PbJWZ05MiAgklkKQC0G5mjot5iEYA2hEEYjfgZB1PAjBZLad1O4bAmvy9uPv9RViwflfpmjLT03Bu54Z45MKOqJad5VukJtYAACAASURBVJi1aiEikEoEklQAVgdALxwb/15R8/arqI/jYh6iEYB2BIGk0megonuVANSTIAI2EcjbWYB731+Mb1b/UnqAJz0NOLN9PTx28Qk4tqrKzNmEWsOIQEgEklQAWqt/0Hvn7zwgNVRFuY5D4pOoTtEIQAWB2Gc1CUD7WGokEfAQ+GXfAdz7/hJ8tjwfxd56wwBOa10Hj1/SGU1q5YiUCIhAHAgkqQD8HYBZJvkzzwPmAShLSlrCjQeNmwII5QxgHEiHN0U0AtAaBHIxgE/8FEr2rkZBIBXbRQIwvOdWvUUgZAJ7DxzC/R8sxX8XbkKRVwkCOKVlbfxlcDfUqy6PYMgw1VEEIiCQpALQeqd21wKOgKL9l0QjAK2rURBIdLaRAIyOn64WgaAEDhQW4dFpK/D2vDwUHi6pXskfgGd1qIenLu2MGjmVgo6hDiIgAuETcIEADFQLuBmAZQCOCZ9K4q+IVgBOAzAEwG5zK2MAvATAewqbhTu/NtU7En+3zl2BBKBzbaOVuYxAUVExHvt4Of793XocOlyyN5yRBlzcvTEeuaCjooZdZm/dTuIJJLEAfNbQY6WzcT5Vy1gL+GSzLXxa4imHv4JoBSBVMWv5bjVT++at4TbxJv58DX9pKXWFBGBKmVs36wQC9AjeO3kJpvy4sfSMYFZGmieP4D3ntFNCaScYSWtwBYEkFoBfGAPwPOC3KKn/623eWsCs8bs6GQ1ltwBkIq4ullq9EoChPRUSgKFxUi8RsJ3AroJC3PHOQsxYsbU0zI8JpUf3PR439GaeezUREIFoCCSxAPTe9gQA9AKGku4lGlRxvVYCMK64A04mAegMO2gVKUxg8679GP32j5ibyxSnJa1GlUzcO6A9Bp3EQD81ERCBSAi4QABGctuOvyZaAehb2oQeQNa7Y1AImzyAoT0CEoChcVIvEYg5gVX5e3HbWz+UqyxyXLXK+POFJ6BfR554URMBEQiHgARgOLTi1zdaAcgzgB9b0r+cB2AGAG9xzsoA+usMYFCDSgAGRaQOIhBfAvPX7cAfJy3Euu0FpRM3rV0FTw/sgp4tGN+mJgIiEAoBCcBQKMW/T7QCkPviobQRoXRK4T4SgClsfN26swl8vjzfU1kkf+/B0oW2r18Nzw3qinYNglWIcva9aXUiEA8CEoDxoBz+HNEKwPBn1BX+CEgA6rkQAYcTeHd+Hv780XLs2n+odKUnNa+F5wd3RaOaqiricPNpeQkkIAGYQPgVTC0B6Ay7SAA6ww5ahQgEJfDPL9fiL5+vRkFhSVUo/hDt3bauxyNYU8mkg/JTh9QjIAHoTJtLADrDLhKAzrCDViECIREoLi7GE9NXYvys3NJk0ulpwPldGuGxi09ATqXMkMZRJxFIBQISgM60sgSgM+wiAegMO2gVIhAWgcKiYtz3wRK8O38DDh8pqSqSmZ6Gy09phvsGtEdmJmvFq4lAahOQAHSm/SUAnWEXCUBn2EGrEIGICOw9cAh3TlqIT5bmlyaTzs5Mx419WuGWPq1VVSQiqrrILQQkAJ1pSQlAZ9hFAtAZdtAqRCAqAvl7DuAPb/+I2Wu3l45TrXIm7u7fFlf8pnlUY+tiEUhWAhKAzrScBKAz7CIB6Aw7aBUiYAuB3G37PFVFFm3YXTpenWMq4ZELTsCAzg1smUODiECyEJAAdKalJACdYRcJQGfYQasQAVsJLMzbidvfWYi127y58YHGtargyUs649TWx9o6lwYTAacSkAB0pmUkAJ1hFwlAZ9hBqxCBmBD4cuVW3PP+YmzafaB0/Db1quL5QV3RoWGNmMypQUXAKQQkAJ1iifLrkAB0hl0kAJ1hB61CBGJK4IMfN+Kh/y7Djl8LS+fp2qQmXhjcDU3qKJl0TOFr8IQRkABMGPoKJ5YAdIZdJACdYQetQgTiQmDCrFw8/elK/HqwJJk0W6/jj8Vzg7rg2KrZcVmDJhGBeBGQAIwX6fDmkQAMj1eseksAxoqsxhUBhxJgMunnP1uNf371Ew4WFXtWmZYGDDihPp64pAuqZiuZtENNp2WFSUACMExgceouARgn0EGmkQB0hh20ChGIO4GiomI8+N+leGteHoqKS5JJZ6Sn4cpTmuH+c9srh2DcLaIJ7SYQgQA8HcCdAE4EwLD5iwBMsayL2uUhACMB1AQwC8CNAFZb+tQG8AKA8wDwN6z3AIwGsM/SpzOAvwM4CcA20/9Ju+/fqeNJADrDMhKAzrCDViECCSOw70AR7pm8CB8t2gyjA1G1cqYndcxF3fkjQk0EkpNABALwHACnAfjeCDdfAXg3gHsAXAXgJwCPAOgEoAMAb6TVx0Y8Xg8gC8AEAPMADDUUqwNYBeAzAI+b68cDuA3Ay8lJOrxVSwCGxytWvSUAY0VW44pAkhHYsa8QN7/5fblk0s3r5ODFy7srYjjJbKnllhCIQABa0dEtbhWA1C2bADwD4GnTkaH0+UYQvgWgPYBlxrM33/TpD2AagMbmenoMHwVQH4A3KmssgAsBtEsF20kAOsPKHgGYm5uLRo30m74zTKJViEBiCSzeuBu3vb0IP+/cX7qQ01vXxnOXdUb1KpUSuzjNLgJhENi4cSNatGjBKyisNlsuPQiAr4qarwBsCWAtgG4AfrRc+KX5N7d5rzYCsZblfR6qpXdwIIDJAF4HQC8gBZ+39QEwAwC3j3eGcYtJ2VUC0Blm8wjAiRMnIidHqSCcYRKtQgScQWDdXuD9dRlYv6/kx3WdykdwfrNidKl9xBM0oiYCTidQUFCAoUO9O6/lVstzfA+GKQBPNWf+GvqIyXcATynuQQDuBTAcQFufsbcCeADAPwB8CiAXALeIvY1byEvNVvJyp3ONdn368REtQXuulwfQHo4aRQRcSYCBIn/+eAXemrcBh0viRFA9OwOPnN8BAzqptJwrje6im7LZAxhIAE4CwLxKgysQgAz0uA/ASwEEYEcAS8wW8goXmcDvrUgAOsPCOgPoDDtoFSLgaAK/7DuAUW/8gLm5O0rX2fLYYzznA9s14G6Wmgg4j4DNZwC1BWyTiSUAbQIZ5TASgFEC1OUikEoEFqzfiVve/AGbdpWdD+zTti7+OqQbqmUz4FFNBJxDwGYB6A0CYQAIA0HY+NsPt3cZFWwNAukBYIHp0w/AdD9BIPUAHDJ9HgNwsYJAnPPspMJKJABTwcq6RxGwmcB/vl2HR6etwP5DJRVFMtPTcN3pLfHHfm2UP9Bm1houcgIRCMCqAFqbGX8AcDuALwDQ9f0zAKaBGWPO+fEcH9PAMKefbxoYirsbLGlgGBHsPYzIyOGVZiv4CQAnAGAamD8oDUzkttaV4ROQAAyfma4QAREAwPOB905ZjHcXbCjNH1ijShbGXtIJ55yg84F6SBJPIAIB2NsIPt/Fv2a8fN5E0NeZRNDfABhl8vp5r2Ek7998EkHf6pMIuovpw0TQv5hE0BSDKdHcvgWcLNnEJQBT4uOmmxSB2BHI38PzgQuwYP2u0kmOP64q/nF5d7SuVy12E2tkEQhCIAIBKKZxIOB2AZgs2cQlAOPwsGsKEUgFAnN+2o7Rb/2ALXvK0qud1f44PDeom+oLp8ID4MB7lAB0oFFYe9yZy4rJqpycTVwCMCYm16AikLoExn+Tiyenr8CBIpZBBbIy0jCqdyuM7nu8zgem7mORkDuXAEwI9qCTprIATGQoeWUAfHkbD+qsyMvLQ+PGrFKjJgIiIALREygsKsaY9xZh8o8bccTkD6yVk4WnLu2MMzuwApaaCMSegARg7BlHMkMqC8BEZhNn5nNmIy/XJAAjeYR1jQiIQDACm3ftxw1vLMDCvN2lXdvVr4Z/XnkimtU5Jtjlel8EoiIgARgVvphdLAEI+JaTiUc2cXkAY/ZIa2AREIFABGav+QW3vf0jtu4tOR/IL4D+J9THM5d1QU4llkpVEwH7CUgA2s/UjhFTWQAmcgvY13Y6A2jH06wxREAEQiIw7qu1ePrTVThoOR/Is4E3n3F8SNerkwiEQ0ACMBxa8eubygLQSdnEJQDj98xrJhEQAQAHCotw13uL8d+Fm2COB6L2MZXw7GVd0LvtcWIkArYRkAC0DaWtA7ldACZLNnEJQFsfaw0mAiIQKoG8nQW48d8LsGTTntJLOjaojpeuOBFN6uSEOoz6iUBAAhKAznw43C4AkyWbuASgMz8fWpUIpAyBL1duxR3vLMQvvxZ67plfDud2aYCnLumMbJ0PTJnnIBY3KgEYC6rRj+l2ARg9ofiMIAEYH86aRQREIAiBv3+xBn/5bDUKD5fkD6yUmY47zmqD63/XSuxEICICEoARYYv5RRKAMUcc0gQSgCFhUicREIF4EOD5wNsnLcTHi7eUng88tmplPD+oC357fN14LEFzuIiABKAzjSkB6Ay7SAA6ww5ahQiIgIXA+u2/4ob/LMDyzXtL/7dz4xr4xxXd0aimzgfqYQmNgARgaJzi3UsCMN7E/c8nAegMO2gVIiACfgh8vjwff5y0EDsLDnneTUsDBp7YGGMv7qSycnpighKQAAyKKCEdJAATgv2oSSUAnWEHrUIERKACAs9/tgo8I3jocEnimGrZmXh+UFf0bV9P3EQgIAEJQGc+HBKAzrBLSALw8OHDOHSo5DdwtfgTyMrKQkZGRvwn1owi4CACBYVFuOmN7/HFym2lq+rRrBZeGd4DNXMqOWilWopTCEgAOsUS5dchAegMu1QoAI8cOYItW7Zg165dzlhtCq+iZs2aqF+/PtK4B6YmAilMYP66HZ7zgb/sK0kbk5mehlv7Hu95qYmAlYAEoDOfB32LOcMuFQrAzZs3e8Tfcccdh5ycHImPBNiMIrygoABbt24FRWCDBg0SsApNKQLOIlBcXIynPlmFf361FsWmnEiDGtkYN6wHTmhUw1mL1WoSRkACMGHoK5xYAtAZdgkoALntu2rVKo/4q1OnjjNWm8Kr2L59u0cEtmnTRtvBKfwc6NbLE9i65wCufnVeuWoi55xQH38Z3M2TR1AttQlIADrT/hKAzrBLQAF44MAB5Obmonnz5qhSpYozVpvCq9i/fz/WrVuHFi1aIDs7O4VJ6NZF4GgCUxduxJj3FqOg8LDnzSpZGXjsok64qDt/xKmlKgEJQGdaXgLQGXYJKgAlOJxhKK8glz2cYQ+twnkECouKPSljpi7cVLq49vWr4ZWreih3oPPMFZcVSQDGBXPYk0gAho0sJhdIAMYEq/2DSgDaz1QjupPAss27cd3rC7Bh537PDaanASNOa4H/G9BOuQPdafKAdyUB6EyDSwA6wy6uFIBXXXUVXnvtNQ/hzMxM1K5dG507d8aQIUPA99LTy84GcYt7/fr1nr4MdGnZsiVGjx6Na6+9NqYWoqC744478NZbb+HgwYM4++yz8eKLL6JePf95zSQAY2oODe5CAi/NXIunP12JIhMlUvuYSnhxaHec0kpnml1obr+3JAHoTEtLADrDLq4VgPn5+ZgwYQIYzMK/T58+HY8//jh69eqFqVOneoQhGwXgNddcg5EjR3qibSdNmoQxY8Zg2rRpOOecc2JmpRtvvBEfffQRXn31VdSoUQM333yzR5jOmjXL75wSgDEzhQZ2MYHdBYW47t8LMCd3R+ld9jr+WPzj8hNRNbvkZ4CaewlIADrTthKAzrCLawUg09dMmTKlHOUZM2agb9++GDduXKmHjwLwtttu87y8jVHPw4cPx7PPPhsTK+3evRt169bFxIkTcemll3rmWLFiBdq3b49vv/0Wp5xyylHzSgDGxBQaNEUIfLlyK25960fs3l+S0D4rIw33Dmjv2RpWcy8BCUBn2lYC0Bl2SSkBSORdu3ZFw4YNPR4+NqsAZG6xyZMnY+DAgbjrrrswduzYgFaid/Drr78O+H6zZs2wdOlSv+97hejOnTs9uf28jddQiP7hD3+QAHTG50OrcBEBfr7v/2Ap3pj7M46Y3IHN6uRg/FUnoVXdqi66U92Kl4AEoDOfBQlAZ9glLAHIpMT7D5WkWYh3Y1qHUKtg8JyfPw8g1zx48GAsWrQIy5YtKxWATHjNcms8i1dUVOQ5Mzhnzhy0bt064G1u3LgRTM0SqHE8Cjp/jZ6/ESNGeOaztp49e6JPnz544oknJADj/YBpvpQhkLe9AFe/Ng+rt+7z3DO/jC49sTEev6gTMpU70FXPgQSgM80pAegMu4QlAFmLs8P9nyRk5csePhs5lUI7s1ORABw0aBCWLFlS6p2jB/CKK67wBIdQCN55550YNWoUhg0bFrP7DCQATzrpJM8WtT/Po7aAY2YODZyiBN6c+zMenLoUB4uKPQSqVs7Es5d1Qb+O9VOUiPtuWwLQmTaVAHSGXVJOADIauGnTpvjwww9LPYDWM4B5eXno1KkTZs+ejQ4dOgS0kraAnfEAaxUiEA2BA4VFuGniD/h8xdbSYbo1rYl/DTsJtatWimZoXesAAhKADjCCnyVIADrDLmEJwGTfAvaevRs/frxnC5bNXxDI9ddfjy1btuCDDz4IaKVotoC9QSBvvvkmLrnkEs8cLLvXtm1bBYE443OhVaQYgQXrd+LG/yzA1r0lxzIy0tNwyxmtcduZbVKMhLtuVwLQmfaUAHSGXcISgM5YcvBVcDs3UBqY3r17e6KDMzIyAgrA5cuXo2PHjpg7dy569OgRfMIIejANDANRmAamevXquOWWWzyj0PPor2kLOALIukQEwiTw1Ccr8dLMNThsgkTqVa+Ml688EV2a1ApzJHV3AgEJQCdY4eg1SAA6wy6uFYDWRNC1atVCly5dMHToUE96F99E0L5pYGia/v37e/p5o4XtNpc3ETS9gNZE0PXr+z9/JAFotwU0ngj4J7B1zwGMfH0+Fm7YXdrh7A718JfBXZEd4jlksXUGAQlAZ9jBdxUSgM6wiysFoDPQ2rsKCUB7eWo0EQhGYNqizbjz3YX4tbAk80F2VjoevuAEXNajSbBL9b5DCEgAOsQQPsuQAHSGXSQAnWGHoKuQAAyKSB1EwHYCRUXFuPO9RZjyw0aYXWG0rVcN40f0QKOaObbPpwHtJSABaC9Pu0aTALSLZHTjSABGxy9uV0sAxg21JhKBowisyt+La1+dh593luT+TE8DrvxNczxwbvtyR0qEzlkEJACdZQ/vaiQAnWEXCUBn2CHoKiQAgyJSBxGIOYFxX6/Fk9NX4pCJEqmZk4W/DemG3x5fN+Zza4LwCUgAhs8sHldIAMaDcvA5JACDM3JEDwlAR5hBixAB7D1wCNf/ewFmr91eSuO0VnXw0pUnolp2lgg5iIAEoIOMYVmKBKAz7CIB6Aw7BF2FBGBQROogAnEl8M3qbbj5zR+wq+CQZ96sjDTc1b8tRvZqFdd1aLLABCQAnfl0SAA6wy4SgM6wQ9BVSAAGRaQOIhB3AsXFxXjow+V4/dt1OGKiRJrXycG/rz0ZTWopSCTuBvGZUAIw0RbwP78EoDPsIgHoDDsEXYUEYFBE6iACCSOQt7MA17w6D6vy93nWwCCRm/u0xu392iZsTZoYkAB05lMgAegMu0gAOsMOQVchARgUkTqIQMIJ/OfbdXjow2WlQSJNalXBf649Gc3qHJPwtaXiAiQAnWl1CUBn2EUC0Bl2CLoKCcCgiNRBBBxBYFdBIYaNn4tFppJIWhpwXa+WuGdAe0esL5UWIQHoTGtLADrDLhKAzrBD0FVIAAZFpA4i4CgCb8/7GfdNWYrCw8WedTWskY3Xr+6J1vWqOWqdbl5MBAKQxnkEwEUAjgPwA4DRAOYZTtQuDwEYCaAmgFkAbgSw2sKxNoAXAJwHgMZ/z4xRcj5ADRKAzngIXCkAr7rqKlhrAdeuXRudO3fGkCFDwPd8awGvX7/eY42cnBy0bNkSo0ePxrXXXhtTC7388suYOHEivv/+e+zduxc7d+5EzZr8eeK/SQDG1BwaXARiQoApY66aMBcL1u/yjM8vvhGnNceffq8E0jEB7jNoBALwbQAnGFG3CcAVAP4AoAOAjQDuBnAPgKsA/GTEYifz/gEz/ccAGgC4nsHhACYYATk0HvecDHNIADrDSq4VgPn5+ZgwYQIOHz4M/n369Ol4/PHH0atXL0ydOhWZmZkeCzRv3hzXXHMNRo4ciYKCAkyaNAljxozBtGnTcM4558TMSs8//zwo6tjuueceCcCYkdbAIpB4ApO/34gx7y/CwaISb2C9apXx2tU90a5B9cQvzsUrCFMAVgGwF8AFAD6yYFkAgKLuPgAUhc8AeNq8XwNAvhGEbwHgPv8yACcBmG/69AcwDUBjc72LiYd2axKAoXGKdS/XCsBdu3ZhypQp5fjNmDEDffv2xbhx40o9fBSAt912m+flbXXq1MHw4cPx7LPPxpo/Zs6ciT59+kgAxpy0JhCBxBLYd6AIV782D3Nzd3gWwi/By09uiocv6KhycjEyTZgCkNu/ewCcCeBzy5K+AVAE4GoAawF0A/Cj5f0vzb+5Vcw+FIi1LO/T28Df9gcCmByjW02qYSUAnWEujwDMzc1Fo0b8a1mjdyovL8/jIcvOzi55g4muDhUkZuVZOQBPU4fQRowYAQrAyZOP/qx1794dDRo0wEcflfyC593y5bYvc3rxmkGDBuHOO+/0eAwDtQEDBuCbb/hzwX9r1qwZFi9eHHS1FIAUpdu3bw+6Bbxu3To0adKkzB5BR1cHERABpxGYtngzxkxeiv2HSryBdatWwrgru6NjQ3kD7bbVxo0b0aJFCw7bDsBmy/gHAfDl22YDKATA7Vp69oYAeA3AGu7emzN/DX3GeoffjgAGAbgXwHAAvvl/tgJ4AMA/7L7HZBwvtG/yZLyz5FqzRwDyLBrPv1kbt0jr16/vERyVKlUqeetQAWr+PTGRbLtuWg5QBIbQRo0ahd27d+ONN944qvfVV1+NZcuW4bvvvvO8x7OB3CLOysrCwYMHUVRUhFq1auGzzz7ziMNAbdOmTaVbuP76kF/Tpk2DrpYi8rzzzgPFXY0a3E3w3woLCz2CfMuWLZ41qomACCQvAcaFfL4pDdM3pOPwkTRUyTiCC5sX4+S6R0L9PTd5bz6OK+exnqFD/R69YyDHg36WwjIu4wGcDuAwgO8BrALQHQAPhjPow1cATjJ9B1cgALeZLeSX4nj7jp1KAtAZpgnPA1j4K9LH8hhD/FvxmA1ApdByaVXkARw8eDCWLl1a6p2jyLv88ss9W76bN2/G3XffjRtuuAHDhg2Ly03KAxgXzJpEBBxJ4PPlW3H7u4tQUFjiDaxzTBb+eXk3dGkSOCDMkTfi0EVF4AH03gm/bOiSpdeQgSFVAdyiLWB7DC0BaA/HaEcJ7wxgkmwBM9LX3xlAwqLHj565Dz/80MPO9wwgvWydOnXC7Nmz0aEDA7/8NwaIfP311wHf5xYwhWawpjOAwQjpfRFwN4EDhUW44Y3vMXMlnUQl7aJujfDMwM46Gxil6cM8A+hvNp7lywVwF4BxJoiDASA858dGkcjtXUYFW4NAegBg8AhbPwDTFQRShlcCMMoH26bLwxOANk0a62ECCUBvEMj48eNBLyGbvyCQ66+/3rPV+sEHHwRcKn+z3L9/f8D3uaVMERisSQAGI6T3RSA1CMxYsRW3TPwevxZy5xGoWSULLw87ET1b1EkNADG4ywgE4NkmPmclgNYAnjJnBX/LQ1AmDcwYc86PwpA5Azv7SQNTD8ANljQwjAhWGhhjYwlAwAkJJ10rAAOlgendu7cnOjgjIyOgAFy+fDk6duyIuXPnokcP/iJnf6PA5Gv+/PmeFDRfffUVqlWr5vFOMm+hb1MeQPttoBFFwGkECouKcdMbC/C/5XQqlbTfd6qPvwzqhszMdKct1/HriUAAXgaA0X8868RwbSZx/j8Auy3ahecHrzOJoBkJOMqcE/Ty4A/wv/kkgr4VgBJBSwCWfmackHDStQLQmgiaQR1dunTxHAbmWT/fRNC+aWBoof79+3v6MR9gLNqDDz6Ihx7iz5HyjbkL6cGUAIwFdY0pAslB4JvV23Djf77H3oMlAV/VsjPxzytOxKmtj02OG3DIKiMQgA5ZubuXkeoeQKcknHSlAHTjR0ceQDdaVfckAoEJFBUV49a3f8C0xVtKO/XrUA9/G9odleQNDOnRkQAMCVPcO6W6AHRKwkkJwLg/+pFNKAEYGTddJQLJTmDOT9tx3b/nY/f+Em/gMZUz8Peh3dG7LUvVqlVEQALQmc9HqgtAWiURCScrA+DL21ivcAUjXxs3Lp/eRYLDWR8c2cNZ9tBqRCCeBJik/g/vLMQHP7ISWUnr07Yu/nllD3kDKzCEBGA8n9LQ55IABBKRcJKJL5mNvFyTAAz9wU1UTwnARJHXvCLgHAIL1u/ENa/Nw64CBqQCOZUy8NfBXXFmh/rOWaSDViIB6CBjWJYiAVgGI54JJ+UBdObnIeiqJACDIlIHEUgJAvQG3v3eYkxasKH0fnsdfyz+eeWJyKnEsrNqXgISgM58FiQAj7ZLIhJO6gygMz8fR61KAjBJDKVlikCcCCzasAsjJszD9l9ZuhbIzkrHswO7YkBnnuxRIwEJQGc+BxKAgBMSTkoAOvPzIQGYJHbRMkUgkQToDbzvg6WYOOdnHDELOblFbfxr+Emomi1voARgIp/OwHNLAAJOSDgpAejMz4cEYJLYRcsUAScQWLZ5N64aPw9b9x70LKdyZjqeuKQzLuzGH/Gp2yQAnWl7CUBn2EUC0Bl2CLoKbQEHRaQOIpDSBOgNfPjD5Xht9rpSb2CPZrUwYcRJqJadlZJsJACdaXYJQGfYRQLQGXYIugoJwKCI1EEERIA1yfL3Yvj4udi8+4CHR6WMdPz5ohNwWY8mKcdHAtCZJpcAdIZdJACdYYegq5AADIpIHURABCwEHv1oGV75JhdHzOHALo1r4LWre6JmTqWU4SQB6ExTSwA6wy6uFICspWutBVy7dm107twZQ4YM8dTZg7PdGAAAGihJREFU9a0FvH79eo81cnJy0LJlS4wePRrXXnttzCy0Y8cOPPDAA/j000/BHIzHHnssLrzwQjzyyCOoUaOG33klAGNmDg0sAq4lkLttH64cPxcbdu733GNWRhoevuAEDOnZ1LX3bL0xCUBnmlkC0Bl2ca0AzM/Px4QJE3D48GHw79OnT8fjjz+OXr16YerUqcjMLImQa968Oa655hqMHDkSBQUFmDRpEsaMGYNp06bhnHPOiYmVlixZ4hGAFKMdOnQABegNN9zgEanvvvuuBGBMqGtQEUhdAk99shL/mLkGxcYb2LN5Lbx6dU/X5w2UAHTmMy8B6Ay7uFYA7tq1C1OmTClHecaMGejbty/GjRtX6uGjALzttts8L2+rU6cOhg8fjmeffTZuVqLwvOKKK/Drr7+WilPr5PIAxs0UmkgEXEkgb3sBhrzyXak3sEpWBv5+eXec0c69NYUlAJ35KEsAOsMuYQnAI0eOYH9RyVZCvFuVzCpISwvtsaFnzZ8A5Jq7du2Khg0bejx8Xg+gVwAyim7y5MkYOHAg7rrrLowdOzbgbdI7+PXXXwd8v1mzZli6dGnImF555RXcc8892LZtmzyAIVNTRxEQgXAJPPzfpZgwqyxSeECn+vjroG7IzEwPdyjH95cAdKaJQvsmd+ba3bSqsARgwaECnDzx5ITc/5yhc5CTlRPS3BUJwMGDB2PRokVYtmxZqQDcvHkzsrKycPDgQRQVFYFnBufMmYPWrVsHnG/jxo3Yvz+wGOZ4FIGhtF9++QUnnniixwP46KOPSgCGAk19REAEIibAKiLDxs8trSlcMycLr1/dE50b14x4TCdeKAHoRKsAEoDOsEvKCcBBgwaBZ/C83jluAVN4UTRSCN55550YNWoUhg0bFhcL7dmzB2eddZZHdPJsIoWjv6Yt4LiYQ5OIQMoQ4I7HLW/+gI8Wb/HcM7+UR5zWHPef19E1DCQAnWlKCUBn2CUsAeiGLWAGWjRt2hQffvhhqQfQegaQUbmdOnXC7NmzPQEagZodW8B79+7F2Wef7Yk+5nqys7MDzicB6IwPjFYhAm4jMGPFVtz0xvfYf+iw59Ya16qCN687BU1qhbbj4mQeEoDOtI4EoDPsEpYAdMaSg68i0BawNwhk/PjxGDFihF8ByP+8/vrrsWXLFnzwwQcBJ4t2C5ieP4q/ypUre84jUgRW1CQAg9tdPURABCIjUFBYhKvGz8XcdTs9A6SnAfec0w4jT28V2YAOuUoC0CGG8FmGBKAz7OJaARgoDUzv3r090cEZGRkBBeDy5cvRsWNHzJ07Fz169LDdUvT8cduXaWcYdHLMMceUzlG3bt3StVknlgC03QwaUAREwIfAm3N/xn1TlqDI5Ivp2LA6Jl57MmokafJoCUBnPuISgM6wi2sFoDURdK1atdClSxcMHTrUk97FNxG0bxoYmqZ///6eft5oYTvNNXPmTPTp08fvkLm5uZ7chL5NAtBOC2gsERCBQAS27jmAoa/MwZqt+zxdWEru6cs64/wu/LpIriYB6Ex7SQA6wy6uFIDOQGvvKiQA7eWp0URABCom8Nz/VuKvM9aUlpL7XZu6GDesByolUboYCUBnPuUSgM6wiwSgM+wQdBUSgEERqYMIiIDNBNbk7/V4A7fuPegZuWrlTPxreA+c3LKOzTPFZjgJwNhwjXZUCcBoCdpzvQSgPRxjPooEYMwRawIREAE/BJguZsz7i/HO/A2l7w7s0RhPXNyp3HEaJ8KTAHSiVZQH0ClWkQB0iiWCrEMCMEkMpWWKgEsJzPlpO655bT72HSzy3OFx1Sp7AkRa16vm2DuWAHSmaeQBdIZdJACdYYegq5AADIpIHURABGJMoLCoGCNfn48vV5WUrGR1zlv6tMbt/drGeObIhpcAjIxbrK+SAIw14dDGlwAMjVPCe0kAJtwEWoAIiIAhMHXhRvzxnUUoPFzs+Z9WdavizZEn47jqgZPZJwKeBGAiqAefUwIwOKN49JAAjAdlG+aQALQBooYQARGwjcDugkJc/socLNm0xzNmZnoaHr7gBAw9ualtc0Q7kARgtARjc70EYGy4hjuqBGC4xBLUXwIwQeA1rQiIQIUExn21FmM/XoHDR0q6ndS8Fl67uidyKmUmnJwEYMJN4HcBEoDOsIsEoDPsEHQVEoBBEamDCIhAggjk7SzA0Je/Q97O/Z4VVMnKwN8v744z2h2XoBWVTCsBmFD8ASeXAHSGXSQAnWGHoKuQAAyKSB1EQAQSTODh/y7FhFnrYJyBGNCpPv46qBsyE5Q8WgIwwQ9EgOklAJ1hFwlAZ9gh6CokAIMiUgcREAEHEFiycTeu+Ncc7Co45FlNzZwsvH51T3RuXDPuq5MAjDvykCaUAAwJU8w7uVIAXnXVVbDWAq5duzY6d+6MIUOGgO/51gJev369B3ROTg5atmyJ0aNH49prr40p/Ouvvx6fffYZNm3ahKpVq+LUU0/FE088gXbt2vmdVwIwpubQ4CIgAjYSYPLoW978AR8t3uIZlV/4I05rjvvP62jjLMGHkgAMzigRPSQAE0H96DldKwDz8/MxYcIEHD58GPz79OnT8fjjj6NXr16YOnUqMjNLDig3b94c11xzDUaOHImCggJMmjQJY8aMwbRp03DOOefEzEovv/yyR+w1bdoUO3bswIMPPogff/wRubm5yMjIOGpeCcCYmUIDi4AIxIjAjBVbcdMb32P/ocOeGRrXqoI3rzsFTWrlxGjG8sNKAMYFc9iTSACGjSwmF7hWAO7atQtTpkwpB23GjBno27cvxo0bV+rhowC87bbbPC9vq1OnDoYPH45nn302JtD9Dbpo0SJ06dIFa9asQatWrSQA40ZeE4mACMSSQEFhEa6aMA9zc3d4pklPA+7u3w7X/+7on3N2r0MC0G6i9ownAWgPx2hHCUsAHjlyBEf2l0R5xbulVamCNKadD6Fxm9efAOSlXbt2RcOGDT0ePjarAOS2xeTJkzFw4EDcddddGDt2bMDZ6B38+uuvA77frFkzLF26NITVAr/++iv+9Kc/4YMPPsCKFStQqVIlCcCQyKmTCIhAshB4c+7PuG/KEhQVl4SIdGxY3VNKrkbO0T/v7LonCUC7SNo7Tmjf5PbOqdGOJhCWACwuKMDK7icmhGPb7xcgPSe0bYOKBODgwYNBb9uyZctKBeDmzZuRlZWFgwcPoqioCDwzOGfOHLRu3TrgvW7cuBH7KxDDHI8isKL24osveoQmBSC3gz/88EO/3j+OoS3ghDx2mlQERMBGAr/sO4AhL8/B6q37PKNWykjHUwM744Ku/Cqyv0kA2s/UjhElAO2gGP0YKScABw0ahCVLlpR65+gBvOKKKzzBIRSCd955J0aNGoVhw4ZFTzfICLt378bWrVs98z799NOgqJw1axays48upyQBGHNzaAIREIE4EXjufyvx1xlrcMTkizm9zbF4ZdhJqGRzuhgJwDgZNMxpJADDBBaj7mEJQDdsATMamIEX9Lax+Z4BzMvLQ6dOnTB79mx06NAhIHY7t4A5SWFhIWrVqoVXXnnFE63s2yQAY/QJ0LAiIAIJIbAmfy+GvjIHW/ce9MxftXKGRwSe0qqObeuRALQNpa0DSQDaijPiwcISgBHPEucLA20Be4NAxo8fjxEjRvgVgPxPpmjZsmWL50xeoGbHFrB1bG4/UwByW5jrlwCM80Oj6URABOJOgOeux7y/GO/M31A698ATG+OJSzqVS9cV6cIkACMlF9vrJABjyzfU0V0rAAOlgendu7cnOtibasVfFPDy5cvRsWNHzJ07Fz169AiVZcj9fvrpJ7z99tvo168f6tat6ylXxIATbv9y7uOOO7p8kjyAIeNVRxEQgSQjMOen7bj2tfnYe7AI9apVxrf3nCEBmGQ2DGe5EoDh0IpdX9cKQGsiaHrWmGJl6NChnvQuvomgfdPAEHf//v09/bzRwnaagMmfmWh6wYIF2LlzJ+rVq4fTTz8d999/P9q2bet3KglAOy2gsURABJxGoLCoGDdP/B53n9MOrepWtWV58gDagtH2QSQAbUca0YCuFIARkXD4RRKADjeQlicCIuA4AmEKQGbgfxDAFQDqA9gE4FUAfwZKyxtTuzwEYCSr3AGYBeBGAKstN18bwAsAzgNQDOA9AKMBlIQ+q3kqw6glnoAEYOJtENIKJABDwqROIiACIlBKIEwBeC+A2wEMB8Akrjz/MwHA/wH4qxn0bgD3AOBB7Z8APAKgEwBGDB4wfT4G0IDHyQFkmTHmARgq05QQkAB0xpMgAegMOwRdhQRgUETqIAIiIALlCIQpAJkaIh/ANZZB6L1j9QN6Balb6BV8BsDTpk8Ncw0F4VsA2gNgktmTAMw3ffoDYOWBxub6lLeSBKAzHgGPAGT92UaNyifipOBgShQGSfjLS+eM5afOKmiPdevWoUmTJrJH6phddyoCIhAFAWZraNGiBUdoB2CzZSjmninJP1PW6AG8DkA/AKsAdAHwqfEKvgGgJYC1ALoB+NFy3Zfm39zmvdoIxFqW91l4nt7BgQAmR3E7rrlUAtAZpvQIwIkTJyLHp8pGZmYm6tev7xEc/kqTOWP5qbMK5gmkIGd6GlYrURMBERABEaiYQEFBgSf4z0/jOT6e97O2dACPAbgLwGEAPBPI7d/HTadTzZm/hj5i8h1zRnAQAIpIbiH7RvNtBfAAgH/IZtoCdsozIA+gUywRZB3yACaJobRMERABxxAI0wM4GMBTAO40ZwC7AnjeeABfAxBIAE4ygpHXBxKA2wDcB+Alx8BJ4ELkAUwgfMvUQc8Acgu4SpUqzlhtCq+CdYe5BcztDG3Jp/CDoFsXAREImUCYZwDzAIwF8HfLBH8y5/+4hawt4JDJV9xRAtAmkFEOE1AAHj58GKtWrfIkJa5Tx77SPFGuN2Uv3759u6ducJs2bUqTWKcsDN24CIiACIRAIEwBuB0ABZ91m5YRvywb1cYSBMIAEAaCsFUHwO1d3yAQRhAvMH14pnC6gkDKDJbqAtAp+YYCCkCaavPmzdi1a5dHBPKMYFpaqpsthJ84Nndh/WWeY6H4q1mzJho0YHYBNREQAREQgWAEwhSAzPl3pknfwjQwDPZ4GcB4AEz/wsY/x5hzfrkmDUxnP2lg6gG4wZIGhhHBSgNjIKa6knBKvqEKBSDFB4MOKALVEkuA4o9BORLhibWDZhcBEUgeAmEKwGpG0F0EgPU4mfLlTQAPAyi0aBcGkDBamImgvwEwykQNe8EwEfTffBJB36pE0PIAegk4Jd9QhQLQu1huBx86dCh5PvUuW2lWVpa2fV1mU92OCIhA7AmEKQBjvyDN4CEgD2Bi8g1VBsCXt3E/cQXTizRuzByVaiIgAiIgAiLgDgISgM60Y6oLwETlG2LeI+YiKtckAJ35IdGqREAEREAEIicgARg5u1hemeoCMFH5huQBjOVTrbFFQAREQAQcQ0AC0DGmKLeQVBeATsk3FNIZQGc+QlqVCIiACIiACAQmIAHozKcj1QWgU/INeQTg3LlzlV7EmZ8TrUoEREAERCBCAkxl1rNnT17NQ+4bIxxGl9lMINUFoFPyDXW3JKu02cQaTgREQAREQAQcQeBEAN87YiVaRMpHATsl3xCFOJNd5tv0TFZlVDEAls3ZZ9OYqTSM+EVnbfGLjh+vFsPoGIqf8/gxKfMPAI5EtzRdbReBVPcA2sXRaeOwLM5uADUA7HHa4pJgPeIXnZHELzp+vFoMo2MofuIXHYEUuFoC0J1G1g+/6OwqfuIXHYHor9YzGB1D8RO/6AikwNUSgO40sn74RWdX8RO/6AhEf7WewegYip/4RUcgBa6WAHSnkZln8B4AjwM46M5bjOldiV90eMUvOn68WgyjYyh+4hcdgRS4WgIwBYysWxQBERABERABERABKwEJQD0PIiACIiACIiACIpBiBCQAU8zgul0REAEREAEREAERkADUMyACIiACIiACIiACKUZAAtCdBr8JwJ0A6gNYCOAWAHPdeatR3dXphhOz0zcAcBGAKZYR+fl4CMBIADUBzAJwI4DVUc3qnosZaHSxSTi+H8BsAHcDWGm5xWwAzwAYbAIbPgEwysak58lMk88SX83NTSwF8DCAj82/xS506/JZfAzAXwDcJn4hgXsQwAM+PfnZZQEBNj1/IWFM3k4SgMlru0ArHwTgdQA3AJhjfhgOBNAWwFb33W5Ud3QOgNNMaaL3/AhAihl+sVwF4CcAjwDoBKADgANRzeyOi6cDeAvAPACZ5gv4BMPnV3OL/wDwe8OQycn/BqDYcHcHhcjv4jwAhwGsMUMMN7+QsCoQxaDYhcb2JADvmKT3X1gEoPhVzI8C8FIAZ1q6FQH4RZ/d0B68ZO8lAZjsFjx6/RR9/EK+2byVDiAPwAsAxrrvdm27I5YnsnoA+dnYZLxXT5tZWFmF5fooCCl81MoTqGt+yfgdgK9MJZptAIYCeNd0pXdhOYDfAPhOAI8isMOIQPISu+APCEu+sbYsvcp/AvCjEYD8rIpfcAF4IYCufrqJX/BnL+l7SAAmvQnL3UAlAAXmtzrrVuZrZgvzAnfdrq134ysAWwJYa2o080vF2740XzKjbZ3dHYO1Ntvj9JIuAXAGgM8B1AKwy3KL6wE8D+A5d9y2LXeRAYCeen5W6QHk8Q2xC46WvCia/wBgpkUA6tkLzo4eQB4VomeeOxrfmh2Pn/XZDQ7PDT0kAN1gxbJ7aAhgI4BTzYfZ+86TAOiVOdldt2vr3fgKQDLkmT8y3WyZiVtN7MutdrUyAvQ0TzW/aPzW/Dc9fxPM2T8rK55H5VYdt9hTvVEs84uX5632GW/pNPOn2FX8dPBc6f8B4BYwBYxVAOrZC/7J4hEYelB57o9noHkesBEAHuPg8QQ9f8EZJnUPCcCkNt9Riw8kAJ8C0AvAKe66XVvvJlQBOMmc2+KXj1oZAZ634hcKxd+GIAKQRxTo3RojgKDXvqkRzpcAuNb8ssZtOX9fwGJX8tA0ATAfQD8T6Mb/C0UAil/gDx0D3eidvx0Ag7r0/Ln8B5QEoLsMrC3gyO2pLeDI2TGwg8cLGFWdaxlG23DhM/3MHD14W1vAFcLj2bXJ5pcxb0duo/NzzCCjswGQpY4fhPcMUiCT2//0/IUHLhl7SwAmo9UqXjODQLjFxtQvbNya45kOfkkrCCQwu0BBIAwAYRoTNhaYZyS1gkBKePDnB4OLGDzT2096HO9B8iEAGGXN1sZsOSkIxP+zOMN8XnnGlEEMYuefUzUAzXzeosdqBYAnTOCb+IX3/cbtYH5X8Gwgz1aKX3j8kq63BGDSmSzogr1pYK4zQpA5sS4zuZ0YwapWRoA/8Bi4wPaD2frg2TQeKucPQp5R4zYl03PQs8U0MJ2VBqYU4IvmrBq9f9bcfzxUzi0kNm4NDzCieY8RjPx/nrFM9ca8dcz5xyh9ChqeW+MzR+8VPTBiF94TYt0C1rMXnB1/uf2v2fbl8SHmPOXRA6a5ovjT8xecYVL3kABMavMFXDxTwHgTQTOC9VaTE9Cddxv5XdFrRcHn2/jbL7183kTQFNM8H/ONSTexKvIpXXUlvab+2ggAr5o3vMlk6cmqDMCbCHqLq0hEdjP/AtDXHMCnaF5kvFcUf2xiFx5XXwEofhXzYyorHtuoYwQff74xqIbZD/T8hffsJWVvCcCkNJsWLQIiIAIiIAIiIAKRE5AAjJydrhQBERABERABERCBpCQgAZiUZtOiRUAEREAEREAERCByAhKAkbPTlSIgAiIgAiIgAiKQlAQkAJPSbFq0CIiACIiACIiACEROQAIwcna6UgREQAREQAREQASSkoAEYFKaTYsWAREQAREQAREQgcgJSABGzk5XioAIiIAIiIAIiEBSEpAATEqzadEiIAIiIAIiIAIiEDkBCcDI2elKERCB5CLgrfxSC8AuU+3leVPlJbnuRKsVAREQgSgJSABGCVCXi4AIOJaAb2mwSgBqA2BNbJaxY7k/qwB8EMCFph6qY29KCxMBERABOwhIANpBUWOIgAg4kYCvAPRdowSgE62mNYmACMSFgARgXDBrEhEQgTgTeBXAcJ85RwCYAMDfFjDFIN+zNvbnOGoiIAIi4DoCEoCuM6luSAREAEANAB8DWALgfkOkI4DPAgjAKgAeAdAfwJmm/24A+0VTBERABNxIQALQjVbVPYmACJCA7xZwsCAQnQHUcyMCIpAyBCQAU8bUulERSDkCEoApZ3LdsAiIQKgEJABDJaV+IiACyUZAAjDZLKb1ioAIxI2ABGDcUGsiERCBOBP4FMBKALeYeYNtAd8LYAiATnFep6YTAREQgbgTkACMO3JNKAIiECcCL5ucfpcB2AegM4DPAwSBcElDAfCa3wLYAGAvgINxWqumEQEREIG4EpAAjCtuTSYCIhBHAm0AvAagCwBG+VaUBobLqgzgDQB9TXUQpYGJo7E0lQiIQHwJSADGl7dmEwEREAEREAEREIGEE5AATLgJtAAREAEREAEREAERiC8BCcD48tZsIiACIiACIiACIpBwAhKACTeBFiACIiACIiACIiAC8SUgARhf3ppNBERABERABERABBJOQAIw4SbQAkRABERABERABEQgvgQkAOPLW7OJgAiIgAiIgAiIQMIJSAAm3ARagAiIgAiIgAiIgAjEl4AEYHx5azYREAEREAEREAERSDgBCcCEm0ALEAEREAEREAEREIH4EpAAjC9vzSYCIiACIiACIiACCScgAZhwE2gBIiACIiACIiACIhBfAhKA8eWt2URABERABERABEQg4QQkABNuAi1ABERABERABERABOJLQAIwvrw1mwiIgAiIgAiIgAgknIAEYMJNoAWIgAiIgAiIgAiIQHwJSADGl7dmEwEREAEREAEREIGEE5AATLgJtAAREAEREAEREAERiC+B/weOQNmhmkrH3QAAAABJRU5ErkJggg==\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"fig, ax1 = plt.subplots()\n",
			"ax2 = ax1.twinx()\n",
			"\n",
			"for dist in example.distance:\n",
			" example.Efficiency_yearly.sel( distance = dist ).plot(ax = ax1, label = 'DR = %d' %(dist), color = 'C%d' %(dist))\n",
			" example.tilted_irrad_yrly.sel( distance = dist ).plot(ax = ax2, label = 'DR = %d' %(dist), color = 'C%d' %(dist))\n",
			" # example.Efficiency_global_yearly.sel( distance = dist ).plot(label = 'DR = %d' %(dist), color = 'C%d' %(dist), linestyle = '--')\n",
			" \n",
			"plt.legend()\n",
			"plt.grid()\n",
			"ax1.set_title('')\n",
			"ax2.set_title('Yearly efficiency / tilted irradiance')\n",
			"\n",
			"plt.tight_layout()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 69,
			"metadata": {
			"scrolled": false
			},
			"outputs": [
			{
			"data": {
			"application/javascript": [
			"/* Put everything inside the global mpl namespace */\n",
			"window.mpl = {};\n",
			"\n",
			"\n",
			"mpl.get_websocket_type = function() {\n",
			" if (typeof(WebSocket) !== 'undefined') {\n",
			" return WebSocket;\n",
			" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
			" return MozWebSocket;\n",
			" } else {\n",
			" alert('Your browser does not have WebSocket support.' +\n",
			" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
			" 'Firefox 4 and 5 are also supported but you ' +\n",
			" 'have to enable WebSockets in about:config.');\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
			" this.id = figure_id;\n",
			"\n",
			" this.ws = websocket;\n",
			"\n",
			" this.supports_binary = (this.ws.binaryType != undefined);\n",
			"\n",
			" if (!this.supports_binary) {\n",
			" var warnings = document.getElementById(\"mpl-warnings\");\n",
			" if (warnings) {\n",
			" warnings.style.display = 'block';\n",
			" warnings.textContent = (\n",
			" \"This browser does not support binary websocket messages. \" +\n",
			" \"Performance may be slow.\");\n",
			" }\n",
			" }\n",
			"\n",
			" this.imageObj = new Image();\n",
			"\n",
			" this.context = undefined;\n",
			" this.message = undefined;\n",
			" this.canvas = undefined;\n",
			" this.rubberband_canvas = undefined;\n",
			" this.rubberband_context = undefined;\n",
			" this.format_dropdown = undefined;\n",
			"\n",
			" this.image_mode = 'full';\n",
			"\n",
			" this.root = $('<div/>');\n",
			" this._root_extra_style(this.root)\n",
			" this.root.attr('style', 'display: inline-block');\n",
			"\n",
			" $(parent_element).append(this.root);\n",
			"\n",
			" this._init_header(this);\n",
			" this._init_canvas(this);\n",
			" this._init_toolbar(this);\n",
			"\n",
			" var fig = this;\n",
			"\n",
			" this.waiting = false;\n",
			"\n",
			" this.ws.onopen = function () {\n",
			" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
			" fig.send_message(\"send_image_mode\", {});\n",
			" if (mpl.ratio != 1) {\n",
			" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
			" }\n",
			" fig.send_message(\"refresh\", {});\n",
			" }\n",
			"\n",
			" this.imageObj.onload = function() {\n",
			" if (fig.image_mode == 'full') {\n",
			" // Full images could contain transparency (where diff images\n",
			" // almost always do), so we need to clear the canvas so that\n",
			" // there is no ghosting.\n",
			" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
			" }\n",
			" fig.context.drawImage(fig.imageObj, 0, 0);\n",
			" };\n",
			"\n",
			" this.imageObj.onunload = function() {\n",
			" fig.ws.close();\n",
			" }\n",
			"\n",
			" this.ws.onmessage = this._make_on_message_function(this);\n",
			"\n",
			" this.ondownload = ondownload;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_header = function() {\n",
			" var titlebar = $(\n",
			" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
			" 'ui-helper-clearfix\"/>');\n",
			" var titletext = $(\n",
			" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
			" 'text-align: center; padding: 3px;\"/>');\n",
			" titlebar.append(titletext)\n",
			" this.root.append(titlebar);\n",
			" this.header = titletext[0];\n",
			"}\n",
			"\n",
			"\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_canvas = function() {\n",
			" var fig = this;\n",
			"\n",
			" var canvas_div = $('<div/>');\n",
			"\n",
			" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
			"\n",
			" function canvas_keyboard_event(event) {\n",
			" return fig.key_event(event, event['data']);\n",
			" }\n",
			"\n",
			" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
			" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
			" this.canvas_div = canvas_div\n",
			" this._canvas_extra_style(canvas_div)\n",
			" this.root.append(canvas_div);\n",
			"\n",
			" var canvas = $('<canvas/>');\n",
			" canvas.addClass('mpl-canvas');\n",
			" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
			"\n",
			" this.canvas = canvas[0];\n",
			" this.context = canvas[0].getContext(\"2d\");\n",
			"\n",
			" var backingStore = this.context.backingStorePixelRatio \|\|\n",
			"\tthis.context.webkitBackingStorePixelRatio \|\|\n",
			"\tthis.context.mozBackingStorePixelRatio \|\|\n",
			"\tthis.context.msBackingStorePixelRatio \|\|\n",
			"\tthis.context.oBackingStorePixelRatio \|\|\n",
			"\tthis.context.backingStorePixelRatio \|\| 1;\n",
			"\n",
			" mpl.ratio = (window.devicePixelRatio \|\| 1) / backingStore;\n",
			"\n",
			" var rubberband = $('<canvas/>');\n",
			" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
			"\n",
			" var pass_mouse_events = true;\n",
			"\n",
			" canvas_div.resizable({\n",
			" start: function(event, ui) {\n",
			" pass_mouse_events = false;\n",
			" },\n",
			" resize: function(event, ui) {\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" stop: function(event, ui) {\n",
			" pass_mouse_events = true;\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" });\n",
			"\n",
			" function mouse_event_fn(event) {\n",
			" if (pass_mouse_events)\n",
			" return fig.mouse_event(event, event['data']);\n",
			" }\n",
			"\n",
			" rubberband.mousedown('button_press', mouse_event_fn);\n",
			" rubberband.mouseup('button_release', mouse_event_fn);\n",
			" // Throttle sequential mouse events to 1 every 20ms.\n",
			" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
			"\n",
			" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
			" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
			"\n",
			" canvas_div.on(\"wheel\", function (event) {\n",
			" event = event.originalEvent;\n",
			" event['data'] = 'scroll'\n",
			" if (event.deltaY < 0) {\n",
			" event.step = 1;\n",
			" } else {\n",
			" event.step = -1;\n",
			" }\n",
			" mouse_event_fn(event);\n",
			" });\n",
			"\n",
			" canvas_div.append(canvas);\n",
			" canvas_div.append(rubberband);\n",
			"\n",
			" this.rubberband = rubberband;\n",
			" this.rubberband_canvas = rubberband[0];\n",
			" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
			" this.rubberband_context.strokeStyle = \"#000000\";\n",
			"\n",
			" this._resize_canvas = function(width, height) {\n",
			" // Keep the size of the canvas, canvas container, and rubber band\n",
			" // canvas in synch.\n",
			" canvas_div.css('width', width)\n",
			" canvas_div.css('height', height)\n",
			"\n",
			" canvas.attr('width', width * mpl.ratio);\n",
			" canvas.attr('height', height * mpl.ratio);\n",
			" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
			"\n",
			" rubberband.attr('width', width);\n",
			" rubberband.attr('height', height);\n",
			" }\n",
			"\n",
			" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
			" // upon first draw.\n",
			" this._resize_canvas(600, 600);\n",
			"\n",
			" // Disable right mouse context menu.\n",
			" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
			" return false;\n",
			" });\n",
			"\n",
			" function set_focus () {\n",
			" canvas.focus();\n",
			" canvas_div.focus();\n",
			" }\n",
			"\n",
			" window.setTimeout(set_focus, 100);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items) {\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) {\n",
			" // put a spacer in here.\n",
			" continue;\n",
			" }\n",
			" var button = $('<button/>');\n",
			" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
			" 'ui-button-icon-only');\n",
			" button.attr('role', 'button');\n",
			" button.attr('aria-disabled', 'false');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			"\n",
			" var icon_img = $('<span/>');\n",
			" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
			" icon_img.addClass(image);\n",
			" icon_img.addClass('ui-corner-all');\n",
			"\n",
			" var tooltip_span = $('<span/>');\n",
			" tooltip_span.addClass('ui-button-text');\n",
			" tooltip_span.html(tooltip);\n",
			"\n",
			" button.append(icon_img);\n",
			" button.append(tooltip_span);\n",
			"\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" var fmt_picker_span = $('<span/>');\n",
			"\n",
			" var fmt_picker = $('<select/>');\n",
			" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
			" fmt_picker_span.append(fmt_picker);\n",
			" nav_element.append(fmt_picker_span);\n",
			" this.format_dropdown = fmt_picker[0];\n",
			"\n",
			" for (var ind in mpl.extensions) {\n",
			" var fmt = mpl.extensions[ind];\n",
			" var option = $(\n",
			" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
			" fmt_picker.append(option)\n",
			" }\n",
			"\n",
			" // Add hover states to the ui-buttons\n",
			" $( \".ui-button\" ).hover(\n",
			" function() { $(this).addClass(\"ui-state-hover\");},\n",
			" function() { $(this).removeClass(\"ui-state-hover\");}\n",
			" );\n",
			"\n",
			" var status_bar = $('<span class=\"mpl-message\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
			" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
			" // which will in turn request a refresh of the image.\n",
			" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_message = function(type, properties) {\n",
			" properties['type'] = type;\n",
			" properties['figure_id'] = this.id;\n",
			" this.ws.send(JSON.stringify(properties));\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_draw_message = function() {\n",
			" if (!this.waiting) {\n",
			" this.waiting = true;\n",
			" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
			" }\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" var format_dropdown = fig.format_dropdown;\n",
			" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
			" fig.ondownload(fig, format);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
			" var size = msg['size'];\n",
			" if (size[0] != fig.canvas.width \|\| size[1] != fig.canvas.height) {\n",
			" fig._resize_canvas(size[0], size[1]);\n",
			" fig.send_message(\"refresh\", {});\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
			" var x0 = msg['x0'] / mpl.ratio;\n",
			" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
			" var x1 = msg['x1'] / mpl.ratio;\n",
			" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
			" x0 = Math.floor(x0) + 0.5;\n",
			" y0 = Math.floor(y0) + 0.5;\n",
			" x1 = Math.floor(x1) + 0.5;\n",
			" y1 = Math.floor(y1) + 0.5;\n",
			" var min_x = Math.min(x0, x1);\n",
			" var min_y = Math.min(y0, y1);\n",
			" var width = Math.abs(x1 - x0);\n",
			" var height = Math.abs(y1 - y0);\n",
			"\n",
			" fig.rubberband_context.clearRect(\n",
			" 0, 0, fig.canvas.width, fig.canvas.height);\n",
			"\n",
			" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
			" // Updates the figure title.\n",
			" fig.header.textContent = msg['label'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
			" var cursor = msg['cursor'];\n",
			" switch(cursor)\n",
			" {\n",
			" case 0:\n",
			" cursor = 'pointer';\n",
			" break;\n",
			" case 1:\n",
			" cursor = 'default';\n",
			" break;\n",
			" case 2:\n",
			" cursor = 'crosshair';\n",
			" break;\n",
			" case 3:\n",
			" cursor = 'move';\n",
			" break;\n",
			" }\n",
			" fig.rubberband_canvas.style.cursor = cursor;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
			" fig.message.textContent = msg['message'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
			" // Request the server to send over a new figure.\n",
			" fig.send_draw_message();\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
			" fig.image_mode = msg['mode'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Called whenever the canvas gets updated.\n",
			" this.send_message(\"ack\", {});\n",
			"}\n",
			"\n",
			"// A function to construct a web socket function for onmessage handling.\n",
			"// Called in the figure constructor.\n",
			"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
			" return function socket_on_message(evt) {\n",
			" if (evt.data instanceof Blob) {\n",
			" /* FIXME: We get \"Resource interpreted as Image but\n",
			" * transferred with MIME type text/plain:\" errors on\n",
			" * Chrome. But how to set the MIME type? It doesn't seem\n",
			" * to be part of the websocket stream */\n",
			" evt.data.type = \"image/png\";\n",
			"\n",
			" /* Free the memory for the previous frames */\n",
			" if (fig.imageObj.src) {\n",
			" (window.URL \|\| window.webkitURL).revokeObjectURL(\n",
			" fig.imageObj.src);\n",
			" }\n",
			"\n",
			" fig.imageObj.src = (window.URL \|\| window.webkitURL).createObjectURL(\n",
			" evt.data);\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
			" fig.imageObj.src = evt.data;\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			"\n",
			" var msg = JSON.parse(evt.data);\n",
			" var msg_type = msg['type'];\n",
			"\n",
			" // Call the \"handle_{type}\" callback, which takes\n",
			" // the figure and JSON message as its only arguments.\n",
			" try {\n",
			" var callback = fig[\"handle_\" + msg_type];\n",
			" } catch (e) {\n",
			" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
			" return;\n",
			" }\n",
			"\n",
			" if (callback) {\n",
			" try {\n",
			" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
			" callback(fig, msg);\n",
			" } catch (e) {\n",
			" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
			" }\n",
			" }\n",
			" };\n",
			"}\n",
			"\n",
			"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
			"mpl.findpos = function(e) {\n",
			" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
			" var targ;\n",
			" if (!e)\n",
			" e = window.event;\n",
			" if (e.target)\n",
			" targ = e.target;\n",
			" else if (e.srcElement)\n",
			" targ = e.srcElement;\n",
			" if (targ.nodeType == 3) // defeat Safari bug\n",
			" targ = targ.parentNode;\n",
			"\n",
			" // jQuery normalizes the pageX and pageY\n",
			" // pageX,Y are the mouse positions relative to the document\n",
			" // offset() returns the position of the element relative to the document\n",
			" var x = e.pageX - $(targ).offset().left;\n",
			" var y = e.pageY - $(targ).offset().top;\n",
			"\n",
			" return {\"x\": x, \"y\": y};\n",
			"};\n",
			"\n",
			"/*\n",
			" * return a copy of an object with only non-object keys\n",
			" * we need this to avoid circular references\n",
			" * http://stackoverflow.com/a/24161582/3208463\n",
			" */\n",
			"function simpleKeys (original) {\n",
			" return Object.keys(original).reduce(function (obj, key) {\n",
			" if (typeof original[key] !== 'object')\n",
			" obj[key] = original[key]\n",
			" return obj;\n",
			" }, {});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.mouse_event = function(event, name) {\n",
			" var canvas_pos = mpl.findpos(event)\n",
			"\n",
			" if (name === 'button_press')\n",
			" {\n",
			" this.canvas.focus();\n",
			" this.canvas_div.focus();\n",
			" }\n",
			"\n",
			" var x = canvas_pos.x * mpl.ratio;\n",
			" var y = canvas_pos.y * mpl.ratio;\n",
			"\n",
			" this.send_message(name, {x: x, y: y, button: event.button,\n",
			" step: event.step,\n",
			" guiEvent: simpleKeys(event)});\n",
			"\n",
			" /* This prevents the web browser from automatically changing to\n",
			" * the text insertion cursor when the button is pressed. We want\n",
			" * to control all of the cursor setting manually through the\n",
			" * 'cursor' event from matplotlib */\n",
			" event.preventDefault();\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" // Handle any extra behaviour associated with a key event\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.key_event = function(event, name) {\n",
			"\n",
			" // Prevent repeat events\n",
			" if (name == 'key_press')\n",
			" {\n",
			" if (event.which === this._key)\n",
			" return;\n",
			" else\n",
			" this._key = event.which;\n",
			" }\n",
			" if (name == 'key_release')\n",
			" this._key = null;\n",
			"\n",
			" var value = '';\n",
			" if (event.ctrlKey && event.which != 17)\n",
			" value += \"ctrl+\";\n",
			" if (event.altKey && event.which != 18)\n",
			" value += \"alt+\";\n",
			" if (event.shiftKey && event.which != 16)\n",
			" value += \"shift+\";\n",
			"\n",
			" value += 'k';\n",
			" value += event.which.toString();\n",
			"\n",
			" this._key_event_extra(event, name);\n",
			"\n",
			" this.send_message(name, {key: value,\n",
			" guiEvent: simpleKeys(event)});\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
			" if (name == 'download') {\n",
			" this.handle_save(this, null);\n",
			" } else {\n",
			" this.send_message(\"toolbar_button\", {name: name});\n",
			" }\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
			" this.message.textContent = tooltip;\n",
			"};\n",
			"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
			"\n",
			"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
			"\n",
			"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
			" // Create a \"websocket\"-like object which calls the given IPython comm\n",
			" // object with the appropriate methods. Currently this is a non binary\n",
			" // socket, so there is still some room for performance tuning.\n",
			" var ws = {};\n",
			"\n",
			" ws.close = function() {\n",
			" comm.close()\n",
			" };\n",
			" ws.send = function(m) {\n",
			" //console.log('sending', m);\n",
			" comm.send(m);\n",
			" };\n",
			" // Register the callback with on_msg.\n",
			" comm.on_msg(function(msg) {\n",
			" //console.log('receiving', msg['content']['data'], msg);\n",
			" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
			" ws.onmessage(msg['content']['data'])\n",
			" });\n",
			" return ws;\n",
			"}\n",
			"\n",
			"mpl.mpl_figure_comm = function(comm, msg) {\n",
			" // This is the function which gets called when the mpl process\n",
			" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
			"\n",
			" var id = msg.content.data.id;\n",
			" // Get hold of the div created by the display call when the Comm\n",
			" // socket was opened in Python.\n",
			" var element = $(\"#\" + id);\n",
			" var ws_proxy = comm_websocket_adapter(comm)\n",
			"\n",
			" function ondownload(figure, format) {\n",
			" window.open(figure.imageObj.src);\n",
			" }\n",
			"\n",
			" var fig = new mpl.figure(id, ws_proxy,\n",
			" ondownload,\n",
			" element.get(0));\n",
			"\n",
			" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
			" // web socket which is closed, not our websocket->open comm proxy.\n",
			" ws_proxy.onopen();\n",
			"\n",
			" fig.parent_element = element.get(0);\n",
			" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
			" if (!fig.cell_info) {\n",
			" console.error(\"Failed to find cell for figure\", id, fig);\n",
			" return;\n",
			" }\n",
			"\n",
			" var output_index = fig.cell_info[2]\n",
			" var cell = fig.cell_info[0];\n",
			"\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
			" var width = fig.canvas.width/mpl.ratio\n",
			" fig.root.unbind('remove')\n",
			"\n",
			" // Update the output cell to use the data from the current canvas.\n",
			" fig.push_to_output();\n",
			" var dataURL = fig.canvas.toDataURL();\n",
			" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
			" // the notebook keyboard shortcuts fail.\n",
			" IPython.keyboard_manager.enable()\n",
			" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
			" fig.close_ws(fig, msg);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.close_ws = function(fig, msg){\n",
			" fig.send_message('closing', msg);\n",
			" // fig.ws.close()\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
			" // Turn the data on the canvas into data in the output cell.\n",
			" var width = this.canvas.width/mpl.ratio\n",
			" var dataURL = this.canvas.toDataURL();\n",
			" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Tell IPython that the notebook contents must change.\n",
			" IPython.notebook.set_dirty(true);\n",
			" this.send_message(\"ack\", {});\n",
			" var fig = this;\n",
			" // Wait a second, then push the new image to the DOM so\n",
			" // that it is saved nicely (might be nice to debounce this).\n",
			" setTimeout(function () { fig.push_to_output() }, 1000);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items){\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) { continue; };\n",
			"\n",
			" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" // Add the status bar.\n",
			" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"\n",
			" // Add the close button to the window.\n",
			" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
			" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
			" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
			" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
			" buttongrp.append(button);\n",
			" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
			" titlebar.prepend(buttongrp);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(el){\n",
			" var fig = this\n",
			" el.on(\"remove\", function(){\n",
			"\tfig.close_ws(fig, {});\n",
			" });\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(el){\n",
			" // this is important to make the div 'focusable\n",
			" el.attr('tabindex', 0)\n",
			" // reach out to IPython and tell the keyboard manager to turn it's self\n",
			" // off when our div gets focus\n",
			"\n",
			" // location in version 3\n",
			" if (IPython.notebook.keyboard_manager) {\n",
			" IPython.notebook.keyboard_manager.register_events(el);\n",
			" }\n",
			" else {\n",
			" // location in version 2\n",
			" IPython.keyboard_manager.register_events(el);\n",
			" }\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" var manager = IPython.notebook.keyboard_manager;\n",
			" if (!manager)\n",
			" manager = IPython.keyboard_manager;\n",
			"\n",
			" // Check for shift+enter\n",
			" if (event.shiftKey && event.which == 13) {\n",
			" this.canvas_div.blur();\n",
			" event.shiftKey = false;\n",
			" // Send a \"J\" for go to next cell\n",
			" event.which = 74;\n",
			" event.keyCode = 74;\n",
			" manager.command_mode();\n",
			" manager.handle_keydown(event);\n",
			" }\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" fig.ondownload(fig, null);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.find_output_cell = function(html_output) {\n",
			" // Return the cell and output element which can be found uniquely in the notebook.\n",
			" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
			" // IPython event is triggered only after the cells have been serialised, which for\n",
			" // our purposes (turning an active figure into a static one), is too late.\n",
			" var cells = IPython.notebook.get_cells();\n",
			" var ncells = cells.length;\n",
			" for (var i=0; i<ncells; i++) {\n",
			" var cell = cells[i];\n",
			" if (cell.cell_type === 'code'){\n",
			" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
			" var data = cell.output_area.outputs[j];\n",
			" if (data.data) {\n",
			" // IPython >= 3 moved mimebundle to data attribute of output\n",
			" data = data.data;\n",
			" }\n",
			" if (data['text/html'] == html_output) {\n",
			" return [cell, data, j];\n",
			" }\n",
			" }\n",
			" }\n",
			" }\n",
			"}\n",
			"\n",
			"// Register the function which deals with the matplotlib target/channel.\n",
			"// The kernel may be null if the page has been refreshed.\n",
			"if (IPython.notebook.kernel != null) {\n",
			" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
			"}\n"
			],
			"text/plain": [
			"<IPython.core.display.Javascript object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/html": [
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\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/plain": [
			"Text(0.5,1,'Plane-of-array irradiance')"
			]
			},
			"execution_count": 69,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"plot_ds = example.copy()\n",
			"plot_ds = plot_ds.assign_coords( timestamp = range(len(example.timestamp)))\n",
			"\n",
			"plt.figure()\n",
			"d = 0\n",
			"for tilt in [0, 30, 50]:\n",
			" plot_ds.tilted_irrad.sel( distance = 2, tilt = tilt ).plot(label = r'$\\alpha = %d$' %(tilt), color = 'C%d' %(d))\n",
			" plot_ds.tilted_irrad.sel( distance = 2, tilt = tilt ).plot(label = r'$\\alpha = %d$' %(tilt), color = 'C%d' %(d), linestyle = '--')\n",
			" d += 1\n",
			"\n",
			"plot_ds.SIS.plot(label = 'GHI', color = 'C3', ls = '--')\n",
			" \n",
			"plt.legend()\n",
			"plt.grid()\n",
			"plt.title('Plane-of-array irradiance')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 50,
			"metadata": {
			"scrolled": false
			},
			"outputs": [
			{
			"data": {
			"application/javascript": [
			"/* Put everything inside the global mpl namespace */\n",
			"window.mpl = {};\n",
			"\n",
			"\n",
			"mpl.get_websocket_type = function() {\n",
			" if (typeof(WebSocket) !== 'undefined') {\n",
			" return WebSocket;\n",
			" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
			" return MozWebSocket;\n",
			" } else {\n",
			" alert('Your browser does not have WebSocket support.' +\n",
			" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
			" 'Firefox 4 and 5 are also supported but you ' +\n",
			" 'have to enable WebSockets in about:config.');\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
			" this.id = figure_id;\n",
			"\n",
			" this.ws = websocket;\n",
			"\n",
			" this.supports_binary = (this.ws.binaryType != undefined);\n",
			"\n",
			" if (!this.supports_binary) {\n",
			" var warnings = document.getElementById(\"mpl-warnings\");\n",
			" if (warnings) {\n",
			" warnings.style.display = 'block';\n",
			" warnings.textContent = (\n",
			" \"This browser does not support binary websocket messages. \" +\n",
			" \"Performance may be slow.\");\n",
			" }\n",
			" }\n",
			"\n",
			" this.imageObj = new Image();\n",
			"\n",
			" this.context = undefined;\n",
			" this.message = undefined;\n",
			" this.canvas = undefined;\n",
			" this.rubberband_canvas = undefined;\n",
			" this.rubberband_context = undefined;\n",
			" this.format_dropdown = undefined;\n",
			"\n",
			" this.image_mode = 'full';\n",
			"\n",
			" this.root = $('<div/>');\n",
			" this._root_extra_style(this.root)\n",
			" this.root.attr('style', 'display: inline-block');\n",
			"\n",
			" $(parent_element).append(this.root);\n",
			"\n",
			" this._init_header(this);\n",
			" this._init_canvas(this);\n",
			" this._init_toolbar(this);\n",
			"\n",
			" var fig = this;\n",
			"\n",
			" this.waiting = false;\n",
			"\n",
			" this.ws.onopen = function () {\n",
			" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
			" fig.send_message(\"send_image_mode\", {});\n",
			" if (mpl.ratio != 1) {\n",
			" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
			" }\n",
			" fig.send_message(\"refresh\", {});\n",
			" }\n",
			"\n",
			" this.imageObj.onload = function() {\n",
			" if (fig.image_mode == 'full') {\n",
			" // Full images could contain transparency (where diff images\n",
			" // almost always do), so we need to clear the canvas so that\n",
			" // there is no ghosting.\n",
			" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
			" }\n",
			" fig.context.drawImage(fig.imageObj, 0, 0);\n",
			" };\n",
			"\n",
			" this.imageObj.onunload = function() {\n",
			" fig.ws.close();\n",
			" }\n",
			"\n",
			" this.ws.onmessage = this._make_on_message_function(this);\n",
			"\n",
			" this.ondownload = ondownload;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_header = function() {\n",
			" var titlebar = $(\n",
			" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
			" 'ui-helper-clearfix\"/>');\n",
			" var titletext = $(\n",
			" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
			" 'text-align: center; padding: 3px;\"/>');\n",
			" titlebar.append(titletext)\n",
			" this.root.append(titlebar);\n",
			" this.header = titletext[0];\n",
			"}\n",
			"\n",
			"\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_canvas = function() {\n",
			" var fig = this;\n",
			"\n",
			" var canvas_div = $('<div/>');\n",
			"\n",
			" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
			"\n",
			" function canvas_keyboard_event(event) {\n",
			" return fig.key_event(event, event['data']);\n",
			" }\n",
			"\n",
			" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
			" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
			" this.canvas_div = canvas_div\n",
			" this._canvas_extra_style(canvas_div)\n",
			" this.root.append(canvas_div);\n",
			"\n",
			" var canvas = $('<canvas/>');\n",
			" canvas.addClass('mpl-canvas');\n",
			" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
			"\n",
			" this.canvas = canvas[0];\n",
			" this.context = canvas[0].getContext(\"2d\");\n",
			"\n",
			" var backingStore = this.context.backingStorePixelRatio \|\|\n",
			"\tthis.context.webkitBackingStorePixelRatio \|\|\n",
			"\tthis.context.mozBackingStorePixelRatio \|\|\n",
			"\tthis.context.msBackingStorePixelRatio \|\|\n",
			"\tthis.context.oBackingStorePixelRatio \|\|\n",
			"\tthis.context.backingStorePixelRatio \|\| 1;\n",
			"\n",
			" mpl.ratio = (window.devicePixelRatio \|\| 1) / backingStore;\n",
			"\n",
			" var rubberband = $('<canvas/>');\n",
			" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
			"\n",
			" var pass_mouse_events = true;\n",
			"\n",
			" canvas_div.resizable({\n",
			" start: function(event, ui) {\n",
			" pass_mouse_events = false;\n",
			" },\n",
			" resize: function(event, ui) {\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" stop: function(event, ui) {\n",
			" pass_mouse_events = true;\n",
			" fig.request_resize(ui.size.width, ui.size.height);\n",
			" },\n",
			" });\n",
			"\n",
			" function mouse_event_fn(event) {\n",
			" if (pass_mouse_events)\n",
			" return fig.mouse_event(event, event['data']);\n",
			" }\n",
			"\n",
			" rubberband.mousedown('button_press', mouse_event_fn);\n",
			" rubberband.mouseup('button_release', mouse_event_fn);\n",
			" // Throttle sequential mouse events to 1 every 20ms.\n",
			" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
			"\n",
			" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
			" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
			"\n",
			" canvas_div.on(\"wheel\", function (event) {\n",
			" event = event.originalEvent;\n",
			" event['data'] = 'scroll'\n",
			" if (event.deltaY < 0) {\n",
			" event.step = 1;\n",
			" } else {\n",
			" event.step = -1;\n",
			" }\n",
			" mouse_event_fn(event);\n",
			" });\n",
			"\n",
			" canvas_div.append(canvas);\n",
			" canvas_div.append(rubberband);\n",
			"\n",
			" this.rubberband = rubberband;\n",
			" this.rubberband_canvas = rubberband[0];\n",
			" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
			" this.rubberband_context.strokeStyle = \"#000000\";\n",
			"\n",
			" this._resize_canvas = function(width, height) {\n",
			" // Keep the size of the canvas, canvas container, and rubber band\n",
			" // canvas in synch.\n",
			" canvas_div.css('width', width)\n",
			" canvas_div.css('height', height)\n",
			"\n",
			" canvas.attr('width', width * mpl.ratio);\n",
			" canvas.attr('height', height * mpl.ratio);\n",
			" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
			"\n",
			" rubberband.attr('width', width);\n",
			" rubberband.attr('height', height);\n",
			" }\n",
			"\n",
			" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
			" // upon first draw.\n",
			" this._resize_canvas(600, 600);\n",
			"\n",
			" // Disable right mouse context menu.\n",
			" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
			" return false;\n",
			" });\n",
			"\n",
			" function set_focus () {\n",
			" canvas.focus();\n",
			" canvas_div.focus();\n",
			" }\n",
			"\n",
			" window.setTimeout(set_focus, 100);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items) {\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) {\n",
			" // put a spacer in here.\n",
			" continue;\n",
			" }\n",
			" var button = $('<button/>');\n",
			" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
			" 'ui-button-icon-only');\n",
			" button.attr('role', 'button');\n",
			" button.attr('aria-disabled', 'false');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			"\n",
			" var icon_img = $('<span/>');\n",
			" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
			" icon_img.addClass(image);\n",
			" icon_img.addClass('ui-corner-all');\n",
			"\n",
			" var tooltip_span = $('<span/>');\n",
			" tooltip_span.addClass('ui-button-text');\n",
			" tooltip_span.html(tooltip);\n",
			"\n",
			" button.append(icon_img);\n",
			" button.append(tooltip_span);\n",
			"\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" var fmt_picker_span = $('<span/>');\n",
			"\n",
			" var fmt_picker = $('<select/>');\n",
			" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
			" fmt_picker_span.append(fmt_picker);\n",
			" nav_element.append(fmt_picker_span);\n",
			" this.format_dropdown = fmt_picker[0];\n",
			"\n",
			" for (var ind in mpl.extensions) {\n",
			" var fmt = mpl.extensions[ind];\n",
			" var option = $(\n",
			" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
			" fmt_picker.append(option)\n",
			" }\n",
			"\n",
			" // Add hover states to the ui-buttons\n",
			" $( \".ui-button\" ).hover(\n",
			" function() { $(this).addClass(\"ui-state-hover\");},\n",
			" function() { $(this).removeClass(\"ui-state-hover\");}\n",
			" );\n",
			"\n",
			" var status_bar = $('<span class=\"mpl-message\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
			" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
			" // which will in turn request a refresh of the image.\n",
			" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_message = function(type, properties) {\n",
			" properties['type'] = type;\n",
			" properties['figure_id'] = this.id;\n",
			" this.ws.send(JSON.stringify(properties));\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.send_draw_message = function() {\n",
			" if (!this.waiting) {\n",
			" this.waiting = true;\n",
			" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
			" }\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" var format_dropdown = fig.format_dropdown;\n",
			" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
			" fig.ondownload(fig, format);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
			" var size = msg['size'];\n",
			" if (size[0] != fig.canvas.width \|\| size[1] != fig.canvas.height) {\n",
			" fig._resize_canvas(size[0], size[1]);\n",
			" fig.send_message(\"refresh\", {});\n",
			" };\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
			" var x0 = msg['x0'] / mpl.ratio;\n",
			" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
			" var x1 = msg['x1'] / mpl.ratio;\n",
			" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
			" x0 = Math.floor(x0) + 0.5;\n",
			" y0 = Math.floor(y0) + 0.5;\n",
			" x1 = Math.floor(x1) + 0.5;\n",
			" y1 = Math.floor(y1) + 0.5;\n",
			" var min_x = Math.min(x0, x1);\n",
			" var min_y = Math.min(y0, y1);\n",
			" var width = Math.abs(x1 - x0);\n",
			" var height = Math.abs(y1 - y0);\n",
			"\n",
			" fig.rubberband_context.clearRect(\n",
			" 0, 0, fig.canvas.width, fig.canvas.height);\n",
			"\n",
			" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
			" // Updates the figure title.\n",
			" fig.header.textContent = msg['label'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
			" var cursor = msg['cursor'];\n",
			" switch(cursor)\n",
			" {\n",
			" case 0:\n",
			" cursor = 'pointer';\n",
			" break;\n",
			" case 1:\n",
			" cursor = 'default';\n",
			" break;\n",
			" case 2:\n",
			" cursor = 'crosshair';\n",
			" break;\n",
			" case 3:\n",
			" cursor = 'move';\n",
			" break;\n",
			" }\n",
			" fig.rubberband_canvas.style.cursor = cursor;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
			" fig.message.textContent = msg['message'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
			" // Request the server to send over a new figure.\n",
			" fig.send_draw_message();\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
			" fig.image_mode = msg['mode'];\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Called whenever the canvas gets updated.\n",
			" this.send_message(\"ack\", {});\n",
			"}\n",
			"\n",
			"// A function to construct a web socket function for onmessage handling.\n",
			"// Called in the figure constructor.\n",
			"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
			" return function socket_on_message(evt) {\n",
			" if (evt.data instanceof Blob) {\n",
			" /* FIXME: We get \"Resource interpreted as Image but\n",
			" * transferred with MIME type text/plain:\" errors on\n",
			" * Chrome. But how to set the MIME type? It doesn't seem\n",
			" * to be part of the websocket stream */\n",
			" evt.data.type = \"image/png\";\n",
			"\n",
			" /* Free the memory for the previous frames */\n",
			" if (fig.imageObj.src) {\n",
			" (window.URL \|\| window.webkitURL).revokeObjectURL(\n",
			" fig.imageObj.src);\n",
			" }\n",
			"\n",
			" fig.imageObj.src = (window.URL \|\| window.webkitURL).createObjectURL(\n",
			" evt.data);\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
			" fig.imageObj.src = evt.data;\n",
			" fig.updated_canvas_event();\n",
			" fig.waiting = false;\n",
			" return;\n",
			" }\n",
			"\n",
			" var msg = JSON.parse(evt.data);\n",
			" var msg_type = msg['type'];\n",
			"\n",
			" // Call the \"handle_{type}\" callback, which takes\n",
			" // the figure and JSON message as its only arguments.\n",
			" try {\n",
			" var callback = fig[\"handle_\" + msg_type];\n",
			" } catch (e) {\n",
			" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
			" return;\n",
			" }\n",
			"\n",
			" if (callback) {\n",
			" try {\n",
			" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
			" callback(fig, msg);\n",
			" } catch (e) {\n",
			" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
			" }\n",
			" }\n",
			" };\n",
			"}\n",
			"\n",
			"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
			"mpl.findpos = function(e) {\n",
			" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
			" var targ;\n",
			" if (!e)\n",
			" e = window.event;\n",
			" if (e.target)\n",
			" targ = e.target;\n",
			" else if (e.srcElement)\n",
			" targ = e.srcElement;\n",
			" if (targ.nodeType == 3) // defeat Safari bug\n",
			" targ = targ.parentNode;\n",
			"\n",
			" // jQuery normalizes the pageX and pageY\n",
			" // pageX,Y are the mouse positions relative to the document\n",
			" // offset() returns the position of the element relative to the document\n",
			" var x = e.pageX - $(targ).offset().left;\n",
			" var y = e.pageY - $(targ).offset().top;\n",
			"\n",
			" return {\"x\": x, \"y\": y};\n",
			"};\n",
			"\n",
			"/*\n",
			" * return a copy of an object with only non-object keys\n",
			" * we need this to avoid circular references\n",
			" * http://stackoverflow.com/a/24161582/3208463\n",
			" */\n",
			"function simpleKeys (original) {\n",
			" return Object.keys(original).reduce(function (obj, key) {\n",
			" if (typeof original[key] !== 'object')\n",
			" obj[key] = original[key]\n",
			" return obj;\n",
			" }, {});\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.mouse_event = function(event, name) {\n",
			" var canvas_pos = mpl.findpos(event)\n",
			"\n",
			" if (name === 'button_press')\n",
			" {\n",
			" this.canvas.focus();\n",
			" this.canvas_div.focus();\n",
			" }\n",
			"\n",
			" var x = canvas_pos.x * mpl.ratio;\n",
			" var y = canvas_pos.y * mpl.ratio;\n",
			"\n",
			" this.send_message(name, {x: x, y: y, button: event.button,\n",
			" step: event.step,\n",
			" guiEvent: simpleKeys(event)});\n",
			"\n",
			" /* This prevents the web browser from automatically changing to\n",
			" * the text insertion cursor when the button is pressed. We want\n",
			" * to control all of the cursor setting manually through the\n",
			" * 'cursor' event from matplotlib */\n",
			" event.preventDefault();\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" // Handle any extra behaviour associated with a key event\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.key_event = function(event, name) {\n",
			"\n",
			" // Prevent repeat events\n",
			" if (name == 'key_press')\n",
			" {\n",
			" if (event.which === this._key)\n",
			" return;\n",
			" else\n",
			" this._key = event.which;\n",
			" }\n",
			" if (name == 'key_release')\n",
			" this._key = null;\n",
			"\n",
			" var value = '';\n",
			" if (event.ctrlKey && event.which != 17)\n",
			" value += \"ctrl+\";\n",
			" if (event.altKey && event.which != 18)\n",
			" value += \"alt+\";\n",
			" if (event.shiftKey && event.which != 16)\n",
			" value += \"shift+\";\n",
			"\n",
			" value += 'k';\n",
			" value += event.which.toString();\n",
			"\n",
			" this._key_event_extra(event, name);\n",
			"\n",
			" this.send_message(name, {key: value,\n",
			" guiEvent: simpleKeys(event)});\n",
			" return false;\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
			" if (name == 'download') {\n",
			" this.handle_save(this, null);\n",
			" } else {\n",
			" this.send_message(\"toolbar_button\", {name: name});\n",
			" }\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
			" this.message.textContent = tooltip;\n",
			"};\n",
			"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
			"\n",
			"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
			"\n",
			"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
			" // Create a \"websocket\"-like object which calls the given IPython comm\n",
			" // object with the appropriate methods. Currently this is a non binary\n",
			" // socket, so there is still some room for performance tuning.\n",
			" var ws = {};\n",
			"\n",
			" ws.close = function() {\n",
			" comm.close()\n",
			" };\n",
			" ws.send = function(m) {\n",
			" //console.log('sending', m);\n",
			" comm.send(m);\n",
			" };\n",
			" // Register the callback with on_msg.\n",
			" comm.on_msg(function(msg) {\n",
			" //console.log('receiving', msg['content']['data'], msg);\n",
			" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
			" ws.onmessage(msg['content']['data'])\n",
			" });\n",
			" return ws;\n",
			"}\n",
			"\n",
			"mpl.mpl_figure_comm = function(comm, msg) {\n",
			" // This is the function which gets called when the mpl process\n",
			" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
			"\n",
			" var id = msg.content.data.id;\n",
			" // Get hold of the div created by the display call when the Comm\n",
			" // socket was opened in Python.\n",
			" var element = $(\"#\" + id);\n",
			" var ws_proxy = comm_websocket_adapter(comm)\n",
			"\n",
			" function ondownload(figure, format) {\n",
			" window.open(figure.imageObj.src);\n",
			" }\n",
			"\n",
			" var fig = new mpl.figure(id, ws_proxy,\n",
			" ondownload,\n",
			" element.get(0));\n",
			"\n",
			" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
			" // web socket which is closed, not our websocket->open comm proxy.\n",
			" ws_proxy.onopen();\n",
			"\n",
			" fig.parent_element = element.get(0);\n",
			" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
			" if (!fig.cell_info) {\n",
			" console.error(\"Failed to find cell for figure\", id, fig);\n",
			" return;\n",
			" }\n",
			"\n",
			" var output_index = fig.cell_info[2]\n",
			" var cell = fig.cell_info[0];\n",
			"\n",
			"};\n",
			"\n",
			"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
			" var width = fig.canvas.width/mpl.ratio\n",
			" fig.root.unbind('remove')\n",
			"\n",
			" // Update the output cell to use the data from the current canvas.\n",
			" fig.push_to_output();\n",
			" var dataURL = fig.canvas.toDataURL();\n",
			" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
			" // the notebook keyboard shortcuts fail.\n",
			" IPython.keyboard_manager.enable()\n",
			" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
			" fig.close_ws(fig, msg);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.close_ws = function(fig, msg){\n",
			" fig.send_message('closing', msg);\n",
			" // fig.ws.close()\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
			" // Turn the data on the canvas into data in the output cell.\n",
			" var width = this.canvas.width/mpl.ratio\n",
			" var dataURL = this.canvas.toDataURL();\n",
			" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.updated_canvas_event = function() {\n",
			" // Tell IPython that the notebook contents must change.\n",
			" IPython.notebook.set_dirty(true);\n",
			" this.send_message(\"ack\", {});\n",
			" var fig = this;\n",
			" // Wait a second, then push the new image to the DOM so\n",
			" // that it is saved nicely (might be nice to debounce this).\n",
			" setTimeout(function () { fig.push_to_output() }, 1000);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._init_toolbar = function() {\n",
			" var fig = this;\n",
			"\n",
			" var nav_element = $('<div/>')\n",
			" nav_element.attr('style', 'width: 100%');\n",
			" this.root.append(nav_element);\n",
			"\n",
			" // Define a callback function for later on.\n",
			" function toolbar_event(event) {\n",
			" return fig.toolbar_button_onclick(event['data']);\n",
			" }\n",
			" function toolbar_mouse_event(event) {\n",
			" return fig.toolbar_button_onmouseover(event['data']);\n",
			" }\n",
			"\n",
			" for(var toolbar_ind in mpl.toolbar_items){\n",
			" var name = mpl.toolbar_items[toolbar_ind][0];\n",
			" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
			" var image = mpl.toolbar_items[toolbar_ind][2];\n",
			" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
			"\n",
			" if (!name) { continue; };\n",
			"\n",
			" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
			" button.click(method_name, toolbar_event);\n",
			" button.mouseover(tooltip, toolbar_mouse_event);\n",
			" nav_element.append(button);\n",
			" }\n",
			"\n",
			" // Add the status bar.\n",
			" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
			" nav_element.append(status_bar);\n",
			" this.message = status_bar[0];\n",
			"\n",
			" // Add the close button to the window.\n",
			" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
			" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
			" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
			" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
			" buttongrp.append(button);\n",
			" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
			" titlebar.prepend(buttongrp);\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(el){\n",
			" var fig = this\n",
			" el.on(\"remove\", function(){\n",
			"\tfig.close_ws(fig, {});\n",
			" });\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(el){\n",
			" // this is important to make the div 'focusable\n",
			" el.attr('tabindex', 0)\n",
			" // reach out to IPython and tell the keyboard manager to turn it's self\n",
			" // off when our div gets focus\n",
			"\n",
			" // location in version 3\n",
			" if (IPython.notebook.keyboard_manager) {\n",
			" IPython.notebook.keyboard_manager.register_events(el);\n",
			" }\n",
			" else {\n",
			" // location in version 2\n",
			" IPython.keyboard_manager.register_events(el);\n",
			" }\n",
			"\n",
			"}\n",
			"\n",
			"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
			" var manager = IPython.notebook.keyboard_manager;\n",
			" if (!manager)\n",
			" manager = IPython.keyboard_manager;\n",
			"\n",
			" // Check for shift+enter\n",
			" if (event.shiftKey && event.which == 13) {\n",
			" this.canvas_div.blur();\n",
			" event.shiftKey = false;\n",
			" // Send a \"J\" for go to next cell\n",
			" event.which = 74;\n",
			" event.keyCode = 74;\n",
			" manager.command_mode();\n",
			" manager.handle_keydown(event);\n",
			" }\n",
			"}\n",
			"\n",
			"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
			" fig.ondownload(fig, null);\n",
			"}\n",
			"\n",
			"\n",
			"mpl.find_output_cell = function(html_output) {\n",
			" // Return the cell and output element which can be found uniquely in the notebook.\n",
			" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
			" // IPython event is triggered only after the cells have been serialised, which for\n",
			" // our purposes (turning an active figure into a static one), is too late.\n",
			" var cells = IPython.notebook.get_cells();\n",
			" var ncells = cells.length;\n",
			" for (var i=0; i<ncells; i++) {\n",
			" var cell = cells[i];\n",
			" if (cell.cell_type === 'code'){\n",
			" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
			" var data = cell.output_area.outputs[j];\n",
			" if (data.data) {\n",
			" // IPython >= 3 moved mimebundle to data attribute of output\n",
			" data = data.data;\n",
			" }\n",
			" if (data['text/html'] == html_output) {\n",
			" return [cell, data, j];\n",
			" }\n",
			" }\n",
			" }\n",
			" }\n",
			"}\n",
			"\n",
			"// Register the function which deals with the matplotlib target/channel.\n",
			"// The kernel may be null if the page has been refreshed.\n",
			"if (IPython.notebook.kernel != null) {\n",
			" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
			"}\n"
			],
			"text/plain": [
			"<IPython.core.display.Javascript object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/html": [
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\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/plain": [
			"Text(0.5,1,'Plane-of-array irradiance')"
			]
			},
			"execution_count": 50,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"columns_to_plot = ['poa_global', 'poa_direct', 'poa_diffuse']\n",
			"styles = ['-', '--', ':']\n",
			"skip_index = 3\n",
			"\n",
			"plt.figure()\n",
			"\n",
			"for i, tilt in enumerate([0, 30, 50]):\n",
			" to_plot = irrad.loc[ (irrad.tilt == tilt) & (irrad.distance == 1), columns_to_plot ].reset_index().drop(columns = 'index')\n",
			" \n",
			" for style, col in zip(styles, to_plot.columns):\n",
			" to_plot[col].plot(color = (\"C%d\" %i), ls = style)\n",
			"\n",
			"timestamp = irrad.loc[ (irrad.tilt == tilt) & (irrad.distance == 1), 'timestamp' ]\n",
			"xticks = timestamp.dt.strftime('%b-%Hh').values\n",
			"plt.xticks( range(len(xticks))[::skip_index], xticks[::skip_index])\n",
			" \n",
			"custom_lines = [Line2D([0], [0], color='C0'),\n",
			" Line2D([0], [0], color='C1'),\n",
			" Line2D([0], [0], color='C2'),\n",
			" Line2D([0], [0], color='black', linestyle = '-'),\n",
			" Line2D([0], [0], color='black', linestyle = '--') ,\n",
			" Line2D([0], [0], color='black', linestyle = ':') ]\n",
			"\n",
			"plt.legend(custom_lines, ['tilt = 0', 'tilt = 30', 'tilt = 50', 'poa_global', 'poa_direct', 'poa_diffuse'], loc = 'upper left') \n",
			" \n",
			"plt.grid('on', axis = 'y')\n",
			"plt.title('Plane-of-array irradiance')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 27,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"<xarray.Dataset>\n",
			"Dimensions: (distance: 4, tilt: 11, timestamp: 159)\n",
			"Coordinates:\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15T07:00:00 ... 2001-12-15T15:00:00\n",
			" * tilt (tilt) int64 0 5 10 15 20 25 30 35 40 45 50\n",
			" * distance (distance) int64 0 1 2 3\n",
			"Data variables:\n",
			" SIS (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" SISDIR (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" apparent_zenith (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" azimuth (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DHI (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DNI (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" rel_airmass (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" DNI_extra (timestamp) float64 dask.array<shape=(159,), chunksize=(159,)>\n",
			" shading (tilt, timestamp, distance) float64 dask.array<shape=(11, 159, 4), chunksize=(11, 159, 4)>\n",
			" SVF_shade (distance, tilt) float64 0.0 0.02778 ... 0.04517 0.05368\n",
			" poa_global (timestamp, tilt, distance) float64 0.0 0.0 ... 5.073\n",
			" tilted_irrad (timestamp, tilt, distance) float64 0.0 0.0 ... 4.359\n",
			" tilted_irrad_yrly (tilt, distance) float64 1.204e+03 ... 1.435e+03\n",
			" n_panels_per_area (tilt, distance) float64 1.0 0.5 0.3333 ... 0.5186 0.3889\n",
			" PV_per_m2 (timestamp, tilt, distance) float64 0.0 0.0 ... 0.2882\n",
			" PV_per_m2_yearly (tilt, distance) float64 204.6 102.3 68.2 ... 120.5 94.89\n",
			" CAP_per_m2 (tilt, distance) float64 0.1667 0.08333 ... 0.06482\n",
			" Efficiency (timestamp, tilt, distance) float64 0.0 0.0 ... 4.446\n",
			" Efficiency_yearly (tilt, distance) float64 1.228e+03 ... 1.464e+03"
			]
			},
			"execution_count": 27,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"example"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 30,
			"metadata": {},
			"outputs": [],
			"source": [
			"mutual_shading = example[['shading', 'SVF_shade', 'n_panels_per_area', 'CAP_per_m2']]"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 32,
			"metadata": {},
			"outputs": [],
			"source": [
			"mutual_shading.to_netcdf('/scratch/walch/workspace_tilted_irrad_flat/mutual_shading.nc')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			},
			{
			"cell_type": "code",
			"execution_count": 33,
			"metadata": {},
			"outputs": [],
			"source": [
			"def get_yearly_sum( ds, var ):\n",
			"# create an xarray datasets that contains, for each timestamp in \"ds\", the number of repetitions of that hour in the month\n",
			"# and sums all values over a year\n",
			"\n",
			" days_of_each_month = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\n",
			" month = range(1,13)\n",
			"\n",
			" days_of_month = pd.DataFrame( data = [ month, days_of_each_month ], index = ['month', 'n_days'] ).transpose()\n",
			"\n",
			" timestamps = ds.timestamp.to_dataframe()\n",
			" timestamps['month'] = timestamps.timestamp.dt.month\n",
			"\n",
			" days_of_month = timestamps.merge( days_of_month, on = 'month', how = 'left' ).drop( columns = 'month' ).set_index('timestamp\\\n",
			"').to_xarray()\n",
			"\n"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			}
			],
			"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": "3.6.1"
			}
			},
			"nbformat": 4,
			"nbformat_minor": 2
			}

solarPOT/PV_output/change_physical_potential.ipynb2072ea374a87master

change_physical_potential.ipynbView Options

solarPOT/PV_output/change_physical_potential.ipynb
2072ea374a87master

change_physical_potential.ipynb
View Options