penguin-tracking-antarctic.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c1809d2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "from pyproj import CRS\n",
    "from keplergl import KeplerGl\n",
    "import matplotlib.pyplot as plt\n",
    "from shapely.geometry import Polygon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "881a8208",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>long</th>\n",
       "      <th>lat</th>\n",
       "      <th>comments</th>\n",
       "      <th>migration_</th>\n",
       "      <th>tag_tech_s</th>\n",
       "      <th>sensor_typ</th>\n",
       "      <th>individual</th>\n",
       "      <th>tag_ident</th>\n",
       "      <th>ind_ident</th>\n",
       "      <th>study_name</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>year</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-01T00:43:00</td>\n",
       "      <td>139.74282</td>\n",
       "      <td>-66.57103</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74282 -66.57103)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-01T00:44:00</td>\n",
       "      <td>139.74310</td>\n",
       "      <td>-66.57141</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74310 -66.57141)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-01T00:45:00</td>\n",
       "      <td>139.74364</td>\n",
       "      <td>-66.57182</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74364 -66.57182)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-01T00:46:00</td>\n",
       "      <td>139.74420</td>\n",
       "      <td>-66.57211</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74420 -66.57211)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-01T00:47:00</td>\n",
       "      <td>139.74433</td>\n",
       "      <td>-66.57228</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74433 -66.57228)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             timestamp       long       lat   comments     migration_  \\\n",
       "0  2018-01-01T00:43:00  139.74282 -66.57103  2017-2018  Chick-rearing   \n",
       "1  2018-01-01T00:44:00  139.74310 -66.57141  2017-2018  Chick-rearing   \n",
       "2  2018-01-01T00:45:00  139.74364 -66.57182  2017-2018  Chick-rearing   \n",
       "3  2018-01-01T00:46:00  139.74420 -66.57211  2017-2018  Chick-rearing   \n",
       "4  2018-01-01T00:47:00  139.74433 -66.57228  2017-2018  Chick-rearing   \n",
       "\n",
       "  tag_tech_s sensor_typ individual tag_ident ind_ident  \\\n",
       "0    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "1    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "2    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "3    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "4    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "\n",
       "                                          study_name        date  time  year  \\\n",
       "0  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "1  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "2  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "3  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "4  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "\n",
       "                      geometry  \n",
       "0  POINT (139.74282 -66.57103)  \n",
       "1  POINT (139.74310 -66.57141)  \n",
       "2  POINT (139.74364 -66.57182)  \n",
       "3  POINT (139.74420 -66.57211)  \n",
       "4  POINT (139.74433 -66.57228)  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reading data\n",
    "fp = r'data/penguin-tracks.geojson'\n",
    "file = open(fp)\n",
    "geodata = gpd.read_file(file, driver='GeoJSON')\n",
    "\n",
    "geodata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4762d9ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "geodata['timestamp'] = pd.to_datetime(geodata['timestamp'])\n",
    "geodata['year'] = pd.DatetimeIndex(geodata['timestamp']).year\n",
    "geodata['t'] = geodata['timestamp'].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6969bd9a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Penguins:  16\n",
      "Time period:  2018-01-01 00:00:00 to  2018-01-11 14:24:58\n"
     ]
    }
   ],
   "source": [
    "print('Penguins: ', geodata['tag_ident'].nunique())\n",
    "print('Time period: ', geodata['timestamp'].min(), 'to ', geodata['timestamp'].max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d7f330dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# subset\n",
    "geodata = geodata.loc[geodata['year']==2018]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "94a72b9e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Penguins:  16\n",
      "Time period:  2018-01-01 00:00:00 to  2018-01-11 14:24:58\n"
     ]
    }
   ],
   "source": [
    "print('Penguins: ', geodata['tag_ident'].nunique())\n",
    "print('Time period: ', geodata['timestamp'].min(), 'to ', geodata['timestamp'].max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b8fc5458",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>long</th>\n",
       "      <th>lat</th>\n",
       "      <th>comments</th>\n",
       "      <th>migration_</th>\n",
       "      <th>tag_tech_s</th>\n",
       "      <th>sensor_typ</th>\n",
       "      <th>individual</th>\n",
       "      <th>tag_ident</th>\n",
       "      <th>ind_ident</th>\n",
       "      <th>study_name</th>\n",
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       "      <th>0</th>\n",
       "      <td>2018-01-01 00:43:00</td>\n",
       "      <td>139.74282</td>\n",
       "      <td>-66.57103</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74282 -66.57103)</td>\n",
       "      <td>2018-01-01 00:43:00</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-01 00:44:00</td>\n",
       "      <td>139.74310</td>\n",
       "      <td>-66.57141</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74310 -66.57141)</td>\n",
       "      <td>2018-01-01 00:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-01 00:45:00</td>\n",
       "      <td>139.74364</td>\n",
       "      <td>-66.57182</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74364 -66.57182)</td>\n",
       "      <td>2018-01-01 00:45:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-01 00:46:00</td>\n",
       "      <td>139.74420</td>\n",
       "      <td>-66.57211</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74420 -66.57211)</td>\n",
       "      <td>2018-01-01 00:46:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-01 00:47:00</td>\n",
       "      <td>139.74433</td>\n",
       "      <td>-66.57228</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74433 -66.57228)</td>\n",
       "      <td>2018-01-01 00:47:00</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "            timestamp       long       lat   comments     migration_  \\\n",
       "0 2018-01-01 00:43:00  139.74282 -66.57103  2017-2018  Chick-rearing   \n",
       "1 2018-01-01 00:44:00  139.74310 -66.57141  2017-2018  Chick-rearing   \n",
       "2 2018-01-01 00:45:00  139.74364 -66.57182  2017-2018  Chick-rearing   \n",
       "3 2018-01-01 00:46:00  139.74420 -66.57211  2017-2018  Chick-rearing   \n",
       "4 2018-01-01 00:47:00  139.74433 -66.57228  2017-2018  Chick-rearing   \n",
       "\n",
       "  tag_tech_s sensor_typ individual tag_ident ind_ident  \\\n",
       "0    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "1    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "2    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "3    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "4    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "\n",
       "                                          study_name        date  time  year  \\\n",
       "0  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "1  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "2  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "3  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "4  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "\n",
       "                      geometry                    t  \n",
       "0  POINT (139.74282 -66.57103)  2018-01-01 00:43:00  \n",
       "1  POINT (139.74310 -66.57141)  2018-01-01 00:44:00  \n",
       "2  POINT (139.74364 -66.57182)  2018-01-01 00:45:00  \n",
       "3  POINT (139.74420 -66.57211)  2018-01-01 00:46:00  \n",
       "4  POINT (139.74433 -66.57228)  2018-01-01 00:47:00  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geodata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "912cc1f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<AxesSubplot:>"
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     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
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     "data": {
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LeVHBXBAd4u5QutXbgxJJMRn4PK+E/2XkuDsc4SgiklYPeutgETPWpnNdbBjGI6zOlFmvZenYASiIeYhC7zqyfpM8TH9fI/1MxiP6m/zSgFiSfY3YFaXtgwWhGxzJv09uNznYj0+GJre4Ws2RYFlpNe/nFLOlyuLuUISjxJH72+RmH+UUc932/e4Oo8edFB7Ie4MTSfEVbxGF3iGSVg/ZU2tlb63N3WH0iqu37+e/u7LdHUar9u57gX2ZL7k7DKEbiBHxPWBPjZV9tTZ+GNHP3aH0ineHJJLm5+PuMFoVFDQWSfyNPiKIpNUDtlXXsqmqlpI6B300eneH0+MmBvm5O4Q2BQeNd3cIQjcRf3p6QFmdk4uiQuhjPPITliD0NpG0esCS0iqWlFW5OwxBOCKJx8Nu9mdJJSvKq/lsaLK7QxGEI5JoaXWz4f4mjg8NIFUMARCEHiFaWt1oS0U1d+zO4dOhyZi14lsrCD1BtLS6ycLiCmZt2EOh3YFVTGkRhB4jklY3GRXgy1lRwSwfO0C8NRSEHiSeYbpJoE7Ls6lx7g5DEI54oqUldEm21c4vReXuDkM4ioikJXTJ85n5/GdnForoxxN6SZeTliRJN0mStEuSpO2SJD1Vvy1BkiSLJEmb6v/Na+HcYZIkrao/Zp0kSWO6Go/Qu8YGmkkQdeKFXtSlPi1JkqYBs4E0VVVtkiQdvvDdXlVVh7VxiaeAB1VV/UWSpJPqP5/alZiE3nVOVDDnRAW7OwzhKNLVltZ1wBOqqtoAVFUt7OD5KvDPig8BQG4X4xF62Yc5xVy7bb+7wxCOIl1NWinAJEmSVkuStFSSpNGH7UuUJGlj/fZJLZx/C/C0JEkHgWeAu7sYj9DLMqpr2VkjqpYKvafNx0NJkhYCkc3surf+/CBgHDAamC9JUhKQB8SpqloiSdJI4DtJkgapqlr5r2tcB9yqqurXkiSdA7wDHNtCHFcDVwPExYmhBZ7CrNORZbVTZncQpBcjaISe12ZLS1XVY1VVHdzMv++BbOAb1WUNoAChqqraVFUtqT9/PbAXV6vs3y4Bvqn/+EugxY54VVXfVFV1lKqqo8LCwjr2VQo95tSwAPqZjPhqxYtooXd09SftO2A6gCRJKYAeKJYkKUySJE399iSgH7CvmfNzgSn1H08HMroYj9DLdtVaOWi1k2O1uzsU4SjR1fb8u8C7kiRtA+zAJaqqqpIkTQYekiTJATiBa1VVLQWQJOltYJ6qquuAq4AXJUnSAlbqH/8E73FaRDCnRYi3h0LvkVRVdXcMHTZq1Ch13bp17g5DAGqdCu9mF3FFTBg+R9iCtIJ7SZK0XlXVUf/eLn7KhC5ZX1HNE/vy+Lu0wt2hCEcJkbSELrE4FBzAxkox7EHoHSJpCZ2ysbwKp9NJpI8es0ZmhL/J3SEJRwkxsEbosAWF5Vxx2OrZKT560kTSEnqJaGkJHTYt2Mxg06FJ0mdFhBBuEIUPhd4hWlpCh83esBdJksmfNszdoQhHIZG0hA6bEOQrSkoLbiMeD4UOK3E48dNo3B2GcJQSLS2hw14eEO/uEISjmGhpCYLgVUTSEgTBq4ikJQiCVxFJSxAEryKSliAIXkUkLUEQvIpIWoIgeBWRtARB8CoiaQmC4FVE0hIEwauIpCUIglcRSUsQBK8ikpYgCF5FJC1BELyKSFqCIHgVkbQEQfAqImkJguBVRNISBMGriKQlCIJXEUlLEASvIpKWIAheRSQtQRC8ikhagiB4FZG0BEHwKiJpCYLgVUTSEgTBq4ikJQiCVxFJSxAEryKSliAIXkUkLUEQvIpIWoIgeBWRtARB8CoiaQmC4FVE0hIEwauIpCUIglcRSUsQBK8ikpYgCF5FJC1BELyKSFqCIHgVkbQEQfAqImkJguBVRNISBMGriKQlCIJXEUlLEASvIpKWIAheRSQtQehlQz8YypAPhqAoirtD8UoiaQlCL1NwJauhHw11cyTeSSQtQehlv5/+e8PHorXVcVp3ByAIR5so/yi2XLwFu2JHlkW7oaPEd0wQ3ECSJAwag7vD8EoiaQmC4FVE0hIEwauIpCUIglcRSUsQetjWoq2c8+M5lFvL3R3KEUEkLUHoQVX2Kmrqaqitq8Wu2N0dzhFBJC1B6CH3/X0f5/90PnH+cfx0xk+Em8LdHdIRQSQtQeghS7OXkhSYRJRvlLtDOaKIwaWC0M0WH1jMmKgxLD1nqRg82gPEd1QQupFDcfDfv//LixteFAmrh4iWliB0I62s5Z3j3qF/UH93h3LEEn8KBKEb5FTnsKNkBwBDwoag1+rdHNGRS7S0BKEb3Ln0Tootxfx21m/uDuWIJ5KWIHSBzWnjzS1vcu/Ye5El8eDSG8R3WRC64NPtn7Jo/yJMOhOpIanuDueoIJKWIHTBG1vfwM/gR0JAgrtDOWqIx0NB6IKbR9zMhOgJ7g7jqCKSliB0QnpJOlpZywUDLnB3KEcdkbQEoRPuWHYHeo2er0/92t2hHHVE0hKETnhl+itixLubdPm7LknSTZIk7ZIkabskSU8dtj1NkqSV9du3SpJkbObcYEmS/pAkKaP+v0FdjUcQekN8QDyxfrHuDuOo1KWkJUnSNGA2kKaq6iDgmfrtWuBj4Nr67VOBumYu8V9gkaqq/YBF9Z8LgiC0qKstreuAJ1RVtQGoqlpYv/04YIuqqpvrt5eoqups5vzZwAf1H38AnNbFeARBOMJ1tU8rBZgkSdKjgBW4XVXVtfXbVUmSfgPCgM9VVX2qmfMjVFXNA1BVNU+SpCOqStqz557S8PHoU89i8oWXui8YQThCtJm0JElaCEQ2s+ve+vODgHHAaGC+JElJ9dsn1m+rBRZJkrReVdVFnQ1UkqSrgasB4uLiOnuZXqXRG3DabQBs+Pk7+o0dT1leDgMnTXdzZILgvdp8PFRV9VhVVQc38+97IBv4RnVZAyhAaP32paqqFquqWgv8DIxo5vIFkiRFAdT/t7CZY/6J401VVUepqjoqLCys41+pG9zy0dcE94klJD6ROU+8SGHmPn5/4xXW/fiNu0MTBK/V1T6t74DpAJIkpQB6oBj4DUiTJMlU3yk/BdjRzPk/AJfUf3wJ8H0X4/E4AydPp7q4iEXvv8mQGceTMvYY4oc2l78FQWgPSVXVzp8sSXrgXWAYYMfVp7W4ft9FwN2ACvysquqd9dvfBuapqrpOkqQQYD4QB2QBZ6uqWtrWfUeNGqWuW7eu03H3tqztWwiMiMQ/tHGXXe7udAwmEyEx3vG4Kwi9qb5LaVST7V1JWu7ibUmrJb+8/gI56ds55/7H8A/1jkdeQegtLSUtMaS3Byx4+Wky1q5s87jRp5yOvbaWogOZvRCVIBwZRNLqAZkb15O+fGmbx4XGxnP9W5/gsNtE4hKEdhJJqwcYfExotLp2H79tySK+f/ZRHA6xArEgtEVMmO4BV736boeOHzhpGiu/+gTFoYj/I4LQBtHS6mbfPf0wO/9u+9HwcAMmTuHyF95ElmVyM9J7KDJBODKIpNXNKgryKc/P7dS5Sz56h68evk88JgpCK8TDSDda99O3VBYXMWDStE6dP/H8S4hPG4ZWrJknCC0SLa1uVHLwAKaAAPxDQjt1vtFkot/o8d0clSAcWURLqxtNv+I6UFRkbde/rXarFQC9sUntREE4qomk1Y10ekO3Xeuz+25DkmUufurlbrumIBwJRNLyUBPPuxgkyd1hCILHEUnLQyWPGgtAdvp2IhKS0YnHREEAREe8R1OcTn555Tl+erG5oq+CcHQSSauLfpv3Iiu+/LRHri1rNEQkJVNdVtIj1xcEbyQeD7ugurSE3WtWEjtwSI/d49T/u6fHri0I3ki0tLrAxz+AyedfzMk33dbj91r03jwyN63v8fsIgqcTSasLNFotQ2eehM7Q853ke9etZuOvP/b4ff5NqXVQ8lk6itXR6/cWhOaIx8MuUBSF588/FZ3RyM0ffNWj90oaOZaQ6D49eo/mlP+eiWVzEZatRZjGRBJ8Wr9ej0EQDidaWt2i58dTHXv5tQw/YVaP3+ff/CbUJ0oFalflk/OqZz6iKorClC+m8OL6F90ditDDREurC2RZ5rYvfuq1+xVl7efAlo2MOuX0XrunLsyE8bxkrJ/vBUA9WNtr9+4IWZaZETeDmQkz3R2K0MNES8uLrPnuS1Z/92Wv3zd0WDQxT0xq+NxRbe31GNrjgfEPMDBkoLvD8Hg7Uwc0/Nv/v7nuDqfDRNLyIifeeBtXvPS2W+6d9/Khx8LSb/e6JQaha6wZGZT/1PjJwPL1126KpvNE0vIisixjNJkA2Lt+Ddba3ntUc+YcupdSLYoUeqP955xL3u13gI8Pke+8DXo9Pscc4+6wOkwkLS+kKAoLXnqKX155uqGETW/xPTuJyOuGd+s1i2uLOVh1sFuvKTSjfv6qHBBA0IQJ6GJikL1wTqtIWl5IlmXOuOt/HNy2hWWfvNfj9yt8Z2vDx0Eju2fYRU51Dvf+fS+KonDT4pu4+veru+W6QvMse/eilpUBYExOBkBjMmHftcudYXWKeHvoIRRFofjgAcLjE9t1fMzAIcz6v3vpk5raw5GBUmWHKD0hZwzo1Pm1jlqMshFZPvQ3cnnOcpYcXEKxtZgHJzxIlb2qm6IVmmNMSmr4uHb5cuz5+Vi3bQMg95VXCJo8BZ+0npuO1p0kVVXdHUOHjRo1Sl23bp27w+hW8x++l4PbNgOuWvFjTzu7zXMUh4NP77+DUbPOIPWYSW0e31mKzYGk1SBpXOPR8p9bh2zWE3blECS59TFqO0t2cvlvlzMifASvHvtqj8UotG1nav0fnbAwzEPTqF64yPW5Xo82KIh+S5e4LbbmSJK0XlXVUf/eLlpaHuLwFab//uwDVnz1GdMvv451P3xFbUU54886n1Enn9bkPKfTgeLsuSk2RfPTsW0oAiDw5sFoa0CxOHBW2bHvr8SQFNDq+RX2ClKDUrk6TTz+uduA9J0AWPfs4cAFF8Ixx8COHfT9/nscRYVujq79REvLQ2z98w+i+qZQkLmXX199rtVjr5r3If5Bwb0SV/YDy8GuNHxuGhWBZUcJAScn4jsiAqmV6qq/Zf5GYmAiKUEpvRGqcIRpqaUlkpYHcjgcvHzp2Sh1dQAERkZRnp/X6Jhhx89ixuXX9HgsikOh8PtdONYWAzQaZNqaR1Y8wrd7vyXQEMiJiScyLmIclfZKCmoLWHxwMTuKd2DHNXRiYvREXp/5eo99DYJ3Eo+HXkSr1XLrx99SU1HGmh++YepFl+Ow27BUVfLz6y+Qs20Lm377kdy96cx59HneuP5SYgelcdIN/9ftschaGcfW0obP7XnV6KPMrZ5TUFPAFxlfAFBoKeSDHR/wwY4PWjw+NbjnXyYczRSrFbTaRqtE5T74EJU//YT/SScS/eCDboyu40RLywv9+eFbbFjwPQDm4FAGTplOYtpwYnqoGGH2f/9q+Ng4KYrQk/u2HWPWn6zJXUOptZQaRw2Z5Zk4VScJAQmMiRzDOf3PwWxoPfkJbbNscQ1H8UkbQs269RhS+6M1m8m6/ga0YaFEP/gge44/Hm1EJAkfHvrD8U+nfPi99xIy5yK3xN4W0dLyUHVWK3vWriR14tRW+4cON+3iq+gzYDA/PvMo1aXF9BkwqMcSFkDorcOpXJuL/e8CzIPbtxDttLhpTIvr3ErbAtSsWkXt+vVUfP8Dhv4pRNx+O3mPP07sc8+hKAo5t99O1Ny55N57L6gqyT/9SPb11+M7YQIxzz+HbPZF9nX9UQi95hp0kVEN1y755JOGjz01YbVGJC03W/7Fx2z47Uci+6cSFB7V9gn1UkaPJ3rAYHJ3buPbx/7Xo9UmjBFmjKekwCmiQ70nKYpC1Zo1+I8dS/Ebb2Lbuwelphb2ZWLdvRvb1m04iopQbDZsW7Zi251B7FtvNpwf89KLGAa6JozHPHVoMZTAM85odJ/C554HIO6r3p983x3E46GbFWXtZ9XXn3Pyf+5sNPiyvZ499xQAAqNjmHXzHYQnJnd3iEIvSR85CrWmBsPIkSR89CHY7d0+zUZVFNIHDgKdjgFbt3TrtbtbS4+HYhqPm2VuXEdFYX6nEhbA6fe4OlHLc7P56L//wWbxzHpXQlN1lZVk3fp/7L/gAlRFIfTWW0GvJ/KRR5BluUfmBUqyjPn44wm95ZZuv3ZvEY+HbmaprMDWhWoNSUNHct3bn/D6lRcC8PrVc7jlI+8rN3I0OXDzf6j9/fdG2yp+/InQiy4k9KILe/z+sS++0OP36EmipeVmpbnZOB1dG9Fu8gtgzpMvA+C029i1anl3hCb0gJ1pQxslLN9TTiH2ww/xP05UXG0v0dJys9l33I+idH0aTnhCIkmjx7Fv7Sp+ev5x+vdiGWihfcrmzwe7a0BtxPPPE3ziCW6OyDuJlpabybKMVqvvlmudfvt96Hx8CI1rX6UIoXdJRiPodMR9Od/tCUux27Gmp7s1hs46ot8e5uzayZ8fvMl5Dz3ZbYlBEI4EeXPnUvHDj6SsW9vpl0A97ah8e/jH269SsDeDFy90jVP55L7b2LniL757+mFWfvMFiqK0cQVB6D67Jkxg9/QZ7g4DgLBbbiHqkYc9NmG1xvsi7oBzH3y84ePykmLyM3bx84tPsn/rZlZ88REf3nWjG6Nz+f3tl3n92ovdHYbQC5SaWpzl5e4OAwBtYCABJ52Ede9elF5ca6A7HNEd8T4mP2SNBsXp5KM7b2rY7rS56qqXZGXx7LmnYA4O5erX3mv3NJrutPWP3wCw1lRh9PXr9fsLvSfitv9DsVjcHUYjWRfNwThsGHGvv+buUNrtiG5pAQT2iQXAXu0q5ytrmubp6tJi6KG+vYw1K1jx1act7h8w5VgkjQbU3k+YQu/SRUXjf/LJ7g6jkahHHyH4kotRamrcHUq7HdEtLYCKwgIAfENCOf6am3DY7BTu30d4QjI/v/IMDpuVhGEjkXro2X7HssUUZR0gY9VyZl59I9EpjeusF2VmMPHcORjNouLBkS7vgQcwpA0hft48d4fSwG/6dHZPmIhh4EDiD5vH6MmO6KRVkpON0+pqjjvq6kgcOhKABS895RrQqaoERkRx5t0PUllSRO7uXaSOn9itMcy+/T6qy0v56uH7UFUVh8Pe6E2moqhkblrPmNlndet9Bc9iz8vDabNhPtbzBpFGPfYohr5tlxvyFEf042FQVDTJo8cB4Ot/qJa5s64OVJXZd97PJc+6nuXfuv4yFrzwBM+eewrdPQzEHBjMpc++Rk76Dl674kJqKysa9sUMGETxwQPdfk/Bs6h2O9TUUP3br+4OpQm/KVPQ9+mepeF6wxHd0pJlmdNuv69J6+YfWxb/Rt+RYwGIHjiE3B2ugmrl+bkERXX//8TUCVOorSjHaPYjfcUyFr/3BpMvupyCvRk47DZ0Bu9bOFNom6O6mvzHHiPoissJu1os8NFVR3RL6x//TljHnOcaYpC5bg0AJdlZDQkLYMWXLXecd4V/aBhTL74SWZaJTE6hT/+BWCsrKDmYRY2HvAoXup8jPx/btu34jhmDJqD11YvcxZ6Vxc7UAWTdcqu7Q2nTEd3Sakn84DRW1H/8Tz2qwx171Q09HkNgRCSzb78Xa20tTqeTbUv+wF5by/TLen6xCqF31a5dizY8HL8pU9wdSovq6udE1vz6K/mPhhJ5771ujqhlR0VL69++fOieZrdH9UvllFvvxuBj6rVYjCYTY087m7K8XLJ37eCzB+5A6WLVB8GzyGYzko+Pu8NolW/fvpimTEabmkr5Dz9Su3mzu0Nq0VHX0lr2yXs46v+qHC4oOoYLHnnGDRG5zLrlLrb++Qdrf/gKBeXo/GtyhAqcNQt9XJy7w2hT/Btv4CgqYu/s0yj/9jtMQ4e6O6RmHXW/Gz7/vEWUJNe/egMmuL/pPmTaTC5//g0xufsIU/nHH2TNuZiaFSvdHUqbtGFh+AwfTs3q1dj273d3OM066pLW6FlncPYDj3HyzXcw/dKruejxl9D7mNizfrW7Q2uw7NP32br497YPFLyCecYMjMOGkffQQ+4OpV2iH34IpayMmpWemWSPusdDgLhBaY0+v+Klt1xjtzzEgc0bKMvPY8j049wditANZFkm8MwzqVy8yN2htIs2OJj+qzwzYcFRmrT+zeTvWa+h5zz5krtDELpZ5a+/Yt20yd1hHBGOusfD5qz+7ive+c/VHlVfy2G38/n/7iI3wzurSwqN6ZOT8Z0+3d1hdIpitbo7hEZE0gIKM/dgra8C4Snq7FaqSoqpLCpydyhCN7Bu3YojL8/dYXSYUlPD7gkTKXrlFXeH0uCILrfcXqqqkr1jK399/iHjz74I1ekgaXiTKq9u8c5/rsIUEMT5Dz3V9sGC0AMKn3uewHPP6fX5iS2VWxZ9WoAkSWRt20LR/n188+h9Ddsj+6VyoRvHbgHEDBhM1rYt1NmsYm6i0KtqN2+m4KGHiX3nbbSBge4Op4F4PKw34dyL+M9H35ByzKSGbdaaaizVlW6MCo67+ibOnfu4SFhezFldjS0z091hdJhaU4ujtNTjyjGLx8NWOOx2Xr7sHMITkrnw0Wd7/H7CkanwtdeoXb+BhHfedncoHeJ0OskYOQr/U04h+pGHe/3+R+VqPF2l1esZOGk6aTPcv6imtbaWD++6maztW9s+WPAoVb/+5pWd8I6DB5H0eswzj3V3KI2IPq02HH/tze4OAQBrdSVl+bmU5mQRN2iIu8MR2kmxWgk4/TSvqgz6D2dVFbq4OHyGeNbPm2hptZOiKCz/8hMqiwrdcn+/4FD8g8PQaHVuub/QOYXPPU/xSy/jO3q0u0PpsLqsLCRZQuthNcBES6udqktLWP3NfDI3ruOix57v9ftrtFpGn3YWK7/8BFmjYdAUz1j0U2hd+H9uxnfCMchG73uR4n/CCZhGjXatFuVBREurnfxDw5h5xXXoDUa3jZwfOGEKfiFhmIND3HJ/oeNkX1+PLv7XGkmjQRcR7u4wmhBJqwPKCvLI2bWT8twct9xf1mo578EniR8yzC33Fzqm5N13sWzx7hcnjupqd4fQhEhaHTDh3Dkcc84F5Oze6e5QBC9Q8v4HFL/zjrvD6LTc++4n45gJruX2PIjo0+oAjVZL9o5tFB88IMrG9JC6klpkXz0ao/f/aPb9/TfQe29BR9+JE6ldvx7J4QCt5/z/8JxIvMSUOVeCWMG+xxQ8vR6AmCcmtXGk5/PGzvdGbFa0AQFIBoO7I2lEJK0O+uium1CcTiZffBVbF/5CWW42w06YxYxeXkUnb89ufp/3Imfe85DomBd6hN+JJ2IcPBhJ8qy/0qJPq4OMZn8Aln34FmW52QBs+vVHCvbv69U4VMVJaV4Oy+d/0qv37WnRj0zw+lZW2ZdfUvnHH+4Oo8tkvR5DcrK7w2hCJK0OuvzFeQT1iQUgLKkvp9x2L35hEXx8183sXPFXj9//4PYtrJj/CdEpA0g9ZjKJw0b0+D17k6z17h9JpbaWgieepPiNN90dSpfVbtvG7kmTsezwrBdP4vGwgww+vlz+3OuNtmk0Gn568UlComN6/P4Hd2xj1bdfEJaYxIk3/F+P30/oGHtuLrJeT8i13r/oriMrC2dVFeBZRRW8+8+ah9izZjlOm41P7+v5JDLu9HOYeP4lJA4fyTdPPMgPzz/R4/f0JJZqO5/MXcmaHxs/jtfZnW6K6F8UBeOIEfhNneruSLpMVRTi330Hn4ED3R1KI11uaUmSdBNwI+AAFqiqemf99jTgDcAfUIDRqqpa/3Xu08AswA7sBS5TVbW8qzH1tmOvuIHsnTswh/R8h7is1TLm1DPJ35eBb1BQry/KUVdQQ8EbW8DqAJMGTZAPung/TAND8EkM7JZO2+wnVmGeGkPguMYt1zqbgx9e2EhFkQVrjWv1pJKcan56ZTPVZTYmntOPodNju3z/rrBs3ox10yaUykrk4GC3xtJV+Q8/giG1PwkffODuUBrpUtKSJGkaMBtIU1XVJklSeP12LfAxMEdV1c2SJIUAza3R9Qdwt6qqDkmSngTuBu7qSkzuoNXrmTLncv7+9AOstbUYTaYev+d3Tz5MSJ9Yjr+md6tQlH6zB2wO15+haifO6mqcB6ux/t1C6RWDDFoJNDKSTkI2akGWkA1aQs5KQRvYeFhA3isboLyO6u8ymyStD+9dgbXaNdBxwll9Kc2tZv7ja/inJNz+rcVuT1rl87/Eb+ZMtF6esFSHA11cHEHnn+/uUJroakvrOuAJVVVtAKqq/lMC4Thgi6qqm+u3lzR3sqqqh69Iugo4q4vxuI3e6IPOaKS6pJDlX/7BqJNPJyA0tNvvY7da+f2Nl5h59Y1EJPbemx17QQ36CF8kvYzv2CjMx8ZTV1yNPbcGW0Y5dTnVUFXnSmaHd4HYFLABOFEBJ3Zcn0HlkiyCT0tpdB//kxIpe2sbftekoapqo5bboMnRrP85C4B5Ny5t2H7KzWn89PIW7Bb3j9w2JCdj6J/S9oEervzrrwm64AICTnB/Lbl/62rSSgEmSZL0KGAFbldVdW39dlWSpN+AMOBzVVXbWpnhcuCLLsbjNvFDhvHtwQN8cPuNAGz/83dufv/LRsfUWa3sXruCQZM6v5RUWW42+zdvYMDEqb02Psu2v4Kit7cSdHYK4Ve4ais5rQ7KP80g4OREAucMbvV8h82B4lBQrXU4y+xIOi2yFvTR5ibH+iYF4fv4JIo/3E5FuC9+E6LR+LlGlY87tS9DZ8by7q3LG51TlF2JLEP/MRHd9BV3XvQTj7s7hC5T6+oofPEldJERBJ1+mrvDaaLNjnhJkhZKkrStmX+zcSW9IGAccAcwX3L9adQCE4EL6/97uiRJLdZSkSTpXlx9Yi0OOpIk6WpJktZJkrSuyEOX1eqTOggAndGE06mw8uvPG+1/55ar+fWV5/j6yQc7fY+IpL7c+O7nJI8cA8DPrzzDloW/dj7odtDF+RF4chI+gw61HK3bSlCq7Gj9256mojVo0fvqMYT4YuobhE+8H4Y+fq32f5nHR2PLqqRg3mYc1faG7T4+Bm6YN51Tbzu0SnjB/gokSSJ5pPuT1pEg5777MQ4cQJ+nPHMFqDZbWqqqtlhrVZKk64BvVFeh+TWSJClAKJANLFVVtbj+uJ+BEUCTdcElSboEOAWYobZSsF5V1TeBN8FVI76tuN3h7PseAVy15d+99Rp2r15BYEQkAyZOBWDW7ffx5f/+y9AZJ3b6HiU5B1EVhdDYeAByd6fjH9qz5UNkWcY8PrrRNp8RYeiifZttLXUHY78gVKDsi104SyxozY2TY2y/UMbMTkSWJAqzqlAUFb2PGMHTVSXvvU/NkiUEnDrLY6utdvX/8nfAdGCJJEkpgB4oBn4D7pQkyYTrzeAUoEnlPEmSTsDV8T5FVVXPWvKjC7R6PVe/+h7bli4k+LCxW336pnDLJ9906dqf3nsbdkstl7/8Frk7tlNdUkxCWu8PMJVluccS1j98+gVhvGcs9uyqJv1bAKNPTARg/qOr0WhlNBrPmm7ibbJvvZWaVasx9OtL5L33ujucFnV1nNa7QJIkSduAz4FLVJcy4DlgLbAJ2KCq6gIASZLeliTpnxU2XgH8gD8kSdokSdK8LsbjUQZPOZaIpNb/WqmKQnb6dtq7KpLdbgNg2cfv0/+YyUy+6HKiUz1rHE13smdXUfJpOjVrC5rsc9id7FqbS3F2DckjwpE17h12WLNiJVULmzxMeA1bXj5+J5xAwscfuzuUVnWppaWqqh24qIV9H+Ma9vDv7Vce9rFntj97UUl2Ft8++RDxQ4Zy6v/d0+bxt3z0Ne/eeh37N65Fo9Mx4sRTeyFK99HH+mFMCaL8lz04cBA4xtVyrSiq5fNH1iDJYPDV0n9cpJsjhYLnnkWtteB3rPeVwi775Vfsmzah8bDSys0RnQA9zG614rBZMQUENrs/NC4BvdGHwnZOuNZotOh0OhSnE1QVPGwGfneTJAmf4aHUrsmn+pvMhqS1+od9OOwKky9IYfDEPm6vRKCqKkHnnodp4gS3xtEZhS+8QMn772MYOpQ+b77h7nDaJJJWD/vy4XuoKCzg+rdarsZw1avvduialz77GgDrF3zHrlV/c8HDz3QpRk9nz6wCwDg2zPW5zcHBnaUMGB/JkEk9P9+zPZTaWkreeQdtWBiGqCi3xVFTZUOSwGRufw2ssm++QRseQcwLz6Pz9e3B6LqHSFo9LHHYKPZtWNPqMbLcsb6Yz/53J4rDyaApM9BojvwlxXRRvmDQEDAlDoDMTUVIksSwY+PcHNkh9sxMHCUlyD7uKfynKAqvX7+k4fMLHhpNULhfu87tt3gxsgdVJm2L90TqpVInTmHP2pUU7N9HREJSt1xz0KRpOB0Ohh13EsOOO6lhe21FOQazn1f0S3SEaUAIpgePafh81ff7kLUQ3MNvLzvCUViIbDCgi+z9vrWa8hre/+/qRts+fWAtADfMa3sgszclLBBVHnrc5/+7i6IDmZTn57b7nA0/f8+Xj97X4v6Ivv3JWLMCu/XQ/POdq5bz+tUX8cIFs7sUr6dbNn8Xlko78YO6f4pUV+Q98SSqRoM+Pr7X7314wjr2qn6N9r167eLeDqfHiaTVw0accApavZ7A8Pb/Bd765x9kbdmEw25vdn9Ffi5l+XnYrbXYrVYUh4OfXzhUoqYwa39Xw/ZYezcUYgrQM+WCVHeH0ogzNxeltLRX76koKm/ceigp3TBvOv1HxnLDvOmMOyuhYfvqn3f3alw9TSStHjbujPP4z0fftDle63C+gUHIWi1VJc1PV0oZN5FrXnsfc2AwH911E188eDc3vPtZw/6QPu6tdNBTaivtWKsd+IX4IMue89bUUVoKDgeaHpgg3xpJAoel+X0jjz3UFbHuh2wyNjVt6e+/4EJy7ml7mI2nEUmrF2xZ9BsvX3YulcXtmzMZ2TcFVVX54I6b2lzNeujMkynI3MPOv5Zw2xc/EZHUlz/efLkbovY8a37ah1Yvc/J1aW0f3Iu0wcGYJk7EkJjYq/e1W5tvif/j8P6s3+el8+oNi8nZXd6wzZDSD2NK/54Kr8eIpNULEoaOoO/ocZgDg9p1/MRz53D+w09j9PXl60fvb/XYESedypDpx9Nv9HgURSE8qS/R/bzvB7E99m0uxses98g5hvFvv0X8u727MOsPr25u+Pj616c1e0yjjngnfPfchoZPo+bOJeTSS3osvp4iklYv8A8NY9J5F7P1z/av0BKVnMKoWWcwcMqxqK20tmRZZsbl12IODuGrR+5j259/UFrQ/k5/b+F0OLFU2NHqPPNHVnU4KP3o4/qa6r2jcI9ryfr+E8NbHVzbnjeI3sQzfwKOQKu+nc/Sj99t83HvcKNOOZ2D2zez4qtP23X8oKnHojqdrP/hW7Yt9d45cM0p2F/JLH8Nx9TYcdS0/ljkDs6qKko//ojiN9/q9XtPv6DtuacNictzugI7zfPa2Ueo6Zddw+hTz+jwQNJhM0/C0M5RyoMmT+fXV58DIP6wyg/fP/sYRj9/cnZuY/SpZ+Ksq6MoK5OZV97QoVh6W07OfHbtfhiNRk+E6WOKjnmA4AMnUlcwBG2SZy03rw0Kwpg2lMpffiH8/27t1WlF7f2ZOlJaXKKl1UtkWSYgrONF6iL7phAU1afdx5vq+818Aw4teKHV6dDq9Zj8/TEFBJK/dzcF+/YAUF3esdf0VevzyX10FWV/7Edxtr/V2Bn7D7yGqtbicJTjFxCKTWNE42tG4+uZswBMI0fgKCrC6mHrBB5pREvLDZZ/8TGRyf1IHjW226991j0P8fMrz7HgpadQJS0ZK5YA8J+Pv0Wrc/2yJ48YDUDWts1888RcZt3y33bFUvL5TizpZWB1UrPoIDWLDhJ65RCMfQO7Jfbq6t1s2XojQ9Pew9e3D2PHLGTpMtdLhdV/vkT+pruY8sJkdHrP/LE1jR6NNizMIyexf/74CkoOWLn21SmkX3YjPpX5JH33rbvD6hTR0nKD9OVL2daBTvmOCItPJCwunt0r/25IWACrvvmCPz96u9GxMamDGHv6ucQPG96ua+uizPiOiIDw+sm4PjKyqfsSSEnpKiyWvaxaPRkArVbLgNQXATDHfY7eqPHYhAVQ8/dyHAUFqI7mFp5yr5IDrtkT825YyhLTWTiPO9vNEXWeSFpuYPTzoyTnYI9d/6SbbufMex9utG31N5+z4afvGm2TtVrGn3keWq2rf+jA1k2Npgb9m/+UWIJOTUbr4zo+4vZR3Vq9NKbPocWYFi2eztu3LyFzRQq5qy+jbPvNnHBNGs5aB/kvbqCu0PMK3ZonTUIfF4e2F9a/7BqJiHNOc3cQnSaSlhsMO+FUZFnCUl3ZY/dISBvObV/8xBUvHxo7FBAVTcbaVc0e73DY+f7pR/jr0/fbvLZs1KKNNePIqaFmS/ctMqLRmEhMvBsAxXEAW7WDTQuzsZdO4sybryfIX0Pe6+tx5NVQ/H1Gt923uxiSEjEOHkTFggXuDqWJG+ZNb/TPP7Tn1+bsKSJpuYE5MBBLdVWPr6IDEBgewW1f/MRtX/yEtaKClS0Mn9Bq9cy89mYK9++jurTZZSop/mA7NZuLcJZakYCSD3dQ9mk62f/9C9v+8m6JNynxSvr2fRhZC4kn3eH6GixO8u5bTukLm6Coft3EvT2X8LuiLi8PR06Ou8NoUdXSpew57ngcHrqiVXuIpOUG8UOGERafxOpv5lPVQoLoCec/8gzHX/ufFvcHhkdSWVTIL68+z6J3Xm+y35ZTTV12JeYxUegizYRcOgjqX+TV5Xff41pIsKsMjcHsSkyO+peUqqpidTigr5nIh8Z32/26U8KHHxL1YNtLxN28fT//2XGgS/caf0YSOoNMVWnLj/T/pg0KRhMYCD4+Xbq3O4mk5SYn3HgbvkFBLPnw7bYP7iYhfWJbXZU6qm8K17z+PpaqSnYuX0pJTjZ/vP1qw35JUbFlVeE3qQ/BZ/bDp28QxpRgZLMOU1r3LWN28OCbgIERw+dzw7zpnPvadH5VHfxY6eS3apWYK4ej9eAO+eZ8kpVHytLNlFntZNXamF9YzhcFZZyxflenrynJEkgSWkP766cZkpMwT5uKbBKPh0IHmQMCmTLnCnzM7asu2Zsueuw5Ln9+HnvWrGDXir/44PYb+OLBu5FGmPD51/CG4AsHIIfoyX1oJRV/ZnX53mvWno4kaembfAtBQSMbts++cST9DTJ9PHOIVgNFUThw1VXUrHUV4at2ODh1fQZ37i2gUlG5a08ODlXhn6GxudbOv2lUnSpDp8fg04Fxa5W//ELJvDew79nT6fu6m0habpSxZgXbliykqqTY3aE0Imu1mAICGXv6Odz47ufEDRlKUdZ+Cv/aRc2mxn0hsizjk+IqyVL12wFKO9hBvmHjxaxcdRwANlsRBn04Zr9U4uOvbnRcWKw/UXqJGKMGRVGw23u3dlW72e3Y9+3DVp8U0qut7Km18vKAWB5KjODNwYkk+fqQNW0Y+dOGsWrC4C7cTCK4T8fe3gaedRZ9Fy/CmJLShfu6l3e1sY8wMy67FkmVcDoc7g6lVdMuuZqQPnFULDtIqNWJYnUgGw/96ATMiEMXb6b07e3Ubi9B9tXhP7EPsrH1FkBm5uvodEEEB01l9ZrTqanZSVzs7ezadT+7dt1PaMgJDB3qejxd8OZijIZsTH13s3LVA9hsxeh0wciylsGDXiAgYGhPfgvaTTYa6bfINe9TURQey8wDCc6I7N5hENm7yogfEkJIJ4aceP6QjNaJlpYb6X1MDJ5+HP5hPbusfWsK9u+j6EBmm8cpipOM/atRwwB90x8bU99ggi4dAJV1VC88SMmn6W1es7x8JXV1pcTEnIfdXkpo6HQOZD3esL+45NDbVTn8QaQJz2CJ+pbczYOJi72SgIChOByVrFt/Nnv3voTdXt6ur7m3fFFQxtryGl5K7d6ijPn7Klj6WTqZmzr+BrDqzyXUFRR2azy9TbS03Kgk5yBfPXofU+ZcwfDjT3FLDD8++xh1dhvXvfFRq8cNnj4Tu9VK9CljWpygW5flKstiGB5GwJSWl/batm0bv/zyC5Mm9WfAwFPRak1MmrgUgHXrz6OiYi0gMXDgoaXRxhzzLAte3IC5LojCqlB+2wyBkWOZef05bN12GfsPvEhu3tdMnLAYSfKMhT3OjgjCKEscGxrYrdfdvCgLg4+OkScmdPjcvHvuwWfECGJffaVbY+pNImm5UUifWGZccR0RCS2/0etpo045ndyMtltFWq2eMaee2fB59s7thMYnYjzsLZSz2Iom2EjYua3Xb9+8eTP2uiIqq77j119/o6L8Iux2OyUlJZx77lgqKrYSG3MRUZGnNZwTGjGaU4aYsaSX8X2V6xV/eb6VLx9wEDdpIqaoddjt2WTseQoJLVFRZ2A2d+/3dfWPe1n/ywFO/c8wYvoHt3m8VpY5PaLt4zpq+HHxaPWaDleSsO7Zg7ZPH6Lm/q/bY+pNkqqq7o6hw0aNGqWuW7fO3WF0iy8fvpeSnINcO+9Dd4fSIa9cdi7BMbHUlJUx54kXMZrNKDYHql1B49d22ZiDBzezctU97MlIxW73Y+jQHzD7VVBn12MwKgwZ/DLh4cc1OkexOrDlVGNMCsBSZef9e5YTN+1+jIH5SBLIcgB6XShW215AYsb0zr0hW7f+XGpq9jJp4ppGrcrXb1yM4gB0cMPLbZd5URSlw6WIWuO02dgzYwaWaieV/gmEFW46tDMkBF2/foRdcTkBkyY1bN45YiRYLAzYuYPSb76l8LnnSPpyPno3LijbXpIkrVdVddS/t4s+LTcbcfJpDJt5UtsHephZ/3c348+8AP/QMLRGPd89/TCZW9e3K2F99dVXLF++nUGDBjNp8irGjvXDz78CSYJt2yczber2JgkLXNOHqv44QO2GQkz+Bs66YxQafU3D/vHjFtYnLJCkzg8lqahYh8NRxp9LXJ375fk17Fh5kLQZ9SWC6mDdb80nxDpF5dYdBxi2fBuDlm/vdAzNqVm2DKW4hIy4k9maehlW7WGd8CUl1K1aRe5VV1Pw5puAK2lSWwuqys5Bgym45x7UkhKvSFitEY+HbvbXJ+9hqaxg3JnnuTuUDokfMgyAxGGuYoOlOQcpytrfrhI3ZrMZRfmL/PxviIw4nXFjr2Pz5pGsW7eOG2+4Hllu+cfSPDOampWFGBL8ydufhaw/VN54+YrRmM2DAYlBA59qcu7KlSv5/fffmTlzJsccc0yT/f/Q6yOx2/OBWv5YmMy+BU/hsDSu77/62yxGHpfc5BHtrvQsvi4oY0ygL6nm7h11bho5Et/JkwibfCqFfxdTeud7zLh4MIqiUDp/PkVzXSPxS597ntLnnkc7Zsyhk51O138Nhm6NyR1ES8vNVMDg6xkrJb97yzX88trznTr38hfeZNwZ55L/6gbyX96Aw9Z0GEdOTg4fffQRM2fOJDhkC6BgteXy44+fkZt3Hf1SXmflqiFs33F3i/dZfeAktoSfytLNgylyzEajbVy+amja24wd8x1m86FxSFarlblz5/Lbb7+hqiplZWWtfi3RUecjSSacdaA6JVrqQnntuj/ZuzXvX1tVBvr5cEVMWLdXNq789TdqNm5CqqkAIH2l6y2gLMuEnnceA9J34n/FFQ3HO9asafi42hRF5TGz2zXFyNOJPi03s1trURQadWi7y58fvM2BzRtIHj2WSec3v0qLqqgUvrMF/0mx+KQ27WTOvucv+KegqVEm+MIBmPq5jtuwYQOLFy9m2LBhDBtmYuu2G1CUSv75EexQv7Lq+me1GLGkP8HQ09PJyppHctId5OZ9ha9vMkPT3uC7775j06ZNDaedffbZDBo0qNVL/718EtVldvb+9HiTfdGp/pxw9SDe/b+VjbZPvag/gyb2IfJP171ODwtkS3Uty8e1Xb+9Obb8fHIfehjrhg1QWQn1awuYTzqRmGee5bXr/wRAZ5CJGRBE//FRJA89NHQm84orse3dS/JPP1K+cQe/fJJD+Mi+nHDVkE7F4w4t9WmJx0M3W/jOPBSnk1NuvsPdoTDtkiv59qmHMfi0XJNekiUc2TXUbixsNmkxJ4i8eRuJ9IkHq0LpO9splcBnXCQjZo/AYrGwcOFCkpLmoCiut4CqCjYbbN1yEmPG/oqqun5BW01iKoySF7O6qIr9ewv5/ZmRJBwXyb7Ml0iIvwaz3yBeeeUViotdsw38/Py47bbb2vV9iIyYhaZPOAXL9Zx000DW/ZzJvnWu1s0xp/Wj7OWtzA7UUe1wsrFWoVSBPz/exXF5WRBiBFUl7a193DqncwnLUVTEvqnNLwlmPu44JFli4IQodizPo86mkLmphMxNJehNGvr0CyQyORDDxXNxqAo6s5lKvwRsPhbGzU5q9preRiQtN/rhxafJWLEUPzcOLv230+88tM5iS2+/zOOjMPRvfg3HkNg41sV8S4l/GRWr9jMu4lQ0qgbLynyy1xYQclEoYWFhxMbGotPdz+6M+5FlMBph5Kifyc9LoLIqnOqqEdxxx6FEvmTpKJzOQ491w0d8RUBwPMcBWVuXYbM4sBT3wzd4O3FxV/HKK29SXl4OwHHHHddqH9a/ZR18n8DAkVzy+KUAHHuxH59v+AutJLHglS0clxYMZTbMWg2T/DWoqsqYY31RNa7vlb6qDsUGf7y9gz/e3tHhBSXkkBD0A1JxWqwEXn45IWeegUbTeOxZnd3Z8PFFj47n1ze3UHyghszNJWRuPlQ5ZN2CTFQnaLQyfkHeW9nhcKJPy432rFkO0KFlxXqLoii8duX5LHrvzSb7nOU2Kn5rvqyKj9mf0+64nxOuuZm+Z08h7J7hrPNdgtMX9En+ZGRkYLPZ0Ol0xMZewIzpexk08FUkCTQaiIjcT79+axg6bB5lZRsbrqvRuH7hIiPnMGP6XoKDD5WIPuvEOE4cE0bBhovJ+P4ZMjNzMBjWotXWctJJJ3UoYQGEh51An+gLGz7X6XVMjzExKUTPiden0WfOQGKemETwNWngp0WSJALsKqgql+6sZsUWJxND9cTXz2L65H8rWfxxOrWV7Vv6LP9/czFPmUq/H75Ho9exe+ZxZF55FfbcQ+tZ+gX7gATjTksiIMSHshZKA1mrnGh0EiMCdpN7+/916PvgqURLy43+75PvePHiM1E8sKa4LMtEpwxg8+8LiBkwkP7jJjbsc9TU4WhHueORJ80GoLQkm4LphfgHBbDlj02cOv6ERsdFRp6AxfJ/7N//Ggp1gBONBjZsdJVfNvn0ZcTwT8jKqmHr1q1YLesZOnQoWq3rx7difzEf5y5AjTRgsocQFjaUpOR1mP1KGDq0cdnp9hg8+Lkm27T+BvCDiKRDqxyZEgMw3euq65WOa5n6srxdBBzXBz7eSUi0iSSLg2UFFsoLLOz8O5cxsxMYfWLrj2mVP/6IISWF9HnzGrZZc3PJuvQyfCdOpPK330g6bTbjXr0dSZbY8Ot+nDYVrUHimhcPPVZ++tBKynItyLJEpLYYu8XzSlR3huiId7MP//sfynJz+M+HX7k7lCastbV8eMeN+IWGcf6DTzZsVxwKSq0DrX/71x7cvfwvMn/cz0rDXmKUEE4IGoshzBdNkAE50EBpXQUfLfsaWa5h5KgfMRjsgB441DpxOqGkJJrduyaiqq5X9yaTidrapr+MRmMlVquZ//3vwW5ZgzB77nKwKfR5bGK7rqc6FXLuWw4qmKbH8uuqXMpyrUgynHPfaEKjmx9HZsmqoHDuXdTu2Oz6gmtrISEBuaKCsLvv4eufZexOLSAh68Av2Ii1qg671cllT07Ax+/QkAaH3ckbN7umRyUND+XEa9K6/H3oTaIj3kNFJiZTmnMQa22tR7xBPJzRZGLM7LNY/vmH5OzaQZ/+ro5lWSsjdyBhAQTFxSFRQ39bDAu121hZsoXxhf0b9ivY8dHpqJVNrFl9bsN2SZIICckgKXkdOl0dYWG5hIXNR1WhpiaQrAMXN5u0rFZ/5s6d2+Gv+WD2h/j7DSEgwPX4Wbksm+rVeWCtf4RXVNC0nbQkjUzItWlULjmAw2bn3LvGsmdLIQvf2ckXD7lqbU08L4mAjx8F/fHIvsGg2JF0Jgg9j7+GnMzMkEB0gVpi/jseu83BW/9Z1ugeSh1UFLheZkQk+DVKWABavYbho/RsXGtj38ZiXr9xMde+PK1XF5LtCSJpuVnqxGkUHTzQ8KjjaYZMn8mulcuoLCpsSFqdERYbT9np2fz89mvYBoxEF+CHX/9E6kotqFV1aK0O5tQcj8NXYk3mRnZp87DjQFVViov7UlzcF61WJiZmNfEJ+ShKOX5+5cyYUcSAAQ+xbds2vvnmG1Ag0BzGLXd2bvXsAwfewM88iKFDXX15VatyUUttSCYtUXeNRtI07gZubaqOrJOp21kBVJC9eDerCovBL65h/9+f72NW8EVIkoSiOHGoGnQqSEicGBwAqopaVser1y5uOMdo1nLyDUMoPFBJaIwZW42CrJOIHxjabAwjpkYS8usDLI64EsUBXzyyhuOvGkxQZPtWLfdE4vHQA5QX5KMqzg6tJO2tfnrxKdItClGxsVx44YXNHlP+634kGQKOS8DpdDJv3jxGRA0iYo1CiVxNxPhEcsMfpqZm/WFn6aBOApsZmyOY6ORU9LoQ7PYc7HUVaDW+6PURGH3CMfnEEBA4Fh9jnyYJx+GoRZaNDdur/s6mdlsxukhfgk/r1+jYP3cVcvGBbO71CeTaSc33UxW+uxV7SQ3pO3ayjwDqJB0msx7/2EBqMmuY5qdFVVV+rHQCKqEmmQl6LSoqTqfC2hqFwsPe03R2aXt7bR0LXt9CeWE1tRVOJpyTzLDp8Z26Vm9p6fFQJC0P8MEdN6I4HFz2/Ly2D/Zy7//f9USlDOD4a29qdn/hx9up21+FJsqIYlFwFFfznroYVQUfVUu4EkCd1okjQs8VV5zPlq03UFm51jX4sv6ppz0/0Yc/IZnNA4mLvYzg4EkYDGHNHm9JL6X0s3RCrxiMIc6flT/u5tX0Qv4cZuKKPyp56KmpLd6rvLCWr59eT6Ixh9z0Yqr8Exi/+n+EnvECmkgzq20OcnZVERLry8nXDsUvxEjRO+9S/NJL+J/1GsZ+wYSc13rljPb687Nt7FjqGkl/zSuTPbaFD6JPy6OdfPMdLP34HTb+9pPb6mq1pSQnmy/m3sXx19xM8qixlC88gH1/BeFXdqxzt7KkCN1BY4v77bvLwa7gyHC9UZWR6K/pQ7o2B4vs4ICmBD+zH9q6OjQ2XwaHvo6toozqhQdRUckYoLAvfQeGgDxkjR1nbQD2mhB2R5px6Gv5vt9gzs1byukDN2Kvy8NmK8HplNmx8150ukDGjvkJgyEEh91J+qoc8g9UkLmpGKVGZbCPzA+PrUMBFozwYcMwE752lWmDXZVA7XYHOl3TkjFGk45z7h6NX/AkMn7dwO/flLBu+B1M2f4DPs5TOP7iIfjc2nigrrFvMjidqNZqVGfzY+I6Y9r5g9mx1PW4uX9LCX1HRHTbtXuLSFoeIDQ2Hmt1NWW5nrtenl9IMJHJ/Vj93VfsWb+acX1nd2zaTb3E4aMwmEzYrbXojU1fPPR58BgsWRXY9lWgOBSMsf6c29/1xm7FihUsXryYSy69BH22g/zHVgMQ/p8ROLJr0MWamT49nulMbXLdpKWbqVVcbbDy+FOpTrqO6aGu4QtffHEVIaHbqKsrpLDoZ2Jj5rDw/R3s3VCEDjg+QIvkD+V1DswyVCrg0IBOhWt+r2SHTWXHisWN7ifJcP1r0ynNreH3d7ZxwjWu6TP9ThjB3gNbKD7og7zlCzT+NnTN1Hn3mzIFY1oatu3z8RnevbMlrnhuEu/d8Tf7N3tn0hKDSz3EuQ8+Qf6+DA5s3eTuUJqlN5o4479zqSzKJ335MvymxRB2ReNWlqqqlOXnUWdreR2+E6+/lU0bNvL5G80/CkuShCk+kKBp8YTMTMQ3NaSh5TJu3Diujj8D6zM7qfz80AIa2jAfnJV2qpYcJO/5tc1OcB7sW/9mTYVvsXPB1kMlpmNjR6CqWoYO/YTYmDkATLmwPxqdRJqPjCy5pi8FGXRM9dMy2SRjrJM45+9qfG3NP4zWz0QiKNLEpHNTCAg9NBr92MsGceotI0n+4Vui7jqO6mXZ1BU1fQMa/9abGAZcgmVd95ZHNpp06Iwy+ftanzjuqURLy0MoDgdlebnk7NrZUPbFEw07cRZbF/3Gh3fchNPpxFZdjd1qwVl3aDyVzseHwVNmMvmiy9DqGi9uodXrCRw6iupOdKUqlXbs2w9NUfE9MR7nwWpy71vesM1ZaHV1av2rFTgtJJA1VfmACk5AI7Gv2kqS2YiPaS8WqxF/v0P9RraaOgZNjCYup4qDdeuoGPY0Go1Mn/W3ElA6mN19dAT2NfPUlAH89vY2sneVUHdYrvarrzYtyRJ9Uho/3lWWWPj5tS2cdP1QAsN8qFmTD0DgSY078xWrlbrcTeiihmDPrUbfjkUsqpYuJffOu4h79118BrX8tjco0peqkvYv8upJRNLyEHqjCa1WR3HWfneH0qpxp53DuNPOYcVXn7Jl4W9YqlwTiSWtFoPJTGB4BBqtjoM7t2KtqsQc3HTll6uvu75T99YGGrHMCMDP30zkWNcvePbcFY0PUsFZaUMb2LjfzFeuz2KK2tALf+qG3fw8qh+VFUsIDBhMecU6ZElDXcVwvn12A6oCljHBlNpWEqoFFYW1mj1ExIwnKcqXKD8fNDoNJ13XsZWAaivsVBRZSV+Zx6hxkZhGRTRJWACawEAc2b9hHJCENtz1KO2otLc6qLfi++/RRkZiSGj9zeCYWUlsX5aDqqiuRV+9iHh76EHsdisvX3IORrMfN7z1ibvD8UiPPPIITqeT0NBQqqur8ff3JyAggIOZB7DYbQ0tLIPBwKxZszCbzcTExHDX7oOYNRpi38viu0EGtsTo8ANi9CXcabuGwYNeJH3XAzgc5Q2Pdg19dof/TquAFMj12nc5JtCP99KaH+qgqirW6jp8mqnk6nQ6+fDulYw8MZ7YKju1mwvpc//4JscVf7cb66qCJtsNg0MIu6j5VlT1X3+ji47CkNx6ffyc3WUseG0Lx10+kIS05t+Yupt4e+gNFAUUBWtlBRt//ZHhJ8xyd0Qex2QyUVlZSVGRa/ksi8VCQUH9L/Y/yUUFm83GV199hcFgoOz0C/mkoII+5U4uL7cza30dJy5X6XNuIpEhS3CURBIaegKO7V+hKMtABVWR0KADVYveHILJ1Jfy8j9Bgqiok0izmjglPLDFOD+8fwXVxTZ0RpmrX5jaaJ9Go+H8B8ZiMGldfWWnJuMoKiLz7HOIuPu/+B9/PADWjc33ZWnDW67WYJ40scV9h4tKDsBR52TL0hyPTVotES0tD1NXV8ebN1xGQEgYFz3euSqinm7dunX88t23HD96OGNmn9Xh8ysrK8nMzCQqKoqNGzeyevVqpk6dyuTJkykuLmb/a2v4STlUtRM/f9KnnUK/L3KJrDhspKYMN7zmGqxZUlLC66+/jk9FAsaqaGbflAafpGMcEETonENFA3fsvIdtNQq/G67hzUHxLY6G37Mhn9/e3EGklMP4kN1EP9L6xO2cZ1bjzK8g7PJYfAYOaNhur7WjNzVurRW8tgl9Hz+CZndttaGf520hcWgoA8ZHd+k6PUUsbOEldDodo2edTlleDqV52e4Op1WOciu5j6yipoUWQUv8/Pww6HSExCZ06r5OZzoJCQrh4eFMnTqV4cOHM27cOABCQ0P5XbOp4ViNRgNVlTwb4cvcRyfRd9yhPrbhp/hTUbEZgJqaGsxmM0NHDmLI1BhiBoXiNy2WwFmNE0NpyXK22IJZW1nTMB2xOX1HRHLCtYMZ7LsXtM2vw2hxKuRY7ZT8kIFabEfW+jRKWECThAWALKHp4NzP5px0bZrHJqzWiMdDD6TVG7FbaslJ30lwVMuLnrqbbNajizWjj+lYjfv+/ftz5//mdvq+6bvuQ5Z1jB2zoKHv6nDDRwxn27Zt3HLLLdhsNv766y8CAgLIstdRnmsDICEtFJ+o59iydSeTJq6muroai8XCyOMTCAgIBCBgZtPObJs9m9F8zIVjbsKkbflvvuJU+OOd7UQmncppt45osv/tAwXct89VX35DZtN6+ocrfvNN/E89FX1kJIpDwZFbjTOq63MHN/5xgKoSK5PP69/2wR5EtLQ80IjjT+aa1z9gyLSZ7g6lVbJWJuySwejCOl6dIn35Ur5+vHOLhg4f9hFm81DWrJnd7P4TTzyRO+64g+IXNmH/I48TTzyRTXUqU9fsYrMZkGDgCetQVAeDB7lWWrbb7eh0OpQ6+OLh1ez7Yz9Vy5sf7PsS/8d5m/e2GmNVmQ1JgqRhzU9kTjAdqsjgPynW9UFQ09aTYrVSPO8Nyj7+GHB9z0OuGEzAyV0vnbx3YyHbluVgrfW8em6tEUnLQxXs38fHd9+Cw96+apfe4qvHHuDbpx7kwNZNZG3dhLWZsjJtMRoj8PVNxGYvwmLJavYYxaHgrLTjrHZ9/8YF+HJ3UhQR6dWgwsoDNdxTdQY+/iMBKC0tZdDw4RQa9FhqHFQuPkjVX02Tlv+wdWyXhuFQlFYrzgaE+nDxoxNImxbX7P4gvQ6DJPFSahzmERGE3zqCPneOaXKcbDTSd/EiIm6/HYCK3/dT8u52FIeDwhdexFFa2vo3qxWjT0lEAvZ08+DVniYeDz2U026jpqyUsrwcwuIT3R1Ot4lM6oeskRkz+2xSxk3oUA2x8oUHQFUJnJngGrmuOtHpml92XqmwIckSxoQAyn7Zx3LnDi6aOpVP9DIOq8JK84nst9RS5XRSV2fn4jpfHDo9bMjg1UQz6zIqufjG4U2uOyQgAANQ4lA4YLWTaGo8HsxeUINtbzmqU8V/UsuP9iMDfPlsaBLjAlyPefqIpo97jqIiVEWl5O230UZGEHrFFUhmHWqdkz3HHg9VZWhDggmeM6fd38PDxQ8MpU//YAw+3pUGxNtDD/bKZefiHx7BxU++5O5QPELRu1tBVZtMH2pNxe/7+WTZNxRqKwEILBpOoH8wr8wKxqmqlNkdWMG1JJAE/Yx6vgjtw3cvbGDyef0ZPKlpuaDnMvPYVW3hjSGNH9GKv9mFdY2r1aKN9iXy5qZ9WR2x99TZ4HTiKCpCFx9P0pfzKZmfjmVDEU5LFpF3z8AQGdmleyz5NB1FUZl+0YC2D+5lYpyWFxp92tk47TZ3h+Exwi7v+Jp9vsdE47cjgMJyV9IqD9vI9JPPIVGr46/ymobjAmurWTAgmuTkZFRFJTjSl9Kc6mav+X+JzS8rf/go/K4mLIDoRx5BdTqoWrQIU/3b0YBT+2LZXITGP67LCQugYF8FNRV2uKjLl+o1ok/Lg42dfRYVJUV8eNd/3B1Ki+qKasl9dDWWXZ3rW3HY7ditPTcHTmvWM+eWK5g7dy6TpywiKXEjstPEO4MT6aPXkGYysD4ljPPWLWLBggWoqmtay7GXDWLYsXFYdhTjKLE0uuYrNy3m6sf/ZuV3exptD5weT8wTk4h5YlK3xO6TNgTT8OHUrlmLdcdO19dj1BJ0ZgrGfs0/FndUythIVBXy9pZ3y/V6g2hpebDty/5kx58LASjcv4/wBM9bbFPjq0cb7oMutHNr6n32vztx2G1c9uzrXY5l1epTCAwcRWr/uY22F721BafFgdx/IIaSgfQbGoNBp2X9BFfL7Z+uhvLyclfSkiRCY8zs31qM9pvdGGL9GrXyViYaWDzUxICdpTSdfNO9LNt3YN+/v9FcQt8REfh2U0mZoTPiqCy24rB53jJ2LRFJy4Oljp/I4vffICwu0SMTFoBs0hJ+VedWebFUV9Kn/0BiBw7ullj8/Abg79/0EdI0PBynxUFdxs1YCsubdDyPGjWKUaMad518nV+KNbOEwcPCGHJ84xcht56STFlRGedeOYie5igsBB8fjGk9s5KOLEuE9DHjcIikJXQDjU7HwIlTiemmX+qeUvJ5Oo4SCxE3NH3b1pq1P3zD1kW/MfG87ulQGTTw6Uafb9p0BQZjHwaMegiA1BATWn3bPSJbKmu4YWcW+MExOgNvfb+HkHMPla0ZlRLJzyld709qD+v2bVBTg9bfv8fusePvHAy+OhLTmh9T5mlE0vJwMy6/1t0htMkQ749s0rV94L9MPO9iBk05ttkKpl3lcFRTUvo3Wq2ZAamupBU7MJjYgW33BSmqigwoQHitA3vWoT43u72C/QdeZ7XxYsYGB5Pie6jz/eB/bsGQmED4Lbd0Kua8VzfgOyYS/9GHptYEzJ6NUlOL3IPLy2l0MtVl3lNbS3TEe5GqkmLevvkqj6tuah4fTdCp7Z+863Q6WbZsGU6nE2t1JW/fdCVl+XndGtOatafi75/GpIlrURwKJR/vYO0n6Sx8b3ub596xO5sQnQZ/jczT5pCG/rpdux7mr79HcPDgWzyemccT+3IbnadaalEsluYu2Sqn00n2f//CebCGyu8aj7SvWrgIbYSr/6pm7VrKvvyyw9dvi86oxV7b+lQiTyJaWl5Ea9Bj9PXF6NuxuX6eJicnh2XLlhEaGkq4ny9GPzM6o6HtEw9T9N42zGMj8Wlhvb+kxFswGMKRZRlHtR1rZgUFJVYOWFWqy62cdutI5mUV8mVBKYtGN17pRi9JhOu13JscjXNDGU6L6xe6vGItrvo3Oh4rSSekdAwc1oUW9+abHfoa/uEsOtTKCbu38aj4qkWLQIKQSy8h74H/oVRVEXT22Z26T0v8QwyU5jY/vMMTicGlgltUVlbi34V+mrxn1uE7KgL/qbFN9mVlvUdIyBR8fRu/vFjyaTrbl7laR6feNJSVwRJf5pfy5fC+7b6vw1HN1m23cGvljaQ7XFVQXxsYyxkRTSu0dkT1unxs+yoIOaf5ycuKw0HGjGNRyssJPP00ojqxenZL/v4qgx1/53DFs5PRaDzn4UuUphE8SlcSFkDU7aOaTVjbd9zBgaw3sFqblvWZekEqUy9yJYVf3tnKOVHBfDm8L6+//jq//PJLk+NVVaWu0tZooYzy8jWUl6/m5DAnqBKosLa84/Mn/82eW01dC4NZAfYedzyG1FQCzzgd8/QZXb7f4QwmLc46hepS7+jXEo+HgkdY9c0XbPptAZe9+AYGY/vGfFUtz8GeVUnI+QNwOKxotUZ8jHGEhkwnJGRyk+Nr00sI/DOLKK1EXq3CpkVZDJsRR21tLRUVFTgcjobFSxWbg9yHV4IDDAOCCLvE9QY3MHA0UVFncGvyIAYs3kVViYXzH4il7MsvqVn2FzEvd27KVfCprbf2gi+8AOOgQfjWj4y37d+PLi6uxSKEHdF/TCT5eyvQG70jHYiWlpf74+1XWfLRO80um+VNYlIHoqoK2xb91u5zHKVWHGU2srLeY9lfI6is3EZS0k0MGPBYk2Ote8qoWpqDanGQFmMkOtTAoEmut3Q1NTWkp6fzyCOPMHfuXN555x3yn10HDpB8tfgfe2hgp1brR2r/B5FlPcEDfqay/ACZm4uw5+RQl5fb5L7dxe/MC6hcb8CWV4X94EEyZ5/WUK6mq5wOhepyG3aLs1uu19NE0vJy+Rm72Lr4N0oOHnB3KF0SM3AIFzzyDGnHntDuc4JmJVPnX8i+je9g0EZgNqdQWPgHGRmPNzm2dmsxzjIrMY9NIiQ1lONO74tO72pZXHLJJcTFxWEymZBlGaNGj+pQ8Z3Shz73j8fQx6/RtfLyvubPJf2w8DYJ018iuI+ZiFtuIfGrrzr99Rd/sJ3Sr3e3uL/ohY04D1ZT/NFO9LGxhN9xB0Fnntnp+x3ObnVSmlPDgnmbu+V6Pc072oNCi+Y8+RKVRYX4h4W7O5QuCwjv+IDNwujPwWIjufhJQEtR8W9UVGykX7+7Gx0XfHo/1q1bx96//mLSaY3nBsbHx3P55Zc3fK7YHOS/sB59ZPPVQTXaQCTJiCyb6T/s5kYLsXaWPbcaydh8WWaAwPP7U/lLJmHXDXN9PRdd2OV7/iMiwR+dQaamzDsm54ukdQT4J2HZrVYcNium+nLB3urT+29H1mg4b+6TbR8caMfsl4zjB5W8HWuISL6ShP6B1FXZ0Pk1HkaxdfUmaoqrmDB6PMig2BW05qbVQmWDFgkJZ3nzv8ThYTOYPq318V415Ta2/HmQ0ackotW1nIz+EX332Fb3O3NrcBbbwOYEQ/f/2l708HisNd5RwVQkrSPI148/QFluDpc8/Qq+gUFtn+ChUo+ZjKxp349mYOAYyivWYewfjHVbCdZNRVg3uZYXQwOSWYc+2g/f0RGcf+LZVP6eCVqZ4ne24iizEf1f17ioWofCHouVND/XyPOou5pWEW1N1Z9L8Bk8CG2YazmuOpuT8kIL1po6zIFtJ622mCZE46iwNZl5UPrZZxS/9DJJC35CG9z5yg8mfwMm/46NlXMX0ad1BJl2yVXo9AZWfPWZu0PpkhEnnorDbuPbJx9q89iwsBkEB40n9KKBRD82gbBbh+N3cgK65ADQSqiVddh2llL60U6s6SX4nZCArJUJPCWJwFMOjeP6v11ZnL3JNRr91h0HiPxzE8/va7lj3W4vJ/+XZVj3lKHa7eTccgt599/fsD8wwkRBZgXfPbehC9+JQyzrCqhdnY81vXEJIN9x4/AdPx45MLBb7uMNREvrCBKZ1I/wxGTyMtLdHUqXWaursdXWtHmcn98g/Pxc1RZkWcYQYcYQYSZg0qExXHWlFuw5NZR9upPqZTmggdBLBmEafGg0/cP9+rCx0jXeKsvqeiwcE9S4A/5wW7deRzV7GLz+I3SRMRhHjSL0+usbHaPVS1QUWnn12sVMOr8faVOajitriaOkhMJnniXywbnIej0lb8zFMPxMfFIbt6YMiYn0ee7Zdl+3NVWlVvyCjW0f6GYiaR1hpl1yFVUlxe4Oo8vGnn42xVn7yd2dTnRKatsntEIX7IMu2AfNDcMo/z0TpdSK5Nu4LytMr+O40AAArgz0oaa6mgmtJK3k5DuxxuQSEuGKLeGdt5scE5MaTEWha05lSHT7lvwq+2Uf2gAjSsVmqv74g+DLLsWQkIBtz0580nJQ7Q4kbdfXPPy3iqJafn59K8ddMYiQPp49TUwkrSOMf1j4EfEmUavTYwoMZN2C7zg56XY02q7/qBpj/Ii83FWXyllpo3LpQfwmxSDJUqPjvtyezjafYIrsdYTpm69esTP9LlRVIX9lKqqvlqGTIpCNjVspUy8YwOTzUpH/df3W2DMrcfpZCZ1zIgEnnujalp2N1t+furIUij9J73T9stb4h/pw7KUDCW5ncnUn0ad1BFMUBcXhPbP3DyfJMqNOOQOn3c53Tz/MwR1bUZSWBz86HBZKS9eQmfk227bfxa7dj6EoLX/tjnIbVX/nYNnaePksp9OJT24WsgR7a1qe1qKqYJL6Erw6l/wfd7B7ytRmj+tIwgKIuH4YoXMGNr6Gjw++410j4TF0vVO/OZIkERbnhyR1LF53EC2tI9j8h+7GUlnJZc91vZRxd9q8eTM6nY6BAwe2elxwdB9mXH4tf3/xMQteepqIpH6cfuf9jY4pK1/Phg3nAv+eESARG3M+JlPzy68Z4vyRDVocxY0TkyRJJDisxDhtRBlarhHmZ+5HQMA4bP2DOLiikvCEri9k0RJtSAjh991H7gPLkX3Fr6yo8nAEy1izgtqKCuqsFoL6xJI8YrS7QwLgtddeQ6fTcdVVV7XreFVRWL/gOzI3ruP462/FPzSsYZ/DUcW6deegImEyJWIy9cPP3B//gDRMPk2X/2qvxKWbmRhk5qO01uuE1dnq+OLKTxgYmM2Il+/r9P1a4yixUPFLJoYBwRj7Bzc7tuxIJJYQOwr1G3MMAO/85yoCI6M9Jmldc801HTpekmVGzTqDnF07Obh9C4OmHKpyoNX6MW5c0woNXXVsiD+SopBrtRHdSq0ve2kZPhoZBvXc99Z2sArrvgoCTkw8ahJWa7rc0pIk6SbgRsABLFBV9c767WnAG4A/rsq1o1VVbbaTQJKk24GngTBVVdt89SVaWh3zz/LteRnpGM1+hPRp/6v3nrB9+3YSExMx9WAJ4db88ccfpKSkEBvWh8LXNxFwclKjoQSXbt7Lr6VVDZ8fmDwEg6ZxX1JZ2Vp8fGKwr3VQvmA/VVP6MOhEz1x8xFv1SD0tSZKmAbOBNFVVBwHP1G/XAh8D19Zvnwo0O0dAkqRYYCaQ1ZVYhJbJsowsy/zyyrP8+trzbo3F6XTy888/s2XLFrfFsH79elauXAkySDoZSXfo16CqqoodWQcbHV/XzN/1bdtvYsuWazCPjiLwlEQSjun8o+i/WXftIve++1Ds9k6dv++00zhw6WXdFo+n6erj4XXAE6qq2gBUVf3nVcxxwBZVVTfXby9p5RrPA3cC33cxFqENZ97zEDofH9JX/IVvcAixqa13hPcUVVWxtKOW+rZl2RRkVjDjku5dqqt///6kpqYiG7VE/GslaEVRmLN/K7NnzyYuLq7Fa8TFXkF29qeoOgfFy3MoX5jFiLnHdEt8ef+bi6O4GEmWURwKhW9txnEgGykihKibxyG3UV00YPZpaMO8Y2Wdzuhq0koBJkmS9ChgBW5XVXVt/XZVkqTfgDDgc1VVn/r3yZIknQrkqKq62RtetXq7oChXa2DBi40nIl8970P8grpnxeK2aDQa7rzzznYdW5xdTUlO16uC/tvpp5/e8LF1TznW3WUEnuR6yxgQEMBNN93U5jWCQ6aQc+BT0k+eiGHYs4SoErbsKgwxLQ9IbS/fSZOQtFokrRZ7ViWOA9WoagAUOLDvr8CY3Pq80pDLLu1yDJ6szaQlSdJCoLmaIffWnx8EjANGA/MlSUqq3z6xflstsKj++XTRYdc11V/juPYEKknS1cDVQKt/AYW2DZg8nZ3LFjd8XllQ0GtJqyOmXtC1kfDtYd1dSvXKPMyT+zR0cpeVlWEwGFrtc/Mzp+CU7VRfaKKkzIfgXBvBhTVozDq0gV2bChN+w6HpQIY4f8wnxVH1w3rQ5mJMblqRtTmO6mosq1bjd2z3lmb2BF3qiJck6Vdcj4dL6j/fiyuBzQBOUFX10vrt9wNWVVWfPuzcIcAiXEkNIAbIBcaoqprf2n1FR7x3KyoqQlEUIiK6Z2n3rrAX1FC1MIuCU+NZU1HLpTGhPP/88/j5+XHllVe2eu6+zJcJCBhBoP946mxOSl9Yjzbc1CMj1veddTb6xERinm7ywNKsvIcepuLbb0lZuwa5G2YTuENPLWzxHTC9/gYpgB4oBn4D0iRJMtV3yk8Bdhx+oqqqW1VVDVdVNUFV1QQgGxjRVsISes5nD9zJ+p97vmtx6dKlLFy4sMfv0x76CF9kPz1b12bzZ2klALNnz2bWrFkNx9gq7Tgrm9bWMr5bRNkFj1BVYsVZpxB62WCCz++Z1qE+Lg6fQe3vg4y48w7i3n/PaxNWa7r6Fb0LvCtJ0jbADlyiuppuZZIkPQesxTVU+WdVVRcASJL0NjBPVVXRVPIwEnTLQgltKSsro6am7QoOvaWuoAbZLpHuU0e1w8mmTZtITU1l68/F7FpdQKpBJsggMfzJyY2mufgMG4ZqtbDow50ERZiYfvGAHosxpoOVHGSjEWdpGXlz53brcmOeoEtJS1VVO3BRC/s+xjXs4d/bm21z17e2BDc676HGjx52ay1avbHbE9mcOXOwd/J1fk8IvyqNfXvzyM8upKislPT0dPR6PQHmFNd+nYRehdeu+5Mb5k1vOK/8i8+pKy3DNvFM/MOMWPeUUfp1BuFXDkEb0vUSzF1V/fff1KxY6e4wut2R13YUus3bN15J8sgxHH/dLd16XaPRiNHoWXWbzv8+h6HDg4jw9WXcuHFMnDgRvV7PpLNTyN+Qx5J3dqL512D06CefJGtbAWULaln9fSYD7h4JQPFXuwg6vR+GcPdWTIi6v2emFbmbSFpCi0bNOoOkEaPZ+fdS9q5fxYwrrsfH3PVX+p7IJ8DApGA/CgoKSExMRK8/lKEiR0Rx3oioJucYEhMJDwiHBasB0ISa0Jh11GVWUfTcBlexwSuGYEwK7HJ8+c88g33/fnzGjEUXFYk2PBzToEFHZJ9VW46+r1hotzGzzwJg25KFZG3bwh9vvMypt93j5qh6huyrw1lu5Zflv6CqKjfccEOb55R+9BF7V2QiyRMZfXIiRl8dxhuGU5teQsXv+3FW2MDZPQUJyt57H5xOahYuarpTpyPxy/kYU3t+iIgnEElLaNPUOVcw9rSzqa2saLTd4bCj7UQVzffeew+r1cp1113XXSF2mbPcRglVjBgxgrS0Q0MW3skuotBm5+7kPqz9KROfAD2DJ7kG6dpz87Ds2Y9+4ET0Pod+lUypIZhSQ7o1vuRFCylfsoTahYtQrFbq8vNRsrNBrwONFkd5ebfez5OJpCW0i4+fPz5+/g2fL3jpaQ5u38K1b3zU4WuNGjWK2truH+neFZUzYzh71y5OWLeZcfVLzwP8VVpFcZ2rmKB/uA/Gw1bDibjzDso/Hc6eyJnsfHcXaVOuRtL0TJE+fWQk4eedB+ed1yPX9yYiaQmdMuKk2YTEHJqZ0JFW15AhQ3oqrE6r3lGCSTJw5llnNdr+ftqhyg39xzSeGCJJEvL5UwkLew/572iK5qmNRrO7m6Io2LZtxyfN877fXSHKLQudEtU3hXFnnAtAdXkpr11xAesXfMfGX39k18q/3Bxd+3388ce899576HVVXLFxFSNCG8/rq1yWTc6DK1Fqmy/dvGfAKnwS9mKdYOfLrclUFB8qaeOotFOzqbDZ83pD+eefc2DOHKx797othp4gWlpCl5n8Axky/QT6j5/EV4/eT01ZKau++YLwxGROuPY/SL0wYLWzEhMTqauro8ZXodqvjn9Pa/MZEIyjsBaMrq8hZ3cZeh8tYbGut6iWfQ+QW5iDrczVIvv4vrUATL2kH1FZtVh2lOA7zD0LjQSedRayrxljcuvVV72NKLcsdCtFUdizdgV7165BlVQGTT6W7595hLQZx5M4fBTxQ4a5O8QWlX67B8lHQ9AJzdeVB1j62S5M/npGn9z4mKL9hcx/ZCNotCCBpJW49oWpOEos6CM8f4UbTyTKLQu9QpZlUsZOJGXsRMA1qr7/+InsXrOSgv17iR8yjP3bCshYl8nMS8e1cbXe5Sy3INuaLmZhdSpMX5vO5CA/nji/f5P9iuKgtOQlpq79ChkjtunnMPiJO5G1MtXLc7DtqyTq9ia/e52mKApKreOoLb0skpbQo/RGE8df+x8cdnvDdKA/3nyZysLtxPS7hQETprg1PqfTyUsvvYRer0ej0TDnnDkN+3KfWI0hIQC/c1JAhY2VNaiq2mSZraqq7eRWfcvA358lIuLkRvuMyUGodUq3xlz+7V4sW4vo001FB72N53Y2CEcUrV7fMHo7aeQsAiMHU1lY0LD/nzr2vU2SJCwWC0VFReTn57Py80WoTlcsviMi8B0diV6WuSE+HAc09HmV5dfgdLiOCwgYSt/kewkKmtDk+qrdibOsaYWIrvCfGoPfjLZryilWK5V//NGt9/YEoqUl9LoZl4yFS8Y2fL7gpafZs24VAydNZ+DkafgFhyLrtJgDe74woSzL3Hnnnfz444/s3rmL7KxsyvcUEdQ/goDjEhqOq3EqFNkd2BQFAxK/zNtK2vRYBk/ug6LY2bP3cSyWPaSkPNDo+qZhYejjunfqU12xBVtGOcqE6FYns5e89z4l8+bh8/vv6CK8f9Xxf4ikJbjd0GNPYN+GNezbuJaMNStQnE50RiPXvPZ+QwusJ0vmaLVaTj/9dNaFr2HhHwv5dulPXN7/ikbHzAjxZ2+tDUmSkWUJU4Aeh91ZH5ue0aO/xeST0OTakk6Drps74usKa3EUW1xrXLXybQm56kpMo0YeUQkLRNISPEDMwCHc9P6XAOTu3kmd3Y6t2jXe6fMH7sRht3HxUy/3eBwOjYIVOwfzstmzZw99+/Zt2JdsMvJk/0NLr40/PZmdK/JwOhU0Ghmzb9/mLtkj/CfF4D8ppsX9jupqKn9aQPB55+I72jPWuuxOImkJHiU6pXEhvWHHn4zDZuWHZx/H4Gti4nkX41Sd5O3NQCNr0Gh0JKQNa9I53hkJCQnoJC2KqmCz2fjss8844YQTCApqupCEzqBFq9Nw+F0zMh4nIGA44eEndDmWrij74ENK3noL/+Nmog32vNr/XSXGaQle4eeXn2HvhjXYm5mzmDxiDKfd9UAzZ3Vc8Yc70IQa+bH4b/bt20dSeBwXnH8BcoCe5w8Uck1sKOYWysGsXDkTP/80Bg9yVRl1VNqxppdgHuMqa6PU2pFN3TdMofSHPdRuLgRFBVmq/y8ga0BxuFb0kWUkowbZVwuyhKzVIGlAE+RD4AmJSLLnroLVUzXiBaFXnHTT7Zxww22HJiTXt6wkrY5jzptDxtqVrPjq0y7fJ/TigdhH+lJaWsrxxx/PlMJ+VPy+n921Nl7OKuCHwooWzx0//o+GhAVQtSiLigX7UBSFmk2F5D62Fnt2VYvnd1RddhVYnGBXwOYEmwI1dShl1VCjolbUoZTZcObVUrenkrrdFdh2lGLdWkrNilxX6RwvJFpawhHhmyfmkrlxHUgS59z/GLGDOj9JuKSkhPnz53POOecQoPFFNuuRtTJF9jrC9E0Hn/5DURxs3nINQbE34uM7kDC9DqXMhjbEB8XqoGppNn4z4pC1PddWyLzwIqzr1x/aYDKR+OV8tLHx4FBBcg3D0Jj0yDrPbrOIlpZwRDv9zgcw+PqCqlKQuadL1woJCeHSSy/ls88+I7PoYEOSaS1hASiKlSfKRjBhk4NLP/gKW/quhlrxslFLwPEJPZqwAOLffYewu+/GZ+IEMJvB4cC6fQdavRatSYfWR4cuwOjxCas1oiNeOCJIssyN737RaNsHt99A6sSpjD3t7A5fT5ZltFotmg7Ux9JqzaxnGE5Zw3ANGPr2/kRl2WAg9JKLCb3k4l6/d2/x3nQrCG3Q6PVs/v1nSnNzOnyuwWDg2muvJSnpUD2t34sruHnHgRbP2VhZQ5jeyEvcxrUzHeQ+to781zY17FfsDreWqjlSiKQlHLEufORZTrr5dr5/9lF+ePaxTl3j008/5ZtvvgFgWWkVS0qrUFWVOpuTqlJro2Nf2F9AiVNHamgaB3PepyLwLxxZVdSsc60/XPVXDmVfZeCo9pzl07yRSFrCEUuSZWJSB9FvzHiMfn68dtWFVJeXtnmeo8RC7uOrsewswelwUFJSAsAZkUFEGXWU1DnZvPggyz7f3ei8h/r14ZnUWAYPehadLpDKcX8iHVeDT1oYAH5TYgm7Jq3XqjNkXXsdVUuX9sq9epPo0xKOeBPPnUNJzkFqKyowmf3bPF720aENNlLy/R6GmPpQO8rVmT7C35efRqSgkyUCpsdiralrdF68j4F4HwMAw4a+x9q1s5AH2pD1rn4xWStjiO2dJdgcJSVYd+7EvjsDpjSupKFYHZR9tZuAU/ui9fe+8jaipSUcFUL6xHLaHfexdcfNHMh6u9VjZZOW8GuGQpWd0CoTxxxzqASMrn4wps6gwS/40IKzC4srGLZ8G5m19Y+MpVZUSx12WwHukHff/WC3E3JV0wXdrRllWLaVUP7bPjdE1nUiaQlHlerqHRw8+F7D5+UF+S0frNAwiLUtSSYDKSYjIXrXw0vhk09hsxdRXr6xK+F2WtSTTxD7xhvN7jPULx5rXV9EzWbvezEgkpZwVBk69G0GDXoJgKztW3n/tuvIWLuShe+8zt71q3HYD+sklyVkQ8tDHkpyqikvcE0rSjIZmT+8L/71U3yiHnkYgIrC3h8EXfDEE9h2Z7S4Co9k0GA+Ph4pQIek974UIPq0hKPK4dUYYvoPYOJ5F5M4fCSL33uDHcsWE5GYzMk334HJLwhUFV2YCYAPP/wQg8HAueee23D+1qU56PQyE87q1+Q+Gl9fjHJfzKZD9ytfeADV5iTo5KQmx3enil9+RbFY8B01stn91X/lUP1HFuE3DkMfbe7RWHqCSFrCUaegYAEmUzJ+fqmMOuV0AK557X3SVyyjojCft2++krMuuA8UUIKNfPf8BoL7hmL2MzW6zqRz+kErT4991t5GRcqfWCzF+PiE4sirQbE1vxRZd0pZuqTV/ZWL9oOKVyYsEI+Hghs5nU7ee+899vbyunwZex4jI+MRAPbUWHl0r2vwaeoxkxl50mmMO+M8glMSkc06bME+FOyvJMDSl6lTpwLw2oECBv69FQtKazmL/OS3KA6dz4oVY1m0OBnr9M2EX5nWw19dyxzlVsoX7AO9jGGA95asEUlLcBun00lVVRVVVd1X+aA9Ro/6jrQ01xvET/JK+CCntKFCqlavZ9wZ52LqG0z0feOIOyaaqOQAKostDef7azU4FJXyMivzH1tL0cHm40+JehxDcYqrQ98JZQv2UPbLPhSHs0e+rqrVq9lz4kk4bU2rNzgq7VQuyqJmTR7Rt48m7OJBPRJDbxBVHoSjnkNR0LZSzrmiyIIkg6Uqj+1L/mDyxVezrdqC375qfntzOydfP4T4waHNnqsoChW/H6BmdR6KxelqJehl/CbHEHBsfLd+HfsvuxzLypVEPPEEwafNPhSD3UHhm1tRyqxE3j22xydtdxdR5UEQmqGoKnIbwxoCwnzwD/Eh/e8lpP+9FBmVYf4m4geHMnZWIjGtPGrJskzQCYmE3zWGJXaVsigTumhfZJ/u706WQ0IAsG7Z0mh76Re7ceRUE3zRQK9JWK0RHfHCUe2+jBxMssR9ffu0eeyUiy5n9Bnn8ejc/6HNy0Jf6Zre02/0e/iHhrV6rt6oJWJgMGVmHUPOa7rga1eoikLOf/+Lbd06wu+5m+ALLmi0Xxvli49WwpgY0K33dReRtISj2qbKGoJ0rf8aqKrKgtc2k7unFEuNA9WvCltwOLbQKLSVJXxyz61c9+bHbd4rLNZM5uZiFEVF7sYyxxU//IBl9RqMI0YQcnHTkjSB3fwY6m7e31YUhC4Y5u/LSH9Tq8eU5tVwYGspdRbQylp8LOPA6AsGI0p4H0LjBrJrxV9NzrMfOMDuCRMbFkxNGBJKZbGFA9uKu/VrqFq4EP+TTiL2+ee69bqeSrS0hKPaYyktL8X1j5BoM5PO60vW9hIi+/pjCuiHYhwKWifLlvxF9oYNlOXtRavXkzzq0CK02rAwdLGxWNN34T9zJsHRZiStxM7luSSmtf442ZqqhYuwbNlC+P/dCkD0E08iGw2dvp63EUlLENohbWocaVMbL0VfV1dHUVERxmHD2Pn1Byx46WmGnXAKky+4FADZZCL48suo/Xt5wzk+Zj2VJY3rcHVUxS8/Y92+oyFpaczduxispxOPh4LQCYpDIe+VLVzhMPPE3ixm3/sIKcdMonh/JvMfuocDWze7DnQ4qPz1V2z7MgGI6R9EZZEFm6Wulas3Zc/Lo2bNGtc1nn2Wvr/+0u5z819cT/FH2zt0P08mkpZwVKt1KNjrB5Z2lFRtx6rRURIcztrVG6mtnoDOPIb8vbtZPv8j3r31Gvbaa/CbMR1tiGtYRHTfQHRGDQ57+waYVv7xBxnTppNz2+3k3HZ7p+L0GRCCz4CQTp3ricTjoXBUO3ZdOqE6LT+MTOnQebJWJuCYPqxM8mdnthVtTS0BYb6E9BnMzCs/wVpVyvyH7mHVz98x5cLLiQ5wDTcIjTHjG2DAbnHi244RCLo+MehiY4h+4gmUysrOfIkEHJfQqfM8lWhpCUe1/0uI5PbEqE6d6yiz8GJmLlc7fLAMH86MSwZQZ1P44YXNfFEpUXjrw4yedSbZO7fx5g2XYbfWYjTrqa2s4+DOlss+F817g/IffwTAZ+AAEj78EH10NMbU1E7FeaQRLS3Bo3z22Wf4+flxyimn9Mr9zopsOppdURzI8qFfjRUrVrBnzx4u/tcYKHtWFYv8tcT560kzm8i12PivXy07RmlRs/MJ0kjcN+sM9nz7NZWFBWi1emStBkVRKC+w/Pu2bF50EH9bPtbXX8cnLY3AWbO6/ws+AoiWluBR6urq2Lx5c8ME5t5WUbGRpcuGU1i0sGGbw+HA4WhaUsZ3ZCR/6oJYNiaVEzfsZvzqnWx31qFqJEIBq1PFoSg4H32CY2oUZK2WD++6GadtIUZz0/ZCxf58in9dTJ/nnyP+ww968sv0aqKlJXiUCy64gMLCQuRWJjD3JF/fAURFnU5w0KHxVgMGDKC01FUJ4vC4/KYcGuN1X2IkT+7OphaJW74soyZIg/6a/mhlGU14OLacbACi+qZQdNBEdXnjSgzLvtjFjnUVTNr8K+bHb0RqZ5nno5FoaQkeRavVEh0d3av3PHNjBj8WltXf30hq/4fQag+tmrN792527dqF3d7yeoVjrZWE5u4nptI1Bsu3zMktCZEA6KKi0Ae73t7NvOpGqssyOLDxm0bn71yRi1OVKb75dWTf7ht3VbOxkJLP07vtep5AtLSEo15xnYMCe8sVRSdMmMCECROa3fd7cQWRBh1pycm8oTcQGhHJsqxt6HSHasvbMjLQBB/qO3PYnKhK4yEPsQODyNxYSr/REV38ahqry6umLq+mW6/pbiJpCV5h69atLFq0CH9/fy6//PJuvfaXQ/vyVnYRFqeCj6bxw4fDUYNW23LL596MHCJ1Wn4clULfWNfj4vSLUpEOmxAdduMNjd78+YePpCjzS3J37yQ6ZQAAx102hPn5a7HXdm+BwMCTkuCkbr2k24mkJXiFoKAgoqOjCQvr/Jy9ltQ4FX4pLCdUr2VKzauUlCzFZi9GkrTIso7hw97F37/5lW2eTYmhwtk40Sx8bwd+IUZmXDLQFfs55zTa32/sYKqLfuPHF5/imlddy5lZa1wtPaOvrru/vCOO6NMSvEJMTAznnHMO06ZN6/ZrJ5oMmLUatlTWAgoOZxWqakNRavH1TcZsTuWVV15h/vz5Tc59OjOfh/bmNXz+ww8/sLXyV4KiW64cMXbWIKZffjnVxUW8fvl57D11NkaNjZmXDSIioe0VsI92oqUlCMCvo/8pzPcwqamuNQuzsz/F6axGlnWkpqYSFdV0EOpdSZH8XHRopLqfnx8qCn5BzVdd2J3xGCUlSxgz2jV3sLamGlRX2yEszq/Zc4TGREtLEFrgcFayL/MFrNYCjj32WJKTkykoaLzM/fdFFfxQVNbweXx8PBqdhD700ITonHvvpejddwEwGKJxOGpxOisIjOoDsobkH39A6+9qYdWU2yi2FGNzNl2cQnARSUsQ6jlVlbl7csiocQ1biIu9mlEjv8JodL3R+/rrr/nwww8bnXNdbBi31w9t+EddXR3fzV/Q8HntqtVY1roWYomOOp3YmAvRan2J7JuCVneoD6v4YBUf3L2cm5+fy6iPm6zn0KwNBRs44/szqLBWNNlnz6tGsbtnkG5PEklLEOqpKqyvqOHXYlcCkGUZP7+BDfsnTJiAn58ftsOW6Ho6M5+n9uc3fB4T43qDaLUcqpml8fPD0DcZAJ0ugISE65BlA8dfexMXPf78oQBkBVWFCftOZsABJ4radsJZmbuSjPIMsqqymuwrmreF8u8y2vnVew+RtAShnlaWGOPvy0c5xRTZ67DZili0uD9Llo5AUeyUl5dTUlJCSUlJwzmvDohj6ZhDwxn0ej0DE0bha02grr78TPDFcwg4pfE8QkvG/7d35uFVFecf/8y5+01ys5OVhLCFsO+LggKiVbHQglWstopaK/rTFrW41bW4oMVad0VRKlRRsQhuIAIiIPsaIawhEEjIvt3c/czvj3uFIAlhNQTm8zz3yblzZua8Zzj3y8ycd94pZ/mUrVSVCPa89Sb+igqi4kM7Pmsm+m2VLN67uFGbzQZz8KCenQCjR7fDcWXGiTVCM0CJlkJRh2FxDkyawKdLTKZIhDASCFRSVZVNRkYGXbp0ITo6+lB+TdOINx/ppjB02GBibcm4qoIe9FGjRmHNPBz6xrm+iPJZO0jIq2LBa5PYuGIfm0f8GuEL9c6EIKVM4/Pdnzdq709zXybtaFcJe9d4jOHmE26Dsx0lWgpFHQZER7Csf0eSrWY0zczQIT+S1WEy+w/8l8jISEaMGIHNZjtmHXGp4Vg6H2D2lx8fdc69vYwHNu4h16ITkRLG4EuupXv8MEpaD2HnpZcdylea9BjZpdmN2lvhrkBDI8oadcL3eiL4y8vxl5c3nvEXQImWolnj9XrJz88/o9dwOrdSWbkegPLycubPn99omU2bNrJ79+6j0v1pDj5LNfFihon1yeNZnT8Xv+YnMbo7WyyCPpsnBTNaYjFVhOP0HXsJjtvvRiKxG4/2C/NWuMl/dCn5D3zP/udWHcedNszOESPJu+WWU6rjdKFES9Gs2bFjB1999RWBwOld/lKXdu0eJD19HEVFX7Nx40bWrFmD213/5hTOyuBwrVO7HgBkZx/ZWwq3GukgjFgjLBjDiolqu4CoYW2wmcIpTWlPrawIvhEArlxzG5o49k/UbgqKVbWv+qhz7o1F4A3WJcs8+EqPjuHVGLuv/h3bBl2ELC7GGBl1wuXPBEq0FM2a9PR0BgwYgMFgaDzzKZC35w1ytj1Cr169MBqNvPPOO6xcufKIPIW5lcx4dAX528pJjmgPUrBk8ZH7Id6XsxePHuCZBeUIfzQGk4ePP8slLDmG7rFDyMlsBXrIx0uamLXo2PNaCWEJSCQFNQVHnYsY1JL4O7sjEm0QYUSzH58veaC2ll3Dr6Jyzlw8O3agFxdjTEwk9fXXjqv8mUaJlqJZs3PnTlauXMmOHWf21X5c3GX4fGWsXnMxPl8NxcXFLFq06NB555pCXNnF+DwB9mwupueQNkTVdKb4YBlzN2zitQcf48Djj9MrMowUiwkkWANmhOYl4AVDm2jibMkY9QhSnRsO1Vs0s5Rq79G9qJ+INEciEJR5jg7fLDSBpWUE1qRwHBe1xGA7vnWNBx59DG9uLsbEBLI2bqD9+nW0W7wIg9V6/A12BlGipWjWdO/enY4dO7Ju3TpcrhMf/hwvbdvei9EYjZSV/PGPHbj77rsZOdLP8sV/xF1bS/nc3Yjlwd5ORKwVW4QZi8+B1Hw8vreUyYN+Rc03CwjfU81Sn491w5OxVWZgMOiYI3P5eukBhMFIu7DuZI3rDyEfLYtsSbGzuEG7hBRIJEbRcC8q9toOOAY1viktgCcvj5r58zGmpxPWty8AhkZePPzSKNFSNHsGDBhAQUEBM2bMOGPX0DQDF1+0hgsuWEpq6hhiYmLw+cqodi9n+ZxnKHRoTM0wowtI7xwM+Ge1WzG54ui4dwc9ayoIVFXRa8UeHt8b4KoLM0gLG4cIWEnrP5XqSh/Emki0ZVBZUUF6RWjoabSy6O3HG7QrQACBqHci/mTYd/s4kJLUF//VeOYmQomW4pxg+PDhDB8+/Ixfx2ZNQoQmx7t0eR6LNQZ7q3WUtIlgdqoJbLBjTREAl9/SGUdVJu2KSuiX9yOLRtzJjiqNUS1j0TSNFr/tjaPoYozhB4nNmsOq3FrMBguuzcUM+fuIQxPyPaevRffUvxYxvyYfiSTaFl3v+RPhwJP/wJeXR+ToUdgyM48456pxs/D9LfjcDQdL/KVQoqU4J2jXrl29URjOJEIYCLP2oqZ6B6Yu1XgMYIk1sXXpfgCS2kWjYcBe2QpnbS0Th/Tmge52ahbtw1fqQmiCrN5PYKpNJj7rKzwtv8Mj3URWRhPWteuh62g+A7nXjqnXhqLaIjQ0zFr9TqR6rZfKb/Ma3Sik6NVXqfz4YyydO5P02GNHnPN7/Uy9bzlblxWycfFh9xJnpQevx4+zysPar3OPq81OB0q0FIpTwLm7G36PjnHvvSxc72VIhU51qfeQSLTvl4DNk4hVOEDq5IZrLHHoFL+zGd0TICwrjvalz2N0xdOi6ywOxiwngih8Za5DPa0trXrj3baNotdeP+r6t3S5BYHgseWPHXXOs7eKojc2Ub0oH72y4fj2hc9OovSNNzG3ziDjvzOO2lRj+mPBoaoj3kLPy9Ip2VfN1AlLeO/+ZUz5yxLem7CMFbNzKdlfc9LteCIo0VKc9+wrryWg17N47zjoc8U1HFyXiMdXyNb2s9nrMGIAFrz7IwDDbgouuLYXZJF1cB8IwYuZVvQyD2WhDSfir+5O2sZHMfrC8PT4BJc9j9JPcrAYgr5g+9OuxJiaStmUKTh/5mbRLrodHWM7kl2STbnrSI/18tk70Z0+Eu7piTG6/jd/JVPfpXz6dKydOtF61iyE8egJ/ehEGyabgRuevABXtZeZT6/GVXV4mGgwQZfBycSlhB9KWzBtCzMe/wHvGRhOKtFSnNf4AzqDJi2izUNfnlT5sOgYsnqMx1Vq5snIbozvYyDeCDtWF1NV6kQIQUSsmR9Tw4iOiCTMXUvbvTuAAO5tZVR8sQuDw0JU9zakrHoQIQSFnabgyavi8kuDsektRNL6k48RDgd7bx+HZ++RER0eveBRdKkzccXEQ2mu7eX4S104rmyNKab+t381y5dT/NJLmNu3p9V/Z9QrWACDf9+BiGgrpftrsDvMZF2QxOAbMrnzjaHc+cZQbn95KBeNOXL3a2+tj4pCF9MeXMaqL3ax/pu8k2rf+lCipTivMdbZyGLMG8tPqo6+vx5NjPF+bna/we1yMlltgo6uMyeuBmDQmPZsTjez2hJNeulB8iPD0N27QULN6oPUZpcQdWUGNi0B2/4LCThKONj6v4SHBbdS06RGqclD6ssvgdvNnt9fj5SHe4YdYjpgNVrZXLL5UFrVwjyMkRbCerZo0O78e+4BoNW09xDH2GcyMt7OFX/uQmxKOEIIhv4hi04DU47ZJleO60Z8WjheV4DVc/NYPmsXeuD0xPZSoqU479k58XIAVuwpZ9ryk5tQbt9vCJVb2pKpbaai9WTCoo14XTo71heyft4+hh3wY9Al+yPj2JmSxtxKN4ZYC3gDVC3cC0IQ0S+J1G034i+Jpzr1O8pq1vJTzJmvcr8irGtXon5/HXppKXl/vPGI69uMNuJtwU0/alYW4CtwEn5hyrE3fdUlhthYDBGNh3mOSrCf8Aayv3ugD3Fph3cymvn0ymPkPn6UaCnOe4xGA7PvGADAY3O24Pef+DrGhLR0/vK3d4gt/A0uew7dsj6jpVVjxezdFOysJH63B0etTo0tDPQAb13Vi2pv0IvfX1JL6QdbcQxLR7MaSVj3V/Cb2BM+CQjasiQvuBwo6ZFHCBt8Ma61a9n/8MOHru/0OtGljpSSis93oVkMhPVN/LmZh5CBQLB3dQZ3shaa4NqH+tFlWNCxtWy/i6rS2lOuV4mWQgF0T4uhW2owTvug5xY1kvswq1ePZl/+4RDMzpT1IAUV8d/Qwya5/Lr2xLcKRwDXL68mo8AFQnAw0sSEqAwMsTYQ4N5RTuW8PYR1jSPGkIB/cw+kwUVUfHDBdeyiToeukfb669h69aRq7ucUPv88ACaDiVhb0KkVg8AQd+yeUfG/X0KvrSX5kb8f972eLBddfTiWmN1x6vG9lGgpFCH+d8dAjEBBlYdHZm86Zt6qZfkceGENCAOaOLymTwvXqDFa8Gs+9nX7F573t/Lra9oTFmXGXgtjlnvJOrAfhGRVWys7u0QijAaEzYh7QzERg1MBA7b9vUBqtMzYAEBKddYR10+fNg1Tq1aUv/se5bNmUeOrIa8qDyEERocF6fbREIXPP0/p1KmYMzIIv/jiRtslf3s5MyeuZMq931FTXn90i8b4adLeaDr1DcCUaCkUITRNMG/8RQC8v2Ifs9bsazizV6IXuUhb/SApKdcdSu7W9XXu4yVe1u7CFZdDYdv/UP7Rdm585kLskSYE8Kv1tSRUlqMbBX92lhPWKwFZ60MPBPAfdOMxChIs7SBgxBAdDO2sScMRMeOFppEx80Ow2yl85hkiavw4zA78ZS78VR4sber3kHfv3k35jP9iTEsLlj8GRXmVTBm/mM9eWE9JvhMZkEfsnN1UKNFSKOrQJiGCiSODvlX3frKJMmf9y2ccQ1qixZrx5dVQvWz/oXS7vRVXB5Yxig+pdVmpTF1CuX0ZvqJaxk4aRLveLbD4Ivj1urVYPG7KHCb+YnQh7Ubw6HhzK0m4uh1mzYpWG43PFlwSpCFYmbPuCBsMNhtpb71JwOfl8fd1smIyqVlViDHaRuSl6fXaXfTU0wiDgVb/mYZ2jKgNlcW1zHp+HV6XTnSKneuf6MdtLw4mLLL+/Rx/SZRoKRQ/44YBGdw8MPijH/DMQrz++l/VJ9zVC4yCyrm7qV51OJ5V68ybeYs7MVlr0QOCwsx3KPxsCQDDbu5ITcJmbN4wrl/1DSIQYJ7By3MDI/GbBDVrConqkUBtwI29si265iLK5AIE6949OtpDWM+e5I/uT4sKGDZlC7WrCrGkO9DMR8cX85eUULthA/YBAzDFxR2zDcIiLaR2iKb7sFR+/0h/ohLCjpn/l+SURUsIcZcQYpsQ4kchxHN10rsKIX4IpW8WQtQr6w2VVyiakkev6ky7+DA8fp1LX1hcbx6D1Uj8uG6gQeWnO8mf+AOl/9vBrPxy9hrbkUMnMPpAeMhNehI94KeoqAip6cTYE7B4LFy5aSXokk/cbh690IF0BSidvhXLRS0xeqOQwkeaLTg/FajS2F/hovpn81WuMVewOxGi94Du9hLWu37frOLXXkMGAiSMH9/o/RvNBlpmRVNaUHuET9jZwCmJlhBiCDAS6Cql7AT8M5RuBKYDt4fSBwNHzQw2VF6hOBuYf8/FWAyQV+bivo/W15vHkhJB4kN90VrYwOnHtbKQW0vuw65X8qp4iNJALLrQ8VtLWL/uVqqqqhBCMPzmfkR40mlZVUyPPYVIKVlk1nk304L7x1JSslKgogUgsLTYAoDAwE1TV3Lj1CP9nXom9OTJ6zX0yAR0txtpOnqdoa+oCOey5RgTE7G0ad3gPdeU1zL1viW8evtCln2yi31bynA7G57UbwpOtac1DnhWSukBkFIWhdIvAzZJKTeG0kullPU5vzRUXqE4o/zUe8jPz6ekpKTePEII1vz9UgA+WXeAGT8cvVEFgDHcQvI9vUl9ZhAJf+tFG18bHvX8E4SLyeIJDnqTCEhJRcVSPN73EUKQm5vL1bdeisFvp9++VbSocuEL6MzMsLAtXKP0k21U5kcjAmZc6d+jAQKBURPkFBy5MDk1PBXdbGJHv1SQAfJvufWI8+UffMCe636Pr6CAsD59jtkun/5zA66a0HrBUAer7MCxN9f4pTlV0WoPDBJCrBRCfCeE6FMnXQoh5gkh1gkhJpxgeYWiUWoq3Hz41Eqqy08sYunatWt57bXXmDFjBtOnT+eVV16hrOzocMUAETYzb1wf3KTi4c+2MvX7nces2xRrp8folxkzbBbPOudTYbDyjOVxvAEjASQHCz7EZj9IeXk5aVmxpHi7g27kih+/w+qRlPkD3N/LTq5fR0sxYqpORreXYA69tBtoshKQklrv4YXIBc4CAgTwJccizBa8e/ZQOCk401KzdBklU94mbNBAEh5+mLg///mY9l/+p85cMjaLO14fwp1vDGXcq0NIaX/qsbpOJ42KlhBigRAiu57PSMAIRAP9gb8BH4mgR5sRGAhcH/r7WyHEJfVU31D5+uy4TQixRgixpri44fCzivOH/K3llO5z8p8HfyBwAl7sbdq0IT4+Hq/Xy+WXB5fwTJ8+vcH8l3dJ5tXrugPw5BfbWJhT2Og1jGYro0c8zZ+slZRrDt4Td6MHNKTQ6dBhPqVFwUXPv73/AsKr2mLze7li4w60ABwwwf1dLZiNHRGV8UiTizBD8C2mrSg49DPU+Zl8tP0jANqnZCFMFgypnan44ANc27dT8MTjGFNSSHroIWKuvQZz6rHXDLZo5aBDv6RDjqnaWeDi8HMaFS0p5TApZed6Pp8B+cCnMsgqQAfiQunfSSlLpJS1wJdAz3qqb6h8fXa8JaXsLaXsHR8ff3J3qzin6DAgibCYoIf1W3/9rtFAdz8RFRXFNddcw9ixY+nevTsDBgygsrKSL79sONLD8G4p/GNE0BXi5vfWkld89GYTqyudvJdffMTE9YQLf8MASxUrzT35Xl5BIAAmk5eE5CmsmPMx0fHhtIpPQvitJLi3cWFODTqSKquBezOtbK9OAKGTEhUMO2O2GwGJ03O4p/Vt3rcYMJB1cR8QgvBhNyH9fvbdPg5htpD26isI87mz0/SpDg9nA0MBhBDtATNQAswDugoh7KFJ+YuBLSdQXqE4Lm56eiAGs0D3w+t3LObVcQtZ+3UuU8YvZvuqxntEAJdddhnJycmsXr2a9evrn3AH+MMFGYzuEeypXPLCkqP2WtxT6+afewoZm51Lpe+wqHw0YChJBp0ZlmuoCKTj8wmstloKPE+z4L03+c39FxJZngUIupSsIMKl49J1Yj2S/7b6LZWEYUvYCkBSSwe6Llm1p/RQ/aXuUmIsMUFvcyMYwuNASgKFhbS45x4MDsfxNmez4FRFayrQWgiRDXwI3BjqNZUDLwCrgQ3AOinlFwBCiLeFEL2PVf4UbVKcZ/z534OxRYWW0kjYv60Cr0tnwbTjW/wshODGG28kLCyML774gs2bNzeYd/K13RncPha/hJGvLAXA56tk+/Z/MDyyhgkZSeTUuBmxdjvv7Q9OYxg0jU/69sIorDxn+Qtgwu/VCI+uosj4X2ZMeoJ+XcKxuOIIiFq67N1LrVljYEUAj8HEf7Q/gjk4+V6dXYEEfth1WLQsBgsOqyN0Lxr+khIIBMBqxXHJ0BNv0LOcUxItKaVXSnlDaLjYU0q5sM656VLKTqFzE+qk3yqlXNNYeYXieBFCcPOzgw6tbxvxlx4ktYtEBmDag8uOa9hoNBoZO3Ysdrudzz//nNmzZze4a/V7N/fHYTWQXVDDuOlr8HiLKCj8jNWrRzGUb5jVvTXtwmxMzi3krh/3cMDtJc1m4bb0FIpEKnMNI9CECU1qxCfm44nfwpaalTjKWyECVjoVbcbsD/B+koErSwvYonXmR1MrHJrEU+tDANWuwz05s8FMUW0RvjIX0uXHk7MCLBY029mxT+HpRnnEK85JRt3bC0e8BXe1n/ceWIrb2XCM9J+IjY3lrrvuIjMzk82bN/P+++83mHf2/w1EA77KPsjv3t5P/35fExN7Ebm5r7A/+1omWD/i0RQXu2o93LhpN0vKqpjQOom2YXY+ZxSFeguE34KmQet2G6g27EBELySmtAcGHfru3kK5VWO3LZx4ilgcmUYbswG/OyjACXWW03gCHnRdx1/oRAb86LW5GGJigBObRM/5oYCv39qE33vioXl+SZRoKc5ZbnjyAmJS7biq/Lw7YelxeXabTCZGjRpFZmYmeXl5zJ49u958rePC2fDYpVgMsLXASZ+n15CZ+U86dpyExZxIWeliEvffx32Bh4nT9/CXrXk8u+sA07pkYNYlk+QTVMgY8FoRAjp1XUJlpIdq8zeYnYl0KtxNcomThTFRCKmzxxZGsikoQkY/XNj28MsoT8CDUTNSufAL0HUcvxqF7nRiTq9//WFdpJSUF9Twzr3f8+20reRuLsWnREuhaBqEEFz7UF80I+iB4BvG450yHT16NGlpaWzatImpU6fi9x+9QYPDZmbLk1eQ7LBQ5QmQ+cjXVAe6063bm/Tr9yWdO/2L+LAUbvc/wxD/p8zZv52/Zm9hVHk+TpOVZ+QkamQEeK1oBujVdx5ehwnp2QEILtm2AikFeaRzwGzHaRKEC0l/l4He6Yd9pzShkWCKpfqLxcEIqIMHgJSYGnnL/t5DS3lt3CI+mLgKt9NHRJyVsc9eiC387H7TqERLcU6jaRq3vzwEzQh+j85rdy7Cexw9CYPBwE033USfPn3Iz89n8uTJrF27tp58GssfGkavNAcSGDz5O2auDMa1io7uRZcu/+bC/p9zZ6qDe4xvU+bcwZIWJq4q/4Jqu4kXvc+BNEDAjMEYoN+Fc/BFm9HcfmwBJ79afwC/MFGrmfgmyUTfMCNZPgO+0O5B3oCXgB7gui+qMSb2R5gNmFLtSJ/3mG8N//PwMpxlwSFzZt8Ern2kL3+ceAHWsLNbsECJluI8QAjBn/89GM0E6DDl7u9Y982e4yp3xRVXMGrUKIQQzJ07l3fffRe3++hAeLPuGMSNA9IAuP9/2bywIOfQOaMxgjZtxjN6wDTe7tSKeLORFbG96OZbQp7DxOP6ZNy+YJx2s8VN544L0U0B0CGhOpv23r34hJE5KQbCDIIUg8bGfRVBGxG0qDHQcW8LDDGtsfVIRK+phICOITGh3vv6YOJKqkuDzqp/enEQl9zY6Yjtv852lGgpzgs0g8a4l4cS2SI4gf3DrN28evvxvazu3Lkz9957L1lZWezbt49Jkybx4YcfHvVW8omRXfjotn4AvLRgF7PX5R9xXggD7Vr049MLrqSjoQUbZQ96+TdQYLPwvPYAAXdQOKJbFGOzlYPuBYOH3/xQgpCwPdJIgUXSxWqgrDIYa91kMPH3r9oQ3v0mDBFWYka2peabBUEn0/79j7i+u9bLG3cvpCzfiRBw6wuDMFtNNDeUaCnOK2548kLs0Yffqs3599FDvvowGAxce+21/OEPf8Bms5GTk8Nzzz3Ht99+e4R49W0dx8vXBdcq/vWjjcxYseeoukya4N3B/ckKCDZ7OnGpJcAeYxIvme4CnxEE9Og5HwwGEDrOWj/RlBAQghnpZiKNGmHfHQTg4Mw5JLe+gYDwk3BPX4TJQPknn6BFRmLreeQilHfvX0rACyar4ObJA7HYm59ggRItxXnI2GeG0O3S4J6C+7ZW8s79SygrPL4t3TMyMpgwYQKXXHIJUkq+//57Jk+eTG3t4V1mft0t+dCSn4dn/8igZxccVY9BCGYOu4AOFcUsqLaQUW0kW3RluRwMusBggazMtSAEPksxQzzLAMl3CSYkkFzowl3kxL1MByEp/30kRocFX3k53p07sWZmHlo/qAd0XrtzIboPjGbBbS8OwWo/++euGkKJluK8ZODoDtgig5ssuCv9fPD4qmAMqf/tOK7ygwYN4v7776djx464XC7efPPNI4TrDxdkcNugYNyqfRUeWj3wBYu3HjyiDrPZzEsX9aFT0X6KLD6sfiMfMJZib7BcXOI2kBIMMKzmW6zSRbHNwC6bxCIEJS+sRBjMzC97kW49LgCg4O9/BymJu/MOIOjSMGX8EmQAhBHGPjfo1BruLECJluK85eZJF3HH60PoPDj5UNqGeft49faF5O9ofAmspmlcc801DBw4kKqqKl588UU2bTq8i89Dw7PY9uSvSAltm3XTtDWMeWv5EcPJtLQ0bosLY+CO9dgCXiqMFp5iIrrfDAIGDa4EwOm20olN6EiWtTBiAHRdozznI6Zf5sKgGajdnI1z8XeY27cnrEdwiDrz6ZX4vTrCCHe8MhSz9dR3w2lqRHNc6te7d2+5Zs2apjZDcY5Rkl/FzKfWHAp+pxlh3CvHt3Zv+/btfPrpp7jdbqKiohgzZgyJiYc3S521di/3fnx4TeNTIztx/YBWQLA39Morr3AgIJjftj/7bQauLMrn+hZ/BWDDhsuxWKoIZJYzSXuS5FrJrO+d+Cv38e3BiUQ8/ShjMq9h57BL8VdU0Oab+Zjj4pg3ZRM71wbFd9xrg9G05tVHEUKslVL2/nl687oLheIMEpfq4M7XhwZdIwDdD6/evhDXcSwBat++Pffccw89evSgoqKCt956iw8//BCfLxiqeHSvNLY8cRkZcTYAHv7sR4b/O7jZhRCC4cOHE1FbxdVbv8cakHzVIpW1noEAdO/xNeVlCWSSg1F6KLIKvonXwFPJ3EEWxmSNYe/t4/AfPEiLu+/CHBfHzGdWHRKs4Xd1aXaCdSzOnTtRKE4T414eyrjXBmMNDw6lpt67lJlPraSmkQipZrOZkSNHMm7cOMLDw8nJyWHSpEnk5AR9tuwWE4vuG8oHtwQD9P5YUE2fifNwury0bt2aq6++Gvxurt6wDKHrvGS+ixX0BwlZWcvxuCKwixo0CZ+kmfBZHXTv92t8Bw5Q+8MPGNPTiR07lu1rCinJC75YuPTWLFp1Orfiz6nhoUJxDGa/uI79ORWHvhtM8NvxPUloHdVo2cWLF7NkyRJ0XadNmzb06NGDTp06IYTA7fXT7Yn5eALB39+r1/VgeLdkSkpKeP/995kXncKG1DaYNC+/lbMYIf/H7l1d+FfbO/D5IzDrFt6evZbMf42i6ta7ca9fT8acOWzarrF67h4Aug1rycCr252BVvllaGh4qERLoWgEKSVLP9nG1mUF+NzB34swwGV/6kTb7vV7nf/E/v37+fLLLykqKsLn8xEWFsbIkSNp3749ANe+tZyVu4NRSZMdZhbcOwQjOp/9432e7pFGQWQ0Rs3PUPkN1/nf4x/aU+RpGUT4TNicpbycGkfsn24i/OKLOXjleFZ+lgvA0LFZZPVLOoOtcuZRoqVQnAb25ZQyf0o2bmdw/aI13MgfJ16AqZG3ci6Xi/nz57N582YCgQApKSlcddVVJCYmsq2gkitfWkqo00VcmIkXTOFY9y5i9IhL8JlMmIWHDnIrF/oX8JbpHm7ck89sh4HIgIl/THmf3Z3/dEhQf3NvD1LanV2bUZwMSrQUitNIbnYR897MJuADBNzwRH8iW9gbLed0OnnllVdwuVwYjUbsdjt2u51+/fqR44nm+fnbKKsNRpSI9VbQJsLPikGd8IsAUmjEyRKcWMny5lLoTMWtRfLnBTUYdAECrn6wFwlpkWf47n8ZlGgpFGeAjyetpig3uMlFclsHV97ZHYutcV+oqqoqli1bxvbt26mpqSEQCGCxWLDb7SQlJbG7Emr2ZiOBnVGJLO7SB6Pw4hdGNKljwY3mC2f4Cicdiv0M/7+upGUde6v75oYSLYXiDLFizi7Wfpl36Hu3y1oycNTxT4D7fD42bNjAtm3bqKiowOl04nIF31Rq4XG4qsrIi09kUVZPpCYBAwCpTidPrKvlgu5tCB+QjOk4enrNCSVaCsUZxFXt5ZtpW9iXHdz01WQzMPz2LqRkxpxwXbquc+DAARwOBw6HA7/fz5jnZ+Gx17KmU2ekFuzJxev72DT4Kiq+zCW8f5ISrbMZJVqKs5WaSg/TH1lOwBv8XZmsGkP/kEXbXsd+y1gXn8dPeUENe7aUs2tNIc4qLz53AN0PFVYX715ho8YUnGh/cN46Ok24mmGx58Y8Vl2UaCkUvyBFeZX871/r8P/kImGEDv0SSc2MIa1TDFWlbgp2llNRWEtlqYuqEheVRZ5DS4iOhU6Ap34XA0IDdIy6IHdod0znkNc7KNFSKJqEorwqPn91I64qX+OZRTDWlT3CQkScjdTM6OAu2g7LEdmcTidtfsiBkEiN33iACXddgTCeH6LV/Jd8KxRnMS3SHdz83CCcVR7yt5SSu6mEsgO12KNMJLeNIirBjjXMRFi0ldik4wt5vG7dOm7dOJO3u43l5u9/z43JM090t7BmjRItheIXIMxhIbN/Mpn9kxvP3Ag9e/Zk8beLePGHDfzmb9lYw5tnBNKT5dzqTyoUzQDvvmqql+Y3nrEBFi9ejDBqRHZPPO8EC1RPS6H4xQk4ffjLPSddvn///sTHx5OamnoarWo+KNFSKH5hbB1isHU4cf+tn4iNjSU2NvY0WtS8UMNDhULRrFCipVAomhVKtBQKRbNCiZZCoWhWKNFSKBTNCiVaCoWiWaFES6FQNCuUaCkUimaFEi2FQtGsUKKlUCiaFUq0FApFs0KJlkKhaFYo0VIoFM0KJVoKhaJZoURLoVA0K5RoKRSKZoUSLYVC0axQoqVQKJoVSrQUCkWzQomWQqFoVijRUigUzQolWgqFolmhREuhUDQrhJSyqW04YYQQxUDeaaouDig5TXWdKsqW+lG21M+5bku6lDL+54nNUrROJ0KINVLK3k1tByhbGkLZUj/nqy1qeKhQKJoVSrQUCkWzQokWvNXUBtRB2VI/ypb6OS9tOe/ntBQKRfNC9bQUCkWz4pwRLSHEVCFEkRAiu07aP4QQm4QQG4QQ84UQyaF0sxDiXSHEZiHERiHE4AbqjBFCfCOE2BH6G92EtjwvhMgJ1fE/IURUU9lSp577hBBSCBHXlLYIIe4SQmwTQvwohHiuqWwRQnQXQqwIlV8jhOh7srbUOXdUGwshHhRC7Azd868aqPOknt0zaM9JPb/1IqU8Jz7ARUBPILtOmqPO8d3AG6HjO4F3Q8ctgLWAVk+dzwEPhI4fACY1oS2XAcbQ8aSmtCV0viUwj6C/XFwTtssQYAFg+SlvE9oyH7gidHwlsPhkbWmojYGOwEbAAmQAuwDD6Xp2z6A9J/X81vc5Z3paUsolQNnP0qrqfA0DfprA6wh8G8pTBFQA9fmYjASmhY6nAb9pKluklPOllP7Q1xVAalPZEuJfwIQ6ZZvKlnHAs1JKT528TWWLBByh40jgwMnaEqK+Nh4JfCil9Egpc4GdQH09upN6ds+UPSf7/NbHOSNaDSGEeEoIsQ+4Hng0lLwRGCmEMAohMoBeBP8X+TkJUsoCgNDfFk1oS11uBr5qKluEECOA/VLKjadiw+mwBWgPDBJCrBRCfCeE6NOEtvwVeD5U/p/Ag6dgR0NtnALsq/M9P5T2c073s3uq9tTllJ7fc160pJQPSylbAjOA/wslTyXYuGuAF4HlgL/eCs4yW4QQD4fOz2gKW4QQduBhDv+gT5lTbBcjEA30B/4GfCSEEE1kyzhgfKj8eOCdk7GhkTau797OqAvA6bTntDy/JzuuPBs/QCt+Ng6vcy79GOeWAx3rSd8GJIWOk4BtTWVL6NyNwA+AvanaBegCFAF7Qh8/sBdIbKJ/o6+BwXW+7wLim8iWSg67EQmg6mT+jY7VxgR7bw/WKTcPGHA6n90zYc+pPL8//5zTPS0hRLs6X0cAOaF0uxAiLHR8KeCXUm6pp4o5BBua0N/PmsoWIcTlwP3ACCll7cnacaq2SCk3SylbSClbSSlbEeyB9JRSFv7StoSYDQwN5WsPmDnJhbunwZYDwMWh46HAjpOxo5E2ngOMEUJYQkPVdsCqeqo5bc/u6bDndD6/J612Z9sH+AAoAHyhRr0FmAVkA5uAuUBKnf9FtgFbCb55Sq9Tz9tA79BxLMEJ2B2hvzFNaMtOgnMHG0KfN5rKlp/Vv4fjf3t4JtrFDEwP1bEOGNqEtgwk+GZxI7AS6HWythyrjQkO1XaFbLridD67Z9Cek3p+6/soj3iFQtGsOKeHhwqF4txDiZZCoWhWKNFSKBTNCiVaCoWiWaFES6FQNCuUaCkUimaFEi2FQtGsUKKlUCiaFf8PdjVnso2TcOUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "geodata.plot(column='ind_ident', figsize=(16,10), markersize=0.2)\n",
    "# plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "cf6697a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'WGS 84'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geodata.crs.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9eaa078c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create world layer\n",
    "world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5267fb70",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define center of Orthographic Projection\n",
    "lat = -90\n",
    "lon = 0\n",
    "\n",
    "ortho = CRS.from_proj4(\"+proj=ortho +lat_0={} +lon_0={} +x_0=0 +y_0=0 +a=6370997 +b=6370997 +units=m +no_defs\".format(lat, lon))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a67783fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Re-project and plot\n",
    "geodataor = geodata.to_crs(ortho)\n",
    "world = world.to_crs(ortho)\n",
    "world.plot(figsize=(12,6))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "27769a8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# geodata['x'] = [xcoor.x for xcoor in geodata['geometry'].to_list()]\n",
    "# geodata['y'] = [xcoor.y for xcoor in geodata['geometry'].to_list()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "87a5bb70",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "<shapely.geometry.multipolygon.MultiPolygon at 0x1d032af3ca0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "antarctic = list(world.loc[world['continent']=='Antarctica'].geometry)[0]\n",
    "antarctic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2ddbe88b",
   "metadata": {},
   "outputs": [],
   "source": [
    "bounds = antarctic.bounds\n",
    "    \n",
    "xmin = bounds[0]\n",
    "xmax = bounds[2]\n",
    "\n",
    "ymin = bounds[1]\n",
    "ymax = bounds[3]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4d5e7ec7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-2435758.3262868873, 2569777.3556817234, -2098008.094902729, 2170137.65170231)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create unique fig, ax\n",
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "\n",
    "# adding layers\n",
    "world.plot(ax=ax)\n",
    "geodataor.plot(ax=ax, markersize=10, color='red')\n",
    "\n",
    "# limits\n",
    "ax.set(xlim=(xmin, xmax), ylim=(ymin, ymax))\n",
    "\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "594b6c83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dO+Ll5QVA27ZtKS8vr3O/s7KyaN++fZ3bN4QETUIIIYS4qM6dOzNnzhwCAwNJS0vj5MmTQMXS2IVCQkL4+eefueuuu9i9e7fzuM1mw2QyodfrOXDgQLXzarpWXTgcDt5//30eeOCBBp1fVxI0CSGEEOKiXn/9dV5++WXsdjsA//znP8nLy6ux7YsvvkhsbCzvv/8+3t7e6HQV4caYMWN49NFHufbaawkMDGxUf86cOeNcRrTZbNx+++2MHDmyUde8GKk9J4QQQlyBmnPtuVWrVtGzZ086derEihUr2LlzJ7NmzWrqbjWazDQJIYQQ4pIKCAhg8uTJuLu7o9FomDlzZlN36ZKQmSYhhBDiCtScZ5quVlJGRQghhBCiDiRoEkIIIYSoA9nTJIQQQrRApnIbqQfyKSy14OdhYEBwGzyNEhbURj4dIYQQooVZvv04K9KOU2Z1OI8t2XyIh3tfxyO3XteEPWveJGgSQgghWpDl24+TuLX6Q1ZlVofzuARONZOgSQghhGghTOU2VqQdr7XNirTj/LlnAB6G+oUIVquV2NhYsrKysFgsjBs3juDgYGJiYlAUhS5dujBt2jQ0mort1AUFBURERLB69WqMRiPFxcVMnjwZs9mMXq9n7ty5tdady87OZvbs2RQUFFBWVkZoaCixsbEYDIYar6+qKgMHDuT6668HICwsjBdeeKFeY5SN4EIIIUQLkXogv8qSXE3KrA5SD5yq97VXrVqFr68vycnJLFmyhBkzZjBr1iyioqJITk5GVVU2bNgAwObNm4mMjCQ/P995/sqVKwkJCSEpKYnw8HASEhJc3stutzN+/HgiIyNJTExkxYoV6HQ6Fi5c6PL6x44dIzQ0lMTERBITE+sdMIEETUIIIUSLUVhqqVs7U93aVTZ06FAmTZrkfK3VaklPT6dv374ADBw4kC1btgCg0WhYunQpvr6+zvYhISGYTCYASkpKnKVXapKWlkb79u3p2bOn81h0dDTPPvusy+unp6eTm5vL6NGj+cc//sGhQ4fqPUZZnhNCCCFaCD8PQ93aedatXWWenp5ARcAzceJEoqKimDNnjrMIr6enJ8XFxQAMGDCg+j39/EhNTSU8PJwzZ86QlJTk8l55eXlcd13VfVdGo9H57zVdv23btjz99NPcf//97Nixg+joaD777LN6jVFmmoQQQogWYkBwG9z0tf/V76bXMCDYv0HXz87OZsyYMQwfPpxhw4Y59y8BmEwmfHx8XJ4bHx/P2LFjWbNmDQkJCUyYMMFl28DAQHJycqocKywsZOPGjS7P6dGjB/feey8Affr0ITc3l/oWRZGgSQghhGghPI06Hu5d+5NxD/e+rt6bwAHy8/OJjIwkOjqakSNHAtC9e3e2bdsGQEpKCn369HF5vo+PD97e3gD4+/s7l+pqEhYWRmZmJnv27AFAVVXi4+PZvn27y3Pi4+P58MMPAcjIyCAwMNA5C1ZXUntOCCGEuAI1pvZcTXma3PSaRuVpiouLY+3atQQFBTmPTZkyhbi4OKxWK0FBQcTFxaHVap3vDxo0iLVr12I0GsnNzWXq1KmUlpZis9mYOHFijcts5xw/fpzp06djNpspLS0lLCyMmJgY59NzF17/zJkzREdHU1pailar5bXXXuOGG26o1xglaBJCCCGuQI0t2FtqsZF64BSFJgt+ngYGBPs3aIapJZFPRwghhGiBPAw6Bndv19TdqFV8fLxzea+ymTNnVtsIfjnITJMQQghxBWrsTJOoP9kILoQQQghRB7I8J4QQQrRApnIbqQfyKSy14OdhYEBwGzyNEhbURj4dIYQQooWp6em5JZsPNerpuZZAgiYhhBCiBVm+/TiJW6vvFy6zOpzHJXCqmQRNQgjRQhQXF7Hu2+/59XAurb3duHdAH7p379bU3RKXkancxoq047W2WZF2nD/3DKh3+gGr1UpsbCxZWVlYLBbGjRtHcHAwMTExKIpCly5dmDZtmjNLeEFBAREREaxevRqj0UhxcTGTJ0/GbDaj1+uZO3cubdu2dXm/7OxsZs+eTUFBAWVlZYSGhhIbG+vM03Th9e12O7NmzWLv3r1YLBYmTJjAPffcU68xStAkhBBXsaNHjvDNph/JOHaK33NMFOmuQdG6AfDlrm8IarWG0Ouv4b4BvejevXu9MySLK0vqgfwqS3I1KbM6SD1wqt7pCFatWoWvry9z586lsLCQhx56iK5duxIVFUW/fv147bXX2LBhA4MHD2bz5s3MmzeP/Px85/krV64kJCSEl156ieXLl5OQkEBMTEyN97Lb7YwfP57XX3/dWbQ3Li6OhQsX8uKLL9Z4/S+//BKbzcbHH39Mbm4ua9eurdf4QIImIYS4qjgcDn7avoMff84g43g+hwvA4tYGRWkFxlZUDonsxtb8Xga/Z8Cq3RsIarWO0E5tGXTbLdx0Uw8JoK5ChaWWurUz1a1dZUOHDmXIkCHO11qtlvT0dPr27QvAwIEDSU1NZfDgwWg0GpYuXcqIESOc7UNCQjh06BBQUfRXp3MdoqSlpdG+fXtnwAQQHR2Nw1ERENZ0/R9++IGQkBCefvppVFXl1VdfrfcYJWgSQogrnLm0lG++28Se37PYn1lAVrkXGLyBtuAOdQl9HEY/DpTBgf3w1Z7vud7nG0I7teGe23rS8+aeEkBdJfw8DBdvBPh51q1dZZ6enkBFwDNx4kSioqKYM2eO8/8dT09PiouLAWosj+Ln50dqairh4eGcOXOGpKQkl/fKy8urltzSaDQ6/72m6xcWFnL06FHeeecdtm/fziuvvFLrPWoiQZMQQlyBsrNPsO67H8g4ls9vJ4opVNqg6IxAANT/77sq7EZfDpbDwd/gq18209l7A907teHu/j25JUwCqCvZgOA2LNl8qNYlOje9hgHB/g26fnZ2Ns8++yyPPfYYw4YNY+7cuc73TCYTPj4+Ls+Nj49n7NixREREkJGRwYQJE1i9enWNbQMDA/nmm2+qHCssLGTXrl0u9yn5+vpy9913oygKffv25ciRI/UenwRNQghxBVBVlV27d/PD9l/IOH6Kg/k2yoxtURRv0HvXaTapIRxGXw5a4ODv8PXeH+jk9S2hndpyd7+b6NXrFgmgrjCeRh0P976uxqfnznm493UNqkGXn59PZGQkr732GrfddhsA3bt3Z9u2bfTr14+UlBT69+/v8nwfHx+8vb0B8Pf3x2QyuWwbFhZGZmYme/bs4eabb0ZVVeLj4zEajS6Dpt69e7Np0yaGDBlCRkYGAQEB9R6jlFERQohmymIp57tNP/DzvqNkHD/F8VJ3VGOrpu4WAEr5Ga73MhN6/TUMvDWUPr17SwB1mTWmjEpNeZrc9JpG5WmKi4tj7dq1BAUFOY9NmTKFuLg4rFYrQUFBxMXFodVqne8PGjSItWvXYjQayc3NZerUqZSWlmKz2Zg4cWKNy2znHD9+nOnTp2M2myktLSUsLIyYmBjn03MXXt9isTBt2jQOHjyIqqq8/vrrhIaG1muMEjQJIUQzUlhwijXrN/HrkTz2Z50mX/VH0bs1dbdqpViK6OhRSo/rr+GO3t3p17ePBFCXQWNrz5VabKQeOEWhyYKfp4EBwf4NmmFqSSRoEkKIJqSqKhkZGWzcspP9x09xIK8ck6EtikZ78ZObIaW8IoDqfn0b7uzdnX59b3Xm5RGXVkso2BsfH8+2bduqHZ85c2a1jeCXgwRNQghxmVmtVn7Y8iM79h4i49gpjpbosBtbN3W3Lj1LMde5ldDj+jbc0bs7/fv1lQDqEmoJQVNzI0GTEEJcBsVFZ1j77Sb2Hsphf2YhuXZfFL1HU3fr8rGUcJ1bCd07+TOgV1cG3NZfAqhGkqDp8pOgSQgh/iCHDx/i25RtFdm4c00Uaa9B0cqeESwmOhiL6NGpDbffciMDbu9fZXOwqJtGB03lJXB4E5SeAg9/6HwXGL0uTeeuUhI0CSHEJWK32/npp+1s3b2ffcdOceS0gsXoL5uia3M2gOreyZ/benZh4B0DJICqo0YFTTsTYVcSWM3nj+ndIexx6DW68Z27SknQJIQQjVBqMrH+u03sOXCCjOMFnLB4g0F+rTeEajERaDhDaCd/busZwsA7bq+1lEZL1+CgaWcibH/P9fu3jpXAyQUJmoQQop5OnMhi3YYfyDh+it+ziynUtEHRNjINt6hCtZbSQX+Gbh1b0++mG7jnrjslgLpAg4Km8hJIGll1hulCend44jMweNbr0larldjYWLKysrBYLIwbN47g4GBiYmJQFIUuXbowbdo05162goICIiIiWL16NUajkeLiYiZPnozZbEav1zN37lzatm3r8n7Z2dnMnj2bgoICysrKCA0NJTY21pmn6cLrv/vuu2zevBmAoqIi8vPzSU1NrdcYJWgSQoiLUFWVnT/vInXHXjKO5XOowH42G7dsZL4cVGspgWcDqL6hQQy6+070en1Td6vJNShoyvgaNv3r4u3uehm6htfr0p999hkZGRlMmTKFwsJCHnroIbp27cpTTz1Fv379eO2117jzzjsZPHgwmzdvZt68eRw7dowff/wRo9HIhx9+SG5uLi+99BLLly/n0KFDxMTE1Hgvu93OyJEjef31151Fe+Pi4nBzc+PFF1+s8fqV/d///R9PPPEEd955Z73GKGG7EELUoLy8jO++/4Gf9x8l49gpMs0eZ7NxtwG3uhXBFZeGovcgGw+yj8GGgwf4YM0OunX0o2+PIO696070Bpnlq7PSU5e2XSVDhw5lyJAhztdarZb09HT69u0LwMCBA0lNTWXw4MFoNBqWLl3KiBEjnO1DQkI4dOgQUFH0t7aZxbS0NNq3b+8MmACio6NxOCoynNd0/XO++eYbfHx86h0wgQRNQgjhlH/yJGs3bGLf0Xx+O3GGfEfrs9m4A8B40dPFZaDo3cnBnZzj8N2hgyz9egehnVrTp/v1DL7nLgmgLsajjoV469quEk/PiuW8kpISJk6cSFRUFHPmzHE+COHp6UlxcTFAjeVR/Pz8SE1NJTw8nDNnzpCUlOTyXnl5edWSW1aeTaqt/Mo777zD/Pnz6z6wSiRoEkK0eL/uy2Dxx+s4kG+hVH8NisYTtJ4o8hBXs6bo3cnDnbzj8N2hI3y4difdOrbm9puDGXzv3fLUYk063wVb3rr4nqaguxp0+ezsbJ599lkee+wxhg0bxty5c53vmUwmfHx8XJ4bHx/P2LFjiYiIICMjgwkTJrB69eoa2wYGBvLNN99UOVZYWMiuXbtcFuwFOHDgAD4+PnTq1LBN9LIgL4Ro0XJycpidsJpfiv0xGwOu2PIlLZ2idyNPE8imTDdmrfqN8VPns3rtNzTzbbuXn9GrIq1AbcIer/cmcID8/HwiIyOJjo5m5MiRAHTv3t1ZBiUlJYU+ffq4PN/Hxwdvb28A/P39MZlMrrsYFkZmZiZ79uwBKvYdxsfHs3379lr7uGXLFgYOHFivcVUmM01CiBar1GTi9X9/yHFHYFN3RVxKOg8yzB5krDnMmh/mE357Dx64f7BkID/nXDqBS5ynafHixRQVFbFo0SIWLVoEwJQpU4iLi2P+/PkEBQVV2fN0oUmTJjF16lSSk5Ox2WzMmDHDZVuNRsOCBQuYPn06ZrOZ0tJSwsLCiIqKqrWPhw8frnXp7mLk6TkhRItks9l45Z8L2H66jTwFd7WzmrnRu4jwATfx56soeGp0RnCLCQ5VyggedFeDZphaEgmahBAtjqqqzHpzMd8cNUh+pZbEaibEu5j7b+/OX8KHXPHBU0uoPRcfH+9c3qts5syZ1TaCXw4SNAkhWpx3P1zGxzvOoOrlV3WLZDUT4lVUETw9MPSKDZ5aQtDU3EjQJIRoUb74+n+8ve53LPpWTd0V0cRUm5kQzyKG3tad4Q8MueJq3knQdPlJ0CSEaDG2bP2J2cu2UKytfw4acfVSbWa6eBQx9LZuPPjnoVdM8NTYoKnUWsrW7K2cLj+Nr9GX/gH98dB7XKLeXZ0kaBJCtAgZ+39j2juryeOapu6KaK5sZdzgcZqh/bvy0LDwZh88NSZo+vz3z/niwBeU2cucx9y0bjwY/CAPdXnoUnTvqiRBkxDiqncyL4/ouR9w1B7Q1F0RV4KzwdOf+nZlxPDmGzw1NGj6/PfP+Xj/xy7fj7gxQgInFyRoEkJc1cxmMy/MeItfze0lQ7SoF9V6NnjqdyMj/hJeay20ptCQoKnUWsq4b8dVmWG6kJvWjbfve7veS3VWq5XY2FiysrKwWCyMGzeO4OBgYmJiUBSFLl26MG3aNOfG+4KCAiIiIli9ejVGo5Hi4mImT56M2WxGr9czd+5c2rZt6/J+2dnZzJ49m4KCAsrKyggNDSU2NhbD2VI6jb1+Ta7MRwaEEKIO7HY7r899m19Lr5GASdSbonfjkLU9b3+fx/9NeZNPPvsSm83W1N1qlK3ZW2sNmADK7GVsy67+mP/FrFq1Cl9fX5KTk1myZAkzZsxg1qxZREVFkZycjKqqbNiwAYDNmzcTGRlJfn6+8/yVK1cSEhJCUlIS4eHhJCQkuLyX3W5n/PjxREZGkpiYyIoVK9DpdCxcuPCSXN8VCZqEEFetN+IT2JbfSkqjiEZRdMaK4GnTSZ6OfZNln35xxQZPp8tPX9J2lQ0dOpRJkyY5X2u1WtLT0+nbty8AAwcOZMuWLUBFRu+lS5fi6+vrbB8SEuIsnVJSUlLrzF5aWhrt27enZ8+ezmPR0dE8++yzl+T6rjSvuUYhhLhE3v9oOd8ccKDo3Zu6K+IqoeiMHLa1552UfNb/9CaDb+3CyAcfQK/XN3XX6szX6HtJ21Xm6VmR96ykpISJEycSFRXFnDlznLO8np6eFBcXA9RYysTPz4/U1FTCw8M5c+YMSUlJLu+Vl5dXLbml0Wh0/ntjr++KzDQJIa46X61bz/JtuTgkeaX4AziDp835PD3lTZKWf47Vam3qbtVJ/4D+uGndam3jpnWjX0C/Bl0/OzubMWPGMHz4cIYNG1YlcajJZMLHx8flufHx8YwdO5Y1a9aQkJDAhAkTXLYNDAwkJyenyrHCwkI2btx4Sa7vigRNQoiryrbtO1iydi/let+m7oq4yik6I0dsASz5oYB/TPk3H33yWbMPnjz0HjwY/GCtbR4MfrBB+Zry8/OJjIwkOjqakSNHAtC9e3dnGZSUlBT69Onj8nwfHx+8vb0B8Pf3dy6l1SQsLIzMzEz27NkDVJRGio+PZ/v27Zfk+q7I03NCiKvGgYMHmfqfz8mlXVN3RbRAqt3C9YZT3Nv7BiL+Ogy94Y+ta9jc8jTFxcWxdu1agoKCnMemTJlCXFwcVquVoKAg4uLiqqRwGDRoEGvXrsVoNJKbm8vUqVMpLS3FZrMxceLEGpfZzjl+/DjTp0/HbDZTWlpKWFgYMTExzqfnGnv9mjQqaFq/fj3r1q1j3rx51d5LSEjg66+/RlEUnnnmGQYPHoyqqgwcOJDrr78eqIgUX3jhhVrvIUGTEKIuTp3K58XZCRyxBzZ1V0QLp9otdNKf4t7eQYwa8Zc/LHi6FBnBt2Vvc2YE7xfQTzKCX0SDN4LHxcXxww8/0K1bt2rvFRUVkZiYyDfffIPZbObBBx9k8ODBHDt2jNDQUBYvXtyoTgshRGXl5WVMm/8+h20BSGYB0dQUrYFjjgDe31rEt2n/5t5enRk18i8YDMaLn3wZeeg9uKfjPU3djVrFx8c7l/cqmzlzZrWN4JdDg4OmXr16cd999/HJJ59Ue8/d3Z3AwEDMZjNms9m5cz49PZ3c3FxGjx6Nm5sbr7zySpVpPCGEqC+Hw8H/e2Mxe03XoGgkYhLNh6LVc9wRwNJtxXybtoBBva7n8YeHN7vgqTl77rnneO6555q6G04XDZpWrFjBhx9+WOXYzJkzCQ8PrzH6OycgIIAHHngAu93O//3f/wHQtm1bnn76ae6//3527NhBdHQ0n332WSOHIIRoyeYvep8f87xQmmmpCyEUrZ5MNYAPfyrhu58XMOiW63ls5F8wGmt/ik00PxcNmh5++GEefvjhel00JSWFvLw8Z+bPv//97/Tq1YsePXo4N4D16dOH3NxcVFWVTL1CiAb5cNmnrP3NCjqvpu6KEBelaPVkOiqCpw07FzLolut5/OGmC55KraVszd7q3NPUP6C/7Gm6iD8kuWWrVq1wc3PDYDCgKAre3t4UFRURHx+Pr68v//jHP8jIyCAwMFACJiFEg6xdv5GPfzyBQ+fX1F0Rol4UrZ4sNYD/bjexcddC7u7ZiccfHo6b2+ULnmp6eu7D9A8b9fRcS3BJg6alS5fSsWNH7r33XrZs2cIjjzyCRqOhV69eDBgwgJtuuono6Gg2bdqEVqtl1qxZl/L2QogWYsfO3bz79S7KdG2auitCNJii1ZHpCCBxRynf/byQe8I68sQjD/7hwdPnv3/Ox/s/rna8zF7mPC6BU80kT5MQ4opy+PARYuM/JUeVXEzi6qLabQRq87inZ0Xw5O5eewmghqQcKLWWMu7bcbUW7XXTuvH2fW/Xe6nOarUSGxtLVlYWFouFcePGERwcTExMDIqi0KVLF6ZNm+bMEl5QUEBERASrV6/GaDRSXFzM5MmTMZvN6PV65s6dS9u2bV3eLzs7m9mzZ1NQUEBZWRmhoaHExsZiMBj44IMP+PrrrwG46667eO655yguLiY6OpqSkhKsVisxMTHccsst9RqjZAQXQlwxTheeJu7t5RIwiauSotWRTSBJP5fx9ylv8e4HyzCbzZf0Hluzt9YaMEHFjNO2bNcPermyatUqfH19SU5OZsmSJcyYMYNZs2YRFRVFcnIyqqo69zpv3ryZyMhI8vPzneevXLmSkJAQkpKSCA8PJyEhweW97HY748ePJzIyksTERFasWIFOp2PhwoUcP36cVatW8fHHH/PJJ5/www8/kJGRwdKlS+nfvz8fffQRs2bNYvr06fUeoxTsFUJcESyWcl6b9y4Hre0lF5O4qikaHdkEkLyrjI27F3L3zdcy5tGHcPdo/Cbt0+WnL2m7yoYOHcqQIUOcr7VaLenp6fTt2xeAgQMHkpqayuDBg9FoNCxdupQRI0Y424eEhHDo0CGgouivTuc6RElLS6N9+/b07NnTeSw6OhqHw4FOp+O9995zPnhms9kwGo08+eSTzmzhdru9SoHfupKgSQjR7DkcDma88TZ7StpKLibRYigaHTkEsmy3le9/ieeumzrwt0YGT75G30varjJPz4oC2SUlJUycOJGoqCjmzJnjfODL09OT4uJigBrLl/j5+ZGamkp4eDhnzpwhKSnJ5b3y8vKqJbesHAS1bt0aVVX517/+Rffu3encubPzvZMnTxIdHU1sbGy9xyjLc0KIZm/hOx/yQ44nikZ+54mWR9FoySGAj3dbiZwSz9sJH1HagGKzAP0D+uOmrX2juZvWjX4B/Rp0/ezsbMaMGcPw4cMZNmyYc/8SgMlkwsfHx+W58fHxjB07ljVr1pCQkMCECRNctg0MDCQnJ6fKscLCQjZu3AhAeXk5L774IiaTiWnTpjnb7N+/nyeffJLJkyc7Z8DqQ4ImIUSzlrT8c77aZwadJAIULZui0ZKjBPDJLzYip8Y36Boeeg8eDH6w1jYPBj/YoHxN+fn5REZGEh0dzciRIwHo3r27MxF2SkoKffr0cXm+j48P3t7eAPj7+2OqJTAMCwsjMzOTPXv2AKCqKvHx8Wzfvh1VVRk/fjw33ngj06dPdy7THThwgEmTJjFv3jzuuuuueo8P5Ok5IUQztv67Tbz5xW7MkotJiGpOr5na4HNrytPkpnVrVJ6muLg41q5dW6U82pQpU4iLi8NqtRIUFERcXJwziAEYNGgQa9euxWg0kpuby9SpUyktLcVmszFx4sQal/HOOX78ONOnT8dsNlNaWkpYWBgxMTFs2rSJ559/nrCwMGfb559/nnfffZf9+/fToUMHALy8vHj77bfrNUYJmoQQzdKuXXuY/sG3FGpcP3IsREvWmKAJKtIPbMve5swI3i+gn2QEvwjZICCEaHaOHz/O3MRvKNRIagEh/igeeg/u6XhPU3ejVvHx8TXWuZ05c2a1jeCXg8w0CSGalaIzZ3h+5jsctAY0dVeEaNYaO9Mk6k82ggshmg2rxcJrb7zLAUv7pu6KEEJUI8tzQohmQVVV4t58h11FbVC0kotJiD+aw2TCtHUr9sJCtH5+ePbvj+ZsriVRMwmahBDNwn/eSyQlyw2llizAQohL4/Rnn3F65eeoZeefnjv1/lJ8//oQvpWydIuq5NtJCNHkPlm5mlW/lIDOu6m7IsRV7/Rnn1GYvKzacbWszHlcAqeaSdAkhGhSGzelkvj9Iay61k3dFSGueg6TidMrP6+1zemVn+Nz//1o6lmuxWq1EhsbS1ZWFhaLhXHjxhEcHExMTAyKotClSxemTZvmzBJeUFBAREQEq1evxmg0UlxczOTJkzGbzej1eubOnUvbtq5TjmRnZzN79mwKCgooKysjNDSU2NhYDAYDSUlJrFy5EkVRePbZZ7nnnnsoLi4mOjqakpISrFYrMTEx3HLLLfUao2wEF0I0mT1704n/YhsmCZiEuCxMW7dWWZKriVpWhmnr1npfe9WqVfj6+pKcnMySJUuYMWMGs2bNIioqiuTkZFRVZcOGDQBs3ryZyMhI8vPzneevXLmSkJAQkpKSCA8PJyEhweW97HY748ePJzIyksTERFasWIFOp2PhwoUUFBSQnJzMxx9/zAcffMDrr7+OqqosXbqU/v3789FHHzFr1iymT59e7zHKTJMQoklkZmXxrw/WUKDIk3JCXC72wsJL2q6yoUOHMmTIEOdrrVZLenq6s8bbwIEDSU1NZfDgwWg0GpYuXcqISsuAISEhHDp0CKgo+qurZX9jWloa7du3p2fPns5j0dHROBwO3N3d+fLLL9HpdGRlZeHj44OiKDz55JMYDIaK8dntVQr81pXMNAkhLjuTqYTpbyWR5ZCASYjLSetXt5JEdW1XmaenJ15eXpSUlDBx4kSioqJQVRVFUZzvFxcXAzBgwAD8LriHn58fqampzlmmc/XrapKXl1ctuaXRaMTd3R0AnU7HRx99xKOPPuoM5Hx8fHBzc+PkyZNER0fz/PPP13uMEjQJIS4rq9XKq/9azG/lku1biMvNs39/FLfai18rbm549u/foOtnZ2czZswYhg8fzrBhw5z7lwBMJhM+Pj4uz42Pj2fs2LGsWbOGhIQEJkyY4LJtYGAgOTk5VY4VFhayceNG5+snnniCzZs3s337draeXW7cv38/Tz75JJMnT3bOgNWHBE1CiMtGVVVmL3iXnadboyjy9SPE5abx9MT3r7UX5PX960P13gQOkJ+fT2RkJNHR0c5Zou7duzvLoKSkpNCnTx+X5/v4+ODtXfEErb+/PyaTyWXbsLAwMjMz2bNnD1Dx3RIfH8/27ds5dOgQzz33HKqqotfrMRgMaDQaDhw4wKRJk5g3bx533XVXvccHUkZFCHEZvZ3wEct3l4LOvam7IsQVrzFlVGrK06S4uTUqT1NcXBxr164lKCjIeWzKlCnExcVhtVoJCgoiLi4OrVbrfH/QoEGsXbsWo9FIbm4uU6dOpbS0FJvNxsSJExkwYIDL+x0/fpzp06djNpspLS0lLCyMmJgYDAYD8fHxpKSkoCgKd955J8899xzjxo1j//79dOjQAQAvLy/efvvteo1RgiYhxGXx6Zdf8863R7DpXU/PCyHqrrG15xylpdUzgjdghqklkafnhBB/uJTUH/nwuwPY9JJaQIjmQuPhgfegQU3djVrFx8c7l/cqmzlzZrWN4JeDzDQJIf5Qv+7LYNq7X5OvXNPUXRHiqtLYmSZRf7ITUwjxh8nJyWF2wmoJmIQQVwVZnhNC/CFKTSZeX/BfjjsCmrorQogaWMpsZGYUUmay4uap59qufhjcJCyojXw6QohLzmazMe2NxWSUteNsXjshRDPya+oJMn7MxmZxOI/t+vYYXW8LoPuAwCbsWfMmQZMQ4pJSVZU5C5ewvcAXRSs7AIRobn5NPcHeTVnVjtssDudxCZxqJkGTEOKSWvLfj9lwWEHRG5q6K0KIC1jKbGT8mF1rm4wfs+nSpx16o7bWdheyWq3ExsaSlZWFxWJh3LhxBAcHExMTg6IodOnShWnTpjmzhBcUFBAREcHq1asxGo0UFxczefJkzGYzer2euXPn0rZtW5f3y87OZvbs2RQUFFBWVkZoaCixsbEYDAaSkpJYuXIliqLw7LPPcs899zjPO3jwII888ghbtmypd/05+RkohLhkvvh6HZ/tOIWq92zqrgghapCZUVhlSa4mNouDzIyCel971apV+Pr6kpyczJIlS5gxYwazZs0iKiqK5ORkVFVlw4YNAGzevJnIyEjy8/Od569cuZKQkBCSkpKc9edcsdvtjB8/nsjISBITE1mxYgU6nY6FCxdSUFBAcnIyH3/8MR988AGvv/465xIFlJSUMGfOHGfh3vqSoEkIcUmk/riN97/JwKJv1dRdEUK4UGay1qmduaRu7SobOnQokyZNcr7WarWkp6c7a7wNHDiQLVu2AKDRaFi6dCm+vr7O9iEhIc7SKSUlJeh0rhfD0tLSaN++PT179nQei46O5tlnn6V169Z8+eWX6PV68vPz8fHxQVEUVFXl1Vdf5fnnn3cW9q0vCZqEEI2Wsf83Fq74gWKtf1N3RQhRCzdPfZ3auXvVrV1lnp6eeHl5UVJSwsSJE4mKikJVVZSzT4N4enpSXFwMwIABA/Dz86tyvp+fH6mpqc5ZpnP162qSl5dXLbml0Wh0BkM6nY6PPvqIRx99lCFDhgAViTLvuusuunbtWu+xnSNBkxCiUU7m5TFryRfkIbmYhGjuru3qh85Q+1/9OoOGa7s2LHt/dnY2Y8aMYfjw4QwbNsy5fwnAZDLh4+O6jFJ8fDxjx45lzZo1JCQkMGHCBJdtAwMDycnJqXKssLCQjRs3Ol8/8cQTbN68me3bt7N161ZWrVrFZ599xujRozl58iSRkZH1Hp8ETUKIBispKWbavz/gqL19U3dFCFEHBjcdXW+rPXda19sC6r0JHCA/P5/IyEiio6Ods0Tdu3d3lkFJSUmhT58+Ls/38fHB29sbAH9/f+dSXU3CwsLIzMxkz549QMVTu/Hx8Wzfvp1Dhw7x3HPPoaoqer0eg8GARqNh/fr1JCYmkpiYSNu2bXn//ffrPUZ5ek4I0SD5J08yZd777C9v75x+F0I0f+fSCVyYp0ln0DQqT9PixYspKipi0aJFLFq0CIApU6YQFxfH/PnzCQoKci6V1WTSpElMnTqV5ORkbDYbM2bMcNlWo9GwYMECpk+fjtlsprS0lLCwMKKiojAYDHTt2pVHH30URVG48847nfuqGktqzwkh6u3osWO8Hv8xh60SMAnRVBpbe85abiczowBziRV3Lz3Xdm3doBmmlkRmmoQQ9bIvYz8z31tNpiNAsn0LcQXTG7V07uk6D1JzEB8f71zeq2zmzJnVNoJfDjLTJISos+1pP/NG0ney6VuIZqCxM02i/mSmSQhRJ99v3sLCz7ZRqJGASQjRMknQJIS4qK/Xfcs7a/dSrG3T1F0RQlwiljIbmRmFlJmsuHnqubarHwY3CQtqI5+OEKJWyz77ksRNRzHrJHGlEFeLX1NPVHt6bte3xxr19FxLIEGTEMKlJR8uY8WOAqx6v4s3FkJcEX5NPcHeTVnVjtssDudxCZxqJkGTEKIaVVV5c9H7rMmwYte7zuArhLiyWMpsZPyYXWubjB+z6dKnXb3TD1itVmJjY8nKysJisTBu3DiCg4OJiYlBURS6dOnCtGnTnFnCCwoKiIiIYPXq1RiNRoqLi5k8eTJmsxm9Xs/cuXNp29b1033Z2dnMnj2bgoICysrKCA0NJTY21lmM1+Fw8PTTT3PvvfcyatQoysrKiI6O5tSpU3h6ejJnzhxat65f5nPJCC6EqMJutxM3bxGr9zuw6z2bujtCiEsoM6OwypJcTWwWB5kZBfW+9qpVq/D19SU5OZklS5YwY8YMZs2aRVRUFMnJyaiqyoYNGwDYvHkzkZGR5OfnO89fuXIlISEhJCUlOevPuWK32xk/fjyRkZEkJiayYsUKdDodCxcudLb597//zZkzZ5yvly1bRkhICMnJyTz44IPOBJz1IUGTEMLJYiln6qyFbDjuBjq3pu6OEOISKzNZ69TOXFK3dpUNHTqUSZMmOV9rtVrS09Od2bgHDhzIli1bgIqM3kuXLsXX19fZPiQkxFk6paSkBJ3O9WJYWloa7du3p2fPns5j0dHRPPvsswCsW7cORVEYOHBglXPuvPNOZ19+/PHHeo9RgiYhBAClJhMvzVjIj/l+KFpDU3dHCPEHcPPU16mdu1fd2lXm6emJl5cXJSUlTJw4kaioKFRVdVYN8PT0pLi4GIABAwbg51d1r6Sfnx+pqanOWaZz9etqkpeXVy25pdFoxN3dnd9++42vvvqqSgAHFYHYudp2lftSHxI0CSE4VXCKF+Li2VVyDYpGyigIcbW6tqsfOkPtf/XrDBqu7Vq/vT7nZGdnM2bMGIYPH86wYcOc+5cATCYTPj6u90jGx8czduxY1qxZQ0JCAhMmTHDZNjAwkJycnCrHCgsL2bhxI1988QW5ubn87W9/4/PPP+eDDz4gJSUFLy8v50zWxfriimwEF6KFyzyeybS3kjloDZA6ckJc5QxuOrreFlDj03PndL0toEE16PLz84mMjOS1117jtttuA6B79+5s27aNfv36kZKSQv/+/V2e7+Pj45wJ8vf3dwY4NQkLCyMzM5M9e/Zw8803o6oq8fHxGI1GXnrpJWe7t956izZt2jBw4EAOHDjApk2buPnmm0lJSaF37971HqMETUK0YPt/+524dz+XOnJCtCDn0glcmKdJZ9A0Kk/T4sWLKSoqYtGiRc5N1lOmTCEuLo758+cTFBTEkCFDXJ4/adIkpk6dSnJyMjabjRkzZrhsq9FoWLBgAdOnT8dsNlNaWkpYWBhRUVEuzxk1ahQvv/wyo0aNQq/XM2/evHqPUWrPCdFC7dy1m3/9dz25tGvqrgghGqCxtees5XYyMwowl1hx99JzbdfWDZphaklkpkmIFigldSsLVmyhQCMBkxAtld6opXNP13mQmoP4+Hi2bdtW7fjMmTOrbQS/HGSmSYgWZs0337H46z0Ua6UsihBXssbONIn6k5kmIVqQ5Z9/xQcbD0kdOSGEaAAJmoRoIRISP+GT7Sex6qSOnBACLGVmjv2yG3NxEe7ePnS8qScGN/em7lazJkGTEFc5VVVZ+O4HrEovw6Fr1dTdEUI0A79s/Ib077/FZrE4j+34aiWhd9/HTff8qQl71rxJ0CTEVcxutzN7wTt8e0QHOq+m7o4Qohn4ZeM37P5mTbXjNovFeVwCp5pJ0CTEVcpqsfD6G4tIzfFG0UlZFCFExZJc+vff1tom/ftv6XrbQPRu9as/abVaiY2NJSsrC4vFwrhx4wgODiYmJgZFUejSpQvTpk1zZgkvKCggIiKC1atXYzQaKS4uZvLkyZjNZvR6PXPnzqVtW9dP92VnZzN79mwKCgooKysjNDSU2NhYDAYDcXFx7Ny5E0/PiqLjixYtQqvV8sILL3DmzBnc3d2ZO3curVvXL/O5lFER4ipkLi3lpX8uIDWvlQRMQginY7/srrIkVxObxcLRvbvrfe1Vq1bh6+tLcnIyS5YsYcaMGcyaNYuoqCiSk5NRVZUNGzYAsHnzZiIjI8nPz3eev3LlSkJCQkhKSnLWn3PFbrczfvx4IiMjSUxMZMWKFeh0OhYuXAhAeno67733HomJiSQmJuLt7c3y5csJDQ0lOTmZBx54wJmAsz5kpkmIq0xBQQFT31jCr+b2KBr5XSSEOM9cXFTHdmfqfe2hQ4dWyfit1WpJT0+nb9++AAwcOJDU1FQGDx6MRqNh6dKljBgxwtk+JCSEQ4cOARXFdXU61yFKWloa7du3p2fPns5j0dHROBwOHA4HR48e5bXXXiM/P5+RI0cycuRInnzySex2OwAnTpygTZs29R6jBE1CXEWyTpxg2r8TOSB15IQQNXD3rluRWnfv+j80cm4prKSkhIkTJxIVFcWcOXOc30Wenp4UFxcDMGDAgGrn+/n5kZqaSnh4OGfOnCEpKcnlvfLy8qoltzQajc77P/HEEzz11FPY7XbGjBlDjx496Nq1K1qtljFjxvDbb7+xdOnSeo9RfoYKcZU4cPAgr8z/iIO2QAmYhBA16nhTT3SG2pfsdQYDnXr0rLWNK9nZ2YwZM4bhw4czbNgw5/4lAJPJhI+P66AtPj6esWPHsmbNGhISEpgwYYLLtoGBgeTk5FQ5VlhYyMaNG3F3d2fMmDG4u7vj5eVF//79ycjIcLb773//S1JSUq3Xd0WCJiGuArv27OXVRZ9z3BHQ1F0RQjRjBjd3Qu++r9Y2oXffV+9N4AD5+flERkYSHR3NyJEjAejevbuzDEpKSgp9+vRxeb6Pjw/e3t4A+Pv7YzKZXLYNCwsjMzOTPXv2ABWpVeLj49m+fTtHjhzhsccew263Y7Va2blzJ6Ghobzzzjt88cUXAHh4eKDV1r/OnpRREeIKl/rjNt5c/gOnlGuauitCiMuoMWVUasrTpDMYGpWnKS4ujrVr1xIUFOQ8NmXKFOLi4rBarQQFBREXF1clWBk0aBBr167FaDSSm5vL1KlTKS0txWazMXHixBqX8c45fvw406dPx2w2U1paSlhYGDExMRgMBpYsWcK6devQ6/UMHz6cUaNGkZ+fz8svv4zFYsFut/PCCy/Qu3fveo1RgiYhrmD/+/Z7Fq3+mSJt/Tc0CiGubI2tPWctK+Po3t2Yi8/g7t2KTj16NmiGqSWRjeBCXKE+/fJrlm44QKlOAiYhRP3p3dwI7tOvqbtRq/j4eOfyXmUzZ86sthH8cpCZJiGuQB8mf8qyrTmUS1kUIVqsxs40ifqTmSYhriCqqhK/5L98ubcUuwRMQghxWUnQJMQVwuFw8K+F7/K/Q4rUkRNCNJqj3E75gdM4Sq1oPPQYg33RGOv/RFlLIkGTEFcAq9XK9Dfe5occD9AZm7o7QogrnGl7Dqa0XFSrw3lM2ZyJZ+92eN7avgl71rw1Kk/T+vXreeGFF2p8791332X48OE8/vjjbNy4EYCysjImTJjAY489xj/+8Q8KCgoac3shWgSz2UzMPxewOccbtBIwCSEax7Q9h5Kt2VUCJgDV6qBkazam7TkuzhQNnmmKi4vjhx9+oFu3btXe279/P1999RUrVqwAICIigv79+/Pxxx8TEhLChAkT+Prrr1m0aBFTp8pGNiFcOXP6DFPmvsPe0nYoWslFK4RoHEe5HVNabq1tTGm5uPdsi8ZQv6U6q9VKbGwsWVlZWCwWxo0bR3BwMDExMSiKQpcuXZg2bZozS3hBQQERERGsXr0ao9FIcXExkydPxmw2o9frmTt3Lm3btnV5v+zsbGbPnk1BQQFlZWWEhoYSGxuLwWAgLi6OnTt3Oku7LFq0yJk48+DBgzzyyCNs2bLFWXqlrhr8LdyrVy9ef/31Gt87ePAgffv2xWg0YjQa6dSpE/v37yctLY0777wTqCjc9+OPPzb09kJc9XJyc3lx1mL2lrZHUSRgEkI0XvmB09VmmC6kWh2UHzhd72uvWrUKX19fkpOTWbJkCTNmzGDWrFlERUWRnJyMqqps2LABgM2bNxMZGUl+fr7z/JUrVxISEkJSUhLh4eEkJCS4vJfdbmf8+PFERkaSmJjIihUr0Ol0LFy4EID09HTee+89EhMTSUxMdAZMJSUlzJkzB8NFSsm4ctFv4hUrVvDnP/+5yj979uwhPDzcZX2rG2+8kR07dlBSUkJhYSE///wzZrOZkpISZ8crF+4TQlR18NBhYt74kANWqSMnhLh0HKXWurUz1a1dZUOHDmXSpEnO11qtlvT0dPr27QtUTJZs2bIFAI1Gw9KlS/H19XW2DwkJcZZOKSkpQadzvRiWlpZG+/bt6dnzfI286Ohonn32WRwOB0ePHuW1114jIiKCTz/9FKh4+vjVV1/l+eefx93dvd7jgzoszz388MM8/PDD9broDTfcwOOPP84//vEPOnXqRM+ePfHz88PLy8v5gVyscJ8QLdUv6b8y+/2vOaFKHTkhxKWl8dDXrZ1n3dpVdm4prKSkhIkTJxIVFcWcOXOcP/wqT5bUVB7Fz8+P1NRUwsPDOXPmDElJSS7vlZeXVy255bmltpKSEp544gmeeuop7HY7Y8aMoUePHqxfv5677rqLrl271nts5/whc/4FBQUUFhaybNkypkyZQnZ2Nl26dKFXr15s2rQJqCjcV9+aL0Jc7X7ctoPpCWs5ocrTK0KIS88Y7Iuir/2vfkWvwRjs26DrZ2dnM2bMGIYPH86wYcOc+5fg4pMl8fHxjB07ljVr1pCQkMCECRNctg0MDCQnp+qG9cLCQjZu3Ii7uztjxozB3d0dLy8v+vfvT0ZGBqtWreKzzz5j9OjRnDx5ksjIyHqP75KmHFi6dCkdO3Zk0KBBZGZmMmLECPR6PS+99BJarZZRo0bx8ssvM2rUKPR6PfPmzbuUtxfiivbtxhT+82UapzVSeFcI8cfQGLV49m5HydZsl208e7er9yZwgPz8fCIjI3nttde47bbbAOjevTvbtm2jX79+pKSk0L9/f5fn+/j4OLfw+Pv7O1emahIWFkZmZiZ79uzh5ptvrkj8Gx+P0WikY8eOTJ48mc8//xyHw8HOnTt56KGHWL9+vfP8QYMG8f7779d7jFJGRYhm4Iuv1/HeN/sxaVs3dVeEEFeIxpRRqTFPk17TqDxNcXFxrF27lqCgIOexKVOmEBcXh9VqJSgoiLi4OLTa8wHZoEGDWLt2LUajkdzcXKZOnUppaSk2m42JEyfWuIx3zvHjx5k+fTpms5nS0lLCwsKIiYnBYDCwZMkS1q1bh16vZ/jw4YwaNarKuZXvWx8SNAnRxBI/XklSahblet+m7ooQ4grS2NpzDsvZjOAmKxrPsxnBGzDD1JJIRnAhmoiqqrz9/kd8vqsYmwRMQojLTGPQ4t7dv6m7Uav4+Hi2bdtW7fjMmTOrbQS/HGSmSYgm4HA4eCP+Pdb97kDVezZ1d4QQV6DGzjSJ+pOZJiEuM5vNxox5i0jJcgcJmIQQ4oohQZMQl1FZWRmvzvkP2wv8UHT1z4MihBCXiqP87J6mUisaj7N7moyyp6k2EjQJcZkUFxcRO2cxv5Rcg6KVLyYhRNOp8em5zZmNenquJZCgSYjLIC8vj1fnL2V/eXsUjdSRE0I0HdP2nBrzNKlWh/O4BE41k6BJiD/YkaNH+X/xn3DYFiB15IQQTcpRbseUlltrG1NaLu4929Y7/YDVaiU2NpasrCwsFgvjxo0jODiYmJgYFEWhS5cuTJs2zZklvKCggIiICFavXo3RaKS4uJjJkydjNpvR6/XMnTuXtm3burxfdnY2s2fPpqCggLKyMkJDQ4mNjcVgMBAXF8fOnTudpV0WLVrEsmXL2Lx5MwBFRUXk5+eTmpparzHKT14h/kC/7stgysLlHLFLwCSEaHrlB05XWZKriWp1UH7gdL2vvWrVKnx9fUlOTmbJkiXMmDGDWbNmERUVRXJyMqqqsmHDBgA2b95MZGQk+fn5zvNXrlxJSEgISUlJhIeHk5CQ4PJedrud8ePHExkZSWJiIitWrECn07Fw4UIA0tPTee+990hMTCQxMRFvb2+efvpp5+v27dsze/bseo9RgiYh/iA/7djJ60u+ljpyQohmw1FqrVs7U93aVTZ06FAmTZrkfK3VaklPT6dv374ADBw4kC1btgCg0WhYunQpvr6+zvYhISHO0iklJSXodK4Xw9LS0mjfvj09e/Z0HouOjubZZ5/F4XBw9OhRXnvtNSIiIvj000+rnPvNN9/g4+PDnXfeWe8xyvKcEH+A7zb9wFufb5c6ckKIZkXjUbendjWe9X+699xSWElJCRMnTiQqKoo5c+Y4Z9k9PT0pLi4GqLE8ip+fH6mpqYSHh3PmzBmSkpJc3isvL69acstzJVFKSkp44okneOqpp7Db7YwZM4YePXrQtWtXAN555x3mz59f7/GBzDQJccmtWrOeNz/bwWlNm6buihBCVGEM9kXR1/5Xv6LXYAz2bdD1s7OzGTNmDMOHD2fYsGHO/UsAJpMJHx8fl+fGx8czduxY1qxZQ0JCAhMmTHDZNjAwkJycnCrHCgsL2bhxI+7u7owZMwZ3d3e8vLzo378/GRkZABw4cAAfHx86derUoPFJ0CTEJZS0/AveXrePEl3zLk0ghGiZNEYtnr3b1drGs3e7BtWgy8/PJzIykujoaEaOHAlA9+7dnWVQUlJS6NOnj8vzfXx88Pb2BsDf39+5VFeTsLAwMjMz2bNnD1BRlio+Pp7t27dz5MgRHnvsMex2O1arlZ07dxIaGgrAli1bGDhwYL3Hdo4szwlxibyzNJnPfj6NVefX1F0RQgiXzqUTqJanSa9pVJ6mxYsXU1RUxKJFi1i0aBEAU6ZMIS4ujvnz5xMUFMSQIUNcnj9p0iSmTp1KcnJyReWEGTNcttVoNCxYsIDp06djNpspLS0lLCyMqKgoDAYDw4YN45FHHkGv1zN8+HC6dOkCwOHDh2tcGqwrqT0nRCOpqsr8/ySwZr8Nh5RFEUJcJo2tPeewnM0IbrKi8TybEbwBM0wticw0CdEIdrudf765mI3HDFJHTghxRdEYtLh3b95bCeLj453Le5XNnDmz2kbwy0FmmoRoIFVVmbPgHdYd0qHojE3dHSFEC9PYmSZRf7IRXIgGevfDZXxzEAmYhBCihZDlOSEa4LMv1/DZzkJUvevHZ4UQojkrLy/n8OHDlJaW4uHhQefOnZ25jkTNJGgSop6+2/QDS7/7HauudVN3RQghGmTnzp3s2rULq/V85u8tW7YQFhZGr169mrBnzZsETULUw65de4j//CdMWtdFJIUQojnbuXMn27dvr3bcarU6j0vgVDMJmoSoo8NHjvKvxG8o1NSeGE4IIZqr8vJydu3aVWubXbt20aNHDwwGQ72ubbVaiY2NJSsrC4vFwrhx4wgODiYmJgZFUejSpQvTpk1zZgkvKCggIiKC1atXYzQaKS4uZvLkyZjNZvR6PXPnzqVtW9c/ULOzs5k9ezYFBQWUlZURGhpKbGwsBoOBuLg4du7c6Sztci5vVH2uXxPZCC5EHZwqOMWM/3xCtioBkxDiynX48OEqS3I1sVqtHDp0qN7XXrVqFb6+viQnJ7NkyRJmzJjBrFmziIqKIjk5GVVV2bBhAwCbN28mMjKS/Px85/krV64kJCSEpKQkwsPDSUhIcHkvu93O+PHjiYyMJDExkRUrVqDT6Vi4cCEA6enpvPfeeyQmJpKYmIi3t3e9ru+KBE1CXERZWRmvzUvgkK1hWXKFEKK5KC0tvaTtKhs6dCiTJk1yvtZqtaSnp9O3b18ABg4cyJYtW4CKjN5Lly7F19fX2T4kJMRZOqWkpASdzvViWFpaGu3bt6dnz57OY9HR0Tz77LM4HA6OHj3Ka6+9RkREBJ9++mm9r++KLM8JUQu73c60fy0i3XQNikZp6u4IIUSjeHh4XNJ2lZ1bCispKWHixIlERUUxZ84cFEVxvl9cXAxQYykTPz8/UlNTCQ8P58yZMyQlJbm8V15eXrXkluee/CspKeGJJ57gqaeewm63M2bMGHr06FGv67siM01CuKCqKrMXvMu2U61QNFJaQAhx5evcuTN6vb7WNnq9nqCgoAZdPzs7mzFjxjB8+HCGDRvm3L8EYDKZ8PFxnaYlPj6esWPHsmbNGhISEpgwYYLLtoGBgeTk5FQ5VlhYyMaNG3F3d2fMmDG4u7vj5eVF//79ycjIqNf1XZGgSQgXFr+fxIYjGhRt/TZDCiFEc2U0GgkLC6u1TVhYWL03gQPk5+cTGRlJdHQ0I0eOBKB79+7OMigpKSn06dPH5fk+Pj54e3sD4O/v71xKc9XHzMxM9uzZA1T8yI2Pj2f79u0cOXKExx57DLvdjtVqZefOnYSGhtbr+q5IGRUhavDJytUkbDyGVZJXCiGaqcaUUakpT5Ner29Unqa4uDjWrl1bZZZqypQpxMXFYbVaCQoKIi4uDq32/Mz9oEGDWLt2LUajkdzcXKZOnUppaSk2m42JEyfWuIx3zvHjx5k+fTpms5nS0lLCwsKIiYnBYDCwZMkS1q1bh16vZ/jw4YwaNare16+JBE1CXODbjSm8+cUuSrV+Td0VIYRwqbG15ywWC4cOHXJmBA8KCmrQDFNLIhvBhahkx87d/OfLHZRK8kohxFXOYDDQtWvXpu5GreLj453Le5XNnDmz2kbwy0FmmoQ46+Chw0z9z2fkSC4mIcQVoLEzTaL+ZCO4EMCp/Hzi3l4hAZMQQgiXZHlOtHhms5lX57/PYVt7FEnFJIRoIWw2E4WFW7BaC9Hr/fDzux2dzrOpu9WsSdAkWjSbzcZr/1rEr+Z2zgRsQghxtTtxYgUnsj/F4ShzHjt67D0CA0YSGPhwE/aseZOgSbRYqqoy+9/vsr3AD0UrK9VCiJbhxIkVZGZ9VO24w1HmPC6BU80kaBIt1n/eS2TDMR2KrvbsuFey59v2xFtv4Jj5DEsLf2vq7gghmpjNZuJE9qe1tjmR/Snt2j2AVlu/UipWq5XY2FiysrKwWCyMGzeO4OBgYmJiUBSFLl26MG3aNGeW8IKCAiIiIli9ejVGo5Hi4mImT56M2WxGr9czd+5c2rZ1/SRzdnY2s2fPpqCggLKyMkJDQ4mNjcVgMBAXF8fOnTudpV0WLVqE3W4nOjqakpISfH19iYuLw9/fv15jlKBJtEjLPvuSVb+UgM67qbvSYAZgrG932nl4VSlVUNm5JccbvPx51f1WZpzYfhl7KIRobgoLt1RZkquJw1FGQcEW2ra9r17XXrVqFb6+vsydO5fCwkIeeughunbtSlRUFP369eO1115jw4YNDB48mM2bNzNv3jzy8/Od569cuZKQkBBeeuklli9fTkJCAjExMTXey263M378eF5//XVn0d64uDgWLlzIiy++SHp6Ou+99x6tW7d2njNnzhx69+7NM888w5YtW5g/fz7//Oc/6zVGCZpEi/O/b78ncdNRrLorJ3mlAlyjMRLh1wV/N0+XQVJt9A04RwhxdbFaCy9pu8qGDh3KkCFDnK+1Wi3p6en07dsXgIEDB5KamsrgwYPRaDQsXbqUESNGONuHhIRw6NAhoKLork7nOkRJS0ujffv2zoAJIDo6GofDgcPh4OjRo7z22mvk5+czcuRIRo4cyYEDB5g8eTIAvXr1Yvr06fUeowRNokXZnvYzi1f/jFnXpqm7UiMFuNunNYfLzPzJuzPXunmjKEqjNqmfS8W2tSj7EvVSCHGl0uvr9mOxru0qO7cUVlJSwsSJE4mKimLOnDnO7y9PT0+Ki4sBaixf4ufnR2pqKuHh4Zw5c4akpCSX98rLy6uW3NJoNDrv/8QTT/DUU09ht9sZM2YMPXr0oFu3bnz33Xd0796d7777jrKy2mfcaiI/PUWL8fuBA8xL2sBpbfMMmAAi215HdPsuLL2hN8GerdBoNC4DJgsWzhiPku/1M/kev5DvuZt83SHyfX7mVOsdlCoFZJqLeTVzK69mbmVN0bHLPBohRHPj53c7Go1brW00Gjdat769QdfPzs5mzJgxDB8+nGHDhlWZFTeZTPj4uK7nGR8fz9ixY1mzZg0JCQlMmDDBZdvAwEBycnKqHCssLGTjxo24u7szZswY3N3d8fLyon///mRkZPD000+TlZXFk08+SXZ2Nu3bt6/3+GSmSbQIeXl5/POdleQS0NRdqVUft9Z46ypqPxkUsKhQqimk1Gs/GK0VU1FnYyi1pljKuwgAB3CiVTofHJM/4kKI83Q6TwIDRtb49Nw5gQEj670JHCA/P5/IyEhee+01brvtNgC6d+/Otm3b6NevHykpKfTv39/l+T4+Pnh7V+wz9ff3x2QyuWwbFhZGZmYme/bs4eabb0ZVVeLj4zEajXTs2JHJkyfz+eef43A42LlzJw899BA7duxg+PDh9O/fn//9738NKkws36jiqmcuLWXa/KUcsQU06+SVXfW+FCseZFsdHFSOktvmiDNIqm+tIwVw1HBSN38bt19b8f73R+HAafkKEKKlOZdO4MI8TRqNW6PyNC1evJiioiIWLVrEokWLAJgyZQpxcXHMnz+foKCgKnueLjRp0iSmTp1KcnIyNpuNGTNmuGyr0WhYsGAB06dPx2w2U1paSlhYGFFRURgMBoYNG8YjjzyCXq9n+PDhdOnSBYPBwMsvvwzANddcw8yZM+s9Rqk9J65qNpuNmLgF7DjTBkVpfqvRbdxt+LrBmdMeTOzQi2JDFha/w86F87r84VRVKqIgFWdQ6HDA2z+DzVE1KHryJhutzs7M2xyw5oDC4TPaSzUcIcRl1Njac3Z7KQUF5zOCt259e4NmmFoS+ZkprlqqqjLzzcXsKGyeySu7+No43sVOya1DYMcqTplTwe18mFQ5YFLVitdabQm39FqLu1sZdhXWHbmHLw4+WOW6Gmw40OLRHRwOByUZ6RVRFHC6HGfQBBDgpXL4DNx3vY22HpByHMJvAL0WfsmFzZnyFSHE1Uqr9ah3WoHLLT4+nm3btlU7PnPmzGobwS8HmWkSV62F73zA53stoHdv6q7UKKq7lsX3D6mYHlIrTROpakWQY7fjZi0HwGAwo2oUyjTuWHEDNKBYedD6OWu/u7PW+9jtdkp+/eXsKwehbRyEtYMSC2zJ1NDOy8Gg6yvetdjBcHbiqcwK7+6SoEmI5qqxM02i/uQbUVyVkpZ/zqq9paBvvskrVT/v84FS5c1WigJaLWi1lBkqNoWXUdM4jHyv+RM/oEdVVYpxMEwxYa/1rhrS8zWkn88nR6C3wxmzldsqVvp0Gsg5uwfT22CjfyDsL4BjRfKVIYRoueQbUFx11q7fSNIPx7DrW1+8cRMqMHdo9DVOa3xZ0PdrHnD/HJ3Fh1e/eYbJRw7iHtQFrZsbqCol+3+t9Rq783S0Mtpo4wGrf1ewOkCvAaujYknzoRDwNkJnX3hvlwNHIzKVBFJAmD6HLdaOFGFAhwaLfA0J0SRsNhOFhef3NPn53Y5O59nU3WrW5NtKXFW2bd/B4q92NdvklZUl7kxn6PVt+L6zJzU+1ld5yc4VRcNHfg8QqKbRU7+Xsmt2wJFWBJd/y9EcP4pKfSqmjXQ6sNhcXibleNWvAquj0i0qTYZpNM7tURflh5mbdHnosXOt3kR71YT+7G16GfeiUrFP64xDwajCUbsn+Q4vMuz+5KoVM2tGbKgggZUQl9iJEyuqPT139Nh7jXp6riWQPU3iqvHbbwd4dfEX5NGuqbtSZzOu7c/hzkaSb/UETS0BkmoHrICeiv1Mlds6MFJGGzWfGPU1fBwlaM/uS/rB0pd39M/jULTYswqwrdoJpZZ69bG9h40+gXCgADIKXAcvXpi5RZ9NR60Zf8x46WxowBkcuZqfOvfw3zk2FYpUA27YcFMcaM4uG84t61vLVYRoeRq6p+nEiRW15mm6tsMTEji5IEGTuCrk5uby0twPOeZo3skrLxR33W3OfJU3tdPz8J0eOCOe2jj/2FbMw6AYAA0arMSpL9GR4wAsJIqflDvOt1XBbirD+uEPYK5f8OSKH8U86Z6Op/b8E3+Vg6RzE1OV8nI6c0jZqJjurhwvqpXOqfxJ2FX41hzAdkenS9JvIa50DQmabDYTu3ZH1lq0V6Nx45awpfVOP2C1WomNjSUrKwuLxcK4ceMIDg4mJiYGRVHo0qUL06ZNc2YJLygoICIigtWrV2M0GikuLmby5MmYzWb0ej1z586lbdu2Lu+XnZ3N7NmzKSgooKysjNDQUGJjYzEYDGzatIn//Oc/QEWCzWnTpjWqHNU58rNNXPFMphJee3MpR+31T4nfXKjA9eWw/dtSpm8vufgamKKc/UcDihvnwhEHOtbwgLPZSD5Gr5bjnM9RFDSebuhH3QbetZdSqI0eO5O8j/OK90+M96oImOB8YORQwaqCxQG/WVvxbdl1fFzaiX3l7iwoCWWmqT8zTf35l6k/H5V24YxdT55NT4lDyyGbJ6cdRiwX/JzTKjDEI5upXlt5zm0b50MrIURdFRZuqTVgAnA4yigo2FLva69atQpfX1+Sk5NZsmQJM2bMYNasWURFRZGcnIyqqmzYsAGAzZs3ExkZSX7++adSVq5cSUhICElJSYSHh5OQkODyXna7nfHjxxMZGUliYiIrVqxAp9OxcOFCSkpKmDt3LosXL2b58uV06NCBwsL6FyCuiWwUEFc0q9XK1H+9zf7ygEvyK6I5uL9ApefKU8z4y+/s0PcFRUvVBawaqIBqxQ0LXct+4QXHIozGYqZoX+V95XEOqdczm2mYFa+KvUm+HhhG34El4fuKta86elCXTqhbcUW8du7WZxNrQsVsUIalFfvtbfjVUf0X4sEaZgKPqf68Zfav8X6PG7bRUadyYZotX53KFK+fyLB68Vl5jzr3X4iWzmqtW/BQ13aVDR06tErGb61WS3p6On379gVg4MCBpKamMnjwYDQaDUuXLmXEiBHO9iEhIRw6dAioKLqr07kOUdLS0mjfvj09e/Z0HouOjsbhcLBjxw5CQkKYM2cOx48f5+GHH6Z160vzYJAETeKKpaoqcfPf5ufT/s0yeeXF+Jyd6HUm9FZVZ+AX4GXkwS+6MHnIs+BzCoCjdGAHt7CeeyhWO4Cm0h9fRUHrUHhiy3f8r1sEuW2uAa7hGft/edfxGDdoj7CEp/jefhdJyt8wOzzB3YD+8QFYk7ZAudVlPycbt+KhO7vkdkHsZjW4Y2l3LZjN7DhmJ8V+HZdyAjvJ0g8scLOSxTCP41UzMwDd9CXEarey02xgnVr/OlJCtDR6vd8lbVeZp2fFk3clJSVMnDiRqKgo5syZ4/xe8/T0pLi4GIABAwZUO9/Pz4/U1FTCw8M5c+YMSUlJLu+Vl5dXLbml0WgEKgr3btu2jS+++AIPDw8ef/xxwsLC6Ny5c73HdKEr728aIc5asHgpKVnuKFp9U3elQZ7w71blddlv653/rigKf/IxcujrGZA2HFToRBYj+IrFvECSEkEP9bsq5zsUBZ3DgZ+p2HlM1eqYZE3g0KFbyD/ZgdvtPzKsIBGHrSKbk7a1F22evZX3nlnGg7f+7DxPRznPuW0lxm0rnvqzT85VDphUsKGhLLALFvdWlLVuT6ZnB/6or5Q9agf+aerPgpIQimyVtnRR8URfb49Lsz9LiKudn9/taDS1L81rNG60bn17g66fnZ3NmDFjGD58OMOGDXPuXwIwmUz4+Pi4PDc+Pp6xY8eyZs0aEhISmDBhgsu2gYGB5OTkVDlWWFjIxo0b8fX15aabbqJt27Z4enrSp08f9u3b16DxXEiCJnFF+u/Hn/HVvnLQNXxfTlNrZzyfD8WhqlgyPsNedj7gURSFP7XSkLF7AIe//Ge1LTyvsAhFPb83QVUUtFoztx/Zh66s1Hm81OjFOz6R7Ns3iO0pT9Ju3UPYdxzm3AJbicabHzwH8/idu/jvk0lM8dzKy54/46uryFRQmUMFk11hcUlXZhX35Wi5AUWpyOsUHgJ929d9qa8himnNwrL+zDL1wXZBWoRxbtv/0HsLcTXQ6TwJDBhZa5vAgJENqkGXn59PZGQk0dHRjBxZcY/u3bs7y6CkpKTQp08fl+f7+Pjg7V2RbsTf3x+TyeSybVhYGJmZmezZsweomKmPj49n+/bt9OjRg99++42CggJsNhu7d+8mODi43uOpiQRN4orz9bpvWbYlC7vOq6m70mB6FLSVnpKzOxzYgdL/vYitUuCk0Rq4Z/c/abvxbTKWL0b/+Zt47b8fzEawwyvEcW5DURtO0r//p7T2P4yu8kZyjUJW2wCW9b4H1XYKgz2X+CwvOhWVg8OBFgcnuQYFcGtlQdGo1dJDqSrklMK/TH1409yPfHwB+PI3DSWWs3XxFOjbAQZc+8cGTlCx4X12af8q++X9dXbGuaUhG8SFqF1g4MNc2+GJajNOGo1bo9INLF68mKKiIhYtWsTo0aMZPXo0UVFRvPXWWzz66KNYrdYqe54uNGnSJL744gsef/xxnnvuOWbMmOGyrUajYcGCBbz11ls88cQTjBgxAlVViYqKonXr1rzwwguMHTuWRx55hMGDBxMSEtKgMV1IUg6IK8qWbTuYk7yZIm3zT15Zm3Y6dyYEhAEVAcf/O/4j3x9Kcv6K8R6+GOcTcdYyStZMwgJsuWMBduAW3SE6+nQl98YPOBh4kF2aMAbpvkGr2sg52pYXO/2nYt2qMtVBZOoaVNXOnWU34Ic/83q2Ia/4N55vPRMPr3JKctw59PX1OABFPVsGT4UvzB3IoObimP5uNh7pfr5mnUOF/+6BM5Y/fsukG2U877mrasoCFXLtBt4rC0N+F4qrWWNrz9ntpRQUnM8I3rr17Q2aYWpJJGgSV4x9GfuZ9s5qTipXTvJKVxRgYruetNa7oUHBjsqdP7yIu6Nib4770H+jM7qDAg5UHuj6HBqbjaFboBNvgl5PWUkGN7oX0MEjhH1eH+F/xz4cDoXf13Vm5kOzqxYAVhQM5WbsOj0ORUNIznHu+203N1k70sNxHd/lbCX2pIUAjYlTDiNlGHFw8XxRQ1t1QkVlY/Fh/q+XikapCJqOF8EXv12e50y8KGW8xx4MF8RHVgdkq178z3wdubS6LH0R4nJqCQV74+Pjnct7lc2cObPaRvDLQYImcUXIzs7m5Xkfcdxx5eZiulCYW2tGtr3R+drtzGFu3zUPANX7OnwGnf1CVOD+rs862znsUL6nE88XPQsGAzabDVvJW1WuvbH3Pey4ZSC6UhP/WPk2pZ1D+Sm4O/sCbwDAWG6m1/Hfue5ULq3NpRjsBo5lefJFfhFljrqlbghvdT23elcEsNuKszmoOcTgzhX9/SUXNmdWDZomXnM9D7VuT6nDzqgDaRTVtR5LHWiwMcljB541TCypVKS9WlzalcKzy4pCXA1aQtDU3EjQJJq9kpJino9bxO+WwKbuyiX1Uvte+OiNztdKzl7u2b8YAI1nOzzvmw5U/KWfrclj3A0zsegqUgPYyiHnuwH0umUnfzryMt6qb0XwZPoC1Fwq9vU48NT402XYEfDLJX9DBM//6X4cGi16qwWLwYBGVRm+cxPtTEXOfjhUOHwaVh+ofaZoWKvrCFMOgv0QRSh8X9qKE/o2eBjgaFH1c78KuZWORncU4ITFzJD9l37jthelPOOxF73iqHjir9J7qgqzTLfygOE3Cu1u/GA/9/ixA1nGE1ciCZouPwmaRLNmtViInvFvdpW0Q1Gurr/Yhvhcy52tzk8vl9kshKc+73x9+p7pXOvTzplE0q7YeST4JUp1ZagqZH36MKga3G0Wpl4/0LkcZ3M40Go0hHtpOPynsc5sbIvVcfzIXaiqFhwqdr0GVBWtw0G/Q3u5+cQR571VIOMU/O+Q68Dpbv1RbnfLrgg3zn6LWFXYbfEjx+FNsdc13NgGtmfDyVId0wK78NfWFTOFZaqDXaYzfHzqBBuLCxr5SVbwUcrQolKougPQXZPDX9yOoKv0v03lOncOx/nE6gBLTMHkqlf2XjnRsjQ2aDLZ7GwuLKHAaqO1Xsedfl546upQxqkFk+SWotkqKCggbkECu4raXpHJKy/mSFkJd7aq/PpMlfdf2vsdybdFOP9W16pa4o+8QmTwtIr6vWrF8VGFe7ktey3Hr70PxXKaMcYOLLm+H3qdvkrxttOKHzbl3B95G4pVRdVrsSsKW27oQaHBg7uO/MruwBs46t+OmzIP0C43j1xT9a+JN8d8SmDrYk7ubUXO1vMzgHoF+hgLsVOIOcgXh0bHNZ4aPtgD/+/E7xy1lHK/bzs6693o7dmKnu56Vh9bA8BBqyerLF0opf5pJAKUEka478dXUzET51DhTVMPPi8L4i/GQxi11QsDX7hPfqzHAQ7bMimy27jZYEOjqbjOXos73fRmVODt0p4UY0QDOGR2SlzBkrNP8Ul2AeZKy+RvH9fwaEBrHguoOUO/kJkm0Uzt2ZvOvA++5qi9/VVTHuVCXho9LwX2QlNpBk2xWbjn7GzT7dePYmvoADx1Fck7HaiUOGw8oCyi6GAXHOaKlAsbDyVxbpHvO/drmRpwF6FGT5K63MLBu//OuTdzac3zyrvOez155i1W6Mdh8jgfFIVkHeZIuw44NFqMlnKmrz3Bswf3V+l30sSlGCvlE9367o1o7Br0ZwvPKYAdMHe5uaL4sNXKF7+U46HY+dV+DQDfd70VX50Oq92KRS2j2FLAD3krKyasVDCroFE07LK04Vvr2Y1StbhJd5I/ux2sVuBXe3Zj+oWZzOujyuxUpWvtMnvxlV1KuIim09CZpuTsU3yQle/y/Sc7tJHAyQWZaRLNzhdfreXD9Rmc1gZUyxd0NSlxWFEdapXZICplN7+urJD++37EqCiMah3II/4BeGv1xFueZKz5F8pwEFRWwLkzHMA7fhV1mNLLTYz4PY0Xi+bSzd2b4lvn0+6a3yryCJwNAdy8LbzhiGSc4wPntMtvAdc7IwSb0Z2Xh9/Af37wYEfpDiyqSr42vUrApAC3/X0/2/d2481vw+hvyKSrrggfxYIh6wh2X3/0+Sd4zL0cuwIdLKUctnmxLftjuviG0c6tE556bzx13vRodQcZxT9hc1jwUCpG1NeYRx9jHqUOHQtLb6GP7gCD9YUV+5U0YHfAN6U+2Bw+FNm1+Gnt5/t2dhwXpiP4ydKKm3VncD+XIsFxtu6xi/9OVWanKr3o6VZCe+tW3rP0d3GmEM2PyWbnk+zal8Q/yS5g+DW+eGrrt1RntVqJjY0lKysLi8XCuHHjCA4OJiYmBkVR6NKlC9OmTXNmCS8oKCAiIoLVq1djNBopLi5m8uTJmM1m9Ho9c+fOpW3b6jUsz8nOzmb27NkUFBRQVlZGaGgosbGxGAwGNm3axH/+8x+gIsHmtGnTKC8vJzo6mlOnTuHp6cmcOXPqXZNO5pdFs2Gz2XjjrSUs+uYwp6/wPEyuTGrTg9cDbuXFdj2JantzlQSXClSpD6I7+zd0uarywaks8m023DRabnTzZkzbawF4qnBPxdNhwCG9D8fdfJ3nHyw3M+7Yr2w2nab9zy9z/cb5XFeaC6oDg1rKHcqPeGtLeVadg85hQetwoEcB1VHxj6Jg0yjMCvOilbtKGw+4vZPJ2VflXFe1cOvN+1jX7S58PG5nUWkv3jD1wVpiwu3EYXSWcizXBFJ+w0107ezNAOMJiu0n2XlqPacteaiqgoKW0Na389eOEwlwu6HKZ6IFvDU2/ua2lyFuhWi155fWtBq436uIYR6Z+GntOFQotsFJu47DVg/sKpyxa7HaK4KjrWVtWG/txjxzf+JKKv6ZWdqfd03dyLG7k2czYHVU/Gew2SpmllxRFGhvaMj/BUI0nc2FJVWW5Gpidjj4obCk3tdetWoVvr6+JCcns2TJEmbMmMGsWbOIiooiOTkZVVXZsGFDRT82byYyMpL8/PMzXitXriQkJISkpCTCw8NJSEhweS+73c748eOJjIwkMTGRFStWoNPpWLhwISUlJcydO5fFixezfPlyOnToQGFhIcuWLSMkJITk5GQefPBBFi1aVO8xykyTaBZOncpnxoIP2HXGD0Xn3dTd+UPEtuuFh6Fircy3pj96dhshe5cAFUHQYbeqv4B2lpwmxM0TDTDIpzW7TGe4w5yFlorlsEV+YTXe940TBwkyuhOq+PLZZgUwkdPpU4pDKrZF3aZJ4zYeY4f5ThI1E7Bio83pHA616wiKgl2tmL1RAL/jD6Bccxq8cgED6M7WfFPAW6djQvvOfHE6Dxs6FpT2ZpDhKL30udha+YNOj1avx+/aa3CcOIKiwPfZq/jMMYjlXXphVEBRNNx6zV8YnfE5N+lO00pr4hqtFZsD3DXmiyzSVcwEeevA02HjnfIwKK/bV9xJtRXvmXtWOz7Fc2ut5zXvzQ1CVFdgrVvG/lN1bFfZ0KFDq2T81mq1pKen07dvXwAGDhxIamoqgwcPRqPRsHTpUkaMGOFsHxISwqFDh4CKor+6C+s4VZKWlkb79u3p2fP8n9vo6GgcDgc7duwgJCSEOXPmcPz4cR5++GFat25NWloaY8eOdfZFgiZxRfp5127e/OgbjtnboWiv3vU4o7bmP26qqvJbUT7375pFByyowCe6jtXa/TvvCCnFp1gcdDM3uHkxJfAGjHsr3tMA290Carz+GYeNxw/uYt513ejh4U1rnZ72R0fic7obWb3fQD3brZus+1i5pQQ3jcpT1xfD2Ryiha38cHe05ga7J13tAazb9RccWjO9b//4/E0cgKqhzOFgUace3ODuwRcFObydpyHd4s+jZhN4+1a0bdUaRXHnmtOepBRmkHDdtWhVByoKCqDBzlud+1FuM7H11FcVs00a0NUjQNFo4Dnjz8SX31r3k2pgcYDRxQqFxQZvlN3SqOsLcbm11tftr33/OrarzNOzop5mSUkJEydOJCoqijlz5jj3pXp6elJcXFEmasCAAdXO9/PzIzU1lfDwcM6cOUNSUpLLe+Xl5VVLbmk0VvwoLSwsZNu2bXzxxRd4eHjw+OOPExYWRklJibO2XeW+1Icsz4km9emXX/P60u847rh6N3yfM/dEGpWfu1BVlWV5GbyauZXEogM81nkkC3x7MqNNP97qeGeN1zhYbqbcUZGr+3o3TzzurajNpABDig/Wev8Xju9jyP6fOFpuBsDzTCidU95CV+KPrvgaAg48yNFBz3Dg3r/za3BXKm8oe/PuO4i77SZmhkCpphyLqqW4IACVio3SduDXO6L4ss17BNy7EPPAadzfseI+2fjw1v42lBWfm5XSYGrlyeFOMLT7vbTxbI9Oq0NB4VR5DuV2EwEenbjepzt/7Rjl7MOF8fRJu5HKP4YvXHDw1tm5UZNX62dyMXPN/SizVeydcpwrK+OAz0s78a+y/jgwXvwiQjQjd/p54X7ho6MXcNdouMOvYbU9s7OzGTNmDMOHD2fYsGHO/UsAJpMJHx8fl+fGx8czduxY1qxZQ0JCAhMmTHDZNjAwkJycnCrHCgsL2bhxI76+vtx00020bdsWT09P+vTpw759+/Dy8nIWAb5YX1xp1EzT+vXrWbduHfPmzav23rvvvsvXX3+Nl5cXY8eO5Z577kFVVQYOHMj1118PVFQpfuGFFxrTBXGFslqtzF/0PusP2LHrr879Sxcqwc6rmVsxokGjKJhVe9UGisInrWt/GuuMw8bTh/bwSZdeFUGm1zXg2R5MOQw7c4A1fjfWej7AIwd28n7nm+nh4YPR5sUNW94A4FivOWj1FlDgBn7hIJVmURSFHE89pzv40TFTS6GHN733jUBp+2/g7B4jo4m7+vyMQ69W7LO64w3Gqw8TlnMT/f0CcSgOkhybsWrPhzfp+ixCygNpTcWvv9aGqhnfDVoDd1zzVzblruRcfGR1aNlhvYYfbJ3OHjHTFgt/cjtOZ935fRhaBUZ4HCLB5EauWv8vx7MD540y2egtrh6eOi2PBrSu9em5RwNa13sTOEB+fj6RkZG89tpr3HbbbUDFJuxt27bRr18/UlJS6N/f9Z8nHx8f50yQv7+/M8CpSVhYGJmZmezZs4ebb74ZVVWJj4/HaDQyduxYfvvtNwoKCvDx8WH37t088sgj9OrVi02bNnHzzTeTkpJC79696z3GBgdNcXFx/PDDD3Tr1q3ae/v37+err75ixYoVAERERNC/f3/y8vIIDQ1l8eLFDb2tuAqczMsj7q3/sruoNYq+5RWHLMfhTAbZEPvKTVVmgVRrCQoQ6jgNwI7uA9BrtewqOU308QzybJYq5zuAJw/voZubJx8H90Jz9lqtsu6kzD8DgOn8k8OOdkx1zAXd+f9GnmVmVvQdhFlvIOeUlXO/A1UV3FQ9pTYHqv7cjJKKp5uNXwP28yv7uf761dx63ekq+ZFKinWsTdPyWPlAFEWpcbaxg2cw2zXhfOsyCaY7J3EnqcybCOM+gvTFzil0DRCiPYXe4SDT0YqLpS4QoiU4l07gwjxN7prG5WlavHgxRUVFLFq0yLlfaMqUKcTFxTF//nyCgoKq7Hm60KRJk5g6dSrJycnYbDZmzJjhsq1Go2HBggVMnz4ds9lMaWkpYWFhREVFYTAYeOGFF5z7l4YOHUpISAjXXXcdL7/8MqNGjUKv19c44XMxDc7TtGbNGlq3bs0nn3zCm2++We29nTt3MnVqRQ6JqKgonnzySU6cOMGSJUvw8vLCzc2NV155haCgoFrvI3mari470naxYNk3HL+K8y/90fy1Wr7vfn4/QHHKfCjcj0Pvh/fQmVWmwy12O2/lHuaDUydqvNY1OgOdDR7c4unDM9d0pNz7CJl9/wn6ii9Shwqj1eUVm4qsFlqVlXLGqxU61YGCHZ1aytMs4IQ5iFY7PNBr7NzUcx1ubuWcyOpC5vFbaBewjaCg33D1w/X3327irgPj8da5Tmq5o+Q0Tx3eU6fPZ4j+d/oYT6GAc/lQQ8X+pJ+sbThg9SeTVlTeneCGhXaaYrrpCtln8+eow69O9xKiKTU6I7jdzg+FJZyy2vDX67jDz6tBM0wtyUWDphUrVvDhhx9WOTZz5kxuvvlmtm3bxscff1wtaDp48CAvvPACH330EVarlQcffJDZs2ej0+nIz8/n/vvvZ8eOHcyaNYvPPvus1g5K0HT1+PizVSSnHKJYK0nTGuuXmwY6/111ODAf/B734HtqDERLHTb6/fIDfvZyCvXutV43sV0wnYOKyb1ttnNSRgWUrBt5vP3rcDbRJqpaZbZLUe2oqkK3Y79x19H9uLlnckuvjS4DpcocDlj9v8d5xjEQT60OTQ0zTg9n7CDDWnrxi531qHEv1+tKsKkKbhq12vySVYXTdh1WVYO31oLn2TxNCmAD3im5iUI863w/IZpCS6g9Fx8fz7Zt26odnzlzZrWN4JfDRZfnHn74YR5++OF6XfSGG27g8ccf5x//+AedOnWiZ8+e+Pn50alTJ2demj59+pCbm4uqqjLjcJWzWiy88Z/3+faQA4deAqZLwWq3oz/7Z8mmqnh0GVTlfYfDgUOpyKqtLSsm9cgyFKAYHUOCHq3xmtMCbuWoTkfO8Tb0aDeE0qD/8YTyASqeaDqUgeI6AlIVLSiw7/quPOY/j85ehXUei0YD1wdvZcCq80mPWmt1rOlyK25aDbMzD9YrYAL4pLwHlIMfpYx131PtCTi9Am11NT9SrQV8NBYKHRI0CdHUnnvuOZ577rmm7obTH5JyoKCgwJlIqri4mMjISLp06cL8+fPx9fXlH//4BxkZGQQGBkrAdJXLyc0lbuGH7C1pi9KAR1hFzQbs28LnQb3RaRXaGavOHtlsVrauf533Qh5msbEc+4ENzpkWb+Azow2fg+sw28qJuO7PlGorngDTn82JUq4o7EwbQUZnDaqm4gkaB+5nE16evVAtf25f9XqH//JIvR7NtShlVV4X2G30z/ixxrZPtbmWbGsZ68643sh6TiEezDX3p7OmgK66U9ykO4Xu7JTShf1TVbCp8JvdV5bnhBA1uqR/iy1dupSOHTsyaNAgMjMzGTFiBHq9npdeegmtVsvTTz9NdHQ0mzZtQqvVMmvWrEt5e9HMbNuexsKPv+OEGlDbJIVoALOqMvTgDv7aqh2vd7zRGcuUnjqM5YfZdEHLXw6uxmrOPH+S17V4DZpKiKJAyCCKVj/LC6fTmdu2D2UOR5VZX1V1kLNnAJUfoEPRgMOG3gpW49mvjrOZw6tssFY0HFevoxPHq/S5cphVeU+A3Q6fbwq+6Jj7e7bixYAggoyeWHCgAGvrEDgBHHa05rClNWstXQAHXTT53GvMxFexoDsbPSkKOOzweXnXOl1TiCudyWZnc2EJBVYbrfU67vTzwlMnX9a1kYK94g+RtPwLPkk9IvuXLoN/X9eVXp6teOlIOr2Ob+LR4v3YFQ0lqoI/NueGaM/7/43WcH5WynIyA9WvMyZVYdyRvZy22vlb2+6UqXZ+LD5G7K/vMub1f1Hm15qqm5NUHrG+Q6puEM/xJq8ob1Hl95eq8gGj0HF++cvVvNS5Lx9VhccXjsZiq/l33I0GD5JDemGoVNw4PucI75w8Vp+PqkavuG91Dk8FTtoNvGvu5aK1nRvJZz8+QO37w4T4ozVmT1Ny9qlL/vRcSyBBk7ikLJZy/vVWAt8fUbDrG5YcTTSCw0Fi5hoCbMVnM2yrlKMyJvDPvHptN+4NuKFSUwca1Yaq0WFToVx1MOK3NE7YygEYVZjOMz5t8Os5kkdu8+BIq/MBjb96goVMRAWK8CKaOEwEAHZeUqdzXWEuvn6F1VbxnC8dONfHzn0BTXr/IbIKfWsc1jdBvQjwrPr/04Bft1Bkr3+ph5o8rttBZ7fz1/reHMgP9upZ2WM9tqLRVAR5/zKFYcX1E39C/NEaGjQlZ5+qNU/Tkx3aSODkggRN4pLJOnGCmf/5iHRTWxSN7F9qKhqHg3EFP/NoUQY6KoKSAsXAnLb96NChD1M7nl9+Uu1WVEVB0ehQALvDwbD9P3H8bG6nXd0HoNVqcQD97vOoNOOkMkmdSV9+rrbU9t3GR3AzGGnffj9dQn6q0jcFKgImB87JKZWKJ+geefOpGsfzc/cB6C54DE9VVW7eu7khH48LDmI9f0KjVPQnz25kibl6iZSpXudr0ZkcWt4sbVyZFiEaoyFBk8lm57E9h2ot2uuu0ZDcM6je6QesViuxsbFkZWVhsVgYN24cwcHBxMTEoCgKXbp0Ydq0ac60KAUFBURERLB69WqMRiPFxcVMnjwZs9mMXq9n7ty5tG3b1uX9srOzmT17NgUFBZSVlREaGkpsbCwHDx5k5syZzna7du3iP//5DwMHDnR5rbqSMiriktiybTsvzkviV3OABExNzKHR8KlPCFYqvvAUwFe18GzBLj45k4e90pelotVjd5wPe7QaDV937ed8fW4mRwOk/K+4Yg/T2asuIKYi84DZ1zmDtP9EG7Saio3lOTk3YrWe7ZOjohRJ+Rkfbvj2HbCeT5ipAHlnzj85d851ip7doXdUC5jsdjv9f02t/wdTKw2Z5rOZFIB22nL6aqr/YLNUSuJu1NirvS9Ec7e5sKTWgAnA7HDwQ2FJrW1qsmrVKnx9fUlOTmbJkiXMmDGDWbNmERUVRXJyMqqqsmHDhop+bN5MZGQk+fnnZ7xWrlxJSEgISUlJhIeHk5CQ4PJedrud8ePHExkZSWJiIitWrECn07Fw4UK6detGYmIiiYmJPPbYY/zpT3+6JAETSMFe0UiqqpL48Uo++fE4pbr2Fz9BXBa5Bm+GdBzJ9NzN3F6ejYpKgdaNQUWHyV73NR2GzkTRVAQjep0eu93uTAcCQEd/dL2uJ+6AiRirHlVV+bHUQY8DZeztcjbgUbSs3b+QyOID5PReCAp0vy6fMvNaik/cDwr886PR7C2o+jXzRVA5/of/wqmun4BGBRu4b5jLre4H2W6uKKDprdHydff+VZ6uVVWVoyXFDDuyq8Gfiw4rz7unoaUiQLIC88qCiXE7wIUF1e9zy+an0k5Vjv3L3J8n3ffQTlPKaYeBs1msGtwfIS63AmvdlrRP1bFdZUOHDq2S8Vur1ZKenk7fvn0BGDhwIKmpqQwePBiNRsPSpUsZMWKEs31ISAiHDh0CKor+6i78Q1lJWloa7du3p2fPns5j0dHROCoFhKWlpbz11lt89NFH9R6LKxI0iQYrLy9j1oL32Jypx6GT9e/mxqbTEdvhHjqUF3G7OYvPfG5kRu5mjLZiir95BZ+h/wIqghHz9gS8+v0DFAWLzYbbw/1AUUgJhpN7SxiZbkEBHtxZxt5gd2fKgd9bt8HnqDeVy2b2Csln/KYS8op8a+zXg4d+puMxHz4pfgFVceBeEIrOR0Nfn1tIP13I3FNH+ZO3f5WAyeFwcG/6D9TtWTnXJrinYagUG+qAqV4Hamxb5mLjwk/l7XnQ4xBttBb+7raLhLLqy3hCNFet65j6xb8BKWI8PStym5WUlDBx4kSioqKYM2eO88+yp6cnxcUVP4wGDBhQ7Xw/Pz9SU1MJDw/nzJkzJCUlubxXXl5eteSWRmPVAtqffvopQ4cOpXXr1vUeiyuyPCcaJPN4JlH/byHfn/DCoWt59eOuJFlGH1b4dsOh0fBfv1Dyte6UlRdTsvtj7JZSSra9i5qbRvGayRT/bwpapWq2733d3EFVcQce8NbQueDsmpsKOS6K6AW3P1lrn47ZrCTtD+C7I13RVrpXqK8fH9wQxmPXXIfd4UAFbDYbPS9BwAQVZWEu2sYBZivMN9dcWPQGXSEazi7j6covQa+EuHzu9PPCXVP7X/3uGg13+DXsQZ7s7GzGjBnD8OHDGTZsWJWyTiaTCR8f18Wz4+PjGTt2LGvWrCEhIYEJEya4bBsYGEhOTk6VY4WFhWzcuNH5evXq1fVOzn0xEjSJetucupUX3/yYjLIA5xKPaH6u03sRoK+a1Xq/Wxse6Ticwdc/StKpLArWTsYYfB9ew97GY+hcKMtHq9WD7ex+HVVl/G4TbfUK97XSodNquS3zbKCgwLFrjBVhU/H5L1irDbb8dgMX899TFcWBbfaa9wZpNRosNhu37NtS77G7sqDsVqz2iqW5C6kqWO1wzOHN2+VhLq+x1nK9M1TUAH81ZFyy/gnxR/PUaXk0oPaZl0cDWjeoBl1+fj6RkZFER0czcuRIALp37+4sg5KSkkKfPn1cnu/j44O3tzcA/v7+mEwml23DwsLIzMxkz56KmpSqqhIfH8/27dsBKC4uxmKxEBAQUO9x1EaenhN1pqoqHySv4NNt2ZTqLt10p7j0urn7cbfPtTiA/xUe5YilqMZ2HQxurA251Tl97rBZULR6FEUh36DgZVNxu2DP6K33ulN5A9CG/51hy2k75YDdYWdaVtUn5lzpbPDm7+16VPRXB9cYNXjpNGihytKc3W4n7JJv/IYumnyGux/CqDicu5LO7VByAGV22Gu7hi3Waymh6kb1ie7b8NFWfHUes7nx37KwS94/IS6mueVpiouLY+3atQQFBTmPTZkyhbi4OKxWK0FBQcTFxVXZPzlo0CDWrl2L0WgkNzeXqVOnUlpais1m+//t3Xl8VPW9//HXmTMzSUgCIRCWoEEQsK00AiqiFtGioldqtRYp1lh/tbfKvS1WKSK2UsEa9ddiXRAQoZRSWcVasCoqyKJUFGSXsG9BhEASss92zv0jMGRIQibrZHk/Hw8fj5xZvuczx5Phne/5nu+XUaNGVXgZ74zDhw8zceJEiouLKSoqok+fPjz++OO43W62bNnCtGnTmDJlSo0+S2UUmiQsJSUlpL80nU8yo7BduhzX2F0V14kr4joEe5r8gQATvv683MW0aBx8fuk1GBV015+7LuSZ7YGDWlESffZLLzWjgKEbS7CBZ498QQnnvzPnjHZmNI8klx8P5ABua20Gu/XrKzSVsvhZ9Da6OIuCk4CeeyR8NhTaTly2zSncfO5N4jp3Jonm2c+5rLgTXwQuqqcaRSpW2wV7CwMBPskp4KTPTzuXk++1jatRD1NLotAkVTp46BDpU+ezs7iDLsc1ESYGP0q8mMtiz85xUlkv0JKvP+SimydWuQ6kZVn8Oy/Aiu9G88l3zgbne2e+TubBIt5vXfVSKOea2OWqkDEPpXVafJC1nSm9+oJt8/TBDN4sqIsRTVUpXV7l9ph9RBuE9D7B+e+R8wZK76wTaUi1DU1NweTJk4OX98pKT08vNxC8ISg0yXmtXLOWqW+t5bjRMdKlSDU5MfjDBVeFhCG/FWDikc9D+oJaBTz8jgJuS70d8zyh+FRBPtft34gFuP53MI6Y6NLB0Ee/Zs7Tv2VTVBKjkm8672K+57rQjOXB5NTgdq6vhOnHt5Fn+arxSSvnAK6La8uaghzCn1XJJol8hkbvJ95RQpRh4C5zCa/cq214qzCZHZSfQVykPrWE0NTYKDRJhWzbZsbf5/PWhixKnFrxvSn7Q5ercJXpzbFsm3nHd7DDewqAPx9ZzpWeY3hxkHHt7+gclUTPWGdID5DHU8h7Hz3Hkyk3AeB8+GZMl6s0SPh9rBj1MwC8wI1dh+M3w79d+dKoBG5P7MHWoizeOVV3v++PJHXl/3XqWnrZzbZ5/eg+Xjl5pAYtWfRwnKSP8zhdnflYhoHPMogyLHwWvFxyKRBfZ3WLhEuhqeFpniYpp7i4mGdenM6nR2NAganJm3BkHeOT++M+PVbBYRj8tON3+OzUUd7JO8B3fNk4sXES4ITdmlMBg515AW6OtXCZDjI/+xuJWevof7qvxRx1E6bLdXYHZRbRdQMrDi5gavylzEvqE1Z92z25bD+6vq4+btB9SRcEe4cMw+CXyRfXMDQ52GMlscebVJoKRaTF0pQDEmLfvv08POEVPjmeAE6t4t5cTPz6c7K8obfvDmjTmTGd+rIqpgs+IBcnLtfZBWg/KLT59yk/+2O7YAM/6XAbQEhgsmwb78fbKXsxzQn8On87t2dtq78PFIZsb0m5xyZ36RmBSkSkuVBPkwQtX7mG6Us+5zidqzMsRZqIl45t4b/apHB1fHJwnFMbVzT25Y9S6b1phkFeyg3kHVtLTlwboHRA+Jlbhq1vcrE2Heb7KcNZcOhfJHM2qIzJ38ySpN71+ZHKcXbaRYfvbYQAbFzfiyExofNUDUzoyBetk7iyDud+EpGWQ2OaBNu2mf63uby98aTGL7UA7c0YHu58WcgA8aoyssNzinHHvzr7QL+uGAUl2LuOhbxu8b4FdKZ0zSob+G2HgfwnrmEGSCfevICYNmfHoScf68prJ36LaRjl7gz8KPc4jxzWpJTStGlMU8PT5bkWrqiwkCeeeZH5G4sUmFqIE4FiJmauC1nYshzbBr8/OHW23906NFh9ebBcYAK4q9vdwWE/FnBL/oE6qvr82t26gFYJoTfuHWh1hKu2f0qOt/xSJ1VNryAiUhGFphZs9549jJr4Kv85mQjO6KrfIM2GD5vxR9aR4ykgEAiUBqQzbJtBq3/NDZ/+Bix/6SzZhsGELldV3bBh8KtOgzluRGEA3y8+zISjq+vpU5Ryp2wjpoKb1wKFiXixGbTrc44V5GNZFrZtU+Tz8ptDO+q1JhFpnjSmqYX6YPlKXn9nAycMjV9qySYd3wrAoOLj3NJ9CLbDScrBd3EAo2Kv5Ho7QAKlA78dDgcTkvvzh6/Pv0zKtladmN/m24zK3QTAjcWH+Yu3iFx3/cwkn9hne7nHbMsgb/fZyTZv3L+xXvYtIi2LeppaGMuymDJzDi+8vZUTRodIlyONxCp3O675zziu+ex3dD/0ASXA+o69ePno5pDLeKZpMr7j5VW293brniEzaT93fFW91A2QuyU1ZAFeywdHl96G72jDzxYsIs2bQlMLUlhYwLg/vsiizSV4XAmRLkcaE9Pkb/G9cPlKpyX4T79nmdjlKp5Ivpxnjqyj7P0irjOTWp5HidPNPsfZa2YBf3jr0dVEyYFv4znWAezTiw57o7E8sVW8S0Sk+hSaWoiMnbsYNWEK63LaafySVGhWuz7sNeP5OHU0xMdjOhw4TSejO/ShpOTsVAKGYfDjhO7naalUWspQigA/cImVX3+FA7nbeuPLj8OX04bjHw6p132JSMulMU0twLvLljPzvU1kOzR+Sc7vN51vZHSbrsFtA2gVVX6S00uiwrjT0uGgxOGmleXFJMAvT2xgevuqL+3VhD87iWPv/1e9tC0icoZ6mpoxy7J4ZfpsXnpnB9kOjV+SqmW7W3Hw0JoqX7c5++uw2jtOaa+mAdydt6s2pYmIRJxCUzOVn5/H2Kf/wlvbvHhdbSJdjjQh0003p76YBJXM42RZFkt9R8Nqa0a7yzjTShQWw7PL3+lWY45A6X8iIg1EoakZ+mpHBqOensYXue01fklqpNAZxYA1v4HC4xinjuD1egkEAhT5PDx1ZF3Y7ayNT2GrMxEAExiVu4mfH/uy1vVFX3CQ5B8sIfkHS4jqnFnr9kREwqExTc3M0vc+ZNayLeRo/JLUwuuJlzE0L4Pr108kAPy8083saZVUo7bSkwYw/+i7GJRepnugcAf2SQez2vWpcX2tLjyM4SztZWrV9RCeoxfUuC0RkXCpp6mZCAQCvDj1r7zy3k5yNH5JasnrcBJPachxAg9kbapxW4dj2rIsqkvIvE0PnKrdZbq8Hd/CXxyNvzia/O3frlVbIiLhUk9TM5Cbk8vTL81kQ3YbDKfGL0ndKNtReUEgr1ZtTexyPcuz9/Kn3M+A0r/Whp7YzjvtL61Re/7c9hx7d2itahIRqS71NDVxW7d/xW/Sp7PhVBKGMyrS5UgzUmaSbZzUfnLKtW0uCmlzXN4mTK+30teLiDQ2Ck1N2NvvvM/419/nYKCzVm2XOlc2zrTBV+v2bNPkd22vDm4bwMrMRbVuV0SkoSg0NUGBQIBJk2cwZdlech01G5wrUpV10Z2DP7fBppXfU+s2V7btTtlJAvQFJCJNib6zmpiT2Sf57cQXWLrLwOdqHelypBl7quPA4EU5A1h66C2iA7W7nDYw/yBmme36W5GuGbiwHc6hfaCTximKNBYKTU3Ips1beSR9BhvzOmI43ZEuR5o5j+niX7EXB4NNDBbTjiwD2z7v+84nPeuTkO2R8VfVosJmzAHuYf0xv9UF990DIl2NiJym0NRELP7Xuzw16yMOW8kavyQN5k8dB7DNlRgcwN3Tn8c/DvyrRm31y8sM+cLJBrYl9ahtic1T2zgMx+mj5TLP/1oRaTAKTY2c3+/n/788nWkf7eeUo32ky5EW6KELb2WTo3SBXgPobhdyQ/6BarVxTcFhXj6xKjiNgQ3c3enOuiyzeTlZEOzRMwwDY4DCpUhjoNDUiJ3IymL0hL/w7l4nfo1fkgh6tMvgkPFHE7I+Zc2+N/hk3xus3vfGed/7g5ydPH98dciXzfKYCyhq1apeam0uLK8/+LPzyu4RrEREzlBoaqQ2bNzMb56bxeaCjhimK9LlSAvncUWxIrp0Vm+L0llxTUq/QJzAqn1v8OKRD3Fa/pD3fa/gEI/lrA8O/raA5VHJjO88qAGrb5p8b20I/my4nBCtuYhFIk2hqRFa+M+lTPzbCo7Ymn9JGo+Jnb7Hqpgu7HHGl7vrzQVc6TnO8gML+d8Tpf/YX1Jygj8e/zQYmPzAvZ1u4ckuNzRg1U3YkZPYntK7FQ0DHP11iU4k0vSnSyPi9/v58+QZfLTPIuDU+CVpXPwOJ090vh6ADt5cpmT+m46U/uV1ZjFeE5uf5GUwIi+DAGe/YALAi237cqBVuzqoxMLZ5hT+/HiwmvdXmOUJYEYBhoHZtZ2maBCJsOb9jdOE5OfnMf7Pr7Extx2GU5fjpHE77k7gx91/CkCCt4gJx9bwHV8uUfiDXypnurEDwPj2V/Nx67oZl5N0/ce422UTKGrFN+/dSnPuMLc+34N5Q+n6fIEdX0e4GhFRaGoE9u3bT/q0hezxdcIwm+8/ANI85bpb8fCFQwCYvW8RPSk/AeZnrbrU2f5cbbMxTAtnXAGYfgg03znLrE2H8Bw4Aaaj9I46EYko/QsdYWvXfcETkxez15+MYeh/hzRt49tfX+4xE/jg0Jt1txPj9EUqA2Iu2lN37daE04HzzitwPzQYo29K/ewjt0iBSaSRUE9TBC16+x3mfLyHfLNjpEsRqRMHWydhn4Bzb1+o0+kZjQp/jAijSyLmxaW/v+7B38Wz+VC9rg1j/mIQjvgYbCCwPRP7g231tzMRKUddGxFgWRYvTZvF68sPkm/WxcBYkcajomV9a77wSgVt+cxgo97jHeqw5eozLrswZNscklpv+zLvvgpnQhwO08Q0TdypXaGrvj9EGpJCUwMrKSnh98++xNtf+bXgrjRLDyUPIZ/QoFSXnS+GMxD82bai6rDl6jM7JYRsB3Z9U387c5bvr3P0UC+1SENSaGpA3xw7xiMTXmJtVltwRke6HJF6sSu6PUO6/5Tx5rcJAMXAwNN32tWejXG2o4lAYUwdtVszvhVfhWy7f3g5xNfP73Zg7loCRSXYZRZMtk/k18u+RKRiCk0NZNOWbYz502wyPMkYDi3AKc3f8q79GNj9pwyus8AE7g5HMc5kBhsiPixzzzF8h04Eu9UMhwP3A9fX22Ar/7TlIU3bO47Uz45EpEIKTQ3gvQ8/ZuJfPyDT6hzpUkSaNKskGivgwA6A50TbSJcDgLVwHf5vsoPbhmni/NGV9bOzuJiz1z0DFng13aVIQ1Joqke2bTNzzgJeXrqVHEdSpMsRafL8eYkEsLANcLXLofTiX+QF3vgPgW9yTwcaG6ugouHwdSCvGGvvMezcQnyfZNTPPkSkUoZd9gJ5I7Qx42CkS6gRn8/H8y+/zooDDmxXbKTLEWkW3P2X0uGiouB2IABHFw+PYEWhzO9/BztgYa3OgMQ4OFUEfvUGSf3Ifff3kS6hxdE8TfUgNyeXp16Yzqa89hguLYkiUmfsxt05Hjg9MNz1w8txXNwR27LxfbYLe9NBKPHX787btYIbU3HaNv4319XrfFEiLZVCUx3bvWcPz762mH3+zhhmpKfeE2levF/chrfLApxOsG04uviHkS6pYp0SwGFgOAzc3/sWXHsJni92w+rdddN+lwRcdw/AcDgwjPLfM8avhuB7eVnd7EtEghSa6tCaTz/jlTc/IctIpoLvMRGpA8ffbjyX4yoT2HoIx9U9CX4RGAZR/XvhDYD9+T7wBc7fwPm0jSHqJ9dwvi8Zw6U7dEXqg0JTHVmweAlzVu2n0KnJ5kRaOmvtbjz5xbhvSsVwnA037qt7wVU98by3EXYcrVHbzjuurDQwnRmi6l23r0Zti8j5Ne4BAk2AZVm88OpMZqzMpNCZGOlyRKSx2JqJXVzBXXQOA/ctl9W8Xd/ZsVEBvx/PzOV4/vxvPDNXYvgDGAEL18W6W1ekPig01UJxURFPPPMSS3da+F3xkS5HRBoZ35w1WCVeLL8/JEAZpgk1WALFHNoHs1Pp/FR2kRf/i8sgp6T0uX4XgcsJpgn+Wlz+E5FKKTTV0Ndff80jT0/ms+xELYkiIhUr8OKb/CG+F5dhnTPOyDW0b7WbMy9JDv5sn7MMspmaEvy5XtfAE2nBNKapBjZu2sykOR9wxO6sAd8iUiXnI7dgmqGhycouqHY7Ze+Us6NOf313ao3rx1dhOEr/BrZtG2vjgRrXKiKVU2iqpn+//xEz3t9CrqNTpEsRkSbAePD7IYHJtm38RcVYf/+k2m0FfH5MV+nXtrXvOK6Hb8HhNEPXuvMHNKGmSD3R5bkw2bbNa3+byyv/3kGulkQRkXBcmow7Pia4ads23ikfYk39uEbN+V9aRuBUEYFvcnF2bovDZZZfHNh04BrWvxZFi0hl1NMUBp/XS/qL01mV6cJ2JUS6HBFpUDaDv7uLhFbFvPvldyj2ucN+p+v7vUO2vRv2QLGvxpWYN3wbMzYKYqOwrTJjmmwbDAPbsjEMA+OCdhgpidiHsitvTESqTaGpCtnZ2Tz1wgy25CdhOHW4RFqa7154lJsvO704rgGLP+sT9nsDu4/iuDQFDPAVFMPKXbWqxfb4OTP+O7DjCI52cQRyCrH3Z2FelITRoyNGq6jSQtvGgkKTSJ1SCjiPnTt389yMf7Lf30lLooi0ULlF0fj8TtxOP3lF1btT1np/K54vD5bOrZRTVPUbqmpv7W58AQtMB9ba3ZSdWMC/6xtc3z57d52jSzusvBLsY6egyFvrfYuIQlOlVq5Zy6tvreWEoTvkRFqywycTee3Dq2kbV8yWg8lVv+Fcx/PqtB5r3d5KnzPss5fsHEmxOHtdju3x4/3rSvDU84LBIi2AQlMF5i56m7lrDmpJFBEBSoPT4ZMNvNPWUVDsD3+dujZRGG5XcNPRvg0YRulEmq1jICu/ngoVaTkUmsoIBAL8ZcpfeX+3n4CWRBGRCHE9eiuO0/MuefYchbe/rPI9zvuvD30guFgwuH56Db5XPoSApiIQqQ2FptOKCgt5atI0Pj/RBsMZF+lyRKSl6tQmGJgAnN06cO6FNaP3BZh9u+JIjMcwDSyb8lMPlOFwOjGu6YG9pnYD0UVauhqFpvz8fMaMGUNBQQE+n4/HH3+cvn1DlwRYuHAh8+fPx+l0MnLkSG644QZKSkoYM2YMJ0+eJDY2lueff57ExMj36GQezuTpKXPZWdIRw6mpq0Qkgk7kY9t2cPZv/97M0OfbtsJ983fBcASDUjjfWmZyYrnwJSLVU6OEMGvWLAYMGMA//vEPnn32WSZOnBjyfFZWFnPmzGH+/PnMnDmTF154Aa/Xy7x58+jVqxdz587ljjvuYMqUKXXyIWpj/YZNjH1xPrs8nTEMBSYRiTC/hXfyB/iLSvCs2gpLtoU87bzlMnA4ztuzVKE2WiNTpLZq1NN0//3343aXTvAWCASIiooKeX7Lli307dsXt9uN2+0mJSWFjIwMNmzYwC9+8QsArrvuuoiHpiXvfsjMZdvIMzXgW0QaEY+fwJTlFT5lxEefnavpVAGONrEha9JVyLbhZGEdFynS8lQZmhYtWsTs2bNDHktPTyc1NZWsrCzGjBnDE088EfJ8QUEB8fHxwe3Y2FgKCgpCHo+NjSU/PzJ3c9i2zbRZb/D2xly8rvYRqUFEpCZ8H23FPaQPtteP/6+rcD9yK2XnRbEsKzgmyrIs7IMnwLLxL9kQqZJFmo0qQ9OwYcMYNmxYucd37tzJo48+ymOPPUb//qHrHMXFxVFYePavmsLCQuLj40MeLywspHXr1rWtv9q8Xg/P/GU6q49EgatNg+9fRKRW9p3AO/Wj0p/dTowyg8axLNh7HN+RbIxWUQRWZ0SmRpFmqkaDePbs2cPDDz/MpEmTGDRoULnnU1NT2bBhAx6Ph/z8fPbu3UuvXr3o168fq1atAmD16tVcfvnltau+mk6eOMHoCS+x6mgcOGOqfoOISGMWE7oOngX4PtyKtX6/ApNIPTBsu8wUsmEaOXIkO3fupEuXLkBpz9LUqVOZNWsWKSkpDB48mIULF7JgwQJs2+bBBx9kyJAhFBcXM3bsWLKysnC5XEyaNImkpKTz7mtjxsGafbJz7MjYyfMz/8UBf6eqr/+LiDQR5s+vw2wbh+0P4Hv9Yy2Z0oLkvvv7SJfQ4tQoNDWkughNK1Z9wtS313HC6FAHFYmIiESeQlPDa/aTW86Zv5h5azMpdiowiYiISM0129AUCAT48+SZfLA3gKUlUURERKSWmmVoKiws4A9/eo31OQkYGvAtIiIidaDZhaaDhw7xx1fns9vbEcPUDN8iIiJSN5pNaLJtm4VvLeWtT3dznM7oBjkRERGpS80iNO3evYcpbyxhU3YcaMC3iIiI1IMmHZp8Xi/T/76AD7ZkkedMauKfRkRERBqzJhszPlu3npn/XMHu4vYYzvNPkCkiIiJSW00uNOXn5/HyjLms2e/D4+yMYUa6IhEREWkJmkxosm2bpe9+wIIVmzlidcRwxka6JBEREWlBmkRoyszMZPLsxXzxjRvLpTvjREREpOE1+tA0642FLP3iEDmOjuCKdDUiIiLSUjX60PT3z/PA7BjpMkRERKSFa/xTZptRka5AREREpAmEJhEREZFGQKFJREREJAwKTSIiIiJhUGgSERERCYNCk4iIiEgYFJpEREREwqDQJCIiIhIGhSYRERGRMCg0iYiIiIRBoUlEREQkDApNIiIiImFQaBIREREJg0KTiIiISBgUmkRERETCoNAkIiIiEgaFJhEREZEwKDSJiIiIhEGhSURERCQMCk0iIiIiYVBoEhEREQmDQpOIiIhIGBSaRERERMKg0CQiIiISBoUmERERkTAoNImIiIiEQaFJREREJAwKTSIiIiJhUGgSERERCYNCk4iIiEgYFJpEREREwqDQJCIiIhIGhSYRERGRMCg0iYiIiIRBoUlEREQkDApNIiIiImFQaBIREREJg0KTiIiISBgUmkRERETCoNAkIiIiEgaFJhEREZEwKDSJiIiIhEGhSURERCQMCk0iIiIiYVBoEhEREQmDQpOIiIhIGBSaRERERMKg0CQiIiISBoUmERERkTAoNImIiIiEQaFJREREJAwKTSIiIiJhUGgSERERCYNCk4iIiEgYFJpEREREwuCsyZvy8/MZM2YMBQUF+Hw+Hn/8cfr27RvymoULFzJ//nycTicjR47khhtuwLZtrrvuOi666CIA+vTpw+jRo2v9IURERETqW41C06xZsxgwYAD3338/+/btY/To0fzzn/8MPp+VlcWcOXNYvHgxHo+He+65h2uvvZajR49y6aWXMm3atDr7ACIiIiINoUah6f7778ftdgMQCASIiooKeX7Lli307dsXt9uN2+0mJSWFjIwMMjMzOXbsGGlpaURHRzNu3Di6d+9e+08hIiIiUs+qDE2LFi1i9uzZIY+lp6eTmppKVlYWY8aM4Yknngh5vqCggPj4+OB2bGwsBQUFJCUl8ctf/pJbb72V9evXM2bMGBYvXnze/ee++/vqfB4RERGRelFlaBo2bBjDhg0r9/jOnTt59NFHeeyxx+jfv3/Ic3FxcRQWFga3CwsLiY+Pp0ePHpimCcAVV1zBsWPHsG0bwzBq+zlERERE6lWN7p7bs2cPDz/8MJMmTWLQoEHlnk9NTWXDhg14PB7y8/PZu3cvvXr1YvLkycFeq4yMDJKTkxWYREREpEkwbNu2q/umkSNHsnPnTrp06QKU9ixNnTqVWbNmkZKSwuDBg1m4cCELFizAtm0efPBBhgwZwqlTpxgzZgxFRUWYpsn48eO5+OKL6/xDiYiIiNS1GoUmERERkZZGk1uKiIiIhEGhSURERCQMCk0iIiIiYYh4aNq8eTNpaWnlHp81axa33XYbaWlppKWlsW/fPizLYvz48QwfPpy0tDQOHjwYgYojqzrHC+COO+4IPjZu3LiGLjfiKjteW7Zs4Z577mHEiBGMGjUKj8ej84vqHS/Q+VXR8crKygoek7S0NK644grmzZun8+u06hwz0DlW2e/kkiVLuPPOO7nrrruYO3cugM6xhmBH0PTp0+2hQ4faw4YNK/fc6NGj7a1bt4Y8tmzZMnvs2LG2bdv2xo0b7YceeqhB6mwsqnu8SkpK7B/+8IcNVF3jU9nxsizLvv322+0DBw7Ytm3bCxcutPfu3avzq5rHS+dX5b+PZ3z55Zd2Wlqa7ff7W/z5ZdvVP2Y6xyo/Xtdee62dk5Njezwe+8Ybb7Rzc3N1jjWAiPY0paSk8Morr1T43Pbt25k+fTojRozgtddeA2DDhg0MHDgQKF3sd9u2bQ1Wa2NQ3eOVkZFBcXExP//5z7nvvvvYtGlTA1YbeZUdr/3795OQkMDs2bO59957yc3NpXv37jq/qnm8dH5V/vsIYNs2Tz/9NE899RSmabb48wuqf8x0jlV+vC655BLy8/Pxer3BSaJ1jtW/Gq09V1eGDBlCZmZmhc/ddttt3HPPPcTFxfGrX/2Kjz/+mIKCAuLi4oKvMU0Tv9+P0xnRj9Fgqnu8kpOTeeCBBxg2bBgHDhzgv//7v3n//fdb/PHKyclh48aNPPnkk3Tt2pWHHnqI3r176/yq5vFKTEzU+VXJ7yPAihUr6NmzZ3B9zZZ+fkH1j1l0dLTOsUqOV8+ePbnrrruIiYnhpptuonXr1jrHGkDExzRVxLZtfvazn5GYmIjb7WbQoEF89dVX5ZZnsSxLJwOVH69u3bpx++23YxgG3bp1IyEhgaysrEiXG3EJCQl07dqVHj164HK5GDhwINu2bdP5VYnKjpfOr/NbsmQJd999d3Bb51fVzj1mOscqlpGRwcqVK1m+fDkrVqwgOzub9957T+dYA2iUoamgoIChQ4dSWFiIbdusW7eO3r17069fP1avXg3Apk2b6NWrV4QrbRwqO15vvvkmzz33HADHjh0LLprc0l144YUUFhYGB0muX7+enj176vyqRGXHS+fX+W3fvp1+/foFt3V+Ve3cY6ZzrGLx8fFER0cTFRWFaZokJiaSl5enc6wBNKoIunTpUoqKihg+fDiPPPII9913H263m6uvvppBgwZhWRaffvopP/nJT7Btm/T09EiXHFFVHS+v18u4ceMYMWIEhmGQnp7eov/qKHu8nnnmGUaPHo1t2/Tt25frr79e59c5qjpeOr9ClT1e2dnZxMbGhqytedNNN+n8OkdVx+zHP/6xzrEyyh6v4cOHc8899+ByuUhJSeHOO+/E6XTqHKtnWkZFREREJAyN8vKciIiISGOj0CQiIiISBoUmERERkTAoNImIiIiEQaFJREQkgipbX66st956i2HDhvGjH/2IV199tYEqk3O13Hs3RUREIuz1119nyZIlxMTEVPqaQ4cOMW/ePObMmYPb7ebll1/G5/PhcrkasFIB9TSJiIhEzLnry+3cuZO0tDTS0tL49a9/TX5+PmvXrqV3796MHTuWe++9l379+ikwRYh6mkRERCLk3PXlnnzySdLT0+nRoweLFi1ixowZREdHs379eubNm4fH42HEiBG8+eabtG7dOoKVt0wKTSIiIo3E3r17mTBhAgA+n49u3bqRmppK//79iYuLIy4ujosvvpgDBw6Qmpoa4WpbHoUmERGRRqJbt248//zzJCcns2HDBrKysujWrRtz587F4/EQCATYu3cvKSkpkS61RVJoEhERaSSeeuopxo4dSyAQAOCZZ56hW7du3HXXXYwYMQLbtvmf//kfEhISIltoC6W150RERETCoLvnRERERMKg0CQiIiISBoUmERERkTAoNImIiIiEQaFJREREJAwKTSIiIiJhUGgSERERCcP/AbLtEIE9AReSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn')\n",
    "\n",
    "# create unique fig, ax\n",
    "fig, ax = plt.subplots(figsize=(10, 7))\n",
    "\n",
    "# adding layers\n",
    "world.plot(ax=ax, color='#CED7E0', edgecolor='black')\n",
    "geodataor.plot(ax=ax, column = 'ind_ident', markersize=7, alpha=0.8, cmap='tab10', legend=True)\n",
    "\n",
    "# limits\n",
    "ax.set(xlim=(1500000, 1800000), ylim=(-2050000, -1800000))\n",
    "\n",
    "# plt.axis('off')\n",
    "plt.grid(False)\n",
    "ax.set_facecolor('#0F4983')\n",
    "\n",
    "plt.title('Adélie Penguins tracks in Antarctic')\n",
    "\n",
    "ax.get_legend().set_bbox_to_anchor((1.2,1))\n",
    "ax.get_legend().set_title(\"Penguin ID\")\n",
    "\n",
    "plt.savefig(r'png/penguin-tracks.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "dfc0b6b9",
   "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>timestamp</th>\n",
       "      <th>long</th>\n",
       "      <th>lat</th>\n",
       "      <th>comments</th>\n",
       "      <th>migration_</th>\n",
       "      <th>tag_tech_s</th>\n",
       "      <th>sensor_typ</th>\n",
       "      <th>individual</th>\n",
       "      <th>tag_ident</th>\n",
       "      <th>ind_ident</th>\n",
       "      <th>study_name</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>year</th>\n",
       "      <th>geometry</th>\n",
       "      <th>t</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-01 00:43:00</td>\n",
       "      <td>139.74282</td>\n",
       "      <td>-66.57103</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74282 -66.57103)</td>\n",
       "      <td>2018-01-01 00:43:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-01 00:44:00</td>\n",
       "      <td>139.74310</td>\n",
       "      <td>-66.57141</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74310 -66.57141)</td>\n",
       "      <td>2018-01-01 00:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-01 00:45:00</td>\n",
       "      <td>139.74364</td>\n",
       "      <td>-66.57182</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74364 -66.57182)</td>\n",
       "      <td>2018-01-01 00:45:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-01 00:46:00</td>\n",
       "      <td>139.74420</td>\n",
       "      <td>-66.57211</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74420 -66.57211)</td>\n",
       "      <td>2018-01-01 00:46:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-01 00:47:00</td>\n",
       "      <td>139.74433</td>\n",
       "      <td>-66.57228</td>\n",
       "      <td>2017-2018</td>\n",
       "      <td>Chick-rearing</td>\n",
       "      <td>AxyTrek</td>\n",
       "      <td>gps</td>\n",
       "      <td>None</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>2018_C15</td>\n",
       "      <td>Adélie penguins, Sphenisciforms, foraging acti...</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>None</td>\n",
       "      <td>2018</td>\n",
       "      <td>POINT (139.74433 -66.57228)</td>\n",
       "      <td>2018-01-01 00:47:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            timestamp       long       lat   comments     migration_  \\\n",
       "0 2018-01-01 00:43:00  139.74282 -66.57103  2017-2018  Chick-rearing   \n",
       "1 2018-01-01 00:44:00  139.74310 -66.57141  2017-2018  Chick-rearing   \n",
       "2 2018-01-01 00:45:00  139.74364 -66.57182  2017-2018  Chick-rearing   \n",
       "3 2018-01-01 00:46:00  139.74420 -66.57211  2017-2018  Chick-rearing   \n",
       "4 2018-01-01 00:47:00  139.74433 -66.57228  2017-2018  Chick-rearing   \n",
       "\n",
       "  tag_tech_s sensor_typ individual tag_ident ind_ident  \\\n",
       "0    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "1    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "2    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "3    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "4    AxyTrek        gps       None  2018_C15  2018_C15   \n",
       "\n",
       "                                          study_name        date  time  year  \\\n",
       "0  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "1  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "2  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "3  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "4  Adélie penguins, Sphenisciforms, foraging acti...  2021-05-20  None  2018   \n",
       "\n",
       "                      geometry                    t  \n",
       "0  POINT (139.74282 -66.57103)  2018-01-01 00:43:00  \n",
       "1  POINT (139.74310 -66.57141)  2018-01-01 00:44:00  \n",
       "2  POINT (139.74364 -66.57182)  2018-01-01 00:45:00  \n",
       "3  POINT (139.74420 -66.57211)  2018-01-01 00:46:00  \n",
       "4  POINT (139.74433 -66.57228)  2018-01-01 00:47:00  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geodata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "57f53113",
   "metadata": {},
   "outputs": [],
   "source": [
    "geodata = geodata[['t', 'ind_ident', 'geometry']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9d4624f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "User Guide: https://docs.kepler.gl/docs/keplergl-jupyter\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "20193fb280d44e94b29b15855a8df016",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "KeplerGl(data={'Penguins': {'index': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create KeplerGl instance\n",
    "m = KeplerGl(height=600)\n",
    "\n",
    "# Add stop durations\n",
    "m.add_data(geodata, 'Penguins')\n",
    "\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ee362ebc",
   "metadata": {},
   "outputs": [],
   "source": [
    "config={\n",
    "  \"version\": \"v1\",\n",
    "  \"config\": {\n",
    "    \"visState\": {\n",
    "      \"filters\": [\n",
    "        {\n",
    "          \"dataId\": [\n",
    "            \"Penguins\"\n",
    "          ],\n",
    "          \"id\": \"ui3c9pzr\",\n",
    "          \"name\": [\n",
    "            \"t\"\n",
    "          ],\n",
    "          \"type\": \"timeRange\",\n",
    "          \"value\": [\n",
    "            1514764800000,\n",
    "            1514795331000.0002\n",
    "          ],\n",
    "          \"enlarged\": True,\n",
    "          \"plotType\": \"histogram\",\n",
    "          \"animationWindow\": \"free\",\n",
    "          \"yAxis\": None\n",
    "        }\n",
    "      ],\n",
    "      \"layers\": [\n",
    "        {\n",
    "          \"id\": \"0ka3h8l\",\n",
    "          \"type\": \"geojson\",\n",
    "          \"config\": {\n",
    "            \"dataId\": \"Penguins\",\n",
    "            \"label\": \"Penguins\",\n",
    "            \"color\": [\n",
    "              221,\n",
    "              178,\n",
    "              124\n",
    "            ],\n",
    "            \"columns\": {\n",
    "              \"geojson\": \"geometry\"\n",
    "            },\n",
    "            \"isVisible\": True,\n",
    "            \"visConfig\": {\n",
    "              \"opacity\": 0.05,\n",
    "              \"strokeOpacity\": 0.8,\n",
    "              \"thickness\": 0.1,\n",
    "              \"strokeColor\": [\n",
    "                112,\n",
    "                108,\n",
    "                99\n",
    "              ],\n",
    "              \"colorRange\": {\n",
    "                \"name\": \"Uber Viz Qualitative 3\",\n",
    "                \"type\": \"qualitative\",\n",
    "                \"category\": \"Uber\",\n",
    "                \"colors\": [\n",
    "                  \"#12939A\",\n",
    "                  \"#DDB27C\",\n",
    "                  \"#88572C\",\n",
    "                  \"#FF991F\",\n",
    "                  \"#F15C17\",\n",
    "                  \"#223F9A\",\n",
    "                  \"#DA70BF\",\n",
    "                  \"#125C77\",\n",
    "                  \"#4DC19C\",\n",
    "                  \"#776E57\",\n",
    "                  \"#17B8BE\",\n",
    "                  \"#F6D18A\",\n",
    "                  \"#B7885E\",\n",
    "                  \"#FFCB99\",\n",
    "                  \"#F89570\"\n",
    "                ]\n",
    "              },\n",
    "              \"strokeColorRange\": {\n",
    "                \"name\": \"Global Warming\",\n",
    "                \"type\": \"sequential\",\n",
    "                \"category\": \"Uber\",\n",
    "                \"colors\": [\n",
    "                  \"#5A1846\",\n",
    "                  \"#900C3F\",\n",
    "                  \"#C70039\",\n",
    "                  \"#E3611C\",\n",
    "                  \"#F1920E\",\n",
    "                  \"#FFC300\"\n",
    "                ]\n",
    "              },\n",
    "              \"radius\": 8.4,\n",
    "              \"sizeRange\": [\n",
    "                0,\n",
    "                10\n",
    "              ],\n",
    "              \"radiusRange\": [\n",
    "                0,\n",
    "                50\n",
    "              ],\n",
    "              \"heightRange\": [\n",
    "                0,\n",
    "                500\n",
    "              ],\n",
    "              \"elevationScale\": 5,\n",
    "              \"stroked\": False,\n",
    "              \"filled\": True,\n",
    "              \"enable3d\": False,\n",
    "              \"wireframe\": False\n",
    "            },\n",
    "            \"hidden\": False,\n",
    "            \"textLabel\": [\n",
    "              {\n",
    "                \"field\": None,\n",
    "                \"color\": [\n",
    "                  255,\n",
    "                  255,\n",
    "                  255\n",
    "                ],\n",
    "                \"size\": 18,\n",
    "                \"offset\": [\n",
    "                  0,\n",
    "                  0\n",
    "                ],\n",
    "                \"anchor\": \"start\",\n",
    "                \"alignment\": \"center\"\n",
    "              }\n",
    "            ]\n",
    "          },\n",
    "          \"visualChannels\": {\n",
    "            \"colorField\": {\n",
    "              \"name\": \"ind_ident\",\n",
    "              \"type\": \"string\"\n",
    "            },\n",
    "            \"colorScale\": \"ordinal\",\n",
    "            \"sizeField\": None,\n",
    "            \"sizeScale\": \"linear\",\n",
    "            \"strokeColorField\": None,\n",
    "            \"strokeColorScale\": \"quantile\",\n",
    "            \"heightField\": None,\n",
    "            \"heightScale\": \"linear\",\n",
    "            \"radiusField\": None,\n",
    "            \"radiusScale\": \"linear\"\n",
    "          }\n",
    "        }\n",
    "      ],\n",
    "      \"interactionConfig\": {\n",
    "        \"tooltip\": {\n",
    "          \"fieldsToShow\": {\n",
    "            \"Penguins\": [\n",
    "              {\n",
    "                \"name\": \"t\",\n",
    "                \"format\": None\n",
    "              },\n",
    "              {\n",
    "                \"name\": \"ind_ident\",\n",
    "                \"format\": None\n",
    "              }\n",
    "            ]\n",
    "          },\n",
    "          \"compareMode\": False,\n",
    "          \"compareType\": \"absolute\",\n",
    "          \"enabled\": True\n",
    "        },\n",
    "        \"brush\": {\n",
    "          \"size\": 0.5,\n",
    "          \"enabled\": False\n",
    "        },\n",
    "        \"geocoder\": {\n",
    "          \"enabled\": False\n",
    "        },\n",
    "        \"coordinate\": {\n",
    "          \"enabled\": False\n",
    "        }\n",
    "      },\n",
    "      \"layerBlending\": \"normal\",\n",
    "      \"splitMaps\": [],\n",
    "      \"animationConfig\": {\n",
    "        \"currentTime\": None,\n",
    "        \"speed\": 1\n",
    "      }\n",
    "    },\n",
    "    \"mapState\": {\n",
    "      \"bearing\": 0,\n",
    "      \"dragRotate\": False,\n",
    "      \"latitude\": -66.56305043473054,\n",
    "      \"longitude\": 140.99577134704958,\n",
    "      \"pitch\": 0,\n",
    "      \"zoom\": 6.3634568363126816,\n",
    "      \"isSplit\": False\n",
    "    },\n",
    "    \"mapStyle\": {\n",
    "      \"styleType\": \"dark\",\n",
    "      \"topLayerGroups\": {},\n",
    "      \"visibleLayerGroups\": {\n",
    "        \"label\": True,\n",
    "        \"road\": True,\n",
    "        \"border\": False,\n",
    "        \"building\": True,\n",
    "        \"water\": True,\n",
    "        \"land\": True,\n",
    "        \"3d building\": False\n",
    "      },\n",
    "      \"threeDBuildingColor\": [\n",
    "        9.665468314072013,\n",
    "        17.18305478057247,\n",
    "        31.1442867897876\n",
    "      ],\n",
    "      \"mapStyles\": {}\n",
    "    }\n",
    "  }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4a0af4e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Map saved to index.html!\n"
     ]
    }
   ],
   "source": [
    "# Save map as html\n",
    "m.save_to_html(file_name='index.html', config=config)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "gis",
   "language": "python",
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "pygments_lexer": "ipython3",
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