Covid.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "UsageError: unrecognized arguments: #To place the content properly in the notebook\n"
     ]
    }
   ],
   "source": [
    "import numpy as np \n",
    "import matplotlib.pyplot as plt \n",
    "import matplotlib.colors as mcolors\n",
    "import pandas as pd \n",
    "import random\n",
    "import math\n",
    "import time\n",
    "from sklearn.linear_model import LinearRegression, BayesianRidge\n",
    "from sklearn.model_selection import RandomizedSearchCV, train_test_split\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.svm import SVR\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error\n",
    "import datetime\n",
    "import operator \n",
    "plt.style.use('fivethirtyeight')#\n",
    "%matplotlib inline #To place the content properly in the notebook\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "confirmed_df = pd.read_csv('confirm_1.csv')\n",
    "deaths_df = pd.read_csv('confirm_2.csv')\n",
    "recoveries_df = pd.read_csv('confirm_3.csv')\n",
    "latest_data = pd.read_csv('confirm_4.csv')\n",
    "us_medical_data = pd.read_csv('confirm_5.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
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       "  Province/State Country/Region      Lat     Long  1/22/20  1/23/20  1/24/20  \\\n",
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       "\n",
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     "execution_count": 55,
     "metadata": {},
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   "source": [
    "confirmed_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
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       "  Province/State Country/Region      Lat     Long  1/22/20  1/23/20  1/24/20  \\\n",
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     "execution_count": 56,
     "metadata": {},
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   "source": [
    "deaths_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
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       "      <td>...</td>\n",
       "      <td>3968</td>\n",
       "      <td>4062</td>\n",
       "      <td>4256</td>\n",
       "      <td>4426</td>\n",
       "      <td>4784</td>\n",
       "      <td>4747</td>\n",
       "      <td>4918</td>\n",
       "      <td>5129</td>\n",
       "      <td>5277</td>\n",
       "      <td>5422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>42.5063</td>\n",
       "      <td>1.5218</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>639</td>\n",
       "      <td>639</td>\n",
       "      <td>652</td>\n",
       "      <td>653</td>\n",
       "      <td>653</td>\n",
       "      <td>663</td>\n",
       "      <td>676</td>\n",
       "      <td>676</td>\n",
       "      <td>681</td>\n",
       "      <td>684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Angola</td>\n",
       "      <td>-11.2027</td>\n",
       "      <td>17.8739</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 133 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Province/State Country/Region      Lat     Long  1/22/20  1/23/20  1/24/20  \\\n",
       "0            NaN    Afghanistan  33.0000  65.0000        0        0        0   \n",
       "1            NaN        Albania  41.1533  20.1683        0        0        0   \n",
       "2            NaN        Algeria  28.0339   1.6596        0        0        0   \n",
       "3            NaN        Andorra  42.5063   1.5218        0        0        0   \n",
       "4            NaN         Angola -11.2027  17.8739        0        0        0   \n",
       "\n",
       "   1/25/20  1/26/20  1/27/20  ...  5/20/20  5/21/20  5/22/20  5/23/20  \\\n",
       "0        0        0        0  ...      930      938      996     1040   \n",
       "1        0        0        0  ...      758      771      777      783   \n",
       "2        0        0        0  ...     3968     4062     4256     4426   \n",
       "3        0        0        0  ...      639      639      652      653   \n",
       "4        0        0        0  ...       17       17       17       18   \n",
       "\n",
       "   5/24/20  5/25/20  5/26/20  5/27/20  5/28/20  5/29/20  \n",
       "0     1075     1097     1128     1138     1209     1259  \n",
       "1      789      795      803      812      823      851  \n",
       "2     4784     4747     4918     5129     5277     5422  \n",
       "3      653      663      676      676      681      684  \n",
       "4       18       18       18       18       18       18  \n",
       "\n",
       "[5 rows x 133 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recoveries_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Admin2</th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Country_Region</th>\n",
       "      <th>Last_Update</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long_</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>Combined_Key</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45001.0</td>\n",
       "      <td>Abbeville</td>\n",
       "      <td>South Carolina</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:50</td>\n",
       "      <td>34.223334</td>\n",
       "      <td>-82.461707</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>Abbeville, South Carolina, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22001.0</td>\n",
       "      <td>Acadia</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:50</td>\n",
       "      <td>30.295065</td>\n",
       "      <td>-92.414197</td>\n",
       "      <td>401</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>379</td>\n",
       "      <td>Acadia, Louisiana, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>51001.0</td>\n",
       "      <td>Accomack</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:50</td>\n",
       "      <td>37.767072</td>\n",
       "      <td>-75.632346</td>\n",
       "      <td>807</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>795</td>\n",
       "      <td>Accomack, Virginia, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16001.0</td>\n",
       "      <td>Ada</td>\n",
       "      <td>Idaho</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:50</td>\n",
       "      <td>43.452658</td>\n",
       "      <td>-116.241552</td>\n",
       "      <td>803</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>781</td>\n",
       "      <td>Ada, Idaho, US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19001.0</td>\n",
       "      <td>Adair</td>\n",
       "      <td>Iowa</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:50</td>\n",
       "      <td>41.330756</td>\n",
       "      <td>-94.471059</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>Adair, Iowa, US</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      FIPS     Admin2  Province_State Country_Region          Last_Update  \\\n",
       "0  45001.0  Abbeville  South Carolina             US  2020-05-29 02:32:50   \n",
       "1  22001.0     Acadia       Louisiana             US  2020-05-29 02:32:50   \n",
       "2  51001.0   Accomack        Virginia             US  2020-05-29 02:32:50   \n",
       "3  16001.0        Ada           Idaho             US  2020-05-29 02:32:50   \n",
       "4  19001.0      Adair            Iowa             US  2020-05-29 02:32:50   \n",
       "\n",
       "         Lat       Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "0  34.223334  -82.461707         37       0          0      37   \n",
       "1  30.295065  -92.414197        401      22          0     379   \n",
       "2  37.767072  -75.632346        807      12          0     795   \n",
       "3  43.452658 -116.241552        803      22          0     781   \n",
       "4  41.330756  -94.471059          8       0          0       8   \n",
       "\n",
       "                    Combined_Key  \n",
       "0  Abbeville, South Carolina, US  \n",
       "1          Acadia, Louisiana, US  \n",
       "2         Accomack, Virginia, US  \n",
       "3                 Ada, Idaho, US  \n",
       "4                Adair, Iowa, US  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latest_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Country_Region</th>\n",
       "      <th>Last_Update</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long_</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Incident_Rate</th>\n",
       "      <th>People_Tested</th>\n",
       "      <th>People_Hospitalized</th>\n",
       "      <th>Mortality_Rate</th>\n",
       "      <th>UID</th>\n",
       "      <th>ISO3</th>\n",
       "      <th>Testing_Rate</th>\n",
       "      <th>Hospitalization_Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:58</td>\n",
       "      <td>32.3182</td>\n",
       "      <td>-86.9023</td>\n",
       "      <td>16530</td>\n",
       "      <td>591</td>\n",
       "      <td>9355.0</td>\n",
       "      <td>6584.0</td>\n",
       "      <td>1</td>\n",
       "      <td>337.127806</td>\n",
       "      <td>200481.0</td>\n",
       "      <td>1765.0</td>\n",
       "      <td>3.575318</td>\n",
       "      <td>84000001</td>\n",
       "      <td>USA</td>\n",
       "      <td>4088.791265</td>\n",
       "      <td>10.677556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alaska</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:58</td>\n",
       "      <td>61.3707</td>\n",
       "      <td>-152.4044</td>\n",
       "      <td>424</td>\n",
       "      <td>10</td>\n",
       "      <td>366.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>2</td>\n",
       "      <td>57.959524</td>\n",
       "      <td>47970.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.358491</td>\n",
       "      <td>84000002</td>\n",
       "      <td>USA</td>\n",
       "      <td>6557.354640</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:58</td>\n",
       "      <td>-14.2710</td>\n",
       "      <td>-170.1320</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>174.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16</td>\n",
       "      <td>ASM</td>\n",
       "      <td>312.719038</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:58</td>\n",
       "      <td>33.7298</td>\n",
       "      <td>-111.4312</td>\n",
       "      <td>17877</td>\n",
       "      <td>860</td>\n",
       "      <td>4452.0</td>\n",
       "      <td>12565.0</td>\n",
       "      <td>4</td>\n",
       "      <td>245.606472</td>\n",
       "      <td>202914.0</td>\n",
       "      <td>2848.0</td>\n",
       "      <td>4.810651</td>\n",
       "      <td>84000004</td>\n",
       "      <td>USA</td>\n",
       "      <td>2787.771526</td>\n",
       "      <td>15.931085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-05-29 02:32:58</td>\n",
       "      <td>34.9697</td>\n",
       "      <td>-92.3731</td>\n",
       "      <td>6538</td>\n",
       "      <td>125</td>\n",
       "      <td>4583.0</td>\n",
       "      <td>1830.0</td>\n",
       "      <td>5</td>\n",
       "      <td>216.647602</td>\n",
       "      <td>118902.0</td>\n",
       "      <td>640.0</td>\n",
       "      <td>1.911900</td>\n",
       "      <td>84000005</td>\n",
       "      <td>USA</td>\n",
       "      <td>3940.017311</td>\n",
       "      <td>9.788926</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Province_State Country_Region          Last_Update      Lat     Long_  \\\n",
       "0         Alabama             US  2020-05-29 02:32:58  32.3182  -86.9023   \n",
       "1          Alaska             US  2020-05-29 02:32:58  61.3707 -152.4044   \n",
       "2  American Samoa             US  2020-05-29 02:32:58 -14.2710 -170.1320   \n",
       "3         Arizona             US  2020-05-29 02:32:58  33.7298 -111.4312   \n",
       "4        Arkansas             US  2020-05-29 02:32:58  34.9697  -92.3731   \n",
       "\n",
       "   Confirmed  Deaths  Recovered   Active  FIPS  Incident_Rate  People_Tested  \\\n",
       "0      16530     591     9355.0   6584.0     1     337.127806       200481.0   \n",
       "1        424      10      366.0     48.0     2      57.959524        47970.0   \n",
       "2          0       0        NaN      0.0    60       0.000000          174.0   \n",
       "3      17877     860     4452.0  12565.0     4     245.606472       202914.0   \n",
       "4       6538     125     4583.0   1830.0     5     216.647602       118902.0   \n",
       "\n",
       "   People_Hospitalized  Mortality_Rate       UID ISO3  Testing_Rate  \\\n",
       "0               1765.0        3.575318  84000001  USA   4088.791265   \n",
       "1                  NaN        2.358491  84000002  USA   6557.354640   \n",
       "2                  NaN             NaN        16  ASM    312.719038   \n",
       "3               2848.0        4.810651  84000004  USA   2787.771526   \n",
       "4                640.0        1.911900  84000005  USA   3940.017311   \n",
       "\n",
       "   Hospitalization_Rate  \n",
       "0             10.677556  \n",
       "1                   NaN  \n",
       "2                   NaN  \n",
       "3             15.931085  \n",
       "4              9.788926  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_medical_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Province/State', 'Country/Region', 'Lat', 'Long', '1/22/20', '1/23/20',\n",
      "       '1/24/20', '1/25/20', '1/26/20', '1/27/20',\n",
      "       ...\n",
      "       '5/20/20', '5/21/20', '5/22/20', '5/23/20', '5/24/20', '5/25/20',\n",
      "       '5/26/20', '5/27/20', '5/28/20', '5/29/20'],\n",
      "      dtype='object', length=133)\n"
     ]
    }
   ],
   "source": [
    "cols = confirmed_df.keys()\n",
    "print(cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "confirmed = confirmed_df.loc[:, cols[4]:cols[-1]]\n",
    "deaths = deaths_df.loc[:, cols[4]:cols[-1]]\n",
    "recoveries = recoveries_df.loc[:, cols[4]:cols[-1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "dates = confirmed.keys()\n",
    "world_cases = []\n",
    "total_deaths = [] \n",
    "mortality_rate = []\n",
    "recovery_rate = [] \n",
    "total_recovered = [] \n",
    "total_active = [] \n",
    "\n",
    "china_cases = [] \n",
    "italy_cases = []\n",
    "us_cases = [] \n",
    "spain_cases = [] \n",
    "france_cases = [] \n",
    "germany_cases = [] \n",
    "uk_cases = [] \n",
    "russia_cases = [] \n",
    "brazil_cases = []\n",
    "india_cases = [] \n",
    "\n",
    "china_deaths = [] \n",
    "italy_deaths = []\n",
    "us_deaths = [] \n",
    "spain_deaths = [] \n",
    "france_deaths = [] \n",
    "germany_deaths = [] \n",
    "uk_deaths = [] \n",
    "russia_deaths = []\n",
    "brazil_deaths = [] \n",
    "india_deaths = []\n",
    "\n",
    "china_recoveries = [] \n",
    "italy_recoveries = []\n",
    "us_recoveries = [] \n",
    "spain_recoveries = [] \n",
    "france_recoveries = [] \n",
    "germany_recoveries = [] \n",
    "uk_recoveries = [] \n",
    "russia_recoveries = [] \n",
    "brazil_recoveries = [] \n",
    "india_recoveries = [] \n",
    "\n",
    "\n",
    "for i in dates:\n",
    "    confirmed_sum = confirmed[i].sum()\n",
    "    death_sum = deaths[i].sum()\n",
    "    recovered_sum = recoveries[i].sum()\n",
    "    \n",
    "    # confirmed, deaths, recovered, and active\n",
    "    world_cases.append(confirmed_sum)\n",
    "    total_deaths.append(death_sum)\n",
    "    total_recovered.append(recovered_sum)\n",
    "    total_active.append(confirmed_sum-death_sum-recovered_sum)\n",
    "    \n",
    "    # calculate rates\n",
    "    mortality_rate.append(death_sum/confirmed_sum)\n",
    "    recovery_rate.append(recovered_sum/confirmed_sum)\n",
    "\n",
    "    # case studies \n",
    "    china_cases.append(confirmed_df[confirmed_df['Country/Region']=='China'][i].sum())\n",
    "    italy_cases.append(confirmed_df[confirmed_df['Country/Region']=='Italy'][i].sum())\n",
    "    us_cases.append(confirmed_df[confirmed_df['Country/Region']=='US'][i].sum())\n",
    "    spain_cases.append(confirmed_df[confirmed_df['Country/Region']=='Spain'][i].sum())\n",
    "    france_cases.append(confirmed_df[confirmed_df['Country/Region']=='France'][i].sum())\n",
    "    germany_cases.append(confirmed_df[confirmed_df['Country/Region']=='Germany'][i].sum())\n",
    "    uk_cases.append(confirmed_df[confirmed_df['Country/Region']=='United Kingdom'][i].sum())\n",
    "    russia_cases.append(confirmed_df[confirmed_df['Country/Region']=='Russia'][i].sum())\n",
    "    brazil_cases.append(confirmed_df[confirmed_df['Country/Region']=='Brazil'][i].sum())\n",
    "    india_cases.append(confirmed_df[confirmed_df['Country/Region']=='India'][i].sum())\n",
    "    \n",
    "    china_deaths.append(deaths_df[deaths_df['Country/Region']=='China'][i].sum())\n",
    "    italy_deaths.append(deaths_df[deaths_df['Country/Region']=='Italy'][i].sum())\n",
    "    us_deaths.append(deaths_df[deaths_df['Country/Region']=='US'][i].sum())\n",
    "    spain_deaths.append(deaths_df[deaths_df['Country/Region']=='Spain'][i].sum())\n",
    "    france_deaths.append(deaths_df[deaths_df['Country/Region']=='France'][i].sum())\n",
    "    germany_deaths.append(deaths_df[deaths_df['Country/Region']=='Germany'][i].sum())\n",
    "    uk_deaths.append(deaths_df[deaths_df['Country/Region']=='United Kingdom'][i].sum())\n",
    "    russia_deaths.append(deaths_df[deaths_df['Country/Region']=='Russia'][i].sum())\n",
    "    brazil_deaths.append(deaths_df[deaths_df['Country/Region']=='Brazil'][i].sum())\n",
    "    india_deaths.append(deaths_df[deaths_df['Country/Region']=='India'][i].sum())\n",
    "    \n",
    "    china_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='China'][i].sum())\n",
    "    italy_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='Italy'][i].sum())\n",
    "    us_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='US'][i].sum())\n",
    "    spain_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='Spain'][i].sum())\n",
    "    france_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='France'][i].sum())\n",
    "    germany_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='Germany'][i].sum())\n",
    "    uk_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='United Kingdom'][i].sum())\n",
    "    russia_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='Russia'][i].sum())\n",
    "    brazil_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='Brazil'][i].sum())\n",
    "    india_recoveries.append(recoveries_df[recoveries_df['Country/Region']=='India'][i].sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "def daily_increase(data):\n",
    "    d = [] \n",
    "    for i in range(len(data)):\n",
    "        if i == 0:\n",
    "            d.append(data[0])\n",
    "        else:\n",
    "            d.append(data[i]-data[i-1])\n",
    "    return d \n",
    "\n",
    "# confirmed cases\n",
    "world_daily_increase = daily_increase(world_cases)\n",
    "china_daily_increase = daily_increase(china_cases)\n",
    "italy_daily_increase = daily_increase(italy_cases)\n",
    "us_daily_increase = daily_increase(us_cases)\n",
    "spain_daily_increase = daily_increase(spain_cases)\n",
    "france_daily_increase = daily_increase(france_cases)\n",
    "germany_daily_increase = daily_increase(germany_cases)\n",
    "uk_daily_increase = daily_increase(uk_cases)\n",
    "russia_daily_increase = daily_increase(russia_cases)\n",
    "brazil_daily_increase = daily_increase(brazil_cases)\n",
    "india_daily_increase = daily_increase(india_cases)\n",
    "\n",
    "# deaths\n",
    "world_daily_death = daily_increase(total_deaths)\n",
    "china_daily_death = daily_increase(china_deaths)\n",
    "italy_daily_death = daily_increase(italy_deaths)\n",
    "us_daily_death = daily_increase(us_deaths)\n",
    "spain_daily_death = daily_increase(spain_deaths)\n",
    "france_daily_death = daily_increase(france_deaths)\n",
    "germany_daily_death = daily_increase(germany_deaths)\n",
    "uk_daily_death = daily_increase(uk_deaths)\n",
    "russia_daily_death = daily_increase(russia_deaths)\n",
    "brazil_daily_death = daily_increase(brazil_deaths)\n",
    "india_daily_death = daily_increase(india_deaths)\n",
    "\n",
    "# recoveries\n",
    "world_daily_recovery = daily_increase(total_recovered)\n",
    "china_daily_recovery = daily_increase(china_recoveries)\n",
    "italy_daily_recovery = daily_increase(italy_recoveries)\n",
    "us_daily_recovery = daily_increase(us_recoveries)\n",
    "spain_daily_recovery = daily_increase(spain_recoveries)\n",
    "france_daily_recovery = daily_increase(france_recoveries)\n",
    "germany_daily_recovery = daily_increase(germany_recoveries)\n",
    "uk_daily_recovery = daily_increase(uk_recoveries)\n",
    "russia_daily_recovery = daily_increase(russia_recoveries)\n",
    "brazil_daily_recovery = daily_increase(brazil_recoveries)\n",
    "india_daily_recovery = daily_increase(india_recoveries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "days_since_1_22 = np.array([i for i in range(len(dates))]).reshape(-1, 1)\n",
    "world_cases = np.array(world_cases).reshape(-1, 1)#-1 in reshape function is used when you dont know or want to explicitly tell the dimension of that axis\n",
    "total_deaths = np.array(total_deaths).reshape(-1, 1)#converts to a 1X1 matrix \n",
    "total_recovered = np.array(total_recovered).reshape(-1, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "days_in_future = 10#\n",
    "future_forcast = np.array([i for i in range(len(dates)+days_in_future)]).reshape(-1, 1)#\n",
    "adjusted_dates = future_forcast[:-10]#"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = '1/22/2020'\n",
    "start_date = datetime.datetime.strptime(start, '%m/%d/%Y')\n",
    "future_forcast_dates = []\n",
    "for i in range(len(future_forcast)):\n",
    "    future_forcast_dates.append((start_date + datetime.timedelta(days=i)).strftime('%m/%d/%Y'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_confirmed, X_test_confirmed, y_train_confirmed, y_test_confirmed = train_test_split(days_since_1_22, world_cases, test_size=0.48, shuffle=False) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\vsulg\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\sklearn\\utils\\validation.py:760: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    }
   ],
   "source": [
    "# svm_confirmed = svm_search.best_estimator_\n",
    "svm_confirmed = SVR(shrinking=True, kernel='poly',gamma=0.01, epsilon=1,degree=4, C=0.1)\n",
    "svm_confirmed.fit(X_train_confirmed, y_train_confirmed)\n",
    "svm_pred = svm_confirmed.predict(future_forcast)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'svm_confirmed' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-1-e5981cc05288>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# check against testing data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0msvm_test_pred\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msvm_confirmed\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_test_confirmed\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my_test_confirmed\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msvm_test_pred\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Test Data'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'SVM Predictions'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'svm_confirmed' is not defined"
     ]
    }
   ],
   "source": [
    "# check against testing data\n",
    "svm_test_pred = svm_confirmed.predict(X_test_confirmed)\n",
    "plt.plot(y_test_confirmed)\n",
    "plt.plot(svm_test_pred)\n",
    "plt.legend(['Test Data', 'SVM Predictions'])\n",
    "print('MAE:', mean_absolute_error(svm_test_pred, y_test_confirmed))\n",
    "print('MSE:',mean_squared_error(svm_test_pred, y_test_confirmed))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transform our data for polynomial regression\n",
    "poly = PolynomialFeatures(degree=3)\n",
    "poly_X_train_confirmed = poly.fit_transform(X_train_confirmed)\n",
    "poly_X_test_confirmed = poly.fit_transform(X_test_confirmed)\n",
    "poly_future_forcast = poly.fit_transform(future_forcast)\n",
    "\n",
    "bayesian_poly = PolynomialFeatures(degree=4)\n",
    "bayesian_poly_X_train_confirmed = bayesian_poly.fit_transform(X_train_confirmed)\n",
    "bayesian_poly_X_test_confirmed = bayesian_poly.fit_transform(X_test_confirmed)\n",
    "bayesian_poly_future_forcast = bayesian_poly.fit_transform(future_forcast)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 776985.4044694622\n",
      "MSE: 1280357643764.035\n"
     ]
    }
   ],
   "source": [
    "# polynomial regression\n",
    "linear_model = LinearRegression(normalize=True, fit_intercept=False)\n",
    "linear_model.fit(poly_X_train_confirmed, y_train_confirmed)\n",
    "test_linear_pred = linear_model.predict(poly_X_test_confirmed)\n",
    "linear_pred = linear_model.predict(poly_future_forcast)\n",
    "print('MAE:', mean_absolute_error(test_linear_pred, y_test_confirmed))\n",
    "print('MSE:',mean_squared_error(test_linear_pred, y_test_confirmed))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-5.56776336e+04  1.53654009e+04 -6.42931280e+02  8.39267869e+00]]\n"
     ]
    }
   ],
   "source": [
    "print(linear_model.coef_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cbd0b43780>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_test_confirmed)\n",
    "plt.plot(test_linear_pred)\n",
    "plt.legend(['Test Data', 'Polynomial Regression Predictions'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 8 concurrent workers.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 40 candidates, totalling 120 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Done  34 tasks      | elapsed:    3.7s\n",
      "[Parallel(n_jobs=-1)]: Done 105 out of 120 | elapsed:    3.9s remaining:    0.5s\n",
      "[Parallel(n_jobs=-1)]: Done 120 out of 120 | elapsed:    3.9s finished\n",
      "c:\\users\\vsulg\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\sklearn\\utils\\validation.py:760: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "RandomizedSearchCV(cv=3, error_score=nan,\n",
       "                   estimator=BayesianRidge(alpha_1=1e-06, alpha_2=1e-06,\n",
       "                                           alpha_init=None, compute_score=False,\n",
       "                                           copy_X=True, fit_intercept=False,\n",
       "                                           lambda_1=1e-06, lambda_2=1e-06,\n",
       "                                           lambda_init=None, n_iter=300,\n",
       "                                           normalize=False, tol=0.001,\n",
       "                                           verbose=False),\n",
       "                   iid='deprecated', n_iter=40, n_jobs=-1,\n",
       "                   param_distributions={'alpha_1': [1e-07, 1e-06, 1e-05, 0.0001,\n",
       "                                                    0.001],\n",
       "                                        'alpha_2': [1e-07, 1e-06, 1e-05, 0.0001,\n",
       "                                                    0.001],\n",
       "                                        'lambda_1': [1e-07, 1e-06, 1e-05,\n",
       "                                                     0.0001, 0.001],\n",
       "                                        'lambda_2': [1e-07, 1e-06, 1e-05,\n",
       "                                                     0.0001, 0.001],\n",
       "                                        'normalize': [True, False],\n",
       "                                        'tol': [1e-06, 1e-05, 0.0001, 0.001,\n",
       "                                                0.01]},\n",
       "                   pre_dispatch='2*n_jobs', random_state=None, refit=True,\n",
       "                   return_train_score=True, scoring='neg_mean_squared_error',\n",
       "                   verbose=1)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# bayesian ridge polynomial regression\n",
    "tol = [1e-6, 1e-5, 1e-4, 1e-3, 1e-2]\n",
    "alpha_1 = [1e-7, 1e-6, 1e-5, 1e-4, 1e-3]\n",
    "alpha_2 = [1e-7, 1e-6, 1e-5, 1e-4, 1e-3]\n",
    "lambda_1 = [1e-7, 1e-6, 1e-5, 1e-4, 1e-3]\n",
    "lambda_2 = [1e-7, 1e-6, 1e-5, 1e-4, 1e-3]\n",
    "normalize = [True, False]\n",
    "\n",
    "bayesian_grid = {'tol': tol, 'alpha_1': alpha_1, 'alpha_2' : alpha_2, 'lambda_1': lambda_1, 'lambda_2' : lambda_2, \n",
    "                 'normalize' : normalize}\n",
    "\n",
    "bayesian = BayesianRidge(fit_intercept=False)\n",
    "bayesian_search = RandomizedSearchCV(bayesian, bayesian_grid, scoring='neg_mean_squared_error', cv=3, return_train_score=True, n_jobs=-1, n_iter=40, verbose=1)\n",
    "bayesian_search.fit(bayesian_poly_X_train_confirmed, y_train_confirmed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'tol': 1e-05,\n",
       " 'normalize': True,\n",
       " 'lambda_2': 1e-06,\n",
       " 'lambda_1': 1e-06,\n",
       " 'alpha_2': 1e-06,\n",
       " 'alpha_1': 0.001}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bayesian_search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 561572.7205084361\n",
      "MSE: 435342715537.853\n"
     ]
    }
   ],
   "source": [
    "bayesian_confirmed = bayesian_search.best_estimator_\n",
    "test_bayesian_pred = bayesian_confirmed.predict(bayesian_poly_X_test_confirmed)\n",
    "bayesian_pred = bayesian_confirmed.predict(bayesian_poly_future_forcast)\n",
    "print('MAE:', mean_absolute_error(test_bayesian_pred, y_test_confirmed))\n",
    "print('MSE:',mean_squared_error(test_bayesian_pred, y_test_confirmed))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cbd0c21358>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_test_confirmed)\n",
    "plt.plot(test_bayesian_pred)\n",
    "plt.legend(['Test Data', 'Bayesian Ridge Polynomial Predictions'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def country_plot(x, y1, y2, y3, y4, country):\n",
    "    plt.figure(figsize=(16, 9))\n",
    "    plt.plot(x, y1)\n",
    "    plt.title('{} Confirmed Cases'.format(country), size=30)\n",
    "    plt.xlabel('Days Since 1/22/2020', size=30)\n",
    "    plt.ylabel('# of Cases', size=30)\n",
    "    plt.xticks(size=20)\n",
    "    plt.yticks(size=20)\n",
    "    plt.show()\n",
    "\n",
    "    plt.figure(figsize=(16, 9))\n",
    "    plt.bar(x, y2)\n",
    "    plt.title('{} Daily Increases in Confirmed Cases'.format(country), size=30)\n",
    "    plt.xlabel('Days Since 1/22/2020', size=30)\n",
    "    plt.ylabel('# of Cases', size=30)\n",
    "    plt.xticks(size=20)\n",
    "    plt.yticks(size=20)\n",
    "    plt.show()\n",
    "\n",
    "    plt.figure(figsize=(16, 9))\n",
    "    plt.bar(x, y3)\n",
    "    plt.title('{} Daily Increases in Deaths'.format(country), size=30)\n",
    "    plt.xlabel('Days Since 1/22/2020', size=30)\n",
    "    plt.ylabel('# of Cases', size=30)\n",
    "    plt.xticks(size=20)\n",
    "    plt.yticks(size=20)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HXlMeLqJq5M5QfS8R8XcR8YXepihGxEb05JxKimlkkqRBMuItSVIbZebvI+JbwAcplsC9ofxX+t9TrAbzMuDdFAlTL6ZYBrdVF1HkrHh+ed07IuJ7wP0UyXgPoQhsLAF+AbxpEPeq9mWKJZy/SPEPRCcDJ0TEbyimIT1Zlm9GMUXpAJos+10uq30cRfLXqcAngFdFxI+BRyhGJB1FkdwUYCXw9sxcNkTvRaXM/GZEvJQiYLE1cFP5nV5B8V0EsBHwQoppSttRBBQ+XXed+yLiCxRLRk8GLouI8ymmyi0DXgS8p7zWRQzRNJ7yb+9NFAG89YAjgNdHxJUU04YeowgebVK+h4OBLZtcbqj+tjYHvg58JSKuAm4sr7GE4v2/lOL5rgQ5v56ZNSuADdH3Mgv4EnByRFwHXA/cQ5F8e8Oy7THla4AfZ+ZDTd6TJGkADNJIktR+H6HInfJ2ih+p/1BuFd0UP6CeZBBBmsxcGhFHUEyJ2ACYDZxWV+1Z4FiKH5pDEqQpc4CcEhF/pAjY7AI8r7zPsc2aAZcAn21wvZsj4tUUU5g2B/6+3OrNB47JzKsH+x7U1DuALorRUpPpWSa6mUcaFWbmVyNiA4rvexzw1nKrdiZFgGPIcq1k5i8jYg+KEW0H07/3cDN1z+UQ/m1VlumeBLy23Bp2HTiDIuDZyDsY3PdS6cd4ilWl9uml7QXU/vdKkjQIBmkkSWqzcvnf4yPiZ8D7KX7EzQT+RjFi5MzM/ENEvGMI7nVDROxGEfQ5GNgKWEoxJejXwLcy86GIeNlg79Xg3r+OiMuAg8ptb2ALin+NXwk8DfwvxSiin/a2fHD5ecyh+HF4GEW+nvWBBRT/4v+r8r08O9TvQz3KANw/laNG3kMxMmMHiu+0myI/yl3AH4BLM/OGXq71uYi4lCJo+QqKQN6TwJ+B72TmZRGx3zp4D3cCh0TE31M8S6+iWFp6I4qA0TMUAY8bgAszs2ES6iH62/oRcAvF57gvRUBzc4qRaIuAByj+Pr6fmTf38p4G9b1k5jURsQNFsvJXUYxm2pJimfQlwEPl5/GDzLyml/cjSRqgKP4bLkmSJEmSpHYycbAkSZIkSVIHMEgjSZIkSZLUAQzSSJIkSZIkdQCDNJIkSZIkSR3A1Z1Gseeee86s0JIkSZIkdaBZs2ZFfZkjaSRJkiRJkjqAQRpJkiRJkqQOYJBGHamrq6vdXdAI5HOjVvjcqFU+O2qFz41a5bOjVvjcjDwGaSRJkiRJkjqAQRpJkiRJkqQOYJBGkiRJkiSpAxikkSRJkiRJ6gAGaSRJkiRJkjqAQRpJkiRJkqQOYJBGkiRJkiSpAxikkSRJkiRJ6gAGaSRJkiRJkjrAiAnSRMQREXFmRFwbEQsiIiPi3CZ1zynP97ZdUdfmHX3Uf3+Te02NiFMj4u6IWBYRT0TEBRGxUy/vZcuI+H5E/DUilkfEvIj4ekRs0EubvSLi0oiYHxFLIuIvEfGxiBjf389QkiRJkiR1rgnt7sAAfB7YDVgEPALs2Evdi4F5Tc4dB8wGLmty/hLglgblf6oviIjJwG+Bvcvz3wC2Ao4EXhcR+2fmjXVttgOuBzYp73UX8DLgo8BBEbF3Zj5d1+Yw4OfAMuB8YD7weuDfynsf2eS9SJIkSZKkEWIkBWlOpAjO3AvsC1zVrGJmXkwRqKkREesDnwZWAOc0aX5xZjY7V+/jFEGSC4G3ZGZ3eZ/zy/t/PyJeWCkvfYsiQPORzDyzqm+nU7zH04D3V5XPBM4GVgP7ZeafyvIvAFcCR0TE0Zl5Xj/7LEmSJEmSOtCIme6UmVdlZldm5iAucxwwFfhFZj41mP5ERNATTPl0dSAmMy8BrgV2pggoVdrMBg6kGOVzVt0lTwYWA8dFxPSq8iOAjYHzKgGa8h7LKEYXAXxgMO9FkiRJkiS134gJ0gyR95b7/+ilzu5lrpfPRsRxEbFlk3rbAVsD92TmAw3OV6ZT7V9VVnl9ed3oGjJzIXAdMA14eYM2v2lwj2uAJcBe5dQrSZIkSZI0Qo2k6U6DEhF7Ai+kCKo0nSpFkRum2uqI+C7wsXL0SsUO5f6eJtfpKvdzB9jmwLJNJbFx0zaZuSoiHgB2ocizc2eT60qSJEmSpA43ZoI0wD+U+7ObnH8A+DBwOUXum1nAK4B/Ad4HzASOqao/q9w/1+R6lfL129BmLV1dXb2d7kgjsc9qP58btcLnRq3y2VErfG7UKp8dtcLnprPMmTOn1/NjIkgTEbOAo+glYXBm/g74XVXREuBnEXEDcCvw1oj4cmbe2t/bVi49kK6uqzZ9PQidpqura8T1We3nc6NW+NyoVT47aoXPjVrls6NW+NyMPGMlJ83bKHK9DDhhcGY+DFxaHu5TdaoygmUWjc2sqzecbSRJkiRJ0ggzVoI0lYTB/95i+yfLffWqS3eX+7k0VglXVueSGdI2ETEB2BZYBdzf5JqSJEmSJI0ay1cnt81fyeAWf+5Moz5IExF7ALtRJAy+usXL7FHuqwMh9wEPAXMjYtsGbQ4u91dWlVUSFh8YETWffUSsB+wNLAVuqDpVaX9Qg3vsQzFC6PrMXN7Xm5AkSZIkaaS78tFlvOKSJ3j5RU/wrzcv4N7nVra7S0Nm1Adp6EkY3Nuy20TEKxuURUT8H2BP4CmqlsHOImT3nfLwK9VBl4g4DHglcAdVeW4y8z6KxMTbAB+qu92pFCN1fpiZi6vKLyzvfXREvKTqHlOAfyoPv93be5MkSZIkabT4xQNLAbj7uVX86y0L+fYdi/toMXKMmMTBEXE4cHh5uFm53zMizilfP5WZn6xrMxN4C0XC4B/0cYtrIuIe4I/AoxQ5YPYGdqVIInxsZi6oa3M6cChwBHBjRFwBbA0cWbZ5V2Z217X5IHA9cEZEvJpi2ew9gFdRTHM6qbpyZi6IiPdSBGuujojzgPnAGyiW574QOL+P9yZJkiRJ0oi3ZFU3lz60rKbsTdtObVNvht6ICdIAuwPH15XNLjeAB4FP1p0/lmJ0ynn9SBj8NeBlwP7AhkA3xXSms4DTM3OtnC+ZuTwiDgA+S7E894nAAuBi4OTMvKNBm/vKETFfopjCdAjwGHAGcGpmzm/Q5uKI2JcigPNmYApwL/Bx4IwcjRPxJEmSJEmqc/nDy1m8qucn8ObTxrHnppPa2KOhNWKCNJl5CnDKANt8m35OBcrMTw28V5CZS4GTy62/bR4G3jnA+1xHEdCRJEmSJGlM+sUDS2qOD99mKuMi2tSboTcWctJIkiRJkqQRbsGKbi5/pHaq05tnT2tTb9YNgzSSJEmSJKnjXfbwMpat7jneesZ4XrzRxPZ1aB0wSCNJkiRJkjpeZVWnijdtO5UYRVOdwCCNJEmSJEnqcM8s7+bKR0fvqk4VBmkkSZIkSVJH++WDS1nZ3XO8/cwJvHDD0TXVCQzSSJIkSZKkDrfWVKfZo2+qExikkSRJkiRJHezJpau55rHlNWWjcaoTGKSRJEmSJEkd7JJ5S+nOnuNdNpjAjuuPvqlOYJBGkiRJkiR1sJ+vtarTtDb1ZN0zSCNJkiRJkjrSo4tX84e/ragpG61TncAgjSRJkiRJ6lAXz6sdRfP3G01k25kT2tSbdc8gjSRJkiRJ6ki/uH9JzfEbR/EoGjBII0mSJEmSOtC8hav481Mra8reuI1BGkmSJEmSpGF1UV3C4D03ncSWM0bvVCcwSCNJkiRJkjpQ/apOo30UDRikkSRJkiRJHeauZ1dy2/yeqU7jAg4zSCNJkiRJkjS8ftJVmzD4FZtNZtNp49vUm+FjkEaSJEmSJHWMld3JeffVBmmO2X5am3ozvAzSSJIkSZKkjvHfjyzjiaXda47Xmxi8YZspbezR8DFII0mSJEmSOsa5dVOd3rjtVKZNGBvhi7HxLiVJkiRJUsd7culq/t/Dy2rK3jZnbEx1AoM0kiRJkiSpQ5x/3xJWZc/xnFkTeOnGk9rXoWFmkEaSJEmSJLVdZq61qtPb5kwjItrUo+FnkEaSJEmSJLXdLU+v5I5nV605Hh/wlu3GzlQnMEgjSZIkSZI6QH3C4AO2nMJm08a3qTftYZBGkiRJkiS11dJVyYX31wZpjt1+bI2iAYM0kiRJkiSpzX790FKeW9GTMfh5k8dx0FZT2tij9jBII0mSJEmS2urHdVOdjtpuKpPGj52EwRUGaSRJkiRJUts8vGgVV/91eU3ZsXOmt6k37WWQRpIkSZIktc1P711CVh3v/ryJ7LrhxLb1p50M0kiSJEmSpLbozuQn99YlDJ4z9hIGVxikkSRJkiRJbXHd4yuYt3D1muNJ4+CI2QZpJEmSJEmShtWPuxbXHB/6gqlsMHnshirG7juXJEmSJElts2BFN5fMW1ZTNpanOoFBGkmSJEmS1AYXz1vK0tU9KYOfP208+20+uY09aj+DNJIkSZIkadj9uKs2YfBbt5/G+HHRpt50BoM0kiRJkiRpWN3z7EpufGJFTdkxY3yqExikkSRJkiRJw6x+2e29Np3E7JkT2tSbzmGQRpIkSZIkDZtV3clP64I0Yz1hcIVBGkmSJEmSNGyueHQ5f1vaveZ4xoTgsG2mtrFHncMgjSRJkiRJGjY/7lpcc3z4tlOZMdHwBBikkSRJkiRJw+TpZau57OFlNWVvc6rTGgZpJEmSJEnSsLjgvqWs7JnpxPYzJ7DHJpPa16EOY5BGkiRJkiStc5nJuXVTnY6dM42IaFOPOo9BGkmSJEmStM7d+vRKbn9m1ZrjcQFHb+9Up2oGaSRJkiRJ0jr347plt1+9xWQ2nza+Tb3pTAZpJEmSJEnSOrVsVfKz+2qDNG+bO71NvelcBmkkSZIkSdI6ddnDS3l2Ra453mBycNBWU9rYo85kkEaSJEmSJK1T53bVjqI5avY0Jo83YXC9EROkiYgjIuLMiLg2IhZEREbEuU3qblOeb7ad18t9jo+ImyJiUUQ8FxFXR8ShvdSfGhGnRsTdEbEsIp6IiAsiYqde2mwZEd+PiL9GxPKImBcRX4+IDXpps1dEXBoR8yNiSUT8JSI+FhFO4JMkSZIkdaxHFq3iykeX15QdO8eEwY1MaHcHBuDzwG7AIuARYMd+tLkVuLhB+W2NKkfE14BPlNc/G5gEHA38MiI+nJnfrKs/GfgtsDfwJ+AbwFbAkcDrImL/zLyxrs12wPXAJsAlwF3Ay4CPAgdFxN6Z+XRdm8OAnwPLgPOB+cDrgX8r731kPz4LSZIkSZKG3Xn3LSWrjl+04URe9LxJbetPJxtJQZoTKYIn9wL7Alf1o80tmXlKfy4eEXtRBGjuA16amc+U5V8F/gx8LSJ+lZnzqpp9nCJIciHwlszsLtucTxEc+n5EvLBSXvoWRYDmI5l5ZtX9Ty/f42nA+6vKZ1IEjFYD+2Xmn8ryLwBXAkdExNGZ2XR0kCRJkiRJ7ZCZ/KRrcU2Zo2iaGzHTnTLzqszsyszsu3ZLKoGR0yoBmvK+84CzgMnAOyvlERFVbT5dHYjJzEuAa4GdKQJKlTazgQOByjWrnQwsBo6LiOoU10cAGwPnVQI05T2WUYwuAvjAwN6qJEmSJEnr3vV/W8H9C1evOZ40Do6cPbWNPepsIyZI06ItIuJ9EfG5cv+iXuruX+5/0+DcZXV1ALYDtgbuycwH+tmm8vryutE1ZOZC4DpgGvDyfvbrGmAJsFc59UqSJEmSpI5x5m2Lao4P2XoqG04xtWozoz1I8xrgOxRTiL4D3BoRV0XE1tWVypErzwcWZeZjDa7TVe7nVpXtUO7vaXLvdd4mM1cBD1BMW5vd5JqSJEmSJA272+ev5DcPL6spe+cOTnXqzWgN0iwB/hF4MbBBuVXy2OwHXFE3pWhWuX+uyfUq5euPkDaSJEmSJLXV1/93Yc3xizeayD6bOwmkNyMpcXC/ZeYTwBfriq+JiAOB3wN7AO+hWI1pQJceQN3Kgu8d0aarq6u30x1pJPZZ7edzo1b43KhVPjtqhc+NWuWzo1a067l5ZGnw8/un0POTFY7eeBH33tts/MHYMGfOnF7Pj8ogTTOZuSoivksRpNmHniBN5SmZ1bBh49EsfbWZ2cY2a+nrQeg0XV1dI67Paj+fG7XC50at8tlRK3xu1CqfHbWinc/NWaZm+GoAACAASURBVNc9QzdL1hzvuP4E3r3HFoyL6KWVRut0p948We7XTHfKzMXAo8CMiNi8QZvKU12dF+bucj+XxtZ5m4iYAGwLrALub3JNSZIkSZKGzWNLVvOTe5fUlJ34ovUM0PTDWAzSVFZOqg9qXFnuD2rQ5uC6OgD3AQ8BcyNi2362uarcHxgRNZ99RKwH7A0sBW7oZ7/2oVgN6vrMXN7gvCRJkiRJw+qs2xaxomo9461njOfN27rsdn+MyiBNROwREZMalO8PnFgenlt3+jvl/qSI2KCqzTbAh4DlwH9WyjMzq9p8pTroEhGHAa8E7gB+V9XmPuByoHLNaqdSjO75YTmyp+JC4Cng6Ih4SdU9pgD/VB5+u/69SpIkSZI03J5Z3s1/3r24puyjL5zBhHGOoumPEZOTJiIOBw4vDzcr93tGxDnl66cy85Pl6y8Du0TE1cAjZdmLgP3L11/IzOurr5+Z10fE6cDHgb9ExIXAJOAtwIbAhzNzXl23TgcOBY4AboyIK4CtgSMpVph6V2Z217X5IHA9cEZEvBq4kyJHzqsopjmdVNevBRHxXopgzdURcR4wH3gDxfLcFwLnN/rMJEmSJEkaTv9+xyIWr+pZ12aTqeM4dvvpvbRQtRETpAF2B46vK5tdbgAPApUgzY+ANwIvpZh2NBH4G3AB8M3MvLbRDTLzExHxF+AE4B+AbuB/gK9m5q8a1F8eEQcAnwWOoRilswC4GDg5M+9o0Oa+ckTMlyimMB0CPAacAZyamfMbtLk4IvalCOC8GZgC3EsRUDqjHNUjSZIkSVLbLFrZzXfuWFRTdsIuM5gywVE0/TVigjSZeQpwSj/rfg/4Xov3+QHwgwHUXwqcXG79bfMw8M4B9us6ioCOJEmSJEkd55y7F/Psip4xBLMmBe/c0VE0AzEqc9JIkiRJkqThs3x1ctbttaNo/mGnGaw30bDDQPhpSZIkSZKkQTnv3iU8tqQnJeu0CcH7d3YUzUAZpJEkSZIkSS1b1Z18/X8X1pQdP3caz5syvk09GrkM0kiSJEmSpJZdMm8pDyxcveZ44jg4Ydf12tijkcsgjSRJkiRJatm36nLRvHX7aTx/uqNoWmGQRpIkSZIkteSPT6zgz0+trCn7yK4z2tSbkc8gjSRJkiRJasl37qgdRXPglpPZftbENvVm5DNII0mSJEmSBuyvi1dzybylNWXv39lRNINhkEaSJEmSJA3Y9+5axKrsOZ47awKv2mJy+zo0ChikkSRJkiRJA7J0VfKfdy+pKXvfztOJiDb1aHQwSCNJkiRJkgbkwvuXMH9595rjWZOCo7eb1sYejQ4GaSRJkiRJUr9l5loJg98+dzrTJxpiGCw/QUmSJEmS1G+/f3wFtz+zas3xuID37Di9jT0aPQzSSJIkSZKkfqsfRXPIVlN4wXoT2tSb0cUgjSRJkiRJ6pd5C1dx6UPLasrev4vLbg8VgzSSJEmSJKlfzr5zMVWrbrPrhhPZe9NJbevPaGOQRpIkSZIk9WnRym5+1LW4pux9O7ns9lAySCNJkiRJkvp03r1LWLCiZxzN8yaP48jZLrs9lAzSSJIkSZKkXnVn8u931o6ieecO05kywVE0Q8kgjSRJkiRJ6tWVjy6n67meZbcnBLzLZbeHnEEaSZIkSZLUq7Pvqh1Fc9g2U9li+vg29Wb0MkgjSZIkSZKa+uvi1fz2kdplt9+3s6No1gWDNJIkSZIkqamf3ruE7qp1t3feYAIv3dhlt9cFgzSSJEmSJKmh7sy1lt1++1yX3V5XDNJIkiRJkqSGrn1sBfMWrl5zPHk8vGU7l91eVwzSSJIkSZKkhupH0bz+BVPZYLKhhHXFT1aSJEmSJK1l/rLV/Ne8pTVlx80xYfC6ZJBGkiRJkiSt5YL7l7Kiu+d4m/XG88rNTRi8LhmkkSRJkiRJNTKTH95dO9XpuDnTGWfC4HXKII0kSZIkSarxP0+t5I5nV605HhdwzBwTBq9rBmkkSZIkSVKNH95TO4rmwC2nsPm08W3qzdhhkEaSJEmSJK2xaGU3P7+/NmHw2+c6imY4GKSRJEmSJElrXPTAUhatyjXHm00dx4FbTmljj8YOgzSSJEmSJGmNH92zpOb4mDnTmDDOhMHDwSCNJEmSJEkC4K5nV3LTkytqyt42Z3qbejP2GKSRJEmSJEnA2qNoXrnZJGbPnNCm3ow9BmkkSZIkSRLLVyfn3VsbpHn7XEfRDCeDNJIkSZIkicseWsbTy7vXHK8/KXj9C6a2sUdjj0EaSZIkSZLEOfcsrjk+artpTJlgwuDhZJBGkiRJkqQxruu5lVz91+U1Zcc51WnYGaSRJEmSJGmM++6dtaNo9thkEi/ccGKbejN2GaSRJEmSJGkMW7iym5/WJQx+z46OomkHgzSSJEmSJI1hF9y3hAUrc83xJlPHcdg2JgxuB4M0kiRJkiSNUZnJ2XVTnY6fO51J400Y3A4GaSRJkiRJGqN+//gK7np21Zrj8QHv3MGpTu1ikEaSJEmSpDHq7DsX1Rwf+oIpbDF9fJt6I4M0kiRJkiSNQY8uXs2vH1pWU/benWa0qTcCgzSSJEmSJI1J/3n3Ylb35Atm5/UnsPemk9rXIRmkkSRJkiRprFm+OvnB3bUJg9+z0wwiTBjcTiMmSBMRR0TEmRFxbUQsiIiMiHOb1J0TEZ+JiCsj4uGIWBERf4uISyLiVU3avKO8ZrPt/U3aTY2IUyPi7ohYFhFPRMQFEbFTL+9ly4j4fkT8NSKWR8S8iPh6RGzQS5u9IuLSiJgfEUsi4i8R8bGIcLKgJEmSJGlALpm3lCeXda85njkxOGo7l91utwnt7sAAfB7YDVgEPALs2EvdfwTeAtwBXArMB3YA3gC8ISI+mplnNGl7CXBLg/I/1RdExGTgt8De5flvAFsBRwKvi4j9M/PGujbbAdcDm5T3ugt4GfBR4KCI2Dszn65rcxjwc2AZcH75fl4P/Ft57yN7+SwkSZIkSapRnzD4mDnTmDFxxIzjGLVGUpDmRIrgzL3AvsBVvdT9DfDlzLy5ujAi9qUIqnw1In6WmY81aHtxZp7Tzz59nCJIciHwlszsLu9zPnAx8P2IeGGlvPQtigDNRzLzzKq+nV6+x9OA91eVzwTOBlYD+2Xmn8ryLwBXAkdExNGZeV4/+yxJkiRJGsNueWoFf3xyZU3Ze3Z02e1OMGLCZJl5VWZ2ZWb2o+459QGasvx3wNXAJGCvwfQniol6lWDKp6sDMZl5CXAtsDNFQKnSZjZwIDAPOKvukicDi4HjIqL6r+MIYGPgvEqAprzHMorRRQAfGMx7kSRJkiSNHWffVZuLZv8tJrP9rIlt6o2qjZggzRCqhAtXNTm/e5nr5bMRcVxEbNmk3nbA1sA9mflAg/OXlfv9q8oqry+vG11DZi4ErgOmAS9v0OY3De5xDbAE2KuceiVJkiRJUlPzl63m5/cvqSl7706OoukUI2m606BFxAuAV1MENq5pUu2jdcerI+K7wMfK0SsVO5T7e5pcp6vczx1gmwPLNlf01SYzV0XEA8AuwGzgzibXlSRJkiSJc7uWsGx1z/FWM8Zz4JZT2tch1RgzI2nKkSY/BiYDp2TmM3VVHgA+TBEUmQ5sARxFMTXpfcD36+rPKvfPNbllpXz9NrSRJEmSJKnG6u7ku3VTnd6z43TGj3PZ7U4xJkbSlMtU/4giye/5wNfq65T5an5XVbQE+FlE3ADcCrw1Ir6cmbf297aVSw+kq+uqTVdXV2+nO9JI7LPaz+dGrfC5Uat8dtQKnxu1ymdHrah+bq55ejwPLerJlDF5XLLX+Mfp6nq8HV0bk+bMmdPr+VEfpCkDNOdSLFN9AfC2/iQfrsjMhyPiUuBYYB+KgA30jGCZ1bAhzKyrN5xt1tLXg9Bpurq6Rlyf1X4+N2qFz41a5bOjVvjcqFU+O2pF/XPz2QeeApavOT5iu+m8dOdmaVjVDqN6ulNETAB+ChwN/AQ4JjObJQzuzZPlvjqb0t3lfi6NVf4SqnPJDGmb8v1tS5EE+f4m15QkSZIkjXH3PreSKx5dXlP2Xpfd7jijNkgTEZOACylG0PwQOC4zV/feqqk9yn11IOQ+4CFgbkRs26DNweX+yqqyq8r9gRFR89lHxHoU07GWAjdUnaq0P6jBPfahWA3q+sxc3uC8JEmSJElr5aJ56cYT2X2jSW3qjZoZlUGaMknwRcBhwPeAd9Yved2gzSsblEVE/B9gT+ApqpbBLqdMfac8/Ep10CUiDgNeCdxBVZ6bzLwPuBzYBvhQ3e1OpRip88PMrP7rubC899ER8ZKqe0wB/qk8/HZv702SJEmSNHYtWtnNT7rql92e0abeqDcjJidNRBwOHF4eblbu94yIc8rXT2XmJ8vX3wEOoQhuPAp8MWKtbNVXZ+bVVcfXRMQ9wB/LNrMoRrbsSpFE+NjMXFB3jdOBQ4EjgBsj4gpga4rRO0uAdzUIDn0QuB44IyJeTbFs9h7AqyimOZ1UXTkzF0TEeymCNVdHxHnAfOANFCtRXUiRDFmSJEmSpLX87L6lLFjZk5p1oynjOGybqW3skZoZMUEaYHfg+Lqy2eUG8CBQCdJUph9tBHyxl2teXfX6a8DLgP2BDYFuiulMZwGnZ+ZaOV8yc3lEHAB8FjgGOBFYAFwMnJyZdzRoc185IuZLFFOYDgEeA84ATs3M+Q3aXBwR+1IEcN4MTAHuBT4OnDGQRMiSJEmSpLEjMzn7zkU1Ze+YO53J4112uxONmCBNZp4CnNLPuvu1cP1PDbRN2W4pcHK59bfNw8A7B3if6ygCOpIkSZIk9ct1f1vBHc/2rJ8zPuAdO0xrY4/Um1GZk0aSJEmSJMF376xNGPy6raew5YwRM15jzDFII0mSJEnSKPTE8uCXDy6tKXuPCYM7mkEaSZIkSZJGoV88PoHVVRlMd1x/Aq/czGW3O5lBGkmSJEmSRpkVq5OLHq+d1vTenabTYOVjdRCDNJIkSZIkjTL/9eBS5q/sCcisNzE4ajsTBnc6gzSSJEmSJI0yZ9clDH7r9tNYb6IhgE7nNyRJkiRJ0ihy69MruPGJFTVl79lxept6o4EwSCNJkiRJ0ihSv+z2fltMZu76E9vUGw2EQRpJkiRJkkaJp5at5mf3L6kpe6+jaEYMgzSSJEmSJI0S379rMctW9xxvOX08B201pX0d0oAYpJEkSZIkaRRYtirXShj8vp2nM36cy26PFBP6rjJwETEZeDfwivIetwL/kZlProv7SZIkSZI01l1w/xKeXNa95nj6+OTtc53qNJIMOEgTETsD5wIJfCgzb6g7vx7wO2C3quI3Ax+JiAMz89ZB9FeSJEmSJNXJTL51+6KassM2XcWsSU6gGUla+bZeB+wObAHc2OD8v5Tno27bGPhFOcpGkiRJkiQNkSseXc5dz65aczw+4OgtVvXSQp2olSDNARSjaC7PzKw+EREzKaY5JfAAcCiwK/Ctsso2wHGtdlaSJEmSJK3tm/WjaLaZyuZTskltdapWgjQvKPc3Nzh3CFAZKfOuzLw0M+/IzBOAW8ryw1q4pyRJkiRJauB/56/k6r8uryk7YZcZbeqNBqOVIM1G5f6xBuf2K/ePZObv6s79jGLa04tauKckSZIkSWqgPhfNnptO4u83ntSm3mgwWgnSzCz3Kxuc24tiqtMVDc49XO43buGekiRJkiSpzmNLVnPh/Utqyj7kKJoRq5UgTWXR9U2qCyPiecAu5eF1DdpVxl6ZWlqSJEmSpCFw9p2LWNmz6jaz1xvPwVtNaV+HNCitBEzuK/f71JUfTjGdCRoHaSpBnedauKckSZIkSaqyeGU3379rcU3ZB3eZwfhx0aSFOl0rQZqrKYIxb46INwNExFbA58rz8zLzrgbtKrlo7m/hnpIkSZIkqcpP7l3Csyt6VnBaf1Lw1u2ntbFHGqxWgjTfAVYAE4ALImI+ReBlG4p8NGc1aVdZuvvGFu4pSZIkSZJKq7tzrYTB795xOtMnmmFkJBvwt5eZ9wInUARcAlgfGF++vho4o75NROwBbFseXtliXyVJkiRJEnDpw8t4YOHqNccTx8F7dzJh8Eg3oZVGmfndiPgT8G5ge2AJ8Fvge5m5qkGTI4EHgW6KQI4kSZIkSWrRWbfVjqI5YvY0Nps2vk290VBpKUgDkJm3AB/uZ91PAp9s9V6SJEmSJKlw/ePLueGJFTVlLrs9OjhZTZIkSZKkEeTLtyysOX7VFpPZdcOJbeqNhpJBGkmSJEmSRojrH1/O7x5bXlP2yd3Wa1NvNNRanu4EEBHjKfLNHAjsBGwATMzM7erq7QrMBJ7LzNsHc09JkiRJksaq+lE0+2w+mb03m9ym3miotRykiYj9gB8AW1YXU6z6VO8w4EvAwojYPDOXtnpfSZIkSZLGokajaD6zu6NoRpOWpjtFxOspVnPakiIwsxp4rpcm/06xstN6wOtauackSZIkSWOZo2hGvwEHaSJiI+BcYDywgGIZ7vWBdzZrk5lPAdeWhwcMvJuSJEmSJI1djqIZG1oZSfNhihExK4ADMvM/M3NJP9rdQDHq5u9auKckSZIkSWOWo2jGhlaCNAdT5J05PzP/PIB2XeV+dgv3lCRJkiRpTHIUzdjRSpCmsnLTVQNst6Dcz2zhnpIkSZIkjUmOohk7WgnSTC/3C3uttbZp5X5ZC/eUJEmSJGnMcRTN2NJKkObpcr/ZANvtVO6fbOGekiRJkiSNOY6iGVtaCdLcXu5f3d8GERHAmyly2fyxhXtKkiRJkjSmOIpm7GklSPNrilWaDo2Iv+9nmxOBOeXr/2rhnpIkSZIkjSmOohl7WgnSfBd4AhgP/Coi9mpWMSKmRsQ/Al+hGEVzP3B+Kx2VJEmSJGmsuOkJR9GMRRMG2iAzF0fEOylGxGwKXBsRNwHzK3Ui4gvALsCBwCyKkTfLgWMzs3soOi5JkiRJ0mh15m2Lao4dRTM2DDhIA5CZl0XE0cD3KJbUflnlVLk/pdxHuX8WODozb2qxn5IkSZIkjQn3L1jFrx6sXRj5Ey+a0abeaDi1Mt0JgMz8ObAr8E3gGYqATP22APg28MLMvHzQvZUkSZIkaZT79u2L1oyAANh1w4nss7mjaMaClkbSVGTmI8BHgI9ExC7ANhTTmxYBjwI3O71JkiRJkqT+mb9sNed2Lakp+/CuMygWTdZoN6ggTbXMvJ2e5bklSZIkSdIAfe+uxSxd3TOOZotp43jTtlPb2CMNp5anO0mSJEmSpKGzbFVy9l2La8rev/MMJo5zFM1YMWQjaepFxCHAK8p73ApcmJnLe28lSZIkSdLYdMH9S3hiaU/GkPUmBsfvML2NPdJwG3CQJiK2AU4vD/85M/9Ud34icAnw2rqmJ0XEQZn5UAv9lCRJkiRp1OrO5Ky6ZbePmzuNWZOcADOWtPJtHwocDuwH/KXB+c8DB7H2Sk87AheH2Y4kSZIkSarx348s5+7nVq05Hh/FVCeNLa0EaQ4s97/NzBXVJyJiCvAxIIH5wAkUQZ3/KqvsBhzVWlclSZIkSRqdzrxtYc3xG7edytYz1lmGEnWoVoI021EEYf7U4NxrgfXK1+/KzG9l5qXAm4GusvzIFu5JRBwREWdGxLURsSAiMiLO7aPNXhFxaUTMj4glEfGXiPhYRIzvpc3xEXFTRCyKiOci4uqIOLSX+lMj4tSIuDsilkXEExFxQUTs1EubLSPi+xHx14hYHhHzIuLrEbHBUL4XSZIkSVLnu+WpFVz7eM0YCE7YxVE0Y1ErQZqNyv0jDc69qtw/lZmV0TNk5mrgPIppT3/Xwj2hmEZ1ArA78GhflSPiMOAaYB/gIuAsYBLwb2VfGrX5GnAOsDlwNnAu8ELglxFxQoP6k4HfAl8EFgDfAP4beCPwp4jYo0Gb7YA/A+8Ebir7cz/wUeAPEfG8oXgvkiRJkqSR4azba3PRvGKzSey+0aQ29Ubt1EqQpjLaY1mDc3tTjLK5osG5+8v9pi3cE+BEYC4wE/hAbxUjYiZFkGU1sF9mvjszP0UR4PkDcEREHF3XZi/gE8B9wIsy88TM/BDwYoqpW18rkyZX+zjFe74Q2CMzP5OZxwBHANOA70dE/Wf8LWAT4COZeXhmfjYz96cIuOwAnDbY9yJJkiRJGhkeXrSKXzywtKbsw7uu16S2RrtWgjSVp2fD6sKIWI8icADw+wbtKou9txQOzMyrMrMrM7Mf1Y8ANgbOq159KjOXUYzIgbUDPe8v96dl5jNVbeZRjFyZTDH6BYAyAXKlzaczs7uqzSXAtcDOwL5VbWZT5PSpXLPayRSf0XERUb3GWivvRZIkSZI0Avz7HYtZXfUrd+6sCbxmy8nt65DaqpUgzYPl/uV15a8DKvlRrmvQrhLUWdDCPQdq/3L/mwbnrgGWAHuV05X60+ayujpQ5ObZGrgnMx/oZ5vK68urgzoAmbmQ4nObRu1n28p7kSRJkiR1uOdWdPODexbXlJ2w6wzGuSjymNVKkOY6itwyb63kXClH0XymPP+3zLy1Qbtdy32jgMZQ26Hc31N/IjNXlX2YAMwGKEeuPB9YlJmPNbheJenx3P7cY7jaNHovkiRJkqSR4fRbF7JwZc8wmo2njOOo2dPa2CO1WytBmv+gyDszFbg2Im6myDfzorL8u03avao8/+cW7jlQs8r9c03OV8rXb7F+p7eRJEmSJHWwu59duVbC4PfuNJ0pExxFM5YNeNH1zLw5Iv6RYkWjCcBuVadvB75c3yYidgF2oQjSXNlaV4dU5anvT36bagOp38o91lmbrq6u3k53pJHYZ7Wfz41a4XOjVvnsqBU+N2qVz87okQkn3DaZVTl+Tdkmk7p57ZS/0dX1tyG9l89NZ5kzZ06v5wccpAHIzFPKETTvAbanyIvyW+BfM3NxgyYfqTRleII0ldEls5qcn1lXr6/6jUazDPQew9lmLX09CJ2mq6trxPVZ7edzo1b43KhVPjtqhc+NWuWzM7pc9MAS/vjcMzVlX9lrI3bbduqQ3sfnZuRpZboTUKxglJmvz8ydMvPF5VLSzzap+77MHJeZEzLzqda72293l/u59SciYgKwLbCKclnwMrD0KDAjIjZvcL3KU12dF6bpPYarTaP3IkmSJEnqXItWdnPSTbX/xr7fFpM5bJspbeqROknLQZoOVxmtc1CDc/tQrKB0fWYu72ebg+vqANwHPATMjYht+9nmqnJ/YETUfPZl8uW9KZY4v6Gf/Wr2XiRJkiRJHeirtyzkr0t6FvudOA6+sscswhWdxOgN0lwIPAUcHREvqRRGxBTgn8rDb9e1+U65PykiNqhqsw3wIWA58J+V8szMqjZfqQ66RMRhwCuBO4DfVbW5D7gcqFyz2qnAdOCHdVPGWnkvkiRJkqQO0yhZ8Id2mcHc9Se2qUfqNC3lpGmHiDgcOLw83Kzc7xkR55Svn8rMTwJk5oKIeC9FgOPqiDgPmA+8gWJJ6wuB86uvn5nXR8TpwMeBv0TEhcAk4C3AhsCHM3NeXbdOBw4FjgBujIgrgK2BIyny9LwrM7vr2nwQuB44IyJeDdwJ7EGx+tU9wEl1/Rrwe5EkSZIkdZbM5NM3PMeqqiVfnj9tPJ/cbb32dUodZ9BBmojYiyLIsCVFEtvxvbcgM/PdLdxqd+D4urLZ5QbwIPDJqptcHBH7UgQ93gxMAe6lCMKcUY6Eqe/YJyLi/7N332GSVXX+x9/f6tyTE5khDkhGchCBQZAVc15XZHEVA4oi6qqoBLMgq6ioiCiw7gqLK/xQcEGSwBAl52FgyANM6Okc6/z+qOqZrp6ONd1THd6v56nnVp97zr2nmzvN1GdOeBD4DHACkAXuBc5KKf25j/ptEfEm4CvAh4CTgXrgCuC0lNKjfbRZkh8Rcya5KUxvAV4GzgXOSCmt7KPNsL8XSZIkSdLYceXSVm5+uXCViu/sN4OpFRN1gouKUXRIk5/SczZrQ5LhGHZIk1I6HTh9mG1uIxeCDKfNRcBFw6jfApyWfw21zfPA8cPs17C/F0mSJElS6TV2ZPnaXYX77By6qYsFa11FhTQR8Wngp91fDlI99arjqA9JkiRJ0qRx9gPrLhZ81gEuFqx1DXtcVURsC/yYXPDyCvBRYKf86URumtCuwDHkpvA05ssvArajuJE3kiRJkiSNO0/2sVjwp3d2sWD1rZiRNJ/Ot+sCjkopPQz0TABfza/F8ihwTUScDVwJfARoTin13tVIkiRJkqQJ6Zv31NPRYzuZzWozfGlPFwtW34pZoehwciNjruoOaAaSUnqB3Foqq4FP5nc0kiRJkiRpQrt1WRt/fb61oMzFgjWQYp6MrfPHRf2cr+xdkFJ6BfgtuSlSHyvinpIkSZIkjRvZlPjm3asLyvbfqJJ3bl1Toh5pPCgmpOkel/V8r/LWXud7uzd/3L+Ie0qSJEmSNG786ZkW7l3eUVB25j7TXSxYAyompGnqp233fmJb99Oue1WkTYq4pyRJkiRJ40JbV+KMf9QXlL1tq2r237iqRD3SeFFMSPNM/rhxr/LHyU1nOrSfdvvmj+1F3FOSJEmSpHHhgsebeK6xa83X5QGn7z2jhD3SeFFMSHMvuTBm917lN+WPh0TEUT1PRMS+5LbqTsCgiw1LkiRJkjQe1bVlOev+wlE0x79uCtvNKGZzZU02xYQ0N+SPb+pVfhHQln9/VURcGhHfjYhLgVuA7nFdlxRxT0mSJEmSxrwfPdhAXXta8/W0iuDf3XJbQ1RMlHcVuSlLW0TEUSmlawFSSs9GxFeBc8itP/PeHm26V0a6Efj1evRXkiRJkqQx6dmGTn71aGNB2ed3m8bc6rIS9UjjzbBH0qSUGsjt4FQD/K3XuR8DxwJPkwtmul9N5MKbY1JK2fXssyRJkiRJY863762nvccn3s1qM3xqlyml65DGnaImxaWUOgY493vg9xGxDbnFhZuBxwZqiCdSUQAAIABJREFUI0mSJEnSeHb/8nb+5+mWgrJT95pObXkxq4xoshq1lYtSSs+wdicoSZIkSZImpJQS37h7dUHZLrPK+eB2tSXqkcYrIz1JkiRJktbDtS+0ccuy9oKyM/edQVkm+mkh9W3QkTQRUQO8L/9lQ0rpT8O5QUS8i9waNgCXppTaBqovSZIkSdJ40ZFddxTN4ZtVccTm1SXqkcazoUx3+jJwGpCADxZxjwrgd/n2mwHfL+IakiRJkiSNOb95vIknV3eu+TqAM/aZXroOaVwbcLpTRNQCp5ALWC5LKf3PcG+QUroMuIzcs/rliKgqpqOSJEmSJI0lK1u7+P599QVlH15Qy+5zKkvUI413g61J8y5gKpAlN5qmWKflrzEDeOd6XEeSJEmSpDHh+/c3UNee1nw9rSL4xt6OolHxBgtpjswf/5FSerLYm6SUngDuyX/55mKvI0mSJEnSWPBEXQe/ebypoOyU3aexUU1ZiXqkiWCwkGZvclOdrh2Be11LbsrTPiNwLUmSJEmSSubrd62ma+0gGraaWsYnd55aug5pQhgspNk0f3x2BO7VfY3NRuBakiRJkiSVxHUvtHLdi4UbF5+57wyqy91yW+tnsJCmezJd3Qjcq3tPsmkD1pIkSZIkaYzqyCZOvatwy+2DNq7k7Vu55bbW32AhTfcy1bNH4F4z88eGEbiWJEmSJEkb3IV9bLn9vf1nEOEoGq2/wUKa1/LH7UfgXgt6XVOSJEmSpHFjVVuW7/Wx5fYebrmtETJYSPMAuWDw6BG419HkFiF+cASuJUmSJEnSBvX9++oLttyeWh58fS+33NbIGSyk+Vv+uGtEFL11dkQcDezW65qSJEmSJI0LT9R1cEHvLbf3mMbGtW65rZEzWEjzR9auS/PLiNhouDeIiE2AX+S/bAAuH+41JEmSJEkqlc5s4qTb6gq23J4/tYxPueW2RtiAIU1KaRXwE3JTnuYDN0fEXkO9eL7uTcBW5KY6nZu/piRJkiRJ48L372vgzlfbC8q+5ZbbGgWDjaQB+DZwO7mgZgfgjoj434h4d0Rs2rtyRGySP/cn4A7WLhh8B/CtEeq3JEmSJEmj7uaX2vjRg4WbFB+5eZVbbmtUlA9WIaXUERHvBK4B9gLKgHfkX0REK1CXrz4T6PmkdseK9wPvSil1jFC/JUmSJEkaVa+1dHHC31fSY5YTG9dkOO+QWW65rVExlJE0pJReAw4GzgM6yYUv3a8aYJP8q6bXuc58mwNTSq+OdOclSZIkSRoN2ZT49C2reKUlu6YsgPPfOIt5NS4WrNExpJAGIKXUllL6DLA98EPgPqD7ae0OZciX3Z+vs31K6TMppbaR67IkSZIkSaPrvEcaue7Fwo+yp+w+jUM3c5qTRs+g0516Syk9D3wF+EpETCE3gmZO/vQKYFlKqam/9pIkSZIkjWX3LW/njH/UF5QdsFElX3n9tBL1SJPFsEOanvJhzJL8S5IkSZKkca2+PctHb1pJx9pZTsyoDH596CzKM65Do9E15OlOkiRJkiRNZCklvnB7Hc80dBWU/+wNs9hy6nqNcZCGxJBGkiRJkiTgv55q5vKnWwrKPva6Kbxtq5oS9UiTjSGNJEmSJGnSe6a+ky/fsbqgbJdZ5Xx73xkl6pEmI0MaSZIkSdKk1plNnPD3lTR1pjVlteXBhYfNprrcdWi04RjSSJIkSZImtbMfaODu1zoKyr673wx2nFlRoh5psjKkkSRJkiRNWne/2s5ZDzQUlL1lfjXH7VBboh5pMjOkkSRJkiRNSg0dWU74+0q61s5yYqOaDOcePJMIpzlpwzOkkSRJkiRNSl+7c/U6223//A2zmFtdVqIeabLrd6P3iNg9//aZlFJDf/UkSZIkSRpvrnq2hUsWNxeUffx1Uzhyi+oS9UgaeCTN/cB9wOE9CyPim/nXDqPaM0mSJEmSRsHLzV187ra6grIdZ5Rzxr7TS9QjKaffkTQDOB1I5EKcJ0e0N5IkSZIkjaJsSpx4yypWtmXXlFVk4FdvnEVtuSuCqLQGegK7n1j3HJMkSZIkTQjnP9bEDS+1FZSd+vrp7Dm3skQ9ktYaKKTpHvu19QbohyRJkiRJo+rBFe188+7VBWUHb1LJZ3edWqIeSYUGCmkeAQI4MSL2jYjeI2pSH20kSZIkSRpzGjuyfPSmVbSvneXE9Mrgl4fMoizjdtsaGwYKaf6QP24F3AG0RkT33mQBXBERXUW8OkfzG+opIv41ItIgr64e9bcepO4fBrjXcRFxV0Q0RsTqiLgpIt46QP2aiDgjIp6IiNaIeDUiLouInQZos0VEXBgRL0VEW0QsjYgfR8Ss4n9KkiRJkjTxnXJ7HU/VF34c/fGBM9lyajFLtUqjY6Cn8VfAMcBb+jk/HqLG+4Ez+jl3CLAQuKaPcw8AV/RR/nBfF4qIs4FTgBeAXwOVwAeBqyLisymln/WqXwVcBxwM3AP8BNgSeB9wTEQsTCnd2avNdsAiYCPgSuBxYD/gc8DREXFwSmlFP9+rJEmSJE1a/7W4iUuXtBSUHbdDLe/etrZEPZL61m9Ik1LKRsTbgHeSC2q2BKqAQ8lNdXoUWL4hOlmslNL95IKadUTE7fm35/dx+v6U0ulDuUdEHEQuoFkC7JtSWpUvPwv4B3B2RPw5pbS0R7MvkAtoLgc+kFLK5ttcSi4cujAidusuzzuPXEBzUkrppz3ufw5wMvAd4JND6bMkSZIkTRZP1nXwxTsK16HZaWY539t/Rol6JPVvwHFdKaUE/Cn/AiAiuoODU1NK/28U+zZqImJX4ADgReAv63m57mDkO90BDUBKaWlE/Bz4BnA8cFr+3tGjzZd7BjEppSsj4hZyo3wOBW7Mt9kWOApYCvy81/1PA04Ajo2IU1JKTev5/UiSJEnShNDamTj+ppU0d65dUrWmLLjwsNlut60xabI+lZ/IH3+TUurq4/xmEfGJiPha/rj7ANdamD/+tY9z1/SqA7AdMB94MqX0zBDbdL+/ttfoGlJKDcBtQC254EmSJEmSBHz97tU8sqpwHZofHDCDnWb13hdHGhuKWSHp8Pyxz/VZxrqIqAE+DGSBC/qpdmT+1bPdTcBxKaXnepRNATYHGlNKL/dxncX54w49ynbMH5/s597Ftjkq3+b6fupIkiRJ0qRx5dIWLni8cKLBe7ap4dgFrkOjsWvYI2lSSjfnX+N1kdr3AzOBa1JKz/c61wx8C9gbmJV/dU87Ogy4Ph/MdOuexFg4wXGt7vKZJWgjSZIkSZPSsw2dfPa2VQVl20wr4z8OmkluBQppbBqRvcby66zsDGwKTAMagJeAx/Lr2owlJ+SPv+p9IqX0KvDNXsV/j4ijgFuB/YGPkduNaTiG8zPo/o0xom0WL17c36kxazz2WaXnc6Ni+NyoWD47KobPjYrlszM07Vn4xENV1LeXrSkrj8Tp2zbxyrNLeKWEfSsFn5uxZcGCBQOeX6+QJiJ2A74EvAOY2keVxoj4E/CjlNJD63OvkRAROwMHkdsq++qhtkspdUbEBeRCmjeyNqTpHsHS37LgfY2AGazN9BFqU2CwB2GsWbx48bjrs0rP50bF8LlRsXx2VAyfGxXLZ2fovrCojocbCqc5nbnvTN6xS18fWSc2n5vxp+iFgyPiK8A9wL+QGz0TfbymAccC90TEv693b9ffYAsGD+S1/HHNdKf8TkovAlMjYtM+2nT/aei5lswT+eMO9G2k2kiSJEnSpPKfi5u48InCgObNW1bzqZ2n9NNCGluKGkmTD1y+S256TZCb3nQruZCgkdyomgXAG8iN8qgAvhsRKaX0wxHodzF9riYXGGWB3xRxie6dk57uVX5D/rpHA7/tde6fetTptgR4DtghIrbpY4envtrcmD8eFRGZnjs8RcQ04GCgBbhjiN+LJEmSJE0o9y9v55Tb6wrKtp5Wxq8OmeU6NBo3hj2SJiK2B87Mf9lGbrrTJimlY1JKJ6eUvpE/vhXYBPgiuQAhgG9FxHYj1Pfheh+5hYCv7mPBYAAiYv+IqOyjfCFwcv7L/+x1+pf546kRMatHm62BE8n9jNaEN/k1errb/DAiMj3avAM4BHgUuLlHmyXAtUD3NXs6g9zonovzI3skSZIkaVJZ0drFh29YSVuP+RI1ZcElC+cws6roCSTSBlfMSJpPkRsZ0wW8PaX0t/4qppRagXMi4gHg//L3+xS54GZD614w+PwB6vwA2CW/3fYL+bLdgYX5999IKS3q2SCltCgizgG+ADwYEZcDlcAHgNnAZ1NKS3vd5xzgrcB7gTsj4npgPrkgqRn4aM/RMnmfBhYB50bEEcBj5NbIOZzcCKZTB/zuJUmSJGkC6som/u3mVbzQVLiixU8OnslusytK1CupOMVEim8iN83pfwYKaHpKKV0PXEpuNM1RRdxzvUTETuSmXg22YPAlwJ3AvsDHyQUjC4DLgDemlL7dV6OU0inAvwLLyIVBHwEeAd6WUvpZH/XbyP0czyS3bfbJwJHAFcC+KaU7+2izBNgH+B25cOYUYDvgXODAcbwluiRJkiQV7dv31nPTS20FZZ/ceQrv3662RD2SilfMSJr5+eN1w2z3N+CfgS2LuOd6SSk9xtptqgeq9xuKW6+GlNJFwEXDqN8CnJZ/DbXN88Dxw++dJEmSJE08Vy5t4T8eaiwoO3DjSr61b38b40pjWzEjaarzx+ZhtuuuX1XEPSVJkiRJWuOJug5OvGVVQdkmNRl+d9hsKjIuFKzxqZiQ5tX8cZdhtts5f3xtwFqSJEmSJA2goSPLh29YSWNnWlNWkYGLF85m49qyEvZMWj/FhDR3kZs69NH89s+Dytf7KLm1bO4u4p6SJEmSJJFS4rO31rF4dWdB+ff3n8F+GzlxQ+NbMSHN/+SPmwJXRcS8gSpHxFzgSmDzfNEfirinJEmSJEn88tEmrljaUlD2z9vX8tEdp5SoR9LIGfbCwSmlyyLi88ABwCHAkxFxEXAtua2gm4Ap5HZFOhI4jtwORgm4I6V0+Qj1XZIkSZI0idz5ShvfuHt1Qdmusys458CZRLgOjca/YnZ3AngncAu5IGY68Nn8qy/df1KezLeTJEmSJGlYXmvp4vibVtJjGRqmVwQXHz6bmnIDGk0MxUx3IqX0KrA38CugnVwQ09+rDfgFsE9KyUWDJUmSJEnD0pVNfOzmVbzUnC0oP++QWWw7vdixB9LYU/TTnFJqBD4VEd8AjgH2I7dOzTSgAXiZ3CLDf0kpLR+BvkqSJEmSJqHv3d/AzS+3FZSdtOtU3rpVTYl6JI2O9Y4c8wHMRfmXJEmSJEkj5trnWzn7gYaCsoM2ruSbe08vUY+k0VPUdCdJkiRJkkbbsw2dnPD3lQVlG9VkuPCw2ZRnXIdGE48hjSRJkiRpzGnvSvzrTSupa1+7UnBZwIWHzWaT2rIS9kwaPYY0kiRJkqQx58cPNXDf8o6Csm/uPZ03bFJVoh5Jo8+QRpIkSZI0pjxR17HOOjTHzK/mpF2nlqhH0oZhSCNJkiRJGjOyKfH5RXW099hte151hp+9YRYRrkOjic2QRpIkSZI0Zlz0RDO3v9JeUPb9/Wcwq8qPr5r4fMolSZIkSWPCy81dnHbP6oKyN29Rxbu3qSlRj6QNy5BGkiRJkjQmfOn2Ouo71u7mNLU8OPvAmU5z0qRhSCNJkiRJKrmrnm3hz8+1FpR9fe/pbDm1vEQ9kjY8QxpJkiRJUkmtbs/ypdvrCsr2mVfBx183pUQ9kkrDkEaSJEmSVFJn3FPPspa12zmVB/zkoFmUZZzmpMnFkEaSJEmSVDKLlrVx4RNNBWWf320au8yuKFGPpNIpKqSJiKcjYklEHDLSHZIkSZIkTQ6tnYnPLyqc5rT99HK+uMe0EvVIKq1iV2DaGkjAOvugRcRsYFeAlNLfi+6ZJEmSJGnCyqbEJ25ZyZOrOwvKf3zwTKrLneakyWk0lsk+BPgTkB2l60uSJEmSxrGUEl+9czVXLi3czem4HWp5wyZVJeqVVHoDhigR8TfgBuAm4M6UUtcwrm30KUmSJElax08fbuRXjxWuQ7PjjHLO3HdGiXokjQ2DjXRZCByef98cEbeQC2wkSZIkSRq2S5c088176gvKNq3NcPlRc5hR6d42mtwGC2l+BxxGbg2aKcDRwJt7nD8jIg4CbgfuSCmtHvkuSpIkSZImghtfbOXEW1YVlE2vCP7nyLlsOdXVMqQB/xSklD4KEBFbA0eQG1lzGLBpvsr+wH7d1SPiCWD5KPRTkiRJkjSOPbCinWNvWElnWltWkYH/PGIOu7rdtgQMcWHflNJS4Df5FxGRzZ+6FdgM2JbcGjQ7kdv1iXy9p4Abu18ppZdHquOSJEmSpPFhaUMn779uBY09Exrgl4fM4o2bulCw1G19x5N9O6V0bUTMAw7Mv44CXp8/vy2wDdA9IudJ4IaU0onreV9JkiRJ0jiwsrWL9167gldasgXl39lvBu/ZtrZEvZLGpgFXZYqI2UO5SErptZTS/0spfRU4s8epM8mNtmknN9JmR+CTRfZVkiRJkjSOdGQTH7lxJU/VdxaUn7jLVE7cZWqJeiWNXYONpHk1Ih4kt6PTDcDfU0r1AzdZK6V0OnB6RFQDB5HbKeqwonoqSZIkSRo3Ukp8+Y46bl3WXlD+nm1q+Na+00vUK2lsGyykyQB7AnsAnwOyEXFfj/NDmjyYUmolF/LcUEwnJUmSJEnjywWPN/HbJ5oLyg7cuJLzDplFJqJEvZLGtsFCmneTG/lyGLAbUAbsQ25x4ACuyO/otAi4LX/0T5skSZIkTWI3vdTKV+5cXVA2f2oZlyycTVWZHxml/gy2BfcVwBUAETELOJRcYHMSa4Oa15Fba+b4fLM1Y9kiYteU0sMj3mtJkiRJ0pi0ZHUnx924kq4eGzlNLQ/++4g5zK0uK13HpHFgwIWDe0oprUopXZFS+nyP4h8APwLuYO3iwFWsDXAeiIhXI+J/IuLEiNh5BPsuSZIkSRpD6tqyfPD6FaxuX5vQBHD+obPYZXZF6TomjRPruwX3jSmlawEiopLcVKjjgI+zNqiZC7yH3NQpIuK1lNIm63lfSZIkSdIY0plN/NvNK1m8unAnp9P2ns5b5teUqFfS+DLkkTSDSSm1p5QWAVf3KN6d3ILDVwJ15EKbeSN1T0mSJEnS2PDNe1Zz/YttBWXv366Gz+3mVtvSUK3vSJoB5dejeRj4aUQEuZ2iDh/Ne0qSJEmSNqyLn2zivEeaCsr2mVfBuQfNItzJSRqy9QlphvUnLaWUgPvyL0mSJEnSBLBoWRun3F5XULZ5bRm/XziH6nIDGmk4igppUkojNk1KkiRJkjQ+PdvQybE3rKQju7aspiz4/RGz2bjWnZyk4RqN6U7PAReNwnUlSZIkSWNEQ0eWf75+BSvasgXlvzhkFnvOrSxRr6TxbcRDmpTSfcDxI31dSZIkSdLYkE2JE25exaOrCndy+sqe03jnNu7kJBXLaUuSJEmSpGH59r31XPN8a0HZO7eu4ct7TitRj6SJwZBGkiRJkjRkly1p5pwHGwvK9phTwXmHzCTjTk7SejGkkSRJkiQNyT2vtfPZ21YVlG1Uk+H3C2dTW+7HS2l9+adIkiRJkjSoF5u6+JfrV9DWtbasqgx+v3AOW0wdjT1ppMnHkEaSJEmSNKC2rsRHbljBKy2FOzn95KBZ7LuROzlJI8WQRpIkSZI0oK/ftZp/LO8oKPv8blP54Pa1JeqRNDEZ0kiSJEmS+nXZkmZ+/XhTQdmbt6jiG3tNL1GPpIlrQoc0EbE0IlI/r2X9tDkoIq6OiJUR0RwRD0bE5yOibID7HBcRd0VEY0SsjoibIuKtA9SviYgzIuKJiGiNiFcj4rKI2GmANltExIUR8VJEtOW/tx9HxKzh/VQkSZIkaWgeXdXB5xfVFZRtNbWMX71xNmUZd3KSRtpkWN1pNfDjPsobexdExDuAPwKtwKXASuBtwH8ABwPv66PN2cApwAvAr4FK4IPAVRHx2ZTSz3rVrwKuy1/vHuAnwJb5ax8TEQtTSnf2arMdsAjYCLgSeBzYD/gccHREHJxSWjGUH4YkSZIkDUV9e5Zjb1hBc2daU1ZVBhcvnM3Mqgn97/1SyUyGkKYupXT6YJUiYjq5kKULOCyldE++/BvADcB7I+KDKaU/9GhzELmAZgmwb0ppVb78LOAfwNkR8eeU0tIet/oCuYDmcuADKaVsvs2lwBXAhRGxW3d53nnkApqTUko/7XH/c4CTge8Anxz6j0SSJEmS+pdS4sRbV7Gkvqug/OwDZrLHHBcKlkaL8eda7wXmAX/oDmgAUkqtwNfzX36qV5vuYOQ73QFNvs1S4OdAFXB8d3lERI82X+4ZxKSUrgRuAXYGDu3RZlvgKKD7mj2dBjQBx0bElKF/q5IkSZLUv5890shVz7YWlB27oJZjd/BjhzSaJkNIUxURH46Ir0XE5yLi8H7Wl1mYP/61j3N/B5qBg/LTlYbS5ppedQC2A+YDT6aUnhlim+731/YaXUNKqQG4DagFDujjepIkSZI0LLcta+P0e+oLynafXcEPD5hZoh5Jk8dkCGk2AS4hNyXox+SmLi2OiEN71dsxf3yy9wVSSp3AM+Smh20LkB+5sjnQmFJ6uY/7Ls4fdxjKPUa4jSRJkiQN27LmLj5600q61i5Dw4zK4OKFs6kpd6FgabRN9DVpfktuCtEjQAO5gOUzwAnANRFxYErpgXzdGfnj6n6u1V3eHR8Pt/6GbLOOxYsXD3R6TBqPfVbp+dyoGD43KpbPjorhc6Nijfaz09QJn364ildaCicenL59Cx3LnmFxn/vjaqzzd87YsmDBggHPT+iQJqV0Rq+ih4FPRkQjuQV/TwfeNcTLdcfGacBafXRjGHWLuceQ2gz2IIw1ixcvHnd9Vun53KgYPjcqls+OiuFzo2KN9rPT2pl433XLebSxvaD8i3tM4/i9Nh+1+2p0+Ttn/JkM05368sv88Y09yrpHpMygb9N71Rusfl8jYIZ7j2LbSJIkSdKQdGQTx9+0kluWFQY0Czer4qt7TitRr6TJabKGNK/mjz2XJn8if1xnbZeIKAe2ATqBpwFSSk3Ai8DUiNi0j3t0x5U915Lp9x4j3EaSJEmSBpVNiRNvWcU1zxfu5LTX3AouWjibsozr0Egb0mQNaQ7MH5/uUXZD/nh0H/XfSG4HpUUppbYhtvmnXnUAlgDPATtExDZDbHNj/nhURBT894qIacDBQAtwRx/XkyRJkqQ+pZT48h2ruezploLynWaWc/mRc5hWMVk/LkqlM2H/1EXELhExu4/yrYCf5b/8zx6nLgeWAx+MiH161K8Gvp3/8he9Ltc9berUiJjVo83WwIlAG7nFiwFIKaUebX7YM3SJiHcAhwCPAjf3aLMEuBbovmZPZ5AbDXRxfmSPJEmSJA3Jt++t54LHCz9GbD2tjP9981xmV5f100rSaJrICwe/D/hKRNxIbvvsBmA74BigGrgaOLu7ckqpPiI+Ti6suSki/gCsBN5Obhvsy4FLe94gpbQoIs4BvgA8GBGXA5XAB4DZwGdTSkt79esc4K3Ae4E7I+J6YH6+v83AR1NK2V5tPg0sAs6NiCOAx4D9gcPJTXM6tZgfkCRJkqTJ6ScPNfCjBxsLyjapyXDFm+eyaa0BjVQqEzmkuZFcuPJ6ctObpgB1wK3AJcAl+ZEta6SUroiIQ8mFHu8hF+Y8RS6EObd3/XybUyLiQdZu7Z0F7gXOSin9uY/6bRHxJuArwIeAk4F64ArgtJTSo320WZIf3XMmualVbwFeBs4FzkgprRzmz0aSJEnSJHXxk02cdk99QdmsquBPb57L1tMm8kdEaeybsH8CU0o302Pa0DDa3UYuBBlOm4uAi4ZRvwU4Lf8aapvngeOH0y9JkiRJ6umhlR188fa6grKp5cEfj5zLTrMqStQrSd0m7Jo0kiRJkqS1WjoTH795Je09FleoKoP/ftMc9ppXWbqOSVrDkEaSJEmSJoHT7lnN43WdBWW/eMMsDtm0qkQ9ktSbIY0kSZIkTXB/e6GV8x8r3Mnpn7ev5d3b1paoR5L6YkgjSZIkSRPY8tYuPn3rqoKyraaW8YP9Z5SoR5L6Y0gjSZIkSRNUSomTbqvj1Za1C9FkAs5/4yymV/pxUBpr/FMpSZIkSRPUxU82c/VzrQVlX9xjGvtv7Do00lhkSCNJkiRJE9BTqzv46l2rC8r2nlvBl/aYVqIeSRqMIY0kSZIkTTAd2cQJf19Fc2daUzalPPj1obOpyEQJeyZpIIY0kiRJkjTBfP++eu5d3lFQ9r39Z7Dt9PIS9UjSUBjSSJIkSdIEcv6jjfzowcaCsrfOr+bYBW63LY11hjSSJEmSNEFc8FgjX76zcB2aTWoy/OTgmUQ4zUka6wxpJEmSJGkC+O3jTXzxjsKApqoMfn3obOZUl5WoV5KGw5BGkiRJksa5i55o4uTb6wrKqsrgv46YwyGbut22NF4Y0kiSJEnSOHbJk018blFhQFOZgf9cOIcjNq8uUa8kFcOQRpIkSZLGqd8vbuKk2woDmooMXLxwNkduYUAjjTeGNJIkSZI0Dv33U8185tY6Uo+yigxcfPhsjt6ypmT9klQ8QxpJkiRJGkdSSvzkoQY+dcuqgoCmPOB3h83mn+Yb0EjjVXmpOyBJkiRJGprObOLLd6zmwieaCsrLAi48bDbHbGVAI41nhjSSJEmSNA40dmT5t5tW8n8vtBWUlwf85rDZvH1rAxppvDOkkSRJkqQxbnk7fOya5TywoqOgfHpFcMnC2Ry6mYsESxOBIY0kSZIkjWGPrerg+AeqWdZWGNBsMaWMy46cw86zKkrUM0kjzZBGkiRJksaom19q49gbV1DfXrjny+6zK7j0yDlsWltWop5JGg2GNJIkSZI0Bv33U82cdNsqOrKF5UdtUcWFh81maoWb9UqsR9u2AAAgAElEQVQTjSGNJEmSJI0hKSV++EAD37uvYZ1zx+9Yy1kHzKQ8EyXomaTRZkgjSZIkSWNERzbx+UV1/H5x8zrnzthnOiftOpUIAxppojKkkSRJkqQxYHV7luNuXMlNLxVusV2ZgdMWtHHibtNK1DNJG4ohjSRJkiSV2AuNnbz/byt4dFVnQfmsquC/jpjD3PrnStQzSRuSK01JkiRJUgk9uKKdI//y2joBzdbTyrj2mHkcuHFViXomaUNzJI0kSZIklUBXNvHrx5s48x/1NHemgnP7zKvgv4+Yw7wat9iWJhNDGkmSJEnawB6v6+CkW+u467X2dc69dX415x86i9pyJz5Ik40hjSRJkiRtIO1diZ881MBZDzTQnl33/Kd2nsK3951BmVtsS5OSIY0kSZIkbQD3LW/nM7eu4pFea88ATK8MvrvfDD68YEoJeiZprDCkkSRJkqRR1NSR5fv3N/DzRxrJpnXPv2V+NT86cCab1rr+jDTZGdJIkiRJ0ii57oVWTrm9jucau9Y5N7c6w1kHzOCdW9cQ4fQmSYY0kiRJkjTiljV38bW7VvO/z7T0ef7929Xw/f1mMLva0TOS1jKkkSRJkqQRkk2J3z3RzOn/WE19+7pzmzavLeM/DprJUVtWl6B3ksY6QxpJkiRJGgGPrOzg5EV9b6udCThhpymcutd0plW4tbakvhnSSJIkSdJ66MgmfvRAA2c/0EBnHwsD7zGngh8fNJPXz63c8J2TNK4Y0kiSJElSkR5Z2cGnblnFgys71jk3pTw4da/pnLDTFMozLgwsaXCGNJIkSZI0TJ3ZxLkPN/K9++rpyK57/ugtqznrgBlsOdWPXJKGzt8YkiRJkjQMT9R18OlbVvGP5euOnplXneFHB87kbVtVu622pGEzpJEkSZKkIejMJn7xaCPfvreetq51z79nmxp+eMAM5rittqQiGdJIkiRJ0iBufqmVr961mkdXda5zbk5VbvTMO7epKUHPJE0khjSSJEmS1I8lqzv5+t2rueb51j7Pv3V+NeccNJONahw9I2n9GdJIkiRJUi91bVnOeqCB8x9r7HNh4JmVwVkHzOS929a49oykEWNII0mSJEl5ndnExU82851761nR1kc6A3xguxpO32cGm9Y6ekbSyDKkkSRJkiTgxhdbOfWu1Txat+66MwD7zavke/vPYO95lRu4Z5ImC0MaSZIkSZPaU6s7+Prd9fy1n3VntphSxhn7TOfd2zi1SdLoMqSRJEmSNCnVtWX54QP1nP9oE51p3fO15cHJu03lxF2nUlue2fAdlDTpTNjfNBExJyI+FhF/ioinIqIlIlZHxK0R8W8RkelVf+uISAO8/jDAvY6LiLsiojF/j5si4q0D1K+JiDMi4omIaI2IVyPisojYaYA2W0TEhRHxUkS0RcTSiPhxRMwq7ickSZIkTU6d2cQFjzWy1x9f4bxH+g5o/nn7Wu5598Z8ac/pBjSSNpiJPJLmfcAvgJeBG4HngI2BdwMXAP8UEe9LKfX+lfwAcEUf13u4r5tExNnAKcALwK+BSuCDwFUR8dmU0s961a8CrgMOBu4BfgJsme/vMRGxMKV0Z6822wGLgI2AK4HHgf2AzwFHR8TBKaUVg/5EJEmSpEnu3tfa+dyiOh5a2dHn+f03quR7+81gL9edkVQCEzmkeRJ4O/CXlNKaZdkj4mvAXcB7yAU2f+zV7v6U0ulDuUFEHEQuoFkC7JtSWpUvPwv4B3B2RPw5pbS0R7MvkAtoLgc+0N23iLiUXDh0YUTs1rPPwHnkApqTUko/7XH/c4CTge8AnxxKnyVJkqTJqLEjy3furedXjzWR7WPkzBZTyjhzn+m8y3VnJJXQhB23l1K6IaV0Va+wg5TSMuCX+S8PW8/bdAcj3+kOaPL3WAr8HKgCju8uj9xv++42X+7Zt5TSlcAtwM7AoT3abAscBXRfs6fTgCbg2IiYsp7fiyRJkjQhXfNcCwf86VV+8ei6Ac2U8uDre03n7ndvzLu3rTWgkVRSEzakGUT32Ma+9tbbLCI+ERFfyx93H+A6C/PHv/Zx7ppedQC2A+YDT6aUnhlim+731/YRODUAtwG1wAED9FOSJEmadJY1d3HcjSv45+tX8kJT1zrn37ttDfe8Z2O+uMc0asoNZySV3kSe7tSniCgHPpL/sq9w5cj8q2ebm4DjUkrP9SibAmwONKaUXu7jOovzxx16lO2YPz7ZT/eKbXNUvs31/dSRJEmSJo22rsSFjzfxvfvrqW9fd27T/KllnHPgTN60RXUJeidJ/Zt0IQ3wfWBX4OqU0v/1KG8GvkVuXZin82W7A6cDhwPXR8SeKaWm/LkZ+ePqfu7TXT6zR9mGarOOxYsXD3R6TBqPfVbp+dyoGD43KpbPjorhczN6OhNc/UoZ5z9fwStt604aKCPxoc07+fj8ZmpaGhhv/yl8dlQMn5uxZcGCBQOen1QhTUScRG6h38eBY3ueSym9CnyzV5O/R8RRwK3A/sDHyO3GNBx9LEvWfxdHq81gD8JYs3jx4nHXZ5Wez42K4XOjYvnsqBg+N6MjmxJXPNPCd+9r4Kn6vlY0gNfPreAnB81k9znjc9cmnx0Vw+dm/Jk0IU1EnEguYHkUOCKltHIo7VJKnRFxAbmQ5o2sDWm6R7DM6LNh3yNgBmszfYTaSJIkSRNeSolrX2jjW/fW83A/W2pPLQ9O3Ws6J+w0hbKM685IGtsmRUgTEZ8H/gN4mFxA8+owL/Fa/rhmB6WUUlNEvAhsHhGb9rEuTXdc2XMtmSfyxx3o20i1kSRJkia0x+s6OOX2Om5b1t7n+coM/NvrpvCF3acxr6ZsA/dOkooz4UOaiPh3cuvQ3A8cmVJaXsRlundOerpX+Q3kpk0dDfy217l/6lGn2xLgOWCHiNimjx2e+mpzY/54VERkeu7wFBHTgIOBFuCOIX4vkiRJ0rjV3JnlrPsb+OnDjXT2MeG/LOBfFtTypT2mseXUCf9xR9IEM6G34I6Ib5ALaP5BbgRNvwFNROwfEetMUI2IhcDJ+S//s9fpX+aPp0bErB5ttgZOBNroEd6klFKPNj+MiEyPNu8ADiE3HevmHm2WANcC3dfs6Qxyo3su7rGgsSRJkjQh/fX5Fvb/06v8x0N9BzTv2aaGO9+1EecePMuARtK4NGF/c0XEccCZQBdwC3BSxDpzUJemlH6Xf/8DYJf8dtsv5Mt2Bxbm338jpbSoZ+OU0qKIOAf4AvBgRFwOVAIfAGYDn00pLe11z3OAtwLvBe6MiOuB+cD7yO0w9dGeo2XyPg0sAs6NiCOAx8itkXM4uWlOpw7hRyJJkiSNS883dvKVO1fzl+da+zx/xOZVnLb39HG7KLAkdZuwIQ2wTf5YBny+nzo3A7/Lv78EeBewL7lpRxXAK8BlwM9SSrf0dYGU0ikR8SDwGeAEIAvcC5yVUvpzH/XbIuJNwFeAD5EbpVNPbuvv01JKj/bRZklE7EMudDoaeAvwMnAucMZQF0GWJEmSxpPV7VkueKyJcx5soKmPoTOb1Wb43v4zeftW1fTxD7KSNO5M2JAmpXQ6cPow6v8G+E2R97oIuGgY9VuA0/KvobZ5Hjh++L2TJEmSxpdlzV384pFGfvtEE/Ud64YzZQGf2HkKX339dKZVTOgVHCRNMhM2pJEkSZI0vjy1uoNzH27kD0810957AYC8feZVcM6BM53aJGlCMqSRJEmSVFL3LW/nnAcb+POzrfSxHjAAMyqDM/aZwUd2qCXj1CZJE5QhjSRJkqSSWNrQyZn/qOd/n2npt86cqgyf2HkKH99pKrOqnNokaWIzpJEkSZK0QdW1ZTn7gQbOf6yx32lNW00t47O7TuVDC2qpLTeckTQ5GNJIkiRJ2iDauxIXPN7ED++vp66974lNu82u4PO7TeUdW9dQnnFak6TJxZBGkiRJ0qhq6Uz8+dkWvntfPc80dPVZZ/fZFZy2z3QWblbldtqSJi1DGkmSJEkjrqUzcd0LrVy5tIW/Pt9KU2ffI2c2ry3jG3tP5/3b1bggsKRJz5BGkiRJ0ogYajADMLU8OHn3aXxqlymuOSNJeYY0kiRJktZLSolLFjfzzbtX97vWTLeygH/dcQr/vuc0Nqop20A9lKTxwZBGkiRJUtFebu7ic7et4toX2gast2lthrdtVcPHXjeFHWZWbKDeSdL4YkgjSZIkadhSSvzxmRa+eHtdv6NnNq3N8PatanjnNjXsv1Gla85I0iAMaSRJkiQNy4rWLk65fTVXLG1Z59yU8uDDC2p51zY17GcwI0nDYkgjSZIkaciufq6Fz91Wx2ut2XXOHbhxJee9YRbbTPdjhiQVw9+ekiRJkgZ15ytt/PCBBq5/cd21Z6rK4Ot7TefTO0+lLOPIGUkqliGNJEmSpH4tWtbGD+5v4OaX+14YeI85FfzykFnsNMvFgCVpfRnSSJIkSSqQUuLWZe384P56bl3W3medsoAv7jGNL+4xjQpHz0jSiDCkkSRJkgRAXVuWq59r4ZLFzdz+St/hDOTWnvnefjPYc27lBuydJE18hjSSJEnSJFbXluUvz7Vw5dIWbnypjY511wNe4w2bVPLve07nkE2rNlwHJWkSMaSRJEmSJpn69ixXPdvCFc+0cNPLAwczAIdtVsWX9pjGwZsYzkjSaDKkkSRJkiaBlBL3Le/gd0828cenW2jqTIO2OWLzKr68xzT239hwRpI2BEMaSZIkaQJb3Z7l8qeb+d0TzTy0smPQ+ttPL+edW9fwrm1q2GW2OzZJ0oZkSCNJkiRNMO1diUWvtPHHp1v44zMtNA8yambBjHLesXUN79y6hl1mlRPhbk2SVAqGNJIkSdIEsLK1i2tfaOOvz7dyw4ut1HcMHMxsVpvhQ9tP4V3b1LCzwYwkjQmGNJIkSdI4tbShk/+3tIVrnm/lzlfbyQ6yzEwm4MjNq/jXHadw5BbVlGcMZiRpLDGkkSRJksaRho4sVzzTwn8/1cyiV9qH1Gaz2gzH7jCFDy+oZcupfgSQpLHK39CSJEnSGNeVTdyyrI3/eqqZPz/bOugaMwDzqjMctWU1b9uqmjdt7qgZSRoPDGkkSZKkMeq1li4ueLyJ3y9u5oWmrkHr7zyrnH/aspqjt6xh73kVZFxnRpLGFUMaSZIkaYx5vK6D8x5p5NIlzbQNks3sN6+S92xbw9FbVrPVNP96L0njmb/FJUmSpDEgpcTfX27jZw83ct2LbQPW3WJKGR/crpYPbl/D9jMqNlAPJUmjzZBGkiRJKqEXGjv524tt/ObxJh5a2dFvvdry4G1bVfOh7Ws5ZNMqpzJJ0gRkSCNJkiRtQI0dWW5b1s4NL7Zy40ttPLm6c8D686eW8amdp/IvC2qZXpnZQL2UJJWCIY0kSZI0yp6s6+Dq51q56qkqHlz0Mh3ZwdvsM6+Cz+wyjbdu5c5MkjRZGNJIkiRJI6wrm7jntXb+8lwrVz/XylP13aNlygZsF8Ax86v5zK5T2X+jSsIpTZI0qRjSSJIkSSOgpTNx88ut/OXZVv76fCuvtQ5huAxQFrDfRpUctlkV79u2lm2n+1d0SZqs/D+AJEmSVKSVrV383wtt/OXZFm54qY3mzjSkdttNL+Pwzao5fLMqDtm0yrVmJEmAIY0kSZI0LEsbOrn6uVb+8lwLd7zSTtcQcpmKDByySRX71DTwoddvydbT/Gu4JGld/t9BkiRJGkBHNnH7K+1c90Ir1z7fyhOD7MbUbXpFcOQW1Rwzv5ojtqhmRmWGxYtXGdBIkvrl/yEkSZKkXl5p7uK6F1u57oVWbnyxjfqOoU1j2qw2w1vm1/CW+dW8YZMqKstc+FeSNHSGNJIkSZrU2rsSj6zq4O5X27nntXbufq2dZxq6htx+51nlvGV+DcfMr2bPORXuyCRJKpohjSRJkiaNrmxicX0nD67o4IEVHdzzWjsPrGindeiZDGUBB2xcuSaYcfqSJGmk+H8USZIkTUhd2cSDK3NhzIMrOnhwZTuPrOykZSgr/fYyrzrDm7ao5s1bVHPYZlXMrHI3JknSyDOkkSRJ0oSyqi3LxU82ccHjTTzfOIwhMj2UBewxp4Ij88HMnnMryDiNSZI0ygxpJEmSNCE8srKD8x9r5LIlLcMeLbNpbYZ951Wy77xK9p5XyZ5zK6gtd7SMJGnDMqSRJEnSuNWRTfz1+VbOf7SRW5a1D6nNvOoMu8+pYPfZFew5t5J95lWy+ZSyUe6pJEmDM6SRJEnSuLCqLctDKzt4uMfr8boO2rP9t6kug4Wb53Zd2n1OBXvMqWSTmow7MEmSxiRDGkmSJI0pXdnEMw2dPLyyk4dWtucDmU5ebB76+jJbTCnjY6+bwkd2qGV2taNkJEnjgyGNJEmSRlVnNvFEXScPrGjntdYsXQmyCbIp5Y7kvl7e0sXDqzp4dFUnzZ3D34EJ4KCNK/nEzlM5Zn415RlHy0iSxhdDGkmSJI2Y9q7Eo6s61mx9ff/ydh5Z1UFrcZssDckmNRmO3KKaE3aeym6zK0bvRpIkjTJDGkmSJBUlpcSzjV3c81r7mteDKwZeI2Z9lAfsOLOcXWdXsOvsCnbLH+c6nUmSNEEY0owjEbEFcCZwNDAHeBm4AjgjpbSqlH2TJEkTQ0qJxs7EitYs9e1ZGjoSjR2Jxo7c+4aOLKvbEw+v7OCe19pZ3jo6iczsqkw+jClnt9mV7Dq7gh1nlFNZ5hQmSdLEZUgzTkTEdsAiYCPgSuBxYD/gc8DREXFwSmlFCbsoSZI2kO4gpb49F5o0tCeaOxOtXblXS/59c2eirSvRmU10JvJrwSQ6s7n3HdlEXVuW5a2514rWLMvbumgbhalJG9dk2HNOBdvPqKAyA5mAiCATUBaQAarLgh1n5kbHbFrrDkySpMnHkGb8OI9cQHNSSumn3YURcQ5wMvAd4JMl6pskSZNSNiXau6A9m+jIJtp6ve/IJtq7Em3Zte9buxJNnYmmjlyI0tSZaO7M0tyRaOlae732rkR7du37lq4eoUxHbsHdsWrz2jL2mFvBHnMq2HNOJXvMqWCTWqckSZI0GEOacSAitgWOApYCP+91+jTgBODYiDglpdS0gbsnaYSkNLxPXMP9fDbMyw//+sOtP9r9GWKDtiy0dqYivt9h/vfaAD//lN8xB3LhQcqXZ1P+XL5O6nG+u35320TKHwvb9mzT/XXPa65zvx5t6XHNbEHb1OPa9NGfVNhmzTVTwfdSeI3U43vJvbpSbnehtnzo0dGVaMsmOrLkA5RERz/BSHs+XGnrytfvUd7WVUPXrS8N87/UxDOlPNhzbgX7zqtk73mV7DOvkk0NZCRJKoohzfiwMH+8NqVUMPE7pdQQEbeRC3EOAK7f0J0babe/0sZ7b6+h7M6h/cV3zH0wHG79YfdnnH+QH83rpxrSbS8O7/qj/P1qPKiFRX7QVjEm7lScqjKYW1XGjKpgekWGqRXBtO5jZTC1IsPmtWXsPa+S180sd6trSZJGiCHN+LBj/vhkP+cXkwtpdmAChDRdCZq6IvdGGpYwRZE0adSUBdMrg+mVGaZVBDXlQU1ZUF0W1JYH1eW599VlQUUGyjJBWUBZBOXd68BkghmVwdzqDHOry5hbnWFOdYap5eF6MJIklYAhzfgwI39c3c/57vKZ/V1g8eLFI9qh0fTC6gxQXepuSJI0JBWRqMhARUBFJuWOwbpl+a8rM4maMqgpS9RkcsfqDNSUQXUmUdmzXff7fLsp5TC1LDG1DMozI/hNtOZeHcCyEbys+jae/l6mscVnR8XwuRlbFixYMOB5Q5qJofufuvodQzDYgzCWvLKsDR5aXupuSOPCcP+de7j/MD7s6w+3/mj3ZwgNUjYR+akaw/9+h9ditL/fTOTaRI9jhsgd82Vr6uTLI7+rThScj4JrZfKdyUTk23bvzNO7bfRx/7U7+BS0zR/Jt1mnf330PQquEYP2nR7nKzNBZVlQmcm9rygLqjJQWRZUZPLlZZGrl4GKHnUry4KqTFBRxprzlWXBc08vYacdtnfEiYZl8eLF4+rvZRo7fHZUDJ+b8ceQZnzoHikzo5/z03vVG9cO2KiSGw9oZtvtthtymzH3wXC49Yfdn2F+MBze5cfEB+dirr/4qadYsP32Y6Y/uWv74W2s8y8vKlZFxj/jkiRpZBnSjA9P5I879HO++9NFf2vWjCvlmeD/t3ff4ZJUZR7Hvz8ZcgYliMhIlKSiCAoSRpCgiKLkBRldEFZEEBB2jcCqyIJK0AWRnCSMCgqISBgQUILAKoikcUCRIGlmgGFI7/7xnrZrms5z79yemd/neerprqpTVaf7nntv19vnvGehUbDoPEPZj9vmBKOEk1eamZmZmdksy3fBs4Zry+MWkqb7mUlaGNgQmAr8fmZXzMzMzMzMzMyGhoM0s4CIeBC4EhgN7Nuw+3BgQeCsiHh+JlfNzMzMzMzMzIaIhzvNOj4H3AQcL2kz4B5gfWAMOczpKyNYNzMzMzMzMzObQe5JM4sovWnWBc4ggzMHASsBxwPvj4inRq52ZmZmZmZmZjaj3JNmFhIRfwM+PdL1MDMzMzMzM7Oh5540ZmZmZmZmZmYDwEEaMzMzMzMzM7MB4CCNmZmZmZmZmdkAcJDGzMzMzMzMzGwAOEhjZmZmZmZmZjYAHKQxMzMzMzMzMxsADtKYmZmZmZmZmQ0AB2nMzMzMzMzMzAaAgzRmZmZmZmZmZgPAQRozMzMzMzMzswHgII2ZmZmZmZmZ2QBwkMbMzMzMzMzMbAAoIka6DjZMJk2a5B+umZmZmZmZ2QBadNFF1bjNPWnMzMzMzMzMzAaAgzRmZmZmZmZmZgPAw53MzMzMzMzMzAaAe9KYmZmZmZmZmQ0AB2nMzMzMzMzMzAaAgzQ2MCS9RdJpkv4haZqkiZKOlbT4SNfNRo6kJSXtKennkh6QNFXSJEk3SPp3SU3/jknaQNLlkp6W9IKkP0o6QNJcM/s12OCQtLukKMueLcq47RgAkjaS9FNJj5b/S49KulLSh5uUdbsxJH2ktJG/l/9XEyRdJOn9Lcq73cwhJG0v6QRJv5U0ufwfOqfDMT23D0l7SLpF0nPl89J4SdsM/SuymaGXdiNpFUmHSrpG0t8kvSTpcUmXSBrT4TpuNwPEOWlsIEhaCbgJWAq4BPgLsB4wBrgX2DAinhq5GtpIkbQPcCLwKHAt8DCwNPAJYFHgp8AOUfljJuljZfuLwAXA08BHgdWAcRGxw8x8DTYYJC0P/AmYC1gI2CsiTmko47ZjAEj6KvDfwJPApeTfoDcC6wDXRsQhlbJuN4ako4BDgKeAi8m2szKwLTAK+FREnFMp73YzB5F0J/BO4Dng78DbgXMjYrcW5XtuH5KOAQ4q5x8HzAPsDCwB7BcRPxjil2XDrJd2I+l8YCfgz8ANZJtZjfwbNBewf0Qc3+Q4t5tBExFevIz4AvwaCPIPQXX798r2k0a6jl5GrG18kPxQ8oaG7cuQAZsAPlnZvgjwBDANWLeyfT4yEBjAziP9urzM9HYk4CrgQeDo0g72bCjjtuOl9jPfofy8fwMs3GT/3JXnbjdeav+TXgUeA5Zq2DemtIMJbjdz7lLawSrl/9Gm5Wd8TouyPbcPYIOy/QFg8cr20WTg8EVg9Ei/D16Gtd2MBdZpsn0T4KXSnpZ1uxn8xcOdbMRJWhHYApgI/LBh9zeA54HdJS04k6tmAyAiromIX0bEaw3bHwNOKqubVnZtD7wJOD8ibquUfxH4aln9j+GrsQ2oL5ABv0+Tf1OacdsxyhDKo4AXgF0jYkpjmYh4ubLqdmMAK5BpBG6OiCeqOyLiWmAK2U5q3G7mMBFxbUTcH+UOuIN+2sc+5fFbEfFM5ZiJ5Ofrecn/gTYL6aXdRMQZEXFHk+3XAePJHjIbNOx2uxlADtLYIPhgebyyyY34FOBGYAHgfTO7YjbwajdKr1S21drTFU3KX0/eeG0gad7hrJgNDkmrA98BjouI69sUddsxyA+wbwMuB54pOUYOlbR/i7wibjcGcD/5TfV6kt5Y3SFpY2BhsjdfjduNtdNP+2h3zK8ayticp9lnZnC7GUgO0tggWK083tdi//3lcdWZUBebRUgaBXyqrFb/sbRsTxHxCvBXMjfAisNaQRsIpZ2cTQ6N+3KH4m47BvDe8vg4cDuZj+Y7wLHATZKuk1TtEeF2Y0TE08ChZM60P0s6WdKRki4EriSHzu1dOcTtxtrpqX2U3ubLAc9FxKNNzufP0nMwSSsAm5HBvesr291uBtSoka6AGZn8FWBSi/217YvNhLrYrOM7wFrA5RHx68p2tyer+jqZ6PUDETG1Q1m3HYNMYA/ZBfyvwObAzeRwlu8CWwIXUR9m6XZjAETEsZImAqcBe1V2PQCc0TAMyu3G2um1fbg9WVOlt9W55LClQ6pDmnC7GVjuSWOzApVHT0VmAEj6ApmF/i/A7r0eXh7dnmZzktYje898NyJ+NxSnLI9uO7O32tS2AraPiKsj4rmIuBvYjpz9YpNWUyo34XYzh5B0CDkzyhnASsCCwHuACcC5kv6nl9OVR7cba6bf9uH2NAcpU7WfDWxIzhB2TJ+ncruZyRyksUFQi9Iu2mL/Ig3lbA4maV/gOHJ6wTGli3mV25NVhzndB3yty8Pcdgyg9i3jhIj4v+qO0hur1nNvvfLodmNI2pRMOP2LiDgwIiZExAsRcTsZ3HsEOKhMlgBuN9Zer+2jU/lOPSZsNlMCNOeQsxVeCOzWJPmw282AcpDGBsG95bHVeMdVymOrnDU2h5B0APAD4C4yQPNYk2It21O5cX8bmTRtwnDV0wbCQmQbWB14UVLUFnLWOIAfl23HlnW3HYN6O3i2xf5aEGf+hvJuN3O2bcrjtY07IuIF4Bbyc/c6ZbPbjbXTU/uIiOfJQOBCkpZtcj5/lp6DlDbyE2Bn4DxypsLGhMFuNwPMQRobBLUPNFuUqd1DN0IAABiCSURBVE//RdLCZBe9qcDvZ3bFbHBIOhT4PnAnGaB5okXRa8rjVk32bUzOFHZTREwb+lraAJkGnNpiqU1PeUNZrw2FctsxyKSKrwCrSJqnyf61yuPE8uh2Y5D5HmD6abarattfKo9uN9ZOP+2j3TFbN5Sx2VT5vzWO7EFzFrB7RLza5hC3mwHkII2NuIh4kJz5YDSwb8Puw8kx3WeVaK/NgSR9jUwU/Adgs4h4sk3xccCTwM6S1q2cYz7gm2X1xOGqqw2GiJgaEXs2W4BflGJnlm0XlHW3HaP8fbmA7Ob99eo+SR8iEwdPoj6rnNuNAfy2PH5W0nLVHZK2Jr9wehG4qWx2u7F2+mkfJ5XHr0havHLMaPLz9TTg9GGqrw2AkiT458DHyC+hPh0Rr3U4zO1mAOn1Q9PMZj5JK5EfXJYCLgHuAdYHxpBd7DaIiKdGroY2UiTtQSZhfBU4gebjYidGxBmVYz5OfsB5ETgfeBrYlpzSchywY5NxuTaHkHQYOeRpr4g4pWGf244haSngRmBl8ub7FnJ2p+3IBIq7RsRFlfJuN3O40hP41+RsYFPIG6XHyCGX25CJXg+IiOMqx7jdzEHKz/vjZXUZMuA7gXqA78mIOLihfE/tQ9J3gQPJBOfjgHmAnYAlgf0i4gfD8uJs2PTSbiSdDowlA3z/S/OEv+MjYnzDNdxuBoyDNDYwJC0PHEF2t1sSeBS4GDi8SXJYm0NUbqjbuS4iNm04bkPgK8D7gfnIKVBPA47v0O3TZnPtgjRlv9uOIWkJ4KtkYGY58sb7BuDIiHjd8Fu3G5M0N/nN887AGuSQlKfJIN/xEXFlk2PcbuYQXXyeeSgiRjcc03P7KF9ufZ5sg68BtwNHR8SlM/gSbAT00m4kjQc26XDKwyPisCbXcbsZIA7SmJmZmZmZmZkNAOekMTMzMzMzMzMbAA7SmJmZmZmZmZkNAAdpzMzMzMzMzMwGgIM0ZmZmZmZmZmYDwEEaMzMzMzMzM7MB4CCNmZmZmZmZmdkAcJDGzMzMzMzMzGwAOEhjZmZmszRJ4yWFpBjpupiZmZnNiFEjXQEzM7NZQZsAwEvAZGAS8BBwO3AzcFlETJ1J1ZtlSVoa+BTwIWAtYHFgLvI9fRi4B7gVuCYi/jhS9ZzVSVoWWBd4T+VxmbL7oYgY3ed5FwaeBOYBvhQRx1T2rQZsBWwEvAN4MzA38CxwF3AlcGpEPNnFdd4KbA1sDLwTeCswH/l7dy9wDXBKRDzcx2s4H9gJuDsi1qpsXxTYEhgDvBtYGVgEeI5smzcCp0fErT1ebyvg08D7gKXJtn4/MA44OSKe73D8KGBTYHNgPWB1YAngZeBx8vflfOCXEfFqD/VaC9ib/F18C/Aq+TovBU6KiIe6fpFmZtY3RfhLJzMzs0766KXxLHAm8I2ImDQMVZrlSdobOAZYqMtDPhcRJzY5z3hgE4CI0JBVcDYh6aPAL9oUmZEgzY7ABWV1tYi4r2y/A3hXF6eYDOwbEee0ucbFwLZAp5/tNOCr1UBRJ5LmBv4JLAocGRFfLtsPAY4A5u3iNOcAe0fECx2uNS9wOrBLm2IPAp9oFZCUNIYM5izRRb1uBXaJiAc7FZR0MPBtMojWzBTgsxFxfhfXNTOzGeCeNGZmZr3brvJc5A3e4uRN6cbAaGAxYH/gk5J2iYgbZnYlB5mk/YDjK5vuBH5J9iiYSr5/awAbAu8l3+e5mp0rIjYdzrrOBhrft5fJnizrDMG5ty2P99YCNMXa5fE14AbgOmAC8ALwNmBXsnfNIsBZkmgTqFmLeoDmVuBa4D4ywPMW4JNkO5kXOFrSvBHxrS7rvwn5+wvTB7JWpR6gmQBcRbbRJ8nf9c3KdecCdgOWkrR1RLzW5lpnkj12AJ4CTgb+BLyxnGM9YCXgCknrR8TfmpxjOeoBmqdLvX4PPEoGWNYje6YtQv7eXCtpvYh4rFWlJO0DHF1WXwbOJn9ec5M9ibYHFgbOlvRsRFzR5jWamdkMck8aMzOzLlR70rTrrSFJ5LCMY4FVyubJwAYRcfewVnIWUYbePAjMDwTZQ+akNuXfTA4P+UtE/HTm1HL2IWkD8v27DfgD8MeIeKnSpvvqSSNpLuAJMmhwdEQcUtn3NHAiOUzmdcEGSW8gAwMHlk3PAitFxNNNyt4FjAdOiIh7W9TlAOD7ZfUVYM2GoFGr13A8sB85TGjZKB+MJf0YWLbU8fpo8oFZ0kbA5dR7gn0mIk5vcZ2PAReX1YeBjapDs8r7cQr5cwIYFxE7NDnPbsAhwJHAzyJiWpMyywG/BtYsm86KiD1a1GtZ4AFgAfJ92zoirmooM5bsAQTwN2DViHix2fnMzGzGOUhjZmbWhW6DNJXyiwCXAR8om+4B1urwTfscQdK+wA/K6gURsfNI1mdONQRBmk3JXi2QQYcbKvsWj4hnOhwvMn/Te8umpkGObs5Vyo0je7cAHBER3+jimL+SPd9OjYg9+7jm54ETyur1EbFJi3LV4V8fiYjLm5SZH/gLmW8HYO2IuKuhzGLApGZBo4Zya5G9dCB7pr2x2XAsSd8HDiir0wXaGspdCNSCRp+PiB+2u76ZmfXPszuZmZkNg4iYDOxI9hCATO65U7OykuaXtJ2kH0q6WdJTkl6WNEnS3ZJOlPTOVteS9B+12Y0kfbGb+kn6ZeWY1Zvs31TSmZLulfScpJckPSbpLknjJO0paZlm5+7C2yvPr+vzHNW6tp3dSdLYymsdW7atIelHkh6UNLW851dL2qUED7q57uKSDpF0laR/SJom6fnynp0n6d8kzdfhHFtJOkPS/ZKmSHqh1OkMSR9od+wAqA11ehK4qbqjmwBHCTRUe0at3aJcx3MVF3U6V5Wkd5ABGmjI2TOU15S0CvUAzf3NAjTlmlOBH1c27dikzLOdAjSl3F1kwAeyx9rKTeol6oGXoB5saqY6NLHp3zEzMxsaDtKYmZkNk4h4lMw7UfOZFkX/DPwM+ByZU2IJMm/cImReln2AOyV9u8Xx55AzzgDs1aleZfjQ1mX1hoi4p7LvDWWox7VkbotVgQXJ/BRLk0MoPkneTP5np2u1UM2R8qY+z9G3Eqi5HfgssCI5S9ASwAeB86gP7Wh3jj2AicBRZH6SZckZjhYg37NdyJ/LoS2Of5Okq4FfAXuQN9ELkTfUK5Ztv5V0ijK57SD6aHm8bAZ6iE2pPJ9/BuvT67lqQaapwG+G8ZpbVp7/usP5qvletuqrRnWd6rYmmeMGcmarZjlwam4ih20CbKic1cvMzIaBEwebmZkNr/PIHBIAG0iaOyJebigzP5kE9DfAHcAjZALP5cipf3ckgyT/JemJiDi2enBETJF0Hhl0WF3ShhFxY5s6fYZ6oOTHDfv2A2rDPp4lAw13kFMdL0D2PFifnJa4X9XZZvaQdGzpeTQzbEX2HpgE/JB8bUEmfP40+T7vIen6iDit2QkkHUTOSlVzI5n0+CHyfR1NJqQdQ5MZiSQtAfyOTBILGaS7iEyG+xp58zyWTIr77+TntbF9vdphImkN6r0z2s0c1claleczOsVzr+eqBWmuKr1Yhuua1TJ/6HC+O8mpr+cC1pCkbnrONJI0D/WcWK3q1nW9IuK1MmRrE/JL3tWBW3qtl5mZdeYgjZmZ2fC6C3ie7I2yANkz5v8ayowlbxRfaXYCSV8hv2F/O3CEpFMjYkpDsZPIIA1kb5qmQZoyxKHWo2cS0w/XqB1b27d+q+SrJefOis32deGnZOLTucs5bpd0HHBpRPy1z3N2ayfyRnjLiHiisv1cSVeQPZoADgZeF6SR9H6y9wzAi8DYiLigsRzwrZLA9S1N9p1KPUDzNeDbjT1RJB1Fvk9bkEGj8wdsVp1agGMacGU/J5C0KNMPnbms38pIGkU96W7Hc5WEueuW1RkJMn228rzVNVetPJ/Y7mQR8YqkR8i8NAuSgdq/91GvHckZ0gBubzG7U9f1KqqBnlVxkMbMbFh4uJOZmdkwiohXmf4m63XDeyLiilYBmrL/IXIoFORUuB9rUuYOcnpigB3KDXAzm5NTIAOc06QHQa13xHXtZseJiMkRcWer/e1ExESmHyq1EpnzYoKkxyVdJukwSZuXHgFD6WVg+4YATa1eP6ce3Fpd0vJNjj+cei+k/VsEaGrneyQibq5uk/Ru4ONl9bSI+GazoUIR8RywMxksg/osSIOiFqS5ptS1H0dRn076soj4U7vCHRxMPdfRn+gc8Pko2cspyF5QPVN91izIgN2xLYouVnn+ZBenfqrFsd3Wa3HgfyqbjhyEepmZWXccpDEzMxt+1SSkS/Z5jmpi1vVblKlNY70AsGuLMtWcNSc32V+bAWaV4cyFEhHfI3PbTGjYtRTwYeAb5PCvxyQd1Sbo1KtLI+LBNvuvqTxfo7pD0puAD5XVCeSUyb3avfL8mJal+Ffy2lqS2Y0lzdvH9YacpKWot8G+eqEop5Leu6xOBvafgfqMAf67rL4C7N1FjpxakOmWiHi8j2suA1xI/bP019rkdFmo8rybqaurgdOecr8op0U/n8yRBBn8GjfS9TIzs+55uJOZmdnwq34p0moGoqXIRL1bkMGBxclgSzPNhtBA3px9D1iUDMac2HCNN1LvhXNLRPyxyTl+Qw6VWB24StIxzFjOjpYi4meSLiET725LTle+FtMnFl6czOmzg6St2vXu6dLvO+x/pOHaVdXZli7tM1nuRuXxJWA1Sat1KD9v5XFFcir3kbYN2ab76oUiaSPquZAC2KtD4Kzdud5ODtmrfab9ckT8rsMxC5BtDvoIMklaELiEetLdy4Dvdnl4z/llenQc+TcE4GG6z2U03PUyM7MuOUhjZmY2/KpDA55u3ClpJ+BHZHClG4s02xgRL0g6G/g8sI6kd0fE7ZUie5AzEMHrEwbXHEoGI95MJtPdGJgm6TZyKNA15BCXxuTHfSnDwa4sC5LmB9YhE5TuSj256duASyS9Ywav3WlYx7TK88bps6vBsX6DJaPL4zzAz3s8tjFoNFJqvVD+EBGPtC3ZQNK6wKXU39svRsSF/VRC0tvIoGKtd9qxEXF0F4duUbn+JT1ecz4ysLNe2XQjsFOH5L7V4WDdzDpVLdOYe6pd3b4F7FtWHwc+FBHt2vtMqZeZmfXGw53MzMyGURl+UL25/2fD/o3JGaBqAZrbyXwSe5M5SbarLDXVniaNflR53jgdd23WpufIXjevU/LFrAP8gJzdCbIXx4Zkj5YrgL9LOqAkIR5SETE1Im6KiCOBd1CfGQsy58hOzY/sWr9TRcP0wbF+87DMyLCtoc7P07MSpKgN+eqpF4qkd5BTUNfex/+KiOP6rMfyZMCw9rt1UkR8scvDa73JJkTE3T1ccx4ysfQHy6ZbgA9HxPMdDn228ryb4Y7VMs+2LDV93b4KfLmsPgls3kWvs2Gvl5mZ9c5BGjMzs+G1NvVhS8+T0y1XHUb9//FnI+I9EXFoRJwcERdExMURcTHZY6CjiLiLevLbXcvQjtoQk1pi1Z+0S/YaEU9ExH5kfpgNyKSsF5O5Qyjbv8/0AaEhF+lo8sa+ZrNW5WeC6jThC7Us1V7tfZ8YEepxGT9j1R8SH6LenrsO0khaE7iKeqLgb0TEd/qpgKQ3kwGa0WXTadQTa3c69g3AR8pqL/WfmxxWtXXZdAewVZdTx1eDJaM7XGcU9WFUzzP98LtWxxxCPSfPM2QPmruGsl7FCi2ONTOzIeQgjZmZ2fCqJvC9qTpUp3wzX8tRcltEtBqCBNPfIHVSSyC8CJlfBuq9aKB5wuDXiYiXI+J3EfHdiNiOnJnqM9SHBO0lae0e6tWvqyvP3zwTrtdKdZau1fs8R+2me/kyjfmspjbU6aGIaJxKvqmSN+Zq6jObHRkRR/Rz8ZKw9xrqs5CdS+a06Tanyvsr9egqSFMCJz+h/tr/RAZCnml91HSqAZN1W5ZK76LeU+7PnV6XpC9SnxJ+Mjm1fLezrnVdrxLcWqesvsZg5EYyM5stOUhjZmY2TCQty/RDjk5tKLIk9fxwnRKnbtnDpcdRny53rzIz0g5l/c6IuK2Hc/1LRLwUEacDJ1Q2b9jPuXr0UuV5v8OMhsIN1BOsblNuXHt1XXmci5wGepZRhrdtU1a7ShgsaWUyqLJ02XRMRHy5zSHtzvUmMthTS7Z8AbBHjwmca4GWZ4DfdnHNuYCzyZnIIHvCbR4RT7U+6nWqPcE6/R5vVXl+RYe67UsmCofMEbNVRNzaQ73uph54XFNSq4TkkD3qakHFGyPCOWnMzIaJgzRmZmbDQNLC5BS9taTB95DDJapeqDxfqcO5us23QUS8CJxZVjcAvk096We73jrdmlh53vMkBGUmq15UgxmNw8Vmmoj4JyXBMTnT0p5tirdyVuX518tMQbOK9YBlyvOOvVBKYt9rqE8HfXxEfKmfC0taghwuVZsW/WfAbiXxdC9qQZpfRcQrHa75BnIo1c5l033AZhHxRC8XjIj7yeFRkFPbb92sXMn3Uw3qtkyoLGkv6sHS58ncOG1ntWpSr6D+N0nAfm2Kf6Hy/IJermNmZr1xkMbMzGwIKW0N3EZ9yubJwA6N3/hHxCTg/rK6rqRqcuDa+RYib6SW77Eq1XwxtXwdL5DDQ1rVfVlJx5Sb61ZlFiBniarpashLgwMl3SJpp3Jj2upao8qMNbU8NK+Sw05G0mGlHgDHSdqxVcHyfq5X3RYRNwM/LaurAr+UtPTrDq6fY5Skj0vqKufKMKsFOCYD49sVLL0yrqHebv83Ivbv56KlJ9iVZCJpyADRzp2CLE3OszL1vExtg0yl19CPgE+VTQ8AYyLisV6uWXF45fmJkt7acL03AD8EatvHtcorI2l3ckijyN/pbSLihj7rdTT1YPGBkl6X80nSWOo98f7G63sEmpnZEPIU3GZmZj2S9PHqKrAwmRD1XeSU1dUgx9+BXdrMInMCcHx5Pk7SueSwmink9NNjyTwsZ1G/YewoIu6TdC0wprL5whIYamVe4CDgIEm3ksNB7iFnclmUHGayK/XEpr8tde3He8kZpiZLug64mXyvniOHVawJfILp38vvRMSI9aQBiIjfSzoUOIacxvkCSV8gb/ofJr8AW4HMNbQ52YvplobTfIYM0KxN/nwmSBoH/I6cmWc+svfJu8npopdgBm+MJR1E6ym8F5P0zYZtf42IxmvWgjRXtJsGvQQWq4l97wauavi9aebJFsGGXwHvKc//QQYaP9JhcrEXIuLKhm21WZ1eLuds51vUe0q9TP6OrtfFhGZXRsQLjRsj4hJJF5Czk60A/EHSj8i8MEuSv9u1gN6jwIHNTl4CwKdT/6L1NPLn1+m9vT0iHm5Sr0dL2ziRvC/4laSzyGF5o8hEyduX4q+Qyc1f7HAtMzObERHhxYsXL168eOmwkLlIelmeAY4DFutwXgHndDjXxeRwpdr6+C7rvGPDeTboUH6FHl7fNcCSfb6Xe5LBmG6v9RxwcJvzja+VbbF/bOVcYzvUrauy5TVM6aLuX29x/MJkkKrb9+CIGWy/E3tsv+Mbjh9d2fdvHa41usdrtW3XfZ5rYpPzXFf2/aaL92t8n9cd3eac85I9wdod/wDwzjbnOKzPenVq9weTuZ9aHT+Z7L3Udxv04sWLFy/dLe5JY2ZmNmNeJm9gJpM3wreTvUIujYipnQ6OiAB2k3QZmY9iHXKK4yeAO4GzI+JCgC6+xW90VeX5nyPipg51eagMw9iM7OGxDjn8YiFyRqdHyGFc50XEpb1WpnKdUySdA3wQ2ITsMbIKOevOvOTwi3+SvQyuBs6PHvOADLfyGi4B9iaTva5K9lSZRg4JuY3sXXNJi+OnADtLOorsRbEJ+V4vCrxI9qa4G7geuCQiJgzrC+qs1gvlFeDykaxIP0pOm1qS666n3h5KETEN2EXSmWRvqveR09lPIYc9XgScHBHPj0DdjpF0BbAPOc36cuQsTg8Dl5HD1R6a2fUyM5sTKT8bmpmZ2exG0p7UEwV/MSKOHcn62KxL0tVkUG18RIzpVH7QlDwutaTNox1wMDOzQeXEwWZmZrOvfcrjVKafVcisayVx70ZldUR6oQyBWj6dPzpAY2Zmg8xBGjMzs9mQpG2pJ1s9NyKeHsn62Cztw8Dc5fksF6SRNA+wZVmd5epvZmZzFg93MjMzmw1Imp/MazIKeCfwJTK/yUvA6gOQ08TMzMzMOnDiYDMzs9nD0jSfVvg/HaAxMzMzmzU4SGNmZjb7eRa4BzgmIn420pUxMzMzs+54uJOZmZmZmZmZ2QBw4mAzMzMzMzMzswHgII2ZmZmZmZmZ2QBwkMbMzMzMzMzMbAA4SGNmZmZmZmZmNgAcpDEzMzMzMzMzGwAO0piZmZmZmZmZDYD/B8C7yfHZFcXrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "country_plot(adjusted_dates, india_cases, india_daily_increase, india_daily_death, india_daily_recovery, 'India')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_predictions(x, y, pred, algo_name, color):\n",
    "    plt.figure(figsize=(16, 9))\n",
    "    plt.plot(x, y)\n",
    "    plt.plot(future_forcast, pred, linestyle='dashed', color=color)\n",
    "    plt.title('# of Coronavirus Cases Over Time', size=30)\n",
    "    plt.xlabel('Days Since 1/22/2020', size=30)\n",
    "    plt.ylabel('# of Cases', size=30)\n",
    "    plt.legend(['Confirmed Cases', algo_name], prop={'size': 20})\n",
    "    plt.xticks(size=20)\n",
    "    plt.yticks(size=20)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_predictions(adjusted_dates, world_cases, svm_pred, 'SVM Predictions', 'purple')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_predictions(adjusted_dates, world_cases, linear_pred, 'Polynomial Regression Predictions', 'black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_predictions(adjusted_dates, world_cases, bayesian_pred, 'Bayesian Ridge Regression Predictions', 'green')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>Date</th>\n",
       "      <th>SVM Predicted # of Confirmed Cases Worldwide</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>05/30/2020</td>\n",
       "      <td>6312835.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>05/31/2020</td>\n",
       "      <td>6509940.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>06/01/2020</td>\n",
       "      <td>6711646.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>06/02/2020</td>\n",
       "      <td>6918025.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>06/03/2020</td>\n",
       "      <td>7129147.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>06/04/2020</td>\n",
       "      <td>7345087.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>06/05/2020</td>\n",
       "      <td>7565915.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>06/06/2020</td>\n",
       "      <td>7791705.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>06/07/2020</td>\n",
       "      <td>8022531.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>06/08/2020</td>\n",
       "      <td>8258468.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  SVM Predicted # of Confirmed Cases Worldwide\n",
       "0  05/30/2020                                     6312835.0\n",
       "1  05/31/2020                                     6509940.0\n",
       "2  06/01/2020                                     6711646.0\n",
       "3  06/02/2020                                     6918025.0\n",
       "4  06/03/2020                                     7129147.0\n",
       "5  06/04/2020                                     7345087.0\n",
       "6  06/05/2020                                     7565915.0\n",
       "7  06/06/2020                                     7791705.0\n",
       "8  06/07/2020                                     8022531.0\n",
       "9  06/08/2020                                     8258468.0"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Future predictions using SVM \n",
    "svm_df = pd.DataFrame({'Date': future_forcast_dates[-10:], 'SVM Predicted # of Confirmed Cases Worldwide': np.round(svm_pred[-10:])})\n",
    "svm_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>Date</th>\n",
       "      <th>Bayesian Ridge Predicted # of Confirmed Cases Worldwide</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>05/30/2020</td>\n",
       "      <td>7851984.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>05/31/2020</td>\n",
       "      <td>8098323.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>06/01/2020</td>\n",
       "      <td>8350412.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>06/02/2020</td>\n",
       "      <td>8608341.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>06/03/2020</td>\n",
       "      <td>8872200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>06/04/2020</td>\n",
       "      <td>9142079.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>06/05/2020</td>\n",
       "      <td>9418069.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>06/06/2020</td>\n",
       "      <td>9700260.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>06/07/2020</td>\n",
       "      <td>9988747.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>06/08/2020</td>\n",
       "      <td>10283620.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Bayesian Ridge Predicted # of Confirmed Cases Worldwide\n",
       "0  05/30/2020                                          7851984.0      \n",
       "1  05/31/2020                                          8098323.0      \n",
       "2  06/01/2020                                          8350412.0      \n",
       "3  06/02/2020                                          8608341.0      \n",
       "4  06/03/2020                                          8872200.0      \n",
       "5  06/04/2020                                          9142079.0      \n",
       "6  06/05/2020                                          9418069.0      \n",
       "7  06/06/2020                                          9700260.0      \n",
       "8  06/07/2020                                          9988747.0      \n",
       "9  06/08/2020                                         10283620.0      "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Future predictions using Bayesian Ridge \n",
    "svm_df = pd.DataFrame({'Date': future_forcast_dates[-10:], 'Bayesian Ridge Predicted # of Confirmed Cases Worldwide': np.round(bayesian_pred[-10:])})\n",
    "svm_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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