4. Identifying Fraudulent Activities.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7b7ed26d",
   "metadata": {},
   "source": [
    "## Goal of Analysis:\n",
    "\n",
    "### 1. determine each user's country based on the numeric IP address\n",
    "\n",
    "### 2. Build a model to predict whether an activity is fraudulent or not\n",
    "\n",
    "### 3. explain the model from a business or product side of view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "456110ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "127d8152",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>signup_time</th>\n",
       "      <th>purchase_time</th>\n",
       "      <th>purchase_value</th>\n",
       "      <th>device_id</th>\n",
       "      <th>source</th>\n",
       "      <th>browser</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>ip_address</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22058</td>\n",
       "      <td>2015-02-24 22:55:49</td>\n",
       "      <td>2015-04-18 02:47:11</td>\n",
       "      <td>34</td>\n",
       "      <td>QVPSPJUOCKZAR</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>M</td>\n",
       "      <td>39</td>\n",
       "      <td>7.327584e+08</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>333320</td>\n",
       "      <td>2015-06-07 20:39:50</td>\n",
       "      <td>2015-06-08 01:38:54</td>\n",
       "      <td>16</td>\n",
       "      <td>EOGFQPIZPYXFZ</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>F</td>\n",
       "      <td>53</td>\n",
       "      <td>3.503114e+08</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1359</td>\n",
       "      <td>2015-01-01 18:52:44</td>\n",
       "      <td>2015-01-01 18:52:45</td>\n",
       "      <td>15</td>\n",
       "      <td>YSSKYOSJHPPLJ</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Opera</td>\n",
       "      <td>M</td>\n",
       "      <td>53</td>\n",
       "      <td>2.621474e+09</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>150084</td>\n",
       "      <td>2015-04-28 21:13:25</td>\n",
       "      <td>2015-05-04 13:54:50</td>\n",
       "      <td>44</td>\n",
       "      <td>ATGTXKYKUDUQN</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Safari</td>\n",
       "      <td>M</td>\n",
       "      <td>41</td>\n",
       "      <td>3.840542e+09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>221365</td>\n",
       "      <td>2015-07-21 07:09:52</td>\n",
       "      <td>2015-09-09 18:40:53</td>\n",
       "      <td>39</td>\n",
       "      <td>NAUITBZFJKHWW</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Safari</td>\n",
       "      <td>M</td>\n",
       "      <td>45</td>\n",
       "      <td>4.155831e+08</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id         signup_time       purchase_time  purchase_value  \\\n",
       "0    22058 2015-02-24 22:55:49 2015-04-18 02:47:11              34   \n",
       "1   333320 2015-06-07 20:39:50 2015-06-08 01:38:54              16   \n",
       "2     1359 2015-01-01 18:52:44 2015-01-01 18:52:45              15   \n",
       "3   150084 2015-04-28 21:13:25 2015-05-04 13:54:50              44   \n",
       "4   221365 2015-07-21 07:09:52 2015-09-09 18:40:53              39   \n",
       "\n",
       "       device_id source browser sex  age    ip_address  class  \n",
       "0  QVPSPJUOCKZAR    SEO  Chrome   M   39  7.327584e+08      0  \n",
       "1  EOGFQPIZPYXFZ    Ads  Chrome   F   53  3.503114e+08      0  \n",
       "2  YSSKYOSJHPPLJ    SEO   Opera   M   53  2.621474e+09      1  \n",
       "3  ATGTXKYKUDUQN    SEO  Safari   M   41  3.840542e+09      0  \n",
       "4  NAUITBZFJKHWW    Ads  Safari   M   45  4.155831e+08      0  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user = pd.read_csv('Fraud_Data.csv', parse_dates=['signup_time', 'purchase_time'])\n",
    "user.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2db1257d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id                    int64\n",
       "signup_time       datetime64[ns]\n",
       "purchase_time     datetime64[ns]\n",
       "purchase_value             int64\n",
       "device_id                 object\n",
       "source                    object\n",
       "browser                   object\n",
       "sex                       object\n",
       "age                        int64\n",
       "ip_address               float64\n",
       "class                      int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "841cd837",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable     Count of unique value    content\n",
      "user_id              151112\t [ 22058 333320   1359]\n",
      "signup_time          151112\t ['2015-02-24T22:55:49.000000000' '2015-06-07T20:39:50.000000000'\n",
      " '2015-01-01T18:52:44.000000000']\n",
      "purchase_time        150679\t ['2015-04-18T02:47:11.000000000' '2015-06-08T01:38:54.000000000'\n",
      " '2015-01-01T18:52:45.000000000']\n",
      "purchase_value        122\t [34 16 15]\n",
      "device_id            137956\t ['QVPSPJUOCKZAR' 'EOGFQPIZPYXFZ' 'YSSKYOSJHPPLJ']\n",
      "source                  3\t ['SEO' 'Ads' 'Direct']\n",
      "browser                 5\t ['Chrome' 'Opera' 'Safari']\n",
      "sex                     2\t ['M' 'F']\n",
      "age                    58\t [39 53 41]\n",
      "ip_address           143512\t [7.32758369e+08 3.50311388e+08 2.62147382e+09]\n",
      "class                   2\t [0 1]\n"
     ]
    }
   ],
   "source": [
    "print('Variable', '   ', 'Count of unique value','  ', 'content')\n",
    "for column in user.columns:\n",
    "    uniques = user[column].unique()\n",
    "    print('{0:20s} {1:4d}\\t'.format(column, len(uniques)), uniques[:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8d7f7746",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lower_bound_ip_address</th>\n",
       "      <th>upper_bound_ip_address</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16777216.0</td>\n",
       "      <td>16777471</td>\n",
       "      <td>Australia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16777472.0</td>\n",
       "      <td>16777727</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>16777728.0</td>\n",
       "      <td>16778239</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16778240.0</td>\n",
       "      <td>16779263</td>\n",
       "      <td>Australia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16779264.0</td>\n",
       "      <td>16781311</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   lower_bound_ip_address  upper_bound_ip_address    country\n",
       "0              16777216.0                16777471  Australia\n",
       "1              16777472.0                16777727      China\n",
       "2              16777728.0                16778239      China\n",
       "3              16778240.0                16779263  Australia\n",
       "4              16779264.0                16781311      China"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country = pd.read_csv('IpAddress_to_Country.csv')\n",
    "country.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f232a4bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "lower_bound_ip_address    float64\n",
       "upper_bound_ip_address      int64\n",
       "country                    object\n",
       "dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d71b6b74",
   "metadata": {},
   "source": [
    "### Part 1: determine the country for each user"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3bfc9441",
   "metadata": {},
   "outputs": [],
   "source": [
    "countries = []\n",
    "for i in range(len(user)):\n",
    "    ip_address = user.loc[i, 'ip_address']\n",
    "    tmp = country[(country['lower_bound_ip_address'] <= ip_address) &\n",
    "                  (country['upper_bound_ip_address'] >= ip_address)]\n",
    "    if len(tmp) == 1:\n",
    "        countries.append(tmp['country'].values[0])\n",
    "    else:\n",
    "        countries.append('NA')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "d622dd8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>signup_time</th>\n",
       "      <th>purchase_time</th>\n",
       "      <th>purchase_value</th>\n",
       "      <th>device_id</th>\n",
       "      <th>source</th>\n",
       "      <th>browser</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>ip_address</th>\n",
       "      <th>class</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22058</td>\n",
       "      <td>2015-02-24 22:55:49</td>\n",
       "      <td>2015-04-18 02:47:11</td>\n",
       "      <td>34</td>\n",
       "      <td>QVPSPJUOCKZAR</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>M</td>\n",
       "      <td>39</td>\n",
       "      <td>7.327584e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>333320</td>\n",
       "      <td>2015-06-07 20:39:50</td>\n",
       "      <td>2015-06-08 01:38:54</td>\n",
       "      <td>16</td>\n",
       "      <td>EOGFQPIZPYXFZ</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>F</td>\n",
       "      <td>53</td>\n",
       "      <td>3.503114e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1359</td>\n",
       "      <td>2015-01-01 18:52:44</td>\n",
       "      <td>2015-01-01 18:52:45</td>\n",
       "      <td>15</td>\n",
       "      <td>YSSKYOSJHPPLJ</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Opera</td>\n",
       "      <td>M</td>\n",
       "      <td>53</td>\n",
       "      <td>2.621474e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>150084</td>\n",
       "      <td>2015-04-28 21:13:25</td>\n",
       "      <td>2015-05-04 13:54:50</td>\n",
       "      <td>44</td>\n",
       "      <td>ATGTXKYKUDUQN</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Safari</td>\n",
       "      <td>M</td>\n",
       "      <td>41</td>\n",
       "      <td>3.840542e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>NA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>221365</td>\n",
       "      <td>2015-07-21 07:09:52</td>\n",
       "      <td>2015-09-09 18:40:53</td>\n",
       "      <td>39</td>\n",
       "      <td>NAUITBZFJKHWW</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Safari</td>\n",
       "      <td>M</td>\n",
       "      <td>45</td>\n",
       "      <td>4.155831e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id         signup_time       purchase_time  purchase_value  \\\n",
       "0    22058 2015-02-24 22:55:49 2015-04-18 02:47:11              34   \n",
       "1   333320 2015-06-07 20:39:50 2015-06-08 01:38:54              16   \n",
       "2     1359 2015-01-01 18:52:44 2015-01-01 18:52:45              15   \n",
       "3   150084 2015-04-28 21:13:25 2015-05-04 13:54:50              44   \n",
       "4   221365 2015-07-21 07:09:52 2015-09-09 18:40:53              39   \n",
       "\n",
       "       device_id source browser sex  age    ip_address  class        country  \n",
       "0  QVPSPJUOCKZAR    SEO  Chrome   M   39  7.327584e+08      0          Japan  \n",
       "1  EOGFQPIZPYXFZ    Ads  Chrome   F   53  3.503114e+08      0  United States  \n",
       "2  YSSKYOSJHPPLJ    SEO   Opera   M   53  2.621474e+09      1  United States  \n",
       "3  ATGTXKYKUDUQN    SEO  Safari   M   41  3.840542e+09      0             NA  \n",
       "4  NAUITBZFJKHWW    Ads  Safari   M   45  4.155831e+08      0  United States  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user['country'] = countries\n",
    "user.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e348ea44",
   "metadata": {},
   "source": [
    "### Part 2: Fraudulent activity detection"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c6fba3f",
   "metadata": {},
   "source": [
    "1. time difference between signup time and purchase time (too short period may indicate fraudulent activity)\n",
    "\n",
    "2. whether there are many user id associated with one device id (could be fraud accounts)\n",
    "\n",
    "3. whether there are many user id associated with one IP address\n",
    "\n",
    "4. purchase week of the year, day of the week of the time variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "658274fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# time difference between signup time and purchase time\n",
    "time_diff = user['purchase_time'] - user['signup_time']\n",
    "time_diff = time_diff.apply(lambda x: x.seconds)\n",
    "user['time_diff'] = time_diff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5e5d910b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check user number for unique devices\n",
    "device_num = user[['user_id', 'device_id']].groupby('device_id').count().reset_index()\n",
    "device_num = device_num.rename(columns={'user_id': 'device_num'})\n",
    "user = user.merge(device_num, how='left', on='device_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "bcaac02d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check user number for unique ip_address\n",
    "ip_num = user[['user_id', 'ip_address']].groupby('ip_address').count().reset_index()\n",
    "ip_num = ip_num.rename(columns={'user_id': 'ip_num'})\n",
    "user = user.merge(ip_num, how='left', on='ip_address')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "3806d00e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Signup day and week\n",
    "user['signup_day'] = user['signup_time'].apply(lambda x: x.dayofweek)\n",
    "user['signup_week'] = user['signup_time'].apply(lambda x: x.week)\n",
    "\n",
    "# Purchase day and week\n",
    "user['purchase_day'] = user['purchase_time'].apply(lambda x: x.dayofweek)\n",
    "user['purchase_week'] = user['purchase_time'].apply(lambda x: x.week)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "52e96d07",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>signup_time</th>\n",
       "      <th>purchase_time</th>\n",
       "      <th>purchase_value</th>\n",
       "      <th>device_id</th>\n",
       "      <th>source</th>\n",
       "      <th>browser</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>ip_address</th>\n",
       "      <th>class</th>\n",
       "      <th>country</th>\n",
       "      <th>time_diff</th>\n",
       "      <th>device_num</th>\n",
       "      <th>ip_num</th>\n",
       "      <th>signup_day</th>\n",
       "      <th>signup_week</th>\n",
       "      <th>purchase_day</th>\n",
       "      <th>purchase_week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22058</td>\n",
       "      <td>2015-02-24 22:55:49</td>\n",
       "      <td>2015-04-18 02:47:11</td>\n",
       "      <td>34</td>\n",
       "      <td>QVPSPJUOCKZAR</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>M</td>\n",
       "      <td>39</td>\n",
       "      <td>7.327584e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>Japan</td>\n",
       "      <td>13882</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>333320</td>\n",
       "      <td>2015-06-07 20:39:50</td>\n",
       "      <td>2015-06-08 01:38:54</td>\n",
       "      <td>16</td>\n",
       "      <td>EOGFQPIZPYXFZ</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>F</td>\n",
       "      <td>53</td>\n",
       "      <td>3.503114e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
       "      <td>17944</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1359</td>\n",
       "      <td>2015-01-01 18:52:44</td>\n",
       "      <td>2015-01-01 18:52:45</td>\n",
       "      <td>15</td>\n",
       "      <td>YSSKYOSJHPPLJ</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Opera</td>\n",
       "      <td>M</td>\n",
       "      <td>53</td>\n",
       "      <td>2.621474e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>United States</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>150084</td>\n",
       "      <td>2015-04-28 21:13:25</td>\n",
       "      <td>2015-05-04 13:54:50</td>\n",
       "      <td>44</td>\n",
       "      <td>ATGTXKYKUDUQN</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Safari</td>\n",
       "      <td>M</td>\n",
       "      <td>41</td>\n",
       "      <td>3.840542e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>NA</td>\n",
       "      <td>60085</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>221365</td>\n",
       "      <td>2015-07-21 07:09:52</td>\n",
       "      <td>2015-09-09 18:40:53</td>\n",
       "      <td>39</td>\n",
       "      <td>NAUITBZFJKHWW</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Safari</td>\n",
       "      <td>M</td>\n",
       "      <td>45</td>\n",
       "      <td>4.155831e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
       "      <td>41461</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id         signup_time       purchase_time  purchase_value  \\\n",
       "0    22058 2015-02-24 22:55:49 2015-04-18 02:47:11              34   \n",
       "1   333320 2015-06-07 20:39:50 2015-06-08 01:38:54              16   \n",
       "2     1359 2015-01-01 18:52:44 2015-01-01 18:52:45              15   \n",
       "3   150084 2015-04-28 21:13:25 2015-05-04 13:54:50              44   \n",
       "4   221365 2015-07-21 07:09:52 2015-09-09 18:40:53              39   \n",
       "\n",
       "       device_id source browser sex  age    ip_address  class        country  \\\n",
       "0  QVPSPJUOCKZAR    SEO  Chrome   M   39  7.327584e+08      0          Japan   \n",
       "1  EOGFQPIZPYXFZ    Ads  Chrome   F   53  3.503114e+08      0  United States   \n",
       "2  YSSKYOSJHPPLJ    SEO   Opera   M   53  2.621474e+09      1  United States   \n",
       "3  ATGTXKYKUDUQN    SEO  Safari   M   41  3.840542e+09      0             NA   \n",
       "4  NAUITBZFJKHWW    Ads  Safari   M   45  4.155831e+08      0  United States   \n",
       "\n",
       "   time_diff  device_num  ip_num  signup_day  signup_week  purchase_day  \\\n",
       "0      13882           1       1           1            9             5   \n",
       "1      17944           1       1           6           23             0   \n",
       "2          1          12      12           3            1             3   \n",
       "3      60085           1       1           1           18             0   \n",
       "4      41461           1       1           1           30             2   \n",
       "\n",
       "   purchase_week  \n",
       "0             16  \n",
       "1             24  \n",
       "2              1  \n",
       "3             19  \n",
       "4             37  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "b641e715",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "   signup_day  signup_week  purchase_day  purchase_week  purchase_value  \\\n",
       "0           1            9             5             16              34   \n",
       "1           6           23             0             24              16   \n",
       "2           3            1             3              1              15   \n",
       "3           1           18             0             19              44   \n",
       "4           1           30             2             37              39   \n",
       "\n",
       "  source browser sex  age        country  time_diff  device_num  ip_num  class  \n",
       "0    SEO  Chrome   M   39          Japan      13882           1       1      0  \n",
       "1    Ads  Chrome   F   53  United States      17944           1       1      0  \n",
       "2    SEO   Opera   M   53  United States          1          12      12      1  \n",
       "3    SEO  Safari   M   41             NA      60085           1       1      0  \n",
       "4    Ads  Safari   M   45  United States      41461           1       1      0  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define features and target to be used\n",
    "columns = ['signup_day', 'signup_week', 'purchase_day', 'purchase_week', 'purchase_value', 'source', \n",
    "           'browser', 'sex', 'age', 'country', 'time_diff', 'device_num', 'ip_num', 'class']\n",
    "data = user[columns]\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e33944b",
   "metadata": {},
   "source": [
    "we can see that for row 2, the class is 1, which means a fraudulent account, the device_number, ip_number, and signup time are all so different from others"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "665bb071",
   "metadata": {},
   "source": [
    "#### next, I will use label encoder to tranform the data and make it easier for analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "7b53edd4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# Label encoder\n",
    "le = LabelEncoder()\n",
    "data_new = data[['signup_day', 'signup_week', 'purchase_day', 'purchase_week', 'purchase_value', 'age', \n",
    "                 'time_diff', 'device_num', 'ip_num']]\n",
    "data_new['source'] = le.fit_transform(data['source'])\n",
    "data_new['browser'] = le.fit_transform(data['browser'])\n",
    "data_new['sex'] = le.fit_transform(data['sex'])\n",
    "data_new['country'] = le.fit_transform(data['country'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b0136c02",
   "metadata": {},
   "outputs": [
    {
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       "      <td>46</td>\n",
       "      <td>37</td>\n",
       "      <td>48519</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151111</th>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>20</td>\n",
       "      <td>38</td>\n",
       "      <td>68493</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151112 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        signup_day  signup_week  purchase_day  purchase_week  purchase_value  \\\n",
       "0                1            9             5             16              34   \n",
       "1                6           23             0             24              16   \n",
       "2                3            1             3              1              15   \n",
       "3                1           18             0             19              44   \n",
       "4                1           30             2             37              39   \n",
       "...            ...          ...           ...            ...             ...   \n",
       "151107           1            5             6             13              43   \n",
       "151108           4           20             1             22              35   \n",
       "151109           1           10             2             21              40   \n",
       "151110           3           28             0             37              46   \n",
       "151111           2           24             1             30              20   \n",
       "\n",
       "        age  time_diff  device_num  ip_num  source  browser  sex  country  \n",
       "0        39      13882           1       1       2        0    1       84  \n",
       "1        53      17944           1       1       0        0    0      172  \n",
       "2        53          1          12      12       2        3    1      172  \n",
       "3        41      60085           1       1       2        4    1      115  \n",
       "4        45      41461           1       1       0        4    1      172  \n",
       "...     ...        ...         ...     ...     ...      ...  ...      ...  \n",
       "151107   28      77233           2       1       2        0    1      172  \n",
       "151108   32      67270           1       1       2        4    1      119  \n",
       "151109   26      28816           1       1       2        2    0       84  \n",
       "151110   37      48519           2       1       2        0    1      172  \n",
       "151111   38      68493           1       1       1        2    1      115  \n",
       "\n",
       "[151112 rows x 13 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "8d4a7826",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>signup_day</th>\n",
       "      <th>signup_week</th>\n",
       "      <th>purchase_day</th>\n",
       "      <th>purchase_week</th>\n",
       "      <th>purchase_value</th>\n",
       "      <th>source</th>\n",
       "      <th>browser</th>\n",
       "      <th>sex</th>\n",
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       "      <th>country</th>\n",
       "      <th>time_diff</th>\n",
       "      <th>device_num</th>\n",
       "      <th>ip_num</th>\n",
       "      <th>is_fraud</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "      <td>34</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Chrome</td>\n",
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       "      <td>16</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>F</td>\n",
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       "      <td>United States</td>\n",
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       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Opera</td>\n",
       "      <td>M</td>\n",
       "      <td>53</td>\n",
       "      <td>United States</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>44</td>\n",
       "      <td>SEO</td>\n",
       "      <td>Safari</td>\n",
       "      <td>M</td>\n",
       "      <td>41</td>\n",
       "      <td>NA</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>39</td>\n",
       "      <td>Ads</td>\n",
       "      <td>Safari</td>\n",
       "      <td>M</td>\n",
       "      <td>45</td>\n",
       "      <td>United States</td>\n",
       "      <td>41461</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   signup_day  signup_week  purchase_day  purchase_week  purchase_value  \\\n",
       "0           1            9             5             16              34   \n",
       "1           6           23             0             24              16   \n",
       "2           3            1             3              1              15   \n",
       "3           1           18             0             19              44   \n",
       "4           1           30             2             37              39   \n",
       "\n",
       "  source browser sex  age        country  time_diff  device_num  ip_num  \\\n",
       "0    SEO  Chrome   M   39          Japan      13882           1       1   \n",
       "1    Ads  Chrome   F   53  United States      17944           1       1   \n",
       "2    SEO   Opera   M   53  United States          1          12      12   \n",
       "3    SEO  Safari   M   41             NA      60085           1       1   \n",
       "4    Ads  Safari   M   45  United States      41461           1       1   \n",
       "\n",
       "   is_fraud  \n",
       "0         0  \n",
       "1         0  \n",
       "2         1  \n",
       "3         0  \n",
       "4         0  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.rename(columns={'class':'is_fraud'},inplace=True)# 'class' is a reserved keyword\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cae04d18",
   "metadata": {},
   "source": [
    "#### Next, I will build a model to detect the fraudulent activities, first I need to divide the dataset into training and testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "bb03e039",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xgboost as xgb\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X = data_new.loc[:,data_new.columns != 'is_fraud']\n",
    "y = data.is_fraud\n",
    "\n",
    "# split into training dataset and test dataset\n",
    "Xtrain,Xtest,ytrain,ytest = train_test_split(X,y,test_size=0.2,random_state=42)\n",
    "train_matrix = xgb.DMatrix(Xtrain,ytrain)\n",
    "test_matrix = xgb.DMatrix(Xtest)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6df006f8",
   "metadata": {},
   "source": [
    "I am going to fit a random forest model, but first I need to find the best number of trees using cross validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "1f02770c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[16:52:39] WARNING: /Users/runner/work/xgboost/xgboost/python-package/build/temp.macosx-10.9-x86_64-3.7/xgboost/src/learner.cc:627: \n",
      "Parameters: { \"early_stopping_rounds\", \"num_rounds\", \"silent\" } might not be used.\n",
      "\n",
      "  This could be a false alarm, with some parameters getting used by language bindings but\n",
      "  then being mistakenly passed down to XGBoost core, or some parameter actually being used\n",
      "  but getting flagged wrongly here. Please open an issue if you find any such cases.\n",
      "\n",
      "\n",
      "[16:52:39] WARNING: /Users/runner/work/xgboost/xgboost/python-package/build/temp.macosx-10.9-x86_64-3.7/xgboost/src/learner.cc:627: \n",
      "Parameters: { \"early_stopping_rounds\", \"num_rounds\", \"silent\" } might not be used.\n",
      "\n",
      "  This could be a false alarm, with some parameters getting used by language bindings but\n",
      "  then being mistakenly passed down to XGBoost core, or some parameter actually being used\n",
      "  but getting flagged wrongly here. Please open an issue if you find any such cases.\n",
      "\n",
      "\n",
      "[16:52:39] WARNING: /Users/runner/work/xgboost/xgboost/python-package/build/temp.macosx-10.9-x86_64-3.7/xgboost/src/learner.cc:627: \n",
      "Parameters: { \"early_stopping_rounds\", \"num_rounds\", \"silent\" } might not be used.\n",
      "\n",
      "  This could be a false alarm, with some parameters getting used by language bindings but\n",
      "  then being mistakenly passed down to XGBoost core, or some parameter actually being used\n",
      "  but getting flagged wrongly here. Please open an issue if you find any such cases.\n",
      "\n",
      "\n",
      "[16:52:39] WARNING: /Users/runner/work/xgboost/xgboost/python-package/build/temp.macosx-10.9-x86_64-3.7/xgboost/src/learner.cc:627: \n",
      "Parameters: { \"early_stopping_rounds\", \"num_rounds\", \"silent\" } might not be used.\n",
      "\n",
      "  This could be a false alarm, with some parameters getting used by language bindings but\n",
      "  then being mistakenly passed down to XGBoost core, or some parameter actually being used\n",
      "  but getting flagged wrongly here. Please open an issue if you find any such cases.\n",
      "\n",
      "\n",
      "[16:52:39] WARNING: /Users/runner/work/xgboost/xgboost/python-package/build/temp.macosx-10.9-x86_64-3.7/xgboost/src/learner.cc:627: \n",
      "Parameters: { \"early_stopping_rounds\", \"num_rounds\", \"silent\" } might not be used.\n",
      "\n",
      "  This could be a false alarm, with some parameters getting used by language bindings but\n",
      "  then being mistakenly passed down to XGBoost core, or some parameter actually being used\n",
      "  but getting flagged wrongly here. Please open an issue if you find any such cases.\n",
      "\n",
      "\n",
      "[0]\ttrain-auc:0.84298+0.00166\ttest-auc:0.84265+0.00662\n",
      "[1]\ttrain-auc:0.84333+0.00188\ttest-auc:0.84269+0.00666\n",
      "[2]\ttrain-auc:0.84339+0.00186\ttest-auc:0.84264+0.00668\n",
      "[3]\ttrain-auc:0.84342+0.00185\ttest-auc:0.84258+0.00667\n",
      "[4]\ttrain-auc:0.84357+0.00183\ttest-auc:0.84269+0.00661\n",
      "[5]\ttrain-auc:0.84386+0.00192\ttest-auc:0.84265+0.00664\n",
      "[6]\ttrain-auc:0.84459+0.00305\ttest-auc:0.84292+0.00629\n",
      "[7]\ttrain-auc:0.84465+0.00299\ttest-auc:0.84293+0.00625\n",
      "[8]\ttrain-auc:0.84728+0.00299\ttest-auc:0.84317+0.00532\n",
      "[9]\ttrain-auc:0.84862+0.00142\ttest-auc:0.84379+0.00656\n",
      "[10]\ttrain-auc:0.84941+0.00148\ttest-auc:0.84380+0.00633\n",
      "[11]\ttrain-auc:0.85045+0.00092\ttest-auc:0.84420+0.00629\n",
      "[12]\ttrain-auc:0.85189+0.00144\ttest-auc:0.84395+0.00617\n",
      "[13]\ttrain-auc:0.85372+0.00206\ttest-auc:0.84359+0.00630\n",
      "[14]\ttrain-auc:0.85505+0.00279\ttest-auc:0.84256+0.00758\n",
      "[15]\ttrain-auc:0.85669+0.00195\ttest-auc:0.84161+0.00781\n",
      "[16]\ttrain-auc:0.85802+0.00135\ttest-auc:0.84181+0.00777\n",
      "[17]\ttrain-auc:0.85895+0.00176\ttest-auc:0.84201+0.00777\n",
      "[18]\ttrain-auc:0.86007+0.00192\ttest-auc:0.84199+0.00757\n",
      "[19]\ttrain-auc:0.86201+0.00243\ttest-auc:0.84215+0.00770\n",
      "[20]\ttrain-auc:0.86387+0.00246\ttest-auc:0.84185+0.00759\n",
      "[21]\ttrain-auc:0.86542+0.00242\ttest-auc:0.84169+0.00781\n",
      "[22]\ttrain-auc:0.86705+0.00223\ttest-auc:0.84107+0.00783\n",
      "[23]\ttrain-auc:0.86828+0.00220\ttest-auc:0.84176+0.00787\n",
      "[24]\ttrain-auc:0.86927+0.00142\ttest-auc:0.84102+0.00772\n",
      "[25]\ttrain-auc:0.87111+0.00137\ttest-auc:0.84117+0.00714\n",
      "[26]\ttrain-auc:0.87250+0.00120\ttest-auc:0.84136+0.00750\n",
      "[27]\ttrain-auc:0.87392+0.00121\ttest-auc:0.84203+0.00741\n",
      "[28]\ttrain-auc:0.87496+0.00149\ttest-auc:0.84251+0.00684\n",
      "[29]\ttrain-auc:0.87629+0.00123\ttest-auc:0.84235+0.00685\n",
      "[30]\ttrain-auc:0.87753+0.00100\ttest-auc:0.84240+0.00678\n",
      "[31]\ttrain-auc:0.87862+0.00114\ttest-auc:0.84225+0.00678\n",
      "[32]\ttrain-auc:0.88013+0.00126\ttest-auc:0.84223+0.00687\n",
      "[33]\ttrain-auc:0.88032+0.00128\ttest-auc:0.84273+0.00651\n",
      "[34]\ttrain-auc:0.88165+0.00134\ttest-auc:0.84341+0.00680\n",
      "[35]\ttrain-auc:0.88272+0.00158\ttest-auc:0.84374+0.00733\n",
      "[36]\ttrain-auc:0.88363+0.00153\ttest-auc:0.84385+0.00730\n",
      "[37]\ttrain-auc:0.88467+0.00144\ttest-auc:0.84375+0.00724\n",
      "[38]\ttrain-auc:0.88532+0.00123\ttest-auc:0.84332+0.00645\n",
      "[39]\ttrain-auc:0.88595+0.00101\ttest-auc:0.84363+0.00649\n",
      "[40]\ttrain-auc:0.88695+0.00117\ttest-auc:0.84364+0.00583\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "params = {}\n",
    "params['silent'] = 1\n",
    "params['objective'] = 'binary:logistic'  # output probabilities\n",
    "params['eval_metric'] = 'auc'\n",
    "params[\"num_rounds\"] = 300\n",
    "params[\"early_stopping_rounds\"] = 30\n",
    "# params['min_child_weight'] = 2\n",
    "params['max_depth'] = 6\n",
    "params['eta'] = 0.1\n",
    "params[\"subsample\"] = 0.8\n",
    "params[\"colsample_bytree\"] = 0.8\n",
    "\n",
    "cv_results = xgb.cv(params,train_matrix,\n",
    "                    num_boost_round = params[\"num_rounds\"],\n",
    "                    nfold = params.get('nfold',5),\n",
    "                    metrics = params['eval_metric'],\n",
    "                    early_stopping_rounds = params[\"early_stopping_rounds\"],\n",
    "                    verbose_eval = True,\n",
    "                    seed = seed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "0022f24c",
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.002991</td>\n",
       "      <td>0.842935</td>\n",
       "      <td>0.006250</td>\n",
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       "      <td>0.843167</td>\n",
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       "      <td>0.001425</td>\n",
       "      <td>0.843793</td>\n",
       "      <td>0.006561</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.849410</td>\n",
       "      <td>0.001476</td>\n",
       "      <td>0.843796</td>\n",
       "      <td>0.006330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.850451</td>\n",
       "      <td>0.000916</td>\n",
       "      <td>0.844197</td>\n",
       "      <td>0.006290</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    train-auc-mean  train-auc-std  test-auc-mean  test-auc-std\n",
       "0         0.842977       0.001660       0.842649      0.006622\n",
       "1         0.843325       0.001879       0.842687      0.006659\n",
       "2         0.843392       0.001862       0.842636      0.006685\n",
       "3         0.843423       0.001847       0.842580      0.006675\n",
       "4         0.843570       0.001831       0.842688      0.006614\n",
       "5         0.843859       0.001923       0.842651      0.006637\n",
       "6         0.844585       0.003047       0.842921      0.006288\n",
       "7         0.844649       0.002991       0.842935      0.006250\n",
       "8         0.847278       0.002990       0.843167      0.005321\n",
       "9         0.848621       0.001425       0.843793      0.006561\n",
       "10        0.849410       0.001476       0.843796      0.006330\n",
       "11        0.850451       0.000916       0.844197      0.006290"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cv_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "935852f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_best_trees = cv_results.shape[0]\n",
    "n_best_trees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "b3cf4e66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[17:00:04] WARNING: /Users/runner/work/xgboost/xgboost/python-package/build/temp.macosx-10.9-x86_64-3.7/xgboost/src/learner.cc:627: \n",
      "Parameters: { \"early_stopping_rounds\", \"num_rounds\", \"silent\" } might not be used.\n",
      "\n",
      "  This could be a false alarm, with some parameters getting used by language bindings but\n",
      "  then being mistakenly passed down to XGBoost core, or some parameter actually being used\n",
      "  but getting flagged wrongly here. Please open an issue if you find any such cases.\n",
      "\n",
      "\n",
      "[0]\ttrain-auc:0.84293\n",
      "[1]\ttrain-auc:0.84257\n",
      "[2]\ttrain-auc:0.84272\n",
      "[3]\ttrain-auc:0.84282\n",
      "[4]\ttrain-auc:0.84320\n",
      "[5]\ttrain-auc:0.84328\n",
      "[6]\ttrain-auc:0.84354\n",
      "[7]\ttrain-auc:0.84397\n",
      "[8]\ttrain-auc:0.84402\n",
      "[9]\ttrain-auc:0.84416\n",
      "[10]\ttrain-auc:0.84419\n",
      "[11]\ttrain-auc:0.84809\n"
     ]
    }
   ],
   "source": [
    "# retrain on the whole training dataset\n",
    "watchlist = [(train_matrix, 'train')]\n",
    "gbt = xgb.train(params, train_matrix, n_best_trees,watchlist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "9c7d5558",
   "metadata": {},
   "outputs": [],
   "source": [
    "### plot the ROC and choose a threshold\n",
    "def plot_validation_roc():\n",
    "    \"\"\"\n",
    "    we cannot plot ROC on either training set or test set, since both are biased\n",
    "    so I split the training dataset again into training set and validation set\n",
    "    retrain on training set and plot ROC on validation set and choose a proper cutoff value\n",
    "    \n",
    "    define a class to limit the naming group, avoid polluting the global naming space\n",
    "    \"\"\"\n",
    "    Xtrain_only,Xvalid,ytrain_only,yvalid = train_test_split(Xtrain,ytrain,test_size=0.3,random_state=seed)\n",
    "    onlytrain_matrix = xgb.DMatrix(Xtrain_only,ytrain_only)\n",
    "    valid_matrix = xgb.DMatrix(Xvalid,yvalid)\n",
    "\n",
    "    temp_gbt = xgb.train(params, onlytrain_matrix, n_best_trees,[(onlytrain_matrix,'train_only'),\n",
    "                                                                 (valid_matrix,'validate')])\n",
    "    yvalid_proba_pred = temp_gbt.predict(valid_matrix,ntree_limit=n_best_trees)\n",
    "\n",
    "    fpr,tpr,thresholds = roc_curve(yvalid,yvalid_proba_pred)\n",
    "    return pd.DataFrame({'FPR':fpr,'TPR':tpr,'Threshold':thresholds})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "9ab9fdff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[17:01:32] WARNING: /Users/runner/work/xgboost/xgboost/python-package/build/temp.macosx-10.9-x86_64-3.7/xgboost/src/learner.cc:627: \n",
      "Parameters: { \"early_stopping_rounds\", \"num_rounds\", \"silent\" } might not be used.\n",
      "\n",
      "  This could be a false alarm, with some parameters getting used by language bindings but\n",
      "  then being mistakenly passed down to XGBoost core, or some parameter actually being used\n",
      "  but getting flagged wrongly here. Please open an issue if you find any such cases.\n",
      "\n",
      "\n",
      "[0]\ttrain_only-auc:0.84076\tvalidate-auc:0.84708\n",
      "[1]\ttrain_only-auc:0.84095\tvalidate-auc:0.84724\n",
      "[2]\ttrain_only-auc:0.84103\tvalidate-auc:0.84720\n",
      "[3]\ttrain_only-auc:0.84087\tvalidate-auc:0.84845\n",
      "[4]\ttrain_only-auc:0.84171\tvalidate-auc:0.84703\n",
      "[5]\ttrain_only-auc:0.84179\tvalidate-auc:0.84705\n",
      "[6]\ttrain_only-auc:0.84177\tvalidate-auc:0.84702\n",
      "[7]\ttrain_only-auc:0.84186\tvalidate-auc:0.84696\n",
      "[8]\ttrain_only-auc:0.84173\tvalidate-auc:0.84687\n",
      "[9]\ttrain_only-auc:0.84193\tvalidate-auc:0.84715\n",
      "[10]\ttrain_only-auc:0.84557\tvalidate-auc:0.84623\n",
      "[11]\ttrain_only-auc:0.84921\tvalidate-auc:0.84615\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score,classification_report,roc_curve    \n",
    "\n",
    "roc = plot_validation_roc()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "fff35787",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'TPR')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(10,5))\n",
    "plt.plot(roc.FPR,roc.TPR,marker='h')\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "25dd7e42",
   "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>FPR</th>\n",
       "      <th>TPR</th>\n",
       "      <th>Threshold</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>591</th>\n",
       "      <td>0.390869</td>\n",
       "      <td>0.815580</td>\n",
       "      <td>0.169269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592</th>\n",
       "      <td>0.393363</td>\n",
       "      <td>0.816170</td>\n",
       "      <td>0.169256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>593</th>\n",
       "      <td>0.437162</td>\n",
       "      <td>0.827088</td>\n",
       "      <td>0.169253</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          FPR       TPR  Threshold\n",
       "591  0.390869  0.815580   0.169269\n",
       "592  0.393363  0.816170   0.169256\n",
       "593  0.437162  0.827088   0.169253"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "roc.loc[ (roc.TPR >= 0.78) & (roc.TPR <=0.83),:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ddd87fa8",
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Normally the \"Fraud Detection Model\" is used in a pre-screening step, \n",
    "\n",
    "the result of the model will be further investigated by expert later, \n",
    "\n",
    "so\n",
    "\n",
    "if 'Not Fraud' is classified as 'Fraud', human expert can still have method to fix the problem\n",
    "but if 'Fraud' is classified as 'Not Fraud', the company will lose money directly. \n",
    "\n",
    "so in this case, \"false negative\" cost much higher, so we should choose a relatively smaller threshold.\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9fc8c71",
   "metadata": {},
   "source": [
    "### Part 3: Explain the features to business department"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "2868e963",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Feature importance'}, xlabel='F score', ylabel='Features'>"
      ]
     },
     "execution_count": 61,
     "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": [
    "# first plot the feature importance from GBM\n",
    "xgb.plot_importance(gbt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc23022e",
   "metadata": {},
   "source": [
    "Clearly, the most important feature is time difference, which is the time interval after sign up\n",
    "\n",
    "we will next fit a random forest model to see it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "34106196",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "clf = RandomForestClassifier(max_depth=3, min_samples_leaf=30, random_state=42)\n",
    "clf = clf.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "11f50603",
   "metadata": {},
   "outputs": [
    {
     "data": {
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altr+cztol7W3jT7dcw7cKRecuOfqY6p/cdeUtQqUU+YuzuV/enJL5P++9pinlCefMGbEdvmf1xydl376miQd20rXV6C847E5+ewvH0iS7Dd6SL77thM2WGgcMnDLvm2xYMnyXH7r46t/ff4Je2zR/QAAAICeTYESAAAAANZh5cqa4/796jw2e3EG9euT2//lxessEj3dKR/7de6fOj99+5Tc+o8vzOg1ym8rVtb84YHp+e2903LLhNl5cNr8zFqwLH37dBwffPjYEXnpYbvkrKN3a1x8e8Kx/3Z1Js5alLE7bJebPvLCDV77//3s3tXH3V76zpNy8n47rvfa5StW5tJbHsvP75ic2ybOycz5S9KnT8ku2w/KSfuOymtP2jNH7D5ii7LTzE7DBmbUkAGZOm9Jlq+smblg6SaVL5+u1pqLbpyw+tev6cQC2ge//+fMWrgse40anA+85MDcMmFWp2XpCQ7cZejqj6fNXbzW43+4f/rqo8Wfc+BO2WX4+l8/R+0xIgfvOix3T5qX2yfOyf1T5q3z2Pgv/Hp8lq9q4/7rmYdu9W2QP7rt8cxf0nEc9zPGbJ8jfT0CAAAANkCBEgAAAADWoU+fklceMzaf+eUDWbx8ZX70p8dzwUa2Ct7yyKzcP3V+kuS5B+70lPJkkpz/pevy2/umrz24Inls9uI8Nntyrrxjcj7/6/H55l8clz1HDWnt82nD7RNn520X3pKHpi9Y67Hx0xZk/LQF+fb1E/Kmk/fOv778Gem7nuOE2TrmLFqWWQuXJkkG9O2TEYM3Xvhdl2vun776COedhg3Miw7ZubWMm+PyWx/LlXdMTpJ84pwjst2Avp2Soyd5aPrC1R/vtI5y7aQ5T5Yq9xs9dK3Hn26/0UNz96R5SZJf3DV1rQLl3EXL8uPbJiXpOEb9eQet/5jvtnz3+ifLv7ZPAgAAABujQAkAAAAA63HOcbvnM6uOnr3kpokbLVBectPEp8w+3aJlK7LdgL45aZ9ROWL34dlj1OAMHdgvS5atzIPTF+Snt0/KPZPn5Z7J83Lel67PVX/17Awd1DXewrvhoZl59Revy6KlK5IkJ+w9Mi88ZHR2Hzk4K1fW3DVpXi6+8dFMm7ckX/39Q1myfEU+cc4RnZy691i6fGX+7vt/zrIVHZv+XvSMnTOwX7PC4beve7KAds6xY9NvC7ehNjF9/pJ86LKOo7vPP2GPPGv/9W9F3RQ3PDgzp37qmjw0fUEWLl2eEYMHZN+dhuTk/XbMBSfusd4jynuSmx+elW9e+3CSpJTk9MN3XeuausbHpWxeAfquSXPX+r2bHp6VpStWJkmetd+OKaXkmvum5Zt/fCQ3PzwrM+YvzbDt+mX/0UPzwkN2zhueudcWfc27f8q83PBQx5bSQf365JXH7Nb4XgAAAEDv0DXefQUAAACALmi/0UNz9B4jcsuE2bnh4Zl5ZMaC9W6FXLZiZX74p8eSJMO365+XPGPtrX1/85IDc8yeO2TIwHW/LfeBlxyQz/zygfznT+/Jg9MW5CvXPJj3veiA9j6hhuYsWpa3XXhzFi1dkUH9+uRzFxydcU8rX70iyXtesF/e+PUb84cHZuRb103IGUeMyXMObLZxbuHS5fntvdNaSN/hOQfutNWPDt4W5ixalmsf6NhiWmsyf8ny3Ddlfn74p8dWb43cZ6ch+beXP6PR/WctWJqfrdr6mHTeBr+/u/TPq44gH5h/etkhW3y/h2csTGY8uX1x2rwlmTZvSa57cGY+88v78zcvOTDvecF+m10a7IpufnhWps7r2CS5bEXN1LmLc+34Gfn5nVOyYmVNKcmHTjsoh4zZfq3ZXdbYSjl+1TbdDXlw2pPbaO+fMm+tx2+dMHv1x/vvPDQf+N5t+b81CrpJMmP+0syYPzPXPTgzX/jN+Hz5dcfkmfs1K8x+5/pHV3982uG7ZsTgAY3uAwAAAPQe3f8dQwAAAADYis45bvfcMmF2au3YMPk3LzlwndddfdeUzFywLEly5pFjMqj/2tv/nn3AhsuEpZS894X751d3T831D83M926a2CUKlF/7/UOrj/b9j1cctlZ58gnbb9c/X379sTnho7/MvMXL84XfjG9coJw+f2ne+PWbGmd+uhs+/ILsMbL7vx360PQF6/1zGTaoX846erf8w7iDM3y7Zsd3X3rzxCxZ3rEx8MR9RmbfTTjGuW0/ue3x/GTVsc//8YrDGn8uT9h/56F59v475cBdhmbE4AFZvGxF7p8yPz/986SMn7Ygy1bU/OdP78ljsxbl4686vI1PoVN96ur7cvVdU9f52BG7D8/7X3RAXnLoLut8/IR9Rq7++Df3Ts3UuYszeh1HfSfJ7RNn587Hn9w6OXfR8rWumTLvySPBv33dhDw0vaNweeqhO+cFB++cYYP6ZcKMhbn4xkczftqCzJi/NOd96fr86N0n54jdR2z0c13TshUrc8lNTxYoHd8NAAAAbIptf/YKAAAAAHQjLz9qTAasOsJ4zSO6n+57Nz752KuOHbtFz3nc3h0lpgenLcjMBUu36F5tuPiGjlLSTsMG5tXHr300+ZpGDhmQFx7csX3zuvEzsmT5iq2ejw7H7TUyz95/xwxbz4bTTbHmBr/OKKDNXLA0f3fpn5Mk4w7bZb1l3U0xcvCAXPX+U3LNB5+Xj77i0LzumXvlZUeOyTnH7Z5/OP3gXPPB5+UfzzgkTyydvPCPj+SHf3q8jU+jS3ri3+ZBu669efIJu48cnOcfNDpJsmjZyrz9/27J/MVrFyMnz1mcd3371qf83vwla183d9Gy1R8/NH1B+pTky68/Jt940/F57Ul75uVH7Zb3vHD//OZvn5vTj+j4u16yfGXe+90/pda61v025Ko7p2T6/I6vl3uNGpyT9xu1WfMAAABA79T9f+QaAAAAALaiEYMH5EXP2DlX3D4pj8xYmOsfnJET9nlqMWfWgqX55d0dG9/22WnI6gLkuixauiI/vu3xXHXXlNz9+NxMnbckC5Ysz8r1dIUmzV6UkUM67xjayXMWdxx/nGSX7Qfmqjsnb2QiWbqqNLl4+cpMmLEw++88bLOfd4+RgzP5/52x2XM93ZG7j1j957JyZc2shUtz+8Q5+dYfH8kVf56cX90zNc87aKf872uP2ezNjbdOmJ27JnVsFNx+UL+cccSY1vNvzD9cdkemz1+a4dv1z3+88rAtutfQQf1y+NgR6328T5+Sdz5v38xbvCyf+sX9SZJP/vzenHnktv+82/StN5+w+uOFS5dn4qxF+fU9U/O5X43PJ6+6L1/4zfj893lHrvfv96NnHZrT/vuazFq4LNeOn5FnfezXOff43XPQrsOyYmXN7RPn5KIbHs2cRcuyx8jBmTCz4+vDug4/X/G0L2xvetbe63ze/n375L/PPTI3PTQrk+cuzj2T5+Wa+6dvdGvvmr5z/ZNHg593wh494jh2AAAAYOtToAQAAACAjXj1cWNzxe0dRwpfctPEtQqUP7j1sSxd0XHs8Ya2T9788Ky87f9uzsRZizb5ueetY6vbtvREOSpJ/vzY3M0+VnvWwmUbv4hG+vQpGTV0YJ530Og876DR+fofHs7fX/rn/PqeaXnD127MD971zM2633fXKKCddfRu2W7A2sfQb00/u2NyfnDrY0mSfzrjkOy8nqOj2/aeF+yfL//uocxfsjz3TZmfR2YsyJ6jhmyT597aBg/olwN2HpYDdh6Ws48Zm7M+d23umzI/b73w5nzvbf1zyjoKinvvNCSXvOOk/MU3bsojMxZm8tzF+fTV96913RG7D88HTz0o53/5+iTJ8MFrF3aHPm0b6uueued6sw4Z2C+vOnZsPvurB5Ikv7tv0wuUk2Yvym/unZYk6dun5NXHbXhTLgAAAMATFCgBAAAAYCOef9Do7Dh0QKbPX5of/enx/PtZh2ZQ/yfLZU8c7V1KcvYx6y5QPjpzYV79xetWH3O7x8jBed5BO2W/0UOz49CBGdCvT/qsWph2+a2Prz5K+Okb3La1OYu2rAC5bFWxlK3vjSfvlR//6fFcO35G/jh+Rn5777Q858BNK6AtXLp8dXkx2fbHd89euDR/e8ntSZKT9xuV80/cds+/3YC+OWbPEfntfdOTJPdPmd9jCpRrGjV0YD72ysPyis//MbUmH//ZvessUCbJobsNz2//9rn53o2P5so/T86dj8/N7IXLMnRQ3xyw87C84ujdcv4Je+SqO6esnllX4XXNUuV2AzpmN+Tw3Yev/vih6Qs2+XO76MZHV3+tfP5Bo7PL8G1TvgUAAAC6PwVKAAAAANiIfn375BVH75Yv/e6hzF28PD+/c8rqY34fmDo/t06YnSR55r6jsvvIweu8x39fff/q8uQ7n7dvPjzu4PTps+4jZm94aFb7n8QGrKzrL2kOWWML4dnH7Jb/ec3R2yJSFi5dnt+u2ijXhuccuFMGD+j5b4e+4ODRuXb8jCTJNfdP3+QC5Y9vm5R5izten4futn2O2H3E1oq4Tj+/c0qmzluSJNl95OB86hf3rfO6CTOe3Ig6cdbC1dcN7Nc373zevo2ff9TQgas/nruFpeGu7KR9R2XIwL5ZsGRFbn5kVhYuXb7efxeD+vfN6565V173zL3We78nvvYlHcfLP93+o4eu/vjp2yjXZc1j5+cv3rS/h1prLrrh0dW/fs02LN8CAAAA3V/Pf8cQAAAAAFpwznG750u/eyhJ8r0bH11doPzejY8+5Zr1eeJ42R2HDsg/bKA8mTz12OymBvbrkyRZunzjGyBnLFi63sfGjNhu9cf3TJ63xbk21fT5Szf7uPANueHDL8geI3v+26HDBj35Oc5ZuP6/16db8/jubb19MknW7PCuWYbbkEdnLsp/XXlvkmT7Qf22qEA5c41/A9tvt/ZR1D1FKSVDBvTLgiUrsrIm8xavv0C5KX51z9TVH5+078i1Hj9kzJMbJecvXpZaa0pZ/9e+NTfeDtvEv4c/PDAjj6wq1o4eNjAvPHj0Js0BAAA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vRKv2p2vxxiN6/raZrq/71d5U/eD5NcoqKK31+r6UXO1LydVb6+P19t1na2hMmOtrt1drDqSf3CcYFKmQwAb2CQJ9NWVQpFbsSVVRWYXWHszQ2SN7tWh+NfctvsnzdCRkFHiunT4cWVVl9cbaeM/X103n+G4AAIC2QAElAAAAgA7h8S8O6ZFPTx7/fP6oaM0dEaXQQF8dzS7SmxuS9NX+TN331jZX1919LE9PrDik8soqXT2hj6YNilBIgK+OZBXpP2uPKCGrSGl5pbr9xU367N7Z8mli54OObk9Kvud6XL/ujY4f36+7VuzL8MS2hwLKNYeyPNczh/SUJH247ZheXXdUO5NzdbyoXN2DfDWyd6guHB2jhVNi5e/jvHPmin0ZSs4pliTFhAbo3BFt/zMAAAAAgI7q8c/26uFluzxfnz+mt84b1VuhQX5KzCrQm2sT9NXeNN376gZX192VfFyPf7avep9gUn9NG1K9N3Eks1CvrDqkhMwCpeWW6LZnV+vzX1zQdfYJjuV6rscPiGh0/Pj+4VqxJ9UT29IFlDW7TvY9zZNBPtqWpKVbq08aCfT11twTx3k314o9qUrKKZIkxYQF6txRLfszAAAAQN0ooAQAAADQ7iVkFuqvy/ZKkry9jB6//kxdNq725vQP5gzSj1/bqsWbk11de9nOVEWH+uvV26ZoVJ/anSNunjFAl/9rlXYm52lvar4+3ZWmi8e27Gb3sh0prs01eWB4g0eKNeRQ+slOC7FNuPFQc8zBGrFtaUvicc91/4gg3fDsen164ljyb6Tnlyp9X4ZW7MvQkysO6flbJmlEr1BH6726PtFzfe3kvvJu4ePCAQAAAKCzSsjI118+2C6pep/giZum6bIJ/WqNuePc4brn5XVavOGIq2sv25as6LAAvXbnWRrVt0et926ePViX/e1z7Uw6rr3HcvXpjmO6eFxfV9f/to+2Jbk215RBkY73CQ6m5XmuY8ODGx1f89jyAzViW8qLKw96rs8d1bSCx5X70pRfUi5JKquo0rGcIq3Yk6Iv91bvHfh6e+mhRZMUGeKsA+Wraw57rq+dOlDeXl2j2BYAAKC9oYASAAAAQLv33NfxKq2okiTdOmvgKcWTUvWm9cPXnqENCTlKzC5ydf1/Lhp/SvGkJHUL8NGvLh6hRc+skyQt35ve4gWUNz+/0bW5Ft85TTMGO7sxkltc7rnu2c2v0fERwSfH1IxtS2l5JZ7rRz49oPjMQnl7GV0xvremD+6pID9v7UvN1+vrjyolt0QJWUW66vHV+vSns9W3R/O6VWQVlOrTndU3WIyRFk7u10gEAAAAAKA+z355wLNPcNucoacUT0rV+wSPXDdZGw5nKjGr0NX1/3nD1FOKJyWpW4CvHrj0DC18/EtJ0ue7W76A8uanv3ZtriX3nK0ZQ6MdxeYWnfysHxHS+F5DeI1CzbyiMkdrNtUrqw5pzcHqUzFiwgK1qIlHZT/w1mbtS8k95XVjpGmDo/TL+WM0eVCko5yyCkr1yY5kz3yLpg10NA8AAABOH4+xAAAAAGj3PtpRfaSTMdLts+vf5A7w9dZNMwa4uvbIXqGaNbT+zfAZQyLkc6KTYM1jrTu7wtIKz3WAb+PHWtccUzO2LeUVn8wjPrNQQX7eWnLnNP3zujO1aEo/XT6+j35+0XB99fM5mjIwXJKUXViuXyze0ey13tqYpLLK6pt70wdFaEDPxrtxAAAAAADqtuxE10VjpNvPGVrvuABfb908e4ira4/s012zh8fU+/6MoVEn9wmOnVp811kVlp4soGzKPkFgjTEFLbhPsDE+Uw+8tVlS9e/LgwsnKtj/9HoM9e0RpLmjemlAZIjjOd5aF6+yE0XA04dEndZcAAAAOD10oAQAAADQrmXklyopp1iSFNczWH16BDY4fuaQCFfXnzTw1I4SNfn7eCs82E/p+aXKLW7ZjgmSlPrI/BZfoyWYdnhadWWVrfX1zy8apilxp/7+hAT46qkbJmjanz5XcXmVPtudrsMZBYqL7HbK2Pq8tv6o5/q6KXSfBAAAAACnMvJLdPTEyRNxkSHq06PhB9RmDo1ydf3JcT0bfN/f11vh3fyVnlei3BburChJaf9a0OJrtIhW2Cc4nJ6vG59aqZLySknSj84boQvG9Gly/Fe/vshzXVhaoYSMfC3blqwnl+/T797dpn99tlfP3jpD04Y0/3fs1TXxnuvrmtgREwAAAC2DDpQAAAAA2rWaxyz3j2i8a9+AJoxpjvDgxo+n9vOp/mhVUl7l6trtWc1uDd/ciGhIcdnJMafb6cEt3QJO5uHjZXTdlP71jo0JC9AFo092GFl5ILPJ62xKyNG+1OrupN0DfVv8mHcAAAAA6MzSjhd7rgf0bPzBtgHNePitKWoePV0f/xP7BKVN+LzcWQT7+3qum7tP0K0F9gkSMgt01WPLlZlfKkm6YeYgPXDZGY7nC/b30ai+PXTfvNH67BfnKzosQFkFpVrwry/rPOa7IRvjMz0x3YP8NG9crOO8AAAAcPoooAQAAADQrtU87jnIv/EjoIL8Gh/THF7tsXViOxAaePLGSFZh4x01smt03QirEduWauYxMDK4VkFlXcb27e65js8sbPI6/1mX6Lm+ckKfJh1lBgAAAACoW+19gsYL74L83C3O82KboE419wmyC0obHZ9TeHJMaFDjD682R0Jmga58dLmOnSi2XTQ9Tg8umOja/AMiQ/TApdXFmCXllXr0493Niv/P6sOe6ysn9WefAAAAoI21j7YfAAAAAFCPmt0Ka3YnqE9xJ+/usGxHimtzTR4YrogmdM6oy6AaHTwSs4oaHV9zzKBId7uEOjUk6uT3ENKEm25hgSfHFJRUNDDypMLSCr23NdnzNcd3AwAAAMDpqb1P0Phns6bsJXRkH21Lcm2uKYMiHe8TDI4O9VwnZjX+0GHNMYOjQhytWZeEjHxd+dgXSs6p3odYMHWgHl44ScblB2TPHXXydImV+9KaHFdYWqH3Np180PJ6ju8GAABocxRQAgAAAGjXokMDPNdHmrABn5DZeDFfR3bz8xtdm2vxndM0Y7CzGyMje5+8ubE18Xij47fUGDOiV2j9A1vRyN4n88hvQkFkbvHJMSEBTeui+d7WYyosrb5Zd0ZsmEb1CWtmlgAAAACAmqK7B3quEzILGh3flDEd2c1Pf+3aXEvuOVszhkY7ih1Z4/PuloSsRsdvrjFmRO/ujtb8tsPp+bryseVKOdF5csHUgfrbdZPl1QJtQ2vuC+QWN34yxzfe25To6aI6rl+4RvXt4XpuAAAAaB6O8AYAAADQrkWG+KtPj+qbI4cyCj3HL9Xn64OZrZFWlzdtUIQCTxyXvi4+u8GOjPkl5VoXny2p+oj1qYPCWyXHxpw1LFK+3tU3UQ5nFiq/pLzB8duOHvdcD45qWhfNV2sc372I7pMAAAAAcNoiQwLUt0eQJOlQer6O5TT8IOXXzegOCOemDYk6uU9wKFMFDXzGzi8u17pDGZKqj1ifOiTytNc/mJanKx5tneJJSTqcke+5bk7Xzv+sPuS5XkT3SQAAgHaBDpQAAAAA2r2LR8fomZXxslZ66svD+u1lo+ocV1JeqRdWJbRucq0s9ZH5bZ2CpOobHOePjNZ7W4+pqKxSL6xO0A/PGVzn2BdXH/EcmXbh6BgF+bWPj6Jhgb6aOyJay3amqrLK6j9rE/WDOYPqHJuaW6JPd6VKkrxMdfFlY/an5WtjQo4kKdDPW1ee2ce95AEAAACgC7toXF8988X+6n2C5fv026vG1zmupLxSz6880MrZta60fy1o6xQkndgnGNNH721KVFFZhV5YeVA/PG9EnWNf/PrgyX2CsX1Oe5/gQGqernxsudLzSiRJC6cN1COLWq54UpJeWnmyEHJSXM8mxexPzdXG+OrOm4F+3rpyYv8WyQ0AAADNQwdKAAAAAO3e92YNlL9P9ceXf6+M13tbj50ypryySve+sU1Hsjr3Ed7tyb0XDJX3iZsRD3+yT+tPdJmsad3hLD38yT5Jko+X0b3nD613vpiffuD5LzG7df4df3bRMM/38ODH+7Tu8KnHjBWUVOgHL29ScXmVJOmK8X083U4aUrP75PwzejX52G8AAAAAQMNuPWuIZ5/gmRX79d6mxFPGlFdW6af/Wa8jmYWtnV6Xdd/FozyfsR9aulPrT3SZrGndwQw9tHSnpOp9gvsurvshWUmKvut1z3+JWXUfxf7t4slF0+Mcd558avk+bTjc8MkmlVVV+vunuz2FucZI3ztrSJPmf3X1Yc/1peNjFRLIPgEAAEB70D7afgAAAABAAwb0DNbPLxqu332wW5VVVt9/aZOWbErS3JHRCg30VWJWod7ckKQD6QW6bFxvT4FlCzYagKSh0SH62YXD9OeP9qq4vEpXP75GV0/sq6lx4bKS1h3O1tsbk1RWWV14+IuLh2tQVLfTXvfVtYmnFFjW/Pq1dYlaub/2DY87zh6ksDpuTIzoFapfXDRMf1y6V0Vllbry8TW64sw+mjm4pwJ8vbQ/rUCvrUtUSm71jZh+4UH6/RWjG82xvLJKb29M8nzN8d0AAAAA4J4BkSH6xfyx+u07W1VZZXX7c6u1eMMRzR3dS2GBfjqSVaA31yboQFqeLpvQz1NgaQwbBS1paEyYfjZvtP78wQ4Vl1fqqr9/oasnD9C0wZGyVlp7KENvr09QWUX1PsEvLx2rQdGhjtc7llNUq3hyWEyozhvVW8u2Jzcae/EZfU95bfWBdP1m8Rb1iwjWrGHRGtG7uyJC/OXr5aXjxWXaeyxXn2xP0tEaexD3XDBSUwdHNbpeeWWV3lqf4Pma47sBAADaDwooAQAAAHQId549SPkl5Xr0swOyVvpkV5o+2ZVWa8zsoT3116vHeAoou/nzkael3TN3iCoqrf723/0qq6zSq+sSa3VelE50nrxgaL1HfDfXW5uStObQqZ0iv/H2plNvlCya2q/OAkpJ+tG5Q2SM0YPL9qnsROFjzeLHb4zv113P3jRR4cF+jeb4yc5UZRaUSZIGRwVralxEozEAAAAAgKa7c+5w5ZeU628f76reJ9iRrE921P48OHt4tB5cMNFTQNnNn45/Le3HF45SZZXVI8t2qayiSq+uPlyr86J0Yp/g4tH1HvHdVPEZ+Z7iSUnal5qnm5/5ukmxDR19nphVqP98K+dv6x7kpwcuG6sbZjZtr+OT7cnKzC+VJA2ODmlS0SUAAABaB3cTAQAAAHQYP79ouM4bGa1nV8ZrzeEsZeaXKSzIV0Oju+k7E2N1zcS+yios84zvHtR4oRtO370XDNVFY2L08pojWnkgw9OtsVdYgGYPjdR3p/bXiN7OO0q0hh+eM1gXjo7RK2uPaMXeDB07XqyS8ipFdPPT+H7dddn4Ppo/tleTjwB7dd1Rz/XCyXSfBAAAAICW8PNLxmjuqN569sv9WnMgXZkFpQoL9NPQXqG6ZvIAXTNloDILSj3jezThgTicvnsvHq0Lz+irV74+pK/2pSrleLEkqVf3QM0eHqPvzhikkX26t22SdfjnDVO17lCG1hxM1+aEbKXlFiszv0SFpRUK8vdRdGigRvbtrjnDYzS/mUdw1ywiXTSN7pMAAADtibHWtnUOAAAAgCuMMaGScps6/sCfLlRIAJ0HOptPdqbqxuc2SJJ+d9ko3X4Wm9IA3JNfUq4hv/q4OSFh1tq8lsoHAAAAHU9z9y8OPnRVswq1UNvH25N141MrJUm/u2q8vn/OsDbOCEBz5ReXa/B9i5sTwmdxAADQZF5tnQAAAAAAuOm5r+M91zOH9GzDTAAAAAAAQFt77sv9nuuZw6LbMBMAAAAA7REFlAAAAAA6hKyCUu1Jqf/B8coqq//3/i59uT9TkjR5YA+NbOfHRgMAAAAAAGeyCkq159jxet+vrKrS/1uyRV/uTZMkTY7rqVHt8NhoAAAAAG3Lp60TAAAAAICmSMkt0dyHv9KYPqGaNTRSg6O6KTTAR0VlldqXmq8PtqUoMbtIkhTg46W/Xj22jTMGAAAAAAAtJSWnSOf+5RONie2h2cOiNTg6VKGBvioqq9C+lFy9v/moErMKJUkBvt56cOHENs4YAAAAQHtEASUAAACADmVHcp52JNffibJnNz/9+6aJGtGL7pMAAAAAAHR2O47maMfRnHrf7xnir2dvnaERvbu3XlIAAAAAOgwKKAEAAAB0CEOjQ/TyrZP11b4MbTySo/T8UmUXlslWWXUP8tOI3iE6d3iUFk7pp2B/PuoAAAAAANCZDe0VqlfumK0v96Zq4+FMZeSVKKuwVNZK3YP8NLJPd50zspcWTY9jnwAAAABAvfi0AAAAAKBD8PPx0nkjo3XeyOi2TgUAAAAAALQxPx9vnTe6t84b3butUwEAAADQgXm1dQIAAAAAAAAAAAAAAAAAAACtjQJKAAAAAAAAAAAAAAAAAADQ5VBACQAAAAAAAAAAAAAAAAAAuhwKKAEAAAAAAAAAAAAAAAAAQJfj09YJAAAAAEBnM/H3nykpp1h9ewRq4//Mbet0AAAAAABAJzHxf97X0ewixYYHaePvL23rdAAAAIAOjwJKAAAAAECHtSXxuF5de0Rr47OVmlui8ooqRYb6a1xsd115Zh9dNKbXac1/IC1fcx/+SqUVVZ7XUh+Z32DMNwW0TdXYfOl5JdqWlKsdJ/7bnpyr5Brzr//1ueoXHtTk9STJWqv3th7Tks3J2pWcq8yCMoUE+GhQZDddPDZG10/tr2B/tgwAAAAAAF3X/tRcvbY6XmsOpishs0D5xeXy9/VWZEiARvftrnnjY3Xp+Fj5eNd96GNiVoEm/eZDR2svuedszRga3WK5AQAA4CTuhgAAAAAAOpziskr9YvEOvbHh6CnvHc0u1tHsYn2wLUVnDe2pJ747QeHBfs1eo6rK6sevb6tVPNnaPt2Vqhue3eDqnBn5pbr9pU1acyir1uulBWXKLMjWuvhs/XtlvJ6+YaLG9+vu6toAAAAAALR31lr94b3teuLzvaqssrXeqyitUGFpgRIyC/Th1iT9bdku/fvWGRrWK8y19Y2R+kV0a5e5AQAAdEYUUAIAAAAAOpTKKqvbXtqoz3anS5ICfLx09cS+mjggXAG+XjqcUag3NxxVQlaRvtyfqeueWae375jW7I6KT311WJuO5CjIz1tFZZXNzjOim58e+s7YZsfV9O2bId5eRoOjuikxq1DF5c0v7CwsrdB1z6zT9qRcSVKfHoG6bko/xUUGKzO/VEs2J2tz4nEdzS7Wdc+s1Qc/mqlBUXXftAEAAAAAoDP6/bvb9K/P9nq+Pmt4tM4aHqNePYKUV1SmPcdy9ea6BBWVVWh/ap6ueHS5VvzqQkWFBdaap2dIgJ6/fWaT1ly8PkEfbk2SJM0aFq3YiOAWzQ0AAAAnUUAJAAAAAOhQXl2X6CmejArx11t3TNOwmJBaY+46Z5DueHmzPtqRqi2Jx/XYZwf0q3kjmrzG4YwCPbis+obELy8erv95d1ez8wz09T7tI8R7dvPXoin9NKZvmMb2CdPI3qEK9PNu9jHh3/jH5wc9xZOTB/bQf26bopAAX8/735s1UL9+Z5ee/Tpe2YXluv+t7Vpy1/TT+h4AAAAAAOgokrIL9eTyfZKqH2J86fuzNHd071PG3TdvtK567AvtS8lVVkGp/vXZXv32qvG1xgT5+ejiM/o2ad0/vLvNc33d9EEtnhsAAABO8mrrBAAAAAAAaI6nvzzsuf7LVWNOKZ6UJH8fb/1j0Xj17ObnicksKG3S/FVVVj95fZuKy6t0Zr/u+t7Mge4k7sCkgeF65NozdPOMAZowoIcC/bwdz3W8qExPfXlIkuTv46XHrz+zVvGkJBlj9NvLRmpEr+qf6epDWfpqf4bzbwAAAAAAgA5kxZ5Uz2kQF5/Rt84CRUmKDAnQA5edPHVizcF0x2uuOZCuQ+n5kqTwYD9dNLZPu8kNAACgK6ADJQAAAABVVVm9v+2YPth6TNuTc5WZX6oqW71pG9HNT0OiQjR7WE+dMzxK0aEBp8SXVlRqxd4MrTyQqa1Hjys+s1B5xeXy9fZSz27+Gt+vuy4f31sXjo6RMabePF5ff1Q/fn2rJOnRBeO0YHKs9hzL07Nfx+vrA5lKyytRaKCvRvYO1Z1zBmnW0Mha8ZuP5Oi5VQnaGJ+t1NwSBQf4aGL/HvrhOYM1aWB4vev+38f79PCn+yVJi++cphmDe+rrA5l6cXWCNiceV2Z+qUICfDS2b3ctnBKr+WfUvUHtxPGiMr2yNlHL96TrUEaBcgrLFeTnrX4RQZozLFLfmzWwzp95TRn5pXpl7RGt2JuhA+kFyi8pV4CvtyKC/RQZ4q8JA3rorKGRmjG4p/x8OvZzdGl5JTqQXiBJ6h7oqwtHx9Q7NtjfR5eN66Nnv45XSUWVlm5P0Y3TBzS6xrNfx2tdfLZ8vY0evvYMeXnV/zvbkXy8M81z7Pf8M3qpb4+gOsf5eHvptllx+umb1d0v3tmcrNnf+n8NAAAAAJqqqsrq/S1H9f7mRG0/mqPMvBJVWavwbv6K6OavITGhOmt4jM4Z2UvRdRwzXFpeqS/2pGrlvjRtPZKl+IyCk3sOIf4aPyBCl0/op4vG9ml4z2HNYd3zynpJ0mPXT9aCaXHanXxcz365X1/vS1dabrFCg3w1qk8P3XHuMM0eXvvz5uaELD335QFtOJyp1NxiBfv7aOLAnvrR+SM0Ka5nvev+39Ideuij6lMNltxztmYMjdbKfWl6aeVBbU7IUkZ+iUICfXVGbLgWTovT/DNjnfyY63S8qEyvrDqkz3el6FB6nnIKyxTk56P+PYN11vAY3TpnaJ0/85oy8kv08teHtGJPig6m5Suv+MSeQzd/RYYGaOLACJ01PEYzhkbJz8f5Q3/tRWZ+iec6LurUBzZrGlzj/cLSCsdrvrrm5IOiV00eIH/fun+ObZEbAABAV0ABJQAAANDF5RSW6YZn12tDQs4p76Xkliglt0Q7k/P0zpZk3TxjgP581ZhTxp39f1/qcEbhKa+XV1YqMbtIidlFem/rMU2NC9e/b5qont38m5Tby2uO6IElO1VWWeV5rbi8VGl5Gfpib4b+55IRuuucwZKkv/13vx78eJ+sPRlfUlCmT3al6dPdafrbtdUFmU3xv+/t0lM1uhxKUmlBmZbvTdfyvem6cHSSnvzuBAXUs6HdVG9uOKpfv7NTeSW1N7LLiqt0PClX25Ny9cxXh/XXq8fqmkl15/7F3nR9/6VNp8xRXlmh/JIKJWQVaUNCjp5ccVgf/2SWxsV2P62c29qx4ydvFgyMDG60uHFwdDfP9X93pzVaQHkkq1B/+qj66O67zx2iEb1CnSfbzizfe7LjxNyR0Q2OPXdklOf68z10qgAAAADgTE5hqb775EptOJx5ynspx4uVcrxYO5OO652Nibpl9hD9+doJp4yb86ePdfhEd76ayiurlJhVocSsQr23KVHTBkfq37fOUM+Qhh9C/MZLXx/UA29tVllFjT2H3Eql5aZo+e4U/ebyM3TXeSMkSY8s26UHl+6ovedQXqlPdiTr053JevS66oLMpvjfxVs8xzB/ozS/VJ/vTtHnu1N04YY+euqW6ae/57AuXg+8tVl5xeW1Xi+rKNPxxDJtS8zRM1/s14MLJ+qaKXWfvPDF7hTd/tzqU+Yor6xSfkm5EjILtOFwpp74fJ8++dn5Gte//odXO4qavz/xdfze1XSoxvvDe4U5Wi+/uFwfbDnq+fq66fX/HrV2bgAAAF0FBZQAAABAF3ffW9s9xZP9woN0+fjeGhzVTUF+3iosq9SRrCJtSczR2kNZ9c5RXFap0AAfzRzSU6P7hKlvj0AF+XmrqKxS+1Lz9cG2FCVmF2nt4Wzd8vwGLblzuny8G+6E+PmeNC3dnqLQAF/dMmWARveu3uz9+mCm3tqYpMoqq99/uEeTB4ZrS+Jx/XXZPvUKC9C1k2I1LCZEpRVV+u+uVC3dkSprpZ+/vV2TB/ZQXGS3Btd9bmW8lu5IVWiAjxZO6aexfcNUWWW1IT5bb25MUmlFlT7emaY7X9ms526e1Myf9klPf3lYv3mvugOFr7fR+aNiNH1QhCJD/FVYVqH1h7P1zuZkFZdX6e7XtsrHy+jKCX1rzZGaW6LbXtykghOdBM4eFqmzhkUqJixAXsYop6hMB9IKtOpgpvakNLyx3lHYGnermtsXcs+xvEbn/snr21RcVqmh0d10z9whDjI8KaeoTN95Yo32pOQpt7hc3fx91KdHoCYPDNeCybEa27f7ac3fXHtSTn7/4/s1vHZ0aIB6dw/QseMlSs8vVVZBqSKaWPgMAAAAAN+479UNnuLJfhHBunxCPw2JCVWQn48KSyt0JLNAW45ka82B+h/cKi6rUGigr2YOjdaY2O7qGx6sID8fFZVVaF9Krt7ffFSJWYVaczBDNz/9td758TmN7znsStGHW5MUGuir7501UKP79pAkrdyXprfWJ6iyyup3727T5EGR2pyQpb9+uEO9ugfq2qkDNaxXmMrKK/XpzmNaujVJ1ko/e32jJg+KbLQr4LNfHtDSE+sunBansbE9VGWt1h/K1Jvr4qv3HLYn647n1+j522c286d90lPL9+k3i7dIkny9vXTBmN6aPiRKkaEBKiyt0LpDGXpnY6KKyyv1o5fWydvL6KpJA2rNkXq8WLc+u0oFJx7YPHtEjOaMiFFM9yB5meoHcven5mnV/jTtOZbrONf2Zu6o3vLz8VJZRZWWbkvSF7tTdPbIXqeMyyoo1Z/e3y5J8jJGPzh3uKP1lmw8ouKySknS+P7hGtG7e7vJDQAAoKuggBIAAADowjLyS7VsR4okaeKAHnr7jmn1djio7ixQVOd7D10zVrOGRNZ7PPQvLh6uB97ZqZdWH9H6+By9t/WYrvpWMeC3fbAtRaP7hOq126cqMuRk4dbVE/tq8sBw/fSN6uOFf7F4hw6mF+isoT313M2TFOx/8mPOgsmx+vNHe/TYZwdVWlGlZ1cm6I9Xjm5w3aU7UhUXGay375im3t1PHmN1zaRY3TJroK5+Yo2yCsr00Y5UvbM5WVec2afB+eqyKSFHv/1gt6TqotWXbp2s4TG1b7IsnNxPd5w9SNc8sVapeSX62ds7dPbwKPUI9vOMWbI52VM8+fvLR+m22fV3KdiXmq+Ibn71vt+YpJwi7Uhy54ZIoJ+35gyLanxgHWLCTnZbOJxRKGttg0e0HT5x3LckJR8vUWFpRa3fkZqeX5Wg1Yey5GWkR64947SPOy8srdTKAye7rOQUlSvn/7N314FxVWkbwJ8bd3fXJqk3qZd6C4UCBQoV3H2Bj4UVlmV3kYVdYHEtUJy2UIpVqGsqSSpJ07i762Qmk8nc749JJkkzmsw09vz+mmTOOfPOzA30nvve923rwPmyZnx2tBCrpgbgtTWT4WxnPajXMYRSKaKgq0qshYA+x7Y2IR4O6oqfudWtTKAkIiIiIiKj1LTIsONcGQBgergntj6+RPueg1RVzVCT12+egfkxvlrbQ//lmsn425bT+OJoLk7l1+KnlGLcODNMZ2y/nCnBxCA3bHp0Ebx7VfW7cWYYZkV64/++UbX6/vOmZORWNWNhrC823j+/757DnAj8+5dUvPX7BbQrlPjkYDb+vaZ/Bc3etp8tRYSPM7Y+thgB7g7q36+ZFY57FkVj9VsHUNfajh3nSvFjchFumB6qcz1Nkgtq8a9tZwGokla/enABYgP6ViBcPycCDy+LxU1vH0RlkxR/2pSMJeP94e7Yc973Y3KROnnyhRun4f7FMVpfM6uiaVDnjKX1EqSW9O+MMhAONpZYFNc/qdBQfm72+Pt1U/D3H86gUyli3XuHsGS8PxbE+MLPzR7N0g5kljdhy6kCtMoUcLCxwhu3ztTZxl2XbxN7OqDcMi9yWMVGRERENFYwgZKIiIiIaAwrrmuDsqug3+qEIJ3toZztrDEpSHPLn6VxutsBW1ta4N/XT8SBzGqU1EuxJalEbwKltaWAT+6Y3id5stvNs0Lw9t4cFNa1Ib28GR6ONvjo9gSNiXGPL4vGhsMFaJN39mlhrI2FAHx8e4LGBLM4fxf8b80U3PFZEgDg3f25A0qgfGVnJjqVIqwtBXx930yM89VcoWKcrzPeWj8Vaz86gdZ2Bb46XoTHelVFLKztaZt+y+wQna8Z46e7CoY+R3Pq8MSms4Nao1uQuz2S/75sQHMD3OwR4uGA4vo2NEo7sDu9CldM9NM4tk2uwM9ny/v8rlnaofE4Ka5vw0vbMwAAd80Lx/SwwbUd83G2xcIYb0wKdIWPiy1EUZWEui+jGify6wEAP58tR0GtBNsemas1qdNUJHIFFF1/7K721rDWU40FADx6Jes2SRU6RhIREREREfVXVNsKZVcXgRtnhunec7C3xqRgd43PLZ0QoPN1rC0t8O818difUYGSOgm2nCzQm0BpbWmBT++d1yd5stvNcyPw1u8XUFjbivSyRng62eLje+ZpPG97YsV4bDiQjTa5AvsvVOh8TUBVDXDD3XP7JE92iwtww/9umYk7PjoCAHh3d8aAEihf+TWta8/BAt88vADj/DTv5Yzzc8Xbt83CmncPolWmwJdH8/D4FePVzxfU9HSyuFVPYl/MIFtEH82qwuNfnxrUGt2CPRyQ/MK1g1rj/sUxCHBzwL+2nUVxnQT7L1T0+36tLS3wxIrxuG1eJII8HAf0OulljThbrNojcLCxwvUJuvd2LmVsRERERGPJ4MppEBERERHRiOZg03PxIrWk0ayvZWVpgfgQ1cWQ08WNfVoxa7J8vC/CvLRv8s6K8FQ/vml6ENwcNFdXdLCxwtRgNwBAYZ0Eso5Ona+7MMYbEwO1b/xfMdEPUT6quNLLm5Ffo7lChjbljVJ1VcLLJ/hpTZ7sHY+viyqJ9GBWTZ/n7Ht/fyaqDjkS3D635wLSn39QVSC9mFyhxOPfnUV1S3uf33dX7LzYHzefg6S9E4Hu9nhm5eBaW717yzSc/cdyvHPzNNy/MALXTQvE9fGB+MPSaPz06Dx8d/8suNmrqk6mljbh+a5qpOYkae857nVdtOyt9ziJls+NiIiIiIhIGwebnoTDc11JYuZiZWmB+DDVPsHpwnr9ew4TAxDmrf18fHaUt/rxTTPDdO85hKpuwCusbdW757Aozg8TtSSKAsCKyYGI6tonSC9rRH51i9axmpQ3tOFIVhUA4IpJAVqTJ7stjPODb1enh4MZlX2e6/39pZr5+xuOrpwSiH+vSdDalr2jU4nPD+fi4wPZer93bb45lqd+fG18MJwM7FBxKWIjIiIiGktYgZKIiIiIaAwb5+cMPxc7VDbL8N2pEnSKIm6ZFYLpYR6wtNDeFlmTJmkHtp0uw/7MamRWtKBeIodEroCmaxYtMgVaZAq42GvfGI4P1X5BAVBV+DN4bFcCoiiqKhDqSiBbMM5b63Pd5kd7I7daVf3xTHEjIryd9M7pdjyvTv3Y3sZS3UJdFydbK1ShHTkXJQouGOeFjw6pWj3dvTEZjy6JwtVT/BHi0b+SxWCtmxmMdTODTb7uQNw7PxzbUytwprgRlc0yLH/9EG5MCMKMcA/YWlsiv6YVW5JKUVArgZu9NUSojk8AGtt9f3W8SJ3U+t8bJw26GuTsXsm9miyO9cEnd07HjR8cBwB8c6IYT14+Dr4u/SufDCXj/gtARERERETUV4y/C/xc7VHZJMV3xwugVIq4ZW4kpkd4wtLCuBovTW1ybEsuwr4LFcgsb0K9pB2Sdm17Dh1okXXAxV5z0iMAJITrPm/z7nV+1p2YqY1P11hRBJrb5LBz7d/RotuCGN0dPFRj/JBbpUqcPF1YpzVJTpPEnJ7OG/Y2VthxrlTvHCdba1RBhpzK5r5xxPriw/1ZAIC7NxzDo8vjcPW0IIR4Gr4HYqh1cyKwbk6EydcdqNJ6Ce76+ChSSxrg72aPV9dNx+Lx/vBzs0dbuwJni+rxwb5MHMioxEf7s5CUX4tvHloADyPamLd3dOLH5CL1z/qqfF7K2IiIiIjGGiZQEhERERGNYZYWAv5702Tc+3ky5J1KbEkqxZakUjjaWmJaiDtmhLnjsmgvzInwhIWOhMrd6VV4YtNZ1EvkBr+2vgTK3u2DNbGx6rnY4mnEWJlCqXNshI6ql+ox3j1jKppkesf3VlLfpn78Q3IpfkjWfzGjW8NFn+/SOF/cEB+IH0+XoV4ix/O/XsDzv15AkLs9EkLdMSvCA0vjfBDqObraNdlZW+Kb+2bhoa9ScCi7FtIOJb46UYyvThT3GeftbIvP7pyOmzecVP/O9aJjrqxBqq4AeWNCoN529KZyWbQXFozzwuHsWiiUIvZnVmP9TP2tugbK0bYnadjQ6hPSXuPM3WKciIiIiIhGH0sLC7y6fjru+eQY5AolNp8sxOaThXC0tcK0UA/MiPDC/BhfzIny0b3nkFaGJ74+hbrWdq1jLqYvgdLDUXcymW2vfQR9iWe2ffYcdJ9vhRuQDBnu05OgWNkk1Tu+t5J6ifrx96cK8f2pQoPnNkj6fr5LJwTghumh+DG5CHWt7fjXtrP417azCPZwQHy4F2ZHemPJBH+EeZk+oXIoVTfLcOWre1DdLEOwpyN2PLVcnSQLAK4ONlgY54eFcX7486ZkfH4kF6cL6/DM9yn48K65Br/OjnOl6n2ecX4umBHhNWxiIyIiIhpreAWEiIiIiGiMu3yCL37/v/n4355s7E6vQrtCCUl7J47m1OJoTi3e2JMDPxc7PLYsCnfNC+tXwe90UQPu3pgEhVJV9iHGzxkLx3kh1NMRnk42sLG0QPeUT44U4FiuqgJjp552WhYaKgVqY8RQvXq3NTdkjLGtjZukA2+F3P0Z9/beLdOwMMYbHx/KR3q5qlpEaYMUpQ1S/Hy2HAAwL8oTz10zHlO6WpmPBh6ONtj84BzsuVCFrSmlSClqQG1LOywsBIR6OOLKSX64d344BEGVrAsANpYWcHfom0D51JZzaJEp4OFog3+tmnBJ38O8KFUCJQDkVBnXCt5YjjZWsLIQoFCKaJYpoOhUwspSd8WX3gnRrvbcPiAiIiIiIuNdPikQv//pcryxMx2/p5V17TkocDS7Gkezq/HGrgvwc7XH41eMx10LovrtOaQU1OGuj4/27Dn4u2JhrC/CvJzg4WQLWytLdfn8Tw5m41i2qgJjp4bz596MabphZIMOnQzbc+g5/2qVdRi1fnObceN707Tn8P6ds7Eozg8f7c9CelkjANWNoSX1xfg5RXUT47xxPvjH9VMxJcRjwK89nLyxKx3VzaqbZf96zaQ+CYoXe+76qdiWXIQmaQd+TinB8zdI4aOjAmlv3yTmqx/fbGD1zUsVGxEREdFYwysgRERERESEuAAXbLhjOtrkCpwuakRyYT1OFTTgeH4dpPJOVDbL8MyP53G+rBn/Wzulz9z/7MxUb7K/dP1E3DM/XOvrbD1dZtb3YQptcv3V+XqPMbYyX+9KgP9bMwU3zx5c1UFBELB2RjDWzghGeaMUpwrqkVKo+u7Ol6kSKo/l1uHqt4/iu/tn47Jo/RUNNCltaENaadOgYu1mb2OJRTE+Jllr+XhfLB+vvWrkgcye9mUTA136JA2W1LfhQFYNACDWzxlfHi/qN1+TN/Zkqx/fOjsU3s4Da4PVu3Jqs3TgF7kMYWEhINzLETnVrehUiihrlOqtTNq7Wmqkz+iqKEJERERERJfO+EA3bLh3HtrkCqQU1CG5oBZJebVIzK1W7Tk0SfHXLSlIK23AG7fM7DP3P7+lqvcc/n1TPO5ZNE7r6/yYZNg53VAybM+h58ZLJzvtnTs06b1H8b9bZuCWuYa1hdZGEASsnR2OtbPDUd7QhpN5NUgprMPxnGqcL20EABzLrsbK1/biu0cWYr4BLco1Ka2XILWkYVCxdnOwscSiOP8Bz9+T1rN3pW8dR1srzIjwwt70CihFEWeK63HFpEC9r1Fc14qj2VUAVF1TbpoVNmxiIyIiIhqLmEBJRERERERqDjZWuCzaS51kJ5V34tuTxXju53R0KkV8e7IYd84LxeQgNwBAR6dSXVFycpCrzuRJACiua9P5/HBQUCsxaoyfjrv9NQnodbd/ZmWzUXP1ru1mj+umBeK6aaoN8aK6Nvzj5/PYdb4KHZ0invspHfufXjigtY/m1OGJTWdNEmeQuz2S/77MJGvpsz+jJ4FyTqRnn+d619ZIzKtDYl6dQWv+Z2eW+vHy8b4DTqDsXeFRVzt7U4kLcEFOtarS5ZniRp0JlFXNMpQ1qqpaeDvbwktPyzoiIiIiIiJ9HGysMD/GV51kJ5Ur8G1iPv6+9YxqzyExH3fNj8LkrkqGHZ1KdUXJycHuOpMnAVVS2nBXWNOid0xBTc/78DOyYqC/e689h3LT3ATZLcDdAddPD8X100MBAEW1rXhu6xnsSi1DR6cSz209gwPPrBjQ2kezqvD416dMEmewhwOSX7h2wPMrm2Tqx4acqzv3GmNol5LvjheguzHLFZMC4eVs2N7SpYiNiIiIaCzS3a+LiIiIiIjGNHsbS9wzPxy3zQlV/+5EXr36cb1Erq4EEe6lu5pdZZNM3WJ6ODuUXaN3zJGutssAEB/qZtT6vZP4dp6v1NtWbDBCPR3w0e0JcOvaML9Q0YwmM1c6HE5aZQpsPV0KQNXm/ZZBVvs0tWO5PcdRlLf5KzwujvVWP97bK7FUk30Xep5fGmeaaqFERERERES92dtY4Z5F43D7ZT1VEo/n9pyT17e29+w5+DjrXKuyUaquiDicHcqs0jvmSK8x8WGeOkb2Nzeq5/xtZ2oZOpVKo+YbI9TLCR/fPRduDqruChfKGtHUJtcza/jrXcWzrF7/Tbalvbo3ePTqNKGNUili84kC9c+Gtu++FLERERERjVWsQElERERERHqFejqoH3d09my+O9j0tKPWV7nxtd+zzJosaCqHs2txobwZ4wNcND6/50KVuorfeH8XRBiZ+Bbu7YgZYe5IKmxASb0Unx4pwP0LDd8sN5atlSX8XO3Q2JU42fv7M8a6mcFYNzPYlKGZ3UvbM1AvUb3vqyb59/uuQjwcUPm/awxay+/JX9WPDZ2jS2JuLQ51JeJaWgh9khvN5cqJfnjGOg3SDiV+PVuOv14Zi0D3/tVMFJ1KbDiSr/75+mls8UVEREREROYT6tlzrqbos+fQcxmzoFp35cZXd6SNiD2HQ5mVSC9rxIRAN43P7zlfjpwq1c2n4wPdEKEncfRi4T7OmBHhhaT8WpTUSfDJwRw8sCRmsGFrZWttCT83ezR2JU4OeM9hTgTWGZFIaE5xAa7qRN4fThXhqZUTtY7Nr27B6UJVNwsLQcDkYA+96x/IqEBZgyqxMcjdAYvi/IZNbERERERjFStQEhERERGNYQcyq/HhwTw0SLRXCGiVKfB9Uqn654mBrurHznbWiPJRVZ5MLW3CT2fK+s0XRRHv7MvF1yeKTRi5+XQqRdz/ZXKftkjdsipb8OTmc+qfH1kS2W+MIZ69Og6WFgIA4PlfL2DjsUKIovYLPY1tcnx0KA+HL6qO+drvWdiXUaXzItGx3FpkVakuNPm72sFzlFQcOJFfp/V9yxVKvPRbBjYeKwQAeDha4+UbtF9UMKU39mQjo0J3pdUj2TW494tk9c/rZwbD3824tmwD4eZgg/sWqC5ItSuUePjr02iR9a1IKooi/vnLBWRUqI6Z2REeWBhj/uROIiIiIiIafQ5cqMCH+zLRIGnXOqZV1oEtpwrVP08Mclc/dra3RpSvKoEwtaQBP6X031cQRRHv7M7A18fy+z03HHUqRdz/6TFUNkr7PZdV0YT/69XG+pFlsQN6jb+vmtKz57DtLDYeztG75/Dh/iwcyqzs8/vXtp/HvvRynVUsj2VXIatC1Src380enk62A4p5OLlhek8Xlrd2X8DutP57XQBQ1STFvZ8cU+9NLJvoDw8D3v+3iT3H6ro54bDo+q6GQ2xEREREYxUrUBIRERERjWFVze345y8X8OJvGZgT6YmEUHeEejnAydYKTW0dyK5qwbYz5ahpUV3siA9xw/xorz5r3L8gAn/6IQ0A8NDXp7E9tQJzo7zg7mCN0gYpfjlbjtTSJvi62CLO3wUHs/S3yB5KKyf5YXtaJRb+9yDWzwrG5EBXdIoikgobsOVUCWQK1YWDKyb4YnVC0IBeY1aEJ164bgL+tu08FEoRf92ahs+OFODKSX6I8nGCvY0lWmQKFNVJcKa4Ecfz6tDRKeLdm6f1WedYbh1e+z0bnk42WDTOGxMCXeHrYgtLCwG1Le04mluLvReq0X2d5A9LoyAIhm/MD2d//iEN9RI5lsb5YHKQK7ycbCHt6ER2ZQt+PVeB4q42VS52Vvji7pnwcbG7JHH9dq4C/9mZhTh/Z8yN9EK0rxPcHFQt1EsbpNifUY3EvDr1+EmBLvjntRN0rvnBwTw0tfVNdGzu1Yr9w4N5cLGz7vP8X67SfKHt8WXROJBZjbSyZpwsqMfiVw/hltkhCPdyRG2rHNtOlyGlqAEA4GZvjVdvmmz4myciIiIiIuqlqkmKf/x4Fi/8dA5zon2QEO6JMC8nONlao1EqR3ZFE7YlF6OmRXUDY3yYJ+bH+PZZ44HFMXh6k+oGtAc3JmL7mRLMHecDd0dblNZL8HNKMVJLGuDraoe4ADcczKjsF8dwsnJqELafLcWCF3fg5rkRmBTsDqVSRFJ+HTafLICsoxMAcMWkQNw4M2xArzEryhsv3hiPZ75PgUIp4i+bU/DpwRxcOSUQ0X4usLe2QousA4W1rThTVIfjOTXo6FTivTtm91nnWE4VXt1xHp5OtlgU54eJQe7wcbGDlaUFapplOJpdhb3ny9V7Do9dPn5U7DncPDcC350owOnCOsgVStz+0REsifPHkgn+8HWxR5tcgTNFddiaVKQ+N3d3tMG/bpimZ2WgtkWG39PKAaiqQq6bbVzVTXPGRkRERDSWMYGSiIiIiGgM677JXaEUcSSnFkdyarWOnR3hgQ13TO93Z/ztc8OQVtqEr04UQxSBX89V4NdzFX3GBHvY47M7Z/RpCzxc3T0/HAFu9thwpAAfHtQc7/LxvvjwtoTBvc5l4Qh0s8dT36eipqUdOdWtyNmXq3W8rZUFPC6qHtn9VdS1yrH1dBm2ntZcecDKQsAfrxiHuy8LH1TMw01NSzs2nSrBplMlGp+fGuyG/62dorUduzllVLSoqzhqszo+EC+vngQnO92n5p8eKUBpQ//qJN0+O1rY73faEigdba3w7f2zce/nyThZUI/SBin+szOr37ggd3t8fHsCon2NaxdHRERERETUrXv/QKEUcSSrCkeyqrSOnR3pjU/um9d/z2F+FFJLGvDVsTyIIvDLmRL8cqbvOWCwpyM23ncZNhzof24z3NyzMBoB7g7YcCAbH+zTHO/yiQH46O45g3qdu7te56lvk1DTIkNOVTNydmvvlqDac+hbobA7GbKutR1bk4qwNalI41wrCwF/vGoi7l4YPaiYhwsrSwt898hC/OHLE9idpkoQ3XehAvsuVGgcH+XrjI/ummtQu/XvTxaq25wviPVFsKfjsImNiIiIaCxjAiURERER0Rh20/QgTAp0xbG8OhzPq0NWZTMqmmSQyjthb2OJAFd7TAl2xbVTA3H5BF+t67y6ZgqWjffFl8eLcKa4Ec3SDrg5WCPMyxFXTfLHbXNC4HxRhbzh7IXrJ2LpeB98dbwYZ4obUNsih7O9FSYHumLdrBCsmhpgkte5YqIfFsZ4Y2tKKfZnVCO1rAl1rXLIFUo421kh2MMB4wNccFmUF5ZP8IWrfd/P8Kt7ZyKpoAHHcmuRVNiAwloJ6iVydCpFONtZIcLbCfOiPLFuZjAivJ1MEvNw8crqSTiQWY1TBfUoaZCivrUdlhYW8HGxRXyIG1ZO9seKiX6XvPrFu7dMw8n8eqQUNSCrsgV1re2ob+uAUinCxd4aYZ4OmBnugTUzghHjNzQXMLydbfHTo3Px05ly/Hi6DOe7jjtneytEeDli5WR/3Do7VG9iJxERERERkS43zQzDxCB3JOZU43hONTIrmlDRKO3Zc3BzwJQQd6xKCMHlkwK1rvPazTOwbGIAvjqaizNF9Whqk8PN0QZhXk5YOTUYt82LhLP9yNlzePHGeCyb4I+vjubhdGEdalvb4WxnjcnB7lg/JwKrEkJM8jorJgdiUZwffjhViP0XKpBa0oC6lnbIFZ1wtrdGsIcjxge6YX6ML5ZPDICrQ9+bNr9+aAGS8mpxNLsKyQW1KKhpRX1ru2rPwd4aET7OmBftg/VzIkZdgp6bgw2+enABTubWYGtSEVIKa1Fa34ZWWQdsrCzh7WKLycEeuHJKIK6ZFgwbK0uD1v32eM+NurfMNa76pLljIyIiIhrLBLG7rjoRERER0QgnCIILgCZDx+f8e8WISuoj83l1VxZe350NANj68BzMi/LSM4OIxqoWWQein9llzBRXURS1l3ohIiIiojHH2P2L3NdWj6gEQerr1e1peG1HOgDgx8cXY9447TeoEpFmLdIORD211ZgpPBcnIiIig1kMdQBERERERERERERERERERERERERERJcaEyiJiIiIiIiIiIiIiIiIiIiIiIiIaMxhAiURERERERERERERERERERERERERjTlMoCQiIiIiIiIiIiIiIiIiIiIiIiKiMYcJlEREREREREREREREREREREREREQ05lgNdQBERERERERD7ekVMXh6RcxQh0FEREREREREo8zTKyfh6ZWThjoMIiIiIiLSghUoiYiIiIiIiIiIiIiIiIiIiIiIiGjMYQIlEREREREREREREREREREREREREY05TKAkIiIiIiIiIiIiIiIiIiIiIiIiojGHCZRERERERERERERERERERERERERENOZYDXUARERERERkuOL6Nsx8cR8AYM2MILy9ftoQRzS6Hcutxer3j2t87tSzSxHi4XCJIyIiUxj3zE40yxT9fv/muqlYNzN4CCIiIiIiIhp9iutaMeO53wAAa2eF4e3bZw9xRKPbsewq3PDWAY3PJT1/NUI8nS5xRER9RT+1Fc3Sjn6/f+vWmVg3J2IIIiIiIiJSYQIlERERERGRCYmiiIJaCVJLm5BW2oTU0iacL2tCQ5tqgzjI3R7Jf19m0FpN0g6cyKvD2ZJGnCtpQmlDGxraOtDYJoeNlQW8nWwxMcgVV030w9VTAmBjpbvJwGPfncGWpFKD38vWh+dgXpSXzjFKpYid5yvx05kynCluRF1rOywtLODvaod50V5YNzMYU4Pd9L6WKWPrnWhsiDmRntj2yFyDxw9Wq0yBtLLu46MRqaVNyKuRoFMpAjAuie98WRNSihpwrqQJGRXNqGuVo14iR7uiE8521oj0dsTsCE+smRGEaF9nnWtNf2EvShukRr+fP14+Dk+viOnzu02nSvDEprNGrwUAlf+7RufzR7JrsPV0GU4XNaCiSQapvBMONpYIdLdHfIg7VicEYq6e45aIiIiIiIi69jBqWpFa0oC0knqcK27A+dIGNEjkAIBgDwckv3Ctweu1yjqQVtKA1JIGpBbXI62kAbnVLerz3YEkypU3tOHzI7k4nFmJotpWtLYr4OFoiyhfZ1w9LRjrZofD3sbwS94SWQe+SszH9jMlyK9pQYu0A17OdpgQ5IbVM8KwKj4YgiAYFeNgmeNzq22RYfOJAhzIqERWRROa2uQQBAFuDjaI8XfBkgkBWDsrDO6OtnrXUipF7EwtxU/JxThTVIfalnZYWgrwd3XAZTE+WDc7AlNDPQb03omIiIiGAyZQEhERERERGWDV1ABcNy1A/bOXk43Gcf/85QI+OpRvktf87Vw5/rglVeNzHZ2dkLS3obCuDb+dq8Dru7Px3q3xBiUrmkpJfRvu/zIFZ4obL3pGiZzqVuRUt+LLxELctyAC/7hmPCwsLu0FiOGoWdqBmGd3QRRNs95tn5xCRZNM43P1ElUyZVJhA94/mId754fjuWvGw9LE30OYl+kqsYZ6al+rSdqBh746jf2Z1f2ea5Yp0FzRgoyKFnxzshiXT/DFe7dMg7Odtca13rs1HopOJQDgaE4dPj1aYJo3QERERERENAysSgjBdQkh6p+9nO00jvvnj2fx4f4sk7xms1SOcU//aLLzXQDYcCAbz/90FnKFss/vK5ukqGyS4mh2NT7an4WP756LySH6E/hOF9bh/k+PoaS+rc/vyxraUNbQht1p5fjiiA8+uXcePJ30Jxaagjk+t59SivGn75LQpKHaY/dndyizCm/uSsdr62fg6mnab+IsqZPgvk+P4UxRfd8nOoAcWTNyqprxxZE83L94HP5x/VSdez/v3zkHHd3n4llV+PRQzsDeIBEREZGJMYGSiIiIiIjIAFE+Trhykr/ecUpl3x1vextLRHg5Ir28eUCvayEAsX4umBLsiiB3B/i42MLNwRotMgUyypvxy7lyVDW3I69GgtXvJ2LXE/P1VhoEgFdvmqw1CbRbrJ/2dWpa2nHD+4koqVdVLPRxtsX6WcGI9XNBp1LEuZJGbEoqQYtMgY8O5UOuUOLl1ZMMes+Dja23eVGeuHd+uM4xHo66X8uURKDfRZEgd3vIFUpUt7QPaE13B2tMDXFDnL8LfJxt4eNsCwsLAeWNMhzJrsGBrBp0KkV8dCgfLTIF/rd2isZ1XlszGVJ5p97XO1/WjNd3ZwMAnO2ssHJy/7+Ly6I9sfGu6QbF/9L2DORWSwAA67VU3uxUirhlw0kkFzYAAGwsLXB9fCAmBbnCy8kGVc0ynMqvx87zlVCKwO70Ktz2ySn8+PBcjRdvlo/3VT9ukvZv5U1ERERERDSSRfs646opQXrHdYoa9jC8nZFe1mj0a4pi//PdYA8HtCuUqG7WfOOfLu/szsCLP59T/7x8YgCWTfCHh5MtKpuk2H6mFCfyalBQ04q17x7EL08uQ7Sfi9b1siubsP69Q2hsU1XXjA/zxA3TQ+HlbIuCmhZ8cywfpQ1tSMypxi3vH8K2J5YYVdlyoEz9ue1OK8NDG49D2bVojJ8LrpsegmAPRyiUIgprW7HlRAHKG6VokMhx36eJ2PTIQiyM8+u3VnWzDNe/tR8ldapzdh8XO6yfE4HYAFcolSLOFtdj0/ECtMg68OH+LNXez9oErbEtn9hzY3Jz1/dARERENBwwgZKIiIiIiMiExvk54/4F4ZgU5IpJQW6I9nFCWaPUqJbS3ZaN98X556/QmeD315WxePCr09idXgVJeyf+9esFfH3vLL1rL4zxRojHwCsHPvdTujp5cnaEB768ZyZc7Huq/d04PQgPLY7ETR8cR16NBBuPFWLFRD8sjPE2e2y9BbrbG5T4eqlYWQhYNTUAk4JcMTnIFZMCXeHuaGN0C/Nu3z0wG+N8nLRWeHh4cSQOZdXg9k9PoV2hxLcni3HbnFBMC3HrN3ZRjI9Br7kvo6cC5PXxgXDQcEEpyN0BQe76v8PyRinya1QXYiwtBKydoTmB8qczZerkSX9XO2x7ZC7CvBz7jHlgYSROFzXgxg+Oo03eiRP59dibUYXLJ/S/CERERERERETAOD8X3L94HCYHu2NSsAei/ZxR1tCGGc/9ZvRaVhYCViWEdK3ljsnB7nB3tMVjX57A5pOFRq2VXdmEl39VdeSwEAR8fPdcXBPf93zx/sUxeG9PBp7/6RzqJXL83zen8Nsfl2ld86lvk9TJk/csjMZLN8X3adV976JxuOX9wziVX4szRfV4b08mnlo50ai4B8KUnxsA/OPHs+rkyccuj8Mz107u15L8j1dOwONfncKPyUVQiiJe/PmcxgTK57aeVidPzo70xlcPzYeLfc8e1Y0zw/Dw0ljc+PYB5FW34LPDOVgxOVDjWkRERETDmcVQB0BERERERDSa3DYnFM9fNxE3TQ9GrJ/zoNol+7rY6a2O6GBjhdfXTFG/zsHMGnU7JHOpapbhp7NlAAA7Kwt8eFtCn+TJbgFu9nj3lnj1zy9tzzBrXCOBo60VPro9AY8uicKCcd5wH2T1y1g/Z72t0RfGeOPW2aHqn/dcqBrw60naFfjpTLn655tnhegYrd93J0vQXbR1caw3/N3sNY7b3ytp8w9Lo/olT3aLD3XHbXN63mtiXt2g4iMiIiIiIhrNbr8sCi/cGI+bZoUjNsAVlhYDv3TsaGeNj++ei0eXx2FhrB/cHQfeAvuTAzno7DpZvHthdL/kyW6PLI/Dsq6qhkn5tfg9rUzjuAMXKnAyrxYAEBfgiudXT+uXVOhib4MP7poDWyvVZ/De3kw0S81fJdGUn1tBdQvyq1sAAN7OdvjLNZP6vU8AsLGyxMtrE2DVtZ+QWtIAiaxvu++qJil+SikGANhZW+Kju+f2SZ7sFuDugPfunK3+uXfVUCIiIqKRghUoiYiIiIguolSKmPHiXpQ1ymBnZYHUf12uMTnsYvNfOYCc6lZYWgg489wy+LjYqZ/rVIo4lluLQ1k1OF3ciPyaVjRIOmBpoWofPDnIDVdO8sP18YGwthzcfU7TX9iL0gYpgtztkfx37XfeA8Cru7LUrXi3PjwH86K8tI5VdCqx9XQZfj9fiXOlTahvbYeFhQA/FzvMifTEbXNCMSXYbVCx08B4O9vC09EG1S3tUChF1Evk8O11/JnasZxadXuphTHe8HPV/lrTQtwQ5++MjIoWpJY2IaeqxaAW42RaMX5O6sc1A2gB1u2Xc+VobVe1vJ4Q4IKpg/ibF0URm5KK1T/foiMZs7a1p715pLeT1nEAEOXT83xbu/6W5EREREREI5lSKWL6c7+irKENdtaWSHt5lcYkp4td9vwO5FQ1w9JCwNkXr4WPa8/NTJ1KJY5mV+NwZiVOF9Yhr7oFDRI5LAUBHk62mBzijqumBOH66aGD38P4+y8oqW9DsIcDkl+4VufYV7en4bUd6QCAHx9fjHnjfLWOVXQqsTWpCLtSy5BaXI+67j0MV3vMifbG7ZdFYUqIx6BiJ/M5kt1z49+62eE6x948Jxx7z6tu9NuaVIQrJgX2G7MtuUj9+L7F42Cl5bgN8nDENdOC8UNSEdrkCvyeWoabZul+/eGk97lzmLeTzoRYNwcbeDrboqpJtUcgaVfA0a5n//NodlXP3k+sH/y03PAIANNCPREX4IqM8iakljQgp7JZZzt1IiIiouGGCZRERERERBexsBCwOiEIb+/LhUyhxC9ny3Frr4pmmpwuakBOdSsAYFGMd5/kSQC4+eMTOJRd239iJ1DWKENZYyV2nq/E+wfy8MU9MxDqqbm62lBJLW3EA1+eRkGtpN9zeTUS5NVI8M3JYtw9LxzPXzdhUFUXyXhN0g40dLWhsrG0gJuD/oTfwaho6knA652spk2UjxMyKlQVEPZcqGYC5RAoqG1TP/YeRHLtdyd7Eh4HW33ySE6tug28t7Mtlo/XfvHTy6mnAkd+rURnK/i8mlb14xg/HmtERERENLpZWAhYPSMUb+/OgKyjEz+fLsFt8yJ1zjldWIecqmYAwOI4vz7JkwCw/r1DOJSpuXJ9WUMbyhrasPNcGd7bm4kvHpiPMC/954WXUmpxPe7/LBEFvc4NuuVVtyCvugXfJObj7gXReOHGaYOqukjmUdHYcw4bpWcPIcq3J1Fv7/lyiKLYr+ri/guV6sfLJwToXG/pxAD8kKRKuNybXjGiEih7nzsX1bZCqRS1dq1oapOjrkWVcOnpZNtvr6CyUap+HG3AuXW0rwsyypsAAHvOlzOBkoiIiEYUJlASEREREWmwZkYw3t6XCwD4PrlUbwLl98mlfeZeTNrRCXsbS8yJ8MSUYFeEeDrAydYK7R1K5NdKsCO1ApmVLcisbMH6j09i9/8tgJPd8Pjn+qmCeqz96ASkclUlt1nhHlg23gfBHg5QKkVcqGjB5qQS1LS049OjBWhXdOK1NVOGOOqxQ65Q4i8/pKGjU1UWYPkEX9haWeqd9/SWc8itkaC2pR02VhbwdrZFfIgbrp4SgCsm+Gps8dRN7PVY1zhNLlQ0mzW2i53Kr8eKN46goFaCNrkCbg42iPR2xLwoL9w6O0Rry+jRJKWwAV8kFgIABAG4erL/gNbJqWrBqYIGAKrW7asT+lf1MMY3J3qSMddMD9JaAQQAVkzyw9bTqlZs7+zLwdI4H4R4OPQbd66kEV8dV13o8na2xY3TgwYVIxERERHRSLB2djje3p0BAPj+ZIHeBMrvTxaqH6/RkBwmlav2MOZG+WByiDtCvZzgZGuNdkUn8qtbsP1cKTLLm5BZ3oT17x3Cnj9fDic7897IZ6hTeTVY8+7Bnj2MSC8smxiAYA9HKEURF8qasPlEAWpaZPj0UA7aFZ14/eaZQxw19SPqH6KJpF2BojpJn6TemhYZalpUN4IGujv0Sxi+WHxoT2XS7oTAkSLcxxmxAa7ILG9CdbMMr+44jz+tnNhvH0XRqcSzP5yGoqtN+oNLY/qN6fsVGLn3U9ZofPBEREREQ2h4XJElIiIiIhpmonycEB/ihtPFjThVWI+iOonWqpAdnUr8fFaV2ONqb40rJvSvovbUFTFICHWHo63mf4I/fcU4vL0vFy/vyER+jQSfHMnHE8vHme4NDVCTtAMPfJkCqbwTdlYWeO/WeKy8KPnqBgCPLY3CXRuTcCy3Dl+fKMY1UwJ0VojTpU2uwKGsGhNEr7IwxhsONiP/1KdJ2oHEXFUVU1EEWtsVyK5qxc9ny9RV/CK8HfHCdRMMWq93RdR2hRItMgXyayT4IaUMEwNd8OFtCVqrS/r1qkqQV92/osfF8mt6KpfmVLWYNbaLFda1AXU9lStqWtpR09KOE/n1eHtfDp66IgaPLY0yOhF0OEopbEB110Whjk4R1c0yJObV4ff0KnQqRQgC8MxVsRgfMLAqEN+eLFE/vmqyP9wc9LcF1KZBIseu8z0VQPRVs7x6sj9WTvLD9rRKlDfKMP+VA7g+PhCTAl3h6WSDmpZ2nCyox47UCihFIMzTAZ/dNQOu9sPjIi4RERERkTlF+bogPswTpwvrcCq/FoW1rVqrQnZ0KvFTiuqmI1d7a1wxuf+NUU+tnIjp4V7a9zBWTsRbv1/Ay7+mIb+6BRsOZuP/Vhh2LmpOTW1y3P9ZomoPw9oS7985Gyun9r3JdfUM4PEr4nDnx0dxLLsaXx/Lx7XTQrAwzm9Ar9kmV+BgRqX+gQZaFOc3KvYwBsvX1R6Ftar9hvzqFkwIctc6Nq+67z5DTmVzn+M/r6rnRs5gD/0dXwI9HGEhCFCKIvKrWzRWtBzOXl03HeveOwRJuwL/25mOHedKsSo+BMEeDuhUiiisbcX3JwtR2qDaK3lkWSweXRbXbx2/XommedX6b4bt/T3kVOofT0RERDSc8F/gRERERERarJkRjNPFjRBFVYXJp66I0Thu74Uq1Es6AACrpgbAzrp/9b8F43QnEwqCgMeXRWN/RjVOFtRjS3LpsEig/Oxogbpd879vmNQvebKbi701NtwxHbNe2ocWmQIfHMwbcAJlbascd21MHnDMFzv17FKEeIz8U5+CWonWz8XZzgrXxwfibyvj9CaMOdhYYn60F6aFuCHYwwHWlhZdCYV12HW+Eh2dIs6XNePqt47il8fmYZyGVlmzInqqMRzMqkZ1s6xf2/puqaWNSC/v2ThvlirMGltv0b5OWBDtjRg/J7g52EDW0YmcqlbsSKtAXo0EHZ0iXt6RibIGKf5702Sda40Eb+zNxt4L1RqfmxLsiieXj8MVEwd2UbCjU4nvk3sSKAfbvntrSinaFUoAwOwID0TqSYgVBAEb7piO13dn45MjBWiSdmDTqRJsQkmfcd7OtvjTihhcPy1w2FTxJSIiIiK6FNbOCsPpwjqIIvDDyUI8tXKixnF7zpejXiIHAKxKCNG4h7EwVvd5gyAIeGLFBOy/UIGTebXYcrJwWCRQfnooBxVdbYf/vSa+X/JkNxd7G3xyzzzM/MdvaJF14P19mQNOoKxtkeGuj48OOOaLJT1/NUI8h1dL9KEwO8pbnUC5+WQhnteRQLnpeEGfn5va5H1+bmzrUD/2dLaFPtaWFnCxt0ZjmxwdnUq0tSvgOEwqrBpiZqQ3tj+1DE99m4TkgrquarFp/cZdlxCCh5bGYmqvipu9zYrs2dc7eKES1U1SrdU7U4vrkd6r6mSTVK5xHBEREdFwpb0/FhERERHRGHfdtADYdLWU7d2i+2Jbknqeu2mQ7WJnhKs2LfNrJOoLGkNp8ylVcpK3sy3WztR84aGbh6MNlsWpqm+eyKtDu6LT7PGRyowwDyyI9oKzluog3e6+LBxp/7ocX9wzE08sH4fVCUG4dmoA7pkfjg13TMfhPy3GeH9VdcJGaQfu+yIFSmX/vlnBHg5YEusDAJB2KPHgV6fRKuufGFnZJMMj35zp87vWds0JlKaKDQA8HGyw+8n5OPLnxXjphom4fW4Yrp0agDUzgvG3q+Nw5M+L8dw149FdQOLL40X4+Wy5zs9uJOv+24z1H1jlSQDYnV6F2lbVf5PCPB0wL8pzUDH1rmZpaDKmhYWAhxZF4q9XxcJJy7Fe09KO9/bn4ocU7f/NJiIiIiIaja6bHgobK9UexpZTBVrHbTnZ85ym9t3GmBGhSrDKr25BfWv7oNYyhc0nVO/N29kO62brfm8eTrZYNlF1k+iJ3Bq0d3APYzi5Y36U+vEnB7Ox46zmc7wP92fh97SyPr+TXLTvIGnvSaDUlDCsSe9x2vYxhrO4ADe8vCYBS8ZrvhEaAHacK8U7uy+gpE6i8flgT0cs7Zov7ejEAxuPo1XW0W9cZaMUj3xxos/vNO0REREREQ1nLMdARERERKSFm4MNlk/wxfbUChTVteFkfh1mRfRNGmqQyLEvQ1XxLcLbUZ0AqYlU3olfz5Vj94UqZJQ3o7qlHZJ2BbTkgKGiUQoPx4G3yB2syiaZqv0xAD8XW+xO19+SSt6VNClTKFFc14ZoPRUCNQnxcEDl/64xet5oNzXYTf25KJUiGtrkSC1twtfHi7A9rRL7M6uxONYbH96WoLUK5dRgN52vEe7tiM0PzsaiVw+irlWOrMoW/JZagWunBvQb+9L1E3HVW0fQ0NaBxLw6XPbKAaybGYxYf2d0KkWkljZh06kSNEk7EOLhgOJ61bGkremVKWNzsrPC5CDt61lYCHh4cSRaZB14Y08OAOD137OwSsNaI8nX985SP26TK1DaIMWBzGq8tz8Pr+/OxgcH8/DW+qm4Zorx7/Pbk8Xqx+tnhQyqfdmZ4kZcqFBVJXWxszI4nqM5tbj/yxTUS+SYFuKGx5ZGYUa4B1ztrVEvkeNoTi3e2JON3GoJ/rI1DWmlTXhtzeQR1WqNiIiIiGig3BxscPnEAPx2thRFtRKczK3BrKi+nSEaJO3Yl14BAIjwccaMCC+t60nlCvx6pgS708pxoawR1c2yrj0MzZsYFY1t8HDSX93PXCobpeqKhX5u9vg9Tf9NcvKuqviyjk4U10kQ7Wf8TWchnk6oem+d0fNIt/gwT9y7aBw+OZiNTqWIuz85issnBmLpBH94ONqiskmKHedKkJhTA0EAgjwc1YmApjgDHMmnkVK5Ak99m4Qfkopga2WB/1sxHtclhCLM2wlKUUROZTM2HS/A50dy8dvZUpzMq8U3Dy/AlJD+e5ov3RSP06/tQYNEjsScasx7fgfWzQlHrL+rau+npAGbjuer9n48HVHc/R2M4M+PiIiIxiYmUBIRERER6bB2RhC2p6ouLnyfXNovgXLbmTLIO1Ub7rqqT6YUNuCBr1JQ2iA1+LVbhvgO9+6ENwBIK2s2uq12Q1v/u9LJNCwsBHg62WJxrA8Wx/pg47FC/HVrGg5k1uDOz5Kw7ZG5A17b29kW980Pxys7swAAey5UaUxSDPd2xPcPzcE9nyejqK4Nlc0yvLk3p9+4KcGu+POKWNy84SQAwNVh4G2vDI3NUI8tjcaGwwVobVcgu6oVRXUShHo6Dni94cTBxgrjfJ0xztcZNyYE4fr3EpFd1Yr7v0zBlgesMX+ct/5FulQ0SnEwqwYAYGkhYO0M3dVo9fmuVzLm9fGBsLfRXwHkSHYN1n98EgqliOXjfbHxrumwsuxpquHrYofVCUFYMdEP17+XiNTSJnxzshhTQ9xw25zQQcVLRERERDRSrJkdjt+6KvVtOVXQL4FyW3KxOmnwpplhWtdJLqjFg58loqTXvoA+LRoq011KxXWt6sdpJQ1Gt9VukAx9BU3q6/nVU2FtKeDD/VkQReD3tLJ+1SZtrCzwwupp2H+hUp1A6erQ92ZkR9uefQiZgZVGpfKecdo6IAxHSqWI2z48giNZVbC2tMCWPyzC7CifPmOmhHhgSogHZkV544HPElHTIsM9nxxD4nNXwcaq7/l5uI8zfvjDYtz9yVEU1UpQ2STFm7su9HvdqSEe+PPVk7D+/UMAVAndRERERCPJyPkXHxERERHREFgS6wMvJxvUtsrxy9lyvHj9xD5tfLpbewsCcGOC5gTKkvo2rP3ohLrlT4iHAxbHeiPKxwleTrawsbKARded2T+dKVe3Eu7UVpryEmmSDu7iR0dXYimZ313zwvDr2XIk5tXheF4dDmXVYGGM4QlyF5sX5QVAlaSYU9WqddzEQFcc+tMibEkqwc60SqSXN6OxrQNOdpYY5+uMG+IDcfOsEOxOr1LP8XWxG3BcxsRmCHsbSySEuuFQdq16vdGSQNmbp5MtXlk9CTe8fxyiCPx3V5ZRCZSbkkrU/z1aEusDP9eBf4dtcgW2nem54GVo++7nfk6HQinCQgBeWT2pT/Jkb462Vnjx+om49p1jAICPD+czgZKIiIiIxoyl4/3h5WyL2pZ2/HK6BC/dlNBnD6O7fbcgaE+gLKmTYO27B9UteEM8HbFkvD8ifZ3h5WwHWysLdZX3n1KK8XOK6gYp7mGQqVlaWOCfN0zDmlnh+PJoLhKzq1HW2IYOhRJ+bvZYGOuHexeNQ4y/K744mqee53vROWvvLh2GtJpXdCrVCcFWFgIcRlAC5Y5zpTiSpdqDWTs7rF/yZG/XJYTgm8Q8HM6sQkmdBDvPlWFVQv9z9InB7jj87FXYcqIAO86VIr2sEY1tcjjZWiHG3xU3TA/FzXMjsLtX1VefQe79EBEREV1qI+dffEREREREQ8DK0gI3xAfi48MFaJYp8Ht6lbrNb251K84UNwIA5kZ6ItjDQeMab+3NUSdPPrw4Es+ujIOFheZeNqcKGkz/JnTQ1noLABx7VYW7MSEQ794SfylCQptcgUNd1e5MYWGMNxxsRv+pz9I4HyTm1QEAjuTUDiqB0tOpp1JAs54qInbWlrh9bhhunxumdUz33wmgv1W3KWMzbL2eFnPNg7zgNpzNifSEo60lJO2dSClqQJtcYdDfhSiK2HSqRP3zLbMNS3jU5tdzFWjpuhA7MdAFUww4Horr25BR0QIAiPZ1RqC7vc7xM8Lc1e81p6oVrTIFnOxG/38DiIiIiIisLC1ww/RQfHwgG83SDvye2pMQlVvVjDNF9QCAudE+CNZy89ibv6erkycfWRaLZ1dN0bqHkZRXa4Z3oZ2uJE3HXkluN84IxXt3zrkUIaFNrsDBjEqTrbcozm9M7GEYY3ygG15ZO13r821yBbIrmgCouiZMCu7bijrSt6c1e3eLaV1KG9rUx1qkj7M6YXgk2N2rQueiWH+94xfF+uFwpirh8nRhncYESqBr72d+FG6fH6V1rdNFderHU0M9tY4jIiIiGo74L3AiIiIiIj3WzAjGx4dVVRq2JJWoEyi3JJX0GaNNd+tbLycb/E1H8iTQt232QNlaqSqzdbfl0qVOItf6XIBbT5JSZmXLoOMyVG2r3Oh24bqcenYpQjxG/6mPc68EsaY27d+rIep7HRcudgNvud1tf2a1+vGcSA8dI/UzdWx91rMf/HrDlSAIcLSxgqS9E0oRaJEZlkB5LLcORXWq/y75ONtiWZz26hWG6N2+29Dqk1VNMvVjFwMSIQVBgJOt6r0CgETOBEoiIiIiGjvWzgrHxweyAagqTnYnRG0+UdBnjDaHupIBvZxt8bdVk3XvYdQNrisAAHXL4HYD9jDqWw3cw+hKprsUaltkRrcL1yXp+asR4ulksvXGgoMZlVB0JTxODnbvk0wLqKohdldmLWtoQ3WTFD6u2m/MO13YkwgYG+hmlpjNpbJJqn5syB6Hc68xkq6bvwdqf3qF+vHc6IHf1EtEREQ0FDT3vCIiIiIiIrWJga6I83cGABzKqkFNSztEUcTW06q7uh1sLHH1ZO13dVc3q9oDhXg4wFLHhQepvBOJuYOv3uDmoKrQVy+Ro13RqXNsso6Kl2FejghwU7XcOV/WjIIa/Xfp09DJr+35fnpXVRyIY7k9FwuifAbX0jq5sB7p5c0AgEB3eyyKGVwCniljk3WoqjH2rDd6L1I1SzvUCdOCALg72OiZofLNiZ6ExzUzgrW2zjZEXnUrTuSrKt7YWVlgdUKQQfN6X/wqa5TqGKnSJlf0SYx1cxi9ibFERERERBebGOyOuABXAKrEsupmGURRxI9JRQAABxsrXD1V+7/Fq5pVNzCFeDrB0kL7v/+lcgWO5VRrfd5Qbo5dexit7Wjv0L2HkVSgfc8kzNtZnUR5vrQRBdWX7kZQGlpfHMlVP751XqTGMUvG9+zb7e2V6KfJvvM9raiXTdBfxXE4cbTtOf8tbTCg2mavG7ndHQ3bJ9AkKb8W6WWNAIAgdwcsivMb8FpEREREQ4ElGIiIiIiIDLBmRjD+9csFKJQifjxdigkBrihrUCXyXDXZv9/d7b052FhCLlWisE4CURS1tv75+HA+GtoG30I4xs8ZKUUNUChFJObWYXGs5oS1w9k1uFDRrHOtm6YH4a29qo3o53+9gM/umm721kUhHg6o/N81Zn2N0aZVpsC20z1tmmaEuw94rdrWdmw4nK/+edl43wGv1a7oxDM/nlf//PCiSJ1JxJcyNgB4b3+eup10lI8jwrwGl5A5nH19oljdgmxqsBtsrPQnQja2ybEzrefC0s2ztFfaNcS3vapPrpzsD1cDK36GeTnAzsoCMoUS5Y0yJObWYm6Ul9bxP50pR0en6r2O93eBbVdFGyIiIiKisWLtrHD8c9tZ1R5GchEmBLqhtEGVKLVyahAcdVTzd7CxglwhR2FNi849jI/2Z6FBR1cLQ8X4uyKloE61h5FTjcXjNSesHcqsxIWuBC1tbpoVjrd+vwAA+NdPZ7HxvsvMv4fh6YSq99aZ9TVIu19Pl6hbqAe6O+CGGaEax12fEIotJwsBAB8fyMKaWWEabxAsa5Dg1zOqjjP2Npa4YlKgeQI3k7gAV+w4VwoA+OFUEW6ZqzmhFAA6OpX4OaXnPH3aANtut3d04m/fp6h/fnhZrM7kayIiIqLhiP96ISIiIiIywOr4QHXi1/fJpdiS3NO+e+103VXUpoW4AQDqJR14d3+exjHfJ5fg1V1ZJol1aa8Wuy/vyNTYgudCeTMe/eaM3rUeWhQJH2dVNcOd5yvxxy2paJNrb+kjVyjxy9lyfHa0QOsYMoykXYGXfstATUu7znGVTTLc9ukpVHVVOo32ccKCcf1bJW1OKsH+jGqIoqh1raK6Nqz/6ARqu9qiRfs44ZopARrHSuWdOF2kvYJpbWs77vwsCamlqtZpsyM8cNe8MI1jTRmbpF2Bl3fo/txEUcRHh/Lw+u6ev7knl4/TOn642nSqBPsyqqBUav/cuse9vCND/fM9l2lv19fb1pQyyLra6M2J9ESE98ArdCo6lfg+uVT9882zDWvfDagu4K6Y1FO94rHvziK/RnOrwOTCevzz53T1z2tmGFblkoiIiIhoNFk9I7RnD+NkAb4/2XOOvmZWmM6500I9AKi6Wry7J1PjmO9PFuDV7ec1Pmes3hX+/v1LqsY9jPSyRjz6xQm9az28LBY+LqpOGjvPleHJb5P07GF04pfTxfjsUM4AIidzSy2uR4tU+43GP6cU49Eve46LN26ZCQcbzTc4L5ngjxkRqhvxMsqb8M9tZ/vtQbRIO/DgZ8fV7eQfXhoLVwO7NwwXqxJCYNGVNJyYU42Xf03VuNciV3Tiia9OorBWdW7t42KHReP7V42UyhVIKajr9/tutS0y3PnxUZwrVu0PzY70xl0Lok3xVoiIiIguKVagJCIiIiIygI+LHRbFeGNfRjXOlzUju1K1wRjoZod5OiqhAcD9CyNwIKsGAPDS9gwcy63FsjgfeLvYoapJhp3nK3E8rw6OtpZYEeuD387pbiWkz+UTfDHO1wnZVa1ILW3CstcP49bZIQj2cECrTIHEvFr8fLYc1pYWWDHRF7vOV2ldy83BBp/fPQM3fXgckvZOfHuyGLvOV+KaKf6YHOQKF3tryDo6UdEoQ2pZEw5n1aBZpsDNswxPjhptmqQd+OBA30TZZlnPhn+ztAOv7Oh7ESrEw6FfQplCKeKd/bl4/2AeZoS5IyHUHRHejnC2s4ZSFFHZJENKUQP2XqiCtEO1ue9iZ4V3bpkGaw1VFM6XNmHDkQL4udhhYYw3xgc4w9vJFlaWFqhtbcfJ/HrsTKuEvFO1lqu9NT6+I0Frxcg2uQJXvXUU0b5OWBzjjVg/FzjbW6GprQOnixvx27lyNHdVd4zzd8aGO6bDQstapoxNoRTx1t5cvLs/D7PCPZAQ6o5wL0c421tB1tGJ3OpWbE+tQG51TyurW2aF4AYd7aSP5dZi9fvHAQBB7vZI/vsyrWMNsT21AmldiaU9n0FPNdgdaRUorO3bamv9rBCEejr0+V16mepz83WxxYJx3hgf4AIfZ1vYWlmgpV2B3KpW7LlQheyqnmTDGxMCcaOepO9u353qqUQx2OqTey5UoborqTXcyxFzI42rbPHMyjgczq5FvUSO0gYplr52CNdODcSscA8421uhXiLHkZxa7EyrVFfanBLsirsuCxtU3EREREREI5GPqz0Wx/lhb3oFzpc2IrtSdb4R6O6Ay8bpruT/wJIYHOiq6Pfiz+dwNLsKyyYEwMfFDpVNUuxKLUViTg0cba1w5Xh/dbW+gbp8UiBi/FyQVdmM1JIGLH15F26bF4lgT0e0yDqQmF2Nn0+XqPYwJgdiV2qZ1rXcHGzw+f3zcdM7ByBpV+DbxHz8nlqGa6YFY1KwO1ztbSDrUKC8UYq0kgYcyqxEs7QDN8+NGNR7GMma2uR4f1/fPYrmXkmLTdIOvPxrap/nQzwdtVY23H62BKklfW+2TCtt7Hn+XCkKavveEHfznAiEevW/Ye+74wX47kQ+FsX5YXq4FwLdHaAURZTWt2FXahlOF6oS+wQB+PdNCViop2306zfPwDWv70WTtAMbDmTjdGEdbpgeCk8nWxTUtOLbxDyUdLW0nhrigUcvj9O61rHsKtzw1gEAQLCHA5JfuFbna+tjqs8txt8VDywZhw/2qW4YfXPXBexOK8eq+GCEeTtDKYrIrmjC1qQiFNep9h26Pz9Nyadt8k5c9doejPNzwaI4P8QGuMLFzgaNUjlOF9bhtzMl6uMlLsAVG+6dp3Xvh4iIiGg4YwIlEREREZGB1swIxr6MagBQJ3LdOD1I78bg4lgf/OXKGPxnVxZEETiYVYODXQmV3TwcbfDBrfE4VVCP3zC4BEprSwt8fMd0rPngOKpb2lFQK8ELv2X0GePhaI0Pb0vAyfx6nQmUABAf6o5dT8zHw1+fRlpZM+olcnyRWKR1vCAAfq52g3oPI1mTtANv7tVevaJZpuj3/JxIT60V+TqVIk7k1+NEfr3O100IdcdrayYjzt9F57jKZhk2J+m+wDU12A3v3DwV0b7OOscBQE5VK3KqNFcDBIDrpgXg5Rsmwd1Rf9UGU8bWqRSRmFeHxDztlRJsrSzw1BXj8MjiKL2xmdLv6ZXYklSq9fnd6VXYnd7373L+OK9+CZTdqprb+1R31MTe2gKPL4vGY0sNqwRxrqQR58tUF1ld7a1x9WTNlUgN9e3Jnu91/cxgo9vohXg44IeH5uDBr1KQXdUKaYcSm5NKtB4vS+N88M7N09i+m4iIiIjGrDWzwrE3XbW/IO+qqHfjzDD9exjj/fGXaybhP7+lqfYwMirVLZK7eTrZ4oM75+BUfg1+1d/cQidrSwt8fM883PTOAVQ3y1BQ04rnfzrXZ4yHow0+vHsuTuXV6EygBICEcE/8/qfL8dDnx5FW0oC61nZ8fiRX63hBAPxd7Qf3JkawJqkcb+66oPX5ZmlHv+fnRntrTaD8PbUMm7taZWuyO60cu9PK+/xuQYyvxgRKQNX9Yue5Muw8p/l793O1x0s3xePqafpv+ovxd8U3Dy/Eg58lorShDSkFdRqrK86J8saGe+dprWZpDqb83P5x/VTYWFni3T0Z6FSKuFDWiAtljRrXdbG3xn/XTcc18bo/v+zKZnUitibXJYTglbUJcHe01bkOERER0XDFBEoiIiIiIgOtmOgLV3trNPW6E/+m6YZVZXti+TjMjvTEhsMFSC6sR71EDmc7KwS5O+DyCb64Y24YvJ1tcapAd5KcoWL9nHHg6YX48GA+dl+oQnF9GywEINDNHpdP8MO988Ph52qHk3qS8rpF+zpjzx8XYu+FKmxPrUByUQOqm9vR2q6Ag40l/FzsMM7PGXMiPLB8gp/WRC8ynKu9NU48swSJeXU4kV+H7MpW1LS2o761HUoRcLazQqinI6YEu2LlZH/MjfTUmZT28OJITAl2w+niBqSVNqG6pR0NEjna5J1wtrOCv6s94kPdcM2UACwY56U3wc3NwQYf3Z6AxNxanCluRFWzTH1c+7rYYX60F66PD1K3sNfFlLE521ph68NzcLqoEWeKG5BfI0G9RI7Gtg5YWgpwd7BGjJ8zLovywtqZwfBy0r+5L5V3qh97Og2f9l1/XRmLyyf44nh+PVIK61HeJENdazuapKq/S09HG8T5u2BetBeumxZg0Hvt9u3JnuqT18cHwt5m4ImIlU0y7M9UJZ9bWghYO3Ng1SzHB7hg31MLsSOtEjtSK5BW1oTq5nZIOzrhaGOJADd7JIS644aEQL2VgYmIiIiIRrsVkwP77WHoa9/d7f9WTFAlkR3IRlJBLepbu/YwPBxxxaRA3D4/Cj4udjiVX6N/MQPEBrji4N+uxAf7MrE7rRzFda2wEAQEuTtg+aRA3LdoHPzc7HEqz7DXi/Zzwd6/XIG958vx29kSpBTUoapJ2rWHYQU/V3vE+LtgdpQPLp8UoDV5j4bWvYuiEejhgOM51cirbkFNiwyKThFeTraI8XfFiimBWD09FI521gavOSPCC4eevRJfHc3D9nOlyK9uQYusA55OtpgY5I4bZoTi+oQQvXsiffcJhtdNxIIg4JlrJ2P97HBsOlmA4znVyK1SvU8BgJujDeIC3LA4zg9rZoXDQ8degZuDNT6+ey4Sc6pxurAOVc1S9X8PfF3tMT/GFzfMCMW0UOO6TBARERENN4IoikMdAxERERGRSQiC4AKgSe/ALjn/XgFnIzZZaezp3br5j5ePw9MrYoY4IhoKL/x6Ae91tWX/7M7puGqy/xBHRKa06VQJnth0FgDw5rqpWKcnwbNF1oHoZ3YZ8xKuoihqL9VBRERERGOOsfsXua+thrM99y9It95tpZ+6agKeXjlpiCMavV746Sze3aNqfb7xvstw1dSgIY5o5Nl0PB+Pf30KAPDWrTOxbk6EzvEt0g5EPbXVmJfguTgREREZzGKoAyAiIiIiIiIazg5lq6qcxIe4MXmSiIiIiIiIaIzrbmsfH+bJ5EkiIiKiUYAtvImIiIiIiAzw+u5svL47W/3zqWeXIsSDrcpHu9rWdqSXqwoW/O3quCGOhkxl3DM70SxTDHUYREREREREZvHajnS8tiNd/XPS81cjxJOtyk2htkWG9LJGAMCzqyYPbTAjTPRTW9Es7RjqMIiIiIj6YQVKIiIiIiIiIi2OZNdCFIHFMd6YF+U11OEQERERERER0RA6nFWl2ieI88O8cb5DHQ4RERERmQArUBIREREREWkR6+eMjXdN1/icl5PNJY6GhsL18YG4Pj5wqMMgE3vv1ngoOpX9fj8pyHUIoiEiIiIiIhq82AA3bLz/Mo3PeTnbXeJoRq8bpofihumhQx3GiPT+nXPQoeFcfHKw+xBEQ0RERNSDCZRERERERERaeDrZ4spJ/kMdBhGZ2PLxrBJCRERERESji6eTLa6aEjTUYRBptXxiwFCHQERERKQRW3gTERERERERERERERERERERERER0ZjDBEoiIiIiIiIiIiIiIiIiIiIiIiIiGnOYQElEREREREREREREREREREREREREYw4TKImIiIiIiIiIiIiIiIiIiIiIiIhozLEa6gCIiIiIiGh0Kq5vw8wX9wEA1swIwtvrpw1xRESkDf9eiYiIiIjInIrrWjHjud8AAGtnheHt22cPcUREpA3/XomIiGisYQIlERERERHRGLXpVAme2HRW/bOviy2OP7MEDja6TxV7z3t0SRSevTrOjFGqXq+kvg0A8PSKGL3jX92Vhdd3Zxv1Gm+um4p1M4MHFB8RERERERHRSLfpeD4e//qU+mdfVzuc+OfV+vcIes17dHkc/n7dFLPHWVIvAQA8vXKS3vGvbk/DazvSjXqNt26diXVzIgYUHxERERGNPGzhTURERERERACAquZ2fHwof6jD6GdzUgle351tdFIkEREREREREQ1MVZMMH+3PGuow+tl8sgCv7Ug3OimSiIiIiEgbVqAkIiIiIiIitfcO5OG2OaHwdLId6lBMYtXUAFw3LUDvuElBrpcgGiIiIiIiIqKR4709mbj9sqjRs0eQEILrEkL0jpsc7H4JoiEiIiKi4YIJlERERERERAQHG0u0yTvRIlPgzT05eOH6iUMdkklE+Tjhykn+Qx0GERERERER0YjhYGOFNrkCLbIOvLErHS/eGD/UIZlEtK8zrpoSNNRhEBEREdEwwxbeREREREREhJumB8HD0RoA8EViEYrq2oY4IiIiIiIiIiIaCmtmhcHD0QYA8MWRXBTVtg5xRERERERE5sMKlEREREREpJNSKWJHWgV2na9ESlEjalvbIZV3wtXBGlHeTpgd6YFrpwRgQuDAWiDn17Riz4UqnMyvR2ZlCyqbZJArlHCxt0aEtyPmR3vhjrlh8HO107tWRnkzvj5RjJMFdSiua0ObvBMu9lbwdLSFv5sd5kZ6YmGMD6aFuJll/kjmbGeNJ5aNw3M/p0PeqcR/dmbi/VtNU2Fiz4UqbDtdhuTCBtS0tsNCAHyc7TArwgNrZwRjTqSnxnnXv5eI43l1fX7n9+Sv/cbNifTEtkfmmiTWTadK8MSmswCAN9dNxbqZwThf1oSvjhfhWG4tKpva0dquwPOrJuD+hRHqeaY6jrvfnyHv6bHvzmBLUikA4NSzSxHi4aB17NGcWnyRWIikggbUS+TwdLLB+AAX3DwrBCsns0InEREREREZRqkUseNcKXaeK0VKYR1qW9ohlSvg6mCDKF9nzI7ywar4YEwIGlgL5PzqFuw+X46TuTXIrGhCZaMUckUnXB1sEO7thPkxvrhzfjT83Oz1rnWhrBFfH8vDybwaFNdJ0NaugIu9NTyd7ODvbo+50T5YFOeHaaGaz0kHO38kc7KzxhMrJuC5rWcgVyjxyq9p+OCuOSZZe8/5cvyYVITkglrUtMhgIQjwcbHDrEhvrJsdjjnRPhrnXf/mPiTm1PT5ne8jm/qNmxvtjW1PLDVJrJuO5+Pxr08BAN66dSbWzYnA+ZIGfHUsD0ezq1DZJEWrTIHnV0/DA0ti1PNMdRx3vz9D3tNjX57A5pOFAICk569GiKeT1rFHs6vwxeFcnMqvRb2kHZ5OtpgQ6Iab50Zg5dRgQz4aIiIiolGFCZRERERERKRVZmULHvgyBVmVLf2eq2uVo661HicL6vHW3lxkv7QCLvbWRq3/Y0opHv7mjMbn6iVy1EvkSC5swAcH8vDfmyZjzQztm7hv7snGf3dlQSlevE4H6iUdyKluxeHsWry9Lxf5r1xl8vmjwZ3zwrDhSD5K6qXYdqYMDy2KxKSggSXGAkCDRI77v0zBkZzafs8VtEtQUCvBplMlWDU1AG+umwp7G8vBhG8W7x/Iw7+3Z0Bx8YHRiymPY1MTRRHPbkvHp0cL+vy+okmGiiYZ9mVUY9XUAPzlythLFhMREREREY1MmeVNuP+zRGRVNPV7rq61HXWt7TiZV4u3fr+AnNdugIu9jVHrb00qxMOfn9D4XPf6yQV1+GBfFl5dPx1rZoVrXeuNXen472/noRT7nst1n6PlVDXjcGYV3v49AwVv3Gjy+aPBXQuisOFgNkrqJNiWUoSHl8ViUvDAEmMBoEHSjvs+TcSRrKp+zxXUtKKgphWbThRgVUII3rp1Juxtht9l7Pf3ZuKln8/p3CMw5XFsaqIo4m/fn8anh3L6/L6iUYqKRin2pldgVUII/nr1pEsWExEREdFwMPz+5UlERERERMPC2ZJGrH4/EZL2TgCAt7Mtrp0SgIlBLnC0sUJjmxzny5uxL6MaZQ1SaN861k7aoVp7vL8LZkd6INrXGe4O1hAEAdXNMhzPq8Pv6VWQKZR4fNNZeDrZYGmcb791dqdX4ZWdWQAAOysLXDM1ANPD3OHhaANFp4ialnaklzfjSE4NGts6TD5/tLCxssCfV8Ti0W/PQBSBF3+7gM0PDqzChFTeiRveT0RGhSr51tXeGutmBmNSoCuUoojTxY3YnFQCqbwTP58tR71Ejs0PzIaFhaBe4y9XxqBeIscrO7PUSbwb75re77W624qZ2q/nyrEvoxoONpa4eXoQ4kPcYWdtgbxqCQLceipJmuo4NocXfstQJ09aCMA1UwKwcJw3HGwtkVnRgu9OFePns+U6L/4QERERERGdLarHDW/th6RdAQDwdrbDtfHBmBTsDkdbKzRK5Dhf2oh96eUobWiDOIBTDKm869wq0A2zo7wxzs8Fbg42sBAEVDVLcTynBr+nlUHW0YnHvjoJTydbLJ0Q0G+d3WlleOXXNACAnbUlro0PxvRwL3g42qJDqURNswwXyhpxOLNS8x7BIOePFjZWlvjL1ZPwyBcnIIrACz+dxZY/LB7QWlK5Ate/uR8Z5arkW1d7a6ybE4HJwe6qPYLCOmw6UaDaI0gpRn1rO7Y8uqjvHsHVk1Enaccrv6apk3g33n9Zv9fydLQdUIz6/HqmBHvTK+BgY4VbZoYhPswDttaWyK9uQaB7T0cIUx3H5vDCT+fUyZMWgoBr4oOxMNYXDjZWyKxownfH8/FzSjE6O5WXJB4iIiKi4YIJlERERERE1I+kXYF7NiapkydvTAjEf26cDEfb/qcQoihib0Y1bK0sjH6d6WEeSPzrYkR4a24rdN+CCKSWNmL9xydR1yrHcz+lY0msDwRB6DPuy+OFAAArCwE//2EepgS7aVxPFEWcyK/v9/vBzjdGamkjyhqkg1qjW6C7PSYHuZlkrW6rEwLx4aE8nC9rxqHsWhzJrsH8cd5Gr/PS9gx18mSMnzO2PDgbvi49SYdrZgTjgQURuPGDRJQ1ynAkpxYfHMzDI0ui1GNmRajaoH18uKd64pWTLl276X0Z1Qj3csTmB2frbI9tquPY1E4XNeDDg3kAVInBn98zA4tierVCmwY8tDgSt2w4ie2pFWaNhYiIiIiIRi6JrAN3bziqTp68cUYo/rt+hvY9gvQK2Fob32FgRoQXjv9jJSJ8nDU+f//iGKQW12Pde4dQ19qOv/9wBkvG+/c7t/riqOo8yMpCwC9PLsWUEA+N64miiBO5Nf1+P9j5xkgtrkdpQ9ug1ugW5O6AyVpiHajVM0Lxwb5MnC9txKHMKhzOrMSCWD+j13nx51R18mSMvyu+/8Mi+Lr2tK9eMyscDyyOweq3D6CsoQ1Hsqrwwb5MPLI8Tj1mVpRqb2LDgSz1766aEjTQt2a0vekVCPd2wpY/LNLZHttUx7GpnS5UVb0EVInBXzxwGRbF9d1jeXhpLG5+/xB+O1tq1liIiIiIhhsmUBIRERERUT+fHytEWaMMADA/2gtvr5/W567/3gRBwPLxA6umF+OneTO5t8lBbvjbVXF4css55NVIkFzYgBnhfS8IFNZKAAATA121Jj92xzon0rPf7wc73xifHCnAliTTbESvmRGEt9dPM8la3QRBwN9WxmH9xycBqCoY/v5/XkZt5NdL5PjmRBEAwNbKAp/dOb1P8mS3cG9HfHBbAla9ewyiCHx4KB/3LgiHrZXpWnm/vjsbr+/O1jnm+VUTcP/CCI3PfXBbvM7kScB0x7GpfXAwT92S/ukVMX2TJ7u42lvjkzumY94r+9UJ00RERERERL19fiQXZV1JfvNjfPHO7bN17xFMHFg1vRh/V71jJod44G+rJuPJb5KQV92C5II6zIjw6jOmsEZ1M9/EYHetyY/dsc6J7n+eNNj5xvjkYDY2nywc1Brd1s4Kw9u3zzbJWt0EQcCzq6Zg3XuHAKgqGO7+s69xewSt7fjmmCop1dbKAhvvm9cnebJbuI8zPrxrDq59Yx9EEfhgXxbuXTRuQMm42ry2Ix2v7UjXOeb51dPwwJIYjc99eNdcncmTgOmOY1P7YG+muiX9n1ZO7Jc8CQCuDjb49N7LMPf57eqEaSIiIqKxwPgSMURERERENOp9n9yT4Pfs1XFaL4xcKjPC3dWPk4sa+j3vYKO6N6yoToJmqfHtswY7f7RZHOuD+dGqjfvU0ib8dKbcqPl7L1RB2qFq93T1ZH9E+mi/uDAz3ANzuipN1rS04+QgK3ya0qxwD0zVkVBrLH3HsSnJFUrsTq8CADjYWOLOeWFax/q52mF1/KWr2kFERERERCPLllOF6sd/v27KkO8RzIzo6ZKQnF/b73n1OX5tK5qlcqPXH+z80WbxeH/Mj1HdOJta0oBtKcVGzd+bXg5ph+qGvaunBSPS10Xr2JmR3pgTpUpKrWmR4UTe4Cp8mtKsSC9MDTXdjZD6jmNTkis68XtaGQDV8X3ngmitY/3c7LF6RqhZ4yEiIiIabliBkoiIiIiI+mhskyOrSlVtIcDNTmdFRlNJLqzHj6fLcKa4EUV1bWiVKSDvVGocW9HYv/31/GgvpJY2oaGtA6vePYZHl0RhaZwP3BxsDHr9wc43xtvrp5m8aqQ5PHt1HFa8eQSiCLyyMxMrJ/vDxsA27Sm9kgMXxepv/70kzgeJeXXquQsG0DJcm1VTA3DdNN3VT+L8NV+8mRVh3IWRwR7HppRe3ox2heq1p4e5a2yt19v8cV748niRWWMiIiIiIqKRp7FNjqwKVevlADd7nRUZTSUpvxY/JhfhTGEdiuskaJF1QK7QfG5V3ti//fWCWF+kljSgQSLHtf/bh0eXx2HZxACDz/EHO98Yb98+2+RVI83h79dNwRX/3a3aI/g1FVdPDYKNgd0jUgrq1I8Xx+lv/710gj8Sc6rVcxcOoGW4NqsSQnBdQojOMeMDNFeQnBVp3F7FYI9jU0ova+zZI4jw1LtHsCDGD192tbInIiIiGguYQElERERERH1UNMrQ1dEHMb76WxMPhqRdgce+O4vtqRUGz2mR9W8h9IelUdibUY2syhZkVLTgkW/OwEJQtVZOCHXHnEhPnQmRg50/Gk0JdsOqqQH46Uw5iura8GViIe5doLnN9cWqm9vVjyO9dbe2Uo1xVD+ubJIZH6wOUT5OuHJS/7ZUhghw699STBNTHcemVNnUk6AZ7uWoY6RKhAFjiIiIiIho7ClvaOvZIzCgNfFgSNoVeOzLE/jtbKn+wV1aZP27SPzh8vHYc74CWRVNyChvwiNfnICFICDG3wUJ4Z6YE+WjMyFysPNHoykhHlgVH4KfUopRVCvBF0fycN/icQbNrWruOT/VVX2yW4RPz15UVZNpbz6M9nXGVVMG1oEh0N3BoHGmOo5NqfdNnBHe+vf6InR0EiEiIiIajZhASUREREREfbS09yR2Oei5I32wHvr6tLrNsL21BZbE+WJykCv8XO1gb20Ja0tVW7DaVjme/j4VANDZfeWmFzcHG+x4/DK8fyAP354sRkWTDEoRyKhQJUR+faIY1pYCbogPwrNXx8Hb2dak80erv14Vi+2pFejoFPHG3hysmxkCJzv9x0SrkcdQ78oHknbzJhYaw87asGoapjqOTUnS3ql+3N1+ThdDxhARERER0djT2iuxS1/VusF6cGMidqeVAwDsrS2xdII/JgW7w9/NAfY2lrCyVHVFqG2R4envkgEASqXmPYKdTy3D+/sy8U1iPioapVCKIjLKVQmRXx/Lh7WlBVbPCMXfVk2Bj4udSeePVn+9djK2ny1FR6cSb+xKx/o54XCys9Y7r7XXDYSGnHv2Ps5azZxYaAxD9whMdRybUlu7cd8B9wiIiIhorOG/foiIiIiIqA/nXhvVbWZMZksqqFcnncX6OWPzg7Phq+WiQ2Zli971HG2t8PSKGDx1xThkVbUiqaAeSYX1OJZbh7IGKTo6RWxOKsGRnBrsfGJ+v9ca7HxDpZY2oqzBNBUUAt3tMTnIzSRraRLq6Yjb5oTis6OFqGuV470DufjzlbF65zkZeQy1yXuS/cx9Qc7UTH0cG0PXBRZH254LO21yQ76D4ZO4SkREREREw0fvBDlz3vCWlF+rTjqLDXDFlkcXwddVc1eAzPImves52lnj6ZWT8NRVE5FV0YxT+TVIzq/FsexqlDa0oaNTiU0nCnA4sxK7/nR5v9ca7HxDpRbXo7TBNO2bg9wdMNmMLdbDvJxw22WR+OxQDupa2/Hungz85ZrJeuf1vhHToPPTXseZIQmaw4mpj2NjdOrYI+h9cyv3CIiIiIj6G1lXpoiIiIiIyOz8XO0gCIAoAtlVpk346u1gVo368TMrY3UmJBbXGX4xQRAExPo5I9bPGbfNCQUAnCqoxx+3nENOVSvKG2V4Z18uXrx+olnm6/PJkQJsSTK8jZMua2YE4e3100yyljZPXj4OW5JK0dquwEeH8nHXvDC9c3xceip05tdIEB/qrnN8bnWr+rGf68iq3GHq49jG0gLyTiXkCqXesXUSudbn/HpdoCmslehdq8CAMURERERENPb4u9n37BFUNpvtdQ5mVKgfP3PtZJ0JicV1rVqfu5ggCIgNcEVsgCtuvywKAHAqrwZ//DYJ2ZXNKG+U4u3dGXjppnizzNfnk4PZ2HyycEBzL7Z2Vhjevn22SdbS5o9XTsCWkwVolSnw0f5s3L0gWu8cX5ee7zK/ugXxYZ46x+dV9+xFDTQxdaiY+ji2sbKAXKFEuwF7BPU69gj83XriKKjRv9dXUGP43xgRERHRaGAx1AEQEREREdHw4u5og1g/ZwBAWaMM50oazfI61c0y9eNwL0edY/dlVA3qtWaGe/RJNDyeV3dJ549kXk62eGhRJABVpcjXdmfrnZPQK2HyYFa13vG9kxATNCRbWgg9j0Uzt742lqmPYzcHVXWNiibdVUoVnUqdf5sTAlxga6U65U8uatBbKeZwTq3e2IiIiIiIaOxxd7RFrL8rAKCsoQ3niuvN8jpVTT3nVhHezjrH7kuv0Pm8PjMjvfH27bPUPx/P0X/easr5I5mXsx0eXqrqTNEmV+C1Hel65ySE9yRMHrig/7vrPab33G6C0LNJMNz2CEx9HLs52AAAKvRUKVV0KnG2SPte1YRAt549goI6/XsEmYPbhyMiIiIaaViBkoiIiIiI+rlpejCe//UCAODf2zOw6YHZfTaoTaF3+6CCWgmifTVvLBfUSLAlefAVG0M9HdSPOzr137lv6vnd3l4/zexVI03twUUR+CKxENUt7fj2RDHc7HW30Foa5wM7KwvIFEr8dq4CT10hQZiW5MKUwgYcy1Ul73k52WBWRP92Y73bekvaO/u0/xpqpj6OY/ycUd3SjvJGGXKrWxHl46Rx3OakEtRLOrSuY2NlgWXjfbE9tQKS9k58ebxInQh7sapmGX5MKdMbGxERERERjU1rZoXjX9vOAgBe+vkcNj+6yKx7BPk1LYj2c9E4rqC6BZtPFgz69UI9e861FAPaIxjc/G5v3z7b7FUjTe3BpbH4/Eguqptl+CYxD64OevYIJgTAztoSso5O/Ha2FE/XtCBMS3JhckEtjnUlpHo522J2pHe/MX33CBTDqs23qY/jGH9XVDfLUN4oRW5VM6J8Na+36USBzgqUNlaWWD4xAL+dLYWkXYEvj+TioWWxGsdWNUmxNblQb2xEREREowkrUBIRERERUT93zA1FoLuqvc+h7Fo8vuks2uTa707fn1ENWUenUa8xLcRN/fi137MhlfefX1zfhts/PaXxud6e3HwO6WVNOsdsPFqofjwx0NWk80c7R1srPHn5OACAQinikyO6N/k9nWxxy2xV+3OZQom7NyajpqW937jCWgke+CoF3QUjHlgYCVsry37jQj16klfPlTYO8F2YhymPY0CVfNrtHz+na7wQdzSnFs/9rL/Kx0OLItB9TfO/OzNxJLum35gWWQfu/yIFrXqqTxARERER0dh1x2WRCHJXnZcdyqzC41+d1L1HkF5h/B5BaM/NdK9tPw+phvWL61px24dH9J5b/d83p5Be2qBzzMbDOerHE4L6dkIY7PzRztHWCn+8cgKArj2Cgzk6x3s62eKWuREAAFlHJ+7acKxPN4duhTUtePCzRPUewYNLYmFrrWGPwKsnedVcFVEHypTHMQAsm+CvfvyPrWc07hEcyarCc1vP6F3rwaWx6j2C//yWhsOZlf3GtEg7cN+nx9Aq4x4BERERjS3Dp2wHERERERENG462Vvj0zulY/X4iJO2d2JJUioOZNVg1NQATAl3haGuJxrYOZFQ0Y++FahTXtyHrpRWw07Cxrc2Vk/wQ7GGPknopUkubMO+V/bh5VggivBzR3qlESmEDtqaUQtqhxNoZwdicVKJ1rW9PFuPbk8WI8nHE3CgvxPo5w8PRBopOERVNUuxMq8Tp4kYAgLWlgIcXR5p0/lhw6+wQbDicj7waCdoM2OR/ZmUsjubWIquyBRcqmjH/lQNYNysYkwJdIYpASlEDNieVqNeaE+mp9XNdEOONDV1Jm09uPof75ocjxNMRVl29vd0crBGvofX3pWDK4xgA1s0Mxrv7c1HbKse+jGpc9dZRrJkeBB8XO9RL5DiUVYNd6ZXwdrJFfIg7juhovT09zAP3L4jAR4fyVa//0QmsmhqI+eO84GBjiazKFnx3sgSVzTKsnOSH7Wn9L54QERERERE52lnj0/suww1v7YekXYHNJwtxIKMSqxJCMDHQDY621mhoa0dGeRP2ni9HcZ0E2a/eYNQewVVTghDs6YiSOglSSxow91/bccvcSIT7OEGuUCK5oBZbTxVB2tGJdbPDsemE9hv7vk3Mx7eJ+Yjydca8aF/EBrjCw8kWik4lyhvbsPNcGU4XqtodW1ta4JGLKvENdv5YcOu8SHx8IBt51S06k2m7/W3VFBzNrkZWRRMulDVi/gs7sH5OOCZ2JZ+mFNRh04kC9Vpzo73x8LIYjWstjPXDhgPZAFTJrvctikGolyOsLFR1g9wcbRAf1r/196VgyuMYANbNicA7ezJQ29KOvekVuPLVPVgzKxy+rnaob23HwcxK7Eotg7ezHeLDPHEkS3vr7RkRXnhgcQw+3J8FaUcn1r57CKsSgrEgxg/2NpbIrmzGt4n5qGySYuXUIGw/O/huMEREREQjBRMoiYiIiIhIo6nBbvj1D5fhgS9TkFPdiuqWdnUSmybGNu+ytbLEZ3fOwPqPT6C2VY7yRhle+z2737j75ofj3gUROhPPBAEQRSC3WoLcaonWce4O1njn5mn9KkgOdv5YYGVpgb9cFYv7vkgxaLyjrRV+fHgO7vsiBYl5dWiUduDDg/kax66c7I93bp4KSwvNR9HSWB9cFu2Fozm1KKprw7M/9a2+OCfSE9semWvcGzIRUx7HAODmYIOPbk/A7Z+egqS9E6mlTUgt7VsdNcjdHhvvmoENRzR/nr3945rxkHV04ovEIihFYNuZMmw707dd99VT/PHMVbFMoCQiIiIiIq2mhnrg1z8uwwOfJiKnqhnVzTJ1Epsmxnb4trW2xMb7LsO69w6itqUd5Y1SvLrjfL9x9y0eh/sWjdOZeKY+x69qQW5Vi9Zx7o42ePf22ZgY3PeGvMHOHwusLC3w12sm495Pjxk03tHWCtueWIJ7PzmGxJxqNLbJ8cG+LI1jr54ahHfumA1LC82NFJeO98dl43xwNLsaRbUSPPvD6T7Pz432xrYnlhr3hkzElMcxoNoj+PjuubjtwyOQtCuQWtKA1JK+1VGDPRyw8f752HBA8+fZ2z+unwpZRyc+P5ILpShiW3IxtiUX9xlzzbRgPHPtZCZQEhER0ZjCBEoiIiIiItJqfIALDv5pEX45W44daRU4U9yIutZ2KJQi3BxsEOXjhDmRnrhuWgBc7K2NXn9SkCsOPL0IHx7Mw54LVSipb4MgCPBxtsXMCA/cPCsEsyM8UVzfpnOdtH9djsTcOhzLrcW5kiYU17ehRdYBC0GAm4M1Yv2csSTOB+tmhsBVQ5yDnT9WXDMlAPEheepqnPp4Otnix0fmYnd6JX48XYaUogbUtrQDggDfru947YxgzIvy0rmOhYWAb++bhc+PFWJHWgWyq1rRLO2AQima4F0NnqmO427zorxw8OlFeP9AHg5m1aCiUQprKwuEejpg5WR/3H1ZuMHHoYWFgP/cOBnXTAnAxmOFSC6sR4OkA+6O1hgf4IJ1M0OwamqAwbEREREREdHYNSHQDYeeXYGfT5dg59lSnCmqQ21Lzx5BtJ8z5kT54LrpIXCxtzF6/UnB7jjwzJX4aH8m9qSpKlkKggAfFzvMivTCzXMjMDvKB8V1rTrXOf/ydUjMqcax7GqcLa5HSZ0EzdIOWAiq6oSx/q5YMiEA62eHw9Whf5yDnT9WXBMfjPh9nupqnPp4Otli2xNL8HtaGX5MKkJKYR1qm2WAAPi62GNWpBfWzg7HvHG+OtexsBDw3SMLsfFwLnaeK0V2ZTOa2uTDZ4/ARMdxt3njfHHob1fi/b2ZOJBRodojsLRAqJcjVk4Nxj0Low0+Di0sBPxn3XRcPS0Ynx/OQVJBLRokcrg72mBCoDvWzQ7HqoQQg2MjIiIiGi0EURwe/5gkIiIiIhosQRBcADTpHdgl598r4Gw3dpPhiIjIeC2yDkQ/s8uYKa6iKDabKx4iIiIiGnmM3b/IfW01nMfwzXxERC3SDkQ9tdWYKTwXJyIiIoNprn1ORERERERERERERERERERERERERDSKMYGSiIiIiIiIiIiIiIiIiIiIiIiIiMYcJlASERERERERERERERERERERERER0ZjDBEoiIiIiIiIiIiIiIiIiIiIiIiIiGnOYQElEREREREREREREREREREREREREYw4TKImIiIiIiIiIiIiIiIiIiIiIiIhozGECJRERERERERERERERERERERERERGNOUygJCIiIiIiIiIiIiIiIiIiIiIiIqIxhwmURERERERERERERERERERERERERDTmMIGSiIiIiIiIiIiIiIiIiIiIiIiIiMYcJlASERERERERERERERERERERERER0ZjDBEoiIiIiIiIiIiIiIiIiIiIiIiIiGnOshjoAIiIiIqKh0iJTDHUIREQ0wvD/HURERER0qbXIOoY6BCKiIcX/DhIREZE5CaIoDnUMREREREQmIQiCC4CmoY6DiIioF1dRFJuHOggiIiIiGj64f0FEZHY8FyciIiKDsYU3EREREREREREREREREREREREREY05TKAkIiIiIiIiIiIiIiIiIiIiIiIiojGHCZRERERERERERERERERERERERERENOYwgZKIiIiIiIiIiIiIiIiIiIiIiIiIxhwmUBIRERERERERERERERERERERERHRmMMESiIiIiIiIiIiIiIiIiIiIiIiIiIac5hASURERERERERERERERERERERERERjDhMoiYiIiIiIiIiIiIiIiIiIiIiIiGjMYQIlEREREREREREREREREREREREREY05TKAkIiIiIiIiIiIiIiIiIiIiIiIiojFHEEVxqGMgIiIiIjIJQRAEAM5DHQcNS/8A8KSRc0oBzAHQbPpwaBh7B8DtRs7JBLAAQLvpw6FRoEXk5gsRERER9cL9C7rI2wDuMGL8NAD5ZopluIgEcNqI8RsBPGGeUGiE4rk4ERERGYwJlERERERENKoJgjAXwBEYX4F/mSiK+8wQEg1jgiC4AEgFEGrk1NdEUXzaDCERERERERHRKCUIgg2ACgAeBk45LYpighlDGjYEQTgNVbKoIeoB+Imi2GHGkIiIiIholGILbyIiIiIiGrUEQXAE8CWMP/d5h8mTY5Mois1QVf4w9m7DPwqCMN8MIREREREREdHotQyGJ08CwCZzBTIMGfNePaD6LImIiIiIjMYESiIiIiIiGs3+C1XbJ2NkA/iLGWKhEUIUxUMA3jRymgDgC0EQ2IaPiIiIiIiIDLXOyPFbzBLF8GTse11rliiIiIiIaNRjC28iIiIiIhqVBEFYDmC3kdOUAOaJonjCDCHRCCIIgj2AFABxRk79WBTFB8wQEhEREREREY0igiDYAagGYOiNeMdFUZxrxpCGHUEQjgOYbeDwZgC+oijKzBgSEREREY1CrEBJRERERESjjiAIbgA2DmDqK0yeJAAQRVEK4HYAnUZOvV8QhCvNEBIRERERERGNLlfC8ORJYGy17+5mzHt2AXCFuQIhIiIiotGLCZRERERERDQavQ0g0Mg55wD8ywyx0AglimIygJcGMPVTQRA8TB0PERERERERjSrGtJwWAfxgrkCGse+heu+GMrYlOhERERERW3gTEREREdHoIgjCDQC2GjlNDmCGKIqpZgiJRjBBEKwBnAAQb+TU70RRvNkMIREREREREdEIJwiCI1Ttux0MnHJQFMXFZgxp2BIE4SCAhQYObwPgI4qixHwREREREdFowwqUREREREQ0agiC4AvgowFMfY7Jk6SJKIodULXybjdy6npBEG4yQ0hEREREREQ08l0Dw5MnAWCzuQIZAYxp4+0AYKW5AiEiIiKi0YkJlERERERENCoIgiBAlTzpZeTURACvmT4iGi1EUUwH8LcBTP1AEAR/U8dDREREREREI54x7bs7YXynjdFkK1SfgaHYxpuIiIiIjMIESiIiIiIiGi1uB7DKyDltAO4QRdGYjXgam94EcMTIOZ4ANnQl9xIRERERERFBEARXAFcZMWWvKIo15opnuOt67/uMmHKVIAgu5oqHiIiIiEYfJlASEREREdGIJwhCCIC3BzD1aVEUc00dD40+XUm2dwKQGDl1JYC7TR4QERERERERjVSrANgYMX4st+/uZsxnYAvjb7AlIiIiojGMCZRERERERDSiCYJgAWAjAGOrC+wB8IHpI6LRShTFfABPDmDqm4IghJk4HCIiIiIiIhqZjGkx3QFgm7kCGUG2QfVZGMqYFulERERENMYxgZKIiIiIiEa6RwAsMXJOE4C7RVEUzRAPjW4bAOw0co4TgM+7kn2JiIiIiIhojBIEwRPAciOm7BJFsdFM4YwYoig2ANhlxJQrBEHwMFc8RERERDS68OINERERERGNWIIgjAPwnwFMfVQUxVJTx0OjX1fS7b0AGoycuhDA46aPiIiIiIiIiEaQGwBYGTF+k7kCGYGMaeNtBdVnTURERESkFxMoiYiIiIhoRBIEwQrAlwDsjZz6I4BvTB8RjRWiKJYDeHgAU18WBCHO1PEQERERERHRiGFM+24pgF/MFcgI9AsAmRHj2cabiIiIiAzCBEoiIiIiIhqp/gRglpFzqgE8yNbdNFiiKG4CsMXIabYAvhQEwdoMIREREREREdEwJgiCH4BFRkzZLopiq5nCGXFEUWwBsN2IKUsEQfA1VzxERERENHowgZKIiIiIiEYcQRCmAvjnAKbeL4pijWmjoTHsYQCVRs6ZDuCvZoiFiIiIiIiIhrcbYdy1Wbbv7s+Yz8QCwGpzBUJEREREo4fAwitERERERDSSCIJgCyAZwEQjp34uiuJdZgiJxjBBEFYC+M3IaQoAs0VRTDFDSERERERERDQMCYJwFMA8A4e3AvARRVFqxpBGHEEQHABUAXAycMoRURQXmDEkIiIiIhoFWIGSiIiIiIhGmn/B+OTJYgBPmD4UGutEUdwO4BMjp1lB1crbzgwhERERERER0TAjCEIwDE+eBICfmTzZnyiKbQB+MWLKfEEQgswVDxERERGNDkygJCIiIiKiEUMQhLkAnh7A1LtEUWwydTxEXZ4EUGjknPEAXjR9KERERERERDQMrTFyPNt3a2fsZ3OTWaIgIiIiolGDLbyJiIiIiGhEEATBEcA5AJFGTn1HFMXHzBASkZogCAsBHAAgGDFNBLBIFMXD5omKiIiIiIiIhgNBEE4BmGHg8EYAvqIoys0X0cglCIItVG28XQ2cckoUxVlmDImIiIiIRjhWoCQiIiIiopHivzA+eTIbwF/MEAtRH6IoHgLwppHTBACfC4LgbPqIiIiIiIiIaDgQBCEShidPAsCPTJ7UThTFdgA/GjFlpiAI4eaKh4iIiIhGPiZQEhERERHRsCcIwuUAHjZymhLA7aIotpkhJCJN/gYgw8g54QBeM0MsRERERERENDysNXL8ZrNEMboY+xkZ+x0QERER0RjCFt5ERERERDSsCYLgDiANQKCRU18SRfFZM4REpJUgCNMBnABgaeTUq0RR3GmGkIiIiIiIiGgICYJwDsBkA4fXAvAXRVFhxpBGPEEQrAGUA/AycMo5URSnmi8iIiIiIhrJWIGSiIiIiIiGu7dhfPLkWQDPmz4UIt1EUUwG8OIApn4qCIKHqeMhIiIiIiKioSMIQhwMT54EgO+ZPKmfKIodAH4wYsoUQRBizRUPEREREY1sTKAkIiIiIqJhSxCEGwDcauQ0OVStu+VmCInIEC8BSDFyjj+A98wQCxEREREREQ0dtu82H7bxJiIiIiKTYAtvIiIiIiIalgRB8AVwHoa3Y+r2F1EU/2OGkIgMJgjCeACnAdgaOXWtKIpbzBASERERERERXUKCIAgAMgDEGDilHECIKIqd5otq9BAEwRJACVQ3JBoiE8B4kRfHiYiIiOgirEBJRERERETDTtdFho9gfPJkIoDXTB8RkXFEUbwA4G8DmPqBIAiGXvwhIiIiIiKi4WsyDE+eBFTtu5k8aaCuz+p7I6bEAphkpnCIiIiIaARjAiUREREREQ1HdwBYZeScNgB38GIDDSNvAjhs5BwPABu6koiJiIiIiIho5Fpn5PhNZolidDP2MzP2OyEiIiKiMYAtvImIiIiIaFgRBCEEQBoAFyOnPiyK4gdmCIlowARBCAeQCsDJyKn3iqL4qRlCIiIiIiIiIjPruikuH0CYgVOKAISzvbRxuj7nAgChBk7JBxDFz5mIiIiIemMFSiIiIiIiGjYEQbAAsBHGJ0/uBvCh6SMiGhxRFAsAPDmAqW92JV8SERERERHRyDMDhidPAsBmJvUZr+sz22LElAgA080UDhERERGNUEygJCIiIiKi4eQRAEuMnNME4B5eaKBh7BMAO42c4wRgY1dSMREREREREY0sbN996Rj72a01SxRERERENGKxhTcREREREQ0LgiDEADgDwN7IqbeKoviNGUIiMhlBEAIAnAfgbuTUJ0VRfMMMIREREREREZEZdN0IVwwg0MApOQBieGPowHS18c4GEGXglFIAoaIoKs0XFRERERGNJKxkQUREREREQ04QBCsAX8L45MmtAL41fUREpiWKYjmAhwcw9WVBEOJMHQ8RERERERGZzTwYnjwJAJuYPDlwXZ+dMVUogwDMNVM4RERERDQCMYGSiIiIiIiGgz8DmGnknGoAD/EiA40UoihuArDZyGm2AL4UBMHaDCERERERERGR6bF996XHNt5ERERENGBs4U1ERERERENKEISpAE4BMDZBbJUoir+YPiIi8xEEwROqVt5+Rk79hyiKz5shJCIiIiIiIjKRrg4bZQB8DJxyXhTFSWYMacwQBOE8gAkGDq8CECiKYqcZQyIiIiKiEYIVKImIiIiIaMgIgmAL4CsYnzz5OZMnaSQSRbEOwD0DmPp3QRASTB0PERERERERmdQiGJ48CbD6pCkZ81n6AlhorkCIiIiIaGRhAiUREREREQ2lfwGYaOScYgBPmD4UoktDFMUdAD4xcpoVVK287cwQEhEREREREZmGsa2hN5slirHJ2M/S2FbrRERERDRKsYU3ERERERENCUEQ5gE4DONv7FoqiuJ+M4REdMkIguAMIBVAmJFTXxdF8SnTR0RERERERESDIQiCDYBKAO4GTkkRRXG6GUMacwRBSAEQb+DwegB+oih2mDEkIiIiIhoBWIGSiIiIiIguOUEQnAB8AePPSd5m8iSNBqIotgC4E4CxdzU+KQjCAtNHRERERERERIO0HIYnTwJs320OxnymHgCWmSsQIiIiIho5mEBJRERERERD4b8AIo2ckw3gr2aIhWhIiKJ4CMAbRk4TAHzeVcGSiIiIiIiIhg9j23dvMUsUY5uxnynbeBMRERERW3gTEREREdGlJQjC5QB+N3KaEsBcURRPmiEkoiEjCIIdgNMA4oycukEUxfvNEBIREREREREZqevcrhqAoTe7JYqiOM+MIY1ZgiAkAphj4PBmAL6iKMrMGBIRERERDXOsQElERERERJeMIAjuAD4bwNSXmTxJo1HXRZrbAXQaOfU+QRCuMkNIREREREREZLwrYXjyJABsNlcgZNRn6wJghbkCISIiIqKRgQmURERERER0Kb0NINDIOWcBPG/6UIiGB1EUkwG8OICpnwiC4GHqeIiIiIiIiMhoxrSCFgF8b65ACN9D9RkbytjW60REREQ0yrCFNxERERERXRKCIKwG8IOR0+QAEkRRPG+GkIiGDUEQrAEcB5Bg5NRNoiiuN0NIREREREREZABBEJygat9tb+CUA6IoLjFjSGOeIAgHACwycHgbAB9RFCXmi4iIiIiIhjNWoCQiIiIiIrMTBMEXwEcDmPp3Jk/SWCCKYgdUrbzbjZy6ThAEVssgIiIiIiIaOlfD8ORJgO27LwVjPmMHqL5DIiIiIhqjmEBJRERERERmJQiCAOBjAJ5GTj0G4HXTR0Q0PImieAHAMwOY+r4gCP6mjoeIiIiIiIgMYkz77k4AW80VCKltheqzNhRvTCQiIiIaw5hASURERERE5nYHgGuNnNMG4E5RFI3Z7CYaDd4EcNjIOR4APulKViYiIiIiIqJLRBAEVwBXGjFlryiKteaKh1REUawBsM+IKVcJguBirniIiIiIaHhjAiUREREREZmNIAghAN4awNQ/iqKYa+p4iIY7URSVAO4E0Grk1KsA3GPygIiIiIiIiEiX6wDYGDF+k5nioP6M+axtAawyVyBERERENLwxgZKIiIiIiMxCEAQLABsBGHsH/+8APjJ9REQjgyiKBQCeHMDUNwRBCDd1PERERERERKSVMe275QB+MlMc1N82AB1GjDfmuyQiIiKiUYQJlEREREREZC6PAlhi5JxGAPeIoiiaPhyiEeUTADuMnOMEYGNX8jIRERERERGZkSAIXgCWGTFllyiKjWYKhy7S9VnvMmLK5YIgeJopHCIiIiIaxnhRhYiIiIiITE4QhBgA/xnA1EdFUSwzdTxEI01XEvG9AOqNnLoQwOOmj4iIiOj/2bvPeFnPsnzY55VGKkmAhBRC7733LiiIqEgJ+n+lCSiKAgoqiqiIooKASlFqEixJ6CCgIiBFpJcQmkqvCTUkIW1nX++HtUTQlLnXnmetWTPH8UV/5jmfnHHNzG/vWddzXwDA//JTSfYYuN767s038v/zPZLca6oiAAAsLgOUAADAXFXVHkmOS7L3YPTlSf5u/o1ge+ruryT5xQ1En1JV1553HwAAAH7A0QPXnpXktVMV4UK9NsnZA9db4w0AsIIMUAIAAPP2G0luPpg5NckjrO6GH9TdJyQ5YTB2iSTHVdWeE1QCAABYeVV1WJI7DkT+obvPmKgOF6K7T0/yDwORO1XVZafqAwDAYjJACQAAzE1V3SjJ720g+rDu/tqc68Cy+KUkXx3M3CTJb03QBQAAgOQ+Gfs9q/XdW2fkocTdsvazBQBghZQDXgAAgHmoqkskeV+S6w5GX9zdD5mgEiyNqvrRJK8bjO1Icsvufv8ElQAAAFZWVb0jyW1mvPyMJId291kTVuJCVNW+SU5Jsv+MkXd09+0mrAQAwIJxAiUAADAvT8r48OTnkzx6/lVguXT365M8fzC2R5KXVNU+E1QCAABYSVV1VGYfnkySVxme3Drd/d0krx6I3LaqLjdVHwAAFo8BSgAAYJdV1W2SPG4D0Qd193fm3QeW1K8l+cxg5lpJnjxBFwAAgFV1v8HrR1ZIM43Rn8HozxgAgG3MCm8AAGCXVNX+ST6U5CqD0b/o7kfNvxEsr6q6fZJ/TVIDsU5yp+5+6ySlAAAAVkhVvTfJTWe8/NtJLtvd507XiItTVZdI8tUkB80YeU9332K6RgAALBInUAIAALvqTzM+PPnJJI+foAsste5+W5JnDMYqyTFVdcAElQAAAFZGVV0lsw9PJskrDE9uve4+J8krByI3r6orT9UHAIDFYoASAADYsKr6kSSPGIydn+QB3f3dCSrBKvjtJB8bzFwxyZ/NvwoAAMBKOXrw+uMnacFGjP4sRn/WAABsU1Z4AwAAG1JVByc5OckRg9End/fvTFAJVkZV3STJu5LsMRi9R3e/foJKAAAAS6+qTkpyvRkv/1qSI7p7x4SVmFFV7ZHkK0kuM2Pkw919w+kaAQCwKJxACQAAbNRfZnx48oNJ/mCCLrBSuvv9SZ68gegLqurS8+4DAACw7Krq2pl9eDJJXmZ4cnGs/yxeNhC5QVVdc6o+AAAsDgOUAADAsKq6d5L/Nxg7N2uru8+doBKsoj9K8v7BzOFJnj1BFwAAgGVnfff2Z403AAD/hxXeAADAkKq6bJKPJhk9xe7Xu/upE1SClbV+AsoHklxiMHr/7j5hgkoAAABLp6oqyceTXGPGyJeTHNXdO6drxaiq2j3JF7L2cOEsPpHk2u0X6gAAS80JlAAAwMzWf2Hw/IwPT74jydPn3whWW3d/LMlvbSD6nKqa9RdGAAAAq+4GmX14MklONDy5eLr7/CQnDkSumeT6E9UBAGBBGKAEAABGPCjJPQczZyZ50PqX1MD8PTPJWwczl0rygvWhaAAAAC7a/Qevt757cVnjDQDAD7DCGwAAmElVXSHJR5IcMBh9RHf/1QSVgHVVdaUkJyXZfzD6sO5+wQSVAAAAlsL6g2efTnLFGSOfTXJla58X0/rP8zNJrjBj5DNJruLnCQCwvJxACQAAXKyq2i3JizM+PPlPSf56/o2A79fdn0nymA1En7E+fAkAAMAFu3lmH55MkhMM2y2u9Z/NCQORKyW56UR1AABYAAYoAQCAWTwyyZ0GM99O8nN+aQCb5oVJXjeY2T/JMetD0gAAAPxfoyucR4bz2BqjP6PRFe4AAGwjVngDAAAXqaqumeSDSfYejP6/7v67CSoBF6KqDk9ycpJLDUZ/rbufPkElAACAbWv9YbMvJDlixsh/JLmmh0kX2/oa708mudqMkS8luXx375yuFQAAW8UJEwAAwIWqqj2SHJvx4cmXJfn7+TcCLkp3fyXJIzYQ/aOquva8+wAAAGxzt83sw5NJcrzhycW3/jM6fiByZJJbT1QHAIAtZoASAAC4KL+Z5OaDmVOSPMIvDGBrdPeJGftFUJJcIslxVbXnBJUAAAC2K+u7l5c13gAAJLHCGwAAuBBVdaMk70myx2D0x7v7tRNUAmZUVZfK2irvwwejv9/dvzf/RgAAANvL+laOLyc5ZMbIR7r7+hNWYs6q6iNJrjvj5acmObK7d0xYCQCALeAESgAA4P+oqkskOS7jw5MvNjwJW6+7v5nkoRuIPqGqbjrvPgAAANvQHTP78GTi9MntaORndmiSO0xVBACArWOAEgAAuCBPyuxP4P+3zyV59PyrABvR3a9P8vzB2O5ZW+W9zwSVAAAAtpPRlc0GKLef0Z/Z6Ep3AAC2ASu8AQCAH1BVt03ytiQ1GL1zd79lgkrABlXVAUk+nORKg9Gnd/evTVAJAABg4VXVXklOSXLQjJH3dffNpmvEVKrqfUluMuPl30xyeHefO2ElAAA2mRMoAQCA76mq/ZMcm/HhyT83PAmLp7tPT/LAJKNPTz6mqqwmAwAAVtVdM/vwZOL0ye1s5Gd3qSR3maoIAABbwwAlAADw/Z6a5MqDmU8mefwEXYA56O63J3n6YKySHLN+giUAAMCqGV3ffeIkLdgMoz87a7wBAJaMFd4AAECSpKp+JMk/DsbOT3Lr7n7PBJWAOamqvZO8P8m1B6Mv6O6HTVAJAABgIVXVPllb3z3rA2Xv7O7bTFiJiVXVO5PcasbLT09yaHefPWElAAA2kRMoAQCAVNXBSV60gegfGZ6Exbf+i50HJNkxGH1oVd1jgkoAAACL6u6ZfXgySY6fqgibZuRneECSu01VBACAzWeAEgAASJK/THLEYOaDSZ48QRdgAt39/mzsPfuCqrr0vPsAAAAsqJEVzTuTvHSqImyalyYZWds4uuIdAIAFZoU3AACsuKq6T8a/7D83yU26++QJKgETqao9k7wzyU0Hoyd0t18QAQAAS62q9k9yapJ9Zoy8pbvvPGElNklVvSXJHWe8/LtZW+N95nSNAADYLE6gBACAFVZVhyX5qw1En2B4Eraf7j4va6u8zxmMHl1VBigBAIBld8/MPjyZWN+9TEZ+lvsm+bGpigAAsLkMUAIAwIqqqkryvCSjq3nfkeTp828EbIbu/niSx28g+pyqOmLefQAAABbIyPru85O8YqoibLqXZ+1nOisPGQIALAkDlAAAsLoelLWTFUacmeRB3T3yhTKweP48yVsHMwcnecH68DUAAMBSqaqDktx9IPLG7v76RHXYZOs/y38ZiNy9qg6cqg8AAJvHACUAAKygqrpC1gaoRv1ad39q3n2AzdXdO5M8OMkZg9G7J3no/BsBAABsuZ9IstfA9dZ3L58TBq69RNZeMwAAbHMGKAEAYMVU1W5JjklywGD0H7O28htYAt39mSSP3kD06VV1pTnXAQAA2GojK5nPTfKqiXqwdV6Z5LyB663xBgBYAgYoAQBg9fxykjsOZr6d5KHd3XNvA2ylFyV53WBm/yTHrA9jAwAAbHtVdZkkdx2IvKG7T5uqD1uju7+d5A0DkbtW1aUnqgMAwCbxyw4AAFghVXXNJH+8gegvdfeX5t0H2FrrQ9EPS/LNwejts7HTKwEAABbRTyXZfeD6kVXPbC8jP9s9svbaAQBgGzNACQAAK6Kq9khybJK9B6MvS/L3828ELILu/kqSR2wg+kdVdZ159wEAANgCI6uYz0ry2qmKsOVek7Wf8ayOnqoIAACbwwAlAACsjt9McvPBzClJHmF1Nyy37j4xyfGDsUskOa6q9pygEgAAwKaoqsOT3HEg8truPmOiOmyx9Z/t6wYid6qqw6bqAwDA9AxQAgDACqiqGyX53Q1EH9rdX593H2Ah/VKSrwxmbpzktyfoAgAAsFnuk6QGrre+e/mNPGC4W9ZeQwAAbFPlIBkAAFhuVbV3kvclGV21+6Lu/rkJKgELqqrunuT1g7Hzk9yyu983QSUAAIBJVdW/Jbn1jJefnuSy3T2y4pltpqr2SXJqkv1njLyju283YSUAACbkBEoAAFh+T8r48OTnkjxmgi7AAuvuNyR53mBs96yt8t5ngkoAAACTqarLZ/bhySR5teHJ5bf+M371QOS2VXXUVH0AAJiWAUoAAFhiVXXbJI/dQPTB3f2defcBtoXHJvnMYOZaSf5wgi4AAABTut/g9SOrndneRn/W952kBQAAk7PCGwAAllRV7Z/kw0muPBh9Znc7fRJWWFXdLslbk9RArJPcqbvfOk0rAACA+aqq9ya56YyXfyvJYd197oSVWBBVtVeSU5IcNGPkvd198+kaAQAwFSdQAgDA8npqxocnP5HktyboAmwj3f32JE8fjFWSY6rqgAkqAQAAzFVVXTWzD08mySsMT66O9Z/1KwYiN6uqq0zVBwCA6RigBACAJVRVd0vyC4Ox85M8oLvPmqASsP08IcnHBjNXzPjgJQAAwFY4evB667tXz+jPfHQlPAAAC8AKbwAAWDJVdXCSk5McMRj9g+5+4gSVgG2qqm6c5N1J9hiM/lh3v26CSgAAAHNRVSclud6Ml38tyRHdvWPCSiyYqtojyZeTHDJj5KTuvsGElQAAmIATKAEAYPk8K+PDkx9M8uQJugDbWHd/IMkfbCD6gqq69Lz7AAAAzENVXTuzD08myUsNT66e9Z/5ywYi16+qa03VBwCAaRigBACAJVJV90nyM4Oxc5L8bHefO0ElYPt7SpL3DWYOS/KcCboAAADMg/XdzOqEwetHX1sAAGwxK7wBAGBJVNVhWVvdPXrq2+O6+2kTVAKWxPoJGh9MconB6E93t180AgAAC6OqKsknklx9xsiXkly+u3dO14pFVVW7J/l8Zt/28skk12q/hAcA2DacQAkAAEtg/cv/52d8ePLtSZ4x/0bAMunujyf5zQ1En1NVs/6SCQAAYDPcMLMPTybJiYYnV1d3n5/kxIHINZJcf6I6AABMwAAlAAAshwcn+bHBzJlJHrT+RTDAxfmLJP86mDk4yQvWh7wBAAAWweiK5dEVziyf0dfA/SdpAQDAJKzwBgCAba6qrpjkpCQHDEZ/obv/ev6NgGW1C583D+/u58+/EQAAwOzWH+76dJIrzhj5bJIrW8e82tZfN59JcoUZI59JchWvGwCA7cEJlAAAsI1V1W5JXpzxYaZ/TPK8+TcClll3fzbJYzYQfUZVXXnOdQAAAEbdPLMPTybJ8YbgWH8NjJxCeaUkN5uoDgAAc2aAEgAAtrdfTnLHwcy3kjzULwCADXpRktcNZvZLckxV7T5BHwAAgFmNrla2vpv/dvzg9dZ4AwBsE1Z4AwDANlVV10zywSR7D0Z/prv/foJKwIqoqsOSnJzk0oPRx3b3n01QCQAA4CKtb/H4QpIjZox8Msm1PIBK8r013p9IcvUZI19Kcvnu3jldKwAA5sEJlAAAsA1V1R5Jjsv48ORLM/7EPMAP6O6vJnnEBqJ/WFXXmXcfAACAGdw2sw9PJskJhif5bxtY431kkttMVAcAgDkyQAkAANvT45PcbDBzSpJf9OU/MA/d/dIko6fZXiLJcVW15wSVAAAALor13eyq0YeSj56kBQAAc2WFNwAAbDNVdeMk706yx2D0nt39DxNUAlZUVV0qa6u8Dx+MPqm7f3eCSgAAAP/H+iaPLyc5ZMbISd19gwkrsU1V1UeSXHfGy09NcmR375iwEgAAu8gJlAAAsI1U1d5ZW909Ojz5QsOTwLx19zeT/NwGor9dVaOn6AIAAGzUnTL78GTi9Eku3MgplIcmucNURQAAmA8DlAAAsL08Kcl1BjOfS/KrE3QBSHe/IcnzBmO7Z22V9z4TVAIAAPjfRlcpG6Dkwoy+NkZXxwMAsMms8AYAgG2iqm6X5K1JajB6p+7+1/k3AlhTVfsn+XCSKw9Gn9HdBrwBAIDJVNVeSU5JctCMkfd1txPzuVBV9b4kN5nx8m8lOay7z52wEgAAu8AJlAAAsA2sDycdk/HhyWcangSm1t1nJHlQktGnNB9dVdaZAQAAU/rhzD48mYytaGY1jbxGDk5yl6mKAACw6wxQAgDA9vC0jJ/s9okkvzVBF4D/o7vfnuTPBmOV5JiquuQElQAAAJLx9d0nTtKCZTL6GrHGGwBggVnhDQAAC66q7pbkDYOx85PcqrvfO0ElgAtUVXsneV+S6wxGX9jdD52gEgAAsMKqap8kpybZf8bIv3X3bSesxJKoqn9LcusZLz89yaHdffaElQAA2CAnUAIAwAKrqksleeEGon9oeBLYbOu/DHpAkh2D0Z+rqntMUAkAAFhtd8/sw5OJ9d3M7oSBaw/I2msRAIAFZIASAAAW27OSHDGY+UCSJ0/QBeBidfcHkjxpA9EXVNWl590HAABYaSOrk3cmedlURVg6L00ysurRGm8AgAVlhTcAACyoqrpvkhMHY+ckuUl3f3SCSgAzqao9krwzyc0Goyd299ETVAIAAFZMVe2ftfXd+8wYeXN3/9CElVgyVfXmJHea8fLvZm2N95kTVgIAYAOcQAkAAAuoqg5L8twNRJ9geBLYat29I2urvM8ejN6vqpzKAQAAzMM9M/vwZDK2khmSsdfMvll7TQIAsGAMUAIAwIKpqkry/CSjq2zfnuQZ828EMK67P5Hk8RuIPqeqjph3HwAAYOWMPJy1I8krpirC0np5kvMHrrdxAQBgARmgBACAxfPgJD82mDkzyYO6e+RLW4Cp/UWSfx3MHJzkhevD5AAAAMOq6qAkdxuIvLG7vz5RHZbU+mvmXwYiP1pVB07VBwCAjTFACQAAC6SqrpjkmRuI/mp3f3q+bQB2TXfvzNpQ+OmD0bsledj8GwEAACviJ5PsNXC99d1s1PED1+6VtdcmAAALxAAlAAAsiKraLckxSQ4YjL4hayu/ARZOd382yaM3EH16VV15vm0AAIAVMbK++9wkr5qoB8vvVVl7Dc3KGm8AgAVjgBIAABbHryS5w2DmW0ke2t09QR+AeXlxkn8YzOyX5Jiq2n2CPgAAwJKqqsskuctA5A3dfdpUfVhu3f3tJP84ELlrVV16ojoAAGyAAUoAAFgAVXXNJE/ZQPSXuvvL8+4DME/rQ94PS/KNwejtkjxm/o0AAIAldu8kIw9ijaxghgsy8hraI8lPTVUEAIBxBigBAGCLVdUeSY5Lsvdg9MT4kh/YJrr7q0kesYHoH1bVdebdBwAAWFojK5K/m+S1UxVhZbw2yVkD14+smAcAYGIGKAEAYOs9PsnNBjNfTfKLVncD20l3vzTJ3w/G9kpyXFXtOUElAABgiVTV4UnuOBD5h+4+c6I6rIjuPiPJPwxE7lhVh03VBwCAMQYoAQBgC1XVTZI8cQPRh3b36CpcgEXwyCRfHszcOMkTJugCAAAsl/smqYHrbfZgXkZeS7sluc9URQAAGFMOrAEAgK1RVXsneX+Saw9GX9jdD52gEsCmqKq7JXnDYOz8JLfq7vdOUAkAAFgCVfVvSW494+WnJzm0u8+esBIroqr2SXJqkv1njPxbd992wkoAAMzICZQAALB1/iDjw5OfS/KrE3QB2DTd/Y9J/nowtnvWVnnvM0ElAABgm6uqy2f24ckkeZXhSealu89K8qqByG2q6qiJ6gAAMMAAJQAAbIGqul2SXxuMdZIHdvd3JqgEsNkem+TTg5lrJvmjCboAAADb3/0Gr7e+m3k7YfD60dcsAAATsMIbAAA2WVUdkOTDSa40GH1Gdzt9Elga68Pkb01Sg9E7dfe/zr8RAACwXVXV+5LcZMbLv5XksO4+d8JKrJiq2ivJKUkOmjHyvu6+2XSNAACYhRMoAQBg8z0t48OTH0/y2xN0Adgy3f32rH0mjjqmqi457z4AAMD2VFVXzezDk0nycsOTzNv6a+rlA5GbVtVVpuoDAMBsDFACAMAmqqq7J3n4YOz8JA/o7rMmqASw1Z6Y5KODmSskefoEXQAAgO3p6MHrR1ctw6xGX1ujr10AAObMCm8AANgkVXWpJCcnOXww+qTu/t0JKgEshKq6UZL3JNljMHrP7v6HCSoBAADbSFV9JMl1Z7z81CRHdveOCSuxoqpqjyRfTnLIjJGTuvsGE1YCAOBiOIESAAA2z7MyPjz5gSRPnqALwMLo7g8medIGoi+oqsvMuw8AALB9VNV1MvvwZJK81PAkU1l/bb1sIHL9qrr2VH0AALh4BigBAGATVNV9k/z0YOycJD/b3edNUAlg0TwlyXsHM5dN8pyqqgn6AAAA24P13Sya4wevt8YbAGALWeENAAATq6rDk3wkyaUHo4/t7j+boBLAQqqqayb5YJK9B6M/091/P0ElAABgga0/TPWJJFefMfKlJJfv7p3TtWLVVdVuSb6Q5IgZI59Mcq32i3sAgC3hBEoAAJjQ+hf5z8/48OTbkzxz7oUAFlh3fyLJb24g+uyqmvUXUwAAwPK4YWYfnkySEw1PMrX119iJA5FrJLnBRHUAALgYBigBAGBaD0lyj8HMmUke1N3nT9AHYNH9ZZK3DGYOTvJCq7wBAGDl3H/w+tHVyrBR1ngDAGwTVngDAMBEquqKWVvdvf9g9Oe7+3nzbwSwPVTVFbL2+XnAYNTnJwAArIj1B6g+k+QKM0Y+k+Qq1iSzGdZfn59OcsUZI59NcmWvTwCAzecESgAAmEBV7ZbkmIwPT74hayu/AVZWd38uyaM3EH16VV1lznUAAIDFdIvMPjyZJCcYTmOzrL/WThiIXDHJzaZpAwDARTFACQAA0/iVJHcYzHwryUN9mQ+QJHlxkn8YzOyX5Jiq2n2CPgAAwGIZXXlsfTebbfQ1N7qSHgCAObDCGwAA5qyqrpXkg0kuMRj96e72ZT7Auqo6LMnJSS49GH1cdz9tgkoAAMACWH9o6gtJDp8x8skk1/LQKptpfY33J5JcfcbIl5Jcvrt3TtcKAID/zQmUAAAwR1W1Z5LjMj48eaLhSYAf1N1fTfILG4j+YVVdZ959AACAhXHbzD48mSTHG55ks62/5ka+7zsya69tAAA2kQFKAACYr8cnuelg5qtJfnGCLgDbXne/LMnfDcb2SvKSqtprgkoAAMDWG13ffcIkLeDijb72Rl/bAADsIiu8AQBgTqrqJknelWSPweiPdffrJqgEsBSq6uCsrfI+YjD6B939xAkqAQAAW6Sq9kjy5SSHzBg5qbtvMGEluEhVdVKS6814+alJjuzuHRNWAgDg+ziBEgAA5qCq9s7a6u7R4ckXGJ4EuGjd/a0kP7eB6G9V1c3m3QcAANhSd8rsw5PJ2AplmMLIa/DQJHecqAcAABfAACUAAMzHk5NcezDz2SS/Ov8qAMunu/8xyV8NxnZPclxV7TNBJQAAYGvcf/B667vZaqOvwdHXOAAAu8AKbwAA2EVVdfsk/5qkBmKd5E7d/dZJSgEsoaraP8mHk1x5MPrM7n7MBJUAAIBNVFV7JTklyUEzRt7b3TefrhHMpqrem+SmM17+rSSHdfe5E1YCAGCdEygBAGAXVNUBSY7J2PBksjbMY3gSYEB3n5HkgVkbQh/x6Kq60wSVAACAzfXDmX14MrG+m8UxcgrlwUnuOlURAAB+kAFKAADYNU9LcqXBzMeT/PYEXQCWXne/I2ufvaNeXFWXnHcfAABgU42uNn7pJC1g3ImD1x89SQsAAP4PK7wBAGCDquruSV4/GDs/yS27+30TVAJYCVW1d5L3JbnOYPRF3f1zE1QCAAAmVlX7JDk1yf4zRt7R3bebsBIMqap/S3LrGS8/Pcllu/usCSsBABAnUAIAwIZU1aWSvHAD0ScbngTYNd19dpKfTbJjMPqQqrrnBJUAAIDp/WhmH55MxlYmw2YYWSl/QJK7T1UEAID/YYASAAA25tlJDh/MvD/JH07QBWDldPcHk/z+BqLPr6rLzLsPAAAwuZH13TuTvGyqIrBBL83aa3NW1ngDAGwCK7wBAGBQVd0v46cYnJPkxt39sQkqAaykqtojyb8luflg9KVJjm5figAAwLZQVQckOSXJPjNG3tTdd5mwEmxIVb05yZ1mvPysJId29xkTVgIAWHlOoAQAgAFVdXiS524g+tuGJwHmq7t3JHlgkrMHo/fN2Ok1AADA1rpnZh+eTKzvZnGNrPHeJ8mPTVUEAIA1BigBAGBGVVVJnp/kUoPRtyV55twLAZDu/kSS39xA9DlVdeS8+wAAAJMYWWW8I8krpioCu+gVSc4fuN7DfwAAEzNACQAAs3tIknsMZs5I8qDuHvliFIAxf5nkLYOZg5K8YH04HgAAWFBVdVCSuw9E3tjd35ioDuyS7v56kjcORO6+/h4AAGAiBigBAGAGVXWlbOwUyV/t7s/MuQ4A36e7dyZ5cJLTB6N3S/Lw+TcCAADm6CeT7Dlw/ciKZNgKI6/RvZL8xFRFAAAwQAkAABerqnZL8uIk+w9G35DkBfNvBMD/1t2fS/KoDUT/rKquMu8+AADA3IysMD4nyaunKgJz8qok5w5cb403AMCEDFACAMDFe1SSOwxmvpXkod3dE/QB4IIdk+S1g5n9khxTVbvPvw4AALArquqQJHcZiLyhu0+bqg/Mw/pr9A0DkbtU1WWm6gMAsOoMUAIAwEWoqmslecoGoo/o7i/Puw8AF259aP3hSb4xGL1tkl+dfyMAAGAX/VSSkYedrO9muzhh4No9svZeAABgAuVAHAAAuGBVtWeSdya56WD0hO62Wgdgi1TVfZK8dDB2bpKbdPfJE1QCAAA2oKrekuSOM17+3SSHdveZ0zWC+aiq/ZOcmmSfGSNv6e47T1gJAGBlOYESAAAu3G9lfHjyq0l+aYIuAMyou1+W5G8HY3slOa6q9pqgEgAAMKiqDk9yh4HIaw1Psl109xlJXjsQueP6ewIAgDkzQAkAABegqm6S5AkbiP5cd4+ujgVg/n45yZcGMzfKxj77AQCA+btvkhq4fmQlMiyCkddsJbnPVEUAAFaZFd4AAPC/VNXeSd6f5NqD0Rd098MmqATABlTVjyT5x8HY+Ulu3d3vmaASAAAwo6p6Z5JbzXj56Vlb3332hJVgrqpqnySnJDlgxsi/dfdtJ6wEALCSnEAJAAD/15MzPjz52SS/Ov8qAGxUd/9Tkr8ajO2etVXe+0xQCQAAmEFVXSGzD08mySsNT7LddPdZSV49ELlNVV1+qj4AAKvKACUAAHyfqrp9xgchO8kDu/v0CSoBsGsel+TTg5lrJHnKBF0AAIDZ3G/weuu72a6OH7x+9L0BAMDFsMIbAADWVdUBST6c5EqD0ad3969NUAmAOaiq2yZ5W5IajN65u98yQSUAAOAiVNX7ktxkxsu/meTw7j53wkowiaraK8lXkxw8Y+R93X2zCSsBAKwcJ1ACAMD/+LOMD09+PMlvT9AFgDnp7nckeeoGoi+uqkvOuw8AAHDhqupqmX14MkleYXiS7Wr9tfuKgchNq+qqU/UBAFhFBigBACBJVf1okocNxs5P8oDuPnuCSgDM1xOTnDyYuUKSZ0zQBQAAuHBHD14/ugIZFo013gAAW8gKbwAAVl5VXSprQzWHD0Z/r7t/f4JKAEygqm6U5D1J9hiM/nh3v3aCSgAAwP9SVR9Jct0ZLz8lyZHdff6ElWBSVbVHki8nOWTGyEe6+/oTVgIAWClOoAQAgOTZGR+efH+SP5qgCwAT6e4PJtnI4Pvzq+oy8+4DAAD8oKq6TmYfnkySlxmeZLvr7h1JXjoQuV5VXXuqPgAAq8YAJQAAK62qjk5y/8HYOVlb3X3eBJUAmNYfZ+0UyhGXTfLcqqoJ+gAAAP/D+m5W1ehrefS9AgDAhbDCGwCAlVVVh2dtdfelBqO/1t1Pn6ASAJugqq6R5ENJ9h6M/r/u/rv5NwIAANYfWPpkkqvNGPlSkst3987pWsHmqKrdknw+yZEzRv4jyTXbL/sBAHaZEygBAFhJ61/KvyDjw5NvS/LMuRcCYNN09yeT/MYGos+uqll/mQUAAIy5UWYfnkySEwxPsizWX8snDkSunuQGE9UBAFgpBigBAFhVP5fkRwczZyR5kC/nAZbCs5K8ZTBzUJIXWuUNAACTsL6bVXfC4PX3n6QFAMCKscIbAICVU1VXSnJSkv0How/r7hdMUAmALVBVV0jykSQHDEYf0d1/NUElAABYSesPKX0myRVmjHw6yVWtL2aZrL8PPp3kijNGPpvkyt4HAAC7xgmUAACslKraLckxGR+efF2SF869EABbprs/l+RRG4g+raquMu8+AACwwm6R2Ycnk7X13YbGWCrrr+mRk1WvmOTm07QBAFgdBigBAFg1j05y+8HMN7N2+qQv5gGWzzFJXjOY2S/JsVW1+/zrAADAShpdRTy66hi2C2u8AQA2mRXeAACsjKq6dpIPJLnEYPT+3e2LeYAlVVWXTXJykssMRn+9u586QSUAAFgZ6w8mfSHJ4TNGPpHk2h50ZRmtr/H+eJJrzBj5cpKjunvndK0AAJabEygBAFgJVbVnkuMyPjx5guFJgOXW3ack+YUNRJ9cVdeddx8AAFgxt83sw5NJcrzhSZbV+mt75LvII7L2HgIAYIMMUAIAsCp+K8lNBjNfSfJLE3QBYMF098uT/O1gbK8kx1XVXhNUAgCAVWF9N/yg0df40ZO0AABYEVZ4AwCw9KrqJknelWSPweg9uvv1E1QCYAFV1cFJPpLkyMHok7v7dyaoBAAAS62q9sjaA6yXmTHy4e6+4XSNYDFU1UlJrjfj5V9LckR375iwEgDA0nICJQAAS62q9knykowPTz7f8CTAaunubyX5uQ1EH19VN593HwAAWAF3zuzDk4nTJ1kdxw9ce0iSO01VBABg2RmgBABg2T05ybUGM59J8msTdAFgwXX3PyV57mBs96yt8t5ngkoAALDMRlcPG6BkVVjjDQCwSazwBgBgaVXVHZK8JUkNxDrJHbv7bdO0AmDRVdV+ST6c5CqD0T/v7kfPvxEAACyfqrpEkq8mOWjGyHu6+xbTNYLFUlXvTXLTGS//dpLLdve50zUCAFhOTqAEAGApVdUBSY7J2PBkkjzd8CTAauvuM5M8MGtD9SMeVVXWpgEAwGx+OLMPTyZOn2T1jKzxPijJXSfqAQCw1AxQAgCwrP4syRUHMx9L8oT5VwFgu+nuf0vy1A1Ej6mqA+fdBwAAltDoyuETJ2kBi2v0NX//SVoAACw5K7wBAFg6VfWjSV43GNuR5Jbd/f4JKgGwDa2vFHxfkusORl/c3Q+ZoBIAACyFqtonyalJ9p8x8o7uvt2ElWAhVdU7ktxmxsvPSHJod581YSUAgKXjBEoAAJZKVV06yQs3EH2y4UkAvl93n5PkZ5OcNxh9cFXdc4JKAACwLH40sw9PJmOrjGGZjLz2909y96mKAAAsKwOUAAAsm2cnOWww8/4kfzRBFwC2ue7+UJLf30D0+VV1mTnXAQCAZTGyanhnkpdNVQQW3Muy9h6YlTXeAACDrPAGAGBpVNXRGT+R4JwkN+7uj01QCYAlUFV7JHlHklsMRl+e5L7tyxcAAPieqjoga+u7954x8qbuvsuElWChVdWbktx5xsvPytoa7zMmrAQAsFScQAkAwFKoqsOTPGcD0ccbngTgonT3jiQPzNovokbcO8nPzL8RAABsa/fM7MOTifXdcMLAtftk7T0GAMCMDFACALDtVVUleUGSSw1G35rkz+ffCIBl092fTPKbG4g+q6qOnHcfAADYxkZWDO9I8oqpisA28YqsvRdmZY03AMAAA5QAACyDhyb50cHMGUke3N07J+gDwHJ6VpI3D2YOSvLC9WF/AABYaVV1cJK7DUT+ubu/OVUf2A66++tJ3jgQuVtVHTRRHQCApWOAEgCAba2qrpTk6RuIPqa7PzPvPgAsr/Wh+wcn+c5g9EeS/Pz8GwEAwLbzk0n2HLh+ZHUxLLOR98JeWXuvAQAwAwOUAABsW1W1W5Jjkuw/GH1dkhfOvRAAS6+7P5/kURuIPq2qrjLvPgAAsM2MrBY+J8mrpyoC28yrkpw7cP3RE/UAAFg6BigBANjOHp3k9oOZbyZ5WHf3/OsAsCKOTfKawcx+SY6tqt0n6AMAAAuvqg5J8kMDkdd392lT9YHtZP298IaByF2r6jJT9QEAWCYGKAEA2Jaq6tpJ/mgD0Ud091fm3QeA1bE+hP/wJF8fjN4mya/NvxEAAGwL904y8kCR9d3wg44fuHb3rL3nAAC4GOXgHQAAtpuq2jPJvye5yWD0+O7+6QkqAbCCqureSV42GDs3yU27+yMTVAIAgIVVVW9JcscZL/9ukkO7+8zpGsH2UlX7JTk1yb4zRt7S3XeesBIAwFJwAiUAANvRb2d8ePIrSX5pgi4ArKjufnmSvxmM7ZXkuKraa4JKAACwkKrqiCR3GIi81vAk/KD198Q/DETuWFWHT9UHAGBZGKAEAGBbqaqbJnnCBqIP7e5vzrsPACvvl5N8aTBzwyS/M/8qAACwsO6bpAauH1lVDKtk5L1RSe4zVREAgGVhhTcAANtGVe2T5P1JrjUYfV53//wElQAgVfXDSf5pMHZ+ktt097snqAQAAAulqt6Z5FYzXv6dJJft7rMnrATbUlXtnbU13gfMGHlnd99mwkoAANueEygBANhOnpzx4cnPJHnsBF0AIEnS3f+c5LmDsd2ztsp73wkqAQDAwqiqK2T24ckkeZXhSbhg6++NVw1Ebl1Vl5+oDgDAUjBACQDAtlBVd0jymMFYJ3lgd58+QSUA+H6PS/KpwczVkzxlgi4AALBI7jd4vfXdcNFG3yOj70EAgJVihTcAAAuvqg5IclKSKw5G/6y7nT4JwKaoqtskeVvGH1j9oe5+8wSVAABgy1XV+5PceMbLv5nksO4+b8JKsK1V1V5Jvprk4Bkj7+/um05YCQBgW3MCJQAA28HTMz48+bEkT5h/FQC4YN39b0meuoHoi6vqwHn3AQCArVZVV8vsw5NJ8nLDk3DRuvvcJC8fiNykqq46VR8AgO3OACUAAAutqu6R5KGDsR1JHtDdZ09QCQAuyu8m+chg5vJJnjFBFwAA2GpHD15vfTfM5oTB60ffiwAAK8MKbwAAFlZVXTrJyUkOG4z+bnc/aYJKAHCxquqGSd6TZM/B6E9092vm3wgAALZGVZ2c5DozXn5KkiO7+/wJK8FSqKo9knwpyaEzRj7S3defsBIAwLblBEoAABbZszM+PPm+JE+ZoAsAzKS7P5Tk9zcQfX5VHTLnOgAAsCWq6rqZfXgySV5qeBJm0907krx0IHK9qhp5PwIArAwDlAAALKSqun/GV8uck7XV3edNUAkARvxJkncPZg5N8tyqqgn6AADAZhv9Xmd0JTGsOmu8AQDmwApvAAAWTlUdkbXV3QcPRn+1u58xQSUAGFZVV0/yoST7DEb/v+7+2/k3AgCAzbH+UNAnk1xtxsgXk1yhu3dO1wqWS1XtluTzSY6cMfIfSa7ZBgQAAH6AEygBAFgo61+wvyDjw5NvTfLn828EABvT3f+R5Dc2EH1WVc36CzAAAFhEN8rsw5NJcoLhSRiz/p45cSBy9SQ3nKYNAMD2ZYASAIBF89Akdx/MnJHkQb5oB2ABPTvJmwczByV5kVXeAABsY/cfvN76btiY4wevt8YbAOB/scIbAICFUVVXSnJSkv0How/t7hdOUAkAdllVXT7JR5JccjD6i9393AkqAQDAZNYfBPpsksvPGPl0kqtaKwzj1t9vn0pypRkjn0tyJe83AID/4QRKAAAWQlXtnuTYjA9Pvi7Ji+bfCADmo7s/n+RRG4g+raquOu8+AAAwsVtm9uHJZG19t2Eu2ID1987ICa5XSHKLieoAAGxLBigBAFgUj05yu8HMN5M8zJfsAGwDxyZ59WBm3yTHrD9kAAAA28XoiuDRFcTAD7LGGwBgF1jhDQDAlquq6yR5f5JLDEaP7u4TJ6gEAHNXVYcm+WiSywxGf6O7/3SCSgAAMFfrD/98IcnhM0Y+keTaHo6FjVtf4/3xJNeYMfLlJEd1987pWgEAbB9OoAQAYEtV1Z5Jjsv48OTfG54EYDvp7lOT/PwGon9QVdebdx8AAJjA7TL78GSSHG94EnbN+nto5BTKI5LcdqI6AADbjgFKAAC22m8nufFg5itJHjlBFwCYVHe/IsnfDMb2SvKSqtprgkoAADBPo6uBT5ikBaye0ffS/SdpAQCwDVnhDQDAlqmqmyZ5V5LdB6M/2t1vmKASAEyuqg5KcnKSIwejf9jdT5h/IwAA2HVVtUfWHnq9zIyRD3f3DadrBKulqj6c5PozXv61JEd0944JKwEAbAtOoAQAYEtU1T5JXpLx4cnnGZ4EYDvr7m8nefAGoo+vqlvMuQ4AAMzLnTP78GQytnIYuHgj76lDktxpqiIAANuJAUoAALbKHya55mDmM0keO0EXANhU3f3GJM8ZjO2W5Liq2neCSgAAsKtGVwKfOEkLWF3WeAMAbIAV3gAAbLqqukOStySpgVgnuUN3v32aVgCwuapqvyQfSnLVwehfdPej5t8IAAA2pqoukeSUJAfOGHlPdztdHeasqt6T5GYzXv7tJJft7nOnawQAsPicQAkAwKaqqgOSHJOx4ckk+TPDkwAsk+4+M8kDk+wcjP5KVd15gkoAALBRP5zZhycT67thKiOnUB6UtfcuAMBKM0AJAMBme3qSKw5mPprkd+ZfBQC2Vne/M8lTNxA9pqpGfkENAABTGl0F/NJJWgAnDl5vjTcAsPKs8AYAYNNU1T2S/MNgbEeSW3T3ByaoBABbbn3d4XuTXG8wekx3P3iCSgAAMLOq2jdr67v3nzHy9u6+/YSVYKVV1duT3HbGy89Icmh3nzVhJQCAheYESgAANkVVXTrJCzYQ/QPDkwAss+4+J8kDkpw3GH1QVf34BJUAAGDEj2b24clkbMUwMG7kPbZ/1t7DAAArywAlAACb5TlJDhvMvC/JUyboAgALpbs/lOT3NhB9flUdMt82AAAwZGQF8M4kL5uqCJBk7T22c+D6o6cqAgCwHVjhDQDA5Krq/kn+fjB2dpIbd/fHJ6gEAAunqvZI8vYktxyMviLJfdqXPAAAbLKqOiDJqUn2njHyL9191wkrAUmq6k1J7jzj5WcluWx3nz5hJQCAheUESgAAJlVVR2Tt9MlRjzc8CcAq6e4dSR6YtV9ejfipJP9v/o0AAOBi/XhmH55MrO+GzXL8wLX7JLnnVEUAABadAUoAACZTVZXkBUkOHoz+a5K/mHshAFhw3f0fSX5jA9FnVdXl5t0HAAAuxsjq3x1ZOz0dmN4rsvaem5U13gDAyjJACQDAlB6W5O6DmdOTPLi7d07QBwC2g2cnedNg5sAkL1x/eAEAACZXVQcnudtA5J+7+5tT9QH+R3d/I8kbByJ3r6qDJqoDALDQDFACADCJqrpykqdvIPqY7v7snOsAwLax/hDBg5N8ZzD6w0l+Yf6NAADgAv1kkj0Hrh9ZKQzsupH33J5Ze08DAKwcA5QAAMxdVe2e5Jgk+w1G/yHJi+ZeCAC2me7+QpJf2UD0aVV11Xn3AQCAC3D/gWvPSfLqqYoAF+jVSc4duH7kPQ0AsDQMUAIAMIVHJ7ndYOYbSR7W3T3/OgCwLR2X8V8y75vk2PWHGQAAYBJVdUiSHxqIvL67R09YB3ZBd5+W5PUDkbtU1WWm6gMAsKgMUAIAMFdVdZ0kf7iB6CO6+6vz7gMA29X6QwUPT/L1weitkzx2/o0AAOB77p1k5KEd67tha4y893bP2nsbAGCllAN+AACYl6raM8m7ktx4MPr33f0zE1QCgG2vqu6V5BWDsXOT3LS7PzJBJQAAVlxV/WuSO8x4+XeTHNrdZ07XCLggVbVfklOztq1gFv/a3XeasBIAwMJxAiUAAPP0hIwPT34lySMn6AIAS6G7X5nkJYOxvZK8pKr2mqASAAArrKqOSHL7gchrDE/C1lh/7712IHKHqjp8qj4AAIvIACUAAHNRVTdL8tsbiD6ku7857z4AsGR+JckXBzM3SPLECboAALDa7pukBq4/YaoiwExG3oOVtfc4AMDKsMIbAIBdVlX7JPlAkmsORv+6u39hgkoAsHSq6q5J/nkwtjPJbbr7XRNUAgBgBVXVvye55YyXfyfJZbv77AkrARehqvbO2hrvA2aMvLO7bzNhJQCAheIESgAA5uEPMz48+ekkj52gCwAspe5+Y5LnDMZ2S3JsVe07QSUAAFZMVV0xsw9PJskrDU/C1lp/D75yIHLrqrrCVH0AABaNAUoAAHZJVd0xyWMGY53kQd19xtwLAcBy+/Uk/zWYuXqSP56gCwAAq+d+g9db3w2LYfS9OPpeBwDYtqzwBgBgw6rqkklOSjL6RPLTuvtxE1QCgKVXVbdO8vaMPxh7l+5+0wSVAABYEVX1/iQ3nvHybyY5rLvPm7ASMIOq2ivJV5JcasbI+7v7phNWAgBYGE6gBABgVzw948OTH03yOxN0AYCV0N3vTPKnG4i+uKoOnHcfAABWQ1VdPbMPTybJyw1PwmLo7nOTvGIgcpOquupUfQAAFokBSgAANqSq7pHk5wZjO5I8oLvPnqASAKyS38vaKdAjjkryzLk3AQBgVRw9eP3xk7QANmr0PTn6ngcA2Jas8AYAYFhVXTrJyUkOG4w+sbv/YIJKALByquoGSd6bZM/B6E9296snqAQAwBKrqpOTXGfGy09JcmR3nz9hJWBAVe2R5EtJDp0xcnJ3X2/CSgAAC8EJlAAADKmqSvLcjA9PvjfJU+bfCABWU3d/OGsnUY56XlUdMuc6AAAssaq6bmYfnkySlxqehMXS3TuSvHQgct2qGnnfAwBsSwYoAQAYdf8k9x3MnJ211d07JugDAKvsT5O8azBzaJK/Wn8oAgAAZmF9NywHa7wBAP4XK7wBAJhZVR2RtdXdBw9GH9Pdz5x/IwCgqq6W5MNJ9hmM/mx3/80ElQAAWCLrD978R5Krzhj5YpIrdPfO6VoBG1FVuyX5fJIjZ4z8Z5JrtKECAGCJOYESAICZrH9Z/sKMD0/+a5K/mHshACBJ0t3/meTXNxB9VlVdbt59AABYOjfO7MOTSXKC4UlYTOvvzRMGIldLcsNp2gAALAYDlAAAzOphSe42mDk9yYN8aQ4Ak3tOkjcNZg5M8iKrvAEAuBjWd8NyGRmgTJL7T9ICAGBBWOENAMDFqqorJzkpyX6D0Z/r7hdNUAkA+F+q6qgkJye55GD0l7r7ORNUAgBgm1t/2OazSS4/Y+TTSa5q3S8srvX39aeSXGnGyOeSXMn7GgBYVk6gBADgIlXV7kmOzfjw5D8kefH8GwEAF6S7v5DklzcQfWpVjaxkBABgddwysw9PJsnxhqxgsa2/R0dOir1CkltMVAcAYMsZoAQA4OI8JsltBzPfSPIwX5gDwKZ7SZJXDWb2TXLs+kMTAADw/UZX946uBga2hjXeAADrrPAGAOBCVdV1knwgyV6D0ft298smqAQAXIyqOjRrq7wPGYz+Znf/yQSVAADYhtYfsPliksNmjHw8yXU8UAuLb32N98eSXHPGyFeSHNXd50/XCgBgaziBEgCAC1RVeyY5LuPDk39neBIAtk53n5rk5zcQfVJVXX/efQAA2LZul9mHJxPru2HbWH+vjpxCeXjGtxQBAGwLBigBALgwT0hy48HMl5M8coIuAMCA7n5l1tZ5j9gryXFVNfrwBAAAy8n6blhu1ngDAMQKbwAALkBV3SzJvyfZfTB69+7+xwkqAQCDquqgJB9JcrnB6B9192/PvxEAANvF+maSLye5zIyRD3X3jSasBEygqj6U5AYzXv71JId3947pGgEAbD4nUAIA8AOqap+sre4eHZ78a8OTALA4uvvbSR6ygehvVtUt51wHAIDt5c6ZfXgycfokbFcj793LZO2zAQBgqRigBADgf/ujJNcczHw6yWMn6AIA7ILufmOSZw/GdktybFXtO0ElAAC2h6MHrzdACdvT6Ht39LMBAGDhWeENAMD3VNUdk7xlMNZJbt/d75h7IQBgl1XVfkk+lOSqg9G/7O5fmX8jAAAWWVVdIskpSQ6cMfLu7naCOWxTVfWeJDeb8fJvJzmsu8+ZrhEAwOZyAiUAAEmSqrpkkmM2EH2a4UkAWFzdfWaSByTZORj95ar6oQkqAQCw2H4ksw9PJk6fhO3u+IFrD0rywxP1AADYEgYoAQD4b09PcoXBzEeTPHGCLgDAHHX3vyf50w1EX1xVI788BwBg+xtZ0dtJTpyqCLApRt/D1ngDAEvFCm8AAFJV90zymsHYjiQ37+4PTlAJAJiz9VWM70ly/cHosd39oPk3AgBg0VTVvklOTbLfjJG3d/ftJ6wEbIKqenuS2854+RlJDu3usyasBACwaZxACQCw4qrqMkmev4Ho7xueBIDto7vPSfKzSc4bjD6wqn5igkoAACyeH83sw5PJ2OpfYHGNvJf3z9pnBQDAUjBACQCwwqqqkjwnyWUHo+9J8sfzbwQATKm7T0ryuxuIPq+qDpl3HwAAFs79B67dmeTlUxUBNtXLsvaentXIZwUAwEKzwhsAYIVV1U8n+bvB2NlJbtTdn5igEgAwsaraI8nbk9xyMPrKJPduXyYBACylqjoga+u7954x8i/dfdcJKwGbqKr+JckPzXj5WUku292nT1gJAGBTOIESAGBFVdWRSZ69gehvGp4EgO2ru3ckeUDWfuE14l5J/r/5NwIAYEH8eGYfnkys74ZlM/Ke3ifJPacqAgCwmQxQAgCsoPXV3S9IcvBg9C1J/nL+jQCAzdTd/5nkcRuI/mVVHTXvPgAALISRlbw7snZCObA8XpG19/asrPEGAJaCAUoAgNX08CR3G8ycnuTB3b1zgj4AwOZ7bpJ/GcwcmOSF6w9jAACwJKrq4CQ/MhD5p+7+5lR9gM23/p7+54HI3dY/OwAAtjUDlAAAK6aqrpLkzzYQfVR3f27efQCArbH+UMRDkpw2GL1rkkfMvxEAAFvoXkn2HLj+hKmKAFtq5L29Z5KfnKgHAMCmMUAJALBCqmr3JMck2W8w+tr1HACwRLr7C0l+ZQPRp1bV1ebdBwCALTOyivecJK+eqgiwpV6dtff4rI6eqggAwGYxQAkAsFoek+S2g5lvJHl4d/cEfQCArfeSJK8azOyb5Nj1hzMAANjGqurQJHceiLyuu78zVR9g63T3aUlePxC5S1UdMlUfAIDNYIASAGBFVNV1k/zhBqK/0N1fnXcfAGAxrD8k8fNJvjYYvVWSx82/EQAAm+zeSUYejLG+G5bbyHt896x9hgAAbFvlICEAgOVXVXsleVeSGw1G/667/98ElQCABVNV90ryisHYeUlu2t0nTVAJAIBNUFX/muQOM15+ZpLLdveZ0zUCtlJV7Zfk1KxtHpjFv3b3nSasBAAwKSdQAgCshidkfHjyy0keOUEXAGABdfcrkxw3GNszyXHrD2sAALDNVNWRSW4/EHmt4UlYbuvv8dcORO5QVUdM1QcAYGoGKAEAllxV3SzJb20g+pDu/ta8+wAAC+1RSb44mLlBkt+doAsAANO7b5IauP74qYoAC2XkvV5J7jNVEQCAqVnhDQCwxKpqnyQfSHLNwehfdfcjJqgEACy4qrpLkjcOxnYmuU13v2uCSgAATKSq/j3JLWe8/LSsre8+Z8JKwAKoqr2TnJLkkjNG/r27bz1hJQCAyTiBEgBguf1RxocnP53kcRN0AQC2ge7+lyTPHoztlrVV3vtNUAkAgAlU1RUz+/BkkrzK8CSshu4+O8mrBiK3qqorTFQHAGBSBigBAJZUVd0pyaMHY53kgd19xvwbAQDbyG8k+c/BzNWS/PEEXQAAmMb9Bq+3vhtWy+h7fvQzBQBgIVjhDQCwhKrqkklOSjL61O+fdvdvTFAJANhmquqWSf4t4w/g3qW73zRBJQAA5qiqPpDkRjNe/o0kh3f3eRNWAhZIVe2Z5KtJLjVj5APdfZMJKwEATMIJlAAAy+kZGR+ePDnJEyfoAgBsQ939riR/soHoi6vqwHn3AQBgfqrq6pl9eDJJXm54ElbL+nv+5QORG1fV1abqAwAwFQOUAABLpqrumeQhg7EdSR7Q3edMUAkA2L5+P2unWo84KsmfT9AFAID5OXrweuu7YTWdMHj96GcLAMCWs8IbAGCJVNVlsnaS5GUHo7/T3U+eoBIAsM1V1fWTvC/JnoPRe3X3q+bfCACAXVVVH01y7Rkv/2qSy3X3+RNWAhZQVe2e5EuZ/fvmj3b3dSesBAAwd06gBABYElVVSZ6b8eHJ9yT54/k3AgCWQXeflOSJG4g+r6oOnXcfAAB2TVVdN7MPTybJSw1Pwmpaf++/dCBynfXPGACAbcMAJQDA8vjpJPcZzJydtdXdOyboAwAsj6cm+ffBzCFJ/mr9IQ8AABbH/QevH13hCywXa7wBgKVmhTcAwBKoqiOztrr7oMHoo7r7L+bfCABYNlV1tSQfSrLvYPQB3f2S+TcCAGDU+sMt/5HkqjNGvpDkit29c7pWwCKrqt2SfC7J5WaM/GeSa7RBBABgm3ACJQDANrf+xfcLMj48+ZYkz5p7IQBgKXX3fyb59Q1E/7Kqjpp3HwAANuTGmX14MklOMDwJq239M+DEgcjVktxoojoAAHNngBIAYPt7eJK7DWZOT/JgX4ADAIOem+RfBjMHJnnR+qklAABsLeu7gY04fvD60c8aAIAtY4U3AMA2VlVXSfLhJPsNRh/S3S+eoBIAsOTWT5P8SNYGI0c8srufPUElAABmsP5Ay2eSXH7GyKeSXM0aXmB9C9J/JbnyjJHPJ7mizw8AYDvw5D8AwDZVVbsnOTbjw5OvSXLM3AsBACuhu7+Q5Jc3EH1qVV1t3n0AAJjZLTP78GSytr7b8BOQ9c+CkRNpL5+1zxwAgIVngBIAYPv61SS3Gcx8PcnDffkNAOyiv0nyysHMPkmOXX8IBACAzXf04PWjK3uB5Tb6mTD6mQMAsCWs8AYA2Iaq6rpJ3p9kr8Hofbr75RNUAgBWTFUdkuSjSQ4ZjD6+u/94gkoAAFyI9YdYvpjksBkjH09yHQ/hAv9tfY33x5Jcc8bIV5Ic1d3nT9cKAGDXOYESAGCbqaq9khyX8eHJvzU8CQDMS3d/LcnDNxB9UlVdf959AAC4SLfP7MOTSXK84Ung+61/JoycQnl4kttNVAcAYG4MUAIAbD9PSHKjwcyXkvzyBF0AgBXW3a/K2oMdI/ZM8pKqusT8GwEAcCFGV+meMEkLYLsb/WywxhsAWHhWeAMAbCNVdfMk70yy+2D0bt39TxNUAgBWXFUdlOSkJEcNRp/S3b81/0YAAHy/qtoza6t0Lz1j5EPdPfrwLrAiqupDSW4w4+VfT3J4d++YrhEAwK5xAiUAwDZRVftk7YSn0eHJ5xqeBACm0t3fTvLgDUR/o6puNec6AAD8X3fO7MOTydiKXmD1jHxGXCZrn0EAAAvLACUAwPbxlCTXGMx8KsnjJugCAPA93f2mJM8ajO2W5Niq2m+CSgAA/I/7D15/4iQtgGUx+hkx+hkEALCprPAGANgGqupOSd48GOskt+vuf5ugEgDAD6iqfZN8KMnVBqPP6u5fnn8jAACq6hJJTkly4IyRd3f3LSesBCyBqnp3kpvPePm3kxzW3edM1wgAYOOcQAkAsOCq6pJJjtlA9KmGJwGAzdLd303ygCQ7B6OPrKq7TFAJAIDkRzL78GRifTcwm5HPioOS/PBEPQAAdpkBSgCAxffMJJcfzJyc5InzrwIAcOG6+11J/ngD0RdX1UFzrgMAwNjq3E7y0qmKAEtl9LPCGm8AYGFZ4Q0AsMCq6p5JXjMYOy/Jzbv7Q/NvBABw0apqryTvSXKDwehx3f3ACSoBAKykqto3yalJ9psx8rbuvsOElYAlUlVvS3K7GS8/I8ll1zcXAAAsFCdQAgAsqKq6TJLnbyD6+4YnAYCt0t3nZm2V93mD0QdU1U/OvxEAwMq6R2YfnkySE6YqAiylkc+M/ZP86FRFAAB2hQFKAIAFVFWV5LlJLjsYfXeSP5l/IwCA2XX3SUmeuIHo86rq0Hn3AQBYUSMrc3cmedlURYCl9LKsfXbM6uipigAA7AoDlAAAi+mnk9xnMHNWkgd2944J+gAAjHpqkn8fzByS5K/WHyYBAGCDquqSGTvt7U3dfepUfYDl092nJHnzQOTHquqAqfoAAGyUAUoAgAVTVUcmefYGor/Z3Z+cdx8AgI3o7vOTPDDJdwej90rys/NvBACwUn48yd4D11vfDWzEyGfH3ln7bAIAWCgGKAEAFsj6aUsvTHLQYPTNSZ4190IAALugu/8zyeM2EP3Lqjpq3n0AAB30z3oAAQAASURBVFbIyKrc85K8cqoiwFJ7RZKRjUjWeAMAC8cAJQDAYvn5JD8ymPlOkgd3984J+gAA7KrnJnnjYOaSSV5UVb67AgAYVFUHZ+z7pX/u7m9O1QdYXuufHf88ELnb+mcUAMDC8CU0AMCCqKqrJHnaBqKP6u7Pz7sPAMA8dHcneUiS0wajd0nyiPk3AgBYevdKsufA9cdPVQRYCSOfIXsm+cmJegAAbIgBSgCABVBVuyc5Nsl+g9HXrOcAABZWd38xyS9vIPrUqrravPsAACy5+w9ce3bWvl8C2KhXJzln4PqRzygAgMkZoAQAWAy/muQ2g5mvJ3n4+qlOAACL7m+SvHIws0+S46pqjwn6AAAsnao6NMkPDURe393fmaoPsPzWP0NePxD5oao6ZKo+AACjDFACAGyxqrpekidvIPoL3X3KvPsAAExh/aGPn09y6mD0lkkeN/9GAABL6d4Z+/2f9d3APIx8luyetc8qAICFUA4sAgDYOlW1V5J3J7nhYPRvuvtn598IAGBaVfUTSV41GDsvyc26+8PzbwQAsDyq6q1Jbj/j5WcmObS7vzthJWAFVNV+WXtYbt8ZI2/t7jtO1wgAYHZOoAQA2Fq/k/HhyS8l+eX5VwEAmF53vzrJsYOxPbO2yvsSE1QCAFgKVXVkktsNRF5jeBKYh+4+M8lrBiK3r6ojpuoDADDCACUAwBapqpsnefwGog/p7m/PuQ4AwGZ6VJIvDGaun+R3J+gCALAs7pukBq63vhuYpxMGrq2sfWYBAGw5K7wBALZAVe2b5ANJrjEYfW53/+IElQAANlVV/VCSfxmM7Uxyu+5+5wSVAAC2tap6V5JbzHj5aUku293nTFgJWCFVtXeSU5JccsbIu7r7VhNWAgCYiRMoAQC2xlMyPjz5qSSPm6ALAMCm6+43JXnWYGy3JMdW1X4TVAIA2Laq6kqZfXgySV5peBKYp+4+O8krByK3rKorTlQHAGBmBigBADZZVd05ya8MxnYmeWB3nzlBJQCArfIbSf5jMHPVJH8yQRcAgO3sfoPXj6zaBZjV6GfL6GcXAMDcWeENALCJqurAJCclufxg9E+6+zcnqAQAsKWq6pZJ/i3jD/retbtHV4ADACylqvpAkhvNePk3khze3edNWAlYQVW1Z5KvJrnUjJEPdPdNJqwEAHCxnEAJALC5npHx4cmPJPndCboAAGy57n5Xkj/eQPTFVXXQnOsAAGw7VXWNzD48mSQvNzwJTGH9s+XlA5EbV9XVp+oDADALA5QAAJukqn48yYMHY+cleUB3nzNBJQCARfH7ST48mLlckj+foAsAwHZz9OD1x0/SAmDN6GfM6GcYAMBcWeENALAJquqQJCcnOXQw+oTu/sMJKgEALJSqun6S9yXZczD6U939ygkqAQAsvKqqJB9Ncq0ZI19NcrnuPn+6VsAqq6rdk3wpyWVnjHy0u687YSUAgIvkBEoAgImtf5H93IwPT747yZ/MvxEAwOLp7pOS/M4Gon9dVaN/zgIAWBbXzezDk0nyUsOTwJTWP2NeOhC5TlUZoAQAtowBSgCA6f1MknsPZs7K2uruHRP0AQBYVE9L8s7BzCFZG6KsCfoAACw667uBRWSNNwCwbVjhDQAwoao6Mmuruw8ajP5Kd//l/BsBACy2qrpqkg8n2Xcw+sDuPm6CSgAAC2n9AZL/THKVGSNfSHLF7t45XSuApKp2S/K5JJebMfJfSa7ehhcAgC3gBEoAgImsf4n9wowPT745ybPnXggAYBvo7v9K8rgNRP+yqo6adx8AgAV2k8w+PJkkJxieBDbD+mfNCQORqya58UR1AAAukgFKAIDp/HySHxnMfCfJg32ZDQCsuOcmeeNg5pJJXrx+0gkAwCqwvhtYZNZ4AwDbghXeAAAT2IXVkw/q7mMnqAQAsK1U1eWSnJzkwMHoL3f3syaoBACwMNYfGvlskllP4P5UkqtZjwtslvUNTf+V5MozRj6f5Io+pwCAzeaJfACAOauq3ZMck/HhyVcnOW7uhQAAtqHu/mKSR24g+qdVdfV59wEAWDC3zOzDk0lyvKEkYDOtf+aMnEJ5+ax9tgEAbCoDlAAA8/drSW4zmPl6kof7IhsA4Af8bZJXDGb2SXJsVe0xQR8AgEVx/8HrT5ikBcBFG/3sGf1sAwDYZVZ4AwDMUVVdL8n7kuw1GL13d48OBwAALL2qOiRrq7wPHYz+Vnc/ZYJKAABban37yReTHDZj5GNJruvBXWCzra/x/miSa80Y+UqSo7r7/OlaAQD8ICdQAgDMSVXtlbUV3KPDk39jeBIA4IJ199eSPHwD0d+vqhvMuw8AwAK4fWYfnkys7wa2yAbWeB+e5HYT1QEAuEAGKAEA5ueJSW44mPlSkl+efxUAgOXR3a9OcuxgbM8kL6mqS0xQCQBgK1nfDWwn1ngDAAvNCm8AgDmoqlskeWfGH1D54e5+4wSVAACWSlUdmOQjSY4ajP5xdz9+gkoAAJuuqvbM2orbS88Y+WB333jCSgAXq6o+mNkPH/h6kiO6+7zpGgEA/A8nUAIA7KKq2jdrq7tH/2z1HMOTAACz6e7TkjxoA9Ffr6pbz7kOAMBW+aHMPjyZOH0SWAwjn0WXSXLnqYoAAPxvBigBAHbdU5JcfTDzX0l+fYIuAABLq7vfnOQvB2O7JTm2qvaboBIAwGY7evB6A5TAIhj9LBr9rAMA2DArvAEAdkFV3TnJmwZjO5PcrrvfOUElAICltn769wcz/gDLs7v7kRNUAgDYFFV1iSSnJrnkjJF3dfetJqwEMLOqeleSW8x4+WlJLtvd50xYCQAgiRMoAQA2rKoOTHLMBqJ/angSAGBjuvu7SR6YtYdSRvxSVd11gkoAAJvlbpl9eDJx+iSwWEY+kw5M8iNTFQEA+H4GKAEANu6ZSY4azJyU5Pfm3gQAYIV097uSPGUD0RdX1UFzrgMAsFlGVtp2kpdOVQRgA07M2mfTrKzxBgA2hRXeAAAbUFU/nuTVg7Hzktysuz88QSUAgJVSVXsleXeSGw5GX9LdD5h/IwCA6VTVvllb373fjJG3dfcdJqwEMKyq3pbkdjNefmaSQ9e3EAAATMYJlAAAg6rqkCTP30D09wxPAgDMR3efm+QBSc4djP5sVd1rgkoAAFO6R2YfnkyS46cqArALRj6b9kvyo1MVAQD4bwYoAQAGVFUleW6SQwej70ryp/NvBACwurr7I0meuIHoX1fV6J/nAAC20v0Hrj0/ycunKgKwC16eZOfA9SOffQAAG2KAEgBgzM8kufdg5qwkD+zuHRP0AQBYdU9L8s7BzCFJnrf+cAwAwEKrqktm7QTKWb25u0+dqg/ARnX3KUnePBC5R1UdMFUfAIDEACUAwMyq6nJJnr2B6K9393/Muw8AAEl3n5/kgUm+Oxj9iaytAAcAWHQ/nuQSA9db3w0sspHPqL2z9hkIADAZA5QAADNYP53ohUkOHIy+Kclz5t8IAID/1t3/leSxG4j+RVVdft59AADmbGSF7XlJXjlVEYA5eGWSkW1N1ngDAJMyQAkAMJtfSPLDg5nvJHlwd++coA8AAD/or5L882DmkkleVFW+IwMAFlJVXSpj30n9U3d/a6o+ALuqu7+Z5J8GIj9SVQdP1QcAwJfDAAAXo6qumuRpG4j+Snd/Yd59AAD4v7q7k/xcktMGoz+U5Bfn3wgAYC7ulWTPgetPmKoIwByNfFbtmbXPQgCASRigBAC4CFW1e5Jjk+w7GH11kuPm3wgAgAvT3V9M8sgNRP+0qq4+7z4AAHMwsrr27CSvmaoIwBy9Osk5A9db4w0ATMYAJQDARXtsklsPZr6W5OHrpyABALC5/jbJKwYz+yQ5rqr2mKAPAMCGVNWhSe48EHldd39nqj4A87L+WfW6gcidq+r5VfXJqjqlqj5WVb9bVUdM1REAWB0GKAEALkRVXS/JkzYQ/fnuPnXefQAAuHjrD7H8QpLRP4/dIsmvz78RAMCG3Sdjv8uzvhvYTkY+s3ZP8tAkV09yaJJrJfm9JO+tquvPvxoAsErKwUgAAP9XVe2V5D1JbjAYfUl3P2CCSgAADKiqH8/aWrgR5yW5WXd/eIJKAABDquqtSW4/4+VnJjm0u787YSWAuamq/ZKckmS/XbzVt5Jcubu/vculAICV5ARKAIAL9sSMD09+McmvTNAFAIBB3f2aJMcMxvZM8pKqusT8GwEAzK6qLpfkdgOR1xieBLaT7j4zyWvncKuD43t5AGAXGKAEAFZSVe1eVT9dVX9XVa9f/5/3qqpLVNUtkzx+A7d9iKdcAQAWyqOTfH4wc72srYJLVd2kqp5WVf9cVS+rqt+tqkvPuSMAwAW5b5IauP74qYoAzFtV7VlVv55kXuu37zun+wAAK8gKbwBg5VTVlZK8Ick1LuAffzDJJZNcZfC2z+7uR+5qNwAA5quq7pzkTYOxnUlemuToC/hnZyT5he7+213tBgBwYarqXUluMePlpyW5bHefM2ElgLmoqssneWWSG8/xtl/q7svN8X4AwAoxQAkArJT1E4PemeTqc7ztfyW54frKEQAAFkxV/Xnmu9JtR5J7dPc/z/GeAABJvvfw76cHIsd094On6gMwL1VVSf4lyZ3nfOtTuvuwOd8TAFgRVngDAKvm0Znv8OTOJA8wPAkAsNAen+Q/5ni/PZL8+fov/wAA5u1+g9db3w1sF/fO/Icnk+QzE9wTAFgRBigBgJWx/gvu+8/5tn/a3f8+53sCADBH3f3dJA/I2sMv83LNJDeY4/0AAP7byPdX30jy5qmKAMzZ7Se678ipvQAAP8AAJQCwSg5PctU53u+kJL83x/sBADCR7n53kqfM+bZT/fIPAFhRVXWNJDcciLysu8+bqA7AvF1zovt+aqL7AgArwAAlALBKrjLHe52XtdXd58zxngAATOtJST40x/vN88+XAABJcvTg9dZ3A9vJf010XydQAgAbZoASAFgl8/wF95O7+8NzvB8AABPr7nOztsp7x5xuaYASAJibqqqMre/+apK3T1QHYArvnOi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      "text/plain": [
       "<Figure size 3200x3200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import tree\n",
    "\n",
    "fn=list(X.columns)\n",
    "cn=['NotFraud', 'Fraud']\n",
    "fig, axes = plt.subplots(nrows = 1,ncols = 1,figsize = (4,4), dpi=800)\n",
    "tree.plot_tree(clf.estimators_[0],\n",
    "               feature_names = fn, \n",
    "               class_names=cn,\n",
    "               filled = True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79e8416f",
   "metadata": {},
   "source": [
    "From the random forest graph, we can see that:\n",
    "\n",
    "if the time difference <45 seconds, it is likely to be a fraud\n",
    "\n",
    "or, if the signup day <2.5 days and time difference <1.5 seconds, it is also likely to be a fraud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b35dc323",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}