notebooks/run-backtest.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Syllabus\n",
    "\n",
    "Notebook to demonstrate how to run a backtest with GekkoPy.\n",
    "\n",
    "Make sure Gekko is running!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import pandas as pd\n",
    "from pprint import pprint\n",
    "from gekkopy.gekko_client import GekkoClient\n",
    "pd.options.display.max_rows = 100\n",
    "pd.options.display.max_columns = 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'http://localhost:3000'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Initialize Gekko Client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "gekko = GekkoClient(url)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Strategy and Backtest Config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "macd_cfg = {\n",
    "    'short': 10,\n",
    "    'long': 21,\n",
    "    'signal': 9,\n",
    "    'thresholds': {\n",
    "        'down': -0.025,\n",
    "        'up': 0.025,\n",
    "        'persistence': 1,\n",
    "    }\n",
    "}\n",
    "bt_config = gekko.build_backtest_config(\n",
    "    exchange='binance', \n",
    "    asset='BTC', \n",
    "    currency='USDT', \n",
    "    candlesize=360, \n",
    "    strategy='MACD',\n",
    "    strat_config=macd_cfg, \n",
    "    date_start='2019-01-01', \n",
    "    date_end='2019-06-01'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run the backtest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "report, jdf, profits = gekko.backtest(bt_config)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Results\n",
    "\n",
    "## Report\n",
    "The report contains high level statistics as returned by Gekko:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'startTime': '2019-02-19 23:59:00',\n",
       " 'endTime': '2019-06-01 00:01:00',\n",
       " 'timespan': '3 months',\n",
       " 'market': 118.83289531934932,\n",
       " 'balance': 5605.98664554,\n",
       " 'profit': 1598.1966455399997,\n",
       " 'relativeProfit': 39.87725518402908,\n",
       " 'yearlyProfit': 5779.418924137776,\n",
       " 'relativeYearlyProfit': 144.20463457760448,\n",
       " 'startPrice': 3699.94,\n",
       " 'endPrice': 8551.53,\n",
       " 'trades': 34,\n",
       " 'startBalance': 4007.79,\n",
       " 'exposure': 0.4925674839454903,\n",
       " 'sharpe': 13.77354874158137,\n",
       " 'downside': -2.5799428969375042,\n",
       " 'alpha': 1479.3637502206504}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "report"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Profit\n",
    "The profits are aggregated statistics per month.\n",
    "\n",
    "* fcurrentBalance, lcurrentBalance: balance on first and last day of month\n",
    "* fclose, lclose: closing price on first and last day of month\n",
    "* marketProfit, stratProfit: relative profit of market and strategy during the month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fcurrentBalance</th>\n",
       "      <th>fclose</th>\n",
       "      <th>lcurrentBalance</th>\n",
       "      <th>lclose</th>\n",
       "      <th>marketProfit</th>\n",
       "      <th>stratProfit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-01-31</th>\n",
       "      <td>4007.790000</td>\n",
       "      <td>3699.94</td>\n",
       "      <td>4007.790000</td>\n",
       "      <td>3434.10</td>\n",
       "      <td>-0.071850</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-28</th>\n",
       "      <td>4007.790000</td>\n",
       "      <td>3419.81</td>\n",
       "      <td>3637.272743</td>\n",
       "      <td>3813.69</td>\n",
       "      <td>0.115176</td>\n",
       "      <td>-0.092449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-31</th>\n",
       "      <td>3648.193078</td>\n",
       "      <td>3825.14</td>\n",
       "      <td>3596.587239</td>\n",
       "      <td>4103.95</td>\n",
       "      <td>0.072889</td>\n",
       "      <td>-0.014146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-30</th>\n",
       "      <td>3623.667136</td>\n",
       "      <td>4134.85</td>\n",
       "      <td>4301.169445</td>\n",
       "      <td>5320.81</td>\n",
       "      <td>0.286821</td>\n",
       "      <td>0.186966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-31</th>\n",
       "      <td>4313.139365</td>\n",
       "      <td>5348.99</td>\n",
       "      <td>5605.986646</td>\n",
       "      <td>8555.00</td>\n",
       "      <td>0.599367</td>\n",
       "      <td>0.299746</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            fcurrentBalance   fclose  lcurrentBalance   lclose  marketProfit  \\\n",
       "2019-01-31      4007.790000  3699.94      4007.790000  3434.10     -0.071850   \n",
       "2019-02-28      4007.790000  3419.81      3637.272743  3813.69      0.115176   \n",
       "2019-03-31      3648.193078  3825.14      3596.587239  4103.95      0.072889   \n",
       "2019-04-30      3623.667136  4134.85      4301.169445  5320.81      0.286821   \n",
       "2019-05-31      4313.139365  5348.99      5605.986646  8555.00      0.599367   \n",
       "\n",
       "            stratProfit  \n",
       "2019-01-31     0.000000  \n",
       "2019-02-28    -0.092449  \n",
       "2019-03-31    -0.014146  \n",
       "2019-04-30     0.186966  \n",
       "2019-05-31     0.299746  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Joint DataFrame\n",
    "\n",
    "All information about the trades, plus calculated profit etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>open</th>\n",
       "      <th>ind_macd</th>\n",
       "      <th>action</th>\n",
       "      <th>adviceId</th>\n",
       "      <th>amount</th>\n",
       "      <th>balance</th>\n",
       "      <th>cost</th>\n",
       "      <th>effectivePrice</th>\n",
       "      <th>feePercent</th>\n",
       "      <th>id</th>\n",
       "      <th>portfolio</th>\n",
       "      <th>price</th>\n",
       "      <th>entryBalance</th>\n",
       "      <th>exitBalance</th>\n",
       "      <th>lastAction</th>\n",
       "      <th>lastAmount</th>\n",
       "      <th>lastBalance</th>\n",
       "      <th>profit</th>\n",
       "      <th>currentBalance</th>\n",
       "      <th>marketP</th>\n",
       "      <th>stratP</th>\n",
       "      <th>marketMax</th>\n",
       "      <th>stratMax</th>\n",
       "      <th>marketDrawdown</th>\n",
       "      <th>stratDrawdown</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>start</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-05-21 00:00:00</th>\n",
       "      <td>7874.94</td>\n",
       "      <td>7998.00</td>\n",
       "      <td>7790.05</td>\n",
       "      <td>7937.16</td>\n",
       "      <td>6.672743</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>buy</td>\n",
       "      <td>0.756233</td>\n",
       "      <td>6027.125986</td>\n",
       "      <td>-0.017084</td>\n",
       "      <td>5955.291391</td>\n",
       "      <td>2.128397</td>\n",
       "      <td>1.485929</td>\n",
       "      <td>2.208109</td>\n",
       "      <td>1.54309</td>\n",
       "      <td>-0.036100</td>\n",
       "      <td>-0.037043</td>\n",
       "      <td>2019-05-21 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-21 06:00:00</th>\n",
       "      <td>7848.37</td>\n",
       "      <td>7980.90</td>\n",
       "      <td>7771.00</td>\n",
       "      <td>7874.91</td>\n",
       "      <td>-1.045374</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>buy</td>\n",
       "      <td>0.756233</td>\n",
       "      <td>6027.125986</td>\n",
       "      <td>-0.007181</td>\n",
       "      <td>5935.198274</td>\n",
       "      <td>2.121215</td>\n",
       "      <td>1.480915</td>\n",
       "      <td>2.208109</td>\n",
       "      <td>1.54309</td>\n",
       "      <td>-0.039352</td>\n",
       "      <td>-0.040292</td>\n",
       "      <td>2019-05-21 06:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-21 12:00:00</th>\n",
       "      <td>7962.55</td>\n",
       "      <td>7971.00</td>\n",
       "      <td>7793.38</td>\n",
       "      <td>7847.92</td>\n",
       "      <td>1.328789</td>\n",
       "      <td>sell</td>\n",
       "      <td>advice-28</td>\n",
       "      <td>0.754343</td>\n",
       "      <td>5920.360278</td>\n",
       "      <td>14.837996</td>\n",
       "      <td>7828.749075</td>\n",
       "      <td>0.25</td>\n",
       "      <td>trade-28</td>\n",
       "      <td>{'asset': 0, 'currency': 5605.98664554}</td>\n",
       "      <td>7848.37</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5920.360278</td>\n",
       "      <td>sell</td>\n",
       "      <td>0.754343</td>\n",
       "      <td>5920.360278</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>5920.360278</td>\n",
       "      <td>2.152075</td>\n",
       "      <td>1.477213</td>\n",
       "      <td>2.208109</td>\n",
       "      <td>1.54309</td>\n",
       "      <td>-0.025376</td>\n",
       "      <td>-0.042691</td>\n",
       "      <td>2019-05-21 12:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-21 18:00:00</th>\n",
       "      <td>7904.87</td>\n",
       "      <td>8042.32</td>\n",
       "      <td>7865.20</td>\n",
       "      <td>7960.05</td>\n",
       "      <td>-2.948071</td>\n",
       "      <td>buy</td>\n",
       "      <td>advice-29</td>\n",
       "      <td>0.741667</td>\n",
       "      <td>5905.559376</td>\n",
       "      <td>14.800901</td>\n",
       "      <td>7942.643625</td>\n",
       "      <td>0.25</td>\n",
       "      <td>trade-29</td>\n",
       "      <td>{'asset': 0, 'currency': 5605.98664554}</td>\n",
       "      <td>7962.55</td>\n",
       "      <td>5905.559376</td>\n",
       "      <td>NaN</td>\n",
       "      <td>buy</td>\n",
       "      <td>0.741667</td>\n",
       "      <td>5905.559376</td>\n",
       "      <td>-0.015589</td>\n",
       "      <td>5862.780033</td>\n",
       "      <td>2.136486</td>\n",
       "      <td>1.462846</td>\n",
       "      <td>2.208109</td>\n",
       "      <td>1.54309</td>\n",
       "      <td>-0.032436</td>\n",
       "      <td>-0.052002</td>\n",
       "      <td>2019-05-21 18:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-22 00:00:00</th>\n",
       "      <td>7921.09</td>\n",
       "      <td>7988.00</td>\n",
       "      <td>7830.23</td>\n",
       "      <td>7904.48</td>\n",
       "      <td>-5.522576</td>\n",
       "      <td>sell</td>\n",
       "      <td>advice-30</td>\n",
       "      <td>0.739813</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>14.656950</td>\n",
       "      <td>7885.107825</td>\n",
       "      <td>0.25</td>\n",
       "      <td>trade-30</td>\n",
       "      <td>{'asset': 0, 'currency': 5605.98664554}</td>\n",
       "      <td>7904.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>sell</td>\n",
       "      <td>0.739813</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>2.140870</td>\n",
       "      <td>1.459189</td>\n",
       "      <td>2.208109</td>\n",
       "      <td>1.54309</td>\n",
       "      <td>-0.030451</td>\n",
       "      <td>-0.054372</td>\n",
       "      <td>2019-05-22 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-22 06:00:00</th>\n",
       "      <td>7802.31</td>\n",
       "      <td>7930.92</td>\n",
       "      <td>7730.00</td>\n",
       "      <td>7920.07</td>\n",
       "      <td>-16.718075</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sell</td>\n",
       "      <td>0.739813</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>2.108767</td>\n",
       "      <td>1.459189</td>\n",
       "      <td>2.208109</td>\n",
       "      <td>1.54309</td>\n",
       "      <td>-0.044990</td>\n",
       "      <td>-0.054372</td>\n",
       "      <td>2019-05-22 06:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-22 12:00:00</th>\n",
       "      <td>7880.55</td>\n",
       "      <td>8016.00</td>\n",
       "      <td>7760.00</td>\n",
       "      <td>7802.95</td>\n",
       "      <td>-17.937734</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sell</td>\n",
       "      <td>0.739813</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>2.129913</td>\n",
       "      <td>1.459189</td>\n",
       "      <td>2.208109</td>\n",
       "      <td>1.54309</td>\n",
       "      <td>-0.035413</td>\n",
       "      <td>-0.054372</td>\n",
       "      <td>2019-05-22 12:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-22 18:00:00</th>\n",
       "      <td>7628.43</td>\n",
       "      <td>7917.68</td>\n",
       "      <td>7465.00</td>\n",
       "      <td>7880.55</td>\n",
       "      <td>-37.109617</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sell</td>\n",
       "      <td>0.739813</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5848.123082</td>\n",
       "      <td>2.061771</td>\n",
       "      <td>1.459189</td>\n",
       "      <td>2.208109</td>\n",
       "      <td>1.54309</td>\n",
       "      <td>-0.066273</td>\n",
       "      <td>-0.054372</td>\n",
       "      <td>2019-05-22 18:00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       close     high      low     open   ind_macd action  \\\n",
       "start                                                                       \n",
       "2019-05-21 00:00:00  7874.94  7998.00  7790.05  7937.16   6.672743    NaN   \n",
       "2019-05-21 06:00:00  7848.37  7980.90  7771.00  7874.91  -1.045374    NaN   \n",
       "2019-05-21 12:00:00  7962.55  7971.00  7793.38  7847.92   1.328789   sell   \n",
       "2019-05-21 18:00:00  7904.87  8042.32  7865.20  7960.05  -2.948071    buy   \n",
       "2019-05-22 00:00:00  7921.09  7988.00  7830.23  7904.48  -5.522576   sell   \n",
       "2019-05-22 06:00:00  7802.31  7930.92  7730.00  7920.07 -16.718075    NaN   \n",
       "2019-05-22 12:00:00  7880.55  8016.00  7760.00  7802.95 -17.937734    NaN   \n",
       "2019-05-22 18:00:00  7628.43  7917.68  7465.00  7880.55 -37.109617    NaN   \n",
       "\n",
       "                      adviceId    amount      balance       cost  \\\n",
       "start                                                              \n",
       "2019-05-21 00:00:00        NaN       NaN          NaN        NaN   \n",
       "2019-05-21 06:00:00        NaN       NaN          NaN        NaN   \n",
       "2019-05-21 12:00:00  advice-28  0.754343  5920.360278  14.837996   \n",
       "2019-05-21 18:00:00  advice-29  0.741667  5905.559376  14.800901   \n",
       "2019-05-22 00:00:00  advice-30  0.739813  5848.123082  14.656950   \n",
       "2019-05-22 06:00:00        NaN       NaN          NaN        NaN   \n",
       "2019-05-22 12:00:00        NaN       NaN          NaN        NaN   \n",
       "2019-05-22 18:00:00        NaN       NaN          NaN        NaN   \n",
       "\n",
       "                     effectivePrice  feePercent        id  \\\n",
       "start                                                       \n",
       "2019-05-21 00:00:00             NaN         NaN       NaN   \n",
       "2019-05-21 06:00:00             NaN         NaN       NaN   \n",
       "2019-05-21 12:00:00     7828.749075        0.25  trade-28   \n",
       "2019-05-21 18:00:00     7942.643625        0.25  trade-29   \n",
       "2019-05-22 00:00:00     7885.107825        0.25  trade-30   \n",
       "2019-05-22 06:00:00             NaN         NaN       NaN   \n",
       "2019-05-22 12:00:00             NaN         NaN       NaN   \n",
       "2019-05-22 18:00:00             NaN         NaN       NaN   \n",
       "\n",
       "                                                   portfolio    price  \\\n",
       "start                                                                   \n",
       "2019-05-21 00:00:00                                      NaN      NaN   \n",
       "2019-05-21 06:00:00                                      NaN      NaN   \n",
       "2019-05-21 12:00:00  {'asset': 0, 'currency': 5605.98664554}  7848.37   \n",
       "2019-05-21 18:00:00  {'asset': 0, 'currency': 5605.98664554}  7962.55   \n",
       "2019-05-22 00:00:00  {'asset': 0, 'currency': 5605.98664554}  7904.87   \n",
       "2019-05-22 06:00:00                                      NaN      NaN   \n",
       "2019-05-22 12:00:00                                      NaN      NaN   \n",
       "2019-05-22 18:00:00                                      NaN      NaN   \n",
       "\n",
       "                     entryBalance  exitBalance lastAction  lastAmount  \\\n",
       "start                                                                   \n",
       "2019-05-21 00:00:00           NaN          NaN        buy    0.756233   \n",
       "2019-05-21 06:00:00           NaN          NaN        buy    0.756233   \n",
       "2019-05-21 12:00:00           NaN  5920.360278       sell    0.754343   \n",
       "2019-05-21 18:00:00   5905.559376          NaN        buy    0.741667   \n",
       "2019-05-22 00:00:00           NaN  5848.123082       sell    0.739813   \n",
       "2019-05-22 06:00:00           NaN          NaN       sell    0.739813   \n",
       "2019-05-22 12:00:00           NaN          NaN       sell    0.739813   \n",
       "2019-05-22 18:00:00           NaN          NaN       sell    0.739813   \n",
       "\n",
       "                     lastBalance    profit  currentBalance   marketP  \\\n",
       "start                                                                  \n",
       "2019-05-21 00:00:00  6027.125986 -0.017084     5955.291391  2.128397   \n",
       "2019-05-21 06:00:00  6027.125986 -0.007181     5935.198274  2.121215   \n",
       "2019-05-21 12:00:00  5920.360278 -0.000000     5920.360278  2.152075   \n",
       "2019-05-21 18:00:00  5905.559376 -0.015589     5862.780033  2.136486   \n",
       "2019-05-22 00:00:00  5848.123082 -0.000000     5848.123082  2.140870   \n",
       "2019-05-22 06:00:00  5848.123082  0.000000     5848.123082  2.108767   \n",
       "2019-05-22 12:00:00  5848.123082 -0.000000     5848.123082  2.129913   \n",
       "2019-05-22 18:00:00  5848.123082  0.000000     5848.123082  2.061771   \n",
       "\n",
       "                       stratP  marketMax  stratMax  marketDrawdown  \\\n",
       "start                                                                \n",
       "2019-05-21 00:00:00  1.485929   2.208109   1.54309       -0.036100   \n",
       "2019-05-21 06:00:00  1.480915   2.208109   1.54309       -0.039352   \n",
       "2019-05-21 12:00:00  1.477213   2.208109   1.54309       -0.025376   \n",
       "2019-05-21 18:00:00  1.462846   2.208109   1.54309       -0.032436   \n",
       "2019-05-22 00:00:00  1.459189   2.208109   1.54309       -0.030451   \n",
       "2019-05-22 06:00:00  1.459189   2.208109   1.54309       -0.044990   \n",
       "2019-05-22 12:00:00  1.459189   2.208109   1.54309       -0.035413   \n",
       "2019-05-22 18:00:00  1.459189   2.208109   1.54309       -0.066273   \n",
       "\n",
       "                     stratDrawdown                date  \n",
       "start                                                   \n",
       "2019-05-21 00:00:00      -0.037043 2019-05-21 00:00:00  \n",
       "2019-05-21 06:00:00      -0.040292 2019-05-21 06:00:00  \n",
       "2019-05-21 12:00:00      -0.042691 2019-05-21 12:00:00  \n",
       "2019-05-21 18:00:00      -0.052002 2019-05-21 18:00:00  \n",
       "2019-05-22 00:00:00      -0.054372 2019-05-22 00:00:00  \n",
       "2019-05-22 06:00:00      -0.054372 2019-05-22 06:00:00  \n",
       "2019-05-22 12:00:00      -0.054372 2019-05-22 12:00:00  \n",
       "2019-05-22 18:00:00      -0.054372 2019-05-22 18:00:00  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jdf.loc['2019-05-21':'2019-05-22']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualization\n",
    "\n",
    "Finally, lets plot what our strategy does:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DO7Vgxrg+jIp9jN82bmX2NZcQFVS+EYjb4z6qisTG9I28v+H9OgW7h3ete3vd26xJXkOZu/o20nCkvvHOu3fiZax9p7szTR7SE0IIIYRootwezUNfb+LXfTlHHd9TESCf7ApyTIgPqfmluD2a9IJSnvhuK5GBVn5KPMRtH//Biz/sACAiwFJ5jdFgJNI/kj5Rfbiy05WE+oSSbcs+YbBbdTOP3bm7GdlxJFd2upI+kX2I9IvEqI5+EO9wfePGJCvIQgghhBBN1Oo92fxvfQpr9+bw84MX42MuD912ZxZjMijahPqcoIeatQ7xwenWJOfaKjfseGvceczflMZ3G1IpcrjoHOF/3F3nDge7NpeN9KL0WtMwqm7m8UrCK9X6OXZl+kzWN64rCZCFEEIIIZqoORtSsXgZSM0v5f1fkrh3WEdcbg/zN6VxfmwwXsaTSwY4r00QRoPihvd+JSrISpifN50j/OkS2ZkpCXFsTy/C1/v4JdZOV7B7eGW6Ieob15UEyEIIIYQQTVCh3clPiRlc3bsVKXml/G99Cvdc0oEftmaQml/KM6NPfhO0zhEBfHvXAG77eB3rD+Rxde9WlRubKaXoGhVwUv02xWD3ZEgO8hm2f/9+unfv3tjTEEIIIcRZ5j9L91DqdDPuwjaM7hnFwVwbH63Zz9PzEmnXwpdhncNPqf+eMUG8c1MffM1GLusecZpm3Tyc9QGyUmqUUurd4uLixp6KEEIIIcRpkZxr48PVSYztE0P3VoFc1j0Cs8nAs/O3YfUy8sGEC46bH1xXfdoEs+npS0noJgFyVWd9gKy1nq+1vsPP7+Se4mwILpeLCRMmEB8fzzXXXIPNZiM2Npbs7GwA1q1bx5AhQ/B4PHTs2JGsrCwAPB4PHTp0qGwnhBBCiHPDh6v3ozU8MKITAP4WL14d24t/X92DhfcNom2Y72kby3SSeczNmfxEGsDOnTu544472Lx5MwEBAbz11ls1tjMYDIwfP57PP/8cgMWLF9OzZ0/CwsIacrpCCCGEaCRaazYczOPrdclc0SOSiMAjZdZGxkdy44WtCbQ2Xn3gc4UEyA0gJiaGiy66CIDx48fXuI30YRMnTuSTTz4BYObMmdx6660NMkchhBBCNL65G9O4+q01OFwebh/UrrGnc86SALkBHH4qtOprk8mEx+MBwG63V56LiYmhZcuWLF26lN9++43LL7+8QecqhBBCiMbz+/5c/L1N/PLIUHpEBzb2dM5ZEiA3gIMHD7J27VoAvvzySwYOHEhsbCzr168H4Jtvvjmq/aRJkxg/fjxjx47FaDx+DUIhhBBCNB+bU/LpER1Iyyo72ImGJwFyA+jSpQsff/wx8fHx5Obmctddd/H0009z3333MWjQoGpB8OjRoykuLpb0CiGEEOIcYne62ZlRRHx0UGNP5ZwnG4WcYbGxsWzbtq3a8UGDBrFr164ar9m0aRM9e/akc+fOZ3p6QgghhGgCFm5JZ+oPO3C6NT0ltaLRSYDcxEydOpUZM2ZUVrIQQgghRPOWV1LGY99uoaDUCUB8jKwgNzYJkJuYRx99lEcffbSxpyGEEEKI+nroIbDb4XjlWbOzwWKB6dPRWvPKz7v46o9kiuxOXhnbk1Knm6hAyT9ubBIgCyGEEEKcDu3bw5QpUFJSextfX5g+HYCP1uznzaV7GNQxjGvP78ronlENNFFxIk06QFZKdQHuA8KAJVrrGad9kHp+2hNCCCGEqNHkyTBnDqxYAWVl1c+bzTBwINx5Jyt2ZfGv77dxadeWvD2+z2nZNlqcPnUKkJVSQcD7QHdAAxO11mvrO5hSaiZwJZCpte5+zLnLgNcBI/C+1nqq1no7MFkpZQDeq+94dVLPT3tCCCGEOEfVZVEtJgYMNRcJ075+/GP0QxR+sp4VuzKJiwjg1et6SXDcBNV1Bfl14Eet9TVKKTPgU/WkUiocKNVaF1U51kFrveeYfj4C/gN8csz1RuC/wAggBfhDKTVPa71NKTUaeLTiutOvHp/2hBBCCHEOq+ui2h13wHvvQWnpkeNWK18+9BKzkvdQYH2ZG7u9xtSrLsTXu0l/mX/OOmEdZKVUAHAx8AGA1rpMa51/TLPBwFyllKXimtuBN47tS2u9EsitYZi+wB6t9T6tdRnwFXBVxTXztNYDgHF1vqv6UAq++KL8DV0TPz/4/PPydmfYLbfcwv/+9z8AhgwZwrp16874mEIIIYSoo8mTYcCA8sWzGnjMZtK792HWuAfJvuFm8ClfT/RYrewefT1PFodSGvACpexju2MqwT5eDTl7UQ912SikHZAFfKiU2qCUel8pdVQ0qbX+GvgR+EopNQ6YCIytxzxaAclVXqcArZRSQ5RSbyil3gEW1nShUmqUUurd4uLiegx3jLAwmD0brNajj1ut5cdDQ0++byGEEEI0DydYVCsyenP5hZN5cM4PtI1YRGFoKB6l2G8J4YqY0RiCPsPuycajPWxI38DsxNkNfAOiruoSIJuA84AZWuveQAnlKQ9H0VpPA+zADGC01ro+EWtNy7Naa71ca32v1vpOrfV/a7pQaz1fa32Hn59fPYarwfDhMGlS5ac9fHzKXw8bdkrdlpSUMHLkSHr27En37t2ZNWsW69evZ/DgwfTp04eEhATS09NPbe5CCCGEOGOSskv4YFUS6w/k1rqo5rFYuWv0I9z11954tZxOsXk/A680s7tFLOte/5BbEhykOhdQ6rIBUOIsYfL3k8m3H/ulvGgK6pL4kgKkaK1/q3j9P2oIkJVSgyh/iG8O8DRwdz3mkQLEVHkdDaTV4/rT46WX4McfYe9eiI4+LQ/m/fjjj0RFRbFgwQIACgoKuPzyy5k7dy4tWrRg1qxZPP7448ycOfOUxxJCCCGarLOgatTBHBtFDifLdmSyek8OmUV2rugRybr9eazdlwPA+H6tGRXfG8Pwv9Jn8TcYSktxW638Mugq/mjfG/+C/5BlSwc0OyLSWDb/Ha7p3pvJb3ai1FV61HilrlIe+PEBPhzzYSPcrTieEwbIWusMpVSyUipOa70TGAYctXeyUqo35VUmRgJJwGdKqee01k/UcR5/AB2VUm2BVOB64MZ63Mfp4e0N8+bBddfBrFm15hjVR48ePXjooYd45JFHuPLKKwkODmbr1q2MGDECALfbTWRk5CmPI4QQQjRpTbxqVFJ2CSNeWYHLowHo0SqQIB8zby4trzdw37COlDhcvL8qic9+PYi5019ZvGYZ0fY0DlhCuD3+OtpHJ/Hp5pmVgbBTl/LoknuYtb03Jc7q9+1wO5iVOIs7+txB/5j+DXez4oTq+ujkPcDnFRUs9gG3HnPeB7hWa70XQCk1Abjl2E6UUl8CQ4AwpVQK8LTW+gOttUspdTfwE+Vl3mZqrRNP4n5OXefOsGnTaeuuU6dOrF+/noULF/LYY48xYsQIunXrxtq19a6SJ4QQQpy9mnjVqE/XHgDg5Wt7ckFsCK1DfbA73SS8tpLsIge3DWpLgMWL8f3a8Pv+XNqF+fKC5UXuffcJ5j72Cq+P6MK47ydWWyUudhaz6sAqXNpV47ilrlLGfTuOnXfvxMsoD+01FXUKkLXWG4Hzj3N+9TGvndRQt1hrfcNx+lhILQ/inc3S0tIICQlh/Pjx+Pn58e6775KVlcXatWvp378/TqeTXbt20a1bt8aeqhBCCHHmKEXpR59i7d6l5gC5AatGHavY4eLr9cmMjI/kr32iK49bvIx8dGtf8mxlBFjKg9fYMF9iw8of0jv/uXE4nrmeR4wGEj5LwOaqvkrs1m4MGLgo5iLsLjtpRWlklmTi1u7KNodKDjFt9TQev/jxM3ynoq6k+N4ZtmXLFqZMmYLBYMDLy4sZM2ZgMpm49957KSgowOVycf/990uALIQQommrZw6x26PZnVnEV78nsyE5nwvbhvDxmv0seutD2ky8oVqN4MasGvXaz7sodriYNLBdtXNtw3xpSy2lYAFvk5EZf8xgTfIaytw1BP6ABw9pRWmVq8Ruj5vMkkzSitJIL05nU8Ym8ux5p+1+xKmTAPkMS0hIICEhodrxlStXVjv20UcfVf778uXLz+CshBBCiHqqZw7xY99uZva6FJQCHy8jm5LLqzV86teRJyZNgg8+AJsN7ePD/quup6BTH3o1xH1U0Frz3i/7eHPpHoodLq6/oDU9ogNPqq/dubsZ2XEkNpeN9KL0E64SGw1GIv0jifQvfwbpyk5XnpZ7EqePBMhCCCFEc3KmqkXUI4c4o8DOlxt+xRH0KrOu+ZqYgFgWbM5g/cE8vt+czp1PPYfXnPkElB4g1TeES1uNotOcLSy4d1D977ceih0uCkqdBPt48dyC7Xzx20EGdQyjfQs/HhjR6aT7fSXhlWrHZJX47CYBshBCCNGcnKlqEYc3yejU6bg5xDanm1cWJ5Jh+j88jgye+uVvrLxlJfcN78jcjanc99VGLpj+C+0ve4Q3577IS7c+y+CurViyI5NCuxOrlxEAL2PtWzWUlpWvzFrNxhNOW2vNmr05fLWjjHuXL6HQfuRhub8Nac9Dl8ZhMJz+vGdZJT67NfsAWWuNaoSE/8aitW7sKQghxNmvAWv2utwe3l6xl37tQjk/NuSU+gLOSLWI35Ny2Z9TQtfIAMxvvk/7SeMw2u1HGlTkEB/AwrhXV7K56DUw5x61Y9x13a/jih6RZBU5cLg8JHS7mLDXJ/KBxYvfknJZvD2Tv3/+J2v25hDs48WDI+L4MTEDf28TF3cKY+7GNNqE+mIrc/FTYgZOt6ZLpD+BVi8sJiOPXt6Zji39K6e0I6OQLSkFfLL2AH+mbSXb/BKjo1/mym69KHa46BkdxMCOx/n9inNasw6QLRYLOTk5hIaGnhNBstaanJwcLBZLY09FCCHObqe4Cvvxmv3ERfjTr10omUV2corL6BIZUK1daZmbu7/4kyU7MmkX5svPDw7GeKqrmXVc6dWUb2N7MMfGL3uy6B4VyMpdWWxKKWBM7yh8zEaW7chiZ0YRv+/PrdKBN093G8F1mxbh43LgtlhZNfgq1jii+PqtNRR61lNmWYzLXR5AH94xLqFDAkGWICYNqv4gXO/WQZiNBn7Znc2gjmHsyCjin3O2EBVoocytWbAlnXB/b9YfyMPfYmJMr1aE+pn580A+RXYXibmFXPHGL9wyIJbOEQGYjIr7vtoIQOsQE56QF3HaDpBhepmb+688J2ICcWqadYAcHR1NSkoKWVlZjT2VBmOxWIiOjj5xQyGEELU7hVXY7zak8vS8RPrGhvD+Lecz9u21pBfY+en+i4kN88Xt0aw/kMe9X27AoCC90M6V8ZF8vzmdH7amc2V81KnP//B2yKNHH1Utwm2x8tOTr/HKx1vJKLDTIdyPXYeKsFWkLCgFob7eLN5+CABfs5FOEf7ce0kHroiPZH+2DS+jIuS2PhQM7It3ZgoHrCHc32cceSv3ERel2WebhsNRvx3jLF5GesUEsT29kFev60VuSRnfb0rjjsHtMRkUy3dmMbBjGN4mAyaDqhbg5hQ7+Nf323jvl6TKY/HRgUy7Jp7//vk46zdmotFHrWYLcTyquXwlHxcXp3fu3NnY0xBN0PLlyxkyZEhjT0OcYfJ7FjU5pfdFdnb5KmxeDQ9WhYSgd+4k0+xHywALWmsO5NhYsSuL5xduR2uNR8MlncNZuiMTi8mAv8ULt9bkFDswGQyEB3gTHWzl5v6xJHSLYPgrKwj392bWnSe3o1pyro1P1u6nyO7inmEdaRVkhXvvrawWYTN5M6vnpTw7/E56tAqkR3Qgybk2wvy8GXdha/ZllTCwYxgt/L2ZvymNMD9vLmwXgrep5jxfx5ZE7H+9li0vv0OfhAE4XG6u/d9IVh5cWWO5M6vJypKbl9S6Y9zerGJKHC7io4NO6v6h/CG8zcn5/G99Cg+M6MTO/DWM/nL0UZt3BHkHkXR/EkGWkx9HNB9KqfVa62p7fTTrFWQhhBCiLg4V2lmxM4trz48+sjpZyyrs4XzbD7YX8vzC3/jHiE58vT6FAzk2AAa0D+XWi9py+yfr+HnbIe4c3I7uUYF8vGY/bcN8CfXzpqDUyT2XdCAqyFrZ7aieUfxn6W6yix2E+XlXm2Nqfikf/JLE+H6t8Xp2WtsAACAASURBVDIasHgZaeFf3u5gjo3r311LWvFeMrxeZM6WJ/n8ltH0mTYNx/cLMO9PIsM/DOf0+/BNfJDXb5xDu+CjUx2q5j//5bwTfxPp3aMb3ru2MbDi9Ueb3mVtytpaawGfaMe49i38Tjjmifh5mxjQIYwBHcLItmUz9uux1Xa2O9FqthAgAbIQQgjBa4t38+XvB+kU4U+vmCori8OHQ5WavR6rlbJbJuI19BI+nr4MrWH6ol20CfXhuTHd6d4qkB6tymvpBvl44fFo/ja4A4E+XozqefzUicu7R/DGkt088r/NRARaGN0zCofLw8s/7yLfVkZGgR2Hy8O8TWnkljhQSjG4Uwucbg+r92RjMXvQYdNwFu7nkOEVxn/Qkl4xQWQNm8Kbc1/kiwf/zewtd7E3by8TvpvAyltOby5ufWsBn0laa2785kZKnNVzyB1uB7MSZ3FHnztqXc0WQgJkIYQQ5zSHy82CzWkAvLBwO2VuD33bhnDvJR3x9TbxxTV3c8ns72hhK+WAJYQE3+FY/m8RRXYXj13emcwiB5MHt69czT3s+TE9sJoNBPpUXy2tSecIf9qG+bJkRyYWLwOf/3YQg4I2ob70igkitLM357UJYsrXmxnRtSXtWvgxd0MqJqOBu4d2YEvJa8zeno4HD07DXmJjNrH7UB9uvHYom2+/gvS0qaRuS61WWeJ0aUq1gN9e9/Zxd7Y70Wq2EGd9gKyUGgWMioo6DQ81CCGEOKc43R4+XXuAQruLtmG+/JaUS4ivmY3J+Xg8mu6tAvnnwt1cfPNzTJ39PNtenMGjrdqy/kAueSVObr2oLWZTzfV6R8ZH1msuSineGnceRXYX8dGBzFydxNbUAv59dQ+CfMyV7S7pHI7Vy4hSikcu6wzA4n2LeeLLjyvTCWwuG7/lvkjSlPJc28X7FvPlzx9Vnj+2ssSZ0li1gGtazT5UfAgPnso2DbWaLc5OZ32ArLWeD8yPi4u7vbHnIoQQ4uyRnGtj8mfrSUwrpFNLP94adx7/XbaXRy7rzMuLdvLRmv0YlOK81kHMvPNyTNNu5vBSzG0D256ROVUtBfe3IR1qbONjPvp/3SfKtX3p0pfOuVzcmlazlyxbQtfzu8rOdqJOzvoAWQghhDgZ//h6Ewdzbbx+fS8u7x6J2WTg1et6lZ+7NI7fknLp0yaYx67ojOk4u7o1phPl2n619SsSsxIlFxcwKtnZTtSdBMhCCCHOORkFdn5PyuXBEZ24qleraucjAi2sfHhoI8ysfk6Ua2t321mXtg5NzSVdJRdXiJpJgCyEEOKc8vlvB1izNweAK3rUL0+4qalL5QiDMtAhpAN+Zr9GrSwhxNlEAmQhhBDnjI3J+Tw+ZysAcS396RB+6rV3G1N9KkdMv3T6cc8LIY6QAFkIIcQ544WF2wnzM/P0qG60DfNt7OmcESeqHNFYlSWEOJtIgCyEEOKc4HC5+S0pl3sv6XDCTTuEEOe2pvlYrhBCCHGaZRY6AIgO9mnkmQghmjoJkIUQQpwTMgrtALQMtDTyTIQQTZ0EyEIIIc4JGQXlAXJEgATIQojjkwBZCCHEOeFQoQTIQoi6kQBZCCHEOSGjwI7Fy0CAVZ5PF0IcnwTIQgghzgkZhXZaBlhQSjX2VIQQTZx8jBZCiObsoYfAboewsNrbZGeDxQLTp5++a5ugzEIHLSW9QghRBxIgCyHqr5kFTs1a+/YwZQqUlNTexte35t/TqVzbBGUU2ukVE9TY0xBCnAUkQBZC1N9JBE6lZW7un7UBb5ORhy+LOzdq0TaFDxKTJ8OcObBiBZSVVT9vNsPAgXDnnaf32ibC7tLYylz8lpRLRqGdCCnxJoSogyYdICulugD3AWHAEq31jEaekhAC6h047T5UxNPzElmRtJEc80ukF7/M17ePaeBJN4KmsAKrFHzxBXTqVPPvys8PPv+8vN3pvPYMSMou4YnvtnD9Ba1RqvxDV1yEP92iAvktKYeMAjtlLg+HCh3EhvmwbEcm3220weKfKvto10y3lxZCnF51DpCVUkZgHZCqtT6pjduVUjOBK4FMrXX3Y85dBrwOGIH3tdZTtdbbgclKKQPw3smMKYQ4A+oROOWWlHHVf1fjoQxP8DQctv0syngSra9q/g9LNZUV2LAwmD0bRo+G0tIjx63W8uOhoce91vnlV3hdPab+155m0xftZPWeHFbvyTnquI/ZiK3MXa29yaAY3tpE1w6x9G0bSssAb9q38Guo6QohzmL1WUG+D9gOBBx7QikVDpRqrYuqHOugtd5zTNOPgP8AnxxzvRH4LzACSAH+UErN01pvU0qNBh6tuK5RlLk8aDTeJmNjTUGIpqeOQdeixAxsZW76n7eAeXsOAZoi9x6+2jqLG3pc3zhzbygNuAK7MTmfpOxiOrTwp10LX7yMBsymKoWKhg+HSZPggw/AZgMfH7jtNhg2jNT8UjYl5+PrbSI62EppmZtVe7KZuSqJ8ABvtqe7mD9yLF0Xfl3tWgCX24PRoFBKYXe6sXjV/29lSp6N1xbvxqAgObcUt9b0aRNMRICF9AI7mYV2Fm5J546L23Fe62Cig634epvYklrAb/tyaBvmy8COYSgUrYKtpOeX0sLfm42/r2HIkLhT/vkKIc4tdQqQlVLRwEjgeeDBGpoMBu5SSl2htbYrpW4HrgauqNpIa71SKRVbw/V9gT1a630V430FXAVs01rPA+YppRYAX9Tprk6zOz9dx7oDeXSO8MdkMHBxpxYoBZGBFsL8vHlw9kZuvagtN/dvwxtL9pCcZ6NrZACDOoaxdm8OtjI3D4zo1BhTF+KUOd0evIxHV4TcllbI0h2H6N+xD32OCbpcEyeSdf4A/B0u/LxNLNiSjn/gdi584wMuKnOT7QNgZ/+qW7D324jFVCUntDk+2Hcqq7d1lF3s4Pp312J3eiqPhft7c9vAtmxLL8TX20QLP2+G3PNP4uYtwHIwiezAMF7pfzNlszeyYHM6DpenWr/92oWQV7afTOtTjI17mNW/rsC/9ABZAWHc2XYMhdOXY/Eysi29EG+TgdYhPuzOLKZv2xAMCkwGA0qBw+XB4mXkvNZB3DawLf4Wr6PG2ZFRyLUz1uLyaLQphTTDi1wY+Dzv/5KH060xGw2E+ZnpGR3EXYPbE+xrrry2bZgvo3tGVZt7x5b+p/xzFUKcu+q6gvwa8DBQ418crfXXSqm2wFdKqa+BiZSvBtdVKyC5yusU4EKl1BDgL4A3sLCmC5VSo4BRUVHV/0CeDnanm9V7ciof7DhUaOfFH3cc1cbiZWDqDzt46aedeLQmNtSXBZvTeemnnZVtJg2q/j8FIZq6t5bvYcbyvXwxqR8Ol5uJH/1BVJCVHRnlXxb5e+/jhZseYPB33+Nbup8UnxCGW4dR9sJSANq18GVvdhpZvs+xM8jNS4vAz3m4dwcsefHoAc90Pm4DPjSXU+zgi98O0j06kCHDhqFqWb09FW6PZmtqAbPXJeNwefji9gtJySslq6h87Bd+2EHLAG9cbk2erYzXNbQfMYU3577Is9c9RdK+fJSCS7tFcPugttjK3GQU2PH1NhHu701chIX4tydg8+xjj/E1rr7sYd6eP52pNz+N1deHMG8jhaUu7h7agWKHi92ZRVzUIYwVu7IItHqhlAetwWwykFPs4LXFu/lk7QEm9I+lbQtfescE8eu+HF79eRc+3kY+m9SHkbPupSRvH3b/N9k8eRlFDhdhvt4YDM08HUcI0aScMEBWSh3OGV5fEbDWSGs9rWLldwbQXmtdXI951PSXT2utlwPLj3eh1no+MD8uLu72eoxXZ1tTCyhze3h8ZBcSukWgtabQ7sJkUKw/kMfcjWncN6wj6w/msj29iEs6h9OvXSgHckrYmVHEjowiXvl5F7sOFdGnTciZmKIQp01OsYMFW9LJtzkxKHh18W48WjPhw99xezT+Fi98vU3cN6wjCd0imPjRH9z9zTbaJzzMjPnT+HrKdP7Wsyvh/hayix1sTsknSb+Jq7SUt8+Hq7fD4APgXT1dtGHycU/TQ3N2pxulYNXubPZkFpOUXUJyno1Xx/bix8QM3vtlH5mFjspV2bZhvsR2vZZnrd8SXVqKKyIKr5deOuoP376sYkocbry9DMQE+2A1V09T8Hg0aQWlGJRi/qY03vsliexiBwCjekYxoP2RwP/Gvq3Zl13Mea2DUUqRV1LGqj3ZtAzoT6vXb2OWz4k/sN/7w72kFqXiwYPBvJ8xt/rQ6b29zDzhlTXbnJLPvxdu59XFu4463i7Mlzdu6M2b658sH0972JC+gXm7vuG67ted5GhCCHHylNb6+A2UegG4CXABFspzkL/VWo8/pt0gyoPj9UCR1vruWvqLBb6v+pCeUqo/8IzWOqHi9WMAWusX6nojcXFxeufOndWOl5a5+WjNfi7pHE5cRP2/cnt7xV6m/rCDdU8MJ8zPu97Xp+aXctHUpTw3pjvj+7Wp9/Xi1C1fvpwhQ4Y09jTOClf9dzWbkvMrX3eNDOCZ0d3496LFrMx5km/G/o+hHXpUni92uNiXVYyft4k2ob4Yj1nlm/HHDKb8PIUSZ3lAGloCu96EEHv1sXVICGrXrpNOOVi2bBnBHXoTFWQh3L+WUl5aQ0LCcR+acw8ewjfPv0d+qZPOEQHM25SGxctAVpGDNXtzCPE1k1FgPyolwbsi19ft0bg8mr5tQ+gWFcA1faJJTC1kwZZ0Cu1OepVkcP3LU/jbqIdJj4wlIsCC1WzkwrahzFydVNmfQcGA9mEEWE1kF5WhFPh5m0jJK2XnocpHPYiPLWar/V881f8Dru5xHoF1CHrravG+xYz+cjSlriNpIUHeQSTdn0SQ5dRqCReUOtmbVcym5Hx6xQTRKyaIJUlLzsh48t+/OEzeC6ImSqn1Wuvzjz1+whVkrfVjwGMVnQwBHqohOO5NeZWJkUAS8JlS6jmt9RN1nN8fQMeKNI1U4HrgxjpeW9OcUUqRkmfjjk/Wsy29kNeX7OKeSzoyYUAsft7Vb3vhlnSeX7Cdvw/twID2obQJ9UEpxW/7cmgX5ntSwTFAVKAFf4uJnRlFJ24sRCNKzrWxKTmfhy+LY+JFbXG4PARavXC4HGwre4IC116e+uVvrGy/srL6hJ+3ifjo2oOX3bm7GdlxJDaXjfSidNKK0rhh7CHmfOHBx3WkncNs4q4rHiL1k0SGdQknNswXp9uDQSn+SMolOc9GiK+ZNqG+JOfaSEwrpNTpJqFbS4KsZjal5LMjpZSsn1bjazYyqmcUIb5mgn3MWLwM/JqUS4HNScsACwMemsbo34fiVctDc/93/T95/9uFZJlfokXZPwnxjsZoUARavUjoFkGR3cnQuHACrV7EhPgwvEs4JqOBDQfz+HjNAW7oG8MlncMrf0bdogIZe0FM5RBpt1/BrTsy2ZNZTFaRg43J+cxcncTwLi257oIYbGUudmQU8f3mNABaBVnx6PIP2yaj4skru6KA89v6cc23F3GgcC8fbHuICX1XnvqboEK2LZuxX489KlgFKHWV8sCPD/DhmA9Pqf9AqxfntQ7mvNbBDTKeEELU1+mqg+wDXKu13guglJoA3HJsI6XUl8AQIEwplQI8rbX+QGvtUkrdDfxEeZm3mVrrxJOZyNyNqTz6zRYu6x7Bsp2ZuN2aV8b25PuKnOClOzKZ+pceLNp2CK014/u14dd9Odzz5QZ8vIz8c84WAAZ1DCPc38KynVlMGtj2ZKZy+J7pHOHPjozCk+5DiIbwU2IGAFf2iMLiZaysRDDl5ylHfe09O3F2nb/2fiXhlWrH3B438/dfxWVrf8biLMNmMvJxfGtKBg4hzKh4e8VePFW+2Aq0etE1MoBt6YUs35lFeIA38dFBZJcm8dKGO2nh/Cc9WnYixt/AvQld+HVvDj8mZlBsd+Gq6KhVkJUwf2927Mrkm+Iyvr3sIT767jm8HFWWsq1Wij/5nM/XFlAa8ALushT8I99hzR2r6/T8wKCOLRjUscUJ20UFWY/6Nim3pIwFm9O4pk9MZVrFVcAjl3U+bj+V6Q8n8Xs5Hq01N35zY+Wqf1UOt4NZibO4o88d9I/pf8pjNcZ4QghRF/UKkGvLCdZarz7mtZMa6hZrrW84Tt8LqeVBvPr4YFUSRoNi4ZZ0+rcP5akru9KuhR9/OS+auRtTue+rjYx49chKyxtL9uDRmp7RgXw0sS/r9+exI6OIN5bsxu3R3HpRLI9efvz/UZ1I54gAvtuYWrmyLURTk5xr4+t1KXSO8Kd16JEd7hbvW8z7f75fubJX4ixh8veTSeiQcNJfexsNRhLve474LRtok5eOLTwaz7/m8enwLphNBkocLnKKy/D2MuB0ewj3txxdrgxwuBz0mHE9LuN+Ytt8xMJbV7JixQqG9GvDTRXBp9aa9AI7tjIX7Vv4oZRCa83BXBtPzW3BrKTfGbflZ1RpKdpqpXD8BKY6WpHJ4zg9WXjwkFK8jYV7vj2jebAhvmZu6h9br2vOxO/lsLfXvc2a5DWUuWtYYad8VXfct+PYefdOvIynntLR0OMJIURdNOmd9OrjkE1z88zf2ZxSwNOjunLLgNhqwehVvVpRWOqkoNTJtefHkGcr45v1KdjK3Dx6eWf8LV4M7RzO0M7h3HpRLF5GQ7WcypPRvVUAn/56gL1ZxXQIb1qlh4rsTr747SDBPmau7BmJj7nZvCXOOmUuT7VAsCHsyypmzH9XU+b2MP3anpXHz+TX3o9cFc+sopn4PHMvLRd+x9+7dKk85+ttwreGNKiqqq5qb8woXz1tScuj2iiliAqyVjvWJtSXx67ozNU7JjJwzzpiSu0csISQEJhA4bp5lFoW4XKVP/h2OgPP0+VMpyPUlBaTWZKJWx95svJQySGmrZ7G4xc/fkpjNcZ4QghRF80mGnJVlDvyMRsZ06tVrSu1VVdqWgZYeHxk1xrbnUyh+9r0a1f+0NHavTlNLkB+a/leZizfC8BLi3ZiMiieHtWNy7pHNPLMmoeCUidTf9iOt8lI5wh/dmcW06mlHzsyirA73QzuFM6gjmE8OXcrS3dkMvfvF9Em1LfWbxuKHeUVVE71/Xl4M4fsYge3f7IOo0Hx490XE1uxDe+Z/trbZDQwbkICTKj+YO2J1LZ6+un5n9a5j84RAXx1z2DmxMzgptceZsP//YeHWofxyOqJuByOo9o2pTzYhkhHqC0tJrMkk7SiNNKL09mUsYk8e95Jj9GY4wkhRF2csIrF2SIuLk5v2JJIQamTyEDriS9oQFprLpq6lF6tg3hrXJ/KY9vSC/HzNtE6xKdOqRdaa574bisHc21EB1vpGhlA16gAukUFHjdg8ng0K3Zl4e1loH+70Mqx8krKGDRtGRd3CuOmfrF8sGofm1MKCPE188N9g5pNOkhjPrl8OK3H4mXA7izfbczt0XgZy4PcIvuRJ9XMJgPRwVZCfMxsTM4n2NdM6xAfBnYII72glG3phexILyLA6sU/Lu1E6xAfXB6Nj5eRvm1DyCxyEObnze9JuZS5PXSJ8MfX28SGg/ms2JXJrkPFmE0G7E43v+zO5vw2waQX2MkpcfDhLX3p3/5I9Yhjq0/UpG1Q2wb/2jvblk2nNztVC5a8jd4MDRvKD5N/OKl+tdYkfJbAigMravyq32qysuTmJY2eB9tUfy9NmVQuEIfJe0HU5KSrWJxNfMymJpkioJSiX/tQFm87xKPfbCYqyMo3f6ZwIMcGQJtQH8b0akVGgZ3kPBvtWvhid3pwezQv/jW+8mv3vVnFfP7bQdqG+bI5pYAvfy/fW6V1iA+vjO3JT4kZJKYVYitzo4HLu0fgcnuYtymNXYeOlKWODfXhvNbBLNp2CFuZi7uHdqRrVAD924cy+49kHv5mM6v35DCwY+2bKdidbr79M5VAqxceXb4JQbi/N/3bhVWWmtJa43Rrdh0qIjzAm3B/C063h6wiB38ezGNR4iGig62M6d2KcH9vAq3l17k9GpOx4VMNzoQdGUWYDIqNT11KSp6N6GAfEtMKaBlgISLAwsrdWWxPL6JDuB8KeH7h9vK6wwNiKbI72Z1ZzOtLduPvbeK8NsFMGtSCX3Zn8ficrUeNExVoIa3Ajq/ZSElZ9SLDZqOBThF+lJa5KSh1cuOFrdmUnE9MiJXXru/FBbFH1+huil97n2j1dFnWMtYmrz2pIPZsyYNtir8XIYRojppeNNlMDe/Skm//TGX+pjRKytz0jAni70M7UOby8MPWdN5Yuhuz0UCHcD8WbE5HKUVuSRkJ3SIq0x2WbM8E4LNJF1YGROv25/LIN5u55u21mI0GukYF4G8xUWh3MfWH8h3/esUE8crYnigF+7JKWLI9k58SM7i8RyQ39G1N16iAynmO7hXFq4t38dTcrTx2RflDU3klZSTn2jg/NoROLf0wmwz8Y/YmFm07VO0+LV4G/nJeNAdySth4MB8/i4lDheVfWQ/qGMYf+3Mrt8MN9vEiv9TJWxUpHmF+ZsL8vNmTWczQzuG8cX3vGjdLOJvszCiifQs/LF7GyvSaqhvGXNK5JZd0PpI7e2m36qktWUUO/C2mI1UlEuJIyi4mt8SJyajYllbIdxtSuaZPNCl5pVzYLoTYUF+2VGxyE9fSn37tQk+Y11tVU/za+0RBrMPjOOkg9mwJPJvi70UIIZqjZpViUdNGIU2F1po8m5NgHy8yixyE+3sflcKQWWjHZDQQ4msGwOX20H/qUnrFBPHadb2YvymNT389gNuj+fH+i4/qe9nOTJZuz+SeSzoQHnBkg4Sk7BKCfbwI8jHXOJ/aUijW7s3hxvd/pba3hkGBR8MTI7vQr10oZpOBIB8vDuaUV0KYszEVk0ExomtLCkudjOoZxY6MIr79M4XBncLp3TqIrlEBxLcK5ECuja2pBWQXl7Fufy4ZhXY6hvsxe10Kr13XizG9W9X3R11NbV+rFdmdfLchlct7RJ50nesTuWjqUvq0CeaNG3qfkf7PJQ/+9CCphanHDWJ9vHz458B/npYgtrbAc/qlZ3ArbHHaydfq4jB5L4ia1JZiIQFyE/b8gm3MXL2fFn7eZBSW12v9+9D2TEk4tbJzdbF0R/nqsEJhMiq6RwWyKSWfPZnF5NnKGN6lJb0rivwfq8DmBDjpXb08Hs2gacvoEO7HxxP7nrB9bkkZS3dkEmj1IrfEwZXxUUetln7341IC23bHXubGz1K+G9nynZmk5peyNbUQf4uJ8f3a0D0qkCAfL7xNBjq29Cclz8b6A3kYKlbzXR5Np5Z+JKYVcvugdpUfZmpTaHcS/8wipiTE8fehHU7qZyGOr2oQu2jtIjwtPBLEiqNIUCQOk/eCqMk5kYPc3EwYEMvBXBtlLg8v/LUHBTYnQzuHN8jYVb/2P2xIXDhD4k48/qlud2swKK7qFcU7K/cxY/leerQKZN2BXK7oEUmnlv4c/lC3fFcWfyTl8sPWDJKyj+SlzvojmVE9o8gotBPub+GV1aWULP/jqDFCfM0U2Z08O7oba/fm8M4xm1P4e5sodborN5qAIyvnANvSCvnwlgswVJQB9FScMFQpC7glpQCAziexxbmoG6PBSKR/JJH+kRSFFjHk4iGNPSUhhBDNgATITVh0sA/v3FTtQ805YVy/NizbmcWLP+6oPDb7j2Seu7o7r/68m8S0AjwalIIQHzMf3nIBAVYvknNtPPzNZv48mF9ZMSLUonhvQl+Cfc1kFTkoc3kY1iUcu9OD1WxkwoBY8krKyCxykGcro8ThYva6ZCxeRh66NA6zyUCwjxm7y82O9CIS0wp4dv42rnxzFVFBVvJtZezIKKLM7SEm2EqbUF8MClbuzsbP20TPmKZRP1cIIYQQdSMBsmiSWgVZ+eG+QWQVOdiaWoDRoLjj03VM/GgdwT5e3H5xO1qH+HBNn2hMhiMbuvRpE8yIri2xO90E+ZjZmlrA/m0bGNChvCJHl8gjY1R9ADDY10xwlZSJYV2qr6CbTQb6tg3hgthg/LxNfPrrAVLzSwm0mriqVxR+3iYO5NjYn1NCmcvDdefHMHlI+zOW3yyEEEKIM0MCZNGktfD3rkwr+fmBwSRll9C9VeBx83+r7sTWMyaIvL2nt56zUoprz4/h2vNjTmu/QgghhGgaJEAWZ42YEB9iQnwaexpCCCGEaOaax24MQgghhBBCnCYSIAshhBBCCFFFs6mDrJQqAhqiEHIgUNAA4zSlsc/2ccOA7EYau77k/XXy/p+9e4+zqiz7P/75cpCzIIgIIgfzLCAoeACtwQN4TEvNUwma8uRTlk+WJoqpqVmZWdqv0jS0ME1IBSVFzfFICigqiIghIqKICMjB4TBcvz/W2rgYBxhw9uyZPd/368WLvde611rXmrlmzTX3vte9/H2u3ccu1HG3Ji+qS337Whfy2FU5br5yoTafc7EdOx/H3SMiPj8fa0QUxT9gcg0d59YCnmNBjl3Xj7s1uVHXz7kuHdvf5/px7AIet0Z+N9Syc3Z+1WAu1OZzLrZj5+O4G8sLD7HYcuPq4bHr23ELeWyfc/04ts+5fqiPX2ufc/Eft5DHrrHjFtMQi8lRyaMCzZwb9YO/z1YZ54XlOBesMhvLi2LqQb610AFYreXcqB/8fbbKOC8sx7lglak0L4qmB9nMzMzMrDoUUw+ymZmZmdkX5gLZzMzMzCyjzhXIkpYXOgarXSSVS5qa+ddtE21LJD1Uc9FZdZAUkv6aed9I0kJ/Ly1H0tfSPNmz0LFYzfM1wqpbnSuQzSrxaUT0zvybU+iArNqtAHpIapa+PxJ4b0t2IKlRtUdltcnpwLPAaVuykaSG+QnHatgXvkaYZdXJAllSS0lPSHpJ0muSTkiXd5M0Q9JtkqZLmpD5YbF6RFJDSb+SNEnSq5L+J7N6W0n3S3pd0h8l1cmfg3roX8Cx6evTgb/nVkg6QNLzkl5O/98jXT5U0n2SxgETaj5kqwmSiRETuQAAIABJREFUWgIDgG+TFsjpp0VPV/azLmm5pKslvQAcXLjIrZptzTXiGUm9M+2ek9SrRqO2WqmuFgZlwNciYj9gIPBrSUrX7Qb8PiL2AZYAJxUoRqs5zTLDK+5Pl30bWBoR/YB+wHmSuqfrDgAuAnoCXwK+XuMR29a4BzhNUlOgF/BCZt0bwJcjog9wBXBdZt3BwJCIOKzGIrWadiLwSES8CXwsab90+cZ+1lsA0yLiwIh4tsajtXzZmmvEn4GhAJJ2B5pExKs1FrHVWnX1I0cB10n6MrAO2AnokK57OyKmpq+nAN1qPjyrYZ9GRO8KywYBvSSdnL5vTfLH02rgxYiYDSDp78AhwOiaCta2TkS8mo4vPx0YX2F1a+BOSbsBATTOrHssIj6ukSCtUE4Hbkpf35O+f5iN/6yXA2MKEKfl0VZeI+4DRkj6MXAOMLJGgrVar64WyGcC7YH9I2KNpDlA03Tdqky7csBDLOonARdExKMbLJRKSC6OWZ4MvO4YC9wAlADtMst/BjwZEV9Lf0GWZtatqKHYrAAktQMOIxl/GkBDkp/p8Wz8Z70sIsprLkqrQVt0jYiIlZIeA04AvgH4SXsG1N0hFq2BD9PieCDQtdABWa3zKHC+pMaQfHQmqUW67gBJ3dPxiKeS3NhjdcMdwNUR8VqF5a357IacoTUakRXaycBdEdE1IrpFxM7A2yS9xf5Zr3+25hrxZ+B3wCR/2mQ5dapATu9CXwWMAvpKmkzSm/xGQQOz2ujPwOvAS5KmAX/is09MJgLXA9NIfpHeX+kerNaJiHkR8dtKVv0S+Lmk50h6EK3+OJ3P/wyPAc7AP+v1ztZcIyJiCvAJ8JcaCNHqiDr1qGlJ+wK3RcQBhY7FzMxqr3Q41Y8i4rhCx2K1m6ROJEMu9oyIdQUOx2qJOtODLOk7JFO2XF7oWMzMzKzuk3QWyWwXl7k4tqw61YNsZmZmZpZvtbYHWdLOkp5MH/wxXdIP0uVtJT0maVb6/3bp8j0lTZS0StKPKuzrB5Kmpfu5sBDnY2ZmZmZ1Q60tkIG1wEURsRdwEPBdSXsDPwGeiIjdgCfS9wAfA98nmd5lPUk9gPNIJozfFzgunQfRzMzMzOxzam2BHBHvR8RL6etlwAySB4KcANyZNruT5AlKRMSHETEJWFNhV3sB/4mIlRGxFngK+FoNnIKZmZmZ1UG1tkDOSif17kMykL5DRLwPSREN7LCZzacBX5bUTlJz4Bhg5/xFa2ZmZmZ1Wa1/kp6kliRzWl4YEZ9I2qLtI2KGpF8AjwHLgVdIhm+YmZmZmX1Ore5BTp+CNgYYFRH/TBcvkNQxXd8R+HBz+4mI2yNiv4j4MslY5Vn5itnMzMzM6rZaWyAr6Sq+HZgRETdmVo0FhqSvhwAPVmFfO6T/dwG+TjKfspmZmZnZ59TaeZAlHQI8A7wG5CbvHk4yDvkfQBdgLnBKRHwsaUdgMrBt2n45sHc6LOMZoB3JDXw/jIgnavRkzMzMzKzOqLUFspmZmZlZIdTaIRZmZmZmZoXgAtnMzMzMLMMFspmZmZlZhgtkMzMzM7MMF8hmZmZmZhkukM3MioCkKyX9aBPrT5S0d03GZGZWV7lANjOrH04EXCCbmVWB50E2M6ujJF0GnAW8CywEpgBLgWHANsBbwLeA3sBD6bqlwEnpLn4PtAdWAudFxBs1Gb+ZWW3lAtnMrA6StD8wEjgQaAS8BPwR+EtELErbXAMsiIibJY0EHoqI0em6J4DvRMQsSQcCP4+Iw2r+TMzMap9GhQ7AzMy2yqHA/RGxEkDS2HR5j7QwbgO0BB6tuKGklkB/4D5JucVN8h6xmVkd4QLZzKzuquwjwJHAiRHxiqShQEklbRoASyKid/5CMzOru3yTnplZ3fQ08DVJzSS1Ao5Pl7cC3pfUGDgz035Zuo6I+AR4W9IpAErsW3Ohm5nVbh6DbGZWR2Vu0nsHmAe8DqwALk6XvQa0ioihkgYAtwGrgJOBdcAfgI5AY+CeiLi6xk/CzKwWcoFsZmZmZpbhIRZmZmZmZhkukM3MzMzMMlwgm5mZmZlluEA2MzMzM8twgWxmZmZmluEC2czMzMwswwWymZmZmVmGC2QzMzMzswwXyGZmZmZmGS6QzczMzMwyXCCbmZmZmWW4QDYzMzMzy3CBbGZmZmaW4QLZzMzMzCzDBbKZmZmZWYYLZDMzMzOzDBfIZmZmZmYZLpDNzMzMzDJcIJuZmZmZZbhANjMzMzPLcIFsZmZmZpbhAtnMzMzMLMMFspmZmZlZhgtkMzMzM7MMF8hmZmZmZhkukM3MapASf5G0WNKLkg6VNLPQcdUWkkLSroWOw8zqNxfIZmabIWmOpE8lLZe0IC1wW27l7g4BjgQ6R8QBEfFMROxR4VhHVEvgtZykUknnFjoOM7OKXCCbmVXN8RHREtgP6AdcXrFB2ju8uetqV2BORKzIQ4xbRFKjQsdgZlYbuUA2M9sCEfEe8C+gB6zvBb1W0nPASmAXSZ0kjZX0saS3JJ2Xtv028Gfg4LQ3+ipJJZLmpev/CnQBxqXrL654/Fx7ScMlfZT2OJ+ZWd9E0g2S5qa93X+U1KzCtpdI+gD4SyX7HyrpOUm/kbRE0mxJ/dPl70r6UNKQTPvWku6StFDSO5Iuz/2RkG7zbBrPYklvSzo6XXctcChwS3qut2TCOELSrHSb30vS1n/HzMy2nHsPzMy2gKSdgWOAf2YWfws4GpgJCHgcmA50AvYEHpM0OyJul1QOnBsRh6T7K8ntJCK+JenQdP3jmwhjR2B7YCfgIGC8pMkRMRP4BbAL0BtYA9wNXAFcmtm2LUlP9sY6SQ4kKeTbAVcB9wDjgF2BrwBjJI2JiOXAzUDr9JjtgAnA+8DtmX3dmcY7DLhd0k4RcZmkAcDfIuLPFY5/HEkv/bbAlPTYj2zi62FmVq3cg2xmVjUPSFoCPAs8BVyXWTcyIqZHxFqSAvQQ4JKIKIuIqSTF5reqOZ4REbEqIp4CHga+kfa0ngf8X0R8HBHL0jhPy2y3Dvhpuu2nG9n32xHxl4goB+4FdgauTreZAKwGdpXUEDgVuDQilkXEHODXFc71nYi4Ld3XnUBHoMNmzu36iFgSEXOBJ0mKfTOzGuMeZDOzqjlxE72672ZedwJyxWnOO0DfaoxlcYUxzO+kx20PNAemZEYlCGiYabswIso2s/8FmdefAkRExWUtSXqFt0mPn41lp8z7D3IvImJlGtfmbnD8IPN6ZRXam5lVK/cgm5l9cZF5PR9oK6lVZlkX4L2t2NfGbCepRYX9zwc+Iile94mINum/1unNhVuy/6r6iGQYR9cKsVTnuZqZ1TgXyGZm1Sgi3gWeB34uqamkXsC3gVFV3MUCkvG8m3OVpG3SMcvHAfdFxDrgNuA3knYAkLSTpMFbfCJVkA6b+AdwraRWkroCPwT+VsVdVPVczcxqlAtkM7PqdzrQjaRX936SMb+PVXHbnwOXpzNI/GgjbT4AFqf7HwV8JyLeSNddArwF/EfSJyQ3DO5R6V6qxwXACmA2yfjsu4E7qrjtb4GT09kqfpen+MzMtpgi/AmXmVldkc568beI6FzoWMzMipV7kM3MzMzMMlwgm5mZmZlleIiFmZmZmVmGe5DNzMzMzDKK5kEh22+/fXTr1q3QYRTcihUraNGixeYbWtFzLliOc8FynAuW41xITJky5aOIaF9xeV4LZEltSB6x2oNkQvhzgJkkjy7tBswBvhERiyWdBFwNfEzyxKpFkr4EXBsRp1Wy+w1069aNyZMn5+U86pLS0lJKSkoKHYbVAs4Fy3EuWI5zwXKcCwlJ71S2PN9DLH4LPBIRewL7AjOAnwBPRMRuwBPpe4CLgIOAu4Az0mXXACPyHKOZmZmZ2Xp5K5AlbQt8GbgdICJWR8QS4ATgzrTZncCJ6et1QBOgObAmfTrU+xExK18xmpmZmZlVlLdZLCT1Bm4FXifpPZ4C/AB4LyLaZNotjojtJB0JXE/yZKhvkjy+9LSIWLyJYwwDhgF06NBh/3vuuScv51KXLF++nJYtWxY6DKsFnAuW41ywHOdC7fDae0sLHQLdWzd0LgADBw6cEhF9Ky7PZ4HcF/gPMCAiXpD0W+AT4ILKCuQK2w4B2gAvAD8ieaTqDyJi5caO17dv36g4BnnNmjXMmzePsrKy6jqtWq+srIymTZtu9fZNmzalc+fONG7cuBqjskLw+DLLcS5YjnOhduj2k4cLHQIjj2rhXAAkVVog5/MmvXnAvIh4IX0/mmS88QJJHSPifUkdgQ8rBNocGAIMBiaQDMk4AzgTuG2LApg3j1atWtGtWzckfbGzqSOWLVtGq1attmrbiGDRokXMmzeP7t27V3NkZmZmZnVD3sYgR8QHwLuS9kgXHU4y3GIsSQFM+v+DFTa9GPhtRKwBmpHMfrGOZGzyFikrK6Ndu3b1pjj+oiTRrl27etXjbmZmZlZRvudBvgAYJWkbYDZwNklR/g9J3wbmAqfkGkvqBPSNiCvTRb8mGaaxhM9u5tsiLo63jL9eZmZmVt/ltUCOiKnA58Z1kPQmV9Z+PnBc5v19wH35ic7MzMzM7POK5kl6VVHdg+LnXH9ste5vc0pLS7nhhht46KGHqtR+6tSpzJ8/n2OOOSbPkZmZmZkVj3w/KMSqydq1a7d4m6lTpzJ+/Pg8RGNmZmZWvFwg59mcOXPYc889Offcc+nRowdnnnkmjz/+OAMGDGC33XbjxRdf5MUXX6R///706dOH/v37M3PmTABGjhzJKaecwvHHH8+gQYM22O+kSZPo06cPs2fPZsWKFZxzzjn069ePQw45hAcffJDVq1dzxRVXcO+999K7d2/uvffeQpy+mZmZWZ1Tr4ZYFMpbb73Ffffdx6233kq/fv24++67efbZZxk7dizXXXcdd911F08//TSNGjXi8ccfZ/jw4YwZMwaAiRMn8uqrr9K2bVtKS0sBeP7557ngggt48MEH6dKlC8OHD+ewww7jjjvu4N133+Xwww/niCOO4Oqrr2by5MnccsstBTx7MzMzs7rFBXIN6N69Oz179gRgn3324fDDD0cSPXv2ZM6cOSxdupQhQ4Ywa9YsJLFmzZr12x555JG0bdt2/fsZM2YwbNgwJkyYQKdOnQCYMGECY8eO5YYbbmDdunWUlZUxd+7cmj1JMzMzsyLhIRY1oEmTJutfN2jQYP37Bg0asHbtWkaMGMHAgQOZNm0a48aN22Ae4hYtWmywr44dO9K0aVNefvnl9csigjFjxjB16lSee+455s6dy1577ZXnszIzMzMrTi6Qa4GlS5ey0047Acm4401p06YNDz/8MMOHD18/5GLw4MHcfPPN5B4bniueW7VqxbJly/IWt5mZmVkxqldDLGp6WraquvjiixkyZAg33ngjhx122Gbbd+jQgXHjxnH00Udzxx13MGLECC688EJ69epFeXk5u+yyCw899BADBw7k+uuvp3fv3lx66aWceuqpNXA2ZmZmZnWbcr2OdV3fvn1j8uTJGyybMWNGvRtqsGzZMlq1avWF9lEfv27FqLS0lJKSkkKHYbWAc8FynAu1Q3U/l2FrjDyqhXMBkDQlIj73UDsPsTAzMzMzy3CBbGZmZmaW4QLZzMzMzCzDBbKZmZmZWYYLZDMzMzOzDBfIZmZmZmYZ9WoeZK5sXc37W7pVm910000MGzaM5s2bb9F2I0eOZNCgQesfMW1mZmZm1c89yAVw0003sXLlykrXlZeXb3S7kSNHMn/+/HyFZWZmZmbUQIEsqaGklyU9lL7vLukFSbMk3Stpm3T5BZKmSRqfWXaIpBvzHWM+rVixgmOPPZZ9992XHj16cNVVVzF//nwGDhzIwIEDAWjZsiVXXHEFBx54IBMnTuTqq6+mX79+9OjRg2HDhhERjB49msmTJ3PmmWfSu3dvPv30U6ZMmcJXvvIV9t9/fwYPHsz7778PwKRJk+jVqxcHH3wwP/7xj+nRowcAhx56KFOnTl0f24ABA3j11Vdr/otiZmZmVovVRA/yD4AZmfe/AH4TEbsBi4Fvp8vPBXoBLwODJQkYAfysBmLMm0ceeYROnTrxyiuvMG3aNC688EI6derEk08+yZNPPgkkRXSPHj144YUXOOSQQ/je977HpEmTmDZtGp9++ikPPfQQJ598Mn379mXUqFFMnTqVRo0accEFFzB69GimTJnCOeecw2WXXQbA2WefzR//+EcmTpxIw4YN18dy7rnnMnLkSADefPNNVq1aRa9evWr8a2JmZmZWm+W1QJbUGTgW+HP6XsBhwOi0yZ3AiZlNGgPNgTXAt4DxEbE4nzHmW8+ePXn88ce55JJLeOaZZ2jd+vPjoBs2bMhJJ520/v2TTz7JgQceSM+ePfn3v//N9OnTP7fNzJkzmTZtGkceeSS9e/fmmmuuYd68eSxZsoRly5bRv39/AM4444z125xyyik89NBDrFmzhjvuuIOhQ4dW/wmbmZmZ1XH5vknvJuBioFX6vh2wJCLWpu/nATulr28A/gNMB54DHgCO2tTOJQ0DhgF06NCB0tLSDda3bt2aZcuWrX/fiuqV3ffGdOzYkdLSUiZMmMDFF1/MYYcdRkSwfPlymjRpAkDTpk3Xj0kuKyvj/PPP56mnnqJz585cd911LF26lGXLllFeXs6KFStYtmwZy5cvZ8899+SJJ57Y4HiLFi0iItbHtmLFCtatW7f+fUlJCffccw/33nsvpaWllZ5DWVnZ576WVvcsX77c30cDnAv2GedC7XBRz7Wbb5RnzoVNy1uBLOk44MOImCKpJLe4kqYBEBF/Bf6abvtT4HfA0ZLOAt4FLoqIdRtsGHErcCtA3759o6SkJLuaGTNm0KpVdZfFn6nKvufPn0+HDh0477zzaN++PSNHjmTbbbclIjbYPve6vLwcSXTr1o3y8nLGjRvHySefTKtWrWjTpg3r1q2jVatW7Lfffnz88cdMmzaNgw8+mDVr1vDmm2/SpUsXtt12W6ZPn85BBx3EuHHjaNCgwfr9n3/++Rx//PEceuihdO3atdKYmzZtSp8+farhK2SFVFpaSsWfCaufnAuW41yoHYb+5OFCh8DIo1o4FzYhnz3IA4CvSjoGaApsS9Kj3EZSo7QXuTOwwbQMkjoB/SLiKkkvAgcD1wKHA499oYi2clq2L+K1117jxz/+MQ0aNKBx48b84Q9/YOLEiRx99NF07Nhx/TjknDZt2nDeeefRs2dPunXrRr9+/davGzp0KN/5zndo1qwZEydOZPTo0Xz/+99n6dKlrF27lgsvvJAuXbpw++23c95559GiRZL82WEd+++/P9tuuy1nn312jX0NzMzMzOqSvBXIEXEpcClA2oP8o4g4U9J9wMnAPcAQ4MEKm/6M5OY8gGYkPczrSMYm1zmDBw9m8ODBGyzr27cvF1xwwfr3y5cv32D9NddcwzXXXPO5fZ100kkbjFXu3bs3Tz/99AZtli1bxj777LN+dorrr7+evn37rl8/f/581q1bx6BBg7b+pMzMzMyKWCHmQb4E+KGkt0jGJN+eWyGpD0BEvJwuuh14DdgPeKSG46yzHn74YXr37k2PHj145plnuPzyywG46667OPDAA7n22mtp0MBTYJuZmZlVpkaepBcRpUBp+no2cMBG2r3MZ9O+ERE3kQzLsC1w6qmncuqpp35u+VlnncVZZ51VgIjMzMzM6o6i70aMiEKHUKf462VmZmb1XVEXyE2bNl0/7ZltXkSwaNEimjZtWuhQzMzMzAqmRoZYFErnzp2ZN28eCxcuLHQoNaasrOwLFbhNmzalc+fO1RiRmZmZWd1S1AVy48aN6d69e6HDqFGlpaWew9jMzMzsCyjqIRZmZmZmZlvKBbKZmZmZWYYLZDMzMzOzjKIeg2xmZmZmlXh/Klx5QmFjuHJpYY+/Ce5BNjMzMzPLcA+ymZlZDej2k4cLHQIjj2pR6BDM6gT3IJuZmZmZZbhANjMzMzPLcIFsZmZmZpbhAtnMzMzMLMMFspmZmZlZhgtkMzMzM7MMF8hmZmZmZhl5K5Al7SzpSUkzJE2X9IN0eVtJj0malf6/Xbr8pLTdM5Lapcu+JOmefMVoZmZmZlZRPnuQ1wIXRcRewEHAdyXtDfwEeCIidgOeSN8DXJS2uws4I112DTAijzGamZmZmW0gbwVyRLwfES+lr5cBM4CdgBOAO9NmdwInpq/XAU2A5sAaSYcC70fErHzFaGZmZmZWkSIi/weRugFPAz2AuRHRJrNucURsJ+lI4HpgPvBN4B/AaRGxeBP7HQYMA+jQocP+99zj0RjLly+nZcuWhQ7DagHnguU4F2qH195bWugQ6N66oXOhFqgVudBsFS1XzS9sEB17F/b4wMCBA6dERN+Ky/NeIEtqCTwFXBsR/5S0pLICucI2Q4A2wAvAj4DFwA8iYuXGjtO3b9+YPHlyXs6hLiktLaWkpKTQYVgt4FywHOdC7dDtJw8XOgRGHtXCuVAL1Ipc2HcWJTN/Wtggriz8HwqSKi2QG+X5oI2BMcCoiPhnuniBpI4R8b6kjsCHFbZpDgwBBgMTSIZknAGcCdyWz3jNzMyK2vtT4coTChtDLSiKzDYnn7NYCLgdmBERN2ZWjSUpgEn/f7DCphcDv42INUAzIEjGJzfPV6xmZmZmZjn57EEeAHwLeE3S1HTZcJJxxv+Q9G1gLnBKbgNJnYC+EXFluujXwH+AJXx2M5+ZmZmZWd7krUCOiGcBbWT14RvZZj5wXOb9fcB91R+dmZmZmVnl/CQ9MzMzM7MMF8hmZmZmZhkukM3MzMzMMlwgm5mZmZlluEA2MzMzM8vI64NCzOqrWvGUpKNaFDoEMzOzOsk9yGZmZmZmGS6QzczMzMwyXCCbmZmZmWW4QDYzMzMzy/BNemZmeeQbNs3M6h73IJuZmZmZZbhANjMzMzPLcIFsZmZmZpbhAtnMzMzMLMMFspmZmZlZhgtkMzMzM7OMghTIko6SNFPSW5J+ki4bJelVSddl2o2QdEIhYjQzMzOz+qnGC2RJDYHfA0cDewOnS+oFEBG9gEMltZbUETggIh6s6RjNzMzMrP4qxINCDgDeiojZAJLuAY4FmklqAGwDlANXA1dUdaczZ86kpKSk+qOtY5YsWUKbNm0KHUa998HsRYUOgQsfaehcqAWcC5ZTK3Jh7Ke0WbmisEGUlhT2+LWAcyFVi3OhEAXyTsC7mffzgAOBucBLwF+BXQFFxMub2pGkYcAwgMaNG7NkyZK8BFxVK1atLejxAZo2UsG/DgZ7tm1Y6BAoX7uGJR/OK2wQ27Qs7PFrAedCyrlQO3KhvBlL2vQobBD+HeVcyKnFuVCIAlmVLIuIuHB9A2kc8D+SLgP2BR6LiNsq2ehW4FaAvn37xuTJk/MUctXUhkfK3nZUC/ekGwClf7+Jkpk/LWwQV75V2OMb4Fywz5SWlvp3hAHOhRypsrK0MAXyPGDnzPvOwPzcm/SmvMlAC6BHRHxD0tOSRkXEypoN1cysCHTsDacvLXQUZmZ1RiFmsZgE7Capu6RtgNOAsQCSGgM/AH4FNAciE+c2BYjVzMzMzOqZGu9Bjoi1kr4HPAo0BO6IiOnp6u8Cd0bESkmvApL0GjA+ImrvQBUzMzMzKxqFGGJBRIwHxley/KbM6wBOr8m4zMzMzMz8JD0zMzMzswwXyGZmZmZmGS6QzczMzMwyCjIGuVjNuf7YQodAaWlpoUMwMzMzq9Pcg2xmZmZmluEC2czMzMwsw0MszIqVn55mZma2VdyDbGZmZmaW4QLZzMzMzCzDBbKZmZmZWYaSJzrXfZIWAu8UOo5aYHvgo0IHYbWCc8FynAuW41ywHOdComtEtK+4sGgKZEtImhwRfQsdhxWec8FynAuW41ywHOfCpnmIhZmZmZlZhgtkMzMzM7MMF8jF59ZCB2C1hnPBcpwLluNcsBznwiZ4DLKZmZmZWYZ7kM3MzMzMMlwgm5mZmZlluEA2MzMzM8twgWxWh0lSoWMws9ohez3wtcHsi3GBXEdI8vfKAJD0JUl9ASIi/IvQzFItcy/Sa4N/b9RD/r5XD89iUQdIOgzoBDwcEYsLHY8VjqRjgV8BC4BmEXFQulzhH+Z6RdKXgXXA8xGxrtDxWGGl14aLgYnApxFxVbq8gfOj/nC9UH38V0YtJ2kA8DgwBBgkabsCh2QFImkf4BrgmxExEPhQ0i6Q9BYVNDirUZK+ApSS/LF0oHuM6jdJPYGbgF8CDwMHSHoIICLWOT/qB9cL1cs/NLWYpEbAdsCpwJ+A44Cjsknvj9frlWXAy8BCSe2AAcC1kh5Ji2fnQz0gqQmwK3AS8FfgCuBgF0H12grguYh4OCKeiYhjgSaSxkFSJBc2PMs31wvVr1GhA7CNi4i1kh4FtomIFekvxqOBBpL+FREfu+ewXlkNlAPXAf2A6yPiV5JuBH4DDHI+FL+IWCXpn8CaiFguqTlwGfBzSc9HRHmBQ7SatwboKKlfREwCiIgjJT0k6ZKI+EWB47M8c71Q/Vwg10KSSoASYBZJr8AcgIgYlfYSDSb5eL0PsF1EXFqgUC3P0o/MDgTeBJ4FhgNtgBHAgwAR8UNJEyTtFhGzChas5ZWk/sD+wDRgakQsB4iIG9KeoUuB70s6lOS6cGPhorV8S/NhP2B6RDwp6R/Ag5IGRsTMtNnvSa4fVqRcL+SPC+RaRtLRwPXAGOAooAWZ56VHxF8lfQDcALQFvlqIOC3/JB1HkguPAfuQ/DL8VUQslPQm0EfSx8ChQAfAN2QUKUlHAb8GHiX56PS3wHhJDSOiPP0kYSHJ+EMBxxYuWsu3CvlwgqRmEXG7pLbAk5JOiYjngO7AQWlv4mr3IBYX1wv55QK5FpG0B0kP4Xcj4llJPwB2lbQ7UBYRc9OmLYFdgAMj4vUChWt5JGk34ErgnIh4UdLhJD2EtwCfAq8B/wO82tQ6AAAgAElEQVScAnQluXHvowKFa3kkqTfJzXjDIuI5ST8D9pE0GVgLfJw2XUoyBvFgXxeK10byoZekyekfSu8Al0haCfQETo2IVYWM2aqf64X88zRvtUg6yH6viHhN0g7AcySF0FySBL8sXXck8J6TvXiluXAaMDoiytJlDwC/i4h/p+93ArYBVkXE/IIFa3klqTGwb0RMltQRmAy8CCwhuXHzRuA94ExgUkRML1iwlnebyIdlJDkxHGhO2gHma0Nxcr2Qfy6Qa4mKc1Wmc5zunI4j2h64HPhPRNzjOW+LWyW50DAiytMbs/4SEeMkHUBy0XuvcJFavlWSC8cAXSPiD5L2BS4Cbo+Ip3J5UrBgLe+qkA8XA7dGxFMFC9LyzvVCzfAQi1qi4jQ8EfF05vVHkhoCO6TvnexFrJIpmRqQzF7xLvC+pOOB/yPpMbQiVsl1YXzm9SuSyoGd0/cujotcFfJhNdC5xgOzGuV6oWZ43sxaprJ5CiV9AzgEGP/5LazY5HIg939ErElXLQJuI+kd+EFEvF+YCK2mVMyFCuu+QXLj5nM1HZfVvLToyb3eVD48X5NxWc2Q1KKSZa4X8sgFcoFI2rGSZYqIkNRX0rfTZd8EriK5Ceutmo7T8k/SgZKGSvqKpLZpDjTM5MJ5adNtgb2BMyLitQKGbHki6VBJF0g6UdL2aQ40SP/vJekESY3S68LVJLnwdqHjtvyQdKSkkZB8QpB+750P9Uw6o9ENkppllrleyDMXyAUg6URgvqSh2eVpsh8M/Bl4J118H8kDIHzjTRFKL3x/JvmLfwhwtqRG6S/DXC7MSZtfBvSMiP8WJFjLq3TKpltIPiI/FRgE6x8VfBgwCvgoItYCTwJH+bpQnJRoRDJd31mS7oLkYRBpPgzE+VAvKJnS72rgHxHxaW55Wi8cguuFvPFNejVMUifgZpKEHkzyNLS/ZtafCSyOiPFpobS2QKFanil5PPQo4OyIeFnS10iK5FMjeVpaNhcaZ4ZaWJGR1JNk/tKLIuJ5SSNInpw4imT6tmOAdRFxn2+6qT8kHQj0JpnOcVUkj5DOfYy+LiJGOx+Kl5LpPu8H/hgRtyiZ53o/YDkwEziA5Ml541wvVD8XyDVMyWNhD4qIf6e9ALcDP80WyWk735Fe5CS1A04imYWgPF32GHBpREzOtHMuFDlJ2wG7RMSU9C70F4AZJH9Ib0cy5nyhi6H6ITO2dBDwtYj4jqRSoBnJI8YPybVzPhSvtCC+FphN8jTVS0muCZH+uyC9Kc95kAceYlFDJO0oaceIWBnpPLYR8SRwDnCVpLPSdl9Oxx66ICpSaS50jIhFEXFrOpyiSbp6LensMpJ6S2rtXChemevC4oiYki4+FLg6Io4Dfk7yYJiDwHekF7s0H9rHZx4Fcp8cXUZyD8L6cajOh+KU+R3xMUlR3Am4jmSaz1OBHwMrgH7gPMgXT/NWAySdBFwINJZ0PzA1vfAREaXpAPvfp2ON9iZ5lKwVoY3lQnz2pKv3gQ8lfR04j2TIhRWhCrnwT+CVNBfuz7WJiHmSAmhTqDitZlSSD69FxL/SdTcDR5BM7fgzSXdHxBmFi9bypUIejAWeAC4B/hUREwAi4l1JDUgeH2154iEWeZZ+jP44SU/xGuBIYA/gyYi4N9PuFpIbcw7zDAXFqSq5IOlGoA/J40HPjohpBQrX8mgTufBURPw90+4kkmn9ToqI2YWI1fJvI/mwF/AAyRPybgMuj4jRafvunq2i+GwkD/YBHoqIBzLtTib5RMHXhTxyD3L+NQQ+Ad6OiCWSFpH0BHxF0sJ0LPJeJI+GPMLFcVHbVC4siojHSXoE9gf28zQ9RW1juXCopAXpdWEYyQNhTvYvwaK3sXw4Dvg3cHhEvJe7WdfFcdHaWB4MlvRJel34JvATkpu5fV3II49BzrOI+BCYSjKHYYtIHu7wBMnz0nunzd4BzoyIVwoUptWAzeTCvmmzK0hu4nRxXMSqeF0YCxzrKZuK32byoXNaHMsz2RS3TeTBO3x2XZgAHO/rQv65QM6jdIwQwO9J/iq8JE36+cCjwAmS2qU37i0uWKCWd1XIha+mN+fMjYjXCxao5V0VrwvbR8QH7iEqflXIh69JauMbsYrbFlwXPvQnCDXDBXIe5Kboic+el/5fkrkMmwN/TKdx2p1kxgL3CBSxLcyFVZXuxIrCFubC6oIEaTVmC/NhXaU7sTrP14XayzfpVaN0zsKyiFiZWbZNRKyW1JlkfOkQkpkq2gLnR8RLhYnW8sm5YDnOBctyPhg4D+oCF8jVRNIJwLkkPcL3AzMifdiDpMOB75A8JWuupNbA2ohYUbCALW+cC5bjXLAs54OB86CucIFcDSTtDowhmaZte+B4oDPJWKIXgGeAX0XEmIIFaTXCuWA5zgXLcj4YOA/qEk/zVj22B+blbq5S8tjY7wLfAD4CToiIBeldyP6LpLg5FyzHuWBZzgcD50Gd4Zv0qsc0YKmky9L3+wEzSW666h4RC8CPg6wnnAuW41ywLOeDgfOgzvAQi62UDqJfFhFLJTUCBpL8FdgAICK+Kul04ChgqJO9eDkXLMe5YFnOBwPnQV3lIRZbQdKJwPXArZL+GhELgcckPQHsACxMm7YCljjZi5dzwXKcC5blfDBwHtRl7kHeQpLaA/eQPOFoHvAhcE+a9Nl2FwJnA98MPz66KDkXLMe5YFnOBwPnQV3nMchbbilwIck0LFOBXYHTJO0An036TfJM9TOd7EXNuWA5zgXLcj4YOA/qNPcgV5GkLsAHQKMKE3ufBHwFmBURN0vaz5N5FzfnguU4FyzL+WDgPCgW7kGuAknHAuOBW4C/SNozty6dq/ApoL2kB4CnJO1UmEgt35wLluNcsCzng4HzoJi4QN4EJXYmGWD/PWAE8CLwb0n75NqlSb8L0BvoHxHvFSJeyx/nguU4FyzL+WDgPChGnsViEyIiJM0HJgKzgA8j4teS1gATJA2MiDcldSSZy/BEjyEqTs4Fy3EuWJbzwcB5UIw8BnkjJO0KbAfMBv4fMCUifplZfzGwN3B+RHwqqWVELC9MtJZPzgXLcS5YlvPBwHlQrNyDXAlJxwHXAYuB14BRwO8kNYyIn6fN/gEMB8oAnOzFyblgOc4Fy3I+GDgPipkL5Aok9QduAE6PiJcl3QocAPQH/iOpIcm8hoeQfEzShuQHw4qMc8FynAuW5XwwcB4UOw+xqCBN+N0jYmT6vj0wMiKOlbQLcDnJX4EHAGd7DFHxci5YjnPBspwPBs6DYucCuYL0L74WEfFJ+rojMA44JiLel9QVeC9ts7SQsVp+ORcsx7lgWc4HA+dBsfM0bxVERHlEfJK+FbAE+DhN9m+SjCNq7GQvfs4Fy3EuWJbzwcB5UOzcg1wFkkYC7wODgKH+mKT+ci5YjnPBspwPBs6DYuICeRMkCWgMzEj/PzwiZhU2KisE54LlOBcsy/lg4DwoRi6Qq0DSUGBSREwvdCxWWM4Fy3EuWJbzwcB5UExcIFeBJIW/UIZzwT7jXLAs54OB86CYuEA2MzMzM8vwLBZmZmZmZhkukM3MzMzMMlwgm5mZmZlluEA2MzMzM8twgWxmZmZmluEC2czMzMwswwWymZmZmVmGC2QzMzMzswwXyGZmZmZmGS6QzczMzMwyXCCbmdUwSVdK+tsX2H66pJJqDCkvJJ0vaYGk5ZLapf/vUui4zMw2p1GhAzAzs42TNBKYFxGX55ZFxD6Fi6hqJDUGbgQOiohX0sUtM+tHUuG8zMxqC/cgm5lVI0n1ouOhCufZAWgKTK+BcMzMqpULZDOzL0jSHEmXSHoVWCGpkaROksZIWijpbUnf38T290n6QNJSSU9L2iddPgw4E7g4HZ4wLnO8I9JjfCqpbWZffSR9lPbgIukcSTMkLZb0qKSuG4mhm6SQNEzSfEnvS7oos/5KSaMl/U3SJ8BQSU0k3ZS2n5++biJpd2BmuukSSf9O9xGSdt3YeZmZ1RYukM3MqsfpwLFAG2AdMA54BdgJOBy4UNLgjWz7L2A3YAfgJWAUQETcmr7+ZUS0jIjjsxtFxHxgInBSZvEZwOiIWCPpRGA48HWgPfAM8PfNnMfANJZBwE8kHZFZdwIwOj3HUcBlwEFAb2Bf4ADg8oh4E8gNA2kTEYdViHuT52VmVmgukM3MqsfvIuLdiPgU6Ae0j4irI2J1RMwGbgNOq2zDiLgjIpZFxCrgSmBfSa2reNy7SYpzJCk9xt3puv8Bfh4RMyJiLXAd0HtjvcipqyJiRUS8Bvwlt+/UxIh4ICLWped5JnB1RHwYEQuBq4BvVTFuM7NaywWymVn1eDfzuivQSdKS3D+SntwOFTeS1FDS9ZL+mw5dmJOu2r6Kxx0NHCypE/BlIEh6inNx/DYTw8eASHq1q3Ie7wCdNrKOdN07m2hvZlYn1YubSczMakBkXr8LvB0Ru1VhuzNIhi4cQVIctwYWkxSyFff7+YNGLJE0AfgGsBfw94jIbfMucG1EjKrqSQA7A2+kr7sA87OHq9B2PkkRPn0j7TcZ+hbEZGZWo9yDbGZW/V4EPklv3GuW9hL3kNSvkratgFXAIqA5yTCIrAXA5uYOvhs4i2Qs8t2Z5X8ELs3c9Nda0imb2dcISc3Tbc4G7t1E278Dl0tqL2l74AqgqvM7V+W8zMwKwgWymVk1i4hy4HiSm9feBj4C/kzSO1zRXSRDE94DXgf+U2H97cDe6TCJBzZyyLEkN9YtyMw5TETcD/wCuCcdvjENOHoz4T8FvAU8AdwQERM20fYaYDLwKvAayQ2G12xm/zlVOS8zs4LQZ5/EmZlZfSWpG0kx3zi9oc/MrN5yD7KZmZmZWYYLZDMzMzOzDA+xMDMzMzPLcA+ymZmZmVlG0cyD3KZNm9h1110LHYbVQitWrKBFixaFDsPyzN9nq4zzwnKcC1aZKVOmfBQR7SsuL5oCuUOHDkyePLnQYVgtVFpaSklJSaHDsDzz99kq47ywHOeCVUbSO5Ut9xALMzMzM7MMF8hmZmZmVmdEBGvK1+X1GEUzxMLMzMzMilNE8Np7S2ncsAF/ee5txr4yn307t+HjFatp0rgBu+/QisuP25u2LbZhxaq1NGwgxr/2Pk/OXMjuO7Tke4ftiqQqH6+oC+Q1a9Ywb948ysrKCh1KndG0aVM6d+5M48aNCx2KmZmZGX/9zzvc9vRs5n68cv2yAbu2Y/mqcnZp34JVa9fxwNT36NC6KcvK1vCPSfNYnfYwt22xDeNemU/DhuJ/SzaczGHxitUbPWZRF8jz5s2jVatWdOvWbYv+aqivIoJFixYxb948unfvXuhwzMzMrJ6LCH4+fgY7b9ecX57ciw8/KWP12nX835G7b1DbnTNyErc+PZvydcE3+nZmx22bsluHVhzbsyPnj5rCTY/PYmj/bjTfJil9/7twOV+9+dmNHreoC+SysjIXx1tAEu3atWPhwoWFDsXMzMyMDz4pY+Xqcr55cFe+0XfnjbY7rd/O/PuND+n/pXb84qReG9R+Q/p349HpC3hm1kcM3mdHytcFF49+lYYNNl4fFv1Nei6Ot4y/XmZmZlZbzF64AoAvbb/pOawP23MHfnjk7vzqlH0/V8v069aWbZs24rHXFwDwy0feYMo7i/np8ftsdH9F3YNsZmZmZnXX7IXLAdilfctNtmvUsAHfP3y3Stc1btiAw/bcgYdffZ83Fyzj1XlLOevgrnx9v502ur+i70EuJqWlpRx33HFVbj916lTGjx+fx4jMzMysNitfF/zq0Te4+YlZX2g/S1au5q6Jc1i1trx6Aqui/y5cQYttGtJh2yZfaD//d+TufGX39jRqIC47Zi+uOG7vTX5q7h7kOmLt2rVbvM3UqVOZPHkyxxxzTB4iMjMzs9rik7I1/OXZORy+1w702Kk1kNzg9uPRr/DPl94D4JDdtqdPl+22av8/H/8G905+l8Ur1vCDIyrvqd1S69YFUjK885OyNTw36yP6dW/Lp6vL6bxdMyTx34XL6d6+xRceAtq1XQv++K39q9zePch5NmfOHPbcc0/OPfdcevTowZlnnsnjjz/OgAED2G233XjxxRd58cUX6d+/P3369KF///7MnDkTgJEjR3LKKadw/PHHM2jQoA32O2nSJPr06cPs2bNZsWIF55xzDv369aNPnz48+OCDrF69miuuuIJ7772X3r17c++99xbi9M3MzCzPIoLL7p/Gbx5/k+NufpZL//kqj72+gN8+MYt/vvQe//OVXdihVROueHD6Fj9g480Fy/jlI29w35R3admkEb8vfYs5HyXjgj9esZrVa5P9vTx3MU/O/JCIqNJ+75v8Lgdf/wT9rn2CW5/+L98eOYnzR71E32se59BfPsnQv0zirQ+X89aHy9ll+00Pr8iHetODfNW46bw+/5Nq3efenbbd5ADvnLfeeov77ruPW2+9lX79+nH33Xfz7LPPMnbsWK677jruuusunn76aRo1asTjjz/O8OHDGTNmDAATJ07k1VdfpW3btpSWlgLw/PPPc8EFF/Dggw/SpUsXhg8fzmGHHcYdd9zBkiVLOOCAAzjiiCO4+uqrmTx5Mrfccku1nreZmZnVHg9MfY9xr8znf0u+xNp1wW3PzObvL74LwCG7bs8lg/dk385t+N9RL3HSH54nAs4e0I2v79d5k/v99xsL+M7fXmJt+Tp279CKm07rzcl/mMiIB6fxm1N7M/BXpXRo3ZQh/btx3cMz+HRNOW2aN6Zj62b84qSeTHvvE07rtzMNMrNFfPhJGR8uW8Xw+1+jx06tadKoAdeNfwOA4cfsSfk6WFO+jj899V+OuPEpAA7+Urs8feU2rt4UyIXUvXt3evbsCcA+++zD4YcfjiR69uzJnDlzWLp0KUOGDGHWrFlIYs2aNeu3PfLII2nbtu369zNmzGDYsGFMmDCBTp06ATBhwgTGjh3LDTfcACTT282dO7cGz9DMzMxq2trydZTOXMgVD0ynb9ftuGjQHjRsIL51UFeWrExqib06tqJBA3FMz46ceWAX7n/5PTq1acYP//EKfbu2pUu75hvd/32T57Fd88Y8/P1D2b5lMgb4okG7c9W41znr9hdZvnotLcrWMuKBaXRs3ZQL++/GmwuW89Cr8/nqLc8B0KlNU0r22AGAif9dxDkjJ/HpmnJaNWnErd/qS/tWTZi9cDmLV65h/66fDf/4Rt+dGfXCO/Tp0oaB6fY1qd4UyFXp6c2XJk0+G1jeoEGD9e8bNGjA2rVrGTFiBAMHDuT+++9nzpw5lJSUrG/fosWG05p07NiRsrIyXn755fUFckQwZswY9thjjw3avvDCC3k6IzMzMyu0Pz09m189OpPtWzbhN6f2Xj+v785tm7Nz28+3v+bEHlz51X2Y+u4STvnjRP770fJNFshzFq1k747bri+OAc46uBsvvv0x/5r2Acf16shvTu3Nq/OW0LF1Mzq1aQYkU6797T/v8Pr7nzDmpfco2WMHFnxSxrl3TqLzds0YsOv2HLRLW9q3SvZb2QwVO7ZuykWD9vjc8ppSbwrk2mzp0qXstFMy1cjIkSM32bZNmzbcfvvtDBo0iBYtWlBSUsLgwYO5+eabufnmm5HEyy+/TJ8+fWjVqhXLli2rgTMwMzOzmvbqvCV0a9ecR//vyzRp1HCz7SXRuKHo2jYpiucuWrnRthHBO4tWcNAuG1baDRuI353eh3tenMvgfXakccMG7N91wzbH9urIsb06MuKBafxj8rv8v9K3eG3eUlaXr+PPQ/rStd2m5zSuDWr1TXqSWki6U9Jtks4sdDz5cvHFF3PppZcyYMAAyss3P31Khw4dGDduHN/97nd54YUXGDFiBGvWrKFXr1706NGDESNGADBw4EBef/1136RnZmZWhGYtWM6eO25bpeI4q32rJjRr3JB3NlEgL1y2ipWry+lWSTHbuGEDvnVwN3bYtukmj/PNg7qyXfNt+OUjM/nXtA/45kFd60RxDFXoQZa0M3AXsCOwDrg1In67NQeTdAdwHPBhRPSosO4o4LdAQ+DPEXE98HVgdESMk3QvMGprjltI3bp1Y9q0aevfZ3uIs+vefPPN9ct/9rOfATB06FCGDh26fnlJScn64RddunRh+vTp69f96U9/+tyx27Zty6RJk6rjNMzMzKwWKVtTzpxFKzi2V8ct3lYSXds1Z+7HKzbaZk5aPHfbzBPsNmWPHVvxn+GHs3jFaqa8s5hDdtt+q/dV06rSg7wWuCgi9gIOAr4rae9sA0k7SGpVYdmulexrJHBUxYWSGgK/B44G9gZOT4/RGXg3bVazM1ObmZmZ1VKzF67g/7N35+FRlWfjx79ntkwmyWSy7zshZAHCvgiyKJuKu7hvLVrbattfW6ttfa1aW7tr37fa1talVlsXFJHVDZAgOwTCGkgCIcuQfTJJZp85vz8OCYQkZCEb8HyuKxfkzFmeGQLc5z73cz8+GdKjgrrfuROJoYZ2GeT1R6q44jfr+dXqQwBtrdxS+iHjGxKg4+qsKPTa3mW6h1K3AbIsy2ZZlvec/n0TcBg4d22+WcAKSZL0AJIkPQT8byfn2gTUd3KZyUCRLMslsiy7gHeBG4BylCC5y7FKkrRYkqRXm5ubu3srgiAIgiAIFxWfT+Y3a49woKKx3fZj1coco5FRfesRnBRmoLTehs8nU9vs5OG3dtPi8vCPvOM8/sE+/rapGFC6UFyOelWDLElSMjAOaNceQZblD4B1wLuna4W/ASzpxanjOJMpBiUwjgM+Am6RJOmvwMrODpRleaUsyw8HBg5+E2lBEARBEISBtP14PX/7qpjH/puPw33mYfrRqibUKomUPpZAJIUF4PL4qLDYyTtWg8cn88YDk7htQjyr95spqWkhJTwAjXpYT1cbMD3uYiFJUiDwIfADWZY7rLghy/LvJEl6F/grkCbLcm9Sup2tHyjLstwCPNiL8wiCIAiCIFwyPthdhk6j4nhtC//MK+HRuel4vD5W7K1kXIKp1xP0Wo1LNCFJcMer24g16QkP1DE23sS4xBBeuHk0O07UE2LQ9fO7uXj06LZAkiQtSnD8jizLH3Wxz0wgB1gO/KKX4ygHEs76Ph6o7OU5BEEQBEEQLhmNNjdr95/ilvFxzBgRzrs7y/D5ZFbvN1PeYOfhK1P7fO7s2GCWPTINp8fHzhMNXJke0bbinUatYnpaOJkxxv56KxedbgNkSZIk4DXgsCzLf+pin3HAP1Dqhh8EQiVJer4X49gJpEuSlCJJkg64A/ikF8cLgiAIgiBcUn7/2RGcHi/3TUvmlglxlDfY+fOXx3hq+QEyooK4OjPqgs4/ISmU1+6fSEywvttlpy83PckgXwHcC8yVJGnv6a9rztnHANwmy3KxLMs+4H6g9NwTSZL0X2ArkCFJUrkkSd8EkGXZAzwKfIoyCfB9WZYPnnv8peKll17CZuu692BX3nzzTSorRWJdEARBEC51haeaeGf7Se6fnkxmjJEF2dEE6NT8+ctjxJj0vPHgpLaM74UYm2Biy5NzL6oWbIOh2xpkWZY303mN8Nn7fH3O926UjPK5+915nnOsAdZ0N55LwUsvvcQ999yDwdBxeUev14ta3Xk90ZtvvklOTk7bEtOCIAiCIFyaXt1Ugl6j5vtXpQNg0Gl47YFJNDs8zBwZ3ufa484oxQLC2S7PqYmDqKWlhWuvvZaxY8eSk5PDs88+S2VlJXPmzGHOnDkABAYG8vTTTzNlyhS2bt3Kc889x6RJk8jJyeHhhx9GlmWWLVvGrl27uPvuu8nNzcVut7N7925mzZrFhAkTWLBgAWazGYCdO3cyZswYpk2bxuOPP05OjrImy8yZM9m7d2/b2K644goKCgoG/0MRBEEQBKFTLU4Pb3x9nE/2VbBkYjymsybKTU0N4+qsqH4NjoXO9biLxUVv7ZNwan//njN6NCz6zXl3WbduHbGxsaxevRqAxsZG3njjDTZs2EB4uPI4o6WlhZycHJ577jkAsrKyePrppwG49957WbVqFbfeeit/+ctf+MMf/sDEiRNxu9089thjrFixgoiICN577z1+/vOf8/rrr/Pggw/y6quvMn36dJ588sm2sSxdupQ333yTl156iaNHj+J0OhkzZkz/fiaCIAiCIPTZB7vKeHblIZLCDDx0AZPwhAsjMsgDbPTo0XzxxRc88cQT5OXlERwc3GEftVrNLbfc0vb9hg0bmDJlCqNHj2b9+vXtlpRuVVhYyIEDB5g3bx65ubk8//zzlJeXY7FYaGpqYvr06QDcddddbcfcdtttrFq1Crfbzeuvv95uGWtBEARBEIbenpMWoo16vnp8DvEhHUsxhcFx+WSQu8n0DpSRI0eye/du1qxZw09/+lPmz5/fYR+9Xt9Wd+xwOPjOd77Drl27SEhI4JlnnsHhcHQ4RpZlsrOz2bp1a7vtDQ0NXY7FYDAwb948VqxYwfvvv8+uXbsu8N0JgiAIgtCf9pZZyE0wDfUwLnsigzzAKisrMRgM3HPPPfz4xz9mz549BAUF0dTU1On+rcFweHg4zc3NLFu2rO21s4/LyMigpqamLUB2u90cPHiQkJAQgoKC2LZtGwDvvvtuu/MvXbqU733ve0yaNInQ0NB+f7+CIAiCIPSe2+vjaFUTJ+tt5CaKAHmoXT4Z5CGyf/9+Hn/8cVQqFVqtlr/+9a9s3bqVRYsWERMTw4YNG9rtbzKZeOihhxg9ejTJyclMmjSp7bUHHniARx55BH9/f7Zu3cqyZcv43ve+R2NjIx6Phx/84AdkZ2fz2muv8dBDDxEQEMDs2bPblXVMmDABo9HIgw+KBQoFQRAEYbj40fv7+GSf0spVZJCHngiQB9iCBQtYsGBBu20TJ07ksccea/u+ubn9qtzPP/88zz/fcZ2VW265pV2tcm5uLps2beqwX3Z2dlt3it/85jdMnDix7bXKykp8Pl+npeWGccsAACAASURBVB6CIAiCIAyuKquDVQVmPtlXiZ9GhU6jYnRcx/lKwuASAfIlaPXq1bzwwgt4PB6SkpJ48803AXjrrbf4+c9/zp/+9CdUKlFdIwiCIAhDqcJi58aXv6amycnIqEA+eXQGXp9MgJ8Iz4aa+BO4BN1+++3cfvvtHbbfd9993HfffUMwIkEQBEEQztZod/PgGztwuL289/BUchNNor/xMHLJB8iyLIsVYnpBluWhHoIgCIIgXLI2FFbj9cq8srGI47Ut/OvByUxJDRvqYQnnuKQDZL1eT11dHWFhYSJI7gFZlqmrq0Ov1w/1UARBEAThkvPpwVN869+7AQjSa3jp9nFMHxE+xKMSOnNJB8jx8fGUl5dTU1Mz1EO5aOj1euLj44d6GIIgCIJw0XF7fTS0uEACk78OnebMfJ/yBhtPrzjAqOggnr4ui8wYIyEBuvOcrR/k5YHXC0FBXe/T1ARqNcycObBjuchc0gGyVqslJSVlqIchCIIgCMJl4IE3dvB1UR0AyWEGln17Ou/tLOM/209isblQSRKv3T+WnMHqUhEWBm+9BcnJ0NnkfJ8PTpwAMT+pg0s6QBYEQRAEQbhQzU4PR6uaGBEZiFGv7XSfsnobXxfVcUNuLNmxRn63rpCZv92A3e1lZno40cYwvj07jdSIwMEbeFYWTJ0Ku3dDQkLH1ysqlNezsnp/7ks8Oy0CZEEQBEEQBMDj9eGVZTYdrWVrcR21zU6uzoriy8NVrNhbib9WzVPXZbIwO5pNx2qYnxVNgJ+GaquDt7eXAvDj+RkkhBpQq1S8s72Uny7KZF5W1NC9qYULobgYGhogJOTM9oYGMJmU1/uiNTvt8YAsw7nzl3w+MJvh2mth48aLLlAWAbIgCIIgCJe96iYHV//xK6wODwB+GhVBeg2r95uRZZkbcmOpbXby8+UH+PnyAwCMii7hujEx/O+XRbi8PsYnmkgINQDwzRkpfHPGMCjz1Oth/mR47W0IHANaLbjd0NgI3/1ux8D2fHxeUJ1uRdeanV63TinTCA1tX8bR0ABJSVBXp2SwL7IyDhEgC4IgCIJw2Xt7aylNTg/fmZ3GhKQQZqZHYHN5uPpPX2G1e/j5NZmEB/rx5ZFqdp6oJyU8gN+tO8IfPjvK5ORQrh0Tw+SU0KF9E801EBAOZ3fuKvoCVtwDDhWcMEB6JpSXwzXXQFxcz8998GNY/UO450OIHadsa81O22xKINyaobbZwGCA7Ozel3EMk9INESALgiAIgjAo3F4fWvXwW8nV7vLy9vaTXJ0ZxU8WjmrbrtPoePPBydQ0OYk0KpnWeVlRbSUTt02Ip7TeRlKoAc1Qv6+C9+GjhyBuIlzzO4ibAHXF8N59YEoA11Go3gFfH4eMNIhogaOf9ezcsg/L6h+y2mZm8SePYXz4KyWTrNfDHXdAVRU0NyuBsZ8f2O0we7ayrbdlHMNkYqEIkAVBEARB6Hden8yx6iY+3F3OvrJGJqWE8K8tpXz0nemMjDpPdnAIvPTlUepbXDwyK7XDa+frOKFRq0gbzEl3XWk4Aat/BJHZYK2Ef86DwEhwNoNaC/cuh21/hQ3/B9VusGrh3X/2+PReZJZJPgpictCa97Bk1+swaSms/yVEjILrroP331eyyc3NMHYsBAYq2ePelnH0dmLhAGWcRYAsCIIgCEK/e+LDApbtLkeSwF+rZseJegDe31nGU9ededzu8vhYua+SpDADE5MHr0RBlmVe2VjMKxuKsLm93D4xgQlJQ1wi0RdeD3z0LeX3d/4X9Eb4+n+h5fQaEOPuheB4WPAruOIHYDnZ60tsMedTXJ1PVmQO+Zv/xIQvfkGaWgd5f1R2MKWCFAqSD7QGSEuD0tLel3G06s3EwgHKOIsAWRAEQRCEflXeYOOjPeXcPD6O78weAcDa/WZ2n2xgxb5Kbp0Yzyd7K/H6ZFYVmKmw2BkVHcS6H1w5oOOqtjo4ZXUQYtDxu08LWbmvkrmjIkkND+Cxq9IH9NoDomQjrHgUGsvgplchJEnZfvUvOt8/MEL56oUKawVrC0uIj8hCpVITlnMLH219he+vfAxdcCLM/CEc/RTqvwa/WoieCZtXwshkCK6CAx+d/wKRmcqXrV6pl06cBm4b3H47vPKKkok+38TCAWplJwJkQRAEQRD6jbnRzq/XHEaSJH48P4NYkz8Aj12VzroDp3jk7d0sfCkPjUrCJ8uMTTCRm2hidYGZumYnLU4v/jo1EUF+XV6jrN6Gy+sjJSwAlUrqcj8Ah9vLJ/sq+XCvg/zPN+Dy+gBlHttPFmbw7VlpSNL5zzFs7f8AHI1wy2uQc0u/n97hcfDuwXcJ9gtGq1b6PxtDUynNuZm8ws+4au5TMPYOmPgNcNmwrPgOn+1+j+uqwGDTwkdvd38RSQ0zfqAE+xW7z2xPnglT74StByAlRZlYeNVMCAuEr/8M+96DxCnQUgs+DdTXgUEPYWfdAFxAKzsRIAuCIAjCEGq0u3l25UGuzozimtExQz2cDrw+mfd3lVFaZyMjOhCn20ddi4txiSamp4W323fniXq++eZOmpweHp6Z2hYct5qfFcWf78jF4fYyJyOSsEA/1CqJ3aUNrC4wc/ur2yiqbkanUfHA9GTWHThFoJ+GmenhrCowkxDqj93lZV95IwBGvYYgvRY/rYqfLcrk6tOT52RZZvV+MwcqrCzbXU5tsxOTn8QtExKYMSKcZqebnLhgsmMHaUW7gVJTCDFjYfStA3L6dUXrsNgtJAS3z8zGxk9ifXAsOWlzaO3w7NX4sSxtBgV6PVyfwZIRi7q/gOzFsvHXrM57gcXoMC76Pcg+8DqV8o0TW6EqHva5IEoDm1+FbVrw2MGUCAUfgDFW+d7vBBy2w5QbL6yV3WkiQBYEQRCEfuT1yfzso/1MTgnllgnx7DnZQFm9jRty29diNrS4aHJ4WPrWTo5WNbPpaC1zMiLx16kHfIx1zU7qW1ykRQSy8Wg1nx+qIis2mM3HajhQYWXx2Fj0WhWbjtZQXNNCo92NWiXh9cntznPftCRigv35OL+CiCA/tpXUkRhmYMWjM0gJD+hwXZVK6vA5AIyJD8agU1NU3cytE+LZX97Iq5tKGJ9owuuT+fumEsbGB1Pf4iLYX8tPFmYQFqBjb5mFFqeXw2YrS9/axfS0MDKig9CpVfx9UwkAs0ZG8K1ZqThP7mfOnNED84EOBVlWAuQxtw/I6Q9VH2Jb+TaSTckdXtOqtRi0AawoXMHS8UtRSSq2lG2huL6YrJhc8i2lTNBoSQtNO+81vD4vy9LnUOCnQxuWyZIpD595ceydsPlFMOWBp4LG3HhWhaWyWGfCiAw3/xM0ujP7v7YACo5DWRmkpvatld1ZRIAsCIIgCP1ElmV+9+kR3ttVxt4yC+MSTdz/2g6anB5MBh1xJj3VTU4OVVp5fvVhAIL8NDy+IIPff1rIO9tLWTqzYyeF/rA8v5zjNS0crWpm/ZHqtlIDAI1KwuMrI8roR3pkEH/7qhhJgjHxJq4dE8OMEeHMHRVJpcWORqUiJEDL7z8t5K2tyupxuQkmyhps3Dw+jp9dk4nJoOtqGJ3SqlXMGBHO4VNWfnlDDjaXh20l9SzKiUaSwNzoINqo71BOcfukREBpH/fa5uO8v7OM3aUNOD0+FuVE8+c7xqHTKBO3NpZdpGUUXbFWgNMKkaO637cPau21XJl4JSqVCpvbhs1tw+62I6PcJEUERHC84Tj55nyiA6NZW7SWeGM8KklFmCGMj458xPenfB+duuufhbagOn6KElTXF58JqgMjYeELsFAJpD/Y+wYFVQVoE2ewJHtJx5NNuB9KH4H67fDpJkiNAqc/rP+qT+9fBMiCIAiC0AcWm4vPDlVxy/h4Smqa2VxUy+ZjtXx5pJo4kz+FVU0sfWsXGrVEUpiB+1/f0e74WSMjyIkzckNuHCOjgthYWM27O8v45oyUPtXEfnrwFC9+fpQmh4cnF41i8djYtteOVjXxw/f3IcsQE6znrimJZMcaKWuwExGo4+bx8ZQ12EiPDEKtkiiqbibEoCUssH0dcOpZLc2evT6bB6YnY9BpiA7u/SPsc/3p9ly8Xhl/nRp/nZprx5wpNzm3VONcWrWKR2al8cisNGqanKw7YOam8fFtwfFFr64YghPaZ0yrjyi/RgxMgHxlUscJk7IsY/fY2wLmquYqGhwNbCzd2L5O2c9IqaWUvJN5XJVyVafnr7BW9DiobgukI7LIN+czIWZCx+x09k1QuAYOrIdKi9Le7uuNfX7/IkAWBEEQLntbimt5Le84r9wzHj9Nz0oclIzvSf674yT5Jy0AmAxaHl+QwaKcaOb+8StKalr43a1jGBtvYvV+MynhBsIC/Gi0u5mfHdXuWtfnxvE/Hx+gsKqJjKggJElClmXK6u1Y7C72lVn4+6YSvndVOla7G71WzbWjY/D4ZJbnl/O7dYWMiAwkNEDHY//N51hVE/dMTeKfm4+z43g9Bq2aTT+ZQ2iArtMAfFS0se33IyK77+0rSVK7gPlCBfr1T0gSEeTHvdOS++Vcw4K1El6eopRS3Pjyme01yhMIIjIHbSiSJGHQGjBoleW0E4MT+fjIx53XKQfFsr5kPTkROUQFRrV7rdPJf10E1T0OpLX+cPvb0NuKk2c6vxkVAbIgCIJw2fvrxmLyjtWy7sApsmKMpIQHtK2MJssydS0uNh+rpcrqwOCnISJQx0d7KjDqNeSftHDz+Lh2HRsARkUrQe4t4+NRqyQyos+/OMainGh+seIAt/51K5JEW/C7bHd52z5Beg0/WVbQ9v0znxzEJ8v4ZJiWGsar903AX6vmZ8v387/ri/i/DUVIgE+G71+V3iEjLFwE9v0XfG7Y+zaMuQ1SZyvbT2yGwGgICBuyoXVfp2xoV6fcqsvJf+cE1b0JpPubCJAFQRCEy5q50c7moloAfvbRflpcXsIClCWGk8IN3PWPbRyosHZ67PvfmoHH5yM3wdQhK/vWNyajUatQd9OGrFV4oB8LsqM5UNnIpKRQPsqvwOXx8Y0rUpieFkZIgI4RkYE884nS8SI53MCqAjNalcR1Y2PbrU7321vGcHVmFFtL6rh1QjwJoQYCdeK//IuOLEP+OxA/Caxmpb1Z6mylvOLoOpj15JAOrzd1yhNiJwC9C6p7GkgPBPG3RRAEQbhsbThSzUtfHEWW4Z6piby97SRLJsazsbCGpz7eT0SQnsPmJh5fkMHU1DBGRQdhc3k5WNlIo93N6Piu24RFGntfl/vyXeORJOVR9g/nj6SoupnZGZHt9nnx9ty233fVpkySJOZnRzM/O7rXYxCGkYPLob4Yrnwc6ksg7w9KPfK6J0DjD5Mf7v4cA6indco2j63t9Z4G1R8e/JDdp3b3OjvdX0SALAiCIFyW/plXwvOrD5MUZuCXN+Zw1+REbp2QwNj4YJbnV/DD9/cBjfzPdVl8c0ZK23EBfpoOQWt/ObtLQ3yIgfgQw4BcR7gIOJvh059B9BgYswQaTsCm38HfZip9f697aUjLK7rSWZ3y2XoaVG+r2Nbr7HR/EgGyIAiCcNlxe328vKGImenh/PP+iW2T5XITTADcmBuH2+tjbIKp3eQ1QRg0e/4FTWa47V+gUkNYGoy/Tym1mPptGDFw9beDrbOgelLcpA77dZed7k8iQBYEQRAuK7XNTraX1NNgc3PftOROu1aoVFJbj11BGHSuFtj2N0icriyn3Or6/xu6MQ0D3WWn+5MIkAVBEITLhsXmYsGLm6hrcWHUa7hyZHj3BwnCYCreAO/cCj4PLPrtUI/msiUCZEEQBOGy8eLnR2mwuZg1MoIpqaE97nksCIPm2Geg0sLdH0Da3KEezWVLBMiCIAjCZcHrk/nvjjJuGR/P728bO9TDES5GeXng9ULQeXpaNzWBWg0zZ/btGuW7IDZXBMdDTATIgiAIwmWhttmJy+tjzOmJeILQa2Fh8NZbkJwMqk5ai/l8cOIE3Hdf387vcYF5H0x+6EJGKfQDESALgiAIlwVzowOAmD70JxYEALKyYOpU2L0bEhI6vr51K6Sng92u7NOZrjLMh1bAF8+C1wnxE/t/7EKviABZEARBuCycarQDEB0sAmThAixcCMXF0NAAISFntjc0QGQkWCywc2fvMswttfDJY+BoVL6PEwHyUOv/pUcEQRAEYRhqyyCLAFm4EHo93HEHNDaC261sc7uV73/wA5gxAyoqOj+2okLJQGdlKd/7fLDq/8Gfxyqt3W59HW54GUydZKeFQSUyyIIgCMJl4VSjA51aRWiAbqiHIlxszPvg4McQOw4yF0NcHCxaBGvWQEoKlJfDNdco28PCus4wm0xKBrrVl8/Crtch5xYYcweMnD/4703olAiQBUEQhMuCudFBdLAeSZK633kwuhUIw0/JV2Cvh6Iv4UQeNNcoAXFtIVTmK/ukL4Cs66F8Ddgb4NOvIDUKnP6w/qvT+6hgfRkEBoJWeybD/N3vKhloWYYd/4CvX4KJ34Br/wQ9+bkUBo0IkAVBEITLwqnTAXKPDHS3govRhd40DPebjsp8eOt65fe6QEidDTFqKHhX2XbtH5UuE+ufh2OfQkAkBFpBbgK1Fr7e2HYqi+xlR5OXK4/cjn701DMZZoMHXswBnxeaKpVge9HvRXA8DIkAWRAEQbgsnLI6GJfYwxZv3XUrOLeW9HJwoTcNw/2mY+vLoAuCez+CqGzQBSiB7BuLoLECxt0LGj8Yfy+c2g/xk5TA+Bxen5dleb9h/8ZfYzq4kskVhyAtFpwGePdTLPYGVkeksHjqtzFO/TaoRSg2HIk/FUEQBoXF5mLpv3ah06h4enEWo6KNQz0k4RLn88lUNvsoqm5m14n63mWQ4fzdCs6tJR1OBipTe6E3DcP5pqP+OBxcDpO/BQmTz2xXqeH+lcoEOo2fss0vCJKmd3mqLWVbKHY3kzlxKWvld0kq2EeU+jBsXo9X48+y3FspUEtoTdEs6STAFoYHESALgjDgvjpaw69WH+JErQ1/nZpfrjrEO0unDvWwhIvMvjIL33s3n9smxANgd3tJjwxiQlIIm47VUNXowOn1UWN1khQWwOaiGnaesMPmr9rOkRXTxY1Z1SHlUfpVz5zJbrZ2K3j55a5rSYejgczU9uWm4eR2qNwD8ZPB/jEEpA2fmw6PC8q2waY/gMYfpj/acR+N35nguBsV1grWFq0l3hiPSq0lYP7jvDVf5vtTvo9OrWNLaR7Fx9aQZUoi35zPhJgJpIWm9fObEvqDCJAFQRhQFRY7D76xg1iTP/+4fyIf51ew43j9UA9L6IEqq4MQg47DZiuZMUZ0msHpDOrx+pAkCbXqTF2mLMu8sPYw5Q12/vDZUQBUEvjkM8dJEqgliZAAHR/lVxAe6Medo3TkZmcwISmUiCA/gv27yNh99Vs49DEkz1RqT1sze+frVjBcDWSmtjc3DfnvQN4fob5Y+V5SgeyD8U/Ctsahv+loroH374WTW5Xvr/kDGGP7fDqHx8G7B98l2C8Y7emfH6OfkVJLKXkn8xgVNupM8CypCDOE8dGRj9qCZ2F4EQFyDxyvbcFqd5MZY8Qny+i16g6vJ4Ya2v1jLgiCYuW+Snwy/GfpVBLDDOw+Uc+KvXbcXh9atWjF3l/e2V7KYbOV1PBAUsIDiDHpe1TGIssynx6sYueJegJ0amJN/thcXraV1PHZoSrUKgmvT+b+aUk8e0NO23GNdjdOtxedRsUhsxWDTkNCiD8HK62MTwpBr1GhVklIkoTPJyNJnLd7xBeHqvjNuiNIKJPpPD6ZMfHBRBn1nLI6qG1yUlLbwi8WZzEzPZzoYH/8tWqOnLKy83g9KRGBTE4OxSfLBPhp2n6+Nm7cyOxJief/EGz1ULhG+f2qH4K1QlnJ7OZ/KAGT+U2o2w+HPJAUDg0OWLW8s0+zuw/7/K/31zkCImDW0v4tD/H5wOdWMqk9uWmwW7Cs/Qmr9QYWz3oCo38o7H0bXDYwr4NFzw/6TYfk88De/yjlFIZQpea4pQauewnCRkDyjAs6/7qidVjsFhKC29+UxAbF8lnRZ2wu3dxl8HxVylUXdG2h/4kAuQe++84eDpmtSBLo1ComJYciSRBt1BMR5McrG4uZkxHBnZMTeXlDEWUNdkZFBzE9LYztx+txeny89/DUnrUWEoRhxObycLDSyqTkUGRZJr/MQkywnu1vfcK+E7XkZiVwQ67yn5rb66O8wUa11Umj3U2Qx0FKlJEVRXrGJphIDDMAEB9qwCdDpcVOUljAUL69S8aRU1Z+vvwAATo1LS4vAGqVxIwR4RwyWwn00xAeqGPGiAga7W6OVTdRVN2MSpKQZZnKRgd6rQqXx9eWkdVrVXx7dhpuj48TdS38e1spZQ12Ck810eLy0Gh3I8sds7gA/lo1Lq8PCSWr6/bK6DQqcuNN/GBeOtPTwtvtv2JvBd9/dy8jowKJDzEwLtGEQachv8xCflkDMUZ/MmOMLMiJ5q4pifhpziQpsmODyY4N7vCZ9Pjmq6YQNvwKvC4YMQ+KPofE6XCqANY8DqGpcGgZpCSCtQrC6uFIcdfn6/bf+R78P3AB57DIXlbbzCzOfwvj3Fdg2YbuM7U+HzgsStBYewwq90LaXKXWtnwH1ByBLX+BxnIISwOPA5pqwBwKh/xgRCzYNPD5522n9FYfZpmrnoKRV6KNHMGS7CUw9RHY+gp8+lNQPQdNHlj7JaREQLMEn67r/rPpC9kHNYVML90GnpbTn58MwYnw4FqIG3/BlzhUfYht5dtINiV3eE2r1lJuLcfisLA4Y3G712KDYllfsp6ciByiAqMueBxC/xEBcjcsNheHzFbmZESQExdMfYuLgvJGVCqJvWWnaHJ4GJtgIu9YLRsKa4gM8mNBdjRbimvbHgMCVDc5iTIO03o1QeiELMt89509bCis4ZnFWdjdPn677ggAabX13Hc0j+0HwrBtDcHt9XGi1obdrQRnkuwjvrGap3LmUhyeyNPXnXmUmxCiBMpl9ZdOgOxwe7Ha3UQa9ciyzIEKK8eqm/jXlhNkxwVz79QkYk3+HK9tITxQR/zpz+BCyLLMjuP1fHW0hq+Lagny05D3xBwsNjc1zU7+mVfClqI65mVF4fbJlNa18OIXR9FrVaRHBjEtNawtVzkpOZTbJyXg9vqoa3ERoFMT4KdpCzItNhfzX9xE4akmJiaHYPLXEhrgR4CfGqvDw6TkEJodHoqqm0mPCmLTsRqC/bWtYQg6tQqby8OqAjN3/WM7o+OCSQozkJtgYueJer48XM3klFD+/c3J7YLfAXfwY1j+LUBSJmdd9T9w6BMYfRtsewW++MXpD+ghuPYPgzeuPvL6vCzb+wYFJV+iLc5jyaffgLA5UFCs1COXVcINt4KfDb54BqyVEJ4ORevh5BYwxoO1XDmZ3gQ+D7iale/DRsCUb4GlFFQaMIRD8G7YtBf0J2HnjnZj2eJzURyZQVbyrPa1tmPvUK5la4CIY3DKAoaTsCd/QD8biymBtwMTuG/eExhHLlIm3RnC+q29Wq29lisTr0SlUmFz27C5bdjddmRkKq2V1NnrQIayxjKSTEltx2nVWgxaAysKV7B0/FJUkniqNlyIALkbrbWS3549gskpoe1ea7S7yTtWw7ysKCw2N8XVzWTHBRPsr0WWZZweH/knLdz5j20cqrSKAFkY9j47eIpXN5VgsbvRqCSOnGoiMdTAMysPATA/K4qxCSamp00nZ2c0G95Zw+7aFvy0KjJjgkiPCiQswA9jrZmGzOmYcmYSGqBj7qjItmskhPoDUNZgG5L32Fserw+NWkWTw83W4jpCA3SUNdhweXx8XVRHSW0zZouDJqeHJxeOYu0BMztPNACQFGbgg11l/Gf7ybbz6TQqls5IYUx8MJFGPf5aNfEh/vxjUwktLi9+GhWJoQZmjowgSK/B0uJGkiDAT0NFg52NhdWoVBJrD5g5UGFFo5LwyTI/WTgKk0GHyaAjOTyAScmheH1yu9KvRpubIL0GVRflYGqVmjiTf4ftJoOOLU/ObSuZ6M7CnOhOt/9ofgb/3lrK54eq2HG8nlUFZiKD/HjwimQenZs+uMGxLMNnT0H4SLjnQwg8/TM67m7l16nfVh6/x0+CzOsHb1wXYEvZForri5WgVB/KhLqTpB1fBWY77PNClBq2rICtEkhqCAiHgveUYHjao0r2ePpjEJkJO15VXh8xD2LGgDFO6ehwrsc6bqqwVrB258vEB8V1rLU1hMLtbw/8h3GW1huH9bvXEImHJVp/0Hb8Ob8QVyZd2WGbLMvYPXa+KPmClJAUGh2NWF1WDFpDW/AMEBEQwfGG48qNROyEfh2X0HeXfIC8+Vgt/7PiAAuyo/nR/JFdPnZzerxsKapjRnp4u312HK9Hp1ExJr7jI7xgfy3XjVEK+qOM6nYBsCRJ6LVqsuOUGsBDZitzzgoSBGG48Xh9PPFhAYF6DZnRRpweHzfkxnH/9CRWFZiRZZkbcuPO1OBHLmL+iRLmezwdaxxjIgm++xaSO5lwExPsj0YlUVZ/JkBucrj54nAVcSbl8frZfwctNhfmRgdhAToijXqqmxwcNjdhd3m5cmQ4/lo1pXU2Cmo8rF1WQHpUIHdPScJfp4xTlmUabG4sNhcRQX4E6c/fVml3aQO/XnMYi83FqGgjaw+Y0aiV8oNzBejUjE8KISHEwIk6G8+tOkR4oB+/vCGbUTFGxiWYaLC52VBYjdXuJibYn+X5Fbyysf0j+thgPWarA4NWjdPjw3O6ZlcZf+fjHBUdxG9uHs31ubHoNepOg95z50UEG/reUkrTD/Xieq2ah65M5aErU/H55NNP1vwGv/zM54PyndBYBnOfOhMcn03jBwt+NbjjugDtuidIKsJCU/goNJnv3/YmuuI98Nl6mDMFi/UIqy1FLJ7+Y4wRGeBxKhnhc3vxps7q0zi6m6g2FLW2rTcOcG1lqAAAIABJREFUyYbkQe0cIUkSBq2B6zM63mC1Bs+t2eaq5ipsnosjaXC5GJYBsiRJAcArgAvYKMvyOz09tq7ZybqDp5iXGcW7O8t48YujhAXo+NtXxazcV8mz12dzdVYUHq8PGaVOzeH28q1/7+arozVkxxoZnxjC7ZMSiAjy47NDVYxLMHWYmNdTRr2W+BB/DpmtfTpeEAbL9uP1NNjcvHDzmA4ZwCUTO5kJ38cWWGqVRKzJn7IGO2v3m3l3Zxm1zU4OVip/R4x6DfEhBlxeHyoJimta8J4uctVp2geqOo0KP42KJodHGZK2Aofbx6/XHMZfq8Zk0KHXqiiuaWk7JiMqiOhgPc9cn01KePsSD1mWeXrFAaqbnMSH+LPu4Clun5RIkF5DsL+W8YkhNDs9RBv1GP01hAToMJ4OuBvtSoZ5dkZEu38vIoL82n1+146JocXp4XhtC9VNDvKO1fLvraW8uCSXG8fF4fPJlNS2sHa/GRmINfnjk2WaHB7UEtw4Tqn5Nhku7lnvKpXUu57E/cXtgFdng+UkaPSQcc3gj6GfnTcordrLVaPnweh5pzOptRTYK9HWFLAkchRo+/fP4HwT1Yai1vbsG4eS6pJh0zmiNXg2aJVyq8TgbiaSCoNu0AJkSZJeB64DqmVZzjlr+0Lgz4Aa+Kcsy78BbgaWybK8UpKk94AeB8gvfnGUt7ed5OfLDwBwQ24sv75pNDtO1PPbtUf47n/2sDAnmg1HqgG4e2oSBeUWthTX8cD0ZDYdreHDPeW8s70USZLw06j49U2jL+i9Z8UYOSwCZGGYW7PfjL9WzayREZ3vIMtQskF51Lp/GRz7DDKv610LrJpC0AWQEOrPzuP1bDhS3Rbw/vmOXPw0KjYW1lDT5MRPq8LtlbkqM4oxccFUWOzUNDmJCPIjJy4Yn09mQ2E1DrePrFgj9SeP8eD1sygob2RrcR3NTg8VDXZaXB7umJRIWKCO8gY7e8ss7Dhez9MrDvDvb05pN7zdpQ0crLTyq5tyuGtyIj65Yxa2K8H+2i5LC84V4KchJy4YCGbuqCieWDiqLahWqSRGRAby2FXpPTqX0Etb/wI1hyE4QZmIpr/4F6zpaVDaVoIRkTUgmdTuJqoNdq3tcMxmCxePwcwgvwn8BXirdYMkSWrgZWAeUA7slCTpEyAe2H96N29PTu5xu8jfvZ19+Qe5PcVIVoyRMfEmchMMSNYS5oRC7k2hfOedExQfquTukRE0Ozx8tikPgL8vGsX8LB1Mj6PJ7ub93cpEhaszI0kKaYDahnOu2PNHgtNDGig6UkpzZTSBfoO0ak4vHll6vDIadev+fXzU2adHpINzLT9HNVjKBuVapw8axGv18XpnXcvnk/nD54V8sbucW7Ki8XfWgLOTY3b+Ezb9/sw1w9Jg/fOQNg8cdtiwE0bEg+4w7CzseHxzNZZNv2c1bn4y4Wm+YR6HLMt8/sMrMRl0bf1pF+bE9PhtTB9xphvCRlsJBp2GqalhTE0NO+9x/8wr4fnVh3lu5SGaHG4AWlwe8o7VYtRruGlcnNKHd5Ce/Pf1CZXQS7IMX/9ZyRrf+d+hHk2/6GlQumjEogHvwXu+iWow+LW2wy2bLVxcBi1AlmV5kyRJyedsngwUybJcAiBJ0rvADSjBcjywF+jRbWaI4yTjVs5npQSYT3/tOWcf4L+cPmPR6Y2t/y6sP/0FBAHfbD1ob0+ufn4PAA/ogFcv/FwDYVjW2fSjaQDbhnoUw5cK+AnwEz+gGPjjeXYefZsyaSl5JkRkwNqfwPFNYDgBzmZwa2FtZ/1hwYvMsogRFLSY0Ra/yZc/+gFNDg8JoRfe0aG37p2WxJ6TDbyx5ThGvRadRoVeq2J+VjT3T0/CoLvU/1Zcpmx14LRCSt/qa4ejngSlx+qOcbjmMNGB0QOaST3fRLXBrrUdbtls4eIjyT1qXN5PF1MC5FWtJRaSJN0KLJRleenp7+8FpgBPoGSbHcDmrmqQJUl6GHgYICEqZMIfn36MFjdMilb3NYfXQ737zDw+mX8ddJIZqmZ6XO/+45XOuZS5xUeLWyZQJxGql9B1+vi34/ha/7GUzvpkZGQ+OubG5YUwvUSpVUnWjwhRMSdhYDPdUp9/7np/nNPpwM+vL3V2fRvj2e/N3OJj7QmlPlYF+ACtBO7Tu/hrINogUdbkwytDZqiKUL1ErV3GTy0RpIOYABUtbmhw+Kixy/ipYVykBp26tYlWN+9ClrE4weL0tfWsLW/yEh2got4hc6TeR0aIiqkxmi6T0Vavg/X2MkYn34dB13HCquTzoPE0n3cc+xoPsrnpIKMbC2loOsrYSX8jzr//FgZobm4mMDCwd8e4ZPQa0IhFfi5ZZ/9cBDaVMHH3/+NA9pPURkwb4pENHFmWcfqcOH1OHF4HG6o3cKLlBNnB2e328/g81LnruDnuZkJ1oV2c7eK0z7IPu9eOSlLh8Dpw+pxYbVZ0fmey5WaHmVkRs8gIyhjCkQpDbc6cObtlWZ547vahTpN0Gt3JstwCPNjdwbIsv8rpvGxGRoZ823ee7efh9Z/q17aT32AnfVw2cSY9y/Mr+PRgFQF+Gq5IC+P63FiqrE7KG2ykhAW0zWSfl3Xm8Y/F5mLx81/gOasrf0KoPwuzo3li4SgKKho5bLZid3mRZViQHY3L62N1gZk3thxHr1EzMTmElPAAxsabWL63gtUtZv60ZCw3j4+nwmLn718V88ftJ7l+6exue7XWNTsJ1GuQkLDYXQT7a3vcpsnm8rDpaA1xJgOjO+kQ0p82btzI7NmzB/QaXVm/sZj3io/wws2jOVbVTFKYgYLyRuJD/EkJD2D1fjMbqppIGxFIoJ+GX+yrBJSJai0ub9vktFZhAToabC5UdRImgxa3V8agU3P92FjyyywkhRrYdKwGt1cmPTKQIL2GfeWN1DS1r5kw6NTY6pUbonunJnHP9dld1tp6fV7e2PsGFVU+UuKcXJM9u9efQ4W1ggOvf8htughkRw0t5U68MZu5Yuz9bRktAJqaQK2GmTN7fY2h/HMWhq92PxeFdtgNOdPmQ/zl0U7rUPUh8gvyudF0Y6eZ0pqWGmoDarlxfOevX6xmM7vDtg0bNjBlxpR22WyH18HMxN7/eyNc+oY6QC4Hzi4Oigcqh2gsA2rGiHBeWHuE+19XmqmrVRLTUsNweXz87aviDm2fWn3y6BWMiTcBsP5INR6fzN/uGY9Oo+KwuYn8kw38I+84n+yrpMraPgj61ZrDbb+fnaFMvDpQ0cjq/WZkWQnCHrwimevHKq3q4kz+PDIrjf9sP8mv1xzm97eORSVJWB1uKi12MmOMbbWS/956gv9ZcbDdKlpatcT0tHDumZpEWb2NvWUW9FoVm4/VEmnUc/3YWHaeqOdkvY2jVU24vcqByWEGIoL8SA0PJDxIx9GqZq7OjGTJxISLfvXBw2YrcSZ/7pzc+Qzl1o4EoLRZu3daEqEBOlLDA/D6ZErrbWw4Uk2UUc+U1FAiAv04UGFl7QFzW6/iwlNN/H1TCSnhAew9aWFySigJoQYOVTbSaHczNTWMmSPCGZMQjMPto9HuZnpaGEXVzQSd7hhxPhc6sadtokxYBMlfHqLJ30m4WaZ+7wGKat4jMzxT2dHngxMn4L77enxuoQfy8sDrhaCgrve5gBuTi4q1QvnVGDu04xhEw60ueCiJzhFCbwx1gLwTSJckKQWoAO4A7hraIQ2Mu6YkEqjXkBBi4HhtC3MyItuW3q1pUlrTBejUTEgKodLiQEbmwTd28v6uMkbHBVNS28Ka/aeIDPJjflY0KpXE3FFRyLLMr1YfZs1+M7+9ZTQz0pXFBax2Nyv3mQkxaJk5MqJd8/+SmmbKGuxMTQ3tkPGNNfnzo/kZ/HbdET47WIVaJeH1yXh8MhqVRHpUEP5aFXtOWpg1MoIx8cHo1CpMBi1lDXZW7K3gobd2AUoA7nD7uCozkmPVzTy36hARQX5kxRiZmR7BzPRwDlQ0UlDRSG2TkzX7zTS7PMQY9Xx+qIqEEEO7SVj9TZZlCquaGBkZ1OXCCRfqsNlKZsx5ApOzaE4vY37me4m0iEDSItqXDYyOD26XdZdlua27A9Djm4rMmO5n73fordqHiT2tE2WCskZRXe0gIr+AZiAYNYU1hcQFxmHUG6GiAqZOhaysbs950RgOwWlYGLz1lrKSmqqTDOHldGNirVQWyOis7/ElajjVBQvCxWQw27z9F5gNhEuSVA78Qpbl1yRJehT4FKXN2+uyLB8crDENpiC9lrunKMtLXnlOG62IID/unXpm6cnW5XevGR3DivxKyhvsbCysAeDOyYntgjlJknjquiyeuq59UGHUa/n27M6zfKkRgaRGdF2r+a0rU6lrduLxyagkCa1aIjfBxP6KRg5WWmm0u/nRvJE8dGVqh9n3jy/IYP2RatSSxNxRkbi8PvRaNV6fzGGzlZFRQeg0Z/6TvuKsANjh9mJzeTHo1Ez61Rcs21PeowDZ4/VRVNOMUa+lvsVFVoyx3Wfkk2Wqmxw43b621cjyimoorm7hwz3ljI0P5pFZaWTFGtvKRPRaFdbTS+eqVRINLS68Ppn0qEAOVVq5KjOq3fvojMPtpaS2pcetv/pKkiQiB2CVxv5okXTuRJnyadkYT5SjOyXj8tjQ+ZvYW7WXGUHZqEwmWLiw399HO4MdsA6H4DQrS7nx2L0bEjrpZ32+G5PhEOD3J2slBMV0viLcZURkUgWhe4PZxeLOLravAdYM1jguJg9MT2ZLcS17yyw8OmcEVoeb+6YlD/h1VSqpQ8ANsGh09+23tGoVC7LPBIT60/8RqVXS6b6vXdNr1W0B93VjYvk4v4JFOVVkxxrJP1060JolBSUTvrfMwvL8CvKO1bZtv3lcHDeNj6PK6iQyyI//+dpOxadfdnrNG3Nj2XmigW+/077lyajoIGqbndQ2uzo97t6pSfzyxpxOX2t1rKoZr09mVPTF2We1P1okdXi8q7VRcs0VZBV8htvWRGB4IPXWaqqsOmKe/GWXi4v0m8EOWC8kOO1PCxdCcbGyyuG5qx6e78ZkOAT4/clacVmVVwiC0HdDXWIhnMfYBBPbf3b1UA9jSNw3LYmV+yrbyjVAKQn405Kx/GV9EYfMVk7W2/CeLv14fEEGRr2Gcoudv39Vwkf5FW3H6dXw1LWZBPtrqW124fb6uGlcHDaXl4zoIDxeH9uP13Oq0YHF7sbm9LA8v4KIID3P35iDVq0iJECHy+PjsNnKsepm/r2tlJomJzEmPRabm8NmK26vj8RQA4mhBiRJYs1+MxqVxNiEgZ2EOBD6q0VSp493R8s4P3sT71EHjpwknHUeqmeMJCZYB801PR+k1h/8znkSYjWDv0l5rTNDEbD2NTjtrc0vwan9EJ4OoWlgSoDEqcprfVz1cNgE+P3FWglR57+xFQRBABEgC8NUZoyRXU9dzb4yCwcqrWjVEs98cpBFf85Dp1ExNyOSeVlR3Dw+DpO/rt2StTeNi8Nq9xAaoGN/hYXm8qPcOzO1y2tp1Kp2pR4Aj84dAXSs552aGobH6yPUoOOd7aV4vDJGfy2pEQEE6DScrLex60QDLq+PKalhfG/uiG4nwQ1HAzmxR5Ik9FOnQPF7BCz/PUSpiT22Bv7wQu8GqdLC5IfBlAjmvYw7ng8bjyiP0HPvBkMYGEKV5YRPbgV7AwRFQ3Iu5LcMfMDaqq/BaW9U7IYvfgGBUXDgQ9ra/8VPUoJmXaBSdxsxCvaXQHIKlFXCnOngq4Cyis7Pq9bB/Plw9AjU10PoWa3ABurz6m+yF7xu5TOyVkL6gqEekSAIFwERIAvDll6rZkpqGFNOr4o2Oi6YY9XNTEoOJSU8oMvjzi5pGBEZyMbGoi737cr5Jrpp1Cp+vCCDHy/ovHemLMvIMgM28W8wDPjEnhv/AqnXweq1MHMMBPX+JsJS+jWrt73IYrQYA6KQVCaY+WMo3QKbX1QCo1a6QPAPheZT4HVBkw9OXAGTF/dPwNpYrgRfCZPBZYPCNVB9GHa8CjFjYdI3YUIqbN4Do8Z2vyR3TzisULxeWajl5FbwD4FHd4HHCS01sPVlZWnw8feDzw31JVC1HCqdsNcLUWrYvxwOdPNzGhQLVZVQMwWm3DAwAX5P1R+HdT+FcXcr37vtyoI1UTlQtl35M/C6oMkMoalQvJ5Ze96GzRplO0BY1zfLgiAIrS76AFmSpMXA4thYUVd2qRuXGMK4xJDudxxikiT1fdXoYaxfJ/b4BcKkW5WvPvD6vCzTSBTo/dDGTGTJhKXs+eqrM/1u3Q7w2JUlxl3NkDBFmZjldigZ1S+fha074VgypGcqdbTzr4YQf2ipA9kHOgNoDVB7DLR6Jeg8nqdkpi2lSiB6fJPyusehBOQTvwnHPoPG00ubp10FVQfhgweUfojFbth6OjjVvQxfXtgPigWZ1WoNizUGjFf9AvSnbw4DI+DGlzseYLfAsa3w2UaYOw2M3Sys0nQKy/4PWC15ubFxFwFHkyFzHJSVwqJFEB2pZGf7k/o8ixR9+SwcXat8nU0bAO6WjvtLaswxVxGbnKH8DARFQ+y4/h2vIAiXpIs+QJZleSWwMiMj46GhHosgCIOjrTdzzDjyLSVMaChpv4NWr3z5h3TcnjAJFr4AJ2bBnn/BttMBq+E1+PqsgFXtB+EjoWp/xwFIapBUSnnHuHuUgP/UAdj1GsSOh+v/D6JHQ0A4eD1QsQscjTD7KHyeB9NHQWAXddI95FWpWOayUOCyok2exZLsJd0f5G+CMYuUr55cw+dlmeygoNSEzrqc2/b8G7a/qXxefn+DDQNwJxg3AWQZfB6In6hksK0Vyg3KkVUw/TGldMQYr3zu5gI4uUWpu06ZCUhK/XVjOQRGc3TXQWLFAjKCIPTSRR8gC4JweemqN3OuL7fnJ4keDY9uh/2fwoYdMGMMGAOUoBcJi8fO6qMrWdxUj3H+8+BnVILLhClKaUNgBPgFgyTR9rjA64a6YuWR/9mPENSaM5PlRi6AuY/1y+ewpTSP4mNryIoa3acFXHp0jdYbkYRp7NHomTghgpRtRTA9C4IuLMDvlMeJ5fBKVntbWGxMxFjwAbialPKYwCjIuEYpo/E3nTkmIgPG3NbxXOfeHAmCIPSCCJAFQbhonK83837rfuYxr+cnC0+HOekwp/1mr8/Lsr1vUBCdhXbyjI6Z2aAu+lqrtRA5qhfvpu/6YwGXXl8jLJ1lyHz/ubf67Rrn8vq8LDNFU1BVgDZxBksybwWvs+uuJIIgCAPk0ll4XRCES15rb+aQc7KDsUGx7LHsoaq56oKvce7S2sX1nS8DP1S6ukmw2C3kncy7aK7RmQ6fveW4CI4FQRgSIkAWBOGi0NqbOc7YsfODVq3FT/JjReEKfLKvz9foKjPr8na+YMxQON9NwvqS9f1ykzAY1zjXxfDZC4Jw+RABsiAIF4XW3szJpmTCDeEYtAYkztT6mnSmtt7MfTFUWdPe6O4moXUBlwu5SRiMa5zrYvjsBUG4vEiyLA/1GPqFJElNQOEgXCoYaByE6wyna1/s1w0Harvda2Cu3Vvi56u3JFSnv8JRY0VChZPmXl/bHxNaDHhpn7KUkFCho5kqfHj6PM6urtsbfgQinU5snHnf/5+9+w5vqzofOP49mrYlea/YiUfi7AnZCSMEKKO0jDILZbRQSjelLbR0L/iVtpQOSgu00NKWlrL3CNkhe+/txHsvybbW+f1xJVkecWwTL/J+nidP7Huv7j2Sr6T3vvc957RPdFiw00wtXk40SHX3xz41x+jdcfv3te/L+/9UGZ7vqeF57J4ct7/OhaH8nD9qx+6P447XWrs6LTUmNRj+/4CNA3ScvwzicxyUYw/34/bl3Bjuz3k4HVv+zqfHsQfxuAPy3TDEnrOcXwN4Lgzl5/xRO3Z/HPdE54WUWPTeq6fhsU+34w7mseU5nx7Hlud8ejgdX2t5zh/94w7msQfsuB+lEouNWutZg90OMfTIuXF6kL+z6IqcFyJMzgXRlROdFx+lDPJfBrsBYsiSc+P0IH9n0RU5L0SYnAuiK12eFx+ZDLIQQgghhBCnwkcpgyyEEEIIIcSHJgGyEEIIIYQQUYZdgKyU6un4puI0oZQKKKW2Rv3L62bbRUqp1waudeJUUEpppdQ/on63KKUq5W8pwpRSV4bOkwmD3RYx8OQzQpxqwy5AFqILzVrrGVH/jg52g8Qp5wamKKViQ79fCBT3ZgdKKcspb5UYSm4AVgHX9+ZBSilz/zRHDLAP/RkhRLRhGSArpZxKqSVKqc1KqR1KqctDy/OUUnuUUo8rpXYppd6JerOI04hSyqyUekgptUEptV0pdWfU6nil1ItKqd1KqceUUsPyfXAaehP4eOjnG4B/h1copeYopdYopbaE/h8fWn6rUuo5pdSrwDsD32QxEJRSTmAh8DlCAXLobtGKrt7rSqkmpdRPlFLrgPmD13JxivXlM2KlUmpG1HarlVLTBrTVYkgaroFBC3Cl1vpM4Dzg10opFVo3Fvij1noyUAd8apDaKAZObFR5xYuhZZ8D6rXWs4HZwB1KqfzQujnAPcBUYAxw1YC3WPTFs8D1SqkYYBqwLmrdXuAcrfUZwA+AX0Stmw/corVePGAtFQPtCuAtrfV+oEYpdWZo+Yne6w5gp9Z6rtZ61YC3VvSXvnxGPAHcCqCUGgfYtdbbB6zFYsgarrccFfALpdQ5QBDIBjJC645orbeGft4E5A1888QAa9Zaz+iw7GPANKXU1aHfEzAunrzAeq31YQCl1L+Bs4D/DVRjRd9orbeH6stvAN7osDoBeFopNRbQgDVq3bta65oBaaQYLDcAvw39/Gzo99c58Xs9ADw/CO0U/aiPnxHPAd9XSn0L+Czw1IA0Vgx5wzVAvhFIA2ZqrX1KqaNATGhda9R2AUBKLE5PCviK1vrtdguVWoTx4RhNBgMfPl4BfgUsAlKilv8UWKq1vjL0Bbksap17gNomBoFSKgVYjFF/qgEzxnv6DU78Xm/RWgcGrpViAPXqM0Jr7VFKvQtcDlwLyEx7Ahi+JRYJQEUoOD4PyB3sBokh523gLqWUFYxbZ0opR2jdHKVUfqge8TqMjj1iePgr8BOt9Y4OyxNo65Bz64C2SAy2q4G/a61ztdZ5WutRwBGMbLG8108/ffmMeAL4HbBB7jaJsGEVIId6obcC/wRmKaU2YmST9w5qw8RQ9ASwG9islNoJ/Jm2OyYfAA8COzG+SF/scg9iyNFaF2mtH+li1S+BB5RSqzEyiOL0cQOd38PPA59G3uunnb58RmitNwENwN8GoIlimBhWU00rpaYDj2ut5wx2W4QQQgxdoXKqb2qtLxvstoihTSmVhVFyMUFrHRzk5oghYthkkJVSX8AYsuV7g90WIYQQQgx/SqmbMUa7uF+CYxFtWGWQhRBCCCGE6G9DNoOslBqllFoamvhjl1Lqa6HlyUqpd5VSB0L/J4WWT1BKfaCUalVKfbPDvr6mlNoZ2s/XB+P5CCGEEEKI4WHIBsiAH7hHaz0RmAd8SSk1CbgPWKK1HgssCf0OUAN8FWN4lwil1BTgDowB46cDl4XGQRRCCCGEEKKTIRsga61LtdabQz83AnswJgS5HHg6tNnTGDMoobWu0FpvAHwddjURWKu19mit/cBy4MoBeApCCCGEEGIYGrIBcrTQoN5nYBTSZ2itS8EIooH0kzx8J3COUipFKRUHXAqM6r/WCiGEEEKI4WzIz6SnlHJijGn5da11g1KqV4/XWu9RSv0f8C7QBGzDKN8QQgghhBCikyGdQQ7NgvY88E+t9QuhxeVKqRGh9SOAipPtR2v9pNb6TK31ORi1ygf6q81CCCGEEGJ4G7IBsjJSxU8Ce7TWv4la9QpwS+jnW4CXe7Cv9ND/OcBVGOMpCyGEEEII0cmQHQdZKXUWsBLYAYQH7/4uRh3yf4Ec4Bhwjda6RimVCWwE4kPbNwGTQmUZK4EUjA5839BaLxnQJyOEEEIIIYaNIRsgCyGEEEIIMRiGbImFEEIIIYQQg0ECZCGEEEIIIaJIgCyEEEIIIUQUCZCFEEIIIYSIIgGyEEIIIYQQUSRAFkKIjwCl1I+UUt/sZv0VSqlJA9kmIYQYriRAFkKI08MVgATIQgjRAzIOshBCDFNKqfuBm4HjQCWwCagHPg/YgIPAZ4AZwGuhdfXAp0K7+COQBniAO7TWewey/UIIMVRJgCyEEMOQUmom8BQwF7AAm4HHgL9pratD2/wMKNda/14p9RTwmtb6f6F1S4AvaK0PKKXmAg9orRcP/DMRQoihxzLYDRBCCNEnZwMvaq09AEqpV0LLp4QC40TACbzd8YFKKSewAHhOKRVebO/3FgshxDAhAbIQQgxfXd0CfAq4Qmu9TSl1K7Coi21MQJ3Wekb/NU0IIYYv6aQnhBDD0wrgSqVUrFLKBXwitNwFlCqlrMCNUds3htahtW4AjiilrgFQhukD13QhhBjapAZZCCGGqahOeoVAEbAbcAPfDi3bAbi01rcqpRYCjwOtwNVAEPgTMAKwAs9qrX8y4E9CCCGGIAmQhRBCCCGEiCIlFkIIIYQQQkSRAFkIIYQQQogoEiALIYQQQggRRQJkIYQQQgghokiALIQQQgghRBQJkIUQQgghhIgiAbIQQgghhBBRJEAWQgghhBAiigTIQgghhBBCRJEAWQghhBBCiCgSIAshhBBCCBFFAmQhhBBCCCGiSIAshBBCCCFEFAmQhRBCCCGEiCIBshBCCCGEEFEkQBZCCCGEECKKBMhCCCGEEEJEkQBZCCGEEEKIKBIgCyGEEEIIEUUCZCGEEEIIIaJIgCyEEEIIIUQUCZCFEEIIIYSIIgGyEEIIIYQQUSRAFkIIIYQQIooEyEIIMUiUUk8ppX72UT+mEEIMNxIgCyGEEEIIEUUCZCGEGGKUUpbBboMQQpzOJEArQyeuAAAgAElEQVQWQogBopQ6Qym1WSnVqJT6DxATWr5IKVWklLpXKVUG/E0plaSUek0pVamUqg39PDK0/XlKqR1R+31PKbU+6vdVSqkrujtm1LZ3KKUOKqVqlFKvKKWyQst/rJT6fehnq1LKrZT6Zej3WKVUS6iNeUoprZS6RSl1TClVpZS6v19fSCGE6GcSIAshxABQStmAl4B/AMnAc8CnojbJDC3PBT6P8fn8t9DvOUAz8IfQth8ABUqp1FC2eQowUinlUkrFAjOBlSc7plJqMfAAcC0wAigEng2tXg4sCv08GygDzg39Ph/Yp7WujWr/WcB44HzgB0qpib1+kYQQYoiQAFkIIQbGPMAK/FZr7dNa/w/YELU+CPxQa92qtW7WWldrrZ/XWnu01o3AzwkFqFrrFmAjcA4wC9gOrAIWho5zQGtd3YNj3gj8VWu9WWvdCnwHmK+UysMIwscqpVJCx3kSyFZKOUPtWN7h+f041O5twDZg+od+xYQQYpBInZsQQgyMLKBYa62jlhVG/VwZCnwBUErFAQ8DFwNJocUupZRZax2gLcNbFPq5FiNwbaUteD3ZMbOAzeFftNZNSqlqIFtrfVQptTG0z3MwAvQZGEH4ucDvOzy/sqifPYDzxC+FEEIMbZJBFkKIgVGKkYFVUctyon7WHba/B6NkYa7WOh4jSAUIPz4cIJ8T+nk5RuAand092TFLMEo4jB0r5QBSgOKoYywGzsDIPC8HLgLmACtO9oSFEGK4kgBZCCEGxgeAH/iqUsqilLoKI9A8ERdG3XGdUioZ+GGH9WswAug5wHqt9S6MYHcubcHryY75L+A2pdQMpZQd+AWwTmt9NLR+OXAzsFtr7QWWAbcDR7TWlb19AYQQYriQAFkIIQZAKMC8CrgVoxziOuCFbh7yWyAWqALWAm912J8bozxiV2jfYATEhVrrip4cU2u9BPg+8DxGtnkMcH3UYdaE2hAOuHcDLUj2WAjxEafal6YJIYQQQghxepMMshBCCCGEEFEkQBZCCCGEECKKBMhCCCGEEEJEkQBZCCGEEEKIKBIgCyGEEEIIEeUjM5NeYmKiLigoGOxmiCHI7XbjcDgGuxmin8nfWXRFzgsRJueC6MqmTZuqtNZpHZcPSoCslLoYeAQwA09orR9USv0TmAq8prX+bmi77wPbtdYvn2yfGRkZbNy4sT+bLYapZcuWsWjRosFuhuhn8ncWXZHzQoTJuSC6opQq7Gr5gJdYKKXMwB+BS4BJwA1KqWkAWutpwNlKqQSl1AhgTk+CYyGEEEIIIU6VwcggzwEOaq0PAyilngU+DsQqpUyADQgAPwF+0NOdmppKOfSHq8hIsFNU08z4TBf+oGZfWSO+QJCx6U6c9r493ZL6FhQwIiGmT48Xg2tyZSWUPznYzRjebA4YORvKdsA534L1f4baozD7Dsg/u9uHaq154M29HK/xAHDtrFGcNyF9ABotRGe/fmcf2fv/waRps/E11aB2tU1m6HVmM/fOR1GmnuWOimo9/Hv9Me65cDwmk2Lr8TqeXX+M+mYfADfNy2VhQWq3+9Ba88u391FY7ebWBfnMyU/u+5MbIv7xwVHWHKputywnJY67Ziex97kfccZtv8EeEzc4jTuBFk8jOx6/E7OvCV/O2ejKfdg85QAEx1+KM7OAuu1vMuuWB7FYbSfcz/Obili6rwKHzcLs/GSunjkysq6p1c8v39pLncfHneeOZuneChx7/8ek5o2YdBATAbwpE8k591ZKX7wfU9AXeaxWJpIv/R75k2a3O96BLStoXPIrCE36FrDEMO7mP5CQkhHZZv3zD2M5/D6BcZcw+/IvnpLXa6A9sfIwmwprAThvfDpj0p2sPVzNl87rv9LawQiQs4HjUb8XAXOBYxjTpv4DKMCY5W9LdztSSn0e+DzA5BEx+Cv2UV0Dyg+1HkWTT2P1gxVoaFEom+pTg5s9QYIamupMdNxDEKhuDpJoV1hNfdu/6F/2YBC3p3iwmzGsWX112Lb9G4Cmve/jdBt3pCoqq9k9OdDtY6ubg/xlRTNJdkVLQLOrsAK1MPaUt7GpqYlly5ad8v2K4S36vChzB3liZS3b7I+yf2kBGboWl3ZTrZJw6ibS3St4682LiXEk9mjfbx3x8ew+L9m+Etw+zS/WtRBjgeQYRblbU1ddiW96DIGgJqDBZu78HVHbEuRPy5oBaKyp4nNT7afsuZ9K+2sDuH2aM9K7Dxu8Ac1Pl3iIsShcoTjyTN9mFu57i80bE1gcWMUr/8gmfmz3F9b9obvPCO/hlXys9nUqdSJpu5fTqq0UqwzSdDVlmwupNacyL7CJ5b86hJ5/9wmP8dBKD3UtRrD6ytbjpDYexBvQrCv1c6guyPIiP7EWeHNHCb4grI15HCceakggTjeT3LiCd6tKuci9hMO0Bdd5uph33kimsOKWdsfTa3/PwuZVFKkRgGY0xbz2zC9wTr8yss34HX9gBFUc3HKUZQmT+v4CAs1+Taxl4GOdh5e4ATApWLGvjPx4MzurA8Q1FBJrUSTFKOxdvL8+jMEIkLt6Blpr/fXIBkq9CtyplLofmA68q7V+vIsH/QX4C8DoseP1Rd5fgtdYNy7Jyf76Jr5/2SRe2VpMrM3Ms5+f3+vGtvoDXPj9twhqWDAyBVeMhcdumolSxtNYc7CKTz+xjm+dM77LKxl/IIjHFyA+xtrrY4tTQ+rOToGAD6r2w4YncG78K8RnQ8oY0lvqST/Ja7vmYBUsX8cfPjOHncX1PPDmXsZMm8Oo5FObQZK/s+hK9Hnx2PJDnGlaj00FmKL3AbBu0neZe929bHj5UdK3fIfJ48cwqmBqj/b9gWcP7DvMiIIp/Pa9/aTHa979xrnEx1i55JGVOJNiWbRoFg+8sYc1h6p59StnddrH0r0VwAYA7PEpLFo065Q871Ptod+tZH95I699ZS4HK5r41/pCfn/DmSQ72mdTl+6twBvcwOM3zebccUa/p5on/0by8R1U+uNBQW7BeKYPwnu1u8+II4f+Rr2Ow/3FbdSX7SR5RD6j07NZ9/ubGVu9FI8tA5rh3NZllBf8hoyRYzrtIxjU1Lz7FrcuzCfFYeOBN/cyc95CXtxSzJM7dwFw07wcbpqXyzWPfcBVExLJ3FsNi76Lc9G9bHv/WVJX3MmZ7hUcV1mM/uGuyL4rfpRPsqWFOR3av3f1dzhon8Sk764C4NBPZ1DQuI4Jix4BwNvagmVpNShIpIGCD/G6r99zhA3/epAb7/41WcnOPu+ntwJBjeftN/jK4rFMzHRx1z83s7PaSMw8vMVPQ4ufGKuJX10zncumZXV6/Ir9lTS1+rl06oheHXcwhnkrAkZF/T4SKAn/opS6HNgIOIApWutrgc8opbr9NrWaYEya0TvVYTOzv7yJgnQnty3IY/qoRHYU1RMI6l439kiVm/DD1hyq5u1d5aw7UhNZf7jKuKrZVVIPwJf+uZnLfr+St3aWAvDZpzcy7Ufv9Pq4QgwpZitkTIaFXwerA86+h+bEcejqQ5FbeydypNp4j+SlOrhoUgageXtX2QA0Wog2W47V8uq2Ej6RcLjd8lFzLgfA6jRKG5obajo99kQqG1sBeHFLMduK6rnnwvGRZIjDZsbj9QOwo7iefWWNBLv4Dtpd2gDAtJEJ1Hq8vXxWA6PO42V3aQO+gObWv63n7v9sZfXBar713DZ0h/f/e3vKcdjMzBsdKhUJ+Ekq/wCANGU8V39z44C2v1vNtbD8IdLLVrAyOJ2RqfEUTD+L5PRsAIKOTJJpIKG1lGoSACjeubLLXZU3tuANBMlJjiMzVJJZ3tDC2sPVpLvsfP2Csdx78QQmZMaz7rvn8+B5oSAzxQi2sycaSbw0aqlwjm+373pLCjEtle2W6WCQbO8RGuPHRpZV5FzKBP8eyo4dMI5//AAmpSkjjSRdT8Dv7/NL5dv1Kt8yP0vlgfV93kdf1Df70BqS4qycPS4Nm9kIXSeNiKehxc9nF+YzJSuBr/57SyQWC9twtIab/7qeL/5zc6+POxgB8gZgrFIqXyllA64HXgFQSlmBrwEPAXFA+J0Xrk3u1lVnjiTFYeOuRcbJ9sVFYzCZFDNGJeL2BjhU2XTCx+4vb2TBA0sidZJhB8qNx3z30gn85PLJJMRa+cUbe/jByzvZV9bIkUiA3ECt28vrO0rZW9rI917aSas/wIr9lZ2OJcSwlZQL3zpA7cSb+L/1XpS3Cdzdn+NHq9zYLSZGxMeQ9+rVPOT6Lx90qE8Uoj+tPVzNlY+uYVdJA+dY96FHzKAeB8dM2WTlTwDA7kwCoLWx5+dmZZMRIBtZYDh3fNtIUXF2C+5WI8tVVNuMNxCkJioA9gWC/Pa9/aw6UMWo5FhyUxzUuIdmgLzuSA1aw7cuGs+YNCfTRyXwxUVjWLK3gr1lbcGu1pqleys4a2wqdovZWFiyBeVtHxAHPO2DmEG1/TlY+jMcvhq2x87BYm4fFpkTjKzjqEARhxPm49UWvEe7DhALq434ISc5jhEJRhlZcV0Law/XcNbYVL5+wThcoQuoOJsFVRO6WEseDUDqiFwqMc5DX/q0dvtusqXh9Lb/rC0vOoRLNUN6W9nEyAXXGW1Z+xIAtceNOyXFrqmYlaa2qrSnr0wnutFIbHiqi/q8j74IXzgmxdlw2i3MH5NCfIyFZ++cx38+P48ffGISD35qKkENByvax3k/eqUtC+/1B3t13AEvsdBa+5VSXwbexhjm7a9a6/Az+BLwtNbao5TaDiil1A7gDa113cn2fde5Y7htYR5aQ5rLzuUzjCvA6aOMerKtx+oYl+Hq8rEfHKqmpL6FVQeruGFOTmT5gYomTApunp9HjNVMcV0zf15+mD2lDTy7/jg5KUZiu7Daw4oDxsl757mj+ePSQ/zyrX2R/QSCGrPUKIuPApuDR97axVGdafxefQicJ+50d6TKTV6KA5PPDcfWcpFy8VLrnQPUWHE6O1jRxM/XNmPeuotUp50/fPoMRvxrH2rirRwc+RkssfGEP+1j41MA8Lpre7z/cAa5sdVPUpyVdFdb/bDTbqa0rplAUFNSZ9QYl9W3kOo0ttlwpIbfvmdk+T42KYPkOOuQCZCPVLnJTY7DFPrO+uBQNTFWE7efnR8pJdxf3sijyw6xr6yRiSPiAThW46GkvoUvhssNfc2w7k+Aos6USGLQeG2DLUMoQC7dBsCTcZ/lcMrHOq22JxlxhFlp/Ak5HHEXkFC9FR0Msn/D24ydeQEmixH0Hgsl2HJT4jCFyjBX7q+kxu1l3uiUzseuPmj8n9JWrlESO4605nU482a229Qbm06SZ2e7ZeUHt5AJxOe2BdMjx0ylmgRMxUbZTnPFIQD8WbNg3/s0VJWQmjmKvjC5jU6Lvrq+B9l9URcKkBPjjNf5Z1dMocbtJT7GytzQ65oQa+RQG5rbOjZWNLawq6SB0WkODle6KalrJi+15+NgD8pMelrrN7TW47TWY7TWP49a/lut9dOhn7XW+gat9VSt9b092a/JpIizWXDYLVw3OycSkOanOEh12li2v+KEjz1QYVzhbi5s/+F4qKKJnOQ4YqzG1fA3PzaeNfctZsk3FuENBDlY0YQrxrjO+McHhVhMii+dV0BOchxPrjoS2U9vr1yEGApafIFOt6zqm338c10hR8IBcs2hduuP13h4es1R9oUyS0eq3OSlxkH5TkATrxsoaNkxEM0XHzFaa3aXNPR4+1e2FnOgLsjeskY+f04+8/KTUf5msLuY+fHbmb742si2jgRjtAl/HwJkgAmZ8ZG+KWBkCD3eAOUNLfhDpRXlDS2R9eHyPIDMhBiSHDbqm334AoP7XbH6YBXn/WoZL28zOjb/bskBnllbyIIxUVlhIC/FgdWs2FfeSL3Hx8IH3+cnr+4GaCuveO9HsPN5WPhVyhOiMqItQ6jEonQbesz5POy+mOzUzp0znaltHeXM8SOoTZ5OnvcAO5a/wPg3r+f4f78NGEmwY9UeTAqyEmPJiDdKLF7eZlSQzu8yQD4EcakQkxBZ5Ek/A582M2rSvHabBp2ZJNFAa0vbXe7mIuNzNGvsmZFlymTiWNxkMhuMdbrmCC3aSnyesY27uu8d1u2hEg/dWN7nffRFrdsIepPijCB4VHJcJPEZFo7DwiPI/OODo/zhfeMC5Ka5uUDbBUxPnRZTTZtMisumZfHengoaWnxdbhMupdh8rP2H4/7yRgrS24rRrWYTWYmx5KTEMTnLuGq+ZEomSsHGwloK0p3E2Sz85eaZ3LYwj9Ghq5VWf/c9/YUYiv6z4TiX/2E1tW4v9R4fV/9pDX9adghfQJNfMAmfNuOvPBjZ/p1dZVz6yEp++MouLn5kBUv3VnC8JnTVXrodgAAmZresHqynJIaxN3aUcenvVvL69p5lsD44XM0ol4nfXDudWxbkgQ4Fn6bON0+dCUYAE2zuWXbT16FkYnxm+7uTDpuZplY/RbXNkWVlUQHyoUrj7uQt83O5dUEeKaHObnWerr+j+tOxag8/e203Hq+fH7xsZClXHahm7eFqfvPufi6anMlDV7e/5W+zmBid6mR/WSNv7yqjuK6ZJXsrSHXaGJMW+s6s3AfZM+HCnxAzMqrjY2vPL3L6lb8VXbmH5Y1ZNLX6yU3pnF1MzGi7o2xPzsJecA6xykvCyh8BkLv/r+iHxlL/0zxuWXMhG+xfxPqb8dhevpN0h4XKxlayE2MZmdTFyD01h9tljwGmX/NdCq96pd0wbQCWBKPzWU152yBgptpDVJFIQnL7SeBaM2cxSpdQU1GMvfEYZeZMXGlGoN9S2/f+H7GtRvmR2XPiZGN/iC6xOJEYqxm7xURDi5+jVW6+//Iu/v5BISkOGxdPMZI5EiCfwOUzsvD6g7y1o+uT42ColOJQpZtjoToij9fPocomJoVuH3V0/kTjBJ6dl8wPLjNqgM4ea2QhJmTG88NPTOZzZ+cD0CoZZDEMHaly4w9qjlS72XK8lo2FtTy2/BBJcVYuP3MUhToD0/o/wXs/5tVtJdz5zCZGpzl49ctnkZ/q4Cv/3oI3EGRcugvKtkFcCkdt48j2dTlxkRDdqmg0Asz39nSdwdJas6mwhsdXHMbj9bP1eB1TU81cdeZII/sZCAWf5s4BckysA6+2QPOJq/m01rhb/QSCmhq3F61hVLIR+Ewc0SFAtlvweP0U1bZ9KZfXR2WQK91MHBHPjy+fwug0J0mhAHkwOuo9u+EYT6w6wtef3cqhSjeZ8TGsPVzND1/excikWH51zXRSnJ2HnxuX6WJfeSOv7yjFErpjOzc/pS2T3lxjZEiB3LNvgslXUk0iZu8QySBX7EEF/fy3yKj7ze/i9ntS6gh82sicO1JGMfncq6khntzgcd4PzODlxJvxjL6YN30zeScwiyXMgryFsOO/fM3+CgBzRye3u7sAGJ2bK/dBSvvRr+KcCRRM7zzaSbjUo76iLUC2ttbSaOqc9Y4ftxCAwqduZ5RnF3X2bBLTjQA50Nj3ADnebwTIMS0DGyCHLxoTHd2PBhYfa6Wh2cfzm4swKWPuigsnZZAZH4PNYurUx+xkBmWq6cEwY1QiGfF21hyq4trZ7etvatxeqt1eLpiYznt7KjjnoaU8euOZZMTbCWqYkp3Q5T4/OT2L5zcVMSsvmfxUB2cVpDIyqf1gG+FbUq0+CZDF8FMcqp08Vu2hqbWt9/N549MZk+bka74v80TOCkas+g3VpqN8PSWHu+YVYKss5C9Tm3h85WHmj0/hMmqhcA1kTiNQUo050Pee1OL0FS5V21fWyD/XFVJc28x1s0eRm+Lg7v9spdrt5VBFE8V1zWw+VosvoJmQHJUHCk+8YOr8RatMJhqVA5P3xBnkO/6+kff2VJCVEMP1ob4q8/JTOF5T1Ol7wmG34AvoSEfuxDhrpwzymTlJkd+TQ9mx6iYvtE8e9rv1oZGZ3tldzpg0BzfMyeFnr+8B4I+fPpNYm7nLx43PcPLqthKKapu5/ax8ShtauG5W1Perp6atA1n6RLjmKRr2TMPiP3GH+QEVqj/eqfP58Scnc9bYzpO6mMxmKlQSmVSRmJGDzR7DvhGfZH7pMywxLWCJ5wLiJ0/l/g0bcNkt3H3BOFiYB/5WLj/wCvdzadf1x+U7wVMFuQt71FRnmvG6RneQi/HV47F0jk9GTz+b/e+NI8ezCyt+WnMX4XAm0Kxt6Ka+B7fJ2jhPXL6qPu+jO3tKG3h8xWF+cdXUSFkrGBeNFpPCdZLJ3hJirdQ3+1h5oIqzx6bx58/MxGJSmEyKUUmxvc4gnzYBslKK/FQHx6Nud4WFez3eODeXT0zP4gcv72L5vspIRmDqyK4D5IJ0J6vvWxz5fWwXHQDtFuPD2RuQEgsx/JTWG++XwmoP7tCQVbPzkrhu9ijyUh3s0nm8POZCLmtu4NbqF6AJeM14bAHwf2agMPQPYNr1BMvexqxbEaK3wp3Ydpc2cP+LO1EK3thRyn+/MJ/Xd5RGAujRaQ7e3FnG2HQn45OikhPB0IVZFyUWAG6TE1tLNRtf+RPTL/4sVltb1nTj0Rre21PBFTOy2FPayG/e3Q/A9XNGceO8XCZntf+eiAsFlXvLGkl32clMiKGsoZW/f3CU3y05QFWTl2tmtgWTyc6BzSA/u/4Ye8sauffiCWwrqsNpt9DU6ufm+XnMzDUC98lZ8VwSuj3dlXDnPKtZcfP8vEin9QhPNcS1Dw5bzA6sXQTIT6w8THyslWtn9a0DWZ+UbcdNHGPGTjJKcE6gwZJMqq+G5DSjzGHsJ77NuuebGFFwLWXLS1h90AgYV923mITY0MXXyFk4971BDK3t64+1ho1PQsVe4/eC83vU1KRQqYe3NjIqLnGBBqrj8jttGxPrYNz3NkR+nxv6v9aUiLW5byNred31xGF8bicGej4UYm88uuwQr24rYfqoRFwxFj4xPQur2UStx0dinLVzFr6D+BgLx2o8FNc189mz8tsF2TnJcRIgdycnOY6l+zqfHOEOeuMyXWQnxvLqthI2HK3BH9SkOm1kxvd9iulwgNwiGWQxDJXUGRmvwho37lY/BelOnvvCgsj6FIeNl7aV8XDll7k05wv85trpqC7nAgKUgoRR6A1LMGm5YBS9Vx01ysP5E9K589wx3PD4Wj79+Dq8/iCLJ6STER/Ddy+dwK6SBmbnJbNyxfK2HYTvXJi7vlXbbHJyhnsVbF7FB+V7mX+HMdmCu9XPz9/YQ6rTxgNXTaOsoYXzfrUMgHRXTJeT3jhC2a6DFU2MSIwl3WVnxf7KdkN/5qe13dKPZJAHYCQLXyDIr97ZT1VTKzVuL76A5udXTuJgRRPXzDLKUa6dNZLr5+RERrLoynnj03nspjM5a2wazo7ZPV8z+DwQ137qbK/ZQZyvfV+fplZ/JGM9kAFysGQrO4K5TM5O6nY7tz2dan81GWYj4ErNyiX1K0/jP1gFy0v43+YishNj24JjMCZTAu6eE9e+/ri+CF6/x/g5Ywq4TnwBEi0xJQOvtqAb2+rvXcF6yuzdtz1aozmZmNa+ZX/rK4tIA0pVGmm6GndzK47YDz/r4/82FVHZ2Mpdi8YQngjvx6/uIqiNOvfLpmVR5/GS2E39cVh8rJW1h40ykI5xW1ZiLNuKejd6ymkVII9KiqOysZVmb4Cn1hzlYEUTv752OgfKm3DYzGSFBvaenZfMe3sqqPF4mTEq8aRXLd2xhQJkqUEWw02zNxDJ2IVLLHI7BAI3zMnhiVWHyU118qPPLEDFnXzGyIDJip2B74gkhr8at5dxGU4+PjWLG+flkOq0c9uCPJ5YdYQYq4lHbzwzkjXq8rZ2pMSi66++Vks8hGLoycX/pcXzc2LinGx55BqmN+Tw2WvuJdZmJj/VQazVTLMvEBm2rSOHzThGUa2Hc9PSyYyPodUf5NKpmdw8P48fv7qb2XltwU2kBnkAAuQV+yupamolKyGGV7aVYDUrLpqcybWz2t6/v7x6+kn3YzIpLp5ygtnJPKEsY2z7ANlvdRHb2n4c3Xd3D8LEQcEAlO1kV/A8pmR33c8ozPWx71BWXdSp8mXayATiYyzUeXzM6DCqQjhAvnNGjJEcCKs71vbzuIt73FxlMtGgnJhajBp5HQwSr5sIxvQ8QG62JZPWchiCQTD1rgtaY1UxaUBZ3DhGuFdTXFmKIyevV/voqMUX4Oev78btDXDz/FwKQxneoDamlF59sIrLpmVR6/GS1IPvlvgYayQZmR7f/n3pirG2KxPsidMqQA7f/vngcBUPv7sfbyDIPR8bx8EKY9a9cCA8O994Q9d5fJGOeH0VrkGWYd7EcFMSKq+Is5k5Wu3B4/WzYEz7Gr1vXjSeLy8uQCnaDQHVHW2yYJYMsuiD6qZWMuJj+NoFbTOHfXlxAc9tKmJWblK7W6pdOkmJhc/qglCZcDwetqx6icnnXs1Znvc5ywJUp8Nqo5Ru/Xl+Suqaid1wqMt9ja9s4g6z0aHqjJZEzkhP4sIJjSzMTcVcupo3ZwE7t0S2twJfjtnHhMNrIOZDfO/4W8AaB/O/1D4wi/KvdcdIcdh4755z2Xq8joRYa/vs56nQHAqQO5RY+G0uYnX7W90vbzXKBsZlDNz0xVQdwBRoYWcwj49ldV1GGdZVpzkwgq4fXz6Zu/+zjREJHe40JxgBMvUdhlWrD10c3PRCj+uPwzwmBxafcce7ob6GBBVExXVxIXgCR1IXMePYGnj9bsg6o1fHjtm7DoDmlCngXk1DxXH4kAHyWzvLqA11wFt5oIrCag83zBnF7WeP5oE39rD6oJENrvP4urxL01F8bNv7OnpMcjDGJff6g/gCQayhyWA8Xj8vbD7xsHenVYAc7kB393+2Eb4L/NbOMg5UNHJWQdswKVOzE5g3Opmzx6Zx09ycrnbVY3ZrOIMsAYEYXsKTG8zKS47cFs7tWGMIJw9KOtAmGxbJIIs+qHZ7GZ3WPnlz43wAACAASURBVIhKjLPx4hcX4IzpwddZZBSLroNBv83IJB40j6EgcAhvXQmVxUfIDm+w4peRbV3A+E57aFMA3B8+TKnxbwTA0RM/5psAxaF/H9bYCyGtfQt3Ftezo7ieJXsruOfCccTZLJ0uek8ZT2hGwg4lFkGbC2dUgNzU6o/U8Db7BuB7cvtzUHsUEo3v9mO2gq6HYOuhK2ZkY1Kq8zjHoQwyDR0D5NAoFDnzwdq78s0WkwNrKEBuqi0nATA7eh4gl+V/iv8cXsN1m56CTU/16thZQJOOwZY3F479GfcpmE3vhS3F5CTHUefx8vLWYmrcXnJTHIxJc7KwIJX39lRwvMZDrcfLtBP0BYsWnuYdjNKnaHGhOzruVn+kXON4TTPfe6n95CvRTqsAOSd0BVLf7OPWBXmsPVzNfzcep7yhlbEZ7cc6fvbz80/JMe1SYiGGGa2NSQ3CAfIFE9O7DZB7vX+TBYtkkEUf1Li9JDs61yJ2DJpP6CQZ5KDd+BKuSpnF6PLDBBvLqS05QDaw6/ynmTzngh63dU9ZA5/60wcAfPeSCdw0L/ekj7nmzx+Q4rDx2E0zT7rtCdUfh0fnGaPGdAiQb3h8LY0tfrITY7njnNF9P0ZPRALkDgGc3YVd+Wht8WCPiWPVgUp8Ac2YNAf1zf08uo3W8N4PjaDV5qJBuYgdMfFDlVEqpSKz9rZjsYMjrS1jHFZ/3HhNbL3/LG01O7GHOjg21RhDHdriex4gZyXF8jX/Hcz+7K8Zndrz4/9r3TEeWXKAOFci/x07HlaAt66k03Y/emUX9c0+Hr5uRo/2e7zGw7SRCZiU4pXQhCp5oe+YhQXGhdvKA1XUun3djoEcFr4L4oqxdBp5JVwj3xQVIEePKtOV0ypATnW2vcCfnptDZkIMD75p9CQdm94/t3YkQBbDzd3/2cqBiiaS4mxYTIob5uQwJTuBbcfrIh9aH4Y2W7Egw7yJ3mnxBfB4A10GyD12kgBZxRp1pKYRU6iteAuTuwJP5VEAErPHgr3n3xOxDoUHI4uVmJTUo8daY11U+4K9Ok4naRPAmWEEyLNuiyz2+oM0tvgZnergj1G12j1Wvhu8TTBqTs+293RdYmEKzRpXW1PFvW+VUVTrwRVj4ayCVP636cNnJbvjbDpkBMdpE9ABH5+puJ25I5NP/sC+is+Chg6BZH0RJPStI6LP6iLeZyQrWhqMrLs9Pq27h7STnRgLKI754hkdn97jx71ReJyEjBxe/cpZ2LRRI68bjLrxwmo3GfExxFjNrD5olEn84sqpJxwaMFpFQwuLxqdx2bSsSIAcnqxlbLqTNJedv6w4hDcQZNrIzuM9dxQfCpA7lldAW6dZj7ctOVNW33lUs2inzUQhQLurxHEZLm6NGtaloN8CZKlBFsPH0r0VvLS1hL1ljaw6WMX9H5+I1WzizJwkbluYH6nd+lBMRoAczlSLoavO46XFF+CuZzax9fiJJ9AYCOHRHVI+TIB8khILUyhAThg1hXpTEraWKgI1xwhqRVr2mC4fcyKOqFEdTtSRryOn3UJjy4e8eFQKchdA4WojYxoSHj7utrPyI8Oz9cqrX4W/X27M/nZwCTx/O7R0MyNepJNe+05kplgjQF62/RDL91dyqNLNOePScMVYafYF+vVzIbVqHSgT3PYme69eyjZ/bmRG3H4RP7KLEosiSBjZ9fYn4be6iAsaGWRvoxEgOxN7Xq+elWiUkoRHJ+qJQFCz5Vgtc/KTsVvMKGssDTgxeyoIBjVvPHwnP3/sKYJBzbEaD95AkPVHa046Zbq71Y/bGyDdFRMZVhDa7vQrpVgwJoWjoem7z+pBciZcYpHRxchjDrsRi0V31Cur73640dMqgwyw+r7FkaxujNXMv26fy383HmdU0oe/ddyVtgyy3FIWQ99jyw+RmxLHU7fNocbtbffBdcqYrFgJ4A9qrOa+39oU/Wvr8TqufHQ154xNY/n+SqxmE7+7oXcde/pqy7Fa4myWdtM3VzcZX2ZdzejWY5EMctcB8ugFn+KD6iPMmraQPe+l4PBW4W8sokolkW7vXb1o+AsZ2t+97I4zxtLrnvYdvby1mLKjGdzpLjaCsUQjW1nd9CEuMFrqoXiTMVX3M1dDY6kxhFvAB9c81XVnwOYasCd0uhixxhkXIe9vPUiyI4/7Lp7A3NHJvLa9lKA27rb2OrvdE00VZJW8Q2nSLP70bknkIuFEE4GdEgnZcGQF+FqMemOtoe44jFl88sd2IWhz4QjVbweajADZldzzADndZcekYHdpPUv3VnDehJNnkfeXN+L2Btp9F9SZU7A3V9DQ1MRdlleh+lXKm26M3Cm/5a/ryUmOY8W3zzvhfisbjfdzWijbu/q+xWw5VtvuwnLhmFRe3lrCGTlJJPRkFItQJ73uMsju6AC5oYUUh40Tzet62gXI2Ynti/EXFKSy4BTcNj4RmUlPDCfVbi9TshLIT3V0Oe3qqaDNVqz48Qc0/fE9KE6NZfsq0BqWh+rPo3uI9wetNd98bjszc5N44I09xiQgXzs70rm6KDTJ06kpsej6xEvNyiX1zt8D0GpPJb3lGD5PMTXWTHp+Q9oQazWjlBET9TSD7LJ/uAD5cGUT9z2/g4n+TO60Y8zWFgqQwxnkPr1+hWuM4Hjh1+HIcrDEwNgLYPUjsO7PMO8LnR/jqe7UQQ/A6jAC5Ls8j7FmwnciM9uGJ1Zp9gZOfYAcDMILn8cc8PD1umtZV1KI2aQYkRBDfkr/fM4BxjBu6/8CL30BCi4wRhjxufucQdYxCcSpVnzeVrSnhoBWuBJ6XiJiMZvIjI/hmbXHeGbtMZZ+c9FJP+c3FRpjVs/MaTuO25aK01tFfXUZ4cKH3cXGGMMxVhMtviDHajzUe3wnDGwrQxe84WA2OzG2U3y2cGwqSsF543tWRhLOIKd3lUG2dQ6QyxtayOw4+kiU0y5AHmi2yEx6EiCLoa+pxd8u89UfVChAbgoEiUUi5KFq7eFq0l12fIEgtR5fJOPTX45UuXl+cxHPby5CKYizmvnKv7dwz4Xj+b+39rIj9AXcaTit3jhJiUU0f1wayXW1BH2KEufUXh9KKYXDZqHFF+jxEGrOGKPEQmvdp45jz6w9RlBrDhAKwCp2w/hLgF6WqFQdgOTRbRcSh0NB8aLvwIU/NpYFg8Z2b90H7/+s8z58ni6HEsuZPI/Na85hjGc7U0q+D9sCoBQTKqq43HQcdtRCDzpk9crx9XB4KatHfoF1B7OYN9oI9h66enq3E6F8aAXnwznfghUPwa4X25ZnTO7T7lSofrupvgZTSy0NykWSuXefoakuOyX1RonF69tL+PLisd1uv7esgfgYC6OS24LX1pg00psLqasrjyxbtX49YOI3187gzZ1lvLqthOO1Hlr89i5LHioa2meQu5KdGMuLX1zIhMzOsxR3JaGbGmRnJIPcdje/tL4lMv9FVyRA7meRiUIkgyyGgaZWP077KR4PtSOzDbPS+H0+ONVjr57GXt5azJEqN5fPyO519r+6qZVNhbWMSo5j4oh4WnwBNh+r4+Z5uXzn0onc8tf1VPRzgBwe6ivFYeP8iemcOy6dL/1rMzc9uY7clDi+c8kEZucnR+oo+yQyUcjJzzvlTMem/GTpCgpdXYxS0ANxNjMOu7nHwa7TbiUQ1LT4gj3q5NTRgYpGxmW4CASdVDWkk1q+O7KuJpSxO2kG+eASeOYquOIxmHEDvP9zIwtacEH7YclMJrjyMVj7pxPXIo/tPOqHKyGZM7/5KpRshb9dAi9+HoD5wHwb8FZvnnEvTL2Wf1ach82sefzmWbhiBuizZ/H3YPbtEAhNAGO2g6tv41ybQ/XbnsYarK01NJpc9LYIbl+ZMUycK8bCa9tLTxogt/iCuGLaT/MccKSTUlNHYVXbBC+N+5djUudxwcQMcpLjeHVbCfc+v51dJQ2suW9xp/dtZaMRpHcVzEbrNAFLN0YmxXL97FFdzl8RTvy4ve0zyGfknHj/EiD3M7NJYTUrqUEWQ14wqI0AuSfjyX4YZmP/Pp8X6J/a/9PRD142hlh6cUsxS75xLpZedKj89v+2s2RvBRaT4gvnjmHdkWq8/iDzRqdgNinSXHaOHnX3Y+th9cFqshNjWXLPudjMJkwmxa6SMWw5VsejN54ZmWnuQwmGPodPMIpFNEt82xTAcQVn9+lwDrslUjrQE+H3XmOrr08B8uFKN7PzkkiMs7FzUzbnVOyO9MSvcXtRiq6n7K3cD2v/CBf+BN74ZmhnS8GZboz9POVquOSXnR8XkwCL7ut1OwHImgHf2B3pzLfqQCXfe3knf/nMLMZl9Cxj2GNKccCbyvLfr+Tc8RkDFxyH9XA66ZOxxBkBcnNjLUmeQmrt2fR2poZvXTSeh9/dz5fOK+DBN/dS0dDSZUlCmNcf7NRXxBQ/Arvy4y7ZG1l2hWk1L7EYm8UUmdRjV4lx4VTj9rYLkBtbfJQ2tGAxqR4N39ZTFrOJBz81rct1jqhh3sAYFafG7WVEN89dAuQBYLeYZZg3MeR5QoP0O/u9xML4QPT7+n9K3dOFLxCkvtnHlOx4dhY3sOhXyxiT5uTpz558SK5Wf4DVh6q4YkYWByqa+MPSgxSkO7l65kjOGmv0z0hz2alobO3y1n9RrYcXNhczPtNFfqqDa//8AU/cPItZeT2vjQwENWsOVXHxlMx29affvnhCj/fRswOFSyxO/tUXk9Q2hfKEBZf16XCpTluvAgBX+Eu8xU96L2PEZm+A4rpmrksbxeg0B3vWj+ScqreM52y2Uu32khRnw9xVScGWvxsTR9QeNUapSMyFIyuhaAMkj4HL/9jrSS16JDapbZSLmgSO6mrqYnMg5dQOvaa15mu/W4XNrPjp5VNO6b4Hks1pvC7umlImBYrYmLSo1/u4/ezR3H72aF7aYoyuET3sWVeiZ56LtCMpCwBrlXGHomrm11iw6REu0BuBS0mItRIfY6EhNCJLdF291pqLHl5BSX0LmfEx/VviEsVuMWE2qUgNcrjEI0NKLAaXzWKSYd7EkNcU+jDr7xILFar/DPj695b96aQ2VF963axRWEzFbD1eR1FtMx6vPzKD1IlsKqylxRfkE9OzmJWbzO7SBuaNTm4XCKe77Hj9QRpa/JE6v5+9tpsdxfXE2sws29c2kUydx8ezG44zNsOF027B6w/i9QeJj7WcsNSguLaZhhY/Z+b0w6gp0XpRYuFINgJkvzZhj+nbnY6Hr5uBrReZfFdM+yxXR15/kF+9s4/PLszv1LnocJUx/NeYNCfjM128FxyFKeiDyr2QOZUat5ekE40EcHR1aCfLIHMqnHlLWyb508/1T3DcQThj7vH6qfN4qWxsZWw3meSl+ypIiLX26JzZVdLA7tIGbplk67ZT1lAX4zTKATyH12JVAWwjp/d5X+Gg92TDsXUVIDuSjZKj5KaDBLUi9ZL7aTz4Jo94n4aGOyB+BDkpcewsNjLIDc1tM6dWNLZGaqC7vFjrJ0afAHOkBrk0NAZypmSQB5fdYpISCzHkNbUaH2L9XWKhLKEMsl8yyKdKVXgIL6edZ26fy7u7y7j7P9tYfbCaFl+AS6Zktiu5CAY1L2wpJj/VwfJ9lVhMirmjU3DaLcwf03lmrnBHmsrGFrYdr2PVwSqeWHUksv6r549l5YFKthyrw2Y28caOUl7fXkqqy0ZNkxe3N8DkrHgeuno6k7oYd/ZItVG+0V8jp0ScZKKQaCPyJ7HTPgPL4vvpax57ZC+HD3VGZZC7svZwNX9ZcZjM+Bg+e1Z+u3WHKo3XcEy6g7yUODaZphBQZsxb/w0XT6Xa7SXFEVXvufp3ULIZPv4bKN0KcangqYK5d0H2mcY2OQuMKasHQGzozsGWY3Xc+rcNAOz/2SWRfjzR6j0+vvjMZiwmxdt3n3PSuvSXthRjM5uYM2J4hzyxLiODHF++DoC0gr7PuGgJlU2cbAABb0Bj7fA3SB9pjAk+JniURuUgwWLHdeM/4PHF8Po9cMO/GJXUFiBHj+19sKIp8nNxXfcTdZxqTrslkkEurDGGy+tudtjhfbYME0aALBlkMbQ1ha6sXfZ+DpClxOKUq4kaocBpt7BgjFEa8Y3/bKWx1c+kEfEsGp/GV88fi9mkuOuZzby3p60H+tljUyPBWVfCAfKDb+6LPG5mbhLjM10s21vBHWfn88npI/jV2/tZPDGdb/9vO6OSjWGbZuUmMy7DxV9XH+Hz/9jIym+f1ymTfLRqgALkQOiLugejWMTEOpjyneX9254O2mqQTxwgAxytdvP2rjImjYiP1HsermxCKchLcWAxm4hPz2FdyznM3/x3flR/GeuP1HLx5FAtrNdjjKzQ2gCNZcYQbp/8HdQXw7RrjQuIRd+FyVd0PcZxPwjXaj+67GBk2aHKJo5UuVk4JhWzWXHVo6u59+IJHKly0+wLYLeY+NqzW/jYpEwOVDTyy6s7Z1QDQc0r20pYND4Nh7Wp0/rhxJFgXLxObN1JMzayR/e9XMQWySB3PzGLzx/E1qEGOS4tj2bsxKlWikypJACkT4Dp18OO5yAYjJyXAA0tbRnkA+VGJ8Gb5+cyN7/n02SfCnF2S6ST3tEqNxaT6jS0XLQBDZCVUouAl4Fw6uEFrfVPlFJpwItAIvA9rfVLoe1fBu7SWnee9HsYsVvMMoqFGPLCWStHvwfI4RILCZBPlWp3eBIN4+IjIz6GNJedysZWpmTHEwzCo8sOkeK0U+Nu5b095XznkgkEtMakFNfP7n7q23BP8/f2lPOxSRn88uppxMdYMZkUXn8Qm8WEK8bKY5+ZSSCoaWj28bFJmeREZWdSnDa+/T+jV3vHyRmOVruJs5m7HfLplIiUWAzN3JArVN7UXQYZYHdJA8+sLWRhQSr/+NxctNYs31/JmDRnpIZ7fKaLP+2/lAX+pUzd+QBwZ9vdoT2vGMFxzgI4tsaY0GP0eWCLyqYturffnmdXwgGyL6CxmBT+oOaht/fx/t4KnHYLd184jv3lTTz09j4aW/zMzkviM/Pz+Oq/t7DhqDFW71cWj20XmAF8cKiaisZWrjgjG6r3DehzOtWc8UY5iUlpjlnyGW/p+3ncmxILu7VDFt9kosyWS753P25L1CgQWWfAxieh5jAXTc6gpK6Z17aX0tDcdj4fqGgiIdbKjz85uU9DGX4YDrslkggqrPYwKjmu287Mg/EpsVJr3bHHww3A08CzGIO8vKSU+gSwebgHxxCqQZZxkMUQFymx6OcA2RQqsQhKgHzKtM2S1hZgTs1O4P29Fdx38UTOGpvKNY+t4ZH39tPY6ufaWSO589yeT52c5mqr0/v5lVPbjYTQ8Ra42aS4/ezRnfZx/oR0TAre2V3eOUCucpOb4uj/L8xelFgMhkgGOSrjFtbU6md7kTEW9MbQ5A0rD1Sxo6ieplY/W47V8dMr2jKKEzJdvLA5mzUFn+Pqoie52ryC4C4FqffC/reMcY5vewPclWC2tQ+OB0FM1Kgd88eksPJAFcv3V+K0W/B4/fz6HSO43VvWiEkZ9d1z8pNpbPGx4UgNL20tYeWBKj49t/24Di9uKcZlt7B4QjprVw/vANkcFRDXjv7Eh9pXeGQK30nubvsCwS7L7ppcBVC9n1ZbdIA8w/i/ZAszp13DzNxk3t/7Vrvz+UBFEwXpzgEPjsHogO4J3Z05Wu0mr5vyCoCe9x7oXz4gFrADQaWUBfg68NCgtuoUkRpkMRyE68RcA1aDLJ30TpVqdytmk2o3IcXFUzKZm58cqSm+4+zRNLT4OW98Oj/pZU/++BgLSXFWbp6f2+csb4rTzqy8ZN7ZVdZp3dFqD/mpAxCg9WKikMEQHqu1rtlHS2hUmeM1Hr753DY+8ftV+IOa+aPbbkvHWs08tuIQjy47SKrTzjUz22ZomzTCuAj5SslF/J/lLo5O+TL+vEWw/EGj5vjce43yCWc6xPZ8rNn+Ehc1esmYNCdpLjuBoGZ2XhJz8pPxeANMG5nA1OwEvnPJRObkG/W4N87N5eHrZpAZH8P/s3fe8VGV2f9/P9PSey+QUEMLhC5VEAHBghW74qroruL6c3Vtq+vattnL1xUbuqtiYV1QUBEhUgy991BDSAjpvUx5fn/cmUlCEhKSmWQSnvfrNa+Zue05d+bOnXPP/Zxz1h7KrbfN99ccYemuLGYkR7unfXUHMmTWg21a39jCJmbVloZJegAyUlPmW7zqVByJ6Kc1lMne7pwU6G2sJ7E4fLqMPpH+bTG91fiZtE6VUkrnRfnZ6IjL6DFCiB1AFvCwlHIP8Jn9cRvwKPA74BMp7U3Hm0AIMReYCxAREUFqaqo77W41FWWVFFvxWPu6OmVlZeqzbwHbj2snsR2bN3DY5L6r++qME/QDDuzbQ1FZ69vqnsn5/D3vTq/GzwCrV9dqZiOB3ybBGvs0E/D0GG+6B5Sxft2acx7j5QlGdCKvTZ9xLy8znx+t4ctlK4n01f50rTZJRn4FAwJq3PL91T0u4jL30wdYm7YBi9HFtXZdhEEHr61I58v1h3h2rA/fHzWzKN1Mn2AdDw7zotxcShoQ6i24IEbHsp3ZSGB2X2O979Vqk4R5C/IrLGyNnsTocG9OBI9lZPZOqryj2V4QBR72ezEIsEgoyztJqMFKLhBkLSLOS7AeSPSq4Oo+JrBlkJqaUW/d3gEWftl/ipWrVqETguwyG8+vrSQpRMdov3xSU1O7xDmiNOxObD7hBG3a0qbtHCvWLsC27dgJ2U27gsWlFQRQ0eBzM1drd5UKa3T15g31TYA9K9jmpSV36mzVHDmRTWpqIZUWSX55DbbiU6SmFrTJ/tZQWlRFfrGNJctTKa+xYi7MIjU1t8nl29tB3gokSCnLhBAzgf8BfaSUxcClAEKIEDQn+WohxHtACPCylDLtzI1JKecD8wGSkpLkpEmT2mcvzpGPj24kv7yGSZPGd7Qp5yWpqal46rHhSexemQ77DjLtogsbzRx3FYfTiuAY9OqRwIjxk1y2XU/8nvdll9Arwt+tnyfAZxmbiTFXMGnSxLMuN8mtVjRPz/wKPt+/ipKARGbbZRj7T5VgXb6GC4f1Z1IzWujWUO+4+HUXHILxEy4E74bVNDwB/9XLKaowk1UmyQ/oRY1vPvEhhfz06EUAbM0o5L1dvzKyVyTPzBrEin+swtug46mbJjdogPE701Ge+24vl4xMYtI4e9WL8ePxNngzyeBmvXcr8E39kZIqC2OGDMB4vJADGzOYNSGFwXFB7P/3Fu6/IrnJJiLFwSdZu3A7Yb2HMqRbMKv2n4a1m3jxhgsYnqBpdz3xHHHOuMj+A6dKIW01Sf0HMik5psnljBtXERcdzKRJ9duGV+Ulwlsv0qPPAHrWtUk3G1Y+xyTDNogdyjT/o5gMOiZ17092cTVjdbu5PK4XE7qH164T1geC4uDkFvjln3DtB2ByfcLuiqJdHCg+RVzSEFiVxtQLhjApKbLJ5d3uIAsh7gPutr+d6dAUSymXCSH+TwgRLqXMq7PK08ALaLrkLWiR5cXAZHfb6i5Ukp6iM1BabcFk0LndmdMbHEl6DXWWXYmTRZVc+sYa/jAtifsm93brWPnlNc4EPU+me5gv/aIDWLorm5tHJ+Bj0vPZhgxMeh2T+zX9R+UyPFxiAVBUodnoa9Lz9qrDeBt1JNVxCnuF+2PUC4YnhBAZ6M3zVw7C38vQaHe4G0d141RxJZcPia2d6B3UYDlPwdekNZeIDPRicHwQ32zTkRIfTIifia9/O/as647rrTlcaw/lMaRbMCcKtRvQ3ULb0Jq8C+PUILeiDjKAd3giXP0+PXtdVH/GuAfh6GpY8QwAzzimfwIxwGcmIM3+cBA5AH6XBr++CQe/h1/f0o7T4XNcWoNbS9KzsGLfaXQC+sec/SLZ7Q6ylPJt4G0AIUS0EEJIKaUQYhSaBjrfsawQog8QK6X8RQiRAlQCEui8lb0BL6PSICs8n7Iqi9tLvAHo7Rpkae3aGuQ1B3OxSfh2R5ZbHeRDp8s4WVjJiEQ3N9lwEVcNjeOv3+9nwj9WsnDuBXy9JZMrUmLdX8EC6rSa9lwH2cFDU/vy/NJ9AEzpH+WcHuRr5Nt540m06ydnj2g66u5rMvDkpQPca6gLcTQLiQr0ZmyvcC7qF9niFuPh/l70jwlkTXou903uTWZhJV4GHRH+nhcp9wQcTm9zTczMVluDOshOBl/XcJreADd/rdXYljZeW5HO4dxS3rxxGGlH8nll+UH+ed1g5/HL7v/CpvegPB+wS/tSX9SevQJg6M2t2LvG6RsZQI3FxntrjnDJoGiiztIkBNo/Se9aYLddg/wGcIOUsm4RvheAP9lffw7MAdYDL7Wnka5G1UFWdAbKqy1ubxICdapYWLp2BHnNIe3G2P5TpRzJdU/91V2ZxUx99RdOlVQR3FSXNA/j7gk9+eD2ERRWmLnuX2lUma3ceUbTC7fhLPPmuQlbPSP88DHquSKlNuqbdIasoF90YJdLOoPaZiGRAV7odaJZB+ZMJvQJZ8vxQl5bcZBjeeXEh/h0SLWEzoDjTmFzdZBrLLZz6gYJgMEE3S+AhLHkhQ1jnTkJEsZy0CuZTbIffn0mQsJY7THwKm2dzE1QcFh7rfcCoy8cWdX0GMfT4OfnQJ7d/rpcNTSOi/pFYrVJ7hzfsNJOg91o8ZZdgJTyLeCts8yfXef1aeDs91Q6CarVtKIzUFZtwa+ZtsSuQG90OMhdt8zbwZxS1h3KY3zvcNYeymPR1kwemd6PRVsyAbimTrWB1iKl5MVl+wjxNTEwNpCL60QZPRmdTjClfxRXD43jqy2ZzBmb2OytTpdhNWsl3jzYaVr2wAQAvI16BscHsTOzuEndbVfD16THZNDVq8ZyLtx6QYLdQU5HCJjYJ8LFFnYdWloHucZqa5PsLsDbSGmVGSkleWXV6ASE1r0rEDtU+02e2AD5h2HUPTD1w7JfHwAAIABJREFUWVgyDw6vBJsNdI2Mv/g+zaFOHKc1ugnpAWFnL12p0wneumko+7JLnLr0s+GZxSC7GF4GvYogKzye0qr2iSAbjNotz67kIH+64Tif/Hqc738/gU3HCrh+/noAbhrdnUAfAx+tO0ZCmB+PLdpJRIAXVw+La3Nka0dmMWlH8vnz5QO4Y1w7RWBdyCOXJBET5M3cc6jH3GZsFo+XV9SNDF+aHMPx/Ap6Rri5w6CH4GPSExXo1erfRrdQXxbOvYDhz/1ESZVF6Y/PQss1yNK5bGsI9DZitkqqzDbyyqoJ9dPuDjgx+UL0YNj/HdSUaU6u0Rt6XQS7voScXRDTsEMiXvZScZ9eV1vffPKfYOLDZ70A9jUZGJ4Q2uT8unhKHeQujaqDrOgMlNe0rwbZmTDVyZFS8v6aoxzIKeVkUSU/7c3BpNex+L5xzBgUzSPT+1FjsfHHr3eiE4KckmoyCyvbPO53O7Iw6XUuiUZ3BJEB3jw0LcntjWnqYbN4bJOQxrhrQk9W/3Fyl5RTNMbUAVFcNbRtx7NRr3NWJogP6djmJ56MU4N8FgfZapNYbbLRJL2WEuij/d5KqszkllYT3lgycY8JkHdQex1qv2DuZa/LcLgJmUVpnXrql74MybNh1fNwbG2rbT2TznOm6MR4GfSYrRKbTaLTee6tPcX5TVGFmZ7h7i/grjdpEWRp7fwR5NdXpLNyfw5H88oBTVqRejCX0T1DGdJNa77QI9yP928fQXGlmcgAb258bz1bjhc2aIl7LthskqW7spnYN4LARqoXKJrAataSiDoJZzZ/6ercNibRJduZ0j+SJTuy6KYc5CZxSiwsTWt4HdHltjjIjuoqJZVmcstqGk/GHf1bWPe69tohkwiIhsiBmsxifJ2mKHnpUFkEZTlw0VMw4jfgG1obcS4+0Wpbz0RFkNsBRx9zJbNQeCqZhRVkFlYyKM79WlCTXYMsLa5rEtIR1FhsfLD2CDsyi53JRakHcjl0uowL+9bXPk5KimRWShyjeoTi72Vg07GGRfI3Hytg3aE8iiuaj6yvPZRHdnEVlw1uun6pohE6gcRC0XZmDIrhyZn9uag9Sgd2UvQ6gV4nziqxcMw75yS9OvSwV6v446KdHMopbbyqSGAMDL5eex1UpypLr8mQkQY19p5xNqsmqfj4Mu19WC/NOQbwtneDrCxqta1n0nkupTsxvvbSNRU1FmcZG4XCk/h532kApg6IdvtYersGmU4YQXbUBP1+VzZ7skooqbLw16uTGZ4Qwq0fbODLzVr0oqmavnqdYFhCCKkHcimrtjjlBbtPFnPtv9Kcyzw+ox93TWiYZb3qwGn+smQPNqnVd71kkPu/ry6FzdypJBaK1mEy6Lh7YvNVCs53jPrmHGQtutyWJL3k+CDeumkov1+4HatNEt5UOcer3tWkEnXv8PSaDGlvwbE10Hc67F0MhUdr54fWyV9w1PeuUg5yp8IRXaqosRLWwbYoFI3x094cekX40SPc/clABkcEuZNpkE+XVDHzjTVM7BPB4h1ZWG2SAG8D1wyLx2TQ0ScyQGtSEB9Er4impSr3TuzJrR9u5L5Pt/LI9CRyS6vJK9NqQr8yewjLdmXz/NJ9xAX7MOOMDlf/TjvOsXwtmvJ/Nw87b7SpLsNq6VQSC4XCnRj1urNqkF0hsQC4bHAsP+87zTfbTtKkyFQIre5xXRLGgX8U/PCYJo/66WkI7g7FJ0FaIbROcrJOD15BKoLc2fCzR4kqalSinsLzsFhtbDxawK1jEtplPKG3J2nYOkcEuaTKTKC3kTdWppNXVsN/t50kwNvAlSlx9Izwc0ZX+kT5s/ZQXrNJc2N7h/PcrEE8vXg3vxzMBeDi/pEY9YIrhsRy6eAYZr21jpeWH6C40szaQ3kE+RjpGeHPmvRc5oxN5MqhcaTYNc6Kc0BJLBQKJya97qwRZEd52rZUsXDwxMz+ZBRUNLjoPytGH5j9b1hwKXxxMwTGae9X/AVyDzR0qH2CVQS5s+GQVZTXdG7NpaJrkl1cRY3VRt8o9yfoAbVtfj04gnyquIqNxwoI9zNx0/sbGJkYwtaMIq4bHk9ZtYXpA6O5cmhcvXXG9w5n+Z4cLh8c28RWa7lpdHeGJ4SwfM8pXv7pIKsO5NIz3A+DXocBuOfCnvy/L3bw2H93ERnghcUmKSjXLiiuGhrnTABUnCNKYqFQODHqdWdN0nNEl9sisXAQEeDFombahTdK99Fw/yYoyoDYFE1KcfnrUJ7bcFmfYKgsbLOtDtSZoh1wNF+oVBFkhQdyLF+rwJAQ1k61Vu0RPOEGB/l4fjnh/l7OuzatwWy1cc+/N7Mjs5ixvcIw6XWcLKxk9ohuPD6zX5NVI6b0j6rXErg5kqID6BPpz3trjlBSZalX6/bS5Fhe+vEgoX4mvrp3DF4GHV9tyWRvVgmD44NavW/nPVZL7QWaQnGeYzS0LEmvrRKLNhPao76c4sz3DryDlcSis+FI0iuv9rwI8umSKv72/X5mDY1rkHmvOD9waFrbQ38MgE6HBV1t218XUWGWzHx9DdcMj+fZWYNavZ3/rD/OjsxiAH49nM/F/SN5//aRrjKzHjqdYEi3YNak59XTLZsMOr6bNx5fLz1eBu38MXtEt6Y2o2gpnawOskLhTprVINujyx3uILcUn2AozXbZ5jrJXnduaqtYeF4EeXV6Hv/ddpLbP9zIhiP5HW2OogM4nleOt1FHZFPZxW7AggFRx0EurjDz0bqjVJlb9hux2SRFFfU1zBuyLZTXWPlxzymkbPq2YXPszy4lIsCLC3pq5YPcfeHo0BKfmdgX4mdyOscKF6EkFgqFk2Y1yC6UWLQLLo4gd5K97tx4cpJevj17HuCHPafOsqTCnZwqruLbHVkdMvax/HISw/za3Pr4XLBgQFhr76gs3nGSv3y7lzs/3oTV1tC5rTJbnU7v6ZIqbvlgA6Ne+JnDuWUAlFVbSM20oNdpnep2nyxptW2FFTWE+pq4Zlg8Rr1osmSbqxjTMwwhYFCckk64HatZSSwUCjtGvc5Zyq0xaiUWnaTBmSNJrw0BkrooB7kdqFsH2dPIL6/By6BjYt8IVu4/zSs/HeS4XZOqaD8+XHeUeZ9vo6Sq/RPXjuVXkBDWvh2nrOjrVbFIz9Ec3XWH8vlqc20nJCkl9322lX5P/cC1/0qjrNrCPf/ZwraMIiSST349xrG8cib+YxXHS2z8YVpfhIDvdtVebFTUWHjqf7sZ9cIK3l9zpNnoclGFmWBfI9cOj+fXx6a4vV3t2N7hbHh8CknRAc0vrGgbNquKICsUdpqrg+yoYtGWRiHtinewVl/fXOmSzakzRTvga0/SK6/2vAhyXlk14f5eTE6K4C/f5vLGz+lYbTYemd6vo03r0uw/VYKfyeBsN7wvW4t4ZhZUMiC2/SJcNpsko6CCKf3bt+OURRjR2WovGA/klDKsezBWCW+uPMRVw+KosdjYllHE0p3ZXNw/khX7TnPhP1aRX17D/908jBV7c/h6Syabjxdittr402hv7prUmz0nS5i/+gg7TxTTN8qfGqtk4aYMBsYG8vzSffh5GbhxVPcmbSuqrKFnuD9CiMbborqByEDvdhnnvMdmBkP7SYkUCk/GqNc5neDG8JgkvZbiE6I9VxWBqe2BDeUgtwN6ncDLoKPC7IER5LIawvxNXNw/ild/OkhJlYVqs2qJ7SqO55dzzTu/Mq53OE/O7M/vPt3KrWMSeH7pPkx6HcsemECQr5F92aUAnCisYECs+9s9OziWX06NxXbWxhbuwCr0CJuZn/flsHDTCQ6cKmVmcgwzBkVz24cbGfe3lRSU12CTEBXoxVs3DeODtUdZfTCXx0d0Y2ZyDH0i/dlwtIA9WSW8fkMKQUXpALw8ewgAWzMKSTuSjxBw2wUJPHPFQG58bz0vLttHek4Z8y7qTYifqYFthfYIsqILoiQWCoUTk0F31uIBnc9BdrSbLoTA5sttNodykNsJX5OeCg+MIOeXVxPh70W3UF+2PjWVC/+Z6qy3qmg7h3PLyCurYfH2LNYdyievrJoDp0optZ+Unvl2D0/M7O/spJZZ6JpbQy1lT5YWuR7Yjk452CPI0sILS/dxJE+T9PSLDmBi3wg+nDOCLzadoEe4P6dLqpiRHIO3Uc99k3tz3+Tezm30iQpg7aOTKa22EOhtJDVVc5C9jXrevnkYZquNy99cy5G8cn47qTdCCP5+zWAeWLidD9cdZWBsYIOmHlJqyX/Bvg0dZ0UXwGZVjUIUCjvNaZBrnK2mO4kG2dvhILsmUU85yO2Er8ngkY1C8stq6B+tOUcGvY4wfxMFFcpBdhWOaPzlQ2L5dkcWwb5GiirM+Bj1zB4Rz7/XH2d4Qohz+RMFFWfdXkmVGYtVEtpI5LM17M0uwagX9IlsX/2rFT06m4XYUB+ng9w3SrPhon5RXNSvZfWEhRBN1iU26nV8cucocoqriQ7SJAwJYX58dtdoBv75R06XVjdYp7zGitkqCVER5K6Jzay1pFUoFM1qkM1ODXIn+c04Isgu6qbXSeLmnR8/L73HNQqRUtolFrWavBBfk4ogu5Aqi/ad/35KH56/chCLfjsWH6OeKf0juW9yb/Q6wd9/2A9AdKA3mYWVVFusfLX5RIOEPbPVxg3vruf2Dze2yaZtGYWMeH4FR3LL2JNVQp/IgHYv42MVRnTSTE5JFQBeBh39Y1zvpEcGeJN8RmMNPy8DfiY9uY04yIX2Yz9ERZC7JkpioVA4aawOckWNxVlJyCmx6CwRZIcGOfeASzanIsjthI/JQLmHOcglVRZqrDbC/WudgTA/k7N0lqLtOCLIviY9t1yQAMDXvx1DVKA34f5e3DYmkY/WHWV4QgghvkYyCyt4e+Uh3lh5iE/SjvOvW4cTF+yDlJK3Vx1irz2ZL7+sut6Fzbnw9ZZM8sqq+fjXY+zNKmZyUvsm6AHYhAEhLWQVVTJnbCL3XNizXWUNkYHenC6tajC9uFK7KFEa5C6KzaIkFgqFnTPrIFttkotf/oUbR3Vn3pQ+nU+DHJwAPS6EVS9Czm4QbbNbOcjthJ9JT4ULOuld9X/ryC+rYe7Enk6Hq7U4aiCH1XGQQ/xUBNmVVNtvUXkba29RDYytjWg+ddkAnrpsAADPLNnDin2nOZxbxvCEEPZkFTP5n6n869Zh/Lg7hy82n2BATCB7s0tYf6SASwfHtNiOn/fl8PaqQwR4G9mTpXWJW7jpBNUWW7vrjwGsOiOypobyGivxIT7EBPm06/gR/l6NR5Dt8iKlQe6iqE56CoUTo17n7JYHsOtkMVnFVc5Ooo7/r07jIAsB1y2ARXdC1rY2b84tZwohRD/gI2AY8KSU8qU68y4BXgf0wPtSyr/Zp38KJAPfSSmfsE97CtgppVzsDjvbE1+TgaKKtiVgOcpeAfzpf7vJKaniD9OSWrTu8fxy/LwMhNeJOubbHeEwv9ppoX4mKmqsVJmt9Zw6RetwdIbzaoGEIT5EcxKjAr1599bhVFts3PrBBh5dtIvc0mruGJfIYzP6MezZn0g7ktdiB/lEQQW/X7idMH8Te7JKqLbYmDuxJx+tO8qMQdENEtXaA5PJhK1S+z3EBbevcwwQEejFvqyGzUQKK7QIcqfUIK99Tbu1OOw2SBjT0dZ4JlYz6JWDrFCAJp2oG0FedygPwNkLwZHA12nqIAP4hsKt35zbOr9vXELirjNFAfAAcGXdiUIIPfA2MBXIBDYJIZY47JBSDhZCrBFCBAG+wCgp5XNusrFd8TXpGzQKySysIDLAu8X6T0c5lqcuG8DBU6W8ufIQEQHabfqzYbVJZr+bRs9wfz6fe4FzemMR5DB78ldBeQ2xHeC4dDUcV+AtcZBnj+yGr8nAVUPj8LE3l7l/cm8e+nIHoX4mHp6WhJdBz8geofyw+xSje4RRXm3BYpPcNKo7Op1ASslfv99PfIgPN47qjkEneOKbXQD8587RHDhVyucbM/j9lD48Mj2pwyIDAX6+5Bdrpe3iQjrAQfb3YnUjEeSizhxBXvMyVJdA+nK4d40mJfB3b5vsToeSWCi6CGazmczMTKqqGkrFWsql3SSTo8LYt28fAMl+1bx3RQxCwN69+xgWZOa9K2I4euhAu3ZadRfe3t7Ex8djNLbsHOAWB1lKeRo4LYS49IxZo4BDUsojAEKIhcAs4H+AjxBCB5gAK/As8LQ77OsI/Lz09TTIx/LKmfrqLwztHsJHc0Y621GfjTK7gxzkY+TFq5PJL6/hz0v2EBngzSWDoptcb8ORfHJKqskpqWb/qRL62atWOGrv1m2GEKIcZJdSbbFi0AkMLXBEA72N3DS6fgOLy4fE8sWmE8xKiXMeI3+YmsQ9/97MvM9rbyGF+Jr4z/rjXJESy/zVRwD49VA+lw+JZU16Hn+5YiDdQn3pFurLxQNaViHCnQT6+eKL5qC69DirLgWDT7NRwshAL0qrLVTWWJ0XIwCF5Z1Ug2yu0pzjfpfB/u/glf4Q2hMeaPttxi6FklgougiZmZkEBASQmJjYauc1u7hSq2QVF4RNSixZJegFWGyS3tGBFJTXkFtaxYD4YBdb3/5IKcnPzyczM5MePXq0aJ32PlPEASfqvM8ERksp9wkhMoCtwL+B3oCQUp717C6EmAvMBYiIiCA1NdUtRruCgpxqSissThvf21mNlJJNRwu4Z/7P3JXcfMJVRonmYB9L38+a0kNcFy9JP6njya+34p3XdNeYj3ZX46UHm4Qb3lnLqGg9M3saeXd1JUMi9Ozdsp69jjEKtTFS0zaRF941/kjKyso67Ng4dLQag5BtGv+3SUDlEVJTjzinPT1Sx4lSb/yMgqfXVfL411spqYH1R/Ix6GBGDyPf7jnFj3tO0S1AR3zVUVJTj7V5f1xFgjWSfrqfeNL4KXlL1pLPuZ/ga0xB5IePdr6vKCmg+uVkTkVP4WjPW8+6bn6m5gh/u+IXIn1rL152p1fjY4B1a1afsz0diVfVacYA+2UiAbEzictaBgVH+PXHb6jxCml2/a5M3d//BHM1J7OyOeLB/xUK99GR/wWuJigoiLCwMMrKWp9Ub66xIaWktLQUq00ipcSkF1hsUFRaRrVdn1xaWuoqszsUk8lEUVFRi4+B9vaAGvsXlABSygedCwnxLXCPEOJJYAjwk5TyvQYrSjkfmA+QlJQkJ02a5A6bXcKWmgMszzjEhRdeyMmiStJ+XMWd43ugE4L5a47w2NUXsDOzmIM5pTx12QAKK2rYdLSAGcm1OtNNxwrg1zQuGJ7C+D7hABzSHeKfPx5g5JjxCAFfbjrBrpMlnCyq4G9XDybM38QDqSu5JDmWlG7BfLYhgxUZZXgFR2KRVbx623h61umi1i23jBc2/EK33v2ZlBLn1s/kxz2n6Bbi6/bOcampqXTUsbGiaBe+uafcOv73ORtYk56HTmgXQRf3j+aNW4YRtHg3oEWcG+sY16HYJpA9P5u7Ty2Fg23Yzr1rIToZgH0L/4xXTSEJJZtIuPB9LWGjCcTBXD7YvZGeA1IYkRjqnL7g6EYig8o77HhpNZlbYD30GzYBkl6AjPXw4XTGyo2QsQ8ufBTihoPBw46DdqDe73+1je4JPene2b5fhUvoyP8CV7Nv3z4CA9v231khq5DVVfj7+2ta5NJSAny9qCipQm/0wihs6GpqCAho3zr57sTb25uhQ4e2aFmXOchCiPuAu+1vZ0opsxpZLBPoVud9PFBvOSHELGAz4AcMklLOFkKsFkJ8KqU8excFD8bXZEBKmPLyLyTHB2GTcNuYRAJ9jHy5+QR//2E/e7JK7Lc0qlm6KxuAjU9OITJAa3JQVqVJLPy9a7+2nuF+ABzNK+ed1MMs3ZVNRIAXheU1fJx2jGAfEyVVFu4a35Pk+CDG9w5n6qur+XZHFlemxNZzjqFWg5xf1nwli7Yk8mXkV/C7T7cyrHswX907tlXb6AxUm214u7nG8JR+kaxJz2PeRX1IO5LPHeO0W27PX5ns1nHbhE5PzD3/hdJT2K+Rz43KQnhnrKa3jU4GcxWxWd9r84qOw+m9EDWwydUj7MmqdStZ7D5ZTOqBXB6Y0ufc7eloyk9rzw7NcfRgEHpY/3/a+yOrwDsI7vj+rJ9Ll0ZKe6OQrnFnTKFoK44YggQcDfW8DDqEENRYbUhJl9AetxaX/XNLKd+WUqbYH405xwCbgD5CiB5CCBNwA7DEMVMIYQR+D/wTLUnP8c/p0CZ3WhwS1CN55SzensXoHqF0C/UlyMfIHeN6sCY9j4LyGsb1DuOHPaec6zk0kYCzPbF/Hb2yw8F94+d0lu7K5o+XJLHpyYuZNjCKb7ad5L01R5g2IMrZLKFPVAD9orWrwTnjGupwAr2N6HWC/PKGCUx1OZ5fTr+nfuCd1MP8eiiP3326hUVbMlv8eby1Kh2rTbLpWCGZhZ32uqdZqi02vNxcDeTKoXHcckF3fjOuB1/eM4bRPcPcOp7LEAICYyAw9twfUQMhZgik/wSFx+GNoQSVHIDxD2nb3v3f2nHMlfDjk/DOONj0PkhJjL2z3sGcMv66bB//Xn+cZ7/dS5CPkTvHt0yf5lGU2R1kP3tNa5MvRGnlA5nwB5j1tuYg/vKPjrHPE5D2bH3VKEShAEDYb+pLCTZ7cxC9TuBr1FNQXkOV2Xq2G3EuJTU1lcsuu6zFy2/fvp1ly5a50SL3lXmLRosCBwI2IcSDwAApZYkQ4n7gR7Qybx9KKffUWfU+4GMpZYUQYqe2KbELWCaldE3vwA4iKlD7Q54xKJrvd5+qV1rrlgsS+L/UQ/iaDCy4YxQ6IVh9MJc7FmxyNi6A2ghyQJ0IckKYL0LA8r05xAX7cO/EXgBcMyyeZbtOERXo5ayz6+D/Te3LxqMFpHRrKLzX6QSxwVpHt7Ox/YT2dTi6wOl1gh/35BAR4MXEvrWZ89nFlXy+8QQ3jOzmTMZafTCXr7dkMn1gFD/uyeHzjRk8PC2pS16pVpmtLapg0RaCfU2eHS12F32maZUbvrwVasrYMfgvDJnye63U2dpX4ORmiOgPlirY8hFE9IOlfwC9iZBhtzG+dzjvrj5MRZ3k2deuTyHIpxM6UI4Isl+dqhXxo+D0fhh9L/hHQv5hWPsqZO+EmMEdY2dHYrWfS1UEWaEA6kSQpcQmNQdZJwTdQn04dLqc8hpLu5R4s1jOvUfE9u3b2bx5MzNnznSDRRruqmJxCk0+0di8ZUCjbr+U8rU6ryVwozvs6wguGxzLsO4hxIf4sPFoQT3dY6ifiReuTMagF86yW47Sa46yUwBl1doJvm4E2duoJz7EhxMFlUzuF4FOpx3xF/aN4LEZ/Zg2IIpuofUT+KYPjGb6wKarXnQP9eV4/tmjuuk5WmLA1cPiGJkYyvSB0cx+N41nluzhp4cuZOPRArZmFJJVVMmnGzJ4f80RfnxwIt/vzubNnw/RNyqAV69P4bf/2crbqw6zNj2PR2f0I8DLyMJNGfz58oHt3v7YHbRHBPm8ZciNsGMhZO+Aq9+jsCBSO+Nf8x78dy6c3AJHUgEBI++GGf+Ajy/XosnZO7h7+F3cfiiPuGAfLh8SS1yID1cOda/u3m2U5YJXIBi9a6dNehxSbtKcY4Ax98P2z2DhzTDyNy3brtEXhs8BQ+u6NnoM1aWw5AHttXKQFQqgNilMUhtB1ukEJoOemGBvThRUNGhFXZdjx45xySWXMH78eNavX8+QIUO44447+POf/8zp06f59NNPAXjwwQeprKzEx8eHjz76iKSkJBYsWMDSpUupqqqivLycp5+uLVq2adMm5s6dy6JFi4iKimLevHns2rULi8XCM888w4wZM3j66aeprKxk7dq1PP7441x//fUu/3zUmaKd0OuE01Ft7Bb4mc0agn00B/nMCLIQWk3luvQM9+dEQSUX9attGWzQ67j3wl6tsrV7qB/L68g8GuNgTim9Ivx4ZXaKc9qDF/fh/s+2sXzPKT7fdILVB3MxGXSMSgxl47ECnvhmF2vS85jQJ5wXr0rG12TgvdtGsGhrJm+tPMRvFmwiKSqAHZnFJIT5Mndi6+z3JKot7o8gn7eE9YIHd0FVMfgEgyMz2eQHN3yqRQznT4b8dJj4MOh0MOst+OYe2PQ+E2YN44ohA5iVEsuU/m4ofSclbHgXBlyhyULcSfnp+tFj0PTIdesg+4XBjZ/Df66GFc+c2/YzN8OY+yA2pfllPQlLNZE5v8DqlbDnv5pevdvo5tdTKDoRf/l2D3sbaXzUHBabpNpsxdekxypxvhZCMCAmkKuGNR8wOHToEF999RXz589n5MiRfPbZZ6xdu5YlS5bw4osv8sknn7B69WoMBgMrVqzgiSeeYNGiRQCkpaWxc+dOQkNDnZUlfv31V+bNm8fixYvp3r07TzzxBBdddBEffvghRUVFjBo1iosvvphnn32WzZs389Zbb53zfrcU5SB7KEH2Oqz1HORqK/4mQwMpwoDYQLYcL2RMz3CXjN091Jf88hrKqi34exmQUiIlzug0QPrpMqeW2cGMQTEkhB3gX6uPkJ6jlYWpsdi4/6LevLT8AGvS8wj2NfL+7SPwMmhOvsmg48ZR3bmgZxgXv/ILOzKLCfAy8PqKdG4Y1Z1A7054u7sO1RZbvYi/wsUIoTnHjaE3wm2LoewUBNjvmIT20LosvRiLriyHN2682X22ZW+HHx6FvINw2SvuGwe0CLJ/ZPPLxQ2Dhw9pyWrNISW8Nxl+eBykFYQOrn637ba2J9v+zYB99s9+wJUw++OOtUeh8FCkXWLh1F0I6B8T6IwsN0WPHj1ITtYkfgMHDmTKlCkIIUhOTubYsWMUFxdz++23k56ejhACs7n23DN16lRCQ2vvpu/bt4+5c+eyfPlyYmO1oMLy5ctZsmQJL72kNWSuqqoiIyPDVbt9VtQ/t4cS4GVAiDMdZHO9ChYO7p/cm5tGda/X8KAL861EAAAcjklEQVQtJIRpke4dJ4pIjg/i1Z8OsjY9j8X3j8PXZKDKbOV4fjmXD6kfFdPrBLeMTuCFZVpXnmuHx1NSaWZc73B2nSxmZ2YxV6bEOZ3juvQI9+OGkd1YsiOLP13an0cX7SKzoJIBsZ3bQa4y2wj3VxKLDsMvTHvUxeSnyRHKctw7dvpP2vOeb2DG392XHFaer10ERA5oflnQmqi0tN1yyk3wk/3WZ135RkeRtR3mXwhzf2lZNDt9BTXGYEyJo2HqX9xvn0LRAfz58tZVpimqqCGjoIK+UQGUVJo5VVLFoLggdHWDcM38fXl51cqvdDqd871Op8NisfDUU08xefJkvvnmG44dO1avzJ6fn1+9bcXExFBVVcW2bducDrKUkkWLFpGUlFRv2Q0bNrRij88Nde/XQ9HpBEE+Rooq6jrIlkajkX5ehgY647bQ3b6tm9/fwE3vreeLTSdIP13G37/XEvIO55Zhk9A3yr/BulcPi8Oo135cT8zsz/zbRqDXCa4cGkdKt2BuH5vY5LjPXDGQVQ9PoluINn7di4POipJYeCj+UVCa7d4x0pdrGt7KAjj0s3vGyNmrdc3LPwR+rrmDVI8hN2ol4wBK3Px5tYRja7TnjQ3K4teSvRO2/Qcs1XB0NbkRY+DmLyEksV1MVCg6C4670VJKrFIihKjvHLuA4uJi4uI0qcaCBQvOumxwcDBLly7liSeecEoupk+fzptvvumMcG/bpvWPCwgIcHsDE/XP7cEE+RjrOYmlVZZGI8iupntYrbO9+2QJFTVWxvcO5+O04zz33V4WbjyBQScY1r1hh64wfy9mpcQxKjGU0DrNKeKCffjffePoEe7XYB0HRr2OcH8vAn0ayks6K9VmW6MRc0UHExANpS6MIBcchR1faK/L8+HzmzTd7gW/05zxNS9rkgVXIiUsexiMPpoT23Oya7cPmmzj3jVaxRB3X1CcC9nb4de3NPnHae3CnSXz4PMb4YtbYPF9sOguMJdTEDqsY21VKDwUg102WWOxYZOgc0MhqT/+8Y88/vjjjBs3DqvV2uzyUVFRfPvtt9x3331s2LCBp556CrPZzODBgxk0aBBPPfUUAJMnT2bv3r2kpKTwxRdfuN5wlMTCowk+w0FuKoLsaurqflO6BWO22vj4N6N47ru9fLD2KAA3juruLNt2Jn+/pm0lpILt+uuSruAgW6x4G9V1qMfhH6WVgXMVPz4JB5ZC0iWwe5H99UwYfrsWuVxyvyYN6H+FljDoCnZ9BcfXweWva5Um3ElADGRtc+8YLcEhi8nZDcufBJ1Rq3l96zew/fNabXVUMuxbAjFDKAwZ0nH2KhQejI9Jj14ISqstSAn6c4weJyYmsnv3buf7uhHiuvMOHqxtl/rcc88BMGfOHObMmeOcPmnSJKf8onv37uzZU1sB+N13G+Y+hIaGsmnTpnOy91xRDrIHE+hjpOiMKhbRge2jA1w49wKiA70JD/DCapPodYJnrhhI91BfFm7KYN5FvZtcV9/Gy9AgFUFWuBtHBFlrFdX67RxbqzmOB+1d/E7vgwPLILyvVjECIOVmSP9Rq8+88jnI3Q++LpBD7P5aax899La2b6s5AmOhPBcsNR3brtrREAVg2O1ajecPpsGCmZpzPPIu7bsdMw8KDkPkAGy//NJx9ioUHoxOCPy8DJRVWfAx6esl4iuUg+zRBPuanA07juWVt1sEGeCCJrqx/WZ8D37j5k5j/l4G9DpBUWXz7a7bytG88rPKPtqKVgdZRZA9joBosFRCdYnWgrk1SKnd1i84UjstI01zmsf8rnaaTgfX/wdsVlh8P+xf2jbbHfgEwWWvatt3NwEx2nPZKQju7v7xmqIsB+JGwKTHoMdErT7ztGfhu/+n3RWY8c/az+N8bamtUJwD/t4GSqrMUKOVh1XUohxkDybIx0BRRQ3pOaVMe201UtIuGuSORghBoLfB7RHkXw/ncdN7G/j87gsY08v17ZltNkmN1aaS9DwRf3vZt9Kc1jnIp/dpEeGCIzD4Bi2Su/J5WP8vLZLZd0bDdXR6uOqdttndUTgc5NKOdpBzNclKn6m104bN0SqGxA5rn4sFhaIL4Qi61VhtXaI5lyvp+t5WJybYx0RxpZmV+08783t8zpOubFqC4rm3nzwXtmVo7bKX7spyi4NcbdE6EHmfJ99ZpyLA3hikNBsi+rZsnaoS+Ox66D1Fa9lcUwZ6L5j5D83J3vNfLYIcktj1mlEE2h3kkqyOtaMsB7qNqj9Np6uVsygUinPCZNAh0LrptVUe2dVQlwseTJCPEZuEH+p0tSuscL/swBM4s4KHO9ibrXUeWr4np9li6K2h2qJl7KoIsgfijCCfvWMkoOluQatEkfGrpiO2mqHnJE3z6ohAO+oQD7u960UyA+w1zzuykoXVDBX5mpRCoVC4BJ0Qzsixq0u8dXZUBNmDcXTT25ZRxO1jEogM9OaKIW5uWeshBLrRQa6osXAwp4x9WSX4mvScLq1ma0YhIxJDm1/5HHBEkFWSngcS3A18QmH1P8E3tGGiXkWhNi0gBj6+DBInwPFfYcAsKM/TnkffU3+dxPFa4lyKG7vzdRS+oeAbBlv/rZV807spUU8IzRlv7AKjPA+QLesYqFAoWoyXQU+1xaaS9M5AOcgeTP/oQLwMOqotNi7qH8WFfSM62qR2I8jH6ExQdDXzVx/htRXpAMyd2JPPNmTw6YaMszrIZquNnJIqogK9+XZHFpcPicXYTEJDlVmLIKsybx6I0Qdu+BQ+mQWfXtv0cgnjQWfQ9MbJ18H0FzRnsTEGXa2VcWtpl7rOhBBwzfvw6XXwppvrCk98BPpeon1HdRPtHCXeVARZoXAptRHktm/rtddeY+7cufj6nlvzsgULFjBt2jRnBz1PoAueybsOyfFBbH1qKodzy0iOa2WmfScl2NdIUQvlJHll1Xy5+QQT+0Twyk8HefGqZKKDGpbDs1htWKVkxb7aBhEjE0Opsdj4dMNxHpmeVK+28+qDuaQdySfMz8QnacfJLKxgXO9w1qTnodcJZqXEndUuFUH2cBLGwgPboeRkw3k2Kyy4FI6vhX6Xac50S+iKzrGDXhfBncu17n3uYucXWpe89e+A0MFdKyAiSeuKl7FeW0ZFkBUKl+JwkK0ukBq+9tpr3HLLLY06yFarFb2+8f/DBQsWMGjQIOUgK1qOn5eBwfHBHW1GuxPkY6SkyoK0t788GwvWHeOtVYf4xw8HAFh14DQ3jqrNtE89YeZf89PYk1WCv5eB7OIqhieEcOBUKUO6BdEn0p/PNmQw/dXVTB0QRWK4H9MHRvPy8gPsyCwGYEh8EOXVJtak5wGQU1LV7D5Umx0OsoogeyxBcdqjMXpP0dpFJzVSkeJ8JW649nAXoT20CxOdEXyC4bPZWhOUta9CVTEIPQQnuG98heI8xKjX/mMt1nNzkMvLy5k9ezaZmZlYrVauu+46srKymDx5MuHh4axatQp/f38eeughfvzxR15++WVWrlzJt99+S2VlJWPHjuXdd99l0aJFbN68mZtvvhkfHx/S0tLYu3cvDz30EGVlZYSHh7NgwQJiYmLYtGkTd955J35+fowfP57vv/+e3bt3M2HCBN58801SUlIAGDduHO+88w6DB7e+cZlykBUeSZCPEatNUlZtIaBOZ7/GcCTbJYT5cjy/gr1ZJfXm/++QGR/vCqYNiGbJDi1a+MJVg+gTGaBl7QbA4vvHMX/1EVan5/LfbSdZujOb9NOlzBmbyB3jEkkI8+OrzSd44ptdmK2SY/kVze6DI0lPVbHopIy+Ryvn1ljJNoV7SBgHSZdC/AhN973gUljxjBa9HnEnxA6trUCiUCg0vn8MTu1q9eqBSHpW27u+OvT/0ckw429nXe+HH34gNjaWpUu12u7FxcV89NFHrFq1ivBwrRlSeXk5gwYN4tlnnwVgwIABPP300wDceuutfPfdd1x77bW89dZbvPTSS4wYMQKz2cy8efNYvHgxERERfPHFFzz55JN8+OGH3HHHHcyfP5+xY8fy2GOPOW256667WLBgAa+99hoHDx6kurq6Tc4xqCoWCg+lpd30pJTszCzimmHx/PLIZEb1CGVPVrFzfl5ZNUXVkjvH9+Dl2UN48apkLhkYTVJUQL2SNv1jAnn1+hQ2/2kqj83ox4GcUmwSpg2MIiFMayRy3YhubHlqKindgjmeX97sPlQ5IshKg9w56X0x/L/d4Of6EoCKJhACbvwMJjwE3UbCDZ/B1Gfh5q+h/2VNR/sVCkWrEQj8vQwYzrH6TnJyMitWrODRRx9lzZo1BAU1lILq9XquueYa5/tVq1YxevRokpOTWblyZb2W0g4OHDjA7t27mTp1KikpKTz//PNkZmZSVFREaWkpY8eOBeCmm25yrnPdddfx3XffYTab+fDDD+u1sW4tKoKs8EgcDnJhuZn4EK3pRmMZtlnFVeSV1TCkm/bDHBgbyMKNJ7DaJALYY48mD4gNBDQn97oR3c469uVDYvnb9/sx6XUM6x5Sb16gt5HEMF82HStsdh9UmTeFoo30uVh7KBSKpmkm0usu+vbty5YtW1i2bBmPP/4406ZNa7CMt7e3U3dcVVXF7373OzZv3ky3bt145plnqKpqKFeUUjJw4EDS0tLqTS8sbPp/19fXl6lTp7J48WK+/PJLNm/e3Ma9UxFkhYcyICYIk17HmyvTKaqooecTy/hsQ0a9ZT5ce5Rxf1sJ4NRpD4wNotJs5YO1Rxj5wgr+9D/tttPAmJYnOcYF+zChTzjjeoc1Ko9ICPMjq7jS6QA3hWoUolAoFIquSlZWFr6+vtxyyy08/PDDbN26lYCAAEpLSxtd3uEMh4eHU1ZWxtdff+2cV3e9pKQkcnNznQ6y2Wxmz549hISEEBAQwPr1WsLuwoUL623/rrvu4oEHHmDkyJGEhra9bKuKICs8ku5hvjwyPYkXlu0j64MNAHy28Tg3jdaS76SULPj1GABhfib6RQcAWjIdwIvLtAhwfnkN4T7CWVO6pbx324gm5yWG+yIlnCiopHekf5PLHcktAyDE1001YxUKhUKh6CB27drFI488gk6nw2g08s4775CWlsaMGTOIiYlh1apV9ZYPDg7m7rvvJjk5mcTEREaOHOmcN2fOHO69915nkt7XX3/NAw88QHFxMRaLhQcffJCBAwfywQcfcPfdd+Pn58ekSZPqyTqGDx9OYGAgd9xxh0v2zy0OshCiH/ARMAx4Ukr5Up15x4BSwApYpJQj7NP/DswAtkspb7NPuxUIlVK+7g47FZ7NneN7sOV4obOToKPucJXZyvYTRWQUVPD3a5KZlRLnjNL2iQrgs7tGY7ZJYoK8mfn6GhICz/1Gydmivg5N8tG8cqeDfLq0CqNOR4hfrTP87Y5sRiSEEBHgdc7jKxQKhULhyUyfPp3p06fXmzZixAjmzZvnfF9WVlZv/vPPP8/zzz/fYFvXXHNNPa1ySkoKq1evbrDcwIED2blzJwB/+9vfGDGiNpiVlZWFzWZrVOrRGtwVQS4AHgCubGL+ZCllnuONECIIGCulHCyE+FQIkQwcAuYAl7jJRoWHo9MJXrl+CD1W+rEnq4TtGYVIKbn3P1tIPZCLQSeYPjC6gTM7tne48/X7t48gK323S+3qFx2An0nP97uzmTogiqyiSq54ay0AH84ZyeD4YA6cKuVATinPzhrYzNYUCoVCoVC0hKVLl/LXv/4Vi8VCQkICCxYsAOCTTz7hySef5JVXXkF3jsmGTeEWB1lKeRo4LYS4tIWr2ACT0Are+gBm4BHgDSmle/oNKzoFviYDj17Sjw/XHmX1wVwyCytZdyiPftEBXD4kluBm5AuTkiJJzXat1N7XZODqYfF8sfkEiWF+fLn5BFVmG8G+Rm7/cCPLfj+Bv/+gSTxmJse4dGyFQqFQKM5Xrr/+eq6//voG02+77TZuu+02l44lpGx755QmNy7EM0DZGRKLo0AhIIF3pZTz7dP/CNwE/Ay8BMyXUl7ezPbnAnMBIiIihn/55Zfu2A2FB7Ar18LLW6q5rKeR746YeXiEN4PCW5b8VlZWhr9/01rh1nCy1MaT67RW2H1DdFzdx0SQSfBMWiUCqLLCLf1NXJxwbtpnRetxx/es6Pyo40LhoCsdC0FBQfTq1avZRlqKWqSUHD58mOLi4nrTJ0+evMUh961LRzjIsVLKLCFEJPATME9KufqM9d4H3gaGA9OAnVLKhqKVOiQlJckDBw64ehcUHsKJggom/GMVAd4Gqs02dvx5Gj6mljnIqampTJo0yeU2rT+ST0yQt1OTDLAmPZdvtp4kOT6IOWMT1cmrHXHX96zo3KjjQuGgKx0LR48eJSAggLCwMPU/0wKklOTn51NaWkqPHj3qzRNCNOogu0xiIYS4D7jb/namlDKrCSOz7M+nhRDfAKMAp4MshBhqf3kQeF1KOVEIsVAI0UdKme4qexWdi7hgH3yMekqrLFzQM7TFzrE7uaBnwwYSE/pEMKFPRAdYo1AoFIrzhfj4eDIzM8nNze1oUzoN3t7exMfHt3h5lznIUsq30aK+TSKE8AN0UspS++tpwLNnLPYcmmzCCDi8IBvg6ypbFZ0PnU7wzi3D2H+qlMlJkR1tjkKhUCgUHYbRaGwQCVW4FneVeYsGNgOBgE0I8SAwAAgHvrHfDjAAn0kpf6iz3pXAJkeUWQiRJoTYhSax2OEOWxWdh0lJkUxSzrFCoVAoFAo3464qFqeAxuLYJcCQs6z3P+B/dd4/DDzscgMVCoVCoVAoFIomUK2mFQqFQqFQKBSKOri1ikV7IoQoBdqjjEUQUNzsUl1r7M4+bjiQ1+xS7hn7XFHHV+tR37Nnj91R47bmuHAV59tn3ZFjt2Rcdx0LnrzPXW1sd4ybJKUMaDBVStklHsDmdhpnfgfuY4eM3dnHbc2x0dn3uTONrb7n82PsDhy3Xf4bPGyf1fHVjseCJ+9zVxvbHeM2dVwoicW58+15OPb5Nm5Hjq32+fwYW+3z+cH5+Fmrfe7643bk2O02bleSWGyWjRR6VijUsXF+oL5nRWOo40LhQB0LisZo6rjoShHk+R1tgMJjUcfG+YH6nhWNoY4LhQN1LCgao9HjostEkBUKhUKhUCgUClfQlSLICoVCoVAoFApFm1EOskKhUCgUCoVCUYdO5yALIco62gaFZyGEsAohttd5JJ5l2UlCiO/azzqFKxBCSCHEv+u8NwghctV3qXAghLjKfpz062hbFO2POkcoXE2nc5AVikaolFKm1Hkc62iDFC6nHBgkhPCxv58KnDyXDQghDC63SuFJ3AisBW44l5WEEHr3mKNoZ9p8jlAo6tIpHWQhhL8Q4mchxFYhxC4hxCz79EQhxD4hxHtCiD1CiOV1fiyK8wghhF4I8U8hxCYhxE4hxD11ZgcKIb4RQuwVQvxLCNEpfwfnId8Dl9pf3wh87pghhBglhPhVCLHN/pxknz5HCPGVEOJbYHn7m6xoD4QQ/sA44E7sDrL9btHqxn7rQogyIcSzQogNwJiOs1zhYlpzjlgjhEips9w6IcTgdrVa4ZF0VsegCrhKSjkMmAy8LIQQ9nl9gLellAOBIuCaDrJR0X741JFXfGOfdidQLKUcCYwE7hZC9LDPGwX8AUgGegFXt7vFitawELhBCOENDAY21Jm3H5gopRwKPA28WGfeGOB2KeVF7Wapor25EvhBSnkQKBBCDLNPb+q37gfsllKOllKubXdrFe6iNeeI94E5AEKIvoCXlHJnu1ms8Fg66y1HAbwohJgI2IA4IMo+76iUcrv99RYgsf3NU7QzlVLKlDOmTQMGCyGutb8PQrt4qgE2SimPAAghPgfGA1+3l7GK1iGl3GnXl98ILDtjdhDwsRCiDyABY515P0kpC9rFSEVHcSPwmv31Qvv7pTT9W7cCizrAToUbaeU54ivgKSHEI8BvgAXtYqzC4+msDvLNQAQwXEppFkIcA7zt86rrLGcFlMTi/EQA86SUP9abKMQktJNjXVQx8M7DEuAlYBIQVmf6c8AqKeVV9j/I1DrzytvJNkUHIIQIAy5C059KQI/2m15G07/1Kimltf2sVLQj53SOkFJWCCF+AmYBswHVaU8BdF6JRRBw2u4cTwYSOtoghcfxI/BbIYQRtFtnQgg/+7xRQogedj3i9WiJPYrOwYfAs1LKXWdMD6I2IWdOu1qk6GiuBT6RUiZIKROllN2Ao2jRYvVbP/9ozTnifeANYJO626Rw0KkcZHsWejXwKTBCCLEZLZq8v0MNU3gi7wN7ga1CiN3Au9TeMUkD/gbsRvsj/abRLSg8DillppTy9UZm/QP4qxBiHVoEUXH+cCMNf8OLgJtQv/XzjtacI6SUW4AS4KN2MFHRSehUraaFEEOA96SUozraFoVCoVB4LnY51cNSyss62haFZyOEiEWTXPSTUto62ByFh9BpIshCiHvRSrb8qaNtUSgUCoVC0fkRQtyGVu3iSeUcK+rSqSLICoVCoVAoFAqFu+k0EWSFQqFQKBQKhaI98FgHWQjRTQixyt4Zb48Q4vf26aFCiJ+EEOn25xD79H5CiDQhRLUQ4uEztvV7IcRu+3Ye7Ij9USgUCoVCoVB0DjzWQQYswB+klP2BC4D7hBADgMeAn6WUfYCf7e8BCoAH0OofOhFCDALuRuuoNAS4zF4oXKFQKBQKhUKhaIDHOshSymwp5Vb761JgH1rHvFnAx/bFPkZrMYqU8rSUchNgPmNT/YH1UsoKKaUF+AW4qh12QaFQKBQKhULRCfFYB7ku9q43Q9EyTaOklNmgOdFAZDOr7wYmCiHChBC+wEygm/usVSgUCoVCoVB0Zjy+1bQQwh+t6PuDUsoSIcQ5rS+l3CeE+DvwE1AG7ECTbygUCoVCoVAoFA3w6AiyvU3wIuBTKeV/7ZNzhBAx9vkxwOnmtiOl/EBKOUxKORFNq5zuLpsVCoVCoVAoFJ0bj3WQhRYq/gDYJ6V8pc6sJcDt9te3A4tbsK1I+3N34Gq0hiMKhUKhUCgUCkUDPLZRiBBiPLAG2AU4uts8gaZD/hLoDmQA10kpC4QQ0cBmINC+fBn/v737Ba0yCuM4/v1xDepQg0EQi3WiQV0YaBiI+KebJ1hsQ9YMRhHtLsmCBtEuCMMgNnGgWAyypGUgQ3SC4GO4bzhBBhO8977z+6nnPIfntB+Hc94XprtrGS+Bgwwf8N2oqpWRbkaSJEm9MbEBWZIkSRqHib1iIUmSJI2DAVmSJElqGJAlSZKkhgFZkiRJahiQJUmSpIYBWZJ2iCQLSfb+Rd18ksP/oidJ6iMDsiTtHAvAtgJykgEwDxiQJamza9wNSJK2L8kUw58mHQEGwBOGIfdFkvWqmktyH5gB9gBPq+pWV7sGPADOA0vAaeBRkk1gtqo2R70fSZokBmRJ6qcLwKequgyQ5ABwFZirqvVuzs3uT6MDYCXJiap62439qKozXe01YLGqXo94D5I0kbxiIUn99A44l+ROkrNVtfGHOVeSvAFWgWPAdDP2eBRNSlIfeYIsST1UVR+SnAIuAbeTPG/HkxwFFoGZqvqSZBnY3Uz5NrJmJalnPEGWpB7qvjrxvaoeAveAk8BXYF83ZT/DELyR5BBwcYvl2jpJ+u95gixJ/XQcuJvkF/ATuA7MAs+SfO4e6a0C74GPwKst1loGlnykJ0lDqapx9yBJkiRNDK9YSJIkSQ0DsiRJktQwIEuSJEkNA7IkSZLUMCBLkiRJDQOyJEmS1DAgS5IkSY3fBnbYhKXPNCUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gekko.plot_stats(jdf, profits, figsize=(10,10));"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}