Trade call Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trade call Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Series</th>\n",
       "      <th>Date</th>\n",
       "      <th>Prev Close</th>\n",
       "      <th>Open Price</th>\n",
       "      <th>High Price</th>\n",
       "      <th>Low Price</th>\n",
       "      <th>Last Price</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Average Price</th>\n",
       "      <th>Total Traded Quantity</th>\n",
       "      <th>Turnover</th>\n",
       "      <th>No. of Trades</th>\n",
       "      <th>Deliverable Qty</th>\n",
       "      <th>% Dly Qt to Traded Qty</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>15-May-2017</td>\n",
       "      <td>274.95</td>\n",
       "      <td>275.9</td>\n",
       "      <td>278.9</td>\n",
       "      <td>275.50</td>\n",
       "      <td>278.5</td>\n",
       "      <td>277.95</td>\n",
       "      <td>277.78</td>\n",
       "      <td>5462855</td>\n",
       "      <td>1.517477e+09</td>\n",
       "      <td>52501</td>\n",
       "      <td>4128324</td>\n",
       "      <td>75.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>16-May-2017</td>\n",
       "      <td>277.95</td>\n",
       "      <td>278.5</td>\n",
       "      <td>284.3</td>\n",
       "      <td>278.00</td>\n",
       "      <td>283.0</td>\n",
       "      <td>283.45</td>\n",
       "      <td>280.93</td>\n",
       "      <td>11204308</td>\n",
       "      <td>3.147583e+09</td>\n",
       "      <td>98347</td>\n",
       "      <td>8307567</td>\n",
       "      <td>74.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>17-May-2017</td>\n",
       "      <td>283.45</td>\n",
       "      <td>284.1</td>\n",
       "      <td>284.4</td>\n",
       "      <td>279.25</td>\n",
       "      <td>281.5</td>\n",
       "      <td>281.65</td>\n",
       "      <td>281.56</td>\n",
       "      <td>8297700</td>\n",
       "      <td>2.336261e+09</td>\n",
       "      <td>99107</td>\n",
       "      <td>5924804</td>\n",
       "      <td>71.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Symbol Series         Date  Prev Close  Open Price  High Price  Low Price  \\\n",
       "0    ITC     EQ  15-May-2017      274.95       275.9       278.9     275.50   \n",
       "1    ITC     EQ  16-May-2017      277.95       278.5       284.3     278.00   \n",
       "2    ITC     EQ  17-May-2017      283.45       284.1       284.4     279.25   \n",
       "\n",
       "   Last Price  Close Price  Average Price  Total Traded Quantity  \\\n",
       "0       278.5       277.95         277.78                5462855   \n",
       "1       283.0       283.45         280.93               11204308   \n",
       "2       281.5       281.65         281.56                8297700   \n",
       "\n",
       "       Turnover  No. of Trades  Deliverable Qty  % Dly Qt to Traded Qty  \n",
       "0  1.517477e+09          52501          4128324                   75.57  \n",
       "1  3.147583e+09          98347          8307567                   74.15  \n",
       "2  2.336261e+09          99107          5924804                   71.40  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_df = pd.read_csv(\"ITC.csv\")\n",
    "stock_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>Symbol</th>\n",
       "      <th>Series</th>\n",
       "      <th>Date</th>\n",
       "      <th>Prev Close</th>\n",
       "      <th>Open Price</th>\n",
       "      <th>High Price</th>\n",
       "      <th>Low Price</th>\n",
       "      <th>Last Price</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Average Price</th>\n",
       "      <th>Total Traded Quantity</th>\n",
       "      <th>Turnover</th>\n",
       "      <th>No. of Trades</th>\n",
       "      <th>Deliverable Qty</th>\n",
       "      <th>% Dly Qt to Traded Qty</th>\n",
       "      <th>botlinger_avg</th>\n",
       "      <th>botlinger_upper</th>\n",
       "      <th>botlinger_lower</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>493</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>2019-05-09</td>\n",
       "      <td>300.65</td>\n",
       "      <td>299.4</td>\n",
       "      <td>301.30</td>\n",
       "      <td>296.35</td>\n",
       "      <td>299.85</td>\n",
       "      <td>299.85</td>\n",
       "      <td>299.17</td>\n",
       "      <td>10223616</td>\n",
       "      <td>3.058551e+09</td>\n",
       "      <td>129794</td>\n",
       "      <td>5965688</td>\n",
       "      <td>58.35</td>\n",
       "      <td>303.710714</td>\n",
       "      <td>308.374681</td>\n",
       "      <td>299.046748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>494</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>2019-05-10</td>\n",
       "      <td>299.85</td>\n",
       "      <td>300.0</td>\n",
       "      <td>300.45</td>\n",
       "      <td>296.90</td>\n",
       "      <td>297.15</td>\n",
       "      <td>297.75</td>\n",
       "      <td>298.68</td>\n",
       "      <td>6904657</td>\n",
       "      <td>2.062297e+09</td>\n",
       "      <td>132469</td>\n",
       "      <td>4024203</td>\n",
       "      <td>58.28</td>\n",
       "      <td>303.035714</td>\n",
       "      <td>308.229561</td>\n",
       "      <td>297.841868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>495</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>2019-05-13</td>\n",
       "      <td>297.75</td>\n",
       "      <td>295.1</td>\n",
       "      <td>303.50</td>\n",
       "      <td>287.70</td>\n",
       "      <td>288.80</td>\n",
       "      <td>289.30</td>\n",
       "      <td>296.21</td>\n",
       "      <td>35880558</td>\n",
       "      <td>1.062813e+10</td>\n",
       "      <td>226154</td>\n",
       "      <td>14476904</td>\n",
       "      <td>40.35</td>\n",
       "      <td>301.957143</td>\n",
       "      <td>310.870301</td>\n",
       "      <td>293.043984</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Symbol Series       Date  Prev Close  Open Price  High Price  Low Price  \\\n",
       "493    ITC     EQ 2019-05-09      300.65       299.4      301.30     296.35   \n",
       "494    ITC     EQ 2019-05-10      299.85       300.0      300.45     296.90   \n",
       "495    ITC     EQ 2019-05-13      297.75       295.1      303.50     287.70   \n",
       "\n",
       "     Last Price  Close Price  Average Price  Total Traded Quantity  \\\n",
       "493      299.85       299.85         299.17               10223616   \n",
       "494      297.15       297.75         298.68                6904657   \n",
       "495      288.80       289.30         296.21               35880558   \n",
       "\n",
       "         Turnover  No. of Trades  Deliverable Qty  % Dly Qt to Traded Qty  \\\n",
       "493  3.058551e+09         129794          5965688                   58.35   \n",
       "494  2.062297e+09         132469          4024203                   58.28   \n",
       "495  1.062813e+10         226154         14476904                   40.35   \n",
       "\n",
       "     botlinger_avg  botlinger_upper  botlinger_lower  \n",
       "493     303.710714       308.374681       299.046748  \n",
       "494     303.035714       308.229561       297.841868  \n",
       "495     301.957143       310.870301       293.043984  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_df['Date'] = pd.to_datetime(stock_df['Date'])\n",
    "stock_df[\"botlinger_avg\"] = stock_df[\"Close Price\"].rolling(window=14).mean()\n",
    "stock_df[\"botlinger_upper\"] = stock_df[\"Close Price\"].rolling(window=14).mean() + 2*stock_df[\"Close Price\"].rolling(window=14).std()\n",
    "stock_df[\"botlinger_lower\"] = stock_df[\"Close Price\"].rolling(window=14).mean() - 2*stock_df[\"Close Price\"].rolling(window=14).std()\n",
    "\n",
    "stock_df.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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wGCo9dBEREREREZEbjZJHcmM5sRtih8DpfZbfe86wJI4ucKgJ7UZYfq5E7XBL8ikrFZxrX328IiIiIiIiIjc4JY/kxmA2W5akffuSJUHU8x3wCIQG7Sv3OheKZp/8TckjEREREREREcBY1QGIXFZOBix9DL76J9S/DYb+DLc8DP4dKn9p2V93XBMREREREZEbyubNm7ntttuIiopi0KBB9OvXj8TExDLbfPbZZ+Tn57N582ZGjRoFwPDhw60ea1RU1EWx5ebmctddd1n9uldCySO5vqXshDl3wm/L4K6XYdDn1p0R5FwL3P1hV6xltpOIiIiIiIjcUNq2bUtMTAzz589n+PDhTJ48uczzZ8+eTVFR0UWPzZgxw5oh3nC0bE2uX6f3wwd3g5MHDP4K/Ct5iVpp7ngevngG9nwFYT2uzTVFRERERERuNjsWwi/zK7fPloOgRf9yn56RkYGvry8A8fHxjBs3DpPJhL29PePGjWP9+vWkpqYyatQoBg8eXNyuffv2rF+/nqioKEJDQ9m/fz+ZmZlMnz4dX19fZs6cyapVq/Dw8CA7O5uRI0cSHh5OdHQ06enpAIwdO5aQkBA6depEYGAggYGBREdHlyvuqKgoAgICSE5Oxmw2M3XqVJKSknjvvfcwGo2kpqbSt29fBg4cyN69e3n99dcBcHNzY8KECcTHx/Pmm29ia2tLZGQkDzzwQLlfs5IoeSTXr1/mQ1EBPP4D1PS9dtdt1g/WT4fVr0NINzCart21RURERERE5Kps2rSJqKgo8vLy2Lt3L7NnzwYsyZzx48cTFhbGqlWreOONN3j77beZNWsWU6dOZceOHSX216xZM6Kjo5k6dSpff/01d9xxB+vWrSM2Npb8/Hx69LBMOnjvvfdo27YtAwYM4ODBg4wePZqFCxeSkpLC559/jru7e4Wexy233MJrr73GggULmD17NnfffTcnT55k+fLlFBUV0aNHD+69915efvllJkyYQHBwMEuWLOGDDz6gXbt25ObmsmTJkqt7Mf+g5JFcn4qKYNcSCO5ybRNHACYb6BQNSwbDr4srlNUWERERERGRP7ToXyX/nmrbti1Tp04FICkpiX79+rF27VpOnTpFWFgYAK1ateKtt94qV3/h4ZbauHXr1uX06dMkJibStGlTTCYTJpOJJk2aALBv3z42bdrEypUrAcusJwB3d/cSE0f29vbk5+cX/56VlYWDw5+7ibdt2xawJJFWr14NQMuWLbGzswOgYcOGHD58mMTERF599VUA8vPzCQgIACi+rQxKHsn16dDPkHEM7n6taq4f1hO8m8OaCdCkN9jYVU0cIiIiIiIicsW8vLyK79euXZs9e/YQGhrK1q1b8ff3B8BgMFxS86gswcHBxMTEUFRUREFBAfHxlg2XAgMD6dmzJz169CAtLa141o/RWHK56caNG/Pdd98RGhoKwNq1a2natGnx8d27d1O3bl22b99OcHAwAAkJCRQWFpKXl8eBAwdo0KABAQEBTJo0CR8fH7Zt20ZqamqZ170SSh7J9em3ZWDnbFk2VhWMRuj8b5jfG7Z/DK2fqJo4REREREREpEIuLFszGo1kZWXx0ksv4eDgwOuvv864ceMwm82YTCYmTJgAQEREBE8++STPPPNMufoPCQnhzjvvJDIyEnd3d2xtbbGxsWHo0KFER0ezePFiMjMzL7tj2xNPPMG///1vevXqhZ2dHW5ubowbN674+LJly5g3bx6Ojo5MnjyZffv2UVBQwBNPPMHZs2cZNmwYHh4evPLKK7z44osUFhYCMH78eE6dOnWFr17JlDyS69PBn6FBO7BzqroYgjpDgw7w02RoMQDsalRdLCIiIiIiInJZbdq0YePGjSUeCw8PZ8GCBZc8PmnSpOL7F5aKrV+/HoCYmJjiY/37W5bgpaWl4erqSmxsLHl5eXTv3h1vb2/c3d159913L+n/Ql9/5+zszJQpU0p9Ls8++yxBQUEXPRYUFFS8JO+CJk2aXBQnWJastWnTptS+K6ry5jCJVJas03B6H9S/rWrjMBgss4+yTsHm2VUbi4iIiIiIiFwX3N3d2b17N71792bAgAH06dMHHx+fqg7LqjTzSK4LgwcPxt3dnWnTpsHhP7LEDdpVbVAA9dtYklgJX8Ltz1Z1NCIiIiIiIlLFjEYjEydOtOo1/j6TCCyzqipzNlFFKHkk14Xvv/8eV1dXyy+HNoLJHnxaVm1QF9RpYtl1zWy2zEYSERERERERqUassmytsLCQ0aNH069fPwYOHMjhw4eLj3355Zf07du3+PfFixfTq1cvIiMj+fHHH60RjlznsrOzSUlJITEx0bJN4eEN4BcBNvZVHZqFZzDknoOs1KqOREREREREROSas0ry6EISaNGiRfzf//1f8XSuhIQEYmNjMZvNAKSmphITE8OiRYuYO3cuU6ZMIS8vzxohyXXs0KFDABQUFHAwYTuk/Hp9LFm7wNOyJSJpB6o2DhEREREREZEqYJXkUZcuXYq3lzt+/DheXl6kp6fz5ptvMmbMmOLzfv31V1q2bImdnR0uLi7Ur1+fPXv2WCMkuY4lJycX38+KWwTmQgjrUYUR/Y3XH8mj0/urNg4RERERERGRKmC1mkc2Nja8+OKLfP/990yfPp3o6GjGjBmDvf2fS5EyMzNxcXEp/r1GjRpkZmaW2W9ubi4JCQnWCluusZycnIu2UXRK+pZct3okpdvC2etknIsKCTHakb5/M6ecWld1NDeVnJwc/T1Xc3oPVD8a8+pLY1+9afyrN41/9ZKfn092djZms5ns7Oxrfv2tW7fywgsvEBgYWBzPq6++SkBAQKltYmNjuf/++9mxYwexsbFMmjSJZ599lilTplg11scee4yxY8eWGZu15OfnV+jv0qoFsydNmsRzzz1H586d8fLy4pVXXiE3N5cDBw4wfvx42rZtS1ZWVvH5WVlZFyWTSmJvb09YWJg1w5ZrKCEhgezsbOzs7GjoXZNg03GMtzxPWHh4udovXbqUOnXq0KFDB+sGuiYIT/NZPPXeq1QJCQn6e67m9B6ofjTm1ZfGvnrT+FdvGv/qJSEhAUdHR7Kzs3F0dLzm17e3t+e2225j6tSpAPz8889Mnz6d2bNnl9rmo48+IjIyEnt7e0wmE46OjsyaNcvqsZpMJuzt7avkdbK1tb3k77KsZJJVkkfLly/n5MmTPPXUUzg6OuLl5cXKlSuxt7fn6NGjPPvss0RHR5Oamsq0adPIzc0lLy+PxMREGjVqZI2Q5DqWnJyMv78/g1raYTQchvAHyt322WefpaioiAMHDlw0q63SeQbB6X3W619EREREROQmsyJxBcv2L6vUPh9s+CA9g3qW+/yMjAx8fX0BiI+PZ9y4ccVJm3HjxrF+/XpSU1MZNWoUgwcPLm7Xvn171q9fT1RUFKGhoezfv5/MzEymT5+Or68vM2fOZNWqVXh4eJCdnc3IkSMJDw8nOjqa9PR0AMaOHUtISAidOnUiMDCQwMBAoqOjy4w3Pz+fMWPGcOTIEQoLCxkyZAgBAQFMmzaN2bNn89VXXzFnzhxWrFhBXFwcX3zxBS+88MJVX/dyrJI86tq1K6NHj2bgwIEUFBRcslztglq1ahEVFcWAAQMwm82MGjXKugkAuS4lJycTEBBAC7+z5BWCXe3yfSthNps5deoUOTk5zJ07l6efftp6QXoGw77voLAATFadsCciIiIiIiJXYdOmTURFRZGXl8fevXuLZx2NHTuW8ePHExYWxqpVq3jjjTd4++23mTVrFlOnTmXHjh0l9tesWTOio6OZOnUqX3/9NXfccQfr1q0jNjaW/Px8evSw1Ox97733aNu2LQMGDODgwYOMHj2ahQsXkpKSwueff467u/tlY//ss89wd3fnv//9L5mZmfTq1YtFixZx/PhxcnNzWbduHQaDgdOnT7N69WruvvvuSrnu5VjlX8FOTk5Mnz69xGN+fn4sXry4+PfIyEgiIyOtEYbcIJKTk2nTpg2Bbr+QfKIQzzPpbN68mbi4OP7zn/+U2i4rK4ucnBwAxo8fz5NPPomNjZUSO55BUJQPGUfB3d861xAREREREbmJ9AzqWaFZQpWlbdu2xcvWkpKS6NevH2vXruXUqVPFS7VatWrFW2+9Va7+wv8oq1K3bl1Onz5NYmIiTZs2xWQyYTKZaNKkCQD79u1j06ZNrFy5ErDMegJwd3cvdwInMTGRdu0su487OzsTFBTEkSNH6NChA5s3byYlJYUePXqwYcMG4uLiGDVqFDExMVd93cuxym5rIuV1/vx50tPTCQgIoLZtFonpRSQmJjJ37lxeffVVTp8+XWrb1NRUAO666y6OHz9u3SJ8NWpZbn9Ps941REREREREpFJ5eXkV369du3bxDu9bt27F398fAIPBQFFRUbn7DA4OZteuXRQVFZGXl0d8fDwAgYGBPPLII8TExDBt2rTiGUlGY/lTL0FBQcTFxQGWTcb27duHn58fXbp04f333yckJIQOHTqwYMECGjRogK2tbaVc93K0/kaq1NGjRwEI8PfHZe9pEtPNZCQnk5iYiNls5ttvv2XQoEEltr2QPOrWrRurV68mLi6Opk2bWidQRw/L7e/p1ulfREREREREKsWFZWtGo5GsrCxeeuklHBwceP311xk3bhxmsxmTycSECRMAiIiI4Mknn+SZZ54pV/8hISHceeedREZG4u7ujq2tLTY2NgwdOpTo6GgWL15MZmYmw4cPv2xfI0eOxM7ODoA2bdowatQoXn75Zfr3709ubi7Dhw/H09MTDw8PkpOTefzxxwkNDeXYsWM8/vjjAFd03YpS8kiq1IXkUbCvJ6bfskg8U8T5pCSSkpIA+Oabby6bPGrXrh0uLi7ExcUxZMgQ6wTq9EfyKPuMdfoXERERERGRq9amTRs2btxY4rHw8HAWLFhwyeOTJk0qvt+2bVsA1q9fD0BMTEzxsf79+wOQlpaGq6srsbGx5OXl0b17d7y9vXF3d+fdd9+9pP8Lff3dX/suLZ4LDAYDP//8c/Hvf71f0eteCSWPpEoVzzxyMwOQVuTCwS1byMzMxM7Ojm+//ZbCwkJMJtMlbS8kj+rUqcOtt95aPLXPKopnHil5JCIiIiIiUp25u7uze/duevfujcFgoE+fPvj4+FR1WFal5JFUqWPHjuHq6oprgaWWUIFrfX788UcA+vXrxyeffMLgwYMZOXIkrVq1uqjtheRRrVq1iIiI4J133iEvL694yl+lcnQDDKp5JCIiIiIiUs0ZjUYmTpxY1WFcUyqYLVXq6NGjBAQEYEg/CIBdnYbFleGfffZZhg8fzvLly2ndujURERHMnTuXgoICwJI8sre3x9nZmYiICHJzc/ntt9+sE6jRZEkgadmaiIiIiIhImcxmc1WHIGW4kvFR8kiq1IXkEWeSwcWHegENi481atSId955h2PHjjFjxgxycnJ4/PHHi7dTPHXqFLVq1cJgMBAREQFg/aVrWrYmIiIiIiJSKgcHB9LS0pRAuk6ZzWbS0tJwcHCoUDstW5MqYzabOX78OPfffz+c+Q3c/QlwCwDAx8cHR0dHAGrWrMkzzzzD008/TZs2bVixYgUvvvgiqamp1KpVC7Bsiejm5kZcXBxPPPGEdQJ28tDMIxERERERkTL4+flx9OhRjh8/jq2tbVWHIyVwcHDAz8+vQm2UPJIqc/LkSXJycgjwbwAnF0PzvgQ6BQIQFBR0yfkGg4F7772X8ePHk56eflHy6MLsI6vPPDqfYr3+RUREREREbnC2trYEBASQkJBAWFhYVYcjlUTL1qTKJCcnA9DExwnyzoN3C8sSNiwziUpy7733UlRUxKpVqy5KHgFERESwa9cucnJyrBOwkwdkp1unbxEREREREZHrlJJH1UlRIRQVVXUUxS4kj4JrZFoe8GmBn58fdevWvWRntQtat26Nm5sb3333XYnJo/z8fHbt2mWdgJ08VfNIREREREREqh0tW6suDm2EZU+Ciw8MXAIOrlUdUXHyqG7RCTDZQ61QbEw2HDx4sNS1sTY2NnTt2pXPP/+crKysS5JHAN9s2Mmewtr0jaiHnU0l5kcd3SE/C/JzwLZixcVEREREREREblSaeXSzK3uZsTQAACAASURBVMyH1a/DvG5gNsOxOFjwEBQWVHVkJCcn4+npiW3qb1C3CZgsCSN7e3uMxtLfms8++yzp6ZblYxeSR2mZufxwpBC/x2fyUYo3Ly/fzcIthys3YCcPy62KZouIiIiIiEg1ouTRzexMEnx4L6z9LzTvD09vhH9MhiObIWVHVUdHcnIy9fx8IWUneDcvd7s2bdrwwAMPAJbk0Xe/naDtxB947asEajg64vDbCm6p78bsnxLJK6jEZXqOfySPtHRNREREREREqhElj25W+Tkwtyuk7YeHPoIH3gV7Fwi9z3L80PqqjQ9ISkoiIsgLcjPAu0WF2k6cOJFbb72Vli1bMm3Vfup5OPHtP2+nT80kDqycy5Pt63P8XA7LfzlWeQFr5pGIiIiIiIhUQ0oe3awSV0NWKvSeC016/fm4Sx3wDIZDG6ouNqCgoIAjR47Q2s/O8oBPxZJHoaGhxMXFccrsQkJKBo93CCS0risREREUFhbimnWEpr41mbZqHzn5hZUTtGYeiYiIiIiISDWk5NHNKmEFOLhBYMdLjzVoZymgXVRJSZUrcOTIEQoLC2nskQ8mO6gVdkX9zNtwEFcHGx5o6QP8WTR727ZtRHcP4/i5HOb+nFw5QTt5Wm4180hERERERESqESWPbkYFebD3GwjpVlyE+iIN2kPuOTgVf+1j+8OFndb87c5CncZgY1fhPk6cy+G73Sfo26oeTnaWjQN9fHyoW7cucXFxtA305J7GdXj3xwNk5VZCgXAnzTwSERERERGR6kfJo5vR4Y2Qcw7C7y/5eIN2ltsqXLp2IXlUq/B4hYpl/9Wnmw9RaDYT1da/+DGDwUBERARxcXEADGkfQFZeIT/uPXXVMWNjDzaOkJ1+9X2JiIiIiIiI3CCUPLoZeQbD7f+CoLtKPu5WH2rWq9Ki2cnJyQR5mLAtyKpwsWyA3IJCPt1ymLtCalPf0+miYxERESQkJJCZmUkrfw+8nO35+teUygnc3gXyMiunLxEREREREZEbQLmSR0lJSdaOQypTTV/o/O+yl4I1aG+ZeWQ2X7u4/iI5OZmuTWpbfqlgsWyAJXFHOZ2ZxyPt/S851qJFC8xmMwkJCZiMBv7RpC4/7j3F73mVsHTN3gVylTwSERERERGR6qNcyaPo6GhrxyHXWoN2lt3Y0g5UyeWTk5PpEOSM2WgDtcMr1DYzt4Bpq/bROsCDDsFelxx3cXEBIDs7G4DuzbzJyS9izd7Uqw/c3gVyz199PyIiIiIiIiI3CJvynOTk5MSECRMICAjAaLTkm/r27WvVwMTKGrS33B5aD14Nr/nlk5OTaXa7Mzk1g3C0sa9Q2/fXJnE6M48PBodhMBguOW5raykSnp+fD0BEA3ccbU1sPXiGbk29ry5wJY9ERERERESkminXzKOWLVvi6upKWloaqamppKZWwgwOqVqeQVCjNiT+CIX51/TShYWFnDx5kkCHDHLcQyvU9lRGDu+vS6J7M29a1HMr8Zy/J49sTEaa+tZkx5GzVxc4KHkkIiIiIiIi1U65Zh4NHz6cDRs2cPToUZo1a0ZAQIC14xJrMxgg4HbYvRT2fA3ezcCvNfhFQL024FbPapc+d+4c9V3ByZDDOfeQCrWd9sN+8gqKeL5r6e3+njwCaF6vJh9vPEReQRF2NldRJ97eBfKUPBIREZEbWFER5GaAY8lfxImIiPxduZJHU6ZM4cSJEyQmJmJra8ucOXOYMmWKtWMTa/vHZAjqDKkJcGw7bJsHm2dZjrV+Cu59AwpyYNtH4N0c/DtUymXT09O51ccEUO6ZRxk5+Uz4OoFFW4/wSDt//L1qlHruheRRXl5e8WPN67mRty6ZvSfO09Sv5pUHr5lHIiIicqNb/Rr8PBUc3MDOGUy2YLL748fGcmvjYNnBt064pdxB7bCqjlpERKpQuZJH27ZtY8GCBURFRfHggw+ycOFCa8cl10INL2g58M/fC/Ph5G/wSwxsmW2ph5R5CrJOWT5YPL6qUj44pKenc4u3iSJM5LoFXfb8HxJOMmbZLlLP5zL0ziD+2aXsGk0lzTy6sMRtx9GzV5c8snNW8khERERuXEVF8OtiqNsM6rWG/BwozPvjJ//P+3lZsGsJxGWAwWj5HOh7a1VHLyIiVaRcyaPCwkJyc3MxGAwUFhYWF80u6/yxY8eSnJyMyWRi4sSJZGVlMW7cOEwmE3Z2dkyaNAkvLy8WL17MokWLsLGxYdiwYXTq1KlSnphcAZMt+LSwzDJy94e9Ky21kZo8BN88B3PvAVfvP76NsrfMwgnpBs36goNruS+Tnp7Ord4mfndugNlUerHsvIIiXlz6K8t+OUZIHRfefziCZn6Xn15dUvLI180RL2c7dh45S1TbBuWO9RL2LpYPVAW5ltdAREREpCpkp4PZDE4eFWt3fDtkHIO7XoYW/cs+12yG9IPw4T3wzfPw2Cq4zL8DRETk5lSu5NHgwYPp1asXZ86coU+fPgwZMqTM83/88UcAFi1axObNm5k4cSLnz5/n5ZdfJiwsjEWLFvH+++/z+OOPExMTw9KlS8nNzWXAgAG0b98eOzu7q39mcuUMBmg3wvJzgXsD2DTL8i1UYT4U5kLGcUtSacscGPR5uesknUlLo5O3kXyv8DLP+3rXcZb9coxhHYMY1aVRuWsVXXj//DV5ZDAYaB3gwXe7TzC8U3CZy97KZP9Hkiz3vJJHIiIiUiWOHdhNndge2OScAec6lpnhtcPBu4WlpqWrT+mN478Aow2E3Hv5CxkM4BEAXV6F5UNh56fQclDlPREREblhlCt5dOutt/Lpp59y6NAh/Pz88PAo+xuOLl260LFjRwCOHz+Ol5cXr776KrVr1wYsM5Ps7e359ddfadmyJXZ2dtjZ2VG/fn327NlDs2bNSu07NzeXhISEcj49qTx2EDrykkedTmzBb8NoCt/vSuI/PrPMXrqMQwnbqF3DyAFbb3Jyckodz/nrUqhdw4b76heRuH9vuSO9sBvg4cOHL+o7spEt6/YVMWTuBqZ088HhCgpn10w7jw9wIH4H+c6+FW4vFytr/KV60Hug+tGYV18a+8qxfft2fv/scYa0sGVJWjB3+4dgn56M/aGNGAtzMWPgvN+dZNVtS6F9TQptnbH9PRXbzKPYZR7BOWUT2bUjOHLwBHCifBe1a0YDz6bYfTuWRGMIRXbOFY5b41+9afyrJ437zaVcyaPRo0eTl5dHp06dcHd3v2zyCMDGxoYXX3yR77//nrfffrs4cbR9+3bmz5/PggULWLduHS4uLsVtatSoQWZmZpn92tvbExamgn2XU1RURIsWLQgJCeG9997D09PTOhcKCwNvL0yLBhBmcwRCu1+2yXa785AP9Vp2IcngUOJ4nsrI4ZeUJIZ1DKJxePmKal9Qq1YtALy8vC7qOwx4x7UuQ+ZtJSYhn7f6NMdgMFSobzgAWyDYrzZ46314tRISEvT3XM3pPVD9aMyrL4195dizKoaBt9jx6UEvhn5+gBP//RlHJycoKoSTv2GI/wLXre/jenTNxQ0NRqhZD+pF4HznC4Q1qOBYuM2AOR0JOb4U/vFGhePW+FdvGv/qSeN+4ykr2Veu5NHcuXPJzMxk7dq1PP/88+Tk5LB8+fLLtps0aRLPPfcckZGRfP3116xZs4ZZs2YxZ84cPDw8cHZ2Jisrq/j8rKysi5JJcuUOHz7Mrl272LVrFxs3biQmJsZ69aQa3gM1asOOT8uVPHLKOgJ2YO/XDI6dK/GcFTuPU2SGB1tWfHZPSTWPLugYUpuRnRsybdV+bqnvzqCK1j+y/+P9qaLZIiIiYm1mM6QnQ/ohqBUKLnVpcXoZJ7KK8O4/jfMf9+SLL76gf//+YDSBdzPLz50vQlYq/J4GOefAxRvc6oPNVZSG8GkBrR6z7Mwb1Aka3VN5z1NERK575Vq3s2rVKqZMmcLcuXOpVauW5X9QZVi+fDmzZ88GwNHREYPBwPfff8/8+fOJiYmhXj1LbZxmzZqxbds2cnNzOX/+PImJiTRq1Ogqn5IAxMfHA/DOO+/g7OxM586dGT16dIkJlatmsoFmkbDvW8g6fdnTa+alkJGH5YNMKZbvOEZT35oE1654MrGs5BHA/93VkDsb1eK1L+PZceRsxTpX8khERESs6fczsPMzWP4MTGsGb7eEmAdgSih80JkAw3Fm7qrBnXd3p169enzyySeX9mFjBzV9LYmkgNvBK/jqEkcXdH3dsrHK509AWuLV9yciIjeMciWP3nzzTbZt28ajjz7K+PHj6du3b5nnd+3alfj4eAYOHMhjjz3GmDFjGD9+PFlZWYwYMYKoqCjefvttatWqRVRUFAMGDGDw4MGMGjUKe3sVIa4MF5JHAwYMYNu2bTz++OO88cYbjBo1yjoXbDEQigoss48uw4szJJ+3sxRhLMH+k+fZfSzjimYdwZ/Jo7y8vBKPG40GpvVtQS0Xe0Ys3E5hkbn8nV8omJ1X9vJKERERkQrJy4JVr8K0prDsSdjzFfg0h25vQtRy6DQW0hI58rs9634PxGg0EhUVxf/+9z9SUlKuTYy2jhAZY1kC91mUJWYREakWyrVs7dtvv+Xo0aP8/PPPDB8+nJycHBYvXlzq+U5OTkyfPv2ix7p06VLiuZGRkURGRlYgZCmPhIQE6tSpU1yfas6cOSQnJ7Np0ybrXLBOONRvB1vfh9uesUydLoWv7Xk2ZbjQvJTjy345hslooEfzMnYKKYONjeVtXdYsK/cadjx/Twj//GwHu46do0U9t/J1fqFAZG7GFcUmIiIicomDP8MXwy1L1Br3gtuGg09LMP7le96gTtB2GPc1b0rjW/wBiIqKYsKECXz66af861//ujaxujeA3nNhfm9Y8X/Q+4NSvxAUEZGbR7lmHv3222+sWLGCr776Cjs7Ox588EFrxyUVkJmZSVJS0kWPxcfHEx4eftFjwcHBJCcnWy+QNk/B2cPw2zLLVObDmyDhS4j7EDa8A5mn4PczeNoXcLLIvcQuiorMfLHjOLc39KKWy5XNQjMYDNjY2Fx2id4djWphMMCPe06Vv3MtWxMREZHKtOYNmPdHzchHvoY+H4HfrRcnjv5QZOvEnuTjxSUgQkNDad26NTExMdcyYgjuDHdFw+5Y2Pzetb22iIhUiXLNPHr33Xfp2rUrs2bNUkHr69DIkSNZvnw5qampGI1GzGYz8fHxDBo06KLz/P39OXPmDBkZGbi6ulZ+IKH3gasfLH2s5OMb34UWAwA4a1O7xFO2HDzDsbPZvHBvyFWFYmtre9nkkUcNO1rUc2PNvlRG3V3OWlt2NQCDkkciIiJy9TJS4KfJEHAn9F/4x+eM0p06dYq8vDzq169f/FhUVBQjRoxg586dNG9e2rxuK+jwLzj2C/xvrKV4tkfgtbu2iIhcc+WaefTGG2+wZ88e/vWvfzFhwgTOnq1gkWGxmqysLBYvXsyZM2eKZx8dP36cjIyMS2YeBQQEAHDw4EHrBGOysXxbdvdr8MB7MHApPLUWnk2AJ34Eow2se5P8QjNnHUve5WzZ9mPUsDPRNbzuVYViZ2dXruLgHRvV5tejZ0nLzC1fxwaDpe5RrmoeiYiIVBs552DbPPioOywZYilqXRl+mQ/mQug45rKJI4AjR44AFM88AujXrx82NjbXfvaR0Qj3TbF8vlv7ZuX1e+4Y7PnastOciIhcN8qVPIqOjsbHx4dRo0bh6+vLSy+9ZO24pJy++OILMjMtiYwdO3YAlnpHAGFhYRed6+/vD1gxeQRQrzW0Hwkt+kPDLpYdOVx9wPcWGL6Vgqe34jMlE5PbpcWwc/IL+WZXCvc28cbRrvSaSeVRnplHAJ1Ca2E2w9r9qeXv3N5FM49ERESqg2PbIPYxeLMRfDkSMk9YClnPuRPOXGUpgKJCS0IqsBM0aFuuJocPHwa4aOaRl5cX3bt3Z8GCBRQUFFxdTBXlUhciHoOdC2FBH1g2FLLTr7w/sxmWPg6LBsDC/rDpPTj5W+XFKyIiV6xcyaP09HSioqIICwtj8ODBZGSoWPD1Yv78+fj6+mIymdi5cycAP//8MwaDgaZNm1507oWZR1ate1QWWwfOGj04/bu5uJD3X/2QcIrzuQVXvMvaRZcqZ/KoiU9Najrasv5AWvk7t3dWwWwREZGbXX42fPIAHFgFLQfBE6theBwMWWn5EunjnnD2SLm7279/P0OGDGHixIl8/91KcmKfgoyj0KqU5f5/cSEpVNLMI4CHH36YEydO8MMPP1TgCVaSDv8Eh5pweh/sioU5HSGzAl/K/dWBVXB4AzT6BySuhm9ftCSkRESkypWr5lFubi6pqanUqlWL06dPU1RUZO24pBxOnjzJ//73P55//nlWrFjBzp07MZvNLF68mDvuuINatWpddL6XlxdOTk5VlzwCzpyxTPN2d7+0YPayX45Rx9We24I8r/o65U0eGY0Gbgv0ZMOB05jNZgzl2S1EM49ERERufklrLF8WDfrcUiD6Ar8IiFpuKXL9v7EQ+XG5uouNjWXevHk42sCihxxxCLFl+g4H1u2ex8CBBaVuSPPiiy8yf/58fv31Vw4fPoyjo+MlX8Ld2fkevMLbMWHZVlacrsXu4+fwrGHHbUGe3BboRbN6NXF1sL3SV6JszrXh+STLMrZDG+CjbrB5FnT+d/n7yEyF+OWw/m1w94fITyzL+db+F9ZNsSwTdLr0i0cREbl2ypU8GjlyJP369cPZ2ZmsrCzGjRtn7bikHBYtWkRhYSFRUVEcOnSI9evXs3v3bhISEhgxYsQl5xsMBgICAjh48CA5OTk4ODhckzgLCwvZuXMnLVq0ID3dMpX578mjM1l5rNl7ikc7BGAyXv12r7a2tuTl5ZXr3PbBnnz72wkOpf2Ov9fl6w0oeSQiIlIN7PkK7GuC/+2XHvNpARFDLJuBnDsGNS8/azo5OZlgPy8SxjbDlLKN/9l2ZYO9gS0bN7J06ef07duXmTNn4un555doH3/8MZMnTwZgxowZbNmyhQYNGmAwGPg+/iQrd6Ww8+hZkk5nUaPHGA4BhUfP0sSnJifP5/DeT0nM/DERgACvGjT2caWpb00eutUPT+cr29W2RBd2hmvQDsLug61zocOzltnaZYlfAds/hsQfLcmi2uHQ7b9gY2c5HtwF1r1lSUqF3Vd58YqISIWVK3nUvn17fvjhB86cOVPiciOpGvPnz6dly5aEh4fTvHlzFi5cyIwZMzAajfTq1avENgEBAcTFxeHt7U2HDh2IiYnBzc3NKvGdPHmSuXPnMnv2bA4fPsynn35anDT6+/vo61+PU1BkrpQla1D+mUcA7YK9AFifeLr8yaOM41cTnoiIiFzPigph70po1PXPRMbftXocNsyA9dOhSW+wsQcHV0vCyd7lknbpR/fxbSTYnPoV+syja+MH6IplSdqYMWOYNm0aa9as4ZtvvuGWW25h8+bNPPXUU3Tq1AkHBwfGjRtHYWEhM2fOZO2+VJ6MicPzj51jezb35diuDbwV/X/8sGs7QUFBAGTmFhB38Ay7j51j17Fz/HL4LF/9msLXu1KIHdoOO5tyVbComHb/BwlfwpbZcPu/Sj/vaBwsjoKa9S31Mps+BHUaX3yO761g4wgH1yl5JCJSxcpMHvXt27fUZTyLFi2ySkBSPnv27CEuLo633noLoHhr1jlz5tC9e3fq1KlTYjt/f3+++uoratSowbfffssDDzzAmjVrrjoes9nM/PnzadSoEQUFBbz77rssWbKE/Px8OnfuzOnTp9mwYQOtW7cGLp55dO73fD5cf5DQui6EebtedSxQseRRoFcN6ro6sCExjYFtSt4F7iJ2mnkkIiJyUzu0AX5Pg9DupZ/j7g8h/7AkSbbMvvR48wHQ/c3iXdTa2+8lwDkPBq6AwDuLT7OxsWHy5MkMHDiQf/zjH4wcOZLPPvuMBx98EB8fH5YsWUJCQgIrV66kW7du9B44hG5v/0yj2i4sf6Z98SYju+rk8N9nM9iwYUNx8sjZ3oaOIbXpGFK7+Hord6UwbMF2Xv86njHdwnCwvbpNSi5Rr7WlZtEPr1mScHc8b9mt9u92LLAkhoattyTdSmJjD/XbQPK6yo1RRKqHc0dh0yxIWAE2DuDkBTX++HHyAq+G0LArOFpnMsXNpszk0ZQpU8psvHPnzuKkhVxb8+fPx2g00r9/fwBuv/12+vfvT9u2bRkyZEip7S58mJgxYwbx8fFMnTqVgoICbGwufivEHTzDrmPncLa34b5mPpfsfrZ3716ef/55PvzwQ7y8vFi3bh0PP/xw8XFXV1eGDRvGsGHDCA0N5c477yQuLg4AJyen4jhyC4p44pM4jqVn8/Gjra/+hflDRZJHBoOBdkGerNmXSlGRGePlls1p2ZqIiMjN7Zf5li+LGnYt+7zuUyCsJ9SoBYW5kJNhqZOUdgC2vA+n4uHR7yg02tLC7Twp5jr4/iVx9FfNmzfn5Zdf5umnn6Z9+/ZkZGTw3Xff4enpSYcOHVi9ejW33HIL/1q+m8zcAj57qu1Fn8/Cw8NxdXVlw4YNREVF8c0337BlyxYGDhxIw4YNi8/7R1NvHr6tAZ9sPMQ3u1Jo7ueGv1cNGtZ25q6w2tR2qYSyBpGfwIoR8ON4SD8I9027+Hh+DuxaCuH3l544usD/dlg9Do5ssSSmRETKY3sMfPsSFORA8N1gsrV8KZC6Fw6tt9RSwwxGWwjqZPnvUUi3itdX27vSMpOy88tWeRrXkzKTR76+ZS8heuutt/jkk08qNSC5vKKiIhYsWECXLl3w9vYGoEaNGnz66aeXbfvII49Qv359HnzwQT766COKTPYs3xhPoYMbR9OzOZqezd4T54lP+XM3sbdX72dy7+bFhazNZjNDhw5lzZo1zJs3j+eee45Fixbh6OjI9OnTMZlMREZG4uz85zr3iIgI3n33Xc6ePUuHDh2wtbWlsMjM5HWn2HL4d97p37JSCmUDFJmLMPoYy13zCCxL1z7/5Rh7Tpwn3OcyH2IuJI/M5pK/SRMREZEb1+9n4Ldllh3W7C6znN3VG1r0L/lYwB3w2SD44TWONRpCW18j+1zCKevT9aOPPsobb7zBwYMHiY2NvWjn3E6dOrH8l2OsSjjF2O5hBNd2uaityWSiTZs2rF27lscee4wPP/wQgNdee43PPvuMPn36FJ/7as/G3NO4Lgu3HObAqUzWJ54mJ78IgwFa+3twXzNv7mlS98oTSTZ28OB7ltlZP70B545gbPGXf1jt+Qpyz0GLAZfvq8VASzLv457Q5yPLbC8RkbIkroYVwy3/He75juW/RX9XVAjHf7EU64//Ar74HxhMljbh90PofeBc69J2f7V/leW/88F3W+VpXG/KVfOoNGazubLikApYv349Bw8evKLC5W5ubsX1kOKpT71/fsZzXx8BjmA0gHdNR/zcHXmlRzjdm/mw/+R5xi7fzcAPNvHkHUHU83Bk+7Y4tqYacWvaiY8Wfc7IkSNZsmQJPXv25IknnijxuhEREeTk5LBnzx4efvhhzGYzr6z4jQ2Hf+ff94XTo7nP1bwkF3kr7i1yHsoh+8vscrdp90fiakPi6fIljzBDXtblC0GKiIjIjeXXxZZZRLc+cnX9hPWAVk/AppmYU1JxsDFQWL9dmU3s7e2JjY3l8OHD9O7d+6Jj6w+c5oWlv3JrA3eGtA8osX27du149dVXSUhIYPTo0QwdOpTevXszfPhwOnfuXFxz0mAw0D7Yi/Z/1H0sKjKz/1Qm3+xK4ZtdKbz8xW+88mU8z3QKZmTnhle2mYnBAJ1Gg3sDWDEC/9RHweND8LnFsouaZ3DJxcj/ztUbHvsePu0DiwZYZntFlD7LXkSqudxM+HIkeDaEAYvB1rHk84wmy+6ZfhFw9zhI2WEp4h+/HL76J3z9LAR2hF4fQI0SJjkc3mxJHNUOg14lLF2+CV1V8qhc25pLpVuwYAFOTk488MADV9zHud/z+Sopn+zk7QyK8Oafjw2gbk0HbE0XF06s5WLPihEdeCF2J+/9lPjHow543fcsAFlA+7GLyXT2K15CV5KIiIji+x07duTdNYnEbDrEQ41r8miHkj8AXYnP93/OJ/GW2XD59uVbtgbg4+ZIgFcNNiSm8fjtgWWffCFhlHteySMREZGbTfwXULcpeDe7+r7ufg2Sf6LBocUUFpmp2fTeyzZp1aoVrVq1uuixdftTefKTbQR41uCDhyNKTeb07t2bZcuWMWHCBLp3t9Rrev/994mIiOCll15izpw5JbYzGg2E1HUhpK4Lo+5uxL6T53lvTSJv/7CfhJQM3ht065XvhttiALg1wLj4UfjwHgi4E1L3QN/5f+7S9v/snXd8Tfcbx9/3Zu8hO0EkERISIfaKvdUeQVWLFq1RP1VFqVFaarcoRe3WprV3iJEYIQgykEQiQ/bOHb8/TqWNrJtlnvfrlVc45znf73POuffknM95Rknom8NHf8PuEcJDXUoUtJ0uRoCLiIj8i0IBCaGw/zNIioBPjhUtHL2MRAI29YWf9rMg5q4gIl1YCucWQPcl+e1j7gqCtqE1DNsH2kYVvz9vIOUSj0ReDzdu3KBFixb50sJKy3a/J2TJFGRf/YNcy/ZUNR1VpK2+ljqrh3qSkJ7DnHnf88vqNezZt48q1tXoPWYaMvfOWA6az/ksa9pk5mKko1FgDEdHR4yMjMjNzUVq4cRPv/nRy8OGj90rrk3s9ZjrzLsyD2cTZx4mPiRXXXXxCIToowM3n5IrVxQQ0fKh9U9kUnYqYF12h0VERERERETeLOS5EHUDGn5SMeNp6kLf9ch/bcuN6FzqOdUpeZt/UCqVBD5N5q9bUfx+6TGO5vpsHdkEE70iur8Bbm5u3Lp1K98yDw8PJk2axJIlSxg+fDgtW7YscW5nSwOWDvKgrq0Rc/++x5y/7vJdzzol14UsCvsWhHXZTq1Hm4QUtKpNetmAewAAIABJREFUhZSQ0qClD947BfHIZ5HQia1WyWKciIjIO0hKNNzdBwlhkPhEqK2WFC5EjWrqC+J0taZlG1siAau6wk9mIlzbBNWbg1wm1EzSrQInZ4GGLnx4APQtSh7zHUFMW3sLiYmJwcXFpczby+QKNl96TEsnM+6ZahEcHKzSdvFPH7Nm6UI+HDqU3h2EG48dMz8iNT2Th5rV+M03nLMP4ulS1xq5QkGOTEG2TPitUCqpO2AyBrnPmXHwHjZGOizo40Z4mGpzl0RkaiRfnv0SO307VrZbSZe9XZCpy0o1RgsnM7ZfDed2ZDKe1U2KNtT6p8aAWDRbRERERETk3SLmjlBc1a5hybYlcP78efbv30/btm25+8Qdv8BgDmgWLfy84MnzdP70j+Dv29GEJ2SgLpXQ0dWSH/q5F/qCThW+++47du/ezZgxY7hx4waaKvgB8EnLGkQnZ7L+wiMexaezuH89rIzKVgdJoaEHvX4Bz4/BuHrZoobUNKD7MqHYdtg5UTwSEXnfyEiAi8vAb51wrdY2EuoZWbpC7W7Cvx3agmkFZbZ4TYNbf8Kel14oaBvDx0eFtNz3CJXEow0bNjBy5MgCy3v27FnhDokUj1KpJCYmBktLyzKPcfVRAjEp2XzXsw6/n6zJ9evXVZp3woQJ6Ojo8MMPP+Qt79y5c96/ezWoxsIj9zl2JxotdTU01aVoqUvRVJcikyuJrOIpGMamsenjRuhpVUzgW3puOuPPjEemlLGq3Sps9GxAAQoNRanGaerwT92jkHjVxKMcUTwSERERERF5p4gUOsNiV76uXkqlkvHjxxMYGMiKFSsAaN26dbHbZMvkLD3xkI2+j1AohYjoz9s60rmOFca6qok9L7j27BpGWkbUNBG6rOnr6/PLL7/Qs2dPlixZwjfffJNnm5ubS2BgIImJibRv377AWNO7uVDDTJ95f9+j83If5vWuS09367KXryivMKeuKYwRfql844iIiLxVKJIiyV3ZGE1FBhL3QeA1Fao4VuqcWeoGaH96FtJiQd9S6MSW+BiM7N6riKMXqPT0fv78eUaMGIGaWv527QMHDqwUp0SKJiUlhezs7HKJR4cDo9HVVKNtbQt8a9Zk79695ObmoqFR9NusI0eOcPz4cZYvX17k3HVsjNg2qkmRY0QkZBCZmIm5gRZOFhVXK2hH0A5Ck0L5teOv2BvZA6CWq0aOlurd1gBM9TRxtTbENzSe8e1rFm2o+Z+aRyIiIiIiIiLvDhF+oG8lPBiUA19fXwIDA/nll19wcXHh9OnTeHl5FWkfm5rF2G03uP4kkYEN7fhfp1pYGpYtwmfn/Z0suLoAgCZWTRjqMhSvql706NGDfv36MXfuXAYOHIiFhQV9+/bF19eXzEyhyci5c+cK+CmRSBjSpBrNHKvw5Z8BTNh5k0MBUczvXbfMUUjlpnoLIXUtK/m9qTUiIvK+c3fHTNwU6fyU3I0pKhSoTk5ORl9fv4CGoSpr165l/Pjx3Llzh1q1Wvy7Qte0TOO9C6hUpS4xMZFWrVoxcOBABg0axODBgyvbL5EiiImJASizeCSTKzh+5xlta1ugraFGzZo1kcvlhIaGFrvd0aNHMTAwYNy4cWWaF6CqqS7NHKtUqHAEcPXZVZxNnGlm0yxvmbpMHaVm6dMqWzhV4caTJLJy5UUbiWlrIiIiIiIi7yaR/kJUSzkKMSuVSlatWoWRkREjRoygbdu2zJ8/n44dC2/lfDsyiQ9W+XIvKoWfh9RnUf96ZRKO4jLimHFxBguuLqBN1TZMbDCRxymPmXB2AoP/Hsylp5dYvnw5crmcdevWcefOHU6dOkWvXr3YsWMHFhYWLFy4sMjxa5jpsWdMM2Z0c+FiSBwdl55n25UnKBSvoYxF9eagVAhin4iIyDuPUqHAIOxvfJ7ImLZqN3fu3CnWPiMjgxo1avDjjz+Wab6DBw/y+eefI5PJ8PMTrzMvUEk8Wrt2Lbt372bZsmUsXbqUJUuWlLyRSKVQXvHI71ECz9Nz6O4mFHpu1KgREomEnj174uPjk2enUCjIzf234PS9e/dwdXUtNjrpdZArz+VW7C0aWuUPgVaXqaPULv3NTHMnM3LkCq49TizaKF/BbBEREREREZF3grQ4SHwEdo1Kti0EhULB/v37adq0Kbt27WL06NHo6uoWP2W2jE9+9wdgz9hm9HC3KfW8OfIcNt7ZSI/9PTj66Cij3EaxtM1SRrmN4li/YyxouYCUnBQ+O/UZ3939jqqNqhIdHU1sbCwAU6ZMwdvbm0mTJnH8+HFu3LhR5FzqalJGt3bg+KTWuFc1YuaBO3ivv0JKVumalJQbu0YgVYcnvq92XhERkVfC1KlTsbCwwMPDg27dujHjo07Y6+eS6dwHQ0NDJk6cWGz95QsXLpCYmMjGjRtLXaf5ypUreHt74+npibq6Ovfv3y/v7rwzqCQeqaurs2zZMmbNmoWvry/x8fGV7ZdIEZRXPNp74yl6mmq0qWUOgKurK6dPn0ahUODl5cUXX3xBTEwMbdu2pV27dnnb3bt3jzp1VO8Q8qq4+/wuWfIsPC098y3XlGsi0S79W8PG9qZoqEnYdzOyaCMtMW1NRERERETknePxBeG3fcndyF5m586d1K1bl759+xIfH8+aNWv4/vvvS9xuw4VHxKfl8H2futSxKX36lU+kD30O9mHZ9WU0tm7MgV4HmNhgIhpS4WWfulSdno49OdT7ENMaT+Nh4kN0P9Xlse5j4uLiADA3F+4Jx40bh6GhYb7alkVRvYoe20Y24cd+blx/ksgnm/zJyCldo5JyoakL1ZoJndvSxecSEZEKJz4YnhefmVKZnDlzBi0tLapWrYo86SneRtfIkEloN34lc+fO5cyZMxw4cKDI7U+dOgVAaGgo/v7+Jc63Zs0adu3axcOHD+nRowc2Njb8/fffODk5ERQUVGH79bajknj07bff0q9fP3JycmjYsKFKfwxFKofyiEepWbkcCYzmAw8bdDX/LXfVtm1bbt++zcSJE1m9ejV2dnb4+Pjg7++PXC7n+fPnxMTE4OrqWmH7UVFcixEKWxYQjxSaoFP68fS01BnZ0oF9N55yMOBp4UbqWqCmKYpHIiIiIiIi7xKPL4CmAVh7lGozX19fhgwZgrq6Ojt27ODBgweMGTOm2I5madky9l6PZP2FMLrUsaK9S+nu67Ll2Uw+N5nPT3+OVCJlTYc1rGq3imqG1Qq111TTZKjLUI70PYJauhpJVZLyIo9eiEdGRkZ8/vnn7Nmzh4cPH5bog0QiYVCjaqwYXJ8b4YnMPni3VPtQbrr8INQ8Ovg55KS/2rlFRN5VZDlwaDz83AhWecLe0a9FRIqNjaV9+/b8tXEJxwcocLPWRfejPWjomzJmzBjq1q3L5MmT80Twlzl16hSenp5oaWnxxRdf4ObmxvHjxwu1DQsL44svvmDQoEG0aNECqVTKsWPHsLCwoJpHK27pePD94XtEJ2dW5i6/FagkHmVnZ9OsWTMkEgkODg5oaWlVtl8iCDnzDx48yLcsJiYGqVSKmZlZqcf7+3Y0mblyBjasWmCdnp4ey5cv58KFCzRv3pzu3buTnZ1NREQE9+7dA3gjI4+uPbuGo5Ejptr5C5dpKjWR6qr08S7A/zo508jehG/2BRISm1a4kZaBKB6JiIiIiIi8SzzyEWrpqP37gu2zzz7ju+++Q6EouoPr1q1b0dXV5dKlS3h7e6OuXng/GoVCydn7sUzYeZOG80/yv923MNPXZFrX2qVyM1eRy5RzUzj55CQTG0xk3wf7aGmrWrSUvqY+hpmGyIxlxMbGYmBggI7Ov2/bJk2ahJaWVpF1QlavXs2oUaPyLevubs0YL0d2X4/kdFBMqfalXFjVhY5z4eExWO4GPosFMUlERKTsXN8EN7ZA07HQYgIE/SUISUe/BvmriS5UKpXExsbSyEoBGzuBLBNG/A01OwBCVtTq1auJjo7G09OzQOfw2NhYAgIC6Nu3L7169cLf35+YmBg++OADjhw5UmC+lStXIpVK6d27N1lZWWzdfZBz0VJ6rLrAg+q9yLWozUbfx7RedJav99wmNjXrlRyHNxGVnq41NTW5cOECCoWCgICAYt+kiFQcR48epXbt2gQEBOQti4mJwczMrNRV4+PTslnnE4azpT4eVY2LtGvRogXnz59n6tSpADx48CBPPHrTIo/SctLwf+ZPU5umBdZpK7WR6kjJVZQ+B19DTcoq7wZoa6jx+fYbZOYUUjxbFI9ERERERETeHVKi4HkI1Gidtyg9PZ1169YxZ84chg4dSnZ2doHNcnJy2L17N7169UJfv+iGINkyOV/svMHHv/vjExxHf0879o5txtkpbbA301PZTaVSybzL8zgXeY6ZTWYyym0UGmqlq0dphhnSKlKexT3Lizp6gYWFBSNHjmTr1q1ERkaydu1aDh06BIBMJmPu3Lls2LCB27dv59tuYoea1LYyYNq+QBLTS9fttlw0HQufHAebBnBmPvzSBGLuvbr5Rd5elEp47Au3dwnpj6e+E1qwv89kpwkirH0r6LxAEGcnBoD7ILi6Frb0gpToSncjJSWFtlXlfKp9GHRMYeRJsG2Qz6ZVq1b4+go1z1q2bMnWrVvz1h07dgyADh06sG7dOh48eMD9+/epW7cuvXv35q+//sqzTUpKYsOGDQwePJiZyzfwwdITjD2WwPzDQUglErpZpRO5egQb+tjh3bga+wOe0utnXwIikir9OLyJqCQezZs3j3379uUVnfruu+8q2S0RIO8P89mzZ/OWxcTElDplLT4tmyHrrxCdnMmcD+oiUaGDSK1atQB4+PAhd+/eRV9fn6pVC0YsvU7ORpwlR5FDF/suBdZpK4UuJSnZKWUa28pIm+WDPHgYm8rsQ4VU8xfFIxERERERkbeWBw8ecOLEiX8LqT76p2nIf8SjFy/Punbtyh9//EGnTp1ITMzfUOPEiRMkJCQwZMiQIud6URT7SOAzpnWtjd/0Dszv7YZndVOV7sn+y477O9gfsp9P3T9lUO1Bpdr2BXbadkjUJDyMf4iFhUWB9VOmTEGhUDB8+HDGjh3L3LlzAeGB7EX5hF9/zd8mW0tdjaUDPUjKyOHbg8V3QapwqjWFYXtg1Bnh/5u6QPjVV+uDyNuDUglh52BjF/i9G+wbLaQ+XlwGx2e8bu9eD9lpcHs37BwM6XHQfva/HScNrKDPGujyI0TdgF9bCcevEomNjWVhey3SNcwE4ci0RqF2np6eXLt2jSZNmjB8+HAmTZpEdnY2P/74I7Vr18bT0xMjIyOcnZ0xNTXl1KlTeHh40K9fP/bv3w/Ab7/9RnqOnCrtRjJg7WVC4tIZ18aJU5O9OPRFSz5p6YAyJ5OEiBDm9qrLvrHNAej9iy/DfrvK2Qexr6fj5GtCJfFIoVDw1VdfsX79eqZNm4aWlla+TlwilUNISAgAFy9ezFtWWvHohXAUnpDBxo8a0cyxikrbWVhYYGhomBd55OrqWuobnMrm2ONjWOlZ4W7uXmCdjkQIwU7OLnv4cmtnc75o68Sua5Hsu/FSAW1NA8gpIqVNRERERERE5I1mxowZdO7cmS5dugj3W9c3g6EdWNbNs3nRCnrFihVs376dy5cv06JFC548eZJns3LlSszNzenUqVOh8ySk5zB0/RWuhCWwZEA9xng5oqletrR6mULGb4G/0cS6CZ97fF6mMQAcjR0BiMyKLFQ8sre3Z8iQIXkvLwMCAkhPT2fTpk2Ym5vj7e3N1q1bSUvLfx/kamPIxPY1+ft2NFsvPy6zf2XGzlOIQtI1EyIkHp549T6IvLkolYJI/Ht34fORFA7dl8AX12H8DWg9Fe7/Dc8CX7enrwalEoJPwe4RsNgJ9o2ChDDoNB+qFtJxsukYGH0WdKvAlt5wdV3xY2clQ3wIxiH74dh0ODkbUlVLa33+NAx3Synxlq1Br/hnVwsLC06ePMmECRNYsWIFderU4d69e3z33XcFMnVMTEw4efIknp6eDBw4kM3b/2Dl8UDsv9jMgQfp9Gtgx6nJXkzpXAsnCyGStHZtIa34RdHsurZGHJvYmq861+JhTCofb/Kn47LzHLtT+RFZbwKFJ2W/xGeffUZMTAwODg48evQIHR0dZDIZX331Fb169apsH99bQkOF4mQXL15EqVQikUiIiYnB0dFRpe3zCUcjGtHcUfU6SRKJhFq1ahEQEEBgYCADBw4s0z5UFsnZyVyKusTQ2kORSgrehL0Qj+LT43EwdijzPJM6OOPzMI7V50Lp28Du3xVaBpD2rMzjioiIiIiIiLw+EhISMDc35/Lly3zWxY3TwzTJ7bgADamUlStXEh8fT3p6Otra2jg4OFCzZk1sbGzo3bs3TZs25fDhwyQnJ3Py5EmWLFlSaEmH6ORMhv12lcjETH4d5kkH17J1yn2B71Nf4jPjmdl0ZqH3PqpS27I2yidKpOZSzI3NC7WZMWMG169fp0ePHixatIijR4/y119/8cUXXzBgwAB27tzJjh07+PTTTwHy7lPHtnEiICKJ2YfuIlMoGdCwKvpaKj1uVAwm1QUBaVtf+MMbeq8F9wGvbn6RN4/sNAjcBX6/Qexd0LeCrouhwXDQ0P7XrtnncPVXOP8jDNr2+vx9FWQlw+YPIDpAEFvrD4W6/aFqE5AWc22xqA2jz8DeUXBsmiDY2noKItS1DUKHtoznkJUESqFOnDWAhi7IcyBgBzQbB0ZVwdAWjGzBwBpeSr1VPLmMVCJBWa2ZSrujoaHBihUr8PT05NNPP6Vu3boMGPDv916pVOIb8pz7z1J4FJ9O1eGLiW0awexAA6SeA3EyUrLkw5a42RXseKmvr4+TkxO7d+9m6tSpaGhoYKSrwedtnRjdyoHDgVFsuPiItefD6FLXWiV/32ZUuprb2dmxefNmTE1NSU5OZubMmcybN4/Ro0cXKh7J5XJmzpzJo0ePUFNTY+HChSiVSqZNm4ZEIqFmzZrMnj0bqVTKzz//zLlz51BXV2f69Om4uxeMInlfCQkJQVtbm9jYWIKDg3F2dlY58kihUDJ8gx/hCRlsGtFY5Yij/+Ls7Mz27dsBGDp0aKm3r0wuPL2ATCGjk33hb/r0pEL9gISMhHLNoyaV0LOeDfMPBxGVlImN8T9FJbUM4HlwucYWEREREREReT2kpqbSqFEj1q9fT+zSVsSmx9J70nouXBnD6tWrCQsLo0GDBri6uua9vW7Tpg2+vr5069aNpk2boqenh62tLWPHji10jql7bhOTks2WTxrTxKH092Evsz9kP6baprS2a12ycTHYWNqQfTUbLVstLPQKRh6BUL7g7t27JCQksGjRIr766ityc3P5+OOPqVu3Lu7u7qxdu5bRo0eTlpaGs7Mzq1aton///qz0rs+ITf7M+esei48/oKe7DYMaV0Vb+YpSO/TNYcRh2OkN+z8D+xZgaPNq5hZ59SRFwOWfhYih7BTIShFKS2gZCMJGyClhuZUb9FwJ7gNBo5CWzDrGQnTN+R/h2R2hIPu7yq0/BOGo+1JBRCtN3TRNPei9BtY0hz2fQP1hcO4HQZSzbQD6FqBtDDomoGNCaI4Jjo27QmwQ7B0p1JbKhwSMq0KTMdBwJGhoox17kxy5Er1apbvWDR8+nFatWqGjo4P0HxEsOTOXKbtvcfKeEPVkpKOBg7ke3RvV5OKRvciePeTYid159oXxvwX/44uRX7BkyRKmTZv276FQl9Knvh196tsVue27hkri0fPnzzE1FbpZGRkZER8fj7GxcZEH+UWY6x9//MHVq1fzxKNJkybRpEkTZs2axenTp7GxscHPz4/du3cTHR3N+PHj2bt3bwXt2ttNZmYmkZGRDBkyhB07dnDkyBEsLS3JyMhQSTwKepbCvegUFvRxK5NwlCPPoaprVSRqEpwcnPDy8lJpO5lCRlxGHJpqmmipaaGppomGVLggJWYnkp6Tjq6GLlV0yncTdSHyAqbaptQ1K/zCrqumK8yZmVjo+tLQ2tkcDgfh8zCOwY3/aYEr1jwSERERERF5a0lJScHR0REbYrHRj+eidicuX9vHxYsX8zrdXr16lQ8//DDfdnXq1OHKlSssW7aM27dvM2bMmHzdyl5wKTSeC8HxzOzuUiHCUWxGLOcjzuPt4p13X1VWLCwsyHqahV4tPfQpusg3gKmpKS4uLgQFBeHp6YmbmxsAY8aMYdy4cfj7+xMXF8ezZ8+4fv06/fv3R1dTnT8/bcrNiCT+9Ivgr9tR/HktAidTTaYqTenoaln5pRC0DaH7T7C6KTw8Dg0/rtz5RF4P4Vdhc08hyqVqYyGixcJAuE9PfgqPzoNzF2g8Guwa/VvHpyiajoUra/6JPtpavO3bilIJ1zYKReYbjSzbGDrG0H+jIB6dmY/S1hPF0L2o6ZoUMM0JChKOu6UrjLssiHspT4Xzk/LPz5NLcHw6XNsEvX7BLP0h16PkeFpXK7VrNWr8Wx/pXlQKY7df52liJjO7u9CvgR0mev+JEh3SEJlMVqxwlCXLYotsC26L3Jj3/TxcXFze68wrlcSjOnXqMHnyZDw8PAgICMDFxYUjR45QpUrhfww7dOhAmzZtAIiKisLMzIxz587RuHFjAFq3bo2vry81atSgZcuWSCQSbGxskMvlJCQk5AlV7zNhYWEAdO/eHT8/P7788kv+97//AUIkWEn4PIwHoINL4W+USmLK+SmctT1L7VW16ZnVU6U/8pmyTD459gl3nhcslKguUUemlOX9+1DvQ1Q1LFsBbrlCjm+UL152XkWGbRuoGwCQmFV+8aimhT5Whtqczyce6QthsCIiIiIiIiJvHampqRgaGsLFpaBlRPX+c+GbfSxduhQAqVSKQqGgbt2CL6msra1ZtGhRkWPHpmax4EgQ1kbaDGtavUL83XRnE0qUeNf2LvdYZmZmJPkkYehhyCGtQ+hc16GxVWPqW9RHV0O3gH3z5s0JCgpixIgRecuGDh3KV199xdq1a/OeB6KiovLWSyQSGlQzoUE1E77t6cqhgCh+PhXEp1uv42ptyJxedWhkX8n3++a1wbgaPDwmikfvIplJQvqUgZUQaWZcAY19dEyECBifRUJRaIc25R/zTSP8MsTdhw9+LtIkPT0dXV3d4p//qjWFSYEQfoVZa/ZwvE1n/Pz8Sp5f21D4sXDJvzz4FPw1ETZ2ohpwIFaDZuXo8L77WgQzD9zBWFeDPz9rimf1wq836urFyyHnIs+RmpOKtr42jt844j3GmxNVTtCyZcsy+/Y2o5J4NHv2bE6fPk1oaCi9evXCy8uLsLAw2rZtW/TA6up8/fXXnDx5kpUrV3L27Nm8D6Cenh6pqamkpaVhbPxv2/gXy4sTj7Kzs/MKVr3LvIjeUldXZ/PmzZw6dYqIiAhq165NnTp1SjwGxwKiqGGiyfOnj3j+tHRz30+9z9mIszQ3ao5fth/BtsHcu3ev2AuIUqlkRegK7ibcxdvOGz01PXKUOeQqcslV5CJTyjDWMEZDqsH6x+vZ5r+N3ja9ycrKKvX5fJj2kOTsZGpQo8htU+JTUOooCYsKq5DPi7uFBj4PYrlz9x5qUglmKdmYyzIJuhsI0kK+RgoZWimPyNWxQKFVMH9WRKAs51/k3UL8DLx/iOf8/eVNOvdJSUlUUcajvHeG564fkZYrxcbGJq+Fc9++fdmzZw+GhoYq+yxTKPkrKJmttxLJlSuZ2sqCRyEPy+9rThJ/3v+TVlVakRaZRhDlP4aa0ZqEzgul7dy2bL67mY13NqIl1WKQ3SC6WXbL93LO09OT48eP4+npme9YdOvWjZ07d2JtLdT5CA4OLvJY1TeElV3MuRItY1tAIt7rLjOlpQVeNYqPfCovluZNMA49xMPAmyjVtUveQKTSqOjvv/XVeRilPOVxu1/Jik6D6IoZW2rWmepGe9HY4c2TdmvINqlVIeO+KVj7/YKBhh7BGnVQFnI+nj59Srdu3fDy8uLrr7/G1ta2hBFNOXn+Mv7+/hw9ehR7e/t8a1U/77ZIO2zGOOwgcT6bOB4lpaOKnxelUklajoKEDDmx6TL+up+M/9NM6llpM621JboZMQQFqVas+2V2PtxJFc0qfOP8DbPuzaL6/6oz+4fZ/Ly4aPHtXUYl8SgtLY3s7GwsLCxITEzkwIED9O7du8TtfvzxR6ZMmcLAgQPJzs7OW56eno6hoSH6+vqkp6fnW25gYFDsmFpaWri4uBRr8y5w5MgRADp27IiJiQnNmzdXeduMHBn34h7xcYsapT5WydnJfH/6e8x0zFjWfRl/h/3NvCvzCJQG0te5b5Gh0hvvbORSwiUmNpjIKLdRxc5xNe0qAZkBfOPyDUFBQaX28fTN00glUgY0GoBREcJM9WrVkafJkdpJK+Tz0j3bkBMhASiNbHGxM4JkB7gDLjVsQfclsfPhCTg4SihGZ+4Co08L+cEiBSjL+Rd5txA/A+8f4jl/f3lTzr1cLiczM5NBttFI1LUx6/4tZnpmtG/fnq1bt+Lk5MTixYsBGDJkiBChVAKXQ58z+9AdHsak4eVszuyerjiYl08YeZr2lF0PdrEveB8KFExpNYXqhhUTyWRtbc3du3f5ocEP1HStyc3Ym2wP2s6W8C0EZAYwr/m8vIYjLi4uhdZ1+uabb9i9ezePHj0CIDk5udjzGxQUxBc9XPiwXS6jtvizxDeOAa3dqaKvVSH7VCiaQyB4N7U1Y6BWl8qbR6REKvT7/+QyPD4MLb+kRqtKKIhu/zds6ISD71cw8kSRreLfOmQ5cPACuPSktluDQk0ePHhAbm4up0+f5tSpU9jY2NC0aVNmz55dZG3i+Hgh4+X+/ft07do137pSn3f3hgxc5oNST1nodvefpXDtcSJ3o1IIjkklJjWLmJRscmSKPBtDbXWmd6vNyJYOqEnLniL7PPM5t/1v82GdD+ns2RnLqpZ8dPgjQp3bU046AAAgAElEQVRCMTExwcrKqsxjv8kUJ/ap1Kph3LhxnDlzhtDQUEJDQ/NSqoriwIED/PrrrwDo6OggkUioW7cuV69eBcDHx4eGDRvSoEEDLl68iEKhICoqCoVCIaas/UNISAimpqaYmBTMHS2Ja4+FN16taxbeQaMwYtJj+Mn/Jzrt6cStuFtMqD8BXQ1d+tTsg4upC/OvzqfRtkZ4bvWk4baGNN7emBY7WzDsyDC+OP0Fy68vp7N9Z0bWLTl3tmP1jtx7fo+I1IhS7xvA6fDTeJh7FCkcgVB1X5YsIz4rvkxzvEz9qsJ5uBWZJCzQ+kfkfLnu0f0j8McQMK4O7WcLYaF/TQJZNiIiIiIiIiKvn7S0NKobSXAnCDxHgJ7QjbZ1a6E4a6NGjbC3t2f37t0qCUfXHicw5LcrZOTIWfehJ79/3KhcwtGtuFuMPzOernu7svnuZhpaNuT3Lr9XmHAEQt0jAHNzc3Q1dGlh24Jf2v/CwlYLCU8Jp/9f/Vl3ex1yhbzIMerXr59XksLd3T1f2lpMTAzPnhXeldZIV4P5vd3IlSs5GBBVqE2FUb2lULz39p+VO4/Iq0OphKNfgaEdtP6qcuYwtIFh+0CRC1v7QFps5czzqnl0Xni5XafoIJDgYKEhkL+/PytXrqRt27acP3+enj17kppasN6rQqEgIkJ4pjt8+HCB9bdv3+bcuXOlcjM2NrbQGr+HbkXRZfkFZh64w+HbUUilEjyrmfBxc3tmdndhlXd9dn3WjIvT2vFpa8dyCUcZuRl8ee5LAHo7CsfLw8KDYdWHYVDfgDm755R57LcZlSKPlEolP/30k8qDdurUiW+++YahQ4cik8mYPn06jo6OfPvttyxduhQHBwc6d+6MmpoaDRs2ZNCgQSgUCmbNmlXmHXnXCA0NxcnJqUzb1rTUZ1wbR5o4lCzEPUt/xtpbazkYehClUkmXGl34pO4nOJs4A6Ah1WB7t+1cirpEQFwAcqUclKBESaYsk9CkUGIyYuhQvQNzm89VqTZSR/uOLLm+hJNPTtJMTbUWjC8ISw4jJCmEaY2nFWunoaFBTnwOMVllC1F8maqmOpjoanA7Mgmo/q94lPOfukfP7ghdBKzc4MP9QjE5eQ6cWwiPL0CLidDgI9AsWE9ARERERERE5NWQkpLChCaaKJFC8y/ylr+o19msmer3Jkqlku+PBGFhoMWxSa3L1ZY+V5HL0mtL2R60HRNtE0a5jWJgrYFY6VX82+0XD2ZmZmZ5yyQSCT0cetDMuhkL/Ray6uYq0nLSmNxwcpHjzJw5kwULFtC5c2fmzJlDRkYGurq6tGrViuDgYOrUqUPHjh3p0KFDXnobQC0rA9ztjNhzPZJPWlZiVIe6JngMAb/1kBYndGJ7mawUoZW4WtnPncgrJNJf6Kz2warKjew3d4Yhu4WC3Nv7C3WVtIrPkHnjuXsAtAzBsV2RJiEhIZiZmeHp6Ymnpyfjx4/H19eX1q1b8+WXX/Lbb7/ls4+NjSUnJ4cqVapw/vx5Nm7cmNehMiwsjO+//x5tbW3Cw8NVDhKJjY3NE7gBcuUKztyPZeqeWzSyN2HpQA/sTHQqrfB+liyL8WfGcyvuFotbL86LwgSY3GYy2xZv46LhRTJyMwqtE/cuo9JVslatWty6dStf6JhmMQWsdHV1WbFiRYHl27ZtK7Bs/PjxjB8/XhU33itCQkJKdfPyX6yNdJjapXaJdmfCzzDtwjTkCjn9avZjRJ0R2BkULMatoaaBV1UvvKqq1nGtJGz1bXE3c+dI2BGa1SzdPp58fBIQopeKQ0NDg5y4HGKzY1EqleW+uEgkEtztjLkdmSws0PznjWJ8sNB68pEP3D8sXJC9dwrCEYDX10JBufOL4dg0uLBEEJGajgOpWrl8EhERERERESk9qampeFipkaBjj7nRv/c9Tk5OXL58mfr166s81tE7z7gZnsSifu7FCkcHQw6ir6FP++rtC12fK8/lK5+vOB1+msG1BjPJcxJ6GpX3YOzs7EyNGjUKvZ+volOFn7x+wljLmE13N1HPvF6Rfvfs2ZOePXuyefNmAKKjozExMSE4OJjOnTsjl8tZs2YNy5cvx97enmvXruUV2O7vacesg3cJiEjCo6pxoeNXCJ4j4MpquLRSuCcLvyzcvyVHQnKEEIlhUgM+PiJEnIi82dz6A6W6NvJaPVR7kC0PVRvBwM2wYyBcXVt5kU6vAoUcHhyGWl1BvehU0eDg4AIBDC1atODrr79m4cKF9OzZM1+3sfDwcEDIVJo3bx4jR+bPQmnSpAlXr15l2S+/Uq/bhzyOT0eJEldrI9ztjAqIQLm5uSQkJGBubsH1J4kcDHjK4dvRPE/PoaqpDquHemJuUHmprjnyHCadm4T/M38WtFpAJ/tO+darSdXopNmJY7rHWOe3jkktJlWaL28iKn3n/Pz8OHPmTN7/JRIJp0+frjSn3ndycnJ48uRJgfawFc3+kP0YahqyuetmbPVLKoZWsXRz6MYPfj8QkRGBC6rlwebIczj2+Bj1LepjoVt8FzkNDQ1y43PJUmSRkpNSbIqbqtSzM+Lns3Fk5MjQ1fonjH33R8JvLUOo3gLaThe6PrxAIhE6NTi0EdpQnl8EJ2aCVAOajim3TyIiIiIiIiKlIyUlBVsDCTKdglEoTZs2LdVY6y+E4WCmRz/Pojvh5shzWOi3EKlESiPrRhhq5k+Fy5JlMfncZC48vcC0xtMY6jK0VD6UhenTpzNx4sRibaY2msrtuNssvrYYr6peqBfWIOQfbGwE0SUqKirvYXLy5Ml06tSJzMxMjhw5wpAhQ+jTpw8nT55ES0uLD+rZsPJ0MJ9uucYfnzYtd42oIjGvBdWaC+LRpZWgpgVmNYW27tWagb4F+K6ELb3h46OgV3g3aZE3AFkOyjv72H8vm4AflzN37tzKn9O5s/A5ub0bWk0R7u3fRp7egMxEYX+KISQkJC8K87989913HDt2jNGjR9O0adO86MUX3/e+ffvSedDHRD5PIzlLTnKmjMQsBTcjU3BomcyWVE0ku28hlYBUIkGmUAJgoquBm50xiSEBtHO1oncLNySaOpxR1uX3NZfQUpfSwcWSXh42eNUyR0u98l6+5ypymXJ+Cr5PfZnTfA49HHoUajei0wh2b9zNduV2RjceXalC/5uGSuLRoUOHKtsPkf/w+PFjFAoFjo6OlTrPs/Rn1DKt9cqFI4Au9l1Y7L+YC88v0IlOxdoqlUp8In1Y5L+I8NRw5rWYV+L4L9LWQCg4WSHiUVVjFEq48zSFxlXdodFooS2ofSuwrldyJFH15kI629Y+Qiqb+8CCxbZFREREREREKpXU1FTqGEhJ0StYU6M03ItK4WZ4Et/2cC22tob/M3/Sc4UGMdvvbWesx7/Fp2UKGZPOTuJS1CVmN5tNf+f+5fJJVbS0tNDSKv7tvaaaJmPrjWXC2Qkcf3ycrjW6EpQQRHhKOFKJFDWJGlKJFB11HdSrCI8UUVFRebWO6tWrBwj1T/v168eCBQuYMmUKo0aNYsuWLRjrarJjdFOGrL/C4HVX2PlpUxwrS0Dq+6uQ7mRUTSgvoPFS57XqzWFbP9jWFz76S2glLvLaUSqV5ObmChFySiVcXoUkK5Hf/DO4f2Ubc+bMqbTUpXy4DYDDk+HZbeGe/20k9AwgAYe2yOVyfHx8aNWqVb5W9ZmZmURERFCzZs0Cm2tqarJt2zYaNGjAqFGjOHToEBKJhCdPwtF378QXx+KJTMrf4ltdKsHRVJM2jobs3fE7H7arz4rZ/yNXoeDBs1RuRSYTGJlEQHgiD2RWBN5R49fAG9h88gtPc7T5rqcr/TztMNAuvGFTRbM6YDVnI84yvcl0+tbsW6Sdq6srkssSstyz2Hl/Z4nNot4lihWP5s6dy6xZsxg0aFCBL+Yff/xRqY69z4SEhACUueaRqkSnR1PP/PVcAKvoVKGpTVN843xRKBX5WsL+l0fJj1jkv4iLTy9Sw6gGv3b4lea2JXeeexF5BBCVFoVrFddy++xuJ4RU34pIonENU+iueh2wPCQS6LwA1rYQBKRui8vtl4iIiIiIiIjqZCTGYKAlIdWofC/Pdvg9QUtdSr8GxY9zJvwMOuo6NLBswMY7G3mQ+IBaprVwMXXB75kfvlG+zGo265UJR6XBq6oXjkaO/HTtJ5ZcW0JcZlyRtiZeJkRFRREYGIiFhUWBgrfdunUjMzOTb7/9lmbNmjFu3DicLQ3YObop3i8EpNFNcbKoBAHJuJrwUxT2LWHgFqHpyek50H1JxfsgUmoWL17MrFmzGOo9iB+8wPzxAS4mmHI8NAWF8hEBAQGlSjMtM3X6wNGpcHvXWywenQab+kQ8T+fjjwdy+vRpNm/ezPDhw/NMXjTFKuoZ1NXVlR9//JFJkyaxZv1GTD068sczM6p0nYCFoQ4TOtTCwUwPUz1NTPU0MdTW4MGD+7i4uJB+fgO/LfqWScP74OjoiLud8T/PVtU5ceIEXb4ZjK5zM7Tt62PtUJuVIxrRtlbxmSYVSURqBJvvbqanQ0+8a3sXayuRSOhSrwsnAk+wSXMTg2sNRl+zkoTvN4xixaNx48YBsHTp0lfijIjAqxCPMnIzSM5OxlrPumTjSqKHQw++efoNN2Nv4mnpWWD9g4QHeB/2RktNi68afoW3izcaUtWUZ01NzXyRRxWBuYEWNkba/3ZcKyuWrtDwE/DfAA1HgkXJ9alEREREREREKgZ5UiQA6iZFp5qVRFq2jP03ntLd3Rpj3aLrgCqUCs5GnKWlbUumNJzC8uvLCUoI4kz4GZQIaRsDnAcwwLkS2o1XAFKJlM/rf878K/NpaNkQr6peuJq6okSJQqlArpSTnpvOnMtzyGieQVRUFLdu3cqLOnqZGTNmsHHjRnx8fPKeM2rmCUhXGbzuCrs+q8QUtuJw7gzOXSD45KufW6RQrly5QhU9DQYr9mP+WML2x2Z8tPUxo0Z/ym+//cbevXtfjXikawqO7eH+39D5+8qfr6LJTILIa5yV1aeLkxNqampoaGhw8+bNfOLRi05rhUUevWD8+PFsP3WNH2+rIwkLRF2pg+bdQ+xZsBZpMRGYS5Ys4fDhw9SpU4cePXqwcuXKvHTXS5cuIZFl46afwZW/l3Dq5k08XqFwpFQqWey/GHWpOpM8Vath1LVrV36f8Du6brpsC9rGmHrvRzmSYsWjLVu2FLlu8uSiOy+IlI+QkBAMDAwwNy+kI0QFEZ0eDfBaxaN2VduhJdXicNjhQsWj1QGr0VbT5kDvAyXWOHoZDQ0NFBkKtCXaKolHaWlpKJVKDAyK76JQr+p/imaXhzbTIXA3HJ8Ow/a+vfnTIiIiIiIibxupwj2QlnnZu3wdCogiPUfO0CbVi7W7E3+HuMw42lZti42+DYu8FgGQnptOcGIwT9Oe0ql68en7r5uO1TuW2Kiks31nHic9Jux0GHfv3i2yGY5EIqFatWpERUXlW17T0oA/Pm1C39WXWHLiIb8MbVBh/peKGq0FgSDxMZjYvx4fRPJIfXqfS6P0qaaXwwnNrnzrcwmJVMrkyZMJDg5m5cqV3Lx5kzVr1lCtWjGRZRWBYzsIPg6JT8Ck+O/9G8eNzaCU8+3m8/Tu3Y8ff/yRAQMGcOfOnXxmJQUwpGblsvDofWLrDEaW8BRv06ec+fNXrCwtixWOAGxtbfH19WXTpk2sW7cODw8PtmzZQpcuXfD19cXd3Z0dO3bg5+eHh4dHxey3ivwV9hdnI84y2XOyys+c7dq1QxGtwCLZgi13tzDEZUiBenbvIoXnCv1DjRo1Cv1xcHAobjORchIaGoqTk1Ol5vDmiUf6r0880tXQpZFJI048OUGuPDffugcJDzgTcYZhrsNKLRyBIB4BGEuNiUqLKtQmNDQ0L/2yd+/eDBhQ8ls/dztjwhMySEjPKbVP+dCrAl7ThBDS4BPlG0tEREREREREZdTSYwHQsSibeKRUKtl+9Qm1rQxoUK34LmFnI86iJlGjtV3rfMv1NPTwsPCgu0N3NNReTT2PyqRdtXZIpBL8E/zJzs7G3d29SFtra2uio6MLLHeyMKCXhy2n78eQkSOrTHeLpsY/5+mRz+uZXyQPpVLJIOtwrLWzkQzbS6dp2wgODiY8PJxatWoxf/58OnfuzLFjx9i4cWPlO/Tis/H4QuXPVZE8uoDy1Bx8Yg15JLfg999/x97eHjc3NwIDA/PMkpOT2bBhA9WqVcPYuOB1zedhHJ2X+bDTL5zRrWrgFLKbLT/NJPjhQ5WFO3d3d5YtW8a1a9ewtLSka9eufP3111y5coXmzZtTo0YNBg0aVGG7rgqRqZEsuLoAT0tPhrsOL3mDf9DX18fLy4vovdGk5qay9d7WSvTyzaFY8ahPnz706dOHwMDAvH/36dOHS5cuvSr/3ktCQkJeSb0jeL2RRwAtq7QkOTuZi08v5lv+6+1f0dfQL3PHkRfikRFGhUYeKZVKhg0bhre3N4cPH+b06dP4+/ujVCqLHbeenVB4+3Z5U9cAGo2CKk5C9NFL4pmIiIiIiIhI5aCZ/Vz4bVq2SIXbkcncjUphaJNqJb7oOxN+hoZWDSukccebjKupK5pZmkicJdja2uLl5VWkrY2NDVFRUYXec3V3tyYrV8HpoNjKdLdozGuDnoUoHr0BREdH08wGorUcha7FgJqaGtbWwrNL8+bN2b17Ny1btmTPnj2V75CFC+iavVWfDdnzJ2RvH0JkhiY9NkQya9ZsdHR0AKhbty4xMTHExcUhl8vx9vYmJCSEzZs35xtDqVTy7YE7DN/oh7amGnvGNGdGd1dWLF2MiYkJaWlpuLio1jn7BS4uLvj5+fHZZ5+xaNEi0tLSaNGiRYXtt6rIFDK+ufANUqQsbLkQtZKaH71Et27dCPIJooVZCw6HHa4kL98sihWPtm/fTsuWLfO+mC1btqRFixbExMS8Kv/eO2QyGY8ePap88SgtGjWJGuaFtKl9lbgbumOqbcrfYX/nLQtODObkk5MMcRlS5putF+KRIYY8TXta4AZl165dXLlyBYAhQ4YAkJCQQFxc0YUgAeraGSGRwK2ICkhdU9eETt/D8xC4tbP844mIiIiIiIiUiHZuIsnZgGbZ2ivvv/kUTXUpveoXXyj7UfIjwpLDaFe1XZnmeZuQSCR41/fGuIExV4OuFhuJYG1tTUZGBikpKQXWNbI3xdxAi8O3C0YmvRIkEiHCJPSs0Nb8ZbLTIPXZq/frPeTRvRvUsVAjx6r4FMb+/ftz9+5d7t+/X7kOvfhsPPIROr+9wSQlJTF7xtfc+daD7PRkvA8qmfT1t4wcOTLPpm7dugDcvXuXadOmcfToUX7++WfatGmTb6ytV56w9coTerpbc2RCKzyrmwDg4eHB/fv3efDgAWPHjkUVrsdcZ/6V+Uw8M5E9j/Yw9Yep/PHHH3Tu3JnOnTtXzM6rgFKp5GbsTab6TCUgLoAZTWeUKRunW7duALiGu7Ki7YqKdvONpNiaR0OHDmXo0KGsXbuWMWPejyJQr5uIiAhyc3NxdHSs1Hmi06Ox1LUstcJa0ahL1els35l9wftIy0lDX1OfdbfXoauuW6rQwZd5IR5JUiVk6maSkpOSJ0RlZWUxbdo03N3dadSoERs2bEBfX5+0tDSCgoI4dOgQDRs2LDTf1lBbAwczvYqJPAKhOKOpA9zdDw3Kvr8iIiIiIiIiqqGnSCE2R42yvJ6SyRX8fTua9rUtMCyhffTZiLOAkNL1PjCszjC239/OtqBtfN346yLtXhTJjY6Oxsgo/1lQk0ro7mbNTr9w0rJl6GsV+6hSOXiOgKBDsKk71O4OOemQkwZZSRByRvh3o5HQfjZov0U1TjKT4Fkg2NQHrTe/M1T6feH7o+/Svli7vn37MmHCBP78809mz55duU7VaA1390F8MJg7V+5c5eDLLyfROnEXHh4aXK0xibOB3+Y9G73Azc0NgNmzZ+Pj48Pnn3/OZ599ls8mNC6NBUeC8HI2Z0Z3F7Q18j83SiQSnJ1VOw4PEh4w6sQotNS0MNEy4UzEGQCs9KyoP70+CwIXoCZVQ0OqQWpOKpMaTMLBuGJL5cRmxPJX6F8cCDnA45TH6KjrMNptNN0dupdpvJo1a+Lo6MjJIyeZMHZChfr6pqLSFXno0KEsWrSIkJAQ7O3tGTduXKG5kCLl51V0WgNBPLLSs6rUOVSlu0N3dt7fyanwUzSxasLxx8f5uO7H5QrxfnGBPPf3OXQH6uJ/z58O9TsAsHLlSh4/fszJkyextbVly5YtTJ8+nenTp3Px4kW+/fZb2rRpw5kzZwodu15VY84/iEOpVJa/LpVEArV7wJXVwh91HfF7JSIiIiIiUpkYks7zHA2K7idUNJfDnhOfls0H9WxKtPV/5o+TsdMbc79V2VjpWdG1Rlf2Bu9FXaqOTCHjedZzErMSScxKRF2mTndld/QshIivqKgoatcu2HG2u7s1v196zOmgGHp5FB/dVSnUaAVDdsHuEeCzCDT1hSg1TT1w6SH8vrYRws7D4O1gXuvV+6gKchk89hH8fHQeom+BUgHaRlDPG2p1E4SkN1QA03h2A5lUiblHl2LtbG1tad++PXPmzCE2NpaFCxdiaFhJ++TYVvgdcuqNFY9iY2ORBfzJx700ofVXNGk3s1A7KysrTE1N8fHxoX379ixbtizfeplcweRdt9DWUGNRf3csDbVL7YtSqeRZ1jNiI2JZeXMlhpqG7O+1H1NtU56mPeVS1CUuPb3EzdibaKtpI1fKhetG5nO01bVZ1HpRmY7ByyRmJTLr0ix8In1QKBU0sGjAJ3U/obN9Z3Q1dMs8rkQioWvXrmzYsIGsrCy0tUt/jN42VBKPZsyYQcOGDenZsyd+fn5MmzaNtWvXVrZv7yWvSjx6lv4MD4tXW8m+KNzN3KlmUI0/7v9BZKrQPndgrYHlGvOFePQs5BkOOLB532Y61O9AXFwc33//Pd27d6dDB0FMio6OxsTEhO+//561a9eiVCo5e/YsoaGhhUaANalhyr4bTwmJTaOmZfHd2VTCpSdcWikUznYv336LiIiIiFQgSiVE3QQrd1B7DREQIpWCiXoWj+Wlj7xQKJRsvfwEfS112tYuvpmHUqkkMD6QDtU6lNXNt5JP3T8lKCGInfd3oi5Vx0TLBFMdU6z1rAl9Hsoif+Fh0LSDaYGOay/wrGaClaE2f9+Ofj3iEQgiwdQwQALSQqp81OkjiEvr20Gvn8G196vrnKtUCveMChmY1BC6wmn+5wE4OxVubIWrayApHKTqYNcIWk8FyzpwZy9c2wRX/3mWaz8bWr05XbRjY2NZsWIFAzOCCZJp4KZTshC0f/9+Zs6cyapVqzh48CC//PILvXr1qnjnTOzBzBlCTkKzcRU/fgWwfv16eteUkKNrhWabb4q0k0gkNG7cmJCQEHbt2lUgMmn1uVBuRSTxy5AGKglHz9Kfsfvhbp6lPyM+M574zHhiM2JJyhayNdQkaixvuxxTbVMAbPVtGeA8gAHOBRsWLfJfxM6gncQ2jC1T46T/IlfI+drna67HXGdk3ZH0cupFdcOK65bXrVs3fv75Z86fP/9KU+9eFyrdCSUmJjJ8uJBS4+LiwvHjxyvVqfeZkJAQdHR08orBVQZyhZyY9JjXXiz7BRKJhDH1xjD94nQeJD6gmU0zbPXLd7OgqakJQG6iUIj6jN8Z0tPTmTNnDunp6SxevDjPtkqVKgDUqlWLGzduoK+vT0ZGBps2bWL+/PkFxm7mYAbApdDnFSMe2TYEfSvhj7i+BVRvAe9A5xURERGRt55rG+Dw/4SHrnYzXrc3IhWBQkEVzVxSKJ14JJMrmLrnNifuxTC5o3OB9I2XCU8NJzk7GXfzoruOvYvYG9mzv9f+QtcFBQWhZ6vH/87+jyyvrEI7rgFIpRK6uVmz7coTUrNyMSghPbDSKK60g31L+PQ87BouiEhmzsILQLeBldvGXamEU7PB96X6KvqWgpCkpgFPb0BuOlRrBp3mg1OH/PW9XD8QBKYnl4QIqjPzoYYX2HlWnt+l4NChQ6xfvpBZX+pzON4WNxW2MTAwYMWKFQwdOpRRo0bRu3dvvLy88PLyYurUqejpla2+WaE4dQT/3yAnI79o94awYcNv3PDWQbNmu+I/wwg1YEE4fv8lIT2HNedC6e5mTXf34p8XHyU/Yl/wPv588Cc58hwsdC0w0zHDRs8GNzM3THJNaOPaBlt9W8x0zFTaB+9a3my7t40l15bQt2ZfnIydqKJTRaVt/0uuPJeFfgu5HH2Z2c1m09+5f6nHKIk2bdqgra3NkSNHRPHoBdnZ2cTFxWFubk5cXBwKhaKy/XpveRHtIi3sLUcFkZidiEwpK7eSW5H0cOjBrge7CIgLoF/NfuUe74V6LksSWr3mauUyePBgjh49ymeffVZoVwAXFxdu3LhBp06dyMzM5Pfff2fOnDmoqeW/8FY11cHWWIfLoc/5qLl9uX1FKoXWU+DETNjSSwgnrtlJCCl2Kj7PW0RERESkkojwg6Nfg5omXFkDTceCrunr9kqkvDwPRl0KyRLVU+OzcuVM2HmTE/dimNLJmc/blhwdfjvuNiBEV4v8SzXDanRz7Mb9pPuE3Q0r0q67uzUbfR9x8l4MfRvYqTT2jBkz2L59O8OGDeOTTz7BwaFi66UU4P/snXd8Tff/x583udl7yZJBgkhiJ7H3pqg9qnShShWt8W2p0apfUUrVKGpvitQItfeIGSJTIiFD9p73fn5/nEqlMm5IVOs+H4/zCPd8Pp/zOefce87n8/6836+3iT28f1hKenJnl2SEOfktOLaA3svA8kUCI8vB/1fJcOT1ATQcDikRf26RkBwp6TM1egfqDynbGKRjJOluOjSFlS1gxzDwGSWNPU3+IW+vP3nw4AETmumgpQnhpm0qVNfHx4fr16+zePFi1vmeYXWoHvWwdF0AACAASURBVDd/PkWLeq7UtjakgYMpNS0NXk52olYnuPwzRJ6TruFrRGJiIjoZUZhqGYJTi3LL/91o9JQNFyLIKVAwsVPZ3+EjEUf48tyXAHRy6sRnjT+julHx3+v9+/epa1WxbGwOxg70rdWX30J/43DEYQDMdMxwMXXB1dQVV1NXXExdqG5UneyCbNLz00nPTyctL420vDQCkwK5n3yfjPwM4rPjed/j/UqZX5aEnp4eHTp0wM/Pr0raf91QyXg0ceJEhg4dip6eHjk5OXzzzTdV3a83lrCwMGrVqoKXzTMkZEsZxf7pTGvPIpPJmNtyLruCd9Heof1Lt/fUeCQKBFoKLVp2bYnvBF8MDQ2ZPXt2iXWeGpS6dOmCpaUlAwYM4OjRo0VK+s/2tbmLBcfvx6NUCjQ0KsFN2WcUNBwmZfcIPgwhfhCwB0afkuLRq4KgQ9KEKD8TCnKhIBtkGtB8HHh9WLKbtho1atS8CSiVcGgyGNlC/7Xwazc4/AW0naaavokQkBkvidNqaoFtw4pr2kWchTs7Qd8CjOzAyAZMHMCmHigLQFGg1sl7EQIPABAqUy0xSVZeIaM3+3MhLIk5vT1UXjS6nXAbAy0DapjUeNGe/mdpYdeCxdcX80BRuvGosaMp9qZ6HLoTq5LxKCwsjAULFmBvb8/8+fOZN28eHTp0YOLEifTq1asyu18cuY4ksN3kPSlELGA3XPoZtvSDD4+DkXXlHSsvA059B86toccP0jjtZb2F9Exh8Bb442s4+Q2cmgcuHaHJSEmT81WF4j3D44gQfvTRIcepHeOGLCm/wp8olIKwJ5ncjk4lxbU7ijaeyNOeEJulYN35BxQopAxp1sY6tK5lRZvaVrR2tcTMQLtiHXRqCVr6EPrHa2c8un37Nm2c/lz0VsF4VBIZuQVsuBhJVw/rMiMszj8+z7Sz02hs3ZhFbRep7FWkKrObz2Z8w/GEpoYSnhpOeGo4Yalh/P7gd7IKssqsa6ZjRn2r+mhpaPGly5dVnrRg+vTpHDp0qEqP8bqgkvGooKAAIUSRQPBLiwSrKRGlUkl4eDjdu3ev0uMk5EjGo8r+kb8sNUxqlJmdoyI8G7drLDOmet3qXL58GaVSiZVVyUaztm3bYmpqSo8ePbC2tsbKyop169bRo0cPlEolERERRRpILVws2HP9EV/uC6COjRHOFgY4WxrgbKH/4r+Pp0KMdd+C3DRY1hiOTIcP/FR7eRfmwZNAiL0DSWGSu7JrJ5CX8FI8vwSOzwZzFynbm5au9CJMjZImSMdnSytmtbpAgyFSGTVq1Kh5UwjYLRl++q0Bx2bQ7BNppfnuXrCsI4V91BtUXDA1LwMur4Koi1LdrIS/9sk0JM0RKzcwsPrLg0mpkARsNTSh3kDJQJSTKk0+zy2ShHoLciRj0VO09KXnvYYm9FoqLTyoUZ3AA1x8pERpWr73tRCCUZv8uRKRzA8DG9C/iWoeMCB5Hnlaev7jWW1fR2qb1UaWLSPBIKHUMjKZjB71bNhwMZK07AJM9MsOXfvqq6/Q1tbm0qVLKBQKNmzYwLp16+jduzchISG4urpSWFj4nK5LpWLqCK0/h5rtYUNP2D8W3v2tctoWAs4uguxE6DSnchf47BvDewch+QHc2iZtO4dL4Vlvr5AkFV4hrnkBmOkI6DQd9MsPC8stUDBz/10OB8SSla8AwEhXThc3C1aPGczUBd/xybjxPEjM4sbDFM6FJfJHYDx7rj9CJoPhTZ2Y09tD9cVguY6UdS3s+MucZpVw+/Zt2jjKUehXQ/MFx+5br0SRnlvIJ+3K9rDcHrSdavrVWNVpFbryyheKlslkWOlbYaVvRQu7vwxhQgjis+MJSw0jJjMGQy1DjHWMMdE2wVjHGGNtY0x0TNCQvbpF8NatW9O6detXdrx/EpWMR8uXL2f37t2Ym5uTkJDAuHHjimIk1VQeMTEx5ObmlijSXJkk5iQCYKX/+ngeVTZy+V9fbQsdCxKyE/Du4F1mnVatWpGSklL0/3fffZdly5bx5MkTDh48yKhRowgICMDd3Z32darR0MEU39sxZF9TFNUZ286Fad2ezxxSYXRNoMMMODhRysTWfNzzZQrzpclJZjw8vADnfoCcP/sv05BEuHVNweNtaZLj1EIyQhXkwJmFULsbDNokvQSfIoS0KvvwopSV4+xCOLMAqrlLwoyFuaDIlyY4AzdWbVy/GjVq1PwTFOTCyW9RWtcjoVprrAG6fQctPoWgg9Iz8twPcP5HeGuxZOx/fF16bmbGS+LatbpKHkI2ntIzM+qyNNEIPiJN/kQJ4f83t0Kzj+HoDMjPAM8BknFISx9ykiEjVprcPbwoLTZEX5Ump4V54PX+q75K/04SwyD+Ljvv5mPRo3wR3qC4DC6GJ/FlD7cKGY4uxlwkKDmIsQ3Gvkxv/7PIZDJMkk1IsU0pM3Ntz/p2rDkXwbHAOAZ6OZTa3rVr19i1axczZ84s0gydMWMGI0eOxNHRkb179xIeHs7mzZtp1aoV27dvL3UhsVKwbyzJEZyYC3F3pefAy5AYKhlzEoJItmvP7AUbWbKk4XOyCi+NeU1p7Nnuf3BtHfwxE/aNgeG/vVIPpGbG8SQpDLBwaFpu2dTsfN7fcI1b0akM9nLAp4Y5DRxMqWFhgFKpYNV7WaSkpCDX1KC2tRG1rY0Y4uOIQim48yiV3dcfsfnyQzQ1ZMzq5a76ArBrJylKICkcLKp23lYRbt26xfya2mjWaPlC9yy3QMHacxG0crWkgUPpnq3JuclceHyBkR4jq8RwVBYymQwbA5s3Jovl64ZKxiMDAwPMzaVVMisrK/T09Kq0U28qryrT2lPj0evmeVSZyGQy5HI5hYWF2BnbcS/7XoXb+PDDD1m8eDGbN2/mjz/+QKlUsmPHDubOnYuZgTb7x7VECEFiZj5RyVlsvPiQVWfC6ehWDS/nStDFaDxCcok9+iVEXZJ0N7ISIPOJtOUkFy/v0hEavwu2DcC4Ojw4DQG7pDj86xug63wpM0T4SUlIsemY4oYjkF40Hm9LG0B6rCQYGxcglZXrSv247wsb34L3/f7x2Hg1atSoqVSurYW0KDYm92GSW12ioqKktM/GtlKIsc8oyIiHPe+D76dSHbMaUmha26lQ3ev5Nl06QHtJFwKlEvLSpH/LNCUPoqjLsG0Q/P6ZpJfS/f+kZ/lTDCylzaYeuP+ZQUhRINXx+5+0OPC6pgt/nQjcD8Bv9wuY+o5ZucUP3IpBU0NGfxU1dwCiM6KZenYqLqYujPQY+cJd/a9jLbMmVT+V5NzkUoVwG1Q3obqZHr63Y0o1HgkhmDZtGpaWlnzxxRfF9jk4OODj48OaNWt4+PAhbm5unDhxgvPnz9O3b99KP6diNHlf8hS6vELy3nlRspNh60DJs7HvL3y34QI//fQTbdu2pX//qtFwQUMTmo6WjNx+0+DePvDsVzXH+hvpCY9pU13JHR0PLMoxfqTnFjDi16sExWaw8p3GdPMsLuysoSHHyMio2MLwUzQ1ZDRyNKOhgyl6WpqsOx9BTSsDRjR3Vq2jtTpLf0P/eK2MRzFB/tjXFODQrMJ103IKWHQ0mMTMPD5pX3ZGbr8IPxRCwVs133rRrqr5l1Km8Wjx4sUAKBQKxowZQ5MmTbhz505RJis1lcurMh4lZCdgpG2EjqZO+YX/xWhpaVFYWIizpTNnQ85SqCxErqF6qmV3d3eaNWvGypUriYqKAmDnzp3MmTOnaGVCJpNhZaSDlZEOdWyMuf4whSl77nB4Qmv0tF9yRUhDEwZthMNTpBVrTS0p3MGylhRvbWgtuRIbVgNTp+dXtmp3kba8TMl9OmC3ZDy6/7vk2eSsgnulsa20CvV3vD6Q2vSbDoM3v9x5qlGjRs3rQlaiFC7m0oHFC26SlpbGvn37GDnyb0YAI2tpNf7mZilEuCKeBRoaoPc3w4VrRxiwHhJDoOVnqmXc1NSCt1dKYrer20hhcU4tpK26z2uZBeifpuDOXgKeaKJh6sCwYWWH+ymVgt9vx9C6liUWhqqNl7ILsvns1GcohZJl7Zehr6W+B6Vho29DMME8SHyAhUPJxiOZTEa/xtX56WQo0cnZOJg/fz1PnjzJqVOnWLZsmWTk/Rv9+/dn2rRpyOVytmzZQqNGjXj48GGln89z6JtDo+Hgv14KMzNU0dMpPRYeXZU8Cx9dg5hbgICRB8GxKYHBGwH4/vvv6devX9VKiXh/BLe3wZGp4OADJqobUV+UlKs7cZLLyHQoW6Mmv1DJ6E3+BMaks/rdJnSsW7K2lKmpKampqaW2I5PJ+KpHXSITs5j7eyBuNsb41FBhAdjMGSxqQdgfksfoa0BeXh5m2Q8AnZIXMUohLaeADRciWXf+Aem5hQxsUp3mNUvPbCaEYH/Yfmqb1aaWWdXq9Kp5/SgzGLBGjRrUqFGDfv360a1bN6ysrOjYseNzAsJqKoeIiAg0NTVxcCjdNbcySMxJfK3EsqsKLS0tTExMcDBzQCmUJOUkVbiNDz/8kPDwcAoKChgxYgQhISHcuXOnxLKGOnIWDqhPRGIWC48Gv2z3JTS1oNePMOkuTLgJHx6ThA3fWgztpkmhCm49y5646BhKoocxNyDtsSTIXaeHapOT0rBvDK0mSR5IkedfvB01atSoeV2Iugyr20JeJvH1x3H37l0AtmzZUnJ5LV3JC0kFw5EQgvfee4+zZ8+WXsi9txTqUpFns5GNNKn0+lDyTDi7UMrauaqlFNqspohjO1ejlRjIjju57NmzBwuLstM++z9M4XFqDn0a2qnUvhCCry9+TXhqOAvbLMTBuGrHcv92nmZkCokPKbPcIC+p3G7/6BL3+/n5oaOjw6hRo0rc/9Q755133qFBgwYYGBi8GuMRSL9LZYHkBV4aigIpWcqhL+DHerDYDXaNgKtrAEhy6cc1zzngKIVwhYSEYGhoyLVr16o+u5OmHPr+IoXybh8qZXKrSvKzMQjcTnymEhPPTmUWnbE/gMsPklk4sH6phiMAMzOzEj2PnkVDQ8aSIQ2xN9Pj8923yMwrVK2/tbpIiQ3SHqtWvooJDAzE2xYUMrnkpaoCO69F0fr7kyw5HkLTmhYc/LQVCwc2KNMoeSnmEveT7zPEbUhldV3Nv4gyjUd9+/YtdVNT+cTGxmJjY1P5Mcx/IyEn4Y0xHjk6OlJNXxL6e5L9pMJtDB48GAMDA6ytrVmwYAEaGhrs27ev1PItXC15t5kT6y9GcCm84saqKqN2F+nv3o8kfQ73t1++zebjwdgejs95+bbUqPm3IQTE34PQ108wU00FUSql8JL1PaTJ0ofHOOgvTS779evHiRMnePz45SYHYWFhbNy4kf3791dGj4tj7S5pMo05A9MeQvcFkjZS6LHKP9a/lOjoaM6smAzAiO/34u1dtgYiwM5r0Rhoa9LFXTVdjfX31nM08igTGk2gpX3Ll+rvm4CzuTMAEUkRZZarbqZP29pW7PJ/RExqznP7r169SqNGjdDVLVl3xcXFhcOHD7N48WJkMhlOTk6vznhUzQ3sGsOt7SXvT3sMyxrB5rfh5hZJL63rfPjoBPwvmoxBe2k0/TA+/caxZs0a8vLyiIiIYOzYsdSpU4fhw4cTGhpa9ecw4FdJvuDwlPLLCyHJIwQdlhK4ZCdLiQEur6LG0RGwsJZk4D79vXTOl1bAiW+kkN21HbHICmH6iTxq1Cw9CuNcaAK7/B/xSTsX+jYq2xtKFeMRgLGuFj8MbMCjlBy++T2w/PMESf4B4PR81cpXMRcvXqRZdU0KLOo+L0tRAreiU/ly313q2hpz8NNWrBnhhae9Sbn1Vt9ZTTX9avRx6VMZ3VbzL0Odi/s1IjY2tkjorypJzEnEUv+/q3f0FG1tbZycnF7KeGRkZMSSJUv4/vvvsba2xsPDg6tXr5ZZZ3p3N5wtDJi86xap2a/Jyq9NfTC0kbIA1epSOalFtfWh2VjJvTqhkjyt1Kh5XRFCykZ4eyf8NgZ+qCOFC23tD5EX/uneqXlRspJgS18pRbV7HxhzFuwbc/ToUezt7ZkzZw5CCI4dq5ghJjc3l5UrV1KnTh0+++wz/P39AYpCoKsMXWPJ28HACm6XMmF9A5k1axb93DTIs/TEs2X5GW3Tcgo4FBBD74b2GOiUH+4enR7N0htL6erclQ88P6iMLv/nqW5VncLMQqLTS/YoepbRrWuSkJlHmwWnmLjjJncfS5phhYWF+Pv707Rp2cLK3bt3L9JudXJyIjIy8qX7rzINh0F8gGRIeYoQpMeE8WRFD0R2kpSAZOoDGLJVkheo7gVyHWbOnMmjR49o1qwZo0ePZteuXSiVSho0aMChQ4eQyWT07NmTpKQqXqys3UXyiry1VUqikptWetnT82FzX9gxFFa3hgU1YJ4N+E1DqakjjUEz4uD0d3BgHBz9n5QBOOgQyDT5Ja0t+yMNMDMrWZOsUKHk24P3cTDXY0LH8kOmygtbexYvZ3M+aefCTv9oNlwo26gJSEljvEdJ1+VJkErHqErOnDqBt70cHZfyjde5BQom77pFNSMdflHRaATgH+fPjSc3+MDzA7Q11TI2byKqC8CoqXJiY2NxdHSs0mMIIUjIfjM8j3r06IGPj0+R8SguO+6F2nnWFbpJkyYcOnSozOwgBjpylg5pSP+VF5n7eyCLB5ctOvdKkMmkkIi7v0Hv5ZWXNaPeIPhjlpTWtbPaA0nNf4zUKClTTmKIJByf+ufEX88cXNpDzXZwbKYksOys9jT4V3L4c3h4CXotk5IUyGQUFhbyxx9/0K9fP2rVkiYnjx49Uqm59PR0Vq5cyZIlS4iPj8fAwIDNmzcXvS9eiceDplx6Nl/9RVr116+EBA7/YkJDQ7l6aBO/jjWAJmXrHD3F99ZjcguUDPVRLfTs9KPTKIWSSU0mVa0GzX8ICwsLChILiDeKL7dsC1dLzkxpx/oLkey4GsX+WzG0crXkQ08tsrOz8fHxUfm4zs7OXLlypdxyuQUKdlyNolApsDDUxsJABwtDbWpVM0JbXoG1d8/+0ntiUx/pnZH6EBLDMM5LwxiYGeDIZ2NaYfk3jbJr167x008/MXbsWObNm4eVlRXz5s0DoE6dOri4uLB//346duxIv379+OOPP6pWk7btdMn76NQ8OLcYPPpKz0zHP4WZc9Ok7Gw3NklaT14fQNqjP7fH4ODDQ1lt6rq7S+ULcqTslLomoGMiacEBuzt1ombNklPM34hK4f+OBBEcn8Gq4Y3R1So/UkNVz6OnTO5ch+C4TOYeDORhcjafdayFqX4Z17X155L23Ym5MHSbysepbJRKJQl3z6DniaR/Vw6/XojgQUIWmz7wwURP9VDpNQFrMNc1p1+tVyOgrub1Q208+gc5cOAAjx8/5pNPPgEgJiam3NWTlyU9P518Zf5/OtPaU9auXQtIBjMdTR1iM2Nfuk0vLy82bNjAo0ePytSmql/dlA9b1WT12XBGt62Jm035KYEri9DQULp06YK1tTVeXl54e3vj7e2NW+dv0OgwQ3pRVxZG1lK60js7oePXksi3GjX/RnLTpUF9ykPpb8wtuLsXhELa79QKWkyQBmU29YsGuiQEw5VVUvYto9J1F9S8hsTelrIItf4CmvwliH316lVSU1Pp1q0bOjo6WFpaEhMTU25zCoWCxo0bEx4eTufOnfnf//5HXFwcw4YNK9JNqnLPo6c0HAqXf4YD42HgepVCGP6r+Pn5MbyeHCHTRFZvYLnllUrBpksP8bAzpp6Kq/HnH5+nhkkN7A3V2UdVxdLSkvzEfJIdkssvjBS+NvMtdyZ0rMX2q1H8eDyEJzGSBk9Fxs5OTk4kJyeTkZGBkZERAIsWLSInJ4eZM2cCEPYkk7FbrhP6JPO5+tbGOoxqXZPhzZxUMl6gbw7vH4IzCyUBbPMaUG8A89fu5epjJYfvhJA4cyYrV64sqlJQUMCoUaOwtrbmu+++w8TEhHbt2nH8uBQmXbt2bQBatWrF+vXreeeddxg1ahQbNmyodOPl8ePHOX36NLNnz0Y+dAfE3JQMRAF7JDFtuS4U5gECkEHLidBxlvSOtG9SvLH79//6t5aeJDr9DOnp6Zw7d47x48cX+zzsSSYLjwZx9F48lobazOvrSVcP1cJJK2o80tSQsWxoQ745eJ+NFyPZd/MxkzrVZlhTR7Q0SzAaGlhISQ5OfiPp5jlWPMtZZXD37l28LTIBXSmJQxkkZeax4pSUHbpNbdWdCe4m3uVizEUmNp6Inlydef1NRR229g/yww8/MGHCBKKjoykoKCAhIaHKw9aeika/CZ5HT5HJZNga2BKTVf7gvzyaNJFehNevXy+37Mdta2KoLWfR0WCEEBU+VmZmJsOHD+eHH35Q2eVWCMH48eNJSkpCR0eHjRs38t577+Hh4YGDswvfLf65wv0ol4ZDISNWLZyt5t/JxZ/ge2f4PwdY1Qp2vgNHv4SQo5IY8kcn4bM70uDfZxTYNfzLcATS6qqyUDIglUV+NlzfCL+0l1ah1fyzCAHHZ4OuKbT4tNiuo0ePoqGhQadOkmCrnZ1diZpHOTk5+Pr68uSJFBIdEBBAeHg4K1as4NixY7Rv357OnTsjk8lISkpCU1OTJ0+ekJ2dTXRyNkFx6QQ8SuP6w2SuRSaTW6CovPOzqSdpHwUfAt9Pyy//H+b82TO810gXmWsnKTtpOZwIekLok0xGta6p0kQ8pzAH/zh/Wtm3qozuvjGYmZlRkFRAuiy9QmMkEz0tPm7rwugWDoRk61GtUemeKiXh5OQE/OUFuGjRIqZMmcKSJUsQQhCVlM2wNZdJzMglftfXtE7w5eTnbdn9cXOWDmlITUtDvj10n44/nOG3G49QKlXou30TGLZDSn4y8nfC647jywNRtH3ncwYPHsy2bdvIzs4uKv7jjz9y+/Ztli9fjomJZMDs3bs3ALa2tsWyyg0bNow5c+awadMmvv/+e5Wvg6qsWLGCefPmMXz4cAoVCilhSq8f4Ytg6LNCysjW5gvoMBNGnZC80DWen16mpKRw69atMo/l5+dHfn4+b7/9ly7ntitRdFlyhvOhiUzuXJszU9rzTlMnlY1kZmZmZGVlUVBQoPI562vLmd+vHocmtMbd1phZvvfovvQcDxKeNyYCkoSDoY3kif8C4/3K4NSpU/SqLSff3A1MyjZi//BHCDkFCv7Xw61Cx/jp5k8YaRsxuM7gl+mqmn85auPRP0hoaCgKhYJly5YRHy+57Va18SghJwHgjfA8ehZ7Q3seZ758NoQGDRqgqalZpF9RFqb62nzczoXj958w+JfLhMRnVOhYX3/9NVu3buWLL76gWbNmZGRI9QsLCzlz5gyTJ0+mdu3afPjhh4A0EPrqq684duwY3377LWfOnCE1NZXAwEB+/fVXrK2tmTdv3gsZssqkVhdp5SnoYOW2q0ZNVZObBqe+AwtXKZXywA0w6hRMjYDpD6H791C9iaRrUBoWLlBvIFz6GZLCpc8UhZAQAvd/l7Jf7f0IlrjD7xMkr6aLy+DBmVdyimpK4eZmSdS13XTQMy22y8/Pj6ZNmxZpbtjb2z/neXTx4kXc3Nzo06cPzs7OrF69mgsXJO2r7t3/0tSxtLSkSZMmyOQ6uL87B+uh82n+/WlaLzhFtx/P0Wv5efqvvMTAVZfovOAY4aVNTl6EpmOg2TjJQyCj/NCg/yJCCGqlnsbGQEjaMyqUX3k6jOpmerxVX7Xx2LW4a+Qr82llpzYeVQS5XI48S45CQ0FKnuqeISAJ0M8Z1ob8hEj0Ok9g+t4A9t18xN3HaeUaYZ2dnQFpzLRmzRqmTJmCjY0NKSkpXLr7gGFrL5NXqGRiAxm5ETfY8usvBF07i7ezOX0a2rN9dDO2fdQUMwMtJu+6Tc+fznMmJKFCYytfX19AMgh9+OGHpKens3fvXkDKvDxr1ix69+5dLEHRU+NRnTp1nmtv5syZDB48mK+/W8TPv53iXkwayVn5lTLeCw4OxsTEhJ07dxbXftM2gEbvQNd50GGGZECyb4JCoWDGjBksWLCAK1euUFBQQF5eHt26dWPYsGGEh4eXeqz9+/djaWlJixYtAIhJzeHbQ4E0q2nB2antmdCxlkoaZM9iaio931VdhH2WurbGbP2oKWtGeJGQkcdX++6WfE21DaR3SfRlCD5S4eO8LPn5+fju2EALBzna9coWsb4dncr2q1GMaO6EazUjlY8RkhLCxZiLDK87HENtw5ftspp/MeqwtX+I9PR04uLi0NbWZvXq1XTr1g14hcajN0Aw+1nsDO0ITFIxe0IZ6Onp4e7urpLnEcDYti6YG2jzf0eC6LH0HB+2rsGEDs+//KZOncrGjRuxs7PDzs4Oa2trNm7cyMcff0yfPn3o2bMnQ4cOxcLCgoMHD5KcnIy2tjb29vZs3LiRKVOm0Lx5c1JTU+nRo0dRKKSmpiZ169alTh03fovS5klcPlN3XWdqj3pYGVVSGIO2gRS6FnRIWulW6z2o+ZcQd2wZNgXZ0vfWvvGLN9T5Gwj2g22DwbwmRF2CvPS/9ps4Qs320gqtXSMpjfrvE+CTy5LrvppXhxCSUe/IdHBuDT5jiu1OSkri2rVrzJ49u+gzOzs7bt68+UwTgo8//hiAXbt2sXTpUqZPn0779u2xt7cv8mx4SofO3Yiq2Zt06wYQdRfd1EgenD2IS3VrdLXlyDVkBIZHEddpNP1WXGTbqKZ42FVSeHGT96TwtTs7oeWEymnzX0TMqbXMbZFPpG49nOv2Krf8xfAkbkSlMqe3B/KSQlRK4GrsVXQ0dWhi06T8wmqKYVBoAEBMZgzmuqprc23ZsoWMtFRW93TgtrI6e28+Zqe/JLytLdfAx9mcVrUsaV3Lkro2xmho/DUuefr7XL58OUePHqV79+588cUXdB8+ltG7gtDR1mbzhz5cOrQTAAcHB0aNGsW9e/eKDBEtnTmLiwAAIABJREFUXC3xHdeK3+/EsPBoMCN/vYqbjRHvt3SmT0P7csPZfH198fT0pGbNmtSoUQNXV1dWrVrF8OHDGTt2LJqamixfvryYd42TkxMDBgygefPiIUkxqTmcD0vEtPsk7ByGsvBqNguvSp7gpvpaeDmZ0b9xdTq5W5ccdlUGhYWFhIWFMXLkSNasWUNQUBA9evQos86WLVuKtJkADAwMcHR05P79+8hkMtavX8+3335brE5GRgbHjx/n0KFDDBgwAE1NTbLyCvlyXwBKIfi+f30sDF9szPp0ESAlJQUrq4pHXchkMjq7W/NFl9rMPHCPY4HxJYfMNXoXLi2XPJcfXQWLWuDaEQytIcQPEoJAQw4aWpLEg4Zcev/bNQbLWi81dv7yyy+xy76HpoYe1O5WajmFUjDzwF0sDXWY1Ll2hY6xNmAtupq6vFP3nRfup5r/BpVuPCooKODLL7/k8ePH5OfnM3bsWOzs7Jg1axaampo4Ozszb948NDQ02LVrFzt27EAulzN27Fjat29f2d15bXmaWnPs2LEsXbqU7dulrChVbTyKyZRWT230VYsV/q9gZ2hHSl4K2QXZ6Gvpl1+hDJo1a8bmzZvZu3cv/fv3L7OshoaMoT6OdHG35nu/IFafeYDvrRhm9XKnq4cNMpmM+Ph4li5dSv369bG2tiYmJobr16/j6urK/PnzMTU1ZdasWcyaNQszMzPeeustevfuTdeuXYmOjsbDw4NevXqRmprKpUuXaNaseLx1aHwGP58KIyDHlMKMe+y/Hc+FB2mse8+buraVpMXk9pbkeRRz4/kYdzVqXkNiY2JI8lvAo0LB0ulL2LRp04trRRjbQu9lcH4xpEWDx9uS5oCVG1jWBp2/rdK99SNs6g2XV0him2peDULAvo/hzg7p3vRdVSy8IiMjg/feew8hBD179iz63N7envj4eAoLC5HL5Rw8eJCAgAA2bdrEwIEDMTMzo3Pnzuzbt49BgwYhk8kQQhAUl8Hp4ARO6bdGr0YBU9raMr5HL7IMDZHL5dy4noTGn8fv3r07Uad/xKDvLIatuUI3DxsGeTvQxKnkjEMqY1UbHJpKKbFbfPrvN+4rCqQw6bTHkhBvRiyYVIcabSXtkWd5fINq577EP0aJyWc/l6vJJ4Rg0bFgbE10GeytmlA2wMP0hzgaO6Kj+ebqSr0oJjITsskmKj0KT0tPlevt3r2bNm3aMKRfb4YAc/sqeZiURXBcJjeiUjgfmsj/HQni/45AdTM9fn3Pm9rWkpeFtbU12tra+Pn50bp1a1Zt2Ibf3Vish3yHTJHPnrHtqGFpwOawMHR0dNizZw8tWrRg0qRJrF+/vqgPGhoy+jS0p5unDftuPGbDxUim7Q3g/44EMcTHkbHtXDDWfV6IODk5mXPnzjF9+nRAMk5MmjSJcePGMXjwYI4ePcrSpUtL1NXcvXs3IGUD/OlEKCeDn/AgQdJ9sjTUpqFxFn5r5rNx+26yhA7BcRmcC03g+P0bWBvrMMTbkaE+jtiY6Kp0nSMjI8nPz6d58+bs2bOnTK8hkLJMzpw5E29vb3x9fTl37hxnzpzh/PnzzJ49m5MnT7J+/foi4/zPP/9cVK6goAATExPGjBnDwTsxfHfoPjFpuczq5Y6D+YuP2581HqmKEIIHDx7g4uJS9NlQH0c2X37I3N8Dae5i8fy91ZRDl3lS6PuFZX/pJRpUg6xysj3X6gqDt4C84oLnBw8e5OZvP7LjHWswNATb0pP07LgWxZ1HaSwd0rDE72ZppOamcjTyKN1rdMdEpxJ1U9X8K6l045Gvry+mpqYsXLiQlJQU+vbti4eHB+PGjaNt27Z8/vnnnD59mnr16hVNwPPy8hg2bBgtW7as2kwBrxEhISEADB8+vOjhCVVvPApPDcfWwPalDSj/Np6KWMZkxuBq5vpSbc2dO5eAgAAGDBhAy5YtGTlyJAMHDixakSoJC0MdFgxowCAvB2bsv8vHW27Qro4Vc3p7sGHVKvLz89m6dWuRCOLfmTlzJv369cPNzQ25/K+frbu7O15eXvj7+9O9e/ciw9HDpCx+vx3DwTuxBMVlIJNB/zp6LP5+GrO2/86GB4L+Ky+yeFADOrvboKnxkhOK2l1BpglXVkPf1f/+CYqa/zwPLh2gZTUNfgxzZsvWLQwaNIhevcr3TCgVz37Spgo120KdnlLGGkNryMuAnJS/NkWBFErn/SEY2714n9QUJ2CPZDhqOVHS59D861kaFRVFr169uHfvHsuXLy/StwPJ80gIQXx8PHZ2dsybNw9nZ2eGDBkCQIcOHXBwcCA6OhrrJl2YvPMW58ISScjIA8Db2Yxlw+rQuLoRn8pkZGZm0qtXryLDEUCLFi04OmsWd3Z5sOR0NH734vjt5iPm9PbkrQa2FRroP0fDdyRPt9jbkmbXv5G7eyWtsIxYEMrn9+uZw/uHpdV+DU3JiLttMKn5ct4/psfdXxqUe4jd/o+4GZXK/H71VBNC/pPojGgcjas2U+5/FSsNKx5mPeRIxBF61Czbo+Up9+7dIzAwkOXLlxd9pqWpgWs1I1yrGdHzz3DD+PRczocm8r1fEEN+ucyaEU1o4mSOhoYGbj7tyK/mjknbvrRdcgEhQJYRh1vCDWpYSqFi4eHh1KxZEx8fH6ZNm8Z3333HgAEDihmWAXTkmgzxcWSwtwOXHySz8WIkq8+Ec/ReHL+864VrteKLB4cPH0ahUBSFoQF8/PHHbN26ld27d+Pt7c24ceNKPf/LD5L4fNdt4tJzaV3LkmE+jrSqZUkdayMOHTrEgei71NBKL8pAp1AKTgU9YcuVhyw7GcryU2FM7lybT9q5lLtgEhwcDPyV3S0sLKzM8ps2bSI6OpqNGzdiY2PDwIEDGTjwL5F6MzMzPvvsM/z8/Hj48CETJ07Ew9OTTyd9TpsOXbCq6c7CE+Fci7yJu60xPw1rRBOnl8sW+SJha76+vrz99tts3bqVYcOkcFe5pgb/178+A1ddYrbvPSb4mGJubl5Mf4o63WBmorRQEX8Xwk/A4+vSAmvdXqBUSBqJT7fcdLjvK2Ww2zkcnFpIHkmaz3gnGdtLi7IlZM2MCbyM2DGcEyMMUJpaQJ/lJepNAUQkZrHAL5hmNc3p3aBi44rzMedRCiXNbcsW4lbzZlDpxqNu3brRtWvXov8/DZtJTU1FCEFWVhZyuZw7d+7QqFEjtLW10dbWxtHRkaCgIOrXr1/ZXXotCQkJQSaT4enpSYMGDbh+/ToymQxr66rN1hORFkFNU9WFBf8r2BpIg4mYrJc3HtnY2HDy1EnGrRnHpR2XGD16NJ9++ilvv/02S5cuLfMeejmbc/DTVmy89JDFx4LpsuQsGafu0LNnz1INR0DRd6UkPvjgA/z9/YtWsdZfiOCbg4EoBXg5mTG7lzs96tlSmJnMYoCUaA6Me59Rm/z5eMsNjHTlNHEyw9vZHJ8a5jRxNCvm4q0S+uZStonzi6Uwth4/lPoCU6PmdUAW4odSCIbN3covNwYxefJkunTpgo7OK/Ie6DwXVjaHA08nCTIpE6KeGcg0JE++O7tgpK+UnUfNiyME3NoqhapV93nOcHTlyhX69OlDTk4Ohw8fpkuXLsWq29tLiw+PHz8mJCSEK1eusGLFCrS0JINOdoGSDu9+xpHQLHyTbTDPS6CVq2VR2IytyV+hiba2tsTExNCmTZtix2jRogVCCGJC7rDuvS6kZRcwZos/X+4L4Kv9AbhYGdLIwRRvZ3PebmRfsVThbj3h98+k0Il/o/GoMB+OfgU6xlJmPJPqkiCsiYNkfE0Igl0j4deuUlkjG2nipchj2GEt3LxalDlJzswrZO7v99jl/4jGjqYMaFJd5a4phZJHmY9oad+yMs70jcPKworga8GcMThDdEY0Dkble3zt3r0bmUxWrue3tbEu/ZtUp7GTGe+uu8KAVZdoXcuKlKx80v4M4ZRpaDCpU2061q3G1NErCQgLo2PHjvTo0YOwsLAiz5Ovv/4aX19fRo8ezb1795DJZLz99tvMmzevSJ9HJpPR3MWC5i4WXHmQxCdbbzBo9SW2ftS0mJe3r68vtra2eHl5FX2moaHBr7/+yvjx41m8eDGams8bL+PScvnl7APWX4zAyVyfPR83p5Fjcc/EpyF5kZGRRcYjTQ0Zndyt6eRuTVRSNguOBrHwaDCXHyQxsVOtEo0zycnJHDlyhNhYKUvxU+NReXqfFy5cwMbGptRIkrZt22Jvb8/8n9eTaOaO86Sd5Ogaslcp2HsqG075Y2mozf/1q8dAL4eXX9jkxTyP1q1bB8CECRPo3LlzUbhbY0czxrV3ZdmJULat/pFBHsYsW7aseGWZTNps60sbMGbMGHR0Lj5f1tgOqrlJuqHHZ0Po0ZI7pGUAHxwB2z+N4AU5KM4uxuL0Qjo4KUls8AmWb80Grec9yp5k5LLsRCg7rkajI9fgmz6eFfayPvvoLOa65m/k/FHN81S68cjAQIpfzszMZMKECUycOBGZTMbcuXNZuXIlRkZGNG3aFD8/v6IUmU/rZWaWLxSZl5fH/WdTPf5LuXbtGra2tkRERFCnTh2uX7+OmZlZuVb9l0EplISnhlNTq+Zrcw1zc3NfSV+y86UsFjfCbmCV8fKZ5kIzQ7lmfA2t0VoMHzuc3FO57Nm4ByMjIyZPnlxu/RYWYNVanwnb/NFu/QGGlgXcvRf4Qi/K1q1bs3fvXiwsLZm06Tz7AtNo7qDP2KaWWBnIgVySHkcQkh6CRTsLbt68Sbt27fimnRnnH2pz70ku9+JSOR0s6WE5mGgx2tsCL/sKeqfZDcTKLQFL/19JTUog1mt6uWECr+r+q3l9+ae+A1YpN7iRroFBniaTJk1i9OjRfPXVV0UC9KqQlpbG6dOn6d279wuFvMl77EamLEChbYxSblDs96KbHITDmQmItd2I7LSGwv9QhsxXec+10yOw8V+AQcJNsi3r87jhlxSGhBbtP3/+POPHj8fa2pq1a9fi4ODwXN/y8iQPoitXrrBt2zYsLS1p3rw5gYGBHA/PZK1/EukKN4xdFHzkbUHPOsZ/PsszSY3JJPUZrW0rKytiYmKeO46JiQkaGhocOHCgKFzlq5Ym3HHRJjghj6DEPI7ejWH39UesOR3M9DbVsDNW3RvJybIestu/EWldtphqVfMi99440g/7jFiiG35Bpu2fRpoCIFEJibGACdqtFmNzfSF5JjXRT7yDdkokt+t9zfFbnzG92zulHvP+k1wWnHvCk6xChtQz5Z2GZoSFBKvct+T8ZPIUeWhlaanfZSrw9/svk8mIPRKLa3tXVlxcwQjHEeW2sXnzZry8vEhJSVHZIPBjN2s23UzmTnwaBloafORlTrsahljoy4FCSIvB3s6Ow4cOERwcTFhYGAkJCTRq1Kiov7NmzWLIkCFMnDgRT09PTp8+zXvvvcfevXuLeYQDGAMLulgz9WgMg1dd4IfudlQ30SY/P59Dhw7Rs2fPIq+eZ/l2wRLis5VEnr9FdoGyaLv+OIczEZkIoFstI0Z5WaCbFcf9+3HPXV+Aq1evUq9evRKvxScNdamua8G228n0X3mJ+ja6jPa2wMX8r4WTiRMncuzYMezs7DAzM+PJkyeYmJjw8OFDAgICnjvfp1y8eJE6deqU+FvIyldyMDAd83cW81hmgFAUUEOeRlMPe/S1NNDXkmGorYl3dX0MtLMICQ4q7XZWiMTERADu37+Pv78/Fy9exMfHpyiL3d9JSkriyJEjdOzYkTNnzvD++++zcOHCov1d7AQnDbO56z2Q4yFHy/3dJyQksHbtWgB69epF9eolGKfNO8OA9siUhciEApmyEEQhMqUC7Yxo7K7MQWwZTKLHKLQzHmLy8Cha2XHsvl9AerMptHYbQkJYRLEmcwqU7ApIZd/9NAoVgm61jRlW35TC5EfcT1b9+imEgrNRZ/Ey8yIqMgp5QsVNB+qx/n8MUQXExMSIvn37it27dwshhGjWrJkICQkRQgixZcsWMXv2bHH8+HExa9asojqffPKJuHPnTrltBwYGVkWXXzne3t6ic+fOQgghNm3aJABRv379Kj1mdHq08NzgKfYE76nS41SEV3U/FUqFaLypsfjh2g+V0t6JhyeE5wZPMfHkRNFoUyPRaFMj4T7OXfQZ0EflNmbMmCE05Vrik9VHhdO0g6LV9yfE8LWXxRe7bolFR4PE/puPRE5+oUptpWbli9GbrgmnaQfFrAN3RaFC+VyZiScnCs8NnqL/mP4ltpGcmSf2Xo8WHX84LWr+75DwvfVY5XMpQqkU4uQ8IWYZC7F3tBCFBUJkJgrxY30hfvIS4uwiIXJSi4r/V37Pal6cf+Q7kB4rxCxjsXaEW9FHvXr1EoaGhiI2NlblZgYPHiwAce/evaropRCPbwrxra0QK1sKkZteNcf4B3gl91yhEOLEt0LMsRBivqMQ/hukz54hNjZWWFpaivr164uEhIRSm4qLixOAGDFihADEwoULhRBC7Lj6UDhNOyj6rbggzocmqPS8Hjx4sDAwMBD5+fnP7WvQoIHo1KlTqXWVSqU4fCdG1JvlJ9xnHhH7bjwq93hFnFssPZdTK1CnCqjwvVcqhVjVRohlTZ67f6WiUAiRnSy2bdsmAHH9+vUSi22/8lDUmH5QtPy/E+JqRFLF+vUn/nH+wnODpzj/6PwL1X/T+Pv9nz9/vgDExBMTRfNtzUVWflaZ9e/evSsA8fPPP1d637Zv3y4A4eTkJAABiJ9++qlYmQEDBohq1aqJwYMHC7lcLgCxfPnyUtuMSMgUjeceE62+PyGik7OEn5+fAMShQ4eEEEIkZeaJNWfDxaSdN0WHRaeE07SDJW7uM4+IOb73RFRS2ddHCCHMzc3F2LFjyy2XlVcg1pwNF02++UPUnXlE7PGPFlFJWeLosWMCEJqamgIQLVu2FEII8euvvwpAhIeHl9heZmam0NDQEF9//XWxzxUKpTgd/ES0mH9COE07KN7+6ayo1nKA0DOzFsnJyeX282XJzs4WgGjXrp3Q19cXgBg6dGixMkqlUuTm5gohhFiyZIkAxN27d8WcOXMEIHx9fYuVHz1mjLDsPVU4TvUVp4Piyzz+okWLiq7nhAkTXuwkov2F+MZaeobPMRcJi5qJtk6aYsyYMSUWz8orEP1WXBBO0w6KcVuvi4iEzBc7rhDietx14bnBU/hF+In4rLLPtTTUY/1/H2Xds0r3PEpMTOSDDz7g66+/LsoIYGJigqGhFPNbrVo1bty4Qf369fnxxx/Jy8sjPz+f8PDwMsN2/ksIIQgJCWH48OEARTo1Va139CDtAcAb6XaoIdPAztCOx5mPK6W95FzJbD/NZxpTvaey8vZK9in2EX65bDHBZ7l69SqeHu78PLoLXW495tCdWOLTcwmJzyAhIw+lAHMDbTq4VcPFyhClEOQVKMgpUJBboPzzr7TdeSSlZZ35ljsftio5xCU4RVrliqgWUeJ+MwNt+jWuThcPGz5Yf40JO24Sm5bDqNY1VfeqkMmg/ZdSNolT30JmnKRPkR4D9l5wYq4kJPjWEtX1YdSoqWRE0GFkwBOzv3RtFi9ejLu7O//73/+KiaKWxpEjR9i5U8rGExoairu7e+V31K4hDNoE2wZJegjDdr+QoOYbSeA+OLsA6g2ErvPB8HnPrbFjx5KZmcmOHTuwtCw9A6mVlRVyuZxNmzZhZmbGmDFjuP4wha8P3KOVqyUbP/BR2Wt05syZjBgxoijk7Vm8vb05cOBAqXVlMhnd69lS38GUSTtuMXHnLbLzFQxrqoLeTp0eUljErW3QdopKfX0tCD0GsbckkXlVQ6E1NEDPjHPnzmFkZESDBs/rHeUXKll0LBgvJ3PWveeF0QtqSkVnSBm+qhupHuqm5i+e/u66WnXlePRxDj44yKA6g0otv2vXLmQyGf36Vf74oXfv3ixbtowuXbrg5uYGgKtrcZmDYcOGsWfPHnbt2sW7777Lo0ePmDlzJkOGDMHCwuK5Np0tDVj3njdDfrlEmwWnMChMx/6jlXx/V5dvbp8gKTOffIUSG2Nd6tgYMdDLAWtjHQy05RjqyjHUkTYbE130tVWbsjk7OxMZGVluOX1tOR+1rknvBnZ8sPEan+++Le1QFOL08Rpq2xhzcfcqXNxqARSF8IWFhVGz5vPziDt37qBUKmncuDEKpeBqRDJH7sbidzeOJxl5OJrrs6i7HQPaNmKH5WNSUjoUhZRVJUq5Eh0dHU6fPk3t2rVp2bIl69evZ/LkyUWhg+vWrWPatGlERkby22+/0aBBAzw8PKhVqxZ79uzh448/pk2bNpiYmKBUKvE9cID0tEy0LBz4aKMmnT2s6deoOm3rWBXLaCeEYOPGjTRt2pTatWuzbt06Zs+eXfHzrt4EJgdCbipPsgTujZpib+/BkiVLniuaW6Bg9Kbr3IxKYcU7jelR7+XmlmcfnUUuk9PCrgVG2kblV1Dzn6fSjUerVq0iPT2dFStWsGLFCgC+/fZbJk2ahFwuR0tLi2+++QYrKyveffddhg0bhhCCSZMmvTqtiX+YgoIC8vPzadxYSg3t6uqKtbU1NWpUra7Fg9Q/jUcmb57xCMDeyJ7ApEAKlYXINV7uq5+UkwSAua452prazG05l5O3TxJnGYdSqSwmhFoSQgj8/f3p21cSZuzT0J4+De2L9hcqlFyNSGbr1SiO349nz/VHRfv0tDTR1dL4868mOlqa1LExYmpXN+pVL9kNN6sgi+iMaDTzNcmrkUdUelSpAp+//LyMfg7OWBo58d3hINJyCpjS1a1C14e2U0DPFE5+C7mp0GMR+IyCmJtweArseR/iAsC2bM0CNWoqncJ8FGcWERCrwKzhXzolrq6uTJo0iQULFjB27NgivYiSyM7O5pNPPqFGjRpERERUabgxtTpJIpj7x0pbvzVqPbFyyM3NRfP6VrSM7aHvLyVer7y8PA4ePMhnn31G3bp1y2xPQ0MDW1tboqOjGTl+KtN/D+XQnVhsTXT5cUjDCoUbe3h44OHhUewzIQSFohA3NzfWrl1LcnIy5uali8Tam+qx5aOmjN7sz1f7A7Aw1C45dfSzWNYGl46SUT87ETp/8/obIpVKOPENmDlDo+EVrn727FlatmxZon7MscA4EjPzWTTQ5YUNRyAZjzRkGtgZqIXtX4SnBhfrQmvqmtdle9B2BtYeWOKClRCC3bt307ZtW2xsKj9jsL6+Pp9++ikADRo04Pbt28WybYGUFdHExIS0tDTeeust6tatS4MGDZg1a1YxAe9naehgyh+T2rLjWhQ/bd6HpakxDRzM0JFrYG6gzYAm1allXXmTcmdn5wqFCFUz1mXv2BbcjEpl9bZ97D9xkTY9+hNXoIPlW59zXib4cMM1WjiYgaa81Ixr169fByDfshatvj9JbFouuloatK9Tje71bOlc15rIcClZ0NNkA1XNtbhrjDo2CodRDoT/Es68efPo0qULBw8eZMqUKZw8eRKZTIafnx/JyckcOnSIy5cvM2nSJAC0tbVZt24dzZo1Y+rUqaxevZqrV68SFxfHqFGj+HX7LEbO38KVB8kcDojD0lCbnvVs8bA3wcXKkOBrZwgIvM/H363FzL4m3IplxvKtTBozEmNdLRRCYGOsq9oCrb456JuzZuU8kpKSOHPmDHp6esWKFCiUTNh+k/NhiSwcUP+lDUcAZx+fpZF1I7XhSE0RlW48mjFjBjNmzHju8x07djz32aBBgxg0qPQVhv8q2traBAcHF4lwymQyzp07V+ZgsTIITwvHQtfijU2zOLDWQCaensjekL0Mdhv8Um0l5yZjpGWEtuZfg29nbWdSnFN4+PghNRzKNgRGRkaSnJyMt7d3ifvlmhq0cLWkhaslSqUgr1CJTAY6co0X0lYJTZE0Puok1yHQJpALjy+UaDxSKpXMmjWLZs2acfToMb7SC+DnU+GY6GkxorlzhTLQ4DMKGgyVMk44NJU+s2sE7x2Cw1/A+cVUt70CLtsloWA1al4F/r8iz3zM9BO5zBheXIR+xowZbNq0iQkTJnDx4sVSjcBz584lMjKSM2fO0Ldv36o1HgE0HAYZcXBiDhhWg67fqTMalsEn7w1mda3TZDb+CMNS7uHdu3cpLCws8vwtD+sadchvOIgDBfXQDXrCpx1c+ah1TUz0KmZ4UCgV7Avbx5bALaTmpZKryCW3MBeFUGBjbYNJcxOCg4OLPLdLQ1uuwarhTRi8+hJf7LpNnU+NcLY0KL2CTAbDdsIfs+Dyz5Ihf+BGMK5aj+eXIfbsBmzjA8jpvpSlC3/g5MmTHDt2TKW6SUlJ3Lt3ryhT0t/ZdiWK6mZ6tKn1clpijzIeYWtgi5bmS2TDe4N56nmUlJTEsLrDmHlhJlfjrtLUtulzZe/du8f9+/cZP358lfdr8ODBREVFFQlQP0VXV5cBAwawefNmunTpgomJCWPHjmXlypWMHDmy2JguLCyM7Oxs6tevj4O5Ph0ss5i69Uu+2bCBkUMbVVnfnZ2dOXLkCEIIlceLOnJNHHXz2PP9JNq1a8eBKT1RKgU3o1M5EhDLkbtxnAh6QvVRqzn4IJPa9+OpbW2EvaleUYKVazduY997MlN+j6C2tSEzejamvZuVyh5TlY0Qgh+v/4ieXA9FEwUe8z3wbO+JsbExs2bNYvz48Rw+fJiePXty+fJlQHq3FxQU0KFDh6J2vL29mTx5MosWLWLEiBGcO3cOgEmTJrFmzRo88u+z6suJnAp6wtIDl9h0IRxRtECthdOk3RxJ1oLkdCx7TORQFhxafLaofQsDbbp52vBJe1fsTYsbg7Jz89DS1ERLS150Ths2bKBdu3bFFiEKFUoeJGYxY99drkYmM7uXOwO9yhefL4/YzFhCU0L5vMnnL92Wmv8O/8wvWk2RIOZTatWqVaXHy1fkc+vJLVxMXcov/B+lg2MHvKy9+PnWz3RMpfIXAAAgAElEQVSv2R1jbePyK5VCcm4yFnrFXZQbV2vM7ZTbnLp3qlzj0dOMFc9m2ygNDQ0ZetoVMNqUQHCyFLLW0LAhd9LucO3RNYbWHfpcuZCQEDIzM4mIiEBDQ8Y3fTyJT8/ju8NB/HwqnL6N7Bns7VAsc0iZ6BiC498mZ3Id6LUMbOpjeGQarOkIQ7eDZdX+BtS8wSgKIOgQXN8AD079P3vnHRbV8f3hd5depIkUUYpSLCh2sYu9xG6sUWOPNZrYYiwx9t4rmmBvsZeIxhorIkgRRUSQpogISC+78/vjfiU/QkeJKbzPs49478y5c8vO3vnMmXN4IbfmYrAvB/601KxcuXIsXbqU4cOHs3//foYMGZLLlJ+fH6tXr2bEiBG0bNkSW1vb0hePAJpPhaRouLtFyibV7OvSP+Y/kPDwcLSeX0CtmiaT93qwumMK2tq5g/97eXkBZHsAF0RSehbCZQq66YJhzWwY17oqxrrF85RWCiUL7izgUuglEjMTqW1cm7qmddFS1UJTRRO5TM75oPNYDLfAN9C3UPEIQFNNhc2D69F1w016bL5Fr7oW9K1fCUeLfMR4FTXotERaAnFqEmxvCd03gn3Hv6UYGXFpK5pZgvFrznH85Olsr2119cI9pm7evAlICSX+zAX/l9wOjmV6R4fiZxb9cxsTI6ikW7ZkraS8F48iIyMZ4DKANZ5rOPD4QJ7i0dGjR5HL5aWyZO3PzJgxg1GjR3Ew6CDl1MtRy7gWVfSroCJXYdWqVYwfPz474PKiRYs4c+YMgwYNwsvLKzsZUO/evfHz86Nnz54cOnSIkydPIpfL6dq1a6m23dramtTUVGJiYjAxMSlyvRkzZpCRkcG6desA6d2zvpUh9a0M+b5rdW4EvWHE2uM8UqnKyN3SO6ymqgxDLVXeJqaQVv4zVE1UGdnchukdHYo32fiRyVJmceLZCXzf+DK/yXyIhw3BG/ji1y9Y1HwRY8aMYf369cyYMYOaNWsSGRmJXC7n8ePHqKqq0rx58xz2FixYwNatWzl48CBhYWE4ODhQvXp1TExMePToEa9fvWTjrK84f/YsyOTM/HEFN32DCHqdxOBRE+jd2I4G1ob8cu4SoyZNY8L0OdRp1ASE4MGLOI54hnPAIwwH03Koq8p5m5zB26R0UjKVyBUZNHWoyJAmVrwOCSQiqxzdeo1llXsgwTFJPHudRGhsMpkKgaaanHX969CzrkU+V6Z4/B4pCWUtK7UspGQZ/yXKxKP/CMs9lhP6LpSp9ad+6qZ8MmQyGdMbTmfA2QG4+rrybYOSK+mxabEYaeb0FHNxcOHnuz/jEeXBCEYUWP/+/fuoq6vnmw3jYxMYF0g59XJUt6hOyvUUHpk8yrPce7fjFy9ekJWVhaqqKjuHNuDO81gO3Q/nwL0w3G6H0tjGiJ3DSh4nApkMGo0mLFUbq3tzwbUN9P0J7NqX9BTLKCM3QsDvq+Hedkh+DXqVwOV7pq+6hJ2dXZ4xKoYOHcqWLVuYOXMm3bt3z5GRRalUMmbMGAwMDFixYgUgLXe7ffs2lx9Hc+phFKmZCpwq6VOnsiFm+ppUNCh6rIoCkcmk2D1Jr+HSPClFudNf4/r/T8LV1ZXuDqq8Vhqw7cRN3MqXx8XFhc6dO9OwYUPWrFlDuXLlUFdXR19fv0jLxRedDSA2HQ6PaUojm5J5CN+MvMnxoON0sOpA1ypdcanskssrwNnMmeEXh/N71O+MZWyR7FYy1ObA6MZsu/6cAx5S/1zdXI9RzW3ok1/Kecc+YFIDDg+Bg/3BpKYUW8vYNu/ynwChVGCT9YwLwVkcOvZL9vaIiIg84638md9//x0NDY1c3r2BrxL55ogPdSobMKrFh4cKCE8Mp41lm8ILlpEnVatWpUqVKsybN4/u3bvTx74PP/n/RGRSJBa6fwyAhRAcOXKEli1blsqStT+joqJCQGoAqzxXZW/TUdPBsbwjY2qPoVG9P5Y1GxgYsG/fPlq3bs3kyZP5+eefiYyMxM/Pj8aNG3Py5EkOHjzInj17aNu2bYHx1T4G1tbWgOThXpB4dObMGSZMmMDOnTvJyspi//79zJkzJ9dSPZDen1vZV+DCN23YuXs/Z254Ev4uCzVjK2K19BAZKdhUrsj0wZ3p51IK8f+KSODbQM4En+FcyDnepL7B3tCeHrY9UJOr4VLLhanXpjL9+nRmNZrF0qVL6du3L+PGjQOkeFb79u3D2dk5O3P4e7S1tWndujXu7u7ExcXRo4eUtbJmzZqcP3+eY8eOkZGRwZo1azh//jybl/9AUlISq1at4tsv/pgIGNyjI8vnTufSziXM6H+JqVOnkpqaytfd+iKsGuH5Ig6ZDCpoKLl05yzJcTGgoYufRifGPpOyxpn2X8jxKFB5FYyVkTZVTXRpW90UWxNdGtsYUdmomJmSC+BGxA0q6VbCRr90w6qU8Q+j1MN1f2TKIrYXnxNBJ4Sjm6NY47nmUzclF5/ifn7/+/ei7p66IiwhrMQ2epzoIaZcmZJjW1ZWlrBfZi/abGxTaH0XFxfRsGHDEh+/uAw6N0gM+3WY8Pb2FhV6VBCObo4iKSN39oUpU6ZkZxkJCQnJtf/t/zKDVPnunBjpdl8o8sjqVhwCAgKEiHshZZP6wVAI36MfZK+Mfx6l2gc8vy5lJ9ndQ4jAC0IoskRaWprQ0tISEydOzLfanTt3hFwuFxUrVhTnz58XQggxc+ZM0aBBAwGIPXv2ZJedO3eeMGgxWFjNPCuc5p3LM2NOrfkXRP/tt8WvflF5ZkIsFplpQrh9JsQCIyGeXvowW5+I0rrnCoVCVK5oJlLmGAjl2W/F5cuXxddffy3s7Oyy+7X3HzMzM+Hi4lKozQcv3gqrmWfFkvMf1uavLn0lXA67iIys3FnW3qNUKkXNdTVFoxWN8tz/7NkzMX78ePH69es898cnZ4g9t0NEp3U3hNXMs+L2szcFNyozTQjvA0IsryLEchshbm0Q4lUpZQ78H0W99yE3fxFivp44+eMgUbNmTdGtWzcBiKtXrxapfsOGDUWLFi1ybItLThctll8RDRZdEq8SUovb9FzEpsYKRzdH4ebv9sG2/ivkdf89PDyEmpqa6NWrl4hKjBJOu53EJu+cGcz8/PxKLctafoy5OEa0OdxGPIt7Jk49OyUW3lko2h9tL5rsbyLC34XnKj937lwBiEOHDgk3NzcBCG9vb+Hg4CAMDQ0FII4cOVLq7fb19RWAOHjwYL5lEhMThYWFRY6sanZ2diI5ufBsbu8JDg4Wa9euFUuXLhXh4bmvR178//sfnxYvXH1dxWrP1WLZvWVi4Z2FYvbvs0X/M/3F0ntLi9wOIYTIVGSKiZcnCkc3R1FnTx0x+fJkcSn0kkjPSs9RLj0rXUy+PFk4ujmK40+PC2dnZwEITU3N7Ov252xx71m/fn3278fOnTuFEEJ8/fXXAhCtWrUSQUFBQggh3N3dBSAqVqwoUlJSctn5+eefBSCqV68u1NXVhY2NjQDE8uXLhRBCPHnyRJibmwtjY2Px8OFD0a5dO6GhqSUa9RgutGwbiWnLt4qg6ESRllm0bMwlJT0rXTTc11AsurPog22Vjd3/eRR0z8rEo385AW8CRP299cXICyNFpiLzUzcnF5/ifkYnR4uG+xqKqVenlthGi4MtxMI7C3NtrzG1hqi9o7ZQKPNPKaxQKISenl6RUql+DF4kvBAN9jYQS+4uEUlJSUK3tq5wdHMUHi89cpVt0aKFUFdXF4C4fPlyvjZ/vvlcWM08K2Yf9/0gASn7/qe9E+KnzkLM1xci6J85IC6jZJRmH6A8OFCkLbQQ/g89s7f99ttvAhBnzpwpsO7NmzeFra2tcHBwELGxsQIQ1apVE7NnzxZKpfTMK5VK8cXKX4TVzLPCsu9sIVNVExcuXBAxiWnibvAbcdI7Qmy5+kzMPeknmi+X0hQ3X35ZXPB/+WEnlpogxJamQqxyECIzvfDyfzNK655HRkaKRhYqkmDofzzHvqCgILF7927h7e0ttLS0BCC+/fbbQm0O3XVP1P3xokhKK/nvZ2hCqHB0cxRbvLcUWrb5rOai5k81RccBHcWyZcuyt797907UqFFDAGLAgAEF2khJzxLNl18WbVZdLdoA480zITY7/y8NdHkhnvxaeJ0SUtR7f3NhZ5E1t5yIeOorlEqlCAoKEoBwcytcqElMTBQqKiri+++/z7F9xM8ewm72eeEZ+nHSg3u89BCObo7iZsTNj2Lvv0B+93/16tXZae8/O/5ZrvezHTt2FJgm/mMTHB8sHN0cxbaH23JsD38XLprsbyJ6n+ot/GL8cuzLzMwUzs7OQl9fX7Ru3VqYmpoKhUKRLTpUqFBBpKeXfn+dlpYm9PX1xbBhw/ItM3v2bAGI8+fPi4EDB4r58+eLxMTEUm/b+/uflJEkBp4dKBzdHEX9vfWF835n0fJQS9H2SFvR7UQ34ejmKPxj/Itsd9m9ZVIf+3CLeJta8Pc7PStdjHYfLWrvri3W/yrdm2bNmgkhhDh9+rSIi4vLs97jx4+zxaPHjx8LIYR49eqVOH36tFAo/njnVyqVYvTo0eLEiRN52klLSxPm5uYCEKtWrRIZGRliwIABAhDjx48XpqamwsTERPj5Sc9XdHS0GDp0qFBRURHjx4/Pfv8obe5G3RWObo7iatjVD7ZVNnb/51EmHv1HiU+LFx1/6SjaHmkr3qQUMgP5ifhU93Prw63C0c1R3H95v9h1MxWZopZbLbHZO/cMWOvxrYWjm6N4FJP/7G1gYKAAxK5du4p97OISmRgp2h9tL5ofbC6exz8XQghR2b6ycHRzFD/5/ZSjbFZWltDR0cme4XV1dc3XrlKpFEvOBwirmWfFtCMPS/xjluP+pycJsbGhEGtqSmJSGf8JSq0PeBsqFPP1xaI2GgIQ9erVE+vWrROjR48WampqRXpRXrRokQDE4cOHBSB+++03IYQQL94ki01XgrI9PIw6jBeA0NXVFUZGRiIyMjKXrSyFUvzqFyU6rbshbGefE3eDP7BPfnpRGuw/zH92+e9Kad3z+/fvixnN1KXrkpi3d44QQowaNUoAYv/+/QXa8/qf19Hmq0ElblN6VroYcn6IaLC3gXidnH+b3jPx+4mi2qZqotqGasKyoaVQKBRCoVCIHj16CBUVFdG7d28BiNOnTxdo58qTaGE186zov/22iC6ql01CpBDbW0kC0tERQjw6KfXLH5Gi3Pt7h1eL+Fl64v4E0+xtaWlpAhALFiwotP77mf8LFy5kb7vx9LWwmnlW7Lj+8cSHA48PCEc3R/Eq6dVHs/lvJ7/7r1QqRdeuXYW6uroY+MtA0e9Mvxz7Fy9eLACRmvrhHmNFYZP3JlF7d+08352vh18XzQ82F45ujqLnyZ5i9f3V4v7L+0KpVIrg4GBRrlw5AYjBgwcLIYSIj48XhoaGYs6cOaXaZqVSKdY9WCfaHG4j2v/YXuib6osXL16ItWvX5rpu9vb2okuXLqXanrwICAgQUYlRov+Z/sJpt5O4/CL3JGVieqJofrC5GHtxbKH24lLjxPRr04Wjm6NYdm9ZoeXfk5yRLL4494Wos6eOGL9ivDh27FihdZRKpbC0tBRGRkY5xKKScPToUTFmzBiRlSWJ+1lZWWL48OECEKampuLRo9xjiPj4+L9MOBJCiDWea0SdPXVEckbRvdHyo2zs/s+joHtWlu/3X8ycm3OITolmTes1uYI7/9cZVnMYptqmrPZcXey68enxCESumEcAHat3BGDXb7vyrX///n2AfDOtfSyik6MZ6T6SpMwkdrTfkb1m2cHSAVmCDK/XXtllFQoFrq6uJCcn07NnT1RVVQkJCcnXtkwmY1anakxqY8vRBxH8dCv0wxusriMFb02IgJPjIS1B2p6ZBu9eQmywlLq5jDKKQMLlNSiVAk+c2LBhAzKZjClTpuDq6kqzZs3Q1dUt1EbjxlLQ1q1bt0o2da3psekmLVdeZaV7IFpqcma2tebtxa1YWFhw8+ZN3r59y/79+3PZUpHL6ORozqHRzlgaaTN23wPC36aU/ARt20GFanB7kxTb6UPIyoAHu+HuNgi6BBnJH2bvExEZGUkrKxVSdS1BN/8sWjNmzMDFxYW2bdvmWyY4Jolx+7ww1lVnaBPrYrdFoVRwJ+oOX1/9Gu/X3ixsvpAK2oVn9qpXtR7PFz0HBah2VMXT05MFCxZw6tQp1qxZw8GDB7Gzs2Pp0qUF2nFxMGFNPyd8whPoteU2YbFFeNb0KsKQk1B3MARfgSNDYUVVOPwFRHoVXv8DSU9PZ+/Mnjj5/sCbdFX0h/3xPdLQ0MDMzIywsLACbXh5efHll19iZGRE06ZNAVAqBcsvPKGSoRZDm1oVWL84BMcHU06tHCbaRQ9KXEbeyGQy3NzcqFChAg+vPyQiMSLH/piYGHR1ddHU1PxL2hMUF4RlOcs8351bVmrJhT4XmN5gOuU1y7P38V6Guw9nwLkBvFB9webNmwHo0qULAPr6+jx//pwffvih1NqrUCpY57WOnX47MdA04JXlK8xmm9H0i6ZMnTqVuXPnZpdNSkoiKCioyJkmPyZ+CX70P9uf0HehrGm9Js94Ybrquox0HMmtqFvs8sv/XfpO1B36nO7DpbBLTKgzgWkNphW5Hdpq2mxutxlbA1s8zD2o0rzwOGoymYz58+czd+7cfDOxvkp+xQavDTx8/RCFUgFAXFocP/v/zAavDVx+cZlXya/o06cP27dvR0VFCiquoqLCzp07+fnnn7l16xY1auSOG6Wvr49AZNstbW5H3aZOhTpoq328GEpl/DsoC5j9L+VV8iuuRVxjfJ3x1K5Q+1M352+HlqoWg6sPZs2DNbxJfYOxVtEDGMamxgLkKR5N+2oa+zfu50z0GdwXudO9e3eWLFmSo4ynpydaWlpUr179w06iAN6kvmHUxVHEpcfh2t6V6uX/OJaDgwNPPZ9y0+Am0UnRXDt3jR9++IEnT55Qv359evbsyZIlS3j+/HmBx5DJZExtZ8+TV4ksOf+YmhX1cK7ygSKlZWNovwB++wGeXQahhKzUP/brmkLbeVD3iw87zqcm4gGkxUkCQBkfn4xk1P0PcvxxJmt2HsLGxoZJkybx6NEjjhw5QocOHYpk5n02xJu+QdgMXsg3J55ga6LLd52r0bW2OZUMtRFC4N6jO4MGDcLJyQknJyfOnj3L9OnT87Spr63GT1825LONNxm/34ujXzUpWVYamQyaTITTE+H5NajqUnwbIAlPpyeC7+E/tmnow5ATUlaufxBREeEMtlRFadm0wHJ2dnZcuXIl3/1PoxMZ5HoPIQT7RzdGV6Por0pBcUGcfHaSX0N+JSY1Bl01XaY1mEYn605Fqt+iRQsq61Smr3VfThqeZOIPE7n/632GDx/OpEmTkMlkjB49mhkzZvDkyROqVauWr63e9Sphb1qOL3bdY8COO5yY0AxTvUIG31oG0G09dFkNL27B49Pw6CQEtofm30CtvuC1R3puqrSWnsOsdFBkgKom2HUAleK9Wgoh8PP15fKiXkytGUtQpimV5t5Ay9A8RzkrKytevHhRoK3hw4ejoqLCjRs3KFeuHB4hb1l8/jH+ke9Y088JDdWPlwEqKC4IW0PbIqdDL6NgjI2NOXDgAH2X90WlvgpJGUnoqksif0xMTKkHmv7/BMcHY2uQfwB5HTUdhtYcytCaQ0nOTOZi6EVc/VyZfHUyDoYO7Ly+k37N+gGQlpXGg4QHlM8oTy3jWqjIP24WsuD4YObemovfGz/62PVhXpN5PIl9Qh/XPhgMN8CsqhmrV6+mZ8+eNGvWDB8fH4QQ1KlT56O2oyCEEPzk/xPrA9dTRb8Ka13WFhiEeXCNwQS8DWCd1zoUQsGY2mOy7bxKfsW+x/vYE7AHG30bNrXdlOMdt6joqeuxrd02Bp8fzII7CzjW/RhyWcE+FSNG5J8MJz4tnjGXxhCSEIKrnysyZGioaJCmSANARaaCQkjCT3nN8pjqmJKUkURVg6oYahoiQ0a/bv3QUNfgWvg1nsU/41n8MzRUNNBQkbZFp0QDYKxpTF3TujSt2JQm5k0w1zXPt10lISYlhidvn/B1vbKsrmXkpkw8+pfiFS3NEpalV8wfR2NHAB7HPqZFpdzpfPMjNk0Sj/KakVJVVcWlqguXtS+TlJLEypUrGT16dI6MPp6entStWxdV1dL5+iVnJjP64miiU6LZ1m4btSrkzOjm4OCA62JX9Nrq0e6bdvi7+lOzZk2OHTtGr169kMlkVKlSpVDxCKRUrmv6OdFj8y0m7PfizKTmVDTQ+rATaPY1WDWDhwdAXRu0DKWPTA5ee+Hct2DTEgwsC7f1Jgj8j0sD60oNP2066rchEH4PQm+C9z5AQPuF0HTS3zJN9j8a3yNokc7epzr0+3/fvZo1a7JgwYJCq2cplPhGJnDYIxzribsROuVBmcWUdnZMcLFFTeWPF0yZTMbJkyez/9+1a1eWL19OXFwchoaGedq3Kq/D6s+dGLP3Ac5LL9Opphmf1a6IcxUjVFWK4RBcux9c/hHubCqZeBQTCFcXQ8ApcPkeGoyEVz5wdirs7wOtZoFJNahQHXRN/vbPaUaUP3oaMpR2rUpUPy1TwamHkSy/EIiqXMaBMc7YmpQrUt10RTo7/Xayw3cHcpmcFhYt6FqlK60qtUJTtejeEra2tjx79oy4tDhOHjhJuGE4zs7ObN26NVukGDJkCN999x1ubm4sW7asQHuOFvrsH9WYz7fdYfx+Lw6OdkZdtQjPmIoqVGklfdrMkfrdGyukj1xV6o/vbs5dr3p36LMTVDWKdL4+Pj60a9eO6XUSmdFMg0iDxthNOA1qua+ZpaUlPj4++dpKS0vj0aNHfPfdd2hUsGTUbk9+exyNmZ4mK/vWptdHSl8N0iA2OCGY9lZlGUI/Ji1btqTipoooUBCZFImDkQMAb968oUKFwj33PgYZigzCEsPoYF20SQYdNR162fWiW9Vu/BryKzt8d7AuZB1n485io2/D3ai7JGYmAqAmV8NYyzj7Y6FrQfeq3almVI249DgCYgPQV9fHXNccI02jAsWMTGUmbv5ubPXZio6aDitarqCTdSdkMhk1jGuw2HExbm/dCGkdQtX4qgwbNgwfHx+8vb0BqFu37odfrCKQlJHEnFtzuBx2mSZGTVjXaV2h3ixqcjWWNl+KikyFjd4biU6O5m3aW3xifIhJjQGgv0N/vm3wLVqqJX/nLK9Vnkl1JzHr91lcCbtCO6uSTeilZqUy4coEIhMj2dx2M3FpcYQnhpOuSKecejnaVG5DpXKVCIwL5NGbRzyKfURsWiyVdCvx5O0TUrNSSc5M5ljQsRx2zXXMs/c1t2hOt6rdAIhMisTjpQfuoe4AWOtZ42zuTC+7XtQo/+HZ7t63o51l2QRnGbkpE4/+pXi99kJbVRsHQ4dP3ZS/LdWMpBnbx2+LJx69TXsL5O15BPBZ7c+4GncV17OudKvXjblz57J+/XqMjIxQKpV4eXkxevToDz+BfNj8cDPB8cFsa7+Neqb1cu13cHAgIzoDRbACUUOwYf8Gxvcfn+0+C2BjY8OePXswMjJi8+bNDBw4MM9jxcbGkpGRwY4hDei5+RZdN/zOzE7V6NegMnL5Bww0KzWQPn+malvY1BAuzoHPd+c/mE15+0eKdmUmXFsCpo7QYDjU6geaeiVvW14oFdJSH41yf7QpORbC7kjLP4KvQNz/lgHK1aDR6P+lXJ8Lj89Aw5HSLH650k9B/K9BqYT4FxD96H8ff3gXJd2Ht8E8S9YhSrVo1/NNUjreYfF4h8XhFRaHb0QCKRkKtNVVMFZJ4em1M8zq14op7XoUauuzzz5jyZIluLu7M2DAgHzLdahpxr6RjfnlQThnfKI4dD+c8jrqTGlvzxDnIi6tUdWARmPg6iIIuwsV64Gq+h/7k17D6ckQGwQ6FaDeUGlwHx8GN1bCoxOgpgWtZ0PL6dKzW7WNtHRpX2+4MPMPW5oGUKM7tFsA2iVLV1/a6CQEgjHI8+o7CuBlQip777zgoEcYcSmZVDfXY8vgetgY6xRaV6FUsMN3B/se7+Ndxju6V+3OtAbTMNTMWzgsKoaahjhpOeHj4kObkW3wjfOlnkk9VOQqmJmZ0blzZ7Zt24ZcLue7776jXLn8Ra6aFfVZ2deJCQe8cFl1jVYOFWhpV4FmtuUpp6lWeGO0DKHvT5LnUdBFqNFDep6i/aX+TFUdVNSlfZfmwYmvpPJFEBvv3r2LviKWGc3KkVqtLxb9XCGfJSFWVlacOXMGIQQymQylUsn169epX78+enp6BAYGolAoiDOpS8d1v6OlpsL0jg6MaGaDlvrH9fZ4k/qGhPSEAr1TyigZthVsCSSQiKSIbPEoJiYGM7O/5vcxJCEEpVAW+96qylXpVrUbXWy64B7qzi7/Xfi/8aetVVs623TmXfo7At4GEJsay5vUN0QmRXI76jb7Hu/L4ZXyHnW5OmY6ZpjrmGOjb4ONvg2Xwy5jqm1KM4tmuD1y48nbJ3Sw6sDsxrNzTWj27tabbopuTLwykbs97xISGsKsWbNISUnB2NgYC4uPJ6bmR3B8MFOuTiE8MZzpDabTQNagyMugVOQq/NjsR1KzUjny9AiVdCvRyLwRtY1r08CsAfaG9h+ljZ2sO7HVZys7fHfQ1rJtsT0Js5RZTL8+Hf83/qxutbrASXunCk44VXDKc19iRiJngs+goaKBraEtVfWroquuixCCLJGFmjxnXy2EIDg+mDsv73An6g6ngk9xLuQc53qd+6Dfn0xFJocDD9PcojnW+tYltlPGv5cy8ehfyoPoB9QxqYOqvOwW50c59XJY6VkREBtQrHpvUwsWj5wrOqMqV8Un2Ydx48axbt069u/fj4aGBiYmJqSkpGQvh/nYBL4N5MDjA/Sx70PTinkv3XBwkF7GXnC4O2UAACAASURBVBx+gd1MO1wzXYm4FcFXTl9luxHXrFmTtLQ0srKy2L17d77i0ciRI/H39+fp06ccG9eUuSf9mXXcj0P3w1nU0xFHC/2Pe4IGlaHFN5K3xMlx0HWN5J30noRI8DkAtzZARhI4DYKW0yDkOtzfJc2eX5wHtT8H5wlQoZCXD6USstLgla/knZEQASmxkjiVkSwdIzNFKgNgVhuaToaba+D1/54rdV2wbg7O48C6BRjbgYqaJDg9aAk318KJsVLZCtUkEanuEDBz/LjX7t9EyA3JOyb22f82yMDIBgysJAHOrh1TfzhOpUqVCzX1/Qk/9t+T4qioymXUqKhHvwaVqWtpQJtqJux328W49b/Qeu03RWpao0aNMDY2ZtWqVTRo0ABb2/wHIM3tjGluZ0xapoJrga/Zc+cFc0/6k5Gl5Atny6ItsWk4UnqGfpLiraFTQboG5czh9RNIjgGHTpLAdnIcnJkCinTpuWw+FZpMAJ0/LQcxsoFJXpAUDTFPJDsvfcB7///EztFQZ5C0jPRNIMhUpCVLqhqSGKWqIX1XorxBkfk/o3/EZTJ4+QoUAVCz90f1ZqqQGUlylhyd8kUf9O25E8qCMwEIIWhX3ZThzWxwrmJUpAFEpiKTSVcncSvyFu0s2zGg2gAamzf+gDPIyYpuK1h5fyXuke6cDj+NsZYxHa07MrnuZJYvX86kSZNYtmwZKSkprFu3Ll87CQkJqL3yY/Ogepx8GMkp70gO3AtDVS6jnqUhbaubMKSJFdrqhbwvmDnm7Jes/vQbY1Jd6tcuL4CKdSSxUqvgQUxUVBSj66sjZCpodVmUr3AEkudRWloar1694vr16yxatIhHjx4xbNgw3Nzc8PV/hH6LLzgbqUHHmiYs6VWL8rpF84AqLs/ipb6nTDz6+DhZOxFIIM9eP6OtpRSXLCYmhlq1ahVS8+MQHB8MQFWDqiWqryJXoUuVLnSp0iXXvk42OZevJqQn4B7qzqvkV2iraeNUwYnkzGReJr/kZdJLXia/JCo5ilPBp0jNSqVyucr4xvhy5vkZLHQtWNN6TYHeb2oqaqxtvZaR7iNhMuxasgvtOG3q1atX6sstL4ReYN6teWipauHawZWGZg15/PhxsWyoydVY57IuxxLGj42KXIUva37JgjsL8H3jm6+4kxdCCH688yPXI64z13luiT2XQBqTDKo+KNd2mUyGmiy3yC+TybA1tMXW0JYhNYbwLO4Zfc/0ZcvDLXzv/H2J23H06VHepL7hi+r/8PAQZZQaZcrCv5CE9ASexT8rcoyF/zLVjarjG+NbrDqxabGoylXRU8/be0VPXY+mFZty8cVFzq04R4sWLQgLCyMqKorIyEhSU1Pp1Onj35ssZRbzb89HT12Pr+vmv065cuXKaGlpkfI0hR2NdnAz/SaHnhziQugFOtt05rMqnzFi1AhatWrF3r172bhxI4mJiblmtpVKJTdu3CAuLo6LFy/SqVMnDo915oR3JEvOP6b7ppuMb23Ltx3sP+5LSotp0gDl+nII94B6Q6SBbbgHvIuUyjh0JaXpNLIMbdHT05MGw/WGSUFfPX8Cn8PgfwJGukviz9sQaZAcdFEShjJTIDNV+vc9qlrSUjkdYzC2lQbf6jqgpi39K1ORlnEcHwWGNtD+R7BoIC2X+//eIO+Rq0gD//rDIdpPilvz/JoUuNjvF/gmoMhLPz4pSiUkhIMy6w8BQUVd+ltF7aOJAzt37qRFixY4qERIXjGG1pJ4aO4kiW4aOV8sbw3YwsC6BS/luh38hv33wuhTrxIDGlWmloV+rvhDQ4cORVdXt8jBRVVUVNi4cSNjx47F0dGR2bNnM3PmTDQ08r+XmmoqdHI0p001U8bte8DCswGsuRjIeBdbvmpVFZWCvPi0jWDMNcnLLfHl/z6vpH+1DOBzNyl2kRDw4jY8OQua+pLHUkEeRDLZ/0QoM0nQBElourpE8lq6sUJ65kXxg3eaAzxAEhaq5g6YWlJs1N8SkqaHYwECxP/n6pPX/HD6Ea3sK/BjD0cqGxUvMOidl3e4FXmLaQ2mMazmsJI0uUAq6lZkrctaUjJTuBF5g4uhFzn45CCRSZGsa72Oy5cvM3z4cHbs2MHs2bMxMckduPnx48f06NGDoKAgPDw8cB3akIwsJV5hcdx4GsP1pzEs/fUJe+68YGp7e7o7VSzasrb8aDZFehYvzZM+jcdBx8VSf5cH0VHhLKyrgcy+E+gVHLfDykryyKtfvz4vX76kevXqdOjQgf379zNsyves8VPBoOkAetetyIq+TsVbAlpMnidIy7qr6BceaLeM4lG/Zn0Ohh3EP9wfGkgD9JiYmL9s2VpwQjAqMhWs9axL/Vj6Gvr0c+hXaLlMRSbhSeFY61kTkxJDcEIwjcwaFWmC+H1w6CHnhqD4VsGzhc9KdclabGosrn6u7H+8H6cKTqxutRpTHdMPsllawtF7Ott0ZsX9FZx6dqpY4tGmh5s48ewEY2uPLdJ9LE1sDW353P5zjj49yhc1vsBKr3jJAeLS4ljmsYzzIeepa1KXJhWblFJLy/inUyYe/Qt5L4bUN/1nBTv9FFQvX50LoReIT4vHQNOgSHViUmIw1jIuUBDpYNWBGxE3eBz/mN69e3+s5hbITr+dPIp9xOpWqws8F7lcTr169dDT06ORYyMa0YhhNYbh9siNw4GHOff8HO0s27HWZS3x8fGsXr2aS5cu5TqPp0+fEhcXB8C2bdvo1Elaa9+7XiXaVjdl4dkANl19hpa6ChNcPuLsrFwOLt+BdTM4NUEKrq1fGSydoVIjsGkBpjUZNWgQ58+f5/jx47Rp00YaDFeqL31azYBd7WFbC2lZG0gxPCybgklNyXtCXVsShtS0Qc+C228NaNyiTY7lfblw6i9lq3IamNMjqrDzMXeSPs2+lpa47e0lBal16v/Bl6vUiHgAHtsh8AKkJ+RdpkJ1GPVbLmGnuMTFxTF69GhqVbfj4WhNMnUro/7VLWT52E1OTiYuLo7KlfP3PMpUKPnh9CMqGWqxuJdjvkGrtbW1+eKLwmfgAmIDOPD4ALFpsYxyGcWTJ0/45ptvmD9/Pvv27WPnzp20bFlwDDp1VTnbhtTnemAMRx+Es9I9kCtPXjP3sxrUqVxA/1TBvnAvOplM+s5YN8ux+fTp05w7d45ly5blG6MpGzNHGHgA4kLhyTlJaDWvLX13stIlD7zMVOlvbSOo3Fj6/vyJoKdPsPttGPgc+njiUVYG9vqZ3MqsSFF89l6/S+PrQ95UN9dj8+B6hXvd5MGtyFtoqmgyoFr+yxM/Btpq2nSy7kQn607sf7yfZR7L2O67nfF1xjNr1ix2797NnDlzWLduHdraOa/38OHDs/vpy5cv07BhQ9RV5ThXKY9zlfLoBF/G/9IxtAfOYdpRHzZffcaeEY2KLaRlI5dDv72SEP/sN7i3VfLC/GwtlM/tyWGR+pgKFkD9wsW3GjVqIJfLMTY2Zv369fTp04fg0Bc0Hj6fEQefoKKQo+mzjzXLDpas7cUgNCEUXTXdYiXbKKNo1KpVi4wHGTzlKX379mXOnDmkpaX9ZQGzg+ODqVyuMuoqeUz6fCLUVNSyhUpTHdNiizFGmkbs6LiD/if7Yz3dmtpVP34inUxFJlt9tuL2yI1MZSYDHAYwo+EM1FSKsDT2E6OjpkM7y3ZcCLnAjIYzihSn7tCTQ+zw3UEfuz5MqDPhL2hl4Yx1GssvT3/hSOARpjfMO2nHnxFC4B7qzlKPpbzLeMf4OuMZ5Tiq0ODhZfx3KROP/oXYGdox0nEkTiZFV8//q1Q3kjI0BLwNyHeZ15+JSo6iok7FAsu4WLqgekcV91D3D852F/4unOCEYGTIUJGroCpXRVWmiqpcFTW5GqpyVa5HXGfzw810tulcpCCP58+fzyGClNcqz7cNvmVCnQls993OTr+deLz0oGnTphgYGHD69Olc4tHdu3cB6NmzJ6dPn+bp06fY20sDWH0tNVb0qU2WQslK90CMddXp37AIAa6Lg01LmOgJaQlSMN//R1ZWFufOnSMxMZGOHTuyadMmxo4d+0cBQysYfBSuLOK1UUM07FqjY2rD/uPn6eHSAwODnAN1X19fmrk4sXfv3oKFBANLyZvog86rNZS3hfuuf0/xKCsdLs6VhCMNPSkOjkUDSXDLSpPSvivSJWHh5hq4uxVaFe0lJj/eu7p/bhaGPEGDTruTmWB9gb59++ZZPjJS8kCrVKlSvjZ33w7laXQSO4bUL1m2sz+xwWsDXq+90FHTYdTFUUysM5EtP29h+PDhjBs3jq5du/LixQuMjAqOF6SmIqddDVPaVjfhuFckS399TM/Nt3CqbEDf+pXoVtscA+2PN6hZv349V65c4fLly1y7dq3Aa5aNobXkhVRCsnTipSVrvochPVGKFfaBpIZ5oaUKSVp2hZYVQjDnpD/pWUo2DqxbIuEI4GbkTRqaNURD5a/zEBxUbRC+Mb7s9NtJ1ypdcXBwYNSoUbi6uvLLL78wevRoJkyYgKWlJTExMXh4ePDjjz9y5MgRrly5wqxZs7Jtubu7M3nyZJRKJd8O64Xjl/2YetiHz7fdYWRzG1o5VMDORLf4nqNqmlK/UKM7WNQH9+9hSxNoPhWZcU6v25pq4SRnqaBTBBHR1taWoJAwXmdq8OhlIt8e9cUj5C16TfqT8vg6ygdHaNv8r0k/HvIuBGs967JMa6VApUqVEPGCUNVQnh57SsWK0vvWX+V5FBQXhJ1h4f3IPw0LXQt2ddnFlxe+5LDiMF3SuhQrNs6Tt0+49/IeUUlRJGYkkpiZSFJGEokZiSRlJhGfHk9yZjKfVfmM0bVH/+O88nrY9uDM8zMcfXqUITWGFFjWN8aXZR7LaF2pNXOc5/xt+gFjLWPaWLbhVPApJtWdVCQRbKXnSvYG7MWxvCM7O+z8Vz77ZXxcymTFfyFmOmZMqT8lV3C1MnLjaOyIqlyV25G3i1znZdJLKuoWLB7pqevR0qIlZ5+fJTM75kfxiEuL45tr39D1RFcmXZnExCsTGffbOEZfHM1w9+EM+XUIA84NoO+Zvmz03kgXmy782PTHItnW09NDRyd3MFhNVU3G1h6LmY4ZqzxXIVeR07t3b/bu3cvu3btzlL179y76+vps3LgRfX19Bg4cSHp6evZ+uVzGir5OtLSvwHfH/bjg/6pE16FAVDVyCUcADx484N27d2zbto327dvz1VdfMWbMmBztw9yJ5J5u2A1YTIPOgxk1aTpffvklkydPzmXPw8Mjx7+lilwODUdBxH14erH0j1ccsjLgyDBJOGr8FXzzGHpslgKROw2A+l9C4zFSBrl288GhK9zeIAlJH0BAQACW+jJmtdDCPUqPgJTyuLm55Vs+PDwcyF88ep2YxrrfgmjtUIH2NT7MnR6kbDL3Xt2jn30/TvY4SWPzxqzzWkfbo21xV3dnwZ4FJCUnsWHDhiLblMlk9KlfibVt9ZH7nODN23jmnvSn0eLLjN//gMcv331wu7OysvDw8KBNmzZERUUxbdq0D7ZZZJwGSstCA05/FHNJfucAUJoVPmly9EEEFwOi+aa9PVUqlMwrLuxdGGGJYTSzaFZ44Y+ITCZjWoNpqKuos9RjKUIItm/fzo0bN2jbti2rVq3CxsaGUaNGcfHiRYQQdOzYkTZt2nDz5k3S09OJiIjgyy+/pHPnztSoUYNq1apx5Mhh2lQz5dAYZwy01Vh8/jEd1t6gydIrzPjFB6+wuJI1uP4wmOQJ1bvB9WVUuTAYgn6T9glB4/JJPMk0k5a4FoBCKdh6LZhOO3wZ4HqPhWcDuB38hurm5VjZzYaUK1t5E/kCR8e/JlZcaEJoganGyyg5MpkMAwxQLa8KMrh+/Trw14hHz+KeEZYYRkOzhqV+rE+Bg5EDG9tsJDIxkuEXhhP4NrDQOnFpcUy/Pp3Pz3zOKs9VnHl+hgfRD3iZ9BKBwFzXnHom9ehetTtb2m5haYul/zjhCKChWUOaWTRj5f2V7PTbSfi7cN5lvCNDkYEQf8TsS8lMYfbN2Zhom7C4xeK/XWzZ/g79SUhP4OKLwt8f36S+4eCTg3Sv2p29XfaWCUdlFA3xDyMgIOBTN6GMj8jf4X5O+G2CaHe0nVAqlYWWzVRkCqfdTmKD14ZCy94IvyEc3RzFhZALhZZVKpUiKjFK+L72FVdeXBGHnxwWXY93FfX21BMbvDYI39e+wi/GT3hHe4v7L++LO1F3xO8Rv4urYVfFpdBL4nbk7SK1v6icf35eOLo5ii3eW0RiYqJo166dAMTGjRuzy9SuXVt06NBBCCHEiRMnBCDmzZuXy1ZSWqboufmmqPLdOXHSOyLHvuLc/5iYmCKXXbx4sQDE69evRVZWlpg9e7YAhLOzs4iMjMwut2/fPgEIVVVVAQg7OzsBiDt37uSwN27cOAGI5s2bF7kNH0R6shBbmgqx1FKItyF/zTHzQ6EQIvy+EL/9KMTGhkLM1xPi3o6i1X31SCp/fWW+RYryDEydOlUc+lxXKBeaCBEXJmbMmCFUVFTE69ev8yzv5uYmABEUFJRrn1KpFCPd7gu72edF8OvEop1HIVwIuSAc3RyF5yvP7G2BbwPFsnvLRPODzYWjm6Oov7a+MDQxFAkJCSIpKUncunUrX3tKpVK4urqKiIgI0a9fPwEIDQ0Nsev4RfHDaX/htMBdVPnunFh9MVAoFCX/3nt7ewtA7N+/X8yfP18A4vr16yW2V1QCAgKEUCqFWFtLiH19P9xgYrTIWGguLg/VFr9dulRgUd/weGH3/XkxyPWOyMxSlPiQ+wL2CUc3RxGaEFpiGx/C++P/5PdTju0vXrzI7q8sLCyEsbGxUCgU4tSpUwIQ/fv3F1paWkJdXV1Mnz5dxMXFiYULFwpAhIeHZ9uJjEsRB++9EOP2eQrH+ReE1cyzYsye++L1u7SSNzr4mkhbVUvqEy7MFpnhD4SYrydOzutdYLXMLIUYs+e+sJp5Vozd4ykuP34lot+l5iizfv16AYjTp0+XvH1FJDkjWTi6OYrtPttL/Vj/Nor6m99rTi/h6OYoqjSoIpCi7ef6XS4N1j9YL2rvri1iUor+vvFP5E7UHdH6cGtRd09dsdt/t1Aoc/aFWYos8S79nQiODxadfukk6uypI7Y83CKik6M/6Lh/h3f+gkjNTBVfXfpKOLo55vjUcqslGu9vLNZ4rhEjLowQtXfXFh4vPT51c/NEqVSK7ie6i96neue6r39mh88O4ejmKJ7HPy/VNv3d73sZuSnonv295NIyyvgEdLTuyPWI6/jE+FDHpE6BZaNTolEIRaHL1gCaVmyKuY45R58epaN1x3zLCSGYcnUKV8Kv5NhupGnEro67Cm1TadDJuhO/R/zONt9tNDZvzJkzZxgwYACTJk3i3bt39O7dG39/f3r0kFKX9+zZk+7du7Nt2zbmzJmDmtofs8g6GqrsHdmYkW73+faID5UMtalvlberdEJCAvr6OTO0paWlMWXKFLZv386JEyfo2bNnvu1OSEjAx8cHd3d3ateunT1TuXjxYurVq8ewYcOoX78+x44do2nTpuzbtw9LS0uWb9/HybuBaFauSdpvl/hyyyWGvdXHSEcdQ211rsfqYj5iEyFCydBd9yivq4GhtjpGOmoYaKtTXkedKhV0qVpB5+MEaVXXhv57YUdrODocRl4sdGa+VLi+Ejx2QPJrKTiyZRMppXvtz4tW37SGFEfK5yC0+LbEwbNfBT2kf3255O1kUJkhQ4awYsUKpk2bhpOTExkZGWRmZtKwYUM6depEREQEkNvzKEuhZPuN5/z2OJq5n9UosdfJn7kWfg0DDYMcgTbtDe2Z2WgmU+tP5ezzs/xw+we0u2uzectmwsPC2bp1K/fv388z82JISAijR4/GycmJR48e8eWXX/LgwQMmDu7BhQsX+Hpaa348E8CGy0GExSazoq9TiYIc37lzB4CmTZvSs2dPdu3axcKFC7l06VLJL0ZRkcmgWlcpC2J6UvHiYgkhBcd/5S8Fmw/8FXlWGuPPpXHyu/yX3aVlKph8yBtjHXU2DKhb4u9qdHI0W3224ljeEctyH3k5bhEZVG0QD6IfsM5rHQ5GDtnLri0tLdm0aROenp7cv3+fgQMHIpfLadmyJXK5nMOHDzNo0CAWL16MtbU1AP369WPu3LnMmTOH7du3o6GhQUUDLQY0smRAI0uS07P4+VYIG688o+O6G2wYUJfmdiWIP1OlFSEd91ItbB/c2YT8wR4AEk0b5VtFCMGMY764P4pmTtfqjGxuk+cSkYkTJ1K9enUpvl0pE/ouFKDM86gUmTJoChM8JlCvcz2ee0rByUvb80gIwa8hv9LYrPG/PpaVs7kzx7ofY/7t+az0XInbIzeqGFQhLi2O2NRY4tLjUAolAAYaBuzutPuDQzD8E9BU1WRL2y0ExwfzMOYhKZkpZCgzSMtKI/RdKD/5/4QMGUtaLPnbeqfJZDJG1RrF7JuzuRZ+jTaWefeJWcosfnn6C43NGpf1ZWUUizLxqIz/PC6VXVCXq+Me6l6oUBOVFAVQ6LI1kNJ/9nPox3qv9cy5OYdZjWblmTHiSOARroRfYWiNoTQya4SxljHltcpjrGX8ydxhZTIZc5zn4BntyYr7KzjY9SBHjx5lxIgRfP/99yxduhRjY2NGjBiRXWfMmDGcPn2aM2fO5IqPpKuhyo6hDfhs4+9MPujNjqH1qWGeM1vd8+fPsbe358SJE3Tr1g2A4OBgPv/8c7y9vSlXrhxLly6lR48eyGQyzp07R4MGDTA1NUUIwbFjx5g0aRKvXknL4775Jmdq9T59+lCtWjV69uxJa5c2dB03D2/DlugPHMusa+8Ac6rEp2Nq78Sr2ERcbwSjRBqkCOsWqLwKJD0liei4RIJjkolPySA5I2emKTM9Tb5sZs2o5jYfLiIZVYFuG+DoMLi2DNrO/TB7xcVrL1xdBLbtoXZ/sG1bcHau/KgzEE5PgghPqFyyl61KqQHSH7Uk0crR0RFnZ2f27NmTo5y5uTlRUVFERERgbGyMpqa03v/Z60SOekZw3DuSmMR02tcwZUQz6xK15c8ohZIbETdoValVnt9XdRV1etv15lXyK7aylS2HtxD9WzQACxcu5NSpU7nqBARI5+vj4wPA7Nmz0dfXp3Xr1nTp0oWLFy+yul8TqprostI9kJikdNb1r0uFcsWLvXP79m3MzMywsrJCJpNli3KxsbGUL1++uJei+Dh0gbtbIPgy1OhRcNmYQCkTYcgNiA/LGaTd0JozWS14Fn+uwCDpa397SsibZPaPalziFO4KpYJZv88iQ5HBkhZLPlmsC5lMxqJmiwhJCGHGjRkc6nqISuUk4Uwul7NhwwaaN2+eLbYbGBhw5swZTExMcgmW9vb2TJ8+nZUrVxIVFcXFizmXO+hoqDKxjR0da5ox8YA3Q3+6x+DGVnRyNMPORJcK5TSKfB2Eijp0WQmWzogTE3gQpUC/fo18y/98K5TjXpFMbWfPqBb5L4WRy+W0b59/yvKPSWhCKMBfko3rv0pTh6ZoPNBAw/KP72lpB8z2e+NHRFIEY2qPKdXj/F0w0jRig8sG3F+4c+XFFSKTI6moW5FaxrUor1UePXU9lEJJO6t2VC6Xf7/6b0Mmk2FraIutYe5EL33t+6JQKv7y5crFpbNNZ7b6bGWV5ypC34VSzaga1YyqYaQpvcMJIVjmsYyo5ChmNZpViLUyyshJmXhUxn8eXXVdmlZsyuWwy8xoOKPAl+D34pGFrkWRbA+rOYyUzBR2+e/i/qv7LG6+mAZmDchSZnEl7Aonnp3gbtRdmlZsyrQG0/42QfdAyvAzvs545t6ay6UXl+hg3YHdu3djaGjI8ePH+fXXX7NnrgE6deqEhYUFrq6ueWaY09dSY9PAegzYcZeuG27iYFqOphZqjDJPxcJACx8fHxQKBVu3bqVbt26cOHGC4cOHI5PJOHXqFOHh4UycOJFbt24hhOCzzz6jbt26HDlyhG+//ZbTp09Tt25dVq9ejb+/P6NHjwakrFpB0Un4RyUQEAWOX+9CERaLt1wdVd0IXOzL41LLipb2FTDX10KpVNKsWTNCQ0Px9gvAPyiUju3b8M24UaxatYrhfQ4yYICUXSk9S0F8SiYxiek8jU7kuFcky359wu3gWNb3r4OhzgcGNq7ZE4K+gN9XQ8U6UtyQUkAIwZs3b/6Y2Q33gPPTwKYVDDqcb5rtIlGjJ5yfAWengEl1Ke27fWfQKZo48e7dO5oZvyOB8uib1szefuPGDRISElBXV0dNTY1Vq1Yxb948kpOTCQ8Pp1KlSsQmpTNuvxceIW9RlctwqWbC5/Ur0aaayUf7rgXHB/Mu4x2NzRsXWG5s7bFce3qNR70ekRCYwJdtv8TV1RVPT89cg/n34tHMmTNRKBTY2UlxCC5fvkyrVq3o1KkTo0aNYuDAgaz63IlZx3xpuPg37E11aWRjRGOb8jS2McJEr+BgmXfu3KFp06bZ16JPnz4sXbqUU6dO5RCGSw3LJqBlCE/O5yse3b17l7mTh3O++zvURAZYNwerJmBsD2a1wKQGaOqxomlTGjZsmGcsN++wONZfDuJaYAwDGlammW3JB6Gufq54RnuyqNmiTz5bq62mzXqX9Qw4N4Chvw7lK6ev6GXXCzW5Gs7Ozrx8+TLHgLtLly7Zf6cr0nkc+5h0RTpWelasWLECXV1d5s+fT2hoaI6+/T12puU4Pr4pC8484rBnOHvvvpDaoa6CVXkd7Ex0GdTYEucqf3y3lUolCoUihzcqAI59uPQkiRErhnN6jHme53c/9C1Lzj+mfQ1TJrf9iBk7P5DQd6HIkGGp92m8zv4LqMpVsTe0JyUxBQA1NTX09PQKqfVh/BryK2pyNdpatS3V4/ydkMlk2ZkcyygcZ/O/JiD/h6IqV2V249n8eOdH1j5YJYRI6wAAIABJREFUm73dTMeMNpXbEJkUyfWI6wx3HI6LpcsnbGkZ/0TKxKMyygBaVW7FtYhrPIt/VmDAuKhkSTwy0zErkl01uRqT602mZaWWzL45mxHuI+hSpQte0V68TH5JRZ2KDK4+mJG1Rv6thKP3dKvSjd2PdrPUYylmOmbUrlCbDRs2sH79+lztVVFRYcSIESxatIiwsDAsLXO/WDtVNuDWrDac83vJSe9IfvZ6y89eV2hsY4R2TCxyDR3c3d2ZPXs2S5cupUGDBhw9ehRra2uSk5OZN28eU6ZMQVNTEz09Pby9vbG3t0dTU5OVK1cyZcoUVFWlbu3/2LvvuKqr/4Hjr3u5l723KIiAIIIJ7j1Rc+FOc1RfVzn7Wm5LMzWtnGmuTEttuVLcC/fEBYogCg4UENl7XO75/cE3ih/gBM06zx49ivs5n/P5fDyX6+fzvue831qtYPXxSBYejCAnv3D6taGuDjUrmTKoaXWaulnT2r0DanXxj0GlUsmSJUto2LAhi+d/iaenJ9rMFAYNGsSSJUu4fPlyUfBIT6WDnakOdqb6eFc2o2edKvxy/h6fbr9G0y8D6eFbmebVrWlYzer5A0md58OjcNg6DLovB68ez738qyyzZ89mzpw5xF3eh3nmbTg4HUwdoNf3LxY4AtA3hSaj4epmuH2i8L8KJVRtCu4dsHz4ENStwM2v1N1vhAbTzlXFQ5sGmP3lutVqdbEH4z8q/UVGRhYGj6q58d66ICIepjOtkyc96lTG+jlnmzxO8KPC2UF/XbJWGh2lDiu6rqDdhnZUn1advs37EhAQgL+/P4GBgdSoUaOo7fXr13FwcGDevHnF+qhUqRKBgYEMGjSIFStWsHbtWm7cuMHusc05HP6Qc1FJ/H7pARvP3gOghr0JqwfVw8mqZNn1+Ph4IiMj+eCDD4peq1OnDs7OzmzduvXlBI90VFC9A9zcDwWawp//4saNG/h36cTv/rnk5eii+m8QCuuSQYT09HTOnz/PpEmTir1++V4yiw/d5FjEIywM1Ux804PBTZ8/4HPp4SVWBK+gs0tn/F39n7uf8uRk6sR37b5j3vl5zDo7i3XX1jHSZySdqnUqsczn9IPTnHhwguBHwYQlhaHRaoq2eVh40LVdV5gBu3fvZtSo4tX0VqxYQWhoKMuWLeOr3rWZ3tWLi3eTuZOQyZ3ETO4kZHLqVgIBwTG0rWHL3F61sDXRZ/jw4Zw/f55Tp05hYlK8qt6dhGxiM0RRNa2/up2QyfsbLuJoacj8PrX/Vn8/RqZEUtm48kutsvdv5Gnpye6UwkT4NjY2FfoeKNAWsO/OPlpUaYGpbsUGqSTpZWhWuRkHeh8gNTeV8KRwwpPCufjwIpsjNmOuZ84HtT9gRO0Rr/o0pdfRy0i6VJ5k0q1/lr/LeMZlxAnvH7zFmpA1j233yclPRJvf2jzXMTLzMsXM0zOF9w/e4r2974nDdw8LTYHmufp6mW4m3RQdtnQQvut9xbaIbY9te/v2baFQKMSMGTOequ9DZ4PFkkMRovXXR0TVSbuE08fbhHnLd4VC10D06NFD5OQUT84aEBAg1Gq1AMTixYvFggULRK9evURkZGSxdnmaAvH++gui6qRdYsgP58WOKw/Erfh0oXmG5MLvvfee0NXVFU5OTsLCwkJoNBrRsGFDoVarhZ+fn/j000/Fjh07RExMjMjOzharVq0S7777rhgyZIgIvZ8kPvzlkqjxyV5RddIu4Tx5l+i4+LhYcODG8yXpTY8XYkWzwkSzP3QR4mH5/d7cunVLWJnoibX++oX9zzAVYnFtIVKin7zzs9JqhXhwqTD59rIGfx5vhqkQv/QXInS7EDn/S2KdmynEjX3i4if1hJhhKh4c+/GxXQcFBQlAbN68WRha2ovaE34WrlN2i8CwF0vw+SSfnPxENPul2VMnrL+Xek90+72bqP1jbTE/cL6wtbUVdnZ2IjQ0tKhN/fr1hZ+f32P7CQsLE2q1Wrz77rvFXs/XFIjg6GSx+likeOOz/aLN/CMiJTOvxP7bt28XQInE3R9//LFQq9UiPb18komXptjnfuj2wvGPOl6iXevWrcV7DSyFmGEqBr2hFjt27Ci1v927dwtAHDp0qOi1A6FxouqkXcJn5n6x/MgtkZGT/0LnnJKTIvw2+4mOWzuKjLyMF+qrImi1WnEs+pjoHdBbeP/gLbpv7y4O3TkktFqtyM7PFp+d/kx4/+At6m2oJ97d+65YeGGhOHz3sDgbc1b8cO0H0WNHYYJiz/96ig6dOhTrOyYmRhgaGgpAREUVJlbNzs4WISEhxdpl52nEqmO3hPu0PcJn5n6xJyRGeHt7FyXq1mq14vr16yIjI0P0799fdOjQQSiVSpGfny9SMvPE3quxYmZAqOi05LhwnrxL1J65X0Q9+nv9WYcnhguf9T5i+qmSxSGkJ3uWe77NNzYL7x+8hZ2Hnahdu3YFnlVhAumnLXAiPb+/yz3/v1mOJueJibTLmxz318/jxkwhxF/qD74GwsLC8PT0fNWnIZWTv9N49tnZB0OVIT92/LHMNkP3DyW3IJcNnTY893HyC/JRv4rkxy8gJSeFCccncDb2LP1r9Gd8/fGolaVfQ4cOHQgLC+P27dvo6Dx+1sof4y+EoFXPd4kz8SDXwQeFtoBajhYolEryNFpyNQUUaAUOZgbYk0TC6S18t3J5UU6bv4pNzWbWruvsuRrHtE6eDG1eeoLVv0rKSeLwvcOEJ4ZjZ2RXuDZcY0kzn2bY2tqyfv163H3cSY5JZuWKlRw4cIDQ0FAKCgpzHunr65OTk4OZmRmpqamEhIRQq1Yt8jRaQu6ncDoykVO3Ejh3O4m+9RyZ16vWs3+LWqCBi+sgcDbkpkOD4dBmGuiZPHnfMggh6Nm1Ix/ZnqJxFQVXjFpSb9gSMHNEKFVcuHABa2trqlWroOU56XFERN7BPe0EnFwMeRmgbwb2bxQunSvIJTNPcCXPiabzLoHqz9lbyZl53HqUwcO0HB6m5XIvPoVlK1fjXrMW97FC38CI1e82oHUN24o59//x3+6Po4kj37b99qn3ycjLYMqJKRy9f5SW1i3ZOmIrBTkFBAYG4uXlhYmJCUOGDGHJkiWP7WfKlCnMmzeP3bt3F1uS9IezUYkM+v4c1sZ6fNqlJp1q/bk8aNKkSSxatIi0tLRiv0fbt2+nR48enDt3jgYNyk5k/CKKfe7npsNXLlB/KLw5t6jNiRMnaNGiBVGz6uJskIH7ijwcnZwJDAws0d/48eNZtmwZycnJGBgYkJ6TT7uFxzE3VLN1RBOM9F58kvWM0zMIiAxgY8eNeFl7PXmHV0QrtBy8e5Bll5dxJ+0OXlZepOWlEZ0ezWDvwYz2GV3q3z/52nxWBq9kdchqssKymN5+Os76zig0ClauXMnmzZvRaDTMmTOHqVOnMn/+fCZMmMCaNWsYMmRIUT8LFy7EzMmD7bFmXH2QiiY5BsWjWyTfvMj493rRp2NLrly+zMCBAwGwt7dn2a4gZgSEkpGrQU+lpI6TBQ2qWeLv44BrOSW1L9AWsOzKMiz1LRngOQCl4tlz0uVr8xmwewAPsx6yvdt2LPRLL/wgle1Z7vlCE0Ppt6sflYIqYZNsw08//VTu5yOE4MLDC3wd9DV30+5yrO8x9FWPX+4rPb+/0z2/9PLIcX/9PG7M5LI1SfqfFlVasObqGhKyE8qstPEg4wG1bGq90HFet8ARgLm+OSv8VrD44mJ+vP4jkamRrGi7otRrGTZsGH369OHAgQN07NjxqfpXKBTEXDtDnTq5TB01kt1X47j2IBWVjhJdHSV6aiUK4G5iFr8/EFi6vs1/N4dSp6o5lkZ63E7IIDI+k6iEDCIfZaIVgqmdajCsRdkJVu+n32fe+XmolWpOxZwiW5ONsdqYjPyMojbeK7zxsPBgadJSQn4Lwc7QjsbdG/PRex/hYuRC7r1cQi+HEhERQa9evbCwsKBOnTrcuHGDWrVqoatSUs/ZknrOloxtW50FB26wNPAWTlaGjGr9jDk8dFTQYBh49YTAz+HcysIH7+5PH7T4/3YF/M5gk+M0c1IzbJ8OyjcqUc/ShZSUFNq3b09QUBAqlYqxY8fy6aefYm5uTmRkJDNnzmTmzJllBpUSExMJCAggJyeHESMeMy3axJ4CveTCCm5N/wv3zkLQd5AYyS3LVoxatB19jzZs2b4TVIXvtRtx6Sw5HMGB0IdotH9+96GrUmJUsyUxKMiODOLbCW9XeOAoNTeV26m36eLS5Zn2M9Y1ZkmbJawIXsGq4FXUWVCHkNkhtG7dmnXr1pGZmUnNmmUnEf7D9OnT2bt3LwMHDuTSpUsl8tQ0crHi1+GNmBEQysifLjG4aTWmdKqBWkfJmTNnqFu3Llqlih9O3Wb9mbvkarQYKI2x6vgh56+GV1jwqBg9k8LcWuG7ocMXRUsyZ82ahU81G5w1t1D4TqCrfyLLly8nJyenWLArJyeH33//nSZNmmBgYADAooM3eZiew4qBdcolcARw8v5J2ldt/7cOHAEoFUo6OHegrVNbdkXtYlXwKnR1dFnTfs1j83KplWrG+I4h834mG6pvYH70fIRGkH03myyRxdtT3ibqWBQ//fQTU6ZM4fz580Dh572hoSFvv/02Dx48YMKECbi4uBAaFs6qg1eZ9f15LDyaoePegh8ewa8/RaFKTceh/VCy7odhUr8LH28OpoGzJeM7eFDb0Qw91YstlY3PimdrxFb0VHoYq40x0TXh5IOTBEQGAHAs+hiDag6iRZUWzxTEX3t1LWFJYSxqtUgGjl4CVzNXFCjwH+xf7strhBCcijnF6pDVXI6/jLWBNTMaz5CBI0mSpCeQwSNJ+p8uLl1Ye20tCy8s5IvmX5TYnqPJIS4zjo7Vni4g8k+jUqoYX388LuYuzDg9g9VXVzPKpzAvRmZ+Jr+E/4JWaPFu6I2Ngw3ffffdUwePCgoKuHPnDn369KG2owW1Hcu+MT8blcgv5+9x6V4y+0Lj/nduCpwsDXGxMeZNL3v61HPE0bJknpe/Whm8ktMxp6lkVIk2Tm34j9d/ChN0arKISI4oWiMenhSORqthZO2RhCWFcfz+cbbf2l7UT1WnqtT0qYnWWUsVs8JqRxEREaUe86N27txJzGLBgRvUrmL+fOWujayg65LCvEFXfoYOswuTDj+jrMwMNFvep4eHmoKO87l19Cfyrl0DChMzBwUFMXfuXCIjI1m0aBHr169n5syZrFq1ipCQEC5cuMDp06cxNzcHIDY2lu3bt7N161aOHj1aNCurSZMm1K79+HxAAOiooVpzqNackydP0q5dO954w5fATVtRq9U8Ss9l4cEIfgu6h5GeiveaONPc3QZ7U33sTPUwM1DTsGFDgoKC0NXVpeO2uU8+5gtIyUlhbeha4Mn5jkqjVCgZ5TMKHxsfJp+YjP14exJ/TiyqjvU0wSMDAwO2bNlCvXr18Pf35+TJkyWSytatasn2kU2ZsyeMtaduczoygbYe1kTYtsLKtRZeM/YjBNR3tsDJ0oiEjBwiPFuw7KYCcfgmPk7m1HY0x1S/AoPeNTrBroMQfx3svDhz5gyHDh7kyqyWKDRXwHcgbbKusmjRIs6cOUPr1n8m+Jw5cyZRUVGsWLECgAcp2Ww8e5e36jri61Q+D/jxWfHEZ8dTy/rFvjh4mVRKFd3dutPdrfsz7TepyyQ8D3hyI+MG97X3uet5l3tu97gsLmNWzYybE29y9epVrly5wptvvklWVhaDBg3CwMCAmzdvotVquXXrFqdOHMdbHx5t/ZyNBw5gXc2LXu+PJ8O0MsLSGbVPN8x8u1OggAntPfigpSs6yvLJabP8ynK23txa4vVhtYZhZ2jHt1e+ZXTgaD5v8jk9qvd4qj5vJN1gZchKOjp3xK9q6fnZpPKlr9KnikkVbqc9eRbz08gryONWyi0SshNYGbySqwlXsTeyZ2rDqfRw6yEDR5IkSU9BBo8k6X+qmVVjsPdgVoespq1T2xIVN4IfBaMRGnxsfV7RGf499KzekwtxF/gu5DuSc5LJLcjlxP0TJOYkFrWxn2NPyJ0QNlzawKA6g57YZ3R0NBqNBheXsmcK/aGRi1VRNZ9H6bmk5+TjaGmIWufplyHEZcaxO2o3fWv0LVGm1EhthK+tL762vmXun5CdQFhiGGFJYVxPvM75uPPsvbMXAM8vPQm9EVrqfgqFgnk9axEem8bYXy+za0wzHMwNnvq8i6nzLlxYCyGboeEzlhYWgpCvOtHDNY8ol0G4NByGt3cw69evRwhBeHg4AKNHj8bY2JiRI0fy3//+l1GjRqFQKJgxYwZffPEFVatWpUGDBiQlJXH58mWEELi7uzNx4kTatWtHx44dWbFqNbX6jGPr6XAibkdjYajCq1plfDycqWRuSH5aJqFZ94lLzcarshmqtFj8u3XHqXpNvt2whfCEPM6ej2X5kVvkarS828SZsW2ql5qA3NXVlaCgILy8vEpWdyoHQgiCHwWz6cYm9t/ZT542j6YOTV/oM6Fp5aZs7rqZ8cfGE9wvmGrm1bj1662nCh4BuLm5sWXLFjp27EifPn3YtWtXiWtX6SiZ0dWLxi5WTN8RyvJjt9GxqIyLpR5t61anQTVLGrtYFc3C8GzcFkWDgSw4WBgEVSjAzcaYbj4ODGvh8sIzQ0rw6Ay7x0PIJmg3ky9mz+Tnt8x5Q3MZGo8Gi6o0b26OUqnkyJEjRcGjCxcu8PXXXzN48GDat28PwDeHbgLwoV/ZhQ+e1bWEwqCqt7V3ufX5d6VQKOjWoXjluxxNDsfvH+ezU5/hMtWFH7b+wK1btxg0aBD//e9/8fPzo2/fvlhZWVG3bl0iIyP57rvvisbJw92dqlUd+H3BRBo1akRubi5HTpxGt1J17Ez1y21pGkB6Xjp7bu+hh1sPJjeYTHpeOhn5GSgUCqqZFi5h7unekze3vsmZ2DNPFTzK1+bz6alPMdU1ZUrDKeV2rtKTuZq5EpUa9cL9ZOVn8d6+9whLCgMKi5581vgz/F39X8vZ4JIkSa+KDB5J0l8Mf2M4J+6fYNzRcbxf+30+eOMDdP5XbSooLggdhQ51bOu84rN89SY1mER8djx7ovagUqrwsfVhWK1hOJk6EfwomMNhh/n5/s98deUrTvxygm9mfVNqfqI/REZGAoUP/8/CxkQPG5Nnq3ij0WqKSpe+U/OdZ9r3D9YG1jSv0pzmVZoX9Xk29izBj4JZGbySsKiwMvc10lOxclBd/JeeZORPl/hpaMPnW1rj4AOVasOZZWDuCO5vPnUVtqRtE2mkCGZ3siudBy0FwNvbm/T0dKKjo7lx4wZVqlTB2Ljwoc7X15ejR4+yY8cONBoNvXv3pn379qxbt47g4GAsLS357LPP6NWrFzVr1iwKQvTsN4id6c7s238DEu6gzE4lpcCIkxEPOROTj6KoutbDYudnNuxHcoHea0OKXmtX044pHWvg8pgHzT/ePz4+5R/gFUIw6+wsNkdsxkhtRI/qPXjL4y3cLdxfuG97I3vWvbmODwM/5GLni2zstRErK6sn7/g/Hg08WLxqMaOHjGbkyJGsXr261OU47b3saVPDliVLlzH+yw85f/8+lStXLtHOu4olV/Z8QXDIdULup3D5XgpnoxKZfyCCbZcfMKG9Bx287FGW00wRTOwK379XfuKSUSuGmx6nq4caWk8rXNIImJmZUbduXY4cOQJAXl4egwcPxs7OjgULFgCF1dW2XLrPO42rPn9QthTXEq6ho9DBw9Kj3Pp8neir9Gnv3J6qplXpvb03v1/9HSEEvr6+mJiYsG/fPlq3bk1wcDAzZswgNDSUVatWYWRkhK6uLlWqFM7I9PHx4euvv+batWu0bNqoQqpn7YraRbYmm74efTFUG2KoNsQOu2Jt1Eo1b1i/URQUfBK5XO3VcTV35WTMSfK1+WXmWXwSrdAy9eRUbiTfYHKDyVQ2rkxjh8ayWp4kSdJzkMEjSfoLPR09fnjzB+aen8vK4JVciLvAly2+xNbQlqC4IGpa1cRYt/y+JX1dmemZsab9mlK3tajSghZVWnB86XHi/ePZk7KHPif60LZtW/Lz89HTK3nDFhVV+M3i08w8ehGJ2YlMOD6BoLggPqj9AQ7GJUtEPw+VUkWzys1oVrkZv5z4hUSPRB7GP+RR/CO8vUvOVnC1MWZ+n9qM/PkS7RYe4z9Nq+FV2RSvSmaYGT7DDXLbGfD7+/BLP2g4AjrOK7ttVhKE74KEm1heXc0PIVo6LNtVFHCqVatwSc61a9cIDw8vVjoeCmck/LGkCgqXozVp0qTUQ+XkFxByP5V71XuhSs4hM3AlCUG7CAwMpEmTJgQEBPDdmuUcPnmO3oOGMufzz7Az1WP28vWs+Gk7fd8ZTLP6vpgbqjEzUFPZ3IDqdk9ODO7mVphHqryDR1qhZVXwKjZHbGag50BG+47GSG1UrsdQK9WM9h1N3119yfHIeWzb5JxkdJQ6XIm/wvrQ9ZyLO4darab90vb8uupXnOc5M23KtFL3VekoCTp7Gicnp1IDRwCenp5s27YNPUUBzavb0Ly6DWPbVudIeDyzdl9nxE+X8HIwZUwbN9p62qHWUSKEIFejJSe/AENdFbqqZ0xIXPc9uLEbx1198XFXk+M3F/1mI4s1ad26NYsWLSIpKYklS5Zw9epVdu7cibm5OVl5Gj7aFIy9qT7j2r14QO+vQhNDcTV3xUBVfgGp15GHpQeV0ysT3SganU06Rb9nFhYWHDx4kA0bNvDOO+9w/fp1li5dyvr163F1dS225MjPz48xY8ZUyPlFp0Wz5uoavKy8npibytvam0P3DpGSk4K5vnmZ7VJzU/nu6ne0r9peLld7BVzNXdFoNUSnReNi/nz3Bxuvb+TwvcNMrD+RAZ4DyvkMJUmS/l1k8EiS/h9DtSGzms6igX0DZp2dRe+A3kxpOIWQhBAG1XzyEiyp0K5fdjH39Fy262znyKUjnD9/ntWrVxMVFVXsYUIIwcmTJ1Gr1UXfUFeEq4+uMu7oOFJyU/ii2Rd0de1aIcepp1OPw6aH8Rvpx81dNwkKCioKzPxVx1qV2PJBYz7ZHsqcPX/OVKpiYUB3n8p83N79yd/Mu7WFj8Jg/zQ4t6IwgbaNOwgBWg1oC0BowdASTi+D1HsAnEq24ZsoQ95z+DN45uVV+LB18eJFbty4waBBT/9ef5SeS9CdJC7eTebi3WRCY1LJLxAY66kY5Q2B1/LxGDu2aBlLnz596NOnDwMGDGDbj98yYWg/vlm/ntWrV9O0aVNWj+3+XLMS6tWrh0qlokWLFs+8b2nup9/nSPQRtt3cxq2UW3Sq1omJ9SdWyIwJgJpWNWni0IR1oesw0TWhq2vXooDFo6xH7L+zn7239xKS8OeMLFtDWz6s8yGJ2YnsjNyJ83hn1ieu5/6G+3zS4xMqG5cMEJ0+fbrMwB8UBo+0Wi03b94s9t5tXcOW5tWt2XElhiWHb/LBxksY6eqgVCrIyiusiPgHJ0tDmrpZY6qvQqWjQEepRK1UoNJRkpiQQs3s+/jXdkD1x3JTt7bkGdhhqoljm043ev+/wBHAgAEDWLBgAX369OH48eMMHDiQLl26kJSZxwcbL3I7IZOfhzUs1/xMQghCE0Np69T2yY3/Bd7xfIe5sXOpNqIa0cpo7LR2qJVqbGxs+OijjwCoU6cOnp6ehIWFFQV0K1pidiLv7XuPXG0uMxrPeGL7P/JXXUu8RrPKzcpstztqN7kFuQypNaTMNlLF+SNgFJka+czBo8z8TPbe3suiS4to7diagZ4DK+IUJUmS/lXKPXiUn5/P1KlTefDgAXl5eYwYMQIfHx8++eQT0tLSKCgo4KuvvsLJyYlNmzbx66+/olKpGDFiRLEkmJL0qnV17YqXtRfjj41n4vGJANS3q/+Kz+r1YWRkxPuN3mfHth2ceXSGtCNp3Lt3j+DgYOrUKVz6J4Rg/PjxrF+/ntGjR5dLUszSbLu5jdlnZ2NraMuGjhvwtKq4kqHtqrVj14Vd6PrponNBh7fffpugoKCiSlB/VbeqJXs/bE5CRi6hMWlcj0njbFQiy47cwtJIl8HNCquZ5ebmMnr0aNq0aUO/fv2KBy901IUlzvMy4NoW0JQxa8W0Mry3B8yd+KhDL6xti3/bbm5uTv369Vm7di1paWklZh6VpkArWH08ioUHb5BfINBTKaldxZwhzVyoW9WC+s4WmBvqMvG90pP2zpw5k99++42GLRtiUd8C/1H+DPrPIA7ePYijiSNOpk7PNMPH29ubtLS0Uv+sn4YQgojkCA7fO0zgvUBuJN8AwMPCg69bfE175/YVFjj6w8T6E5l2chqzzs5i6eWlNKzUkITsBC7HX0YrtNSwrMEY3zHoKnWxM7LDz8mvKGfHuLrjOBB1gOmbpnNCcwL/bf4E9AwoFkC6f/8+0dHRjw0e/ZFv6fr16yUCnyodJb3qVqGbjwPHbz7i6I1H6CgVGOmqMNTTQV+lQ3qOhpD7KewOiSFHo6VAK4oFlgC4kMSRG49Y9FZtVDpKhELJh+cdCAl+yJ6Ly0o9rzfeeINp06Yx64svsfdqimefj+m3+gyX76UggCX9fGji+hxJ6B8jKjWK1NxUvKz+3lXWXpberXoz+T+TMWtjxvCDwzHTM6NllZa0dWpLE4cm6Kv0USgUDBw4kGnTpj02eJRfkA8Knns50l9tidhCfHY8v3X57ak+372svVCg4Oqjq2UGj4QQbL25FU9LT2paPV0OMql8uZi5oEDBrZRbtKva7onttULLxYcX2X5rOwfvHiRbk42HhQczm8ys8M9uSZKkf4NyDx4FBARgbm7O119/TXJyMj169KBRo0Z07dqVTp06cfbsWaKiojAwMGDDhg1s3bqV3Nxc+vfvT9OmTdHVLZkEVZJeFRczF37r8hu/3/ydiw8vUt9eBo+ehaMCe+TCAAAgAElEQVSJI3oZetzXvU/k5cK8RkePHqVOnTpotVpmzpzJpk2bGDNmDIsXLy734+cX5DP3/Fw2R2ymcaXGfNXiq8cuUSgPnh6e3B1wF/fP3Kn1eS2uzb3GxIkTWbp0aZn7WBvr0dLdhpbuNrzfwoUPNl5kzp4w0nLyGdnKjQMHDrBmzRrWrFnD999/z/Lly3F3/8vSHKUOdF8O3b4tDCIpdECpKvwXAWkxYGQN6sKgysOH8Xh4lAwO9ezZkylTChPCeng8Pr9L5KMMJm4J4eLdZDrVsmd4C1dqVjJ97HKlfG0+KTkpJOYkkpSdRJoqjWGfDuOK7RUyDDMII4ypF6cW/7MxsMbX1pc5zeY81bKhZw0cFWgLuBR/icB7gRyJPsKDjAcoUOBr68v4euNp49gGR1PHZ+rzRbiau/JL51+4HH+ZDdc3EJYYhrGuMcPfGE5H546P/fZdV0eXLtW70GREE5p0b4JiiIKd4Tvp796fR48e4erqypkzZwBo3Lhxmf24u7tjZmbGiBEjiImJYeTIkSWWm6p0lLSpYUebGnZl9FKcVisoEAJNgSA0LJygZH2+3BeOVitY3M+HX37ayMptx1iwYAFmZmYl9r90L5kDoQ8JsW1H1Y/qIRRK1px5gJeDGQMbVaVnncp4OZTc70Xtub0HBQpaObYq975fR7q6uizquQgreys0VTQcvneYI9FHCIgMQKVUYaprirWBNa71XdE31i/6ogAKH+xjc2IJvxnOsfvHOB1zmppWNVnXYd0LPdgXaAvYenMrjSo1euogj5HaCFdzV87FnWOYdhgqZcnb4WsJ14hIjuDTRp8+97lJL8ZAZYCDsQNhiaXnEbydeptDdw9xNeEqd9Pucj/9PnnaPIzURnSq1onubt2pbVNbBo4kSZLKiUIIIZ7c7OllZmYihMDY2Jjk5GR69+6Njk7ht+/Hjh2jcuXKTJs2jTNnznDs2DE+//xzAEaNGsX777/PG2+88dj+r1y5UmrOFOn1lJOT89hEytLrb9LeSUSaRhI+OhyVUNG0aVOWLFnCJ598QkBAAEOHDmXcuHHlfnOXlp/G/JvzCc8Ip3ul7vSr0g+l4hnzsDyHgoIC+vfvT5dBXbjodJGYrBhiN8Xyuf/ntG715NmVQgiy87UsPZvI0dsZOJur0b+2nVM7NjB27Fi++eYbcnNzGTp0KMOHD3/mz8M/Et0OGDCACRMmFNt2+/ZtOnfuDMDhw4epVKlSyevTCraHpbL+cjK6Ogo+aGBFGxfjx45fQGwAex/uJSkvCUHJv3JUChVjXMegr9RHX0cfA6UBcblxxObEEp0dzcnEkwytOpT2du2f6VqfJC4njoW3FnIn6w5qhZpaZrVoYNGAuuZ1MVOXfyDiZQoKCuLzu5/jUtkFm8M2bNmyhZ9//pmdO3fy22+/ce7cucdWpIuIiOCrr77i9OnTODo6Mm7cOFq2bIlWq8XI6MXyPf3xub8tNIXvLiThY6Mk8It3qe7syI8//lhsBmJMWj4rzidw4UE2KiW4W+nhbWeAt50+NW31MdKtuN9pIQRjQ8Ziq2fLpzVkAKEsGq2G6+nXuZZ2jQxNBol5iVxOvUwDkwY0sG7Ajcwb3Mm8w73se+RqcwGw0rXCQd+Bq2lXmV5jOt6mz1/J7lLKJeZFzOMjt49oZNnoqffb+mArvz34DXdjd0a5jKKSfvHPu5W3V3Iq8RSrfFdhqGP43Ocn/el57vl+uPsDex7uYXDVwdQzr4dSoUSpUHIz4ybfRH5DrjaXyvqVqWxQGXs9e5yNnKlvXl8mxP4bkvf8/05y3F9Pnp6lz+It9+DRHzIyMhgxYgRvvfUWkydP5vPPP6dXr14sW7aMgoICnJ2diYiIKHp4mThxIt27d3/sVHqAsLCwMi9Gev3I8fznW3NgDUtil/Dou0d0cu/Etm3baNu2Ldu2bePDDz+skBlHBdoC3tn3DjeSbjC76WzerPZmuR/jaWTkZTD1xFSO3D9CTnAO+8btw9Wx9IpyeXl5/PDDD8ydOxc3NzcOHjzI4bCHTPv9KnFpuRjmJdOnpQ+VDAW7f1rN7p/XMPqDYXzzzTfPdE6pqamYm5szf/58Pv744xLbvby8uHv3LmlpaSiVhQ/mKVl5XI8tXFb38/l7RD3KxM/Tji96eGNr+uQbgnZb2mGoMqSDcwesDayx1LfEUt8SQ7UhR0OP0tyzeZkJboUQDNgzgNTcVAK6BxRVP3wR++7sY+3VtdxKuYWByoDJDSbT1qkthup/zgNiVlYWru+4Yt3FmoKlBYRdCsPOzo709HQaNmxIYGDgU/Wzf/9+xo8fz7Vrf1amcnZ2Zs6cOfTv37/UfQIDA9FoNLRvX3qw76+f+98fv8Ws3WEUpMYzo2cdWtZ2I/JRJpGPMoiMz2DvtThUSgWj2rgxqFHV56tM+IyEEKTmpnIu7hzjj41ndtPZdHPr9uQdpSKrglex7Erh8kMTtQnulu54WHhgmmuKn7cf7hbu5Gnz6Li1cDZdWQUYnkSj1TBozyDisuI40PvAMy2BE0Kw9/ZeZp+bjUar4eO6H/OWx1soFAoy8zNpvak1HZw7MKvprOc6N6mk57nny9fmMyZwDKcenCqxzdPSk2/afIO9kX15naJUgeQ9/7+THPfXz+PGrELuwmJjYxk1ahT9+/ena9euzJs3jzZt2gDQpk0bFi1ahLe3N5mZmUX7ZGZmYmLy5Go6kiS9Xno16sXCjQtx8neibeW2rFu3jm3btrFo0SI6dOhQIcfcGLaRkEchzGs+75UFjgCMdY1Z0mYJXx75ko3ajfTe1pszo86gr/oz4JKbm8vatWuZO3cu0dHRmJubExgYSFpaGlXV6bxlEsFnW/fi3H0Ymy/eJyuvAOzfxOmjN9ly8xQzUjMxNdR97CySv4qLiwPAzq705UYzZ84kPDyc67HprDkRxdmoJOLS/syjVN3WmFWD6tK+pt1TzRaLyYghLjOOyQ0ml1rpRlgLPK3LvqlQKBS84/UOE45NYOvNrbzl8dYTj1mW2IxYfr3xK2uvrcXDwoOBngPpW6NvqUmlX3eGhobYZ9ijUWiIM46jV69eHDlyhG7dujFnzpyn7qdDhw74+fnx22+/ER0dTUFBAQEBAQwYMIC0tDQ++OCDYu1//vlnBg0ahK2tLTExMaW+R5KSkvj000/ZuXMn4eHhYOOG9+B5zA6MYXZgTFE7e1N92nraMq2zJ5XMKqbS2c3kmxy+d5i4zDhiM2OJzYwlLjOObE02ULhsRibLfnbD3xiOo4kjlU0qU8u6VtGsz7CwMDwsC5fE6uno8a7Xu8y/MJ8dt3Y8c4BOK7SsClnFtcRrLGi54JlzJykUCjq5dKKuXV2mn57O7HOz2XpzKw7GDigVSrI12fR27/1MfUrlT61Us7jVYo7eP0p2fjYFooACbQEqpYo3q71Z7pUvJUmSpLKVe/AoISGBwYMHM3369KKcCnXr1uXYsWN0796doKAg3NzceOONN1i8eDG5ubnk5eURGRlZPIeHJEn/CBamFrTWbc1xu+PgVVhGfdSoUQwdOpSwsNLzGDwNIQR30+5yJ+0OyTnJJOUkkZSTxK2UW5yLPUerKq3oVK1TOV7J81EoFExuM5mHKx5yyPwQC3ctZGr3P/P6tG/fnuPHj9OkSRPWrFmDUqmkXbt2HD9+nP/85z8kJCRgaGhIwIc/YWxswv3kbMLj0vjtyEUOaRvR+IuDZNwLZWhbb2YM9kdH+fiAzsOHDwGwt//zm1pNgZZL91I4eiOeGI0r1wxtWLP0JMZ6Kvw8bfGsZFr0r43Jsy0FuPjwIgD17Oo9035/5efkh4+ND7POziIoLoi+Hn3JK8gjNS+VfG0+Gq2G/IJ81DpqsjXZfH/1eyz0Lfiwzoe4mLlwJvYMu6N2F52Lv6s/MxrPQFfnn51jr5FLIw5FH8LuLTsG1BzAli1bnqsfHR2dYrOMPvroI/z9/ZkwYQLvvPMOhoaFM7aWLFnCuHHjsLCwIC4ujsjIyBIJk3///XeGDh1KSkoKzZs3Z+zYsbRo0YJOnTpz8lYCSZl5uNoYU83GCOMKnGUkhGDW2VlsjtgMgJW+FZWMKuFm7kazys2oZFSJSkaV8LDwwFjXuMLO45/qj8DMk7xd421OPjjJjNMzSMxJpKdbz8fmpUvKSeLUg1OcfHCSMzFnSM5NpqNzR9o7P/+SVjsjO1b6rWTTjU3sjNpJVGoUd1Lv4GnpyRvWj0+lIL0c+ip93nR+dV8ESZIkSYXKfdna7Nmz2bt3Ly4ufyb1nDdvHp988gnZ2dkYGxsXJcTctGkTv/32G0II3n///aeahSCnvv2zyPH8d9AKLe/ufZc7aXfY32t/0fKg5xn/e2n3+DH0RwKjA0nITii2zUBlQCWjSrRybMVg78GY6f198tbk5ORQZ1kd9NDj8vjLAERHR+Pk5MT06dP57LPPUCgUZGRkYG5uTu3atbl06RLLli2jc+fOODs7F+tPo9Hg6NOC/KoN0atcE7WlA3amejSoZoWFoRoDXR0M1Droq3XI02ixN9WnjactgXt20LdvX85evEKi2pZDYQ85Eh5PclY+ah0F9mb6VLU0ws/Tlh51qmBm8GKVkGaemcn+2/s50e9EqUvOnvY9kF+Qz+qrq/kx9MeiWSFlqW1Tm0dZj4jJ/HMWSzWzanSu1plOLp1wNHl5CbBfpfXr1zNs/DBcZ7jiUsmFnzr/VG6/E0eOHKFNmzb8+uuv9OrVi3HjxrFs2TJ69uzJ1KlTqVevHt9//z2DBw8GIDk5mbFjx7Jx40Y8PT3ZtGkT3t7Pn+fmRe2/s5/xx8bT16Mvo31GV3gifalQab/vmfmZjDsyjjOxZ1Ar1fg5+dHLvRf17esXy1N3NvYsow6NIk+bh6W+JU0dmtKkchPaV21f7oHglJwUVEqVDByWM3nP9+8mx//fSY776+dxY1ZhOY8qinwD/rPI8fz3uBJ/hUF7BxVbvvT/xz9Hk8Px+8cJTwonMScRIUTRshcFCvK1+ey/sx8FCppXaU4ThyZ4WHhgaWCJhZ7F3z5nzZBvh3De+DwzXGbQu3lv1qxZw7Bhw7h27RpeXn/m/GnQoAFBQUFYWloSGxtbZhXKqVOnsnTpUvq9/TY/H79Oj7GzuJ0myMzTkJVXQJ5GW6y9jlJBVXUGoTduYurqS36BwNxQTRsPW/xq2tG8ujUm+i9eNvuv/Lf7U8W4Csv9lpe6/Vk/A9Lz0jkbexYLPQss9S1RK9WoddSolCpyC3LJzM+kunl1cgpyCIoLIi4zDm9rbzwtPf91FXdu3LhBjRo1aPJWE7K6ZFHPrh7L/ZaXS2n0goICnJyc8PLyQk9Pj127djF+/Hi+/PJLFAoFNjY2dO3alXXr1rF3716GDh1KfHw806ZNo2fPnk8sjlGRMvMz8f/dHysDK37u/HOplbakivG43/eI5Ai2RmxlZ9RO0vPSqW9fn29af8O+O/vI1mSzOmQ1VvpWzGk+B09Lz5dSAEEqX/Ke799Njv+/kxz3189Lz3kkSZL0//nY+uBj48OG6xtoVKkRidmJBCcEcz70PAnZCdxKucWlh5fI0mShUqiw0Lf482FfgPjfP60cWzGx/kRsDW1f7QU9h1n9ZtHu93asO7eO3s17s2/fPqpUqULNmsXLSzdv3pygoCB69epVZuAICmd6Tpo0CY1Gw4bKldG7uJFT339ftF1ToCVXo0VXpSTiYToBwTGsPxaOjpE57zZ2pl1NO+pWtUClUzEPYUk5SdxOvY2/q3+59Wmia0K7qu2e2M5AZUCLKi3K7bivo+rVq+Pp6clbTd7CqZET009PZ/zR8Xzd8usXnqnxRxXVBQsWoFQqWb58OSNGjCja3rx5c44cOcKwYcNYs2YNXl5eBAQEULdu3TKXqxZoC1AqlBUe5Nt4fSPx2fEsbL1QBo7+Rtwt3JnScArj6o5j281tfBn0JX5b/MjML8yPaaJrwpI2S6hqWvUVn6kkSZIk/TvJuyZJkl6a97zf479H/kv3Hd3/fDEKdJW6VDGpQheXLrRzbkc9u3r/yIc6BysH9OL0uGd6j/z8fA4dOkTv3r1LPCy3a9eOhQsXMnDgwMf2p1QqMTMrXIY0YsQIFi9ejLOzM926dcPIyAhDQ0PMzMxQ6xni5WCGl4MZt7bMZ+/evXzy/agKu84/nI89D0BD+4YVfiypJKVSyfXr14t+ztZkM/f8XNpubouzqTNOpk44mjhia2iLWlk4e0upUGKia0ID+wZP/B0cPnw4x48fZ+bMmXTs2LHYtubNm7N9+3bWrl3LpEmTmDlzJnp6ZefL0gotww8OJzYzlskNJldY4C89L53119fTyrEVtW1qV8gxpBejr9Knv2d/jNRGrApZxWeNP6OefT30dfTlMjJJkiRJeoX+eU9nkiT9bbVxbMPc5nNRosTawJq02DQaeDfARG3yr1lS5G3ozWWzy6zdsZbU1NRSc7116NCBiIgIqlev/tT9zp8/n5iYGKZPn8706dOLXler1fzyyy/06tULKEyYXValtfJ2JvYMJmoTalrVfHJjqcL19+yPg7EDR6OPci/9HudizxEQGVBqW3sje9pXbU9jh8bUtauLgapktTN3d3fOnz9f6v79+vXj/PnzfPjhh0XFMx4nIDKA83HnsdK3YtThUbR2bM2kBpPKvRLexrCNpOWlMaL2iCc3ll6pbm7dnrkCmyRJkiRJFUcGjyRJemkUCgVdXLoU/RyWEoaprukrPKOXr2ftnly+f5l5m+dhZWVF586dS7RRKBTPFDiCwmVEP/30E++//z5JSUlkZWWRmZnJ6tWrGTFiBC1btsTa2pq4uLhildYqihCCMzFnaFCpQamJsqVXo5VjK1o5tir6OUeTQ1JOEhqtBo1Wg1ZouZN2h80Rm/kl/BfWX1+PWqnG19aXHtV70Lla56cK9Do4OPDrr78+1Tml56Wz6OIiatvUZm2HtWwM28jK4JV0296NMb5jeNfr3TL3zdZkczbmLA8yHmCmZ0YXly5lnt+DjAesvboWPyc/GdCUJEmSJEl6RjJ4JEmS9BK92fRNJnw1AR1PHUbWGFlU5vx5aIWWe2n3yNJkcS/9Hlb6VrRu3brYw3OzZs2oW7cukydPZs2aNTx8+PClVLmKTo8mNjOWwd6DK/xY0vPTV+njYOxQ7DU3Czf8qvqRrcnm0sNLnIk5w/EHx5lyYgq7InfxaeNPy3VG0Lpr60jKSWK533J0dXQZ7D2YTtU6MefcHOZfmI+prik9qvcoap+ck8yx+8cIvBfImZgz5BTkFG2zNrCmsUPJmU7JOcnMOjMLhULBpAaTyu3cJUmSJEmS/i1k8EiSJOkl0tfXx/q+NRlNM3Cr5fbc/eQX5DPu6DiO3T9W7PWqplWpZloNG0MbbAxtMNU1pfns5uw8sJO4uLiXMvMoLS+NtdfWApT6IC+9HgxUBjSt3JSmlZvyUb2P+DX8V5ZcWkKPHT0Y6zuWt2u8/cKzyuKz4tlwfQMdq3XEy+rPioP2RvYsarWIkYdGMuvsLK4lXMNE14Qrj65wOf4yWqHF3sientV70sapDa7mrvTd1ZeVwStpVKkRCoWC/IJ8jj84TsCtAI4/OI5Gq2FKgynYG1X8zDtJkiRJkqR/Ghk8kiRJesm+Gf4NM8NnsjpiNS3dWj519SCt0BKVEsWl+Evsu7OPoLggRtQegYeFB5VNKhOeFM6BOweIzYwlJCGEpJwkAFR2KmwG2OA/wh+NRkP37t2fcKTnk5STxIbrG/g1/Fcy8jPwd/XHycSpQo4lvVxKhZL+nv1p7diaWWdn8WXQlxy+d5ilbZYWJTEu0BaQmJOIhZ4Fah31E/vUCi1zzs5BIzSM8R1TYrtKqeLrll8z++xsdkbtJF+bT3Xz6gyrNYw2Tm3wtPQsNstuiPcQ5p6fy1dBX6EVWvbe3ktybjJW+lYMqDEAfzd/3C3cy+8PRZIkSZIk6V9EBo8kSZJesvr16vON2ze8s+8d+u7qS+/qvalkXAl7Q3vsjOywM7TDUt8SHaUOeQV5nI09y7ab27jw8AKpuakAWOlb8UnDT+hbo29RvzUsa9Dd7c/AUH5BPql5qegqdWm8vDGpzVJpmt+URo0alev1xGXG8WPoj2yJ2EJuQS7tndszrNYwPCw9yvU40qtXybgS37b9lh2RO5h5eiaD9g7C3sie++n3eZDxgHxtPiqFiuZVmjO72ewyc5oJIVgVsorA6EAm1JuAo4ljqe3M9Mz4uuXX5BfkAzw2KNXLvRdHo4/yS/gv6Ch0aO3UGn9Xf5o4NPlHVm+UJEmSJEl6meTdlCRJ0ivgYu7C5i6b+fTUp/wc/jP52vxi25UKJQYqA7LysxAIrA2saevUFl9bX+rY1sHRxPGJiYvVOmqsDawBaJPVhkPmh8h9K5edkTvp7NIZpUL5wtcRmhDKf/b/h7yCPDq7dGZIrSG4mLm8cL/S35dCoaC7W3fMdM34MuhLErITqG5RndZOralkVIno9Gh+Cf+Ft3a+haelJ/oqffR09Ir+m5GcwaPYRxyJPkIXly4Mqjnoicd8mplMejp6rG6/mmxNNkIIDNXPn09MkiRJkiRJKk4GjyRJkl6RSsaVWNNhDUIIknOTeZj5kIdZD3mY+ZD47Hiy8rMw0TXB3cKdllVaPtUDdFm+GPsFXru8OG56nKknp7IxbCODvQfj5+T33Hlr4rPiGRs4Fgs9C9Z0WFPm7BHpn6m1U2taO7UufZtja5ZdXsadtDvkaHLIKcghV5NLTkEO+dp89HT0GFd3HO/WfPepqrc9CwOVQbn2J0mSJEmSJMngkSRJ0iunUCiw1LfEUt8STyvPCjmGiYkJH7z9AcPFcHZG7mRVyCrGHxtPFeMqvOP1Dt1cuz3TTI34rHiG7B9CRn4GGzptkIEjqZj69vX5seOPpW4LvR6Kew131MrnD4ZKkiRJkiRJL5cMHkmSJP2LKBVKurl1o4tLF45EH2Fd6Dq+OPcF84PmY65nToEowNLAkm6u3ejq2hVLfUugMEdNliaL9Lx0riZc5augr0jLTWOF3wqZhFh6JkqFUgaOJEmSJEmSXjMyeCRJkvQvpKPUwa+qH35V/bgcf5nAe4Gk5qaio9ThZvJN5l+Yz+JLi7E1sCU9P53M/Ey0Qlu0v5u5G4tbLcbL2usxR5EkSZIkSZIk6Z9ABo8kSZL+5XxtffG19S322s3km+y4tYOknCSMdY0xVhtjomuCia4JlvqWNK/SXM4ekSRJkiRJkqR/CRk8kiRJkkqoblGd8fXHv+rTkCRJkiRJkiTpb+DF6zRLkiRJkiRJkiRJkiRJ/1gyeCRJkiRJkiRJkiRJkiSVSQaPJEmSJEmSJEmSJEmSpDLJ4JEkSZIkSZIkSZIkSZJUJhk8kiRJkiRJkiRJkiRJksokg0eSJEmSJEmSJEmSJElSmWTwSJIkSZIkSZIkSZIkSSqTDB5JkiRJkiRJkiRJkiRJZVIIIcSrPolnceXKFfT09F71aUiSJEmSJEmSJEmSJP1j5Obm4uPjU+q21y54JEmSJEmSJEmSJEmSJL08ctmaJEmSJEmSJEmSJEmSVCYZPJIkSZIkSZIkSZIkSZLKJINHkiRJkiRJkiRJkiRJUplk8EiSJEmSJEmSJEmSJEkqkwweSZIkSZIkSZIkSZIkSWWSwSNJkiRJkiRJkiRJkiSpTKpXfQLS6yk/P5+pU6fy4MED8vLyGDFiBG5ubkyePBmFQkH16tWZMWMGSmVhfPLu3buMGjWKXbt2ATBnzhzCw8MBePToEaampmzatKnYMe7evVuiv5MnT/Ldd98BIITg4sWL7Nq1C1dX15d49dLLGP8/fPHFF1SrVo23334bgE2bNvHrr7+iUqkYMWIErVu3fglXLP3Vi45/TEwMEydORAiBmZkZCxYswMDAoNgxkpKSGD9+PDk5Odja2jJ37tyiNklJSfTr14+dO3eip6f3ci/+X+xVj7tWq2X48OG0bdu26PNAejle1djfuXOHL774oqjNlStX+Pbbb2nRosXLu3jppYz/H3744QcSEhIYP348AIGBgXz77beoVCp69erFW2+99XIuWiryouMfHR3N5MmTEULg4ODArFmzSox/aff8ZfUnvRyvetyzs7Pp168fH3/8sfzM/zsRkvQctmzZImbPni2EECIpKUm0bNlSvP/+++Ls2bNCCCE+/fRTceDAASGEEL///rvo0aOHaNKkSYl+8vLyRO/evUV4eHiJbWX194fvvvtOLFiwoFyvS3o6L2P8ExMTxZAhQ0Tbtm3Fzz//LIQQIj4+XnTp0kXk5uaKtLS0ov+XXq4XHf85c+aIjRs3CiGEWLhwoVi/fn2JY8yaNUts3bpVCCHEqlWrxLp164QQQhw/flx069ZN+Pr6ipycnAq7RqmkVznuQgixYMEC0bt376LPA+nledVjL4QQe/bsER999FG5X5v0ZC9j/LOzs8XHH38s2rVrJ77++mshROE9gp+fn0hJSRG5ubmiZ8+eIj4+vkKvVSrpRcd/zJgxIiAgQAghxKZNm8S3335b4hjPcw8pVaxXOe5CCDF58mTRrVs3cezYsYq5QOm5yGVr0nN58803+fDDD4t+1tHRITQ0lAYNGgDQokULTp8+DYCZmRkbN24stZ+NGzfStGlTPDw8Smwrqz+AuLg4duzYwejRo8vtmqSn9zLGPzMzkzFjxtCtW7ei10JCQvD19UVXVxcTExOcnJyKZjBJL8+Ljr+npydpaWkAZGRkoFKVnAR78eJFmjdvXqI/pVLJunXrMDc3L/8Lkx7rVY77vn37UCgU8tvHV+RVjj1AVlYWS5cuZdq0aeV7YdJTeRnjn5ubS/fu3fnggw+KXouMjMTJyQkzMzN0dXWpW7cuFy5cKPfrkx7vRcf/1q1bRZ/dderU4eLFiyWO8Tz3kFLFepXj/v333+Pr60uNGjXK/8KkF18XuvIAAAY5SURBVCKDR9JzMfq/9u4sJKo2juP4T3uTcivbN4lpkaagkopsQaguEi2KFoJgLBoQIgzrZiTRSqyoaIHAItrAwjChoIVuEhtBR9CromLAZG5shUJHrCnnvBcvSOIc39Fx5vjyfj+Xc8485/nz8zDP/OecY1KSkpOT5ff7dfjwYRUVFckwDMXFxfVt7+rqkiRt2LBBiYmJA8YIBAK6f/++nE5nyGOYjSdJt2/f1v79+5WQkDDSpSEMscg/PT1dy5Yt6/ea3+9XSkpKv3n4/f6RKgthijT/GTNm6N69e8rLy5Pb7VZOTs6AY/yZ9Z/jrVu3TmlpadEsDyasyt3r9erJkyf9FrGILSvPeUmqra1VTk6OJk2aFK0SMYhY5D9hwgStX7++32t85o8OkeZvt9tVV1cnSXrx4oV6enoGHGOoa0hEn1W5NzU1yefzcYvqKEXzCMP24cMH5efna9u2bdq6dWvfParSP1eNpKamDvr+pqYmrVq1qm9h8Pz5czkcDjkcDr1+/dp0vGAwqPr6euXl5UWhKoQr2vmHkpycrO7u7n7H+XNhidiJJP9z587pzJkzevr0qUpKSuRyudTS0tKXf319fb+sw/l7QmxYkfujR4/06dMn7du3Tw8fPtSdO3fkdrujXiv6s/Kcf/z4sXbv3h294vCvop1/KHzmjx6R5O9yuVRXVyen06n4+HilpaWFveaHtazIvba2Vl6vVw6HQw0NDTp//rzevn0b1ToRPh6YjWH5+vWrDhw4oLKyMq1Zs0aStHjxYjU3N2v16tVyu93KysoadIzGxsZ+tyDk5OT0+zXKbDyv1yubzaZx48ZFoTKEIxb5h7J06VJdvnxZP3/+VCAQUFtbmzIyMiIvCEMSaf6pqal9XwCmTZumzs5OrVy5UlVVVX37NDQ06OXLl9qxY4fcbrdWrFgR3aLwr6zKvaCgoG/7lStXNGXKFG5fizErz/muri4FAgHNnDkzihViMLHIP5T58+fL5/Pp+/fvSkxMVEtLi+nVyoieSPNvbGzUoUOHtGjRIt26dUtr164Ne80P61iVe25ubt/24uJi5ebmym63R69QDAnNIwzLtWvX1NnZqcrKSlVWVkqSSkpKVFFRoYsXL2revHnavHnzoGO0t7dr+/btpttdLpdKS0sHjNfe3q709PSRKwZDFov8Q5k6daocDof27t0rwzB05MgR/tuWBSLNv7S0VOXl5QoGgzIMQ2VlZQP2OXjwoFwul2pqapSWlqYLFy5ErR6Eh9z/v6zMvr29XbNnz45OYQhLLPIPZezYsSouLpbT6ZRhGNq5c6emT58+IjUhfJHmb7PZdOzYMSUkJGjhwoUh8zdb88M65I5Q4gzDMKyeBAAAAAAAAEYnnnkEAAAAAAAAUzSPAAAAAAAAYIrmEQAAAAAAAEzRPAIAAAAAAIApmkcAAAAAAAAw9ZfVEwAAAPivaW5uVlFRkRYsWCDDMPT792/l5+crNzc35P4dHR169+6dNm7cGOOZAgAARI7mEQAAwDBkZWXp0qVLkqTu7m45HA7ZbDbZ7fYB+3o8Hr1//57mEQAA+E+ieQQAABChpKQk7dmzR8+ePdPdu3f18eNHffv2TdnZ2SosLNT169f148cPZWZmas6cOaqoqJAkTZw4UadPn1ZKSorFFQAAAJjjmUcAAAAjYPLkyXrz5o2WL1+umzdvqrq6WtXV1RozZowKCgq0ZcsWbdq0SaWlpTp+/LiqqqqUnZ2tGzduWD11AACAQXHlEQAAwAjo6OhQZmamXr16JY/Ho+TkZAUCgQH7tbW16eTJk5KkX79+yWazxXqqAAAAQ0LzCAAAIEJ+v18PHjzQrl271NPTo/Lycvl8PtXU1MgwDMXHxysYDEqSbDabzp49q1mzZqm1tVVfvnyxePYAAACDo3kEAAAwDB6PRw6HQ/Hx8ert7VVhYaFsNpuOHj2q1tZWjR8/XnPnztXnz5+VkZGhq1evasmSJTpx4oRcLpd6e3slSadOnbK4EgAAgMHFGYZhWD0JAAAAAAAAjE48MBsAAAAAAACmaB4BAAAAAADAFM0jAAAAAAAAmKJ5BAAAAAAAAFM0jwAAAAAAAGCK5hEAAAAAAABM0TwCAAAAAACAqb8Bu+sDgFzRIX0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,4))\n",
    "sns.set_style(\"whitegrid\")\n",
    "sns.lineplot(x=\"Date\", y=\"Close Price\", data=stock_df,color=\"black\")\n",
    "sns.lineplot(x=\"Date\", y=\"botlinger_avg\", data=stock_df)\n",
    "sns.lineplot(x=\"Date\", y=\"botlinger_upper\", data=stock_df)\n",
    "sns.lineplot(x=\"Date\", y=\"botlinger_lower\", data=stock_df)\n",
    "plt.legend(labels=[\"Stock\",\"Botlinger Avg\",\"Botlinger Upper\",\"Botlinger Lower\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = stock_df[\"Close Price\"]<stock_df[\"botlinger_lower\"]\n",
    "stock_df.loc[mask,\"call\"] = \"Buy\"\n",
    "\n",
    "mask = (stock_df[\"Close Price\"]>=stock_df[\"botlinger_lower\"]) & (stock_df[\"Close Price\"]<stock_df[\"botlinger_avg\"])\n",
    "stock_df.loc[mask,\"call\"] = \"Hold Buy/Liqiudate Short\"\n",
    "\n",
    "mask = (stock_df[\"Close Price\"]>=stock_df[\"botlinger_avg\"]) & (stock_df[\"Close Price\"]<=stock_df[\"botlinger_upper\"])\n",
    "stock_df.loc[mask,\"call\"] = \"Hold Short/Liqiudate Buy\"\n",
    "\n",
    "mask = (stock_df[\"Close Price\"]>stock_df[\"botlinger_upper\"])\n",
    "stock_df.loc[mask,\"call\"] = \"Short\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Series</th>\n",
       "      <th>Date</th>\n",
       "      <th>Prev Close</th>\n",
       "      <th>Open Price</th>\n",
       "      <th>High Price</th>\n",
       "      <th>Low Price</th>\n",
       "      <th>Last Price</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Average Price</th>\n",
       "      <th>Total Traded Quantity</th>\n",
       "      <th>Turnover</th>\n",
       "      <th>No. of Trades</th>\n",
       "      <th>Deliverable Qty</th>\n",
       "      <th>% Dly Qt to Traded Qty</th>\n",
       "      <th>botlinger_avg</th>\n",
       "      <th>botlinger_upper</th>\n",
       "      <th>botlinger_lower</th>\n",
       "      <th>call</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>2017-06-01</td>\n",
       "      <td>311.8</td>\n",
       "      <td>312.0</td>\n",
       "      <td>316.75</td>\n",
       "      <td>310.8</td>\n",
       "      <td>315.0</td>\n",
       "      <td>314.20</td>\n",
       "      <td>315.10</td>\n",
       "      <td>8253042</td>\n",
       "      <td>2.600519e+09</td>\n",
       "      <td>91321</td>\n",
       "      <td>4704937</td>\n",
       "      <td>57.01</td>\n",
       "      <td>298.089286</td>\n",
       "      <td>326.064967</td>\n",
       "      <td>270.113605</td>\n",
       "      <td>Hold Short/Liqiudate Buy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>2017-06-02</td>\n",
       "      <td>314.2</td>\n",
       "      <td>316.1</td>\n",
       "      <td>319.90</td>\n",
       "      <td>315.2</td>\n",
       "      <td>319.3</td>\n",
       "      <td>319.20</td>\n",
       "      <td>317.86</td>\n",
       "      <td>11073749</td>\n",
       "      <td>3.519852e+09</td>\n",
       "      <td>65848</td>\n",
       "      <td>7008906</td>\n",
       "      <td>63.29</td>\n",
       "      <td>301.035714</td>\n",
       "      <td>328.559730</td>\n",
       "      <td>273.511699</td>\n",
       "      <td>Hold Short/Liqiudate Buy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>2017-06-05</td>\n",
       "      <td>319.2</td>\n",
       "      <td>315.0</td>\n",
       "      <td>318.25</td>\n",
       "      <td>313.3</td>\n",
       "      <td>317.5</td>\n",
       "      <td>317.45</td>\n",
       "      <td>316.83</td>\n",
       "      <td>9482413</td>\n",
       "      <td>3.004339e+09</td>\n",
       "      <td>69774</td>\n",
       "      <td>6130621</td>\n",
       "      <td>64.65</td>\n",
       "      <td>303.464286</td>\n",
       "      <td>330.295422</td>\n",
       "      <td>276.633149</td>\n",
       "      <td>Hold Short/Liqiudate Buy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Symbol Series       Date  Prev Close  Open Price  High Price  Low Price  \\\n",
       "13    ITC     EQ 2017-06-01       311.8       312.0      316.75      310.8   \n",
       "14    ITC     EQ 2017-06-02       314.2       316.1      319.90      315.2   \n",
       "15    ITC     EQ 2017-06-05       319.2       315.0      318.25      313.3   \n",
       "\n",
       "    Last Price  Close Price  Average Price  Total Traded Quantity  \\\n",
       "13       315.0       314.20         315.10                8253042   \n",
       "14       319.3       319.20         317.86               11073749   \n",
       "15       317.5       317.45         316.83                9482413   \n",
       "\n",
       "        Turnover  No. of Trades  Deliverable Qty  % Dly Qt to Traded Qty  \\\n",
       "13  2.600519e+09          91321          4704937                   57.01   \n",
       "14  3.519852e+09          65848          7008906                   63.29   \n",
       "15  3.004339e+09          69774          6130621                   64.65   \n",
       "\n",
       "    botlinger_avg  botlinger_upper  botlinger_lower                      call  \n",
       "13     298.089286       326.064967       270.113605  Hold Short/Liqiudate Buy  \n",
       "14     301.035714       328.559730       273.511699  Hold Short/Liqiudate Buy  \n",
       "15     303.464286       330.295422       276.633149  Hold Short/Liqiudate Buy  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_df = stock_df[stock_df[\"call\"].isnull()==False]\n",
    "stock_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x2660225d688>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0lWI3k5ZgYe7GPQB6dGHKygL993RPFWWVFzPaU/vSrQd4/JZezHx/N+9NHUKNN8CcP36n29DCu7LoIMuoamQx5IXcXxd6LwunQSC4yAntpBgqimrJ7o5NoUM7C+8+OJiAClaTTKq9bs5Wu+Yar58yh5e0eAtF5S698kFzFhJtJiD4ZJYab6GixkuJw0NRuYtFm/Y1ew29oPUS2qVx19EK/fMPKCpvbjvEnBF9SLSZqHD5eHPbIZ6542oAjpXX1Nk/sdxfFquVkmpP2Hkv5F4WToNAcBFzrvbQLTHS+nyp71pS7ZZzHqdFF3YdrdArH0LFjK+O7c+SLd+zv9ihRxh2Ha0g/+NClk8cIByGixwtjaUCS8fnMHVVgf75r5symHuGZtbRtBgk8CkqP1ywtd626829vxRFpcaUyMQl2+rs5wu1l6NyGm6++WYCgbOiCqPRSKdOnZg5cyZXX311zBYnEAiaRn3K6g+n57YphwGivxbtuLR4i/50WOMN8MStvbh7+VdkJNmo8QZ4dWx/kuwm8kf25bkN/2LX0QoA3t5+KOadJgWti0q3h/IaH698sZ/nR/Ylf2RfUuPNWE0GfAEVr1+pE61698HBvLL5e+DC7asyp5epq3e16H6OymkYPHgwt956KwMGDGDXrl2899575OXl8cILL/DOO+/Eeo0CgeA8aYtVEvUR7bV4/QHS4i08fkuvsKfD18b15+Y+6Tz8o544PH6e2/AvAJ64tRclDg8QTFP88sYrRWThEqPGozB99U5+97NrKTrtItluwuHxMy2CFkaLVlW5/awrKNLPcSH2VWvYz1H1aTh06BBDhw7FbDYzaNAgSkpKGDJkCLIs2jwIBK2Z1t4eujFEey1mo4FHbuzJ29uDeeh3HxzMnBF9+MMX+5l1W28CqsrM94PphxKHB5vZwLyfXqMfl2Q3CYfhEsOvqAztnkLH9laMBokUu4U3tx2q0wV06rAeQNDuTlaGV1RciH3VGvZzVJEGs9nMO++8Q3Z2Nrt27cJsNvPdd9+FpSwEAkHrQlFUVFRW3T+IQ6VOvdSwpaok6hNkRku0KvEUu5krO8RHzEPXePw8v6FQFzgmxpmZ+d63emoiI8nGuw8ObtbrFrR+rEaZ8UMu5+f/82WYvWgluUCYFmb5xAFYjLJe6qi9ZpAjCyPPl9p7JslmYum4bD1F0RJVT1E5DYsWLWLp0qVs3ryZK6+8kgULFrB7927mzp0b6/UJBILzIJIYcNn4HDolWkm0XfgcvcVqbVCQGQ3RKtJlWcJkkPH6FV4a3Y8Kl4+lWw8wa/1u3po0UBe4LZuQg4pKWoKZZRNy9JLLtFZedipoPA05rIqiElDB61eYM6IPS7ceCOvdMWVlARB0KDOSbHw4PVf/ktZs0WSUcbj93PlKXYHi+e61+oS/7aWaFq16isppeO211xgzZgxXXHGF/toNN9wQs0UJBIKmEUk0OGVVAR9Oz22R0LvRnsjEN5suyIxGke73KxRXe8Lq6rV8tMUoseXxG5AliXiLAX8Anry9N4dLa5i7cY8eiWnKzV7QutC+fF/+fB95OV1JsZup8fppbzMSbzaxv8RRb6WN5hxoX9id2tvC7EKzxZJqDxPf2NGsAsX6hL9rJmW3qIg5Kqehf//+LFy4EKfTyU9/+lNuv/12rFZrrNcmEAjOkwstmDpX6kFBjtl6Qn+3ySgTCChMXVVQJx/98phrqXL5mbKqgKHdU/QBRNrsicdv6cWiTfvabHWJIDJlTi8vf76P6cOvoNzpI6CoHCxx0iXJSqkU/FmkSpuZ7++mU3sr22YNP+cTfSz2W33nVFp4ZFRUTsOtt97KrbfeSnFxMS+++CK/+c1v+Prrr2O9NoFAcJ5cyNay5+oFASCjxGQ9kX73a+P66+Vx2V0TmTqsB4k2E12Tbew5Uc0f7s4mKc4ccfbE1GE9mLKyoE1Wlwgi4/UHeGj4FSRYTfgDqu4kTsrNxCjLPPjDHnj8Sp1KmzfuHYDdYiAx7tzOY337LaCoKIp6XlGr+s4pozT6XM1JVC7L8ePHWbJkCZMnT8ZqtbJ8+fJYr0sgEDQBTTSoKa1jKZhqaKKfht9Z0azrURSVkmoPRRU1nKx0kxZv0X/3H77Yz8LR/fjTL3J57s6ryf+4kHmf7KXkTMpi1JLtjH/9K+4Zmkl210Q9EpGX01UXurXF6hJBZGxmAwZZZuIbO7hr6d/J/7iQe4Zm8ua2Q6TGm0mJt2A2yLw0uh/LJuSQFm9h2uqd2ExG2lmjs88Ue1AXE2rf8/OyeGFjYdQTWCOdM9Ke8Tsrzut8zUVUkYaHH36Y0aNHs3r1auLj42O9JoFAcB7Ubi/bMy3+ggimognNetxuel3ePK1uQ6MLafEWHrmxJ4vvvhZvQKXGG8BuNjDvkz3k5XQl/+NCispdzBnRR6+519YXafZEtdvfJmZwCKLHr6h10lVvbz/EzFuuQpIk/IpKgtXArb//f2GaBlmiUSLdVLs5rNW0pot49o7oolaRUnyRhL/79h07779FcxCV07B+/XqKi4upqqqisrKS4uJisrOzY702gUAQJQ21l421oC/aVEhztdUtc3r5aOdRVj8wiGq3n8Wb/x2xvLKd1aivKdFmiujYhM6eSEuw0D3N3iLVJYLY4fMrYZ99dtdE7hmayaS3/qHby9LxOTx2U09e+r/9zFq/m/yRfRsdbZJlWXdSNaKNWjWU4mtt2pqo0hNPPfUU9957L+PGjSMvL48XX3wx1usSCASNoL72sucbGo2ElhI4Vl5DSbUHRQlO+LuQqRBFUVEVhTuuzeBgiZOpqwrIy+mqOwxwNopgNZ1thKPNmAgldPbEsgk5dGlvIznC8CtB26Z2Q6Spw3rUsZepqwoY1T9DT1dlptobZb+KomKQYdn4nPPaB9Gk+FoLUTkNBw8eZOPGjVx//fX8+c9/xmJp2PMJBAI8+eST/PznP2fcuHH85z//4ciRI9x9992MHTuWZ599FkUJijleeeUV7rrrLn7+85+ze/fupl+RQHAJEutqCe1JaNSSbeTO38KoJdvYd6paF3lpYdRts4bz4fTcmEQ4/H6FPSer+NeJaqauKiDObNCjBZGu3eHxMz8vK/gkufUAC+/KCruhL5uQw7UZ7VkzKZveHdthNIoOtxcjtfUGKXZzRHsJqCpTh/UgI8lGnMUQtf1qe+POV7bx9EffkT+yL1sfH8YH04dGvQ9aQ3voaIkqPWG325EkiZqaGpKTk/H5fA0ev2XLFgDWrl3LV199xYsvvoiqqjz66KMMGjSIZ555hs2bN9O5c2d27NjBe++9x4kTJ3j44YdZv359069KILjEiHW1xLmGRcVqYqaW51UUBbdfYcrKAl4a3Y+icpceJdD+W/vai6s9rC8IpjEqanzUeP0sGt2Pju2sxFkM+kjtPXsOI6cnNfvaBa0DWZbolZ7Auw8OxqeoGGUpor0YZEmPmtWenNoQoXujqNzFpLf+oTeBitbxuJDVTk0lKqfh6quv5vXXXyc9PZ0ZM2acs330TTfdxLBhw4Bg5UVqaipbt25l4MCBAPzwhz9k27ZtZGZmcv311yNJEp07dyYQCHD69GmSk5ObdlUCwSVGks3E6gcGUVLt0UvKZvy4V7OlCFriScjvVzhe6aK42kNqvIVShyfMWVi69YBeKqmNs9a7X07IIdVupv9lSSTZTMSZjS3WQU/Q8siyREBVkQCLUdLHX2v2smRcf4wydE60NXpYWWP2Rn39TKJtkd4aiMpp+NWvfoXD4cBqtfLXv/6VrKwsAL799lv69esX+cRGI7NmzeLzzz9n8eLFbNmyBUkKfhB2u53q6mocDgeJiYn6e7TXG3IaPB4Pe/bsifoCo6F3797Ner7moLmvUcPtdsfs3M1Fc6yxpT7TWNjnubBYrdSYEsP60S8d3594pbrZlNb2lI6R69B9HvbsOXLO95/rM7VYrRjtiSjIyChIvhoqsTN11U7S4i387ufXUub0hjkLs9bvZtGmfTxyY08uTwnOjPAHAkiKH7/zNKfPDBQqrfW7av+7JfZES95zWsJGLwQNfY4pnTNQVZmSag++gEKy3cRbkwYiS6CoEFACKCq4y0+y74Q74jnqI9q9EXGfjssmzleBx+3GYrWyZlK2vgf8zrKI+/dC2Wt9NhqV0wDopZY/+tGP9NdeeuklVqxYUe975s+fz+OPP86YMWPweDz6606nk3bt2hEfH4/T6Qx7PSEhocF1WCyWVvkl39zE6hr37NnT6v9+bWGN9dES9llS7dGrJkATdu3kw+m5dO3SpdHni/Q0BER8EspITYgqtN/QZ6rlhLU20xlJNtY8MIip//sVReUufveza1FUlfUFR8OchfyRfemWaudYeQ0g0SHBGqJLiD7d0Jbt7Xy4WO+h9X2OiqJyrMJFSbVbj8IFu0N6iDMbqPEG6JpswyBJdLu8W6O0DFrqbNmEHL10t769EXGfrt7Fh9Nz6R4xtRfZhlvaXqN2GiKhqmrE1z/66CNOnTrFlClTsNlsSJJE3759+eqrrxg0aBB//etfGTx4MJdddhkLFy7k/vvv5+TJkyiK0iypCbcvgNXU+nJBAkEsaM7UQUOlX9EMizofIukliqs9+r9T4y2cqHQxKTfYkEebUJlsN1Pl8jL7g3/ywfShQsgoCCPU+fX4Fd1huGdoJku2fE9eTlcSZCOZqXb8ikLhiWr6ynJU2pza++TmPumseWAQBlmqd2+0JbFjQzTJadDSDbW5+eabefLJJxk3bhx+v5+nnnqKHj16MGfOHH7729/SvXt3brnlFgwGAwMGDOBnP/sZiqLwzDPPNGU5OlaTgW6zN0Z9/OF5P2mW3ysQtATNKaI6l+CxKWJHRVEpdXpw+wIYJAmb2UCizRzxZqqlIorKXRhkiTe3HWL68Cu4e+DlxJkNVLv9JMaZ2HXkNGsfHIzLG+B4hYv0eItwHi5BFEUlPq0z/zntxCBJ2C0GTlR6mLzia14a3Y/0BIvuMLy9/ZA+uCotwYIvoGAxGvjknye4skN0zQtr75PPCospPFHd4MyStiR2bIgmOQ31ERcXx+9///s6r69atarOaw8//DAPP/xwLJYhEFwSNKeIKlZPQ5FGYy+8K4sO7azEW411bqbrC47qIV+jQWJSbvjT4eUpcbSzGrnp6k54/QoBRWXNl4e549oMruqQIByHS4hg+qEGj2JAVlUwgMMT0G2twuVDliQ9UqU5DMl2Mw63n5/84f/p9mgzR/cFfj77pC2JHRuiSTurvvSEQCC4cGh9EtZMym5yn4TajXCgeZ6GjPbEOhGMme/v5khZDUZZqtMcasaPe9ErPZgOMUiQEm/m7oGXk2gzUe3241cU/IqKcuYeJEkSdw++nD99U0Sxw1PvOgQXHw6vF0mSkCUwyBIl1R5OVrp1W1u69QAmo0Sc2RBmQy6vn6c/+g44a49+JbrvtPPZJxeqn0msiSrS8Prrr3P//ffXef2OO+5o9gUJBILGI8sSzrKT9QrBGhpbHUqsnobqG40dZzbg8gbq1UukJVgornaz/uuj3DXgMgyyREBRef/r/zC4RxqAXhe/ZFx/7snNxB9o2SmAgguH369wpMzNtDPlk2/eex1z/vgdc0b00aNXu45W8PyGQp66vTc9O8QHu4oCj679hl1Hzw5/Kip34fNHZzvaPnn583165CI9wULSmbbk9RGrfiYXkqichr/85S/ce++9GAzhXtSYMWNisiiBQNA8RDO2OpTQp6FzORn1aRQinree0dg13uDvCL2Zhjo5NrMBh9vPiH4ZYbMCtKFCs2+7Cgje8Kev3snaBwdjNIjUxKVCscOjOwyA3iU0tCy3qNxFicNDvNVI5/Y2ypxevjtWSYnDEzY6vcYbwGSQoxplLcsSPdPi+eVNV9apmmiL0YPGEJXTUF5ezg9+8AMyMjKQJAlJkli7dm2s1yYQCJrIuYSNkYjmaSiSM6JpFLql2OvcNLXR2JGOD41i1D6v9uS4+oFB5I/sS5zZoE8QLHF4qHCd7U5bVO4ioKh0bG893z+XoI3hC4QPo9Iaf+06WsGiTfv0SpvQpk0pdjOXp8Tx6thsarwBZr5/tinYy2P64fD4I9pwbcpdPt1hgOj21sVAVJNuoHYAACAASURBVE7D0qVLY70OgUAQA2IlbIzkjMx8PzgdMMFqqnPT1EZjfzB9KG6fgkECu8WAN6ByotKlRzRqn1d7cqxy+Ui2m3lozc4wp2PBp/v035GRZMNkkIUI8hLCZJDDIljajJGZ7+9m19EK8j8uZPnEAWFdHmVZoluKnVNVbkYv+3uYDc9Y9229Nlybi6WEsrFE5TQYjUYWLlxIeXk5t9xyC7169aLLeTSNEQgEF5amlHk1pIWo74YZZzbUe9OUZYn0BKt+7khpk9Bx1nD2yfF4pZudh8tYcd9AAoqK3WLE6fVTckb0qI03To+/eJ/wBHVJj7fw2vgcPUVR4vCQmmDhvalD8AUUVBUCEcSNsiyhqGqjbTiUi6WEsrFE5ZLPmTOHvLw8vF4vAwYMYO7cubFel0AgaAbOd2x1Q1MtoX71uKZR0M6hjdK2p3TU3wv1p00kSQo7r/bkuL7gKD/s1YF5n+zhYKmT4xUu2luNrJsyhL/OHMa6KUNEqeUliNEo0yvNztoHB7Pl8RtYM3kwEuD1K3xReJK9J6uZ+MYOSp11K2oasuGAoobZayQu5Ej41kRUkQaPx8OQIUN47bXX6N69+zlHYwsEgtZBY4WNWmRBkiRe/nxfvfnaSFUWoRqFcwkw64tUGKTwdtUlDg8d2ll5YdQ1qIrKc3f2RVVVMXhKoGM2G+kgSZxyePD6g9GFNV8e5oe9OrBoU9CGazwBFHu4wDHUhtPiLTxyY08uS4nDIEms/vIwD/zwigZTFI3ZWxcTUTkNZrOZv/3tbyiKwjfffIPZfHF7UgLBxcT5Chvn52VRUu3Vy9JC87XaDTNUoxBaPVFS7WlQgFlfaFeW5UvyRixoGiaTAW/FKaxJHTle4aJ/txQWbdrHrqMVZCTZOFTqxG4x1tkHHdpZWD91CCUOb9jUy/l5WSjKucsvL4YSysYSVSwvPz+fDz74gPLyct544w2ee+65GC9LIBDEitC0QUm1R48w1P6Sn7V+N1OH9dDfVztfK8sSqXYLtjNzXkLbI5xLJNZQaFe7EXdJiiMtwSIcBkFUeNxuOrazYjMZyP+4UHcY5udlsXjz/jCdguYk3/nKNqrcft1hgLO2HxC9CyMSVaRBURRmzpx59k1GIz6fD5Op4UYWAoGgdRGtABGCN08tP5uRZGPZhJwGyyNDUxDnEoldqqFdQWyRZYlOidaI5bmaTkGWpTAn2e1XItq+6HgcmaichilTpnDq1Cm6d+/OoUOHsNls+P1+Zs6cyciRI2O9RoFA0AwoisrJKjdOj585I/qwdOsBdh2tYPKKr1k3ZUjEL/n2NhPvPjiYCpeP1Fpf6vWJGdc+OBiTLEUcFxzqdFyKoV1BbPD7FRI6XMaRMic2k4H0dpYw25ufl8ULGwuZOyqLtARLWCSsndXIm/depzsZS7ceoMThqXcg46VOVE5DRkYGb7/9NsnJyVRWVvL000+Tn5/P5MmThdMgELQB6tMsaHnf2gJE7edPnKl3v7lPOtd0ac+x8ho9KlBfCsLtC/Dfn+7loeFX8M7kwcgSBHweMlIv7k55gpbB71fYe6qaP31TxF0DLiOgqCTHmZgzog+JNpMebdh1tIJn7wimKLRIWFq8hSq3nzl//C5M0GszGzAIU41IVE5DWVkZycnJALRv357S0lISExORZVHeJBC0NiL1V6hPszBnRB/yPy6sI0AMKCovbCzUHYZHbrySMWca4WipitR4S8ToRKnDyz1DM3l1y/fcPfByenVMQEGmzOkVKQhBk6lt376Awp++KeIn/bow6a1/MLR7Cg/96AryPy6sNz2maWpOVrrD2lBrTcoWje4nvt/qISqn4eqrr+ZXv/oV1157Ld988w29e/fmz3/+MykpKbFen0AgaATno1moLUDUzjN3VBbP3hEsvxxTq3PelJUFrJsymJfH9GPGum/DntJUVdUdkjizgZJqDyNf3XbJ9OYXxA5FUTlc5uRIWQ1xZgM13gDd0+zcNeAyJr31D9LiLUwd1oO5GwvDZk/U1uRompp4iyHivuhYq7254CxROQ3PPvssmzdv5sCBA4wcOZIbbriBgwcPMnz48FivTyAQnAPtycuW0pmTVe6I/RXq0yyE9uQPRevRX+r04PJGTkMcr3DjV9SwMPCCT4NDpDSHpNrtJy3BQnbXRF0/cbH35hfEjgqXl1NV7rB0wrsPDiYgSxSVu3h1bDayJPFZYTEl1d4w26ytyZFlCYMsc3OfdPJyuurHrS84isUoC8e2HqJyGhwOBx6Ph/T0dMrLy/noo4/4r//6r1ivTSAQnINo+ytE0izU7smvna/M6UVRFEqdXqasLAgbM6yRkWTT0w1TVhaEva61fk62mzEaJOZ9soepw3rowrSLvTe/IHa4QgZMZXdN5Ilbe2E2yqjAlB90Q5ZlDpU69aFVmm1mJNn4cHpunfOZDRK/+FFPpq8+O9Nkybj+mISgoV6iStpMnz6dL774ggMHDnDgwAEOHjwY63UJBIIoiLa/QqhmYdus4Xw4PbdOmkAL/X53rJIab0D/ktfGDIf2VJifF2ztnGI3R3x96fgcqt0+nt9QyGeFxSTaTPoxF3tvfkHsCJyZF5HdNZFn7+wDgMcfAFQmDs1k2qoCFm/eX8deI5ULl1R78PgV3WGAsyPWvaJJQ71EFWlQVZVFixbFei0CgaCR1FfBENpfIZJmoTaKolLq8ATLMf/4HS+N7qefN3TMcM/0eCTgxU/28Isf9WTtjiPM++k1dE60YTbKGCS47/ruzPnoOz3SERp9uBR68wtih9UUrHqYOqwHbp/CzPd3s/CuLJLtJszGoD6hqNyl22uizUR6OwvtbEbdQQ6Nzv3h7mzRo6GRRBVp6NWrF99++y1er1f/n0AgaFm0gTrvTx3Csgk5ZHdNBIJf0p3aW+uNKEQ6z75T1fzreBXTzjx1aV/yGtqY4SNlNRgNMncPvJxVfz/C4B5pdEmycbzCxcNrdqGo0N5mCps+uWxCDn072aNai0DQEKl2i95JND3BQlG5iwWf7sNmNnK4tEa3WS018dh73/LvUw7c3rPtSsucXl7+POhUJJzp0aDtHRDRsHMRVaRhx44dfPHFF/q/JUli8+bNMVuUQCBomPq0DG9vP8Q9QzMxyhId2tuiOs/JKjdev0Jmql1/6tJSEqHq84V3ZRFnNvCHzfu5sU8H8nIyqPEGOFnpZvzrO/Sbba8OtjqdHvft20vv3r1j/WcRXAKkxJvx+hX2n3LoToKioqclQm126fgcFm/+N/0vy9LfrygK9wzNrGPbCz4Ndo4U0bCGicpp2LBhQ6zXIRAIokT7oteeljTV99vbDzHzlqtYuGkvc0dlRXWeUMfjzXuv0wWPWkoif2RfuqfZMcgSJdVuVGD7wTLWFRSRkWTjtXE5+JUA//erG7AaZWQ5GP0Q1RGCpuL3KxQ7PPgCCiaDTJrdzPelTiav+JqXRvdj8eb9vDI2G9cZx7XE4QlLS9R4AyTbTcz4cS998mqp04Pbr+D1K6TFW/R0xsz3d7P2wcFYRDvzc9Kg0/Df//3fPPPMM/zsZz+r01Jz7dq1MV2YQCCoi/ZFr6hqnael+XlZeAOKfpM813lOVrnDRJSLN+9n4V1Zujq9xOEh3mJAlmD/KQdz/vgdafGWsJtyaoKZvSeq+e8/7aHE4TkzHttPtxS7uPEKzhuty+Pizf8mL6crGUk2VFXV7bXC5aPE4UFVVdw+hZ7pdt12p6ws0KMHBinYjwFosCNqUbkLCeHsRkODTsP06dMB+O1vf3tBFiMQCBpGq5Z4897rdIchu2siU4f1wGKUSbSZ6JBQt+9CKJrj4fT4w0Rgu45WsODTfay6fxCnqtx0TrTx0c4iRlzbOSz0q92Ul47P4XCpk3d2HOHxW3qxaNM+Zr6/m/yRfbEYZTokWDEaRVc9QXSERhaMssSfvili9m29cfkC+AMqJyrdur1uLjzFO5MHUenyM+eP3/DS6H4s+HRfnZ4hi+/O5kSlC0mS6vQv0RqQafYsdAzR0aDTsGLFinp/9qtf/arZFyMQCBpGq5ZwnPnC10rPfH6VFLsZl0/hRJWbTu3q/8LWHI9I/RdKHB4UVeX1/3eQuwdezk/6deZwaU3E0G9avBlFVZk+/AqWbPle78UQZzZQ6vBSXuMjI8mK0xPAntJRnzAoEEB4O+h4q4GKGj8l1R5MBomO7axMGJpJQFFpbzXx8+Vf6vaaFm9hZHYXvi926k2etMhD7Z4hAP85XcOb24Jan9r9SxJtJlHV00gafAzIzMyM+L/u3btfqPUJBIIQtEE7xdUeMpJsPHFrLyTAryi8+MkeDpQ4OFXl5lilC79fqfN+RVFx+/z19l94aXQ/5n2yh9m39Wbx5v2cdnr1KIN2U37svW9JS7BQ4fKiqiomWWJSbqZ+A67xBkiwGlm8+d+cdvrInb+FsW/uCqZVFFHKJjgb7fr1h7v5z+kaik67Gfe/X7HuH0fPTJv04vYpBBQVvxLszbC58BQr7hvIwtH9MBtkLkuOqyPcrd0zJP/jfwEwffgVvL39UJ3+JentLKybMkRU9TSCBiMNo0aNAs5qGzSeeOIJ0RFSIGgBUuxmlk3I4ff/92/m52XRsb2Vw6U1vLPjSB2Nw7IJOfTu2E6/Gfr9CiUON4qK3jFPix6k2M0kxplxeHyUVAdLqmffdhVJdnPEKIPLG0A1yaS3s+D0KGTYzJysdOsTAud9soe8nK4YZEm0kBbUQSt7DFb6yBRXe3htfA7p8WYCqsppp4/7396hC3Rv7pPOyOwuTHxjB2nxFp64tRf/OV0TUbh7eUocEHQkPisspvBENfkj+5KX0zWsf0lwTgoR26gL6qdBp2H16tW89tprVFZW8tlnnwHBRk9XXHFFve/x+Xw89dRTHDt2DK/Xy7Rp0+jcuTPPPvssBoOBbt26MXfuXGRZZt26daxduxaj0ci0adPELAuB4BzIskSq3UxeTlfaWY3IkkSc2UBeTlfdYQBIi7dQXOUh2e5CVSUMEpQ6vBRXe3hnxxFdn6D1X3htXH9Kqt2YDDILR/ejzOHlZ//zJTf3See18TlMW1Wg537n52Xxmz8HhY8r7hvIzPe+pcThYdmEHPwBiec2BKdjPvjDHvgCqmghLaiD1x8gL6cr+09Wcl1mKjPWfaM7A26fEi66jTPx/Mi+HCmr4aXR/Ui2m/XhVKElliUOD2ajzGPrgvY4Z0Qf1hUUUVTuIs5sIEE2kmQ389eZwzDIEjazgUSbqJRoLA06DePGjWPcuHEsXbqUqVOnRnXCDRs2kJiYyMKFCykvL2fUqFFcffXVPPTQQ9xwww089thjbN26lWuuuYaVK1eyfv16PB4PY8eOJTc3F7NZ5JUEgoaQZEkf+7vq/oH4AkE9g+YwZHdN5PFberH/ZCVpCRamrirQR2C/NLpfxGE+SXYTf/hiP58VFp8ppezPmJwM1hUUAfDO5MEcrwjmjjXFOcBpp1d3CqasLOB3P7uWXUcrgrnnBAuvfvE9eTkZgGiaIziL2WigR5qdqzomMO5/v6Ko3MWcEX2Y+f5uXhrdj7R4C4/f0otZ63frzoRW1fP+1CEROz92SbKx+P/267YZ2rq8xhvg8pQ45n2yh7mjskS0qwlE1adh3LhxLFiwgO+//55u3boxffp0EhMTIx576623csstt+j/NhgM9O7dm4qKClRVxel0YjQa2b17N9nZ2ZjNZsxmM5dddhl79+4lK+vc9eUCwaWMUZb08rKXPvs3L/zX1djMRj1UO3VYD/667xRjB3fTb8iJNlNYp8faw3zyR/Zl4pBulFQHnQCPX+GRG3sCsK6giF//pA+PvfdtxKFV2s25qNxFarwlmBoZn8NXB0rZfrCMG/t0EGIzQRgpdjNefyCsIiLRZiIt3kKy3czC0f0od3qZ99Nr6JJoY8IbO/TjypzesLSEFgFbef9AbuzTQe8hotl6sM20mXd3HImqHFnQMFHVQ/3617+mY8eOzJgxgy5dujB79ux6j7Xb7cTHx+NwOHjkkUd49NFH9ZTEbbfdRllZGYMGDcLhcJCQkBD2PofD0fQrEgguclzegF5eNvu2q6hy+/H6Aywbn0NGko1Em4m7BlxGSbVHv9FqN9ClWw/w2rj+dQRjizfvp3OijWfvDEYk5m7cw/5iB9OG92Djw9cjSbAkwvvWFxylwuXTXzMaJFbcN5C3tx9m8ZYDLJuQw7UZ7VkzKVuIzQQ6sizhP1M9cXOfdJZNyCE1wcJLY/qxcNNeZr73LX5FYfYH/6Q4xI4hsujx5TH9OFnp1sW4S8b1p3enBFbdP4juqXYSbSYe+OEVwgabgagiDeXl5UycOBGA3r17s2nTpgaPP3HiBA899BBjx47ljjvuYMiQIaxevZqePXuyevVq5s2bx/XXX4/T6dTf43Q6w5yI+vB4POzZs6fBYy6GdrXnusbzxe12x+zczUVzrLGlbCAa+2wq9pSOEcvLFt6VRf7IvnROtOELKGFPZKFtoR0eP/kj+55RqQfTDSUOD0fKauiWGse8n15DvNXIL9bsCmuzm2w3sfqBQZRUeyhzenl7+yEm5Way4NN9+jFGGRTVx/QbuvGLGy7D7zzN6Uo3brcbZ5k1pn+X86Ul9kRL3qMuhI2ei8SUFIymeHYeLtNHU6fFW3jkxp7Mui34t7nnTHRBc3hDB6i9vf0Qax8cjNsXoNThJcluZsGne3ny9t7MGdGHZ//4Lz1NtmZSNs6ykwCUttgVNx8Xyl7rs9GonAaPx0NJSQlpaWmUlJSgKHVLuTRKS0u57777eOaZZxgyZAgA7du3Jz4+HoD09HR27txJVlYWv/vd7/B4PHi9Xg4cOMCVV155zrVYLJaLwik4F7G6xj179rT6v19bWGN9XAj7VBSV5RMH1Olut+DToNbg5j7pPHPH1awvOBomeHx7+yFWPzAIs1GizOFj6qqCOt3xZt92FbM/+Ccvj+nHwruykCWJCpePrXtPcf8PuuMNqKQlWOjc3srAzGv4/lQNs2+7Kti3IcFCqt2KsX1cyGqTgNb9mbbmtcWClryHejx+Smu8qBKgwvgh3fi+2MnQ7imMzO6iixo13QJEnoMy+QfdOXq6BpNBJj3Bgs0s88sbr0RV0fU+WkosIzUBOT2pRa43FrS0vUblNDz66KPcfffd2Gw2XC4X+fn59R67dOlSqqqqWLJkCUuWLAHghRdeYMaMGRiNRkwmE/n5+aSlpTFhwgTGjh2LqqrMmDEDi0WIU1ojbl8Aqyl6AVtjjxc0DlkOtsb9cHouLq+fPSerw8SJnxUWMy/vGh6+8Ur+sPnfekllWoKFdlYDHr9KWrw5YrShwuWjqNzFjHXfkj+yL5Pe+oeuUfApKr6AwslKN29uO8QjN15J9/Q4HO5A8OYdbxEdIAX14nb7KT3T26Oyxh/mtK64byATG9AtaOWUPdLsIEmcqnQjS1Dt9tM+zkRxlYdUu5FOifY6w9JEOqJ5icpp8Pl8qKqKqqpIklRnDkUoTz/9NE8//XSd1yPNqhgzZgxjxoxpxHIFkWjMl3Tv3r0b/aVuNRnoNntj1McfnveTqI8VnB+yLJGWYKGk+uyTlUZGko2AItG7QwLP3dkXX0DBF1B59Yvv2X6wjPl5Wew/WcmAzNSI0QZAL1PT/v+UkAqMpeNzyB/Zlx2HSkmKS6FLe5twFgT14vMFOF3jpcThDavkCW3pfNrpjahbCC2n7NDOQuf2NhxeH16/GVmCgKKy/C8H2X6wjDWTsvV9IYgdUTkNr7zyCu+99x7JycmUlJTw0EMPsW7dulivTRAl4kv90iXFbq6Tqlg2PgeDHHQsTAaZMcv+HnZDnrV+N+9MHozRIOlTLA+WOMOiFZr6XCO0AmPqqgLyR/alW1o7rCZZOAyCevH5AuwtdlBa7dFbPmt2FEpoZAHO6hbemTwYRVUxG2Q6nGnC1E42c6LSE2bzyycOwO8sQ0uHCWJHVLvdbreTnJwMQFpaGjabLaaLEggE0aGlKj6YPpQtj99A/si+PP3Rd9z5yjb2narGc2ZWRShF5S5KHR7e+n8HSU0INoFKS7BQ4vAAZ0WVS7ce0N8T6kRoUYhpqwpw++rXNwkExQ4P01YF55HUruQJZX3BUZaeqf6BoL394kc98SsKr37xPZ6Qluih6blts4bz4fRcenVIwON2X7gLu4RpMNKgTbcMBAJMmTKFnJwcdu/eLRowCQStCFmWkJCY8PqOMAdh8oqveffBwXWGUmUk2UiNt7DjcDCqcO/1wVky70wejMcfwOH2E2cxhDkRoakLzYEoKnfhF7MkBA2gzY0IrYCIJGy8Z2gmf/qmiNUPDAKCvUhKHR5+9W6wu+Nt13TCbjHqqQeRhmg5GnQaMjMzw/4LcOONN8Z2RYKYI4SKbZ/QCYFmo0GffhlKUbkLJOrcoOfnZQEqz97Zh+c3FPKj3jV8seckE4ZmsuDTvdwzNJNP/nmcN++9DqNBRpZg7sZCvYRNcyAykmwYhchM0ABGWdL7g0Sq5JEAj1/BG1AYO7hbsN250xtW7hscoraXV8Zmt/TlCIhyYJXg4kJoINo22oTA0JzumgcGRYwoqCq8vf1QWMvot7cf4u6BlwPwyI09qfEGuD2rC9v3l/Dwj67kD1/8m7ycrlS6fKQlWAgE/Dx7x9U8eXsfDpc69UqL4IAh8bQnqJ/0eIs+u0SrgOiWasdskFDUAIUnnHplz1cHSnnig+/I7ppI/si+ZKbaKSqvYd4ne8/MlRAPOq2BqISQAoGg9VDm9OoOAwQjCi9sLGTp+P5MXbVTdySWjOvPyu2HePjGK5kWoUriv/+rL/EWIxU1HmQJnvjgO8bkZPDErb0xGSRkSWJz4QkG9UijS3szTr+fKzvE87ufX4tRlkiPt2ASEStBA5hMBq5Kj+fdBwfjV1SMsoTNLGOQobgqQM/0eFTA5fOzeEtQQ1Pi8JAab+Y3fy7UZ6GIFuStB+E0CARtjEipiM8Ki3n+zj6sfmAQ/oDKf07XIAE7DlcwcWhmxJ4M7axGKl0+Kmr8+nm2HyzjnqHdSLCYUYDb+3Uh1W5BliUsFiPYL+y1Cto+JpOBDglW9p2q5veb/809QzPx+hW9mgKoE11Y+fcj5OV05f7ru5ORZKNTe5vot9BKEE6DQNDGMBnliKkIRZUY979f8tLofkx66x+8M3kQC0f34/k//Yt7hmbqA6cykmwsHZ9DcZWHOIuBbql27GYD22YNFw1xBM2KoqiUuzy4vAoWk4FZt/Xmnjd2RBxrnRISXQD0wVMfTs8V9tiKEE6DQNDGMMjoUy5DZ0OoBJXqiqqy9sHBpJ9Rl0cahZ1sN+E2GzAbZRKsMu1trXMuhKDt4fcrFDs8+AIKFqPMsQoXv1z7TYNjrTsn2vjD5v3cMzSTwhPVYf0XRFqidSGcBoGgDaEoKtWus1MuNSdgwaf7eGlMPz6b8QN8fpUpZzQM//erGyKOwn5n8mBKqj3UeANkJNuwm8yiSZOgyfh8AY5XufWhZu1tJh4PGale31jreT+9hnUFRewvdjBnRB96d0zAZjaKqFcrRNwlBII2RJnTy6FSpz7lct4newH49U96E2c2YDEadIcBwOX11xkjrJVczvtkL3P++B2l1R5O13hb6pIEFwmKonKkvIaDJU4CitbF0RLVWOuXPvs3EOwEmf9xITZzsCeDcBhaHyLSIBC0Ibz+AJ/88wQr7huIyxfAH1B5aE2wYuLNe68jwWoMu0kfr3SzvuBonZLL+67vzuO39GLRpn3MfH83ax8c3IJXJbgYqHJ7kSWJBKuRMqeX9QVHmX1b74jtod+89zrMRpmSag9GgxTWSEykJFo3ItIgELQBFEWlpNqDxSgzfsjl+kRAzWEAiDMb9PCvxtKtB5iUm0n+x4X87H++JP/jQib/oDtWk8zb2w8xdViPoA5CdHYUNAG/X6HS5ee006s7DPcMzeTdHUdYVqs99D1DM1m4aS+KquL2BXh+QyFzRvTh/alDWDdlCL06JIgIQytGRBpaIaJjoyAURVE5XOakzOElvZ2F6at3Rhz8U+Hysb7gaB1VelqChdUPDMIXUCh1eDEZZZZs+Z68nK4k2kxkJNmEvQnOG0VROXzaydHTwZkkZoPM9OFX6DaW3s7CivsG6g7F29sPMSk3k5OVbjon2vSUxPKJA+h4ZiiVoPUinIZWiOjYKICzraIVRaHM4cHhCSBVU2fwj/bvpVsP8MStvXhzW7ADpNZpzxdQ2HuyWn/6027mKXYz1W4/yycMIFV0dhQ0EkVRqfZ48fnVOmmJSbmZTMrNpJ3NhIqKoqpUu/0k2kzcPfBybGYDS7Z8zzMjrub9qUPonGgTDkMbQaQnBIJWiNYqetSSbbj9CjPWfVsn/VBbVKbVuj9zx9Vc1TGBDu2szN1YyE2//Sv5Hxdyz9BM3t5+SHcY0hIs9Ovanl4dRThY0Dj8foVylwenN8CpKg/zPtlDmdNLit3M7Nt6s3XvKbomB9uY/+tYNfEWA5enxGGQJbwBhSVbvmdSbiZIKjaTQTgMbQgRaRAIWhGhg6i0VtEq6JMCQ9MPtQf/yJKEgkq500upw0uy3URJdbAqoqjcxaz1u8MiEPEWA8l2EWEQNI5gwyYvBhlUBf5xqJQ5I67GF1AIKCrv7jjC7VldkCWJqasKeGl0Pw6V1hBnNoRFG+LMBhQVOiUKh6EtISINAkErITS6oDXAye6aiEE6OylQixZowrEnb+uNoiocKHFyrMLFgWInAVXlnR1HqPEGeOLWXvr5i8pdusNgNko4PIEWvFpBWyWYMlM57fRhkCG3ZzrfFzsoqfZQVO4ib0BXdh0pw+NXdGf3zW2HqC21tZkNeP0KiTZRKdGWEE6DQNAKUBSVk1VuPbqg6RWmDuvByUo3C+/KosThYdGmfdw98HJ6psfTqb2VGm+AKpc/7FwSMCk3k5nv76Zju7OdZ95xvwAAIABJREFUHjOSbLrGwelRxFhrwXnh9QfwKSoGCRQFPUqwvqAIAIMs8+OrO3G4tCbM2V2y5Xu8AQWDLNE9zY7Pr5Ismje1OYTTIBC0MFqE4XiFK0zUOD8vixS7md/8eQ82s4H8kX2ZfdtVAAQUBZcvQFq8mfR2Vromx+ELKHqEoesZgaRWSZmRZOPVsf0xGyVMBhmzUcJuERUTgsZjNhowGySMBgM1PgWLQaJnBzsTh3Zjzh+/48aX/sKJSjeLN+9nfl64s3tlh3jcvgBzNxYCiChDG0Q4DQJBC6ONug4VOe46WsGiTftIjDNT4vDw/IZCvAFFf0+pw8u9b/6Df52opqTag9Pjw2oy8OQZEZqKdKaUUub9qUN4897reHXLfvwBiLcYsJpk2lnFDVvQeBKtRlw+hSq3D5NBorzGz/5TTqaGdCItc3p1Z2HOiD66sytLQaf17oGXCy1DG0U4DQJBC6ONuo5UDaGi8vKYfnrb6Mfe+xazUWbBp/soKg/WxU9fvZPEODMd21kIqDBuSDeMBnh5TD+OV7jx+BUWbtrLL2+6EptJRpYg1S5u2ILGoSgqxVVujle5McgQUFQOljiZtrqAOLMhYrvoULu1mmQeXfsNj733LR3bW0WUoY0iqicEghZGOiN01KILWoVDp/ZWjle4sZoMrJk8mOIqN2VOL4s27WPX0QoykmxUuHzBJk7VHqrdfia99Q8ykmwsm5BDh/ZWrAaZAPDCqGtItYte/oLzw+9X2FdczZSVBXrL8jl//I6XRvcL0+DUbhf91qSBlJ2ZeAnBGSmiJ0PbRkQaBIIWxiChRxi07ngev4IkQWqCGYfHz+q/H8JslMn/uFB3GObnZbF06wEykmyUOb3EmYMahaJyF1NWFmA1Gkhvb6NTexvpCeImLWg8iqJSWu3mVLVbdxgAPbKgOQuRBlHdf313HB4fj733LeNf38HM93djtxiFw9DGEZEGgaCFkWRJL6MMHSo1+7bezPtkD5NyM7ktqzMbvz3GyvsHAhKHS50s2rSPEoeH+XlZetMmjaJyV5gGQiBoLIqicrjUwalqDyaDXKdleaizMGv9bhZt2kf+yL50S4070/ApOIFVi5yJCMPFgYg0CAQtjCxRZ6jUpNxMLEZZ765X7vTRv1sKIJEUF+yu9+uf9GbOiD56L/+lWw/o58xIsiFuzYKmUOb0cuS0i5nv7444CC20DDh/ZF9eGtMPk0HitS0HUFWVEodHj5yJCMPFg4g0CAQtiNvtx+kJsODTfWGRhgWf7mP2bVfx2HvfsmRcfyTA4w/2Vth/qoYku4nO7a2kJ1iYM+JqTjs9YeOFXxufgyTuz4Im4PUH9DTE0q0HWDKuvz4srcThIc5sYM3kQaDCnpPVPLbuW3YdrQBgf7GDd8+MWzcbDaSIfgwXDcJpEAhagOCwHw//Oe3B6fHrKnONUJHj9NU7WXn/QNpJEoqq0CnRgixJePwKJyvdbN17ivFDurHq/kH4leAkS7c3gBpnasErFLR1zEYDNd6ArrXZe7ySdx8cjNunIEtwssrNcxu+4ZEbe5L/cWFY+qLE4cFsNJCWINqUX2w0u9Pg8/l46qmnOHbsGF6vl2nTpnHttdfy9NNPU1VVRSAQYMGCBVx22WWsW7eOtWvXYjQamTZtGsOHD2/u5QgErQ5Nid7OauIPm//N9OFXsPCuLGa+HxxnrYkcF23aBwT1CbIkUVHj5bkNhZQ4PGz4RS5GWaZToo27B3Uj/+NCPissJiPJxsK7skiMN5MuJlcKmkCK3czlyUF7enPbIa7rnsKJSjd3Lf172HGLN+/ntXH9mXYmCqFV76TYRUnlxUizOw0bNmwgMTGRhQsXUl5ezqhRoxg8eDB33HEHt99+O19++SUHDx7EZrOxcuVK1q9fj8fjYezYseTm5mI2C0MTXLz4/QrHKoPVDaseGEReTld+sWYXP8vJYO2Dg/Xad62sEoJRB1WFka9uJyPJxvKJA0i0BcO9fr/C6Rovz9/Zl6d/oiDLEiZZIjnOjMkkOj4Kzh9ZluiWGk+i3cTzd/blWIVL1zbUjiq0s5mYM6IPV3VMwCBLdBTVOhctzS6EvPXWW/nlL3+p/9tgMLBz505OnTrFvffey5/+9CcGDhzI7t27yc7Oxmw2k5CQwGWXXcbevXubezkCQatBUVSOV7r0wT6yJJFiN1NU7uL2fp05WenmeIULq0kO0ycsvCsLm0lm26zhbPhFLr06nB1lbTTKpLez0inRhrP4P2QkxdGhvU04DILzQlFUSqo9HCuvoczpptTh4XiFB49foczp1aeshpZWvjq2P1UuH/kfF2I84zAYjUJjf7HS7JEGu90OgMPh4JFHHuHRRx9l9uzZtGvXjrfeeotXXnmF5cuX061bNxISEsLe53A4znl+j8fDnj17Gjymd+/eTbsIQZM512fUEG63u0nvh5azgYbsMz6tM8WOgP609sedRdyZ3YWMJBsGSdJvytOHX0H+yL7EmYM55bQECyeq3CzZ8j2P/OgKKoqP4/n/7J17fFP1/f+f5+TepNDSCwitggiMgkUoQxC/87Yv6Abzy0BQykXc5CpOnCgiyL7r3FBEvnMMiuhQuaNs6nBjOgSdouKvIkypqFwcBYS2tNCkuZ/z+6Pk0LRJm7ZJE+jn+XjsMRuSk89JPueV93lfXa56x4/G5xYrxNqCiadGhdujJrOZakMK09fvJcNm4uFbe+HyKix8/XM23juYrUXHgqasBiambvjoKIO7Z7ByQh5m2cvXX38bh7NK7D0WTVrrPMPt0ZgkQp48eZJZs2Yxfvx4Ro4cyeLFi7n55psBuPnmm1m2bBl9+/bF4XBor3E4HEFGRDhMJpMwCi4CWvIdFRcXX7TfcUP78z/lDsodTu1u7ZGt++nYzsSqCXnoZEkT5RU7v2F0XjbJsp4rM6x4fH7u27CXhSNymL5+L3+ZOZQrQySYJfLnJtaWOITbo6VVbiadH8u+cEQOc1/dr3V8VFSVKUO7seaDmn4gaVYjHaxGjHqJkddkkW4zkmSSaGc2k9a+fRzOqu18j/E+z6j7kMrKyrjnnnuYO3cuY8aMASAvL493330XgE8++YSrrrqK3NxcioqKcLvdVFVVcejQIXr27Bnt5QgECYNcyzAI3K1dmZlMqtWAxSAz+5aeWpOmwF3czuLvOFxWTUmFkxSLoaZpk88f71MRXIIEZqAA2l4LNHH64zvfkGYzctegK0ixGKhy+fCrKhLg9Pixu33YjCLxti0QdU9DYWEh586dY8WKFaxYsQKAxYsXs2DBAjZt2oTNZmPp0qW0b9+eiRMnMn78eFRVZc6cOZhMYtMJLl30shTybk2vk/ErKh2sehaO6IPXr+BXVDZ8dJQf9OrI0/84qJVgZqVaMOpFvoIg+uhkSUtyDNXxEWDqDd0x6CR0soTD7aWkwktmOxNd2ltE4mMbIepGw4IFC1iwYEG9x9esWVPvsbFjxzJ27NhoL0EgSEhkSSLJqOOuQVeQZNRR5fJpAgxQWe0h3WbCoJORJJXB3TPqtYpePWmgKGUTxAQJtNLJQMfHua/Wbg9txairyb1xuH0YdDIdrEbaW/Qi8bENIZo7CeKOy+vHXCvbv7F4Xd3nXyx0SDJy1uXljMOrPWYx6tjw0VHyh3Rj1oa9FNzeF49f4cr0JLJSLfz+zmvQyRJ6WeKJUbmis54gZrh8CqlJBl6cMojKag86GbZMHYzbr6CXZXYcOMk1V3SgwuHVjN4OViPtzMKIbUsIo0EQd8wGHV3nvRnx848u/nEMVxM79HqZy9tbsBh0eHw1IYhX/99/GHFNFq9/WkJJhZMko45kWc/hsmoKth3gxSmDaGfQkdnOHO/lCy5x9LKE06tQbncz7rmPAPjlD3twY++O/GFHMaPzsjHoZHp0tAFgEu2h2yTCaBAIWhGTSU9HWeK03Y1PUckf0o3XPy1h6T+/JivVQrXHzxVpSTz3Xk2vf5NeIl10dhS0Apk2Eyer3Frr6JIKJ0v/+TUAC0f0QVFV9LJEps0k+oC0YUQgShB1XF6R3d8QBoOOy9rXGAjjV3+kGQxLxuSS3cGCzaRj0cg+XN7BQpeUJHEnJ2gVDAYdnWxGss+3jg40cNpcVILd7SM7NYkuqUnCYGjjCE+DIOq0lXBDS5BliV4dk/nzzOtweRV0Uk1+Q6A9tEAQD4xGPVem2+hgNbJ56mD8KpgNMulWk9iXAkAYDQJB3JBlicxkkasgSCxkWaKD1QTWeK9EkIiI8IRAIBAIBIKIEEaDQCAQCASCiBBGg0AgEAgEgogQRoNAIBAIBIKIEEaDQCAQCASCiJBUVVXjvYim8Nlnn4nBVoJG0ev19OjRo9XfV+xPQSTEa3+C2KOCyAi3Ry86o0EgEAgEAkF8EOEJgUAgEAgEESGMBoFAIBAIBBEhjAaBQCAQCAQRIYwGgUAgEAgEESGMBoFAIBAIBBEhjAaBQCAQCAQRIYwGgUAgEAgEESGMBoFAIBAIBBEhjAaBQCAQCAQRIYwGgUAgEAgEESGMBoFAIBAIBBEhjAaBQCAQCAQRIYwGgUAgEAgEESGMBoFAIBAIBBEhjAaBQCAQCAQRIYwGgUAgEAgEESGMBoFAIBAIBBFx0RkNX3/9dbyXEJajR4/GewmNItYYW+K5PxP5cxNrSxwSWUNbQlv5HuN9nhed0eDz+eK9hLA4nc54L6FRxBpjSzz3ZyJ/bmJtiUMia2hLaCvfY7zP86IzGgQCgUAgEMQHYTQIBAKBQCCICGE0CAQCgUAgiAhhNAgEAoFAIIgIYTQIBAKBQCCIiJgYDX6/n0cffZQ777yT/Px8/vOf/2j/9tvf/paNGzdqf2/ZsoWf/vSnjB07lp07d8ZiOYJLBEVRKa1yc7yimtIqN4qixntJAoFA0CoE9M+S1jmu+qePxUEDP/6bNm3i448/5ne/+x1PPPEEDz/8MEePHuVnP/sZAKWlpaxdu5atW7fidrsZP348Q4cOxWg0xmJZgosYRVE5eKqKe1/+f5RUOMlKtbB60kB6dUxGlqV4L++ixuX1YzboYvZ8gUDQMhJJ/2JiNPzwhz/kxhtvBODEiROkp6fjcDiYPXs27733nva8/fv3079/f4xGI0ajkcsvv5wvv/yS3NzcWCxLcBFT7vBoFwxASYWTe1/+f/xl5lAykk1xXt3Fjdmgo+u8NyN+/tHFP47hagQCQV0SSf9iYjQA6PV6HnnkEd5++22effZZsrOzyc7ODjIa7HY7ycnJ2t9WqxW73d7gcd1uN8XFxbFadotwuVwJu7YAF+saLWmdtQsmQEmFE4fTRVnJ4XrH6N27d0zXGI547s/mfrfN+aya+j6JvO/isbZ47U9IbA1tCYm8x1pKU/UvGoTbozEzGgCefPJJHnroIcaOHcubb75JUlJS0L/bbDYcDof2t8PhCDIiQmEymeJ6wTVEcXFxwq4twMW6xtIqN1mplqALJyvVgtVipmsCnU8892drfrdNfZ9E3neJvLZYkMga2hIu5e8xkfQvJomQr732GqtWrQLAYrEgSRI6Xf0YaG5uLkVFRbjdbqqqqjh06BA9e/aMxZIEFzlpViOrJw0kK9UCoMX00qwi/0UgEFzaJJL+xcTTMGzYMB599FHy8/Px+XzMnz8fk6l+3CUjI4OJEycyfvx4VFVlzpw5IZ8nSFwURaXc4cHj82PU60izGqOemBN4jw5JBrZMG4KqqjF7L4FAIIDW0bZIkWWJXh2T+fPM63B6fOhlGYsxPsnIMTEakpKS+P3vfx/y32bPnh3099ixYxk7dmwsliGIMT6fwomzTk5XuSl3eNhadIw5/90rqhm94bOGLcJgEAgEMUFRVI6WO/i2vJoko45qj58r0pLommaNq+6U2z1xr6AQzZ0EzUJRVI6ecXCo1IFfUTHqZGbedBXL3j5IucMTtfcJlzUczfcQCASC2lQ6PVS5vEGPVbm8VDjdcVpR4mhhTBMhBZcuFU43pVVuFr7+uWb1LhmTy5Sh3fD4/FF7H4/PHzJrOJrvIRAIBLXx+hSqPf56+ub1qSiKGhdvQ6JoofA0CJqF16fi8iosvaMfqybmkWEzMffV/XRqb8aoj16szajXack/AbJSLVF9D4FAIKiNV1GZ++p+MmwmVk3MY+kd/XB5FVSgzBEfb0OiaKEwGgRNRlFUyuweFr7+OeOe+4iCbQd4aHgvMmwmZEmKakZvImUNCwSCtoGiqmTYTDw0vBcF2w4w7rmPWPj655TbPfjj1L45UbRQhCcETabc4WH6uqKg2NojW/dTcHtfDDo5qq67QNbwX2YOTYgsZoFAcOljNui4/5YePLJ1f5DOTV9XxOapg+OypoAWbpjSH53BFDctFEaDoMmEi611TU8iyRgd51UilTsJBIK2RbrVRNf0pJA651fil9eQCAijQdBkJEkK2Z3MoJNpZ265q8xkNifMcJZEIZIhUYFueGKglEDQMmRZwmrUh9S5E2ddWIz6Vp/5cKH8fG9cdVEYDYImoSgqqqry5OhczXWXlWrhj+MHYNZHJzSht6YwaU1iDGdJFJoyVEoMlBIIWoaiqNjdPlZOyGPG+VBsVqqFpXf0Y/Hfv2T5+P6tvqZEGVoljAZBxCiKynfnXHx1ys7GPd+ycEQOKRYDlU4vf9z5NU+Mis50UgU5IUqLBAJB2yOgc5P+tIclY3IpuL0vSUYdlU4vi//+JaV2d1yqtxKl5FIYDYKICLjGHG4fz+74moeG9wryNKyakBe1LF4ZJaRbUJRZCgSCWFJb50oqnDy1/SAPDe/FL1/ZFxQSiEf1VqDkMt66KEouBRERcI2VOzyU2t08/Y+DLByRw+apgym4vS+XpZhbHJpQFJXSKjc6vZ5VE/PiXlokEAjaFrV1LivVwt5jlZrWvTp9CFumDYlLbpWiqOhkWDUh/rooPA2CiAi4xgp3HdLyGaatLdI2boqlZRu37oyJYTmZbPj5tehkSVRPCASCViGUzu09VknBtgOsnjSQTu1afnPUVGprY4bNRMHtfemWbiXJpCPdahIll4LWp7HyRkVRtYqJ2pZ3mtVI5xRLVC6kukk+bx04zYGTVW06+VEgEESHSEu4AyGAWOlcc6itjSUVTqa8+AlZqRb+MnNoXNYTE6PB7/ezYMECjhw5gk6n43e/+x2qqjJv3jwkSaJHjx4sWrQIWZZZvnw5u3btQq/XM3/+fHJzo5NMJ4iM8FMkk/H7Fc5Ueyi1e3h2x1c8OTqXl3YfYXReNmlWI5nJJjJt0bF0EyXJRyAQXFo0pHG1tcvr9aMoCqsm5DFtXZHmYVgyJheX1885lweH249fVTEbWu8uP9G0MSZGw86dOwHYtGkTH3/8sWY0PPDAA1x77bU8/vjj7Nixg86dO7Nnzx5eeeUVTp48yezZs9m6dWssliQIQ7nDw7K3DwZVQix7+yC/+Z+rOVXlpqzWUKoUi5FfDuvFiUoXfkXlUKkDn6JGZVxsoiT5CASCS4vAnXqGzaTp3HdnXXRsZ6KDtcaL6fX6+fK0nRnriupVTDy1/SCDuqYwfnBXSqvclDs8bC06xpz/7tUq+Q2Jpo0xSYT84Q9/SEFBAQAnTpwgPT2dL774gkGDBgHwgx/8gN27d1NUVMT111+PJEl07twZv9/PmTNnYrEkQRgkVObd1ps0q5FKp5etRceYfF03/IrCjHVFJBl12mbNH3w5Bp1MsllPpdPLxj3fcuqci0pny0ezJkpfdYFAcGnh8fnJsJlY9JMcjLoLP3lnHB6U83MkTtvdWj8GWZKY8uInjHvuI6atLQLgp3nZHC514FdUjDqZmTddxbK3D7bKWOpE08aY5TTo9XoeeeQR3n77bZ599ll27tyJJNVYZFarlaqqKux2OykpKdprAo936NAh7HHdbjfFxcWxWnaLcLlcCbu2ALXXaDKbcRo7MK1W85JACGLRyD6UVDjx+mvKHzNsJnSyzKQ/7Ql67poPjvD4iBxO/edws9dkMpvRW1NoZ9Kz6d5r8fn8yPjxOco5+m05emsKCjIyCj5HJW6Xq9FjBrojtjax2p9NPZ+mrKE5n1VTzzGRr414rC1e+xMSW0NbQrjv0ZrWifk/6o0zxKhrq16h8tQJkjIv126OKp3eoDv7h2/txRmHp95rpwzthsPpoqyk+doXKbZ27dh077X4VdBJKqrzLAcPHq/3vICWNlUvQxFuj8Y0EfLJJ5/koYceYuzYsbjdF8aJOhwO2rVrh81mw+FwBD2enJzc4DFNJlNcL7iGKC4uTti1Bai9xtIqN5NWfFBv8NTCETn4FZVhOZnYzPrzMT0l5JCqhSNyUJCafd6BeGOgA2RWqoXC/P7kdE6B9JR6/7Z60kB6XZG47aQTZX/Geg3NMWIS4XMJRSKvLRYkyh6NNuG+R0VRkfVO7lz9UZB+zX11P5unDqZ3794cr6jWDIUdB06xIn8AM9d/SkmFk07tzUx8YU+916792SCsJgNdY/xZajkZqz8O1sFeneslrLeGXsYkPPHaa6+xatUqACwWC5Ik0bdvXz7++GMA3nvvPQYOHMiAAQN4//33URSFEydOoChKg14GQXRRFEXrtbBqYh79s1MoqXCSZjVi1MssGJHDfRv28tT2g3TPtIZ9rtnQ/G0UqjXq9PV7KXd4wrZNbQ2XoEAguDSQZQmdjpD65Ts/fCrJJLMifwBZqRZ+ck1nlr/ztfZ8CYkMm4lVE/O012fYTMiSRKrFEPP1R6qDraWXMfE0DBs2jEcffZT8/Hx8Ph/z58+ne/fuLFy4kGeeeYYrr7yS4cOHo9PpGDhwIOPGjUNRFB5//PFYLEcQAkVRKXN4KNh2oF5oooPViEEn4fSqlFQ4ybCZqHB4Qz43I9lEurX5JZGNZQYnUtawQCC4+FAUlTNh9OvkWRdJRj1pVhP2JD8b7r0Wv6Ly1oHTvHXgNAB/mTmEh2/txdxXL3TAXTImF6NeosLpjXlJeKTVE61VZREToyEpKYnf//739R5ft25dvcdmz57N7NmzY7EMQQOUOzxMW1s/3LDuZ9eyYuc3zLr5Ko6W1bjsAjG9pXf0o9LppXDXIR7Zup/1P78Wi6FlQ6oaywxOpKxhgUBw8RFO69beM4gHt+xj+fj+yLJEl5QkTp1zceh0VZDuONx+Xv7waFCF2ZoPjvDYj3NQ5NjfwERaPdFaVRaijXQbJZxVWlHtYffhchRV5dkdX7N8fH9sJj0LX/+ccc99RMG2Azw0vBcZNhN+RcWntGwdoTKDC/P7k2Y1JlzWsEAguPgIp3WVTm/Q8ClZlvAqCs/u+JonR+dqupNqNTL5um4UbDugaeDk67ohS2jJ/bEkUh1sLb0UHSHbKIEOj3Wt0spqL4UT8vjurItSuxu7y8e8P/+7npVecHtf9DqZTFvzXHO1O7R1bGfizzOvw+tTMOp1VJWdQJZTAejVMZm/zBzaaCc3gUAgCEW4O/DKai+rJuQF5SXoJClotk6KxUA7syGkp2LTvYNpBZsBgI7tTGyeOhi/CpLipUuH+smNsiy1il4KT0MbxaiTtMQfOH+HPyGPnMuSSbMZSU0ysPHea+mcYmHhiBz6Z18ojS2pcNI13YrNJKPXN30LBbJ8R634gKFP7uQnyz+g3O7hsvYWMpJNQSVCsiyRkWyiS2oSGcmt32ddIBBc3KRZjfUGPa3MH4DZIPP7HV/xdamdMw43JRXVAGy891ruv6UHOw6cotrjR1HVkBp4zuXV+jzEioBW/mR5jVaOX/0RZ13h3butoZfC09BG8fhVLUM4EKd7dsdXjM7L1lqnun0Kv3rjAKV2NyvzB2B3+3hq+0FK7W5qeqQ0b0OGy/IVcyYEAkG0kWWJy1LMFNzel+wOFo6dcfL461+w91glAAdOVlFwe19tpsOTo3PZuOdbZt/Skz/s+Iq3DpwmK9XCH8cPQJbgxFkXW4uOYTbosBhjm18VrrosnlopPA1tFEWtyRCetrZI63z21oHTpFgMWh3yGYeX6Td2p6TCyYz1n+LyKjx8ay/W3D0QCZo12VJRVJxen6iKEAgErUaKxUin9mYqq71MefETzWCAGu1JOv/jHwg9jM7LZsa6IkbnZWuPz9rwKSfOuijYdoDZt/TEYpRbPN23IRJVK4XR0AZRztcmB9x1AbJSLVQ6vcCFCynlfLwv8PfcV/djMxnokpLUZNdXwNV26LQj5HuLqgiBQBALAvH+LimWkNrj9V9w+dfM2TFo/x/q8RnritDJLasca4hE1sqIjIbDh2PfJlPQepQ7PPzmzQNBGcIB91vhrkPa39Uev2ZEBAyKkgoniqo262IJuNrqZieLqgiBQBBrZFnCZJBZMiZYe5aMyUVXS88CWlf7Jqr241BjQHhbWjrWAA1pZaC6LF5ElNPw2GOPsXHjxlivRdBKKIrC6Lxskow61tz9fVxePyfOutDrJPYeq9QupCSjjl+9cUCL8z39j4NNtnJrV0n4VVWbCV87Ozkr1cJl7S0iyVEgEMQUp8fPU9sPsmRMLp3amfGrKt+ddZF6/ke4duOnlRPy+MOOr4Ief/ofB7W/Y3G3H9DLao8vrFa6K09p1WXxICKjISkpid/+9rd069YNWa5xTowbNy6mCxPEBpPZHLIT5NaiYywc0YcPHrkJRQWTXkYnw7Jx13CkzMHT/6hJgGyKR6DuHPs1d39fK33ae6ySaWuLyEq18JeZQ4XBIBAIYo5RryMj2YiiwsRaw/cKJ+Sxe95NeP0qOlmi4Pa+dEgy8sSoXBaN9ONXVH7z5gHtpioWntHaerlwRE5YrTzXzAFU0SIio6F///4AlJeXx3Qxgujg8ymctrvx+hUM53spBEoj9dYUpq2pX3P88j2DKNj2BVOGdqNjOzNdUmru/FOTVKwmPcvH929y3W/dzN9nd3zNkjG5Qe1Yw118tT0Uoj+DQCBoCEVRsWV05j9nHOgkCYtRR4qlvmakWY0s+HGw+UdKAAAgAElEQVQO45//OLgiYV1RUAXF6kkDyUg2axUKiqJqBkSs9Ki2XhbuOsSTo3N5ZGt9rSxrwjFjoaMRGQ333Xcfu3fvpqSkhNzcXLp169aiNxXEhtrGgk6WMOgkXvrgMCOvyeJ7HZPR62VUWR8yG9fh8fPWgdMcOFnFn2dep22sQN1vc6jbiW3vsUqe2n6QzVMHA4TdxCazOchDoU1r65i40y0FAkF88Hr9nLa7USQ9OklClqG0ykVltZeuadYgzZBlCVmWQmpgStKFpO+6JeAt0cFIqa2Xe49VamGJ3p2SsRj1Tf7Br+vpjZaORpQI+cwzz/Daa6+xefNmiouLefTRR5v9hoLY4PMpfHmqirGrPuSGJbu487mPKLN7uGvwFfz1sxJO2934fAp6nS5kNq75vCeipQk+iqJSWuXmeEW11nWyNoG2rQ01H9FbU8R0S4FA0Cg+n8LB03bGPfeRpnulVR5MBh1Oj7+eZiiKigQhNdBmunAP3VpljQ3p5d5jlRRsO4DFqG9Wo6ZYTb2MyGgoKiriqaeeIikpiVGjRlFSUtKiNxVEn9N2N9PXBYcdZq7/FJ8fxgy8HJ9f4fhZJypqvWzcJ0fn4lcU7e/GEnxqb/TSKrfWFa1up8dfvfE5hXU6sUUSC1SQE642WSAQJB4N6V47iyFIM3w+hZKKahQ1tAZajLI2NjsaiY7hdLL2v0dDL8MRq6mXEYUn/H4/brcbSZLw+/1aMqQgcfD6lZAbRJYAqcYl9+u/fsG823rz0u4jQZ0gX9p9hHm39WZYTiZz/rtXg5u0IZdXXcs2MFp2y7QhqKoacUxNRhHTLVuAy+vHbBCfleDSpyHdU1QV03nNUBSVg6ermLa2iMU/vbre1MqXdh9h/o9y2Fp0jIdv7UXHduYWJTpGEhqIll6GI1ZTLyMyGiZPnsxPf/pTzpw5wx133MGUKVMafL7X62X+/PkcP34cj8fDjBkz6NSpE4sWLcJoNNK7d28ee+wxZFlm+fLl7Nq1C71ez/z588nNzW3RCbVVDDqZrFQLGTYT02/sTorFQLXHj14nIUsSa3cfYdKQriz+ezGTr+sWlGBTOCGPxX8v5lc/6UundmZtk4ZKommoBXQoy/atA6dZNFKlS2pSxOfic1SyetLAehec6OMQGWaDjq7z3oz4+UcX/ziGqxEIYkdA92rrzrCcTAw6GUVV8fkVTccCQ6d0ssSUod2CErKXjMmltMrN6Lxs5r66PyivKxwNJRlG0io/WnoZjsDUy2jraERGQ15eHhs2bODbb78lKyuLDh06NPj8N954g5SUFJYsWUJFRQWjRo2iQ4cOLFiwgAEDBrBs2TL++te/ctVVV7Fnzx5eeeUVTp48yezZs9m6dWuLTqitkp5kYM2U71NW5Wbuq/vJsJm4/5Ye+BUVi0nHqAFZmAw63jpwmtIqT5CV3d6i1zZrbYMhlKXczlw/kTLDZtJcXtGwbN0uF72uENMtBQJBw2TaTBROyNNCFMNyMpl9S0/uWv2RpoEev4pRJ5FhM5FhM9GpvZkHN+8L0sCnth/k8ZE5WsfHxvK6GvMkNBYaUBQ17KThaHlUYzX1MiKj4dFHH8Xj8XDTTTeRmpraqNFw6623Mnz4cO1vnU7HqVOnGDBgAAADBgxgx44dnD17luuvvx5JkujcuTN+v58zZ840enxBMIqi8l2VG6tRz5RXPyHDZuKh4b14afcRfjmsJ2eVGlfX0bJqslItWt0v1GzSQP+E2ps1nKW8ZdqQoI3ePzuFh2/txbjnai7SSEsqG6M1spUFAsHFjV4v0yvTxuapg/EpKnpZ0rTooeG9NI/qsJxMVk0awDmnD70sU2p3axoINTqYbDZwqNQe0Q93Y56EhkIDAYNj2dsHw5ZVRotY6GhERsMLL7yA3W7nvffeY+7cubhcLl577bWwz7darQDY7Xbuv/9+HnjgAdavX8+ePXsYNGgQO3fuxOl0YrfbSUlJCXpdVVVVg0aD2+2muLg40vNrVVwuV1zWZsvozGm7n3SbkZIKJwtH5PDS7iM8OKwnZoOew6UOks16rSVp3dDEq//vPxTm96eq7ARlJTWNQyxpnUNayqriozC/P9PX76Wkwsn9t/TQjISSCidPbT9Iwe19uTIjCcnvxeco5+DB4006n2h8jr17927R65tLrPZnvM4nHE09x3hdG5EQj7XF8/tMZA1tDraMzphNRs6c8+L2+jUNDOhc/+wUHhzWE6dH4dgZJ5ntTPV08MnRuZj0EluLjtXTwlCE00eH00VZyWFMZnOQTgbaP1eVncDpTOHel2seD3h906xGOrUz4Tl7ulG9bK39Gm6PRmQ0/POf/2T37t3s27ePzp07c/311zf6mpMnTzJr1izGjx/PyJEj6dOnD0888QTPP/88V199NUajEZvNhsPh0F7jcDhITk5u8LgmkynhBDRAcXFxXNb2nzMOyh1OfOeHUKVYDIzOy0Yv6yitcpNk1FHu8FBqdwe1JK32+Mm0Gfn5D64677a60Jq0tMod2lI2GMnpbNNcXoHW0AH2Hqtkyouf8MEjN9ElLRVoervTeH2O0SCR92c0aeo5JvJ3mshriwWX2h79zxkH35x20Km9idQkg6aBAV2afmP3IC0sqXCe74AbnAj5q5F9eGJUbj0tDEU4fbRazHQ9/9kqihoiNJDK8YrqoH4MAY/HB4/cxJUR9ECK936NqAzi6aefpqioiHvuuYcnnnii0RbSZWVl3HPPPcydO5cxY8YA8O677/Lb3/6W5557jsrKSoYOHcqAAQN4//33URSFEydOoCiKCE00A50knZ/vLrNsbD+qPf6aDSpxvo+5n61Fx3hydK7mlvvlK/vIbGci/XzXs1Cd01ZPGhiy/Cfg8uqSmoTFoE+4KWwCgaDtoJMk1nxwhLNOHycrXazMH0C1x6/pUorFUE8LJ1/XjYJtBxj33EcUbDvA/bf0JDOMFoaiIX0MUFsnax83ELqozcWkmRF5GrZv305JSQnvv/8+9913Hy6Xiy1btoR9fmFhIefOnWPFihWsWLECgClTpjB16lQsFgvXXnstN9xwAwADBw5k3LhxKIrC448/HoVTantYjDqmDO3Gip3fMGVoN3p0tOJXwOtX2Vp0jJk3XcWUod1Y88ERzRWWZjOSmmQIe4FEmkQTqwxdgUAgiITa+jc6L5usVAvfuyyZVRPymLauiEqnlzSbKawWZiSb2Fn8HR3bmSOO/7ckyfBi18yIjIYvvviCd999l927d2M2m7ntttsafP6CBQtYsGBBvcdvvvnmeo/Nnj2b2bNnR7hcQSjamQxkJJu4a9AVyJLE16ccfO8yG5IE993cg+XvfM2Uod149Ee9kSUJSYJfbPyM5eP7k9JAZU8kSTSxytAVCASCSEixGOnYzsxdg64gyajj9Dk3Jr1Mz8yaMKqiKLj9SkgtPOv08sSbBxidl93kpkfNTTK82DUzIqNhxYoVDBs2jJUrVzaacyBoXRRF5etSO8vePsjovGySZT3dM6xkWM2UO9yoqsrCEX3wqyp+RWXlzm8YnZeltXOOBqLSQSAQxAtZlrg8NQmdLFFa5cbjV3hq+5fM+e9eWgmkoqi0M3tYNLIPXuWCFm4pquluPPUH3Vs1PHAxa2ZERsPixYtZsWIFb775Jl27dmXmzJlBVQ+C+FG79CfQUezCuGmZWRv21kvWue3qyy4qd5hAIBA0RIXTS36tyZUAB05WaSWQsiyRkmTC63czbsUH9TQxM9kk9DBCIkqEfOyxx+jcuTNz5syhS5cuzJs3L9brEkRIQ01EQiXrFE7Io192ezExUiAQXDJEOmchlCaumphH5/YWoYcREpGnoaKigokTJwI1pVb/+Mc/YrooQeQ01l+8YzsTm6cOxq+C2SBjLztJB6sYbS4QCC4dIp2zUDefQJIkdFKNp+JiyiuIJxF5GtxuN6WlpUBNOaWiNH90siC6hCv9SbUYOHiqip8sr5mgNn71R5TbE3e0dO2JcNa0TvUmwgkEAkE40qxGCvP7RzQhUpYl0qxGzrl8jF31Idf+7h1GrfiAg6eqLnndaWzyZiRE5Gn4xS9+wZ133qk1YyooKGjyGwliQ7hM3HBtTjdM6R/nFdcnkolwAoFAEA5ZlkjyVkZckRDJQKlLjWjpbERGw9ChQ9mxY4eYC5Fg1J2ydlmtuFy4GJ8SmXOpVWmLF7BAIIgubpeLK5NNmi6ePOsMazxEmgNxKREtnW3QaBg3bhySFNoC2bRpUxOWK4g2jVmN4WJ8MokXWmqLF7BAIIg+kd5NR5oDcSkRLZ1t0Gh45plnGnzxvn376NevX5PeUBAdGrMaw3Ud8znKac48iFjSFi9ggUAQfSK9m77YuzI2h2jpbINGQ5cuXRp88dKlS3n55Zeb9IaC6NCQ1Rhwz3VIMrBl2hBUVdXcdA1NUKsb7mitbOK2eAELBILo05S76bqVZenWyOZOhCNe+hkp0dLZiHIawqGql3amaSITzmo06GWOljv4tryaJKOOao+fK9KSgvIdQhHPZMS6yZx+r5usdJEEKRAImkYkd9MBrQt00U2zGslMNqFY1GZrzsWQzB2t9tUtyooLl+8giD3hSi2NOolT51wsfP1zxj33EQtf/5xT51xUOhsutwzn1it3tE6ZZu2JcI7y7xLmQhMIBBcPkUyfLHd4WPb2QW3S5ZjCDxn//MccPN38kst462ekhJu82RRa5GkQxI9wVuPJs07mvro/aPPOfXU/m6cOBmv444lkRIFAcLETyd20x+dndF42j2wN1slpa4uaXbHVlvQz6uEJr9fL/PnzOX78OB6PhxkzZtC5c2cWLVqETqeja9euPPHEE8iyzJYtW9i0aRN6vZ4ZM2Zw0003tWQ5lxyNxchCDT3xq2rIzetvxIAWyYgCgeBioDm6WJvAa6L5I9+W9DOi8MQLL7wQ8vGRI0fWe+yNN94gJSWFDRs2sHr1agoKCli+fDmzZs1i48aNeDwedu3aRWlpKWvXrmXTpk288MILPPPMM3g8ieXKiQWRduQKxMhGrajp6Fi7Y1lDxzAbdJprLkBWqgWzoeGvOhK3nkAgEESL5nQnbEgXIz12IIchlE4290e+LelnRJ6Gd999l7vvvhudLvgDHTt2bL3n3nrrrQwfPlz7W6fT0bt3byorK1FVFYfDgV6vZ//+/fTv3x+j0YjRaOTyyy/nyy+/JDc3t4WnlLg0JVkmXIzsjfuGcuqcO+wx0q2mkBmy6daGXW4X+4x3gUBw8dDcxMGGSiojPbYsS3RuXzOoatraoqhUbLUl/Yx4YNV//dd/kZWVhSRJSJIUtrmT1VoTOLfb7dx///088MADSJLEr3/9a1auXElycjLXXnst27dvJzk5Oeh1dru90bW43W6Ki4sjWXar43K5GlybNa0T9768t96G3zClP47y74Ke265jFgtH5JBiMVDp9FK46xB7j1VS7faFbQ8dOIbJbGbDlP4oyMgo+BzlWqllY2usTVmTP4Ho0JQ1hqN3795RWk3TiNX+jNf5hKOp5xiN7zRWxGNt8fw+E0FDm6KFtbGkdSbDZqqnjQ6nS/seIz22pQGdjAax0s/W2q/h9mhERkNhYWGT3uzkyZPMmjWL8ePHM3LkSIYMGcL69evp0aMH69evZ/HixVx//fU4HA7tNQ6HI8iICIfJZEo4AQ1QXFzc4NqOV1SHjKPpDMHnpCgqxd+do2DbAUoqnAzLyWTp2H5UuXz4VSI6RjAXmjk1tsZYE0ktc7zX2BISeX9Gk6aeYyJ/p4m8tliQCHs0Ui2syxmHm4dv7aUle2elWlgyJpcUmxm5S1d0BlPYvK7Gjp1oTe/C0Zz9Gs0eEhEZDXq9niVLllBRUcHw4cPp1atX2MZPZWVl3HPPPTz++OMMGTIEgPbt22Oz2QDIzMzk008/JTc3l//7v//D7Xbj8Xg4dOgQPXv2bNZJXCwY9TqG5WQyOi9bs5K3Fh2rF0crd3g0t1n/7BQmX9eNSX/aQ0mFkzV3f/+iTbi5GGqZBQJB7AkkDmbYTEy/sTspFgPVHj8WY8M65lPUetVhaz44wi9+2JNpa/de9BoZC6KtuxElQi5cuJDRo0fj8XgYOHAgTzzxRNjnFhYWcu7cOVasWMHEiROZOHEiv/nNb5gzZw4TJkxgw4YNzJkzh4yMDCZOnMj48eOZPHkyc+bMwWS6tIcTpVoM3H9LT7YWHUN3Pgb2+Mg+qKqKz3dhJkTt8p3pN3bnpd1HWDgih81TB2M2yCwb2++iTLi5WGqZBQJBbEmzGnn5nkE8fGsvCrYdYPHfvyQ1yUCVy0dJRTWnz7mCNDGA16fU8yKMzsvm9//86pLQyFgQbd2NyNPgdrsZMmQIK1eu5Morr2zwx33BggUsWLCg3uOhciDGjh0bMpnyUqXC6eXZHV8x86aruG/D3iD32rlkE107WNHr5aDynSvTk5h3W2/OODyUOzxsLTrGzJuuYsvUwajQYldTa7Y+bUu1zI3h8voxG9rmnY9AIMsSNrOeSX/aT4bNxGM/7s19G8NrYoBwpY2Tr+vGS7uPaB0eO7Yz1Wuh3xrezERsJR1t3Y3IaDAajfzrX/9CURQ+++wzjMa2abG1FI/Pz9QfdNcMBoAMmwmXVwEkTlW5uKy9RSvfWfb2QSRJ0lpCG3UyM2+6ihU7v+FXP+lLl5QLJUPN2aytHS5oS7XMjWE26Og6782In3908Y9juBqBoPUJeA0Wjsjhgc2f1WtIt2zsNVgMLuDCzVGo+QntLQZ+/8+am7EKhxe/ovLNaQfZHSxcmW6LSAej8UOfqOHXaOtuROGJgoIC/vznP1NRUcGf/vQnfvWrXzXrzdo6Rr2OdJtJ+/L6Z6ew6Cc5AJTb3Xx1ys7R8prk0F4dk/nN/1xNaZWbha9/zuK/fwlAstnAvNt6o6u1ByOtXa5La4cL2lIts0AgaJjAj1mKxVDvTjjDZiIlSc9Xp+yUVDj5/PjZIG38y8yhfPDITVqp5ZSh3XB6/EHt8x1uH6fOuRrsA9Fc7QxFooZfo627EXkaFEVh7ty5F16k1+P1ejEYDM1607aIz6egqip6ncSuh26kzO7GoJOoPr/Ra7vlbCY9Xr+CCsx9tcZ999DwXlrb06zUmhrjjGQzsixR6fTw3VkXS+/op5UghRoHW5fWDhe0pVpmgUDQMGlWIxvvvRa9TuZfD9+EX1Eps7t54s1i5v+oN2V2Tz1tTEky0MFqIiPZpHkIJKBTezMTX9gT5MGt9vi5Y9WHDd71N1c7Q5Go4ddo625ERsO0adM4deoUV155JUeOHMFiseDz+Zg7dy633357s964LeHzKRw946C0yh1UKrRqYh56WQ3asHNf3c/anw3iwc37+L87r9Hcd+H6pKdZjZysdAVdXE+OzuXpfxxsdLPGI1zQWItXgUDQNlAUFff5EEVtXSyckEe6zciYwg+DejJUe/x4zydH1g4FPD8pD7NRH6Rj02/sXq/Koq4xoChqs7UzFIkcfo2m7kYUnsjKymL79u1s2rSJt956i6uvvppt27axbt26qCziUue03c2xM/UHSU1bW0Sn9mYUVWVr0TEeGt6LDJsJv6Lyy2E9UVQ1rPsuYMGWOzxMW1cUdNxHtu7n/lt6NLpZRbhAIBDEi3C6OH1dET5FZeWEPJ69qz9ZqRYqnV427vmWUrtH8zAEQgE6WabS4QlqC92QZgZoiXaGoq3oaUSehvLycjp06ADU9FwoKysjJSUFWW7RZO02gaKoeP0KSUZdyE5mHp9CO7NeS3Cc/6PemPQyXVItrNx5iJX5Ayize8JasOFcYt3SrY1uVhEuEAgE8SKgi7X1q392CtNv7I7Pr2Iz6vjurIt2Fj2fHi1n8nXdeHbHV/xm1NVaEmX/7BTMBhmHB5aN7cecLfsoqXBS7fE3etffEu0MRVvR04iMhj59+vDggw9yzTXX8Nlnn9G7d2/+9re/kZaWFuv1XZT4fAqn7W68fgW9LGHUS8iSFLKTmUEvYXeryJLErJuuQi/LfHO6JuGn0unB7VPo2dHGqgl5mlVc24Itd4Q2KJJMupCb1WQ2U1rlDtrUsQgXJGLpkUAgiC91tdFm0mv61T87pV7u1sr8ASQZddx9fTcWvf4Fo/OycXkVLAYd0/6rKz/K7YLbp7Ji5zdMGdqNtfcMQqeTkIDCCXlMD6GZAcKFE8JpZ0PU1bvL2lsSQu9iocMRGQ2LFi1ix44dHDp0iNtvv50bbriBw4cPi1HWdUhJS+N4RTU+RUUvSySbdaiAx6dwRbqFn66oH6Nzef0kmw1YDDIev0r+8x+z9I5+bC0q4b6be7D8na8ZnZdNVqqFTVMHA2Cq9eWHKkEKN6BKUVSqDSlMWvFBTEuCErX0SCAQtD5er5/TdremixajjMmgw+H2k2zR88LkPH72UhHTb+yuGQwBj4Pbp+D21eQ+TBnajXYWAzqpJjl//OCu5D//MSvzBzD5um5a0vjDt/ZizQdHaoyInw1CliQshprKtdr60xTtbIhE1btYrSsio8Fut+N2u8nMzKSiooLXXnuN//mf/2n2m16KeL1+yrwmZqz56IKVPCGPNFtNhYlBlupVQQzLyWT2LT25Z90eFo7I0Wa8Vzq93Hb1ZSx/52smX9etXtVE704XrNimuMTKHR6mr68/yKU5mcIN0dAkOpEEKRC0HbxeP1+etjOj1h1/QBf9ioLXr5JuNbHx3sEo52dGhPI4LBvbj27pSZTZvTUllbX08sRZF1uLjrFwRA49M2387u/FmhFRWzfTbcHaE61wQqLqXazWFVFSwsyZM3nnnXc4dOgQhw4d4vDhw81+w0uV03Y3M9YVkWEzsWpiHkvv6EdZlRsJCb8fqj0K99/SI8iSnjv8e9rFlGIxaKGGwl2HuDwtidF52SGrJurW/QYyY7ukJpGRbAq76VurJChRS48EAkHrEtDFgOYtHJGD2+tHUcBs0HO8woXLp/BfT+3kcKmDrFRLkMcBarRj9b8O41fQwg119XLydd0o2HaA01XuiHUTItfOhkhUvYvVuiLyNKiqytNPP92iN7rU8SlqyH4KhRPy6GA14PWrdE1PCrKkzzq92pcaGF715OhcHtm6n3NOD90zbFH90lurJCiRS48EAkHr4VPCew8CpZU+RWXz1BpPw7Kx/ZAkqV5y5OTrunHyrCusXj79j4MU3N6Xy9OSSHO37o94oupdrNYVkaehV69e7Nu3D4/Ho/1PEIxeloI8CXChfEhVa/79+PmLJWBJl9cqEwpYyy/tPsIfx/eng9WETiaojAgufOmKolJa5W6w21ld0qxGCvP7x7wkqK2UHrVVXN6miW9Tny+4dNDLUljvwfR1RViMenSyxLjnPmLuq/sx6mUua28O0r3G9HLhiBwe+3Fvrsq0cra65rcpnG6Gozl6GiBR9S5W64rI07Bnzx7eeecd7W9JktixY0eL3vhSI9NmwuO/UAYUGPda6fQiy5BkkOnU3kzhhDxc3hpLuHDXIc1S3nusUrsAzjp95D//MRk2E0vG5AbF5lZPGohBB8Unz9WrpmgswUWWJZK8lTEvCWorpUdtFTE3QxApmTYTKyfk4fb663kPpt/YHcP5fvjvP3wjLp+KSS9jNshBuhfIXQill/Nu681Zp5fTVW50Mri8Cms++Ep7XrjKCbhQWaAoCmUOD9PWNk1PAySq3sVqXREZDW+88UaTDur1epk/fz7Hjx/H4/EwY8YMtm3bRllZGQDHjx+nX79+LFu2jOXLl7Nr1y70ej3z588nNze36WeRABgMOsx6mWE5mfWSFwsn5LFox1fcf0tPLksxUe1WyEq1sPdYJU//46CW1NPeYuDb8mrm/fnflFQ4Kalw8tT2GrdbdgcLFoMOt09h73/Oal3MIHyCS6hyG7fLxZWtkJwjOj8KBAKDQUevDCultUrDQ4UqlozJ5antBym1u1mZP4AOVgNP39GPdJsR03k3e129vKy9mf/96xe8deA0ADt/eQMTN9a0ki6t8gQ9r24JZO3KgoUjcijYdqDJCYMXQ1l5LHS4wfDEr3/9awDGjRvHnXfeGfS/hnjjjTdISUlhw4YNrF69moKCApYtW8batWtZvnw5ycnJPProo3zxxRfs2bOHV155hWeeeYb//d//jd6ZtTI+n4Ld42P+j+q3fJ6+rojRedlMX1dEhcPHH3Z8zZIxudqFULDtABaDDo9PoXNKcAxq77FKprz4CZXVXiRJYtKf9tRriBJ4n9oxu3CDWExmc0zOvyXuPYFAcOliNOrpmGxm1cS8sKGKua/uZ/qN3SmpcDJj/adYjQYua2/mqe1fcv/GvSH10myUWTgihzV3f5/NUwcjyxdyIfYeq2Ta2iLGFH6IolLvx7x2ZUEk3SPrEs1BV7EglnrcoKdh5syZADzzzDNNOuitt97K8OHDtb91uguxpD/84Q9MmDCBzMxMtm/fzvXXX48kSXTu3Bm/38+ZM2e07pMXE2eqPXi8KkYzITdgYGNWVnvIH3wF7x08rXkQjp1xotOBw+3ndJU7ZPJKZrIJnVRzLEVVWXP390ky6rTOkqV2d1DMLly5zYYp/aN+7olapywQCBIDvV4mw2bi6Tv6cVl7c1iNDPz38Uonv3xlH38cPwBZArvbp732cKmDBa99TqndTeGEvJr20lUenhnXL6R2qqqKoqhBWlS7sqDS6WVYTiaj87K1kPLWomMN5kAkapklxF6PGzQaXn755bD/9uCDD4b9N6vVCtT0d7j//vt54IEHgJp21B9++CGPPvqo9u8pKSlBr6uqqmrQaHC73RQXFze07FbHZDZTbeyA2aDT5kXUzm0IhB6G5WRS7vBQsO0A6352LXM2f8avb++Dx69g1uv5+Us1JZt143GrJuQhuSpxG5IYlpOJLEn1pr9l2AxUlZ2grKRm/rwlrXPIC9OvSlH//Kxpnbj35fr9HzZM6Y+j/LsmH8/lcrBPLAcAACAASURBVLV4jb17927R65tLpPszXuuLF9H4TmNFPNYWz+8/XhravtPl+JWa7rehftwVVWXVxDxNLzNsJmZt+JSN9w7G4fFjNsjY3T6mvPiJ9rrp64pYMiaXdJuJ3/2tuJ52/nH8AH7z5gEW3HpVkBZZ0zppa9hx4BT33dyDmes/rdVLYgCuc2UUl5wLeS7h9NXhdFFWEtuWBI3t12jpcbg92qDR0K1bt5CPS1Lj1srJkyeZNWsW48ePZ+TIkQBs376dESNGaJ4Hm82Gw+HQXuNwOEhOTm7wuCaTKeEEt7TKzeK/7Gf+j3I4edbJsrH9WP2vw/VyG1bkD2Ddh99q3oI/jL8Gr1/FaJepqPZoeQyBuF2KxUBmsokko46O7bugKCoLfpzD+Oc/rufa+/PM68js2C1oTaEuTJ2kRv3zO15RHfIC0hma910VFxcn3HccKYm4PxMBs9mcsJ/LxbzfmkO89ujximpe2n2ERSP78MfxA5i14dNaP+79cXkVLbeg9sTJE5VOHnplH8vG9iM1qSaZMXBDlplsooPVSGW1l7cOnNZyGQIeA5Ne4q0Dp1k0sk/QOSuKqnWDvCWno2YwQI12zVj3KX+ZOZTsLl1Cnks4fbVazHSN8Wfb2H6Nth7XpcGchlGjRjFq1Cj+/e9/a/89atQodu/e3eBBy8rKuOeee5g7dy5jxozRHv/www/5wQ9+oP09YMAA3n//fRRF4cSJEyiKclGGJhRFYfJ13fApKms+OIJBLzPvtt714nYz13/KLTkdyUq18G15NS6vyoOb97Fxz7ek20xaaUwgHvfLV/ZxtLxaGwwmyxI6WQq5IQIjYwOEK7fxOSqjfv6BeuDaJEKdskAgSBx0ssTk67rh9Cr8bf9xXr5nEK/PGsrL9wwi3Wbil6/sC9LLwMTJyvP9bOZs2YdOkvjLzOtYOrYfW4uOMWrFbvKf/5hks17LeZi2tohxz31EwbYD6GQ5pBbVriz4XqfkJuc0JGqZJcRejxv0NKxfv56VK1dy9uxZ3nrrLaCm0dNVV13V4EELCws5d+4cK1asYMWKFQCsXr2aI0eOkJ2drT2vb9++DBw4kHHjxqEoCo8//nhLzycu+FV4ZOt+rrsyjdm39OQPO77i4Vu/F7L8srYF/diPe7PoJzm4vQoF276o51pbmT8Aq0kf0ZCVhi6K2tm9Bw8ej/r5h+vhnggXkEAgSAyUWjo5cUhXFv+9mNF52Xj9NUPz6v5wZ9hMXJVpo8zuZtXEPAp3HeK7cy7GFH6o6WhplYe9xyrZvOdbVubnMWN9UZBnV5IIq0WByoLSKprcBClRyywh9nrcoNGQn59Pfn4+hYWFTJ8+PeKDLliwgAULFtR7/M0369d2z549m9mzZ0d87EQk0DN9S1EJ/52TyeMj+6CqBJVfZthM3H9LD5KMOpwePxnJRrx+hZQkM/dtqF8mlJJkpJ1ZH/GQlYYuiqifb4hSo0S9gAQCQWKg1tLJ7FQLC0f0wetX8CsqFXWm9fbPTuHhW3tx1+qaWT7DcjJZOrYfKmgGxCNb97NkTC7nXD5t5kTt0MTyd75m0cg+XJne8MTJ5v7IJlJZeV1N7pFhi5keR9SnIT8/n6eeeopvvvmGrl27MnPmzKAExrZC7bGuBp1Mps2EXi9j1Mmsufv7pNuMKGqNEWHQyTz24xytSVOgLjlgPDw+MocKh5fK87kMcCEsAbDroRvrGQwQfwu3oczcRLmABAJB/Airk+e9pBk2Ez0va0dltYeUJCM6WcViNLIif4CWW3D/LT205k6BNtKT/rRH05zl4/ujqioGnY65r+5n6R39eOvAaa1nQ4BFI/s0qo3x1tSW0trVaxG1kX7sscfo1KkTc+bMoUuXLsybNy/qC0l0vF4/x886OVHp5MvvqvjVG59TfKqKs04XDo8PgLNOL7M2fErxySoWvf651nc9UJccMB4Wvv45X5yoYsb6T4NaowYIN9M9UHt78myNkXFZe0uzh6w0l3ClRqGGwQgEgrZFOJ0sq3KhovLK9MEsHduPNKuRE2ddHK908sSbB3B6FHSyxJq7v89fZl5HdocLXoe6fR0ybCacHj+V1T5tgFUg9FubtpJX1dqaHJHRUFFRwaRJk+jduzeTJ0/m3LnQZSiXKoqi8m1FNYdLHfgVFaNOZuZNV/GHHV9xzqnw4OZ9LHz9c65IS2LhiBw6tzcz++Ye/Ke8mqxUi9ajofbmDzwWaI1aN6Gm7kz3RGkmkqgT3QQCQXxpSCcrqr38dMVuyuxeFv+9mDGFH1Kw7cD5nAIPZXY3igpTXvyEUSt2c+yMU9PEus2Xpt/Ynbmv7g9qchdORyOJ4yeKtjaX1tbkiMITbreb0tJSMjIyKC0tRVGUxl90EVM3PiTLNXf4dXsjTBnaDa9fYcWEAXh9CooK7S0GHn/9CzKSjfzv7X0onJCnlefU3vwBy7hua9TOKRY6tTPXa3n63TkXDrePhSNyKNx1iL3HKuPSTCRRJ7oJBILWpSk6Gaj6mrGuiI33DmbqD2rmThh1MsvuvIbvzrpYu/uo1sDJpJdZNTGPaWuLNK0MaI7WKK/W4wEdLbi9L90zbVgMkYcYKp0evjvrYukd/bRmeYnSqCkSWluTI/I0PPDAA9x1112MHDmSu+66i1/84hcxWUwioCgqR8scHC1z4PEpOL0+XJ6a2NzCETn0z07ReiN0am9GJ0uUVbkZ//zH3LBkFw+9so95t32P0ioPdxR+RAergT6dk1mZn0e1xx80pS1gGQdao1pN+pAGw8FTVYxd9aFmnT80vJe2jlje4YdqRZrIpUYCgaB18PkUDpfZNZ086/Ti9am4vApL7+jHqol5ZNhMmk76z9+1l1TUhC6ee+8Qsixz1+qPuPG8bo7Oy+LJv39J/vMf881pO7//51es//m1dE1L4o/jB2iaE9DRut6FUrubTu3NZKVEHrZVFJWTlS4Wvv65Vqb50PBeZNhMCes9NZnNQbqcajG0qiZH5Gnwer2oqoqqqkiSFFFzp4uVimo3RoNEdgcLfkXFp6h4FAWvX2Fr0TEW/SQHu8tHe4sBo07Gr6rMOJ+8E8j4zWxnYtm4ayipqKbK5SM1yUhGshGX18/K/AHMWP+pNqVt/c+vRS9LYZNvQsWrHtm6XxuyErAmoz08paHkmos5aUggELQMRVEpdbjxKwoZ7Yz4/NDOosPjU7kiLQm/ovJO8Xc8NLwXT//jICa9TLndxeapg6k+39lx7vDvMeXFT4LyFKo9fpbckUtplZvOKRZ+dv2VHC510KdzO7x+hRenDKLK5SXNZmTZ2H7M2bJP8y5ckZaESS9xWfukJmlRucOjTQuGC/pacHvfiO7UW3tolaKoVBtSmLTigyBdjmW1RF0iMhqWL1/OK6+8QocOHSgtLWXWrFls2bIlJguKN5JU03ehosqtGQMBN9uDw3pS5fTx8odHmXxdN2as/5Sld/TTDIZFP8nB6fEz8YULWb4r8geg14HdpXDHqg/pn50SVBZk1st0bG8Ju55w8arAHX+a1RiT7NnGeqtfDG47gUAQfQIJdu0sBqpcPrw+lVNePzPWBfdIeHPfceb/qDflDi8PbP5MK52cfXMPzp5v2AQETb3MsJl4+NZe5J/vehtoo9+rYzIVTi8WQ82N2m//9mWQjv5yyz6W3dG3yXoXTl+7pVsbvVOPx8ydcoeH6evrt4huzVBKROEJq9WqdWrMyMjAYgn/I3exoyigQ+IP73zNwhE5bJ46uGaS2gdH0Ms65mzZx+i8bC2hMRBXm35jdyocXq1MCGq+0Df3Hafc4cWnqCE7lgW6PYYjXHevzikWbXNGK3u2djjC4/OTYQvehCLhUdAauLxN22NNfb6gZXh8fvyKik6WMep0pNmMlFW5g8ISM9d/ypiBl3NZe7NmTACMzsuuVzVWO0E8kORYW8umrSuiwuklI9lEps2EqtaEIgI6Om1tEaV2NzJNz7ULp6+hqtfq0hpVC/VDxErcE9Eb9DQEplv6/X6mTZtGXl4e+/fvx2i8NOPXiqJyqsoNUG9uxJOjc9HJwRMr4UJugkkv4z9fYlmbMQMvp+SMk417vq0/iOr8cJaGCNd4pHbuQzSyZ0NZzYEZ93uP1bSeFgmPgtbAbNDRdV79RnDhOLr4xzFcjaAuRr0Or99PaZWb3//zK+6/pWdQ8mOg461OlvCrwZpYt2rska37g/S0sTHVp+1unnjzQOihfl47kNqkcwmnr3Wr10IR66qFUJq8amIew3Iyg/pRtLYuRzSwqvbgqltuuSW2K4ojZY6ai2DBiD5MW1s/zrVp6mCyUi0hs3aX3NGPY2eq62Wx6mSJJKMu5DCV9EbiToF4WYckA1umDUFV1ZDxqmhkz4aymue+WhPbm/LiJyLhUSAQADU/tCfPOpm2tojFP71a65UAdXMCZO3HrqGqscx2Ju05dSslIFjLfIoaUktTrQbO2JPoUmcEdmPIskSPDBtbpg3B51fQn29GFckxYl21EEqTp60tYv3Pr+XAyaq4texv0GgYNWpUa60jIfCfHzxV4fDUsyAzbCZcXj9LxuSy5oMjQZZuqb0mKSiznYklY3I191rNBpK1bN/aHR+zUi1smTYk7FrCx8vqt0SNRq/xcFZz90wbHzxyk0h4FAgEQM0PraKqZNhMXJZiCakbXdOtJBllLu9g0UonSyqcbC06pnV+DFSNrcwfwNI7+vHLV/ZRuOtQPQ2trWV6WQqppRvuHcz09XubHNtXFJWvS+3NykuI9YyHcJqM4o9rInpEiZBtBR01dcPpNiP/fPAGdBJ8d87FU9sP8sht3+PuNZ+QYTMx/cbutDPreXHKIGSpZhDLc+8e4o6B2XRNt7Jp6mAURcVs1JFqNuA8b2zUvhD+b9w1SFLNpg31hTeWiFibprZBDZXxG85qthh0IulRcEnh8voxGy7cDTY2Lrju8wUgSxL339KD0io3w3IymTSka00JuiRRZvdgNkjM2/pvpgztRtf0JApu70uSUUel08u6D7+l4Pa+XJlhxa+oLP57MaVVHgpu70vXdCt6GZbf1Z8OViM6WcJivPDZZ9pMrJyQF5R0uXJCHq9/WkJJhROnx0dpFRH/kDZFZ+t9BlFuP11Xly3G0Josqf64anKbNBoURaXM4cbl9aOTajZlslHPObcPUBn33EdBcf3Fo2vKb0oqnJqLKMDOh27A4fIyccgVQdUWNXWzNeU/GTYjJr3MxnsH41dUyuxunnvvEHcNuoLKam9Iq7ap8bKGhqfU3oy2jM4cLXcE9XEPlOyISZWCtoDImYicUFqZYjFiMero0dGK3e1j9s096lWanbF7mDK0G3Nf3c/L9wxiyoufBB13S1EJb8/5AQ+/ul+bAhwox3zx/cOMvCaL8bUqKAJ3/waDju9l2tg8dTA+paYFwOuflrD0n1+TlWqh+LsqCrYdiNhb0NK8hKYOrQpXohnOs/zyPYPqabXPUU5TczeiSdSNBq/Xy/z58zl+/Dgez/9n78zDoyrPxn3PPpOZ7AuLYRcokQYhFBH8WnBBq1CrYGgJoLixWGxREUFAW7SKuFQ+ZSmtKKBGJGoVW6sfFduKggaUnyYiQoREliwkJDOZ/ZzfH8M5zCQzYQKZJCTvfV1eJoczM++Z8+R5n/OsHmbPns3FF1/M4sWLqa2txe/388QTT9CzZ082b95Mfn4+er2e2bNnM3bs2JZeTiOU5k2HTtSTZjNiM+vxuWTqPX6sJr26uWuQKa12sv7jEu6/ZhDfVzbOV8hMtiDLcKzWzbKtRWGt1VRrYIhVndOn1gMHJwtV2N28MXsUGQlmVaCUjptbZl1KlcOjdoA8m3hZpATHdJtJNYKUtYr+C4LzEeEJiA2K7njmg31MzOmhVhnUueoDvWW0WuKMeuySj1dO6UyXV2LL54cZ2S+d3qlxlFU7Mei0YXVnnFGnVkEoOhFZ5ubRfcld+0nEp3+DQUeXeDP7yuvUsEewTlXOz79zJBpQDZ2GTfOUKodxWRlMzOmh5kcUFJbGJLGwqRLNSB6PN+aMaqST9+37ocXX1hxa3Gh4++23SUpKYsWKFVRXV3PDDTcwcuRIJkyYwLXXXsunn37KwYMHsVgsbNy4kYKCAtxuN1OmTGH06NExr8yodro5Xufi1V2HuO2yvo0sZJtJz//+az8zRvchzqhjztgL0Wlh5bb9jTJ210zNQa/T0D/DFtZalSRJFZJ0m4mNt42gvNZNjdPLk/88XZXg8PjxeHwcqKrnmQ/2ha3ceGlHCfOuGtjsJ/9ICY5LxmepHhPFsm5Po14FgmgRnoPYUOXwqPropR0l3HZZ35BNesWkbFJtRl78+Ht2HKxS9dRvLu+v9lPITLYgIzfSncsnZqPREJLM+NKOEh69IfuMT/9KHsKz//ctS8Zn0T/Dxv5ye4hOLat28kO1k3tf/zLwkBRvoneKFb1eG7J5j+qbym8u769O11T0erLFEJPvM1IoJNI1e30SFyTHtfhazoWo+jQ0h2uuuSakzbROp2P37t0cP36cW265hXfeeYcRI0awd+9ehg4ditFoJD4+np49e/LNN9+09HIa4fRIzN+yl4k5Pbj39S8bbaaVdg+/uTwwlvWEw0u1w4tBp6XC7lazfV+7cyTLrh9MgkVP8dE6Dp0aTBVMZrIFv4wqJHtKa/j2uJ17X/+SmRsLQ8oYv690UO7wYDXpWDw+C49PUnskKNnID/9i8Fk1DYkkjElBfxSilFIgEDTE4/OrPWki6csfql3cdfmFPD9lKC/tKGFiTg/mvLwbs0FPpd3DiknZSBK8tKMkpO/NSztKkGVYtrVI7Vnz2ysGhORXBROso5TN9/2icmZuLGR/uZ1lW4tUnaqcX3OqgdT8LXspPeHkyEknJxxuymrqOen0smJSNnf+rC9Vdk+Ivp11qi9ELL7PSMbQma65PdHiRoPVasVms2G327n77rv53e9+xw8//EBCQgIvvvgi3bp1Y926ddjtduLj40NeZ7fbW3o5jVB6KSj1wEN7JLF2Wo4qzGk2I4kWA6P6phJn1JFmM6pVE4or7d7XvyQjwYRfkumXbmVQt3jWTs1p1PtbblCjvGb7AdY0OG/5xGxWbtuPxydxoNxB6ameDsp8CQgIliw3r5RIIZIw1nv8IWsVuQsCgSAYxR3esDeNQrrNRO9TbaNTrCbuGTeA7onmgJdVlumdGodeq2XVh99x22V9QwyEGaP7UOcKbNxbZl3Ky7dfQmaKGQCdlrD6VNFRDTffcBMul0/MZs32A0BAf8YZdZTXufmy9CQ/fSIw6wJg/ut7WfK3rxrp21g0S2rKMDifZvrEJBHy6NGj3HXXXUyZMoUJEybw+OOPc/nllwNw+eWX88wzzzB48GAcDof6GofDEWJERMLtdlNcXHzWa0vs2ovMZAtev8S4rIxGoYBVecPQaeHOn/Wj9EQ9GQkmpv11F+k2k+pKq/f4SbMakWSZEw4vt6z/hHSb6VT2bxx6/HjrqvDrktRY3tAeScwa049UmzEkk1jJa/BLMnFGHfe+/iVLxmep8yWUeJ/f66a4+FCzr9dkNrMmb6jaejQz2cKavKGkxmnZfs9laJHwOaraPE4WjMvlOqd7DGfOiI8V0cpnW62vrWjOPW2P3825ymND2vIao5VRk9lMekJGo940gDpnZ9oLoS3zEy0GMpMt6LUatPiwGHXsOFjFDcMuCNF7T7wX0HtK3gGAw+Wj9ISTWZt2h9Wnio6ypnYNWYsyxyf/jhH4ZQ0HKxwhoQrlIcnjl1QPa8MwbUvp2zN9n+F0cV3lESrLXJjMZl6ZMRQJbZN6uSX0YzREktEWNxoqKyu59dZbWbp0KZdeGuhDkJOTw0cffcQvf/lLPvvsMy688EKys7P505/+hNvtxuPxcODAAQYMGHDG9zeZTOf0B1dT72b9LcOp9/h58Los8v6yM8QgqLJ7SI4zYNBp6J502mXVsGpCSVJUEiDLqp1qE6Q354ymR1ofJElm3fThIXkKk3MyGTOoS6M+7Vs+P8yw3qkhVn3SqT/AddOHk5kWjzbj7DJmJUlW42Z+r5vMtKQGXou2y8QNR3FxcbvcOKLhXOWzo2I2m8/r7+V8XntDmiOj1Q4Xa6bmsHLbt/xp8sXqDIm7r+ivlpArD0Qen4ROo2H9jJ/gl2W+PRrwmj5+44/pnmThZyu2N3r/WqeX6npvyBC+SPpUQdGrwQmF864aiOw8id+YiM0USLAE1NwLi1HHqg+/Y2JOD/V9gsO0LalvmyJYF59ONo/0OeGPt7V+bHGjYc2aNdTW1rJq1SpWrVoFwOOPP87ixYvJz8/HZrPx1FNPkZiYyLRp05gyZQqyLDNv3jxMptgn4SWYjdjdflb8cx+Lrh1Eus2kDktR637zcsiIN+KXdBGrJqocnjO2PFXqeB/+xWA1G3hAtwQKSyp59Y6ReP0Sfklmy+eH+enALjz5z30hVr3yB3OuVQzBCY7FxYdi8scgEAg6HvEmIwkWP/dfMwirScdzvx5K8imXuWIwNNSfa6flsOK9b7jtsr68X1TO+0Xl/Pv+sWH1qM1s4M5TyZVn0qcKkfojlFX6mf5CwCv8p8kXkx5vQpJljp10serD75gxug9PvLcv5PNrTuUutKS+bYqOkGze4kbD4sWLWbx4caPj69evb3QsNzeX3Nzcll5Ck2i1GjQEBqc43H7uvqK/Ol1N8TZU2t1kxBupc/nCVk2szhvG0r99zawx/c7YRlSr1YTkNiRZDMzc+A1/+/IYf/rVxcjAyH7paphCyUBeN3043RIbd38UCASC1kKv19I9wUK53Y3HJ/HLVTv4212jSLEGWj8HD5tSPA5Oj5/5V/+ISrtb1Y9unz9sBYVWc1o3nqmFdDDhNl8JreqlmLTmE975zWiOnHSRZDEw/dLepNmMjTwQT7y3T/UuCH0bHZ2yuZNimaYnmIgz6Rp5G8ZlZfDgdVmqkClVE0o+Q2KcgT2lNSFDV5pqiBTcbTG49/o3x+ooKCxlYk4Plk7IwmbS4/FLPPyLwSEDqQQCgaCt0Ou1dE+yUFEXMAJcXokTDjdrp+bg9PojehyeumkIf7k5h6M1biwGnVpBEVxiuXj8RapujFafRkKLFGJ0HDnpCumf8+odl6h5FV5/oBfOg9cNonuSRejbZtDi1RPnA8kWA92TzJTXujle61a9DWXVTnJzMrlrbH8efbcISQ7UFwdXTRj1WjSgbvwv7Sjhldsv4eMFY3llxtCwZZHBmbFKb3Xl5xmj+7BsaxE3rNrBjBc/Q6vRCAEWCATtDkWP1Xv8eP0y6fFGuiSYG3kcIBBW+FfxMXx+eHXXIWRZ5uZRfUIqKG4e1Qenx6dWPjTUp0rDuWh1oc9RE1KBUFBYGlKttv7jEtLjTdz7+pdM/esu5m/Zi9WkF/q2mXRoT0O4lp0A+yvsuL1+Vm3/Tu2NHuxem/7CLpaMz+K7cgev7jrUyDp+8LosNes3uHNipHyBhjE4i1HHG3NG4fVJIT+LLowCgaAtidTmGE5PhEyy6PH4Zbx+mU2flPD8lGF4/VJIWGFojyQmj+h1Rl16/zWD6JUa1+QU32hxu1wM7BWa65BsMTT5u9C3zafDGg2RWnZ2STBxx4bPWZ03jHvGDcBqNKDVoFrLJ05NuEyyGHj8H980crmtmZqDWa8lPb551mlHSIARCAQdl6baHCu6rtrp5aa1nzKqbyrzrurPTwd2Yc+hKq66qFtIaCBaXVpR56JvmpUuiZamlhY14fTsmX4XNI8OG56I1LLT6QnE4FJtRnx++PW6T/nNK3sCLVGtRqocHjWrNlwXSKfHj1arFdapQCDoUETSmcqMBjjdWGlzYRn1Xol/7zvO8D5p/P6dr0MaLEWjS+tcXuZv2YtW22G3oQ5Jh/U0eHz+kIoISZbxSzIaDfzfPT/DJ8mYDTpW5w3jyEkXb+7+gTt/1o8///uAWsGgJOUoDT+UXuvtsUuXQCAQnAsNOy0q4dp6j48jNRIZNhMWo47XZ15Kmi3g1p8+qg9HalzcdllfJFnm8Rt/jNmgo0uCuUldunxiNus/LmHttByhT88zOqTR4PNJGHRa7r9mIPO3BMop779mIBs++b5RB8jnpwxj9/dVXD/0Av780QHmXjGA/932bWDqWZyBV+8YiU+SQIY4o67ZYQmBQCA4Hwiu8gpXDfHijJ+gRYNPkkI6Qa7OGwZApd1DstXA798u4g/XX8TdVwxgZQNdanf70Gs1uLyBuRZpIqfgvKPD+YXcbh/H61z4/JJqMDz764vVIVUNM3zvemU3k0f04qUdJdw0vAcmvYb7rxmk9ly/+9U9jH3yI6a9sEuEJQQCQYcl2WJg7bScsP0XlozPwmzQcehEvdoJEgI6dPbLuzEbdLy66xBOj59F1w6i0u4h3WbkoQkX0SPZQoLZwLKtX/PzZ//DVc/8mwnPfcyyrUUiNHEe0qE8DV6vn28rHczeVMiGW0eQbjPx9OTssEOqZo3pp2bxev0SM0b3oVuSmV/9+VO1b4NS49ueh4cIBAJBS+DwejHqtSy7fjB90q0hHof9x04yoIuNOKMubNdGs0HLomuzOOn0kmoz4pdlUuKMaDSBh6zfv/M1N4/qQ9HRupDOkUKnnn90KKOh3O5WZzr4JZm7r+iPXqvju3K7mpDTcEjVuKwMHv7FRXj9gXajSkex4IZOmckW0S1MIBB0aOwuPzPWf0ZZtZMP5v00xOPwyh0jOVAemELcsGvjuKwMap0+ZgbN03lpxk+o9Xg5VuPG6fXzflE5FXWekJJLEZo4P+lQviGfJJNuM7F2Wg4g0zstDr8sq62gCwpLeeDng0LcbjeP6sO+Y3ZmbSpUs30hMDntdEMnnRBugUDQofGd8sgO7ZFEvcfH6qk5aphWOqVHk60GtTkdBAyIhdcOUg0GCIzMLq9zs7e0lplBelXRqUpzJxGaOD/pUHfNatTxVO4QxKD0SQAAIABJREFUUq1GDlbWo9dq0Wk0arnPxJweaDSE1BIvKNirutzCzWUXYQmBQNAZ0Gs1jMvK4KFfZHHC4cWs19A1MdDxUXtKj/7+7SIANt46gm33/IzX7hyJBk2I52HWmH7M3yL0akelwxgNkiRzvM7N4/8opsrhIdVqRK/T4JP8rJ6ao7aCVqZWAmqOQ/A8CCUssWXWpWyeeWmz2pgKBALB+UqGzcTDv7gIp8fPq7sOcbCynpNOL2un5vCvoqOqHv31up1Me2EX9V4/bxSWUVLpUHUqCL3a0ekwRkOVw8Oz//et2t980ppPeOhvX+GXwGLQkn/nSD6aP4asbvE8N2VoyAjqYEt4T2kNy7YWiZ7kAoGgU2Ew6JDlwIwGRY9et/K/vP1FGWMHdSXRolf1aP6dIyn+oYan/m8/K7ftZ3XeMNVwqPf4hV7twMQkEdLr9bJo0SJ++OEHPB4Ps2fPpmvXrsyaNYvevXsD8Otf/5prr72W5557ju3bt6PX61m0aBHZ2dln9Zken18tqZyck8n1wzKRZBmzXkvx0TrijDpqnF7WbD9AeryR9bf8BJfXz9qpOczcVMiT/9wXyBpOsxJn0pFmNQnBFggEnQq/LDcqTbeZDBj1WvxSoEHewQoHK7ftZ09pDQAVdjd2t48l47P4Udd4LAYd66YP544Nnwu92gGJidHw9ttvk5SUxIoVK6iuruaGG27grrvuYsaMGdx6663qeV9//TW7du3i9ddf5+jRo8ydO5eCgoKz+kxl+MjknEzGDOrCI1u/ZsboPlyYYSUj3hSS2Xvf1QO5f8teKuxuCmZdKgZGCQQCAWA26NTkR4B7r+zPmEFdeOhvXzExpwf90q2kx5uosLsB1O6OT7y3jwq7m9fuHEmazUSazSQGQ3VQYmI0XHPNNVx99dXq7zqdjq+++oqSkhK2bdtGr169WLRoEYWFhVx22WVoNBq6d++O3+/nxIkTpKSkNPszU61GnB4fvxyWybKtX3PPuAFoNRrqXH7qPQGPQpxJz/eVDp78Z0DAV0/NISXOiMGga8nLFwgEHQiX14+5GTqiuee3J9KsJlynwgtl1U6uH5bJI1sDPRZe2lHC3Mv7kxZv4rlfDyUxzsD3lfUh+jTDdtqTIAZDdUxiYjRYrVYA7HY7d999N7/73e/weDzcdNNNDB48mNWrV/P8888THx9PUlJSyOvq6uqaNBrcbjfFxcVh/82WkIBkTmLG6D4YdToOVdUTb9bzx78Xc9/VA3n7izImDe/JU7lDMOq16Lx2vvvuSItdt8vliri29kJnWeOgQYNaaDXNoyn5DKat1tdWNOeetrfvxmzQ0fuBd6M+//vHrzvjtbblNZ5JRm0JCayZOoxZm3YjBYUrHr/xx1TaPWi1GhweP//4f0dUfWrQabEY4Lvvvm3FKwnlfNBtLUFrXWckGY1Zc6ejR49y1113MWXKFCZMmEBtbS0JCQkAXHXVVSxbtowrrrgCh8OhvsbhcBAfH9/k+5pMpib/4H6orqdropkqu4c4o44qh0ctuVTGtdZ7/AzpkUhKcgbdMjJa5oKB4uLidqfwGiLWGFvOJJ+dFbPZ3Km+l/Z8rdHI6AWSrIYXlHCFolfLqp0UFJYyMacHJxweapxeCgpLefSG7Da97vNZbzSHtr7OmFRPVFZWcuuttzJ//nwmTZoEwG233cbevXsB+OSTT7jooosYNmwY//3vf5EkiSNHjiBJ0lmFJoLJsJnQajRUnTIOCgpLWT4xWy25vPf1L8lIMJFkETXCAkFr4PL6O4Uy70hotRrS401k2Eykx5vITLag02hUnapUVyiNmn575QDRd6GTEBNPw5o1a6itrWXVqlWsWrUKgAceeIA//vGPGAwG0tLSWLZsGTabjeHDhzN58mQkSWLp0qXn/NkGgw6zQUdBYSlzxl7IjNF9WP9xCUvGZ5FqNZIRb6K7aAktELQaZ+PeF7QPDAYd3eJNrJ2aQ6XdQ4rV0EinpsebuEDo1E5DTIyGxYsXs3jx4kbH8/PzGx2bO3cuc+fObdHPT7eZmHfVQJ75YB8zRvdh4bWD0Go0WAw60myi5EcgEAiixWjUM6hbAjVODyccHjw+mYU/H4Qkg1GvpVuCGb2+w7T8EZyBDjWwSkGr1TCwSzyP3pAtSn4EAoHgHNFqNaRYA2HdKotH6NVOTIc0GuB0TE4gEAgELYPQqwLhUxIIBAKBQBAVwmgQCAQCgUAQFcJoEAgEAoFAEBXCaBAIBAKBQBAVGlmW5bZeRHP44osvMJlEIo6gafR6Pf3792/1zxXyKYiGtpJPEDIqiI5IMnreGQ0CgUAgEAjaBhGeEAgEAoFAEBXCaBAIBAKBQBAVwmgQCAQCgUAQFcJoEAgEAoFAEBXCaBAIBAKBQBAVwmgQCAQCgUAQFcJoEAgEAoFAEBXCaBAIBAKBQBAVwmgQCAQCgUAQFcJoEAgEAoFAEBXCaBAIBAKBQBAVwmgQCAQCgUAQFcJoEAgEAoFAEBXCaBAIBAKBQBAVwmgQCAQCgUAQFcJoEAgEAoFAEBXCaBAIBAKBQBAVwmgQCAQCgUAQFeed0bB///62XkJEvv/++7ZewhkRa4wtbSmf7fl7E2trP7RnHXoudJb72NbXed4ZDT6fr62XEBGn09nWSzgjYo2xpS3lsz1/b2Jt7Yf2rEPPhc5yH9v6Os87o0EgEAgEAkHbIIwGgUAgEAgEUSGMBoFAIBAIBFEhjAaBQCAQCARRIYwGgUAgEAgEUaFv6wUIBACSJFPl8ODx+bGmdkWSZLRaTVsvS9AKBN97o15HqtUo7n0Hx+X1YzboYna+IHYIo0HQqoTbIAD2Ha/jjg2fU1btJDPZwrrpwxnYJV5sHucZzTUAJEkW974TYjbo6P3Au1Gf//3j18VwNYLmIMITglZD2SBuWPUxo5d/yA2rPmbf8TpqnB510wAoq3Zyx4bPqXJ42njFguYQ6f5KkhzxNVUOce8FgvMJYTQIWo1IG4TT41ePKZRVO3F6/fxQXU9FnbvJjUfQPjgbA8DjC3/vPT5/VJ8pSTIVdW4hJwJBKyHCE4KYEM5NHWmD8MuQmWwJ+bfMZAsHyu3MePEz4bJuRzQVfjgbA8Co14W990b9mePXIrQhELQ+MfE0+P1+Fi5cyK9+9Svy8vI4fPgwVVVVzJ49m7y8PH71q19x+PBhADZv3syNN95Ibm4uH374YSyWI2gFgp/4yutcfF/laOSmthgDG0QwmckWzAYt66YPV/8tM9nCiknZrNwW6JEvXNatw5me2s8UflAMgGDOZACkWo2N7v266cPVXJemEKENgaD1iYmnQdn88/Pz2blzJ4899hiJiYlMmDCBa6+9lk8//ZSDBw9isVjYuHEjBQUFuN1upkyZwujRozEaz6wwBO2HcE98KyZlk24zUVbtVJX5G3NGsW768EZPhmlWE2lWE2/OGY3H50eWZea++gV7SmvUz2iOy1rQfKJ5ao+0Sb85ZzTp8SbVAGj4HqlWI5URPler1TCwS7x675tTPXGuoQ2BQNB8YmI0XHnllYwZMwaAI0eOkJaWxs6dOxk4cCC33HILF1xwAQ8++CCffPIJQ4cOxWg0YjQa6dmzJ9988w3Z2dmxWJYgRoTbTOZv2cuS8VnM3FioHvP6pCY3iPR4EwCHy6upsLtDPiNal7Xg7DiTQQBn3qTP1gDQajXqZzSHcwltCASCsyNmOQ16vZ4FCxbwwQcfsHLlSt544w0SEhJ48cUXee6551i3bh29e/cmPj5efY3VasVutzf5vm63m+Li4lgt+5xwuVztdm0KsVijJbV72M0kyWJQf89MtuD3utm371DIeeGeQDUaDWvyhjLr5T3qE+uaqTn4vC4OlhzB7XKdcU2DBg06q2s5V9pSPs/l3ka6hw6ni8qygwBYU7uG3aT9XjfFxaH3VUG5v7GQO5PZ3FhO8oZSV3mEyrLIMmIym9Fbk5DQokVCo9G0+j1rK/mE9qFDz+b6z7Tm80H/tgStdZ2R7lFMEyGXL1/OfffdR25uLvHx8Vx++eUAXH755TzzzDMMHjwYh8Ohnu9wOEKMiHCYTKY2/YNriuLi4na7NoVYrLGizh12M6n3+NWf100fTmZaPNqM5KjWmNU9iTfmjKLe7aek0sGSt76iwu4OuMx7td9Et7aUz3O5t5HuodVipvep95QkOWz4IZr7Gqu/DUmSw3g2Iq9FCcNMX/95iKGR1T2p3cpUS9OedWhTnGnN54P+bQna+jpjkgj51ltvsXbtWgAsFgsajYYRI0bw0UcfAfDZZ59x4YUXkp2dTWFhIW63m7q6Og4cOMCAAQNisSRBC9IwYS7ZYgibzDakRyIfLxjLm3NGNzujXavVoEHD1L/uZMaLn7GntEYkurUwwfdRRmbDrSOaTEgMDj+c7X1taZTQxgXJcaTHm864lnBhmFkv7xEyJRBESUw8DePGjWPhwoXk5eXh8/lYtGgRgwYNYvHixeTn52Oz2XjqqadITExk2rRpTJkyBVmWmTdvHiZT82ObgtYjUsJc/3Rb+Fi29ew/SyS6xY5I9/Ht34zG6Ymcj3C2+QftBSFTAsG5EROjIS4ujmeffbbR8fXr1zc6lpubS25ubiyWIYgB0STMtRQi0S12NHUfL0iOa+PVxQ4hUwLBuSE6QgqaRWs+qZ1LDb+gaTrrE3c4mVqTN1TIlEAQJaIjpKBZtOaT2rnU8AuaprM+cYeTqbrKI00mTwoEgtMIT4MgIuE6BLb2039zE90EjWkP97E90VCmoinhFQgEAYSnQRCWpjoEtvbTf3PHLQtO057uY0dByKOgMyOMBkFYzpTwGOsMekUxS5JEpcPDzI2FYijRWdDW9/F8JpxxAIghWYJOjQhPCMLSlolyJrNZHYz0RdlJ1WAY2iOJJeOzcLh9HKt1iTHIUdBZEx7PlUjDuSod7ohDssSYbkFnQHgaBGFpzUS5YK+CXwZjYgbT1+1UW1ErBsN9Vw9kQcFe8YTXDDprwmNTNPQgmMzmRsdk5LDGwSt3XBLWCJMkSXggBJ0C4WkQhCXWiXLKU9nxk06Kj9Xy4Jt7+a7CQe7aT/ihxqUq5hqnl8xkC7PG9FMNBhBjkKOlMyc8QuMkUJ9PauRBkOJSGh2rd4f30Og0mrDjv/0yYky3oFMgPA0ClYZPWxG7PLbA5yhPZUvGZ7FsaxFLxmepRoFiKJRVO1mz/QDLJ2Zj0muFm72ZKPczwaxn88xL0WlAq9V2msS9cEmgr9x+SaPNvbTazZK/fRVyrKTSEdZDYzHqws7fkGVZyKegUyCMBgHQdJZ9S24wkiRzrNalfo4SflD+D6iGwoKCvewpreGlHSUsnXCRcLM3g9a6n+2RYOO3oYFQXudutLnHGXWNjq3ctp+1U3OYuSk0ATfJYiTJYmxkTFc5PEI+BZ0CEZ4QAJGz7FvSvapsZEdqnI3CD8r/AfaU1vDkP/ex7PrB/Pv+sTx6QzZd482d2s3eXFrjfrZHghMYy6qdjYwBZXMPpt7jb3Sswu6mW5I57HCucL1DOnsYSNB5EJ4GAdA6WfbKRrZkfFaj8MNLO0pU70JZtZMKu5uuiWYykyzqk7HoKxA9nbVqIthYCg5zKRQUlrJ2Wk5ICW+PZFPYkEOSJXr5Et1LBZ0FYTQIgNhl2Qe7iv2n4r7hwg+Lr8vCpNeyeealeL1e4symRkr3fJ+w2Jp0tqoJRc7qPb6wYS7FGJh31cBGuTp1lUcY2Kv3OW/4Qj4FnQFhNAiA01n2DZ+2zsW92jCuvv6Wn5CZbFHDD0vGZ5FqNdI9yULXBLOqpIuLv6fXoEEtdWmdkljcz/ZKw8RaxVgKDnP1y7BhMZw2BoI398oyl9jwBYIoEUZDJyRSG9yWdq82jKuv3LafFZOymb8l4GFYtrWIddOHhxgMgrPHZDZTUeeOefVLeyNYzhp6F8KFuQQCwdkjjIZOhtJtMVJWfUs+bTWMq+8preGJ9/bx2p0jATr0RtbaSJJMvSGJ6acSADtTtUSwnAV7sQZ1jcdi1AsZawVcXj9mQ8cMfQlCEUZDJ0NvTWL6+sizCM6VYC+G5lQjnGDDocLuxqjXCVdwC1Pl8DDr5T0xu6/tEUXWgBA5U7xYHfna2xtmg47eD7wb9fnfP35dDFcjiCUxKbn0+/0sXLiQX/3qV+Tl5XH48GH139555x0mT56s/r5582ZuvPFGcnNz+fDDD2OxHEEQErFrktSwX//Db3/Fmqk5ogytFehs1RLBsvabV/awYlK2kDOBoBWIiadB2fzz8/PZuXMnjz32GKtXr6a4uJgtW7Ygy4FBLhUVFWzcuJGCggLcbjdTpkxh9OjRGI3ijz1WaJFillXfMIfh/aJyADbPvBRZlkU4IoZ0tmqJYFkrq3byxHvhEx4FAkHLEhNPw5VXXsmyZcsAOHLkCGlpaVRXV/Pkk0+yaNEi9by9e/cydOhQjEYj8fHx9OzZk2+++SYWSxKcwueoafEmNEp//+ByN4X3i8qRZTmkEY6g5Um1GlmTN7RDP20Hz5Fwen2N8mVmvPgZOg1CzgSCGBKznAa9Xs+CBQv44IMPePbZZ3nwwQdZtGgRJtPpGKPdbic+Pl793Wq1Yrfbm3xft9tNcXFxrJZ9Trhcrna5NpPZjN6ahIQWrSURm7+OV2YMDfyOhM9Rxb59P5z1e9cbkpj18p6QcjeFzGQLfq+b4uJDUb9nS3yPg9qoZLOt5NNkNpNgTeLl20ag02rQ4cN58uzva0tzrvc0WM6Cy3fPVdZaYm1nQ1vJJ8RGRlvjes605vaqf1ua1rrOSPc0pomQy5cv57777uOKK64gLS2Nhx9+GLfbzXfffcejjz7KyJEjcTgc6vkOhyPEiAiHyWRq0z+4piguLm53a1Niv0ryo5pVnxacVZ981u9fUedWM/bDNdNZN304mWnxaDOi/4z2+D1GS1vIZ8R73Kt3u3niPtd7GixnEFq+ey6y1hJrO99ozzq0Kc605s5yH9v6OqMyGh577DEWLlwY9Zu+9dZbHD9+nJkzZ2KxWEhLS+Mf//gHJpOJsrIy7rnnHh588EEqKir405/+hNvtxuPxcODAAQYMGHDWFyNoTKQZBC2VWS7K3dqeWN/j9oAo3xUI2gdRGQ0HDhygtraWhISEqN503LhxLFy4kLy8PHw+X6OwhEJ6ejrTpk1jypQpyLLMvHnzwp4nOHtinVXfMAFPlLu1Pp2hciJcoqco3xUIWp+ojYZLLrmElJQUNJqAJf/f//434vlxcXE8++yzYf8tMzOTzZs3q7/n5uaSm5vbnDULmkGss+o7U7vi9kpnqJwQciYQtA+iMhpE/4Tzl1grWzHdr+3pDBuqkDOBoH0QldGwf/9+HnroIerq6pgwYQL9+/dn7NixsV6boAVoqGz9XncgWawFla0Y9tO2KPf4lRlD0RlMHXZDFXImELQ9UfVpeOSRR3jsscdISkpi0qRJ/O///m+s1yVoQRRle0FyHI6qY+e8mQTXy1fUuZEkuYVWKjhbtFoNjqpjnaIfhpA/gaDtiLrkslevXmg0GlJSUrBarbFck6Ad03DcdWcajCRoe4T8CQRtS1SehsTERPLz83E6nbz77rtRV1EI2j/NfWqLVN6nDA4SdE5a6+lfyJ9A0LZE5Wn44x//yJo1a0hOTuarr77i0UcfjfW6BK1Aw6e2cVkZLL4uC51WEzEu3hnK+wTNI9qn/+AJqGebdyHkTyBoW6IyGmw2G0OGDCEhIYH+/fuTlJQU63UJWoHgp7ahPZK4eVQfpvxlZ5OKvzOU9wmaRzTNpUxmc4uEFYT8tQ4urx+zQXyngsZEZTQ8+OCD1NfXc/HFF/PWW2/xySefhAyeEpw/mMxmKurcgUoKWVaV76wx/dT2zxC5q2BnKO8ThCeSpyCap3+9NUltc638+9l0rRTy1zqYDTp6P/Bu1Od///h1MVyNoD0RldHw7bff8vrrrwNw8803i2ZM5ymSJFNvSFJ7+AcP/UmyGKJy+4p6+c5JUyGIaJ7+JbQtElYQ8icQtC1RJUL27NmT0tJSAKqqqujWrVtMFyVoPtEkolU5POqUQDg99Ccz2UKN06uOVVaI5PYNLuHs6OV9HYGWSFJsKgFRefpvaiy3Filq+ToTQv4EgrYjKk/DF198wc9//nO6d+/O8ePHMRqNXHbZZUDT7aQFrUOkp8D+6TaqnV71iaypoT96rYa103KYubFQfY8Nt45ARuaH6nrxRHeecjYliuHCEE2FIKJ5+vc5alokrNASyZQCgeDsicpo2LZtW6zXITgHIj0FvnL7JSGJja/cfkmTQ3/S482q4rcYdRyvdTN91Q5RD38e09wJmJGMjFSbsckQxJm6NbpdLgb2OrewgujRIBC0PVGFJ3bv3s3111/PZZddxo033khxcXGs1yVoBpGeAsvr3CGbxSPvFrFm6rCIbuRgt69fQtTDdwCaW6IYycjQazVnDEGciXMNK4geDQJB2xOVp+GRRx7hqaee4sILL+Tbb79l6dKl5Ofnx3ptgiiJlIjWUJm+X1TOQ+N/FNXTnqiH7xg0t0Qx0n13evxtnoAoZFIgaHui8jTEx8dz4YUXAjBgwADMZnNMFyVoHuES0dZOy6GgsDTkvMxkC36fL6qnPWWzUcjNyeT/7vkZPknmSI0Tn0+K3QUJWoxokhSDaXjfldcY9bo2T0Bsam1NIUkyJxyBRNDDJxyU17nEvAqB4CyJytOQmprKgw8+yMiRI/n666+RJInXXnsNgMmTJ8d0gYIzEy4RLdliYN5VAyk6WhcS//U5qoDkM76nstk888E+fnN5fxItBrQaDQZdYKOodLjRajSkxBnR66OyPQVtQHNLFNtzH4TmrC04YVIGZFnmhMOLzaxHg5+jJ50YtBpcPon4rr04ftKJQa8lySISKwWCpojKaOjbty8Ahw4dwmazMWLECCoqKmK6MEHzCJeIFm6z2Lfvh6jfr3+6jd9eOSCkomLFpGzijKef7GpdXnqnWIXh0I5pzkjp9twHIdq1hUuYXDEpmyfe20eF3c3yidm8tKOEGaP7qMcUua4xe+mdam0X1ysQtEeiMhpuvPHGRse6d+8e8Xy/38/ixYspKSlBp9Px2GOP4XA4WLZsGTqdDqPRyPLly0lLS2Pz5s3k5+ej1+uZPXs2Y8eOPfurEYTQnM0iHNVOr2owQCB+PH/LXpZdP1g954TDi8Wgw6DXkmYVNfMdgXOVm1gSzdrCJUzO37KXJeOzmLmxkAUFgZ+DjylyrXgjMuIDIdhgj4XFqMMnyXh9UrsypgSC1iQqo2HevHloNBokSaKsrIxevXrx6quvRjz/ww8/BCA/P5+dO3fy2GOPUVdXx5IlSxg0aBD5+fmsW7eO22+/nY0bN1JQUIDb7WbKlCmMHj0ao7HtXaGCyIlnwZ4GAJ8ko5NkKh1uUiwiXCFoWyLJbZLFEPJzw2OKXLu8gXwdn09iX3kdMzcWMqpvKrPG9MPl9RNvNuD1+zlyKsQhwhqCzkRURoOSvwBQW1vL0qVLmzz/yiuvZMyYMQAcOXKEtLQ0fv/735ORkQEEPBEmk4m9e/cydOhQjEYjRqORnj178s0335CdnX2WlyNoKSRJRqPRsGXWpVQ5PKzZfoA9pTVkJluo94Rmq3v9MkdqHKTajLi8fjKT4oQCFbQZSsJkus3ErDH9SLIYqPf4keRA8mNwB9Qap1c9psi1ThOQ/yMnnczcWEi6zUTeyF5Mf2GXGu4IDnGIsIagMxGV0RBMfHw8hw8fPvMb6/UsWLCADz74gJUrV6oGw+7du9m0aRMvv/wy//nPf4iPj1dfY7VasdvtTb6v2+1ut30iXC5Xu12bQjRrNJnN1BuS1JbT4ZSkgsWo488fHWDHwSqWXT+YHilxlFXW4Kg6FtM1nolBgwad0+vPlraUz/Ysf625NpPZzIu35FBh9zJ/y15Vhp+6aQjjsjK4eVQfXtpRouY5BOfqWE16zHqZIzX1ap+TJeOzuOuV3SHhjuAQhxLW0MveqOW+reQTopPRtlxfJM605vYs/y1Ja11nJBmIymiYPHkyGk3Agq6qqmLUqFFRfejy5cu57777yM3N5d1332X79u2sXr2aP//5z6SkpGCz2XA4HOr5DocjxIgIh8lkapcCDQGhbq9rUzjTGiVJ5liti+lrP2mkJF+7cyS6U09SMuDxSTz/r+/YXFgGQJxRh1YDOv253aPz4XuMRFvKZ3v+3lp7beV1Lm55MTQf597Xv+TVO0YCMrde1heTXsPTuUMw6LWATOkJJ3/fe4QJF2fi8vqpcnjITLZEHOamHFeMaJ2h/eqmYNqzDm2KM625Pct/S9LW1xmV0fD000+rP5tMJtLS0gD48ssvGTJkSKPz33rrLY4fP87MmTOxWCxoNBo++OADXnvtNTZu3EhSUhIA2dnZ/OlPf8LtduPxeDhw4AADBgxoiesSnAVK1rnHJ4VVkkdPuqhyeEi0GLjv9S8bNQwKuIA5qyFEAkFL4o0gw26fn1vWf6b+29ppOSzbWhTy+6xNhSwZn0VBYSnLJ2ZT7/GHbZClhDiUsIaQe0FnIKqMtQsuuED9TzEYAJ566qmw548bN46ioiLy8vK47bbbWLRoEY8++igOh4O5c+cybdo0Vq5cSXp6OtOmTWPKlCncfPPNzJs3D5OpfWZtdwaqnW6OnXSRaDGw/pafMLRHkvpvSofJNdsPYDZoeX5KaDvqFZOyuSDZjEmvaRc1/YLOjVGvY1xWBmun5fDanSNZOy2HcVkZ6DSakM2/oRdB+X3N9gNqGMNs0LI6L1Tel0/MpqCwlBWTskmxGuiVGifkXtApaHZOQzCyHL6rWlxcHM8++2zIsSuvvDLsubm5ueTm5p7LMjoNSvmXJElIMnglCZ1Gg8WoO+vsbeU93T4/fknm1V2HeL+ovFFt+/NThvH8h/vZU1rD798u4v5rBpJ/50gkSUar1WC6bKcEAAAgAElEQVTQajAaNCSaRdlleyfSpMiGx5MthpApqe21xDDc9SSZ9cy9YgCzN53uMbIqbxi1Lm+I10DxFjT8fU9pDU/+cx+zxvTDoNPSJcHMG3NG4T3VCVWrgaUTLhLVE4JOxzkZDUqeg6BlCVaCGo0Go06D1y/j9kkcq3VhNeqY/fLukMY1mckWTAZd1DXk0qkSyXq3n5JKByu37afC7mZ13jC16c38LXt59Y6ReP0Sr+06xM2j+lB0tI49pTXM37JXTBhsJyjyYkntTkWdO+JmH+meK2PU91fYQxoirZmaw8pt36pGZLj73VajqoM/1y/JPPJuUcg6021GKuvcPHXTEGqcXtZsP8Ccl3fz5E1DWD4xmwUFgQTJgsJSVuUNY86pv6eCwlJWT81h9qZC9pTWsGxrEeumDyfNJoxhgQDO0WgQtDzhutmtyhvGc//aH+IBSLeZKKt2qo1rXr1jJIer6qlyeCgoLGXeVQMjbujhPmP5xGye/Oc+Zr+8m2XXD+a+qwfy5D/34fVLGPUapo3qgyzLvHbnSIB2/eTZmQh3L8Nt9uGMAuWe37HhczbPvLRRQyQltv9+UXnYkdo+n8SRk4FpqtHIXSyvefnEbCrqPOwpreGODZ/z8u2XsORvXzW61jSbEbdPUr1kxcfq2PTJIZaMzyLJYqDG6aVLvLFddsQUCNoD59SFJ1J4QnD2hOtmN+fl3UzM6aH+Pn/LXmaN6ae+pqzayfFaF5PWfMKyrUXcdllf7C4fZTX1VNS5Q4bzmMxmjtW6cLh9LBmfxdAeSWp1xKwx/dRs8AUFe7n7iv4YdFq+PlLH3Ff28Ot1OwHabGCRoDHh5GXWpsIQebljw+eU292Nzgu+515/+MRBpfmR8rsyUVKSZPaV1zHlLztVubt5VB+e+WBfxFHVkiRTURcYHNVQLpt7zc98sI8l47N47c6RLBmfxUs7StS/ibJqJxUNxsIr8mw26MiIN9M13oxWq2HZ1iI2F5Yxc2Mhk//8Kcu2FuH1y206mEsgaM9EZTT89a9/DXt8woQJLbqYzo4kyTi9vqiUd/DvwWOwldIyu9vHT5/Yzg2rPqb4aC019W6q612Yk7sgyRJdEsz0z7DxzOSLyc3JVN9TyQovq3bSO83Kpk9KmLmxMBC6mJpDhk0kqrYnztT9UPm9KaMgM9mCQacNO0FSaX6k/K5UCFQ5PI1ajC8o2MvEnB5hR1WbzGb2Ha/jhlUfM3r5hwG5PFarTkuNZFA0PO7zSXh9fpaMz6Jfuo1Ei55+6TYWXjuIH3WNZ2iPpLBj4RV57hpvJj3ehF6vJcNqZPXUnJAERyHjAkHTRBWe+Oijj7jlllvQ6UJLikQCY8uhuHo9fpn1t/yEldsCSYcQXnkrZV7BrleF4NrxsmonMzcV8vqskTjcfhxuHwBOr0R6vAmdVsPvrurPlEt64vXL6ntlJluIM+iYPqoPU0b2Rq/VkGEzYTCIsrL2QlNdOxvKi2IUhCuTXTd9OBk2U6MJkkpYTDl37bQctUIgkrGSajWGLT3UW5OYvj7U0zFzYyGv3H4J3RMtjUIn4UIqM/+nNxMuzmTltm/VyoabR/VhQUGga+PdV/TnydwhmPRaTjg8vHbnSCRZxi/JmA06jDpNiNfAaNTzowwbr905Ep8kCxkXCKIgKqOhurqa//mf/yEzMxONRoNGoyE/Pz/Wa+sUSJJMjdPD0RoXMzeFTpNUKhcaKu/VU3NIsujZdu/PMOq0LNv6tWpgKOcEbxrpNhMeX6B5jc2kB2S1z4LSKU+r0ZAWb6TK7iE93sgfb/yxcM22UyLJjNK18zeX9w+Rl0hGwdqpOXRLMquZ/8oESafHp8b6J+b04LbL+lLj9JIWFNtXWjU3NEIy4k3hR1WjDWtklNe50eu0jUInd2z4nDdmj+LYSRdP3TQESZbpmmBm2gu7WDI+S+3IuKBgL+k2E/ddPVBNblT+ft7c/QM3DLuAB974f+rxDbeOwGbWhyQM1x471CmaAgkELUFURsOaNWtivY5OiSTJfF/lQJLB6Q24XJWnxflb9rLptksw6DSY9Foe/sVgloyX+a7cztK3vlKNhHFZGfz2ygEUHa1rZHAADO2RxNOTh1BR5ybOqCPNZmTaqR76cDqcsez6wdy09hN1M+mfbhMGQztESQI8dtLFq7tCE/he2lHC/Kt/xLp/H+ShCRfx0ISLQhL5zjRWWpkgWVGH2vBI6faZmWzhzTmj1XNTrcbGRsi0HLonWsLKjRYprJFR5fCQHm9qZFCk20yU17nVZMb8O0dS5fA0GjaltHlWDAY4nfez/pafMOPF042c0m0mjte6mP7C3hCPhslsbrkbJBB0cKIyGvR6PStWrKC6upqrr76agQMHcsEFF8R6bR2eGqeH47WukP74SnhgT2kNlXY3vVKtpJ3KVpckGbvbR4XdDQSU7ryrBtI/3aZuBlqNhvI6FxV2N0N7JPHILy9CkgMxaKNOi18m7BNf33Qrnyy8HI9P4pVPv+f2n17Ybscjd2aUxMfVecNOueZDZcfl9bPjYBXz9T9qdP+iHXkdziBYN314iAchGiMkGJ+jhrXTctQ8iGDPyMO/GNzIoLj7iv7MOuVFGdojiS4JJr49bm80bKqpNs86bWgjp/uvGYjLK/HUTUPw+iWsJh0GnRZjUhfKa13IsoxWqxXVEgJBE0RlNCxZsoQZM2awatUqhg8fzgMPPMDmzZtjvbYOj9PjVw0GCB2Es2xrUSNXb1OKOj3IsHB6/Tx50xB6pljYd8wOBMrh5oy9EL1WE/aJ72CFA7NBS5xRx8ThPdAgKmPaI0ougdlwulcHnJadF2eMaLTBN5doDYJojRAAt8vFwB7xvHL7JWqJ5ks7Sph31cCwoZM+aVb12u4dNwC/hNrW+aUdJSH/j9Tm2S/J6vGhPZKwmfTM3xLa3+QP73xJhd3NiknZWIw6Vn34XauUjQoE5ytRVU+43W4uvfRSNBoNffv2Fa2eWwi/LEdMJovk6lUUdaRyMK1WQ+9UKwO62PD6ZeKMOlZu28/No/qw6sPvOOn0sHZaaMb48onZrNy2n/lb9nLC4eWHahfuU1ntgvaFkktgd4evsjHptS2y4Z1Jzs4GvV5LZnIcvVKtDO6ewKM3ZDOwSzz6U2t+c85oPl4wljfnjCbOpFNltFuiBafHpyY/TszpQVKcgSXjL6J3ahx9062saVAFsWJSNuv+fVBtfDZrTL9GRpZSuqz8XO3wMjGnB3ds+Dxi2ahA0NmJytNgNBr5z3/+gyRJfPHFFxiNosf6uaB0s9Nrwj/1d0+y0DXBfNaKWqvV4JdAkmXqPX4q7G61Ja7LK6H1ybx6x0iO1DipcXrVcAigVl34z7KGXhBblNDBsZOusLJjNuja9RNyJO9Ew+OSJKveB6Ney+ETHl7dFUjMVMIRBYXfMjGnR6DXwsyRvDF7FF6/hEGvRa/V8NsrA31GnrxpCBlh8iaCS1OViqM4dCH9KAQCQShRGQ3Lli1j+fLlVFdX88ILL/Dwww/HeFkdFyWR7ZkP9jH90t5suHUEh6rqQ1r6hjMYmtuu1+Pzc+ykixSrgRWTspm/ZS8zNxYGqi/yhgFwb4RJlQB63Tn1/RLECK1WQ/90G0kWPavzhjH75d1quWHvtDhkZHUeSGsQqzbSwSESvySRYjUwY3SfkPyftVNzeHbbt6ydlkOGzYxe30BmrafXd6iqPuKkSuXneo8fj18K6UchEAhCicpokCSJ+fPnn36RXo/X68VgMDTxKkE4qhwe3tpdygM/H8QJh4f95XYKCktZ9svBdA8qf1MIV143LiuDxddlodNqwipqSQrUpq//uORUHoOWjbeOODW2Wku8WYfNaGDdtOHcsfHzkBhvnFGH1aQXDW7aMdVOLzet/ZR0m4kVk7JJsxkpq3ZRXuum3lNPr9Q4eqdaW9RwCGccAI3aOQfPpwh+jTW1a7ONGcX7UOVwAYTIsU6rId6k49Ebsps0VBTjo0uCibVTc8KWNSs/KzkN55oTIhB0ZKIyGmbOnMnx48fp27cvJSUlWCwWfD4f8+fP5/rrr4/1GjsUkiRxY04PDlXVE2fUYdRpmTP2QlZu+5ZHb8gGoKLOjcfnx2LUcbw2MK5aKT0b2iOJm0f1YcpfdqpPmH3SrMSZdKRZAxv9sVoXj7xbpOYxTMzpgUZDwP3rrCYpJVD5MrBrPG/MGYXLG6i60Gs1aDUaUuKMjZ/aBO0GJRlSeWqutJ923SubXa3LQ1Jc8w2/5hgHqTZj2P4Kb84ZTarV2KRBEemzwm3+GgLH7G6fGnJLsRqIt1hIt575GrVaDSlWE0mW0zMlDHotOi08++uhaJEx6nXIsnxGI0Qg6OxEtTNkZmby3nvvkZ+fz/vvv8+Pf/xjtm7dyqZNm2K9vg6D0g4X4ITDw5K/fcXkP3/Kkr99hdPjZ8boPkiSxL7jdTz45l6+OlLLSaeXOzZ8TpxRpyrmWWP6hTS0WfK3rxjz5HZuXLWD76sc7Dtex5EaJ+8XlfPkP/epMeAqhwezXou9tlZdk1arISPeTM8UK5nJcXRNtJCREMbNK2hXKMmQAF0TzKz/ONAZcdnWIiat+YTpL+zih2pXs2c7KKEzpdXzg2/upay6niMnnWGNA5c3fFdIj88fdiZGcIJhw8+6YdXH7DteF3bNTo+fh98uwuMPJOd6/BIPv11EndPfrGsMTu7MiDeTajXTMyWOuuOHyUgw0yXRIhqaCQRnIKrdoaqqipSUFAASExOprKwkKSkJrVZsLtEQrCCdXqlRmeX6j0vomRKHX5ZJijNw9xUDWLa1iPLawNAdpR4dUJPAFONB8T4sGZ+FRoOqmDOTLewprQkZxCPuV8cg2WJQqwX8sszEnB6NmhvN3FQYVQVA8GyHoyedGHQa1t/yE9777WXcNbY/U/6ykx+CvBoKZdVOtGjCzqvQaDQR20wrCYZNGRUN500Y9Foq7G5VlpVZKCWVDo6edOLx+M76uxQIBM0jql3koosu4p577mHDhg3cc889DBo0iL///e+kpqbGen0dgmAFqdWiTudbOy2H3JxMbrusL79/52tKKuv55mid2tRGMRbWbD/A8onZYRvaDO2RxH1XD6SgsBStJtDMJvh8ON1KWMRpOwbVTi8rt33LkvFZGHSBZkSKLKydlqNOfpSkpstmGz7t//6dr6n3+Jnx4mccOuHkrld2NzJaFTKTLRw96WpU6rgqbxgvfXwQ36keCQ1foyQYRjIqFG9bsAfC7fU3+hylTNjjkzha56asup7yWpc6AEsgEMSGqHIaHnroIbZt28aBAwe4/vrr+dnPfsbBgwcZO3Zs2PP9fj+LFy+mpKQEnU7HY489hizLPPDAA2g0Gvr3789DDz2EVqvlueeeY/v27ej1ehYtWkR2dnaLXmB7QFGQQ3skUVPvVVv0ZiZb2HTbJUz96061Fe5TNw1Rlamy+S8o2MuT/9zHsusH07+LlbVTcyivc6v15y/tKOGecQPUoUR7Smt48p+B0cGpViNdE810sQm3a0fB4/PzflE57xeVB9qE5w5hXFZGow6Ra6flkB4fuXS34dP+xJwezDnVyyC4y2KwHAZ3c/zj34t55IbBIa2sn/vXfibm9ODRd4tYMzVHNYAbGq6RZlf4ZULWlG4LlErqtVqWXT+YOKNOLROusAfmVnj9El6/jMPtpdblpXeKVYTYOhgurx/zGQaJBc8PieZ8wdkRldFgt9txu91kZGRQXV3NW2+9xS9/+cuI53/44YcA5Ofns3PnTtVo+N3vfscll1zC0qVL2bZtG927d2fXrl28/vrrHD16lLlz51JQUNAyV9aOUBTkrDH9VKUMMKpvKmgIUdLKU11ZtVPd/JddP5ieKXHIQOmJgAJOsxlZOzUHpzeQD2E16vFJEqvyhjHn5d3sKa1h2dYiVucN42S9F61GQ/ckS9MLFZwXBG+4e0prWL39AA9el0XeX3Y2miL55pzRYfsihBvDHmwoNCWHkixz/5a9VNjd6ucEc9tlfXm/qJzfXjmAF2eMwKjXgs9NZtrpJMhIrarlBg3PZo3px/wtexnVN5Xpo3qHGCFrpuZw7KRLTY68INmM2ytRbncLWe9gmA06ej/wbtTnf//4dTFcTecmKqNhzpw5ZGRk0K1bNwA0mqafWK+88krGjBkDwJEjR0hLS2P79u2MGDECgJ/+9Kd8/PHH9OnTh8suuwyNRkP37t3x+/2cOHFCzZ/oKKRajWy4dQQaDTx10xBqnF62FR0nb2QvSiocIWGHhk91FXY3ZoMWu9uLDKz/ODCUSJZhULcEjtW6cPv8aDRQdiKQH6F4GFKsRpweP3FGHT6/cNt2FBpuuDsOVjHn8gtDNtuhPZKYNaYf9R4fFXWEVAQED70KftoPNhSaksOH3y6iwu7m+SnDeP7D/SFrC5ZlxRjOTLZQW3UMbUayel6kVtVKPo6yJsWQuSKrCxoNvHbnSI6edNEt0Uyl3c28zV+ElFD2TrPiFSEKgSBmRGU0yLLMk08+2bw31utZsGABH3zwAStXruTDDz9UjQ2r1UpdXR12u52kpCT1NcrxpowGt9tNcXFxs9bSWrhcrkZrM5nNWBJTcHoIqRHfcOsIpr+wi3SbKaSPfnAooneaFaNOg0xgrPX6jwNjj7d8fphpl/Zm375vMJnN6BIykGWNmmD5flE5EFDgSl27QQPFxcVh19jeaIk1ttWo49aST5PZzCszhiIRKB3UagmZs9BwVPSavKHEeWtwu1xYU7tyx4Y9quwp5xUUloZ4ql7aUcLLt1+CJMsgg8mgRZJlHvj5j0ixGtny+WHuGts/ZMJqw9kQvx7RC7/XHdU9rTx1XWvyhjLr5T2UVTvVuRKK8XCwvJbe6QnIMtz1yp5GbaHz7xyJ9pSsR0tb/E205SjuaGS0I4wKb8497dm7L1ZL9CXKDqebw98fPJtlnTOtJa+RZCAqo2HgwIF8+eWXIW8STSvp5cuXc99995Gbm4vb7VaPOxwOEhISsNlsOByOkOPx8fFNvqfJZGq3Al1cXByyNuWJ7lB5YIzxiknZ9Ei2IKNBOuWGLat2qi2eE8x6Xr1jJLIsc8Lhwe3zYdDpAQ1dEszMv/pHbPn8MBMuzqRrgoXMlMBnlde6Is4iUBo6dU0wk5kyqNEa2yPnwxoj0dryqXYY/XuRagA0rKyZNaYfLp9MRmo3bBpwefwhsqfkJHRPsnDC4ebxG3+M2aAj0WLg0XeLmJjTgzXbD/Bk7hC+K7ezbGuRWvL7970/sOHWEbi8fuLNBmpdgfkNL+0oYcboPqTHm+ieYsVRZY76e5EkWfVAWIw6tW12QWEpN4/qw/cVtST0SAkr735J5oLE038b0XA+y9vZ0J51aEvS3Gtsbvijrb7DtpbXqLKFdu3axbx587jmmmu45ppr+PnPf97k+W+99RZr164FwGIJlGANHjyYnTt3AvDvf/+b4cOHM2zYMP773/8iSRJHjhxBkqQOFZpQEs36psdx/zU/Is6o4+hJF79e9ynfHKtTs8GV0sjZL+/G65d47l/f4fD4efr9byk94USvBZNei1Gv5ebRffnRqSE/Cmk2k5oEGUwgW11L13iTSAzroCgypvTlWDI+i/4ZNsqqndx7ZX+W/XIwy7YW8ei7xRyosLP4zf8XUtmgyN69r39J0dFa7nplDzqtBr1Ow/1b9vJ+UTlJFgOzxvTjcFW9OmlSmWcysl86Rr0Gk0FHvcdHcpyRH3WNZ+G1AaX2xHvfsK+8joQumVTUuaPqqxDcTyHFamJgl3iG9Ejkt1cM4KUdJRgNBrSa8OWeZoNOyLpAEEOi8jS8/fbbzXrTcePGsXDhQvLy8vD5fCxatIh+/fqxZMkSnn76afr27cvVV1+NTqdj+PDhTJ48GUmSWLp06VldRHvF4/MHkh3RUHqiHotRx32n5j2Ey0hfMzUHj9/PjoNV7C+3c/cV/emaaMbtk3n03SIWX5cVdi6FVquhW4KZtdNymLnxdAhk7bQcuolmTR2a4NJFxQBYOy2Hmf/Tm18MvUBNjlwyPov5WwJj1x//R3Ej2Xt+yjAefvtr1c3/8u2XMGtMPwoKS6lxesmIN/GHd4q47+qBvLTjdN5MeryJlf/3HZsLywD49/1jQxIyAYqO1p0a9/5Zo66Q0RDc0fHRG7JPeyAatEFfN2046aL9uUAQU5o0Gv7whz+wdOlSJk+e3Cj5MT8/P+Lr4uLiePbZZxsdD9dBcu7cucydOzfa9Z5XGPU67vxZPyrq3MQZdaTajCEKPvjJcH+5HY0GFhZ8pbqL6z1+Kus8nKj38H5ROXf+tB8Woz5sNrxer2VQ14RGiWWizLJjE650saCwlKUTLuLYSVejhMIki4H3i8qpqPOElEqmWAPehDXbD7CntIZjJ12B6pupORSWVNI/wxYyLTXJYqDO5cPrl1SDITPZgu5UNVAwwdVBSpvpcDJ8JhpOwgxuCy3kXRCMKLmMHU0aDXPmzAHg6aefbpXFdDRSrUbqPT6qHB5S4oyYDaEKXimLfPzGH7NsaxEbbh2hdr5TssENeg1rth8gM9lClcNDt0RzxM+LNHZY0HEJV7o476qB+E/NdVDkTaloUP6veCUgsNkrMqgkMNY4vZRVO5m9qZDNMy/l4be/Ur0TinyumZrDym3fqu+xbvpwLMbw/ReUaZItOXZayLsgEqJEM3Y0aTRs2LAh4r/dc889Lb6YjoZWq8Gg07L7+yrGD7ng/7d33+FRlWnjx79naiaZNFLonQABDCWKCP6Uoq/ggixSlNBZKQEFRZoYRDcgSNl1BQOou8JCRBD01cUFdFH0pa1ugrIYilI0IJBOMpNk2nl+fwxzzJiAQUNC4Plcl9dlhinPmXnmzH2ect/88R/flBsWXjYkDoNOx0uD41iz5yTz+7ejbb1gdIrChUulvHB5e5vvZN6lyc2X/Er69cpuXbSXlBJkCSAiyMSFwlJt/cGcbYdZs+cky4bE8ea+06wY2lEri162wmOU1cycbYf5+/iuPL3la8CbXMlxOZnUz0cnoqze6YIFA/yLW/08iHlpcBzLdx0H/LNCSpJU+1w1aGjevHmFt/9SngbpJ9FWMwndmmnzvL4Tb0SQiVCLkdlbD7NsaByz3jnMocwC9p/K5b0pPQi3GBFC8OzvYsm1O1m//zRP3d9GpoKWyvFdceecPUWzy6uqo61mpvVpraWbjggy0SAsgAUD2qPTKX7ZFZfu9GZXnN+/HZM2pHGpxMWhzAIApvWJ4UxOcYWjE5sndsOkg/qhFr9pgbL5FzyqYOGHGRzKLJDpzCXpJnDVoGHQoEHAT2sbfGbPnn3VjJBSeT9frAbeRDXZNgeZeSU/nVRH3a7NzTYKD8RiMlA/NIAuTWTJXqnyDAYdbesG8/xDHXB7VAx6HdGXU4mfzS9m3Lovyz0mJtrK1sl3EWoxsmnCnRj1OqKCzTz59lcVLtr1CIHd4cajqggEqgoWk54wi0mbNlBVb7npeX1/GgWRfViSaq+rBg2pqamsXr2aS5cu8dFHHwHeRE+tWrWqlsbVdqoqOJ5VRFaho8J5XoE3Q6QqBFsn30W9kAA8CFRVoNMpcs5W+k0MBl2F6ZT1OqXC/giw6MOjZNscrB7RhQ0HvqffbfW1BZBlF+iGBRp44q2vyLY5tOmNlE+/Y1yP5tQNCaBZRJBfHy47CiJJUu111b14I0aMYO/evUydOpW9e/eyd+9e9u3bx/r166urfbWGqgqCIupx8VIJPxaUcC6/mIuFpUzakMYru78tV3Vy2ZA4GoQFsGTHMWZtPYwQgvOXSjmVZSfL5viFV5Ok8swBAX4lpX05EX5eatps0PFqQpdyVSOX7DjK5J4tvQsgU9OZ0qsVO/57nmVD4rQFuk+/8zWRVhNCwF+Gd+KN0fG8ue80+XZvUqdZWw/zfW5xpcpyS5JU+1QqT8OIESNYunQp3333Hc2aNWPKlCl+6Z9vZaoqKChxcr6glL/s/s6v0uAnT99bYea9uiEBPLX5K5YP7cifHukIgMujkm93yToRUqWol3dH+LYbhluMFBvDGJ2yz68AVEyUlW+zbX4LE9eOiifAqPNb1Lh813EOZRaQ2LMVa0fFE2YxotcpDOrSkKU7j5P62J24VcEPucU89/43ZNscpIzoQnigkSd6xwBQfDnTZKBJX2U7JCRJurFUKuvPs88+S7169Xjqqado2LAhc+fOvd7tqhV8KXy/zrzEpI1pDI5v7Je+16D/KWtd2cx7qhBEBZv4LtvGqL9+4c3rb9BT7PRQ7PRg0MtkTNKV+frdoJR99HjpUwal7OPHSyVavQZAy4mQZXP4lZr2VaW0mg0kb8/gkdcOMmlDmramJtRi1G4f/vpBrGYDUcEmnG6VMX/7gnHrvuRQZgFn80uYkpqOKiDH5sRiMmjbOYud3oDBLQtHSdJNp1K/Tvn5+YwePZrY2FjGjBlDYWHh9W5XreBL4Rto0nM2v4QGYT/NEz//UDuMeoW1I+MrHAae2y+WNXtOavUh9DqFOkFGGtexEC2z2klX4et3ZQOBrCJHhUmVXB61wtsLSlysHeXfN9dcLrU+v387OjcO06Yp5j3YThtF+PnzqEIQaTWh13mTSi0bEkd4kJEX/vENxy4WycBBkm4ylZqecDgcZGdnExUVRXZ2NqoqTwTwUwrfghIX/9MummCzgUbhFqKsZsKDTGQXOVn1ybd+parX7DnJRxlZJPZspV3d6XUKRp1CvZAAIoJknQjp6sqmjvb5eUlp8AYCvpokP7+9xOmhSUQgfx/flaJSNyEWA4v/eZSPMrL8ciscyiygyOEmLNBY4fOcySmmcZ1ATHod8/u3R0GQeXlr8eTLiaEqWowpSVLtVKmg4cknn2T48OFYLBZKSkpITk6+3u26ofnmk+HyFdqek6wY1pEXL1caDLMYUVCYkpperlT1/P7t2H8ql6wih3Z1pyVhbE0AACAASURBVOjgs+NZdGsZKQMG6RddKXX0mpFdmLwx3W9bZM7l3Q2+sum+RbgNwy04XSqj//YFSx6+jalvpfuNXMzZdpg3x97BpRIXFqOef5/MYc3IeCaXKe/uCyxefrQTmfkl6BWFoWsP+P2bXJ8jSTeXSgUNLpcLIQRCCBRFuaWTO/nmkyf8/T9EWc1alj3gckVAE2O6N6Oo1FXhcG69kABeTeiCToHkgR2Itpr4539/pGlksFzLIFVKuMVY7gd8Wp/WRBgdWlIlRVFYv+8Uw7o2ZcH73/gtely68zjPDWhH6OV6EPVCAyrsq5dKXAxZc0ALQOqFmP2SQi3f5U0KdexCEcnbM1gzMp7OjcM4lFnAnG2HSR7YAZ1OqVRlS0mSaodKBQ2rVq3inXfeoU6dOmRnZzN16lS2bNlyvdt2w1FVwYXCUm0++Wx+Ce+ln+Px3jF8n+vNmtenXV1OZRfSpWlEhcO5dYJMTNt0SNvf7vCoPL/9GJ/O7CnXMkiVklfi1DI9+gKBV3afIKlvK+oGmci1O3F7PIy9uwVOt6ptl/TxLXjMuzyloVcqztsQajGyeWI37fmn9GxFpNVEYmp6udGGs/klTN6YxsuPdGLImgOczS+hWWQgG/afZnT35gRF1NPyj0iSVHtVKmgICgqiTp06AERFRWGx3HpzlL4RBrvD7XdyfahTA6akphNlNfPS4Dhi6gaRVejkhQrqTLw0OA6BYG6/tn5XfI3CLQSZ9HJqQvpFqioodnhrQfimvXzm92/H0fOF/GX3CcZ0b47TrbLpi+95NaGLNv1QdjFuYs+WrBjakRybk9Uj40ksM3KRMqILy3Yd81vjUMdq4uIlB8kDO9AiKohjF4q0dQ/gHZ2IvBz4Ngq3kGtzsvb/ztA7th5Pv/P1ryqLLUnSjeWqQYOvuqXH42HSpEnEx8dz+PBhTKZbL3d8jt27dW1+/3baYsdnfxdLVLBZG3VIP5NH04hAbdj453Umlu06xuD4xn75+wuKXawdGa+dbCXpanLtTk7n2CscGVAUhUkb05jfvx1zth1mxdCOfJSRxYz7W1eYk2FOv1i2fPE9I+5qhkmvY9XwzoQHmdDrFP74j2+0oMS3xmHThG6oQjBu3Zf83+xeJG/PKNcGX7bJlwbHsejDo1qFy99aFluSpBtDpQpWlS1c1adPn+vbohuML3mTb4RhzZ6TrErojMut8uTmr7Qg4mx+CX1vq4/T/dMWt7J1JrZOvovHe8ew6pNvAe8Jdu3IeEIsBixGvbz6kq7Kt/i2xOnWMoz+vBbEpcs/zmGX1yr4dvWYDfoKf+CzixwkdGuGDnC4VYLMBrKLHIQHmcqNYvi2VzYMt7BnVk90Cmz4wx2M+uuXfgssTXpvMSzfeoeyFS6rsiy2JEk1o1IFq25FvmAhz+7EZNBh0On414x7uXCpBLdH8NSWr7UgwncC118uhV3RVWDDMAvr9p1icHxjJt7TkqhgM6UuN8nbM1g0SJa7lsrzBQqqqpJjdzJpQxpvjr2DqGATQgjWjbuDAIMOlyrQKwoOt8r/tIvWkiz5dvUs3nG04oJTqooqBIs+PMrsvrHodYp3PYQqKuzD+suBrdmgI7vIQaBJz7pxd5Brc1Ls9BAVbKZOoIkODUP5y/DOnMyy+U1fyLLYklT7VWpNw7VwuVzMmzePc+fO4XQ6SUxMpEGDBixYsAC9Xk+zZs1YtGgROp2OLVu28Pbbb2MwGEhMTKRXr15V3ZxrVjYtNIDJoHAuv4RZWw8TZTUzrU8MjeqY/UYTfCmiA0167A53uS1ua0bGE2hSGN29OW5VIAS8+sl37D+VK0sFS34qChTm92/HtrRM5vdvR3CAnul9WjNpYxpRVjOz+7Yp19cirEbentgNl0dFpyh8lJGlTZX5pigUBXSKQk6Rk8HxjSlxugkLNLEtLZMpvVrx52EdtcDYN4rwxFveBbxrR8YTHWwi1+YkKjgAk16nVdE0GHREGfWoqrcCZvblOiqyLLYk3RyqPGj44IMPCAsLY9myZeTn5zNo0CDat2/P1KlTuffee3n66afZs2cPt912Gxs2bGDbtm04HA4SEhLo0aNHja6X8C12vHCplE1ffE9S/3aczLIz//0jdG8RwYhuTXn102+Z9UBbvyuxQ5kFJG/PYOvkuxjz5pdEWc1+FQGtZj02h0pUkAmDQU+u3cn0+2KYZWgrSwVLmrLbeef3b6dNKTQIDWBM9+as33+amOhYJl1eMzO/fzstYADv8P8/vjrLgE6NtHU1b469g0bhFr+pMl++kOTtGbz8SCcigkz8eKmUPceyeKJ3a1Z+coJxPZqz4Q9d0SkKp7LtLN3504jBpI1pbJ7YjXphAZQ4VZpEBJU7Fp1OoU3dYG0LqMfloFGkXAQpSbVdlS/X79u3L9OnT9f+1uv1xMbGUlBQgBACu92OwWDg8OHDdO7cGZPJRHBwME2aNOHYsWNV3ZxKK7udMtJqYtYDbXG6BYEmPVFWM5N7tuTVT79lTPfmLNt1rFzVyg1/uIMSlzdTn+8E/chrBxm37ksURcGtCkwmg1YquGF4IFHBZnkSlYDy23l96xIAAox65mw7zOD4xuTZndrtZe8D0LlxGI90baoFDAA7/nuelBH+FS1TRnRhd8ZFzuaXEB74U6bSFf/6lg0HzjC7byz1wyx4VLSFj76AAbzByflLpfxY4MBivPIppGxft+dekH1dkm4CVT7SEBTkveqw2WxMmzaNJ598EkVR+OMf/8jq1asJDg7mzjvvZOfOnQQHB/s9zmaz/eLzOxwOjh49WqVtNgcEUGwMo9QtiLKaUQVcKnEREWSi2OlhWp8Y8uxOv4JUP98ZYdDp+S7LdsW5YAWqvN2/Rmlp6Q3RjqupijbGxsZWUWuuza/pn2X7n6/v+NYlnM0vofTy4towi9EvXXTZ+wBM7tnSL6gA6NOurpbK3Dc1seqTb3mmXyz9bqtPoFmPy6Nq0wj7T+UysHND1u8/zZjuzbXdED/v07l2J8nbM9g8sVuljvdG7nc10baa6p9QuT5ak+2rLWqqP1dXf71SH6jyoAHg/PnzTJ06lYSEBAYMGMBdd91FamoqMTExpKamsmTJEu6++27sdrv2GLvd7hdEXInZbK7yDp1d5GB0yj7vVrV+bZn6Vjrz+7dDCKgTZMQaYOS7LBsRQaYKd0a8P7UHJoPuiqvajTqFsAAjDW+AL+LRo0dv+BNCbWjjlfya/lm2//l+oMsusA006bWti9vSMrXb1+w56bd+JuJyYqeyP/JhFmOFOR3+cHcL5r9/hLWj4mkTHeyXSVJRYMGA9uh0CiaDt+japArSR5/NL8Gtikod7438md7Ibbsersc59FZUU+9hTffXKg8acnJyGD9+PM899xx33XUXAKGhoVitVgCio6NJT08nLi6Ol19+GYfDgdPp5OTJk7Ru3bqqm/OLVFVQ4vJup9ydcZHEXi21k/aCh9oBoFO8uf3n9out8Kor0updh5Ftc2iLIn3rGaKsJkLNRszm6xKfSTcBXwGqsoHCocwC1u8/zaYJd6Io8NLgOO3qf/3+09ooV/3QALZM6kZmXgmhFiOvfX7SL3AtdnqumJl0xdCOZBU6qB8acNXcCVaDgc0Tu3H+Uim5dqe2I6JRuAWDnHKQpFtKlf+SrVmzhsLCQlJSUkhJSQFg4cKFPPXUUxgMBoxGI8nJyURFRTFq1CgSEhIQQvDUU09hNldv0peyCx99KaDP5BRrC8de+CCD2X3bEGE1Ma1PazZXkF1vxdCOGHQKdQJNWla9SRvSaBRuYfXIeELNRgICZMAgXZnRoNP6nC/o9AUEp3PsuDyCTV98z+D4xoQEGJj1QFuKnR4CTXoef+sQT/9Pa+a++1+6t4jQcoH4nqNBWABrR8UzaUOa3+iX2agjKtg7FWdzuAmzXHlBrtlsIEJAXrFLW5zp698y9bkk3Vqq/NcsKSmJpKSkcre//fbb5W4bNmwYw4YNq+omVFqu3akVnlqV0Bmr2cisd772u9qbtfUwa0bGUyfIwNA7mmI2KGya0A3P5SI8docbnU6H0agn0uhg88RuuFWBQacQbTVjNMp96dLVGXSKNs3g24mzbEgcRr2O4AAjz3/wDTMfaFNu2mvrf37gUGYBKz46wYqhHSl2evjw63PMeqAtep2CRxWs33eahG7NmN+/HTHRVkwGHSD49qKdV3Z/S7bNQcqILoQEOAkLvHIAEBBgoG20VfZvSbrF3dKXwL5h4SirGYdLJd9eXOEUQ4TVuyAyM69YO9EuGxKHQaejfmiAtve8IDeX2NjoGj4qqbYpcXpYuvN4uUqUqxI6E2k1VdgnS5weftexIadzi/koI4u/7j3F8w+1x2TQMW7dl37rD0qcbtLP5NK2XjAXLk8xbEvLZOYDbVi+6zhTUtPZPLEbYYFXb6fRqKdh+C/cSZKkm9otGTSoqiDH7kDgnd+d3LMlT7/ztVZ0as62w9oUw9qR8SgIsgq9uRt8J9pZWw+zYXxXVGTlPum3MRn0FVaiBAgy67SFiL4++dLgOF7851GybQ7eHHsHf7i7BcVOD3pFQa9TWDfuDvSKwoXCUvYcu8iYHi1I6NYMVQhcHpVtaZna2ojJPVsyaUMablm+WpKkSrjlggZVFRy/UMSEDd5piWVD4gg0GbSiU2Wv6BqGW/jXN+fp0iyCOkFGpvRqRcqn32knWlVAkByelX6jcIuRNSPjtfwKjcItrB7Rhcw8O/XDAkGBTRO68WNBiV/BKQBFgaM/FnBf+/qUulUahlkodbk5k1dC3VAzY3o058eCEm10YVyP5lo/HhzfmDCLkUbhFox6WWFVkqRfdssFDTk2BxM2/EcLEt5LP8fU3q20Fea+rZSNwi38fXxXusdEse0/mTzStSmFJR6/E63JoCMySC4Ek36bvGInr+w+4Tc9sfKTb3luQHtcHpXCEhdFpW5mvvN1uV0QmXklxDeP1KpS+pI3HTyZTc+2dbGXehi69oA2QvHmvtMM79qUwfGNiQgyUVTqZo1c0ChJUiXdUpcXpaVuLWujT592dVn0YUa5DI8pI7qwZMdRzuWXMuT2JuTZnURaTVrCp7Wj4qkfEiCnJqTfxOn09smPMrK0LKKTNqTxUUYWTrfK4n96k7iEBRr487COfn30pcFxvLL7WxI3ppHUvz3/eLwH8/u3Y9Un3zLk9ibM2npY2w7sK289OL4xgSY9EUEmooLNtG8QQtu6wRgMt9SpQJKkX+mWGGlQVUGJ08GpXAc5RQ6/fesNwiwVFvSpE2Qku8hJoEmvVf8LD/SeaFtEBV11i5okXY2vKJqqCs4Xlu+T4A0KdIqiTSUM79qUAKPuitMUHlUQZDaQfiaXMd2bE2DUcTa/BI/4aa2CLwFUUambFlFB1LOaZf4QSZKuyU1/eeF2q1wsKqGgRMXh8lAnyKjl4u/cOIyQAINfQZ9HXjtI8vYMXB7BtD4xFDs9GPU6tqVlYjLoaBhqoU6QrBkh/Tput8qpHBvHLxRRWOomcWMaO/57nlcT/OtDrBkZj04HVrORcT2aE2jSY9TrUBR4+p2vmbQhza/ktBCCJTuO8mCcNwW0wJv++cKlUu21fUmdGtexYDIo5BQ7a+Q9kCSp9rqpgwa3WyXLVkquzcUjrx1k0YdHKXZ6tOQ3f3qk4xWnJow6haYRgTQKt7A74zzT72uNxaiTw7jSr6aqgh8vlZCZ5y21rlMUoqxmBnZuyKufevvk+1N7kPrYnbyy+wT3LN3D2De/wGo2eO8bbMaggzUj48tNUyzZcZT5/dsTZDYwtVcrbKUuVo/owt8PnNHut2ZkPNYAA/l2F7ZSj9wxIUnSNbtpxybdbpVzl0pQheCV3SdYNiSORuGBDH/9IGfzS/goI4sd0/5fhVMTFpMeh1sQYNRh1Cvc374+J7MKiQ4OqOnDkmqxHLuDrCIHgSY9Z/NL0OsUpvWJ0ZI2fZSRxcY/dNUyjoJ3SiExNZ1NE7pRWOIiX1WxGPV+/dU3TTG7b1sKil1EBZuxGHX89f9OMbtvLHP6xXK+oIRXdp9g3oPtCA00sPU/PzC6e/MafkckSaptbsqgwXdFl13kIDrEzPT7WlNY4uJiYal2Mu7cOIxAs95vagK8V2S+jI/FTjdmo54z2UVEBlu0JE6S9GuUujzk2p2Y9N600Xl2B80iA7U++fR9MTQKD/Rb2wDewEEVggCTnjomI6qKls7Zx7eTYty6L7VRhaF3NCHf7tRyOqwdFY/JoLDp35kM6NRI7piQJOma3ZRj7Tk27xVdrt2JXlHIKnQwa+thrQIgeMsIVzQ18WpCF/Q6CDLrCQkwYtQpxNQNpXV0sFzHIP0mOkVhW1om4UFGlg2J49VPv9NKTw+Lb8RDnRviVoXWH30ahVtwulX6rPiMMznF/FhQyuoR/msglg3x7qQAb5AxeWMaQWYDDcMC+MujndgysRsRQSbcHsGYHi1oHRUkU0BLknTNbrqRBrdbpeTyFd35fDtt6wVrw8Flqwj6Sgb/fGrCoFcA739uVcVk8G5PkwGD9FsZdArjejQn5dPvGNejOc88GEuAwZvx0WLSk13kwGzQlSuv/tLgOEpdHgCW7jzOCwPbs/Lyupy29YJRhWDG5q+1hZFweXRCFTQMD0RVBbl2J063B4vJIPuzJEm/2k0XNGTZHKhCsC0tk/n92wNo5YHLVhGMDjFXODWR+tidRFvNcsGjVOUUINCkZ3jXpugUhTM5xdQJMlI3xIzDLbSpi01ffO8XyK7f703IBN7y6+GBRpJ+146sIgcFxU7CAr31Kcoqm+VRp1OuWvpakiSpsm66X0aXR+XCpVLG9WiOKgSqENS5PBzsCxKSt2fgUYW29RLQ6kw0CAmQAYN0XRiv0K9O5xRj0P00dTGuR3OSt2do23+n92lNl6ah7JvTi/em9KBhWCCNwgOpFxpAkNmAy6OW21GxZmQ8MjO0JElV7aYbaTDoFN7cd5pnHmwLwFsHzzD49sY43cJbYEp4T97vp5/lk+PZfnUm9DrkPK903YRZTOSZneTZXdptAnhz32leHHQbT/RpzcrdJxjXozkb/tAVnaJgK3VfrrBaWi5zo0mv48KlUoasOUDnxmF+oxOKAiUutQaOUpKkm9lNFTS43SpGvcLjvWMQQmHRPzMY07052/6TyZDbmyAAs1HHoe9zWfEv76IxX52JTRO6odfJSzPp+vFOE5gw6nVkFzlwelRSPv2Ox3vHUFDiIsJqZH5/b70Jt0ew9T/fc0+buizfdZxsm4Mtk+6iQdhPiyQjrWZKXZ4Kp9nm929HsMz2KElSFbtpfiV92yyT/vcIJoO3RPBHGVks33WcLs0iyLM7+TbLhk6ByGBLuZXnBr0ii09J112w2YROgbBAEzHRVmb3jcVkUJj1zmGef/8bDHoFk0FHnt1Jl2YRWg6Gs/kluD0qapmETDqdQoNQC2tHlU/2tC0tkwA5aiZJUhWr8ksRl8vFvHnzOHfuHE6nk8TERDp16kRSUhKFhYV4PB6WLl1KkyZN2LJlC2+//TYGg4HExER69er1q1831+4kq8ih7YhYmdC5wiuwdybdRd2QAJIHdiDQpKfY6SEq2EyUTA0tVQOdTqFhWCDnL3mrrBaUuFiz56S282HiPSXUDQng6QoqWp7MtmN3emhT96ftvwaDjjbRwbz12J3aNuP1+0/z1H1tiJR5GCSpVip1ea4Y9MfGxl7T/atalQcNH3zwAWFhYSxbtoz8/HwGDRpEt27dGDBgAA8++CAHDx7k1KlTWCwWNmzYwLZt23A4HCQkJNCjRw9Mpl+XQMnp9mh5GA5lFpBdVMqyIXHM2vrT1rVlQ+IwGRXqhgQRHGDE6fbILZVStdPpFEwGfYWBQa7dSajFwOqR8SRuTPPbdumbpnhvSg+/3RAGg45G4YHgcVI/NIQuTeJkn5akWizAqKfZ3A8rff8zS353HVvjr8qnJ/r27cv06dO1v/V6Penp6Vy8eJGxY8fyj3/8g65du3L48GE6d+6MyWQiODiYJk2acOzYsV/9uiaDnm1pmVqyJqdbsHSnd3vl5ondmN+/HUt3HqfUqWpb0BqGBxIVLEcYpOoXEWS64rTC2fxSVFVl04RuWt8tO03hdHvKPZ9Op2DPvSD7tCRJ11WVjzQEBQUBYLPZmDZtGk8++SRz584lJCSEdevWsWrVKl5//XWaNWtGcHCw3+NsNtuvft2IIBPT72vNX/51QsvDkG1zaFMT4D0xmwxynleqeTqdUuG0wrgezbGY9Dz/QQbT+sQw//0j5UYjZB+WJKmmXJfl1efPn2fq1KkkJCQwYMAAlixZQu/evQHo3bs3f/7zn+nQoQN2u117jN1u9wsirsThcHD06NEK/y2qbl2S+rfH5VYx6hRWj+hCYmq6NsS7ZkRninJ+JOdsaYWP/61KS0uv2LYbxa3Sxorm/arD1fpnRcwBAdQNrkNUcDDz+7fnwqVSXvggg2ybg4bhAawZGc/kMtMUV+vDN/JnK9vmr6b6J1Suj9Zk+2qDa11DYC9x8MOZU5W+/7W+/9ejPVdqQ5UHDTk5OYwfP57nnnuOu+66C4D4+Hg+++wzfv/73/Pll1/SqlUr4uLiePnll3E4HDidTk6ePEnr1q1/8fnNZvNV31CXy0OWzYFbFUQHm9k6+S48qiizdiG8yo71544ePXrDf9lkG6+vX+qfV+N2q+h1Ci8/2gmDTiHAqCPEbOS9KT1+tv6m4j58I79vsm03jt/SRyWvX7Pm4Hq+59XZnioPGtasWUNhYSEpKSmkpKQAsGTJEpKSknj77bexWq2sWLGC0NBQRo0aRUJCAkIInnrqKczm377a22jU0zA88Dc/jyRVN4NB55eHwSdKbp2UJOkGUeVBQ1JSEklJSeVuf/PNN8vdNmzYMIYNG1bVTZAkSZKkG0Z1bom83mTKOEmSJEm6jm7kLZTX6qbJCClJkiRJ0vUlgwZJkiRJkipFBg2SJEmSJFWKIoQQv3y3G8dXX31VJbsspJubwWAgJiam2l9X9k+pMmqqf4Lso1LlXKmP1rqgQZIkSZKkmiGnJyRJkiRJqhQZNEiSJEmSVCkyaJAkSZIkqVJk0CBJkiRJUqXIoEGSJEmSpEqRaaSvgcvlYt68eZw7dw6n00liYiLbt28nJycHgHPnztGxY0f+/Oc/M3nyZAoKCjAajZjNZt54441qaaPH4yEpKYnTp0+j1+tZvHgxQgjmzp2LoijExMSwYMECdDodq1atYs+ePRgMBubNm0dcXFyNtdFut5OcnIxer8dkMvHSSy8RGRnJwoULSU9PJygoCICUlJRKlVC/GVXU/zp16kRSUhKFhYV4PB6WLl1KkyZN2LJlC2+//TYGg4HExER69epV7W1r0KABCxYsQK/X06xZMxYtWoROp6v2tkHt+F5IV3erfIYVHWdRURGTJ0+mWbNmAAwfPpwHH3ywZo5TSJW2detWsXDhQiGEEHl5eeLee+/V/q2goEA89NBD4uLFi0IIIfr16ydUVa32Nn788cdi7ty5QgghDh48KCZPniwmTZokDh48KIQQYv78+eKjjz4SR44cEaNGjRKqqopz586Jhx9+uEbbOGLECJGRkSGEEGLTpk3ixRdfFEII8eijj4rc3Nxqa9uNrKL+N2fOHPHhhx8KIYQ4cOCA+PTTT0VWVpbo37+/cDgcorCwUPv/6m7blClTxJ49e4QQQsyYMUPs3r27RtomRO34XkhXd6t8hhUd55YtW8Rf//pXv/vV1HHKkYZr0LdvXx544AHtb73+p6plK1euZOTIkURHR5OTk0NhYSGTJ0+msLCQiRMnVsvVFMB9991Hz549Afjxxx+JjIxkz549dO3aFYB77rmHffv20bx5c+6++24URaFBgwZ4PB7y8vKoU6dOjbTxhRdeIDo6GvBG2mazGVVV+f7773nuuefIyclhyJAhDBky5Lq370ZVUf9LT0+nTZs2jB07loYNG/Lss89y4MABOnfujMlkwmQy0aRJE44dO3Zdr0IqaltsbCwFBQUIIbDb7RgMBg4fPlztbYPa8b2Qru5W+QwrOs4jR45w+vRpdu/eTdOmTZk3bx5paWk1cpxyTcM1CAoKwmq1YrPZmDZtGk8++SQAubm5HDhwgIcffhjwDtWOHz+eV199lVWrVrF48WJyc3OrrZ0Gg4E5c+aQnJzMAw88gBACRVG0YygqKsJms2G1Wv2OraioqMba6AsY0tPT2bhxI2PHjqW4uJiRI0eybNky3njjDd566y2OHTtWbW280VTU/86dO0dISAjr1q2jfv36vP7669hsNr8pnKCgIGw2W7W3zTcl0a9fP3Jzc7nzzjtrpG0+teF7IV3drfIZ/vw44+LimD17NqmpqTRu3JhXX321xo5TBg3X6Pz584wePZqBAwcyYMAAAHbu3En//v21kYfIyEgeffRRDAYDERERxMbGcvr06Wpt50svvcSuXbuYP38+DodDu91utxMSEoLVasVut/vdXt1rBcq2sbi4mH/+858sWLCA1157jTp16mCxWBg9ejQWiwWr1Uq3bt1u6aAByve/sLAwevfuDUDv3r05cuRIjX22P2/bokWLSE1NZefOnfz+979nyZIlNd7vasP3Qrq6W+UzLHucd999Nx06dADg/vvvJyMjo8aOUwYN1yAnJ4fx48cza9Ysv2HyAwcOcM8992h/79+/XxuFsNvtfPvtt7Ro0aJa2vi///u/rF27FgCLxYKiKHTo0IF///vfAHz++efcfvvtdOnShb1796KqKj/++COqqlbb8F1Fbfz444/ZuHEjGzZsoHHjxgCcOXOGhIQEPB4PLpeL9PR02rdvXy1tvBFV1P/i4+P57LPPAPjyyy9p1aoVcXFxpKWl4XA4KCoq4uTJk7Ru3bra2xYaGqpdCUVHR1NYWFgjbYPa8b2Qru5W+QwrOs7HH3+cw4cPA97fm/btkUmcVAAACFtJREFU29fYccraE9dg4cKF7Nixwy8AeP311xk8eDCbNm0iJCREu33RokV8/fXX6HQ6HnvsMe67775qaWNxcTHPPPMMOTk5uN1uJkyYQMuWLZk/fz4ul4sWLVqwcOFC9Ho9K1eu5PPPP0dVVZ555hluv/32GmvjvHnzqF+/vvYe3nHHHUybNo3XX3+dnTt3YjQaGThwIMOHD6+WNt6IKup/S5YsISkpiZKSEqxWKytWrCA0NJQtW7awefNmhBBMmjTJb71BdbVt+vTpLF++HIPBgNFoJDk5mUaNGlV726B2fC+kq7tVPsOKjrN+/fokJydjNBqJjIwkOTkZq9VaI8cpgwZJkiRJkipFTk9IkiRJklQpMmiQJEmSJKlSZNAgSZIkSVKlyKBBkiRJkqRKkUGDJEmSJEmVIoOGKvTuu++yfPnySt1348aNfo/Jzs7m+eefv46tk25FtalPnj17lmHDhlXb60k1qzb1TeknMmioIatXr/b7OyoqSn4JpBol+6R0o5J988YhC1ZVsa+++ooxY8Zgs9l44oknMBqNvPzyy5jNZsLCwnjxxRdJTU3l0qVLPP/881qhnrNnzzJjxgy2bNnCgAED6Nq1K8ePH0dRFFJSUrBarbzwwgscOXKEyMhIzp07x+rVq9Hr9Vo6VbPZTHJyMh6Ph8TERMLCwrjnnnuYMGFChW1dsWIFR44cwW6307JlSxYvXszDDz/MK6+8QqNGjdixYwdpaWlMmTKFmTNn4nQ6ad68OQcPHuTjjz+uzrdV+g1qU5/02bdvX7k2zp07l8TERG677TYeeOABZs6cyf3338/48eNZvHgx6enprFu3Dp1OR3x8PDNnzmTlypUcOnSI4uJiFi1aRMuWLavjLZcqqbb0zbKvBzBs2DD+9Kc/8d5773Hq1Clyc3MpLCwkKSmJ22+/nT59+tCxY0d++OEHYmJiWLRoEXa7nWeffZb8/HwAkpKSaNOmDb169aJFixa0aNGCZ599tvre/F+rWmpp3iK2bdsmHnvsMaGqqsjJyRG9evUSvXr1EhcuXBBCCLFu3TqxZMkSIYQQ3bt31x6zbNkykZmZKYYOHSqEEKJXr14iLS1NCOEtKbx9+3bx8ccfi+nTpwshhMjNzRXx8fEiMzNTTJ8+XSs/vH//fjFjxgyRmZkp7rzzzquWHC4qKhKvvfaaEEIIj8cj+vbtKy5cuCBSU1PFypUrhRBCTJgwQRw/flwsWrRIbNy4UQghxN69e0WvXr2q9H2Trp/a1Cd9r6eqaoVtfO+998SqVavEDz/8IAYMGCAWLFggCgsLRUJCgsjPzxf9+vUTxcXFQgghZs6cKfbu3SteeeUVkZycXNVvq1QFamPf9Bk6dKjIzMwUr7zyilbG+sSJE2LAgAFCCCHat28vzpw5I4QQYtq0aWLXrl1i6dKlIjU1VQghxOnTp8Wjjz4qhBCiTZs2Ii8v77e+ndVGjjRUsfj4eBRFISIiAovFAkDdunUBb2rkP/3pT5V6nnbt2gFQv359HA4H586do1OnTgDUqVNHS9d74sQJ1q5dyxtvvIEQAqPRCECjRo0wmUxXfH6z2UxeXh4zZswgMDCQ4uJiXC4XDz30EMOHD2fo0KHYbDZat27NyZMnGTRoEECtSscqedWWPumTn5+P1Wot18bJkyczZcoUwsPDmTBhAm+++Saff/45vXr14ocffiAvL4+JEycC3povmZmZADRv3rxSxydVv9rWN31EmUTK3bp1AyAmJoacnBytHU2bNgWgc+fOnD59mhMnTnDw4EF27NgBQGFhIQDh4eGEh4dX+rVrmgwaqth///tfALKzs3E4HKiqSlZWFtHR0XzxxRc0a9YM8O90FfGVe/WJiYnh/fffB+DSpUucOXMGgBYtWjB+/Hi6dOnCyZMn+fLLLwHQ6a6+XOXzzz/n/PnzvPzyy+Tl5fHxxx8jhMBqtdKhQwdtqgKgdevWHDp0iNjYWL766qtrej+kmldb+qRPeHg4NputXBtDQ0MJCAhgx44drFy5kl27drF+/XqWL1+O1Wqlfv36/O1vf8NoNPLuu+8SGxvLv/71r0q/rlT9akvfNJvN5Obm4vF4sNvtnD17Vvu3b775hoEDB3LixAkt4Ll48SLZ2dlERUWRnp7OwIEDycvL46GHHmLAgAHk5ubyzjvvVOq1bzQyaKhipaWljB49muLiYpKTkxFC8MQTT6AoCqGhoSxevBiAli1bMnPmTLp3716p5+3Zsyeff/45jz76KJGRkQQEBGA0GpkzZw7PP/88DoeD0tLSSs+JxcXFkZKSwrBhwzCZTDRu3JisrCwaN27M0KFDeeyxx3jxxRcBmDBhArNnz2bHjh1ER0djMMhuU5vUlj7poygKCxcurLCNffr04d133yUsLIy7776bt956iyZNmgAwduxYRo0ahcfjoWHDhvTr1++aXleqfrWlb0ZFRdGjRw+GDBlCkyZNtFEEgKNHjzJmzBhKSkpITk4GwGQykZyczPnz5+nYsSO9e/emS5cuPPvss2zZsgWbzcbjjz9+je/WjUEWrKolTp48ybFjx/jd735Hfn4+/fv359NPP72mIbVf67PPPiM8PJy4uDj279/PmjVr+Pvf/37dX1e6sdVkn5Skq6muvrly5UoiIyPLVd/t0aMH+/btq9LXulHIS8Zaon79+ixfvpz169fj8XiYOXNmpb4AmzdvZvv27eVunzFjBp07d67Uazdq1Ih58+ah1+tRVbV2rPCVrrua7JOSdDWyb14/cqRBkiRJkqRKqV0rMCRJkiRJqjEyaJAkSZIkqVJk0CBJkiRJUqXIoEGSJEmSpEqRQYMkSZIkSZUigwZJkiRJkirl/wNwthLwRe4iqAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(stock_df[[\"botlinger_avg\",\"botlinger_lower\",\"botlinger_upper\",\"call\"]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trade call Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import metrics\n",
    "\n",
    "X = stock_df[[\"botlinger_avg\",\"botlinger_lower\",\"botlinger_upper\"]]\n",
    "Y = stock_df.call.astype('category')\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split( X, Y, test_size = 0.3, random_state = 42 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Acc: 49.112426035502956 %\n",
      "Test Acc: 42.758620689655174 %\n"
     ]
    }
   ],
   "source": [
    "# Logistics regression\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "log_reg = LogisticRegression(multi_class='auto', solver=\"lbfgs\")\n",
    "log_reg.fit(X_train, y_train)\n",
    "\n",
    "print(\"Training Acc:\",log_reg.score(X_train, y_train)*100,\"%\")\n",
    "print(\"Test Acc:\",log_reg.score(X_test, y_test)*100,\"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Acc: 100.0 %\n",
      "Test Acc: 55.172413793103445 %\n"
     ]
    }
   ],
   "source": [
    "# Decision Tree\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "clf = DecisionTreeClassifier()\n",
    "clf.fit(X_train, y_train)\n",
    "\n",
    "print(\"Training Acc:\",clf.score(X_train, y_train)*100,\"%\")\n",
    "print(\"Test Acc:\",clf.score(X_test, y_test)*100,\"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Acc: 66.5680473372781 %\n",
      "Test Acc: 57.24137931034483 %\n"
     ]
    }
   ],
   "source": [
    "# K - Nearest Neighbours\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "knn = KNeighborsClassifier()\n",
    "knn.fit(X_train, y_train)\n",
    "\n",
    "print(\"Training Acc:\", knn.score(X_train, y_train)*100,\"%\")\n",
    "print(\"Test Acc:\", knn.score(X_test, y_test)*100,\"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Acc: 78.10650887573965 %\n",
      "Test Acc: 56.55172413793104 %\n"
     ]
    }
   ],
   "source": [
    "# Support-Vector Machines\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "svm = SVC(gamma=\"auto\")\n",
    "svm.fit(X_train, y_train)\n",
    "\n",
    "print(\"Training Acc:\", svm.score(X_train, y_train)*100,\"%\")\n",
    "print(\"Test Acc:\", svm.score(X_test, y_test)*100,\"%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction for stock2 using Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "stock2_df = pd.read_csv(\"RELIANCE.csv\")\n",
    "\n",
    "stock2_df['Date'] = pd.to_datetime(stock2_df['Date'])\n",
    "stock2_df[\"botlinger_avg\"] = stock2_df[\"Close Price\"].rolling(window=14).mean()\n",
    "stock2_df[\"botlinger_upper\"] = stock2_df[\"Close Price\"].rolling(window=14).mean() + 2*stock2_df[\"Close Price\"].rolling(window=14).std()\n",
    "stock2_df[\"botlinger_lower\"] = stock2_df[\"Close Price\"].rolling(window=14).mean() - 2*stock2_df[\"Close Price\"].rolling(window=14).std()\n",
    "\n",
    "stock2_df = stock2_df[stock2_df[\"botlinger_avg\"].isnull()==False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,4))\n",
    "sns.set_style(\"whitegrid\")\n",
    "sns.lineplot(x=\"Date\", y=\"Close Price\", data=stock2_df,color=\"black\")\n",
    "sns.lineplot(x=\"Date\", y=\"botlinger_avg\", data=stock2_df)\n",
    "sns.lineplot(x=\"Date\", y=\"botlinger_upper\", data=stock2_df)\n",
    "sns.lineplot(x=\"Date\", y=\"botlinger_lower\", data=stock2_df)\n",
    "plt.legend(labels=[\"Stock\",\"Botlinger Avg\",\"Botlinger Upper\",\"Botlinger Lower\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Series</th>\n",
       "      <th>Date</th>\n",
       "      <th>Prev Close</th>\n",
       "      <th>Open Price</th>\n",
       "      <th>High Price</th>\n",
       "      <th>Low Price</th>\n",
       "      <th>Last Price</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Average Price</th>\n",
       "      <th>Total Traded Quantity</th>\n",
       "      <th>Turnover</th>\n",
       "      <th>No. of Trades</th>\n",
       "      <th>Deliverable Qty</th>\n",
       "      <th>% Dly Qt to Traded Qty</th>\n",
       "      <th>botlinger_avg</th>\n",
       "      <th>botlinger_upper</th>\n",
       "      <th>botlinger_lower</th>\n",
       "      <th>call</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>2017-06-01</td>\n",
       "      <td>1340.70</td>\n",
       "      <td>1332.70</td>\n",
       "      <td>1340.0</td>\n",
       "      <td>1323.00</td>\n",
       "      <td>1329.85</td>\n",
       "      <td>1328.25</td>\n",
       "      <td>1329.31</td>\n",
       "      <td>2179328</td>\n",
       "      <td>2.896998e+09</td>\n",
       "      <td>79314</td>\n",
       "      <td>1229535</td>\n",
       "      <td>56.42</td>\n",
       "      <td>1332.289286</td>\n",
       "      <td>1374.066261</td>\n",
       "      <td>1290.512310</td>\n",
       "      <td>Hold Short/Liqiudate Buy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>2017-06-02</td>\n",
       "      <td>1328.25</td>\n",
       "      <td>1335.00</td>\n",
       "      <td>1338.7</td>\n",
       "      <td>1317.00</td>\n",
       "      <td>1322.90</td>\n",
       "      <td>1324.75</td>\n",
       "      <td>1326.29</td>\n",
       "      <td>2627565</td>\n",
       "      <td>3.484909e+09</td>\n",
       "      <td>92530</td>\n",
       "      <td>1625375</td>\n",
       "      <td>61.86</td>\n",
       "      <td>1330.907143</td>\n",
       "      <td>1372.279297</td>\n",
       "      <td>1289.534988</td>\n",
       "      <td>Hold Short/Liqiudate Buy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>2017-06-05</td>\n",
       "      <td>1324.75</td>\n",
       "      <td>1326.25</td>\n",
       "      <td>1341.0</td>\n",
       "      <td>1315.85</td>\n",
       "      <td>1330.00</td>\n",
       "      <td>1329.35</td>\n",
       "      <td>1328.64</td>\n",
       "      <td>2476706</td>\n",
       "      <td>3.290663e+09</td>\n",
       "      <td>77234</td>\n",
       "      <td>1452622</td>\n",
       "      <td>58.65</td>\n",
       "      <td>1328.982143</td>\n",
       "      <td>1367.686657</td>\n",
       "      <td>1290.277629</td>\n",
       "      <td>Hold Short/Liqiudate Buy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Symbol Series       Date  Prev Close  Open Price  High Price  Low Price  \\\n",
       "13  RELIANCE     EQ 2017-06-01     1340.70     1332.70      1340.0    1323.00   \n",
       "14  RELIANCE     EQ 2017-06-02     1328.25     1335.00      1338.7    1317.00   \n",
       "15  RELIANCE     EQ 2017-06-05     1324.75     1326.25      1341.0    1315.85   \n",
       "\n",
       "    Last Price  Close Price  Average Price  Total Traded Quantity  \\\n",
       "13     1329.85      1328.25        1329.31                2179328   \n",
       "14     1322.90      1324.75        1326.29                2627565   \n",
       "15     1330.00      1329.35        1328.64                2476706   \n",
       "\n",
       "        Turnover  No. of Trades  Deliverable Qty  % Dly Qt to Traded Qty  \\\n",
       "13  2.896998e+09          79314          1229535                   56.42   \n",
       "14  3.484909e+09          92530          1625375                   61.86   \n",
       "15  3.290663e+09          77234          1452622                   58.65   \n",
       "\n",
       "    botlinger_avg  botlinger_upper  botlinger_lower                      call  \n",
       "13    1332.289286      1374.066261      1290.512310  Hold Short/Liqiudate Buy  \n",
       "14    1330.907143      1372.279297      1289.534988  Hold Short/Liqiudate Buy  \n",
       "15    1328.982143      1367.686657      1290.277629  Hold Short/Liqiudate Buy  "
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Using the same KNN Model\n",
    "\n",
    "stock2_df[\"call\"] = knn.predict(stock2_df[[\"botlinger_avg\",\"botlinger_lower\",\"botlinger_upper\"]])\n",
    "stock2_df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trade call prediction using RandomForest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Series</th>\n",
       "      <th>Date</th>\n",
       "      <th>Prev Close</th>\n",
       "      <th>Open Price</th>\n",
       "      <th>High Price</th>\n",
       "      <th>Low Price</th>\n",
       "      <th>Last Price</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Average Price</th>\n",
       "      <th>Total Traded Quantity</th>\n",
       "      <th>Turnover</th>\n",
       "      <th>No. of Trades</th>\n",
       "      <th>Deliverable Qty</th>\n",
       "      <th>% Dly Qt to Traded Qty</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>15-May-2017</td>\n",
       "      <td>1350.45</td>\n",
       "      <td>1356.40</td>\n",
       "      <td>1356.40</td>\n",
       "      <td>1333.50</td>\n",
       "      <td>1343.6</td>\n",
       "      <td>1344.1</td>\n",
       "      <td>1344.22</td>\n",
       "      <td>1540213</td>\n",
       "      <td>2.070379e+09</td>\n",
       "      <td>75812</td>\n",
       "      <td>802733</td>\n",
       "      <td>52.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>16-May-2017</td>\n",
       "      <td>1344.10</td>\n",
       "      <td>1346.05</td>\n",
       "      <td>1376.90</td>\n",
       "      <td>1341.00</td>\n",
       "      <td>1356.2</td>\n",
       "      <td>1356.3</td>\n",
       "      <td>1360.59</td>\n",
       "      <td>2892947</td>\n",
       "      <td>3.936121e+09</td>\n",
       "      <td>79767</td>\n",
       "      <td>1238129</td>\n",
       "      <td>42.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>17-May-2017</td>\n",
       "      <td>1356.30</td>\n",
       "      <td>1353.00</td>\n",
       "      <td>1365.95</td>\n",
       "      <td>1347.75</td>\n",
       "      <td>1350.0</td>\n",
       "      <td>1353.1</td>\n",
       "      <td>1354.16</td>\n",
       "      <td>2250304</td>\n",
       "      <td>3.047263e+09</td>\n",
       "      <td>56277</td>\n",
       "      <td>1225837</td>\n",
       "      <td>54.47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Symbol Series         Date  Prev Close  Open Price  High Price  \\\n",
       "0  RELIANCE     EQ  15-May-2017     1350.45     1356.40     1356.40   \n",
       "1  RELIANCE     EQ  16-May-2017     1344.10     1346.05     1376.90   \n",
       "2  RELIANCE     EQ  17-May-2017     1356.30     1353.00     1365.95   \n",
       "\n",
       "   Low Price  Last Price  Close Price  Average Price  Total Traded Quantity  \\\n",
       "0    1333.50      1343.6       1344.1        1344.22                1540213   \n",
       "1    1341.00      1356.2       1356.3        1360.59                2892947   \n",
       "2    1347.75      1350.0       1353.1        1354.16                2250304   \n",
       "\n",
       "       Turnover  No. of Trades  Deliverable Qty  % Dly Qt to Traded Qty  \n",
       "0  2.070379e+09          75812           802733                   52.12  \n",
       "1  3.936121e+09          79767          1238129                   42.80  \n",
       "2  3.047263e+09          56277          1225837                   54.47  "
      ]
     },
     "execution_count": 361,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_data = pd.read_csv(\"RELIANCE.csv\")\n",
    "stock_data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Series</th>\n",
       "      <th>Date</th>\n",
       "      <th>Prev Close</th>\n",
       "      <th>Open Price</th>\n",
       "      <th>High Price</th>\n",
       "      <th>Low Price</th>\n",
       "      <th>Last Price</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Average Price</th>\n",
       "      <th>Total Traded Quantity</th>\n",
       "      <th>Turnover</th>\n",
       "      <th>No. of Trades</th>\n",
       "      <th>Deliverable Qty</th>\n",
       "      <th>% Dly Qt to Traded Qty</th>\n",
       "      <th>Per_chg_oc</th>\n",
       "      <th>Per_chg_lh</th>\n",
       "      <th>Per_chg_day</th>\n",
       "      <th>roll_avg</th>\n",
       "      <th>roll_std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>22-May-2017</td>\n",
       "      <td>1318.85</td>\n",
       "      <td>1326.5</td>\n",
       "      <td>1333.60</td>\n",
       "      <td>1315.2</td>\n",
       "      <td>1326.00</td>\n",
       "      <td>1324.15</td>\n",
       "      <td>1322.82</td>\n",
       "      <td>2011859</td>\n",
       "      <td>2.661318e+09</td>\n",
       "      <td>89828</td>\n",
       "      <td>1123947</td>\n",
       "      <td>55.87</td>\n",
       "      <td>-0.177158</td>\n",
       "      <td>1.399027</td>\n",
       "      <td>0.401865</td>\n",
       "      <td>1335.95</td>\n",
       "      <td>17.420211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>23-May-2017</td>\n",
       "      <td>1324.15</td>\n",
       "      <td>1325.7</td>\n",
       "      <td>1329.85</td>\n",
       "      <td>1302.0</td>\n",
       "      <td>1304.55</td>\n",
       "      <td>1305.55</td>\n",
       "      <td>1313.55</td>\n",
       "      <td>2108223</td>\n",
       "      <td>2.769247e+09</td>\n",
       "      <td>81667</td>\n",
       "      <td>1172410</td>\n",
       "      <td>55.61</td>\n",
       "      <td>-1.519952</td>\n",
       "      <td>2.139017</td>\n",
       "      <td>-1.404675</td>\n",
       "      <td>1325.80</td>\n",
       "      <td>17.383757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>24-May-2017</td>\n",
       "      <td>1305.55</td>\n",
       "      <td>1307.5</td>\n",
       "      <td>1313.70</td>\n",
       "      <td>1295.1</td>\n",
       "      <td>1299.00</td>\n",
       "      <td>1297.70</td>\n",
       "      <td>1302.71</td>\n",
       "      <td>3274804</td>\n",
       "      <td>4.266122e+09</td>\n",
       "      <td>78535</td>\n",
       "      <td>1782580</td>\n",
       "      <td>54.43</td>\n",
       "      <td>-0.749522</td>\n",
       "      <td>1.436183</td>\n",
       "      <td>-0.601279</td>\n",
       "      <td>1314.72</td>\n",
       "      <td>12.641875</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Symbol Series         Date  Prev Close  Open Price  High Price  \\\n",
       "5  RELIANCE     EQ  22-May-2017     1318.85      1326.5     1333.60   \n",
       "6  RELIANCE     EQ  23-May-2017     1324.15      1325.7     1329.85   \n",
       "7  RELIANCE     EQ  24-May-2017     1305.55      1307.5     1313.70   \n",
       "\n",
       "   Low Price  Last Price  Close Price  Average Price  Total Traded Quantity  \\\n",
       "5     1315.2     1326.00      1324.15        1322.82                2011859   \n",
       "6     1302.0     1304.55      1305.55        1313.55                2108223   \n",
       "7     1295.1     1299.00      1297.70        1302.71                3274804   \n",
       "\n",
       "       Turnover  No. of Trades  Deliverable Qty  % Dly Qt to Traded Qty  \\\n",
       "5  2.661318e+09          89828          1123947                   55.87   \n",
       "6  2.769247e+09          81667          1172410                   55.61   \n",
       "7  4.266122e+09          78535          1782580                   54.43   \n",
       "\n",
       "   Per_chg_oc  Per_chg_lh  Per_chg_day  roll_avg   roll_std  \n",
       "5   -0.177158    1.399027     0.401865   1335.95  17.420211  \n",
       "6   -1.519952    2.139017    -1.404675   1325.80  17.383757  \n",
       "7   -0.749522    1.436183    -0.601279   1314.72  12.641875  "
      ]
     },
     "execution_count": 362,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_data[\"Per_chg_oc\"] =  ((stock_data[\"Close Price\"]-stock_data[\"Open Price\"])/stock_data[\"Open Price\"])*100\n",
    "stock_data[\"Per_chg_lh\"] =  ((stock_data[\"High Price\"]-stock_data[\"Low Price\"])/stock_data[\"Low Price\"])*100\n",
    "\n",
    "stock_data[\"Per_chg_day\"] = stock_data[\"Close Price\"].pct_change()*100\n",
    "stock_data.drop(stock_data.index[0],inplace=True)\n",
    "\n",
    "stock_data[\"roll_avg\"] = stock_data[\"Close Price\"].rolling(window=5).mean()\n",
    "stock_data[\"roll_std\"] = stock_data[\"Close Price\"].rolling(window=5).std()\n",
    "stock_data = stock_data[stock_data[\"roll_avg\"].isnull()==False]\n",
    "\n",
    "stock_data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Series</th>\n",
       "      <th>Date</th>\n",
       "      <th>Prev Close</th>\n",
       "      <th>Open Price</th>\n",
       "      <th>High Price</th>\n",
       "      <th>Low Price</th>\n",
       "      <th>Last Price</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Average Price</th>\n",
       "      <th>...</th>\n",
       "      <th>Turnover</th>\n",
       "      <th>No. of Trades</th>\n",
       "      <th>Deliverable Qty</th>\n",
       "      <th>% Dly Qt to Traded Qty</th>\n",
       "      <th>Per_chg_oc</th>\n",
       "      <th>Per_chg_lh</th>\n",
       "      <th>Per_chg_day</th>\n",
       "      <th>roll_avg</th>\n",
       "      <th>roll_std</th>\n",
       "      <th>Action</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>22-May-2017</td>\n",
       "      <td>1318.85</td>\n",
       "      <td>1326.5</td>\n",
       "      <td>1333.60</td>\n",
       "      <td>1315.2</td>\n",
       "      <td>1326.00</td>\n",
       "      <td>1324.15</td>\n",
       "      <td>1322.82</td>\n",
       "      <td>...</td>\n",
       "      <td>2.661318e+09</td>\n",
       "      <td>89828</td>\n",
       "      <td>1123947</td>\n",
       "      <td>55.87</td>\n",
       "      <td>-0.177158</td>\n",
       "      <td>1.399027</td>\n",
       "      <td>0.401865</td>\n",
       "      <td>1335.95</td>\n",
       "      <td>17.420211</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>23-May-2017</td>\n",
       "      <td>1324.15</td>\n",
       "      <td>1325.7</td>\n",
       "      <td>1329.85</td>\n",
       "      <td>1302.0</td>\n",
       "      <td>1304.55</td>\n",
       "      <td>1305.55</td>\n",
       "      <td>1313.55</td>\n",
       "      <td>...</td>\n",
       "      <td>2.769247e+09</td>\n",
       "      <td>81667</td>\n",
       "      <td>1172410</td>\n",
       "      <td>55.61</td>\n",
       "      <td>-1.519952</td>\n",
       "      <td>2.139017</td>\n",
       "      <td>-1.404675</td>\n",
       "      <td>1325.80</td>\n",
       "      <td>17.383757</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>24-May-2017</td>\n",
       "      <td>1305.55</td>\n",
       "      <td>1307.5</td>\n",
       "      <td>1313.70</td>\n",
       "      <td>1295.1</td>\n",
       "      <td>1299.00</td>\n",
       "      <td>1297.70</td>\n",
       "      <td>1302.71</td>\n",
       "      <td>...</td>\n",
       "      <td>4.266122e+09</td>\n",
       "      <td>78535</td>\n",
       "      <td>1782580</td>\n",
       "      <td>54.43</td>\n",
       "      <td>-0.749522</td>\n",
       "      <td>1.436183</td>\n",
       "      <td>-0.601279</td>\n",
       "      <td>1314.72</td>\n",
       "      <td>12.641875</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Symbol Series         Date  Prev Close  Open Price  High Price  \\\n",
       "5  RELIANCE     EQ  22-May-2017     1318.85      1326.5     1333.60   \n",
       "6  RELIANCE     EQ  23-May-2017     1324.15      1325.7     1329.85   \n",
       "7  RELIANCE     EQ  24-May-2017     1305.55      1307.5     1313.70   \n",
       "\n",
       "   Low Price  Last Price  Close Price  Average Price  ...      Turnover  \\\n",
       "5     1315.2     1326.00      1324.15        1322.82  ...  2.661318e+09   \n",
       "6     1302.0     1304.55      1305.55        1313.55  ...  2.769247e+09   \n",
       "7     1295.1     1299.00      1297.70        1302.71  ...  4.266122e+09   \n",
       "\n",
       "   No. of Trades  Deliverable Qty  % Dly Qt to Traded Qty  Per_chg_oc  \\\n",
       "5          89828          1123947                   55.87   -0.177158   \n",
       "6          81667          1172410                   55.61   -1.519952   \n",
       "7          78535          1782580                   54.43   -0.749522   \n",
       "\n",
       "   Per_chg_lh  Per_chg_day  roll_avg   roll_std  Action  \n",
       "5    1.399027     0.401865   1335.95  17.420211      -1  \n",
       "6    2.139017    -1.404675   1325.80  17.383757      -1  \n",
       "7    1.436183    -0.601279   1314.72  12.641875       1  \n",
       "\n",
       "[3 rows x 21 columns]"
      ]
     },
     "execution_count": 363,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_df = stock_data.copy()\n",
    "stock_df[\"Action\"]=1\n",
    "\n",
    "for i in range(489):\n",
    "    if stock_df[\"Close Price\"].iloc[i+1]>stock_df[\"Close Price\"].iloc[i]:\n",
    "        stock_df.iloc[i,20]=1\n",
    "    elif stock_df[\"Close Price\"].iloc[i+1]<stock_df[\"Close Price\"].iloc[i]:\n",
    "        stock_df.iloc[i,20]=-1\n",
    "\n",
    "stock_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {},
   "outputs": [],
   "source": [
    "# RandomForest Classifier\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn import metrics\n",
    "\n",
    "X = stock_df[[\"Per_chg_oc\",\"Per_chg_lh\",\"roll_avg\",\"roll_std\"]]\n",
    "Y = stock_df.Action.astype('category')\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split( X, Y, test_size = 0.3, random_state = 42 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Acc: 100.0 %\n",
      "Test Acc: 54.421768707483 %\n"
     ]
    }
   ],
   "source": [
    "clf=RandomForestClassifier(n_estimators=1000)\n",
    "clf.fit(X_train,y_train)\n",
    "\n",
    "print(\"Training Acc:\", clf.score(X_train, y_train)*100,\"%\")\n",
    "print(\"Test Acc:\", clf.score(X_test, y_test)*100,\"%\")"
   ]
  }
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