duckdb_demo

duckdb_demo_aml.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What's this dataset's timestamp range?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>end_timestamp</th>\n",
       "      <th>start_timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023/01/12 16:49</td>\n",
       "      <td>2022/08/01 00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      end_timestamp   start_timestamp\n",
       "0  2023/01/12 16:49  2022/08/01 00:00"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import duckdb\n",
    "import pandas as pd\n",
    "\n",
    "con = duckdb.connect('db/ibm_aml.db')\n",
    "c = con.execute(\"SELECT MAX(Timestamp), MIN(Timestamp) FROM demo;\")\n",
    "\n",
    "df = pd.DataFrame(c.fetchall(), columns = ['end_timestamp', 'start_timestamp'])\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How many rows/records in this dataset? and How many of them are the records have is_laundering flag?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>total_record</th>\n",
       "      <th>is_laundering</th>\n",
       "      <th>persentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>430920901</td>\n",
       "      <td>386163</td>\n",
       "      <td>0.089613</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_record  is_laundering  persentage\n",
       "0     430920901         386163    0.089613"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import duckdb\n",
    "import pandas as pd\n",
    "con = duckdb.connect('db/ibm_aml.db')\n",
    "c = con.execute(\"SELECT Count(*), count(is_laundering) FILTER (WHERE is_laundering), count(is_laundering) FILTER (WHERE is_laundering)/Count(*) * 100 FROM demo;\")\n",
    "\n",
    "df = pd.DataFrame(c.fetchall(), columns = ['total_record', \"is_laundering\", \"persentage\"])\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets focus on the is_laundering data. Whats the payment format based on the total amount paid? Showing in the bar structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr > th,\n",
       ".dataframe > tbody > tr > td {\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (6, 2)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>total_paid</th><th>payment_format</th></tr><tr><td>f64</td><td>str</td></tr></thead><tbody><tr><td>2.2740e13</td><td>&quot;ACH&quot;</td></tr><tr><td>6.2122e11</td><td>&quot;Cheque&quot;</td></tr><tr><td>5.2556e10</td><td>&quot;Cash&quot;</td></tr><tr><td>5.6701e8</td><td>&quot;Credit Card&quot;</td></tr><tr><td>1.4183e6</td><td>&quot;Bitcoin&quot;</td></tr><tr><td>32253.69</td><td>&quot;Wire&quot;</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (6, 2)\n",
       "┌────────────┬────────────────┐\n",
       "│ total_paid ┆ payment_format │\n",
       "│ ---        ┆ ---            │\n",
       "│ f64        ┆ str            │\n",
       "╞════════════╪════════════════╡\n",
       "│ 2.2740e13  ┆ ACH            │\n",
       "│ 6.2122e11  ┆ Cheque         │\n",
       "│ 5.2556e10  ┆ Cash           │\n",
       "│ 5.6701e8   ┆ Credit Card    │\n",
       "│ 1.4183e6   ┆ Bitcoin        │\n",
       "│ 32253.69   ┆ Wire           │\n",
       "└────────────┴────────────────┘"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import duckdb\n",
    "import polars as pl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "con = duckdb.connect('db/ibm_aml.db')\n",
    "duckdb_to_arrow = con.query(\"\"\"\n",
    "  SELECT \n",
    "    ROUND(SUM(amount_paid), 2) as total_paid, \n",
    "    payment_format \n",
    "  FROM vw_is_laundering \n",
    "  GROUP BY payment_format \n",
    "  ORDER BY SUM(amount_paid) DESC;               \n",
    "\"\"\").arrow()\n",
    "\n",
    "polars_df = pl.DataFrame(duckdb_to_arrow)\n",
    "\n",
    "display(polars_df)\n",
    "\n",
    "# polars_df\n",
    "plt.figure(figsize=(8,8))\n",
    "\n",
    "# plot a Pie Chart for Registration Price column with label Car column\n",
    "plt.bar(x=polars_df[\"payment_format\"], height=polars_df[\"total_paid\"])\n",
    "plt.show()\n",
    "\n",
    "plt.show()\n",
    "\n",
    "# close connection\n",
    "con.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What's the most laundering currency? showing in pie chart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr > th,\n",
       ".dataframe > tbody > tr > td {\n",
       "  text-align: right;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (15, 2)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>total_paid</th><th>payment_currency</th></tr><tr><td>f64</td><td>str</td></tr></thead><tbody><tr><td>8.4865e12</td><td>&quot;Rupee&quot;</td></tr><tr><td>6.4202e12</td><td>&quot;Yen&quot;</td></tr><tr><td>4.5248e12</td><td>&quot;Ruble&quot;</td></tr><tr><td>1.2780e12</td><td>&quot;Yuan&quot;</td></tr><tr><td>7.4596e11</td><td>&quot;US Dollar&quot;</td></tr><tr><td>6.4494e11</td><td>&quot;Mexican Peso&quot;</td></tr><tr><td>4.9302e11</td><td>&quot;Euro&quot;</td></tr><tr><td>3.7528e11</td><td>&quot;Shekel&quot;</td></tr><tr><td>1.6231e11</td><td>&quot;Saudi Riyal&quot;</td></tr><tr><td>1.2594e11</td><td>&quot;Brazil Real&quot;</td></tr><tr><td>5.5224e10</td><td>&quot;Canadian Dolla…</td></tr><tr><td>4.5819e10</td><td>&quot;Australian Dol…</td></tr><tr><td>3.0428e10</td><td>&quot;UK Pound&quot;</td></tr><tr><td>2.6438e10</td><td>&quot;Swiss Franc&quot;</td></tr><tr><td>1.4183e6</td><td>&quot;Bitcoin&quot;</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (15, 2)\n",
       "┌────────────┬───────────────────┐\n",
       "│ total_paid ┆ payment_currency  │\n",
       "│ ---        ┆ ---               │\n",
       "│ f64        ┆ str               │\n",
       "╞════════════╪═══════════════════╡\n",
       "│ 8.4865e12  ┆ Rupee             │\n",
       "│ 6.4202e12  ┆ Yen               │\n",
       "│ 4.5248e12  ┆ Ruble             │\n",
       "│ 1.2780e12  ┆ Yuan              │\n",
       "│ …          ┆ …                 │\n",
       "│ 4.5819e10  ┆ Australian Dollar │\n",
       "│ 3.0428e10  ┆ UK Pound          │\n",
       "│ 2.6438e10  ┆ Swiss Franc       │\n",
       "│ 1.4183e6   ┆ Bitcoin           │\n",
       "└────────────┴───────────────────┘"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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GckyI3qUIIXQkYVnUe1/9tY9XZ2/B5VX1LkUI0cCEWIw8fkl77j6nFQaDonc5QggdSFgW9VZRmYdnZmzkl39kq2ohRM06o1UM427pJVtmC9EISVgW9dLa/YU88u06DhSW6V2KEKKRiAuz8N5NvTi3XZzepQghapGEZVGvaJrGJ7/v4Z1ft+NV5Z+uEKJ2GRR46MJ2jLionUzLEKKRkLAs6o08u4vHv9/AHzty9S5FCNHInd0mlvdv7kV8uFXvUoQQNUzCsqgXlu/K47Hv1pNT4tK7FCGEACA+3Mr7N/fk7DYyLUOIhkzCsqjTfKrGuwt2MH7JLmTWhRCirjEo8OhF7Xn4wrYyLUOIBkrCsqizMmxlPDptHX+nFupdihBCHNN57eJ476aexIbJtAwhGhoJy6JO+nVzFiOnb8Tm8OhdihBCVEmTCCsf3NyLM1rH6l2KEKIaSVgWdYrbq/L6L1uZsiJV71KEEOKEGQ0Kj1/Sngf6t0FRZFqGEA2BhGVRZ+TZXfzfl6tZu9+mdylCCHFK+rWP592behITatG7FCHEKZKwLOqELRnF3PPlatJtssmIEKJhSIoMYvxtvemVEq13KUKIUyBhWeju181ZjPhuPQ63T+9ShBCiWgWZDbx3Uy8GdE3UuxQhxEmSsCx09dHiXbz963bkX6EQoqEyKPDcFZ0Zdm4rvUsRQpwECctCFy6vj6en/8PMdel6lyKEELVi6NktGXVlZ+nHLEQ9I2FZ1D57LiN/WM/32916VyKEELXqks5N+ODmXgRbjHqXIoSoIgnLonbl7YSp1+MwRnBO9hMUekx6VySEELWqR3IUnw85nTjZwESIekHCsqg9+1bAtFuhzL8jX1bTSzhr71A0TS5JCiEal5SYECbf1Yc28WF6lyKEOA6D3gWIRuKfH+HLQYGgDJCYsYCZbefrV5MQQuhkf4GDwR+vYNXeAr1LEUIch4RlUfOWvgPTh4PPdcRdPdO+ZGybdToUJYQQ+rI5PNz++Up+3pChdylCiGOQaRiiZs17Bv4af8yHaAYTb8a8yqcHUmqpKCGEqDsUBZ68rAMP9G+rdylCiKOQsCxqhqrC7Edh7ZdVerhmjWCY6Q1+y5edroQQjdMtfVN4dVBXjNJaTog6RcKyqH4+L8y8Fzb9eEJP80akMLD0RXaWBtdQYUIIUbf17xDPR7f2JtQqnYKEqCskLIvq5XXBD0Nh+y8n9XR7fG/OyhxBiVd+UQghGqeeyVF8Nawv4UFmvUsRQiAL/ER1cjvgmxtPOigDhOWuZV6Lb1EUOYcTQjRO69Ns3DlpFSVOj96lCCGQsCyqi7MYvr4O9iw55UM1S5/L920XnXpNQghRT63bb2PIpFXYXV69SxGi0ZOwLE6dowC+uAr2/1lth+yTNok3Wv9TbccTQoj6Zu1+G3d+vlICsxA6k7AsTk1JNky+HDLXV/uhb85+h6FND1T7cYUQor5YKyPMQuhOFviJk2dLgy+vhoI9NfYSalA0Qw2v8UdBVI29hhBC1HWnt4jmi7v7SpcMIXQgI8vi5BSlw5TLazQoAxichXxuHkPLYGeNvo4QQtRlq/cVMnTyKkplhFmIWidhWZy40jz48hqw7a+VlzMX7eXn+I8JNaq18npCCFEX/Z1ayF2T/5bALEQtk7AsTkyZDb4aBPk7a/VlI3L+5pdW39fqawohRF2zKrWAuyb/jcMtgVmI2iJhWVSdu9TfRzlLny4VLQ78zNR2v+vy2kIIUVesSi1gqARmIWqNhGVRNV4XTLsV0lbqWsY5aZ/yUqututYghBB6W7XXP8Jc5vbpXYoQDZ6EZXF8Pi/8eHe1bDhSHYbkjObWpEy9yxBCCF2t3FvAXVNWSWAWooZJWBbHpmkw637YNlvvSgIUn4tXna9zRlSx3qUIIYSu/tpTwLAv/sbtlQXQQtQUCcvi2Ob8B/6pewvrDGX5fBX0Ns2CXHqXIoQQulqxO5+np2/UuwwhGiwJy6JyC0bB6s/1rqJSFtsu5iR+RrBRLkEKIRq3GevSeXfBDr3LEKJBkrAsjm7pO7D8fb2rOK6orD+Z3XqW3mUIIYTu3l+0k+lrDuhdhhANjoRlcaSNP8Cil/WuosrapE1nUrvlepchhBC6e2bGP/y5O1/vMoRoUCQsi4r2r4SfHtS7ihN2Qdp4nm0plyCFEI2b26dy71er2ZVj17sUIRoMCcvikMJUfy9lX/1bNKegcU/eWwxukq13KUIIoatip5e7pqwiz17/fpYLURdJWBZ+zmL45mZw5OldyUlTvGWM9r5B70gZURFCNG5pBWUM/2I1To8sgBbiVElYFqD64IehkFv/d8YzlubwTehYEq1uvUsRQghdrU+z8dh369E0Te9ShKjXJCwLmDsSdi/Su4pqE1SwjTlNJ2E2yC8IIUTjNndTFm/M3aZ3GULUaxKWG7u/PoG/J+pdRbWLzfyD2W1+1rsMIYTQ3Wd/7OHrv/bpXYYQ9ZaE5cZsx68w/1m9q6gxHdK+45O2K/UuQwghdPfiz5tZvD1H7zKEqJckLDdW2Zvhx7tBa9iLPy5LH8d/WuzWuwwhhNCVT9V4+Jt1bMko1rsUIeodCcuNkT3X3/nCXaJ3JTVO0VQeKniTqxJy9S5FCCF0ZXd5uXvK32QXO/UuRYh6RcJyY6P64Me7oGi/3pXUGsVTynvqm3QLL9W7FCGE0FVWsZOHv12HT5UF0EJUlYTlxmbx65C6VO8qap3Rnsn3Ee8Ta/HoXYoQQuhq1d4C3lsoO54KUVUSlhuTnQth6Tt6V6Gb4PxNzG3+JUZF1bsUIYTQ1UeLd7FsZ/3dhEqI2iRhubEoSocZ9wCN+9JbQsYiZrWdq3cZQgihK1WDEd+tI6dE5i8LcTwSlhsDn8e/Q19Zgd6V1And0qbyQds1epchhBC6yrO7GTFtParMXxbimCQsNwYLX4IDq/Suok65Kv09HkxO1bsMIYTQ1Yrd+Xzw2069yxCiTpOw3NBtnQ1/fqh3FXWOovl4ovgNLo2T0XYhROP2waKdrNgt85eFqIyE5YasMBV+ekDvKuosxVXCeOUN2oeW6V2KEELoRtVgxLT15NldepciRJ0kYbmh8rrg+yHgLNK7kjrNVJLOzJhxRJq9epcihBC6ySlx8dh369E0mb8sxL9JWG6o5j0Dmev1rqJeCM1dz/yUr1EU+SUhhGi8lu7MY/yS3XqXIUSdI2G5Ido8C1Z/rncV9Upi+q9Mb/ur3mUIIYSuxi7Ywaq9spZDiMNJWG5o7Dkw53G9q6iXeqd9wdutN+hdhhBC6Manajzy7ToKSt16lyJEnSFhuaH53whw5OtdRb01OGssw5un6V2GEELoJqvYyePfy/xlIQ6SsNyQrP8Wts/Ru4p6TVE9PFfyOv1jCvUuRQghdLNkey6f/rFH7zKEqBMUTU4dG4biDBh/pnS/qCaeiBZcZn+RPY4gvUsRjVTJul8oWfcL3qJsAMxxKUSdfQvBbU4PPMaVvpXCP77CnbkdFAOWhNYk3PgyBrP1qMcs+vN7HDv+xFNwAMVkwdqsE9H9hmKObR54TMGiCZRuWoRiDiKq3xDCulwQuK902zJKNy0i4foXa+hdi7rEYjTwv4fPpUNiuN6lCKErCcsNxVfXwe5FelfRoJQknM6ZGY9S6jXqXYpohBy7VqIoBkzRTQGwb1pE8coZJA19H0t8C1zpW8n+/kUiz7qB4DZ9UQxG3Dl7CWl3JorJfNRjZn8/itBO52NJbAeaD9vvX+LO20fTYR9jsATh2LWS/HnjSBj8It7CDPLnvk+z+ydjDIlEdZWS+cVjNLn5VUwRCbX5rRA66tE8khkPnIPRoOhdihC6kWkYDcHqyRKUa0B4zmrmt5ymdxmikQppewbBbfpgjmmGOaYZ0efficEShCtjOwAFiyYScdpVRJ55A5b4FphjmxPa6bxKgzJAkxtfJqzbxVjiW2BJaE3sFY/hK87Fnb0LAE9+GkHJ3bAmtSO0cz8US0hgZLtw8WTCe10uQbmR2XCgiAlLZTqGaNwkLNd3hfvg1+f1rqLBan5gDt+1W6x3GaKR01QfpVt+R/U4sTbriK/UhjtzO4bQKLK+eoK0cbeT9c3TOA9sPqHjqq5SAAxBYQBY4lvhztqFz2nHlbULzevCFN0U54HNuLN3E37aVdX+3kTd9+6CHezJtetdhhC6kWkY9ZmmwRdXQepSvStp8KY2fZbn9nTVuwzRyLhzU8n66gk0rxvFEkz8VU8Q3KYPrvRtZH39BIagcKIvuBtLk9bYN/1Gybo5NL37I8wxzY57bE1TyZ3+CqqzlMTbRwe+bls2ldLNS1BMFqLOu43gNn3InDKC2Csew5W+lZK1szEGRxBz2UNY4lvU5NsXdcjpLaL5/t6zMMh0DNEISViuz/76BOY9pXcVjYJmtPBi5Ot8mdFU71JEI6L5PHiLc1FdDhzbl2Hf8CtNbn0T1VlK9tQniTjzBqL7DQk8PmPSQwS3OZ3ofkOPe+z8+R9RtmcNibeNxhQRV+njbMu+QXWVEtbtYrK/f4Gmd39E2a5VlKydTdLQ96vjbYp64sWrOnPXOa30LkOIWifTMOqrvF2w8CW9q2g0FJ+bl8pe55xo6TYiao9iNGOOboo1sS3R/YZiSWhFyeqfMYZFA/4OGYczxybjLc497nELFnxM2e6/aXLL68cMyp78NEq3LCbqvNtx7v+HoOZdMYZEEtLxPNzZu1FdjlN7g6JeGT1vO/vz5e9cND4SlusjTYOfHwJvmd6VNCqGsgImW8eQEuzUuxTRSGmahubzYIpsgjEsBm/+gQr3ewrSj7kAT9M0ChZ8jGPHnzS5+TXMUYnHfGz+/I+IvnA4BkswaCqa6vXfefBPTT3l9yTqjzKPj2dmbtS7DCFqnYTl+mj9N7D/T72raJQstj3MTviUYKNP71JEA1f4+xScaZvwFmXjzk2l8PcpuPb/Q2jn/iiKQkTfwRSv+R+l25bhKczA9sdXeAsOENb90sAxsqc9S/Ga/wU+L1jwMfbNS4i76kkMlhB89kJ89kJUj+uI17dvmI8xOIKQtmcAYG3WCee+jbjSt1H890+YY1MCCwNF47F8Vz4z1x04/gOFaEBMehcgTlCZDRbKhgB6isheydxWifTfdZPepYgGzFdaRN7ssfhKCzBYQ7HEtyThxpcJbtULgIg+16D53BT+NhHVWYIlvhUJN72COTopcAxPYRbWsuLA5/Z1vwCQ/e0zFV4r9vIRhHW7+LDXLqToz+9JvH1M4GvWph2I6HstOT/+F0NIJHFXPFYj71vUfa/N2cqFHZoQGVJ5m0IhGhJZ4FffzHkC/p6gdxUCWJp8H3fsPF/vMoQQotbd3CeZNwd317sMIWqFTMOoTzI3wOpJelchyp2b9ikvtNqmdxlCCFHrvludxt+pBXqXIUStkLBcX2iaf1RZk7mydYWCxt25o7kpKUvvUoQQolZpGjw38x88PlnkKRo+Ccv1xbqv4cAqvasQ/6J4nbzhep2+UcXHf7AQQjQgO7LtfPaHbIUtGj4Jy/VBWaH0VK7DDI48vgoeS1KQW+9ShBCiVo37bSdpBdJ7WTRsEpbrg0WvgCNP7yrEMVgLd/BL4gSsBrkkKYRoPJweldHzt+tdhhA1SsJyXZexHtZM1rsKUQXRWcuZ3WaW3mUIIUStmr0xg40HbHqXIUSNkbBcl2kazPmP7JJVj7RL+5GJbVfoXYYQQtQaTYM350pnINFwSViuy9Z9Demr9a5CnKCL0sczssVOvcsQQohas2J3Pku25+hdhhA1QsJyXeUpg8Wv6V2FOAmKpnJ/wVsMaiK/OIQQjcebc7ehqrLPmWh4JCzXVSs/gZJMvasQJ0nxOHjH+wY9I+x6lyKEELViW1YJM9al612GENVOwnJdVGaDZe/pXYU4RcbSbKaFvUuC1aN3KUIIUSvG/rodp0c2zxINi4Tlumj5e+C06V2FqAZBBVuZ23QSZoNcmhRCNHwZRU6+WJGqdxlCVCsJy3VNSTas/FTvKkQ1is38nZ/b/E/vMoQQolaMX7KbIodcURMNh4Tluub3t8AjuyE1NJ3SpjG+7d96lyGEEDWuqMzDh4ulI5BoOCQs1yUFe2Dtl3pXIWrIwPQPGJGyR+8yhBCixn3x5z4OFMrAj2gYJCzXJb+9BqpcumqoFM3Ho7Y3uDxeti4XQjRsbq/K2F936F2GENVCwnJdkfUPbJqudxWihinuUsZpb9IpTEZchBAN26z16WzJKNa7DCFOmYTlumLRy4B0TGgMjPYMpke9T7TZq3cpQghRY1QN3pwn22CL+k/Ccl2wbwXs/FXvKkQtCsn7h/nJX2BUVL1LEUKIGvPHjlyW75KpZ6J+k7BcFyx6Re8KhA4SMhYxs+18vcsQQogaNXaBzF0W9ZuEZb3tWwH7V+hdhdBJ97SveK/tWr3LEEKIGrNmXyFr9hXoXYYQJ03Cst6WvqN3BUJn12S8x/3JqXqXIYQQNeazP6Rtpqi/JCzrKXMD7FqodxVCZ4rqZWTxm1wSJyMvQoiGacGWbPbmlepdhhAnRcKynpa9q3cFoo5QXMV8bHiLdqFlepcihBDVTtVg4lIZXRb1k4RlveTvhi0/6V2FqENMxWnMihlHuElaygkhGp7paw+Qb3fpXYYQJ0zCsl6WvweatA0TFYXmrmd+i29QFOm5LYRoWJwelS//3Kd3GUKcMAnLerDnwIbv9K5C1FFN0+fxQ7tFepchhBDV7uu/9uH0+PQuQ4gTImFZDys/BZ9cihKVO33/JN5s/Y/eZQghRLXKL3Xz45oDepchxAmRsFzb3A5Y/bneVYh64Kast7m7WZreZQghRLX6fNleVFWmmon6Q8JybVs/FcoK9a5C1AOK6uH50jc4P8amdylCCFFt9uaV8uuWbL3LEKLKJCzXJlWFPz/SuwpRjxicNj43j6FlsFPvUoQQotpMkDZyoh6RsFybts+Bwr16VyHqGXPRXv4XP55Qo3RPEUI0DP4tsOUqq6gfJCzXpr9lrrI4OeE5q5nXapreZQghRLX57I/depcgRJVIWK4thamwZ4neVYh6LPnAbL5pt0TvMoQQolos2JJNqmyBLeoBCcu1Zc0XgKz+Fafm7LTPeLnVFr3LEEKIU6ZqMHGZzF0WdZ+E5drg8/q7YAhRDe7IGcNtSRl6lyGEEKdsxtp0Sl1evcsQ4pgkLNeG7b+AXdrkiOqh+Fy84nyDs6KL9C5FCCFOicPt45d/MvUuQ4hjkrBcG9ZM0bsC0cAYyvL5wvo2zYJkJ0ghRP02fa3s6CfqNgnLNa1wH+xZrHcVogGy2HbzS5NPCTb69C5FCCFO2sq9BaQVOPQuQ4hKSViuaWu/BE3644qaEZn9F3NazdC7DCGEOGmaBjPXpetdhhCVkrBck3xeWPe13lWIBq71gZlMabdM7zKEEOKkzZCpGKIOk7Bck3bMBXuW3lWIRqBf2sc813K73mUIIcRJSc13sDq1QO8yhDgqCcs1SRb2iVqioDE8bzQ3JMrJmRCifpKFfqKukrBcU2z7YfdvelchGhHFW8Zb7jfoHVmidylCCHHCZm/MxOmRBcui7pGwXFP++UEW9olaZ3Dk8m3IWBKtbr1LEUKIE1Li9DJ/s1wdE3WPhOWasnmm3hWIRspauJ1fkiZiNcjJmhCifpm+VrpiiLpHwnJNyNsFWf/oXYVoxGKylvG/Nj/pXYYQQpyQZTtzyS526l2GEBVIWK4JMqos6oD2aT/wWdu/9C5DCCGqTJWey6IOkrBcEzbLJhGibrgk/UP+k7Jb7zKEEKLKpq+RrhiibpGwXN1yt0POFr2rEAIARVN5qPBNrmmSo3cpQghRJTtz7Gw8YNO7DCECJCxXt00yqizqFsVTyljvm3QLL9W7FCGEqBIZXRZ1iYTl6ibzlUUdZCzN4vuI94i3ePQuRQghjuvnDRn4VE3vMoQAJCxXr+zNkCdbDou6KTh/M780n4JRkZZyQoi6rdDhYe3+Qr3LEAKQsFy9ZFRZ1HHxGYv5ue0vepchhBDH9ds2WWsh6gYJy9VJwrKoB7qkfcOHbVfrXYYQQhzTYgnLoo6QsFxdMjdC/i69qxCiSq5If5+HU/bqXYYQQlRqW1YJGbYyvcsQQsJytdkiu6WJ+kPRfDxue4MB8fl6lyKEEJWSqRiiLpCwXF12LdC7AiFOiOK28yFv0jHMoXcpQghxVDIVQ9QFEpargz3XPw1DiHrGVJLOjKgPiDZ79S5FCCGOsGJ3Pk6PT+8yRCMnYbk67P4NkH6Qon4KydvI3JSvUBT5NyyEqFvKPD7+3CPTxYS+JCxXh92L9K5AiFOSmL6AmW3n612GEEIcQaZiCL1JWD5VmlY+sixE/dYz7UveabNe7zKEEKKCxdslLAt9SVg+VZkboDRX7yqEqBbXZY7l/5rv17sMIYQISCsoY1dOid5liEZMwvKpkikYogFRVC/PlLzBhbGyzawQou6QFnJCTxKWT9UuCcuiYVFcRXxmfIs2IbIZgBCibpCwLPQkYflUuEogbZXeVQhR7UzF+/kp9iPCTdJSTgihv9WphRQ7PXqXIRopCcunYs/voMp/XtEwheWuZW7LadJSTgihO6+qsXRHnt5liEZKwvKpkPnKooFrfuAXvmsr3V6EEPqTqRhCLxKWT4XMVxaNQN+0z3m99T96lyGEaOSW7ZLOU0IfEpZPVmEq2PbpXYUQteKW7HcY0jRd7zKEEI1YdrGLDJssPBa1T8LyyUr7W+8KhKg1is/Ni47XOTemSO9ShBCN2Lr9Nr1LEI2QhOWTdUC6YIjGxeAsZLJ5DCnBTr1LEUI0UuvTpAe8qH0Slk+WtIwTjZC5aA+zEz4h1KjqXYoQohGSkWWhBwnLJ8NTBtmb9a5CCF1EZK/il1bf612GEKIR2pRRhMcnJ+uidklYPhkZ66S/smjUWhz4ma/b/a53GUKIRsbpUdmWWaJ3GaKRkbB8MmQKhhCck/YZL7baqncZQohGZp3MWxa1TMLyyTggnTCEUNAYmjuGm5My9S5FCNGIrJd5y6KWSVg+GRKWhQBA8Tp53fkGfaOK9S5FCNFIrEuz6V2CaGQkLJ+own1gz9a7CiHqDENZHl8Hv0OzIJfepQghGoG9eaXYHG69yxCNiITlEyWjykIcwVK4kzmJE7AaZJW6EKLmyeiyqE0Slk+ULO4T4qiislbwS5uZepchhGgEZN6yqE0Slk+U7NwnRKXapE1nUrvlepchhGjgZGRZ1CYJyyfC55XNSIQ4jgvSxvN0ix16lyGEaMA2pNnQNE3vMkQjIWH5RBTsBp8sKhDiWBQ07s1/i8FNZCGsEKJmFJV52JNXqncZopGQsHwicrfpXYEQ9YLiLWO09w16R9r1LkUI0UDJvGVRWyQsn4gcCctCVJWxNIdvQseSYJWt4YUQ1e+f9CK9SxCNhITlEyEjy0KckKCCbcxtOgmzQeYWCiGq116ZhiFqiYTlEyFhWYgTFpv5O7Pb/Kx3GUKIBiY1X8KyqB0SlqvK54X8XXpXIUS91CHtOz5uu1LvMoQQDciBwjI8PtkISdQ8CctVVbBHOmEIcQoGpI/jsZQ9epchhGggfKrGgcIyvcsQjYCE5aqSKRhCnBJFU3nE9gZXxufpXYoQooFIlXnLohZIWK6q3O16VyBEvae4S3lfe4Mu4fILTghx6mSRn6gNEparKner3hUI0SAY7Zn8GPk+sRZpKSeEODWyyE/UBgnLVSUjy0JUm+C8Tcxt/iVGRRbnCCFOXmq+Q+8SRCMgYbkqVB/k7dS7CiEalISMRcxqO1fvMoQQ9ZjMWRa1QcJyVRSlgc+ldxVCNDjd0qbyfpu1epchhKin0m3SPk7UPAnLVVF0QO8KhGiwrs58jweTU/UuQwhRD/lUjf0FMhVD1CwJy1VRnKF3BUI0WIrq5YniN7g0rkDvUoQQ9ZBMxRA1TcJyVcjIshA1SnGVMF55k/ahssGAEOLEyCI/UdMkLFeFjCwLUeNMJQeYGTOOSLNX71KEEPWIjCyLmiZhuSqK0/WuQIhGITR3PfNSpqIomt6lCCHqCem1LGqahOWqkLAsRK1JSp/P9HYL9C5DCFFPyC5+oqZJWK6KIgnLQtSm3vunMLrNBr3LEELUAxnSPk7UMAnLx+N1gSNf7yqEaHRuyBzL8OZpepchhKjjVA0KS916lyEaMAnLx1OcDsj8SSFqm6J6eK7kdfrHFOpdihCijrOVefQuQTRgEpaPRzphCKEbxVXEBNNoWoc49S5FCFGH2RwSlkXNkbB8PDJfWQhdmYv38VPceEJNPr1LEULUUYUOmYYhao6E5eORThhC6C48ZzXzWk7TuwwhRB1VJCPLogZJWD6ekiy9KxBCAMkH5jCt3W96lyGEqINsZTKyLGqOhOXjcRbpXYEQotyZaRN5pdVmvcsQQtQxhTKyLGqQhOXjcZXoXYEQ4jC357zNHU1lepQQ4hBZ4CdqkoTl43EV612BEOIwis/Ff8ve4KxoueojhPArkmkYogZJWD4eCctC1DmGsgK+sL5N8yCX3qUIIeqAwlIZWRY1R8Ly8TglLAtRF1lsu5nT5FOCjdJSTojGTjYlETVJwvLxyJxlIeqsyOy/+KXVdL3LEELorEj6LIsaJGH5eGQahhB1WqsDs/iy3VK9yxBC6Ei6YYiaJGH5WDxO8MnZqhB13Xlpn/BCq216lyGE0EmZx4fLK1OyRM2QsHwsMgVDiHpBQePu3NHclCSbCAnRWMkufqKmSFg+FpmCIUS9oXidvOF6ndMj5SRXiMZIpmKImiJh+VgkLAtRrxgceUwNeYekIJk+JURjY5NFfqKGSFg+FmkbJ0S9Yy3cwS+JE7AaVL1LEULUolK3V+8SRAMlYflY3Ha9KxBCnITorOXMbjNL7zKEELXIJ+fHoobUaFjWNI2LL76Yyy677Ij7xo8fT1RUFAcOHKjJEk6NdMIQot5ql/YjE9v9qXcZQoha4lM1vUsAIDU1FUVRWL9+fY2+ztChQxk0aFCNvobwq9GwrCgKkydPZuXKlXz66aeBr+/du5eRI0cybtw4mjdvXpMlnBpV2tCcjDeWuugzwU74G8UkjClh0DQH2/MOfS9TbSrKf4uPevthc9UWaNw3uwzlv8W899eh7Y5dXo07ZpYR8UYx7cfZWbin4iW5MctdPPxLWfW8SVEvXHTgI0a22Kl3GaIeKFk7mwMf382+t68l88vHcWVsP+bjS7ctI33Cfex7+1oyPn+Qst1/V7i/aOUM0sbdRtq42yheNaPCfa6M7WROeRRNfsdUK1WrnbA8dOhQFEUJ3GJjYxkwYAAbN24EIDk5mczMTLp27QrAkiVLUBQFm81W6fFOJvS+//77TJky5STfhTgRNT4NIzk5mffff58nnniCvXv3omkaw4YN49JLL6VXr14MHDiQsLAwmjRpwh133EFeXl7guf379+eRRx5h5MiRxMTEkJiYyEsvvVTTJR+iyTWdk/H7Pi8P9rHw17BQFtwRgkeFS792UOr2/yBLjlDI/E9Yhdt/+1sJs8DAdqbjHn/mVg9/HfDRNFyp8PXP1nhYk+Hjz2Gh/N9pZm6dXoZW/sNzb6HKhLUeXrsoqPrfsKizFE3l/oK3GNQkR+9SRB1WuvUPChZ+huouA03Da8sm+7vn8ZXajvp4+6bF5P30Jr7SQvB5MIbFkDPjNdy5qQC4c/Zi++NL0DQ0j4vCJVMC92mqj/xf3sPnKELzuI56fHFyamtk2el0kpycTNOmTTGbzQCsWbOGSy65BACj0UhiYiIm0/F/n8HJh97IyEiioqKO+ZjDQ/3B27nnnnvCr9XY1cqc5SFDhnDRRRdx99138+GHH7Jp0yY+/fRTLrzwQnr16sXq1auZN28e2dnZ3HjjjRWe+8UXXxAaGsrKlSsZPXo0L7/8MgsWLKiNsmVk+STNuz2UoT0tdEkw0iPRyJRrgthfpLEm0//9NBoUEsMMFW4zt3m4sbOZMItyzGOnF6s8PNfJ1OuCMf/rX+/WPB9XdzDRJcHIg30s5Do08hz+H573zynjrYutRFiPfXzR8CgeB+9436B7hKxBEEdn++OrCoMjmqahucsoXvPzUR9fsm42itkKBiMAitmKpUkbStbOBsCVuQNUb+BkHU2jdPMSAIpXTkd1OWRUuQbU1sjy4sWLsdvtfP311+zcuZO5c+dy3XXXkZOTQ25uboVpGKmpqVxwwQUAREdHoygKQ4cO9derqowePZrTTjuNJk2akJKSwmuvvRZ4nX/++YcLL7yQ4OBgYmNj+b//+z/s9kM/x/49In20AUaAyZMnk5mZGbj9/PPR/117PMe+sjtlypTjhvOGqtYW+H322Wds2rSJESNG8Nlnn/Hpp5/Sq1cvXn/9dTp27EivXr2YNGkSixcvZseOHYHnde/enRdffJF27dpx5513cvrpp7No0aLaKVqTH2bVoah88CQm+OhBdU2Gj/VZKsN6m495HFXzT7N48mx/EP+3Hk2MLNvvo8yjMX+3l6QwhbgQhakbPQSZFK7tdOzji4bLWJrN9+HvEW+RPqyiIs3nwWvLPOp9jm3Ljvp1T95+UIxQPjLsOrAFc3wKrvTyXSQPZmSfG01RAA1PfjqewkyK1/wPn8eJwWTxB25RbWpjZNlms5GTk0NQUBAXXHABLVq0oHPnziiKQkJCAm3btg0E3k8++YRrrrmGu+66C4AJEyYwc+ZMZs6cSVRUFJdffjlvvvkmiYmJnH/++XzzzTcYjcbACHD37t1ZvHgxFouFl156iYULF3L99dfTt29fQkND+eabb1i6dCn79u0L1PfvAUbwz6FOTEwM3GJiYgKB/rvvvqNfv34EBQUxdepU8vPzueWWW2jWrBkhISF069aNb7/9tsL3oCpX/W02G/feey9NmjQhKCiIrl27Mnv27Br8m6lZtRaWExISuPfee+nUqRODBg1iw4YNLF68mLCwsMCtY8eOAOzevTvwvO7du1c4TlJSEjk5tXRJVc78T5mqaYyY5+ScZCNdjxJwAT5f56ZTnIGzk499yeqtZW5MBnjkDMtR77+7l5keTQx0Hm/ntaUuvr8hmEInjFriZNzAIJ7/zUnbD0q47OtS0otlik1jE5S/hXnNJmE21I1FQKJu8NoLAh/HXHA3SXd9QEj7M/33Fece9Tma20lI+7NJvH0MKAYUk5XSLb/jKz+WVj5KbTAHY7QE+59kgPy57/unXnjdoChkfvEYzrRNNfjuGpfaCMthYWEoikJmZmYgu4SHh/Pzzz9z//33oygKZ5xxBuAfOVYUJTAA+L///Y9bb72Ve+65h6KiIhYvXszo0aNp27YtoaGhnHvuuVx44YUAnH/++URERDB58mRiY2N55ZVXeO2115g/fz6nn346Gzdu5IorrqBFixYoyqGBqH8PMAKBudRH8/TTT/Poo4+ydetWLrvsMpxOJ6eddhpz5sxh06ZN/N///R933HEHq1atqvC8Y131V1WVgQMHsnz5cr7++mu2bNnCm2++idF49AxQH9Rq6ziTyRSYw2O327nqqqtYv359hdvOnTs5//zzA885OB/oIEVRUNXaCjryS/VUPTjHyaYcH9OuDz7q/WUejW/+8TCs17FHfddk+Hh/pZspg4Ir/GA4nNmo8NEVwex9NJy/7wnj3BQT//nVySN9LazL8jFrm5cN94VxZjMjj8xznvJ7E/VPbObv/NSm/o5uiOrnKy0EwBASjW35t2ROeRR3zt7yOyvp26souDK2kv3tM6CpqB4XqCpa+eMVg//3nFpWHDi+5vPhtWX5H6P68Jbkozrt5E5/Fc0rVzyqQ22EZZPJREREBIqi4PF4aN++PUOGDKFPnz68++67qKpK3759AcjPz0fTtEBY/fnnnxk9ejS9evUiPj4et9vNRRddVOH4BwcDY2Ji6N27N0OHDuXrr78mNzcXt9vfocvpdHL11Vfz888/s23bNn744YfA87t3746iKMyaNSvwtZ9//hlFUTAYDISFhfHZZ5/RqlWrwPu5/fbbGTRoEKmpqTRr1ownnniCnj178scffzBmzBg0TeO2224jPz+/wutUdtV/4cKFrFq1ihkzZnDJJZfQunVrrrzySgYOHHhK3/v+/fszYsSIwOctW7bkvffeO6VjVlXVZp/XgN69ezN9+nRatmxZ5UnwtU/mt56Kh34pY/ZOL38MDaV5xNHPy37c4sHhgTt7HDssL93vJadUI+XdQ/O1fBr851cX7/3lJnVE+BHPWbzXy+YcHxOvCuLJBS4ub2ci1KJwYxczH05xnNqbE/XW2qgCPmy+E1NUE7AasFvdlBrKwAgYNVRFQ1XBpxnw+Ux4fQZUDRQfmFQvZtWHER9mnwej6kVRfRhVH0bNh0H1oaheTJqKgooBFQM+DJoPAxoGTcWo+QAVRTt486FooCn+abOqApqmgKagoaChoWn4P9b8p/CaRoWPKb+p5V88OFdWU8tP+TXN/zVVAxT/nFxNQ9HAoIGi+X/aVfi8/GM0UNAwqIe+rpQf89BjtMDz0EApv08pDy8VPj/4fFULfN1/rMM+VrXA1zja1w4et/xrqBpoauD5Bz8/+DhU9civl38TV9uKuANQHYW8ltKC7k1j+DInB3/80Jj7v6cOPb9cbzTOdxdxb2I8N+wrJd5TSrbqo4kKc2c9wcKSYh4BEo0GPJpGvs+HZe9qTOXf91IgEQVLWSH7PR5e/u4R+oaG1sC/9sYlsdd/oW9Kjb9OUFAQMTExPProozz22GPs3buX4uJiDAYDRqORiIgIADIyMnA6nfh85et1jEaGDh3K448/Tp8+ffjll1+OOHanTp0A/yi0qqpMmDCB9u3bA2C1+qftTJ48mfbt29OlSxc0TeOFF14gNjYWOHKAEaBPnz6sXbuWmJgYli5dGgjdAP/3f//HNddcw3PPPcctt9zC9u3bGT16NF988QW7d+/GYrEEQvarr74aeN6xrvqvX7+e5s2b0759e1q2bBmYJhIUFESTJk3o27cv9913X2AUvT7QLaU++OCDTJgwgVtuuSUw72XXrl1MmzaNiRMn1o3h+kpGMMWxaZrGw3OdzNzmZcmQEFpFV34B4/N1Hq7uYCI+9NgXOe7obubi1hX/uV72tYM7upu5q+eRPxycXo0Hf/EvBDQaFHyH/a7zqHWnH6eoXb+1O48xpds53+TgtlXnkp4URxw+eoa3p1TTyAspJdtXSE5pDtagUqKjNcLC3YQEl6GY3ThMFhxGMyVYKDJGU6rEYCeSEsIo0UIo0qwU+8w4vAouD3h9YFXBqoFZA7OqYFY1jCoYfBqKzx8CFZ+KVfVg1dxYVQ9m1YNF82BW3f6b5sGkujGpHiyal2CDlyCDlyC8WA1erHiwKh6seLEoHsyaBwtezHgwaYff3BhVD0bVjVFzo2leVE313/Chaj5UTcWraGiKAa+i4DOY8BmMeBUjPoMBn8F42OcKvvKvuxUDPsWA16DgO/ixouBTlMDHKgo+BbyUPwb8jwF8Cv7Pyz9WAS+a/77Axxo+TSv/WMWnHfqa/3MVr+b/08dhH2v4H6Op+DQfPtWHV/Ph03zYd7rhVTCEGvj25XC+BVRvIgz3T6m4caSC/0zKf2JgxEDw+AhWuTWKH41BHZ6KLcoI+T7KWgfx6MgoclapBE+3UmI0oADGQhelACiEJYTCATslUWZMZiNkeRjXy8LpV7RCAQyaggEFg6ZgPPgxCooGRhQMWvljFIP/BAb/1xUNDBgC9x/+eOXg/ZqCofx9HPoa/uOr/kvNBhRQtfIaDp4cKYHXCpxQUfGk6vATKUXV/O9FPfzk6tBJ08ETLEVTDp1IBU6WDn585AkXKv86wSr/evnJlCMqiOga/hlykKIo/PPPPzzyyCN8/vnn3HjjjXz33XcYDId+l2VkZJCenh4Iyx07dmTZsmX8/vvvPPLIIyxevPiINVgHs8+ZZ57J8uXLGTt2LHv27CEkJASfz4eiKPTq1Yvrr7+ed999l4KCAm6++WbGjBlDfHz8UWsNDvZfkTWbzbRt25bU1NTAfZdccgnt27fnv//9L126dOHZZ5/liy++oF27diQlJTF58mRGjBiByWSiQ4cOzJs3Dzj2Vf/g4IpXkl9++WXuuece3G43qampfP3111x88cW88sorPPfccyfx3a8eB7+fh/+dVUa3sNy0aVOWL1/OU089xaWXXorL5aJFixYMGDCgSoXXCqWO1FHPPPiLk2/+8fDTzSGEWxWy7P7/QJFWhWDzoROQXQUqf+zz8cttIUc9TscP7bxxkZVrO5mJDTEQ+6+HmQ2QGKbQIe7IE6tXfvePJPdK8t93ToqRJxc4uauXmQ9XuTknpa5ezRA1ZXOzbjytZaNqKkuC93G7L5JW25qyqemlZLtXUrh/C706XkYHYzvIbYUjwkeewUluaQk7yvLIKcgN/DJQFIiKKqVpTAkREV5CQp1YrXaMxiI0LQ+vNxufWorPEITT0owyU1McxiY4DHHYlRhKlUhKCC8P2EEU+czYfBZs3lCKfeoxJ4AZ0QjSFII1hSAOC+MqmMpvRlXzh3EVFK+K5tNQfRqaT8XnUfF6VTxeFY9HxeXxld9Uyjy+wIlkqFEl1OQjzOgj1Ogj5OCfBh/BRi8hBh8hRi9Bis8f3hUvVuXgnx6CFX+Ityhef/Cn/HZYcDdpHoyHBXjDwZvPjaK6MXhd/s2hfC6UGmrlud3moyOglao8PPsAPVOC+GiZnS34Q948Gzwy9QAJUVYevzYFn2Jk9QXJ3PXOZs6ca+MvFdz5/pG6oWckc7U1hr1tLIwo28v7b57PP9sKeO+jNZjNBlq0iCQzy3917PobupKeXszC/+0gXDHRqUlU+YkEqCh4lUMnCj40vIC7/ITBW36SoIL/hICDJwhahc8PniyoaP6TA9V/suA/UTh04uDTfGgNYNrhy619XFtLr+X1evn222+ZP38+O3bsYMWKFWiaViFE7t+/n5CQECIjI8nMzETTtMBUhEsuuYQhQ4Zw//33B+Y2d+zYMdB+bvny5QBs2+ZfNJqSksKoUaNQFIXIyEi2bt1KYWEhRqMRm83Gtm3b2LNnD8uW+RelXnvttYHpGU6nE5fLVWFE+d82b94M+NvYGY1GtmzZwl133UXr1q3ZsWMHLVu25KeffiIkJIT169ezbNkyFi9ezCeffMJZZ51V4Vjdu3fnwIEDgbna4eHhgc4cKSkpnH/++SQlJTFq1Ciuv/56OnToAMDvv//Ok08+yYYNGwgLC6OgoIDc3Fzi4uKYMmUKy5Yto2fPnpW+h7FjxzJ58mT27NlDTEwMV111FaNHjyYsLAzwd/MYMWIEX375JU8//TQ7duxg165dtGzZ8jh/27Ucll966aUKKybbtWvHjBkzKn38kiVLjvja4fNwap6MLJ+Mj1f759/1/6LiVIfJ1wQxtOehxXmT1rlpHqFwaZujX0XYnq9S5DrxH+Cbcnx8v8XL+nsPXda8vrOJJakmzptcSodYA98MPnpAFw1TRnQKD4UbKXMdmqv+dq8MXhm3mR7FuaxrdzdhSZ3Ynvs7y/Z9S2JiW3okXkSLgnhSikKBRHxmjYJ4D3mh/tHnjMJsdu924P8xGlZ+SwT8P/hDQxViYiEqykdkqIsmQaWYTZmgFODz5eDx5B9ZKKAqFsqMTXGZm+EwNKHUGOcfwVai/AGbEIrVIIpVM4U+I/leKPIeLWAf/Pl1YlfprBoEa2AuH1n0qlCm+a/IODR/EDf68I+K+4dswaeiejV8PhWfV8Xr9odxt0fF7fHhDNxOPvBaDSphJn9gDzWq/j9N5aG9PLgHGw4Gd59/5L08wAcrHqyKFwv+EXf/nx7MeMkJKgRmoAH3T7ehamAy+L93FiPEaxaWbS0hIczBRxcGofjcLN1WhNen8d4Pe4BDq1vuCdtPl53pAPySrHHPwwtQAZMCQYpKE1cRZ7VW+GojfPHJaozlf0X9i/by6Pqjd+SoLT7F4L+KYDSVXy0w4j34ucGE12CocJVBLb/K4DUYDj1eUfxXHo5ylcHHwasMSvkVB8NhVxkOXl1QKl5h4PArDhWvMqgVrjL4P45Xar7jUX5+PjabDZfL3wnlvPPOC9wXEhJC6L+m0zgcDn777Teuu+46tm7dCvhHXtu3b88ff/xBly5d2LFjB06nk/z8fPbs8f+buuaaa5g/fz7Jycns3LmTrKwsrrzySvbu3cuyZct48sknOeOMM1i1ahXNmzcPhO1evXoxZcoUNE3jf//7H+CfvmEymY46ReOgsjL/hl2XXHIJ69evp7i4mK+++gq73U52dnYgUDqdTlq3bk3v3r1xOBzccsst7Nq1C4Bdu3ZVWFPUqVMnDAYDM2fOpHnz5oSFhTFgwAAAHn30UV555RV++uknRo4cSXp6OpdffjlDhw7lyy+/5Mcff+SFF17g7bff5s0336zS343BYOCDDz6gVatW7NmzhwceeICRI0cyfvz4Cn8fb731FhMnTiQ2NpaEhIQqHVuG145FRpZPivZiRJUe9/pFQbx+jE1Cjneco81TBuiaYGTnw2EVvmZQFMZfEcz4K46+0FA0XCVBkTzYPJk8e1qFr28z55E2oDfNf1rJacX5/HPWSIqKryS5WwYFBxYwf4V/19GO7c6hQ5MzCM4PIj5DIR4LnYgGWmOP9pEf7STHWExmaS65hXmB+cKlpRqlpZC23wAEl9/igNYAmM0QG6uUT/VwERxchsVcgmIoIEjNx+NcRYxWtYVfmmLCaWx6aATbGE+pEntoBJtQitQgilULNp8RmxdsXpWjRVeX4r8FImClWVvhRAO5QdOw4h8VD9b8wdyiKVhUDbMKRhWMmobx4BQVn4ZWflO9/iDuKx8VL/CoZHlUXM5DYdzjO/GTa29JPuAftNFMQeDz4FUMgAe3NYr2WS+Tp95OoTeS1raPALDZfgC+OOJY/WYnct0jL1KavZefd7/GHQ8+wuzvvyU/N5eUth1wWoxYO7WGjbMJtloAjTKXh8jul7IpOTkw8n749Bmj6h+BN6j+EfhDo+8uFJ8bxecffVd8lY8aVoVRUzH63P6R/Pqq9U01/hIHO3dt2LABRVGwWCw0bdqUzMxMmjZtSkZGBi1btmTy5MncfffdGI1GzjjjDDZv3kzv3r3Zu3cvl156KQBpaWmMGzeOxYsXY7PZmDVrFgsXLuSXX35h4cKFOJ1OFEVh3LhxPPTQQ2RnZ/PDDz/g8/l4++23SUpK4plnnsHhcNCxY0fWrVsHwJw5c8jJyQmMTt9www2BXQQrc/XVVwNw//33M2nSJObMmYPD4cBoNDJo0CAyM/0nc1arldjYWKKjo3nqqafo0qVLICwDREREsH37dgoKCnj++eeZNWsWf/zxB3/++ScTJ04MPC4mJoaEhITAlJDx48eTnJzMhx9+WGHjlI8++ojXX3+9Sn83/1789+qrr3LfffcFwrLX68Xj8TB+/Hh69OhRpWMeJGH5WCQsC1GveQxmHu/Ul122o29d/GaHHXwUFYkpfRc9FjzLtoGvkHWgKUbz7aR030b61sVs27mcbTuXYzEH07PLpbQI6Ywh279YLKzQSFhhKC0IBZLwWDUK4z3kBtvJ9haQUZiN03n0ziseD2RlaWRlAVjLb1FAMuCf6hETYyA6WiU8wkNoiAuLtSQw1cPjyUZV/VdvFM1LsHc/wd79xFTxe6NixGVMxGluSpkxEYcxHrsSS2lgBDuUYjWIovKAXeRTsHlVvKdwtV5VFMqAMuXwgxztgIcH8aozaxDMoSBu1RQsqn+KilnzzxU3BuaJ+0fFVVcMM8oHnkwWC16nF1NQKJ5SG5bgUGJCLRz4VymuA0dv92bXrPyaF0Ppjs0Y4lqxOPQSirVZYDCxZW8mTYd+wNRF/pMwlzG4vAuGh7eKLuS9ne1P+P0eTlE0Qowq4eXTZUJNh6bNhJRPowlWvIEpNEGKlyDFQ7DiC8x7tyhe/7x3PIG572a8mDQP5sC0Gf/8eWMgwB82baY8wONzg9eFUttTOww1H2msVmtghPbOO+/k8ccfx2q1MmzYMFasWMH3339/qByDAZPJRGhoKDExMXTo0IG9e/eyZcsWMjIyuPDCCxk6dCg9e/YkPT2dkJAQ+vTpA8DIkSMZO3YsX3/9Nc8++ywvvfQSHo8Hg8GA1+vl+eef56abbuLPP//kvvvuIyoqCoPBgMFgCJywZ2Vl8ffff/Poo48CBKZhHJxDbbVaOeuss0hJSeGqq64C4N5776W0tDRwjHXr1rF3797AZihGozFw1b+wsBDwd/CYNWtWYJrDwX7OM2bMoGXLlgwbNowPPviAX3/9NdDOzuVyUVxczOTJk5k0aRKhoaGcffbZRwR6u93OgQMHjvh72L17Nzk5Obzwwgs8//zzdOrUiRtuuIH58+ezbds2iouLA+/j1ltvZfbs2XTv3h2LxXLE4sSqkLB8LKaj9/MVQtQPr/S8lL8K/6n0/hyjnY1X9Kbb1FUYivLoNOMxrNe/xb4MEzlpXYhs2gardSWZO9bg9pSxav1PrOInoqKS6N3hMuJ9zSD/UHsxs0sh4YCFBGLoQgya0gZ7tI+8aCc5ShGZpbnkFR59+sW/aRrk56v4uzWZy29hQFLgMWFhCrGxEBnpIzTMidVaitlUDEoBXm82Xm9hpcc34CPYl06wL73Ki6I0FFzGJjhNzXCYEnEY4ik1xFKqRGMPjGAH+0ewVSM2r4LNq+GppZ3VPAp40CgO/L6t7HUPhXHN4/81aGzRGl+ZA81dhpbcDHY78IZayDg3HsP0NhibNIVLmxGsgefj3Uc9astzz6PLmc2wN+3D4kUf0ynBRZ7ixYNG2wuupVnTYFZk7cASGYfm86GEhOHRVMzmU/9VrGkKpV4jpd46sDi+XLDRR1hgysyR4T2kfNrMwTnvB/88OO/9yPDuPTTvHQ8m1R/ijeUj8Io5hrDjl3VKCgoKWL16NeDvNfzFF4euMFgslsCc44Nrr5o1a8bChQvZs2cPd9xxBwBxcXH069ePBx54gDlz5lBaWkrr1q1Zu3Yt27dXPLEvKSlhyJAhjBs3Dk3T6Nu3L0ajkW+++YZXXnmFpKQkQkJCyM7O5oEHHqB79+6MGTOGXbt2UVpayq233sqzzz7LihUrAsc8uPaia9eu/PDDD6xYsYLbb78dgCeeeILLL7+cp59+mp9//pl//vH//OzQoQMbNmyosMvfwWB7vHa+4eHh3HbbbUyaNAmfz4fRaOThhx+mrKyMYcOG8fjjjzNw4EB+/fVXCgoKiIk5/im/3W4nODiY4cOHM3z4cD744AOeeuophg0bxmuvvUZMTAxnn302+fn5dO7cmVdeeYXp06ezadOmY46wV0bC8rFYjn6ZXwhR903ocTkzjxGUDxqdvIGvmzdFO5CB4nbS+tsRBN/0GtuyInEUB+GgH007daPM9huFmfsBsNky+W3lFABapPSga/L5hBdHoNkr9uVVNIXwAhPhBWG0IgxohjtIoyDeTV6QnSxPAZmF2YH5jyfKbtfwD/gYgJDyWzzQBgCrVSEmBqKjVcLC3AQHOzCXT/VQ1Tzc7hz8s0CrRkEjyJdFkC+LqBMo2WWIo8zcHKcxEYcxgVIlFrvhYMAOo1grD9g+Ezafgs2j4aqlgK0W+U8ofOn7ifjPC5g7dsUx/Ru8u3eCxd+qy5iQiCE2DqcCTgUs/S+hbM4MwoY/grFpMxw//Yhn60byBg5geSTQrQ1B9zzEwvf+g6Z5McQ3oejxR9g38n6s9zxIyfuvY4iJ858RWUy4ru+D2WL1L9wEgjTFP0VFVTBrh01RObhwMzBXvOIUFW/5ok2314e7fPGm0+OjzO1DjwZAZT4jZT4judTO7qlT6Ez/Gn6Ngwvuhg4dyn/+858K9w0aNIhvv/2W++67j/j4eFRVZcOGDYSGhtKyZUvOOOMMZs6cGQiuU6ZMwev1MnfuXNq0acMtt9wSWGjXtm1bfD7fEe3VYmNjycrKYsyYMVx55ZX8+uuvDBw4kJSUFD788EPAv4hu4MCBhISEsGPHjsBUh8jISMC/XmzIkCHYbDZatWoVaHXXr1+/wHs6OAo9depUrrvuOlJTU2nVqhX9+vU7qe9bx44dKSkpIT8/n9DQUD7//HMMBgNPP/00bdu25ZZbbuGdd95h4sSJjBw5MvC88PBwmjdvfsTxevToQXh4OElJSbRr147+/fvz0Ucf0b17d848s3xTIa//5/FDDz1EVFRUlecnH42E5WOxSlgWoj6a27E/44o3V+mxLsXHooFNuHBCBuBvRdV02rNYBz3JxqKWaBoUZMWAMpiU7vvJ2fMrTntJ4Pn79m9g3/4NGAxGunW6kDbRvTDnGP0r4o7C4lRITLOSiJWuxKIpbSmJ85EXUUa2UkSmPYcCW+UjwifC5dLIzITMTIVDUz2iAX8vWkXRiI01HjbVw4nFUoLBaCuf6pGDqpadch1WNQ+rK++EnuMxxFBmbobDmESZMYFSQyx2JRo7kdgJpUgLpli1YvOZKPIpFHo1nKeQCM3delE85mX/zq1BwVh6no5aUgyALycLDuvSVDb3J/D5sH/6boVj5D84hCY//w6AVlaGr6QISooJvu4WnAtmowSHYj3rfEo+eBM1LxclItJ/3PLWenYF/Be7D76P6puiEqT5Z81bVX8XFYtGYIrK4R1UDCqBMK75VDSvFgjiB+eLu8u7p7jKg7jLWzd2RLWaan5U/WC3iYsuuoiuXbtWuG/w4MF8/vnn3HfffZxxxhlYrVY6duyI2+2mqKgocFLscDhQFIWvvvoqsPhu+fLl/P3333Tr1o1NmzbRsmVL7HY7P/74Iz/99BMrVqwgLy+PkpISNE1j/37/ifvWrVuJi4sjPT2dadOm0adPHzZs2HDc97Ft2za2bdtGfHw8Dod/OtemTZvYtWsX+/fv5++//wY4ojtZQUHBEcc6npKSksB0tL/++osvv/wSVVV56qmnaNu2LQAPP/wwb7/9NpMnT+bqq68OfJ8feOCBo3ZIs9vtFBYW8sYbb/DSSy/hcrnQNI2ffvqJK6+8kuXLlwemjlQHCcvHYq3pCzpCiOq2NqU3z3sOnFArrE/i/uGCTm1Rth5aqBI7awynXzyUtfTF59VAU8hJa4El/C7iW24kfetSVN+hUVlV9bFh8wI2sICQkEh6dx5IU1NrlBzfMTcDVTSFiFwTEbnhtCYcaI47WCU/3k1uUAlZrgIyC7IrXP6sLpqmkJenkpcHh6Z6hANNA48Jj1CIjYHISC+hoS6s1lJMpiIgH68vB6/XVu11AZjVAsyuAiI4/tWBgzxKJGXmZjiNSf4RbEMcpYZoSojEHhjBtmJTTRR5DRR4NRyR0aAY8Gxc6x9Z7uQfWS6b/zOWXv6d2GLenVjhdeJ/+LXCrntaURH5w67H1Nx/EuLZvQP7lI+Jfu19NDRszzyCKzKKmI++xLN5PRgMxLw/CXPHLuRcewHeA/swt2536t+0Y3Aq4AQwHuv/hfKvP6u+cDMIhWAUglR/MD8Yxiu0M1QrX7jp9ap4PSru8jDu9qiBUXFvFU+Cgsw1v87ot99+A/yL8/5t8ODBjB49mo0bNxIREYHX68Vut1NWVsbZZ59NcnIyX375JW63m5CQEEpLS3G73bRv3564uDiuu+46zjvvPGbNmsXZZ5/Nfffdx6233orH4wlMpzj33HOx2WyBkd+5c+dis9l47LHHeOihh3C5XIEFhJWZNm0af//9N127dmXKlCmEh4fz6KOPsmjRIrp27UqHDh04/fTTmT9//hHP1Sq54pOamspdd90VaNN2uFGjRgU+fvjhh+nYsSPgX0x4ULNmzTjrrLPYtm0bPXr0CBzniSeeOOrrPfHEEzgcDgYPHsxjjz1GcHAw/fr1Y+XKlXTt2pXzzz+fqKioCrsOngoJy8dikbAsRH2yL641jwZ7jtlPtDJTLzJz+9aKXwtfOIW+fXNYG3s1rjJ/MHY7TeSm9ya2ZQcUbSk5e7YccSyHo4hlq6cB0CShDT3bXkx0WTyarWqB11JmIGl/EEkE0Z14VEN7iuN85IU7yFFsZBTnYiu2nfB7PBklxRr+AVYjFad6+EeErNaDXT1UwsJcBAWXYTYXoyiFqL5cPJ7c8qZfNc+sFWF2FxHBkX8nlfGaw7jGqpDQLIKXrndTathHUZeBjJo7k0STiwsjSilWrRSpJmw+A4VejdKIyArHsC+cC4qCuWMXAHxpqZhbt8PS2x+2leBgLKefhTG+CfYJ76MEBQUei8/n3yGwHlMVBQfgQDtOvj65UXHLYQs3LSpY8S/ctGiaP4iXj4iHhtX8OqN58+bRvHlznn32WZ599lnA39mhT58+jB49msLCQqKiopg+fTqKopCfnx8YGT18BzyLxcJ9993Htm3bsNlsga8f3h73448/5uuvv+bzzz8PzHdetWpVYEc/ILBt9mOPPcbo0aMBmD9/PjNmzGDq1KmB6RMAO3bsICYmhuDgYHr27MmaNWsCx3G5XHTs2JH169cD/mkm11xzDYMGDQL83SUeffTRwP0AUVFRgfB8+EYnh0tNTSUnJ4fOnTtzxRVX8MUXX1BaWkpMTAzLly+nRYsWAHg8Hvbu3ctTTz3FE088wZIlS7jgggsq7PAcFhYW2N56+fLljBo1ihdeeAHwjzSXlpYyfPjwwGNatmzJ888/T1RUVOA9DR069Kh1Ho+E5WORaRhC1Bu2kBgeaBKPzXFy/Wp/Dt/J9Wd1I+jPiiOZwat+oU/HXNZ3GI696NCc5JKCUGAAzbv0pih7ASV52Uc9bnbObubn+BeEdWh7Fh0TzyQ4PxjNWfUAaVAVonJMROVE0JYIIAVnqEpBnJscSzFZrnyyCnICc/Rqk8sFGRkaGRkKEFR+iwb8vwQNBoiNLe/qEe4hJNTfIs9gtKGpeXi82ajqyc3Zrg6auwS3y0fmvkK2T59Ah45W5k8vwmjQiPds4faiO3nzzRzi40w8M9y/8OiLr0po3TWFmBatKHCE8tbX36EoCnfediZBkTmkdWvK/97bR7viTNLXrkOzlxByw+1409Nwb9qAVubAtXIZvtxsMBgxJbfQ7f3XB27FvyFLkYJ/en4ll2qswbUTac444wzmzJlDixYtePLJJ4mPj2fs2LH069ePxMREtm7dStu2bfF4PIwbN46rrrqK5cuX88knn5zwa7Vr146vvvqK008/neLiYp588skKO+S1bt0aq9XKkCFDGDNmDMXFxZXuirdgwQISExMZMmQIa9euZdq0afTu3ZuvvvqKv//+OxCqT1VWVhaapmGz2fjzzz95/fXXiYyMDPRLDg0N5f777+fJJ58kJiaGlJQURo8ejcPhYNiwYVV6jYP7dFx11VUoisILL7xw3IWGp0LC8rHIyLIQ9YLbaOWR9j3ZX7Tr+A8+hg/PKuaJv03wr9Bp2fY3vYvz2XT2UxTkVbwvLyMBg/EWUrrvJHPHIjyVtIoD2L7rT7bv+hOzOYhenS8lJbQzxmw4mdVXQaUGmpYG0ZQgIAHV2BFbnJf8cAfZmo2M4hyKy+fc6klVITdXJTcXDk31iACaBR4TGWkgJkYjMvLgbojlUz20fH9XD1/NvY+iIh+aBoMGRTJlSiGFhV7atLHSr18o6en+v+ucHC+GwwZES0tcfDx6A4WFawgKMuC0qzz1dDyXxIwDGxADyXdb+PHBq8nO9nLrzVEMafUiTz6ZxV2PdmP1qnj+eP5RFEXhgvtvpkdCEcWah2LNWr6bo78X9vF2cxQVhRprpxNIeHg4/fv3p23btrz66qtkZmYSGRmJzWZj8uTJwKHFdP/97395/PHH0TSN4cOHM2HCBIYNG8Zff/1Fbm4uPp+Pb7/9lltuuQXwt2EDjujY0LVrV9q0acMll1wSmM978HGtWrWirKyMvn370rJlSz744IPA5h+Hi4uLo2vXrnz22WecfvrpDB8+HLPZzC233MINN9zA999/T1hYGKGhoYSFhQV21gP/iPr3339PTk4OsbGxnHXWWbz//vu0adOmwmvY7XaSkpJQFIWIiAg6dOjAkCFDePTRRwMLCQHefPNNVFXljjvuoKSkJDDtIzq6ar15xo4dy913383ZZ59NXFwcTz31FMXFNfdzQtEqm4Ai/F6Jr99N2oVo4DQUnuo9kLmFR+99e6I+XtuT2Pmrj3qfGhHL9iteJTPz6CMYwaEuQsLXkL5tpb/TQRVERjbhtI4DiPc1r9CGrjo4w1XyY13kmIvJdOaTXZAT6LFanwQF+ad6RJVP9QgOcmAyF6MoBfh8uXg8eXDULVaOLy/Py8037eeDD5rSucuhTZI++zSfjRudfPhRs2M8G94dm8uWLS4mTDxyxf7hfp1fwvLlpYwYEcfQoQf4aHwz8nK9vPFGDl99nYLFcuT0BE0xUWZsRpmpGQ5jAg5DPA5DLCVKJHbCKdZCKdGCsKlminxGCr1QXMlmM43Bvn7dsR5lMVh1Gzp0aGATEfAHxCeeeIJFixaxfft2DAZDYPpDy5Yteeedd+jVqxdBQUGoqsq3337LxRdfTEREBHPmzOGxxx5jxYoV9O3bF5/PR67/zBLwj9JefPHFPPDAA7z88suBXsYHp2689NJLzJo1q8L0iMMdrGPdunX07NmTsrIyRo0axdtvv83cuXMZMGAANpuN9u3bM3z4cO68807Kysp46qmn8Hq9gTnaB6eVdO/eHbvdzqhRo0hNTWX9+vUV3u/B12loZGT5eCxhUHbiqz+FELVjXM/LmVuFFnFV9Vb3VMYsDUFzOI64z1CcT4fpI7BeP5rUjCN/fJaVWikrPZvE9l3wlC4m/8Ce475eUVE2v63092ptkdydrinnE14ceUQbupMRVGKgWUkwzQimF03wmTphi/eSF1a+ZXdRDvbS6lsxXlOcTkhP10hPP3yqRwzQEgCj8fCpHm5CQpyYLcUYDDZU1b+Bi6YdfdAjMtKIwQCFhRVPIgoLfUTHHHuksqxMZfESO0OHHLsvbFGRjy+/KuTdd5uydZuL5s3NgZvXq3HggIfWrY+cb6toXkK8+wjx7iP2mK9wiIoRl6kpzsBujgmUKjGUKFGUEk7xYZvNHAzYRV61lmaV1xyrQamVoHzQ7NmzA4vQSktLSUpKYvbs2Ud0bhgxYgTXXXddha8dvmjt4YcfZv78+Xz//feBHsqJiYmAf2vpQYMGcdZZZ/HSSy+dUr1nn302BoMBh8OBpmmcdtppXHTRRQB8+OGH9OrVq8JOeZMmTSI5OZkdO3bQvn17Bg8eXOF4kyZNIj4+ni1bthzRFaQhkrB8PFYJy0LUVTM6X8yEouoLygCpJhu7L+9N6x9XHfV+g9tFq29HEHTjK2zLPvolQ1tOJBrXkNw9nfzUX3FUcTHevrSN7EvbiKIY6NbpQtpG98Kca6q0Dd2JMnoVYjPNxBJFB6KAVjgiVfJjnOSYiskqyyO7ILdG5/7VBJ8PcnJU/FewLeW3CODgaK9GVJTx0FSPkDKs1lKMpiKs1nzad8hm7boyzjk3FABV1Vi3roxrBkUe9fUO+uP3UjxuuOjiY0/Z+3h8PoMHRxIfb2L7dhfew7bl9q/vq74LvAZ8BHvTCPamneBmM0mUmZpSdthmM3YlCjsR/hFsgrD5LBQFNps5td0cq1t4LU3BOOiCCy7g448/Bvw72Y0fP56BAweyatWqwKI1gNNPP73C83w+H6+//jrff/896enpuN1uXC4XISEhR7zG3XffTUlJCQsWLDhq+7QT8d1339GxY0c2bdrEyJEjmTJlSmAnwg0bNrB48eKjdrLYvXs37du3Z+fOnYwaNYqVK1eSl5cX+Bmxf/9+CcsC2ZhEiDpqRaszeMV5/JHbk/FGmy18HheLmnf0tkOKptH0u+exXvMfNha3PuqMCwWF3LTmmIKHkNJiC+lbF+Or4gI8TVPZuGUhG1lISEgEvToNpJm5zXHb0J2MkCIDIUUhJBMCJOIz+7fszgstJctXSEZhNo6yI0fZ6xcFm03Ff+XaiH8nxDCgCQBdOofz00+ziIm+kO49kvh1/gqcThNXX30RQUFlvPzyX8TEeBk+vOII8ty5JZxzTgiRkZUHtTWrHRw44GHkU/EAdOhgJW2/h1UrHeTkejEYIDm5djbtqIx/s5kMgnwZRFdxraWGgtuY4B/BNiUdFrCj/QGbUEq0YIrKA3ZhDe/mGFkLPZYPFxoaGugRDDBx4kQiIyOZMGFCha4XoaGhFZ43ZswY3n//fd577z26detGaGgoI0aMOKKDz6uvvsr8+fNZtWoV4eGnnkOSk5Np164d7dq1w+v1cu2117Jp0yasVit2u52rrrqKt95664jnJSX5dwy96qqraNGiBRMmTKBp06aoqkrXrl1PqvNQfSRh+XikI4YQdc7OJh34j7kYr6dmuj8UGZysvLwjfb48do/O2J/e4fSL7mSt4Sx8lYz+et1Gcg50Iyq5LWbjCrJ2HX/DgMM5HMUsX/MdAAkJrejZ5hJinAlVbkN3oowehbgMC3FY6Eg00Bp7tI/8aCc5xmIyHbnkFuRV2m+1PuratSsOh4MZMxbz5Zd2EhMTuemm21m7xj8yvX3bP8TERLFj+7VER2uEhbvJz0tn06Yveffdc7BYjOVTPSr+nbhcKuPG5fP8CwkYylcIxsebeOihWMaMycVsVhj5VAJWa+1NH6guChpWXzZWXzaRrnVVfp7LEIfT3IwyYyJlxgTshwXsEsL8AVu1UOQzUXgCuzlGmfXd5ltRFAwGA2Vlx97EZ/ny5VxzzTWB7aVVVWXHjh107tw58Jjp06fz8ssvB3b2q27XX389o0aNYvz48Tz22GP07t2b6dOn07Jlywqt2g7Kz89n+/btTJgwgfPOOw+gwiLDxkDC8vHIxiRC1Cm5EYk8GBuGvSz3+A8+Be823ci3rVLQ9u4/5uPCF31J3z45rI0fhMtR+czPUlswcBHNOvfEnr+Qouz0E64pJ2cvv+Z8BkD7tmfSMfEsQk6wDd3JCCs0ElYYSgtCgSS8Fo3CBDe5waVkeQvJLMymzHnqO/3pqW/fvvTt2/eo9x3szZqdrZGdDf5pHq148cUXsdlg0UJQFIiKMhAToxIR4e/qERZmZ9p3RWhaHl5vNj5fKQCXXxHB5VdEHPW1GrqDuzlGUvWTRo8hmrLygO0wNqHUEEtp+W6OxeUBu3Vo7Z5wuFwusrKyAP80jA8//DAwQnss7dq148cff2TFihVER0czduxYsrOzA2F506ZN3HnnnTz11FN06dIl8BoWi4WYmGPPja8qRVF45JFHeOmll7j33nt58MEHmTBhArfccgsjR44kJiaGXbt2MW3aNCZOnEh0dDSxsbF89tlnJCUlsX//fp5++ulqqaW+kLB8PMFVnfUlhKhpDksoD7VsT2ZJao2/lldRmX1ZFFd8cuywDBD89zz6tM9jfad7KvRiPpr8zFgU5UZSuu8he9dCXI7Sk6pvx66/2LHrL8zmIHp2voQWoV0w5gC+mh/xNbkV4g9YicdKZ2LQlNbYo1Xyo8rINhaRZc8jt/DEtrfWw759+1ixYgUZGRnY7XZuuummwO5ilfF6vfz+++/8888/2O12wsLC6NevH7169aKwUGX16t388ssv2O12OnbsyNVXX43R6G/BZTC4GD/+M1566TZatgomKKgUs6kYlAJ8vhw8nurZbayhMauFmF2FRFB5x5uk4OuAMbVW07x58wJTFMLDw+nYsSM//PAD/fv3P+bznn/+efbs2cNll11GSEgI//d//8egQYMoKioCYPXq1TgcDl599dUK0zn69evHkiVLqq3+IUOG8Nxzz/Hhhx8ycuRIli9fzlNPPcWll16Ky+WiRYsWDBgwAIPBgKIoTJs2jUceeSSww98HH3xw3PfakEjruOP59XlYMU7vKoRo9FTFwKM9L2WJreq7s1WHb39pi3HDtio91pfUin/OfZqC3KpND7GGeAiPWk/6luVo2qkvqouMbELvjgNIUJtDXs1MUakqT5B/05Tc4FKyPQVkFGbjcum3+cjR7Ny5k7S0NJKSkvj++++rFJanTZuG3W7nwgsvJCYmhpKSEjRNIyUlBU3TePvttzn33HNp06YNP/zwA3369AmMWM+ePTvQo/ZozOaDuyFqhIW7CA72b+CiGApQ1Xw8npwjpnoIv5SU4bRr+4zeZdSof7es69+/Pz179gzsWHeyWrZsyYgRIxgxYsQp1whHtqtrCGRk+XjCm+pdgRACGN3zcpbYNtb6607upzJ8o1KlvsnGzL10n/cM2698lczM4z/e5TDjcvQhvm0nNPfv5O7bfkq1FhVls7i8DV1K8650bdGfiGpqQ3eizE4DTQ4E0YQguhKLprSlJNZHfqSTbMVGpj2XfJu+nYYOLniqql27dpGamsqjjz4a2EXt4Fa6AA6HA4fDQZ8+fTCZTLRv3z7QMzctLY2MjAwuv/zySo/v8UBWlob/yru1/BYFJAP+qR4xMeUt8iI8hIa4sFhLMBr9Uz08nmxUtb4vxjw5FnP1TFE4ntzcXEaNGsWcOXPIzs4mOjqaHj16MGrUKM4555xaqeGgGTNmBDpaHM2UKVO46667AP/UiyZNmnD++eczZswYUlJSAo/7+++/j1iIKCqSsHw8EUl6VyBEoze12wCm6hCUAX4N3cPN5/ck7PeqLWIylBTQYfpjBF3/JnszjuydezTFeWHAFSR37U1hxgLsBac+hWH/gU3sP7AJRTHQteMFtI3tjSWn+trQnShFU4jIMxGRF0YrwoDmuINVCuI95FpLyHTnk1mQjcdTd0dOt2/fTtOmTVm+fDkbN27EbDbToUMHLrjgAsxmMyEhIYSFhbF7925at27N/v376dGjBz6fjzlz5nD11VefUgswTYP8fJX8fDi0G2IYcOj3VFiYQmwsREb6CA3z74Z4cKqH15uN11t4it+Fusliia+V1xk8eDBut5svvviC1q1bk52dzaJFi8jPr/0pNFWZwxwREcH27dvRNI29e/fywAMPcMMNN7By5crAY+Lja+d7V59JWD4eGVkWQleL253L6NKqTYOoKe+ens0LK8z+ob8qMLhdtPrmMYJufIWtOVUf8cpNT8Jouo2U7jvI2LYIbzW0ZdI0lX+2LuIfFhEUHMFpnQfQzNy2RtrQnShLmYHE/VYSsdKNOFRDe0pifeRGOsihiMySHAqLbPoWeZjCwkL279+PyWTipptuwuFwMGfOHMrKyrjmmmtQFIUbbriB+fPnM2/ePNq2bUuvXr1YtmxZoNPApEmTcDgcx1xQeCrsdg27HcAAhJTf4gF/VwWrVSEmBqKjVcLC3AQHOzAHpnrk4XbnQD3coqQ2wrLNZmPp0qUsWbKEfv36AdCiRYsj/h7Hjh3L5MmT2bNnDzExMVx11VWMHj060Mf4aLvuvffee7z33nukpqYC/n7MTz75JJMmTcJoNDJs2LAjOtBUZRqGoiiBTU6SkpIYNmwYjzzyCMXFxYHtpw+fhnH33XeTk5PD7NmzA8fweDw0a9aMN954g2HDhjFv3jxeffVVNm3ahNForHTr64ZEwvLxhCfqXYEQjdbmpl15ilzUapjPeyr+seSQdVkvEmf/fULPS/r+BaxXP8aGkrZV3f0an9dITlonwhNbERz8NxnbT+w1j8VZVszyNd8DEB/fkl7tLiHG2QStsG6M5hpUhchcE5G5EbQlAkjGFaqSH+cm11JClss/+uytYr/q6qZpGoqicN111xEU5N8a+7LLLuP777/n8ssvx2w2k5KSwj333BN4Tn5+Phs3buTee+9l8uTJnHHGGbRr147x48fTokULmjRpUqvvweXSyMyEzEyFQ1M9ogH/ZXlF0YiNNR421cOJxVKCwWgrn+qRg6rWvc4nVmtCjb9GWFgYYWFhzJo1izPPPBOr1XrUxxkMBj744ANatWrFnj17eOCBBxg5ciTjx4+v8mu98847TJkyhUmTJtGpUyfeeecdZs6cyYUXXnjS9efk5DBz5kyMRiPGSjZxGT58OOeffz6ZmZmBBYyzZ8/G4XBw0003Af4dCx9//PEKW19fe+21ga2vGyIJy8cTngQo6D4EI0QjkxmdzEMRJspcxXqXAsAbnXfxwe/haCUlJ/S8mJ/f5fQLb2ed6Ry8JzAFoqwkiLKS80jq2A1n8SIKM/adaMnHlJubyq+5EwBo1+YMOiWdTUhBMFpZ3RpVtJYaaFoaRFOC6EE8qrEDRXFe8sIdZGMjoyiH4pLa+TcSHh5OeHh4ICgDxMXFAVBcXExs7JGbUs+ePZtLL70UTdPIysqiS5cumM1mWrZsSWpqaq2H5ePRNIW8PJW8PDg01SMcOHSVNTxCITYGIiO9hIa6sFpLMZmKgHy8vhy8Xlut110bYdlkMjFlyhTuuecePvnkE3r37k2/fv24+eab6d69e+Bxhy+Ua9myJa+++ir33XffCYXl9957j2eeeSawVfYnn3zC/PnzT7jmoqIiwsLC0DQNh8M/n/2RRx6pdI7y2WefTYcOHfjqq68YOXIkAJMnT+aGG24IjIw3xq2vJSwfj8kCIbHgqPttkIRoKOxBETzQPIU8e5repQRkGkvYekVvOk47+jbYxxL+29f0PS2HtU2uw3mMXsxHU5gdBVxHcvf95O5ZgNNe/cFw5+6V7Ny9EpPJQs/Ol9IyrGuttaE7UQafQnS2mejsSNoRCbSgLFylINZFjrmYLGc+WQU5+HzVH/qTk5PZvHkzbrcbi8U/Hz0/Px9FUQKXtA+3du1agoOD6dChQ2CzCp/Ph9lsxufz1duNXUqKNfznJ0YqTvXw72hntR7s6qESFuYiKLgMs7kYRSlE9eXi8eSiVeNUD4PBgtlcO21eBw8ezBVXXMHSpUv566+/mDt3LqNHj2bixImBftwLFy7kjTfeYNu2bRQXF+P1enE6nTgcjqNua/1vRUVFZGZmcsYZZwS+ZjKZOP3000/430x4eDhr167F4/Ewd+5cpk6dymuvvXbM5wwfPpzPPvuMkSNHkp2dzdy5c/ntt98C9zfGra8lLFdFRJKEZSFqiddg4vFOZ7DLdmqdIWrCmy3+4YukJmiZ2Sf83KA1v9KnbS7ru95PyQnvvqeQm9YCS/hQ4lv+Q/rWP1BrIAx6vW5Wb5zNamYTGZFAr44DaKIl696G7niCSww0KwmmGcFAE3ymThTFe8kLdZClFZJpy6ak1H7E89xuNwUFhzpyFBYWkpWVRXBwMJGRkSxcuJCSkhKuvfZaALp168Yff/zBTz/9RP/+/XE4HCxYsICePXse0ZWgtLSUpUuXcvfdd/trDA4mLi6Ov/76izZt2rB3797AbmgNjcsFGRkaGRkKEFR+iwZaAGAwQGxseVePcA8hof4WeQajDU3Nw+PNRlWr3mbQaq3d6ZJBQUFccsklXHLJJbzwwgsMHz6cF198kaFDh5KamsqVV17J/fffz2uvvUZMTAzLli1j2LBhuN1uQkJCMBgMR4TemlrYajAYAttyd+rUid27d3P//ffz1VdfVfqcO++8k6effpo///yTFStW0KpVqwr/Vhvj1tcSlqsivClk/aN3FUI0Cq/0vIw/C+vm/zeHwcMflzfnvM9PPCwDmHeto1fJa2w+/1nyq9iL+XBup4nc9F7EtOiAUVlG9u7KN2k4VUXFOSxZ9SUAyc260K1FfyLsUWgldTs4Axi9CjGZZmKIpD2RQEsckap/y25zMVll+WQX5JCRkcEXX3wReN6vv/4KQI8ePRg0aBB2uz2wWQT4d1G74447mDt3Lp999hkhISF07tz5qPNI582bx1lnnUV4eHjga4MGDWLWrFmsWrWKs88+m2bNmtXcN6EOU1XIzVXxd9U7ONUjAjj0/YiMNBAToxEZ6d8NMTDVQ8v3d/XwHbrCEmTVdyF+586dA72P16xZg6qqvPPOO4H5u99//32Fx8fHx5OVlRWYAw9UWOwXGRlJUlISK1eu5Pzzzwf8m+GsWbOG3r17n1KtTz/9NG3atAlsc300sbGxDBo0iMmTJ/Pnn38G2s9B4936WsJyVUj7OCFqxcQelzOjjgblgz6M38B57VvBjr0n9XxT9j66zX2KHVe9TkYVejEfjb0wBLiUZl16UZKzgOLcrJM6TlWlpW8mLX0zimKgS8d+tIs5DWuuGU2nNnQnI6TIQEhRCMmEAIn4zJ0p7H0Ot583mGxfARm2bEodFXsUDxo06IjjxMXFcccddxz39f49rxOgWbNmPPjggyf7FhqVoiIV/3mKEQgtvyUA/r7YQUH+qR5R0SoREVXvlX0q8vPzueGGG7j77rvp3r074eHhrF69mtGjR3PNNdcA0LZtWzweD+PGjeOqq65i+fLlfPLJJxWO079/f3Jzcxk9ejTXX3898+bNY+7cuRWm8jz66KO8+eabtGvXjo4dOzJ27FhsNtspv4fk5GSuvfZaRo0aVaHjxb8NHz6cK6+8Ep/Px5AhQwJfb6xbXzfMZYvVTdrHCVHj5nbszwfFm/Uu47g0BX645PjzDo/FYLfR/ocRtG56apct8zPi8Wg3k9L9SsxBwad0rKrQNJVNWxczc/nbzNo/jrTo3WiJRv8a6HrG6FGIy7DQcWcU/fa05paCs7g5qD+XNj2TnsmdaRKbEBj1E3WP0wnp6RqbNymU2pvXymuGhYVxxhln8O6773L++efTtWtXXnjhBe655x4+/PBDwH9VYuzYsbz11lt07dqVqVOn8sYbb1Q4TqdOnRg/fjwfffQRPXr0YNWqVTzxxBMVHvOf//yHO+64gyFDhgSuUBycDnSqHnvsMebMmcOqVZWvv7j44otJSkrisssuo2nTQxnIYDAwbdo01qxZQ9euXXnssccYM6b2thnXi2x3XRVrv4SfH9a7CiEarHXJvRhuKcGt1p85b18v7IDl71MP95k3/petOXGnfJygUDeh4WtJ3/ZnlXYbrE7xcS3p2e5iYl2JdaYNXXXwWjQK4z3khtjJ9hWSUZgdWKgn6o5BgwY1mG2V6wq73U6zZs2YPHlyoCNHYyZhuSp2/wZfVc8ZnRCiov1xrbgtNgybu+j4D65DznUm88j7+/wTME9R4VWPsr60PdXRTjoyvhhv2WLy03af+sFOQrvWff1t6ApD6lwbuupgj/GRF+Ukx1hEZmkueYX59barRUNx11130aJFC73LaBBUVSUvL4933nmHadOmsXv3bkwmmbErYbkqbGnwXsNshyKEnmwhMdzeuj37SjP0LuWkfPZ3D6IWrqmWY9n738pay3l43aeemDU0EppnkL//VxxF+mxvbDRa6NnlElqFdcWYo9TJNnTVwWPVKEhwkxtkJ9tbSEZBFi5X1Ts5iFP32GOPERkZqXcZDUJqaiqtWrWiefPmTJkyhYsuukjvkuoECctVoWnwejPwlOpdiRANhttoZXi3c1hXtEvvUk5aO28sr39YhFbmrJbjOXtfzNqkG3CWVk/HCZPZR0ziVtK3LsZXQ62pqiI8Ip7eHQeQSAqcRBeQ+kRTNEpiVfIjy8hWbGTac8m3FRz/ieKkGI1GnnvuuQa7c5yoGyQsV9Wn/SBzvd5VCNEgaCg81XsgcwtrrvVZbXl7W29SZp74RiWV8bTpyfpuD5xEL+bKhUQ6sZr/JHPnumo75slq3qwz3VteQERJ/WhDVx3cwSoF8W5yrXayPPlkFuQ06J60tSk2NpaHH5Y1RaJmSViuqhn/Bxu/07sKIRqED3pewYSiut0irqri1FA+/kxBK7RV2zF9CSls7v8ceTnVGyZjEgtwFC7ElnWgWo97UhSFLh360T7udH8bumqYfnIsH/75NXN3/MHugn0Emayc1qwrz/a7jzaxKZU+Z3vuXt5Z9jn/ZO3gQHEWL174EMP73FjhMTM3/8obv3+Kw13GDd0u58WLHgrcl1aUyW3f/Yc5QyYQbj20vbBq0CiJ9ZEX4SBbKSKzJJdCnabL1HcdOnTglltu0bsM0cDJdYuqimuvdwVCNAgzOl/cYIIyQJ6hlHVXVG+fV2POfrr+MpJm1dy1siArBpf7BlJ6XIs1NKx6D36iNI3N25Ywc9nbzNo3jv013Ibur7T1DOl9LT/d/gnf3DQWr8/Lbd//B4e78u4WZV4nKVFNebrfvSSExhxxf4HDxpPzRvP8BQ/w9U3vMHPLryzctSJw/3O/juWZfvdWCMoABlUhMtdEm90RnL0rmcHZvbnDcCFXJJxDn5TuJDdpJouqqig+Pl7vEkQjIP8bqyq+g94VCFHv/dmqL6849+hdRrV7p/lGvk5uhpaWXm3HNNiLaPf9YwTd+Aa7M4Kq7biappCzvxXWiLtJaLmeA1uXoVVDR49T4XTa+XPtj/wJxMWl0LPdpcRVcxu6r298u8LnY694lp7jrmZj9nbOTO551Of0TOpEz6ROALz5+6dH3L/PlkGENYyrO/kXQZ2V0otd+fu4uO3ZzNqyEJPBxMAO/apUn9WhkLQ/iCSC6EE8qqEDRfFe8sPLyMZGRlE2RSXFxz9QIyNhWdQGGVmuqjgJy0Kcil1NOvAfsx2v1vDmqboUH78OqP5f2gavmxbf/IfO8bnVfmy300RuxunEt76HhJadqv34Jysvbz8L/5zItLWvsoZFOJq5UIKN1f46xS47AFFBEcd5ZOVaxSRT5nGyKXsHhWXFbMzcRsf4NticJby99HNevWTESR/boCpEZ5tpuyuCc3alcENuH243XcDAJmdzWnI3miU0xWis/u9LfRMXd+o9yquDoiiBLa9PVv/+/RkxYsRJP3/o0KFH3XVSnDoZWa6qmNZgMIPacBruC1Fb8sKb8EBsGCVl1R/66ooJcZu4qEs7DJt3VvuxE394CeuVD7PB0QlVrd5lJsX5ocBAmnfthS1jAfaCuvN3tGvvanbtXV3ehu5iWoZ3w5R96m3oVE3lv4vG0adZNzrGtz7p40QFhTP2imcZMfs1nF43g7teRv/WfXnilzcZ2vta9hdlcvf0Z/GoXh4/5y6u6Nj/lOoOshtoZg+mGcFAAj5jR4riveSFOcjWCskoyqHEXnJKr1Hf1NbIcm5uLqNGjWLOnDlkZ2cTHR1Njx49GDVqFOecc06t1CD0I2G5qowmf2DO2653JULUK2WWEB5q3ZHM4r16l1LjvrrQyJAa2rE7evY4Tu93E2ut/aulF/O/5aUnYjDdRkr3HWRsW4TXXXd6Bft8btZs/IU1/EJ4eBy9Ow0gkRYn3YbuuV/fZXvuXmbc9uEp1zaw/fkMbH9+4PM/969na+4eXrlkBOd+dgsfXvUiCaExXPXlvZyR3IO40OhTfs2DjD6FmCwzMUTSnkigJWURKnmxTnJNJWQ588jKz0HVeZpNTYmMjMRisdTKaw0ePBi3280XX3xB69atyc7OZtGiReTn59fK6wt9yTSMExEvi/yEOBGqYmBkl/PZ3AiCMsCcsF2UndO9xo4f9vt39M35gaDQmhnnUL0GctI6Ep44nGYd+9bIa5yqkpI8fl/1Nd+teo1lrp8oTipGiaj69+P5Be+yaPcKvrvlPZIiEqq1NpfXzfO/juXNy/5DamE6PtXHWSk9aRObQquYZNZlbqnW1zua4GIDyXtD6L2zCZendeFOd3+ujTmPc5NPo13T1oSGhB7/IPVEkyZNauV1bDYbS5cu5a233uKCCy6gRYsW9O3bl2eeeYarr7468Li8vDyuvfZaQkJCaNeuHT///HOF42zatImBAwcSFhZGkyZNuOOOO8jLy6v0defMmUNkZCRTp04FIC0tjRtvvJGoqChiYmK45pprSE1NrZH3LCqSsHwiZN6yECdkTK/LWWKr+YBQl4w7wwY12MkgaP1v9Nn6ERHR5hp7jbISK/nZ55LUYRgxzVrV2OucqvSMbcxd8THTNr7OJstfuJp6USxH/7WmaRrPL3iXeTuW8t3N75ESVc2tRoAPVnxJv9Z96ZbYAZ/mw6se2u7bq3rx6TDCa/IqxGZY6Lgzin57WnFLwZncEnQBlyadSc/kzjSJTUBRaqgFSQ2rrbAcFhZGWFgYs2bNOubujP/973+58cYb2bhxI5dffjm33XYbBQX+DWlsNhsXXnghvXr1YvXq1cybN4/s7GxuvPHGox7rm2++4ZZbbmHq1KncdttteDweLrvsMsLDw1m6dCnLly8nLCyMAQMGSM/uWiDTME6EdMQQosqmdruMrws36l1GrVttzSD3kp7Ez11dY69h3rORXiUvs/mCF6q9F/PhCnMigUEkd08jb+8CykqKauy1TommsXn772ze/jvWoFB6dx5Ac2t7DNkqlE9vfm7Bu/y0ZSETr3udUEsIOXb/5fNwaxjBZisAI2a/RmJ4HE/3uxcAt8/DzrxU/8eqhyx7HpuzdxJiCaZVdPMKJezIS+V/235j3tDPAWgT0wKDYmDahtnEh8WyO38/PZI61sI34/hCbQZCbaGkEAok4bVo2OI95IaUkuUrIKMwm7Kyylvq1RW1FZZNJhNTpkzhnnvu4ZNPPqF3797069ePm2++me7dD11JGjp0aKDn8+uvv84HH3zAqlWrGDBgAB9++CG9evXi9ddfDzx+0qRJJCcns2PHDtq3P3Tl+qOPPuK5557jf//7H/36+bupfPfdd6iqysSJEwMnN5MnTyYqKoolS5Zw6aWX1sa3otGSsHwi4uvGDzoh6rolbc9ldGnjnd8/umsqb/8RilZaWmOvYcw9QNc5T7Lrmjc4kFFjLwMo5KalYA4dSnKLTaRv/R3VV3c7mricpfy5djoAsbHJ9Gp3KXGeJL5aNwuAG799pMLj37n8GW7sNhCA9OLsCqOs2fY8BkwZFvj801XT+HTVNM5M7skPt34Q+LqmaTw9bwyjLnyIEEswAMFmK2Mvf4bnF7yL2+fhlUtGkBReN9ucmdwKcekW4rDQiWigDfYYH/lRZWQbi8kqzSW3MJ+6todZbYVl8M9ZvuKKK1i6dCl//fUXc+fOZfTo0UycOJGhQ4cCVAjOoaGhREREkJOTA8CGDRtYvHgxYWFH9jffvXt3ICz/+OOP5OTksHz5cvr06RN4zIYNG9i1axfh4eEVnut0Otm9e3d1v13xL7KD34nweeGN5uCt+2fcQuhlS9MuDA31UtbI/5+8vqs3bX+ovm2wK6MZTaTd9Ca7MoJr/LUAwqLKMBmXk7Wrfl01aN3qNLo0PZdQWyiaw3f8J4gKPFaNwng3ucGlZHsLyCjIxuly6laPyWTi2WefxWDQbzbp8OHDWbBgAfv27UNRFGbOnFmhdVtUVBTvvfceQ4cOZeDAgYSEhPDWW28dcZykpCRCQ0Pp378/4eHhrF27lquvvprx48cHTt7uv/9+1q5dG5i/fLj4+HgiIyMZOnQoNpvtlFvYiSPJyPKJMJqgaU/Y/6felQhRJ2VGJ/NQpJkyZ+NqX3U0b7XZwsT4OLTcyhfwVAfF5yXlmyew3jCKzbk1P9JmtwUDF9OsSw/suQspysms8desDnv2rmHP3jUYjSa6d76E1hHdMeUo4JXxoqowuxQSDlhJwEoXYtCUNpTEqORHlpFjKCKzNJe8wtrrDJGQ8P/t3Xd4k2XbBvDzyWya7r3poqW7lCV7apkiuEUBRV8VFBeK83Ur4npVFCfDwRDB8akgqCDIkj3LKi20dO/dpEm+P6rVSgstbXNnnL/j6KFNnnE+BdIrd+7nun2EFsoAEBsb2+bCNCUlBatXr0ZoaOgFV2eMiIjA66+/jmHDhkEul2PBggVN+69cuRI+Pj5wcbn03uB0aXiDX3sF9hKdgMgiVTm4YGZQCArrSkRHsQjlUh12jAs12/l8Vz2HFO1RyGTmuVmrOMcbOsP1CEm8EiqNo1nO2RkMhgbsO7QWq7e+gh9zP0KuVzbgw3Gj9pJMElyK5Qg77YR+pwJxVW4ypmIEJvgMRL/gZHTzC+7Stm4BAZ1/g2ZriouLMWLECHz++ec4ePAgMjIysGrVKsyfPx8TJ05s0zFmzZqFkpIS3Hjjjdi1axfS09Px008/4dZbb4XB0PyTjqioKGzcuBGrV69uWqRkypQp8PLywsSJE7FlyxZkZGRg06ZNmD17NrKzszv7kulf+ArRXkG9RScgsjgNMgUejOmHU2X2O0+5Jf/zP4Dl4d2A02fMcj63H95Fn8HXYo9mRJf0Yv43k1GGgqxIaDy7wcdlL86lbYfJZD09fSurirF5V+PH2oEB0UgIHQG3ag+YKix3TrYlU9VJ8D3rAF84IAGeMEndUellQKFLDQqkcuRWFqKkvLRTzhUYGNgpx2kLJycn9OvXD2+++SbS09Oh1+sRHByMO+64A48//nibjhEQEICtW7di7ty5uOKKK1BfX49u3bph9OjRLY6QR0dH49dff20aYX799dexefNmzJ07F5MnT0ZlZSUCAwMxcuRIjjSbAecst1d5NvBmnOgURBbl6ZRxWFN6SHQMizSlLAYTF5r3Z1OfNAx7g29EbZV5iz5Xr0oY6jeh6Gznr2JoNpKE2KjBiPLuA4dCFUxmeNNhT+odTSjxrkehqgq5uiLklRRAr2//yrizZs0y2+p9RCyWL8Vr0UBVnugURBbh46SxeKvisOgYFm3Zuu5Q7Esz6zn1oXE4mHIfykvaX4h0lHdQDkqy1qO6zLqn5KhUjkiJG41gh2jICowA6+ZOZ5SZUOFtQJFzDfJRhpyKApRXXLhFoVqtxqOPPmq1/aHJ+rBYvhQrpgDHvhedgki4tT2GYW59Bkzgy8iFjKgJxV1vpwNmfrk1eAXi6MinUJhv/u4PcqUBnr7HcO7YRhj01r9ogqdHEHpGXQEvfQBMAt6A2JM6JyOKPetRqKpEXn0x8koK0NDw96ck4eHhmDp1qsCEZG9YLF+KLW8AvzwrOgWRUPuCe+J2VSV0RusvhMzhkx0JcN64z+znNWqccGrSK13ci7l1Wtc6qFQ7kXtij5gAXSAsNAVxgYPhVOYEUw3nN3c1g9yEcu8GFDnVIN9UhpCoUAwcOkh0LLIjLJYvRcYWYOl40SmIhDnrFYYpnk4o01noim4WKE7ng2feKYJJwNK0jb2YX8apHHFdK9z9SlFX9gtKc88Ky9DZ5HIFEmNGIdw1iW3ozMhzehw0PTxExyA7wmL5UtRXAfOCASu665uos5Q5euDm8CicqRY0VGnF/nckBQHfdf1CJa0puOZJHC7yF3Z+SCb4BJ1Bfvp61FdXicvRBZyc3JESMwb+sjCgC5cgt3sSEPB0f8gc2MyLzIfF8qV6bwBQcER0CiKz0snVuCNhIPaWnxIdxSr5GLV4930TTOUVwjKUjb0b++sTYDSIe+lXavRw8ziE7KObYTLa3qBDgH8UEsNGwq3GA6ZyFs6dSemnhe/9KaJjkJ1hsXypvrsX2Pup6BREZmOChLkpY7C2lJ0vOuLpMymIWyZudBkAqgddjb3aUdDXiy1UnT2qIZm2oOD00Q4f65e0UziUnYfCyioo5HKEerpjXGIP+Lg4XXC/zScysD39DEpraqFVqZAY5I+xidFQyuUAgL1nzuGHg8ega2hAn7BgXJkc27RvSXUNPvztD9x/+UA4KJXnH1ySENN9EKK8+0JTrIJJ8M/bFmgv84f7VZGiY5Cd4Qp+lyq4n+gERGb1TvJYFsqd4JWQg5AC/IRm0P6+Gn1yl8HRSexH2ZUlWlSUjkZQ/M1w9vTp0LFOF5ZgYGQ33DtyIO4c2g8GkxEfbv4D9Q2tj+zuPXMOPx48hstju+OR0UNxXZ9EHMjKwdpDjYvrVNfr8OXug5iQFIM7hvbDnjPncDQnv2n/NXsOY1xidMuFMgCYTEg7sQXfbn0da06/hUy3EzD6yfibtwPUoVyAg8yP/2QvVfgw0QmIzObr2FH4qJyLjnSGOqkBG8eab6ne1jgc3ILeh96Cq0crhZ4ZFZ3zgUG6CSGJ46BUO1zSMe4Y0hd9woLh5+qMADcX3NAnCWU1tcgubf0m1MziUoR6uSOlWyA8tI6I9vNGckgAzpaUAQCKq2qgUSqRHBKAEA83RPp4Ir+ica71vrPnIJfJkBDUtjngOl0Ndu77Gqu2v4wNJZ+hyLcAkqf4n721UYW5io5AdojF8qVyDQK8okSnIOpyO8L64rn606Jj2JSFXgdh6hEhOgYUZ44i+ben4eMrFx0FRoMMBVnRcPKegcCYy4AOLjhRp28cUXZUqVrdJtTTHdml5ThbXAagsTg+lluAGL/GUW4vZy10DQacKy1HTb0OWSVlCHBzQY1Oj3WHT2BSyqWt5lpSmoNfdizGit0v4A/jelQH1ELS8oa1i5G7qaFwVYuOQXaIc5Y7Yu1cYOf7olMQdZlTvtGY6ipHpd62OhdYgsmVUbhhQcfn6nYGo8YJ6ZPmISvHclZEc/Mph756I4qz2/9GzWgyYfHvu1Gr1+OeEQMuuO2WExn4/mAaTKbG/fpHhODqXglNzx/KzsNPR05AbzAgJSQQqfFR+HLXAfi5uiDQ3QXf7jsKg9GIK+KikBR86Z1G5HIFEmJGItw1CcoCGdvQtcAx2RseN/QQHYPsEIvljjjxE7DsOtEpiLpEkbMvpgQHI6e2QHQUm/XZrzFQ77SM6S0mmRzZ17+Mk7la0VGamGCCT1A2is9sQE1FWZv3W73nEI7lFmLWiP5wc9S0ut2pgmJ8sWMfRsdHIcTDDUVVNfh2/xH0CwvB5XHdW9wnvaAY/3cgDTOH98e8HzdiymU94eygxtu/bMXcMcPg7NDxkU+t1h0pMaMRIA9nG7p/cL82CtpevqJjkB3iNIyOCB0EyFv/iI/IWtWqHHFPeA8Wyl3svQGVgFz8FAgAkIwGBC9/BAmeOYCFDDBLkFCYHQyZZhqCE0ZBrrj4VIU1ew/jaE4B7hp22QULZQD46fBxpHQLRL/wEPi7uSAhyA9jEqLx67FTMLYwjtRgMGDN3sO4pncCiqqqYTCZEOHjCR8XJ3g5aZvmOndUdXUptuxejpU7X8RvtatR7l8OydXO5zdLgEOUu+gUZKdYLHeESgsE9RWdgqhTGSUZ5sYPwZGKDNFRbN52h2yUjkwWHaMZ79Uvopf6AGRyC6mYATTo5CjMToRb8B3wi0xqcRuTyYQ1ew/j8Lk83DXsMng6XXy1Qp3BcN77Atlfc6Vb+Mz156OnEO3njSB3V5hMpmYFtdFkQld8UJuXdwrrtr2PFftfwEHlVtQF6iGpLeMNljkp/bWQO3NwisRgsdxREcNFJyDqVK8mj8XGUsuYS2sP5idlQdJceATU3FzXfYi+dRugcrCsoqy6TIOy4pEIjJsKV9/mHUXW7D2MvWfOYUq/nlAr5KiorUNFbR30DYambZbv3I8fDx5r+j7W3xfb089i39kcFFfV4EReIdYdPoHYAF/IZM3L6LzySuzPykVqfOON3T7OTpAA7Dx9Fkdz8lFQUYVgd7cuu3YASDvxO779/Q2sSX8TGa7HYfS3nzZ0DlFc3prE4Zzljjq3F/iIBTPZhi8SUjGvKk10DLsz/0QKQleLXaikJfXxg7Av7BbUVFrevFlJZoR3YAbyTm6ArrYGc778ocXtru+TiD5hwQCA9zZuh4fWETf0bRydNhiN+CXtFPacOYfy2jo4qVWI9ffFmIRoaFR/T3swmUx4d+N2jOgRgdiAv+fMHs3Jx5q9R2AwGjE6Pgr9wkO68Ipb5ubmj149UuHdEARTsd7s5zcX7zsToWbbOBKExXJHGY3Aa5FATbHoJEQdsilyEO4zZsNo4ipj5uZu1ODDj5UwFZeIjnKehpAeONjnQZRZaCGmdtTD2XUfzqVtg8nO/+6GhiQhPngInMpdYKq2vDc4l0pykCPgqf6QLGhqENkXFsudYdWtwJE1olMQXbKjAXGYrm1AbUOt6Ch269Hsnkj5bJfoGC0yePji2OXPIj/fcPGNBXHxqoRJtxmFZ46LjiKcTCZHQsxIRLglQ1koB/TW/SZCE+8Jz5tjL74hURdhsdwZ9n4GfHeP6BRElyTXPRhT/DxRWGd5o5r2RGWS44vl3jCdyRYdpUVGBy1OT56HszmWPUnWOygXJdkbUF1aJDqKRXB0dEVK7FgEysOBwoYWb1y0dO5Xd4e2j9gl4sm+sVjuDOXZwJuXtpITkUhVDi64pXsCTlVliY5CAG4tjsOYDw+IjtEqk0yOc9e/hBO5TqKjXJBcaYCn33HkHPsVDTqd6DgWw883AkkRo+Be4w1TuWVOqzmPBPg/3o+dMEgoyx4isBauQYBvvOgURO3SIFPgwZh+LJQtyGLPIzAkRIuO0SrJaEDQ8rlI8Mi2mF7MLTHo5SjIioWL3x0IiO4tOo7FyMtPx0/bPsCK/S/ggPx31AXoIVlYx5N/UwU5m6VQnj59OiRJOu9r9OjRXX5usnwcWe4sv80HNr4oOgVRmz2TMg6rSy1j9Tj62+jqCNz2tuXPu61IvR17G1JgNFj+rxB331LUVfyK0pwzoqNYHJVSg+S4KxDiGAt5vgkwWtafp0tqKFyGB3f5eaZPn478/HwsXry42eNqtRru7u1fDMVkMsFgMEDRhoV0yPJxZLmzxF4lOgFRm32cNJaFsoVap01H9eBk0TEuyuWnj9G3dr3F9WJuSWm+O2prJyMk8Wo4OLmIjmNRdPpa/LH/W3y17WX8VLwEhb75gKflFHiaWPP1V1ar1fDz82v25e7ujszMTEiShP379zdtW1ZWBkmSsGnTJgDApk2bIEkS1q5di169ekGtVuP3339HfX09Zs+eDR8fHzg4OGDQoEHYtcsyb+Sl1rFY7izeUYAP79Yly7cuehjerjgiOgZdwFt9iwArGJFy3PYN+p5dCq2L5WcFJBRkdYPKeTqC44dDZiHLjFuSsrI8/LpjCVbufhE7DOtQFVANyUncn63c0wFKX62w81+KRx99FPPmzUNaWhoSExPxyCOPYPXq1Vi6dCn27t2LyMhIpKamoqSEN1RbExbLnYmjy2Th9gf3xJOGczBZ4y3xdmS/Kg8FqT1Fx2gT1dHt6LXvDbhb0GjkhejqFCg81xMeoXfAN5z3mrTmzNkD+GHrAnx5ZB6OOe6FPsAIKM1bMmhiPM16vu+//x5OTk7Nvl566aV2HeO5557D5ZdfjoiICKjVaixcuBCvvvoqxowZg9jYWHz00UfQaDT45JNPuugqqCtYx6ubtYidCGxq3z8sInPJ8gzFbMcG1OvqRUehNpgXexpvbnaCqbJKdJSLUmQdR2LVUziW+hzy8yy3F/M/VZU4ArgCgXE9UZm/HhVF+aIjWSSj0YADRzbgADb82YZuDAIU4ZAKDF3ehs6cUzAAYPjw4Vi4cGGzxzw8PFBRUdHmY/Tu/fcNpenp6dDr9Rg4cGDTY0qlEn379kVaGldKtSYcWe5MPj0A7x6iUxCdp9zRHTP9/VCqKxcdhdooW1GO42OtZ2qXvLQAsV8/gG4B1lEs/6U4xxt63IiQpPFQOjiIjmPRamrK8fvuFfhyx0vYVPUVyvxLIbkpL77jJZBpFVCFmnd5a61Wi8jIyGZfHh4ekMkaS6V/9kPQ61tuvafVWte0EWobFsudjVMxyMLo5GrMjuqJzOoc0VGoneaFHYbk6yM6RptJ9bUIX34fov0rRUdpF5NBhoKzUdB63Y6gmP6AZMF98SxEfkE6ftr2IVbsewH75ZtRF6jr1DZ0mgRvSDLL+HPw9vYGAOTm5jY99s+b/VoTEREBlUqFrVu3Nj2m1+uxa9cuxMZazxth4jSMzhd3FfDbPNEpiAAAJkh4Kmkk9pYeFh2FLkGVpMPWscEYsLhAdJQ2k0wmBC5/FOpJc3GwLMSqVoyrq1ahrro/fLvHoaF2I4qz0kVHsgrHT23H8VPboVQ6IDn2CnTTxkKejw61oXPsaf43ifX19cjLy2v2mEKhgJeXFy677DLMmzcPYWFhKCgowJNPPnnR42m1Wtx99914+OGH4eHhgZCQEMyfPx81NTWYMWNGV10GdQGOLHc2nxjAy3IXFSD7siB5LH5koWzV3vE7CHQPFR2j3by+fgW9lXsgV1jG6GB7lBe6oKrqSgQnXA9H1/b32LVXen0ddh34Dl9tm4d1RYtR4JMHeLV/TE7u4QB1N/O3+Fu3bh38/f2bfQ0aNAgAsGjRIjQ0NKBXr164//778cILL7TpmPPmzcPVV1+NW265BSkpKTh16hR++umnS+rdTOJwUZKusPEl4LdXRKcgO/d17Cj8t/aE6BjUCW4s74FJ71nnm57afuOxx2M8dLVtm8u85ch32HL0O5RUNt5w5+feDWN63YK4kH4tbr817Qf8cWI9ckoyAQAh3lGY0HcGQn3+vn/k5wNf4uf9KwEAlydfj5FJ1zU9l5mfhpW/v4U5k96FXHb+NAKF0gAP36M4d2wTDK3MU6ULCwmKR3y3YXCpcIWpquGi2zsPD4ZramjXByNqIxbLXSH/KLCwv+gUZMd2hPXF3bIiNBgv/ouJrMMX66Og3HNUdIxLoou5DPu634rqiov/fTyUuQ0ymRzeroEwmUzYeWI9fjnwJR69+gP4e4Set/2SX15CuF8cwn3joJCrsGH/ChzM/B1PXPcJ3LTeOFecjte+uRd3jX4RMJnw/ronMGfSuwj0DIfBaMCra2bixiEPoJvPhW/OdnStg1q5Hbkn913qj8HuSZIMCTEjEOneE8pCBaA3trid74O9oPRxNHM6otZxGkZX8I0FvKJEpyA7dco3Gg8qq1go25iPBtcDMut8yVal7UCvva+1qRdzQugAxIX0g49rEHzdgnFl3xlQKzXIKGj5jcL0kY9jSNxEBHlFws89BFOGPgSTyYTj5xqL2vyyLAR6hCM6sCeig1IQ4BmO/LIsAMDPB1Yi0j/hooUyANSUO6C0aDgCYqfBzTeoHVdPfzGZjDh49Ges2foq/i/7XWR7ZMLkKwf+MVNHGaBloUwWxzpfea1B0o2iE5AdKnL2xSxPZ1TqLb83L7XPJs0ZVAxPFh3jkimyTyLp5yfg59f2jglGowG7T/0Knb4OYb5t6x6ga6iHwdgAR7UzACDAIwwF5dkoqcxHSWU+CsqyEeARisLyHOw4vg7j+9zWrusoyfVEvf5ahCReBbXWqV370t9qaiqwdc9KfLnjJWys+hKlfo1t6ByTraf7C9kPTsPoKpX5wJuxAEf3yExqVY64NaYPjlRkiI5CXaSH3gvPv1MKU731LixjUjng9DXzcSan9aL5XPFpvP7NvWgw6KBWajB95BOtzln+t5Vb3kJa9i48ce0iKBUqAMCWo/+HjQe/AgAMT7wGg2Mn4J3vH8aQuIkwmgz4cfenkMsUuGbALEQGJLb5WlQaPVzdDyA77XeYjC1PKaC2k2Qy3Pnep9C6u4mOQtQMi+WutGIKcOx70SnIDhglGe7veQU2llrnnFZquzeOpiDo2z9Ex+gQkyQh5/oXcTyv5UUnGgx6lFYVoFZXjX2nN2P7sR9x35VvwN899ILHXb9vOX4+sBL3TXgdgZ4RrW634/hPOJi5FTcMvh/Pr5yOhye/h7KqQiz59WU8e9PnUMpV7boeF88qmBo2ozDzWLv2o+bCevbG5EefER2D6DychtGVUqaKTkB24tXksSyU7cS86BOQ3My7sllnk0wmBK54HIlumS2u/6GQK+HtGogQ7yhM7Hc7Aj0jsOnQmgse8+cDX2LD/uWYNe6VCxbKVbXlWLvnM1w78F5kFhyDj2sQfFyDEBXYE0ZjAwrKstt9PRXFTqgsH4ug+Jvg5OHd7v2pUdzQUaIjELWIxXJXihwFuASKTkE2bllCKj4vOyg6BplJgbwKB8fZRi93r29eRW/5rov2YjaZjGgwtN62bcP+FVi393PMHDsP3bwv/LNZvf09DE+8Gu5O3jCZjDAY/25pZzAaYDJd+nSKonN+MMlvQkjiGChU6ks+jj1ycHJGRO+2TbUhMjcWy11JJgeSp4hOQTbst8iBmF/NXsr2Zn7wAUhBAaJjdArnn5egb8UPUGsa5zB/u/NjnMo5iOLKPJwrPo1vd36MkzkH0Lv7SADAp7/Ow7c7P27af8P+5fhh1xJMGToHns5+qKgpQUVNCer1teedKy17NwrKszEkbiIAIMQ7GvllZ3Hk7E78fvR7yGQy+LgFd+h6DA1yFGTFwNnvdgT26NuhY9mTHgOHQKFUio5B1CIud93VUm4BtrwGdGC0gqglRwPi8LBUBIOpbYs9kO2olwz4ZYwvRnyUIzpKp9D88QP69CjAvqjbUVVbik83zkNFTQkcVFoEeoZj5rh5iAnqDQAoqSqA9I+5G1uO/B8ajHp8suHZZscc02sqxvWe1vS9rqEeq35/B7eNegoyqXGcyN3JG9cOvAefb3oVCrkStwybC5Wic0aEayvVqK0cBP8e8aiv3IiSc7zx9kISRqSKjkDUKt7gZw6fTQLSfxWdgmxInlsQbvL3QmFdiegoJNDKb0IhpZ0SHaPTNASE4/CAuSgpsrUuQib4BGehMGM9aisrRIexOAHRsbjxufmiYxC1itMwzIE3+lEnqnJwwczgUBbKhC9G2tbH1oqc00hc/zj8/W3tV5OEgqwQKLS3IiRhJGRyfqj7T8mp40RHILogW3tFskzR4wBHL9EpyAY0yBR4KKYfTladFR2FLMB3zidR1z9BdIxOJasoRo/VDyA0wNZGlwF9vRwF2Unw7HY7fCNs68/tUjm6uiGq3wDRMYguiMWyOShUQNINolOQDXghORXbyo6LjkEWZEH/CkBhWyOVkq4OYcvvRw+/MtFRukRlqSPKSy5HYNwtcPH2Fx1HqMSRqZArbOsTErI9LJbNJWXaxbchuoBPEsdgdekh0THIwvyhPofikcmiY3Q6yWRCwIonkOSW0WIvZltQnOMNvel6hCReCZXGUXQcs5NkMiSOGiM6BtFFsVg2F+8oIHSw6BRkpdZFD8VblVx0hFr2SmImJEfbLLY8v3kNvWU7IVfa5q8rk0GGgqxIaDxnICh2IGz2nUELInr1g7MnpyiS5bPNVx9L1X+W6ARkhfYH98SThhyYwMY11LJMRRnSx8aLjtFlnH/5FH3LvoXaUS46Spepr1aiKLcffLvfDq+Q7qLjmAVv7CNrwWLZnKJGA56RolOQFcnyDMVsxwbUG+pFRyEL93LEUci8PEXH6DKaXevQ59THcHK1rfnZ/1Ze6IyqygkITrgBWjcP0XG6jEdAELolJIuOQdQmLJbNSZKAy+4WnYKsRLmjO2b6+6FUVy46ClmBclkddo4NEx2jS6lO7EavP+bBw9u2C2YAKMwOAFS3ICQhFXKlSnScTpd0BUeVyXqwWDa3pJsAje2OFlDn0MnVmB3VE5nVtrFCG5nHmwEHIYWFiI7RpeS5GUhc95gN9mI+n0EvR0F2HNwCb4d/VC/RcTqNWqtF/PBRomMQtZntv9pYGpUj0PtW0SnIgpkg4amkkdhbbjsrs5F5NEhGfJ/qJjpGl5NVliB69f0IC9CLjmIW1eUOKC0cCv+YW+HmFyw6ToclXT4WKgeN6BhEbcZiWYS+dwJytegUZKEWJI/Fj6WHRccgK7XU/SgMST1Ex+hyMl09wpbdjxhf+1nJsjTPHXW6axCSOAlqrZPoOJdEoVQhZcyVomMQtQuLZRGcfblICbXo69hR+LCcvZSpYxYPNdpNCzL/lU8h2fWUvVwuYJJQkBUGleutCI4bCklmXb/GY4eMgNbNXXQMonaxrn9ltmTgfYDEHz/9bUdYXzxXf1p0DLIB67WnUTUkWXQMs/H49k30lrZDYaO9mFuir1WiMKcXvMLugE9YrOg4bSJJMvSeMEl0DKJ2s59XFkvjGQHETBCdgixEuk8UHlRWocHYIDoK2Yg3e+cDSvtZRtj518/Rt+RrONhwL+aWVJZoUVE2GkHxU+Ds6SM6zgV17zcA7v6BomMQtRuLZZEGPSA6AVmAIicfzPRyQaW+SnQUsiGHVAXIS00WHcOsHPasR++TH8LZzX7eJPyl6JwvDLKbEJI4Dkq1g+g4Leo36TrREYguCYtlkQJ6AuHDRKcggWpVjrg3IgY5tQWio5ANejn2FCRnZ9ExzEp1ci96bn8RnnbQi/nfjA0yFGRFQ+tzOwJ79BMdp5mwnr3hExouOgbRJWGxLNqQh0UnIEGMkgyPxg/B4YoM0VHIRuXKK5E2LkZ0DLNT5J9Bwtq5CPC3l7v+mqurUqE4fyD8omfAM8gyCtR+k64XHaHTbdq0CZIkoaysTHQU6mIslkULHcTRZTv1WvJY/Fp6VHQMsnHzuh2C5O8rOobZyarKELXqfoQH6ERHEaaswBVV1RMRnHgdNC5uwnIExyYgMLrr37RNnz4dkiThrrvuOu+5WbNmQZIkTJ8+vdPON2DAAOTm5sLV1bXTjnkpQkNDIUkSJEmCVqtFSkoKVq1aJTSTrWGxbAlG/ld0AjKz5fGp+KzsoOgYZAdqZHpsHhvUoWMsKCpE7PFjzb7GZbTeueXr8rLztk8+cbzZNotKijHo1EkMOnUSi0uKmz13oLYW12RmoMFk6lBuWYMOocseQKxP8cU3tlESJBRmBUGhmYrghJGQK8w/PWXg9beY7VzBwcFYsWIFamtrmx6rq6vDsmXLEBLSuatbqlQq+Pn5QbKAvoXPPfcccnNzsW/fPvTp0wfXX389tm3bJjqWzWCxbAkCewE9xotOQWayOWIAXqk5IToG2ZEF3geAqLAOHSNSpcJvEZFNX58HX7jwcJLJmm3/c3hE03PH6+qwoKgIr/kH4FX/ALxdVIQT9XUAgAaTCc/m5+FpXz8oOqkI8fvyv0h2PmnX3Tr1OgUKs5PgFnwH/CKTzHbesJ69EdjDfK3tUlJSEBwcjDVr1jQ9tmbNGoSEhKBnz57NtjUajXj55ZcRFhYGjUaDpKQkfPXVVwAAk8mEUaNGITU1FaY/37SVlJQgKCgI//1v4wBXS9Mwtm7dimHDhsHR0RHu7u5ITU1FaWkpAGDdunUYNGgQ3Nzc4OnpifHjxyM9Pb1p38zMTEiShDVr1mD48OFwdHREUlIStm/fftHrdnZ2hp+fH6KiovDuu+9Co9Hg//7v/wAAWVlZuO666+Dm5gYPDw9MnDgRmZmZTftu2rQJffv2hVarhZubGwYOHIgzZ840Pb9w4UJERERApVIhOjoan332WVv+KGyKHb90WJgRT7Lvsh1I84/FHFkxDCaD6ChkR0wSsOpyxw4dQy5J8FYomr7cLzJCKQHNtvf6x/andTpEqdW4TKtFf60WUWo1Tusap0ssKilBb40jEjSduxyyx//9D32MW6FQ2ffrbHWZBmXFIxEYNxWuPgFdezJJwqAbpnbtOVpw2223YfHixU3fL1q0CLfeeut527388sv49NNP8f777+PIkSN44IEHcPPNN+O3336DJElYunQpdu3ahbfffhsAcNdddyEwMLCpWP63/fv3Y+TIkYiNjcX27dvx+++/Y8KECTAYGl/vq6ur8eCDD2L37t345ZdfIJPJMGnSJBiNxmbHeeKJJzBnzhzs378fUVFRuPHGG9HQ0Pa2ogqFAkqlEjqdDnq9HqmpqXB2dsaWLVuwdetWODk5YfTo0dDpdGhoaMBVV12FoUOH4uDBg9i+fTv+85//NI2Wf/3117jvvvvw0EMP4fDhw7jzzjtx6623YuPGjW3OYwvs73ZhS+UTAyRcCxxcKToJdZE8t0Dc46ZGbZ39fiRM4qxyOY6JfeKg2nXkkvY/q9Nh6KlTUMskJDlo8IC3NwIu0Me5xmjEyPRTMAGIcXDA/V7e6K5WAwCi1Gpk6nTI0ethAnBGp0N3lRpndTp8XV6Gr0JDLynjxThtWoa+KQXY638t6qrtu6d5cY4XJNl1CEnMQN7JDdDV1nT6OaIuGySkA8bNN9+Mxx57rGl0dOvWrVixYgU2bdrUtE19fT1eeukl/Pzzz+jfvz8AIDw8HL///js++OADDB06FIGBgfjggw8wdepU5OXl4ccff8S+ffugaOWN4vz589G7d2+89957TY/FxcU1/f/VV1/dbPtFixbB29sbR48eRXx8fNPjc+bMwbhx4wAAzz77LOLi4nDq1Cn06HHxZex1Oh1ef/11lJeXY8SIEVi5ciWMRiM+/vjjpgJ48eLFcHNzw6ZNm9C7d2+Ul5dj/PjxiIho/PQnJubv+eWvvfYapk+fjpkzZwIAHnzwQezYsQOvvfYahg8fftE8tsK+32JbmmGPATL76w9qD6rVzpgVHIYCFsok0PuDaoBLWB450UGDF/398WFQEP7r64tzej1uOXsG1caWPyEJU6nxgp8/FgQG4RX/AJhMJkw5ewZ5ej0AIEKtxv3e3rg9Kwt3ZGXhfm9vRKjVeCY/Dw95++D36mpcmXEakzMzsLumc4s4h70/o8+xhXbZi/nfTEYZCrIioPG4DUGxgyB14qebkkyGgdfd3GnHaw9vb2+MGzcOS5YsweLFizFu3Dh4eXk12+bUqVOoqanB5ZdfDicnp6avTz/9tNnUiGuvvRaTJk3CvHnz8Nprr6F79+6tnvevkeXWnDx5EjfeeCPCw8Ph4uKC0D/fFJ49e7bZdomJiU3/7+/vDwAoKLhwe9G5c+fCyckJjo6OeOWVVzBv3jyMGzcOBw4cwKlTp+Ds7Nx0jR4eHqirq0N6ejo8PDwwffp0pKamYsKECXjrrbeQm5vbdNy0tDQMHDiw2bkGDhyItLS0C+axNRxZtiQeYUDKLcDuRaKTUCdqkCnwUGx/nCg7JjoK2bnfHbIwdURPuP28p137DXFyavr/aDQWz6NOp2NdRSWudnM7b/tkjQbJ/5hGkazRYHzGaXxZXobZXt4AgBvc3HGDm3vTNt+Ul0MrkyFZo8G4jNNY2S0U+Q16PJSTgw3h4VBdQpHfGmX6fqRUvoAjw55AUYF9jzADQH2NCvU1feETGQujbhMKz3T8noq4oaPgESButb7bbrsN99xzDwDg3XffPe/5qqrGRaB++OEHBAY2z6n+8xMQAKipqcGePXsgl8tx8uTJC55Tc5GpQxMmTEC3bt3w0UcfISAgAEajEfHx8dDpmndsUf7jE5u/RoP/PVXj3x5++GFMnz4dTk5O8PX1bdqvqqoKvXr1whdffHHePt7ejf8WFy9ejNmzZ2PdunVYuXIlnnzySWzYsAGXXXbZBc9pTziybGmGPAIoLHP1Jbo0LySnYisLZbIQr/bMhqTp2GuMi1yOUJUKZ/Rta8umlCTEqB1wVtfy9qUNDXivuAhP+PjiYF0tQlUqhKpU6OeoRQNMyGzjedpDXnAW8T8+gkA77cXckvIiJ1RWjEdwwo3QuntdfIdWyJVK9L/mxk5M1n5/zcn9a87uv8XGxkKtVuPs2bOIjIxs9hUcHNy03UMPPQSZTIa1a9fi7bffxq+//trqORMTE/HLL7+0+FxxcTGOHz+OJ598EiNHjkRMTEzTjX+dwcvLC5GRked150hJScHJkyfh4+Nz3nX+s+Vdz5498dhjj2Hbtm2Ij4/HsmXLADROydi6dWuzc23duhWxsea7adMSsFi2NC7+QJ/bRaegTvJJ4hisLj0kOgZRk5OKYpwZnXjxDS+g2mjEWZ0O3m1sQ2YwmXBSV9/q9vMKCzDV3R1+SiWMJkD/j5ZxBpMJho51kGuVrKoc3Vfdj4iA+q45gZUqzPYHlFMQkjgaCpWq3fsnjRoDlz8/QRBFLpcjLS0NR48ehVwuP+95Z2dnzJkzBw888ACWLl2K9PR07N27F++88w6WLl0KoHHUedGiRfjiiy9w+eWX4+GHH8a0adNaLXIfe+wx7Nq1CzNnzsTBgwdx7NgxLFy4EEVFRXB3d4enpyc+/PBDnDp1Cr/++isefPDBLv0ZAMCUKVPg5eWFiRMnYsuWLcjIyMCmTZswe/ZsZGdnIyMjA4899hi2b9+OM2fOYP369Th58mTTvOWHH34YS5YswcKFC3Hy5Em88cYbWLNmDebMmdPl2S0Ji2VLNPghQGVfS9TaonXRQ/FWJRcdIcszL+o4JHe3Nm8/v6AAu2pqcE6vw77aGsw+lw25JGGcswsA4NHcHLxR+PecyveKirC1uhpZOh2O1tVhbm4OcvR6XO16/jm3VVcjU6fDTX9OyYh3cECGTofNVVX4sqwMMklC2CUUbG0la9Ch27IHEetd2GXnsEYGvRwFWbFw8bsDAdG927yf0kGDfpOu68Jkbefi4gIXF5dWn3/++efx1FNP4eWXX0ZMTAxGjx6NH374AWFhYSgsLMSMGTPwzDPPICUlBUDjzXa+vr4tLnoCAFFRUVi/fj0OHDiAvn37on///vj222+hUCggk8mwYsUK7NmzB/Hx8XjggQfw6quvdsl1/5OjoyM2b96MkJAQTJ48GTExMZgxYwbq6urg4uICR0dHHDt2DFdffTWioqLwn//8B7NmzcKdd94JALjqqqvw1ltv4bXXXkNcXBw++OADLF68GMOGDevy7JZEMpk62PWdusbGl4Hf5olOQZdof3BP3K6uQr2BI1ZkmR7P6onkz3e1aduHcs5hd00tyowGeMjlSNFocJ+XN0L+LGKnnT2DQKUSL/k3tiKbV5CPDZWVKDIY4CKTIc7BAbO9vBHr0Hz6R53RiMmZmXg9IAAx/3juq7IyvFVUCJUk4b++fhj6jznTXal0/L3YX9MDpgtPD7VLHn6lqC37BaW5Zy+4Xf9rbsKAa28yUyoi82CxbKnqq4AFvYHK3ItvSxYlyzMUU7ycUaorFx2FqFVqkxyff+EFU9Y50VEsSvXQG7BHPRQNOlbM55FM8Ak6i4LT61FXVXne086e3rj1f+9DqVK3sDOR9eI0DEuldgIuf150Cmqnckd3zPT3Y6FMFq9eMmD9aLHzSi2R9rcV6FuwCg5aNos6j0lCQVY3qJxvRXD8cMj+NRd48E3TWCiTTWKxbMkSrwW6Dbz4dmQR9HIV7otKQWZ1jugoRG3ykddhGONa7xtrrxz2/4reae/CxY0Fc0t0dQoUnusJj9A74BveuJiGf1QPxAwaJjYYURdhsWzpxr4KSOffyUuW56mkUdhTfuE+nESW5rMRfH1pier0QfTc+jy8fFgwt6aqxBHlpVcgKP5mDJ92p+g4RF2GxbKl841jKzkrsCB5HH4oPSw6BlG7/eB0CrUDO9ZKzlbJC7MR/8PDCAwQncSyeYUkwj+Sn1CQ7WKxbA1GPAFoObfQUn0TOwoflLOXMlmvd/qVAW3smWxvZNUViFp5HyIC6kRHsUgqjQL9J0WKjkHUpVgsWwMHV2Dk06JTUAt2hvXBs/WnRccg6pDd6hwUXp4sOobFkgwN6LbsIcR5F1x8YzvTd3wYHF26rg82kSVgsWwtet4MBLa9MTx1vdM+3fGAshoNxgbRUYg6bH58JiStVnQMi+a76ln01B6FTMYlsgHAI0CLhGGBomMQdTkWy9ZCkv682Y9/ZJagyMkHM73dUKmvEh2FqFOcUZTh5Ng40TEsnvsP76J3wyYoVHwtHnxdd8jk/DmQ7ePfcmsSmNI4wkxC1Sk1mB0Ri3M1+aKjEHWqVyKOQvL2Eh3D4jlt/hJ9C76Exo57MUf180VQDw/RMYjMgsWytRn5DODgJjqF3TJKMjyaMBSHKjhPmWxPuVSHHeNCRcewCg77N6L30Xfg4q4UHcXsNM5KDL42SnQMIrNhsWxttJ7AKN7sJ8rryWPxS+lR0TGIusz//A8A4d1Ex7AKyozD6LnlWXj72lev6sHXR8HByf7eJJD9YrFsjXrdCoQNEZ3C7iyPT8WnZQdFxyDqUgaY8G2qi+gYVkNedA5x381BkJ30Yg5L8kL33r6iYxCZFYtlayRJwMR3AZWz6CR2Y3PEALxSc0J0DCKz+MItDQ09Y0THsBqy2ip0X3kfIv1rRUfpUmpHBYbeFC06BpHZsVi2Vm4hwBXPiU5hF9L8YzFHVgyDySA6CpHZfDxE3/jGnNpEMjQgZPkcxHvliY7SZQZMjoTWVS06BpHZsVi2Zr1vA8KHiU5h0/LcAnGPmxq1DbY9YkT0b786ZqJyWLLoGFbH56vnkeJ42OZ6MQdGuyN2kJ3MNSH6FxbL1u7KBZyO0UWq1c6YFRyGgrpi0VGIhHgjJR+SiquztZfbjwvRR/cLlGrb+BWrUMkw/OYeomMQCWMb/5LtmVswcMXzolPYnAaZAg/F9seJqrOioxAJc0RVgHOjk0XHsEra31ejb+5yODpZfy/mfleGw9VbIzoGkTAslm1B71uBiBGiU9iUF5NTsbXsmOgYRMK9FHMckiu7Y1wK9cHN6H3oLbh6WG+bNd8wFySNCBYdg0goFsu24sp3ADV/oXWGRYlj8FXpIdExiCxCgawah8fxI/hLpThzFMm/PQ0fK+zFLFfKMOKWGEg2Nv+aqL1YLNsK1yDgihdEp7B6P0UPxf8quegI0T+9EnIQUoCf6BhWS16ci9jv5iA4wCQ6SrsMmBwJjwCt6BhEwkkmk8m6/vXShX02GUj/RXQKq7Q/OBm3q6tRb6gXHcXmVB+vRtGPRag9U4uGsgaE3BsCl15/fxLSUN6AvC/zUHWkCoYaA7RRWvjf7A+1X+ttqsp3l6Pw+0Lo8nUwGUxQ+6rhOdoT7gPdm7YpWluEwh8LAQDeY73hNcar6bma9BrkfJqDiP9GQJJz5OxiZhYmYtjHe0XHsGommRzZ17+Mk7mWX4B2i/fE+HuSRMcgsggcWbY1V74DaNwvvh01k+XZDfdpjSyUu4ix3giHEAcE3HJ+6ymTyYQzb5+BrlCHkNkhiHw2EkovJTJfzYSx3tjqMeVaOXwm+CD8qXBEvhAJt8FuOPfJOVQeqgQA1GXVIf/rfATfHYzgu4ORvyYfdVl1jec0mJCzNAcB0wJYKLfRQq+DMPWIEB3DqklGA4KXP4IEzxzAgv/aaZyVGDGVi9IQ/YXFsq1xDQSuWig6hVUpd3THTP8AlNSXiY5is5wTneF7tW+z0eS/6PJ1qE2vRcC0ADiGO0Ltr0bA1AAYdUaU7Shr9ZhOMU5w6eUChwAHqH3U8LrCCw7BDqg5UQMAqM+th0OQA5xineAU6wSHYAfU5za+GSpaWwRttBaO4Y5dcr22yCQBK0dxQYrO4L36RfRyOAiZhb5RGzE1Bo4ubBlI9BcWy7YoegzQ/x7RKayCXq7CfVEpyKw+JzqK3TLpG2eCScq/CwdJJkFSSk2F70WPYTKh6mgV6nProY1u/IhbHaSGLl8HXbEOuiId6vPqoQ5So76gHqVbSuEz2afzL8bGrXE+gfp+CaJj2ATXtR+gb93PFteLOWFYEEITvC6+IZEdsf4GkNSyUc8AWTuB7F2ik1i0p5JGYU/pYdEx7JraXw2lpxL5q/IROD0QklpC8U/FaChpQEN5wwX3NdQYcPyB4zA2GCFJEgKmBsAp3gkA4BDgAN+rfZH5aiYAwO8aPzgEOCBjfgb8rvND1eEqFHxTAEkuwX+Kf1ORTRf23oBKPLBbDhi4/HtHOW5dg74JhdgXejNqKi/8d90cPIOcMPDqSNExiCwOb/CzZWVZwPuDgLoy0Uks0rvJ4/B+OVvEmdvh6YfPu8GvNrMW5z451zinWAY4xTo1fu5lAkIfCm31WCajCbpCHYx1RlQfrUbBdwUImR0CpxinFrcv/b0UFXsrEDgtECcePYGIpyOgL9Uj+4NsRL0aBZnSskb5LNUHe5Lgvn6P6Bg2oyGkBw72eRBlxXphGRRqOa57rDfc/fimkejf+JvBlrkFA5PeF53CIn0bM5KFsgXRhGoQ+XwkYt6LQY//9UDonFAYqgxQeV943qQkk6D2VUPTTQOvMV5w7eOKoh+KWty2obIBBd8WIODmANScroHaTw21nxpOMU4wGUzQ5em64tJs0vykLEgarujWWRRnjyFp41PwFdiLeegNUSyUiVrBYtnWcf7yef4I7YNndBmiY1AL5I5yKFwUqM+rR21GLZxTnNu1v8lkglHfcgeN3GW58LrCC0oPJWBs7IjRtJ/BBJORH7K1VbqiBBljOXe5M8lL8hHz7UMICWi9A0xXie7nhx79/c1+XiJrwWLZHox6BgjsLTqFRTjt0x33q6rRYBQ/P9CeGOoMqD1Ti9oztQAAXZEOtWdqoStuHM0t/6McVWlV0BXoULG3ApmvZsIlxQXO8X8Xy9kfZiNvVV7T94XfF6LqcOM+dTl1KFpbhLJtZXAb4Hbe+asOV0GXr4PHSA8AgCZMg/rcelQerETJppLGEWp/dnpoj5cj0yB5eoiOYVNkddWIWHE/ovyrzHZOdz9HDLkxymznI7JGvMHPHsiVwLWLgfcH2/X85SInH8z0dkNlTb7oKHanNqMWma9kNn2ft7yx6HUb6IagO4LQUN6A3BW5MJQboHBTwG2AG7wnejc7hq5Y16w3rbHeiJzPcqAv0UOmkkHlr0Lwf4Lh2s+12X5GnRE5n+cg+O7gpmV7lR5K+N/sj3Mfn4OklBB0exBkKo4dtEeprBZ7xvZAymcloqPYFMloQNDyuVBPfgyHSoOALvzAQ6VRYOzdiVA5sBQguhDe4GdPjv0IrLhRdAoh6pQa3BbbD4cqTouOQmQzVCY5vljuDdOZbNFRbFJ56h3Y19ATRkPn/5qWJGDszES2iSNqAw6l2JMeY4HLZolOYXZGSYZHE4ayUCbqZDrJgB9TPUXHsFmuP32EvrXroXLo/Bv/+k4IZ6Hcgk2bNkGSJJSVlQEAlixZAjc3N6GZSDwWy/bm8ueA0MGiU5jV68lj8UvpUdExiGzSYs8jMCREi45hsxy3fYM+WZ/C0bnzpkpE9PRGrzHdOu14bTFs2DDcf//95z3+72K0pqYGjz32GCIiIuDg4ABvb28MHToU3377bavHXrJkCSRJgiRJkMvlcHd3R79+/fDcc8+hvLy8C66G7A2LZXsjVwDXfQp4hItOYhYr4q/Ap2UHRccgsmlLh4tOYNvUR7ah9/434Oap7PCxPAK0GDEtBpJkmUtt33XXXVizZg3eeecdHDt2DOvWrcM111yD4uLiC+7n4uKC3NxcZGdnY9u2bfjPf/6DTz/9FMnJycjJyTFT+pbpdGxLae1YLNsjRw/gpi8BB9eLb2vFNkcMwLyak6JjENm8ddp0VA9OFh3Dpimyjjf2Yva79CkZakcFxtyVYNE39H333Xd4/PHHMXbsWISGhqJXr1649957cdttt11wP0mS4OfnB39/f8TExGDGjBnYtm0bqqqq8MgjjzRtV19fj9mzZ8PHxwcODg4YNGgQdu1q+0q36enpmDhxInx9feHk5IQ+ffrg559/brZNaGgonn/+eUydOhUuLi74z3/+074fAlkcFsv2yqs7cO1SQGa5L5odkeYfi4dlJTCYuCQvkTm81bcIUNjm64mlkJfkI/brB9AtoP2va5IEXD4jDm4+jl2QrPP4+fnhxx9/RGVlZYeP5ePjgylTpuC7776D4c/l2R955BGsXr0aS5cuxd69exEZGYnU1FSUlLStq0tVVRXGjh2LX375Bfv27cPo0aMxYcIEnD17ttl2r732GpKSkrBv3z489dRTHb4WEovFsj2LGA6Mnic6RafLcwvEPW5q1DTUiI5CZDf2q/JQkNpTdAybJ9XXInz5fYj2b18x2W9iOLrFWf7NmB9++CG2bdsGT09P9OnTBw888AC2bt16ycfr0aMHKisrUVxcjOrqaixcuBCvvvoqxowZg9jYWHz00UfQaDT45JNP2nS8pKQk3HnnnYiPj0f37t3x/PPPIyIiAt99912z7UaMGIGHHnoIERERiIiIuOT8ZBlYLNu7vncAfW4XnaLTVKudMSs4DAV1F57fRkSdb17saUjOTqJj2DzJZELg8keR6H62We/x1kSk+KDX6NAuz9UZhgwZgtOnT+OXX37BNddcgyNHjmDw4MF4/vnnL+l4f3XHlSQJ6enp0Ov1GDhwYNPzSqUSffv2RVpaWpuOV1VVhTlz5iAmJgZubm5wcnJCWlraeSPLvXtzITBbwmKZgNGvAOHWf4dOg0yBh2L740TV2YtvTESdLltRjuNjY0XHsBteX7+C3sq9kMlbr5h9Ql0wcnqMGVO1zMXFpcXOFGVlZXB1bX7/jFKpxODBgzF37lysX78ezz33HJ5//vlLulEuLS0NLi4u8PTsnFH1OXPm4Ouvv8ZLL72ELVu2YP/+/UhISDgvm1ar7ZTzkWVgsUyNHTKuXQJ4WfeSpy8lp2Jr2THRMYjs2ryww5B8fUTHsBsu6z9B3+q1LfZidvFywLiZiVCqOr9Pc3tFR0dj79695z2+d+9eREVd+HdPbGwsGhoaUFdX165zFhQUYNmyZbjqqqsgk8kQEREBlUrVbFqHXq/Hrl27EBvbtjd5W7duxfTp0zFp0iQkJCTAz88PmZmZ7cpF1ofFMjXSuAE3rgA07qKTXJLFiWOwqvSQ6BhEdq9K0mHr2GDRMeyK447/Q98zS6B1+fsGS7VWgfH3JMHRRSUw2d/uvvtunDhxArNnz8bBgwdx/PhxvPHGG1i+fDkeeuihpu2GDRuGDz74AHv27EFmZiZ+/PFHPP744xg+fDhcXFxaPb7JZEJeXh5yc3ORlpaGRYsWYcCAAXB1dcW8eY335mi1Wtx99914+OGHsW7dOhw9ehR33HEHampqMGPGjDZdR/fu3bFmzRrs378fBw4cwE033QSj0dixHw5ZPN66TH/zjACu+wz4bBJg1ItO02bro4fgzUouOkJkKd7xO4gB3UOBk5mio9gNVdoO9KosxqF+c1BRbsTYuxPh7mc5UwHCw8OxefNmPPHEExg1ahR0Oh169OiBVatWYfTo0U3bpaamYunSpXj88cdRU1ODgIAAjB8/Hv/9738vePyKigr4+/tDkiS4uLggOjoa06ZNw3333desyJ43bx6MRiNuueUWVFZWonfv3vjpp5/g7t62gaI33ngDt912GwYMGAAvLy/MnTsXFRUVl/ZDIashmf6a/U70l/3LgW/uBmD5fzUOBCdhhroG9YZ60VGI6B9uLO+BSe8dFh3D7hjdfaB9+1OE9jHvCn1EtozTMOh8yTdaRUu5LM9umK01sVAmskDLXY9B34s3+5mb/90zWCgTdTIWy9Syy+4Chj4qOkWryjVumOUfgJL6MtFRiKgVHw2uB2T8NWMunrfPgMfUqaJjENkcvopR64Y/BvS7S3SK8+jlKtwf3QsZ1edERyGiC9ikOYOK4cmiY9gF14kT4f2PG+WIqPOwWKYLGz0PSLpJdIpmnkoahd3lJ0XHIKI2eK1nDiS1WnQMm6YdOgT+L74ASWrDCiVE1G4slunCJAmYuADoMV50EgDAu8nj8EMpbxoishbHlEXIGp0kOobNcux/GYLefhuSgs2tiLoKi2W6OJkcuGYREDZUaIxvY0bi/XL2UiayNvOiT0Byc734htQumt69EPzee5Bx5J6oS7FYprZRqIEblgGBYta7/yO0D57RZQg5NxF1TIG8CgfHRYuOYVM0SUkIfv8DyDQa0VGIbB6LZWo7tRMwZRXgY952UKd9uuN+VTUajA1mPS8RdZ75wQcgBQWIjmETHGJjEfzRh5A7Wc6iI0S2jMUytY+jB3DL14B7qFlOV+zkjZnebqjUV5nlfETUNeolA34Z4ys6htVTR0Uh+JOPIb/A0s9E1LlYLFP7OfsB038APCK69DR1Sg3ujYjDuZr8Lj0PEZnH+16HYIqJFB3DaqnCwxGyeBEUbVyamYg6B4tlujSuQcCtawHvmC45vFGS4bGEYThUcbpLjk9EYnwxUik6glVShoQgZPFiKDw9RUchsjsslunSOfs2jjD7JXT6od9IHoufS490+nGJSKzvnE+irn/nv2bYMlVYGLp9uhRKXx/RUYjsEotl6hitJzDt+07tkrEy/gosLTvYaccjIsuyoH8FwL7AbaKOjka3zz+D0s9PdBQiu8VimTpO4wZM/QYIGdDhQ22OGICXa7g6H5Et+0N9DsUjk0XHsHgOSYno9ulSTr0gEozFMnUOtTNw82ogfNglH+KYfywelpXAYDJ0Xi4iskivJGZCcnQUHcNiOfbti26LFkHuysVciERjsUydR+UI3PQlEDW63bvmuwZglpsDahpquiAYEVmaTEUZ0sfGi45hkbRDhyD4ww8g07KPMpElYLFMnUuhBq7/HIid2OZdqtXOmNUtAgV1RV0YjIgszcsRRyHz4hSDf3JOTUXwggWQOTiIjkJEf2KxTJ1PrgSuWQwkXHfRTQ2SHHNi++N45RkzBCMiS1Iuq8POsWGiY1gM10mTEPjG65CUbK9HZElYLFPXkMmBSR8A/e664GYv9hyN38uOmSkUEVmaNwMOQgoLER1DOI9pU+H/0ouQ5HLRUYjoX1gsU9eRyYAxrwBXvAhAOu/pxYljsKr0kPlzEZHFaJCM+D7VTXQMcWQy+D7+OHwfewySdP7rJBGJJ5lMJpPoEGQHDq8Bvr4LMNQDANZHD8Ec3RmYwL9+RAQs/zES8gP29SmTpNEg8LVX4TxypOgoRHQBHFkm84if3NiL2cENB4KT8Lghl4UyETVZPNQI2NHIqtzTE92WLmGhTGQFWCyT+XQbAMzYgPk+/qj/c4SZiAgA1mtPo2pIsugYZqEKD0foyhXQJCaKjkJEbcBimczLOwoLLn8fKT4popMQkYV5s3c+YOOdIBx790bo8mVQBQWJjkJEbcRimczO3cEdH1/xMa6MuFJ0FCKyIIdUBchLTRYdo8u4jBuH4EWfcFU+IivDG/xIqI8PfYy3977N+ctEBADwNzjj7YUNMFVWio7SeSQJXnffBa9772XHCyIrxJFlEur2hNvx5rA3oVFoREchIguQK69E2rgY0TE6jczREYFv/Q/es2ezUCayUhxZJouQVpyGe369BwU1BaKjEJFgjkYlln7qAlNuvugoHaIMDkbQuwvgEBUlOgoRdQBHlskixHjGYMW4FUj05t3hRPauRqbH5rHWfQOcdsAAhK36koUykQ3gyDJZlAZjA97e9zaWHF7CecxEdkwyASvXBAMnMkRHaR9Jgucdd8D7/vsgyTgeRWQL+C+ZLIpCpsCDvR7Ee6Peg4eDh+g4RCSISQJWXe4oOka7yLRaBL79FnwefICFMpEN4cgyWazCmkI8uuVR/JH3h+goRCTI5z9HQ7XriOgYF6WKiEDQO+9AHR4mOgoRdTK+9SWL5e3ojY+u+AizkmdBLslFxyEiAd4fVANY+Cit69WTEbbqSxbKRDaKI8tkFXbn7cbcLXPZLYPIDn24KwluP+8RHeM8Micn+D37DFzHjRMdhYi6kGW/XSf6U2+/3vhqwlcYEjREdBQiMrNXe2ZD0jiIjtGMQ2Iiwr5ew0KZyA6wWCar4e7gjgUjFmBO7zlQyBSi4xCRmZxUFOPMaAtpKylJ8LzjdoR+8TlUwcGi0xCRGXAaBlmlw0WH8fBvDyO7Klt0FCIyAy+jFgs/lGAqLROWQe7lhYBX5sFp4EBhGYjI/DiyTFYp3iseqyasQmpoqugoRGQGRbJq7BvXXdj5tYMGIfzbb1goE9khjiyT1Vt1YhXm/zEfdYY60VGIqAupTXJ8/oUXTFnnzHZOydERPg8+CPcpN0GSJLOdl4gsB0eWyepdG3Utlo1bhki3SNFRiKgL1UsGrB/tbbbzOfbpg/Bvv4HHzVNYKBPZMY4sk83QG/VYemQpPjjwAUeZiWzYiu/CIDtyssuOz9FkIvonjiyTzVDKlLg94XasuXIN+vv3Fx2HiLrIZyO6bpEix759OZpMRM2wWCabE+wSjA+v+BAvD34ZHg4eouMQUSf7wekUagd2bis5ydERvk89iZClSyyiJZzJZMKoUaOQmnr+Tczvvfce3NzckJ3NbkBE5sBimWzW+PDx+O6q7zC5+2RI4AgRkS15p18ZoOicfuuOffsi/Ltv4THFckaTJUnC4sWLsXPnTnzwwQdNj2dkZOCRRx7BO++8g6CgIIEJiewHi2Wyaa5qVzw74FksHr0Y4a7houMQUSfZrc5B4eXJHTqG3MMD/i+91DiabIGFZ3BwMN566y3MmTMHGRkZMJlMmDFjBq644gpMnToV+/fvb9q2rKwMkiRh06ZNAACDwYAZM2YgLCwMGo0G0dHReOutt5odf/r06bjqqqvw2muvwd/fH56enpg1axb0er0Zr5LI8rFYJrvQy7cXvprwFWYlz4JKphIdh4g6wfz4TEhabft3lMngduMNiFj7I9wmT7KY0eSWTJs2DSNHjsRtt92GBQsW4PDhw3jssccuup/RaERQUBBWrVqFo0eP4r///S8ef/xxfPnll82227hxI9LT07Fx40YsXboUS5YswZIlS7roaoisE7thkN3JLM/ECztewM68naKjEFEHvXQqBZGr/mjz9g7x8fB7+mloEuK7MFXnKigoQFxcHEpKSrB69WokJycjLCwM+/btQ3JyMoDGkWV3d3ds3LgRw4YNa/E499xzD/Ly8vDVV18BaBxZ3rRpE9LT0yGXN940ed1110Emk2HFihXmuDQiq8CRZbI7oa6h+Dj1Y7ww8AW4q91FxyGiDngl4igkb6+LbidzdYXfM08j9MuVVlUoA4CPjw/uvPNOxMTE4Kqrrmrzfu+++y569eoFb29vODk54cMPP8TZs2ebbRMXF9dUKAOAv78/CgoKOis6kU1gsUx2a2LkRHx71be4MuJK0VGI6BKVS3XYMS609Q0kCa6TJyNi7Y9wv+EGSDLr/LWnUCig+POGRtmf1/DPD4b/Pc94xYoVmDNnDmbMmIH169dj//79uPXWW6HT6Zptp1Qqm30vSRKMRmNXXAKR1bLOVw2iTuLu4I4XB72IRamLuAIgkZX6n/8BILzbeY87xMej2xefI+ClF6HwsJ02kt7ejasY5ubmNj32z5v9AGDr1q0YMGAAZs6ciZ49eyIyMhLp6enmjElkM1gsEwHo49cHq69cjZcGvYQgJ8u7K56IWmeACd+mujR9r/D3R8Cr8xG66ks4pqQITNY1NBoNLrvsMsybNw9paWn47bff8OSTTzbbpnv37ti9ezd++uknnDhxAk899RR27dolKDGRdWOxTPQnmSTDhIgJ+G7Sd3iy35Pw1niLjkREbfSFWxr0g1Lg/cADiFi3Fq4TJlh0l4uOWrRoERoaGtCrVy/cf//9eOGFF5o9f+edd2Ly5Mm4/vrr0a9fPxQXF2PmzJmC0hJZN3bDIGpFbUMtlqUtw6LDi1ChqxAdh4haoZQpcX309bgj8Q6u2klEnY7FMtFFVOgqsOTwEnye9jlqG2pFxyGiP8kkGcaHj8es5FkIcAoQHYeIbBSLZaI2KqotwkcHP8KqE6ugN3KFKyKRhgUPw30970OkO2/MJaKuxWKZqJ3OVZ3De/vfw/env4fRxBZLROaU4pOCB3o9gGSfZNFRiMhOsFgmukTpZelYsG8Bfj77s+goRDavp09P3JFwBwYHDRYdhYjsDItlog46XHQYb+19Cztyd4iOQmRTZJIMI0NGYlrcNCR5J4mOQ0R2isUyUSfZlbcLnx75FJvPbeb0DKIO0Cg0mBgxEVPjpiLYOVh0HCKycyyWiTpZVkUWlh1bhm9OfYMqfZXoOERWw9PBEzf2uBE39LgBrmpX0XGIiACwWCbqMtX6anxz6hssP7YcZyrOiI5DZLHCXcMxNXYqJkRMgEquEh2HiKgZFstEXcxkMmHLuS34/Ojn2J67XXQcIovR27c3psdNx5CgITa92h4RWTcWy0RmlF6WjmVpy/B/p/+PC5yQXZJLclze7XJMj5uOOK840XGIiC6KxTKRAOX15Vhzcg2WH1uO3Opc0XGIupyjwhGTu0/GLbG3cLU9IrIqLJaJBDIYDfg161d8fvRz7C3YKzoOUadL8k7ChPAJGBM+Bi4qF9FxiIjajcUykYVIK07DsmPLsOHMBlTrq0XHIbpkQU5BGB8xHhPCJyDEJUR0HCKiDmGxTGRh6hrqsDl7M9ZmrMWWc1tQb6gXHYnoopxVzkgNTcWE8AlI8U0RHYeIqNOwWCayYFW6Kvya9St+zPgRO3N2osHUIDoSUROFTIFBgYMwIXwChgUPY9s3IrJJLJaJrERpXSk2nNmAtRlrsbdgL1cJJGESvBIwPnw8xoSNgbuDu+g4RERdisUykRXKr87HT5k/YW3GWhwuPiw6DtmBAG0AxoWPw4SICQhzDRMdh4jIbFgsE1m5rIosrM1ci7UZa3Gq7JToOGRD/LR+GBw4GGPCxqC3b28uHEJEdonFMpENOVF6Ausy1mHDmQ3IrMgUHYesjEqmQi/fXhgYOBCDAgchwi1CdCQiIuFYLBPZqLzqPOzI3YGduTuxM3cnCmsLRUciC9TNpRsGBgzEwMCB6OPXBxqFRnQkIiKLwmKZyE6kl6VjR+4O7Mjdgd15u1GlrxIdiQRwVDiir19fDAxsLJCDnYNFRyIismgslonskMFowJHiI00jz/sL9kNn1ImORV0kyj2qsTgOGIgUnxQo5UrRkYiIrAaLZSJCXUMd9hbsxc7cndiRuwPHSo6xNZ2VkiChm0s3xHrG4jL/yzAwcCB8HH1ExyIisloslonoPOX15diVtwu783fjWMkxnCg5gUp9pehY9C8SJIS4hCDWIxZxXnGI9YxFjEcMnFROoqMREdkMFstE1CY5VTk4XnIcx0uP40TpCRwvOY6syiyYwJcQcwl2DkacZ2NRHOcZhxjPGDirnEXHIiKyaSyWieiS1ehrcKL0RFPxfLz0OE6WnkRNQ43oaFYvyCmosSj+c8Q41jMWLioX0bGIiOwOi2Ui6lQmkwlZlVk4Xnr875HokhPIq8njPOh/kEkyeGm8EOgUCH+tf+N/nfwR7ByMGI8YuKpdRUckIiKwWCYiM9Eb9cirzkNedR5yq3ORU5WDvOo85FTlILc6F3nVeagz1ImO2Wnkkhy+jr7wd/I/ryAO1AbCT+vHrhRERFaAxTIRWYzy+nIU1RahqLYIxbXFjf9f1/j/f31fWleKWkMt9AY9dEadWUar1XI1HBWOcFQ6QqPQQKvUNn3/1389NZ4I0AYgwKnxy9fRFwqZosuzERFR12KxTERWTW/UQ2/Qo95QD51B1/hlbPxvvaEeeuM/nvvz8b+eAwCNQtOsEG4qgP9RDMtlcsFXSUREorBYJiIiIiJqhUx0ACIiIiIiS8VimYiIiIioFSyWiYiIiIhawWKZiIiIiKgVLJaJiIiIiFrBYpmIiIiIqBUslomIiIiIWsFimYiIiIioFSyWiYiIiIhawWKZiIiIiKgVLJaJiIiIiFrBYpmIiIiIqBUslomIiIiIWsFimYiIiIioFSyWiYiIiIhawWKZiNpFkiR88803rT6fmZkJSZKwf/9+s2UiIiLqKiyWiezI9OnTIUkSJEmCUqlEWFgYHnnkEdTV1YmORkREZJEUogMQkXmNHj0aixcvhl6vx549ezBt2jRIkoRXXnlFdDQiIiKLw5FlIjujVqvh5+eH4OBgXHXVVRg1ahQ2bNgAAAgNDcX//ve/ZtsnJyfjmWeeafZYbm4uxowZA41Gg/DwcHz11VcXPOfhw4cxZswYODk5wdfXF7fccguKioo687KIiIi6BItlIjt2+PBhbNu2DSqVql37PfXUU7j66qtx4MABTJkyBTfccAPS0tJa3LasrAwjRoxAz549sXv3bqxbtw75+fm47rrrOuMSiIiIuhSnYRDZme+//x5OTk5oaGhAfX09ZDIZFixY0K5jXHvttbj99tsBAM8//zw2bNiAd955B++999552y5YsAA9e/bESy+91PTYokWLEBwcjBMnTiAqKqpjF0RERNSFWCwT2Znhw4dj4cKFqK6uxptvvgmFQoGrr766Xcfo37//ed+31v3iwIED2LhxI5ycnM57Lj09ncUyERFZNBbLRHZGq9UiMjISQOMIb1JSEj755BPMmDEDMpkMJpOp2fZ6vb5D56uqqsKECRNavIHQ39+/Q8cmIiLqapyzTGTHZDIZHn/8cTz55JOora2Ft7c3cnNzm56vqKhARkbGefvt2LHjvO9jYmJaPEdKSgqOHDmC0NBQREZGNvvSarWde0FERESdjMUykZ279tprIZfL8e6772LEiBH47LPPsGXLFhw6dAjTpk2DXC4/b59Vq1Zh0aJFOHHiBJ5++mn88ccfuOeee1o8/qxZs1BSUoIbb7wRu3btQnp6On766SfceuutMBgMXX15REREHcJpGER2TqFQ4J577sH8+fNx8uRJZGRkYPz48XB1dcXzzz/f4sjys88+ixUrVmDmzJnw9/fH8uXLERsb2+LxAwICsHXrVsydOxdXXHEF6uvr0a1bN4wePRoyGd+vExGRZZNM/56gSEREREREADgNg4iIiIioVSyWiYiIiIhawWKZiIiIiKgVLJaJiIiIiFrBYpmIiIiIqBUslomIiIiIWsFimYiIiIioFSyWiYiIiIhawWKZiIiIiKgVLJaJiIiIiFrBYpmIiIiIqBUslomIiIiIWsFimYiIiIioFSyWiYiIiIhawWKZiIiIiKgVLJaJiIiIiFrBYpmIiIiIqBUslomIiIiIWsFimYiIiIioFSyWiYiIiIhawWKZiIiIiKgVLJaJiIiIiFrBYpmIiIiIqBUslomIiIiIWsFimYiIiIioFSyWiYiIiIhawWKZiIiIiKgVLJaJiIiIiFrBYpmIiIiIqBUslomIiIiIWsFimYiIiIioFSyWiYiIiIhawWKZiIiIiKgVLJaJiIiIiFrBYpmIiIiIqBUslomIiIiIWsFimYiIiIioFSyWiYiIiIhawWKZiIiIiKgVLJaJiIiIiFrBYpmIiIiIqBUslomIiIiIWsFimYiIiIioFf8PaTVgnqv4ldIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import duckdb\n",
    "import polars as pl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "con = duckdb.connect('db/ibm_aml.db')\n",
    "duckdb_to_arrow = con.query(\"\"\"\n",
    "SELECT ROUND(SUM(amount_paid), 2) as total_paid, payment_currency FROM vw_is_laundering GROUP BY payment_currency ORDER BY SUM(amount_paid) DESC;                  \n",
    "\"\"\").arrow()\n",
    "polars_df = pl.DataFrame(duckdb_to_arrow)\n",
    "\n",
    "display(polars_df)\n",
    "\n",
    "# polars_df\n",
    "plt.figure(figsize=(8,8))\n",
    "\n",
    "# plot a Pie Chart for Registration Price column with label Car column\n",
    "plt.pie(polars_df[\"total_paid\"], labels = polars_df[\"payment_currency\"], autopct='%1.1f%%')\n",
    "plt.show()\n",
    "\n",
    "con.close()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "myenv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}