notebooks/politicians.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: mkwikidata in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (0.14)\r\n",
      "Requirement already satisfied: requests>=2.25.1 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from mkwikidata) (2.31.0)\r\n",
      "Requirement already satisfied: idna<4,>=2.5 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from requests>=2.25.1->mkwikidata) (3.4)\r\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from requests>=2.25.1->mkwikidata) (3.1.0)\r\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from requests>=2.25.1->mkwikidata) (2.0.3)\r\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from requests>=2.25.1->mkwikidata) (2023.5.7)\r\n",
      "\u001B[33mWARNING: You are using pip version 21.3.1; however, version 23.1.2 is available.\r\n",
      "You should consider upgrading via the '/Users/pavelerokhin/pavel/sparql/venv/bin/python -m pip install --upgrade pip' command.\u001B[0m\r\n",
      "Requirement already satisfied: matplotlib in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (3.7.1)\r\n",
      "Requirement already satisfied: importlib-resources>=3.2.0 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (5.12.0)\r\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (3.1.0)\r\n",
      "Requirement already satisfied: numpy>=1.20 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (1.24.3)\r\n",
      "Requirement already satisfied: cycler>=0.10 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (0.11.0)\r\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (4.40.0)\r\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (2.8.2)\r\n",
      "Requirement already satisfied: packaging>=20.0 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (23.1)\r\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (1.4.4)\r\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (1.1.0)\r\n",
      "Requirement already satisfied: pillow>=6.2.0 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from matplotlib) (9.5.0)\r\n",
      "Requirement already satisfied: zipp>=3.1.0 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from importlib-resources>=3.2.0->matplotlib) (3.15.0)\r\n",
      "Requirement already satisfied: six>=1.5 in /Users/pavelerokhin/pavel/sparql/venv/lib/python3.8/site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\r\n",
      "\u001B[33mWARNING: You are using pip version 21.3.1; however, version 23.1.2 is available.\r\n",
      "You should consider upgrading via the '/Users/pavelerokhin/pavel/sparql/venv/bin/python -m pip install --upgrade pip' command.\u001B[0m\r\n"
     ]
    }
   ],
   "source": [
    "!pip install mkwikidata\n",
    "!pip install matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "import mkwikidata\n",
    "import pandas as pd"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "outputs": [],
   "source": [
    "query = \"\"\"\n",
    "SELECT ?politician ?politicianLabel (GROUP_CONCAT(DISTINCT ?partyLabel; SEPARATOR = \", \") AS ?parties) (COUNT(DISTINCT ?children) AS ?numero_di_figli_in_politica) (GROUP_CONCAT(DISTINCT ?childrenLabel; SEPARATOR = \", \") AS ?figli) (GROUP_CONCAT(DISTINCT ?childrenPartyLabel; SEPARATOR = \", \") AS ?partiti_figli) WHERE {\n",
    "  {\n",
    "    SELECT ?politician ?politicianLabel ?children ?childrenLabel ?childrenPartyLabel ?partyLabel WHERE {\n",
    "      ?politician wdt:P27 wd:Q38;\n",
    "        wdt:P106 wd:Q82955;\n",
    "        wdt:P102 ?party;\n",
    "        wdt:P40 ?children.\n",
    "      ?children wdt:P102 ?childrenParty.\n",
    "      OPTIONAL { ?politician wdt:P570 ?deathDate. }\n",
    "      OPTIONAL { ?children wdt:P570 ?deathDateChildren. }\n",
    "      FILTER(!(BOUND(?deathDate)))\n",
    "      FILTER(!(BOUND(?deathDateChildren)))\n",
    "      SERVICE wikibase:label {\n",
    "        bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\".\n",
    "        ?party rdfs:label ?partyLabel.\n",
    "        ?childrenParty rdfs:label ?childrenPartyLabel.\n",
    "        ?politician rdfs:label ?politicianLabel.\n",
    "        ?children rdfs:label ?childrenLabel.\n",
    "      }\n",
    "    }\n",
    "  }\n",
    "}\n",
    "GROUP BY ?politician ?politicianLabel\n",
    "\"\"\""
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "outputs": [],
   "source": [
    "query_result = mkwikidata.run_query(query, params={})"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "outputs": [],
   "source": [
    "data = [(x[\"politicianLabel\"][\"value\"], int(x[\"numero_di_figli_in_politica\"][\"value\"])) for x in\n",
    "        query_result[\"results\"][\"bindings\"]]\n",
    "data.sort(key = lambda x: x[1])"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvsAAAGdCAYAAACMxLyUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAACjrElEQVR4nOzdd1QVV/fw8e8F5NJBsYAGBaWIIiiWRI1iDagQLBFjx957TywYC8YWW2IX0GjU2B9NbCgqaFRUsCEiSjARY2wQMIDKff/wZX65ARRsKNmftWYtZ aUfQYS9px7Zq5Ko9FoEEIIIYQQQhQ5OoUdgBBCCCGEEOLNkGRfCCGEEEKIIkqSfSGEEEIIIYooSfaFEEIIIYQooiTZF0IIIYQQooiSZF8IIYQQQogiSpJ9IYQQQgghiihJ9oUQQgghhCii9Ao7ACFE4crKyuLWrVuYmpqiUqkKOxwhhBBC5INGo Gvv/6ibNmy6OjkPX8vyb4Q/3G3bt3CxsamsMMQQgghxEu4efMmH3zwQZ7nJdkX4j/O1NQUePY/CzMzs0KORgghhBD5kZKSgo2NjfJ3PC S7AvxH5e9dMfMzEySfSGEEOI986IluPKArhBCCCGEEEWUJPtCCCGEEEIUUbKMR7w3EhISsLOz49y5c1SvXr2ww3lnhYWF0bhxYx48eICFhUW 67lM2YeO2ujNBSaEeC0SZrUq7BCEEO8RmdkXr1WjRo0YPnx4juPBwcEFSjwLg0qlYseOHa/cTkBAACqVStnMzc1p0KABR44cefUg86FevXokJSVhbm7 VvoTQgghCoNGo Hx48ekp6cXye3x48doNJpXvk4ysy/ 8zIzM9HX13 tbVatWpWDBw8CcP/ febOnYu3tze//fbbG0/C9fX1sbKyeqN9CCGEEIUpMzOTpKQkHj16VNihvFFGRkZYW1u/Up4iyb4oFP7 /jx8 JA6deqwcOFCMjIyGDlyJF988QUTJkxg9erVGBkZMW3aNHr06KFV98qVKwwcOJCzZ89ib2/Pt99 i4eHh3L 4sWLjBkzhmPHjmFsbMwnn3zCN998Q8mSJYFnnz64uLigp6fH999/T7Vq1bhx4wYAbdq0AaBChQokJCQAsHTpUubOncvNmzexs7Nj4sSJdO3a9bnj09PTUxJuKysrvvrqK4KCgrh69Sq1a9cGIDExkSFDhhAaGoqOjg5eXl4sXryYMmXKABAdHc3w4cOJjIxEpVLh4ODA8uXLqVWrFr/  iuDBw8mPDyczMxMbG1tmTNnDi1btnzpZTxCCCHE yArK4sbN26gq6tL2bJl0dfXL3JfCqnRaMjMzOTPP//kxo0bODg4PPeLs55Hkn1RaA4dOsQHH3zA0aNHiYiIoFevXhw/fpyGDRty8uRJNm3aRL9 /WjevLnWl0WMGTOGBQsWUKVKFebPn4 Pjw83btzA0tKShw8f0qRJE3r37s0333zD33//zbhx4/Dz8 PQoUNKGyEhIQwYMICIiAgASpQoQenSpQkKCsLLywtdXV0Atm/fzrBhw1iwYAHNmjVj9 7d9OjRgw8  IDGjRvna5wZGRkEBQVhYWGBk5MT8Ox/VL6 vpiYmHDkyBGePHnCoEGD6NChA2FhYQB07tyZGjVqsHTpUnR1dYmKiqJYsWIADBo0iMzMTI4ePYqxsTGXL1/GxMTklX8mQgghxLsuMzOTrKwsbGxsMDIqus aGRoaUqxYMX799VcyMzMxMDB4qXYk2ReFpkSJEixatAgdHR2cnJyYPXs2jx494osvvgBgwoQJzJo1i/DwcD7//HOl3uDBg2nXrh3wbNZ97969rF69mrFjx7JkyRJq1KjBzJkzlfJr1qzBxsaGq1ev4ujoCICDgwOzZ8/OEZOFhYXWEpi5c fi7 /PwIEDARg5ciS//PILc fOfW6yf HCBSX5fvToEaampmzatEl5j31oaCgXLlzgxo0byrfXrl27lqpVq3L69Glq165NYmIiY8aMoXLlykrM2RITE2nXrh3VqlUDoGLFivm65vDs5iMjI0PZT0lJyXddIYQQ4l3xsjPd75PXMcaif5XEO6tq1apav8RlypRRklcAXV1dLC0tuXPnjla9unXrKv/W09OjVq1axMTEAM Wvhw fBgTExNly06W4 PjlXo1a9bMV4wxMTHUr19f61j9 vWV/vLi5OREVFQUUVFRnDlzhgEDBtC fXsiIyOVdm1sbJREH6BKlSpYWFgobY8cOZLevXvTrFkzZs2apRX/0KFDmT59OvXr12fKlCmcP38 X MBCAwMxNzcXNn GYMQQgghihZJ9sVrZWZmRnJyco7jDx8 zPFgavaSlGwqlSrXY1lZWfnuPzU1FR8fHyXRzt7i4uJo2LChUs7Y2Djfbb4MfX197O3tsbe3p0aNGsyaNYty5cqxYMGCfLcREBDApUuXaNWqFYcOHaJKlSps374dgN69e3P9 nW6du3KhQsXqFWrFosXL85XuxMmTCA5OVnZbt68 TJDFEIIIcR7QJbxiNfKycmJ/fv35zh 9uxZZQnNq/rll1 UxP3JkyecOXOGwYMHA Du7s7WrVuxtbVFT69gv97FihXj6dOnWsecnZ2JiIige/fuyrGIiAiqVKlS4Lh1dXX5   /lXZv3rzJzZs3lZn1y5cv8/DhQ622HR0dcXR0ZMSIEXTs2JGgoCDlIWIbGxv69 9P//79mTBhAitXrmTIkCEvjEOtVqNWqwscvxBCCPGusx2/56319b5854XM7IvXasCAAVy9epWhQ4dy/vx5YmNjmT9/Pj/88AOjRo16LX18  23bN  nStXrjBo0CAePHhAz549gWcPrt6/f5 OHTty vRp4uPj2bdvHz169MiRyP bra0toaGh3L59mwcPHgDPHgYODg5m6dKlxMXFMX/ fLZt28bo0aOf29aTJ0 4ffs2t2/fJi4ujunTp3P58mV8fX0BaNasGdWqVaNz586cPXuWU6dO0a1bNzw8PKhVqxZ///03gwcPJiwsjF9//ZWIiAhOnz6Ns7MzAMOHD2ffvn3cuHGDs2fPcvjwYeWcEEIIId5NR48excfHh7Jly7627/d5EUn2xWtVsWJFjh49ypUrV2jWrBkffvghmzdv5scff8TLy u19DFr1ixmzZqFm5sb4eHh7Nq1S3mtZtmyZYmIiODp06d88sknVKtWjeHDh2NhYfHCh1zmzZvHgQMHsLGxoUaNGgC0bt2ahQsXMnfuXKpWrcry5csJCgqiUaNGz23r0qVLWFtbY21tTfXq1dm8eTNLly6lW7duwLPlSTt37qR48eI0bNiQZs2aUbFiRTZt2gQ8 xTg3r17dOvWDUdHR/z8/GjRogVTp04F4OnTpwwaNAhnZ2e8vLxwdHTku   e5XLKoQQQog3LC0tDTc3N7799tu31qdK8zq mksI8d5KSUnB3Nyc5ORk5W1BQgghxLsqPT2dGzduYGdnl N1lO/TMh6VSsX27dtp3bp1nmWeN9b8/v2WmX0hhBBCCCGKKEn2hRBCCCGEKKIk2RdCCCGEEKKIkmRfCCGEEEKIIkqSfSGEEEIIIYoo VItIYQQQggh3oLU1FSuXbum7N 4cYOoqChKlChB fLl30ifkuwLIYQQQogi4V3/VtvIyEgaN26s7I8cORKA7t27Exwc/Eb6lGRfCCGEEEKIt6BRo0a87a 4kjX7QgghhBBCFFGS7AshhBBCCFFEyTIe8U7SaDT069ePLVu28ODBA86dO4ebm1uOY9WrV3/lvvz9/Xn48CE7dux45bbeZy5T9qGjNirsMIQQL/Cur0kWQrxbZGZfvFb /v6oVCpUKhXFihXDzs6OsWPHkp6eXqB29u7dS3BwMLt37yYpKQkXF5dcj71Lrl27Ro8ePfjggw9Qq9XY2dnRsWNHIiMjX0v7AQEBr XmRgghhBD/HTKzL147Ly8vgoKCePz4MWfOnKF79 6oVCq /vrrfLcRHx PtbU19erVe 6xd0VkZCRNmzbFxcWF5cuXU7lyZf766y927tzJqFGjOHLkSGGHKIQQQhQpb/tB18LwOsYoM/vitVOr1VhZWWFjY0Pr1q1p1qwZBw4cUM7fu3ePjh07Uq5cOYyMjKhWrRo//PCDct7f358hQ4aQmJiISqXC1tY212Pw7BOAjz/ GAsLCywtLfH29iY Pl4rnps3b Ln54eFhQUlSpTA19eXhISEPOPPysoiMDAQOzs7DA0NcXNzY8uWLXmW12g0 Pv74 DgwLFjx2jVqhWVKlWievXqTJkyhZ07dyplL1y4QJMmTTA0NMTS0pK ffuSmpqqnA8LC6NOnToYGxtjYWFB/fr1 fXXXwkODmbq1KlER0crn5xkv6Jr/vz5VKtWDWNjY2xsbBg4cKBWm0IIIURRUqxYMQAePXpUyJG8edljzB7zy5CZffFGXbx4kePHj1OhQgXlWHp6OjVr1mTcuHGYmZmxZ88eunbtSqVKlahTpw4LFy6kUqVKrFixgtOnT6Orq4u vn6OYwBpaWmMHDkSV1dXUlNTmTx5Mm3atCEqKgodHR0eP36Mp6cndevW5dixY jp6TF9 nS8vLw4f/48 vr6OWIODAzk   /Z9myZTg4OHD06FG6dOlCqVKl8PDwyFE KiqKS5cusWHDBnR0ct4/W1hYKLFmx3L69Gnu3LlD7969GTx4MMHBwTx58oTWrVvTp08ffvjhBzIzMzl16hQqlYoOHTpw8eJF9u7dy8GDBwEwNzcHQEdHh0WLFmFnZ8f169cZOHAgY8eO5bvvvsv1Z5KRkUFGRoayn5KSks fphBCCFH4dHV1sbCw4M6dOwAYGRmhUqkKOarXS6PR8OjRI 7cuYOFhYWS97wMSfbFa7d7925MTEx48uQJGRkZ6OjosGTJEuV8uXLlGD16tLI/ZMgQ9u3bx bNm6lTpw7m5uaYmpqiq6uLlZWVUi63Y 3atdPqe82aNZQqVYrLly/j4uLCpk2byMrKYtWqVcr/CIKCgrCwsCAsLIxPPvlEq35GRgYzZ87k4MGD1K1bF4CKFSsSHh7O8uXLc0324 LiAKhcufJzr8uGDRtIT09n7dq1GBsbA7BkyRJ8fHz4 uuvKVasGMnJyXh7e1OpUiUAnJ2dlfomJibo6elpjR9g PDhyr9tbW2ZPn06/fv3zzPZDwwMZOrUqc NVQghhHiXZf8tzE74iyoLC4scf/cLSpJ98do1btyYpUuXkpaWxjfffIOenp5WUv706VNmzpzJ5s2b 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 tVuc5FiGEEOJ9oqur 1oS4qJMHtAVb5SOjg5ffPEFEydO5O //wYgIiICX19funTpgpubGxUrVuTq1asFbvvevXvExsYyceJEmjZtirOzMw8ePNAq4 7uTlxcHKVLl8be3l5ry17z/k9VqlRBrVaTmJiYo3xes9/Vq1enSpUqzJs3T/lk4Z8ePnwIPFuSEx0dTVpamnIuIiICHR0dnJyclGM1atRgwoQJHD9 HBcXFzZs2ACAvr4 T58 1Wr7zJkzZGVlMW/ePD766CMcHR25detW/i6gEEIIIYo8SfbFG9e fXt0dXX59ttvAXBwcODAgQMcP36cmJgY vXrxx9//FHgdosXL46lpSUrVqzg2rVrHDp0SGt5CkDnzp0pWbIkvr6 HDt2jBs3bhAWFsbQoUP57bffcrRpamrK6NGjGTFiBCEhIcTHx3P27FkWL15MSEhIrnGoVCqCgoK4evUqDRo04KeffuL69eucP3 eGTNm4Ovrq8RiYGBA9 7duXjxIocPH2bIkCF07dqVMmXKcOPGDSZMmMCJEyf49ddf2b9/P3Fxccq6fVtbW27cuEFUVBR3794lIyMDe3t7Hj9 zOLFi7l /Trr1q1j2bJlBb6WQgghhCiaJNkXb5yenh6DBw9m9uzZpKWlMXHiRNzd3fH09KRRo0ZYWVnRunXrArero6PDxo0bOXPmDC4uLowYMYI5c ZolTEyMuLo0aOUL1 etm3b4uzsTK9evUhPT8fMzCzXdqdNm8akSZMIDAzE2dkZLy8v9uzZg52dXZ6x1KlTh8jISOzt7enTpw/Ozs58 umnXLp0iQULFiix7Nu3j/v371O7dm0   wzmjZtqjy8bGRkxJUrV2jXrh2Ojo707duXQYMG0a9fP DZw8heXl40btyYUqVK8cMPP Dm5sb8 fP5 uuvcXFxYf369QQGBhb4WgohhBCiaFJp/gvfSCCEyFNKSgrm5uYkJyfneQMkhBBCiHdLfv9 y8y EEIIIYQQRZQk 0IIIYQQQhRRkuwLIYQQQghRREmyL4QQQgghRBElyb4QQgghhBBFlCT7QgghhBBCFFGS7AshhBBCCFFESbIvhBBCCCFEESXJvhBCCCGEEEWUJPtCCCGEEEIUUXqFHYD47/L39 fhw4fs2LGjsEN5ZwUHBzN8 HAePnyY7zqNGjWievXqLFiwoEB9uUzZh47aqGABCiHeuoRZrQo7BCHEe0Rm9sUb4 /vj0qlQqVSoa vj729PV999RVPnjwBYOHChQQHB e7vbCwMFQqVYES34LIbr948eKkp6drnTt9 rQylrepQ4cOXL16tUB1tm3bxrRp095QREIIIYR4n0iyL94oLy8vkpKSiIuLY9SoUQQEBDBnzhwAzM3NsbCweO19ZmZmvlJ9U1NTtm/frnVs9erVlC9f/pXafRmGhoaULl26QHVKlCiBqanpG4pICCGEEO8TSfbFG6VWq7GysqJChQoMGDCAZs2asWvXLuDZzH/r1q2VsllZWQQGBmJnZ4ehoSFubm5s2bIFgISEBBo3bgxA8eLFUalU Pv7A8 WrQwePJjhw4dTsmRJPD09AThy5Ah16tRBrVZjbW3N PHjlU8Vnqd79 6sWbNG2f/777/ZuHEj3bt31yp37949OnbsSLly5TAyMqJatWr88MMPWmUaNWrE0KFDGTt2LCVKlMDKyoqAgACtMg8fPqRfv36UKVMGAwMDXFxc2L17N/BsGc8/b4gCAgKoXr0669atw9bWFnNzcz7//HP  usvrT6HDx/ wnEKIYQQouiTZF 8VYaGhnnOvAcGBrJ27VqWLVvGpUuXGDFiBF26dOHIkSPY2NiwdetWAGJjY0lKSmLhwoVK3ZCQEPT19YmIiGDZsmX8/vvvtGzZktq1axMdHc3SpUtZvXo106dPf2GMXbt25dixYyQmJgKwdetWbG1tcXd31yqXnp5OzZo12bNnDxcvXqRv37507dqVU6dOaZULCQnB2NiYkydPMnv2bL766isOHDgAPLvBadGiBREREXz//fdcvnyZWbNmoaurm2d88fHx7Nixg927d7N7926OHDnCrFmzXjiubBkZGaSkpGhtQgghhCia5AFd8VZoNBpCQ0PZt28fQ4YMyXE IyODmTNncvDgQerWrQtAxYoVCQ8PZ/ny5Xh4eFCiRAkASpcunWP5j4ODA7Nnz1b2v/zyS2xsbFiyZAkqlYrKlStz69Ytxo0bx TJk9HRyfs t3Tp0rRo0YLg4GAmT57MmjVr6NmzZ45y5cqVY/To0cr kCFD2LdvH5s3b6ZOnTrKcVdXV6ZMmaLEuWTJEkJDQ2nevDkHDx7k1KlTxMTE4OjoqIz7ebKysggODlaW6nTt2pXQ0FBmzJjx3HrZAgMDmTp1ar7KCiGEEOL9JjP74o3avXs3JiYmGBgY0KJFCzp06JBjGQvAtWvXePToEc2bN8fExETZ1q5dS3x8/Av7qVmzptZ TEwMdevW1Xqgtn79 qSmpvLbb7 9sL2ePXsSHBzM9evXOXHiBJ07d85R5unTp0ybNo1q1apRokQJTExM2Ldvn/KJQDZXV1etfWtra 7cuQNAVFQUH3zwgZLo54etra3Wmvx/tpcfEyZMIDk5Wdlu3ryZ77pCCCGEeL/IzL54oxo3bszSpUvR19enbNmy6Onl/iuXmpoKwJ49eyhXrpzWObVa/cJ jI2NXz3Yf2jRogV9 /alV69e Pj4YGlpmaPMnDlzWLhwIQsWLKBatWoYGxszfPjwHMuUihUrprWvUqnIysoCni1rKqjntZcfarU6X9dUCCGEEO8/SfbFG2VsbIy9vf0Ly1WpUgW1Wk1iYiIeHh65ltHX1weezai/iLOzM1u3bkWj0Siz xEREZiamvLBBx 8sL6enh7dunVj9uzZ/Pzzz7mWiYiIwNfXly5dugDPltdcvXqVKlWqvLD9bK6urvz2229cvXq1QLP7QgghhBD5Ict4xDvB1NSU0aNHM2LECEJCQoiPj fs2bMsXryYkJAQACpUqIBKpWL37t38 eefyqcBuRk4cCA3b95kyJAhXLlyhZ07dzJlyhRGjhz53PX6/zRt2jT /PNP5e0 / bg4MCBAwc4fvw4MTEx9OvXjz/  KNA4/bw8KBhw4a0a9eOAwcOcOPGDX7  Wf27t1boHaEEEIIIXIjM/vinTFt2jRKlSpFYGAg169fx8LCAnd3d7744gvg2QOxU6dOZfz48fTo0YNu3brl aVc5cqV46effmLMmDG4ublRokQJevXqxcSJE/Mdj76 PiVLlszz/MSJE7l /Tqenp4YGRnRt29fWrduTXJycoHGvXXrVkaPHk3Hjh1JS0vD3t6 QG/XeV0uTvXEzMzsrfcrhBBCiDdHpdFoNIUdhBCi8KSkpGBubk5ycrIk 0IIIcR7Ir9/v2UZjxBCCCGEEEWUJPtCCCGEEEIUUZLsCyGEEEIIUURJsi EEEIIIUQRJcm EEIIIYQQRZQk 0IIIYQQQhRRkuwLIYQQQghRREmyL4QQQgghRBElyb4QQgghhBBFlF5hByCEeDWJiYmEhIQwatQojIyMXrodlyn70FG/fH0hxNuRMKtVYYcghHiPyMy KHKCg4OxsLAo7DDemvLly/PHH38wePDgwg5FCCGEEO8YSfbFW Pv749KpaJ///45zg0aNAiVSoW/v/8r99OhQweuXr36Sm0EBARQvXr1V47lbVm0aBH37t3j   /L xQhBBCCPEOkWRfvFU2NjZs3LiRv// WzmWnp7Ohg0bKF  /Cu3//jxYwwNDSlduvQrt/U 0dHRYefOnXTp0qWwQxFCCCHEO0SSffFWubu7Y2Njw7Zt25Rj27Zto3z58tSoUUOr7N69e/n444 xsLDA0tISb29v4uPjlfMJCQmoVCo2bdqEh4cHBgYGrF /PtdlPEuXLqVSpUro6 vj5OTEunXrXmkc69ato1atWpiammJlZUWnTp24c eOVpldu3bh4OCAgYEBjRs3JiQkBJVKxcOHDwG4d 8eHTt2pFy5chgZGVGtWjV  OEHrTYaNWrE0KFDGTt2LCVKlMDKyoqAgACtMvPnz6datWoYGxtjY2PDwIEDSU1NfaXxCSGEEKJokGRfvHU9e/YkKChI2V zZg09evTIUS4tLY2RI0cSGRlJaGgoOjo6tGnThqysLK1y48ePZ9iwYcTExODp6Zmjne3btzNs2DBGjRrFxYsX6devHz169ODw4cMvPYbHjx8zbdo0oqOj2bFjBwkJCVpLkG7cuMFnn31G69atiY6Opl /fnz55ZdabaSnp1OzZk327NnDxYsX6du3L127duXUqVNa5UJCQjA2NubkyZPMnj2br776igMHDijndXR0WLRoEZcuXSIkJIRDhw4xduzYPGPPyMggJSVFaxNCCCFE0aTSaDSawg5C/Df4 /vz8OFDVq5ciY2NDbGxsQBUrlyZmzdv0rt3bywsLAgODs61/t27dylVqhQXLlzAxcWFhIQE7OzsWLBgAcOGDVPKBQcHM3z4cGUGvX79 lStWpUVK1YoZfz8/EhLS2PPnj259hUQEMCOHTuIiorK19giIyOpXbs2f/31FyYmJowfP549e/Zw4cIFpczEiROZMWMGDx48yPMBYm9vbypXrszcuXOBZzP7T58 5dixY0qZOnXq0KRJE2bNmpVrG1u2bKF///7cvXs3z7FNnTo1x3Gb4ZvlbTxCvAfkbTxCCICUlBTMzc1JTk7GzMwsz3Iysy/eulKlStGqVSuCg4MJCgqiVatWlCxZMke5uLg4OnbsSMWKFTEzM8PW1hZ49qrJf6pVq9Zz 4uJiaF /fpax rXr09MTMxLj HMmTP4 PhQvnx5TE1N8fDw0IotNjaW2rVra9WpU6eO1v7Tp0 ZNm0a1apVo0SJEpiYmLBv374c43N1ddXat7a21loydPDgQZo2bUq5cuUwNTWla9eu3Lt3j0ePHuUa 4QJE0hOTla2mzdvvtxFEEIIIcQ7T5J9USh69uxJcHAwISEh9OzZM9cyPj4 3L9/n5UrV3Ly5ElOnjwJQGZmplY5Y2PjNx7vP6WlpeHp6YmZmRnr16/n9OnTbN  PdfYnmfOnDksXLiQcePGcfjwYaKiovD09MzRRrFixbT2VSqVspQpISEBb29vXF1d2bp1K2fOnOHbb799bixqtRozMzOtTQghhBBFk3ypligUXl5eZGZmolKpcl1nf /ePWJjY1m5ciUNGjQAIDw8/KX6cnZ2JiIigu7duyvHIiIiqFKlyku1d XKFe7du8esWbOwsbEBni3j ScnJyd  uknrWOnT5/W2o IiMDX11d5g05WVhZXr14tUFxnzpwhKyuLefPmoaPz7N598 bNBR6TEEIIIYomSfZFodDV1VWW0ejq6uY4X7x4cSwtLVmxYgXW1tYkJiYyfvz4l przJgx Pn5UaNGDZo1a8b//vc/tm3bxsGDB59b7  //86xZt/U1JTy5cujr6/P4sWL6d /PxcvXmTatGla5fr168f8 fMZN24cvXr1IioqSnkWQaVSAeDg4MCWLVs4fvw4xYsXZ/78 fzxxx8FSvbt7e15/PgxixcvxsfHh4iICJYtW5bv kIIIYQo2iTZF4XmuQ T6OiwceNGhg4diouLC05OTixatIhGjRoVuJ/WrVuzcOFC5s6dy7Bhw7CzsyMoKOiFbV29ejXH60CbNm3KwYMHCQ4O5osvvmDRokW4u7szd 5cPv30U6WcnZ0dW7ZsYdSoUSxcuJC6devy5ZdfMmDAANRqNfDsgd3r16/j6emJkZERffv2pXXr1iQnJ d7bG5ubsyfP5 vv/6aCRMm0LBhQwIDA nWrVv L9D/d3GqpyzpEUIIIYoYeRuPEG/JjBkzWLZs2Tv3QGx n YXQgghxLsjv3 /ZWZfiDfku   o3bt2lhaWhIREcGcOXMYPHhwYYclhBBCiP8QSfaFeEPi4uKYPn069 /fp3z58owaNYoJEyYUdlhCCCGE A RZTxC/MfJMh4hhBDi/SNfqiWEEEIIIcR/nCT7QgghhBBCFFGS7AshhBBCCFFESbIvhBBCCCFEESXJvhBCCCGEEEWUJPtCCCGEEEIUUfKeffFGBQcHM3z4cB4 fAhAQEAAO3bsICoqqlDjep oVCq2b99O69atSUhIwM7OjnPnzlG9evXX2o/LlH3oqI1ea5tCiNcvYVarwg5BCPEekZn9XPj7 6NSqXJs165dK zQ3kk//PADurq6DBo0qFDjCA4OxsLC4rW1d 7cOdq3b0 ZMmUwMDDAwcGBPn36cPXq1dfWhxBCCCHEmyTJfh68vLxISkrS2uzs7HKUy8zMLITo3i2rV69m7Nix/PDDD6SnpxdKDI8fP36t7e3evZuPPvqIjIwM1q9fT0xMDN9//z3m5uZMmjTptfYlhBBCCPGmSLKfB7VajZWVldamq6tLo0aNGDx4MMOHD6dkyZJ4enoCMH/ fKpVq4axsTE2NjYMHDiQ1NRUpb3sWed9 /bh7OyMiYmJckPxT2vWrKFq1aqo1Wqsra0ZPHiwcu7hw4f07t2bUqVKYWZmRpMmTYiOjlbOR0dH07hxY0xNTTEzM6NmzZpERkYq5yMiImjUqBFGRkYUL14cT09PHjx4AEBGRgZDhw6ldOnSGBgY8PHHH3P69OkXXqcbN25w/Phxxo8fj6OjI9u2bcvX9V2 fDk2NjYYGRnh5 dHcnKy1vlVq1bh7OyMgYEBlStX5rvvvlPOJSQkoFKp2LRpEx4eHhgYGLB /Xp69OhBcnKy8klMQEAAAA8ePKBbt24UL14cIyMjWrRoQVxcXJ6xPXr0iB49etCyZUt27dpFs2bNsLOz48MPP2Tu3LksX75cKXvkyBHq1Kmj/LzGjx/PkydPAFixYgVly5YlKytLq31fX1969uyp7O/cuRN3d3cMDAyoWLEiU6dOVdrIj fFIIQQQoj/Nkn2X0JISAj6 vpERESwbNkyAHR0dFi0aBGXLl0iJCSEQ4cOMXbsWK16jx49Yu7cuaxbt46jR4 SmJjI6NGjlfNLly5l0KBB9O3blwsXLrBr1y7s7e2V8 3bt fOnTv8/PPPnDlzBnd3d5o2bcr9 /cB6Ny5Mx988AGnT5/mzJkzjB8/nmLFigEQFRVF06ZNqVKlCidOnCA8PBwfHx ePn0KwNixY9m6dSshISGcPXsWe3t7PD09lbbzEhQURKtWrTA3N6dLly6sXr36hdfv2rVrbN68mf/973/s3buXc fOMXDgQOX8 vXrmTx5MjNmzCAmJoaZM2cyadIkQkJCtNoZP348w4YNIyYmhsaNG7NgwQLMzMyUT2Kyr62/vz RkZHs2rWLEydOoNFoaNmyZZ6fBuzbt4 7d /m Plly14q9Pvvv9OyZUtq165NdHQ0S5cuZfXq1UyfPh149vO6d 8ehw8fVurev3 fvXv30rlzZwCOHTtGt27dGDZsGJcvX2b58uUEBwczY8aMF17H/MQghBBCiP82eUA3D7t378bExETZb9GiBT/  CMADg4OzJ49W6v88OHDlX/b2toyffp0 vfvrzUj/fjxY5YtW0alSpUAGDx4MF999ZVyfvr06YwaNYphw4Ypx2rXrg1AeHg4p06d4s6dO6jVagDmzp3Ljh072LJlC3379iUxMZExY8ZQuXJlJc5ss2fPplatWlrxVK1aFYC0tDSWLl1KcHAwLVq0AGDlypUcOHCA1atXM2bMmFyvUVZWFsHBwSxevBiAzz//nFGjRnHjxo1clzxlS09PZ 3atZQrVw6AxYsX06pVK bNm4eVlRVTpkxh3rx5tG3bFgA7OzslEe7evbvWNc8uA2Bubo5KpcLKyko5FhcXx65du4iIiKBevXrAs5sJGxsbduzYQfv27XPElz3rn30d8/Ldd99hY2PDkiVLUKlUVK5cmVu3bjFu3DgmT55M8eLFadGiBRs2bKBp06YAbNmyhZIlS9K4cWMApk6dyvjx45VxVaxYkWnTpjF27FimTJny3P7zE4OOTs77 YyMDDIyMpT9lJSUF/YjhBBCiPeTzOznoXHjxkRFRSnbokWLlHM1a9bMUf7gwYM0bdqUcuXKYWpqSteuXbl37x6PHj1SyhgZGSmJPoC1tTV37twB4M6dO9y6dUtJCv8tOjqa1NRULC0tMTExUbYbN24QHx8PwMiRI nduzfNmjVj1qxZynH4v5n93MTHx/P48WPq16 vHCtWrBh16tQhJiYmz2t04MAB0tLSaNmyJQAlS5akefPmrFmzJs86AOXLl1cSfYC6deuSlZVFbGwsaWlpxMfH06tXL61xTp8 XWs8ALVq1XpuPwAxMTHo6enx4YcfKscsLS1xcnLKc2wajeaF7Wa3XbduXVQqlXKsfv36pKam8ttvvwHPPm3ZunWrklyvX7 ezz//XEnCo6Oj eqrr7TG2qdPH5KSkrR d14lhn8LDAzE3Nxc2WxsbPI1XiGEEEK8f2RmPw/GxsZaS2j fe6fEhIS8Pb2ZsCAAcyYMYMSJUoQHh5Or169yMzMxMjo2esMs5fUZFOpVEpiaWho Nx4UlNTsba2JiwsLMe57GUlAQEBdOrUiT179vDzzz8zZcoUNm7cSJs2bV7Y/stYvXo19 /f12o7KyuL8 fPM3Xq1FxnlV8k zmHlStXaiXoALq6ulr7//45vC6Ojo4AXLlyhbp1675SWz4 Pmg0Gvbs2UPt2rU5duwY33zzjXI NTWVqVOnan1Ckc3AwOCV s7LhAkTGDlypLKfkpIiCb8QQghRRMnM/mtw5swZsrKymDdvHh999BGOjo7cunWrQG2Ymppia2tLaGhorufd3d25ffs2enp62Nvba20lS5ZUyjk6OjJixAj2799P27ZtCQoKAsDV1TXPtitVqqQ8g5Dt8ePHnD59mipVquRa5969e zcuZONGzdqfQJy7tw5Hjx4wP79 /Mca2Jiotb1 eWXX9DR0cHJyYkyZcpQtmxZrl /nmOcz1saBKCvr688g5DN2dmZJ0 ecPLkSa3YY2Nj8xzbJ598QsmSJXMs1cqW/Z0Bzs7OyjMA2SIiIjA1NeWDDz4AniXsbdu2Zf369fzwww84OTnh7u6ulHd3dyc2NjbHWO3t7fN1s5SfGP5NrVZjZmamtQkhhBCiaJKZ/dfA3t6ex48fs3jxYnx8fLQe3C2IgIAA vfvT nSpWnRogV//fUXERERDBkyhGbNmlG3bl1at27N7NmzlRuKPXv20KZNG6pWrcqYMWP47LPPsLOz47fffuP06dO0a9cOeDabW61aNQYOHEj//v3R19fn8OHDtG/fnpIlSzJgwADGjBlDiRIlKF  PLNnz bRo0f06tUr11jXrVuHpaUlfn5 WktIAFq2bMnq1avx8vLKta6BgQHdu3dn7ty5pKSkMHToUPz8/JS19lOnTmXo0KGYm5vj5eVFRkYGkZGRPHjwQGtG t9sbW1JTU0lNDQUNzc3jIyMcHBwwNfXlz59 rB8 XJMTU0ZP3485cqVw9fXN9d2jI2NWbVqFe3bt fTTz9l6NCh2Nvbc/fuXTZv3kxiYiIbN25k4MCBLFiwgCFDhjB48GBiY2OZMmUKI0eO1ErUO3fujLe3N5cuXaJLly5afU2ePBlvb2/Kly/PZ599ho6ODtHR0Vy8eDFfD9nmNwYhhBBC/DdJNvAauLm5MX/ fL7  mtcXFxYv349gYGBBW6ne/fuLFiwgO   46qVavi7e2tPCyqUqn46aefaNiwIT169MDR0ZHPP/ cX3/9lTJlyqCrq8u9e/fo1q0bjo6O Pn50aJFC6ZOnQo8m/Hfv38/0dHR1KlTh7p167Jz50709J7d782aNYt27drRtWtX3N3duXbtGvv27aN48eK5xrpmzRratGmTI9EHaNeuHbt27eLu3bu51rW3t6dt27a0bNmSTz75BFdXV60Hh3v37s2qVasICgqiWrVqeHh4EBwc/MKZ/Xr16tG/f386dOhAqVKllJn5oKAgatasibe3N3Xr1kWj0fDTTz/lWFb1T76 vhw/fpxixYrRqVMnKleuTMeOHUlOTlaS8HLlyvHTTz9x6tQp3Nzc6N /P7169WLixIlabTVp0oQSJUoQGxtLp06dtM55enqye/du9u/fT 3atfnoo4/45ptvqFChwnPHmi2/MQghhBDiv0mlye/TiEKIIiklJQVzc3OSk5NlSY8QQgjxnsjv32 Z2RdCCCGEEKKIkmRfCCGEEEKIIkqSfSGEEEIIIYooSfaFEEIIIYQooiTZF0IIIYQQooiSZF8IIYQQQogiSpJ9IYQQQgghiihJ9oUQQgghhCiiJNkXQgghhBCiiJJkXwghhBBCiCJKr7ADEOJtsLW1Zfjw4QwfPrywQ3lnuUzZh47aqLDDEEK8QMKsVoUdghDiPSIz 6LAbt  zZAhQ6hYsSJqtRobGxt8fHwIDQ0t7NDeqCNHjtCkSRNKlCiBkZERDg4OdO/enczMzMIOTQghhBAiV5LsiwJJSEigZs2aHDp0iDlz5nDhwgX27t1L48aNGTRo0Eu3 /TpU7Kysl5jpK/X5cuX8fLyolatWhw9epQLFy6wePFi9PX1efr0aWGHJ4QQQgiRK0n2RYEMHDgQlUrFqVOnaNeuHY6OjlStWpWRI0fyyy /KOXmz59PtWrVMDY2xsbGhoEDB5KamqqcDw4OxsLCgl27dlGlShXUajWJiYnY2toyffp0unXrhomJCRUqVGDXrl38 eef Pr6YmJigqurK5GRkVpxhYeH06BBAwwNDbGxsWHo0KGkpaXlOY7ExESlPTMzM/z8/Pjjjz/yLL9//36srKyYPXs2Li4uVKpUCS8vL1auXImhoaFSLiIigkaNGmFkZETx4sXx9PTkwYMHAGRkZDB06FBKly6NgYEBH3/8MadPn1bqhoWFoVKp2LdvHzVq1MDQ0JAmTZpw584dfv75Z5ydnTEzM6NTp048evRIqbd3714 /vhjLCwssLS0xNvbm/j4 Hz8NIUQQghR1EmyL/Lt/v377N27l0GDBmFsbJzjvIWFhfJvHR0dFi1axKVLlwgJCeHQoUOMHTtWq/yjR4/4 uuvWbVqFZcuXaJ06dIAfPPNN9SvX59z587RqlUrunbtSrdu3ejSpQtnz56lUqVKdOvWDY1GA0B8fDxeXl60a9eO8 fPs2nTJsLDwxk8eHCu48jKysLX15f79 9z5MgRDhw4wPXr1 nQoUOeY7eysiIpKYmjR4/mWSYqKoqmTZtSpUoVTpw4QXh4OD4 PsrM/9ixY9m6dSshISGcPXsWe3t7PD09uX//vlY7AQEBLFmyhOPHj3Pz5k38/PxYsGABGzZsYM ePezfv5/Fixcr5dPS0hg5ciSRkZGEhoaio6NDmzZt8vykJCMjg5SUFK1NCCGEEEWTSpOdMQnxAqdOneLDDz9k27ZttGnTpkB1t2zZQv/ /bl79y7wbGa/R48eREVF4ebmppSztbWlQYMGrFu3Dnj2fIC1tTWTJk3iq6  AuCXX36hbt26JCUlYWVlRe/evdHV1WX58uVKO Hh4Xh4eJCWloaBgYHWA7oHDhygRYsW3LhxAxsbG DZMp2qVaty6tQpateunSP p0 f0rt3b4KDg7GysuKjjz6iadOmdOvWDTMzMwA6depEYmIi4eHhOeqnpaVRvHhxgoOD6dSpEwCPHz9W4hozZgxhYWE0btyYgwcP0rRpUwBmzZrFhAkTiI Pp2LFigD079 fhIQE9u7dm u1vnv3LqVKleLChQu4uLjkOB8QEMDUqVNzHLcZvlke0BXiPSAP6AohAFJSUjA3Nyc5OVnJRXIjM/si3wpyX5idsJYrVw5TU1O6du3KvXv3tJaf6Ovr4 rqmqPuP4 VKVMGgGrVquU4dufOHQCio6MJDg7GxMRE2Tw9PcnKyuLGjRs52o JicHGxkZJ9AGqVKmChYUFMTExuY5HV1eXoKAgfvvtN2bPnk25cuWYOXMmVatWJSkpCfi/mf3cxMfH8/jxY rXr68cK1asGHXq1MnR57/Hb2RkpCT62ceyxw4QFxdHx44dqVixImZmZtja2gLPlirlZsKECSQnJyvbzZs3cy0nhBBCiPefJPsi3xwcHFCpVFy5cuW55RISEvD29sbV1ZWtW7dy5swZvv32WwCtN9cYGhqiUqly1C9WrJjy7 zzuR3LXqaSmppKv379iIqKUrbo6Gji4uKoVKnSS442d XKlaNr164sWbKES5cukZ6ezrJly5TxvA7/Hus/97OP/XOJjo PD/fv32flypWcPHmSkydPAuT5liC1Wo2ZmZnWJoQQQoiiSZJ9kW8lSpTA09OTb7/9NteHXx8 fAjAmTNnyMrKYt68eXz00Uc4Ojpy69atNxaXu7s7ly9fxt7ePsemr6 fo7yzszM3b97UmtG fPkyDx8 pEqVKvnut3jx4lhbWyvXwtXVNc/Xj1aqVAl9fX0iIiKUY48fP b06dMF6vPf7t27R2xsLBMnTqRp06Y4OzsrDwQLIYQQQkiyLwrk22 /5enTp9SpU4etW7cSFxdHTEwMixYtom7dugDY29vz PFjFi9ezPXr11m3bp0y /0mjBs3juPHjzN48GCioqKIi4tj586deT6g26xZM6pVq0bnzp05e/Ysp06dolu3bnh4eFCrVq1c6yxfvpwBAwawf/9 4uPjuXTpEuPGjePSpUv4 PgAz5bHnD59moEDB3L /HmuXLnC0qVLuXv3LsbGxgwYMIAxY8awd 9eLl  TJ8 fXj06BG9evV66bEXL14cS0tLVqxYwbVr1zh06BAjR4586faEEEIIUbRIsi8KpGLFipw9e5bGjRszatQoXFxcaN68OaGhoSxduhQANzc35s fz9dff42Liwvr168nMDDwjcXk6urKkSNHuHr1Kg0aNKBGjRpMnjyZsmXL5lpepVKxc dOihcvTsOGDWnWrBkVK1Zk06ZNefZRp04dUlNT6d /P1WrVsXDw4NffvmFHTt24OHhAYCjoyP79 8nOjqaOnXqULduXXbu3Ime3rMvqp41axbt2rWja9euuLu7c 3aNfbt20fx4sVfeuw6Ojps3LiRM2fO4OLiwogRI5gzZ85LtyeEEEKIokXexiPEf1x n YXQgghxLtD3sYjhBBCCCHEf5wk 0IIIYQQQhRRkuwLIYQQQghRREmyL4QQQgghRBElyb4QQgghhBBFlCT7QgghhBBCFFGS7AshhBBCCFFESbIvhBBCCCFEESXJvhBCCCGEEEWUJPtCCCGEEEIUUXqFHYAQ74Pg4GCGDx/Ow4cPCzuUFwoLC6Nx48Y8ePAACwuLfNdzmbIPHbXRmwtMCPFaJMxqVdghCCHeIzKzL94Yf39/WrduXdhh5MuRI0do0qQJJUqUwMjICAcHB7p3705mZiYAHTp04OrVq4UcZf7Uq1ePpKQkzM3NCzsUIYQQQhQySfbFf97ly5fx8vKiVq1aHD16lAsXLrB48WL09fV5 vQpAIaGhpQuXbqQI80ffX19rKysUKlUhR2KEEIIIQqZJPvirVixYgVly5YlKytL67ivry89e/YEID4 Hl9fX8qUKYOJiQm1a9fm4MGDWuVtbW2ZOXMmPXv2xNTUlPLly7NixQqtMuPGjcPR0REjIyMqVqzIpEmTePz4cZ6x7d /HysrK2bPno2LiwuVKlXCy8uLlStXYmhoCDxbxvPPJTEBAQFUr16dNWvWUL58eUxMTBg4cCBPnz5l9uzZWFlZUbp0aWbMmKHV18OHD nduzelSpXCzMyMJk2aEB0drVVm6dKlVKpUCX19fZycnFi3bp3WeZVKxapVq2jTpo3yKcSuXbuU82FhYahUqvdiyZEQQggh3ixJ9sVb0b59e 7du8fhw4eVY/fv32fv3r107twZgNTUVFq2bEloaCjnzp3Dy8sLHx8fEhMTtdqaN28etWrV4ty5cwwcOJABAwYQGxurnDc1NSU4OJjLly zcOFCVq5cyTfffJNnbFZWViQlJXH06NECjSk Pp6ff/6ZvXv38sMPP7B69WpatWrFb7/9xpEjR/j666 ZOHEiJ0 e1LoOd 7c4eeff bMmTO4u7vTtGlT7t /D8D27dsZNmwYo0aN4uLFi/Tr148ePXpoXTeAqVOn4ufnx/nz52nZsiWdO3dW2niRjIwMUlJStDYhhBBCFE2S7Iu3onjx4rRo0YINGzYox7Zs2ULJkiVp3LgxAG5ubvTr1w8XFxccHByYNm0alSpV0pq1BmjZsiUDBw7E3t6ecePGUbJkSa1keOLEidSrVw9bW1t8fHwYPXo0mzdvzjO29u3b07FjRzw8PLC2tqZNmzYsWbLkhUlwVlYWa9asoUqVKvj4 NC4cWNiY2NZsGABTk5O9OjRAycnJyW28PBwTp06xY8//kitWrVwcHBg7ty5WFhYsGXLFgDmzp2Lv78/AwcOxNHRkZEjR9K2bVvmzp2r1be/vz8dO3bE3t6emTNnkpqayqlTp/Lxk4DAwEDMzc2VzcbGJl/1hBBCCPH kWRfvDWdO3dm69atZGRkALB /Xo //xzdHSe/RqmpqYyevRonJ2dsbCwwMTEhJiYmBwz 66ursq/VSoVVlZW3LlzRzm2adMm6tevj5WVFSYmJkycODFHG/ kq6tLUFAQv/32G7Nnz6ZcuXLMnDmTqlWrkpSUlGc9W1tbTE1Nlf0yZcpQpUoVZTzZx7Jji46OJjU1FUtLS0xMTJTtxo0bxMfHAxATE0P9 vW1 qlfvz4xMTF5XgNjY2PMzMy0rsHzTJgwgeTkZGW7efNmvuoJIYQQ4v0jr94Ub42Pjw8ajYY9e/ZQu3Ztjh07prW8ZvTo0Rw4cIC5c dib2 PoaEhn332mfJGnGzFihXT2lepVMqzACdOnKBz585MnToVT09PzM3N2bhxI/PmzXthfOXKlaNr16507dqVadOm4ejoyLJly5g6dWqu5XOL43mxpaamYm1tTVhYWI62CvKKzLz6/vfzEHlRq9Wo1eoC9SeEEEKI95Mk  KtMTAwoG3btqxfv55r167h5OSEu7u7cj4iIgJ/f3/atGkDPEuOExISCtTH8ePHqVChAl9  aVy7Ndffy1wrMWLF8fa2pq0tLQC182Lu7s7t2/fRk9PD1tb21zLODs7ExERQffu3ZVjERERVKlS5bXFIYQQQoj/Dkn2xVvVuXNnvL29uXTpEl26dNE65 DgwLZt2/Dx8UGlUjFp0qR8z1b/s43ExEQ2btxI7dq12bNnD9u3b39uneXLlxMVFUWbNm2oVKkS6enprF27lkuXLrF48eICjzEvzZo1o27durRu3ZrZs2fj6OjIrVu32LNnD23atKFWrVqMGTMGPz8/atSoQbNmzfjf//7Htm3bcryVSAghhBAiPyTZF29V9hdXxcbG0qlTJ61z8 fPp2fPntSrV4 SJUsybty4Ar8p5tNPP2XEiBEMHjyYjIwMWrVqxaRJkwgICMizTp06dQgPD6d///7cunULExMTqlatyo4dO/Dw8HiZYeZKpVLx008/8eWXX9KjRw/ /PNPrKysaNiwIWXKlAGgdevWLFy4kLlz5zJs2DDs7OwICgqiUaNGry2OvFyc6omZmdkb70cIIYQQb49Ko9FoCjsIIUThSUlJwdzcnOTkZEn2hRBCiPdEfv9 y9t4hBBCCCGEKKIk2RdCCCGEEKKIkmRfCCGEEEKIIkqSfSGEEEIIIYooSfaFEEIIIYQooiTZF0IIIYQQooiSZF8IIYQQQogiSpJ9IYQQQgghiihJ9oUQQgghhCii9Ao7ACHEu8Flyj501EaFHYYQ4gUSZrUq7BCEEO8RmdkX741GjRoxfPjwwg5DCCGEEOK9Icn f5y/vz8qlUrZLC0t8fLy4vz584Ud2htha2vLggULCjsMIYQQQoi3QpJ9gZeXF0lJSSQlJREaGoqenh7e3t6v1GZmZuZL1dNoNDx58uSV hZCCCGEEM9Isi9Qq9VYWVlhZWVF9erVGT9 PDdv3uTPP/9Uyty8eRM/Pz8sLCwoUaIEvr6 JCQkKOf9/f1p3bo1M2bMoGzZsjg5OQGwbt06atWqhampKVZWVnTq1Ik7d 4o9cLCwlCpVPz888/UrFkTtVpNeHg4aWlpdOvWDRMTE6ytrZk3b16OuB88eEC3bt0oXrw4RkZGtGjRgri4uAKNXaVSsXz5cry9vTEyMsLZ2ZkTJ05w7do1GjVqhLGxMfXq1SM Pl6pExAQQPXq1Vm fDk2NjYYGRnh5 dHcnKyVturVq3C2dkZAwMDKleuzHfffad1/vjx41SvXh0DAwNq1arFjh07UKlUREVFaV2b0NBQatWqhZGREfXq1SM2NlarnaVLl1KpUiX09fVxcnJi3bp1BboGQgghhCi6JNkXWlJTU/n    xt7fH0tISgMePH Pp6YmpqSnHjh0jIiICExMTvLy8tGbwQ0NDiY2N5cCBA zevVupO23aNKKjo9mxYwcJCQn4 /vn6Hf8 PHMmjWLmJgYXF1dGTNmDEeOHGHnzp3s37 fsLAwzp49q1XH39 fyMhIdu3axYkTJ9BoNLRs2ZLHjx8XaMzTpk2jW7duREVFUblyZTp16kS/fv2YMGECkZGRaDQaBg8erFXn2rVrbN68mf/973/s3buXc fOMXDgQOX8 vXrmTx5MjNmzCAmJoaZM2cyadIkQkJCAEhJScHHx4dq1apx9uxZpk2bxrhx43KN78svv2TevHlERkaip6dHz549lXPbt29n2LBhjBo1iosXL9KvXz969OjB4cOH8xxvRkYGKSkpWpsQQgghiiZ5G49g9 7dmJiYAJCWloa1tTW7d 9GR fZveCmTZvIyspi1apVqFQqAIKCgrCwsCAsLIxPPvkEAGNjY1atWoW vr7S9j8T04oVK7Jo0SJq165Namqq0ifAV199RfPmzYFnNxyrV6/m   /p2nTpgCEhITwwQcfKOXj4uLYtWsXERER1KtXD3iWYNvY2LBjxw7at2 f7/H36NEDPz8/AMaNG0fdunWZNGkSnp6eAAwbNowePXpo1UlPT2ft2rWUK1cOgMWLF9OqVSvmzZuHlZUVU6ZMYd68ebRt2xYAOzs7Ll  zPLly nevTsbNmxApVKxcuVKDAwMqFKlCr///jt9 vTJEd MGTPw8PAAnt0UtWrVivT0dAwMDJg7dy7 /v7KjcbIkSP55ZdfmDt3Lo0bN851vIGBgUydOjXf10cIIYQQ7y Z2Rc0btyYqKgooqKiOHXqFJ6enrRo0YJff/0VgOjoaK5du4apqSkmJiaYmJhQokQJ0tPTtZa3VKtWTSvRBzhz5gw Pj6UL18eU1NTJWlNTEzUKlerVi3l3/Hx8WRmZvLhhx8qx0qUKKEsDQKIiYlBT09Pq4ylpSVOTk7ExMQUaPyurq7Kv8uUKaOM5Z/H0tPTtWbAy5cvryT6AHXr1iUrK4vY2FjS0tKIj4 nV69eyvUyMTFh vTpyvWKjY3F1dUVAwMDpY06deq8MD5ra2sAZSlUTEwM9evX1ypfv379516DCRMmkJycrGw3b97Ms6wQQggh3m8ysy8wNjbG3t5e2V 1ahXm5uasXLmS6dOnk5qaSs2aNVm/fn2OuqVKldJq55/S0tLw9PTE09OT9evXU6pUKRITE/H09MzxAO /675NxYoVU/6d/clFbseysrLy1V5qaioAK1eu1LoZAdDV1X0t8eU3ltyo1WrUavVL1xdCCCHE 0Nm9kUOKpUKHR0d/v77bwDc3d2Ji4ujdOnS2Nvba23m5uZ5tnPlyhXu3bvHrFmzaNCgAZUrV9Z6ODcvlSpVolixYpw8eVI59uDBA65evarsOzs78 TJE60y9 7dIzY2lipVqrzMsAskMTGRW7duKfu//PILOjo6ODk5UaZMGcqWLcv169dzXC87OzsAnJycuHDhAhkZGUobp0 fLnAczs7OREREaB2LiIh4K9dACCGEEO8 SfYFGRkZ3L59m9u3bxMTE8OQIUNITU3Fx8cHgM6dO1OyZEl8fX05duwYN27cICwsjKFDh/Lbb7/l2W758uXR19dn8eLFXL9 nV27djFt2rQXxmNiYkKvXr0YM2YMhw4d4uLFi/j7 yvPEAA4ODjg6 tLnz59CA8PJzo6mi5dulCuXDl8fX1f/aK8gIGBAd27dyc6Oppjx44xdOhQ/Pz8sLKyAmDq1KkEBgayaNEirl69yoULFwgKCmL /PkAdOrUiaysLPr27UtMTAz79u1j7ty5wP/N3ufHmDFjCA4OZunSpcTFxTF//ny2bdvG6NGjX/ ghRBCCPHekWU8gr179yprwU1NTalcuTI//vgjjRo1AsDIyIijR48ybtw42rZty19//UW5cuVo2rQpZmZmebZbqlQpgoOD eKLL1i0aBHu7u7MnTuXTz/99IUxzZkzR7nhMDU1ZdSoUTlebRkUFMSwYcPw9vYmMzOThg0b8tNPP2kte3lT7O3tadu2LS1btuT /ft4e3trvVqzd /eGBkZMWfOHMaMGYOxsTHVqlVTvgHYzMyM//3vfwwYMIDq1atTrVo1Jk eTKdOnbTW8b9I69atWbhwIXPnzmXYsGHY2dkRFBSk/OwK4uJUz f PIUQQgjx/lFpNBpNYQchxPskICCAHTt2KO/Df13Wr19Pjx49SE5OxtDQ8LW2/TwpKSmYm5uTnJwsyb4QQgjxnsjv32 Z2ReikKxdu5aKFStSrlw5oqOjGTduHH5 fm810RdCCCFE0SbJvhCF5Pbt20yePJnbt29jbW1N /btmTFjRmGHJYQQQogiRJbxCPEfJ8t4hBBCiPdPfv9 y9t4hBBCCCGEKKIk2RdCCCGEEKKIkmRfCCGEEEKIIkqSfSGEEEIIIYooSfaFEEIIIYQooiTZF0IIIYQQooiS9 wL8YpsbW0ZPnw4w4cPfyv9qVQqtm/fTuvWrV9ruy5T9qGjNnqtbQohXr EWa0KOwQhxHtEZvZFvvn7 6NSqZTN0tISLy8vzp8/X9ihvdC5c do3749ZcqUwcDAAAcHB/r06cPVq1cLO7QCS0pKokWLFoUdhhBCCCHeA5LsiwLx8vIiKSmJpKQkQkND0dPTw9vb 7l1Hj9 /Jaiy93u3bv56KOPyMjIYP369cTExPD9999jbm7OpEmTXrrdzMzM1xhl/llZWaFWqwulbyGEEEK8Xwqc7N 9e5fZs2fTpk0b6tatS926dWnTpg1z5szhzz//fBMxineIWq3GysoKKysrqlevzvjx47l586bys09ISEClUrFp0yY8PDwwMDBg/fr1BAQEUL16da22FixYgK2trbLv7 9P69atmTt3LtbW1lhaWjJo0CCtm4UHDx7QrVs3ihcvjpGRES1atCAuLi7PeB89ekSPHj1o2bIlu3btolmzZtjZ2fHhhx8yd 5cli9fDsDTp0/p1asXdnZ2GBoa4uTkxMKFC7Xayo5vxowZlC1bFicnpxz9ZY8/KipKOfbw4UNUKhVhYWHKsUuXLuHt7Y2ZmRmmpqY0aNCA Ph45fyaNWuoWrUqarUaa2trBg8erJxTqVTs2LFD2b9w4QJNmjTB0NAQS0tL vbtS2pqap7XRAghhBD/HQVK9k fPo2joyOLFi3C3Nychg0b0rBhQ8zNzVm0aBGVK1cmMjLyTcUq3jGpqal8//332NvbY2lpqXVu/PjxDBs2jJiYGDw9PfPd5uHDh4mPj fw4cOEhIQQHBxMcHCwct7f35/IyEh27drFiRMn0Gg0tGzZMs9PD/bt28fdu3cZO3ZsructLCwAyMrK4oMPPuDHH3/k8uXLTJ48mS   ILNmzdrlQ8NDSU2NpYDBw6we/fufI/rn37//XcaNmyIWq3m0KFDnDlzhp49e/LkyRMAli5dyqBBg jbty8XLlxg165d2Nvb59pWWloanp6eFC9enNOnT/Pjjz9y8OBBrZuDf8vIyCAlJUVrE0IIIUTRVKAHdIcMGUL79u1ZtmwZKpVK65xGo6F///4MGTKEEydOvNYgxbtj9 7dmJiYAM8STWtra3bv3o2OjvZ94/Dhw2nbtm2B2y9evDhLlixBV1eXypUr06pVK0JDQ nTpw9xcXHs2rWLiIgI6tWrB8D69euxsbFhx44dtG/fPkd72bP lStXfm6/xYoVY rUqcq nZ0dJ06cYPPmzfj5 SnHjY2NWbVqFfr6 gUeW7Zvv/0Wc3NzNm7cSLFixQBwdHRUzk fPp1Ro0YxbNgw5Vjt2rVzbWvDhg2kp6ezdu1ajI2NAViyZAk Pj58/fXXlClTJkedwMBArbEKIYQQougq0Mx dHQ0I0aMyJHow7OlBSNGjNBaviCKnsaNGxMVFUVUVBSnTp3C09OTFi1a8Ouvv2qVq1Wr1ku1X7VqVXR1dZV9a2tr7ty5A0BMTAx6enp8 OGHynlLS0ucnJyIiYnJtT2NRpPvvr/99ltq1qxJqVKlMDExYcWKFSQmJmqVqVat2isl gBRUVE0aNBASfT/6c6dO9y6dYumTZvmq62YmBjc3NyURB gfv36ZGVlERsbm2udCRMmkJycrGw3b958uYEIIYQQ4p1XoGTfysqKU6dO5Xn 1KlTuc4kiqLD2NgYe3t77O3tqV27NqtWrSItLY2VK1fmKPdPOjo6ORLv3Jbe/DsBVqlUZGVlvXS82TPmV65ceW65jRs3Mnr0aHr16sX /fuJioqiR48eOR7C/fe4/i37E45/jvXf4zQ0NMyz/vPOvS5qtRozMzOtTQghhBBFU4GS/dGjR9O3b1 GDRvGrl27OHnyJCdPnmTXrl0MGzaM/v3757k2WhRNKpUKHR0d/v777 eWK1WqFLdv39ZKggv6KZCzszNPnjzh5MmTyrF79 4RGxtLlSpVcq3zySefULJkSWbPnp3r YcPHwIoS4MGDhxIjRo1sLe313pgNr9KlSoFPHs9ZrZ/j9PV1ZVjx47lerNjamqKra0toaGh erP2dmZ6Oho0tLSlGMRERHo6Ojk gCxEEIIIf5bCpTsDxo0iJCQEE6ePEm7du2Ut/G0a9eOkydPEhwczMCBA99UrOIdkJGRwe3bt7l9 zYxMTEMGTKE1NRUfHx8nluvUaNG/Pnnn8yePZv4 Hi /fZbfv755wL17eDggK vL3369CE8PJzo6Gi6dOlCuXLl8PX1zbVO9hr7PXv28Omnn3Lw4EESEhKIjIxk7Nix9O/fX2k7MjKSffv2cfXqVSZNmsTp06cLFB88m5n/6KOPmDVrFjExMRw5coSJEydqlRk8eDApKSl8/vnnREZGEhcXx7p165RlNwEBAcybN49FixYRFxfH2bNnWbx4ca79de7cGQMDA7p3787Fixc5fPgwQ4YMoWvXrvIpmxBCCCEK/urNDh068Msvv/Do0SN //13fv/9dx49esQvv/yi9SCjKJr27t2LtbU11tbWfPjhh8obYBo1avTces7Oznz33Xd8  23uLm5cerUKUaPHl3g/oOCgqhZsybe3t7UrVsXjUbDTz/9lOv692y vr4cP36cYsWK0alTJypXrkzHjh1JTk5m vTpAPTr14 2bdvSoUMHPvzwQ 7du/fSN65r1qzhyZMn1KxZk HDhyt9ZLO0tOTQoUOkpqbi4eFBzZo1WblypTKG7t27s2DBAr777juqVq2Kt7d3nq8XNTIyYt  fdy/f5/atWvz2Wef0bRpU5YsWfJSsQshhBCiaFFpCvIEoxCiyElJScHc3Jzk5GRZvy EEEK8J/L791u QVcIIYQQQogiSpJ9IYQQQgghiihJ9oUQQgghhCiiJNkXQgghhBCiiJJkXwghhBBCiCJKkn0hhBBCCCGKKEn2hRBCCCGEKKIk2RdCCCGEEKKIkmRfCCGEEEKIIkqSfSHeAWFhYSxdurSwwxBCCCFEEaNX2AEI8SapVCq2b99O69atCzWOsLAwGjduzIMHD7CwsNA6d/36dbp06cKOHTte2E5CQgJ2dnacO3eO6tWrv9YYXabsQ0dt9FrbFEK8fgmzWhV2CEKI94jM7Iv3jr /PyqVCpVKRbFixShTpgzNmzdnzZo1ZGVlaZVNSkqiRYsWbyyWefPmUbx4cdLT03Oce/ToEWZmZixatIh69eqRlJSEubm5VpmMjAw //xzVq5cSa1atV7Yn42NDUlJSbi4uLy2MQghhBCi6JJkX7yXvLy8SEpKIiEhgZ9//pnGjRszbNgwvL29efLkiVLOysoKtVr9xuLo2rUraWlpbNu2Lce5LVu2kJmZSZcuXdDX18fKygqVSqVVRq1Wc rUqXzdkGRmZqKrq4uVlRV6evKhnBBCCCFeTJJ98V5Sq9VYWVlRrlw53N3d eKLL9i5cyc///wzwcHBSjmVSqUsj0lISEClUrFt2zYaN26MkZERbm5unDhxQqvtrVu3UrVqVdRqNba2tsybNy/POEqXLo2Pjw9r1qzJcW7NmjW0bt2aEiVKEBYWhkql4uHDh8r58PBwGjRogKGhITY2NgwdOpS0tDTlvK2tLdOmTaNbt26YmZnRt29fZQxRUVEASruhoaHUqlULIyMj6tWrR2xsbMEvqhBCCCGKHEn2RZHRpEkT3Nzccp1l/6cvv/yS0aNHExUVhaOjIx07dlQ DThz5gx fn58/vnnXLhwgYCAACZNmqR1A/FvvXr14tChQ/z666/KsevXr3P06FF69eqVa534 Hi8vLxo164d58 fZ9OmTYSHhzN48GCtcnPnzsXNzY1z584xadKk545p3rx5REZGoqenR8 ePfMsm5GRQUpKitYmhBBCiKJJkn1RpFSuXJmEhITnlhk9ejStWrXC0dGRqVOn8uuvv3Lt2jUA5s fT9OmTZk0aRKOjo74 /szePBg5syZk2d7np6elC1blqCgIOVYcHAwNjY2NG3aNNc6gYGBdO7cmeHDh Pg4EC9evVYtGgRa9eu1Vr/36RJE0aNGkWlSpWoVKlSnjHMmDEDDw8PqlSpwvjx4zl /HiuzxFk921ubq5sNjY2z71eQgghhHh/SbIvihSNRpNjXfy/ubq6Kv 2trYG4M6dOwDExMRQv359rfL169cnLi6Op0 f5tqerq4u3bt3Jzg4GI1GQ1ZWFiEhIfTo0QMdndz/E4uOjiY4OBgTExNl8/T0JCsrixs3bijl8vPQ7ovG9G8TJkwgOTlZ2W7evJmvPoQQQgjx/pGn/ESREhMTg52d3XPLFCtWTPl39o3Bv9/iU1A9e/YkMDCQQ4cOkZWVxc2bN nRo0ee5VNTU nXrx9Dhw7Nca58 fLKv42NjfPVf0HGpFar3 hDy0IIIYR4d0iyL4qMQ4cOceHCBUaMGPHSbTg7OxMREaF1LCIiAkdHR3R1dfOsV6lSJTw8PFizZg0ajYZmzZpRoUKFPMu7u7tz fJl7O3tXzpWIYQQQogXkWRfvJcyMjK4ffs2T58 5Y8//mDv3r0EBgbi7e1Nt27dXrrdUaNGUbt2baZNm0aHDh04ceIES5Ys4bvvvnth3V69etGnTx A5z7QCzBu3Dg  ugjBg8eTO/evTE2Nuby5cscOHCAJUuWvHT8QgghhBD/JGv2xXtp7969WFtbY2tri5eXF4cPH2bRokXs3LnzuTPwL Lu7s7mzZvZuHEjLi4uTJ48ma   gp/f/8X1m3Xrh1qtRojI6MXfmOvq6srR44c4erVqzRo0IAaNWowefJkypYt 9KxCyGEEEL8m0qj0WgKOwghROFJSUnB3Nyc5ORkzMzMCjscIYQQQuRDfv9 y8y EEIIIYQQRZQk 0IIIYQQQhRRkuwLIYQQQghRREmyL4QQQgghRBElyb4QQgghhBBFlCT7QgghhBBCFFGS7AshhBBCCFFESbIvhBBCCCFEESXJvhBCCCGEEEWUJPtCCCGEEEIUUXqFHUBh8ff35 HDh zYsaOwQ8lTQkICdnZ2nDt3jurVqxd2OG/Ny4y7UaNGVK9enQULFgBga2vL8OHDGT58 BuL82WEhYXRuHFjHjx4gIWFRWGHo8Vlyj501EaFHYYQ4gUSZrUq7BCEEO RQp3Z//PPPxkwYADly5dHrVZjZWWFp6cnERERhRnWKwkLC0OlUqFSqdDR0cHc3JwaNWowduxYkpKSCju8l6JSqd7pm6LX7Y8//qBYsWJs3Lgx1/O9evXC3d39LUclhBBCCFFwhZrst2vXjnPnzhESEsLVq1fZtWsXjRo14t69e4UZFgCZmZmvVD82NpZbt25x vRpxo0bx8GDB3FxceHChQuvKcJ3y6ter3dJmTJlaNWqFWvWrMlxLi0tjc2bN9OrV69CiEwIIYQQomAKLdl/ PAhx44d4 uvv6Zx48ZUqFCBOnXqMGHCBD799FOl3Pz586lWrRrGxsbY2NgwcOBAUlNTlfPBwcFYWFiwb98 nJ2dMTExwcvLS2sW/enTp4wcORILCwssLS0ZO3YsGo1GK55GjRoxePBghg8fTsmSJfH09ATgyJEj1KlTB7VajbW1NePHj fJkycvHF/p0qWxsrLC0dGRzz//nIiICEqVKsWAAQO0yq1atQpnZ2cMDAyoXLky3333XZ5tZn9qsG/fPmrUqIGhoSFNmjThzp07/Pzzzzg7O2NmZkanTp149OiRUm/v3r18/PHHyvi9vb2Jj49XzmdmZjJ48GCsra0xMDCgQoUKBAYGAs WwwC0adMGlUql7AcEBFC9enVWrVqFnZ0dBgYGACQmJuLr64uJiQlmZmb4 fnxxx9/PPdanTp1iho1amBgYECtWrU4d 5cjjIXL16kRYsWmJiYUKZMGbp27crdu3ef2 4/PXz4kN69e1OqVCnMzMxo0qQJ0dHReZbv1asXoaGhJCYmah3/8ccfefLkCZ07dyYrK4vAwEDs7OwwNDTEzc2NLVu2aJX/6aefcHR0xNDQkMaNG5OQkJCjr61bt1K1alXUajW2trbMmzdPOffFF1/w4Ycf5qjj5ubGV199pewX5PdICCGEEP8dhZbsm5iYYGJiwo4dO8jIyMiznI6ODosWLeLSpUuEhIRw6NAhxo4dq1Xm0aNHzJ07l3Xr1nH06FESExMZPXq0cn7evHkEBwezZs0awsPDuX//Ptu3b8/RV0hICPr6 kRERLBs2TJ //13WrZsSe3atYmOjmbp0qWsXr2a6dOnF3i8hoaG9O/fn4iICO7cuQPA vXrmTx5MjNmzCAmJoaZM2cyadIkQkJCnttWQEAAS5Ys4fjx49y8eRM/Pz8WLFjAhg0b2LNnD/v372fx4sVK bS0NEaOHElkZCShoaHo6OjQpk0bsrKyAFi0aBG7du1i8 bNxMbGsn79eiWpP336NABBQUEkJSUp wDXrl1j69atbNu2jaioKLKysvD19eX /fscOXKEAwcOcP36dTp06JDnWFJTU/H29qZKlSqcOXOGgIAArZ8dPEvUmzRpQo0aNYiMjGTv3r388ccf Pn55fv6t2/fXrkpOnPmDO7u7jRt2pT79 /nWr5ly5aUKVOG4OBgreNBQUG0bdsWCwsLAgMDWbt2LcuWLePSpUuMGDGCLl26cOTIEQBu3rxJ27Zt8fHxISoqit69ezN /Hit9s6cOYOfnx ff/45Fy5cICAggEmTJin9du7cmVOnTmndnF26dInz58/TqVMnoOC/RxkZGaSkpGhtQgghhCiaCu0BXT09PYKDg nTpw/Lli3D3d0dDw8PPv/8c1xdXZVy/3zA0tbWlunTp9O/f3 tmcvHjx zbNkyKlWqBMDgwYO1Zj0XLFjAhAkTaNu2LQDLli1j3759OWJycHBg9uzZyv6XX36JjY0NS5YsQaVSUblyZW7dusW4ceOYPHkyOjoFu1eqXLky8OwB1NKlSzNlyhTmzZunxGVnZ8fly5dZvnw53bt3z7Od6dOnU79 feDZDPSECROIj4 nYsWKAHz22WccPnyYcePGAc WS/3TmjVrKFWqFJcvX8bFxYXExEQcHBz4 OOPUalUVKhQQSlbqlQpACwsLLCystJqJzMzk7Vr1yplDhw4wIULF7hx4wY2NjYArF27lqpVq3L69Glq166dYywbNmwgKyuL1atXY2BgQNWqVfntt9 0PgFZsmQJNWrUYObMmVpjsLGx4erVqzg6OuZ5rQDCw8M5deoUd 7cQa1WAzB37lx27NjBli1b6Nu3b446urq6dO/eneDgYCZNmoRKpSI Pp5jx45x4MABMjIymDlzJgcPHqRu3boAVKxYkfDwcJYvX46HhwdLly6lUqVKyky9k5MTFy5c4Ouvv1b6mT9/Pk2bNmXSpEkAODo6cvnyZebMmYO/vz9Vq1bFzc2NDRs2KGXWr1/Phx9 iL29PUCBf48CAwOZOnXqc6 ZEEIIIYqGQl zf vWLXbt2oWXlxdhYWG4u7trzaYePHiQpk2bUq5cOUxNTenatSv37t3TWqZiZGSkJPoA1tbWyux5cnIySUlJWksh9PT0qFWrVo54atasqbUfExND3bp1UalUyrH69euTmprKb7/9VuDxZi8dUqlUpKWlER8fT69evZRPOUxMTJg fbrWLG5u/nkzVKZMGYyMjJREP/tY9vgB4uLi6NixIxUrVsTMzEyZtc9eouLv709UVBROTk4MHTqU/fv352s8FSpUUBJ9eHa9bGxslEQfoEqVKlhYWBATE5NrGzExMbi6uirLgAAlec4WHR3N4cOHta5T9o3Ti65Vdv3U1FQsLS212rhx48Zz6/fs2ZMbN25w PBh4Nmsvq2tLU2aNOHatWs8evSI5s2ba7W5du1apc2YmJgcS3D PbaYmBjlxi1b/fr1iYuL4 nTp8Cz2f0NGzYAz36HfvjhBzp37gzwUr9HEyZMIDk5Wdlu3rz5wmsohBBCiPdTob9608DAgObNm9O8eXMmTZpE7969mTJlCv7 /iQkJODt7c2AAQOYMWMGJUqUIDw8nF69epGZmYmR0bPXBBYrVkyrTZVKlWNNfn4YGxu/ljHlJTvhtbW1VZ47WLlyZY6EUFdX97nt/HO8KpUq1/FnL9EB8PHxoUKFCqxcuZKyZcuSlZWFi4uL8lCtu7s7N27c4Oeff bgwYP4 fnRrFmzHOvP/ 1NX69sqamp Pj4aM2IZ7O2ts5XfWtra8LCwnKce97rLx0cHGjQoAFBQUE0atSItWvX0qdPH1QqlfLz27NnD XKldOql/3pwevSsWNHxo0bx9mzZ/n777 5efOmsjTqZX6P1Gr1a49RCCGEEO mQk/2/61KlSrKax7PnDlDVlYW8 bNU5bMbN68uUDtmZubY21tzcmTJ2nYsCEAT548UdZtP4 zszNbt25Fo9Eos/sRERGYmprywQcfFCiOv// mxUrVtCwYUNlNrxs2bJcv35dmaV9E 7du0dsbCwrV66kQYMGwLNlLf9mZmZGhw4d6NChA5999hleXl7cv3 fEiVKUKxYMWWW XmcnZ25efMmN2/eVGb3L1  zMOHD6lSpUqeddatW0d6eroyu//LL79olXF3d2fr1q3Y2tqip1fwX1l3d3du376Nnp6e8qlGfvXq1YsBAwbw6aef8vvvv Pv7w88 z1Vq9UkJibi4eGR59h27dqldezfY3N2ds7xqtmIiAgcHR2VZP2DDz7Aw8OD9evX8/fff9O8eXNKly4NPPsU5238HgkhhBDi/VRoy3ju3btHkyZN P777zl//jw3btzgxx9/ZPbs2fj6 gJgb2/P48ePWbx4MdevX2fdunUsW7aswH0NGzaMWbNmsWPHDq5cucLAgQN5 PDhC sNHDiQmzdvMmTIEK5cucLOnTuZMmUKI0eOfOF6/Tt37nD79m3i4uLYuHEj9evX5 7duyxdulQpM3XqVAIDA1m0aBFXr17lwoULBAUFMX/ /AKPMS/FixfH0tKSFStWcO3aNQ4dOsTIkSO1ysyfP58ffviBK1eucPXqVX788UesrKyUWW9bW1tCQ0O5ffs2Dx48yLOvZs2aUa1aNTp37szZs2c5deoU3bp1w8PDI9dlUwCdOnVCpVLRp08fLl  zE8//cTcuXO1ygwaNIj79 /TsWNHTp8 TXx8PPv27aNHjx75uglp1qwZdevWpXXr1uzfv5 EhASOHz/Ol19 SWRk5HPrtm/fnmLFitGvXz8  eQT5SbG1NSU0aNHM2LECEJCQoiPj fs2bMsXrxYeTC2f// xMXFMWbMGGJjY9mwYUOOB35HjRpFaGgo06ZN4 rVq4SEhLBkyZIcDyl37tyZjRs38uOPP ZI6t/G75EQQggh3lOaQpKenq4ZP368xt3dXWNubq4xMjLSODk5aSZOnKh59OiRUm7 /Pkaa2trjaGhocbT01Ozdu1aDaB58OCBRqPRaIKCgjTm5uZabW/fvl3zz6E9fvxYM2zYMI2ZmZnGwsJCM3LkSE23bt00vr6 ShkPDw/NsGHDcsQZFhamqV27tkZfX19jZWWlGTdunObx48d5juvw4cMaQANoVCqVxtTUVOPm5qYZM2aMJikpKUf59evXa6pXr67R19fXFC9eXNOwYUPNtm3bNBqNRnPjxg0NoDl37pxW29ljz2v8U6ZM0bi5uSn7Bw4c0Dg7O2vUarXG1dVVExYWpgE027dv12g0Gs2KFSs01atX1xgbG2vMzMw0TZs21Zw9e1apv2vXLo29vb1GT09PU6FChVz7yPbrr79qPv30U42xsbHG1NRU0759e83t27fzvF4ajUZz4sQJjZubm0ZfX19TvXp1zdatW7XGrdFoNFevXtW0adNGY2FhoTE0NNRUrlxZM3z4cE1WVpZGo8n586tQoYLmm2  UfZTUlI0Q4YM0ZQtW1ZTrFgxjY2NjaZz586axMTE58am0Wg0ffv21QCazZs3ax3PysrSLFiwQOPk5KQpVqyYplSpUhpPT0/NkSNHlDL/ 9//NPb29hq1Wq1p0KCBZs2aNTl hlu2bNFUqVJFU6xYMU358uU1c bMyRHDgwcPNGq1WmNkZKT566 /cpx/3u/RiyQnJ2sATXJycr7KCyGEEKLw5ffvt0qjeYnF7UKIIiMlJQVzc3OSk5MxMzMr7HCEEEIIkQ/5/ftdqG/jEUIIIYQQQrw5kuwLIYQQQghRREmyL4QQQgghRBElyb4QQgghhBBFlCT7QgghhBBCFFGS7AshhBBCCFFESbIvhBBCCCFEESXJvhBCCCGEEEWUJPtCCCGEEEIUUXqFHYAQ4t3gMmUfOmqjwg5DCPECCbNaFXYIQoj3iMzsv eCg4OxsLAo7DDeCpVKxY4dOwo7jLcqISEBlUpFVFRUvusEBARQvXr1NxaTEEIIId4fkuy/If7 /qhUKvr375/j3KBBg1CpVPj7 79yPx06dODq1auv1EZwcDAqlUrZTExMqFmzJtu2bXvl F6npKQkWrRokef57GuuUqnQ19fH3t6er776iidPnrzFKF8vGxsbkpKScHFxyXed0aNHExoa gajEkIIIcT7QpL9N8jGxoaNGzfy999/K8fS09PZsGED5cuXf X2Hz9 jKGhIaVLl37ltszMzEhKSiIpKYlz587h6emJn58fsbGxrxzj62JlZYVarX5uGS8vL5KSkoiLi2PUqFEEBAQwZ86cXMtmZma ttjeFF1dXaysrNDTy/ KOxMTEywtLd9gVEIIIYR4X0iy/wa5u7tjY2OjNUO bds2ypcvT40aNbTK7t27l48//hgLCwssLS3x9vYmPj5eOZ 9nGPTpk14eHhgYGDA vXrcyzjiY Px9fXlzJlymBiYkLt2rU5ePDgC2NVqVRYWVlhZWWFg4MD06dPR0dHh/Pnz2uV fcyGgsLC4KDg58b47179 jYsSPlypXDyMiIatWq8cMPP2i106hRI4YOHcrYsWMpUaIEVlZWBAQE5IjxRct41Go1VlZWVKhQgQEDBtCsWTN27doFPJv5b926NTNmzKBs2bI4OTkBcOHCBZo0aYKhoSGWlpb07duX1NRUrXbXrFlD1apVUavVWFtbM3jwYOXc/PnzqVatGsbGxtjY2DBw4MAc9SMiImjUqBFGRkYUL14cT09PHjx4AEBWVhazZ8/G3t4etVpN fLlmTFjhtY1zV7GExYWhkqlIjQ0lFq1amFkZES9evW0bspkGY8QQgghskmy/4b17NmToKAgZX/NmjX06NEjR7m0tDRGjhxJZGQkoaGh6Ojo0KZNG7KysrTKjR8/nmHDhhETE4Onp2eOdlJTU2nZsiWhoaGcO3cOLy8vfHx8SExMzHfMT58 JSQkBHh2w1JQ/44xPT2dmjVrsmfPHi5evEjfvn3p2rUrp06d0qoXEhKCsbExJ0 eZPbs2Xz11VccOHCgwP3/k6GhodYMfmhoKLGxsRw4cIDdu3eTlpaGp6cnxYsX5/Tp0/z4448cPHhQK5lfunQpgwYNom/fvly4cIFdu3Zhb2 vnNfR0WHRokVcunSJkJAQDh06xNixY5XzUVFRNG3alCpVqnDixAnCw8Px8fHh6dOnAEyYMIFZs2YxadIkLl  zIYNGyhTpsxzx/Xll18yb948IiMj0dPTo2fPnvm JhkZGaSkpGhtQgghhCia5G08b1iXLl2YMGECv/76K/Bshnfjxo2EhYVplWvXrp3W/po1ayhVqhSXL1/WWq89fPhw2rZtm2d/bm5uuLm5KfvTpk1j /bt7Nq1SyuB/bfk5GRMTEwA PvvvylWrBgrVqygUqVK R7r82IcPXq08u8hQ4awb98 Nm/eTJ06dZTjrq6uTJkyBQAHBweWLFlCaGgozZs3L3AMGo2G0NBQ9u3bx5AhQ5TjxsbGrFq1Cn19fQBWrlxJeno6a9euxdjYGIAlS5bg4 PD119/TZkyZZg fTqjRo1i2LBhSju1a9fWGm82W1tbpk fTv/ /fnuu 8AmD17NrVq1VL2AapWrQrAX3/9xcKFC1myZAndu3cHoFKlSnz88cfPHd MGTPw8PAAnt1ctWrVivT0dAwMDF54bQIDA5k6deoLywkhhBDi/SfJ/htWqlQpWrVqRXBwMBqNhlatWlGyZMkc5eLi4pg8eTInT57k7t27yox YmKiVrJfq1at5/aXmppKQEAAe/bsISkpiSdPnvD333 /cGbf1NSUs2fPAvDo0SMOHjxI//79sbS0xMfHp0Bj/neMT58 ZebMmWzevJnff/ dzMxMMjIyMDLSfs2jq6ur1r61tTV37twpUN 7d /GxMSEx48fk5WVRadOnbSWA1WrVk1J9AFiYmJwc3NTEn2A vXrk5WVRWxsLCqVilu3btG0adM8 zx48CCBgYFcuXKFlJQUnjx5Qnp6Oo8ePcLIyIioqCjat2 fa92YmBgyMjKe235u/nmtrK2tAbhz506 ngWZMGECI0eOVPZTUlKwsbEpUP9CCCGEeD9Isv8W9OzZU5lV//bbb3Mt4 PjQ4UKFVi5ciVly5YlKysLFxeXHA R/jMpzc3o0aM5cOAAc fOxd7eHkNDQz777LMXPoyqo6OjtTTF1dWV/fv38/XXXyvJvkqlQqPRaNXL7QHcf8c4Z84cFi5cyIIFC5S17cOHD88RU7FixbT2VSpVjmVML9K4cWOWLl2Kvr4 ZcuWzfFg64uu378ZGho 93xCQgLe3t4MGDCAGTNmUKJECcLDw nVqxeZmZkYGRk9t40XtZ Xf14rlUoFkO9rpVarX/igsxBCCCGKBlmz/xZ4eXmRmZnJ48ePc11nf /ePWJjY5k4cSJNmzbF2dlZeXizoCIiIvD396dNmzZUq1YNKysrEhISXqotXV1drTcJlSpViqSkJGU/Li6OR48e5SsmX19funTpgpubGxUrVnzl14XmxdjYGHt7e8qXL5 vN9g4OzsTHR1NWlqaVrw6Ojo4OTlhamqKra1tnq yPHPmDFlZWcybN4 PPvoIR0dHbt26pVXG1dU1z/oODg4YGhrKqzKFEEII8UZIsv8W6OrqEhMTw XLl9HV1c1xvnjx4lhaWrJixQquXbvGoUOHtJZZFISDgwPbtm0jKiqK6OhoOnXqlK8ZX41Gw 3bt7l9 zY3btxgxYoV7Nu3D19fX6VMkyZNWLJkCefOnSMyMpL /fvnmI3PK6YDBw5w/PhxYmJi6NevH3/88cdLje9169y5MwYGBnTv3p2LFy9y PBhhgwZQteuXZWHZAMCApg3bx6LFi0iLi6Os2fPsnjxYgDs7e15/Pgxixcv5vr166xbt45ly5Zp9TFhwgROnz7NwIEDOX/ PFeuXGHp0qXcvXsXAwMDxo0bx9ixY1m7di3x8fH88ssvrF69 q1fCyGEEEIUPbKM5y0xMzPL85yOjg4bN25k6NChuLi44OTkxKJFi2jUqFGB 5k/fz49e/akXr16lCxZknHjxuXrbSspKSnK2m 1Wk2FChX46quvGDdunFJm3rx59OjRgwYNGlC2bFkWLlzImTNnXtj2xIkTuX79Op6enhgZGdG3b19at25NcnJygcf3uhkZGbFv3z6GDRtG7dq1MTIyol27dsyfP18p0717d9LT0/nmm28YPXo0JUuW5LPPPgOePRA9f/58vv76ayZMmEDDhg0JDAykW7duSn1HR0f279/PF198QZ06dTA0NOTDDz kY8eOAEyaNAk9PT0mT57MrVu3sLa2zvXL2N60i1M9n/t7KoQQQoj3j0rz70XYQoj/lJSUFMzNzUlOTpZkXwghhHhP5PfvtyzjEUIIIYQQooiSZF8IIYQQQogiSpJ9IYQQQgghiihJ9oUQQgghhCiiJNkXQgghhBCiiJJkXwghhBBCiCJKkn0hhBBCCCGKKEn2hRBCCCGEKKIk2RdCCCGEEKKI0ivsAIR4kYCAAHbs2EFUVFRhh/Je8Pf35 HDh zYsaNA9Vym7ENHbfRmghJCvDYJs1oVdghCiPeIzOyL1 rEiRPo6urSqlXR mP022 /oa vj4uLS2GHokhISEClUuW4CVq4cCHBwcGFEpMQQggh3i2S7IvXavXq1QwZMoSjR49y69att9JnZmbmG 8jODgYPz8/UlJSOHny5Cu3p9FoePLkyWuILCdzc3MsLCzeSNtCCCGEeL9Isi9em9TUVDZt2sSAAQNo1apVjtnlsLAwVCoVoaGh1KpVCyMjI rVq0dsbKxWuVmzZlGmTBlMTU3p1asX6enpWuf9/f1p3bo1M2bMoGzZsjg5OQFw8 ZN/Pz8sLCwoESJEvj6 pKQkKDUO336NM2bN6dkyZKYm5vj4eHB2bNnXzgujUZDUFAQXbt2pVOnTqxevTpHmePHj1O9enUMDAyoVasWO3bs0Jp1zx77zz//TM2aNVGr1YSHh5OVlUVgYCB2dnYYGhri5ubGli1blHYfPHhA586dKVWqFIaGhjg4OBAUFASAnZ0dADVq1EClUtGoUSOt6yOEEEIIIcm eG02b95M5cqVcXJyokuXLqxZswaNRpOj3Jdffsm8efOIjIxET0 Pnj17arUREBDAzJkziYyMxNramu   y5HG6GhocTGxnLgwAF2797N48eP8fT0xNTUlGPHjhEREYGJiQleXl7KzP9ff/1F9 7dCQ8P55dffsHBwYGWLVvy119/PXdchw8f5tGjRzRr1owuXbqwceNG0tLSlPMpKSn4 PhQrVo1zp49y7Rp0xg3blyubY0fP55Zs2YRExODq6srgYGBrF27lmXLlnHp0iVGjBhBly5dOHLkCACTJk3i8uXL/Pzzz8TExLB06VJKliwJwKlTpwA4ePAgSUlJbNu27bnjyJaRkUFKSorWJoQQQoiiSR7QFa/N6tWr6dKlCwBeXl4kJydz5MgRZcY524wZM/Dw8ACeJb tWrUiPT0dAwMDFixYQK9evejVqxcA06dP5 DBgzlm942NjVm1ahX6 voAfP/992RlZbFq1SpUKhUAQUFBWFhYEBYWxieffEKTJk202lixYgUWFhYcOXIEb2/v547r888/R1dXFxcXFypWrMiPP/6Iv78/ABs2bEClUrFy5UoMDAyoUqUKv// O3369MnR1ldffUXz5s2BZ0n3zJkzOXjwIHXr1gWgYsWKhIeHs3z5cjw8PEhMTKRGjRrUqlULAFtbW6WtUqVKAWBpaYmVlVWe8f9bYGAgU6dOzXd5IYQQQry/ZGZfvBaxsbGcOnWKjh07AqCnp0eHDh1yXfLi6uqq/Nva2hqAO3fuABATE8OHH36oVT47Ef6natWqKYk QHR0NNeuXcPU1BQTExNMTEwoUaIE6enpxMfHA/DHH3/Qp08fHBwcMDc3x8zMjNTUVBITE/Mc18OHD9m2bZtyEwPQpUsXrXHFxsbi6uqKgYGBcqxOnTq5tpedtANcu3aNR48e0bx5cyVmExMT1q5dq8Q8YMAANm7cSPXq1Rk7dizHjx/PM9b8mjBhAsnJycp28 bNV25TCCGEEO8mmdkXr8Xq1at58uQJZcuWVY5pNBrUajVLlizB3NxcOV6sWDHl39mz8FlZWQXqz9jYWGs/NTWVmjVrsn79 hxls2fAu3fvzr1791i4cCEVKlRArVZTt27d5z7gu2HDBtLT07VuQDQaDVlZWVy9ehVHR8eXjjs1NRWAPXv2UK5cOa1yarUagBYtWvDrr7/y008/ceDAAZo2bcqgQYOYO3dugfr9d9vZ7QshhBCiaJOZffHKnjx5wtq1a5k3bx5RUVHKFh0dTdmyZfnhhx/y3Zazs3OOt9388ssvL6zn7u5OXFwcpUuXxt7eXmvLvtGIiIhg6NChtGzZkqpVq6JWq7l79 5z2129ejWjRo3KMa4GDRqwZs0aAJycnLhw4QIZGRlKvdOnT78w5ipVqqBWq0lMTMwRs42NjVKuVKlSdO/ene //54FCxawYsUKAOWTjadPn76wLyGEEEL8N0myL17Z7t27efDgAb169cLFxUVra9euXa5LefIybNgw1qxZQ1BQEFevXmXKlClcunTphfU6d 5MyZIl8fX15dixY9y4cYOwsDCGDh3Kb7/9BoCDgwPr1q0jJiaGkydP0rlzZwwNDfNsMyoqirNnz9K7d 8c4 rYsSMhISE8efKETp06kZWVRd  fYmJiWHfvn3KzHv2Jxe5MTU1ZfTo0YwYMYKQkBDi4 M5e/YsixcvJiQkBIDJkyezc dOrl27xqVLl9i9ezfOzs4AlC5dGkNDQ/bu3csff/xBcnJyvq zEEIIIf4bJNkXr2z16tU0a9ZMa6lOtnbt2hEZGcn58 fz1VaHDh2YNGkSY8eOpWbNmvz6668MGDDghfWMjIw4evQo5cuXp23btjg7Oyuv7TQzM1PifPDgAe7u7nTt2pWhQ4dSunTp546rSpUqVK5cOce5Nm3acOfOHX766SfMzMz43// R1RUFNWrV fLL79k8uTJAFrr HMzbdo0Jk2aRGBgIM7Oznh5ebFnzx7ltZr6 vpMmDABV1dXGjZsiK6uLhs3bgSePRexaNEili9fTtmyZfH19X3hdRJCCCHEf4tKk9u7EYUQr2T9 vX06NGD5OTk53568C5ISUnB3Nyc5ORk5cZICCGEEO 2/P79lgd0hXgN1q5dS8WKFSlXrhzR0dGMGzcOPz /dz7RF0IIIUTRJsm EK/B7du3mTx5Mrdv38ba2pr27dszY8aMwg5LCCGEEP9xsoxHiP84WcYjhBBCvH/y /dbHtAVQgghhBCiiJJkXwghhBBCiCJKkn0hhBBCCCGKKEn2hRBCCCGEKKIk2RdCCCGEEKKIkmRfCCGEEEKIIkqSfSGEEEIIIYoo VItUWQ1atSI6tWrs2DBgsIO5ZUEBASwY8cOoqKiAPD39 fhw4fs2LHjtfbjMmUfOmqj19qmEOL1S5jVqrBDEEK8R2RmX7ySEydOoKurS6tWL/fHJyAggOrVq7/eoP6/bdu2MW3atFdu59y5c3To0AFra2vUajUVKlTA29ub//3vf7zu76RTqVQ5kvjRo0cTGhr6WvsRQgghxH DJPvilaxevZohQ4Zw9OhRbt26VdjhaClRogSmpqav1MbOnTv56KOPSE1NJSQkhJiYGPbu3UubNm2YOHEiycnJrynavJmYmGBpafnG xFCCCFE0SPJvnhpqampbNq0iQEDBtCqVSuCg4O1zoeFhaFSqQgNDaVWrVoYGRlRr149YmNjAQgODmbq1KlER0ejUqlQqVRKG4mJifj6 mJiYoKZmRl fn788ccfStvZnwisW7cOW1tbzM3N fzzz/nrr7 UMo0aNWL48OHK/oMHD jWrRvFixfHyMiIFi1aEBcXl f40tLS6NWrF61atWLPnj188sknVKxYEWdnZ3r16kV0dDTm5uZK YsXL9KiRQtMTEwoU6YMXbt25e7du1rxDB06lLFjx1KiRAmsrKwICAhQztva2gLQpk0bVCqVsv iTz ysrIIDAzEzs4OQ0ND3Nzc2LJlS57lhRBCCPHfIcm eGmbN2 mcuXKODk50aVLF9asWZPrspYvv/ySefPmERkZiZ6eHj179gSgQ4cOjBo1iqpVq5KUlERSUhIdOnQgKysLX19f7t /z5EjRzhw4ADXr1 nQ4cOWu3Gx8ezY8cOdu/eze7duzly5AizZs3KM15/f38iIyPZtWsXJ06cQKPR0LJlSx4/fpxr f3793Pv3j3Gjh2bZ5sqlQqAhw8f0qRJE2rUqEFkZCR79 7ljz/ wM/PT6t8SEgIxsbGnDx5ktmzZ/PVV19x4MABAE6fPg1AUFAQSUlJyv6LBAYGsnbtWpYtW8alS5cYMWIEXbp04ciRI7mWz8jIICUlRWsTQgghRNEkD iKl7Z69Wq6dOkCgJeXF8nJyRw5coRGjRpplZsxYwYeHh4AjB8/nlatWpGeno6hoSEmJibo6elhZWWllD9w4AAXLlzgxo0b2NjYALB27VqqVq3K6dOnqV27NvBsRjs4OFhZqtO1a1dCQ0OZMWNGjljj4uLYtWsXERER1KtXD4D169djY2PDjh07aN  fY46V69eBcDJyUk5dvr0aRo3bqzsb9y4EW9vb5YsWUKNGjWYOXOmcm7NmjXY2Nhw9epVHB0dAXB1dWXKlCkAODg4sGTJEkJDQ2nevDmlSpUCwMLCQut6PE9GRgYzZ87k4MGD1K1bF4CKFSsSHh7O8uXLlev T4GBgUydOjVf7QshhBDi/SYz  KlxMbGcurUKTp27AiAnp4eHTp0YPXq1TnKurq6Kv 2trYG4M6dO3m2HRMTg42NjZLoA1SpUgULCwtiYmKUY7a2tlpr8q2trfNsNyYmBj09PT788EPlmKWlJU5OTlptvoirqytRUVFERUWRlpbGkydPAIiOjubw4cOYmJgoW XKlYFnn0D8s/4/PS/m/Lh27RqPHj2iefPmWn2vXbtWq99/mjBhAsnJycp28 bNl 5fCCGE H/t3XtYVOXaP/DvyGFQh4N4AnQAERRQUBElYSu6RSGJcG93oFtFAt07xV1WGlobESnFhCzTykoBew3RV8QuLU0JyNDtCfCQRIqitFMpkpMmAvO8f/hj/Zw4DiDg P1c17pkPetez3ru9cww9yzXDNS18co tcrWrVtRU1MDCwsLqU0IAblcjk2bNqndy66npyf9XHfbi0qlavMYHu63ru/26LeOnZ0dgAdvbJ566ikAgFwuh62tbb3YyspK Pn5Yd26dfW21b3BeRRjrqysBAAcOHAAAwYMUNsml8sb3Eculze6jYiIiLQLi33SWE1NDbZv3464uDhMnTpVbdv06dORlJSEF154oUV96evro7a2Vq3NwcEBRUVFKCoqkq7uX7x4EaWlpXB0dGzVmB0cHFBTU4MTJ05It/GUlJQgPz /0T6nTp0KU1NTrFu3Dnv37m2yfxcXF zZswfW1tbQ1W3900pPT6/e WiKo6Mj5HI5rl /3uAtO0RERPRk4208pLH9 /fj9u3bCA0NxfDhw9WWGTNmNHgrT2Osra1x9epV5Obm4tdff0VVVRW8vLzg5OSE2bNnIzs7GydPnkRQUBA8PT3h6uraqjHb2dnB398fCxYswHfffYezZ89izpw5GDBgAPz9/RvcR6FQ4NNPP8WBAwfg6 uLQ4cO4cqVKzh37hzefvttAICOjg4AICwsDL/99htmzZqFU6dOoaCgAIcOHcLzzz vUfFubW2NtLQ03Lx5E7dv32423tDQEEuXLsXLL7 MxMREFBQUIDs7G  //z4SExNbfFwiIiLSTiz2SWNbt26Fl5eX2q06dWbMmIHTp0/j3LlzLeprxowZ8PHxwaRJk9C3b18kJSVBJpNh37596NWrFyZMmAAvLy/Y2NggOTm5TeOOj4/H6NGj8cwzz2DcuHEQQuDLL7 sd2vNw/7yl7/g2LFj6NGjB4KCgjB06FD8 c9/xjfffCN9OBcALCwskJWVhdraWkydOhVOTk5YsmQJTExM0K1by59mcXFxOHz4MJRKJUaNGtWifaKjoxEREYG1a9fCwcEBPj4 OHDgAAYNGtTi4xIREZF2kon2/hOgRPRYKS8vh7GxMcrKymBkZNTZwyEiIqIWaOnrN6/sExERERFpKRb7RERERERaisU EREREZGWYrFPRERERKSlWOwTEREREWkpFvtERERERFqKxT4RERERkZZisU9EREREpKVY7BMRERERaSndzh4AEXUNwyMPoZu8R2cPg4iaURjj29lDIKLHCK/sU7uZOHEilixZ0qLYjIwMyGQylJaWtumYMpkMqampbeqjPRQWFkImkyE3NxdA  VHRERE1BYs9qlRwcHBkMlkeOGFF ptCwsLg0wmQ3BwsNSWkpKC6OjoDhxh29UV6XWLvr4 bG1t8eabb0II0dnDIyIiImoTFvvUJKVSiZ07d L333 X2u7du4fPP/8clpaWarGmpqYwNDTs6CG2iyNHjuDGjRu4dOkSoqKi8NZbb2Hbtm2dPSwiIiKiNmGxT01ycXGBUqlESkqK1JaSkgJLS0uMGjVKLfaPt/FUVVUhPDwcSqUScrkctra22Lp1q9o Z86cgaurK3r06AF3d3fk5 erbd 3bx9cXFxgYGAAGxsbREVFoaamptHxFhUVISAgACYmJjA1NYW/vz8KCwubzbN3794wMzODlZUVZs eDQ8PD2RnZ6vFfPrpp3BwcICBgQHs7e3xwQcfNNvvw/bs2YNhw4ZBLpfD2toacXFxatutra3x5ptvIigoCAqFAlZWVvjiiy/wyy /wN/fHwqFAs7Ozjh9 rRG/RIREdGTi8U NSskJATx8fHS rZt2/D88883u19QUBCSkpKwceNG5OXlYcuWLVAoFGoxb7zxBuLi4nD69Gno6uoiJCRE2nb06FEEBQXhpZdewsWLF7FlyxYkJCTgrbfeavB41dXV8Pb2hqGhIY4ePYqsrCwoFAr4 Pjg/v37Lc739OnTOHPmDNzc3KS2HTt2YOXKlXjrrbeQl5eHNWvWICIiAomJiS3q88yZMwgICMDMmTNx/vx5rFq1ChEREUhISFCL27BhAzw8PJCTkwNfX1/MnTsXQUFBmDNnDrKzszF48GAEBQVJtxi1tN HVVVVoby8XG0hIiIi7cRv46FmzZkzBytWrMC1a9cAAFlZWdi5cycyMjIa3efHH3/Erl27cPjwYXh5eQEAbGxs6sW99dZb8PT0BAAsX74cvr6 uHfvHgwMDBAVFYXly5dj3rx50v7R0dF47bXXEBkZWa v5ORkqFQqfPrpp5DJZACA Ph4mJiYICMjA1OnTm10vO7u7ujWrRvu37 P6upq/OMf/0BQUJC0PTIyEnFxcfjrX/8KABg0aJD0BqRufE155513MHnyZERERAAAhgwZgosXL2L9 vVqn3uYNm0a/vnPfwIAVq5ciQ8//BBjxozBc889BwAIDw/HuHHjcOvWLZiZmbW434etXbsWUVFRzY6ZiIiIHn8s9qlZffv2ha vLxISEiCEgK vL/r06dPkPrm5udDR0ZEK cY4OztLP5ubmwMAiouLYWlpibNnzyIrK0vtSn5tbS3u3buHu3fvokcP9a JPHv2LC5fvlzvcwP37t1DQUFBk NITk6Gg4MDqqurceHCBfzrX/9Cr169EBMTgzt37qCgoAChoaFYsGCBtE9NTQ2MjY2b7LdOXl4e/P391do8PDzw7rvvora2Fjo6OvXOR// /QEATk5O9dqKi4thZmbW4n4ftmLFCrzyyivSenl5OZRKZYvyICIioscLi31qkZCQECxevBgAsHnz5mbju3fv3qJ 9fT0pJ/rrsarVCoAQGVlJaKioqSr6Q8zMDCo11ZZWYnRo0djx44d9bb17du3yXEolUrY2toCABwcHFBQUICIiAisWrUKlZWVAIBPPvlE7dYeAA0W023R0Plo6hy1hlwuh1wub/X RERE9PhgsU8tUnffu0wmg7e3d7PxTk5OUKlUyMzMlG7j0ZSLiwvy8/OlIrwl8cnJyejXrx MjIxadcw6Ojo6qKmpwf3799G/f39YWFjgypUrmD17dqv6c3BwQFZWllpbVlYWhgwZ0qY3DI qXyIiItIOLPapRXR0dJCXlyf93Bxra2vMmzcPISEh2LhxI0aMGIFr166huLgYAQEBLTrmypUr8cwzz8DS0hJ/ 9vf0K1bN5w9exYXLlzAm2  WS9 9uzZWL9 Pfz9/bF69WoMHDgQ165dQ0pKCl577TUMHDiw0WOVlJTg5s2bqKmpwfnz5/Hee 9h0qRJ0puGqKgovPjiizA2NoaPjw qqqpw vRp3L59W 2WmMa8 uqrGDNmDKKjoxEYGIjjx49j06ZNGn jT0f1S0RERNqBxT61mKZXyz/88EO8/vrrWLRoEUpKSmBpaYnXX3 9xft7e3tj//79WL16NdatWwc9PT3Y29tj/vz5Dcb36NED3377LcLDw/HXv/4VFRUVGDBgACZPntzs2Ov 90FHRwfm5uaYNm2a2mcF5s fjx49emD9 vVYtmwZevbsCScnpxb/xWAXFxfs2rULK1euRHR0NMzNzbF69epGP0TbUu3Z74Uo7zb/jwgRERF1LTLBPxNK9EQrLy HsbExysrKWOwTERE9Jlr6 s3v2SciIiIi0lIs9omIiIiItBSLfSIiIiIiLcVin4iIiIhIS7HYJyIiIiLSUiz2iYiIiIi0FIt9IiIiIiItxWKfiIiIiEhLsdgnIiIiItJSup09AOq6Vq1ahdTUVOTm5nb2UJ4YwcHBKC0tRWpqaocfe3jkIXST9 jw4xKRZgpjfDt7CET0GOGV/SeQn58ffHx8Gtx29OhRyGQynDt3DkuXLkVaWloHj65jyWSyJpdVq1Y9kuMWFhZCJpPVeyP13nvvISEh4ZEck4iIiJ48vLL/BAoNDcWMGTPw008/YeDAgWrb4uPj4erqCmdnZwCAQqHojCF2mBs3bkg/JycnY XKlcjPz5faHs5fCIHa2lro6j66p42xsfEj65uIiIiePLyy/wR65pln0Ldv33pXkCsrK7F7926EhoYCeHAbz8iRI6XtwcHBmD59OmJjY2Fubo7evXsjLCwM1dXVUkxVVRXCw8OhVCohl8tha2uLrVu3StsvXLiAp59 GgqFAv3798fcuXPx66 /StsnTpyIF198Ea 99hpMTU1hZmamdnU9ISGhySvwKpUKq1evxsCBAyGXyzFy5EgcPHiw0XNhZmYmLcbGxpDJZNL6Dz/8AENDQ3z11VcYPXo05HI5vvvuOxQUFMDf3x/9 /eHQqHAmDFjcOTIEbV ra2tsWbNGoSEhMDQ0BCWlpb4 OOPpe2DBg0CAIwaNQoymQwTJ05UO8ctPR8AcP36dfj7 0OhUMDIyAgBAQG4detWozkTERHRk4PF/hNIV1cXQUFBSEhIgBBCat 9ezdqa2sxa9asRvdNT09HQUEB0tPTkZiYiISEBLU3DUFBQUhKSsLGjRuRl5eHLVu2SFfHS0tL8ec//xmjRo3C6dOncfDgQdy6dQsBAQFqx0hMTETPnj1x4sQJvP3221i9ejUOHz4MAAgMDMSNGzekJSkpCbq6uvDw8ADw4DaYuLg4xMbG4ty5c/D29sazzz6LS5cutfp8LV  HDExMcjLy4OzszMqKysxbdo0pKWlIScnBz4 PvDz88P169fV9ouLi4OrqytycnKwaNEiLFy4UPpfg5MnTwIAjhw5ghs3biAlJaXR4zd1PlQqFfz9/fHbb78hMzMThw8fxpUrVxAYGNjqfImIiEh78DaeJ1RISAjWr1 PzMxM6apyfHw8ZsyY0eStJL169cKmTZugo6MDe3t7 Pr6Ii0tDQsWLMCPP/6IXbt24fDhw/Dy8gIA2NjYSPtu2rQJo0aNwpo1a6S2bdu2QalU4scff8SQIUMAAM7OzoiMjAQA2NnZYdOmTUhLS8OUKVPQvXt3dO/eHQBQUFCAsLAwrFmzBlOmTAEAxMbGIjw8HDNnzgQArFu3Dunp6Xj33XexefPmVp2r1atXS/0DgKmpKUaMGCGtR0dHY /evfjiiy wePFiqX3atGlYtGgRACA8PBwbNmxAeno6hg4dir59 wIAevfuDTMzsyaP39T5SEtLw/nz53H16lUolUoAwPbt2zFs2DCcOnUKY8aMqddfVVUVqqqqpPXy8nJNTwkRERE9Jnhl/wllb28Pd3d3bNu2DQBw fJlHD16VLqFpzHDhg2Djo6OtG5ubo7i4mIAQG5uLnR0dODp6dngvmfPnkV6ejoUCoW02NvbA3hQuNep 7xAQ8eoU1ZWhmeeeQa vr5YtmwZgAdF688//yxd5a/j4eGBvLy8JvNqiqurq9p6ZWUlli5dCgcHB5iYmEChUCAvL6/elf2H86i7PeiPebREU cjLy8PSqVSKvQBwNHRESYmJo3mvHbtWhgbG0vLw/sSERGRdmGx/wQLDQ3Fnj17UFFRgfj4eAwePLjRQr2Onp6e2rpMJoNKpQIA6Yp7YyorK Hn54fc3Fy15dKlS5gwYUKLjgEAtbW1CAwMhJGRkdp98I9Kz5491daXLl2KvXv3Ys2aNTh69Chyc3Ph5OSE /fvq8U1l0dLtVc/dVasWIGysjJpKSoqanVfRERE1LWx2H CBQQEoFu3bvj888 xfft2hISEQCaTtbo/JycnqFQqZGZmNrjdxcUF33//PaytrWFra6u2/LGgbsrLL7 M8 fPIzU1FQYGBlK7kZERLCwskJWVpRaflZUFR0fH1iXVgKysLAQHB Mvf/kLnJycYGZmhsLCQo360NfXB/DgjUtbODg4oKioSK1gv3jxIkpLSxvNWS6Xw8jISG0hIiIi7cRi/wmmUCgQGBiIFStW4MaNGwgODm5Tf9bW1pg3bx5CQkKQmpqKq1evIiMjA7t27QIAhIWF4bfffsOsWbNw6tQpFBQU4NChQ3j  edbXPTGx8fjgw8 wEcffQSZTIabN2/i5s2bqKysBAAsW7YM69atQ3JyMvLz87F8 XLk5ubipZdealNuD7Ozs0NKSgpyc3Nx9uxZ/P3vf9f4Snu/fv3QvXt36UPKZWVlrRqLl5cXnJycMHv2bGRnZ PkyZMICgqCp6dnvduPiIiI6MnDYv8JFxoaitu3b8Pb2xsWFhZt7u/DDz/E3/72NyxatAj29vZYsGAB7ty5AwDSVffa2lpMnToVTk5OWLJkCUxMTNCtW8seipmZmaitrcWzzz4Lc3NzaYmNjQUAvPjii3jllVfw6quvwsnJCQcPHsQXX3wBOzu7NudW55133kGvXr3g7u4OPz8/eHt7w8XFRaM dHV1sXHjRmzZsgUWFhbw9/dv1VhkMhn27duHXr16YcKECfDy8oKNjQ2Sk5Nb1R8RERFpF5l4 LsXieiJU15eDmNjY5SVlfGWHiIiosdES1 /eWWfiIiIiEhLsdgnIiIiItJSLPaJiIiIiLQUi30iIiIiIi3FYp IiIiISEux2CciIiIi0lIs9omIiIiItBSLfSIiIiIiLcVin4iIiIhIS7HYJyIiIiLSUrqdPQCiR2XixIkYOXIk3n333c4eSpv8MQ9ra2ssWbIES5YsaTC sLAQgwYNQk5ODkaOHNni4wyPPIRu8h5tHzAREREBAApjfDt7CLyyTx3vl19 wcKFC2FpaQm5XA4zMzN4e3sjKyurXY TkpKC6OjoNvdz fJlhISESOMdMGAAJk ejB07dqCmpqYdRtq lEolbty4geHDh3f2UIiIiKiT8co dbgZM2bg/v37SExMhI2NDW7duoW0tDSUlJS063FMTU3b3MfJkyfh5eWFYcOGYfPmzbC3twcAnD59Gps3b8bw4cMxYsSINh nPeno6MDMzKyzh0FERERdAK/sU4cqLS3F0aNHsW7dOkyaNAlWVlYYO3YsVqxYgWeffVaKu379Ovz9/aFQKGBkZISAgADcunVL2r5q1SqMHDkSn332GaytrWFsbIyZM2eioqJCipk4caLarS6fffYZXF1dYWhoCDMzM/z9739HcXFxo2MVQiA4OBhDhgxBVlYW/Pz8YGdnBzs7O8yaNQvfffcdnJ2dpfjw8HAMGTIEPXr0gI2NDSIiIlBdXa3RmO/cuYOgoCAoFAqYm5sjLi6uwbHdvXsXISEhMDQ0hKWlJT7  GNpW2FhIWQyGXJzc5ueDCIiItJ6LPapQykUCigUCqSmpqKqqqrBGJVKBX9/f/z222/IzMzE4cOHceXKFQQGBqrFFRQUIDU1Ffv378f /fuRmZmJmJiYRo9dXV2N6OhonD17FqmpqSgsLERwcHCj8bm5ucjLy8PSpUvRrVvDTxWZTCb9bGhoiISEBFy8eBHvvfcePvnkE2zYsEGjMS9btgyZmZnYt28fvv76a2RkZCA7O7vecePi4uDq6oqcnBwsWrQICxcuRH5 fqO5PKyqqgrl5eVqCxEREWknFvvUoXR1dZGQkIDExESYmJjAw8MDr7/ Os6dOyfFpKWl4fz58/j8888xevRouLm5Yfv27cjMzMSpU6ekOJVKhYSEBAwfPhzjx4/H3LlzkZaW1uixQ0JC8PTTT8PGxgZPPfUUNm7ciK   gqVlZUNxv/4448AgKFDh0ptxcXF0hsWhUKBDz74QNr273//G 7u7rC2toafnx WLl2KXbt2qfXZ1JgrKyuxdetWxMbGYvLkyXByckJiYmKDnwuYNm0aFi1aBFtbW4SHh6NPnz5IT09v6tRL1q5dC2NjY2lRKpUt2o IiIgePyz2qcPNmDEDP//8M7744gv4 PggIyMDLi4uSEhIAADk5eVBqVSqFaGOjo4wMTFBXl6e1GZtbQ1DQ0Np3dzcvMnbcs6cOQM/Pz9YWlrC0NAQnp6eAB7cMtRSvXv3Rm5uLnJzc2FiYoL79 9L25KTk Hh4QEzMzMoFAr8 9//rtd3U2MuKCjA/fv34ebmJm03NTVVe7NR5 Hbh2QyGczMzJrM/WErVqxAWVmZtBQVFbUseSIiInrssNinTmFgYIApU6YgIiICx44dQ3BwMCIjIzXqQ09PT21dJpNBpVI1GHvnzh14e3vDyMgIO3bswKlTp7B3714AUCvYH2ZnZwcAarfH6OjowNbWFra2ttDV/f fbz9 /Dhmz56NadOmYf/ /cjJycEbb7xRr29NxtyUtvQjl8thZGSkthAREZF2YrFPXYKjoyPu3LkDAHBwcEBRUZHaFeeLFy itLQUjo6Orer/hx9 QElJCWJiYjB /HjY29s3eyV81KhRsLe3R2xsbLOF9LFjx2BlZYU33ngDrq6usLOzw7Vr1zQa4 DBg6Gnp4cTJ05Ibbdv35ZuJyIiIiLSFL96kzpUSUkJnnvuOYSEhMDZ2RmGhoY4ffo03n77bfj7 wMAvLy84OTkhNmzZ Pdd99FTU0NFi1aBE9PT7i6urbquJaWltDX18f777 PF154ARcuXGj2O/hlMhni4 MxZcoUeHh4YMWKFXBwcEB1dTW /fZb/PLLL9DR0QHw4H8Brl /jp07d2LMmDE4cOCA9D8HLaVQKBAaGoply5ahd /e6NevH954441GPxxMRERE1BxWEdShFAoF3NzcsGHDBkyYMAHDhw9HREQEFixYgE2bNgF4UGTv27cPvXr1woQJE Dl5QUbGxskJye3 rh9 /ZFQkICdu/eDUdHR8TExCA2NrbZ/Z566imcOXMGQ4cORVhYGBwdHeHu7o6kpCRs2LABCxcuBAA8  yzePnll7F48WKMHDkSx44dQ0REhMbjXL9 PcaPHw8/Pz94eXnhT3/6E0aPHq1xP0REREQAIBNCiM4eBBF1nvLychgbG6OsrIz37xMRET0mWvr6zSv7RERERERaisU EREREZGWYrFPRERERKSl G08RE 4uo/tlJeXd/JIiIiIqKXqXreb /gti32iJ1xJSQkAqP3FYiIiIno8VFRUwNjYuNHtLPaJnnCmpqYAgOvXrzf5y0IblJeXQ6lUoqioSOu/eYi5aifmqp2Yq3Z61LkKIVBRUQELC4sm41jsEz3h6v5ol7Gxsdb/4q1jZGTEXLUQc9VOzFU7Mdf20ZKLdPyALhERERGRlmKxT0RERESkpVjsEz3h5HI5IiMjIZfLO3sojxxz1U7MVTsxV 3EXDueTDT3fT1ERERERPRY4pV9IiIiIiItxWKfiIiIiEhLsdgnIiIiItJSLPaJiIiIiLQUi30iLbN582ZYW1vDwMAAbm5uOHnyZJPxu3fvhr29PQwMDODk5IQvv/xSbbsQAitXroS5uTm6d 8OLy8vXLp06VGmoBFN8v3kk08wfvx49OrVC7169YKXl1e9 ODgYMhkMrXFx8fnUafRIprkmpCQUC8PAwMDtZiuPLea5Dpx4sR6ucpkMvj6 koxXXFev/32W/j5 cHCwgIymQypqanN7pORkQEXFxfI5XLY2toiISGhXoymvwM6gqa5pqSkYMqUKejbty MjIwwbtw4HDp0SC1m1apV9ebU3t7 EWbRMprmmpGR0eDj9 bNm2px2jCvDT0PZTIZhg0bJsV01Xldu3YtxowZA0NDQ/Tr1w/Tp09Hfn5 s/t1hddYFvtEWiQ5ORmvvPIKIiMjkZ2djREjRsDb2xvFxcUNxh87dgyzZs1CaGgocnJyMH36dEyfPh0XLlyQYt5  21s3LgRH330EU6cOIGePXvC29sb9 7d66i0GqVpvhkZGZg1axbS09Nx/PhxKJVKTJ06Ff/973/V4nx8fHDjxg1pSUpK6oh0mqRprsCDv9r4cB7Xrl1T295V51bTXFNSUtTyvHDhAnR0dPDcc8 pxXW1eb1z5w5GjBiBzZs3tyj 6tWr8PX1xaRJk5Cbm4slS5Zg/vz5akVwax4nHUHTXL/99ltMmTIFX375Jc6cOYNJkybBz88POTk5anHDhg1Tm9PvvvvuUQxfI5rmWic/P18tl379 knbtGVe33vvPbUci4qKYGpqWu 52hXnNTMzE2FhYfjPf/6Dw4cPo7q6GlOnTsWdO3ca3afLvMYKItIaY8eOFWFhYdJ6bW2tsLCwEGvXrm0wPiAgQPj6 qq1ubm5iX/ 859CCCFUKpUwMzMT69evl7aXlpYKuVwukpKSHkEGmtE03z qqakRhoaGIjExUWqbN2 e8Pf3b  htpmmucbHxwtjY NG  vKc9vWed2wYYMwNDQUlZWVUltXndc6AMTevXubjHnttdfEsGHD1NoCAwOFt7e3tN7Wc9cRWpJrQxwdHUVUVJS0HhkZKUaMGNF A3sEWpJrenq6ACBu377daIy2zuvevXuFTCYThYWFUtvjMK9CCFFcXCwAiMzMzEZjusprLK/sE2mJ /fv48yZM/Dy8pLaunXrBi8vLxw/frzBfY4fP64WDwDe3t5S/NWrV3Hz5k21GGNjY7i5uTXaZ0dpTb5/dPfuXVRXV8PU1FStPSMjA/369cPQoUOxcOFClJSUtOvYNdXaXCsrK2FlZQWlUgl/f398//330rauOrftMa9bt27FzJkz0bNnT7X2rjavmmru doe566rUqlUqKioqPdcvXTpEiwsLGBjY4PZs2fj vXrnTTCths5ciTMzc0xZcoUZGVlSe3aPK9bt26Fl5cXrKys1Nofh3ktKysDgHqPyYd1lddYFvtEWuLXX39FbW0t vfvr9bev3//evd 1rl582aT8XX/atJnR2lNvn8UHh4OCwsLtV 0Pj4 2L59O9LS0rBu3TpkZmbi6aefRm1tbbuOXxOtyXXo0KHYtm0b9u3bh//5n/ BSqWCu7s7fvrpJwBdd27bOq8nT57EhQsXMH/ fLX2rjivmmrs VpeXo7ff/ 9XZ4TXVVsbCwqKysREBAgtbm5uSEhIQEHDx7Ehx9 iKtXr2L8 PGoqKjoxJFqztzcHB999BH27NmDPXv2QKlUYuLEicjOzgbQPr/ruqKff/4ZX331Vb3n6uMwryqVCkuWLIGHhweGDx/eaFxXeY3VbbeeiIgeIzExMdi5cycyMjLUPrg6c ZM6WcnJyc4Oztj8ODByMjIwOTJkztjqK0ybtw4jBs3Tlp3d3eHg4MDtmzZgujo6E4c2aO1detWODk5YezYsWrt2jKvT6LPP/8cUVFR2Ldvn9p97E8//bT0s7OzM9zc3GBlZYVdu3YhNDS0M4baKkOHDsXQoUOldXd3dxQUFGDDhg347LPPOnFkj1ZiYiJMTEwwffp0tfbHYV7DwsJw4cKFLvFZgpbglX0iLdGnTx/o6Ojg1q1bau23bt2CmZlZg/uYmZk1GV/3ryZ9dpTW5FsnNjYWMTEx Prrr Hs7NxkrI2NDfr06YPLly 3ecyt1ZZc6 jp6WHUqFFSHl11btuS6507d7Bz584WFQRdYV411djz1cjICN27d2 Xx0lXs3PnTsyfPx 7du2qdzvEH5mYmGDIkCGP1Zw2ZuzYsVIe2jivQghs27YNc fOhb6 fpOxXW1eFy9ejP379yM9PR0DBw5sMrarvMay2CfSEvr6 hg9ejTS0tKkNpVKhbS0NLUrvA8bN26cWjwAHD58WIofNGgQzMzM1GLKy8tx4sSJRvvsKK3JF3jwzQfR0dE4ePAgXF1dmz3OTz/9hJKSEpibm7fLuFujtbk rLa2FufPn5fy6Kpz25Zcd /ejaqqKsyZM6fZ43SFedVUc8/X9nicdCVJSUl4/vnnkZSUpPY1qo2prKxEQUHBYzWnjcnNzZXy0LZ5BR58s83ly5db9Ma8q8yrEAKLFy/G3r178c0332DQoEHN7tNlXmPb7aO RNTpdu7cKeRyuUhISBAXL14U//jHP4SJiYm4efOmEEKIuXPniuXLl0vxWVlZQldXV8TGxoq8vDwRGRkp9PT0xPnz56WYmJgYYWJiIvbt2yfOnTsn/P39xaBBg8Tvv//e4fn9kab5xsTECH19ffG///u/4saNG9JSUVEhhBCioqJCLF26VBw/flxcvXpVHDlyRLi4uAg7Oztx7969Tsmxjqa5RkVFiUOHDomCggJx5swZMXPmTGFgYCC //57Kaarzq2mudb505/ JAIDA u1d9V5raioEDk5OSInJ0cAEO 8847IyckR165dE0IIsXz5cjF37lwp/sqVK6JHjx5i2bJlIi8vT2zevFno6OiIgwcPSjHNnbvOommuO3bsELq6umLz5s1qz9XS0lIp5tVXXxUZGRni6tWrIisrS3h5eYk ffqI4uLiDs/vYZrmumHDBpGamiouXbokzp8/L1566SXRrVs3ceTIESlGW a1zpw5c4Sbm1uDfXbVeV24cKEwNjYWGRkZao/Ju3fvSjFd9TWWxT6Rlnn//feFpaWl0NfXF2PHjhX/ c9/pG2enp5i3rx5avG7du0SQ4YMEfr6 mLYsGHiwIEDattVKpWIiIgQ/fv3F3K5XEyePFnk5 d3RCotokm VlZWAkC9JTIyUgghxN27d8XUqVNF3759hZ6enrCyshILFizo9BfUOprkumTJEim2f// Ytq0aSI7O1utv648t5o jn/44QcBQHz99df1 uqq81r3lYt/XOpymzdvnvD09Ky3z8iRI4W vr6wsbER8fHx9fpt6tx1Fk1z9fT0bDJeiAdfO2pubi709fXFgAEDRGBgoLh8 XLHJtYATXNdt26dGDx4sDAwMBCmpqZi4sSJ4ptvvqnXrzbMqxAPvlqye/fu4uOPP26wz646rw3lCUDtOdhVX2Nl/y8BIiIiIiLSMrxnn4iIiIhIS7HYJyIiIiLSUiz2iYiIiIi0FIt9IiIiIiItxWKfiIiIiEhLsdgnIiIiItJSLPaJiIiIiLQUi30iIiIiIi3FYp IiIiISEux2CciIiIi0lIs9omIiIiItBSLfSIiIiIiLfV/ncCnhHI9LuEAAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.DataFrame(data).set_index(0).tail(25).plot.barh().invert_yaxis()"
   ],
   "metadata": {
    "collapsed": false
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}