sandbox.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import json\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "\n",
    "import base_style\n",
    "sns.set_style(\"white\", base_style.base_style)\n",
    "sns.set_context(\"talk\", font_scale=1.5)\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import globus_auth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_vectors(data):\n",
    "     for key in data:\n",
    "        return (data[key]['content'].get('composition#comp', None), \n",
    "                data[key]['content'].get('http://www.oqmd.org#delta_e', None),\n",
    "                data[key]['content'].get('http://www.oqmd.org#energy_pa', None),\n",
    "                data[key]['content'].get('http://www.oqmd.org#volume_pa', None),\n",
    "                data[key]['content'].get('http://www.oqmd.org#magmom_pa', None),\n",
    "                data[key]['content'].get('http://www.oqmd.org#stability', None),\n",
    "                data[key]['content'].get('http://www.oqmd.org#bandgap',None)) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Authenticate Search Client\n",
    "Uses a valid authentication token if it exists, redirects to web if not"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "client = globus_auth.login(\"https://datasearch.api.demo.globus.org/\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Search for Data and Aggregate into a DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'gstats'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-124-8d60affd6a74>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msearch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Found %d results\"\u001b[0m\u001b[0;34m%\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'gstats'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'total'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m: 'gstats'"
     ]
    }
   ],
   "source": [
    "params = {\n",
    "        'q': \"JANAF\",\n",
    "        'highlight': True,\n",
    "        'resource_type': None,\n",
    "        'count': 20,\n",
    "        'from': 0,\n",
    "        'stats': True,\n",
    "        'facets': None,\n",
    "        'filters': None,\n",
    "    }\n",
    "    \n",
    "r = client.search(**params)\n",
    "print(\"Found %d results\"%(r.data['gstats']['total']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Aggregate a Larger Query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "n_records = 1650\n",
    "offset = 0\n",
    "vectors = []\n",
    "\n",
    "for i in range(0,5):\n",
    "    params = { 'q': \"OQMD\",\n",
    "               'count': n_records,\n",
    "               'from': i*n_records}\n",
    "\n",
    "    r = client.search(**params)\n",
    "    result_iterator = r.data['gmeta']\n",
    "    for result in result_iterator:\n",
    "        vectors.append(get_vectors(result))\n",
    "\n",
    "df = pd.DataFrame(vectors, columns=[\"composition\", \"delta_e\", \n",
    "                                    \"energy_pa\", \"volume_pa\", \n",
    "                                    \"magmom_pa\",\"stability\", \"bandgap\"])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "    \"http://oqmd.org/materials/entry/363255\": {\n",
      "        \"content\": {\n",
      "            \"composition#comp\": \"Lu1Pt2Sm1\",\n",
      "            \"http://dublincore.org/documents/dcmi-terms#title\": \"OQMD - Lu1Pt2Sm1\",\n",
      "            \"http://www.oqmd.org#bandgap\": 0.0,\n",
      "            \"http://www.oqmd.org#delta_e\": -1.177739863125,\n",
      "            \"http://www.oqmd.org#energy_pa\": -6.515356935,\n",
      "            \"http://www.oqmd.org#id\": \"363255\",\n",
      "            \"http://www.oqmd.org#stability\": 0.0915803743750001,\n",
      "            \"http://www.oqmd.org#volume_pa\": 20.8716\n",
      "        },\n",
      "        \"mimetype\": \"application/json\"\n",
      "    }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "print(json.dumps(r.data['gmeta'][1], sort_keys=True, indent=4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize the Results "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x11c409630>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PhDs3IiLy3LXRXCnt3vTXQAU3wHcRJg1/pv2CbdsXLct6EnhRo79NlGtzpP3etsfXy8np\n6PDhw93cLiIiA6i9NNwPAmJGmHOj0vD+G7RjqWTj6+Q61ycBH3Bt2z5B2OjvLsuyMq03NYKfu4AZ\n27aVTCwiIl2JSsMXV6rYpxY5Nr2AfWqRxZUquYxKw/tt0IKbhwk7Gf68ZVn51guWZf0ksB/4nG3b\nUTj9x4Q5Oe9ue533ADnCpGQREREg3JHZrJFckrNzRRw3rGNZLjp87cQ8x55Z4L4Hp5V700eDdiz1\nEeA/ECYQP9UoBS8ALwZeCZQIOxRH/ivwBuDtlmW9GPgK8BLg1cCjwO9s39JFRGSnah+IuZmqp+WS\nw77dQ8wvVVgu1ihXXXLpBDXHayYXA8q/6YNBnC2VIByb8AOEgzOTwEXg3wjHLNht9w8DvwK8icuD\nM/8W+M8anCkiIusNxLzj6J51AxPPD/jwJy9/3Dx5cgG3fvnz4QVTExiG0Zw7JRvS4MzrScGNiMjg\nudpAzKs9zw8Cjk1frpxKJkysg5f7oL351ZZycDbW9S9n0HJuREREemYzAzHXE41diBkGycTlj9td\no+nm3zV3qj8U3IiIiKzjWgZiTu0f5Y6jexjKJpgcy1L3fOqez7n5EvapJRaWK5o71ScKbkRERDZw\nLQMxp/aP8vq7p3jtnQc5uDdPNh2nUqszt1RienaZBx6bVdVUHwxatZSIiEhPRUnD33jmEuVKfUsz\nop44uch4PjyOqrkemVT48Xvq/AqPJlU11WvauREREdlAVAZertTJZboPbDw/YKXkADC/VMFoyY91\nXJ8gCNYd1SBbo50bERGRdbSXgZcqV+9PEzX6MxvDM4/NLHDidAHf91gt15u7NgDJRAzDMDSSoccU\n3IiIiKyjm+GX07MFHnhsllPnV4GA0aEUiYQJQLnqsrBcperUGRlKMTqUAmByLAuoaqrXFNyIiIh0\nsJky8CggmZ4t8PFHTnJ2rti85/jJReJmjFQjwPGDANfzmVssEzcNrIPjzTwcVU31loIbERGRDqIy\n8PUa+LXutBybWWB+qdL8PiDA8wJKlRrJhEnMMIgZBsOZJG7do+75zdfpNodHrk4JxSIiIuvYTBl4\nlDDsuF7zMQMDMwaeF1B16rR2r0+n4owOpdm/O8fr755SYNMH2rkRERFZx2bKwM2YQT6XJJkw1wQ4\nuUySUrWOH4BhXN7lyaUTJBMm5aqnJOI+0c6NiIjIOjZbBn708ASTY5k1j2VScQ7fmCeXDvcRTDMM\ngjKpOJNjGSUR95EGZ/aQBmeKiAyO1jJwPwiINXZf1psG3l4tdXBvnrtftJ9z86t86otnqNd9kgmT\nybEM4/n0hlPFZQ1NBb+eFNyIiAyO+x6c5vSFVeaXKjiu1wxMbtozvOE0cN8PmD5b4ImTi5y+sNps\n4BcEASNDKW7aM6wk4u50Hdwo50ZERKSN5wecvrC6prTbcb3m9+vlynh+wMlzy3zx+EUWV6prnr9v\n9xBjwykFNttAwY2IiEgbM2Y0d1zarZScKwKbKDenWHY5eX6FfC7J/FJ5zT3zSxVGh1MdGwBKbym4\nERERaeP5AflcktUOAU4+l7yigV9rbs5qyWGlVKNauzwgs1Krs7BcoebWSSXi3HpogpsPKMDpF1VL\niYiItDFjBjftGWbf7iGSifCjMpmIsW/3EDftGb6igV8kZhjhvCgMam4dCAOblZJDAI2hmQFfOH6B\n6dnCdv5IzynauREREeng6OEJimWX8XyaIAiavWraG/i1dzCeHMtydq5IKhEnCALK1fB6Lp1oXofO\n86mkNxTciIiIdBAFHlEuzXoN/NpHNETzolZKDsPZBMslh2zaZGQoyeRYtnldk8D7R6XgPaRScBGR\nwbRRENKac9PqjqN7OHzjCB97+BlWS86aLsUQzpXaqKRcmrqO/pRzIyIichUb7a5M7R/ljqN7GMqG\nx05D2USzQV8sZnD08MQVgQ1oEng/aeemh7RzIyLy3LbeDk9rqbgmgXdNHYqvJwU3IiLPDZ4fYG4h\nV0Y5NluiDsUiIiL9cq07MApstod2bnpIOzciIoNro8Th9gBnqzs70pF2bkRERPqhtVlf++NRcLOV\nnR0FQr2n4EZEROQqomZ9fhAQa6t8ivrVzJxbXrOzUyy7ze87BThKMu4fBTciIiJXcfLcMifPr7Ba\nckgmYmua8Q1lE8RixqZ2diLtR1xXC4SkO+pzIyIisoEoEMnnkgA4rs/ZuSKLK1Ug7FfTaQxDJNrZ\nabVRICTXTsGNiIjIBqKAYzyfbgzSNIFwvEKUTByNYegk2tmJdBsISfd0LCUiIrKO9kBkPJ9eM0jz\n8I0jzfuOHp7oWE3V3om40zyqSHsgJFuj4EZERGQd6wUihhE+PnNueU1S8L7JHMsl56pJwpsNhGRr\n1Oemh9TnRkRk8KzX32bfZI6z86UrHo8GZgawpsS7veRb1VKbpvEL15OCGxGRnaVXPWQ6BSLR9+2q\nTp1do5nmvSO55Ia7ORrJcFUKbq4nBTciIjtDv3ZFokDE8wM+/En7iuuLK1XOzhV5wVQ4CTz6ft/u\noWbpOHTuaizr6jq4UbWUiIgMlOgYKdpViXrITM8WtvyaXqOCKdph6VQd5QcBc0tlkokYRqPR3/xS\nufG1suZelXz3lxKKRURkoHTTTO9qNtoBipKCF1eqnDq/wtJqldWyy+6xDIsrVUaHUziuD4Djes0K\nK7hc8q3jqP5QcCMiIgNjMz1kNhtQXK2L8NT+UWbnVnnkG+e4uFjG8wN8P+DiYpl6PeDo1ATJRAzH\n9UkmzGZgAyr57jcdS4mIyMDoppne1RybWcBvyaOM/t66MzR9dpnVsosBxGMx4mYMt+6zsFLh5Pll\nJseyAEyOZda8tkq++0s7NyIiMlB60UPmxJkCX35iDsf1qHvh0VLcjJFMmEyOZfD9gAA4eX6FquMR\n5bzGDIOYYeC4HrMXi4wNZ7jdmiSdinc82tJE8P5QcCMiIgMlChy2Wi01PVvgi8cvAAGVWp2VkgPQ\nnC01v1Rm5twyh24cgQAa/wDAC/xwcngsxlA2waG9w9S9sHvx4RtHmjtH6nHTXwpuRERk4EQ5MVtJ\n2o2OnSbHspy/dLlJX6nqkknFmRzLNpOTD92Y5/TFVUoVl7rnU/fCQMeMBWRS8WaeTWsysyaC99+W\ngxvLsnLAzUCedWrQbdv+7FZfX0RE5Fp1G9hECcl+EDA6nCKbTlCquniNoOXGyRzj+XQzOfme2/cz\nPbvMEycXm4ENhOMZ6vWAxZXqmvtjMaOn1VzSWdfBjWVZR4DfAV7N1ROSza0sSkRE5Ho4eW6Zk+dX\nWC05JBMmiXiMXSMZAgJSCZOJkTAxOEpOnto/ysRIGjNm4BngBxAzwtybiuMyv1RmPJ9u3t/Lai5Z\nX1fVUpZlHQQeAe4FHgVmGpf+BvgS4DW+/yjwwR6tUUREpO+i46Iot8ZxPdy6T6VWx8BoVj7B5eRk\nzw84d6lEzDBIJUxS8bCBX93zWS46nJsvsrBcad7fy2ouWV+3peDvBMaBn7Bt+9uABwFs2/5h27bv\nAL4Z+DLwTcDP9nKhIiIi/RQdF43n0+zbPUQyESOTipPLxDly02hzB6Z9dEKp4mLEwqMoI2YQJRj7\nfoBpXvkxe8vB8Y7vr/Lw3un2WOrVwFO2bf9Rp4u2bT9hWdb3AE8D7wF+8RrXJyIi0nftx0Xj+TTj\n+XSzq/CbX20BnXN4hjIJShWXmuPh+X4Y5BhgGDCcTXJuvsSHP/UUd922tzlAs+rUAUgn46qW6oNu\nd25uBB5v+b4OYFlWKnrAtu054AHg+695dSIiIttgveMiwzCax0WdAhszZnDL4XHG82ky6XjzOWbM\nIJuOE2/s3Mwtlvn4Iyc5fWEVPwhIJ+Okk3G+5dY9vP7uKQU2Pdbtzs0qayujlhtf9wInWx6vNB4T\nERF5Vthq8797bt9PuVpnfqnCufkiAG7dY3T48hTwmhvu1Bx7ZoHRoRTJRIzJsSzHTy5w8wEFNr3W\nbXAzC+xv+f544+t3AB8AsCwrAdwJXPlviIiIyA611eZ/U/tHed3LD3FsZoFkIsaZi6vUXChXw2Ou\ndNIEjGYzwIAAx/U5OxcGQqqQ6r1ug5sHgR+3LGvUtu0C8E9ADfjvlmWlCYOffw/sA/60pysVERHp\ns602/4sCoNWSw8hQimPPLFBzPEpVl93jWZYbgY1pGhgtByArJUeBTR90m3PzYeCrhDsz2LY9T5g0\nPAz8HvCPwHcDZ4F39W6ZIiIi22crzf+OzSxgGAbj+TRHnzfB7vEMu0YyVGt1Uomw7VsuvTavJ59L\n4vtBp5eUa2AEwbX/Ui3LeinwJsIy8SeBDzR2dp5TDMMIevH7FBGRZ4doRtRKyeHE6SUmx7KMDqeI\nGQaLK1Xml8o4rs9QNoFhGNQcD8f1mgM4b9ozzOvvnrreP8ZO1/XWVk+CGwkpuBERee5onxH1mD1H\noVgjl04wMpRkcizLeD5NLpPgBc+7nKwclZcDV/TMkY66Dm4GdnCmZVnfD/wUcDuQA84Dnwd+ybbt\nsy33DQPvBd4I7Gnc9xHgvbZtl9pfV0REBFgzI2pxpYpb9/G8oDlgM0oYbg1gNAl8e2wpuGmMYfhx\n4BWEycMQ5tl8Fvhj27ZP9mR1W2RZ1vsJ1/c08NeEJew3AvcABwnXimVZWcI13wZ8AvgrwmDoF4FX\nWJb1Ctu2nW3/AUREZEdrb/o3v1Qhkwo/UstVtzGLKk42HW8GMNcyqVy6s5XBmT8O/A8gzdqtosPA\nXcDPW5b1Ntu239+bJXa9vp8hDGx+D/hZ27aDtuutSdRvJxwZ8Zu2bb+r5Z7fbFx7G/BbfV+0iIg8\nq0RN/6IJ4o4bjlbMpOKMDCW5+cAoZiz8uGkPZhTY9F+3gzO/C3g/kAL+Hvg+4EWNP98H/B2QBP5n\n495t1ShHfw/hjs3PtQc2ALZt+y3fvpVwV+fX2m77VaAI/FiflioiIs9yUXO/mGGQbFRDVWp1ytU6\nx59ZxD61RNWpK5i5DrrduXkH4USwN9m2/dG2a18H7rMs6/WEJeHvAP752pfYlVcTVmx9AIg35lwd\nAQrAp2zbno5utCzrCOFR1f22bVdaX8S27bJlWQ8Dr7Esa19rjo6IiDx3eH6AuU5w0ppHMzmW4dT5\nsGl/3Iw1GvV5lKt1pmcLyq3ZZt0GN7cDD3cIbJps277PsqyHgBdf08q25qWEwZdPGGwdabkWWJb1\n323b/qXG99G1E+u81gngNY37FNyIiDyHRCXeV0v+bc2j+bP/fYwnZha5tBz+9/LoUDh28djMgoKb\nbdZtE78acGYT950Brkci7m7CPKCfB5aAlxE2GHwFYBPmA/1E496Rxtfl9hdpWGm7T0REBpjXaKYX\nlXhHCcPFssujxy4wPbt++7YAKFfrxM0YEyNpdo1kiJsxzs4Vw2GZatS3rbrdufk84e7N1dzeuHe7\nRcFaDfg+27YvNr5/2LKs/4NwN+cXCPOG+mJmZgaA0dFRxsbG+vU2IiLSI+27NJcKFdLJKz8eN9qB\nMWOXZ0cZbW1Z2kcsbHTUJb3R7c7Ne4DDlmX9hmVZZvtFy7JilmX9OmHl1Ht6scAuRbswX2oJbACw\nbfs48AwwZVlWvuXe9XZm8m2vuSn33nsv9957Lx/60Ie6eZqIiFwH7bs0hWKNE6cLLK5Ur7i3WHbX\n3YHx/IB8LtnxWjRiYXq2wH0PTvPX//Ik9z04veFOkFybbndujgJ/Rlgm/UOWZf0dcIpwR+4g4QiG\ng4Q7I7dalnVr65Nt2/7gtS74KuzG1/X+jYkez3A51+bIOvdeLSeno/vvvx8Id25ERGRnixrxtY5K\nKBSr1D2f8Xx6zb1D2cS6lU9mzOCmPcMAzC2VcV1/zYiFmXPLfPyRk833SCZinL6wyutefkj5OH3Q\nbXDzZ4SBjAHcRNgHplX0v/pPNP6063dw8+nG11vaL1iWFQduBkrAvG3bFy3LOgfcZVlWprViqtHc\n7y5gpttKqcOHD2958SIisn2iRnyLK9VmN2GAVCLOwnKVheUKEyOZ5uNR6Xf0XGDN8dJILsl8I7BJ\nxA0mxzLhEM3DEzzw2Oya93Bcn7NzRR54bFbBTR90G9x8kDC42ZFs237Gsqx/AV5tWdZbbdv+k5bL\n7wBGgQ8wI9nnAAAgAElEQVS29Lr5Y8Ljs3cD72y59z2EIxv+cBuWLSIi10HUiM8+tbjm8UwqTiIe\nY7XsMjGSWVMtNT1b4IHHZjl1fhUIOLg3zz237wfg7HyJybEs80sVHNdjfqnCC6cmOHTjCB/85+Nr\n3iMgwMDg1PkVdSzug66CG9u2f7RP6+ilnwIeBv7QsqzvI5xSfjvwSmAG+H9a7v2vwBuAt1uW9WLg\nK8BLCPvlPAr8zjauW0REttkthyZ45OvngcsBB8DBvXnG82l+4FXPJx4P01OnZwt8/JGTzM6tYmDg\nBz4nThcoV+tk03HSyTjj+TTj+XRzOOZyKSocDl+3UqtTqrp4XoBpGs1ycemtbhOKt8yyrLdalvWn\n/X4f27afIex382eEvXb+I+Fx1O8Cd9i2Pddyb5mwTPx/AN9EWEL+fOC3ge+0bbvW7/WKiEhveV2U\nXR85MMrkWIZCscrcYoVCscpwLsnocIqhbKIZ2AA88Ngsx565xOkLq5w4s8T02WVOXVjhyVOLjZ2c\ny6Kp38WyiwEc3DtMpVZnpeTgeeH6oq8z57qqW5FN2M6p4N8G/Ajwln6/USNP5q2bvHeVsDz8F/q6\nKBER6auopHul5JDPJTc1dXt6tkAyYTI6FO62VB2PmXPLzC2Wue3IrmZ34ROnl3jq1BKFYo1K1SMI\nAgLAqwdcrJeBgCAYbQY1kSgJ+Z7b9/PEzAJx06DuBcRNg2w6wcG9eTX564PtDG5ERET6IjoyivJd\nkgmzYzVSe4+ZYzMLjA6HR0Onzq+wUnKImwaJuEE6GefRYxcAePBrZ1kuOZQrdVo3hupBgO96rBSd\nKwIbuJyEfOjGEQ7uHWF+qULNqZNKxpsJx1GJufJuekfBjYiIPOtdWY3kralG6jROwfUCvvzEXDMY\nAtg9lmkGKVHezGe+MsvTZwok4kbHipogCLsT75nIUqy4HUc2RKXirfk4fhC+2kYl5rI1Cm5ERORZ\nzfODK3JeIEwQPnU+zI/54vHLfV1PX1jlwcfO4rgeTt0nlTAJCFhYrpLPJcmk4iQTsWaQc+r8ColE\njCwJ4jED1wva3gecus9nv3qWX/mxl6+7C3P08ASPHrvA0mptzQ7TK1+6v7e/ENm+hGIREZH+uRxw\nVGp1Li1XmFusMLdU5rOPzTavLa5UefpMgbPzReaWylRqdRaWq1RrHqZpUK6GnYonx7IsrlR58tQi\n5xdKVKp1qjWPbLrznoABPHlykU9/+cy6uzBT+0fZN5lrNPLzSCZiTI5lODtfUrfiHlNwIyIiz2pm\nzODg3nBiTntFUi6T4Okzyyw0JnWfOr/MSqmG5wX4PsQMMAxYLTvk0gn8IODGyRwAZ+eKuK7P6FCK\nuBl+XI7mU3SKXQzDwPcDPtcoK+/E8wOWSw7WwXFeMDWBdXC82QU56pQsvaFjKREReda75/b9lKt1\njj0TBgmmaZBLJxjPpzlzcZVLyxX27spxqVDFMAyMWNR5xiBuhoFJPpdsNu9bWqmSTceZHMsCMDu3\n2jiuSrG86lAohv1rwuDIwGh8LZYd6nV/TQl5axXXidNLTI5lrxjtoKTi3lJwIyIiz3pT+0d57Z2H\nwmokt04qESeVNFktOaQSJjXHo+Z4VJw6CdMkGb88+9mt+7ieh1P3OLg3z+hwipVSjV2j4eiF+aUy\n1ZpHrZEjc8N4lprjUfd9giAMamKGQTIeYyibvCKwiSquYoYBGM3E59YAR0nFvaXgRkREBsKRA6O8\n5JbdrJbCsmz71BJweZxCOmmSTsZxXI/djR2ZUtWlXPPJpRPs3x1WMy2uVFkuOlxYmCNuGgxlwiTj\nKNH44N48qWSc6bMFfD9oDlx0PZ9symz2xoErj5smxzKcnSsyv1ReE9y0zq2Sa6fgRkREBkZUkeQH\nAY7rNR+PxilMjmZ5erZAPpfArQfkcwmyKYcjN401A5uzc0UIwjyceMygWKkzNpRidDjVPKY6+rwJ\ncpkE07NLFMt1TNPg8I15bpjINXdqDt04QrHsrllfFNDML1UIgoDhTTYblO5sZ3Dzj8DJbXw/ERF5\nDvH8YM2OSdi7JliT4zI+kua2zC4mRjKcubDKStmhUvOYXyoDYdBRqdWpuXXMmEEsFubjLJdqHGj0\nqQF42a03MJRNUHM8gsBn93huzU5M1HV4KJvoGODctGeY77nreTqK6pMtBTeWZZnAdwF3AruAR23b\n/tPGtUlgDJi2bbsZNtu2/VHgo9e8YhERkRadGvS9/u4pbj00wReOX1hz72IjUfjMxVXmlkrsHs+R\nzyU5O1dk9uIqVcdrlIOH4xHCPJnw4Knm1IEwP+bIgTGet2+0eQTWLkoQjnaS2h09PKHApo+6Dm4s\ny7oD+CvgEOExYwAkgGgo5quAvwS+H7ivJ6sUERHpoDVhF8KgIvr+5gOjGAbNwKfaCE7SyTinzq/i\n1gPOzhXZt3uIfbuHmF8KB2cGQD6XBGClMdXbNA0c1ycIgjX5McO55BU7M3A5Qbh1J6lT52Lpj66C\nG8uybgb+BRgmDFweJJyg3eqjQA14IwpuRESkj9brDxMdC0V/fD/gYw8/E+6otOXjzC+Vmz1nJkfT\nzBcqOK5PpVbHDwKqTp10Mk4sBne+YC8A9z043QyYytV680jKDwJihrEmAIrW4NZ9EnG1l9sO3e7c\nvBsYAn6s5RhqTXBj23bFsqzHgJf2ZokiIiJX8vyg464JXNk3Jmg8BmFJdjJhNgOcaEfGMAxu2pvn\n6NQu/vnhGVZKDol4jNGhHOmUyd5dQ8zOrXJ2vtR8n3QyTrla58JCieWiAwQc3JtfM1zzxOklnji1\nqJ2bbdRtcPMq4BtRYLOB08BrtrYkERGRqzNjRseEXT8IG/K15rS03xuVZAPNOVKLK1WqTp1i2SWZ\nMBnLp0jGTZIJsznB++Gvn+dQoxtyq+VijeffNMbSao1T51c4cfpxJscyGMDcUqX5GkDz2EwBTv90\nuz82CdibuC8BZLtfjoiIyOa1Hv8srlSxTy1ybHqBS4XKFfOaWu8dz6fZt3uIZMJk12hmTT7OwnKF\n+aUySys1XM9vBjZ+ELBacgiCtYMzwyGYPksrNc7OFZtHWk+cXOT4yUUqtXpzSnk0BkLjFvqr252b\nRWAz40uPAFemh4uIiPRQtPvxwGOznJ0rkkyY7Ns9RDoZX7ND0l4mXiy7ZNNxDu4dJpUwOXVhlXwu\nyeJKlXPzpeYYzuVibU1H4eFcck11VJS/k0zEmC+Um4+Xqy6e5wNho8Do68Jyhb27hpgcy2jcQh91\nG9x8Hvhuy7JutW37eKcbLMt6OfBC4C+udXEiIiJXM7V/lGMzC6QSZjPwiBJ7H3hstmOZ+NNnCs0y\n8WhHZrXkUKyEScI1JxzHkIjHCAiYX6ownk9z12171+TcRPk7u0bTnGs8HgQBdS/AbAzbrDleI9Ax\nGt/XmV8qM3NuWUdTfdLtsdTvEAZE/9gIYtawLOtFwJ8DPvC71748ERGRjUWJxVHejH1qkcefvsRj\n9kW+fuISq41y7mLZ5ZHHzzM9W+DxmUvN54cBSoxy1eVSodycKO77AeVKnQsLZcpVl5fdegP3vPgA\ndxzdw1A2AYQl36986X4mRjIkEuFHqmGEwzhz6QS5dIJ6S2ATNw0Mw2ByLKujqT7qaufGtu3PWJb1\nXuCXgYcsy7pAmIT+PZZlTXO59807bNv+Uq8XKyIiz12eH2B2OMaJkoVPX1jl6TMFylUXt+7juOHO\ny9JqDQhLvpeLDp9//ALxmMHIUKqZTzM5luXcpRIBBm7dw3F9DAxymTgJ0yCTjjca+rGmvDwWM5ie\nLTB9dplKtU6hWGN0KMWhG0fC/BwCRoaS1L0Azwv/vm/3EOP5tCaB95HRnhi1GZZlfR9hWfjtbZeO\nAb9s2/Y/9GBtzzqGYQRb+X2KiMj6OnUgbj/OmZ4t8Af/8DUuLFRwPZ963cP1fOKxGEPZBGPDYR+a\nlVINMIjFaA7E3Ld7iNHhFF86fpHVco1ytU4Azcnhbt1j93iW3WNZ3vxqa817tzcRXFiucKlQZXIs\nQyYVxzDg1PkVwGByNM34SKZ571A2wevvnurb722AdB39bSm4iTRGLRwiPN46Y9v2uS2/2ABQcCMi\n0lvtwUPkjqN71gQZnh/wc+/7NPOFCq7rU/f8ZlJwzDDI55LUXA+CsNtwPpfE9wMmRjIkEybWwTHs\nU4vsGs3w9GyBSrVO1fFw6j5x0yCbilP3Ag7cMMS3v/gA3/HSA8DlZn6twqniNQ7fOMJQNkE+m+Dc\npTLt2n8GWVfXwc01Dc60bXsemL+W1xAREVnP1ToQt6p7Psm4ieN4GAYEfpg34QUBxUpjjEIsRuAF\nLK3USCRi5OthCXguE+eVLz3A2fkSlwpVsimPS4UyQQCGAXUvwA98zl0q8Vf/8iQz55e5+0X7OwY2\nUXVVEIS5QMWyy77JHMslR438tsl2TgUXERHZtG46EEN4zLS0UsMPAhpV2E1uPczXMY0AwwgTf30/\nIBGPc/OBUd7wipuBcKeo6tR56tQSGAamaRAzjEZSMM1k41PnV0gnLzRHM0Tml8I+NlFjwMhyyeH1\nd08px2abbGVwZgJ4M/DtwI1Aap1bA9u2X7X1pYmIyHNZa1fhqLQ7Eg2mbL33mw6Nc3GxTLlWX+cV\nA2Ixs+U5MfwgoHWod5Qs/PSZAh/+lM307DKmaeAHRvP9W4dotmYitM6smhxb28e2WHY1W2obdTs4\ncy/wSeAWrn4GpuQTERG5JiO5JF9+Yq7RKO/yGITWbsORb3/xfp6YWWC5WGt+ABnRPwIIgnBHxWsM\nfgoIqDleOC7hzBJHDow1r918YJQ3v9riD/7h6xRWa1SqdYxYmGScz6Wpez5PnV7CcX1uPjCCYRik\nk3GGc0nyuWSzo3GsUZ6+UnL4yL8+pSOpbdLtzs37gFuBJ4E/AKaBYq8XJSIiMj1b4MxckcmxDPNL\nZRzXY36pzAunOgcHU/tHed23Hmbm77+G5/mNfBkDwwiTijFg764sjhuwUqqRz6XIpOKAwSc+f4p/\nevAZCqs1DAMO7s0ztW+E0eEUhWJtze5OOKohjuP6JBMmmVTY8+Zbbt3DHUf38PFHTvLkqcVmYrNb\n97n5QLjeYtnVbKlt0G1w81rgHHCnbdsrfViPiIgI07MFPvypp1gtOSQTMSbHsowNpzAMg+VGU75W\nUQ+cV73sJv73w8+EIxQaycDJRHgUFTcNzJhJzW0NbCCVNDk2vcByqUY6GSduGswtVnj4a+cggHLN\npe75eH7Yq6bmeuRz4Q7Pvt1DzTUcP7nASC7JqfMrFIphbx3fDxjOJq9Yb6eEaOmdboMbE/icAhsR\nEemX6dkCjzx+vtlZ2HH9NfOdWpOJO/XAecMrpvhfn5mmWHHxfZ+4GSObTvD93z7Fnokh/uoTT645\n5gqDkSq+DxBQdXxqTjg0EwwSZgwwMAjwPB/f75yVcfrCKvNLZeJmjF0jGfwgaCYYR+MbImrg11/d\nBjdfB6486BQRkeec9ToGX6tjMwvNmU1Rgi6EHYbH8+lmMnF7D5zoyGffZI6xfIpLyxXcusdILsW3\n3raXe14c9qZ5yS27WS05GIaBHwR87akavg9hEZWBU68DRjgfKhbm5vhBAAYkTBPP99nVaMYXrQnC\nIZuOe7lMK9aotipVXTKpOEEQNCuo2hOipbe6Tdv+beAVlmV9Sz8WIyIiO9/0bIH7Hpzmw5+0ue/B\naaZnC5t+bpSwu9H1lcaOzeRYZs21qEIpSibu1ANncaXKxx6aoVrz2DWSYTibpO75fPH4RR74yhkA\njh6eWFOmjQGxWNSROAj74wRra8kvV0YFJBMmfuATEDTX5AcBI0Op5hFYJJdO4HnBFaXhnRKipXe6\nnS11n2VZvwB83LKs3yOsnJolHJTZ6f7T175EERHZKdbbLYGNE2Q3O0Lh2MwCJ04XgIDJsSz7dg8x\nv1TBcT2Gc0nufMFepvaPrtsDZ36pTKFYI5uKs7Raw6l7BD5UnSIfe2iG/buHm+8brWf3WIa4GaPm\nhLtERgzwY8RNSCfNcMq3ER5MpZJxEvEYvg/LxSqmGaPmetxz+/5msBUdoQFkUuH9B/fm8YOAfC6p\naqltsJUmfl8l7Er8nxp/1hNs8fVFRGSH6qZjcGQzAVHrPbtG05ybL3F2rsi+3UNYB8cIgqAZ2MDa\nHjgRPwiTfQ3CpnlRsAJh872F5Qqf/vKZZi+baPjlzLmwwsk+tcjCchXfD4+P9kxkG/1pvGaPm3LV\nJZkwKRRr5NIJpvaPNJv43XJwvLmeKCBLJkxutyZJp+LNHCLpv2773Lwa+BiQaDy0gErBRUSeE7rt\nGBzZTEB0bGaBxZVqo+Tbp+55gMH8Upmb9gx33O04enhiTdAUMwxSCZP8UJLZlhEIhmEQEFB1PB49\ndoHJsQwveN4upvaPEosZTO0f5YVTE8wvVchlEqQSJqlknKWVKjWnjls3mj9/O6PRx+bDn3qKQ3vz\nVJ062XQc6+AYuUyc0aEUZ+dLFMsuhmFQLLs88vh5QKXg/dTtzsp/JgxsfgP4bdu2l3u/JBER2Yk6\n7ZZE1kuQ7RQQRc3tooAoIKw0aj3OiZth7squ0Qzfc9fzOr52+/HSUDbBK196gK8/fYnTF1ap1wOC\nRju/MPCJYXB558j3A47cNAaEOz3RDlHQuL/meAQE7B4zmS+U8TyfctXD9wNy6QSZVJxT55ebaw2C\nMB8nZhh8y617uPnAKPc9ON1cbxi8hTs6py+s8oPf+XwFOH3SbXDzQuALtm1vdBwlIiIDqn23pPXx\nTloDotadmWQizEOJgpaVdY5sVsvuFYFNa5VW6/FS631feuIiq54bNiduNPMLGkm/S6s15pcq2KcW\necktN3DLoQlWSg6FxuOO6xGPG6yW3Ealk0mx4hL4UPd9YsblCqjlosP4SBrP83nqdKF5FFV16hze\nN9IM7BaWK5ybL13+uUoOn9cOTt90G9wUgWf6sRAREdn5Ou2WXC1B9ujhCT7+yMk1OzOO61Ou1pme\nLXDoxhHyuWTHnJR8LrlhT5vofVsDm0LR4WW37uHpM0sUKy7Lqw4+AU7do+p4PH2m0Gzgd+r8Cl9+\n4iKLK1Wqjkc8FsPzfepeQNWpEwQBnpcgmuEQw8DzfWqO16iYgmrNa/xMl7+eOF1g5uwyVafOqfMr\nnL9UIoDmjk9UPaVmfv3RbXDzSUBl4CIiA2CrfWrW2y3Z6P5sOt7sW9M6Iyr6cL9pzzCwNhF3cizD\nTXuGN+xpE70+hEnJ33jmEo9+4wLJRIzd41kSK1WKZRfTMEjEY1Rr9WbuTDwea+6mlKt1HNfHcR1S\nSZO4GSNuxihWXOKmT8KM4fgesZhBwow3jtZi7B7L4Lhho8BWyUSMz351lnK1Ts3xqDemiUc7VPt2\nXx7HoGZ+vddtcPMO4MuWZf0W8C7bttcbvSoiIjvUZsqyN2OzH8ieH5BOxps5La39XqIP96OHJyiW\nXcbz6TX3bNTTJnp8av/omuAnCqKWiw6rZYdYLMyf8b0Atx4eK1WdOsmESSIeI5uKEwRgmmB44NQ9\nUkmT4caATM/zSKcSxE2jmY8zMZLm333vUQzgT//p2BXrmhzLcur8Cs9vyempOR6mGQZZUeM/NfPr\nj26Dm7cA/wz8IvAmy7I+w/p9bgLbtn/12pYnIiK9tNU+NdeiNe9mTfM8Ln+4dzruuuXg+Lo9bVqT\nkt26z+PPXA5+JscyPH2mwHKxRqnqYhAOz8SAet3HD8JgyyAsEV8tu0C4E5NNxYCAiZE01Vq4UxMz\nYiTiBplUkpGhFLtG0xzcm28GLkduGuXU+ZVmLtHkWJbR4RTzSxUMwwinmD9vgtm5VYxwTnkzgFMz\nv/7oNrj5FcL+NQbwvMafdtH1AFBwIyKyg2ylT00vbCYROTruevpMgeMnF/jiExd54tQiRw9PtCUl\nh0dX4TBLnydPLXLhUomRoSQH944wnk+TiIc7JOE4hPBjKdboX5NoVDfF4zG8xnFRLhOn6vh4XoBp\nxqjWPFZKDsPZsMPwWGOnJTpOa133Pbfv59HkhSt2pQ7uHW7+PdqpCWdNBQyrmV9fbaUUfOPe2SIi\nsiNttU9NL2w2EXl6tsAXjneeF9VaLl6p1VlcqQLg++EH08JyDbdeYGr/CHHTJBYLd2Eg3CmpB+HX\nmAHZdJJsKk6lVseMxag5PmbMoFRxGRlKUnU88rlwmrdn+iwsV5vBy+tefqi5bs8P1v3ZgDUB3Xg+\nzXg+zctuvYEjB8Z6/BuWVt2OX/iVPq1DRET6bCt9anppM4nI6+0sLZecRlJyuBtTc6MjI4Ny1SWX\nTrBScihXXS4VKiQTMVZKNeJmrJHMGzT/07zm+pi1OvlcklTSZLXskoiHCcgTIxkWliuUq2Fn4mTc\nJJU0cesuVadOsbLCPz7wNC+95QaWS86aYOb1d091/Nl6kd8k3TGCQBsxvWIYRqDfp4jsZO05N5E7\nju7p64fuZiqzPD/gw5+0O17zgwCDsF9N3fM5PrPA3GKleX33WIaq41Gqukzk00ztH+XBr56l6tRx\n6z6+H9DaYDhmQCYdJgnHDIORoSRmLEapEShVHRfPD8u8Pd9vHl/FYpBKhp2Hbz4w2jxugs6/w+jn\nVkXUNen6F6fZTyIizyFb6VNzLTaqzIpKsqOgZ6OdpXwuyaVCpZm4u1x0mknFcdPAMAwyqTgjQyle\n/E2TvOEVNzNzrsAz51aIGQZeh//wdN06NSccbll1PAw8PC+cSp5MxPA8D9fzcBul3n4Q4HtQK9Vw\nXG9N1ROszVvqVUWabE23s6Xe08XtqpYSEdmBuu1Ts1XrVWbNzq3y9GyB0xdWAYODe4e55/b9TO0f\nXTfxeCSX5PSF1UaCMKQSJqWKi09APnc5wIjmRnl+wGvvPMRf3v8kK+UwEIp2b6LKqaCRg1P3fOp1\nP3y8sUng1sNEZMcNAx4/CC7PlgqghselQoWF5QoTI5nmzxcO4lze9oo0WetaqqU6iUJjVUuJiOxw\n/T4m6ZQ/M3NumX/94mmCAOKmQTad4MRpj3K1viZRt33X49jMQlvFEdwwnsXzfYazSaIgaWrfCMdm\nFnj02AWGsgl2j2WYW6o0A5PoJzYwmh9Ybt3HD3xS8Th1Lwx2AMbyKco1n6rvUvfCYzGiknLPx637\nXCpUm8FNlLd0vSrS5LJug5t/t87jMeAg8DrgZcDvAF+9hnWJiMizWHtl1uJKlVPnl5mdK+K4PtlM\nHDCbHXvnlyrND//2nSXPD5o7H1HFUWvZ9Zu+4wiJeOyKHZPHpxc4d6nMUCZBzfVwXC/cuSHcvTEw\nMM0wH6bq+BiGH1ZTxSARN8mmEowN+Vyo1aExgtOk8WQCXM/Hcb01PWuuZ0WaXNZttdSfX+WWX7Es\n6zeA/5swyBERkWeRrY5kaNc+MPPsXJHCqtOYAh7gOD5G0iBuxig3hlCulpw1H/6xDXJxDMNgYbnC\natnl7z99gqFsgkuFCunk5Y+1MxdXgLCfTTJhUqm5lKv1ZpfheDzWnORtxmLETYNyNZw/lU6GeTb7\nducoVlxWSjX8ALwAYoTPMQxIxI0retZcz4o0CfUjofg/AT9EeCT1g314fRER6bF+JMBG+TPzS+Vw\nAGUjcDGDcA6TU/eImwZ1DxLxGMO55Lof/q25OOEu0AoLy1UmRtLkc0k8P+DE6QL7dg8xnk9T931q\nTni8FDMMhnNhZZTnh+vYPzlE1amTSSWoOR7LpRqOG+bgJOIG6aTZyOupU/e8K9bj1n0yqQQ/8l1H\nufnA6LprbX9ctkfPgxvbtn3Lsr4CfEevX1tERHqvU+LvI4+fB2iOP9jqgE0/APvUEoYRjkAwzRh1\nz8OpewSA7wfEzRjpVHzDD/8o0HrgsVnOzhUpVhzyuSRu3edrJ+bJpcOjp7rnM55PE4/FSCUbzflM\ng2wqQTYVTuReWq1Rcz0Kq05zJMTusSylitPoixMGRYVijXLVpVKrrznOCgCCgGQifkVg07pWVUtd\nP/0qBc8Dw1e9S0RErrvWBNjW8QZPzCwytX+ERNxkZKi7cQFRQHTkwCgvuWU3p8+vUKnVCRpHT27d\nw/fBwSedNDf1mlP7Rzk2s0AiHuP4M4tUavVGzk7Q7E+zsFxtVjAduCHP02cK5NKJ5ms4rk8iHsPz\nA4wY1H0f34eqU6cR0zSngi+tViEw8VumJ/oBmI1eN0ZjVlU8vnYieLTW7ahIk856HtxYlvWtwN3A\nk71+bRER6a3WBNgoNwbC8QZzS2Vmzi0TN2PkMgken77ED36ntWGAMz1b4BvPXKJYdsk3clGOHp7g\ny0/MkUmFHzmlarhbkk7GyKYT7N2VY7Xk8MBjsxu+drRWMxbm0JxfKFF16gQ+GDHIpuNMjKRZLbtM\njGR4wdQEN+8f4enZZVZLDsO5JDW3zmgiBXC5q3EjSMplwjlSuXSCYsUhnYxTrrjNqqroayoRh4BN\nBS4KbK6PXva5GQYs4F7ChPLfu4Z1iYjINmhN1o1KrAEuFSpUnToJ08QPPOJOjKfPLHPfZ6d52w+9\npONrPfCVM3zsoRkKxRoGMDKU4vSFVV57x0EmxzLMLZUJMMP3zCRIxMMdm6ja6NT5lQ0Dhta1JhMm\nlWqdgCCc+g2sllxuPpDj0N48P/Cq52PEjOZxWr3u4wO//P7PNV8vCrb8IKBSrZPPJSisOswtlSlX\n65f72rSpuXVSibBhoHrS70y97nMDsAr8um3bf7TVRYmIyPY5eniCRx4/j+OGibNBEFCp1ZtBRuBD\n9H/9T50pNCqeWJOHMz1b4GMPzbCwXG08ErCwXMWth+XSVSfs9JuMmyQTJrFGGXfcNFo+Ua6+yxEl\n6xZWK2G/GTcAwycbT5DPJak5HuWayz8/MtMx36W9kikKcJIJE8cNWC07YZn4Bkvx/LCJoBkz+Jt/\neVITvnegXvW5AXCAs8AXbduubHDftrMs6+3Abza+vdO27S+0XR8G3gu8EdgDnAc+ArzXtu3Sdq5V\nRK6bQaEAACAASURBVGS7RR/Kpy+sslpycOt1gsaoAd/wiJsxwGgGPfc9OE25Wl8TODz+zAKFYo26\n54fJwn6AETNw6h7lqsttN+9qvHaYwBIl7fqBwdxiBdM0uOXQ+FWPcab2j3L64iqf/vL/z96bxkiS\n5ud9v/eNK+86uqvva6ZnJrU7e3B3JS2XS3JJiTooUYdlgyIgWzBswYJt0pAPQLYk84NlgJAFCJY/\nmIIh2DAlS6IAUiK9IClKWnL20HK9O8fuTG9vbk8f1VXd1XXnHff7+sMbEZV1dR1d3dPDjgfo6Z7M\niMjIyMyIJ/7/5/88EZYURGi00oyDmOUNxVrPpzsMmG54zM3UAApX5N4oQgjBWs+nXjHi4ly388rl\naRaW+9QrDkKAUlEWuLk3Um2IoBCidCB+DnHSPjfPHdrt9scwFachUN/j+RrwZeATwL8C/gnwKeC/\nA3603W7/aKfTiZ7ZDpcoUeKFwEn5yZwUrl+a5i/+xGv85r+7y/uLPRCQZq68WiuGfpS5CksWV4bM\ntirFRV0pU/GIE4UfJqRKobOYgzBKsaRgplUBIVjd9JlueGwOAgQU2VC1imlT3V7s7kkQJo/XYBwx\n3fAIwgQpBInS5o+f4DgSgSCKVaEfAjOx1b46w7XzLWDLAydVmlcuT3PpbIP3F7qFMeDjMpCFAM9x\ndj1eOhA/P/h9HZzZbrdt4P8G3gbeB/7SHov9deCTwC90Op2/ObHuL2TP/dfA33n6e1uiRIkXAc86\nUPEoJOr6pWniRDEKYhzbIkkSFKBSjdYK15FMN92CNORxCDfurdOqu0VOUw6diW7BNLVyd+H1ns87\n34+QWZ6BmU4SPFwd8sv/5vv8xZ94bd8Ayo9cnS3aSmGcmrRwQZH4HcWmenP5jBnYXd0cF4+nSmFJ\nyZVzTa6db1HxLIJwy8MmHx3XWgECS8LE2ylQca3MN0duc0ouHYifH/y+JjcYQ8GPAJ/GEJW98J9i\ndEL/847H/zbGafmvUJKbEiVKnAD2C5KEk29nHIdEpUrTHYbUKw5pqpBCGI8XpdFa06y5TDe25zvl\nY+PXL0+RKuPqO1m5sSyzjfdur+E5Fp5r0x+FSCk4PVVlcxCw2g1wbUnFtfDDhN/LPHaAXcfrmzeX\n8cOkiE1Ild5WZRHAyI/xw9gY9MUpQZgQxoo3b64QximeYzHV8JibqXL5bJPBOEJmqeIrGwOUNtv0\nXJsoSsg6aUgpaNUcGjWHwSgmihWbg7AgeaUD8fODx5Kbdrv9pSfYtu50On/0CdZ/IrTb7U8DfwP4\nW51O53vtdnuvZV4FLgC/tVMn1Ol0xu12+2vAH2+32xc7nc6DZ7HfJUqU+P2LZxGomCrNvSdKpRaM\nghgwLr0qIyqWJbamm9D0hiFhlCCEwHUkFdfGtixwBKkSpKku3IDDNOXR+ojpRoVxMKJWcZhuePhh\nQncYohVEsXErHgUmrmG/YwWGNCWpYq9hJp0dg+4gpOqZ0e5RkGBLWXjihJGp1oyDmChOWdkYMwpi\nesMIz7UI4xS0eY2XLk7x0oUp7j/qESdbrxNGIZ5jbatilQ7Ezw8Oqtz82BNs+wObkGu32y7wS8Bb\nwN99zKKvZn/f2uf5W8Afz5YryU2JEiWOjacdqDhZqbm31KdVd4uKQo6DSJQlBZfPNVhYHmSp1ylx\nokFo3My0bq3nk6aaKEk5PVWl6tnMzdSQQjA3XaU7CKlVbDb6QeZnY3Q6YZSy3vOxLMmULbl6vsW3\nb62SZincJrwyxbElb35vhdWuz5npKtPZe5AT40sV1+b8qTr3lvroZPf70Bp6owjHHtOsu7x0YYrv\n398kjBJU5okTJQnNqsethS6eY/FofQwa6jWHMzO1okUVJ5pTU1XqVYfbiz1GflyMgocZ2+mPom2J\n5iU+eBxEbl56Jntx8vjbwHXg051O53Ekayr7u7fP8/0dy5UoUaLEsbBX+GOOJ21nTLa7lNYMRhGD\nLG17kuAchkT9+Kcv8+3vr7LaDdAKLFuilUYpY+w33fAY+TEiq/Ccma0y26qw0Tcj4GFsRrHzqSjb\nksW4tXElNq2vK0pnuVLK+MnorYrMyI/Z6Pk8WBmSKo1rS6YaLlfPTzHbqlCvOniuTavmshoFu96D\nFOZ4f/z6KZbWfZRSRQsrTsy/lYYgTKlVHJp1x+h/ssNS8UyFKt/v/+DHX8WyJb/4K99mcXlAxbUm\nhMeaVkagduJ5E42/SHgsuel0OvPPakdOCu12+3PAfwv8fKfTufmsX//u3bsATE9PMzMz86xfvkSJ\nEs8xnlag4mQLR2ZtoihWrG7628jNYUjU9UvTvHxhiiBKi2gBS4qspWOM+V65PM3q5pgoVkVF5uHq\nCNuSnJmt0R0EJEmEY5vwySRVBGGKRuPYkihOebg2IopVNo1lXjtVGikgRdEdRgggTjVSCNZ7IXHS\n5ZXL03z29XPcuLNu2kd7QAhjEiikpDsMmX/UL4hNmuqirRDGCqUjVjYESapRWhMOQvwgRkhBxbW5\nOFfHzeIhltZGbPQDklQjhaZR86h6Nv1RtO24PmvReInd+H0lKG632xZmOurb7BYB7/WLzis2+1Vm\nWjuWOxB/8k/+SQB+9md/lp/7uZ877GolSpR4AfA0AhX3anfNzdR4sDIkitNt0zyHIVGp0pw9Vcdx\nLO4t9egPI1M9cSym6i6vXZkutndrYZP1XsLDtRECqFUcQ3wqDg/FsCATQZQYC0BhRLm1isPAD+kO\nAuIdXjJKm//4YYItRaahMVNOYZxSq9hcuzBVeO4IsXtsO1WaYRDz5vdWqDhWpv9Re/rWxInRD9mW\nIIrM80GUYklJmsRobciK0kaoPBjHRFkFanMYMV33uHimUVTEnqVovMT+ODa5abfbfxT4AnAxe+gB\n8Ean0/m3J7Fjx0QDeAWj94n3EBFr4Peyx/88kFd2Xt254I7H99Pk7MJv/dZvAaZyU6JEiRI7cdKB\ninu1u/JqTT8zrWvUHD5y7XAkKt/eRj/AsSxmpyoIBGvdMeMwYXMQAjC/1GezH6K0qax4E+GXczNV\nesPQVHtkNgqe8QozgWUEyzpL2t5JOVQm5hVYOLbAkpJm3aR6e45VTETt50VjHIYFfmAmvTxPMhrv\nMdOdIUn1NuKjNSitkEgero345X/zfc7O1kiVSR3XOn9PmoEfEcVp8Vk+C9F4iYNxZHLTbrc/AvxT\n4OPZQ/mvUwN/s91uvwv8TKfT+SCCM0PgH+7z3BcwxOfXgFXgXqfTudVutx8Cn2+329XJianM3O/z\nwN2jTEq99NKHVaZUokSJZ4mTHBneq90126rwk5+7htKam/c2+OZ3H3Hz3vqhKkV50CUYXcooiAlj\nhZSCzvwmjaqTVTsknmvRG4bGox5Dej7VPsMrl6d5uDpktevj2BZa62yiSjL0jeHf4xyAtYJIp1jS\nkCY/SJhuVGjWXd54a4GHa8Y8XsA2n5v8MZ1qsARxkjLbqhBGKdEe4uM9XxtQClKhGY4j7jzocuv+\nJuPAEEjHssjjKJRWrHXNpeNpi8ZLHB5HDc48B3wJOAssA/8cuJM9/RLw0xin33/bbrc/0+l0djeX\nnyI6nU4A/Gd7Pddut/8vDLn5hR3xC/8Q+Hngf8SMjuf4eYyj8f/xdPa2RIkSJU4G+7W7AL753eVi\nub1aJJPhkJYUpEpz7cIUczNV5pf69EcRliWKatDK5hiB0a14rkUYmXiGKDGj3Ou9gPWez6mpKj/5\nuWu8d2edr7yzyEbPVHziJM3aZQe/L61hHKakKqRWcTg9XWGq7vKlby3g2kaoPApi1I6ijAaiVCG1\nwsq8ehxLAntrdPZ8bUxFJ1XaaI8sQZwoLEuiMZUepRRCwL2lPl/61gJ/5A9efmqi8RJHw1ErN/8D\nhtj8A+C/ychEgSzD6e8B/znw3wN/7SR28injfwH+HPDXM2+ct4DPAH8M+Abw9z/AfStRokSJQ2Gv\ndtevf+V20TbK/4at1skbby9y8+4GQz/GtqBV9zh/usGVc01qFZtaxcayqoiCzkCj6jDd9JgRkodr\nW/EGSmnGWRzCo/URf+qHXjL7o+H33l2iVXfpDkNGfryn6+9OSCkKM704MSTiE6+cpjuM6A0jokQV\nguSdyNtdaQoKTXcYZRNOj49V2AtawyhI8BzL7LdQW6+RjbkD/OtvzGPJpycaL3E0HJXc/GlMpeZn\nO53Orq9np9MJ2+32zwF/AvgpPgTkJjPr+1FM/tS/j/H2WcL44/xPnU4n/OD2rkSJEiUOj8nR41sL\nXd68uWLM9na48m70A+497HPnQY/+KCJJzdRTdxAz8pNsW4re0PSaRkFMmk0TKa1YXBkx2/IIwjTL\njzIJ4lXXptVwi2UBXr08zatXprl5dwMpQAszqr2XAd8kdEbGpAWOJZmbqdIdRty4s87K5tiIhLXa\nVbUp1p/423j2CJpVh2Gm1TkKx4mTFAE4tjTj7BmxcSyJFIKphgfA176zxN/4jy8DJysaL3F0CH0E\nGttut33gVzudzl4ZTZPL/T/AX+h0OtUn3L8PFYQQ+ijHs0SJEiVOAjtHj6fqLg9WR7zdWWa9t3V/\n1qq7AIxDc4Ef+TGWFJmJHtn4s0XVs5lueCyuDIgyX5hcSCuEwLYkF+carPV8xkGuJZE4tsSWAtuW\nvHZllp/5YyYj6vZil1/6jZsEUcz373cLn5nHIffsc21Jo+Zy/lSdC3N1btxZZxwkBGFCnD5etwOZ\nKFSYv6UUOLYs3o9Shyc5UoDMsqby07wlBaemKpzJ0scB/vZf/SFs21RzSo3NieHIB/GolRsfmDvE\ncnPZsiVKlChR4ilir9HjN2+uMDdTZWsWyVwb1no+SaKKds9kyKUtJWjN2FdIAeNQEsRpZuBn/mhA\nYqoqa72xIQdZUrhAEEYJIQIh4Nu3Vtgc+PyZH36ZH/6BS8zNVLn3MDwUsQGz245tiNJ0w8N1THxC\nxbWJYuO/s5/PzY7NFAxGKVMNcj2LqbrDRj9k6B9OZaw0qJTC7M9MVGn6o4hmzaXq2TTrLiIjM6WB\n3weLo5Kbt4EvtNvtT3Y6nW/vtUC73f4kprXz5SfctxIlSpQocQAmR4/zVlAUp9x72KM3ikhSTRjF\nhYmd65jJpTQjLEIIk+aNAgGeY2FZknGQGK8XFGmitihS5lWjFNSrDqnSCDRhlGc9aSxhsqU2eiFf\n/OpdLp1pcuVck878hrn4H1BtMVuBRGmsLLTz9HTNtMDilDBO8cMY1zY5UIfkSmidtcSU2d6pqRrv\nL3QZ+HtPOO0FpbeXEaIkpT8KCeOEuZkqv/gr36Y/imjVXa6ca5YtqQ8IRyU3/zvw48CX2u32LwC/\n1Ol0VgDa7fYZ4D/EiI6tbNkSJUqUKHHCyKsC+ejxRj8o0rldx2KjH9AdBqSpITST3XIpBHGW+K0F\n20z+UEZXUqvYDEaxSekOVNFa0Rp0RpKS1OxDNYsiiOIQtFkmVRokxGlKbxjy3p01PnrtFP/stzs4\nUqAmXIJ3YtL3xlSXNL1RxGbfJ4xNNENvGOLYFrZlzPl2GgHuBytrKzmOIIxTLs01ub/cRwRHExpr\nwLaEIXMTrTp3Ikgzj7/IJ6dKgvNscSRy0+l0fqXdbv9vwH+FcQD+O5kOByDX1wjgf+10Or96crtZ\nokSJEi8ucjKzl61/ECXFBRVgeWPE8sZ424j3JMxEkwmPzDmNJcF1LKLEiFCiOKVetbGkJIjMBFTu\nFCwwbagkVYyDBNeWpNqMRuevKIVpTUWRwpKK4Tjm8rkWrmOhtMZSCqWzGSy9XVw8uddaQ8U1bamF\nlSH1ioNGY0mZaYEUnmshMl1QmurCwA90MZWVe+G4jpX9kXiOMShs1lx6w2hbLMNhoLWm4tjUqxaX\nzjSIYsXKxmjbMnn8RWng9+xxZBO/Tqfz19rt9u9gJqF+EMiVVCHwdeDvdzqdXzu5XSxRokSJFxOT\nZCaIEsZBUvjN5J41uWOwHyZ0hybS4KBRa6WBVOPYAikk000PmYmJ6xXHuPuGRosy0/QYjOOsTQWW\nNGJZSwosyxCbndNHWuvCfM+Sgmbd5cHKANex8IME27IK/U6cKtRjKi9+mLKyOca2JKemKqSpplFz\nCMKEMIYzMzXCOGWt66O1QkpjwIcG28q0MSpzPU4UtqVo1ir82Gcu0x9FNKourbrLOEiI4vRweiBM\nBchzLV6+OMPIj3EcSRxvP/B5/EVp4Pfscaz4hYy8/Fq73baBfHh/vdPpHNL/sUSJEiVK7IXJKs1k\n0vf80oAoE9DmKdwrGyOW1sdUXItBRoAOe3EGSBJNtWLhhwkV18KSDq2GRxilRYXkE6+eZuTHvPP9\nVVJlgi/TVNGqe3QHAeMwQWdmdnlrJ9feeK5Ns+bSqjl848Yjrp1v8d54jSQ2mVNSmpWqrsSP9mZk\nuYme0pogTKl6Nh+5NsPDtREbvYCKZ1HxLAbjLLxSg5KK01N1Bn7IyE+wLIpU8CRRzLY8fvwzZmRb\na8033nuEHybcW+odenxKCmjUbEZ+THcYcvlsE0FCNEFwXMcq4i9KYvNscVSH4nvAPwb+UccgwTgV\nlyhRokSJI2BymiZVmnsPe9taTmtdn3GQsLrpE0YJ6/2AesUpWh+TraggND4sUog9s5r2gxEGmwu+\nZQlGQczSmvGw0UpjO4If+YGLXL84zRe/dofBKEJpePPmMsNxyCirdji2RAq9TSccRApLplw516Sf\n6U5adZepukd/FBILhWNLtLaYm6nyYHVIGO8mOFpDEKd4WKz1xjRrHhrTgrJtyXrPCGZsKTh9qo7n\nSvrDmEQpRr7JlrIsURgZJkpx52GP24tdrl+a5vWXT/N2ZwWNdShimLfwlNZM1Su4jsXls00Go4hG\nzdlGbszEWmng90HgqD43WbEPgG8CvwT8s06ns/EU9u1Dh9LnpsSzRDlqejJ4kuN4nHV3tpqAjMSM\nmZupMduqoLTmW1lsQtUz96CP1kf4UYprS2pVG6EFiVJE2fSQa1uMM7O95JDlm1yLYkTETrEvRm8j\n8Fyb118+xU9+7hoA37jxiHtLfd67vZZlNaliO3u9ogAunWnw0ZdPMduq0JnfKC7+SimklDxYGzL2\nY5JEHThEJYB61abqOSitqXo2s02PjUHI5iDAEoIzs1WGfkKSpHSHhozpib6ZMMUdphsu1y9N8+rl\nGR6tj3h/YYOFlfGBxywrNuG5FqemKlw516JVd5lf6jP0YxpVB9exOH+6Xk5LnRyeus/NHwD+MvCX\ngD8M/CHg77Xb7d/AEJ0vlq2pEiWeLvYSlZYnz6PjSY7jrYUuN+8dfd3JVtNGPyiqL0mqsC1Z/P9s\nq0IYp6SpourZ+GFCqnQ2qZQy9o3GBgEVxzLVjShBa3AcSRodMrsJc9VwHZMRlaRGczIcx9iWRGnN\n+wtd3qgs8p/8mY+xuDLgK+88IFW6IDb5dvbb/srmmJk1j1bD3VbVkNIEaCaJMuLnQ5ScNKZK5bnm\n0jXyY/ww4dypGlppuqOQ+4+GVD0bkVexMk1QsY1sHHzoJ9y8t4FjW7TqLuv9w5vRW5kYe+Qn3Ly7\nQaPmMN3wmG54vP7yKaQU/OGPnuOVy+Xv8oPCUaelvg/8LeBvZZEFfxkTWfDnMflMm+12+59h2lbf\nOOmdLVHiRcdehm07gxBLHIzjHsfbi13eeHuRW/e7uI5kLnOmPexnMOlJs7ppqgRaa7rDkNNT1eLx\n6aaH51j0IyNIHRWRAWYCKPQjVKoRUhJhpobAuO+eO1Vn/lH/QOfeHHk2UpSkxTqW1FQ9CymMcd7N\nuxsoZTKaPMdCH0HYk6SKpbURaarpjUI8x6bq2WitGWeZTUJogtC8j8dtWWD0R1FswjqDKCFNNWG0\npXVJUkWUmJF4y5IkarfRn0n9Vigl+N69DaI4ZRw83hCw5lnGG0hr4kSThClhZFpyqVKF0WCurfnu\nvfWS3HyAkMddsdPpfLnT6fwV4BzwM8BvAi3gvwD+Xbvdvnkyu1iiRIkckxfHwzxeYm8c5zjmhGh+\naQBAFCsWVwZs9IMD1wUKTxrIL9BZS6fQyeQGfGbceqrhUq86dIcB3UHIODDVlFbdM/oRzAU6TlIS\npYmzESnPtfBcm6pnHepYaK0Z+vE2MpQqkyc1DmPiRDH0jQngwvKA1e74UM7Ak9sKopRW3aVRdVnv\n+6xsjs1k1zBkMI5wbNvocRpuNsG1z75mf9JU4QcxUWyExmGUZrlXRqQsAFsKZpoerbqz54aUyj4T\nP2IcHNxwiBJFGCviZOs4KQ1hbHK5tNYF2QWKCanjYL8x/hKHx7GmpSaRBUv+c+Cft9vtOeDngf8S\neO1Jt12iRIktTF4cd6IcNT08jnscb9xdL6oGfpgUYZK9YcTrLxvB6F7rTupyGjWH/igyEQCOLAjO\nVMNDZLIC15EIIfBcC0sKGs0q/ZEhGblGx+Q8me3nrSXbNlWDP/GDV/kXv3ub5Y1RYVr3OOxngJek\nkAYJlkypVmzml/qsbIyP/B2Tmb/MyqZPmqVcjoMYkbkYgy6ImyUljmXCKR8HjcnB0onask3OYEmB\nkMakT0pJo+Iy8pNt5C3/V5IYg8LDUIn0MZWwVCkunW0WY/rAsSakypbzyeGJyQ1Au92ewVRv/iPg\nsyexzRIlSmyHJcW2i+MkylHTwyM/jnsRnP2OY06IpDAhk/3MfRYgjFIWVwbUKva2dfML1f1Hg2x5\n014a+QlTDRfPtQpyc/V8CzCmb3MzVRo1h3On6rTqXjEdZQz0RKa/Ma9hDHJNRHWqFJ40I+F/4cde\n4R/8i2/jOfaRx8MnoTPH4TCK+fI7i5yZrbG0NmRkCVRyuI26tkXFteiPIoIowbYkfpgWWVX5MUwt\nDaRF3tV+EhwrIyOWlFQ8UZj3IczouhSC6YZHfxQZUimMKNsEbept29aYibGDlMwHyYEsyxgNTuKo\nE1Jly/lkcWxy0263HeCnMITmTwEO5jtwF/hHGIFxiRIlTgi3F7usdf1M72HGZ/M7xXLU9Gh4/aVT\n2y4kk4/vRN4i2I8QWZYoqi458gtVLhr2w8QELNYdBCIzjFOcmaky1fSouDaNmsNPfu4aL12YQgO/\n/K87jIOkiEbIidVOopIqsCwTfGlbkoXlAX/13/sEv/q7t1jvBXiOhR8dvo201/sPY8V376xTqzhZ\n5MBR1ld0hyaaIU4UoUh2tV2UphAoS7E1kQTbiUXFtWhUTZvJ8yyaVZcgSljJoieU0ngVi5mmcR6+\neLbBvQd9Y3QoJrKxMgdlx5Z4rkUcR4+NgziI/0zVXZp1l5F/uIrLXlN2j2uVluTm6DgyuWm325/D\nEJqfBmYwn30PQ2Z+qdPpfPVE97BEid/HOOwocX6xrLg2F880WN0c82BlSK1i84VPXSpPfkdEfrwe\n1wLIxcPzS/1sdNjDsWWme3EZB6ZVNN2ocPFMw3ifZG2p/EK1umnSabrDkCBK8MOYRs1luuHxseun\naNZd/uyPXN/Wzsq/E3msgnH7lSidZJM+AssS26eVlMbxZFGxcGzJp9pn+M6tNYZ+RNz1SQ5oT02a\n8O3EyE+4/aBHo+oQZa2cA6sd2fbiVEOcIqXI2lL7f9/zn8LOOAYhQGi4OFen4tm4tmRups5gHLGy\nMaZecXBtSZya1O+hH/HShSnGfsLyxpgkUejiGBt25tgWZ2drpt0XmnH6/d7/Qdrsj16b4c/96PUD\n25L7tZ3KlvPJ46gmfreAlzHfzgQjIv4l4Ncy7U2JEiUOgaP21ifv6mZbFWZbFbTWNOtuSWyOiWsX\nprh+aXrPC8ftxS6/+fV73FrYZByYiZyHq0POztbJ0gewLEG14qKB+aUeq5suX/zaHT5yddZckLQm\niBJDajLBqsaMcq/3fDb6AUKI4vV3fie6WayCEIKKZ+EHggQzDr6XUDW/MLfqLkpprl+c4ju31rJR\n64OPx0Gj40mqGYwj1CG2tXN7aapJEm3yrND7tnn2a5/pTFi0vOEjBDRrDp5rMw4SHNuQzTBO8RwL\n2xIIITh3qk5nfhNLZmJtsRXYKTDtrSTVrGeC8IprGSfkrF2W78tBRSpLwh96/TzAtu/Rrfub3Jzf\nKD7PqbrLg9Wt7KmdbaejtkpLPB5HrdxcB97BEJp/kieClyhR4vA4am99v7s6IUR5V3cMHIZYvvH2\nIm93VszxzS7GKk3xg4RLZxt4rplE6g5D/CBBSnj54jTDccw3by5za2GTR+tjNgchSWK8Y8zoMYzD\nFCngm99d5sc+c6kgNpNRC/1RxOqmT7PuEkYp9UqmtVKaYlh64qqrNIzDmOWNEVfONZFS0BtFnJmt\nMgpiahWb0QETQYcRHyt9pI5UARNmabQpxrxPHHkiSGvwwxjHloSxxfsL3aKidv3SFKemqqRK8f5C\nlyhWrHfHzD/qMwoStNbb9l0I0yJb7/pIIahWbVo1h6X1UTbuffj39fKFKXoTGqzbi11+961F3l/Y\nah8DvHlzZVsrOceNu+tcuzB1pFZpiYNxVHLziU6n895T2ZMSJV4QHLW3fhwBbIm9cRhieev+Jt+/\nv8k4MMQxmBh7DpOY793b5PR0FT9MSFJzoXZsi9XNMRv9Ov1RyL2HfYQQOJYgCPWuC7nW0B9F3F7o\nFmRrox+wsjkmjhWOI0lS46PSvjqD1prfe2+JRxtjgnBv/YxWZopqfqnP73zrPv1RVBCjcbB3y2MS\nUpoK0cjfnwQd14A970bpLObBtozR4FGRKkgjRZyENGsuqTLi7u/f32S2FRDGCRu9ANeR3H6QMBxH\nqAmyUvxShCGRGqi5Nkpp/NAIrw9LbBxbcvVsgz/40XPFTcZX3lnkS99a4OGaqdDUK04RnhnFKaub\n423kZqMf0JnfYDCKaNZdLs7V6Y2iclrqBHBUE7+S2JQo8QTYqwqjdKYTeEwVpryrOxnsRyzfu7NF\nLG/Ob+A6JrU62MPPRWnYGATMNDxGvsK1LWxLkqSalY0xq10fIQTNmoMfCob+bmKRXz83BiHv3BJJ\n8gAAIABJREFU3lnju3c2uPuwl7kEG7diKaDqJbx2ZRoNNKouF04LFpcHxIneVUExk1MQxim/8rvv\nM9P0WFgeEsXpY8eYc8SJxjmR+dnd0Nl/NGCRp4ZvkaWdqeIHIVU6q+JYxEnKajemXnUIwpShHxP1\n08IPZ5d+J/vj2hKEBDRxorCynK2DYElBvWJyqHqjmK+884DXLk9z92GPL31rMXOWNtvJp+rWugGu\nYxVERwhRiM3zcM3hOGY4jvns6+d46cJUedPyhHhKX+USJUrshckqzEY/YDWb8nAdi6vnm/ue0A4j\ngC3xeOxFLM1nMM5GsjUffek0w3FMJbub3w9JNgYtpCBKjFuubRlvlSBMiqymqmcz8iMG46QQxhZX\nWGA4jri/1GdhuU8YmUpNqjRBlBpRcZyyvDHGdSyGfkwcpwgh2E1tDMJY8WB1hADWNn2iRKG1Qgp5\nqEDNIHy66Tn5+1doppsVlDJEbnMQmniJIzCcJNW4jml1pVnlZRwktOouyxvjbaPmO2Fbxkuo4lr4\nUYJrZ+7DB5AbxxY4liRJc9NFYyA4/2jAv3zjfaI4RWAE3znBGQUxVc/m4ly9IL6w5VCdt61ylNNR\nJ4OS3JQo8Yzx+kun+M2v39uW6mzs35MiqXgvXL80va8A9kXDcQIrd7b3JrOdXMe0Y7753Uc8Wh8x\nGEVM1R38fVpAYAz7HFsSRYYY1SouFdc2DsGOtWX0p7dM4vKLtwSkNGRjMI7xHJtudoFPlRG1pgpc\nLN67vcYrl6ZpX53hzZvLh6ouaCgM/5SGRB9OBfy0jXELgqWNgDeIDDkR4lDRUtugtPkOCODiXINa\nxabmOWg0yxt5tMXu9WxbmGOSGoFz3XOwLMHmIDyQXKWp3mYwqJRmqu7huRbvL3Y5M1Mnirc0Uvk6\nriOZnary8VdO0xtF2XOCi2cauzQ4pY7uZFCSmxIljognTeO+fmmaWsUuHGrzjKLZVuVQd20v8knv\nuA6u+Wc22d5b2dxKgJ6bqRbtwfWeGd8+NVXj0Uaw7zb9MAEEUgrqmffKYByitWZpfQTaTFTFO1pb\neSq1QNCoOrTqLn6UsNG3CKKoqGDknizjMOHuUp9PvHLamM5ZB49hm/ecvd6BS27HUUnGUaA0CK0R\nwkQyVD2bME5J9mizHQgN9apDs+Zy5VyThxOTSI4tjR5K73YWlkJg25JLc02uXWhx4856Jjh+fK5V\nvv+TSFLF5jDAz4jkxbkGUbyV5D7KtE5Xz7f47Ovniu+qUpovfu3Onjq6erXU0Z0ESnJTosQhcVLW\n6KnSVFyb9tXZov+eo7xr2x+5GHhSo3SQg+ten9nFuTpf/fYSi8tDPNditlVhddPnwcoQx5GM/ITr\nl6ZY6/pU3b0N8GwLPNdGCphuVnBsiWNLtAbPsemPTF6RjgyZkWJitFibKlKtYnPhtBlX7g1DhpmA\nOSc1AuNfk2Iu0CubPo4tqboOUXxwlSHHUUmDxrRf4kM6EB8VShny0R9GDEchqT4GscnQqDmcP11H\nCFFoWgSCWsXBDxLC2CSni8K4T2BJgRSC2SmPqYbH5bMN3n1//VjvN1Vm22GcMt3wGPlJMeEGJlbj\nxz5ziR//zOVt68kdRBu2WqRzMzV+/Su3y7bzE6IkNyVKHAInaY0+2R6ZJDZQTj89Drmh3mGrXXt9\nZr/59XsAvHShRRjF9EcxS2sjWnWXimcRx4ow07W0r84yN13l//vuMt2hIRNSmlDHRtXEJ0w3PH7g\ntTk69zdNmnejwjhMUMpUbXQ2qZNXYqQwGVC2LQmilHdvr5Mqlek9tvZdCrO+JSVk/04ShecYUpB7\ntDwtGF3J/qZ2J4FUG7HvYTx49oLnWnzqtTOFOHeq4bK66ZsWUNNjMcuvEplaOVEaS2q0ZeHYkvdu\nr/PebVO18cPk2O81STWWhpcvtJhqVuiPIl69Mk2z5vCxl08/ts0MFBEdJnrDfKfL6IUnR0luSpQ4\nBE7aGr2cfjoabt3f5Nb9bvH/Uay2aZb2qnbt9ZkZx2DNbKvCmdk6S+urJKliZXNMxbWxLMGZmSqr\nmz6zrQrTrQp/6KNneff9NTxXMtOq0h9GVDyryHnqzG+wsDzAj1I8xzahkBJUTEFscqQa0liZKIJU\nFSZ+uyafdD5BpLGlpObZpmrjObhORHRAsOST42ji3qNt2XjMPMnmpTBEc7MfMDtlvGMaNYc//fmX\n+dp3HvD1d5eoVRySNCUI02wayhzTJFUmJ0wK4sQQuCfRGklhJq+mmkY7E0YpxjPw4JuUXEf3a19+\nf5f2Bkpx8ZOgJDclShyAp2GNXk4/HYxJbVM+nh3t0K+sbo65dLaxp+X9XiP3+fpaa6abHrYlGCRm\ndFdrM1q8sunTrDrcfdhjOI5p1l0+cm2WM7M1hBB05jeIYoUfJnSHIaMgxo8USaJY7/sIBK5tFa7E\neyFRKiMw+7dktDZuxDITwG70A6MHyoiPNFPMT0UEPA6PWU45JJ50l03rTBrH34xE5H4xD1eH1Dyb\n2pTDaneMQJCkEVm+KHGiEZhS2kkQOM+1mG1WmF/qYVsWrmPS2Q9bfUmV3tdbqGxTHx8luSlR4gA8\nLRO9F3H66TBi7J06mfYVE2cwN1PdVq3xw4T1Xszco+EujcJen5nMdBlgdE5mLwwRiUhxbIsoSfHD\nhM1+wOmZGh+7fqpoe2wOQmZbFeZmajxYGbLW8wuNh0JjWdnklIB6xca25Lb8p+3H4fHHSWfLpEoR\np7FJBBdm1DxJdXGhfjG+NXsjN96bX+pnPkOKzv1NFpeHjIMY25LEiSJO0sJE0MqckfOJrSeFbWXf\nn0TxcHXE6ZkqF8/MbFvmoOqLlQnSR3v4IZVt6uOjJDclSuyBnRfhp9lGehFOXocVY0/qZIx76yZf\n/84SUsL5040sNNSnl1VMphses1N7axQmP7NchDzpKaK0xrUlm0mKFKIQgaZKYQnJnQddWnW3yPIK\nooRGzUxFRVHCnYddBAIhoWrbRRUmihMsSzLd9Fjr+k9cWUmVZugnOLZJH9dZueGoxncfVljSiJAn\n36vAiKy7wwDHtqh5NkII7FihtCZJNVESY0u55Q6td1dqjjMZ1qzZNKouSaqIEkWaKsaBKibgduJx\n1Zf8d7GwPCjExJPtqbJNfXyU5KZEiQnkJ5v+KKJRc/h4Jgh80dtITzL+fhQxdq6TmfSggS2NzcUz\nDdpXZ+jMbxhjtDONXevn27x+aZrFlQFf+84S/VFIq+7x+U+c59KZZiZOHhDGCksIEpWb8oGlJJYt\nUYptdvkV1+anPv8yAL/+1dt8b36TJFXZhTQlTTQaTaPq8IMfO8/95QFrXf9Yx2wvpKk20dgvGPJM\nqJyISGFaUkKacfKKa+M6xiU6hyUFKJF3rMy0lBSoHezmOEfTtSVTDY/Vro9rW2Z0jq2Ih1yvlWO/\n6svk7yJfPk+Rv3Ku+UKdX54GSnJTokSGPAl6fqlPbxiiga+985Cf+uGX+MKnL7+QbaSTGH8/rBh7\nUieTn+Rz2Jbkwlyd/ihiuukBHGiAdnuxy7u31wkzD5IwSnj3ttmXimszN11hHMR0hwFxrPBcScW1\n8UlwLIllCaJYFeP6tapdBD6O/YSphsfyxpgwSlFKk2TjThrTLkHrIrDyJLQdyhjivnDQW4UXwJAU\nS5rR+zTV1KsOvWFIreLgOTITaGetu6zlk6SKOFGGGLmSON4eyyCylpUQZiptv8NsScHZU3VeuTRF\ndxiSphrLEtQrLrDlRjxp8bBf9WXn7yKvENarNn/2R64f93CVyFCSmxIlMrzxtkny7U8k/K73Ar74\n1btcOtMsLsTHJTZPav73rHES4+9HEWPnOpn+KNolHHYdyampKqemqvz0H32N3/j63W3bzdtOjZpT\nXJjeeHuxqP4IRFH9WVobcv50gwerI2xLMtP0eLQ+ZhwmpEqbu3Gg5pmKwOYgZGVjzJnZGv/yy+/z\n+kunadQcrp5vGTt9KUgzbY0AtBa8d3uNimtzarqGvzwgfZoz1S8YchfnOBHMTVd46cIU3/zuI5Oa\nLo0uSWBIjedI6lWXIEroj6KicmNJSZoRntx3qFlzmW15dIcRG71gT4JT9Sxa9Qr1qseF0w3jo8P2\ndlSj5iKy7+J+NwOP+12M/OSFuoF6WijJTYkSmJPN/NIgS082RXCVZfJ0h+G2YMWj4qTM/541TmL8\nfaewNychsHe5PtfJ7JyMmpupFevYtiyWm8znSlLFhdN1fvlfd6hVbW7e3djWqgBTVVnZDIx/TAbP\nsal6NkGYmH0TJrrg4XrCatfn3lKXmufyYHXIt24+4je+ereoGk3VXRwrZjMTrTrZfgdRgm1JWnUX\n1xH4YUluTgo6UwPPND3On27Qmd9g5MfEqRHm2LZEa53FT9ggYoQwpMMPYoIo3VZZIWtz1asOWpvP\n3nUkYbxd9W1JwZmZGj/8yfP0RhGea/FwbThRvXGYarj8zB97bVfw5c4bm6c1pFBiCyW5KVEiw8iP\n6I+jIrwwv6OrehbDcXSsu6lb9zf55s3l4v8/LOZcJzn+nmdpTYaEzs1U+ezr53ad9PNjEkQJt+53\nC7O+vBX1kWuniuUWVwbFWHaSpsRJ5uLrWCjtFa2K3JMGzB22lYVd5j41K5tj0lTjOBZCQBSl2JbA\nyiZwxr4iiIKiL6JcuPuwz1o3YBzEWZK3RmlNvG38O2Xkx9j24UIrSxweqdKMg5jbi5t0B1FBmlOt\nUUohpXGLjhJDNDXw6qVpRq7Fw/UxKtVYlhnjzh3D/TAhjExmuOtYRqOjtIlxkALPsfn8Jy/whU9f\n5ne+dZ/BKKJecUx+WGr254c+cX7b73pSw9equ9tubEqvq6eLktyUKAHce9gjjBV+kGzrxZuTqAm0\nPAqxyU9qb95cBsyUzqQ+5Hk353o6d5ZFfCT9Ucgbby/yjRuPdlWzcm3T+wtdvvyOEf7OL/VxbDOS\nffOeEVv2RlERYfH9+92i0rO6OWa66eG5cps5Xz1L6X7tygzdYUh/GNEfhVn2kC4M+KqeGeP2oyQL\nsNTEqTHoy/U0Uggc2+hygijeN4FaaSOGLu/DTxZKQX8YAlmdVZgpMmPSB1IppATPcUizZda6xr3Y\nkiBtkwl2dtbouPqjEKUNyalXLEZBQsU13wPLEpxqVbh0tsnQj/n1r9zmzZvLDP0sYkObtumVc00q\n3tYlNdfwTZL6+48G/OTnrpVDCs8AJbkpUQKjz7Ck2HNsV2u4tdjd/cQ+mMxAirLSdq79yAnOh8Gc\n66TuLG/cXTduv00PAWwOQh6sDAmjAe2rM/tWs4Qwwl/HlvSGIUmqWesG2cUoopv5zpjxa0Ns/DBh\nrRfTHYYMxqaKYlmiuLOuV03rwCznZ+TFmKD4YZL5okRFNUlaAo2JRojiFJVdQC3LjI4bsbJZ5nEo\nqzYnC61hMgpq5yegNOjUTFMJIai4FnGqCGNDTFMMaV3rjo2pnxA4lqDiGtF4nhSepCbr61I2lXfr\nfhfHtugNo8J4r1l3qHkOg1HM/UeD4nc9qfkC8/15sDLkjbcXdxH55/1c8GFESW5KvPDI9TZpurel\nvRAw9hOiKMV1rQO3l2tVjGmcLAjO5IjoSfTV9xMon5Rw+STuLFOls9yccZEJNQ6MHiWKt2sfdlaz\nfvetRW7eW2cxu0DYUgA2dx/2aNVd+qOI2ValMOfrDUP6owjLEvhBUjw+3fCwpGAUxCyuDIo08CBM\niJKtqsqkb4xKNVLkFQHzeDLBfJNUMxiH2/KgSjw7iB3uwnuRRw3F5NQoMHocDVQ8K2tfQZKmWFJg\nWYKqa9OsOdQqDpuDkOmmC9oEpM5OVenMb2aVHyNazuEHCTXP+B/loub8nLIX5pcGu8hMSWxOHiW5\nKfFCYjcB0IzD/e3yc5+Mw2x3spWTu9kC2y7mT9JXv73Y5d07a4z9ZBvheBrC5b3uLI9Cnu497GVl\necMCwjhlvRfQqru06u6eieh3H/b41d+9xVvfWyn0T2AuTLZM8Fy7MDzLj+fcTJWHa+Y41zybQfYZ\nTDc8ahWbueka37z5iCDMDPvidJtgdOfF0Uw9mRwiKfY2e0vS45nAlXhyHHb4LA8XtSyRuRJrgm0h\nmcYL53SjiudadIchvVFkLAIGARXP5tXL00V0x8UzDZTWeI5VmD4m6ZbOp1V3UQUJ3jdY43hvusSR\nUJKbEi8U9iMAV861WFgeIsXurB4NnJmtYdtyz21OYqdWZcucawwImjtEhUfFG28t8KVvLW4T5g7H\npiLxYHVULHfSwuXcN+ao5OnG3fVtsQkCY6SWV08685uFHqlRc/jKO4t88at3uf2gS5zsvgjEqSYN\nYhaWB3z6D5zhYy+f5sbddZTWTDeM6DiPPfAci6pn0xtGPFofMxhHxsckzXxoMux5qRFb4ZWuI1Hx\n1p3/JMrL1AeDwx73LZqxlbqe+yDmpn62ZdFquEWbUWmdVXMkQZjwvXsbjIOYMxO6uamG8bXpDkPi\nOGVjEBZEWmPOA1fPt7aFvea4er61ZxbafjcMHzYLiecFJbkp8cLgcb4tP/bpS7zz/RUGY4sg2io5\nSwG1is1f/InXDv06O7UquTnXH/7oOV65fHyicXuxy5e+tWCM5dBFDx/g3lKfa+dbu9Y5KeHyUT1v\nokRhZeGBk+6rvUwEaluSimdtew8X5+p86VsL3HvU35PY5DAhkiF3Fnt87OXT/NkfuY5SmlbdZTiO\n0VoXup6VjTG9UUiqjCW/bYEfxsUd/X7I7+wFYNsWUayKi2FpWfPhggC0Mr9lNCi2XI7TVBNGCfcf\nDQjjJBvrlni2mZQyQZuKjX5Iveqy0Q+KfLHeMEIKOD1TzawEUm7e3eAXf+XbXDnX5PrFKcZBsq0l\nOzdT4wufulQQlsfdMHxYLSSeF5TkpsQLg8f5trz+0inOn64TRGZ8NxeoTjU8/sQPXuULn7586Nd5\nWlMQ791ZpzeMGPoRSlFMAK1sjoknnHQncVLC5cN63rzx1gJf+84Sg1FEs+5ScS3OnaoXBC+PTUhS\nU1nJT/q1ik13aETCQbi39mkSQsBG399GsHJSKYRgtlVhaW3E5iBA6a279iTVW1lDh4DGOBvn+o0S\nHz5oMrI68fEpKAz8hBAEUVJ8LwQQxClaGxJuSUEYJfRHIRXXolFz2OgH+GFMlKSsbvpIKbAtyXTD\nY3XTZ7rp0R9FfPz6KXqjJoNRRKPmMt1wuXF3nW/ceEQQJYyDZNuQweQNxJMaaL7oKMlNiRcCe/m2\n5N4Yw3HMe3fWuXZ+ilbdK8iCYwuuXZjip3+ifeTXO+kpiFRpbtxZLzxZhNA4tp2NMcPcTHUXsYGT\nEy4fxvPmjbcW+K2vzxfPDUYRKxsJQZRy7Xxr2/TY1fMtM+mUETKlzXh4EO2ve8qRW+UnKWitC4KV\nH++b8xsMxzGrm2NzTHbmCR2RoyTJQbNQJT5s0JqiMgMiIydGCKy0Ksiw0gpbWliWRCDoDkM+cm2W\nzUFA1XOyCqPR60khWO8FrPV8Hq4OMi1YjT/+2Storbn/qM9bXb8Ix5xf6he/h502EfvhebeQeJ5Q\nkpsSLwQmtTDG1XarVHzlXLNYLq8wTFZBnoSgnNQUxL2HPRaWB6RKmbtKBUKa0EDPtfjhT17YprnJ\ncRKGYIf1vPnad5Z2PV/1bEZ+VKzfzITE+clcCONd0x9FBGHCyN+bROXI+ZsJSjTrD8cxtxY2uXlv\nozBL++Qrc/zOmwuZVf8+2+Jw2o2S2Pz+gyD7bWrTonJtiWNb+GFCkqoim0olGq1TtA4Z+TFSCv7+\nL7+NLSVrPR8pDCnSCvwoMW2vIsJDs7A84J/+dodmzS3y6nrDiOuXpvacogQzcSVgz5uVD4OFxPOC\nktyU+FDhuOK6VOnCKXdn2rQf5l4Y5udwUETAB4H37qwTxSlhpIrRZK2Mr0vVs/iRH7jE3Ye9p9aj\n36kjyo9RTp6iRDGYyOSahFLwpz73ElIK7j7sFdtRWtPNtDEXzzRo1V1uLWw+dj+KgENgME7ozG8y\n1XD5V783z8rmmP4wIogTPNuMhj+uBSVl5odSspcXDvlHbtsmaNOMeEuqnnEqnrSFUEqbKTupsG1J\nf2h8kJTSJvLBtRAS0siktkshySNcwjglShRJqrKKq6A/irj/aECtYhPFapclQqtuxMplNMOToSQ3\nJT4UOK64bud6+ZTR5LTRbKtCECW7KjpzMzU++/o54IOdWEiVZuTHjIM8pM/8J7+7G47NHeXTaIXl\n7zk/1m+8vZj5d2iuTgiYXVvSrLv0R+G2EEGAZt0tJs2uX5rm3lKfb9x4xGAUMfRjzp+uA7CStZH2\n6CQB4FhgSXMhaTU8qp5NFKd05jcIY0UYJcYNWJiLVrJfySaDLonNC4uiMiJEQXLD0KTB16sOji0Z\n+jFW1jIFSFNN1TPfK9uyEZgKYpIqHEsSC4UQEscW5HVBrTVpqhmM46IF5lgmr+7quRYPVoe4jrWt\nSpPfMORGoHKP50ocjJLclHjucdx06p3r9UcRq5s+F880mGl6204o4yDJrnT5Y+bvxZXBBz6xYElB\ntWITJ+YOL99LIQRSCHNnmKiCQDyO2ByGpO0khB+5dopXsymvimvz2pXp4thNHt+Ka/H+gr8t6gDg\ncx87Dxix8W9/Y56ltTGeK7k4Z1xfVzbGrGyMqXo29apDGCviOEVKipaSFNCse5yaqmBJY4nvOhLX\nsbi1sEmcqG0j/FGi9u0n5e0oOTH3n+t+SrLzYkBjBMWOJWjUXZo1l8E4yqbqVCEmBiALxlQK0lTh\nuTagkdIQGQebuZkK4yBhvRcUkQ21isPQN20k2xa4tvHGiVSKJWGm5UE2jQns8qwKooQ7i5tYls3V\n802+8KlLpd7mCCjJTYnnHsdNp965Xu5Yu7o53tbjBkN8rp1vMTtVLUrEG/2AL31rgfbVWeBkJhaO\n6yo8XfeKyQ4ygoPWOK5F1bMem0AMh698TRLC9V5AZ36Dr39niVevbJGbVGvsCWL4xtuLVFybc6fM\ntNnC8iBzaoVLZ5o8WBvy9/7Jm9x/NGAUmFJ7GCnuPOhTr9qEUYrG6HNqnk1fRihboJXGtgyBm256\nnJ6q0Gp4pj2XTbPdW+oTZVMvkyhGuTMmkz9tSbCkJE2Vca/NwzBLVvNCIlWa65emuHquxeYg5N5S\nj4erI0Bnnlfme5F/V6JEYVmKesXDc8FzTPDm5bMtahWbR+ujTDOTBbUKgSXBsSS2JUksRRil+BHM\nPxrw+U+c5wufvlxkk+Xj4f/n/3uD+Ud9M9jgmGrRj/zApQ/0OH3YvHZKclPiucZx06n3W29upsri\n8mC7YFjros8NW0K+3Fl354j1USYWDvKzuL3Y5b0764z8x5OOgR9xarrC2maAzlpSljQtnFcvzzzW\nZO8ola8bd9fZ6AfML/VZ7wVFFebeUj87HglaCzxXcvlsi2vnW9xb6tO+MoMQgmvnzWPr3TH3l4f0\nhiErm2MWV4ZFtam4IwbGQYzW5thqNLWKg+NI4iQFIfAcC9ex0NpMpPTHMdMNjyA0TsfL6+PHCn51\nJhjNuYupBCkQYtto936tsJ3wHLnN2bjE84H8Mz4qRc09bFr1kMWVAb1hZEJTw9iMirM1Rp6fAmxL\nEsYpr1ye5vLZBj/08Qu8dGGq+A2a1m0fpaFeMW7ZpoITIYRpZc00Pa6ea/JgdcQbby3QHUbFOeBr\n337AvYdb0Q1hlHLz3jp/9x9/k5/64ZefafX4w+y1U5KbEs81jptOvdd6RlPjm9yXRwNadZcr50zC\ndP4DzpHbrbuOPJZ3zORJYT8/ize/t8yNO+vbND75PkyeQHKi9olX5njv9hob/YAkVSjAsySfbp/h\n9mKXr737EFvKba8Be1e+1MQI9eTr3H804MHKkG5mtpemmv4oYjA2/joCqFVcwkjxvXsbPFwbEkUp\nYkfy+f3lIcsbYzxHEqeKcRBjSVn4geTQWjDb8hgFCQLTapqqu8SxQkhwbYsoSQkjI56eblQYhzGD\nUWzadPt+AlvYSVpSZYIW866UlIZ0pQcY++XHqMTzB9NmZN/JuP2gNCwsD9jsBwWBztPAw3h7RVBr\nc16pVx3QsLQ2olV3i9/XZNL3e1Nr3Li9ThiZuI/8FFJUCpUxmuyPIr7yzgOmGx6uIzk9XeX2Yg+R\njacrrQvt2EYvYDCKnpnfzXHlAM8LSnJT4rnHcdOpJ9fb6AfFlNSkx8rkncjka+QtrLmZ6q7tHjSx\nsPOkML80KEwB84v/Rj/gxp31IjIgilWxfztJhyWNydjq5hiBIQeuLalVTML1v3v3Ifd+e0CSKDzX\n4vLZZuFWnGdQ5dgpmv7ItVlevTxTvE5/FKHROy70ms2+GWNNlSZKAhzbAm1OuBfn6tuchqebHqtd\nnyBKiBIzJqsUKKWwrVxoaQiF50quXZgyr6IUq70AP0wLwXQYpYbkuBZRlJKkCis1Qs1cYH0Q8nTn\nSUyqq1zbVIYEHOhcnKdEH4XiWMe46JY4GrTeHZtyWARhglaKiucgMLqaMEq2fc756LgUgotzDYa+\nmQycaXr7mu8trAyRUhJHEVIIlDDf+zAyE1Sd+Q2CMCFJNbrhEsWKhZUBqdLF66UTyazGjFJhWdYz\n8bs5rhzgeUFJbko89ziu42/+/Lt31ujM+0V1ZNJj5b0769vuuCZf44/8wUvH8o6ZPCnkFSBgm9Zn\nZWOUaU30tumifJnJytDtxS7jwEwCJami4tpobVo4rmPx/kKXcZhS84x+5f0Fk2dz7XyLsZ9QrzqM\n/HgbwTMQfPO7y0hhJq3SLMJgkCVrm5NwShSnxKnO9Cpmn4IwwbElnutw+WyTpbVxtv/GndUPE5Ta\nIhCWFMSpMiGDWmcRF4Kr52f4+PVTvPW9Fb57byNrXRkSuDkIcB2JY0tAEJIQpym9zcSM4SaHYwz7\nOQvnD8dxSq3qYEmBHyYHtp2Oeg0tic3xcRCRnHz+SWpqcaJROsa1LcZhQrzDJNu0pzQ+4W6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TxXt6CWVwe6WgK4eUq0EERxSqcf6jBLpbbcpV1b7uJkbr9p1p7JNSgl3ylCJPPjWbrd4fU3l+kN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\ng1YN6QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c4095f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pal = sns.color_palette(\"muted\")\n",
    "\n",
    "x_col = \"energy_pa\"\n",
    "y_col = \"volume_pa\"\n",
    "\n",
    "\n",
    "# Make plot\n",
    "g = sns.lmplot(x=x_col, y=y_col, data=df, fit_reg=False,\n",
    "               palette=df['bandgap'].apply(lambda x: get_plot_color(x)), size=8, scatter_kws={\"s\": 50, \n",
    "                                                 \"alpha\": 0.5})\n",
    "\n",
    "# Set axis labels\n",
    "g.set_axis_labels(x_col,y_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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//hbttkkg4MPjSZBKWYRCIQzDIBAIsLi4SDQaxe/3o+s6Xq+XgYEBxsbGWFlZ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\nIAhCxZCkIgiCIFQMSSqCIAhCxfj/gbMFYN5A3uUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118f58c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.context('fivethirtyeight')\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "def get_plot_color(property):\n",
    "    if np.abs(property) == 0:\n",
    "        return \"white\"\n",
    "    else:\n",
    "        return \"blue\"\n",
    "\n",
    "ax.scatter(df[x_col], df[y_col], s=30, c=df['bandgap'].apply(lambda x: get_plot_color(x)), alpha=0.2 )\n",
    "sns.despine()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# JANAF Example\n",
    "* http://kinetics.nist.gov/janaf/\n",
    "* e.g., Search Na2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_janaf_vector(data, index, fields=['composition#comp','http://kinetics.nist.gov/janaf#Cp','http://kinetics.nist.gov/janaf#T']):\n",
    "    result = []\n",
    "    for key in data:\n",
    "        for field in fields:\n",
    "            result.append(data[key]['content'].get(field, None))\n",
    "\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "n_records = 30\n",
    "offset=10\n",
    "\n",
    "vectors = []\n",
    "\n",
    "for i in range(1):\n",
    "    params = {\n",
    "        'q': \"JANAF\",\n",
    "        #'highlight': args.highlight,\n",
    "        #'resource_type': args.resource_type,\n",
    "        'count': n_records,\n",
    "        'from': n_records*i+offset,\n",
    "        #'stats': args.stats,\n",
    "        #'facets': args.facets,\n",
    "        #'filters': args.filters,\n",
    "        #'boost': args.boost\n",
    "    }\n",
    "    \n",
    "    janaf_vectors = []\n",
    "    r = client.search(**params)\n",
    "    for result in r.data['gmeta']:\n",
    "        janaf_vectors.append(get_janaf_vector(result, 2))\n",
    "\n",
    "df_janaf = pd.DataFrame(janaf_vectors, columns=[\"Composition\", \"Cp\",\"T\"])\n",
    "composition,Cp,T = df_janaf.ix[1]\n",
    "df_t = pd.DataFrame({\"Cp\":Cp, \"T\":T})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Composition</th>\n",
       "      <th>Cp</th>\n",
       "      <th>T</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AlOH+</td>\n",
       "      <td>[33.535, 33.616, 35.837, 37.986, 39.947, 41.68...</td>\n",
       "      <td>[298.15, 300.0, 350.0, 400.0, 450.0, 500.0, 60...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AlOH-</td>\n",
       "      <td>[36.521, 36.578, 38.106, 39.556, 40.861, 42.00...</td>\n",
       "      <td>[298.15, 300.0, 350.0, 400.0, 450.0, 500.0, 60...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OAlOH</td>\n",
       "      <td>[0.0, 34.495, 42.414, 46.534, 50.137, 50.267, ...</td>\n",
       "      <td>[0.0, 100.0, 200.0, 250.0, 298.15, 300.0, 350....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LiAlH4</td>\n",
       "      <td>[86.4, 86.944, 93.722, 101.253, 106.901, 111.2...</td>\n",
       "      <td>[298.15, 300.0, 400.0, 500.0, 600.0, 700.0, 80...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AlI</td>\n",
       "      <td>[0.0, 31.012, 34.703, 35.586, 36.127, 36.144, ...</td>\n",
       "      <td>[0.0, 100.0, 200.0, 250.0, 298.15, 300.0, 350....</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Composition                                                 Cp  \\\n",
       "0       AlOH+  [33.535, 33.616, 35.837, 37.986, 39.947, 41.68...   \n",
       "1       AlOH-  [36.521, 36.578, 38.106, 39.556, 40.861, 42.00...   \n",
       "2       OAlOH  [0.0, 34.495, 42.414, 46.534, 50.137, 50.267, ...   \n",
       "3      LiAlH4  [86.4, 86.944, 93.722, 101.253, 106.901, 111.2...   \n",
       "4         AlI  [0.0, 31.012, 34.703, 35.586, 36.127, 36.144, ...   \n",
       "\n",
       "                                                   T  \n",
       "0  [298.15, 300.0, 350.0, 400.0, 450.0, 500.0, 60...  \n",
       "1  [298.15, 300.0, 350.0, 400.0, 450.0, 500.0, 60...  \n",
       "2  [0.0, 100.0, 200.0, 250.0, 298.15, 300.0, 350....  \n",
       "3  [298.15, 300.0, 400.0, 500.0, 600.0, 700.0, 80...  \n",
       "4  [0.0, 100.0, 200.0, 250.0, 298.15, 300.0, 350....  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_janaf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Make Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x118652fd0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Tu3dNNqbtfnIKt6S54JgbSQPRaWXh5UuXdAw4y5cu4dB7rODQezhAWNLg2XIj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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1183e5c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pal = sns.color_palette(\"muted\")\n",
    "\n",
    "g = sns.lmplot(x='T', y='Cp', data=df_t, fit_reg=False,\n",
    "               palette=pal, size=8, scatter_kws={\"s\": 50, \"alpha\": 0.5})\n",
    "g.ax.set_title('%s \\n Max: %s | Min %s'%(composition, np.max(Cp), np.min(Cp)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Ab Initio Solute-Solvent Database Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "params = {\n",
    "        'q': \"dane\",\n",
    "        'count': 10,\n",
    "        'from': 0\n",
    "    }\n",
    "    \n",
    "r = client.search(**params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Keys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['_#moments_of_inertia', '_#reciprocal_cell', '_#TESTING', '_#masses', '_#angular_momentum', '_#chemical_symbols', '_#number_of_atoms', '_#potential_energy', '_#positions', '_#total_energy', '_#volume', '_#initial_charges', '_#pbc', '_#cell', '_#all_distances', '_#forces_raw', '_#temperature', '_#chemical_formula', '_#momenta', '_#kinetic_energy', '_#celldisp', '_#initial_magnetic_moments', '_#cell_lengths_and_angles', '_#scaled_positions', '_#center_of_mass', '_#forces', '_#dirs', '_#tags', '_#atomic_numbers'])\n"
     ]
    }
   ],
   "source": [
    "for key in r.data['gmeta'][0]:\n",
    "    print(r.data['gmeta'][0][key]['content'].keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "    \"globus://82f1b5c6-6e9b-11e5-ba47-22000b92c6ec/published/publication_164/data/BCC_solute_FeAg_20160524T091201/defect_vac1b_opt\": {\n",
      "        \"content\": {\n",
      "            \"_#TESTING\": \"dane_morgan_test1\",\n",
      "            \"_#all_distances\": [\n",
      "                [\n",
      "                    0.0,\n",
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      "                    0.1670720378018154,\n",
      "                    0.1670720378018154\n",
      "                ],\n",
      "                [\n",
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      "                    0.16639828423707598,\n",
      "                    0.4996071145078342\n",
      "                ],\n",
      "                [\n",
      "                    0.8350986972409439,\n",
      "                    0.1667551851638523,\n",
      "                    0.8350986972409439\n",
      "                ],\n",
      "                [\n",
      "                    0.8342211685595962,\n",
      "                    0.4996071145078342,\n",
      "                    0.16639828423707598\n",
      "                ],\n",
      "                [\n",
      "                    0.8324590438518162,\n",
      "                    0.4997343267193584,\n",
      "                    0.4997343267193584\n",
      "                ],\n",
      "                [\n",
      "                    0.8333777987128245,\n",
      "                    0.5002278629844386,\n",
      "                    0.8333777987128245\n",
      "                ],\n",
      "                [\n",
      "                    0.8350986972409439,\n",
      "                    0.8350986972409439,\n",
      "                    0.1667551851638523\n",
      "                ],\n",
      "                [\n",
      "                    0.8333777987128245,\n",
      "                    0.8333777987128245,\n",
      "                    0.5002278629844386\n",
      "                ],\n",
      "                [\n",
      "                    0.8334720299806202,\n",
      "                    0.8334720299806202,\n",
      "                    0.8334720299806202\n",
      "                ],\n",
      "                [\n",
      "                    0.31944988728173535,\n",
      "                    0.31944988728173535,\n",
      "                    0.31944988728173535\n",
      "                ]\n",
      "            ],\n",
      "            \"_#tags\": [\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
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      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
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      "                0,\n",
      "                0,\n",
      "                0,\n",
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      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
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      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
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      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0,\n",
      "                0\n",
      "            ],\n",
      "            \"_#temperature\": 0.0,\n",
      "            \"_#total_energy\": -428.52955291,\n",
      "            \"_#volume\": 611.9062067444503\n",
      "        },\n",
      "        \"mimetype\": \"application/json\"\n",
      "    }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "print(json.dumps(r.data['gmeta'][1], sort_keys=True, indent=4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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   "language": "python",
   "name": "python3"
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  "language_info": {
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    "name": "ipython",
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   "file_extension": ".py",
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