Tutorial_8 - A very simple example for tensorboard.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 例1 - 在 tensorboard 中记录 tensor 的变化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created log_dir path\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "config  = tf.ConfigProto()\n",
    "config.gpu_options.allow_growth = True\n",
    "sess = tf.Session(config=config)\n",
    "import os\n",
    "import shutil\n",
    "\n",
    "\"\"\"TensorBoard 简单例子。\n",
    "tf.summary.scalar('var_name', var)        # 记录标量的变化\n",
    "tf.summary.histogram('vec_name', vec)     # 记录向量或者矩阵，tensor的数值分布变化。\n",
    "\n",
    "merged = tf.summary.merge_all()           # 把所有的记录并把他们写到 log_dir 中\n",
    "train_writer = tf.summary.FileWriter(log_dir + '/add_example', sess.graph)  # 保存位置\n",
    "\n",
    "运行完后，在命令行中输入 tensorboard --logdir=log_dir_path(你保存到log路径)\n",
    "\"\"\"\n",
    "\n",
    "log_dir = 'summary/graph/'\n",
    "if os.path.exists(log_dir):   # 删掉以前的summary，以免重合\n",
    "    shutil.rmtree(log_dir)\n",
    "os.makedirs(log_dir)\n",
    "print 'created log_dir path'\n",
    "\n",
    "with tf.name_scope('add_example'):\n",
    "    a = tf.Variable(tf.truncated_normal([100,1], mean=0.5, stddev=0.5), name='var_a')\n",
    "    tf.summary.histogram('a_hist', a)\n",
    "    b = tf.Variable(tf.truncated_normal([100,1], mean=-0.5, stddev=1.0), name='var_b')\n",
    "    tf.summary.histogram('b_hist', b)\n",
    "    increase_b = tf.assign(b, b + 0.2)\n",
    "    c = tf.add(a, b)\n",
    "    tf.summary.histogram('c_hist', c)\n",
    "    c_mean = tf.reduce_mean(c)\n",
    "    tf.summary.scalar('c_mean', c_mean)\n",
    "merged = tf.summary.merge_all()\n",
    "writer = tf.summary.FileWriter(log_dir+'add_example', sess.graph)\n",
    "\n",
    "\n",
    "sess.run(tf.global_variables_initializer())\n",
    "for step in xrange(500):\n",
    "    sess.run([merged, increase_b])    # 每步改变一次 b 的值\n",
    "    summary = sess.run(merged)\n",
    "    writer.add_summary(summary, step)\n",
    "writer.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 例2： 分 train 和 test 两部分进行记录。\n",
    "每隔10个step记录一次test结果。一般在网络训练过程中，我们都会隔一段时间跑一次 valid。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "created log_dir path\n",
      "END!\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "import os\n",
    "import shutil\n",
    "import numpy as np\n",
    "config  = tf.ConfigProto()\n",
    "config.gpu_options.allow_growth = True\n",
    "sess = tf.Session(config=config)\n",
    "\n",
    "\"\"\"TensorBoard 简单例子。\n",
    "tf.summary.scalar('var_name', var)        # 记录标量的变化\n",
    "tf.summary.histogram('vec_name', vec)     # 记录向量或者矩阵，tensor的数值分布变化。\n",
    "\n",
    "merged = tf.summary.merge_all()           # 把所有的记录并把他们写到 log_dir 中\n",
    "train_writer = tf.summary.FileWriter(log_dir + '/train', sess.graph)  # 保存位置\n",
    "test_writer = tf.summary.FileWriter(log_dir + '/test', sess.graph)\n",
    "运行完后，在命令行中输入 tensorboard --logdir=log_dir_path(你保存到log路径)\n",
    "\"\"\"\n",
    "\n",
    "log_dir = 'summary/graph2/'\n",
    "if os.path.exists(log_dir):   # 删掉以前的summary，以免重合\n",
    "    shutil.rmtree(log_dir)\n",
    "os.makedirs(log_dir)\n",
    "print 'created log_dir path'\n",
    "\n",
    "a = tf.placeholder(dtype=tf.float32, shape=[100,1], name='a')\n",
    "\n",
    "with tf.name_scope('add_example'):\n",
    "    b = tf.Variable(tf.truncated_normal([100,1], mean=-0.5, stddev=1.0), name='var_b')\n",
    "    tf.summary.histogram('b_hist', b)\n",
    "    increase_b = tf.assign(b, b + 0.2)\n",
    "    c = tf.add(a, b)\n",
    "    tf.summary.histogram('c_hist', c)\n",
    "    c_mean = tf.reduce_mean(c)\n",
    "    tf.summary.scalar('c_mean', c_mean)\n",
    "merged = tf.summary.merge_all()\n",
    "train_writer = tf.summary.FileWriter(log_dir + '/train', sess.graph)  # 保存位置\n",
    "test_writer = tf.summary.FileWriter(log_dir + '/test', sess.graph)\n",
    "\n",
    "\n",
    "sess.run(tf.global_variables_initializer())\n",
    "for step in xrange(500):\n",
    "    if (step+1) % 10 == 0:\n",
    "        _a = np.random.randn(100,1) \n",
    "        summary, _ = sess.run([merged, increase_b], feed_dict={a: _a})    # 每步改变一次 b 的值\n",
    "        test_writer.add_summary(summary, step)\n",
    "    else:\n",
    "        _a = np.random.randn(100,1) + step*0.2\n",
    "        summary, _ = sess.run([merged, increase_b], feed_dict={a: _a})    # 每步改变一次 b 的值\n",
    "        train_writer.add_summary(summary, step)\n",
    "train_writer.close()\n",
    "test_writer.close()\n",
    "print('END!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "训练完后，在summary目录下输入 tensorboard --logdir graph2 就能看到结果了。如下图所示："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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hYGjd/NCPrxgfjmfPQ2i4nZkmAAomgRljGI4h3X/YP5BVDAZVjWjnamFgJfjjq2aoxbd9\no+WcbNmbZ1DLyEAe8Pnnwy+3/3DbAVUshLDltMSJypOuOxJN4GnazW5s1I6bR4Gs+gw8Gb+oZ+VM\ntJnLW1W/oVgTuboCvz1NL2Qc/YCnWTdckbaReMzimhda8hV5rCGbcNAVCuy4OBHt9uX602sZp71m\n3SvqNLYLLNwpQur3ZvL04G7YFj0QnSfy2bqkI3E6fEd2lMyvp4ndiORBYeLoC37/dGH39byQbiKx\ncMwukAd/wj0C3zxhV2G1y5cVWvKlubH4Nq/2MA7FMETSbBY07mmLpppIFm6nnhb7uUJB8wVBn2Op\nNcgVCd6hy5DcoQ0L8t+52LqB+GtnDH6aFL6bxV7bZngicq0GV3znWfG9/6h76WvIINqLvbZLvL/h\nhq3e+xJDRTsuRS6S3TsydhYu2OberR1eX0Y5+csVjpFuhhrtjbPmvWt5ies2Rbq7iXkx286lERBh\nJQfyrF+un14LR6JRIj9tlmjni1DCLc7KwBbvUizh5l9tPK0Quc+w12oyz9aRb2ukAZE/Rfc3OyW0\ncTHcPI27oBMYardUPXw2/hGMBHpEXav2WdoRgWQhwATv/c5ncNnpYze22THzCTEVB3tUOQRJFepq\nXPrHjrICfxwbv4yOT+XbRZnjZrfnsfORBua9NphSSKx1zWJvp5NckfB7PnrKV3YFcx+e0ddS7JbH\n+85a/Mudu9jlyvLsO9YWuq7tU/P/bR3a/uJE7jwufydvX5frgAvwhLtcswvGNM8d03n7mLEhPtXq\n4z0Kjf2fiGLPDf0wMFJmm/xFOZEy73c8Q+UEv70g92F37viJnGdttfpl3BWubf2bndm7j7tgdfDr\nC4zw9p54o6XYMeNhY8YLIaR7vYG+0w53uR71RRR76OtO28d0zn1gcMDy2zfz7HdVpNDIn4LFgf8N\n3H5rm7wpN/jbtyGpqLFt8n5aHMmhPyJQDQQQJIRrWoFwQ9/2H34TY+e5zxyW9/rJbh6S/LVwGPKI\niVnEtHM/yv/gqtBKayDK8rrjl/jtQ0Ssp+UBSPoSTEew4fQLLvgYLyVPUTwbRWW2/Hj4TAhT3LYu\nvGEBcXfeXhdlDn0bhZ//0dW5/9m/asLjo6xi8ACBbdQ4h1A14UC+HU1Nirfdke6G7aAXWvmDOwv3\nZm8r2+6EF2aF184rdAYWbMt74/S8548oFI0xdYQ3LUdg4OexQq3cvvwPriSMueoUe5Munmb7WoHu\ny6YzUsPjWoyBxSZYV07OUndGHQ8RlUUbT3v0tYug9IhiJxlXDyG+OHiLslTi/9Zjet1mlld/zc+m\nGqI3c5/qy1XkrBWXONH+XMDhSIQVcxxKheBp1dddr5klG7avdxbl3A/lLCGkHI9WxjH/8vUcxsyO\n/InDCyZd58xTNfv0S2jdPK5Dxo/sGumICptnqfHajRiLga1doHMHBeXevQMdTaSxM71c+1b31dvD\n2X18ESxVVrcpVCkqtP43PnI/sYYYijYURbhgO7N4CPlG3hPnnP/WWYHvqyg8vsiKkv5nSJTREF+n\nwf5jHmCEK/D1I/lvn8s8i7jnMBiK99h5Awmv/93qyj0OKMu1TZncTvHnE5sQ3rqmxGu7pPtb9d6X\n4pLhBgVJd62GJi7Us+fB1nDzhoWxma1va4OWKPzwuvmxR2NTmJoRzttk6fwmXZxH497iTIa4l2IJ\nN/9k5Olsqr2PyP/lbSKVrLm4GbWZqVE1g612/doRgV0hwGRPTicWPaqQxCp2CicWHV+3XYs11Wj8\nBcYTzl/2nVFp5LQi2yu2ZWXz+MSYr3123vgL8l4dbH/kF9M5guBQuHaWhO+0GeFpSKGLg5+NDkcK\nD304I9TZ8ld7swsrC6+eWBj0vmBqaPtgb61sN1PeFuRGDrfxHnp+4L0XwzmX5d56WeEJQ/pZ4w3b\nZwQmTI6kLAmMH+e75lKPvweSPmgybZyUz1nW/hKT4HLlhNaujuxnMYvA7W/m3fdG3/TJgZxLfC2t\nKXah3y8ImIeWBRcWLB6Y2aGZp9UIj2tI7q0ji0rg/8m4/V0Ns911e9iJ4eWj8r+MWNJ5oMfy7y8O\njjeNXRJcvjjcrQ1jFtpEoOoJoMnzx5/vP/oB4gk9R97D+yS4OxSwwGbMFpz/gUmLaOzueBSDcycQ\nv0q8YlTQu/NUE0hPLVaso9fv63E+Q/746k0eX6+L+GftB/OReYHP7yFnOJjv73Olt8vJ/OO5s+Cr\nBwPTHnGWWWX7aD9kgDWrHwW/W/vwxoVEg9u1W4/RGXXIY2Xb6whLSODzcXvtEPod04zztzG11Tox\no7Y1mX+AFU/ORE2mwuZ/cgtz+71tDyd2kWhzRkmYJW6iiO2KKm/HhPcTABlaMi3c/mjLecXcxbJv\n4RAuRKvV9sZH185DvaEAHh63L8POUok7LMpQdCc1s4vNtFUaGJz/PvUysJJ12feWAeEQvUaIciTR\nmuMQBcEsK4ArPuPEovUUcI0umsK3wNu2v7MfrdIivYkXi9F9MxvZmiOw/3D6kchSK8ak6rdQ0Ooa\nb+aOmgu2lds85+VKPMhP46wn+O7n7CjTiRQ+rHHw4yuEzDgzlGPf0X2FZ3GB8Y9005CC7agIK0oc\nX0pkKg3ZSCEDKYTz0L++Q6+nr6vyjrHTRWLs3rpToy0PSaiAifpcOfyzxshmv8RE/Z0y2R8cN5DC\ntEhXEg5T3LXNMB85d5jB7IJt63D7WLHxPS8s7trmlBLub9V7X8I2xon4ZxGIzJ22dviWbV4ZZsSt\n5YEu12P89ITztwLTOdd6x1kE+/z0Gl9YX8TZviM9Uhrz0k2BhX/ty8xfZ6d0q8qYW5zJEe9SLOHm\nX+08o9sV+bzjmqGhG/8wi5gQp+Btf4y71YHhv1Y6ZUncEpQoAklFwFpLiDvb6tlRVpGy7R5LZyZs\ny83B142L1xRou8Ht8kmxX89mvOL2oXLtxLaIeFi7BBaoIxrULC1kEqtEtJuZ6q42vovCO9eX7e5s\nRfQUu825tOAAKy7d0/uFWr3HhjcvDv0+Kn/Ck5zia2hpbNeWxcSuF24588JMi6uV5a5blIJboGi3\n8P/tswNjihaiy74kEnvfz3/6DYGnOkUmq+eEl9vy3hXcjHxvxtwJHlFD2Wf4T7zd16aTWRg/qtSd\nPjaLTL/fvjjE2dpEIAkI4M7Ke8VaJInFnHjgxoHsOup+JGWUacRnujLqEUxrjcHXa2GNwS+bYQWE\ntz40KujdeWJhID1T6ea/x9zv8D6netr2tz3zZk67//B/uGo3IoPx6vPAzT80sO/Av6Pb/YffbD09\nVMcMVdwpyAB3s+5et89yO9DYjoNM64hAtmL+C7bipQku/gLJbcLLXcG8iMywgoQI8XXPf9+awbtb\nh0ImzjntLDGFF9qSUv8kascaHSBns+643PPfvbTQUe9EWQn7JrLdmtuJ25zAyBY98WLRrWWtClnI\nQ61zGjwfXVbAU9RGkEJUSqV8LNiKS9Na0s/tCa38vuDzuxmipmvsuswEbG/X01nEAZVu5HR8CJG1\nAHfM+UTkr/tth/x29qOZDR6pgwxWgBwzbzse66M3W/b29/m/KD+/bUzl7rASHn3B1ejYym1epJl4\nOH3dznRt+TO4YJKjsMJdgxTZbOkiQnAD25lPHputTCmR8R1bmu44hfSihgS+e9JakoC1Nv4sDKYg\nG4MF/CNciCge/jGG6Nq2IfYpakeBCd3bcZGgnCMzh2OLR6LzD0cu15637RHenhcxicAabojdmKQQ\neavwTkeY6x7Y7i7x2jZmWPOVWFlg4yIzPbuEa5vyS7i/Ve99Cdt2zEKPfPWsFUDZCB9Y95u7WTdW\nMSBOPswqAAT5O7bCs/y1fPue6et2tiu/cIWOqNKs1UmcG/cx/gXzWdPBmWztx97iinLEuRRLuPlX\n632+yOTo/52XLjEs5rCX3+im+3D3YK0TX9dTC758IPo0fRYBEUgCAlYQft+rCsPyi+zZ2WdSlFo5\n/zMhfB6OJue/8JaSq1oSeK5H7ocvBNeuDhdkufHM9xxb6/opvuySzyrb0Zwng+ssYe3O7rcjSj/+\nqcdkDBvn79DJHZgXnDsu8NO44FoTAhA/t1JFIHkIEBJf6x/rMs9+F8FMFHrBlNvxXVjPQ+t/4wnJ\nWn4msiGzuUFkHDea2ZjWKr5ePxqeUUbWcEYjxQ16NydagfQZdXnIrnXLXxknP2+tklW/pbdd5AmM\n0f3InPYAE4b9dbz7nsEpWZd+W+v6lXilkJGEGIUW/M/N6TtHLZqSq+IvAQKrf0KNI2WtyII/PrUr\n9bbpR7QqzfEfeXfW375w77YXUs3SEoQHB3I9jTqh6mkCWgIHrH2WPZXXkhl/fIYPP/P8SRmnvEQG\nAg0KPr+P4QlmP7KawI5TKm3PhPfTfQyO4H9GYSK9aIKlexnOBLsJQvbXthbbi9nQA0hinF3Mv7UP\nhtb+yoMgQzCMQZhEa1EAf5YzVMzOnPAdK5p6yxpig2kFExkQRda6aM6h2cIJ2B9Yns+2/awZ+JE5\nDnEgGOPMPGE66/dJOxQ7h4ome9OPVoAuQisy7JJ54acZgx5B8BBiygLmVmh3g5YJb2apBSJfmadg\nLTzuCFYnYr/c5plJ8t8+QbA9fe3tcGycqg3See9ac+PDQSLUIjTCLHJmMltfk1gHZpyCXFaU8uYV\nLA2ALDfH2eEjfbpjfTvYznmDlQWtCzWyAZx2WfMRNv6Bw8H6xnl87gat4tVQOWn2RcLFEHW9GQtP\neYmvObKT65Ngh+DyGSwXRx/FtYblMBj4cKMqTQAL3z726cqVM0u5tiNmBH601rn0NO5sLSRR8rVN\n9cXc3wi3qcb7UiGWyCx06z6581cvuHSa2+1j9jh/2Y9maM765b/ce/mR2nEZFFOaOZ3hV24a4KWD\nnAXGvcXtyBBzKRZ3808Knjvsduw5Ll2ztgW3RF+Xk7kfWkHyuTmedkdagUXaRCBFCPCyHiy1plsW\nv/EjZa0Vt4vL0WVlZ541wa6EGFJ73+ywJq6dYuWsaHXFtYhWoNgZNLfC8h3bzp5vx4FE7m4xEjcn\n9GVne+U2u/yM4u8Y7jYneepluVbdnjfmQvK793s982TWe+/n6+/K3bjaWhmurvWi+SJne5uItzzX\nGggod5TEjPD2C1xWTH5rO5beaxa6Z/7kATf6rQIXB57onG/JfGt1em/jLGsvdlu9OuzCb9/Mk00w\nfuxhpYhAlRKw3KoF2xClmae9xsRmX9fTeFNXeO1c3vrI6rtMDsy84OPwunmsQMM9Ap3pzqhnrTXF\nwnWf32v8Et4e5xEcbjnZ+A6yNWxb6Ntkjno4hGZj5rD1bq3Ikume9kezKjWKjpXq7XayFh3ee6qw\nIorXzPE138/f7xam46IVPW0PxwES3rzazlzFOyxw5dmzLxMpWeGJcFO79shL2vw8Uxq/NHGGvKaO\nhzNWzCLolKdAVgJD5FuKxRr4iET5crLb8sUZVlZRrEW/bQOzWBkQAb4Vb89ad4SAbl1jV1R5O1Z1\nmXXt0HGWMED5MDnKsoFlq4k0PvDv1lKozbrz7IvvrtC36fYypuPfqz+ro1tLFcx/3xkyDSJa7SNk\ng/fYsYJgZLyGqdTB3wrnVlRec0zJPOIzx97XbahlM4sht+rLkIHlc3ZsxHegoJjWjgqlZ+NCsAcd\nHOeVsmupelZnaLE/rwYMrfnJkkyZ9Z2yuZTzd/1w5OoiMt8aUWItQyYF/PyWHazON8vLcFKFzGP4\ng9gEhjmCv38YbaYvk+uZa8bbYRBqmTsDDxl85blsWA6Ny8Ya42OhuKJVBqJP3/lzYfcR696ka9gV\n8jTvZS2dVbQ+gslrGcOK3/ucaj4yoOBr1cfbZTDDTMjdyJxG6xWSOxdcnZ9YpwN6lnOYmfkMSfB+\nx+IXRzDzL7iBZA55Dk+4Nf6yW3sUuzU7idtpade29QVcNNV6B167o6wZ4PG+4M5rO+79jXU6qvG+\nVNhVGXV23CdZ7LPo3XgWH34sGu3NOGBo+TcMj+7UtZGzmMrkaX0wg4+8uLRwYkVUab7ItBEuXcJh\nIi+GsN43UTRpiyj3Em5xzuqiLkW776Ju/gUfbHQAACAASURBVJYZ1XefdxocvR9pqbdodUlumNZo\nyO7W9VYw43HmcfIti31fQ3Qh+iwCSUPAzP3243+ePqo4o3ifOWPQuxgtTyGWQ6Jo4wc3Y8jzvCHY\nmtbOQnSDHqWKooNM9hmcNaxN7hOFA812epl2cnO41zGDMiozw9nWG9p/eCEqvUpE+5xxoUEDvfWa\neQ593bvozMhL1I7xsyz8qktz35scZZDzo+ewscwqd22emPvAEB7KwrMmhY8a6qoXyTJrRqhnJ0+t\nPr4hx0Smtbf2njXYChsomB382OUa5iymmP32//G1RFjzGoypQdeT7tX3e9tmezq/4JvS35rW3uxR\nfxsrAj+0bFTIdzs7+AhduKOsQzd4m1knxt+mTwod1c/LQnonX+V+jmntrb0t27jjZ1WqCFQ6AXQ4\ny2XhLmbVYi9BsLh0ln2dP/l6a+W5dy8tfE87AfO8v33++6yInnHMA0iRwLx3d7ygNaOeF63CeDzT\nCzPq+o+4o9BoXlG+4jsrkH7JFwVf3G8SvdvW8TRpBZbnbbLbRl28u8J/0NVMTM0bdxoRj97uZ6N8\nyGDNaZ/2cODbJ+zMVbyDYGDWgKt+C55u7apZc4sF6qx3gM97z3LpRDYeExHtTPgnWsF3yPWsWO47\n4BKes3lfHaEEVjmdTsR7ZiUWbcgqlry2Fupv2RsNbC3FF3nBsnN0oChvgv834f3WEs0LP7ack5HN\n07ynt/1RLDfNTGzzVmHL5xmy1lLGh2msQqjz+iIieInIsIJ+I+9pdxpnreztsQIxLLVGvsh72qts\nNaPIC43cDBvRECu0tWBbaOn0wMxndvjcIrYWqtC9IysqFwPB2aiy7BM/H5p6N72JXLcCTLj+V/8Y\nmD6mLOcmJo+5uuia/M3B3z6y3tPu2LhQCypqXuEwR9N9vUSe77zx4FL47ILjcfEXgR+eJcYh8M2/\n0ahwMF0A7QLeO1WGzVql35dFoI21UjpXD9+dOeNI3KHfIoWQiC/FzLKxXskeyOMUM1ZotZ27U2S1\ngjJUWBVZrLYTtdRhkK/35Vaj+OL8/ApI49dNHPVXD5mVEbysamndkKfzPoJI+MZ/GeeLvbajygnO\ne4eRC2tldU4v7dqOe3/jzlZd9yW7LdaXiOsnspn3tBceYnm51T+6GMhY8X3sfbLwLPMVYGmDOW/4\nepzHiVGl8Z52Egsv3Z3f0056qbe4Qksi/zkvRfoo7s2f+yQRW9Vyn3eaGrtf2NKiAyBlAdpw3hbr\nZQ1Mjfn5bcb4oBT1voai7PpfBJKPAO91m/UiT5K8BSl2AXnMxUGCnCZP4aJxFW0B0wldDtFOMXxN\n+MeEc7NSZlTBuxJsyOMxTnVc9845X6Gcxfmf/jOqWPK4t94SVfUuf+w7pZb1drd5gVs729Mc3fYr\n3wpfqJaFjg1vHJf/yJnewve0j9j+3OhI3Vdl3mS9es164fmUR7OuHGGt68YUcdz1dVHpliwvGLNf\nQY7LM2RupvOVb2RzWYvJ88q3ove0v7At4qK3ih0yt3ZPa8g28n44K8GNf4atYF7gtc75hH/yyrfL\nna98syx0bZ4UeeVboUnWK9+YnMpL6awzXa61VvlF72m37d9hWOSVb1lF0+B3AmIK0F8REAEREAER\nEAEREAEREAEREIFSCGRl175msSurAaKdt7XvyJyVjQfeeqVx7qZtD7fZRdFO5GmtaxbtKLy0ve0P\ntyWSpbRc8Y8X1pWbs+3htrbZDA1kDZuy0+vorYYvspzTVbCFp/fPfXdscCN+akRslrsgx1pS7rkz\nrZmCJWw5I3OfujSwNidcqw0ri3hqMSt+UsGEwSh2ttCEgflfs9R8rlWgn+HteYF3++x4SXsxxUYy\nWzZYCtwqbaCl2NlyRuc9F6nLWMg684tG5T1lvaTd5Rqd9+Yo23jXxqkFc+dZyZHgfGtn5w3DCn6a\nFybRkveLg19PJExAmwiIgAiIgAiIgAiIgAiIgAiIQEUI5OZY71fL3YQ+r33zRqLWWcWdWeUIWqPY\nI0cjKrEipReegwI3YYb4umPjDU2mSHziEvYjO4sLzyz/f9SV/+FIou5R6fbceFz9KHYzHcAqsuho\nJXjay2+xzhABERABERABERABERABERABERCBkggwsZzF1TsPxuVuZytcaD1RK55kZVvrvMydSPmx\njnfbtc6Edkta73KlGSe/QNg/5eR/MCIw750dBWZl+zqdlHHcKHQ7DZRot7tbOyIgAiIgAiIgAiIg\nAiIgAiIgAslOwJ5h7ny9eWUYXeuaxfbicyxnk/vvHgmvhUgB+93vdnPsBppQ+SpZiC7hLVOBIiAC\nIiACIiACIiACIiACIiACaUnAFreV3XqC2G3RvsMNntBamaXPcvH+g0ZYb9Bo28+UTXw+3v6Cr0eZ\nOfPytCcUuQoTAREQAREQAREQAREQAREQARGoGQR4nWfzQu+69XL1XY6HL5UKMflGqDtzSrQ7aWhf\nBERABERABERABERABERABERABJKIQBWtHp9ELZYpIiACIiACIiACIiACIiACIiACIpAiBCTaU6Sj\nZKYIiIAIiIAIiIAIiIAIiIAIiED6EZBoT78+V4tFQAREQAREQAREQAREQAREQARShIBEe4p0lMwU\nAREQAREQAREQAREQAREQARFIPwIS7enX52qxCIiACIiACIiACIiACIiACIhAihCQaE+RjpKZIiAC\nIiACIiACIiACIiACIiAC6UdAoj39+lwtFgEREAEREAEREAEREAEREAERSBECEu0p0lEyUwREQARE\nQAREQAREQAREQAREIP0ISLSnX5+rxSIgAiIgAiIgAiIgAiIgAiIgAilCQKI9RTpKZoqACIiACIiA\nCIiACIiACIiACKQfAYn29OtztVgEREAEREAEREAEREAEREAERCBFCEi0p0hHyUwREAEREAEREAER\nEAEREAEREIH0IyDRnn59rhaLgAiIgAiIgAiIgAiIgAiIgAikCAGJ9hTpKJkpAiIgAiIgAiIgAiIg\nAiIgAiKQfgQk2tOvz9ViERABERABERABERABERABERCBFCEg0Z4iHSUzRUAEREAEREAEREAEREAE\nREAE0o+AL/2arBaLQAoTqH1XOIWtT5zpBd8/U/DO8MSVp5JEQAREQAREQAREQAREIEkJyNOepB0j\ns0RABERABERABERABERABERABETAPWHCBI/H43a7xUIEREAEREAEREAEREAEREAEREAERCCpCPjq\n1avn9Xol2pOqV2SMCIiACIiACIiACIiACIiACIiACEDAV79+fZ/Ph2iXbtcFIQIiIAIiIAIiIAIi\nIAIiIAIiIAJJRcDytCPaFSGfVL0iY0RABERABERABERABERABERABEQAAr7atWv7/X6Jdl0NIiAC\nIiACIiACIiACIiACIiACIpBsBNxbt25NNptkjwiIgAiIgAiIgAiIgAiIgAiIgAiIAAT0yjddBiIg\nAiIgAiIgAiIgAiIgAiIgAiKQpAQk2pO0Y2SWCIiACIiACIiACIiACIiACIiACEi06xoQAREQAREQ\nAREQAREQAREQAREQgSQlINGepB0js0RABERABERABERABERABERABERAol3XgAiIgAiIgAiIgAiI\ngAiIgAiIgAgkKQGJ9iTtGJklAiIgAiIgAiIgAiIgAiIgAiIgAhLtugZEQAREQAREQAREQAREQARE\nQAREIEkJSLQnacfILBEQAREQAREQAREQAREQAREQARGQaNc1IAIiIAIiIAIiIAIiIAIiIAIiIAJJ\nSkCiPUk7RmaJgAiIgAiIgAiIgAiIgAiIgAiIgE8IREAEkp9AOBzGSPM3+a2VhSIgAiIgAiIgAiIg\nAiIgAokiINGeKJIqRwQqiwBaPRQK2X8rqxqVKwIiIAIiIAIiIAIiIAIikHwEJNqTr09kkQg4CBit\nHgwGs7OzHcnaFQEREAEREAEREAEREAERSAsCmtOeFt2sRqYuASPaA4FA6jZBlouACIiACIiACIiA\nCIiACFSYgER7hdHpRBGodAIodiPa8bRXemWqQAREQAREQAREQAREQAREIPkISLQnX5/IIhFwEJBo\nd8DQrgiIgAiIgAiIgAiIgAikHQGJ9rTrcjU45QgY3Z5yZstgERABERABERABERABERCBXScg0b7r\nDFWCCFQ6AXR7pdehCkRABERABERABERABERABJKPgER78vWJLBIBERABERABERABERABERABERCB\nCAGJdl0IIiACIiACIiACIiACIiACIiACIpCkBCTak7RjZJYIiIAIiIAIiIAIiIAIiIAIiIAISLTr\nGhABERABERABERABERABERABERCBJCUg0Z6kHSOzRKCyCbz66quXXnrp9u3boyoqLj0qW3V9XL9+\n/cCBA6dNm1ZdBqheERABERABERABERABEahKAhLtVUlbdaUSgR9//HH58uXFWcwhMhR3VOkiIAIi\nIAIiIAIiIAIiIAIisIsEgsHg9OnTq0205+fnr1y5MhQK7WIzdLoIVAaB33///emnnx41alRc3U4i\nh8hAtsqofdfLnD179umnn14/srHDR1PmsmXLhg0bRvIZZ5zx22+/2RUVl25niNrZsGHDzTffvPvu\nu7dp0+aBBx7YvHkzGT777LMjjzxy8eLF7P/111/nn38+iHhZXVxjcJifeeaZr7322sknn4w9I0aM\nAObFF1/MPinsmwyvvPIKZVIR1VFpWcyIyqOPIiACIiACIiACIiACIpCiBD7//POcnJyEiXZkzOjR\no3nONjimTp36zDPP5OXl8bGgoODFF1/8+uuvnaRWrFjxxhtv8BROHnL+8ssvzqNJu08zH3/8cQRJ\nVVr45ptvwnPXa0xUObtuSfKX0KFDh3POOSc3NzdWtxvFziEykC0J27J06dJ//OMfhL5v2rSJL1qj\nRo0Qzxi8cePG6667rl+/fnxP0cCTJ082xheXXlzTtm7detttt+21116Mu/HN3bZt2/333x8IBA47\n7LADDzyQuvjK8+3mdIYGGA6IawxHqferr7569tlnGT5YsGDBRRdddOWVV65du3a//fZ7/vnnGVYk\nw9tvv/3cc8/RIr/ff++995pbijGsODOKM1vpIiACIiACIiACIiACIpBaBA455JBBgwYlTLTjCsvK\nyjKuMB7ZlyxZsm7dOkYFgIJaQOU2b97cCaht27YjR45ETjgTtS8CyUOgT58+sbrdqdjJkDzWOi3Z\nc889P/rooyOOOMLtdterV+/ggw9GAOPxnj9/PrEtJ510EgK4W7duF154oTmruHRnmc79efPmMRMe\nB35mZmadOnVwj//xxx+MDvh8vuHDhzPb/KGHHnr55ZevueYa3ObFGWMKHDp0aMOGDZs1a4baP/ro\no/fZZx/KPPzww7mTEIyD/VdccQUlUAt+e2pZvXq1bUlxZtgZtCMCIiACIiACIiACIiACKU0gIyMD\n+32JagOKHd2OQwzfIxIdh1iTJk14jm/atCnqnaf5Bg0a4FHPzs7Gq3bQQQe1b99+4sSJRx11FJ40\nMnNi165dkQELFy58//338QRS2qmnnrrHHnvYFvIQj2/whx9+QHh06dIF7UGl9lHcyGTATccpccvh\n6KRJk2bOnIli6dix45o1a5ABiAE0xhdffMFAgykTtyERuQMGDEA/LFq0CCPxFrZo0YKKcHcTAMwO\nmoTETp062eeiK4YMGbLbbrvZ9rAzd+5c2kLkMG0h4rdVq1ZOI0855RT7dLs5ZH7vvfcQUR6PBxnD\nhpsRfyml4Yo899xzkTEGAikcBaDX67UrtenRrhNPPLFz587mED2C/9NZDuLTcHbm5PR3332XoZaW\nLVui8aCEV9ZZeNTRvn37os3sPqVbbduAc8IJJ9SuXZsmcyWYcvDKMiWDVrzzzjt0B73M1rhxY/qL\n68SuKHl2jCznesDfTvw2hrFjfOxJq9gNPUQ135Rvv/32p59+grnhT/9yiZpvPtlwlc+aNYud4tJN\nUbF/Uctclmz2Ib715uoiWp7BOLr44Ycf3nfffU2GuMaYQ86rl4E8Lm/S7UQuLS5FkxP9z3eT65ZL\ny6SUYIbJoL8iIAIiIAIiIAIiIAIiUAMIJEy087SNBpgzZw7qF29Y3bp1EeGITyJd+cgDtxHYxLsS\nBMuzOOoafLjfr732WoQf8g+RTM4JEyYgRHncR2mgKtHVtjJHM//555/E93IiOmrGjBlOSUkiZaKN\nkX9xy0HDMDRw1VVXYRviE9HIKagadAuBxDgkx40bh3rH3YejDzmNbUj0Xr16GcVOZqozYw3nnXce\nLcJCzsXNSHOmTJmC5Thm8ROSk40BCxQsyhk9w4plyFTaQrptZGzVjBR88MEHaCpCl5HZtBGdj7vS\n1r0IaZgYCEjH119/HRdljx49IhW6EMC0C/8q9KiR2rGcsRKOYq2znLg5GSag9t69e9MXgKJwU6z5\ny2hCcUdNn1IRNWIbFTEswmDHhx9+yECGsxDn/pYtWwCCqsdmcp599tm2mHRmq/Z9p27HmJRQ7Fxj\nl19+Ob1w/PHHX3/99VyoXGyxJO1rNepQcenObJdccsmjjz5aq1YtZyL7XKJcKmwM/TC4hvwuozFR\n5cT9yE3G1vMmQ3FmxD1diSIgAiIgAiIgAiIgAiKQigQSFh5P43Go8rDORFM8zDjN8HibjyhA9Lx5\n2sY5jKguThXghEcqo/YRkChP9D9eehsrM2ZRxcg8tnbt2qEP7UNmh4jf1q1bI/Jjy1m1ahV+ORS4\n8TQaFzS6HVMPPfRQovQxaf/998dU3P4YgLB/6aWXEAkYHFWL+Ug2cy6tRm3iZCaFKb52ZryXtAVn\nNW1hPIKxAEPAGEnJsVXTXrzTRBBQIM55Tkfw2AWyg9BllS9kOQRoCMXSUjsDYweMIMCNGuFPdfC3\njzp34ubEh0kehgA4napxgDtPKeGo6VOMN7aBDpgMfMDczI9wlmPv4y/FDFrav39/rhmUv30o2XbQ\n7bQRuc7GTpL72KHHwm+wJbDlrLPO4lKnawxSvjWM19AK85ErsOR0czT2L+50glDidq7xfo8fP/6T\nTz4xbvzijIktNjaFKuw7AMNYjBFwZdrZSjDDzqMdERABERABERABERABEUh1AgnztAMCnYlaQ/cS\nKIsSxruLr49VoJmeiv/WkIpylEXhwzWHc/6OO+4w6Shbp+xEe+BnRqYyQZcMSOuo0+3C45ZDIiZF\nnUIiPmE2k870WpQ8rUCE87bqY445hv2oU+yPnGsfRXyyEb5rH0VsYD8bKRxCvZtDTiOjqqaBCCrW\n00Yh47Ekf1TQOImYxxpddi3oFgYLjBmIbULo//e//xlotm12Znsnbk6aw1gAExnsbM6dEo6aFmEb\njaXHzVkUxcfYd4A7yzT75hRbWMZmqPYUYjq++eYbE/HBDqETSa7bgc8AChNAGMMiZuQ///kPQ0Us\nFMcsDIZUUNQMfvHF5EIyYRrFpRdHnoEhQjyefPJJwl64zJg/T1wG61BSL+531oQfPHgw3wVWlSdP\nccYUV7gznYuKNSz57lAIO8SAEC1vDxYUZ0bUeJOzQO2LgAiIgAiIgAiIgAiIQMoRiK/QKtYMVA2i\nl0njqDgcfYgxorsJmKe0Mi44h5jEe8wMZ6N1nWYg1AnPZgI2K1GjgU2ovDODcz+2HDQhfj/0rTMb\n++Rk5jySxpmOMCZOnjEIBA8uazs+35nHnGsXyCkIVAyz89BkXM1GyqJ4ORpVTmzVRrFDgJdywZCo\neLs0swMWCoEPYKMO8ZHF/4jnZ2UvhA26nUiB2DwmJW5OjAcypsY9q+SjnIJtNNbW3mg2SrM1fNwy\nTaI5pSw5Syik8g6h2JmnAHZ7TjsfqS6ZdTvhAFzVhDBg52mnnXbPPffwygMuCaZL3HfffSz8zrRz\nVqFkTAphTx4Gs+KmF0eV/P/6179Y2YGlHMjD6gx85IJnnAtFTdVcDMSMMH7EihUXXHBBXGNKGFRy\n1suwFOUzFEjAP5s95mXMjjVDit1JT/siIAIiIAIiIAIiIAI1gEAiRTtP6oTB43ZjtWrzRM4Dt9G9\nOMpw9JXAy/ioCd/9/vvvf/75Z4Qr/nn0kgkF50TEJAoZYcBTOyG++AnNbO24ZcYtB38dk3sxCWej\nCQxGiDJHHQsRM0Sb//rrr8QI4M1j3AERTmgxnnBsINKbptkVoUU5im4h8PjLL79EISPvmTNMaU4t\njQ3MosfhibeTkQty4t60C4FPbNWMHaBgiQGmOqbEsxF7b05B8yOJwYipvKwPTybZ8PrSFnvEgXMZ\nCMAMWNEWYs7t6uwdU07cnAQe0y5shgDDDUTmY6F9YslHyYYlsGXUgCX6sIFXeREmQH/RBDoLiYtV\nzLS3CyQRNy8tYjkAYDLcYx9Knh2nYjcroiHdWYsuyXU74RJM9mazSR533HFmHw/5U5HNPlRyelQ2\n+yPlINrZ7BR2uMLti5w+xTdujhZnDAtD2qffeuut9j43EDa+5qTw7bvpppvsQ+zwdbNPjGuGM7P2\nRUAEREAEREAEREAERCDVCSRStMMChYbLFJlquCDbEGOoHZR2caId+Yr6ZSky3L945JjRTQz8W2+9\nhVN94MCB9kpXFHvkkUfiuMMHjjONh3UUJvrZ6XmzO4Pp9LHlMKEdN+Bjjz3GKfbMWLQBZ40dOxYd\nix5mHTszWIDIQXUwZIAljEQYjyI5qZoW4bdEmhLzz1koIP6SAZem05eODXgyMZiJ6MgMvIVEH9gW\nshNbNYvhsRYdC7OxwZBRCTP9mIkAhDQjpFmtDcNY742ludHAe++9N/5Mu0zsJIW2kIKSByyG2UfZ\nscshgDk2J6qbsQAqwkGK2EZ4O88t+Sg5GWigvcY2PjJlnUX4QM1KAcx/xpGLPmcgw55BQM8i6hBm\n9AX9HlWds+rq2mcAAhrGx24UO5awkxK6vbqgqV4REAEREAEREAEREAEREIHEEnDH9ccmto4kKQ1P\nNRu+aOzh3WM42Fm93EQEJImF1W6GPQhCUANL+jMqYbvxsa3ko+Uy3l4Pv1xnVWVmAgGYpB2l2G0D\nWHTAvPuNlxEwxd1OT/gOV6yJ7CBEwhnHkfCKYgtkdQlGppzBESYPQzOEwTMOFXtKYlMY0GGUCg+8\nGd5KbOEqTQREQAREQAREQAREQARShUCCPe3J3GyC3lnRHWcyKoiwZxy8SejdrUaA+MB56R0CCRXK\nGuBEJdjB+VhV8tFqNLuSqgbC8OHDkaa2j91ZkfG3oyorVbE7a6z6fWIxWPi96uu1a3SGwduJ2hEB\nERABERABERABERCBdCOQRp52wukJ3mbONn1M8Dbx885o9nTr+LjtZVCDuQloUQL1ecW3eTGenbPk\no3a2suwkv6e9LK2ogjzV6GmvgtapChEQAREQAREQAREQAREQgVIJpJFoL5WFMohAshGQaE+2HpE9\nIiACIiACIiACIiACIlDFBKwJ3tpEQAREQAREQAREQAREQAREQAREQASSkIBEexJ2ikwSAREQAREQ\nAREQAREQAREQAREQAYtAwhaiu+2220RUBJKZwJ133pnM5pVsG2/UKzmDjoqACIiACIiACIiACIiA\nCNRIAprTXiO7VY2qIQSY0x4KhVhDkZfwtWjRooa0Ss0QAREQAREQAREQAREQAREoMwGFx5cZlTKK\nQDUR8Hg8Pl/CgmKqqRGqVgREQAREQAREQAREQAREoCIE5GmvCDWdIwJVRgBPezAYDAQCK1as2GOP\nPdjH/c5WZQaoIhEQAREQAREQAREQAREQgWokIPddNcJX1SJQOgFmsxtPe0ZGRlZWFhqecyTaSwen\nHCIgAiIgAiIgAiIgAiJQIwhItNeIblQjai4BI9r5S4Q8up2GSrHX3N5Wy0RABERABERABERABEQg\nmoBEezQRfRaBZCOAYmcz/nYp9mTrHdkjAiIgAiIgAiIgAiIgApVKQKK9UvGqcBFIGAEj3fmbsBJV\nkAiIgAiIgAiIgAiIgAiIQNIT0OrxSd9FMlAEREAEREAEREAEREAEREAERCBdCUi0p2vPq90iIAIi\nIAIiIAIiIAIiIAIiIAJJT0CiPem7SAaKgAiIgAiIgAiIgAiIgAiIgAikKwGJ9nTtebVbBERABERA\nBERABERABERABEQg6QlItCd9F8lAERABERABERABERABERABERCBdCUg0Z6uPa92i4AIiIAIiIAI\niIAIiIAIiIAIJD0Bifak7yIZKAIiIAIiIAIiIAIiIAIiIAIikK4EJNrTtefVbhEQAREQAREQAREQ\nAREQAREQgaQnINGe9F0kA0VABERABERABERABERABERABNKVgER7uva82i0CIiACIiACIiACIiAC\nIiACIpD0BCTak76LZKAIiIAIiIAIiIAIiIAIiIAIiEC6EpBoT9eeV7tFQAREQAREQAREQAREQARE\nQASSnoBEe9J3kQwUAREQAREQAREQAREQAREQARFIVwIS7ena82q3CIiACIiACIiACIiACIiACIhA\n0hOQaE/6LpKBIiACIiACIiACIiACIiACIiAC6UpAoj1de17tFoHSCEybNu3SSy/dvn27M2PcRGeG\nqty/6667Xn311aqsUXWJgAiIgAiIgAiIgAiIQBUTkGivYuCqTgREoEoJ/PLLLzfddFNeXl6V1qrK\nREAEREAEREAEREAERCBBBCTaEwRSxYiACCQfgXA4PHny5P79+2dmZiafdbJIBERABERABERABERA\nBEonINFeOiPlEIEaSYC499GjR7dp02b33Xe//fbbt27dSjNJvO+++0g57LDDPvroI9PwuImxTOwC\nKfPJJ58MBAKfffbZ0KFD165di3h++umnr776avJs2LDh5ptvpgo72/z584cMGYIx3bp1I/E///kP\nShsDbMM4i0D9e++9l8T69etfeeWVFOI0ILZqc3T9+vUU3rVrVz7SwDvuuIPyTRVxfe/E27MNGzaM\nWk4++eQZM2YYU6mXfQqhUePGjcNOsTTK4AAAIABJREFU2zYSZ8+eTWa3221no9IzzjjjqaeeMi0y\nNIxJ+isCIiACIiACIiACIiAC5SIg0V4uXMosAjWHwGuvvYa2nDNnzuLFi1esWDFx4kTaNn78+N9+\n+23evHnI5tq1a5vWxk2MAoEsR6OaAtG3X3755eeff46IRTBTMmW+8847l112WUZGxqhRo+rWrbty\n5cqvvvrqww8//Oabbyhq9erVbdu2Rf2+9957SFwSMYCz/vjjj6+//trUhepmHAFTUc4vvPACNZr0\nuFWbQz/++GOnTp2aNWsWDAafeOIJchItP2vWLFr9wQcfmDxRf6nxX//6FwMN++23HyMFp59++p9/\n/nnDDTcwlLB582bOevPNNzFj6dKlf/31FwJ+1apVt9566//93/9RxW233Xb//fevW7eOMhcuXOj1\ner/77jtaBEA+RlWkjyIgAiIgAiIgAiIgAiJQFgIS7WWhpDwiUAMJ4Ap++OGH60W2Qw89FLGam5uL\nQj7rrLMaN25cq1atww8/nGbjkY5NjMWRk5NDNlQu5SGSBw0axEefz3fhhReizNG055xzTocOHTwe\nzzWRjXj1PfbYA2HMkAGl4f0++OCDOdquXbsDDjhgwIABGIA3m1PQzKa6Y489tk6dOpRPLahxNLNJ\nj1s1h7D8448/pih84GTmFNz+lNCwYUNEeOfOnc3pUX+PPPJImo95NL9Pnz4dO3ZEe7dv3z4/Px/R\n/r///Y+hByynnFNOOQVNjj2vvPJKv379ML579+6ciHufMrF88ODBfORcxiOMko+qSx9FQAREQARE\nQAREQAREoFQCEu2lIlIGEaiZBFCh99xzD2oZTXv++efTSBzRuIttB7tpdtzEWCKhUGjTpk2oVkpj\nQ6LjPGcUAH17wgknIHGPPvpozuIQ+hkNjyBH5RKvHlUUGRDJUYlRH1HCGI+/3aQXVzXO/IKCAkYB\nyLZx40a0PYWbU1q3bl2caLfrijXDoKAhlMN2yCGHLF++nCpmzpxpEps0aUKsgV2CdkRABERABERA\nBERABERg1wn4dr2IqBJ4UH7//ff5G5Ue+7FFixY8zTdv3jz2kFJEQAQqlQDinDD1Ro0azZ07F582\nL07D044QRalu27bNWXXcRGcGs48CN6URju48iiPdBKLjbz/77LMpnPnzAwcOJFgdPzwTyJ2Zy7iP\nC50we04vuWpm1OO9Z7yAbHjXs7OzUd3mFObAQ4Ao/TLWaLIZFCbs3z6RePtHHnnk8ccf33vvvZlp\nz3iEfUg7IiACIiACIiACIiACIrDrBBIv2lHsRI3iRivVOOJFJ0yYMHz48FJzKoMIiEBiCSBZt2zZ\nstdee/n9fmZlI0RbtWqVlZV10EEHMde9R48eCFoSqRS3dmxirDGs3Iab/cUXX7z++uuJGGci9267\n7UZ4OWqWReYQz9dee22vXr0YqkMwN2jQAAH8+++/M3cdG2JLi5tCrDuG4VcfO3Zsz549qdFki1s1\nOb///vsbb7zRmYe55SNHjsRFTzozAoiWj1tRcYmg4Kxnn30Wm2kIr6wndB+nPSMIDHyAlBkBy5Yt\nK+50pYuACIiACIiACIiACIhABQgkPjweH3tZFDu24pdjTalyGc0MUiQBD/3lOquMmSuj8ISXiU8P\n4VHGFsVmi7UH/ypzdAkeJt4YpyiKKPYsUmJPjJtNialCAJ1Jv7/77ruI9hEjRqDYjfOZVdBZ8Bxv\n+YEHHkge44uOmxjVUlz0OJmZzc409aZNmyKY9913X2Q/AeTHHXcck7opBAGPe5y13++++25c3489\n9hjql7GDqKKK+4g9TJUn3h6Vfu655yL7Tc64VROmjq5u2bKlnefyyy8nlJ2oeObM08ZTTz21uIpK\nSOcsbGB2PX77559/vnfv3owOHHPMMUyAZ+46lXL3i7sufQll6pAIiIAIiIAIiIAIiIAIlEDAbd7z\nVEKO8h4i9pWtjGeVkBlvGPG0rEeNkuzSpcsVV1yBs465o2+99RbzYPFrlbGKsmdDl5ZQOOL2wQcf\n5KVTiI1ElVn2cuyciHYmIaN/7JRy7cS20W4X7lYWzWbt67gTFmJPLFe9yrzrBNasWYP03fVyElIC\n6pR17FjazS7tzjvvZBF1+2NidxhQwEOOUOcmUJaScXrzVUVLI6qLy1/FTSjODKWLgAiIgAiIgAiI\ngAiIQMkEEh8eX3J9ZT/66aef4qZ77rnnWNsJ3f7Pf/4TxxrhqWUvQTnLRYCREWKby3WKMqctAeZv\n83q2pG0+vvdSRxCSvAlJy1aGiYAIiIAIiIAIiIAIVDGBxIfHJ6oBLO9E3CmKnQLxLfO2ZF7azD5R\n3GjLvn378mamSZMmmZWlyDxs2DDeCE024nJJ5FXPL7/8ssmP4Dch5fjreNUTTmPbSFa3JkaX+bFM\nu2XZKpPO6cxWJYUCKZYhA04/8cQTefU0M1o5PTaDXSA7ccskvVxGYgATAZhdjAFwuO6668x7pOyK\niEQgthkIGE+jzGuxqPqZZ54BDokPPfSQCaMozh67KLNjx8nTQOKlmTYcBdlko8z77rsPaMQAR1GK\nKlAfRUAEREAEREAEREAEREAEREAEdpFA8op25PHrr78+btw43iNFI5kWi3xlh5WrmDv61VdfIcU5\nymTspUuXMkWW10ETrHvTTTeNHj160aJFqNZ58+YhLMnw888/cwi1j+4lxbwCyoAjAn/hwoUscEVd\ndsg962Mx+ZZY8Z9++sksc80sVhQyJqHbmRAbm8E5zT5umeU1knEKLJw1axYx+TSWYQKzKpgxm79E\nIkycOJHxixkzZrAAGC/cxgYW9luwYAHN+eKLL3jh1uTJk8kZ1x67nLg7sZBNNqKOmcfLPOdLLrlk\n7dq1Tz/9NAIeSvQOMj7hUy3i2qbENCTAd5NRpDLGxqchHzVZBERABERABERABESgBhNIXtGONkYH\n/vrrr/3798d/jlo2a6ShnHl2J/wVNziP8rx7GUHOkle4hUlEvvLyZDzAe+65J6+D5ijS/YgjjqAL\n8UUzbZuFsuxFpxHweJXxqLN2FOtmU4LpaQQzc+k7dOjAW6wQ/xSCs9p5EZSQobgyy2sky1xRIw3H\nNkQyy3fj8LdtoJapU6fybm0W5WJ1LjQzgpkMhAMwlkF+NhbuJqU4e+yi4u7EQiYbAwcME7DQIKMn\nVMpGCkMeDBacdNJJLE9gj3rELVOJIiACIiACIiACIiACIiACIiAC5SWQvKKdluASZ3Wrb7/9lpdF\n4WfDgRy3eawIjeQ2L21m3nvjxo1xArNcHKvT43Jn7TokKOIWeYnjmqWt7dc7MwqA67h27dpRxaLV\np0yZwjvkGRcYPHjw5s2by56huDLLayQ2RFXq/BhVC/qZVrAKN7WMGTOG0QcsN8sBRuV0FlLefUgy\nQ4HFxs2JzFwgwIFRD1bSvvjiiwklKNnm8lan/CIgAiIgAiIgAiIgAiIgAiIgAiUpw2qkg05mRjdx\n19iAxmYJaPzhzAmPaxIyEk84c7w5iu8XxY6fGR2LqxmdT3Q9L1Jmn4hx3jCH/9wuBJGJc37btm12\nitkh4JzAcmK/iasnKt44vZ15SshQXJkVNtJZr70fVQuR/zSTtmAzL8dmxAHLGe8gf1ROu4QK7BB0\nQKcQqoC/Hc5UChkc+1SHz5/4fDORoQIl6xQREAEREAEREAEREAEREAEREIG4BJJUtKO6O3bsyEpy\nZn01/jLLOu6ryGgVIfFz5syZPn06bnOC4Ykb79evH+noc85CxBIPj25ftmwZ89t5g7QNgrXoCcJn\nHjhz3ZH9lGAOEWpOpDe+a5NImL1J5yMb+8Vl4FBxZVbYSFN11F9qoY1MaGcYgtEKxiYgZl55TWMZ\n5oCYaU5x9kQVWJaPRv8Tsc/sA8ASe8+Lr/lLdAOHylKC8oiACIiACIiACIiACIiACIiACJSLQJJq\nLXTgeeedx9x1pk+bJdyZtY6zPW7bmL5+yy23sEAawhjH7zXXXGPc6ehzdGyvXr0oDSnLK80oqk6d\nOs5CCO0m/aijjjr++ONxzpujzIrHn8xcehLR58Te41VmyIC3ZBMzT5R43Ax2sXHL3BUj7ZKdOwMG\nDCB0Hxc3YQjEqLOAPH5vVuMjRoDV5gHSokULhhiQ9HHtcRZVrn3m2FPLs88+26BBgwsuuODqq6+m\na1iy/qqrriKlXEUpswiIgAiIgAiIgAiIgAiIgAiIQMkE3IjSknOU9yhTqc1s6rKcWK7MZSlQeUSg\nphJYs2YNw0Y1tXVqlwiIgAiIgAiIgAiIgAiIQFwCSeppj2urEkVABERABERABERABERABERABEQg\nrQj4Et5aorLXrVvHyu2llsxMcjKXmk0ZREAEUoLAhg0beH+BMZU5KSlhs4wUAREQAREQAREQAREQ\ngYQT4GGYl5olqtjEi3ZmfbO0GwuklWois8SZlV1qNmUQARFIOQIs/cArG2PfvJByDSnV4FWrVrEu\nY5rcypijwdofvFCzVCw1IANvuGQ91BrQkFKbwIs/eItKcUu9lnp6amXg7aQ8QrHWbGqZXQFrWYuH\nJ7E0mVTFa4N4gQ4LD1cAVMqdwq2JlZvSYWScN0nxMuM0uTWxWjYXcNTCWyl3cZbFYG5NNJZHxLJk\nTvU8uLFpQqJ0e+JFO9+u4cOHpzpl2S8CIlBeAs4HJl5bQLiNM6W8paVKfvPOyCZNmqSKwbtiJwtb\n0rOsRrkrhaTKuciANOlW3kjK6jZp0lhayvMTb4dJleuwwnbyZLx9+/Y06dZQKMR7c8oS41lhnslz\nIjKAazgd3trDzw3DxGlyDZtbE6+CSp4rrZIs4daUPr84vCE7gRg1pz2BMFWUCIiACIiACIiACIiA\nCIiACIiACCSSgER7ImmqLBEQAREQAREQAREQAREQAREQARFIIAGJ9gTCVFEiIAIiIAIiIAIiIAIi\nIAIiIAIikEgCEu2JpKmyREAEREAEREAEREAEREAEREAERCCBBCTaEwhTRYmACIiACIiACIiACIiA\nCIiACIhAIglItCeSpsoSAREQAREQAREQAREQAREQAREQgQQSkGhPIEwVJQIiIAIiIAIiIAIiIAIi\nIAIiIAKJJCDRnkiaKksEREAEREAEREAEREAEREAEREAEEkhAoj2BMFWUCIiACIiACIiACIiACIiA\nCIiACCSSgC+RhUXKWrx48cSJE3NyckotuUGDBoMHD27btm2pOZVBBERABERABERABERABERABERA\nBNKQQOI97e+8805ZFDusN23a9N5776UhdDVZBERABERABERABERABERABERABMpCIPGifePGjWWp\nODMzk2wbNmwoS+Ykz/PII4+MHz8eI//8888yNr+EFuXn5xOtEAqFSshT3CHbkuIyVFm6bUlCmFSZ\n2apIBERABERABERABERABERABJKKQOJFe1maV7du3UsuueS4444rIfN33313/fXXb9++vYQ81XjI\nFqW2DQUFBc8888yuxw4sWLDgn//855o1a+ySq2AntjkJqTRRTBJijAoRAREQAREQAREQAREQAREQ\ngZQjkPg57aUiQLEPGzasZcuW4XC4Tp06peZPlQx+v/+mm27adWu7dOny4osv7no5yVBCopgkQ1tk\ngwiIgAiIgAiIgAiIgAiIgAhUPYGq9rTbin3ZsmXPPffc1q1bS20z2n7atGnHHntsz549b7/99uHD\nh+OEZxsxYsTYsWP79u175JFHTpo0iWwU9csvvzAi0LVr19NPP/37778n8Y8//rjwwgsffPBBSmA/\nNzcXfzhnsb300kuBQMBpwMqVK0eOHNmjR4/jjz/+ww8/JEYdVz8Of6oz2QiDv/fee88880yMv+22\n26JiAWx/dWwtUWbYFTmNN1WQ87LLLiPMnp2LL774lVdeIU9ca4mihwbWDhkyxDSWEghHv+6660iE\nAxlIsY0B4EMPPWSYY+o999xz/vnnl9CcuEbOnDkTthCmfIICKJ8lDO6//34Kj2ukYWIwvvbaa5yF\nbVi4fv16cy5mmCaMGTMGniRqEwEREAEREAEREAEREAEREAERMAQqS7Tvvvvu+++/fxTlCih2SkDe\nP/7443fccQe69Kijjvr5559Nsd9880379u2/+uorgsnHjRuHyl26dOndd9+NRP/xxx9xeo8ePXrR\nokVkXr16dYsWLVC/e+65J3+Rmh9//DEL5lHCjBkzbCNZGI9aDj74YCqixrfffvvbb7+1j9o7WVlZ\nr7/+OuLzzjvvfOCBB2rVqmUfMjuMFMStxTajefPmTz75JBL3hx9+eOKJJ/Cr//7771GFmI+03ePx\nMHzw/PPPf/TRRzTQzobopfYzzjgDFY3wxmAyc5QBjr///e9Yvu+++7KMP8ZMmDDBNPmLL77AhsmT\nJ5tC5s2bd8stt1x11VVxm8PU+lgj4fnYY4/BFsJwRpBjxtNPP03EBCQZ0fjss89mzZplGxm1wyFG\nT+gyrPr888/5+8Ybb1DR119//fLLLzNGEJVfH0VABERABERABERABERABEQgzQlUimhHsaNp8cce\neuihNt+KKXZORx927Nixe/fuyFdCx9u0aWPKpHAEttfrxeuLcsbfS06UKmKYRPIfcsghKFgyt2rV\nauDAgbvtthtOZtQs7mWMadKkyYABA5yyHGXL8niDBg3y+XzUcuqppyJBK7Ag3F9//RW3FtsMgsYx\nAAG8bt06xh2eeuopu1GmafZf0rEnIyOjdevWnG680+YoXnQKOeigg2hshw4drr32Wj5yCK87Z3EK\nzUcG42Y/8cQTGdfgKFufPn2M+52cJ510EicWN0MB2uSPMpIRE2jDlkoPPPBAFiagoksvvdTsNGvW\njKNm7MBugnOHS4Jrg2IxGzMAxbjJKaecUrt2bRJ79+7tzKx9ERABERABERABERABERABERCBSpnT\njracPn06WvGEE04A8ZdffokkQ8Yzjx1FV8aoeLtvWMyMN7ojDu2U4nbIiRscyU0Gt9vduHFjI1BR\nmEhQElHgmzdvPu200+wSsDAvL88sZc9RTjc5ycDpDATgB7Yzl3Enbi2UY5uBhTjD33rrLeQuwvXK\nK68kdL+MhdvZ8JmzTzP5S4GoZftQ1A5Y8JnjdaftHKIjTAa7pVH5zce4RhrPv6mUHkG9k5mhAYIO\nPv30U8OK/bgFxiYCCvJcG7GHlCICIiACIiACIiACIiACIiACIgCBShHtlEsINH+NbkeY4SGvmGKn\nEFzBuIuZfG7UOCnFbXiw7ZyEXq9duzZKECJT8bcjX/FvxxbCUU5HSZpDnI4Dv9RK45YTWwsT1O2c\nVBEMBs8++2x8/suXLydGfY899ujVq5edoSw7uLXJRjPN3y1btpihh6hzqYjwdeyZMmUKQxJEsNue\n9qicUR/jGom3f/78+VSKbieDmR7/8MMP9+/f/7777oMVAfNR5ZTwkfx0GYMmJeTRoaok8M7ED5nz\nQY3nX3DmlVdewk5sysyZsy8ePqJZ86aPP/5A27atq9I81SUCIiACIiACIiACIiACaUigUsLjDUd0\n+7vvvsv+0UcfXWHFzumdO3eeO3cu06FRib/++msJmhPH75w5c3Dyo1SZsD116tR+/foZY8xf9D8e\n6TfffJPp64wCMEvcOacdJY+AJJFDK1asYE47U+iR/cyHJ8yeRNZ4Y1q4XSCOa6OZ7ZSy1EIeVmVj\nRT3mltMi3O9Rp5fxIzHwCHUmtFMIU+KvuOIKbI49l6Nkq1+/PgoZ+4ETm8ekRDUnrpHQI0IethRL\nUTfccANRFeSsV68eMp6uKWFCe2y9sO3WrRvrEWzbtg0jnVMVYjMrpbIJLFq0ZP36DTN/mDrt60lb\nt2zjY2xKTs6mF194/e3/vvjqq0898/RLfKxsq1S+CIiACIiACIiACIiACKQ5gUoU7ZC1dXsFouLt\njsG7y2JprLXGynY4ydGH9qGoHdaZw2vNmm2od2ZxX3PNNczZduZBuLJ8GrPZmeLODGrmwHfq1MnO\nQBA+Z6HPqYhJ2sxpZ+o1WpSZ2AwWsML5jTfeSMy8yX/YYYexdhpLssU6ikuuhdMZO0BjI9pZcf3c\nc8/FGBNnbltSlh0mh7PWOgvgUwitpsC2bdvGnogrmyZTF/aTjQEIE4wQlTO2OXGNpAoqghKVvvDC\nCxjA2MFFF100atQoIgVYlp+592V5I4CpHbZDhw5FujP9Hg6xJKOM1MfKJrBmzVouDyIy9j9gP1NX\nVMrChYvad9gLB3t2doN27dpu3JhT2SapfBEQAREQAREQAREQARFIcwLuskusMpLChxyVE0mGA7a4\nimLzR53ORzs2niXi8e6iFePGt8eeqJQkJ4DHHunOhp2E7jOJgBX1ktzm6jJvzZo1ccdlEm4P/vNJ\nkz4dOvRku2Q7hWh5Ek8abC3BwH7LVi169ephZ2PYxY49YSUL4jIaNmxoH62pO7zTgaCe8847r6Y2\n0NmuVatWsZgFI4bOxJq6T4QXcV41tXXOdvHDSrgTs7SciTV1n4gwBu5Z/bSmNtBuF6vMcHdKk4cl\nfh/xl6TJrYlox7333ts8ONndXSN3iIolCJRY3RrZuqhGcWtq1KhR1KzeqDw14yO3JhrLEuM1ozkl\nt4IYZ6Za2x7fkjOXerSy5rQ7Kzbz250p5drnMfHRRx+9/PLLcaSznDv3qUQ1vlxmKHNlEHj11VeZ\nIEBQA2H277//Pm+wq4xaVGbZCRAS/+gjT9x51032KbEp9qGoHe5NOOpNIpMmWKGwuKG6qBNT+iPv\ngMB+FqdI6VaU0Xi6mLUz6Nwy5k/pbMiAEgK7UrppUcazHip9ao+4RR2tYR/pVtwAxBPVsHbFNoc1\naPnCpkNLaTv3YZ4l0ufWRCxkOoh2Jk6yxV7bNTKFWxNqNh3GE82tKR1ayoW6YcOGBPrbEi/as7Oz\nWXS9jN8oMpeakxXXeDnZyJEjef3YAQcccPPNNxPHXupZypASBFi9f+zYsbyIjofjv/3tb7yELyXM\nrqlGos/HvT7+gQfvsJ/zolJwrU+b9o1pPhPgu3Xfx4mCmSz2R2bEcJ9iBUQ7pabu4N5hoYc0cWfx\nK4toTxN3FpEjadKteNoZX0sTdxbSrmnTpunwvIgA4O6UJtcw/kkai6Oypv7QONtFz7Zr167kFwA5\n86fuPp52hhSdjxap25ZSLefWhEsyTTztXL1pcmtiLKbUri97hsSLdgT2O++8UxbdjvbmpeKl2spo\nIu9jZys1pzKkHAFGbVgpgC3lLK95BhMD/957k0ZefRmKffUq6y6TVSsrKoV57OP/+x45Ocr89pNP\nsd7pqE0EREAEREAEREAEREAERKDyCCRetONeGzFiROVZrJJFQAQqgwAinJXh+UfhXbt2Hj3m/tgU\n1p9DqA844iTzyjc+VoYlKlMEREAEREAEREAEREAERMAmkHjRbhetHREQgRQiwJJyvO/NaXBsCkfj\nJjrP0r4IiIAIiIAIiIAIiIAIiEACCVTuK98SaKiKEgEREAEREAEREAEREAEREAEREIF0IyDRnm49\nrvaKgAiIgAiIgAiIgAiIgAiIgAikDAGJ9pTpKhkqAiIgAiIgAiIgAiIgAiIgAiKQbgQk2tOtx9Ve\nERABERABERABERABERABERCBlCEg0Z4yXSVDRUAEREAEREAEREAEREAEREAE0o2ARHu69bjaKwIi\nIAIiIAIiIAIiIAIiIAIikDIEJNpTpqtkqAiIgAiIgAiIgAiIgAiIgAiIQLoRkGhPtx5Xe0VABERA\nBERABERABERABERABFKGgER7ynSVDBUBERABERABERABERABERABEUg3AhLt6dbjaq8IiIAIiIAI\niIAIiIAIiIAIiEDKEJBoT5mukqEiIAIiIAIiIAIiIAIiIAIiIALpRkCiPd16XO0VAREQAREQAREQ\nAREQAREQARFIGQIS7SnTVTJUBERABERABERABERABERABEQg3QhItKdbj6u9IiACIiACIiACIiAC\nIiACIiACKUNAoj1luir5Dd2+ffv111//3XfflWzqzJkzhwwZcvTRR//xxx8l54w6unHjxjPPPLPU\n8qPO0kcREAEREAEREAEREAEREAERSF0CEu2p23cpafnmzZvHjh179tlnv//++61bt65wGxD8CPjy\nyv4KV5cmJ74z8cNePfvxb8yYJ02TZ86czcfjjjtj0aIlxaWkCRw1UwREQAREQAREQAREQASqhUAN\nF+1vvPHG/fffH0U2Ly9v0aJFoVAoKr0yPq5Zs2bDhg2VUXKpZeL3vvLKK6dPn15qzqgMnMKJnB6V\nnpCPgUDA5/P17NkzIyPD6/UmpEwVkhACyPL16zfM/GHqtK8nbd2yjY85OZtefOH1t//74quvPvXM\n0y/xMTYlIVWrEBEQAREQAREQAREQAREQgeIIJLVoRz3Widkqpid///33Cy64wOhn9q+77rpVq1YV\nB2UX023RW1BQ8MQTT4wfP34XCyzX6Xbt5TqrwpnD4fCkSZOOPPLIvn37PvXUU1u2bLGLWr9+/R13\n3IE+5+iHH37IKAmO8TPOOOPLL7888cQTCaRnXCA3N/fZZ589/PDDyXbDDTdwijn9kUcesbnFOtU5\nRAlz5szhr53Nrlc7FSawZs1aeiQrK2v/A/ajkIULF7XvsFfbtq2zsxu0a9d248ac2JQK16UTRUAE\nREAEREAEREAEajyB0QtWDJn+S/8vfhz548Il2/NqfHsrqYFJLdrRgVsj2yeffHLRRRetW7eOT2PG\njKlVq9au4Ojatevbb7+9xx577EohZTnX7/ejWv/2t7+VJXOK5vnpp5+efvrpf/3rX1OnTu3UqdOs\nWbNMQ+gpEvfZZ58ZM2aQ4c033/z222/32msvYh8OPfTQd99994EHHqAfX3/9dcZQ+Ei2li1bPvfc\nc7jiS0Vx8sknc8q+++7LX/ZLzZ+QDIxHEDcRd3MOVSSkrmopBHH+j5tGothxp+Ny5+PyZStb79nK\nGLP77rtt2LAxNqVaTFWlIiB3EfvlAAAgAElEQVQCIiACIiACIiACyU8AuT7ix4UTV66funbTqAUr\nOn4ya+72guQ3Owkt9CWhTaWatHz58rvvvnvChAmdO3ceOXLkCSec4PF4cNsi+R5//HFOP+ecc666\n6qq6deuaohCKw4YNY/+tt95C/zdq1Oiee+7Blzt//nw84WjFl19+uUWLFvfee++AAQPcbrc5Cx/y\nF198Qc5p06bh0b3rrrvat2+PpKTeBx98cOXKlaeccspNN93UtGlTIvDRqHPnzt1///05l5z8RaNS\n7H//+9+2bdtyOm7kXr164ZT+7LPPTjvttNtvvx0zWFkNM3BQd+/e/aijjlq2bBlC1x6SMIH9ixcv\npsYjjjiCluKvfuaZZ7p06ULze/fu7TTmsssuGzFixGOPPWbXTk7M+O233xjmcFYaFxSJ//73v0eN\nGkXhBx98sCHA5HNQ33bbbYSym5TYv1OmTGFJOfzkcEON2+f++uuv+GwHDRrEuRAALAvI9enTx1kC\nhE899VSi5U2TOYqpkGzQoIEzW5LsZ2Zmcj3k5ORE2ZOdnU3fRSWm7kei4h995Ik777qpAk1YsmQJ\nnW5OZPGChQsXMtBWgXJS65Q///wTg/mipZbZFbN27dq1fKPtiJiKFZIqZy1dupSB11Sxdlfs5Nu6\nLbLtSiGpci6/3bSX0clUMbjCdhLrR0Qhv7MVLiGFTuS3hgl31TUbsYpBcWuisfbDahXXXpXV4RHh\nmZAH1KqstLrq4ta0adOm2rVrV5cBlVQv+hy5bhXOvahIYT2xdG2X2mnx1ITQw2GZKLapJ9pRTTff\nfPMxxxyDPkflIpt33313tCKKHZ8tweE8ZiE+EZyoXIOJkGxUpRHqu+22G9lsfOwTb88hYrYRycjy\nNm3amKMUjo599NFHGRrAUfzwww8/9NBDaFTisZHiTZo0GTduHDrfSGs0Kvt47xkpINgbB7JTfpsC\nUa2Iap4VEPCffvrp6aefjqrnZ5Xwb35Wb7nlFtsqe4e599g2evRozMBOXNa33nrrxx9/zA7qGuc2\nxkycOBGVi1YnfODGG2+0ay+u0rigcFmDYvbs2UxHAKx5KMeJze2yBMVOFdxl7JEOfkIYPTH1Qo+R\nggMPPNBuixk3sT+yQ35+eF599VU4mBpxnlfNWgNOM8q4z3WFOOcCYyDDPoURH+JBasyTPYp93Ovj\nH3jwDvNE27JVi2nTvjGNxfferfs+7Mem2DQY+bK7jwsAOHzd7KM1dYfLmK//rqyqmEJkuBuwcctN\nIZsrbCp3vzTpVp4q0OxVEH1W4b5I4In82vLzXfOejGMR5efnk5gm1zCj6jgA8IXEcqh5KXxb6dZ0\nEO2IWIbYeJaoeZ0Y2yJuTVzAtrsxNkOKpixZv9m1YJ2l2F2FPlEastGXmSa3JtsRm5DuSz3RjkeL\np0Z819ygceEOHToUEYuC/eabb5gmjdsTLixOjn/YeMBKxoS/mmh5pOYhhxzC/i+//GKLdmpBgVAd\nKTiEjz32WLIhtocPH96qlRUzfNJJJ+F6xZ3IPl73vffeu+S6sMr8ohx22GGocW5GKEBsRidzItoP\nl35UCTjYzSmYhzxmTAGV265dO6Q+NzJjDEqJszCGkQIGAqJKiK00FhT6iuh0hjbsuiiKcniyiSqt\nXB9hwvAKGIs7i0gBJrSvWLGCUALUHYMaxB0UlzkZ0hHn9B29RvdhD5cfvZYMhiXEBqLi33tv0sir\nL0Oxr161hjKZxz7+v++Rzj6z2U8+5YSGDbOjUpxVOwcv+LLwFMXmzFAj902r06GldB9f50iv1vxu\ntRtbIy/aqEbRp9yNdQ1HYUn1j4g684VN9YaUxX6uXp4J0+capmdtH0lZ+KRoHjqUpaPTp1tpaU1q\n7Jdrcz75M+eJhStdYeS6O6LbC5W7eURM0cuyXGaXIILKVY7JnHqiPRgMMm6BdjUNQFjiJSAo13kF\n1K9fn4/lmmlMgRTrPKVZs2Z41/HYMy8dZ/s//vGPDh06mNpN1Xy10NuIZz7a9phDZfnLiAAllHFQ\nLbZ8xuQwhqkBdl0DBw7k7mZ/jLtDpXFBOdsV98TiEhkyIIAfY3g+4K/taKVfGO8gLMIof9LJwOYs\nh6EHxguYLGD8sdjgPGoX5UxMhn1bqNs7yWDVrtuALGeteP5RVNeunUePuZ/15xDqA444qVnzpo8/\n/gAfORSbsutVqwQREAEREAEREAEREIGUJrA6N392zpZvNvz11B+rVuaaiethv9tTgKPdsYraAbXT\nYupZwrsy9UQ78pX5LbbAw51OnBvOLjSeLVn/+uuv8g7OUSDFOiU0oWUNGzYk6J0AdaLi77vvPqLu\nTe2mG6gCb3mFp8YxKozZts3l7VoEMMZMnjwZJ3zZz0WxxwXlbFfZSyNn//7977zzTibzE7CA559g\nATz2pBPoDsyXXnrp8ssvp0bGPoiGIFrBWTiVMrzCWcQOMPLC3H77KNENBFAw64HOZQpA7BxaZgQA\nkHRCOqt+YLKGyXWDvVevHrzvze6C4hLjZos6Sx9FQAREQAREQAREQATSgcCSrbnjV6x9f/WGz/60\nYjMjW/joJg1PatHorNZNmNM+YvaCTYFCz9yhu9U7v1HNX1WkiEMi/3eMeySy2Eosq2PHjshp5mAT\nzoeflonleJiJ62b6NEuv4dpFe7PgHBIxaoYe3vjY1SxY/Jz5qKjKr776ipXPUZ626cS9X3jhhQsW\nLEAeo3VJRxwyf5v55NRL7SwLh6TEHvsUewePPW5k+2PcnXr16vXo0eOVV15h5iT5CbqOm624RIw5\n6KCDXnzxRcLLsR+1zOR2dshfQu1o3VhQrJHAInAs18dSLiAChamUARETB16cDaR369aN+QLM0u/X\nrx+T8/fbz3pVGBsVMdjBslWMKTAVnGkLhPqbQ/ZfgkZYPw/hzSEys6AdKWYaHmsWEHzOOnaE98Of\n0RP7LLND+eS/5JJLnFI/Ko8+ioAIiIAIiIAIiIAIiIAIJJzA/C3b7/h18QGf/tDmo2+v/mkRir1z\nvdp/a9v0nq5t1p940OTDul3evkW233dB66azj+o15bDuz++/N38/OXif+t7Uk58Jp1eBAlPP0478\nQ+CxfDrrzJnV45lmjK5jnTOWWDMuUFaP5yiOXJsI61ggTfHcsqScUwEyO53125gQztH/Z+9N4KOq\nzv//mw2yTTIzmZnsCUlYRLBsVvSrVRRBERULiGJrtYtYq6V+20q1v39p6/9Xa7F2oai1LsVWi1pF\nwA1QERRUUBCRRYQQsk1mX5LJvszvM3OTyzhZCZPkzr2f+8prcufMueee531ubuZzn+c8B7ncCgoK\npEOwgBnk6J133gk9DPWI8HicGg8IIGsxWxszzPGKJPDijHTpKOwgih79gVcZijq0PGwfdW655RZk\nmMNkeDxiQAdOd+bDN7/5TbSJV2TtxitS2eHhgnR2PFwIOyPe9gYKOQIg0fEQAeHu0MmiUXBx95s9\nHg2CCbbu50JgPLLxYQv9CPAfe+wxqQQZrZCKX3qLDAXiPjqA2f7YpI/EHXGyPfbhZr85uIVV4FsS\nIAESIAESIAESIAESIIGhIPCBw/unY1UfuurMjYFsl8gLD61+c0HmDQXG4pSe1+Qek5yIH3j0UFt0\nzgUP5MvpEYiBm/f0jlBQbTi3IQKhKiOb3G/ghOAYh+jFhkPg6IZXH8nwxbcDb4Q1VUIAS8Qj+iBa\njMXaAXgGpIbs8cjpsHXr1mXLlkXL0JxJP/GwEjE+Kskej7ykkyYFVkxQ/IbZSfgmoJIUzQgfw0Kt\niJJT/LDimzEe6OM5vuIthYEWiwWP8sVkuoq3F/Gh8CqJEaDKNhZTUDHdVcz9rGxLYR1uTUajMXSW\nrtxM3mR2/qvcEqLVhZn6tGtz9DcVmIKCfKD9xa0JxvabvXugzcm7Hr66408VIxuRbkafpz0iZsuk\nkX/+85/4NwP3MkLEEdwuhoLLpG/sBgmQAAmQAAmQAAmQAAmQgDoJHPD4Xq52vGl1fezySQTmmLQL\ncw0/LAmsXcVtOAlQtA8n7fBzYSF0rMGONGx4PPzjH/+4xyDz8GP4ngRIgARIgARIgARIgARIgAQi\nTaDd7/+8tv6VKscLlbajvqZg8/7cpNFnY756cfaSvMg4jSPda1W0p2rRjgnw4hz4kRpqTPDGrHhs\nI9UBnpcESIAESIAESIAESIAESEDNBBrbO16utm+zerbY3NJk9Zk6zXcKs67K0Z9WALyaMQ6p7aoW\n7UNKlo2TAAmQAAmQAAmQAAmQAAmQgDwJwK/+eo3rr8erQlZrE87Xa67LybjhNCery9NAJfWKol1J\nozkCtqxcuXIEzhoNp8Ty9dHQTfaRBEiABEiABEiABEhARQQwWX1jjXO/t/4jh9fcFFijOjdp1Pzs\njNkmLQPgZXsdULTLdmiio2OUptExTuwlCZAACZAACZAACZCAigkcrq3/b5V9XYU0WV1IjYu9Ps+4\nrCjr8kydisFEh+kU7dExTuwlCZAACZAACZAACZAACZAACQycAALgD3nrkQQ+NLGcuLL61/UaavWB\nkxzxmhTtIz4E7AAJkAAJkAAJkAAJkAAJkAAJRIYAtPq6Slv3xHILcgxLC09vZfXIdIitnDEBivYz\nRsgGSIAESIAESIAESIAESIAESGBECbR0dLxYZd9Q7dhq9dS1tYt9YWK5ER2TiJ2coj1iKNkQCZAA\nCZAACZAACZAACZAACQwnAUxW32b3brO53+7S6pr4uCX5hkW5RiaWG86BGNJzUbQPKV42TgIkQAIk\nQAIkQAIkQAIkQAIRJnDU1/iG2fH4iZqjviax6ZykhKuy9YtzDYvzjBE+GZsbaQIU7SM9Ajw/CZAA\nCZAACZAACZAACZAACfRHAAHw/z5pfd3q2u2qMze2BKv7Z+o03zBqb8g3nqvT9NcAP49WAhTt0Tpy\n7DcJDAUBj8d78OCRiy46X2x89erHn1m7DvsrV65YcN1V2Nm7d/+y2+7Oys5cs2ZVUVHhUPSBbZIA\nCZAACZAACZAACUgELE0tmKy+yex4x+btKgxo9WtzDTfmG4tTkroK+VuxBCjaFTu0NIwETpeAKNGh\nz8UDoc+xs3ffdrw+/dSzZWXlOp0WGv6ll5/BzkOrVt+zYrlWmy5W5isJkAAJkAAJkAAJkEAECSAJ\n/COl5sdKzV/UNYrN5iaNujpbPzdTvzDXEMETsSn5E6Bol/8YsYckMEwEli+//cILZ1ZVmsXz6fW6\niRMniPv5BXnYKS0tGzuuWHSwl5QUud0eivZhGhuehgRIgARIgARIQB0EkFjuv1X2nc7aw7UNwRh4\n/0RNyjU5+hvyjNMZAK+Oa6C7lRTt3ZmwhARIIEAA4vzAZ4dmTJ91y61LCwvyxbfYEelkZOhdLjcj\n5HmtkAAJkAAJkAAJkMAZEoBTHVq9rL756XLL+iqH1BqSwP9+chED4CUgqt2haFft0NNwEuiHQFNT\nU3JKMsLjETZfXlHZT21BcDqdra2tYrXm5ma73S697ffY6K3gdrvReavVGr0mDLznDodj1KhRbW1t\nAz8kemu6XC6VDKvX621sbExISIjewRp4z3GbiomJSUpS/vzPlpYWGJuWljZwONFbE7em+Pj49vbO\nVamj15CB9By3JpvNhst4IJWjuk5dXZ3P58M/nai2YiCdP1zf/GxpzWsHzLbWzms4c1Tc93P0s/Up\nk1JGB1rw1Vp9tQNpSv51xFuTSv694tZkMpkiNSgU7ZEiyXZIQGkE3n//o7Fji2AVwuY3bngDU9zz\n8nN27dot2ul0ur42ZVKozbHBTSzx+/2hb0OrKWwfZsIi8VVhpnU3RxxTlRiL78QqsRRmqsdY0VI1\njCxsFLfuf8jKK4GlaruGYa/yxjHMIsUP65cNTdtc9etttfvrOhdsm65JnJmePCZp9HdztGE0FPO2\n88YU/O6kGKN6MyQuLq63jwZRTtE+CGg8hARUQaChvgHh8WIAvCjRkX9u/cuvIsM87Mf89oWLrgkF\nodPppLeJiYkZCKDX66USpe7U19fDNKNRFQuiInRi9OjRGFmljmaoXfBlqWRY4aLEH6xKjIXjzmAw\nJCcnh461IvfhzmpoaFDJsMLHjssYI6vIoQwzClFssBTKJ6xceW/hY0cEkMKuYSzY9vcTNUgCf6Su\nsWvBNmGiJunq1IRbJxScbVD+tybcmnAfVtiw9vbX19HR0dtHgyinaB8ENB5CAsokIC3wtmfP3l+t\nvAdrvKEEc9phLVLKi+odQn32ZQvEJd+YhU6Z1wGtIgESIAESIAESiBABTFZ/zeLa6fDu9/h2O+vq\n2gIx8Jr42Jm6VGnBtrKyMmOi8icCRIioSpuhaFfpwNNsEuhOAGHw+Akt714yY8ZUcRG40GrcJwES\nIAESIAESIAESkAjAqf58pX27zbPF6jI3dWb8yUlKWFpg+sWEPCaWk0BxZ4AEKNoHCIrVSIAESIAE\nSIAESIAESIAESKBXAgc8vnds7vedtW9bPV1O9ThkgL/UoD1XrzmXC7b1So4f9EOAor0fQPyYBEiA\nBEiABEiABEiABEiABHojcMjre/Kk9cVKm+RURwD8suLsRbnGuZmKzSrXGw2WDwUBivahoMo2SYAE\nSIAESIAESIAESIAElEzA3tzyQpVjQ7X9HVsgRy+28/Waa7MzrsjSTadTXSTC1wgRoGiPEEg2QwIk\nQAIkQAIkQAIkQAIkoHQCyC332ImaV6rt27q0em7SqP/vrIIbC0zaBGorpQ//CNnHC2uEwPO0JEAC\nJEACJEACJEACJEAC0UBAFOp73XWHa+v3uHxil6HV52dn3FaUxcnq0TCG0d1HivboHj/2ngRIgARI\ngARIgARIgARIYCgIWJpatlrd+zx1/61ySCurIwn8RYb0e8bnU6sPBXO22SMBivYesbCQBEiABEiA\nBEiABEiABEhAjQSO+hqfr7BizbYv6hol+5EE/rYx2UgCzxh4iQl3ho0ARfuwoeaJSIAESIAESIAE\nSIAESIAEZEoAWn2LxfVshfXjrgD4iZrkbxjTZ5u0czN11OoyHTZ1dIuiXR3jTCtJgARIgARIgARI\ngARIgAS6Edhh9zxz0rrF6pIWbJuoSbq5IHNpoWlMcmK36iwggREgEF9ZWTkCp+UpSUDpBPLz85Vu\nIu0jARIgARIgARIggagkgMnq6yqsb1jdVQ3NUgz8TF3qN4zaO0qyi1OSotIqdlq5BOIpLZQ7uLSM\nBEiABEiABEiABEiABEggQAAZ4N+wuN6xuXc5aj9xd2aARzm0+veLc67PMzAAnheKbAkwPF62Q8OO\nkQAJkAAJkAAJkAAJkAAJnBEBaPV1lbZtVs9L1Y66tvZgW35MVr82OwMrq0/Vpp5R6zyYBIaFAEX7\nsGDmSUiABEiABEiABEiABEiABIaRwIfO2q1W1z9O1IiT1TXxccgAf7lJT6f6MA4CTxUZAhTtkeHI\nVkiABEiABEiABEiABEiABEaWgL25ZV2lfZPZscflk/zqS/KNi3KNS/KMI9s3np0EBk2Aon3Q6Hgg\nCZAACZAACZAACZAACZDAyBNobO94oqwGWv0dm1fsjSY+do5Je6lRe3tJtn5Uwsh3kT0ggTMgQNF+\nBvB4KAmQAAmQAAmQAAmQAAmQwEgQwGT1nQ7vBrMTr1JiuZykhKuzDbcXZU3XaUaiUzwnCQwJgdgh\naZWNkgAJRCcBj8e7c+dHUt/x9pbv3DFj+qyNG94QC/fu3Y+38+ffUFZWLlXjDgmQAAmQAAmQAAkM\nGwFXS+vDX1YVvLF71o4DfzlW/Ym7Ljdp1O3FWXtnT6uef8Hj08dRsQ/bWPBEw0OAnvbh4cyzkEAU\nEFi9+vFn1q5buXKF2NempqbHHn36N7+9V6fTPrRq9SWzLkQ5Krz08jNiyT0rlmu16VFgGLtIAiRA\nAiRAAiQQ/QQwX33NcfMWm/uwt0Gcrz7XpF2cb5qTqR2TnBj99tECEuiVAEV7r2j4AQmojcDy5bdf\neOHMqkqzaHhNjTUz01hUVIi3v3vgV3iFm33suGKxpKSkyO32ULSr7SKhvSRAAiRAAiQwnARaOjpe\nrLJvqHYc9NYf9TVJp0Ye+D+cU0ytLgHhjrIJULQre3xpHQkMnoDL5cbBCI8/ePDILbcuhaSHni8s\nyBdbzMjQo4Io4MWS5ubmjo4Ocb+9vR2O+sbGRvGtgl9bWlpgnRoshZkYU7/frxJjcT2rxFKYqZK/\nVvEahr0xMTEKvimJpuHWpJ5rGBdwfHy8Sv5gMaywVw3XcHmtb12lc/1B85f1zV1/sP7xKYlL8ww3\n5mYUJo0OFirkX5J4E46Li+uyVLG/1XZrSk5OjtRYUrRHiiTbIQGlEYBE37Fj119XPwh3OiLn4Wbv\n20KbzYb/OmId7FgsFjV8hXI6nTDZbO4MT+gbUbR/iiEePXq0NMrRbk7f/bfb7enpqpj9UVtbqxId\nixHHsOLZYmKi8sNoW1tbYWxSUlLf17kyPnU4HFA7ULPKMKdvKzCsGo1GwaL947rmLd7GvQ0tn9e3\nBlH4ixPjJyQmXKlNnq/rup7dTnPAraCcDcPa1tYWQYEnWzTirSklJUW2PYxgx1wu15gxYyLVIEV7\npEiyHRJQGoG8/JyFC68RA+ARNg/zULJr127RTqfT9bUpk0Jtzs/vdMKjsLKyEvcpvV4fWkGR+/im\n+Pnnn5eUlCjSujCjIAAg2jMyMsLKFfkWzyZUMqxut7u+vj4vL0+R4xhmVGxsbGZmphq+GcOdhbuT\nSq5hCAB42g0GQ9hwK/Itnk0UFxfjSlaSdZamlpeqHe/aPR85a82Ngfg1QfBPSE2akRz/u3PPVkMA\nPAbUaDSmpqYqaVh7tAW3JjxyUsmtKbIDStHe4xXFQhIgAUGv1yHtHPLPQbd/tv/gpZd9A/nn1r/8\nKlLKg05padnCRdcQEwmQAAmQAAmQAAkMggAWbHu9xvXX41XbTq2sHofEcgtyDFfl6HWtzYgDymd6\nuUGQ5SFKJEDRrsRRpU0kMCgCYvZ4HLpnz95frbwH89UxlX32ZQtQgpTy4vR1CHWUZGVnrlmzilno\nBoWZB5EACZAACZCAegkcrq3fZvdut7k/hF+9KRADj9Xars7WL841Xp6pk7h4vaqY7yDZyx0S6JsA\nRXvffPgpCaiIAFLN4SfU4Bkzpu7dt73vktBPuU8CJEACJEACJEAC3QmU1zchBv6JE2YpA7wmPu76\nPOOyoqxQrd79QJaQAAmAQNSL9rKysscee+yXv/ylVquVRhRpZqqrqzFvbdSoUVIhd0iABEiABEiA\nBEiABEiABIaNwPt2z3qz880aZ5dW98/UaS4xaWeb9HMzT311H7b+8EQkEKUEhkS019TU/P3vf//s\ns8+QF+Siiy66+eabI5646NFHH0XWnGuvvbZH7khx/Ic//OGuu+4666yzeqzAQhIgARIgARIgARIg\nARIggYgTwGT1R0rNr9Y4D3vrxQB4JJabqEm+Njvjh2Nz1JBYLuJI2SAJRF60I2nEX/7yl7lz5/7q\nV7+Cx3vTpk1//vOf4QkfzmStWVlZa9as4eiSAAmQAAmQAAmQAAmQAAkMAwF7c8sLVcEk8A6vpNXn\nmHQLcw03Fpi0CZEXHcNgFE9BAjIhEPm/H6xajOUozjnnHLjZYeTll19+7NgxFK5duxZvEbV+8ODB\noqKiW2+9dXtwgxN++fLlU6ZMwfqEW7Zsee655xoaGqZNm/ajH/0Iix/gkCNHjjz++OOlpaXZ2dl3\n3HEHjr333nvRDj7at2/f0qVL29vbceDGjRuxisDi4Obz+R544AFURh2o9/POOy/0U3QMbT7yyCNY\nlWrq1Kl4svD1r3+9N6c9WuBGAiRAAiRAAiRAAiRAAiTQncBRX+PzFdb3HF4pCTz86kvyjb8Ynz9d\np+lenyUkQAKDIBB50Q5pjaUy4V3/7ne/i5UkMdX8vvvuE3tWVVX1s5/9TKPRPPnkk6tWrYIrHnL9\nvffee/7558eNG/fhhx++9dZbf/zjH3E4/PMIgP/FL34BtQ+//S233HL++ecfOnQIUfc///nP8SqF\nx2NOO4LhsRgpHgqcPHny4Ycfnjlzpk53Kvlk90+xdvQTTzwBlY4HCsePH//d734H0T4IdjyEBEiA\nBEiABEiABEiABNRGAAHwOx3eteVWZIA/Wtcomt9jEni1kaG9JDBEBCIv2hMTE6Gr3377bcwq93q9\noXPaIbzFye0QydDS8JnHxsYWFhbCVY6g+g8++ABu8pycHJg6Z86cTz75pLy8HA72CRMmQIej5uTJ\nk2fMmLFnzx4cGIoDjwkgv5FzrqCgAPtutztUtHf/FOeKiYm54IIL0CYOCWsttGXukwAJkAAJkAAJ\nkAAJkAAJgACyym13eE/WN222us2NLUEmgcRyWFn9hgJjcUoSKZEACQwRgciLdnQUuv3q4AY/+fr1\n63//+9+vXLky1AA4xkPfivuQ7tK899GjR6OR+vp6xMxjR6wPpQ0nPNz13Y89rRKcCN7+hISE0zqK\nlUmABEiABEiABEiABEhAbQQwWf3Zcuu6KvvHLp9oO1ZrW5JvmJupX5Rr4GR1tV0PtHdECERetGOi\nOvLG33777RDb8KsvWrQI8edQ7/2aB2WO2exiNcyKx7x0OM8x/7ypqQkyG5/6/X6HwyEJ+34b7K0C\nmsWzAExl760Cy0mABEiABEiABEiABEhAtQQQAP+axXXA49vvrV9f5RA5zNSlfjPXME2XxtXaVHth\n0PCRIhB50Y7Z6evWrcME9W984xuwCgIeCjwlJaVvC6Hw/+d//uell17CNHiTyfTuu++iBPsIdEcO\nud27dyO0HgntsIPYe7Ep+OEh4/tutsdPERKPBwE7d+5EUH1FRQVmxU+fPr3HmiwkARIgARIgARIg\nARIgAZUQsDS1vFhl3+HwvmVx17W1i1bnJCVck52xYkI+A+BVchnQTBkSiLxoz83NRTD8P/7xj7/+\n9a8weNKkScg2Bx3er9se7ywAACAASURBVPGXXHIJtDQ0uZg9/ic/+Qmc6tjuvvtuZI9HjD1mpyMh\n/NixY9EUFD5S2SGN3PXXX99vy2EV0tLSkJp+9erVSCCPRwxJSZyBE0aIb0mABEiABEiABEiABNRC\nAH71V2tca0/WIAO8qNU18bE35BunpafQr66Wi4B2yptADPzV8u7hkPROjLdH03hM8OCDD86fP58J\n5IcENBuNHAGr1RpFSRO3bduG9RSxUkPkAMi0JSxasXXr1mXLlsm0fxHtltlsRsIRMZ9oRBuWY2NY\nrwQPneXYs0j3Cdlb8U0gLy8v0g3LsT3E1mVmZsIfIMfORbRPWAQX2XzhmYhoqzJtzGKxYDYl0h7J\ntH8R7dbhw4fPOusspFKOSKvwq2+1urfbPFtsnYnlNHFxNxUaf1CUfe5Ir9aGbNZIHZ2fnx8RS2Xe\nCG5NWOg6NTVV5v088+7h1gRjkWX8zJuSfwv46o4/VXEJ8zPvbeQ97Wfep6FuAd9OsIwclnzDF7L9\n+/fX1NSIKeuH+rxsnwRIgARIgARIgARIgARGlgBmqv+z3LrZ4vqia7U2MbHc9bnGxXnGke0bz04C\nJNAjATWKdkywX7hwIULusZ4cQu7vvPNOhPT3SIeFJEACJEACJEACJEACJBDtBBAA/1yFbZ+nbovF\n3aXV/RM1Kdfk6Geb9OfpU5kEPtqHmP1XNgE1inaM6MSJE+FsV/bQ0joSIAESIAESIAESIAGVE4Bc\nX32s6o/HqrtWVheQBP47hVk3FZoo1FV+bdD8KCKgUtEeRSPErpIACZAACZAACZAACZDAwAm0dHRs\nsbo/cdXtcnr3uHxibjkklluYi8XVddTqAyfJmiQgEwIU7TIZCHaDBGRBwOPxHjx45KKLzg/tzcYN\nb+Tl58yYMRWFe/fuX3bb3VnZmWvWrCoqKgytxn0SIAESIAESIIERJPC+3bPe7AydrI7OIA/8knzD\n7ycXccG2ERwanpoEzpAARfsZAuThJKAcAqtXP/7M2nUrV64INamsrPwfTzxz//33oRCSHhVeevkZ\nnU770KrV96xYrtWmh1bmPgmQAAmQAAmQwHASQPT7Bw7v2mBiOXNTa/DUgcnq52iTLzVoz89Im6pV\nfk7y4QTOc5HAiBCgaB8R7DwpCciRwPLlt1944cyqSrPUOayJ+OQT/5I86qWlZWPHFYtvS0qK3G4P\nRbvEijskQAIkQAIkMGwEoNXXVdo2VDu2Wj1i9Lsg+OeYdNflGDhZfdhGgScigWEjQNE+bKh5IhKI\nPgL/+MczCxddI8l47BQWdK6YmpGhd7nckp6PPtvYYxIgARIgARKINgJNHf5HTtS8a/e83aXVsVrb\n9XnGy4zpNxYwsVy0DSf7SwIDJkDRPmBUrEgCKiOAwPjLL5919tkTJNHeN4Dy8vLGxkaxTl1d3fHj\nx9PTlR88b7PZYPLRo0f7hqOMT+12+6hRoxwOhzLM6dsKXM/x8ar4F4m/Vvzl1tfX9w1EGZ+azeba\n2trExERlmNOHFa2trTU1NR0dHX3UUcxHTqczLi4Or4qxqLshx5vbdtW1bKtt+qy+uUkIWJocK8zT\nJl6ZnnhF2uhA/bY664k6a/cjo7bE5/PhvtTQ0BC1FpxGx3Fr8ng8ycnJp3FMdFbFram6ujo6+37a\nvXa73SUlJad9WC8HqOIbSS+2s5gESKAvAgc+O3T//aukGpjrjnR0u3btFkucTtfXpkySPsVOTk6O\n3+8XSyorKwsKCvR6fWgFRe7jm+KRI0eKiooUaV2YUaODW0ZGRli5It9Cx6pkWPGtAt+M8/LyFDmO\nYUbFxMSYTCY1fDNuaWmJjY1VyTWclJSER2wGgyFsuKP9LQLgP3TW7a9r+E+lba+nU7sa4+O+nWv4\nbmHmuUqfqe71evFIUT23JlzAqanKzz6AWxP+MFVya4rs/xqK9mi/pbP/JDBUBBZcdxV+0LqUPR6J\n6Na//CpeUYj57YicDz13QkKC9BZSFi5ZbFKJUndEZ6waLMUIBodUFcMKY3E9q2dY4fpQibHisKrK\nWKXee0PtwoDiVqyYYYVWP1rXsN3h/d3h8q7EcsJETdK12RlL8o2JNZVnnTUBT2RCCShyHwOqnvsw\nb01KvYYjaBdFewRhsikSiG4CYvZ42LBnz95frbxHjCCVCuFph4aHUJ992QJxyTdmoYvu8WbvSYAE\nSIAE5EQAcv2RUvMfvqiQtPpck3aWUbs43zAutTNw+nCNnHrMvpAACQwXAYr24SLN85CA7Akgezx+\nwroZVojV2vfu2x5Wh29JgARIgARIgAQGQeCAx/dytWOz1YW5G7uddcEW/Ofr0/4nI21elv7yTN0g\n2uQhJEACyiNA0a68MaVFJEACJEACJEACJEAC8iUgavUXKm1HfU1SL3OSRl2dnfGLCXnFKUlSIXdI\ngARIAAQo2nkZkAAJkAAJkAAJkAAJkMCQE7A3tzzwReWbNc4ure4/Oy3lOwWmGwpMY5KVv6jBkPPl\nCUhAuQQo2pU7trSMBEiABEiABEiABEhgRAlYmlperLLvcHgrG5o+dvnEvswxaS81apcWUquP6Njw\n5CQQPQQo2qNnrNhTEiABEiABEiABEiCBaCDQ0tHxfKV9Y41zfZVD6m9u0qhvFZjuO6tAm8Bv4BIV\n7pAACfRPgLeM/hmxBgmQAAmQAAmQAAmQAAn0S0DU6hvMjretnrq2dtQXhfock45Z5fqlxwokQAK9\nEaBo740My0mABEiABEiABEiABEigfwJiYrmdTi8C4EWtnpOUcFW2fnGuYXGesf/jWYMESIAE+iSg\nStH+5nLhxBYhPklobRRKrhTm/bVPRPyQBEiABEiABEiABEiABMIJHK6t32b3vmv3dMXA+3OTRkOr\n/2BMFv3q4bD4ngRI4AwIqEy0tzUJD2cKHW2niB1+Xvj8X8JPLUL86FOF3IsGAidPnrz//vv37Nkz\nZsyYu+6664orrsAap1LH29razGbzu+++u2vXrnvvvbe4uBgfNTU1Pfvss0899RT2f/jDHy5dunTU\nqFHSIdwhARIgARIgARIggb4JIAP8mxb3JrPjQ1edubFFrIwY+DuLc5hYrm90/JQESGDQBFQm2sMU\nO7C1BNN4/ilLWOEeNEQeOPwE6uvr//a3v82fP//JJ588fvz4r3/9a8jy8ePHSz1544033nrrrYsv\nvrixsVEqfOWVV1AZ5c3NzQ8++OBrr722cOFC6VPukAAJkAAJkAAJkECPBKoamp4os7xpdUkZ4DXx\ncUgCP02XOtukn5up7fEoFpIACZBARAioSbQjKj7Uxx7KLzZB2Hy3cOVfQsu4L2cCVqu1rq5u1qxZ\nsbGx48aNmzFjxtGjR0NF+7XBze12b9u2TTQEQv3AgQPXXXddanBbtGjRxo0bIftHj2aQhZyHmn0j\nARIgARIggREjUN3Y/JbVs6nG8Uq1U+wEnOrzszOuzzUwAH7ERoUnJgH1EZC3aP99SgRHBJHT/t6a\na61vPrzxU+2NvX3O8uEhcP755w/wRFDjWq02KSkJ9REVD+ne2tra97EdHR3t7YE8ruJmMpk8Hk9D\nQwNFexcS/iYBEiABEiABEhCwsvq6CusbVvfh2gYpAB6J5W4pyFpWkj0mOZGMSIAESGCYCchbtEcU\nhh+S/dSU5/CmO2Lpbg1nIuf3UODoXugk9n57C4U/bdq0DRs2TJ48GZXXr18P0d7vUaxAAiRAAiRA\nAiSgBgKN7R1v29xry61dWeVgtH+mTnOJScsF29RwAdBGEpAzAXmL9vvqI8nukQlCbVVvDSaPihm4\nm7e3Rlg+bATgWse5/IEnMaexIWS+uroaE90LCwvnzZuHafCJiXxefhoAWZUESIAESIAEFEYAieW2\nWN3rq78SAH91tn5ZUfZ0nUZhxtIcEiCBKCUgb9EeUagxJfP8nz7Rc5MJKf6SeT1/xFJZEsjIyMCc\ndiSZS05ORqJ4pIVPSEjot6cpKSk/D26ouW7dOkh3McC+3wNZgQRIgARIgARIQEkEDnl9D39Z/YHT\ne9TXJNqFyerzsnTn6dNvK8pSkqW0hQRIQAEEVCTa/cgzd+AZob1zcY6vDJ6/XbjiT18p4Rt5EzAa\njZDr27dv/+Y3v3nixIkjR47ceGMgJUF5eTlWccvOzu6j+1D4yE73+uuvP/DAA31U40ckQAIkQAIk\nQAJKItDS0fGm1b2h2vGhs/Zonbi4jP8sTfLFRi0TyylpoGkLCSiPQCDGWEXbTy0xcaOFhJD8dtiP\nTxT+t0ZFEBRhKnzmP/7xjzdv3jx9+vSf/vSn3//+94uKimDZpk2bsK5bHyZiKjtWdMfq7qtWrSoo\nKOijpjo/8ni8O3d+JNm+ccMbM6bPws/q1Y+LhXv37sfb+fNvKCsrl6pxhwRIgARIgATkTGCT2bnw\nw0OGTR9et+vQ2pNWKPaJmuTHpo11L7jwyBVff3z6OKaCl/PwsW8kQAIq8rQHBjt+tH+FK2bL//qP\nvwmtHtPeHIiKp489Ov8OxowZ88QT4fMdoORDrdHpdI899lhoCRZm59rsoUBC96HMn1m7buXKFWIh\nZLnT6dq7bztiE/78p8fwVqfTosJLLz+DnYdWrb5nxXKtNj20Be6TAAmQAAmQgEwIiJPV37V5djk6\nY+A18bE35BsXB1dr0yao7DuwTEaF3SABEhgUATXesPxX/FnATx8rwA0KJQ8igWgnsHz57RdeOLOq\n0iwZYrXaodiRru/cr09DYWlp2dhxxUVFhdgvKSlyuz0U7RIr7pAACZAACYw4AQTA//1ETWVj86fu\nunds3q7++JH+fVlx9uI8Y1cJf5MACZBANBFQo2iPpvFhX0lg5AhAnN/3y//F+REzD5f7nDmzDnx2\nqLAgX+xRRobe5XKLAn7k+sgzkwAJkAAJkECAAPzqD3xR+WKVPXRl9auzDbNN2rmZOvrVeZWQAAlE\nNQGK9qgePnaeBIacAKLi//ynR+///3/Z75kcDkdLS2eiRyT2t1qtzc3N/R4V7RVcLhdMqKlRRV4M\nu92OZRqkUY72seu7/7ieVTKsXq8Xf7BxcXF9A1HGp7iGsVaoGtYNwd8pjE1NTVXGwPVhxeH65s1V\n1p2N7QebOnztHai5wJi62JCWMSpuaqq4qmtbo8MuJp3ro51o+Qi3JovFEhMTEy0dHnQ/sUiQz+eL\nj1eFVMFfa3t7OxI2DRpXtByIWxOu4bS0tGjp8Jn00+l0ZmZmnkkLoceq4i8h1GDukwAJDJwAFPvz\n69aveui34oL2efk5u3btFg+H7/1rUyaFNoX/rPg2LJbExsZC3WELraDIfVHqqMFSDB+GODiqyh9W\nyVhFXrRhRmFMW1tbVXINixewGozF3Vj8gw0bbmW8bff7d9c2Pl/jftfdYGluFY3KGh1/a67ufwuN\naXFKzrIsDqsaRDssFY1VxkXbtxWqujXhi5MabsIYcVzAfY/7aX0aybZO68SsTAIkIHMCiIp/9dXN\n//vTO6DYLTVW9Bbz2Ne//CrKsY/57QsXXRNqglarld6OHj1aH9ykEqXuwA8A0wwGg1INDLULD8gx\nshkZGaGFSt1HqIhKhhXfnzCsKjEWvjtcwFgxVKnXrWQX/lrr6+sVNqyWphZEv79n93zoqpNi4M/X\nay5LS5xj0MwakyeZr+Adm82GaxhPxhVso2iaqGMVdg33NmrirUkNoTG4NcFYlQwroid6G/FBlFO0\nDwIaDxl5AitXrhz5TvTZg/vvv7/Pz+X4oZg9Hj3bs2fvr1beA1mOXPH4QcnkyRP/uvpBpJ2DUJ99\n2YKs7Mw1a1YxC50cR5F9IgESIAFlETjk9b1j924yO6TEcpr4uOvzjIvzDEuCieUQLh5Zj5ay+NEa\nEiABJRCgaFfCKKrQhmiUxPIfJmSPx4/UzxkzpmK9N+mtuNNjYVgdviUBEiABEiCBMyHga2vf6fB+\n6Wvc4fCur3KITeUmjfpWgWm2ST8381Rg15mchceSAAmQQLQQoGiPlpFiP0mABEiABEiABEhAyQQO\neHwvVzved3jftUurtQnQ6ncW51yRpZuu0yjZeNpGAiRAAr0ToGjvnQ0/IQESIAESIAESIAESGGIC\nWK1tXaX9sVLzF3Vilnf/RE3yOdqUKemp5+rS6FcfYvxsngRIIAoIULRHwSCxiyRAAiRAAiRAAiSg\nMALv2z3b7B741bsmqwe0+s0FmUsLTWOSxdXaFGYxzSEBEiCBQRKgaB8kOB5GAiRAAiRAAiRAAiRw\nugQ2mJ3/rrB+5KyVMsDnJCVcnW34xYS84pSk022N9UmABEhADQQo2tUwyrSRBEiABEiABEiABEaM\nQEtHx/OV9n2eui0WtxgDr4mPnWvSLsgxnJ+h4WT1ERsYnpgESCBKCFC0R8lAsZskQAIkQAIkQAIk\nEFUEMFn9hSrHNpv7baunrq1zyeKZutSfT8hfHFytLaqsYWdJgARIYMQIULSPGHqemARIgARIgARI\ngASURwArqz/8ZfUHTu9RX5NonSYu7oZ848Jcw9xMnTaBXz6VN+a0iARIYGgJ8L45tHzZOgmQAAmQ\nAAmQAAkongCc6ntcvk/cta9bXB+7fEF7kVgu5WJj2rKibAbAK/4CoIEkQAJDSoCifUjxsnESIAES\nIAESIAESUCwBTFZ/5Hj14ydqJKc6TEUS+OVjc24sMNGprtiBp2EkQALDS4CifXh582wkQAIkQAIk\nQAIkEOUEGts73ra5N1Q7/lvlCE5WDzjVLzRopqVrrszWMQl8lA8vu08CJCA7AhTtshsSdogESIAE\nSIAESIAEZEhgB1ZWt3nesLg+cYsB8IImPu724qwVE/Ip1GU4XuwSCZCAYghQtCtmKGkICZAACZAA\nCZAACUSeAOarP1pqXldh64qB9+cmjZqXpZ+h1TAGPvK42SIJkAAJdCNA0d4NCQtIgARIgARIgARI\nQN0E2v3+5yps222eD1214srqguCfa9ItzjfNydSOSU5UNx5aTwIkQALDSoCifVhx82QkQAIkQAIk\nQAIkIGcCBzy+f5ZbX6yymxtbgv30n6VJvrkw86YCE7W6nAeOfSMBElAwAYp2BQ8uTSMBEiABEiAB\nEiCBfgjAqf55bf17du9+t2+L1WVuahUPWJJvWJRr5Mrq/eDjxyRAAiQw9AQo2oeeMc9AAiRAAiRA\nAiRAAvIjcMjre7HK8UKlNFkdXfTPMemuyzHcVMgF2+Q3YOwRCZCAWglQtKt15Gk3CfREwOPxHjx4\n5KKLzhc/3Lt3/7Lb7s7KzlyzZlVRUSEKu5f01AzLSIAESIAE5EvgfbvnbZsHAfBdk9WF8/Wa63Iy\nvpaeOi9bL99+s2ckQAIkoFYCFO1qHXnaTQLdCKxe/fgza9etXLlC/AQCHm9fevkZnU770KrV96xY\njvKwEq02vVszLCABEiABEpAdgZaOjresnvXV9s1WtzRZfSImqxdkLi3kZHXZjRc7RAJKI9DoE8yl\nsW1tgpCqNNOGxZ74ysrKYTkRT0IC6iKQn58fdQYvX377hRfOrKo0iz0vLS0bO65YdLCXlBS53R6X\nyx1WQtEedaPMDpMACaiKgKWpBR71x0rNklMd5s81aRfkGK7K0TOxnKouBhpLAiNGYN0qYc9WnB3u\n4nGjk4Rv3Succ+GIdSY6TxwfjdIiOlGz1yQQZQSg3gsLOh89ZGToodi7l4iSXjSssbGxo6ND3G9r\na8PbhoaGKLP59Lvb1NSEg9RgKcwUh1glxmJkVWIphhWbSoxVz7C2tLRsdtbdVv3pDkdd8MbmH5+a\nOCk1aZYh/focfXp8XLCwQxnjjgs4Pj5eGbYEx6WvF1zDsDcmJqavSor4DAOqtltTbGysIoYu3Ij4\nfe+MCip2we8XYmJimxv9//lD0z1P+RNTwqsq6z3+WpOTkyNlE8PjI0WS7ZCA2gm4XC78fxUp4D5l\ns9mam5sVD8Xj8cBGi8WieEthoN1uHz16NMSAGox1Op0qGdba2lr85cbFiSpO4WPrcDj8fn9iomLX\nGG/1+9/3NW9xNez1NZc1t2M4SxITztOMus2UWjg6ITi67Y0Oe+edWimjjWHFBdza2pn0Xilm9WyH\neGtSg2j3BTc8jukZhLJKcQ23t7fDYiWZFdPWEtPeFtvemvneKwG7oNi7tpimBs+hvY2547sKlPkb\nf61jxoyJlG2q+EuIFCy2QwKqIpCXn7Nr127RZKfT9bUpk7DfvURikpubK+1XVFQUFhbq9cpPaITn\n4gcOHCguLpZsV/AOpA5Ee0ZGhoJtlEyDjlXJsLrd7vr6+ry8PMl2Be9A6mRmZkbQ9SEHVliw7bkK\n28Ya50fO2q7J6oF+XZg66jfTJlyeqZNDJ4e0DxhQSDuDwTCkZ5FJ43gmXlRUpFSXbChkr9eLR4oq\niQjGrcloNKamRu1k7452obVFaGsV2luFiqNCQ61w8ohQ6xBq3YKtQmjq4TlhtlYjKP27U0pKJEMJ\nKNpD7w/cJwESOEUA89jXv/wq0tGhCPPbFy66BhnpwkpO1eYeCZAACZDAMBI4pdUdXmll9fP0qWNS\nErG4+ixditdcPU4Fin0YkfNUJEACQQKtzQKmQzY3CO3twokDgrNG8DgEW6VQ6wq8ShvmcMC5rjUK\noxKFOrcgfHVOR1LUPqGQDBzeHYr24eXNs5GAjAmI2ePRwT179v5q5T1IMgehPvuyBeKSb2LOue4l\nMjaIXSMBEiABpRFobO94udr+rs2z2eKStPqSfMP1ucbFeUbJWkxjCTxw5UYCJEACZ0IgVJ9XH+/Z\nhS6Kc/Es2UVCRpaQN07QZwV+xk4JFB//THjkZ1/pRcnXOj/6Sinf9EWAor0vOvyMBFRFANnj8RNq\n8owZU/fu2953Sein3CcBEiABEhgKAliwbbPF/fTJmo1mV1f7/iX5xjCt3vURf5MACZDAaRIQQ9xb\nmgR/h2CtEDw2oeak4HUI9urAq9cZ3hzSyBVNFoy5gj5TGDs18AqV3uMG6X7nw8KOl4Xq4x1aU11C\nSvqt9/VYkYV9EKBo7wMOPyIBEiABEiABEiCBESNw1Nf4htnxusW1x+WrawsklstNGjU/O+NSY/qV\nWXptAr/FjdjQ8MQkEN0EAvPP2wIh7tgpOyj4PIK1socQ904jYwL6PDVNyB0b+EFku+hCHzgC1A8e\n0tbSYikrS2ds/MDRddXk7b6LBH+TAAmQAAmQAAmQwEgTOOT1PXnSujMwU71FSiyniY+dl6X/6bhc\nNSSWG+kR4PlJQHEEwiS63SzUOoWqYz270BHinpwqjJsWEOcBlV4S2OE20gQo2kd6BHh+EiABEiAB\nEiAB1RNAYrlHSs3PVlg/dknLPvln6tOvzdFfmambrtOonhABkAAJDIBAaCJ3e5XgsQvVpZ1R7j0k\ncg+60KUQ96SUgErnJksCFO2yHBZ2igRIgARIgARIQAUEoNX/cqz6hSrbF7WNYgD8RE3SXSW5NxWa\nGP2ugvGniSRwZgSaG4WASm8OpGe3nBREFzpSuGNqOpZeC9vEWegF44Px7X3OQg87kG9lQICiXQaD\nwC6QAAmQAAmQAAmoicABj+8dm3unq+6jrgXbMFl9aYHp9qIsOtXVdCHQVhIYMAEpkXvoLPQ+1kJn\nlPuA0UZFRYr2qBgmdpIESIAESIAESCC6CVQ1NK03O/e7fVusp1Zrw0LGSAL/h3OKxyQnRrd57D0J\nkEAECUCiQ5yLLnRzaQ+J3MWF1sRXnSkQ1o6F1gIp4qYKjHKP4EDIpimKdtkMBTtCAiRAAiRAAiSg\nOAIIgH/D4lpbbl1f5ZCMm6lLXZBjuMCQPsuYLhVyhwRIQJ0EYhDN3ugTOpoFzEJ3WYSyw4G87lhr\nrfss9NCF1gaXyF2diKPfaor26B9DWkACJEACJEACJCAzAjvsnvcc3s88vq1Wj7Ra2zVZGYvyDMwA\nL7OxYndIYBgJSFHu7e1Yt1xw1mBRdGNNRWJLfSBjXNgGiV5yTsCFjiXQmcg9DI7K3lK0q2zAaS4J\nkAAJkAAJkMDQEIBT/QOH91Nv/Q6HV/Kra+LjluQbFuUal+QZh+a0bJUESECWBML0eUOtcPJIpwvd\n6xC8TqnTKVKUuz4zsNYaJDp+TnctdKk57iiRAEW7EkeVNpEACZAACZAACQwXAWh1LKv+js3z1EmL\ntLI6Esv9uCRnmi5tbqZ2uDrC85AACYwcASRyDyyH3grPueCxBWahNzUE1kLHK9K5h2/BtdYM2UJG\nNlzo1Y1t6WfPSE3lcujhmPheIiA70e7xeFpbW43GoX0aXVZW9thjj/3yl7/Uagfzr3R4OikNEndI\ngARIgARIgARkSOB9uweT1Tdb3ZJWn2vSTtOmXpapp1aX4XixSyQQMQKhEt1tDbjQxUTu3RdaE4L6\nPDUtEN8uutBzSwIZ40K2lrKykHfcJYEeCERetEPQ3nvvvcuWLZs+fbp4QpQ88MADd9xxR1FRUQ9d\n+GrRm2++WVNT8+Mf/zghIeGrn5zGu6ampgcffPDaa6+V+jDwg7du3frGG2/89re/TU/vNTdMRDo5\n8C6xJgmQAAmQAAmQgEwIHK6tf9vmebXGudtZJ05WR8eg1Rfnm67PM3BxdZkME7tBApEkIEl0aPLg\nLPSA8zxsLfSwEHfI8oBKzwwIdW4kcMYEIi/az7BLS5cuPcMWzuTwhoaGjz76yOv1Hj58+IILLuit\nqZHtZG+9YjkJkAAJkAAJkMBQEEAA/B5X3Vara12F7aivSTyFJj4WWv2buYYbC0zU6kOBnW2SwAgQ\ngD7vaA+stSYuhw6J7nEEJHqtqzPKXRTnYs+wFnpGVmeiOM5CH4HRUtEph1u0w4u+Zs2agwcPIi79\nW9/61uWXX97S0gKveHZ29s6dO6+//nqwr6qq+t73vofCvXv3SkMB1zfc5keOHHn88cdLS0tRH677\nqVOnfvrppy+99FJJSQm836NGjcKB2P8//+f/1NXV4fB58+b96Ec/ko4ymUzLly+fMmWK1GzYDlpG\nf2688cZ33313UBW0RgAAIABJREFUxowZaNBut//+979HV/H2iy+++Nvf/vaLX/xi//796CRaRhDB\n2rVrt2/fHh8fvzi4YSesTb4lARIgARIgARKIRgLQ6o+UmjeZHXtcvi6nun+mTnNtruHKTN10nSYa\njWKfSYAEOgmE6nPzCcFpFqwQ5w6h1n1qrbUwiY5Z6IEs7kEXOl65kcBwERhWhVlbW/vwww9fdNFF\nUOBQ79jX6XTnnHMOjDWbzVDpGRkZiE7H28TExN/85jfY8fv9r732GkTyWWedVV1d/Ze//OWWW245\n//zzDx069Pe///3nP/856nz55Zdz58598cUX4SR//vnn0fjTTz8thcfbbLZHHnnk29/+9nnnnYcK\nTz31FCrgqO4bzvXxxx/jQcC0adPQDZwO8fyYXb9kyZINGzYUFha+8MILV111VUFBAfojHo5yCHuc\n2u12Q9ujTh/++e5nZAkJkAAJkAAJkIDcCFiaWj52123Hmm127yduH7qHrHIX6DWXmLQ3FZjGJCfK\nrcPsDwmQQP8EINER0A7/uaM6EOKOQHdxLXQpkbuoz8VXcTn0gvGByedjpwpJKQGhzo0ERo7AUIn2\nX//616FGaTSBp9FI/4aZ6hDYcEfn5+dDAL///vuTJk3CR1dffXVubm7oIeL+vn37Nm3aBM95cnIy\nHNoTJkyYOXNmbGzs5MmT4fres2fPuHHjsA8Zj8Kzzz4bah/e76SkJKkpvV4POZ2SkoIKUP7oACpI\nn4buwKl+4MCBO++8E88OIL/hqBcn4Z977rlQ+5D6WVlZs2fPDj0EaR6PHz9utVrReczbxylCP+U+\nCciZwOrVjz+zdh16uHLligXXXYWdvXv3L7vt7qzszDVrVhUVFfbY+YHU6fFAFpIACZCAzAmIWeV2\nObxSADw6DK3+fycXXWYaTNpamdvL7pGAkgmI8e14rXMHlkPvMVGcpNKLJgvG3MD8cyjzgErvNSZX\nycRom7wJDJVoh8SVksCJiejAob29ffTo0ZKyNRgM8L0jVzw+iouL6w7K4XCsW7futttuGzNmDD5t\na2uDJhdrxsTE4HDEqEO0dz8wtAT14ZaH7x2+fZSLjw9CK0j78J/j0QDkNw658MILn3vuuTlz5iAd\nHR4xzJ8/HxZ9//vfRwek+thBrru0tDQ8FIDgx3OHG264IfRT7pOAbAlAe6Nve/dtx+vTTz1bVlau\n02mh4V96+RnsPLRq9T0rlmu14bkYPR5vv3VkazI7RgIkQAI9Ejjg8f3lWPUWq8vcFPhCgiC/iZqU\nCw2aGVrN+RlpU7VfSfLcYwssJAESGGECgVnoLQFHOlR62UGhulSA/9xefSrKXeqfzhSYhQ7neS+J\n3KWK3CEBWREYKtHeo5EQw83NzR0dHeKn0ORwiYsivHt9zC2H0p44cSI86uKnEM9ICw/lj0MQyo7D\nobG7HxhWAk/4v//9byS0h9scGebgDw+rIL5Fyx988MHnn38uCW88XBDT0aEnCINHVDxex48fL50U\nfYA5l156KWIH8PThoYce2rZtG8IHemyfhSQgKwJ6vW7ixAlil/IL8rBTWlo2dlyx6GAvKSlyuz3d\nRftA6sjKTHaGBEiABHoj0NLR8Y8yy7/KLR+7AgHw2OaYtNczA7zIgq8kIGcC0lx0n0eoKQvEuiNX\nHFZElwLdpc4jyr3kHGHctE6JThe6RIY70UZgWEU7ZDP86pguDqc0pppjZTUo5B4zt0EPb9myBZIY\nedolVY8Echs3bty9ezeC4Y8dO4YdzGlHwrnemIsfoRGExMPDD7WPrHWQ+j3Wr6ystFgsWLw9Ly8g\nYNCBf/3rX5jijpnwiOGvr69fsWLFE0888c4776DzYgt4+vDPf/4TrvjQTvbYOAtJQG4EIM4PfHZo\nxvRZt9y6tLAgX3yLHbGfGRl6l8vdPUK+qtLcbx25Wcr+kAAJkIBEAInlNlk9/7WePOyt/6KuUSyf\nqElaPjaXGeAlStwhARkR6FGfhy23Jka5o9PSRHR40RHo3m05dBnZxa6QwGkSGFbRjkjyn/3sZ8ge\nD60rZo/HBHX4sbv3GS7x119/HangJL83guQRi3733XcjezzC0cXs8WPHjoUO7344gtiREA6Z3pHv\nHTHtEPk/+clPUA3J5DG5HWdE9rjQoyDRocyRfw7NiuUIv8f0dTjP4Xtfv379D3/4Q3QY6eH/+Mc/\nYua8WAdPE5Df7sknn0SmOjx6uPLKK2fNmhXaLPdJQLYEEFqSnJKM8HjMbC+vqIxIP0+ePIlFE8Wm\nEHuCIBc80opIy3JuBM8f0b2jR4/KuZOR6hvmAeHm2dujz0idRSbtlJeX9/hMWSbdi2A38IC7sbER\nz6Yj2Kbcmmr1+3fWt7zladrhbXR24At+YCtOjDs3ZfQSfeLkxAShrc56os4qfqCIV/hIMCtQim1U\nhE29GuF0OvGVDK+91lDQB7g1IRQUX1MVZFOnKTFtLTF+f0xLY2xHe5KltM3jiHfV1Ptb4nzeRHtF\nVyU41gQhqNJbU3VtqfomU0HH6OSGnPGtGn2rJuMUlnZBqKg+9Vbee0jIjdnEUjCvvDt7Rr3DrQn6\n7oyaiJ6DcVPqdx73wK2JUfb/6YGDYE0SkDkB5DsUMyNGpJ9vvbV97Fi0F8g2t3HDG3n5OdjZtWv3\n8uW3Ywez3C+97BvdPe2YCd9HHQSzSF8Qd+zYgdAYLA8Rkd7KuRF8f0IADhablHMnI9U3fKtA1BJS\ndUaqQTm3g+lR0iNaOffzzPuG1U/wTUCMMjvz1mTVgq255blKx4vV9k/cpx5JzM7Q3D4295vZell1\nNeKdgX8Cd6cIfl+MeA8j2CAiJfGIDamOItimbJvCMsZIq6wE0Q4XOhK5t7fGYOa52xKDRHHNDTEO\nc4y9UmgKRsGI/nPxVWv0a03+/HHIEucvmYJc7v6cEtmO0SA6hlzdWK8K+a0HcWx0HYJbE4xFZvHo\n6vbgeouv7nB1YGQHd3jYUcPqaQ87N9+SAAmMFIGG+gaEx4uy3Ol0fW3KJOSfW//yq0g1hy5h7vrC\nRdd07xvmuvdRB44ObOJR8ANgXw2OStFkNViKkYWZ4tb92lBeiUouYEUOKxLLvWJ27HTW7nbWiYur\nY8G2iwzpC3MNE5pqx+Vkq8GdhUeo6vlr7bozqeI7LW5N2KSkztFx7w2I87bO5dZOHOicgo4Q91qX\ngNewTQxxN+Y2p2h96VkZ484W11qDeMePUjf1XMNquzVF8IpVxQ0ugrzYFAkogwDWeENgPOa0wxws\n+Saqdwj12ZctEJd8QxY6pJS/664V999/34wZU0WrURhWRxk0aAUJkEC0E9jv9T1XYevw+9+ocUmT\n1TXxsSsm5N1RkiOtrF5W1plzLtrtZf9JQKYEkLwdCaex/nl7e2ChtcY6oexw53LotooeXOjZRUJy\n6qlEcSGz0Ju83oba2ozczmw7MrWX3SKB4SJA0T5cpHkeEpAZAUTCi8HwUr8gzsVF4MQSKPnXX39B\n+lTcCasT9infkgAJkMBwEmhs73ih0v7vCss2WyBKSNyQBP5So/aKLN10naarjL9JgAQiTSBMnzfU\nBtZCh1xHuHv3LO44uehCN2QLGdmBFdeSUkQXeqS7xfZIQJkEKNqVOa60igRIgARIgASUSsDS1LKu\nwvqaxYXV2roC4BO+U5D1DUP6hLSk4pQkpRpOu0hgZAhIq6D7OwRrheC29qPPEcleNFkQ9TmyuCel\nClxrbWRGjmdVDgGKduWMJS0hARIgARIgAQUTwGT1f5Zb36xxHvU1iWZisvpNBcYfFGWfS6e6ggee\npg0zAcmFjrnoZQf7mYIu6vPUtIDbHAutBdZaKwmodG4kQAIRJUDRHlGcbIwESIAESIAESCByBLCy\n+rpK24Zqx4euOnNj5xqxM/VplxjTbsgzMgA+cqTZkloJdGVxD7jQPTah5mQguL23EPfep6CrFR/t\nJoFhIkDRPkygeRoSIAESIAESIIEBErA3tzxaan7f4d3TFQCPA2fqUr9TmHVToUmbwG8vAwTJaiQQ\nQkDM4i5liXOaBWtlIH97S5NQcTSkXnC3K4u7oM/kFPRwOHxPAsNOgP/2hh05T0gCJEACJEACJNAT\nAQTAb3d4dzi8b1nc4mT1nKSEedm6RbnGJXmRWeq2p9OyjASUSEByode5BXNpwIXe1CBUHTuVJU5c\nAl00XWcKiPNx0wKR7Qh0Z4i7Eq8I2hTVBCjao3r42HkSIAESIAESiHoC0OpPl1s217ikyeo5SaPu\nKMlemm+aquXk2KgfXxow5ASkRHHwpWOhNTGRe61DqHX34EIXZ6EbcwMqPTARPfg65F3kCUiABM6I\nAEX7GeHjwSRAAiRAAiRAAoMg0NLRscXq3m73hK6sPlGTdG12xuWZOvwMok0eQgJqIBDT3ia0tgcW\nV+stUZzoQhdfRRd63rhgirigREeuOG4kQALRRoCiPdpGjP0lARIgARIggaglICaWe8XsXF/lkIyA\nVl8+NvfGAk5Wl5BwhwS6CEhR7vYqwWPP/Gy38IlfcJhPRbl3VQz8RqI4LLQWiG/nQmuhXLhPAlFP\ngKI96oeQBpAACZAACZCAzAnAr/5ilX19teNtq0earH6RIf1Sg3Zulo4rq8t8+Ni9YSIAfR4IdG8O\nd6GHJIrLkLoSligOUe50oUtwuEMCiiNA0a64IaVBJEACJEACJCAPAtDqmy3uteWWV6qdYo/ExHLX\n5xoXM7GcPMaIvRgZAmGJ3ENnodsqhKbGQK96ShRnra03Tr0gNn8c10IfmYHjWUlghAhQtI8QeJ6W\nBEiABEiABBRK4Kiv8fkKa+iCbblJo+ZnZ8wxaanVFTrmNKtPAqLzHK9I5G45KdjNQq3zK4ncxaNF\nlR7mQk9KCcS6d23Ow4eNY88SYmO7CvibBEhAFQQo2lUxzDSSBEiABEiABIaUACarf+Dwrjc7N1tc\nX9QF/YSCoImPvSJT+4OibGr1IYXPxuVFQJqFbq0QPLbAWmteh2CvFiQX+qnuxghFk4XUtGAW96xA\nfPvYKac+5B4JkAAJdBGIvGi3WCxvvvlmeXl51ykU+LuwsHDevHlZWUy/qcDBpUkkQAIkQAIDJ2Bp\natlqdW8yOz501ZkbW4IH+idqUr5daLoyUzddpxl4U6xJAtFHQIxyx5xzca01Z40Aod7bWmtwoZec\nIzCRe/QNM3tMAiNPIPKiXfGKHYOGRxIw87vf/e7IDyB7QAIkQAIkQAIjQWCH3bO61CwlgdfEx801\nab+Za2AS+JEYDZ5zWAhILnREuZtLAy70poavRLmL8e3iq7jW2rhpAf85fnJLOAt9WAaJJyEBZRKI\nvGhXto9dugpUYqZkL3dIgARIgARUTgAB8Dsd3ndsng9dtYe99eamVgARJ6vPNmmXMLGcyq8PhZkf\nmijuxAHB5xGslYKtUghJ5B5icUiUO+afI5F7yCz0kGrcJQESIIFBEoi8aB9kR3gYCZDA8BLweLw/\nWX7vwYNHVq5cseC6q3DyvXv3L7vt7qzszDVrVhUVFfbYnYHU6fFAFpIACUQpAXtzy+s17tdqQgPg\nYYp/rkn3/eJsavUoHVZ2+xSBwCprLYH49vZWAWuhuyynZqFjLro3uPCB6DwXj5Fc6EmpwbnoXGvt\nFEvukQAJDBEBivYhAstmSUDWBJqamh579Onf/PZenU770KrVl8y6EN19Zu26l15+Riy5Z8VyrTY9\nzAbo/H7rhB3CtyRAAlFK4IDHt89T/77D898qh7iyOgxBAPzifNPXdalTtalRahe7rXYCSOHe0SE0\nN3SuhT4QF7oxt9N5The62q8e2k8CI0aAon3E0PPEJDCCBGpqrJmZRtGd/rsHfoWewIU+dlyxWFJS\nUuR2e7qL9tLSsn7rjKBRPDUJkMCZE0AM/COl5mcrrB+7fGJrmKx+e3HW4lzj5Zm6M2+fLZDAsBLo\nPgtdTOQ+EBc6Z6EP61DxZCRAAn0RoGjviw4/IwGlEnC53DDtlu/cgfD4W25dunz57VWV5sKCfNHe\njAw9KnSPkB9IHaUSo10koGACEOp//rJyp6vukLf+aOdqbcgAn3xtdsZUXeqVWXptAr8tKHj8lWJa\n6Cz06uOBWegVR3tN5C4EZ6HTha6UwacdJKB4Avw3rPghpoEk0AMByO8dO3b9dfWDcKevXv043Ow9\nVDrNIofD0dzcLB7U2NhotVoRhH+abURfdaczMN3RbDZHX9dPv8c2m23UqFHSKJ9+A9F0BK5nNQxr\nS0fH85WOfznqjjT7xeEpSYo/OyXx3gL9mMRRwZK2BrutIZqGrq++4hru6OhISkrqq5IiPmttbbXb\n7SkpKYqwpgcjYtpaYtrbAq+tLa1ffhpb56xvb4p3WeJ8nnhXTeCAkFno7ZqM9nRDc+HZHaOTW02F\nbZmF2AlvNEpu4xjW9PT0mBiYp/CtLrjFxcUp3M6gebg1tbW1KfgPVhrElpYWXMMajSpWA3W5XJmZ\nmZLtZ7hD0X6GAHk4CUQlgbz8nIULrxED4C+8cCZsQMmuXbtFY5xO19emTOpuWN914uNP3U9iY2Oh\n7kaPHt29EYWVJCQkwCI1WAozMaYqGVYYi5FV6rAe8TW+7vS5W9t3e+v313Y+WbtMn3pXgeFinWI1\nnnjnwZiKm/hWwa8QdYq6hlubRYkeC01uK4+1VsT63HGuGkj0mFrXV8cxpt1U0KHPDIrzMVhlrbXw\n7NAKELuBu3bUbuJNWA2iHQ+IVfLXiotRHFbYG7UX5kA7rrRbU592i18R+6xyGh+e+pJ9GgexKgmQ\nQJQT0Ot1SCmH/HPQ7Z/tP3jpZd9A/rn1L7+KVHOwDHPXFy66pruJmOveRx2tVisdgn88Op1Or9dL\nJUrdgScApmVkZCjVwFC7xK9QKjEWviyFWRp0qts3mB2vVAezYQeHFjHw56UnXaEZtXTSuNCxVup+\nbW0t7kvJyd28rIozGO4sn88XrdcwcsUh1h2v0nLo4kR0W4XQ1PiVsUpMEUrOaUzW+XWm5K/9TyBd\nnD4Lnln8RLUy/4qNX32DWxOuYTwZ/2qxAt/BE4AtWq/h0xwQ8daUmqr8BJ+4NcFYlQwroidO80Lo\nq7qsRXtxcfHVV1+dk5ODpzL4Zrxjxw4EK9544424YYXahCjczz///NJLL5VCaNrb2999913UkQr9\nfj+iWN96661PP/009NgR36+qqvr3v/8thpviecy555572WWXIbT4qaee8noD8knclixZkpeXh5oL\nFizATldx5+9jx45t2rTp5ptvNplMoQ1K1XB4Wlraxo0bv/3tbwMjBNUVV1whfopzPfvssxdffDFi\ncqSe4CPUQYPdzyW1OZw7GL7//ve/BQUF559/Ps6LQcT2rW99C50EpXXr1i1cuBC246OPPvro448/\n/t73vieGGOG+0B0aCCAyZ/HixcNpgtzOhfnqmMo++7IF6BiWfBOnr0Ooo0Rc8g1ivqys/K67Vtx/\n/30zZkwV+4/CsDpys4v9IQESCCMArf5ilX19teNtq0dMAo+V1e8szkH69wsMaZis7na76+vrw47i\nWxIYJgLiRHQsfu7vCExBb6wTyg73OhE9KNGFvHFQ5oG11roSxXktFqi7ZINhmPrM05AACZDAsBOQ\ntWifP39+YmLi008/7fF4rrrqqksuuQTK7Xe/+x0ozZ0794ILLnj11Vf37dsnvsXsWemtiBF1pELo\n/3nz5qEEag2ydtg593VCyGnIY7zCTBgIOXrWWWchTuYHP/hBqGaG/uyxFQjaI0eO4MFVaWkphCsO\nue+++1AzTJqKVuPxx4QJE95//32QAVtUwyMPPOPAkxGoX6knPZ5oBAvR7ezs7OrqavQB9sJSzBJB\nh2Evvm7iYYc4NwZT+PD8Ar4FGAszR7DDUXFqSPG9+7aHdjWsBEr+9ddfCK2A/bA6YZ/yLQmQgHwI\nbDA7Vx+retfe+fxXEx+7rDj7tqKsc3WqmEwon4FgTzoJ9LgcelODUHVMwKutMhyU1ihkZAnjpgUk\nekCllyDWPbwO35MACZCAOgjIV7RnZWUhgK2srOzLL7/EWMCDOmvWrEFH2544cQJyDjpf9EXLc3AR\nXTx+/PiKigqI9oH3EBoVChYxBTAQjvp+p09An0OlQ6sXFhbiLEePHs3NzYXoDXXsD/zsw1YzPz8f\nWh0hCcghhCcOiKuBCRhNi8UCbmJWIQRTwDR442EUSELqD1v3eCISIAESkAOB6sbmt6yeHQ7PR87a\nLwJ54P25SaPnZ2fMwfrqeUY59JB9UAsBKcQdvvSyg4LdLNQ6A8ocTnV41LtvRZOFFE2nFx0SfeyU\n7lVYQgIkQAKqJSBf0Q4xBlU2efJk+JAR6/5FcBv0OCGyeuzYsWgK6RkH3chQHwhPO55QTJlyev+o\nIPIxLwA6H3MEQCzUOd9jh6HPodtxIoh2xMbjcDwN6bGmrAoxQRozQ/CEAn3GVK6pU6eWl5efc845\ncL/joYPYVWh1iPlJkyZt2LABgQlh0yhkZQ47QwIkQAIRJGBvbnngi8o3a5xHfaeWbJipT/u/kwq5\nuHoEObOpXglIy6FbKwSPTag5KfQ2Cx1N6EyByedwocNzjij34ET0XlvmByRAAiRAAoIgX9GO0cFc\n5WuuuQbybObMmTU1NZs3bxa97j0OHIK9Md0dGz6Fdn344YexIxUiphoqbtu2bXKLjUcn0bE//elP\n2IH2xtzyGTNmYHohni88+eSTKMSGJw6Yvy3uh73CsXzw4MFx48bB24zYBMTJ9yva0QIUPoLn4a8G\nKAhg6RCpJ6iDxyWymvWNsAvMYMfsBjzagDIHk0OHDiHEAKxE0Q5zEGuAORSQ93C8I0YDV04YLr4l\nARIgAcUQOOpr/E+59YVKW6hQn6hJutiYviTPNF2XysXVFTPW8jJEmoWOHSyH7jQL1sr+Z6FDn4+d\nKiSlBFQ6NxIgARIggdMkIGvRjljol4Ib1Be8wdCQL7zwAmKke7QRmi1sTjuq9VjY4+EjWCjOJIci\n/c9//oP4fzGdXvc57WKyurB+QsFiMWHExqMcAeHvvfceHNH9rkALlQ6tDsUO1zTUr1RftnPaYR3C\n/sWpDYiBnz59OhJsIvodznYMsZi0HKEZ4uR81ERUxeHDh+GHD8PFtyRAAiQQ7QQOeX1PnrTucno/\ndvmCtvjP0iSnJcTNMmrvO6uAQj3ax1d2/Zei3H0eoaasM8ods9DhSPcGlyHARDR/V68lFzpnoXch\n4W8SIAESiAgB+Yp2eIMh1D/77LMPP/xw//79EJnwupeUlPQm2iOCYwQbgWifNm0aMp9Dew+8G/At\nw/n86KOPioeAEkIJ4HjvuwWodEwRh6xF/MLs2bP7riyfTxHP/8EHH0CrQ70Dl8FggAmI9hcX78Hs\nAJjz0EMPiR1GIeS9mGxPPiawJyRAAiQwOALQ6i9WOZAHPjhTPdAGVmu7ucC0tNA0JjmQVZQbCZwp\ngdBEcWGJ3LuvtSbECJiFnpoWzOIeDHGnC/1MB4DHkwAJkECvBOQr2hsaGuBBPe+88+AQhvqChocL\nWlwSuVdrovwDyHWI9pMnTyJT+kBMQbJ0zPTH4m1IsIf6mAKAWANEyMPP3G8ONpwLsw8yMzMRVD+Q\nc8mhDsIQEFaAMAFxHUusCIBnOpg6IV4YmJy/dOlSMWk8yDz33HN4voP57XLoOftAAiRAAoMjYGlq\n2WxxbzDbN5pdYgsIgF8+NvfKbD21+uCQ8qhOApiFHlDpzYLoQnfWCB5Hr4ncw9Za4yx0XkYkQAIk\nMLwE5CvaocGw9jgWaVu2bBkkKKK+IWjhde+NjzR9HRUQJi2u095bZXmWwzmMmeSw8dprrw2d047e\niuu0hxbC1Ywl8fBoQ/LMgxKS2EG3DyQHG+Q6NDB0L9qRaITOaUe5fNZpF3uIxHJin8UZBPC3Y9CR\nVA+fms1mdFjMh4+3iJDHlAosB4iggzBoMAoVkAgAm9is3Gbvi73iKwmQgGoJYLL6W1b3Plfdhy4x\nA3yAhLi4Ov3qqr0qBm94qP+8zi1YTvacyD00yj27KLDWmrgcOhO5Dx49jyQBEiCBiBGIQR6viDUW\nbOg3v/lNZBuUbWvqsVS2Q6CqjiHkpKioKFpMRtJHPDfBQ5Zo6fCg+4nQmK1bt+LZ4qBbiKIDxadj\nyAQZRX0edFeR6nKYQ3XgVH+s1NwtsVzyxcY0JJa7zKQdtC19H+h2u/FNQMpI2nflaP8UOUrxzFqc\nVBXttvTc/64s7q2+Wte+9zNTkwRbVc8LrYkqHWuh6zKFgvGBRO5IFBedLnQktYmPj8ekuZ6ZKKsU\nEwMRfIrpkMoyqwdrsBQxnEmYztnDZ4orwq3JaDSKkaSKM+4rBsGXBmPFwNivfKDEN2LCb4xsRIyT\nr6c9IuaxERIgARIgARKQLYGWjo7dztrtDu8Ou+cdmzfYTz8mq1+Tg5XVdVytTbYDJ5eOIX874tvx\nAxe6uTR0obWEpsbMsF6KWeLgP2ci9zAyfEsCJEACsidA0S77IWIHSYAESIAEFEfggMf3z3IrEsuZ\nG1tE4xAA/6OSnJsKmFhOcYMdKYPEQPeWpoBKLzt4KpF7aJY40X+emNJRNKk2LVObnceF1iKFn+2Q\nAAmQwAgSoGgfQfg8NQmQAAmQgIoIIAB+q9W93eb5wOkVF1fXxMctyTdMTUu9Iks3XadREQua2i8B\nKPOODqG5AXl6hBMHBClRnLTWmtRCWJa43BL40ttaWuzl5dr+VpOR2uAOCZAACZCAnAlQtMt5dNg3\nEiABEiCBqCdwzNfwaGnNmxbX0bpGyRgkgb+rJPemQhNXVpeYqHcnTJ/7vIK1Qqh1CLVuQfKin0oU\nF1xrzZgrQJxjlbWgRFcvOlpOAiRAAuogQNGujnGmlSRAAiRAAsNIoN3v3+nwri41f+SslQLgZ+rT\npmhTZpu0czN11OrDOBpyOhVmobe3CQhx93cIWAu9oVY4eSRcn4f2F150LIduyBYysqM3UVyoQdwn\nARIgARINOQrEAAAgAElEQVQYBAGK9kFA4yEkQAIkQAIk0AMBBMBjmvoOhzdEq/tn6tOvzdFjvjqF\neg/IFFwUps8b64Syw4Fwd3u10D3EHRxC9Tlc6IF0cVMUjIemkQAJkAAJDJwARfvAWbEmCZAACZAA\nCfRAAEngX6txP1Jata0zA7yAyerX5xkX5xmW5EVmrZcezsoi+RCQUsTBf47Ido8tkMi9qUGoOhZ4\ntVV262kwxF30n1Ofd6PDAhIgARIggTACFO1hQPiWBNRFYOOGN/Lyc2bMmAqz9+7dv+y2u7OyM9es\nWVVUVNgjiIHU6fFAFpKA8giIfvXtds9uV50YA4+Z6lytTXkDHW6R6EKHzxw7yOKO5dbEtdBrXT3p\ncyEQ356iEbDWmj4r8MNZ6OFA+Z4ESIAESKAfAhTt/QDixySgYAJlZeX/eOKZ+++/DzZ6PN5n1q57\n6eVndDrtQ6tW37NiuVabHmb7QOqEHcK3JKA8AlhTHUL9fYe3a2V1+NVj52Xpfz4+7zKTVnn2qt0i\nKUucKNHtZqHWGXCh9xjinl0kJKcK46YFgtvhQtdnBlQ6NxIgARIgARI4MwKRF+1jxow5efLkmfUq\nCo6GmVHQS3aRBHon0NTU9OQT/5I86qWlZWPHFYtvS0qK3G5Pd9E+kDq9n5CfkEAUE0AA/FtWz9s2\n92aL64uuJPBYWf1bBaYb8oxcrS2Khzas682NAf95e2vAf24uDUS5Q5xjFrqUxf1U/a4s7lDmY6cK\nSSkBlc6NBEiABEiABIaAQORF+5VXXrl582Zl63Yodpg5BMPBJklg+Aj84x/PLFx0TVWlWTwldgoL\n8sX9jAy9y+WW9LzUp4HUkSpzhwQUQOCQ1/dSteN1i+tjl6/LHP8ck25hruE8vYZavYtJdP6GCx36\nXHw1nxCcZsFa2ZnIHXndwzZpLfRAfripdKGH4eFbEiABEiCBISUQedGelZV16623Dmmn2TgJkMAZ\nEkBg/OWXzzr77AmSaD/DBnF4Y2Nje3u72E5ra2tDQ8Po0aPPvFmZtwCr0cP6+nqZ9zMi3cOYYogT\nExMj0pqcG4Fffaur/s7tn+5w1In9HJ86elJq0iUZadfn6NPj48RCZYw7hhWbMmzp9aIKJoqLaW1u\ns5tbnOVxDZ5YW2VMS1NM9bGYWlcsnOrYTi2ELnSkGyDL27OL/brM9qwif06xH6I9bJP3X31LSwvu\nTgof1q4RwQUcHx+vEmMxrLA3JgbXq8I3mKmea1i0VA3DqqpbE4Y1JaXb/47B/uFGXrQPtic8jgRI\nYPgIHPjs0P33r5LOt3LlCqSj27Vrt1jidLq+NmWS9Km003cdp9PZ3NwsVsaO3W7HrVk6Vqk7Ho8H\nplmtVqUaGGqXw+HAgxg8kQktVMx+q9//qqvxLW/Dsca2sua2oF1NJYnx39SnXKNPyhsl/rvsaHI6\nmhRjc9CQ2tpafLGA5lGSWbGtzZDocKSPqrXH19pHW07G1Xvi6r3jbOXhZsYITdljW7WmtrSMZkM+\nxHlj7vjwOl6fgJ+o2vB36nK5UlNTo6rXg+wsbk1xcXFtbeKf7SAbiZbDMKz4j6MGdecLbgq7NfV2\nmeEbVEdHhxoePIm3JpV8a8JfK0V7b9c8y0mABAZEYMF1V+EHVaXs8Ugyt/7lV/GKQsxdR+R894Yw\n172POnl5edIh5eXlhYWFer1eKlHqTmxs7Oeff15cXKxUA0Ptgo8doj0jIyO0MNr34VTf6/ZhcfWn\nyix1bZ2hIhM1yQUxbT+fMuHyTF20G9hv/91uN74phv799nuI7CpIE9Gx3JrbKpw88pUo91Mu9Ji2\nVH2sKSd2/PTORHHBRO4IHVFe9AiemeLupJJbU3JyMqSdwWCQ3ZU5BB1CPpqioiIM7hC0La8mvV4v\nHinm53dO3JNX5yLdGzyFMRqNanjKJrpzVHJriqBixxWnqCfrkf4LYnskoHACq1c/jozxMBKedmh4\nCPXZly0Ql3xDFjqE0N911wrklhcXhEM1FIbVUTggmqdcAu1+/7pK2/pqx9tWj6jVsbL6DfnGH4zJ\nEoX6oUOHJqlAsUflCEtz0fvNFaczCRlZwSnowYXWcsdWlpVlZmZC40Wl4ew0CZAACZCAWglQtKt1\n5Gk3CQjC8uW340ciAXG+d9926S0S0b3++gvSW3EnrE7Yp3xLAjInYG9ueaHK8a7d85GzVlxZPScp\n4X8yNBcbtT8qydEm8H+i/AYQXvTAjPRmwV4luCxC2WEBC6SHpXMXfemQ6MjfjuXWxOXQx06RnzHs\nEQmQAAmQAAkMhgC/oAyGGo8hARIgARKIIgIHPL63bJ43LM5ttsAEEGzwq1+fZ1ySZ1icZxRL+CoL\nAlKgO/K3O2sEhLvXOoRatxCazl2U6FI6d0h0aHVKdFmMHztBAiRAAiQwJAQo2ocEKxslARIgARIY\nWQKYrL7F6n6lyvGB03vU15k8Diurz8/OuD7XoIbJ6iPLv5+zB9ZCb+tcER0udI89INE9DqHqmNDU\nINgqTx0uedGxHDq96Ke4cI8ESIAESEBFBCjaVTTYNJUESIAEFE8AWv0tq+dtmxu55cQAeJg8U5e6\nIMcwL1s/VauKZNryGmUpvh1LQlYfFxrrhJqTAWUeps9FcS6+Fk0WUjRC3riACx1aHa/cSIAESIAE\nSEDFBCjaVTz4NJ0ESIAElELA0tSy1ereZHZs/WpiuYW5hrmZOk5WH6ZxDi6HLrQ0BVzo0OdOs2Ct\n7JyC7nUIXmcP3cguEpJTAy70pNROiY5wd24kQAIkQAIkQAIhBCjaQ2BwlwRIgARIIKoIYLL6K2bH\new5vyGT12CX5hksytDcVmqjVh3Ywe5ToiGyvdXXGt4c6z7EP/3lqWlCZZwVzxWUGXrmRAAmQAAmQ\nAAn0R4CivT9C/JwESIAESEBOBLBa286ASve8UGmTJqtjZfVvGNNnm7RLmFhuiAZrgBJdPDv854bs\ngD7HT8CFXhJ45UYCJEACJEACJDAoAhTtg8LGg0iABEiABIaXACarP19p32A+tbK6IPhn6jSYrH5D\ngbE4JWl4u6Pos4n6PJArrjWw0BqyxFWXhs9CF73oIoZQic4p6Iq+NGgcCZAACZDAiBCgaB8R7Dwp\nCZAACZDAgAiISeA3VDs2W91iYjlNfOwVmdpFeaY5mdoxyYkDaoWV+iDQ3BiLlc9rnUKdW7CcFOzm\nwD6i3DE1PXShNakFRLnDi56RLYydKiSlBHzp3EiABEiABEiABIaSAEX7UNJl2yRAAiRAAoMlsMns\nXFtueTsksdyN+cafjc87V6cZbJOqP66nEPdUpyUFa615rUJTYzggZokLJ8L3JEACJEACJDACBOIr\nK0NWQx2BDvCUJKBMAvn5+co0jFaRwJARgFN9t7N2bbn1gLf+E7dPPA/86kgsd6lBe2MBE8udJnpx\nLXR40X0eoaas04WOhdakRO7BEPcEMdBdZwr4zLHKGiaf04V+mqRZnQRIgARIgASGlEA8pcWQ8mXj\nJEACJEACfROwN7e8aXGvr7YjA3xdW3uwsj83afTZmuRlxdmLmViub3zip91noZd+3rnWmq2iBxe6\nlMg9d2xdm99rHJOXlzeQ87AOCZAACZAACZDA8BNgePzwM+cZSYAESIAEBGj1F6ocG6rt79i8Ig46\n1Qd0WbQ2Cx0dgQnn/g7BWhGYf949S1xoQ4kpgbXWCsZ3utCRKO6rC621ud1CfX3oEdwnARIgARIg\nARKQFQGKdlkNBztDAiRAAgonAK2+rtK+yeyQtHpu0qirs/VL8kyXmbQKN/50zYM+R4g7Xtvbherj\nQkOtcPJIp/+8qaFzLfSwNqVZ6FDm+Bk7JexzviUBEiABEiABEog6AhTtUTdk7DAJkAAJRB+BAx7f\n0+WWg956SavnJCVck52xrCh7OhPLieMpSXRkcTeXCk5rwIseOgU9bNjhP4+NEcZNCy6EPlbo5kIP\nq863JEACJEACJEACUUqAoj1KB47dJgESIAG5E2j3+z9weNebnZstri/qOjOTQ6t/uyDzhjyj2rV6\nmESvORnID2evFrpPQUeiuMAU9HQhtyTgPMcPdpAujhsJkAAJkAAJkIA6CFC0q2OcaeX/a+9O4KMq\n7/2PTxYSEhLIAkmAsIRNwA1xAdwLqGhVWnftRVttsba+rN5e7VXb3lft/+/t1dvNv93UviytClZw\nQyviviCKAooIIkrCloXsG9mT/3c4chjnmZmckJnM9pmXr3jmOc8553neTzLM7zzLQQABBAZQ4I3K\nuiUlFS/u+/LJ6rryrOyMb48vWDAyJ06frN7W4h7o3tXhnoVet89V5j9E1xT0iUe7V3F3B+eTiM8H\n8NeWSyGAAAIIIBChAgTtEdowFAuBUAs88/S/7rrrHl3lmm9fedNN12tj/foPF3/v5oKR+ffff09R\n0TifBXCSx+eBJMa8wJaG5uLmNi0Cr3710tYOq77n5Gd9Y9Tw+IrVvZ+FXnZgubgqV0Ota9e2Q78G\n1oPWCNEPibCFAAIIIIAAAr4FCNp9u5CKQGwLFBfvrK6uWb/h9dbW1t/+5k96m52dteRvS5evWKKN\ne++579bbbsrKGuaFUFdX32ser0N4G/MCn9Q3PVhS/sSeqtKW9oOV7Tk7L/uSMXmXFg7PGhTr/8po\nlLvWctez0NWRXrzZVV3mqqtyT0S3F4qzgnP7Weiaea5Z6NYod1aJO/gbw/8RQAABBBBAIIBArH+d\nClB1diEQ3wIVFZWK2AcPHnzCicdJ4osviidNnmB1sE+cWFRbW2cG7U7yxDdqvNTenqz+TnX9upom\nq9qzczJPzh06cUjaVePyYjNWd49v73TH5+Za7uZEdKF4PAvdvUqcxrrzQgABBBBAAAEE+i5A0N53\nM45AIPoFFJzffsctqoc6z9XlftZZZ2766JNxY8dYNcvNzampqTVHyO/ZXdprnui3oQZ+BRSrr6pu\nWvFZ+csVdY2dXVY+LSx308TR108cFVOBemdHorrQtYq79Sx0z1noWi6uvtrbqLdnoXvn5z0CCCCA\nAAIIIOBYgKDdMRUZEYg5AY2K/+1v/njXL+8ISs127NjR0vLlCuH19fXbt28fOnRoUM4cySepqqpS\n8bZu3RrJhex/2dY3d7zU2PZa3f7dXRrn7UpPdJ09NGVORsppmamjkhNdPc1ln28v6/9lwnSGhM72\nxO4u/Uze35BavSeluS6pqW7k3s/bE3tSFK57vxJaCiZ2pQ1pzS3syMxtz8jZP2ryV7JoOn9Frfu/\nKHk1NjbqL1c/o6S8/Srm3r176+rqNMKoX2eJhoM7OjrKyso6OzujobD9LWN1dXVSUlJlZWV/TxQN\nx5eUlKiYCQnuj+LYfjU1NTU3N+tnbFfTql1paWltbW1aWlrMV1YfTapst6aVxcFLbTp58le/IfSj\n1gTt/cDjUASiWUAR+7KlT95z7y+s76+FY0atWfOeVSH1vR9z7JFm5QLnGT9+fE9Pj3VURUXFhAkT\ncnJyzJPEWEpqaqoi9ilTpsRYvVSdbU0ty3ZXrqrQ09paD/arJxw/NO22qWMvHj08euur4Nw9/7yj\nraehJqFshxZyT9Dj0Cv3JlTudrV+edfpYO0SegrGu4ZkuibN6MnO10T0nlET9Ky1lAO7Y+a7lb5V\n6JtxYWHhwVrH8v8HDRqUn5+fnp4ey5U8ULf29vaUlJQgfl+MZLHy8vLk5OThw6P4c8k5r27E6F+c\neAjadfe/oaFhzJgvxwA6J4rGnPpoGjFiREZG7D/LUx9N+muNyW9N5i+evgybiYedQtB+2HQciEAU\nC2hU/MqVq2759xsUsZeXuT9TNI/9yRUrla5tzV2/6OILzOoFzpOYmOh5iPo99PJMicltq9YxU1MN\ngH+7qv7p0uoXyqq3NbVaTZaZnHhp4Yiz8rNPS+4ckZ6Wm5sbTU1pP2utco+rptxVvMXVcGAhd3MW\n+lcXct9e3TB51ml2Z5a9EU11d1bWA3+pcfHXKo/4qWz81DSumtWqrP7dsf7pcfYnHq25+B2O1pYL\nWO54a9aAGH3bSdDeNy9yIxAbAgrLtQ68/lN1jjpq2u/v+5WWnVOgPm/uQuuRb3qrrvgbb7ztrrtu\nP/74GVatzTyxoUEtJKB+9cd2VjxUXHbwaW090zLTF43Nv3Jcnv1kdQ1pi2grz4XidmxyNdW5Kna7\n9u12tbf6eNZa1gj3ynD+H4fe3vZJRFeWwiGAAAIIIIBA3AgQtMdNU1NRBDwEFIfreW8eCe5Nr0Qt\nRPf8848HzuO1N1bfds6Z469qGlJ8rcvV+fDD/jL0Mz157dp+niHA4e3d3WurG77ar+5+Wts3Rw+/\nYmxkrwBvPQvdHaV3uJ+C7nOhOHWOa7qG9TM7z71+O89aC/DbwC4EEEAAAQQQiFQBgvZIbRnKhQAC\nkSTgL3jWmkCrV69evHhxKAob4GZBfy5X2db++J6qV/fVeiwC3zMrO3PhqOGe/er9uUSQj7W70LWh\nZ6H760L/8qoJ7metjRj95VPWeNZakBuD0yGAAAIIIIDAQAsQtA+0ONdDAAEEwiLwVmXdq5V1b1XV\nv7LPvXKBXpqsfvmYEWcOHxZZ/eqahe7uSG9zWbPQy0pcespa5V73T+tZa1bn+YEquEYWudIz3F3o\naRnu4e6jJ7o3eCGAAAIIIIAAAjEkQNAeQ41JVRBAAAFDwJqs/vjuffbCcqPTUs4fmXNZYd7cvCwj\n+8AmKDLXc1/a9ru6ulzuWej17rHu5ix0q1DWs9CtLvRJM1xpQ9xROi8EEEAAAQQQQCDWBQjaY72F\nqR8CCMSfgCarP1Bc/lpl3bvVDaUt7QcAes7Ky56Xl6VF4GdmZ4aBxBrirjXherrdy8Ltb3CVbHWH\n655d6FaxvGah04UehtbikggggAACCCAQQQIE7RHUGBQFAQQQ6I+AtbDc//t87+qKuoNPVnfNys64\ncPTwq8YeWgS+P5dwdKy1SpwVn9urxLXud+3Z7tJPdaR7vw7MQh8+0pU70t15zix0bx/eI4AAAggg\ngEBcCxC0x3XzU3kEEIgBAS0s98jOireqG+yF5TKTkxZPGHnp6OHz87NDXkE7RFdf+t7PXdWlXz5o\nraHGb3yeMfRAcF7gyilgFnrIG4gLIIAAAggggECUCwQ/aK+rq/vP//zPvXv3SiYxMXH06NFXX331\nrFmzEhI05JEXAggggEBwBNSv/mJF7dN7q57YU2X1q2thuXMLci4uHH7d+ILgXMM8i0J0LRSnXnSF\n6JqFXl3mqqtyB+c+QvQE9ypxQzJd7vnnB1aJUxe6onReCCCAAAIIIIAAAn0RCH7Qbl39F7/4xcyZ\nM7u7uzdt2vSHP/whNzd38uTJfSkYeRFAAAEEfAi8UVm3pKTixX21ByeraxH4pOsnFCwuGhn8yeqK\nz/U6uFBcRvG21JYGV+Vu3wu586A1H81FEgIIIIAAAggg0F+BUAXtVrnU0z516lR1tjc2Nm7YsOHZ\nZ59VJ/zgwYPVG3/33XffcMMNtbW1y5cvnzhx4gsvvJCSknLttdfOmzevq6vrxRdffPTRR5ubm2fM\nmPGjH/0oJyenvxXleAQQQCCaBRSrP1deo5/v1zRZ9ZiVM/ToYWnz8rIXFORkDerfh7m1Spz7Z4er\nsdZVXnKoC12d6vt2uVrd0ftQz2etKUS3ZqGrI50u9Gj+1aLsCCCAAAIIIBDhAv37ntdb5dTTrli9\nrKwsPz+/oqLCZ/bPPvvs7LPP/uc///nuu+8uW7bs+OOP19D6l1566Te/+Y1i9YcffviRRx754Q9/\nmJSU5PNwEhFAAIEYFthU1/R6Vf0juyo8Y/XrigouLRx+mIG65xT0pjpXebGrusLVUO39oDUrPrd+\nZo1wjZyoEL0xJaNn4rFDx09mlHsM/8pRNQQQQAABBBCINIFQBe3/9V//ZVV11KhRN998szrb/QXt\nRx111OzZs9UnP336dKsTPjU1taWlpaSkRIPq1ffe2tqqvZEGR3kQQACBEAl09fS8U1X/ZGn1vS7X\nsS9vsK6iReC/Pb7ghJzME/r6wDYNcbe60LWQe22F+0FrDVWuhlr3c9fMV3aeu9u8cLJ7FrrxLPTG\n0lJ9Prtycs3jSEEAAQQQQAABBBAIkUCognZrTvvHH3/8t7/9LS8vr0+lnzRpkuL8xx577Ne//vWU\nKVNuvPHGzMxwPFW4T4UmMwIIINAPAStQf7Wybtnuyk8bD8wkd7kUtE8fmn712Lw+PFy9o80douun\nzxDdc3y74vNcLd4+yWd83o+qcCgCCCCAAAIIIIBAMAVCFbRbZTziiCM0MH7NmjUXXnih81K3tbWN\nGzful7/8ZWdn58qVKx966KFbb71VnfDOz0BOBBBAICoErFj9bzsrVlUcWlhuambaMVlDzsjNUhU+\nOfuEQBWxQ/TKPa6acldZiXuJuMq99ix097FWoG6F6O755wcetDbp2ECnZR8CCCCAAAIIIIBAxAiE\nNmjX2nLnnnvuX/7yFw2Az87O1uR2zVdXQL5+/fp9+/b5Q9i4cePTTz/9H//xHxoe7y8P6QgggED0\nCrxVWbexvvnNyrrVFXUHn9aWdHZe1pkjsi4fO2LCkDSrap1eNbQHumtku561pr50c6C7HaKrC33y\ncYToXoS8RQABBBBAAAEEok4gtEG7ONTZPnbs2Ndff/3iiy8+77zzfvKTnyjxjDPOGDZsmD+sE088\nUeG9Fo3X6vGa6P6DH/yAbnZ/VqQjgEAUCextafvn7n2P7a78oPbLFeD1tLZLC0do9Lv3wnLWcnGq\nm1Zu3/2Zq7rcVVfp2rP90LPWrGrbIbomohOiR9GvAkVFAAEEEEAAAQQcCwQ/aM/Kyvrzn/9sF0Cd\n7bfddpv1duGBl71LG0VFRXqcu5WiA++55x5r+6IDL8+cbCOAQHAF1q//cPH3bi4YmX///fcUFY3z\neXIzj5ni80ASPQU+qW96qKTihbLqbU2tB9J7ZmVnqlN9fn62/nOnaJR7d4fr47Wuzk5X8Sfu565V\n7HbpWWt63f0d90/rZYXoetbakEz3WnHqS1esrp+8EEAAAQQQQAABBGJXIPhBe+xaUTMEYkegrq5+\nyd+WLl+xJDs769577rv1tpuysrwHv5h5VP9ej4odo/7VpLKt/ZGdFc+X12xtbCltaT9wsp5pmelX\n5qZe0VM7efB+V/E61+edrpIt7l1eC7lbwblVAIXohZNcw0d9GaJrRjovBBBAAAEEEEAAgXgSIGiP\np9amrggcFPjii+JJkydYHewTJxbV1taZQbuZp6amttejDl4hTv+vWP3dmsan91Y9safKmqzucvXM\nyhmmFeCvGpeXtfy3rhdW+aAZNtyVPcKVM9Ldc543xj0RPW2IO0qfM8f1o9/7yE8SAggggAACCCCA\nQNwIELTHTVNTUQQ8BPbsLh03doyVkJubo2jcHCFv5jFTzKM8LhJHm4rV//hF6dJd+w4OgHdpsvr1\nEwoWF42c6flY9cIprvIS18gi91PWcke58grdXeh0nsfRbwpVRQABBBBAAAEE+ixA0N5nMg5AAAGf\nAnokRHu7NQ7c1dTU9NJLLyUlJfnMGXWJ33C5li9f7rPYqvJvM8Zcv/LdA3t7Rvd0HZHQPsnVdXJn\n65AdZTt2bNrhddiYr7kTOlyu8nZXuXZ67/fMHuC6ntkGbLujoyMhISE5OS7+4Whtbd26deuA2Ybx\nQl1dXd3d3YMGDQpjGQbs0nqmrJba0a/xgF0xXBfq6elRZT/66KNwFWAgr6snBOty8fPRtGXLgXlV\nA0kcjmvpo0kv/cGG4+IDfU39tepDODExcaAvPODXsz6aPv744wG/chguqG9N8+fPD9aF4+K7V7Cw\nOA8CMSNQOGbUmjXvWdWprq455tgjzar5zBPgKD3lwf7OpH9l09PTY+m5DwUFvieTNzY25la3Txs0\n5LgU14VpCaOT9fXC+obhvUaAKewkxd91nRwb9Dy6F6MmjqVmDUBUVVU1fPjwABliZpe+LOqLRUZG\nRszUKEBFGhoa9NFkf1IFyBntu3QjRpXVEr/RXhEn5dfDhnSPOE4+mqqrq+Pkici6J65XnHw01dfX\n66MpHm6e6kaMPpr0IHAnf9rRnmf//v1BrAJBexAxORUCUSOgeexPrlippeZUYs1dv+jiC8yim3m0\nal2Ao4YOHWqfREH7jBkzcnJy7JSo3lAnzqmnnuqzCiUlJVevXr343xb63NvPxADX7eeZD+/w0tLS\n1NTUOPm++Mknnxx5pI+bWYdHF8lH1dbWKuYpLCyM5EIGq2zFxcX5+fn6chysE0bseRTt7Ny5c/Lk\nyRFbwiAWrLy8XDdi4uQum7rZp06dGg9dsopjFd2NGfPlVL4g/sJE4Kn00TRixIh4uEOhjyZVVk8E\nj8BWCHqRKioqgnhOgvYgYnIqBKJGQMvOKVCfN3eh9cg3vS0u3nnjjbfdddftxx8/w6qGmUfpXkdF\nTYUpKAIIIIAAAggggAAC0SlA0B6d7UapEei3gILz9Rtet0+jJeWef/5x+6214ZVHiWaK1yG8RQAB\nBBBAAAEEEEAAgSAKxP6CB0HE4lQIIIAAAggggAACCCCAAAIIDKQAQftAanMtBBBAAAEEEEAAAQQQ\nQAABBPogQNDeByyyIoAAAggggAACCCCAAAIIIDCQAgTtA6nNtRBAAAEEEEAAAQQQQAABBBDogwAL\n0fUBi6wIIBC3Ap1z5visux6Tda3L1fnwwz73kogAAggggAACCCCAQD8FCNr7CcjhCCAQ+wLJa9f6\nq6Se075az2lfvNhfBtIRQAABBBBAAAEEEOiPAMPj+6PHsQgggAACCCCAAAIIIIAAAgiEUICgPYS4\nnBoBBBBAAAEEEEAAAQQQQACB/ggQtPdHj2MRQAABBBBAAAEEEEAAAQQQCKEAQXsIcTk1AggggAAC\nCCCAAAIIIIAAAv0RIGjvjx7HIoAAAggggAACCCCAAAIIIBBCgfCvHl9TU5OcnDx06NAQ1jKsp+7p\n6R8fqMsAACAASURBVNmwYYPWl25tbR01atSVV16pyr7++uv79u277LLLwlo0Lo4AAggggAACCCCA\nAAIIIBDRAsHvaVc4+uijj3Z1danebW1tDz30kFIsg4qKit///vfl5eU2SWdn5wsvvLBmzRqlfPLJ\nJ8qsQ+y9kbzhvLSVlZVvvfXWRRdd9NOf/vTyyy8fMmSIZ7327Nlz//33NzQ0eCayjQACCCCAAAII\nIIAAAggggIAEgt/TPm7cuK1bt6pXWdFpXV1dVVXVoEGDOjo69FOd6ikpKcOGDbPp1cf+rW99y34b\nkxvt7e2q5siRIyWQlZUVk3WkUggggAACCCCAAAIIIIAAAqEQCH7QnpOTo252xecK2vfu3ZuXl6fO\nc/Uk5+bm7ty5c/To0dXV1StWrMjPz9+xY8fVV1/9zjvvKI/Gim/evFk1/N///d9rrrlGIa663998\n801F+9OnT1+4cOHgwYPt+jc2Nq5cuXLbtm2JiYmzZs0666yzkpKSrL261j/+8Q/Fxp999tnJJ598\n2mmnmef54osvnn32Wd1QKCws1Nj1KVOmnHnmmQqtX3zxRY1j13l0zvnz5+vqJSUluqegkPvxxx9X\ndS644AJdURn++c9/epZW5bePnTp1qrKlp6db5VGHvI7Vtuqlbnb1unuOitcYhFdffdXee+SRR6ps\nzz33nIjEdckllwwfPtyzOiqnfdpXXnklMzOztrb261//+ksvvSRJjbq3qj9nzhzdGXnqqacmT578\nwQcfqDksJR1ra6jul156KTcRLE9+IoAAAggggAACCCCAAAKRKRD8oD0jIyM7O1ujvhUWKiw/9thj\n9VND4hVSanj80UcfLYjm5maFiz/84Q+V2XLR7G6FrGvXrl20aFFqaqo2Nm7c+P3vf19x6bJlyxQ/\nn3322VZOhaDPP/+8euzvvPNO3Qt45JFHxowZo2M9fRXKXnfddbrEunXrvM6jgFaHn3TSSdrYtWvX\n0qVLdaBCd0XdCqdvvfVWjRFQYkFBgWJ+lVzBuXrIFUWfd955VsSu/J6lVUkUZuvYH//4x8r59NNP\n/+tf//rmN79p3UdQwRYvXqxEK6i2ZwpYpVUQPmnSJHuvlBRp6x6ElCSg0yrOV067OtZR1k8lnnji\nicqp+yOe6fa2bm0kJCTcdtttpaWly5cvP+qoo1paWiwNtYVuW6xatUpxu32/wz6QDQQQQAABBBBA\nAAEEEEAAgQgRCP6cdgWB6k5XH3t9fb3Gxit0nzhxojqQFajrpV2quULx2bNnqzfYZ8So7mINsFcn\nufqZFcCfcMIJiq6VaJEpclZXtvreFS2rO1p98uq+9tJUx7J68pVonqe4uFjpM2bM0Hl07IgRI/S2\nqalJnepz585VD7lGCijSVke9+vbnzZv32muvKZ7XLn+d0vaxugGh0p5xxhllZWXqxvcqkpO3uqiK\npOhaZVM0rlEGisx1oFUdndzzJMo5c+ZMXdS+leC5V9uKzHVjQkrKqcKrOXRPQedU0yiYF6A9cMDr\nQN4igAACCCCAAAIIIIAAAghEiEDwe9pVMU1r3759uwbDa0i5YmClqINX0bJCdEWS6rVW0Ogv1LRc\nuru71f+sl/VWXfcavm5FrTp2//79jz32mDrz1UOuDFZ8buW0ftr3AszzKGpVZK4R7575dR6d/+GH\nH7YTx48fr9sEqojuMqiDWuPM7V1eGzpWRVI8bKXr5HqrQ7yyOXmr0mrM/y9+8Qsrs86j3nJt29Xx\nPElgQM+c9raqo/XwXn755WeeeUZo2lYD2XvZQAABBBBAAAEEEEAAAQQQiDSBr8SuwSqcAnXFxppN\nrT52RbPq5tVPze5Wx3haWpqTqygi1YzuY445xsys4etPPvmkOsOvvfZaRbOaXm7msVPM8+huggbY\nKzy282hD4bH61TXoXSPtPdPV9a1uc+1Vj73G+Xvusre1V3G76mul6IaCzm/H8HY2JxsqreqlYuic\nVn7dONAIfyfHOsmjGxN65pyG66uEGkGgdQE0Y9+rA9/JeciDAAIIIIAAAggggAACCCAwMAIhCdo1\nZltxu8a0n3POOaqGwkJNEdeCcxdeeGHgWilG1UPg1P2rmd5aMk0Rps6zZcsWDe3WSG+rb1kBpyJk\nBf+KbDXSWy+tA+fztLqueR4NO1fsqgXndEIF5BparzzqHte13njjjW984xs683vvvacqTJgwQQu8\naYS8UjRCXvG8NWrAvpZVWuVUt7zWk9P8c41Ff/vtt9WJrYH9drZeN1QjFUnZdI9Ddzo0i16hu2aq\nv/vuu6ecckqvh2uugdA0kEFV0zQELRzg7xDdepCqHhTvb6i/vwNJR8CJgHXHysqp32pN7rBvZjk5\nPErzaDiM/gYD/N1Fab18FlsfxRqmpA8cn3tjLFEDpuKkWTVzTXfD46Sy+oPV7f54uFutv1NN34uT\nZtWcRDWr/t2JsU8hn9XRP7VaR8nu3fGZJzYSVVO94uR32FqISp/GsdF2AWqhb4aqZpw0q741abR4\nAI0+7QpJ0K6PTkXpCjvVtW6VRsPLP/roIyUGKJwGouszSA9y//a3v20Fq3/+85/VtAqnNZDbith1\nuEJ6BdJaR00vjffWxHh92/B3WvM8Gp+vyFx99atXr1ZorTBbx6rAWoNdkfmvf/1rdcIfccQR559/\nvsJvfRefNm2a9mpauLqmdaC2rWt5llb3JqxjtUurx+vehJ3NX8HsdE2qV3PqUe2K+XUtTTXX+nNP\nPPGEqrlgwQLdTbBz+tuQgCbSq9tcldKNBpXZX05F9bpJ8cc//lGqagtdKx6+uPjTID3oAvrapDtZ\n1mn1x6UP5cObJxL0goX0hBpoo796c2WNkF40XCfXd2I1sd3K4SrGwFxX/+jET7PqH774qaw+qexv\nFAPzuxSWq+ijSdeNk2bVHQp9gYyTjyZ9w1SzxkPQrn9x4uqjSatr60ZbWD4uBvKi8fbRFMSgPSEe\nbup4/S7qU8AKqvX5rgeqaSV5n+PwvY7iLQLhFdBdyaKiovCWwfnVNQ9FN7ac3HVyfs7IzKmbhrt3\n7w6w7EVkFvvwSqWRTbrT16eRRId3oUg4SoOe9MDReIjuNChG3xS9ZodFQhOEogwaj6Z71rotHoqT\nR9Q59Q1HK+yqEyKiShWiwmjgpAYBWUsLh+gSkXPa+Plo0v01dVSqfy5y8ENXEj2vSgOHNXo3dJeI\nkDNrcLE+h9VPGSHlCWkx9FwwfYvwNyS8r5cO/urxfS3BAOfXSJslS5ZovTfdvfv000/1iRAsygGu\nCJdDAAEEEEAAAQQQQAABBBCIeYGQDI+PZDV1/WkwuYagP/rooxpJrmHwgQftR3JdKBsCCCCAAAII\nIIAAAggggEBsC8Rd0K7m1HpvP/rRj2K7XakdAuEV0BAv5ys7hLeo/by6Bj7Fw1BbS0lP2bDWAekn\nWlQcrru68TBrVG2hx52oZaOiUfpfSN24j5+PpngYamv9SugXOB5msliV1dpM/f9DiIoz6KMpHibZ\nWW2hmno9jjoq2ugwCqk/1fj5aNKMwiB+kYjHOe2H8RvGIQiEXSC65rSHnYsCIIAAAggggAACCCAQ\nGwJxN6c9NpqNWiCAAAIIIIAAAggggAACCMSDQPCHx//85z+PBzjqiEBggbvuuitwBvYigAACCCCA\nAAIIIIAAAr0KMDy+VyIyIBARAgyPj4hmoBAIIIAAAggggAACCAysAMPjB9abqyGAAAIIIIAAAggg\ngAACCCDgWICg3TEVGRFAIJ4E1q//8PiZZ37965cXF+/0V28zj5MUf2cLV3pra+udd/xSldV/11x9\nQ11dvUpiVsQsnpnHTDGPioQU1fHtt9+1S2IW20yxM9sbTvLYmcO14VnTIDZ0uKoT4LrPPP0v63f4\nvvv+YmUzG8hMMU/oJI951ECmeNU0tptVren1OWw2kJliNoeTPOZRA5ziVdnYblnZ6jdZ7WIhmw1k\nppjN4SSPeVRYUuzKxmqzOq+Xk1Zzkics7RjeixK0h9efqyOAQCQKKNRZ8rely1csefTRBx568O9W\nHOtVUDOPkxSvk0TI22/922XrN7yu/5b8/U9ZWcPMipjlNPOYKeZRkZCib8bz5i6srqqxCmMW20wx\ni+0kj3nUAKd41VRXD0pDD3AtnFxOd9aqq2v0C7zmnVXNTfv11mwgM8U8s5M85lEDmWLWVFeP4WbN\nGDJEzXr//fcsW/qkogKzgcwUszmc5DGPGuAUtaxXZWO4ZVU11feBB5dYyGYDmSlmczjJYx4VlhTP\nyqoAsfoH66ReTlrNSZ6wtGPYLxr8hejCXiUKgAACCPRT4IsviidNnlBUNE7nmTixqLa2TqGs1znN\nPDU1tV5HmSnmebxOGwlvzaqZxTbzREtlb7rp+lNOmbVnd6lFfXgVMY8yicLelF41NcvjpBZO8phn\nHviUiopKBXV6XvcJJx6nq5vFdvL7aR4Vgc3qVVOT2kktnOQxzzzAKfoELrrO/SE8cmT++KKx2jCL\nHTPNalbW1Darb/5+OsljnnmAU/Snqrvh1r+wsd2sqp1XZU1qJ03mJI955vCm+Cyzz0SvcjrJ43VI\nnLylpz1OGppqIoBAHwQU0Y0bO8Y6IDc3R98LzYPNPE5SzPOEPaW1te3dte9rIoCGoWoIn8pjVsQs\npJnHTDGPisAUs9hmillsJ3nMo8KbEqyGDm8tfF5d3/5vv+MWRezqolGXu96aDWSmmKdyksc8aiBT\nzJrGcLPasGVlFcOH56p9zQYyU+yj7A0neezMYd+wKxvDLfvAA0suuviCs+afaWmbDWSmmO3iJI95\n1MCneFU2VpvVYb2ctJqTPAPfjpFwRYL2SGgFyoAAAgiETUB9NWPGFq5YsURDi7ds2aaBfGErChcO\npUDMN7R+dX/+s7sXLJgXSsWIOLdnTWO+WTXL48Ybb5s0qSgi6ENcCM/KxmrL6rd3/vwzjz9+Rogt\nI+L0ZmVjtVljtV4R8Wt0sBAE7Qcl+D8CCCBwUKBwzKidu3Zb79Rxl5OTfXDPof+beZykHDo+krbO\nOutM9WLpZQ0tNitiFtbMY6aYR0VgillsM8UstpM85lFhTwlKQ4e9Fj4LoC/HmvZ8z72/0HdHZTAb\nyEwxz+Mkj3nUAKd41VRXj+FmVe00y0O3FNW4qrjZQGaK2RxO8phHhSXFs7IqQEy27KaPPln0b9dr\nYNddd92z+Hs3a3iX2UBmitkcTvKYRw1wilnZWG1Wh/Vy0mpO8gxwO0bI5QjaI6QhKAYCCESQgOax\nV5Tv01Bb/afpVdnZWWbhzDxOUszzhD1Fy7Sqe0fF0NS7D97fqA2zImYhzTxminlUBKaYxTZTzGI7\nyWMeFd6UYDV0eGvh8+r6O125ctUt/36DbjyVl1XoP7OBzBTzVE7ymEcNZIpZ0xhuVrtqtrDZQGaK\nndnecJLHzhyuDbOydko/P5nDVSN/1134jfOsdU9//vPbHnjwd3prNpCZYp7NSR7zqAFOMSsbq83q\nsF5OWs1JngFux0i5XDMvBBCIBoEdO3b08BpAgQ8+2DjzuDPOO++yHTtKdFn91LYSPYvglUe7nKR4\nniEStltaWu64/S5VVv89/dTzVpG8KnLY1Y+ECnqV4fe//7NVWdVaddder8qaKQ6r73WhsL/1qmkQ\nGzrsVfMqgNWCVrNevej7WjlSGWKyWc2axnCzOqma2dBR+tdqVtZMiZnKqiL2p5P1j05M/rWqmtbL\ns7Kx2qxO6mVpeLV1lP7BHmzbAf1/gqKV0N0/SNrxccqK+xLqKnq9RE92XtvFN3cXHdVrTjIgEJ8C\nFRUVRUVxMakvPtuXWiOAAAIIIIAAAggg4FMgtI98cxixq2QJtftSn7yv5ccP+CyllZjQ2py09b2E\nWvctgJ7s/K5ps3oGDwmQn10IIIAAAggggAACCCCAAAIIRLVAaIN2J33sbr7UNFdbS0JNeQDKQa88\nlvzOswmt+3uyRihbQl1lz+D0zlMWdsy9MsBR1q61a9cuXbr0f/7nf9LS0nrNrAwa4/GTn/zkyiuv\nnDNnjpP85EEAAQQQQAABBBBAAAEEEEAgFAKhDdodlTgz2/W9/+v6/EPXs3672VOW/y5546sdc69Q\nlG71rqu/PXnDK4NeWaqN9otvdnQhMiGAAAIIIIAAAggggAACCCAQVQLhXj3eitjHTHFNPMY1xP2Y\nFvPl7mPf+Grbd+/umHeVPR5ew+P1VonJG15VBvMoO+Xxxx+fP3/+X//61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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('figs/graph2.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 关于 tensorboard 的一点心得"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 1.一定要学会使用 tf.variable_scope() 和 tf.name_scope(),否则稍微复杂一点的网络都会乱七八糟。你可以通过上图中的 graph 来看看自己构建的网络结构。\n",
    "- 2.使用 tensorboard 来看 training 和 validation 的 loss 和 accuracy 变化对于调参非常非常有帮助。\n",
    "\n",
    "想要了解更多，可以参考[详解 TensorBoard－如何调参](http://blog.csdn.net/aliceyangxi1987/article/details/71716596)"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}