GNN/GCN_code/GCN_numpy.ipynb

{
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   "cell_type": "markdown",
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   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#GCN\" data-toc-modified-id=\"GCN-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>GCN</a></span></li><li><span><a href=\"#简单分步示例\" data-toc-modified-id=\"简单分步示例-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>简单分步示例</a></span><ul class=\"toc-item\"><li><span><a href=\"#创建有向图-邻接矩阵\" data-toc-modified-id=\"创建有向图-邻接矩阵-2.1\"><span class=\"toc-item-num\">2.1&nbsp;&nbsp;</span>创建有向图 邻接矩阵</a></span></li><li><span><a href=\"#进行传播规则\" data-toc-modified-id=\"进行传播规则-2.2\"><span class=\"toc-item-num\">2.2&nbsp;&nbsp;</span>进行传播规则</a></span></li><li><span><a href=\"#增加-self-loop\" data-toc-modified-id=\"增加-self-loop-2.3\"><span class=\"toc-item-num\">2.3&nbsp;&nbsp;</span>增加 self-loop</a></span></li><li><span><a href=\"#归一化处理\" data-toc-modified-id=\"归一化处理-2.4\"><span class=\"toc-item-num\">2.4&nbsp;&nbsp;</span>归一化处理</a></span></li></ul></li><li><span><a href=\"#Putting-it-All-Together\" data-toc-modified-id=\"Putting-it-All-Together-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Putting it All Together</a></span><ul class=\"toc-item\"><li><span><a href=\"#计算-A_hat-的度矩阵\" data-toc-modified-id=\"计算-A_hat-的度矩阵-3.1\"><span class=\"toc-item-num\">3.1&nbsp;&nbsp;</span>计算 A_hat 的度矩阵</a></span></li><li><span><a href=\"#参数初始化\" data-toc-modified-id=\"参数初始化-3.2\"><span class=\"toc-item-num\">3.2&nbsp;&nbsp;</span>参数初始化</a></span></li><li><span><a href=\"#应用激活函数\" data-toc-modified-id=\"应用激活函数-3.3\"><span class=\"toc-item-num\">3.3&nbsp;&nbsp;</span>应用激活函数</a></span></li></ul></li><li><span><a href=\"#应用到真实数据集\" data-toc-modified-id=\"应用到真实数据集-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>应用到真实数据集</a></span><ul class=\"toc-item\"><li><span><a href=\"#数据集可视化\" data-toc-modified-id=\"数据集可视化-4.1\"><span class=\"toc-item-num\">4.1&nbsp;&nbsp;</span>数据集可视化</a></span></li><li><span><a href=\"#构建-GCN\" data-toc-modified-id=\"构建-GCN-4.2\"><span class=\"toc-item-num\">4.2&nbsp;&nbsp;</span>构建 GCN</a></span></li><li><span><a href=\"#去掉-relu\" data-toc-modified-id=\"去掉-relu-4.3\"><span class=\"toc-item-num\">4.3&nbsp;&nbsp;</span>去掉 relu</a></span></li></ul></li></ul></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 本文需要对 GCN 有基础的了解\n",
    "\n",
    "\n",
    "* 参考 ：[How to do Deep Learning on Graphs with Graph Convolutional Networks](https://towardsdatascience.com/how-to-do-deep-learning-on-graphs-with-graph-convolutional-networks-7d2250723780?source=user_profile---------2-----------------------) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:08:59.542939Z",
     "start_time": "2020-04-20T03:08:54.618474Z"
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   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GCN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "传播规则：\n",
    "\n",
    "$$\n",
    "f\\left(\\boldsymbol{H}^{i}, \\boldsymbol{A}\\right)=\\sigma\\left(\\boldsymbol{A} \\boldsymbol{H}^{i} \\boldsymbol{W}^{i}\\right)\n",
    "$$\n",
    "\n",
    "简化： \n",
    "\n",
    "$$\n",
    "A H^{0} W^{0}=A X W^{0}=A X\n",
    "$$\n",
    "\n",
    "$$\n",
    "f(X, A)=A X\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 简单分步示例"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://tva1.sinaimg.cn/large/007S8ZIlly1gdzzheeq2pj30pu0lujtf.jpg\" width=\"30%\">\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 创建有向图 邻接矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-19T16:13:02.095421Z",
     "start_time": "2020-04-19T16:13:02.080165Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[ 0.,  0.],\n",
       "        [ 1., -1.],\n",
       "        [ 2., -2.],\n",
       "        [ 3., -3.]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.matrix([[0, 1, 0, 0], \n",
    "               [0, 0, 1, 1], \n",
    "               [0, 1, 0, 0], \n",
    "               [1, 0, 1, 0]],\n",
    "              dtype=float)\n",
    "\n",
    "# 创建特征 ： 基于索引生成 整数特征\n",
    "X = np.matrix([[i, -i] for i in range(A.shape[0])], dtype=float)\n",
    "X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 进行传播规则\n",
    "节点更新后的特征： 是邻居节点的特征和 (有向图中指向的点为邻居)"
   ]
  },
  {
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     "end_time": "2020-04-19T16:13:34.882329Z",
     "start_time": "2020-04-19T16:13:34.871340Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[ 1., -1.],\n",
       "        [ 5., -5.],\n",
       "        [ 1., -1.],\n",
       "        [ 2., -2.]])"
      ]
     },
     "execution_count": 7,
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     "output_type": "execute_result"
    }
   ],
   "source": [
    "A*X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 增加 self-loop\n",
    "节点聚合之后的特征包含自身的特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
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     "end_time": "2020-04-20T01:50:14.508843Z",
     "start_time": "2020-04-20T01:50:14.487797Z"
    }
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[ 1., -1.],\n",
       "        [ 6., -6.],\n",
       "        [ 3., -3.],\n",
       "        [ 5., -5.]])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "I = np.matrix(np.eye(A.shape[0])) # 单位对角阵\n",
    "A_hat = A + I \n",
    "A_hat* X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 归一化处理\n",
    "通过节点度矩阵进行归一化\n",
    "$$\n",
    "f(X, A)=D^{-1} A X\n",
    "$$"
   ]
  },
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   "cell_type": "code",
   "execution_count": 12,
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     "end_time": "2020-04-20T02:04:05.220461Z",
     "start_time": "2020-04-20T02:04:05.212788Z"
    }
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[1., 0., 0., 0.],\n",
       "        [0., 2., 0., 0.],\n",
       "        [0., 0., 2., 0.],\n",
       "        [0., 0., 0., 1.]])"
      ]
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     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "D = np.array(np.sum(A, axis=0))[0]\n",
    "D = np.matrix(np.diag(D))\n",
    "D"
   ]
  },
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   "cell_type": "code",
   "execution_count": 15,
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     "end_time": "2020-04-20T02:05:33.908799Z",
     "start_time": "2020-04-20T02:05:33.902983Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[0. , 1. , 0. , 0. ],\n",
       "        [0. , 0. , 0.5, 0.5],\n",
       "        [0. , 0.5, 0. , 0. ],\n",
       "        [1. , 0. , 1. , 0. ]])"
      ]
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     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A_nor = D**-1 * A\n",
    "A_nor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T02:05:45.134300Z",
     "start_time": "2020-04-20T02:05:45.128104Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[ 1. , -1. ],\n",
       "        [ 2.5, -2.5],\n",
       "        [ 0.5, -0.5],\n",
       "        [ 2. , -2. ]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A_nor * X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "相当于对聚合的邻居特征求了平均值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T02:10:54.165121Z",
     "start_time": "2020-04-20T02:10:54.161627Z"
    }
   },
   "source": [
    "# Putting it All Together\n",
    "self-loop + 归一化 + 权重参数 W +  激活函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算 A_hat 的度矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T02:19:35.163409Z",
     "start_time": "2020-04-20T02:19:35.155861Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[2., 0., 0., 0.],\n",
       "        [0., 3., 0., 0.],\n",
       "        [0., 0., 3., 0.],\n",
       "        [0., 0., 0., 2.]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D_hat = np.array(np.sum(A_hat, axis=0))[0]\n",
    "D_hat = np.matrix(np.diag(D_hat))\n",
    "D_hat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 参数初始化\n",
    "W: 2 x 2\n",
    "* 前面的 2 代表输入的特征纬度\n",
    "* 后面的 2 代表想要输出的纬度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T02:27:36.082079Z",
     "start_time": "2020-04-20T02:27:36.078386Z"
    }
   },
   "outputs": [],
   "source": [
    "W = np.matrix([[1, -1], \n",
    "               [-1, 1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T02:27:39.433118Z",
     "start_time": "2020-04-20T02:27:39.426769Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[ 1., -1.],\n",
       "        [ 4., -4.],\n",
       "        [ 2., -2.],\n",
       "        [ 5., -5.]])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h_1 = D_hat**-1 * A_hat * X * W\n",
    "h_1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "也可以减小输出的纬度 \n",
    "\n",
    "W： 2x1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T02:27:48.764377Z",
     "start_time": "2020-04-20T02:27:48.756110Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[1.],\n",
       "        [4.],\n",
       "        [2.],\n",
       "        [5.]])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "W = np.matrix([[1], \n",
    "               [-1]])\n",
    "h_2 = D_hat**-1 * A_hat * X * W\n",
    "h_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 应用激活函数\n",
    "Relu : \n",
    "$$\n",
    "f(x)=\\max (0, x)\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T02:26:46.534779Z",
     "start_time": "2020-04-20T02:26:46.522171Z"
    }
   },
   "outputs": [],
   "source": [
    "def relu(x):\n",
    "    return (abs(x) + x) /2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T02:28:18.629303Z",
     "start_time": "2020-04-20T02:28:18.621599Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[1., 0.],\n",
       "        [4., 0.],\n",
       "        [2., 0.],\n",
       "        [5., 0.]])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h_3 = relu(h_1)\n",
    "h_3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 应用到真实数据集\n",
    "空手道俱乐部: Each node in the returned graph has a node attribute 'club' that\n",
    "indicates the name of the club to which the member represented by that node\n",
    "    belongs, either 'Mr. Hi' or 'Officer'\n",
    "\n",
    "数据集 : https://networkx.github.io/documentation/stable/_modules/networkx/generators/social.html#karate_club_graph\n",
    "\n",
    "```\n",
    ">>> import networkx as nx\n",
    ">>> G = nx.karate_club_graph()\n",
    ">>> G.nodes[5]['club']\n",
    "'Mr. Hi'\n",
    ">>> G.nodes[9]['club']\n",
    "'Officer'\n",
    "```\n",
    "\n",
    "<img style=\"float:;\" src=\"https://tva1.sinaimg.cn/large/007S8ZIlgy1ge010li9dyj30ya0u0ala.jpg\" width=\"30%\">\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据集可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:09:42.398138Z",
     "start_time": "2020-04-20T03:09:42.392569Z"
    }
   },
   "outputs": [],
   "source": [
    "G_kar = nx.karate_club_graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:23:02.881968Z",
     "start_time": "2020-04-20T03:23:02.875812Z"
    },
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "def plot_graph(G):\n",
    "    '''\n",
    "    G: a networkx G\n",
    "    '''\n",
    "    plt.figure()\n",
    "    pos = nx.spring_layout(G, seed=1234)\n",
    "    # Position nodes using Fruchterman-Reingold force-directed algorithm.\n",
    "    # return A dictionary of positions keyed by node\n",
    "    # 固定seed 避免每次生成位置不同\n",
    "    edges = G.edges()\n",
    "\n",
    "    nodelist1 = []\n",
    "    nodelist2 = []\n",
    "    for i in range(34):\n",
    "        if G.nodes[i]['club'] == 'Mr. Hi':\n",
    "            nodelist1.append(i)\n",
    "        else:\n",
    "            nodelist2.append(i)\n",
    "    nx.draw_networkx(G, pos, edges=edges)\n",
    "    nx.draw_networkx_nodes(G,\n",
    "                           pos,\n",
    "                           nodelist=nodelist1,\n",
    "                           node_size=200,\n",
    "                           node_color='lightcoral',\n",
    "                           alpha=0.7)\n",
    "    nx.draw_networkx_nodes(G,\n",
    "                           pos,\n",
    "                           nodelist=nodelist2,\n",
    "                           node_size=200,\n",
    "                           node_color='skyblue',\n",
    "                           alpha=0.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:23:03.851226Z",
     "start_time": "2020-04-20T03:23:03.738605Z"
    }
   },
   "outputs": [
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       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_graph(G_kar)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 构建 GCN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:40:02.506508Z",
     "start_time": "2020-04-20T03:40:02.499466Z"
    }
   },
   "outputs": [],
   "source": [
    "from networkx import karate_club_graph, to_numpy_matrix\n",
    "\n",
    "zkc = karate_club_graph()\n",
    "order = sorted(list(zkc.nodes()))\n",
    "\n",
    "# 按照节点顺序创建矩阵\n",
    "A = to_numpy_matrix(zkc, nodelist=order)\n",
    "I = np.eye(zkc.number_of_nodes())\n",
    "\n",
    "A_hat = A + I\n",
    "D_hat = np.array(np.sum(A_hat, axis=0))[0]\n",
    "D_hat = np.matrix(np.diag(D_hat))\n",
    "\n",
    "# 随机初始化矩阵:标准正态分布\n",
    "W_1 = np.random.normal(loc=0, scale=1, size=(zkc.number_of_nodes(), 4)) # 输出4 个特征\n",
    "W_2 = np.random.normal(loc=0, size=(W_1.shape[1], 2)) # 输出两个特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:28:16.606769Z",
     "start_time": "2020-04-20T03:28:16.602701Z"
    },
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "# 定义 GCN 传播层\n",
    "def gcn_layer(A_hat, D_hat, X, W):\n",
    "    return relu(D_hat**-1 * A_hat * X * W)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:40:05.889012Z",
     "start_time": "2020-04-20T03:40:05.878284Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[0.11743332, 0.        ],\n",
       "        [0.        , 0.        ],\n",
       "        [0.23761968, 0.        ],\n",
       "        [0.        , 0.        ],\n",
       "        [0.16797176, 0.        ],\n",
       "        [0.12593345, 0.        ],\n",
       "        [0.07769329, 0.        ],\n",
       "        [0.        , 0.01636965],\n",
       "        [0.30804179, 0.        ],\n",
       "        [0.36372876, 0.        ],\n",
       "        [0.13777397, 0.        ],\n",
       "        [0.2544023 , 0.        ],\n",
       "        [0.        , 0.        ],\n",
       "        [0.        , 0.        ],\n",
       "        [0.69047194, 0.        ],\n",
       "        [0.71065603, 0.        ],\n",
       "        [0.08763562, 0.        ],\n",
       "        [0.        , 0.0315847 ],\n",
       "        [0.82880027, 0.        ],\n",
       "        [0.08009458, 0.        ],\n",
       "        [0.55756427, 0.        ],\n",
       "        [0.        , 0.02975639],\n",
       "        [0.68853292, 0.        ],\n",
       "        [0.64212557, 0.        ],\n",
       "        [0.76219299, 0.        ],\n",
       "        [0.70790021, 0.        ],\n",
       "        [0.44018507, 0.        ],\n",
       "        [0.45538525, 0.        ],\n",
       "        [0.519651  , 0.        ],\n",
       "        [0.49939538, 0.        ],\n",
       "        [0.32597351, 0.        ],\n",
       "        [0.5164308 , 0.        ],\n",
       "        [0.86460857, 0.        ],\n",
       "        [0.81422056, 0.        ]])"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "H_1 = gcn_layer(A_hat, D_hat, I, W_1) # 单位阵 (one-hot) 作为初始特征\n",
    "H_2 = gcn_layer(A_hat, D_hat, H_1, W_2)\n",
    "output = H_2\n",
    "output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:40:12.838086Z",
     "start_time": "2020-04-20T03:40:12.826361Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: array([0.11743332, 0.        ]),\n",
       " 1: array([0., 0.]),\n",
       " 2: array([0.23761968, 0.        ]),\n",
       " 3: array([0., 0.]),\n",
       " 4: array([0.16797176, 0.        ]),\n",
       " 5: array([0.12593345, 0.        ]),\n",
       " 6: array([0.07769329, 0.        ]),\n",
       " 7: array([0.        , 0.01636965]),\n",
       " 8: array([0.30804179, 0.        ]),\n",
       " 9: array([0.36372876, 0.        ]),\n",
       " 10: array([0.13777397, 0.        ]),\n",
       " 11: array([0.2544023, 0.       ]),\n",
       " 12: array([0., 0.]),\n",
       " 13: array([0., 0.]),\n",
       " 14: array([0.69047194, 0.        ]),\n",
       " 15: array([0.71065603, 0.        ]),\n",
       " 16: array([0.08763562, 0.        ]),\n",
       " 17: array([0.       , 0.0315847]),\n",
       " 18: array([0.82880027, 0.        ]),\n",
       " 19: array([0.08009458, 0.        ]),\n",
       " 20: array([0.55756427, 0.        ]),\n",
       " 21: array([0.        , 0.02975639]),\n",
       " 22: array([0.68853292, 0.        ]),\n",
       " 23: array([0.64212557, 0.        ]),\n",
       " 24: array([0.76219299, 0.        ]),\n",
       " 25: array([0.70790021, 0.        ]),\n",
       " 26: array([0.44018507, 0.        ]),\n",
       " 27: array([0.45538525, 0.        ]),\n",
       " 28: array([0.519651, 0.      ]),\n",
       " 29: array([0.49939538, 0.        ]),\n",
       " 30: array([0.32597351, 0.        ]),\n",
       " 31: array([0.5164308, 0.       ]),\n",
       " 32: array([0.86460857, 0.        ]),\n",
       " 33: array([0.81422056, 0.        ])}"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_representations = {\n",
    "    node: np.array(output)[node] \n",
    "    for node in zkc.nodes()}\n",
    "feature_representations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:42:52.991978Z",
     "start_time": "2020-04-20T03:42:52.983150Z"
    },
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "def plot_result(output):\n",
    "    plt.figure()\n",
    "    for i in range (34):\n",
    "        if zkc.nodes[i]['club'] == 'Mr. Hi':\n",
    "            plt.scatter(np.array(output)[i,0],np.array(output)[i,1] ,label=str(i),color = 'b',alpha=0.5,s = 250)\n",
    "            plt.text(np.array(output)[i,0],np.array(output)[i,1] ,i, horizontalalignment='center',verticalalignment='center', fontdict={'color':'black'})\n",
    "        # 为每个点添加标签，一些形如（x轴，y轴，标签）的元组，水平及垂直位置，背景颜色\n",
    "        else:\n",
    "            plt.scatter(np.array(output)[i,0],np.array(output)[i,1] ,label = 'i',color = 'r',alpha=0.5,s = 250)\n",
    "            plt.text(np.array(output)[i,0],np.array(output)[i,1] ,i, horizontalalignment='center',verticalalignment='center', fontdict={'color':'black'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:43:18.028748Z",
     "start_time": "2020-04-20T03:43:17.831370Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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ItZcMxdaFyVAgAABAgQIECBAgAABAisFmnX9rUSNFRAANtbb1T4SaLYJKN3dN316xOOPRyxeXLrbb+HCiHffLQV/KfRLW58+pT/Ll5f+pC0FfykIHDAgYuONS3cFrrtuxOc+F7HLLqW/2wgQIECAAAECBAgQIECAQB4Czbb+zsPANSMEgEZBLgLNMgGlO/r+8z8jHngg4v33I15+uXTnX/r39dePGDiwdIdfCvfS31P417GlAPC990ohYbpD8O23S39fZ53SnYCbb1769332idhrr08emwu6ixIgQIAAAQIECBAgQIBA2wk0y/q77eCbrMMCwCYrSLs0pxkmoFdfjbjlllLg9+KLEXPnlvQ32aQU4G2wQXXVSHcJpjAwnW/BgtKxW20VMWxYxNChEYcfXjq3jQABAgQIECBAgAABAgQINEqgGdbfjeqr65QXEAAaHbkI5D0BzZgRcdddEe+8EzFrVim423LLUlhXi3f3pXcJplDxpZdKdw+OGVMKFA88MGL8+FzIXZQAAQIECBAgQIAAAQIE2lAg7/V3G5I3ZZcFgE1ZluI3Kq8JKN2lN3VqxH33RfzpTxHPPVd6TLcjoKu1fEfAmB4p/vM/j9hii4iJEyMmTCi9O9BGgAABAgQIECBAgAABAgTqKZDX+ruefXLu6gUEgNWbOaIGAnlNQOldfyn8S8FfukMvBXIpmFv13X416N4nTpHeFZiulwLHdIdhul4KAdO7AW0ECBAgQIAAAQIECBAgQKCeAnmtv+vZJ+euXkAAWL2ZI2ogkMcElL7yO2XKx+Hf1luXHvtt1JYeB54z5+MQ8JBDPA7cKHvXIUCAAAECBAgQIECAQLsK5LH+blfrZu63ALCZq1PgtjV6Akof/Jg8ufShj2efjWh0+NdRyo4QcOTI0gdCTj7Zh0EKPMx1jQABAgQIECBAgAABArkLNHr9nXuHNaBTAQGggZGLQCMnoGXLIq65phT8zZxZ+iLv5psviHnzpmd/5s+fEfPmzYjFi1/PLHbY4bg4/PAbunR5660X4gc/GFGV3cCBW8UZZ7yQtSN9KXinnSJGjYo48cT6PoJcVSPtTIAAAQIECBAgQIAAAQKFEmjk+rtQcAXrjACwYAVtle40cgJKH/24556IRx+NSGHgzjtHfOtb5b/AUa8AcOut949jjrk70jsBUxDZt2/EjjtGfP7zEXvv3SqV004CBAgQIECAAAECBAgQaCWBRq6/W8ml3doqAGy3ijdJfxs1Ab3xRsSkSaX3/j3/fClw22CDiIsu+jgAHDhwWGy00ZiYM+e3mU4lAeCyZUvi9def7lbz97+/NJ588l+y/Y444hex3XZ/lf17+jpwCiTTB0FGjIg47bSIwYO7PZ0dCBAgQIAAAQIECBAgQIBAVQKNWn9X1Sg7N1xAANhwchdMAo2agO66K2LatIgHHyw9+pve/Ze2++67IIYOHR9DhoyP/v03jVUf6a0kAKykisuXL4vvf39YvPvu/FhrrQHxD//waqy55rorD00fBJk3L2L33SMmTIg44IBKzmofAgQIECBAgAABAgQIECBQuUCj1t+Vt8ieeQgIAPNQd82GBIAffhhx5ZURs2dHvPBCKWhbc83O8esRAD777N3xi18cmF3wc587Ib74xes+cfElS0rB5PDhEaNHR5x1Vvn2GTIECBAgQIAAAQIECBAgQKAnAgLAnqgV7xgBYPFq2hI9asQElB6xvfXWiIcfjhg0KGLMmPI09QgA/+3f/nrl47/HHXd/DB++z2oNmDUr4q23InbdNeLwwyPGjWuJ8mkkAQIECBAgQIAAAQIECLSIQCPW3y1C0dbNFAC2dfnz63wjJqCf/jTiD3+IePLJj9/9V67HtQ4AP/jg3bjiis1iyZJFMWjQ8Pi7v3su1lhj9Q+PdLwLcLvtIrbfPuKkk/KriSsTIECAAAECBAgQIECAQPEEGrH+Lp5a8XokACxeTVuiR/WegD74IOKyyyKeeiri3Xcjxo/vmqXWAeBjj10f//7vf5NddMKE82PixP/baQNWrCh9EXjAgIixYyP+6Z8i1l67JUqokQQIECBAgAABAgQIECDQAgL1Xn+3AIEmRoQA0DDIRaDeE9DcuRHXXx8xY0bEwIGld+x1tdU6ALzxxonxwgv3Z5f82799JgYPHln28k8/XfoqcAopTzghYqutcimJixIgQIAAAQIECBAgQIBAAQXqvf4uIFkhuyQALGRZm79T9Z6A0sc1pkyJ+P3vI0aNihgypHEB4Ntvvxjf//7wiFgRW265R/zN3/xnlxefPz/imWci9tor4uCDSx8rsREgQIAAAQIECBAgQIAAgVoI1Hv9XYs2Okf9BQSA9Td2hU4E6j0B/eu/lsK/xx6L2Gmn0iO2XW21vANw2rRL4t57/092uUMO+UnsvPPJXV47PaL8yCOl9xSmEPCIIwwZAgQIECBAgAABAgQIECBQG4F6r79r00pnqbeAALDews7fqUC9J6D0AZD0br30eO2ECRF9+jQuAJw0aWy89tqs6Nt37fiHf3gl1llnUJcXX748YurUiM98pvQY8IknGjQECBAgQIAAAQIECBAgQKA2AvVef9emlc5SbwEBYL2FnT+XAPCqq0p31T33XCkA7G6r1R2A8+ZNj2uu2TW73DbbHBVHHXVzd5fOfk8B4NZbl+4CPOWUig6xEwECBAgQIECAAAECBAgQ6FZAANgtUVvsIABsizI3XyfrPQH96Eelx3/Tx0DSY7XdbbUKAKdMOT1mzJiUXe4rX7ktRo8+tLtLZ79PmxYxfHjEuHERp59e0SF2IkCAAAECBAgQIECAAAEC3QrUe/3dbQPs0BQCAsCmKEP7NaLeE1AedwAuW7Ykrrhi81i8+PVYf/1N4swz50WfPv0qKq47ACtishMBAgQIECBAgAABAgQIVClQ7/V3lc2xe04CAsCc4Nv9svWegPJ4B+CsWbfEr371/2Wl3XXXM+LAA79XUZm9A7AiJjsRIECAAAECBAgQIECAQA8E6r3+7kGTHJKDgAAwB3SXjKj3BJTHV4B/9asjYtas/5eV9+STH4vNNvtcRaX2FeCKmOxEgAABAgQIECBAgAABAj0QqPf6uwdNckgOAgLAHNBdsv4B4IMPRkyZEvH730eMGhUxZEjX6r19B+DixW9kj/8uW/ZhbLLJdnHKKX+ouMzz50c880zpXYUHHxyx++4VH2pHAgQIECBAgAABAgQIECDQpYAA0ABJAgJA4yAXgXpPQOnjH9dfHzFjRsTAgRGjR3+ymy+++Pt4441nV/7HRYtei9/97h+zv2+55Z6x444nfuKAz33u+C6dZsz4cUyZclq2zxe+8N3YY4+zKnZ9+umId96JGD8+4oQTIrbaquJD7UiAAAECBAgQIECAAAECBASAxkC3AgLAbonsUA+BegeAH3wQcdllEU89FZEesU3h2qrbLbccH088cWPFXbvgghVd7nvNNbvFvHkPxxpr9I0zz/xT9O+/WUXnXrEiYubMiAEDIsaOjTj33Ii11qroUDsRIECAAAECBAgQIECAAIFuBeq9/u62AXZoCgEBYFOUof0a0YgJKH0I5A9/iHjyyYgdd4zYYIOPnWsZAL7++jPxox+VbjEcOfLA+Ou/vrPigqY7/x59NGK77SK23z7ipJMqPtSOBAgQIECAAAECBAgQIECgW4FGrL+7bYQdchcQAOZegvZsQCMmoBSs3XprxMMPRwwaFDFmTPNZz5oV8dZb6avBEYcfHjFuXPO1UYsIECBAgAABAgQIECBAoHUFGrH+bl2d9mm5ALB9at1UPW3EBLRkScQVV0TMnh3xwgulj2usuWbzMKT2pY+VDB9eekfhWWc1V/uaR0pLCBAgQIAAAQIECBAgQKCnAo1Yf/e0bY5rnIAAsHHWrrSKQKMmoLvuipg2rRS0DR0asfXWzVOGOXMi5s0rBZMTJkQccEDztE1LCBAgQIAAAQIECBAgQKAYAo1afxdDq7i9EAAWt7ZN3bNGTUBvvBExaVLEc89FPP/86u8CzAup491/f/7nESNGRJx2WsTgwXm1xnUJECBAgAABAgQIECBAoKgCjVp/F9WvKP0SABalki3Wj0ZOQFOnRtxzT+ljG8uWRey8c0SfPvmBLV9e+vJv376lQPLzn4/Ye+/82uPKBAgQIECAAAECBAgQIFBcgUauv4ur2Po9EwC2fg1bsgeNnIBS4HbNNRHPPBPxyCMRQ4akr/Xmx/bssxHz50fstFPEqFERJ56YbyCZn4QrEyBAgAABAgQIECBAgEC9BRq5/q53X5y/5wICwJ7bObIXAo2egF59NWLy5Ii5cyNSAJfeBbjllr3oQA8PfemliPTuvxRAbrVVxMknR2yySQ9P5jACBAgQIECAAAECBAgQINCNQKPX3wrSnAICwOasS+FblccENGNGxB13lN4H+OKLjQ8BO8K/YcMi0rv/DjkkYvz4wpdaBwkQIECAAAECBAgQIEAgR4E81t85dtelywgIAA2NXATymoAeeCDivvs+DgG32KIUxnX2TsClSyP+938j3n239Gfx4oj0OPGKFRFrrFE6Zt11IwYMKP3p3z+iX7/VOdMxKXT8058iOsK/iRMj9tknF3oXJUCAAAECBAgQIECAAIE2Eshr/d1GxC3RVQFgS5SpeI3MawJK4V36KEgKAVMgl4K5ddaJGDMmYoMNSh8JWbCg9I6+FPqlLQV4H34YsWRJKfzrCABTCLjmmhFrrfVxgJiCwPSOwfRYb/rIR/ra76xZEe+/XwoaU+CYwr8JE0ohoo0AAQIECBAgQIAAAQIECNRTIK/1dz375NzVCwgAqzdzRA0E8p6A0uPAd931cUD3xhulIDCFfelPuttv0aKIDz4oBX8dWwrt0p+OILDjv6cgcO21I9Zbr3RXYLo7MP1Jwd/gwR8HjAce6LHfGgwfpyBAgAABAgQIECBAgACBCgXyXn9X2Ey71VlAAFhnYKfvXKAZJqB0p9+//VvEQw9F/OEPEa+/XrrTL4V76VHeFOSlUDDd4dfxZ9W79tJ+af+OPynsS8FhenQ47ZeO2XDDiO23j9htt4gjjvDBD/8/ECBAgAABAgQIECBAgEBjBZph/d3YHrtaZwICQOMiF4FmmIDSl4FTAPjwwxFPPBGR7gJMYV7a0uO7KQBMd/WlP90FgOlOwRQApj/pMeK0pWPS3X877CAAzGWQuSgBAgQIECBAgAABAgQIRDOsv5UhfwEBYP41aMsW5D0BffoR4DffLAV9lTwC3FGwdAdgx1buEeAUDP7Zn3kEuC0HuU4TIECAAAECBAgQIECgCQTyXn83AYEmRIQA0DDIRSCvCainHwFJ7wHseDx41Y+ApLv8UvjX8RVhHwHJZTi5KAECBAgQIECAAAECBAiUEchr/a0gzSUgAGyuerRNa/KagB54oPQF4PT13xdfLH2VN32dtyPAW7UA6V1+//u/pa8Bp3+m9/ulx3s7AsCOx4T7949IwV/6Z3p34Ke3dFdhul766vCwYaXrpS8B77NP25RbRwkQIECAAAECBAgQIEAgJ4G81t85dddlywgIAFeBmTt3bvzwhz+MO+64I1566aVYe+21Y+utt46jjz46TjvttFgvfeK1Btudd94ZkydPjhkzZsTChQtj4403jvHjx8fXv/71OOigg7q8wgMPPBD/9V//FdOnT4/Zs2fHa6+9Fm+++Wasu+66MWzYsNhrr73ixBNPjJ122qmilqbjU59vueWWeOGFF7Jjhg8fHocffnj8/d//fWyYvmJRhy2PCWj69IgpUz4O/7beOmLLLevQuTKnfOmliDlzPg4BDznEF4Ebp+9KBAgQIECAAAECBAgQaE+BPNbf7Snd3L0WAH5Un9tuuy2OOeaYeOeddzqt2OjRo7NgcOTIkT2u6PLly7OQ79prry17jhTeXX311dGns1vSIt2xtkXMmzevyzasscYacfrpp8f3v//9sudJJ3j44YezoO+VV17p9Hybb755FgzusssuPe5zuQMbPZ2X5acAACAASURBVAGlD35Mnhwxd27Es89GNDr863DoCAHTMNpqq4iTT/Zl4JoPLickQIAAAQIECBAgQIAAgZUCjV5/o29OAQFgRDz22GOx5557xuLFi6N///5x7rnnxsSJE7O/33TTTfHTn/40q14KAWfOnBkD0vOePdjSeS+77LLsyHHjxsXZZ5+d3WE4Z86cuPzyy7N2pC3td8kll3R6hc985jMxYsSI2H333WPUqFGRQroNNtggC/HSXYEpPHw1pV0Rcc4556y83qdPlu5wTHcJpjsQ+/XrF2eeeWYceuih2W633357XHnllbF06dLYZJNN4pFHHsmCx1pujZyA0mO711xTCv5mzowYOjRivfVmxjPPTIkXX/x9LFz4x1i0aGH06bNmDBgwJIYN2zPGjftaDBu2V5ddXrFiebz22qyYN2969mf+/Bnx6qt/iGXLSp8SPu64+2L48L9Y7RypHfPnR6SbNEeNijjxxM4fQa6lt3MRIECAAAECBAgQIECAQHsKNHL93Z7CrdFrAWBETJgwIaZNm5YFYVOnTs3CtVW373znO1lYl7YLLrggLrzwwqqrmx7X/exnP5uFajvvvHN2nfTYbse2aNGi2GeffbKAMbXjqaee6vRuw3R8+r3c9vrrr2d37D333HPZfikY7Owx3q9+9avx85//PDvNzTffHEcdddQnTpn+25e//OWPgqzj4oYbbqi6z10d0MgJaOrUiHvuiXj00dI7/P7nfybEiy9O67Y/O+zw1TjssJ9G375rdbrv44/fGLfeenzZ85QLANM7AVMQmd4huOOOEZ//fMTee3fbHDsQIECAAAECBAgQIECAAIGqBRq5/q66cQ5omEDbB4Dprrldd901Az/55JPjJz/5yWr46dHdbbfdNgvlBg0aFAsWLIg106dfq9hOPfXUuOqqq7IjHnzwwdhtt91WO/qhhx5aGT6m/SdNmlTFFT7eNd1lmO4iTFu6m++Q9LK5VbYUCg4dOjRSvw444IC46667Or3OgQceGHfffXf2GHF67HizzTbrUXs6O6hRE9Abb0QkxvQRjuefLwVuN9wwMt58c052t9822xwVw4btHQMHDosVK5bFSy89GA8+eEW8+27pMettt/1KfOlL/9Jpvx9//Ia49dYTst/S3YObbrpdLFu2JBYseDL7b+UCwPRbetI8BZLpgyAjRkScdlrE4ME143UiAgQIECBAgAABAgQIECCQCTRq/Y27uQXaPgA877zz4tJLL82qlAK4jjDw02VbNVRLodj+++9fcWVXrFiRPUI7f/78GDNmTBYkltvS708//XQW0KXHdNP7/KrdUnCY3gGYtt/85jfxpS996ROnSB8gSWFn2tIjzh13+n36Oum3r3zlK9l/To8Wp/cX1mpr1ASUss1p01LoWnr0N73771/+5dBId/eNHful6NOn72pdWrTotbjuuj3j9ddnZ78df/wDsdVWE1bbLz32+6c/PRxDh46PzTb7XPTrt07cf/+F8cADF2X7dhUApt/TB0HS6xzTDacTJkQccECtdJ2HAAECBAgQIECAAAECBAiUBBq1/ubd3AJtHwB2PP67/vrrx1tvvVX28dp0194ee+yRVfOb3/xmXHRRKeSpZEuP46Z3/aWt3F2GHedJv6eALm3puPS+v2q2dFdfen9hesQ4bf/93/+dPXq86rbq478vv/xy2Tv70m9DhgzJDk3H3HjjjdU0pct9GzEBffhhxJVXRsyeHZE+cJyCtkpv3Jw9+/b45S8Py/qwyy5/Gwcd9MOK+l5NALhkSSmYHD48vV8y4qyzKm9fRY2xEwECBAgQIECAAAECBAi0vUAj1t9tj9wCAG0fAG688cbx2muvxQ477BCPP/542ZK9+eabMfijZzTT+/LSO/Iq3dJjuIcdVgqTvve978UZZ5xR9tD0e/ogR9rSV4cPPvjgbi+zbNmy7F1/6SMi3/3ud+OBBx7Ijvn85z8fv/vd71Y7Pr2DMH3YY+DAgVno2dWW9klfRh4/fnz2kZFabY2YgNIjtrfemr52HDFoUMSYMZW3/sMP34tLL+2fHTBq1MHxV391R0UHVxMAphPOmhWRSpCeQj/88PRxmIouYycCBAgQIECAAAECBAgQIFCRQCPW3xU1xE65CrR1APj++++v/BBHek9eCuq62tIXgt97773s/X3pjsBKt/RewVNOOSXb/de//nUceeSRZQ9Nj+x2fJAjHdfxqG5nB3T1ePCOO+4Yt91228o7+FY9Pr3LL30pON0ZmO4Q7GpL7z78n//5n+wuwXRHYKVbmmC62tK50sdK0pYeda71V4bTedPHm//wh4gnnyy9+2+DDSptfcTixW/E5ZdvmB0wevRh8ZWv/HtFB1cbAHa8C3C77SK23z7ipJMquoydCBAgQIAAAQIECBAgQIBARQICwIqYCr9TWweACxcujE022SQrcnoPXnrnXVfbpptumn0AJIViT6ZUqcJt1a8I33nnnZE+rlFuS7933PWX7uY7Kz0XWmbrLABcb7314oorrogTTjgh1l577U6PTI87p68Op/cdpvcedrWlfdKdfyn8fPfddyvscVT17sJ6BIAffBBx2WUR6XWLqdnjx1fc9GzHp576f3HzzUdk/77HHmfHF77w7YpOUG0AuGJF6YvAAwZEjB0b8U//FFGmbBVd304ECBAgQIAAAQIECBAgQGBVAQGg8ZAE2joATMHTsGHDspFw7LHHxs9+9rMuR0XaNx2T3uf37LPPVjyCvvWtb2XvDUzbPffcE/vuu2/ZY++9997Yb7/9st/Tcd/4xjfK7ttx9156BDjd0XffffdlXzFesmRJnHTSSXH55Zd3+rXivn37Zl8A3nvvvVe+K7DcRTrekZiOWbp0acV9rubjJfUIAOfOjbj++ogZMyIGDiy9Y6/SbcWK5XHttbtH+shH2k46aWYMGbJTRYdXGwCmkz79dOmrwCmkPOGEiK22quhSdiJAgAABAgQIECBAgAABAt0KCAC7JWqLHdo6AGz1OwA7G6EpTNtnn33i+eefjy984QuR7ihM4d2qWyPuAMz7EeD0hPaUKRG//316h1/ER98yqeh/6v/6ryvid7/7h2zfsWOPiKOP/teKjks79SQAnD8/4plnIvbaKyK98jF9rMRGgAABAgQIECBAgAABAgRqISAArIVi65+jrQPAVn8HYLnht+pjxFdffXV8/etf/8SujXgHYHf/a9R7AvrXfy2Ff489FrHTTqVHbCvZXnjhgfj5zz8fy5cvjfXX3yROOeXJ7J+Vbj0JANMjyo88UnpPYQoBjyg9eWwjQIAAAQIECBAgQIAAAQK9Fqj3+rvXDXSChgi0dQCYhDfaaKN4/fXXW/orwJ8eKemR4AEDBsTixYuzuwB/+9vffmKXdvgKcPoASHq3Xnq8dsKEiD59uv//acGC/4nrr9873n//zejXb5045pi7Y6utJnR/4Cp79CQAXL48YurUiM98pvQY8IknVnVJOxMgQIAAAQIECBAgQIAAgbICAkCDIwm0fQDY8Y679FjsW2+9Ff369et0ZKSv/u6xxx7Zb+l9fhdddFHFI+i5557L3huYtvRV3/SevnJb+n3y5MnZz+m4ESNGVHydVXccOnRozJ8/P0aPHh1PpxRsle2rX/1q/PznP8/+S/oab7ojsLMt/Tbko2dn0zE33nhjj9rS2UH1noCuuqp0V91zz5UCwO62N998Pq6/fq949935scYafbPHfseM+WJ3h632e08CwHSSFACmIZLuAvzog9FVX9sBBAgQIECAAAECBAgQIEDg0wL1Xn8Tbw2Btg8AzzvvvLj00kuzaqUv4qav3na2XXbZZXHuuedmP919992x//77V1zhFStWxBZbbJEFcmPGjImn0qdpy2xjx46NWbNmRQrw0vv8qvmYRscpP/zww+wOwPTPHXfcMR5JSdgqWwoYU9CYtvTl4/QF5M629NtXvvKV7KfOHiWuGKCTHes9Af3oR6XHf9PHQNJjtV1tKfRLd/69+eZzKROPww+/IXbY4as96l5PA8Bp0yKGD48YNy7i9NN7dGkHESBAgAABAgQIECBAgACB1QTqvf5G3hoCbR8ATp8+fWXoV+7uvPTF3G233TYL7gYNGhQLFizo9Ou6XZX81FNPjavSbWkRke4m3G233VbbPQWQu3/0BYi0/6RJk3o0in7961/H0UcfnR173HHHxQ033PCJ87zyyitZwJj6dcABB8Rdd93V6XUOPPDALOzs06dPzJs3r+ydgj1pZL0noErvAFy06LW44YZ9YuHCP2bdOOigH8Uuu5zWky5lx/Q0AHQHYI/JHUiAAAECBAgQIECAAAECXQjUe/0NvzUE2j4ATGXqeAw4Pf47derUlSFcRwm/853vxNlnn5399YILLogLL7zwE9W9//77Y+LEiWUDt/TD7NmzY5ttton0fr70Dr50nXXXXXfledL7+lI7Zs6cmT2G/Mc//jFGpc/XrrL9x3/8RwwfPjxGjhxZdnSl4/bbb79IIV/a7rnnnth3331X23/Vx4BTYHjkkUd+Yp/uQsTeDu96T0CVvAPw/fffjp/9bN94+eVHs+7st99lsdde5/Sqaz0JAL0DsFfkDiZAgAABAgQIECBAgACBLgTqvf6G3xoCAsBIj4o+FnvuuWf20Yz+/ftHeiw4BXrp7+kx2I538qX36aWALj1eu+pWSQCY9k+PEKdHidM2bty4OOecc7J3A86ZMye+/e1vZ+3o2O+SSy5ZbQSl4PHiiy/OAr505972228fG264YSxdujTmzp2bfewjvdsvfd04bX/zN38T1157bacjMT1evNNOO8XChQuzwPGss86KQw89NNv39ttvjyuuuCI778YbbxyPPvpo9ghzLbd6T0DdfQV4yZJF8fOf7x8vvfSfWbf23vv/xL77XtzrLvYkAPQV4F6zOwEBAgQIECBAgAABAgQIlBGo9/obfGsICAA/qtNtt90WxxxzTLzzzjudVi6Ff3fccUend99VGgCmR25POumkuO6668qOjq997WtZ4Jgeu/30lgLASj4+0rdv3zjzzDOzdxumfy+3Pfzww3H44YevvFvw0/ulj4PccsstZd+L2JshXu8J6MEHI6ZMifj97yPSjZQffcska/KyZR/GL395WMyZU/o68q67/n0ceOD3e9Odlcf2JACcPz/imWdK7yo8+OCIj54Cr0l7nIQAAQIECBAgQIAAAQIE2lug3uvv9tZtnd4LAFepVbqL7gc/+EEW9KX/QdZaa60s8DvqqKPi9NNPj/XWW6/TylYaAHYcPGXKlCzkmzFjRrz22mux0UYbxfjx47MPcxx00EFlR8/bb78dd955Z6TrPfHEE9kXfNP7CFOw+Gd/9mfZB0bSY8Tp8d6Orw53NxTT9VOfU9D3wgsvZLunLw9/8YtfjDPOOCO7w7AeW70noPTxj+uvj5gxI2LgwIjRoz/uxc03fymeeurfPurrvnHAAd/v8mMrffuuFRtuuMoJVgF5/PFPvl9x1qxb4umnb8322HPPc2Kjjcas3Hvw4JExbNjqXyRJH2lOufP48REnnBCx1Vb1EHdOAgQIECBAgAABAgQIEGhHgXqvv9vRtBX7LABsxaoVoM31noA++CAiPW2dPricHrFN4VrHdtFFa1QlOHDgVnHGGaVw9NNbNefaYYfjsi8Mr7qtWBExc2ZEeqp87Nj0mHjEWmtV1Tw7EyBAgAABAgQIECBAgACBsgL1Xn+jbw0BAWBr1KlwrWzEBJQ+BPKHP0Q8+WTEjjtGbLBBibGa0C7tX88AMN359+ijEdttF7H99hEnnVS4UusQAQIECBAgQIAAAQIECOQo0Ij1d47dc+kKBQSAFULZrbYCjZiAUrB2660RDz8cMWhQxJiPn8atbWd6cbZZsyLeeiu9hzDi8MPTx2F6cTKHEiBAgAABAgQIECBAgACBTwk0Yv0NvfkFBIDNX6NCtrARE9CSJRFXXBExe3ZEer1h+rjGmms2D2dqX/pYyfDhpXcUnnVWc7WveaS0hAABAgQIECBAgAABAgR6KtCI9XdP2+a4xgkIABtn7UqrCDRqArrrrohp00pB29ChEVtv3TxlmDMnYt68UjA5YULEAQc0T9u0hAABAgQIECBAgAABAgSKIdCo9XcxtIrbCwFgcWvb1D1r1AT0xhsRkyZFPPdcxPPPf/JdgHkCdbz778//PH11OeK00yIGD86zRa5NgAABAgQIECBAgAABAkUUaNT6u4h2ReqTALBI1WyhvjRyApo6NeKee0of21i2LGLnnSP69MkPa/ny0pd/+/YtBZKf/3zE3nvn1x5XJkCAAAECBAgQIECAAIHiCjRy/V1cxdbvmQCw9WvYkj1o5ASUArdrrol45pmIRx6JGDIkYuTI/NiefTZi/vyInXaKGDUq4sQT8w0k85NwZQIECBAgQIAAAQIECBCot0Aj19/17ovz91xAANhzO0f2QqDRE9Crr0ZMnhwxd25ECuDSuwC33LIXHejhoS+9FJHe/ZcCyK22ijj55IhNNunhyRxGgAABAgQIECBAgAABAgS6EWj0+ltBmlNAANicdSl8q/KYgGbMiLjjjtL7AF98sfEhYEf4N2xYRHr33yGHRIwfX/hS6yABAgQIECBAgAABAgQI5CiQx/o7x+66dBkBAaChkYtAXhPQAw9E3HffxyHgFluUwrh6vhMwPYKcQsc//SmiI/ybODFin31yoXdRAgQIECBAgAABAgQIEGgjgbzW321E3BJdFQC2RJmK18i8JqAVKyLSR0FSCJgCuRTMrbNOxJgxERtsUHvn9LXfWbMi3n+/FDSmwDGFfxMmRKyxRu2v54wECBAgQIAAAQIECBAgQGBVgbzW36rQXAICwOaqR9u0Ju8JKD0OfNddER0B3bvvlt4JmO7QW3PN3pdhyZLSY8bpsd8BAz4OGA880GO/vdd1BgIECBAgQIAAAQIECBCoVCDv9Xel7bRffQUEgPX1dfYyAs0wAS1YEHHLLRHz5pWCuhdeKDU2fZQjfSk4BXfV3KWX7i5MQWI638KFpXMNH14KFocOjTj8cB/88D8EAQIECBAgQIAAAQIECDRWoBnW343tsat1JiAANC5yEWiWCWjZsoj//M+I9G7A9Jjuyy9HzJ9f+vf11y89FpyCwPQn/X3VdwWmd/u9914p9Et/0t2E6e/pkeIUIG6+eenf/+IvIvbcs77vGcyliC5KgAABAgQIECBAgAABAk0v0Czr76aHKngDBYAFL3Czdq/ZJqA33ohIjwU/9ljE4sUR6e/pLr4U7C1aFJHu7ktbCgDTXYHp7ykATFv6+3rrlULCjTeOGDw4Yt11I8aNKz3um/5uI0CAAAECBAgQIECAAAECeQg02/o7DwPXjBAAGgW5CDTrBJTe3fff/x0xc2bpTsAU9KW7BNOdfelPCv3SnxQEpj/prsD0p2/fUhCY7vzbeeeIbbetzbsEcymOixIgQIAAAQIECBAgQIBAYQSadf1dGOAW6YgAsEUKVbRmtsIE9MEHEa+8UgoC06PB6a7AFBCmQDAFfuljIenuvvSobwr+NtssYu21i1Yp/SFAgAABAgQIECBAgACBVhZohfV3K/u2StsFgK1SqYK10wRUsILqDgECBAgQIECAAAECBAg0pYD1d1OWpeGNEgA2nNwFk4AJyDggQIAAAQIECBAgQIAAAQL1F7D+rr9xK1xBANgKVSpgG01ABSyqLhEgQIAAAQIECBAgQIBA0wlYfzddSXJpkAAwF3YXNQEZAwQIECBAgAABAgQIECBAoP4C1t/1N26FKwgAW6FKBWyjCaiARdUlAgQIECBAgAABAgQIEGg6AevvpitJLg0SAObC7qImIGOAAAECBAgQIECAAAECBAjUX8D6u/7GrXAFAWArVKmAbTQBFbCoukSAAAECBAgQIECAAAECTSdg/d10JcmlQQLAXNhd1ARkDBAgQIAAAQIECBAgQIAAgfoLWH/X37gVriAAbIUqFbCNJqACFlWXCBAgQIAAAQIECBAgQKDpBKy/m64kuTRIAJgLu4uagIwBAgQIECBAgAABAgQIECBQfwHr7/obt8IVBICtUKUCttEEVMCi6hIBAgQIECBAgAABAgQINJ2A9XfTlSSXBgkAc2F3UROQMUCAAAECBAgQIECAAAECBOovYP1df+NWuIIAsBWqVMA2moAKWFRdIkCAAAECBAgQIECAAIGmE7D+brqS5NIgAWAu7C5qAjIGCBAgQIAAAQIECBAgQIBA/QWsv+tv3ApXEAC2QpUK2EYTUAGLqksECBAgQIAAAQIECBAg0HQC1t9NV5JcGiQAzIXdRU1AxgABAgQIECBAgAABAgQIEKi/gPV3/Y1b4QoCwFaoUgHbaAIqYFF1iQABAgQIECBAgAABAgSaTsD6u+lKkkuDBIC5sLuoCcgYIECAAAECBAgQIECAAAEC9Rew/q6/cStcQQDYClUqYBtNQAUsqi4RIECAAAECBAgQIECAQNMJWH83XUlyaZAAMBd2FzUBGQMECBAgQIAAAQIECBAgQKD+Atbf9TduhSsIAFuhSgVsowmogEXVJQIECBAgQIAAAQIECBBoOgHr76YrSS4NEgDmwu6iJiBjgAABAgQIECBAgAABAgQI1F/A+rv+xq1wBQFgK1SpgG00ARWwqLpEgAABAgQIECBAgAABAk0nYP3ddCXJpUECwFzYXdQEZAwQIECAAAECBAgQIECAAIH6C1h/19+4Fa4gAGyFKhWwjSagAhZVlwgQIECAAAECBAgQIECg6QSsv5uuJLk0SACYC7uLmoCMAQIECBAgQIAAAQIECBAgUH8B6+/6G7fCFQSArVClArbRBFTAouoSAQIECBAgQIAAAQIECDSdgPV305UklwYJAHNhd1ETkDFAgAABAgQIECBAgAABAgTqL2D9XX/jVriCALAVqlTANpqAClhUXSJAgAABAgQIECBAgACBphOw/m66kuTSIAFgLuwuagIyBggQIECAAAECBAgQIECAQP0FrL/rb9wKVxAAtkKVCthGE1ABi6pLBAgQIECAAAECBAgQINB0AtbfTVeSXBokAMyF3UVNQMYAAQIECBAgQIAAAQIECBCov4D1d/2NW+EKAsBWqFIB22gCKmBRdYkAAQIECBAgQIAAAQIEmk7A+rvpSpJLgwSAubC7qAnIGCBAgAABAgQIECBAgAABAvUXsP6uv3ErXEEA2ApVKmAbTUAFLKouESBAgAABAgQIECBAgEDTCVh/N11JcmmQADAXdhc1ARkDBAgQIECAAAECBAgQIECg/gLW3/U3boUrCABboUoFbKMJqIBF1SUCBAgQIECAAAECBAgQaDoB6++mK0kuDRIA5sLuoiYgY4AAAQIECBAgQIAAAQIECNRfwPq7/satcAUBYCtUqYBtNAEVsKi6RIAAAQIECBAgQIAAAQJNJ2D93XQlyaVBAsBc2F3UBGQMECBAgAABAgQIECBAgACB+gtYf9ffuBWuIABshSoVsI0moAIWVZcIECBAgAABAgQIECBAoOkErL+briS5NEgAmAu7i5qAjAECBAgQIECAAAECBAgQIFB/Aevv+hu3whUEgK1QpQK20QRUwKLqEgECBAgQIECAAAECBAg0nYD1d9OVJJcGCQBzYXdRE5AxQIAAAQIECBAgQIAAAQIE6i9g/V1/41a4ggCwFapUwDaagApYVF0iQIAAAQIECBAgQIAAgaYTsP5uupLk0iABYC7sLmoCMgYIECBAgAABAgQIECBAgED9Bay/62/cClcQALZClQrYRhNQAYuqSwQIECBAgAABAgQIECDQdALW301XklwaJADMhd1FTUDGAAECBAgQIECAAAECBAgQqL+A9Xf9jVvhCgLAVqhSAdtoAipgUXWJAAECBAgQIECAAAECBJpOwPq76UqSS4MEgLmwu6gJyBggQIAAAQIECBAgQIAAAQL1F7D+rr9xK1xBANgKVSpgG01ABSyqLhEgQIAAAQIECBAgQIBA0wlYfzddSXJpkAAwF3YXNQEZAwQIECBAgAABAgQIECBAoP4C1t/1N26FKwgAW6FKBWyjCaiARdUlAgQIECBAgAABAgQIEGg6AevvpitJLg0SAObC7qImIGOAAAECBAgQIECAAAECBAjUX8D6u/7GrXAFAWArVKmAbTQBFbCoukSAAAECBAgQIECAAAECTSdg/d10JcmlQQLAXNhd1ARkDBAgQIAAAQIECBAgQIAAgfoLWH/X37gVriAAbIUqFbCNJqACFlWXCBAgQIAAAQIECBAgQKDpBKy/m64kuTRIAJgLu4uagIwBAgQIECBAgAABAgQIECBQfwHr7/obt8IVBICtUKUCttEEVMCi6hIBAgQIECBAgAABAgQINJ2A9XfTlSSXBgkAc2F3UROQMUCAAAECBAgQIECAAAECBOovYP1df+NWuIIAsBWqVMA2moAKWFRdIkCAAAECBAgQIECAAIGmE7D+brqS5NIgAWAu7C5qAjIGCBAgQIAAAQIECBAgQIBA/QWsv+tv3ApXEAC2QpUK2EYTUAGLqksECBAgQIAAAQIECBAg0HQC1t9NV5JcGiQAzIXdRU1AxgABAgQIECBAgAABAgQIEKi/gPV3/Y1b4QoCwFaoUgHbaAIqYFF1iQABAgQIECBAgAABAgSaTsD6u+lKkkuDBIC5sLuoCcgYIECAAAECBAgQIECAAAEC9Rew/q6/cStcQQDYClUqYBtNQAUsqi4RIECAAAECBAgQIECAQNMJWH83XUlyaZAAcBX2uXPnxg9/+MO444474qWXXoq11147tt566zj66KPjtNNOi/XWW68mRbrzzjtj8uTJMWPGjFi4cGFsvPHGMX78+Pj6178eBx10UJfXePXVV+O2226Le++9Nx5//PF48cUX48MPP4wNN9wwdthhhzjiiCPi2GOPjXXXXbfL86yxxhoVnXoTcwAAIABJREFU9WWfffaJ+++/v6J9q9nJBFSNln0JECBAgAABAgQIECBAgEDPBKy/e+ZWtKMEgB9VNIVqxxxzTLzzzjud1nj06NFZMDhy5Mgej4Hly5dnId+1115b9hwnnnhiXH311dGnT5/V9vnpT38ap5xySixbtqzLNowaNSp+85vfxPbbb192PwFgj8voQAIECBAgQIAAAQIECBAg0DICAsCWKVVdGyoAjIjHHnss9txzz1i8eHH0798/zj333Jg4cWL295tuuilS8Ja2FALOnDkzBgwY0KOipPNedtll2bHjxo2Ls88+O7vDcM6cOXH55Zdn7Uhb2u+SSy5Z7RoXX3xxnH/++bHWWmvFoYceGvvvv3+MHTs2a086R2rnb3/72+y4dFfho48+GltssUWnbe0IAFOgeOqpp5btz/rrrx8jRozoUX+7OsgEVHNSJyRAgAABAgQIECBAgAABAqsJWH8bFElAABgREyZMiGnTpkW/fv1i6tSpsfvuu39idHznO9/Jwrq0XXDBBXHhhRdWPXpmz54dn/3sZ2Pp0qWx8847Z9dZ9THdRYsWRXrcNgWMqR1PPfXUancbfu9734v0CPBZZ52VBXydbem3K6+8MvvphBNOiOuuu67LALCn/aka4FMHmIB6K+h4AgQIECBAgAABAgQIECDQvYD1d/dG7bBH2weA06dPj1133TWr9cknnxw/+clPVqt7enR32223zUK5QYMGxYIFC2LNNdesanyku+yuuuqq7JgHH3wwdtttt9WOf+ihh1aGj2n/SZMmVXWNtHN6H+Dw4cPj5ZdfjoEDB8Ybb7zR6ePEHXcACgCrJnYAAQIECBAgQIAAAQIECBBoGQEBYMuUqq4NbfsA8LzzzotLL700Q04BXEcY+Gn19OhuejQ3bXfffXf2+G2l24oVK7JHcefPnx9jxozJgsRyW/r96aefjqFDh2YfIqn0XX2rnu+oo47K3gGYthRWdna3oACw0urZjwABAgQIECBAgAABAgQItK6AALB1a1fLlrd9ANjx+G96191bb72VPX7b2Zbu2ttjjz2yn775zW/GRRddVHEdnnvuuexdf2krd5dhx8nS7+kLwWlLx/Xk/Xt/+Zd/mX0pOG2vv/56DB48eLW2CgArLp8dCRAgQIAAAQIECBAgQIBAywoIAFu2dDVteNsHgOnuuNdeey122GGHePzxx8vivvnmmyuDtHSH3c0331xxIW6//fY47LDDsv3Te/zOOOOMssem388888zs9/TV4YMPPrji66QdlyxZEkOGDMn6tOmmm8Yrr7zS6fEdAeA222wT6Q7FF154Ifr27RubbbZZFnQef/zx2YdQ6rWZgOol67wECBAgQIAAAQIECBAgQOBjAetvoyEJtHUA+P7776/8EMchhxwSKajraktfCH7vvfey9/elOwIr3dJ7BdPXdtP261//Oo488siyh6ZHd1PAmLZ0XLojsJotvTfw9NNPzw5J//znf/7nTg+v5NHiww8/PG644YbsXYLVbmmC6WpL7yjcZZddsl3So87lvlZc7XXtT4AAAQIECBAgQIAAAQIECHwsIAA0GpJAWweACxcujE022SQbCV/+8pfjpptu6nJUpDvq0jv10gdBnnzyyYpH0KpfEb7zzjvjwAMPLHts+r3jrr/vfve72Rd/K93SI8M77rhjvP3225HCyvQuwXQ3YGdbeuQ5PSq83377Ze8lTPsnjwceeCALHtOjw2lLXyb+3e9+V/VHTyoJGDvaJQCstML2I0CAAAECBAgQIECAAAEC1QkIAKvzKurebR0ApuBp2LBhWW2PPfbY+NnPftZlndO+6Zj0Pr9nn3224jHxrW99K3tvYNruueee2Hfffcsee++992ahXNrScd/4xjcqus6iRYuyR3efeOKJbP/rr78+e4y33Jbed5i+aNzZ9uqrr8ZBBx0Ujz32WPbzD37wg/i7v/u7itrRsZMAsCouOxMgQIAAAQIECBAgQIAAgboICADrwtpyJ23rALAodwAuXbo0vvjFL8aUKVOyAZgeN/7xj3/cq8GY7iZMdwamdwqOHDkynnnmmarO5xHgqrjsTIAAAQIECBAgQIAAAQIE6iIgAKwLa8udtK0DwCK8AzB9wCPdvfiLX/wiG3xHH310/PKXv4w+ffr0ejCm9yJ2hIrz5s0r+zhxTy5kAuqJmmMIECBAgAABAgQIECBAgEB1Atbf1XkVde+2DgBTUTfaaKPsfXet+hXgU089Na666qpsfKbHdm+99daq39dXbnD/4z/+Y6T3EKZt+vTpMX78+Jr9f2ACqhmlExEgQIAAAQIECBAgQIAAgbIC1t8GRxJo+wBwwoQJMW3atEgfxUjvxevXr1+nIyN99Te9Yy9t6X1+F110UcUjKD1Om94bmLb0Vd/0kY1yW/p98uTJ2c/puBEjRpTd95xzzonLL788+z3146677lr5VeOKG9fFjmeffXakD5ikTQBYC1HnIECAAAECBAgQIECAAAECjRUQADbWu1mv1vYB4HnnnReXXnppVp+HHnoodt11105rddlll8W5556b/Xb33XfH/vvvX3FN02O6W2yxRcyfPz97r95TTz1V9tixY8fGrFmzYujQodkHR8p9TOPiiy+O888/PztPujMvfVxkwIABFbepkh0PPfTQuOOOO7Jd04SR2lSrzQRUK0nnIUCAAAECBAgQIECAAAEC5QWsv42OJND2AWC6s60j9Ct3d97y5ctj2223zYK79OXcBQsWVP2Y7aqP6qa7CXfbbbfVRmAKIHfffffsv6f9J02a1OkoTV/lPeOMM7Lftttuu7j//vtj8ODBNR3Rzz//fBZWfvjhh1V/9biShpiAKlGyDwECBAgQIECAAAECBAgQ6J2A9Xfv/IpydNsHgKmQHY8Bp8d/p06dujKE6yhyegw2PQ6btgsuuCAuvPDCT9Q/BXATJ07M/ttxxx0XN9xww2rjY/bs2bHNNtvEsmXLYuedd86us+66667cb/HixVk7Zs6cmT2G/Mc//jFGjRq12nmuv/76+NrXvhbprsLRo0dn59l0002rGo+33XZb9r7Aco87v/rqq9nvjz32WHbeK664Is4888yqrtHdziag7oT8ToAAAQIECBAgQIAAAQIEei9g/d17wyKcQQAYkQVde+65Z6QQrn///pEeC06BXvr7TTfdtPKdfClwSwHdpx+1rSQATIMlPUKcHiVO27hx4yK9wy+9G3DOnDnx7W9/e2Xglva75JJLVhtft9xySxx55JFZiLjBBhvEr371q+zR4q629A7B9H7DVbfhw4fHkiVL4ktf+lIWdqa/pzDytddey+4mvPrqq7N/T9tee+0V//Ef/xFrr712Tce7CaimnE5GgAABAgQIECBAgAABAgQ6FbD+NjCSgADwo3GQ7oo75phj4p133ul0ZKTwL70Pb+TIkav9XmkAmB4lPumkk+K6664rO/rS3X3pIyB9+vRZbZ/jjz8+brzxxqpG7n333Rd/8Rd/sVoAOHfu3G7PkwLCa665JnvsudabCajWos5HgAABAgQIECBAgAABAgRWF7D+NioEgJ8aAykUS+/XS0Ff+h9krbXWygK/o446Kk4//fRYb731Oh01lQaAHQdPmTIlC/lmzJiR3Wm30UYbZR/ySO8gTI/elttqFQA+8MADkf6kdxGmLw2nNqTgM939uOWWW2ZfO06PMne8j7Ae/6uYgOqh6pwECBAgQIAAAQIECBAgQOCTAtbfRoQA0BjITcAElBu9CxMgQIAAAQIECBAgQIBAGwlYf7dRsbvoqkeAjYNcBExAubC7KAECBAgQIECAAAECBAi0mYD1d5sVvEx3BYDGQS4CJqBc2F2UAAECBAgQIECAAAECBNpMwPq7zQouAFTwZhIwATVTNbSFAAECBAgQIECAAAECBIoqYP1d1MpW1y93AFbnZe8aCZiAagTpNAQIECBAgAABAgQIECBAoAsB62/DIwkIAI2DXARMQLmwuygBAgQIECBAgAABAgQItJmA9XebFbxMdwWAxkEuAiagXNhdlAABAgQIECBAgAABAgTaTMD6u80KLgBU8GYSMAE1UzW0hQABAgQIECBAgAABAgSKKmD9XdTKVtcvdwBW52XvGgmYgGoE6TQECBAgQIAAAQIECBAgQKALAetvwyMJCACNg1wETEC5sLsoAQIECBAgQIAAAQIECLSZgPV3mxW8THcFgMZBLgImoFzYXZQAAQIECBAgQIAAAQIE2kzA+rvNCi4AVPBmEjABNVM1tIUAAQIECBAgQIAAAQIEiipg/V3UylbXL3cAVudl7xoJmIBqBOk0BAgQIECAAAECBAgQIECgCwHrb8MjCQgAjYNcBExAubC7KAECBAgQIECAAAECBAi0mYD1d5sVvEx3BYDGQS4CJqBc2F2UAAECBAgQIECAAAECBNpMwPq7zQouAFTwZhIwATVTNbSFAAECBAgQIECAAAECBIoqYP1d1MpW1y93AFbnZe8aCZiAagTpNAQIECBAgAABAgQIECBAoAsB62/DIwkIAI2DXARMQLmwuygBAgQIECBAgAABAgQItJmA9XebFbxMdwWAxkEuAiagXNhdlAABAgQIECBAgAABAgTaTMD6u80KLgBU8GYSMAE1UzW0hQABAgQIECBAgAABAgSKKmD9XdTKVtcvdwBW52XvGgmYgGoE6TQECBAgQIAAAQIECBAgQKALAetvwyMJCACNg1wETEC5sLsoAQIECBAgQIAAAQIECLSZgPV3mxW8THcFgMZBLgImoFzYXZQAAQIECBAgQIAAAQIE2kzA+rvNCi4AVPBmEjABNVM1tIUAAQIECBAgQIAAAQIEiipg/V3UylbXL3cAVudl7xoJmIBqBOk0BAgQIECAAAECBAgQIECgCwHrb8MjCQgAjYNcBExAubC7KAECBAgQIECAAAECBAi0mYD1d5sVvEx3BYDGQS4CJqBc2F2UAAECBAgQIECAAAECBNpMwPq7zQouAFTwZhIwATVTNbSFAAECBAgQIECAAAECBIoqYP1d1MpW1y93AFbnZe8aCZiAagTpNAQIECBAgAABAgQIECBAoAsB62/DIwkIAI2DXARMQLmwuygBAgQIECBAgAABAgQItJmA9XebFbxMdwWAxkEuAiagXNhdlAABAgQIECBAgAABAgTaTMD6u80KLgBU8GYSMAE1UzW0hQABAgQIECBAgAABAgSKKmD9XdTKVtcvdwBW52XvGgmYgGoE6TQECBAgQIAAAQIECBAgQKALAetvwyMJCACNg1wETEC5sLsoAQIECBAgQIAAAQIECLSZgPV3mxW8THcFgMZBLgImoFzYXZQAAQIECBAgQIAAAQIE2kzA+rvNCi4AVPBmEjABNVM1tIUAAQIECBAgQIAAAQIEiipg/V3UylbXL3cAVudl7xoJmIBqBOk0BAgQIECAAAECBAgQIECgCwHrb8MjCQgAjYNcBExAubC7KAECBAgQIECAAAECBAi0mYD1d5sVvEx3BYDGQS4CJqBc2F2UAAECBAgQIECAAAECBNpMwPq7zQouAFTwZhIwATVTNbSFAAECBAgQIECAAAECBIoqYP1d1MpW1y93AFbnZe8aCZiAagTpNAQIECBAgAABAgQIECBAoAsB62/DIwkIAI2DXARMQLmwuygBAgQIECBAgAABAgQItJmA9XebFbxMdwWAxkEuAiagXNhdlAABAgQIECBAgAABAgTaTMD6u80KLgBU8GYSMAE1UzW0hQABAgQIECBAgAABAgSKKmD9XdTKVtcvdwBW52XvGgmYgGoE6TQECBAgQIAAAQIECBAgQKALAetvwyMJCACNg1wETEC5sLsoAQIECBAgQIAAAQIECLSZgPV3mxW8THcFgMZBLgImoFzYXZQAAQIECBAgQIAAAQIE2kzA+rvNCi4AVPBmEjABNVM1tIUAAQIECBAgQIAAAQIEiipg/V3UylbXL3cAVudl7xoJmIBqBOk0BAgQIECAAAECBAgQIECgCwHrb8MjCQgAjYNcBExAubC7KAECBAgQIECAAAECBAi0mYD1d5sVvEx3BYDGQS4CJqBc2F2UAAECBAgQIECAAAECBNpMwPq7zQouAFTwZhIwATVTNbSFAAECBAgQIECAAAECBIoqYP1d1MpW1y93AFbnZe8aCZiAagTpNAQIECBAgAABAgQIECBAoAsB62/DIwkIAI2DXARMQLmwuygBAgQIECBAgAABAgQItJmA9XebFbxMdwWAxkEuAiagXNhdlAABAgQIECBAgAABAgTaTMD6u80KLgBU8GYSMAE1UzW0hQABAgQIECBAgAABAgSKKmD9XdTKVtcvdwBW52XvGgmYgGoE6TQECBAgQIAAAQIECBAgQKALAetvwyMJCACNg1wETEC5sLsoAQIECBAgQIAAAQIECLSZgPV3mxW8THcFgMZBLgImoFzYXZQAAQIECBAgQIAAAQIE2kzA+rvNCi4AVPBmEjABNVM1tIUAAQIECBAgQIAAAQIEiipg/V3UylbXL3cAVudl7xoJmIBqBOk0BAgQIECAAAECBAgQIECgCwHrb8MjCQgAjYNcBExAubC7KAECBAgQIECAAAECBAi0mYD1d5sVvEx3BYDGQS4CJqBc2F2UAAECBAgQIECAAAECBNpMwPq7zQouAFTwZhIwATVTNbSFAAECBAgQIECAAAECBIoqYP1d1MpW1y93AFbnZe8aCZiAagTpNAQIECBAgAABAgQIECBAoAsB62/DIwkIAI2DXARMQLmwuygBAgQIECBAgAABAgQItJmA9XebFbxMdwWAxkEuAiagXNhdlAABAgQIECBAgAABAgTaTMD6u80KLgBU8GYSMAE1UzW0hQABAgQIECBAgAABAgSKKmD9XdTKVtcvdwBW52XvGgmYgGoE6TQECBAgQIAAAQIECBAgQKALAetvwyMJCACNg1wETEC5sLsoAQIECBAgQIAAAQIECLSZgPV3mxW8THcFgMZBLgImoFzYXZQAAQIECBAgQIAAAQIE2kzA+rvNCi4AVPBmEjABNVM1tIUAAQIECBAgQIAAAQIEiipg/V3UylbXL3cAVudl7xoJmIBqBOk0BAgQIECAAAECBAgQIECgCwHrb8MjCQgAjYNcBExAubC7KAECBAgQIECAAAECBAi0mYD1d5sVvEx3BYDGQS4CJqBc2F2UAAECBAgQIECAAAECBNpMwPq7zQouAFTwZhIwATVTNbSFAAECBAgQIECAAAECBIoqYP1d1MpW1y93AFbnZe8aCZiAagTpNAQIECBAgAABAgQIECBAoAsB62/DIwkIAI2DXARMQLmwuygBAgQIECBAgAABAgQItJmA9XebFbxMdwWAxkEuAiagXNhdlAABAgQIECBAgAABAgTaTMD6u80KLgBU8GYSMAE1UzW0hQABAgQIECBAgAABAgSKKmD9XdTKVtcvdwBW52XvGgmYgGoE6TQECBAgQIAAAQIECBAgQKALAetvwyMJCACNg1wETEC5sLsoAQIECBAgQIAAAQIECLSZgPV3mxW8THcFgMZBLgImoFzYXZQAAQIECBAgQIAAAQIE2kzA+rvNCi4AVPBmEjABNVM1tIUAAQIECBAgQIAAAQIEiipg/V3UylbXL3cAVudl7xoJmIBqBOk0BAgQIECAAAECBAgQIECgCwHrb8MjCQgAVxkHc+fOjR/+8Idxxx13xEsvvRRrr712bL311nH00UfHaaedFuutt15NRs2dd94ZkydPjhkzZsTChQtj4403jvHjx8fXv/71OOigg7q8xquvvhq33XZb3HvvvfH444/Hiy++GB9++GFsuOGGscMOO8QRRxwRxx57bKy77roVtbVRff50Y0xAFZXHTgQIECBAgAABAgQIECBAoFcC1t+94ivMwQLAj0qZQrVjjjkm3nnnnU6LO3r06CwYHDlyZI+Lv3z58izku/baa8ue48QTT4yrr746+vTps9o+P/3pT+OUU06JZcuWddmGUaNGxW9+85vYfvvtu9yvEX0u1wATUI+HkQMJECBAgAABAgQIECBAgEDFAtbfFVMVekcBYEQ89thjseeee8bixYujf//+ce6558bEiROzv990002Rgre0pRBw5syZMWDAgB4NinTeyy67LDt23LhxcfbZZ2d3GM6ZMycuv/zyrB1pS/tdcsklq13j4osvjvPPPz/WWmutOPTQQ2P//fePsWPHZu1J50jt/O1vf5sdl+4qfPTRR2OLLbbotK2N6rMAsEdDxUEECBAgQIAAAQIECBAgQKAmAgLAmjC2/EkEgBExYcKEmDZtWvTr1y+mTp0au++++ycK+53vfCcL69J2wQUXxIUXXlh14WfPnh2f/exnY+nSpbHzzjtn11n1Md1FixbFPvvskwWMqR1PPfXUancbfu9734v0CPBZZ52VBXydbem3K6+8MvvphBNOiOuuu67T/RrR566QTEBVDyEHECBAgAABAgQIECBAgACBqgWsv6smK+QBbR8ATp8+PXbdddesuCeffHL85Cc/Wa3Q6dHdbbfdNgvlBg0aFAsWLIg111yzqgFx6qmnxlVXXZUd8+CDD8Zuu+222vEPPfTQyvAx7T9p0qSqrpF2Tu8DHD58eLz88ssxcODAeOONN1Z7nLhRfRYAVl0+BxAgQIAAAQIECBAgQIAAgZoKCABrytmyJ2v7APC8886LSy+9NCtgCuA6wsBPVzQ9upsezU3b3XffnT1+W+m2YsWK7FHc+fPnx5gxY7IgsdyWfn/66adj6NCh2YdI1lhjjUovs3K/o446KnsHYNpSWPnpuwUb0efuGm0C6k7I7wQIECBAgAABAgQIECBAoPcC1t+9NyzCGdo+AOx4FHb99dePt956K3v8trMt3bW3xx57ZD9985vfjIsuuqji+j/33HPZu/7SVu4uw46Tpd/TF4LTlo4bMWJExdfp2PEv//Ivsy8Fp+3111+PwYMHf+Icjehzd402AXUn5HcCBAgQIECAAAECBAgQINB7Aevv3hsW4QxtHwCmu+Nee+212GGHHeLxxx8vW9M333xzZZCW7rC7+eabK67/7bffHocddli2f3qP3xlnnFH22PT7mWeemf2evjp88MEHV3ydtOOSJUtiyJAhWZ823XTTeOWVV1Y7vhF97q7RJqDuhPxOgAABAgQIECBAgAABAgR6L2D93XvDIpyhrQPA999/f+WHOA455JBIQV1XW/pC8HvvvZe9vy/dEVjplt4reMopp2S7//rXv44jjzyy7KHp0d0UMKYtHZfuCKxmS+8NPP3007ND0j//+Z//+ROHN6rPaYLpakvvKNxll12yXdKjzuW+VlxN3+1LgAABAgQIECBAgAABAgQIfFJAAGhEJIG2DgAXLlwYm2yySTYSvvzlL8dNN93U5ahId9Sld+qlD4I8+eSTFY+gVb8ifOedd8aBBx5Y9tj0e8ddf9/97nezL/5WuqVHhnfcccd4++23I4WV6V2C6W7AVbdG9bmadxcKACutsP0IECBAgAABAgQIECBAgEB1AgLA6ryKundbB4ApeBo2bFhW22OPPTZ+9rOfdVnntG86Jr3P79lnn614THzrW9/K3huYtnvuuSf23Xffssfee++9sd9++2W/p+O+8Y1vVHSdRYsWZe8ofOKJJ7L9r7/++jj++ONXO7ZRfRYAVlQ2OxEgQIAAAQIECBAgQIAAgboKCADrytsyJ2/rALBRd8PV+w7ApUuXxhe/+MWYMmVKNvDS48Y//vGPOx2EjeqzR4BbZg7QUAIECBAgQIAAAQIECBAosIAAsMDFraJrbR0ANup9ePV8B+CKFSuyuxd/8YtfZGU/+uij45e//GX06dOn02HQqD53NwZNQN0J+Z0AAQIECBAgQIAAAQIECPRewPq794ZFOENbB4CpgBtttFG8/vrrLfsV4FNPPTWuuuqqbCwedNBBceutt8aaa67Z5dhsRJ+7+5/DBNSdkN8JECBAgAABAgQIECBAgEDvBay/e29YhDO0fQA4YcKEmDZtWqy//vrx1ltvRb9+/Tqta/rqb3rHXtrS+/wuuuiiiuufPs6R3huYtvRV33RHYLkt/T558uTs53TciBEjyu57zjnnxOWXX579nvpx1113rfyqcVeNa0Sfu8MxAXUn5HcCBAgQIECAAAECBAgQINB7Aevv3hsW4QxtHwCed955cemll2a1fOihh2LXXXfttK6XXXZZnHvuudlvd999d+y///4V1z89prvFFlvE/PnzY8yYMfHUU0+VPXbs2LExa9asGDp0aPbBkXIf07j44ovj/PPPz84zfvz47OMiAwYMqKhNjehzdw0xAXUn5HcCBAgQIECAAAECBAgQINB7Aevv3hsW4QxtHwBOnz59ZehX7u685cuXx7bbbpsFd4MGDYoFCxZ0+5jtpwfHqo/qprsJd9ttt9XGTwogd9999+y/p/0nTZrU6Rj7wQ9+EGeccUb223bbbRf3339/DB48uOLx2Kg+d9UgE1DF5bIjAQIECBAgQIAAAQIECBDosYD1d4/pCnVg2weAqZodj8Smx3+nTp26MoTrqPSqX/G94IIL4sILL/zEIEgB3MSJE7P/dtxxx8UNN9yw2iCZPXt2bLPNNrFs2bLYeeeds+usu+66K/dbvHhx1o6ZM2dmjyH/8Y9/jFGjRq12nuuvvz6+9rWvRbqrcPTo0dl5Nt1006oHZW/7XPUFP3WACai3go4nQIAAAQIECBAg8P+zdyfQllX1gfD/FBTIUEAIoAwCJQUC4gBSMoZBbMIQW1tFk7WwxSVoBDsxkmDD5xJoswDn6CdBQRH9MpRDuk2QKWlUQIVQZaAlLWMhJVoMhUIKoUCG+tb/XG/xKN59dzj3vXPeOb+z1ltV7929z9n7999v37v/7wwECBAg0F/A+ru/URtKSABGxI033hgHHnhgZBJuk002ibydpT+MAAAgAElEQVRENhN6+f2iRYvW3JMvE26ZoFv7UttBEoA5mPIS4ryUOLe99tor8h5+eW/ApUuXxkc/+tGiHd1yZ5999vPG37e+9a14y1veUiQRN9100/ja175WXFo81Zb3EMz7G669le1z2V8OE1BZQfUJECBAgAABAgQIECBAgEB/Aevv/kZtKCEB+NsoX3LJJXHcccfFypUrJ417Jv8uvfTSWLBgwfNeHzQBmJcSn3jiiXHRRRf1HFt5dl8+BGTOnDnPK3P88cfHV77ylaHG5Xe/+9049NBDJ61Tps9DNWKSwiagsoLqEyBAgAABAgQIECBAgACB/gLW3/2N2lBCAnBClJctWxZ5f71M9OUvyPrrr18k/I499th43/veFxtttNGkY2LQBGC38mWXXVYk+RYvXhwPPvhgbLnllsWDPPIehEcddVTPcTfuBGAeaNQ+l/3lMAGVFVSfAAECBAgQIECAAAECBAj0F7D+7m/UhhISgG2Icg37aAKqYVA0iQABAgQIECBAgAABAgQaJ2D93biQjtQhCcCR2FQqK2ACKiuoPgECBAgQIECAAAECBAgQ6C9g/d3fqA0lJADbEOUa9tEEVMOgaBIBAgQIECBAgAABAgQINE7A+rtxIR2pQxKAI7GpVFbABFRWUH0CBAgQIECAAAECBAgQINBfwPq7v1EbSkgAtiHKNeyjCaiGQdEkAgQIECBAgAABAgQIEGicgPV340I6UockAEdiU6msgAmorKD6BAgQIECAAAECBAgQIECgv4D1d3+jNpSQAGxDlGvYRxNQDYOiSQQIECBAgAABAgQIECDQOAHr78aFdKQOSQCOxKZSWQETUFlB9QkQIECAAAECBAgQIECAQH8B6+/+Rm0oIQHYhijXsI8moBoGRZMIECBAgAABAgQIECBAoHEC1t+NC+lIHZIAHIlNpbICJqCyguoTIECAAAECBAgQIECAAIH+Atbf/Y3aUEICsA1RrmEfTUA1DIomESBAgAABAgQIECBAgEDjBKy/GxfSkTokATgSm0plBUxAZQXVJ0CAAAECBAgQIECAAAEC/QWsv/sbtaGEBGAbolzDPpqAahgUTSJAgAABAgQIECBAgACBxglYfzcupCN1SAJwJDaVygqYgMoKqk+AAAECBAgQIECAAAECBPoLWH/3N2pDCQnANkS5hn00AdUwKJpEgAABAgQIECBAgAABAo0TsP5uXEhH6pAE4EhsKpUVMAGVFVSfAAECBAgQIECAAAECBAj0F7D+7m/UhhISgG2Icg37aAKqYVA0iQABAgQIECBAgAABAgQaJ2D93biQjtQhCcCR2FQqK2ACKiuoPgECBAgQIECAAAECBAgQ6C9g/d3fqA0lJADbEOUa9tEEVMOgaBIBAgQIECBAgAABAgQINE7A+rtxIR2pQxKAI7GpVFbABFRWUH0CBAgQIECAAAECBAgQINBfwPq7v1EbSkgAtiHKNeyjCaiGQdEkAgQIECBAgAABAgQIEGicgPV340I6UockAEdiU6msgAmorKD6BAgQIECAAAECBAgQIECgv4D1d3+jNpSQAGxDlGvYRxNQDYOiSQQIECBAgAABAgQIECDQOAHr78aFdKQOSQCOxKZSWQETUFlB9QkQIECAAAECBAgQIECAQH8B6+/+Rm0oIQHYhijXsI8moBoGRZMIECBAgAABAgQIECBAoHEC1t+NC+lIHZIAHIlNpbICJqCyguoTIECAAAECBAgQIECAAIH+Atbf/Y3aUEICsA1RrmEfTUA1DIomESBAgAABAgQIECBAgEDjBKy/GxfSkTokATgSm0plBUxAZQXVJ0CAAAECBAgQIECAAAEC/QWsv/sbtaGEBGAbolzDPpqAahgUTSJAgAABAgQIECBAgACBxglYfzcupCN1SAJwJDaVygqYgMoKqk+AAAECBAgQIECAAAECBPoLWH/3N2pDCQnANkS5hn00AdUwKJpEgAABAgQIECBAgAABAo0TsP5uXEhH6pAE4EhsKpUVMAGVFVSfAAECBAgQIECAAAECBAj0F7D+7m/UhhISgG2Icg37aAKqYVA0iQABAgQIECBAgAABAgQaJ2D93biQjtQhCcCR2FQqK2ACKiuoPgECBAgQIECAAAECBAgQ6C9g/d3fqA0lJADbEOUa9tEEVMOgaBIBAgQIECBAgAABAgQINE7A+rtxIR2pQxKAI7GpVFbABFRWUH0CBAgQIECAAAECBAgQINBfwPq7v1EbSkgAtiHKNeyjCaiGQdEkAgQIECBAgAABAgQIEGicgPV340I6UockAEdiU6msgAmorKD6BAgQIECAAAECBAgQIECgv4D1d3+jNpSQAGxDlGvYRxNQDYOiSQQIECBAgAABAgQIECDQOAHr78aFdKQOSQCOxKZSWQETUFlB9QkQIECAAAECBAgQIECAQH8B6+/+Rm0oIQHYhijXsI8moBoGRZMIECBAgAABAgQIECBAoHEC1t+NC+lIHZIAHIlNpbICJqCyguoTIECAAAECBAgQIECAAIH+Atbf/Y3aUEICsA1RrmEfTUA1DIomESBAgAABAgQIECBAgEDjBKy/GxfSkTokATgSm0plBUxAZQXVJ0CAAAECBAgQIECAAAEC/QWsv/sbtaGEBGAbolzDPs6GCeiJJyLuuy9i+fLO169+FfHUUxFPPx2x7roR660XscUWEdtu2/l60YsiNtightiaRIAAAQIECBAgQIAAAQKtFZgN6+/WBmcGOy4BOIPYDvWsQF0noCefjLj55ogf/aiT9Fu9upPw+/WvIx57rPP//Nk663SSgBttFLHJJp3/588yEfjqV0e8/OURc+eKOAECBAgQIECAAAECBAgQqFagruvvalXad3QJwPbFvBY9rtsElGf33XBDxE03Raxa1Tnbb8WKiEce6ST+MumX25w5na9nnul85ZaJv0wEzpsXsdVWnbMCN9ww4lWvinjNazrf2wgQIECAAAECBAgQIECAQBUCdVt/V2HgmBESgEZBJQJ1mYDyjL4f/CDi6qsjHn884t57O2f+5f833jhis806Z/hlci+/z+Rfd8sE4KOPdpKEeYbgf/xH5/sXvKBzJuA223T+f8ghEQcd9Ny6laA7KAECBAgQIECAAAECBAi0TqAu6+/WwdeswxKANQtIW5pThwno/vsjvvWtTsLvZz+LWLaso7/11p0E3qabDheNPEswk4G5vwce6NTdcceIHXaI2G67iDe+sbNvGwECBAgQIECAAAECBAgQmCmBOqy/Z6qvjtNbQALQ6KhEoOoJaPHiiCuuiFi5MuLWWzuJuxe/uJOsG8e9+/JegplUvOeeztmDu+3WSSgeeWTEwoWVkDsoAQIECBAgQIAAAQIECLRQoOr1dwvJa9llCcBahqX5japqAsqz9K65JuK73434+c8j7rqrc5luN0E3bvlugjEvKX7JSyK23z7isMMiDj64c+9AGwECBAgQIECAAAECBAgQmE6Bqtbf09kn+x5eQAJweDM1xiBQ1QSU9/rL5F8m/vIMvUzIZWJu4r39xtC95+wi7xWYx8uEY55hmMfLJGDeG9BGgAABAgQIECBAgAABAgSmU6Cq9fd09sm+hxeQABzeTI0xCFQxAeVTfi+77Nnk3847dy77naktLwdeuvTZJOAxx7gceKbsHYcAAQIECBAgQIAAAQJtFahi/d1W6zr3WwKwztFpcNtmegLKB35ccEHnQR933hkx08m/bii7ScAFCzoPCHnPezwYpMHDXNcIECBAgAABAgQIECBQucBMr78r77AGTCogAWhgVCIwkxPQ009HfPGLncTfkiWdJ/JmAq7fdvHFh8ayZVf3K/ac19/xju/GTjsdOmWdbEc+KfjVr47YZZeIE06Y3kuQh+qAwgQIECBAgAABAgQIECDQKIGZXH83Cq5hnZEAbFhAZ0t3ZnICyod+XHVVxL/9W0QmA/fZZ7CE27AJwHXWmRPvf//PYtNNt5syDHlPwExErrtuxN57R7zudRG/93uzJXLaSYAAAQIECBAgQIAAAQKzSWAm19+zyaVtbZUAbFvEa9LfmZqAfvWriPPO69z376c/7STcNt10MISHHvppPPnko1MWXrHiJ/HNb76tKPOSl/ynePvb/3mgnefTgTMhmQ8EmT8/4uSTI7bYYqCqChEgQIAAAQIECBAgQIAAgYEFZmr9PXCDFKxEQAKwEnYHnakJ6IorIq69NuK66zqX/ua9/8a5/cu/fDB++MOPFbv8L//l/4tXvOK4gXefDwT5xS8i9t8/4uCDI37/9weuqiABAgQIECBAgAABAgQIEBhIYKbW3wM1RqHKBCQAK6Nv94FnYgL6zW8iPvWpiNtvj7j77k6ibe7c8bmvXv1MfPrTO8Qjj/wi1l9/k/jzP78/5s7daOADPPlkJzG5004Ru+4accop423fwA1RkAABAgQIECBAgAABAgQaKzAT6+/G4jWoYxKADQrmbOrKTExAeYntP/5jxL/+a8Tmm0fsttt4hZYu/Zf4m785otjpq151fLzhDV8e+gC33hrx8MMR++4b8cY3Ruy119C7UIEAAQIECBAgQIAAAQIECPQUmIn1N/76C0gA1j9GjWzhTExAF14Y8eMfR9x883D3/hsU/H/9r7fHj3/8N0Xx//pfvxPz5x82aNU15br3Anz5yyNe8YqIE08cehcqECBAgAABAgQIECBAgAABCUBjYEoBCUADpBKB6U4APvFExLnnRtxyS8Qjj0QsXDjebv7mN7+OT3ziRcVDQjbbbMf40z/9aayzzjpDH2T16s4TgefNi9h994j//t8jNthg6N2oQIAAAQIECBAgQIAAAQIEJhWY7vU39tkhIAE4O+LUuFZO9wS0bFnEl78csXhxxGabde6xN87tppu+Ev/4j8cXu/y93/t/4rWv/cuRd3/bbRF5JmAmKd/5zogddxx5VyoSIECAAAECBAgQIECAAIHnCEz3+hv37BCQAJwdcWpcK6d7AsqHa1x2WcT3vx+xyy4R2247XsKvfvXw+OlPv1Ps9H3vuy1+93dHzzAuXx5xxx0RBx0UcfTRnYeV2AgQIECAAAECBAgQIECAwDgEpnv9PY422sf0C0gATr+xI0wiMN0T0D/8Qyf5d+ONEa9+decS23FtK1f+PP7qr3aMfArw9tvvF+9613Wldp2XKP/oR537FGYS8E1vKrU7lQkQIECAAAECBAgQIECAwBqB6V5/o54dAhKAsyNOjWvldE9A+QCQvLdeXl578MERc+aMj/D73z83rrrqtGKHxxxzfuyzzx+X2vkzz0Rcc03ES1/auQz4hBNK7U5lAgQIECBAgAABAgQIECAgAWgMPEdAAtCAqERguhOA55/fOavurrs6CcBxbn/91y+LFSt+Euuuu0Gccsq9seGGv1N695kA3HnnzlmA731v6d3ZAQECBAgQIECAAAECBAgQKASme/2NeXYISADOjjg1rpXTPQF97nOdy3/zYSB5We24tuXLl8SFF3YeKbz77m+Ot771m2PZ9bXXRuy0U8Ree+U9BceySzshQIAAAQIECBAgQIAAAQISgMZAISABaCBUIjDdCcDpOgPw8sv/JG644f8tzP7wD/8pXvrS14/FzxmAY2G0EwIECBAgQIAAAQIECBBYS2C619/AZ4eABODsiFPjWjndE9B03APw6aefjE99art47LEVsdFGW8UppyyPOXPWKx0b9wAsTWgHBAgQIECAAAECBAgQINBDYLrX3+Bnh4AE4OyIU+NaOd0T0HQ8Bfi22/4pFi16QxGLfff90zjyyL8aS1w8BXgsjHZCgAABAgQIECBAgAABApMITPf6G/rsEJAAnB1xalwrp3sCuu66iMsui/j+9yN22SVi223LE37962+JW275h2JH7373j2KbbfYuv9OIWL484o47OvcqPProiP33H8tu7YQAAQIECBAgQIAAAQIECLgHoDFQCEgAGgiVCEx3AjAf/vHlL0csXhyx2WYRu+5arpurVj0Un/zkNvH000/E1lvvGe99783ldjih9m23RaxcGbFwYcQ73xmx445j27UdESBAgAABAgQIECBAgEDLBaZ7/d1y3lnTfQnAWROqZjV0uiegJ56IOPfciFtuichLbDO5VmZbsuTzceml7y128brXfSwOPPAvyuxuTd3VqyOWLImYNy+fKhxx2mkR668/ll3bCQECBAgQIECAAAECBAgQcAagMVAISAAaCJUITHcCMDuVDwL58Y8jbr45Yu+9IzbddPSuXnTRgXHPPT+MddZZN/7sz34W8+aN4Zri6Jz592//FvHyl0e84hURJ544ehvVJECAAAECBAgQIECAAAECawvMxPqbev0FJADrH6NGtnAmJqBMrP3jP0b8679GbL55xG671Y/y1lsjHn44HyoS8cY3Ruy1V/3aqEUECBAgQIAAAQIECBAgMHsFZmL9PXt12tNyCcD2xLpWPZ2JCejJJyM++cmI22+PuPvuzsM15s6tD0O2Lx9WstNOnXsUnnJKvdpXHyktIUCAAAECBAgQIECAAIFRBWZi/T1q29SbOQEJwJmzdqQJAjM1AV1xRcS113YSbdttF7HzzvUJw9KlEb/4RScxefDBEb//+/Vpm5YQIECAAAECBAgQIECAQDMEZmr93Qyt5vZCArC5sa11z2ZqAvrVryLOOy/irrsifvrT8vcCHBdq995/L3lJxPz5ESefHLHFFuPau/0QIECAAAECBAgQIECAAIGOwEytv3nXW0ACsN7xaWzrZnICuuaaiKuu6jxs4+mnI/bZJ2LOnOpon3mm8+TfddftJCRf97qI3/u96trjyAQIECBAgAABAgQIECDQXIGZXH83V3H290wCcPbHcFb2YCYnoEy4ffGLEXfcEfGjH0Vsu23EggXVsd15Z8Ty5RGvfnXELrtEnHBCtQnJ6iQcmQABAgQIECBAgAABAgSmW2Am19/T3Rf7H11AAnB0OzVLCMz0BHT//REXXBCxbFlEJuDyXoAvfnGJDoxY9Z57IvLef5mA3HHHiPe8J2LrrUfcmWoECBAgQIAAAQIECBAgQKCPwEyvvwWkngISgPWMS+NbVcUEtHhxxKWXdu4H+LOfzXwSsJv822GHiLz33zHHRCxc2PhQ6yABAgQIECBAgAABAgQIVChQxfq7wu46dA8BCUBDoxKBqiagq6+O+O53n00Cbr99Jxk3nfcEzEuQM+n4859HdJN/hx0WccghldA7KAECBAgQIECAAAECBAi0SKCq9XeLiGdFVyUAZ0WYmtfIqiag1asj8qEgmQTMhFwm5l7wgojddovYdNPxO+fTfm+9NeLxxzuJxkw4ZvLv4IMj1lln/MezRwIECBAgQIAAAQIECBAgMFGgqvW3KNRLQAKwXvFoTWuqnoDycuArrojoJugeeaRzT8A8Q2/u3PJhePLJzmXGednvvHnPJhiPPNJlv+V17YEAAQIECBAgQIAAAQIEBhWoev09aDuVm14BCcAJvsuWLYvPfvazcemll8Y999wTG2ywQey8887x1re+NU4++eTYaKONxhKNyy+/PC644IJYvHhxrFixIrbaaqtYuHBhvPvd746jjjpqymM88cQTceONNxZ1b7jhhuLrjjvuiNV5alvEmn/7NXSdAU8/O+SQQ+J73/tev90N/XodJqAHHoj41rcifvGLTqLu7rs73ciHcuSTgjNxNyDTb+0jMpGY+1uxorOvnXbqJBa32y7ijW/0wI+hB4oKBAgQIECAAAECBAgQIFBKoA7r71IdUHksAhKAv2W85JJL4rjjjouVeUrYJNuuu+5aJAYX5ONbR9yeeeaZIsn3pS99qeceTjjhhPjCF74Qc3rclO6d73xnXHzxxT3rdxOB/ZooAdgRevrpiB/8ICLvDZiX6d57b8Ty5Z3/b7xx57LgTATmV34/MSx5b79HH+0k/fIrh05+n5cUZwJxm206/z/00IgDD5ze+wz2i7fXCRAgQIAAAQIECBAgQKCdAhKA7Yz72r2WAIwozqg78MADY9WqVbHJJpvEaaedFocddljx/aJFi+LCCy8s3DIJuGTJkpiX2aARttzvueeeW9Tca6+94tRTTy3OMFy6dGl87GMfK9qRW5Y7++yzJz3C8ccfH1/5yleK17Ide++9d9x2221x3333FT8bNgH43ve+N0466aSevdl4441j/vz5I/R26ip1m4B+9auIvCw4Q7BqVUR+n2fxZWLvscfStdOfTADmWYH5fSYAc8vv8+TQHBZbbRWxxRYRG26YMe5c7pvf2wgQIECAAAECBAgQIECAQBUCdVt/V2HgmBESgJEPZDg4rr322lhvvfXimmuuif333/85Y+PjH/94kazL7Ywzzogzzzxz6LFz++23x8te9rJ46qmnYp999imOs2FmiX67PfbYY5GX22aCMdtxyy23THq24de+9rUiMZmXDO++++7FmYKHHnpoXJ2nsI2QABy1P0MDrFWhrhNQ3rvv3/89YsmSzpmAmejLswTzzL78yqRffmUiML/yrMD8WnfdTiIwz/zbZ5+IPfccz70EyzqrT4AAAQIECBAgQIAAAQLtFqjr+rvdUZn53rc+AZj30Nt3330L+fe85z3x+c9//nlRyEt399xzzyIpt/nmm8cDDzwQc4d8UkSeZXf++ecX+77uuutiv/32e95xrr/++jXJxyx/3nnnDTQiJAAHYhq60BNPROSJlZkIzEuD86zATBBmQjATfjkE8uy+vNQ3E38velHEBhsMfRgVCBAgQIAAAQIECBAgQIDAtAlIAE4b7azacesTgKeffnqcc845RdAyAddNBq4dxbx0Ny/Nze3KK6+MI444YuBA52W522+/fSxfvjx22223IpHYa8vX85Le7bbbrngQySD36pMAHDgUChIgQIAAAQIECBAgQIAAgVYJSAC2Ktw9O9v6BGD38t+8193DDz9cXH472ZZn7R1wwAHFSx/+8IfjrLPOGngE3XXXXcW9/nLrdZZhd2f5ej4hOLesN8j99yQABw6FggQIECBAgAABAgQIECBAoFUCEoCtCrcEYC+BrbbaKh588MF45StfGTfddFNPqIceeii2+O3THI499tj4+te/PvAI+va3vx2vf/3ri/Kf/vSn4/3vf3/Puvn6Bz7wgeL1fOrw0Ucf3fc4ZRKAe+yxR/HgkLvvvjvWXXfdeNGLXlQkOvNhI/kglOnaTEDTJWu/BAgQIECAAAECBAgQIEDgWQHrb6MhBVp9BuDjjz++5kEcxxxzTGSibqotnxD86KOPFvfvyzMCB93yvoL5tN3cvvGNb8Rb3vKWnlW/+c1vRiYYc8t6eUZgv61MAnCqfb/xjW+Miy++ODbbbLN+TXje6znBTLXde++98ZrXvKYokpc65yXSNgIECBAgQIAAAQIECBAgQGC8AhKA4/WcrXtrdQJwxYoVsfXWWxexe9vb3haLFi2aMo4vfOELiweA5ANBbr755oFjPvEpwpdffnkceeSRPevm692z/j7xiU/EKaec0vc4oyQA85Ln//yf/3McfvjhxX0JM7mZHvk04Uw8/vKXvyyOm08m/pd/+ZehH3oyyL0Lux2TAOwbYgUIECBAgAABAgQIECBAgMBIAhKAI7E1rlKrE4CZeNphhx2KoL797W+Pr371q1MGOMtmnbyf35133jnwYPjIRz5S3Dcwt6uuuipe+9rX9qz7ne98p0jK5Zb1PvShD/U9zigJwLzfYT7ReLLt/vvvj6OOOipuvPHG4uXPfOYz8Sd/8id92zGxgATgUFwKEyBAgAABAgQIECBAgACBaRGQAJwW1lm301YnANt8BmC/kZoPIMkzA5988slYsGBB3HHHHf2qPOd1lwAPxaUwAQIECBAgQIAAAQIECBCYFgEJwGlhnXU7bXUCsM33ABxkpOZ9ES+77LKi6C9+8YvYdtttB6k2UBkT0EBMChEgQIAAAQIECBAgQIAAgVIC1t+l+BpTudUJwIzilltuWdzvrm1PAR5kBP/FX/xF5H0Ic7vhhhti4cKFg1QbqIwJaCAmhQgQIECAAAECBAgQIECAQCkB6+9SfI2p3PoE4MEHHxzXXntt5EMx8r5466233qTBzaf+HnDAAcVreT+/s846a+BBkJfT5n0Dc8un+uZDNnpt+foFF1xQvJz15s+f3/c4o9wDsO9OI+LUU0+NfIBJbhKAg4gpQ4AAAQIECBAgQIAAAQIE6iUgAViveFTVmtYnAE8//fQ455xzCv/rr78+9t1330ljce6558Zpp51WvHbllVfGEUccMXDMVq9eHdtvv30sX768uK/eLbfc0rPu7rvvHrfeemtst912xQNHBnmYxnQlAP/gD/4gLr300qKtOWFkm8a1mYDGJWk/BAgQIECAAAECBAgQIECgt4D1t9GRAq1PAOaZbd2kX6+z85555pnYc889i8RdPjn3gQceiLlz5w41gk466aQ4//zzizp5NuF+++33vPqZgNx///2Ln2f58847b6BjTEcC8Kc//WmRrPzNb34z9FOPB2m0CWgQJWUIECBAgAABAgQIECBAgEA5Aevvcn5Nqd36BGAGsnsZcF7+e80116xJwnWDnJfB5uWwuZ1xxhlx5plnPif+3/ve9+Kwww4rfvaOd7wjLr744ueNj9tvvz322GOPePrpp2OfffYpjrPhhhuuKbdq1aqiHUuWLCkuQ/7JT34Su+yyy0DjbNgE4CWXXBJHHXVUz8ud77///uL1G2+8sTj+Jz/5yfjABz4wUFsGLWQCGlRKOQIECBAgQIAAAQIECBAgMLqA9ffodk2qKQEYUSS6DjzwwMgk3CabbBJ5WXAm9PL7RYsWrbkn36677lok6ObNmzd0AjAr5CXEeSlxbnvttVd88IMfLM6uW7p0aXz0ox9dk3DLcmefffak4+y+++6LK6644jmv5T5vu+224mdf/vKXn/PaQQcdFAsWLHjOz3baaT0YcvUAACAASURBVKd48skn481vfnOR7MzvMxn54IMPRiYzv/CFLxT/zy3r/+///b9jgw02GOu4NwGNldPOCBAgQIAAAQIECBAgQIDApALW3wZGCkgA/nYc5Flxxx13XKxcuXLSkZHJv7wf3trJtCw8yBmAWS4vJT7xxBPjoosu6jn63vWudxUJxzlz5kxaZuKxBhnCmRA8/vjjn5cAXLZsWd/qmSD84he/WFz2PO7NBDRuUfsjQIAAAQIECBAgQIAAAQLPF7D+NiokANcaA5kU+8xnPlMk+vIXZP311y8Sfscee2y8733vi4022qhvUq7XJcATK1522WVFkm/x4sXFmXZbbrllLFy4sHhCcF56O9U2jgTg1VdfHfmV9yLMJw1nGzLxmWc/vvjFLy6edpz96N6PcDp+VUxA06FqnwQIECBAgAABAgQIECBA4LkC1t9GhASgMVCZgAmoMnoHJkCAAAECBAgQIECAAIEWCVh/tyjYU3TVJcDGQSUCJqBK2B2UAAECBAgQIECAAAECBFomYP3dsoD36K4EoHFQiYAJqBJ2ByVAgAABAgQIECBAgACBlglYf7cs4BKAAl4nARNQnaKhLQQIECBAgAABAgQIECDQVAHr76ZGdrh+OQNwOC+lxyRgAhoTpN0QIECAAAECBAgQIECAAIEpBKy/DY8UkAA0DioRMAFVwu6gBAgQIECAAAECBAgQINAyAevvlgW8R3clAI2DSgRMQJWwOygBAgQIECBAgAABAgQItEzA+rtlAZcAFPA6CZiA6hQNbSFAgAABAgQIECBAgACBpgpYfzc1ssP1yxmAw3kpPSYBE9CYIO2GAAECBAgQIECAAAECBAhMIWD9bXikgASgcVCJgAmoEnYHJUCAAAECBAgQIECAAIGWCVh/tyzgPborAWgcVCJgAqqE3UEJECBAgAABAgQIECBAoGUC1t8tC7gEoIDXScAEVKdoaAsBAgQIECBAgAABAgQINFXA+rupkR2uX84AHM5L6TEJmIDGBGk3BAgQIECAAAECBAgQIEBgCgHrb8MjBSQAjYNKBExAlbA7KAECBAgQIECAAAECBAi0TMD6u2UB79FdCUDjoBIBE1Al7A5KgAABAgQIECBAgAABAi0TsP5uWcAlAAW8TgImoDpFQ1sIECBAgAABAgQIECBAoKkC1t9Njexw/XIG4HBeSo9JwAQ0Jki7IUCAAAECBAgQIECAAAECUwhYfxseKSABaBxUImACqoTdQQkQIECAAAECBAgQIECgZQLW3y0LeI/uSgAaB5UImIAqYXdQAgQIECBAgAABAgQIEGiZgPV3ywIuASjgdRIwAdUpGtpCgAABAgQIECBAgAABAk0VsP5uamSH65czAIfzUnpMAiagMUHaDQECBAgQIECAAAECBAgQmELA+tvwSAEJQOOgEgETUCXsDkqAAAECBAgQIECAAAECLROw/m5ZwHt0VwLQOKhEwARUCbuDEiBAgAABAgQIECBAgEDLBKy/WxZwCUABr5OACahO0dAWAgQIECBAgAABAgQIEGiqgPV3UyM7XL+cATicl9JjEjABjQnSbggQIECAAAECBAgQIECAwBQC1t+GRwpIABoHlQiYgCphd1ACBAgQIECAAAECBAgQaJmA9XfLAt6juxKAxkElAiagStgdlAABAgQIECBAgAABAgRaJmD93bKASwAKeJ0ETEB1ioa2ECBAgAABAgQIECBAgEBTBay/mxrZ4frlDMDhvJQek4AJaEyQdkOAAAECBAgQIECAAAECBKYQsP42PFJAAtA4qETABFQJu4MSIECAAAECBAgQIECAQMsErL9bFvAe3ZUANA4qETABVcLuoAQIECBAgAABAgQIECDQMgHr75YFXAJQwOskYAKqUzS0hQABAgQIECBAgAABAgSaKmD93dTIDtcvZwAO56X0mARMQGOCtBsCBAgQIECAAAECBAgQIDCFgPW34ZECEoDGQSUCJqBK2B2UAAECBAgQIECAAAECBFomYP3dsoD36K4EoHFQiYAJqBJ2ByVAgAABAgQIECBAgACBlglYf7cs4BKAAl4nARNQnaKhLQQIECBAgAABAgQIECDQVAHr76ZGdrh+OQNwOC+lxyRgAhoTpN0QIECAAAECBAgQIECAAIEpBKy/DY8UkAA0DioRMAFVwu6gBAgQIECAAAECBAgQINAyAevvlgW8R3clAI2DSgRMQJWwOygBAgQIECBAgAABAgQItEzA+rtlAZcAFPA6CZiA6hQNbSFAgAABAgQIECBAgACBpgpYfzc1ssP1yxmAw3kpPSYBE9CYIO2GAAECBAgQIECAAAECBAhMIWD9bXikgASgcVCJgAmoEnYHJUCAAAECBAgQIECAAIGWCVh/tyzgPborAWgcVCJgAqqE3UEJECBAgAABAgQIECBAoGUC1t8tC7gEoIDXScAEVKdoaAsBAgQIECBAgAABAgQINFXA+rupkR2uX84AHM5L6TEJmIDGBGk3BAgQIECAAAECBAgQIEBgCgHrb8MjBSQAjYNKBExAlbA7KAECBAgQIECAAAECBAi0TMD6u2UB79FdCUDjoBIBE1Al7A5KgAABAgQIECBAgAABAi0TsP5uWcAlAAW8TgImoDpFQ1sIECBAgAABAgQIECBAoKkC1t9Njexw/XIG4HBeSo9JwAQ0Jki7IUCAAAECBAgQIECAAAECUwhYfxseKSABaBxUImACqoTdQQkQIECAAAECBAgQIECgZQLW3y0LeI/uSgAaB5UImIAqYXdQAgQIECBAgAABAgQIEGiZgPV3ywIuASjgdRIwAdUpGtpCgAABAgQIECBAgAABAk0VsP5uamSH65czAIfzUnpMAiagMUHaDQECBAgQIECAAAECBAgQmELA+tvwSAEJQOOgEgETUCXsDkqAAAECBAgQIECAAAECLROw/m5ZwHt0VwLQOKhEwARUCbuDEiBAgAABAgQIECBAgEDLBKy/WxZwCUABr5OACahO0dAWAgQIECBAgAABAgQIEGiqgPV3UyM7XL+cATicl9JjEjABjQnSbggQIECAAAECBAgQIECAwBQC1t+GRwpIABoHlQiYgCphd1ACBAgQIECAAAECBAgQaJmA9XfLAt6juxKAxkElAiagStgdlAABAgQIECBAgAABAgRaJmD93bKASwAKeJ0ETEB1ioa2ECBAgAABAgQIECBAgEBTBay/mxrZ4frlDMDhvJQek4AJaEyQdkOAAAECBAgQIECAAAECBKYQsP42PFJAAtA4qETABFQJu4MSIECAAAECBAgQIECAQMsErL9bFvAe3ZUANA4qETABVcLuoAQIECBAgAABAgQIECDQMgHr75YFXAJQwOskYAKqUzS0hQABAgQIECBAgAABAgSaKmD93dTIDtcvZwAO56X0mARMQGOCtBsCBAgQIECAAAECBAgQIDCFgPW34ZECEoDGQSUCJqBK2B2UAAECBAgQIECAAAECBFomYP3dsoD36K4EoHFQiYAJqBJ2ByVAgAABAgQIECBAgACBlglYf7cs4BKAAl4nARNQnaKhLQQIECBAgAABAgQIECDQVAHr76ZGdrh+OQNwOC+lxyRgAhoTpN0QIECAAAECBAgQIECAAIEpBKy/DY8UkAA0DioRMAFVwu6gBAgQIECAAAECBAgQINAyAevvlgW8R3clAI2DSgRMQJWwOygBAgQIECBAgAABAgQItEzA+rtlAZcAFPA6CZiA6hQNbSFAgAABAgQIECBAgACBpgpYfzc1ssP1yxmAw3kpPSYBE9CYIO2GAAECBAgQIECAAAECBAhMIWD9bXikgASgcVCJgAmoEnYHJUCAAAECBAgQIECAAIGWCVh/tyzgPborAWgcVCJgAqqE3UEJECBAgAABAgQIECBAoGUC1t8tC7gEoIDXScAEVKdoaAsBAgQIECBAgAABAgQINFXA+rupkR2uX84AHM5L6TEJmIDGBGk3BAgQIECAAAECBAgQIEBgCgHrb8MjBSQAjYNKBExAlbA7KAECBAgQIECAAAECBAi0TMD6u2UB79FdCUDjoBIBE1Al7A5KgAABAgQIECBAgAABAi0TsP5uWcAlAAW8TgImoDpFQ1sIECBAgAABAgQIECBAoKkC1t9Njexw/XIG4HBeSo9JwAQ0Jki7IUCAAAECBAgQIECAAAECUwhYfxseKSABaBxUImACqoTdQQkQIECAAAECBAgQIECgZQLW3y0LeI/uSgAaB5UImIAqYXdQAgQIECBAgAABAgQIEGiZgPV3ywIuASjgdRIwAdUpGtpCgAABAgQIECBAgAABAk0VsP5uamSH65czAIfzUnpMAiagMUHaDQECBAgQIECAAAECBAgQmELA+tvwSAEJwAnjYNmyZfHZz342Lr300rjnnntigw02iJ133jne+ta3xsknnxwbbbTRWEbN5ZdfHhdccEEsXrw4VqxYEVtttVUsXLgw3v3ud8dRRx015TGeeOKJuPHGG4u6N9xwQ/F1xx13xOrVq4t63X8HbehM9Xnt9piABo2QcgQIECBAgAABAgQIECBAYHQB6+/R7ZpUUwLwt9G85JJL4rjjjouVK1dOGt9dd921SAwuWLBg5Pg/88wzRZLvS1/6Us99nHDCCfGFL3wh5syZM2mZd77znXHxxRf3rD9MAnAm+tyroSagkYeRigQIECBAgAABAgQIECBAYGAB6++BqRpdUAIwojij7sADD4xVq1bFJptsEqeddlocdthhxfeLFi2KCy+8sBgEmQRcsmRJzJs3b6RBkfs999xzi7p77bVXnHrqqcUZhkuXLo2PfexjRTtyy3Jnn332pMc4/vjj4ytf+UrxWrZj7733jttuuy3uu+++4meDJgBnqs8SgCMNFZUIECBAgAABAgQIECBAgMBYBCQAx8I463ciARgRBx98cFx77bWx3nrrxTXXXBP777//cwL78Y9/vEjW5XbGGWfEmWeeOXTgb7/99njZy14WTz31VOyzzz7FcTbccMM1+3nsscfikEMOKRKM2Y5bbrll0rMNv/a1rxWJybxkePfddy/OFDz00EPj6quvHioBOBN9ngrJBDT0EFKBAAECBAgQIECAAAECBAgMLWD9PTRZIyu0PgGY99Dbd999i+C+5z3vic9//vPPC3ReurvnnnsWSbnNN988HnjggZg7d+5QA+Kkk06K888/v6hz3XXXxX777fe8+tdff/2a5GOWP++88wY6xrAJwJnqswTgQOFTiAABAgQIECBAgAABAgQITJuABOC00c6qHbc+AXj66afHOeecUwQtE3DdZODaUcxLd/PS3NyuvPLKOOKIIwYOdF6Wu/3228fy5ctjt912KxKJvbZ8PS/p3W677YoHkayzzjp9jzNsAnAm+tyv0SagfkJeJ0CAAAECBAgQIECAAAEC5QWsv8sbNmEPrU8Adi+F3XjjjePhhx8uLr+dbMuz9g444IDipQ9/+MNx1llnDRz/u+66q7jXX269zjLs7ixfzycE55b15s+f3/c4wyYAZ6LP/RptAuon5HUCBAgQIECAAAECBAgQIFBewPq7vGET9tD6BOBWW20VDz74YLzyla+Mm266qWdMH3roodhiiy2K14899tj4+te/PnD8v/3tb8frX//6ovynP/3peP/739+zbr7+gQ98oHg9nzp89NFH9z3OsAnAmehzv0abgPoJeZ0AAQIECBAgQIAAAQIECJQXsP4ub9iEPbQ6Afj444+veRDHMcccE5mom2rLJwQ/+uijxf378ozAQbe8r+B73/veovg3vvGNeMtb3tKz6je/+c0iwZhb1sszAvttwyQAZ6rPOcFMtd17773xmte8piiSlzrnJdI2AgQIECBAgAABAgQIECBAYLwCEoDj9Zyte2t1AnDFihWx9dZbF7F729veFosWLZoyji984QuLB4DkA0FuvvnmgWM+8SnCl19+eRx55JE96+br3bP+PvGJT8Qpp5zS9zjDJABnqs+D3Luw2zEJwL4hVoAAAQIECBAgQIAAAQIECIwkIAE4ElvjKrU6AZiJpx122KEI6tvf/vb46le/OmWAs2zWyfv53XnnnQMPho985CPFfQNzu+qqq+K1r31tz7rf+c534vDDDy9ez3of+tCH+h5nmATgTPVZArBv2BQgQIAAAQIECBAgQIAAAQLTLiABOO3Es+IArU4AztTZcG08A9AlwLPi918jCRAgQIAAAQIECBAgQKDhAhKADQ/wgN1rdQJwpu6H18Z7APYbfyagfkJeJ0CAAAECBAgQIECAAAEC5QWsv8sbNmEPrU4AZgC33HLL+OUvf9mqpwDPRJ/7/XKYgPoJeZ0AAQIECBAgQIAAAQIECJQXsP4ub9iEPbQ+AXjwwQfHtddeGxtvvHE8/PDDsd56600a13zq7wEHHFC8lvfzO+usswaO/1133VXcNzC3fKpvnhHYa8vXL7jgguLlrDd//vy+xxnmHoC5s5noc79Gm4D6CXmdAAECBAgQIECAAAECBAiUF7D+Lm/YhD20PgF4+umnxznnnFPE8vrrr49999130riee+65cdpppxWvXXnllXHEEUcMHP/Vq1fH9ttvH8uXL4/ddtstbrnllp51d99997j11ltju+22Kx44MsjDNIZNAM5En/vhmID6CXmdAAECBAgQIECAAAECBAiUF7D+Lm/YhD20PgF4ww03rEn69To775lnnok999yzSNxtvvnm8cADD8TcuXOHiv9JJ50U559/flEnzybcb7/9nlc/E5D7779/8fMsf9555w10jGETgDPV56kabwIaKLQKESBAgAABAgQIECBAgACBUgLW36X4GlO59QnAjGT3kti8/Peaa65Zk4TrRnniU3zPOOOMOPPMM58zAL73ve/FYYcdVvzsHe94R1x88cXPGyC333577LHHHvH000/HPvvsUxxnww03XFNu1apVRTuWLFlSXIb8k5/8JHbZZZeBBtqwCcBx9Hmghk1RyARUVlB9AgQIECBAgAABAgQIECDQX8D6u79RG0pIAEbEjTfeGAceeGBkEm6TTTaJvEQ2E3r5/aJFi9bck2/XXXctEnTz5s0bOgGYFfIS4ryUOLe99torPvjBDxb3Bly6dGl89KMfLdrRLXf22WdPOv7uu+++uOKKK57zWu7ztttuK3725S9/+TmvHXTQQbFgwYLn7atsn8v+cpiAygqqT4AAAQIECBAgQIAAAQIE+gtYf/c3akMJCcDfRvmSSy6J4447LlauXDlp3DP5d+mll06aTBvkDMDcaV5KfOKJJ8ZFF13Uc2y9613vKhKOc+bMmbTMxGMNMkAzIXj88cdPWrRMnwc59lRlTEBlBdUnQIAAAQIECBAgQIAAAQL9Bay/+xu1oYQE4IQoL1u2LD7zmc8Uib78BVl//fWLhN+xxx4b73vf+2KjjTbqm5TrdQnwxIqXXXZZkeRbvHhxPPjgg7HlllvGwoULiycEH3XUUVOOu3EmAPNAo/a57C+HCaisoPoECBAgQIAAAQIECBAgQKC/gPV3f6M2lJAAbEOUa9hHE1ANg6JJBAgQIECAAAECBAgQINA4AevvxoV0pA5JAI7EplJZARNQWUH1CRAgQIAAAQIECBAgQIBAfwHr7/5GbSghAdiGKNewjyagGgZFkwgQIECAAAECBAgQIECgcQLW340L6UgdkgAciU2lsgImoLKC6hMgQIAAAQIECBAgQIAAgf4C1t/9jdpQQgKwDVGuYR9NQDUMiiYRIECAAAECBAgQIECAQOMErL8bF9KROiQBOBKbSmUFTEBlBdUnQIAAAQIECBAgQIAAAQL9Bay/+xu1oYQEYBuiXMM+moBqGBRNIkCAAAECBAgQIECAAIHGCVh/Ny6kI3VIAnAkNpXKCpiAygqqT4AAAQIECBAgQIAAAQIE+gtYf/c3akMJCcA2RLmGfTQB1TAomkSAAAECBAgQIECAAAECjROw/m5cSEfqkATgSGwqlRUwAZUVVJ8AAQIECBAgQIAAAQIECPQXsP7ub9SGEhKAbYhyDftoAqphUDSJAAECBAgQIECAAAECBBonYP3duJCO1CEJwJHYVCorYAIqK6g+AQIECBAgQIAAAQIECBDoL2D93d+oDSUkANsQ5Rr20QRUw6BoEgECBAgQIECAAAECBAg0TsD6u3EhHalDEoAjsalUVsAEVFZQfQIECBAgQIAAAQIECBAg0F/A+ru/URtKSAC2Ico17KMJqIZB0SQCBAgQIECAAAECBAgQaJyA9XfjQjpShyQAR2JTqayACaisoPoECBAgQIAAAQIECBAgQKC/gPV3f6M2lJAAbEOUa9hHE1ANg6JJBAgQIECAAAECBAgQINA4AevvxoV0pA5JAI7EplJZARNQWUH1CRAgQIAAAQIECBAgQIBAfwHr7/5GbSghAdiGKNewjyagGgZFkwgQIECAAAECBAgQIECgcQLW340L6UgdkgAciU2lsgImoLKC6hMgQIAAAQIECBAgQIAAgf4C1t/9jdpQQgKwDVGuYR9NQDUMiiYRIECAAAECBAgQIECAQOMErL8bF9KROiQBOBKbSmUFTEBlBdUnQIAAAQIECBAgQIAAAQL9Bay/+xu1oYQEYBuiXMM+moBqGBRNIkCAAAECBAgQIECAAIHGCVh/Ny6kI3VIAnAkNpXKCpiAygqqT4AAAQIECBAgQIAAAQIE+gtYf/c3akMJCcA2RLmGfTQB1TAomkSAAAECBAgQIECAAAECjROw/m5cSEfqkATgSGwqlRUwAZUVVJ8AAQIECBAgQIAAAQIECPQXsP7ub9SGEhKAbYhyDftoAqphUDSJAAECBAgQIECAAAECBBonYP3duJCO1CEJwJHYVCorYAIqK6g+AQIECBAgQIAAAQIECBDoL2D93d+oDSUkANsQ5Rr20QRUw6BoEgECBAgQIECAAAECBAg0TsD6u3EhHalDEoAjsalUVsAEVFZQfQIECBAgQIAAAQIECBAg0F/A+ru/URtKSAC2Ico17KMJqIZB0SQCBAgQIECAAAECBAgQaJyA9XfjQjpShyQAR2JTqayACaisoPoECBAgQIAAAQIECBAgQKC/gPV3f6M2lJAAbEOUa9hHE1ANg6JJBAgQIECAAAECBAgQINA4AevvxoV0pA5JAI7EplJZARNQWUH1CRAgQIAAAQIECBAgQIBAfwHr7/5GbSghAdiGKNewjyagGgZFkwgQIECAAAECBAgQIECgcQLW340L6UgdkgAciU2lsgImoLKC6hMgQIAAAQIECBAgQIAAgf4C1t/9jdpQQgKwDVGuYR9NQDUMiiYRIECAAAECBAgQIECAQOMErL8bF9KROiQBOBKbSmUFTEBlBdUnQIAAAQIECBAgQIAAAQL9Bay/+xu1oYQEYBuiXMM+moBqGBRNIkCAAAECBAgQIECAAIHGCVh/Ny6kI3VIAnAkNpXKCpiAygqqT4AAAQIECBAgQIAAAQIE+gtYf/c3akMJCcA2RLmGfTQB1TAomkSAAAECBAgQIECAAAECjROw/m5cSEfqkATgSGwqlRUwAZUVVJ8AAQIECBAgQIAAAQIECPQXsP7ub9SGEhKAbYhyDftoAqphUDSJAAECBAgQIECAAAECBBonYP3duJCO1CEJwJHYVCorYAIqK6g+AQIECBAgQIAAAQIECBDoL2D93d+oDSUkANsQ5Rr20QRUw6BoEgECBAgQIECAAAECBAg0TsD6u3EhHalDEoAjsalUVsAEVFZQfQIECBAgQIAAAQIECBAg0F/A+ru/URtKSAC2Ico17KMJqIZB0SQCBAgQIECAAAECBAgQaJyA9XfjQjpShyQAR2JTqayACaisoPoECBAgQIAAAQIECBAgQKC/gPV3f6M2lJAAbEOUa9hHE1ANg6JJBAgQIECAAAECBAgQINA4AevvxoV0pA5JAI7EplJZARNQWUH1CRAgQIAAAQIECBAgQIBAfwHr7/5GbSghAdiGKNewjyagGgZFkwgQIECAAAECBAgQIECgcQLW340L6UgdkgAciU2lsgImoLKC6hMgQIAAAQIECBAgQIAAgf4C1t/9jdpQQgKwDVGuYR9NQDUMiiYRIECAAAECBAgQIECAQOMErL8bF9KROiQBOBKbSmUFTEBlBdUnQIAAAQIECBAgQIAAAQL9Bay/+xu1oYQEYBuiXMM+moBqGBRNIkCAAAECBAgQIECAAIHGCVh/Ny6kI3VIAnAkNpXKCpiAygqqT4AAAQIECBAgQIAAAQIE+gtYf/c3akMJCcA2RLmGfTQB1TAomkSAAAECBAgQIECAAAECjROw/m5cSEfqkATgSGwqlRUwAZUVVJ8AAQIECBAgQIAAAQIECPQXsP7ub9SGEhKAbYhyDftoAqphUDSJAAECBAgQIECAAAECBBonYP3duJCO1CEJwJHYVCorYAIqK6g+AQIECBAgQIAAAQIECBDoL2D93d+oDSUkANsQ5Rr20QRUw6BoEgECBAgQIECAAAECBAg0TsD6u3EhHalDEoAjsalUVsAEVFZQfQIECBAgQIAAAQIECBAg0F/A+ru/URtKSAC2Ico17KMJqIZB0SQCBAgQIECAAAECBAgQaJyA9XfjQjpShyQAR2JTqayACaisoPoECBAgQIAAAQIECBAgQKC/gPV3f6M2lJAAbEOUa9hHE1ANg6JJBAgQIECAAAECBAgQINA4AevvxoV0pA5JAI7EplJZARNQWUH1CRAgQIAAAQIECBAgQIBAfwHr7/5GbSghAdiGKNewjyagGgZFkwgQIECAAAECBAgQIECgcQLW340L6UgdkgAciU2lsgImoLKC6hMgQIAAAQIECBAgQIAAgf4C1t/9jdpQQgKwDVGuYR9NQDUMiiYRIECAAAECBAgQIECAQOMErL8bF9KROiQBOBKbSmUFTEBlBdUnQIAAAQIECBAgQIAAAQL9Bay/+xu1oYQEm8NfRgAAIABJREFUYBuiXMM+moBqGBRNIkCAAAECBAgQIECAAIHGCVh/Ny6kI3VIAnAkNpXKCpiAygqqT4AAAQIECBAgQIAAAQIE+gtYf/c3akMJCcA2RLmGfTQB1TAomkSAAAECBAgQIECAAAECjROw/m5cSEfqkATgSGwqlRUwAZUVVJ8AAQIECBAgQIAAAQIECPQXsP7ub9SGEhKAbYhyDftoAqphUDSJAAECBAgQIECAAAECBBonYP3duJCO1CEJwJHYVCorYAIqK6g+AQIECBAgQIAAAQIECBDoL2D93d+oDSUkANsQ5Rr20QRUw6BoEgECBAgQIECAAAECBAg0TsD6u3EhHalDEoAjsalUVsAEVFZQfQIECBAgQIAAAQIECBAg0F/A+ru/URtKSAC2Ico17KMJqIZB0SQCBAgQIECAAAECBAgQaJyA9XfjQjpShyQAR2JTqayACaisoPoECBAgQIAAAQIECBAgQKC/gPV3f6M2lJAAbEOUa9hHE1ANg6JJBAgQIECAAAECBAgQINA4AevvxoV0pA5JAI7EplJZARNQWUH1CRAgQIAAAQIECBAgQIBAfwHr7/5GbSghAdiGKNewjyagGgZFkwgQIECAAAECBAgQIECgcQLW340L6UgdkgAciU2lsgImoLKC6hMgQIAAAQIECBAgQIAAgf4C1t/9jdpQQgKwDVGuYR9NQDUMiiYRIECAAAECBAgQIECAQOMErL8bF9KROiQBOIFt2bJl8dnPfjYuvfTSuOeee2KDDTaInXfeOd761rfGySefHBtttNFIyGtXuvzyy+OCCy6IxYsXx4oVK2KrrbaKhQsXxrvf/e446qijBjrGU089FV/84hfjb//2b+PWW2+NX//617HtttvG6173uviTP/mTeNnLXjblfnbaaafI/vbbdtxxx7j77rv7FRv6dRPQ0GQqECBAgAABAgQIECBAgACBoQWsv4cma2QFCcDfhvWSSy6J4447LlauXDlpoHfdddciMbhgwYKRB8IzzzxTJPm+9KUv9dzHCSecEF/4whdizpw5Pcs8+OCDcfTRRxcJxMm2TFx+7nOfi9xXr00CcOQwqkiAAAECBAgQIECAAAECBGaNgATgrAnVtDZUAjAibrzxxjjwwANj1apVsckmm8Rpp50Whx12WPH9okWL4sILLyyCkEnAJUuWxLx580YKSu733HPPLerutddeceqppxZnGC5dujQ+9rGPFe3ILcudffbZkx7j6aefjkMPPTS+//3vF6+/6U1vihNPPDG22GKL+Nd//df4y7/8y3jggQeKBOK3v/3tnmcUdhOAb3jDG4o6vbb111+/6Pe4NxPQuEXtjwABAgQIECBAgAABAgQIPF/A+tuoSAEJwIg4+OCD49prr4311lsvrrnmmth///2fMzo+/vGPF8m63M4444w488wzhx49t99+e3FZbl66u88++xTH2XDDDdfs57HHHotDDjmkSDBmO2655ZZJzza86KKL4l3veldR76STTorzzjvvOW25884749WvfnVxJmOerZj7yf2tvXUTgO94xzvi4osvHro/ZSuYgMoKqk+AAAECBAgQIECAAAECBPoLWH/3N2pDidYnAG+44YbYd999i1i/5z3vic9//vPPi3teurvnnnsWybTNN9+8OMNu7ty5Q42PTNadf/75RZ3rrrsu9ttvv+fVv/7669ckHydL7mWFPfbYo2hHnvGX9ymc7L6EeZZhnkWY29e//vU49thjJQCHipbCBAgQIECAAAECBAgQIECgGQISgM2IY9letD4BePrpp8c555xTOGYCrpsMXBt2YlLtyiuvjCOOOGJg+9WrV8f2228fy5cvj912261I4PXa8vXbbrsttttuuyLBt84666wpmmcRvvSlLy2+/+M//uM1CcW193XffffFNttsU/z4j/7oj+Lv/u7vJAAHjpaCBAgQIECAAAECBAgQIECgOQISgM2JZZmetD4B2L38d+ONN46HH3540stlEzjP2jvggAMK6w9/+MNx1llnDex+1113Fff6y63XWYbdneXr+YTg3LLe/Pnz1xxn4uW/f//3fx9/+Id/2LMNmSjMhOEOO+ww6dN+XQI8cPgUJECAAAECBAgQIECAAAECs1ZAAnDWhm6sDW99AnCrrbaKfKruK1/5yrjpppt64j700EPFZbe55SW1eWntoFs+jOP1r399UfzTn/50vP/97+9ZNV//wAc+ULyeTx3Op/12tz//8z+PT37yk8W3+cCQV73qVT33kw/3+Kd/+qfiDMJHHnkkMsE5cesmADPBuOmmmxYPIskHjLzwhS+M17zmNcWZg7mPiWcgDtrfQcqZgAZRUoYAAQIECBAgQIAAAQIECJQTsP4u59eU2q1OAD7++ONrHsRxzDHHFE/NnWrLJwQ/+uijxf378ozAQbe8r+B73/veovg3vvGNeMtb3tKz6je/+c019+zLenlGYHfLM/6+9rWvFd+uWLEittxyy577ed/73rfmASG33nrrmkuHuxW6CcCp+pBPRs7j5eXIw245wUy13XvvvUWiMbe81DkvkbYRIECAAAECBAgQIECAAAEC4xWQAByv52zdW6sTgJlE23rrrYvYve1tb4tFixZNGcc8Oy4fAJIPBLn55psHjvnEpwhffvnlceSRR/asm693z/r7xCc+EaeccsqaspmkvOyyy4rvV61aFS94wQt67ueDH/xgfOxjHytezycL55OBJ2677rpr7L777sW9DLM/m222WXEJdCY282ElmZTLLcvkz/L1YbZhzhyUABxGVlkCBAgQIECAAAECBAgQIDC4gATg4FZNLtnqBGAmnvIeebm9/e1vj69+9atTxjrLZp28n9+dd9458Lj4yEc+Utw3MLerrroqXvva1/as+53vfCcOP/zw4vWs96EPfWhN2fx5vp5bXq47Z86cnvvJ42X93K699to46KCDnlM2k335ROPJtrxkOM9S/Od//ufi5T/7sz+LT33qUwP3NwtKAA7FpTABAgQIECBAgAABAgQIEJgWAQnAaWGddTttdQKwzWcA9hup//Ef/xEveclL4le/+lVx/8D8d/311+9Xbc3rLgEemEpBAgQIECBAgAABAgQIECAwbQISgNNGO6t23OoEYJvvATjIKD355JPjr//6r4uiP/jBD9Y8BXmQuv3KmID6CXmdAAECBAgQIECAAAECBAiUF7D+Lm/YhD20OgGYAcwHafzyl79s3VOABxm85513XuTDRHLLpx7n04/HtZmAxiVpPwQIECBAgAABAgQIECBAoLeA9bfRkQKtTwAefPDBxT3y8jLXvC/eeuutN+nIyAdhHHDAAcVreX+9s846a+ARdNdddxX3Dcwtn+qbT/ftteXrF1xwQfFy1ps/f/6aohdddFG8613vKr7/+7//+8inAvfaXvrSl8btt99e3ONw2bJlA7d1YsE8+y/PAsxNAnAkQpUIECBAgAABAgQIECBAgEClAhKAlfLX5uCtTwCefvrpcc455xQBuf7662PfffedNDjnnntunHbaacVrV155ZfH03EG31atXx/bbbx/Lly+P3XbbLW655ZaeVfOpu7feemtst912xQNHJj5MIxN6mdjL7Y//+I+Lp/VOtt13332xzTbbFC/90R/9Ufzd3/3doE19Trk8+y/PAszt+9//fhx44IEj7WeySiagsVHaEQECBAgQIECAAAECBAgQ6Clg/W1wpEDrE4A33HDDmqRfr7Pznnnmmdhzzz2LxF0+OfeBBx6IuXPnDjWCTjrppDUJuzybcL/99nte/UxA7r///sXPs3w3+Tax4B577FG0Y4sttigShBtttNHz9jMxWTnqmXv5EJA8azEvj85j5ENANthgg6H6PFVhE9DYKO2IAAECBAgQIECAAAECBAhIABoDUwq0PgGYOt3LgPPy32uuuWZNEq4r9/GPfzxOPfXU4tszzjgjzjzzzOegfu9734vDDjus+Nk73vGOuPjii5+HnmfvZfLu6aefjn322ac4zoYbbrim3KpVq4p2LFmypLgM+Sc/+Unssssuz9vPxMuA8/Lcz33uc88ps3Tp0th7771j5cqVsWDBgiJZuPZlzVdccUUccsghzzn+xJ38+te/jje/+c3xz//8z8WP/9t/+2/x2c9+dqy/ShKAY+W0MwIECBAgQIAAAQIECBAgMKmA9beBkQISgBFx4403Fpe3ZhJuk002ibwsOBN6+f2iRYvW3JNv1113LRJ08+bNGzoBmBXyEuI8Oy+3vfbaKz74wQ8WZ9ll0u6jH/1o0Y5uubPPPnvSEZoJxEze5VN5c8tE3Yknnhi/8zu/E3k240c+8pHiDMU5c+bEt7/97TjqqKOet59DDz00br755njTm94UBx10UNGG7Hee9ffDH/6wuEfhz372s6JeXnKcP8szDse5mYDGqWlfBAgQIECAAAECBAgQIEBgcgHrbyNDAnDCGLjkkkviuOOOK86cm2zL5N+ll15anFW39jbIGYBZJy8lzmRdnsXXa8uHfORDQDKB12t78MEH4+ijj47FixdPWiQv1c0zA0844YRJX88E4NVXX933NyATjX/7t39b3I9w3JsJaNyi9keAAAECBAgQIECAAAECBJ4vYP1tVKSAMwAnjIN8Wu5nPvOZItGXvyDrr79+kfA79thjIx+IMdn99rL6oAnA7qEuu+yyIsmXCbxM5m255ZaxcOHC4gnBk52xN9lQfeqpp+LCCy8sHvCRl/k++uijse2228bhhx8ef/qnfxove9nLeo7wPIvxqquuirwX4W233Va0IZ+AnP3LfeSDUPLhIfmgk4kPIRnnr4wJaJya9kWAAAECBAgQIECAAAECBCYXsP42MiQAjYHKBExAldE7MAECBAgQIECAAAECBAi0SMD6u0XBnqKrzgA0DioRMAFVwu6gBAgQIECAAAECBAgQINAyAevvlgW8R3clAI2DSgRMQJWwOygBAgQIECBAgAABAgQItEzA+rtlAZcAFPA6CZiA6hQNbSFAgAABAgQIECBAgACBpgpYfzc1ssP1yxmAw3kpPSYBE9CYIO2GAAECBAgQIECAAAECBAhMIWD9bXikgASgcVCJgAmoEnYHJUCAAAECBAgQIECAAIGWCVh/tyzgPborAWgcVCJgAqqE3UEJECBAgAABAgQIECBAoGUC1t8tC7gEoIDXScAEVKdoaAsBAgQIECBAgAABAgQINFXA+rupkR2uX84AHM5L6TEJmIDGBGk3BAgQIECAAAECBAgQIEBgCgHrb8MjBSQAjYNKBExAlbA7KAECBAgQIECAAAECBAi0TMD6u2UB79FdCUDjoBIBE1Al7A5KgAABAgQIECBAgAABAi0TsP5uWcAlAAW8TgImoDpFQ1sIECBAgAABAgQIECBAoKkC1t9Njexw/XIG4HBeSo9JwAQ0Jki7IUCAAAECBAgQIECAAAECUwhYfxseKSABaBxUImACqoTdQQkQIECAAAECBAgQIECgZQLW3y0LeI/uSgAaB5UImIAqYXdQAgQIECBAgAABAgQIEGiZgPV3ywIuASjgdRIwAdUpGtpCgAABAgQIECBAgAABAk0VsP5uamSH65czAIfzUnpMAiagMUHaDQECBAgQIECAAAECBAgQmELA+tvwSAEJQOOgEgETUCXsDkqAAAECBAgQIECAAAECLROw/m5ZwHt0VwLQOKhEwARUCbuDEiBAgAABAgQIECBAgEDLBKy/WxZwCUABr5OACahO0dAWAgQIECBAgAABAgQIEGiqgPV3UyM7XL+cATicl9JjEjABjQnSbggQIECAAAECBAgQIECAwBQC1t+GRwpIABoHlQiYgCphd1ACBAgQIECAAAECBAgQaJmA9XfLAt6juxKAxkElAiagStgdlAABAgQIECBAgAABAgRaJmD93bKASwAKeJ0ETEB1ioa2ECBAgAABAgQIECBAgEBTBay/mxrZ4frlDMDhvJQek4AJaEyQdkOAAAECBAgQIECAAAECBKYQsP42PFJAAtA4qETABFQJu4MSIECAAAECBAgQIECAQMsErL9bFvAe3ZUANA4qETABVcLuoAQIECBAgAABAgQIECDQMgHr75YFXAJQwOskYAKqUzS0hQABAgQIECBAgAABAgSaKmD93dTIDtcvZwAO56X0mARMQGOCtBsCBAgQIECAAAECBAgQIDCFgPW34ZECEoDGQSUCJqBK2B2UAAECBAgQIECAAAECBFomYP3dsoD36K4EoHFQiYAJqBJ2ByVAgAABAgQIECBAgACBlglYf7cs4BKAAl4nARNQnaKhLQQIECBAgAABAgQIECDQVAHr76ZGdrh+OQNwOC+lxyRgAhoTpN0QIECAAAECBAgQIECAAIEpBKy/DY8UkAA0DioRMAFVwu6gBAgQIECAAAECBAgQINAyAevvlgW8R3clAI2DSgRMQJWwOygBAgQIECBAgAABAgQItEzA+rtlAZcAFPA6CZiA6hQNbSFAgAABAgQIECBAgACBpgpYfzc1ssP1yxmAw3kpPSYBE9CYIO2GAAECBAgQIECAAAECBAhMIWD9bXikgASgcVCJgAmoEnYHJUCAAAECBAgQIECAAIGWCVh/tyzgPborAWgcVCJgAqqE3UEJECBAgAABAgQIECBAoGUC1t8tC7gEoIDXScAEVKdoaAsBAgQIECBAgAABAgQINFXA+rupkR2uX84AHM5L6TEJmIDGBGk3BAgQIECAAAECBAgQIEBgCgHrb8MjBSQAjYNKBExAlbA7KAECBAgQIECAAAECBAi0TMD6u2UB79FdCUDjoBIBE1Al7A5KgAABAgQIECBAgAABAi0TsP5uWcAlAAW8TgImoDpFQ1sIECBAgAABAgQIECBAoKkC1t9Njexw/XIG4HBeSo9JwAQ0Jki7IUCAAAECBAgQIECAAAECUwhYfxseKSABaBxUImACqoTdQQkQIECAAAECBAgQIECgZQLW3y0LeI/uSgAaB5UImIAqYXdQAgQIECBAgAABAgQIEGiZgPV3ywIuASjgdRIwAdUpGtpCgAABAgQIECBAgAABAk0VsP5uamSH65czAIfzUnpMAiagMUHaDQECBAgQIECAAAECBAgQmELA+tvwSAEJQOOgEgETUCXsDkqAAAECBAgQIECAAAECLROw/m5ZwHt0VwLQOKhEwARUCbuDEiBAgAABAgQIECBAgEDLBKy/WxZwCUABr5OACahO0dAWAgQIECBAgAABAgQIEGiqgPV3UyM7XL+cATicl9JjEjABjQnSbggQIECAAAECBAgQIECAwBQC1t+GRwpIABoHlQiYgCphd1ACBAgQIECAAAECBAgQaJmA9XfLAt6juxKAxkElAiagStgdlAABAgQIECBAgAABAgRaJmD93bKASwAKeJ0ETEB1ioa2ECBAgAABAgQIECBAgEBTBay/mxrZ4frlDMDhvJQek4AJaEyQdkOAAAECBAgQIECAAAECBKYQsP42PFJAAtA4qETABFQJu4MSIECAAAECBAgQIECAQMsErL9bFvAe3ZUANA4qETABVcLuoAQIECBAgAABAgQIECDQMgHr75YFXAJQwOskYAKqUzS0hQABAgQIECBAgAABAgSaKmD93dTIDtcvZwAO56X0mARMQGOCtBsCBAgQIECAAAECBAgQIDCFgPW34ZECEoDGQSUCJqBK2B2UAAECBAgQIECAAAECBFomYP3dsoD36K4EoHFQiYAJqBJ2ByVAgAABAgQIECBAgACBlglYf7cs4BKAAl4nARNQnaKhLQQIECBAgAABAgQIECDQVAHr76ZGdrh+OQNwOC+lxyRgAhoTpN0QIECAAAECBAgQIECAAIEpBKy/DY8UkAA0DioRMAFVwu6gBAgQIECAAAECBAgQINAyAevvlgW8R3clAI2DSgRMQJWwOygBAgQIECBAgAABAgQItEzA+rtlAZcAFPA6CZiA6hQNbSFAgAABAgQIECBAgACBpgpYfzc1ssP1yxmAw3kpPSYBE9CYIO2GAAECBAgQIECAAAECBAhMIWD9bXikgASgcVCJgAmoEnYHJUCAAAECBAgQIECAAIGWCVh/tyzgPborAWgcVCJgAqqE3UEJECBAgAABAgQIECBAoGUC1t8tC7gEoIDXScAEVKdoaAsBAgQIECBAgAABAgQINFXA+rupkR2uX84AHM5L6TEJmIDGBGk3BAgQIECAAAECBAgQIEBgCgHrb8MjBSQAjYNKBGbDBPTzn0d8+9sR3/9+xG23RfzylxFPP935Wnfdztfv/m7ES18acdBBEX/wBxHbb18JZ20P+sQTEffdF7F8ecSyZRF3391xfOihiFWrOs3ecMOITTeNmDs3YuONI9ZbL2LOnIiNNur8m875sy22iNh2287Xi14UscEG4+v2xHZmW3/1q4innno21qtXd9qSX8880/laZ51nX5+sfdm6bt8n2+d09qlff6bz2OOLyvTuaRxG49jH9Pay3N7H2r+x7qxcv55Xu85tG3NXp2V3Zf3K1p+WTg2w03G1e9A3yt/5nc6Hjp12ithxx+l5M+zX7XH1ud9x2vr6bPfttj8/7N1yS+dDX36geuSRZyM6b17nA12O49137/zb60PdbPrdGHXMzvaY9+p32X6VrT9qPKaqV8c2DdnP2bD+HrJLio8gIAE4Apoq5QXqOgE9+GDEhz8cccUVnSRVJn4y2fPkk51kT37f3TIBlMmpTFxlYii/z8/nRx4Z8T/+R8SWW5Z3mo17SKubb4740Y8i7rkn4v77IzKZmp8Bf/Objmf+mwm2fC/t/iz90nH99SNe8ILOVyYE03GrrSI22aTzleZZNhOBr351xMtf3onBsNvEdmaCLmObMf71ryMee6wT80xW5tfjj3eSkHmc/Hm2PduXa7H8yp9nwjKTmVn+3ns7rdlmm077c3/51R1D3bGTdcbVp379mc5jD2tfVflxGL3iFZ3x93/+Tyexvfa4me3O4zBa83sZEyaDumGNtaMjTEBV/RKM67hl/bbeuvOXn0wM5JvEbPlFKtvv7hvXbrtF3Hpr/zfKnFByyze+fHPsvklmAiX/4vjCF0a8+MXl3gz7jYlx9XnUN+t+7Zvtr8923277b7gh4qabIn7xi4iVK5/9gJcf8rJMbvnmmR+mciznV/4lN+eB/L141asi9t03Yjb9bow69mZ7zHv1u2y/cj7LBHGOnwceqMf7Qtk+lV2sjDrGetSr6/p7zN20uz4CEoCGSCUCdZuAvvOdiLPP7nx2ybk+E1P5byarBt3yc3kmgvLzTP6bn2VOPz3ita8ddA+zu1wm+Lqf//L/ubbJs/66ya9u4qx7FmUm0XLLdV/3K7/vnmmX651MsmWSLD8vZqIsPydutlnn80EmBXMNlEm3tH7Nazrf99smtjPPQszvV6zorEOzrflZNf//6KPPJn+7CcscD9m+7ufXbvK3ezZiJgqz3RO37G+2Pduc5SaeRdj9PJx9HLVP/frTTVqvfQbjOI7dz7our4/DKNcqGcscF7llcjpjnWMjx81sdx6HUXcMb7fhr2L+ihviVevcFDtsuSo2XLXWL1mVWOPs6CgTUF1+KUZtR1m/nDy7CYGcQPP/3WRAvilUOTamMinb7+4kn78kOWHkX4ry//lmk8nxfDPq/uVpokP3TTITJ91T0bt/jcp95leeDZhJkxyPw7wZ9hsD4+rzqG/W/do321+f7b7d9v/whxFLl0bcdVcncZNvkjmWcxx3L5eYGKuJv+M5lvNDXH5I6v5FND+s5Fiu8+/GqGNvtse8V7/L9qv7vtB9P8gFQ74/5HtDVe8LZftU5oP9qONrgHp1W38P0GRFpkFAAnAaUO2yv0BdJqA82+v44yOuuqrzHpMJnG5iKj9vd8/Uyvem7qWp3d7l55os271UdGISK8tm8ir/PfzwiL/5m873TdwyKfKDH0RcfXXnM1+eGXXHHZ0kahp1T2Do9j+N8/NduuV7fb7eXdtk+XTsng3Y9c/PgvmVr2++eeczQR4r95l/XMsz7fL/hxzSuRw797/2NrGd2YY8Sy/XXfn/TObkWiw/t+Z7fh43/5+fP7Od+Tmke+Zhtq8b9/xZHqubIOz2K/ue+8h2ZtIy25yfcefPj9hhh85r2ZfuMXIc/sd/dL4ftE/9+pOJ0m7iMfs30aTssWfLOB6HUcYlr2L62c86Y2XiCTkZq4xnxjXjPBudx2GUvyc5hh95+OmYv/wHsc+jV8cWGz0e28S9sdmjy2PLTR6PzbbdONbZvMJBOc6ODvvLOlt+YaZqZ1m/HCR33vnsX4VywORE2v3rTk6QeSngLrt0Jq66TFhl+92d5DMxkn8Ry/tC5BtAvml0/8rU/ctQ/rx76nv+rJsYzbhk+fzKN5esl5NRbt03oSyfdpkATMup3gz7jcdx9XmUN7Z+bWvC67Pdt9v+73638zv9f/9vxMMPP3uZQ47jHI/5hphJkO5Y7n7Q647j7l+HM/nd/QtxzgfdD4I5B9Ttd2PU8TfbY96r32X71X1fyA9ZOQ7Wfl/o/oFjJt8XyvapzAf7UcfXEPXqsv4eosmKToOABOA0oNplf4E6TED/839GfOADnUt9u3+szJZ3r7AZ9h5z3UuFu5e05r7ys0y+f2Xy6q/+KuINb+hvM5tK5JVb3/pWJ5GW90m88cbO+iQ/53XXdvkZMC3zfT5fy6/u2qW7vkmn3LpXgXU/H3ZPeOha5m1i8pLbTNbl1U/5mTOvEsgtT4LIZMx220W88Y0ReYVZd5vYzkzk5DostyyTCcSMeZ6xmG3MtX1+5dZNDK49FrJd+Tklk4gTx0433pmQzL51zyTMfWVCLr8yUZQna+S+J265z+4fvPv1qV9/8hjDbMMce5j9Vll2HEYZ44njIk/aybGZXjkmcixOFdO1+18353EYdfu48a/vj91u/Vas/+Dy2OD+n8VmD3dzQ9KHAAAgAElEQVR+yX6z+dbx1Au3jRdstemk477nGBkn1jg72p2oBv1lrfKXYFzHLuu39i9STtwT//KTE2e/CXLUybKMQdl+d489sf/dG8N2L4nsfuDIDwr5ZpTJz35b/m50T1XPfadlGubPM4GYScC8OfFkb4b99j2uPnePM87f435tnw2vz3bfbvtvvz3iuus6H/7yQ12OwXxT7F6iMegH6Kyb++x+WMrvc+v+FTjHc/5O1OF3Y9TxNdtj3qvfZftVx/eFsn2q+4e+yFsy/TxenLeNiLxN0z2xvZvXj/qbPavrSQDO6vDN3sZXPQGdcELEP/xD5zN0/tGpm2jKP5x3k1FldDP5lfvtXv2Q+82E0JvfHPHFL5bZc33qLl7cuVdinthw/fWd+/xlP3Ndk1/dy3W7Z9Xl58PuffDys2H3D7u9epR23YRh92Eg3f3m+1XWX7Cgk8TLpF7ebzATg5lcy2PnvRgXLoyY2M5uMiff+zJZmGf25e1q8o/Yeay8B2SOiW7b176ct9vW7HMmjjPO2b+JSaHupaGZ9M39ZL8zoZh1cgzkPQG7bc/12WRb9rNXn7J8132y/pQdIVMdOz1nw9Yv5oP0YapxkfWHjenax6zaeRxG3T5t+4vFseDOK2KDJ1bGlg/eGuv/5pF4eJMXx89ih3jo13MHHvc941IGa5wdHfaXdbb8wkz1C1HWr98EO8oEObG9ZcbGdPa7u++J/c83yXwjyDee7inwWa57tlS+4XTfOAaZpLLMRL/cb37lh498k9xvv+e+GfbbZ9lY99v/dMWq33Hr8vps9+22P//am//PD3T5QS3HbV7mkMm/Xh+aJovBxA9S3XsGdi+xyPLd+63kB6n8cFnl78aoY2i2x7xXv8v2q47vC2X71G+M1GT+q3r93Y/J6zMjIAE4M86OspZAVRNQfuZ+61sj8p5/mbjJ77tXKwz6B8thgtlNYOVnmkwsZnIo7wn49a+PJ9E4TFvGVTb7cs01EXn1Rybd/u3fOmfDpV+aZj8zyZXJrkyS5Mke6ZBrku7TfYdJsmaMup8zu/dhyzVOnmWXnze7D0TMPyBnQizPLnzJSzonP+TnxbykNz9r5O1p8o/J3QRh9qP7ZOLu59Bu23uNhayzdp/y825+Ns2t2878PvfR/UycY6ybYMz+5MNi8jNtt+35eq/PxxP71L08PY/5058+tz/jim93P2ky8di5njzssIiDD+78ztRxmzg2c629dswHafMw42KUmK7dhpl2HofRmj6sXh07Lrsm5t/93Zi38uexxUN3xZPrvSAe3HK3+M0GndNQx2G05njDYI21owOMnGHaNsDuKi9S1m+YX6RxDJRx+ZftdzdwE/ufbxp5unguALs3Du2+GfZ74xh0IEz8RcsPGvl9njm1996dh4RMNXmPq8+DtnVcsRr0eFWXm+2+3fbnB+clSyJ+8pNn75WTH6q6f9Uc1HniB6n8wNY9i7V7b5SJv0P5//x5935q+eEpP/gN8yGkzO/GoH1au9xsj3mvfpftVx3fF8r2adgxUvH8V9X6e1gm5adXQAJwen3tvYdAVRPQm97USf51P2/kZ/C179s17qB177fW/UNpfibPJGBegjwbt7zXXyb/Mrny4x8/+6CUfE/LpFZ+PsvPZpn4y69M/OXnr0yI5WfFYT63TfwcmJ8Tcz+ZBOzenzEfGJbHy0RafqVxtiuTP3m87nHz30xgZWKwe2upvOVIfuWZfLk+m9j2XnHp16f8HNFtZx4/E4GZBMyv3PL1PF5a5WfYiW3vdcxun/7935+9P372f889n9uf6RhLEz3zjMn0y3Vk3l6qjtvEsZlnUP7/7F0HeFTF2n63Jtn0kF6AUEOvoRdRERSwgP0qxQIK9o7e673/1Wv36kXxIhawoSIogoBgpUtvAgGkJSSQRno22exu/uedc0442ZzN7qaAXvmeh4ckZ86cmW++mfnmna+4jrk3bfZVLhoypq7tOJd8bgoeKe1vdXyNAP/CCo4irCgdRSGJKAxvg2pd7SCcTcGjGp55y6ym7Kg3gsMy3rbN2/rOZ7nG8s/XidTQBVLNo6bgf2P7rbRH3X8ly7Hiuuu6GXraOLyVA/VEU+JAcMNj6vL6Fu+m6rO37fxfmyue+v1H56/Sfrr80vqPMkXLU0WJ8VWpUytSvDWm3PKfoiQrN8RKsGWlfipU/KZaqfLEe7USqShfvswNb+t3LfdHH3N3/W5sv36P+0Jj+9QQGWmKvaoh373gAtxArv3vvXYBAPzfG9M/RI/OBwB4220S6KYOmeMah605madYHNIAgCDgtdf+8dyBmeV3xQoJZFMAKe5jBNCUi1nykAAXLe8U8I/AX1MkQSG4xn9q92G6APPbjBGsuNTSKpHgpJJxl+cfGkIoRItAJipRwD91293JgGufFCs/rfLqdmp5rpBf/LaiP6vbrlUf28uLd4bbITEcTt++Z/vbnHLLumnpySR/Cgg4ZozkXv17IrVsEvxr21YyfPGFGiIXSv2+jqlWu5qbz03BI6XdCZlb0P7wihrw70x4WxSH1s/wpuBRDd/qY1ZTdtQXAVLKNvdANqRNvrzTWP41ZiKxnY0VlIbyv7H91tpglICuSkyL+jZDTxuHt2Oo5h83QfWNkevi3VR99rZtruUaOlYN/d65fu+Pzl+l/fyfln8E5xQ3BiowvpJakaJSTCL4p8SxdHUPUYOALEdLQAJ4vroDa23UnuaGr31Tyv/Rx9xdvxvbr9/jvkCZUg41DVUcGyonfO88rH/n4/zdGBZdeLd5OHABAGwevl6o1QMHzvUCRODv9ttrJ5g6l+Cfwg4FBFQSH86f/8dJDEIjhrlzJbdZ6oG0quPeSaBPDaAxHp4SF5oAYFOBfwoPlTOS4nZLXkZFSWAaQTG2aft2qQ1sMwFCAoN8xjEnAMznPCO5tt2d2LJP9ODit9mn+sA/rXYSsCRoR+tFVz2UeqzSdi2ZVLeXbWD/WFd97zTHAqToKYy7yIQr06bVTrTSHN/0tk61bDKeY0PAv4bIhWv7lHO3pzGtr1/Nxeem4JHSbib86LN9LkKLTqDFmd/gDfjnq9x7NfZazOIEURaqhgqDVx/3UKi5BrIp2lZfHY0VlKaYSGxfYyeTr/xvbL8Vnqr7n5t71lXS281QvcFpbRzejr+af0qck86day/eTdVnb9vkrpyvY9XY752r9//o/FXaz1ggGzacdavw5sZUi8dqRUrJgM1ySsY4d7FhXEFAAoBK0hy1UuXtuHozN7yty7XcH33M3fW7sf36Pe4LzOLGtZHBv/9EusK5Pn83dCpdeK95OXABAGxe/l6o3Q0HzuUCxH2H7pLUxRmjjZd+AQH7YLd/Drv9ZzidB1Bdnc9rSNFana4tgoN3wGb7FHb7t3A4dqC6Og+AVVUmBkbj9aiuLoDTuQVO58lazwE/6PXtYDY/ArN5EnQqFwnGqqMxAPUXglMHDjSNdVxzChsvZ5m8hHsk4+TyLENLRoJs1MWCgnJQUrIFxcVbkJe3FRUVW+F0kqcE3SYhPPwlVFZuQUXFd7Bal8NuP87o5TK/LTCbe8PffwQsluuh0wWipGSWKGu3M5OoEwZDPPz9RyI4eAbM5i7i+2Vl36O6+mNUVq6H03kKer0R/v4xCA7ujoCAS2C33wqDQcqoyHiB3OuZHJGZign8KW0nWKOmiooTyMychfz85aiszIBe7weDoS0qK7d5xWK9PgZJSadFWcUCkslJCBqyHWpvGbaD8uDvvxIFBXNRXr4V5eW5sFiikJCQil69pqK4+PJa7WW9fEfpEy0bffHA+e67x7Fx40s1fZk06Se0bn2RV33j+JNvffpIFpdMpqO4VHtVQTMUUssmrSQJ9hKk9ERZWdtw+PAKpKevR27ufpSV5QIwQa+PR3DwYLRqdTsCAjrUyHVJyVbwn90uyXVMzCSkpMyv8xllTJXx6dXLifz8NGRmbhH/srK2Ijt7DxwOm3hXi/9NzeeG8kjpHNu6e/eH2L//C9H2ivI8mKBDrN6IlKAYxIS2RpmjAgdLTiGvshhFVeWodFYhyOiPVpYo9I9ojyvieiHUZBFVuvJILcMbMzLw1tatWJeejuzSUoT5+6NHbCwm9+iBm7p1qzusamYR+SUASBNlX4RBrrXCbsf7O3di8YED2JOdjaKKCkRaLOgZG4uJPXrgRm4kvlBTD6Qv325IWTeCsi0rCysOH8b69HTsz81Fbnk5THo94oODMbhlS9zeqxeG0DyYGxvNr1UL7DaTCSvy87G+uBj7y8qQW1UFk06HMKMR/no9rE4nCu12GHU6xJjN6B4YiEvCw3FrTAyCiopw/MwZJNNyxAdqFRqK4w88IG1Y3ixYGv3eZrF412d1u1z6X1xZiRU2G74vKcG3DgeynU7YXfphBNDSYMAwf3/cHhSEIbwxc9k4fgsLw9bSUmwpLsaWkhLsLC0VfCO18vMT/CtzOhFsMCDFYsHo8HDcFR+PaCo/ymbBPlLp4E0YF+8pU4D335d4JM+VBvW5nnFZefgw5u7Yga2ZmUJmoiwWpCYkYGrv3ricbVCTt2Plgxyc16JNJVMunTiQm4sfjh3D1qws7M3ORk5ZGfLKy2HQ6xETGCj4e3PXrriyY8daeqfXc+Hsoi8pfcz2+803ksJXXo5tRiNW2O34sbAQv5aVCdkjUXuWJBKYFBOD+Qy2rCauy7zBtFpRXlyMb202fOdwYE1VFY4xVqyqLEMMsz5JI5frNBgwnwChonBQcaM8x8VhfnY2ptA12Uea16IFJnfoIFkfqudGQxWbZhpzd90qr6pC17fewjG6VHMtUNY95YWmmlMa/SpOShLrI+f2tlOnkFlcLOa4tapK7Nmdo6JwRfv2Ym9owTXNZV/ICQrCN/n5+DIvD7tLS3HKZpNPBICBOrufH3oFBeG6qCjcGBUl9psaclEgjrdpg/9u24bvjx3DkTNnUFZVhWCzGSmRkRjdrh3u6tsX0erbdfKFewqDiZOqqlAcHY0VDod3/aGsaFCVwyHm5qrffsPmzEwcys9HUWUlAk0mtAkPxyXJybg7NVX8XIeaaqy8mAPn8vztRXMuFDlPHLgAAJ4nxv/ZP3suFyC62n73naQHk+h+W1LiPosBAUCLZQ7KykY2yTDp9Z0QGLgOen0LUR/1durlJAJDl10GfPFFk3yq2Sph0o8ffpD2cAKpvHQ9ffqsNdrate75SQCwrOwDr9rm53exAPQACRypS2aEhT2DysqNsFq/rrfOpKSdaN26p9A5CZARkKEOwItntSWdGjzLy1uGtLRb4HAUe9VerUJqAJA6L+WO36Dccd9X4gFKsuDE7t0E+d5z+73Y2DsQFPQ2U+IJyz8Sz7RKnxjaiRZ53tDp07vwzjupcDrPHkN9AQApuzwr8ixA0ObSS4GhQ735cvOVUcsm9VSebz2BkvPmDUN6+rpGNcodAMgxV4+P0/kB1q+f7PZbWvxvaj43hEdKgwsLT2DBgjHIzd3XKH4R/Hsy5Rr0i2gnMDotGf7Hzz/jmbVr4WQBDRrTvj0WXX89/NWWImpmEeUn5edLhzpvhEH+zsG8PFz12Wc4yHfd0GVt22Lx9dcjyFurk6YeyEaNgBcvawjKsA8+EGCsJyJA+k737jDTRFxeYIfl5GAdXf4aQDv79EHPwEAcP3ECyazTB+I4rbrlFmmz9WbBcun3sH37vO/zuHEwK5lP2U6Cz+x/eTm+t9kwkhumDzQxMBDvRETATCVBp8MaoxEXKW7EPtQTYTTis06dMJJgIjeL2FgpXT3N5bl4M3EDLV+4qTscaHCfNdrE+Tt12TK8x9s2N3RHr154e9w46JUN2Nux8oEH57VoU8mUSydu+fJLfLJ3r8euDW/VSqxVLRSwwlf+Ku2n8izL8LCTJ7GOFqoeqK2/P/anpsKs3ogJUhUUYE9hIQYXF0NWgT1VVfP8FqMRH6nXfYI3VKjCwzG/oqJhAGB0NCbTlcJ1bjRUsWmmMXfHpEdWr8arjMsoUx0A0Ncxd/chjX3h++PHMfKjjzyOHy/QPh48GKPoMqRSvHWs00vqFhiIr7t0QbLi9qNSID7S6zHtt99g5X7vhiICAvDZhAkYyQtCEvmyerV0UUWKiMD37dph5CefeGyR6M8112CUyy1zblkZOs2ejXyut/UQ94qXLr0U9zNDu5qaaqw89oAx0k8iSY6Pk5GRgUQGy75AfzoOXAAA/3RD/vvo8LlagJjwY8KEs66/vIiiV01RkRqwMkCnC5OtACULwLoAYCQMhjZwOLbIDIwBkF3DTIPhUhiNF0OvbwmnMwN2+zdwODbUPCcIGBT0K3RycHzuhdSjFFfgxYulxCC/R+IeOXu2dK7hZTD3XlpSUp8jqEZ+rllzlp/kgV6fArt9tehOXQDQCKOxDez2Q+K5v/9lwrqvtPSdmr/pdKEICXkY/v4XQ6fzg822E8XFL8Fu/60Wi4zGa2CxXAs/P27sBthsGaiqWoPKysXo3HkZIiJ6Cldl6h0EW3mmUtyAlbYrFZaU7MSuXYPhdFqF5WBS0kwEB49ATo4VxcWfwWp9RxRl26qri1RjHweDIRk220bxt4CACYiOXlTznBfk/K7iCk0LNeXi8ejRmcjIeEF+rxdat34Mffu2RXn5Eaxb9xJycqQDVEjITHTu/JzgNUnpkwIo9ut3NhOxOxmqrnbi3XcHCAu0wMBolJXliKK+AIAsz/M8z4wEHpOTgRkzpHA854PUssmsyDzXKvG962vPrFntUFBwBMHB8ejQ4TpUVAyFzdYSJSUO+PltwqlTr8Jmq2115OfXEhZLCgoKJLl2BwC6jo/VOh8HD04R7+j1JsTEdIPDUYWcHOkQ547/TcXnhvKIbWM73367Vw34FxvVBRNbdEBneyV0xRn42WTBx1nbUFUtKd8DIzrg8rieaGEOFiBebmUx1uTtx7rcA3CiGiadAW/1vgPtgmLryPAe8zbct3q5qKdteDieHDoU3aKjkVVSgv9s3oyfGDwcwE1du2IBF3U1kVmMT8SFicSDQv/+3gkDIKxo+s6diwwZrLquc2dM6tFDWLjx+x/s3o0vGPcAAEHIb26+2Xtxb6qB9P6LDSvpRlDazZqFIwUFghfky9CWLdEyNBSO6mpsysgQB9BM+XbtpuhoLODCKm8O7XbtwpGKCsSbzcKSo3dQEJ5PT0eafEiiBWCFbMk2Kjwc0+LjsaawEIvz8rCsa1f0DApCldWKg3QR5cTmIk4rUI2Ass+vX48FMjDyyfjxuFmxFvXEf41+t5s/3/s+K/LIPlEGGdyVdTqdeKqwEM/Jcc4Uq6YQnQ79ZAB5g80GqwbYfZPFggVc3EtL8bNejxGsU1wBAa38/XFMBcIMCQnBI0lJgsfplZX4IDsby2QQO0Cvx6/du6MN32d9nBcE3Jgxizd4zKJFJL53bzSoz24kbeb33+MFuowC6BUbi8cGDxZzmnL00oYN2MlvA5g5ZAieu+SSs7V4GquGSfa5f6upZEqj5ZOXLEFaXh4GJyWhW0wMYoOChGVlQUWF+Pvb27fjVxkwHpiYiPW33XYWZPWWv0r76Z5CgIkgYlkZ2p0+jSOVlULWsggmyxRjMgmL3oMq8EOsBZ06SSWY/ZpyZrVifUkJhsrrtD8AwoktdDpcZjTiU5ZzQ8k6HY7yFpXfVYI7y67A800mTKEFFYCHExPxKrPAAXi7fXtEuVzWsK0hMpBI2COM4KZ6bnTs2DDFphnHXIslO0+dQuo778BkMAjruBKbra4FIF/0dszdMd7NvvD90aO47euvMSI5GX3i4pAUEoK4YGnfP1lcjEX79+PLAwfEPmHW6bClfXv0oOIqK946Jt6QKUivR0uCxrJcXBYeLvaLeadPY6O8J7fx98eevn0RqFy2VFZiw7FjGJadLSxPeZHAPfuqjh3FXpVeVCT27WU8tFAlMBrx6/TpkvUd5XTdOulQw/UwORnfJyXhtm+/9a4/BgO23HGH8ExQiH1Oeu018Ss9BtiO/gkJiAkKEp4EK3/7DW9s2QJ6GQjZHDsWU+lKo6bGjpWXK925On972ZwLxc4TBy4AgCrGnzhxArNmzcLy5ctBVNzPzw9t27bF9ddfjxkzZsDixuzX17FbuXIl5s6di61btyI3NxdRUVFITU3F1KlTcfnll3tVnd1ux7vvvotPPvkEaWlpKC0tRXx8PC699FLcd9996NKli1f15OXliT4vWbIEx+UDVuvWrXH11Vfj/vvvRwvFosKr2rwvdK4WIF7kbd4sATDUGXh+IJWWDofRyH/Xw2jsCrt9PcrKJFMmyQX4ICor/wmDIVX8o1WX03kcJSXJoozBcLkAgZxOCfQhEBUYWDutr832JazWswfVgIAlMJuvqmGS4gpMnYaXQbxo/T3St99KeyX1QO6V1L+oX5GXCvBz/PjfAaSiqioVZWV0jz6O/HyJVwT4Kiok0MRiuQ6RkZ/A4chEZqb0nABhRMRb4nenMwc6XRBiYzfBbK7tbud0FuPkyVaorpbcHSIjP4Nef4MAEqgHsl2K/hkeXo1WrRzQ6ehgJZ3HGMKEuiB1TLpeu4JWu3YNQ1HROvFOjx5rERo6ULzHsyz3ZTVo7Oc3DCEhj8LPj/IRI1ya1f2JjKztGqp4dLGdtADkt8vLD2Hbti6orrYjIKAvoqLWomXLAGHNx8vFtLRyLF8+HKWldD02ol+/AwgIOOvbqnhB8PJOeac++fnll9exatWDiIxMQUrKNVi//nlR3FcAkO8wIQg9KAYOBIYNA0aNOj+Sq5ZNAqvKBa+n1ixYMBY9ekxEp04TcPSoQcS1VMt0VVUedu4cDKtVUh47d/4KUVFXo6LiODZvluS2PgBQkTnO8dDQLTCZNqNHj1TExvaE0eiPn3/+B9as+T+P/G8KPjeUR2zc/v2L8MUX14l2JiYOxL+GPoXWGRuRdHITioMTUBDRFgeKT+K+XfNgr3YKl98lgx6FwSUL8Pq8NPxt3+einqGRKfhnlxtq5iV5FBJjxaQd/0FJVaUAl7ZPnSpcbxVyOJ245vPPa5T5nyZNwkUEMdTERUo+BIoJ5INp6j0rVmA2YxsA+Pvw4fjHRXVd4v/+00/4p2y18MV11+FaxlPzlppiIL39VkPLuRGUsQsWCPfnCZ06CTdDV6L74eD33xfuTqQ1sbEYRiuziAiM3bsXE2NiMCEqCgadDhPT0vBRdjb8dDos7NwZg0JDMXjnThySF+41PXpgWBgv46qFOxjdgmsJipvFjvLR8vXXBVhL16/sRx5BgHLLwgrq479Gv33u8+TJGMaNRVlIANA9rzVdX+l1oNOht9mMGcHBmGCxCF6Qip1OdMvKQrpsvRIIQE6LgDUxMRhWXY3D5eX42mBAakQE+iQk4Mb9+7FcsVwBMK9jR0xWHURZ78NHjuDfMggyIz4eb1KP40Qj/7gJ0vKPigcVI2bIatsWDeqzhuk55aDLW2/B7nSib3w81k6eXGssyJfh8+eDbuVGvR4HZsxAO/Vm/EeYK57mWFPJlAZ/yVfyzR1xLly/aJEAX0hf33ijcAeuIW/4q7Sfrr+UTYLYwcEYm5lZM5//eeIEUoODxT+67h+vqEAylW0VKfNZrUhtdDjwn4oK/F2nw2MOByb6+WGCySTmxN+sVnxqt+OI0wkFMK9VX2CgmBOiTQSCOI8iIjC/uhpTZHl/uU0bPEpgB8Cx/v3R2lP2ObUixbnB+hui2DTjmLuONce4/7vvYvupU/jnRRcJS9sTRUXaAKCn9a8BssxX2Aat/UBd3ZK0NLFvk66xWPAlFTR5rv/9+HFxITQgJKSO/KhdyB/47Tf8Rw4B8Z+2bXGfylpt7I4dWC5fPs1OTcX0K66o05uHV63Cv3/5Rfx9Rmoq3mQZ6glcq5kJkNS+PRxJSTDQHbweqtWflBR8eYOkx5DoAj3l66/xzxEjMMCNRd3mkycx4oMPYLXbEernh4wHH0SwcquvVOTN/PQ0Zh6en6vzdyObeeH1ZubABQBQZvCyZctwyy23oNiNu0qHDh0EMNjOm+BSbgaN7n4E+d57z7273x133IG3334b+no2eIJ2V1xxhQAQtYjA5ZtvvgnWVR9t3rxZAH2n5dtY17JxcXECGOxH86ImpnOxALFbDNnEeL+8dKHll/sYw7UBwJCQ2pZm7L4aADSZJsFimY+SkhQ4nQeh00UiJKSuq09p6Qg4HD8L7plMt8Ji+bCGk2wT9Sq2iV4IjLNMr5zfExFU+/e/Jcs/5bKMgBj/cY9TLuNoxEH9ixd4NE6wWI7j1CkJKNHpglFdXQKTqQfi4rYJgM0VMAsIGIu8PAloCAl5CuHhz9ZhQ0XFemRnn/U3DQ9/A0FB9whwjjoegUDlApl8ZEgqZRrx7zTgob5I/Y5nd/X5kLELd+7sL74ZFzcNHTrMEV4C6j6pAUC9PgyJiQQrpRgingBA1qW0k7gGeXfkyHRkZf1XvN+9+yYUFw8Q4CDPapxyNCZJT/8Fhw8PFGXi46ejffvZNXyhDsz2Ke9QZ1XGw5V5RUXpeOutLrDZSjFp0s84fvwnrwAod7JIfhIQJgZDnenhh2vz81zIsFo2eXfB/qvH1Js2kIfsB7ELV5nOz/8Gv/46TlSTkHAv2rVjXErvAcD6xsdbALCxfG4sj1ategi//CLdat98/WJMyT+EFvmHEFZ4HBmJA+E0SPL/9L7PsS4vTfz8Xp+70CaIFtK1aeKWN5FhzRdxAAkSkhQe/Vi5AR+e+l787dMJEzRj7fGGvfXrrwuLAsYWWq62wmNF69dLiyiJ8aeGDHE/IVRN40GmxUsviVg9dKE6ct99mgcblmsza5awLKDFw7apU70RMalMYwfS+y81rGQjBeWbtDSMkw969wYHY1aPHnV4v76oCEN37RLt4yGdVmskxoEax5TyAO5NSMAsLR3Lw2LHmEujZfetKT174v2rzl601cv/RvT7m0OHMO7TT5opr4YAACAASURBVKV2p6ZiFm93uJDI1nqLCgtxHZUPAE+FhOBZrbhPAL63WjFStthSLKJEneQjF3eXjSNi0yYUyFYkLKcFABbZ7QiTLfB4yN7O4LfKZkFlgy7d3Cy4MV13nddBiGv1uV8/zNK4sJ6+fLmIx0XadPvtmofhX06exEBZD57ety9mMzOxQr/3ueJphjWVTLnhr6fP87mav48MHIiXGWfGW/4q7SeAyDWVQDFlUK3waTRCCwAU85muAmpFiu8qST0IfqhisPy7shIPV1Sgo16Pzno9vlLJuZgTZjNmKcoe5ZfrQlgY5jscmEJQW15bfAIA1WsL5xsVRLbZF8XmHI/5vzdtwsOrV6NjixbYc/fd6PDGG/UDgA2dU43olxgMhwMp//43DpaXI1KvR+6gQW73ZLX8qAHA0zYb4mQ352sjI/GFyrglYsMGsRa2MBiQx0s7DSWY1ndhL74omtM7Lg7bmQ1SUfpULsBC8a5PiZZlPuXNN0WYEF5Q5j4q6TG+kNptmy764xUrWW/npy8fc1P2XJy/m6CZF6poZg5cAADBpAA7MXgwrT2sCAoKwsyZMzFixAjx+2effYZ33pFc/wgCbtu2DcGKGZmPg8N6X3hBcvfr1asXHnvsMWFheOTIEbz00kuiHSSWe+655zRrdzgcuOiii7CeGzOA8ePH484770RERAQI6D377LPIyckRAOI333zj1qKQFo59+vQRFohGoxEPPfQQxo4dK+rke//+979BK8Po6Ghs3769yWMEnIsFaPp0gGcC6i5q6z8txrpaAHoLAJaWpsLhoLIbhNBQOcig6gNW619hs/1L/MVoHI3AwJW1Pq9YAfLsMHEi8MYbPgpVMxenq+fXX0tWlDwrEGTjZRx1MDVYyX5Q/+L/BDTN5rMWcUoTIyMXIDDwJvGrK2BmMMSiuFjapGNi1sPff3CdnuXm3ojycuk2keTnNxyxsT/XgI6KdSL1Qu7lbJ8yVdkunnkIuBIIJjionsZHjz6JjAzJIq5Xr18QEtJf9EXdp9zc2nEOo6NXISBAUqw9AYAsQ3CU+iy/26JFNfbtS4TNliXcSlNTD4hvETylJZsSnom8zshIgc12EGZzAgYMyKgV2Fv9DjEPeldo0aefjsOhQ9+gR49JuPrq+V5boNUnXsRaCJrR0/Lqq8m3ZhZGl+rVskm93TXmuDetoWs4+6El0w5HGdavl5LIRERcgW7dlvsEAPI9d+PjLQDIOhrD58byaMWKe7B1qwQ6P33tQozI+RWJmZtR4R+GvMizQd7nHFmNz09KsYjm9L4THYPlYJWqQbhrxzs4WJKFAIMZK4bMrHlCHs387T38VnkSwSY/5D3+6NmYai6DOPrjj7HqyBH4GQxC+a65PVcGUnb3EYe3+iaEql66zTF2D4lxyd658kq3onPH0qU1cc2O3ncfkt2AOpoVNGYgvRHmxpRppKCUpacjaN480YIrgoKw3NW1CRCWa5/n5iLUYMDpQYNEAhBSmcOBIFmfuSIiAsu1Er3UN5kA/OXLL2vcf3+eNAnDXa1D3U2kRvS7zGZD0PPSnnFFUhKWMx4CFxICCHY7nsjOxovcMAGsj4nBYDeWSHa6yKWni4QHDH6vRLK6IiAAy2mqrt44IiMRtGuXSPihkBYAyGdRGzcij0kCAgOxl7EwlcWIACBBSipGdAEmUO5u43CRqVp9dgXhmbShuhqJr70mLDEZgJ/Wfe5IOUgnBAcLSxh1orRGLXqNmQdN8W5TyZQGf71t3r6cHHT9r3S5eE9qKt5wtYyqby1S2k+XFALYlGFXhU+jIVoAoJjPnIuKIsW5QdlV3HhVN3YnnE50KSkRFrA/BQZin8OBe1ziDV5hNGI5FTgCWqyHSp/RCOECLIM5PlsAuq4t7Cvr9UWxOYdjfqKwUFjYMtGFYgnPi7F6LQDdrX+eBKoR/RJV0015wQJsKy0F3XxL6rHKdwcAqveHsRERWKbaH4LWrRNrYV8/P2zleLnZ86NeflkkyukaHY29VFbVSh/bqSjeXugMdLum9TLjAJfMPKvHeGKl8nz5oUMYK18cMRbgo4PrnnWae/07F+dvb/lxodz548AFABB0YRuGdevWCSBs7dq1GMhbABW9/PLLAqwj/f3vf8c//vEPn0fs0KFDwi2XoFrfvn3FdwKUgKYCHCjH8OHDBcDIdhw4cEDT2vD999/H7bzBADB9+nTMlg8uSoN+++03AezRkpHWiqyH9bnSxIkT8ZEcwHXhwoW4jrfAKuLfbpDNmydNmoT58+tmu/SZCaoXzsUCxEs8hh1R9BdXS2t1+xsCAPr5zURpKd1U7TAY+iIoqK5FZmnpSDgckmWLyXQHLBYJTFZIiQXItjHBg+y50BjWNum7xL737AEYWom6GvVBGiu4xs8jnwmu8R8vjAFXAFCHpKQi6PWSD3Zl5S6cPi0hRnQBpiVdaem74vf4+MMwmWqnca2utiEjg7H3KqDT+Yv/ATOSkophs+WgoMABgohOp7/wcCLIxnYo5xq2j+cdAlYEi3gGUp95FPdfvT4QQ4YUCitFYgr0kFL6lJlZGwAMDX0aYWGSG6c3AKASC5D6q9l8FMePSwGJFYtDJa4fz3z8mTJBXlut05CTM1eU7dfvKAICJMtKiY9SfEO+w7Ocxrkb+/YtxKJFNyAgIAL33HMQFktkkwCASrgS6mP0IrvzziYVPY+VqWXT29h/rpVu3y65hmvJdFXVGWzcKCWVaNFiHLp2XeozAOhufHwBABvD58byaPPmN/Dtt/cJHjyVOgPjoENMzl5kxfWGzS+khp2KBSBnyLLBTyDQKAerlEukl+fhtm3/haPaKcBBgoQKlVoduGrLv0SMwIFRbbFx+i1ux/75devwJAO7Avhx4kQRr0eQMpCc6NIi4n5CuNS+IT0dQ2Tw6qmhQ/FsPcFYn/rhBzwng1UfXH21cI31mhozkF5/pIEFGykoZzZtQgsGVQcwLjwcS7kgqMjmdCJ0wwYR709txUFrTmYG7s7x47stWmCpu0zLbiZTSWUlYl99VXK5DQsDgdlaYJLSDi3+N6LfZ6xWYTkq2h0Tg6W8VeJCQmCzshJ35ubiXdkk/XB8PNq5MU8+WFWFFFlu1W6P4wICsJQLu3rjCAxEn1OnsEPJIubGArCYLmayBeCEyEgsotWMwj82mFZPvOEiOENLTK2NQ0OUavW5QwcsvUm60FPoaEEB2s6aJX6d1qcP5siXylpSOW3ZMpEhmFQHTP89zxVPU6ypZEqDv54+rTz/248/4lmGRADw5uWXY4arF099/FXav2qVFPtPHey5ngZoAYBiPvM2VlGkCKxRnjkvqKipPJ3GlJWJ7MK3mkz40GKBYg2o/uQ4oxFLqUApICLPNg4H5vv7Y4qcCbdBAKB6baFyyPb5oticwzEfs2CByL57a/fu+PCaawR7vAIAGzKnGtEvtuvgmjXoumYNeMnRNzAQW3kR4YbcAYDvnTqFO+SLvUcSE/GyKs5Ln+3bxVrYQq9HHtcwDSWYmdhDZcMbhrFYxPfVSh/b40mJltvMRGEE1pXwBlsboPTSNX/CwoWixlcvuwwPueAN4kFDxsrbxQEXkoD4wKr/6aJ/egBwy5Yt6M+bAyos06Zhzpw5dQacrrtdu3YVYFpYWJiwsDP56GtGsO6/8o3cpk2bMMA1AxDN9n/5pQZ81AL32LDOnTuLdtDij1Z8WnEJaWVIK0KSFrhHl9+EhASRgXTUqFH4lrErNGj06NFYtWqVsCbMzMxErEucmcbMjOYGAOlxwP2b6ygvHT0lBvAVANTr+6K6OgPV1VIikICAj2E2/0X87HTmwek8DJvtXVRVvV/DpsDAX2A0SrKmkJIRmHoR20ig7feSkIk6EfdNeoJQt+IlGS9y+Xdaqan7QOs6xVCB/VADYixnNCYjIeEoysoWoKjoeVRVSS5fJJ0uBGZzD1RWSgprbOw2+PnVDo5bWbkVp08rrujmmizBinuxVJMZOt0wBAY+hYCAi4TuyjMZSbH+U8A85Zmif27cGAXGfQsM7IG+fXcJ/VLpE89KBBRPnHDNdMzkMQECeDSZusNqlWJAEtB0jQHIvysZgSU8/hvk5krupW3bvobExAdqMqNSL2Y72UbqodXVr+HIkYdE2a5dl6NFi7NxTpRkaAQLaTVIYw413l9RUYjZszuhtPQ0xo17B717S2EBfAGgVOJa60d+m55e5A29GJ54QgItzwWpZZPn2NRU37/KcwixHC2ZZm15eV9h377xouKkpMfQps2LPgOA7sbHF/43lM9NwaPycsaIbYvKymJ0DUnCx4kDEGArQ1bCWYYfLjmFGTvfE4lALo3uhqc6STyrcFQhr7IYG/MP4bOMDSiokqKbMRPwyJizANHR0hzcvl2yVpmQ0B+fTR7tNlTDVwcOYLysPM++4gpM58CrB5KLFBdTdxNCQ0x2nz6Nnm8zy7YbaxnVO+pYgY8PHowXGGTWW2roQHpbf0PLNVZQ7HZ8tWQJxu+TskQ/lpSEF3n7pqKtxcXoJ3s4/F+rVnggMRFPHz8uElYUqtz8Wvn5YX5KCi5Sp0pX6nEzmebt3Inbli4Vpf42bJiIwaRJrvx/8EGAQdu5wTVgEVHLougzNz7KH/tTXo4Hi4vxumwBuC02Fn1Ui2O504lMhwPLrFa8VFSEbJVFn9L2x0JC8CItTNUbh8WCd0wmTFViXboBAB89cgSvyDHRvuveHZcq9dBCUQlzw3p5YNbaONzIUq0+DxqEF0eOrFVS7SL82qhReEBDz1VeeG3TJjwkg8Z056dbfw39XueKpznWyLnkib/1fZ4WTofz8/Hujh2Yt2uXsCilm+Lhe+9FmKv1qTv+Ku2nSz7d9Smzrgqfm0ZoAYCPJSbiRbpkKMoh5Vyx3lPNh89sNtxktSJcp8NBJjXR63FVWRmWurgAP2Y240UaTrD9tCKUY7rMNxoxRQbFUwICapIMMYYotTZeNIQYDOhosYi5cHd8PBLUyorr2kJ+cQ3yRrE5h2P+2a+/4qbFixHu74+D99yDKIKh3gKAvs6pBvaLFzGMh7csLQ0vrVmDbPkS5OOUFPyF640X8nNjVJTYRxgv9s2sLFTJiUQOpKaijcpw5p1TpzBVBgf/GxeHu2j576IEP7p6NV6RXYi/u/lmXMo1UK30eVCia/pz6JBIYJQtJ3ViJuC/uFx0eVoe+Pz+lSsxi/F9AKy4+WZcrl731HtdMyrXzX3+9oYPF8qcfw786QHAJ598Es/LbhwE4BQw0HVo1KAaQbHL1DE1PIyjcItITERWVhZSUlIEgOeO+PzgwYMCoCPAp77JphVhRzmY71133VUDKLrWRYCP8ftIN910ExYsWFCrCBOQEOwk0cVZsfRzrYfP+D6JcQkZv7CpqLkXIOK4BCRosebJ/Zd9qg8AtNnmw2qVsnhqkZ/fE7DbN8HhOJvVyrWcTtcGISFHNN9X3IB58UjA7a67morLjauHMXJpGMNQkwSVyEvFVVKdG4ZnHsZb5LmC5QhcuQKAZnMq/PwGoqREsg6oj8LDX0VIiAR4KVRa+gHy8yd7elV+rkNAwPOIjn4cCmattI9gHttI0IrPqOc5nRVYty5AvBsRMQbdun0jznGufaoLAGo3x2K5CVFRteecUlLRg3W6OThz5m7x586dv0BU1LXiZ+ol1C+ok1C3pRWj07kI+/dLFrrt289BfLw0dxVS6zIM9aQ+Oy9bNhU7dryDpKTBmDKFCU4kENMXAKo+ph88KI07cZgpU6RkJOeC1LLJeeMhdrNmkwhq84yjJdPMmLxzJ+VVUtR692bohz4+A4DKmCpnKGV8fOV/Q/jcFDxi+w8eXIovF90Im92Kzn4huDmyM8Kju8DqsOHXonQsPLkJ5Q4b2gfF4bKY7ph9ZJVbEbg5aTDuSL6k1r625cxveHzvJ+Kdu9qMxPPjBtWSYXVldL2hCw7picGD8TwBONeB5ORxZXg9Qkm3xvAXX0SV04nuMTHYXc8C3P2//8VeOV6bZjZiT8LfkIH0VGdjnzdSUJwFBRg4bx62yMHYt/XujT4uYVI+OH0ak9l3elG0aoUFOTk4rMoYqu4CV6jnk5PxuHJ742GxY1D1n+UEZgQ7aiWUcOWNmv8Er+jmyA3Ox0WEmS4Zw26LHJxe9FmJNULZKy7G3KoqTJNBiVfDwxGh12OKnCjFmyGrBRqqbtccTA6SllaTHXOYnAU4zs8P6RUV4tC8RP7OUy1b4lnFSpYfpaULNwzOER6kuVnzNs9149BoYJ0+33kn+tDSVkVztm3D3culTN6eEuUwS+h1X3whys4ZMwbTXK2Dfo9zxdPANWIuecNf189fNH8+1vCbGkTw76sbbsAQrXkkLex1N2+l/Ux2xOy4VISoJHmRDFALANzWtSv6cF3g3KDuQQWM84NKuWxEUVBdjU4lJciursbbAQGYajZjt8OBPqWlNe7wSve2BQWhjxLoWAES9XopCYib9USLNww/8HrbtiLreA2pFSmC+WyrN4rNORrzAqtVhKogAOWaQdYrC0B3Y+5Opn3o1/xdu0QCDHf0RGQknuvcWdsyW37p2n37RPZ3LbLo9fgoJQXjmVxKRQR2bzt4EB9mZ4sM6bfFxuLK1FTExcaKWL0f7dkDJu4gCet+uopoKX0uSvT848fr78/gwSJ7uaaleT1rxKmSEnR8802RsZmZu9MffBD+7gLTN+P619znb0/L5IXnvw8O/OkBQMX9NzAwEIWFhZrushwqWu0NYgBTxkJ6+mn83/9Jrn/e0NGjR0WsP5I7K0OlHj4nQEfie8kq5U3t/vvpp5/ixhtvdPt5AoUEDFu2bAlmN1aT2v331KlTbi37+IyZhUl854MPPvCmu16Vae4F6JZbABoFUPegnuEpgXNDAEC9vicCAubCaExFaelF9QKAFstSmEySxZcrUbenLsMzE8NPffyxVyxs9kK8NFuxQrKSoj7EsEG0iqMuqD7fERhk+BX+zzMFL1ZdAUDFbddgiENY2Mswmbri9Omeog96faSwmlTIYEhAXNwuGAxnM6IUF7+GgoLaoCDLh4W9ALP5AZSWFsNqXYzq6icASIHXIyOXIDFRCgavtI97LS+Ved5jMjL+b7PlYtOmaFEuKuoGdO78meiLa5/S0wMREHAlrNblIqmJ0dgWERH/RUXFGpSUzK7JTsyM0YmJBO+lBAlqou5LPVWnexmFhVJYgW7dViIiYrT4mfJKbzDKLGWC089mW4lff5Ws/tq0eQVJSQ/XqpPv8LxHPZ+XiXJsfZw4sQ7z5w+HXm/AtGk7ER19NquyrwCUO2FjW5lIjZeuDDOk5c3QHIKqlk322eUc6tUnMzKktmvJdEbGqzh69BFZjsajS5fF4mdfkoAojdAaH1/53xA+NwWPaubk3k+xeeNLWHFasixRU7gpEDe3HIKxcX3wc+4+vHiw7kGgXVAsHm4/FikhKtNhuRK+83/7F4nfHmg3Bg8N61sjw64DeSA3F53fekv8uSa2letA8qHWhKhHKpTYgiyyYPx43KQRh+7TvXtx85dnM72P7dABy1xcID0KXkMG0mOljSzQSEF5dcUKPCInJBsfFobFGm7Rr508iYeY3ZBZ4fV64Qo8OjwcHQMC8B/Z/bVnYCCOVVSgSM6Iu6RLF1zlmhXLZTKlh4QI9zfK5KCkJGy47bb6maHmPxdKyg43OB8XkVc3bsQjBA8Zh7lVKyzm4suFhJsfQZOiImSYzWiTmws7kwgZDHg8JAT3yQlC1I0M1ulQQkBOReMtFixWH3aVjUPeuOZbrZgiA6paHR4RFoYnW7aULP/URABQSfqmPHPdONxwsFafO3UCA9i70ssbNuCx76WQJyv/8heMridp3srDh3GFfDn9ysiReFjWr2vq/D3OFU9TrRFzyRv+un7eHQB4X79++Nvw4bUyqddpuhZ/lfYTxKVMUl5dFT43PHAFAMdHRmIx3VkURYrAHZUvyjIVMRn4uKO8HO9VVWGgwYANgYGwARhSVoZt8jqgfK6lTocTalceJZEIYwBWVeEZpxPjw8NhNZnwVV4eOAdiTCbsLivDj4WFdfYt1vt2+/aYqigP6rWFc4OgpTeKzTkacyX+7MDERLHOqcEnrwFAX+aUD/1yBwByTZ/LTNHksYfY+e4AQFoDvtSmDZLqyea8KD0dz2VmYietQl1oROvWeHLoUFxKq3R3Sp/LvjI/P18TAOwZG4u5Y8ciVe0C5WlNkJ/TEOiqzz7DMtlicdbo0bhX9j7UrMKXsfKyDUqx5j5/+9icC8XPEwf+9ABgVFQUmFW3R48e2CVnqNMai4KCAuF2S2K8PLrWektMqjFunAT+vPbaa3jggQfcvsrnTMhBYtZhZvtV6JFHHsGrr74qfmXCkJ68tXVDV111FZYuXSo2iZKSEhDgVIgxCJnYIzQ0VICe9RHLMJ5gamoq6C7dVNTcCxAv7ujFQF2coBTdKuuj+gDA6upCOJ0n4XRmorxcAmp0upaork6HXt8W/v6vw2DogupqurhVCyDIan0UTudmuWwigoK2gcCQFnHPIijE/Y3nziZkc6OGa/Fi6WxEzy3u3bwQ5tnBNf4f/07AjMYOtFiTQLa6SUB0Ogvi4nbAZOpY67nFcguqqvaiqmp3TXuNxg4ID38J/v4joNOZkZ9/P8rKJGBcTS1afASd7hbBP461ybQeFRXD6YgNo7ET2rffJ+aA0j7KAsuynTxL8YxVUZGBzZslX+GYmFuRkvKh6Ktrn5zOQjD778mTLeFwZAgAMCFByhZd20UZCA//D0JCpNhpalLCOTmdz6Ck5GnxqHv3HxAefrFcD0DvLgWo5PmpvPxH7NlziXjeuvUzaNXqr7XqVMLXcFx4lqPXisNhw5w5PZCXl4ZBgx7FyJFSrCqFfAWg3AkS9SaG7+LFKnXl8ZL3Z7OTWjYZ+qUheZmYFZpndleZLixcgz17LkV1tR0mUzT69t0Ls1kCiBsCAGqNj6/8bwifm4JH7DNlae+iG7Hmt29RaLdqji3j+t3achh6hLVCbmWxJMuOKmRVFAhQkBmC4/3DcU+70RjYokOtOlZn78bzaUvE3x5scyXu7NtLyLAWqWOM3d6rF97ljYnrQPJFAh3qCeFBIpk1c+i8eSK2j0mvx9PDh4v4fnFBQThVWooPd+/GP9esEWuJTT6YXpKcjO+ZuckXashA+lJ/Q8o2QlDWHD+OSz/8UMR4itbrsbdXL0RLQWBr0bMnTuBvspUeH4wMD8cTSUkYtXev9K7JJBJVHLJaMXzXLjDFRSeLBfv69q1tZeEymZ7Ly8NTckxITSsy14ao+a8AEtzgfFhERJ8/+kjISjQTbFx8MaJpFcqFhIoGb/TkzfDe4mK8KVtGtjUYcF9ICPqZzQIU/KmiQjzLcXH/DdHpcDghAdHqlO7KxiFvXM+Vl+MpFT9du0mQ9eoWLfBK27a1XR15qFQAQIKr/LYX86ROn+++W/TdlZ5ZswZP//yz+PMPEyfiYrX1oUvhH48dwyUffij++syIEfjrsGG1S/we54qn+dXAueQtf10/f6ygQCSDILhQWFEhkhMwA/ORggLhUv3uuHGI0ZiPoh4t/irtp2s2wWyCd64KnxsefJaTg5tk7ybK34n+/RFNJUpRpCjPvNWkwivH/1trt+OisjKR/GZ7UBC6Gwy4s7y8Jnam+lPXG434XC1zqjiARU4nQsLDoQsLQ1F4uHD3VQNkzDTOEAV0JfXT6YRLMOcgLcuO9O+PWLZHvbZQMSQA6I1icw7GfO2JEyDYa9DrsX3qVGGpriavAUBf5pQP/aLsnZRDC1irqoT8LfzlF3yVmYm2RqOwthzrIYTUL8XFGCiHibg8PBxXRkaCLr6M8TckJATvd+yI9hqWHAfKyvD4kSNYWVAgxrTOWmg04uqUFPCSIYFhEbSUPpd9pTA5uW5/9u3DV2lpaBsejtdHjwYvAH2hf61di7/+9JN4haAkdQe9KgN2nbp8GStfGnIhBqCP3PrfLf6nBgArKipqEnGMGTNGZL+tj5ghuKysTMTvo0Wgt8S4gnffLbn7ffHFF7j2WsndT4sWLVpUk5CD7ymuuixLi7/PP5eyoDJ7b6Tr7biqwnvuuacmQUhaWlqN6zCLMJZfdna2SEryK1GyeoixD/ft2yfeoUWgt0SArz5iXf3kwMR0daaLdFMSL3vYBMWyThVrWPMzvsYANJkmwWi8BFbrJMKBCAh4D2az5KJaUfE8KiuflL8TKizSdLokBAVthF5ft5/UYxRLRRolyIYSTcmOBtVFTzuGoaChAXVIDj8Na+jmqd63eKZg+wmsEVST4jzXBQCDg+9DRMR/RFtck2ZYLNchN1fKQu0LRUUtgcNxldDdFG8Vm+06VFVJFkWtWu2G2dy9pn28QKaeQiCQP1O31bIAZF9ZTt0npV0ZGTFwOhkHtCvi4/fW6Q//YDS2Q0LC4Tpd4aU69WGn82WUlNS1AORzTkk5tA0YD//MmfotAPkOjXx5Uc+LSeqsCsAUGtoS06fvh9lc+7DmKwDlbkwou/QWYmQCgu53SCEGm53Usslzo6f5rdUgApeUXbVMl5Xtw65dQ2G3F0Cv90e3bqsQFnb2YNoQALC+8WG7Jk36Ca1bX1QvzxrC56bgkc1Whk8+uRzp6etggA53hCRiUIexiAtoAZvTjgPFJ/HhibXYW5wuYi3d1eYyXJ9UO4kWO0aQ74W0JWBEpkc7XonRsWcvr9QWgHcnjcEdPfsKGdYiTQtA14Hki64TwguJfH/nTkz75hsB7GhRgNGIl0eOxD0rpUzuPFTQxc4nashA+vSBBhRuoKAw0yhB04KKCvjrdFgVHY1hXAg0DjWvZGTgUVWGqy86dcLUw4dRYLcLi8BV3bphmBy74Lp9+7BIdgXb3acPuqsBDJfJ1GnTJjCLM7NCn37kkbqxzlzZoeY/F3duBNzgvFxEavXZaMSqW27BMLZVb8IMvQAAIABJREFUWUhouk3wT944mAN4fG4uVtTjnkjrQMYDVOhfoaF40jUGorJxBARgndGIUZmZsMpWg3fGxuKZ5GREGI0i3tbSvDwBtp6x2xFvNmN19+7oogAndFnm5sYxkja/2huHhvho9tlNrIcmtQD8Pc4VT9OrAXPJF/56+jyfV9jtwrWa8RiTQkKw8fbbkagVBFuLv0r7CVRw3hEAdFX4tGSkrAyDd+6ssd4dFR6ObxkfTa1IcZOmvBHM9vMD50aP0lIcdDrxsNmMVwIC8HxFBZ6U42aqM2KLfdJkwnw1AKSEepATgYi4EYpSp9FG9SXEJWFh+EE2fni2dWs8xT6q1xZarFGp9UaxaeYxr7Tb0WPOHBzMz8fDAwfiFY3wU14DgL7MqQb0qxbbt2/HR3v3YtKJE0I3eK9jR0yuBwTUSgJCoHbG4cN4+9QphBuN+KlHD/RQ7QfrCgsx7tdfhdy1MhjwbGIiRnbsiIh+/YSr9NKDB/G3n34CkxfFBwdjde/eItN0nYOMlpKmIUMf7d6NSUuWCHD5vSuvxOR6jHDUr3+yZw9u/eorYYWaHBYm5mSsO2BeedGXsfJmYVCVaW4DHB+bc6H4eeLAnxoAJIgWzSxrgIiDx5h39VFMTIxIAEJQbC+zNXhJ6izCK1euBJNruCM+V6z+XnnlFTz88Fl3P4KUK+iTCeqXVvjXYxL9+OOP4yU5Qx0zCzMzsEK0BmTWYcY7ZNzD+ohlaPlH8JOWhN6SL7ERmgMA5H5OnVxx9/TU7oYAgBbLfJSX34CqKlqDBiI4OB1VVV+gokIK4qfXpyAgYAnKyniaLYfJdBMsFu3YcASFeHagTu4mpIunLjT5c+as4dma5zaek6jL0SPEVffnmUI58yjnFi0AMCrqG1gsY0Q7XQHAFi3mID2dGYLtAjzT6YJki0DJNap2sg9/qrni7zExa2CzDRN6pQIAVle/i/JyKctodPS7CAm5vVb7qPexP7Qao56nFQNQATVZJ0FNNaWnBwlrT7N5AOLipIsArf4mJGTCaKwdI4ll+f3q6jkoLq4bA5DP1UsLLUJzc+uPAch3KDP0WqH8JCenCes/Wm7deOPX6Njxyjqy0VQAICsmAMgIBwRt5HuOJpdF1wrVsulqOOLtx+m1qJZpq/UYdu0aApuNmWQNwu03MlJyIVeoIQCg6/gQKG0I/33lc1PwaPXqR7Fp0yui+/9oOQy36g1Ib1XbUoeZfR/d8xF2Fh6HHjq83Wcq6PLrSnTzJdjnrzfh8wEPIsQkxd1UxwCcHD8S03sOcpvURTMGoOtAajHcS6HYceoUnl27FquPHBGWNSSjXi+saV689FIUVVRgwHvvib9P6dkT719VWz68+oyvA+lVpY0o1ABBoeURMydnlZTAoNNhcevWuIqHKDfA0NtZWbiL/vaMs2o0CtAvy2YTlj+LXVx93z11CnfKblLvduiA29Xp2lVjuyUgAP03bhR1Xte5MxZeJ8VJ9UgK/7lpERjjBufFIlKnz9dfj6tSUqQYgspCQjDCZTNkbLf3S0sxu6QEu2mtJTeQFpPXWSz4srwcp1Sg87KoKIzVillSWIhKf3+0zcurBRjO0zhY7ysrQ98dO4SrdZ+gIGxT9D9u1ooFIPlKGVc2Do1MSm777IbJTRoDkN/4vc0VT8Ll41zylb+ePq88Z0KQVq+/LjJj1xur1JW/SvuZQZhzQ0vhc2nEMasVQ3btEvNZoUkxMSKZj1DCeW5QkjMpAKC/P56uqMAzlZVI0ulwIDgYH9tsuIvluOYKTbA21QEA+Zjl1QAgQRU37pk5NhtiN20S8294aCjWFhWJn2mNTJBckFqRImjvjWLTzGP+9E8/4Zm1awWYe2DGDARquDN5DQD6Mqd87Fcd2ZTXxRsOHsTC8nIE6vVIHzAAEW4SaLrLAswM8u22bEFGZSUGEtDu1Ut8qtLpRNvNm5HJcTWbsTM6GrG03OS6plrLCLD3fecdAYz3CQnBNo6pllyrx76erHI3LFqEhfv2IdBkEjH8IlRJSbTm5/JDh3DN55+LGMME/dZPmYK2sjehx/ncTOvfBQDQI+f/FAX+1AAggSfGyCPdeuut+FB2R3A38izLdxjP7zdVFjZPkvLMM8+IuIGkH374ARdfLLn7adGPP/6ISy6R3P343l//etbdj3/nc5LD4RDZed0Rv8f3SevWrcMQ+ufJZDAYRAbgoUOHYi0XmHpIiZHId+wuGbnqe+98A4A0KGSm9+YGAG22BbBapey/JtMMVFUxm6UTOl0rBAWtFxZ/ZWWXwW5nvCALQkIKNWPDEQCkHkPLfg/Gk57Ercmev/mm5P7LfZE6B884bKdrTGmeKajj8eJWAcu0ALG4OMkaj+QKADJr7smTcXA4TsNo7IiEhDQ4nSVwOLJB12GbbUdN1lyCg9XVpaKexMRclJVF1gIAdbpVKC2VQPYWLZ5HePgTtdrHPtC7hQCgoitu2BAJuz2/JguwVp+keVeAkyelUAC0WoyKkkIBaPU3NnYL/PzqpqclAKjTfYPCwtpZgJWBcwUAT550nwVYeYdeDeQ9dZ/s7GnYsWMuwsPb4OKL/6UpD/v3L8KBA1Jcu2HD/oaoqM7i5w4dxtWxFvQkUDwrtG4NUC+75x5PpZvmuVo2VUubT5XT1V6R6ZiYLGH5V1FxVFj0duw4H7Gxdd07GwMAEhzn+NDwuSEAoK98biyP6Fb28suRsFrPICEwGkvbj0VY0Qmktzy7l9TIbFE67ts1T/x6bUJ/zGhX95Lr++y9+FeaFEPvqZTxuDSmm/j5WFkObtsmZQEeG9kff0sdLXikRZpZgNUDqU77rUwId5XVIy20AmTAbrr7JoSE1ATq/li+yeermnHLvJFAXwfSmzobU8ZHQSHoR8s/umPTsmN+9+6YSF1Ea3OQ27UiPx9jZG8DM92oq6uldzt2xEQXq5BVZ85gtLwIMhnIE64bDjeksDDcc+YMZnPhA0QsRq9dshT+08SbFkOsz8MiUqfPV18tXMQFqeWPbo6um6FqbEqcTmQ7HLDodCAwODwnB0dd9Ko5ERGYphXToKgIX1dX42ryWUVaACAf33nwIN6Vwb5dffpIljNqAJB8p+Whm3lSb5/dyFuTZQFW6v+9zRVP88yHudQQ/nr6vPr5ZR99hO+OHoXFZELh44/DpHYpd8dfpf2M/UIQup45zSqyKisxdNcuHK2oEPNZAbdrAEC1IkWrUxUA6FdUJOL9TTGZQP+E2TI4zlMNbbBZH6+IyuW2DjMYcLfZLEINXKwkTlADgJRjtVKnwayojRuRV1WFzhYLcqqqan7epwA+akWKCq03ik0zj7nfs8+KfYgXTpfJseRdu3bvypUg6MvEL29cfrl4TBd9TRd8b+eUD/3SlEt5XVyQmYm/MKYOgE9SUnCzm0zA7gBAvsdMv3QHJp0cMECENfg6Lw9Xy5nn/8U4f5QvN2vZnUuX4l3ZvXhXx47oQTl0s6/UKGluJtuCvXvxFzkW8Cfjx+NmjXjByqtMTnX5J58I8JGZm3+ePLmO+3a9c9rbsfJlYbjgAuwjt/53i/+pAcALFoDNZwF4vl2Az5UFYFXVdygvv0xeISTVRaeLQ2DgOhgMUuKX8vK/oKpKsvwLDs6CXi9laFbTn8ECkPH/zGbp9k4LAMzIiIbTmQuTqQvi42u7ptvtJ5CZ2VpmmeQcYjS2QULCEeGqq7YA1OlWoLRUsjSMjHwZYWGP1GsByHK7dg1DUdE66PWBGDKkEKdOGWsurtUWgJWVm3D6tJQMKDT0aYSFScmAfAUATaajyMuT5CMubho6dJhTIw6uAOChQ9Nw6pQU/7Bfv6MICEiuIz/qy8vMzMnYvbthCXvuv/8YwsIUPnu38TXTJWW9H2/s5TQrVwx3GAM2P384ysv3i2+2a/cmEhJmaH6/MQCg2tCmIQCgr3xuLI9KS0/j1VeltWpoXB+8FtsT4QVH61gA8jndgUetk8DmfuHt8GJ36VJETdvOHMGje6UMR3ckX4y/tBwqfq5yOjB63b/gRDV6BbfF20NvcWsB+Py6dXhSvgT7ceJEjGCMsSa0APQk8Q9++y1e3yzFdl07eTKGNiTtta8D6alRjX3ug6DwkDl8/nzslw90b15+OWbw4OXOPFxu24mKCrSW+aY098127TBDw1pHDRa+3KYNHlGyGikvnjiBqrAwxO3bh/yqKnHQzXzoIWGp6RX5aAGo2Wc1qOzBAlCrTXkOB4ZnZ2O/bGV61qYdeC4sDDNdzc5ZSWEhXnA4MFPOLKzU6w4AnJOVhbtlq8vPOnXCDfR28dIC0GOf3TBaHaNzWp8+mDPWfViPacuWYe6OHaKmo/fdh2TXhCVikp0H83KvhMhNIS/nUkP560vTCFIQrCBlPfQQ4rRA5UZYABJIY7zO/Yx5CeD/WrXC32X3FW8sAHUuQLa3fRtuMOBnxX3SBwtA1h+9cSNyZQCQ/ys/1wCAzWgB2NAx1/mQcFLNw+GtWgnAqQ55O6e8lGW34yavi99lZeEyWmMAeC45GTPdZKWuDwB86tgxPCdf9mzs2RMDQ0PxQno6Zh47Jupd2a0bRvPixY01s9oy+bPWrSECd7ju3V5aAH535AgukzM1PnfxxZg5VNJjXIkZ4hnjtNRmQ5DZjO9vvRX9fQ115e1YeTt55HIXLAB9ZNj/aPE/NQB4IQZg88UA9DRfmnsBOhcxAOkCbLPNh9U6paa7Ol0LBAauEUlBFFJnCA4JKRburGr6s8QAjIxchMDACaLrrgBgRMQsZGSEiTtkf//LEBOzqo4InTzZCg6HZPFBCgmZifDw52oMLhQXYKfzDVitUgKO2NgFCA6+qd4YgCx39OiTyMh4XrzTq9cvKCvrrxkDsKjoBRQWzhTloqNXISBAAn+1XYBPwmisnfVUCeXk71+NvLxEOBxZsFhSkJp6QNSjFQNw27ZOKC9Pg9mcgAEDmF2Yd+NnyTV8SXr6uQMAmzFMSb1LSGPD07ByurdnZBThwIGLhYUpKTn5BbRs+bjbbzcEAPyjxgAsL8/Dyy9HCV4MjO2NWfF9EZl/EMfpAqyrDbaU2ysxZsMLUtmIDniu2011ePjt6V01GYLvbTca4xP615SZsfM97C8+CYveDz9e/ij69yXIX5eUbL2M+Zb76KMIpilvE8UArFfgeOXgdKLNrFlILyoS7ljH7r9fBGX3ic7XhKmvkV5OJro/X/zhh6CbNOmFSy7B47Sc0wqm6fK9IrsdtL5hEH6SpmWf/M4bmZm4T/awWNCpE26Sw7TULJAnTmCJwYBr5JiCD/Tvj9fqCatSqyk+xgB022d1per+u8QA1IqHyIQFF2dnY4fsMnl7YCDeK2MCMYlmhYfjXteYbfLG8YrTiUddQrG4AwDVfFzUuTMm0D3OixiAXvXZjTzRajjxtdeEa3hKZKRwWXRHnWbPFvEbE4KDkfHgg3X2NZGg5HwEmPVpQrsU9mIuNYa/vjRNnSG4+IknpLVSTY2IAcj5fPHu3SJBg1gLkpMFwJwsg/w1AGA9MQB1ctIIX/rEsjUAoI8xAHNtNsTILsDDQkOxTnYBvjQsDN/RmrcZYwA2ZsybFAD0ZU55Icv1jp28Ls4/cQJTGGiZa1u7drjXjYt2fQDg5LQ0fCCDiHv69EG3oCCo48ou69IFYymL6kDYqsa9sXkz7vv2W/GXRcnJmEA+qGNbehkDkO+rMx67y+S7JztbJG0R8XGNRpER/SJak/pCvoyVL/VesAD0kVv/u8X/1AAgh5WJNPLz8y9kAXYj4xeyAJ9ljNN5HCUlkvUVk4AQACwtHQSHQ0kIE4igIIJ/Z+MtMntwSQktvWzCLTgk5HgdTv9ZsgAHBv4FkZGSBZArAMhsv/n50m1laOgzCAurnemWf8/PfxClpa/L/DMiPv4QTKZk8OykZAFmWMzKyhGw26VMhO3bp8NkSqo3CzDLFRdvwc6dEiBBi7zw8Dl1sgBXVztx6lRXVFUdENmAExNzaty5XQFAdYZg9YCrkzmWl09HQYHk+tir1yaEhAwQbtTqLMAxMb9g3z4pqUJ8/HS0bz+7jvxoZZn1tGU1xAJNq85mTFRWbxd8SFDntp49e8rx3XeXobR0gyjTsuVTSE5+tt7vNgQA/KNmAaa8v/hiOCorixHuH4Gvu9+CpOzdyIrrA5tf7UuMTfmH8OSvnwreXZPQD/e1k9yQ1PTE3gXYfEaKA/daj0noqbI0/fjYBryX/r149sqACXh4VNc67zPLIGMdMTA4Y/Itv/lmqUwTZAH2NF/4fO727SJJCOnZESPwlBdx4+rUe74mTH0d9GIyMZYYXQo3ZGSImp4aOhTPKqFM3KXTlr9Z7nDgsj17sEF14P+ue3dcqmXxxQyJu3bhZ9k6KL1/fySpYx3Lk2l8cTG+YhwnADunTUNPDxkma7rvQxbgevus5qe6/y5ZgEVcDxWVO524LCcHG+REB08GB2ONzVbzO4v+FBODi1zjO8sbx2KDAdcyMYOK3AGA1+7bh8VyMpXtvXujNy3APGQB9rrP9cjT9OXLRSZa0qbbb8cADasXZt0eKMfSnN63L2aPkSz2a9Hvca54Wig8zKWm4K+nJvA518q2s2YJ19FWoaE4/sAD3vHXiyzArvP5qZYt8WxyMjQBHFoKu8kCvJFzoawMhL7VCT+e8vPDs7L8JxYVIVNueZ0YgKoswAK843pCy1kC3Rr0rxMn8Fc5c7Y6CcgzrVvjrwSDmikL8LkYc69jAPoyp7zYF+qVRXldHLNnT00SJCbxuMg1wZFciTsAsMzhQJvNm4XLdoBej/xBgxBgMGBxbi6u5TcAPBYXhxe59rrJaH7twoVYLGeo3t61K3qTD+rs1j4o0WMWLMAK2bL6p0mT6gB7h/LzMWzePJGExKTXY8mNNwp9xWfyZax8rLy5DXB8bM6F4ueJA396AFCJccfEGIWFhTC6KGzKuDDr76BBkusf4+v9nw9m2UePHhVxA0nM6svsvu6Iz+fOldz9+F4yXZxkev/993H77beL3z799FORFdgddezYEYcOHRIxDk+4ZJWYOHEiPvroI/Eqs/Eyw68W8Vk8syQA4DsffNAwt0Ktupt7AbrlFmDp0rPZdbViaqvb5ZoExN//rzCZboROR+ccidQAoNF4NWFA2O1fyE91sFh+hsl0NkB+dXURysrGweFYJ8r4+f0N/v7/rMMOelAo2YqvvBKQrcvdju25esBE18w5w3AwNEjgeYtW+LxkU3uTUL/jmYT/Mx4uL5rVgJhenwCnk2qcHtHRqxEQcEmt5xbL9ais3AiHg5mjTUhIOKZhOedAfv4UlJVJcqvXR4ssu3p9iIgDzcs/yRvkY1RW3irK+PuPQUqKdGBX2sfprcSFZBxetaeV4gas0xnRrt1aVFYOrOmTw7EMNts+FBVJ1n+hoX9HWNg/aoaisnIrTp8+G7gsPPxVhIQ8VGeoqGcomYUtlkNIS2PsPQeCg/uiR4+1KC8PEGc0GpLYbFaUlAxDefk2sE19++6HxVJXkVCSmtGzgnqGq8eclrw0FQDItlIXoiHQFVcAA+smgG0WcVXLJvssL1Nef4sJUubNG4fMzNXinaio+9G5swIuu6+mIQCg1vj4yv+G8LmxPCIXFi++Gb/KwN7klsPwtE6P/BbtURp8NrnNkswt+CpzK9KteYJxL3W7BakR0n6n0BcnN+GtIxKv4/zD8FG/e2FQWRFmFVhxx97/wFpdicSgUOy6eypaqBZtWt8xkPYyOTlELcWboBSFUFmc+BFaHPgyIQBkFheLeH9a9OOxYxi7YAGsdjs6tGiB3XfdVRMX0GuhY8GGDKRPH2hAYQ+CQhBh3KefisQopPv798fraos7V/6rNgcGcGeWxtUyWKcc9LsFBmJ9z54IcdG3Ps7Oxq1paeI7YyIi8I1rfKWSEpzJyUFcZqaII9gtOhp7fMk8pOY/F0q2nRucyyLisc9qNqv7z82PG5G8Gb5ZWYlbg4IQqteL9o7LycFqOdHBvUFBYO7ft1QuvclGIw7Hx4vEKrVI3jgKg4ORkJUFAokKaQGAK/PzMfbXX0UstQSzWQTf1yuu2koSEAWAleeJLT6+/nH2UrR4AO48e7YA6vvGxwtX+QBV4H9rVRWGzZ8PJvSh2/b+6dPRnkqFK/0e54onHtQzl3ySKTffIW8J7mnGdpPfobUZ5+s62WXyb8OG4Z8jRnjHX6X9y5dLFnGctyqFz3U+35+QgNfbtRN1awI4auWQMQipfFVWYpdOhxEVFSh0Af/uN5vxuiqpQr0AIOuy23Fcr0dBdTV6RUfjeGAgCgIC0MvF3fmb/HxM2LdPzEHGIKWlKlM8EVA63K+fiCkn3ESUfYNzgxcW3ig2zTzmnkSOz70GAH2ZUx72BVrC3di1q/t9MCMDr/38Mx6SLbWT/f0Fr5W1jS7kawoLJctkN/LDJEaT0tKwUA45cWtMDD5kchlGRLDbkbBpk1gLg/V6bIiJQTfKoosSvPLwYYz99FMRczXBYkF6797Qc81WH2RKSkBLxRtTUuDPzM9ulOjXNm3CQ6slPYbZfA/fe28tLwB6Bwx5/31kFBeLfn527bW4trMUX9tn8mWsfKy8uc/fPjbnQvHzxIE/PQD45JNP4vnnJdc/ZsRl1lsteuGFFzBzpnT4X7VqFS7TSMXubgyFW0RiIrKyspCSkoID8k2EVvlOnTohLS0NCQkJIuGI2t2PgB6BPdJdd92F/zJGgwadPn0acXLmvJtuugkLFtTOPEuAkUAjiZmPmQFZi/iM75PefvttTJ06tcnEtLkXIGKsTzwh6eH00nINf1JZ+RYcDsntj1RdfRp2+3L5N1q3UHWupI0odLoQmEzXMvcybLbX5DLqqD38Rjf4+T0p1Jnq6jw4HDtht38lfibp9e1gsXwHg6GuGTj1DurzBKNeeIFj22RsblRFxI3nzZNCbPGcRl7Sg4iXs2p9neeZ48fXo6TkN1DH40Wcw5GHwsJHxffN5t4CPJP4qYfR2BX+/oNRWqrIr1lYSErkB3//YQgOvhsGQ0tUV1egqmoPSkrmoqpqV63+MFlIaOjj0Ou7o7i4GDbbl6iuZp0OMWZxcduQlCQBZjzzUJ9jzHP2hfJA3FttaFFSshO7dg2G02mFXh+EkJAn4XCMgF5vRXHxlTWJR/T6WISEPI7q6mKRqKSqKg2VlT+iulqKhcNvh4e/UivZS1CQZN1IsJd6K3EGfj8rayYyMiTXyaCgXggLexwOR1tUVTG24Yuw2XaKZ0lJM9GmzXOa40kjD54P6VnRs6eIj++RfAWg3FV48KDEV8bQnjLFbRJQj+3xtYBaNjlvOnTwrYaFCyfgwAEpIUVAwMVISHgdYWEuh27wTLADlZXpAoA1m2NRVZWHo0cluQ4JGYy4uDtqfTg2tm7MHY5Pbu58YaDAszZxrbS0JTh48Gvx7uDBjyMyUlJqSRER7dDSJdFGQ/jcWB6xLXl5aZg7tw+qqiTZHmGJxtgWHRAc1VnE/dtfchJzjnwn4veRWlki8XCHcQgwmGF12HC0LBtM/vFrsWQ5ZtIZ8Hy3m9EnvE0tvpFHK3K2YV6utAa3DQ8XVmbdYmKEO+Hrv/yCn2TrjTpZLZlVZ9eus4uT4hrmy4QAEP7ii2DcpDHt26NLdDToZkyF/qu0NHyyd684QDDjH2MP9vDW4sxVLBsykL6Jtu+lPQjKhIUL8aWssxB4eH3UqNrumlwA2C+6aPn5wRwejg4yeMtD95eyFdrFYWEiEcVrcpar1n5+uC0uDh0CAkArj+8LCvB5bq7YeUMMBmzr3RvtXW/u8vLwVk4OZsgHQp8Tsaj5P3Ik8N130gbnsoh47LOay8XFMB86hA4ES6hscDEmT4xGROfnI8/pRBeTSRxUj3ID4npuMAgwIlsF5JmYCCEiAgNlV00CFR1k4GxRQQFKuXEEBGCp01lj/ci6egQGYlR4OAINBhQ5HDhYXo5VBQWwy+7WH6Wk4BYl8D5dMjkefEaghfyV58mE1avrH2cXyTIbDAIM16KZ33+PFzZIltW9YmPx+ODBIvPlkTNn8OKGDdgpg5AzhwzBc3LSuzr1/B7niqfZVc9c8kmmqDdp8JdJBUZ88AF6xMTg6pQU9ImLE5lFCaSeLi0VFrrv7dwpfiZ1jY7G5jvuEIlAvOKv0n66XnOOKXFV5HFWz+feQUG4OjJSJOsgEZB5VZ7bPQMDBbBjtNsRyxtPqxWTqWw5HDhitWKQzYYclwb1NxgwzmjEadWceL+qqiYJSE+9HjeYTIhVwi44HJis1+Pn6mqMYIZYPz90CQnBu7m54AXD0NBQaR0pKcEPhYU1CUrUn53drh2mKy6pakWKChrnqjeKTTOPuSeR43OvAUBf5pSHfYHfLLHZMKFTJwxp2VLs2Yx1x7/tzc7GJzt3YoMcLoJr2fJu3WpZfX+Rk4PrDxxAtMmEvsHBiDSZ8KHs5tvFYkGKxSIyNTNOI4kXGVt790acypX9mRMn8LSsFwTpdLg3MREjU1MRHhWF7NJSfH3wIN7ZsQNM6kX6aNQo3EKZdj3I5OWh9cGDKAEwISUFQ9q1q9ufvXtrLOA5N+mBcCljTcmUX14urJoPyxbajw0ahFuVRFFuBpGJQdxdOoo9tZmU6+Y+f3sjsxfKnH8O/OkBwC1bttSAfu6s85gxt2vXrgK4CwsLQ05ODkxuUpm7G9Lp06fXAHa0JhwwYECdogQgB8omNCw/e3Zdd7/OnTuLdkRERAiA0KJh2qYGKxcuXIjrrruu1rcIEBJgZL9GjRqFb+XYCK4NGj16tAA7mW04MzPTraVgQ8S4uRcg6iE0HuD6SV3X1bCjuLgdqqsli4ZzRX5+f4e//1mrMX6X+xJ1NV7Os408ZzX0bNnU/eA5hoAk28QzNvdNtY6kfI992LFjMsrKms5CVLsvOgQGToFeH4GSkldVOedql9bpohEaugShoQNrEn3xMpxPLag2AAAgAElEQVSuwvzH+NGcNgRjXEN4/X975wFtVXH9/03viAoWokGUYC8gWPMTiSW2qAmWuJaGGGvUJC41GtPUmBCNMf5M4jKW+CfRnykGFwawxBgVxYYl0cQKCCqigg1FkPB4//U9983zcLn3nnrnnvveZ9a665U758yez8w+s8+ePTNLlkyz558/1lpaluaKc9iw1qAfytkrB6Qrv0uX1fbiiyfZG2/cULW8jTY6wUaOvNa6lO27pgt0T00UyiYaPNhM+xFXOuyv/OZ5OABVtlZ6yZm69dZmmh+R89dHCvdNMXWH+MUt+6KL1nb2xb22Vr5x49w5iKVcrn3mzIlf3o47TrTDD5/cXkxazlkZOQHmzfu7TZlyjGlPwCxpSK+Bdu7IQ21MWXRguA9P+/Beu3HBzIovaypbS2mmHHXUmlEHcowoiksPJz2k9DBNqhBywE+aZMvaXjYq1XPbIUNMp/6ldv6lbcgs0ONcG9FRku5BNaxXL5vfZt90uf/+OBKskUcvhFO33TbY6H2N1NZRdlu40B5dvjyIsHjtrLMCB0isVM7/rLPMfvGL0gBX9hBJVWdFn6j/qT+2zfRsoBfYkEMjlpxtmYZ162bztXy2tdU2e+01W5DwPj26dAk23W8/REX114uvW4qtv+UYbBs4uvy49vYH5bJXXVoqu6a11XTy5g1yzFdJJ4waZdd+4QulyMTyVFRdiWrAGrqUuE9VWLrrHIBRYuh7TWT8v8MOsyH9dMZuWarG18mvE7vVdnqOutlFTW6m0GdXcqtmwFavtsnLl9vxbftfxqlHrTytffrYfatW2fgaz+1K1/ft2tWu2GILO9ktHSg3pOQc1/MnjmFT5zaPwyiWAzCpTkWMC67MKPk26d7dbthgA9uvbBlseIuCqHvo+7m77GKbh6JD9T8F15w1d65duXBhVZtB+bQUVxMN5+jwJmcruH7d1vabLVhgC2L0o00GDrQbDj3U9is7kTmJbrr6TtxxR5t8uFaTxdTPOKBi5Kn3+3cMEchSAAKd3gGoNnDLgLX8d+bMme1OONc+l112mZ177rnBnxdccIFdeOGaTpz77rvPxreF2E+cONEmT/7k5c3dQ9F7ct61tLTYmDFjgnL6hB5my5cvD+R4/PHHg2XIzz77rH2mwr4B4WXAp59+uv1aR7WH0ty5c2306NFBRNSIESMCZ2GlZc3hZcC33HKLHXGEItw+SfrfUUcdFfyjWp2y9F8fDyBNzsg5oue8Jh/DeyAXxQEo2fTOINlki7RFy2dBm+u12gf46afNdJicfN6KAnzrrTW3z1CBcgB+8EF+DsDu3YdbS4tODutq3boNNe0R2L//8darVylCV6fxfvDB1bZixQPW0qJN6Xtb164jrUuXQ61Pn2/YwIHrBI6+tkDYoB/ovUeOTEXIybZz35UDW7Figb322pX21lszbNWq16y1tad167ah9ejx6SCrTiTWEudPohajkcsB6Pb/kz2uT3jZ6ttv324LF15rS5fOttWrl1i3boOtf/+x1rPnKbb55geu0XfDpbmtS7RPvt7ldv5k+8maQuXhABRPHeIoR/sOO5iddFI0hzxzhPvm6NFrO/lrleXLAejaZ8GC9A7ALJyzMArz++ijt+2taSfbMwsftQXL3rL3W1uCJbzr9exvm/YZHPxc1rLCFi5/195d+aEtXbXcenXtboN69LMR/Tey3dcfaXsP2dZ6d1s7EqW8D3+8wat21ezZ9sCCBcE+OoN69w4iXo7faSc7pnxJqBNSG44rekCKriTlSqIQiobXUtW5c02n9y368MPg9L4hffvaDhtuaEdus40du8MO1iOOd71ax8vSkHkqTqV71egoiR0XPXva/LaJzKQOg0Fyeu22m61TaSuWjz+2l155xUa2tfEBI0YEm6vHTpX4V6l34jr36WPzt9uuNDi6KMBly2xWjx52yYcf2uyVK9eI9osjc7sDcNUq2+z1121BW0Rf1LX9u3YNHBunKLoyPEHsFE03UHSTnJ7amF7L3Xbe2RLXudreciEBtVeW9s6c/frrplNQB/fta2Ml284724G19sUqsq5ENUBefaoC3/+2tASR0H+fNy9YQq3lwHpGap+5gb16BcsSteeioqT3rHLaaiB+Lb5O/rvuKs1Uymhq2y8tqT6HUbXK6OrSpeQAbNsDMwpl1Pet/frZB6tW2V/79LGHW1vt0ZYWe3nFiiASVkvQ3airn+t17x4cHqH9/07ceGPbIDxbGR6EJKccQUkMmzq2eRQDfR/LAZhGp2qMCy8sWWIzXnopiIqb8847QcTd28uXWx9FPvfrF+zLekjPnnZUt27WV0urw3vu6b3yuefs93pexkyt48ZVzvnxx/bE/Pl2fUuLPbhihS34+ONAHxSNOGK99YKo/lPGjPkkWtnZCu5FRnddtMheGDDAZqxebbNaW6vXZ+RIO2rbbStG1ObqAEzTVjE5KpuP9+8E4pC1QQRwAGoT6aeesj333NPkhOvfv79pWbAcevpby2DdnnwjR44MHHQDytaTxnEAqn21hFjReUqjRo2y8847L9gbUE67Sy+9NJDD5Zs0qfJyPzkQx40bZ7PalldMmDDBTjrpJFt33XVN0YwXX3xxEKGoqL3p06fbgQeuvRm7ylD04M4772yLFy8OHIRnn322HXLIIUH5uu7yyy+3VTq5b8gQe/LJJ4MlzHkmHw+g004z+7//K9k6lZYB51mftPdyy38V/feVr5j96ldp71Sf6+Tgue02Mx3upgAE2Ukuel6BAy6pHgrACUe41Ueite+qYAsX+KOJZb2ja8WK5HOqKrlcFKCcb7KNy5eFl9857zq55b8qNyybK9cFMGlFir7X35VYh+UMX6OtUao5NevRFtqqS+8G2jVBk5ijRtWjlOr3DPdNOXXbtoZJJIRWqKgeUZwT3TSUOY/2ycI5D0auOhsvetK2fP4222Tho7ai9yBbElq2nJaPrsuDkQz4oCHb9ggM1oT7VogoCFkaMureWb/P2lHqrUh5dJRK/LPW23EP11+OOs325DUYRg0ccdveKZocHFquLMNITnLtc+Zz4Igjb5F1JUr+vPpUVDlZvq/F18mv5fGa8XUz6GGDL0nZYUNKuuEO75BRnnAlVXuxctDpPooe1WSBogsrGVVx5QwPQooW0H2TGDbN3ubVOGWtVxHHhXKZVHe9QMjwLorNUOfnn4/377iqR77GEcAB2MZ+2rRpduyxxwaRc5WSnH8zZswIourKU1wHoJbcylmnKL5qSYd8yOEoB161tGTJEjvooINstvauqZB69eoVRAaeeOKa+1OVZ3300Uft8MMPNy0JrpR0OMjUqVOr7ouYpdv6eABpTNfzXDaM7HE5fqqc8ZKlKqmvlUxakiqZZJPrmZ/WxkotRMSFsrMuv7z0Xq3oRNlFcvroI5+wC4iRLaZl184ZJ4dmjS6cm7gqVypbOv23NHGrJI7hJb76vw4Mk/yyQbUvb5TtmWedwnJqUl3swnwUkCF+cmTJeSnbU05XTZyWs3bwyq9R0E2WAKUkjSKe2iNaASTytZx9djTPJPePkzfcN7UNjOof1abl9xVD1aMW5ziyVMqTR/tk5ZwHI1e3ri3/tT0evtzWf/tFG/TefHt1k91tdYWIviS88mAUlKcbaWlP2wESwYNfjg1fChFV6awNGXX/rN9n7Sj1VCTXvuEHZNKHXTX+Wesdfhi7B0nbgSfBS6U+WQbDqIEjbruHFU3GhmbDpBu6v7aIKT91OO5965Gv6LoSVee8+lRUOWm/j+Lr5Nez9IEHSnumyMgKG3xJyi43pHRt2wEewdKGSkvAa93f7fGq/qt+LaOpklEVV8awbuheur+WDyUxbJq9zauxylqvIo4LYZncieo6EVCGd9JxJW4fS5IvSj+T3KtKXh/v3zmIyS3qTAAHYAiwTsu98sorA0efFKSnQohHjAj20DvjjDMq7reny+M6AF1Rt99+e+DkkwNPzrzBgwfb2LFjg4M5qkXslfcDReddd911wQEfWua7bNmy4MTeffbZx771rW/ZtttuG6vrqHzVWY6++W2bqerk4cMOO8zOPPNMW7/KJs+xbl4jk68H0L77lhwp2mevaFGALvpP9pW2TNKEaxGTtoiUHaj3G9lqirLTu5gi2TRuuqSxVM4q2Yqy68q266hL1bS/tBx/eseSXPpbSXING7ambFohqFUfGl+1ZDYsezXh8qpTWE7ZmOVlqxz1B9nYklvzDHPmmGkf5kqsJW+la+oCucJNdSCoouZkL+21l9nnP++r5DXLCfdNTeCWbcsSS6gozrFuUiFTHu2TB+c8GLnqjZhzp316wQO26WsP29IBn7J3y/bzS8oqD0btZeohpcZUkgJpQ8yipDwast51ydpR6qVIeTzsavHPWm/XLuH663960cw6GEYNHHH7RFjRNAhqdlSGhwwj7d+Q5sEZt+yk+ZpBV6LqlFefiionzfdx+Dr5p08v9WPNVJcbfEnKDhtSMiLdchI58ZLO2smAk0y6VveSMVXJqIorX7luyAGYxrBp9javxitrvYo4LjiZXnqpVGttR+AM77j9pl754uhnxrJ9vX9nFJPL60wAB2CdAXP7ygR8PYD+8Q+zCRNKdq4mHcv3AmxU+7i9/xT9Jzt8yhSzz32uUdLULlf2kc6jUQSgIgFlHynSL7Q1THAD2WVyCrnAB9WrnhGXbk89takrR/9zq0LkTHN7WCvqX/ar+oEiQfWzbEuSihBUJ205pfcw1StNncJySlY5qsI2r9t+RqtYZMdqn2I5T1XmY4+VVmuVs652jY8e5LYn0ST58OFmp58ez5laD9nCffPll82S7gUomWpxTitzHu2TF+c8GDkOfZa/Y2Mfu8rWfXeeDXrvZVu08Whb2WtgKkx5MGovWLCkLHowKUmBFEZbfvpTKkkzXpRXQ2YUI/LyrB2lHookobN2lCj+WevtwIbrr3vKyaGHf70GjsgGbcsQ5ie90ACp0G2t/NASYA1waR6ccctPki+qrZLcq5F58+pTedchLl8nvw7I0cyvIuzkBIxjNFWSOWxISU/cUmDphxzScZeLhJcP63c9391J1kkdieXPFqcbW26ZzrBp9jav1tey1quI44Jk0oShW9YkQ1YThj6iFmrpdFz9zPhc8PX+nVFMLq8zARyAdQbM7SsT8PkA0vkmiq5ThJWSnDhx7Y16tJ87+Vf3llNq//3NbrmlHiXld8+ZM83uuad06MPixSWbTe8PsuO0375bxSFHlRxWcrDpO9Uv6QqPOFK7E3V1bzn0xFR2oNvzXH4A5ZG9Kuef8ul35ZUdq/+Vy16t3HCdXP+JW6ewnOp3zsnnynKHzzn55FQLRy4qAlA2SlheXat3tmrXxOGXNo846+RfTb7rnVERto0OtAr3TQUGjBmTXL8rcY7bxuUso9o0Dvu8OefByMk9bMFMGz7vHtOegF1aW2zR0DHWWuGE6lr1zINR+/3DsFzEutZ0p+0McRoobp68GzJuuWnzZe0oeSqS6pC1o8Tln7Xejne4/hqEZGhowEk6GEYNHHHbN8xvo41KYfJDhpQe3m6jWQ3q6EpcovHz5dWn4pdYO2dcXXB3cfLLeJbR51LY4EsiW9iQcnu1uJ8yKKMGXPXl8OnBcvjJoCo3quLKVEs30ho2zd7m1dhlrVcRx4W//a20jEZJUaR6EWv0i6En49rn+3dcdSSffwI4AP0zp0TPpxBpAn7rrUsH9DmbPOoAiHo2klv6K2eVlqJqkrVIW/BUqrtsx+uvN1PEvMYocZQTyEXWuSWtsqn0P02wqZ71WgrsVkapHSWbbEHZpU4OjeuSwyU5/+Qb0EEVOmtH/oFy2au1eZY6heXU5KLkCNu5bvWJk0/vZeHvVbbez8LySk6xrXZNPfuuVk7I+ajThrVqQtuMNtJmUl3DfVMHvKkfVNiqtSaWSpzjLBGvdNOoNo3TPnlzzoORk7tL62ob/eT1tt7bL9nQRU/Y0gFD7d311t4bt1Y982DUfv8wLLeUUcto0naGOA0UN0/eDRm33LT5snaUPBVJdcjaUeLyz1pvxztcfz0o5eDQAzLpYBg1cMRt3zA/OflkdGiGRA/vr33NTPtRa1BHV+ISjZ8vrz4Vv8TaOePqgruLk1/LPqZNKxl86pdplwKXG1Lqj25PmThLgd3SX2dwaIBWfy43quLyqqUbaQ2bZm/zauyy1quI44KWK7moUfUtLc1JajjG7Wtx8iXVzzj3rJIHB2AGeB3oUhyAHagxm6kqvh9At95qdsIJnywF1pJRRYP5TgoG0KoHt/R38mSzww7zLUW68rSH3rXXlval04EaWlmkcV12lCZhtbe4kiZp9e6j72UvyrmZp4PTLTF20fpiqaAGla93G8mk9xnJIJnlZNXYru/c8l99r8NhymWvRkZ1ksNQZatOKlvOzVopLKfyyjGliW6XVL6iJWXHOtkr9UlFUzp5w5GAta5J18K1r3r1VTP5VWQjKUrxlFNKbIuQwn1TdpT8QJtumkyyMOe4/aK8hLhtWkuyenHOg5GTu9+Hb9rOT1xr67y/wNZ/Z469s+4WtnSdeMDzYNTOrxIsPQDcgyptZ0jWdSrnrldD5iFbrXtk7Sh5KJLky9pRkvLPWm/HNFx/RU5pwFeKOxhGDRxx2z/MT44WDUI6/Sr88M6rznFlqpYvaVtlLc/X9c3O18mvA0FmzfpkT5WwwZeEZdiQkjEsx5KSM4qr7RnjDg1xp7i5pb/lRlVcWeLoRtx7ledr9javVu+s9SriuKCoAPUp7YnaiWwF3+/faVWJ6+pLAAdgffly9yoEGvEA0qTeX/5ScgJq8tG3E9A5/zTZqeWgWpqsqLpmSjp4esaM0rLUf//7k61cZE+FbUJtZSEnigtkyMsJ6N6N9C7jJoLlhFLZCmqQo09JUXNPP13KIxtT+5wrus4lTf4p8EEOuHLZq7VHeZ1qOQHDciqfnHzh7cic/SknXrnslcqXvIq8lFNTSXavHJquvvXuQ+79TCcra5nywQebjR1b71KT3T/cN3XIZRonYJp+4aRM2qaValdvznkwcnIPXTjbRr40wwZpP8D3X4nlBMyDUTu3WrDyrGiybljKXe+GTCNTkmuy8suiSJIza0dJyz9rvSsNMFp6oOQOPqg1GEYNHHHbMMxPg6BecrfbrvLDO686x5WtPF/atkpbnu/rmp2vk197rGrmV4azHHJpnYBhQ0pGsZImbZxRXu4ELHf+KepPxlS5URW3XZPoRtx7ludr9javVu+s9SriuKC6upeatIZj2n7SIFuhEe/fWRBxbX0I4ACsD1fuGkGgUQ+gL33JTAeDOCegbGNFXdVzGaPsfjfZ6Zx/OvBDUYnNmO6/3+zee0tOQDnZ3CSu7DrZZbIL9b6hLV/0cU5AOe307hO11UslJrIP9W6kqEK3XYzuoz3MVZ72NNdHskgunZzrDgBxP3UoiJxXrq116LU+zgkYlr1au0TVKSynW/6sgz30cXauyhMr5/xzslcr09XJOVyVL/w+V+++63g659/48WbjxhWz54b7pmy58jaPI3XSfqE2T9qm5XKE+229OefByMk/bP79Nnz+ve1OwPcHbmLvrbv5WnsC5sGonVlcWHlWNE7HUZ64ssW9XyPzZeWXVJHSPiDDjPLgn7XeTp5w/RU9IyVw+5iVD4ZRA0fcfhBWNDfjpAFCM2Aa/Ko9vPOqc1w5O5quRNW72fk6+XUgyAsvlIwoOeycEZPUqAsbUm6PTPVd6a+M5PCpbu5kNzHWbKrKDBtVUezd92l1I+79y/M1e5tXq3fWehVxXMhapzR9JI+xKk25nrfgSikil3kggAPQA2SKWJtAoxyAsiWOOqrkBHQReW51TNSSzjTtKIeVWyrrIg7l/Pvzn+t7Qm4aWeNeIztKewLLCajJe0XbyaEqfmKqemp/cTnqNNkqW88tB5bdqAncJKcDq82056DGS91Tdqe27tDWL7IF5UDTqiZts6SVKnIU6l1H0XGaJFYkoiYe5ciSA3KrrUqOStVDy5llj8ghJyeOk71aX9A15XWSveqWIzs5XXSg7FTJqD4mBlpp4CbPJYOTvZr9LLnCdXKryVSmTr0N1ydu+8XNV162nGl6f9xrr3RO3LjlZskX7ptyApe3eZx7J+kXadq0XAbfnPNg1F6H1lYLDgWZf68NWPqarffuPPtv9962ZPBW7acD58GovbwksHKtaIyek0S2GLdreJas/JIokiqbtaPkxT9rvcMOBzfAaNDQ/g3aa0oPby2FdIOh8tcaOOJ2hDA/zWrqby01UOi79kOo9fDOq85xZc2rreKW1+h8zc7XyS/DWUsRFAnojBEZITL4khjQYUNKBpubkZch5GaU1WbKp6T/y3DU/oMu8jCJ0zGLbqTtO83e5tXqnbVeRRwXstYpaR9p8POvUe/fSTGRv74EcADWly93r0Kg0Q8gLQeeMqVkhytCTc9/2eNy3CRxTlVrYNlGuq9sGdkpuq+cVxMmNN+y32p11GqAO+8sOc8eeaQUdad66h1HHzm45PySU1BOODnu9J6jn7IVw8t4K5XhVkzJdlPb6L3J3VfOKF2v/ei0BFjRXnJGyj50Dr4DDigtUw3LKWeaHIV6H1KklRyJcg5q+w9nI6pPONlVZqXkHIZqZ9VP16gPSSa9e+k6t0JF9dX7n65RH3C2smSvtoRX9axWJ8njuFeqT9aHTq2yi7bsN07fTMuoVr9QuUnbtFzWRnOO0osk/UjLgUfMudN6fbzUBi953nqu/MDe67+pvWKftnc/7BG731ctMwusPCtaScAssiWB3Ki8WflFPWDTPCDDLOrFP2u9nYzh+muQ1ECggUeDhzvVtNLAEbe9w/x0X31kfGiQ3G230mDmBsOoe+ZV52rl1KutoupVlO+bna+TX1GA+t05rmXwuNnOakZTlCElvXCz5c65KMNPBrn6cKW9VKLaNU/diCqrnsZIrbIbpVNZ+3IRx4WsdYrqI41qqzK5Gv3+HYWJ7/0QwAHohzOlFPABdNttZmeeWXJOyY4J2xxy1MiOTrK8Ug4rPd9l07tJTNkumriUM+h//7d5DvyI22G1vdHUqSUnmg6L0wm7mtCV01M83ZJnvd/IvhMb2XjKoyTO+iif299ZNpvyOKeaawOx3Gij0mm+cvTp/UZRe9pnXUnRdHLsyal2+OFrHlARllOOQkX9Kcl5qP30VIZsWsmoj6IWleTMU1lu2bHjImefHH/aky/cd1x7KzpR/UfORn2vJPtYdqw+clKWH/iheyq/WEbVKao+kjnJBHmSsuP2jUbny4OR2lgORPUJOfx0GrP6ppL6tPqinNzV2rScQdE458HI1bHfsrdsy+emWq8lC63nm6/aoPdKSrZy0Aa2asOh1nvwANtq6y7xD1/KE1aeFVWl8pSt0YoSp/ys/MKK5GZP9KB3SQOAIntqPSDDcvrin7XeTuZw/d94ozRwyFhQ0uCjwUIDggYj/Yx6eKv+GiA1YIQ3Ndb/FZGl4+5Hjqw8GEa1d151Dg+WcQe2KNk6wvfNztfJL4NPS4JlsGhQdDO7TofLjaZqbadrtURefUR64gZY6YB0QwOtDJoi6Eba/tfsbV6t3lnrVW1ccC8DjRgXstap6EYfS4DTanGHuw4HYIdr0uaoUFFmIGQ7f/WrZvfcU3JYyTHlHIEag/RxW5LIuRN2CDqHn+wefWR7uxULyis7XD/33dfsxhvzPQm3SK2suuuAOG2jIWfXv/5VOmBDdpwYufc8dxKwGIujC4DQ9268V34xdLaf4y8Hqj76Xg4X2YQqS/eUXSiHm37fe2+zPfes7LgNyykZtCJL72H6Xe9cWi2le8ohrHJlm8gmlZx6P3NOSlcn5+BUXfQupr9dvVR33UM2sOxhOf80gT18eCny0K10cWWoHL0X6++4dYqqj8qV3axP+T6Xbl9KlZum7CL1v1qy5MFIjj8tt5bjWH3F9Wf1B7WV2lPtKt7NyDkPRq4fffh+iw1/fZaNWXa/rdd3hW1ki2zQR6/b4H4rbJ2h/azLOg3slHlWNKmyNovC1FOZ1EkUaq3ZF0WoafB1p3/q4asHpGZxdJqT/i4fbLM8LLPwz6vf6EGisG45ADUAaNBwmwO7cHj9Xw8VzRrqp5shCzzpKz+ZQdN1bhZNDyLnKBG7nXYqsaw1GEbxyKvOHXlwiWJYT11qlC64Orn+oX1gpNP/+U9p1tQt8XD76qgfa1BU/3YOQee8lpGk/ProeSCHuHseOEPQ9WsXVVgE3Ujb7h1Vp7LWq4jjQtY6NVo/I/poUd6/06oS1+VDAAdgPhy5S0ICRXsAaWuTn/60FMEmO0S2iX6GtyOJqqKbyJetI4eRJuHPP99Me/51hiTHmSLoxVC/K3JKWyA5G088Na7KxnM/xcU5Tp3zVBzdkl9n78mRqndCtzRXTq0hQ0pOQb3riLWWp+rvqBSWU3an/lbEnYvWc4EV7t3MRXU6R69blRKOEnXb3+idrHwFjK6T7JJZ+cLOTska3t4mTZ2i6hPmmnfZUayL8n0ejNz+k+7gQrfUW/1FfbzZOefByOnlp/q8Y8OXzLZR9pRtOni59VlepmSNhJVnRdM8gIqiFGnlyMpPD3MpjR6sGij1u5RLD0f9r5F9oxaTrPV2e5hJSfTAUDixfpcjVFFUGoz0f+cIcfuHOB5ONg0w+oid7qmPNsFVWLn6Y5LBMKoP5FXnNANblGwd4ftm5+vk1wywNtydO/eTmUy3NMIZ0S6qNdyfXV92jkL9dM5/9eUi60ba/tfsbV6t3lnr5cYCjQf63Y0PGhv00tCIcSFrndwzv2DPv6K9f6dVJa7LRgAHYDZ+XJ2SQFEfQDqk4aKLSqfCa3mpxpxwpJ9zWDlbxtnhcgrpf1rFdPDBZhdcUNrrrTMmjds6sVZ7RStqSqs7tPWRxlK3PNq948hh5v7nov009svxJ8eexvOCVpgAAB+8SURBVE+NnWLpItlcJJ4i/8aMMdtuu5K9kDSF5VQkoNpazjo5eNwBMXpH00fvZipD766yRXSt5NMSUH3cAS+SW/kVXaikyETJruudQ1H9yTk55URyjiTVP0udouqjcutVdlL2jcqfB6MddyxJr0jXSv2m2TnnwahdLy30MCgarFwrmuIB1CglyKvcrPy0/4JCoxUZ507JDT+Ai6pIWevtHvJbblnadyLOQKk20yDj9iXRS7EcJNoHY8MNS3tfZBkMo/pEXnVOO1hHydfs3zc7Xyf/o4+a/fOfJYd2eM8XN4uqdpKh4/aqdJGBmtnV3i0aXLVvZTPpRtq+1+xtXq3eWeul55mW+SiiVMtxyw3zRowLWeuUxbBP279qXFfU9+86VJVb1iCAA5Du0RACzfAAktNq+nSzBx8s7W8nx46LXnPLguX80VY7n/2s2SGHlOxx0icEFEnptjzS6iet/pKTVc5Vt4JJTjPZf3qnkTPMLbWWg81FAspe1PuOHGoaS7UXYJJD56LaJCynnHdyVrqIRRfR55YlO6ew7qn3VecELpdP37u6V7pnPesUVZ96lh3Fuijf58Eoj3sUhUclOXKtX643y5lakWXLuap1uV1Wflmvr0ulYtw0L7njDpSaYdSMkpZKa++BegyGUdXOq85R5XTW75udr5Nfxp6WgeinjGdF87n9XRTlJ+NZkatbb13qz9WMumbSjbR9ttnbvFq9s9Yr6/Vp26PWdUWUKWE9m+H9O2GVyJ6CAA7AFNC4JDsBHkDZGXIHCEAAAhCAAAQgAAEIQAACEIBAFAHev6MIdY7vcQB2jnYuXC15ABWuSRAIAhCAAAQgAAEIQAACEIAABDogAd6/O2CjpqgSDsAU0LgkOwEeQNkZcgcIQAACEIAABCAAAQhAAAIQgEAUAd6/owh1ju9xAHaOdi5cLXkAFa5JEAgCEIAABCAAAQhAAAIQgAAEOiAB3r87YKOmqBIOwBTQuCQ7AR5A2RlyBwhAAAIQgAAEIAABCEAAAhCAQBQB3r+jCHWO73EAdo52LlwteQAVrkkQCAIQgAAEIAABCEAAAhCAAAQ6IAHevztgo6aoEg7AFNC4JDsBHkDZGXIHCEAAAhCAAAQgAAEIQAACEIBAFAHev6MIdY7vcQB2jnYuXC3nz59vw4cPD+R67LHHbOONNy6cjAgEAQhAAAIQgAAEIAABCEAAAhBodgKLFi2yXXbZJajGyy+/bJtttlmzVwn5UxDAAZgCGpdkJzB79uz2B1D2u3EHCEAAAhCAAAQgAAEIQAACEIAABKIIKABn7NixUdn4vgMSwAHYARu1GaqEA7AZWgkZIQABCEAAAhCAAAQgAAEIQKAjEcAB2JFaM1ldcAAm40XunAisWLHCnnnmmeBuQ4YMse7du+d05/rdJhw2zbLl+nHmzh2XADrUcduWmtWfAPpTf8aU0LEJoEMdu32pXf0JoEP1Z1zPElatWmWLFy8Oith+++2td+/e9SyOexeUAA7AgjYMYhWPABunFq9NkKi5CKBDzdVeSFssAuhPsdoDaZqPADrUfG2GxMUigA4Vqz2QBgJpCOAATEONazolAQa9TtnsVDpHAuhQjjC5VacjgP50uianwjkTQIdyBsrtOh0BdKjTNTkV7oAEcAB2wEalSvUhwKBXH67ctfMQQIc6T1tT0/wJoD/5M+WOnYsAOtS52pva5k8AHcqfKXeEgG8COAB9E6e8piXAoNe0TYfgBSGADhWkIRCjKQmgP03ZbAhdIALoUIEaA1GakgA61JTNhtAQWIMADkA6BARiEmDQiwmKbBCoQgAdomtAID0B9Cc9O66EgAigQ/QDCGQjgA5l48fVECgCARyARWgFZGgKAgx6TdFMCFlgAuhQgRsH0QpPAP0pfBMhYMEJoEMFbyDEKzwBdKjwTYSAEIgkgAMwEhEZIFAiwKBHT4BANgLoUDZ+XN25CaA/nbv9qX12AuhQdobcoXMTQIc6d/tT+45BAAdgx2hHauGBAIOeB8gU0aEJoEMdunmpXJ0JoD91BsztOzwBdKjDNzEVrDMBdKjOgLk9BDwQwAHoATJFQAACEIAABCAAAQhAAAIQgAAEIAABCECgUQRwADaKPOVCAAIQgAAEIAABCEAAAhCAAAQgAAEIQMADARyAHiBTBAQgAAEIQAACEIAABCAAAQhAAAIQgAAEGkUAB2CjyFMuBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQ8EMAB6AEyRUAAAhCAAAQgAAEIQAACEIAABCAAAQhAoFEEcAA2ijzlQgACEIAABCAAAQhAAAIQgAAEIAABCEDAAwEcgB4gUwQEIAABCEAAAhCAAAQgAAEIQAACEIAABBpFAAdgo8hTLgQgAAEIQAACEIAABCAAAQhAAAIQgAAEPBDAAegBMkVAAAIQgAAEIAABCEAAAhCAAAQgAAEIQKBRBHAANoo85UIAAhCAAAQgAAEIQAACEIAABCAAAQhAwAMBHIAeIFMEBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQaRQAHYKPIU27DCCxYsMB++ctf2owZM+zVV1+1Xr162RZbbGFHHXWUnX766da3b99cZLvjjjvs2muvtdmzZ9vixYttyJAhNnbsWDv55JPtwAMPzKUMbgIB3wTqqT8fffSR3XnnnXb33Xfb448/bnPmzLEPP/zQBg4caCNHjrTPf/7zduqpp9pGG23ku9qUB4HcCNRTh6oJKd3abrvt7OWXXw6yDBs2zObPn59bnbgRBHwS8KlDf//73+2mm26yBx980BYtWmTdu3e3DTfc0HbYYQfbZ5997LjjjrP+/fv7rD5lQSATAR/6o/Hl6quvNunP3LlzbdmyZTZgwADbaqut7IADDghsuQ022CBTPbgYAhBIRwAHYDpuXNWkBKZNm2bHHnusLV26tGIN5GSQY3DEiBGpa7h69erAyffb3/626j1OPPFEu+aaa6xr166py+FCCPgmUE/9efrpp23PPfcMHH61kpyBcqwfffTRvqtPeRDITKCeOlRLuHPOOccuv/zy9iw4ADM3JTdoEAFfOvTuu+/a8ccfb7fddlvNmj711FO20047NYgGxUIgGQEf+nPjjTfaKaecYsuXL68q3HrrrWd//OMfbb/99ktWAXJDAAKZCeAAzIyQGzQLARlpcjBoQNJs7fnnn2/jx48P/tYgdN111wVVkRNQ0UeaqUqTdN9LLrkkuHTUqFF27rnnBhGGmgH72c9+ZpJDSfkmTZqUpgiugYB3AvXWH0VX/M///E9QL+npIYccYmPGjLH1118/iKC99dZbAx2Vg71bt24mI5ZIWu/dgAIzEKi3DlUTTeUq+rxHjx7B54MPPiACMEM7cmnjCPjSoffffz+I7nviiSeCyn7xi1+0I444IrDlNP5o9cj9999vU6ZMCcYiHICN6xOUHJ+AD/2ZNWuW7bXXXoGtpiCHiRMn2mGHHWZDhw61V155xX73u98FOqPUp08f+/e//22bb755/EqQEwIQyEwAB2BmhNygWQhoQHrggQeC5RszZ8603XfffQ3RL7vsssBZp3TBBRfYhRdemLhqL774om277ba2atWqwHmhcjTAuaRlWOPGjQscjJLjueeeyxRtmFhALoBASgL11p+HHnrIrrzyykD3ttlmm4pSKhJDL2Ktra3Bi9hLL71kXbp0SVkjLoOAXwL11qFKtWlpabFdd901cGT86Ec/CiLTtfyLCEC/bU9p+RDwpUNf+cpXTFFM2iLmz3/+sx166KEVK6CxSDome44EgaIT8KE/mrzVSiqlq666yk477bS1sJx99tn2i1/8Ivi/tl769a9/XXR0yAeBDkUAB2CHak4qU43AY489FrwEKSks/Te/+c1aWTVbpT2S5JQbNGiQvfXWW0G0RJKkgU57Xig9/PDDtttuu611+SOPPNLufFR+DZAkCBSZgC/9icNAURiKulCSU2P06NFxLiMPBBpKoFE6pJcsvWxtueWWpmX2inDHAdjQrkDhKQn40qFwNLomhrV8ngSBZifgS3+0tFfL57V6Y8mSJRWxKcJW71lKsuFcpG2zM0Z+CDQLARyAzdJSyJmJwHe/+1376U9/GtxDDjjnDCy/qZbuammu0l133WX7779/7HI1E7zJJpvY66+/HmxyK0ditaTvX3jhBfvUpz4VLCUhiik2ZjI2gIAP/YlbLTnMzzjjjCC7IjOOPPLIuJeSDwINI9AIHZKjTxHp2nz93nvvtb333ts222wzHIAN6wUUnIWALx368pe/bH/6059snXXWsTfeeMN69+6dRWyuhUAhCPjSH22xpDFHq6B0CGK1pIMR5SBU4MUzzzxTCEYIAYHOQgAHYGdp6U5eTxf23q9fP3vvvfeqLtdQ1N4ee+wR0PrhD39oF110UWxy8+bNC5YlKlWLMnQ30/c6yEBJ1w0fPjx2OWSEgG8CPvQnbp1cRJPyKxLwS1/6UtxLyQeBhhFohA4dfPDBdvvttwenlP7+978P6o4DsGFdgIIzEvChQytXrgwcfytWrAj2/LvlllsCqbXMV5O7+qlT6HEKZmxMLvdOwIf+qFI777yzPfnkkzUjAHUQo/RMacKECfaXv/zFOw8KhEBnJoADsDO3fiequ5tp2nHHHe2f//xn1ZorbF3h60qKLFKEUdw0ffp0+8IXvhBkv+KKK+zMM8+seqm+P+uss4LvtVfGQQcdFLcY8kHAOwEf+hO3UtpM+q9//WuQ/dlnn7Wtt9467qXkg0DDCPjWIR1sdcwxx9i6664bRJurfCUcgA3rAhSckYAPHVLE0i677BJIqglg2XGaDNbBBZo8VurZs2dwyMH3vve9IKqWBIFmIOBDf8RBh7WdfPLJARJtiXTqqaeuhefb3/62/fznPw/+f/fdd9u+++7bDAiREQIdhgAOwA7TlFSkGgHN5LqDOBQRIUddreTC17V/nyIC4ybtK/j1r389yK5ZY80eV0ua7XJLF3WdIgJJECgiAV/6E6fu//rXv4LZZUVhbL/99sGeZiQIFJ2Abx3SRJYc42+++aZdc8017S9j4oQDsOi9BfkqEfClQ3L0ffWrXw1E0IFUN998c3DYVKWkrVu0tcx5551Ho0Gg0AR86Y8gyD772te+FkSd6xRg/a5DdDbeeOPgFGAdrjN16tSAl5zoP/7xjwvNDuEg0BEJ4ADsiK1KndYgsHjxYttggw2C/x199NGmyIhaacMNNwwOAEm6L0X4FOE77rjDDjjggKrF6HsX9adZMG3SToJAEQn40p+oun/88cf22c9+NjhBW0lRgC7iNupavodAIwn41qETTzwxOO1XJ93PmjVrjT1mcQA2sidQdloCvnQovDpDy3zlOJEtpxO0d9hhB9PSRW098Z3vfMd0kIGSnBmKTCdBoKgEfOlPuP4KdJg0aZI99dRTa2EZP368aU9CIv+K2mOQq6MTwAHY0VuY+gWHbHz6058OSIT3QqqGRnl1jfbzmzNnTmyCF198cbBUROmee+6xz33uc1Wv/cc//mH77LNP8L2u+/73vx+7HDJCwCcBX/oTVaeTTjrJrr/++iDbxIkTbfLkyVGX8D0ECkHApw7NnDkzWJbYrVu34GRFOS3CCQdgIboEQiQk4EuHFI30gx/8oF26/fbbzzRhK30KJ50UPG7cOFu9enUQbfuf//yHw9wStinZ/RHwpT+uRjoEUZGx0p1Vq1atVVE51w8//PBgGbAOQyRBAAJ+CeAA9Mub0hpAwNfMFxGADWhciqw7AV/6U6siWmal2WKlsWPHBiea6kAfEgSagYAvHVKUrPa51Z5/iip3eyzhAGyGXoKMtQj40iHpjPYnc0mHGYwaNaqiaNrGxR1eoO0pyp3ttCgEikLAl/6ovg888ECwOkMRssOGDQuW+MqRrv3VtS2FVm/Iyf7OO+/Y0KFD7W9/+1twWj0JAhDwRwAHoD/WlNQgAr72vmAPwAY1MMXWlYAv/alWCe1h5jaR3mqrrQLjcvDgwXWtMzeHQJ4EfOmQItAVUb7pppuaIjAqOcmJAMyzZbmXLwK+dCg83ujQBG0HUy0pIl2R6Ur6/YQTTvCFg3IgkIiAL/3RJJRWTy1cuDA4LVvLf/WzPClidsyYMcESe+3r7LZ2SVQpMkMAAqkJ4ABMjY4Lm4mAHAZvv/12EB3BKcDN1HLIWgQCPvSnUj3/8Ic/2LHHHhsss9JMspZdbbLJJkVAggwQSETAhw716tXLVq5caccff7ztv//+FeX7xje+YUuWLAmc6L/61a+CPNojt9aWFYkqSmYI1ImADx26/fbbTYfFKSnyTxGA1dJdd93VvtezotS1LyAJAkUl4EN/brvttmBpr9JPfvKT9pUblZiEt3XRe5nez0gQgIAfAjgA/XCmlAYT2GuvvYLIIUVEvPfee9a9e/eKEunU3z322CP4TtEUF110UWzJ582bF8x8KelUX0UEVkv6/tprrw2+1nXDhw+PXQ4ZIeCbgA/9Ka+TlolMmDAh2D9Gp8dJf51++a4/5UEgKwEfOqRTSdMk7WV23333pbmUayDgjYAPHVqwYEFwUraSlvRqaW+1FHYWaguYc845xxsLCoJAUgI+9OeSSy6x888/PxAt6jDE8KopHc6oQxpJEICAHwI4AP1wppQGE9D+YZqhVXrkkUds1113rShRePDS7G61KIpKF7e2tgbRSa+//rppqaKWYFVL2jT6+eefDza/1ea8aV/cGoyV4jsJAR/6E0apQ3QUhaHlJOuvv77df//97BHTSfpaR62mDx1KO47gAOyova5j1cuHDomYos1feeUVGzhwYDBhXE2vFEH7zW9+M4B888032zHHHNOxgFObDkXAh/6E99CcNm2aHXLIIVUZhvVHe2lqwpcEAQj4IYAD0A9nSmkwgccee6zd6VctOk/LDLfbbrvAcTdo0KBg75cePXokkvy0006zq6++OrhG0YS77bbbWtfLAbn77rsH/1f+q666KlEZZIaAbwK+9Ef1euihhwLH+7Jly2ydddYJTtTWHjEkCDQzAZ86VIsTewA2cy/q3LL70qGzzjrLrrjiigD23Xffbfvuu29F8OPHj2+PnJXDUHtvkiBQVAI+9GfKlCl2xBFHBAjOPfdcu/TSS6viUD7lV9KJ9aNHjy4qOuSCQIcjgAOwwzUpFapGwIW/a/nvzJkz251wLn/4FN8LLrjALrzwwjVupSVSMviUJk6caJMnT16rqBdffNG22WYba2lpCTa4VTl9+vRpz7d8+XKTHNrwVnI8++yz9pnPfIZGg0DhCfjQH+0DIx1T1IWW6ysKd8899yw8GwSEQBwCPnQoSg4cgFGE+L7IBHzokJx5W265ZXBAwfbbbx/sPatowHC66aab7Ljjjgv+pWj16dOnFxkbskEgIFBv/ZHtppVNH330kQ0YMMBmzZoV6FB50vJgRQcq8EL5pXNdu3allSAAAU8EcAB6Ak0xjSeg06jkTJATrn///sHmtHI26G/tP+H25Bs5cmTgoNPgFU5xHIDKr/0vtJRYSZtIn3feecHeZXPnzg1mwySHyzdp0qTGg0ECCMQgUG/9kX5o/0136qIiMKpFXjhxdXiBPiQINAOBeutQHAY4AONQIk9RCfjSofCEsJyBsuO0J+DSpUvt1ltvDVZ6aKJXjkHZi0zkFrXHIFeYgA/90Un02kNdSe9aOnhqv/32s3XXXdfefPNN00Eh1113XbC/s9KNN94YHPZGggAE/BHAAeiPNSUVgID2pNBAIyOuUpLzb8aMGTZixIi1vo7rANSMlk63uuGGG6rW+IQTTggcjsx4FaBTIEJsAvXUH0XU6vTSJKlSpG6S68kLAd8E6qlDceqCAzAOJfIUmYAvHdJkriZttb9zpaTJp6lTp661mqTI7JANAvXWH+mLltFfeeWVVXVHraAtlhQEweE59EkI+CeAA9A/c0psMAGd8qaBSY6+1157zXr27Bk4/I488kg744wzrG/fvhUljOsAdBfrhDg5+WbPnm1LliyxwYMH29ixY4MTgg888MAGU6B4CKQjUC/9wQGYrj24qvkI1EuH4pDAARiHEnmKTsCXDmkvZ0X76RT6RYsWWe/evU0TxYceemgQ2aR9akkQaDYCPvRH+/pdf/31wRJ6ladlwYoI1PuWDp7Su5B0iQQBCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgngAPQP3NKhAAEIAABCEAAAhCAAAQgAAEIQAACEICANwI4AL2hpiAIQAACEIAABCAAAQhAAAIQgAAEIAABCPgn8P8BYF+4TevfhQ4AAAAASUVORK5CYII=\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_result(output)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "太多 0 值， 表现不是很好"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 去掉 relu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:43:53.228376Z",
     "start_time": "2020-04-20T03:43:53.224619Z"
    }
   },
   "outputs": [],
   "source": [
    "def gcn_layer_norelu(A_hat, D_hat, X, W):\n",
    "    return D_hat**-1 * A_hat * X * W"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:44:18.002748Z",
     "start_time": "2020-04-20T03:44:17.993997Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[-1.22446848e-01,  4.18804025e-02],\n",
       "        [-2.77003343e-01,  2.86586035e-01],\n",
       "        [ 1.06350683e-01, -1.18372878e-01],\n",
       "        [-3.79651464e-01,  3.50003929e-01],\n",
       "        [-1.85614233e-01, -3.95335737e-02],\n",
       "        [-1.71583272e-01,  3.35748866e-02],\n",
       "        [-1.99997652e-01, -7.31914280e-04],\n",
       "        [-5.10585270e-01,  5.01679223e-01],\n",
       "        [ 2.13255314e-01, -1.13189231e-01],\n",
       "        [ 2.57484459e-01, -1.86635069e-01],\n",
       "        [-1.90002284e-01, -7.50235318e-02],\n",
       "        [-1.33443821e-01,  4.77932273e-02],\n",
       "        [-3.63178848e-01,  3.50588991e-01],\n",
       "        [-2.71140755e-01,  2.80847376e-01],\n",
       "        [ 8.27856192e-01, -5.58365912e-01],\n",
       "        [ 1.00480066e+00, -5.90038447e-01],\n",
       "        [-1.58852760e-01, -9.26604434e-03],\n",
       "        [-3.82739209e-01,  4.08886097e-01],\n",
       "        [ 1.01434999e+00, -7.34534388e-01],\n",
       "        [-8.72125419e-02,  1.85080760e-01],\n",
       "        [ 7.21066523e-01, -3.38618342e-01],\n",
       "        [-5.34852885e-01,  5.87137629e-01],\n",
       "        [ 9.56359451e-01, -6.55037162e-01],\n",
       "        [ 8.35999685e-01, -6.48972999e-01],\n",
       "        [ 1.02536654e+00, -7.54584653e-01],\n",
       "        [ 1.08745392e+00, -6.63643497e-01],\n",
       "        [ 2.99537787e-01, -2.73471825e-01],\n",
       "        [ 6.82890768e-01, -4.66603206e-01],\n",
       "        [ 6.08610786e-01, -5.59432144e-01],\n",
       "        [ 5.65300194e-01, -4.03541292e-01],\n",
       "        [ 2.35449458e-01, -1.12090722e-01],\n",
       "        [ 6.19745984e-01, -4.03040083e-01],\n",
       "        [ 1.14544236e+00, -8.21095446e-01],\n",
       "        [ 1.00213662e+00, -7.83946462e-01]])"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "H_1 = gcn_layer_norelu(A_hat, D_hat, I, W_1) # 单位阵 (one-hot) 作为初始特征\n",
    "H_2 = gcn_layer_norelu(A_hat, D_hat, H_1, W_2)\n",
    "output_2 = H_2\n",
    "output_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-20T03:44:33.653852Z",
     "start_time": "2020-04-20T03:44:33.470348Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
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