{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br />\n",
    "\n",
    "<div style=\"text-align: center;\">\n",
    "<font size=\"7\">数値計算試験問題</font>\n",
    "</div>\n",
    "<br />\n",
    "<div style=\"text-align: right;\">\n",
    "<font size=\"4\">2024/07/10 実施</font>\n",
    "<br />\n",
    "<font size=\"4\">cc by Shigeto R. Nishitani 2024</font>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " # 1 簡単な行列計算:25点 \n",
    " \n",
    " 次の行列\n",
    "  $\n",
    "  A = \\left(\\begin{array}{ccc}\n",
    "    0 & -2 & 0 \\\\\n",
    "    1 & 3 & 0 \\\\\n",
    "    -1 & 0 & 3\n",
    "  \\end{array}\n",
    "  \\right)\n",
    "  $\n",
    "  の固有値と固有ベクトルを求めよ．\n",
    "  \n",
    "  また，固有ベクトルで構成される対角化行列$P$ を用いて，ドット演算 により$P^{-1}.A.P$が対角化されることを確かめよ．\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "np.set_printoptions(formatter={'float': '{: 0.3f}'.format}) \n",
    "\n",
    "aa = np.array([[0,-2,0],[1,3,0],[-1,0,3]])\n",
    "print(aa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.+0.j 2.+0.j 1.+0.j]\n",
      "[[ 0.000 -0.577  0.816]\n",
      " [ 0.000  0.577 -0.408]\n",
      " [ 1.000 -0.577  0.408]]\n"
     ]
    }
   ],
   "source": [
    "import scipy.linalg as linalg\n",
    "l, PP = linalg.eig(aa)\n",
    "print(l)\n",
    "print(PP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 3.000,  0.000,  0.000],\n",
       "       [ 0.000,  2.000, -0.000],\n",
       "       [ 0.000,  0.000,  1.000]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linalg.inv(PP).dot(aa).dot(PP)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2 Gauss-Seidelの収束性:25点\n",
    "\n",
    "初期値を$[0,0,0]^{t}$として，\n",
    "$A(tt)x=b$ \n",
    "にガウス・ザイデルによる連立一次方程式の反復解法プログラムを適用する．\n",
    "ただし，\n",
    "\\begin{equation}\n",
    "A(tt)=\n",
    "\\left(\n",
    "\\begin{array}{ccc}\n",
    "1&tt&tt \\\\\n",
    "tt&1&tt \\\\\n",
    "tt&tt&1\n",
    "\\end{array}\n",
    "\\right)\n",
    ", \\, \n",
    "b=\n",
    "\\left(\n",
    "\\begin{array}{c}\n",
    "4 \\\\\n",
    "4 \\\\\n",
    "4 \\\\\n",
    "\\end{array}\n",
    "\\right)\n",
    "\\end{equation}\n",
    "\n",
    "である．\n",
    "$tt=0.25,0.5,0.75$ に対して有効数字6桁の解を得るための反復回数を求めよ．\n",
    "\n",
    "(E.クライツィグ著「数値解析」(培風館,2003), p.89, 問題2.3-9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 [4.   3.   2.25]\n",
      "1 [2.6875    2.765625  2.6367188]\n",
      "2 [2.6494141 2.6784668 2.6680298]\n",
      "3 [2.6633759 2.6671486 2.6673689]\n",
      "4 [2.6663706 2.6665651 2.6667661]\n",
      "5 [2.6666672 2.6666417 2.6666728]\n",
      "6 [2.6666714 2.666664  2.6666662]\n",
      "7 [2.6666675 2.6666666 2.6666665]\n",
      "8 [2.6666667 2.6666667 2.6666666]\n",
      "9 [2.6666667 2.6666667 2.6666667]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.set_printoptions(precision=7, suppress=True)\n",
    "\n",
    "tt=0.25\n",
    "A=np.array([[1,tt,tt],[tt,1,tt],[tt,tt,1]])\n",
    "b=np.array([4,4,4])\n",
    "n=3\n",
    "x0=np.zeros(n)\n",
    "x1=np.zeros(n)\n",
    "\n",
    "for iter in range(0, 10):\n",
    "    for i in range(0, n):\n",
    "        x1[i]=b[i]\n",
    "        for j in range(0, n):\n",
    "            x1[i]=x1[i]-A[i][j]*x0[j]\n",
    "        x1[i]=x1[i]+A[i][i]*x0[i]\n",
    "        x1[i]=x1[i]/A[i][i]\n",
    "        x0[i]=x1[i]\n",
    "    print(iter,x0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 [4. 2. 1.]\n",
      "1 [2.5   2.25  1.625]\n",
      "2 [2.0625   2.15625  1.890625]\n",
      "3 [1.9765625 2.0664062 1.9785156]\n",
      "4 [1.9775391 2.0219727 2.0002441]\n",
      "5 [1.9888916 2.0054321 2.0028381]\n",
      "6 [1.9958649 2.0006485 2.0017433]\n",
      "7 [1.9988041 1.9997263 2.0007348]\n",
      "8 [1.9997694 1.9997479 2.0002413]\n",
      "9 [2.0000054 1.9998766 2.000059 ]\n",
      "10 [2.0000322 1.9999544 2.0000067]\n",
      "11 [2.0000194 1.9999869 1.9999968]\n",
      "12 [2.0000081 1.9999975 1.9999972]\n",
      "13 [2.0000027 2.0000001 1.9999986]\n",
      "14 [2.0000006 2.0000004 1.9999995]\n",
      "15 [2.0000001 2.0000002 1.9999999]\n",
      "16 [2.        2.0000001 2.       ]\n",
      "17 [2. 2. 2.]\n",
      "18 [2. 2. 2.]\n",
      "19 [2. 2. 2.]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.set_printoptions(precision=7, suppress=True)\n",
    "\n",
    "tt=0.5\n",
    "A=np.array([[1,tt,tt],[tt,1,tt],[tt,tt,1]])\n",
    "b=np.array([4,4,4])\n",
    "n=3\n",
    "x0=np.zeros(n)\n",
    "x1=np.zeros(n)\n",
    "\n",
    "for iter in range(0, 20):\n",
    "    for i in range(0, n):\n",
    "        x1[i]=b[i]\n",
    "        for j in range(0, n):\n",
    "            x1[i]=x1[i]-A[i][j]*x0[j]\n",
    "        x1[i]=x1[i]+A[i][i]*x0[i]\n",
    "        x1[i]=x1[i]/A[i][i]\n",
    "        x0[i]=x1[i]\n",
    "    print(iter,x0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 [4.   1.   0.25]\n",
      "1 [3.0625    1.515625  0.5664062]\n",
      "2 [2.4384766 1.7463379 0.8613892]\n",
      "3 [2.0442047 1.8208046 1.101243 ]\n",
      "4 [1.8084643 1.8177195 1.2803621]\n",
      "5 [1.6764388 1.7823993 1.4058714]\n",
      "6 [1.6087969 1.7389987 1.4891533]\n",
      "7 [1.578886  1.6989705 1.5416076]\n",
      "8 [1.5695664 1.6666195 1.5728606]\n",
      "9 [1.5703899 1.6425621 1.590286 ]\n",
      "10 [1.5753639 1.6257626 1.5991551]\n",
      "11 [1.5813117 1.6146499 1.6030288]\n",
      "12 [1.586741  1.6076726 1.6041898]\n",
      "13 [1.5911032 1.6035303 1.6040249]\n",
      "14 [1.5943336 1.6012311 1.6033264]\n",
      "15 [1.5965818 1.6000688 1.602512 ]\n",
      "16 [1.5980644 1.5995677 1.6017759]\n",
      "17 [1.5989923 1.5994238 1.6011879]\n",
      "18 [1.5995412 1.5994532 1.6007542]\n",
      "19 [1.5998444 1.599551  1.6004534]\n",
      "20 [1.5999967 1.5996624 1.6002557]\n",
      "21 [1.6000614 1.5997622 1.6001323]\n",
      "22 [1.6000792 1.5998414 1.6000596]\n",
      "23 [1.6000743 1.5998996 1.6000196]\n",
      "24 [1.6000606 1.5999399 1.5999997]\n",
      "25 [1.6000454 1.5999662 1.5999913]\n",
      "26 [1.6000318 1.5999826 1.5999891]\n",
      "27 [1.6000212 1.5999923 1.5999899]\n",
      "28 [1.6000134 1.5999975 1.5999918]\n",
      "29 [1.600008  1.6000002 1.5999939]\n",
      "30 [1.6000045 1.6000012 1.5999957]\n",
      "31 [1.6000023 1.6000015 1.5999972]\n",
      "32 [1.600001  1.6000014 1.5999982]\n",
      "33 [1.6000003 1.6000011 1.5999989]\n",
      "34 [1.6       1.6000008 1.5999994]\n",
      "35 [1.5999998 1.6000006 1.5999997]\n",
      "36 [1.5999998 1.6000004 1.5999999]\n",
      "37 [1.5999998 1.6000002 1.6      ]\n",
      "38 [1.5999999 1.6000001 1.6      ]\n",
      "39 [1.5999999 1.6000001 1.6      ]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.set_printoptions(precision=7, suppress=True)\n",
    "\n",
    "tt=0.75\n",
    "A=np.array([[1,tt,tt],[tt,1,tt],[tt,tt,1]])\n",
    "b=np.array([4,4,4])\n",
    "n=3\n",
    "x0=np.zeros(n)\n",
    "x1=np.zeros(n)\n",
    "\n",
    "for iter in range(0, 40):\n",
    "    for i in range(0, n):\n",
    "        x1[i]=b[i]\n",
    "        for j in range(0, n):\n",
    "            x1[i]=x1[i]-A[i][j]*x0[j]\n",
    "        x1[i]=x1[i]+A[i][i]*x0[i]\n",
    "        x1[i]=x1[i]/A[i][i]\n",
    "        x0[i]=x1[i]\n",
    "    print(iter,x0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3 家の価格\n",
    "\n",
    "回帰モデルとして，家の売却価格の予測を行う．家の特徴量として，\n",
    "x: 家の面積\n",
    "y: 寝室の数\n",
    "をとる．\n",
    "z: 家の売却価格\n",
    "とすると，５軒の家の表は次のようになる．\n",
    "\n",
    "| 家番号|x面積|y:寝室数|z:売却価格|予想価格\n",
    "|---|---|---|---|---|\n",
    "|1 |0.846|1|115 |120.52\n",
    "|2 |1.324|2|234.5\n",
    "|3 |1.150|3|198\n",
    "|4 | 3.037|4|528\n",
    "|5| 3.084|5|572.5\n",
    "\n",
    "2次元曲面のフィッティングを参考にして，\n",
    "$$\n",
    "z = a_0 + a_1 x + a_2 y\n",
    "$$\n",
    "の平面にフィッティングして，予想価格を求めよ．\n",
    "(ステファン・ボイド，リーヴェン・ヴァンデンベルグ 「スタンフォード ベクトル・行列 からはじめる 最適化数学」 講談社 ２０２１年, c2 pp60-2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "z = np.array([115, 234.5, 198, 528, 572.5])\n",
    "x =np.array( [0.846, 1.324, 1.150, 3.037, 3.084])\n",
    "y = np.array( [1,2,3,4,5])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection=\"3d\")\n",
    "ax.scatter(np.array(x),np.array(y),z) \n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "array([-38.2039269, 166.7913287,  17.6228467])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-38.2039269, 166.7913287,  17.6228467])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pprint import pprint\n",
    "import scipy.linalg as linalg\n",
    "\n",
    "n = z.size\n",
    "n_j = 3\n",
    "bb=np.zeros([n])\n",
    "A=np.zeros([n,n_j])\n",
    "for i in range(0,n):\n",
    "    A[i,0]=1\n",
    "    A[i,1]=x[i]\n",
    "    A[i,2]=y[i]\n",
    "    bb[i]=z[i]\n",
    "\n",
    "c, resid, rank, sigma = linalg.lstsq(A, bb)\n",
    "pprint(c)\n",
    "\n",
    "Ai = linalg.inv(np.dot(np.transpose(A),A))\n",
    "b = np.dot(np.transpose(A),bb)\n",
    "np.dot(Ai,b)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       " * https://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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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/X1xk3fBPpvLsdOGWvp+vbRELntlvlTVBbITbz4gW+46Zor0y/YlhEKbv7pCLnzpBymtqve/NrJvptx99BQZnO8rvYPv+9Nfr5B7PlxsmSNchy/ff5y4kn0Jn2DVRcmiTTWB+rq45t3HTFEZkdEwr0tfma9cknWbPCxP7jhysr9kUOQ0O/5kcnKy4E8ksbwUtx3zZQ8S6AkCFLc9QZnXIIFeIkBx20vgE/Sy1dXVUl5eLlVVVRS2CXoGuOyuI4BswytKaiwZiZOTRLn3akuovhr6Li+uFq9R6xY3eCjhk9NqNdV9S6rqZU2F15IQKtfjUuMmJwVuC8trGgTxs0ZJXEENW5T7QXysFrary2ultDogfvE6rLFasOLf5TX1sqrMaxkLdXMxFhJHoWGM1eXWeeVlpMqQfI9lXl1H2Hmk1NRUyc/PV38gdENtFLehkmI/EuheAhS33cuXo5NArxKguO1V/Al18bKyMlm3zmpdSigAXCwJdCGB5pYWlfHYDJuF7kTGYVOA4pJOffF6qivJbzU1RXBjU4tlpq6UJIu7Mt6EWLb3g6BNdSX7a0jCYlvfBA8N68IxRy1+g41lv6bT9Zzm1YWIOxwqOztbBg8eHLIVl+K2Q6TsQAI9QoDitkcw8yIk0DsEKG57h3uiXRUW25UrfRlUMzIyJC8vTzweT8g3hYnGi+slgfYIVNY2CKyhEK26eVJTZGiBp41YrfQ2yOoKa198JtftksH5Gf7PI0RgVXmtxQ05SZKUhRXWUd1wzXUVtVLuDbgO473+2W4pyEz1f6chRleW1Ejd/2dQ1s2VlCRDCzMEc0ULNtaAHIzlq5nb3Nyi4oMragPX880rXfIyAnV1e+rEgFNFRYWUlJSoSw4YMEBZcENpFLehUGIfEuh+AhS33c+YVyCBXiNAcdtr6BPqwqtXr5ZNmzYpYTts2DCK2oTafS62qwjAErqxsk7WbQqU+cHYeZ40n2tuq/suXgvWF++5kpNkbP9scbUmj6pvbJLlJTVSa2RZhmV1eEGmZLld/umj1A/coKvrA/GusBLb3aARD4t+jYbJFkmtRhRmSJrLJ2wx1srSGouYxlhwQ9Zu0k7XS0GfwgzJdgcEd1fxDWecNWvWKJGbmZmpftNCaRS3oVBiHxLofgIUt93PmFcggV4jQHHba+gT5sK4yV60aJGKsR00aJDk5gayrCYMBC6UBDpJABbMVeVeFZtqNlg5EbtqJjgK1ld/DgJSWz2dhGi6yydE040syxC+y0uqlSu0bsisjH6etIAADsTOBqzKWekuFdub0hqfCjG9rLhG1bLVDUIbY2W0jlWnrmfto67XJ9Nv+e0k0k59HHkDioqKFPfNN988pAd2FLedQs4Pk0CXEaC47TKUHIgEoo8AxW307Um8zaipqUmJW7TNNttM0tJ63pUw3phyPYlFIJA4ymYxzfdIrs0116mvSQsWT4hIiDII0aIyJGiyClGIX23VxWerahtkRWmNNBmZo+BaPKIwU8XYogWzFMO9eFBeIOFTcKtupooXRvP1qZZG+/X6ZLaJ/e2tk1BfXy9Lly5Vlx8zZoy4XAGBH2xOFLe9tVu8LglYCVDc8kSQQBwToLiN482NkqU1NDTIkiVL1GxGjx4tyDTKRgIkEBoBb32jsmBCtOrmZDHFeyj1s6K4WiVx0g3xqS3iE69w+x3bP0sJxA2VdbLe5t5sF6L4TGl1nawuq/WPgddy3KnKFVknhULs7Joyr5TarMoDcz3SJyvNb9WsaBXTZqwwxPawAo/fquskuO3XC41c9/aK5HeN4rZ794Sjk0CoBChuQyXFfiQQgwQobmNw02JsypHcBMbYEjldEugWAhXeeikqRXmcgGUVbrtw8YVANdsmb4OKYTX7oo8piiE2CzPTVMmdcq+9NI9ViMISi9hexPiarW9WugzIdfsFa7DYWTMOF2MVV9WpxFBmM8W0svxW1alkVWYrzEqXQcb1ugV0BING8rtGcRsBaH6EBLqBAMVtN0DlkCQQLQQobqNlJ+J3HpHcBMYvDa6MBDomEG7iqOKqellb4bUMDItoVV2j3+VYuxHDvbjGlhDKTOKEQRCzW1RWIxVGRmRYgAfluQViUzfEzC7vIHZWWXXLvY51bvtk+WKFsV7Ur21bC9cquDsm13M9Ivldo7jtuf3hlUigPQIUtzwfJBDHBChu43hzo2RpkdwERsnUOQ0S6HECwZJB9c9xSz974qggwrFftlsJWIhbNAhTlAmCVdR0WXZyb4alF4mjvPWBZE9wP4YANjMUhxI729Tsy66s54G5qOzKRqww4nhhcUZ5I918GZg9kuuJ3vj8SH7XKG57/OvEC5KAIwGKWx4MEohjAhS3cby5UbK0SG4Co2TqPT6N5cuXy8iRI9V1zSQ/ThPR2XGXLVsmI0aM6NRc8fkVK1ZIV4ylJ/LTTz/JlVdeKV999ZWUlpaqbNl33nmn/O1vf+vUXKP9w5988onsvvvusuuuuwr+Hk4LJ3GUKpNTWqOSL+mGMwHhiDxMq8pq/K/nelKlqrZRmsy6uGmtCaEM92YIWghb05UZSZ6QOAqlfHRziou1x84iqzLGMssLuZJbMyKn+5IvhdInHH492TeS3zWK257cIV6LBIIToLjl6SCBOCZAcRvHmxslS4vkJjBKpt7j04gXcVtdXS3jx49Xgnnq1KmqVEpKSor86U9/kn322adHuHZGZHZmgpFeN5zEURCMyCZcZ5TlgXBELC7E6KL1lf7MxrC6whociNoVgdgdmp9hqYvrFLNrj+/FAxenRFSI40VGZP3ABVZjJMGCANcN5YVG9gnUuXVarypB1CdD8N9ob5H8rlHcRvuucn6JQoDiNlF2mutMSAIUtwm57T266EhuAnt0glF0sd4Styhpgn1CqaauyGb98ccfyx577CE77LCDfPnll71COFKR2dnJRnJdxLYW2ZJBZaSlyHCU2rEljoL7Ltx4zbI8sKrCugphi/fstXDNNcFluX9OoC4uBGtJdb2sLfdaBHCeJ02G5Hv8Ahixs6vLvFLWUUZkh7Wgzu2wwgyBAEfbhDWUWJNfZaIWrq0EUWf3ojs/H8nvGsVtd+4IxyaB0AlQ3IbOij1JIOYIUNzG3JbF3IQjuQmMuUV20YR7S9x20fT9wzz99NNywgknqD9PPvlkVw8f0niRiMyQBu6gUzjXDSdxFC5bUlUna8qDl+WB8F1WXO04Q1hVh+R5JD8zEMeK62O8kmprRmR7fK+TCzTiYu2JqIor62SNLbFVfkaaDIZITvLdTjqtwd6nK/ahu8eI5HeN4ra7d4Xjk0BoBChuQ+PEXiQQkwQobmNy22Jq0pHcBMbUArtwsp0Vt9otFKLlxRdflLvuuksWLFig3EWnTZsm119/vey0005tZhws5na33XaTTz/9VGCJzc7OVp+HJRZux3A1Pvfcc+WUU07xj6eFnROS4cOHC9anG8a477775OWXX5bffvtNWY5HjRolRx55pFx00UWSlZXlSPbbb7+Ve+65R7744gtZt26dmhfmf8ABB6j5FBYWip630wD2WFjN6vHHH5fvv/9eKisrpX///rLvvvuqmOFg8cyvv/663HbbbfLjjz8qa/e2224rV111lYqVDiXmNpzEURgTZXRQTsdsfbPTZUCOrywPLLmL11daEkbpvq7kJGUFhnVUNyR7WlnqtSRyUgI43yMQm7rVNSAOt0aQGVk3WJPhAg23ZTQlkitqlXA1G+aGOeqMyE6lhfrluKW/LVFWF36lum2oSH7XKG67bTs4MAmERYDiNixc7EwCsUWA4ja29isWZxvJTWAsrrMr5txV4vbqq6+Wf/zjH0rIDhgwQObPny8LFy6UtLQ0leRo++23t0y3I3F76aWXyh133KEE7YQJE2TlypUqURTa7bffLhdeeKH6O67xz3/+U5YsWaJEMNyctZju06eP6ou2atUqJR5/+eUX6du3r0yZMkXcbrfMnj1b1q5dK1tttZWaZ35+vmWeN998sxKcEFOI6cVcIEYXLVqkrgkRDmGLOeDz7733nhKq++23n3+ccePGyWWXXab+jbN5zDHHyKuvvioej0cJVPRHMiysBdd///331etmu/XWWwVM0OB6DeGOhwhYzznnnCN33313uwmlwkkcFUyEDs7zCOrE6ga3YtSJtTenONZ6lPApqWmT7AmC1RTAvozI1dKIDFWtzXSBxksQ1XCphquxbjqxVV6rSA5WWggWXXMNXfEd6qkxIvldo7jtqd3hdUigfQIUtzwhJBDHBChu43hzo2RpodwEImuqmd01SqYe8jSG5PsS+XS2dZW4LSgoUKJsm222UVNCpuIzzjhDHnnkEdlrr71k1qxZlql2JG7R+bHHHpOTTz7Z/7lnn31Wjj/+eMnJyVGCNCMjw/8eXJFPOukkR7dkCNMdd9xRvv76azn77LMFQhHCEs3r9cpf/vIXwdh2l+bXXntNDjvsMGXRfe655+Sggw6yrAHCeODAgTJkyBD1eijuwRC5t9xyi+yyyy7yn//8x/9ZfP7f//63EqoQ6BC6LpfPSjlv3jyVJAsCDqLYnAcsuZdcconqFyxbcrDEUaYlVC/MqY4sEkTBCos4Vt2QwGnJhqo2x88e64oOTiV8nAQwYmtXlXktWbtz3KkytCBDMAe0htaMyN6GgFXXbiWGSzOEtFlbV62hIEOy3Kmd/cr02udD+V2zT47itte2ixcmAQsBilseCBKIYwIUt3G8uVGytFBuAn/fWCV7/OvTKJlx+NP46MJdZVRfZzfacEbrKnF77733KuFotvXr1ysrbnp6urJ2momjOhK3hx9+uMycObPNUrbcckv59ddflesyBKJu7Ynbd999V/bff3+ZPn26su4mtyYZ0p+FuzLck1E+aMOGDX7r7eTJk5UL8AMPPKCEeketI3GL8SGEkcUZCbX69evXZsgDDzxQ3n77bfnvf//rF7Fww4YLc7B4Ylh5586d6yhuw0kc5WQ1dRKhsIouXFcpjc2BzMRYCDIYD8wLxLriNacSPkoAG4mcgmVE7pOVLgNzfS7QaE5lg9T8CjMkvbVsELI6oxwQHl7plpaSLCP6WEsLdbSX0fh+KL9rFLfRuHOcEwmg9jcbCZBA3BKguI3brY2ahYVyE0hx69uurhK3werVwqJbVlamLK0Qurp1JG6feOIJOfHEE9ucKVhSYVF9/vnnlXtvKOIW1lBYRWHlRGytU0P87DvvvKPcilE6CLG1sMpCkFdUVPgtve0d8o7E7SuvvCJHHHGEitV96623HIfSltjLL79cbrrpJtVn9OjRSgzD+g0ruL0hzvn888+3iNtwE0eVVtfLamQvNurSOllhIWyXbKyyuBdjPijLA3FrxmBvrKwTxLyaDS7B6KuTPTllRMZNIEQyxK1ujtmO01wqDtfVmt0Z4hzC1szq7HGorRs1P1RhTiSU3zX7kLTchgmZ3UmgmwhQ3HYTWA5LAtFAgOI2GnYhvucQyk0gxa3vDKAurE5gBFdiLU7sJwSiR1s8IYgR84mm+zc1NbWxiOL9YCK2I3H74YcfqtI+9gbB+9RTT4ld/LZnudXCNZRTD/fk4447TpBECpZeuAgjtjaU1pG4NV2IOxrv1FNPVS7daIgNrqurU/PAfOwNiaYOPfRQv7gNN3GUU9Klwqx0GWRYTXFNxO0iMzKso7rhhm1YYaaqY6tbqCV8VEbkkhqprm/0f9YpI7Iv27GtbFBGa9mgVquuk4XY7tLcEfNofz+U3zX7Gihuo31XOb9EIUBxmyg7zXUmJAGK24Tc9h5ddCg3gYy59W3Jxo0b/e6xcB0OljEY7yHWFa24uFhlCEYzLXVOmxypuNWJmuxjRiJukdwJFlnEpAbLRKyvA1GJhFTfffedbLfddl0qbpF0ChZZJMmCcG6vYQ6YC1o44nbWhx8pwWjGm0IwDs33SK6RkRjjOiZmkiQZmOe2WE3R18klGK/DvVgnccK/gwlWxM2aAtiXEbla6gz3YWREhouxx8iI7JSx2SwbFMxCbXdp7tEfoG4d/p/FAAAgAElEQVS6WCi/axS33QSfw5JAJwlQ3HYSID9OAtFMgOI2mncnPuYWyU1gfKw8/FXA4pqbm6tK7SBxEeJMnRpK1iBZFMQv3HS1FTcWxO1pp50mjz76qHJNPuuss0KCpN2Ske25vLy8S9ySkUBqxowZyjUZ5YhCbbDW/v777/LBBx/Innvu2eZj2i155112kYdeeFNZWHWzl9DRr+PhDsSlaYVF0iWI1Wxb0qVN3gZZWVojsMiaDS7GSGymG8ZCpuP2BCv6VrVmRLa4D6cidjZTUluTpDlmO7bVzcV81pR5pbSm3jIvuD2bLs2hco72fpH8rtFyG+27yvklCgGK20TZaa4zIQlQ3CbktvfooiO5CezRCUbZxZBsCUmXUDP1xhtvdJzdFVdcISiLg75IeKRbLIhbZBhGgqpg2YSDbcekSZNUSaMHH3xQTj/99A53DaWKkJUZf1AT196QYGvo0KGSmZkpiFHOy8vrcEx0QMZouGEjGzQSS9kbMinPmTNHtp2+ozz2ciCWNyMtRWU5hsA1G6y6yCYMK6tuyLwNcYmyO7rBKlpcVS9rK7xtrokxx/bP9mcxrqptlBWltnjXVN/1zazeZdX1ssoW29smI7JyV66WmvqA+7Mv23GmZLl9GZtRrggWaghl3ZxcmkMCHCOdIvldo7iNkc3lNOOeAMVt3G8xF5jIBChuE3n3e2btkdwE9szMovMqH330kUpUBPdXWBQRo2q2N998U4466igV94lY2N13393/diyIW8QST5s2TWUUhkhFoiYkujIbLLVYJ6y8umlRnJ2dLS+88IIS9maDoESSLF0KSMcvo24t6urqUj7mZ5D4CZbWnXfeWR5++GFBDVyzwYL+xhtvKAstxkHDvDF/WMvxnjkP1ALWNX9NcZvnSVVW1eTWEjr6GohNRbkd0wqLOrMok6MTM6GvsoqWewWJppwahHBOa5ytSkaFEj4SsOzaBSuE8vpNdbKh0ppgyu4+rLIdF1dLfTvC28nq7EpGRuQMyWh1aY7Ob1rnZhXJ7xrFbeeY89Mk0FUEKG67iiTHIYEoJEBxG4WbEmdTiuQmMM4QhL0cJDu69NJLVbbc8ePHqz9oP//8s/oDEYv6rBdffLFl7FgQt5gwxCZE4YIFCwRiFVZZWFFra2tl0aJF8ssvv6jYY4hcs91www1y7bXXqpcmTpyouCD++LffflMJnuyxwVtvvbVy795iiy2UGzfKICHGVnPD2YRr8ksvvaRKAsENHGWIwBGJulB6CA8RUO7IFL6wmsN6jn477LCDSuiFtWBvjjnxNHnu8Yf8llszJlWvJVi5nYKMNBmUby3fA4su3JBNq6jJJM+TJsMKM9RZcUpGZResKsFVmVfKvQGh7JQRubK2QVaW1EiT4f4MsYo4XC28nazOsDajT5orYHUO+wsQAx+I5HeN4jYGNpZTTAgCFLcJsc1cZKISoLhN1J3vuXVHchPY3bPTJVaCZSPu7uuHMj6SKCEuFS61KN2DhnI4SG6EGrawHtpbrIhbzBtC9rHHHlPCEsKwqqpKJcYaPHiwskYj4zCEo72Bxz333KO4IJkWYpRHjhypLNwoM2RagSFQ8ZAAdXjRFzHNTu7QsBJjLmCOfhDcYA0X40MOOUSNbdYFxpxgSb799tuVAIZVePxWU+Sksy9QFt1TjzpIiVsklDITPOFzPnFZI+XeBsvSUEMWQtQ8k75ETzVS12jNiKxtsnAPVu7ISUlSVFYjqKOrW5IkyaA8tyDTsm5BMyIXZgisu7qVVtfJ6rJai/UXCaiGGtZnp9hfp3JFoZz1WOwTye8axW0s7jTnHI8EKG7jcVe5JhJoJUBxy6PQ3QQiuQnszjlB2Oo/EBJaTESz0O1OHhy7cwScMhcHSxyF5FJO2ZOROEq7FevZOCV6ciUnSWNzwN0Yrs7ZblfbmNikJGXNNZNRKRfjkmqBG7FuvozImYL6s2g+d+Va2VBZZ4HSNztdBuS4/d+V4qo6WWsrB5SfkSaDbVbnzpGN7k9H8rtGcRvde8rZJQ4BitvE2WuuNAEJUNwm4Kb38JIjuQnsjilqa60WtrqOrF3cUux2B/34HBOW0iJb5mIIRZVp2JY4ytuaOMqePdkUl5qSipu1JXqCSzDG0NIWsbmofQvLrjlmGgRrH2syqqraBllRWqPKDenmgftwn8A8HTMiS5IMzndLQabP+ovvTkflgOJzp9uuKpLfNYrbRDkdXGe0E6C4jfYd4vxIoBMEKG47AY8fDYlAJDeBIQ0cRictaPUNOv6rxS3eg6Ctr69XLqXa/TSY6A3jsuwapwSC1XO1u+7q5TuJYIjV4YUZFhEcLG4WrsU1dY3ibfC5J+NsQthCaJrJqJzGDCXBFNyVIZLNerxwdTatv0HLAeV7BFbbRGuR/K5R3CbaKeF6o5UAxW207gznRQJdQIDitgsgcoh2CURyE9iVSLWwRYynKV61qNWCFzGfSCqELMWmizItu125G7E/FkQerKpltnquwRJHbayqk3UV1qzESAI1BC68RvZkWFURi2uPmx2Y5xaYa9cYJYAQH4uET2alW3tG5qAuxlnpMiA3cMad3JXt1l8nd2pVDqgwUxBnm4gtkt81ittEPClcczQSoLiNxl3hnEigiwhQ3HYRSA4TlEAkN4FdgdPuhoysukj8k5HhyyxriltcD+9D3Or39Rzs/Sh2u2J3YnOMYDGzEKptEke1tKiSPKGI4IZGWE6r/ZZZ0NGW03RXiixaX+m30EJUmu7F6Nsv2y39cwLJqJySVjklmHKK67W7VYdSDig2d7Nzs47kd43itnPM+WkS6CoCFLddRZLjkEAUEqC4jcJNibMpRXIT2FkETm7IWtzCMovyLugDMQvBC8GqLbcQt/amhTJe12IX68LnnNyYmZyqszsYfZ8PJ3FUsKzETiLYKRZXW07TXckqAdWmWmtmZU0H52xInkfyMwNuwaG4GOPzZdX1ssoW12uvh+sUq+vk+hx9u9X9M4rkd43itvv3hVcggVAIUNyGQol9SCBGCVDcxujGxdC0I7kJ7Mzy7MIWAgCvQdzCLdl83xQJWrRC3KJfew19IYbRz+PxdOjGTLHbmR3t/c+GkzgqWFZixNdCGJotWCyuriVbXlOvatw6NWROhlswEkvpFszFeHifTEECKf1wBtmQkRXZbPZ6uE7iN1hMce/vUM/PIJLfNYrbnt8nXpEEnAhQ3PJckEAcE6C4jePNjZKlRXITGMnU7W7IGMOs+wpxq1t6erqy2qLuqf5jWmfxOW3VxX+dxK4Wy5mZmUow6xaKGzPFbiQ73POfUYmjHGJmg4k8xMGuLKmRJuM8QFRChKa5Ag9MMK4qp2OLxVXldPJ8sbiwwC5aXyWNzYHSPf7z60Km4wyBy7JuzlZW37V15mYkn7K7SuMmb1Cex18PF3NzEr/2ckA9vxvRdcVIftcobqNrDzmbxCVAcZu4e8+VJwABitsE2OReXmIkN4HhThk35Mh+bJb30QISr3m9XiVi0SBGtQXXFJkQq1rUNjY2WqaA1+G+DKGrxS4st3gd49mbKXb1e7g+Xqcbc7i72zv9w00cVVJd36b2K0QwatEiTlY3CMw1ZV4ptSekknrpl5YkSXm5ImlpKrkUMh3bGxI4oS6uyyg1VFpdJ6vLaqXFSDFlF+DKVbq0RqrrAmc7GRmRjRq7oYjf3tmN6LtqJL9rFLfRt4+cUWISoLhNzH3nqhOEAMVtgmx0Ly4zkpvAcKar3YxRygcZkRFTm5bmi0HEtSFsdYMw1ZZWp4RSEL1arGqLLoSuFsZ6HPTTQhr927PEaqFbU1OjPpOVldVGOOMFM1EVLbvhnICu7xtu4qi15V6BuDVbv+x0QQZlcy8dBWZLiwypLpG8+hoRuMOnpEhVboH83uyrLWu2gow0GYQsy0m+W7NgpYPsVta6hiZV6qeu0feABw3WXLg/e1pdpTE3uEAjyZT/nNvEb9eTjt0RI/ldo7iN3f3mzOOLAMVtfO0nV0MCFgIUtzwQ3U0gkpvAUOZkj63FdbS4hXUUf8draBC8+Hc44tacg7YMa6HrJHZNN2YncVpdXe0obu1rdRK5FLuhnIiu6YPEUStKqqW+KeAODCHoFDPrJAidkjxhZk4C09XcJCMq1ktGS6ughJt8UrIsLBwmTa0CVq9qYK5bEBcb8EhokSKH0kGD8t1SmBkQxrDUIimV6d4MV+kRcFdudZWub2ySZcXti9+uoRs/o0Tyu0ZxGz/7z5XENgGK29jeP86eBNolQHHLA9LdBCK5CexoTk5Jo7SVFlZbiFBYSXXCJwjPTZs2RSxu7fPRCaXwuo7dNfvgunaxq8Vtdna2/QGT43L1GjEWBI3+g84Uux2dkMjeD5o4qiAgBPXIjmI12SeCzSRP6O8UD+turJcRVcWShlDcViHbKEmyJLOv1CcHYmmx13Adhpuxbo51Z9GvMEOy3YF+SEhVVOa1xITbMyLX1DfK8mKr+HW3il8zTjgyovH7qUh+1yhu4/c8cGWxRYDiNrb2i7MlgbAIUNyGhYudIyAQyU1gsMuYSaPQx3Qttrsgw3oLi60WghC3EIpwC9bC0R5za7old7RUxNyi6fHM5FROll19TfQPxY0Z5YqwJmRjhlC2i1qK3Y52KPT3w00cVVXbKCtKqy31Zn2CMEPSjCRPmIFTPGxOg1eGbtooKakuv7CtS0qRZRmFVmErIpv1zZIMe0bkYqtlWZcOwhz092JjZZ2ss2VELsxKl0G5ge+Ek5hHTC8EekoHGcNDpxufPSP5XaO4jc+zwFXFHgGK29jbM86YBEImQHEbMip2jJBAJDeBTpeyW2tNsYf3ENOqRSUEoU7cpMfqSNy2lyDKaT6muLW/j/mYMbuwIptNJ6bS/3USu9qtur3SRObnKHYjO6BOSZQwEuJlETdr3xsnsQpr6bACj0UQBouH7dNQIwMrNkiSy6Xia9GqUtJkhSdfuSSbbVRNiWSNGeUXwE7ZmO11Z4MlrBqY65E+WWn+9UD8rq0IxKPjugWZaSpzso7pjYxoYnwqkt81itvEOBtcZfQToLiN/j3iDEkgYgIUtxGj4wdDJBDJTaCTWIRY0FmPzSROEJEQttqqC7dkWGztLRRxi8/YEz4FW2Z74tZp/jqhlE5G1ZHYNcWtttziM06ZmPVY2pJNN+bQDmc4iaPAFqV7UMLHbPb6sHivqblFikprZFOtL+YbLUmSZFCeWwpXLRNBkrPUVCVuS10eWe3JM/Ic+/r3rSmXgU1ekbFjVb+S6jpZ01FG5OZmVYrInhRqqOHWHGwdA3Ld0teI6Q2NYOL2iuR3jeI2cc8LVx5dBChuo2s/OBsS6FICFLddipODORCI5CbQFGta0JnWWcStQsDBdRd/0FCqB7G2qGGLP/bWm+IWc9GWZcxdW3Z1gipt2d1qq62kqKhI3n77bdlpp51U3DAst6a4ta9Li12MBUEMca+zRa9atUquuOIK+eSTT2TDhg3KmnzuuefK3XffHddndfny5TJy5EgZPny44O9OLZzEUe2K1SzrWatvbFYJqbwNgczEKAWEuFkVD7tkiUh1tbQkJ8v6jHzZkG7Nno25pjc1ypiy1ZLscUvL2LHKvRiWVrPZMyI7JYVCuSC4SsO6i+a4jqQkGZrvkbwMX4ZxttAIRPK7RnEbGlv2IoHuJkBx292EOT4J9CIBittehJ8gl47kJtAUtPrv+C8stxBxsK5qKy5ELtyQtYAMJm51HdtgMbfhWGJxrXD7m+LWSaBiXZtvvrmsXLlS3nzzTSVudTOTU+kEU/Yx8Hkwwfrhkg3Ru8MOO8icOXNkyy23FAhniN69995bjj322B5JUBWKyOyOr0FH13VMHGXLIKznBdGIMjq1NrE6vCBDsozkTer81fsyE8MirBuSMiEzsY6HlY0bpXnDBily50lFetsayfjcZuVrJbOlUZr79JWitGzBfHWDBXhwvke5EOsWPClUIAYYc1pe3FZ0Y272BFjdsSfxNmYkv2sUt/F2CrieWCVAcRurO8d5k0AIBChuQ4DELp0iEMlNoFM2ZC1eIeIgaNEHog+WTfwbr0NA9pS4RfZjzCFUN2YtbttLKLXZZpvJihUr5IMPPpBp06YpS6teq7kJptjVVl1T3ELELlu2TMaMGSPDhg2T3377TVm27c0sO4T37P/u1MaLKKtpRxbUzl7D6fPBrhtu4iinMjrpLl/iqPTW5E36+hWtmYkR86pbZpovORMsqLo11NXLinUVUpMSyGpsrqGgtlKGVJVIg9sjK/IGSk1jQCjDAmwX1RXeeikq9Yp5XXtSKAhzCFuzvFF6q+i2r6M79iMex4zkd43iNh5PAtcUiwQobmNx1zhnEgiRAMVtiKDYLWIC4dwEmtmQ9d/NhD6wlmoXXruI1eI2WMwtLLdo2i3YzLSM18O1xHa3uJ0+fbrKlqzFu5mgyh53C+EKTugPLmDw2WefyR577CG77LKLfPTRR/79Mz+LNcMSjGs4idvOit1oErfhJo4qq6mXVbYyOhCNcC82xaoSzA6ZifMz0pSF1UzOBFflFTaRiZssLYdTm5tkTMVaaUhLlxVZfaU+oJPFbgHGdRH/izhgizi2JYUKloQKAt1cR8Rf8AT9YDi/axoRxW2CHhYuO+oIUNxG3ZZwQiTQdQQobruOJUdyJhDqTSBu1iFc0R+Cy7Q04nXthoyrQIzZLZEQfxCcPSluMS973dpg5yBcy60Wt4iRfeaZZ+Sxxx6THXfcUa677jolVsvLy1VM6XHHHSfnnHOOYoYGt+ZJkyYFPY54CKBbaWmpPPvss/LKK6/Izz//rBgPHTpUDjjgALn00kulX79+jqJ34cKFcuedd6p5rF69WiXwwuf22WcfNRfM68QTT5SnnnrKcR5OsbDvvfee3HffffLtt99KWVmZFBYWym677aZihidOnOg4zueffy433HCD+gzOD1yvL7roIpkyZYrFYhxu4qj1m+pkQ2X7ohETCiaYnZIzIblUUUmNNBmWXZe0CGrb6jbcWybJ6WmyMiXL0s+eERlrXV3uldLqegsX+3Xx/moIdCNdVZ4nVYbkZ0hyMm/vOvObHervmnkNitvOEOdnSaDrCPDXr+tYciQSiDoCFLdRtyVxN6GObgJNay3EIqyJiBnVcbRm/VrtogvXXi3mNLDOittwLbHo35PiFiL3ySeflD59+si2226rEkR98cUXyh37r3/9q9x6663qwUBJSYlcffXV6v0PP/xQCdS99tpL8QK/J554QiFDgq39999fvvnmG8nNzZWtt95a8vLyZN68ecqdGO7McI+GW7Fu+DyE9umnny719fUyatQo2WabbdTflyxZogQyxoewffTRR+V///ufEs7Ibn3EEUf4x8Eabr/9dv+/zzvvPLnnnnvUA4upU6fKkCFD1HiYC4QzxsBczfb888/LjBkz1B5AzI4bN06WLl0q3333nZx//vlKfENE/7poqUrwZLrkpqYkK3dhnWhJj9uMLMdlNbYYV5EBtjI66N/YhMRRNVJdH3hYACvt0AKP5HqsyZmUhbUcIjPQYAU2sxrnuJIk2+2SNVWN7YrRJmRELvUKLLK6qevmeyS3NSkUvlNOAt2ehCrufmx6cEEd/a45TYXitgc3iJcigXYIUNzyeJBAHBOguI3jzY2SpbV3E+iPrW2ql5ayFcr6BgsnRA7ca5EJWVsa8W8IWPzbqfYr3oPlEcLYKVuyLhcEoaWva7o847MQSng/lGbpnzdMJKX9bLOdtdxiThCt+KOFPVyPIVzREFcL0Yi1gx+sqvvtt5+y9r711lsWgYo43ZNOOklmzpwpf/zjH+WRRx6R/Px81Qccr7zySiU+4dIMgazbV199JXvuuafid//998vJJ59sSUwFiy4aElihheKW/OCDD8qZZ54p48ePV/OBSNXt9ddflyOPPFLFNf/+++/+Oa5Zs0Yl38KDkAceeEDOOOMM/2defPFF+dOf/qT2ctiw4fL2Vz9a4lE9QRJHNTQ2y3J7lmMlVjMkx2ONj1UxrBDMRjysk2AOVnYHInOTt1HqGn0ZlSFO8zJS21hi+2W7pX9OoNYurofrmsmtXMk+oa6TQsGaDHfq8pqAVVeVIcp3S2Fm2yzioZx19mlLgOKWp4IEYpcAxW3s7h1nTgIdEqC47RARO3SSQLCbQEvSqOLFknL/tE5eqfc+3vTX70QKR7c7gc6KW1hrv/76a3/SJ32xAw88UFlIYSk9/PDD/TG3KP8D4QuBOmvWLCVa9cMBiNDtt99euRLDpTcnJ0cl58IfXYcXFtkFCxYo66l2Cz7kkENUmSK4/t58881K5JoPCOwxukiOBetusJI8mA/msHbtWmX11aLYBHn22Wcrd2VYduHyjHbjjTfKNddcI7vuuqsqc2Rv4PDqq6/KoCFD5d2v5/vfzvWkylAHl1zHLMcoo9PHyHLcOoqKYS2tUWV1dINgHl6YqeJidcP76GdaWMFnSJ5HWZHXbwq4PSOTsilY0W9wnjUjsre+UWVtNjMxq+RWfTIE/0VzsianJCXJsMLWMkS99xWJuytT3MbdlnJBCUSA4jaBNptLTTwCFLeJt+c9vWL7TaCOlTXdkZNKl0ryfVN7empddr2eELew2F577bVt5nzhhRequrUQfBCCOqGUKW7NhFIYAFbZyy67TE499VS57bbbLGNC3ELkYtyHHnpIWUZPO+00JYxh3YVI/+WXX2Ts2LHqc2aCKrvYhbgdPXq0ErewvEK0mWJ47ty5ysUaVtuffvrJcT9efvllOeqoo1T5oueee071gWiHRRkWZ6zBbLBcPv7sS3Lan4+xiNv+OW7plx2wgurPBMtyDEEIa6zZSqrqZE15rcVtOMedqqy7yGSsm5OFVWU6LswUV3KSLN5Q5ecGq62Z6diXETlTstyB7NabvD5Bbc+IbCa3ghV4eXGN3xqMuWD+KPXjSfOJX7auI0Bx23UsORIJ9DQBitueJs7rkUAPEqC47UHYCXop8yYQpW7s4laJnZIlFLeob2qUArInlIKQgyuxvV1//fVK2MKVGBbVUMQtLKAQraG0q666Sgnh4uJiGTFihNo/CFx7zLMeyxS7ELRwH0b8LuJh7ZZduCEfffTRoUxDCVpYoNHgugw3bMQEw01aN1g1V5bUyNx58+To/XZR4va9bxbIkHyP5LXGo5rzDDXLcXvuxQNy3BbB7lRzVpcPgmX3943Vljhdc/FtauKK+DIi2+J17ZmYnUoWBXO/Dgk2O3VIgOK2Q0TsQAJRS4DiNmq3hhMjgc4ToLjtPEOO0D4B8yYQLqqImcVrZlKopnqv1K5bFLBmJaN+rafNwIjBxWeRbErXd9WdEGOp43WRhMje8B764LqxGHOLbMknnHBCl4hbJKB6+OGHZfLkycoV2Mw8rcUpWOHvSOSE7MkbN25U1lr0RaZm/Bd7YFpi7ZODoDXFrd2y+9JLL6lsz4MHD1Yitb2xIGghsoOJW299kz9x1MKfF7SK22GyeOlSx8RRyDaMcj9mg1BFPKw5D7gXF5XWCLId64YY1sH5bimwxbA6WYHN8kEl1XUqe7FTs9fEDSao7RZop2tmu1NVySLTmszfqa4lQHHbtTw5Ggn0JAGK256kzWuRQA8ToLjtYeAJeDmdSRdLh2XSLm4hWPEHDWV80B+iySmxU21trXof7zmJW3umZRO3rpGL+FIncRtu9uNw+yMBFdYOcR1MxJmWW8TEYq1mKaCuErc33XSTilmFGzP+ruvcOh1PsIJLMuYyYMAA9QDh+++/92dR1mWbdMyuuTZT3MKKi2Zadr/88ktV7gfxvcjabLfs2t2Y9fwghOFqjTjjU045Rexuux/97205/7QZjrG+wcoCOWU5roerb0mNJR7WyW1Y1bqtqpN19pqzGWkyqLXWLa67aH2lJVZXrwdWZcTi6vI8joK6NSOytkAHq3Nb2Frntr0HBQn4M9TlS6a47XKkHJAEeowAxW2PoeaFSKDnCVDc9jzzRLoirH8QpMuWLVPCxRS3EFQQtRBOeA/WWFgDUaKmO8QtxCiuFUzc6oRP4datDbV/NIlbiNNp06apZE9z5sxRTEJpBx98sLzzzjvK/Rnu0DpJlflZU+wiURRKCQ0aNEjV37U3CASU/YElGDG3iM/FaxBueNARTOyiti3ij3fffXd54Y132ojKy886Sd757+ttxK23oUlWFLctCzSiMEM8aYEYV8yzps6XwKmxudk/be1enJ4aiGENtdYtyhFVeAPWXz1ovxy39DesxRDBy4urBXPVDYIasbM6IzL4rCn3Somtzu3AXLf0yWobVxzK3rJPeAQobsPjxd4kEE0EKG6jaTc4FxLoYgIUt10MlMMpArj5hrCFpRIWPwgbLW61FVCjgqCFsNVCpj1xq628EMamKy3G0jVy8bqTJZLi1no4kVH4jTfekIMOOkjuvfdeJTLNVlZWJkjmhHI/mvXnn3+uYl+xV0g2BUuytuxiX5FoCvugk01p8YrXioqKVKkiu0URWZAvuOAClVQKrtJbbbWVpdwTzs97770nY8aMkS222EJNEaWA8Hfs6TW33CWH/yngrv3dR+/I6Scdr+ZhZml2SsqEREsQjfbEUSijU1TmtViZTfdizUllJy6tEcS86mavOYvXMR4SQplNZ07OzwyUkIJrNUr9WDMi+5JCaUHtlIXZ6Zr8KepeAhS33cuXo5NAdxKguO1OuhybBHqZAMVtL29AHF4eYgeiFmJHC1wIGy1uIVDxOhqSH9lr0kYqbnHdyspKJcQobtNUiRxdCsieLRnsKyoqBJZYuAYjRhmiEgmjsHewtM+fP1/tIdy5dQwzrM9PPvmknH/++aofLPFTpkxRDzDggoxyPnAVnjFjhnoff/B31NlFyZ/ttttO7Q1ELkoJwcqLc6EzPmNeEyZMUPPAAw+I2B9++EGJWIyx7777qnMDgffvR5+US845Q7PhGs4AACAASURBVJ2lLSZOkhGjxsjGNStlzuzv1PzuvPNOJW6xluKqellX4ZVA8R4Rp7JAOEMbKussZXpwvQLDvVh/ZetUrVtrdmKXyk6cYYnxRYmfxeurLBmWdeZkCGbdVImhkhppagnM0h6H61SL117nNg5/UqJySRS3UbktnBQJhESA4jYkTOxEArFJgOI2NvctWmetkzqtWrVKiZi+ffsqgYSSMBAxiNnUWXYhmOB6am8Qt+iD2FR7a89y21Xitr2YWHM+odStNftHk1sy5gVeELivvPKKIGsx6tnCPRjlfuBGvMMOOyir7j777ONfhl4D4mdhcf34449l3bp1KgYaGZEhps866yz1dyVCm5oEZwEuzCjds379eiV4IXQhntF0rC5q+CIjNMT2hg0blLgdOHCgEt2YB4S4cmVvbJaVZbXKujn76y/kkXtulwXz5goq8cD6CyswygtBeEPcfjHvFym1ue/2y3ZL/xyr+25zc4usKvcqK6vZBuZ6pE9WwEUa71XVNarkVWatW9SqhYXVrHWL2rRLN1ZbSvhAjG7WN2CJxXhOJYbyPGkqy7OOw3W26lrr3Ebr70I8zoviNh53lWtKFAIUt4my01xnQhKguE3Ibe/yRZuuqRCnX331lcqAO3HiRCVmFi9erCyqECupqanK2ubkWoyJJbK4NTcGQh4WUXCyJ89y2kBwhvjUpYA62mTsGayyGLu9hFJOAh1iNlgpILM/xC0eAuAhhrbQm5Z9bd03P4OHIOijY7DN9yprG2VVea1FLLpdyVKQ1izuNJffwozPNLeIci2urg/ErmLsoQ5lgYInmcpQFl6zQSgj07KZGMspO7GTGzQstpv3zxZYePUDhnWbagUlicxmF9+hWHU72m++37UEKG67lidHI4GeJEBx25O0eS0S6GECFLc9DDwOL2d3Q4aYgfUN1j+Umfn1119VkiAkXoK7KcQUhFtnxC2ED0Sy2UK13OoEUPayNOFaYsPtr62eoQrDeBW39q8AHnToxFQQ6KZoRF9dcqiirkU2VFmtqjlulwzMSRNvTY3qp92nYd0tKquV+qZAMihXsk/YZqT5yhfp2F/0RQInsy9icO1JpjCv9ZvqZENlrWUJSOCERE5mLLFTbVqUDxrbP8sfOwtLcVFZjSXJlK/EkEcKjDhcR6susiu3ZmGOw5+UmFgSxW1MbBMnSQKOBChueTBIII4JUNzG8eb2wNJ0TC3EiRaLyI782WefqbhKCDr86devnxK3cBXFZ9oTt4ibhVBwckuGJRPjtydug2VahhiFeMI8dDyodomFFTJcsRpu/3gSt6G6bjtZbjs6lporxKrPstsipXUi1YGcTWqIPpmp0i87XZ07xOTqxGRwGYZ113QZTncly7B8tz9xlBbQ1fXNbSzBTkmmnIWoyMA8uCyn+5ekshhX1Co3Y3uDAO6b7au/7GQp9pUYypAst++hDcYKxarbEU++3z0EKG67hytHJYGeIEBx2xOUeQ0S6CUCFLe9BD7GL6vdkCESdXIonRwIIu7TTz/1rxDxlXBJ1Qmlukvc4oLtJaPS4hYWX9yYmg1z17VvQ7WsUtx2fHugXaVNt+SOjr7JVdV7LauVGqMsDq5akC6SmSrqTGHvIIIhbr0tLlUWyEwclZ3ukiF5bhW7qkUtHpKUVNVLeb1Y+sISrOvNaktsY3OLrCipkZr6gLpOSUqSYYUZAndk3ZyyGOv3IJhH9/XVN0aCKbulGHG6iNdF3C5aqFbdjljy/e4jQHHbfWw5Mgl0N4GO/+/V3TPg+CRAAt1GgOK229DG7cAQCLixg0i1C1uIBiQKKi4uVjfykydPlsLCQlm+fLlf3OLzwayvgAbLLZpT/dj2LLcdiVtdCgj9IIgguLU7LP5rF7vaHRbWXXv5GvTtKXHrFHvqdLh6MuY2VMttZ8RtqjvDnzhKrxfJmIbkpUlqUot/73wPJUQJ1UpbGdk+mWnKuptk3Mmg72q4A9dZ9xx9+2alWmrrwmV5RanXUponDS7LfQJCFHOrh2tzSbUSrvYGV+PR/TJVHd2q2gZVOsi0KmekuWR4YYbfqozyQsjC3JGYjtsfmBhZGMVtjGwUp0kCDgQobnksSCCOCVDcxvHmdsPSIAIhWObOnauspLvuuqs/fhF1UX/88UclXNEKCgpk2rRpqn9vi1vciMKijAbLLWIztRVPJzDC+1gfhK8W7Rqhdl+G4NUWaorbjm8PIhW3VXVNUlKXZE0clZpicS3We1NX36Bci2sNXYmZ5aeLZKcl+WN2sYctkqT6wnVZN4jPQXnpkudJtcT7+tyb6yxz8GAOBR4lRPUDD29Dk7LsmrVpza9e32zE5HpUxubVqJ1r2Irt5Yh85YWqVUZo3ZzEdDd8tTlkmAQobsMExu4kEEUEOv6/VxRNllMhARIIjwDFbXi8ErW3PWnU7NmzVdkYXXcUNU6XLFmi8IwaNUpQKgYW26lTp4YtbpHBF9drz3LbXhkhM+ZWW4lNN2RtdTTFLeZtxsRCuGgh75TRVwmllhYlgkO1YkYac5toltu1ZVVSWms6FovAXXgwXItNE2yrxXRlmdciBhG7OjDLJWnJvnrLukEvbqwVaQjoRkHfYa1Jpszvdml1g4p3NWeRmZokhekiWVmZqivOiFP2ZohlLWDhbjymX7ZsrKxV9XPtondATiARVXVreSG4QesGMQ0rMcQ0W3QRoLiNrv3gbEggHAIUt+HQYl8SiDECFLcxtmG9MF2dNEq7IeOmHpbbkpIS2WWXXeSnn36S0tJS5eaLmqSok/r+++93aLkNJlDbE7faAhtKjVxdcxf/hbUVfyB2QhG39jI3HZWv0S7M2rLrtE3xIG7DtVaHY7n1JWOqk3Kv1be4b1aawPppvxmpqW9SpX5MMehLHOWx1JrFwwm4A6+tbJQm+CS3ttRkkX6eJFVCCA8rsHciSbK+sk5KbHVxMYeM5EZpaX2YgSHQZ32lNXszrKxm1mXE0ZbXNEi5N9DPZyl2S6GRiAq1dbEWM1N0jjtVhhZkKAHOFn0EKG6jb084IxIIlQB/VUMlxX4kEIMEKG5jcNN6aMraMqmTRulsyBB+c+bMUXG1OjlT3759VU1bJA5Cv/fee0/y8vJk+vTpbSy3mD6EXnviFoI0JyenzUpDFbcQ2nY3ZLhL4/ORiFv7RDA/jI//ardm3Qf/1mIJ/9VCmeI2kFXYzhMCFeIOgtXkODg3vU2dWbwPAbymvM7i4puRmizDHMSg6ltRZxGOHleSFKS3SIpxhwODKVyhvY0BAWy6LCNm22epz1ZW3dIaqwjPdbukojZgKYa1Gesy12RPRIXvysaqOpUEy2xO5YV66GvPy4RIgOI2RFDsRgJRSIDiNgo3hVMiga4iQHHbVSTjaxy7GzJWp2NNcYP/+eefK3EHIbf55pvL8OHDLUmXIG4hTrfffvseF7fmTpglgzDfrhK3WqBD+CO7Mhr+rhNUmRY4MIJVUNdzDTUbs65zG01uyZFabvGwAQ8+nFptQ7PAtdiMWYXoRFkcZBk2G2Qn3HuLbfVus1JF+mf5Yql1Q9+NlXWy0dY3PyNVxeM2NjSoWstotfUNsqayUeqbAsIWBtN+nmTJTPdZdfFwpLmlRcoaXNaY3aQkGZSTrmrw6jVAxCI7s7kmuBYjXheuxr6WJGsqvCoW12yDcj3SJzv4g4D4+qWJ3dVQ3Mbu3nHmJEBxyzNAAnFMgOI2jjc3wqVBhCFZVEVFhYp7hbiCQMMfWK+QNArvo2277baqnq29zZo1SwmHHXfcMWxxq7Mat2e5hVjCH7Nh3nBpRoMQx/VN9+LuFLd2N2YtcrXgNeeJvqZl1ykTM/ongrh1illNS0mSvu4WycvJtu5vS4usLq+VTYZ1FDco/bLSJF3qlXjWZwIiFJbditqAdRV9++ekS2FmmhKqECd40FDX1CIrS2ulsTkQjJuakiT9PUmSLIHXnGJ2XclJMjTfo+ZkujIjNhhz0A0lfobmpftjZ2Eltie2wmfghowkU2zRT4DiNvr3iDMkgWAEKG55NkggjglQ3Mbx5oa5NF27FsIMCaEWLVokkyZNkoEDB6qR1qxZIz///LOyTkLwQiwiWzL+bm8ffPCBsqLttNNOQcWtk0DFOO2JW4hFWA/tnzWzIWMMiHK7aLSLW/TTrtb4uyl47GLVCWWobsbavVtZ/gwBpcfEtZzKDsW7uIX1FfGtZoMrb15qs0hLsyWhGCygK8tqLaV2YB0dku8Wd4rPzV2L20aI1TKvIIuxnzH65rkl24242sBeN6eky5pN9RYhmpmWogQrYl31dwLJntZWNohh2BXE7PbPRNbkFFm1qcGSfMpcU0ZqkgwvzFTJsFQZrdb5mRmRIZIRKwxLtT63+oFSmF9jdu8hAhS3PQSalyGBbiBAcdsNUDkkCUQLAYrbaNmJ3p2HvXZtUVGRLFy4UCWI6tevn/zyyy9K3MLiuOWWW6oEUqtXr1YJpbRrp7mCDz/8UMXj4n17KSDctDsJVP35cMStUzZkjO+UaVmLW+0WbM+W3F3iVq9Ljw9eWjTpeGaTnS47pBN5xZtbckeJo2paY1v1Hnrrm5SwNS2rSNwEF18kkDKTVrUku9rUxlXuwBDBfndgnxgurWlUtXHNhnJAg3JRFzdw6wOrLCzGpiXW40qWvh5o8GZZ7xWpNzIwm+Nlp4r0zXT5HwChDu4Km5UYaxia5xZYi3U4QCDBlS8rMxrFbu/+RtqvTnEbXfvB2ZBAOAQobsOhxb4kEGMEKG5jbMO6Ybq65A3ElLZkQrjCSrvZZpvJ2rVrlRiFmzAsuRCHyJC8atUqZZlFgiZ7+/jjj5VLMCy7kYpbJ+urabmFtVMnddJuyBDGaE7iFuKyvr5ezR/9g4lbiE+Ii45aqJZbu7i1x9yaQtep7BDmigcFWvQGm5cWee3Ft5qfxXXhxo1xnR5QOF0n3JhbCABw13MKJXEU9hBzw7mqaE0GZQrLjFbLKqydaHrdjUmpsq6qsW1d2nyPuIzMURi7qLRGKm2KtH92uvTJssYFFyMj8iardTnfkyoDWwWwk/VZc1N1dlN9LvLwYqhpaFGuyOZaTCuxuRbst93t3hS5FLsdfTu7/32K2+5nzCuQQHcRoLjtLrIclwSigADFbRRsQi9Nwcl6qJNGQbhCwOpMwEgYhcRR2l0XltyVK1fKDjvs4JjV+JNPPlGr2m233cIWtxBQECztiVsIW13DVLujqrqjlZUxJ27t26+tdxDidjdmnYlZW/ZM9+loF7fNSS6VEdksleNK9llVzcRROm7a25ImG6qswtLJsop1b6jwKiusWZc2150qg/LSLbVxm1qzMlcbWZnhLowaunCJ1g17sHZTnZTZMiLnpyfJoALfw5z6xmZZWlxjEat4HeP1z0yRtKQm/wOUygaRMutSJNhaTBdrMzGZ/ZxQ7PbSD2frZSlue5c/r04CnSFAcdsZevwsCUQ5AYrbKN+gbpqeU+1a7fYIUYVSP0gaBREFay1ck83266+/yooVK1Q25Nzc3Daz/Oyzz5T43GOPPdqIWwgyWOcgSs3stnqQUMSt7mtmQ8Zr7dXI7WrLbbhuzKZbcjDLMCzl4Go2WPBQamnq1KlyyimnqCRduulMzHo800ra0dHRlls8KHCKm3b6fKSWWyerKtyEIWzhNmy2yqoqKfG2SHWgqo5628myqlycy2ul3Egyhb5OtXEhRhGLGyzWVc8BAtgp2RNKB2WlJfuzYy8rqfGX+Zk0NF99/JfVFTKswOcCDSt8dXWNbGpMkoo6U3aL5Kb5/oA9akbvvvvuctFFF8mNN96ovBGw588//7za7z//+c/y+OOPW0oZmbzAAH/0gynTfTlYsrKOzkYivY8zje/dkCFD5LvvvmsTqx+MBcVtIp0SrjXeCFDcxtuOcj0kYBCguE2s46CTG8HC+dtvv0lBQYG6qdM3xIilRTZkJDNCGzVqlIwdO7YNJHx22bJlst1220l+vu/G3mwoFQSRvOeee3aZuIVYwI2odp12KqkTL+J2n332UYIWDyGwV9gTxEGj3XbbbXLWWWcp8aSt1yZ7CF08OMB/2xM3PSVuN2yqbRPbCisprKWwcpoNyaCWl1RJXSAXlOpjJoMyRWhRea0g2ZNuWC9iZmEVNRtqzULYQrjqhoRQIwozJM0VcEGHVXllaVsBjARTTXU1SkDi3KEckVliSItbb129X6w3NuKaNeI1RDrq5vbPdkmmy+dOjf3da6+9ZOnSpfLDDz+o7yNew/698MILFnFr/45pqy5EFr6vEMRwZzZZ4O8Uux3/xv/73/+Wc845R5588kk54YQTOv6AiMq2vWTJEtV39OjRFvbBBkji04aQ2LITCXQ3AYrb7ibM8UmgFwlQ3PYi/B6+tFm7FlbZr7/+WgnbCRMmqBtq3GDjDxoyJCPWFsIWAtfeFi9erPpOmzZN3ZDb25dffqmE6N577x2xuEXMpXa7hVCGVVK3YFbfeBG3yDYNqzjWDasq9u7888+XBx98UAkfZLLG3qHpskO42ba7MQfLxIzPdUbcOsU0O4mv1WVeqTCVahCrKj6LZEtIHNWmNqwtGRT6Ollhkd0YGYcRk2u2csTtltdJi+G0nOFKElhic7Kz/A8AfImrvIK4YN2Q7AmJq5DACg8Z8MCgTlJlTUXgLKKvFrf6YQPGWFlaI96GQKYpzA8iGXG2uv3nP/9RYurSSy+Vyy+/3GKdxXd048aN6uHR0KFDLWWtzPXhjEDcwgsClmCnZmoqit22hMAQoRf4vuChXbCazOYnKW57+H9gvBwJdCEBitsuhMmhSCDaCFDcRtuOdM98tBuyTlgEofjFF1/IoEGDlICFZbCsrEzdICNDMvrDNRkWCfyxN1gs8CdYnduvvvpKuQjDAmlPKNWRW7K9ZI9258UcYJ3CjXx74hZzd6qRq92SzYRRZikgXXon1IRS3emWbBe3OnkW9gsi65FHHpGTTjrJsi065hbWOwgYLXrNTjopFcbTdYsjcUvuSNyGkjjKnJdTvVuPclu2JoPCZxAvi9hduxV2cG6aZLoDtY8hUTfaLKz4fEFGmuSkNklzU5NKWgUOThmRM9NcMjTf7S8JVFlZJVVNyVJWa02NnJ3uklH9fDV5sQdwe4b114wtNrM7m+uePn26ckvGw6IRI0aohxk4hzrhmRlzq+Otddko88GPFrem5TaUeF3MhWLXtyMXX3yx3H777fLss8/Kcccd1+EPMcVth4jYgQSilgDFbdRuDSdGAp0nQHHbeYbRPIJOGqVFrY7Nw80wkj7BKgQRihs1xNXCigvhWFJSIrNnzw7qlqzr4G699dZt4nHBA1bhiooK2W+//dqIWwgsXBM34k6xnlrcQmTq2rA6GzLmj3jdYJ/FuMHELdaMP10tbsMVw+311zG3TuIWXOEGDjH097//XS677DLL0cMewhKIWE24uEIE9+/fX7m94sZ98ODBjnV2UeLpoYceklmzZql4X+wP+iIZ2BlnnKHOhG6wxiPR2P3336/Oz4YNG1TiL8QDw1X6D3/4g9Q2NPsTR804eG9ZMG+O3Pv4f+TEY46wJI7SY579twvlwX/fLX/+y9ly4dU3qpczU5NkWGGmzHr/fXnggQdULCQevuQXFMrW2+0op559vozZYnxr32TJT2uWDevXyRZbbKEscL8uXCh/v+UOmfnic7Jy+TJJTXXJlz+vkAE56VKQmSaffvqpwBUV42INWdk5stXWU+XEM8+VradtL/kZqTIwJ1ASCBmOZ33+rdx+y80y95svlQgdsdlomXHSaXLZeWf6LaYVNXVthLfblSTDCzItGZsxcXy/YJ1HRnGUzkIzrbDPPfecckueMWOGYoDvMM4/HkoddNBBKvb69ddfV27qL7/8svK0gMfFiSeeqM4G9hGu7DfccIO899576juNB1U4C0cddZS6Fh4W6Qcd+uzBIwN7jHHx0AvfNcQE498jR45UZ+juu+9WccDoiwdJhx9+uPzzn/9sk6Ucc3nqqafkiSeeUPOyt+uuu06uv/56ufbaawV/1818/cwzz5RrrrlG3n77bWXJxgOeo48+WvV3itnHGN9++63ceeedihX2F3kBwPqSSy5RGd6dGtY8ceJElSQPnicdNYrbjgjxfRKIXgIUt9G7N5wZCXSaAMVtpxFG7QCmG7J2V9VJZyBSkPQJDZabcePGybBhw/wumhASuEHEzSyyJNsbXPcQdztlyhQloOwNn8UY++67r7opX758uRobN9Chils9pmmlxTraE8bt1ciNB3GLfYLF3G65xY32scceq8QOHhhss802al9Qzgn1ivEQ491331Wvw7qo43UhqiA6IIQhjGCJx/5gv+bPny9XXnmlEh66zZw5U7nRguX48eOVGEBmbVjqsTcXXXKZnHDuZf4Mwi8987j844oL5cADD5LXX3/Nckx0SZ5pE8dK8Yb1MnPWlzJm3JaSh2RL6Uly9dVXy7333qvEl/IQGDBIrX3hT/MlPd0t/3r4KTnkwAOl0JOk5rN+/Xp1jocOGyZjt5ggn338gWyz3Q6Sl18g69aslo8//VRgZb3jjjuUGzDahK0my4Ahw2T92jXy0w9z1Wu33nmP/O2sM/xzhYV45tuz5JRjD5faWq+M2GyMjBs/Uc35++++VrGaEHto84vKLe7PHpfIoJw0cacHLMp64KuuukoJQojPK664Qr3sJG51Qim8j31DmS08NMIDBewV9heCDQ+CsA/4bv/lL3+RCy+80F+HGn1R3kuLtscee0wOO+wwiyszhC8ebuBzEIYQzzhD8ODAecADD4hdPPB455131MMP7A1+R8rLy5WXBkS02Torbk8++WQ1Js4KRCdctSFYsUYI/P/+979tfnv+9a9/KQGPhodv+A3DGcWDDDS49p922mmOv9sDBgxQYhhnCTHv7TWK26j9Xx8nRgIdEqC47RARO5BA7BKguI3dvWtv5k61a7X7IcQhLHu6ximsgXY3XlhdYX2FFQzWMHvDTTAyJiOTMkSRvcEqBUsRYm5xY9qRuG1oapDV1atVLRfcuDa3+Fw/3elucaUaJVqaW6S6plpSXamSbrig6ut7a+Cu6nM3tTcIBxXD6vb469iabsnq/YZ63zWDxC6aY0JQNTQ2qPGG5gyV1BRrEiP79cPJluxkuYVQxc06BI0Zc4vrIF4TljUIACTFMeOk77vvPjnvvPPUgwWModeGPZw8ebISthCS6GNmcYYgwAMKLaJw07/lllsqgYFrIQZYN1hxDzr4YPHW1Mj9z8yUHXfbU73V7K2U7bcaq0QZrIh9+vRRr2u35ff+966cfcLRsuXEyfLiu5/IoFy3JDd6laXvggsuUAL6+RdekOwBI5TrMNpH/3tbLj7zRMnMzJIlSxarvQZbLW7RZ+DgIfLw82/IsJGjVIInZGVGBmMIfIginNm7H3laNp+0rX8NP875Vs464Sip9XqViIO7PuJ/f1tdKvvssLVsWLdGTjnrfDnn0qvVgxrMdf7sr9R4OLNoPxaV+cfL97gkK7lR3O50xxjOnXfeWX3H3n//fZVVHE2LWzyggBXezJZssoY1Hg0CFImn9HlfsGCBSuIG3mPGjFF/v/XWW5WFFnOGxf3cc89V5wMeALiOPg/acovXIF61hRNsDzjgACViYcWHqMP5hNjFmCgJhodcSEaHPliXbp0Vtxjn1FNPFZxhHQeL3x3E+uP3C0LXzB6O/d1///2VdffVV19Vng66QdjjPXiGwErrlCjv0EMPVQ+IXnzxRWXdbq9R3LaLh2+SQFQToLiN6u3h5EigcwQobjvHL9o+bdauhVUON724wdP1auGCihq1uPlFQzIo3CjaGwQPbgaRyAYCw95wQ4txEJ+LG0l7g7WnuLhYucSiOYlb3FTDRVe9v2m5HPLGIdGGM+T5vHHwGzI8Z3i7/SMVt/gceMKihthMWDNhPdMNogIPISBMv//+e5Voyp4Q5+CDD1aC5bXXXlNiDA3iFGPBpRQ382hmbLZ2g9XXgaC96aab1HmCqNBJilQ5noo6ue6aK+WJ+++W6TvvJg8995oqx5OXnqTcaiE0YA2EldOMSb34zJPk/bdelyv+fptcfsG5ym0ZVkCIqHXr1sn3P/wgWQNGibchkD45JSlJ7r7xMnnkoQflrrvuUlZKPGhYVrRWtt5qSzXdm+95WPY/9Eixx+3CNRUPXh585mXZfjff2URztSajuv/eu5RV929/+5vcePMtKnb2tZefl6v+dqYMHT5S3vh0tuKMpFDItIy1n3nuBfLoA/eqcSBucdM0IMct2WmiRDeEpVOCIjxQgiiG6NcPiHTcdyjiFl4YEOEQqhDF+ruE/XzrrbeUJwbWqq+t43jRH2cGlnl4ZegHGlrcYv3/+Mc/LMmt3njjDTniiCPUGjE2LMe64RyAF84SXIzhQqxbZ8Utfn/gIWIPX/jrX/+qXLXt18PZhIUWZx0u8vaGmFpYdfHgBBZee4OnAs443Lpvvvnmdr/PFLch/zyyIwlEHQGK26jbEk6IBLqOAMVt17Hs7ZHstWshblG2BJYNuKLCaoe4PNzMwgIHKw/cVU3rhl6DtorobMr2tcGqB+sHRIjO2mv2gVUI8XGwSOGm2hS3ELUQz6a4XVyyWI54x3fzHIutq8WtEwOIJIhEuHqbDa/ByoSbecRpOokp3NTjhl0LF3weDy0gHODaCYuWU9NJqXB+IIoRqwpBCddkldAoOUXWVzeprMDLf18ih+w6VbkMF60vloIstxJdEBoQRrDuffzF17KqrFaaWlpkU3m57LntOJ9lf8VK6d/XZ9VFGSnEeG6x5ZbyygdfW7In68RMb77+qhxzzDHqD2I/i6vq5OclK+UPO0xSY3y7aI30y8+2lBvCwxa4nSK+9rMFv/tFHTIiDy/wKAuvjoOdut10efyV/yn36usuPldee+EZOe2cC+XsS65Son50nwyVaKqoBSyyKwAAIABJREFUrFbmzpsnR++3i7ruglXl/rJFED/BxC3c53V9aAhcLUDDEbdwt8XDDvtDE4g3PEjAHj388MN+N3T9QAts4bkBizHEPmJq8Zug3ZI/+ugj5c5sNnzXYeVHX1jzccbMBoswLP940ADRqR98IOlZZ2JusQZ4ItjbPffco653+umnKzdjNOwvXInx0ADi3amWNPYXD/Owbrhw2xsEL+oNY944V+01ittY/KXmnEnAR4DilieBBOKYAMVt7G+url2r62ZqV1vcpOImFNZVWHhwE40bP7gSQ/Qilg3/xo2evemYXFhl8Xl7gwUYlh+IZFiI7G3evHnKTRQ30jqGU8fcmuIWFhncnC8tWyrHfdhxhtJo3a1QxG0o2Zi19UzXuYUgwU07LKXghKRfcP00M1hr4RoKG7i5InkUmnbnRcymU0Zs+3h4kIG+sP7C3RWlezZ6RRpbK+c0/L+QnTZmoLL+Ir4T8ZoQt3ADxRnCazPf/8KfCErH4x562GHy8ksv+S/3zDPPtMkEHWxtmMfjL7wm5bVNsrpopey/wyQp6NNXFixeLv2y0y03MB9/8Y3svZtzMiH7+MNGjJI3P/fF4J454wj56tMP5drb7pHDjjlejZvnccmK1nq4myoqZOcJI1TfSm+dshajaXGLpEdmFmO8h+8Pvjf4fkLo6maeEWTtbc8tGW7DcAe3i1tYM2+88UYVL42/66a9OhAqgAcIb775piW5En4XtEcGXJrN8kF4OIUzAldkJJHCd9jMxgwBC/fh448/XolC/VnEzD799NPqNVhx7WVeO0ooBXd5xCTbGwQvBKgpfrVwDeV7gLXgwYC9IZYdAh3uyXho1F6juA2FNPuQQHQSoLiNzn3hrEigSwhQ3HYJxl4bpL2kURC3EBravRSlRhBnpkuIwHIDgYM4TXvDDTNunGHpgsXG3mABhmDW2Wnt78MyBLdSnXTGyXIL0auFeXNSs5Q1lUlScpLU1/liXzM8GZKckmwdukWkqrpKXCkucXvcbeftrZXGpkbJysxq82gWN6OqZIqO423x1XrVN9zhxtzq/qHG3IYjbhHTiH3BZ/AAAFZwWFdhbUcMLKxOet633HKLEjLYWySMAle9x3ZAsOJDMKEhyzGEZ7jiFjGJu+61n6wqr/UnjlIDNtbLlM184hYxwTg76uXGJrn6+r/LfXf/S44/7Sy56Jq/q9dPOmxf+X72dyrG8cADD/RP9YFHn5RzzjhV+g0YJNN32lW9nupKlozUZIs4wt4NGL6ZzDj9PNVHi1sklFr2+++WpW+sqpcPPv1Cjj9kH8nOyZHd9zlAXMkimekom+Tr+v9GWuX+jBq6eQWF/szNprg95rg/y+A8j8qIrOvhmuJW17nFeO2JW/2gCf1My60pVDsSt7Cu4juOPcR18cAK+67FLYShmQxMA4E3BR6QQNwibEB7fODhBVyk8b2G8DZrJON1CF64CSOpl90qCnGLc6XFrf5eQdziYcWjjz5qEbf67GJ+EOLtZUs2syjrNTiJ22+++UY9qINF/I9//GO7v8mI/cZDIXvTllvMG0m32msUt+3i4ZskENUEKG6jens4ORLoHAGK287x681Pm27IELA6EzJuHCG8IE7RB1YjWM7s2T8hoGBVciqNgc/jxhnWN7iT2hussrDOImYP7pH2BqsurFO4AYfLpZO41Z+x16w1sxrbEzvhptnu0mxeG0IBN/oQbnYrEdYE8QCxCCYYyy5utZgMNaGUjnV0coG0M+mMuMV8IEKxF7iphpjQtTjhioyMush+ixvyYDGe9vnA6g4RCpHjFJ9o7w9rMs7EP2+/S/5w9AmWt3PcLqlav0ImTpigzhSstDiPTS0iJbUiCxf7XJYL+/aTWd/9InWlq2X7bSYpAYyzoS2Bayvq5KPPPpcTD/uDjN9qijz39kfKUor4XbMh0dPK0lqpbQzE4q5btVL23X6Sij+GdRFNxwOXextURuR9po1X5YR+XLhUctJ81mu05uYWKSqvlao6X9IqNJwfuCxfet5f5fUXn5XTzr1Irr3mGlXnFu7Kuq1Y9IscvOeO6p+muDUzH9stt+gLEQarrRlz29PiFi7u+kGI9hpALL29bBQsurDs6hhYXUtZM9Di1szsDPawgiI5GEQjElmZbPF3WF8hfhGnCxGrv7PBLLr6807iFmcOIRIQrngYFElD1mrE2jLmNhJ6/AwJxA4BitvY2SvOlATCJkBxGzayXv+Adi9E4h3cTMO1GDeF+iYVWYohLiGm8DrqaDrVg4RQgaiwx9dhgRBQiNmFIIY10N6QORfJi2AtNDPz6n6wMOJmE8IZ1zbFLcbWIkALTXN8itsVKhutabnVYhuJcBBvaGY+xoMGWOVhuYPFHK7LTgmM7HuIJECo9Yp4WGTc7aihti5Ex5Sp0+XJV9/1d4fw7JudLldecYXKzAtXYbi81zU0KdfdhmafEDzh0H3lhznfydP/eV5+mDtbleRB3CQSVbUI4le9Ul3fpM7eXtuMk8pNFfLN3B9lyoRxlqnBugph29jsy6iNBitsc8U6mbilr84txC1K+Ogxdb8j9t5RFi/8RQl6ZPWFuHUSykgwhXq4Gyrr5M2ZL8hV558pw0eOktc+/s5itcz3pMpdN12j1oIWjriFVwPczcEKzNC0uMVeQvS155Zst9xiLfi+h2O5RWIoLSi1uIVlFufJTE6HutZ4QAZxi98WNDzQwR+cTcwVbsmmuEUfWGSRnAqxsThrumFsrBXWYghnbWXWc8Ea4I5st+jqzzuJW7yHOeK3B+WSwDfcBosvkme99NJLcuSRR7b7cVpuw6XL/iQQPQQobqNnLzgTEuhyAhS3XY60Wwc03ZARN4cbLLgZ4qYQVlrc1OMP/g3rCm62YXFzarDsojndBMISPGvWLCksLFRusPaGOFBk8EXsmlO8JpJXwSIFN1gIWC1uYanTIhz/dSrZE4q4VRlrMzPbzKsrLLdOMZJO/MzkP11l6dUCI5i4hUUKDxRgvdaunpibFr1wy0RyH9SfNRsshEgchbOi6xKjVjEswUgeBuGKRESmBRr7h4cYqjZuc4t8/9ty2Xv7raW6qlIuuf6fMuOUM2RwbrrkelKVmysSTuE6yKa78x57K2EJganbGy88LddcfJ7qhwcjuu4qatsW14o0BLSqPPfYg3LLdZerpFeIg9QZvVEOaHV5rXpw8+UnH8jwUaNly3HjpCCtWYo3+urcQtz++ttiWVnmVZmZdXMlJ8v8L9+XY486UmX4htja5w8HKKHc0CqUce5R3mdo3zwZMGYrtW6vt0YO2nkb2bh+nbLennXRFer7BYvybz98p8rk6LhZJ3Frltsx9wQPCsAdQg5u5Wimi3Go4hZnHvPuanFrzlXH3ELcwrKL3xpdOxv94D1w1llnKW8CxNdqLxL8xsD1GQ/gUPZI18zGOpHxGGtEQ81f04UawhbuyrDo4nVdxkzPKZi4hTCFQIXlGfOw//aBE5KiIbP09OnT23yt8d3Ad4x1brv1f2McnAR6nQDFba9vASdAAt1HgOK2+9h29chmmRaIXMSY4cYWCWJws4hYOVhzIc7gQoh6kBBB9uy6el4QJLjZQ9Ine8P4sCgFy6YM6zASuECMIRbP3nADDIsMrI+4uUfyFohtlDzBv+GyGUygtiducR3UWe1I3OJG3x53qt2SwQeWzWBuyd0tboOJHaytI3GLPrjphyCCxRycIazxkAPxjjNnzlRsECcNd3GIAggTbclH1lsIQDScJ8S7Ir4QAheCACJSfwZWYIiuS6+4WgnV+qZm+fi9d+SSs06W+ro6GT9hgnJDhvs5LJAYD26d5192tcC9uAVFi1sbSufkpjTIsKFD1FlFQ83eWR9/JmsqGy1uvqnJIn3dItdfe7Xf2geL3JBhI6QpKUU2rFsrC39eIN6aannqxdfk8AP2kYaGen+d22HDhsu7X//oj4nFtdyuFBlW8H/svQmcXFWZ/v9WdVdXdXfS3emsBBJWcRhERHYEFRFFUEARBDcUEUUQN2Tc5v/TcV8YRUXAGRVnXEadcWFRZBFlX2VTWQVJyAZJOumku6t6/ff3VL3Vp06fW7fq9pJOcs7nk0+Svtu577n39nnO87zPmzOOyDgJIzvl2d9ltz0MQG5pbZW1zz0rj/71IeneuEE+/9VvyGtPHZNe33nrTfL+098khUJedt1jT3nxfi+Stc+uMcZMlDe66KKLzD3Z4DZu8QNZPwtHysBy/NYAblk807JC3C9xxDQKsHraaaeZxRWaLpTAgPItAVCi5OB5xU2dc/BtAqjC3GoJIc4J8CeXXH+ujK7+jQya59bnpgyLfsEFF5h+sRAEoOZ7gAcAMecbiaOzXU6L/sL48pzxzaIMWlwLzG1chML2EIGZG4EAbmfu2ISehQhMOAIB3E44hFN+AlseqGwJE0PALUAPIMPEjEkhzANSP4Ak25nIMYF080/pNICECbhKIt0bueaaa6Sjo8PLcFAO5M477zQAStkY+3iA9dNPPy0HHHCAUDaIfpMHCyADPNLvKObWzY11+1UN3AIOmHT6wC0/ZzvXJx7cu22aQ/yM4ZTH3dY3yHHgxT2mlv1rAbcAUWIOu0SpFyb5CqxweIVFAzzArhNzFhQYB2rdYkql+Z+MCYwj48NkH4Mx2FpydsldhNF/yzvOlLbFu1WAz3889jf5n+9dLH/64x8Ny8U1AGkwdy8+/ChZ19NfceuzMyI7tJPn3Ghkq/SP9sWv/rscd+oZlSA4k5Y5TcOSLs08ABkwcLffeZcBn4zNvAWLZM+99pYTjj9e3nLKGwxY4pkhHgD3xTstkd/dXpTO0mZlG015Hkr3aLvhptvk0u/+h9xz+y0GLDc0NsrChYvkBXvvJUcfc6y86IhXS/ucORX38ejfHpJLLvyi3HfX7eY5ATiRU4rkVpn7esAtJ0fZQF1WFn+QAiu45fkFMNYiS1bmlnGg1SNLtnOtXVmyffM2c4tE2f2eaM4tNY0pzUMc1E0Z+TFAFZdtFkLIiUUOzSINzt38bZtfcSxsrQ1u7dx4+mXHhpxel9lloY+6uzDHKAQYH94DDPBQDpCfTo1vu1ECiNxgjLw0n73axz2A2yn/1RcuECIwZREI4HbKQhtOHCKw5SMQwO2WH4NqPWBSxyTKlgGq5E/BK8fzMyb2yAZ14smkmXqPSPN87rkAB2V+fX2o5qa8ceNGIzNEAsqE0W3UT0X2ClCi/4BuJuxMoAFXWxLcwihpzU+738SNeNM/+u1bELD3rwWsTmR/NSSqxvTa5wcUAI5qNZRScMvEn2u4bW1Pv6zpLlT8uKUxJXNzI9JWAlK6EUMm3JM32YZMIjK/tVFyqUFzfgWAeDGRy8r57Ta3tUkWzm4yLDJjxH30DwzKyk0Dktd6Q6X6hPNb0oKJlY5lodAvfZKRtT0DFefsbMnIojYWM4o/5tprNhXGAXA1rcIo6sm1vRVyZj1hY0pkx7aMzGoZ79Lte39qMRD72c9+ZoCUlu2xwW3c86fXZIFCF49q/ZolOcaVP8ddiz4BbHnX9N3SY/i/nbNrf5+i6gPbpYfca7vMrgt24/rKu8a3jH7w3aolZz2A27iohu0hAjM3AgHcztyxCT0LEZhwBAK4nXAIp+wETArd2rU6aQMAAC7Zh9xT2FtlbrRD5MTC3pHz5ssJ5XhAZpRsuZqbMsdRjoaSIbju2o1JqDKH/JxJo7qrKrhFLs29+HJup4q51fPSJyaxarKlcXYBr83qMhF3wca2Cm4ZP2TFXX2VQBEwOSczZBYA7GfNZ8gES7qkIyeNMmRYVQW3gEcDgvOWK7GILGrPCUCUcyu4bWzKjcub5bwLmlOSSY3l0gJY1xdEesZOaR7HRW1ZATBrM9fucgB4KiWL26lbmzG7AbopG+S25kxaOjPD0pxrMqC7llYLuOV+kcHC3PKHc9v5s7VcJwlQTXKMyxDX0jfb/Zn3x37XbLBqg13OW4uCwj6ef3MM76nt5GyD3mqLBeRfIy9HIo3UuZYWwG0tUQr7hAjMzAgEcDszxyX0KkRgUiIQwO2khHFST6KmUcjpmBxqzUllP/g5sl8FY8hHfW7ImPZgCISJkI+JQFaMvDhKtoxbMsfhKus2AAiyZuSryKC1MeHDTIr8NhpmU8gtbbdkJp+AW5oLyPlZLeA2StIcJUtmkYDJOY1j1YzKVwpIy9K4YFedYZVx2hbBLQZK5Nf29o+V2CFmmDHtuaDFxJCY6aIE+9k1X9m3qTEtS+c0mzI6doxGUmlZ1pWX/MDYuRtSKdlpTs5Ih2kKbgekQZ7tHa4wpOJ8O3c2m7xZleors1uwusukZUFrg2F2GUvGe5DSQV15U8dWGyrlpZ0tQj4wLT8wLE+u7bEyhYt7cp6FsxqlkM/XzIqb8+XzRrVArmm1UlG8h+SiIotFnpsE3NpjUsvHiPeX5ltcijo+CSB2a/Da57Y9BLQWt71dgWq1us26v6oQ2NenQvCBXP0ZzzSLbnzLULvUypgHcFvLkxb2CRGYmREI4HZmjkvoVYjApEQggNtJCeOkncSuXYvsGPmvyopt4MikHYDGdgyhfGwShkCAzCjwiyEUxlBRsmXKaQAMKCXkNia6mOlgQqTOvPSFXDcmi4BtJveYBpHbVg+4tXNjfaC8mqTZB27VoErvgVjxxzWUUjmk5tzauc5Mvm13WM5FbPhZrTLgesFwXJ1Ud0wmKkvGWXjZ+qJxlNt2mVsEgYy7Ailqx67EOMqq+co+S+Y0l/Nb9Z5Tmays2DhQUb6nqSEtSzuLIFgb51rTtdkwsWN2VP682f7BYXkao6sKR+SUMaPKpMeOHhhOyXN5qTCY4pILW9LSMbvouM11H3+u15QFstu8WU3GFXlwYMA8z7WOdT3g1r5eEnY0CVBNcsxEwK06OVf7UPKO8UfTMOx9AZx883RhyU2zcCX21STMnLca2K31Yx7Aba2RCvuFCMy8CARwO/PGJPQoRGDSIhDA7aSFckInYjJmA1v+j6wYZhXwCaADOALe2tvbjRsyMsZVq1YZ8OljK3DIxcAFN1bYI7chHcYQKEq2TMkM+uRzU6YfbMekBYdRnJEfeeQRAxIwmYKdfeyxx0ypGcoJTSa4rSZpBoAACgH+TIAVLDCZBSgDtuLAbRSAIRbVZJU6+eZvH/szk8HtYCpj5MJId92GZHfHjmKeKaCIMe6TpnHy3TktGdmhrTJXmXve0Nsv6wupinO3lEAw9WTt5pMFd7Y0GYmx5s2yP4wxpX7sUkM5GOMSs6vvEjnAz/YMiVWRSLINIvOyIo0NqTKDv2JDQTbmK2XYO5Sk0lwvKg+02ktv16z15bz7jk0CIJMAVY7hGfWV04q6pyTXqTdPl2vre6ILdvrORYFd3jfGm2vx3fGpWKLArqozNG3DztWNY3ADuJ3Qr7xwcIjAFo1AALdbNPzh4iECUxuBAG6nNr61nF1lyDY7yGRY81aR9lJ+Q4EjpXfYjkMyEmVkw75JKmVfcMJF8uiTH1IWA4fZKNkypYJgA9nuNibuOJEuWLDATJI5DxNLWFx+BpgF7JILjDuqC24VJPlkyXHMbS3glgkuk2RipoZJxJcJcFJw68ZAJ+HK4Nrbffm6MxHcbt7cI73DaVnXN56t5X7Icd1jXqsBgrRNmzfL2r4R6bXyW9my0Mlv1Vis3tAr6/oqJc6AZfJcbfAAqIYF3mjl+Uad18cYNzeILOlskUxjUWJM6+odkFUb85UMcCYlc7IjohOboRGRdfmU5PlHqbEN9nl2riiVpiUBt9UkuVHfhSTglvfBltrX8s1Jcsx0g1tXzq3MrpYfsu9TUzZUlhwHTBXs8j0AGNvfR75tfDdRnPAti2oB3NbypIV9QgRmZgQCuJ2Z4xJ6FSIwKREI4HZSwpj4JHbeGf9WJ2QmZ8qscnJYR4Dj/Pnzy9fSWrKUE/GBRLvWbFtb27g+xsmWyallogez6zbY0T/84Q9laS4lg2CTlUGGyeX6sLoKdrknNZRiosz9+vpVC7ilP757VuZW+6tAlv9r3u1kgVvbzZhJtZtDaMdMcy6ZoNfqfjzVsuShoWFZvr5nnBGT3e8K9nJoWP6xrkfsdNw0ObMduQogyPGAB8AqQNRuC2dnBamv3Uye7/o+6XXyYXfqqASYHONjdtuzaWlrBKAU2XpgqnFjdoyh5s9qkvmzs8YymedvaCQlz/aJDFi0LhgeuXJLdkwCy3PrStZreeGTgtt682eTANXpOiYJWK8lV9lWuijotceE58DOkY8CuwrY7cVBYsNi4qJFi0we7hSDW2zK3y8iJ4sIBcN5OdaIyD0i8g0RcQvuouE/W0TeKSIUrGbliLpXFBf+acxz+ebSsS9k3UpEHhn1+/vB6NrUJZS9ruWZDvuECGwrEQjgdlsZyXAfIQKeCARwu2UeC83ntCdmCmzpES7HGEIBmObMmWMYUDevVmvJHnrooUaq7DaYUxjTQw45xNSrdVucbBk3ZCZ/yKLtRt85L+V+aMiQlU3W/aiXirEUZlNMEn3MbRS4dUGo2+8oMyr6pZNpjoH5sV2ipwrc+uri2uOrjtf2fdgS5ijJ6lSCWx+gVACgrFZzpkF2ndti5MAYMS1fn5eB4bE5MMZOGEflMmM5s9yjz5QKEIy0GXMmu/nyfAGYO8xqkPZZY1J6H1hWZrclXXQVNwAllZIVG/LSXeHGnJId2rOCbJrGudZt3Cxr8ykZsmTY2YaULGhJSWqkcp6vTtlco9YayFwnSVmfJOxoUqDKffnSFaK+iEmuMxFwq6kFtXyhdfHBXkSyj4sCu754UxucckD4CZB2EdUmgbndVUSuxXdPRFaJyJ28PhjMi8h+lCwe9XL7nHV9AOkvReR4EekWkRtGy0Vj3X1U6e9vjgoWPhDR34tH13zeh89Z6ThWnTiO4si/EpE3BoBby5MW9tlWIhDA7bYykuE+QgQ8EQjgdvofCybXTIxgB5gAU59WgS2A74knnpAnn3yy3LEoWbHWkj344IMNAHYbOa+c56CDDjISO7fFyZZ9pYLoN8chQ6bBnsIcuw25NLLpvffe20wQXXDLpBdg72Nuk4BbzkUs1fQJdhSZtN2mE9y68WDMYaToQ1TNTwW8CnanCtz6ACW5r7gcq0syv/h3ndciAFyAIoDRzseNypmNAquUBWrNVY7H5sKgKc1jA0yAMiV3ck1jtXejwLIyxgois80t8syGQoUjMm7MS+bkpLXkxsy4IH3mfqIMq+KMxFzX7KgvyHSC23qAqjpS13MM95gE3CYB60kYb1c27i4eRpX54h1zJd3UBn/66adNzXDqc08RuMXJ7AER2W00zfjjo8bVXyuxsHq5uSLCn8es63+ktN/fRIRckeJHuMj43kx2gIicOAqMf+P0+SQR+V8RwcL+pSLyeGk7+98oIhQq/6CIXDT9vw3DFUMEtkwEArjdMnEPVw0RmJYIBHA7LWEuX8SuXUsJENsNmfwvTKP4GeAM4EgpnyjZMSCYPwcccIDJa3Vb3PY4WbNbKoh+IWVm8gkTDMMBqAZcuw0jK5hhauAuXrx4UsGtm69r169lwk6MXdaW/sWB23rdhusFn7aM2ZSnGRwsG1TZ8VOWiZ8xaa+VLayl/xgsAShtoNrUkJJ5s7KyciOkTrFh4gTbSc1XJL52a82kZOncVoGNtZsPrMKGzs2OSNusynI463sHZLWTDwuru0Nbk/T19pbzpH1gucgY5ySXKebX8jz2FQZlbX+6wu3Y58a8rqdfVndX3k/RCCtXYVhl31ctCxMKeG0WPomZUr1GT0mAqh6juei1fAGTXIfzTgTc1uKwrH2Pk43HKSkYP3LiVYJOzi31ue00EDdOE2RuvzjKon5MRL5dkiXHDQMP+0qqXI0CUuzrb3IOoDjv5SJyt4gc5GxD4ry/iLDPfznbONcfS8B3x8Dexg1D2L6tRCCA221lJMN9hAh4IhDA7fQ8FjYbpOwiObWwBMh+AbEwogAUZLwwnoBTGIQo2TGsLOws5XZ8xidx2+NkzVoqiJxbJnswxdzHbrvtZurXXnvttQbkInt2GyWIAMKw0uStTSZzq+CWya/m53F9FgSILZPUauCW/GUAI/fCH5Xj1gIO7fucCLi15dKcM84sBxZaa7ZG5Q/G9R9gt6a7UMFYYsS0YFajrNo8XC4BBIu7+7xWWbNpfM5sRzYl7U3j66P6wOrsbKPMb07J4OBYrVdUwJyXvthNS+6MDA8baTn3O5TOmBq6FY7ImQYDbAG42tZv6pU1jiMyjDOSaTXC4rqru/NCP+3mywH2fRHchYlqrtkKdAE/9dasrZcdTQI63bI5tXwBk1yH89Z7PxyTZFGg3ndRTfz4fmjDeZ5nj/eLMWRxke9qlDx6AuCWvFqAKswszO1TNYzB4SV29hn8zjz7o+HfICLII0gUXlHah38vp3z4aA4vuSl9nmM5J8AWCc5tNfQl7BIisNVHIIDbrX4Iww2ECERHIIDbqX867BI//FvLTZBTSykecruQ8cL67LXXXgYMso/KjqNkxbYjMYDYbeSNcQ7ydX3b42TNamgFe0E/ARwYRCmbAbgFYB522GHjro1sGTfm5z//+UbeFwVumUC6YE0ZVgWh7snVjEpdivkbMMvfWtPWB24BGkxe48At2311g91+1DuhtgGSC27tc+tCCPu7ckr2i5LFRoFbzrdqY0G6HHOnea0ZaZYB2TSUlg35sTxTTKSQ7qpEmWtqzmx6sAgG1F02Eqy2FuvDFgp5wz4zHql02rDGsMfaUlKZD6vAKz/cIM/1DsuIBcUByzvNyVUwxht6qbVbKTGGASa/V5llWOrx1xVZ0Nog89rGl8jyfRGqOV3bRmKMgdt4b3TM4lx86wWDSVjYiYDbetjeiYJbn2Fc1Ne61nfLfc/4lnBPLHahRKHkGj/jfNr4rvC842tgy5QnAG4PLYFIACjg88WjEuXXl1hZpMaO+bfYAAAgAElEQVTk4d7i3CumU+TUkh/7hog43CciLxo1o3qtiFxd2ud1o+e/QkTYxnV8jXMiZz5XRMjNDS1EYJuPQAC32/wQhxvcniMQwO3Ujb7t6MmEUllCBbfKjCpYwG3YntDFyYptR2Kkv26D9YWdBZD6tlMnl7zfAw880NSidZvKkvk58mP6Z9eQvP766w1b6su5BQwDjjGaQt7nglvYGYCAD9y6INTtFwBATY+0rqWChm0B3Or96oQdoM39KVuo985+yjIxQefnWscXgE7z5atyDKV42rINsqG7R1b3SRlCwnhyzMCQZRyVTsuSzpzJv7VlpsPDI6Y2bjWwqsx6U65ZntnYL3nLEZkyQ0s6mqWVwrOlxj2u6uqVjZUEq8xtbRJYVlsJ7XNOngeopiZu6Xzcx7Ku/LjrzsuOmDxcX31o3xehnjJOysJzjNviXHzrBbdJgKoeE1UT1nf/Sa7DebifenN7k5hQ1TM+en9R98RCI0oavpkAWO6B5xhwy/dM2wTA7VkicpmI3FViY8mldduvReStItJT2vDvo+niHyo5KPO3r5Fri9kUQBi5M+28Ui4t5wNA+xq5tux34aiS/PyIfcKPQwS2qQgEcLtNDWe4mRCByggEcDs1T4TK3tzatWomhMwXN2Eahku4CqvTp/YoTlbMOZAyc6yvZIXtWOzbDrAF4O6///4VuWX0HWCM2zJt6dKlZdMrO1o33HCDYUGps+s23J7vueceI1/eZZddJg3c2qV+fKZR0wlu4/L83JgkZXrdnFsm5VGyWK4JgGJchiQty7vyZbkx25AcU8MVQyjO8+TaHimUytDyy57n087HBdBiyKQyYAW3mDctW5+X/OBYDdsiWK00b2K8evIDsraQMqBZmy8fluuOdzoWWdSWk87WMTOqqJq4i9qy0tk6VmYoPwCw7avMw21My5KOrAzk+4wSwV6sqfYlSAKeFKTBWmt+tcvE887bf4hvPWAwCejUes/13H8SQJxUypwE3NZSPsgd36g48N3k+4WKRksE8e4SA/t5mQC4JdeWnFuWcHiwKfkDGF1XMnyirA8yYfJjyZOlfXdUavzu0f0/P7pm9amIZ/XHowZUlPv5ROn87Ma/OYZtgGVfYzv7cY33TM1vxHDWEIGZFYEAbmfWeITehAhMagQCuJ3UcJqTqUwRt2AmtTCnytYyIQLUkpOqQDfKDTlOdmybNgFA3aaOxZg6+barbHm//fYry+3oH/2GuVDZ70tf+lJvyZAbb7zR7POyl+FJUtnWrVsnMNPk5/JnoswtMcU4yAYHPqdlBbc+4DvZsuQtBW59k3Tujf5oPnffoMi6goiFJyXX2CBLO8eAaldvv6lFG9VceS/7Ab4Aw2vzRVZYmw+ssm0d+bCbhyryfH1Oy1GOyADrWZbTsX8/kblZkfkds8oSd8ytAPauwzN5uCkployqB9wpuAWouotQUfHzgbQ4YyPOxXeB57eW6yQBqnpMrfJ7+pTkOkkk0/qM8bdK32v5Qk8E3LpxYGEPLwR8D6ox+xMAtwo4ubUficjbnHs8oMTq8mOo4r8HcFvLUxD2CRGoPQIB3NYeq7BniMBWF4EAbidvyOyJKyDj1ltvNTJRDJlo5HThhqxuw0yUAajkrPqAWpzs2DZtgh11GwYpXA9TJ992FzzTP0ygmCgiQ4al4BxR4PuPf8RkU+TlL3/5uGt3dXUJsmZq4O6+++6R4JYJrFvnVUEo4IPJpeaSEl+V30aVEVLn5GrgVs8bZShV66R/KsAtsWJyrQ2gA3uEcdeee+5pnLFPPfVUs2DitmKucp/0DjfI+r5KQIlx1NycSKaxoVj7N52Wp9blKwCqfb75s5pkPjJg5yJrujbJuvyYjJnNrU2wu80Cc6uNZwvWfvFOS+R3tz9Y/nlHc8ZIou3c06jSRDt3UkN3TLLcPzgsT6/vq2CiYZQXNIs0yLABQ5y3q3dAVjl5uO25jCzuyJo83CRALQl4AtzyjFUDaXFlh7Q8lLK77pgnuRd9n2p9zrlmEkCchFXmWhNxWK6nNm5UHFj041vIO6byft9viQmAW82f5bQ+52N+jusxIPddo+KZ74tIkCVP3q/qcKYQgXG/20JIQgRCBLahCARwOzmD6ZMh33HHHYYhOvroo4UJExJg220Yp2NAAG7DgBe3qewYBgFTJrfBrmJKBeiBHXWbbeoEyHSbgud99tnHsH7qhgzA4g/5ukj0okoR3XTTTQZ4vuIVlFysbEwOuX/ybclTc5lbAD7X9IFbJsVMcAGhahLF2QHbTDar1citBm7t8wJ+XXBb7wR+KsEtDto4tdInFkhgwll4oBwT7bWvfa1ceumlFUZh9GflhrxsdjyNOlsaZU62COqU2V1fENns5LVyXs3HBYS6zVcWaE5zxpQMssEqcb3rL4/JS/bbuwLcYjAFaLZbT2FIlm+odERuSossbstIa3OuvCvmVkiMfc7JA4V82ZWYPvLHbi5QTwIIk4DbekGaMp2al8u7FZVfDdhlv3qfWeKSBNwmOSYpuK0375h7SlJTOMqADa8D+oARXzXjtwmAWwyfriw9o0hucDN2289F5ORR6fInReQLVu5sNUOpP4/WuN1PRDCRuqp0QnJwycWtZij1y1I+rp2rOzm/GMNZQgRmaAQCcztDByZ0K0RgMiIQwO3Eo2jXrrVNo2AuAXmYNQFOMAYCSGpN2jhDJ2Veyf0CJLrNzmuFJRsHRixTJ8Cq2xQ8Y+rEZA7gCFuh/YsrFXTLLbcY4HXUUUeNOzeuo7fddpuRQwO+k4BblW3zty0HVXDrM6PaEuCWca3G8Ghwasm5VeYWsy4YfeKrObeAhauuukrOP/98IR+buN58883m+UKuu2x9r/QNjBlB+YCqARyFAVm2oRIA0seGlMiiWY3GaIlJvQJWX44r+/vK6AA+kQM/9vcn5djD9jXg9prbHzRsbUdLJbAtMqyUJhqTN8/KNkhH45DksmOO1Tg3r2A/rJlLzXZOxpxsYHBINg1lZGN+DLEzecH5mTq2dpup4NYHBqvlVzM+CnDrkVjHlYzyfRGTgNskcebaScBtkvJBujjlvr8sOvKNocSaqyqxYzMBcEs+LeV3aIDR+z0x/4OIHCkiHyi5JCctBcSq6LKYUkCAa1ybucatE/+NGM4QIjDzIxDA7cwfo9DDEIHEEQjgNnHozGTbBracicmQggLAn7I3AEaArV1iJsrQSXsUx7ySF3bXXXcZ1hag4zbNewUw2S6fup+Ca/7vc0OOKxWE7JpJJcy025igsh0jK2TR9YBbJo0wMTQtPWIzg9WclrdlcKsxRvJN7WMYpre//e1yyXf/U5Y5cl3bOMoeG/DhE8/1VEh72d7UkBIchBvHyscWJ/bpBlNDtgI0MxOe0yzk5NoN2TDsKjLjFcuXlcHtn+9/UDrbWstAAYiK0/Fah2HFEXleS4MZe5XM+thi1zl50+YeWdM7XDbGok8NqZQpG2Tn62pfk7CdytzWI3vl3VdZeS1fmVqYTnVi1u+Ofd44J2bdNwrUVetjkmOSgNukJlQKbpOUD3IN2zDSY1EJL4JqpZsmAG4J9R0icnDJnRiXYrvNKdW+bbdqz6LPXzVaqmd+hJQZ46nLS3Lmg5zz3VsqA8Q+mFTZDVk0+SWrSyZWY6tjtTy0YZ8Qga00AgHcbqUDF7odIlBLBAK4rSVK4/dxa9eyhwJbtgEckSLTYFUBmO5EyWfoZF/JLqfjY15V+ks+LQDSbXbeK/VmtTGBBGwCXmkwfzgmuywFDAYMYVSd3dtvv93UhXz1q1897towH7CK1PCFeY4Ct4AF2zhHDaE0nr58xVrArUqY7Y7VKkuulQWrd8I/UebWvperr75aTjjhBBO7G+7+m8yZv6C8uXdjl/z6R9+Vq6+6yjyDjDfj/5a3vEVOePMZ0jtU+Wu9b+N6ufX3v5bf//735pkgl5tFmOc9b0855vWnyElvPaM8RrC7C5pTMqet1TzPjPHnPvc5s8gCa7vnXv8sbz/r/fJPL3ihAbdLli6VBx94wOQNG4OykRFZuaEwjmFd1J6TzpZMWTKbyTTJuvyIbLBq89LrhW1ZUxZIG4D6H+t6ZcAytyIPF+OoXMZC6lbwkrCQKnutB9zWy0DW60jMuPIM8s6oysF+Roi3nbOr35965fScs95nnWOSxDmpCVUSh+Wo9/Fvf/ubWbSk9NkUglutP7teRPiA3lMaO7T4gNQ3jcqLAaUHyliKO2V6vioifyuxus+WjsF06iYRodg59WqRIdvtjSLyixKAxdr+idJGPho3isg/j1pCfLBUMijZL8RwVIjAVhaBAG63sgEL3Q0RqCcCAdzWEy0xQIFJKJM93ICRy+JGrG7IAC9MnMiNBHgwScJwyVdyJM4wKo55VXYU6S99cBt9AIAiaQZg0pjQ4YYMcGbiywQ0Kmc3rs4uObUAbMCtOwkkDuTkUiuSvrngVkv6KLglrgogdKJO/4iv26qBW2V9t3VwS7wWLFgoXV3r5Uvf+g95zYnMX0WWPfZXOeutJxsjMFhzZOY8r4BPmP6DD3+ZXPzDn0umVAd3dkbkhqv+T9595plmfxZiFi5cKCtWrZK77rxT+gsFOfJVx8rX//NHkoXdzVFOqDgiv/rVr+TMM8805wfM7rr782T50/+Qv9x/r5zxnnPk+5ddbGTpvA+M87CkDMPcZ9W6xeDJdkTmedzc2yfrC2npGxwjkdhvp46czLbY4mp5uFq6yPd2JwFd0wFukzCdNuhkUcZmdqPKDikodhnLal/CJIA4SZxrYa99/azFvMs9Lqq8E+XV+AahtJlCcEt3vjaqwqbGLVp6mFxKAcG6UrR8RQnAPm71G/aWnFuAcbeI3FAqJYRjIaD4W6XcXF+IKC90tojkR+XH15euST5Jm4hQA5cPyFhdr/p+LYa9QwS2uggEcLvVDVnocIhA7REI4LauWJXrVTIJIy8SGRy5kTQABWV+mNQtWsQiuhgWLKqUTlydWmVeo5hZZI9InwEl1Lp1m4JfzKgwpeJ8AA2AZWdnpznuwQcfNJJlHzMcV2dXARPmRy7ryzVwUyYO9K0auKXfvd3dMrBihTkPk24ALIsDvlIcWhIIwOROPgcGBqVQyBvmkcm+3Rgz+7w+Qyn6Dai25eNRTwjjzAQZCW3LzrtIqmm8CZN97GQxt/R7VXdBTjnxtXLHzX+Ud7//I3LuBZ+S5tSAHP2SA43b8uc//3n5yEc+Yu4FRvUvT62Uc8483ez/3g/9i5z94Y/J3JaMtKYHBHk893HwwagkRdb3DMjq7rw8u2a1nHP6KfLoXx+Sb333cjnr9DdLb29P+bk+8MADjez+k1+4UE552xnlW735mt/Iee85w4BeBbeN2WZ5ZkNhnNOxy7D2FQZk+Ya8WKnD0phOmxJG1NzVtjE/aGriRuXhVnurk4CurQHcunnfcU7MvGu8I1FOzPU+u27Mk7C99bLXes16zbs4Lqq8E99I3n9dtIx6liYoS9bTvkFEzi3l3rKSR37sFaNg9Usi8pzn2iwtvU9E3ikiyHUApNiRA15/EvPbjBq454jIPij3RYRC5jgxX0IFu9p/E4Y9QwS2/ggEcLv1j2G4gxCByAgEcFvbw2HLkGFEmBjecMMNBnyR/4j5EmCVnzMpQo4L0OVnUW7DcXVqbVMmHzNrs6O+0jAqDYY9BYQjM2bCC5CFoYPJg32OysmNk01zLOwyObduTU4mjtTBhQWEAYkCt0zIAX2Dy5bJc6egxNs62y5XXyVNnnJM9t3Uwn7ZhlI8N4Btm2HDOOqZrj7p6R+SfznnXXLNFb+Uk992hlzynYvlJz/4DznvvPPkpJNOkp/97Gfm0nYe7LOrV8lrDttXZs9uk7sffkqWdGQN2FcZNvm4q7sLsr53zGzq9ptulPe+5Q3lc6rU9t+//nX5zKc/LQcc8hL53i/UmFVkTpPIrIzI6ae/Xa688koDbu+89wFZV0jJkGUIBVAF2Daicy41LxPr1OZlV3J112yqrM8LA71k7mxJ1TBjmQi41XJDtTylxIr3wqc+8B2fJBe4lmdKr6WO7rxv6ppt90MlzPztLlbpwgzfu2oOwr7nvVbDNY5Nwl5zXL35zRzjc8AmRriSs3BGqscUM7e1PEZhnxCBEIEpiEANvyqm4KrhlCECIQLTEoEAbquH2a1dq27ITP7+8Ic/mEkgE1iAJACSPC3NE41zG44zjIpjZm0AifmJ22Cb/vSnPxkWQhlG+keOLS0qJ1fPAwPIPXDMDjvsMO789957r5E345bssqRMugH/8+fPN8dHgVs9aeOzz8ry40+Ylmd+Ki4yHeDWrQf70bPPkGuv+pWcedZ75NLvXCzHH3+8/Pa3v5Uf//jH8qY3vUkAi8u7+ipq2b7+qEPlyccekYf+8lfZ83l7lMFtKt0gv7jy93LnnXfI2mfXmOdFkOD398pVV/zGyJspOwVgG0ml5bWvO0Fuu/mP8v++cpG84bS3m/qxi9uapLmxmGt5xRVXyFvf+lbZackS+e1tD1p+yGKMqHbsyJljtMHEUsaInFxtmEEhRdb6uWxa1Z03dWzt1plNyazMiHn/amlJ3ILrdeNNYoyUBHTXogZwY6KMpaZKcF1AZbWyQ7zPXKsecJukb0kAPvdXb34zx/jYeEA/zC3Pku1T4HuuJom5reWRDfuECIQITHIEArid5ICG04UIzKQIBHAbPRq+2rVqGsU2wC0THBoMFZMhm8GMcxuOM4yKY2ZtAIkhlNu0Di4/R4YMyLTltr6cXPsc1LiFfYZ5hYl223333ScAdOrcupJIJszItnGJpl6kDW51MYAYEk+YLZjbp449bia9GnX1ZarBbWE4Jc905SvYz/ecdqLcccuf5BOf+IT827/9mxknFiNqaSx6UF+ZZ+yJJ5+SU089Tf7+eNFgzNeQxpODvX7jJnkun5LjXnqg/OPvj8t3f/prOfxlR8rSOTnJWbJhng1ky5QC+t3tqCaLrS0j0pEV854oU9jVNzSOiW3PNsiOc1rKTOwwJYao4VsYK+ILOAYkNwwVywT5zMd895JELrstglsXqKo6RfN2bbCrceQ95081RlP3TQJukwB8rlcvS84xPnDLs0HObXt7u9dh3n6eArit5UsT9gkRmJkRCOB2Zo5L6FWIwKREIIBbfxjtiZ5du5ZJnU6AAHY0WFPkt26LM2SKM4yy81YBiG5jEnrdddcZJhYgoU3dkFWGDHg84ogjxk1I3Zxc9/xxOcHI98gp9hlmEb9rr73WgGrqRSq4xdxKFwS4HhNsWN+R/n4ZWLmy3AVYawW+br+IC5Ng7suVT/Jztusk3D6WuMCway6vm3NLn5nw1p5zO2Tye2vNua1FQurKkvv68pKXRlnbM1jBflIP9oDn72zY95/+9Kdy8sknGzk8Y/6Ko18ts9o7vQ82LOisXKP8ywUXmMl716ZeOeLwl8jjj/xNXn70a+QdZ59n5Jh777xImrMZcz7Oy7g98LdHDROMMfEJLz/IgNvLf3GFnHr8MdLYMOZMDPt63c13yXGveEkZ3DKRWDArYyTLjFEx9iJdBZHNY3jV9LmjSWTerLE6twNDw7JsfV7yg2N+N5Q6Qtbc3NRQLrc1E8GtlrKq5WOdhFGOMkWqdj2fHNe3v4JcZXbtfWopO5Skb0likIQl5158Cxb0GbdkvluUWKvWArit5akO+4QIzMwIBHA7M8cl9CpEYFIiEMBtZRhVhowLMJOcBQsWCKyVMhW2KRMgCUDkK4XDWeMMmeJK+cB8wA4j7fUxs/SV8i3UqFUzINsNWfNZXfCrd6w5uVGGVHE5wZhRsY/PMMvuG30H3NIwmFLWjomsglv3YSbfmP3IfXMbAJSJpVtGiP04J5NWGGrXFIo+AejVhZl9GT/+z/jW69RaL8tUL7jFqGzVxsI48Afwu/tP18mJJ55oFgaQj/OcYuzF8/Kty/9HXnrU+PJM/DLfbV5LmWHt6umX2/78kJxw5MHSOW++XH/Pw9LWnDXuxSoFRuaM3JmSPlff+kAZYL/71BPkrltvkssuu0ze9a53lYdocGjE1Lq9+sor5EPvfqsBt7+/40FZ0tFsQLW2wSEk03nptZyj6N/cnEhLY5HZ5fkdGE6Z/QaGx/xuso3FUj9NJdvmes2EJsLc1ip9TlLSJkm/kgDIWsGt/d7pMTxvvCeuE7Ov7FCSviWJQZJY2+DWHlO+LdS5RXHCdz+A20mZZoSThAjMuAgEcDvjhiR0KERg8iIQwO1YLLVEBpM3gOedd95p5MYwV2wDrMLGqinT2rVrTckfXykczgqgY6IUlbMaZxgVxczaow+4bWtrM6ZWNvAG0CJTxbHYBr/2sXGyZ1hZ2FmYPN9Ej5JCK1asMKywD4Rec801Rt5HP3DkhWlVcyvujQlzNXDLhNnHxrllhOx7qgXcApw4t80gq2MsiwO1sm1JwW01gx1lbq+97nrZZZ8Dpc8Gf+S1tmdlJL/ZjDfP4hlnnCHf/e53BXbz01/4qnz5M5+U4994mnz2698xOa12Div1YRe1ZU24nt1UkOc298v999wpp7/+GHn+3vvIdTfdLju0ZSsY/re+9W3yP//z03Hy4v/+zoXytS9+zrD2yM9p5AQ/vb7P9OX8975Drrv6N+a4++9/UOa0zyqfl+3sx/7aYGJ3mN0oDSNDZbOjvkGRdflKG9eWpqIRlYJvjk8KbusphVNvHdV6F0q4jyTALsrxt9pvCAWq9dTsdY+xvQh0kci+pqZn8J7z3ruGc1H9q2UByD02Saw5h29M+RlqBRaL+PYHcDt5c41wphCBmRSBAG5n0miEvoQITHIEArgtBpRJmE7SmLgB/G699VaTa4p8E5YSd2GACeY6gMdqbsGcMy5nNc4wysfMusOPLBmACGh8/PHHDfDGCRmQBBtpg1/32DjZs+bskku86667jnvyyMflHqPcoJElAyCIa0dHhzFpIZawP4DI6Qa33AALCtpUWsnYu+6xAFzNCXWlz3r8VILbH/7vVfKig19SAf52bM/KjdddI+eff75ZLGDR4eabb5bcrDYj2+3e1C2vf8UhsnrlCjnnwx+Td77vPMlkm805Mum07DG/RZ76x1Py2+tvkle87iTz8/Xr1spRL36+AfuMFyy8th/84Ady1llnmWdKc2cNu9qclsGeDWbRBzBw6aWXyqlve0c5JxhQe8H7iqWAYHwffOABs0jB80iNW/o66DKxnc3S1FBccOC56BtukLW9QxVS7NZGkU7q7Fr5uoCmbQ3c1gO6k7CwScoaxR2jYFclzL73SReQqgHdJHm6SR2WfbVx+T7wbmGg5/MZsD+CQZY8yZORcLoQgWmMQAC30xjscKkQgemOwPYObqNMo5g0YroD68nkmYkM8mBYSDVPwj0WAOgzVGIc42S96mYMMPWV8uEc1cAp22HNdGJpA299jgC/MCcAULep7BmWgrxYt8UZXiHbXrZsmanzC3tsN/oEWOJvJrNMFOkfoHs6wC1jpG6wNhhl0cKAvUzGbNd8as2xNi7BTovKL5wKcLvrbrvJcmL6sqNk3vwFpieD/QXp7e6S+++/zygKaCeccIJccsklkp3dKSs3jrkMP/7wX+W8d54mK1csl/aOOfK8vfaWBQsXyXB/nzz+6KPy978/Ifvsd4D86IrrzHn4Bf+Nf/uYfP8/LjMAF3CLdBxWnsWLd53zIfnexV834PbaOx+SudkRacmkDVOPK/M73/lOA2L32mdf2WW3PeSZZU/LQ/fdI+967znyvUsvLte5BdxuKgyZ2rQ2m9za1Fghg+Y9W70xL92Vhsgyt6VROrIpswhlAycAs46hLwfb9z1NAqCSMrf6nNXyXU/Sr4mA23rKGim4rfUYxoi+MV46RhoD/q9A1y07lKTkUFJw61sU4f2iBBrfK59DvD2OAdzW8lSHfUIEZmYEAridmeMSehUiMCkR2J7BrV27ln8z6dI/ymoaAJBKGSdkTHVsl9BqhkocFyfrjSvlwzmqgVMt5cN+MMkAZDfPlHI8AD2kw26zHY0POOCAcdvjDK+QXCO9xnUXZlYb9wXTzfHEC7MrWG/+7YJbAKbrtMx5yI1l/3plyUx0ASIuuKVPClw5Lyyyz1CKY5lwc7yy+W5+oU7MOY+WWHLj7ns542Sn63r6Zb+9ny8rn1lePpxrACSJ75577mliedppp8kLXvACIytGXmw32M3GwV75929fJjde+1t56olHpb9QkHnz5sv8HRbLwYe/XI4+7njZc68XSCadMmAVU6af/OQnJn8WSSaA7J9esK+8/axzZZc99pRjD9tXFu+0VB5/4gnp7+sxIJg+UbTn17+9Tr72lS/JQ/fda7qxx/P3knPO+4C84vBD5Hl77GHA7f33PyD96ew4R+Q5zRnZoX1MBg3opYYvILgMhCQlizuy0tGcKf9Mcz6jStjY9Vp9rr5JQGS94DYJ4ErSryQS43qdnwl8kmNstpdz2O+T7cTMGOmYsQ/vST0lh+pdZNIHyVc+iO8UOexLlizxmgQGcDsp045wkhCBLR6BAG63+BCEDoQITF0Etkdwy8TKBrbK/Kj8lIkstQ6RqPEzzJrIHXVbXM6pynqR4gLq3BZXyof9AaeADVsuSn9hF1SGDNh65Stf6S3PceONN5p7eNnLXjbu+raj8UEHHTRue1wdXF+pI44B9AP6mLQCXmGN3Tq33DuT34mAW5g6JsV2c8EtsdJJtjJIalTlgtsoY5q4/ELiyxi5LJRvvAEjbs4t51/VXRhfv7W5UVrTmG7lKuoIAwJXbizIxr5KenN+a0ZyMiBrC2npK+Wzcs/k0a7uLlQwps2ZBtmxvUn6831lFtssKuQH5RmHXSXPdcmcZiEvVkuu5JqbDQvbnR+zOk5JyoDVOS1jQBRQ9FzvkGx2mNiFs7PGEVnbIKV+1vdJ78AYsG1IpQyr25qtHGM3rroQwrgCdOzmMzpKAudHQT8AACAASURBVCLrlT5PBNzWA+zi5MK+3xxJgGqSY6qxverErIDX7SfvEu8UYxpXdiiJw7J51jdtKi/U6PXxUSDVAo8BTKWqtcDcTt28JJw5RGCqIxDA7VRHOJw/RGALRmB7A7cqQ6bMDWZIAE+Aq06gkBIjx1S2DsYMZtLXqsly2T+O+VRwGeVmzDkwhKJh3ENjYg4ryiQMkES/6etRRx3l7SPHc89HHnnkuO1xOb1xbs6Aa/LTYBMpnQGA1fJDsIwwIPTv8MMPTwRu6bDPnVZZ2Dhwy+SYSblKo9lfJ7QwwrWCWzdw+gwxuXVZXZuFUhdmPd7H3A4B6rr6pKffYitLxlGwsC4YVjdicle1ab1XXIaf6+6T9RaZOyvbKD2FyjJCbblGUx92ZHjYxEelszDHgGC7wZhiYqXvB/EbSaVlbb6YP6sNg6clHZVAlNq0T6/rkd5BON5i4zzkDrdbTCzGUsvW90n/qCmWNljlnee2CM7Icc0GKfbClQIo+3jb6Kie3Nak4BYFQC2sPn1M4i48EXBbq/MzfauXueaYegCxjhXfN5vV5Ty+BQp7TOMUEb7nRxeyeB74LmijvBu/AygDxDetWgvgNu7NDNtDBGZuBAK4nbljE3oWIjDhCGxP4NauXQso4w+5puScsvr/8MMPG8DLhAeznL/85S8GXJFT6mtRslzdV5lPWADMf9ym4LIagL7ppptM38jrRTIHo8wkWGXI99xzj5lEHn300d4+cjyTsCjwWy2nN87NmfgBcHGDXrVqlck/ZjLP/+kfOcvEHEl0EuaWG0oKbhlDBZ62RFnZ+Grg1p3wRr1kNjvHBNzHQunEHKCreYjK3PpAHewoLClsqTtpz2PGRFkcGwQ2UBYnZ8r7FPoH5Mn15LQWewzzOUQxWavNn9Uk82dnTa6t9r8xkzH1Zrt6K+nVBbOzwv52W7dhk6wtpASmVRtGUEs7myuAqKlN25UX+qwNAIzTMfemrbefe+oTQH75fGmRnTqy0pytvHbUOPgYON23VqOjONZ9poPbWnNhiUsSoJrkGAW39YBolVmz8KDy86i0AB0zrW1dz2JFlEqD7xjpJJjy2akWvmcvgNsJTz/CCUIEtlgEArjdYqEPFw4RmPoIbA/g1paV6kQJIyRktS960YvMyj2gkQkcEzHAGZPFavmqjIzNXALm3BYHDtkf0yWuFQWgb7nlFiOrhUngejTYZv4PC3b77bcb+XRUrV09Pgr8VsvpjXNz1jq+Wk8X8y1ip0ZOOPnCxCCJdsFttZI93CPXZtySglsdC7fU0FSAW5uds5lDX4kU+sWkfEAajbTYBp+5xgZZ2pmTTEORrbTBbWE4PU4ujLQYYNtY2p981Y2WTNh+HnlWYGDt3FXehU09vdLVn66sN+thV82YFAYNy2zhUGnJNMiSzqJkWZsPhFOTdmerNi37IqtesbFQwdTNakpLR2ZYWhwpdrUvYTVw6x7H+ACgGJsooyOfSzbPo+Y/1/JVTpIHmqSsTz3sqPY7CVD1OQvHxSHJdXxMdNwCBQtIAOF6WPKo8kEsbrJIh8dCHCgP4DbuCQjbQwRmbgQCuJ25YxN6FiIw4Qhs6+CWiRGTECYz6rLKZAhZMvJjHDFZqWc/DKOQ06p00ZUEu8FW5nL//fc3TspuiwOH7A+AhslDuutrgFNljdgP8GjL5ajFC0P8qle9ysj33HbbbbcZKW4U+K0G4JmcAlBxDsUl2m7EiwUBYkejVBCg2+4DfQdIIKmeDnDL+DLZ13Fm0cCNyVSDWx+YUka3CHZHTP5pV3/lnrOzjbJTR07SFkgs5iXnpW+kUdb2VuaStucyxmgJSTINBvSpdUUnaLfZbLC9Ld8/aFhTq5SuAanKHNv7ru8tuhjbPLDbB/bfVBg0JYFsR+Rsg8iu82ZV1Kb1mWFRh7czVzTpqoeF0zxgW15a7cNoy395PtSYypevy7cAsAvoUiOtWj66ScBtEufjJOC2Xhaa+01yzETAbTUmWtMCVMocVXaoGhuv4NZ1sybflpSPvfbay1u72x77hOD2hyJyepVn6FERGS/zEeHjfraIvLO0HUnEgyLyHRH5acwz+ebSsS9E0CEij4jID0TkEqksI13Lox32CRHYJiIQwO02MYzhJkIE/BHYlsGtW7vWdkOGuSVnlsYEB/CGPNlutiTYFz0AG9Jk2F/Kp7hNS/0AoAGlvlbN8AkZMrV0mczBDHMO11lYa+1iKOWaK3G9O+64w5SPAdz6jFmqXT+q/0zciR25abQo2TXAmkkxkuok4JYJqFtiiOv5auQqmNB8PcYU1tZttgtzVM5tElmyW3bIN9ZMhlduyMvmSpwqbRmR9iaRhoZ02TWWPgwMDJoyPz3O/kiFkQxrQ3n85NpeyQ+OSYB1GzmrSIFhTu3mkwObfUv1Zu1zr9lUEPJx7WbLm/Xn63sGZHV3JQCelUnJnKYRaWubbXYz5lkbC9LlmGEtassK4DaJ2VNScAsYdmuuKmBSwOuOI++fgqZqRkdJTI6SgNskADIJUJ2uY5KAdY0bY8k3w87Z1bJDLhsfZfjFd4rFQtzI497pCYLbW0XkCc93YtVo+vXHnZ8DSH8pIsdTqps1URHhA4DRAn9/U0Q+EDHHuVhE3ici+dJx5B5wHC/kr0TkjQHgRkQu/HibjkAAt9v08Iab294jsC2CW1vGZrO1OhkFNN53333lkhO4IfsmMrfeemvVfFYFyABj2E231VLqR/NSbcMn+o/kV2XInDcKvMbV2r3rrrtMrm4Us+u7vt6Hr/9McnFD5m9ixsQy6v5VMk2+71SCW7vMD+w2/59p4Jac0mXre8fJfxfNzgjGUa750dCIyLp8SvL8o9RgaZEW22ZMbPIZQfFzzKRgg8l1tZtXDuzZt1iaJ2/YWG2caV5zWhZ0tJZ/Brj2AeAFs7LSki6qJpB4GvOsDXljcGXfE32cnSs6ItcLbqOMgap912uV/9rpDPTLbcrqamkoe3sSk6MkZX2Sgtt6JNbcVz3Sb41DEkA8kTxdXaywvRV4r1ywq0ZvjKkrZea7u3HjRlNWzVeizB3jJ54o4lNydPnmxLVUKqXMLQzs5XH7l7Z/ZPR1/pqIsBr7ilEWdk3p588bBao3jzKwC0XkRBH5jXO+k0Tkf6lKJyIvJZOmtJ39bxSRvUTkgyJyUY39CLuFCGwzEQjgdpsZynAjIQLjI7CtgVud2JBPC3uCkZMytkxykBLrhEQnJUxMfC2O9SQ/i3JAe++9t6mL6La4OrLsj3SXybYaPtk1YgFqAEgmW2z3TZ7iau1iOIXMLgocV2On3VJFmK1gssWEkfsFsMDgwnLstNNO4+5f40ff1TlZ69xG1aPVkzBpZ59qzC2xIcaaP8nklrFmUl0N3HINX51bncRPNnMbZxyl96xgqq8wICs3D0qpmo/Z3JASWTSrQVqzxfIoKrfGuOnxZ3tlpEIwLNLZkpFFbTkpqZbLY/Pcpn55dnOlI3J7Ni07zinGTluUIdTcphFpzY45zBoAvCFvSghpoySQ1qZV8JVraZWn1/cJsdCGBBqmmNxhbQpuay2HkwTcJmFIFdzZ9Y+rMYQ8u76yT9V+ByVxPk4CbpMA1ek6Jsn9xI1nNTZe3c157vh+sAjHve63337jWH137CbI3NYKbnk5kMggK6Ke201OP5A4A5LvFhG3nts9IrJ/SQb9X85xnAsrfoAvK7NjL2aYKIUIbAcRCOB2OxjkcIvbbwS2FXBrG/kAcGFdmbAgiWUCwwSIHFEkZ4BGckSRFGPMRJ6tr8WxnuSbAi4B0Ehz3RZXR5b9VboLs0rpIMr8AHCpsQh7QF4w5Slgdn0lRdgfeTB1cH05h3HMrubFAn7dpuAcSXRra6vAVAOsAPOLFy821+X6OEsvXbp03PEaP8aAYxmHyQS3dt1aBbbEHHALO+OLBxNX2nSBW0yYYD9t46hsQ7HMjRpH2YHz7d/UkJL5uREDcLUBbtMNDbJsIyDYcURubZQFbZWS7KjauHOaRDqpj5vLlc/tNYQquTL353vNM0BsfWWJTEmgOc3SWnJEBqzkB4ZN7d3B4bH5MxLonTubx8VgJoNbd9FD3XxVwuyCXf7PIouW7Ir7LZME3CZhR+sFqkkWELjXeq/DMUmMq+qJm/6e4DnTHGvGkbrhbGPxgp+z4OnL2bfHcJrALWYMsLPPiMj4FVQR6hhtILtGRFhhXFHqI/9ejhhCRDpEpM/z/HFOgO1L+FUU93yG7SEC21IEArjdlkYz3EuIgBOBbQHc2gYjKkPGaImJH6AR90sYViYjGD8ho2VChGwWEynMQ3zt3nvvleeeey6SNeW8gEfAMSDZ16qV2mF/ZTeZTMEoA9gwZgJ8828AOYwpjsO+HFKYVMyxMKRiMua2OGbXBtfusQrOtawOABdGQ68TB+41HxhDKfo4WeCWsWMsaXaZH/7Ps8CkeiaAW+TCa7oLFZxqc4PI4vYmyWXHcmY17utLdWZtqFrcPyu5bFNZuszku39wSNb0SQW7ayTDOZGO1myFpBLwi8sxebZlcIzEua1J0kOFCmmmzxCK0j0AVsA175RhjjO5ohmVVZbIVxLouY098lzvcEUMWpsaZcmc8XJp+lZvrdeoki7VPvRxTJ97bK3grhpDGFerlWsqSKunrE9ScFurOkHfKR33Wk27FNzWcx2OSXI/SeJmy8YZX77lXJtnQxvfK8YC9QhO8G7qygTBLUzqOrIHSjLjW0ZB5nUeBvX9pZxa8mPfEPFc3yciLxKR14rI1aV9XiciV4gI214ccRznRM58roiQmxtaiMB2E4EAbreboQ43uj1GYGsHt3Z+Ff9mEsmkBNYQlhZGUVlDyjsAZlW6CmuJnBZZra/FAUOYVgAcbCSA1Neqldphf3U75t8wPJhTMZHSFgdekQVzf5QS8kl445jdatJrBe/0BVMsGFvbtApGmdxl4goYd5suDgDMkXD7wG2UfFhlyTCstlyWyafmP/qOnQxwW6srbpQpjTFN6i6Mqxvb2dworelByWabKlh4clYxYsKR2G66fy5XCVZ9zCrHLWgWyZUUvowTf4ZGUrJ8Q0H6PbVxM2kxOeWad+gD1+T37tieLZfNAQD0j6Tlud6RCjZaAbBdEgiDqVXdY2CBPlKKCLAeZcY0neCWxRqfw7j7HNcKbu3jlIHW+sauo68vXzeJmVK9YDDJvSRZQEhyHQW39eYDJ4lbVG4331MWj1CrsEgGcKahzEFNY7cJglvfrwtyak8VkYesjf8+WjXrQ6OvzjdKf/uOI9cWsymA8LdLO5xXyqX9tYi8PmJuQ64t+104uq5w/vY4/wn3vP1GIIDb7Xfsw51vBxHYWsGtbfaiDpkKbF3QCNsAaLTBXy1OxgoMjzjiCG9ZCMAz4DTKLZh+UGoHEIZs2G2AYwAg/Y9yQ44Dr0iryRM75JBDpKMD9VlliwPHPuk1scXMCnMVGowFANUFJLDa9B9gD8B3m0qiuXckzDa4VflwFLhlwsokU8Et+zNmAEqVI9Mv1/QlDtza9XNdt2T6X4+U0ldOxJgmdfVJj8WSao1ZnIO5B9vEhv3JWUWOrM3krLZnpTUj4/I2yW1lf7vUDsctnN0ksxqLZa+0kQa7tiAVdWlzpdq4SKJtcL6hP+V1RK50ZR6R1V2bpasgVUsCRRpMzc4KLsvV2kwGtwBVn3rCdz8ueLJN7oi7DXbV0VfLldXD3NbzvNLPJKAzqiZstXFMAojrff/0+klMqKKeMxQ+LDyw4Mm48D4RY75DrudBQnALUEVCcb2ILBORthKz+vlR92Is9Z8t/V/lxd8dlRq/e1R2zPZPRcT8xyJCuZ9PjK6RfrG0D//mGLa9NeI4trMf13jPdjDdCbcYImD9ng3BCBEIEdhmI7A1glufDNkGtrCEgDr2o0QPExW3TA6Tzz/84Q+m/M+LX+xXbZHvSt3Dl7zkJWZy4zZqpiLrhR0m79TXfLVyfcZWSHd9js1x4PWxxx4zIPSggw6qqH+rfYkDx67hFJM+pNA4LDOR5/8wXMTAbcpcI6n2mXIp883iANLqpOAWMAAoJG6MI5NM/j/TwG2ccZRb+7R/cNhIe22TJXJWKd0DE+o67q4tyZzdcWDfXee2mMUA4oICYNPAiKzp7h8niZ6bE8k0NpgJPOPRly9IV39aeqxit7YhlF4LqfSz3QWhD3abVypLpKvggO4VG/LSXWEwJbK4I2dY27hWL7hNArzqydG0AWEScBtljBWXr6ula9TZNypu9YLbJPGarmMU3NYrZU5iQuV7zvi+sKDJ+8P3vFqpJ/qaENxGEUas+vxJRA4pSYSRCtMCuI37aITtIQIJIhCY2wRBC4eECGwtEdjawC1AB1BJvmd7e7uR8Kobsl1/Vdm9KKMlzoNkGMb0wAMP9A5XHLCEBUTaTBkg8nh9DTdiJkG2G7KCR8AZwBGQGNXPOPBKni5/DjjggHGyOfoTdw92XjETZfrGxI/cZAyt6D9MIwDVbQBgmN8oUy7NFwYYI2FOAm61tA/X5t/8IZ4K4lyTLWVumSATW7cxZlo/dzKZ28FU4zjjqFxjgyzpzAm5qDQb3LI/DC/MrTa3Jq2C26amrKzLD4+TOXMcv6B3n98qHMv5e3v7ZPNQg3TlK2vedrY0ypxcWoYGB8usIcbFa/Mi/ZZPqmsIxTX8gDUlO7RnZU7LGGD1GUxRhWh+TmRex/jFId/7MhPBbRJwl+Q+YCBtUyqNT7V83ekAt1Hy+2q/43yqhrjfiUlYZc6ZxITKl3fN9VmQ47uhLvvV+jzJ4JZLIS1GYvyUiKiJQ5Alxz04YXuIQIIIBHCbIGjhkBCBrSUCWwu4tWV95IKS62kzhpTLAUwxQUR+jBQZABzFunI+zJ4Ax9S59TWkuZQOAvwCgt1Wi7TZrpULiKWPsMZqbAV4rWYIFQdeYW05B+wzLLTb4sAxcQR4IivmXMQFgyw1tLrxxhsNy+eTVW/YsMEYYkXJspH4waKTD8yY+cBtlPGTypINgEulDIus7HsRxPWWwa57zyx+TBe43by5R/qGG2Rd31AFSzq7VDc2bdWYVXCbH2mU53rYfwzY+mrSMnnu6cvL+v609FnMqn2/MKcLZxfNqfoHBgzA7rNwLSysC0IZ4578gKzY2C+DaIhLrTFN3m5KmpsaTfyKObsiy9b3Sd+AbUYlxmCKPmvzsdaA+vnNI9IgI17lQwC3lRFQBhJZslur1d5T6+oyPrwH9TCdSUBnEnCb5JikUuZ6846Jpa+mMH2GueX3R5SDvj0OUwBuse1/tORwrI5zmjtbzVDqz6OgeD8RwUTqqlIfFShXM5T6ZSkf187V3VqmLqGfIQITikAAtxMKXzg4RGBmR2BrALc60dOcNHJdkdMCwJiEUEOVurZMjjCMwuAIUFctF5VRufbaa40bJuDL1wC2ANwo4FiLtBlHZoA34JHzAdToM4CQf8fJhilRwb1F9YF7hJ0lpxgJttviwLGCW46DoeU8nZ2d5dP4ZNW6kfuq5jit+b6HHnqocZ22wW213FjNx+U6sFYsVNjGPzMF3A4NDcsz63tk81i6rAmNkerOwjSpcjTo96oNfdJd6RslnS1NsqituD/jqRLv7s298szGgkTgWtl3SdF4jDHecclSA0LzVh3ZhhRleXLSaoFQ9vfl7R576L6y4pllZvFFyzqBZ58rpCpKDTWW6u22z6ICSbGRX+yy0NSu3bTy7/Kvn/pk2TSNcb3wwgvlAx/4QORHURlPxhzQFteSgLV63XXrZW55ZyitxcIaqQ+13IeJY0+PAbVuCkS1fF2O473i3QXsxhlkJQGdrpw+bkzYrtex88vjjqs3zno+wG29JlQ+aTpglW8W3gVRtc/te5gCcHtoqSTPehHR1dSkpYAoG0ROb7VSQJQKomQQ17g1bnzC9hCBbSkCAdxuS6MZ7iVEwInATAa3TOpsYMv/mcQgxQNUIQcGYAKcyMNEGqzsZRzrShgwe4qS3LI9DjjadWCjpM3qRsz5kCHvu+++FW7IAFcAbJQhFMD94YcfNsfhWOw2nJIByEiIqT3rtmrMLuAUWTETUSTelPlx836RJXOf1Kp1G+MAM71kyRLjpOw2Be4w47DWtYBblRzruXy1JicCbtWFGXbGJ0uudaKMnJh8Wbu8jhpBdVhSXb2P4ZLR1GbbaEpEFrXnpNPa3wa3f3lmQ4UjMZJhW8as4PavjzwqqbZFsWV56IuvPNHsprQcedALzSIR7w3gdlNfv6zaPFhhRtWULkqMM41pw6QDpDb0DcjKDZQ7GmOA23KN0pEZkhftu685JwszlNsC5J166qmmPFdUm0xwqyAT1QEgU1u97rr1AuiJgFueSV9JLzte6jnAe6C1WnW7mlNpzq4LdqcL3CYBxPXGWe+5Xmk2x/kWOHj2+GaxuBdV2m2Kwe3XR2vWflBEfj9aJe6Y0rVY4Vk1moc7X0ReJiI3Oe/O6aNmzpeLyN0icpCz7d6SORX7UHrIbpzrjyKyulTr1kpOCNOkEIFtPwIB3G77YxzucDuOwEwFt9VMowAoN998s5lcMyFiMgK4s4FZnFyXIa/GSrIdMylMpQDNAGm3xUmb165da9yE2Y8yEvTRdfeNA+FxfUDSDNuAaRZljdymzK/N7NIfjgM0q2trVCkhcoqZ9GnOsH1+zTmOKqfE+QE3mF2RnxsHbu0yP1pbd0uAW+6xGsCIM45yx4BasMvW5yU/OCbthVXdaU6uQtrLcTa4fWB5V/lUmEbZQBrZ824Linms19z+gOyw09Lyvs2NaVk6t0XssjzFckMFWd9baQjV3iTGwZjngYUFFAY9gzIOsLZm0jI3N4LdrrkOf20aSMmGfrsqr8i81iZZ0JaVP954oxx99NFG8o/8Pw6waefrrUFbDaxNFritFxAmBbf1ymsVDJYl5END48Au30i77JCas9XDqNpGZe73K+pXZxJwW2+c9dqA23qk2RznW+DgZyw28q1GWRPX6mVuyefdb7/9kA7/ruSYrJdA34+c4SuIVUrAFoCrjTI9XxURSgUdWXJUZhv15wC7SHaoV0u+rt3eKCK/KAFYTBOeKG0kf+VGEcEFETBNSaDQQgS2qwgEcLtdDXe42e0tAjMR3NpsLRMedUIGHLGNCQigyfx2f97zzCq762wZx3hyLAAZ5tcH3NhO+RpysHDOVKmm+3wwcUdGaEubAY9IRZEha4tyQ1bp8/7772/ycN1Gziq5qzCjMKRui+ujxkGZXdt0C7YbCR7MdxS4tXOG3WszGYTZhTHm/G5TMyvMrsjPtcEt+2puLBJUnWwy1rCCjAuTR8xdXFmnMrdMtH0O05yX8/gAVS3MLX2LAmOU7CGvdcjKVW1qSMnOc1vKxlF2HACkSHYHLeOoTLq4PyZQdgMm3vvXx+SQfYvO2wpuO3INUhiSct5rOpWS3ee1SEuuWFbnt7c9YGTJtJZGkcVtlXV0DWvslhtKpWTR7IxkhvsrShM9u6kgz22uBMBzW4t5vSMjw0Y6m0qnZV1eZLPtRIWOMpcyBlOM109+8hM544wz5LTTTpNLLrkkgNsafrEkBbeuizPfTN4R/uaP3XRBkHcfM7Y4R2COdV27a7iVRMckkTJPxITKlYATfxYbFy5c6P3WuvddL7j99a9/La9/vSk5i+yYPFnK/iA/xo0Q2Q3s6cdKQNa+HOwtObcA425ER6NlfnByeyWCoNFzfKtUr9Y3NN8RkbNJMy6VHyIp4qhSCSJq4AKAKx+SWgY47BMisJVHIIDbrXwAQ/dDBKpFYCaBW80tAwjBFqoTskrrkJIBNsm5pQHMkPP6WhyjyTGU8WFCEyWTxJCK1XZyeMnv9bXrr7/eAKzDDydtqWhUQh9hKm03ZOrE+mpkKrOKJJhJldsooUMeJLJO8ondhhkUebNRfVTmF2aXeHE/3DOyXNhcZM3VcpORfwMWX/3qV4+7NvcKS0WuL+dym5pZAdyRQPvALWOr8mCdpLOfsrg+cMskGJA13eDWJ+ltbhBZOKtRWluax93/xj5MmwoVDrjZBpHFszPS0sycdKypI/HDjz8pxx5GuUuRB5d3SUcWGXCjPAudWmrUnh0cGpYlc2eZnyi4ndvSKDvNLbK5gJuf//zn8o2LLpK/PPQXEjPlBS96sZz94Y/JgYccZsoNNaVHynV3WcBhIcQGyvzyf+9px8ttt9wsPOcA/v/36U+bHFoWI3bZbQ857Yz3yBtPe7vMb05JNj1s3MNf9zrm4OMbz6+94MMYfuc735H/+7//MwtWgAUYsxNOOEEuuOACI5X3Na7/7W9/20jieUfpF+c+7rjj5P3vf78xf0NGz8KLr/GuXnnlleXcVp4/YvWDH/zAvEswgbyLfBc+/vGPG6DD/QII7cWU3/zmN/K1r33NvO9s4zn/xCc+YcZbc24xZIvLg9U+1iqJ1/1rkfHqN1UBr11fl/PYrG5UbrCCW+7drfXqDXBCQJyE7U1qQuXLb+Y7x/NJ+odPqePea73glm/9brvtBkuKfJiPOcCWNa1nWGstlQBCSuxrrIS9T0TeKSL/VAKkD4oI4PUnUeNQ+jk1cM8pgWiA8iMi8v3R8tiXlAB1zOFhc4jAtheBAG63vTENdxQiUI7ATAG3tgwZ0MnkA1mjMguAOOS3TCjIq8V9t5rTcRwoJABMkgHKADcfgwGjiawYdhi5pq/p5BXwigyZiS6sI30EUMa5IcflzHKff/7znyPBa1wflfllsgYQYJILC02pCybdcW7K1WLEAgT3DxAAnLtNJdfkXDJx9IFbPUbL/Oj/ZxK45dlc1V0YV4pnbmtGWmRAMpnGioULZqvPeRjQjlyjzG4YlGy2klk1suWuvOQHhmTF8mVlcLuuu0dGBvpldV+qzBTjQEzOa09hsGwo9bvbH5CDXrCnYW11AeWTn/ykfPGLX5QXH3SodM5bII8/8ld56onHJNPUJNdee70ccfhh5dJExY613gAAIABJREFUDY0Z2euf/9lcW8Et7DBmVMe/5lUGJH70ox+Vb3zjG7LL7nvI7nvuJatXPiP333OXGa4vfPFLcsFHzzegjpzFr3zlKwYkkG/OopAuQCH3ZBsgCsXBsccea/ZHscDiCODp7rvvNs8pqQDkyfKO2+1LX/qS/Ou//qu5FmoGQDmLYaQhcE1AOCqJL3/5y/KnP/3JmMbxfNqLMyg9MLVCccH35M1vfrP86le/MrEDoLI/6QgoD7j+1VdfbRaXbCnvV7/6VQN8aRimAa75PnE/5557rnzzm980hlL1gNt6c0eTyHj5NvHeMgYAXbv0UFS+rh5TD7hNckwS+fNETKgYO1uhwXMEAOVb6fM3mCi45fhULVR5mJ+ECIQITHkEArid8hCHC4QIbLkIzARwa5e9YLKFEzKgE+aE/8PqAAIBYzCUgDMmra4c2I6igkKciaPMQZhIY3QEiPaxFnF1XLkeE2gmmbA76oZMH5ns1uKGHMcwA5iJh132yL5P+s99AL4B4W5TcMvPuUcAgW08FeemjOEUcWAsXAYKYIApF+AEUOA2lVwDfJm4K7iFodXcSo5BlpyStGxC61pqTMA5f3NLszSkK11zh4aHpK+3z7BIbp1bDjfS2VTKnNdtsP+Ml9bAVZMy3Q+GTvvE38iPV28sSK9VCgfjqAWzm2R2tqFYiqWxQeYv7pCGxrS3JiznwQ25PZsuM6Xab0rsLF+fl4Hhop+LDW6J0TNdfSYHVlumIV02jlJDqYceflT2et7uxXg1FxnkOZ2dcsmPfil77VNkgXnHvvTJj8jPfnS5keEjpwdMdPf0ydpCSl550D6y8pnlBtzCni6dk5NcpqGCAf3shd+S4095a7kvv//1L+SC959lVAA8x3a8f/jDH8q73vUuI0uGndW60xxMzI855hhjZnb22WcbIKrH8t6fc845hkl9+9vfLt//PgRTsSHrfOMb32gAyX//938bhtiWsrKwBCjR3POonFubtQOgAlSp48w57bz1iy++2IBgvh8s8tBHxg12F8DOPf3iF7+oYKphcj/2MZSlMiPBrSsx5rmwZcw22NV8XV14nGpwm0T+nATgMzY+lpxvKb9n+P3iK6vmfkvqZW45PoDbcZ/k8IMQgS0SgQBut0jYw0VDBKYnAlsS3NolLlQux4QKphJGkgkkDArACDCCYzATaVqc03Ec6OMcXAcQjITRZ5QSV+qGc8BqKSBi8gcDhfxXm+adYqzjslDsE5czGwewAQNMvGHIANV2o18AY/7m/jB2cnNJ44y3OB6AjcxS68zqNdQtGkaOvFq36bmJiU4mAQqwOvZ406cNa3rlp58pMoFbYzv1/ztQWuflZDl1ZitqwqZkp46czM41jiuP0p0flBUb8gYQa1u/+hk58kBS8ES6NvXKsg2F8jYbIPJDuxQQgNQGtx/77JfltHecVT62ozkjDfkNBrwB0GCp8oMjptQQ6cCvOfSFBtzecNdDcti+zxdANE3lvUcfe7x87bIfls+ndXlftO8LjTEZLKtdC9kGt5pzqzmgv/3tbw1IxWH8mmuuMYsmWruVfWD5Yft59lFg6HvDAgoSfUDne97zHtOXanmaceCWeLEIxbVRMPgAzfHHHy/0lxxi5NLE7t3vfreRMLvgW4PDu47iA+aWPtRK1tVrjJQkRzWOUdUx0pxd+13kPlhQ0rGqdl/qem3Xp457r5PIn5OCWx9Lzu8cFml4l/imxbUAbuMiFLaHCMzcCARwO3PHJvQsRGDCEdhS4BZgy+RAa9dyI2ocpbVX1fwEmRiyQBtcxTkdM3lHFslEBQmurzFRZvIclQ8bV+rGdkNmYoyU0s1Ji3NDjsuZjbuPKAAOaMeIihjTopjduHJH1RYAGDsYdNyqAc5u03NjNqULAOTnMjkGbDPRVuOnrR3cnviJ/aU7k6ooxwNAVAbUBmI8I5sH07Jm0xhwZTsAtL9rVZmBf2TlRikM+St0AC53L7klw7674NbOnSVHF0dkGiw7CyJ/e+IpGczOKZfwUXD72OOPy25WfvlLX36kybn9twsvlhNOIXVPpK0pLTt1thjQBkiFUf3xj38sb3rTm8qPgA/c6kbYUAAqsunzzjvPMMhuLijn4tlCEoykGKkywJzYAXqVoa6WpxkHbq+77jo55ZRTjDz6iiuu8H4jlIn90Ic+JJ/73OcMuGURCVUCwJxFH7dddNFF8pGPfKQucJvEGClJjmocuLXvRRcfOcY1pmK/avm6ScBtPX3TfiaJAcf6FhL4FrPYyAKcXes76pdsALcTnn6EE4QIbLEIBHC7xUIfLhwiMPUR2BLg1jY3UVkoE2X+MFnBKAb5qE9GqxGJczqOA6achxw5VuoxmPG540a5ATMRB1DATGrzyXbZptJcmCgfMxSXMwuLRQ4yUjnyC93m3qfdN+LJcRgFRYHbOFdpXWg48sgjx0mA40oh6bmRQnMfAFpko8QakKJS5W2BuT3wfXtLrjNbHp6WTIMsmdMsjQ1jv0KLRli9snEwLd2FStCqAFTHihPdv6xYPsltOBIvmt1UVhvwjO20ZKlxZd5jYVHZcN/T68z7s2N7VtqbMVYtNp4D1ziKnx932L7yzPJl5rkGKGvpoNcf9yq5545b5bv/8xs5+CUvlY4mkc6WsRxjHJH/67/+S773ve/J6adTTrPYbHB76aWXlmXgbENO/LvfUQ0lvl122WUGNPMc8gzSf9IUtE0E3HJulRDH9QSWlvvgGUZFAnijH75cfIymTjrppBkNbuthVG2gSpyU1bUXJDRfVwEvwA+wipQ7yqjKjbmC23r6liRPN2ohgYVOFlFI74gyM7P7HMBt3FsTtocIzNwIBHA7c8cm9CxEYMIRmE5wa5tGMdFnQqRsLTcCCwmbqixflIMw+8Y5HceVqeEcWocVQxjfZMZnmEQeJH2E/WISxmSXfvtku1wjjhmNk0/H1ZLVmr+w2+QX0zdltpADMwGNki3Tv7g6unHsNrmbSMWJodv03IBXJrnkSAMGNN8UcEvj50ODwxU5t0x0+ZNrBiBW5txyT4xvY6ZRctlK12HOR0xomler/eL54zhdUMnmcoJxEm1ERmRwcEjWbu6vyHE1/WtKSWdzozQ0NkpDeqx8D+d5dmOvdA+I5DqaJF2S8gImF7dny+fW6/cPDMqyrj5T1kcb19+xIydtOUpdipHjq5nN7Y8sl5bWoiOyNnJ3Kc1D7FSu+8zKVbI51SLU31Wp8l9XbDDgmvq49v3vutvuBsTazO68lgY57MX7GNALuF26886m3NGmwqC86+TXGnD7vZ9fKSccc5Q0DBWMgkKZ0yTgFqYUVhYZs1tPFLBCXBUQve1tbzOqAGS+vGPI73kmFUSxLwthvrqt1ZhbjoM9xngLJhYpcVTjeUNCjRx5qsGtW9YnslMJHYmTMKpRtYer5etqv3nXWciqRZqdpG9J8nSjTKjwJ0DxwvPANymuBXAbF6GwPURg5kYggNuZOzahZyECE47AdIFbNY1SAyVYSGSGmkcICCTvjUknQBPAyKQ2Sh4W53Qc5+RL4OKcgl3DJIAHpjX8HEdV3JCR/lbL241zQ46THTNxx7QKwEPOsdt0O3EC1HHftkQ6Lm84ro4u98c+GO64YJG+IO3k53adX+2jxpcFDOTI7Ae4Vem2DW7d++I++AModnN9eZYA/ZzHV16JbTxH9gRVAbGyTfRFyxDxDA5RC7YrLz39Y+5N/PKb25ySloaxnFiboXq2Z0g25i23p9G6HLYE2L4ngOey9X3Sb8mMG9NpWdqZk+bMGABl0WfOnE7p7e2Rn11zk/zT3sX8W0Cw5u7yf+TimkN9+8PLZFiKv6oV3Pbm+6XJqqNbvL8+een+e5eNo5Ys3Vk6syPS0dJkVAGA20cefUzS7YvKecMKbq++5lo5+hUvN8/YRMEt+bIwvTgKv+99VDcZazzPAFwdH7YwljyDAGHAJd8Kd9wBu+S826ZnUeBW68kiRYaRhWX92c9+FvktdQEUi0ioNljY8dXItmXJvLu1tCSuv0mAXRIAqeDWHhPfPdnGgIyh3RgXnptq+brat3rY3iR5ulGx5lvNYiPvgs+Mzr3nAG5rebLDPiECMzMCAdzOzHEJvQoRmJQITAe4tWXISL8ATFq3lQkN/yd/lYkreatIWMlVxUCGHEFfq2Z0xP5xZkfso5LhqOtoTikMGX+Y0AJubDfkOGYzDjzGyY7jQLrWmuV+6BsTb0CAMiVx8uy4kklx0m23zq+CEVhbmHGACWPIgoVbCsgHQnWsYW25N0CMm8es4JbJsm8S6p5XpYvK2PI3bLIurPQPjXiAJ6VwisynKg5Ujjk4NCJrCzKOgYWttSXAei+U7Vm+IW8AtLZcY4MBtmrcpD/v6h2Q15/wOrnlxuvl3eedL+d+9JPSmE7J0s7mChAM44jL8BGveJV8+4djwEzBrQ0uANQAawC25tZee8eDctAL9pCRgYJ57xTcXnfng7Jg8ZJyP8885XVy9+23mBI7MK2TAW4pu3PyySeb82FEFQdudTvSfhaXYFxhjPW74pazURCFGzP59Cy82DVvFdxyL7wrgDYYa9sIzu6TCyLPPPNMufzyy+Ud73iH/Od//ue4zxNGeHyfMJSaDnBbj4txFAtb7ZeJb8Eh7pePHsO7qwyvfYyCXB0rtiXpW5I83SgTKhZNUOSwaGnXM4661wBu456CsD1EYOZGIIDbmTs2oWchAhOOwHSBW0AajZVxWCdAGICHySrb5s6da4Atk4o4KS/n0VxQalr6JiJx+aCcg5qG5M1Vkz9jGsNEjAkRQAupry1hVmYzKm9XwSOmVq4Ekz7EyY6rldthG+CahQGYERyLXabbli0TX7fFGVpRtxNGA4CgTtX2OQAnTFDVKZc44XCNMYvGjcUAlaHbzG1ScMvYAtqrgVsm1PRXGWD6zHMC6OOPgtvNhUEjwaXkj7ZMWmSXea1CTVm3UYuWmrTUptVGWu28nEi2Ycxkh74xJoDVVRsLZeMmjmnNpGXp3JZxsmVkwIDQO2+9Sd5z2omSzebk65f9QN5y0uukJTeWz3vllVeaEjvcG7mwBx12hOlKe65BdplfzLlVcNvbP2QY28ESsFZwC0O7y85Ly5Lef9prL1m+rFKuDLA/4+TXys033VQBbgEs+s4lkSUzNsjYkRqfddZZxqhJn1sFRTwbmEkBJLUpKIaRx8AKebMCT+LNd4XvCBJ9Gs8tageUDCxMIZFlQUPBLc/Ahz/8YcMg8/6SU+uaz/H+/PKXvzTPP/nr3Dv9pv+ML9vohzZqAZ9//vnmv0nArR3buI97EmCXBEDqmOg7E9cvtrvH2M74fAtcAzHGT80F4xhi+/pJ8nSjXKZ5RlC68My4C2q+ew7gtpYnIewTIjAzIxDA7cwcl9CrEIFJicB0gFsmNgpuWRmHUYElQZLLZJMarjhUKtsYV/uVGwcUA6Ci5LLsQ14fEzKfZFYnv4A33Hzt2q8aWDV74v8qQ3YnPXHgL67ebpzsmIkY0l8m7eT9aWMSdv/995tJJA1m2Zc3GHf+OEMrLWUEG+Vjtm688UYzyYchI5+VRQeAJ8AS2TnxYSGDiauPuVUQ6j7M1ZjbWsEtE2ZAnta8BWwTDyalPBddfYOyemNexmCtSEtjykh129vG59wBPgHCdumeprTIgpa0ZDPFBRCdtIOVNw6kpLvfPrvI7IzIgllj4FDvGxC8cuNYnd/LL/2mfOMLnzasMSoH2CQa8WTxgHv64Cc+Le9473nm5wtnU0c3VeEi7Cs1dOxh+5paujCVjA/xyI80yv4v/OeyXHnHJUulPZeRxR1ZeeVRRxnW02ZuJwpu6S/vOMZSLA4BVnkHqRUNmES1waIToBTlg90++9nPymc+8xnzIxZrAKO8C6gw+EM/+SYoyw5o5VvBAgugBVDOAguOzTwDPAtIk6lXy/PB4hV5vcSXRTZdfCMNgj7q+/+lL31JPvWpT5n9ALqUFELlwNhQp/db3/rWjAa39QBI3mue7XrAbdwxtv+C5lnrOBNTW8Ls1te2n4ckMusoEzLeCb5dLHbWYoIVwO2kTEHCSUIEtkgEArjdImEPFw0RmJ4ITBe4BazQFOzxbyaaTDjd+q9xUlmd5FdjFNknrhZulGQYgMIEG2aXxoSWep8+U5S4OrawqkgUAfD8cVuc7NhloPm/LfllUQDGIQrcxp0/rn+aNxtVpxfZJfHCERkgwMQR0AQgU5Ye91GVBLvM7VSCW2LNJBXGXSfIgLn+/gHZPJIxrKrd5rU2yayGYlka11BmXU+/rOmGgR1rmEC1NQxKprGhLI/m2IGBQVm5qV96B6xcXRHpzKWktXHETNx59o0smndiU8EYWdkNufLaJ4o1XQFWuLjS5i9YJPseeLCcevq7ZZ/99jfs7+KOnLTnGivq3K7e0Duu1BAuy0e8eO+ycRTjtGpDnzHEUkYXo6l999rD5A7zy1/r3E42uOVeYBG///3vG2AJMIRRhcElv5zrnnjiid6FqVtuuUW+/e1vG1d1nl8WUlBFHHfccXLuuedWqBd4hz/+8Y8bgM7zCEiDUb3qqqtM/NWYCoUGtWvvvvtuc07Gn36ghnjNa15j+sPP7MUtmOQLL7zQPPeMKekNXItnDfOrepjbJPVak7CWSSTGcUDV95tKj6nFmInjeW/om8vosk3rICvgtb/DSZjoKIdlFlToN+NYiwFWALfTM0cJVwkRmIoIBHA7FVEN5wwRmCERmA5wy60Cspigw9SoxBdG1Sf/imM7OR8TESauUaCLfeJq4dIf2E9bMswEC6kvrDKgSCdblCHxtbg6tjDV1dyKNTeYvFQmVb6mDDQGQjBDgH/iBnMFu1XNsbiarJlr4awMkw5IhmF1W9z9AW4ZW+LEJFSNwjiPssIAWi31ZINbWDqeBZ/cmX4zFoBAckLtVo25JZ7qtu0znOrp7ZNVmwYkbzkWpyQlO7RnBfDnTsq51qruwjggTN1Y/gDIAEia+4tcedn6vOQHxy4AAF3QnJKmdGX5n3RDo6ztG5HN/VZnyJ2mZM/8VmmQ4oSf+081Zsp5sxoLcnFtR+RizPLSPdggG21LZpjdtqwA3rVxX8909Um3tR/X3aE9Z+Lga2rEU490FiaM58JnRlYNFNXKEtZrqqT34Lt2lOlREhBpS59r+dQnAbdJWMsk4Jb31LfgU+2+khxjg2jbnMqtsWvn6zL+/EliQoVM3f624BHAuWDvA7it5akN+4QIbL0RCOB26x270PMQgdgITAe4ZXICYIRxZALJxAWZL/IvX4srj8MxSMj4A7Myb94873niauG6klyfGzLAFHYAJsbXYE1hN6Pq2Ma5FatpFYwV4NXXYM0MwEmljGyTnF8mYOoYi2yZyR1MkduiZM26X5xbczXTLSb9gNuofGQdR4CzlnyaDHBL3zHiYpJrgyY7v5Z9XNCModI/1vbIgGXsBEDcaU5OWpuKpXhscOt1UIYpbc9KR6l2LOBNwW1ffzEfd3B4DMSSt4sZVLYxbeLE+YkFObDP9o5IfyXeNX2YN6vJyIyVYRpOZ2T15sFy3iz7cD7Oa+cFF/oH5JkN+Qrg7pYa4ljui5JE5ONqY78lc3IyK1uMg68lAWDTBW7rMVWy+6SmVPztA1GaCwroqaf+alJw6ytpFDUeEwG3tS4ecO0kQDXJMVFsr+br2saEbkyIm21OVe0XX1SuMguHXAv5eQC3sVOHsEOIwFYdgQBut+rhC50PEagegekAt0z0YFGZHJI7eMcddxgH3SimMg4Qcke1mEHF1cJV1pIcOz0nkxqYXMxj+DfnYDL86le/2hvIOPMrdStGAqp5k/aJVHZMPit5rb4GeNWJN/2if3Yemmvq5Dt/lGw5zq1Z4+yCd8aI/FqAPw3ZpsuwanyRjDLxdHNukzK3XM8Gt1rrVPNruY4rd8Y4CmMl17EYQJdpSJUnszrBbmpuNQCwf3AMfbpMKf1QcDuQbpKVGyrzcVubGgyz2pAu/hpVcDicbpQ1PcMVplQ6Zo0pkUUtYqTOjPHGvgFZV0iZSbe21myjLOnIlc/Lz2GMn15HDd3K/i6d0yzNVq1b7sfU2nXua+fOZslZJYm2F3Drvis22HUlsixiwFrzd7U8UM7JN4/nsFbGOioPtNrXO0npnCQS4yRAtV5wz33Weh07X5dFB7vZUvOocYpi4lEVcQzf6WkCt18YFTV9vNT/j4rI1yLG+80icraIvJBMCxF5RER+MCrIuARFd5Vn5JjRT+WHReQAsoBE5EkR+WnpOkWHx9BCBLbTCARwu50OfLjt7SMC0wFuiSSuvORfMSlERhsFtnRiSF5dFCBkn7j6sewTVwtXQTTyNK2pSg6w7YYcdw7YaFb8kQirS6v95DCZJN8PwyoYAV+LqhXL5BqpHNeg0TfyAN0WJ7+uJluOc2v2gXf6g7ERk0yN3THHMI+qbMoKY7YDKIgCtzwX7mSymiyZqyi4ZcGEGBMrZVB1Aq/M7fqe/nGOxbOyAM8WKWa9Fsso0Ti2pzAk6/qLtW+1+ZhStgFuNw2kpKtQaRwFswvDa98XwGldd68Bq7YplR21HWY1SjY9LENDw7JpQGRDZSquzGnOGAm1fd4+HJzXVzLGvv66zslcF0OsHduapKV5zI056suXlLm1ZdtxX9V6wVcSx2Cbba/WHy1hwzVcoFstD1Sfi3rk2EnAbZJ803pzYfV7zN+wvbW2pOBWy3TVeh29H75Dyr7bC0G+cfIx3hxD7jTnIbViGsAt7oC3k1JcykSIArcXj6blUwyaVcQbWMcSkaNEBMe7X4nIGyMA7gUi8mXW1MjQEZEuEXkZafsickfpHL21xjnsFyKwrUUggNttbUTD/YQIWBGYLnDLBFEnHXEuxnEOv3Q/rn4s+8TVwn366acNeKQtWrTImCK5OcBx59B+MCGCVXWb1qGtJsP2GV8xaSMfGBCn7qFHHcWcZnwDPDM5hj31tWqy5TjwbS8icA+AWu4ZJhawDrNLXjHMtjsh1MUDXHC1DIstS+ba9NsHbjV3luP44zbiohJ3A9KamsrlaZQRnjV7tqzuLgjg1m5tGZHFna3SkE6Xn0nt+5oNPbKub7jCOGp2tlF2dJhSzsfz/PTazdIzWNk7JMVIi922dnNB1mxy0Kq1EwZVML2cd+XGgmzoq2SlOpqKbssNDemyBLN3UGSFwxi3UGqos6WC2fU5J8Msz8kMSS7b5I2x2//tDdzq/SsYQvpss4Z2fNy6rfXKsaNMjqr9skoCbmtlR+3rJgGq9d4/10tyHR9YV5Crjtn2vSjjzmKFLTNnXPneAuDdclBRYzABQyk+aPdRvUtE7hKRE0eJax+4PUlE/ldEcJN7qYg8XurLwlGgeqOI7CUiHxw1y7/I6SNMLefFSp9fCneWtrM6cXXpXN8QkQ9Ve77CthCBbTkCAdxuy6Mb7m27j8B0gVsmAsp+VJPRMiAAYfapJl1WMyhKfKis2B1MrYWLGZQNkFw3ZJhaJMG+1fqoc+i1fKZUdj/iDJ3Y1y6nw/8x1EIix7EwvgA5AP/RRx/tfV5huavlBVdzjY5bSNCyTJhNca/0BTBKvjR5vphRIT9+1ateNU6qaUuy1R14MsGtBoNJqr0owYS30D8oG4YapacwhjwZ3/ktDZJLDRq5qE50i4suKeMujCuy3ea2FvNfS8RueRM5s8ic3bxVQDAg1W6cfnV3XtY77syNJve2qCok53WP+cXat8u78tLTX9nvxW1N0twwYrFTIpsHRLocrPz/s3cmYHIVVfs/Pd3T3bNvSchCFiAR9RNQlFUWPwRFEXfFFRABlVUEUUFBcUVEUVFwA1zYRXZE/cvnxgcKgvKhIsiWhCRkmSWzdc/6n191n+7qmnv79u2EmTBz63nyJJm7VZ2qe+e89Z7znoaEyIJmNgSK4HpjXunZ7lN7fa3MqU9IJpMTrPLaQHAX21SC20pVdsMyt8y1KwIW9EvAK/y3kjxQLUEVFMLM88MKY3HNVIlDVQNUp+qaILBeyTzRV9YbGg5Ee3gJ63mtkS0AtzCqMKtvFBEA7FE+4PZ+EUFlkOM/cfoACwsjC/ClsLMdngwg5r7nTnxaznOu2zEPkvnAAJK7g9Z/dDyywEy0QARuZ+KsRmOKLJC3wHSAWy0f46dAXInIkopB+ZXYYXhaC/eAAw4oqNm6asj8vxyrihAW6sT2PezFE1QnNkjQiXupPagVqyWIcIgpp0NoNjnKgEq/vN+g3GIXPNv9DyoVRC1h7AgzxVgA2zDcWgeyHLNthzxvLXBr59cyDkCqW5Oyu7df1vWPipVWKuTLwmbWjA2bzRMFt9yP6GOEmMjL1WYrKLsfC/JVV3YOypCV31pbUyOL29NS5+StEto8+d4iLXW1JcwsALq5LjFJETkeE1nYVCvNDaTM5RohzdTnpU6v3VqSIrDSMLsA1ng8YQC7C6pVOTlsKGxYcFsNkAwbNjsV4LYShrSSuq1epWx0/qYS3IYN/a0WqIYJR8cO1TwnCNy6765+P1jLbD7wXSVlhqYhzHzjALlBGz5VgluEFe6eYF2vnQCZ7xWRK3zA7fYiQj4K21eteRbWHc7qPLBFSfB/8wfZ1SIEuV5EqD33uIez8ycR4Rqef1XkDEUWmI0WiMDtbJz1aMyzxgLTAW6DmEaMXy5PlONBJXY4h1xY8kNREWZn3mZECUMm/Ix8VdSWUV32atTfhL3cb7/9PHPOgpSdKxGMUnvQR8YFE4kasub+BuX9An7Jb/UKDWZMjJF+eG0mlGOWuQZwD2OLIwjYJsTYZrj/+te/mpI/hEy7Id12yDMsr5tzq2HJhAK67JZXWDKbHppfq86omwcIQAV42jmt6URclnTklIUBKgAiLR3iJbCE/hPhwV7Kwdx/dVdGRi2Bp2Q8Jss66oXatHYD/NIXW7yJe8+rj8uGgbHCPciPpQQPpXlghLXx847kmNSni8zLlCwTAAAgAElEQVQq4+L5vQ4jvV1jQtKx0UJ0BLfZlBEZtKoMucrJYUNhpwLchgUrYcv0VAO4KwG39rzrM1jvrGtXhVlLDgF2VUVcwW0Y1WdlbsMoH1cT+ltpjrLaoBobK7gNC4irGY/NePMO8O0E5OraK7x/qZQBuWgpMFduCwtuWUd1dXX/puS1iLxYRDaWAbeHi8gt+fDl3X0cEnJuCWk+aSKXltxc2i7s61LlTUQ6fK77Rj6cGQErwqGjFllg1lkgArezbsqjAc8mC0wVuLXzn4LAGPan/A2OHqDSqwWp/HLNI488IggiUWIHYMu/cSYBtYA0WpC4FTm55Obus88+JUJT2qegUjqcF5RjTM6s1malbi3iVDZQvO+++wQQTViyy1Jy/3KhwRzn/jhiXjm7fswy58PYAlxp5BOTV+y2cmHbdsgzTKkLbjnOc8qBW82lVYEpns/PADXMpQ1uvYSjmshjba2TmrxisZYLAtxS4pXQYhtQ1tbEZE56XNqaGyeFqcOAwpja0lH1CZG5dfSjocQ0XuJNgNX25Jj0jtRIn1UDiHq5G/uHSxSRAdYLmmola4UNmxq6XRnJDBcRK0rMKCLXJ+OF0NZYPCHr+kYlO1rsqQHVaZH6VMKsIS1xwxy49T79vn/bIrgNWw5HgRfj11JaQd97Bbd2KHu5a1xwZ6IDxsZMfjl/XHEqBU4cCwNuw4pv0eewYLAaoFqNjat5jo4njCo113jZjZ9ROx2hQ74p/H4B1NPYaPQKLQ8Lbk8//XT5+te/zi3flWdu+bcfc3tKPpf2JhF5i896I9eW8y6cmNoz8ucQ6nzzBOj928Tf3rX2crm2dOSGvCBV0CsQHY8sMOMsEIHbGTel0YAiCxQtMB3gNgis0bsgBWB22aljy646YNCrEeJLnVacUs4H0OCo2PVPg4AnDg+iSQBkatG6TUE2YJlwXa/ml/OKQ8e9qZNLI9eL/GE397ccO8p1QaJXMMN+ObvKLNvq1YwJ0Mo1sMk4eStWrBDyZd2mYduvetWrCoJOeo4tpqWiUXbObTlwC5BizrS8EGCWpvm19Ak74YhCoq4lp9UjX3Z+S1rsX2IKbinds663FFBS63ZuncjYqJuTK575uIhG1UsOZNslXyjf80xPtrR8TzIhi1qS0t07IOtz1ZNMo/yODVb5Gfmw85vTMjo6YuYAG4zXJAywBeBqSyZqZGlbnfA3DWd7c39GNmZjJYAdxnp+Q43ExkdL+oT9mH/AlYaNl/s2RuC2mKddzk5B4K6SEGbdgCin2lsNuA0b+hs0Fi87AN55d8NsIFTzHJ4ddjxc4xX6Dujn9wUpKrrxyTj4XvhtgoQBt6SO7L///mxsuGDVD9yeJSJfFJErJ8q6v89nvXGc874vIh/Kn0PZIK4h9Nl7Z1jkuPw1v55QbPaucVdugUfHIgvMAAtE4HYGTGI0hMgCfhaYDnAbJNJEXwGuABo/hWAFToQXA1i9mubccozzqF/ohpcBPGGu/BhiREb4Q9gy4ctuqwRke+W8MjZEo2BGFWR4iTLxPFQ8CQ32ApAcf+CBBwwz7VVrluNBObmw1yqqhRIy4dw4djvuuKNhMgDXfrnNXnnNaiMVBoONZkMhDHOr4FZto+I8ylwrq1Lf0GjY19J8WZG2lMj8tsnhzjirz27OyuZSIeI8oEyZsGUYNGXpvHNmY6YcT1t97STnekPfkKzvLS0hyXmIPI2NjcvjG/tlOI9PdWz2mprfnBJErGgaNjwSyzGxdqg1TC2MrdbQ5fyegays2Txkcoi1uefZDKIbLquASpV/3bU+E8BtNcArrHBTWKCmIIr5dpuGMOuc2GA3bH5yNWCwGnvpNUSfsGlSSavmOTqesKHMXqHvKLs/8cQTptSaV0k3rzFUCm5ZP5Rx41vf3d29cAKIrrXuF4HbShZIdE5kga1sgQjcbmWDRreLLLAtWWA6wG05QKS2CQJk5XJFcZRgQwlDpiHKBKvqxYKUE1viWphV2FvUgdnVd1slINst1YMjBcDnWthg+kXYsVfeKs8LslcQ+A0KA4e9Bsy1traaHGU2AGDDGS9KyIQ9A3S9VETL5STjrBNezqYA93bBrea/eolC2WHI6rza8we4BSRSM9bOaQXsbdcQl8T4yKRwZ8Dhyk39JSHB/IJDYEkBZUk+3rhMFniqiZl8XMro0GB8FHh7le+xwSqgF/Dr1dx8WM7Bfus3D0p3VkpCoRGjWuTUuu0aGJa1Tsi013n2szXPE/tq6KweZ0wKdlkP/F/BbaXqytWEmobNuQ0bllwNiAoLbqt5hj0ObK1pHOU2IHh/eFalytLVgMFqxhJ2E4R+VQOIq1lf+s7yt53SgNYBvy/4XcFGaCWtUnB72mmnyUUXXSSXXXaZHHPMMa5PHYUlV2Ls6JzIAlvZAhG43coGjW4XWWBbssBUgVscHmUmqJVK/VQVevKyh4oo+bGZforKsBmEygIgNTcTxhanxasF1Yi167yiouk2m53cfXdv3Q8VjAK8Ah7J48UxI0QXRhRwimKnW7JInxUkahUEfoNycqmDq+AGhw8gr2G2QTnFrmiXbR87nxcGuFJwawNbN69W77+hu1c2DOaUjrWpcNToUHZSLq/JV+0clEErXxVAuX1bWhqT8cLGhwKZmmSdUTl2BZ5gSzUMWB1liNhN2ZqyZYEQl3p8w0AJ+6r9piTQEkdp2ZQP6hmUTkcRmfzceU3Fur8MH9C80QHN7nlea98VlOKd0veUv1kT2pgH/nBNpYxcWAaTZ1ULblUgLOjbWg1YCyvcVM0z/EA6NrTnxM3XZbywo2xEBJUcqgYMVgNUw26CMIZqnlPN+vIDt2wu8q1HW4BIk0papeB22bJl5rtPWPLvkcYvbS/Ml+R5Iq+O/B8ROTZfJojcWerh+glK/SKfj3uyiFycv+2uEz/7e4CgFPm25N3aubqVDDk6J7LAjLFABG5nzFRGA4ksMNkC0wFuNY91r732MmGvXi0oz5RrCKeFtdh3333NLQCIhPrigBNe1tHRIQBDVH6XLl3q+Zy7777b5GD51ZDVOq9+ALmSUj/33HOPAdv0ibJCgINdd93V1PGlBYFT3QxgnHa+sA4oCPyWy8nduHGjydml0T8Ybjt0m37Tf+yHHd1WTnBLNyCYY+aiEnCrbK4+B1u5OW854ahSYSdbOMrN5QXQPt05KCN26Z54TJa21wsiTzjJygpzbc/giHQO5fJRtZGPu7gtXRIGzLGuzX0GZGuoMT/zKgsEsLYVjvW+BpC3p0uUlmGYn+nOyOZMaWmiha0paa2rLfSJ89Z0Z6UnU4yx5hf2vMaEzGmqC/zcBakl26DKj0FUxV+vh1UDPgC3XOeqYPsNxqsGbbmBV8MQVgtuK90EoL+VjsPegHDDmLWUjV/JoakCt2FLTDH+agBxNZsIPMsrT5eQYb71AFGv9BOvNRUG3CJKWGEDmJJng+LhyoBSQJQKYteW3FpybGnkNFC7lg9AUCkgcnnJz41aZIFZZ4EI3M66KY8GPJssMB3gNiiPFfsHhdpyjgo1wQADmHEg7PqwOCzkoxJOS1itVwsK2QWMwgT7AWQVZCLsdu+9KWE4uRFijUgTjdxWcoRtwBYETlX12W8zIAj8euXk0m9yzBBRoeEQwyy7ods4gmwA+AlmlduosG2Dw+gHbpV10xxC5hA2iv/b4NZPOAphp+2ai8JRCm5hn1ElBija+aqpuMji1rSkkjmgaIPbNV390pUpijZxXHNmXdv0Z0dlZRdsbHHOEYha0lYKVgGp5AW7DUVk+qFKzhwfGR2XlV2TGeYl7cVQaHPe2Li5J6rM2mCi56TGpaUhVRDiKvctCwK39rXYiCgFFfayj2EXBVQawqx2JWw7jLBQWDXfsGV6qmEIwwo3VfOMsOPAvtiKeUEzwFaj17lxc6ir2WyoBnRWA26ruaYaO2MbL3DLxig1vYmm8dtwdd+lSsGt865UGpbMZX/Ns7ZHichPnOcfiO6iiKzL17q1P1qoIL914tN27kT53vOc6/hFyEefnTPybADCUYssMOssEIHbWTfl0YBnkwWmCtyyy44zQCO3CcAGyPPLb4KBRdyIUC5bidaeGxSVuS9AEYYRkERIreagBdWg5V5Bys0INQUB5HKKyzhMMLM0ACIg2Q0fDAKnqvq8xx57GAbUbUHg190oYB6wL2PDMdbmVQc3SDCL3GZAsp+atNYrhqV2wa0qFwNk+bcq9zKf6ogruEXYyUs4amFrnQGfdgMoZLNDkoklJ+W4Nqfi0pIYlfr6ugJDzbPAp+TMonRsNztn1v55Lsc1K7krc60plTBhzoBMbYhIPbq+v6QuLsfa65PCva1TTe7wiuXLZc3qlfLD626VPfbZTxIxkYXNtdJUXxTmoTYvTDShztqosbuouVbGhrMlpX0IhzzrrLOM+jjzDSA45ZRTTEkSzbmttBSQDUCYFwVULoOo4kf8zUbDdIBbvjGE/BNxgGK6tmoA0bYMbhmXstzlQpjtmrth5qMa0Bl2XTGGMBstWzKXfuw132kALqrwWl88yA+YAnD7dhG5Pg9g959QTSZkmUbc9P/ka+V+NF8yyO7uHiLyZxFhR+2/qRaXP9goIrdNXAswvigfmhw0zOh4ZIEZaYEI3M7IaY0GFVkgZ4HpALc43ORqIlrkp0wZBPjoO2JQgCKaV0htUL4o1wUpDVcCkL1K/eBEAzoZq6ri+qkZB4Vp45wDcF/+8pcXQpnt9RsEfu2wZ/qFmBUOOwwFGwzk5PopU3MeecnkGxNK7bYgFp58XjYnyGPzA7d6T0CWgm02LZT1iyfTsrJzoFQ4KiYyJy0yt615Up8GBzOytndIBhzxWdjdlqQYIS8AdKG+aL5+7KR83Na0EO5sN78cVwSptmsqBas40o9vLO039+qoq5H5raV1cVF7Xt2VkdfsvYusWb3KgNsDDjhA2mvHpC6dLNgFphZmF7CvDbZ4aVtaxsdGzdgUrPJ86jMTdk6NYhRbAaWE4L/73e/eInBrb4povrZXHVfyGHkuuYyslaC80K3F3D4X4LZS4aZq2M6wtXSZexUz89v8C8qhtpldv5JD1YDOasBtNddUA7z92GtCkon0oQZ6pSHxUwBumebvTmTcfEREKCD2/6j4NVFM4NUTdWr58FFWCABcDN8ofqzOnAhNPj9/7K48QwuoBRgDfA+iKlLkB0UWmK0WiMDtbJ35aNyzwgLTAW6VzcThxun1auUYQZw2DUPmWvJhAclhQ2q5Nij8GRVNxK2oP7vzzjt79tVVXAYQcl9CkXGUYCbJbT3wwAM9ayYGgdMgxeYg8Kthz4Rncy7ON7ll/B+wUS7vOEgNOujZqCUDJFFedsEtrLDmcmr9WjUwTqhRRJa4rB8YKwFzqURc5taNS8342KQcZMJ6n9rUL5mRIquZE46qk+Z0woB4BbcAvcGhkUn1Y+MxMaHF9alSRtg7F5ayQzFZ0A4pUmyAT9hVGzDzy7QjLaYfdli6zQK/bp9dDbi9+qY75M2HHiSZfJ1bwKRX/VybLXYBAusGJop3jPfJLYMVFlBUCiaYOwW6sPqAW6IW2GQJygudKnBbqeIzMxq25E414DasIjP9ClvjVefbqwSVsu2aQ63f0rBrhH7xjrHpyHePd6ySps8Jc001wNsvT5dNGDYy+Z1EBFAlbYrALV2hdu2JIkJBd2TaHxGRyybCii9BaLpMXw+dWCanT7C1r0B3TEQQrbpqguz/GmnelYwxOieywEy1QARuZ+rMRuOKLDCFzK3m7GH0SkJ9/UCTDRxxlHFWXvva13qW+QliHemLAj+/8GcAKjmzAAQcH69mKy4zNpx4HC/YTgSaYKHLhVgHAURyiRFuAiTAULstCPyqojHX4cTCmNvh4AhGMU7s6LYgNeigZ991113GwaXfCm5xoBUw8DwcWsCG3Vgvazp7J5XBAcxRimdwcMAAY1tgK5MXjkIZWRvhukvb6wR2Ux1vwC3PzIzGjCJyaT5uTDpS49LcWG9spQ0xqpVdmRKwGifHNS0CuVtge8bGZKh/QJ4eGJchx+3cnvzakUwhTNeLBVZwy6YAtZcBPdimdzgmzzr1c93QZheIsC6JFoABZh7cFha4VApu9Tm8m7pueX9414Jq61YLbrUusT47iLkNA27DKjiHtRN9ngpwa4dks1nC/1U0zFVh1hxq+gZQrTR0Xd+xsOB2SwBxmL75CYqxXtjIZKO00tq8WwncRn5IZIHIAtNggQjcToPRo0dGFpgqC0wVc2uD20pCfb3yctetW2ccZAWOOFDc6+CDD57ESqlTBqsKa0gurlcLCn8OyjnlnpT6AayR3wfYs0WtAHTlyuVwfVAOsoZx+yk2lwO/ADnAK7aCLSS02Q2707JLXpsEWquWnFmudVtQ37E/IBGgjy1gwHFkWQ+6OTGZtRWjhtw5UFoT1haOUtZXwW1vXrTJBqrpRI0s7WiQWqjYfOPZhC1nxhOywYlbbqiNydw6NkzIyS2CW0AzwNYGzck45XvqZDiTi+xrTKcltm6dDPQOyNPN82S0pgiMOZ4LW04WQq1T6bSn0vFhr9xNVq1caeoDs+HS3z8gx33kRLnh2qvkvAu/Iy/bY2/57oVfkvv+94+yuafb2POoo46SM844wwAV5pv3xEvZugDUR3Lx2jjnsH9XX321XHfddWadArJgWQ877DD55Cc/WRIGb4M2GNlvfvObJjWAjRsAAdfxLp500knmXfjABz4gP/3pTz3fO8Aued82qAKA/+AHPxCU0kkpIL+caAf6wYaMVyMl4Mtf/rK5hjXFeaeffroJt/fKua0GeE4luOXd9AsRdsfP3GkN6Ep+X5Qbu7LtCnZtpXDuzXPYpLIFw/yeGbb2sH6reTftdIGgMVXD9vrlXLPByAafhu4HPVvfH0Ltaay1SljqWKWTW0kHonMiC0QWqNoCEbit2nTRhZEFtn0LTAe4DSovg9XsEjwAI/JXCR0DEMGgEoYcVB9WgRlKva94BZFZk1tQvivOPqUJYTpxmL0aYb04mjRAEefZjKIKPqGmjKqy24Jq6QaFcfvlMAP8UXpWhVu/nF0V1fKqKRxU6iio7wgZ0bTOMHbEUYZtwc+zQ4Q5z1M4KhaThS3pEuEoBbfkQW7qH5Z1m0lJK7b6hMjitnqprS3NmcUWa3oy0leqGyUtyZg011ISKHcP+oazCru7ZvNQCbtbXxuXxe11kqiJ5fIeh4elac0a6a5JyeqWeTJuq0RRm2NkWFbEszK+YH7u/Jq4bBgUGbBq7sICI0a124t3NqrfgNt9X7mfEdH6+CknyC0/v1re+8EPy83XXSVz5nTInnvsYSIg2FhhnZ944onyta99zdiTtfjpT3/agFzEztjcsVn5yy4jolHMxtCb3vQmQTEcER3qNLM+yclm0wIACuAkhJ2m4Oj66683ABZbokLOdfwbgABA/tGPfmQA9w9/+EO544475JZbbjF5129729sKEwRwveCCCwy4ZY197GMfk0suucSAJzaieL8B0ERBAJwB369//etL5viaa66RI4880tyDd458SfrAej711FMN+HYFpaYS3IZhFMOKVlVT1ifM2LEp5wMgXVaXbzDz5IYw6+RMFbithu31swGpIbybrD07YqPcb/CIud32/Zuoh5EF/CwQgdtobUQWmMEWmCpwiwlV/AknAqccwAMb6dW0BA+lGRD6YFcdBxknVoVdVCjJL6RYS9EgnEQZHa8WJIgUFJYLQECwh2chmgRz5O7ga/6wn9pxUC1dQApAHuddgYY9FpgzWDBCoGHP6AvghOfSABLk/ALwvWo4ak1hLwY8yIZBfdeQbWyDs094MvOHY2znv9bERDauXWeAp60CHJeYLCD/NR9WrOPOhXGOysB4QnqserAcb03Fpa5mNM8CFRlUgPMzXQOSGS2KMcUkJvMak9Jcl5DR0THTJ5hbWv+wSI8DghuTcdmuOVVQRAaU1K1dK8Mdi2RjK1otk9sOnWukaWhARpculc54rWzMxGTYEoQidHpJG6HTNaYUCeD2V7/+jSzdZU8jovWZ03Lglvapsz4tn/vsOQVhJuzLvNHYRIFhV1DFxgLH/MKS3/Wud8nPf/5zectb3iLf//73CyVQAJtnn322Acv2tQADNnIAyqwLwCjsrE1GEYZMgzm2w5JdkGlb6Xvf+54B56xfgDe57QAo+nH77bfL0Ucfbd591jjrl7XDO8EmF9+SCy+8UE4++eSCTQDC73vf+8zztxa4ZbxhhIZsYa9Kfn1MJbgNA7oVQHKNsrsu2FVhKgW71ZQ1quYa7VsYttcP3LLJyTeFjZpKydUI3FaysqNzIgtsmxaIwO22OS9RryILbBULTAe4DRIpYmCal6uhq7C3OLO2KE5QSDH3KVemh+NBOaN+zKVbJ5Z7USfWKzQtKKc2qJZuUI6yfT2MFyCAshbkFbIZQIgnQBfHDZDptiDFaC3ng/Ku21xg7R4HfDHfgBJALeF7ml+r4BZmbv3adXL9J0/aKmt6Om6y7ycvkIa5k/OhWzJ9srSbUpQivU2t8nTjnJK6uHX5uriJeI05R8HtFdffJi/b+5XmZwpuX/6KV8i999wzyfl+wxveIHfeeadhSmFHKwG3vDuoX7MZwsaJW/4EAAPTz1qCyWXTBmDw1re+1bCxH//4x004cLlWCbhVcTPWMJtV9Id3HjCrpW0oXQT4Pv/88+X44483j4T1/dKXvmTykm+99VZzvq3E/I53vENuvPFGX3AbBuCFzQMOm8vMeMKKVlVTs7aafnmxsHbJIdaEHcIMMOSPlmhzRcz81ks14LYahtjPBmzKcIzvZQRup+MLGj0zssDUWiACt1Nr7+hpkQWm1AJTCW411xInglw5vzxOHCMcbkAdjgaMjoa12sYJCinmXK8yPfY9gsJqlbkkXJOwYhrjwOmHUcZJJhQZMRLqxNolUvQ5QQAaIAqAgLEih9JtsK6wwwBD/rhNr4fVpU+E7NJfHDWAoz7fr65wkGK0lvPZd999Jz27HDDHJpQZYg5hbLET4E03AFgHsCUZqZWnnlwld3/ljCld+1vzYQpu+YWpvDBqzjtvWCm1YyPSVdckq5tLQ5YpM2REpqww5h123NHk3GqdW/r42dNPlBuvu0o+85nPyLnnnjup2+SYEoJ73nnnGQazEnBLndszzzxTjj32WPnWt741SdCLh3Av2Fn+HHfccSbygncWIAZL7LUW7c5VAm6JGiCqgnecEHovBWDYZVjmI444Qi6//HLD6ALoSRdg3IQm26GyMIk333yzAfp+zO1UgNswyr9h83r9VH/LrektAbd2Drr7DA1h1nxd+7jOi6ox+wHHagS1qgHEfnm6hNPzrWfDJwK3W/PLGN0rssC2aYEI3G6b8xL1KrLAVrHAdIBbnCEY1fb2dtlzzz1LxmGrIXMAUITIh1cLCinmGs35fNWrXuV5j6CwWi6y2V/yhQGiOFaE++IM4egD8gjh9CojEQSgAaQ4+ZRtAfy5LagckV6vJT5w6DW0k3up4BR9hQF3m10H16v/5H/iqMOSuc0vZJoxw4aocBS5mW4poKHhYVnTPWjyX/s3rJX//crHt8qano6bAG6bO7aT0ZocA2vW7uaNMmegW55tbJf1je0l3fKqi9vZPywv/a8XFOrc7rHPftKQEDn3jJPkyiuvNGJLhAG77XOf+5x8/vOfN6HECEtVAm4VuFZiK0DzWWedZYSjWFuwcaz/oFYJuFXgGnQvjhMZQRQBDTDM5hYglvfObTDTr3zlKyeB22oAXrXM7bYKbsP0qxoAqSy0Rt3Yc2PX1rVzW6cK3Prl6bJZSX9Ik4nAbSVvY3ROZIHntwUicPv8nr+o95EFylpgOsAtHfIKF7bVkAmfhbktl5cbxIjynD/+8Y+GacUx9mpB+axcA/sL24hjD5AFsAFCYa5whLScEODPKy8vCEB3dnYahpN7AnDdVk6ACwAB4wV7S18AsG65oCC15aD+IyoEoPECEW7INP0BWDBmbEYIMo6rC25zdWAHZGAol986NjIima6NMq8pJS11OREoI74UI0Q1V3eye2BYNvQNyXiBGxVpqI3LAof9zAGYrAyM1kiPU4+nORWXhppRSaWSpm/MJX+yI+NGoXlkvJiPiyLywuaU1CaKgJV+DAyPybqejIxa57Y1tchIKi1jsdy56eGs7NS5Wp5pnifddU0lU9pRVyPzWxsKP+OJz27Oyqb+IdFSQDC3rzv4v6VOhuXkk3PgVoWa3PVRDbg94YQTTKgvbD4OvR3S694f0Sn+IGyGyFSl4BYmj/eFzSm/nNtrr71W3vve9xoBKd5R5o517BXOyobNJz7xCdM9BbeIVWnOvV3ahg0b1ithzqxvBVXMddh82Nw6jJnQ50paNUJHYZlbP9Xfcv2rpl/VgFsFqvotVEaXv+18XWyq88K8czyMWnQ1gNgvzJpvKLm75IpH4LaSVR6dE1ng+W2BCNw+v+cv6n1kgbIWmEpwaytv2uHCODWwMLB9ODvk1sLqEnZYjrkNYkQZODVqcU5RAvZqQfmsXEO5E+07gA0ASXimNs39JSfVzV3kHFU7xnHCyXcbObEo1hJWjGiU2wjVRMgHRx2nXhuOGiHFMLs0AIJXyRTNi8WugBO3af9hulSsyz4H9huHj7IsbrNZZ54Pqw0Y5z4oj8KI8H8b3I7F4rKyc8CIJWmL18RkSXu9NCSLAlCMOwcqGo0aMuDPbs21Itt3NE4CZplsVtb0ZMWu9MMvsvktaWlJ1ZiwWthNFcnpGRw259tlhBCwotQP/bJbN+d2Z0sAdnOmX2IyLj3pxsKpiEitb2yT/mRd4WeEKXekRRpSCcPwm9zE8XF5pjsjm/OiWApub7rjV/K6V7/K9BVl4q0NbslXPeecc8y9v/rVr3qGJbtzbYcl8756RRnY11QCblnXrCvEzngHvMKSvd7bQw45xLyXF198sR6xYw4AACAASURBVAHHLij6xS9+Ie985zvNege4uA3wzOZGJcq4lfZJn1ENiAzLDm8JuA0jwFQNgCwnjqXq2OTqMga35JCWG2JegkCmDaKDzrW/mW7JIfrAd5Q15PX99Vp//CwSlPKzTPTzyALbvgUicLvtz1HUw8gCVVtgusAtgAmngrBknE/UkHEuYJL4O0ilmAEHiRlxTrkarhwPqrmLYwtApq8AV/qHc2i3oNzfoJxaxs4zcMQBoG7zqrULoMUhA3CwEQD7C3D2qm+qebF+asuEDxO67AfO2WTAKSWn2G1qP8KdyQ1m3tiQgA3EQaUsC31VcLtg8TJZ0ztsSv5oS8ZjsqyjQZIOQ4rtxyUmnUM10pfN1Wal4cjOqasxisisFZt1HBoZlac39Us2RwibRk7r4rY6IccVp1rBLeAGJnh9b7ZkWIQCL2qtm1RGiPM4324ttSJt69fKU21FManWwT4ZrE1JNlFbOLV2dEQWjfTKWEdb4WfjsRpTEihjgXwFt1rn9rkCt4iI8e4xL6wjr3B0d66xHcrKv/zlL02+LgC5XAO8IKampbtYY24DIBCdwQYPeY+ULaqkdith2DDWsLOEJrvglvzcG264wbwTpC8oe+glgGSr/XqBpGrBbRgQWS24ZQ175fl7zUs1AkxbAm69Nsrcfinbrkr69nHN02UjwmsTIqzCNPf2YqJZE2zCUb7tBS94Qdk1bR+MwG3FpopOjCywzVkgArfb3JREHYossPUsMF3gllJAOCc4kzg4sH4AMw1HLJeXq6OvJKQYISZAl1eZG+5TjjUFPMNq0j/6CVvkFb5JjUSceL9SO8pu+glCBZVG0lq7gEZYY0ACgBrAjTOGEjHg2GV21U5B4DoInJcL7daQap6FjQgdBVAoSMD+nAOIAs+ONy8QsfJS03GRRc1JqatLT1rUXT29sn5wXIaLBK9hUmF4a0aHDHNig9v+zJCs6iK0uHgrQos5nzI7NAW3yWRKNg6OCUys3ebUJ6QuNiL19XXFtTg+btjankzxXGWCk+PUzR2R4Xw4cnws11k797ZuOCtL+zdKzfKdpC+TMbYZGY/Js/1jJX2lbi7gloiE5xrc0keAKkrDb3zjG42olCvaxqYENW2POeYYYwtsx3tLKSDGQAkf6tnajTBkGhspvDew9tyX95lNFspyuY1nU+eWqAQEogDdNthmw4RcW0L2lVnj3QQ0s/Fz0UUXmVJCuuYAte9+97s9SwEpqwpDqKq/NnvoJYAUFtxWAyLDgtswNWvV3tX0qxp2NGyINf3Ta9gQ0I0IvxBmgC7zFFZh2ga3tro2a4KNFUT4gkTSInC79XyP6E6RBabTAhG4nU7rR8+OLPAcW2Aqwa2GouG8wAbiVGgYMuDWbeVK0HBuEGjkHMJkAXd+SsZeIb/0DzaTvFH6BzOCI6VOvdvPJ554omypHQWAADwvZsAGr17iWcpiEwpNfwD1MDaci6iVMruwp4BftwUJVik496vDS+gofdR6qnp/7IR92TzA2aR0DP2xGwzhsxs2SsOchdLRkJJ42wKJ1eRCj9vra6UhNmzyXxG5sVv/UI6BtQheSSVqZGl7vWF46Y8Nbjv7BmXt5mErG1cknaiRZXMaBNCojTXY2zdg2OBBizGF3V3UmpZ0zZhhw5V1Gxkbl1Vdg4XcYO6TY4LT0phKyDOdfdKdtermAuCt35pN2QFZnO2R2A7LZLy21oTID4/XGNBus9epuMiclMjLXrqrkCN92223mXBd+vtchCUzDlh3Svswv9iftUNoPM8kn528VeaYPnNcAdU111xjlJT5P6HJhJ+zRtngASRobrCGzqJmDIhm0wPFbWzLOrFLCaniM/2C9deSUYBYmGXWODY59NBDC3NJqDYCW4AgylzxbvEukr9+6qmnGqDs5vp6hQzbOaH8224K6rU8USWf42pAZFgAvSXgtpzysTu+atjRasCtF7jXurpeIczMh+bLb2meLmwu33vWpJdavd+cR8xtJW9DdE5kgW3TAhG43TbnJepVZIGtYoGpBreE4OKs4szR/EJhOVZOpZfjQSrCnBOkBIzzRi1WBYa2WjNOE4477C1AAObWKzxO1YgBm66YE31QdtgvbBhnmPxBQjJ5nttw7rAFz8b5Jjya8xQQBtUNDgq9DqrD65W3DLgE2DKfND9g/cc//1W++5cuOWK3Dlkxr9GA25qahCxsTUtzqsaAFoC6DW67BsiBzZTk4wEkCS3WHFjGDFCBgVlPPu5gKSipN6HFaUklkyXmHMgOy8quQbFwrQG/5NdSc1bBj2GQpEZWdg7K0GiROq6FCW5LS5pzR8bkPxv6SwC1/bCO0YzJ85WmnKAUzvizXX3SmS2WC+LnzemE6ev42JhhJ2FuAYOqTo3409VXX22YUsCcGz1QjaAUz8U5x/433XSTIOzEfLJWYVeZT4Do4YcfXshXt5WGYfthTFm3bLYwD4TVswECi8q/FdyyRugjInKcy3r2EpjiPSSHFnBKLjxzoNEK9AOG2RV1YgOMnGHUxmmwv7DAbLQAkCsBt/acBdVwBexqmKxfnqeC2zAgslpwG6akUTXiUNWwo2FZaOxfyTW2YJi7CWGHMPN++M2NF1jnZ6xnNg+9NBG2FNx++9vfNsKGhD4/8sgjnbzy/FqYCJ4gGfwKEbnSqiBmP45wk49MCN4jkY4YAx+5h0TkuyJydYAD8J78tex2sptISMXlInIJ+n1bxXmIbhJZ4HlsgQjcPo8nL+p6ZIEgC0wluMVpVzYIMIOzddBBB/mK2eA446T4lfEJylVl7DBJMGF+YkkKLOfPn28cevqH8w2TTNgjThOOM+ynX1+D1Ij9BKF0bhS8+tX91ZxZzgc0EJpZkmc6NCQoGvuB46BNAFWdhv1CpdptCP0AepS5BiyzQQHYUVVrr5DopzYNyNGX/Vn6h8bk7P3bDbhNti+UpXObjHAUDqoNblU1eGNfaQ4sZXPmN6fFKgdr1k42OyTdQzHpHbbikEVkTn2t1MWGTagzwFlbf3bEgFVb5TidiBsWVvN9FdyOxZOy1skNBvwCbBPxXIjz052DJbnAtt3mN6eEftttQ19W1veW5ux6lQRSIIx9vXIRVU3YBVlhy9w81+cruK00LxRgCcipJOe2MKf9/Ya5rSS/k2vszQsvRWZ37esYtMyWfdwvJ3QqwG3YuaPfCm7tkNyg3w9bi4UNek5YcM9aoW9aaswOYeZZ+m7wt/2t9AK3PJu8bH4HeNVT31Jwyz3ZrCEi4cEHH7yNKOwJoImy4F5kc4jIzROg9a0O6ASQ/kJE3igi7CD+VkRSVMTK//2tif3dU3369h0ROYEpz19HPgXXsct2o4i8PQK4QSsyOj7TLRCB25k+w9H4ZrUFphLcEqKKcjDsCqGs/NuvNiyTElTGx0toyZ1MFUvae++9TU6V2xRYwhLBRuIIAWptJwcgB+MEyHbDZ7mfqiH7qREHhQ375Rfzc0KGAZ80mCCvcjw6BnJvyft1W7lSQpz71FNPmZItiGXh4LkNJo3QaphrNihgOXD2yZFGzIo8TFep+Z4nOuXU6x6SnsERaU7GDLh9wXaNsmL5cqlP50CfDW6TqZSs7hosqAZznF8+bSmRhR0QHaWtr39A1vWNSMYibOnT9q1pgbVlLpkrBbdebDACU5zPc5TpAfxs6stKlw+7SkgyDXVjwpXdxnHuyb214YCjxmzn95qc3ea0tDcURafce9mKuIyDedYQTftcFUTiZwCrStm8sAAp7PkzAdzagJtvBO+kzoNfTijjxlZhmdswoD7sXLA2qhGHqgbchgWq9K2aa+wSTRrCrCHmdh61bgZhX95vdzOE7yPh7GxuetUB93MQKg1L5vtIpA2bCrFSShnpe0DrdiJyTJ5Z1cedLiJfE5F/ishBVAvLH6BW3B/z17w5D4ztLr5tIrL/5yKyTkQoAP1Y/iDP+B8RedEEa/zRiU/rN/3GFf08ssBssEAEbmfDLEdjnLUWmEpwi2OBQ8Iv+SBGlQkJKuMTFI7LPYLySTUsmXNxRgF4qGbajXAycv+0nqa7WFTYCjElr5ytoH7iiBFeCfgGhCtIQUUaUIlTzT1gpwgVdVuQ+FYQcxxUUgnFY9hamGHylwFaOGuEr7ph3fTtqr+sli/88t+FnFLA7ZcPnis7zGkwOZqI+dAU3MbitfLswJhkhotIlfDjOemYpGrGJs1HfyYrq7uzJUJTiRqEo+qkPhk3wMIGt9SQhTW1W2s6LovacvVzsb9h5vAIuwelc7CozMzxOQ1JmdecMiCYNjY2Lo9t6Bfyce2W60PahDdrI68Wkav+IVvtWWRxa069uVzzK/eiobNewjvcjw0a5gjWqlyJlLAAKez52yK4DZsPq+AWW7oq6eVyQpkHrmGtB5W1qYax1rlgA0ffp6BfYtWA20rChd3nhgWq1YyfZ5Z7jm5C6Dvi9pH3Q0Ev4JYNPjY0vTb3/OxaKbi1r3fALYc+M/HKnpcPMyaUmMYHZM1E+DFhNNRf+4PTB1TcCGe+T0T2dI7dLyIvFxHO+YlzjHv9Lg98EbmIwpODXpro+Iy1QARuZ+zURgOLLGAc+1IP/Tk0iu1owBTiUPgxqnQjqIwPzgX1cv3CeblHObEnABsAEtCNI4qAj5ejqHVgAZYu8OUZQYJNlZQ1+s1vfmNAP88gBJj8R60ritAP+YgwcpqHaU+TFzi2jwcx3AhnPfzwwyZszissT5lb7lku3/clu+wqX7rzUbnyL6tLVtGhi0VO2H+JJBLxEnCLA7qpp082ZmIlocKECCMcNZwZMCyLbfOu3gFZ2zdSIjRFaPGSjjpBGZmm4BY2eEP/2CSV49aUmJBhgIGK0vAS2PVmuY8qIiN8ZbfVXZmSe3IsJ3ZVJ+TkahseHTOhyyX1fGMi2zXUSFtTQ+Cb5gdu3Qu1dqiyUvbxcuVUwoLVsOeHFT0qByT9jBWWWdya4Nbtk+aEMg/uZ1XZdZ0P9/0NG45dTS3dapSPw4LbaoBqNddgP8BtJWw391ewi9208f3nW8umBWuVyBdyvCutmbuVwO2nRISaWoBVcmtp++XZWT6kiz3WPrty5OzyYdqeT1f+HP69iuh7ESFMaXJoiQj3BNi+kv3jwI9QdEJkgRlqgQjcztCJjYYVWQALTBe4JceJP37lc+ib5rr6lfEJYiy5h4bc2mJPODuAXlhdHBn+4ODAzHq1ICAepIaM0wt4RY0TRWKvBkgHWKNWSyg1fURcSOvDkn8MIwcA92qI9SCA5cXsBqkxlwurBrgTTk5/CNkDAHvl+za0zZXL/x2Tux9HLyXXEGo6fvdmeVGqywi1sIFgM7ddA0OypjtTIsjUkEwYBhbmFuCC7QC3PH99d78p32PvxjQm47nSQB6KyJuGakpqyMaNInJKZDhTELEy7NvomKzsysigxRzbisi2vTf1D8m6zaUsMOWMls1pLIhdcT73WtmZkZF8aSB+BgDuSI5JqjZeUV3ZSsGt9k/BJ+vIlBsaGTFOvTZ+Ztd05TgRAZWyf7MR3GI/1qEXc+v3G0RBJHZVwFtuHrgPIDLMM6oBt9UoH08FC1vNpka1gFjBOnNDFAp6BKxrbbw7bOARJcN3pxwrvhXA7Q55JnVJPueWfFjayRNi8uTU8n9ycb3agyLyUhF5g4jcnj/hcBG5hSIBE3/v7nMd9ySc+SQRITc3apEFZqUFInA7K6c9GvRsscBUglscPHUkVMSI8FbCXb1aUK4r1wSVC3JZSZxCRKPI+YUJJQyZ55QDjkGhzUFqyMqsEsa7115oiExuCEKpI4xDBRiHSdBG6STsR0kjr1ZOWTpIjdmrXjB9Zo4effTRwuO8co6Zz6tv+61c9lhS1vYXgVRrXa1864hdpCW73uTpuuB2fS/iSqUgsa0+KQtbisJRCm5htNd0DUjPUGmQQVOtyMK2eqlNlIb3+tW7XdpRL4lYTogGG5tw7+FRw67CsmpLxEQWtSSlsQ79lmLb2Dckzzp9bqiNSXtyXJqaGguMT29mRFZ3Z2TMCopoQO25NS0D/ZULJlULbu2c23KhsyqSRIimhmmW++491+C2GiCpokJs7FTSwoo9VdMnr/BfZdc1X9fuK98ejrPxwJqshDkMy0DzvGqUj6sFt2GAejU2rgYQYwOv8bC5h+AT3xnmTpWYWVNaV9lrbYUFt5dffjk1o39sMa7kmBDq8ZWJgJOzrWd8XUROm2BfL8r/7fV4RKgQmwIIX5w/4ZR8Lu1NlLH2eR/IteW8Cyf2VM6o5J2JzoksMBMtEIHbmTir0ZgiC+QtMF3gVhWGd9llFyNG5NWCcl25BsYTx9yPdVWlYcSP2JEHyMJWwaICILmWkF8cGj/gGFTHNiinlX4Cwv1yZnE6Ec/CYYMtAPC7+X1B4lqAYxxKL8GpoPBtHDvYWc0ZxgHH9jAbACX6zWaAl/jX3f/ZKCdd9aAMjBZ/Vew0t0Eufc9uhlFFfIpSSQpud9xpJ3m2b0R6BotsCfZBXGlOY6m6MMBleGTUlM4ZsNJgYxKTuQ1xScdGDANqq972ZkdkVedgCbAkD5e+wCTjSMPeAG5Ha2rNuaXqyTl2taG+mMsIRl27OSOIUtmN8kRz0+Nm7WitTS9mt62uVha0pAxoCQMWtga4dd+roJquqjLrlhviPtsiuA0bNlstuGW9eInJeX23Kgn/DZoHZdi95oFnVgNuw4ZwKxisJPRX7VANUA27znlWNc/xGw/glm8ddZL51vE9Romf3w1u3W57vsOC22OPPdbUgLYaX7VzJ0oDAWZRNtb2/YlQ4+MmQPAXReTTPs4K5YPI0T1rIijky/lz+DfXcOx9PtdxnPN4xociRyiywGy1QARuZ+vMR+OeFRaYLnAbpDCM8YNyXTnnd79DH0N8ywUpcCMvF4AGgCQ0lhqYypDcfffdxqFBDdirBakJB6khc08/ZpX+afkh+kMItlct3aA+lrNDUFi0nTOMoAr5voAGmGaYbZhrGHDyfW2G7Or7Vsvnb/93CTg8YEWHfP3tuxTEklTtWcFtvHWBZMeKv1b417yGuMxtmZyD2r25V9YPjMuQJXtCaPFicltl1Dj4Nrg1wJL6uNYkttTVmhqyqnKs4HZwLC4bBwhxLp5NvVn6MmQpDiMIBQvbly0VmUI86gXz6gtMT0NjoynzQx/sNq8pJXMt0D7d4Nbum4a2st6wi50nCqhSoKuCSDMB3Iat9VoN8KoE3NrzoM/A5poDrsf9yj5NBbitJvRXQWeYzYBqbFzNNX7j4dvGNxCWttIIAOYnLLjlmrygVJ2IEJJMji3lfFBEfn1eRIrTInA7K7yvaJDTaYEI3E6n9aNnRxZ4ji0wleAW50IFPVy20GuYsH6Exu65556m5IxXC2I09Tlc6xXuy8/vueces1P/mte8xjMkMIhlDlJD5hluziy2IOf48ccfL6jbYhv64NW0j9Sa9WqwzzCu1OJ1W1BYNMIqKCIDbNkA4D52PV3dZNBaweSofvnOR+VnjnDU0fsskTNfs6Ik95QxwnzPW7i9JGtrpaZ1gcRqcmrCiC/BktanEiU5qPS3u49SP6MyaiFVBKMILSZ3FVthdxjuRKJW1m3OTAKW7XVxWdhWCppxvldv6pPNpSSsYY0BoiPDw+a+MNaxeMLkzWZGrHpDeeMua68TQo3ZFIFd7hlJCKyxDUoWtaQEcG23bQncuoq7GhbvVW5I2XGOVZqjG1ZQqho2LixzOxXgNmxuqwvUyin9qiCVnhOm3FDYEO5qwG01oDPsOuF9quY5fuuLyBJ0Eyjlhj0rbVsAbu1HaMkfO782CkuudBKi8yILVGmBCNxWabjossgCzwcLTBe4VUAFi4pwklcD+MH8vfzlLzeKyF6tXLkggASiVApWUGZ2w325p6oBAyy9wgCDWOagsF+eYefMAsxQacYG9Ad2FNEqxE0Ar145d0F9pJYi44T59WrlcpNVEIvrGD91iO1Qca0VvM8++0gsWS+nXf9/8idLOKomNi5Hvjgln3onZRVLG8D2lvselx0XzpGd5jZKvC0HbgkVXtxWJ4P5HFTy3Wg4oBt7+mXDoM2pijlfQ4s5T8FtKl0n63qHS4GlxKQ9NS5teUVk7RE5sJNr6cZkQUtSyPelKeCTeFLW9I6UCELpfQCs1LKl9Zp6u6Ol7HJNTJa05coSuW1bBrd2XwE2GjoL+LBZXT820R1rWNASgdvJoc86D35lnwC7Wm7IL4RZ5yXsRkA18xG2/BN9C7tOqr3GbzxsoKKbQIoMm1qVtq0EbjsmxJ02Ygaq0fEJyufEkhtbTlDqgYkaty+b0F1EROq2fJ/JwSUXt5yg1C/y+bh2rm6lQ47OiywwYywQgdsZM5XRQCILTLbAdIFbFWFCHdhPtCMoHJjR+JULoi4ttXRVpXTx4sUGtHk1VWV+9atf7amOGVTHNijsl2cqw4w6NGG/AFEEoyjzQ26X1pIlNNorLPn+++83rKqfcnRQTWDUmmElYF/thoNGvi3AmufCkpObbDdl0Be8YDf5xO1PypMbBwqHEY46cqcheenCyffGMf/qrQ/KDf/XJWft3y4r5uXAbVtD2oQKA5JgzHku4BYnd13PgHSX6kwJz1jUitBOsVemZvJARlBELim1UxOT7VtSMm4pIhtneHRcnu4cKFFEJsR5+7a0NCTjhQ0F7NHVl5FN2VhJ3q4+mWuWz22QRDxmnvvUpoGSerewy6g9wy57tecLuHX7zntEKCxz5DZbgdkGWApabIGrct/gakJaAWysI90cCfrGK3PL+UFgkHtVA9bCCjeFeYYKhDEXbrkhxmOXHHI3yaYC3FYDVMOGu9vgttK1Zc+lGzLNJirfITQYKq0ZzP22ErjlQ8EXD1W8+SLy7BaUAqJs0MqAUkCUCqJkEOWG7g56X6LjkQVmqgUicDtTZzYaV2SBKS4FhMFxymg4WrCN1FWlvIxX03Bgv/qrXOOCPhxFmEbyqHD0EAnh/5SxAUh6tSBV5qA6thr229raaur2ejXAJ8CG5pX3GwSwAaCEWBN2DBh227333mvYBz/m10t4izngvjjjND8bwZ7/8oEn5CePJ6U3WwzRVeGoxx68Z5Ko19DImJxz67/kxr+tleZkTM7Og9vtFi+VBa3FUGEFt/FEQtb2ZKXfwU4tSZFF7Y2TgMjmgYw80zNUEracqzVbL/G8IjJ2IoQ2M0y92YFSReSamCzLhzgzHwoENvRmZH2fE7NsGXtBc1raG2qlH+GqrkxJvnF9bdzkAyNc5deer+BWnXmNggBIebGJyurqBo2e77VmXRtVA27D2JPneSkZl/tFUA1YCyvcVM0zdBxEfthhzPZY3Nq6YW1VzXyE3dBw11Ul66Taa/w2Efi+8S3cfffdK9rwUBtvJXD7KrJW8nVrkcfnA0vIx9qJUj2EK1H77Q/OGj0qXxf3PhHZ0zn213wZIM75iXOMeyFSsS5f69ZSM4jcocgCs8sCEbidXfMdjXaWWWAqmVtMq+A2qPYq59pKxwgSeTVYUJQuUTrGeQGoAphQvSTcFwcPsSXKDaFC7NWCVJmD6thyT+rMwga5zCjH6BdhybCN5C7CELhh1gqwGYdXaFwQAFfm1y+02s35xWYIWdE3QC2h134bDd++40H57l82yth48dfB/ss75BvvyAlHuUrNnf1DctI1D8lfV3YbcwNuP3NAu7xwQZO8YPnyEnaEucLD2jAoYuFmIwA1t75GUrGcErHNsm0eHJZV1Md1Su0QCkx9XMYEwMBRHoklJikip2pE5jclpKmh3hLwiZn6tZ0DpYJQKDNrgHRdbVx26KiXnsywrOnOThKjsoWrng/gNmytVDdHV8dYrswN5/AOsqa9IhJsO1WTRxkWsM00cGsz0HYoObZ0a+vqJg7XVFJuqJr5qIaFDbsObXBbaf431/htIhCZwroA3FZilzDglg1cNh0PPfRQ8+3PC0rpLQijAYDu6FGahzI9F+TFpqj/tj5/ETk8gF1YXurVEoZst7eLyPV5AEvh9v/kD87Lg+gXTwDpj+ZLBs0ybycabmSBogUicButhsgCM9gCUw1ucWRUWApQBMgjp9arqRgU7OuOO/L7f3IDoAHMEAOhJisODPmi/B9nmv+jVFzuOa5gkvuUnp4eIzoFwKakkFfzK0kEK6qAm+tUlMm9h47Dq9wO5wYdV+bXL2wZgI/dqVULU0EuLIARVhzGGUEql7lFOOorv3pMfvpnItmK7ai9FxvhqEQ8F3prKzU/tr5PPnzV301uq7ZFDTG58ND50tyQNkrVGvqH8921uU82ZERGLA4BJeKl7XUio0Mm9M8Gtxv6svLs5vL1cRXceikit6RrpSk+LMnanIiVAQRj4/JMd8bJ2xVJ18ZLwph37Kg352zoKwXAzbWwy5WFuYYBY2HBRVhgERZUVHI+9lQmkf64ubp2CLMLJMKOl/UVxp6cvy2D2zAhtpUoMgfV1gVs8YfvgBeoCxMure+63wZIuV+hlawr9/pqrvF7P4js4RiboVsb3F5xxRXygQ98wHxjAc933XXXVRNAtklEdhIRgCbtdhF5B8vTGifsLTm35NRupupdvj4uogok/H87n5vrZdrvToQ3fyRfXuj/5fN4X80+o4hQAxcAPFklbwb7OdHQIgu4FojAbbQmIgvMYAtMF7jF8YLtRAWZPE+vVonoFHm1hC/TcNIAtTCQ2vQ5lLXZa6+9PJ+jOaUc5zy3aR3bciHUXqV4CGcGlOI44bjCWvvl9T788MOe5Xa0LzpOP3BsM9hezC/gFYcQJ4vcXcIZYbKpq+ul9gw76gpHgWU/e9iL5J2vKK1LrHWC49vvYq7psyjY5R0pOXqHQXnJ8sWGSVVwi+PcuXlANmTGZcxSRAZQAmxRUsaBV3Abi9XImp7BSbVm59QnZH5rqcIp917d2S+9TnTx3MaUzGtKGkCEU09/+gYGZf2gyJAly0xUMUrLGweK/l9bVzgLZwAAIABJREFUfa1AFHdb9Xn55dhRVyP18THD2leSwxkGjIUFe9sCuLXfHe2PKi0zHq9yQwqweFfZDApTRiaMPW1wq3WJgz7t1YTZhlUlDjtv9DmsIrMqHwPeNKTcHruWfdK54Fg14dLVgM5qyhrpc3Jq6aSrBjc/O/PtxS4ISm1tcItY1eWXX240F8jtXbVqFfVs+XQQGny/iPwsDzi9BsDu4Qn5kkEvzAPShyaqpwFeAcnlGjVwTxSRXfJhzo+IyGUicgm6fcHWis6ILDCzLRCB25k9v9HoZrkFpgvcYvZyCr4cD2JMAWUwqjhHADoYYMCa23gOYcr77ruv52zDZOJ47LHHHtLRgXhlacOR9GI27bPsUjw4ktyPMjg4S7C9AHVCgWFOCaVzW1BNX1ux2BV84l6oLxPGfeCBB3oqQhMWDVikMUZCozW/DUcRFn3evHmGXUAk6cNX/a1EOKo+MS5ffN0O8vpXLJ/Ud8b+66eG5IYnpASoHvKiuXLaPh3y+L//aTYcmCPALfbZ2JuRrqyU1KQlxBkFZa1Jq+A2Xd8gz3RnpX+omJDLOSgitzemS3KQUURe1Tk4ST15YWtacgB1vMD2kYsLa2yXG0IHak5KZGM2VhCKItSZfN6BoSLY5fmL29ISHxs2IGBrgVvsQ2kSu2E35obNl4985CNmjr1aWJAUFoiEPd+rP5qnq2WH7HHA6vLzbQncVmpTu1RSWOEmQldJR/jYxz4m559/fsEkP/7xj+WDH/ygHHnkkXLZZeCSYqsW3GLjQsTC6KhZu35q2Hy7mHO+E5WqCIddI4yoGnBbzTV+fUOU8E1vepMgbogqfaUAdyvl3M5yDyQafmSB6bFABG6nx+7RUyMLTIkFphrc4hBoLphfKK8OvJzoFGARQKd1cwkpo06rV+M5OGf77YdA5ORGiC4hzQA7QITbcKTIWS2Xt3v33XcbNgXwClsLawuIpV+wpUFhxUHscdDxcnnDmrvMuHbYYQcjsmU7cBq6jXrzcPuOcup1D0nPYBFILmlJypE7DMhBe+5SUiKI+w2PjslJl/1efre6NMrtQ/svk48etJOsX5/L7VVwS8h4Z2Z8EqtKndntmtOG0tDG5kV/Zkg2ZWtkaLRINhC2vKilVsaHs8bGCtI9FZHzZXmoSUtTcMvwNmVLwXg6HpM5deNC1LNdBxeBqBGLXq6tQRE5nQtbHhx8TsAtudOsN+aGvGRsqBEKX/va1+SjHyVtrrRVCsT0qrBAJOz5Qf1R5V8FvF6srtZ19QMcMLcK2Cr5YIYFhUFj0GdWC24ZMyJ0bISxwcWca6sE3LJpV0lT5pZ+epVDK1dbF9uz4aDsbrnnVQM6w9Ye5vnVXOPF9mIXfo/84he/kC996UtCGPFRR6HFFNwicBtso+iMyALbqgUicLutzkzUr8gCW8EC0wluvUJ57SF5iU7hjABGYVtxusilJTeXEFvbMbTvE/QcmDKYUdjMBQsWTLKqDf4o5ePVYJBhmnEc6bfLjmrYsV9YcRB7HHTcK2wZh5XrCI3T5qWmrKHbf+ttlJ/+M1sC5PZb3iFn7tchT/77n6aUEiWVtPUMDsup1/2f3PNEZ+FntfGYfOGNL5I3v3Sh+RlsNc4joBYQWtu6QLJGDDTX+AXTno7JgvbJTnpX74Cs7RvxDFuOjedCWNm04E9meFSe7hwsUUSuRRF5TkOhLA9rh2u6M6Om3JAVDW36kpJxaa2PyfqB4jH6Z5+XjMdkUXNS0slcruJzBW7JEyf/mhBXrWN62mmnyaWXXmrsyGaMHX5P/ysFYmr7sGA17Plh+6Pn8167ZW68wmYZx7YKbistT3T11VfL+9//fvn4xz8u5513XonYGt8TNqaI1HC/S2EVmcPUrFVhKuabjQe7MS5bhdkNxd+Wwa1X37AL3yfeKb6NjIfvZSWqzRG43QoOSHSLyALTZIEI3E6T4aPHRhaYCgtMJ7glHE/zUL3G6obL8n8YLHJGYewAozi3MB6U+UEQyavZIcNexykbBPj0KzlUSd4uOVU4nDTEr1asWFHCjgaFFRPGDBAltNpVUuaeQcfd+2MrnDYYbsIQAQcwgF5qysMjo3LCD34rf1hXWpv1yL0Xyydes0I2rM8BVPKZlyxZYsZI6PKHrvyb+VsbYb8Xv2s3ecXS1sLPYLDJB27rmCsNqB63LpBYTQ7cEu5LCHA6ISZs3G7dA8PyTPegb9gyGw4KboclLis7B0vq0qbiIgsaE9LYkMvHNc79wIB0Do5NYo1LnHcHzNrH6hIiHSkRrfSjjj333tphyS64Zb0DpFnjrPkf/OAHRqjGbmHBZFiwGvb8sP2xBYwAF8ro+oXNsqaxyVQwt0GqvDZzGyYPGNYWMThE54ioqLTOarXgNkzItz1/gFrmwS9vWhl2vudcxzcnSB1b127YDSKuq+YaL7aXMRH1wgbC97//fSEq4mc/+5m8973vDfz1G4HbQBNFJ0QW2GYtEIHbbXZqoo5FFthyC0w1uFUHiZ7DdgK42DH3agoqYUEBiziAOCg2K/rMM88Y58RlFe37UWMWZ/CQQw7xfE4lJYf88oPpI8BSQ0b9QLaGFSOehYiW25566il55JFHTBizV3h10HE7bBmnEkCJAwhQpk+AUzYFXDVlL+EownDPOWxnOeIVOWGudevWGdu/8IUvNHlp9z7ZKadcWxq6PL9uXH52/CtlcXupuBMM4x//8ZTMmzNHdpzbJPG2HLhN5mvSDmcGDEtng9tne7OyobdUEbmjISnzW4phywpuM+MJ2dA/UgKCW9IJaYqPFBSRORdguzEjYkVbC2V+WlPj0p8VKdU/nrxMAO4LmlMGJNt5o/aZqj6L/f3EpQi1L8fqac6tF7jlWeTdAoa+8IUvyCc/+cmSjgI+r7rqKoENZL4AWUQzsKHxqU99ysyd3RSssgHxne98xwi8EcVA/2HaCbH/8Ic/XKhDrecTOfGNb3zDqGQTNcHcka9+4oknyute97rCI3D+999/f1OLmrDPN77xjZ7vH6wl9yPU+txzzy3J8eS9u+SSS0wuZFdXl3l3iH4gP5V3XhvsPZtUAERUzXkfvvnNb8qVV15pQn4BdWz0aFgyG2IcJ52AMQBuAJpnnHFGSfqCDeh5Pz/72c+a/HtA3M4772zsQ15sNeCW8l377LOPYehvvvlms2Fng1u/sGTsznuMHbAP4bTXXnut8C2E4T366KPN2mAe+S7BCHMe42d9feITn/AEb7r2sBff1AsuuMD8TZ9YC+QDk9bAvH7rW98S+gfLyfwffvjhZu7QPOB9VqGnY445Rn7yk5/Ij370I89w38997nPy+c9/3vSJNa3h5/rzz3zmM8bG2P2OO+4w6R5s8LzlLW+RM888U0il8ApZJ4/WnV++vSeddJIR9VPgzfwS9YKQIN9LRKXQZmBdBLUI3AZZKDoeWWDbtUAEbrfduYl6Fllgiy0wneAWh5Uasn61WXGScMpw+nAm+f/y5cuNg6YOjQu8vAxy7733mlqDXiG5nF9JySHABv2w83ZxhgARhA/i3AKi/OrU4jDyh7BmHDK3rVy5siwDHXRcw5ZxPgEogDDshL2w1QMPPGDGedBBBxVC7p6GfXWEo1rrauWbR+wie+9QBOC2fe7vTMnnbn+kJHR5t7kJec+yjBz+ukMKTiNzBbC98f6n5OanE/KJ/dplxbxGA24b0ylZ0p6rSQvYU3CLGBQleQh3ttt2TUmZ21QqwoWtn+kamKyI3JSSuY1J6csrIjMv/QMZIxw1ZGmEwr4uba+X+mTc5G0/0zkgA+PFcOnS56eEnGC30W/WAGDXDaUF3NpgV6/dUnDLBgPryGVucbTf9a53GZAEsCACAGCL4w4ow3n/5S9/adafNsbNz2CA2WQCNAAANDSTDZGzzz7bgBYa5994440CYOF9BFwCBgCVbCCx5s466ywDpmj06bvf/a6cfvrpRrDnhhtumGRDbAcY5T0GtBP1oAJGhGF/+9vfNnak34RhE8HAxg3vIsCV9ayNd4RoDkLn+RuwDrjmfeMY0RWAW0DPOeecYy4jzx7QzxgAmzT6fOyxxxbGzFg5xhiYb0Atm1BsihF9cvLJJ5t70liXlTK3n/70p+UrX/mKsS/A3lX+DQK3zBXAE6COyBh90zF+6EMfMhsAWloM+wF0+RbSAJzveQ+CusWm4Jb5YrMBkIftsDffFDY8+I6ccMIJZt3wTOaGZ/J9ZS7sOeadYMODefrhD39oQLfbgsAta5N55F1jI4B1qvoG1I699dZbJ4Hbr3/96wYs+80vGznHHXecOc5mKZuTbJjy7WRjke8d6RReETR2/yNwO2k6ox9EFnjeWCACt8+bqYo6GlkgvAWmE9x6AS57BDiKiEHh2ODE4bC6wJCdfJximF2cM6+GYwprAXPrFSpXSckhBKVw+lWpFhYU5x8HB7aEPuKg+9WpDRKtCgqNDjqu4JnxM0bYWjsHGRBO/1St2ZN9rY/JT47dR5Z2lLKvjPUv990vv+9pl5v+RcnFYqPm7cFzeqVzU5EVxibY5qq/bZLbV8WlORmTs/fPgduOhYtl+/YmieV/swD2AEV16QZZ/XS3DFoIFEXi1uS4tDamS8p9AILXdA/KgHUujjQguLkup4gMUw8zS4kfVJlHrMTZREyko75GWhpzdW75Q+1aW0RLRwjcbU2NSnvLZBVuzgH4GLXk+S0SS9QEsro40/SVUjRerRxzC1AFjDG/bs4tzCxMG4AEURy7LjTO/KmnnmreD+6hLCNAEdADGANkAAjssioAQt4vrUOt4JHzeRbgUxtsIsws4PH22283G0msA0ACgBwQC7hy31/YOK7jGYAWABrgljEAjADQsJLcQxsA/ogjjjA2BHgBTPg+MB5SC2gAYc7ju2DniN50003y9re/3QD566+/vqQ8GM+HgaQPrF9YYAA9wA07UU/bZRhRIecaxk1TcFtJqDTAm+gV7MW8hQW3PA/29pZbbjHMM41+w0Bjb0A43zzmikYfKUsD6GUtwG7bTdce/QC8wsYzftYrcwRjjX2ZVwAnYJfGusA+bFTeeeedxqaqfA0QJpKANfi+972vsOGjtXWDwC33hxlnk0PzYAGjAF2+HdgfG2ij38yH1/yiCP+2t73NAFqdX74TvEsICZJyASPMGmHNvfOd7/R8R/WHEbgta57oYGSBbdoCEbjdpqcn6lxkgS2zwFSDWw3pVEfMr3wNDjSOKw4ZjhCg0auEDqGKhKCx644z59W0BqzNWtrnVXIPnChAGODQFrTC6cYpAjQAQP0Eo4JEq4JCo3GsyTe28151DAAsGBmccsIzcUpd8GSrNd/yj075/B3/LmFfX9wmcvwuCXndq181yYQr16yXU6/9m/yzu5iTS+jyZ16/s7xrj+1LWGGc4T/f/1e5/P+yct/G3PkKbl+0oEl2XrG8JPQSBzU7Miad64al4SeUYnx+tvZTdpXUdkXAWk4JmBHiqHupz3qBW2zE5gSMGgw9jj6hmtoAFbCfAAo2jAB2riAO4AQgCfOK808D8AI6AHvXXHNNoOEViAAsYOvcpgCbsE8iLjSk9/jjjzdAEjYQltNusM0///nPDfMJ26g5tLzLvBO65t1nnXLKKYZhJVQWAAUgI3SfSAUapXMAMqrMzs8AafSNzTAYPzuEWu9/4YUXGgALk0r+JWOAQaUEE3MDS+pukBHKfNFFF5lbAHiYr0rALSG8fN/YmAKghwW3fBcBaZQas9tb3/pWA3hhpOkva0Fr1nIN30rWDN8xzaHnel17jP+LX/xiSYkeADj2pLGOiLaxm7LsMP3YQ+sIw7z+9Kc/NaHlzLXdWP9f/vKXTVi1PlOP61qDhWcMrsIza4VQZ1hvQpe1sTbZzPSaX2zNPMHa6/zyewb7w9jy3tB/+kNYN30r1yJwG/jJiE6ILLDNWiACt9vs1EQdiyyw5RaYTnDrpfDLiMgd4xiOqTJJ5Jh5NcLUCInESQP4eTWtAevHqlZyD8IPVQWZsDVAJKGJhHvSggSjYK0Yk59oFQwXIBynHufTbX7h14REcx1sBM3v/ghmPb1qtfxlaHu55oF1JbdHOGqf9FojlAR4t9vqrkE5/qd/lcc35e5Pa04n5FtH7Cr77JgLXVZWmBDV+x76l3zvH+PyRG/xVwdqyN947VyZ29JgHGg7r3BDd59sGBwT6cxK65WPbvmCnqY7uODW7YbWdWUjwm0avszfgDO3zq2ez5ojd9XNUednsEyANXJuOc8FtwA1HHYbRPC+wFop0xpkOlhAIhgAxIALt3Ev7skmFOuSMTNegDDgGkVzDf3lWjaVABRsBLAxBNjjHeM9Ifwf1pZ316sBiAFLAC5YXhfcAlr4mW4yAO54b1l/5IiSK6rlbbC7MomaBwv7qYJ3bCQA0ADv5Ie6jfWv4d6VglsYQ2VbsQPNFWEKCktmQwO22m2aw0wYMOHANAW3rA0YYwA+42Oc2hTcwnDyrbQFmPi+8b3DZgre7edqdAAh62wQKLi1c26p16uaCyoSRlg2GxSsS0CqbvgQ2o6tvWr88lzdhGDjhE0OGhEmgFTWEREH7iYE4Jb5ZYND55d1CsiH6eUP9wWcA8rd2sKunSNwG/TFiI5HFth2LRCB2213bqKeRRbYYgtMJ7glFxC2BUeDWrA4wzhROLo4OQA1HA+cKZcp0IHjJOI8EyIHuPJqWoYHh9krHLSSe+AI0g8agBZHD0dRW5BgVDnmlXsEhVd7HcdOsBpsAhBWh/OODTRc0LbFfX97WL5w1xp5pKeUfVXhKC9F6QdWdsuJ1/xdOvuLObDLOurl0vfsJjvMaSjcXsHtugGRH/w7LhszxV8bcxtr5YPLs7LHioUGbNjgtrN/SNb05EBzTdfMBrdqLF1DrB2v+q6E3hPmCZDEUceBZu4JmQVsMM/MlTKU3FeBayUfA0I8v/e975lTeRe4J2yw14aKez/AJuvcDwzDcnJP1iPrnXcacAvQZtOG9cpGjL6n9IPQY5jG6667rgDAuD8hrJU0NmNg6Wxwi414vtsUuFZyX+zL94n+A8xJj0BNF7DmNsKWNdxawa1fPVm9lv6xIcc6IC3CS2E4CNwSysxacJuynrCQ/JtmKx+Tq8p16AjYm1kKbtmkIKzdBrdszmETmFS7tJg+W/tKHi9AVwXiyglKsU4QilLm1hZIA/ACfO0cbnucunZs8FvN/MJgs5nEJgvvG7nsAGbCk9k0KtcicFvJmxSdE1lg27RABG63zXmJehVZYKtYYKrBLQ4NTgHNrt2Kc4rjC+OCYwR4pLwKIccwG35iUDhg5PvhmHCNVwtiVYPuocCUe8OW4Ki7arhBglFBwlc4WQhs4VSS6+c2Oy8YJxTHGxCEEw0gAligbOoVtoxw1DFX/EVWbx4p3NYVjgK8YwdlyG/++1o5++Z/yvBoMVl1l3lJ+eEH9pHW+trCfWBgAF4Prs3IFY/GZdAqi/niBU3y9TevkMceut/kJcNM0fdEba2s68nIpn5Lo3h0TOaMxkqEm4aHhiU7lJWsJKTTUURuSsWlMT4qyWStAQiMP5Mdkp6hyYrIc5uTwni19ff1S/+ISI+pdVscX1MqIXMaE5LNZIxduW9nd4/0DCWkaDkRtgeaEiMyr72lJOc2kSo+w+/lVHBrb7LY6ssASIAEgE3Fy2CgAFCHHXaYmWPCzolWUFE1gABAhnVD7mo5tWbC5gG4NN4zmNKw4NYrLJX7+YFbmFxADP3UcFDOpy+83+Q4vuENbyiAW0JqjzrqKLNJA8vm12BlAeUwlTa49WM0Cd3HpjB7b37zmwv51tzHDl/meYQJ019+zrlbG9zCItIPGu8+cxmWuWUsWsPbtpGtNKxiYGHALd8yQprtcjt8awC3fratBtzSZ/pHCDTMLf3WdwHAq4wujLlbW9cL3Or8wogj/uU2/b0D+8z8kosM28v7xrgQkFLmFlBO2HO5FoHbreKCRDeJLDAtFojA7bSYPXpoZIGpscB0glsYAJggHFQcDIASO+jkkGlIGWVEvErYqHVwMHA8cUxU+Ma1HEwEDDCgAKfGy+nxugeOrYJIVcN1S+novXQshF7aQk56PIiZBbzgnOFU2uI5er3mBcOcsAHA+QAknscmgB94Rjjq1Gv/T7otBeId58C+vrREOAqwBPA6+OBD5Jt3PS6X/vGpEjPtO29MTt1/gbx01yI7joPOhsQvH+uTG56skTEp/ro4+IVz5YK3vURkJGvCHxXc7rjTTrK2d1h6M0W4yFULW9PSVl+qSJwdGjIguLdUPFnmNaWkoz5hRKM0xDmTHZaNWZGsBa4Js17SXi+NqUTJWFZt3GxAsN1QQ+a+49TDzd9Xc7z7Bwfl2Z5hGRwv/XXYEBuVuU1JGRsbrbiupxe4tfuh7BkAEmYO4KUN0MHPWPOACa3FSSgyDBZsE6GUXmHJXl8TDUv2A6vuNax9wFQlYcmsT94fmE/syPvB83g3YMoIpwXIsylF9AabCQrAyBsG1BLqq+q+Xv03tYv7+821lYBb0h0AMXwDSANwm4aO2+XKOIc8YWqfAsAIlXU3tuywZAC+3adyX3FAGOdqzq1bKzmIua0G3DIXbBSWY263JrglpJvQaHKqYendpjm5sLaUAtKmAB1gi93t9wD7Mx/c7/3vf78RyaLp/MKi8z10m9e7R7QL1/E7iHUBU0yubZRzOzX+R/SUyALTZYEI3E6X5aPnRhaYAgtMJ7hVkSWGicOC8wu4tZur8uuaRGvhUv+S0hheDUcadgrw61XewesesJg8GycdpxOnEPbUr9SPjsWvzm2QIjOAFQbUL3eY3DCUVVWFFFBA2LbmJGu5Hjtn99r7V8t5t5cKR+21pEkufs/uRlXYboCIZzd1y2/7Fsqv/rm+cAiA+LH/XibbD/xHFi1aaFSYaYzngQcflOsfG5PfryuGOnPs2FculdMPXi41NTHDBuNIA27r6usl3rpAhsaKv1bisZh0pMZlbhsKysWfo4gM49w/VESrHF/UmjYsLHOmZXVQRCYUenisCATjMZH5DTXS1lwq8rTaKTXEE+e3pKQ9D6wVMAGabQGzUUJtN/TI5rFSoExgenNyWDpaWzyVuCtxsO1zvASlNB8U8IWzf+mllxpnHBCo65L/s05Zs4Tlujm3Xu+FijK94x3vMIq2QU0Bh184LMDgq1/9qgGmtqCU1m9VdWCYWtYyzBxCRKrmq+CW8RLBwLtH/q0dgm330Z0rFZTyYxe5lvVLKL8bkuuOHTClOcNsHiAoRZ+IrrBzpHkfAV+Un6GFAbeEBLPxoyz9cwlu7Xq9YcEtm2h83yphbt/97ncb8SiNTCB3lj+IflEb124ww2xwwAr7gVvycGF33Y0H5gRwy/NgcXVO+MYT3eA1v14lmgDBCJcxNsLoYelR2SZMnveiXCvH3HKM7x4bR4gRssGaD/MmXv4eEblYRH5X5v7UafoISxYBfBFBbQ8Uf4mIWEXNJt3hUBH5mIhQ84v6aU+ICC/31xB3D3rHo+ORBWaLBSJwO1tmOhrnrLTAdIFbftHjKML+4YjDqmqelj0ROCrsrOMY4/x5NRxpQvxQyvRqOL0wsIQtAwq9HFlKW+g9AG4I2eAQKojEISY82U+UKqhUTxAzWy7vF0cbNkXFYwg/BczYYFCZYZy0ZTvsKF/51WPy0z+vKhnqAfPH5HNv2U0Wzt9ukg3u/MO9csG9vbK6v/jJb0jF5Rtv30X2WtJYCP3WnNAHH35Efvxojfyz2wKqNTE57/AXytt3z5UIocHc4dy1zd0ux262LpBYTa6ebCpRI/PqYxIbGzVzr+MZHh2TpzsHJTNcBLbUxNW6tFyL84hznBkVA2wBw9rqauPSXjsqydp4Yc2Mjo2bew4MFRljSg0tbktLQzJeeLYfuNV7r9vUKd1DtWIRxCZMuTUxLAvmFmsD+31MKmVucc5ZazYLyDrAEQcQ4KhffPHFBfaWsGSEdXgH+NvNP+c+hPuiGK6RBVp3mT7BmhHea4vwEE3BpolGRABweId4tqt8jCOPCjPPue2224S8TgVUqgIMgweTB4AgIoN3BjCu5Xvs0FkAPCVrGCt5kO7GldboZTOMcwDQlYBbSrzAeBPyzH3dXH5AFOuVtYoWAN8pNpawAUAIG7HBoGsVkA4IYty63vmmuZsjXuuBUG3sDoBjrJWCW0S9yMkOw9zac8GYK2FuGQf22BJwC3gHxPNtxVaqaM+7Czil3i4tCNza9uMdZe64XnN89ThgkvlFHIr1Zs8v65Z3iLWn88s3HRafbyp95N3gW7qldW55f5kjGr9DWD/M73XXXfcwun/5/qJOliu4XNq+M1F+/QTK8IrIb/nciQjx+U0icqOIvN0H4J4pIueLmM8TwBmlsgNFZK6IUOCYe+RqVkUtssAst0AEbmf5AoiGP7MtMNXgFudCc1hxuGgAMj92BlDJzj5skeaouTNCSDGhmJqj6B5XpWI/sSXO/81vfmNCG3F62WWn4YjBAuHIBolS6ZgIqeYatwUpMuPs4VTDcAIgteHIYQOAAM2Podac3XnbL5PvPDgof/rPpsI9KNvzkb06ZLms8wT4D6/ZLMdecZ90ZYsAEYaU0OUXbNdoACoOtTKCDz2+Wn7wSELWWG5SfWJcLnjTznLwrktKhg5gufiG38lOi+bITnMbJd6WA7cNyYQsaa+TbGbQhKMruB0cHpWVnYMCwNWWjMdkWUeDJBM5hliBLTpXnSZvttia07WyfVta+np7TTQAjvnQCGB5wJQc0kat22VzGgzAZk0qWHFDXb3e/s19fbK+d0yyVhg25zXVjMjCOc2SiOfAu1fbEnCr9yM0FhaVDQ7AIX0HhKFgTKkfrXPMcf4N6KOkDvPIOtawd94/gCj5hfSLtQ+I5H5cw70BzZq3yfWwrpzPv3mfAJasfUAMtrMFgFxwyzvAM1jrNBx+cm612eCWDS9KHxHOSoNxhTlWY48DAAAgAElEQVTl52x20TcAJSWGUImuFNwyTsKqKQcDcAPU8Id1oqH9bERp6LWKKtFPQDn/x370h/MZN4BdFXu5lvWE3fme2BtQ7nogpJ9NPb5bsLeqMKzn+YUlVwNumS/mgz6FBbe8m0EbB9pXmFQ2JuyNSPJfEQkDUDJWWFbUmnk/6QvXhgG32BdxL8At4fiAWFuFmblTtpffKzq/bAyxWWrPL78bSHvhu03qCvPK7xqiaIJaOeYWxWnWBOW22JjVFsstiCNE5Mo8I3vQBAD9H+tZ1Fv6uYgQV30A0hT5Y+xIch51nz46oWuYezGKDab2LyLCy8U99cUidOX2/L2oV1UsTh00wOh4ZIEZbIEI3M7gyY2GFllgqsEtDiGOIr/jYV1wLgjFXLFihedkqArxXnvtVSi7456ooipuGRs9L0ipmPMAyDjnOLwAZQAmQFJbkChVUCkfnGocYT9VZxxPHCKYA/JoaTjSOMAwRziLOPN+wlk4bLf+z71yxRPpEuGolrpc2Z4FNb1GidoNm77zH8/KJ278h2SGi8DvZYtb5Dvv2k06GnM5sJrXjFP6n64R+dGjCdls5awuakrI0Ttl5LADSnOacUK/94cn5Ud/elLO3r9dVszLgdv2xrQsbMHxF8Pc45ji2PcPjcmqrsESFjYVF9m+JSV16ZwyNTbJZodk87BMypvtaEjK/Ja0gZwAKZznmmSdrOwcKKnpm6wRwxi3NjcVRIXCgFv6QZ+f2dgrfeOTw5QRkubeXm1rgFvuwcYLa04VfLE1AAZ2lnxEQpaJQMCuyhyh+gu7qnnKCj55J6mdS/QC7yPrn3eT9wngpiW2FCABAgjDBWTBcgF+AGmAjde//vWFYbvglgOAEUJKaW4epgtuOQeGkbBTcsIZL+CMDSDWMQJbhEATTlopuNXQVFhrQBAbSoBl1jb3BbgibkX+Mu+/glveP4ARbCvq7NgC0ISy7nHHHVcIA9eyPmoEQK4thuSuCUS1iGABrGNnGwxPN7jle8M3cUvBLTYkNJlQX2xNTizMPps0AGHYa7fMkpcoltrOZm7dUkEqDsb6B1zyzQXUMr98W5kznV8264hGYGOQTRoYdASleH80n72ch7CFglLUaELZ7bL83/qo+9n3EZGjRCRHaxcbLCyMLMCX8Bg7PBlADDA+dyLL5zznuh3zIJmwFUByd7lxRcciC8wGC0TgdjbMcjTGWWuBqQa3gAJKNsDC0MqJKHE8KF+Wc3A2caT9lFUrAZ7s1OMYUeYHYGvnW/IMFaWC2bJBry4cOyzYi4X2Y2b1euxCKBuOH0I6OFw4vIwLpxunDEcch2z33XeftF7veni1nH7jv2RgpPjJ3iEvHEX5HrfOLmO99A9PyUV3ldbJfMNL5smX3vxfkqotso/KCj+wMSZXPR4XCwfLXju0yWl7NMqzq540/daSKLCln73tEbnhwTXSnIwVwO38xctkfmt9of/YZWhoWIbjKVm3uTQljHq6LfERqatLG0DGucPDI9I5FJP+4SJfm8ubTQvgVhvgdnA0JhszUiJG05ROSFvtqAHAOO3YISxzaxt/zYZN0jOSLPEy4Zeb48OycG7bJOYuCNza966ERbbPt8EhgErZLDZstAGeFGxxf2XzNHe73IfQZv+ei/O1/5qjG/RRZlyVhgDrvbzyLss9x1YMdoWkvK7TPum5tgqzbXvsx/81TJpwZxSCyzG9+rxqxq1z5yoylxu7DW6D5oLjvEdaA5fnVNLCrnHuGWb8dp1j3gdtRMLwbL4rgG9+H7GxwbwhflZJzvoWglvUtci7/fVEDu5r8/1CcIJcErYOW/MsrGtGQngAtq8Ukf/NH+TDRwgyRl/Or00P2/8pf817RSS3uxS1yAKz2AIRuJ3Fkx8NfeZbYKrBLRbF0aKpiBIKwOyce7WgfFmuUaVfv1q4hJ2RZ+UV/syuPqGaOEw4luRJeTmxWurHT5RKASChoJpXZo9HQ3ttZtY+rqJWgGuYNnKEaRoaTf9s8Gtfi3DU527/t5BXqm2/ndrlG+/YpSAcBWOipYK2W7BIzr7lX3LrQ6WKooctHpUvvGd/Ez6ojesefvgfcsfKcblzdWm47Tt2XyjnvuGFsurppwz4B3QDvnsGh+Xkax+SPz+Jv4XgUkw+fUC7UBpoxfLlBeaQYwODg7K+b1j6PBSR29I1BtDiaOKYDo+MyaahmGRGiuNE8GpxW70AWu22etNm6XbkU9obkrKgOS39/X3GEd8a4JZ57enrk56hpPFI7VYfG5PtWlJSX4euS65NFbi1nXPbwWcd2cqz9Amgxfl2vq3XuxiB21LhNC8bKfDCnjDg5WzPdwabH3jggSannj+8/0EtDLjTe9k1a4PmuZq1yjXVgNtqxrIl17DWsTupLoB3fRdglRE2u+iiiwwTHxRSzni3ENwSInyqiPxYRI7O2/xwEblFRB6c+HvyDmbuJHJu3ywiJ03k0pKbS0PC/iGqSlHFymf9fCMfzoyw1MeD1lh0PLLATLdABG5n+gxH45vVFpgOcAtbhFMRxGYyMZXkywbVwtUyOjbwBEwCyADPOHs4oziAKIl6taBSP6pmTL4t+Vtuc5lZ9zj2QBgLJgGnif7AIGvpIj9V6H+s2SwnXv13WWuxnu/fa7F88rUrJBEvOuOAeESytlu6XM6/u0seXNVT6EK6tkZOenmTLI5tKgh38TxCwv/z5NNyzRMJuX9DsceEE595yAr5wL5LzIaAbZtMokmOv/Jv8tSmYkLuwoaYnH9wh3S0NJkQdA2LHRsbl6c29cuARQWbcPXWtLTU1RpACzNnHMkxkY3ZWEndXaOI3BiXtqai0Bi6Umt7MtI5UAo15zenCzV0AZiMjxzuLWVuFfAxX892D0ivo6YM5G5JDsv8jlyIuzrUdp1bvw9QWFbLK6zX695aS5TzbaDrxSza1z/X4NZW9NU1Uu7j7ALJSj7kzzVzy5rVDRnArdvsmsbKqLPxxsYcNYBhb8vVKeZ+1YzbDq+uhIHmOWE2Yjhfwa2WZqpkPqoBqkE29lvzLsvP+0WIPVE3hKGjpE8ouKbMeIkP2vfeAnCLqiG7ly0i8saJMORb8/c9JZ9Le5OIvMXHfuTact6FE1N0Rv4c7nHzBOj928TfuZyWyY1cWyS9b8gLUlUyPdE5kQVmrAUicDtjpzYaWGQB45DYejxTYhIFt5pn6hdqS2eChJo4J6gWrivmhJNOyC+gF5aSHFfyUWFfcTK9nD92+hF28iv1oyw0uYqq/mob02ZmyR92mwJ9fg7ook+wB3ZzVaHJT339xffIi+c3yr/W9cnw6Kgcs1ujfPwtk1WjCc2+/U8PyuWPp2V9fzE8j9qul75nN5GuVWYjgRxAnHKA8JNrN8kV/6mVx3uKS6Q+GZevve0l8uoXIsCZa1oGKTZvuZzz62dKauoiSHXk0j55wfZzTf6nglsvRWSEr6hLyzNoOOQG8KCInI2VMNPpvCJyOpkoMM0oJiNG1ZctVUTevq1OCHHWVg7chnXQXcD37KYu6R5KSLEHuac2xkZlYUejDA1lDQiYTnCrdlAwCZDU0jf258DNF50p4JZxVRo2q2HJrtiT34cyDPBSVpd17ja+QYBEnQM7XDnMM/S+YcOruU5Lbfmp1Lt9DrsZw/XVjGVrXkOEDPYn6oT78ruCjUqAbdAaqRLcUoPtzrxyMUrIB1t2PEtEvpgXm3qfzxrjOOd9X0Q+lD+HskEIVKGCtZ/Pdcflr7HDoP2WcfTzyAIz3gIRuJ3xUxwNcDZbYDrBrQI+2EkEabya1m8l51TzdN3zEF0CvPnVoLXL7AA+AbY46oQIo/iq6p3s4B988MGF2rH2c7TUD+HThFG7DVYA8RtKUGgtWPccv5JFCP/QJ5wl+sI4vEIHUXTG4QKA0k6+5u/y63/lKFWA4ZHLR+SQF831zMm96S+Pyzm/fEKyVo3Z/1rYJJe8+6WyXXPKAHcAPGwxjPbjmwblR48mZeNgUbOkLRWTyz+wp7xoQalYEtf9+Pf/kmueiIslSCwHrOgwpYT+fPfvDQNNGDDgdkRqTFmekRJF5BohN1gVkRXYeikiN6USAmDt7+s1dsL59iwfhCJyR4PU5cGyzocXuOUYAGJLwS33Gchk5NnurAyMl4axkhjXnByShlRqmwK3WqqHviuziKPv5otiH35mn1/u2xkWDIdlbqsBOWxChQG3djmcSvJhtU9sEFWSt4n9NLeVd9tmdm3bKtDlb+agHDvsNSfVgNuwLHdQGS2vflUzh5VGKNjP85sXvnvYnO9eJfNr37NKcPujvIAUubUUZrdzQyJwO5udsWjsU2qBCNxOqbmjh0UWmFoLTAe4xSnAEQJI2PVlvUYO8EOAqpyiMmVOytWgBSihqAy4AtjwXHJZly1bVnBoggCyhvUiOsJ1btNn+OXUcr4LTukHYdGE/9ohoX6qzyg64zBTWuKeJzrl6B8/UOjG+/ZcJHvEny4IUukBnnHFPSvl/F89VlIy57X/n73zALOqur74msoMTKOD0qVIERALirGh2GLvvSXWaEw0MSbq355oEhO7JnajaDR2jS1qLKgoKiBWBBVRQToMw8C0P787s+edd+e+9+59okzgnu/jA9675Zx9zr1vr7PXXntIF12x39Bm4EcEg74QMZq2oEF3fZqvFU5ua68S6eebFmqvnalOkWhQiy97bLLufjdReohvXWo0KtCIcGH/rj366JtlNS0UkalhW1iQ30xXRzhqWW2OFjvlibiu5c1CjSbK4kW2Cos8sOyWDypAEbk4R+3LW6oW+8GtgTgDt4CNsAAoFYDD7t/MX6QltQVJYlOekFVujTbsXBHIEEi2bX1SndtMb4aoTn+QmrF7j3T5oplUgLlOawO32eSERgW3UecAOwXRfy2SDijjj58+zv+JuAOiw4CyqBFo+hUV3GZDMc7GXlGFxxhLqvugt4D92OQMY8fvAm4pC3TNNddwCX+ZH7tsTEvO9JKLv48tsIYsEIPbNWTI+DKxBVqjBdYmuMUeiCShjpqqRi0lblBUTpXLyjUs6khEEwDlby7l15/LasdmAsiZIshWLoe8LUSnghogj8jLdttt5zmsOFaUYaFP0JARfMJBJHIb1Ci9Avjc5kfbat+bJmr6t8u9wyraFujp07bSxFdeTKqDi2LxxU9+pAfe+Trpcqds11c/37GfclFjasqVI28ZW78yJ1cPfZ4rR5tKAOEfd5wvqMCI31irrqnTOQ9/oKfen9v8GZc8d/dBOnJ0IrrNxkJ5ebnalpSqoaybV+fWWlmbPJXn16ldu7be2BrBRL0W1+Rq2Sq30oXk5s1yPuB2ZX2u5q1oSALL1NDt0KZOxE2D1gPgFTuboJRrHIAufbA6pfZdKsc3E4BbvKxSCyrrVe2riVukBnUpy1dpu9SqslFpnlGBQiZwG/QcsW6ZJ39U140smq0y2cZ//e87cvu/BG79tsHeBnRd9WuOM/VrE0sKendEBenZ2CqbXOCoa5axRV0nnJMKEPPeZ5MARs73CW6p2Uz5LElQbXbgZytgnix3Np2g1ENN+binN6ktc5nhqz+bkkFQipuTd+vm6gb+zsQfxhZYHywQg9v1YZbjMa63Fljb4DZTjVqrD5sql5WJS1cLFyBDzUOLxhH19Jf54Rrvv/9+c85pECDKFEFOJfjkLiwbK+WEiBQTGQH0AWzpEzUZiQBDjQ5q0J5xIGcXb6RLn/qk+ZCL99pYh2zeQ08//bRX83OrrbbSoqpV+vk/39ObnzcqFtPycxp0+ugOOnn3BPjGYcbB+2but3r4s1y9MjeZSnvydn10xo4b6ZVXXvaiRxZVnl+5UqfeO0VTZi9tvn5xfo6uPmSEth/YKan7L7z4XzUUl6tbRWOdWwO30KFL8xs8Z5UIFGCorkFauCpXK3wiUz19ebPc4OsFS7VopZIi0hXFBdqwojhJEdlvSwO3bCoYKOMYbIH9GSffGa2U//sdX/t/GIDInH09f6knNuUmuAPxy/Nr1L1zop6y29fWBm7dcjIAXANbbokVA1sALuwGqAhbfiaMLV37RKW0ZgPYDBQGvROCntFsoopRhZvMTmbjMBsNPwS4jTof2C8boBp1naS6D+sBbQFo9ogAfl/g9uyzz/aUmEnNWLBgwYgmZeOg5cOO4KwMpYCgM1MyiNxacmxpZDxQuxaRhkylgMjlJT83brEF1msLxOB2vZ7+ePDrugXWNrjNVKM2jKKyldFw66wyb+ThAtws0oFQ05gxYwKn1Gi5AEMAor+Z4jKUZKjJ/mZqx4DVrbduKejE8YwV8AQwwAkGsA8ZMqSZnpqppBHgd0FltS59N19Lqxsliyiv868Tt1Rebo5H8Ub4puuAETpl/GSPqmutQ9t8Hd2vWtsNSZRdAuQBsuctrtRdMwr0wcIE9CrIy9Glew/WviM38C4BsMZ5HTt2rD6ZW6mTx0/WV4sTQjgVhQ36/W49tdNmybaprK7Vybe9rAOHtdeALo3gNjcvv1kRGcBkpaHI152/MlernFxcFJG7l+aroiQ5wklNXAC22xDH4g/NpR67xzBP5hzb5zi1zImtE8uXDKO1xrXC1oqdt2ixFlXnyVf1SO1y6tStQ7GKCpPVdVszuPXnhKfK1cXGHEt0zGq7pnqnRgUtUfNbo+ZT08+otV6zAbdR6b9+QMg6ce3v2tfo45ZDHRakZ2OrqPNBP6POOedEZQSkOge7AW6xSVD5tky//WFybs855xxdccUVXokn0kpGjRqVyad+u6kM0DGS7vL1AdrMf5tozdS6daktqCDvv5qIc4Gki33nUVR+Ovt3kro2AeFMw4u/jy2wTlsg04O4Tg8+HlxsgXXdAmsD3OIEGZAA0OHcpSrBE0ZR2V+mB6dl+vTpXokaQAuUM9SQ09GfOX7GjBmesJWV33Hn3q+4HLQu/Dm1flAFrZjxAKYAtX5hqkwljbDVrVOW69U5idfyPcdvps17N9bGxHmaUZmvv3/QoGVN4JfPUSz+y74DNWPqm9pwww29/DJq/yJiNaeyVnfMKNKXSxP6vtCcrz90ePN1uYZFldv02VRn3D9Vy5EwbmqDuxTr8J7LtNnQAV5utLWvFq/QyfdM1pzFVTp32w4euG3TYQP17lzarIhsUVQYyPOrc1Tr8KHb5OeqY2G9itsUNCtHo4gMqKaWbjM4VY42rCjy6NnWgsCtC1bdnEacVD8gAIi5NM9UQNfALWuL42npIkCLly7V4qp6LW9IrhlMz9sX1alz+8TGyvcNbqOCBDdym65WquXqYhs3qohtjEJroMu1e9T+RAVTUe1J36KC22wikd8V3PrfMy6F2W9/W9eZNhqysVU2FOOoc85Ys6nZG7R2WT+kgrAhOWDAgMg/9ZnA7XnnnafLLrvM2ywl/YZ0lZzM4eEDJT3QBGC3lfRpU8e6SHqR/cymerWUBHIbiowTJbGjSV7Lm01flkh6YvW5AGNq60JNjltsgfXeAjG4Xe+XQGyAddkCaxvcvvnmm2lL8IRRVHbL9ABM2Y2nrI+V+WFn3vJV3ZxRd16pd4hKMCUhKE3kb67iMuAwqAEuiVCRU+s2c6KIJNMoBcROvr8hnAX9edy4cYFqyf98doIumFClhqb8zT036aorD0z05cK7n9c/PyX/NHHlHQd20p8PHKa8+hq99NJLXokLnDmPyr0sR7d/Wqgl1Qmg2quiULces7lXksdtAOunP12uf32Wm1SSh3zcs7frpmlT3lH//v29P7Sps5folHunaH7lKpUV5njgFpA9oH9/tS0q9CirRpWsqpUWrsxJypstaZOvDcvbaEXVcs+mUAcBvrMWVqlqVaK/5PgiRtWuTaLUD/f3g9tU4NSEdvA5TYnWzWm0zw0UcG27FscZjZn+BQE+vy9rYKlyZY2W1BQoMRJ5s1qaW6sNOpV514oKMKKCi6jAIiqosOMB/ga40lFoo0TBmYeo441qT+7RmsFtGNXqMOWGbBPHXavZKB9nE7UOu2HivouirkPODTqHe6PXwLvY3ZQL+3ufDtw+9thj2meffbxLwShig5V2J4V0kxv1bi/3fXbDauLRKXQbWQqWelPpoDJJ1MAFALuvDjv97NXU5CuavnuhKUILqOUHDeA7FjH3sOOLj4stsC5bIAa36/LsxmNb7y2wtsHt22+/LUrw7LTTTh6I8bcwispfffWVtwPft29fTzUZpwVhJ0ry2DVdWm3QpKMUDDV55MiRHgD0N1ND5juOCWpB+cNG/QVs4UQCdFPV0k1nC+ywzzX/1ccLG32a4oJcPX36GHUrL/JK6lz+zHT9YyLpWIl2/Jhe+tW4AR5lGZsA8AEajOXdRQW6Z7pUQ5JrUxtUXq8/7buxBvXrlXSduvoGnXHHS3rui+TqrSdt20e/GLuRFi9eJDYpKNVEyaZnPpirsx96X9VNebOA20t2aK8B3co9J9KEo1BaXl6bo4U+ReT2bQu1QXmRGhrqPZDKHOYWtNEXC6uESJa1/BypS9scdQhQRHZFo4LmysA1TryJR5lz76oEB+WTWoTW6NRufm6mFwqAnnuy4bJseZXmLavViobkn1nIyR3aNqiitOR7VUv+ocCtm3ObzramVh22jE5rBrdhgKetlajliaLOG/exvF5vk6iJOeMXprINHMvlZa3y7AVpFASt82yi1tkA1WzKGtl9KBtmdcy5Du/8Tp06BSrgZ3qW04HbO+64Q8cdd1ymS/D9S00CU/5jqV37M0nsXkLzAATftppWfKOPjuw/b7fVQtdngalXg+YiSTNXk3fGry61/WcY3WE6FB8TW2B9sEAMbteHWY7HuN5aYG2AW8sPw+hEWSmzQ0QVxyuoZVJUtjI9di4UM4CWG4mYMGGCFykkKhrUvvzyS09Uiqgs1F1/M3p0OjVkf/4wCsvk/OJM9urVy7s/dOBUtXQ9mvCcOZ5ok9+h/Pe0OfrlA9Oau3XG2H46dft+Hv34Fw+8p1c/TZTioebthXturIM2S4wDBxobENV94dsiPT4zGajuNbhCO5bN1/BNkuv4Vq6s1a/+NU0vfjK/+d7k416812Dtv2ljPq6bj/zq/CL96Tlj0jWesmufAh0zolQV5eWe6jVOYUODtLQuLylqzLFdy4rUuQR9FHkgEKe8NidPc5fXJ0WMiwvy1LFNvVfflzxjf0sHbll/OLZWTiWT854unxRAALi1qG2mPF0Dt/TZ6sZ+PX+xltYVJIlNWRS3tChXbQoLUz4b7rijgr2oICkqEMl0PLZKRaF1I+bYNojNGXW82UZu6WfQGgt6j0S1aTYiV1HvQT9TlRsyoJuq3BDrm+cjM5s2u/zZINCZ6cc4G3AbdA7vCNg6MHV4P0dtmWjJQdcLQUuO2o34+NgCsQWysEAMbrMwWnxKbIH/FQusbXBLOZzZs2d7pYBSOZDpKMUADyKe0JDZkYdWzE68v1FOiFI35PYGOWpEfAGi5MIGOTrch5xaaM/k5QY1A9CAV/J3EbqynF8Ac6ZauqnKEUHD3f3a14SIEo380qdO21rfLlupk8ZP0Yx5jSWBaG3zG3TTkZtpdN+EAi/gk3tXrlil+z7L19sUo2hq0Hp/u9tA7dwr3xs/qqEAUNo3S6o94aiP5lQ2H19elK/rDhuhLfskaNVLlizRqxNe11PzyvTczGTW21k799fwgsZyRwh6EflGLXlRTZ6WO/Ri5qRHRZHKixPRe8DI3EWVWuhTRC4rKlCP9kVaXtnYr3Tlfvw5hpanyXlhI4TuXJuTHDT/QfmMLthlPAaq/Wt90dKlWlCVq1W+CxPFLSusUZeOwYrK7uFRwV5UkJQJrPptku3xgNlU5W7cXN2oNNhsqLZRlYyj2vS7gNuwKtTMS5i8XmxuGzlBUV3Ll7bIp3++o46d87MBqlGVn7lP0DnYhHc07yTE/aK2GNxGtVh8fGyB1mOBGNy2nrmIexJbYI1bYG2DW4SevvjiC09hmFzQoAalGEcC6rLbcFispA6fpysXlCmflXxYroVqJvRmfzM1ZCu1E9RPA9BEd6FaE/GgzI+Ny6LU5OTimPpbKqB/9QszdMNLnzUf/pf9NlbX9u30s/umanFVQgypW7scnTCwVkfuu2vzsUSkyStbsrJBt3ycpy8qE6/0toV5+utBm2iHgZ08ZWl3/NO+XuoB23nLEnCrc1GD7jh+tPp3JfUr0b76dqFOvnuSPlmSKCOEGNQf9x+q3YZ2FUJZ0BsBoV26baBFtfla6dCLAdg9ygtV1hYWXaIB3vnjto7tCj0qNqPAOaX5wa2VoMHZdsGl0V45JwptlOO5Do44Tj/OPfPH9dxyOO69OMaleVoNUK7lpzFznnetujrNWbCsRckgi+J271jaLFoVtP7+18GtC44s59jsG5Sriw0YM89ZUEqD30Y2B1GottmC27DAMxtV4qibBtghDLh17WVriXVMH/3Pkbu2s61rzP0M3BqTIWhd+z+LWp6J84PALZudiA6y8di9e/cwt046Jga3kU0WnxBboNVYIAa3rWYq4o7EFljzFlgb4BZH1RRqM6kUM+KgEjku5bdr164eOCPiSuQ1qFHrlnMoZWP1S93joAtPmjQpSRTJf510asgc+/rrr4soJq1Dhw5ebq57r0xR6iCg/+WiFdrjutebc00HltfrsDH99ftnP0vKlx3Tr4OO2miVVlU2RqdxRsknQ2xr7sp83fpJgeZWJoAwOa03HTFSg7o2UnqxDTYiZ3bGyhL96sFpzTmzfL9xx3wd3bdae+2abD/6d+I/3tHMBYmyQwDQGw8foRE9yr38XiLaiLaUlJYqt3wD1eUkQHBhXq5HLy5tW+TUlZW+XlLt1ep1W/fyInFtawAPxumCWz8t2Giv0MpTOeiWQ5vq6bKIK39zbCr6vEux9Ue+7NputDiIwowgF5s91gAOxW3bqbSsTH03GqAtRo3Uccce4+WT+1trArfksDMWFMGJjqVTV7ZxpBMXSm2i5UsAACAASURBVFfuBgBmpYZSRRW5R2sEt9lQpX8IcOtXok63ti2ia1HfsMCeOckmChtV5Iv7BJ0D24dnjTXKb0jUFoPbqBaLj48t0HosEIPb1jMXcU9iC6xxC6xtcJtJpZgBuyVy+D/OMrRfHFnALMCJfFcrcxNkpEy5vZY3StQ2Vc1D1JABq9tuS4WG5EauLPcAsACyqYXrd7SJoAI2qbULRdffPAXjzz5LUlM+/b4pevbDRh4xL+MtO9dr4rwEOOTzw7food/tPlCT33nbU1smfxmKMWOasaJYt3xQpypq7TS1ET3KdMNhI9SpJFFXFXD/1luTNHVVZ93+7iIvJ9bafiO768DeqzT/27lJ+cBTUEQeP0ULlidAaP/O7fS3I0aqR/tiD+gDmHEC21V0UkVZqVfnFloyrV1hvlfDdtXKai/6hm0RrwIwk+trjchuz/ZtVVrUUhHZwG2qXFd/xJV7WJ6he4456G75H+7v5udyLuA0bOM+ALZU5XCCSg0ZuCU3vKyig2oaclVdvUILF8zXx+9P1bKlS73b//jHP9bf/va3JPGz1gpu7VnNZLewoM1ydbGtfxMhXa5uNuA2asQz7BjMFt8F3LriSOlsmw31Od1a4nouhTnbckP0OZso7JoCt7zzYLaQhgHbJmqLwW1Ui8XHxxZoPRaIwW3rmYu4J7EF1rgF1ja4dcv4bLBBo0CRvxFRxRGBzovoEwCO6BmRUSi/YZSMM0VNw9SxDVJDxtEj+gxItxYkCMV3QeDVHas/iv36zIU69s53mg/p2g5hpeQyOOfuPkhHju7pHWNqywDFFSuq9XZlme55vyqpNNCWXXN18wnbq6gguc7qt/MW6Oz739br3yYD5zN32kgnbtvHU6MmL9mEv55+v1ER2aUXD+9SoNt+so0HQjkWm+P4vrukWEO6l6p/lwS4rSgu0IYVKLfWeNREQGNufoG+WLBC1bWJMeblSIy7Q1m7FuvCyv0E5dxyMPfGeWaOgiKuqYSijFLMNYj40sJSX91OGtABcLnlcNKVGkJNmmjSs88+qy233FLLV67UslWFnswp43npuaf154vP1exZn3vK07AarC7z+gJuzcamzsvacSni7hy4mxasA9ZDlE2KHwrcRqFKR81T/S7gNsy6t6i6Pw2AebAcaZ6/oOh9NkA1KlWcfgSdA1sFpX3EB2HaRG0xuI1qsfj42AKtxwIxuG09cxH3JLbAGrfA2gC3OFsGGqyMD3UAoYcFNVMRxonFgUIwClqmUX5xMoiqplMyzpTbi/Pz6quvps3b9ashc1+itQBvwDZ5Y+TapsqpzUTBdqPYHTp20r43TdT0bxvFooheuvVrS9rk6aqDh2vb/h2bTWa06Lp66bmFFXpqekIIioN+3DtHe/fL86Kvbluyokan3vOOJn3ZmMNKI2f2iv2HavehjXQ9wC1zhfDX+Hfn68r/JCsij+lSr1O36qTNR23aDPaJ0L6yrLOe+WiBV+d2QJcSL3LbtbytupQ2RkCJbgI4lFeor5fVqrY+EWFuk5+njoV1alOQJ6JU/pYO3LrCUWHADGvSzZ9174VTbrTXMKqxqfJz7ZruvQC6bgR5xIgRXnT/8ccf92zt3begQN/MX6Jl9Y2KyksXL9YRe+2kWZ/P1AEHHaJ/3Hm7dxz9B1CHFcqKKgAUJSrp0pLXdOTW7BhUeiZdVNFyrqMoAGcLbsNGVbOJJmcLbtNR6v3PVjZlfaxfvAtt48ifK+1uNjAf2YJbzg16J6T6gQyaR1T2YdzAlkBLIWqLwW1Ui8XHxxZoPRaIwW3rmYu4J7EF1rgF1ja4zSTkxIBNqIl/E63CGXFBBg4UkS5234l2BTVKPgAe+T5olx7H7KWXXvKERQAYQc0tJ4SzhAATwIzIGecAXqG5bbPNNoEKvpko2G6t3ec+X6VLn/oksB8blBXq5qNGqX+XxnxZHHrGB6W5qlZ64KsyvfN1QrW4MD9Xv99niEoXUipRSeB21sIqnXjPZH02P3F8p5JCj7ZMzqw1IuafffGlXlreXY9NS8gt5+RIZ47tq57Lp6tz504eFZuISG5hkR6YXaKXZywWdW4N3Pbs01cdSxMlnwBkC5ZWacHKHNU7XOh2bfLVq32xllcu8yI+6cCtn1Jsjjl9DxN58hvZVUR2Rag4zi8U5T83bH6ue54bQR42bJi3hgC30N9dBWZPUXk5xSpz9PLzz+j0Yw/1bPPCm+9rQM+Oal9a4oFbQP8NN9zgXYM1wfqAan/EEUfoZz/7WbP4koFbjn/ggQf09NNPe+sIpx+ADLX+yCOP1EknneTdJwjcsuFz6aWXenWOuQ+ltM466yyPVWE5t983uE0nDpYuVzcVFd2dm6jgNirwzAbcRs1TzYb6bM9QFOG1oH6l28jhWaJvBlTDbBwxN1HnJNU5bNbxruLZSMX+SPeDG4PbNe6OxBeMLfCDWSAGtz+YqeMbxRb44S2wtsFtOiEnHD/yVHFCaG6ZGr+lnnnmGS+PFdXloIaDDfjcbLPNAvOrrI4tNQ8pJxTUDGQDZKHc0j9ydBFhwjHLFB12wSvlJ/zNKNq9BwzR0ffP1NLq5Fq0HL9RaYOuOmioBvZupHC70eOFq/J00wfS3BWJ13aHdgW6/tARGtWrQqhOAyYR1aJN+mJRC8XlXmX5uuMnoz3KsNvemvK+LvrPV5q+NEFbLirI1Z/2H6axAzuIWsRWwiWnuFw3fpCjD5tKCAFuz9+uvQZ3L9OA/v2TlG3nLavWXEeRmXu2b1ugDcqLBXCGLh4EbnGaGTvz5s/5s35HEbbhHKOtcj3uiWNvtWgtqpuKUmzqvlbqJ0y02D//jAVHG3D7xBNPeJskbrMc3XlLlmtpbb62Hb6RlixepMuvvVm773ugSnJqNXvmhzr0kEM8gIp6OAwHxgP4RECHuefa9M/A7cMPP6zjjz/eOx5AirgOES3WO8fsvffeevDBB71/e/nT7dp5IP++++7T0Ucf7V0fVXD6znOGMvkZZ5yhq6++2mNjrE1w69rPovnMleXt2vepcnUBUhwfpG4e9I7IFtxGWS8/BLiNGtXHFmH65ZYaCio3ZPTldMJgUeckFS2b54zfH35XokSBbd5jcPvD+yvxHWMLrCkLxOB2TVkyvk5sgVZogbUNblMJOeEoQUcG3OD44fiPHj3aE48KaoAronRQOYNaJmAZpo6tAQSuj8NLlMoFqZmiwwZeOQ/xK38zivZzizrqiY8aVZfdNq5/qXbruEibjxrp3ZeIG4JN2GqeynX121VatiqhBDWgSzvddHijuBMN2jXRN+rwPjrlG5376AdJisuDK+r12+27avSo5Mj1lwurdOztb2r20gTY7kx09/ARGr5huecgkhdNqy/tpj++sUzfNNXk5bP+7fP1fz8qU6f25V7kHQotvZy7tFrzKxtzWuvr6rS8cqk6tStUB58ispXeMVv4xaMsOoSz6f/OonP8nS4yBEDDNpafm0o4yqW9upRiNlYspzAKULExWVQUMIrTzXqGPp4qL7i6pkYHHHCQXnvlJZ1w+lk67ezzVL1ihQ7YeWvNnvWFLrvsMp155ple5Jc+85wdfvjhHn3//PPP1wUXXNAMbsnxhR7K8+U2APJee+3lPYfjx4/3QK6BW8AvYm6sweuvv96L7lq7//77vYgvNs0G3Ial9EYFYAZubX5MAdhs7I7d1g33yAbchi1t4+9TmJ+IqCJM2USHo9qWfkelGBvo5NxUDAnL2bVnN5v84VTnsO7Z8CElJpUCerr5iMFtmNUaHxNboHVaIAa3rXNe4l7FFlgjFlgb4JaO4zzR2IWH7osTjJNBI28VtV+cB0SmcDyI/qSKunJOkNiTayAAA9TaVMASB4job6o6toBrKJj0if4Q3fVT2TJFhzPlFwMmHnl1iq6alqwKTATzVzv317iejdFhABCgBRvhHM+s76wb3lqsGicpl1zcqw7aRCWOwjDiQ8uWVeqjgo2S6uZip0NGddPowtnqsUEyLfudWYv1s/umaOHyRBmhgV1QRN5UG1QUeUCM6Dr2m1nVRrd8KC1flRCEGtWrXGeMKlJhQ40n/gW4zcvP1+xF1Vpanbhm5ZJFevaBO9fIml4bFznmmGOSNl7cSGCmUkMW7QPEM7c43QZu3bH4y7H85Cc/0UMPPaSDjzxO5/7hL7r/rlt12bm/0i577qcbb7pZXdu3VZvCguZLIPJFZJZ54N8W+U5HPaX81e67764DDjhAd955ZzO4/f3vf68LL7zQyy9/4YUXWpj8oIMOEhHh1ghug3KSMykAW851pk2SqHVbswG3UUHkdwG3UdgPUftl73/WPRsargJzUFTXgC7gPkr+cCpaNpR9at26+g1R3h0xuI1irfjY2AKtywIxuG1d8xH3JrbAGrXA2gK3VncURwW6LCAW4AlApNQP4AC6GM4xzj41W8njC6LzYhC/2JPfSDjzgEGiTZTqCWqp6tgSPSZCSnSNliqnFmcJRWQomkF1E4l2EQUjl7FPnz4tusD3R971nr5cnnjtQv298sBh2nnjLh49G2EnqNPkiiknVxOrOmv85AVJ1zpoZGdduPcmys9LVj5+ecLruvHtZXpnQeJzhKp+t9tAHbxpV7344otev+k/7cn35uicRz5orrHLZ6N7leqGIzZT28Jcb6zMDY7/S7Nr9cBneUmiVz8e1lV/2HeIZkz/2LMdoKpPv4301ZJVWlGTrPpcVLNUd99x2xpd2z/kxY499lhvDbsA1L2/mzvrRqFY/y4N2koBBYFb/3gOOeQQjy587HHH6bcXX6kTjjtML//nGf35pjs07sf7iC2S8oIadevUoTmiDaWezQg2engOAFcwHmjMP1Rk8uAtis3mEyAVAMDmiEVud9ttNw/UUo4IkO1vjz76qAeIo4DbqJTeqNHFKGrSNo+2CeeOL12ubhhqrnstfz3ZMGs2Kog0cBuFURBFPMz6TL/YJCBqHaali8LaZoOlA/gZGQBiNikybTbQDwO3fkVqfmdY3/yuZNqAChpPDG7DzHJ8TGyB1mmBGNy2znmJexVbYI1YYG2DW8t1RQEZp5+oLc42AAswRMsUdeUYHG8okrvsskugXcIIV+Gs4+QQjbLmlrQhUoszhNBPUI5WprJGAFJAMjm6lJ/wt/te+0QXPDOr+WMUke8+bnMN7l7qfTZ79mwv15eWk1+oh78p14ufLmo+HqC6f586/XLPzTxFabctqFylo2+eoE8XJ0Bl28I8/fWgTbTDwE4eaDHFaaLSN738ua56YUbSNbbpWq/LDhipTh3aeyDdK8nUtq0mLOukO9/8OunYk7frozN23Ei5uTnexgROfynU3fLuqlECXBfk5apTm3qtrKrULbfcskbW9Nq4yCmnnNLC5ulKDeGU47jjtLtOt5UCygRuOZe1zsbQOeeco4suukjDNhmu6Z98HGr4bORsvvnm3jPHuiLSCisgVWMzho0V7svaZyOKzQ3YDjvttFOL01gfXP9/FdwyIBd8eTWY6+q88fsVgG3jgjkFoHNcWFpyFMBtRo4KbrOJDhu4DUsRp29RS/SYfcNEYf2sBXfBZRIGSxW5Jo0EW/K+S5fjm+qZSAdueTYQaCP/nJQN7tUE0A+S9K8MD+nhq7M2TpE0nAwYSSgB3i7pRrB6mnN3Wy2mfqakzdHSk0R9unsl/RmyVKgXQ3xQbIH1xAIxuF1PJjoe5vppgbUNbi3X1ZQzTXnYyvwwK2GirhMnTvTyCnfdddfA3Mp0wlU28y61GWfKIpM4T0SuAHMA2DFjxnjiVf5m4BPFW8R5/M36AIAZMGBA0tdVq+q029Wvam5lI1W3Q9sCPXDiFurRvq33f8AhjhLOc3VOG905s1gfNAk28T1A+JxtO6t0+WzPWSO6a236t5U66Z7J+mpxY+SZ1r28jZePu3G3RuBs81DevoMe/bqdHp78TfOx0KJP2LyjhuTN1ZAhg71oLf0pa99R42cW6LmP5jcfm5+bo4v3HqwDNk3ULMaOC5YuV3lpos4tJwCue5S3UfWKKs+5DIqSWTTIVIqZC/7NpgjOJY3NkKAamqmeaJxMnHdTajXRKDue6xsFMui6nEdfLeLK/aGzp+tDOufcjeqGidwydvrPBgm0ynvvvdcDp9D6sfUOO+3izY2/FeTUq7AgT/yoI/iEABS0U9YLmybk16J0DGOCjSXsgAgb1+3du7d3TDbgFpXwMEq42UZuw1JnowLJVHTWdLm6ZvOwoDBqn7h+VBCZDbiNOhfWryglerJRcTagauJqqTYbDPDSn1SRazbdeI7ZSA2zPv3PUzpw+4tf/MITVAtomcDt9ZJOlcTL+nk0A1cTk9g94kX9sKQDUwDcsyVdwaucLJ3Vjzi7nttL6kzBgaZrJCTxU70c489jC6wnFojB7Xoy0fEw108LrC1wi2OAc+NGI3HWAX1+RyNTxJOZY3cc8IhYUhDFLJVwlTvrRm1GlIrIE+fgpOL8EInBGUKYKpWwFTmz1L1Npeqcrg9XvzAjKQ/2ukOHa9zgRoAKqKY/2Gz2cum2T9toQVUiArthRZH+dsRIFVTNb0HffvXTBTrj/qmqXJk4flj3Ut14xMjmWrPcA8D30BPP6K6ZbfTRwsSxxQW5+vOBwzSgeIUX2bNNiIpuPfWXN5dryldLm01YnC/deMQobd2vQ9LDdNt/JqtjYb36d0mA27KiAvVoX8SNPWed6KVf1CWTIjLrBGATJeqSShHZLVmCw+w2F3xaqR+Oj0LztOsZmOH/prDsUi6tzi2R1R133LHFS8kiakRMDz30UM9ubDawmcHGDtF3KMGbbrm1ltYWeJ6u26guXFKwSu3aFHrPmeWycz4MCb8tn3rqKU9IygW32BxaMjTmv//9757Ssr+5tOTvC9xGpc6a7cOWhwoDvlz6LCAqXVQ3CEBF7VM24DYbAB01d5h+RS3RE8a+/nUVBNQzlXvC7pznf16h5zNnPHNrGtzCQiFaC3sBrQio+5Sak5QO3B7QFNWdIwn60PSm8VNs/EUKBkj6xWpBeT9qJlL7pqQVkpDCn9h0HvzwJ5uudZWkX66fXk486tgCLS0Qg9t4VcQWWIctsLbALY4pzgUONQ2HE3XYoAa4I2oZFPG046k5C/UYQBCkdEveLNRl8gzJuw1qjYJLy7zz6R8Ov4k3cTxRLMDAFlts4dW29bdMIHzJkiV6/fXXW/Rh9qIV2uO617WytpFxNrxroe4/ZVvv30SKAdW0b3I768rXFmhVfeK1vGnPcq8mLQrDflr0vW/N1iX//lh1jtDUiA71+tvx26h9abuk7n+xoEpH/n2Cvq1OXLtzaaEX3R3avdQD19gXJ7Bkg/46/z/fJEWCOxZJp4/I12F7JOYQx//6lz7TnRM+a65zm9e+uzqXFatbWWOeJ46pH9z68+s4zoBuUHQ3KJ81aH5xZK1Ujz//LsiJTpXvx7HZAFvLEcWGAHmL9LpRXaKkQXVurc4sfWIdsYlDziDAEoBJ++tf/6pf//rXXnme2267TSuqV+rbxStU2QCzMdGY4XY5dWIK3p40yQOq0IxZ/2ZLc/ZRPabkD88NGzc0NnxQY4YKzTMLEKe5AMHygaElr8vg1r9ujDKMHf2bJEH0WasnGxZwcz+elygR0mzAbdTcYfoVFdxmI3SVKQrNe8J9nvxlwpgXj3VSVuaxHLAja39Ng1v/uuA5CQFukZzfTNIxku7yXYMoLBFZgC9S+y49GZozwPiC1aW4L/adR/4LIJkdO0Dy4qB3Y/xZbIH1zQIxuF3fZjwe73plgbUBbnFqiJLipBMRxenH6dh+e36/WzaolwjdkPeHGFNQQywK+jL5skE1KXE6uScleHBmghr5izg+NCLIRJJdpwcnnd14P+3XrpWJ+oxTSjkeKMtQl639/J9T9cwH33r/zVWDrhzXSbuNaRT+IbKNbT5s2FDXv/qVV0LH2t7Du+nSvQerTUEjeLEo+OAhQzX+gxW64/VE/i7f7zuorbZvv1Q7bJ9so0lfNCoiL65KqBcP6lriRYO7lhY294NrLGu7ga6YsFDLnBq8wzcs01F9lot6trZBsaq2Xv/3+IcevZnPz922gwZ0KdGGvfqoc3kj1Zpm4JYxMm9BwJbj/MDUwIPlrdr1jL4MeHWjkOYUc1yQWm7ggnD6yGaHX8E1G0XkTNFmy7n997//3aJmM7Z69tlndd5553mbLDwLrGkrj8X6Ym0Djin3A9DFpt8uXKQlK/NF0SXKBE2e9Ib23P8QT3CqZvE3GjVimGerRx55pLm2Lv+n/M+pp57qzQkglWcM22FbxM0A4jxXN954o3760582mxCRK8oOWSmgqOA2bL5q1MhtVCCZSogo3Vpx82HTRXWN+s61AJ9RwG1UEJlNdDgquM2mRE82QldRgTr9svrMZmuYDjQ2qPieZ44Nm6gAN4qgVAhwSx4LO708phVNUVj/UpvdBGwpgP1a05eFTRRkXqr9JSULJTQe9Co6iKtB7hGSxqdbv/F3sQXWFwvE4HZ9mel4nOulBdYGuMXQiNMQRcNBJpqJ4xkkTOMBqqZyQX5Q6E4Y6q849amUjHGEyalFbRl1TLfhxEK5tShyKlVmq5ULja179+4t1ksm6rOrDE1EmPb6zIU69s53mq+1Xbd6nTK6k2cPQH1xuxI99W2ZHp7aCH6tnTG2n07Zrm+SQwa4f+vdqXpoTrnemLW8+VjLgx1UsNADwNCuTdH08alz9NtH3k+qd7v9gI76y0GbCFKr0bNxvl+atVL/nJmnOgdh7zK4s/64/zC99cYEL1I1duxYLV1Ro9P+OVUTP2sUuwLcnr9de23crUwDB/T3wJE1F9ymqjWZCZimymc18GmUY+6ZruxNqheAUTQt4mpRZLfOLecGReY41kSG+J77p3OiDdwiFsVaNYAFe4HIKRtCtD333FPXXnutp9Ds5vryXO2zzz5eFL9Dhw4e2O3cubMX7fvoo4/1+eefaZNNN9fdjzVGW2l/Ov/XuvuOWzyAi1gax/M88Uz88pe/9CLCgFsYBAAC6//dd9/tRY7pI9R9cngBstSDJqeXnMNsIretBdxmE1lMpxicLu8a21u5oUw0+6jgNiqoZ01EFa3KBtxmisIGPY/ZAHV3/MwBm5DYkOfSGs8Q0VxyzdksCpPDv4bB7V6SHpP07uq/R6V4F5Fzu6+k01bn0pKbS2OndqqkhZJa0okaj/lrE50ZYalfp3rPxZ/HFlifLBCD2/VptuOxrncWWFvgFscA5xFHOZPSMU4IlC4AJcAyqEExoxRPqnxYVw2YHChrgF4AHEDSooGpqM2m2pxKMMpox+Qnknfrb0QQ3HI7tXX12u+mifrk20YgWlGcr98Mq1ZJYa4HGEo6dNHfptXrzS8STLKCnAadPrpCJ+2+RYvrT/30S/3iwY/0VVXitV1enK9rDhmurfp28CKwJoiF8jOU4WtfRFAz0Xbskavrjt9BK6qW6+23326mZz85K0d3v5tccuj4Mb3163H9PUVkItKMb9CoMTrxnsmaMS8BrnuV5+uS7crUqaLMq7PqglucYhzNVIqpRuWlh2GAqUXLmO9UtFDuHyZKEwaYhlVEDqMIyxgN3NqMGP0UpxvwyNo98MADPcVtt7nUbCj4RFPJezXRHAArm0Pbbre9thu3p3oPTrAXWGuP3PcP/esft+rzz2Z68wM74bTTTvP6wzNnkVvuadFx7knkmJq3AFoam1UAYs6nj6aW7No7le2j5nlGVfSNCvKyAbdhxZ5snZowmTuXFtXFvkGlbnhe+DyIoRL0bow6bq4RFdx+l/zZKEyKbMZi57jvD/rLZhGfEbXlmeE4Wti6t2sY3P68KZf2EUn7pXBEyLXluCtXs9N/1XTM3pIeXQ16J6/+u7GGW8tGru1fVgPhB5sEqVIcFn8cW2D9sUAMbtefuY5Huh5aYG2BW4CH0TxN6ZhoVVDUwsoFkQOL0xzUyD/kDwIe/jI4HG+UTqJZW265pXcJIq0AWxxMq59LrdlU1OZMqs2paMfWXz/Avnvil15OrLUztumifvWNJXXadu2jS19eoC8WJqILHdsV6Ji+K7T1oA08B8xt075eqpPufkfzlyfEkHp1KPaoxf06NebXmiDWqM231J9f/lqPTiF9q7GhiHxw/1yN7ZHrAXMoqMxPzz79dOt7K/XktLnNx+bl5uj8PQbpsC0SitATJkzQh3OrdPuMNppf2egk0gZ2LdGFO3RWTvUSLzKSCtxyLA67Ra8AQG7ENBvhKIuYci3+uPl3LkBLpYhMpB0QEhaYhhWlCgOsXeGpVJRVywkOomabSqy3ltq2TYpE0c85CxZpaU2Bl4jnNjiOFW3qVNq2yKPLGo2aY+x+Lj3bpWYbEPNvCtD/VGN2P49Khc0W3IbZJGG83ye4NZvb5g02svXjp78byOVv7MV7Jgq4jVoPmL5FrVmbDbiNSjGmX0FA1beEW/w3aPzcG/VvNo1IQTEFdcYd9PsRdI81DG5/J+my1Rkx90g6MsWY+J7jSLI/qekYygZxzgRJP0px3glN5zy7miy0ayZ7xd/HFlgfLBCD2/VhluMxrrcWaA3glggh9W2hJbtRPZsUK1ODiBNiTkGNqC3RW+iRXbuim9GyoTALwNpqq608CjK0S5waIkx9+/b1qJh+2q57lUy1co12nCrC7ALs/kNHardrX9OSFY3wom9FgX6+8QpRq3b2qmL9/YOG5u/4nhzYqw/YWB+/+0YLavV/PvxWv3pwmlbUJDRGNu9doWsPGe4JTVkjX/i9j2fq/q8rNPnryubPKclz5YHDlDfnA895xN6Av14DhujiF+bo7VmJyHFxQY6uOWSEthuQXEf3+kde0Y1TqlXjiF39aKMOuvrg4Vr47dceFdAPbi2/1sr6+MVf6CD9AJyFAYQ2IK4TBEwNPBhrwJ1bvyKy5V5nIxyVSRE5U11Oc+DpX9gyN5mo2TY+d8zVq1Zpuoco6AAAIABJREFU7sIqLW/IS8rl5hgEp8qLc1RRVtbC9m4uqR9YuwrQ3BPQlqpxHXdeo9aIjVquJiowyiYnNKrYkwEvd57T2dfUyqM8F9mA27ARaPcdzTOTSajNXQvZUIyzGUtQbjbXgcnCZmdQzfEwDkEMbsNYKT4mtkDrtEAMblvnvMS9ii2wRiywtsCt0TkZBNFTIqaIbgQ5wzh7COkAjrbeeuvAcfuVgoMO+s9//uMJ4pBTBYjFEYNyaTv1gF3ERrgHO/r+BgAHiBN95I+/+WnH/u8ZBwCbmqhPzSvXfZO+aj7k50NrNbx7O/1nZpUe+Cw5r3XHgZ28cjxtchu8Ui9QTKGncr3bX5ulPz43nYo6zW1s33a6+sjRKszPTerCS+98qHOfma15jiJyl9I2+tsRIzSoSzu98MILHrBlDjr2GayzHv00KXJcUdigS8ZtoF22HJp03Ttfn6U/PP1JEkA6aNQGumDPjVWQl+vZGiVpF9wGCUcB0HAYjR5oN4ki3GSAhHMzAdNUkU+7b6bzg9ZYKmAaBnwCDE38JpPwVKqH36KfnM/1wuQFz1+0WIur87TSd1Fkysrya9S9U/u0mwupqNmp5i2VaJiBWxP3ybShERXcRgVG2eSERs2HDSOKlS5X143qpsrVDQLQmX48fghwmw3FOJuxBNmYtQOThXc/QoXZtDUMbmNacjaTEJ8TWyBLC8TgNkvDxafFFvhfsEBrALfQw9JFTLEjwBTQhRhSUEO9FTEdcv7I8wtqgDccEpxrck6J8rp5a0Q2EcSBtsyOvr8tXLjQyy1kp9+f88ixOMP0E4cJenRQo2zK/LoiXfzGSlmFnlEd63XmmA56fn6Jbn8dQcxEO3brXjp7lwGCCuxGsEeO2kwXP/mx7n87AZA568c963TCNr1a5Py+9fkinTL+XS1bmYjuDu7WqIhcXii98847Xt4ZrWyjUfrlgx9q8YqEevLAzsU6stcybbpxYuyUGALU/mNiYzkna2ft3F8n/Kh3MyBiboh6G7gNqkNs9jORF4Al4CyoHE+qyGcYKm+qZxLb4jh/F0Vkc6IzAdN09GX6Z8JVYURtbDxcE2ALEPJTVsOAT64zZ8FSLasvSKoxwudFalCHkhy1Ly1N+UpzNxVsfsPkPBvQ5VjsR0ulXOsHu+sLuHWNbvRfs4W7UZAqVzcMgPZPbFSQnk2UO2oknT5mM5agdQL9mPc9qS6UucqmrWFwa7mz6QSlHmrKxz1d0nVNfSY/hRpd6QSlyLcl79bN1c1myPE5sQXWGQvE4Hadmcp4ILEFWlqgNYDbTBFTeo0QE85bqnJBRH6JAFMeJWgn3oAp14I2jCiUHzxQXoVatkRFiY76WybBqKC8Xv81AL9Xv5ejTxY3hloLcxt01R7d9eD0Wj3/8fzmwwGz/7fHIB3q5LVa5LewpEJ3zSj0lJatEaW9cLe+arfg4xZ1dB+Z8o3Oe/SDJEVkosFQkWtWVIoawQA7Itmvf12r+z7LTz52UCf93849NfWdt5rLMVWtqtNZ/3pPL7h9zmnQFfsN1V4jNkga9jfffCP+pAO3bsQzKCcynXATYMqiW9kAQzrrV0R2o2XuYIJq6ro5plHoonZdA3b+iGamvGA736VhZ6KFZgLWNXV1WlKdo6qG5Kg/jkBJbq26dShRoaN2TR9cNWt/fnCmecOetrHAtTg/1eaHOw9uTjZgOJPCMOf+r0Zu3XH7c1vDRHVtDsJS3LlfVHCbTZQ76ny4z2nYOXfPcVW42cjjfc9vAeXhsmlrGNyyI0vttnSlgNhFROiAHV5ybL2fkKbatcUhSgGRy0t+btxiC6z3FojB7Xq/BGIDrMsWWFvg1iio2BZAiaNBPi15tUGNGrRWaiboe6MMIw6Cwqs1nHkoy1DQLMcP4aogyqOV+klVCiiTYBT3tLzeVPTpP973vG79MMEhPmRER02du1IfzknkwBbnSzccvqnGbNTSFnc/+oxu+Thf3yxPXKNju0LdcNgI9W+fl1RHl/Gihowqstv2H9ZBlx6wqebO+cYTVWEuiETf/NpsPTQ9IQbFOUeN7qnf7jZQyyuXearWRDk699xIJ42frPe/XtZ82ZKCHB0/sEYn7tcybzoTuHUjngDbTBHLNSncFEUR2aL+NmiLlFneaVjhKT9YsfxggCkRaxcQuscGAesoNOyg58ZVo3a/X1a9SstqC1sITlEbt9ShKrvR8kxCTZmANWN3Sw2loi9bP10acxRwGxbkGWCLouYbVck4qihWutq76XJ1sZmJtQUpMPvXRtRxZGOrbCjGUaP1jCtIqAx1fHQaALZBZd3C/OavYXDLLd9uKgN0jKS7fH2gCPx/IVg01bpNUHAaVZD3l3TBapmCi33n9eMnlj0oSYhRJAQUwgwyPia2wDpqgRjcrqMTGw8rtgAWaA3gFiowFDGUkKGJBbVM5YIsMoswFCVTaDj+iEShcozTjHMHHW3XXXcNBLdW6ofaoEG7+UF1av19hXaMkx9En162YqXG/fVlLVrZ+Frt1A7101zNc9SFOxdLpw7L0eF77tTCDAg7nXjnW6qsTbyWB3Rpp5sOH6ke7Ys9J45NAGqfDho8VL979EM98V5CERmxqv161+mUnYd4x+Lc4egOGbaJrn1jgR6e/E3zPTkWUHv0Vo2UPQP2DWXd9Mc3KvX1kkYKKa13h2L9YlQb5S6fL38ZJRxuKMnMAVRwKOMWnfuuEU+XihtE08wk3JRKeCrdmyFdpMzAQ5jIo61PE65KBaBS5QUbQDHqbypF5XRj8QNTAKKriFxbV6dlKxtUWZ/fQnAKqnJZmzoVFTQq+IbZlPD3xUCH//OgiLUf6NraYT78NOZUubpRKa1R1XzpU1Ql46hgLYqCs61VWBF++6XL1c1mHFFtxZxHnQ/OiaqozTlBZY34vUBfgfdRKgHCTB7C9wBuD1xdTeuBJgC77WrV5E+b+sCP4ouShjTVq6UkkNtQWZwIAUXSjpIa63JJJZKeWH0uwPiqJmpypmHF38cWWC8sEIPb9WKa40GurxZoDeAWJwNqMuJOqXbRrVxQKmAKzcwii0OGDPFoptBt+Rw6LPm1RCkXLFigcePGBUYHM5X6ySQYxRoirxfHkXJCbsPBuuBfb+rxmXXNHxfk5STRf1E4PrLPChXUr9TOO++cdP5jU7/R7x5JphajRnzVwcNVWkQ8rdFZ/O9//6viis666f16vTNrSfM1UEQ+b+wGarfkM0HPwwkHkPQfMlznPDFTb36+qPnY4oJc/eWgTTR2UIKaTf9veeJV3fFJvqpqE1HjTXuWe1HjWdM/aCEKhpOMg81cAKQBYMyvPzIbpayJdTIVFdcYAYA0V30ZwONGrr5rxNOl4gLGGKsLIDIB62zyg8OIUoUF1hY1SwdMDeguXV6lylX5WqFkd4D/oarcubyN2hbDigzfDNQZjduN6n5fpYaigqmogC0bUPh9glubDbsHz5+xAvy5ugZ27dnk/RCFiZCN8nHUqDXjMXDLRlnYFgRuUW9nM5MUlrClf/z3Swdu0TA49dRTm09BmZloeFMUNZFPIm3lu+4Nkk7hdY7UhCSED9jpLJNEDVwAcOJHJHHy2atLgV/R9N0LTRFaQC3AGOA7FvOFtVl8XGyBdd0CMbhd12c4Ht96bYG1BW5xrkwVN4wY1KRJk7xyMoC+IAceB+aVV17xIq5ELsm/xfng/4BdnDYcDlR7x44d60Vy/S1T3m4YwSjAJWMjgmmNfj//xmRdMqlBNQ3Br9T9RnbXxXsN1ttvTfScIKjTNK513X9n6rr/JlOLD9+ih87dfaDy8xK5kYx3/BPP69ZPCjW3KsFa61aGIvJIFVUv8OjZNASzOvYepNPuf18z5yd8nrKCBt181CiN7J1Mib5v4ue66Knpqnf6v/vQrrpivyFqU5Dn1cVlc8BqBBuwNbDJHANkcCYNpLn2t2gdADQTxdQFlukoo5losNw/CuXU+psqPzhMfqkpItvaD0uRdW1loIDPTBHZ/d5fL9i/zsMKX7nn1dXWau6iJYFUZVSVS/NQVa7IOHdhaODp6LXuRkLUUkOmRB3W5tmC2yig0ICnmw+a7gcpm9zWoGhnOgaCrakom07ZKB9HBfbYJQioZvoBD1J+NjYJ4oBB4oGZrsn36cAtvwPub0Ca6wX9IFC79meSNuERp0S5pNtW04pvpGR7mmvttjpd+qzV0VrUDKnBNXN1qfHxqyO4fyblPMyY4mNiC6wvFojB7foy0/E410sLtAZwmwlUMjFEYXFIUpULsqglO/qAQyJSgwcP9mhnRlOcMmWKJ2yEKBVRS39Llbdrx5lgFKWERo8eHbheANg4etTsxUknj5f6u7d9nKcpC4Nfp666sBuhXlVbr989+oGeeG9u8724woEb5eiSo8a2oFa/PmO+Tr3nXVXVJe4ztHupbjx8pApql3tljABglCIq3GCQfnbfVC1cnlBE7lWWp+P7r9R+uyZKMjGGq1+YqRtfTgbXqCGfuVN/5cJfljylagAsdGzAA7ayyCl/o4bNPJCza1RagCWN/6eK1vk3MjIJT2UCBgAcN6JrANHyWTMB67D5wZmAdbZUXn/E09Z2GGDN2CxPNRvhK8a0rLJSS6pqPFVlp/qUZ3Zms7SwRu1LS7wouZ8e7NLIowDAMGrP7jpJlavL3LHWWJ+MP1OpoajRSIvcRhlbVJrtmgK37nOSaTPBjeqmslk2ysdRgf2aBLf8DvC7Q0k33ofZtCi0ZLt+TqZFl01H4nNiC8QWiGyBGNxGNll8QmyB/x0LtAZwmwlUuuBp22239XLs/M3ALZ8TlYWGDAh1W6aSQ5lK/XCtTIJRlhsMuLV838+WF+iqqX4oIBUV5OpP+w/TLkMSecZvvfWWR53ebMz2Ov3+aXr3y2Rq8U+H5GpQaU0L2vLDk7/W+Y9+qBqrLwQPbRCKyJtowdyvBS3OnP45BRvoL6/N18raRBBg2/4d9dMhOVo8b05z9NXA9eNTk/N2L9pzsA7ePFlhlLFC80NIC/Bg9wJEAE74jtatW7dmuqNLTzYHG4fRX0LGgKfRZL8rMOR8KJoWvQoLrFMByzBPeypF5Ez0Zbt2mIineyz3w5b+0kYcky2wtVJDzMequjotrKxroarM9aEqlxQ2qLhNoTfX/MHmrnBWUD3rdHb050dzbKpSQ9zPNilsHWIHKzPF+qQ/fpzh/3/UaKRfyTjMusgW3EZhHESNdhqAxh5BuboGdt2NoGyUj6OOHXtGrb/LOUHKz2zEweJBnyEKxdmd0xjchlnh8TGxBVqnBWJw2zrnJe5VbIE1YoG1BW7pPA4RbdGiRSJi6YpB+QcHOEP1eMyYMV4OrdtwkqAcm5gLADjIec5UcihTqR/umane7htvvCGUOOkj+b4lpWW66K16zVqUEGDiOp1LCnXTESM1bIPksRBdfe+LefrHFyWavThxjlGLF858zxun0Zbr6xt09YszdNPLnyfZ5Lite+msnTfS9E8+9uxGJA373vDidD0+C6Zboh2y+YZe2aGPPvygud5wbW4bnXbfFL31RUJcs01eg36xeYmO32PrFmvP5ocawVAsDUThILPxgBo20XIo4ziTmSKkqaJ1XJfNC3OwwzwEmYBhuiir3QdH1mrIMo4oARg3YgmYBZjY+MIAa8tb5u8oUUGzjRvtdu0VFli7wBLbW8Sda81dsEhLV+V79UvcBlm+NLdGpUV5SXNtVOIo9nPzo/2gLkzE2uaf/nE+z0KmRv9+SHAbFmBFpUozzqjg1hWtcteqqYKb7VzhL77DXmEp31wjm/xZ3n3MTdAGZ6o5DVJ+ZrONdBHYPVGu5d4jBreZnqL4+9gCrdcCMbhtvXMT9yy2wHe2QGsAt34xqKBBQe1FlAg6sBuRJepLvieOBg1QCQAOaigyo8wMAAvKswpT6idTvV0it4yHBpB7bm6R/v4q5QsTrUe7Bt16zBbq07UlHe6uZ9/UX95YohUutXiDUk8RuUtpG28TgM0AhLWIrJ7zyAf697QEbTlXDTpicKF+c8AYL++YKDDO2yYjRur3z8zQo9MStXRzcqSzxw3QcWN6eQ6jAdTeQzfTLx+Zrs+cXNyupW10TN/lGt6ro1eyyW2AB3J5EQaD4of6KHWCAYFEy6CD828ceGiAYcCFXd8FVv5IEv93y+MEzXk2ishrElhnqkGbCVgDICw/1w8swzz8fuEsbO8qIts1UtkyHbC0c1FVnrNgiZbVFbRICCSzvSR/lUqKknPcw+ZYp6uh6x9/Jio4YwesBSlrB9kSu/MnrBJ1ujI9qeYqKvD8IcFt0HpLl6vLGE2VPtPmFcdGHTvnRK2/m0rki3QR3qPUO4/KIrC5jMFtmDdQfExsgdZpgRjcts55iXsVW2CNWGBtglsrURGmxA6RP+rhbrbZZh5wwmkBqPIZziqiUQBgHJWgMjwYy38NvwEBYi+99JKn6Ityc1Djexy8ILEQKyXEedTbbd+tp3a9ZoKWVifELTfvXqiDe1Zp5x1a0qv/OWm2LnziIznMYo0b3Fl/3H+YUDumpaMtt2uTp2MH1GlEl8Z8R+yKrfoOHKJfPfyhJsxIiHQGUaKJbL807QvdMaNIi1ZQFrGxDe5WopsOH6HJr7/kbSy4+cYmHIWjyPk4rNYAtBadx6ZEdahBHFbR16ik3MMc7XT5gf46sN9VEdk9PxtgHVb4yl1n6fJLXbXnMA9/JmCYCVgzZts0CgPwKquqNH9pjZY3JETOrJ9tc+rVvl2u2rZpEzrHOkoN3SB7uMJb7vdhSg1xvAlQWekqu0aqqHOUMj12ragAL2oeMPeJSuUNm9frPou2Tmxcro1T5Tczdq5hTI8wazpq/d1UedD8dsDUGT58eKC4YJi+xOA2jJXiY2ILtE4LxOC2dc5L3KvYAmvEAq0B3IYpscNOO9HBkSNHeqUbEDBCYIpIDPm1RAyJquJ4IjoV1NxrkPvpb4BtSvkQeeSaQe3VV1/1aLZuqR7ALsAOcGsgiD5c/p/Pde9bs5svs+ewrjpuSK5mf/llEr26rr5Bf35uum57LTnC+9NteguxKRNt4kKpaMsblBd5NOfZ0yY2AxKUiUu79tbJ4yfrk28ToLO8Ta5uOXozDe9RnjTE2597V1dOmJ+k6LzdgI7660GbqKRNfot8YxONwoHkjwkWQfdDQMqALp8Dsonc0qcwkZKwpXLSgUHLFwwDzPxzHXT/dMDar1D8XYGZez7285c1yhSxzkZ4a00B63kLF2nJyvwW8qxA3pLcWnXrWKr8vLxmaraf7uqv4RuF6mrzaOO3/Gz+ThWxdunZBlz9pZLSRSJdUS82lNiECLPG6WtUgBeVKv1dwG2UvF7LR2cTinXkz/W29YqtzZZRQXeqKGy6H8JUedCffvqpFwXmPe8vTRb2hzUGt2EtFR8XW6D1WSAGt61vTuIexRZYYxZoDeAWR+i5555Tx44tKa82UIuKDhw40Cs5g2NEFBGwazmArlJxkIHsGptssolXIsjfwpT6ef311z3aMbRgGk4w9F8il0QgcMQRKuk6aJQOv3NqcxR218Gddc2hIzyADsjeaqutPEBetapOv3pwmp7/aF5zd3JzGvTbnfvq6B/1b9HHfzz7pq700ZbJ273xsOGqWjinudQPY1yoUp0yfrLmVSYyIrsVN+j/duisnbYa2XxtnMbbX5ulPz47PUkB99DNN9T5ewxqLjfEHEFxRjTKgJ4rHGXAngg5FHKcWNSRTaEY+1idW3+U1R2oAQs+iwJsjDJpjAC7Zhj6cjb3DwOso/SfPrA2oG7TyN0m+o3zHQSsjZ7PRo9FxLF5mBq2/oXF+dDKcfqZI6NCB5UaSjd39kxUV6/UpClTdfkfrtDkt9/UksWLPID+6wt+r+N+eopKC2rUrWP7ZorwmgLWdn/6z7ybMnLQs25g1xVNMqBDf+z8VJFaznO/M6YBefe77767J8zGZlm6FhXgZQNuo1J5s6E++8v6pNsIsqiuzVHYyG2qKGw6+6aKppOiwsYCTKAo+d/uvWJwu8bckPhCsQV+cAvE4PYHN3l8w9gCP5wF1ia4NZEenBZUiAF7gL6gBqAlt9aiWICmjTfeOEmsxpSKTWzJfx27BhRmzvc360e6Uj+W88o9cEwRsiKSS7QXQAk1etasL3XX7PZ6Z/Yy7xZQgJ8+fYy6lxfJ8n7JW60taKeTx0/RB980HkdrV5CjYwfU6qhdtmyh9vyvd77S/z32oeoc4WVoy9SanfnJR14pHhw1jwbYc4TO+tc0VdckFJFH9y7Xvl0WaKOeCdp1bV29Ln3qk6QIM/04e5cBOr4pF9f69vzzz3sbCQZuLZpotEMcSVSTiagTuSIqguMKiEDUiuN69OjhXc6NRLoURhxejk8HTNI9HeZkcz5RJAO8fgBjFF+/Y+uenwoYBd2f67Oe0wFri0im6z+bH+QB0rhWqoghtrZNHXKa/es5qv0M3DJ/5IpzX4C13d+AYFCU1S2jZFRg7Mg6ATAPH7Gpem00QLm5edp93wM1Zvuxjc+FGlRe3KBOFQkGgVtqyZS2XXtlAtZ2PudC4YdhkQlkpsojTbUp4q4lt28GbtkA22OPPTLel3OzBbfMTVh6/w8BbjMpH1s011/2CxtkmlOzcTZq1KnALc8Zm0C8o2Jw+8P5G/GdYgu0FgvE4La1zETcj9gC34MFWgO4ZVhEBQET22yzTYtR4kwCbKlNiCOC8x8UeXXFloIcFkAX9XIp/4BycFB79tlnPUCWSpRq0qRJnsomfUCACYeLSBvggHviND086QvdMT2hSHzG2H46dft+3u0s77ek52D99qlZ+nZZo2I0rVeHYv12m/ZaNX+WJ9pEJJuGIvJfn5+hv7+arIh8/Jje+vn2PTVl8uRmhWacx6dnrtRDn1PGIzHCAzbdQL/bpa9effmlZtr18pW1+uUD7+ml6QuaDyzIadD5u/TWIWMGtjAPUSgcUUAL4zZQy7gtgk1Um00KcpYBlzT6ZJRtizCmE6bhemFVba2TpoiLMwuI9CsaZ1LV5RzAZKrzMz167v2xi9EzM4FBf/+JeFu+t7/Ujb8PBm7IO+d58ANrjg8LHFiXgCBAMra3cjlB484kKsT8ASzHjRvnrRUYFQsWL9HiFTmqVkuXgtJBHUsLlZ/bSB32lypiTqxElAss/bmz/lJN5MeHAbc2Rndjg/UQpdQQ/QJY01c3csuGkLWgd1JU9d9sSu5EBbfZRIczgVt3HVmuN/byt6B8aDsmm5zmVPnDbOLQD3JuY3Cb6e0Wfx9bYN2zQAxu1705jUcUW6DZAq0F3KZSIcaphXYJ1ZdG5M8iW/5pNOCJQxsU1QCUcgxg1Kif/mvgjAJMKCcU1IjUWl9wgHGOiNpam/rBRzrh4S+1eFXjq3PDiiL9+7StVVTQCHYBL/96/RPdPSNf1bUJ9LlZrwpdd+hwLZ4724vujho1Sl26dFF1TZ1+8/D7evr9xvHTUET+zbi+2n94l6TI8eChQ3XmP17T87MSYlAcf+ZOG+nEbft4zjrjI/+1x4ChOumeyfpwTmXzdcnFPW7AKu237UivHq3bcAQBC8wHebNcg00AHEMALdRsHG8orUTG3YhjELh1r+0KR/ltHgacRVVEtihrUBQpW2Dt1oAFWPvHZ5HPoIi1KSLzHdF3W99RwC1rxUoVsX5TUW7dKKv1EXtY/1nTANuwzWxpwmF23n333adTTjlFRx55pG6//fbmXPRv5i/SstoCJa9Q1jT5uDUqb1ugstLSlLfPBKxdYPzf//43NLg1cObfGAlDl7Zcc47l32+++aYH7IkYu+DWHZQBqqjAMyq4zSZPNRtwG1UYy+1XqtJY2Mt9/u05j5LTbODWnz/MbwpzzbMWg9uwT3t8XGyBdccCMbhdd+YyHklsgRYWWJvg1gUXL7/8sueQjx3bSFmkGe0Xx9PqxgKsoCMHNaKyRGdRMnZrcdqxYerp4hDTgkSpAHYISuFgQrslX8tfn/KiBydp/NREbdhrDxmuXYZ08a6JQ/eXf0/RzW/OU4MTwdp7eDddts8QFebnejmXJpyVX9Jep947RVNmN5YWorUtyNEx/Wu195YDvCgwDjVAvWuP3h4N2Y3Ccj0oy3sMawSqltu8vKBC10yu0Zyliahxn45tddHYLlo8+1MPsENNtWbCUfQLoShrgDhycCk3xNjoB/PjdxbTgVtX0dcUkTNFWXFuDTx/V0Vk9/7+NWVCQ9wvlQPsAvMwpXosamXg070n95gzZ07z+g4Lbo2WTD8tf5Fz77//fl199dWaNm2a1382TM455xwvmmqUW8bIeoZST3SdnFvm0BrPI88m9Z1Z65dccomg/wNmYED87Gc/06GHHuoBa4AIlNxUaQFEhYky1zfUa86CSn1buVL33nmLnnviUX0+81PV1tSoR+8+2muvPXXBeee2eLasTzA0rrvuOk2YMMGzF2Pm2tz3pJNO8sp87bXXXt6zGtRcmrIB+wceeEDjx4/3ylYBONmw4nq//e1vm+3hn7snn3xS11xzjUfFZ+xQXM877zzvlhYxDgK3bq4u7zjWcthaq0a7DpvLnQ24jQqgGW+24NZft9lsbO8Af6Q+aq3noPxhYwLxG8FGXAxuAx+T+MPYAuu0BWJwu05Pbzy49d0CrQXc+vNlcVrZXcfJwdkGbHFMz549NXTo0MBpg7pMXi3Oa1D0KUw93VSiVC7Q5uZBtXJnL1qh3a99TauakmK37tdBtx/dmNNVU1evS578WP98+6ukvv98RyjLfZsdLHJToTuX9Ryk8579Sl8tTlD3iAL/dkyF6hY1AkycYo9W17aiRRS2ojhfNxw+UkSEreHUXf3PZ3X79DxVO6GzzXtX6PpDR6hy4VwPCBHNIELO8SYMwzXM8SQCTn1h/jbnE5BENJc/0KndWrapwK2r6JtK0ThdPqSbk5mNIrILbO38TMAaZ9xEh9zzoyjL2nwA1rmBAAAgAElEQVQEAWvm32jJbOpwv1R5t8ZOAJBRegpwbZ+de+65+sMf/uDR/InC8yyxOcEx//73v72NGbexjgC3gE+Xsm/g9te//rWuuuoqD9Dy/NFPgCwNwHvmmWd6G0rc449//KMHknle+/Xr5+XRs05YFxxrIH6ffffVxx99pPYdO2njocO989+f8q7mfTtHgwYP1cOPPqKB/ZLTBy6//HKdf/753vXoB/0BjFLahc2ep556ykspuPLKKz3wC7gkqk0k1fLROec3v/mNdw3KwRx33HF6/PHHPSo7dgHYAlgZC/n3XHPzzTdPstef/vQnD/jau4D3Es8tOfcA7BtvvDEp5zYoT5fPAIUWbbYbpANb2YJbP4hM97uXLbhlPGHFocLmz9rz6FdgxkZBKtf+cQVFoeknTBM2FNgobWXg9nBJp0gavvrRgu7zkaTbJd1Ihsr67q/E448tsKYsEIPbNWXJ+DqxBVqhBVoLuHWFmnCMcVZx+gBaANswNWhxSHHQcej9EVVMjyMJeCU/kUhVULOoFM6wNWjIAAgcLIsgE/0qL08upfPzf07VMx800odzc6THTt1KA7qUaOmKGp1x/3t6bWaizmxBXo6u2G+ofrxJMv0XWuoDr0zTnZ8WqMoRgxq+YZmuO2QTTX/vbS+iDUjB4f5qeY5OGj9Zc50obJeiBt1+3Jbq3y25f/dP+koXPP6B6p2o8Z6bdNMf9m2MGruCWzjrOIEWtTUwjSNopY84HqeZSBkgwaipHAMooGQTYJe++nNuXeGgxvzYOlVXJwN///wY0A6iE5ujG0a0ieua+BP/BtgGlQOx+9XU1qq+LlGrmPGZHez8du16KTe3Mcc4TAsqFYRdAWiDBw/2LgHTgBYkbIQNrNwMIMxo9gZumRNAmYFYrn3qqafqlltu0U477SSijjxTdn2L3LLO2UwyOijPAZFb2s033+wBQRrPAnTjk08+2XsmiOi7G0p33nmnfvKTn+joo4/Wbbfd5p1j0WrGTlSUvNwTTjhBvzn3XNXllXn5uNUrVujic36hJx+6X3sfeJiuvOo6rz5uRWmpHnnkER144IEegLrrrrs8lgdzZBFzrgct3jZmyBFH1Zz3wRNPPNE8LbZhQD8uuOACL7pNGsI//vGPZsEzDr7++ut1xhlnePn0Fp3lcxgiAHbmhX7svffeXh8YH6Aa8E2z+wZR65kP7M/fbAQFMU2swy74sucGYJauPJGdGxZEumvWwG3Y6DDnRhXGsn5FoRjbM8O4bePN+p0qVzcI3LJ22Qhl3aK+n237HtSSr5d0qiR2NEnWrpG0kyR4+g9LOjAGuNnOVnxebIFkC8TgNl4RsQXWYQusTXBru/KYl/qtRAOJ7kBzBfBA88MBoVkNWqIw0CuDmpXZGT16dAulYY7HMYR2TCSLEkJBDTEYSrBYqR9ANtEsnCciRQBkPvNHbt/4bKGOueOd5kvuO6RCVxyyub5cWKWTxk/RjHmJOrMl+Q26eJce+vHoRhDjtpuff19/efnrJAC665AuumiPjfThe1O8/FYaYOTT5W30iwfe88oJWRvcMV9H9a3Wj8ft0Ax+UglSnbJdXyF2Zc4z0XIiGkQzALcGbF3hKOYBAISN2EDAjoAsnE0iaMwhf/i3NcAIIlPMKZE8nELLTzThoqqqz/TmW43llf4X26Yjn1BpKTWJyR5N39yItR9AuKWATODIT0/mHsyNlQJyqcQGbgFsUIbdBmWfjR2AFJsNAAtT3TW1ZCK8pmjNuXvuuacXAd1vv/08mjNrxY04s8nDcweQhDFhLQjc2ncA63322ccTTUMlnWs21DeocuUqVda10ZKq5frxNptq6eJFevHd6SqvqPDq4+6z21gvAn3ttdfqqKOO8tZcuoi5m3OLYJ0/75nNA55pNjaoUw0w9jeAK5Huhx9+2KM6037605/qjjvu0GGHHeZtFviBKe8f3mc/+tGPPFDtRm25F394Bvg8E7D194d3GOP4PsFt1OgwfYwqjJWNOJSBWz/LIl1Ul+eE581Vl+Y6MFR4J6XSXsj0DPP9Gga3B0j6l6Q5kniQpjf1AUGHFyXxY/ELSVeH6Vt8TGyB2ALpLRCD23iFxBZYhy3QWsAtURdALQ2A66rt8pnli6arhYuTzx8imkQN/Q1nxASV/LRMO9b6QVQImiGAD+cVQE2k1tSOOZ+oJI1yOvvdNFGffNsIYNvlN+jOg/upprijlzO7qIoN+MbWp0ORju5dqdHDkkWtAKB//s+nunXCF0ndPvFHfXTc5h09RWQiKvSBKOlneT11zYRvmuvochK5u4f2q9O8ud80U7NX1tTpnEc+0L+nzW2+bl6OdPHeg3XgqORav0SoEcyC4koOo+UGGmDDgQX8ArrYZCCqHhTx5EY4yEZfBggTSQQMW51bvyLu/zq4HTrkIRUV9fbArUXqgmzjRqyDSg254NYFtaYYzBq2ZuCWdYqTbvfme3/urJ3DmgXUAUihH1sf3Tq3RG4NCLLJA7glinn44Yc3l+LiegAG8m2JqN5zzz065JBDmvuWCtxy3dNPP92LAkObhu7s5rKuWlWjZdW1OuqoI/TKC8/pxrsf9EoHzf92rnbabGMPDH72+edq17att6ni0t/9z3uQoJSbow0VmcgyUeR//vOf3un+KOuf//xnL08ZGvNll13mbSpAa0YYjvOpZ+tvbCycddZZzbTkdCJYVpLKFcALojDbPaKC22xAZNToMH2LKoxl/QqTp25jTyd0lS5Xl/Oxs+Xqcx2eGd5JbLZl29YwuJ0kiVyBYyTd5evT9qtlIBCDAPjy0o7pydlOWnxebIEmC8TgNl4KsQXWYQu0BnBLiR9oYjgoRI2IpvjzoPiOMj1EcokWBTUcTnLeiPi6CsZ2LE4m18CpIfIa1EwNmWgjYI7dfa5n0Rm7BxFLUxS+e+KXuuTfHzdf7uB+deq7YXf99fX5WlWb8EN+tFEHXTCupz6Y8rbnVBklbsWqOp390DQ9++G85msAQC/aa7C26Z7jRRnMqVZOri5/+mP995vkCOFpO/TVaTv08+iTUESJGq3KKdTP7puid2Ytab5uUZ50yvB8nbzvDi2GT8SViBMAiP4BRm0e2HhgjgAngB/AVNhcNUA5dsORNXBrNwdc4XSuWvWl3pq02//skzZq0ydVUNAjqXyMSydmnGwK+CPW/gFTFxagScN5dm3slqoBDFl+owlKcSzrlRZUIxfQAuWZqC2K3K5j7we31i/LuSXaCs3WBV7cj+gwwPbWW2/VMcfglze2IHBrkbeDDz7YK/0Vpv3hmr9pj/0O1tR3J+movcepZ+++evbVd1RSUKNuHdunXYN+cOsCW4AxIBTgGqZBsb7hhhu8OeTdwprmXWNz5V7j0Ucf1QEHHNCizq2r6h1ErXVzSG1DybW3UZn5jMit//kLeh6zAbe2zsJGhxl7VHCbqkRPurkwcBumxq+xgixCznXJYYe9wKYS1+L5SVUSLsyaWIPgluLfX/LYSuIBbswXSG4ILQBsqZX3Wpj+xcfEFogtkNoCMbiNV0dsgXXYAmsT3OIcQAcE+HjUxIYGD7j6c1nN/Ci24pQC3IKaiTH51X7dY6FBpgPIlPFYuLAxNxag7S9r47/HoqpV2vWa17RkRaNCU/+ORdqoeLmemZ2oc8vnh26+oc7fY5CWVy7zhHh69+7tAY15y1bqlHun6L2vEorIxXkN+t32XTSiW5FnG4AMkex25R102j1vacLnifI95O5eus8Q7TuikVJJRII+9hg8Smc+Ml1fLEz4Sd3L2+iEgbXasCQnSQ3a8tdwUMl9tnI1OLdEwPmeazJH2MNVUg7zaJCbC3AGLDNuNgr8FNH6+hrV1s7xIol5+XnKy03Yr66+TtUrGoW1AMJWPzfMvTmGe/lL1fB5bl6e8ptoounoxNgDYIgd6J/lurr3LyrasDnn1sbG3/4oHPfBOU91P+xk9Fgi3jjgXMOAsZWqYePFIrdsZvDMcD/7jOisG0Fm/HzPOmIu/ZHdTOAWaq6pLLs1fMnjvffee73ILlFQuye5qG7OreVxsoYOOuggD9xCY3aVmYPm86BDD9XGw0dr4jvv6si9d/bA7ROvNtL/i9WgsqJ6dawoDwS5LrhlU8tyjA0cXXHFFUJ4i0gsVGKaPQvMuTt3jB0qNI1Nrajg1gW2LpU6XamhoDI4YanMBnSziZBGBbf0ifUYpYxUqhI96Z7pbISubCzYnGcCcItNrPGO49nhT7razkH9WoPgFr77Y6Rzr/47OOemMed2X0mnkQ4e9t0XHxdbILZAsAVicBuvjNgC67AF1ia4JcqIk41TQTQVJz1IhdjMn6oWrn2PGBM5eUR+yRkNaqkAsgE4wDYNZz8oOum/x4VPfKR730qUx9myV6nenJXIN83Jkc7ZdaCO2aqn54ADIKF50r+CTr09leOvlyQUkbuXFerYvlXq27HYc8axDZToFQ0FOnn8FE37OgGCy4vzdd2hI7Rln/bNQ/XyH6d+rjtmFGmJI4k8tHupbjpipD56d2JSySXXmccBx4EE3AOy+NutywolnJxN/g6qI+y3N9cGnPMHkMymAjb1UzBxEv0iURb15JpGxc1EQw2ab7+iMfc28Ok6uXY/wLNLJ45a6sffh1SlhlLRl7kfzwK53dRkBowG1dCFYcCzAvhlngwsm22hrrtzR78YIxs/2YBbKLimQu5GCI899ljdfffdzbRlGz+AF+ALIEQ52KLQrGfq3xLppYwOx2RqRNk+nD5Dm43YRAWFhXp12ucqaqoljIPSNqdOZUVSSdu2SerSBm4Ri3rsMbCDvOfJ5pfSPwByoqxGS3b7YlRXyxG372ByQB8nmo3gln+jwk9LdiPG6XKEXXp2qjJQrgBTKvqypRPQX1u/Uei/VvPX6lhnmp9swG1QiZ5M98lG6MoP1Okr6RKwhVgHrC1rvF+CWEOp+rUGwe3Pm3JpH5G0X4r7kWvLcVeuTnH+VSZbxd/HFogtkN4CMbiNV0hsgXXYAmsT3OJ4EGkkcoLDjXCTm8vqN3tQLVz3GFcQKVVEKAggAwIA2gBXE+tJFUF271Fd1NHLta1vaOxF+7YFSfm1bQvzdOWBwzR2UGNuLg3HkXF8m9tRV02q1PKViSjCyB7lumSXDTXzw6nesYAc6M+fL1rVEgSX5uu2Y7dQv07tksx067Pv6i+vzVdtQ+LVveOgTrrygGFq1ybfq/1JFJI6nDh6FqHib1MB5m8cN2jIACcAk33Gzfg3fbPSP0GRTK7H3OJE8j3RSK7DpkEqYEx/XDqhOzCjL1tfwjySrnBTEJUxHZjwjzkbYO2vwWuKukE1brmfAWuEi55++mmv1IyVrPGryhJxJPJIzifA05rZ1jYLeMZcEGQlf1jv7lwERW45j5rRrBmAHLmpfurr8ccf7ykGA1YBsjY2lIehLCO6BJ2XZjZEnInorVtvNtV8uhFfQCqbVxf84S/a/8hG1WZrkPRLcmtU0iZXBfn53hojf57+E5XFnn7xLqJ4vCeI3rHJZpRu97r+zRFsQqkfAP0RRxzh1dv1b1SgpMzGBOMjQs0z744/zNrlmKA8az5PtTESBHbpP887a88YD5nSCaKC22wUmf3iUGFsko3QVdBYYESw4cZGHe8wRPrYDOIdg9ZA2LYGwe3vVpNSLpN0z+p0+SNT3J/vOe7vkk4K28f4uNgCsQWCLRCD23hlxBZYhy2wNsEtTpFF5cg1JGpKpCpItZQpCCrT406N5YwiiBSUC8exfoCMw0RpD5wbaLPQ04ggp1JcdkWXLnhpkd76YrHXBV6UTRjX+3+H4lzddswWGtydKg6Jxv0uve8lPfh5XpIY1B7DuurX23fXB1MnN6uhkuP4+meLRImhSgcE9ylp0O9376XNhg1qvjCO7c2vfqEr//Np0v2OGt1Tv91toPKoTdRkQyiERJxMDdkiPRaBwiFEOIroIVFalJkBCziBpoZspT+4JnYzoMu/mVNXURlABZDAqU4Hbt2OW8TFs20TZd2+D8pN9D+iLigC2KYSvnLPMzDhpxNjFxP+CaOGzDVdUJQKGKeiLwMmUenlPMrtWKkZ6ytgFtDIGKHbAuCsGbgF2DOPLo2V8ZHnzUaS5elyHrZBHMyN6HIe5++xxx4e0wDGww47tMzTdsGtm3OLmjCqwi64tT4yn+TyEn0+8cQTdemll3qbJW5jEwkQfOSRRzbXgUW4ClDMGrv6+r9pix13T1LWoUYuQmf9N+ys0qJ87znmfcJnbJwF0U6pz0sEmVSHm266yVMKt8Y6JtccSvZuu+3WTMcnL53NL9bCfffd55VWsgaQZ+OB5kaMw+SJ+tewS2UGmJpStcs44JygUkO2cWWbG6ylVJtKfrBrgDConJq/j/w/G3CbThwq6B58FpUuzTlB4JY5Za0DZFkb2bYY3GZrufi82AJr3wIxuF37cxD3ILbA92aBtQluccCMFoYjinASTrZbisQduNXCRcE1KPpAlJGcWURCiAYHNRx1HB7AHTv4AFtAAnl0gDh29InipIog4xgREfo6v5uueGV+4D16tGvQedt11I5bJadP1dU36PKnP9JdE5PruZ68bR/tP7BQHzVRorELAP+T2k664ImPxHnWdhpQod07zNeg/glBqpq6el385Me6/+3EdXlxn7PbQB27dXIkwkodmUOOY+rWhiUvDeCD4wZ1GjAUBOiwoakhc45FjSwfEwccwItN+c5f5zbVgg7KL2WuUynOBtGJzQnOlN+aqg8WIeJ7i+TbsdzPgG4qwJwpYpwKIBg9m7ECuC688ELPduRmG12SaDhRV/qB2vCvfpXMUDQAYzVy/TRYi9AihsRzBsDmfhbRJVqP0JQBfKLIgO0o4NbbaLn5Zo9yjMIy4lLu/PFvWBIISzEeQBT3Z71he4Aon7N+/KD0kksu0UUXXeSZcMjQoerXf5CWVFbqixmfatbnM3XL/Y9ri61/pAIiuXmrtOdu4zwGAu8DgC724N+oNFtJHqjJDzzwgPd/mBK8PxgD1GPeSbwf+NsFvpdffrnOO+88bx4AuvSdY9igo3bv3/72t6Q6tzwXYTZYbG34xa/8qtCpNkYsqsu9LE/cjdpm+iFhPGxqMUdhwW02olVRxKGsz9mA26CxsEHH7w1R+yBV/Uw2su/XILiNaclhjR4fF1tgDVkgBrdryJDxZWILtEYLtBZwG4ZSDNUPQAWlNigKQfQVsSZ25BE+CmoG7gDRONA4cQA4HFocu0yKywDilye8oSumtdH8qgSl2O41dmBH7VYxVz27J9fjpRbtrx6cpuc/Sigi5+fm6KI9B2lI8VIvkoADS7/efuddvbigRI9NT+Ticv2Ttu2jYzfrqDcnTvQcM5ztyupanfHAe3r108YySrSC3Ab937jeOnjMwCQT4LAD/gE+RIVx9K2GLQci/IRNaACAVHnLfrtahAuH0UAVx+BgE/nlj6n3povcupEq5pdoV1ALk5towkuZKJj+67vA2CJ9mejLFjnjXplK/WR6B7jAmI0XQBJrlsg3jU2YMWPGeJRfE0Fyr+mC26CIcSr6MZ/7I7pcNyq4tYgvtF36CHC87bbbWqxD1gzRfyK8RGRZdwARIrhs7BBJpRauG5W2iwC2oQOzUcX7oLSsTBv26K0f7bSLDjv2RJW3T+Sgz/tylq6+/P808Y3XvSgsQIy1T/1Z2xjBZk899ZQXJWfjimuSb4qtqcVLP4hg+wEmkeUrr7zSA89cgw0xqOSsYyK9dh/rt3s/d0PJvyYyAVv/8elKDfF885y790uVq2vXtRzvsDm32YDbbMShotKlGQ9rivGasjif8SzxrmMTx88YyPR8ut+vQXC7t6RHMwhKPdSUj3u6pOui9DM+NrZAbIGWFojBbbwqYguswxZoLeA2DKUYZx/HBIfXSvO4U4Mj88orr3i5VEQMg5qrhmwqxFavluMzKS5DzT33vjf07FfJpXg49yfb9NYvduyjF55/3osIUG/Xc6aWoog8We9/nRCaapsvXXvIcLVZ8oXndON8IRxVn5Onn9z8kiYvSFwfEHzhnhvroM02bBakAsB32LCfTrhnsj6Zm1BPrijK0/H9V2qvbYYnqRrj4PEHujHUaho5hoydvpIbS6QKmxBFA5BGaUTiiFpxDxSR+Zs5BSziYHMPU0sGdPmjwf781KD5TdUfzgUU+kV4wtCX7ZoGyiySDbBOBYxTRc2MPs3fQTVsM9nTpVK756e6n398lsfIfbKhwbpzwLX9isGZ7Omn0Yadw7Djy2S/uQsWadmqfK0MOLA4p14VxTnqUF7WnBfsp59bZBU7ZDuH7hzYHLqKyC6wDLKnS2f/rnPoN0OmUkMcb3PI+MlF/n/2zgPMyuJ642fv9kJHUIoiAoKKEnuJHcUejRpbLIkRayxR04ummKJJ1NgTY6JiSazRWP5WiAXEAqIGASsoIFIXFrb//c1y7s4dvnp3gauZeZ59Fu79ysyZ+b4977zvOcduUc8Dz3mapFX5JIdKK5em7xo+YYNb3nVsphK+EpaZP26t8X0ngluyH34YUwqIUkGUDKJUwPNJ+ueP8RbwFgi3gAe3fnV4C3yBLbA+wS1m1RItMH7IjqMkxSSTAUQRy+Y6XlwL1owMqTAuyAvdBgAC/OKUaBZi2+nh+LiMy9M++FSO/utr0mqibNsa4PNnBw+Xr23f34A6yg1RkgVmbfq8WpMMat6ydpe7d0WrnP+lMulbVWQk0gBMJJNLV7UYEDx1TntG5JryYgOCd92sDWwqgG+s6Su/m7hcPqltv+5mG1TLpfv0lYUfzsiRd2v8Hb+xEc4d7BRMt90AtjC2MGdJGU+uiXSUmGndLFA2hO/oL2CacWJzrXNrJ8XRUjv0paOJm2DXuLabfTksCY/t0Gt8alCCrLBXgMaN21lXOTaJfNm+ZlIptbJ0rGE3G7Jez02clOT1FQaMw+7nji9pRuCwvuha4bdufNjjC5Kfu9dijTU2Nsny+kZZ0Vwmjc4Bmlm5V5dS6bIauCUtxZPEhsq6RwHjqPsxbo2nzQfY2psLKkdPMz7OZx3ym+coanPCfj/kU7M2n+RQaeXSzFlQ/V3e8byTeNcllV4HzX8nglsu/8rqMkAUi77Vud+eIvKsiMxbXeu2vXh6koXpj/EW8BZYwwIe3PpF4S3wBbZAoYBbGFESRkVJirWGK7JMysq4DWfjqaeeMmARiaDdcHJIYKO1LpEMBjk2cfLos+54VZ56u60OLq26rFiuPW4b2WVwe0IcraXb0HuonP+PaYIkWduXBnaTozdaLNXFbf4JYB5Z9Luf1snYcVNkzuL2urT9u1fIjSeMkqF9arLn0//rHpggt84qkVVN7bG4lAO65titZcXiBUYmiSwbWyqwVRYOp1R/sDlMrlsDFsdWE0TB4IbFCuI4s+EAQ4szTomUoE0HnF+NudVspEGlTtIwP2oQG5S5wDhOTqwyU10T+dzfBgQqTw7LhmzLl7X/YTHGSV45Oj7mz5WaBiUZCrumLYWOAsZJ5OBRpW7C7h/G+MbNn46R67rlkpqammXeoqWyvLlU3OABnJqaTJNs0L1KKsvLTbd0c4Fng/Xurs84e4ax7lHzmHR8STaakkiZo+5nM/X6HITJl/ncBbeA1TRzr+CW90XSJG2dBW5R56CW4R3Jes+3dTK4PUpE/rkawO7+WdZkzQxIxqtnCDEXkfNXlwzKt8v+PG8Bb4HVFvDg1i8Fb4EvsAXWN7jFsVbWJk5STBIcYmLDMhnjJJM9FuaQGqDaAKyAMBxAAC1Al5g+l7Xl+Ch59MT3FsnJf3s1e11Y1X+ctqPAmNqN5DsvLCiRO99uysmIfPBWfeX0UVXy3jszzeFIp5FQT3pvkZxz1+uyzKpLu2nXIrlt7Jdlgy5tzre2W194Ty57fFYOc/yVbTaUXx62hZSVZIzcDsAKK0Fcrp0R2Y6vtYFtv379DMCGPWf8sLrKRHKOXfZH2RycU+6DLZE3wzxrqRH3cbHBrcbc2qDOPT5p2R8FFJyfhK0Mk79yPuAFcJwESGh/42rgxsltNekPcxQVYxz1+rEZX03mFSS3VXDmAol8QJk9fs53s/fGyZft8aRhfMOyWev1gmy4qr5ePllSJytaSnIyK3NOsUk61SjdqspEWlsNqLXl6HZZKhvouSqAjtiQftgbNIxBn1kdV5TqgGOSANugNZR0fHpuGNil/9iAdwMbRkmeoXySQwVJjKOeDfrLOcyrDWIJv+BdR36DNCoN916dDG65PDWzzkSE9Jn8+EmWhoiQipudXGrgAoDXTPQQZQT/nbeAt0CgBTy49QvDW+ALbIFCAbc4R9Sg7du3r2EAgxpZjKMyGXOOsqZkMMW54fh33nknW+6EhFBIaMPq2Go2ZEAYMVnamppbTE3bGZ+sMB8RM3v/WbvIoF65wJbMxuf85Wl5+iO7MJDIWXsMkr03qDOJTGg4gWQsfmDKx/Ljf/1XGpvbj9+ml8jYrctk9F57ZO/f0tIqlz8xS/76wgc5pvn2XoPl7L3akmHRtFTRkCFDsuCWz21gS9wymV1xohkjMbK2Q4rdkCxr2R8YE20w5vxwDZw7gDHZfKPYFxfc4mwq06aAws2m6zr2KjfWz22mLZ/4Vjsjsm3QOCCRXQ9NTVkVQBIptcqXNTuxe0+ukSabbhzjG5ZkyE5qpNmZ840vtRlf+q/MoA127fu5SeDyBWXYLkoObrOsaufaFXWysLZB6lqLc0p28X3J6szKG/XuEbqOo5I2cY18bejG6OoaiLqfPT5lvelDknXovldtObgdc2wfF1ZqiGN0HdIPXcMuuA0Cu/r8Jk1axb0AqkGxwGF/nsPA7bvvvmveb2zIuUnC0vypXwvgltsf/9ke69nsfa7ef5kuImRku55ln6Z//lhvAW+BcAt4cOtXh7fAF9gChQJucfphPO1ETK7Z2XGfPn26iaclrjaocQ2crJ133v8J9AcAACAASURBVNnIcwF7/J9kTYCyGTNmCM4NzG5QpkzNuAzgA7RpGzdptvz8kbez/z9ly3L5wddQj7W3FfVNcuG9b8gzb7eXCCotLpKfHTRUBjZ9bEoP0QfGWl/fIP8t3lSuHf9ezjW+uevGskPZR5IpKsrWFV3V2Czfve9NefyttkRQtOIikcsO30IOH9Uv53xYV7JKI3fmh6bAFmcPGwL4+QzmOEmdR4CoAl07GzJOLzG0XAP2Ngzg2uCWPilbH8ZW0k8FXkFAic9wprlfUO3SuMfVzWiMw0wfuWcSYNbRxE120iC3r9gEhzsqmy72cWW4UWOOkxOnYdz0PlFsZRK5LddhHmgdjS+FsdZ41TDWWhnFRUuXydKVrVLXumZCuDIosrIm6durPdtymF25j5basY9Jw1onidHVa0epDjgmjSRYrxmVACyu1BDrFJsDUnlm+D99iGNt9ft8Mh8Hxc9GrXvGx8ac+57h/ce12ERNs6Hk3mstgdu415f/3lvAW6ATLODBbScY0V/CW6BQLbC+wa0mxsEhhnUFJAFMgxpxm9T4VDlv0DGwv1wLh5edfgAsYFgls7C4JEAKq2OL00OJEcrgUFuUtriuQcZc/YIsXdlk/k8d20t2rZTdv0ziyrY2f9kqOeOOqfLW3PaMyN0qS+S3hw6RogWzjCOstXSfe3Gi3DSlTl5e0P56/SwhsvzkoOFy/I4DZMKECQZs7bPPPrJoRYOcecdUmTKnPflTZXGrnLd9lXzjoN1yTMC4qfVLORMcOuJmAZ7EzeJUErNMMimcUGwSFLcctk65Now3tuNanIt9FQxyPzYmNPuyzdLZ4BZmHocyaXwr97XlqHb/4uIgg8YSVOrHPS5KTsyxmk0XUJbWObaBrTJtcfJlBRLcO9+MxDpGGxi7404KzNKWOwpLasT9AZ0K5pO+I+OkzGH3s2vAfrpkqSxvLJV6KzGc3r9CWqVbZav07t4ttEv2OmIedQ6TJsHqiJSZe3C+GxccxZK7AwlKPhU22DjW2t1kCpMv29fXzZk0CZ14N7sS46g1o+CW9WXLjwlv4f78DYgD41HX9+A26RPrj/MWKDwLeHBbeHPie+Qt0GkWKBRwy4CeeOIJw8SR7CmoIem1kyUFHQO41QRJJC+iFqzNKMaxvzg9gEvktpTEoV3y8HS5c/Kc7O2+s43IiN5lsscebbLh/86tldPvmGJK/mjboKJV/njEMFkye4YBQ8iEkTovWdkoJ9/0vLy9uD10qqqsWK782kjZc2hvczp1PAEQg0ftImNvnyKznSRTp2xaJ0P61Jh6p9pwKNUJxXmDacX5ojF+zSCsJYeSlmnhfK4LY06WUUApwJgSGnwOmFZWV+2Ow6hxugBenEs2FfgN00sSmbRyQBvQMBbGazvRccDMBnVpauDGASVXLh31YNoy3jC2Mky+bM8h98iHqQtifOPkyy7wTLI5EGWDMDl4UmAWtDkQdT9lkV1WnnO4Z+3KBqltKl0jszLfV1E+qDojPbp0ybmFso5BQCsJa62bNflKmd1yQfY97Y6GPRNpgK1rW71XUBKzJKWGuJ6uQ37beQ+igGaYxDhq7vWd4YJbSpaxHniPeXDbaa6Ev5C3wOfKAh7cfq6my3fWWyCdBQoJ3AJMcZAUNLoj0XhSkiWp5NYGdwBXgB2NZCEDBlAWMLfFsb9u7C+lfIi1bVkdEktSqMM2WGguutdee8kzby+Q79zzRk5G5GE9MnLyZg1SUypmPDDNsLYfLGzLiPz+wrpsp/p2LZebThglwzdsd6BffPFFeXX2Mvn7u+VZtpgTRvbvKjccv41Mmfgfw0SQFEudRTtxlGZDRgbNhgBsrQ0Etb4tLGtQdmPbYjiBbCgAYnFEcQgBZkFOL8yKAl3+rQ0gBhiGpRk8eHBkiZGg1RsGaMKAmRs3azvzrqOb5Gmx41uxrV2yhfOTALN8mLoooMQ4YHSj5Mv22JIwvnHATNdYms0Buw+uDbCbvXkQtFlhJyhaWzVgm1taZHl9kykf1KbNaG9aPqgn5YOqqnJkuEHPgbuewpI2cVw+rLVtg6AkanGbMaxdBab5bpDYUmQ2u6JYazujtb6ruD/vFWV8w55BNw8ASpE0idfUVq5KBPUPa43NSw9uk7wB/THeAl88C3hw+8WbUz8ib4GsBdY3uMUBUWmrLccNmqKwZE+cT4IkQBzOCo7LmDFjAh2XOPbXjv1FtnbiLa/I5A+WmO5UlGbksW/vKrNen2ziRj+qHiq/fmxGTkbkQ0f2lf26fyKtTY0GxHENJLwvf7BEzr5rqiypa6++OaJvjdz49VHSt2tFznD/eN9z8ufXV0pza/vrd78RG8jlX91KKsuK5emnnzZOHpsACjhUDmknjiL+FmCKfQD6AGLAp13fFgcZ6TJAFwBqO3swVGREJm4NBhaQ7iYFCnuUcIDZjCC7NffnfMAtjDh2cZ3esOskYTvVabblvUHXSyqFts8Ni29NI5fuKNtp28Au2aL9VMYsLFNtnIw3zPZh2YlZYwquk5ZxUcY2Kk46CpgpEKavSTJjB4FM5oF5U1Dnbo40NTfL8voWWd5SukbmHp7E6qImqSkXqaqoCNzgifuzouvAPS7J5gjnhCWfCrtv1GYF88DzwHOYFODZmzxBIDPqfrpGdY65v52ZOs52XDsofjbqvDBwS+Z8+sMGaNKxB93Hy5LjZs1/7y1QuBbw4LZw58b3zFugwxYoJHBLrCuAar/99gscF0zkxIkTTRZg5MY0HMbXXntNKG0DOMNpIunR6NGjA4EYWX45Poj95Xo4vJQT6tGjhyysHiQX/HNati/n7TNYztpzsDz3/PNy67Q6GT839/V45pc3lh2qFphkJTQtN/TwtHny/fvfzMmIvEX3Frn51N2kZ9f2bMs4cNdPeE+uevrdnPGfssvG8t39h0oxgbmfMcbPPvus+Q24xVlUxstOHAVDDYvNZ9RzRA6sDeYE4AvQZcNAgTHOrsbN4vzhBOLAIe+mVFAaR5B7AIyZF5hiAL7Kku041ai42bSxnbbRcGwBhXaCKL5PWmZI1wLrEfvGMb5RDB3Xyjf5VRjjG8fQKaubVsbrPng246vrK0nSLfs6+YD7KDlxWtY6SVZmG5jVrVoly+tFVrSWrJFZmTRU1Zkm6dO9SipW18hN8hJ2bcA5cay1HWudFti6fbJtoBuAekySDOFhmzxRY08ba20z90H9x4Zxz6F9ntrMZqi5Bxt+fMZ7Mc07ze2TB7dJVr4/xlugMC3gwW1hzovvlbdAp1igkMDtpEmTDDANY13dZE8cC1AFxMAIkgAKxwUAu/feewfKXzWbMDGw/AQ1EluVVdXIpZNbZO7Stjja/t0r5JFzdpGmllb55p//I1MXtMfMkhH5x/sNkr6rPjSSPxgJHDHA598nz5crn34n5zYHbFYpYzaolb323CNbf7GxuUV++tB/5b7X5maPBcv+6MDN5es7Dcw5n3rAjHnPPffMAlMFHoARQO2cOXMMM0O5C8BlWMMBBeCqnFjjdPV45NRsBITVsA26LvJB5gVwCqgGGBOviyNJ3LGdnTgsbpZz6VtHQSH9g7FWls5O+KNOfVDcbL5sp4Ji7Ki1gtVGjNsGZnEPcFJwHwUE9R6dkZFY47Tj5Ms2K68S1jSJgGy72LWMua69mcNxcbHW+UqZuc/S5ctlmcmsvGb5IFMjN9MofXp2kbLS0sipVGAbJecOA4KuDJ4wgqRsuXYqCNzHxVrbkncb2KYBl7ZRwlhrjokqNaTX0Fq63N/NFxAGUBXc2iWSGAubboRY8F7z4DbuLeS/9xb4YlrAg9sv5rz6UXkLGAusb3CrTh19oYQN4DOMddVkTwAmEhaR/RdnBRZXa7UCbpEeAyyRL7oNQAyIJmYX5yaoPfXUU/LonIw89G47gP3TMVvL1v27msRR0+ctz57WvapULtm3nxQves8AKK4JCP9wzsfy7IqN5KE3FmSPpRTtDw8YJtt1qRWYVRJnIdWtXdUk5979urzw7qLssWWZVrn8q1vIASP753SR8cJwI9EDNCInxnnDSUsaHxu29Ok/yVa0Fq99XNI4XYAycwCoIL6WH+aY8Sq4taXN6mRr1mz7nhyfT0biKFCI/aLKDNE3jtEyNfnUDnVjfAE1Kpm2xxfFWmvSonzAfVupqfrsxofeM06+bPctDbiPY63zBbb2PALqFIjkw1p3BNzX1dfLisaSwPJB1MitLm6UDXt2DVSKRCWfCnsOk24eJAFmSVnrKBaZ9ZxEvRA2niBJepJSQ6rwcEtvRWUot22icn77GWacvJ9QkvD+7EjzzG1HrOfP9RZYvxbw4Hb92t/f3VtgrVqgkMAtbF8U64qzQrypMqPs4sNMIqXVRrIQGzi6xkMm+8ILLxipLbK0oHbPo0/LJS+1SGNL27e7DO4pF43eTM64c6osqG3InrJJz0r5wW7dpP7TOcaxpS+AzclT3pBLn/pYZi5rr6VZWZqR3x81UvYdvoEBkJTV2WWXXWR5a5mcPm6KzPxkRTtgrsjIt4Y2yAkH5QJ0HEwcTUA9TKg25NiAT2JcYUjSxsdyHZw+bIf9cQapAYmjCKPLdZPE6cIWk1WZBouuUmi7FBDMbVjcblj916Qxidw3DSiMipvlWrDV/CQBEToXcaAwruwPjjtggHnuDFAIyxXFWitDZz8HHZEya7bnINbaBvNxL7WkUuYoIKj36AiwtWN0Fy5dKktXiqwMqJELd1td3CC9utZIWVmpYVfzAba2Xew6uKwFl7WOkxMnAbZB8xDFIqeZQ66dJNY6ikW2k7dprHWYfJnPXXCLDe35B5CSn4H3ZZhyJ25t6vce3Ca1lD/OW6DwLODBbeHNie+Rt0CnWaCQwC0xnoC23XffPTCLLw7v+PHjzdi1pI3LzgKuyJq80047mbhZt8F4Iuvt37+/SZAU1I6/9il55ZO29MjEuf7wgKFyxROzZKWiXREZ0rVVLtypqzQsX2wY4m233db0ibI9p/x1ksxZ1p53dYOaMrnhhFGyVb+u5pozZsyQd999V7puspV89+F3ZcHydsA8tE+1XLRDtaxa9HGW2eUcOxuyMosqJSYWWRvOJ2MjSZSbICps0eAAItUDwHIOIN2V/oXF6bLBAKDH0aM/uuFg2z4JuLUBlcbIhQHBMBmj1s5Mk1HVtkmYdDJO+qrXSAsKo1hrnHo2GdLW0Y0ChWlZ646CQi0jlC9rnU9W5qhYa103cbLeuA2KBYuXyLJVGVkVUCO3bDXIralgU6RNNh2kIIl7gYfFWieRE6t8m+eBls882lJkzcjt1tWNqzOdBNgG2UHXixsikbTUkF5TszKr+gPgS5/YXET5g6qkI82D245Yz5/rLbB+LeDB7fq1v7+7t8BatcD6BrfK9DBIGMkPP/zQ1G9FNmY3gJfGceJUUYYniAGcOXOmqam6/fbb5zC6ei2cGxIyEUtKWRu3TXxvkZz8t1ezH2+3cXd5dfYSaV1dCogv9hhYLl/pt0JKMiK9evUyYBCGb+qcpXLmHVNl4Yp2sDqMjMjHj5J+3dszIs+aNUseeOkdue2dUlnVtJoeFpFdB/eUq4/ZWua8NzPL7GIHZRjdxFH0hc0A7EYDXCvA4/+aIAqgizMXBJTs+Ni+ffsaxjUOUEXF6XIfbAvg1TjdOHDryg6D5jWMTaKvWsO3I9JJl/G1GUE3gVJQ3Kyd0TifbL4KjClPgvLgoYceMgnJ8mGtbVDItX74wx+aNQ8Dz1jOPfdc+cMf/pCVSnNvlw1bG6x1EjkxgITjOgoKeY/wXKLQgKlLmgQrDds5f+FiqW0okfbq1u1vk3JAbkm9VMP8Z4oC40rDXuw2sLXl2O7x+l5QMBjEaOYjq4+KsU0yh6o+sMv9pFE/ME57o4jnjb8TSeZQbaBj4DfPo25osPlDTgLeT4SydKR5cNsR6/lzvQXWrwU8uF2/9vd39xZYqxYoJHCL00HpmB133NGAMW3EgOKg4uBoCQnY3aDG+VwHWS1gzW04JMTU4txQpsduTc0tpqbtjNUS4bLijDQ0t4NPjj1t541kZOYjaW1tMSAOMEKfHn9rvlx875tSb4HVHQbWyA1f315qKojMa29XPjJFbpi0QFot5ufIL/WTSw8dLqXFGdN/tQPyOWVtuYKdERkgj7xZJdHYLAx4ch5AHKCLbBnwQnwzbDmOJDHImuwp6YLDCWfDgRhj2FbugfOoDRZYgTWxuEExt7YjnzS+Noq9SpOwiX66DFUQyxYXA6nOOOOzHemkdrQdeQAZwIykZsRku8AzKG7WHoPNWvM50ndi2ZHgc23sQzby4447Lqd7Yax1nPRVLxLGWqOiQP4JkGDTSVvYHPI9dgSUJS07pde0Y3QB8sRU6n3j5lDvpbHWSdlOrjtv4WJZ3lgq7Vta7aatkFapLm2U6nI43bYWpQTIl+3kujz7bLK4DGvSOXSfh7jkUVFzqPPY0efB3iiKmkPbpqwf3eRzE1DxHmLDh03DoUOHpgo5CPpbwkYljTXOveJaUVqUH3dB/723gLdAXhbw4DYvs/mTvAU+HxYoJHCL8wtgA3QCPnFmkPAC9HBeAJKwlDhrZAoOagADjuFYMii7TUv9AAQB0XYbN2m2/PyRtwOvW1aSkQu/3Ec2agDYttG4SJ8Bnzc//4Fc8eSsHHZ31z4t8ovDR8qA/u0leJpbWuW3j8+Qv0+cnXOP8/fZTM7YY1DW0cJh4gepM/JeBfX4RZppGLCPDBjnDwYahsdt9BPJssbN2sBT45Y5h3qPdqmgJCvXzYgMeGJekH27cbp8DsiFWQZEq+TZltDSnzi5aJBzqWCEc+1MyEkYTzfxE4AqSYuLmw2rNxt0bZe1JiEZGxZPPvmkUSfQotgyTVYVxFrz3ODAw17yHIWBRRdQRbHWQTGXURmJw8CtbQt7HlwbxUlf9Xh3DNgwCFTr8VFJsLinbtYkWQ8cQ43c+QuXyIrmMmmvZN1+dmVRi3Qpa5HqivJQBhI7dhbbqWs5jSQ8irFNYoe4RGZ2aaOw69nMeZwCIuy50Gu74Qm8b/j7wnm8V5EldwRreuY2yarwx3gLFKYFPLgtzHnxvfIW6BQLFBK4xREmZhawBss4depUwy7i5MDEkll4woQJhpnYZ599AsePTBc2EnntwIG5JXQ4AQeOOrbs3MNqaVtc1yBjrn5Blq5sj5XV73pUlcp3d+kmVXXzzO48wBs2+UvbbS/XTlwgd7/cntyJc07bobdsWTxPtt56pIl/pa1saJaL7n1Dnpzenj25NFMkv/nqlnLIyA1zxqIgH9AJKNRyIByEEw9bCrjEQVM2Lm4xMG6AJ4wWzIWd8AfQyZj4wS5xDh9zQsZRnETYXgBr0DncQ+OC+Z75A0QryKJP+cRVMla7RIztBEcBT2V16YvtRMNiuzHGSeypZW500yGozFBQwia9dpCUGXu64NbuiwJPHGtbpskxOj61L88KzwmZw0nEFtTspEdsMATNY1TsswF2TW3PTBAYiQO3NrDVeUgqfdXxBMUZx93XtoU9D/bnSTZI9J3Cs2XWc0mxLK5dJcubS2XNN4lIVVGLdKsski5VlYEZtLkeazHNBonOgW5eBc1DXHZinkPNsB3H2IY9G/YGA+Ba5zGJnJhr2s9kUuZc+6Lx5IzB/owkd4yHzb9FixZl63ajXkm7meaO24PbuLek/95boHAt4MFt4c6N75m3QIctsL7BLU6JAi0cERhJGBfAI463HdPKYMl0jCOJtDKozZs3zyRHojzQoEGDAo+BFcP5IqZR2yUPT5c7J89Z4/hBvSrlnJHFUlq/JJvEinu8/tYMuXd+d3npw/ayQOUlGfndV7eUkd2bDMCGzYQ1+3R5vZxxx1SZ9tGy7PWrilvllwcMlIN3HJ5zT+wBuNGsw4BNQCcgFwcVwI+9AM2MMY2Dxvn0C3CK8wizDbOL06dsNI61Al3Ybff6AGNk0zQ7I3LUQuS+MOqABQX79vFJ2Tk9R8FMnAw4KuurjrejMYmuDDiuzJAtf+VYdwxB4Pab3/ym3HrrrXLzzTcbqfIll1xiwCpzh+z2hBNOMHG0Ckw13jRsTlTqjB0BJOPGjZN77rnHZMvmMzaFDj74YPn+979v1oLd1KYce+2115rNprlz5xpANmDAAPNcfvvb3zb90n4H9YPvYZO5H3PB+c8884xcf/318tJLL5l61zz7APOLLrrIrPUgkERyuN/+9rfyyiuvmOuQJO7CCy80G2RRzK32yWbOVULLfXQe49ZpEDjnnMamJpm/aJkBue0FxdquhlNlQG51Rnp06ZLNquzaKamc2GbO49hO7hElJ+aezEW+kvCg0lVJ5MSa7In+pQW2nOOyzvQfoIt6wU5MBdBlXaG4iYpnTvKH1YPbJFbyx3gLFKYFPLgtzHnxvfIW6BQLFBK4xUkGvKnEFHBK3JwNsKhRi+M7ZsyYQJYJphBHFzkmQCGo4UTb0ubp82rl8OsniZUzypy2bf8aOWmzeilqXGmcfFhSnKbJb86Six9+T+bWtb8ee1aXyvXHjZJRA7uJDbCbqnrL2HFT5KMlq7Jd6de1VE4ZvFL2GLW5YT3VOcNBw7HmBwYaEAqAUSCmFwB8uHaJWww24wtoRbatMWI4x8SiKcuqTBxsDgwHY8chhA0DeHMe4AEHMUmzE0oRB811lZniO5vxjIpHxA7Klqat/6rMDhsDtj2VndPMvnHjSSNlDsv6yj3pQ9AYosAtAPZvf/ubmQvsz/p48cUXzabH2WefnU0SRTmnH/3oR4alJ76cjZH999/fPC/8AJLZOGJtHXvsseYaxEcjg2dOUQYw12zMAKLdTaLbbrtNTj/9dLPJwneoKgASZABnUwbQe/LJJxtAzkbSfffdZ4DEkUcemTUva/BnP/uZ+T8bDN/97nflT3/6k3m+SAYHUEbBQF/4/h//+IcceOCBWTYQYAEgpx/MCc8mkm7AzOTJk+W8886Tq666ao1YX3t+7VI7YbGhcZJwBU6a4dtdP6tQLyxeIctbSiQ3el9BbrNUlbZITWWFAXUdkYQnAbZu/6Ik4UmzhKeNE46SEzP/MPhxSe3ccbDhyVhc1pk5Zh3pM28//9yLvxNBIR1x7wG+9+A2iZX8Md4ChWkBD24Lc158r7wFOsUChQJucT5gFWFsccBhYIJiZkmOg1M/evToQHYBFhLmB9CIsxvUYJtwsPbee2/j9Ox/1Qvy4eL2REics9MGLXLc0CIpam021wJM0q83Pl4mY297VRbWtYsOB/eukpu+/iUZ2KPS3A5Q8eqrr0pdlwFy2YRPpXZV+7GjBnSTX4wZIO++NTULwOkDP0GJowANAAauaTeVRyvwjHIGyTQNm52E8aUPgB7uB9jVmFa9d1Cpn7iFCPgC+OBMIkvGmbSTrxgHu6FRPqhbKc1WAq9MpkiKi0ukpKTY2L6t/mur+X95ebL4WBfMKFvaloG1WZqacnk1rm3uWVxMZqOcoXH8ypVtmxQ44PYYBlaUSlmmva6xaxNlA+PKm0SBW65J5mOYSQXGzz//vHkWaDjxKsXHpgDTAw44wLC9Dz/8sDlGgTX//ta3viX33nuvAZ033HBDtnQWfQUcX3HFFWtImgGOJHNjvV555ZUGXNIX3ZjhGeZ8ffbsrMX0T2PGVUILoANsA85RAtx9992GpdX24IMPyjHHHGNUE8RLIsXnXpoRHXk+mZ+/8Y1vZM+5//77zdiwgZvISg8KK7UTtZajGE9XEu5ep27VKvl06UpZEQFye9SUSLeampxTo2T2aktOyAfYaqgCv/OVhKcFtq5dbNbZ/S6pokOl9W6MLe871gy/+VvCu4c5pNY570QS4aGuSQuktZ8e3Ma9+f333gKFawEPbgt3bnzPvAU6bIH1DW4ZALvuOMUwTrSoGrQwORwHMA2Kk8RpgYmCdcJxCWoAAhwiJJSPvDFfLvjntJzDjt68XHbrsUIAVzbIfmr6Arnwnmk59W532rSH/OmYraVbZXumTFjQax95We5+t1is5MkyZos+Rra8YtkSwy4BZJBOKqh1E0cBEkiOBRMMewXbiqOmwFOBEuBCGVbNhKwDwlaaaRqAjl3iYmr1XJxeNgs4347R5XviZ1UuDfAIu6YCEeaYc0jiEjRv79TVyx4vz+jwel5fF5iw/TDZrIoCMMHNlk0qI4Zj70ptmWMAoZ1QSuW9JFp74oknssBWFQ2HHHKIPPbYY3LLLbfIiSeemO0A5X8Avkh7yb5sx+myYULMOeuBjQ/mxp5D1iL347nkmdOa0F/5ylfk3//+t5x//vly+eWXh867snOAUMYE6CZO2wbXGuML+4tqg++DnlkY6+uuu86AaUAwzy5S5MsuuywLvl3gedJJJ5lyStyXuqYKlDBOPsDWnlU7NpS55N62GiCK8VxeVycLl9XLitaSNZQiOFvVRc3So6ZUutasmSAuSmafT5ZwjRMOizmPkhNjT93QSKuiUFsGxdjGxQa7MexhwJa1DrBlrgG1gFv3HUX/k74Lg55qD27X19vW39dboOMW8OC24zb0V/AWKFgLrG9wC4MDGGUXHQeb31HAFAcYdhf2KEhOBpPz3HPPRQJk7sfu/e577SsHXfuizF3anoTknB26yNCSxWa+7LjdWyd+KJc9NiMnI/J+Q7rIH47bQcikbAPCyx99S26eNDdnzk/dbRO5aPQQA5hhRidOnGgkncji1Dm2E0fhlCHRBqwjGUV2aYNCHDO+A+jyo0wY10BaCvDkGsiIcT4BJ8hT0zTmAuADO4ODCDCFNYfRRRpux60q0OXeCroYF+AcgK3JqgD0QfF8X2RwGyVldgGEXeeWbMmAltNOO02QAn/ve9+TH/zgB2uUG4LJRYL7q1/9yhyjzQa3gGKAAA0ww/GwwDCcgFSaC8qInSUGlh+O49li44nrAI7ZmIlrmtiJZ5pn15WEA555lmFtWe9BDfkx8mkY3BtvvNFci0n4GAAAIABJREFU44gjjjC1e/n/qaeeusZpSKG/9rWvZUG1HqDgmt/5xFzagMyO106TBAv7weSuaMjIitbiUJDbs0uZdKmuWmNsdpwwc+YmFotjPIMY27h55Pso4KngOmkOgCTJo6JKfjFGrsExLmNrA1vKtbFmOwJiw2zjwW2SVeOP8RYoTAt4cFuY8+J75S3QKRZY3+AWRnD8+PGmri0SQljVKOYWsASzteuuu5rMvm4DiOH04tQQlxjUYE1hV98uHSLXTXg/e8hJW5TJdt3qDIgEGBJL2HuDPvLrx2bIbZNyy/ccPLBZztxzsAGn2hqaWuTH/3pLHpw6L/tZpkjkpwcPl+N2GJD9DGBNYiziCpFv4qDhpKoDZoNKxhEnnVNnVUvwcH3bmYe14F4uOxe1gOIyIuPYKdDltzrYOJqwx8wnmxAAecA5caKM8X8N3GIXO2kSwDKqsYHA+oZ11IRnZ511ltx5550mJnXs2LFryCgvvfRS+cUvfiE/+clPsnGs3EPBLeDxX//6l7mtJutR4JrkJfLzn//cxLCiIGC9MseuXD3sOja4VfDK86Vg8IEHHsiRFEf1B7CP5BgbEh9MYjMY6X333XeN09iUIXZXE1cBzFz1QdKETXrxqJJHdgeiGE8F1wrIaleskEW1jZEgt1fXMqmpagO5CmzdRGRx5am0DE++wNYen11PGBsmzYas10gCbN0JVZZYx+ky5VyTzQrepTC29JHNPJj7tQFsdS58ndskbxB/jLdA4VnAg9vCmxPfI2+BTrPA+ga3DAR5nJaiiAOmOLQkjaHGLPF3bsP5I4kOTCGyyqBGPOz02Z/Ib14vk/rVuuHNuxfJmcMbZaONNjTMJ8zU0BFbyeXPfSrPzPg0e5nS4iL58X6bSPels3LiepeubJRz7npdXnq/jfWlVZQUydXHbiN7Du2d/QynDAYMEA/QAHSSZIl/0wCoGrcI0ElbixEHHsceVteVTMI0BTGsro00IzJOIcA6rgYuDiXyZU1IZZfjAIjAUOOURoHbhpYWmb2qvUIo49D42IqKcslkinO62draYuJlm5uR9ran6tE4XZxuTR4DqxQHKoPWSX39KnMProntGGdzU7OpaWo718TpblJVKVVlpTmOtA2GkmZltmNuAaUA4zPPPNOAWxI1HX/88YYZV3YOm8aBW425teMyAcw33XSTeUZgTWl27Lc9PjIn88Mc6+ZEWnALyGBdu4mbGBdSajZg7NrVqmJQYIIt2UgigzNzSZ+Tgluk0Xa5INZDkCQ8qIavroukwDZoHYUlFrOZ8tq6Olm8vEnqwpjcTJN0ryoRNCJxWcKjGE+d13zKXzG2oBhbG8wDMqMk2vkAW9emKkXWBGk852yiYE+eM/6esMHGxsbaArb0yTO3neaG+At5C6xzC3hwu85N7m/oLbDuLFAI4FZBCE4gsYY4JrAuQY2dcn74nuPchmNHHVuYwx133DHwGoC/X4//RKYsapMTZ6RVLt6mWfbcZqgBk2Qqfv7VN+TW96tl1sJ2yXL3qlK59thtZGj3IiOlxnkaMWKEzF68Usbe/pq8+2mb7JPWrbRVfvjlHnL4Xu3jUPDAOAHYsJraYFVxOGGUcciocQtrm6bh1DE2nD9ALFJk7ME1kS67DKuW/IFV1Rg6yrPAHKbNiKz9ZEyMDSeWa+AAakwwY8RmOKBR8sWkpX70nlFMWT6lTbieZmUOq8OrzCPjC3Lm+UyZwjSlTWxwu8MOO5j5I870jjvuMGAUea7LlBF/+utf/3oN5hYpMhmGAbeaIVxtRrzqT3/6U/nOd74jv/vd7wKXmS1/5QDui7yY9UUcdpKM3QBQgCjnaUIp+2Zs8gBqeZ5RMygQdKW2nGMDMuLlGRM2ISbZbSSiIlEW6003i5hLwLXd4hhP1rCy75yXb+ImbKYSWtakmyVcs3avbGiQpXUtgSCXt1V1pkl6dinPMrlx74e4uFkF9ElAYNLkUVGxwXYog52QLW4c+r2+G+y55JqoVXjPYWfNRcD7BtUIP7p5mPQ+SY7z4DaJlfwx3gKFaQEPbgtzXnyvvAU6xQKFAG5xEjTuFJkhjCzMbFBjhx5WFclxGPjjGkiWSZgT1O58+hW5ZHw7w7rnRq3y88NHZq/3n2nvyUX/miVLGtpff4N6VcmNJ4wSfmtcL6xrS/eBpobtwhUN2VsN61MtJwxYKsMG9jHySRoOmI6R3ziTMJwAToAnrJg2ZJuwucjqYJGTOJ6cj+wTpxmHHpbLPS+MYcXZxub0h7HhwCPJdoFA3IKzk1chX1UgxPj0urDAKsF2k+AkAZVxfdDyLkHHxcUi6jzZQCSJUxyVRTdtaRMFtypLxkawrFrnlhI7NBuUAWwBuMTb/vjHPzYbFQAMwN+hhx66RsZjzmcDgs0f4mYBqm4ctM2wad1TntOjjz5aHnnkEZNQilI+UdJegAgqANh/Qg2I/3Yb1+Q5YlOE2rkax6ubA66UmPPpK4AcKTZSZTbE3EZ8LpmgWYM8F0HA1j0nDJTpcUnZd/u6jEPXk1umJgp41jc1yfL6okiQ27tbpVRVxGcNd2O+Ncsyn2uLk2gnBbauTXWMdjIzPSbJ82hfLwjY8j3zxoan1kVnPRHagXqFH/4WsGnZ2c2D2862qL+et8C6s4AHt+vO1v5O3gLr3AKFBG4ZPGwTsVPE1AY1nGWcYFhJHOaghrOLI6oxi/YxTc0tcuBVE+TDpW3leapLRf41dlsZ0Ken+f+EmZ/KuXe/npMReftNuss1x24tPara4iVxoignNLulp1zz6nJZ1djuJH55SC/5/VdHyMT/PGviTGHfFNjaiaNUUoeDhPNNgiZABGwD/1bmSkv+AHRho4PKVsA0kxGWRhIsnLu4pmwHUmJAqSYb4jycQcA1zG6SGpBcC+BCrFtQ8iq7zi1gg6a1dPk3ttDEOFzLTRATNxb93s6CCyjVayoQtJ35oIy2UYmfkvZBHXD3eGXm7Ky9Qde0wS2xpLCVmi2ZkjkKbu1zL7nkEvnlL39pJLt2QikSq4WBW86H2YThPPzww00mYl03KsEFcFJCiIRWCn4ps4VcmvEQAwyTrI3PYGexLWBCE/5oCRYyIgeFElx99dWGQYbh/fOf/2xAty0D5nqoMVSmzxohnpvjUCtcc801JhZZ1QCA2uOOO85sJiGHJk4/ySaFbVPuAaCz16mu1Sj5snuNMGAbNPfYi/cB91SGEyZ3RWOJ1LWuWWaKT2oyTdK7e5VUlgdn6rbXtFuLNy5hk2Ym5rlSBQYbXkk22+zxcR/micZ6VsAbJV927RMGbLk2wJbr834kBMJWhWisblASu6TPdNhxHtx21IL+fG+B9WcBD27Xn+39nb0F1roFCg3cUpsTR4TyJUENp1ZLhihQco+DscIBg9Vx2y3PvSu/eeLd7Mc/OWCIfH2XQeb/d06eI7945G1pbmnNfn/IyA3l14dvkZMRGaf3Z3eMlwc/yM10esx2/eUnB28uJZkik+gGRx4HHAdMgS2OlzqHrowYKbKybhrDCuupMjucfAAzQBdJNsfi2MFm828y7fJ9mgbDQakXHFhALX2D7dAGuNU4Xf3edVyRns6ZM8c4rjC+bqIvG9zaCaXCYhHTMjr0J4mUOcyZZ05UKsq1XBCQ1J52XKeCgDDZa9AYNa6UDRw7UVIcuLVjbi+++OLsxoiCW2TJlO9xmXKknABbNmq01BSsP2uBNcUmEoAL1p3vtVFyiDhg+st8oqLgHIAtmywaG8xaYk0QJ0ziKK7NphVAk3UK46xNMz7zfzauOJb+sv6R2vOsALSp26vzePvtt8sZZ5xh/k82cdQKbLKQMA4pN/3gHUGN5bRNFQCMgf7aLGsSUMYxcaV2ovrEmHjP6CZXEpC7QY9qqbASlkUB26B7h61VjlU7pK0Ja/fBZb6TgGtNXsY70GXfOZ81x/pE4cLmR9JszWnXQ9DxHtx2hhX9NbwF1o8FPLhdP3b3d/UWWCcWKARwayd3IXMyTgt1bIMaLCNgDNnrpptuGngMzjqOh5tF9f2PF8gRN0+VujbSVob2rpAHz95NeMld/sRM+esLH+Zc75itusilR+2Yw1QAfH/5yHS5Y/JHOcdetN8Q+dZu7QlMYJqo/6rgloNtYJtERsw5OMkwaJoJ2S75g+PHOAFjJAZKwrLanbYzIiMHhfUIkksr4wlQUaALS8LnxDNyHe4NsA1iyMLALX1xGTplubWfUTVD1T4aH5um3maUJFRBYFK2J6mcOqpcjIJrLQUUVOc2jLlVcKvMrTLfmi0ZBQMyZ7txjMY83nXXXTJu3DjzXLHWAAokeAIUw/zuv//+azxnzDtsLxtJZFFm/mFJ2VCibBD/1sZah11m44rnV6XzABO78dxSdojYW9Y7awnWF5vQj8MOO2yNNc4YKYEEoKURAw+wZS0CeMNifaNernF1cOPK/rBmAaasi3wTN7l90Hsuo4xQCJNLyrVBPcukorzcPJuwxvQhn80a7scYbLUDNuP9kLSmbhSwde0f9Tzqfe1kZBzP+mFzjphaNlnWJbClTx7crhMXxd/EW2CtWMCD27ViVn9Rb4HCsEChgVsSzOCUkTAmqJE0BEcWZ8Yuw2Mfi3PMbr7tlCPd/emDb8pz89vlfVd/ZVPZY6tBcvF9b8gT/12QvQTM6zGbNsmR2w3IZpLlyxX1TXLhPW/kZE+mxu1vj9hSDtqqb/Z8HC8yNuMEAm5xdm1gC8tJ3LA642Hy6iAHEDYI9hp2z3Y8kTPD6PKTpH4n59MH+oUcNCx+GSCCzTUTsso0NW6W/wOGYO/CEsSEgVs7PtZOuhTFsNpZgu14xnylzHYf3OzS2D+ORc63D1GsVVLwoOsjKq7TXkNRyZM4DkATl4k37K0VJOmmXyqzTVIuJg5Uxr0x7T64x8ZtkujxafsQBco0mZld5ituDHyvfQjbrMGWi5Yuk9qGjKy05MpVRS3Sr0eFed8ouM4H2NIHO8aWZ9MG9PYYwp6PNMA2yCZB4Jq/C7zXUYbwHiR8g3+zMbeuga0Ht0lWsj/GW6BwLeDBbeHOje+Zt0CHLVBo4HbixImGPRozZkxgbBffcQwsI/GlQW3SpEnG8eEaNGSzz7/5vlz+eomo4HjbXi3yo4OGyyVPz5NpH7XXhe1aUSJXHL65rPxgqmGvYI1on9TWyxnjpsibc2uzt6wpFbnppO1lu427Zz9T5hFJKIwiTpctJaaMkWYj5towoGmaLSPWhFMwp4xX5ZI4owp0YTXsGDmOyTcjMg4r9mejALZOG9dHgs09YXZtCSvHBIHboPjYIDuEgQfuqeN1E/UktWcYkAlj5lyAZDvw+TJ0CiLos8YIu+BBwW7QuPLtA+cp8LQ3SeISC+XbB419ZC2ozF6vpZm6OwtcK6CLk71iV1tma9dvTbJB5NrCTsLlfpcUXKdN3LRg8RKprS+SVa0Z6V3WIJWWLJl7si6TKhC0z3F9iMswzRpShUk+SbjoRxC45t3Du07LUDEuNuXYXHPfOUnfAR05zjO3HbGeP9dbYP1awIPb9Wt/f3dvgbVqgUIAtwomGCisLEzh6NGjA50ywB3sLrJHrc/pGujll182ThASSeIGP/lkgVw3vVRmLGmDtuUlRXLq0Ea5d3aFzF++WqMsIgN6VMpNJ4yS/l2Kxa63O2P+chk77jWZu7S9LFCfSpHzty2TI/dvjw1WYItTDcNAAh0YT3X0tJ841Ugmg5LrRE22XQMX5hpZtgJXHC1lVxm7KyUGdMJyEBPJcTjvsK1pMyLbUmbmgLFwPeZFG/dR+TL3YX5hiukr/VZQlUZGrNfGsYZtdUvFxDGsrl2D4mPDgFtQeRobXOfLjoX1IQo8KNDl/m5G43xq+dqAjvlIwrDadsq3D1HSXh1jUjZOS/VESXCjGFYbXOezJrFHkAw4Tr6sCZuSgsqod8PS2uVSU1WZkxjOPl7BNbaNSggVB2zdPoRtIHBcvuA6jLlmDokF1zraAFrixrEz/0aC7sb7r80/nh7crk3r+mt7C6xdC3hwu3bt66/uLbBeLVBo4Ja4P+LyiLkFNLhNMxXbrKp7jF4D4MbxM+u7yDWvrsweNmZYd5nwzmJZ2dz+ehs1oJtcd9w20qumzIAvZMUAtPrug+Tbd78uy+ubs+fD1B43cJl0LS82NTppNrDl3ziQOMr8G7AOyHbLmuCIKdtJfG5Y4xqAQxjoOBkx1zCyxUWLTDIegKfLlOULbG05tVuHF6CmccEwLDaLTPIrHF0ca2IoNTsyDHPazKt27VUFc2G1ZoMc+aTxsUFzoQCJebTZzqSZkO1rsi6Zp7A6unpsGMNqg+t82bG04NrdQLCBbUf7oM9LELh2GdYwcJ2mD2EbCDxf+YBrzTYe1od1Ca61D+sSXOt7x8667oJre2Mm7F0XJckG2KJQ4V1JSArPDnZlI5EkeChk0mbF7sgfXw9uO2I9f663wPq1gAe369f+/u7eAmvVAoUGbsmETEwp2ZKDWEWABYlpAIVaQ9Y1kLK/fN633wC54InFMndZG+vavbJEauubpLm9eo8csGUfEzdbUUpKljYWhoRQ01bUyN/eqJcmK3vywVv1NdmTJ734vJHb7rPPPtlsyAp47PhagB6lfug3pVbIAqu1bW0QyFhVSmxnJeaadjZi2Fakxkkbzh/25BoucIiSEtvX5xqalTkJ6+yyyFwLgEtcMOAWUJoPsLXjY7GXLSlVBklrJmv/VWarQDdtDVvXznYfwsqaRLHI+cbo6gYK43PHmBZcuwA/ir2PAki63u146aTrkuNsgK99iAOBaluXuU4DbO0+2lm2uaa7aREX/5wvwI+T9jLOpMx1kvhWtatbb1Y3mlQ2vj6Z6yhgSxZsNuzYmAPYppVap1mXSY/14Dappfxx3gKFZwEPbgtvTnyPvAU6zQKFAG6VnWJQ1KQkJpWSIUESM5xJauFqDVnXEJzLNWhIYB+dnZFrx78Xaq+xXx4kF+xLps32Vx2O3rl/eUL+b05ubckzdh8k5+3TdqzG1JKRmT4pU2kDW2TJ9IXxkd0ZGa/NVAKUFOjC7qpjDWMNa0w8LmwpTh1sBcA2LTPhSpm5rjKsrpRYWWQ73pCxwTrDpnNvstCmycrM+cwJ8kEFtwpK00iJbfmsnTU1aGLDHHk9Nt/kU1HJhpLE6Sqgo3/5xgm74FpBvW2HtQWuwzYQ0mTQVZCuGa7d8i7ufGJXt/Yrx/CcfdHBdZL45yTANugZWVvgOkyiH5dcTJ9Z1pIb78z7g/cjz/2wYcMKAthiUw9uO80N8RfyFljnFvDgdp2b3N/QW2DdWaDQwC0MI0mXdtppp8CYVJwgaoCSRGTnnXfOGgonj3hS5Lvq+A4cPkqOu+0tqW+yaNrVZ2SkVc7YoYecd8j2OcZuaGqRHzzwljw8rT1hUnGmSC49ZLgcvV3/7LEvvviiAWyAW5expY+UqWAcOO8kjoK5jGo48ThwKiXWrMScA0MIWwH4TMNY4BRGSZnDpMQ4kYBgmF1qhDJO2GLAddq4TkAxAB+gzmaFlm9KIyVOGh8bBnQBhK4knGO1HE4Sm6YB11FxiHrftJsUnJcEXIfZVceo5WHWNrhWKbErO+8Ic612ZS51M0mBrp1FO8nbM4g1TgMCOwNc67q2pelpmGvsQdZgWr7Mtb2uXeY6LbhOE3seJQvX8WAXNve0LBTANiwje5I57+xjPLjtbIv663kLrDsLeHC77mzt7+QtsM4tUGjgFlA4c+ZMU7cVgBXUYG4BB9TvpOHsTpkyJctwAqQAdvd/0kuefWfpGpeoLiuWkzZrkNFb9RdiR7UtrmuQc+56XV7+YEn2s+ryYrn6a1vLl4f0yn6GA/rSSy+Z+C/AGqATZlUT8ijTicMJ0xkVTxs0PphaxqMxmSon5vqMTRnWMKBJ/9JmRFYWGUfSTkhF/7A1jiUAPalUkj4gJWQucUgpd8Rv2HQFWnFSYpxbAB3HxTF8YQ+OHaPLfND/ICZQY4LpmwvIFAjlI9nEDkHgOq2UOE2inzC7qo3yBbZR4DqOCVRQorLwfPvgxlyHMddR4FpZ47QMftx6dRNERb3MbWAbJQuPAoG6qdZRYGuv67TguiO1dPXdrQmidMOAdzfvPN47XJ/3HMqXQgK29N2D23Xurvgbegt0mgU8uO00U/oLeQsUngUKAdwqAMA6JA2h/iosYVjt1WeeecaAFJI5kUzklVdeMRmJAcNkIYa9ffilGXLNW20xtHbr161Crj56hHz05mRzfe5D+3BRnZx2+xR5f2Fd9vAe5SJ/P3Vn2bxve7In+opTCSsLEFcGCQcV4AkwxSGDWaYvaZnOICkzzKlKiZWpoZPcQ+N0lQnEGZ42bZoBqPkmjuJc4oQZp81QAQABuNiZ32HOphsnDHNNfLFmSw5iSqOkxFovNAnDas91VIwux4Ula9KkQlovtCPgmvmwy6JgAwUsNvsYJSVeG8x1vuA6SR3cMLvq3KQFlXqezmdQH9KC63z7YM8nz3ZaWThjSQps3XdXZ8nCuW7SzZIk4DoNYxv0fNrzyTPBO453EO9RgC/fs0GIeoR3HvdLm4hubfzl9eB2bVjVX9NbYN1YwIPbdWNnfxdvgfVigUIDtwBTmE8YVRIwBbUJEyYYgMAxgDB2+QcPHmykuzg9773/gRw/boYsash9fW3Vr6tcf/w20r28KCcp1Wuzl8iZd0yVxXWN2dtt3KVITh/RKkcdPDr7Gc4lPzhgmoAlKGYWcETipL59+xppbxK2k+shAeYHUDVy5MhA5hrHT4EuGUK14fwBrtUp5N+AyrRsB+Aa+9OoI0xWau6DXJofrTGJnbkHQNeubctckBRMwTXMNX2wSwHFgVQbQLjzrwl+4q6RRkbMPcJiAvmO+YMdsxNYJXlYbZbRTYDF+XFxuspcK4OftmwT9/iigOso1jgIBAbV8NXj8lUB2LZ05zMOXGuCqKRy6LD1ZSew4lnQTSH7+LhY9qTANg24tu+Z5tkI2qjgHUQdbUDskCFDzGYA7yB+GC+bhkneqUn60ZFjPLjtiPX8ud4C69cCHtyuX/v7u3sLrFULFBq4xbEBsI4YMcJkFg5qJHMC5OHo4OQAcgFh2n730FS5+eUFOafuO3wDueLIraSqrDibDZmkVAurNpaL73tTiLXVttew3nLsxnXSUFcrY8aMyQGzQYmjAH2wpQBfkiYpM8P1cPoUAGpJHHdMOKzEpeLQAaJgk7lOXMPh1xhdGGPtG8479gBcw3QkYTk4V9lozseBxD524xiYcr2nm5AKsMt3OPA2uMbxTwpuXTCGAx+WVCjMie8I06mgM6ikSRq2Mw0Y455RcbrcF2a+I+A6KKNxHLjGvgAhjstHku3aErDCddIy12lt6a5ZQIhKX/W7NHPJOXEbFfY945jrzrClK0VOCq7zBbY6PmVW+a0bTHZ+AH3n2Vmt3feY2jII2PIO5G+ASpHtcnDck3lk7IXQPLgthFnwffAWyM8CHtzmZzd/lrfA58IChQZuAUevvvqqifGEjQ0CguPHjzdxjDg+MIMAOG3Eze535fNSa9WlPXnngfK9McOExFA0nKTHHntcXlxcJXe/3ZBzi+N3GCA/OnCYvPrKy0ZivN9++2XPCUocpXGlCrIBlBxHPK6CQDumDMCoMbMAN40XhpUg4RLANqi+b9RigsmFLeW+MLgaU8g53ANwzT0BnEEASZNxUTIoDbi2E1IxXm3cA9adeyIlBBwlAbe2jDisvEwUIOO+ONoqI86n3JDNjKncMgw4hIHrtKxx0BrvKLhOA8aSgGvWRRxbHjWOoLjQJOCaNcFY8gWENhhT1j8tuE5ryyBw7SbBssE16zZuA8pel3Gll+ISmgVlJE7yx8q2JeDTfk/pXLoJzexSXBrvzvMRBGx5X3700UcG2PL+LxQQG2YbD26TrBp/jLdAYVrAg9vCnBffK2+BTrFAIYBbBqIAEEBJsiaALQ6O3TgG4KtyXBJKucmaLnl4utw5eU72NIDtDw/cPOc6Tc0tcvpNT8lz89pfb0VFIt/bf6icssvGxvEijhfQuNdeexlAqPGnfKdZRcnODCDEyQOUBpUuwiEkZlZlvQpauIayvDhJgOItt9wyNTtnZ0SGweY6OJrYUcE116cFxczyHcCY4+kP40jrVNoJsJBr4rzqRgCOKuAaYOEmlHLnFgCQJKZTz4ty4rlvmgQ/XNMGMfmAa+4HcOoI08mYNEmPAoi04LojTKcCXe2DPUdp2E6bgY8DY2sLXAfZ0h5PVA1fzaTNODTuM64EVdgLWaXI9jW5rh1zzbOpmyWu5DYNsHX7oLJlxmDfj+Pi5MsuSFe1jAts3XvGgWuOd2XdvGvJjMw7gvd+PtnEO+UPYoqLeHCbwlj+UG+BArOAB7cFNiG+O94CnWmBQgG3ymwAXCmzgyQZabI2ACLAFuAEmMRZ23vvvXPYg+nzauWIGyZJS2vbWbtvUiV/+eauOeZaXt8kF/xzmkyYuTD7eXlJxkiW99+iT/YzshUjkQNA48zh2KvTSV+RTpMkKS0gRNaLIwcottk5gLEmh0pSRxZHlTI/MKL0DxmxzWDrQDiOfirQ1eRGjAdWlT4wHiTTxPmmZefsGN0tttjCyKG1rBHj5If/c31sBaOrEltlqzoqI7ZBDNe0nfikgCwu+VTQMxflxCuYTyMltkFMWAbcOLZTv0+zSeCCGDujMc+afU8XkCkbajOPSTYJot5h3EP74B6XFJDZayJJwqM4QJZvRmIb2LqALQ5c2+WbsEOSTYIgu9pSZGwRxFxHgWt7PuKAbRC4Zpw8X5r1nWMAylpijP/zPmS8ZEX+PABb+uzBbWd6Iv5a3gLr1gIe3K5be/u7eQusUwsUGrgF/BFTCwjSMj2ATJXdkjSKYwBVe+yxh2EAaDhgJ97yikxeXcanNNMq1x28oeyx/cisPecvWyVjx02R6fOWZz/rWV0q1x83SkYN7JZiH+eaAAAgAElEQVT9DEf3jTfeMA4XzpyCTpJDAcRee+0185vP6WMaAMNNYCjICE2fydgMULdlvYBblRIDel3JopsRGWl2EofQjpnFpja4BuiqXDopuNYYXZxSkle5MbqMFVvC7AJycaxJtKX2Ukacftm1PtM8AEEyYs5XB15Za71mEDjqKNNpO//5guu0TKfaVsdpAwe+ywdcxzGdXDcOkHGM1hQOSqKVZG7tpEusazuGNQnbmRbYBgEyAKEbS8pxScG1vSaSZGZWhpX16s4l900LKnVMUTG2YYBeN4RYQ2zo6UZDvn1w4+i5L+8f3gt2YwOMH94/cTLtJOtobR/jwe3atrC/vrfA2rOAB7drz7b+yt4C690ChQZuccaeffZZA/pgI2fNmmVK7gB+AFDIbkm+hBx31113zUqBH3ljvmFktR00sFm+uVM/w0bSYHUBtvOX1WeP6VspMm7srjKwZztAxslUwAR4I+uvOrk2GNt4442NfC6NE8a17fqzjA/ArIBAsyDj9KmsF0Co4BpmVmN0SeaUb0ZkOwEWIBonDXZXG86lAt0gcE3fAOfEx2ncc1QCLDuhFHWB1ZHXMXJfLb+jWWWTPBhuDduwzNBh8YDMJ31RyTlgLM18KsBUCa9duzWNlNgeB7Jw4rjtpmtgp512kjPPPNOUwHKbAkL386TMdT6AENtpVmIXkDGPgKG0Gz9x2YTDkjVpbCe/NaN3vmyru9lhA88wcK0lv1RurIAwCbCdOHGi7L777nLRRRfJr3/9azOF9OFvf/ubnH322XLcccfJddddZz5XhpW1FrdW0ySP0jHqunXXUb6bT1EZpnkPLVy40Kwh5lVti814t/GOXReNuaL+NhuqhMTE2VX75MHtupgdfw9vgbVjAQ9u145d/VW9BQrCAoUCbtXB4fdTTz1ldvBxqObPn29iQLfbbrtsBmHkuABPnH3DpjY0y4HXvCBzl7YB137dyuWCzVfIxv3b6thOmPmpnPePaVLX0Jy1+eY9MnLKkEY54uD9jTODY6VAx04cxWewqpTosQEgfdPkUFE1X/WGNtsKiIJtDSvtwrE4fTh/NrjG6aNv/CD/RbadpiQGY2FTAIDNeQB/QGwScA0IxtbcGxad/hHvzDjiYnTdbMnYG+ZbGVvub4MjBSpRMbP5yIgVjAaVickHXNNnHUeU9DUKXOvYNSMyGyaA2/333z9b55n1h0weCTrtiiuukPPPP9/8GxtqAjG7xE0acB3Gfqd5QSkgDDonCduZlunUsdvjtO+NLTTuOp9xhCVdCmM7dZMKQIktOM7e7AjrA+PeZZddzCbezJkzzTOm83HHHXcYcHviiSfKDTfckE2WpteKek7SANugvtmg1LVrWGywe50oYMuapqY584QaB4YemTJhKbxn2VQLSiiYZi7THHvNNdfIt7/9bbOhcPLJJ5sNEvqCfBrwqxsm9AngTcsT3J4gImeKyNbsVbDvKiK3iMj1CF3S9Nkf6y3gLZC/BTy4zd92/kxvgYK3QKGBW5zC//u//zNOD04ezp6bQRhHkJ/tt9/egOCrn35Hrh3/XtbWfzxqC8l89LqR9s5q7SuX/vttadZAXBE5bOsN5fB+K6R26WIDIjRBlAJHnEY7cRRgEGCBU6d1FwGedvwqDo+ynW62YxwjwAlsK+OBsU1af1ZlvYBSAKXt2DJ27pkEXLsxutgUKXKYYxsGrjkep5XxMo4kMbo2uCWWWqXCNiAMY46CmMeOZiO2gZTOtQ2uuafGkoYxj67UMs18cq5u5rhAhbhlwO2TTz5pkplp4/gLLrjAgBxAG2uyf//+WcloFEMYFaerGWy5T75Mpz0fKinlnrqJEMR22syjPR9JAGEaMMaxScA1x6UFhPaaVeWChhewhljf3DuKCbzzzjsNeP3Rj34kl156aU5dYjZwUHPwnCLnp4XJl+3nRNdXRzJM23HXrLcg+XuUKiAK2AJe2Zykf2zmuEkBVT2T5N3SWX9gsTXvJvpE35BN8453W0fALRsVqxn4VZ+lhHgKfCwi+4oIdd/uF5GjPMDtrBn11/EWiLaAB7d+hXgLfIEtUGjgFudw0qRJxuLIxHD2777ibKl/77/S2qeXDO03XJqLymVZfYNsuPFm0tprUzn16WZpaG7LIrXzpj3kryeOksf/7wl5akGVPPxObqmfs/bcVM7de7BJToXjuM8++2SzIeNU2YmjcM6pXwvQw2kHENoxvlrzFSeIf2tDPqxSYq5BjC7OUz5sK9fUjMj0DecKxzEIXGucrguu843R5d6Aa+YECTIsug3GbOZaZZlhwENZR+TmKnGMcl7DYmaVZc/XcbfltzaQSgOuO5owCRtpEi1dbwqukd5jq0ceeUT23XffHFkv57CG2CS56aab5Gtf+5oBO2kAYVScZRygD5rbJIAwSkqs5ZvSjsPuS1C8clRssI7TVj0kGUfUnwFdy3bsvB4flaxp5513NpnZYW153+mGWdLkUWEMPffmPZBEvmyPK26jIUq+rJsIqszguu44YEMBjxwDY5uknve6+vN78cUXG1XE7bffbjY9YeB53/PDhhPPXb7g9t5775WjjgK7yjwR2UNEZq4eV18ReUZEyJ6IHOOqdTVefx9vgf9lC3hw+788+37sX3gLFBK4xaknkZM6ugBPnKB7zttZtn2WzW6RT7u3yrJBTTKw3wrZskudnNN4njzaspP5rlia5f7Sn8qAok/l+03fkv9r2SE7f3x3UdE9sl/mNWlqLW774YxWvimRZv5dxE+JtBSVSktRiTS0FpnPi0orpKKmu5RUVEt5j77Sc/BI6bv5l6S0oi1WlwbToeV+tFSRvXiIH8OZSyMjBhQoawx4tNlWbKTgGpCO46VNk0MBsHGsAdcdidEF3JMdGsCAA841uadd1kgBPQDbTW4FGCRumjEAzmBq0sRiKgvoJofiGkHZesMeWltGHJccJww0MH8qW++shEnK7HFPmCw2Mx566CGTqZtmM48Khn76058aJtceB2viH//4h9xyyy3ZOSdGHUf9Bz/4gQwaNChrGhugk5wNWSbhADyD2BWmEOb4rLPOyiZ205PffPNNufzyy+WZZ54x64D53HHHHY2E9sADD8wxP3HxxDHed999cthhhwUyjz/5yU/M/c8991z53e9+l6MGePzxx+X666831wA4sqFCzPH3v/99I6u3x8HzR7ZdGDhCF6666ioZN26cUXmwThibbiK8/PLL5rrEuzIGZLCM4bvf/a6Jfw1qbHRdcsklMmHCBAN8uNcZZ5wh3/zmN7NKDGSsgErdRAhj6JlTNtiQJDMexukC27///e9y6qmnykknnSR//etfs10iJ8Ho0aNNQj02QS677DK5++67zQYU8/31r3/drA3mkeR1v/3tb83cEsvPOwgQd8IJqGNzG3GngDiedbUfIQjYjrXAdYiZZ2xXX321kfDyXANQmVvWpA1WGSPr57bbbpObb75ZjjjiCBPewXpHAcOxsNX8/OxnPzO21ca/9XPizLn2v//9bzNXvEOOOeYYc3xYSAQbpH/84x9NckLWBe9EbM386nPljp+/Pawp1uzzzz+f8zX26Ai4RWXEJoaInCwitzr3Joj+2dXAt79nb8Pe4P5zb4HOs4AHt51nS38lb4GCs0AhgFucchwLHB9NKIQDRKkf2uOHbStDP1gzHOn5gZvJL7cjfKmtnVL8mJxbcr+c1vAdeaW1vbZtF1khN5ReKbsVv9lp9m9pLZKVUiErWypkZWu5rGopk5WtFbKqtULqiypkVRG/K6WxvKs0V/US6TlAajbcTDbq39+wukGJmuzOpWVbcYwVXNuxwcp0Ajpx3NKASvqDw0w9Xxp1eFUeyf+1rBH3JV5OG06rMtcAXc4HVPA5DnQUyxs0QTabRP+V7bMTUkWxY1wzXxkx5yoLqFmAtY9x93TH4o4jKOZaAQbSfJxsTVCk1yL2nOfkT3/6kwE+aktA1PHHHy/333+/2VzgOIAOQJTkX8jhH330USPl13hl1gbOP+cxf4AGzuNz4iF5JgFCP/7xj7MA++GHH5Zjjz3WgLvhw4cb4IuE84UXXjCg54c//KH8/Oc/zw79xhtvNKD3K1/5isBeaVMGnfGxrlAFAChQatB4D3zve98zMk7+Tb/ZWAFMsVkDqEHSq9JtbAl4BTSxkYRkHsAIUEW2z4bBf/7zHwOuYefoJ43jAMNkRl8NPuTaa6+V0047LWf6xo8fL4cccogBoIBaNprYFMB+AFxN+KTJ5+yTw9jOX/7yl/L73//eADuNobY3TOLALRsdrEES7AHY2GyijBq/x44dazYL2CBkPWy77bamv4B5GhsgyKG10UfWHnaiL4DX3XbbzawhNgJYD8jgAeQAVtYSoJy5wa68cwDc//znP3Ps9o1vfEMeeOABM076wrPEHOn7zwaxQeCWjQPmkf7xPLBOsTljPPTQQ+Vf//rXGq8M7sW6pTFuADkgnw0SGtJ+d371IihLeJ+xHnlnausIuOXeAwcONM9qQ0MDO6IrA95zFGcH2O4mIi8EvQf9Z94C3gKdZwEPbjvPlv5K3gIFZ4FCAbc4rDCEOCPEpyITxFlasXy5PDV2Txk8s1mqLIVxc1FGztnrAnm/W1ssWpeGFXLGx9fLbRufKPMyKL3aWn9ZILeU/U6GZT5a77Zvbs2sBsTlBgivbCmXVQBjAHGmQhpLakQqukuma2+pba2QxpqNpNfGm8uXtt8ucYwugwS8IP3D2bfjHQEEdublqFhAzgNE6YYDIEATqQQZkvnSbM8wbHpfZaq5r4LbIDlyQ1OLfLRkTZ8PELRyJax9m/zWBsaGHWtuluampiybSt80FlCBcGNjkzQ0tCUb0zjItIuB8bWxfsTjlqwBOgf0qJTK8jLTxyB2Pk7uqf1RcGvH3KqsFxYNEMO4ABk4zNiSexKzCZsKmIMpAwhqA6ydd955BrxwHtfDRiQrIyEYjBQsGWBS54axauwhc0/D4YfdBGAAzABPCtBhE2HvAB0wbGPGjDHnAHroC9djPQI0bWk47O9Xv/pVA6oByBovCtN34YUXGgCNTBTQqxtfDz74oGHuCBXgXQEoxyYAMIATDYDLBoH+X20BKAMUcQ7XZfz6HAAMkXoz14BAErZxTwXybPRgI8aum0YAL85RFUMQuHXXmqoCkJ3DMDIeWFhNaqZS4jhwy3UBoLD1zAPnI2+GocTegPD99tvPrAsF2LDVAD8AH2tBk7axOcJGBXMEGMZOynBij4MOOsgw1hzDsdgWsEsDELP5ADPM3KucnnECoO+55x4D4Nkc4B0E+47Sg3/HMbdc/1vf+pbZcNBnn80y1qGWjcMG9vzSV+YXtQBJB7WxecJ3bFCwcYNKwm2wy4BxmHDmVVtHwC0qDJ4N1tprr70W5lMTc3v4Z+Kkc0Tk2rTvJ3+8t4C3QDoLeHCbzl7+aG+Bz5UFCgHcYjAAGT84djiWOMU4yDiRjavqZPqrz8lTj90svT6YJyPfXibPbrirXL/NEVlbf3Xms/LEJjtIbVl19rN+LR/LRUX3yoCiFVJchMC4qU2AXNQiJfybz8y/+d0sJUX6fZtQue2Y9ZvAEvl0nWGIy6WupVKWt1RJrXSRVSXdpLXrRtJl0FayyU4HSpfeG2bHrXV0+QBwgAOrmZdVlomdNUYX0GozuoAP2CCYHhxQnDI36UvUIsf5hQmDZeN+ON2AGsAtgIxrugD3vU9XyOg//udz9ezYnX1w7LaySc9K85GCa2ys5aO0XFCcHDoI3LJZgGNOqRhs+oc//MGwtjqXfA/7yb1w/G12XfuIc42ElQy8OPgAQ8AjDB1OPJ+HNZXY/upXvxJ+AAyPPfaYGacdp4v0GSAFuAH0aUMCC1hAJgrrp0CQdaDgBwkxDC+NcSGhZv3BtiGl1aYJwL7zne/IX/7yF3NNstzSbHALwKeEjtsAfpMnTzYsssbbK0BnnMrq0hdALA3wePrpp5t4S+zrzimSWZh0WhJwq32CvcQWOmf2RhTjhJmGFQ6TJXMM9mHN2DHobBbAaGJDnmN7Q4j+AfwAogA8Baj0SeO9ke4idc5Z3w8+KEceeaT5iHWE1F0b88VGByw9EnOArDb6ztr6xS9+YbIQc3/CNvjNRhNML9+FyZJ5XwAs3VAH1hFAHXCM/bWxNrEJfXQl8hzD/ALuWT8wvG5jk4ixI3vXskwc0xFwyzPG5tLhhx8OcA7zqYm1PfezfVo6dVHow+i/8BbwFugUC3hw2ylm9BfxFihMCxQKuFXpJ1bC+YTFhXUIktFOnvq6nHrfbKmXcmPUPnWLZFF5V2kqLskaeee5b8j3Xr5DMkUN8vpmNTJ7sw1lm92OlD3HHGVYDDdxFAyQLeflQjiM3bvUSLeyIilpXSUNiz+R5Z/MlvqFc6S1brGUNCyXspY6KW9dJRWZVVJZVC+VmXqpLOLfq6S8iGSYa7+1torUSrXUNldLbUu1LGupluVSI02VvaWq/zDZ6Et7yUYjdjCMGXZVhlVjWLGxZl4mNg2HGOcXMAqwdRNUxY0IJhAmHsYL5xlJLAAMMAPw0jlV1pHfn3dw++QFu8vA7uXZDMFBNooDtpyj4DbofOYBFkyddmXjAGrEWQI4AJE0BZ26iYCjDvDAqSd2kvUPIMZpB6iikohq3ItjkOfirCM3tYEc14Pp1dJQABidZ4DuwQcfbKS8MLU01gLMG6wu12ZDRpUByIMBKfSP+M8gWS/sGn04+uijDVPNOG1wyxp0ARFMNbJTQCWKBObDlYbz7gEAI/mlr4xR40bZDMCGKotnHMwJzwvMJS0puMU+MJg07aubCVlLAQHS//znP2el4RpzC3jlOXOTqwHeAP2nnHKK2QBwG7bFxsiJAbTK5BO2AHOL9BzW1o71Bggzf6wr5k3nlnOJMybBGaw2cmiVaAPc2diAuQT8s2GgjDfncB0kwlExtwBiYnvdpoCRTQeuQWN+2bBjfnl/Bf7tmDzZsL7MMUoBtwF42URibdlxzh0Bt4BlQDO2GDduXJhP/avP9njRyt8kIqfHvWP9994C3gIds4AHtx2znz/bW6CgLVCI4BaHDQkkzEpQfOaP7ntd7pm6ZpkGNfRX3pkgp017SIqlLYOytqaMyJubVsl7Q/rKpqP2lcOOOdNIELVMD1I5nD0+07iroHI/SGztfgHccMIBi8ghkbvhxC2bP0fmv/2K1M6ZIfWLPhapWyLFDbUGEFcYAFwvFTmAuF7K1hIgXtVaJstaagz45Qfwu7KkuwHA9d0HSnPvIVJS3sY80mBqcWZdgBC3mAHPyGdx8pGE4oCrJBWbaFIjbGUzVbOX1MuhN7wcd/mC/R5wu2nvdtUAY0aJ4IKduLI0Cm61zi3na0wr65K1hzzUltvCRsE0JWnEMAJEdI65JqDQljG711EZMaCABGc2GLYTb7GZweYFxwMe+TfjZZ6RwSLrJV4SIMjnGo8L0wg7qg0AT1xvkkbMLXHGNK6PbBYboRxwmwLXJNfFvsQq02C6keEijSU+2W6MA5CmbHkScMsx2AepNeAYoBfUAFeARcCtAkaOQz5NnwBozAUA3Q4xACzChmp5IffavFdZQ0iIiWPVbNu69nh+YUztprblczYxaLa8HAaWvirLzHsTiTSbAdyHsQAY3RYXc8v5dgy3ng/g5Xo2+GV+WaNJGvNL/9zGJgLjQJ6MrFmbB7dJrOqP8Rb4/FjAg9vPz1z5nnoLpLZAIYJbnCucU+LQXGZl+rxaOeKGSWKVrc2OmZfVHuVvyDZzH5ctpn8qm3wSzpwiNn5743KZOayPlG44XHYfc6KJsbPjJXHKcTwB2kHlfki2goNHNlYaEuAokBA0OW5G5E36dpNl774hSz6cLo3LPpHS+mVS3rLKgOHqopXSJbNCuhavkK5Fy6W0qCn1fIedQDxwbWsb62sY4NY2AFxf3lPKNtpcRhxwvPTs0y/yfswZLBbNTj6FMw8jhAOOA61sol0ipr6xST5e2hYXqy2f+FjmDMDGtZlLGELb8bdL4bgy0OKSEikpLja3D4vzDTNA/+6VUlaSyX5tZ/FlHMrKxSXBsmXJsIdch/7D9BGzSMbeHXbYwbBOOi6YWIAMMZYaY8j9uJd9PzoHmEHSzBzA0gNCosCtDWDoD04+TCzSY7dxLa6pa1oT8tBPABdsIvJMlYMSK0nMKSwsY9MG+wzLBeuv92GzQMdi145lI4nMwKwxxkF8MAAMptEu+YM9YJ1hn+kjCa6iGqwqEmuaglvAOLG+XAtWUG3M3OimDWylxgYHXV8Tm3GcSoL5d9Amnh1zC+jSjQSAKXHD2A/5rVvaSMGtKxHW/ii4hVFlc0A3sHTt8T7TTSm9p2tbxq/KD54xWGbN7AwQBzhyLhsvzCcJrGCS3YakOEqW7MqV9fwgcEs4C4Cf+UUCHNVQqtA3tylzyyYQcd/aOgJuvSw5cir8l94C68UCHtyuF7P7m3oLrBsLFAq4VaDDqMnwChjCebNLS+BMnnjLKzL5gyVrGKeiNCO/P2orGT28j/kO9vc/j/9dZP4s2fztT2ToR7n1bt0LvNOvTKYP6y2lm24hJ5/+i0BnM6rcD3FsOITEMiZtOH8Aea2ji6TTZUrD7llVUSHltR9J/Zy3pHHBe1LVtEy6FC034LcL4DezwoDhzmqA38WtXWVRU1dZ0tJNlpf2lswGQ2TgbofKhsO3N8ACpxjH3k0+FQZu7b61JY5auQYYA6CqfDmujJKdtIlz4lhnG+hq/KrdpyQy4iD7ajZivnPLBYXdU8cJm0c5FkALjrotOYVJZI0AKgA+Ws4FYAFjRkykypLdzMzYg3mwxwnLBQgheRAhAG7jWI2PBaADQJ9++mkjAyXJj9tgdek/YAdZKE1L4bA2AOWwqtyTMaKSQCbM2rFjsIkvJhMvDC+AJWkNWthQwC7qCZQU2nQTAPaRTReADWx40kZmXcAZclU2EbCFglHmE4kvc0XTOrdu3LXagrHoukCGzeYZ77qgOOmghFKcj1wacIt0GIBqjxM7IkEnNjoM3AJoYdDd2FkX3Nr2CbMtxwB0WYPEB7MmsRNrjXnAXkijkSWfcw65knIbzOutt94aWQrIzqKsZweBW+aXzUXml9CLfBpZtLFfZ8bcEv/MZkpMQiloYpJIEEB+TT599+d4C3gLJLeAB7fJbeWP9Bb43FmgEMEtu+RI32ChiNfU9sgb8+WCf05bw8a9a8rk+uO3ka37dzPf4dgDGklIg4OF4/jofTfJJ/99QTabOV9GfLBKMrmK5ZxrzuldLNM27yHLNuknhxx+kWwxZMuc73H6uT4xXnbdUw4C3GpGYoB5WEZinFQAOJJGWCLi3WBgolpYRmLOIc4M5g7WQu+5eM478uFLj0vdnOmSqZ0vlS3LpKaoVrpm6toY4KLlJqFWR1tta5Usbu4mi5q7yjLpLo1dBkj34TvJkL2ONLWA48At8wWwxa44yoAjrW1rgzE3gZHdb5thVJllmnHRB2S1bi3dIJASdV2uAbjlPM1gG3Z8UCypJvUBtKhywV5DxMzCBAFE2AQCzKAs0I0VQCRrANDE9V1b2PcEhMBGIgtGNmpLpm1gy3xwHRIsATTYdIIFdRvAgDq1mlDKBvmAQRhDmFoSJZH0ByY3qLYtcwBIIQYe4EipHjeuNMimGnPL8djBlkzr8fQddQHss9bRjlsnCjJJKMVz79ZWJQETSb5orGO9r33doPrICjLDmHAX3CrIB/yz0cD6oH6tO87f/OY3Jq6aBF8wozbTzWYFMdtcw87ITV+jwK1tW42D1jERMwyART4MiKN0FOw570E+Y80Qb0stY7thK9QuZFuOqnObFNxybZ4f1A1sAGiZqLj5tb+H8SV7NTJ54rm1dYS5ZfOCv0MxpYBmiwgpzilunVtkN80A/LHeAt4CiSzgwW0iM/mDvAU+nxYoRHCLY8oPzA278MZpbGiW0Vc9J58uz5UaD9mgWm48YZRQioWmUkGtz6rSU4AGMknA5JSJj8qyOa/Jpu98Ilu9s0JKIvDdgq4iU4bXyNzBvWXgiNFy5F5fN84x5VCI0dUyKQBdQAaMlcontfQO8mUbdHIuwBbnH2kiDl4cK+muLsanEmBN0sIxsEp2uZ+w62KX6W9Ok/cnPi4lSz6U6qalUtG4RGqkVmpgfwG/mRUmLjjf1thaIotausmi4n6yfLeLpLLPIOnfp5dUd+8lxWVtycCSsK1aHsZNYKRgTEGFjj9tHV3Os2XEyvjyWVDMrMpAXbso+EgCbINsyv1gHnGGAbdaisUGnawzjlFAoVJPBb2cA9Aiw7DNPAN2YZAAdKxHGuwp65dnAhAE0LST8JDkibWqUmfYTqT73NvOUsy1VCrLfUhIxH0A+rYtAECwewAgaqeyht3atjpWmD7GxLOBzJUSRzbI59kBFDJOjqHZAIys0i57zbMAcIFdRGnBPWCsVRnA9QH1AHfeF8iw+T82p1QR4wfAI/vVvsCAkixL42bt9aIbNHxmS+C1PrJmn+Z6MJxus8EtNmB9MAZiS5FXA25h0u3GPbkeSYxI8KSx2JrhmX7A+tLvfMAtoBWAb7PX9IvMxcwXoBugyve8H3lHHXDAAWbzjQ0NNuD0eT3zzDONAoHWWeCW+QWg8l5lw8bO6sx93Pl1bc6zAevbmXVuuQfrh9JLInKyiNzq3HdPEXlWRJATUF+p4zuO+b60/XneAv8jFvDg9n9kov0w/zctUCjgFqcLh1WdVCSYJDRCtkj7/n1vyv1T5+ZM0oieGbl17O7StbKN8bTjDPXfOKZaBkdBJ44pzi2M7huvPiuvPHuXDHh3voycVSsVEQmOl1WKvDKsVN4b1l2k72Zy1B5nyMghI3P6hCNr31OZR4AG4BqnD1aa/uGYwzKFsbtBK5LzVAKMwwpTAbuNtJlx4pipgx1W7gc7wPrhrAPkkMuFyannTX9NZk96RJrmTpfqxk+lR9ES6b1RZb0AACAASURBVFG8THpmlppSSklaY1k3mbXTb0Q22FyG9CiS0uIiaWrNUIBJKHXE79ZMqZRWd5Xy6m7U0gm9rM1S2YCBExgv9k1jT86z2Vbs4WZZDQMpNugE2NK3JAxj2LzCqmmtURIYwTK6ibfoG7GgxCnCJAIe6AfHaVkdXRcwcdiC9QIgYZzEoioYpB9IkklYBMAFEOCE0wC+MGBk3gV46VgBrhzPtVAbIPMl1hqwxLoC/HF8EHsNUOYemqTNrm2L7dz4YK6jiZRY54yX5whQTBI4BdKAJ31vkChImVvsyTVd9hrwD6vJvHI8P6x/nh/GDGNM8iik1yrLRh5NkiHmGfvxbkIZQsZhShFRyojmbobYmyb0w44dZk6QXwPcAZruulNwCxiH9dS1pbHDQeCWPmjMLQwq8+HK0QGgbCqwxtiE0BbF3PLO4n2lpXnsDSTmmvhVNkhgOwGV2JBYZOYaWzM+NgwYK2uJzQ3Gw9wh+e4scMtYmF/YdGzNRhCAmgR5vO/YVKRvgHE2WuzG3LPOiEvHPnZLwtwyfpKbsU7sMkJchyRpq5lgAOzuItKWqEGEOBpSiG/xWVno80WkbSH55i3gLbBWLeDB7Vo1r7+4t8D6tUAhgluYK8AXzrMmXfn7ix/Ibx6fmU0ktUtfkRNHlMi+e+9lDKjJc9RB1nqYfIfjjlODYwqbisPpgk7YznmzZ8jTD9woG3wwV0bOWCRdVoVrl1eWiUwZnJG3RlRL3cA+smXf0XLCvqfkxOpyD5hcBZ225BVWAyccSXJQyYqgVcHYqIkJmADEAUrtmGS1A3F/3JMf3TDgHtyLH87H8YRNxklPy3QCKiZPfF5WzpgoVcs+kJqGhdJNFhvQ26N4qdQ4sb5B4DZs1be0FkmTFEtza1tV4taScimr6SGllWvGMisoda/FWJVdjQO6adlWLVkVBMa4VxA4jnvCbUk1TCoyTZtVsxNv8W/WM8CQ+QX8AcKUpQSsEv+InJdNFtYHmzioIKh1S3IkV/4OcIGJhQmFrWU9IAsGPJEkyK0zi6N/5ZVXCiVp2EzhHsTTIj0FLGkSLACja3+te4pN7Nq2unaxK/OqDZAB+EHOzHixL+MBhMBAMibdmAmSzobFTSOtBcACFAHLAC5YO8AQgIvr8ozSVJbNOUhkAbT0kWPJrEs5Go0ZtsGtDWzpo6oobGk49gLoAdZ5H9gbJgpu2UwgzlmzImspoDhwqzG3AHStN62AEruqOkDvCWhnU0MTSukc0F82UVibyGuJv9XGGImhBrwhQXZL92AnfgB7d911l7E1ahyk0TDXcaWA0iSUsp8z5gpmHlvp/LJuUB6wbpDia+kpPQ+ZPgmlbr/9dsP+8hxq03wAdpI77KLrmw0SYrOZs7DyRVqb97O9WgKvn0QwIiJkZusqIg+IyFGQy3HvC/+9t4C3QMct4MFtx23or+AtULAWKERwC/iC1SA5Dc6UtmkfLZUT/vqKHLVtP9mzZr5x2Pbee+8cxpZjbWCLg8+OPE4n5UhgJ3BKAJ1Iz3DOFXTi5MGuAnTLi1rknusvk7I578uWb38ivWrDKd3GYpFpmxTJa8NLZeGQrtKncgs5fLuTZZsho0zXASQw0ThZ9M3ONMr/tcYsv8PibukjNtH6s4BSN/bPXWSMExCrQFcZM47D6cceMONpwC2sB444/VF72gCGe8566Sn5eNKjUrJ0tnRrXSzdKlul4cvnSUnvITKkZxtzm7bB9AJ2YXpbMmUipZXSXFwumeJiA3jog8qXbQYQ+7rZZG2HtSNsK+sPm7oMcpokWDawTZLAinupXHptJMEKklQHxQZjQ41HVnCUNPFT2Ny7sdfMmxu/6t7TvVZae9rnc38t4eTaNq6Ek9sPBbZxEnXNDI2EGIbTXksabsDvoI2CJM+QAls3wVqYAkIl05rx2ZZ2u+tTgS3glfcIG5Fxm0lJ+rw+jmETUGO72exhTGzixDXdWEkCblc/MyeIyNkiguSH1OzUm/qriFzv5chx1vbfewt0ngXSeyGdd29/JW8Bb4G1bIFCAbcMUxkbwBjxSTAjSBHttqSuUbpXlRrZGI4bzIdKkG1gy2cwwDgogA2AclBGUpxhAJsCQO2DMp04ufM//kgWvzJeGubNls1nfST9FoZnIW4pEpk+QGTysIy8P7xCulb1l00yo2RYl5HSs0dPw5QCSpFoJq2lC4ACUMLYAYBhtO3sskmWCGOEvcapBTS4LLLG6UZlGGYzAFkrtk1a9khLKTFXhnXr0UVKipqkuLVZShAkF7X9zhRFZPgKGSAsb+NqwNtcVCpFZVVS0a2XFGXaypS4ckwFndiOedYEVgqOk9hRj3ETWMHoBCUwikpI5WYjTrPJQD+Yh6gkWHZMctTY0iTB4jo6Tjf5lgLeuERaQX2Ji70OA2M26NRr8NuOCU0zr/ac6HwEScP1vkEx7UmBrc4hMljYT36ITWWsqrjQvkdt0oSNLwzYuse7ygD7ntiSHxfY0kf6y4YGjDdM/+cV2DJeZN/Iy8nCDPOapDHPWgYOcBuXEHD18+F96iTG9cd4C6xlC/gHcS0b2F/eW2B9WqAQwS3xoyRNgWW1JZG2nYiBA7ApuFW2FgcLZw1QqxJL5HQqMYyytc10AuS0bAfnENcKOO7erZu8+o+/y3uvTpaN358tm368Zlki+x7v9m0DulM3z0hFr24yoHWEHDbqRNlu+PbmMO4JaFVwzb+1cU+cXZhszSBL/Fja5FMaS4hdOB82PKzEEBJTBbo2W4RckVIvgH7AtdYwTbJ2NVsyx8LwuDJs5qyoqV5aG1ZKpqVBMq1NJp63BIFyStDb2iqG4W00sbxtsubiqm7SmmkrhWM37stGQ9qNgiTsYFASLO5tJ6NSJl1lr0lsaR/jlhyyGVabAYxiHW1Zdj7sIOPkGi57rQwg440DPTawTZLpOkoajn2SMOBBtmYsOidseNjrQks4aWkjGwCqfVWRgT3iGFv7/kiuSQSGLBb5rj0nGqfrZg3XJFhhIQ0KbPnerRUe9w7UteveE9sQu0qfAHX8n/cA75O4OU67ttfl8diKvzUAdJJeJR2LB7frcpb8vbwFOtcCHtx2rj391bwFCsoChQRucdYVYL744otGJkaMlNs4hjg1QDBMJswBTpYykirfxRGDKY2rd+peH6cNlhPWUVk9TSyD4wPoVAD4xiP3yvRnxkvv2XNk2IfzIksMze0h8tKwInlpWEbqBpbIRs19ZOPMVnLETifJsI2HmW6EgU6YKC2vkaaWLnFjyl4DSum328JKDOEUczz2AOwDGojzBXCnaTCDOMPYkkReen4c0wmIb1i+RJrqlkmmxXC0baA3YSIru4/Imc0PVykC9FYYaXNRJmMOU7AQB3TzYVvDElIp2M0nCZYC2zAQFQYAbdkp19AMvBrPmWZedb0qA844dKyuNFzt627MpAW2bv+UdXSZTuyiGwlJYtqjgG3Q+ydo7drHufWNk9o1TNodJg3XtasAm3FrOaK0wFb7aM8J12DOWCfE2mJv5plnmg1DTVqWdHxfpOM8uP0izaYfy/+aBTy4/V+bcT/e/ykLFCK4hb0k+yo76WSPtZsmjgJsKXvA9zh1OFsA0v9n7zzA7KiqB37e7r63mx4IBEJLQgelKoRepAqCIChdBEWlCCIgAupfQURQ6dIURESKICAC0qsgQuhINSQQQhIICenb9//97uYsdyczb8q+ffve7rl++23cmbnl3DvD/d3T2Oj2xHyXYCTUQfuqKaVe1a5iUqyFoEzANRD43sQn5YU7bpehU2fIupPfk3xbdEaH2UNFJq6Vk2fXzslrY0VWzNfLSi0ryrj8hvLVbY6UjqZO7bP622neUtpNkkuXDSpmg2hc2eQDpfQ1rrBhww+ZsXJ44EeYRusKnCLnpNpj5Ig8AWO0wlHme1GmrvSdDTabacbk/r+0SfP8OU7bC67ml2h5iwRZDh12mwte1enHy+/22gaRhiGSzxe6Avv4WhwfgLJqW4sFwSpm6uoPIK0ZsWodg2ba+t5kCYIVZ0asMOYHb9P2/NQ7HOaEmb3GrVO9HjxsUN9rX0sf56frz2sWKNUgWMFoz2n9dNP4LBc7MEE2pQDboBadd5m4AfSTfzNe3mu+B3xbOLRKqvVMOr+VfJ/BbSXPjvXNJFBcAga3tkJMAv1YApUIt2geiGIKTKF5pajvF5s6NYFkI6XQiemub0ZMJEzVrqJpSFJIFUGUZjXfRVMatlmjfwq6mEZrAd7Y7AGFzTPflwUvvyD178+SdSZPlsFNnWmOwsqiepHn10Cjm5MXV89JS73IqjUNsmLTCjK+flM5ZKdvyYjBI7qgMy6XLjLCN5Y+slkHbNOYJtJHNq/4+RKQik0uMlEzxagUQ8GxISd8p5kX5hIoR9OTRDuqPrPBADsarTQ4L+2Yx877WDqaF0ltR4vT7ualNbUvr/rxkqO3FT/e+mFSGDLMDU39sYMmq0nWlj7vp8jhbwr1vglosYBUaQAorF/Mo0Z+9a8X8w0O1hMHtmH3+zAWvM564LAgLRj5YBt22JDET1eDgtGnLGCr74rm9GV96mGCD7vBQE1BGfRkXqO0176PeRLtdTEtOm1wmMj3lm/ruHHj3Dri+8A3kOvBg8ik70W13mdwW60zZ/02CYgY3NoqMAn0YwlUEtyqPxu/H3roIWdqTMoTDRgVFjiKqUGbQIocrvMMG01fu4pmoVjAJJ4jQuakSZNS+5TSFppONMlApxY22/jo0m7r3Dny2NWXSds702XtyVNkxMKFkSuqmcjL4zo1umh25w3JSSHXIavKIFmxZWVZZ9gE2X+bw6Slsbkrf6+f1ohUP2w40YgxbvyN0wYqUiilDrTS5DIFPEgxpBGm/RRDaMmROz8Krsgf027u45BATW+TwK0Kx9eoaeRYvZbIp7OjQxZ9MkvamhZKHcCLF24O0+ZojXrYxKDZBXapAe1uw8jlJF9IdmCi9cWlHIrTdGou255Ed6YN5pb1okAZBZ1RZto9NSNGHn6KHF/eaVI4xYFtcB7j/HSzauKLmYdHacyDJtM9AVsdp2+KzNzpePV6nPaa+6ICUDEOvo1Y1OCSQZT0oOWGmqb34/9ULjU0g9uBNNs21v4mAYPb/jajNh6TgCeBSoRbNlP333+/0xCQP1NNkfntB45io402gfyWbOgAOc1dGKVdxXTOD5hEneRwnD59emTu2LgFA3Dg54vGFohDQ6naDJ5F06dt5jva5dGrLpYFb70r46dMkxXmfBxZPQj25ioiz6xTI8+ulZMPl+n8HDc42B0iK7asKuuP3Ep22XAPmffJfAe7ao7JZhYw5SdNLl3AGI0tm3YCxRCxOqhR8wNv0aYG4eE+5M/4CeaFbHmeFCFEruZ6Urj1AUg1pcWC+oSl+wkGXFLtVcvihdK8oNOsudOPF6PkNklq1tzeFbSqTtpyBakdPFwahi2DbXzoXCp4sHaT+rZGBaRChqyxJJFZ/c4k0bZGmbr65tKa+ihr0CY/GBfjYE5Uwxr0041K4eSDbRYtOu1wKBUWYCyNn26c33NQ/sX8dNMEoAousmI+tlHa6+BBQhTYsm4A2/nz57vDMqLXJ3VJiPtuVvt1g9tqn0Hr/0CWgMHtQJ59G3u/l0Alwi1CB24JCDVhwgQHSWyy2ADqxopNG6a3aE0BBsyXowItsZFVM2K0j2rqyv1slNGcYFKM+W5SE2ZfY6JpeoDIDTfc0IE2/SPHLu3y29euKugOHTJEnrr2Mpnx4muy8nszZOyM6UXX25TR4iAX2H2XuFBLYGpwTmTVjqGyQvMqspJ8VjZbbUtp7+jcwFP8XLq+djXYGLIE0v2oynEvALKMivaMfAFb5ELdSeE2CkqDsFAs3Y+CcFJoaGtpksa5syTX0ih5dLQpNbxtHTVL0hLVSXtdg9QPHyV19YO6tGHARJaUQz6UBuciqU9nFm1rMU0nY0HTmRZy4rStSTSdqn3WQ6M4E/ew9Rs8OPGDNen9cZrONGAb1ocoP9002mvqTRM8Kk57HfTTRS4EkcIKg0NB/OXTznnc96OarxvcVvPsWd8HugQMbgf6CrDx92sJVBLc+gFvMEtGi7Lllls6GFWNLZMBjGLyqmZyaGyTarLYlAJa+Oj6/rIaGRjwTBoYxddy+sGngguGTSUmy2rSqxoj+kxbADcb+9x7b8lHL74io6Z+KGtNfU9qyGsTUT4cQYqhzsjL5NXtqPn0Uz3Mwe5wWbFlnDNjHjd0TWlpbXE1sWkHNhknoKsmy2ha33jjDXcd3zk0vmkKc4QGHU06cwXI4Z+ncE17HFag+SlmJp02WBL1+3AS1MYhYw1KlWY8QEPzonlS27K406Q515rKh7czJVGnOTNP5uqHyKCRy3dFZ07SlzBta1wU5GDqHV9TmlXb6puH+/1O49MZB7ZBeRSbU+7NOhYfbMN8bJNoOqlDfWyz5PTVb5hGqtYo07Qd1F5HRZlOC7ZB+epBgh6A6XW+jcwrAaL4LvGN4xuFxUUSv90k67q/3GNw219m0sYxECVgcDsQZ93GPGAkUGlwywaPje0TTzzhtBJqRgxssZH0gRKt4Lrrrptam4D5MBpK2sJfFKDzIwOjlQLGaJNNXligGz93LKa3SXM9sqlk08jzBLBSGGNDCWyqGfGkfz8qL9xxhwydOkvWmTJFCkvgNGxhzhsk8hwa3bVz8vK4nLTku3+2gd2VO4bK8i0ry4qyrqw9YgMZVGhwVWnkY+AbMEIDniQnsN8P5gswBpDZqG+66aYOZP0UQ2zS0Y7jh6ymn/zN3zBnMd8NykPNK4M+unGaOK3H90tdSpNFMKZPPpKO5k4f3nxqc+Zcl3a3raYg+WHLSmFwZ7CqMPjQSMJRuV+jNJ0KnfRfc9AyL2l9r+lTEErVKkEhUPtdTL5p0uxEfXijokwn1V5Tr4JtYm1+W1uoybT2MYtJdBBsg2bqxbTXfm7bNBrbKJn6uXBZY8wTh1P+ARFt8p3F1zaLlrw//4fU4LY/z66Nrb9LwOC2v8+wjW9AS6CS4FbNTNngAX/kaPW1q0CnpoRJA5T+BKuGkr+RQ5eNm27iMR9GuxpmRgx0An1sjEmvQ5odICIqd2yxRaV+bASxAkDQpGL6p9GeqdfXrs763+vyr+uvlbopH7qAVEMbF0dW35gXF3EZrS4RmBcOWvoTToCqVWSQLN8yWpZrWV3WHf45WWbIMg5IiWoM2CfNpQv8vPLKK04bzvOYdjNPfmGzzFwiO5V3EIqoh3kvhfmuD6VxfqRs2PXwIolfalDwrY2LpWneLKlpa+rS7tamCFjVsiRYVSu+u0NGSMOwZZ0c0qbIiQpIRX+Rh/q3pvnYJdG2xkUkVpjjd1YYDGpbqSvMT7dYROKemhEzJ7yfflRr+hEMDhUn3zTBo+K010khPaxPUXDMOPm+0U/91urz+n1Ie/gVJ5Os1zmQ5LujfuB8dzS4XdrI26wnDhs5PPXTjumYw6LNG9xmnTl7ziTQ9xIwuO37ObAemAR6TQKVAreYsF555ZWyxx57OO0eG1U2KGxKAU5MXn0TOuBL88uyAYnbzLBR1LyvweBTQeEWMyNGwwF48BsNJZrlNIXNI+mG2EixGQMG6T/9I2gLYwXsaUM3z35ao8a5s+XhKy6W5kkfyJpT3pNR8+ZGNt9aI/Laajnnpztx7Zx8PDz8c14jHTKmJi8rtoySZZvHyvhBG8p6K3+mS3sdJV8/XRCanSjzcDaOwYBSUQGTfK1uUrkm9SlVk142pep3rfDHetO/R2lK4/rD3LKO2xsXSG1bY5d2l5RESYNVteK72+G8fkUKQ2XIsqMjA1VF9SfKjDip9lrhUQOFJYXSKPlSHzLViNlxcvSvx5kRx2mvNXJwT82Ig+byvnm49jdOvmnANkxGxfx0/dzBcfItpvUFbLHi4Pu61lprue+vpvthbZMCCIDs60I/1Y9f3Ug4IGQ9AN+YUcf9N0HHwNySU5yxIkfGzgEj32BdN7hT8I0Lrk003ZSo/N1BOeWSdqqvBWztmwT6uQQMbvv5BNvwBrYEKgVu//a3v8n+++/vJmPzzTeXffbZR7785S+7jdRhhx3moO/ss8925r9sYji1V0BRf1lgF9PX4P7B1y7GBZ8KrgY1IyaaMkCqbQJDvhlxEn80Nk8vvfSS00azIcMEOCyAFW1o/l5AF+jVgpm0alWGDR4knzz7mHzy33dktXc/kJVnfVh0MU9asUaeXbszKNXU5T8NSBX20HI1ORnTNlJGNa0qY+s3kO3X/4KsvMoqXWbawXRB+OlGBZsJg1va9DWUPMu4feiMSkfj9zeLllPbVsD2/RxZO5jv0naa4Dm+ljNoAuxy8H7ykUjLIhed2Zkz59oSfXhcoCqXhigv4vx2Rxf12w0zAY7TrvraazrVm2bEyDQqCnJQIGm1rXGazqzpfnywBXyC35ckfrrUoT62SSNmB+XhwzFjCdNex/lBFwNbrCv4rtI/LGOCZsjMB9+5JN+6RIs74024dRDBmXW0zjrrdFmKIF8gFTmRfixp3ACCZgH0fFuBWB0f64nvPvEZkAXBAv1vgmluM06gPWYSqAAJGNxWwCRYF0wCvSWBSoFbwPGGG26Q22+/XZ588skuyCFQE6bEbGLuvvtup9WlsLFQM+Kgv6xqdNmssKkkmjGAWEy7WEy+bAgJYAVwAqX8oDUIRiOmXWA8zDcNLQB18BuzX2Aw6SaRZ4BcNloE0dISTGv05J+ukPf+87ysMHWmrDHt/aJLZsYyBXl+7Q55eq12eXPl7gGpwh4cqn67zWNk5brPyDrDN5JCXV7Gjh3rNDzFFBJhcAsMhqWVidL+hflWFgPKpO+LX0fQT1dBgU10MdD1YTApQDUtnCut8+dIbUezFJzvbjLtbntHTpoJbdVRJ+35QTJo5ApSU1fX9U6oaXuUtjUuIBUV6boOC7iURK7BaNfILiyydTGT3rRgG9YvBbngtTR+unFgG6y7WERixsu8JH3v/bqLaX2jTNKDmuRiYItlBd9T+gfYJg3Ql2Q9lPoeUrfxTQzTIvOdB3DpPzCaRFHKgSPrk/gNWKn4Bdny3eYAjHzfyEeLwW2pZ9bqMwmUTwIGt+WTtbVkEii7BCoFbnXgbCY4Kb/kkkvkwgsvdBttTL4wQ2PzgTYXrS7/1o1LVNodNjhsSthwAsXrr79+Km0cfYqKiEw/0SCrGbGacLKRx4wY0EWzSx/Q1ALYbIaSwGDYIkBbQR2MFX9c1SjrvWzKulIMDR0qr95/p7x6730yYklAqrr2aE3h3CEN8vJag+TFtRbL02NblgpIFdYf/HZXlgYZ3bKCrFyznuyz5aGyzmprh67fINxyk8qrGAwyRt8PWysHDhSY+FtSoAx2LkxDGaX9iwKxsHy8aV9i6lg0f67UNC+QjbbYTt57/4OuKmh3yOBBMnL4MFlnjbGy2cafkYO+vJtsuH6nrIFdTJhdVOZcQToahsmQYSMSAVSUSS/1sm7RYKfRXvOcQilaQMzUWe9o2fz329d06t99EON9pZ6e+JQGzYh9AAyapEeZ9KYF2+C894WfLn2I0iRzLUym06ZNc4dnvEccIlYy2LIuCAbIOHDpCFufxWA17N2kPuqNg9ug24XBbdovnd1vEqgcCRjcVs5cWE9MAiWXQKXBLQO866675KCDDnJaypNPPtn5T912223yyCOPdEXyVNDdd9993Ym6bnLYGKPJZXMNEGpho67whwY3yaYdcCWXLpvUYgGs2CzTVwVdTYHjwGTIEKfx5R76jLlc2oJWm35Q/CBYmtaIjalvpo12QbXXaHenvvisPHXDn6Vh2sey9uR3ZUhTY2QXGgsFeW315eWttdrk5TXnyeSGJmmT+P8M4Le7Yk2drNC6rIxuHy+brrqD7LH5Xg6QfLjFrFyjsSb15XQQ197etWn3g/pkNSOO8+VUAYX5BiuIcQ/1UEql5WSdcZCz8047yfLLjpRcR5s0NS6Sjz+eLS/89w2ZO69Tc7/XLtvJVef9WFYc3d3/kRREnbCbFyIyF4YvJ/lBQ2KXXFQ04jQBk3wYZE0yliDcBjtSDMQw7w6mNoodyBLNs8JxmBmxriXmLiz1DrDLtVKaEbPWw/x0GU8xP/Oe+ulqHm9/nMwT3yQsWzhkUv9/5itLRO0kc1KqezgoxM+V943DyrDCde7jW8M3P66o/24xs2T8eDlk9YvBbZxk7bpJoHIlEL+rqdy+W89MAiaBGAlUGtxieovfE+WPf/yjHHjgge7fwCEAd+eddwr+uQ8++KA7bacAv6rRxY/13nvvld///vdyzDHHyPjx4919mBEriLCZVH9ZtKxB0KWtnkREVtBFI+IHwWKDpNAZjCgcNk30Q3PHoq1Ec4DWNqyomTZQgXmhbmYBBNpCA00da6y0grzw1+ul5Z0PZM3J78my8+dFrpC2mhp5a7XV5N1xDTJ57UZ5b7mPZZosksaOZP9ZGJITWUkGy6rtq8uX1zxSRo8c4zTowENW80wfwpi3KDgpZvqZJZcuQkriW5nEDFIFHtYP1jJrj/W9ww47dEF9c1OjtC6YIw/cd6+cftY5Mvnd92Xt1cfKU3//o4xadmTkHH6abzcvrTX1UhixnOQbusNusB+MIU67GjS9D9bB4RIwEAe3fsejzIiLRUEODjyttrVYlGnqzmoVEAelSdZSb/jpAruAH98JvhnMNT8cuvEtzGIyXc7/yHKAiAl1GGxqP1h7jI9vbZLDRIVUgD8YUIr/dnAYyjoOysbgtpwzb22ZBEorgWS7mNK2abWZBEwCZZJApcEtw77xxhsd4E6YMCFUCmxI2aCh4QV077///i4z16222komTpzofFpvuummrtQzasbL5gjQVTBmMwPocsIPOLLRI2crYIoWA9O3LBGR/TpIrwNc8qMFLYFqksPSTNBfrQNApR8Ey0pSVHvNWPlRM0zGqnDNRra1Sa54egAAIABJREFUqVEeueICmfPaO7Laex/Iyh8VD0g1ZcxKMm3V0fLJWsNlyopz5KPCNJlWM0/mthfv1bDaYfKDcT+Q1UesLoNXKEihpk7qOgoyKD9Ulhm6bCK/OFpQYPBNK4uZEft5QbWHYXUkkal/j9bB34J+umyAVRNXDHSj+hGEW79dHSsb9x133FEIhHPw/vvKHy44y/ntJklB1E2zW9sgucEjpa2jcxxhWs5iUK++q5puicMGDZbEoUwauA3CoD+vvqa+mB90HFDGzTNtAtjBdD8856+luAOMtP3oLT9dBX1/XlQGfBf4HgFojA0fVsalfvx8nyqxcPjJt5nvlx6CBvvJde7juw6UJinMgQbU8u/ncENdTIL1GNwmkazdYxKoTAkY3FbmvFivTAIlkUAlwm2agWkKHYJN/fKXv3Tmu+SexW+Xjclee+3lfHS33HLLrkBPCsdqRuwHhmKjB/iy0SfVTxINq99fNDL4cKFlDuZ9ZdMLmPDjm0wDrb6/bLE6ksqGzRr9QIvLGNB00CfVXgehHih76ror5d3/PCejp34oa74/tWhTM5cZJZPHrSwNa64iMmFDeW7mYzKzZorMrJstM9tbpd0zZfbhtjC6ILnaT/+zwr8KkpM6yUte6mX4oGVkcMPgpdpWrV7YRj0of/XT1b+rGbH6X8fVUWzgYf0o5husAOhbBxQbSzG49ftF4LWvfvWrTptEaqnRyy8vHc0Lpa61UebN+Ugu+8O18o/7H5HJ701zhxvrrDFODttvDznuiAO6+VQCu9M+ni833H6f3P/YkzJp8hSZPn2Gi+KNGf2hhx4q3/nOd7q0VkEQe+qpp+TXv/61PPfcc64d3r2TTjrJRQJPCrdxMJgkYJKaj/dkboP98Oc16KcbdYARN5a497dUfrpxYMv3kcM7TJH5PvDOaMofvhWVkO4nTFa9Abe8j5gyI3sCGGpqIYCfYIb8Rh4EsPKLwW3carbrJoHKlYDBbeXOjfXMJNBjCVQ73CIAYPToo4+Wa6+9Vs4991y3CWHzD/CqtpTT9y996UsOdLfddtuuDT6bVu5hs8ePbmLZJLOhATr5nSTIChtbImtilowWmGidYZGTtc8KuqSh0HbVN0/N4YCEqDqiJl8jRBPwCg0H/dDgWmqSSNvBaM+MFW0H7b18z+3yyn33ycgPZss6U6ZIvi06INW8wUPk7fFjpX210bLNEUfJ4kH1cuczN8t7ja/IR3XTZV5djXx7bKfmNgi3YWOoy4nUddRKviMv9bVDpKF2kJMPIId84jRnWmexFDgKJ2leIDa5wF2xfsTlXeX5YnUkgVs242ysuZdDkuuvv96l0WK8BNPh30DASiuNkQ3WW0c62ttk4gsvy+xP5spO22wu9/z5EikU8l1Dv/5vd8thx/9EVhmzgqw1fjVZbvnlZMaHH8szz7/k1sjee+/tLCSCcr/uuuvkW9/6loMC1hhRs9HYArrHHXecXHrppbFmyVlgMCpHMgPqLTPiqAMMP7UR72xP/XR9KM3qp1sMbLFaAdiCaXTSvAd9eW+pzZL5rnA4xDoMCyjFWuM688pBgG/FY3DblyvB2jYJ9EwCBrc9k589bRKoaAn0B7g966yz5LzzzpObb75Z9thjDydvNi1sWB544AG3MceEGYikAJ577rmnA13MOwmo8r3vfU8OPvhgF7CJDTKbQGCGwqaeZ1S7Gga6gCTRjNlYrrzyym6jlCRoFfWzSaI94NrX6LK51TYxE0wCdfiNAdgAULEI0VHRnmkDzQ31sFnnUGAZaZWnb7xO8u991BmQqnFx5JpuyuflrbHjZMEqo2TkhhtJ7crjZdlllpHa+loZMnioDB1dL+117dKMytArubYWyc+bHlov/xGqy+WkFuCVggwuDJMhCYIk+esAOFH5hUXLBVij5Nu5lpqkvb1NamoA7Ial+zlyNZHaQre/F/PnZA3xE/Tji4NbH7AJpvbQQw/JaaedJrwDzDmQOXnyZPn5z38uxx57bFf9rKsjv/ENefTxx+X0E4+RM0/6dpcZ8+tvvyPz5i+UCZtu0K3/02d+JHscdry8+N835ZrLLpCvHXCwNIzo9PnGJBrLBg5ygFi0uwqdt9xyixx11FEOevF5xLyeA5PgWJNq44t9QFUewXuSmofzXFrAZl7DUhtpH9IESvP7XQxKuS+Jny7vbFQwLaw48FdlLoiK7Ke1qej/SHmdK3VAKdYv6xNLBawOwgrvE1YvfE/5tmsxuK2WVWP9NAksLQGDW1sVJoF+LIH+ALdscNEYRUXPZDPKho9oy4DuHXfc4cx1KZihATXA3FVXXSW77757lx8lGx80nGgL/AjIBBhR31VM+wDTV155xWnk0F7h55UERP1lBXijdWMDS90aQEv9/9h8+dGew+r3Uw4RSAtQStIPjfasuXQ1TQ/907Gi0QX65300Qx658mJpnvSBrDH5PRk171M/4uBr0p7LyaRVVpXZa42V9Q48RIYtt7zrE5vr1rZWmbNgtjS1LZLWXIvIJ5Nljes7g4dVY2k75hmRUd2jqeo4kC9rVAHbh2s/BQ5yiYJb3x9UA3Idcsgh7kAHsPzd734nV1xxhdOYYq6M3zrF1zjii0hQMrRPb7/1ltS2NkqueaHkyZyba5HaXPcDB55/4PGnZdeDjpH999xZbrnqPGntqJHmjrycfeFV8svfXiTbbbedPPzww92mjL6iPf773//u4BbzeIo/VoXDtNp4v6EgHPvQ6QcaKxaQKi3YBtdmlJ9ucF7j1nTaQFjF/HRpKwjYGkGetYMGMszPP66PlXA9SSqgYql9gmNALsBrsejLHAjw34CgD6/BbSWsCOuDSSCbBAxus8nNnjIJVIUE+gPcphU0m5LHH3/cAQEbcDb7ACnaKOCWyMu77LJLtwA7wK366M6fP7+rSTaRbLLZzHLyD5imLWhsX3vtNfcYgL7SSiu5f2tgKKATgNYUOgC1BsHSaM+atojNNlpjoD1tAfjZGNIupthsJNFIa9EgWIyRcTcvXiSP/v4Smf3qW7LKezNk1Q9nhDbZMWyYNP3wFMmvuaYsP2yYFIYMkmHLj5ZcrubT+z/+n9RetnnaLlfM/VFw64Mtmlr14Y7SwgGfBLbRaMkM0K9DwZa/ky4LLSkm+eSFZt1iig/w7rffft1ko3UQpA1N1bPPPtuV2gQLg46Odnn43rvl2WeellkffShEZ5aODpm/cKHcds/DsuF6a8lLD97cVefOB3xXHvrXM3LFef8nhx50gLS5SMzLS36JvzTvFX3gvXrzzTe7tI5BsOfQhjElOYTxB6RgGwXHcebhvZHuB0DyodMfq/peh401LdgGFz1jpQ79PnCdv/HN4NuGjFhTtM3hG/EEqrnwreSwCPeToG8w32bWG+8aVgxx60rv5x2IciN5/fXX3eEm31SCA2oxuK3mVWR9H+gSMLgd6CvAxt+vJTAQ4ZYJRYN72GGHObNkTJLvuecep9HllJ7CRnXXXXd1wADwEvRJN0psrIBJNowadZlngD/V6CYx+WPzC1Dzw8YTsAFWwwqbVbS7Gu3ZDwxFX4FQ+kcdgG/aooBNHUSaVkgHItgk0y6aYS3BIFj8/ZE/XiYfTHxRlp82S9ac+p7ULjE9VrgtrLGGrJbPOxPjtppaaawvSK4+L8OWGy21897td3DLnLFWmGcOJAC5sKLRhoETDkhYg//4xz9cKiDAhDVGHT4cUw8HMFgjnH766XLmmWe6zbkeksTN/6OPPuqikbOOgAECR/E7qoxbdSWZ/PRdXZfX3e4r8uakKfLgTZfLTtt2RjX3IzG/8MY7su0uey7lcwsk+FpVrVC1q0ny2vpgm0QDqebheqDgj5H1zoFDWr926ojT+kZpV31NMvIvlpM3bh65zvPALWPhu6PrDr9rtcLgmm9tkqTeSr2H7yDfzKDfsK5l5gWLAf+gUeMbAPZYtWhBVljd8CzuGFxT83nWDTLk24j8yKfuBxg0uK3UFWL9MgnES8DgNl5GdodJoGolMBDhls0MEIgJ5/nnn9+1sWUz+swzz8itt97qQJcNFIUNzRe+8AXno4tPL2B3zjnnOC3NTjvt5Hyx8Gn04U9TamBKHKYpYVOFRkCjOpPqh+jKSQrP0hbAyeZLTZfRPmj+XnyEk2zY2cBhljdp0iR3PwGsMEUOK2ygAV02in4QLMaHjDDxow/Ids4bL8vzd9wmg6fOkrU//ljkxO+LD7d+/e25Gmmsy0muaabUNDRITb4gDfUNUltX625ra2uXtrbWLp/O5o7FzpS5TdqEuMwxmYi6DeVT/90aqZOC1OeHyPBBnx5caHuNS/yKg7l02eR2wgn+sp7mOeBz64MtUAvcJilqloyP+NZbb931CO1Sh8If88baYt1hgowpMptvAJU1qhot7mN98Jux6Mb9hz/8odPwU1h7vBM8x0EP/pisX9YDa4Przrz4349IvqPZpR3aYPu9l4Jbf3wvvvqmbLLbQbLaKivJq/9+VHKDhktHoVOzqdpn1a4CCcF8xRrwK+i3nhZsw2Qe5adbTLsarCcObIP3R2mS9b6sfrrIjr6wPgB9X158I4gnQNusHT1Y4D6+D1msTJKs4XLcQy5ovkWavojfaGFZX0Bq0CVDAwby7WZ9+4WDQY2WzBpQObLWNOjeaqut5t43vxjclmOmrQ2TQO9IwOC2d+RqtZoEKkICAxFuEfyTTz7ZDR7CNqPPP/+80/ASeVm1Wmx+tt9+exfI58gjj5Tf/OY3XRo5NkJ+BGStE2hlY8Rmkn9rVFsAkc0W8BCl1YtaJGziiOIJ4PIsm1XqY6NLYZOrG9ioaM9+Ll3gNA1gaxAsxos5s5pgsonGdI+xahCsD95+XWbM/EhGjF5RVs3npT4QTMofY4fkpKlQkNZCnQwaPkwGjegO2sGotR3tHdLU1iQt0iituWZpzbVKS0eHLO09Gv268R+5vOQkL+TfrZd8rl4KtfVOC6bBw8Ii9Eb5VTI3GowsDdjSQ4VbAqFtttlmTq6045u4Mrdcx6+V/rHRZ33ttttubl1iEkzAtCSaY0yU0dTzPBpj4Nc3mb7vvvvkgAMOcHALAKsZ8S477ySPPva4XPbrs+Sog/aWulz3aNp33PuI7PvNk2TsKmNkyn/udsJv7ah1/rqtNfVSP3IFqav/NDBXVPAtxq6gy/ulkaaTaGzDZjzop+sDdligsTBNclzgp7gPe2eAssZuZsQ8k9ZPtxjYEgGegwnqxBSZ7wxjBQCBXuY5i+tC3NjKeZ3DND/wH98wvnUc8AXNkYvBLX1mPviWIh8FWuZev91hB48Gt+WcbWvLJFBaCRjcllaeVptJoKIkMFDhNs0ksBllY3/TTTc5P11O+jEJxW93q622chpd8ukCCLqpwlRQzXmDqX4UlOLSBUX1kU0VkZnZpKKlQFMKVNJPNmfqG+xHe8bcGeBk48e9fh7cYD7epLLxtc/UibYPTaJqkvmbplKiX0DZ+HHjZPGc2dLe1CSFphbJt7UWba45n5fmQl7ygxpk6HKfypeHojR/pNhtam2U5nY0vM3SkmuT1pTAi042LzVS11En+VyDDB80siv/brEUQ4xRTdWzpKVRuMUseZtttnEwqXOr64ZNPRYDWBZgWk8gKQ5dLr74YjnllFPk61//uvzhD39IZBJNnlqCQqGxnzhxYre5YD0RQRy/Xj8wFDeR25a80phO4x/cOH+2tC2cu0Sz2yIHfudkufXuB7vBbbdDjA4hjJWDXakfKoOXWQG6c7f0lhlxUj/dYprkUqT78c2IgXRfq5vUT7cY2PJ9Ym3wLSLXsO9SkfTdtvviJWBwGy8ju8MkUKkSMLit1JmxfpkESiABg9tkQkQ7if8tpsQXXHCB87e97bbbHGRSgBoFXfKCEhRKQVe1nESr9U2X0QyqHxxgGBf8hHbYoKNRBlwBR7RuwRQrCgh+ECwiP2sBiNFU8OPnwU0mic67AFiiOwNavvaZvwPzqsEGyNRcmvsIAqN+a2zk5300U9oamyTf3Cr1Lc1Fu9BaWydNhbzUNBRcQKqa2jp3v2rSdB6CJq6AH32Yt/gTaWwlOjMa3jZpSaPeFZHanEi+A+DNS76mQYY1jJD6fH2XuXRQuwqUpg2W5MPtzjvv3C2/MuMiYNTJJ5/szMiJeotmlfmkMN9bbLGFy2N66qmnyvHHH+9MzH2TaLR5AC2RlikcwJDeBPncf//9DnR1/Vx55ZXOTJlxERjq7bff7horbWy++eauzYsuusil/lE5/+3WW+Wggw920IZZ8pSn71JujZzftiVRmFtyBckPX04Kg4d19UMjTQcfTmNGnNac2Y+8rIc1fvtZzYiDYBs0u1Y/Xb4ZYZpkxsw9aqGBS4BfB4dIrA0KYJv0u5Lm3bd7OyVgcGsrwSRQvRIwuK3eubOemwRiJWBwGysit8kEXAE2Ak+pzxZ/x1cL02VAlwi0FCCVYD1ALlpd/LW4fsYZZ8jPfvYz5xvJxh9gVhAD+DTVD7ASBrpoZMhhywaZOoGbJECs4EP/8cHzQTdtECzqon36QX+KaZ8ZG5pc2mUjiIYY/2QNqMN1ftico8FqnDdXFs+bJ7UtrdLQ1Cy5IsbF7TU10oi2ulAnNQ2Dpba+viu6dZTmzzdxdYGaWppl7sI50uQ0vC0OeFszAm9tBybNBSnUDHLAm9TE1V99HARgQop5MJYByIoCyAChyFwPRzhoufzyy92aUU0yMsZU/cADD3SAC9gSoAp4BXowQWa9AqUArpYTTjjBWSQwD8AtBy5YKhCcCpDG9B64VWhS+L3uuuu68tliPQBMYSKNBhiwRpOMxve/L78oHYs+kbr2JinkWpYyYQ6+gRqYqtOEuUE6GoZJvtBpJh4Hf2FmxGnBdun+dLhDpSDkpjUjjgPbYLtxfrpBywDea+aItcchSdLc2PFfQLsjTAIGt7YuTALVKwGD2+qdO+u5SSBWAga3sSJyNzz33HMOKKMiEbOhJNcuEIuPLvCggLPppps6DS/wAJBg6klhswzgaqqfoDkvkAHo8pyfSxeoBTbSFh+OAR/6F4yArJrkqHQhaNGALH4DX6QuCmqfgv0CvgA2YAA/P9qNM79sWbxIFsz+WHLNnaBb0xEdNqojl3Og2+78dEdIw/ARXV0oBrpowfS6BuRpamlyGt6Wdnx4W6Ql1y5tGYC3zml461zQKsya6+s6IyUjq7BgSWpmSsRjjdjN/fSLuWAdMO/44ZICCI19sKivL/6WV199tfzzn/90vuJotvFFRPZAMyl6aEcLEHXNNdcImtq33nqrK7DYiSee6NoBWoNwq88SdRnzZAKxUdZbbz059thjnf82wMs7o3XqM41zP5b2RXMln2uWgrRITUh+XX9s7R05Z76MVrdm8EhpGN4ZUTxJQCpNkcNhRlY/3aCPbZZ0P2nBNji3rFP6oVHSuc7f+H5oQDe+P/yNiL+830kPvtJ+R+z+TgkY3NpKMAlUrwQMbqt37qznJoFYCRjcxooo9Q1sMNGcAbpEY8aEGS0L4IiZIFo3NLpEq9UNqJrzaqofzVkJCLF5BUK5N2suXT+HLZpnoIPiB8FCy6rQSZsKumhcaduHY8yLgZ4kG2gfbldffXWn+VWNrUKKChkIUfjTuttbW2XeRx9KR1Oz1Dc3S11b9+BFwQlqyhekpVAnhcGDZMio7sFlfC2n/xygq+0G61uweIEsaJwrLdIkrdLqgLe9B8Bb6zS8DTKoMKgrorX66QJgYWbmcYuQcWnaFzWZjUtFE9RyZo3w3A1EvfRHwT6HyZi5XTxnhtS2LnZa3XyuuA82dRKYqqkjL221DdIwcgWpLXRqyoEN5BCmYc2a7icueFScjBkzfdJUPcGIxnHzqtf9+aUOhV2+M8y7vrdYUuASkTZAXdJ+2H2fSsDg1laDSaB6JWBwW71zZz03CcRKwOA2VkSZbgBWvvnNb8r111/vQPKII45wEZrRdCm4ouVS0MVUWTWgas6rqX7UdBno0ajL+MomhSB8ffEVBhb9HLbBgWkQLDTJ+NLqhhlYAsrRHtMXH46TCMeHWyIpM04/72uUBi4s9yn3zvtwhrQ3tUihpfOnWGmprZPm+rzU1OOnu4LU1HamF9J0MArQQU1yFOhqWwsWzZf5jXOlVTojNLdm0PD6QatqO/LSUDdYhg8ZkSiFkz/mMLANyiROy4kc1I8zSyAsPaQI5vX1c/jGaeupo2nBXGmZ/7HT6AK7tbniiZ4wYSYwVVPtMBmy/Cpu2LQT5qeb1ow4DmyjZBwG2Nyb1U83CLb+e8840fQzv/ydOUTmtIX2FuuKJAdQSd5ju6e7BAxubUWYBKpXAga31Tt31nOTQKwEDG5jRZTpBiLW/vnPf3ZmpES+RQvKphtoJFULfrqkbVGNHVpQfHT33XdfF7mWgs8iGlTMUYFZAjXp/WxkMZHWaMRRQaWS5rANDpKNm28yrWAC9LFhpt0o3+BgXWzO6Qd95Fk0T1F5X6P8DAFitGAaaId+AGGLPpktjfMXSB3my81NReeqrabGpRnCfLl20GDJNwzqMlWN8uWMCloUTCkDQHRqeOdJawcmzZ0a3rQmzV3A69ISFWRw/TAZPjg62JiaMzPwpFrfYlpOxsvcJD04UYEn0fom0XIiV+pifuvrC7J49kzJNS/s1OpKS2Rgqnm5ZWTI6FVdd4JRkbOYEacF2+DCQ8bF0v0wviQyLga2jBMfau7BbBzTc9rF9xZLD74VfFes9I4EDG57R65Wq0mgHBIwuC2HlK0Nk0AfScDgtncET2Cfc8891/nYhvmvqr8r4AvoEqlWNWdoegn6c+uttzrtL2lXMDPkGfwpNdWPn9OWjS0AzW8ApSc5bH2J4MdHlFzgkgA1mCYHfYMBXbREUb63BLGizxotGa1SkqL+sGwifVNTDQwFIPhtNi9aIAvnzEnvpztipDQMG97VpWAuXb2gmmTVzPH/GUsxzdjCxoWyYPE8aXHAm82HF+Ctkxy463x4B9UNkRFDR0prS6e5axqwDTt4UHNm/5pqOZNAWBKwDbZbLFgSc4pcg+uptXGxNM39cElgqmapW6LVxSe3bbl1paYu3w1sw3xsiwWkUm09UMiPBjrLovn0U/UwFv9AwZdFMXN4P19y8OCCd1+jV2ssgCz9TPIe2j3hEjC4tZVhEqheCRjcVu/cWc9NArESMLiNFVGv38DGF2gkEjNAe+eddzptzK677uo0M7vttpvz0d1yyy27tD36DCbEgKMCChtytLxsftHgZM1hS/0EAsJfGE0eQbGA07BUPwgIMFBNMn5/Cib4BBLUCOjGtBlNEhv6NMXf5FOvn+onGAFZ621raZH5s/DTbUnlp1s/ZLAMXna5LmCNzKUr4g4cNP1NmvF8Mn+uLG5eIG0uJRFRmttTR2nmP8x1uZzUddS61ET1tYNlxJCRkq/LJ+5KmDmz5tJV03mtTMEvOHdZwDYMdNWcOQjY2u5SWs6ODlk8d5Z0LJ7nomoPGrNml6l50uBRUYcY9IF1BZQm0a4Gx1MsBy33Rplq+/7mKlfuD5ozc6AB2NIO0aj9/NqJJ99u7LEEDG57LEKrwCTQZxIwuO0z0VvDJoHel4DBbe/LOGkLbPCJpEzu0uOOO07wlSWvKeBLQTO71157OdDdZpttunKgqikikMsP9WhBo4qfKxvgKFPgMNhA84zGFY0RYBumbfVT/QDZajINAKmJJP2hXdLR8HdSlKSB2zAAi4uAHNQ2Usf8j2ZKR3OLFJpbpdAa46dbVyfNLp9uvQxffgXJ1dR08+MEfHz/UTWZDmqSw+Y9zJyZ+xY3LZZ5i+dKi0tLhA9v+rRE1FPncvHWCj68BK0aTnThQsNSXUlizhznL8u4da1l9dP1/WM7TZE78wbrj3Y8zl9WfaiTgm3Ymld/Vf+azi1rNgnoxoFtWLsaCMs/tNH7kIf/3vpgS/RrvgmmsU36hS3tfQa3pZWn1WYSKKcEDG7LKW1ryyRQZgkY3JZZ4BHNsbHdfvvtXeAnTJXR0qrf3gMPPOA0unfddZfLG0tBO/qlL33JBaTacccdHehisnzBBRfI1ltv7bSsFD+nLRpdzaUbFU0VqHjppZecfy9myPj/JoFiNbNWTbKay9IH2qU/1JMGbpMAGPWHRUBWGAJOtC8KCovmfCyNCxZKXXOLNDQ3F10AnX669dJeqJXawUOkftBg5+tbDLCjtI1pAayxuVHmLfpEmtsbpc2ZNGcD3loHvKQmyktdrl4G5QdLTUdnYK2kfrpR5rzUoVCaFrKQ4cKFC50s/QBj/oT4oBsVkEpz0AKgSU3eg5Pu+9j6+XR9DXYcYPvrFVeEuBRZYaDLAZGf7ofvAodcWGDwDn3wwQfuEImIyBYsqm+/3Qa3fSt/a90k0BMJGNz2RHr2rEmgwiVgcFs5E3TTTTc5LSkBpIKFjT2b2ocfftj56BKUioBPFAI7kbt04sSJzpT4lltukR122MFpdAAq9dFVDbA+o6CrQMAGnxy28+fPd5pXcqEm0Vb5fWUz/sorr7jcvapBpd/Ux+YcbZOmZSkGQ35e0DTmoVEwxDgAqKDWuGnhAlk0Z47ULAlIlSP8bkTplk/X89ON0yTTJrJFNj0BMDSLjU2N0tTWKK2kJcq1SFuuTVrIG5xyGX8auKpW6gTgHSojhoxIpAX0Ic5vVn2Sk5hqJwHb4JCKAXZP/GPjgkclAWzuUR/4LGDLWH3ze94RCu8irgE+2HMgAdxi5p8WoFMuE7u9iAQMbm15mASqVwIGt9U7d9Zzk0CsBAxuY0VUkTewsXrsscecRpd8ukRhRrtDdGY0pZgu77LLLk4zpxCJhks1q2h5tbBJxnx5+vTpDqAxISYHb9qNs6/1BbjR+gI6tIWJM3CJtkmBOSynLX0CEhgf/c6aF9QHsKAZsUZABr790trcLAtmfeTMlxuamqW2PSafbqEgLfk6CfrpRuXSpR9Z863/FaMeAAAgAElEQVRGmTPT//aOdvlk/hxpbF0krfjxuv91SPEkOksva/5jn3eBq/DjLUh9Xacfb13tpz7SPoDpoUNYftliptq+n26UxjbupaMffn5XvT8NYPNMHNimAWzuzZruB5mgxaYETbzp47vvvtuVx1fNlzXIm0Ygj5NZua7zLSJtmM4P4+FwC5/8tNp9+gzYUx/WJGo6zruLrKmTb01fFIPbvpC6tWkSKI0EDG5LI0erxSRQkRIwuK3IaUncKcyYd999d7dpRFtLeiGCOFHQIAG4gC5BqdCc6uaSTSKgy4+aOvMMsEGQGnz5wqI8R3XM1/qy4dxggw26INbPczt+/HhXBRtD38dQoUS1cz3RxKnWl3bU7DZtqp9WDUjVAz9dH+KCcisWJTd4bzC1TRJAQL7zFs2TptZFzqQ5ay5e+pLPiQtchR8vP/W1g2T40OFLacHjNNgAiVoTcG/QnzTxovfyFCNH30/Xj6od5y+bFmyD/WN+qSMYfIt21TQ9yQGRv06CYEvdBI/ifeWd5OAJCCbVDz+0T47srObYaWSe5F4gHBBlnjk04zcWI4wRCMUtIcn61bZ0/IyZuVatOO84Vim4Z4wbNy5J10p+j8FtyUVqFZoEyiYBg9uyidoaMgmUXwIGt+WXealafO655xy8srnFTBmNLZv7//znP06je8cdd7j8shQ2zTvttJMD3S9+8YtdOWpfffVVZ4pM0Ck2jn7UWv4/G2rMl9EKR21Keeb55593mpowra8Pt77PbbF8q0B2kgBNQVkqsBTT+hZL9aPaXDUxVU3cwtmzpIkNtjNfTuen24Cvbn29mxuNRhzlPxqUcVo/3bC1pXDMtebW5iU+vERqzh64Cj/eOvx4pU7ymDUXhsjwwd3NmqMiLztgXpKnOMu7oDIJM/FOAtgcpPQUbOl3MNiZRtZOA9hxYEu0dOaPAyNS/vjrQ33yebfTAGMWmSd5hkOySZMmubldZ5113DeHAgQSMZ13Sg/OktTH+HiOuAF8g3Bp8A8LkDPzGJbyKUn9Pb3H4LanErTnTQJ9JwGD276TvbVsEuh1CRjc9rqIe60BzP/OPvts+eUvf9m1kfQbY+OMHy5my7fffrvzx6UAjgShIoAVAajYNHIPG0g2bGhe8NOlfoUwNpDqo6saGepCKwPY8hxa2TDNTBTcal/9iLlBYaWJRJzFnLlYqh826cgqqH0rhZ9uHGADYGqC2VM/XeZGNeH+eHVuW9tbpdnz49VIzWn9eJc2ax4kI4Ys48yao/x01USc30kArRjYhr1oxQC7J2bvPtgGg3LFAbaOuRjYAm5obAFbTHrHjh2bSD699rFJUPFrr73mDsfQpNJnv+A7DKjyTuHLn2Su+Q6hCSaw3VprrZWgB+W9xeC2vPK21kwCpZSAwW0ppWl1mQQqTAIGtxU2Ib3UHQ30pD66bETZaAKkbDa33XZbl2bIz5nJBp4NJqbLBK9SM2I0MtzHbzRL/B1NDZqlKMCYOnWq29AGoyX7YKsQp3DA5jFMCxam0S3mk5pUpKrNCwPsKDPT1H66+YK0FLr76RYDbKAU7XES89ZgvxX2o0y8iwF2riYni5oXOrNml4s3ox8vffrUrLlO6nINMqxhmNTV5B3w+hrsKB9s6uC+nkZFZj1rYC9fVmkBuxjYRq1/9cP2x6v3Bs2zWfO8V77ZbRIYTLrOe+M+zIRffvll945vsskmoeuVKOzMOf78WILEFdKRMecE2ONArdKKwW2lzYj1xySQXAIGt8llZXeaBKpOAga3VTdlPe4wJswHHHCAA1u0IpgxU4Ag0giRXmjvvfd2EVl1U82GG8BFo8tvHzrV742gVGGb8CjNbZLAQklS7gAs9Ac4AgSzgEDQnJk6VOuXFLDZ7C6Y9aELSFXf3Cr5DPl0owIlpdFgM5dpYV8BmzH749XFpsGjFixeIAub5klrB2bN+PK2S2taFa+I+GbNBK/K5+qlUFMvQDXFDwzFXPQUbKnTN0X2zcTDfL/VPzj4sqUF2+DzmjvYT/fDPYAsGmDk/M477zi/WtwMeEezrOcefyRSVoD/L0DOGNZff/3Qp7nOfRyCcThWrCgscw8R5Pn/BJRCbqwN4gf4FiQpu1uS2w1uSyJGq8Qk0CcSMLjtE7FboyaB8kjA4LY8cq6UVn7/+9/Ld7/7Xfn2t78tl156qQNazB9JL4Tp8rPPPuu6yoZ6woQJDnT58f39LrzwQmcmyQaT5xWGMOHFNxA/XUBXtY1hcOtDXJrAQlFmpj2JRBznp5sEsFWziOyy++kWpD1fJ7WDB0vDkKHOJDoMsBlrVC5dH2yzwr76coYFStJAWL4muam5aUk+3sUe8KZPT+TMmglEJKOkvrZ+qVeG8WT1ryzmYxulOQ8Ghuop2DIgPwWSAjT14hsPLPE3/j+aTUxxs2js++Jbw6EX1hkEjVpzzTVDu0BKI6xA+D7ge1usEGGd7xLrjWjQBMkLar2REZYgwajn5Rq/wW25JG3tmARKLwGD29LL1Go0CVSMBAxuK2YqytKRK664wpka//jHP15KI8TmkU22+uj++9//7tpQfu5zn3PaXPzmbrjhBpdy6M4773SbcDQqbG6pVzVSbDgBXTQ0aIenTZvWZZasAMbvYHTYpEKIikQM+PlmpnH1xZnuhj1fzI8zCtSbFsyXRZ98EptP991p02S93Xd3zX405R0ZNGKENAwb4ebBz7fKdQ4QKJhvAhSAkGo404IgkIB/I9o1NPbAILIE1H2trsojDrBZB/9+5ik555xz5Llnn5NP5sx19Zx61qly2HcPKzot44eOl0Jdwa0l+uGXuHbDKk4TPCrKJJ52ff/zYvmfH330Udl5551lu+22c3mptRTL7cthDwDnchk3NnblRAYW+an0nLakEeMdR9u8+uqrh84v17mP7wKHY8UK3xQ02Cp36gVyOfBBqw0oIye+P5g590UxuO0LqVubJoHSSMDgtjRytFpMAhUpAYPbipyWPu8UG3E222hzgd3HH3/cbTQBFID1kEMOkUMPPdT52qrZJNeImKophjAlpAC6PAMosalVjWBPcoJqVGeNuuuDn6/hUQ0nwBssaU13wyZF4Th4rVi7xfx0fbhd9MorrtqmJX66hcGDZMiozlyhjFej0eLL6Ps7Z0mjpHBLaikiZ0cFWwoD++CBAqDGQceWW27ptHmf//zn3TqhX/t8ZR+ZsM1m0trRFGrWXJcTWXPkug4kmWPWlB5W6Bz7gF3sIEMhE1P7e+65p1vO5yQvWDHQTdKuD7f+eIK5fbkGyBGcjYMg5oJ3BxNe3ifksNFGGy2VeinJGMp1T6nhlmB2Guk9DGCRD5HeWR995ZNrcFuu1WXtmARKLwGD29LL1Go0CVSMBAxuK2YqKrYjaEpIIfTggw+6zTeQorlx8a/DbJnr/FvNKNmwszlXjS6aJ8yY0b6g9Qpu8JMOPomfrvo1AkPBlDtAJ+1n1XD6/dR8uqrh5Bob3qh2wwA7mE93+rtTujS3Crd+my21ddJcn5ea+oKMWqUzgNcbb7zhgDRotpkmly4pXJhnImczN5j/xpnERh0o0KcnnnjCafoBXP5drDS1LDFrbmt0t620zGpdYBuWMiiq3eB4H3jgAZf2aptttpFHHnkkk++qb4qMXBR4w9aVzm9QcxsHtkAcZri8I6qB9+VFH8LWTtJ3phz3ldosWX146XtY9GX+zprlO8Q3hRRk5S4Gt+WWuLVnEiidBAxuSydLq8kkUHESMLituCmpqA5hHvilL31JMFEmTy5aXMw8CUqFny5ml6qhxUcQoNl3332dpknhiOukIQKYFG51kGki1QKtaLEoSf10o3LLUkcWDaf2O85PN0lOWwV16lTz7NdeekE2/NxmrpkwuPUXx+ANNnD/d+ITT8j4ddaWwqDB3fx0gwCmsg4LUOSPh/zGaYMYMV7mWbXyN910kxx99NFy8MEHy9VXX+3gLEmdPggmyYUbJWfaAqqJAB40D076gvnrLWhlUGx+n3rqKdltt91cuw899FAXqIdpbKdMmeIOgTj4AWyLmTsn7Xdf3FfqgFIcPmFuT0Hrj3yCBcuSGTNmuLRDAHC5i8FtuSVu7ZkESicBg9vSydJqMglUnAR6C27xy7z88stdegg2gvhFHXHEEW7DG6cRqjghDeAOvfjiiy5N0J577il/+tOfHFRqAUTQnPzjH/9w0Hv//fc7PzgKm01AF60uZrMEkdlggw3cBh7QUQ2nH6m2GOj6GrSsfrrUQf+CGs5iKWjCpt7Pp5sEBKNS7mjd/niAHQ3Is3DuJ7LokzmSa26VhqYmqenoHpZY4fb1e++V1VZZRRoLBRm19tquWsYKYF588cUOEoA9os7+6Ec/cppMNZvm74xnvfXWcybEBPEhQq+WL3zhC84kHa09gHHWWWcJ8IaWF+g47rjj5Mgjj3TvOAcP//rXvxxQhhVMp9EyayAl6rjsssvcIQm+3KwJ1g1r5sQTT1wqV6rWSXRvgqE9+eSTDm7oF8/tvvvu8p3vfMdpQFmvXA8rYb6wf/3rX+WPf/yjvPDCC0JOVtYruaBPOukkN84wzSkHPL/5zW/cN44xbbzxxnLyySe79YUMkPNdd93l/n8YqDPXvD8aPKpawRYZJ0kFhJy4L0kqIN4Zvj38xkxb/cv9+UR+RG5PEqCqNz7hBre9IVWr0yRQHgkY3JZHztaKSaBPJNAbcHvssce6TSubdrR9bOzQYLBpRKtHrlUD3D6Z7kyN4oepPpNRFbCBx2fw7rvvdqD7z3/+08EOwWMAn2uuucZtUtHu+qBQLNeqAphCKW2Xyk/Xj0ScJhVMT/10aQstaTASsaa+IegOMlJAVXm3tTTL/FkfSUcTaYaapa6tTXy4HbvELFP/dsoxx8hvr7hCtth8c1l51VUdgAGQjJvDiM0339xVrQF7yHUM3BJQyteCKdyecsopQpRs1sFnPvMZF9AHbT7lV7/6lYNKCn//7W9/6+oBgplzTJMZN0GBgGMKPpr77befsLZYI4Ah8/388887YKU/fDOCUENbP/nJTxww0g9++K4A5bTJuttiiy1cX4FboBx/b75DOl7GcNppp7lvEICCdhnfctYWgdO4H39OrA1onzrxG/bLr3/9a1cHhfHhS84z5I/mAO93v/udS6sF3FI0qjjWC6x/gndhFcHhSPCdyPSSVsBDjJ13PsyMmDli/THHzG0SLb6aHTMfwRzarCcObXiXOIwhHVm5i8FtuSVu7ZkESicBg9vSydJqMglUnARKDbdoYfbff3/nA4jGRzfq+GShCWEzy8bzhBNOqDhZWIdKIwHAg80sKYduvPFGByCAgGrANAIsGivd5La0tcj789+X1rZWaW1plfaO9qU601DfkMn3kI3w4sbFDogK+YIDPL+4aMAh7dbW1EptXa3k6/Kun2g4ua8mV7NUPt2Vhqwk+dp8rADZEKt2m8Mf9eHUdErAISbdFLRcYYdAbW2tMu/DmbL8qp0RZ9HcBuF22REj5M4rr5RNP/MZaa2tk8V1tXLKz/5PrrvhRgd6AC71qxZb4RZA8f0+FW5phzRSWF9o+ctf/iKHH36405yikcU8VLWPaPm/+c1vyte//nV3sEGhLcbPD9GESTt11FFHOeD1ZfH9739fqNt/lufvuOMO921h3fz5z39eSkMMTAPQpJkBIh977LGuqMX33Xefa9fP4cucnnnmmXL++ec76wTqxGxeTd+vvfZap0EG0AEpPZRBuwtA8/wtt9zSrR9octGOU4BbwJii6X74NxDNIQlWEFFa4diFVIE3aIRjAJZxacAz5A7Ysu6ZGzStWjT4HJDvWwxwnXlgPSJn1iT+/rqOMEnmvym0hUVIXxyWGtxW4CK0LpkEEkrA4DahoOw2k0A1SqDUcIuG47nnnnMmrGxO/cJmc4cddnDgi4aqLzYk1ThH1dZnYBFzzosuushp8ImsjFZL08qophRYYMMK7M7umC37/GOfahtqV3//vvffZezw4ulNfLAFvnwzVIVctI9s1imYrPKO+Lll/YBaqtV85fmJssIyy0pdc6ssu06nWfJvTztNjj744G7ynDlrlozfcUepLxTknf++Kg3DR0hdQ4MDBExFAWuNvKztEpCJQ6qvfOUrgumuXwA2QBxwQUPKu60lDG71GsCH2S7aY0zZfTNxQAbo/uxnP+s0m2h4dZxoVekfWlHVFGudYel+wlLy+CmViOjMwQvzALDyXQpG8sa0nkjLaHbV3Bogx4Q5CN/aF9JkUR9myfRBC7AGzPFbUy1hQq2HPX2Vr7WULx0aaeTKPDI2fnPQxaEC4+SgwNfafvDBB8IPByQAcbBooCr+DgBzMKXyY944POWwoy+KwW1fSN3aNAmURgIGt6WRo9ViEqhICZQSbjlN52SeDQgBRoCZYCEaK2CLyeBWW21VkTKxTvVMAgAIG3sAAE2bvwkkByYaHMCNNaIw8WHrh3Lqm6f2rOE+fDoObv3IysUiEfs+t0CBb77s51pF60c9FN+UWLWLzz/yiKy9/GipCWjAV956a5kzb56888gjssJyy0tToSCthTr5/Hbby3tTpzoNLJFntV2CifGukh8Zra0CufpAH3bYYc70Fk3rAQcckAhusdoAUM8991yn3dd0Pzys7X7ta18Toh3j10pwJnwr+XYAgECv/22JymMblW9WO4n5PO3gq4uFgV/0QAErEzSxp556qpx99tnuFiAMk9l7773XaYb9AnjhD3z66acvFciK7yPgh0YTyMPnmHcAc35kwEFBfwBc0vgwTtWAM160+pifB82R4+AW2fIeYKqOvIBkZMShGIcRfgyAcr/+Brfllri1ZxIonQQMbksnS6vJJFBxEigl3GLqiKZjk002cb5zYQWfW8wL2QDim2ulf0qADa76wUVtAtnQL1iwwIHu6zNel1PeOKVqhXHbnrfJ6susHtr/uMjK/kNovgAfCnLTnLbAsW9Sy3XVaAJa+HxSFG5dBOv2dpn30cxufrrr7rabvPfBB91MmXlO//7cY4/J6muvKUOXG+3aA94IEgVkEoiJ/qj/KM8df/zxzpyXiMiYKGspprlFA6rmunETfuWVVzoAnThxouyyyy7C4Qi+sFqiwJbrcXDrmxDH9QOwv+qqq9z40SDSLhprnSueB+aQGWPDj9cPXAXEoYUE9MjL6pvG8wzghqbTSvVIwOC2eubKemoSCErA4NbWhEmgH0uglHBLZFa0MuQ8xYwvrHCd+zBbZXNppf9LIMkmsLm1Wd7+8G0HAEBCfUO9tDS3OOEMGTpEhg/rzJPrm7I7E9MlvrJt7W1dgvQ1nFn9dF1KmsWLOiPd1uWX0hC1tLZIW2uba58yZvAYKdQWuqIQq4YzbYodNF74fVLQ6mFy6aekUc0e2ksNsvPOO++4IEiArfo5BgNWMY65M6fLJhO2lKnTpkXCrfrvttbWOq3ulw89VJ56+mnBZxUfUubSLxxQERk9DdzusccezhyZ+gg+VCxK8De+8Q2ZMGGCPP30085XGL9MDs4YK2NCNlEpneLgFs3xGWec4UxbcaegH36eZg5faIMffGwxQ+YeNJBBuFWwpV+MjWBZCreYVqN5VB/boM93//8C9M8RJvmuLbWhThJJq3+Ky0ZlEqgoCRjcVtR0WGdMAqWVQCnh9pe//KXbLOJjef3114d2lOvc9+1vf1vQyljp/xJIsgkEIDBXBwIwbUc7hkaXH82jq358+O5hlhjms8q9fvRjntGoy0lTrfh+rcHcpGGzBUhqaiO9Trv8UFeafLrAGkGR0OShrcT/1jfvVLgF8PBZBX7xldU9s2pzMf32o1IrfGH6yv2vvvCcrDByGalpIc1Qs6y3266hGt3djjhCnpg4Ue64/nrZeputpWbQIKkp1Lu66SuRgTHpxcwY+NN0Ttddd91SAaWQDfNMoCmuE8gJzW+SwrrALJn5oP++OapGmtYUQ1pfHNzyjQKeST108803RwYrcwHHlswx/8YyBfNxtNlotpEDP4wdc2l8zTm8A24Bf+CWfmPO3JdmtEnkbPckl0CS75rBbXJ52p0mgXJKwOC2nNK2tkwCZZaAwW2ZBT4Am0uyCcSMefLkyUul9XAa1EWLukAXjRkFmEOTq6ALWKDNxMwZOAQmAI6gz2oc6PpgC4ik1bLRnoKQP9Xabli+1OCSwM8Vf0719eR6MAUSh0RoHgn4hDuAjpVDAQqHAhSFUOTIvwnUhOmz76fbsniRrE2e2/enyX/vv1/GL9Ec87zC7b3XXCPbbbaZq7OxUO/8dBuGDpFjf3CyM0smcNhBBx3UNRRy7AK++OTie61gC7TfeeedDoSD+WbjXg3y9JLSCMsP6vUPEPRZDhJU1mh7aQPffoJi+QV5AajIA5khD9ZSXEGO5PVlzBzi4V6hhbWCjNFIczBBiiD6yt8xRVatelwbdr06JJDkuxYcSc40t9UxudbLfi8Bg9t+P8U2wIEsgVLCrZklD+SVFD32JJtAhViFs7DauIcUKqrR1ZQ67BfR5M6dO9dpMvHL9M2XozSrGjRINbq++W8WsNU++7lwqZv2/YjA2m4U6D788MMuiBIwBBhi5u/fC8wCkoA+JrCk2NKi9wGRyN1vl74Ac2g+g/ls8R0Fet968w0ZNWSwtDc1S31Ti+z59cOc5taHW39uvvmTn8iN+NBfcL4cdfQx0tbe7tpFK4rJMv3EQoO2tT/0kcjKRFXHguMXv/iFO5DwC5paAlV961vf6vozrg5f/epX3aEG6YWQi5qgU/czzzzjAhcREItCACc036SeYWwqGw4wkA+FnLkAKgHQCJpF1Gi/KIyTEklT2NBvwJU1RiAt5go5Uy9WKeT5pQDj9NNPi2NfiP4jgSTfNYPb/jPfNpL+JQGD2/41nzYak0A3CZQSbtHIYOJXLKAUKUXYpF5yySVy3HHH2WwMAAlk2QTGiQWY0KjLRNLFHJnowfwGCqPSq4RpVoNBkng+a9RaNf8F5jSaMWNRzWoQONWM12+Pe8477zz52c9+5qCJdDXrr7++Ewl5P8m5Sp/POeccOfnkk7uJSgGOOuiLmkVzE//WfLavvPKKC4akprwKtz700vYO220rT/77afnHn66TnTbdZKlp+fYZZ8j1d94pV551lhz8lf2ksb4gufq83HHfAw5MCayEybIWNRPHt5pvBf0AVukX5ujM6dtvv+3GiR8xpupagHlAmHFTAFfkQjRdgkzRd1ISoTnVed5+++2dthfA5LvE3OK3izm0alLRIpOvljnbeOON3XX6iWaXZ2mXVFY++JKb9+c//7m7D9AloBdjod+MGbgHboFfAquxHrOuqbh3wa73jQSyfNdMc9s3c2WtmgSWOmgykZgETAL9VwKlhNupU6e6IDfFUgGxgUWjQgRWNqFW+r8EsmwCk0qFvKFoIgnyw7pDq6s+qtSBJlhBN2hiDHDSt2CQpDQmxNpP1Sr7vpdRYygGusCS9geIRZtIKh78NikEm+K9OeaYY5zPbbAo3KLFBmYZi0Ic/3/NNdfsls+W56M0uhwUEKGY9knLs+XnNpXF8+ZKTXOrNDQ3S66jQ3y4PWyfzjzFmC3f/q8nnG8t5sMcZCEfP9AX91E/8MdhF/CISTkgiOYVKEUzq+nC/KjI+BsDzPSLgw209gSmIlAVB2a+FhjgJS0P3xtM35E98iOisZoR0xe04WjJn332WVcnwI2sCTRFBHjqVjhVzfzdd9/ttL4AMHInDy/aap4nxRHQi/myzgVWBZgnW37vpG93Zd+X5btmcFvZc2q9GzgSMM3twJlrG+kAlEAp4RbxscFj80kqEDQifnnsscecOSL5CdHI2CZvYCy4LJvAJJJRsCXQEGuKAkQBTWq6rOanXEOTCugSdElBV/NxAkS+f6q2H2dCrG2qllSDCiXpP/cAnBqMyg+Exbuh8JXGTU/Nu4NgG+wP92m7fooh2tVIxJqKKCwvb2tTo8z/eJbkmlqkvrlZatvbu5pYMHSILLvqam5syIW21MzbRbhe4pcc9IcOmolrhcXS/SSVs29yHnYgoAcacfWhWUYuQc08z+HzrebPRGBWE3vkQC5b1qKaTMe1Y9crXwJZvmsGt5U/r9bDgSEBg9uBMc82ygEqgVLD7a233ur84oCNJ554wmmKKIAIvoGY7V144YUuZZCVgSGBLJvAJJIBelTbF3a/gi4pdYBd7tVCgCY0mvwdoPP9ItOYECeFybjxAOQaLIv++KAbFQ04DFgBKPqUJMqzPq/AyTwFc+kCffwUizTd3tYm82d9KO2NTVJobpHc8qOkYfjIpcA2TAZRZuJqrq3+0mkiTgfb8SFbTc7j5pj2g4cKCrZhfWEdYcaMnNDOFvMdj1sLdr06JJDlu2ZwWx1za73s/xIwuO3/c2wjHMASKDXcIkpMJi+//HIHD6TKYHP80EMPOe0FpoYAcNK0LAN4avrN0LNsAks9eNVUKujip0kBVABdzFDR6AYj2haDINYwUOpy4Xrmv2n77ufCVS1pMc2qahl9y4e06Yui+qgAF7yeJqVS1ojTvkbXD4RFX7L6QYeBbRj8hmnP/UMF5oh7wsCWNUWkb64BtpgfW+n/EsjyXTO47f/rwkZYHRIwuK2OebJemgQySaA34JaOkN8RvziCrAAIBGMhhQbpQcwcOdNUVe1DWTaBvTVYP58u8ALYqraTNjGfVdNlrvklyoQY8OO5MG1f3DjCwDb4TJRmVU2IGQdQ6pv/xrUbdt3vC5pHxpU00rTWlxVsg/1Rv9bg31Wjm0TWScA2DHT9nLb+deTBmvAP5vCnBWy5hikyhyRWBoYEsnzXDG4HxtqwUVa+BAxuK3+OrIcmgcwS6C24zdyhPn6QDQs5Me+55x7BR5gorIADAYsIEEPAGvyGrSSXQJZNYPLak98J/BF8Cj9bYBQtm+bDVY0u1gWqNeSagq4f+Rj4wcQZyAkGSeJvqlmN85UtZnlM2RoAACAASURBVOYaNapiJsS0jYYzy+FRkr5EaVb98QKlpYJs1ZL6WuyguXaUrEsB2X6QMJ0PfIgJGDV8+HAna2IHMM+4XwC2cXOefLXanZUugSzfNYPbSp9V699AkYDB7UCZaRvngJSAwW33aSeVCBFiKfgNEyALLRa+wkR0pZAb88wzzxyQ6yXLoLNsArO0E/cMsEJEb0ySAdtgahauY2WANg4fSkBXYUpBF4BRoCGfLn/nnjBtXzFf2SQwGTeeqCBJaUyIaSNLXzTSdDCHL/WVwkQ7ysc2TtYaLToYyCpOlmHX/UBWaGwZMwcjxA/wzaY5ACEHLubIlQq3RIqm73r4AJiTE5hDu572mXoJpEUhfRMR8wdCyfJdM7gdCCvDxlgNEjC4rYZZsj6aBDJKwOC2u+Aefvhhueyyy1zAq2233bbbxZtvvlkOOeQQt8nlPgJkWYmXQJZNYHyt2e4ASgCkOJ9vvU9BV9O5qLaW6MqkoAn6VybxlQWagMKeBEnywVb9UdOaEGcF26DkmV8AOVjSmBDzbNqoyFGy1n6kCaoV7HuYibbew6HHBx984HxwWUt6AMJ4AV0iIldSTlvAEwAFYtE481sPbugvOY6zAi5yImWVysDgtvh3yeA223fbnjIJlFoCBrellqjVZxKoIAkY3KabjG9961ty9dVXO/9hfluJl0AlwW18b5e+A4hiE4+JOgAJNCnMATRALsGogpq7YibEYf6bSfsWBrbBZ+OiENPvLBrbYDtB81/qjQrOVMxcOy3YBvuhoKsRp/W6+iXTr7gDDX1GI1czR+p7rNfwzyZ3Lu2huWfusQRA049pO3Oz8cYbJ24r6ZxnvY9+TZo0ycG2HxGcOXrzzTfdGiD3OJrntAUZ8E4gE9Y/2mGDW4PbtOvI7jcJ9IUEDG77QurWpkmgTBIwuE0naIJk4Xe76667yn333Zfu4QF6d7XDrYItsIM5M6CE5guY4UfztQJPwA7aMNWQ6ZQDAn7gqiB8AR9JfGV9sMVUVs1wiy2tYibEYQCXdJnGBWyKMyFmzLTfU7Clv8Fo0chSAV/HQ1tRuXSTgC2mzoAt8gRsATpf48kcA4vBQGRJ5dkb9+FOQb/HjRvnzJD9ApQDuMzDhhtumFp7q3mmgWNkgjbb4NbgtjfWsdVpEii1BAxuSy1Rq88kUEESMLhNNxnf//735aKLLpLDDz9crr322nQPD9C7qx1uZ86c6bRSRMMNmpsCVUCCgi5jpQC6AC4ApH66QAYgAPz4wZl8+FLtZpiWMQvYBpccdajfpX9NoS8JLAdhMkmanigTYg3I1RPI9g8OCBSGZt0vxcy11XSa+32NraZk0nqQ2dtvv+0gDlAcNWpUahgs9+vPeF5++WXXz0022ST08OSll15ymnai2adJYaTmyMgJjfD06dMNbvP52Ck2s+RYEdkNJoGySMDgtixitkZMAn0jAYPb5HKfMWOG2wTif3nnnXfKXnvtlfzhAXxntcMt8MRPnGYV0CWKskZeVtAFZoEjgveMGTNmKZNVNeNVDTBLJRgUimvUQUmqsQ1bcppih7EApQp+foCkOF9ZxokWmpIEbIP9UHNtAMlvV02Ik2qxqdcH2yQ+tlERn2mbcSH3MLBFY8uzY8eOdRrQrD6q5fwMsA7pN+NZf/31Q5vmOvcRBAqta5Ki5sis9c985jNuDaC1Nc2twW2S9WP3mAQqQQIGt5UwC9YHk0AvScDgNplg2djuvvvu8tBDD8lOO+0kRFW2kkwC1Q63yUbZ/S4AgM0/0ZnR2AIY/Aai0ORiuowJc1BDG6Zl9GsuBdjSpp/aiPqjcvgGUxsl8fdNIi/fFBmYpd5icB9WZ1qwDdahbaLh9AvgqpBLP9HY0jcAsBTRhZPIpxT3YHHA+mOtkaoorJAaC/NifG6xKkhStF4CZ3FYQzG4XTNREDHT3CZZYXaPSaD3JWBw2/sythZMAn0mAYPbZKLXQFJsAJ955hmXJshKMgkMVLgFHMiJOn78eJdXl+A+/GjQIwBKQRcACQNdwAsI05LEbzRsVlRjGwa2wfujfGVVu8n9WTS22k4xH9ukEZ97CrbaFz/Ss0I2c0R0YTTBaLHVnBzNZjVobHVsmAqTtorI3vgIhxWucx/QjlY6ruBTjB8v87/eeut1ycPg1uA2bu3YdZNAJUnA4LaSZsP6YhIosQQMbuMFSlqgiy++2AHt448/7nwvrSSXwECEW7RhaM1IswK4agHKAE0FXY26DDTh84iPLhpdoArNL3CMfydwrNDpm/Kqj24xX1ngDEBOArZJQVdz+NJunLm2X2ea4FFREZ9pm/EghySmyFEr1QdboiLrOKhbox8zB7SD/Jkb5jIYQTn5m1DeO0sNt8iBAFSYpAO2vvbf4Nbgtryr21ozCfRMAga3PZOfPW0SqGgJGNwWn56TTjpJzj//fKfZePTRRyN91yp6kvu4cwMRbgFRIBYQiioKuuqjqz613A9EEagKeMWk1A9kFRX9OCwoVE/AVvvtmyLTD8bma5OBQoXsYqCbBmyDMksz5iTLPQpseRZtOabI/F5ppZXcYYOvdS+mCU3SdrnuKbVZstaHKTImyX5JC7cEugozB2cd8c6gJceqoZJLlu+amSVX8oxa3waSBAxuB9Js21gHnAQMbqOn/Ic//KH8+te/dpqzhx9+2KXLsJJeAlk2gelbqe4nNI0MqYbef/99ueKKK2TLLbd0g2LDr1rDYLRm9RtFxsGgUEAoptFnnXWWPPHEE863kvuPP/54d2CTpERFaI7K4RsVFKonYKv99E2RaUcDfel1PxDWu+++6w4FMLUlz6tf/OBcaB99c3DkSO5WwAuIA27VFFnnCLkWO7RIItdy3FPqgFJobTlw8bXcOg6dX9YnJsvMTzELF4VbIorrmta1ptCbNf9uULaTJ0920c7D0iH1ZB6yfNcMbnsicXvWJFA6CRjclk6WVpNJoOIkYHAbPiU/+tGP5Nxzz3VQQRApUmlYySaBLJvAbC1V/1PAGED6pz/9SXbZZRcXyVYjEzM6wAJNIusymPImCLrA2M477yzPP/+8MyPdaKON3DPUe9BBB8UKK2nqIQXdsLyyaPSI1AuovPrqq86UNYvfKm2ghQYsfVNkHTNtc00LBwQbbLDBUnAbB7ZobAE1XBDQTmbpa6xgy3RDklRACplJUgEp3CbpPgcGxb6Z2i5phHwNLXOIOT8+z8ieOQyu8yTt+/cY3KaVmN1vEuj/EjC47f9zbCMcwBIwuF168n/84x/L2Wef7UxDiYr8uc99bgCvkJ4P3eA2mQyBWLRd+EpyoPKFL3zBaSeBFDVdxgdUC6CooItPKAV4Aw4wnQXwANpVVllFXnjhBefHG4x+HNWzpGAb9rwfFApQpw/A7euvv+60dGE5fItJyAdb1QyG3e9HfJ4yZUpXu//973/d2IEl9XEOamzpM2DLdSIHI7NqBluVD8GfOBQI01qihQVYkSlWKT0Zb1az5CDc0m/m8cUXX3S/S6FtNbhN9v2xu0wCA0kCBrcDabZtrANOAga33aec/LVf/vKX3R8///nPuzyOYQVNB9pdK/ESMLiNl5GCKZGVgdJHHnlEdthhh24PAnnIUkEXONGCKSigyzU0j/iIv/POOw6Qt9tuO/nnP//pwNfXbkaBbk/A1u8woIhJsMIt2jpKmojPScE2KGHGjok36XteeumlbpeBObSB6h/sgy2+noB4T0Av2WyX567Zs2e7dcCYAUnWCYV1BNgyR0HzX8zX+cFKgPWYpJQSbmlPodxPN8Tf8X0mzziHPIxBNfmYN2NG7mt5eQ9eeeWVyO4HwZl1gF+xvkM8iLxwS+F9CvqTZ/mumVlyktVk95gEel8CBre9L2NrwSTQZxIwuO0u+muvvVaOOOKI2PnYfvvtXYApK/ESyLIJjK+1f97Bhht/UR9uv/GNbzgz5T/+8Y+yzTbbyE9/+lOn2WUTDrxxGHPAAQd0ARlAs9tuu0UKCE2eggG///znP8utt97qNKsEtQIoyOl82mmndeUxDVbGvRdddJHrJ+lkgAAgCTPo4447zpn1kj7rxhtvDO0H9yrsajAqxnT55Ze7VFtADFCx9dZby4knnigbb7xxF5j5FeJL/Itf/MI9AwhjxkoQOO5Xn9s33nijS2OrzyIjIJ4DAf4NLAEwyLO/gK2OlfWkZr5AIOPjYITxY51CRG9/zAqqmAsDxElKqeEWKAVOgwA6ceJEB5nkewZkNXAb1g1o5zl09AGegyLmlrqIRq4WDoxpueWW6zKJ5p1Ac8/7QL3UT8GaAuhFFlhV+ICb5btmcJtkNdk9JoHel4DBbe/L2FowCfSZBAxu+0z0A6bhLJvAASOcwECLwS0pqQBcNuWbbbaZ064Bd2y+8aH9wQ9+4DbmgMwFF1zggug8/fTTDtrws9V0Qddcc41rFQ3YXnvtJU899ZQAPQAhsIemE3NiQI9AavTJL8Dwd77zHWcuTf7UTTfd1P0bLS0mwATDAra5jwOg2267zWkB99tvv65qMJsGSuk7UIoVxJVXXun6iMUEZsEEdgKAgZW//vWvsscee3Trx0033SRf//rXHeDg3wmI0Ydnn31WkBXwjQ8zJq4UgAVtNW0iI19DB/QA3MghTWqjalmnrAXGDMRRkCnriLURhPm+hlsOWFhHYT63HESwRn3TdtYPfcacn/lDY++XOLNk1g/tAcAc7HAwozJhraD5njdvngsuxo+WLN81g9tqeWOsn/1dAga3/X2GbXwDWgIGtwNr+k8//XQ555xz3KCJBH3yySf3ugCSbAI7mpuledq0Xu9LbzVQIPhQodDj6ovBLZX/3//9n9PcKoABn4Ar5V//+pdsscUWTiMHuN57771y6KGHOvgEHAFfNHWaq/Xggw920Ah0ksdZ85by/Jlnnun+hqb4/vvvd9BJm4Djtttu64AULStWDj4cAcbMt+ZBLRa1WIVFPd/73vfcM1hO+HCCOTUAi9YNzRqBtCgaqAqt3O9+9zsH21oYE+MGWlRDDNj6uYC5BghrxGXGgJaOMSIf/G6rISJyjxdcH1UQFlAKkGQO8BnHXJrDFczEkxZdexx0+PAbB7ccEnGYw9pCix0sHNygSaZOTOx1vSf5rgXrMrhNOpt2n0mgdyVgcNu78rXaTQJ9KgGD2z4Vf1kbB0xIL8PGnk19JcFt0+TJ8s4Xu2vmyiqcHja2+j/vkfqE/onFmioGt2hr//Of/3SDSTRKX/ziF532FTA8/PDDu6rHZBifW0x7MWsGeNXnls08UAv8Pffcc07rpVDHJp4N/eabb+40WkAzvueA3yGHHCJ33XWXnHLKKV2HJNpgWLofAjtFpeThOUCaMdM+wIP2Fc2dn9aItv7whz/Ib3/7W5fGCLhA6/uzn/3M+RMD+MGy//77yx133OHGBxSHgS1gDNDgV8rY/MBdaO/QEFrpHQmE5bnVlphf1kyU/AFf1jLrTb9lPMvfAGSic+tBDX+Pg1vWB89ihYBFQVgh0jftfvazn+1m9vy///3P3R7MRR0lNYPb3llPVqtJIK0EDG7TSszuNwlUkQQMbqtosnrQVTaCaDTYxAEtbPwNbnsg0MCj5YBbtLYAXbAAfJdccomDTT/IGSbBO+64o+AfDugCAsAw/qyXXnqpM13+6le/KmeccYarEpNMAFc1U2hT0apyL9DMGkKbhmkr6YUAUfxlAcOoPLZxcAtYT5gwwcEz5sOa7gcYxVQY7dgtt9wi+B0D40Au8I2fMWNCI/3Nb36zm0gAZp5Be0t/MSvVggz4//icMlaApj+aIZduZfdOTWF5bplr5oWDjaD/LL3g71gCzJo1q2inghGY4+BWwTXJSP2USaa5TSIxu8ckUJkSMLitzHmxXpkESiIBg9uSiLHiKzn11FPlvPPOE6JB/+1vf3OaPIPb0k1bOeD26quvliOPPHKpTgO8P//5z53Jsg+/Ptz6wc+AhGOPPdaBa5KCiTLm7DNmzHC+sIAH/pvBAhRjyuubKcfBLYGsDjzwwCTdcFro22+/3UE6BzRo3FjPBLECsmmXa5i2YkaKVhefW8yPFY7UfxKtICaoBraJRF/ym6Ly3KI9Z17R3rOWgEldT6w/AkQx12jkMVVXc3k6SJAz5j4r3LImfA1/2KDR6GuwKYPbki8Lq9AkUDYJGNyWTdTWkEmg/BIwuC2/zMvdIqasmKYS5Ocvf/mL04JVGtyaz23nqoiLlszcBUtauOX5o446ymlBMeEkjzPmnIAFP2q6DPgBEvvss48DUDRmBNQBADDR5Bk1DdU+BdP8xMHtzTff7EydqRcNsz4f9o4ALRzSAOdoegk4hQUCz1Hor/adNDf4Hyvc8oyCLUGHMCM1sC33l+jT9qLgljsAW1IBMWeYjBM124dX5g6te7Cg+WdNpoVb1hEWDVH1RknJ4Lbv1o+1bBLoqQQMbnsqQXveJFDBEjC4reDJKUHXgBCi4BJllA0jEVIrEW5LMNR+UUW54Jb0OhdeeKGLsIwvqxbgEF9UTJeJJswGXsERTRmm7ZgOA48ABv/GT5FgVZgD6/08A6iSJggQ9TWo/kQ9+eSTDk6p9/HHH+/SisVNJkG01CyZgFO0S/ta7rnnHgfNtItfJJDNeEjpAsT4AYfi2rLrpZdAMbilNXzCCfSEaTp+rqwlTQ8U9KnlfuAUSKUE4Za552CGtUB06GBRjTAQnTSvL3UY3JZ+XViNJoFyScDgtlyStnZMAn0gAYPbPhB6GZsk5+f5558vpE1Bc0sxuC3jBKRsqlxwS4oggosBephzhpljojnzQRetLusJCP3ud7/r8tgCi/it+qbIaM/0R6Mao5kFPmjHbwsfcPKH8pvgVfQnSTnrrLOcKfYOO+zgojkD2eqryfOALSbLY8aMcQGnMFfFzJW2DGyTSLh374mDW8ARmOWwRXPdauCnYD5iDvC4hhVBGNxqaiMiYGPOHCwcirD2WN+sU+4LrhHq5l1QLbLBbe+uD6vdJNDbEjC47W0JW/0mgT6UgMFtHwq/l5smgi5pW/bee2/nq6jF4LaXBd+D6ssFt3Rx3333dWa9/CbtD/60fkF7S1odAjax2QcQ0ZZyPwW43HPPPV1kWqIO47MIZFDwlaQAHmh2gRSuqTkpgMvf+LnqqqucuTEa3t///vfOn9YvQMd9993nwFTrRSOMBo8+kc8W7S1aPjTI+JST95e6CZKFFpc6NM0PfcU02SC3Bwu1h4/GwS3VK5Sq9pa5xmKAQwzy9OL7CpgShAqrAj2MCWpuOfjAaoXCvLNGKFix8ByFe9Dws05Ym9SNST71s4aBWw5HSFelxTS3PVwE9rhJoA8lYHDbh8K3pk0CvS0Bg9velnDf1I/fGjkZCfzDxg4NlhaD276ZkyStlhNuMeXk4OOxxx5zsMB6oX20rvinAiBs7llLXKegYcWMmcjM3IcmDJhgo09+Up4DNsk7qxpaTcuDWSiRkYEVgFeDX3EfEZsBbMqGG27otMFACBCLLyVgQwqi3XffvUuM119/vQuwBcRieg/40v4zzzwjJ5xwgusH6/7BBx905qZAEMDOb0B3gw02cABjpfwSSAK3rD0iGbO21KQYCGVN8Jv1p2uJQE8cnjC3QbhldLhlzJw5061l9ctWjbCOnvr4XmK+DtByH2uTdQgUcyjipxgyuC3/urEWTQKlkoDBbakkafWYBCpQAga3FTgpJeiS+lRec801csQRR3Sr0eC2BALupSrKCbcMAYC44YYbBFAkvQ8bezbxmGcShIyUO7vuuqsbLTAMQACmQASphDD5xWcRTReAgdb1a1/7mvs3JstoaoGGn/70p858mHsVijE7pWhOW/xvydWLyTT+ltQJnAK7e+21lwNxtGf6DMD7xBNPOLN7cjhT0P7iR0z/sVrgNz6XPsRqypmonKa9NLVWbT+TgMFtP5tQG86AkoDB7YCabhvsQJOAwW3/nHEgCU0aG/xgeeONN5wWA+0Ymjf8HImc21slyyawt/pi9WaXANosAvNg6uv72GqNQCr3aDAqtGtaMP8EdLUO1icQTUFDxhoBelWrxt/VP5fffnu0A9jyG60a2ju/kC4GDRxwvPbaa5t2NvuU25NFJJDlu5YLe3FMyiYBk0DZJWBwW3aRW4MmgfJJwOC2fLIuZ0uqAUzSJuaomH72VsmyCeytvli95ZEA4ImfIppgYBcY1VQ9QC4aWH6r/6P2Kgp08Y9F+8pvNS0NA1tMVtH6YkYN2AbrL8/orZWBIIEs3zWD24GwMmyM1SABg9tqmCXro0kgowQMbjMKroofM7PkKp68Kuw6oEtwoOnTpzvoBHrVFBkfRiCXn6AGFtBFmwtE+BpdRADkopn1FWHUj9kz9eB3aWBbhYulirpscFtFk2VdNQkEJGBwa0vCJNCPJWBw248nN2JoBrcDb877csSYwGMijwn86NGjHayqRhffXS3AqoKuBrDSa0Sx1VQv+rePP/7YmTkTpRlYph3AFo1tEJT7cvzWdv+UgMFt/5xXG9XAkIDB7cCYZxvlAJWAwe3Am3iD24E35301YgJWEa2b3KQEmfILQIpm1gdd1egCtwq6+NxqiiHM7YFgjc5MkCstaHHJUUqKlyAc99X4i7ULnOMbjJm1preh78gqqWum+h8TxRpZaJRfNNuYflOf+jZXogyquU8Gt9U8e9b3gS4Bg9uBvgJs/P1aAga3/Xp6QwdncDvw5rwvRwzgxuWUBdK4T0EXUFPQxdcWkEBDSxA0v2CGjE8v13leCwAM1AHU+PpWWnn33Xcd2AKxpJnhN2PG/BqoX2ONNRIBLjBLuhwKhwCYeSNrNN34OVNGjRrlUjwlBeZKk1Wl9sfgtlJnxvplEoiXgMFtvIzsDpNA1UrA4LZqp65qOp5lE1g1g7OOllwCCrpAK5GPgVbMjDFLxo9WNbpEY+Y68IspMnAHHPMDKPIMqYEqDeoY16RJk1y/8Q1WLTPvyZtvvum0r5hwo4WOK9wLKAPxCsn6DCbfaLwB5mBO17h67Xq8BLJ81yygVLxc7Q6TQDkkYHBbDilbGyaBPpKAwW0fCX4ANZtlE1hMPGzWiYg7e/bsruBEgA1mmAABaWesVLcEANq33nrLaR/JR4vWFmjF/NYPLoWWEkBEY+kXzJ3RXgb/XglSwUwbMA8DToAUwAV8ye/bUzAnkBc/5BxGTlZKJ4Es3zWD29LJ32oyCfREAga3PZGePWsSqHAJGNxW+AT1g+5l2QRGDRvtHdDDbwAAoAUAABmAYcyYMbLSSiv1A6kN3CGguUXjiPYVsB0/frybY/4O2PJ3zJEBX3I0o8mtlsI6ffnll914Ntlkk1CT6ZdeesmZWa+77ro9PqjhQOB///uf0w5/9rOfrRYxVUU/s3zXDG6rYmqtkwNAAga3A2CSbYgDVwIGtwN37ss18iybwLC+aXAiwHbllVd2ppi+ZgttHT/VEEyoXLKv1nYAWAIuRfmKajAqDjiqqShsolFef/31Q7sOjHLfaqut5qJL96RopGrT3PZEiuHPZvmuGdyWfh6sRpNAFgkY3GaRmj1jEqgSCRjcVslEVXE3s2wCw4aLfyUaOzb8bPytmASqTQIKm2ib0TqHlffee8+Z3WNij+9t1uIfBiX14c3a1kB8Lst3zeB2IK4UG3MlSsDgthJnxfpkEiiRBAxuSyRIqyZSAlk2gcHKMEfFnBPN7AYbbGB5TG29VaUEpk+fLtOmTXPm1sHIzzogrnMfKYHGjh2beZyTJ0922m8sGdASV2LU6MyDq4AHs3zXDG4rYOKsCyYBETG4tWVgEujHEjC47ceTWyFDy7IJDHZ9wYIF8sYbbzg/24022sj5W2K6CewSTIpIsZheWjEJVLIEygW3GkiKgFv47pIayUppJZDlu2ZwW9o5sNpMAlklYHCbVXL2nEmgCiRgcFsFk1TlXcyyCQwOmZygpDwhgBTRkDHvDBZMPQk+FJdTtcrFad2vYgmUwywZ031M+NHUkiLJoof3zoLJ8l0zuO2dubBaTQJpJWBwm1Zidr9JoIokYHBbRZNVpV3NsgkMDlU1Xho1F39EzDbR2qLVBXxpZ9SoUQ5wrZgEKlECvR1QSuEZsF1rrbXMmqEXF0GW75rBbS9OiFVtEkghAYPbFMKyW00C1SYBg9tqm7Hq62+WTWAU3PL3MH9FzJRff/119xgpT6o1YjLRgQF1v9TX17sgWltssYUce+yxsv3221ffIujnPdao3URxLlbCUgE9/fTTstVWW8kPf/hD+dWvfuV8y7lv4sSJcvTRR8vhhx8u1157bawECUJFMCr6Athiqm8lXgKkEFtjjTVklVVWkWeeeSZxbuEs3zWD2/j5sDtMAuWQgMFtOaRsbZgE+kgCBrd9JPgB1GyWTWBQPKqR4u/rrLNOqEbqtddec7luAcTllluuKiWscLvbbru5VEeUOXPmyAsvvCBTp051///888+XE088sSrH1187nRRuGb+/TrE0mDBhgsvr+8477zhLhDfffNP5lj///PNy5JFHJoJbH2yJwjxixIj+KupeGdell14q3/ve99whAocJSUqW75rBbRLJ2j0mgd6XgMFt78vYWjAJ9JkEDG77TPQDpuEsm8CgcNSck79vuOGGUigUlpLfpEmTHAiSA3fMmDFVKV+F20ceeUR22GGHrjEgwxNOOEEuv/xyN3bGiqbJSmVIIA3czp4924EsAMuhxRFHHCE/+clP3A9g29jY+P/tnQlcVlXexw/7vggCCoqAsgoSrmmLpubSoJY1acvo+NrbpJapZUlOuaTOWJZZo6WOmpqlNdqimdlkm2VUagoqqAiiIMimiOzL6+/G5X18fIDL9YFn+53PZz6pz73nnvM9B+b53v85/yMdAYTVB1iOD1HFPnIILPacay+7l/ejow0UW3XzAZFyZKbGcm5kmdb1+0W7ZjW/1yi36saHd5GAvglQbvVNlPWRgBERoNwaQaZd2QAAIABJREFU0WCYaVPUfAnURiEv58S/41gTZ2fnG2hBDK5cuSKJAfbkmmJpTG7Rl7KyMqlf6OO6deukqB6LcRBoidyixVh6DilFlBDL6fft2ydJLM6mRWI0LJOV68T1cvZjZATHygW5YKUCIsEokGHIr66CiPDNnJlrHJRbtxWzZ88Wy5YtE++995545JFHmn2Ymt9rlNtmsfICEmgTApTbNsHMh5CAYQhQbg3D3ZKequZLoC4+kADsrUXEUl6yK1+HI4GSkpIkOcDRJ6aaIbYpuUVfe/fuLQ4ePCiWLFkiEhISrsOE/Z7btm0T69evl5a0QoIhw1jiPHfuXGm5tq6C5c7Lly8Xe/bskaQLUUJEv++66y4xdepUaQ+zZjl27JhYunSpQHQZ0UQIV9++faVlnSNHjrzuWuwTTkxMFJ988okYM2aMzuc/++yz4rXXXhPPPPOMJBea5csvvxQrV66U6kBUHst4EdF+4YUXpPOONUtGRoYU1UQE7vTp0+KNN94Qmzdvlv6MKCmi/3JBfejz/v37pT5ALPv37y/te7399tt1thPz66WXXhLfffedqKiokCQTfB577LEGEW1uz61mxV999ZUYNmyY6NWrl1izZo0kp1hOj0RpEFsskUVUFwKM8YbggjWiuRgb7L3+6KOPxJw5c8TevXslWQaf0aNHi7/+9a/SOCJz8tq1a8WBAwdEcXGxtBf3+eefF48++ugNfZTnHiKX6Osrr7wijhw5IrHD81599VWJL86cXrFihTTPsIIAe3vvv/9+ab+w9nFcaMfGjRvFhg0bpDZpl/nz54sFCxaIefPmCfxZLpr/jn3H4P75559LffT39xfjxo2Trm9sb72a8U1OTpbmFPY///jjj83+ilbze41y2yxWXkACbUKActsmmPkQEjAMAcqtYbhb0lPVfAnUxUdemowoFL6ky1EqfNnGF3LIDyK6kZGRipPCGNs4NCe36DdkTTtyC8bjx48XO3bskM40hQRDbPGFHecDt2vXThIg/Ltmwb/9+c9/lsQH0oD9n1iaiWWzEBssldWUjs8++0w8+OCDktx1795dWiKOY2cgAxiHv//97+Lll19ueMQ777wjJUW69957xccff3wDbryMwMsKSBiESlOksQz7zTfflPah9unTR7oOfcdSXkjN9u3bxT333NNQpyy3gYGB4pZbbpFk/c4775SEEYmWZGGBSCNKh9KzZ09J2NAHJBNCQZv/93//97q2Qmgh7oieQ2rj4uIkyfzhhx+k5eIQZZSWyC1eOEBaFy1aJL180C6acquZUOrbb7+VZBMyDoHFywYIP9r2/fffS/vOn3jiCYGXBrfddpv0M4GXD1lZWZLMo+iKTspzD2zACJKPOfTrr78KsMULD8wJ1L17927pmRgbPBM/mxB1vIzQLDcrt1idgDrBFdKJeYo+oI+jRo0SmI/aRc34ynXgpRledmCPP14yNFXU/F6j3Brbb1y2x1IJUG4tdeTZb4sgQLm1iGE2aCeVfAmsqa4VVwrKm20nhCK/IF9YCSvpSzu+3ONLfVV1lbCztZNEBdmF27q4eTsKG1vrm35sU3ILiYmNjZX6rL3nFtE7RFMhc1u2bLluP66cLAdLXSG6EBIUCB9kEhFeCCnqkD+TP0ekDJFFFAgoxA6CAYGYNWtWQ38hXH/6058k6YBUIlqMAunB/mdILCKP2om+IEm4D89AdmC5yFIMgf7Pf/4jRePlgigwhBzReUg4xB1Fllv8GYL79ddfS3tQNcsXX3whCTFEHi8CIPNygfziM8wnvBTAGbEo+DteKkAOES1fvHhxw8sTSC/uQb9RWiK3EM+ffvpJaufgwYNvmDvNyS1ugIDu2rWrIYEU5BMvAsAbYwXhxFjJZz8jCv7kk09Ky57xokCzyHMPL0fw0kOOYGMP8IgRI6SINeYLfp7RZsiuPE8g+9hLDNG94447Gqq9WblFRYiMo93yPlis4ICs4wgwiC44ykXN+GoyuO+++6RVBlgBgZc4TRUlv9e076fcNomUH5JAmxGg3LYZaj6IBNqeAOW27Zlb2hOVfAm8lFsqtsz72WTRPLLgVuHpd+M+4JZ2SJfcIiKN42JmzJghZdXFF31EQ+UCqUBUU5ZeHBukXeLj46VlnYh0IeKFgvqwvBRLPLdu3dpsUyHAWB4KmZAjgJo3yYI9dOhQgSW3cnnooYek+vGs6dOnX/ccCASW1r711luSdKFAzLA/FC8yIPTYY61dcC04ILKL5dAomnILwX/44YdvuA8yiwgtpFp7CTUuxrJoRC4h7pBCFCxtnjBhgiSE2Ncti6JcOZZTI4M1SkvkFisPIMWQfl0J0JqTW0TYIeFYqaBZECX/9NNPpWXoaK9mciQs30c0FnMGS9DxEkAu8tyDwCOirFkgfBA/FERSIc2aRY6yY4kx5ohcblZuMQ/QBwi3ZsFycCRX036emvHVrFeOpmMu/+Mf/7hh/mj+g5Lfa9oVUG6bRMoPSaDNCFBu2ww1H0QCbU+Actv2zC3tiUq+BFJu/5gVus65lecLItKQFjkqKv87luc+8MADUgQUUTxdBfslsZ9UU1wQDYU4QEQhpM0VXIOIHfaHai/bxb0nT56UooVYMoyomiyBkCFE/hDdw15guUDaIXUQQogszi9GwZ5iLJ9G1BbypqtAiCHGEOf3339fukRTbiGN2kKUn58vLTXFHlHInbakog4swUVUEEt+EVVFQeQQy8AhPlhCrF1+//13qW8oSuUWe8flfeFY4q0rO29zcotVCohcaxd5DzP262JfrHaR921jHy72RMtFnnuI0GIFgGaR96Ni/y0i2drs5NUBf/vb36Rl3XK5Wblt7IxfvNSAUGs+T+34avYTLzTArzF2mtcq+b2mzZ5y29xvGX5OAm1DgHLbNpz5FBIwCAHKrUGwW9RDlXwJpNz+MSW0z7mFLGE5MJZ7YnkoorJYPqu53FYWVyWTCqKGBEMokD/UiYRSSo4VQoQQy5obk2FktEad2HuLPYtyBBl/R5In7Gs9evRoQyIoeekxkhFh6bFcZHFV0h/NKLEst3gunq9dZHFVUi/4IkqOAjGHoP/73/8WkydPvuF2LL2Wl0YrlVtEa7GsFy8sMAa6SnNyi+W/mBfaRU7GhP3SCxcuvOFz7JWFwGofNyXPPSx5DwkJue4+mS0iqVjOrl0aa+vNym1jfdD1PLXjq9kX/Gw8/vjjUpQay9abKkp+r2nfT7lV8tPHa0ig9QlQblufMZ9AAgYjQLk1GHqLebCSL4FK99waKzS1e24hhJBX7GNFBA9LhhHF/OCDD6Qv2PL+YfwbIrZIuoTIIpYpy0fFIEstIrKImmpG4nSxwj5KCC4K9iwjCtdSuf3vf/8rhgwZckP1jcktLkR2Yyzz1Fzui+go+rFz506BZdNywRJmRGQhf81FlBF9xhJSFM1syfizdsGz8ExkRsbS3aYK9gbLmZtbQ24RWZYToqmN3CJbMvY6a5fGMhDL1zUnt0jOpp1Zuzm2auUWS5ix3L2pbMmaCc3kPuh6ntrx1eQnR26RyArResqtsf7GZbtI4OYIUG5vjh/vJgGjJkC5NerhMYvGKZFbs+hoCzsBwcGyYOwxxbJUyCbEA4mLENVEYiAkNZKXryJqiuzE4Il9oPJxLthfij9jaTKinkqLvCy5MVnVrqcly5KRpEozOZW8ZBn7PRHBRXQQz0d2Wsi15rWITEPCsXwW0TilpTkBA1dEqCGuSJSltCBai+W92pmg5fvVLEvGvRhXLE9Wu+fWFOQWUVBEQzX3VGtyx7LjTZs26UVu1Y6vZnvklzDcc6v0p4PXkYBpEqDcmua4sdUkoIgA5VYRJl50EwQot7rhyef2QraQ2AcJguSloYjcYmkslvli76lc5CRQmpmPsQQXy0URCUTUzdPTU9FoyUmAcIQQntdckRNKQTxxBI52QfQYUWTthFLydXJ2YERqsZ8VkVxdZ9tivmAvLpb7Qui1Mx431s7m5Bb34eUAot/aS3Kb6jvkCxKGdqA92vtNkYBKjvIqXZaM52FfKzg29nKhuWXJpiC3SPiEyOu0adME9uVqFqwawAsOLHPWR+RW7fhqtklOxvXhhx9KGbmbKmp+r3FZcnO/Zfg5CbQNAcpt23DmU0jAIAQotwbBblEPVfMl0NwBYR+qnFwJwiUnFJLlFkexyPs4kaxIFipEHCG2iIwimojENygzZ84Ub7zxhnQMCxI+aR6dg88RIUQyKiwnRvQUBdlycbQLkj8hOy4STmmKGyKqOPNT8yggRJLxbO3Mx9j7iSNx8Bwcx4KlvNpFcz8jIrKI4GqfbSvfg/oh8hB79BNLsTULlkDjyCG0R+6rErkFAwgMljyjXu2sv4iiYz8qoujyEm9E2CG2WBqO6C32scpLwpE1Gn1Fv1FaIrcQOtSFlwaoV7uYg9yCD+YkknghSzWWzqNAbJHxe+PGjdLf9SW3asZXkzt+NvAzxnNuzf03MPtn6QQot5Y+A9h/syZAuTXr4TWKzlFubxwGyO3hw4clGWpKbhHNhdzKMoWaIESQAST9wbJmLOkFYyxNRsQJgnrLLbdIn+M+SB/OP8XeTkSLNcUXIoqswxBcCB+OUsE9iABjuS0S+mjueYQ84Ogg1BUTEyPJMZbVIgKJPjW2dBftxr5iLEOG2KBon22rTQn7c5cvXy79MxhB6vESAMtPwU5bpJXILerCsT0QeYgs5BjChSXC2PuMehExxjEzTzzxREOT9u3bJ2WjRvIn8MOYQHYh9YiAy+1sidziWT179hSNRWDNQW4BEPvIkcUbLwwgupivONMYcxsvBjZs2KA3uVU7vrgPL1owzwYMGCAlbWuuqPm9xshtc1T5OQm0DQHKbdtw5lNIwCAEKLcGwW5RD1XzJdASAGEfKoSvqWXJyPyreRYpuEBEEUlEdEk7gy+W/CIRDqJkOBrFzc1NWuKL/btjxoyRBA3HuWgWiCwS6SAjMKK1SGKFval33XWXwHmi2ufM4liYpUuXCggfolx4BiKrOG8W0dumCgQce4RRGtuHqXk/5BGiCdlAf7FMG/2JjY0Vo0ePlvokJ2ZSKreoH7KP5yMhE2QZwoV6kREaMjZ27NiGo4nk9uAeJEBCmyD3EGMIMP4nv3xoidyiXiS4SkxMlI700U7iZC5yixcCWJ6MRGFgjfmOM4YXL14s7S3HZ/qK3GqOVUvHVz5C6b333hOPPPJIs7+C1Pxeo9w2i5UXkECbEKDctglmPoQEDEOAcmsY7i15qvbZp/gijS/02FuJqBPEBdllEXUwxqLmS6Ax9kPfbYIgQXDlbLmIbKEgIomoIs5kRTQVES4W8yQgZ4Zu7Mgb8+y18fUKy9xxXBV+1vCyR9e5w9qtVvN7jXJrfGPPFlkmAcqtZY47e20hBCi3xj/Q2mefosXYB4ioGZY2Xr58WeoEIk7Yb4mln8ZU1HwJNKb2t2ZbwAYRR3kM5WdBdBFJlPfdtmYbWLfhCCDSi729eMmB6C3H2zBjgWRXWHmAaDmShykpan6vUW6VkOU1JND6BCi3rc+YTyABgxGg3BoMveIHy3KrK8Mr9jliKSr2J+LLMZZKIhOtt7e34vpb+0I1XwJbu03GUD+WF+NIHESL5GzHaBcit1gejIiuv7+/9D8W8yWAZclYnox9wMg2zdK2BPCiEPu5sRQfy/k197c31RI1v9cot207tnwaCTRGgHLLuUECZkyAcmv8g9uU3MqtLyoqkvY9nj59Woo8IAJhLEXNl0BjaXtrtaO6ulpg7ypeTiAjMPa5ahbsUzx+/LiUcAqfOzo6tlZTWK8QoqCgQFoJgWRXYA7e2BuKpeFKZUcTJCLx2COMFxWoD+Pr5eUlZarmMnPzmHJqfq9Rbs1j7NkL0ydAuTX9MWQPSKBRApRb458cSuQWvfj8889FfHy8lC0Xx6zIy5NxjubHH38scCwH/h0RQ3w2aNAgMWfOHCmJjmbBcTFIFoSzT3EGqq6C80mRdRZnfL7yyivSJRAyHEeDjL1YZokvf/hCj4y6zz//vBSBDA0NvSGhkfGPgP5bCJnC3j4kY5KPR9F+CjIh49gd7AWEZLG0DgEciQSxhcTiyBr8F4m+8OIB+9oR1WuJ4CLrMn7OUDC+SFaFccQLDeyVx+oK7bNyW6dnrLU1CVBuW5Mu6yaB1iVAuW1dvqydBAxKgHJrUPyKHq5UbhEhQrSpsLBQvP/++1KSKRRk1sWXbUQA5cy7iBoiyou9nciSe/vttze05ZNPPhH33XefdGwHMsNqF0S3kOgI0SnUERwcLInA3XffLUmxh4eHuO2226T/InqFI1MSEhKko18ot3/QBBNkjoU8YXx0FbDFsTRgjf23LPongBUPWBqODNJ4ySBHyCEueLmAFzZYMi6fDdxcCxCpxXFLiM5CYnHEEAoShJ06dUp6sYS6UCeLaROg3Jr2+LH1lk2AcmvZ48/emzkByq3xD7BSuUVPIJiI1M6dO1csWrRI6hxkFVFaiJRcIMJIPoVjTBC5PXbsWEN0Cl/EEa1CRAtnPyLyqlnWr18vJk+eLB0rg/MrUSDBOK8T53biz/LxLPgMmUhxjAr+jXL7B0kc04NEUsjKCr7aS1XxsgAvIMAO59UiAs6ifwJY+o09l/gZw4shzYJoKwQX4otM5EqitxBlCLOuvdLYQ42fJ9SDo4wQ0WUxXQKUW9MdO7acBCi3nAMkQAIkYFgCGUKILkKIu4QQ3zbTlA+EEFhL/I4QYoqCZv8ohBgghIDBHtO4/jkhxFIhxNtCiKla9fwmhOglhPiTEGJ3/Wd/FkJ8KIRYIYSYoXn9oUOHfGpra79wdHSMDA0NPWVvb1+toF1mfUllZaVtUlJSTF1dnbW3t3dely5dzllbW9eh07W1tVYZGRmdCwsLfWxsbGpiYmKSbG1ta8waiAE6V1FRYZeUlNTDysqqLi4u7rDMX7Mpv//+e4/q6mq7sLCwFHd396tNNRPjdvjw4VswptHR0cmOjo4V2tcfP348vLS01LVLly7pPj4+hQboNh+pJwL4GT516lRoeXn5CWtr65E9e/bM01PVrIYESKCVCVBuWxkwqycBEiCBZgi0RG63CSEeFEKsEkJM06i3U72MRggh3IUQNvWf3SGECBFCjBVCfKxxPUKF2DgIEQ0QQlyp/6yfEOJnIcQZIUQoXKz+37sKIVKFEGXX/ve8EGL7NbnOxWeUW92jm5ub633u3LkgfGpra1vl5ORUij+XlZU5Q6ggXUFBQWe8vb0v8SdE/wQKCgo80tPTuzk6OpZGR0ef0PWEkydPdi0uLvYMCAjI7NixY5PycvXqVacTJ05E4YVEXFzc77rqw0uL/Px83/bt2+cGBQX9sTGXxSQJUG5NctjYaBKQCFBuORFIgARIwLAEWiK3X19bJTz4mi9hTfKL9c1ecG118AtwqCa68VchxEatz9deE9zH6iUZsoyCayZcO7FmthBimdb1T9X/m339v0OAf4qOjv5m/fr1U52dnRm51QJ25coV59zcXN+rV6+6QWjxsZ2dXaWLi8uVDh065Lq4uJQbduqZ79Ozs7N9s7OzO7u7u18KCwtL09XT9PT0zgUFBYpkVEOWy6Kjo4/rqk9+poeHR1FoaCh+PlhMlADl1kQHjs0mAcot5wAJkAAJGJyAUrnFy8iCa0uD2wkhxtUvE77/2pLj/9RHXmcJIfYhn1F9hBUde/9axBWZpyYJIbTPD+ohhDgihEi+FomNEULg8Fw52oRorq5llR2EEPcKIZChCv/rgr2+q1evLouKiqoLCwvjsmSDTyc2AATOnz/fIScnJ8DT07OwW7du6bqoZGZmBly8eLGDl5dXfkhIyNmmyOXl5XmdPXs22NnZuSQqKgqrGG4oOTk57c+fP9/F1dW1OCIi4hRHwnQJUG5Nd+zYchJg5JZzgARIgAQMS0Cp3MZf2wu7UwhRJYTAMuSLQoit9aKLqOq/dHTjl2unCPVpRG5x+XfXhPhOIcRAIcSt9ftwIcGQYSUltn379u+//vrrUTExMVVRUVHHuedWCTZe09oEKLetTdi866fcmvf4snfmTYBya97jy96RAAkYPwElcotoLUQV58qsq19OjJ7tRRLl+mjqp1pdxQG3R+uXK+uK3OLyB4QQH9X/r/e1ZcnB9TKMpFKKSnh4+NNz5859Izo6uqZ79+7JlFtF2Iz6otLSUodLly55lJaWupSWljpXVlY6osHYI9y+ffuiphqPCGdeXp5PeXm5E1aH2dvbl3t7e+d36NAhT0lGYn2B4bJkfZG0zHoot5Y57uy1eRCg3JrHOLIXJEACpkugKbm1FkIgYvu6EAJJnVLqsx/LgvHmtaXKiNp+Xp80qrIeg68QAuf4IGqL0pjcYp8u9gbKB3P+ei1Dcl8dKLHPF4IDmdbMhmzj5+f3yauvvhofExNTHRUVdYxya7oTUW65nBhJuyfNyW16enpgQUGBD5JlYWku/ltSUuJeW1trjb2voaGhaW0luPpOKFVSUuKUkpLSXEKpTvn5+X5MKGX6PwOUW9MfQ/bAcglQbi137NlzEiAB4yAgy+2XQoic+iZBJH2EED2FEPIBtp9c20/7t/rlyHLLkQn5kBDCQwhxTgiReG1pMSJmWGaMv2NvIPbINia3qCdBCLGkvkJdiafwEY7/WS6EuFz/POzrdRZC9PP09Oy4cuXKqh49elSHhYWdpNwax6S6mVZg72hFRYWjs7PzVTc3t9L09PSgq1evujYlt/n5+Z4ZGRldkRk6LCws1dnZWToqB5KQmpoajvr8/f3P+fv7Yzl9q5eysjK7Y8eOKToKKDQ0NMXDw0NvRwEFBgam+/r68iigVh/l1nsA5bb12LJmEmhtApTb1ibM+kmABEigaQKy3MpX4TxUfNHGETGQUyxHRmIoJH7SVbCUGHKKBE8Q4iwhBER4Yf25tBObkVssR0bEFsmqsJdXVwZfRI3/Ur8/F0ujERkuEUJkBgUF7f3ggw9GuLm5hfKc26YHOiAgICY7O1vONi0QxXRycqp1c3OrCQkJKY+Li7s6YcKEwn79+uHIJaMpJ06cCNeU29TUVPuIiIgYf3//yqysrCQ0NDk5ObK8vNw5MDAww9fXF3OpoRQVFbmmpaWFQ3xjY2OPtlX0Vt9tko8O8vPzy+7cuTNe8DSU8vJy++Tk5BhEq2NjY4/w7GKjmb6qGkK5VYWNN5GAURCg3BrFMLARJEACJGAwAojIIjL7Sv0Zti1qCM+5VY5Lltvbb7+92NfXF4nBcO6tdUFBge3x48edS0pKpPOJ77rrrssbN27M6Ny5s+YScOUP0vOVzcltRUWFXVJSkqIoaVhYWIq7u3uTUVJ9NT8/P79dRkZGCKQ6IiIi1dHRsdlo8oULF3zy8vJ8EbXu1q0bXjw1FBztlJqaGmllZVUbGhqa6u7uLp1dXF1dbX3q1KlQvABo3779xaCgIKyaYDFhApRbEx48Nt3iCVBuLX4KEAAJkIAFE8Be2xM4frU+WVWLv5RTbpXPHllud+7ceTI+Pv6K5p21tbXi/fff90xISOh0/vx5hy5dulQkJiae8PPzq1H+hNa5sjm51ff+Vn324syZM4GFhYXa+4DdamtrbXTtAz537px/bm5uRxcXl5LIyMgbjvzJysryu3DhAlY4COwrtrGxqSkpKXGrqamxdXJyuhoZGXnS2tq6Vp99YF1tT4By2/bM+UQS0BcByq2+SLIeEiABEjAdAv+sX4KMTMtYYvyqEOI5Nc2n3Cqn1pTcyrXk5eXZ9O7dOzIzM9Nh7NixBdu3b78ueqj8afq7sjm51XdmYv21/I+a6jM4+yKDc11dnXBwcGg0g3Nzcov6CgsL3XNzc/3Kyspc6urqrO3t7SvatWtX4O/vn2ttbY1tBSwmToBya+IDyOZbNAHKrUUPPztPAiRgoQQgTIHXElRh3+BmIcSL9efnthgH5VY5MiVyi9q2bt3q8dBDD3WzsbER6enpRzSXJ+fm5tosXrzYb8+ePZ6I8ELWgoODy8eNG1cwZ86cPAcHh+vkKjs723bdunVee/fu9Thz5oxjfn6+nb29fS32+I4fP75g9uzZeba2SJp9Y9mzZ4/rwoULOx49etQdzwkNDS2fNWtWVr9+/Uo199zq+0xZ5UR5JQm0DgHKbetwZa0k0BYEKLdtQZnPIAESIAEzJUC5VT6wSuUWS5S9vLxuuXz5ss0777yT/re//U3KvPvLL784xcfHh+bl5dn5+flVRUZGluLaI0eOuOLa/v37X/nmm29OaQruqlWrvKZNmxaM64OCgsp9fHyqLl68aPf777+7VlZWWg0ZMuTS3r1706ytcerU/5fVq1d7TZ06NRj1R0RE1Hbp0sU6KyurIjk52WHy5Mm569at85MTSlFulc8BXmkaBCi3pjFObCUJ6CJAueW8IAESIAESUE1AidxWV1VaFWVnNWQJVv0wA93Yzj+g0tbO/qaXmyqVW3RzwIABoQcOHHB/6qmnLrz55pvZJSUlVhEREdFZWVn2CQkJWQsWLMixs8NWaSEQzb3vvvtCcP3MmTMvvP7669kyqoMHDzpCfAcPHnxdEqezZ8/ajRgxIjQlJcVp9erVZx5//HH57GSRkZFh17179+jS0lLrpUuXZo4aNcpLzpa8Y8cOMWXKlBBIryy3xr4s2UDTho81YQKUWxMePDbd4glQbi1+ChAACZAACagnoERu886mO2x67qlo9U8x7J0TXnkr2adLsJRp92ZKS+R21KhRwbt27fJ6+OGH87Zs2ZK5dOlSnzlz5gTec889RZ9//vkZ7XZASENDQ2NcXV1rCgoKjmhHYnW1++OPP3YfO3Zs6IgRI4q++OKLhjpnz57dcdmyZf59+/YtSUxMTNXeczt8+PCue/fu9ZTl1pgTSt3MePFeyyVAubXcsWfPTZ8A5db0x5A9IAESIAGDEaDcKkffErn905/+FLJ79+67MtFpAAAb4UlEQVR2jz76aN7mzZszBw8e3O2bb77xWL9+/ZlJkyY1RFk1n96tW7fuaWlpjkeOHEnu0aNHg4xXVVWJnTt3uv/4448uOTk5dhUVFdbYQ4ujhyCpYWFhZampqcflugYMGBB24MABt9dee+3srFmz8rXldvPmzZ4TJkzoKsttWVmZ3bFjxxQdBRQaGpri4eHRJkcBKR8ZXkkC1xOg3HJGkIDpEqDcmu7YseUkQAIkYHAClFvlQ9ASue3fv3/Yzz//7DZ9+vQLK1asyJbFVcnTvvzyy5Rhw4ZJAnn06FGH++67rxuSSTV2ryyp8ufBwcHdMzIyHD/55JOTY8aMuaIttwcOHHAaMGBAlOZ9ycnJkeXl5c6BgYEZvr6+BZrPKioqck1LSwvHebOxsbFHraz41UPJOPIawxGg3BqOPZ9MAjdLgP8Pc7MEeT8JkAAJWDABJXLLPbd/TBClcov9rO3atbuluLjYZu3atWcee+yxIlk4Bw0adNnLy6u6qSn397//PScuLq4c14SFhUWdOnXKafDgwZeef/75nNjYWByDU4MMyRDf2NjYaH3IbX5+fruMjIwQCGxERESqo6OjFDmGJKSmpoZXVFQ4+vv7n/P3979owT8u7LqJEKDcmshAsZkkoIMA5ZbTggRIgARIQDUBJXKrunIzu1Gp3MpHAdna2tZlZGQcDQgIqJYTTH3wwQenx48ff1kJmsOHDzv27NmzO2Q4Nzf3iPaRP9u2bfMYP358N225vfXWWyMTExOd58+fX/HAAw9UV1RUONXW1krnudrY2FT/97//tZkxYwZktTIrKytJbsuZM2cCCwsLfaysrOpcXV2L8d+SkhK32tpaG3d390uhoaFpjNoqGTleY2gClFtDjwCfTwLqCVBu1bPjnSRAAiRg8QQot8qngBK5zcvLs+ndu3dkZmamw4MPPpi/bdu2s3jC/Pnz/RYsWNBp7NixBdu3b8c5xc2Wr776ymXYsGERERERZSdOnGjYUyvfOHr06OCdO3d6aUvqjBkzglasWOHdu3dv8fbbb9/wnDlz5oivv/66IVuy5gV5eXleeXl5vuXl5U7Y1+vg4IBIcX6HDh3yKLbNDhkvMBIClFsjGQg2gwRUEKDcqoDGW0iABEiABP4gQLlVPhOaklssRf7ggw88EhISOp87d84hODi4PDExMcXHx6cGT7h8+bJ1RERE95ycHHsc9zN//vwcd3f3Ws2np6Sk2O/bt8916tSp0rm42dnZtp07d45FBHXnzp0nR44cWSJfD3mdOXNmEARUW27T09Olo4DKysqsly1bdvaZZ57Jl+/bsGFDu8cee+y6o4CUE+CVJGAaBCi3pjFObCUJ6CJAueW8IAESIAESUE2AcqscnSy3t99+e7Gvr28V7kTm4oKCAttjx445X7lyxQb/NnTo0EvvvvvuWSxH1qz9l19+cbr33nu7Xbhwwd7Dw6MmPDy81M/PrwpZj5ElGdHeHj16XD1y5EiKfN/EiRM7b9q0yRdHA/Xp0+eKj49PVWpqqhP24U6bNi1n5cqVHbTlFveuWrXK66mnngqGdEdFRZWGhISUo/6jR4+6TJ48OXfdunV+uu5TToNXkoDxEqDcGu/YsGUk0BwBym1zhPg5CZAACZBAowQot8onhyy38h1Ypuvk5FTr5uZWA3ns2bPn1YkTJxb06dNHSgalqxQWFtq8+uqrPrt37/ZEBmTIcbt27ao7duxYOWjQoOKHHnqoqF+/fmXyvZDT5cuXt1+3bp0PMiBjH290dHTprFmzcmJiYsojIiJiGpPUXbt2uS1ZsqTjkSNHXFBfaGho2dNPP507YMCAq03dp5wIryQB4yRAuTXOcWGrSEAJAcqtEkq8hgRIgARIQCcByi0nBgmQgLkRoNya24iyP5ZEgHJrSaPNvpIACZCAnglQbvUMlNWRAAkYnADl1uBDwAaQgGoClFvV6HgjCZAACZAA5ZZzgARIwNwIUG7NbUTZH0siQLm1pNFmX0mABEhAzwQot3oGyupIgAQMToBya/AhYANIQDUByq1qdLyRBEiABEiAcss5QAIkYG4EKLfmNqLsjyURoNxa0mizryRAAiSgZwKUWz0DZXUkQAIGJ0C5NfgQsAEkoJoA5VY1Ot5IAiRAAiRAueUcIAESMDcClFtzG1H2x5IIUG4tabTZVxIgARLQMwHKrZ6BsjoSIAGDE6DcGnwI2AASUE2AcqsaHW8kARIgARKg3HIOkAAJmBsByq25jSj7Y0kEKLeWNNrsKwmQAAnomQDlVs9AWR0JkIDBCVBuDT4EbAAJqCZAuVWNjjeSAAmQAAlQbjkHSIAEzI0A5dbcRpT9sSQClFtLGm32lQRIgAT0TIByq2egrI4ESMDgBCi3Bh8CNoAEVBOg3KpGxxtJgARIgAQot5wDJEAC5kaAcmtuI8r+WBIByq0ljTb7SgIkQAJ6JkC51TNQVkcCJGBwApRbgw8BG0ACqglQblWj440kQAIkQAKUW84BEiABcyNAuTW3EWV/LIkA5daSRpt9JQESIAE9E6DcKgeamppqHxEREYM76urqDjZ1p5WVVS98npKSkhQeHl6p/Ck3XhkQEBCTnZ1tr4+65Np//fVXxzlz5gQcOnTItbi42La2tlYsWLDg3EsvvXTxZtpq7Pfu2rXLbdSoUWF9+/YtSUxMTDX29rJ96ghQbtVx410kYAwEKLfGMApsAwmQAAmYKAHKrfKBMxe5LS4uto6MjOwOYY6Oji7t2rVruY2NTd0jjzxSOHbs2GLlRNRfaSjJNNRz1ZPinWoIUG7VUOM9JGAcBCi3xjEObAUJkAAJmCQByq3yYTOU3CYnJztUVVVZRUVFVTg4ONQpb7HuKz/77DO3MWPGhMXFxV09dOhQys3Wp+Z+Q0mmoZ6rhhHvUU+AcqueHe8kAUMToNwaegT4fBIgARIwYQKUW+WDZyi5Vd5CZVeuXLnS+8knnwwaO3Zswfbt2zOU3aXfqwwlmYZ6rn7psbbmCFBumyPEz0nAeAlQbo13bNgyEiABEjB6ApRb5UN0s3Ir78PFft01a9a0W7Vqld/JkyedrKysRI8ePa7Onz8/e/jw4SXaLWpsz22/fv3Cf/nlF9edO3ee9PDwqJk3b54/9tCWlZVZBwUFlT/xxBMXZ86cmS/XJ4udrh77+/tXZmVlJcmfYeny0qVLfT799FOvjIwMx+rqaqtOnTpVjB49umjevHk5Hh4etbrq2bdvn8sbb7zh+9tvv7nm5+fbubi41AQEBFTefffdl+fMmZPr5+dXI7db1/3ae2GxF/jf//53u40bN7Y/fvy489WrV228vb2rBg4cWLxgwYILje1n3rx5s+fy5cs7pKSkONna2tZFR0dffeGFFy4IIay451b5nDfVKym3pjpybDcJCEG55SwgARIgARJQTYByqxydvuT26aefvvDWW2917NmzZ4mvr2/ViRMnnNLT0x3t7Ozqdu/enTp06NCrmq1qTm6nTJmSs3btWr/g4ODy8PDwsqysLIfDhw+7oI6XXnrp/IIFC3Lx58OHDzsuWrSoQ0ZGhgMkuHPnzhV9+vSRZNrb27t6zZo15/HntLQ0u+HDh4elpaU5tmvXrjoqKqrUwcGhNikpySUvL88uLCysbP/+/ak+Pj41mu1MSEjosHTp0oC6ujrRrVs3qS0lJSXW6FtmZqYDJDw+Pv7KCy+80OGHH35w279/vzueO3DgwMtyPeHh4eVLlizJwd8rKiqsRo8eHbJ3715PR0fH2u7du5f6+PhUpaamSrzc3d1rUOedd95ZqtmOuXPn+i1ZsqQT/g1LrwMCAipwT1pamtPEiRMvbtiwwZcJpZTPe1O8knJriqPGNpPAHwQot5wJJEACJEACqgkokdu66lqrqrwye9UPMfCNdj5OlVa21je9V1VfcosoK6TsjjvukKQM0clHHnmky9atW9v379+/+KeffjrVErnFtcuXL8+YMWNGgXzfqlWrvKZNmxbs6upak5WVddTd3b0h0vrmm296P/300zqXJaMtvXr1ivj9999dJkyYcHHlypXnXV1dJXYlJSVWjz76aBCiudpLmjdt2uQ5ceLErs7OzrVr16498/DDDzcIK+797rvvnDt16lTVtWvXKvxdyfLgqVOnBrz99tsdevfuXbJ169Yz8r24f8mSJT5z584NhKCnpaUl29nZSV3/8ccfnQYOHBiFhNabNm1K02zHiy++6Ldo0SJJeim3Bv6hbOXHU25bGTCrJ4FWJEC5bUW4rJoESIAEzJ2AErmtvHDV4eKKQ9GmysL36Z7J9h1dKm62/fqS28WLF2e+8MILeZrtOXfunG1gYGCsvb19XXFx8WHNxFHNRW6HDx9etGfPnjPa/evatWv3M2fOOCIaPHLkyIblzk3J7bZt29zHjx8fGhsbKyWbsra2vq5aLFcODg6OuXz5ss2FCxeOyNHbiIiIKERHly5dmvncc89d1zdd3JuT29zcXJugoKAeeP7JkyeTAgICqrXrueuuu7p9++23Hlu2bDktS+yDDz7Y5aOPPmrf2H7i6OjoyGPHjjlTbm/2p8G476fcGvf4sHUk0BQByi3nBwmQAAmQgGoClFvl6PQlt42dV+vh4XFLcXGxTWZm5pHOnTs3yFxzcrtixYqM6dOnN0Rt5R4NGzas61dffeW5evXqM48//niR/O9Nye3EiRM7b9q0yffFF188v3DhQmk5s3YZNGhQt++++85j+/btp3B0kCzm2NtaVFR0WI70NkW2Obl99913PSdNmtR10KBBl7/55pvTuuqSI7HTpk3L+de//pWFawIDA6PPnTvn8PHHH5+89957r2jft3DhQt958+Z1ptwqn/emeCXl1hRHjW0mgT8IUG45E0iABEiABFQToNwqR3fy5En78PDwGNxRU1NzUDuqKdeEpb02Nja98PfU1NSksLCwSun/sK2spH9r7N7GJLY5uf30009Pjh49+gaRu//++4N27NjhrS2/TcmtLK5KqKxatSp9ypQphUgiNWTIkAgsEc7MzExWcm9zcqu5hLi5+saNG5e/devWs7jOwcGhZ2VlpVVSUlJydHT0DdF6JJqaMGFCV8ptc1RN+3PKrWmPH1tv2QQot5Y9/uw9CZAACdwUASVyyz23fyDOzs62DQgIiMWfL126dLixjMFFRUXWXl5ecbguJyfnd2QI1pRbZEvWNWhq5VZO1KRdpxq5veOOO0KR6Anyh+zITU2uxx9/PB/Znfft2+c8ZMiQSH3KLZJO/eMf/whA1ueePXtel2BLu0233XZbyaxZs6Ss0JTbm/p1YDY3U27NZijZEQskQLm1wEFnl0mABEhAXwSUyK2+nmXq9VRXVwt3d/c4HLXz008/He/fv3+Zrj7t37/f+Y477ohEcqUrV64cliO8mkcBGavcjh8/vsu2bdvaL1myJDMhIaHZvbPoh7wsGdmeCwsL9bIs+e233/aaOnVq8IgRI4q++OKLG/YTNzaXOnfuHH3+/HmHTz755OSYMWO4LNnUf+hUtp9yqxIcbyMBIyBAuTWCQWATSIAESMBUCVBuWzZyAwcO7Pb99997TJ8+/cKKFSuydd395JNPBqxcubIDjrj59ttvG/aLmoLcbty40fOvf/1ri5fthoeHR+HM3ldeeeXs7NmzG87WbYzuV1995TJs2LAIHId08ODBVO3rIMwhISE9nJycas+cOZPUvn37644daqzeP//5z0H/+c9/vB944IGCjz76KEP7OiaUatl8N9WrKbemOnJsNwlwzy3nAAmQAAmQwE0QoNy2DN5nn33mdu+994bh3NcNGzacGT9+/HVH3rz//vse//M//9MV+z4RPdTcC2sKcov9wj169JAyCj/00EN5y5cvz5KXVcukIJ4ffvih5zPPPNMgsbIUu7i41K5bt+7MuHHjruPy/fffOwcEBDQcBSTvX8Y5t8i6LB/lozkakydP7rx+/XrfXr16laxdu/ZsXFxcuebnyNy8ZcsWz/j4+GI5AdcPP/zgPGjQoEgrK6u6LVu2pGm2Y8GCBb7z58/vjDq457Zl897UrqbcmtqIsb0k8P8EGLnlbCABEiABElBNgHLbcnRIdrR48eJOdXV1olu3buVhYWHS8mRELk+fPu1oZWUl5s6de/7ll1++LtuwKcgt+pGWlmY3cuTI0FOnTjlBVsPDw0v9/f0rKyoqrNPT0x3T0tIcvby8qvPz849o0nv22Wc7vvbaa/74t9DQ0LLw8PCykpISGxxHlJmZ6aC9NzgqKiryxIkTziEhIeUxMTGleGEQFhZWLnOrqKiwGjt2bPDu3bvb2djYiIiIiNLAwMAK8D137px9amqqM14iHDp06Jim+CYkJHT45z//GYDr4uLiSgICAipTUlKc0tLSnHB277vvvutLuW35vDelOyi3pjRabCsJXE+AcssZQQIkQAIkoJoA5VYdOiRReuutt3x//fVXt/z8fDvU0r59+6o+ffpceeqppy4OHjy4VLtmU5FbtLu0tNRqxYoV7Xfs2OEFaS8tLbX29PSs9vPzq7rtttuuPPDAA0V33333DYmevvzyS9cVK1b4/vbbb65FRUW2rq6uNZ06daocNmzYpeeee+6iZhQYRyvNmjWrU2JiotulS5dsa2pqdEZUEQ1fv359+6NHj7qgTgi3j49PFc7iHTNmzKUHH3zwsua5wGg/IslvvPFGB0gtjiiKjo4uTUhIuID9z6NGjQqj3Kqb96ZyF+XWVEaK7SSBGwlQbjkrSIAESIAEVBOg3KpGxxtJgASMlADl1kgHhs0iAQUEKLcKIPESEiABEiAB3QQot5wZJEAC5kaAcmtuI8r+WBIByq0ljTb7SgIkQAJ6JkC51TNQVkcCJGBwApRbgw8BG0ACqglQblWj440kQAIkQAKUW84BEiABcyNAuTW3EWV/LIkA5daSRpt9JQESIAE9E6Dc6hkoqyMBEjA4AcqtwYeADSAB1QQot6rR8UYSIAESIAHKLecACZCAuRGg3JrbiLI/lkSAcmtJo82+kgAJkICeCVBu9QyU1ZEACRicAOXW4EPABpCAagKUW9XoeCMJkAAJkADllnOABEjA3AhQbs1tRNkfSyJAubWk0WZfSYAESEDPBCi3egbK6kiABAxOgHJr8CFgA0hANQHKrWp0vJEESIAESIByyzlAAiRgbgQot+Y2ouyPJRGg3FrSaLOvJEACJKBnApRbPQNldSRAAgYnQLk1+BCwASSgmgDlVjU63kgCJEACJEC55RwgARIwNwKUW3MbUfbHkghQbi1ptNlXEiABEtAzAcqtnoGyOhIgAYMToNwafAjYABJQTYByqxodbyQBEiABEqDccg6QAAmYGwHKrbmNKPtjSQQot5Y02uwrCZAACeiZAOVWz0BZHQmQgMEJUG4NPgRsAAmoJkC5VY2ON5IACZAACVBulc+BgICAmOzsbPudO3eejI+Pv6L8Tt1Xnjp1yu6ZZ57p9PPPP7sVFhba1dTUiEmTJl1cv379uZut25jvT01NtY+IiIjx9/evzMrKSjLmtrJtpkmAcmua48ZWkwAIUG45D0iABEiABFQToNwqR6dPua2trRWxsbGRycnJzl27di2PiooqtbOzqxs6dGjxlClTCpW3Sv2VhpJMQz1XPSneaWoEKLemNmJsLwn8PwHKLWcDCZAACZCAagKUW+Xo9Cm3KSkp9pGRkTEdO3asPHv2bJKdnZ3yhujpSkNJpqGeqydsrMYECFBuTWCQ2EQSaIQA5ZZTgwRIgARIQDUByq1ydPqU2y+++ML1nnvuCe/bt29JYmJiqvJW6O9KQ0mmoZ6rP3KsydgJUG6NfYTYPhJonADllrODBEiABEhANQHKrXJ0uuT2/vvvD9qxY4f3ihUrMgYPHlySkJDg/9NPP7lfuXLFJiAgoOLhhx8uePnll3Osra2lB8li19hT6+rqDsqfVVRUWK1YsaL9tm3bvE6dOuVUUVFh3aFDh8q777770sKFC3P8/f2rddVz8OBBx2XLlvn9+OOPbhcvXrS3t7evxX2DBg0qfvbZZy+GhYVVyu3Wdb+uvbDbt293X7lype+RI0dciouLbTw9PatvvfXWKy+++GJO3759y3TVs2fPHteFCxd2PHr0qGtdXZ0IDw8vmzFjRk6/fv1KuedW+bzjlS0nQLltOTPeQQLGQoByaywjwXaQAAmQgAkSoNwqH7Sm5BaJoD766CNvSF9sbGxpfn6+7W+//eZaU1NjNWHChIsbN26UkkRduHDB9sknn+x08eJFu/3797t7e3tXDxw48LLciu3bt2fgzwUFBdbDhg0LPXTokKurq2tNdHR0qbu7ew326CKpFZYzf/PNN6nh4eGVmj1YuXKl98yZM7tUVVVZderUqSImJqa0srLS6uzZs46nT592hIRPnz694PXXX2+/d+9e9y+//LKdk5NT7ciRI4vketCmNWvWnJf/PmnSpM7vvvuur42NTR3qw7MzMjIcTpw44ezg4FC3cePGtHHjxjX0AfetXr3aa+rUqcHYWxwZGVmKfcVnz551SEpKcpk8eXLuunXr/JhQSvnc45UtI0C5bRkvXk0CxkSAcmtMo8G2kAAJkICJEVAit9XV1VYFBQX2Jta1huZ6e3tX2tra1t1s+5uSW9Q9c+bMC8uWLcuWo7RYehwfHx+Oz1JSUo6GhoZWyW3YtWuX26hRo8IaW5YcHx8f8vnnn7cbMWJE0aZNm876+PjU4N7q6mrx1FNPBbzzzjsdtO/97rvvnIcMGRKBZJOvvvrq2aeffjpfbgvuRUQX/+3Vq1c5/qtkefArr7zi8/zzzwd269at/MMPP0yLi4uT7kXZvHmz56RJk0KcnZ1r09LSkuQ2ZmRk2HXv3j26tLTUeunSpZnPPfdcnnzPmjVr2k2ZMiUE0ku5vdkZyfsbI0C55dwgAdMlQLk13bFjy0mABEjA4ASUyG1ubq7D22+/HW3wxqpswJQpU5L9/PwqVN7ecFtTcovI6pEjR05oyiRuHDhwYLfvv//e41//+lfGtGnTCpTILSS0d+/e3SF/qampya6urteJOcQwIiIiCkuVExMTj8vLgocOHdr166+/9pwyZUrOqlWrsprrb3NyC5H29/fvkZeXZ/fbb78dk6VYs94JEyYEbt682WfRokXn5s6dexGfzZ49u+OyZcv8GxP34cOHd927d68n5ba5EeLnaglQbtWS430kYHgClFvDjwFbQAIkQAImS4Byq3zompJbRG1ff/31bO3aHnvssU5YgpuQkJC1ZMmSHCVyO2/ePL+FCxd2+stf/pK3adOmTF0t/Mtf/hL43nvv+SBC++yzz+ZDRN3c3OLKy8utk5KSkqOjo5uV+ebk9ocffnC+8847IxG1PXXq1DFd7Vi/fn27yZMnh8THxxfu3LkzHdcMGDAg7MCBA26vvfba2VmzZuVr34eI74QJE7pSbpXPPV7ZMgKU25bx4tUkYEwEKLfGNBpsCwmQAAmQAAmQAAmQAAmQAAmQgCoClFtV2HgTCZAACZAACZAACZAACZAACZCAMRH4P7ix2BDZk1uTAAAAAElFTkSuQmCC\" width=\"432.27271790346845\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook \n",
    "# for jupyter notebook\n",
    "# %matplotlib inline # for vscode\n",
    "\n",
    "\n",
    "def z_surf(xx,yy):\n",
    "    val = c[0] + c[1]*xx + c[2]*yy\n",
    "    return val\n",
    "\n",
    "x1 = np.arange(0,3.5,0.5)\n",
    "y1 = np.arange(0,6,1)\n",
    "X, Y = np.meshgrid(x1, y1)\n",
    "Z1 = z_surf(X,Y)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection=\"3d\")\n",
    "ax.scatter(np.array(x),np.array(y),z, color='r') \n",
    "ax.plot_wireframe(X,Y,Z1) \n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([120.5243839, 217.8734857, 206.4746411, 538.8327251, 564.2947642])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x =np.array( [0.846, 1.324, 1.150, 3.037, 3.084])\n",
    "y = np.array( [1,2,3,4,5])\n",
    "z_surf(x,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4 ページランク改(感染症の推移):25点\n",
    "\n",
    "ページランクの元になった線形動的システムの代表例である\n",
    "単純な感染症モデルを考える．\n",
    "実際の感染症（例えばcovid19）では成り立たなかったのですが，\n",
    "この問題では単純モデルを仮定します．\n",
    "未感染，感染中，回復(免疫あり)と死亡の４種の状態がある．\n",
    "これらの状態にある人には，毎日次のことが起こると仮定する．\n",
    "\n",
    "- 未感染の人の5%がこの病気にかかる\n",
    "    - 残りの95%は未感染のままである．\n",
    "- 感染している人のうち\n",
    "    - 1%が死亡する\n",
    "    - 10%が回復して免疫を持ち\n",
    "    - 4%は回復するが免疫を持たない（未感染の状態に戻る）\n",
    "    - 残りの85%は感染状態のままである\n",
    "\n",
    "なお回復して免疫を持った人と，\n",
    "死亡した人はそのままの状態にとどまり続ける．\n",
    "未感染，感染中，回復(免疫あり)と死亡のそれぞれ\n",
    "$i$ 日目の状態の人の割合を$x_i$ベクトルで表す．\n",
    "$i+1$ 日目の状態ベクトル$x_{i+1}$ は，\n",
    "\\begin{equation}\n",
    "x_{i+1}=\n",
    "\\left(\n",
    "\\begin{array}{cccc}\n",
    "0.95&0.04&0 &0 \\\\\n",
    "A&B&0&0 \\\\\n",
    "0&0.10&1&0 \\\\\n",
    "0&0.01&0&1 \\\\\n",
    "\\end{array}\n",
    "\\right)\n",
    "x_i\n",
    "\\end{equation}\n",
    "という関係で表される\n",
    "\n",
    "## (1) 遷移行列の完成\n",
    "A,Bに入る数値は何か？\n",
    "## (2) 手計算\n",
    "初日の状態を\n",
    "\\begin{equation}\n",
    "x_{0}=\n",
    "\\left(\n",
    "\\begin{array}{c}\n",
    "1 \\\\\n",
    "0 \\\\\n",
    "0 \\\\\n",
    "0 \\\\\n",
    "\\end{array}\n",
    "\\right)\n",
    "\\end{equation}\n",
    "\n",
    "とすると2日目および3日目はどうなるか？\n",
    "## (3) loopあるいは．．．\n",
    "200日目はどういう状態に落ち着くか？\n",
    "\n",
    "初日から２００日目までの，状態の変化をプロットしてください．ボーナスで10点プラスします．\n",
    "\n",
    "(ステファン・ボイド，リーヴェン・ヴァンデンベルグ 「スタンフォード ベクトル・行列 からはじめる 最適化数学」 講談社 ２０２１年)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.9500  0.0400  0.0000  0.0000]\n",
      " [ 0.0500  0.8500  0.0000  0.0000]\n",
      " [ 0.0000  0.1000  1.0000  0.0000]\n",
      " [ 0.0000  0.0100  0.0000  1.0000]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.set_printoptions(formatter={'float': '{: 0.4f}'.format}) \n",
    "\n",
    "aa = np.array([[0.95,0.04,0,0],[0.05, 0.85,0,0],[0,0.10,1,0],[0,0.01,0,1]])\n",
    "print(aa)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "x0=np.array([1,0,0,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.9500  0.0500  0.0000  0.0000]\n"
     ]
    }
   ],
   "source": [
    "x1 = aa.dot(x0)\n",
    "print(x1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.9045,  0.0900,  0.0050,  0.0005])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aa.dot(x1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.9500  0.0500  0.0000  0.0000]\n",
      "[ 0.9045  0.0900  0.0050  0.0005]\n",
      "[ 0.8629  0.1217  0.0140  0.0014]\n",
      "[ 0.8246  0.1466  0.0262  0.0026]\n",
      "[ 0.7892  0.1658  0.0408  0.0041]\n",
      "[ 0.7564  0.1804  0.0574  0.0057]\n",
      "[ 0.7258  0.1912  0.0755  0.0075]\n",
      "[ 0.6972  0.1988  0.0946  0.0095]\n",
      "[ 0.6703  0.2038  0.1145  0.0114]\n",
      "[ 0.6449  0.2068  0.1348  0.0135]\n"
     ]
    }
   ],
   "source": [
    "x0=np.array([1,0,0,0])\n",
    "\n",
    "for iter in range(0, 10):\n",
    "    x1=aa.dot(x0)\n",
    "    x0 = x1\n",
    "    print(x0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "199 [ 0.0011  0.0005  0.9077  0.0908]\n"
     ]
    }
   ],
   "source": [
    "x0=np.array([1,0,0,0])\n",
    "\n",
    "for iter in range(0, 200):\n",
    "    x1=aa.dot(x0)\n",
    "    x0 = x1\n",
    "\n",
    "print(iter, x0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "x0=np.array([1,0,0,0])\n",
    "\n",
    "history = []\n",
    "for iter in range(0, 200):\n",
    "    history.append(x0)\n",
    "    x1=aa.dot(x0)\n",
    "    x0 = x1\n",
    "#print(history)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "hist = np.array(history).T\n",
    "times = np.arange(0,200)\n",
    "\n",
    "labels = [\"Uninfected\", \"Infected\", \"Recovered (immune)\", \"Dead\"]\n",
    "for d,label in zip(hist,labels):\n",
    "    plt.plot(times, d, '-', label=label)\n",
    "plt.legend()\n",
    "plt.xlim(0, 200)\n",
    "plt.ylim(0.0, 1.0)\n",
    "plt.grid(axis=\"x\")\n",
    "plt.xlabel(\"Days\")\n",
    "plt.minorticks_on()\n",
    "plt.ylabel(\"Rate\")\n",
    "plt.grid(which=\"both\",axis=\"y\")\n",
    "plt.show()\n",
    "\n",
    "# original by Hirayama in 2024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
