Heston Stochastic Volatility Model.ipynb

{
 "cells": [
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    "# python 3.7\n",
    "# based on Zhang, L. implementation\n",
    "# paper: https://arxiv.org/abs/0802.4411\n",
    "\n",
    "%matplotlib notebook\n",
    "import numpy              as np\n",
    "import pandas             as pd\n",
    "import matplotlib.pyplot  as plt\n",
    "\n",
    "from matplotlib           import cm\n",
    "from mpl_toolkits.mplot3d import axes3d\n",
    "\n",
    "plt.style.use('seaborn')\n",
    "\n",
    "def Heston_Calls(series):\n",
    "    # Variables\n",
    "    kappa = series['kappa'] # Mean Reversion Speed\n",
    "    theta = series['theta'] # Long Run Variance\n",
    "    sigma = series['sigma'] # Volatility of Variance\n",
    "    rho   = series['rho'] # Correlation\n",
    "    v0    = series['Cv0'] # Initial Variance (I use Call Implied Variance from BSM instead)\n",
    "    T     = series['T'] # Time to maturity\n",
    "    s0    = series['s0'] # Spot Price\n",
    "    K     = series['K'] # Strike Price\n",
    "    N     = 10000 # Nº of simulations\n",
    "    dt    = 1/32 # Timestep granularity (related to the nº of steps being generated)\n",
    "\n",
    "    # Calculations\n",
    "    vega  =(4*kappa*theta/(sigma*sigma))\n",
    "    K1    = dt*(kappa*rho/sigma-0.5)/2-rho/sigma\n",
    "    K2    = dt*(kappa*rho/sigma-0.5)/2+rho/sigma\n",
    "    K3    = dt*(1-rho*rho)/2\n",
    "    ss    = K2+K3/2\n",
    "    yita  = 4*kappa*np.exp(-kappa*dt)/(sigma*sigma)/(1-np.exp(-kappa*dt))\n",
    "    sh    = ss*np.exp(-kappa*dt)/yita\n",
    "    S     = np.ones(N)*s0\n",
    "    v     = np.ones(N)*v0\n",
    "    Ntime = int(T/dt)\n",
    "    \n",
    "    # Simulations\n",
    "    for i in range (0,Ntime):\n",
    "        Zs   = np.random.randn(1,N)\n",
    "        lamb = v*yita\n",
    "        W    = np.random.noncentral_chisquare(vega,lamb)\n",
    "        v2   = W*np.exp(-kappa*dt)/yita\n",
    "        K0   = -lamb*sh/(1-2*sh)+0.5*vega*np.log(1-2*sh)-(K1+K3/2)*v\n",
    "        S    = S*np.exp(K0+K1*v+K2*v2+np.multiply(np.sqrt(K3*(v+v2)),Zs))\n",
    "        v    = v2\n",
    "    \n",
    "    # Payoff at maturity\n",
    "    payoff = np.maximum(S-K,0)\n",
    "\n",
    "    return np.mean(payoff) # Return expected value\n",
    "\n",
    "def Heston_Puts(series):\n",
    "    # Variables\n",
    "    kappa = series['kappa'] # Mean Reversion Speed\n",
    "    theta = series['theta'] # Long Run Variance\n",
    "    sigma = series['sigma'] # Volatility of Variance\n",
    "    rho   = series['rho'] # Correlation\n",
    "    v0    = series['Pv0'] # Initial Variance (I use Put Implied Variance from BSM instead)\n",
    "    T     = series['T'] # Time to maturity\n",
    "    s0    = series['s0'] # Spot Price\n",
    "    K     = series['K'] # Strike Price\n",
    "    N     = 10000 # Nº of simulations\n",
    "    dt    = 1/32 # Timestep granularity (related to the nº of steps being generated)\n",
    "\n",
    "    # Calculations\n",
    "    vega  = (4*kappa*theta/(sigma*sigma))\n",
    "    K1    = dt*(kappa*rho/sigma-0.5)/2-rho/sigma\n",
    "    K2    = dt*(kappa*rho/sigma-0.5)/2+rho/sigma\n",
    "    K3    = dt*(1-rho*rho)/2\n",
    "    ss    = K2+K3/2\n",
    "    yita  = 4*kappa*np.exp(-kappa*dt)/(sigma*sigma)/(1-np.exp(-kappa*dt))\n",
    "    sh    = ss*np.exp(-kappa*dt)/yita\n",
    "    S     = np.ones(N)*s0\n",
    "    v     = np.ones(N)*v0\n",
    "    Ntime = int(T/dt)\n",
    "\n",
    "    # Simulations\n",
    "    for i in range (0,Ntime):\n",
    "        Zs   = np.random.randn(1,N)\n",
    "        lamb = v*yita\n",
    "        W    = np.random.noncentral_chisquare(vega,lamb)\n",
    "        v2   = W*np.exp(-kappa*dt)/yita\n",
    "        K0   = -lamb*sh/(1-2*sh)+0.5*vega*np.log(1-2*sh)-(K1+K3/2)*v\n",
    "        S    = S*np.exp(K0+K1*v+K2*v2+np.multiply(np.sqrt(K3*(v+v2)),Zs))\n",
    "        v    = v2\n",
    "    \n",
    "    # Payoff at maturity\n",
    "    payoff = np.maximum(K-S,0)\n",
    "\n",
    "    return np.mean(payoff) # Return expected value\n",
    "\n",
    "db             = pd.read_hdf(\"optiondata.h5\")\n",
    "db['Now']      = pd.to_datetime(db['Now'])\n",
    "db['Maturity'] = pd.to_datetime(db['Maturity'])"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "HTest = pd.DataFrame({'T': db['Expiration'],'Cv0': db['CallImpVol']**2, 'Now': db['Now'],\n",
    "                     's0': db['Spot'],'Pv0': db['PutImpVol']**2,'Put': db['PutMid'],\n",
    "                     'K': db['Strike'],'Call': db['CallMid'],'Maturity': db['Maturity']})\n",
    "\n",
    "HTest[HTest['Cv0'] < 0.001] = 0\n",
    "HTest[HTest['Pv0'] < 0.001] = 0\n",
    "HTest = HTest.loc[(HTest!=0).any(1)]\n",
    "HTest = HTest.reset_index().drop('index',axis=1)\n",
    "\n",
    "# Calibration can still be improved\n",
    "HTest['Moneyness'] = abs(HTest['K']/HTest['s0'])\n",
    "HTest['theta'] = 0.0722\n",
    "HTest['kappa'] = 0.4816\n",
    "HTest['sigma'] = 0.621\n",
    "HTest['rho']   = -0.5527"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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     "data": {
      "text/plain": [
       "count    429.000000\n",
       "mean       0.177568\n",
       "std        0.159545\n",
       "min        0.000386\n",
       "25%        0.091800\n",
       "50%        0.152254\n",
       "75%        0.188938\n",
       "max        0.868657\n",
       "Name: CError, dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HTest['Heston Call'] = round(HTest.apply(Heston_Calls, axis=1),2)\n",
    "HTest['CError'] = abs(HTest['Heston Call']/HTest['Call']-1) # Absolute Error\n",
    "HTest['CError'].describe()"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
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     "data": {
      "text/plain": [
       "count    429.000000\n",
       "mean       0.093806\n",
       "std        0.041293\n",
       "min        0.000239\n",
       "25%        0.064486\n",
       "50%        0.101762\n",
       "75%        0.125947\n",
       "max        0.203253\n",
       "Name: PError, dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HTest['Heston Put'] = round(HTest.apply(Heston_Puts, axis=1),2)\n",
    "HTest['PError'] = abs(HTest['Heston Put']/HTest['Put']-1) # Absolute Error\n",
    "HTest['PError'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
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       "    <tr>\n",
       "      <th>Maturity</th>\n",
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       "      <th>2018-05-18 17:30:00</th>\n",
       "      <td>39.0</td>\n",
       "      <td>0.451255</td>\n",
       "      <td>0.283261</td>\n",
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       "    <tr>\n",
       "      <th>2018-06-15 17:30:00</th>\n",
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       "      <td>0.220694</td>\n",
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       "    <tr>\n",
       "      <th>2018-09-21 17:30:00</th>\n",
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       "      <td>0.002740</td>\n",
       "      <td>0.079245</td>\n",
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       "    <tr>\n",
       "      <th>2018-12-21 17:30:00</th>\n",
       "      <td>125.0</td>\n",
       "      <td>0.137622</td>\n",
       "      <td>0.114624</td>\n",
       "      <td>0.000386</td>\n",
       "      <td>0.051094</td>\n",
       "      <td>0.131896</td>\n",
       "      <td>0.182227</td>\n",
       "      <td>0.567401</td>\n",
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       "    <tr>\n",
       "      <th>2019-03-15 17:30:00</th>\n",
       "      <td>98.0</td>\n",
       "      <td>0.159601</td>\n",
       "      <td>0.036463</td>\n",
       "      <td>0.041959</td>\n",
       "      <td>0.137607</td>\n",
       "      <td>0.172851</td>\n",
       "      <td>0.185618</td>\n",
       "      <td>0.223236</td>\n",
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       "                     count      mean       std       min       25%       50%  \\\n",
       "Maturity                                                                       \n",
       "2018-05-18 17:30:00   39.0  0.451255  0.283261  0.002766  0.199734  0.484938   \n",
       "2018-06-15 17:30:00   62.0  0.156919  0.083259  0.005128  0.083065  0.177897   \n",
       "2018-09-21 17:30:00  105.0  0.152429  0.152525  0.002740  0.079245  0.132809   \n",
       "2018-12-21 17:30:00  125.0  0.137622  0.114624  0.000386  0.051094  0.131896   \n",
       "2019-03-15 17:30:00   98.0  0.159601  0.036463  0.041959  0.137607  0.172851   \n",
       "\n",
       "                          75%       max  \n",
       "Maturity                                 \n",
       "2018-05-18 17:30:00  0.709154  0.822857  \n",
       "2018-06-15 17:30:00  0.220694  0.347368  \n",
       "2018-09-21 17:30:00  0.154208  0.868657  \n",
       "2018-12-21 17:30:00  0.182227  0.567401  \n",
       "2019-03-15 17:30:00  0.185618  0.223236  "
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     "execution_count": 5,
     "metadata": {},
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   "source": [
    "HTest.groupby('Maturity')['CError'].describe()"
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       "    <tr>\n",
       "      <th>Maturity</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>2018-05-18 17:30:00</th>\n",
       "      <td>39.0</td>\n",
       "      <td>0.130925</td>\n",
       "      <td>0.036927</td>\n",
       "      <td>0.065993</td>\n",
       "      <td>0.106162</td>\n",
       "      <td>0.126740</td>\n",
       "      <td>0.155706</td>\n",
       "      <td>0.203253</td>\n",
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       "    <tr>\n",
       "      <th>2018-06-15 17:30:00</th>\n",
       "      <td>62.0</td>\n",
       "      <td>0.060654</td>\n",
       "      <td>0.015233</td>\n",
       "      <td>0.018222</td>\n",
       "      <td>0.050768</td>\n",
       "      <td>0.061104</td>\n",
       "      <td>0.074580</td>\n",
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       "    <tr>\n",
       "      <th>2018-09-21 17:30:00</th>\n",
       "      <td>105.0</td>\n",
       "      <td>0.098113</td>\n",
       "      <td>0.037721</td>\n",
       "      <td>0.002030</td>\n",
       "      <td>0.075870</td>\n",
       "      <td>0.104823</td>\n",
       "      <td>0.125951</td>\n",
       "      <td>0.162798</td>\n",
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       "    <tr>\n",
       "      <th>2018-12-21 17:30:00</th>\n",
       "      <td>125.0</td>\n",
       "      <td>0.102391</td>\n",
       "      <td>0.040796</td>\n",
       "      <td>0.003227</td>\n",
       "      <td>0.084165</td>\n",
       "      <td>0.115402</td>\n",
       "      <td>0.130891</td>\n",
       "      <td>0.161938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-15 17:30:00</th>\n",
       "      <td>98.0</td>\n",
       "      <td>0.084444</td>\n",
       "      <td>0.041596</td>\n",
       "      <td>0.000239</td>\n",
       "      <td>0.056634</td>\n",
       "      <td>0.088544</td>\n",
       "      <td>0.117916</td>\n",
       "      <td>0.162074</td>\n",
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       "                     count      mean       std       min       25%       50%  \\\n",
       "Maturity                                                                       \n",
       "2018-05-18 17:30:00   39.0  0.130925  0.036927  0.065993  0.106162  0.126740   \n",
       "2018-06-15 17:30:00   62.0  0.060654  0.015233  0.018222  0.050768  0.061104   \n",
       "2018-09-21 17:30:00  105.0  0.098113  0.037721  0.002030  0.075870  0.104823   \n",
       "2018-12-21 17:30:00  125.0  0.102391  0.040796  0.003227  0.084165  0.115402   \n",
       "2019-03-15 17:30:00   98.0  0.084444  0.041596  0.000239  0.056634  0.088544   \n",
       "\n",
       "                          75%       max  \n",
       "Maturity                                 \n",
       "2018-05-18 17:30:00  0.155706  0.203253  \n",
       "2018-06-15 17:30:00  0.074580  0.085125  \n",
       "2018-09-21 17:30:00  0.125951  0.162798  \n",
       "2018-12-21 17:30:00  0.130891  0.161938  \n",
       "2019-03-15 17:30:00  0.117916  0.162074  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HTest.groupby('Maturity')['PError'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
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       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(9,6))\n",
    "ax  = fig.gca(projection='3d')\n",
    "ax.plot_trisurf(HTest['Moneyness'], HTest['T'], abs(HTest['CError']), cmap=cm.plasma, linewidth=0.1)\n",
    "\n",
    "ax.set_xlabel('Moneyness')\n",
    "ax.set_ylabel('Time to Maturity')\n",
    "ax.set_zlabel('Error')\n",
    "\n",
    "ax.dist=12\n",
    "ax.view_init(30, 112.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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VLbiBrktlQqRWAMDoQ0QvVgpbXSrqwpGIcsyZDmNcDhq+GMA6wKh9jxj5flwYTTDfLhCGQiNGQiEIMsMhEaVpCTC4WjZ57hcheM1YtnxGuXOMUYi0cx4jYDw8Rpmv2aRiPKacVsqtVpiDQyENkD0YqW0Ua2uKhhCIqFUBROJylVBvUBYzcfUqvY8o9utbGtzOvvQ1+eDsk0unNkmp56rKryBTZe5gW2cwBiL1WdenN1UAqEs/DqaxWQyiXA40q/Pob/eSo/X0J5jtGq8hvmvWfkQrbXytlQvt6VSwxJrYCC0AaIXK6WNaL2rgoUVO6C+gVBbFVTPMxqtQFQ7Hy43UDwqbKB4vQaI281AIMxAWIXJZAqhUP8CYSWL11sE0Wg8sy213DnGeCYwhuDx+DPbUsW/ZqmUua8Zu6XSaiTWwEBoA0QvVkobydqrglLNgU4NhHodSM2uCmq/hlkBrfrAmN+5sR6BMRqNMRAakIGwOlOpFILBcNHj3SdPWHod2vEa2nOM5cdriDnHKMuy7mtWL7ktlWol1sBAaANEL1ZKG8FqB8znqoIyQqHqq4JaA4EwAMDvD5teFUylSnc5tapilwuM/mzFIxYrXfEwY4uceoNs5U16MxoMMhBWY6lwc3rvt8KvTWtuvEYwO16j9DnG+lb10+k0AoGQ8NdEK7elto7EGhgIbYDoxUqpaEVUBfUCodLAxZwwGIuVn31oZSCspMPhhsvlzVQ8QpmKh5EtcqUDIwOhMRkIq1OWZQQCxYHw5E+vCr+2alTepFHPMRqr6ldac6UEAL8/KPx7rkZuS7WPxBoYCG2A6MVKqSi93jC8XuOBLhyOQpbTplQFtfr95gXCQCCcrQpGIqVnHzZSIDRiqS1yha3+1cCYSslIpeSWmA3XHxkIq1O32tXdhc5vHxV+bWaqVvX136Qp3paaSsl55xiVbal+9PV5AQA+X0D492SmxralMjA2gsQaGAhtgOjFSqkI+/qCkOU0IpG4oaqgJCUBAPG4BJ/PvG2dSiAMAQCCwUi/q4Lqu/lGziM2UyCsZGFgTCZTkGXZ0M2r2oTD5WqMJhxWGgwqbyCIvo5mMZ1Ow+/PD4TOzk9x5MOnhF+b1Rauudx4Db1zjGndcTaN1p3YLNXAyG2p4iXWwEBoA0QvVkqtVHtWUJZlRKPlA2E4HEM6rVYF+xfYygVOoPZAqFQFU4aqglqbpW19LUYiUUhSbsuoevNaPBuu0jDxiK2HiTMQVidQvP3ReeRJHHpzm/BrazSdTg+83gAAIBKJIRLRjrMp1524fs2mGsnygdEr/G+lXSTWwEBoA0QvVkqtsvCsYColIxZLlKza1bMqqBcIa9mGGo3GNVXB6raculwenRsSe6gEwmRVN6/6w8Qbr2ujmSqBMCX8OppFAPD5CgLhwXtxcMd24dfWiLpcypbRvj5f0b+V7k4s6QbG0meH7bcVnIHQPIk1MBDaANGLldJ663brB6JkMqUbCLVVwf5u4zQqUF0gDATC2bBSqcpZOhB6bRsIw+HqAmElc4ExYKBrY2FgDDdsYAyFIgyEBnU4+gAUn4dzHpyFA6+8LPz6GlG32wcAcLurD236zab0zw4DylbwXGW/ud+oYSA0T2INDIQ2QPRipbSelusgqo430K8K6lcO6xkIjQ6111YF+9OIhoHQPJ3OvrzAqFQ71O1xpc5TJRAOq23+xZynYiA0rhoIvd78QOg6NB77XnhN+PU1on19vsx9Rn22fVa/Fbwx1l3l3zUGQrMk1sBAaANEL1ZK66GRuYKSlEQiIcHrDSISiWW2JVlXFdRaalagVr+//1XB/EDoYyC07Aav1Pa4SuepCm9czb2xZiA0rtPpAQB4PP68x91HL8Xe594Sfn2NqMfjBwBh5wC1b9QEAoVv1JSfgRoMhmuagWrOdfuE/w21i8QaGAhtgOjFSqnZGp0rmEgogVCtCpY6T2hVICzXEEatCqZS/asKanW77RwII0gmGycQVrL6wJgypQEHA6FxXS79QNh38gL8vvVd4dfXiKpNZRp1y2bxuosgFqtmBmp9OhSbGQgPH+7E7Nm3YNCgQWhvb0dHxyr09OhXIJ99djtGjrwUAwaci0suuRRPP/183r8/8sjjuPDCYTjnnHNw/fWT8csvv2f/7eRJJxYsWIQhQ9oxcOBAzJu3AJ2dDuH3A8QaGAhtgOjFSqlZGqkKalWrbaKqglpLjcAwuyrYKoFQHT0h+jrqfeNaqgGHXmDUq3TY7XWqp2og1DZIcXTtR9/Jofjf4x8Jv75G1OdTbshFX0f/fu5eQzNQAfMaTjmdftP+Lk6aNAV33jkfp065sGfPAYwadQW2bHmi6HlvvfUeBg0ajK+++gFOZwBfffU9Bg0ajDfeeAcuVxAvvfRPXHjhMOzatQenT7uxYsVqjBp1RXZkxoIFizBlylQcPXoahw934vrrJ2PJkg7h9wXEGhgIbYDoxUqpGXo8xsOgNmSlUrLQIJgLhMUjMHLbWM2rCjIQ2lP9BhyVKx1qBVLU1rhm0u0u7pjpPvE6XEf/ij0Pfyr8+hpRvz+EdDot/DrqaekOxXoNp/S2gwfhdntx6NBRdHU5Mp/TnEC4e/d+tLW14cCBY9nHdux4C8OHjyh67tNPP4+HH34s77Gbb56DZctWwuUK4tprJ+LBB7dk/62nx4tzzx2ITz75CqdOuXDmmWfiyy//k/33r7/eibPPPhunTrmE3hsQa2AgtAGib+Qp7Y/VVgUjkXg2CCYSEpLJlPAw6PUqIzDUQOj3h7I3E/Xcxmr3QMitkPnqVTrUKof2xrV8i//WDYxqINR2zPQcXwPH/hHY89Dnwq+vEQ0EQpDl1p5z6XT2we32Qanuh3W3g3/44Ydoa2vDWWedhUsuuQSTJ0/B/Pl3YcOGB7B9+8v46KMvsHv3/pJbPUv59tvvYciQ9rzHfvxxN9ra2nDsWHfZjz18uBPt7e146aV/wuUKYtCgwfjXvz7Ie864cVfhiSeexg8//IK2tjZ0dvZm/62zsxdtbW344Yefhd4jEGtgILQBom/oKa3VWquCasiKxRJIpRolECojMKxsbsNASLVnLdWOjUa2xqlvqESj8aKzVKK/p3qpdszUBkL/8Vno/uUS7HnwM+HX14gqcy5bOxBWUtlK6sIHH3yI5557HuvWrcfcuXdg/PhrccEFf0VbW1vWOXNur+pv5Msvv4Zhw4bnPbZnzwG0tbVh374jJT/u4MHjGDfuKkydOj0bQs844wx8/PGXec+77rrrsXnzw/j88+/Q1tYGhyNX2ezt9aGtrQ2ff/6d0PsEYg0MhDZA9E09pdVqtGmMaqmGLNFovGG2jCaTqezWPqua29g5EHLgujHD4ajh5juFgbFci//8mXCRzFkqf1POhFPNjVDQBMKTY3Dqh8uw+wEGQj1bbeu2Warn8lyuILq6+rB79/5slbCav5Vvvvku2tv1K4THj/fofsxXX/2AYcOG4/bb56Grqy/7+MCBA/HOOx/mPVepED6D77//b6ZCmGsik6sQ/iL0foFYAwOhDRB9c09pNVYTBCsNb49G45Bl8YEwHI5lt+1Z2dymsFuinWRlwpjVBMJKlj5LVb/mG1aqjlDQbpv195yHk1+Pwu7NPENY6verkca/NIvaQNgff/11H9ra2nDo0InsYzt2vFVUNVTdvv1lnHPOOXj00aeK/u3aa6/LO2OoniH86KMvsmcIv/56Z/bfv/56J8466yycPs0zhK0AA6ENEH2DT6kRzaoKalW3Z4oKgj5fKDvyIpWSEY9Lln59uwfCVj+7ZEQrb9iLA2O0TPONxguMejP1/D1DcOLTy7F7EwOhnpGIsu1Y9HU0kw5Hn2mB0OVStnXOnXsnOjt78dtvBzFq1BXYsOGBoue98cY7OOuss/D++5/qfp7t2/+BCy8chh9++CXbZfSSS0Zmt5TOmzcfkyZNweHDJ3H48ElMmqScgxR970CsgYHQBoherJRW0syqoF5lTkQYDIejSKfTkGXlrKAkKTMRrQ2EAeE3P/WSgdCYjVTB0Q4RVwNjboh4qcCYyATGMLzeQGYWY30Co95MPV/XYBx//3Ls3viJ8NevEY1GlSqx6OtoJh2OPlP/fh46dAK33joX7e3tGDr0PKxceT96e5U5hwMGDMArr7wOlyuI0aPH4M9//jMGDBiQ5z333AuXKwinM4BHH30KF110MQYMOBeTJ9+AX37Zm/06nZ29WLRoCc4//wIMHjwECxYswsmTTuH3D8QaGAhtgOjFSmkpa60KJpPGxjSEw1EAsDSE+XwhJBJKVTAel+DzKY8nEkkkEkkGQpMMBBgIjdhIgbCSyizG8t0aVZT/DhS29+9fYCwKhN1O+E4NwvF3L8evGxgI9YzF4ojFGAir0exA2OoSa2AgtAGiFyulhVY7SiIQCGc7IVYzvD0UsjYQhsNRyLJSFQyF8s8KqjPhGAjNke3ujdlMgbCSSmD0ZgJjyEBgTGUCYyw7D04JjPqjNQqHrDuO/whv5xAc//fl+HX9x8K//0Y0Hk8gGo0Lv45m0uHwCP8bbCeJNTAQ2gDRi5VSrdVWBWOxRPbmzu+vbnh7KBQBAPh8oboGL6UqKAHIrwpqjcdFBUJ7dhlVAqG9B2KbYSRin0BYyeLAGMkERslQYIxEopm/mUpg7DvwIjxHz1cqhOs+Ev79NaLqLEvR19FMMhCaK7EGBkIbIHqxUupy1VIVjCCVkpFOpxGJGK8Kag0GlUDo99cvEIZCUciynKkKRks+T+3GaHUgdLkas6Njfw0EQkinGQgr2UqBsJIOhzJ8XhmtEcrMYoxnZjEWB8bEkcfh+WM4Trx7OX7f9Bn8/mBmFqN+hbEVlaQkIpGo8OtoJhkIzZVYAwOhDRC9WCm1siqYHyrDANCvz1FKbVUwkZAqViFjMWsDobrNViU3aDyWGTTe3De3fj8DoRGVQMgukEZU32RQA2P495Vw7fsbjr05Bgce/DLv76ra4dhOa6oWk8kkwuGI8OtoJh0Or/C/yXaSWAMDoQ0QvVhp61ptVTAY1FYFY6aEIgCGGtBUY64qmC5bFSwMhKmUNYFQ23zH6w1kB41Ho7FMNSR/blwz3tz6/UEGQgNyLIBxC8+lBn++Hb2/jsSRV6/EL6s/RG+vGy6XJxMYy68pQPsmTDyzpkKZNeUV8v3Vw1QqhVCIgbAaGQjNlVgDA6ENEL1YaWtaS1UQACQpadoWT78/BACmDYP3+ZSzgACQSCSrOpsYjcaRSsl1DYJ+f6hoJEe5GxOjN7eNGBj9/vwGIFRfBkLjFo4yCe26Ed27LsPh7ePxy+oPDH0OvTWlbhcvFxjD4UhmFqNf6CzGalXG6oSFX0czyUBorsQaGAhtgOjFSltL0VXB/ABnXiAMBiPZqmA4bKwqWBgIZbl+gTASiWWCm5xXEe3PjUu5wKilMDAa6ejYXxkIjclAaNxgUNlmrf7/oZ3j0fX95Tj49HX4edX7pnwNp9OTmcUYzDSyKR0Yc7MY45lZjCF4vYGGCozpdBqBQEj4dTSTTqdP+N9pO0msgYHQBoherLR1DASq6+oZj5tfFcwPhMofC6PbOo1cZ60dSyOROGQ5XYfvMQRJUuYexmKJon93OOp3Y1M6MPZ/BEAlC0cEUH3Vn4no62gGQ6FIfiD8zzh0/ecy7H9skmmBsJKlA2OyIQMjAPj9/XvjqdVkIDRXYg0MhDZA9GKl9tftzlXRgMpdPdVqWzqdRjhsblWwUAA1VfTMvk61gmfm96ade1iqClrPQFhJl8t4R8f+zoyj+jIQGjcUiiCZTKG3xwXn6f8htHM4/H+cgyNPXY2fV7wn/Pp6e91wOvsygTGQHZWhBkZZLhUYE5nAGM4ERh+czv4HRoejDwDg89l33ml9foYMhGZKrIGB0AaIXqzU3mrPClZq4qI9g1evqqB+IKw+zJl9pjEcNi8QGpl72AiBsJJ6gdHozLhwOJL571tjbJ1rVBkINZ46DnfnF/AdfR6Bw/cjfOB2RPdfj9i+yxRidsAAACAASURBVBDfdz6k/edAOvgnSIf/L6Q//i/ie/+EyPH/h8/OX4OflzdGIKykMovRB2UWYxjhcBSxWAKSlCyxrpKZdRXNvBETyLwRU3ldOZ1KIPR6GQir0en0C/+7bSeJNTAQ2gDRi5XaU72zgn6/GgiLq1WhkHVVQa3Vnk2s15nGcFgZet3fz6O+jpXmHuYCYXMGJnVmnNfrLxgybv6NrZ1lIMwZ/+AyyJ+fCfmLMyF/eSbkr86E/PWZkL85A/K3Z0D+7gyk/nMGUt//Gakf/ozEZ+ei58nR+HjgZvy3413h12+GSmD0ZgJjKBMYy62r0pV7l8sDAPB4/MK/r2aSgdBciTUwENoA0YuV2k+PR79xjF4Tl8KqYK1n8GpVlo0Ptq9Hp9NckOt/IFTPMlbT4bRZA2Elvd4AAGW7mrEbWyUwFm6ds+vro6p2uRR9HaJ1Hf8J0gdDkf78LEOmPj0Tqc/Pxs83/l0JhMvsEQgrWTow6lfulf9eSqadDW4FGQjNlVgDA6ENEL1YqX2s1EG0sImLdl5fref4+h8I5ewIhlIqQ9zr0+m0MBCW295ZSm3Vstrqql0DjxoIS31/1VRCZDld4qxV43RzrNVoNM5A2OtGZOffkXxvsOFAmHznXKQ+OwefDN6oBMKl/xb+PTSC2sp9KKRs247HEyXPBjfauJpG0OkMCP9bbieJNTAQ2gDRi5Xaw1JVwUIBpYmLesat2nl9ZptKybrdN1VjsUR2a1Q9zzSqDXeqfS3U66u1atnsgaaUlQJh5RtbvcConrVqvG6OtcpAqJj69AIk3x1oOBBK7w1G4J9X4OOBm/HxwM346V4GwkI9Hn/mHiM/3JVuJlV+XE2rBEYGQnMl1sBAaANEL1ba3FY7VzCdTiOdTkOW0/0e92CGyWRKNxAqVcFUpipobEupGYHQaKjLv77aq5aNHlhq1etVbkbrdUawfHOO5gmMsRgDYW+vG/LHA5D897kGA+GZSH12NjofnJ8LhEveEf49NJpqIKx2e2i5+aaFozVygTGeCYyhTGD0Cv/+a5WB0FyJNTAQ2gDRi5U2r0argl5vfufLZDIltCpYGAjj8fxAGI3GNVVB/Y6oZqt2YDXy9cy8PtGBpNFuRs27qSvd/r+R5sUxECrKH59jOBAm3z0XqU8H4LeFW3KBcDEDYaH9rdKXsrrAKOcFRmVt+TNrS/xrVKjD0Sf877rdJNbAQGgDRC9W2nxqR0kYUTsPz8iZPSuVpCQSCSkbypJJ5abC6musNJLD6w3C7w+Zfn0MhGKsPjBKmcCYu6l1ufp/U8tA6EZvdzfkj85G8l1jgVD610DE3h6Bn255JhsId93zL/HfR4Mpahao0+nJrK1gZm3FMmurODDmry3x1XsGQvMl1sBAaANEL1baXFYTBJWqYBIAkEhI8PlCSKX0t2iKMpFIZt9BVqtu5UJZvcyN5ND/2uqcwlRKNvX67Dp2odT5pWaxmpvawipINdvmYrE4YrHWDoTO479D/ugvBgPhmUh9fDaC26/Gj7OezwXCu98W/n00mn5/COl0Wvh1FP28S64t8dV7MwPh4cOdmD37FgwaNAjt7e3o6FiFnh5v2Y954413cNFFF+c9NmDAgDzPPvtstLW14dVX34DLFcSOHW/hjDPOyHvOvHnzhd+rqBJrYCC0AaIXK20O+1MV1J4V1NuiKVJJkrLnGkVWLv3+4pEcXq8SqiVJCdX1CNKNWkHrr80eCGu/qa0mMHoYCHvdcB/8BvJHZyP13oDK20XfG4DkB4PgfWoyds7anguEdzEQFhoIhCHLsvDrqNbatnubM7LG4fCY9jd70qQpuPPO+Th1yoU9ew5g1KgrsGXLE7rP7enx4pFHHscZZ5yBESMuKvt5581bgKlTZ2TD5cqV92PBgkXC71FKSayBgdAGiF6stPGttiqoBph4XCoaoyBJScTjkvAg6PUGEYnEs2FQRFWw8HUD8gOhMpZDCdWFQZGBsLx9fb7Mf9/s+f1Vvqk1HhjT6XTLdXLU6vnfW0ogfL9yIJT+NQjhHVfB+9QN+H66NhC+Jfz7aDSDQWVcj+jrMFuns1xDqeKRNeqM00gkmpnFGMjMYiwOjGYFwt2796OtrQ0HDhzLPrZjx1sYPnyE7vMnTZqCadNuwrp1m8oGwhdffBUXXHABjhw5lX3s+usnY+vW54Tfp5SSWAMDoQ0QvVhp41p9VTCW6SAqIxTSDzDaM3ui9PtzZwWTyRSSyZTQ69EGwlAoCp8vqBnLURyqGQgrmwuEzdttsJ6qjTkkKYlkMlmyMUcrtP73/vIc5A/PRuqDcypvF/3oHDifXAjvUzfiuym5LaM/LmAgLDQUiiCZTAm/DqutZsZpOp3G/PnzcdNNN2Hp0qV45JFH8corb+CLL77D/v1H4XDUNqT+7bffw5Ah7XmP/fjjbrS1teHYse6i5+/bdwQulxL4SgXC48d7MGRIO3bseCv7mMPhx4AB52L69JswfPgIXHjhMCxatARHj3YJv39RJdbAQGgDRC9W2nhWO0rC7y9fFdSaSEiQpKSw4BWJ5J/Fi8USSKXEB0KvV/nDFY3GM813rBnLYfdA6HYzEJYzHk8gFosXPW60k6MdAmPgx4cgf3gOUh+WD4SpD85B8p1BOHn/KnieuBHfTHhWEwjfFP59NJrhcBSSlBR+HY1mYWB8+ulnMHfuXFxzzXgMHToUbW1tWc8880xcfPElmDXrZhw/3mP4b/jLL7+GYcOG5z22Z88BtLW1ZcOfnuUC4ebND2PcuKvyxmIcOnQCEydOwvbtL+PUKRd+//0PTJo0BTNmzBR+H6NKrIGB0AaIXqy0say2KqgGLKPbGuNxSUhFTg2t6XQ67yxeNBpHKiULD4NqIAQASUpaNpaDgbC1LRUIK1kuMGpRA6OyZS6W2TIXzGyZa4zfvdB/7oP84TmQPzq74nbR6LbhOLxgKdxbpuPL0U/lAuHf3xD+fTSakYjyOyH6OppJh8OLzs5e7Nq1G//+90fYuvU5rFq1BkuWdKCz02H47/ibb76L9nb9CmG5YFkqEDqdAQwfPgIvvfTPil/7229/xJ/+9Cd0dvYKv59xuRgIrYKB0AaIXqy0MexfVdB4s5NYLGF5INRWBQtDq1qRExkElSHzMtLptOXnKxvlptxs3W4GQiPWGggrWRwY45nAWLxlTm00JSowhr68C/IH50D++C/lG8q8PwCBB6/GsbsWoGvDbfhsxKO5QDiPgbDQaJQjTarV6fSZ8vf811/3oa2tDYcOncg+tmPHW0VVw0JLBcJvvtmJv/zlbJw65cp7fOfOX7F69bq8quHnn3+HM844A11djTFCg1gDA6ENEL1YqXhrrQrqBaxKWlmR04bWUh061e9FVBjUjrtIp9OIRGIMhCbodnsBMBBWMh5PIBo1PxBW0uXyZgJjSHhgDL9/E+T3z4H8afntotJbg+F/8g6cXn0HjnUswseDH8gGwp13vi78Z9losoNt9ZoVCF2uIK677nrMnXsnOjt78dtvBzFq1BXYsOGBsh9TKhA+9thTuPbaiUWP79t3BAMGDMAjjzyOnh4vfv/9D4wffy3uuuse4fc1qsQaGAhtgOjFSsVZS1UwmezfCASrKnLauX3lQqv6PKuDoLaxjTruQpYZCM0yFwh9wq+lkRUVCMvpcOQCo9KUI5JpyiHpNuWopoujntG3r4H8voHtolsvgvvJDjg2z8a+v9+XDYMfD9yMnXcwEDbD71aja2YgPHToBG69dS7a29sxdOh5WLnyfvT2Kp9/wIABeOWV14s+plQgvPfeDtx22x26X+fTT7/GhAnX4dxzB2Lo0POwbNkKnD7tFn5/o0qsgYHQBoherFSMVlYF9T5PvQJO/tiLyqE1HI4CgKUhTB13kUql8sZdyLJs+SxEuwfCvj4GwnI24017rimH31AXx0qBMf7G5Ui9V76hTPLdcxFcPxrdm+9D35bp2H3zA/mB8PbXhL8ujWYiISESiQm/jmbS6aytqygtLbEGBkIbIHqxUmt1u6sLDNpKlhmD0cPhGID6BLBwuPq5faGQdYEwv7FNcfBLpRgIzdLlYiA0ohII7XXTXk3bf1lOQ3rjIqTeLR0IUx+ejcRr7QiuHYuji1bA8+RU/DT10bxA+MNcBsJCJSmJcDgq/DqaSQZC8yXWwEBoA0QvVmqd1VcF45oRDeYMRq9HAPP5QkgkjI29KL6eCADUvaunkS2sqZRsSuiuRrfbA4fD2Na6ZtLl8gBgIKykOi5C9HWY9nP/7QOEv1iA4Ler4N/1GLx7dsB98Gs4Og+jt8eF3t7iwCi9fgGS75QeSi/9axAiT1yM4Pqrsff6RfA+NR0/3bQ1PxDetkP4995oJpMphEIR4dfRTDIQmi+xBgZCGyB6sdL6K7oqWM8AFgrlqoKhUPWhNRhUrsfvr08gzA+r5V/LZDJlaSBUQyoAyLIMSZIQi8Uzs+RCmVlyzdmURQ2EHo9f+LU0snYLhN63ViP+4sVIvTYEqTcGK76uOgTJN85H8s1hkN4eicQ7YxF/byKSr7cj+c65pQPhO4MQXDsGwSfmYO/4hfA/fRN2z3khLxD+9843EA5HEQiE4PUG4HZ7bflGSzWmUgyE1art1knNkVgDA6ENEL1YaX2ttiqodr0sPN9mlmYFMCVoSQCARKK6qqDWQCCcuR7zv1clrMqGw6raTbHeQVAbUqPRGLzeAILBMCKRGOLxRPbNAC3NNnycgdCYdgqEjiMH4Ht+LgJrx0J68QIkXz4PqdeGQH5zcFmTbwxB8u2BumFQ/ugviL9yPoJrx8L/zDLsnbgIfY9Px66bt+cFwp9ufwPJZLJo3ShvtCQRi8VbLjAqW/fDwq+jmWQgNF9iDQyENkD0YqX10e1WmpQY7VoZCBR3vayHagDrT9jMD1pR4ddTHLiCiMe1YdVY+JWkZN3nEIZCkbyQ6nJ50ZPZSldoNcPHS48GEHPT63QyEBrRTo0/PJ9sg2/rLPhWXoPIoyORfOkCxTLBMPXGYCRfHwzpLf1AKP1rIMJbRiK4dizcj96PA7esgvuxGdg5Mz8Qfn/Lq5rfvT709fng86lvtEQzb7RUCoyRTGD0ZwKj+Ne0P6bTaQQCIeHX0UwyEJovsQYGQhsgerFS8/V4FI12rdTOwqtHVVCr3197APP5ggVVwf5v8/T7QwDQr86pWoNBNXClEQ5XF1YlKYlEon6BMB5PZF67ZPa1KxcIK6k3S87IaADlZ1/fKgkDoTHtFAiDT86Af8uN8K28Br5VVyHx/IW5UFgiGGYD4ZuD9APhm4OV7aJrx+LUitU4tGAjXFum4/vpBYHw5lcNX2fpwFhcmW/mrdwA4PcHhV9Hs+hwNMYgd7tJrIGB0AaIXqzUPAvnCqZS5c+kBQJhpFL1rwqaEcByla10v6uCWn0+8wJhLKYELklK1hRWE4n6BELl5ywjnU4jHM6vGLtcvpoDYaWbG+OdHsttq6vt6zudfQAAr5eBsJx2CYSu375HeONo+DdfqwTCldcgtOmK/ECoDYavK8Ew9fpgJF8bDOmN4kAof3wWYi/+FcG1YxFYOw4Hpi3G4SWb4HhgJr6b8nx+IJz9imnfi9PpyQTGoIGt3HJm229jBUaHQ1l/Pl9A+O9Gs8hAWB+JNTAQ2gDRi5Wao1oV1N7slzuTZmVVUC+AGQ11+dsvawtalT5/NddTKXD1Z7B8IiFBkpKmfn/an7PeuU23uz6B0MjNj9ttrEpSfNNb+fxiLhDyhrScdgmE3rc3IrRhNPzrxmUDoW/l1YhtvUg/FL50PpKvnIfUP9uVQPj6YJ1mMgMReugy5fzgw9Oxd/xCdN6/CqfX3I5vJjybFwj/M9O8QFjJ/gVGa87+8g2Z6mUgrI/EGhgIbYDoxUr7Z2FVUKveFkQRVcFCARjaTtmf7Zf1uJ5aAlc1xuPmBUK/P2ToTKioQFj5hrL4plc9v6i96VUbIGkb3vh8yk0vwEBYSUmSEIk0+ay4090IPTQBwU1XI7B2rCYQXgP/mnFKgxndUHgBkv84H8nXByPx2pCiQKjOHgyuHYu+J+7C3vEL0bVxEf5YfA++HP1UQSB8WfzrkNHo2gHq1yyKTZ2q1+HwCL+fsKPEGhgIbYDoxUprV68qqLWw4hSLJTThxbqqYKF6WxeLw1H/tl9WHwirq+xpR3OYFazVd/n7+3nC4ahmfmT5n3OjBkIjN5z6DW/0zi8WNrwJCG1400hKUrLpA6H7h3cz20WvQ2DtuLxA6Ft5DSKPXFo6EL6kHwjlT85C9Plh2UDYu2UF9o5fCMeDc/D77OX4bMSW/EA44x/CXwejlmsWVenNFqOB0e32AuAc0GpkIKyPxBoYCG2A6MVKq9foKAm14hQIRDRbGsVUBQsDYamtlcFgpOR5NxHXo2ckEsveLJm53TYW618g1I7iMNqttFkDYSXdbh8AIBKJIhyOlDm/mM6cX0y03FiA3l4lEIbDzR0I/S/dowTCjRPhX1McCH2rrkbiuWGlA+FrxYEw+c5AhDaPygbCk/etwt7xC+HeMhP/vXIFPh78QNMGwkqaERi9XqVC73Y3fvObRpGBsD4Sa2AgtAGiFyutzmpmCsZiCciy3BBVQa2lup9qm7LUa1C8/vUYC8p+fwiSpMzvq8cA+VgsgVSqtkCo3V5bzXlIuwZCh0PpcqjX1CK/4U040/AmAUkyNhagEZp2mGWzB0LH0cMIbRqD8MbR8K27Vj8QrrwGwY2jqwqEiX8OzYbB4NqxOHTzvdh73V3oe3QGdo1bkxcGPx64Gd9Ne0n4a2GVRsfRAMqWVP1xNI05v1To77LDK/z+wo4Sa2AgtAGiFys1ZrUD5pWAkO53o5N6mErJeYFKWxUUca1GxnNot2GaNaKi0Gg0jlRKrvrj+tPdtK/PnoGwt1cNhNW3vS8eC2CkaYe5Z7CsstkDoeez7QhvHK0EwtXj4b9fPxD6Vl6D2FN/KxEIh+QFQvnTMxF5ZkQ2DPofmIS94xfi4M33wf3YTOy67oHiQDi1dQJhJV0uD4JBZbxQOBxFNBqvYjt36wZGBsL6SKyBgdAGiF6stLLVBEFtQEillAHkogNgodrup+q5RqurgloLA6rWWrZh9icQVvPz0jYIqjVI27npA1BbIKyk2rTD6Ja6Rr7hbfZAGNg6KxcI77sa/tVXlgyE/vuvhPRCcZVQ2jEEidfa87aLBjdckQ2EnsfnYe/4hThy12a4Hp2Fn258tDgQ3vii8NeikfT5AgCgu+1ab35p9YHRftu5GQjrI7EGBkIbIHqx0tLWUhXUVtrUs26iA2ChSvfTpNCqoNZkUn9eYygUzWzDlE2dfVjKSCQOWTb284pE4qZsBbZ7IBQxGDu3pS7/hrfw/KLy80tmbnijCAbDUM4v+iw7v9iwgfCr99F74Leyz3H+visbBkMbRithcNXVJQOhb+U1CD98mW4glDQVwvgr5+dtF3U8ugx7xy/E8Y4tcD0yG7tmbC0OhDcwEGr1+5Ub8Wo/zuFwZ7Zz+zPzS9Xzv8bWTzM3jHI6fcLvOewosQYGQhsgerHSYsuNkiiltiunWmkLh6MAIDwAFqoGQTNGNZih3rzG3OxDqe5dTnMhr3KAV88xptNpxGL9bxDk8dh3LAMgJhCWM//8YihzfrFUwxvt+cXChjfmXE8y2aCBcONiBNZeCe/zi9F7/Ljuc7zvPJALhOvHlK0OamcTJrblN5iR/pkLhPJnZyLy5N/yAuGptSuxd/xCnFj5GBwPzcauWduKAuG3U14Q/5o1kIFACOl02vTPW836KRUYrXzDpRoZCOsjsQYGQhsgerHSfGs7K6jflTMUUgKhVYGmktotjrU2T6mH2nmN+V1O618V1BoOlw+E6jlGWTbvHKOdA2E6nW64QFhJ5YbXB69XPb8YzZxf1G94kz90PFT1+UUlEEaEf9+F9qycC//qKxFcOxaBtVfC89pG9Hb15p7T1YPQw9dlA2Fw7ViDgfAaBB6ckH+GUBMIpXcGIrhudF4g/GPesmwg7H1gNn6c/XxxIJzMQKg1EAhDlmXLv251b7gUdhhWK/RiOgwzENZHYg0MhDZA9GKlitVWBX2+XBWr1Pm7YDACAA1RhdMOcE8kJFPm7ZllIqEEQlFdTrWBDyiu6Pp8wbxzjD6feV/T/oEwJPw6zL1pLB46rtfwptRIgMLzi8lkCqFQAwbCxTPgv+9KBNbkgllg/TVwf7ANvT0uuH/8MBsGwxtHI3D/OMOB0LFlGTzrxuUHwteVQBh76YK8MBjYMB57JyxUAuGqR9Cz8RbsnLm9OBBO2i78NWskg0HlzT/R11GoeRV68wOj0+k35V7i8OFOzJ59CwYNGoT29nZ0dKxCT0/584lvvPEOLrro4rzHHA4/BgwYgHPOOQcDBgzIevKks+avI0JiDQyENkD0YqXVVwVDodJVQa2BgNLpzcxZedUaCBQPcO/vvD2zlSQJ6bT4jqxqRVf7WK3jJIyqBEJ7dhlNp9MIBOwVCCtZeiSAfsMOtUrSSOevujq70XvXZPjvuypbJdTq33Q9/M/MyQuE/tVXwnffVYYC4Ynlq3Bg8u1IbL8wEwjbkXh9COTPzkT40Uvyvpb3sduwd7wSCE/dfz86V87D99OLA+E31zMQag2FIkgmGy8QVrLcSBpZLjeSpv+B0axAOGnSFNx553ycOuXCnj0HMGrUFdiy5Qnd5/b0ePHII4/jjDPOwIgRF+X9265du3HWWWehu1t/PmI1X0ekxBoYCG2A6MXayva3KlhpK6jfHwKAuo1JqKS2KqgNpbFYbeMV6nmNSjVJ7JzG3BZf9XXKdWCt17ZfBsLWUtvhMRxWRtOo3Yi1qOevRGynO/XNT3DcNUkJhPddhcD9YwtC4RiENozOC4S+VVcbCoTeNZOx7/q7sHfiXehbPyEbCKXXhyD573MRXDsm72s5H79XCYQTFqJ73d04NH8xvptSvGX0m4nPC//ZNpLhcBSSlBR+HWar3dIdCFTe0l1NYDQjEO7evR9tbW04cOBY9rEdO97C8OEjdJ8/adIUTJt2E9at21QUCF944RVcddU1pnwdkRJrYCC0AaIXa6tafVUwmq0UGT3b5vMpgTAUsjYQ+v3FVcHCECZ6HIbfH8peYzKZaoiKpbrFNxCIZK+t3hVLO28ZlWUGwkpqt4zqb6erpjrih8vl7fc1HX/pbTgWXZ8NhIVbR4PrxuSFwdCG0fCtNBYInVsWY9+EBdg3cwV67p6OxLYLkXy1HdLrgxF74a9F1ciuTUpDmQM3rYBz81zsuWE5vpnwbHEgvO454T/LRjISUSrToq/DaotnmJYOjF988QWuvfZa3H777VizZg22bt2Gd975ELt27UFnp6Om+4q3334PQ4a05z3244+70dbWhmPHuouev2/fEbhcQbz44qtFgXDx4mUYNeoKXHXVNRg6dCgmTpyEL7/8T01fR6TEGhgIbYDoxdpqut3V3bBr5+DV0vESgCUjE1TVcQipVKrkVlXR4zDUr59KyQgEwojFEg3R5EYNhJVePzO1dyBUfr6ir6ORTaWMnyEsfbObKrrZTaXkovOLRhveHNv4JJx3T9QEwqsQuH9cNqQVVgdD60crgW9V5UDYufo+JRDOWQvH4ikIP3ipEgjfGITQwyOLAuHRe1Zg7/iFODxvA9yP3IJdozrw5RVPFgXCr69lINQajcYRjyeEX0ejqV1D//vf71iy5F7MmDEDl156Kc4880y0tbVlHTp0KK666hr8618fGL6/ePnl1zBs2PC8x/bsOYC2trZs+NNTLxCuWLEaCxfejf37j+L0aRe2bHkSAwaci99+O1jz1xEhsQYGQhsgerG2krVXBWufg1fpnKFZaitulcYhVOqmWS99PmVkA4C8uYPRqPgtrD6f8voBSuMYK7+26JukeslAWNlqAmEltQ1v8s8vlm54Uzxw3INjS++H857r8gJhrkqYXx0MbxyNwNoxmUBYfgahd/VE7J+yCPsmLMDeW9fDfe91CG24AvHnLkT85aFF20UD667EvkmLsHf8Qvyx5CG4t8zBrpEd+Gz4luJAOGGb8J9lIxmLJRCLxYVfR7OobCH1Yf/+o/jii+/w8suvYfPmh7Fo0WJ88slXhu8x3nzzXbS361fujh/vKflxeoFQz8svvwJbt26r+euIkFgDA6ENEL1YW8Hqzwr2ryqoVZbTiET6P6+unIUVt0rPFzEfMRyOQpb1RzaI3sKqBP909hyX1U2AzJpp12gqP2sGwnKaGQgrWdzwJq7b8KbzrsU6gVCpEobWjy7aLupfPc5QIHRtuVupDk5YgN+mr4WnYzxCG69A+JFLEH70b0XVQd+WWdmGMkc7HoFry234ceRyfDz4geJAeM2zwn+WjWQ8nkA0ykBoVIejz5R7jV9/3Ye2tjYcOnQi+9iOHW8VVfMK1QuEa9ZswPff/zfvsYsvvgTbt/+j5q8jQmINDIQ2QPRitbvVVgW1wcWMrZ6plKx7js8M84ekJwx/nJXzEbXhutTIBpFbWNUmQYmEJKwrrF0DYSrFQFj5NUo1xGvkcLgz5xf9OHHbXLgWFwdC/33jdLeL+u9Tx02UD4Sn1t6XDYS/Xr8S3pVXI7RxFMIPXo7g2iuKAqH78btzgXDpQ3A9dBt2jVtTFAYZCItVq7+ir6NZNCsQulxBXHfd9Zg79050dvbit98OYtSoK7BhwwNlP0YvEM6adTMmTpyEgwePo6urD5s2PYShQ8/D0aOna/46IiTWwEBoA0QvVjvb11dtcFG2M/a3Kqg1lUpVFdaMqq0KVtvF1Kr5iOp4jkrhWsQW1kAgglRKHR2iXJuorrD2DYSNEXYa2UZ7jbo7u3Fi9iy4F1+rWyEsrA4G147RnB0sHQi9912LAzOUhjJ7xy/Ab5M64L/vSoQ2XY7QplFFYTC4diy6H1qRDYRH7tkExwNzsWticXXw44Gb8dVVzwh/ekp4bgAAIABJREFU7RpJSUoiHI4Kv45m0eHQH+1Qi4cOncCtt85Fe3s7hg49DytX3o/eXmXo/YABA/DKK68XfYxeIDx69DQWLFiE8847HwMGDMDkyTdg585fDX2dRpJYAwOhDRC9WO2s0UBodlVQazKZMvVMmloVBFBz0FQrYfUc8xCPK0PmE4nKIxus3sKaG8eRzAvFaldYBkJztHI7ZLPaaFXUk1u34uQtN8G9pDgQFnYXDa5TzvxVqgz6Vl4D/+O57aL7Ji7CgVnLlTOJmy9HcENxdTC4diyOd6zMBcJFG9D7wO346cbHGAgNqO1eSytrZiCk+RJrYCC0AaIXq52tFAi1TU5KbWfsr5KURCJhTiBUK2m1VAW1+v312xoZDGorb8aa6egNhK+HlcZxiBgT4vMpejx+OJ2VO0A2kwyERl6jxgmE3d9+g5N33IpTt86A+97CQHhl3nbR0PrRSuOXNcYCYdfG3HbR/Tctx5Hb71Y6lm6+vKiZjOrBGUtygXDhevRumotdN23VD4Tjnhb++jWSjVZ5bnQZCOsnsQYGQhsgerHa2XKBUA1Xek1OzDSRkCBJyX6GBm1w7f/203ptjdQOcq9mO6q6hbWeZxpzYbr8OAnAujEhanjWos5ljMcTiESimQ6QAbjdvroPJDdbVikq20iNd7rvvQOdt87Cqdumw33vhPztomvG5jeSeXCKEgjvH1t5GP3K8Th0873ZQLh39v04Me8OTSAsDoPBh6dmw+CBGR04tmQzejfcjl9ve6FkIGy29VHv3yt2+DWuw+EVfr9iV4k1MBDaANGL1c7qBULtlst4PFGXqqBWdU5Y7UGmdHfOWs1VwswJPoFAONvavpZB7vU801hq1EUpAWTPFNZTdduqJCXhdnvhcnkzHSBDCIcjiMXimYHk+YFRbyC5Ml+u/wPJzZaBsLKNEgi7P/oA3XdMxYnZM3F67jT0Lc0PhKH1ue2ijruuR8+DHQiuHZvrMFrGvofuyG0XnbAAe2euwemFs5Xgt1E/EPY9sSAXCG9fgxMr70fn8oX47y36gfDbK58tuT68Xj/cbq9tt2brmU6n4feHhF9Hs8hAWD+JNTAQ2gDRi9XOFg6hVxux1LsqqLXWoevaJjf12M4KmBN8cufxUjWfSazXmUbtHEmjP2/ldanf3EjtvEh122qlyobD0ZfpAGlkIHkqbyC5dr6c1TdZyWQS4XCDB8Kubjh//kTY12+EQNjT40L3olvRc+dUHJ85C123T0XfMk0gXH1lNgz67x+Ho9NuxdHpc+DbMgv+1VdW3i76wKq8QLhnymr03D01Ewj1zw/2bunIBsJDizaja81iHLxjKXbO3K5fIRyzFT6fkfUhZ9ZHHKFQBH5/MPOGir22ayv/PbXvjFOzZSCsn8QaGAhtgOjFamfVQFhYFazXzX6pwFTtjD3tXLx6bV+s5oyf0WBTq/UY95BralNdx9haq5xGDIejuvMi+7vVzeksnC8X050vpzbSUbejKtcQyFRPzN9upwTCxu50GHprHmIvXATn3m+EfP1G2NrX/eYO9Nw5VQmEN81G1x03wrNsfK6ZzNqx2a2inTfPxNFpc3B02hx0rV8K/31XVQyEh+9YlqsOjl+AX8Z1wLl4khL+1usHws7VuYYyh5c8hJ71d2D3xOX4frp+IPzyiqfKro++Ph98vmAmMKrrIz8wqlvK1TdUlO3a4t5QqVWHow8A4PUGhF9Ls+h0Nl53TrtIrIGB0AaIXqx21u3u33gGM6xmxp52Zp8SZOp3Xf0JPtrmNmaEODPPNCrbV6traqNVlusTCNV5h3odZ+t99snlUubLBQIhhMPRCttRJcRiavUk1K/qSaO3vvd+/zwS24Yj/sJfEXt1JNxfvWD5NYgOhN3dDnQvmIWeO6ei+46pODbjZnTfeSM8HeOLmsm4Fl+XDYOq3lXjy28XfeDW/O2i4xdg18ilcN97rRL+1o3WDYSHbluqCYQPonfTbdg1sgPfTX5ONxB+Map0IKy8PgrfUImXeUOl+HyvEhgb5/yi0+kBAHi9fuHX0iwyENZPYg0MhDZA9GK1sx5PqOqh7WZrdMaednujFU1NZFmuurJX7Xm8aj4v0P9AmL99tbbziLW8LuXUBtRSP1eRzTAcjr5M9SSQrZ7obbfTVk8ikcLqif71N3IgdP6xB4nnLoK0bTji2/+K+AsXIPXPoYi+OAbunf+y7DqUQCjurFf3i89mq4Onb5umBMJ5N8Kz/Jq82YOBNWNxdNoteWHwyNQ58K4oXx3seWhFfiC87i7svHgZPB3X6DeTWTsWgU0Ts2Fw7/iFOLxoA3o33I5dIzvwzfhn9QPh5U/W7TUy/oZKOnN+MaE5v1i/Cnzp61UCocfDQGhUBsL6SayBgdAGiF6sdtfrre/w9UpWGqng8wULqoLWXG8qJVcV6rTbWM2utPp8/evuaeb21VTKvEBoNKA2UnVB7+bSePUk/2Y4mUwhEok1XvfHHhfiL42FtG24EgifvxDx7X9F6p9Ds0ZevBouC84WynJaWCDsPtmF7r/PyFYHT94yA8dnzEbPvBvgzQTC4LoxCG0YjZNzZhRVB4/NuLnidtEjC5fnB8KpHfh53HL4Vl5VMhB6Hr8jLxAeun0VetbfgV0jO/DlFU/qB8LLnhDyGmrP9wYC4UxgTCCZTBadX8xveKOtwJvbEMrt9gIA+vp8Ql6TZtTp9Au/V7GrxBoYCG2A6MVqdz0ea4JfKcuNVAiFIpmqYOnqUb1MJlOGAmFxYK3P9QC1Nbkxe/tqtUFZTyWgJg0H1GY6n6Q1/2Y4lL0ZliT9m+FGaeYRen9RNgxK24Yj/tyFiD13YV4gTP1zKJKvDkX4HxPh/O27ul1LOi0wED61JRsGu+ZOQ+fsmTg+cza6590A74qrs9tF3UsnFIXBo9Pm4MTsmWXDoGfTzLwwuG/CAuydsQq/3dAB/+orSwZC52NL8wLhwZn3ZgPhZ8O36AfCS8UEwko6ncYq8EBxQ6ha10hfnw8A4HY3XufhRpWBsH4Sa2AgtAGiF6vdFR0IAwF1pEIurPh8uTNliUTSsqqgVqW5SPF5Nq3BoHWBFaiuu6f2vKWZjYKMBuVShkLaxjHGKqnNGggrmUgo5xGNNPPInc2K5Z3NMru66PnlLSQ0YVDaNhyxbRcitm1YUSDMBsNXhiL08lQ49/1s+mtUj0DY0+PCH29+W/Y53UdOoHvedCUQ3j4VXXOn48Ss2TgxaxZ65t0A38qrEVgzDsF1Y4q2iqqenjutbCDsfWR5USD839T7cGDmYgTW6IfB4NqxOLV+VTYM7rvhXhycswI9G+fhx0uX4+PBD+gGws8veVz473stlm4IZWSN6De88Xj8mXsLe/53pT4/BwbCekmsgYHQBoherHbX6qBVaGEHTTVkKU1PrK0KapWkJBKJ0oFQ7dIpSdYE1mqa3OSCqvnnLdWbrlo+Nhfyq6uk2jkQRiKxkv+e244aym5HlSSpzNms4tlyVV3TiT+QeO5veWFQCYTDEHu2dCDMBcPzEPznzXAc+t2016gegfD3NTvwv6XlG+R0P7QurzrYNXc6jt90Mzpvnomev0+Bb5WyXfT07dN0w+DRaXPQM39K2UB4bMnKokC4+7oVOHrb/JJhMLh2LI4sWJ6bQXjb/Tg0fx26N/wdP121TjcMNnMgrKTeGkkkiteItoNwLKb8t9vvD1p+frFZdToDwu9V7CqxBgZCGyB6sdpd0RVCbQdNq0NWORMJCZKULHq8v106a1Xp7ll5e6V6s1Ov11CSKldOy79m1QdUOwfCaLR0ICyn3tksZatd8XbU3Gy5/K12ha9r7NXrisKgtG04Ys8OQ/SZ4RUDoar08vkIvH4HHMcO9/s1MnuA+MmfD+K7v92Hfcu2lXxO9/4D6L5zWl4Y7Jo7Hcem34KTt85Az98nw7/6SniWX1MyDB6dNgeueyaWDIPe9VOx79oFRR1Gfx59LzrnzSndUGb91dh77V2584MLN+HQ3Q+ge/18/HfSQ6UD4d8eE/77brX6W7bjSKVSRfcZ+ecXCxveiP9eRMtAWD+JNTAQ2gDRi9Xuig6EasOUXFXQupBVznhcQjKZHwjN6NJZq5W6eyqhK1XXOYFeb+XKaaFmvGYMhLXcwOVmyxVutdOS3Wr3zUbdMChtG47YM8MRfdp4IFT1PTQePacd/fo+zA6Eu2/ciG8uLB8Iu9YvR8+dU9F1ey4Mnr5tOo5OuxWn5iiB0LfqKhydob9VVLVv2YSSgdCxZVnx+cHMyImuBTeVDIS+R2/Jbyiz5CEcvOdBnL5/Hn6e/njJQPjZRY8K/31vFP1+5W+OEhh98HrV84tG3lQxZ+RMs8lAWD+JNTAQ2gDRi9Xuig6EakUrlbI+ZFW6rmQyBa83CL8/bFqXzlot18wlP3SZN7xez0TCWCBUR3CY8ZrZNRDG44m6BcJKulze7Fa78JHvis4N5gXCp4cj+vSIqsJg9Mm/wb96DE4980y/rlMJhEFTvudDW9/HdyNW4j/DV2Dfsmd1n9P98y/ozm4VnZ71VKaLqLJldBJOzy29VVQZOXFr2ZETJ5avKg6E1y3CzouXo3fRDSUDoevxxfkjJ5Y8iD/uXYvjSxbh51nPlA6EIxgIVQMBZdxSpedp31TRNrzRO7+o1/BG7/xiM+pw9Am/T7GzxBoYCG2A6MVqd0UFwmAwkt1GWO+qVi3GYgmkUjIikXj2D74ZXTprVa+Zi99vXugyaqmttFrNHsFhh5sqPZVAGBd7HadOIfH8yJJhUNqmVAejW40HwsQLf0Vw/RXwrx2NnvnT0HOyp+brA2BKIDx9qBO/jluCL85bix8v6cD+Dv0KYdeqe4q2inbNnY6Tt9ykdA6dORtdt99YNgwenTYHx26aXXq76JrJ2Hf9XcWB8Mal2HnxCjgXTywZCLs2r8wPhHdvxLGOe7Bv9jL8fMvzpQPh8C3Cf98bxWAwDFmW+/15ikfOxMqMnNFvCtXII3VUGQjrK7EGBkIbIHqx2t2+PjFhSz3k7/eHTB92bs41xrNh1cwh87Wq3FDkKnPhcK5bp9lzD8sZj5cPhLU2jimnnQNhLCY2EEZfn142DFYbCJOvDkVw0yiENoyBf/0oOBdOhuOZpzPnssKodhA5YE4g/O3Wh/HDxcvxefs6/Peypdjf8VzRc7q//UY3DHbNnY4Ts2dmZwsenzmrYiDsvGVGyUDo3LK4KAwqMwhXYOfFy9G3dELJQHhsyYr8LaN3rsbJjrn475XL8d9bXigZCD8dxkCoGgpFkEql6v511Cq8cn4xglgsDklKlmkKldA5vyg+MDIQ1ldiDQyENkD0YrW7VgZCbXMRbUVQ2Q7ZOIFQnd2XTqctDVvlVM/uaeceVtvcxQzVGWHlfrZmd4dlIKyP/m8erRgGpW1KGIw+ZSwQhreMRGjDGIQ2jEFg4+VwLpyMnvlTEfMrjZG0KI08lNEbReeyTnWht9ecQHjkre/w65i78Vn7enx07ib8fPm92L+8uELYvezv2RETWo9MvxWHps3PhL3y5wazIyfumFoyEHauvk83EP42eQV+vHQpPMuv0W8os3Yc9t9wd/4Mwun3oHP5HOwa2YFdN79YOhBe+Ijw3/dGMRyOIJmsfyAsZ7kZpfrrRG14E0EgoK4Ta+YoOhwe0+43Dh/uxOzZt2DQoEFob29HR8cq9PR4y37MG2+8g4suujjvsdOn3ejoWIULLxyGgQMH4uqrx+OTT77K/vvXX+/En/70JwwYMCDrxImThN9v6UmsgYHQBoherHbXqkCoVtz0zrn1Z5SBmSqz+5IAkN2KKfqaVBOJZPbdZSvmHpb+ORYHQnVbbb2a7dg1EMZi4gKh69CusucGtUaeGoHoUxdVDIPxbcMQXD86GwhDD1wK58Lr4Vw4Gacefih7I2xkEHmy67dsA5xEQiqYK2e8atJ9she/Xr0MP166DJ8NWY9PB2/Az5cvxf7l+RXC7g8/LKoOnpozA79NXoov2tfj8LQ7DQVB1d67b9DfLrp6IvZPWaQbCHdfvRS/TlgK38qr9BvKPHJTXhjcN2kxDlw/DyeWzsWukR3YeVOZQPjXh4X/vjeK4XAUkpQUfh3ldDqNrROgdBdhsxremBkIJ02agjvvnI9Tp1zYs+cARo26Alu2PKH73J4eLx555HGcccYZGDHiorx/6+hYhauuugZ79/6B3l4fnnvuJZxzzjn4/fc/4HIFsXXrNkyaNEX4/ZURiTUwENoA0YvV7tY7EOZ3v9SvAtYyysBslXNv6uy+CMLhKAAIvSat6s2x6JEcytlKJRCa2TimnHbt5BeLxRGLJaz/2t09iL8wylAYlLYNR9RAIJRePg/BjVfkwmAmELrungjnwsnonX8jeo6eqHht6rms0K6XEQpFAADJZEp3rpyRbXa/L96GPePuxpfnrcXnQ9fh2wvvUwLhylwg7OlxofueufkjJm66GXtvXosv2jfgi/YN+GPqbVUFQtfSSbqB0LXlbv3touMX4OdRS7B36hL4V4/TDYTuJ+7KC4QHbr0PB2cuQeeKO7FrZAe+v2F76UB4AQOhaiSinPUTfR39sVwXYb2GN/nnF6treGNWINy9ez/a2tpw4MCx7GM7dryF4cNH6D5/0qQpmDbtJqxbt6koEN599xK8++7HeY8NHjwEb775LlyuIP7+94VYtWqN8PsrIxJrYCC0AaIXq911u+sXHox2v1Q6V5ZvVFIvfb7Cc29K2AqFlEAoeh6iNlCrQUyk0WgcqZRseuOYcjIQmmv4X3MNh0GlQngRYhW2jIYeujQ/DG4Yg9ADl6Fv6QQ4F05WqoSb1hu+Rv9H69Db7ciswWDmxrT0NrvCqoksy/D8+gd2j70b/7383kww2oSdFy/PBMLns1+r683XsiMmTt06A/sn3ondY+/G7rlblUB43jocmWo8DB6ZOgeejvG6gfDUWv3tosrIiWU4NOsuBNbonx/seTj//ODBBRtx6I7V6Fw1H7tGduDbCdtKBsJPzn9I+O97oxiNxhGPC3gjxkKLG97EyzS8SWYCYzTb8OaPP47h0KGj6OlxweEov6XTqG+//R6GDGnPe+zHH3ejra0Nx451Fz1/374jcLmCePHFV4sCYaEff/wl/vznP+O33w7C5Qri8stHYfLkG3DJJSNx3nnn47bb7sh+vkaTWAMDoQ0QvVjtbj0CYSBQ3ZiGSo1K6mUwGMluwSw89xYMKtUJkaMwIpFYNlAnEpLu2T2rVUM+YG7jmHK6XB709LiE32SZbSxm/Y2p+8e3kNg2zHAYjG8djvCjIxAr01QmuvWi4jC4YQxCmy+DZ8XV2UDYO/8GdB/8w9B1Bv69FM4j/wOQC4SVzG2zCyIQCGHP9fdhz7i78fVf78enQzbg/b88jJ8uW4qfL1+KI+teRjyeQCgYRtddt6Fr7jQcmXYr9ly5CLvH3oPdVy7BN5c+iC/aN2DnlRuqqg4eXXCv/nbRVRNwYEaJhjKZkRPHbrujZEOZEyvyO4weWvwgDt21EZ2rF2DXyA58Nfqp0oHwPAbC3LoT38xJpA6HW+eNlVzDm3Q6jUGDBqGtrQ3nnnsuxowZi1mzbkZHxyo88cQzePvt97Bz5684edJZ1b3Gyy+/hmHDhuc9tmfPAbS1tZUNa5UC4Vdf/YAhQ9qxefPDcLmC6O31YcqUqXj44cdw/HgP/vjjFObOvQOjR49Fb69P+D1XocQaGAhtgOjFanfNDoTaqqDRMQ2lGpXUU3X+YaktmIFAGADqPtdPT3UrJoBsh1PtVk1RBgLh7A1DOGzdmBCXy2vLQCiiUuH94ilIBgJhfOsIxJ4ageCmyxHcNAqxrfpbRhMvXoDghit0A2Hw/7P33s9R3Vm07z8x9erVrXrv3Ve3rjyeh42xDTYmKqdGQrGVswTKOQdQDiiQs3EYe5jx2ONxxDZgbGxERoCEEkgoq7vVObcC6/1w1Ed91Ol0q9UHpN5V6wcftcRXEqd9Pqy91z7kDn6FHwmE3NwwjNVV0zqn9Kt88B98B4A+EOrqSdM/0cUqwD2vIlza1IwrW+rw3YZ23PUowV2PUgzWfgKVSg3+P/+O0X0J6A7MIkBwUU8yjpDtol0R1RYB4dPsUoNAONOebRAGewJz0B1egk7nSoxmJhkFwt6EYurKiZI29BW2YeRgLm65luOXHYeNA+HmVsb/vr8sYnL/56sgDoePrq7H+PLL/+D48RMoKSlDTEwc3N09sGHDG3BycoKTkxO2bt1q0cL6f//7G2zebNghHB6eMvp5poDwww8/xcaNG3H06EmTf/bAwCicnJxw69YDxp+5lstR9ikHEK6BYvpmXQ+yxUP7Spa3q1REG6K9oMZQ0qmh1wGw++5BY62Y2lZNe55FV1q3UguE9vyz1y4QquwPhD+2LgKhYShUn94J9amd0JzZAWmTJyS1LEhqfaE8tRNzn+uvmJAd8jTsDjb6QHrIDfzSvRQgnM4Ox+TjJ2bPKftXBkTXzwAARCKJRd/jWNcgHvgWootVgN93HCSA6O0mXNrUjLsehEPYe/ACJsYm8aywCg9YBRQYfOBbiK7UsyQQ9saV0QfCuDQMxKUZBMLxJsPtoj2BOXgcXoZO50pM5kYbhEHxoTAKDBI7CJvRW9CB51U5uOlWiUtvG4ZBBxBSpdHMQqFwACFdcblLrhqHI0Zv7zCuXv0D1651WvSccf9+D5ycnNDf/5y8dvHil3qu4XIZAsLpaREKCoqxZcsW/PDDZcrHursHUVl5ECMjHPJaT89TODk5oaurl/HnreVylH3KAYRroJi+WdeDVrqcfqXL25VKNRYWVh926M40CoXE0ncAdt/xBxhuxbTXz2i5lruV2pUc9jwDjydas0Bo73AL8X9rMXueCoSas4QjqD61E7Pnt0N9eickjVoYJKQ44oy5z6hAqDjqYhQGtXsIBcuAkJsbhrGDFcR5xsbB6XsI3v0r4P/xBQS/nIXwuxbwfr0I+cUUSH6qA2A5EHbFNKGLVYD7PoX46e0m/PxOI77b0IprW2tIIHxSdhZPqs/igV+JHgw+CCjFrztbSCDsi86lDYQj5c14nhKn3y5aFYD+pBKjQPgwmABCTn6YQSAUHMvSA8L+zBr05LRjuDwbd/Y2GIXBS5tacOmdQ4z/fX9ZNDs7B7lcyfg5XhXpAuFKFRwcitTUDIyMTOPhwz54enqhsfGQyc8xBIRlZZXYvn0HHj8e0Hv9+DgPW7duRVlZFcbHZzA4OIaEhCSEh0dheHgKH330GQUWmZaj7FMOIFwDxfTNuh5kLRCKxTLSFVzJ8nat+7RaQGGNeykSEUBoj/UOUqnC7A6/1f4ZGZJu8qoWjJlIX52ZcQChrST+sowAwvPboTm7nQDB0zvJa+qTOyFp8KLAoKSWBVmLB+Y+e29pxcT5bdQVEwYkqfeA/JAH5C0eULS5Q9HuBuVhV6iOuEB1zBnq41QpjzpD1uQJ0elUyD9PgOy/eYt/1+gD4cCFn9DFKkAXqwB/7qrEpU0tuLylHt9taMeN3ZUkED6MOIDujDZ9GPQtxKP0oyQMXtnciIHINNpA2JN9BJPZ4XpAKD6SZbxdNCAH932L0OlcCV5RsEEg5Bwu1wPCvvhi9GbVYDCrAHfDOxxASFNzc/OQyRSMn+NVkS2BsL//OVJSUrF582Zs2fIeqqpqoJ3r27hxIz777F96n7McCAcHx/DXv/4Vf/vb3yh7BnU/v7PzPiIiovD22+/g7bffQUZGNp49G8dvv3XizTffxPj4DOPPXVo5yj7lAMI1UEzfrOtB1gChFlDm5xdW3Fa5mpCxdE7L3Utg9YFQ61rOzs6ZDLCxtzOnVhMzlrrJq0LhUvqqvc4hFK5dIGQi/l5yMQ+ac1oQ3EGC4Oz57VCd2AVJvT4MSmpZkNT5YvZTAgjnDK2Y0JOXQegzJuVRZ0gbvSFt9IH4aBwUf4+G/F+Ji3/X6AHhxNMx3N9Tgi5WAR74FuDndxuJlQvvLAbKuJWSQNiT1YYHie0GgfB23EkSBq9ubcJgJM2VE8nZ+MO5FrziYD0gnGw13i7aHZCDux7F6HQuB7800CAQjtUdpAJhSAF6QzMxkJWLrsgy3I8zHiijFdN/318Wzc8vQCqVM36OV0VcrpjxZxRb6d69biQn78NPP/2K8XEeOBzmvzdH2accQLgGiumbdT3IkodzsVg/8GSlWlrxYDuIsMU5VzM8Rde1NLafUVf2cuZ011wY+t5X43dl7veoTVil7tKSgM8XUXbOvWqyOxBOTEJ+NgCaM1QQnD2/HarjuyGp9zYMg4tSndmB+X9sgbzdwIoJ3dnBRm+ojloAg4ddIGvwhrTBG/JmL0gOR0LxSTgUf2cv/p2nB4QP04+S7mCnSzk5O/jdhlYiUMZTBwgLT+Aeu15/djC0Ele3NpFAeCOwg/bKicGSFlzfcQDCSv35wYH0MpNAeNO1DHe8iiGs2GsQCJ9lLls5kVKN3pBMPM3ah1se5XiQbHzlhAMIqVpYIP4Rk+lzvCpaC0CoBb8//riDrVu3YsOGDcjPL0ZLSzvOnLmAzz77Al988TVu3Lhn97M5yj7lAMI1UEy/kawH0XUIdV1BW87W2XrFg1yutMk5zQXPWCtrXEt7OHO6ay6MzVhqf1f22M+oDdiZn58nd2nNzs7qLSlfWFhYXFKuhlyugFgsg0Agxsu+v1ChUGJ21g5AODYGybdVUJ/brQeCmnPboTy2G5I60zAoqWVB3u4G1emdpmGwwQvKIy60YVDR5gZpgw+hRi8CCDvCoPwoBKqP/Bb/zpsHwqFvO/HAt4AEwstb6intoj9sbCFh8K5HKR5knsZ9/1I9IHyYcZzSLvogroV2u+iDxDbc9SrSg0H+oRSjMEisnMhDp3MFHoUUQXTATw8GJU2B6A7MoQDh0/wW9EXmYTg3Dbdcy3F//0dmgXBqcu257NboxYsXEItljJ/jVZF7YJamAAAgAElEQVQlSaIvq7Tfw+XLvyMoKBjR0XHw9PTCzp27sHnzZmzatAmvvfYa0tOz7H42R9mnHEC4BorpN5L1IHNAqOu2qdW2cQV1ZatET5GIcJOIc86u+FwLCwsWJ6aaO5+1ruVqgpgl57LXfkbdllU+X6zXMqq7pFwqlUOhUJLrS3SXlGvBe7m7ODPDvLtIAOHc6v0ZI8OQfF0MzdldeiConSFUHXWGpM7HLAwSbaM+kJiYG5Q2eEN52JU2DMoPeejBoLzZC5K2ECgvBEJ13hPzcjHMAeHkOAf395aTMHjLvZSEoJ/fbcB3G9pxeWszBQg7gzsMtoveDKcC4ePYA/SAML0I13ccRHdIph4QTrVVmgZCdjE6nSvxJLoA4mqWHhAKj6bqB8oUtaIvpQJDhVkEEKZ+ahYI5zSzZMImcR9IweeLwOW+ui67NSLeRy1fZbJetRaA0JwmJwUYHBzD0NCk3f9sR9mnHEC4BorpN4r1IFNAqJ1dW74GwZYSi7VAaP3X1w1AsdXc3/z8AlQq2wChoYAWS7RaICaTKSw6l0SiPcfqrOMw1LLK51s+Q8jjCSAQiCEWS19ad1EuXyUgHBqA7MtcaM7uNAiCBAzugPKIMyS1NGFwUdJ64zCo6KAHg0R4jBflc7UwKG/2grQ1EMrzflCe84H8XDbMAWF3xQUSBrtYBfh1a+0iBDXj+zeIdtHrHjpA6FuJPz3120UfRtXgypYGChD2hOXTAsL+4jZc316Np3FJekD4NLfCJBA+CiV2EA4kZENSq98uyj1Wor9yoqQN/dn1GCrNwy3Xctzb93ezQCgRETPLGo3+faCdYyaShJWQSGQQCiWYmRGCw2EeSmwlDocPwLKgovWutQKE2u9jdJSL77//BcePn8HRoyfx9dc/oK9vmLFzOco+5QDCNVBMv4msBxkCQl3XaDVcweV/FmD9igfqugbbAdPc3LxN5iSNBbRYCkqAbUFMpdKea472uVZzP6OxllWBQGzzh8KXwV20NRBynvZA9q80aM7pzwjqSn1mB5RHXCyGQW24jEEYbHOjD4ON3pTPlem4g/JmL0gP7YXqHAvKsyzIm7wh+vG80e955EY3uXOwi1WAu57FuLSpmWgXfY9wB7/b0I67Ue1L7aJJR3HL++AyICxAV/oJCgxe2dyIPnYGLSC8E9qC69urMZYWTYFBQXO8SRjsCczBwwAiYXR4/z6D84PjTVX6QFjYgv6CQxiqKMAt13LcSTQPhJNjHKP3gUQig1yuhEqlwdzcHOU+AID5+QVoNLNQKtWQyRQQi6WvRFu2PtwIAMDm7ylrVRwOf80AIY9HrKSorW3E5s2b8f77W7F9+w68/vrr2L3bGZcuXWXkTI6yTzmAcA0U028g60F8PvXBXC43vBx9NQVYnuhJZ13DSkQEmVjfekq4XQs2CaexJYiJxUsunKUzkkturu2AUCSSkq2+hgDc3g9v1riLxEOyZe6irYCQ2/8AsotJZkFw9jyRLqo8bCUMLi6plzbowqAP5K3uFoXH6H6udBkMypu9IG3xg+qsNxQnfSFvIl7P6Xmg931PTfHwgF1DcQd/21a9BEFb2kggfBCl4xBmfIR7vtT5wf7wJPRHZ+LK5iWH8Or2ZvSH01g5kVeF69urcX17NTj5bAoQTneYdge7A3Jw36cQnc6VGM+MNxwok1+h3zKaXYe+wg4MVRbilms5bkZ/bB4IR6ct+3vF5YPPF0Ekki7+wwkRgqR979CW9h9xXoXQJx6PAEI+X8T4WV4FcTh8xp9PbCHtaotTp87Dw8MLx46dwvDwFMbGeLhz5xHCw6PAZofj4cM+u5/NUfYpBxCugWL6jWQ9SAuEy2fw7JUkKRRanuipdbfMrWtYiWZn56DRWAeE2nUShNu18vOJxStzUbXSDbSxxm201Tm0kkq1LasvjP6DgEDw8rR3WeIuGnpI1nUX5XIF5uasB0JuTyfkn8dAc840BOruGFR2rAQG9dtG5Yc8LAqPWe4sLodBebMXZC0sqM54Qn7YE/Imb8ibvCE5FIbpSarD1dfxFQUG73kXku7gpU0tZLro9+8cxl2vMhII/4j6kNoq6p+L0ZRojCXHYyBiP65srseVzY3oDD1Ca+XEk/wOEgj5ZYEUIBwqrjILhHc9iJbRqZxI/UCZej90h+bp7yBMLENv/mEMVRThlms5/gz50DwQjlgGhOa09A8nMshkCqhUaszOzplpy9a2o4rB4wntfv/OzAgBADMzDiCko7UChFNTQvB4UoSHR6GhoYW8rk0f7e0dgo8PC//5z3d2P5uj7FMOIFwDxfQbyXoQn7+U6GjLGTxLRNet0p0xW40EUF1pNLOYnZ2zGJi0cGDrQBrAehBbSaCNLc+hK90djKZaVl8mIDQnS9zF+XktCFvmLvIeXoPi03DaIDh7fjvUJ3ZBYQMYpLSNtnhaFB5DhUEfvVZREgibfaA67QlFqxsJhPImbwg+PUD+DMZ6hnGfVUQBwus7D5Dw8+NbLaQ7+FvAaRIG7wfX4ncf6v7B0eQ4jCTEYDQpHmPJ8XgatQ9Xt9ThTnSb+ZUTcWno9GnA9e3VuOFcToFBYUMUeoJMt4t2B+Sg07Ucnc6V4Baw9YBQdDhRDwa7g/PQy85Cd2Y7npUSLaO/+ZwyC4QTz6fsChJL7ai6/3Biqh1VRbajEmE3tm9H5fNFAICZGfvD6KsoDkfA+POJLaR1CIOCgnHs2CmDr9m1yxlff/2D3c/mKPuUAwjXQDH9RrIeJJOpANh+Bs8S0Un0pLpuqxNqoiu12jIg1AbwzM8v2HzGTiSyrq1WKNR14VbeAqwFQpnM+q+jhVO60PwqAaHphyuqu0iA4gva7qKw62coPwmxCAQ154iF84p215WDoG7baJP5xfPLw2PowCABhN5QnfKCotWdAoSyRm9wO3/C9PQMuhIOUWDwgW8Bfn6naQmA3mklgfB24rklINx/Gjc8qkkY7GOnYSojCs9i4kkgHEuOx1BMMh6ElJl1B58W15PuYJdfHgUIOYeN7x4kgTAoD53Oleh0rsRMUZAeEPKOFeoB4ZOEKvSGZOJhYjOeFhChMpd3HDEPhMP2A0Jz4nIFZDsq8Q8nS+2oukW9F5SQSuVYCruxvB1VIBAvPle8WrOPzL1nrQ0g1M5BNjW1IigoBFeuXMfUlBBTU0JwOGJ89tm/4OLiis7O+3Y/m6PsUw4gXAPF9BvJepDWIVxtwDKl+XnjAS6r5bqZk7YVkA7gaDSrH8ADwOJZSd3WWlvBPmAdmAqFVCeaLpwSQPhy71CbnORa/DkymQLz8/PkfxtzF2d7f4bmk0CLQJACg21uNoRBFqT13uZh8IizyURSYzBIAKEXlCc8IG/xpAChvMkb0iZ/DH76PQUGu1gFuOFSteQObmrBj5sPk0B4f/8pEghvJH+KO57a+cF8TKRFYzItCk+jEilAOJYcj+fxiXgalWISCB9nLLWL9kWkUoDwecUB80AYQswP3nQrhaAsQA8IJ1sr9dtFMxvQG5KJR1Hl6N1fiJvulbj0tmkYvLSpBRNDk4zfJ3TF4wkhEIh1wm7otKPqOu2GHUChUAIA627VhrVaK0Co1dDQJEJC2PD09EJRURmam9uQl1eIN954A3V1TRgfn7H7mRxln3IA4Roopt9A1oNmZuwDWKak/Vfg5deXZt5s77rRgan5+QWTr9F131bimtEFMbpzlmKxnIRoW7fWEuewHAiXUk0tm0992YFwYuA5ejKaMdo7Quv1U113MPXxcT0gXC7BH59BdYFlEQRSdgwe3wV5q7tNYVBS7w3VUTPzgh0uJmDQtDuoleKoO+RNXnpAKG/yBq8kmAKD930K8POWQyT4/LK9nYTB7za040FsGwGEnqX40fMC7vsQ7uDzhARMZURhfH8MnkXrA+FYcjxGEhKMQ2FyNv5wriWBcDg5fqldtDYMPaF5ZoHwUTCRMHqfVQhhxV49IBwu1QfC/sJW9IZm4klUGu4FluG2f71ZGLy0qQUTz14dIDQNKXzMzIggEtFLCda2o0qlcsjlysXnCodDSO9nLWT8+cSWGhqaxJ9/3kF+fhG8vLyxY8dOeHp64fjx0+Q8ob3lKPuUAwjXQDH9BrIe9DIA4fIAF1vNvK1ESqUaCwvGgXA13DdTogt3usExqwHRAH0wFQpXDqc2bxkdembTrzdy6ToGwlNxL7gag9/eNf7aR3fAb08HtzQM3KJICAd69YFwigfhtXNQnfeyCgRnz2+H5swOqE/sgvyQh21hsM4HqiMupucFW9315gUthUF5sxfkHYZhUNs6+jw5jmwV/W1ngw74NOG30AtLQPhmO+75VhLrJmIO4dL2w3jgW4ieoExMpkdhKiMKI4nxRoFwLDkeI4kJeBqtD4WDJS0kDF7fXo3JnEgSCLmHi8y7gwE56PIrQKdzJbrZBRAd8NMDwidRRQZ3EPbFFaMvcT+xcoLdRgsIxwcnGAcMe4jLXe60a9tR9Xcvzs3NQa3W7l5cWTvqWtRaA8J9+9LQ2zvE+Dl05Sj7lAMI10AxfbOuB70MQKgb4MLE2gtTYLX8uqHl6fbQwsICFArjLbO6raurCdGWgN3SXKX1cGprIORd+hDTE7ZLXBw+9y8MRKSiLzwDd7xK0FX3NfWh6uEtCNpTIKzyB68wGLwCNngFbMz893PMzy8Qr5vkQnjlGNTnPawGwdnz26E+vRPqE7sga7EtDIprfaE8bHrxvKzZ0ygM0mkV1UpSx4KoNgiCir1GoVBa74PHgZm4sauSkix6+b1a/Ox6mgTCqz4nyXbRe+kf4neXBjzwzcf4/hhMZRBA+Cw6Gc9ijAPhWHI8RhPj8SwqmQKEDxLbKEDIKwklgXCk+iAtILzvTbSM9sXmQFzDosCguD1aP1AmIBcDRS3oT6/GQHoWbrmW427McQcQ0pREIlt8T5cYaEelht0Q7ai6uxctWyuzFrSWgJDLleDtt9/BjRv3GD+Lrhxln3IA4Roopm/W9SJDy+ntKbV6FnNz84ytvTAFM7rXbL1OwhKZCt6xZ+sqXSBc+l2uHE5t+ZAj+HcDeNe/ttnXe1p/HAPhqXgatR897Hzc8y7GrehjmLr5G4Qd+yA64AdRlT94hSHg5oeSQMg71YC5WTXEl1qgPue6IhDU7hhUn9gJWbNpGJQ2uEPa4EkfBmt8oewwDoPLl82vxB2U1PpCfMCfFL8kCOJqlkEoFFb54+p7NRTouRHYRGkXvRm3FChzPeEz3HSvwNPoFBIGJ9OjMBixH89iE0wC4VgyETrzLHoRCtOLcH3HQR0gPABh5WK7aHUInoTn0wLCO4srJ54mpOu5g/zj+jDYHZCL/px69Oc1YSA3nwDChDP0gLB/nHHAYFpSqRwLCwtGP760e1FC7l401Y5KDX7SpqOuHXeRyxUx/mxiK01M8JGYmILCwhJcvfoH7t/vQW/vEJ49G8fYGI9cTWFvOco+5QDCNVBMv4msFzENhBrNLF68eGFyH529pZ03EQq1wTb0kzFXQ/PzCwadP3u3rppLhCUc1AW8eGG73yWHY7uHHMG/6iD6tMhmX+9pQS0JhIOR+9EXnQFecTABgsZgsCAEkrYAaM65rBgEiR2Du6A+sRPSJi+zgKdodYfqmDMk9d60YFDR7mY6PMaEK7gSGNRKVOUP8QE/SGp99KBwIiscP7/TSELP/cRmChDe23+GcAdZlfjW9WN0+eWSraLa+cHBiDQMxcWbBcIlKExBfzHVHbztWUy6g7zDBWZhkFw54UKsnBjZn6QHhFMd+gvpuwNy0ZdSjr7CNgwWFRNAmGx+B6EDCAmZm9s1J0PBTxqNobUyLxbDbjQ6uxe17ajM/xzoai0B4fDwFPz9A/Daa69h69YPEBAQhPDwKMTFJSA+PhGFhSWMnMtR9ikHEK6BYvpNZL2ISSBUqwmgefHiBWNrLwxJJiOAUC5X6gTbMNfCOjdHTWJdzeAYUzIFhArF6jiotnyIEn5eCemxcJt9vcH9RegPS8Pz5DjwywIoICiq2gtekQ4MFoZA2uwJ9Zkd1s0HntsOzfkPoDy+g5Ikqj6xC9JG8zAoqfOBssMNqsNuUB3fDUmdcSgU1/hC3upuVXiMpa2ixmBwORiKqvwhrfehzBM+i0vE9R1EyuiDyEpqoEziYWJ+MPkovv7/OjCaHEfC4FRGFEaT4iwCQi0U9kQWUIDwcXAWCYRjdebbRZevnJjIjNEDwpEDB/SBMDAXvWHZ6C3swNPiMmKGMOVjWkA41jvGOGAwLblcgbm5uVX52tTdi9p2VHO7F9Xk7sWXsR11LQHhs2cTaGw8hLNnL6CpqRUVFQeQn1+MjIxsxMTEIScnn5FzOco+5QDCNVBMv4msFzEBhFKpgnSS1GpiJxtTsGXsfNpSq2cZPw+RxEqcwxazedbKkFNp6W5BS2VLIBR9XARFmzemp2yTXDqSmkAFQUMwWBgMWYsnNFaC4Oz57dCc34bZj7ZCc3Y7ZG2u0JzbDvVxC2CwlgVZsycBg1qd2A1Dy+rFNSzID3lYFR6j5w42rRwG9cDwgB+k9QQUSmp90R+Wigd7itC1N5vqEPofxF2PUtxJ/xj3fPMpMDiVEYWh2GQMRqRhOJ4+EGqhsDswiwTCZ/vSiHbRqgD0xpoPlOkJzMHj4AISCKdzw/WAsD+5VH8HYWwFekMy0ZPTgacl5bjlWo7bSZ/QA8Ino4wDBtNSKJSYnV0dIDQPV3xy96K2HVW7e5HOHlI+X2T3sBsul5nkzdVQV1cvjhw5yfg5lstR9ikHEK6BYvpmXS+yN9yoVBq8eEG01YjFMoPzekxKO5MHWJaouZrSJrHacjbPGi3fGWnLxffGZFMgPJ8LZZs7uA9vrOxh6cbPELbEQnTAD+KDVBAUVe3FTHEwuEVBkLW6Q3N2BSB4bhtmL2zF7CfvY/bj9yFvc4O8zW3RGdwNKY3WT0I+ULa7UYHQCBTKmj2tDo+xpFXUUhjUbyXdA2mDN2ZKA9HPTsXzpDhcfb8G321ox2W3E0vzgzEfYyItmgKD2vnBwYg0DCdGWwSEWvWGZOD69mqM5SQQv/PWTFow2BOYg0cBS0DILQihBsq0hBpsF+3NqEdvSCYep7ZisIhwCG/G0XQIexxAqE0cZfochrTUjiqDTKaguXtR245qfPfiit7jbASEAwMjSExMxttvv43NmzejvPyA2Zm9L774Grt2Oetd7+g4hm3btuPNN99EaGgY7t17TH5sdJSLnJx8vPvuZmzatAmZmTkYHp4CjyfFV199iw8+2IaJCT7jz1u6cpR9ygGEa6CYvlnXi+zlEOomdOq2OWrbM5mGLqFwaSZvbm4eAOzuwBnT7Oz8SzFnqbsz0l7zi7b8l3HR6TQo29wh/PqQdQ9Jf/wAYUsMxAf9SC2HQX5pAORt7tCctX4uUHNuG2Y//ACzn7yPuU8JKTpcIT/kvtjKuZvWHOBSmIyXPgxSoNCXgMEmL6vDY6gy3Sq6EhjUA8ODezCRHo7RlBj0habjjmcxbkSexl2PUtwPqUN/bKaeOziRGoXnifGYygoHJ5eN0eQYi4FwLDke/WFpmC6IgKhqL8abaLaLBuSgi5W/CITlmCkOogCh4FiG4UCZgkPoDclEV0wjBvJLccu1HDciP6IFhKPd9PZkrmWpVGqo1RrGz2GpqO2oursXTbWjqsh2VCLsxvJ2VFsBIZsdjoyMbIyN8dDV1QtPTy8cPnzc4GunpoTo6DiG119/HTt37qJ87JNP/oFt27bj1q0ujI/PoLKyGp6eXuByJeDxpMjJyUd4eBSePRvHwMAIQkPDUFxcBh5PiuvXbyMuLgHnz3+Crq5e9Pc/x9DQJMbGeJicFJBfw95ylH3KAYRroJgGpfUiewChbkLncsiSyYj2TCZnCJfDqlgsAwBGV19opXVUFxYWGJ+zJHZ3zdp1ftGmQHgiGco2d0hOJ1j2cPT7txA2R5sEQfFBP8jb3KA5tzIQ1Hy4DbMfL4Hg3KfvQ312O2RNBEjJDnmYnP8zGiZjDAgXZwqlDd5QHbMuPIbiDtb7mIFBH5vAIAmFlf7gFgZiNCUG/ex09LPT0ROUjbuexehNb6IEyUxlRGA6OwycXDa4eUsa3x9tFRCOJcdjNDke/PK96E8qoQ2E2pUTdzyLICgLoAAh50iZ4ZUTJW3oDcnEXf8D6M8swi3XclwPOkcPCB8/ZxxsmJZKpYFKpWb8HLYWlysg21GpuxfnKc9T1HZUJaRS07sXbQFJDx48gZOTE2X/38WLX2LHjp0GX89mhyM6Og719c16QBgUFILW1sPkf09NCfHWW5vw00+/YmyMh7/97W+4evUP8uPXrnXijTfewNgYD99++xM2bHgDr732Gvbs8UdCQhLS07NQWFiCvLxC/Pvf/2Xk2ctR9ikHEK6BYhqU1otWEwiJhM55k/Nl2nk9e69y0Eq7c5AIQyFgVSQigHC11zjQ/dnNzc1jbm6OsbNopT0PEbJjH/fUlkAoPhIHZZs75G0+9B62fv0awqZICggagkFpgxfUZ1aWFqo5/wFmP9pKAcG5T4lWUUm9NxQdLhAf8COAcNHRo7tUngyTMSH16Z1Wh8fQbRWV1NkWBgXle8ErDMZkeiRGk5eAsJ+djr7QVIynxpAgyMlh64GgVpMZEVYD4VhyPEaSEtATmEUbCLUrJx4G5ENY6U8BwrF6A4EyAbkYKD6E3ohc3PUpQHc8kTL6q9dJekD4yAGEWueM6XPYWzyeEAKB2MDuRWo76i+//IKAgACkpqaitrYOp09/iG+//Qn37nVb3Wr51Vff4t13N1Ou3bz5AE5OThgamtR7fU/PU/B4Unz88ed6QPj22+/gP//5nnKNxfLD8eOncePGPTg5OWFkZJr82MjINJycnHDjxl38+uufqKg4gObmNhQWliAxMRnh4VEICgrB++9vRVvbUUaevRxln3IA4RoopkFpvWi1gHAp/MR0QqdEIgdg//ZM3TAUQysdADDWnkn92cnJfVhMnEUrtZqYX5yfX7Drn2tTIOyIgrLNHco2d3AGnxh9HffqlxA2RpgFQa1kzZ5QdLhZlCCqbSnVBsYsB0HdVlFpvQ/krW4QH/An5vjqF6GwxjwYyls8zcIgIVcKFNINj6HbKmpLGBRV+kNQFgBeYTCmssIxkRpNcQj72el4nhBn0A00JE4uG6NJcSuCwuG4JFpQ2B2Qg05nYuXEk4hcIiRHBwgHs8oNA2FuA/pSKtDNTscdH2KG8PKOw7SAcOThMONgwrQ0mlkoFOsPCE2JaEcldi8+fPgYJSUliImJgaurK15//XU4OTnByckJr732GrZv34HQ0DD89lsn7WeLv//9n9i+fQflWldXL5ycnEj4MyRDQPj666/j0qWrlGvBwaFoaWnH5cvX4eTkBA5nqc21vf0YnJyccPnydfLa+DiP8hoej3AS//zzDiPPXo6yTzmAcA0U06C0XsTnrw5oAfTCT5hoz5TJlFhYeGEyDAWwf6iMSGR4qbtKpcH8PDNAqLtbcG5uDrOz9nUqbQmEkrYwEgj5P57W+zj3l39C2BCuB4KmYJBfEgRpkydUx1ygPOwK1Yld9IDwzDbMXqDOCS6X+ux2ouWzjYAz8QF/SOp8IGv0JB05aZ2PCTCk5w4uh0K64THL3cHVhkECBPdCUBYAbl4IOLlsTKTGLAJhLPrZ6RiMSsFkegQtENTV2D7r5gh19Tw+ET1BpqGwO3Bp5cRAXCYkNSwSBiWNAegOMrKUfn8l+rPq8SQuiwiUca/EpbfNw+ClTS0Y6XIA4ezsHORyJePneBXE4fAxNSXE48cD+OmnX3Hhwt9RX9+MrKxcXL9+m/azxb///Q02bzbsEGoDXwzJEBBu2rQJX3/9A+Ua4RCewZ9/3ll0CDnkx0JDwxYdwnsYH58BjydFcXE5WlraweNJyWCboKAQNDe3MfLs5Sj7lAMI10AxDUrrRbYEQjqgpQ9B2vbM1XfjRKIlp0ujmYVIZPy19t7xt5TYqR8co1Sq7e7MCYXL22ll0GhmX2kgFLcEk0Ao/jCduD7FA++nzyGqD7MIBIkAmSBw80JJIFQdc4HyqAuUR4wvnSfmBE2DoG6rqKTWF6rju4nzHPAn5ggXgXD57N5y11DWaCJMxpiOuEJx2NViGDTWKmorGJzOY0NYHgB+cRC4eSHg5oViIjVqEQgjMZFueD6QribSolYMhGPJ8RhJSMCTIOOJo48DlxJGnyXto7iDwqP7DMJgd0AOesMXg2X2FeCWazlu+dXTgsFLm1ow8mCIcchgWnNz85DJFIyf41UQh2ObNM7793vg5OSE/v7n5LWLF7/Ucw2XyxAQBgUFo739KPnf2hnCH3+8Qs4QXru25F6yWH7461//ivFxHgl/UVExaGw8BB5PSs5I+vsH4MyZC4w8eznKPuUAwjVQTIPSepEtgFDX2TIHWoYEEEvgmQIuQzK1hN3W0obuGEvsVCrVWFiwHxDqury67bTaQBl7nUMotDEQNgWQQCjr8Afvh08gqmcbBEHzMBgIbh6xdF7a5EUCoVZEC+kyEDyvHxhjqlVUUsuCrMUTyg5XEowkNSyDQKgLZ1rXUNFmJkzGKBS6QN7uZgEMGm4VtQUMiir2QlAaCEEZ8fMmAC4UkxmRmEiNWhEE6moqK9wmQEhCYbA+FHYH5ODR3nwSCEdTEyhAyDtWbBAIe2LK0BuSib7CdvRlEQmjt0Nb6QPhfQcQzs8vQCqVM36OV0G2AkIej2jrTE3NwMjINB4+7IOnpxcJZcZkCAgvXPgU27ZtJx2/yspquLi4krCXmZkNNjscAwOjGBgYxZtvbkRgYDB4PKobePLkWfB4S0Do6uqGixe/YuTZy1H2KQcQroFiGpTWi1YKhJaCliGtthunUpkGLkOan199IKQTuiMULjl19gAwU7sF7T3LKJEooFZroFSqyRh1gUBsVYz69PQMJA1+JBAqWihfC5sAACAASURBVN0hPrjHYhBcDoMEEHrqAaHqmAsUh12hOrmTWCNhYk7QWKuopJYF1VEXyJq8liCpmgVZk3EgJNVkhTuoq6MukLe6W90qKqj0W3l7aGkAhOUBEJYFYDpnCd6ms9kmQ2KskS3mCClQmJiA3pAMEysnKjGRFUUBQm5HjeEdhOl16A3JRG9+B/pyKwggjDpGGwif333GOGQwrYWFBUgkMsbP8SqIwxHY7Pmiv/85UlJSsXnzZmzZ8h6qqmowPS0CjyfFxo0b8dln/9L7HENAyOVKcOTISeza5YyNG99CWFgE7t3rJj8+MjKN/PxivP/+VrzzzrvYuHEjPvnkIng8KRmK4+XljU8++Qd4PCk5S/jBB9vw449XGHn2cpR9ygGEa6CYBqX1opkZ6x/Y1Wrb7KJbWFiAQmF7+BKL5VavSJibmzcYNmMryeVK2omd2pCZ1QYwc06lPWcZFYqls6jVGnItiLa0M41qtYZwl4d6IZgRYGbGyJLmKR4k9b4kECrb3Il9eJbCYFkguPlsEgZ5BWwCvgwAoerELsx++AFtEKS2irIgbfCG5tQuSKr36ADhHlpAqDjksTIg1ELhIQ+LW0UFFStzBbUQKKoIgKAkENzcUAq42QoCV2OOkLKSIjEefaHpBldOdDpXgpMXRgHC4WLDCaNDJe3oDclEf95RDBbV4JZrOe4mnHEAoQV68eIFxGIHENKRLYGQKW3Z8h6lhZTHk8LFxRXfffcz5do777yLP/5whMqs5XIA4Roopt9Q1ousAULdoBFbBK+shhunddXm5/V3H9IRsbNp1uagQw2Ooff15XIlAKwafOk6labAXKVa3VlGgUACfl8Xmf6qVKr13EAeT7AUoz5wE8qvyqE45g9Jow8mK7KwsNjqOj8/D41mFnK5HOLvz0FUE0SsYNABQmmDN20Q1MIgZxkM8gpCDDiEu4n2UDNzgqZaRSW1LCja3aA66kwFpoN7IGsyDmkEqHlbGCZjGgplzfp/njEYXMnSeWF5AASLICgsDwC/KIgCg6utyfRImwLhWHI8RpPi0c9O01s50elcCV5hyFKgTD0LPWEFBoFwsJQAwscprSQQ3t9Hbyn9pU0teH77KeOQwbQAQCSSMn6OV0EcjpDx55KVatOmTWhqasV//vM9vv32J9y8+QDvvrsZn3zyD/T0PEVf3zCePZvAhg0b8PBhHyNndJR9ygGEa6CYfkNZL7IUCHWXzNtqd6At3Thj82+WanZ2DhqNbYFQKlVgft7y9lqZjABCS2cz6X7thQV6TuVqzTIKpjkQfd0KWbs/5KdjKO2qFCCc5ID/5xeQfpoGeYcPFK0epIRVLPBLA/EHqxkP2n+DWCyB9PuzENcGLwLfHkjrqUAob/akDYMCgzDIBjc/hAhvWQRB9dntVoHg3KfvQ6PTKiqp84X6xC7ID3noA6EBQNOVvJnuqgl6Uhx2gbTBy2yrqLUwKKzYi+ncMNIVFJYFgFcYYjcQJFtRc8IwmmRbINRC4UBYKmXlxC23EiKhdhEIRR3xRgJlcjFQ3IrekEzcZ9ehN/cAkTKa8CFtIJQ+41m0lHyticPhAwCEQgnjZ3kVtBaAcPduZ7i4uMHb2wfe3r7Ys8cfGzduhK8vC2x2OKKiYhAXl4DXXnvNZOLpaspR9ikHEK6BYvoNZT2JzkO7bvulrd08oi1w5fBlTcqpMdk6UVO3HdNSkJZKFQCworZcQ9K2/BoLAuLd+hOS/zRC+HyA/B5sCYSCoT5IPi2E7BALyvZF+DgWSPk+ueNjEFw+Den5WCjaPCkQqJWs2ROC0gAISoPwfF8MeqP2Q1i5d1kr6B5IlzmEilZ3iKr20IDBAHB0Zga1ms4Jx3QOG7ImT6hP78Tsx/TnBE21ikpqWZAf8iDaReuWQdZBP5MOobTBm/xZ2krSJk9I6rxNuoPWwiAnjw1+cRBEFYstoqW64TH211hKrM2BkITC8FTSHbzvWwB+WQAJhDPHDbuD3QG5GMhrRG9oJm57luNJJjFD2BlP3yGc6hqBTKYwupR8YWEBs7OzerO6PJ51s7ovm7hcAQBAIBAzfpZXQWsBCJ8+HUN39yDu3XuMP/64g59/voZvvrmETz+9iBMnzqKx8RDKyqqQkZFNBszYW46yTzmAcA0U028o60nmltOvtP3SnGzhxtFdJ2HJ17MFENINjjElLRDaypEVi+XkTJ6xll/BxBT4FWGQt7pD0e4G+bFgyL89hHnR9MrP0HUd0jOJkB8iAI/qRnlDODII6fctkJ9iGwTA5ZLW+0BQGrSoQAirDAXF6AOhso0IljEJg+X6MMjNZ2MqMxKT6ZEQ1fhi9oJlc4LmWkUltSyojjlDfXw3xAf89IBQbsohXGmYjB4MekFU7wNJvQkYrLEcBnnFweDmh5IgKKoIAL+EWRjk5rExvj96VYBQq77QdHQ6V6I7OBfCyiUgnGqrNAqE/WkH0BdXjNtuZehJIVJG/4y+QBsIhzsHDDz0Ly0ll0rlUChUJmZ1X213kccjgJDPFzF+lldBXK6I8WeS9SBH2accQLgGiumbdT3JGBCKxTJynms1A1ZW4sZJJAqdeUbbra6wRaKmJcExpr9HOQBALF45jFN3Cxr/etz6TIgP+EPW5AVlhxspRbsbZMeCIf5vC4SjQ7T/XIFAAtGv/4DsWAgBmC3UtkZlhyuU7W5QtLlB0epOCwTJdtGKvTpASEAhXSCU1PmYhEFuPhUGOblhmEyPBK8oGKrTO61uD6W0ip7bRoFBaaMXNKd2QdHmbgCmTAOhotXKVRMGpGx3A7cgBMrjzhDXeZEO5EpgUFixF9yCUAjLl0BQWB6AmaJgRkGQnCPMiMBAWCqeRu3DcFzSqrSQ9oenoi8qE6LqvSQQPi+vMgqEvVH56E+vxl2vIjwML8Et13JcZ5+nD4Q39IGQDkQJBGKIxbJX3l2cmRECgPHAKYccQMiAHGWfcgDhGiimb9b1JENAqE22JPY3raz9crXgazXmGbVaaaKm1rG0RSusFghXApW6YTbm4J778QnyAV5a70MBQj04PB4C8TetEI4+NwyCXB7E/22D/DALysOuxF69djeoDrtC2eEKRbsbFG2WASClXbTJcxkMEkAoqFwGhAcNA6Gs0csEDC5rEc2OwHQ2G4qjzjYBQUOtopJaFpQdrtCc2kWE3hgAQlmLB6QN3vrtoo02DJM57AZ+WSB4ZYHQnN0Jcb2XnjtoCQyKKv3BKwqGoCyQ4goKywPAK7D/vKAxcXLZ6Genop+dvqg0DEbsx1BMMkYSEmwGhcNxSRDV7CGBsDfOyA7CiJLFhNEmdAVl4ZZbGW65luPaXvopo0N/9tsUGF41d5HPFy0+UziA0AGEL48cZZ9yAOEaKKZv1vUkKjjIoNEQoSxq9eq5giuBL1u0YZqTtfNyugms1u5lNPT9ArAazC3ZFTnz53Vi/m7xQV5SwzIKhPpwGArxt+0Qjj+H4PlTSD4rgaLDA6ojrpAf8oCi1R3K9kUItNAFNCZxDcsAEBJQKDqgmyBqGAgVhzwgqtwLUeXSHKGgIgDcPGqL6GRGOKSt7rQXy9NuFT3sQoFBSZ0P1Cd3QX1yFwGzy8Gqyh+iWl8IK/dAUs2CpGZRtb42DZOR1PtgKiMSghrWIhB6Q1LvA2m9D2QN3pBU0186LygPALcgCPwSKgwKSgPBzWe2RdSQhmKTdICQqoHwVDyLTsHz+MQVu4ejyXEQ1/hC3BZp3B1MrVlcSt+GRxF5uOVajluu5bjqeYI+EP7RZ1eg0HUX5XLm3UWBQAwAVu8vXW/icsWMP5OsBznKPuUAwjVQTN+s60lah5AIZSGWkstkq+sKWgtfus7laswzaqVQqLGwYNnuv9VyLEUi64HQ3G5BXfFHJ8CvYOs5Uop280C4JML5Ux52heqIKxRtLgT8WdEKak7yQx5kmIxBlfsvJYge8DMIhMo2dwirWBCUEzAorAgARwcGOTlsCOt8LVosb22rqKSWBXmrOzSndkF52NWw01blD36lHwTleyGp3qMjX5uFySha3TGVGYHpfDaUJ5wJIKz1xvKUUWKP4x6TrqCgbHGFRGkAuLls8PKJdlF+SRCYnhc0prH9MUaBkKo0PI3ch+HYJIwkWucejibFg9eeaXx+MK+ZWEpf0IHuxFISCH/e1kEfCK/bFwhNyVp3kXivt85dFAolAPDKzDwyLQcQ2keOsk85gHANFNM363qSULg8lMW27Zfm4cv84nV7O5d0zqTVajuWIhHxPw9LHEft+g26ZxIIJODWpRl8sJcf8qAHgoeXpGhzh6TWB7KWlbWEmgyTafA2DoPa1tEKfwgr90JYaRwIJbU+BLhU7CVXS3Dz2eBX+kF9bpvNQZBsFW3wXgaEvlAd3w3NqV2QNXsZBa2ZCj/wywIoQChr8LaZO8grDsZkWhSmCtjQnN0JzdmdENV4QbroEBKtozpwWO8DSTUL4gN7FucE/TGWGUGZE+SXBoBXEIqpjChMZUSCkxPGOPgZ01RWOE0gpMKhte7hSFISugOzDQNhcRt6QzLRk9uBntTFlRPulbRh8NKmFgz93ss4ZNDVariL2vdPpr+3V0UOILSPHGWfcgDhGiimb9b1JI1mDgsLtg1lsUTmFq/LZAq7O5d0l8HLZLrBMat3NgC0fz/WrN/gfnjYKIDIGr3MuoHKw65QtLpDWu8NUeUeIoylMBiyFg+oju9edAhtC4SC8uVhMvrilwaAXxZoFAgVre4QH2SBX7KUJjpTGgjVKdsExtBuFa1lQdZEhMloTu2CpIZl9PfBLfMHtySIAoSKNtuEyYgO+GEyLRrTeWwIavyWgLDaZ5kjyaK2rNb4QlLjC2GFHyayIiitoUSCaAB4BWxMZUYsQmEUprMiwMllHgANaSBinxVQqKOwJfdwNNE8FD5PSERPYJb+yokSYgfh49Q29GTWEg6hX71FQPjst1cHCE2Jw+GDz7fcXVQqVQDwSiWjMguEzKxhWG9ylH3KAYRroJi+WdeTRCK53V3B5QADGIavpV155lseV+NMplZY6Lqqq30eAEZXROhKpTK9W9CQeL//CpHO3OBySet8DYNgBzEbKK31JdcjzBQHYTqbDX5xMPjFwZA1e0B9YjcBhe22g0Jpk5dZGNS6hLyiIKNAKG3whqjKH7zCYPCKgmwaGGNJq6iklgXlERdoTu2C6qizyZm8yfwgcItCSDiT1vrYBAZlzZ6YTI/EZFo0JrIioDq5mwKE4oN7lnTAj6LpglA8S47XA0GtuAXBRAtuHpsEQq1bOJ0d9tKB4fPEeLPQ1xtC3z2kE0wzkpCAniAqFA7kN6E3JBNdMU3ozq7HLddy3Ga3WQaE154wDhn2kDF3URcWAcJd1Ghe7mRUBxCufTnKPuUAwjVQTN+s60l8PjMgqJWhxeu64Sx0QMgeZzJ8Nvu4qi9evIBCYfznIBbLybZVU69bLv7zMfArQkwHg1TvWQyOcYW81R2yFk+Ily0iF1X6Yyo7HNy8EBIG+cXBkDZ6Qn1it82hUHxwD00gJMJMhFX6QChv8YD4IAuiqj2QtbqtaLG8Za2iXnowKK0nwmQ0p3ZBfsjD5O9jOCMS47lhJBDKWzxWDIOKdjdwctmYTIvGVGYExjMjSRgkgNBwoqiwYi8GExMxUxxsHAbzQzGdHbq0wzEjYhkURmEq8+VyCyfSosyC3pPgDKvcQ1NrLUYSE/AkeGmmsD/9IHpDMnF370F0Z9YRQBh1zDIg/HV9AKExSaVyLCwsWOUurmR28VWVAwjtI0fZpxxAuAaK6Zt1PYlpIFy+Z28110nQP5OCciatmDrbwsICFAo1eMNjeh9bCtqZtyhoRyCQgFezj0ZSpB+k9d4QVxsOEJkpCsZEWhR4hcEUGOQXB0PasASEWihUdriuPEymzHy7KGVZfSU1ZVTRSswOytvcVyUwxmir6BH9VlFJLQuKNneyXVRaZ3qdw3BaFMZywxeB0McmqyYEFXsxmRZNKDMCgpo9y4BQv4V1aH+swfZQcqVEWQAJedM5urscl7uEOm5hVvhLAYacnOXrJ/TVE5i5srZSI+7haGI8ekMz0B2Qi76YQvSG5+K2Wxm60xcdwrjTFgHh0ys9jEMGk5LJFJifnzf5GktmFw25i2slwZTD4TuA0E5ylH3KAYRroJi+WdeTmAZCsZgAQqlUserrJOgDIXX3n6UhLasBhEqlGlM//0a5rt0taE3QDvdsK+3VAcZSJKcyIzCVGaEHglpJ6r0oQGgLKDQfJrNcARCUEa2vitZFd7DNFZrzH9gNBE21ikpqfaE+QYTJqE/sJttvjWkoLQoTBWxIqlk2WTUhbfTGZFoUAYPpUXgWlwRBNcuoQ8gpCMVTE+2hoooATOeFYTpnCbB0gdCoS6gDhi9D6MyzmGSTMNcdYAsg1HcPn0WnYDguCX0RWcTKiZQK3HYrw+OUamKGMOGcAwgtkFyuxNzc3Iogab24ixwOn/HnkfUiR9mnHEC4Borpm3U9iWkg1K5VsMc6CbrS3f1nTUiLrTU/vwCVSoOx83+HULjyfYe8a5chqrQeBrkFIRjbF43pHLZRGOQXB0Nc660HhFppg2gsBUJRlR9tZ5BUWQDEB32haHOF+uy2VZ8TpNsqKqllQdbiSbqDinY3sz/7Z2nRmCoOhqhm5asmFG1umM4OJ93BqexwPE+Ow3h6FBUIa3whrNiL0bRozJQEmYTB4X1xmMgMp8CVLhAS6zzCTADhyxE6M5Ici75Q4/D22D/b5kDYz05HX0g6ulj5uOFeSSylz67HbbcyPIypIFJGEz+0DAh/6WYcNJiUQqHE7Kz1QGhOa8lddACh/eQo+5QDCNdAMX2zrifNzDALg1qXa3Z2jnEQ1D2X9kyAZSEtq6G5uXmoVBqMNLZBoVhZ2yr/2XMIKoKtAkFBeQAmMyIwkhiPodgEjO2LxmRaJKazwzFjoGVUXONjFAgJKHSxCAplzZ7glwTSB8FFGBRW+EN5fJfdQdBcq6iklgXVURcSCGWN3uaBMDUGE/lhmMxnr9gdnCkJXGoVTYvGSHIcRvfFYjg2GbI2DxIIeeV7wS0INQmCwvIA9Mclg5Orv19wORASLqFpIGQ6dGYyMwK9IRlGofCRf45NQbA7IBu3PUrx+7ZqXH2vDr+804gnwZnoLziE2x5FuBdA7CHsjLvgAEILpFSqoNHMMgZYr5K7yOEIGH8eWS9ylH3KAYRroJi+WdeTmAJCqXRpnQRAf62CPaRtGbVncIw5IFSrZzFaUrmitlWBQAJedbKVrmAoxvdHYzijAE/L2jFc2YbRA60YySvCeGocJlKjMJkeCU4uGzNFBBCKqn1NAqH6xG4oj9CHQkGFP00YXPzvMn8ojjhj9mNmQHDu0/ehOW+sVZQFaYM3CYPqk7sgPmi6XVQLhKNZkStuF5XU+iy1iqZFYzo7HE+j92E4LhHDscngFIbqOIQskzDIKwrBYEKiUbhaDoS8Ajams8JpQuFi6EyOfYGQk0vMERqDwkd+KwfC3uAM3PcpxJ+7qvDbB7X47YNa/Po+AYO/vNOE7oBs9BW2475fPrmU/s9oy4Bw8KfHjEMZk1Kp1FCrNYyfw5BeNnfRVkA4MDCCxMRkvP3229i8eTPKyw9gakpo8LXffPMjvLy88eabb8Ld3QNff/0D+bGNGzdS9MYbb8DJyQmff/4FeDwpLl78Eq+//jrlNZmZ2Yw/U9GRo+xTDiBcA8X0zbqexAQQatcjzM4S6yQsTcdcTWkdOABQKJidZdQFwhcvXmAkpwDC5/rBMqbEnxGj98zvuFP6HfrTiqx2BcdSYvEkOAO9+xswUHQcT/a14a5nCe56lOKuRyl6gjIxlhJLrC1Ii8JkZgT4FSyzQKg+sRuqo85moVB+yAMzRt3BQH0YLA2E4vAuxkDQXKuopJYFRbsbCYTKw660fh/P9sVgLCdsRWEy8lZ3TGVGUNzB8fQojKTEYTg2mVB8IlQniNUT4hpfozA4lhmFkf0xJuHKEBAaD5cx4RbaOXRmOD4RfaEZ6A3Wh8KHVgJhX2g6Hvnl4qZrOX77oIYEQQIGa0kY/OWdJjz0y0Nvfge62KUkEF5nn7cMCC89Yhx8mJRarYFKpWb8HJbDmf3dRVsBIZsdjoyMbIyN8dDV1QtPTy8cPnxc73X37/dgw4Y38OWX32JqSoiLF7/CG2+8gSdPnhn8upmZOYiKiiXhsqqqBjk5+Yw/Q1kjR9mnHEC4Borpm3W9yV5gQ8y+6a9H0IamMAldy4Nj6EAqd4Sz6ufSwvPCwgKeZ+Ri+srvtD5vrPMpbiZ9hsvvteDnt5twP6IaoioLXcH8EIynRmEkIR6P92bjsX8uRY+Ci/E4qRmPktpwz78Kdz1KKGDILQiiBYR0oFBcw6LnCmqvlQVAcdgZmgv2SxHVbxV1NgqDkjpfqE/sWmoXbfakB4T7YyGqYa3IHeQVBlNgcCojEoNR+zC6L2YJCGOTwa/yJ4Cw1jAQPk1KwOSyeUFK22V2MAGE2fpAyM1nYyLdEiC0f+jMeGo0+kIzDELhQ79ci0CwJzALdz2LcX3HQQoEanVtKxUGf3m3Gfd8CtGT2Y6HsQdIILy294xlQPjj+gZCwllTMX4OW2s13EUOx7CLZ4kePHgCJycn9PYOkdcuXvwSO3bs1HttXV0TIiOjKdeio+PQ2HhI77Uff/w5tm7diqdPx8hroaFhOHXqPOPPT9bIUfYpBxCugWL6Zl1vEghWH7ios2/U4BhtaApTMGgoOIYOpE7c6F61M4nFMtIZnJubx+zsHJ6nZWPik4tGP4c3wcejhkv41eUwfnmXeLD86e0mXN1aA35poGWuYGYExvfHYCAyBY/9c/RgUA8O/XJxy70Ef+yqxA2XCvQEZ2AqJ4Q2EKpP7IbqmHEo5BuCPr1r2lZRYqZNeXQ31CeZcQlNtYpKalmQH/IgYVBzahckNfqrHQxpND9mRWEyouo9FBicTIvGZBbRLjoUm0gBwtGUWKjP6AOhoCwQ/XHJpmfwssPAKwgyCoS8AjaRUmsxENovdGY6Owx9oelLULjYPtobko6He8wDYW9IBrpY+eh0rtBzA5fD4OV3G3BlSz1+cj2Nb73+ifP/18f4fVcVHiW34GFSHQmEVzxOWAaEPzxkHF6Y1OzsLBQKJePnsKcscRfT0zMQFxePiooKHDt2Ev/+9ze4ceMeRkamrXqW+Oqrb/Huu5sp127efAAnJycMDU1SricmpqCysppyrbKyGomJyZRrw8NTePfdzbh48UvyGocjxsaNbyEmJg47duzEtm3bkZ9fjGfPJhh/nqIjR9mnHEC4Borpm3W9aTWBUCxect5UKsOApW15YQIG1WrCgVseHDM/bx4In391fVXOJJcrKamravUs5ubmMJyaibG2Y3qvf/ZtF/4IPY/Lm5tw+V1CWhj86e1GTGaHW5QgOpEahbF9sXjCTsUd3zyzMGhID3wK8Cgo3SIgNAaFsmZP8IsD6cGgNkimPADK4zuhOuYMjR13DdJpFZXUsohzLcKg6pgzfVg/sMeKNFF3KNrdIG/2wGR65DIgjMJQfBK1XVRHkiZviOt8SBjk5LPxNDHBDEixMZ0VBkFJoEkg5OazMZkeaTUUEqEzq9tGOhi5jwRCLRQSQJhnPIF0bw5uuxMBMcYgUBcGv3uzBRf+x1mc/svHFP22swr32XV4tL+RBMKft3VYBIQD3693IJyDXL6+gNCcdN3FkydPYd++/WCxWHjrrbfg5OREasuWLfD3D0BdXRPtZ4m///2f2L59B+VaV1cvnJyc0NPzlHI9PDwKDQ0tlGv19c0ID4+iXGtpaQeL5UfZkdjf/xwhIWxcuPB3jI3x8PjxINjscMTGxjP+PEVHjrJPOYBwDRTTN+t602oBoS7YmFrZMDs7B41m1q4gqLu6QS7Xbw2dn58361o+Pf3dKgCqdrfgrM41Debm5vF8fwZGKmshFErB6Z/CvcKvcGVbKwmB+jDYjIGYFFqgIVx0BSdSYzCaFIf+sFQ8DMjGHW/rgPCxfy562elQHbcMCAko3E1AzCIQCiv9aYAgFQaF5QFQndgJ1TEXqE/tfHlaRWtZkDZ6UdxBeasHrd/RTHEwFIc8LIZBSb0PFO1u4OSy9dzB6exwDEamkumiyzWZHQ5xPQGEI2kxGE2NMg2DuaEY2xcDQRnxuzIFhLwCNiYzVgKEqx86M5IURwHCvtAMPAnOQNcyIHwSnEkExOysMguBuvrH/3tCDwS1urazCre9KvAotYVYOeFeaREMXtrUgoHvuhgHECY1Pz8PmUzB+DleBXE4QgwMjOLatU58/vkXOHSoAzk5+aiurqf9LPHvf3+DzZsNO4TDw1OU6wkJSaiqqqFcIxzCFPK/uVwJduzYiU8++YfZP/v332/itddes9rdtKccZZ9yAOEaKKZv1vUmW0ONSKS7NN086Gk0s3ZdO6FQqMyubqDjWvY1fL5KgEpNNlWpiHaf4ZQ0PEvJxu++R3B5Sz2ubqnDr+8RYRTX3q/Bta2Eft1ajWtbq/HAL4fW3KDWFRzfH4PhuET0s9OIAIywVDzam2U1EPYEZloFhNoF9oo2NyhaPTBTEkADBoMoMCgsD4D61A6ojrksuoQvR6uopJYFZYcrBQildb5mf0eiKn9M5YZavGdQUB4AZYcb+KUB+q2iadEY3Re72C6aZBAIh2OTIKpmoT8uCVPZxmf3OLlscPJCMbYvFtw89mJraYBZIOTkhq3QJVzd0JmJ9EiKO9gTlIWewCw8YOWjL5SYJTQUEENHX/zvo0Zh8PRfPsavzrXEDsL9BBDe9qu3HAi/fcA4aDAp4h8j5Yyf41UQlyta8bPE/fs9cHJyQn//c/LaxYtf6rmGPJ4UtbWNiI6Oo1yLjo5DfX0z+d+//daJDRvewNgYj/K6zs77qK6up7iGly9fx+uvv46JiZd/n6Kj7FMOIFwDVbbCKgAAIABJREFUxfTNut5kS4dwaZ0E/aXparV9gFAbHAPAaPuqVnRcyydFZyAQSFYdULldo7gZdBiP/LPQG5qGOx7FuO1egttupbjtVopbrmW45VqGmy7luOlSjk7nCtzxLIKgzPTcoLBiL6YWXcHxfTF4GpVCbX8L34/ugEyrgfCxfw5Ux6wDQi0Uypo9zIOgAXdQWB4A9Znti0DoAvXp1XcJZz8x3yoqqfOB+uQSDKpP7Ib4gPl1EyOpMZA2etOHwXY3zBQHQ9bsBUmtL2XFBJksuj8Gg5GpGIxOMQKDhPpi4k1CEyeXDU5+CMb2xWA8NRrC8sXdhCQQhhkFQl7BSttGVzd0hpPLRm9IGp4EZaEnMBs9gTl4vDcbd7yKcGULsSLi6pZ6i2Hw67914PRfPjIJhFddm3DbrQxdSU0EELLbLAbC/m/WNxAuLLyARCJj/ByvgmwBhDyeFMHBoUhNzcDIyDQePuyDp6eXwaCYu3cfY8OGN3Dx4ldkyuiGDW/g3r1u8jVHj55EUFCI3uf29DzFxo0b0dFxDFNTQjx+PIiAgCDk5RUy/jxFR46yTzmAcA0U0zfrepOtgHD5OglLPm9ubn5VYZAIjlmgBMeYkkYzC43GNKT25J0At2/URoBKdSN5k3w8avoJv7oewdX36tDpXIEuVh4e+efipksFbrpUoNO5Ajd2V+LGrkr8ubMKf+w4sKgqTOeGmQQM3qIrOJEag9HkOAyE7dePyGenGkwXtUQrAUItFIoP7rEYBoXl/tCc3UYCoeqYMzSrvI9QcdR0q6iklgV5qzvFHVS0u5mFQU5BKCaz6a+a0MKgsMofinY3A3ODhLqDszAYmYrHAdkmgfBBUIZJYOIuwuBYShxmCkMoy+q5eWxMZUeZBMLpbOpOwvHUaIwkxawIDG0ZOjMYlYKewBxSd72KcMu9BP99vR2Xt7Xh5+CL+P79I7i2lSYQ7jxgFgZP/+VjXHVvJ4AwtoEAwuhjlgPhf+8zDhpM6sWLFxCLpYyf41UQlyu2yfNEf/9zpKSkYvPmzdiy5T1UVdVgepqAzY0bN+Kzz/5Fvva7736Gjw8LGze+BU9PL3zzzY+Ur1VSUo79+9MN/jk//3wNgYHBeOutTdiy5T2UlVVifHyG8ecpOnKUfcoBhGugmL5Z15tWCoRisZxMxLRmn6BSqcb8/MKqwSA1OIYeqNJxLXvyTmD88n2rzrTkpFIBdfiHx/gz/EMyIObK5gZ0OhMASABhDgmEhtTpXIHhpHjTrmDWoiu4PwbP4xPQz041vDONnYZHe80njJqS8qjzioCQhEKjaycIIKTCYABEB/YsA8LVdQnptIpKan2hOr6bAoSyRm+zraIj+2Mhrqa3akLR7oaZkiBw89lQdriBkxdquFU0OQ59YWnoY6fjaZRph/BRcJoRGAwFrzAY4/sJGJxMjyLdQS0QciqSMJ5mGgi1LuFkeiRGU2IxFJOModgE27SR2iB0ZjQllgKEtz2LcNutBBf/50kKwH3+P0+YhcI73kX49t0GszB4+i8f47L7Edx2K8MDdg1uuZbjfoplOwgvbWpB/9frGwgBQCRyACEd2QoIHTIvR9mnHEC4Borpm3W9aSVAqG13nJ+fX1yKa/nXUCrVWFiwPRDq7j00FBxjDiLNuZY9eScx9Nllq77fFy9ekE4qZ3AK94r/gyvb25YFxDTgxu5KEvYe+Obh8d4cdDqXGwXCnpAMo3ODvMIlV3B8fwyeRSebjs0PTcMjGisnTALhkZUDoRYKJbW+NN3BAIjrvKE5RwXC1XIJabWK1rIga6KGyahP7oL44B7TraL7Y8HJCYOizd0sDBKzgoGYzoqArNkLwoN7DLaKTqZFoyc0A4ORqejyyzMJg8OxyXgStl8PqpbD4FhKLPglQXq7CicPFtACwon0SAzHJWEoJgVDsUkYikmyXRvpCkNnprLCqUDoUYxbbiX44n+dwLn/40MKxJ3/P8/iipEW0l82N0BY5Y9P/p9TtIDwJ5cjuO1WglveZYRDmPShxUA4/P1jCARi8Hj6e+fWujgcPgBAKJQwfpZXQQ4gtJ8cZZ9yAOEaKKZv1vUmPt9y2DLV7mgtVNoSBqlzeZaDqjbIxSQQ5p/EYMeXtL+m7m5BhUKFvo/+xO97TuKXZSmhhBrx584qCuw98MnH4705uOlSZhAG73oVQVAWYMQVDMdEagwmUmMwlhKLgXD9FlH9PWrpeOS3MiBUHHaxCRBqJa33MRkko5WkyROac9uXAaEL1Kd3MNIqKqllQXnEhQKEyiMuZltFpzLDISjbS8sd5JcFYDorEsKqvVC0ehiFwYnUaDxZBMLHgabbRYdjk/EkfD+mc5bBYHEQxlOjF2EwDtNZEQaX10+kRpkEQk4uG6MpcQQILmowMgXPopNtOFe48tCZJyHpJBDecivBLbdSfPG/TuCz//u0AZi7gEubmikweGVLPb74awe4pYG0YPD0Xz7Gpd1HcNurmFw5cTPBciCcvjJA/n9V+36oVmugUCghlcohFEowMyMEh8NnHEhsDzgCAIBAIGb8LK+CdANaHFpdOco+5QDCNVBM36zrTZYCoaFF7iuRXK4EAJuAoK1AlY5r+aTgJHqrLlj0MxP1TuN26j9w+b0WAxC4pOvbD/7/7J13fBMHmv5DNpvN3uZ+SXbv9vZu93azQLy5TWE3lFRSaKYaDLj33nu3cccGDBhwoQRCNzYtWVJIAoEUejCm44IN7lZvbnLj+f0x1kiyRtKMLGmMpffzeT6BsSyN5YyZr5/nfV8N4KtaGIdb9tG4PCeFAghTwYl11OkKtoZ44qGv9ojoSN11CB09EG6abVQglJd+CNma+eTUUSoYFKXZQ7ZuHiUQGtsl5ObpB0Fp7mLI8tSHyfRt+wBd62x1RkWbgj3BiXZB5zpbvTAoXEXAoCIq2hHtTAmDbaEeqHENRp1bCO45hqPeXTcMPvAKwC2HUHREOpMwyE9ergaDzUFeEKYupwbCUHe0hmgCITfOEa1h7mjwClCDwQbPAFQ7haDePdDIQDi6oTMN3n4kEF6anYJLs1NxZFIpDk8sxcf/+Qkl0H36f5vw/du5OPvWauz948f41xvrUBvgSxsIT763GT8vzySB8ILPbsZAWH30KpR752To7OxGb68c/f0DGBoaUvt3d2hoCH19/ejp6UVnZzckEhkEAjG43MfTXeTxRAAAgUDM+rk8DrICoflkLfOUFQjHQbF9sVqamAChYk/eyEXuo1FnJwGETAbRUD8PdV+eIerulmNoSLdreTd+K25HaS6K1wBeSRfqin/A93OLtLiB6vrh7Ryyb1BVlQvicGd5JK7MTdb4WFOQJ8UEUaUr2BLsiXpP3RFRDSBcGTYqGLy1NAZdG+cYHQjlpR8Sy+pTlkGYag9Bij14CSvBiXMEN84RvASH4cgoFRDOgnyHcVzC7h3vg5e+jBYQdm9UHybTt+0DSHMWawXCh8Fe4ES7gBvnoHeYjCh9GToi3Yio6Nr5EK5aphUGiWEyEbTjog+8AnB1aRTaIlwIGExZjtZQFRgM9AYnxokSBsWr7NEW5obWUDf1ITLRznjo6zsCBAnVewSg1jkU900GhMoYaVOIB20gbAnxIIHwwiwlEB6ZVIoD/0vlEir7Cg/+heg1/HZmFi4tjaUNhF+9WYhKt3wSCM97GAaEuiCAwxFAIBBDLJZBJutCd3cv+vr6MTg4qPZvsiLi3tsrR1dXD6TSzuEoqoh1kNEmPp8AQj5/7J7jWBGHI7ACoRllLfOUFQjHQbF9sVqa6AChTNatdU/eaCWTdQOA1p2AdKSYcNrXx2zCqXYg1B9jvRu/FTd9C7R+vPHbO7jksZccEENHZ4cnilJFQivnJ+DuiihcmZtEHrsyLxn1Xv5qfYO8hJVqrmBzoBdqXfVHREfq9grmQHjTLgbXF8ehamE8KucnonPDPJMAobz0Q3QW2IKfuBL8RAcNiXMWagVCY7mELUkOtGBQmrsI8lL1YTK9xR9pXTfRFuOM9ggXcKJdIF29SDcMZixFR6QrERVNX4bOdbZao6JtoR544OOH2mGH8PrSaHpAaBeNlnAXCFIJx08VBluCPdUGyWgAYbgrWocjo9xYRzQHexJDYyhgkHAHgwkgdAsaFfA1B9N4TJAX7rmGqMVhtakj2hl3lkcSQPhRKi7NUgLh4Yml2PGfu/UC3k8LkvD1Ozn0gXDqelzzWk8C4U9OzIfK3Dv886hAgccTQSSSQirtRFdXz/BE6AE8evSI/Pda0UNORFF7IZN1QSyWgs8XsxpFFQjEw/cTViCkA4Rs34dYkqxlnrIC4Tgoti9WSxOfrxuOVIegjAbatEkq7QIAg4bSqA6OMWTCqVZXj0aM9W78VtxwyVE7xrnfgWspn+HMzJEDYvTru+l5WmFQEwhTcWtZFGpdgyFMs6fsFWwN8USjnw/tiKgGENqHk5B3Y0kMri+ORdWiOFxbGI/K+Qm4aptI7kS8PDsFl2al4sKHaTj3fgZ+fC8L52blQrJ2vsmAUF76Ibo2zAU/SRMKxdmLdADhLMh3vDe6qOjqJTRhcDFkI4bJ9G37AN0b5lJPgU1fhmpvP3CiXcCJdkJPoXYYFGfakTDIjSMe2x7pQssdvOMQgfs04qIPvAJwwzWKgMEwdRhsDvQGL95BKwyKV9mjLdYLraGuaI9wVQ6N0SZvf9Q4haDWORR1rsGjA8JA+o+t8wpEg5/uXYvcWCfUugbjzvJonP8wDRdnpZFAeGRSKfb/aYdewLu6MgplLxXTBsIv/7EOVX6FJBB+v3QHcyCsuGIyiOBy1aOoPT1y9Pf3U0ZR+/v70dMjJ6OoQqHE5FFUoVACAI9t5NUKhONX1jJPWYFwHBTbF6ulSRsQqq6T6OnRvch9NJJIOgGAccxztINjdEkZY9UNhNeXp0EolKJm3yX8uHSb1gExappO6Lvp+YRm5OO7GavVJopS6WfbBNxdEYkbdtGodgxDjVMouAkOhCuYqO4KtgR7osHLHzVOoQbBYI1TGO4sD8Ol2anDQ2zSVBbfp+H8B+n48b1MfP9OFr57czW+mboGX04pwL/+XoijLxXh8Csfg98mQNdOR5MCobz0Q3RvJFYtaDiEH2sHwu7Nsw12CXt2fQBe5nLaQNgS4w7ZmvnoLfqI7COU5S2kBMJ7QaHDMOgCUYaddhjMXkLCIBEVXQB+8nKdMNgc5IV7TmGocwvBlQUJtGDwoY8vhKuWoy3MTQMGR66ZoNLDiAA0+vvoBsFh3fcIRK1zKAGELgQQtoQYBoSNAcz2GLaGuuOuSwjaIly0AmGjvzcBhB9oAuHhiaXY/h+6XcIbrqG09g+SQDilAFX+m0kg/G5eCXMgLDcdEOoDDD5fDLFYSkZR5fI+8pd3iiJ+fg+gt7ePjKKKRFIYw9UTiaQAMC4H5hj/+yVk/T7EkmQt85QVCMdBsX2xWpqogNAY6yToSiwmgLCzkx4QGnPCqTYpYqy64qe3w7egalECzszcoAXylDrzpi7l4fwHGTph8NKsVahcFDsMgoRaw93U9gqSEdEgL9S5BRkMgkogjMTJf67F569twKcvb0bFxGIc+N/t2Ps/O7H3f3bp1AGbvRCJZOj6xNXkQCgv/RDdm2ZDoAKFkpyFkO+YqRUIe4tnobtolkFAKCsLoQ2D4i1+asAnzVk0vIxeMy4qWOePjjg3Egi71s+jhEFJzmJ0RClgkIiKSvMX6oyKtoV64MYKYhE90T+oPy760NcHwrRlaAvXhMHmQC8IkjTXTCgkTLVHW7ibjnioZlz0nmMoCYS1ziFoD3dHU4CXYUDoZ9jnNYUFoM4zgBIIW8PccGd5NH56n9j3qQqERyaVYt8fdbuEV+xjaMOgAgiv+ReRQPjtO4XMgfDQZdZhg0o8nghCoUQlikoMulGFRQAYHBxEX1+/ShSVGHRDB/LEYuLGm+2v9XGQFQjNK2uZp6xAOA6K7YvV0qQKhOaALSoBQGen/t5EbQvdTQWEupzHStcNuL44HmfeXK0H+HTrp5mZumFwTipu20eSMFjtGIpGf28NV7A1xBNN/t6ocTYsIqoZGY3QC37atH/SHuIXC3u9zQKE8tIP0bN5FgSpy4eBcBHk295Hb/GH2oGwcA5jl7D7uCdtGJTmLoZoR5zO1RLkVNEse3DyI0kY5CeuoBwmI81dhI4oFxIGuXFO6NowB+3hbjphsC3UAzfsCSC8vTIS9R40YDB9KdoiqGDQG+1a1kyIV9mDG+eodWiMNtV7BZBxUQUQtoW5o9HfGy1BzOHuga/PqCKnTYFeaB/hFnJinHBrWRR+npeICx+laQBhxV91u4Q/zk9mBIRfTCnAVf8SYuXE3HTGMPj1Pwtwt2xsAqEucblCCARilSgqMeiGOopKDLpRjaIqdi5KJDI8evSI9a/ncZAVCM0ra5mnrEA4Dorti9USJRQqViOYHraoRGd5vGJwjGKhuynPh05f4/WEA6hckIDv38mhDX+kazg9H6enr8EP72Tr6BtMww27GDVXsMYpBPWefmgLd1MDwZZgTzzw9htVRFTTIRwFEP51N3p7+9BbFmQ2IJSXfoieLbMgTLOHOHcheks+1AmEvcWz0LWFvkvYVzYLkk0utGFQsmYFxLmaq0CoxC9JImGQE+0CWf4CTRjMW6gGg4qoKC/BQS8M3nYOJd1BfXHRRj8fiNKXoj3ClRIGmwO9IEzRXDMhSF5ORJUZgKBC1S6qMBiKWpcQPPT3wkM/HzzwZr6k/oGP36iAsD3cHW2h7mgO8lQbOlPnFoybdrG4NLyHcKT2/M/HWgBvD76dmcUICD9/vQBX/EqJpfR2eYYB4cFLrMOGccFFAD6fGHRDRFF7IJf3ka0NiiLSLUPDveU9wz/HFTsX2f86xpo4HBHr9yCWJGuZp6xAOA6K7YvVEqWc0tlvctii0tCQ9qEwqr2Mxhwco0t0+hrvZB3GpVmp+Om9TFrwp+wjVEwUzdU5UfSegxLOqh2JQRsNnoFo8vdRh8EgT9x3CzQaCJJrJ1aMAghf3E18vw6FmQ0Ge4s+gmytLUQZiyHJWYCezbP0A+HGufSjoofoR0WluYsh+jiWFgyKCoPQEauMinJinDTcQdmaBeBEq8KgG4SrlkGSs1hvVLQt1ANXl8SQQHhjmfZl9I3+3hBl2KE9UhsMeoMT46wRD+2IctE/NEabvPxx1yFMDQjr3IJwa1k06j39UO0ciqZhEG0O8kJLMPELkNYQD0KhHmgLc0dbmBLmGrxHD4QKtQR5ojXMbbiP0Ac3lsShckEijr20RQMIy/+6ldIl3POnHTjySiEzIJyyAZd8thJA6LjRMCA8cJF12DCnlDsXO9HX108OQxsaGhlFVe5cVI2icrmW2W9oBULzylrmKSsQjoNi+2K1RA0MDOp16EypwcEhysE15uxlVJWir1EbEPb29qFuw5c4NzMTP83MUAKgFvijO1H0ypxk3Fkeoe4KOoeg3kPZa9USpDJF1N8Hd1caFwRJIFwZbjgQ/vkTSKVdkB2KMS0ElhCTRiXZiyBIWQZxxlKIs5ZAnLMInRvmDruE2oGwt3gWuos/MnpUVJq7GKJCf/1R0ezl4KyOUHMHxVlL1GCwc918DRjkxjqhq2AO2sL0R0Xv+/qjxoWAwdsrtMdFmwK8Ic60Q3uUi1YYHLlmgp+4Eo3+3oaB4LCIfld1h/DWskhULUrA7eWRuLsyHA3e/njgQ0d+eODrh/vugXjo54tGPx80+vugKcAbjQHeaPTzwUNfX/KYAjBbQzwIsA7T4haGuaM50Att4W64vjge1xYm4seZmZQu4e7/3qkBd4deKsLH/0W9wF4XEJ733Eb0ELoXGwSEd/ZbFhCqqrOzG4ODg+TfuVzlzkXVKOrg4MgoqurOxW5IJJ1qUdTxKCsQmlfWMk9ZgXAcFNsXqyWKLRBUAuGgWs+iWNyJvj7z9zKqCtDsa1R1K+uKTuKn9zJx9q0cnfCnqXyKiaKpuLk0Wg0Eqx0Jp0T15vmBtz8ZEa1zC8K5mRk4N289arIPoTY0e0S8dHS652g4EO77310QiWSQHU402RAZad5CCNOWQZi6HIJUe4gz7SDJsoMkawnEWQshzV+A7s26YbC3eBa6NszTExX9CJLNzoxgUFwSTDMqmqwGg5xoZ3RvmKuEwYJ54EQ7q8FgR6QrOtcsACfGSS8MtoV6oMo9UW9ctCnQC+KsJeiIdtYKg8SaCUfCFUyxR2sYk6Ex2ofJ3FkZPiIuGoyqRQmkbi+PRJ17EE0gJHTfI5D8c4O3P+45hQ2vTEmkoXhcXxKLW/ZRuLMiAvccw1DtHIIalxBUuwTj2sJY8rFfTSnQAMJDL27VmCa678WtjGBw+3/sxYl/bsJ5r+2EQ+iz3TAg3HeBddhgS11dPejvH6AJRHwyiiqV6o6iDgwodi72QCZTjaI+vu4ilytm/R7EkmQt85QVCMdBsX2xWqKEQnaBkPhHtp+ACJXBMXQnj5oKCLu6lEDY1dWj5lbWbD89DIS5jGBw5ETRawvjR4AcMVRD6Qoq1ejng5YgT9ywi8YF+2K0f3sXg4NDpHvKvXUfdSmbUO0UPmogrHYKx8+brhoGhX8igFB6NN14/YFFH0G2Zj5EGXYQptpDmLp8WKowSAChKH0xRBl26N40Wy8Q9hbPQk/pB0aLikpzF0O4LYZmVNRVDQgFqfYkDHZvmAdOzEgYdINwlT1EGXa0oqJt4d6o9o7WGRdtCvIkYDBGNwy2hhJrJrixjnjo4zdKEFTGRe+NiIvecwhTA8KqRfG45xBGGwYbvP1w34PYa1jtEY3rK1NogiBzXZmXjKMvFWlA4Sd/2KUGdx//Xv/i+pH6bGoxLngNO4S+Ow0Dwr2WC4Td3T3o7+83ynMpo6iEu6iYiko16EYRRVUMuiGiqGPbXbQCoXllLfOUFQjHQbF9sVqi2AbC/v4B9PX1m3VwjD6p9iz29fUDAORypVtZt/9H/PReJr5/K4c2EJ5TmSh6ZV4y7q6IUIcwx1DcH+EKquqhry+uem0C/2YzAKLnk+rcBW18NBTuQ7VrjOFA6BgGkUiGn5J/wh6mQPjHnRCJZJB8tnrUkdDO9fMgzloMQYoqBBIgKExbpgKCdhBn2kGQsgyCZHsIU5eha7MtLSDs1OIS9hz3YAyDkgJniLOX6wbCnBXg5IaPcAdd0Ll2/jAMzqGEQW6sE2SFS+jBYKgHWlZnkDB4a7kmDDYHe0CSvQScWCedMNgc6A1unAOagwwbGqN1mMzwoCTV6aLXF8eOAMIEXF8Si/ue9ICw3ssPtW5BuLYgEVfnpaBycTpuRRTjuvtqk0DhD+9maQBh2V+2aQDeJ3/Yiq0v0AfD49O24aIX0UN40Xe3YUC45zzrsMGWFJFQU78Oh6OMoip2LhJR1EG1+xpFPyMRRSV2LhJR1NHvXLQC4eMla5mnrEA4Dorti9USxTYQKgYAmHNwjD4NDQ2ht7ePnFY3Mj5af/wKAYRv0wPCH97JJuOht5ZFabqCLsGUrmCDZyDqXINxfVkcuDVNZIyJTs+nUChFU8XXqPZNZRwnVQChSCTDKd9vGbqEw0D4+QbDIqGFcyBdvQiC4UjoSAlS7CFKX6oOgxlLIUhaAW6CCwTJyyFKs0fXfi9aQNhbPAs9296niIrSnypK9g7ujNfrDgq3pWrAIDfOAT2b5qC7cA44sU4aMNgR6QrZmgXoyE+gBYNtoR54kJROAuF520Q1GGwJ9oAke7FeGGwKIAa6NHgZODRGqzsYgJv2UWruYI1zqAYMKnTLPkpnL2GDtz+qncJwfUkMapxDcXVeirpsU3EzZAtu+BUYFQgrFyTii9fWa0Dhzv9SuoS7/3snDv21CDt/r9lfqE1Hpu3ERU9iyugFH8OA8PZuywXC3l455PI+1s+Dx1NEURU7F/swMDBAMRVVEUVVDLoxXxSVy5UY5T6itrYRfn4BeOONNzB9+nSkpWWivZ26P/HEiZOYP38BXn/9dcydOw+fffYV+TEOR4IpU6bg9ddfx5QpU0g1NXEZv85YlLXMU1YgHAfF9sVqiWITCLu6ekkYNOfgGDpAqOgZkUg03cqH39zETzMz8f07+oFQMVG0alGcBphVO4Xivju1K1jjFIqqRfG4NCsNF+dkjmrATvu566iNymcEhkKhlPz8L+xOMAZC8ckSRisjpPnzIUxfSgmBqjAozliq5goKU+3BS3AAtzQL7dW14CURQCjbQx8IO4vsRh0VlaxeAlGBt04YlBaFgTMiKsqJdoE0d5EOGCSiooKtcbRhsHVVHAmDdW4huLpMuYy+NdQdkuzF4MY56oZBfx88MDYIDuu+RyDuOarHRW/ZR2oFwqpFCbjnSB0drXYORdXCBFydl4Lri+NQ4xKiCYQquu67ATdDN6FyYZJRoPDy3BQcnaweHS37M+ES7vrDTpRPLMWRyVuw70+azqE2lb2xG5c8i3F5dhrOexgIhLvOsQ5EbEku70Nvr5z189ANYupR1J4eOfr7te1c7EdPj/rORWNFUY0FhE5OLggPj0JzMw/Xr9+Dre18bN5covG4a9fu4NVXX8OxY5+jvV2E8vLjeO2113D3bj14PBkuX67CK6+8grY26v2IdF9nrMpa5ikrEI6DYvtitUSxAYTE4BgiijkwMIjBwUHWIVBxXv39AyQMantc07ka/PReJn54O1snDH43Iw8/z03CvZXhIxw4alew3iMQd1dG4Or8JLVew4tzMsg+y9GId78Z97O3otopUi8QCtr45OdJpV349P2jtIFQKJRCfGqX/khowTyIM5dQREIpYHBEv6DCFeRl+KLjKrFzrb21A7zEFRCl2UO4xR+yfQHo/ni5foeweDZ6K+wNjopKcxdDtC1C91TRnBXg50VowCAn2gld6+eCG+dICYPcWGfINjuhLSaANhA25eSSMHg/PFkJg2FukOQsBjfeQacrSPQJjnZZ8CV1AAAgAElEQVRojHaNdAdrnUN0wqCin7DOTTlgpsaF+IWJKuzdtItBrR4gVKjKdQ1uRRSj0m70fYZn385RA8LDE0vxyX9/jGM2RTg8qQSHJxehYmIJSn9LDwj3vb4Plz2KcHl2Gn5y2mUYEO78iXXoYUuKXj62z8NQETsXxRCLpWQUVS7vw+Ag1aCbAfT29pFRVJFICiZRVGMAYVXVXdjY2ODevQbyWHn5Mcyc+b7GY1evXgs3Nw+1Yx4e3lizZj14PBn27DkIO7tlo36dsSprmaesQDgOiu2L1RIlEJgXupSDY4goZk+PHENDQ6zDoOpAG0WER9tj2240EUD4jnYgPDMjB7ftIylcuVDcdx/hmLgH4bZ9FK7MTdFYR3FxVjqqArcb9WsVcIV4uP0Iqt3jtQIht76FfLxc3ocB+QAqppTRAkJeuwii78u1uIEfoXOtLTkllJ6UMEi6golO4FTsQEc7T+0Gh5e4EqI0e7THe4EX7wRevBO46Z4QbAqHaFcMJPsi0bnXB93bF6u7hBXBRFR0i6thQFgayXCq6PAwmbSl4MVTw2BHpCuk+QvQvjqRNgy2xQaizjuCBMKGjLV44BWAtnACBnkJ2mGw0c/HpCDY4ElMy725LFp9mIzjyGEy1Lq+JBY1zsG4vjieEvJuLotBrSs9ICTBcEUO7sRsRZVD5qiio5+/ukEFCktw/G8EBH76chEOTy7CUZstKHpuPy0g3Pn3A7jsvgWXZ6fh+6U7DALCWx9bLhD29/eju7uH9fMwlXg8EYRCiUoUVU7+IlO1BgcH0dfXrxZFFQjEaGhoQvvwz00uVzrqe4jjxz/HtGnT1Y5dulQFGxsbNDS0qR338wtEenq22rH09Gz4+QWAx5MhMTEVtrbzYWe3DDNmzICDgxPOnDnH+HXGqqxlnrIC4Tgoti9WS5Q5gbC3t49ssFcMjlHsG2QTBkcOtFEMutH2eE4DBz+9l4Uf36UCwjX42TZRMx46vGBe1RWscw3GTbsYXJ6dqg6BszNw3W8rWo5cRG+XXOe5jFYtX/yImsAMjfPl3G1Qc0wBgN8swsGX9uqFwvYGHkQX/oXekmE3sPhDdK2fC3HmEgYQSEREVYfHiDOWgp+0EryCGHTcv0/9G+9EJ4jS7NEa6gZuiicJhZTK8YWwOBKi3bGQ7o+A6ECkQTAoLvSAOEvHVNHNoeiI0YyKcqJdwNUKg24QptmDV5xEHwZDPdCSl6MWF30Qk4K2CFcCBhNXanUFDV4uz1A1LiG456juDl5fojlMRptu2MXi6rxkSri7bR+FWtdgRkCoUOXiDFTHbcctrzUGQeGlOak4MqmYhMFPXybcwU9fLkLFxCIcmVyELf+PHhCWTirDZffNuDw7Dd/NLTEMCHf8yDq4sKWBgQF0dY1fINQlLlcIgUCsEkUlBt0ooqifffYZbGxs8MYbb8DOzg6BgcHIylqNnTv34quvTuPGjWrGPXkHDlTgvfdmqh27fv0ebGxscOfOfbXjLi7uyM8vUDuWl7cOLi7u4PEIOIyJicfdu/VoaeFh8+ZSTJnyD9y4Uc3odcaqrGWesgLhOCi2L1ZLlDmAUCLpJAeijBwco+gjZAMEtZ1XX98A+voGtH6egC/Bj+9m4cd3s9Qnib6foREPrRmepliv4goSAzSI/kBlLDQT1wK2oeVEJR49ekQ6lH19/ejv134uxhKnqga1CRtQ7UicP+9GHemYdnX1AgCk0i603GrH/hd36wTC1rsdEFV+i84NcyDOWjxiVQR9GFQMjxFn2hFwlOqGjjNf6r4hSnIhgDDEA+2pwbqBcKQ2RxgEhMKPtQ+TEeesBCc7lBIGO6JctMIgJ9YZkiIPtEX40AfCME/URyh3D96PSEV7pDMkOYvBT1qB5kAvzXior6/JXUGlAnBtUdyIYTJ04qIjoHBJLLXbtygGdW6GAaHqAJrb4cW4HbiRMRSeeSuXhMFjNsR/P325CIcnFuHwxGIUP7cfW2nERjf96RCuuBbi8uw0fPtOoWFAuN1ygXBwcBCdnd2sn8dYE4cjQFsbB8eOfYbi4hKkpKTA1dUdH3zwEV5++WXY2NjAxsYGr7zyCr788hTte4ijR09g+nRq5+7Bg3a1476+/sjIyFE7RjiEgVqff968+di2bSej1xmrspZ5ygqE46DYvlgtUaYGQgXwqe7MU1VnZw8AmB0GlbsFNc+LDoT9+F42CYRn3lqNW8uitbqCihview5hqFyQqATBeVmoCt2Jh19VQiLppJxqKpf3Y2DA9ECoEL+5Aw837EFvcwfpmEoknQAAmYzYDdlwrhF7//cTrUDYWNkK0a1zDGOh1MNjxBl24Kc4gPtxHjpaO/Tf9CS7QZRmj5YQDzSH6HEIR4hbFMt8mEzeMojzXbVHRYupo6Idka5aYbAj0g2S/MVoy4hh5A625qSpuYPtqX6Q5i4GP1kTBhv9fYw/PVSfvAJw0149Lnpnhe5hMtr6CasWJaiB3M9zk3FpVirq3INGB4QaA2g20x5AU7kgEV+8vgGfvlxEgiHhEBaj4q8lKHl+P63Y6MY/VuCKy0ZcmpdhEAx+/c8C3Nz2A+sAwpaGhoYgk3Wxfh5jXRyOgLwPaG8XoarqLr788hR2796P2tpG2vcQ167dgY2NDWpqHpLHysuPabh5PJ4Mublr4OHhrXbMw8MbeXnryI+fP/+z2sc/+mgWdu/ez+h1xqqsZZ6yAuE4KLYvVksUn28asBCLqXf4jZRM1g0AZt09KJcrzos6iimX9+kcKiMSyfDjzBz89F46ri1IoJ7eObxgvt4jEPccwvHzvGQCAufn4Eb0HjSfuUU+lyI2SzXVlBhVbp6hO8T3bAAA0NsrJ4+PBEKRSIZ7/6rF3j9SA2HD+UYIa65BmGbHHAZV+gWFafbg5QSg40Yl/ZucFE8CCIM90RzoDU56AH0gLE5g3ju4I1r7ionNYeiIoYbBdh0wKEyzB3dzKiMYbAv1wMO0TCUMRjtDmrsYgpTlajBojqEx2nR7RSTuqi2jD0HVojgDgDAB1xfHodI2kYS3S7PScP6DdKMCodoAmsgiXFuqfwDNpdlpOGazmYTBT18uQsWkIhx6sRQlz++nFRst/FMFrjhvwOWl+YYD4VbLBUJianUn6+cx1qUKhKPVypWOCAkJR2NjB27cqIat7XxyUIyqrl69hVdffQ3l5cfJKaOvvvoaKitvg8cjHEQHBydUVz9Aa6sA69ZtxIwZb6K+voXR64xVWcs8ZQXCcVBsX6yWKFMA4cjBMboeK5USQCiRmH7thFTaRbpwXV3az4vYQagbwq7YpuCeA9UOv1DUuQWh3iMQ1Y5huDwvGZcWrsbNxANovVhLAWAEnPb2UkMznXMx5ntDfM+6R5wnAYQjj1/fdYMSCOu+a4DoQQ0EqbrXSGgojYBBcYYd+GnO4Hy6l/lNTqoPRGn2aA4igLAtgQEQlqQyj4sWhWqPimaFUMCgi04Y5MQ4Q1QcgLYwT2ZAmBKJOvcQ1LkFoyPWiYDBVHUYbPQzZzxU0x28Mi9JzR2sdtS+e5B+P2ESrs5LweVZqfjx3SzcNwEQKnRteTYuz1uFn+cl64TC02/maQDhwT8TQEgnNrr5z4fxs9N6XHE2LC769T8LcLP0e9aBgy0R/57IWD+PsS5jAmFNzUMEBoZg+vTpmDHjTWRk5KCjg1h6P2XKFBw8eJh87BdffIuFCxdjypR/wNZ2Pk6cOEl+rL6+BdHRcXjzzbcwZcoUODu74uLFa7Re53GQtcxTViAcB8X2xWqJMjYQ9vTINQbH6AMRACbfQ6jLhaP6GgYHdU8+vbU8VmN6aK1zCO67B6HGKQTXlqXhdno52q8/oAFg2uGUzrmY+r0Ri4l/yKjO81LeZewZAYQ1X9ZB1NYCfjI9IBSk2EO4ahnpCvK3JIH7sNGwm5xV/gQQDoNQU5AXuAkutICQU5LObJjMFj+t7iCvOIkSBnXFRImoqB3aksMZu4NNubmocwsGJ85xGAZV3gN/8w2N0aZatyDcsItVcwdv2MWMCggV/YSXZ6Wi0jYZP7ydw3jKqCG6MicF5z9Ix+W51I7h1fmJ+Py1jSQQHn1pMw78eStKnt9PQOHz+3QCYdGLR1DpvB5VvtsMB8KSs6wDB1sCALHYCoT6xOFQ7/qzynSylnnKCoTjoNi+WC1VxoAK9QEtckafB6jHEY0pYuehIgapPbqqDkj6V2HccEglo6KKvYI1zqG467MKbZfuGBVOTbmWQ59DqRAAra7q2cizakB491g1RAIxeEn2EKTQGx4jzrCDIMcbgkvfQySSGb54OTNIDQibA73RkRFCEwgzGcZF46ijolvC0WEADArTloOzgXlUtC3KD3X+EeDGOxCuZZo9moO8WBgao11XbRNxTyUuSgxWGh0MKvoJL89OQaVtMs6+lYt7TmG4PNu0QKjsW0zBhQ/TcWlWmgYUXvhoFT59eQsBhX/bhAP/qwRCfbHRLS8expUVa3DFx7CVE1//swC3SizTIeRwBAAAkUjK+rmMdVmB0PyylnnKCoTjoNi+WC1Vo11Or2tAi35g0+4+jVaquwWZACedVRg3nFeh2pGAwWqnUFS7xaD1X6f1fq3M4dQ0U1hV47N03ntAOxCKRDKcdPqKBMJbZQQQ6wNCYniMHYTpK8A/sAkCgRgikQwCgQQ8nhBcrgAcjkLETUx7O4/coUWp7FAIU+3VBqi0RvrQAsKOkmz6w2TWrIA411EzKprrAE5mMKOYqCIqKihi7gy2hXqgOTcDvMSVBAyuWobmIC9ip6AX+yDY4BmIeo8AXJmTor57MHKNUYDw2sIEVNomodI2GWdm5OHOykicfz/dLECoqosfrcKFj1bh6nwlFJ6akT88YGYTyv6yTekQ6omNFk08jCvL83HJdycOv7TRICBs2HOZXFwul6suLpeAyeLyx01crhAAIBRKWD+XsS4rEJpf1jJPWYFwHBTbF6ulylAgVB8cY/iuPEA3bBgiptFVVXV16Z98etM1E9WO4ah2DMf9pPXg1zXpATDVvkr6cGqKtRyK56TjUCpEtTJEVUKhFJ/NOY69/7ML1z+5MQyEKyBIXqEFCJdBnL4UgvURENTVkM8jEEjA54vA5wuH/0uIxxOCxxOAy1WKChY7ciMgTFEHwuZAL3BTvWkAYQ59d/DjWFpRUTow2BHpBnH+crTFBTGGwdYQd/BTh53B9GVoCvTEA28/1iFQVXdWROCGXYwSCP3iUWWXaBwgXJCISttkVNom4/S0PNy0j8YPb2ebHQgVUgy3uWqbhKvzk3Di1UIct9mEiomlKHl+H63YaNGkI7iybDUOTtuHLb/72CAgvF38vc7F5cQv8AYhl/eRi8tFIin4fBE4HAHrsGKoeDwRAEAgELN+LmNdHA6zfYNWjV7WMk9ZgXAcFNsXq6XKECBkMjhmtLDBRKrR1Z4e+tFVVdFZhXHLIxv3HCPRVPYlhEKpzsd2d5sWTplIMWGVrkPJ5Hsk4EtweHo5KrdeGwbCleAnUQHhMgiznCD45pgaUAoEYjUIpCsCFocdxTUxECQv11i+3p6mPzbaXpxLHwgL/SmiohFqUVG6MChIXY72/GTGMNgS7AFOkgME6UvAT16GJn/vMREPVXMHPQNwcU4Gqj3jlUCYvMHo7uClWSk4NXUNrtvF4rvpeawBoUKXZ6fi/AcZ+HFmJo5OJoBw5+930YqNFk8+gkuLcrD+3w9i7b/vMQgIb2z+jhICNBeXE7CoWFyuqMHBIfT19aOnpxednd0Qi2UQCMTgcsc2LPL5BBDy+ePXBbUC4eMra5mnrEA4Dorti9VSxRQqRuO+UWloaMhgeBsJckNDhkVXVUVnFUZN/gFwbt7X+TxicSf5m/nRwqlYPLr3RiLpwuDgIO2IqKHfI16rCI0/t0AkkoGbog6EghR7CNPsIdieAUE7RwmSAgkEAhF4POYwOFId6xIhSF6hAYTNIfodwvaS1fSGyZQEU0RFHcHJDGIMg5wYZ/A2M9s32BLsgUY/Xzz09QM31hHcOAe0Rbii3oN9AByp+7FZuOpdrBYXveWdbVR38MqcFJx9Mxunpq7FtUUJODV1LS7PTmUdCq/OS8EP72Rj939vR9lftuKQSmy0SEdstMTmCHb/dSsKnz2IzGcOGASE1wtPGwAIAggEYojFMshkXejp6UVfXz8GB9VhcWhoCP39A+jtlaOzsxsSiQxCocTwvl8jSiAQD99LsH8uY11WIDS/rGWesgLhOCi2L1ZLFV2H0BjuG5UGB4fU9t4ZIrm8DwDQ19c/anhSACHdOKW25zCkf1HbuYwGvBU9nkwiooYCoar46U6EGzgMg4JUe/Cv/Kj2GAUMjoyIGgyEG1LAT6IAwkBvcDOD9DiE9IBQuC1GMypalMQYBjsi3SDKd0JblB9jEGz0I8SNcwAvwQH8RAc0BXqxDoAjdTOkELejNpMwWBeTY3R38Mf3MnFq6hqcmroWP9sm49S0NTj3fgarIHju/Qx8/spGHPwzAYE7f78LRyaV4uP//ISEwhItsdGiyRVY/5sDKHz2IJKfKjMMCDcyB0Ld8EC4byKRFFJpF7q7e8h9rSOjqAMDA+jtVfYtCoVET7A5IEcolADAmIDTsS4u9/FZ1zBeZC3zlBUIx0GxfbFaqugA4WgGx+jTwMAg4wijQqrOV1eXcWKno12FYUwHdbRwqoiIyuWGvb8KGQLtgmwXyNbMhzBtKfhJ9hCc/Zz8GBERlRgFAlXF2ZwBfuJKSiBsS9ANhJyS1RDnr9Q9TKbAGeLs5ZBkLoUofSk4MY5oj/dSh8EIejDIT1mO9ux4g0CQBMJ4Agb5iQQYPvDxZR0CSYXG4vycXFR7KNdNVMetN5I7mIBK22Rc+CAdZ2bk4tTUtTg1dS0uzU7D6en5+P7tHFZA8OJHq/DllAIcnVyCioklKHl+L0qe34/SF/ah4q+lKPvzNr2x0XUvHELhswdR+OxBxE84hBOvbmAOhBtOmRUueDwhhEKJSt9iHwYGdPUt9gz/fFX0LRrnPEQiKQA81n2QViAcv7KWecoKhOOg2L5YLVX6gNAYg2N0qb9/wKDnVgxHGRwcNOpie0NXYRgjIjpSCjhl+vWpg/LoB/YMDjKHdsFqV3RvmAdBqh2EG6NGwKAYxoiIagBhcS74CdRA2BTkBW6iq3YgLM6FqMBLd1x0ZzyEqfboiHRBa4g72sLc0Rbuho4oF3REuaA9wpUWDHJinMEt1A2DukBQIZ4KEPITHcCJdUKDJ7s7BxWqTd6ASr8SZVzUOxZVy5KNAoSV85OIqOjbOaQ7eGrqWpz7IAPfzcjD6en5ZgXBS7PS8M0ba3F0chEJg9t/t1vFDVS6hNt/t4eMjW773Yi46At7seE3B0kgjJ1Qjr0vFjMGwqr15gVC3eBBwKKib1Ex5EZX36JM1kX2LTKBO8XUara/5sdBViA0v6xlnrIC4Tgoti9WS5U2IGS6msBQ9fUNoK9vgAF40d+fZ4jEYuZAaKyIqDYgZOJWdnb2GB2UBwYGGbuMgrXu6CqwhTB1JYRNjcQxgWR4eIxxIqIaQLh9HXgJDpRA2BzoDU5mmPYpo8V5EBYGUzuDOYvBS1qBtnBPtIYQ0z1bQ93RHk6oI3LYIRwGw45I3WAoyHNDW7iXwSCodAgdwY1zJGOj/ERFPyH7w2WuOhfgTmShMi6abCR3cGECrs5Lwg9vZ6u5g6emrsUP72bjzJuriT7CWabvI7wyJxWnp+fj2EtbcHRyCY5OLsGRSSXY9V+71GBQERE9MqkUB/53u9bY6Np/U8KgAgi3/CfzSaNVBd+yDhz0oETZt0gMudHdt9jTo+xbJIbcqEdDJZJOPHr0iPWv63EQlyth/d7D0mQt85QVCMdBsX2xWqoEAs2beUXscTR9Z3Qll/ejv58eEKqvbzANpDLdjdjTIwcAow3ZURVTt1LRS2lsN5cAQmbPKdzgCWnuIghP7CVhkGqlhFGBcFchePHagbA1yk87EG7JhWBzlLojmLUYnBgntIa6q616aFOBwbYwN7SFu6qvmyChUBMM+ckr0JYWNSoQVPYQOqI9yhlNAV5qbmFzkCe7QBiXgfOzV6PGPYoEwtsBq43kDibi/PsZOPtmrpo7eGrqWpx5czXOvk1A4rmZmSYDwZ/npuDsW7k4brOZBEGF9v9pOwUMEtr3x+04PLEU2367RyM2WvT8XmxUcQc3/OYgYidUIM+ASaNV6x4PINQlDkdA9i3KZF3o7u6FXN5HJh8UpYjn9/bKIZf3YWhoyKx9i4+rrEBoflnLPGUFwnFQbF+slipVIDTV4Bh9EDMwMEgLvIw53VSXAP27EcXiTrJPprvbNO8VXbdS9ftmrF5KVfX3D6CvjyFkbvSCaEOgSSOiGkC4rwTcOO1A2BzoBe4qXy1AmAPelgRIcxdDkLYM7RGuaA3R3Pun6gy2hbuhKcADTUFeRFw0ykULGKpERQsSKfYJejACQRIIYx3RFumCBs9APPT1BTfOkewnfOjLXj/h3bhCXAssVbqDkZlGcwcvz0nBmRmrceZNdXeQ0Bp8/3YOTk1di+/fMk0f4Y/vZuOzlzdpgODRySX47O09KHl+j1YgLH1hL45MKsX+P+0gYqMqQDjSHVw/DISrfnWQORCu/YZ14DC1eDwRRCJl36ICBjWH3Ji2b/FxFZcrZf3ew9JkLfOUFQjHQbF9sVqqFECojBoOQSo1XuxRn3p75RgcHNIJRcbuzdMnfXv3Oju7MTT0CENDxh+yo/6163cr1b9vpjkXQ4BQuC0Ggnu3jbZSghYQHtoBbqwuIPRGexp1bLRjcxY60kLRpuIGaoXBCALimgM90RofiqbosOHHEY5hR6QLCYeqMVLBai+0hXpqPHdzoCce+DAHQk6ME1rDXUkQe+DtB06sE/iJDuDGOaLBi4V+Qr8wXLRdjTuR60kgrEkwzu7Bq7aJwzC4WsMdVOjsW0Rk9PS0fPw813ggWOWzCd98tJUSBI9OLsG/pu9E2YyjWmGw5Pn9KH5uPw69WIrDE0tR+gIxcKbkhb3Y/Nw+NXew8NmDKPg3AggTf3GIMRBeWzP+gZBKnZ3dGBgYhGLIjUTSOaJv8ZHaPcfg4CD6+vrR3a3oW5SCz2fWt/i4ygqE5pe1zFNWIBwHxfbFaqkSClWnUZpmcIwu9fTIMTREDYSq4GXM3jx9GhrS7vr19ipWXAyMesUFHQHa3UrluZj2+9bXRz/WqxC/rtqoKyXoiHt0LzgxjjqBUNtOwvb0CHowGO2FRn9vNAV4oy0xEB3XbqApNoric92IgTMkHDqjLd6f8jUafX3Q4OXPGAg7op3QEuquDmRe/uiIdgY/0QHtkS5m7ye8n7IGF2zzUeMaQQChZxSur0g1ijt4bmYmEQuldAcJnZ6er5w6Oitt1CB4zW0dfnDcrRUEj04uwdGXSvC5/b90wqBCO/7jExyZVIp9f9xBxkZHuoOFzx7EumEgjJ1QjpP/YAiE+V+zDhxsqKurB/39A3pAiLpvceSQG6JvsV9v3+LjKisQml/WMk9ZgXAcFNsXq6VKKu0x2jRKQ9TdTUwL1QU75gAvdSDU3LunGsvU5R4aW1QxUHOfCxMgVEREzQWBag7hv8rBiXbSDYSB3uBmhWgCYW7icH+gJgwSzp87WkM90ejni0Z/H7TF+YP7sBHcmvtoSozXCpMKOGyP9Sb7Ckc+lpgM6s84NtoR5YzmYA8NKKv39Ed7pAv4iQ5oofi4KXUjcCOqgreqDJMpMIo7eHlOCk5Nzcd30/Nwamq+ViBU1Wj6CK85rMYFr09w9G86QHBYXzseR8kL+2gBYfFz+3F4YikqJpai5Pm9KPi3AxowWPjsQaz9tQIIK3D4b5uYAWHeSdaBgw11dxNwZ+jnK/oWxWJl3yIx5GZQ7V5FtW+xq6sbEol59y2OVhyOwAqELMha5ikrEI6DYvtitVTx+TKT9+TpUldXDwCowE4XK+ClqpFrFjo7ezA0ZNpYpi4gVH0fFK6pOc9FLu/HwIB+ICRg0HwRUQ0gPPkpOqL0AyHVTsL29dkaQKiAwdZQDzQFeBEw6OeL1hg/cGtrCFfyQTOaUlLQSmO5vCJW2h7uRgyjGQbD++6BaPAMwEOGsdH2SGc0BlAvpK/3CEBbuBvRT+jnYx4gDI/HufczcTd8HQmEd4LzR+8OLknCmRl5OPtmrk53UDM+mssYBCvtMnHZfxc+faVULwgenVyCL+fsx86Jh2jBoEK7/7ATRyaVYvcfPsY6Cnew8NmDWKMChDv+uJUREFautkwg7OkhBs+Y6vmJvkWpWt+i4t8qRan2LXZ19UAq7YSib5Ht90cVCNm+77BEWcs8ZQXCcVBsX6yWKj6fHRBUhS0AEIsJOFSsTDA3eKlKdc2CuWKZ2qTqVrLlmtIZ/EOslDBvRFQjMvrdScI10wOETYFe4Ca5qQPhxly0BI2MiXqgJcgLTf7eShiM9AH3RpXyNds4aMnMQgtFbyDV8JjWEA+0BHuiOdALD3290RrigTrXIDR4BuCBN7PYaFuECx74aoe9eo8AtIS6E/2E3n4mB8La5I24sHAtalzCCXcwbJVR3MGLK7fg1LR8nJ6WT9sdZNxHuHAVrgbuwIlp22mB4NHJJfj09e04/P4xRjBIiBguU/zbTyhhsPDZg8j/dRkJhBte+IQZEOZ+xTp0sKHeXjl6e00HhLphUdm32NWl7FtUhUVAW9+iyKx9i1YgZEfWMk9ZgXAcFNsXqyWLTSCUyboBgNwtyHTfnSmkGKJiysmdTIGQTde0t5cY9071McIVlLACgBpAeO4M2iNd9AJhc6A3OrIiKIBQZc9gsAeaA7zRHOCDJn8fNPr5oSXMB9wLP5GvJxCIIZf3oS1vDVqCPUdEQd0J+Av3R5O/Nx54+6HeIwD1HkFKeQag0d8HtS4hBBB6MYuNtoW5osFLP+g1B3miI8rE/YReQa7JEgQAACAASURBVLiyci2uhyqni9Ykjn6YzDWv9YTbx9AdpN1HaJuCa4FbcfKDHbRBUKGvVn5mAAwSsdEDf9qG9b+hhsHCZw8i7xkCCOOeLEP2v+1jBoTZlgmEcnkfenvlrJ/HSCn6FiUSRd+iXGvfYl9fP3p6etHZ2Q2xWNG3aFxY5HCERrlvqK1thJ9fAN544w1Mnz4daWmZaG8XUT72xImTmD9/AV5//XXMnTsPn332FfmxlhY+0tIy8e677+Gf//wnli61xzffnCU//v33F/G3v/0NU6ZMIeXg4MT6fRNTWcs8ZQXCcVBsX6yWLG3L6c0hhUP46JHpdgsylQK+2IiIjtTgIDFK3dQTTfUDoebgH3OulKAFhD9fRHsEPSBsjfQfAYQ5aAnyQkuQB5oDvUbAoC+ag33AOfUV+VoikRSDg4MYGhpC87pNaAnzRXOAJx76+mqCnzZ5BqDOLRg1TqHDQMgsNtoS4jrcf6gf2JoCvNES4m4aGPQMRENiNs7NzMK98HwCCN0jcMNpdA7htaUp+N52C76bTkwVJRxCZkD403va+wirfDfj9MJdjEHw6OQSfG1/GKX/wRwGFSr8931aYbDw2YNYPQyESU8dQMovyxgC4ZesQxAbUsAU2+fBDM4E4PPFevsWh4aUfYvEkBvD+xaNBYROTi4ID49CczMP16/fg63tfGzeXKLxuGvX7uDVV1/DsWOfo71dhPLy43jttddw9249eDwZ0tIyYWe3DLdv16GjQ4xdu/bh9ddfx61bdeDxZNi2bSecnFxYv08araxlnrIC4Tgoti9WSxZbQNjdLScjNTLZ2IBBxXJ3bZNPzSnF7sXBwSFW+zypJsESEVExqxFRDSC8UYW2CFdaQNgc6AVuuhIK2zfkoCXQC80BXmgO8FGDwaZAH3R8VkG+jkzWRQ6WEArFaCosxsMgYphLvUcgPRgcBsJ7DuGoVgFCJrHRpgBmgPfQzwcP/bxNAoR3Yzbhkl0BapzDUOscivtJ60Y/SMZvF7FwfsZqnH1zNWMY1NZHWOVegB8c9EwO1aHP39uN3f9XbjAMFj+3H4XPUg+TUSj3VwQQrnpmL+InlDMCwquZX7AOOmyov38A3d09rJ+HMaX45ZNU2oXubiZ9ixLweNR9i8YAwqqqu7CxscG9ew3ksfLyY5g5832Nx65evRZubh5qxzw8vLFmzXrweDLExyfhxImv1T4+deo0HD16AjyeDJGRMcjMzGX9Pmm0spZ5ygqE46DYvlgtWeYGQsVuQQBkX5w510pQSSLpwuDgIHmjr69nzhzvjwIG2VgHogsIlRHRsQODfL4I3NpatIW70QRCb7SvCieBsG199rAz6EOKgEE/dBzcSb5GT0/v8P+3cvJY8+ZSNMXF4r5HIBq8/BkCYRiqHcOUQMggNvrQh3qgjE55+9F2FWkrIALn5+bgRrhyuui98LWjcwd9NuHUtHXkzsHT0/MMAsJT09bgyhzl5NDznp/gqI1hIHh0cgmOvVyK47afGgyDilUTumCw8NmDyB4GwqxnP0HshHJ88ZoVCPVpYGAAXV3drJ+HuaTet9hD2beo6MnfsmULkpKSUVRUjCNHjuP8+Z/x8GG7wfcMx49/jmnTpqsdu3SpCjY2NmhoaFM77ucXiPT0bLVj6enZ8PMLoHzur78+g5dffhk3blSDx5Nh3jxbODu7Ytas2XjzzbcQHByGO3fus37fxFTWMk9ZgXAcFNsXqyXLnHAhk3VjaGhIbbcgoHv5uqmlOsxGIunS2TNn7vfHkKXwxpZiNchYi4iOFK+5Ba1hdB1CbzQHK3cSthVkE8dUo6IBfmjfvgl8PtEv2N/fPxxt7lZ73eai7WjOz0OdeyBqnELQ4E3TJfQMRLVj6AggpB8bbfD0NQjg6lyN20tYn7qOiIuG5hLDZEJSULU43nAgtE/DDwuKcWoasVfQUHeQ7CO0zcJl/104/nfti+Xp6qTj6GCQjjtY+OxBZD1NAOHq53YhdkIF9k8spg+E6Z+zDitsaHBwEJ2dlgOEusTlCtX6FjduLMSyZcswdepU2NjYkJoxYwbs7VcgPDwKe/eW0b5nOHCgAu+9N1Pt2PXr92BjY6MBay4u7sjPL1A7lpe3Di4u7hrPe/bsBUybNh0FBYXg8WTo6BDDxcUdhYVFePCgHXV1zQgJCcOCBYvQ0SFm/d6JiaxlnrIC4Tgoti9WS5a5HEKFG9jfP6AWgQTA2uAWuVxzmE1Pj5yyZ87UUkREVd+fvr4B9PUxWwpvKiAUicYuDPL5IvA4fLSEMgDCQG9wc8IIIFyXNQyD3mRUtG3DavD5xF6ywUEC0hVTAdWAsPRjtO7dizq3INQ4hTGIjQai2ikUNU7qQEg3NmqI01fvEYgap2DUexgPCK/7b8TlFRtVdg9uHF1U1PcTIio6DIJED6HhQHhqxrpRg+DRySU4ufAQtv33AU3H79/pA+Hmf9cPg4XPHkTm04cQO6ECa1/YgdgJFSj+/Q76QLjKMoGQ+CVaF+vnMZbV3s5Dbe1D/PDDRZSVHUFBQSGiomKxcqUjgoPDaN8zHD16AtOnUzuEDx6oO4++vv7IyMhRO0Y4hIFqxz75ZD+mTJmCoqKtOl+7trYJNjY2uHy5ivV7JyaylnnKCoTjoNi+WC1ZpgZCfYvU2ZieKZUqI6JdXeruJFXPnCmlGhFVrJhQiMlSeFNJJusir1OiX2UAcnkfOTpdIpFBKGRnGf1ItQS7MwLCtoRgAgjXZAxHRYkVE62r08HjCTX6Bales3n7LnScO4da12DUOIWRQ2LoAGENFRDSio36GgSEda7BqHEKQZ1riFFg8EFUEs7NzMLNyOHpoq7huOGaYTgQ+hcRKyPeKcCpaWtIKByNTk/LHzUMfjZ1Jw68cYQS8rKePoCNzxrPHSx89iAyhoFww++3InZCBdb8vz20gfDntBOsgwcbevToEaTSTtbPY6yLyx29s3bt2h3Y2NigpuYheay8/JiGa8jjyZCbuwYeHt5qxzw8vJGXtw48HuECxscnYcaMGfjqq9Nqj7t9uw7p6VlobOSQx+7cuQ8bGxtcv36P9XsnJrKWecoKhOOg2L5YLVmmBEJlHFP7lEzVXXvmUFdXL9mIL5FoDmtROmLmgC3NCK2qiKXw7MRXVVdKKHpViLHpykl4msMN1GFRLDYvLDYzBMKmQC9wk93Rlp9OAGGoH1ozk8Dl8Cj7BSkh9OO94LZzUeseOgyEYahzCaLhFBIRU00gDDAJEJIA6hyCeysjjAKEtcmFODczC9XBWcQwmQTDF9Ffs1+Fs3O3EO7g2/nkQJnRAuGpqWtwdHKR4UD4Ugn+Zad9xUTm0weQ+tQhbP5/xnEHC589iPRfEkC4+Q+liJ1QgfRfHaAPhKmWCYQAIJHIWD+PsS5jACGPJ8PKlY4ICQlHY2MHbtyohq3tfHJQjKquXr2FV199DeXlx8kpo6+++hoqK2+Dx5MhNTUd7703E7du1Wp8bksLD2+//TZSUzPQ0sJHXV0zfH39KeOmY13WMk9ZgXAcFNsXqyXLVECojGPq7oEbHBxEb6959g8q9h3qer2uLgIETH0uiimrIyO0qurt1b8U3nQwSC8iKhJJIJV2qu3Y0g2LPSQsEpNKjQeETUFejICwOdAbHdmRaMtLQ0tiHFpL1oPb2qbSL9il35XcvZ947U2lJBAqIE+fS6gNCPXHRn1RzxAIiRUXYahxDsatpdGjB0KvIFyxX4MrjpuUw2SiCgwGwkueHxOTQedswampa4wEg4Q+f2WDVuCr+Gux7hUTDrqXz6/61QGseaYM8U+WYYsWKCx6Tv8gGVWtGgbC4j8WI3ZCBRJ/cYg+EKb8i3XoMLc4HAIIxWIp6+cy1mUsIKypeYjAwBBMnz4dM2a8iYyMHCj6+qZMmYKDBw+Tj/3ii2+xcOFiTJnyD9jazseJEyfB48lQV9eMl19+GX//+9/V9gyqfv7Fi9fg6uqON96YijfemIqIiCjU17ewft/EVNYyT1mBcBwU2xerJUsgMC5MEHHMIco4JpUUI7NNCTiq56RvgI1iN6KpzkUsJnoDAeh1RtkYcGPMlRIKWOzqMg8stlVUoLVwI5oz09EcH43m8CA0BfmiKUD3TsK2vFXgXK3U2y9ICYR7y8g/P0jKUoHCENR76nYJqSOjRGzUmECoGk+tcQ7BjSWxowfCpFycm5mFW1FEXLQuMBFVSwx0BwNLSHg7885aI7qDhL55Y61W4Ct/UTsQfjl7Pz7+S5lOIEx9+gAKfl2GVU8dQsIvDqHoOc2o6CYG7mDhsweR9hQBhNv+vAWxEyoQO6EcJ/9BDwivJFseEHK5guGf2VYg1P9eSVi/57BEWcs8ZQXCcVBsX6yWLGMCoSJuqS2OSSVTT9Jkek6dnd0AYJLdfwowHRp6RGvVhrkH3JhzpQQ1LA6p/VwYGqKCRSljWOS2c8Gpuo72r75C2549aN24Hs0Zq9AcF43msEC0H6ug1S9IpdYDFWqvUx8UR0KhviX1NS5BWoBQX2yUGRDeHx54owDVG0ticd89aFRAeCdqExEXDVhFAGGKgcNkVmbizEebcGrqWvy4fDsxSGZGHk5NXWM0INTVR1j+V+rjx1/bjop3dbuDxc/tQ9IwEK57pgzRE8qR9NQhFKtAYRGNNRMjlToMhDv/umkYCCtw7P8K6QFh0mesQ4e5xeMJAQBCoYT1cxnrsgIhO7KWecoKhOOg2L5YLVnGAEKxuJN0vZjGP001OIVw4vRHREdKJiOAkC7Q0pUqmNKFTXMNuBlrKyXMCYt8vnK/YE+P7n5BSiA8dEQdPusfos4znNaAmTq3II21E/Rio/SBsN4jEDXOoWpAeHNZFKqdwgwHwqBInJ+Vg5/dthBxUZcw3PLMNggIL3oQC+hPTV+L794pGJ4wmms0GNTXR6gNCL9c+S8ag2L2If6XB7D2mTIU/LoM2U+XIfyJCqT+sgzFzw27gzQHyagq5RcEEO6ZvJEEwp1/2koPCBMtEQhFAACBQMz6uYx1WYGQHVnLPGUFwnFQbF+slqzRAqG+wSj6ZIrBKapOHNMdh1IpMVVT2xAcpjIUTFUh0pQwSEREzeMKGhsWe3tHB4vEfkFiwqtMpr9fkBIIDx/XONZxpRK1LgSE1blqHzBT5xqEew5haPCgAEKdsVH6QKjuDg4D4dIo3LaPMhgI76eux7mZWbgdVUwMk4lbbWBUdBsJbec99hDu4HTjuoMKffEqdR9hxUSKvkH7Iyj9HY3Joc/vQ8xTB5D7KwIIC35dhvgnyxH+RAXSny6jtYSeSsm/KCf2D/5tAwmEG3+7ixYQXk74lHXoMLf4fDEAENfeGDifsSwuV8r6PYclylrmKSsQjoNi+2K1ZPH5hsME1e48pjL24BRDYquqkkgUQMgcbqng0lAwFYmUE1FNCYMExDweMMgUFvv7qWFREVMeGnpE7i8zdMBN67ETlMfbTpxU6xHUBoTVjuHUDqHO2Kgv6j30A6GmO0i4ltcWxuH64jiDgbDKawPOvZ+Far9k1DqHojpuA3MgdMrBmfcLCQh8fyNOv6VwB43XO6iqb6euoQTCwxNLcGSS8u+fv7Mbn9iU09wtuBdRvziIjKeVQJj3qzKEP6GEQkOAMGkYCMv+XkACYc5v9tEDwvjjrEOHuSUQiIfvI4Ssn8tYlxUI2ZG1zFNWIBwHxfbFaskyBAhVdwuOdmWEsfrkFPv8AGJVwGieB4BBbicVzBkKpsRzmGbAjSIiyjbAmRcWpSQs9vURU0RVh9sAwNDQEPr7mcVQ2z77UuvHmrd/ghqnMNQ6B1O6hAogfODlTwmED7x1AWGAAe4gAYQXZyWh0jbJoAX1D2JScW5mFq56FhG9g75xqFqaxBgIL7jsJGHtgvdeotdver5J3EFdfYSHJ5XgyCRisMyxv5Xi2JxPaS+aL31+LyKePIiUXyqBsODXZUh56hDCn6hA+BMVyPoVcyhMfJIAwopX15JAmPrLg/SAMO44OBwlALS389DezmMdREwpoVACAOByrUCoT1YgZEfWMk9ZgXAcFNsXqyWLKRB2dvZgaEj3bkEm6u6WY2hodC7YaGOr6kBI/PA2xNFTyNCIKNV7DQBisfFgUBERHSv9guZWT48cANDT00sJi9qdRQIWe3vVYbHti691vt7D9DxiwAyFS1jnFqgTCO+7B44KCGudQyiB8NLsZFTOT0StC/MF9TWJxDCZO9EEENanMh8mUxm0gwS17xeW4NT0dTg1dS3OGr13UL2P8NhLW3QC4dcO9GGw5Pn9KH1hL8ImHETcU+pAuPaZMkQOu4ThT5Qj5xlmUBg/DIRHp+STQBj/ZDm9HsI4IsLM4wnB4wnA5SrF4QjGJSyKRFIAAIcjYP1cxrI4HAHr9xuWKmuZp6xAOA6K7YvVksUECOXyPgBAX1+/0SBltLFIY8RWRwoArZUZI8VkvQUdKQbcGOvretz6BY0podCwfkElLPaQsDg0pIRF6U/nVWBRruEscjl81IcmosYpRCM6WucaiGrHMEogbPAMQI1TMBr9fA0CwvvuVO7gMBDOScJV2yTcZbqg3jsYl+3yce7DHNR4JxC7BwPymPUNuubhu3c3KHsHXT8hHTxTuYMKffnaesoewsOTinFy4SFs/T19GFQCYRkif6EOhAW/LkPGL5UuYfgT5VjNAArjJhBA+Nk/80ggjJ1Qji+m0ADCWM2e1pHSDotKYHycYFHxSzy2z2OsywqE7Mla5ikrEI6DYvtitXTpW04vkXSR++O6unqNAidKIDQsFqmIiBojtjpSjx49Qnc3s6+zq6tn1BFRbUA42ucjIqISg2HqcZdYLMXQ0BAGB+nvF6QLi9zvvtcKiwDhLPYKxbjvHYn7buoOYa1rIO5pcQiJ3YFheOhjmENI7Q4SQHhlbiLOf5iOm0tjmAFhch7OzcxCpW8Jap1D8SCe2TCZa4sScd5R6Q7+5KiMjZrWHdTeR3h4UgmOvbIN+14/zAgGCSDcg9AJZQh5UhMIC35dhtgJ5SQURjxRjvxf0wPC2GEg/HxargoQVqBs8hb9QBhzbFT/Tz+OsCiRdOLRo0esn8dYlxUI2ZO1zFNWIBwHxfbFaunSBYQKB29wcBASiXEmb6rKkL1/xoyIUmlo6BG6u+lDplxORETl8tFFREdKMfF0NO/7WFspYW51dir2C/abpG+y7fT3GscEAk1nsfN+PWpdw9Dg5a/pEPoGa8ZFh/v/7nsEaADhQ19fNHjqAMIowpHUCoS2Cfh2Wj6uLUhgBIS3w4m4aE0cMV20LrGQERBeDVIC4Klpa/Hj0m1mcwe19REenlSCY9P3MoZBBRAGTyiD/wRqIMxVGTAT/kQFIp8ox9p/0w2DG3+jBMIvZ+SQf46dUIHSP+zQ30MYfdRk1xIBi0I1WBwZRWUDFqXSTgwNDbEOXGNdHI6Q9XsNS5W1zFNWIBwHxfbFaumiAsLRrEtgIqYumCkioppAOETLdVR3TkcfEdUGhIb2ahIRUTEsMSLK54vQ26vZL2h0IDx7jv5jv/kOta7KATOkQ+ijCYS1LgqgC9GIjT7w8dMJhK2ff40aF+1AeNU2ASf/sR6V8xPpL6gPjsb5j7JxflYuar3iUOcdg+v2KfSB0H0tTr+9noSzC557zOoOau0j/L9t2PenHYYB4W8JIPSeQCymp4LCpF+oRkcrEDWhHAVaoHDjbw4i/5mDJACefDMb8U8eIv++9rnd+oEwynRAOFZhUSYjovpsA9dYlxUI2ZO1zFNWIBwHxfbFaunSBBGFA2ecXjhjQI8pI6IjNTg4qBeCFRFRUzmnBHAaPvF0vK2UYCJD+wUNUftPFxk9vmXPQbKXsM4tCPdcoyn3ECpWVlDFRnUB4cO0HPD5ItR5hWsHwvnxOPmP9bhqm0R7QX192kacm5mFm8HbiN2DKevpR0WXJOGn5cqdg6ff3YCzszeTkHZqar6ZgHAtvnq9QLl8/qP9KJ+4FQf+vN0gINz62z0ImlAG7wmHsPpX1EC45pkyRKi4hOFPVCBmQjnW/0YJgut+fRA5vzyEVU+Wk/2DsRMq8PVbWUh4qoz8e8YzB/QDYcQR1q+/kdIPi7xRwWJnZzcGBgZZB66xLisQsidrmaesQDgOiu2L1dKl6hCaw4FjCj2mjoiO1MDAoM74p2K4jlzeb9LzMGQFhqVHRE3VL6hN7Rd/Zvw5D/PWo94zgABCtwQNIGzwDEC1CsTVe6rHRh8GBmoFws6rVejvH8CDqFStQFi5IA4n/7EeFz5aRXtB/XVPAgjvRm1CrXMo7gTmM4iK7lKDsgs++1hwB5Uu4dHJJTj+6jaUvXUU5RNLUfbitlEDYaYWICz4dRlWPaXuEoY/UYHYJ8uR+3QZ0n9RjrQnK5A2AgZjJ5Tjm7czkfRLpWOY9ItDeoHw0hgEQl2iA4sdHXydsNjV1YP+/gHWgWusi8MRsX6vYamylnnKCoTjoNi+WC1dQqF5HTgq6OnspIae3l4CvswFqCKRbHgXnSbsqe5fNPZwHer3htkKDEtfKdHZ2W3SfkEqdVy5ZtBNcGNSGmrdgnFnRTTqRwKhVwDqPQNUIE49NvowLIwSCBuTM9HZSazOaF1frAMICYfw9PQ8WgvqmxIzcW5mFs7PWY0a9yjcj8ykHxX1Wo/TbxaQQPb9vCKV6OganJpmPndQtY/wS/vPUPL8flRMLMWhF7ei+Ll9zIHwd7sROAyEqU9rB8IDfylG7IQyDSiMeqICqRMIGIxXg8EKxD1Zjm/fyUTK0weUxyboXz1xKeww69ehsUQXFru7e9DX1886cI11WYGQPVnLPGUFwnFQbF+sli7CgXtkNgdupADNNQ+q8MV04qcxgLCvTx0IOzsVEVHj7F8czXujCwYtMSLK55unX5BKHdduGPR5nOY2VAen4vbyKA0gfODth+ZAb/XYqK+KQxgWTgmE7aeUA25aKo5rGSwTisqFhEN48h/rcW1Bot4F9TWJm3FuZhaqgkpR6xyK2iR6uwev2SXjR7ut6u6g+24W3UECQr9ZtB8lLxAAeHhSCQ7+ZRu2/nYvYyjc9h+74T8MhAm/1A6EX/9zLb6dtgYJTx/QgMLoJ8oR/4Q6DMZOqEDiU4dw6t0MpD1zQO34Z69s0A2EoeMHCPWJxxNCLJYO/xKzV6uzOJYmolqB0DJlrf/P3nmHN1W2YbxJi+w9XQioBVllFVBB9hIUFAWqiMgSBERBZA+ZXbSU7pHVpE2hQGmhpbJUkE9coKgICIKoCKEz3Yv7++PknOTknIy2SU6avs913df3GZo0nOal+eV5nvt2TBEgdIES+rDWd5WWlqOsrMKmAejVkTH0FRQUo6rK8fBFq6ysHOXlFcx/011KY0h01LUx142kR0SFfnMmlBy5L8in/y7/VuP7/r5uH355jQuEtxfMxZ1Fc/Hne/Px+wzd2KiB2ygfEN5atR6a+1nMY9///Tqumgim/9EACC0G1M/7ABcmU3ETVz8OwrV3VuCnN9dbBYTfLZSwYOzs69EsMDs5aKcAQOiLw333MVC3/5kwKJ+MQlQ7OSLaWg+FoS0VLCD8yMM0EGb098WXL2zHqcE7sbW5lLdTaAyEaxuocHLYJmxsHM+6Xdo53CwQ/m9JkuBn0lHSaikH4dLSMs6fWTK4qY+weP9+ruDvNeqrSDmmCBC6QAl9WOu7srKEAUFahjEPhvAlFKCWlpYzeYJCdSkNgdDU9yb7glpmXzAnx/77gny699vVGt/39y3RHCC8OWch7iyay4hxG531AW4vWEAB4TIuEP6bfoLz+NfnLOcHwsl6IPxm9HqzAfV/bvDFueFb8b+Ju3H17eW4tdG67uDF94JwwtvPJBCeHrJDEBg8MdAX6V5+DNgdeCYM8sejEdVOjqh2ckRaC4UtFYhsK8V8HRAu5QmnZzqEAygg/PKF7TgzdDuCOkRZhMINDeNxavgmbG6iYN0e3C7WPBAuVgt+Lh2hwkLKnbq4uLTa96VgMbvewSIBQuFEyjFFgNAFSujDWt8lNBBWVlahpKRUcPiiVVJShsrKSkG7lLRMRWDU90gJel+wrMxx+4J8unftZo3v+/sOBRcI32UD4a15c5ku4V/rN+qAcDkLCP9c8Sk09x5wHv8Gr7HMB/hx8koGCE8P3W42oP7ykiCcG74Vl5ZE4NqsD/Db0t0WYfDStPU49wp7VPR/78pxYqAvMvtT3cFT3sJ0B+nnQINd8rOhkDwawwAhDYVhrSxAYUsFwtvIGCBcZCKc3r9xAjINgPDLF7bji+e3Q9I1lGd8VA9+W5tKcXr4RmxtJmcB4fZmcvNA+L7rA2FRUTEAoKio2OaPTe0t8nUWs+o8LN6/nyf4e436KlKOKQKELlBCH9b6LmcAQiH280ypvLwCgLBdSnNAqI+UqJ8Sal+QT/du3q7xfa/4JXFHRnX7g7Ruz5uH6++vwdWZS3F7625eIPz3SDrv49/avZcXCC9OXoWMfv46KPTHxZdNBNR/sArnRmyl3EWX++GPpRutHBWVsgDs5PMB+HJCGE4M9EWGly8yBwgHg7TiOsYyQBjXMZYFhDQUhrdWmAbDNgqEtZbhPR0Qvmcmi/DzgbtZQEgruWcglrmxHUg/1kHhjpYSnHlpEz5rLmN3Dhubdxo9vyhR8DPhiLNfUFDk8O9tDhbtnbVIgLBui5RjigChC5TQh7W+S0ggpCMcqLE/YeErN1c/IlpVJfzzyclhZyLW9xFRofcF+XTv9t81vu+VPYdweRrbZfT2fD0M/rVwLm4uWIr/7tzF1dkf4fqiT3VA+CEDhH8uWwXN3fu8j//PgSMsYxoGCF9eieP9fVl7hHwB9dfXUVET/5vsi6s+y3B9reVx0R/nh+DEIDZ8nZ+rj5nI7O+LtN7+DoU/Ph14NoQZGY3tKOEAIa1wI7OZ2J6HEPvScQS2SUBoaznm6oBwrigRu3iBUInPB/ED4ZcvbEd6I27BSAAAIABJREFUf1+s9FBxOoW7WsXii5c2YXtLKdt91N280+j5ha4LhKWlZU519g1l2RFVeFgkQCicSDmmCBC6QAl9WOu7hADCvLxCBr4qKioFMWwxlGHWYUkJlcUoNAzm5FCZiCUlZfV+RDQvj94XrIRQ+4J8uvfvvRrf98q+NFx+bSVuvLOId3/w1nvz8O/x03jwIAd/HTxOjY1+upYFhP8kHzH5+Pev3eAxlvkAFyevxOeDdjFAeGHset6A+u9n+eHc8K34aWkErr29HD/N2mQeBl/fiC/G72OB1+kxITj1YqDBbbuR2muP4ECY2nMPwlrJkdQtHLEdTAMhbTYTNzQVwb2O6jIDkxDQLB4hrdhA+BlPFmFgUyVODNplEgi/fGE7Tg7eiY1N5Swo9G0Vgy9HbsTOVhIjwxk1MidFmwbCBQmCnwlbKysrB2Vl5Xj48CHy8wsEfz7VlbPA4v37+YK/16ivIuWYIkDoAiX0Ya3vevDAsZBTWEhHOFQiP7+Q4+rpaBUXU2NIVNahFoWFJQAgOAzSQKjfk6ufMOgs+4Km3uzV9L5XYz/Hz9NX64HQYH/wrwVzcWvdNtbXX/9gE25v2ckA4Z+LP4LmH/NAyjWW+QAXJ3+Mk4N3MED4xQufcQPqV1PZg+eGb8WVpbvwx6e+FruDF96TcMDr/BwZ57b0vgF2Bz5Lyujnj7BWcqieikCMBSCMaidHRBs5tjZIZIAwqIUCe1vKGRicK0rERp4swqBm8TjpbR4IKbOZHfBrF8MA4a620fhq5Absah3HcSDd5p1gEgi/nqcS/EzYUllZ1FRAVdVD5OZqBX8+9vj3w1GwSIBQOJFyTBEgdIES+rDWdzkSCEtLywGAFfxeWlqGiopKh8NWbm4BM4JIu5zm5FCxF4DwQJidnc+M1AJAVdVDVFRUoLS0DEVFxdBqC5Gb69qxE860L2hrXU/4Ej+/sZYBQsP9wVsLF+O+0Tjq3e9+wh+L1+DWcgoI/0lMtvg9bqzYwAHCS698hDPPb2OAMKOfHyeg/sqqYJwbvhXfTPXH1VlLceVDP/PdwYWhHOj6amoky2n05KCdOKkbJz3eT1ggPDHQFzEdYqB4MsoqIKT3Cnc2VGGDOAkhLeUIbqFgAeGnPFmEe5srrAJC2mwmunMYlrklwa99FL4atQG+bWI5QDjdXYoTEyNdHgizs3NRUVGpG993nqkAR8kyLOqzFgkQOrdIOaYIELpACX1Y67scAYR5eYWorKzU5eqxg9ZpV09HwpbhiKhWW8T6s4ICytI8N7dAMBikg+Y1mhzk5OQhP78AhYVFKCkpRXl5OSorq1hnqKqqCuXlFSgpKUVhYTHy8wuQk5OvC6uve8rOzkNFBb0vWPfGxKzRjZT/4dIb6xkgvL1wHmUkM/89/J2Uwnufm7vCcWv1GtyctwSaO3ctfo9bfvt4gfDLFz8zAMIA/DhptT6gfv5S/G/CdpwbvhU/L4/A9cVrcXHKJ6aB8I3NODNmLwe4zr0Zy/rvk4N24+QgX5wc5IvUXoEOgT4+HevrB2XnSES2jYP0sWjEtLcOCGko9G+iRGhrOfY0ZwPhxzxZhCEt5Tg1eKdVQEhDobpHEAI7RuDc6PXY1TaGMZqh9a44HsGT+c1lvp6rFPx1bQvl5OShspIaEc/Ort8mWnyqLizeu5dFgFBAkXJMESB0gRL6sBLZF24KC0uYEdG8PK6LaHFxqUNNXIqLqR1BakSUC31aLQWEeXnCACENg5ZGRLOycpCTk6+DxWIdLFagqooPFst1sFikg0XnfZPlrPuCttatk5dwcfpGHYgtxF8LKSOZW6s3mLzP/Vt/4+b6bbi50deq7/H3wTQjY5kP8PPUFfhy2BYWEH47bh0TUH9jva9+XHTJdotmMt+8G8eBrq/fYo+PUjETeiBM6RnkcBDM7O+L/d1CIekUi/DWckR2kCP20TjEdJBaDYT6vUIpAo2AcBlPFuG+VrJqASGt44O249zo9djdPhrLDdxHV4qSsFikwuDGkTgxlhtS7wpAmJubj6qqKlRUVCI723WnH+wpY1i8dy9L8PcY9VmkHFMECF2ghD6sRFpkZ9sHbsrK6BHRMpNfU1RU4hATF8MRUb5sP1r5+YUA4PAIDMpF1DaglpWVi9zcfGi1hSgqKkZpaRmzi0MXDellZeUoLi5BQUER8vK0gn4i78z7grbWnW+u4MfXNjFAeGfRXNxetBD3rvxh9n63VIdxM/qAVd/j/h+3cHUm21jm56kf4uxLm1lA+NWwLUxA/c+LqOzBC9P34Npby/Dz7C360dCXjUZFF0Vw4WuIH76cFMa67fTgHSwgPNrHsR3CQ933QvFEDOI6xiGqnRRhreKxr5UMke0kiG5fPSAMb6NAWBsZfJvEs4DwfZ4swtBWMpweUn0gPD10K86PXQe/DtFY5paEDw2gcIUoEf0bRCL8VW6X8NyceMFf17UR9WEQ9WGdq59/R0mjyYVGQ7qDQoqUY4oAoQuU0IeVyPZAmJ9fyOQLFhQUm/1aR5i4mBsRNVZeHg2E5r/O9jDomEgJCha1Olgs0e1wUqBMlxCwSO8LFhW53r4gn/799RZ+mEoB4Z8L3sdfC+fiTozcijd42fjvunX5h3l5Wlx/90M2EE77EF+P2MQCwoz+fvh56sf4c/mnOPcSZShz+cNw/PHJLhYAfj/RAAZnbMXpEdxO3/m5ct7uYGZ/XwYI6Y6dvUHwaJ8AKDtHQfKYBHEdpYjtIGUiJEJbyRDWWlYtIIxsK8e+lvEIayPDzsZKFhDOE3GBMKy1DKeH7Kg2EJ4cvA3fjFuLgI5RjNHMCgYK1ejfIBIvtojGiZH72ED4Tt0Fwvz8AubDIKGfi6uIwKBziJRjigChC5TQh5XItkBId/wqKiqtGru0t4lLUZH5EVEuEBYAgEVwtJWcKVIiOzsXeXlaFBQUori4BGVlZUw8CF30z5YytynRmdtoazzeZbgvWBdt5Wuq+3/fw3eTqZHR2+8vxO2Vq1Ab11Jj0d3WPz/ezALCy9M+xPlRG9hA2C8AF1/+BNfWBjHjor+/vxW/fxzADp2f8Cnz/8+/HcsBsNMjg3HqJTYknhmyHScG6o1k9HuE9oufON7fF4ldwyF7LBZxHSkYjOsoQVgrOQsIQ1rKqwWEYa0U2NdSidDWMuxoxAbCuaJE7DbKIoxoI8WZodUHwsyBO/Dt+DXY82gkK46CgkI1BrtHon+DSMS+xu4SnputEPx1XRNptYV4+PAhSkvLBH8uriICg84jUo4pAoQuUEIfViLbgE1urn5ElA5Tt0b0zp6tTVxyc7UoL68AALMjonz3A2Cxs2krGKR+gQsPg5aUnZ2ng8UiHSyWM0ZBdFGwaL0Tan3ZFzSlbydtxB+zF+H2+wtw97tLNntcOkqluLgEt/zD2ED42nJ8M3Y9Bwi/G78W372+C+eGb8W3M4NxfcFqXHz1UxYQfjtuDS5OXo0f3o/iBbHz77K7gye9d+HEwN06IPRDZn8/u+8RJnuGQPFEDCSd4nQgSHUGww1gMKxVPPa1lGNfS4XVQBjRhuoO0kC4vSEXCLcZZRFGtpXizNDqweCZoTtwfMBOfDfxUwQ9FsECQjq4fqI4Dv0bRGJE6xh8PnwvA4Rn37bcYXY2FRYWMf9GC/1cXEUEBp1LpBxTBAhdoIQ+rES17xDSI6JVVZZHRPnuC4DXcKY2z8faEVE+AeC4odpSjhwRdYQMnVCLi0t1sGjeCbWkpLTe7Aua0oXxG/DHe8twJ2SfTR4vKyuXCfHWagvx4EEO/k7JYAHhL68tx4Vx6zhAeHbMdpwfsYkaF10Rhuvr2GYyP0xajQvj1uLirB04NYzb3ftySjhODPZj3XZa1x2kgTC9rz8DhGm9bbtHmNZrD5SdoyF/3LArSMFgRBsZCwbDWsUjpIWCAsJ2loGQHhXd11JJqbUMnzVUcYDwE/dEFhBGtZXii+erB4QnBu3G8QE78MOkT7H3iXAOEC5zS8IStwT0b0B1CRXT9V3Cs2/VLSAsKqLWBYqKigV/Lq4iAoPOJ1KOKQKELlBCH1ai2gFhdUdEjaXf2bMNEBo+n5p2Hal4jBK7wKC1LqKuIj4nVMOuIlD3nFBtpQsTNuH6is24d/e+Da5zHiorqdw2wxDvezdus4xlfnltOb6dsIYDhMcH+ON/ozZS46ILN+Ly3G0cIPxm3Fp8PTOGF8jOzWK7jZ4ctJvpDp4Y6IuMfn5I6x3IdAk/H2CjPcIX9+DYxETEPxkD6aP6riCt6HZcGAxrpcCuRioEN1cgyooOYVhrhR4GWyoR0kqGLY9wgXChWyLWuSfCTzc6GtVOUu1x0WN9A3RAuAb7ngzjBcJlbknwESnQv0EkxneMw4kXgymX0bcVTmEOZY3oneGCgiLBn4uriMCgc4qUY4oAoQuU0IeVqGZASI2IUiOZ1RkR5T6ObXb2ajqyyqeqqocoKrI9ENY3GDSW8b4g5YRagKIi07EZlZVVOnObUhQUuBYsXpi4BX+mnK3149Cjt5RVP/faXJuznAHCX19fhu8nreYAYUa/AJwfuQnfvRWCP1Zt58RLfD9hNf73diQ/DM7kRk+cMegOnhjoiwwvP6T2CsLhHsE2ySP8fKAvjo+TYH8/BVInHUTcY1IODMa0l/LCYEBTJbZ6JGF3owREWegQRhh3B1sqsbeVDJsbJHCAcIFbIpa5JeETsRq+jRIQ3b76QHi4x14cH7gTP0xag/AnQrHKLQnLeYBwqZsa08Uy9G8Qif0z1Tje3x/n31YIbg5ljUpLy1hdbKLai8Cg84qUY4oAoQuU0IeVqPpAmJ9Pu3Y+REFB7UEOqN3OHntktfZmMFVVVdXaO7QkekRU6DcNQoq9L2j+DSlfbIYzOKHaWt/5BNb6MQoKCg1Gb/m/5saKTSwg/HHyJ7xA+PVLm3F5RSiurgrkAOF3b+7Gce8ALpwN8sWXrxjFTwzajRMDd+nhbYAOCHsGI6lbmH6P8Lma7RGemhKLI6PVSHg2Dkcmp3BAUO8oKufA4J5m8djqkaSTGhFtTANhZFs5Qo1gkAbCjR5cIJyvA8Jlbkn4WKRGTIe4asHgF89vR1K3MGQO3I4fJq1B6KPh2CBOwnpRElaLqPgJYyh8VSzFlCckyByyB1/NlOLBA8N9X8ocijo/3H1fR5+frKwcZqS5PhlI2VsaTR4IDDqvSDmmCBC6QAl9WIm0yMqyHm4sBbvXREDNd/ZqO7LKp8rKqlp3GdkwmANX2ResiQoLbZcvSDuhsmMzLDuhUm92nQvKr8pO1er+xcXUDlZxsfmojluBEQwQ/jZ9KS6+spIXCM88vw2/zduEi1PXsPMGp3yKL16JwLE+fhw4MzaS4esOZvbfjQwvPxzpGQx113BkDvDT7RFWz2n05Ii9OP5aMpRdYnBk7H4ouytMwmBEa2MYjEdwC0MYpOTfVGk6c9BoVNQQCDe4c4HwPQMgXOaWhKgOsdWLm/DehaRuEcgcRAFhSMcobBAnsbRGRBnLGELhBPc4JM9Q4as3JVacH2NzKNPnp6yszGawmJWVy2ShGo40E9VOBAadX6QcUwQIXaCEPqxE1gGhtcHuNdHDhzUb0bTViKixaJio7ePU9xHRBw+o8TDAMcYR9nBCtafu3XtQo/sZmscUFFgeu/s7LVMPhG8sxU+vfsQLhJmD/PDLfJ5x0ffjkNnfF0d7s4Hw1PA9OD0ymNMxNOwO6oHQH0eeC0ZStwikPBes2yP0w+cDrBgPHeSHUzOSoO4pQ8KzEqS9moK4ThJeGIzrKEVkW+7eYHBzLgxu9UjCZx5qRLQx7ypqrOCWMqwVJ3KAcK4REMZ0qh4QZvTzR1K3CJzQAWFQuxgOENJaJ0rCSmacVI23O8rx1SyZjc+PbWAxOzsXFRXUfmt9dBO2lwgM1g2RckwRIHSBEvqwElkGwuoEu9dE1R3RrE7wfU1UXl6B0tLyGt+f6grWndFFe8jZ8gVpJ1Tqza5lJ1QKFgsEg0Xz15V6c52XZ12n5d7tvxljmd/epLII+YAwo18Afpi2hQ2E7/jh5BB/HO/ni9Se7JHR83MV3O7g0B2c2473o4Aw5bm9SOoWgaSnQ5mx0aO9ecZQDXR6mgyHhyVA2TkGh0ckQT1QbRIE4zpKEd83ieso2pIfBmkFNFVxgDCoGT8M7mupRGBLGT4xhkEdEH7gpmaAMK5TTLWA8EjPIAoIvbfhh0lrENg61iQQ0lovUuMTkRrL3dSQvnbIrq874w9bzHXmKVgshFZbgMpKalS8Lo1zO7sIDNYdkXJMESB0gRL6sBKZB0J7jIgaqzojmoWFth8R5QPCsrKaAaGrRUrURNXZF3QGGcZmUOY25RxzG+PYDMrcxrHdDkvmMeZ0bc6HuDpzKa7M+AC/vr7cJBB+M3qDflT0lTU4Oy2ScQk90lM/4vnFxFCcHOLP6Q6eHLSLBwh9ke7lj5QeFBCqu4bj84Hm9whPjglF+isHoOwcA1W3WBydmgLJ46ZBMK6jFPuHHUREezYM7mupMAuDfF3CsNYKBDThh8GQFkr4tZRjlRsPEIoSscQACCWPRVdrf3D/02FI6haBk4MpIAy2AggNtVKkFuT8WN+ZZ8NiXdv5dRZRMCj8+wYi60TKMUWA0AVK6MNKpMWDB1ywseeIqLGsHdEsLaVGRG0xzmlOZWXlKC+vqPb9qBHRXNTnEVFb7gsKraws/tgMc06o9orN0GoLa3VdaWOZKzM+wJU3l5oEwrPDt+DHl3VGMov07qFUhy+IiYr4+m0ptzv4AhcGDYHwcI8QqkPYLQKpvfbonEaN9giHBuDkjANI8JRA2TkGB19IgHqo+a5gXEcp4nuoEPesmgWDoa0U2OqRaBEIDbuEkW3lCGqmxJ6mSuxtzrM/2EIJ35ZyrHJT8wLhYgMglFUDCE8P2clcGxoI97WJxQax2mogXCFOFPzM0MrL0zIfJOo785ZhsajIEBbr9r8f9hCBwbonUo4pAoQuUEIfViIuENp7RLS6Hbm8vELmTYQ9A+MNwbOiorLaMEj90q6/MOjIfUGh5UgnVGvNY8zp1h7KWOb3mUvw+6wlJoHwxKBd+GHip7g4NxAnvP04QJjh5Y9zb/JnEZ703sl7e4aXDgi764HwwDP7cHKQLzL76/cIT0+PR7K3EsrOMVB2icHRV1Mg7SxDdDvT+4JxHaWQPCZD4osp7FHR9iqrYdCwSxjSIh5BzVQIaqZCYFMVBwiDmiuxs4XCJBAuMgBCxRNRVgNh5gBfDhBGtIvFelGi1UA4p2G84OfiwYMc5OcXMB9emPu66nYWndkgyhEiMFg3RcoxRYDQBUrow0rEBsLiYiow2J4jonwdubIy/o5cYWEx88Y6L8824fWWVFJSZjUQkhFRw70259gXFFrZ2bnIzbXOCVVvzsF9o2to01/bAO9/0k8yQHjtrcUmgTCjXwC+m7geX00JN4I6fxzuEYxjfQLw1bQobndwGNeBlFZ6Xz+k9/XHIQMgVHcNoyBykC+OPR+OoxP3UyDYOQbJ3kocHJlsAH3mgfDQpDQWDCoGHsaOFvuthkFavo1VCGqmZIDQvwkXCPc0V2J7c9NAuMDAWCb+SeuBMK33Hg4QxnSMxgax9UD4ejvhgZDuZJeWltX63xQCi3oRGKy7IuWYIkDoAiX0YSWilJtbwHQ4iorsOyLK15HjG9GkO061MXipGRCWorKyyuLX0S6i9RkGDffa6sK+oNCqzhvdqqqHuvNYXGtzm3t//aMzllmMP2YvQkY/f5NA+PUUrtFLel8KCDNHcWHwxEBfnPLmmsnQOtbXD+le/jjouY+BnqRuEUjrTY2N7n8mjIHBtFcOQ9bFOE5CYhIKD45JQVhrBQODsj4H4dv+YLVhcKtHErZ4qBHQRMUAId8eYWAzJbY1U2ClCSDUZxEmQtk50mogTH5Wf21ODtmG7yasgfSxKGxxtw4I14nUeKWbUtDXdmFhEYDadbJtfYZcARYJDNZtkXJMESB0gRL6sBJpkZVVgKqqh6iqqkJ+vmO6cOY6cnl5BUxHxREjosYqLi7VWaRbhsH6PCJKd2/LyspMhqITWS/6jW5xMWWcRHXGq1hvdKuqHupccKsfm3Ftzoe4OmsxbryzCBn9TQPh6aHbcWLgbl4gPDoghNsdHGHeKfRYH6pDaAyEB54N1RnLBGN/PwUOjz3EmyloCgiVPVWIfjKRgcE4z/0IfOJwjWDQcHSUBsKgZirsacYGwoBmSmxpGm8SCOfpgHClOBEqK4HwzNAdrOtyashn+Hb8OsR3jsBnHtYB4UeiRLzWK0Gw125RETXWLPS4eE5OHvLyrNlZrGDBYm6u88GiRpMLAoN1X6QcUwQIXaCEPqxElIqKSpCb61jwMgQwuiNXUOD4EVFj0WH3fH9GIiWoUcb6tC/oSJkyj7GFE+qNjzbj6qz38fvbH+FoX9Mjo5kDqCxB2kCGAsIAHH5uL4705LqCnh7CvztI62gff6T39Ufys6Es8FF3o8ZSj/f3h+LZeBMh8xJIOkk4UCjtLIe8934GBmO6qrH36ZRaweBWjyRscWd3CXcbjY36N1NicxPTQEiH03/qoYLyKeuA8LjB/mBStwicHroVF8auh7pbKLY3sA4I54uUmDFQGJfRkhJqzaC2Y832Fjt6xrlhkcCg64iUY4oAoQuU0IeViFJ2tjAwaNiRKymhIKOmkQ+2Eh1twQ+DZF+Q7AvaR3SXpbi41Or7VMcJ9Z/QOFz1eR/fvfoZDjyzD+lepqDQH8f6Buh2/Sjt7x6Jwz32IuU5dhD9mVF7zMLgiYG+SOvlj/S+ARwgNBwblT0WYxYI9VBI3Z48Xr83GPV4AsJ6pdUaBvm6hMZA6NtUhU2NlSaBkM4i3NBIBdVTEVYB4WFd/qC+Q7gV/xuzAcmeIdjxiHVA+IZYjrdf2O/w12xpaRkePnwIrbZQ8PNTG/HnlJqDxWIGFm3tpkxg0LVEyjFFgNAFSujDSkRJSACjsw6pEdESQZ9LTg7VpQTAuo1ESpB9QXuJMo8ps4l5DPtx2U6oWV98jas+7+PzwX5I6haGIz2DTXYJ0738GSBUdY5GQpdIpPQMQcpze9ndwRfNw+Dn3n5IGxaH9L6BOPBMGAcIabfRhC4RVgKhBIcmpjIwGNFRhegBR20Gg3SX0E/XJQxoSmUP0kC4u6kK6xsp8bEpINRlEW5pHG81EO5/Zp9Rh/AzfD1qI4702oOdVgLhSHEs5oxMduhrtrycMjzKy9MKfobsKcPuvClYrKqyDSwSGHQ9kXJMESB0gRL6sBJREqpDSI+IAhBkf5H/OVHmCLTLan0fEX3wQL8vWFpK9gVtKcOOq73fWN+78y8uvbkK6bruX1K3cBzrG8gLhMf7+yKhSySUnaOh7ByDhC4RSO0bisM99EB4ZkwwZ9eQBYvTZDg8LAEJXcIoIHyaC4TqruE4OcgXh7rvtQiEkk4SyLrIEdlRibBW8QhvE4+4ocdsCoO0Nhl0Cf0N9gh3NVFhXUPzQLjYTY1tTeOR0CXcivzBHVB3DTe4JuE4PXQrzo3YjGN9A+HbSGkRBteI1BjsEY15Ew455DWblZWLigqqC52bm++Q7+ms4odF41FuPlikrptGo/+AkYLBfMHfCxDZVqQcUwQIXaCEPqxElIQAQnpEtKKiEgAcFnNhSVotDYTaej8iargvWFhI9gVtqdzcfFRVVaGy0nEd1zOjfQ2AMAIHPfeZ6BL6IbFrJOP+mdA1AmnekTjcQ28q8+UY/nHRk2NCkf7KAea+iV1Ckd43EPt5gDCpWwSO9glERj9/nYEMWzHt2UAY10mCsFZyhLWOh2Rwql1gkHIcTYK/rku4y2BsdGcTFdY8osJHZoBwkZsau5rLkWgFEGb09zO6HuE4M3Qrvhq+Bcf6BmJPc7lFIPxYpIa3RxTefzXF7q+f7Ow8VFZW6ky36jcMWpIlWHz//ffRv39/TJ06FUuXLsOOHb5QKBJx6tRZXLt2G/fvEzh0BZFyTBEgdIES+rASUXIkEFIRF5U6S/0SBsDy8pwDCPPzCwEAhYVFyM3Ns/mOSF1RTo5h94rsC9pStHlMeXm5Q19f5+Yomf1AWqm9gnhHRg/1CGGgTv1MFFLHJiD52X1UR+uZSCR1C8f+p8Nw4JlQJD8bioPdQ3F4sBwJ3WJ0nUVK6qfDcKxvIJK6hfMCYfKz1Nio9FHuHqExEEo6SRDVTor40Rl2g0FakpcyEdRMhdCnDjBAuKOJCp82MA+EC93U8GtpHRAeMdof3P90GE4P3YovXvwM6V6BCGkttQiEi0UJ8PaIwoqZR+362snJyUNlJfUBRnY2mZqo7bX8/vsfER4egbVr18HH5y28+OIweHp6Murfvz9mz34Xd+/mCP7+gKjmIuWYIkDoAiX0YSWi5Cgg1GqLUFVF2enTI6I0gDnLyGh2dj4qKytZr1O2g2ORzsHRdd8U5ecX6EadyJs/W4s2jykpsd48xla6dugHHOsTyIEQPoOZI72CGCBM6h6NxL4qqLuFIeGpKANFW9T+7pFmgZAeG1U9xd0jjG7HBULJo1Js9VDbHQh3tEhG6BP7EdxShYjHErGvpRLxo9MRPiID27qmmgTCBW6JCGwlQ2JXy0BomD9I71SeeX4LTj+/DelegYjsEGsRCGeLFBjoEYm18zPt9rqhu9kVFRX19gMye8h4TPTOHQ2++eYikpOPIChoHwID95JOYR0XKccUAUIXKKEPKxGlrCz7gxZtT15WVsGKuMjLKwAAaLVFgoOg4Zsd0w6ObOe5yspKlJWVo7i4BAUFRboA5LoLUYWFlKkO2Re0rejxW1ubx1RHGk02jnvru1L7nw3HhU2ZOLv4MAcIj/YJ0ANhzxgoeyiR8FQEErtEIbGL9VCY3CdaB6H8QJjULQLH+gbgUPcQ64CwkwQBTZV2B0LDLqFqeBoFhGMzEDkmE8HPZ5reIWyyH3vbyKDJdkWhAAAgAElEQVTuGmYWBr94frvR/mAEDjwTgtPPb8WpITuQ7hUI6WNRWC9Sm4TB9SI1XhFJMMAjEts/PG2X10xenlbXzSYwaNuzSHYG64NIOaYIELpACX1YiSjZEwhzcwtQXl7BjIjy/TkgLBDSQfPW7gtSDo5anYNjCUpLy5gxWLoom/LKGoWICyFDYCH7grYVZR5T4RDzGEs6+7YCSd0ikD5Ghjs//YUHD3Jw/+4DpHuz9wnT+/kzpjIH+kgg66pA/JNRDBDSUKjuHmcWCA8OkOBonz0mYTCpWwSSPUOQ7hXAAUJJVyUvEEa3lzoECHc0P4DQJ/YjcUw6BYTjMxA++nMEv2AaCD/pdgT72kmh7mYeCD8f6Mu5Dgc9KSA8MXgn0r0CEf9UhFkg/FSkxtRmMvT3iEDg+q9s/lrJzy9gcjGFPkOuJAKD9UekHFMECF2ghD6sRJTsBYTUiGgVqqqqkJ9vGvgAoKCgWFAYtFWkRHZ2HvLytJwAZMOyFCLuaOn3BasEBxZXkxDmMeb0e/L3+Cn8LOf2KwcuskZH0738sf+ZUCg7xyC5vxSSx6SQPx4NVecoKB6PgbRTHOI6SnBwZDKOzzwC9bOxvEB4eKgMR3ubB0J11zBqj7BTrB4GH5dB0iORFwjjOkqwq5HKYV3CmOcOUUA44Tj2jcg0C4SLmu1HeHuJRSBMMxrdTeoWgcM9gnH6+a3IHLgb6V6BUD8dinXiRKwU88dPrBSp8Wo7Obw8whG5+382fZ0UFFB7rkKMNruyCAzWL5FyTBEgdIES+rASUbIHENL5guXlFRYdRIXIIKRGRB37Bl3vPGc+RJwaQS11yAgq2Re0n4Qyj6mpTk1XsbqEtLHMoUEyHajFsgLiacmekiNjZioOv6DiAOGR4Qqk9Q4yC4RJ3SKQ4RXA2iM8ODEN4a1lvEAo6SRBRFuZw7qEYU/sR+yzB6CYmIm9L2YiyAwQzhUlIupRCdTdQs0C4cHuIZxrcKh7ME4P3YqM/n5I9wrEwe578aFYhcXiBF4g/NAtEWNbxqKvRziU4d/b7HVAj40XF5cI/pp0JREYrH8i5ZgiQOgCJfRhJaL04IHtQMtwRLS4uNSq+1RV8Y+T2hcGnSdSwjhEnBpBrTAzglpS4/BjQxUVkX1Be4m+tnWpw3L3j/9wrL/edfRIT8pY5tAQBW9OoLGSXzqA9NcOs4AwbbQSqb0sA+FBzxAc9KT2CA+OO4KwVvGI6aIyCYRxHSXY9kiiw7qEiaOPQTGJAsLgF80DYeyTEiQ9bR4I+WI4DvWggPColz/SvQKR2isIC9zjsUis4s8gFCfCWxQGr0bhOKz82SavgeJiyvSIjI3bVgQG66dIOaYIELpACX1YiSjZCggNR0SrsxNYVVVlNTzWVtSIaC5sNSJqb2Vn5/KOoBrCYlXVQ90IKr2vWKDbV+R/zKysXJSVkX1Be0m/iymMeUxt9OOer/TGMn0pY5lDLyitAkLDbmFSTwkSnorGsQmJSO0ZbBEI1d3CcKxvABIHJiHqMRUkzx3A3g6mgVDSSYLQ1nKHdQkTx2VAPulz7H3pc4sdQsmTEiQ9vc8kDJ703sV7DQ7rgDCtdyDSvSgtaRCPBTxAuE6kxmJRAga6hWJgq0icTP291j/7kpJSQU2PXFUEBuuvSDmmCBC6QAl9WIko2QIIqzMiaqzKykqUlJQ5BAapX9J1AwYtyTD8mBpBLeeMoFL7iuVMZEZBQSETLk32BW2r7OxcxjwmP7/uZjdmjo5h9ggTukTg8HCV1UDIdAuHH8CRUWqkT0nCkeesAMKu4Tjezx+KXomIfToJQV0PY0/zeLNAGNdRgq0ejukSKsefRsLU0wgbewohw0+aBcK4J2Kx/xnTQGicBUkr5bkgnBzyGVJ6BTFAuLaxDPN4gHCVSI0pzRV41mMvvFqE48JXN2v1M6c/xKjLr1tnFIHB+i1SjikChC5QQh9WIkq1AcKajIgaixqFLLcbCDrbiKi9lZWVoxtBLTA7gsqOzCjU7Ss6/66bM4ptHiOcQZAtdOvbm0j3CkRGvwAceCYUKSMTqw2EcR2lUA/dj7PrTyKlh2UgpHbo9iK+SwxCexzBVo8kBFkAQkknCYJbKBzUJUyGfNoZhI49hZARp0zC4NsiFeIei8GBZ00D4WET1yO1ZxCOD9qOQz2CGSDc1VKKuTxA+FHz/ZjyiALPeeyDZ8MQ/Hb5To1+1llZOSgvL8fDh8I74LqaCAwSkXJMESB0gRL6sBLpVZNw+vz8mo2IGqu8vAJlZfYBwupGSriqDPcFrYvMqKgzkRlCi7bnd6WstvMrj+qMZfbiyBjrgVD2lAKZ80/gSvo1aDRUJz51aAzUXS0DYVK3MBx4LpyBsKAWCotAGNtBAnsF1W9veQB7vNIR+GImdgzJgO/LnyN4zAnsMTEy+q4oAa+J4iF93DwQHngmlB8Ie+1BxsAduhgOCgj3tovFHLGSA4SKeV9jSiMFermH4unHQmr0M87KojvaVcjNrdsfYjibCAwSaTQECB1VBAhdoIQ+rER6VRcIi4pKajwiaqyysnKUl1fYDQZdZUS0JqL2Bcut2mljR2aU6vYV+UZQjSMz6q87aV00j7FGGk020oeGIrXXHhwZn2QRBA+OPozvwn7E3T/vcx7r6Cg5ZI/FIOGpSItjo0d6BjFAFmwFENoyqN73qSPYM+Q4fJ/PxNqnU7HQPQnz3dSY76bG+rHp2DwxA0FjTyDQBBC+LorH66J4yB6PQbJnCC8Mnh6ygxNITyutVwAyBuxC0tOhDBBGPxqN2TxAeOn4TYSv/RreLSIhj/2u2j/f7Ow8VFZWorKyql6fX/ucHQKDRJRIOaYIELpACX1YifSyFghzcymAA6g3wbYAN7pLZSsQpEdEhX5jILRycvJsti+Yk5NvNjKDO4Jq/8gMoVWXzWOs0dW0X3CsbwBSJ+znhcD47iqcWfUlbp6/ZfZx0kbHQ9IpDiEt4hH/ZLRZKDzcYy92NqQyBve2tA4IaxJUv63pfgT2OYbAFz/HtgEZWN7mIAN/xtoyNAOjWkuweVIG9oz9nBcIZ4mUmCFS4mWxHHIzQJjRz8/k3z2tVwCOD9yF+CcjGSCUPxmBt4yAcJ1HEuju65aln9fgLOehspIab3bl8ymECAwSGYqUY4oAoQuU0IeVSC9rQCs/vxCVlVWoqqKc6GwFcCUlZbrdK1vBIBkRpccYKyoq7Pqmjx2ZYW4E1Tgyo+5Ce3Z2LrM36+omHGfeUiN1nIHL6KNSpE0/hp9Uv+D+3SyrHiN1lBKSTnEIbq5CcHMlJI/Gmh0bDW8fh60eSQhpJbcKCK0Jqt/9+GHsGXIcfi9kYv2zaVjokWQSAA218vEULBl+BN4eUdj8cgYCx3GBcLZIhddF8XhVpMBkdwXkT8TgYPe9vEB4pKfpCI7U3oE4PnAXJI/GMECY2C0Ms8TxLCD87NEUpkvPdhW2fJ7oXdeKCtcZb3YWERgkMhYpxxQBQhcooQ8rkV6WOoT0iGhFRSXy8mo3Imqs4uJSVFVV1fpxyIgoJcN9QSGfB3sE1VRkBt8IqvPuM+Xm5uu6K1VO/Txtpf/+uo+M1/YjcWASvt7xDe788m+1HyNlhCEQUopuL+XdK1R3DYfyKWqPcJ+VQGgcVL+tyX4E9DqKPS9mYvvADKxof8gq+DPWQo8krBp2FEMbRsPbIwqbJh+H/7hM+A89zgLC10QKpjv4irsMiidicKgHPxAmP7vPdIewdwAy+u9GXMc4HOtLAWGyZwjeMgLC8DGnLLgK85+nvDytbsy/nMCgjUVgkIhPpBxTBAhdoIQ+rER6mQNC/YiofaIhiopKUFX1sJZdQTL6VJ19QaHFjcyo4Ly5rays0o2glupGUAsEHXFzRfMYa/TX73+DHlGsiQ6PUCHOCAiDm6sQ1kaOhC7cvcLEbqEUELa2HgjjOkkQ4H0MG3ocxaJHrOv+WdLGF9PxzoAD8PaIYoBw95jjLCB8QxSPmSIVpojlmOyuwPQGMsifiMFhHiA8M3S7yf1BGgjT+/khrqMEB3XGMkd6BmG2ERCmbfmRdX2zsiyPdANUp57OfC0sLKr3+7+2EoFBIlMi5ZgiQOgCJfRhJdKLDwjpEVEqrLjYLjCYk6NFYSHVfaw5DNafSAlTysnJd4l8QfYIqunIjIqKSpSVlTksMqOw0DXNYxyhw6MSIXlcwgHC4OYqhLSMR/yTUZyx0e2PJCC0GkAo6SSBfyuZTUBwvpsa63odxYIBhxgYpIAwAztGH4efDgjfEinxhkiJ10XxmOxOjYu+3VAG+eMxOPxcMAcIMwf4mt2fTOsdgKN9/RHXUQJl5wikewXiWN9AzHVnA+GNn+9W6zwVFRWznIMtR9C4/v6vrURgkMicSDmmCBC6QAl9WIn0MgZCGtLsMSJqrIIC6s12zUZEc1HfR0QdtS8otLKzc3UjqIUmR1BNR2bU/PuWlpYBAAoLiwW/BnVRKWPUkHaW8QJhcHMVApsoIXsshjU2uq+1BGFtqgeEcR0lmO+WUGsYXNoiGW91VmNqNxULCDdOzsBnI9PhO/g45ohUmCZSYJZIhZd13cHJ7grMa0wBYQoPEKb13mPeUOe5QKT1CUBcRwmkj8Uye4QrGsoYGFzfcH+1rj39QUZxcQnnz6gPX6yJoHHshy91RQQGiSyJlGOKAKELlNCHlUivrCw9aJWW2ndE1FhabREAVCu+Qj8iWr9hsKiohPlZCf1chBR3BNVUZEa5br/K8shcfTKPsadSxh2ArIvcJBAGNFUhpIUSsR3jmL3CuGekCO1QPSCUdJJgWzNFrYFwpXcalrx4hAWD3h5R2PByBja9dBS7B2fgNR0MTtUZydBa0lRKAWHPIA4QHuweYhIGqTD7YBzpFQhJJwmkj8Yh5TkqoH5jCwkDhDu6plp93YuLqX8bavJBhjX7v/U5r9TZYPDatduYP38hBgwYAG9vb2zYsAV37+bwfm1MjBRjxoyFl1c/jB49FlFREsGfv6uKlGOKAKELlNCHlUivrCwt8vIKmV/69hwRNQWE1nQiyYgoJcN9wYIC594XFPY6mdqvMj8yp9UW1ivzGHsqZXwyZF0VJoEwqIMaIS2UCGmhRGRbGRK7RED+RCRC2siqDYTRHSS1gsHNQzLwSut4jGkr5QXCtS+mYUXXQ5ghUmKGUXdwsrsCK5pLIH88BkeMgPCL57cjqVuYifzFCOxoHI8Dz4TicM89OiCUIKFrONK9AuHXJpYBwtjXvrDqmpeUlOr+bSi0+c/TOrMoatfWFWHR2WBQo9Fi5kwfLFu2AnfuaHDp0hVMmDARe/eGcb7u4ME0DBgwEGfOnMf9+/k4c+ZrDBgwEAcOpAj+d3BFkXJMESB0gRL6sBLppdUWO2xE1Fj5+YUAgPz8QitGREmkhKvsCwot60fmXPONraN0+cAvkHfnh8Hg5ir4NVUyQBjSQomwVgooO0chtG1ctYFQ0kmCdY3jawSDq55MwZTm8Xj/xRQODHp7RGH9yxlYMeAwprvHw0eUwBjJGOqDRjJEdIrF4V57WED4+cDdJruDkR3i8FlDFRK7huNQjyAGCOWPRyPdKxBhHaOxXqzGBnESzkT8avF6l5WVCdbVtr5TX3echQ2l0eTB2WDw4sXf4OnpiStXbjK3qdUHMXz4S5yvjYqSIChoH+u2BQvex/r1mwX/e7iiSDmmCBC6QAl9WIn0yssrQmmpY0ZEjZWXVwAA0GpNZxuSSAlK9WVfUCjRO1elpWU8XRDXeWPraMlfOWG6Q9hMib3N2VC4r2U89rSSIrytDJHtqf1AQ5mNoGhf/S7hogZJWNjjIGZ1ScLzjWJ4gXDdpAy83kQJH1ECputiJoyB8ONGMgS3l0Dhye4QJvfgzx9M7BKBLQ0SsbeVHMrOUUj2DGaAUNIpDmm99yDuiQisFauxXpyEf29rTF7jrKxclJdTUwPO9kGRtU6olZXVG+t2pJwRBjUaLQ4dSsOgQd6s27755iI8PT1x8+a/Zu977dpteHt7Q6FIFPzv4Yoi5ZgiQOgCJfRhJdLLcIfQ0crNpf7h5BtTJZESeun3BYnTpT1UUlIKwPLOlbVvbIlro14/Z940CYTBzVUIaMYGwpAWSnzWWAm/pioEtpQjrqPUQFxApBXTQYLI9lK8L1JVCwg3vJiBMe5SvDsomRcGvT2iMKfrfswUqThGMozECqxrrEBIOwnU3dmmMgnd+PMHQ9pIsV6shqSTBLLHYnHgmRAGCKWPSpD0dCiUXcLwqViNjc2TTV7frKxcVFRQr8Pc3Lr1oQSfs7A1Y92OPFPOCoMajRZKZRKGDRvOuu3SpSvw9PTEr7/+YfJ+v//+J6ZMeRWzZ88xuW9IVDuRckwRIHSBEvqwEun14IFwQJiTQ/3DWVjIBkKyL6h/w0T2Be17fW1hHlOdyAxqBLVEN4KqdekR1OxsClYC2yeZBMLdTblAuFUHhP4tFCwgjO0gRVhbGQJbybGrmQJbGyuxsYEKa8WJWCNSY40oCXPdrAfC9b2PYqyHFPP6HTIJg0PE0ZguprqDxkYytKaK5NjZOB4R7aRI7mEEhF25+4PKzpHY6K7G5gYJBgC4jwWEiieisP/ZffhErIZf33QT1zcPlZWVun1X1/rQgX+s21RshrETqm2uhTPDoEajRXJyKry9+TuEf/55l/c+Z86cx7Bhw/HBB8vxzz9Zgv8dXFWkHFMECF2ghD6sRHoJDYQPHz5EUVGJ0YgoiZQg+4KOuL6UeYw9OyvVMeIwHkGtTWSG0NJf30rIppgeG93ZhAuEm3VAuL1pPLY3jcfmhiqsd0/AGrdErBElmdXbbkrrIiZaJmPGo2qMe0SG155N4AdC9yhMEcnhI0rgNZKhNVOkwM7GSoS3kyL5Of3I6AnvXbzdwcAWCmwQJ8GvWTwDgIldQ1lAKHk0Dod7BGOlOBGqBed5rm8ec33rWweaG0NjOjajph/AUDAo/O9nc/rxx1/h6emJq1dvMbep1Qc5XUNaUqkSffv2RUhIhODP3dVFyjFFgNAFSujDSqSX0EBYVVWF4uJSBgapX8j1Gwa12kI8fEhBAsn9sr3Y+5jCXV8+I466tFtlSnl5WlRVUdc3KysXl47dMAmEO5qouEDYiALCVQ1U+NRNbRECDTVTJMc8t0SLQPjxoDSMcZdiyQvcmAlaY8USzBKpTBrJ0PIRxVNA2FaKg8/pTWUO9wrkwKDs8WhsEKuxXqTGqsZy7GtPAaCqSzgLCKWPSrD/mX342D0B36f8wbq+ubn5qKqqYq6v0D9vZ5K1H8DQhlHZ2TlISzuKs2e/xs2bt/HgQd2AQVpvvDEDS5Ysw+3b/+Gnn37HhAkTsXt3AOfrDhxIQa9evXD06OeCP+f6IFKOKQKELlBCH1YitozD6R2pykoKCMmIKCU6Q4zsC9pHhYVFePjwIUpLnTe/0doRVPZulXMEh9MfZpSVlbNuD2in5gXCXY25HcKNDSkgXO6hwodWdAUNNUMkxxwLIfWbh1J7g1NaxmNsB27MhLdHFF4UR+NNkXkjGXp/8C2REjubUEB4qKceCNXPcPMHdzVRYoM4CZ+K1PARJcBHpMKShgrIn4ykgukNgDC+cyTWNo2HRqP/gCwvT6v7sKi8TneQhZDhBzDFxaUoKyvHL7/8ip49e8LT0xOenp4YNGgQpk17HcuXr4C/fxASE5Nx9uy3TjteefXqLSxatATe3t4YPHgINm/ehv/+y4VGo4WXlxdUqv3QaLSYNOll9OjRA15eXiytXr1W8L+DK4qUY4oAoQuU0IeViC0hgbCiohKVlZVO9aZWCJF9QfuLNo8pKqp+YLezyPpxOcdHZtBOrXwfZkhf5h8b9eUZGd3QUAW/pioscVdhjpuqWkA4S6TADJHpsdFVnVMwuZkCY9ylWDycP2ZisHsUpooU8BElYJZIhclmuoPTRHL4GADh4V6BJvcHYzrpcwWXuSXqgJBS9KNRCG4ej7DWcj0YPhaD7R0UzDWkO9vO/GFGXdRff/2DCxe+w8GDKQgM3IsVK1Zi+vQ3MHjwYAYUV65cLfjvaaK6I1KOKQKELlBCH1YitoQCwqws6hNbvhw4eqynpKTM5a39DfcFc3PJvqCtZWgeo9U6PqPNUaLG5Qp043KlVkRm2G4E1ZJTq6mx0T08LqMbHqGAcIFYhRkiFT6uxtjoWyIFXhHLTUZMLOh+EGPcpZjRWY0XmvDHTEwUSxlQM2UkQ2uGiMom3NVEibC2MqTogPD0kB1I7Bquj5noGoHPHklggHCOWwILCKM6RmNPMyX8GyfAv7EKe1vEI7q9FL6Px+PBgxwUFFCdbTI5YB+ZGhO9efNffPnl/3Dt2m3Bf08T1R2RckwRIHSBEvqwErHlaCCkXUT5fjFbu1flKtb+ZF/QvmLDtmt+oGDtdeBGZtTe3j8rK4fpbGu1hWa/NqAt/9hooBEUrntEBd+mKswVUUA43y3BaiCcLYrHOHep2YiJMe5SvDf4IC8MjhTHYaZub3CmGSMZvaEMNVa6s4kSYW1kONI7AF++sB2pffxZ3cGwdhIGBtcy46IGHcKOsdjTlAZCvXZ7pTCd1+LiEsFfR64mjSYXdWln0Na6f5/tonrvXv29FrYUKccUAUIXKKEPKxFbju4KZmXloLr7gvx7VdaOygn/xoNPZF/QvsrPL2A6zQS2+cU+VyVmzlUl51zl5OTpMvCsC0SXTPycf2zUKHpibQMKCN9xo4BwhpsKq6zsEr4jiscoDwneNdoj3NDnGMbSMNiHHwafF0fjdV3Hz0eUgFfE5ruDU8QK+DBAGI+wtlKk9qGAMMlzLwODCU9FYrNHIgOEH/EAYVSHWAQaAaFfowQcj/gNgOWMTKLqq77DoKFOnvwK//6bLfjzcBWRckwRIHSBEvqwErHlqA4hDYO2dhFlO8uZG5XTuzXm5RUI1lWkRhjJvqA9VRfMY5xd1jg20h/CGEdm8D3ej0f+sCp6Ym0DFXY1UeFtNyruYYZIhUVWmsvM0QGh4R7hslbJmPFoIsa4SzG2gRRvdE/kj5gQyxlAe8OckYzB/uAsHRDuahKPsDYypPb15+wPBreSMTC4QZyEBUbjoj6iBES2lyCwiYoFhNsbJuCvX3NQUGC+80pUfREY1Ovy5esYN248JJJ4aDTcriFR9UXKMUWA0AVK6MNKxJa9gZAaEXU8fGVlUaNyWm1BNQPD7WfAkZtL5bORfUH7yRXMY5xZVKwElYFXVGQ4gmpqtLuUGUHlGxvd0ZgdPbHGQ4XtjdlAONNNhdVWdAlpIHzVYI/w40GpzKjo4uf5jWQMIyZ8RAlmjWRovWnQTaSBMK2vP754fjsSu1D7g4ono7BRrGZgcL1IDR8eIIxoL0GAERB+0kBFMkjtIAKDbN25o4GPz9v48MOPBX8uriJSjikChC5QQh9WIrbsCYT0vqCzRUro3RrN5VVV8QSG1xxsyb6gfWXYebW0z0ZUMxnGSvCNYluKzFC+ctpih3CNhwpbGqnwlgEQzhCpsMSKLiENhON1e4R0xMQYdykmt1BgfCcZBwaHiWPwhq7T5yNKwDRRvEUYnCxWYCYPEB718kN6f1+mO+jXLJ7VHfyEZ1zUR5SA8HZsIPRrlID3GicI/vN2NVEwWH87YHQkhbFOnjyLAQMGkJxCG4mUY4oAoQuU0IeViC17ASE1IpqLuhY0rze24e9+1CQDjuwL2v9nRsxj7CtzsRLWKDs7Fz+l3bQYPbHGIwEbG3KB0MfNclA9vUM4ykOCFU8cxstNFQwQLhnODaEfYhAxYa2RDLU/qB8XNQTCY/38kNwjCEndIiB5LIYFgxvESVhiFDdBK6ydFP6N9UDo2zwRCzoeEPxn7kqqzzB448bf0Gj046CpqRk4ffoc8+fXr9/BvHkLsGuXPzQa0+BIZJ1IOaYIELpACX1YidjKyrIPDFK/iOsWDJoT1f3QMgYcZWVlPF3Fh6yuolZbaLAvSLpW9hA1wkibx9RNt1lnl6VYieoooE2iWZfRNR4JWPtIAgcIZ4hUWGahS2gIhDMfS2Rg8I3HEzGsaSwHCCeJZSwws2QkY5w/aAyE6f19kdBtH9RdI7CjkYoFg+tFaszmGRf1ESVgX1sJGwifPogVzx0R/OfuKqrPMHjz5r9YtGgJMjPPQKPR4uzZb9G7d2+MHTsO8+cvwo8//gqNRguVaj/69++PP/64I/hzrusi5ZgiQOgCJfRhJWLLlkDorCOi9hY3LsPcTlXdj8twFtH5bKWlZU7rJlvXZW2shLWSjMs0m0e41iMBnzRIwFtuKg4QzrYQVG8IhKPcJQwQzht6iAODo8SxVOexGkYy+v1BBQvodjeJR3gbGTIG+CKhSzgiO8RxuoOfmhgX9RElIMgICIOmZmLTqAzBf/auoPoMg//9l4v//svFokVL0L17d7z33nxs2LAF3333M2QyFSZPnoIXXngRixYtwenT5zB37nzs3h1A4idqKVKOKQKELlBCH1YitmwFhDWNlHBFGe4L5udrXSouw1mkN48h+Wz2UFZWbrViJazVDwevmY2eWOuRgI88+IFwhkiFFWbGRmfzAOG8vlwYfEEcjdcMdgCtNZKh9wffNLrvLh0Qpvb1R2KXCGxpkMgBwuUmxkWniRTwbSPRZw82UiF63XnsnfOF4K+Buq76CoP37+fjvffm4/z576HRaPH7739i2LDh6N69O6RStptoVJQEixcvRY8ePTB48BD4+LzNehyh/y51UaQcUwQIXaCEPqxEbNkCCO0VKVEXRe8LFheb37WqTlyGoVNjfe8qEvMY+4veyaysrIKpGInayHhsdFcTNhAud0+AjwkgnGsmqH62SKkHQg8JxnhIMKt3EidiYrJBxARtJDPWXYLx7jJMcpeZBcJXxHLMMBgX1QOhHEnP7sW+NlIODG4QJ2Euz7joGyIlRojjsLO1HgjXNVRCueM7JG79XvDXQYYQ1mQAACAASURBVF1WfYVBjUaLv/9+gGXLVjD/fe7cd5g16y28+eZM9O3bF2fPfsu5T0pKOj76aBW8vLwQEyMT/O9Ql0XKMUWA0AVK6MNKxNaDB7UfERX6l78ziAKVilqDSlZWjlmnRsDxcRnOImIeY3/l5lKxEhUVlXZzw40dm2kyemKtRwKWiE0D4QyRCitNdAlne7CB8C3P/Zzu4DixBDMNRkVnilSYKJZihHscxrvLMM5dirE6TXCX4WV3OWd/cJYREO5uEo/wtjLIO4djo7uaA4NrecZFZ4pUGCWOwwiPOGxrpQfCdxvIkLzvR3x18Krgr4W6qvoMg8aGMGFhUUhLy8Tt2/fwyy/XMXv2HHh59cOFCxc5X3/jxj/Yvn03Vq5cjbt3c0iHsIYi5ZgiQOgCJfRhJWKrpkBIwSAZEX3wQJ8vWFlpX1AxFZdhWOy4jKJax2U4i/TmMZX1vktqL+XnF5iNlbCVvtt/zSh6gg2EC0TmgXCBCXMZH8ORUQ8JxjaXsmBwuFHEhI8oAVPEcox11wOhsWhApLuH043GRWkgjGgjQ0ALGW938GMjIJwlUmGcWIIRHhQQbm4pYeImRnnE4bj8F9y+fk/w10NdVH2GQY2GDXi3bt2Fl5cXJk+egq+//g4ajRbff38ZPj6zMWDAQFy8+Bs0Gi0uXbrC3Cc0NBKjR4/FX3/dF/zvUldFyjFFgNAFSujDSsRWTYCwrkZK2EOG+4JCduhycvJ54jLYXUW+uIy60FWkzWPsDSr1WYWFRQAcF41iODa622BkdJ1HAt5zMw+EM9xU+ISnSzjLCAhf8ogziJiIxqtGZjBvipSYKJZhpHusSSBkwaFYijd4gHBXk3hEtJVhg5jbHdwgTsIio3HRl8UyBgZHeMRhQ3MKCLc0VGKERxwuf39b8NdDXVR9h0FDM5j58xchKkqC69fvYNiw4Zg27XVmp/DChUuYMWMW+vXrj0mTXsamTVtx714efvvtBtau3YDRo8fg+nXiNlpTkXJMESB0gRL6sBJxVbNICaLiYsrYpLjYeY1NDOMyqK6i5bgMqqvoHCOZdeEa13XRe69FRbWPlbBWsWOOM0AY0JQNhO+6JZoHQpEK7/N0CWeJFCwgHEkDoTsVMTHLYFSUAjM5JrrLMMzDOiCcLJZhhgkgDG/D3x1cL1LDxwAIp4oULBgc4RGHNc0oIFzyCPVn//7zQPDXRF1TfYdBQ6WmHseUKa8wXcHLl69j8OAhmD79TXzzDTUq+v33l7F16w4sWbIU//6bDY2GMp/57LOdOHPma8H/DnVZpBxTBAhdoIQ+rERcWRNOX18jJfiUnW2bfUGhZV1cRiVPXIb9u4pZWbk2jzwg4qq0tEyQa/xt0lWDsVElgprrgXCOWwJmWQDCmW4qrDbqEs40AsJRHhIM9YjGaHEcxwhmmkiBie4yjHWXWA2EU3n2BykgVCC0tYIXCFcbjItO15nIGAPhqqYS+DVKwASPOIxsEOeQ8+VKIjCo16pVazB06PNYsWIl6/ZLl65g0CBvzJr1Fi5cuMS53927Oaz/Jaq5SDmmCBC6QAl9WIm4sgSExEVUr9zcfFRV2X9fUEhRXUXa2KbE4XEZbPMY20UeELF/xvRYsS1jJaqjgNb6sVG/pnogfMcKIJwhUuHjZvstAuFL7rGciIlZIhUmiWWY6C7DcPdYq4FwutHIKbND2Dgee1vG8wLhUl3cxAyRCiN5YHCERxw+aizFjkYqjPCIw6iGEgvni8Cioeo7DBqbyKSmHseQIUMxevRYZkeQHiX94YfLGDhwEKZMeRU//fQ7cx9iHmNbkXJMESB0gRL6sBJxZQ4I9SOiBAYLCuh9wfJ6+8bMOC6jvLycp6tYpesqVj8ugzKPqSLmMXaUIXALORocMyqDEz2xroEKb1sJhLPEKnwqUpsFwjHuEg7AvSKiRkXH68ZFrQHCCWKpSSDc2Tgee5pzgXC9SI133ChH0fFiGUa5SzDCPY6SARAubyTFykfiMcIjDmMaS4y69qbjaFzNOKq6ckYYvHbtNubPX4gBAwbA29sbGzZssdh1u3DhIvr06YPMzDM1/r6+voE4f/4HaDRaHDt2An369MHy5Svwxx/ULiANhefOfYdFi5YIfp1cWaQcUwQIXaCEPqxEXJERUcuig9DJLhu/qh+Xwe16EPMY+4vucDsDcF9I+N3AaVTnMloNIJwhUmGRSJ9L6OMRzwHCUe7smAnaSGaSuxyjdeOi1gDhZLGcd3/QR5SAnY3i4d9UyQHCNSI1ZolUmCyWsx5rrLsUo90lGOkeh5fc47DkESle95BihEccxjWTmjxf1TeOct3sUmeEQY1Gi5kzfbBs2QrcuaPBpUtXMGHCROzdG2by6+/c0WDixEnw9PSsMRBmZp7BqFGj8c47c/HDD79Ao9Hi0KE09OrVC6tXr8WNG/9Ao2GbzvD9N5FtRMoxRYDQBUrow0rElXGHkB4RJTDoOvuCwl7DPJ64DHbXgwbHioqKet31sKfoWAln6nDTY6N09MSaagKhj0jJAOEMMbdDOMpDgtcNQG6yWI5J7jozGd24qDVAOE0kh4+RKQ2tHY2V8G2i4gDhCrdEvCpWmHcudZdilruE6R5O6RBf7WtoaBxlfsTb9IcxdUnOCoMXL/4GT09PXLlyk7lNrT6I4cNfMnmfFStWYtcu/2oBIR/IKRSJeO216ZgzZy4TI6FWH0Lv3r2xfv0mBgqJ7C9SjikChC5QQh9WIq4MgZDsC+pVH/YFhVZurpbpJJaXV5jpepShuLhE90a2bsRlOJP0sRJlgj8XQ8WMzGBFT6xpoMJb1QDCGSIVPtB1Cd8QyXmBcIpYDh9RAl7TGclMcpdjnLuUgUFLQDhOLMXrJsZF6Q7hzkYJHCB8x02J8WLze4mGWYej3SX4cFyaTa+vNR/GsLNLnctl2FjOCoMaDdWVGzTIm3XbN99chKenJ27e/Jfz9QpFIqZPfxP//ZdrNRDSO4P37+fjxo2/WX8mkcRj6tRpmDt3Pn755To0Gi1Uqv3o3r07EhIOCH596otIOaYIELpACX1YibjKzqZHRElHhhY9vuhM3RRXU3Z2HioqqF02Y2OT7Oxc3RvZQoM3ssZxGXXnjayQEiJWwlp9E38Fwc1V8NeZyqxuoMJbOhdRa4FwTgPzQDjeXYpZIhUzKjrJXY4RBt1BCghjTQLbJLEMb5gFQiW2PcIGwnUitUkYNARAemx0VCMJDkf/5NBrzz+CamofWPgRVGeGQY1GC6UyCcOGDWfddunSFXh6euLXX/9g3f7995cxbNhwXL5MgZs5ILx9+z+cPXuB+e+7d3OwZMlSfPjhx7h27S/W10ZFSTBy5CgsXrwUv//+JzQaLU6dOiv4talPIuWYIkDoAiX0YSXiKiuL7AsaiuwL2l+1MY+xFJdhepeq/oE9HStRUOCc484aTTYCWiUiuLkSwc1rBoQzRCosFyXgTZEco9y5QDjKXYIpOiMZZlzUw3ogNLc/SAPhFo9EFhB+JEo0C4Aveeg19XElrlz6W/CfBS22y7A1+8D279w7OwxqNFokJ6fC25u/Q/jnn3eZ2/7++wEmTZqMAwdSmNvMAeG1a7fx7rvv4ciRDGg0VHdw27ZdmDRpMjZt+owxjqG1cOH76NmzJ2bO9GF9X2NHUiL7iJRjigChC5TQh5WIqwcP8kD9wqWgkALDbNS3sVGyL+gY0W6tlHmM7d5A1iwug+oqupqJDR0r8fDhQ+TlFQj+fMwp+qUMpkv4SQMVfGoAhG+L4imXURNAOMGgOzjGwEyG1ktmgJDKH+TfH6SBcKO7mj0uKlaaBEBDrZqcDo2m7vw7q+/cF5np3D/k7dzX9IzVBRjUaLT48cdf4enpiatXbzG3qdUHOV3Dkye/Qu/efTBgwABGnp6e8PLywqefruc87vffX8a7776HSZMmo3v37ti7NxwajRabN2/DhAkTsWXLdtZI6vbtu/HRR6vImKhAIuWYIkDoAiX0YSWypHxoNHk65aK+gGJurpbZFyRjh/YTPb7o6O4rtUvFtvO3ZVyGMyk72zDH0flfy/+TX2GiJ1Y1UNYICGeIlHjTLR6jeYBwrLuUgUFjMxlLQDhOLMVrZsZFfUQJ2NFIyYmbGCU2DYEvecRhZEMJEoN/FPza21Lczj3/GatOZEZdgUFab7wxA0uWLMPt2//hp59+x4QJE7F7d4DF+1naITx27AR69+4Nb29vJCcfYW7fsGELJkyYiK1bd+Dy5Wv49tufMGXKqzh4MI35GuIm6liRckwRIHSBEvqwEtVU+dDDIhcU9bAo/BuT6orsC9pfWVk5KCsr140vFgn+fPTPq7rjcc7t0OhMsRLWih4b3dlYiZUNlJhVAyCcLlLiFTcFxrhLOd1BelR0kruclT3IyN00EL4slmG6mXFRH7cEzv7gKlGiWRic0jEeP1/4S/Dr7ihZe8YkEgnmz5+Pbdu2QSqV4/jxk/j11+t1Kjj96tVbWLRoCby9vTF48BBs3ryNGdX08vKCSrWf9358QHj/fj4Dc1JpPJYv/wjvvTcfr746DcnJqczXrFu3ESNGjMLgwUMwePBgrF69lvUYQl+T+iZSjikChC5QQh9WInuo7nYVyb6g/WXOPMaZZb1Do3OEhDtjrIS1ih6ejp2NVfhYB4QzqgGEb4qUGCOW4GWRHGONgHC8AQxOcqd2DKsDhFMs7A/6uCVw9gfniZUmYXD5mDTcu5cl+PV2FhmaRx05koqFCxdi/Pjx6NmzJzw9PeHp6Ym+ffti8uQpWLx4KXbvDuDszLmiaIj8558sVocvI+MU5syZi1dfnYaUlHRoNBT0paYeR0yMjLWXSDqDwoiUY4oAoQuU0IeVyJFy3q4i2Rd0jPSjuJUulSvIdmikOh6m4jIcYbpBd7lLS50rVsJafS35FbuaKPFRAyVmVhMIXxZTXb+JIinGGQDhGHcJCwZNjYsOc4/FcCMgpE1gpooUZvcHfdwSsFHMBsJJYikHBEc8EgfZrm8Fv851QRpNHu7ezcYPP/yClJR07NsXgdWr12LWrLcwatRonDjxpRP8brOfaBi8dOkK5s6djxkzZmHJkqXMn6elZWL27Hfx+utvICPjFG7c+Bu3bt1lPQaBQeFEyjFFgNAFSujDSuQsEq6rSDtcUpDi/DtWdVVarX3MY5xZNY/LqDks62Ml6m6XW6PJhl/rRHzYQIkZIqXVMDhVpGAgb5yI6gjyjYryZQ+ygNAjlmMCM0ocZ3F/cJYbO5B+jUjNgcFJbRX4/uwtwa9xXRD1+6B+jjnev5/PjHh+++1PGDBgIObNW4D16zdh6NDnMXfufOZrU1Mz4OPzNp5//gV0794dSmWS4M+fiBIpxxQBQhcooQ8rkbPLvl1FupNSnyBFCOnNY0oFfy7OIr3pBn/uW03iMvSxEs6zl1lTRQ1Lx7IG8Zgh0nUJLeh1UTxeEuvBbqxYwnQIxxkYydAa6R7HC4Qvd1Bg8agUDshNFMvwurlxUVECJrrJWED4gSiB9Rjvv5iCu3fJiKg1qq8weP06ewT2xo1/MG3a69i0aSs0Gi3+/X97Zx4U1dnv+ZLkXXLvvDV3+eNOTU29U3dqptsFaEBBkR2VTQIom6gkKIoSN7wkGCWokahxN2o0GgVRBBRcMHGNGqOivMqiqCCCyGZDHxGhE5OYxe/80faxWxCXYJ/u099P1acST2/nHHiQr7/neX537mHkyGAolUqMGxcrPu/kybPYsiXzmesSqTQS08BAKAOkHqzUkn31qmJzsxobN25Ea2sr1wu+Rs118xhz9tXaZfwgTnnu7DTvthIv6rmt15D45g6M/1suIp9TJdSvGzQMdsNttmHY46meT1cH/d/IhPeb3QfCUf87Gwke+7pu/mKzHZE9BMJgm+3wttlqFAgjbLbrpoj+aSu++Oi85PfUUtT9TJf67xfTu3lzBuLjJxs1ni8uLsfw4SPEpvULF6Zj4sRJyM0tgJ2dHWbOnN3tlFBOEzUPiWlgIJQBUg9WKkd7ripWVFxHaGgo7O3tUVZWJvkvP3L1yeYxjyxq8xhz9t69F9vKv2tV0fLWawrCPUz91xyM+tOO51YHA2267hY63GYbfG22wf+pMBj4xpPNZjy6CYTh/ycHk4buNQ6Eb2ztcf3gqD474PmGblqpPgzO7ZMLT5ut8P+X7bjwTa3k99NStNYweOXKDQwZ4gqlUomUlLliKCwuLkNwcAhOnSpCbm4B3ntvBk6cOPO4oX0QlEol/P0DrGJzHUuUmAYGQhkg9WCl1mQnjh49CRcXF3h5eaO4uASWtAOqJalvdyC3zWPMTcP73NHx/VNb+XdXVbSMdhl6J9nuRnCfrB7DYIjBusEuFUKbbV3CYMAbmWLDes9uAmG0MhcTBucbBcJhNtsQ9oz1g5F9dsLr8TpDX4NAmNQnBxMH7UVzoyD5fbQUrTUM6k1JmQulUonhw0cgOXkOiovLIAhanD59Hg0NGsyYkYTFi5ehsVFAS8t9JCZOQ0bGThw8eFTyc6fdS0wDA6EMkHqwUutx06at6NevH8aNi+3mX1Mtt1WGuanfPMYS2x1Ykk/aSvza431+1XYZ5lBVnBtyBCP7bO9x3aCHTddQF9k3F4FvZXbZWVTXe/DJzqNe3UwbHTsgD3Eu+fD+y5NAGGSTidHdBMLoPtnwfWOb+DzDQPix01eS3z9L0prDoH56Z0XFTUyePAUJCYlwc3NHUlIyysquQxC0qKlpxJAhrti+fRcEQYvs7D3w9vYRQ6MgsM+gOUpMAwOhDJB6sFLrUKPpRGjoKCxc+AnU6vaXeK3h9FOGxef54IFu85iffuLmMa/T3moroW+X0VOD8CdVxdffLuNpN6YUIegZgTCiz0742HQNdEvfO4W7d9sR9E/buw2Ew9540pewu3WE4+33IM45HyP+9qRdxNs2WYjoZv2g3xvGLSX0gXCeTR5qy5sl/z6xFK05DBp669YdJCenYNOmrcjPPwAXl8FITp6DkpIKNDe3ITR0FPz8/DF+/DtQqVTIzd0r+TnTniWmgYFQBkg9WCl9dRkU9ba1yWuHS3NWH7pf52ZIT9plPDBZu4zuPJZT+cxA6Gdj3DZi2H/PwOmvq8XXBv5T1wqh4XRRvU+vI3zXMR/vOu9B4L9n6YKeTffrB0c+3jDG0Hf/Xy5SbfKw8F8KJP8+sRStNQx+990FVFbWQRCMK3tHjpyEo6MjKipuIi9vH4YMcUVKylzcvq1GUdElpKUtRErKXBw69I34WlYGzVdiGhgIZYDUg5XS3vf1tsowN3Wbx/zKzWNMoDmE7pdvl/HDc9tlPMv62lYE9snsEgaD+2wXA5zbm1sw0bXrWr2AbqaMGjaq1/v0OsK4QQWYMHgvQv5nNjzf3IoRNhkIfWq6aNjjTWQMw+Cyqd+i8nwjUm3ysCXgpOTfK+au7meidYbB5OQ56N+/P6KixuDQoeNobm4zenzevDQsWJAOQdBi48YtGDx4CObNm4+qqjqj5zEMmr/ENDAQygCpByulplVeVUVuHmMa29ru45dffjHrthK6dhnaHttl/P67rl3GTz89NKgqdvb4vm+/ZbypzCiDdYMef/4SW9KLu31dQDcVQt+nqoPdrSOcPGQfJrruw6i/7xLXDxo2pI8w2ETG882tGPbPGfgmvxJ377bj2pl6pNrk4eKem5J/PcxZaw6Dt2+r4es7HEqlEl5e3ujfvz9mz34fmZnZ4nN2796H4OC3cfu2GoKgxfr1m2Bra4sFC9LR3NzGEGhBEtPAQCgDpB6slJqHlldV5OYxpvFJ+47fcf9+z+HJXH1SVXz5dhnR/5HzJBDaZMP7cRgM+h9ZuFzc8MzPfLpC6P9GZpcw2N06wkTPQsQ5FyD8P3fB8w3j9YPRfbLhY7CJzBhlHupqWsXPvPrtbaS9tUfy+23OWnMY1Ae5ioqbePvtUMTGxuGjjxZg5szZ8PT0QlxcPI4fPw1B0GLy5ClISkoWX/vZZxtx9uxFya+BvpzENDAQygCpByul5q/5VRUfPPgRADePed0aVmDNYdfP3lZXVezssV1GosMBMRCOsNkGtze34P2ww3je97z/W5nwNQiEw7uZLqrXKBB6HEDswD2IUuTCy2Yrwh6vHxzTJxsjDDaRWfTuiS6fefVkHVY7Hpb8vpqr1hwG9ba03IcgaFFSUgE/P39MnjwFubkFKCoqwZgxYxEUFIy4uIn44ottiI+fjPLySqPXs+G8ZUlMAwOhDJB6sFJquUpTVdSvY/vhB24e8zrt6HixthJyVd8uI3XkMUT1yUboX3fA662tOJ5XI/798XS7jI6OJ+0yDANhd5vJPGsdYaLnfsQOzEdM/90IsMkU+w8GPd5ExvetDHy942q353z5m1s4vLBU8ntnjup+NnGqoyA8CXXFxWUYPnwEYmLGo6joEjSaTnz99XHExcWjf//+UCqVRlNJqeVJTAMDoQyQerBSKk97v6p47959cfMYc13HJhe///6HXmkrIQfXTzuD6Ld2IeL/7kJNpRptbbp2GVptz+0y/AwCoV8P1cGn1xG+56WrEI6324ORNtsxqs8OhNpkwfONrQj/zxzcrFQ/81xvljbjTj0b0T8tw2BX9aHw3LmL8PUdjpiY8Th58qz4eHb2HkyfPgslJRWSnyt9dYlpYCCUAVIPVkqty1erKp49W4S4uDi0tLRw85jXrH467utsK2FJHtl5DSunnX6h5xq2yxjx1wwxEA7roTr49DrCab6FiHXag/H2uxFikyXuKJoaeRSCYF7reC1BhsFnqw+F3313AT4+vnj33Qk4duxb8XF9z1z9NFNqeRLTwEAoA6QerJRSLYyDonFY3LUrD7a2toiKisKdOy2S/4IpZ3/66WcA4HTcXnDEX3SB8HnTRZ9eRzg74BDeHVSAqL/nILRPFob9aRv2bb4s+fVYotYeBp+1G6jhcX0oPHnyLHx9hyMyMhrffXdB8nOnvSMxDQyEMkDqwUop7d7W1g4sWbIcCoUCs2YloalJA3PZ1EZuWkJbCUtz+ONA2F3vwZ7WEc4OOoQ45714+60svP1GFjRN3+P333VrOXVrFV+sXYa1a+1h0LCqd+PGbVRV1eHGjdvdPlcfEL/++jgiI6Nx69Ydyc+f9o7ENDAQygCpByultHtnzpwNhUKBVavWPeNfup9VVTTfVhnmqBzaSpijw/+sC4Td9R7saR3hjICDGO+4ByF/ycLiyG+eapfx6wu3y5D6+qXUXMNgdXU94uMnw8nJCc7OzkhNXSBOy3zaY8e+RWjoKKhUKri7e2DVqs9e+HMMdwJduDAd4eGRGDhwEAIDR2L9+k3iY4Y/V/X/rz8f7iYqD4lpYCCUAVIPVkppVzWaTiQlJaOg4OArvof5tcowR9vbn7SV4NrM3nXYn7e90FTRp9cRzgg6iDED8jDqn3fim12V3b73i7TLePToEX799Vf8/PNDPHjwI7TaH3D/fifa2qS/N69Tcw2DgqBFdHQMpk+fhcZGAeXllfD3D8DatRu6PO/SpQrY29sjKysHGk0nzp8vhbOzM3bv3vdSnzdv3nwMHeqGvLx9yMjYgdTUBejbty+WL1/d489eqe8T7T2JaWAglAFSD1ZKqSmVplWGOdrRobXqthKvW98/vXgYNFxHOCOwEKP+vgvR/5GDV9lERt8u4/vvH+DHH3/Gw4e/4LffjKuK+nYZP/74s6yqiuYcBsvKrkOhUKCy8pZ4LDe3AB4enl2eO3fuR5g2babRsZKSq6iqquv2vQ2refoKX0nJVYSGjhIbzQuCFrdvq7F27QYolUrs2/eV5PeEvn6JaWAglAFSD1ZKqbloPVVFrVbXVuLhQ7aVeF2+SiD0ePNLTA8qxMh/zUKcY36vnk9bW3s3VcWu7TJ+/fW3x1XFnwyqiub/DwbmHAYFQYu9ew9i0CBno2MXLpRBoVB0WbMXGjoK6elLkZg4Hc7Ozhgxwg9ffrn9me99+vR5fPbZRqNj3357Hk5OA3HixBmj49XV9QgPj8SHH6ZCo+lkRVDmEtPAQCgDpB6slFJzV15VRbaVMI3D/vJim8k8vY5wqt9++P0pE++9fcBk52rYLuPHH396XFX8zejvSl1VUb+xzYPHG9uYR1XR3MOgIGixc2ce3N09jI6Vl1dCoVDg2rUao+O+vsOgUjngwIHDUKvbcfz4aTg4OD5zymh+/gH4+Phi5cq1SEhIREnJVZw6dQ5OTk7Iy9O9xrCKOH78O/jggw8lvyf09UtMAwOhDJB6sFJKLVnLqiqyrYTpHPbXlw+E3m9uRazLHgT+t+1ITToq+TXcvatbZ6rb2OZHg41tjKuKv/32m8HGNj+go0NrsqqiJYRBQdAiP78Qzs7dVwjr6tRGx/39AzB9+iyjY3PmpGLKlPe6fe9bt+5g3rz5cHJyQv/+/dHYKEAQtEhImApXV1ecOfMP8bm1tU0YNSocn3++RfJ7Ql+/xDQwEMoAqQcrpVSOmldVsa2tHQ8fsq2Eqfz554cI+c9s+P7LNnj/bRu8/mkrvP66FZ5/3grPP22F15tb4f3m1m5DYdjfdyLo37dj5/YSya+j5+8pfVXxB6OqouEU1NfdLsNSwqAgaFFaeg0KhcKo9UNubkGXqqEgaDFlyntISEg0OvbBBx92OSYITyp/KSlz4eLighEj/LBmzXoIghbV1Q2IihoDR0dHzJs3H0uWLEdo6CiMHh0h+f2gppGYBgZCGSD1YKWUWpumrSreu3ffoK2EVvIgIWdfJngLwj003NagsqIJF8/V4fTRahzJv44x/XLh/W9bUX3jjuTX86q2t3e8QLuM37ppl/HiVUVLCoN6IyKikJg4HfX1Lbh8uQr+/gFYunRFl+cdOXIS/fr1w86dedBoOnH8+GmoVA49bgRz8uRZlJRUICVlHvz8AsQ1ha2tHZg79yOEhY3G2LHjMW9emvgaw16FVJ4S08BAKAOknVrjAQAAHnxJREFUHqyUUqqz96uK7e2d+O03tpUwhW1t98XplH8keC9POgXV3z6X/Hpe1z16srHNTy/cLqOy8gYaGprE97HEMCgIugbxCQmJcHZ2hovLYMyfv0gMZSqVCtnZu8XnFhYeQUhIGBwcHOHt7YMtWzK7fc+nN4UpL6/E7Nnvw88vABs2fCEeb23tMOp5+Kz+h1ReEtPAQCgDpB6slFLas4ZB8cWrikePHkdYWBhaWlosYpdIS9awCvtHp0QeOXANg//XFsmvyfT30Lhdxi+//ILff/8djY2NUCgUUCgUcHNzQ0zMWHzwwYdYv34TCgsPo7y8kpWux+rDYXl5JZKSkjFihB9SUxcgLi4eZWXXuzyPyl9iGhgIZYDUg5VSSl/d7oPi9u070L9/f0yYMAEtLRrJf9mXs+3tHWIVtjd6+dXcVCPAMUvy6zIX29racelSKfLydmP58hVITJyGwMCRsLOzE4PigAEDEBkZLfuql+FOoYZ2F/BKSq4iJWUehg8fgdjYOMnPnUojMQ0MhDJA6sFKLcPq6gb4+Pji6NFTz33unj374eXl0+X4mjXr4ebmDnt7e0RFjUFJSYXk10XlpUbTiU8/XQmFQoH3358DtboN5rCpjVy9f78Tv//+O3799beXWv/2PKfFFEp+bebm09NEW1s7UFFxE4cOHcemTV9i3bqNsq586cOuWt2OM2eKcfToKZw5U9zjaxoaNEbN7FlJtT6JaWAglAFSD1Zq/p44cQY+Pr5QKBQ9BkK1uh1r1qxHv3794OnpZfRYVlYO3NzcUVxcjqamu0hL+xj+/gGy/gWGmt60tI+hUCiwcuXaHr63LKtVhrna0aEVd9Hs7Sm5eZmlkl+fOWmpawZ7S31lsL6+BeHhEQgNDYOnpxcGDhyE9PSlaG5ue+H3oNYlMQ0MhDJA6sFKzdusrBx4eHgiN7fguYEwOjoGsbFxWLx4WZdAGB4eiZUr14p/Vqvb4eDg+EIVR0pf1PT0pcjJyX/F15tXqwxztrPzezx69AgPH/7yWt6/tbVN8ms0F609DOptahIQHPw2Jk6chJqaRty4cRs+Pr4IDR2F2tpmyc+PmqfENDAQygCpBys1b6uq6sSpOs8LhNeu1UAQtNi+fVeXQOjkNBD79n1tdCw4OMRoFzhKzVdWFfVqtT/g0aNH+Pnnh5Kfi9xlGHziqVNFCAsbjaYmXdP5GTNmwd8/ACUlV7Fhwxc4fPiE5OdIzU9iGhgIZYDUg5Vajs8LhHq7C4T9+vXDkSMnjY5FRERh+fLVkl8Xpa+udVUVf/jhAQDgxx9/lvxc5C7DoLEHDx6Fl5cPamoakZg4DX5+/igvr4Ra3Y6YmPFITk6BIHAHUWosMQ0MhDJA6sFKLcc/EggdHR2xf/8ho2O6CuFmya+L0tejvKqKDx78BAB48OBHyc9F7uq+Z6w32Og3fzFc93fqVBHc3T0QFBSMwMCRqKy8JT4WEzMe6elLJT9van4S08BAKAOkHqzUcvwjgTA8PAKrV68T/6xfQ8hpPtT6tLyq4k8//QwA+P77B5Kfi9y19jCoD4FXrtzAggXpWLgwHeXllRAELT76aAGUSiW2bMkUlzIcO/YtXF2HYs+e/ZKfOzU/iWlgIJQBUg9Wajn+kUCYkbEDbm7uKCoqEXcZ9fUdJvu+WZS+uIZB0Xyqij///BCPHj2CVvuD5GFJ7lp7GNRbXl6JQYOcERo6Co6OjvD09MLhwyfQ1CRg2rSZUKlUCA4OwYQJ8Rg0yBlLl66Q/JypeUpMAwOhDJB6sFLL8elAqFKpkJ29u8vzuguEGk0nPvtsI7y8fKBSOWDMmLEoKbkq+TVRahmaPii2tbXj4cNf8OjRI3R0fC95WJK71h4GDaeHbt6cgXnz0qDRdKK5uQ1hYaPh5eWNY8e+hSBokZmZjXnz0rBkyXIUFBzs9j0oFQQGQlPBQCgDpB6slFJKX9XXU1Vsa7uPX375Fb///gj372slD0tyV/e1k/p7STr1Qe7ixSvIycnH7NnvY82a9eLjanU7goKC4eXlg5Mnz/b4HpQaSkwDA6EMkHqwUkopfR2+WlC8fr0KU6ZMQU1NDdrbOyUPS3LX2sOg3uPHT8PR0RHu7h5QKpWIjIxGU9Nd8fE7d+4hKCgYHh6e4o7V3FGUPk9iGhgIZYDUg5VSSqkpffamNhcvlsLDwxO+vr6oqamTPCzJXWsPg/pAV1/fipSUeVi79nPU1DRi5cq1CAgIRFJSMurrW8XnNzRo4O7ugYMHj0p+7tQyJKaBgVAGSD1YKZWj1dUN8PHx7XETnsLCwwgICIS9vT1GjPAzasvR2toBlUoFe3t7qFQq0YYGjeTXRuXp6dPn4ezsjICAQFRV1cJcNrWRq9YaBletWoeMjB3iny9cKMPo0RGIjo7B2bMXIQi6thMrVqxBYOBIzJ79vlGlkBuR0ZeRmAYGQhkg9WClVG6eOHEGPj6+Pe7KWlp6Dba2digoOAi1uh25uXthZ2eH69drIQhaFBeXYcCAAbhz557k10Pl74kTZ6BSqTB6dARqa5u7eY7ltcowZ601DKrV7ZgxYxZKS6+Jx06dKkJERBQGDBiA8+dLxeN37tzDsmWrEBwcghkzksQgqK8qcroofRGJaWAglAFSD1ZK5WRWVg48PDyRm1vQYyD85JNPMW5crNGx2Ng4cfv0zMxshISESX491Dr8/PMteO+9Ga9YgTa/Vhnmqu6+WGcYjI+fjIyMHWKQ++ab77BzZx4EQYtvvz2PgIBA+PoOR2OjIL6mqekuFi78BP7+Abh48Yrk10AtT2IaGAhlgNSDlVI5WVVVJ/5Ldk+BMD4+AWlpHxsdS0v7GPHxkyEIWqSkzIO/fwBCQsLg4uKCyMjoZ+6uR6l5yqoiw6DO6dNnYfDgIWKroYYGDWJixsPfPwC5uXshCFqcPHkWvr7D4e8fYDQttKFBg8uXqyS/BmqZEtPAQCgDpB6slMrVngJhTMx4LFmy3OjY4sXLEBMzHoKgC4ezZ7+P69dr0dQkYO3az6FSOfAXIyoTrauqaM1hcMaMJLi5uePGjdsQBN36QEHQ4h//uIzY2DiMGhWO3bv3QRB0VUMvLx+EhIRxSijtFYlpYCCUAVIPVkrlak+BcOLESZg/f5HRMV2FMOGZ7+fnF4BNm76U/LoofX3Kr6pozWFw2rSZUCqVWLv2c/GYRtMp9gy8cKEMMTHjEB4eITaYP3bsW6hUDoiMjJb8/KnlS0wDA6EMkHqwUipXewqE6elLERsbZ3QsNjYOixcvEx8/d+6i0eM+Pr5Gu/NRaj0aBkXLqSrqzs88K13V1fWIj58MJycnODs7IzV1wTN38NywYTO8vLzh4OCIwMAg7Nmz/7nvP378OwgMDMK0aTOhUjkgI2OnuEbVMBSeO3cR0dExiIiIwoEDhyEIWhw5chLFxWWS3yNq+RLTwEAoA6QerJTK1Z4C4aVLFbC1tUNu7l5xl1FbWztxjc3EiZMQGRmNqqo6NDe3YdmyVXBxGYza2ibJr4tS89I8g6I5h0FB0CI6OgbTp89CY6OA8vJK+PsHYO3aDV2eV1h45PH6vwoIghZ79uxH3759ceXKjWe+d1xcPHx9h6OpSbdBzPTps6BSqbBjR654TKPpFKeFfvfdBYwZMxaBgSNx+PAJ8X30oZHSV5WYBgZCGSD1YKVUrj4dCFUqFbKzd4t//uqrYwgKCoZK5QB//wAUFh4WH6utbUJSUjIGDx4ClUqFMWPGGm3JTil9ns+qKr7+6afmHgbLyq5DoVCgsvKWeCw3twAeHp5dnrtu3Ua4uAzGxYtXoNF0oqDgIGxt7XDtWk23793c3Ibly1ejvr7F6PjUqdPg6OiIXbv2iH0FDUPh8eOnERc3EVev3pT8/lD5SEwDA6EMkHqwUkoppab19VUVzT0MCoIWe/cexKBBzkbHLlwog0KhwK1bd4yOV1bWISAgEAqFAv369UO/fv2Qm1vwQp+j0XQaTUONj0/AwIGDkJe3D83NbRAEXRVQHwoNj0l9j6g8JKaBgVAGSD1YKaWUUvPwj21qYwlhUBC02LkzD+7uHkbHyssroVAoulT+KiqqMWPGLHz33QXcuXMPmZnZUKlUuHDhxdf46XcWFQQt3nknDi4uLsjPL8SdO/cgCAyA9PVJTAMDoQyQerBSSnVu2rQVcXHxOHTouNEvUJRSc7DnqqJO8w+DgqBFfn4hnJ27rxDW1amNjsfFxWPVqnVGx8aOHd+lj+rzNKwUjh07Hm5u7uIaaqnvB5WvxDQwEMoAqQcrpVRneHgklEol4uLixY0XDD116hyysnJQXl4p+blSSvUaVhWlPpcXs7T0GhQKhdgbUBB0awifrhoKghaBgSPx6acrjY69804cFi1a8tKfaxj+/P0DEBU1hoGQvlaJaWAglAFSD1ZKqW6tjbu7B4KCgrvd2EEQtAgJCYNSqcScOamyrCBWVzfAx8f3mTuzCoIWhYWHERAQCHt7e4wY4Yf9+w8ZPb5mzXq4ubnD3t4eUVFjxJ0RKaXGRkREITFxOurrW3D5chX8/QOwdOmKLs9bvHgZXFxccPbsRbS2dmD37n2wtbVDUdGlV/pcwwBYX98q+X2g8paYBgZCGSD1YKWUatHQoIG3tw+Sk+fA1dUVVVV1Ro8fPXoKffv2hbu7BzZu3CIeb23tgFrdbvEB8cSJM/Dx8e2xVUdp6TXY2tqhoOCg2KrDzs4O16/XQhC0yMrKgZubO4qLy9HUdBdpaR/D3z9A3LCCUvrEGzduIyEhEc7OznBxGYz58xeJP0cMd0RWq9uxdOkKeHl5w9HREW+/HYqvvjr2hz7b8OeVpf/souYtMQ0MhDJA6sFKKdXi8uUqBAYGYcWKNQgPj0ROTr74WGnpNcybNx9hYaMxcmQwsrP3vNB7trTcF7d1N+dQlJWVAw8PT+TmFvQYCD/55FOMGxdrdCw2Nk6saoSHR2LlyrXiY2p1OxwcHHusOFJKKZWvxDQwEMoAqQcrpVSLQ4e+QUhIGL766hjeeScOy5atEh9bs2Y9pk+fhfT0pQgICMQ333yH1tYOZGfvxoQJ8Zgy5T1kZOzosl28pVhVVSdOI+spEMbHJ3TZyCIt7WPEx0+GIGjh5DQQ+/Z9bfR4cHAINmz4QvJrpJRSanqJaWAglAFSD1ZKqa75c0zMeDQ0aB7v4LcQgqBFZeUthIdHYteuPVi+fDXCwyNx/PhpJCZOg7u7Bz7+eLE4NfKTTz4V+3jt3JmHTz9diXPnLmL//kMoKrr03M0bDPuBSWVPgTAmZjyWLFludGzx4mWIiRkPQdCiX79+OHLkpNHjERFRWL58teRfX0oppaaXmAYGQhkg9WCllGqRmDgNM2fOhiBokZIyFwkJUyEIWqxatQ6TJ09BY6OAqVOnISkpGcnJczB8+AgUFh4WX5+VlQNbWzvs3r0PgqBFauoCKJVKTJo0BVFRY6BSqRAWNhrnz5cafW51dQOqq+uNjj2vJ9jrDI09BcKJEydh/vxFRsd0FcIECIIWjo6OXTaZ0VUIN0v+9aWUUmp6iWlgIJQBUg9WSqkWvr7DxOpXTk4+vL190NCggavrUBw4oAt+gYEjsWjREgQHh2DGjFloaNBAEJ4ENA8PTyxevAyCoEVCwlQ4ODhi5848tLZ2oLT0GoYMccVHHy0Qm0FnZeVgwoR4DBw4CIMGOSMpKVnchr6mphHl5ZVG4a+7oKivKra03O+V5tI9BcL09KWIjY0zOhYbGydec3h4BFavXic+pl9DePjwCcm/vpRSSk0vMQ0MhDJA6sFKqbWrVrfD3d0DW7ZkQhB0DaL79u2LtWs/R1BQMARBi6amu/Dw8MSyZasQEBCItLSPxQCm/6+bmzvS05dCEHThcdas/zL6nHfeiUN8fALU6nbs2/c13Nzc8dlnG1FVVYczZ4rFbeibm9tw/nwplEol8vMPiOcoCFqcPHkWly5VvFT4e5mpqD0FwkuXKmBrayc2s87N3QtbWzuUlFyFIGiRkbEDbm7uKCoqEXcZ9fUdxj5nlFJqpRLTwEAoA6QerJRauzdvNsLOzk7c5r28vBIODo7w8PBEVlYOBEGLf/zjMry8vLFhw2ZMnjwFEybEQxCehMHKyjoMGDAAO3fmoanpLtzc3LFmzXrxM1pbOxAdHYOkpGQIghZRUWMQHByCM2eKcfu2+vF73IJK5SD2F/P29sGKFWvEz1Cr2+HkNBCpqQtQXFwGT08vFBYexoYNm7FwYToKC4+gqUkQP/NVppY+HQgNt78XBC2++uoYgoKCoVI5wN8/wGjarEbTic8+2wgvLx+oVA4YM2asGBYppZRan8Q0MBDKAKkHK6VUi4qKatTWNkMQtKiursfUqdPE3TMFQTeN1M7ODoWFh7F9+y7069cPhYVHIAi6ADljxiy4urqipqYRFy9ewZAhrtixI1d8fVVVHUaODMbSpSvQ0KDBkCGu8PUdBlfXoVCpHODi4oIRI/ygVCrFlhdJSclGUzTXr98Ed3cP3L6txrlzF2Fra4vAwCB89NECxMVNhLOzM1avXmdUkbt8uQr5+Qdw4sQZ1NWpe7wHra0dvTLtlFJKKRUEBkJTwUAoA6QerJTS51tUVIIVK9agvLwSgqDFwoWfYMgQVwQHvy32J8zI2AFB0CI3twC+vsNw6NA34utPnz4PPz9/ZGZmo6KiGh4envjii20QBC2uX6/FqVPnsHNnHnbsyBUrhBkZOzBokDMEQYurV2/C29sHa9d+DkHQIj//APr27YvNmzPExtLz5y9C//790dgoPH5OIUJDRyE0NAyurkMxfPgI5OYWGF1XbW0zrl2ree71t7TcF/sqSv21oJRSahkS08BAKAOkHqyU0q7qQ9azbG3tQHFxGbKycrBt2w5cv14rPrZo0RK4u3vgzJli8Vh29m4EBATiwIHDuHPnHkaNCseUKe8ZveepU0XYs2e/OO3z0KHj8PLywYkTZ7B8+Wr4+PiK1b/Vq9fB1XWo0RTRr746Bnt7e9y4cRvl5ZVwd/cwmraamZmNQYOccfz4aQiCFleu3MCMGUnw9vaBra0dQkPDxKqnXq7/o5RS+qoS08BAKAOkHqyU0uf7MtMp6+rUuHChTNyFVBB0fQ6DgoJx4sQZCIIWmzZthY+PL1avXoeKimqsX78JTk4DsXDhJ+JrioouYcKEeEydOg0JCVPx2WcbIQi6DW6SkpIRERElnpsgaLF27efw8vJGdXUDNm/OgFKpxLx5acjO3o3i4jJUVdVhypT3MHv2+xAELT78MBWenl6orm5AeXklUlMXYOhQN5SVXYcgaHHx4hUkJEyFu7sH/P0DsGzZKtTXt0j+tTAXq6vrER8/GU5OTnB2dkZq6oJnBujt23dh+PARUKkcMGpUuBjK9V8/lUoFe3t7qFQqUcPvH0optUSJaWAglAFSD1ZK6aup0XS+VFBsbm4TA0Nrawc2bdoKX99hcHBwhL9/AJYvX43KylsQhCeVuUmTpkCpVGLRoiWoqqqDIGhRX9+K8PBIJCfPEc9DEHRrDqOjY1Bf34KkpGS4u3tg+vRZGDkyGC4ug+HkNBBKpRLjxsVCELSYMycVQUHBYnWzsvIWlixZjsuXq3D16k1EREQhISERZ84UY8OGzQgMDMKHH6ZKft/NxejoGEyfPguNjQLKyyvh7x+AtWs3dHnevn1fwdbWFvv3H0JLy33k5x+Avb09SkoqIAhaFBeXYcCAAWI7EkoplYvENDAQygCpByulVHprahq7PZ6cPAcqlQqnT58Xj924cRtDh7ph06atEIQngXD06Aj81399AEHQYvz4d5CYOE18TXNzG65evYlTp4pw6VIFBEFXgQwMDIKDgyMSEhJx6NA34lTZc+cuIjg4BMuXrxbfIzMzu0srDWu1rOw6FAqFGOAFQbd21MPDs8tzExOnibvL6o2NjROrwZmZ2QgJCZP8miiltLclpoGBUAZIPVgppdL4rGbyGk2nWC0KDn4bCxemG01FLC+vhK2tHQ4ePCoeU6vboVKpxArV4sXL4Oo61GhqYmHhYcyfvwiVlbdw7VoNamoa0dJyH3l5+zBx4iQ4OTnh009XilMVly5dAaVSiZCQMHzxxTbcvNmIpqa7kt83c3Dv3oPihj96L1wog0KhwK1bd4yOJyQkYu7cj4yOvfvuBEycOAmCoEVKyjz4+wcgJCQMLi4uiIyMxsmTZyW/Rkop/aMS08BAKAOkHqyUUvPy9m01Pv54MaZOnQZXV9dntosw3Pjm9m01QkPDxJBYW9uECRPiERMzDuvXb8KmTVsxcOAgTJo0BY2NAvLzCzFmzFhx11RB0GLBgnR4efngypUbYqg5c+YfmDv3I4wY4YeYmHG4cKFM8vtjDu7cmQd3dw+jY+XllVAoFF12bc3JyYejoyOOHfsWanU79u49CFtbW3Hqblrax5g9+31cv16LpiYBa9d+DpXKAZcvV0l+nZRS+kckpoGBUAZIPVgppeZleXklPDw8MXbseHGq6Ku0eygtvYaFCz9BaGgYQkNHYdWqdWK4vHSpAr6+w5CWthBFRSW4fLkKMTHjEBAQiDt37iEt7WNs2LAZanU76utbUFxchsGDhyA1dQHXugm6lh7Ozt1XCLsL8Bs3boGv73C4uLhg5szZSEpKxtSp0575/n5+Adi06UvJr5NSSv+IxDQwEMoAqQcrpdR8fNU+fxpN53NbZTzt118fR2RkNFQqFdzc3JGQMFVslbF48TJ4eHji+PHT0Gg6UVVVhyFDXJGSMu+lP0eOlpZeg0KhwI0bt8VjubkFXaqGgqBFVVUdSkuvGR0LCxstTu9NT1+Kc+cuGj3u4+Mr9rWklFJLlZgGBkIZIPVgpZTKU42mE2p1+ws1lK+tbUJtbZP45zt37iElZS5cXFwwaJAzRo4MRnz8ZJSUXJX8uszFiIgoJCZOR319Cy5froK/fwCWLl3R5Xm5uQUYOtQNFRXVaGq6iw0bvoCT00BUV9dDELSYOHESIiOjUVVVh+bmNixbtgouLoONvh6UUmqJEtPAQCgDpB6slFLr9EVaZqjV7bhwoQzHj5/GzZu6nVBftYopN2/cuI2EhEQ4OzvDxWUw5s9fJFZPVSoVsrN3i8/99NOVcHUdCgcHR0RFjTGqCNbWNiEpKRmDBw+BSqXCmDFjcf58qeTXRymlf1RiGhgIZYDUg5VSSruTwY9SSukfkZgGBkIZIPVgpZTSntRoOhkOKaWUvrTENDAQygCpByullFJKKaW9LTENDIQyQOrBSimllFJKaW9LTAMDoQyQerBSSimllFLa2xLTwEAoA6QerJRSSimllPa2xDQwEMoAqQcrpZRSSimlvS0xDQyEMkDqwUoppZRSSmlvS0wDA6EMkHqwUkoppZRS2tsS08BAKAOkHqyUUkoppZT2tsQ0MBDKAKkHK6WUUkoppb0tMQ0MhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiVwkBICCGEEEIIIVYKAyEhhBBCCCGEWCkMhIQQQgghhBBipTAQEkIIIYQQQoiV8v8B8Fjpz+dtmHoAAAAASUVORK5CYII=\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(9,6))\n",
    "ax  = fig.gca(projection='3d')\n",
    "ax.plot_trisurf(HTest['Moneyness'], HTest['T'], abs(HTest['PError']), cmap=cm.plasma, linewidth=0.1)\n",
    "\n",
    "ax.set_xlabel('Moneyness')\n",
    "ax.set_ylabel('Time to Maturity')\n",
    "ax.set_zlabel('Error')\n",
    "\n",
    "ax.dist=12\n",
    "ax.view_init(30, 112.5)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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