Ejercicio_06.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Enunciado\n",
    "Dado un proyecto con los datos que se muestran en la tabla siguiente, se pide:\n",
    "   1. Dibujar el diagrama Pert y determinar el camino crítico.\n",
    "   2. Probabilidad de terminar el proyecto antes de 9 periodos.\n",
    "   3. Reducir la duración del proyecto hasta 10 periodos con el mínimo incremento posible de coste.\n",
    "   4. Si el número máximo de recursos durante las 6 primeras semanas es 4, determinar si será posible realizar el proyecto en el tiempo obtenido en el apartado 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:100% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>precedentes</th>\n",
       "      <th>duracion</th>\n",
       "      <th>desviacion</th>\n",
       "      <th>cur</th>\n",
       "      <th>recursos</th>\n",
       "      <th>duracion_tope</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actividad</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>---</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>---</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>B</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>A</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>-10</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>A</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>E</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>C,D</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-20</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H</th>\n",
       "      <td>C,D</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I</th>\n",
       "      <td>F,G,H</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td>F,G</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>K</th>\n",
       "      <td>F,G</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          precedentes  duracion  desviacion  cur  recursos  duracion_tope\n",
       "actividad                                                                \n",
       "A                ---          3           2    5         1              1\n",
       "B                ---          2           1    5         1              1\n",
       "C                B            4           2   25         1              2\n",
       "D                A            2           1  -10         2              1\n",
       "E                A            4           0    1         1              4\n",
       "F                E            3           1    5         1              2\n",
       "G                C,D          1           0  -20         2              1\n",
       "H                C,D          5           3    1         1              2\n",
       "I               F,G,H         1           0    1         1              1\n",
       "J               F,G           2           0   -1         1              2\n",
       "K               F,G           1           0    5         2              1"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Alargamos el ancho de las celdas al 100%\n",
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "datos_enunciado= pd.DataFrame([\n",
    "#actividad, precedentes, duracion, desviacion,  cur, recursos, duracion_tope\n",
    "  (   'A',     '--- ',       3,         2,        5,      1,       1  ),\n",
    "  (   'B',     '--- ',       2,         1,        5,      1,       1  ),\n",
    "  (   'C',     'B   ',       4,         2,       25,      1,       2  ),\n",
    "  (   'D',     'A   ',       2,         1,      -10,      2,       1  ),\n",
    "  (   'E',     'A   ',       4,         0,        1,      1,       4  ),\n",
    "  (   'F',     'E   ',       3,         1,        5,      1,       2  ),\n",
    "  (   'G',     'C,D ',       1,         0,      -20,      2,       1  ),\n",
    "  (   'H',     'C,D ',       5,         3,        1,      1,       2  ),\n",
    "  (   'I',     'F,G,H',      1,         0,        1,      1,       1  ),\n",
    "  (   'J',     'F,G  ',      2,         0,       -1,      1,       2 ),\n",
    "  (   'K',     'F,G  ',      1,         0,        5,      2,       1  ),\n",
    "], columns=['actividad', 'precedentes', 'duracion', 'desviacion', 'cur', 'recursos', 'duracion_tope']).set_index('actividad')\n",
    "datos_enunciado"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solución\n",
    "### Apartado 1\n",
    "> Dibujar el diagrama Pert y determinar el camino crítico."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pmule import calcula_encadenamientos, GrafoProyecto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>actividad</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "      <th>F</th>\n",
       "      <th>G</th>\n",
       "      <th>H</th>\n",
       "      <th>I</th>\n",
       "      <th>J</th>\n",
       "      <th>K</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actividad</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td></td>\n",
       "      <td>True</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>True</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>True</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>True</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>K</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "actividad     A     B     C     D     E     F     G     H I J K\n",
       "actividad                                                      \n",
       "A                                                              \n",
       "B                                                              \n",
       "C                True                                          \n",
       "D          True                                                \n",
       "E          True                                                \n",
       "F                                  True                        \n",
       "G                      True  True                              \n",
       "H                      True  True                              \n",
       "I                                        True  True  True      \n",
       "J                                        True  True            \n",
       "K                                        True  True            "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calcula_encadenamientos(datos_enunciado.precedentes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nodo_inicial</th>\n",
       "      <th>nodo_final</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actividad</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H</th>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I</th>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>K</th>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f1</th>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f2</th>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           nodo_inicial  nodo_final\n",
       "actividad                          \n",
       "A                     1           2\n",
       "B                     1           3\n",
       "C                     3           5\n",
       "D                     2           5\n",
       "E                     2           4\n",
       "F                     4           6\n",
       "G                     5           6\n",
       "H                     5           7\n",
       "I                     7           9\n",
       "J                     6           9\n",
       "K                     6           8\n",
       "f1                    6           7\n",
       "f2                    8           9"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aristas = pd.DataFrame([\n",
    "    ('A',  1, 2),\n",
    "    ('B',  1, 3),\n",
    "    ('C',  3, 5),\n",
    "    ('D',  2, 5),\n",
    "    ('E',  2, 4),\n",
    "    ('F',  4, 6),\n",
    "    ('G',  5, 6),\n",
    "    ('H',  5, 7),\n",
    "    ('I',  7, 9),\n",
    "    ('J',  6, 9),\n",
    "    ('K',  6, 8),\n",
    "    ('f1', 6, 7),\n",
    "    ('f2', 8, 9),\n",
    "], columns=['actividad', 'nodo_inicial', 'nodo_final']).set_index('actividad')\n",
    "aristas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "datos_proyecto = pd.concat([datos_enunciado, aristas], axis=1, sort=False).set_index(aristas.index).fillna(0)\n",
    "datos_proyecto_apartado_1 = datos_proyecto.copy() # La necesitaremos en el apartado 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "proyecto = GrafoProyecto(datos_proyecto)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto.pert(duraciones=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>temprano</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td></td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tardios</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         1  2  3  4  5   6   7   8   9 temprano\n",
       "1           3  2                              0\n",
       "2                 4  2                        3\n",
       "3                    4                        2\n",
       "4                        3                    7\n",
       "5                        1   5                6\n",
       "6                            0   1   2       10\n",
       "7                                    1       11\n",
       "8                                    0       11\n",
       "9                                            12\n",
       "tardios  0  3  2  7  6  10  11  12  12         "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto.resolver_zaderenko()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tempranos</th>\n",
       "      <th>tardios</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   tempranos  tardios\n",
       "1        0.0      0.0\n",
       "3        2.0      2.0\n",
       "2        3.0      3.0\n",
       "4        7.0      7.0\n",
       "5        6.0      6.0\n",
       "6       10.0     10.0\n",
       "7       11.0     11.0\n",
       "8       11.0     12.0\n",
       "9       12.0     12.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resultados_pert = proyecto.calcula_pert()\n",
    "resultados_pert['nodos']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>H_total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>K</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f1</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f2</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    H_total\n",
       "A       0.0\n",
       "B       0.0\n",
       "D       1.0\n",
       "E       0.0\n",
       "C       0.0\n",
       "F       0.0\n",
       "G       3.0\n",
       "H       0.0\n",
       "J       0.0\n",
       "K       1.0\n",
       "f1      1.0\n",
       "I       0.0\n",
       "f2      1.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resultados_pert['actividades'][['H_total']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto.pert()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['A', 'B', 'E', 'C', 'F', 'H', 'J', 'I'], dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto.camino_critico(duraciones=datos_proyecto['duracion'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apartado 2\n",
    "> Probabilidad de terminar el proyecto antes de 9 periodos."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La duración media del proyecto la conocemos del apartado 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duracion_media_proyecto = proyecto.duracion_proyecto(duraciones=datos_proyecto['duracion'])\n",
    "duracion_media_proyecto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para determinar la desviación típica debemos obtener en cada rama del camino crítico la suma de las varianzas, y quedarnos con la mayor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "rama_1 = ['A', 'E', 'F', 'J']\n",
    "rama_2 = ['B', 'C', 'H', 'I']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Desviación rama: A-E-F-J : 2.23606797749979\n",
      "Desviación rama: B-C-H-I : 3.7416573867739413\n",
      "Varianza del proyecto: 14.0\n",
      "Desviación del proyecto: 3.7416573867739413\n"
     ]
    }
   ],
   "source": [
    "desviacion_proyecto = proyecto.desviacion_proyecto(rama_1, rama_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Una vez caracterizada la distribución normal con la que aproximamos la duración del proyecto, podemos hacer el cálculo de la probabilidad:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21.133903708531776"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import scipy\n",
    "from scipy.stats import norm\n",
    "\n",
    "probabilidad = norm.cdf(9, loc=duracion_media_proyecto, scale=desviacion_proyecto)\n",
    "probabilidad * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apartado 3\n",
    "> Reducir la duración del proyecto hasta 10 periodos con el mínimo incremento posible de coste."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Situación inicial de partida"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto_reduccion = proyecto.copy()\n",
    "proyecto_reduccion.pert()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Primera reducción"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analizamos los costes unitarios de reducción y la capacidad de reducción de cada tarea de las ramas críticas:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cur</th>\n",
       "      <th>duracion</th>\n",
       "      <th>duracion_tope</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actividad</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           cur  duracion  duracion_tope\n",
       "actividad                              \n",
       "J         -1.0       2.0            2.0\n",
       "E          1.0       4.0            4.0\n",
       "A          5.0       3.0            1.0\n",
       "F          5.0       3.0            2.0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto_reduccion.cur_ordenado(rama_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para reducir la rama A E F J la tarea más conveniente es la J, pero no dispone deperiodos reducibles. La siguiente más conveniente es la E que tampoco es reducible. La siguiente más convenientees la A que sí es reducible y es la que se elige recortar."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cur</th>\n",
       "      <th>duracion</th>\n",
       "      <th>duracion_tope</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actividad</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>H</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>25.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            cur  duracion  duracion_tope\n",
       "actividad                               \n",
       "H           1.0       5.0            2.0\n",
       "I           1.0       1.0            1.0\n",
       "B           5.0       2.0            1.0\n",
       "C          25.0       4.0            2.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto_reduccion.cur_ordenado(rama_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En la rama B C H I la tarea más conveniente es la H y es reducible."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reducimos entonces 1 periodo las actividades A y H"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sobrecoste de la reducción: 6.0\n"
     ]
    }
   ],
   "source": [
    "proyecto_reduccion.reducir(A = 1, H = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Con esta reducción el proyecto ya dura 11 periodos y no han surgidos nuevas ramas críticas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto_reduccion.pert()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Segunda reducción"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analizamos nuevamente los costes unitarios de reducción y la capacidad de reducción de cada tarea de las ramas críticas:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cur</th>\n",
       "      <th>duracion</th>\n",
       "      <th>duracion_tope</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actividad</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           cur  duracion  duracion_tope\n",
       "actividad                              \n",
       "J         -1.0       2.0            2.0\n",
       "E          1.0       4.0            4.0\n",
       "A          5.0       2.0            1.0\n",
       "F          5.0       3.0            2.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto_reduccion.cur_ordenado(rama_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para reducir la rama A E F J la tarea más conveniente de entre las reducibles es la A."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cur</th>\n",
       "      <th>duracion</th>\n",
       "      <th>duracion_tope</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actividad</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>H</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>25.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            cur  duracion  duracion_tope\n",
       "actividad                               \n",
       "H           1.0       4.0            2.0\n",
       "I           1.0       1.0            1.0\n",
       "B           5.0       2.0            1.0\n",
       "C          25.0       4.0            2.0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto_reduccion.cur_ordenado(rama_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En la rama B C H I la tarea más conveniente de entre las reducibles es la H."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reducimos entonces 1 periodo las actividades A y H"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sobrecoste de la reducción: 6.0\n"
     ]
    }
   ],
   "source": [
    "proyecto_reduccion.reducir(A = 1, H = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Con esta reducción el proyecto ya dura 10 periodos como nos pedían en el enunciado."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+PGJjY2XrzZo1C2PGjAEgfEGZPHkyli1bBiICAEgkEoSGhmLjxo3Q05N/601ISEC/fv1gZGRU7vNnjOmWH3/8EYmJiTh37pys7OTJk2jZsiU+//xzzQXGGGOMaTntbXvJWBVSNP0mq3g+Pj6Vuv/Q0FAsX74cgJAg6NKlC0xNTWFgYAB9fX04OjoiKioK7du3l9tu1qxZ2LRpE+7cuYOmTZvKymNiYjBw4ECkp6cjMjJSbhsjIyO5mQZCQ0Nl42+IxWIsW7YM+vr68Pb2Rr9+/fDkyRPMmzcPbdu2ldtPdnY29u3bhx07dlT0y6EU1/eqUdn1HQD++ecfpKSklLpe//79YWZmJlcmlUoRFRWFLl26AABevnyJjRs34sGDB+jfvz/69OkDsVhc6r6zsrIQFhaGy5cvo1u3bujUqZNsu5iYGFhaWsLBwaEMZ1c9ODk54ezZs/D390fXrl1haGiIiIgIHD9+XKu7yDDGGGOaxp+SjAHYuXOnpkNQy7BhwzBt2jStnnKwqBUrVlT6Mby8vODl5aX2dnXq1EFgYCBWrFiBoKAgWXnbtm1lM5+U5sKFC8jJyZF9iROJRFi8eDFyc3Px/Plz1KtXT+F2+/btQ7du3dC3b1+14y4rru+VryrqOwC4ublh4cKFWLlyJWxtbfG///1P9gU4IyMD//77L3755RdcvHhRNiUxALx69QqrV6/G5MmTAQCpqano2LEjunTpgkePHiEoKAjt27cvlsQrKjk5GZ07d8bXX38NPz8/LF26FN9//z327dsHsVgMFxcXTJkyBcOHD8f7779feS+EjnNxccGxY8fw+PFj1KxZE19//bWmQ2KMMca0HiczGAPw8ccfazoEtQwbNgzu7u46Fffu3bs1HUKJxo4di5EjR+LSpUulzlaiiLLpWMVisdJERlxcHLZt24bt27erfbzy0KV6A3B9L4mVlRV8fX2xcuVKODo6KuyWIBaLkZ2dLXv86NEjTJw4EVu3bpUNMLlr1y5ERUXJpgf97rvvEBAQgLNnzyodtyEvLw9DhgxB69atZV2sFi1ahKZNm+Kbb77B4sWLoa+vj6CgIHh5eaFOnTpo3bp1Bb8C7xZbW1tNh8AYY4zpDB4zgzHGAOjp6WHLli1Ys2YNLly4UOnHu3//PhYtWoRNmzapNC0sY8qUNuPFlClT0KhRI9ljf39/DBo0SDYtaHZ2Nj788ENZIgOAbLDbol1TCjt9+jTCw8MxduxYWZlYLMaoUaMQFBSE9PR0WZm/vz/GjRun9rkxxhhjjCnDyQzGGHvL0NAQ69evV9qSIl9qairu3r2LR48elTqlqzIGBgbYsmWL3BdIxiratm3bYGdnJ6tnUVFROHjwIIYOHSpbx8DAoNhMOrGxsfD09CyxJcWePXsAoNg6zs7OSE9Px6FDh2Rlffv2RVpammwbxhhjjLHy4mRGNbVr1y7k5eWptK5UKpUbZb2wp0+f4tSpUyofNysrC//88w+WLl2Kc+fOyc1LHxMTg/v376u8L8Yqi729PRITE3HgwAF8//33GDZsGJydnWFtbQ2xWAxLS0s0bdoUDRs2hJmZmaysXbt2+Oyzz7By5UrExsaW+D9Wv359HoiTVar09HQsXLhQrmzp0qVwd3dX2pqDiLBr1y7MmTMHa9asKXH/t2/fBiDU5cKsra0BAPHx8XLlXbt2LRYPY4wxxlhZ8ZgZ1VBGRgYmTJgAAwMDDBw4sMR1iw4Sl+/Zs2dYsmQJVq9ejbFjx6Jnz56lHpcHimPaLDk5GSdOnMDx48dx4sQJ3L17FyKRCI0aNYKLiwsGDRqE+vXrw8LCAnXr1kWdOnWQlZWF169f4/Xr10hJScG9e/dw9epVfPvtt3jx4gVsbW0xePBgDB8+XDZjBGOVJTY2Fn369AEgdB0pPHVw4XWUDaSanp6O6dOnY9u2bcjIyEDr1q3xzz//oEOHDgrXT0pKglgshoGBgVy5sbExAODJkydy5U5OTti0aROys7OLbcMYY4wxpi5OZlRDf/zxB168eIEVK1aUmMxQNEhcvoSEBPj6+uLHH39U6Zg8UBzTRvfu3UNISAhCQkIQGRkJsViMTp064dNPP0WvXr3Qtm3bEscMUCYvLw9XrlzB/v37sXv3bgQFBaFNmzaYPHkyfH19+YscqxQuLi44fvy47HFqaio6deoke5ydnY27d+9i8ODBCrc3MTHB+vXrsXbtWqxcuRIzZ87ExIkTcfHiRYXrKxv0Nr/FnY2NjVy5ubk5pFIpbt++jVatWql1bowxxhhjRXEyoxraunUrvL29sX///hJnbig6SFxhHTp0kBsdvzT5A8WFhobKyvIHivvxxx8xf/58mJiYyA0UFxERof7JVbGnT58iLi5OpZYpgNDNJiwsDJcvX0a3bt3QqVMn2VSeVUUXY65IcXFxCAkJwZ49exATEwMLCwt4e3tj7ty56NWrV6mDKapCT08Pbm5ucHNzw4IFC3DhwgVZC6eFCxfim2++wRdffCGbQlMXHDx4EK9fv5Y9TkxMxOTJk2V34RXRdN3RxZgrkoWFBebOnSt7nJqaitzc3FIHnNXT08O0adNw7tw5hISEICsrC4aGhsXWs7OzQ25ubrHn88eRKZqwyE9+PHz4kJMZjDHGGCs3HjOjmgkLC4OrqyvmzJkDAPjpp58UrqdokLjyeNcGinv27BlmzpyJJk2aYO/evSptk5ycjJYtW+LBgwfw8/PDX3/9hQEDBsiNG1KZdDHminLlyhUEBATA2dkZLVu2xMqVK9G+fXscOXIET58+xebNm+Ht7V0hiQxFOnTogM2bN+PWrVvo378/Jk+ejHbt2iEsLKxSjlfR4uLi4OXlhREjRsiWS5culZgU0HTd0cWYK4Ofn5/sdxsbG9SuXVvlQWs/+OADWFhYKExkAEDLli0BCEmiwp4/fw6geDLjxYsXAIQkCGOMMcZYeenObUFWIYKCghAYGIiWLVvCzc0NO3bswJIlS4o1By5tkDh1lXWgOGXNoTWtMrrZVDZdjLmsiAiRkZHYs2cP9uzZgzt37qBhw4YYNGgQfvnlF3Tr1k0jd9vt7Ozwyy+/YNq0aZg2bRp69uwJPz8/rFixokzdWarK8uXLceLECTRt2lRWZmVlpXR9bag7uhhzVXByckJycrJK6167dg1eXl5Knx89ejS+++47nD17Fo6OjrLy6OhouLq6onnz5nLrP3nyBCKRqNjMKZVt165dVXq86igxMZGTVIwxxqocJzOqkcTERLx69Up2N23y5MkYPXo0Vq9ejcDAQLl1SxokriwqfaC4rCxAyd3DylBZ3Wwqky7GrI7c3FyEhYVh79692Lt3Lx49eoSmTZti8ODBGDx4MDp16qQ1s4c0a9YMBw8exJ49ezBx4kQcO3YMv/32m8pdf6rS06dPERsbi4CAADRs2FClbTRdd3Qx5vJ4+fIlACFhWZru3bvj8OHDcmWZmZlYvnw5BgwYAGdnZwBASkoKLl26JPd6AMCsWbOQmpqKX3/9FTY2Npg8eTKWLVsGX19fiEQiSCQShIaGYvv27dDTk2/8mZCQgH79+sHIyKgcZ6u+YcOGVenxqquqTGacOXMGYWFhiIuLg4+PDwYMGCB7TtWulFKpFFFRUbLBmcvaxayk7WJiYmBpaQkHB4eynyxjjDGluJtJNbJ27VqMGzdO9nj48OGwsLDA2rVrIZFIZOX5g8QVbUVRHuUZKE4lDg6AkxMwfjzw++/A9evlireiqdPNRlvoQsxv3rxBaGgoxowZAxsbG/Tp0wdhYWEYM2YMLl++jNu3b2Pp0qXo3Lmz1iQyChs8eDCuXbuG9u3bo2/fvvj+++9BRJoOS86qVasQGRkJOzs7NGnSBFu2bCk1Rk3XHV2Muaz27NmDWbNmAQAePHiA8ePH49q1a0rXnzVrFh4/fow7d+7IyvLy8hASEgIXFxd07NgRAQEB2LZtGw4dOlRszKTQ0FCEhobK3ruXLVsGT09PeHt7Y9WqVQgMDMS8efPQtm1bue2ys7Oxb98+zJw5s6JOXWVEpFMLAOzcuVPjcaiz+Pj4VNnfMzo6GsuWLcOsWbPQvHlzDBs2DBkZGWp1pXz16hWWLVsm+38vaxez0rZzcXHB4sWLcfr06Yo5ecYYY3K4ZUY1kZWVhY0bN6Jp06ZYtWqVrFwsFuPZs2fYtm0bRo8eDUD1QeLUUekDxTVoAMTEADduAOvXF5S5uwNdugCdOwNt21Zp643C1O1mow20Mebs7GycP39eNoVqZGQkpFIpOnTogJkzZ2Lw4MFo1qxZlcdVHlZWVggJCcHPP/+MWbNmISIiAtu3b1eaAKxqPXr0QE5ODiIiIhAZGYkvvvgC27Ztw+HDh5XetdR03dHFmMsqv+WRqurUqYPAwECsWLECQUFBAIRZTGJiYvDy5UsYGBiUOK7IhQsXkJOTI3sdRSIRFi9ejNzcXDx//hz16tVTuN2+ffvQrVs39O3bV42zY6y4+fPno0uXLjAwMMD8+fMxZswYGBsb4/r16yp1pSw6U1tZu5jxLG2MMaZ5nMyoJnbs2IGJEydiwYIFcuXXrl1D69at8dNPP8mSGeoOEqeKwgPFFe5bXWEDxdnbC8mMwh49AnbvFhZASGS0bSskOPKXKqJuNxttUBkx/3T4MNCzJ9C6NfD++4CnJ6AkaSaVSnHz5k1cvHgR0dHRiI6OxpUrV5CZmYlGjRqhT58++PLLL9G7d2+lX6B0yf/93/+hY8eOGDRoEHr37o2DBw+WOMZDuUgkwPnzgIkJ0KFDiav269cP/fr1AyAMpPrJJ5/g2LFjWLZsmWwg4aI0Xd+1Jeadf/4J6OsDhcdDMTIS6rxIBNSuLfwNjI2BWrWExdgYsLQsWCwshJ/W1kC9esL25TR27FiMHDmy2GxWtWvXLnVbZUk2sVis9P8wLi4O27Ztw/bt28sWMGOFXL9+Hd27dwcgJNNsbW0BqN6VsuhMbWXtYvauztLGGGO6hJMZ1cTPP/+Mffv2FSt3dnZGr169cPLkSRw7dkx210ydQeJUUekDxakyeGJWFhARISxvedWtix0A8pYvh17XroCbG6DKGB1qUrebjTao8Jizs1E/LQ0ICxOWoCDkmpjgWffuiPHwwDWJBAkJCbLl3r17kEgkqFmzJlxdXdG+fXuMHz8e77//Ppo0aVLe09NK7u7uCA8Px4cffigb26BRo0bl37FEAkRGovWePTgJAHXqCF2zLlxQazdt2rRBdHQ03nvvPWzfvl1pYkCb6rumYpZKpRAJOwDeJmcrhKUlUL8+YGcH2NgIiVxHx4Klbt1Sd6Gnp4ctW7ZgypQpGDt2LDqUktAqj/v372PRokXYtGlThbb2Y9VPWFgYrl+/jsTERERFRWHdunWoX78+vL29Vd5H/kxtv/76q6xMlS5mirrRqLNd3759MW3aNOzZs0drBzZnjDFdxMmMaiA0NBQ1atRQ2sphxIgROHnyJJYsWSJLZigaJK6o/NYThcfbKKzSB4qLjgZCQoC//gJu3iwxVmVqPn+OYQAwY4aQxBg/Hli8WLg7WoHU7WajDSo6ZvHz57gFwB5A/l9VnJ4Om8OH0ffwYSSameFOmzao36QJOnXqhCZNmsDV1RUtW7aEvn71eatydHTE2bNn4eHhgW7duiE8PFz9hMbb5AVOnRKW8+cBiQQtAbQEQCIRRLt3Cy0B1GRsbIwBAwZg06ZNStfRtvquiZjTXr3C3Xr10KRxYyA9XSjU0wPy8oS/DxGQmSksEgmQkaHajlNShEXZuBi1a8snNxwdgWbNhKVQSx9DQ0OsX78eDx48UOu81GVgYIAtW7Zo5Zg1TLc4ODjIxuioV68e2rVrp3Z3PEUztZW1i9m7NksbY4zpourzDaGa2rJlC2bOnImMjAz88ssvmDRpktzzERERsiaSx44dw5gxY/DDDz9g1qxZ2LRpE+7cuSM3tWG+v//+G7/99hsA4K+//kKHDh3g6ekpd/cyNDRUNv6GWCzGsmXLoK+vD29vbzK3USsAACAASURBVPTr1w9PnjwpcaC4HTt2FD+hV6+AnTuBtWuBS5fK+/IAACQAXg4ZApvly4W7nJVA3W422qCiY7589y6aK3nOAMD4168xXiIBvv8eeNtsuLqysbHBqVOn0LNnT/Tv3x9nz54tuQtAVpaQvDh5Ui55oczdmTPR9O2sFWXRokWLYq2pCtPG+l7VMcf9+y+aJCUBSUnqB1uzJmBqKiRVDQ2Frir5Cd/8xEdKivB3L+rlS+DiRWEpql49wMUFcHUVunq1aQP7t+ddWSpyIGlWvTVq1AgWFhYAgAYNGqB9+/Zq70PRTG1l7WJW6bO0McYYKxUnM95xn3/+OT7//HOlz7u7uyvsfgKg2CBxhXl4eMDDw0NxwuGtCh0oLiEB+OEHYNMm4U5mYbVqAQ0bqt86w9AQGDUK7XbuxJiuXTG9khIZgPrdbLRBRcb88OFDxD15AqmJCfTz71IrcuGCMFhreHilJZZ0hbm5OQ4ePAh3d3cMGDAA//zzT0GLgfzkReGWF0X/L5TYamiI53XqYHo5Ytu7d6/cVIhFaWN9r8qYHz58iIePHpU92PwWG6qoUUMYV6NWLSHpkZ0tdGtR1LUlKQk4elRY8hkYAC1bCkkOFxehq13btkJXJMbeIfkztRVtGVHWLmblmaVNG29gMMaYLuJkBlNK2SBxqqqQgeJu3wb++19gxw5AKi1Y0cAAaNwYSE0Fnj1TL5Fhagr4+QFz5gD168Pl9WuEhoZi+nT1vt5VZjebylJazEXjrqiY9+/fDxMTE9CuXcLfLjsbiI8HDhwATpwQmtznS0wEPDyEhEY1/0Jla2uLAwcOoFu3bpgyZQrWr18PnDkDfPih6l92C3N1xdFmzfBQxfoeHx+P1atXY9SoUbL3gOvXryM9PR3z5s2TW1db6rs6MReNu6Lre86GDahRtItU4STD69fC+9rLl0BODvDmDZCWJjzOT0jkLzk5ig+WkyMkKRS1ANHTE8bQMDcXkrdv3gCPHwv/f/mys4ErV4SlsMaNhaRG4eVt8/l33Zs3b7Br1y4kJCSgc+fO+OCDD1CjRo1St8vKykJYWBguX76Mbt26oVOnTkpnz6louhhzVVM2U1tZu5hV+ixtOiguLg6XirSaNTIywqBBg+TKpFIpoqKi0KVLFwDCaxYcHIx79+7B0dERI0aMKHFWpXyl1d+YmBhYWlrCwcGhAs6OMaaViLESSCQSGjt2LEVFRVX6sRISEsjX15dSUlKIUlKIpk8nMjAgEr7qCouFBZGVlXyZqkvt2kTz5wv7LmTfvn0kEono1q1bKsd66NAhGjZsGAEga2tr2rBhAz158kRunRYtWpC1tTVJpVIiIsrLy6PZs2eTp6cnrVy5kubOnUu///57mV4rALRz5061tlEl5qJxV1TMbm5u5Ovrq/jJ8HAie/vif6+hQ9U+zrtq7969BIBCQ0OFAk9P9eu/uTnRrVtq1ffo6GgyNzcnANSrVy+aPXs2LVmyhDIyMoqtqy31XZ2Yi8ZdJfW9rFJSiK5dIzp6lOj334mWLCGaMoXIw4OoefPi75UlLfr6RHZ2RE5ORO+9R2Rpqdp2DRsSeXsTBQQQ/fknUXw8UW5uxZ6nIk+fEm3ZQvTmjVqb7dy5k9S9zImLiyNHR0c6ePAgpaWlUXBwMNnb21NYWFiJ2yUlJVHjxo1pw4YN9OzZM/rqq6+of//+sv8Hdaj7/q4NMfv4+JCPj4/a26nr1atXBIACAwMVPp+VlUUAaOrUqQqfr127Ns2YMUOubOHChQSg2HticHAwAaCbN28q3Je6223YsIEA0I0bN0o8R12WnZ1NZ86cIQMDAwJAo0ePpsTERLl1Xr58Sd9//z29fv2aiIT6a2NjQ82aNZNt17RpU4XXJ4WpUn9zcnJowoQJpf4vMMZ01i5OZjCV3L9/v9KP8fjxY8rLzSX69VchaVE0iWFkVPzi2saGaOxYoh07iBwcFF+AW1oSffcd0cuXCo8rlUrJ0dGRRowYUaHnk5aWRqmpqQqP9/Tp03LtuyzJDFUpirs8Me/Zs4dEIlHJCbGHD4UvV0X/djt2lOmY76JRo0aRtbU1JSUlCa+XubnqX15FIqI9e4hI/foukUgoPj6eHj58WOJ62lTfVY2ZSEP1vTJIpUR37wrJjrVriWbOJBo0iMjFhahmTdXqiYUFUYsWQpKjQQMiPb3StzExIerYUXgfXrWK6NQpIgX1oFxiY4Vj1axJ5OMjnGNeXqmblSWZ4eHhQaNHj5YrGzVqFHXv3l3pNrm5udStWzfy9vaWlUmlUnJwcKDZs2erdXwi9eu7NsSsK8mMrl270meffSZX9uTJEzI0NKQtW7bIlc+YMYNcXV0pV0nCTt3tAgMDSSQSUWZmZonn+C5wd3cnABQeHi5X/vDhQ/Ly8qKXha7HPDw86MqVK0RElJycTGPGjCEA5Ofnp3T/6tRfqVRKHh4eFBsbWxGnxhjTLpzMYFrkzh2ivn2LXyjXqFG8zM9PuKAtfAepZ0/59aythbuXaWmlHjr/brWuZO8rM5lRkSQSCTVr1qzYxaNCZ88W//LUsCFRNbjwU8WLFy/Izs6Ohg8fLhSsX696MqPInUiu75VDrfpelaRSops3iXbuJJo7V2jZo6g1lLIWPS1aELm6Cj+Lvh8rW+rUIWrXTkg+zJ5NtG6d8J5954768V+4UHz/771HtHgx0ePHSjcrSzLD1dWVOnfuLFc2btw46tixo9JtTp48SXItp94KCAggExMTeqNmixJ167s2xFxVyYwbN24QAPryyy8VPv/06VMCQOPGjVP4/Jw5c8jV1bVY+YwZM8jJyYny3ibJMjMzqXnz5hQdHS233ldffSWXOFJ1OyIiPz8/+vDDD1U7UR33n//8hwAUSyB8/PHHtGnTJtnjixcv0h9//CG3zuPHj0lPT49atGihdP/q1t+jR48W+x9hjL0TOJnBtMS6dUTGxvLNoA0N5S9eGzUiWraM6MULxfvw9S1IYixeTJSerlYIH374Ibm6uurEXRNd+XI3b948MjU1pUePHqm2wZdfFv/SsmKFWsc8cuQIBQcHl7oouljPycmhs2fPKtzv8+fP6fvvv1cpBolEQkeOHKElS5bQ2bNnizXbjo6OpoSEBLXOi6ggCREZGUk0erRQ10v7Utm5M1FWVrF9cX2veGrXd01LTRVaUqxcKSSIXV1VS1YYGxM1bSq0+njvPfVaCQFCl7927Yg+/ljoTvjDD0RbtxIdP050/TrRs2fy3VfCw5XvS19fSM6EhBSr52VJZgQGBhIA2rp1KxEJLXesrKwoODhY6TZTpkwhAMX+p3ft2kUAaNeuXWrFoG5914aYqyKZERERQYMGDSIAZGdnR7/99pvcHX5VulKmpqaStbU13b59W65c1S5mZe1Ol5WVRZaWlnT06NGKeCm0nqJkRmRkJJmYmMi6lxAJn6t5ClpZdejQgdzd3ZXuvyz118nJiUJCQspyOowx7cXJDKZhqalEQ4YUb3lR9O782rVE2dkl72vNGqJffiGSSMoUyq1bt6hOnTo0fPhwhR+u2kQXvtz9+eefpKenR2vWrFF9o4cPC5JY+a006tVTq698cnIyTZ06lQCQra0tbd68mbZu3Upbt26ldevWkb+/PxkaGlJ8fLzcdkX78RY1cOBAqlevXqnHr+x+vD169KDB7u7FXydFi5UVUZH+yvm4vlesMtV3bSSRCC0h1q4lGjeOqH374ollRYueHpGtLVHr1sLStKmQtFAnyaGoVUijRkTNmqm2vpUV0bRpQrcUKlsy4+nTp/Tee+8RAJo+fTr169eP9rztoqWMh4cHAaCsIsmUU6dOEQBauHChWjGoW9+1IWYfHx9a7u5OtGtXwXL4sNAaR9kSHk508aKwXL8utNq5c4fo0SPh2iA1lUjJWDflsXbtWpo0aZLC50rrYlbW7nS7du2iAQMGqB+sjlKUzBgyZAj17dtXpe1tbGyUdiUiKlv9HTduHLm5ual4BowxHbGrQmYzSUpKwqlTp3DlyhUkJSXJRnKuDoyMjFCnTh20atUKnTt3Rps2bTQdku64ehUYOBC4e1d4rK8vXJLmT91pbAzMmwdMnw4YGZW+vwkTyhWOo6Mj/vzzT3h4eKB58+b49ttvy7W/6uzChQsYNWoUJk2ahAnq/F0aNAC++AJYuxbIyxPKkpKAVauE2WdUYGVlBV9fX6xcuRKOjo4KpybW09NDdqEZHR49eoSJEydi69atqFWrVrH1N2zYgOvXr5d67Ly8PAwZMgStW7fGmDFjAACLFi1C06ZN8c0332Dx4sUAAH19fQQFBcHLywt16tRB69atVTo3AFi4cCHCu3cvKGjcGLhzp/iKenrAH38I0xYrwPW94pS5vmsjQ0OgfXthyZeTA1y7Bly6VDDzyZUrwqwr+fLyhJlSHj8uvk9zc2EmFFNTQCwGJBJhhpanT4G301gq9OqVsKjq2TPgp5+EpVUrtHB1RV3VtwYA1KtXD2fOnIG7uztWrFgBd3d32YwLyiQlJUEsFsPAwECuPH82hidPnqgZhXq0JebpERFARITa26nMxESYDat2beF6wcxMqK/GxgXPmZsLz5mbC8/XqiX8zF9q18bYXr3w5eHDuHL+PNp07ix3iJJmWwMqaJa2aio2Nhbu7u6lrnf69Gno6+uXOONWWeqvk5MTNm3ahOzs7GLbMcZ0V5mTGVKpFDt27MDatWsREREBsViMFi1aoEGDBgq/DLyrXr58iTt37mDLli14/fo17O3t4efnh4kTJ8K6mkxjVya7dwtfWt+8ER7XrCk/1eSAAcDPPwNVPJ1Wnz598Msvv2D8+PFIS0vD0qVL39lp6irL33//jU8++QQ9e/bEihUr1N/B3LnApk3ClJFisfBl54cfgClThAtWFZT2HjRt2jS5i1J/f38MGjQI5ubmxdaNj4/HpUuX4OnpieDg4BL3e/r0aYSHhyM0NFRWJhaLMWrUKPz444+YP38+TN6eg1gshr+/P8aNG4cINb4AdGvTBq76+sKUnnXrClPZKhIQAPTrV+K+uL6XX7nruy6oUQNwcxOWwu7fL0hsxMYCly8Lyen8RGS+kpISRkZCPTYzE76U5k9lm5cnvAdIJEKSIiVFvZhv3IDLjRtIBBDfoQMc//c/6PXtKyT5SrFx40b06NEDPXr0wKZNm9CpUyecPn0a9vb2CtdX9gU3922ixsbGRr3Yy0DTMWdmZiIVgIVaW6kpPV1YCk9vXAZ6ANYCwF9/gfT1IbKwACwtiy9WVsXL6tcXkikqun//PhYtWoRNmzYVmxK2OsnOzsbdu3cxePDgEtfLzc1FQEAA9u/fr7SOAmWrv+bm5pBKpbh9+/Y7OzUuY9VRmZIZp06dwtSpUxEXF4eBAwfir7/+Qp8+fVSaE/pdRUSIjo7G7t27sXr1aqxYsQIBAQGYMmWKSnO9Vys//wz4+xdc8BoaFiQyzMyAZcuAceM0Ft7YsWNhamoKPz8/3Lp1C3/88QfMzMw0Fo+uICKsWrUK/v7++Oyzz7Bu3bqyfTG2tweGDQO2bi24a5uSAvz2G/Dll+WO8/Dhw+jYsaMscREVFYWDBw/i119/LbZuTk4O5s2bh40bN2LBggWl7nvPnj0AUKylhbOzM9LT03Ho0CH4+PjIyvv27Ytp06Zhz549pV7kyWzcCFOpFAAgcXCAUXS0UG5oCGRlCb9/8AEwf75Ku+P6XjYVVt91mYODsHh7F5SlpwPx8cDt28CtW8LP+Hjh9+Tk4vuQSICHDystRCMAzS9eBLy8gFGjgOXLhRYiSmzevBk7d+7EhQsXoK+vj65du2L8+PGYNGmSXJKyMDs7O+Tm5iIrKwuGhoay8vxWqpX9xUkbYk55/hxtICQJ8hMa4rdLHgAJgO6FW5QBwvu7VCq8dxHhfHg4CEAugPz75oSCC9W2bdpAlJcnvM/l5gp1JydHeJyRIfyuJpFUKtRLRXVTmZo1ARsbwNa24Ge9ekLLQmtroTWcnR1Qpw4MDAywZcsWiEQitWN7l6SmpiI3N7fUhM7MmTPh7+8Pt6KJ0yLKUn/zEyAPHz7kZAZj7xJ1OqWkpaXR8OHDCQB5enoW63POBOnp6TR//nyqWbMmtWjRgi5fvqzpkLSDVEo0aVJB/2aRSL6/f+fORPfuaTpKmXPnzlG9evWofv36tGXLFq0aVwBaNobApUuX6P333yc9PT1atGhR+XcYEyPfFx8Q+uAXGUhTmX///ZcA0Pvvvy9XnpOTQ927d6cHDx7Iykrqxztv3jzZgKDTp08vdcyMSu/Hm50tm4UiQySiLAMD4bWxtRUGUcwfYyY5WbX9FcL1XXUVXt+ri1evhPERtm8XpssePZroo4+InJ2FKbTLM76GgiUdoBCArnz1lfKBo4vo0aMHzZ07V65s4sSJZGBgQC+U7GPhwoUEgG7duiVXHhwcTADo5s2bar1M6tZ3Tcecl5dHZmZm1BCgiRX8NyzrkiES0csaNSjVxIReWVuTxNGRqE0borZthcXNTVhatxYGsbW3F6YmFosrLg4zM6Fue3oK1z5LlgjTjZ87J4wLokXvsRUtf8yMGzduyMpq165NM4rMrFXYunXr6LffflNp/2Wpvxs2bCgWE2NM5+0qvb3lW4mJiejevTuOHz+OgwcPIjQ0FM2aNavQxMq7wtjYGIGBgbhx4wZsbW3RrVs3pXdHqo3cXMDXF/jlF+GxWCx83Oe3zhg3DggLAxo10liIRbm7u+PGjRsYNGgQRo8ejc6dO2PXrl1yYy1UdxcvXsQXX3yB9u3bQyqVIioqCnNUHNuiRG5uQK9ewu/5deTOHSAkRK3dxMbGok+fPujTpw969uyJBg0a4MyZM8XWsbW1LbZtWFgY9PX1S+17XlhZ+/FevXpVtXq1Ywfw4AEA4LmtLQzyt5k2TRhbplcvYPt2oXm0mri+l67S6nt1YWYGtGsHfPKJMB7Sr78CBw8K4yc9fy7cXb99Wxh3ITQU2LwZ+OEHPGvbVuVDvADwh0iEYTVq4PLRo5jbvDm2iUQqdw2IjY3Fy8JjgQAYMGAAsrOzkZSUpHCb0aNHw9DQEGfPnpUrj46OhqurK5o3b65y/GWh6ZgvXryI169f41uRCL8CeKD2GVS8mkQwz8lBnfR0mCUnw/D2baE7VEyMsFy6JCxXrwL//iu8r6amFrQGFIsBCwuhhUXz5oCzs/C55OoKODkJYxVZWpbcben1a2GsmQMHhGuf2bOFut+li9CKw8QEaNMGGDq0oHvlmTPCOFHviMLdnJycnJCspAXM3r17QUTw9fWVKw8LC1O4flnq75MnTyASidC4cWN1T4MxpsVU6mZy/fp1fPDBB7C0tERkZCQaadEXTm3WqFEjHD58GJMmTcKgQYOwatUqTJw4UdNhVb3cXODzz4H88QYMDIS+0IDQF3vtWsDPT2PhlcTCwkI2pkBAQABGjBgBY2Nj9O7dG25ubmjYsKHGmuSfP3++ypuuZmZm4vnz57h27RpOnjyJhIQEODs7Y8uWLRg5cmTFxuPvD5w8KfwuEgnJr8BAYMgQ4UJTBS4uLjh+/LjssUQiQc+ePWWPlfXjffnyJYKCgtQesK1S+/Hm5gKLFgm/i8WwfTvejLRWLehPmCBcVP/9t9Bku4y4vsur0vrOhOb7TZsKSyFWBgbCF1AlngDYB2APgDCRCHliMfbv24cuffvC09MTISEhWLx4sUp/r4EDB2Lv3r0ICgqC3tsvqufPn4eLi4vcDZxZs2YhNTUVv/76K2xsbDB58mQsW7YMvr6+EIlEkEgkCA0Nxfbt22X7qSyqxlw07oqKeffu3XBwcIDvrVv4b9OmWPnxx/jhhx/kV0pPL/jcLyojo6CLXF6e/Pgqhbd780boSvL6tfB++OJFwfpSKZCWJqybni78/nah169BL15A782bkgecLSw3V0hupKaqtr6pKVCnjjDuS/6A5VlZQqzPnys+98xMYayZ2Njiz5mZAc2aCYmU1q2FZIqzs3DDR0vfd7788kukpaVh06ZNSEtLQ69evWRjRAFCN6PDhw8X2+7YsWNYsmQJPv30UwQFBQEQPjNv3LgBZ2dn9OjRQ7ZueepvQkIC+vXrByNVBpRnjOmO0tpuJCUlUaNGjahbt2706tWrKmgt8m767rvvSE9Pj/bv36/pUKqWVEo0cmRBs8v8ZvEAkakp0aFDmo5QLYmJifTLL7/QkCFDqFmzZmRmZkYQuvVWi8XIyIjq169Pffv2pXnz5lFkZGTlvdi5uUITXbztkpRfb1RohqqsmwkR0b59++jZs2dERPTkyRMCQN9++63cOp9//jktWbKEQkJCZIunpyeZm5tTSEgIHT9+XOFxR44cSQBIUmR64H/++YcAKJzjfvfu3QSAjhw5UvJJ/fprwWvg6ir7/VSPHiVvVw5c36uwvjPlli0r1oT/DkA/ANQFIL1CfzM9PT3atWuXbNNr164RADp48KBKh0pPT6fRo0eTs7Mz/fTTTzRmzBjy9vamu3fvyq3XokULsra2lk25nJeXR7NnzyZPT09auXIlzZ07l37//fcynS6gXjcTVWMuGndFxJyenk5WVlay99AlS5ZQrVq16OXLl2rtp8qkpxM9fUp0+7bQ5enECaLdu+nqlCl0vG9fSpswgeiLL4gGDCDq1o2oVSsiGxuiGjXK3+2kdm2ixo2JnJyELi8tWwr7VqdrS61aRJ06EY0dS/TTT0THjhG9/TzTtKVLl5JYLCYPDw/q2rUr3b59W+751NRUsra2liuPjo4mExMTpe+/KSkpcvsoa/3NysoiS0tLOnr0aMWfOGNMk3aVmMzIzMwkd3d3aty4MSWXoQ82kzdhwgQyNTWtPmNoSKVEw4cXfAgbGhb8bmVFVF1eB1Z2u3cX1Jn8hEa9ekSpqSVuVlIyI9+LFy8oJydHYT/e/v37U4MGDeQWU1NT0tPTowYNGlC/fv0U7rPS+vGmpgrjYgDCRbWxMRFAb4yMqE/btiW8Eoy9A777jgige8bGtFRPj7oBJFLw5UckEtG2bduKbe7l5UXOzs6Uk5Oj8iHT09Ppxo0blKrkvSYtLU3hc1KplJ4+far6uSmgbjIjX2kxEymOuzwxz58/n8zNzSkpKYmIiF69ekVmZmb0448/lml/mrJ+/XqqW7cuicVi8vLyopMnTxZf6flzomvXiI4fJ9q6lejHH4n8/Yk+/ZSoTx8hSWFhUbZEh4EBkZ2dkMB3cRHG8ahbV/XtHRyIhgwhWrSI6OhRlceIqWgpKSl0584dpWMurV27liZNmlTm/Ze1/u7atYsGDBhQ5uMyxrRWycmMOXPmUO3atdUevKqqPXnyRPEHj5bJzs6m3r17U4sWLSg7O1vT4VQuqZRo8GDFiQxra6LYWE1HyHRBXh5Rhw7FL9w++6zEzVRJZvTv35+ys7Opa9eu9Fkp+yMi+uqrr0odAPTJkydkaGhIW7ZskSufMWMGubq6Um5ubrFtAgMDSSQSUWZmpvId+/oWnHvz5rLfY/38SE9PT+kgf4y9E6KjiW7dovnz5yttRSMSiWjt2rUKN799+zYZGRnRqlWrqjjwsilrMqOq3b9/n4yNjWn58uVy5VOnTiUHBwe1kkfaQCKR0Pbt26lHjx6yz48TJ06ov6PMTKI7d4Skwm+/ES1eTDRuHFHfvkRNmhDp66uX6KhVSxgA28mJqFkzYWDR0rYRiYgcHYk++UQYHDo8nKhIi0FNyM3NpU8++YRiYmKq7Jg3b96kAQMGUEZGRpUdkzFWZZQnM27fvk2GhoYUFBRUlQGpJTk5mWbMmEE1a9akqVOnajoclTx48ICMjY117q6FWvLyiMaMUdy1xNaWSMuTY0zLREUVzGhSuDnuypVKN8nv1uHi4lLsuYyMDJo2bRp5enoSkZC0dXV1LTWMkpIZX331FY0ePZqIhMSFk5OT7M5UZmYmNW/enKKjoxVu6+fnRx9++KHyA69fX3DO9eoV/N6iBT26d48A6EQyl7HyyMrKokaNGlHDhg2pRo0axZIZS5cuLXF7Xbk5Q6QbyYySbs7cu3eP9PX1aceOHRqKrvxOnz5Nffr0IQDUq1cvWXeiCpGTIyQ7Dh8mCgoimjqVyMNDSD6ok+ioV6+gy4qdnfzscIoWIyOh68zcuUQHDmis9YZEIqGxY8dSVFRUpR8rISGBfH19i3VXYYy9M5QnM8rSLLOqRUVF0ZUrVwiAziQziIo3y3znzJunOJFhZ0fE0/mysig8pW/+BZueHtGaNcVW3bZtG3Xs2FH2Jaddu3bUu3dv6tmzJ7Vp04YMDQ0JAP30009EpLgfryIlJTMqrR9vSEhBAkcsJjIxKehqcuECERHVq1ev2J1Rxt41QUFBZGRkRIcOHSKRSCTXIuO///1vqdvrUrdZXUhmlNZtdujQodSpU6cqjqrinTlzpmrfX7OzheukgweFFhVffEHUvn3Be39pi5VVQVeV/K6JyhY9PWFq2okTiYKDiar4mvT+/fuVfozHjx9r1TTjjLEKpziZoe6AWZqUlZWlc8mM9PR0sra2Ljbo4DthzZqCD8rCdxhsbYUBtxgri4wM4aJL0QXZ5MlEaWnl2r3W9eOVSokCAgoSNyKRMHhc/jkHBspW7devn0rdZBjTZe+99x5NmDCBiIg8PDxILBaTSCQqNt5NSXRlQHNtT2aoMqB5WFgYAaCLFy9WYWTvsNxc4Rrqr7+I/vc/oftI69aqteSwtS0YcLRmzZK7pri6Es2cSXTkiPC5yxhj2k1xMsPf358cHR11Ipupi8kMIqLZs2eTg4ODpsOoWH/9JX8XOf8D0tyc6NIlTUfHdN3Nm0JdKtpCAyCytxe6nZRxBH2t6cebm0v0999EHTvKX2BaWhY8Hj5cWO+tGTNmUPv27assbsaqWnh4OAGQddWKiYkhkUhE48ePV/s65dq1a1S/fn1ydname/fuVUK05aetYyPqUAAAIABJREFUyYzs7GwaO3YsicViWr16danrOzs705gxY6ogsmosO1sYlPS334TuKl27yreIVbSYmAhjL7VoIZ8kV9QtpW9fYcyP6GihCzFjjGmXXQonEj9w4ACGDBmi0pzsrGyGDBmC+/fvI1bR/OK66MwZYNgwYW52kahgLveaNYHQUMDVVbPxMd3XogXw99+AqanwOC9PqF8A8OABMHUq0KABMGYMcP68WrvW09PDli1bsGbNGly4cKGCAy/u/v37WLRoETZt2oSaNWsCjx8D//sf0KwZ4OEBREUJK5qaAsbGQEqK8LhXL2DzZkCv4K3b3t4eDx48qPSYGdOUzZs3o02bNmjbti0AwM3NDVu2bMHq1avVvk5xcnJCZGQk9PX10alTJxw6dKgyQn7nJCQk4D//+Q+2b9+OvXv3YuLEiaVuM378eAQHB+PFixdVEKFm5OXlaTaAGjUAJyfA1xf4+WcgPBxITRWuyX76CRg5EnBwkN8mPR2Ijwfi4oCXL4XPUScnwMUFqFWrYD2JBDh2DJgzB2jXDrCzAyZMAA4dEp5jjDEtUCyZkZKSgvj4ePTs2VMD4VQf7du3h5mZGSIiIjQdSvndvg0MHgxkZQmP8y8uxWJg+3age3fNxcbeLe7uwJ49gImJ8DgzE7C0BIyMhMfp6cDGjcJ6rVsLF3epqSrt2tDQEOvXr0e9evUqKfgCBgYG2PLrr7AIDwe8vQF7e2DePODu3YKVHByAjAzhnABg4EBg/37A0FBuX3Z2dnj27Bmy8v//GHuHZGdnIyQkBKNGjZIr9/X1hZ6ewvsxpbKzs8OZM2fQp08f9O/fH15eXrh161ZFhPvOycjIQEBAAFq1aoXHjx8jPDwcXl5eKm07atQoiMVibN26tZKj1JzAwEAMHToUqSp+zlQJExOgWzfg//4P+OMPICFBSJjv3w/Mng107SokQfJlZgLXrwOxsUBaGmBhIXx+tmwJGBgUrPfoEbBuHdC/v7DOBx8In7GPH1f5KTLGWL5iVwI3b94EADg7O1d5MNWJSCRCq1atEBcXp+lQyic1FfD0BJ4/Fx7XqCHcMReJgLVrgQEDNBsfe/d88AFw7hzQpInwOCVFSKS1ayd/B+raNWDaNKG1xogRwIkTQt0shb29fSUF/tatW6i/ahVEDg7C/0doaEFLJlNTIRFTqxZw/37B/9K8eUBISEGrlELs7OxARHj06FHlxs2YBhw9ehSvXr3CkCFDKnS/pqamCA4OxsmTJ3H//n04OTnBx8cH+/fvR0ZGRoUeS9cQES5cuIDZs2ejUaNGWLlyJRYuXIjY2Fi0adNG5f3UqlULI0aMwJo1a0BElRix5nTp0gXnzp1Dhw4dcP36dU2Ho1z9+oCXF7B4sdB649kzoYXF118DnTsLN5/ypaYCV68CN28C2dnC52rbtkDhRH9mptBqY9o0ocVGly7AihXAw4dVf26MsWpNREU+Yfbt24eBAwdCIpHAsMgdQG2UnZ0NQ0NDTJ06FT///LOmw1GLt7c3ateujd9//13ToZRNTo7QJP74ceGxkVFB08P584HAQM3Fxt59qanA+PHA7t0FZSKR0KXJ3FzoqlH0S0ndukKd9fEB+vUr1sqh0ly/Dhw4ICQuzp0TeiQX1ry5cKcrNlY+ZkdH4c7XRx8p3XViYiLs7e0RERGBzp07V9IJMF3w6NEjxMTE4PLlyxCJRHB0dET79u1Rp04dREZG4iMF9UgqlSIqKgpdunQp9tzTp08RFxenckvNrKwshIWF4fLly+jWrRs6deoE8dsvSTExMbC0tIRD0SbvpfDz88PNmzcrtRWjVCrFjh07sG7dOpw7dw5isRjvvfceGjRoADMzs0o7rjJ//vknOnfuDDs7uyo9rkQiwbNnz3Djxg28fv0aDg4O+OKLLzBx4kRYW1uXaZ/5CZATJ06gV69eFRyxdkhOTsaQIUNw5coVBAcHw9PTU9Mhqe/NG6F75rFjwhIdrXi92rWF5IVEIrTKLfpZpqcnJOR9fICPPxaSKIwxVnn+LNYyI7+psi4kMnSdkZERJLrc73DKlIJERs2aBYkMHx/gv//VXFyserCwAP78U2hxkd+SjAi4dAk4dUpo1eDmVtCCAxBaEG3dKnTtqFcPGD4c2LVL5a4oKsvOBk6fBmbOBJo2FeKbMwc4e7bg4s/CQmgKbG8v9F8+f74gkWFiAixYINwdKyGRIawqdLmp7neTq7OcnBzMmjULjRs3xvHjx9GmTRv06tULz58/R8+ePWFlZYXj+e/Vhbx69QrLli1D69at5cqfPXuGmTNnokmTJti7d69KMSQnJ6Nly5Z48OAB/Pz88Ndff2HAgAHIfdvqyMXFBYsXL8bp06fVOq99+/ZVeKuMovT19fHpp5/izJkzePz4MbZu3QovLy80aNCgUo+rjI+PT5UnMgCgdu3a6NixI5YuXYorV64gISEBCxYsKHMiAxD+7u7u7lizZk0FRqpdrK2tcfz4cfj4+MDb2xvffvutpkNSn6kp0Lev0HLj4kWha8qGDUJCok6dgvVevhQ+l27dErqgODsLS353lLw84XMuv8VG377CfvLHfWKMsYpWdEjQnTt3koJiraWrs5kQEfn4+JCPj4+mwyib778vGPG68MjZHToQpadrOjpW3WRnE+3eTfTRR/Iz6eQvDg5EXboIU9Qpm5LOyYlo7FhheuHwcKIiU60qJZEQxcYSBQcTzZ5N9P77yqe/MzEhat9emCav8Gws+UvLlkTLlhElJal86pmZ/8/encfVlP9/AH/dbtq1iGQphJQs2SL7No2Y7NvY0maZsfYbYiyz2GXG1pfBZB1MGTGyjGXsoZQlhpCIaJFEouXePr8/Pu7NVXGrm3NvvZ+Px31wP/eec96aM7dz3+fzeb/fMgAfbZNIyq/MzEzm5OTEjI2NWXh4eIHX09LSmJ2dHZs4caLCeEJCAnNzc2PphXQAioiIYNevX1f6d6tUKmUdO3Zkffv2lY9JJBJWp04d5ufnpzDm6urKoqOjlfq3/fPPPwwAi6W23hpt+/btTFtbmyUkJAgdSpn75ZdfmFgsZmPGjGE5OTlCh6MaEglj587x3292doX/bhOLGWvYkP8eLaybiljMO6MEB/Pf14QQohrB2oJmUlRAViVbo2c4aJq9e/kafoCvs8zJ4X+vV49PpTcwEC42UjFVqgQMGsQfiYnA9u28EKisqF98PH8AQM2agKUlv1MkG2OMLwX5cM2zoSGfOSErMlq5Mi/IKZHwWR5JSUBKysdjq1KFLyPJyuJ1PCIjFV83Nua1M8aMAXr0yC+gqyQ9PT2IxWJkygqFkgpl0aJFiIiIwNKlS+Hk5FTgdTMzM6xevRq7du1SGPf19cWAAQNgYmJSYJs2bdogR/a5roSzZ8/i/PnzCA0NlY+JxWK4u7vjl19+wbx582BoaAixWAxfX1+MGzdOqWUje/fuRatWrVC/fn2lYyHqZ+jQofjuu++wefNmzJs3T+hwypSvry/s7e2xdetWoUNRHbGYzyLs2JHP3IiL40smDx7ksyAlEl73Sfb7Vizm3VEqVeK/82Svy5awWFryGR8eHtTpjhBSeh+mNzRpZsbhw4fZsGHDGABmYWHBNm3axBITE4UOS2kaOTMjMpIxA4P8u9myrLuxMWM3bggdHSH58vIYO3uWsbFjGTMyKvxukpkZn03UqhVj1aoV/p7iPvT1GWvShLF27RirW7fomSBduzK2bZtKZjLp6emxbdu2qeCHRjTJkydPmI6ODtPT02NZWVkffe/Vq1flfw8PD2eGhobs1atXRb6/OLMeJ0+ezACwhw8fKowHBwczACw4OFhh3MHBge3du/ej+8zNzWXVqlVjixYt+uTxifqbMWMGs7a2ZhKJROhQiColJzO2bh1jXboUPttQV5cxR0c+a6Ow34Vt2/LZkIXMECOEECVo9swMV1dXuLq64s8//xQ6lIohPp635JKtzReJ+K+jSpV4u0zqgEPUiUjE2wJ36gSsW8fvCP39N7+jJJtN8eIFcPly/jYmJnydr5ERP7ezs4GXL/k5n5XF/zQw4HeejIz4TA1DQ170LDub7/fJE3436kO6ukD37nwWhpsbnyGiIhKJBNraGv1xTkogMjISOTk5aNSo0SfrXDm+dwd0+fLlcHZ2RuXKlVUSR2xsLACgxgfF/mS1Fu7evasw3qFDByxcuBADBw4scp///PMPUlNTMXz4cJXESIQ1fvx4rFixAkePHi20EC3RUBYWwMSJ/JGayq8Ft2/PL3SdnQ1cu8bfW60an+n48GF+DY3wcP6YPp3XW/P1pdkahJBioatfopyXL3kL1uRk/lxHJ395ydq1fHo8IepKX58nENzceIGyixeBAweA/ft58U2Zly/542NkrytTNNTMjBfw7NcP6NWLJz9UjDEGqVRKyYwKSNYKsl69eoW+/u+//yIkJES+ZKRmzZqYMWMGoqOj4ezsrLI4kpOTIRaLoSMrAviOwbslh4mJiQrjDg4O2Lx5M3JycgpsI7Njxw506tQJNu8X8CUaq379+ujatSs2bdpEyYzyqmpVYNw4/nj0iBfX3r0buHKFv/7sGX8AQOPG/PfyjRv8WjIrixfn3rGDt1kfNw4YPZq/hxBCPoKufsmn5eTwjLnsbrOuLs+2A7xH+fjxwsVGSHFpaQEdOvDHsmVAQgJw/jy/kxQZyetmvHpV/P1WqgQ0agQ0awa0b8/XFzdpwmdxlCGJRALGGCpVqlSmxyHqRzYbIy8vr9DXe/Togfr166NevXqoVKkSUlJSoKOjg7i4uI/OiiguIyOjQsdlnUwsLS0Vxk1MTCCRSBAbG4vGjRsX2C49PR0HDhxAQECAymIkwvPx8cGYMWPw9OlT1FThzDSihqyteTev777jCYstW4CdO/NnRd66xf/U0wPatOG1rhIS+FhUFL+unD8f8PLif7e2FubfQQhRe5TMIB+Xlwe4uwPHj/Pn7ycyhgwBFiwQLjZCVKF2bWD4cP6QefiQL6t6/JjPRnr2jBcwe/WKX3zp6/NlJjVq8EedOkDDhvnt6T4jWfFjPT29z35sIqyWLVsCAO7JCu8Vom7dutDS0kLDhg1hamqKpKQkSKVS6KvwjqeVlRWkUimys7MVlrtkZGQAQIGEhSz5kZCQUGgyY8uWLahUqRKGDBmishiJ8AYNGoSpU6diy5YtmDNnjtDhCCIxMRF6enowe7/daXnXtCnw66+Avz9w6hSwcSOfFZmby2dkyJZ6NmzIC2Jfv86LhiYnA4sX86KjvXvzm2cqnFFGCCkfKJlBPu677wBZTRIdnfxERqdOfF2klpZwsRFSVurW5Q8NIOvoVKEujgkAoEWLFjA0NER8fDwePHhQ5HITLS0tiN51ybG0tISpqak80aAK9vb2AIDHjx+jQYMG8vHU1FQABZMZsnPWysqqwL4kEglWr14Nb29vGBsbqyxGIjwdHR2MGjUKgYGBmD17NrQq4PXDqFGj8Pr1axw/frzind9iMdCzJ38kJ/OZGps2ATEx/HVZUtbMDLC35+Npafym2sGD/NGhAzB1KjBwYJnPeiSEaIaK95uEKG/FCmDlSv73SpXya2Q4OPBCinQnmBDBUTKj4jIxMcH69euRl5cHX19fpbdzcHBAyqdaCheDl5cXdHV1ERYWpjAeFRUFR0dH2NraKownJiZCJBIVmnzZs2cPEhISMGnSJJXFR9THuHHj8PDhQ5w4cULoUASxYcMGJCQkwNXVFa9fvxY6HOFUr86Lfd66xYtzDxwIyOo+vXjBl32mp/NioO8lSBEWxtu6NmvG26/LbrARQiosSmaQwm3dCvj58b+LxXw6IADUqgUcPswz54QQwVEyo2IbPXo0pk2bhv3792P8+PF4I+s29c7z588hlUohfu8uZqdOnXDjxo2P7ld2XsmWMX1o5syZ8Pb2BsBne0yaNAn+/v5gjMm3Cw0NRWBgYIE78A8fPoSLi0uBpVFSqRTLli3DoEGDqPBnOWVnZ4cOHTpg06ZNQociiAYNGuD48eO4d+8ehg0bJq8rU2GJRLyA/N69vGjo0qV86SfAZ2RcuwbExgL16/PlKu9mmOHWLcDbm8+gXLYMUOFMM0KIZhEx2ZXHO8HBwRg2bBg+GCZlYOjQoQD4z1ytBAUBI0fyGgHvMzEBzp7lGXFCiFoICQnB4MGDkZWVVWRnCFL+nT9/Hn5+fnj8+DGcnJzQsGFDPHnyBPfu3UOzZs0wbdo0+XKQFy9ewM7ODhcuXED9+vUL7OvIkSPYtm0bgoKCYGFhgUWLFuGrr75SKORpb2+PtLQ0PH36FGKxGIwxzJ49G//99x9cXFyQmJgIe3t7jB49WmHfOTk5qFmzJv7880/07NlT4bXffvsNU6ZMQXR0NOzs7Mrgp0TUwfbt2+Ht7Y34+PgC7XwrioiICHTt2hUTJ07EL7/8InQ46iUnhyc3AgL4DI331arFa1RducLrbciYmwOTJgHTpgGmpp83XkKIkPZQMkNAapnM2LMHGDGCF196n4EBcOwYX69ICFEba9asweLFi5GUlCR0KEQN5Obm4t69e8jOzoa9vX2RhWE3bNiAGzdulLhjyOvXr5Gbm1tgRpBUKkVqaiqqV69e6HZ79uzBzp07sX//foXxFy9ewNbWFu7u7lixYkWJYiKa4e3bt6hVqxb8/PzgJ5sBWgHt2bMHw4YNw4YNG+Dj4yN0OOrp4kW+5Hn/fj5TQ8bUFLCz493H3p+VYWbGExpTplBSg5CKYQ8tMyH5/vqr8ESGri5PclAigxC18+TJE9SqVUvoMIiaqFSpEho3bowWLVp8tMONj48Pnj9/jqtXr5boOEZGRoUubRKLxUUmMmJiYrBz507s3r27wGvz58+HlpYW5s2bV6J4iObQ19fHqFGjsHHjxgp942zIkCGYPXs2pk6dSsnoojg781ka9+7xBIWBAR9PTwcuXeIziDt04DOHAV5v44cfeCvXWbN4AVFCSLlWZDJDJBLRo4wfe/bs+Zz/rT9u1y7g668LT2Ts3cvbYhFC1M6TJ09QW7bGmBAlaWlpYevWrVi/fj0uy1ojlqH4+HgsWbIEmzdvLtAW9tixY1i3bh1WrFgBE9mXElKu+fj4IC4uDqdOnRI6FEEtWLAAp0+fVljCRQphYwOsXs1bpi9dyluiA8CbN7woaFYW0Lp1flIjI4PX0rCxARYuBDIzhYudEFKmilxmEhQUJFRMJTJs2DBMmzYNzhrUg3rlypWwsrISfpnJ6tW8qvT7U/gA3q1k3z6gVy9h4iKEfFKXLl3g4OCAdevWCR0K0VCPHj2CtbV1mR4jMTERlpaW8haxMgkJCWjTpg26du1a6IwNUn61b98ederUof/upPjevgU2bACWLwcSE/PH9fQAJyfg9m3g2bP88apVge++40tQdHU/f7yEkLJSfmpmiEQiBAUFyetQaALBa2bk5gITJ/L2VgCvEi37766jw5eduLkJExshRCmWlpbyqcqEaJI3b96gU6dOyMrKwsWLF2FsbCx0SOQz2rx5M7755hs8efIE5ubmQodDNFFWFrBpE5+F8eRJ/riuLtCyJe968vJl/riNDfDzz3wmshattCekHKCaGRXW69dA//75iQwtrfxERuXKwIEDlMggRM2lp6cjOTmZOj8QjZOXl4cxY8bg0aNHCA0NpURGBTRs2DDo6Ohg586dQodCNJWeHjB5MhAXB2zbxpMVAJCdzYuH5uYC7drx9wH8faNG8Tav6rTUmxBSYpTMqIhiYviH++HD/LlYnL/EpGZN4PRp4MsvBQuPEKKc27dvAwAlM4jGmTNnDg4cOIDg4GDYyL6AkArF0NAQQ4cOxe+//y50KETT6egAY8bw5SXr1wNWVnz8zRteKNTAgBcT1dbm47duAUOHAt27A9euCRc3IaTUKJlR0WzfDrRpw9tZATyRIZXyvzdvDoSH86l5hBC1d/v2bRgYGMBKduFGiAbYtm0bli5div/973/o1q2b0OEQAXl6euLGjRuIiooSOhRSHujoABMmALGxvKaGrLNSWhqfqVG1Kr+ZJ1ticuoU0KoVT4RQRxlCNBIlMyqKlBSehXZ350tMAF4jQ5bI+OIL4MwZgLoiEKIx7ty5g0aNGkGL1v4SDXH+/HmMHz8e33//PXx8fIQOhwisffv2aNy4MQJlS14JsrOzcenSJaHD0Gw6OsC4ccCdO8DcuYCRER9PSuIzNerUAZo04WN5ecCOHUCjRrygaHa2cHETQoqNroDLO8aAP/4AHBzy1wfKqsnLamRMnsyXnFBLPEI0SkxMDBo1aiR0GIQo5cGDBxg4cCD69OmDBQsWCB0OURMeHh7YtWsX3rx5I3QoamH9+vVwcXHBq1evhA5F85mYAAsWAA8eAH5++Z1MHjwAbt7kM5JlMxtfveLvadiQz2LWsEYIhFRUKktmZGdn49ixY1i+fDkuXLgAqeyOfxltpwqaGHOxXLgAtG8PjB4NpKbysfcLfZqY8ATHmjX56wgJIRqDkhlEU7x69Qpubm6wsrLC9u3baTYRkRszZgzevHmDffv2CR2KWhg7dizy8vKwbds2oUMpP6pWBZYu5bUyvv46/6be9et8tkaHDrz4PQA8fsxnMXfvnr8kmxCitlRyNZGSkgJ7e3s8evQInp6e2L9/P/r16/fJL/kl3a6ixqy08HCgXz+gY0c+nQ7I/+CWFfrs2BG4cgUYPFiYGAkhpZKTk4O4uDgq/knUHmMMw4cPx8uXLxEaGgpDQ0OhQyJqxMLCAn369KGlJu+Ympri66+/xvr168FodoBq2dgAu3YBERE8gQHwjidhYbyGXIcO/E+AF8N3dASmTuWzNgghaqnUyYy8vDwMGjQITZs2hbe3N6pWrYolS5bg5s2bmDNnjsq3UwVNjPmTcnOBffuAHj14caMDBxSnyMn+rq8P/Porr49BFeQJ0VjR0dGQSCRwdHQUOhRCPmrZsmU4fvw4goKCULNmTaHDIWrIy8sLp0+fRmxsrNChqIVJkybh9u3bOHXqlNChlE+tWwPnzvFl2LJlJunpPKlhbQ00a8bHJBI+e7lxYyA4WLh4CSFFKnUy4+zZszh//rxCIS+xWAx3d3cEBAQgMzNTpdupgibGXKi8PJ5dnjGDfxgPHAicPJn/umw2hsxXXwHR0cD06fmVnAkhGikqKgpGRkawtbUVOhRCihQeHo758+dj6dKlaN++vdDhEDXVq1cv1KhRg5ZWvNO8eXM4Oztj8+bNQodSfolEwMiRvEjo0qX5y0wePODXym3aADVq8LEnT4Bhw4Bu3fhSFUKI2ij1N9qQkBAAQNOmTRXGmzRpgszMTBw+fFil26mCJsYsFxcH7NwJjB/PO4+0bQusWAEkJ+e/58MCn/b2wJEjQGgo0KBB2cdICClzUVFRaNmyJdUeIGrrxYsXGDZsGL744gv4+voKHQ5RY9ra2nB3d8eWLVvUa9mugIYOHYqDBw8iJydH6FDKN319Xvjz9m1eY052DX35Ml9e0rGj4tKTFi2AOXOAt28FC5kQkq/UV8GyKYE1ZNnLdywsLAAAd+/eVel2qqDWMb98Cdy/z2dcHD4MBATwbiNffglYWgL16wOjRgEbNwKJifnbyT5ogfwkRqNGvN3UjRtAr16lj40QojaioqLQqlUrocMgpFCMMXh4eEAqlWLbtm0QfThTkJAPeHt74+nTpzh27JjQoaiFAQMG4NWrVzh9+rTQoVQMtWrxLiZnzuQvM8nMBM6f5zcPHRz4WE4OsHgxb+164oRw8RJCAAClbmGRnJwMsVgMHR0dhXEDAwMAQOL7X7hVsJ0qqFPMQXv2FFwOoiwdHf6hCgDv38lo2xaYMoVPiXs/yUEIKRdycnJw8+ZNuttN1NaKFStw6NAhnD59GlWrVhU6HKIBbGxs0KlTJwQGBsLV1VXocARXp04d7Nq1i+oifW6dOgFRUcDatcAPPwAZGUB8PL9Wb9sWiI0Fnj/nM6VdXAAPDz5D2sxM6MgJqZAKJDO037XolEqlECvxRdjIyKjQcdk0QUtLS5VupwpqE3N2NpROY2hrA3p6QFYWL0gE5CcyAMDYmHcm+eYbgO7WElKuRUdHIycnh2ZmELV0+fJlzJkzB4sWLUIHWccAQpTg5eUFHx8fPHv2DNWqVSvwelhYGB49eqQwZm1tjQ4dOiAqKqrADNkuXboUWnRWIpEgIiKiQB2XpKQkxMTEoGvXrkrFm52djTNnzuDatWvo2LEj2rZtK792vnLlCszNzVGnTh2l9lWY4cOHl3hbUgra2ry+3PDhfAnKH3/wWc/h4fx6u3174OJFPrZ5M3DoELB8OTBmjNCRE1LhFFhmYmJiAgB4+fKlUjuwsrKCVCpFdna2wnhGRgYAoHHjxirdThXUJWadZ8+QKxYXXYzz/RkbEgnw+nV+IgMADA357IuQEF4zIzCQEhmEVABU/JOoq6ysLIwdOxadO3fGjBkzhA6HaJghQ4bAwMAAf/zxR6GvN23aFKmpqRgxYgRGjBiB169fo9m7JQHNmzfHvXv3MGLECBw5cgQtW7YsNJHx8uVL+Pv7K9Q/e/bsGb777jvY2Nhg3759SsWakpICe3t7PHr0CJ6enti/fz/69esnv8HVrFkzLF26FGfPni3uj4Goixo1+NKTU6fyl5m8egVcuMCXmdSty8eSkwF3d15o/4NkGyGkbBX4Fl2vXj0Aytd/sLe3BwA8fvxYYTw1NRVA0V/wS7qdKqhLzFfj41FJKuVdSQrzYX9xfX1eiOiHH4CzZ4EXL4A//wQGDOCzNgghFQIV/yTqat68eUhISEBgYCDVySDFpq+vj2HDhiEwMLDQ142NjeHt7Q0tLS3o6enBw8MDld91ocjOzsa+ffuwdOlSbN++HY0aNSqw/ZMnTzB69Gh888038u0A4OHDhxgzZgzeKlnUMS8vD4MGDULTpk3h7e2NqlWrYsmnQkIDAAAgAElEQVSSJbh58ybmzJkDgM90DggIwNKlS3Hjxo3i/iiIOunSBbhyBfj5Z0BXl4/duAEkJfHr8nez2nHoENC0KfDbbwWv4QkhZaLQZIaZmRkuXryo1A68vLygq6uLsLAwhfGoqCg4OjoWeeewpNupgjrEnJCQgFtPnyr3ZrEYWLaMZ4PPnQN+/JGv6atUSenjEULKj8uXL6N169ZCh0GIgosXL2LlypX49ddfSzW1nlRsnp6e+O+//xAeHl7o6/r6+tDW1oaBgYF8aXRWVhb69esHLy8v+Pn5FblvX19fDBgwQD4LWaZNmzaws7NTOsazZ8/i/Pnz8PHxkY+JxWK4u7sjICAAmZmZ8jFfX1+MGzdO6X0TNaWjA8ybB9y8CXTvzseysniB0Hr1ANkNzVevgIkTeQLkXeMAQkjZKZDMEIlE+PLLLxEaGqrUDiwtLTFp0iT4+/uDvctCZmVlITQ0FIGBgQp3DmfOnAlvb+9ib6dqxT22LG5VxnzgwAEYGhpCMncu4O/Ps7iLFwOenkD16opvlkqB77/n09wIIRVaZmYmbt68CWdnZ6FDIUTuzZs3GDt2LLp37w5PT0+hwyEazMnJCc2bNy9ydsaH0tPT0bt3bwwZMgSTJk0q8n0RERE4dOgQBg8eXOoYQ0JCAEBhqQoANGnSBJmZmTh8+LB8rGfPnsjIyJBvQzRcgwa8i8n69YAsKXbvHnDnDr/RKJspfe4cX/q9aRPN0iCkDBXazeTrr79G//79ERsbiwYNGnxyJ/7+/tDW1kbfvn3h4uKCxMREzJ07Fy1btlR4X2hoKNLS0uTFRZXdriwU59jvx62qmH///XcMGjQI2gsWFHwxKwuYOxf45Zf8MamUJzqio6liMiEVWHh4OCQSCdq1ayd0KITIzZ49G8nJyThx4gQtLyGlNnbsWMybNw+//vprkcXXAb7st3fv3pg2bRq8vLw+us/ly5fD2dlZYXlJScW+u+Neo0YNhXELCwsABZdqd+jQAQsXLsTAgQNLfWyiBkQiYMIEoF8/3j3wr7/4dfq5c4CVFb9Oj47mszTGjeOvb9oEWFsLHTkh5Q8rhEQiYQ0aNGAjRowo7OUiSSQSlpSUVOTrGRkZLC0trdjbKQMACwoKKvZ2yhy7sLhLE3NISAgTiUQsIiLi429cupQxns/Nf3h4lOiYhJDyYdGiRaxmzZpCh0GI3NmzZ5mWlhbbtm2b0KGQciI1NZXp6uqyrVu3Fvq6jo4O09PTY7Vq1WIAmL+//yf32bBhQzZmzJgiX8/OzmYA2JQpUz65r5YtWzKxWFxgPCIiggFg3377rcL46tWrmba2NsvOzv7kvokG+usvxiwt86/VtbQY69aNMV3d/DFjY8Y2bGAsL0/oaAkpT4ILXRchFovxyy+/YPfu3cWqwiwWi1H9wyUS7zEyMoJZIbMKPrVdWVLm2IXFXdKYs7Oz4efnh1GjRqFNmzYff/PMmcCHvda3b+fT2QghFdKlS5eo3SVRGzk5OZgwYQJ69eqFMdSWkKiIubk5+vbt+9GlJowxrFu3DtWrV8eMGTOwefPmIt+bk5ODuLi4AjMpSqqo2SKyTiaWlpYK4yYmJpBIJPIZHcWRkZGBunXr4sSJE8UPlHwegwYBt2/zWRgAL+x/6hRgYQHICtG+egWMH887niQlCRcrIeVMkUUeZMsopk6diqysrM8ZU7m2cOFCJCYmYunSpZ9+s0gErFql2LpVKgUWLSq7AAkhai0iIgJt27YVOgxCAPCp+w8fPsTatWuFDoWUM56enjh37hxiYmIKfd3Q0BB9+/bFkSNHYGxsjHHjxhVZl0K2VFhfX18lsVlZWUEqlSI7O1thPCMjA0DB7nay5EdCQkKxj1W5cmVkZGTgzp07JYyWfBampsCGDbyjiawl8OPH/Aakk1N+F5TDhwF7e2D3buFiJaQc+WjFyoCAAMTHx8PT01Ne8JKU3F9//YXFixfD39+/0N7nhbK1Bfr3Vxz7808gLU31AZJPSkhIwLp16zB48GA0bNgQxsbGEIlEFeahr6+PmjVr4osvvsC8efOKrDZPysb9+/eRnJz82Yp/0vlO5/vHxMbGYvHixfjhhx9gY2MjdDiknHFxcYG1tTW2bdv20fe1aNEC+/fvh7a2NkaMGIF///23wHssLS1hamoqTzaUlr29PQBes+N9qampAAomM168eAGAJ0FKwtraukSJECKA3r2B69eBoUP587w8ICICqF2bX9MDQHo6MGIE4OUFqOicJKSiKrQAqEyDBg2wZ88euLq6wtbWFj/++ONnCqv8uXz5Mtzd3fHtt99iwoQJxdvYywt4/25DdjYQFMRbP5HPIjo6GvPnz8fBgwdhYGCA7t27Y/To0ahVqxaMjY2FDu+zycrKQmpqKm7evImdO3di4cKFcHBwwKxZszBy5Egq/FfGLl26hEqVKqFFixZlehw63zk63z9u6tSpqF+/PqZPny50KKQc0tLSgru7OzZt2oSff/4Zld5rR//hDbZu3bph586dGDp0KPr3749///0XTk5OCu9xcHBASkqKSmLz8vLCggULEBYWplAoPyoqCo6OjrCVfWl9JzExESKRCPXq1SvR8apXr47k5ORSxUw+o6pV+XX64MHAt98Cz54B9+8D2tq8Zev583ym9ebNwMmTwLZtQOfOQkdNiGZSprLGxo0bmUgkYr6+vkwikZRpFY+SQgkLgH4Ohw8fZsbGxqx3794l+/llZzNmZsYLCIlE/M/27VUfKCng+fPn7JtvvmFisZg5OTmx4OBgKuD1nsjISDZ27FgmFotZ+/btWWRkpNAhlWuTJk1iTk5OZbZ/Ot8/js73fDt37mRaWlosLCxM6FBIOfbgwQOmpaXFDhw4IB/LzMxkAJiWlhZ78eKFwvvnz5/PADAzMzN25coVhddmzZrFHB0dizxWUlISA8DGjRtX6OszZsxgXl5e8uf/93//xxwcHFjeu4KOb9++Zba2tiwqKqrAtp6enuzLL7/89D+4CO7u7qx3794l3p4IKDmZsYEDFYv5N2vGmLV1/nOxmDE/P369TwgpjmClkhmMMbZr1y6mp6fH3Nzc2MuXL8syqBJRx2RGXl4eW716NROLxWzs2LGl+1IwcqTiB6GWFv+AJGXmwoULrHr16qxGjRps69at8gsWUtDVq1dZ586dmZaWFluyZInQ4ZRbrVq1YlOnTi2TfdP5rryKfr6/ePGCVa9enY0fP17oUEgF0KNHD9avXz/GGGP//vsvGzZsGAPAALB+/fqxf//9lzHGWHR0NJs4caL8NWNjYzZ9+nSWmprKGGMsLS2NWVhYsNjY2ALHOHz4sHy/FhYWbNOmTSwxMVHhPXZ2dszCwkJ+UyovL4/5+fmxr776iq1Zs4bNnj2bbd++vcC+s7Ozmbm5OTt+/HiJfwYzZ85krVq1KvH2RA0EB+ffmAQYMzJirF07xWv71q0Zi4kROlJCNInyyQzG1PtiV92SGSq/2N2ypWCb1s2bS79fUih1T96pI5Um70gBb968YZUqVWK7du1S+b7pfC++iny+T5kyhVWrVq3QVuuEqNrOnTuZtrY2e/r0aan39dtvvxVom6qsjIyMQs95iUTCkpKSitwuODhYnowpqSVLlrB69eqVah9EDTx8yFjnzorX8m3bMlalSv5zfX3GVq0SOlJCNEXhrVmL4uzsjFu3bmHAgAHw8vJCu3btEBwcjJycHJUufdFkkZGR8PDwQOvWrSGRSBAREYFZs2aVfsdffFFw7MiR0u+XFLBp0yaMHDkS33zzDfbt21ehagSUhkgkwpQpUxAaGoqQkBAMGDBA3qaOlF5kZCRyc3NVXvyTzveSqajn+3///Yf169djyZIlhbZaJ0TVBg4ciMqVK+OPP/4o9b58fHzw/PlzXL16tdjbGhkZFXrOi8ViVK9evdBtYmJisHPnTuwuZecKfX196ixYHtSpw2tkLF4MyGrAhIfzWhqyWlhv3wLTpgFffw28fClcrIRoCBFjJWtTUliBuBYtWqB27dqCXAwPHToU06dP/2xV/mXevn0rLxB36tQpPHz4EE2aNIGfn5/qC8Q1agTcvcs/9CQSwNwcSElRbN1KSuXff/+Fq6srvv/+eyp4WwqXL19G165d4eXlhTVr1ggdTrng7++PFStWqLQIHJ3vqlGRzvdu3bohIyMDERER0KLfPeQzmTRpEo4fP46YmJhSX1dlZ2dj8uTJ8PHxQZs2bVQUYUHx8fGYP38+Vq5ciSpVqpRqX9nZ2Xj79i1MTU1VFB0R3I0bwKhRQHQ0fy4SAZ06AZcuAbKbxNbWwK5dQIcOwsVJiHrbU+JkhkxCQgIOHDiAkydPIjo6GsnJyXj16pWqAlR7enp6MDMzg4ODA9q1awc3N7cCFbRVZvx4YONGxbHLl4HWrcvmeBVMbGwsnJyc0KtXL+zcubPCdyoorb/++gvDhg3D//73v+J38CEFDBo0CHl5edi3b59K9kfnu2pVhPN99+7dGDVqFC5cuIC2bdsKHQ6pQKKjo9G8eXOcP38eHVT0xe7Ro0ewtrZWyb4Kk5iYCEtLS/psJUXLygJ+/BHw9+ctXAHAzo7PzoiP58+1tYE5c4B58wCxWLBQCVFTpU9mkM9o1y5g5EjFsSVLgI8sYzl37lyB3uRaWlowNzeHtbV1gfZhH5ItlWnfvr18LCMjA7t27cKDBw/QoEEDjBgxAgYGBp8MPzs7G2fOnMG1a9fQsWNHtG3bFuJ3H8xXrlyBubk56tSp88n9lJVevXohOTkZFy9ehJ6enmBxFCU9PR2BgYF49OgR+vTpgx49esh/fupq3rx5WLVqFe7cuYOaNWsKHY5Gq127NiZPngw/Pz+V7E/dz3cAOHTokEJy/PHjx5g0aZJSnzdCKM/n+5s3b2Bvbw8XFxds2rRJ6HBIBdSyZUu0aNECgYGBQodCiGodPgyMHctbuAKAoSHQvDlw4UL+e7p1A3bsAGrVEiREQtTUnmIVACUCe/pUsZsJwFj37h/d5NWrV2zHjh3y6t6rVq1iq1evZlOmTGF169ZldnZ27NixY4Vum56ezhYvXsxevXolH4uJiWGWlpasYcOGTEdHhwFg9evXL1D1+0PJycmsXr16bNOmTezZs2dsxowZrE+fPvKq4Lm5uWzChAnszJkzxfyhqMb+/fuZSCQS7Pif8vz5c1a/fn02evRo1r17d6alpVWmLTpVJSsrizVs2JCNGjVK6FA0Wnx8PAPATp8+rZL9qfv5zhhjt2/fZiKRSP7ZBYANHz5c6LA+qjyf735+fszMzIylpKQIHQqpoNauXcsMDQ0VrkkIKTeSkxlzdVUsDtqmDe96InterRpjhw8LHSkh6qR43UyIGmjUiH+g6ejwP3V1GXv9+qOb5OXlMVNTUwaASaVS+XhqaiqzsbFhenp67NGjRwrbJCQkMDc3N5aenq4w7urqyq5fv84YYywlJYV5e3szAMzT07PI40ulUtaxY0fWt29f+ZhEImF16tRhfn5+CmOurq4sOjr60z8HFZJIJKxBgwZsxIgRn/W4xbF+/Xr2/Plz+fOff/6ZAWDnz58XMCrlhISEMJFIxCIiIoQORWPt3buXaWlpsYyMjFLvSxPOd8YY8/HxYadOnWKPHj2SP96+fSt0WJ9UHs/3e/fuMV1dXbZ27VqhQyEVWFpaGtPT02O///670KEQUjby8ngnE9k1PsBYrVqMNWmS/1wkYmzKFMZycoSOlhB1ULxuJkQN9OzJ/5QVB8rOBo4d++gmIpEIlStXLjBubm6OPn36ICsrC2FhYQqv+fr6YsCAATAxMZGPRUVFYeTIkWjWrBkAoFq1avj555+hpaWFC+9PhfvA2bNncf78efj4+MjHxGIx3N3dERAQgMzMTPmYr68vxo0b99F/j6odOnQI9+/fx08//fRZj6usnJwcfPnllwoFxMaMGQMAGtF5YsCAAWjRogUCAgKEDkVjXb16Fba2tjAyMir1vtT9fAeApKQkREdHo0GDBrCyspI/1HU5zPvK4/k+ZcoUNGzYsNzWAiGawczMDP3798eWLVuEDoWQsiESAVOnAmfPAjY2fOzJE+DOHaBzZ/46Y8CaNUCPHvw1Qio4SmZomt69C44dOFDi3ckSCe9/SYqIiMChQ4cwePBghffWrVsXI0aMUBirUaMGWrVq9dEWfSEhIQCApk2bKow3adIEmZmZOHz4sHysZ8+eyMjIkG/zOezevRvdunVDgwYNPtsxi0NHRwf16tVTGIuOjsZXX31V4Geqrry9vbF3715kZ2cLHYpGunbtGlrI2raVkrqf7wCwdu1ahIeHw8rKCjY2Nti6dSuYBpV3Kk/n+/79+3HkyBEEBARAW1tb6HBIBefh4YGwsDDExMQIHQohZadtW+DaNd7tBAByc3mCo3VrQHa9fe4c4OgIHDkiXJyEqAFKZmiabt0AWfE7XV3+599/84rIxZCXl4eDBw8iODgYXbp0gYuLi/y15cuXw9nZucBsDnNz80Krcj9+/Biurq5FHis2NhYAT3y8z8LCAgBw9+5dhfEOHTpg4cKFxfr3lBRjDEePHoWbm9tnOV5pMcYQHByMWbNmYf369UKHozQ3NzdkZmbi3LlzQoeika5du4bmzZuXej+acr536dIFM2bMQMeOHZGQkAAPDw+4uLhAKpUKHZpSysv5/vbtW/j6+mLkyJHo0qWL0OEQgp49e8La2hrbtm0TOhRCylblyrzg55YtvCAowDsYGhgAshtZqalAnz58NkdurnCxEiIgSmZoGn39/NkZsrt+L17whIYSevXqhebNm8PY2Bhubm6YPn06Tp06BR0dHfl7oqOjla7Ef/bsWWhra2P69OlFvic5ORlisVjhGADkHQkSExMVxh0cHHDjxg3kyJbSlKG4uDi8ePECzs7OZX6s0srMzMT48ePh4eGBW7duoWnTprh8+bLQYSmldu3aqF27Nq5cuSJ0KBrn+fPnSEhIUMnMDE05311cXLB8+XKcO3cOly9fhp2dHU6cOAF/f3+hQ1NKeTnfly1bhtTUVCxbtkzoUAgBwLuxjRkzBtu3b9eY5KYq+Pv7q6wlLdEwY8cCkZH5CYwnT4Dbt4EuXQAtrfxlJz170rITUiFRMkMTjR5dcOz335Xa9J9//kFYWBiOHDkCf39//Prrr+jUqZN8ymZOTg7i4uIKzKIojFQqxfz583HgwIGPruUv6jXZhYilpaXCuImJCSQSiXxGR1l68OABAKj1lHsZQ0NDbNy4ERkZGVi5ciUyMjIwceJEocNSmq2trfznTZR39epVAFDJzAxNOt9lmjdvjqioKNSuXRu7d+8WOhylafr5HhcXh+XLl2PevHmoRa0AiRrx9PREYmIijn2iXlh5kpKSUqGSN+QDdnZARAQgqyknkQBnzgCtWgGmpnzs7FmgZUvg5Enh4iREAJTM0ESurkC1avzvstkOJ07w6WdKMDIyQqdOnfDdd99h3bp1CAsLw6h36/LS0tIglUqhr6//yf1899138PX1/eQdYysrK0il0gLrxzMyMgAAjRs3LhAfACQkJCj17ymNV69eAYBCoVN1p6WlhWnTpmHgwIG4evWqxqzLNzExQXp6utBhaJxr166hZs2aqF69eqn3pYnnO8BncfXr1w/37t0TOhSlafr5PmXKFNjY2GDatGlCh0KIgnr16qFTp04VqhDoy5cvNaLgNylDenrAhg3Atm0Fl500acKfp6QALi7Ajz8CeXmChUrI50TJDE1UqRIg6wzy/lKMBQuKvav27dsD4F+YpFIpLC0tYWpqKk80FGXjxo1o0aIF+vbt+8lj2NvbA+C1Nd6XmpoKoGAy48WLFwB4EqSsSSQSANDIwnZffPEFqlSpAl1Z7RQ1p62tTXeWSiA6OlolszIAzT7f7ezsYGtrK3QYStPk833v3r04fPgw1q5di0qVKgkdDiEFeHh44O+//5ZfR5R36enpGpeEJmVkzBggPBx4d22Np0+Bu3d5txMAkEqBn34CBg8G3t3AIKQ8o2SGppoyhWdpgfw/Q0OB/fuLtZunT58CABwdHSEWiwHwmhUpKSlFbrNv3z4wxuTtQWXOnDlT6Pu9vLygq6tboP1rVFQUHB0dC3xBSUxMhEgkKtDBgyi6efOm2hdyJKV3584d2NnZCR2G4Pbt24d+/foJHUa59+bNG/zf//0f3N3d0a1bN6HDIaRQQ4YMga6urkYtPSuNpKQklczOI+WEgwMQFQV4e/PnOTl8mYmzc/6sjX37ePeTmzeFi5OQz4CSGZqqenXAw4P/PSuL954GgG+/5QVB3/PmzRskJycDyG/FCgAPHz7ErFmzoK2tjalTp8rHO3XqhBs3bhR62BMnTmDZsmXIzc1FQEAAAgICsHr1aowfPx7R0dHy982cORPe7z5kLS0tMWnSJPj7+8vbK2ZlZSE0NBSBgYHQ0lI8DR8+fAgXFxfoyZI0Fdzbt2+xaNEi3HzvF9Lz589x9epVrFy5UsDIyOcQGxuLhg0bCh3GZ3P37l1MmzZNXisEAP777z9kZmZi7ty5AkZWMcyfPx+vXr2iop9ErRkaGmLIkCEVZqlJSkoKJTOIIn19YNMmXjNPdr188SJQsyZQvz5/fu8eT3AEBQkXJyFlTPPmGpN88+cDu3YBL18CYjEvCPT0KTByJJ+hoaODf/75B4GBgfLOIM7OzrCyssLdu3dhaGiIxo0bF6iSPXPmTGzevBn3799HfdkHIoArV66gf//+yMzMRHh4uEIoenp6ePJeFeXQ0FB5/Q2xWAx/f39oa2ujb9++cHFxQWJiIubOnYuWLVsq7CcnJwd///03/vzzz7L4iWmkvLw87N27F/PmzUPr1q3Rq1cvVK1aFYcPH/5o4VWi+Z4/f460tLQKlcx4/fo1tm7ditWrV6Nbt25wcnJClSpVcOrUKVryUMauXbuGNWvWYO3atfLW2YSoKw8PD2zevBnXrl2Do6Oj0OGUqeTkZEpmkMJ5efFCoIMGAXFxPIFhZAS0awdcugS8fg0MH84LgwYE8KXqhJQjIia7VU4005o1vL80wIsAvXnD/z5sGE90aJVs8s2GDRtw48YNBAQElGj7169fIzc3F2ZmZgrjUqkUqampRf5S3rNnD3bu3In9xVwuU1LBwcEYNmwYNOF/g/T0dOjo6Mhb2mqaoUOHAuA/c6KcyMhItGnTBvfv34eNjU2p96cp53t2djYePXoEAwMDje2koWnne25uLpycnFC5cmWcPn26wIw5QtSRvb09vvzyS6xatUroUMpMTk4O9PT0sHfvXgwYMEDocIi6SkvjNzP/+Yc/F4mA9u15QkNWv6ljRyA4GFCiYyEhGmIPXa1oum+/5RlZgCcyZGvlgoKA/v35h1sJ+Pj4yJcylISRkVGBRAYAiMXiIhMZMTEx2LlzZ4VZA1tcpqamGpvIICUjm+2kTKvk8kRXVxcNGzbU2ESGJlq8eDHu3r1b6NI/QtTV6NGj8ccff2hMV6+S0NHRQWZmJnr16iV0KESdVakCHD4MLF3Kb2QyBoSF8U4nsg6I588Djo7AqVPCxkqICtEVi6YTi4E//wRkiYPMzPyERmgo0KIF/zArJi0tLWzduhXr16/HZSVbvpZGfHw8lixZgs2bNyvVFpaQiuDp06eoUqUK/T9BylR0dDQWL16MRYsWVaglTUTzubu7Iz09HQcPHhQ6lDKlr69PvwfIp4lEgJ8fcOBA/veC69cBbW1eNBTIb99KdZFIOUHJjPKgQQM+bUzWbjErC5Dd0Xz0COjSBfj+e6CYdy50dXWxcePGz7JOU0dHB1u3bkWVKlXK/FiEaIrk5GRYWloKHQYpxyQSCby8vNCqVStMnjxZ6HAIKZZatWrhiy++qDCFQAlRSp8+QEQE0KwZf56YCMTG8mUnAK+xN2sWMGIEvwlKiAajZEZ50bMnsHIlz8pKpbwQaOvW/DWpFFiyBHByAq5dK/aura2tVRxsQTVq1IBI1pGFEAIAePnyJUxNTYUOg5RjCxYswH///YctW7bI23MTokk8PDxw9OhReat5Qgj4jc7wcMDTkz/PzgYuXAA6dOCdUABg927+XeH2beHiJKSUKJlRnkyaBGzcyJeeMAZERvIsrGy2Q3Q00LYtsGgRz8oSQtTa69evqWMNKTMnTpzAwoULsWLFCjRq1EjocAgpkf79+8PU1BQ7duwQOhRC1IueHhAYCGzYAOjo8LGwMKBOHcDKij+PieHfDfbuFS5OQkqBkhnljbc3sGdPfs/pCxd4cqNtW/48JweYO5dnZmNihIuTEPJJr1+/hqGsBg4hKpSUlITRo0dj8ODB+Oabb4QOh5AS09HRwbBhw7B582a179REiCDGjeNJDNlM65gYvrykZUv+PCMDGDKEfz+QdT4hRENQMqM8GjAAOHMGsLPjz58941PNOncGZFPWIyJ4cdBly+iDixA1Rp0liKpJJBIMHToUlStXxqZNm4QOh5BS8/DwwN27d3Hp0iWhQyFEPbVuzWds9+jBn6elAVev8rp6su4nixbxehvp6cLGSkgx0FVyeeXkxD+k/Pz4zAwAOHsWqFQJaN6cP8/K4gWAunenWRqkXHr8+DH+/vtvLFiwAIsWLUJwcDAePHiAhw8f4vz58wXeL5FIcOHChSL39/z5cyxZskSpY2dnZ+PYsWNYvnw5Lly4AOl7ScMrV64gPj7+k/vQ0dFBTk6OUscjRFnff/89oqKisHfvXhgbGwsdDiGl1qpVKzRv3rzcFQKVSqXIysoSOgxSXlSrBvzzD/9uIBLxBMaZM0CrVvk3O48eBdq0AW7dEjZWQpSkLXQApAzp6fF+0/36AWPHAnfv8lkaz57xDy7ZNLOzZ3nF44kTeVa2Aq7RDw4OFjqEcu/x48ewkq3RLGM5OTmYM2cOAgICMHnyZHTp0gUGBgYIDw/HhAkTkJ6ejhUrVqBjx47ybV6+fCNo20gAACAASURBVIl169Zh0qRJRe7X29sbFy9exOzZsz96/JSUFLRr1w7ff/89PD09sXz5cixevBh///03xGIxmjVrhsmTJ+Prr79G586di9yPjo4OsovZhUgZdL6Xvc95vhdHYGAgVqxYgc2bN6Np06ZCh0OIyowdOxY//PADVq1aBQMDA6HDUYn//vsPjo6OiImJga2trdDhkPJAW5t/N2jRgi9Nf/0auHyZ19GoUgWIi8vvfLJzJ5+pQYg6Y6RieP2asW+/ZUwkYoznYhmrVYuxpk3znwOM1anD2P79Qkf72QQFBTEA9PhMjyFDhpT5f9O3b9+yli1bMhMTE3bu3LkCr8fGxjIrKyu2YMEC+VhCQgJzc3Nj6enpRe5348aNrGHDhqx69eofPb5UKmUdO3Zkffv2lY9JJBJWp04d5ufnpzDm6urKoqOji9zXrFmzmKOj40ePVxx0vpe/8704QkNDmba2Nps/f77QoRCicqmpqUxXV5dt375d6FBU5s8//2Ta2tosKytL6FBIeRQTw1jjxvnfAYyMGHNyyn8uEjH2ww+M5eUJHSkhRQmmZSYVhaEhEBDAZ2E0aMDHnjwBbtwAHB0Bc3M+Fh8P9O8PuLkBDx4IF+9nxhjTqAcABAUFCR5HcR5Dhgz5LP8tFy5ciCtXrmDGjBkKMy9k6tevj3nz5iHzvd7qvr6+GDBgAExMTArd5927d3H16lV89dVXnzz+2bNncf78efj4+MjHxGIx3N3dERAQID+uWCyGr68vxo0bV+S+rKys8Pjx408es7iEPhfofP/8wsPDMXz4cHh4eOCnn34SOhxCVM7c3By9e/cuV0tNbt++jfr160NXV1foUEh51KgRcPEiv+YH+CyNyEi+/Fy2DOWnn4Dhw4E3b4SNlZAiUDKjounYEYiK4lPLRCI+du0a7z/dvj0vAgQABw8CDg582UkZTHMnpCwkJSVh+fLlMDAwwJQpU4p8n7u7O1q1agUAiIiIwKFDhzB48OBC35ubm4u5c+di2bJlSsUQEhICAAWm8Ddp0gSZmZk4fPiwfKxnz57IyMiQb/Mha2trPH/+HK9fv1bq2IQU5tatW+jduze6d++OdevWCR0OIWXGw8MDp0+fxv3794UORSVu376Nxo0bCx0GKc+MjYG//+ZLT0QiIC8POHmSd0GULdcKDubfER4+FDRUQgpDyYyKyNgY2LQJOH0aaNKEj71+zdu4WlsD9vZ87O1b3qapYUNg40bqekLU3tWrV5GbmwsbGxtUrly5yPfp6OjIkxfLly+Hs7Nzke//+eefMW3atI/u732xsbEAgBo1aiiMW1hYAOCzPN7XoUMHLFy4sNB9tXzXNi0iIkKpYxPyoZs3b6Jnz55o3LgxgoKCoK1NpbJI+eXq6gpLS0vs2LFD6FBU4vbt27CXXZMRUlZEIl4UNCiIz+QGgEuXgNq1+QMArl/nhUFPnRIuTkIKQcmMiqxzZ97xZNUqQPZF7eFD4PZtnuSQTbl//BgYP573oz54ULBwCfmUmzdvAgDq1aun9DbR0dGoWbNmoa+dOXMG2traaN++vdL7S05Ohlgsho6OjsK4rCBdYmKiwriDgwNu3LhRaNeSmjVrol69eggLC1P6+ITIhIeHo0uXLrC1tcWhQ4egr68vdEiElCltbW2MGjUKW7duRV5entDhlIpUKsW9e/comUE+nyFD+I1N2TXU3bt8eYmjI3+emgq4uABr1ggXIyEfoGRGRaetDUydylswvb/G++ZNvlbO2Zm3cwWA6Gi+rq51a2D/fv46IWpEdtdZquQsopycHMTFxRWYRQEA6enpCAgIwJw5c4oVg1ER3YBkMVlaWiqMm5iYQCKRyGd0fKhr1644dOhQsWIg5K+//kL37t3h7OyMI0eOUAtWUmF4eXkhPj4epzT8DnJcXByysrIomUE+r2bNeHeT7t3587Q0/p2gQwf+XCLh3xvGjweodTxRA5TMIFzt2nxN3MmTgGx95qtXvDBQlSp8apmsxkZUFDBgAM/Ubt9ONTWI2nBwcAAA3Lt3T6n3p6WlQSqVFnrHevr06WjTpg0OHDiAkJAQhISE4N69e8jKykJISAhOnjxZ6D6trKwglUoLtFTNyMgAgALrn2XJj4SEhEL3N3r0aISHhyM6OlqpfxOp2PLy8vDjjz9i6NCh8PT0xP79+2lGBqlQGjVqhLZt22p8IdCUlBRYWFjAzs5O6FBIRWNuDhw9ypeeADyBERYGdOoEyGadbtzIEx7JycLFSQgomUE+1K0bcOUKL/wpW3qSnJzfg7pNm/wiodHRgLs7H//xR+DpU8HCJgQAWrVqBSMjI8TFxSlVAM7S0hKmpqbyRMP7nj17hjVr1mDKlCnyx+nTp5GRkYEpU6YUWRBUdhftwy4kqampAAomM168eAGAJ0EK07VrV9jY2BRauDEnJ0ehKwup2J48eYKePXtiyZIlWLduHdauXUs1MkiF5OHhgZCQEKSnpwsdSol16NABycnJMJTVMCDkc9LW5kVBN2zIT2CcO8c7oFSrxp+HhfHZ2pGRwsVJKjxKZpCCdHWB778H7t/nU8lkH2IPH/KkRq1agJMT/6ADeLLjp5948dA+fYA9e8r9bI2MjAxs2LABs2bNwu+//443Srasys7OxrFjx7B8+XJcuHBB6eUQqqCJMReXubk5fvrpJ0ilUsycOfOj77169SoAPpsjJSWlwOsHDx5EQkKCwmPixImoVq0aEhIScPTo0UL36+XlBV1d3QJ1LqKiouDo6AhbW1uF8cTERIhEoiLrfIhEIsybNw+///47rl+/rvBaZGQkGjdurNAhpaxdv34da9euxYYNG4qcTSKjLueOJsZcXDt27EDz5s3x9OlTXLx4ERMmTBA6JEIEM3z4cIhEIgQFBQkdCiGabdw4PmtbtkT2xg1+/S+7MZOQwGdslJOiu0TzUDKDFK1aNV4c9M4dPgNDlrx4/BiIiADMzPgaOlNTPi6VAocPA0OHAjVqAGPGAPv28a4oZS05GYiPL/vjALhz5w5sbW3xyy+/YOXKlfDx8UGzZs2QlJT00e1SUlJgb2+PR48eyad/9+vX77N8WdLEmEtqypQpGDp0KEJCQuDj44O3H5x/8fHxGDdunLzdaadOnXDjxo1SHXPmzJnw9vYGwGd7TJo0Cf7+/mDv6spkZWUhNDQUgYGB0NJS/Nh9+PAhXFxcoKenV+T+3d3d0aZNG0yYMIEvX8nIAKRShIWF4fHjx+jTpw+GDBnyyf+epZGamgpvb2/Mnj0b/fr1w/jx41FbVuW8EOpw7mhizMV1584d9OzZE2PHjsXw4cMRFRUl74JDSEVlYmKCAQMGaPxSE0LUQocOfPZFmzb8eWIiEBcHdOzIn2dl8e8Js2bx1q6EfE6MEGXFxTE2bhxjOjqM8fKf/KGry1jbtow1acKYSKT4GsCYgQFjvXoxtmIFY9euMZaXp/rYTpzgx2rVirFVqxhLTVVqs6CgIFbc/w1cXV3Z9evXGWOMpaSkMG9vbwaAeXp6FrmNVCplHTt2ZH379pWPSSQSVqdOHebn51es4zPGGAAWFBSkUTEPGTKEDRkypNjbldSOHTuYtbU1q169Ouvbty/z9PRktra2bOjQoSwmJkb+vrS0NGZhYcFiY2M/uc8ZM2aw6tWrFxi3s7NjFhYWTCKRMMYYy8vLY35+fuyrr75ia9asYbNnz2bbt28vsF12djYzNzdnx48f/+Sxb926xUxNTdnXX3/N8oKCGDM3Z0esrVlnLS0mAlilSpWYoaEhW7VqFZNKpYXuoyTnO2OMPXjwgFWtWpWNGjVKqfcLfb4zJnzMZX2+x8fHMy8vL6atrc2aN2/OLl26VGbHIkQTnThxggFg0dHRQodCSPnw9i1jY8bkX9+LRIz16MGYllb+mKsrYy9eCB0pqTiCKZlBiu/xY8ZmzmSsSpWCiYuaNRnr2JGxunULviZ7mJoy9sUXjM2dy9j+/YzFxjJWxJcvpR09qngMPT3Ghg5lLDSUsZycIjcr7pe7yMhI9scffyiMPX36lGlpaTE7O7sitzt16hQDwEJDQxXG58+fzwwNDdnr16+VjoGx4n25U5eYP3cyQyYtLY2dPXuWXbx4kT1//rzQ9/z222/s22+/LfExMjIyWFpaWoFxiUTCkpKSitwuODiY9evXT+njnDx5kuno6LC1nTsrnO/3AbYQYA4A09LSYk5OTuzmzZsFti9JMiM7O5u1adOG2draKv3fXMjzXV1iLqvz/erVq2zs2LFMV1eX1atXj23dulWeRCOE5MvLy2M2NjZsxowZQodCSPmyahVjYnH+dUjr1oyZmOQ/t7Vl7L2bRoSUoWBaZkKKr3ZtYNkyvtzkt9+Apk3zX3v6FDh/ntfXsLLiU9AcHPKXqABAejpw/DiwcCHQvz/QoAEvNtq6NV+iMn06sHIlEBTEiws9egTk5n48pg+ngWdl8e4sbm68xseUKbzeRynVrVsXI0aMUBirUaMGWrVqBTMzsyK3CwkJAQA0ff9nBaBJkybIzMws05oHmhizKpmZmaFTp05o164dqlSpUuh7fHx88Pz5c3kdjeIyMjIq9GcpFotRvXr1QreJiYnBzp07sXv3bqWP061bNxw4cKBAnDYA5gC4CeBqXh6+iIpC3+bNMWvWLGRlZRXjX1LQnDlzcPnyZcycOVPpQnRCnzuaGPPHpKWlYePGjejcuTNatGiBy5cvY+3atYiJiYG7uzvEYrFgsRGirkQiEUaNGoXt27cj91PXEIQQ5U2dChw8mL/MPDKSLz23seHP794F2rcHNLw9MtEMVOaclJyBAe8zPX48/yDbuhXYtQt4150Bjx/zBwDo6/Pe1QYGvGf1/fuKRULfvOEtX6OiCj+WSARUrcqTHqamgKEhYGTEH2ZmH28N9ewZsHYtf9jZAaNG8UedOsX+J5ubmxc6/vjxY3zzzTdFbhcbGwuAJxHeZ2FhAQC4e/dusWNRljrF7JyQwAvEqhktAFvd3DB5xgz49OyJNvXrl+nx4p89w5LgYGx2d4f+wYPF2vZLAM5DhwKBgYW+3gxAM6kUCwBcXL4cizdtQs8NG9B58OASxbp7925oa2vjxo0b6N69OyIiItCyZUusWrWqyNoMQp7v6hRz86Qk4NIlwMKCP9614VXGnTt3cPToURw5cgQnT56EWCyGm5sbjh07hp49e0Ika5VNCCmSh4cHFi5ciH/++Qdubm5Ch6Mx3r59iyNHjuDo0aO4cuUK4uLikJ6ejrwKUg9BS0sLpqamsLGxQcuWLfHll1/C1dWV2ly/r1cv4OJFflPyzh1+E9PUFGjbFggP59f6Li689t633wodbamEh4fj4MGDuHjxIm7duoUXL16U+kZRRVRW/19RMoOoRuvW/PHLL3zWxb59wIEDwLt2lHj7lrd8ldHWBmxteS9rLS0gM5MXFEpJ4ZPUPsQYT0o8e1a6OGNigLlz+aNVKzRs0gSFf9VX3tmzZ6GtrY3p06cX+Z7k5GSIxWLoyDrDvGNgYACAd7T4nISKefrFi/yXnxrSBbARwKN//y3zY+kA2ApAdOZMibY3VuI9IgDtGUP7tDRIhwzB3WrVUMvVValtZZ48eYInT57A0dER8+fPR5UqVXD37l107doVXbp0QUxMDGrVqlVgOyHPd3WK2S8sDHB2zh+oXJknVO3t+cPZGXmtWyPh+XPcuXMHkZGRiIyMREREBBISEmBqaooePXogMDAQ/fr1Q2VZu2xCiFLq1q2LLl26YMuWLRqVzIiIiPh/9u47LIpr/QP4d1maCoLYsKDYkGLvKEaTq0aN2FuuUYMtJlGTmKgxxRaNRm/ijfrTaFSMxoZdo0k0N4oCKoIdY2+AKAhKU9pyfn8cF1h6W2aB7+d55gFm58y8AzPs7rvnvAd169ZF7dq1S/S40dHRWLx4MdatW4eYmBh06NABr732GsaNGwcbG5ssBazLqtTUVERFReH27ds4ffo0NmzYgMqVK2PSpEmYPXs2rKyslA7RMDg6yl7Po0cDBw7IntcBAUC3boC3N5CSAkyZAly+DPzf/+n20jZwQghs3boVS5YsQVBQEBo0aIDXX38db731FqpVq5Zr0XbKnr7uq9JzVVHpYGYG9OsnF40G8PMD/vpLJjjOnZP/2AD5NbtPOlUqOYtK1aryU0ztP4ukJNmTIzFRJj4SEmRvjvj4wscaGIjWgYEIAZA6bBiMxo4F3nwTMDHJ9y40Gg3mzJmDgwcPwiKXT11zekw7S4KtdsqrEqBUzJlnFTFU9UrgGLXy3qRYqQE4RETAYfNmPAGQOmQIjEaNAvr2Tb/HsnH+VQJy4MCBaUN0HBwc8MMPP+Dtt9/G6tWrsWjRoiztlLzeDSXm5Ph4GGf+FDM2Vv4fzDDkLRnAQwB/A/C3tYWVqyvef/99dO/eHR07duQQEqIi8vDwwLhx4/D48eMSfa4tijFjxmDkyJGYN29eiRwvNTUVnp6e+OKLLyCEwIwZMzBu3Lgch0mWN0+ePMHGjRuxfPlyeHp64ttvv4WHh0e5Se7kytIS2LMHmDVLfqCp0chERvfucqh4cjKwbp2ccXDHjvShKQYsMDAQ06ZNw9mzZzF69Gj88ssvaNu2rdJhlTnFdV8xmUH6o1bLuae7dgXmzwdiYmTXs7Nn5dSuAQGyN0ZGhemBUbmyPJZ2eEsBmQPA7t3A4cNyaqlly/LdHfyzzz7D9OnT0bp161y3s7Ozg0ajQWJiIszMzNLWx8bGAgCctfN1lwClYn769Cnu16oFe3v7AsdMujTh4VDfuVOotuYAsHevTDCOHQssXpzj9a7NklerVk1nveur3gY3btzItp2S17uhxBwXEYFzACoYGaECgAoqFYxVKlROTYV5hiSHGQC3VwsePwaCgoCmTQFTU/l/jYiKZOjQoZg2bRq2b9+ea29EQ5GQkIDbt2/DxcWlRI73/PlzDB8+HMePH8cHH3yAefPm5VpPqzyqWbMmZs+ejcmTJ2PevHmYPHkydu7cCS8vL1iXgjfneqdWA//5D9CmDTB+vPzA8cQJObw8NBSIjAT+/FMOQTl4UD7HGaglS5bgyy+/hJubGwICAtCqVSulQyqziuu+YjKDSk7lykDPnnLRiowErl4Frl2TPTUePQJCQmTRz8eP03ty5CYmptAhCTMzHEhMRINZs9Dyq68KNKZ93bp1aN26Nfr375/ntk5OTgBknYrGjRunrX/6ahhOSSUzlIpZCIFr167BPiYmawKLCqywb3GFqSkOJCXBfvZstPr6a1nLJhcODg4A5KcUGdWrVw8mJiY5DntQ8no3hJiFEDh/4wbaq1RAbmPMjY3lp1qxsen/627eBJYskUv9+sCQIcCAAUCnTjLBQUQFUqFCBQwdOhQbN24sFcmMGzduQKPRlMjrgjt37qBfv36Ii4vD2bNnc6wpRFKVKlXw448/YuzYsRgwYABcXV3x22+/oZGe62yVGv/+N2BvDwwaJIeNX74sn8esrIC7d9MLg+7eDbz+utLR6khKSsJ7772HLVu2YPny5Zg6dSprU5WQot5X7B9FyqpaVY6te/993RlMgoNlZjc0VBbQ27sXWLtW9pqYM0fOeDJhAjBsmCww1KRJ/o9pZgb07w/8+itU4eGY5eCAbUIUKJGxb98+CCEwZswYnfXeOdRAGD9+PMzMzODr66uzPjAwEK1atUp7A6ZPSsYcEBCAmCIknagIjIyALl2A//4XqtBQzHJwwHaNJs9EBiCHVrz55ps4c+aMzvpbt24hOTkZXbp0ybadkte7IcQcEBCAqJgYpGp/x2ZmcsksJUX2KNMmMmxsZJFkrQcPgB9+kP8jq1SRw+Dmz5c1ie7ezb6+EOndyZMnsX37dp0lKCgIABAXF5flse3bt6cNV9JKSUmBn5+fzrrnz5/j+++/x0cffYSjR49maZOTxMREHD16FEuXLoWfn59Ou/Pnz+PBgwdFPOPSb9y4cbh69SoCAgKUDiVP169fh1qt1kmq6sOdO3fg6uoKCwsLJjIKqE2bNjh79iwsLCzg6uqKO4XsKVkmde4se15re/8+eCB7W7dvL3/WFgb9v/9TLsZMNBoNBg0ahL179+LQoUOYNm0aExkKKPR9peTEsETFZtOm9Pmts1tMTYXo10+IzZuFeP5cp+n06dNFo0aNRGpqar4OdezYMdGxY0excuXKtOW///2vmDRpklixYkXadjNmzBDjx49P+/nTTz8VLi4uacd5+fKlcHBwEIGBgQU+XQBi586d+d4+vzFnjru4Yp45c6aoX79+gdpQLry8cr/eASE6dpRzwT96pNO0oNf71atXhYWFhfD19U1b99NPPwknJyeRnJycts6Qrvf8xpw5br1f75GRQgQFCbFvnxBffCHE668LYWKS9W+nUglhayuEpWXuf2NLSyHc3ISYMkWI9euFCAgQIiGhQLFSwT179kzMnz9fABAAxL59+8TLly/THr9y5Ypo1qyZACBee+01cfPmTZ32z58/F99++62IiYlJWxcZGSkaNWokRo8eLd544w1hZGQkOnTokGcsT548EQ0aNBA///yziIiIEDNmzBBvvfWWSElJEUIIkZycLCZPniy8vb2L6exLL0dHR/Hhhx8qHUae5s2bJ5o0aaLXYzx79kw4OjqKdu3aibi4OL0eqyyLi4sT7dq1E46OjuLZs2dKh2NYYmOF6N8//flKrRaiWzfd57BJk4TI9JyshKlTp4qKFSsKf39/pUMhUeD7yovJDCobNmzI+kLfxESIvn2F8PQUIpeb4erVqwKAOHz4cJ6HCQwMFJUqVUp7EZtxMTc3F5GRkWnbOjo6iho1aqS9qExNTRWzZs0S/fr1EytWrBCzZ88WmzdvLtTpFuTNXUFizhx3ccQcHx8vqlevLubNm1egdpSLnJIZTk5CzJ0rxI0bOTYtyPWudenSJfGvf/1LzJkzRyxatEj069dPPMqUJDGU670gMWeOW5Hr/flzIXbuFGLoUCEqVMg+sVG7thD16glhbJx3EsvERIgWLYQYM0aIH34Q4u+/hYiKKtA5UN6Cg4MFAFGnTp1sH58+fboAIJYtW6azPiQkRLi7u4vnmZLqa9as0flfvGDBAgFA+Pj45BiDRqMRbm5uon///mnrUlJSRP369cWsWbN01vXp00dcvny5QOdY1ixevFjY2NjoJJ4M0ciRI4W7u7ve9q/RaESPHj1E3bp1RWhoqN6OU16EhoaKunXrih49egiNRqN0OIYlJUWIWbN0n6O6dtVN4r/5ZpYPGUvSmjVrhJGRkdi1a5diMVBWBbivmMygMmLduvTMb5cu8hPpJ0/y3dzd3V00a9Ysy6e2RREbGyuisnkTkZKSIh4/flykfRfmzV1+ZRd3UWL++uuvhZWVlXhSgL8H5SFjMqNuXSGmTRPi1Kl8Ny/s9R4aGprtNS2E4V7vucUshIFd7zExsvdY377Z99gAhKhUSYjmzYXo3Fl+zav3hnaxtxdi4EAh5s0TYv9+Ie7fL9T5kRQdHS0ACCcnp2wfnzt3rgAgfvrpJ531w4cPFxs3btRZl5iYKO7evauz7v79+wJArgmI48ePCwDi0KFDOuvnzJkjKlWqpPOJ+7Fjx0SnTp3ydW5lVWhoqFCr1Xp77iwurVq1EjNmzNDb/tevXy+MjY0L1UuuJPj7+4tt27Zlu2S+TwxFYGCgMDY2FuvXr1c6FMO0YYPsIa19PmrXTohq1dJ/dnAQ4vr1Eg8rNDRUWFhYiK+++qrEj12cnj59KjZs2CDmzp0r9uzZI2JjY5UOqVjk875iMoPKiL//FuLnn4V4+rRQzW/fvi3Mzc3FypUrizkw/dBnMqM4PXjwQFSsWFH88MMPSodStvz5pxDvvy/EyZNC5HO4SEa83vWjWK/3p0/lC8ABA4SoWDHnJIVKJYSdnRxW1K2bfJFoa5u/BEeVKkK88YYQ06fLJMrlywbR5bc0KEwy4+zZs6JSpUo6w0tycvDgQdGvX79ct5k6daoAIO5nSkx5eXkJAMLLy0tnvYuLi9izZ0+exy7L+vTpI/r06aN0GLmaNGlSlgRVcYmOjha2trbi448/1sv+iyo1NVU0atQo256kAAw2ASOEEB999JGoUaMGh5vkxMdHiBo10p9/6tcXomHD9J9tbORr+RI0atQo0bBhQ4PvrZWbCxcuiGbNmonTp0+L+Ph48d1334kWLVpk2xO1NMrHfcVkBpHW559/LqytrcU///yjdCh5Kg1v7pKSksQbb7whHB0dRVJSktLhUCa83ouXXq/3Fy+EOHxYiM8+E6J9+/wNN6lSRYi2bYXo3l32VnN21v1kLLdhKs7OQoweLXu4nTrFOhzZKEwyY8iQIaJHjx657jc1NVXs3LlTODs7i+Dg4Fy37dOnjwAgEhMTddafOHFCABALFy7UWT9p0iTRunXrXPdZ1nl5eQkjIyPx8OFDpUNRxKxZs0T16tVz7a2mpKNHj4pp06aJe/fuicTExLTl6NGjwt7eXunwchUVFSWqV6+uM8SLMrlzRwgXl/TnG2trmYjX/mxsLMSqVSUSir+/v1CpVGLv3r0lcjx90Gg0omXLlmLmzJk66zt06CB69uypUFTFKx/3lRdnMyF6Ze7cuXByckLfvn0RERGhdDil3rRp0+Dv748dO3bAxMRE6XAoE17vxUuv13uFCkDfvnI2J39/WQ3+jz+AxYuB4cOBpk3lrDUZPXsGBAYCJ07IGaKuXQNUKsDZWc6O0q0b0Ly57uwpAJCcLLfdsgX4+GOga1c5fayLCzBmDPDjj4CPD5CYWLznWEoFBwdj4MCBWZYdO3Zk2fby5cuoXbt2jvuKj4/He++9Bw8PD1y7dg3NmzfHuXPnctz+yZMnUKvVMM00ZW/FV3/TsEzTYLu4uODKlStISkoqyCmWKQMGDICNjQ22bt2qdCgl7uXLl1i3bh0++eQTVKlSRelwsmVhPDF97QAAIABJREFUYYHly5fD3t4epqamacuBAwcwZMgQpcPLVZUqVfDJJ5/g559/xsuXL5UOxzA1bChnKOzfX/78/Lmc+aRHD/lzSgowZQrw3nvps3zpycqVK9G6dWsMGjRIr8fRpzNnzuDSpUtorZ055pUOHTrg2LFjWaaoL43yc18xmUH0irm5Ofbv3w8hBAYPHsypRItg4cKFWLduHbZt24aWLVsqHQ5lg9d78Snx693SUk7T+vnncjrr69eBmBjAzw9YswaYNAno0CFroiIxUSYqvL3lcuUK8PIlUK+e3L5rVzmdnpWVbrvsEhzW1kCnTsCHHwIbNwKXLsntyhlbW1ssX748y/Lmm2/qbJeUlIS7d++iVq1aOe6rUqVKWLduHWJjY7F8+XLExsbi/fffz3F7ixymE9dOzWpra6uz3srKCikpKbh9+3Z+T6/MMTU1xciRI+Hp6QkhhNLhlKjff/8dMTExGDdunNKh5MjV1RVGmRKzqamp2Lt3LwYPHqxQVPk3btw4REdH448//lA6FMNlYQHs3QvMmiV/1miAv/6SzyvaDwLWrQP69QOio/USQkJCAvbu3YsJEyboZf8l5caNGwCQ5X9Z+1fT4Pr4+JR4TPqQ133FZAZRBjVq1MBvv/2GO3fuoEuXLrh//77SIZUqycnJmDRpEubNm4dVq1bB3d1d6ZAoF7zei8agrvdKlQBXV2DyZGDtWuDsWZnguHMHOHgQmDtXvjjM/GZaCODhQ9nj49Qp4MIF+QKyRg2gbVugSxegZcusCY6EBHmM1auB8eOBVq2AypWBjh2BDz4ANmwALl+WL1TLMBMTEzRo0CDLkvmT76ioKGg0GlSoUCHPfRoZGeHjjz/G4MGDceHCBSTm0AvGzs4OGo0my+OxsbEAAGdnZ5312uRHSEhIvs+vLHr33Xdx8+ZNnD59WulQStSff/6JDh06oGbNmkqHUiC+vr5QqVRwdXVVOpQ81axZEx06dGAyIy9qNbBkiXye0PYsO3VK9ha0tpY///kn4OYGPH5c7Ic/deoU4uPjS/1rVO3zSUBAgM76Ro0aAQAePnxY4jHpQ173FZMZRJm4uLjg7NmzMDY2RseOHXHkyBGlQyoV7t+/j969e2P79u3Yt29frp8okuHg9V44peJ6V6tlt153d2DePODQIeDRIzlM5dQp4L//BUaPlkNP1GrdtuHhcpiKr6/sdaFNcLRvL4eotG8PVK2q2yYhQSZF1qwBJkxIT4K4uQEffQRs3gwEBckESjlja2sLa2vrtERDfvTs2RM2NjYwMzPL9nEnJycAcqhLRk+fPgWQNZnx7NkzADIJUp61bdsWLVu2hKenp9KhlKiAgIBSkRDIbNeuXRg0aBBUKpXSoeRLp06dcOHCBaXDKB3GjQP+/ls+twDA+fPyOcPeXv589SrQvTsQGlqshw0MDISdnR3q1q1brPstaV26dIGpqSm8vb11emdEv+rRYq/9PZYBud1XTGYQZcPOzg6nTp3Cv/71L7z11ltwd3fHrVu3lA7LIL148QJz5syBs7MzHj16BB8fn1Kf7S5veL3nX5m43qtUyZpgeP5c1sL48Udg7FigWbPsExznzskhKufOAZGRWRMc1arptomPlwmRFSvS92tjA/TsmZ5gefXmuzTJa4iC9vGMb8BcXFwQHh6e72NcvXo112tr/PjxMDMzg6+vr876wMBAtGrVCg4ODjrrw8LCoFKp0KBBg3zHUFaNHTsWXl5eePHihdKhlJj79++jcePGSodRIEII7Nmzx+DrZWTUpEkT3L17V+kwSo8uXYDTp2VdJgB48EA+H2mTsTduyGGVz58X2yHv37+PJk2aFNv+lGJnZ4eFCxciMDAQHh4eOHLkCL7//nvMnTsXAMrUMO/c7ismM4hyYGFhgW3btuH48eN48OABXFxcMGzYMBw8eLBcvQDKjhAC586dw6xZs2Bvb48VK1Zg4cKFuHz5cpn651me8HrPWbm43i0s5IvKadOATZtkPQ1tHY6VK4F335VdgI2NddtlTnA8fQpUr54+RKVZMzkEJqPnz+UY6fnzZSG4GjUAR0dZYHTlSjl8xcALjD5/9cI6JCQkrUZFRtpPxjIO3eratSuuXLmSZduXL19i0aJFuHr1atq6yMhIXLhwAcuXL9fZdubMmWnjvG1tbTFlyhQsW7YsLXmSkJCAQ4cOYcOGDVlqD9y/fx+9evWCubl5Ic64bBkzZgwSEhKwZ88epUMpMTExMbDWduEvJXx9fZGUlITXXntN6VDyzdraOu3+p3xq2FA+1/TtK39+/hy4dQvQJhyCgoChQ4tt2GJ0dDSsMg+dLKVmzJiBEydOoE6dOvDx8UHPnj1hb28PKyurLIVBS7Pc7iuVKG8VkIgKISUlBTt27MDatWvh5+cHtVqNpk2bok6dOqhcuXKJx7Nr1y506tSpxLsLJyQkICIiAteuXUNMTAzq168PDw8PvP/++6ih7SZIpR6vd4nXezaSk4GbN+UQFO0SEJB38qF6daBOHZnYiImRn7blNquGsTHg4CCTIm5uMjHi5JR11hYF/Pnnn1i5ciUOHz4MABg1ahSmT5+ONm3aIC4uDmvWrMF//vMfhIeHo3bt2pg8eTK++OILxMTEwNHREX5+fmljmgE5i0nXrl1x8eJFtGvXDr1790a1atUwbty4LEU+nZycEBUVhUePHkGtVkMIgdmzZyMoKAi9evVCWFgYnJycMHr0aJ12SUlJqF27Nnbs2IEe2pkDyrlBgwYhJiYG//vf/5QOBYBMmq5evRr9+/fXy/86lUqFnTt3Yvjw4cW+b335+OOPERcXh/Xr1ysdSr55eXlhxIgR5a7AbLHQaIDPPpNDIAH5/75OHUA7lG7hQuDLL4t8GO094OXlVeR9GZp79+7B0dERy5Ytw7Rp05QOp9jkcl/tYjKDqICePHmCEydO4NKlS3jy5EmBxkCXdubm5qhSpQqcnZ3h6uqKFi1aKB0S6Rmvd17veUpIkMU+MyY4rl7NfWo9ExOgQQOZ5BACePIEuHs393oalpZAixYywdG2LfDaa+ljq0uJtWvX4sqVK1i1alWWx54/fw5TU9O0qVWzExcXh+Tk5CwFRjUaDZ4+fZpjccddu3Zh69at2L9/f9FOoAw5ePAgBg4ciNu3b6Nhw4ZKh4Pw8HDUrFkT//vf//DGG28U+/5LWzJDCAE7Ozv8/PPP6NOnj9Lh5BuTGcVg1SrZS1AImdg2M5NDFk1M5NSubdoUafdlNZmRlJQENzc3JCQk4Pz58zDO3JOyFMstmVF2zpKohNSsWRMjRozAiBEjlA6FSO94vVOezM3l1K4dOqSvS06WCQ4fn/QExz//pCcrtD08bt5Mb1OpkkxOWFjInh4PHgCvilYCAGJjZf2NjDUiatVKT25oe3FkeqNvSCZOnIhRo0bhwoULWboA52cIQE7TsarV6hwTGdevX8fWrVuxffv2ggdchvXt2xc1a9bEli1b0saYK+nJkycAgNq1aysciWE4ffo04uLi8K9//UvpUKikTZkCpKbKuk4pKelDFZOTgXfekc8n+ZgZqjyJj4/HBx98gAYNGmDlypVlKpGRl/JzpkRERFQyTEzSEwxa0dGyFoevr0xy+PvLmhta8fFybHRG1asDdevK/T1/Dty/rzs8JSwM+O03uQCyaKmzsyxG2rGjXFxcstb6UIiRkRE2bdqEqVOnYuLEiWjfvr1ej/fgwQMsXrwYGzduzNe0sOWJsbExRo0ahU2bNuHrr7/OUmOkpGnrsJS2uhb6smvXLri7u8NUO3UnlS/TpgHXr8vZsaKjZeI6LEwmxZctA+bMUTpCgxAZGYkDBw5gw4YN+OyzzzBo0CClQypxHGZCREREynj0KL3nhq+vLAKXV8HZ6tXlEBVjY9n+4UP5KV5OKlUCWrUyuOEpDx8+RL169fR6jLCwMNja2paaaS1LWlBQEJo1a4a///4br7/+uqKxHD58GP369cOLFy/0kngqbcNM7t27h8qVK6Nq5imgDRyHmRSjpCSgXTuZBAeAypVlzSUrKzks0camULstS8NM9u/fjxYtWhjEUDl94jATIiIiMjy1a8tFOwWpRiM/jctYf+PcOd3eGBERctEyNgbq1ZNJDrVaFosLDU1/XDs9bE7DU7QFRku454K+ExkAUKtWLb0fozRzcXFBu3bt4OnpqXgyIyYmBiYmJuxB8wqnECaYmgLr1gGdO8shitpkRnS07J2xeLHSESpu4MCBSoegOCYziIiIyDCo1XJYiIuLnKoVAOLiZFLD3z99efgwvU1Kihx+kmEaVFhayt4bFSvKF7/37gEvX6Y/nnl4iomJ7L3RsSPQqZP82rixvs+WDICHhwc+++wzrFixQtEhHgkJCRxSQZRZp05yCu8DB4CQEFkT6dkzOY33J5/Iqb2pXFN+jjMiIiKinFhYAN26ATNmALt2pRcGPXYMmDsX6NcPqFZNt01srCxAeuYMcO2aTGRUry4TFh06yGEmGWskJCfLHiCrVskCc02aANbWQM+ewLx5wKFDQGRkSZ41lZBRo0YBAHbv3q1wJESUrW++Sf9/rS2CHB8PeHoqFxMZDPbMICIiotLF2hro0UMugOyCfOuWbu+NixflrChamYenmJmlJy1evJA9O6Ki0h+Pjgb++ksuWg0byiEp2iEqHTrIrtBUallZWaF///7YtGkTJkyYoFgcTZs2xbhx4xQ7PpHBat4cGDgQ2LtXDiOsVEkmM9atk0luhYv3krKYzCAiIqLSTaUCHBzk8s47cl1KCnDjRvrsKZmnh01MBK5e1d1PjRqAnZ2swxETA9y5o1uv4+5duWzZIn/OXFy0Wzegfn39ny8VKw8PD/Tu3RvXr1+Ho6OjIjF07twZnTt3VuTYRAZvwgSZzABkz7qgIPm/+O+/05PaVC4xmUFERERlj7Fxev2NSZPkuuhoOZxEm9zw89PtjREerjtdrFotXzjb2MjkSFiYbu+O7IqL2tvLmhsdOsgpYtu0kUkPMlg9e/aEnZ0dNm/ejG+//VbpcIgoszfflIWeHz6UvTO0Nm9mMqOcYzKDiIiIygcrK93hKYD8dE+b3NAWGk1Olo9pNFmLi1aqJF9UV64sh6fcugUkJKQ/rt1+5075s1oNNG2a3nuDw1MMjpGREUaPHo1ffvkF33zzDdRqtdIhEVFGRkayKPTChbLXnJ2dTGr89pv8f21ionSEpBAmM4iIiKj8athQLtrZU2JjgYAA4PRp4OxZuTx5kr59fLwcrpJRnTpyuldAbpvxk0ONRhYhvXZNd3hKmzay50aHDnLhVJSKevfdd7F48WIcO3YMvXv3VjocoiI7efIkQjNOUw3A2toaffr00VmXkpICf3//LMOcHj9+jOvXr6N79+75Ol5iYiK8vb1x8eJFuLm5oWPHjmmJwfPnz6Nq1aqoX5RheIMGyWQGIIs+BwfLYtDe3uydUY4xmUFERESkZWkJvP66XLQePZK9NrT1N86f153qNTRULlrGxkDt2nIaQe3wlIzDWeLjgVOn5KJVvbpu7422bWUPECoRTZo0QefOneHp6VlmkxmnT59WOoQyz5B+x506dcKRI0cwaNAgAMCKFSswcOBAnW2io6OxevVqTJkyJW1dREQEvvvuO6xevRoTJ07MVzIjPDwcnTp1whdffIFx48Zh6dKl+Pbbb3HgwAGo1Wq0aNECU6dOxdtvv43XXnutcCfUunV6j4yMCeP9+wuczAgODoaXl1fh4qASl9t9pRJCWwmLiIiIiPKUV3HR7GQcnpKYKIe3xMTkfhxra1nzI2OCw9lZFjylYrdhwwZ88MEHCA0NRbXM0/2WcipeMyXKUN5eCSFgY2OD58+fIyoqClWqVEl7LDQ0FO+//z62bNkCKyurtPXnzp2DmZkZWrZsiWnTpuHHH3/M9Ripqano1q0bbGxscODAAQCARqNBo0aNMHLkSCxZsiRtnbu7O7777js0b968cCf04YfA6tXy+5o1ZU+4OnVkciOf1/jw4cOxa9euwh2fFJXNfbWLc9kQERERFYS2uOikSbIAXVAQ8PgxcOgQ8PXXQO/esmhoRtrhKWfPymljY2Jkb4zWreUwkyZNstbReP5cJkxWrADGjgWaNZMv4Pv0Ab76Sn4imbGeBxXJiBEjYGpqip3aeidlzM6dOyGEKDXL0KFDMXToUMXjKMhiaNeOSqWCpaUlAOgkLABg+vTpGDRoUJb17du3L9CsPidPnoSPjw8mTpyYtk6tVmPs2LFYtWoV4uPj09ZNnz4dk7QFmQujf//07+3s5NfQUFnYuQCGDRum+LWijwUoffd5Ue8rJjOIiIiIiqpGDaBfP2DBAuD334HISPki++BBYO5c2Q26YkXdNhERwIULsujorVtyGtjq1eV0rx07Ak5OgJlZ1jZ//AEsWiTHkDdoIAuburkB770H/Pij7C3y6g0E5Z+FhQUGDx6MTZs2KXL8u3fvYubMmUhNTVXk+FR++Pv74/Dhwxg6dGiR97X31ZSpmXtbNGvWDPHx8Thy5Ejauh49eiA2NjatTYG98YbssQboDt3bt69w+6NSjzUziIiIiPShdm25uLvLnzUa4Pr19JlTAgPlJ4pJSeltIiJ0p38FZIKjTh2Z2IiJkUNUEhPTH4+JyTpFLCCLkmqHp7i4yCEqHKaSKw8PD7z++uu4fPkyWrRoUaLHjouLw7JlyzBixAi0bdu2RI9N5cvSpUvh6uqa1mujKG7fvg0AqKUtgvxKjRo1AAA3b97UWd+lSxcsXLgQgwcPLvjBTEyAXr0ALy/5f9DaWvZg27sXWLwY2L5dFldu2rRwJ0OlDpMZRERERCVBrZZJBReX9NlT4uNlQdHz59MTHDduyMSHVnYJDltbOeTE2FjuIyQEiIvT3SYsTE5d+Ntv6etsbICWLWWvDxcXwNFRJjhsbfVzzqVMt27d0KhRI/zyyy/4/vvvS/TYzZs3R/369bFt2zYmM0ivLl++DFdX12LZ15MnT6BWq2GaaZhcxVc90cLCwnTWu7i4YOPGjUhKSsrSJl8GDJDJDEAOzzt3Drh5UxZU/ugjWXj5zBn5lco8JjOIiIiIlFKpEtC1q1y04uJkXY2MPTgyJzgeP5ZLRiYmMilRvbpMnISHy8J4GYctREUBx4/LJSNra6BRI5nYcHGR09U6O8ukh1H5GZWsUqkwevRorF69GkuWLIGJiUmJHnvixIn4z3/+g2+++SbtzSBRcUpKSsLdu3cL1zMiGxYWFtmu17z6f2WbKVFqZWWFlJQU3L59G87OzgU/oLs7YG4OJCToDqf7+OP0xO+IEcCRIzLZS2Ua/8JEREREhsTCQtbAcHNLX5c5wXH+vExwpKSkb5OcnHXaQpVKDlGpUUMmOGJiZC2PzDU1nj9P33fmWLS9N5o2lQmPRo2Axo3Tx66XMe+++y4WLFiAI0eOYMCAASV67AkTJmDBggXYuHGjznSZRMUlKioKGo0GFSpUKJb92dnZQaPRIDExEWYZavzExsYCQJaEhTb5ERISUrhkhnb67N9/l8P2tENNzp9P3+bYMeCTT4CVKwu+fypVmMwgIiIiMnTZJTiSk2X36sBA4No1OauKv7/skaElhExehIbq7s/ERPbgqFZNfp+QIHt6REbqbhcXBwQEyCWzKlVkD47sFnv7Utujo379+ujevTs8PT1LPJlRs2ZNTJs2DXPmzMHw4cPT6g4QFRdbW1tYW1unJRuKysnJCQAQHByMxo0bp61/+vQpgKzJjGfPngGQSZBCGzFCJjNSU2VPssz1ggBg1Sr52OTJhT8OGTwmM4iIiIhKIxOT9BocGT18CFy+DFy6lL7cvq073CQ5GXj0SC4ZGRvLwqFVq8qeHAkJwJMnwKs3JjqePcu+Nwcgh880bix7cdjbA/XqyakU69aVX21tDboQqYeHBzw8PPD48eMs3eT1be7cudixYwc++ugjbN++PcvjDx8+xL1799CtWze9xhEZGYkDBw7g4cOHaNGiBXr16pXjkIKMEhMT4e3tjYsXL8LNzQ0dO3aEWq3Wa6wZlda4S5KLiwvCMyY9i2D8+PH45ptv4Ovrq5PMCAwMRKtWreDg4KCzfVhYGFQqFRo0aFD4gw4fLntePHsGXL2a83bTpgEODnIWlGLy+PFjXL9+Hd27d8/yWGGvIUO49nI7r6LEqO9zK50pcyIiIiLKXr16cprYL7+UhfJu3ABiY4GzZ4GffwY+/RTo3VsmGTInFFJS5DAV7ZCWoKD0REb16rKGRps2cnF0lEmP7MTHyyTK3r3ADz/I8exDhsgpZ2vXlmPeGzUCunWTxVC//BJYs0YWK718Wb5JUdCQIUNgYWGBbdu2lfixLSwssH79eoSEhCAuc1HXBw/g5+eH7t27o3///llmiiguFy9eRPfu3eHs7IyZM2fi9u3b6NKlS5ZijpmFh4fDyckJDx8+xLhx47B//34MGDAgrX6CvpXWuPUpJiZG5ysAdO3aFVeuXMmxjbb3REJCQraPz5w5ExMmTAAge3pMmTIFy5YtgxAird2hQ4ewYcMGGGXqoXX//n306tUL5ubmhT+pChWAYcNk0jTjbFCZJSfL7V7NuFIUERER+Oyzz9CwYUPsy2Yq2MJeQ0pfe3mdV1FiLJFzE0RERERUPsXFCXHunBCbNwvx+edCDBggROPGQqjVQshBKvlbrK2FaNJEiNathWjTRggXFyFq1RLCyKhg+8m4VKwoY+ncWcb13ntCzJkjxMqVQnh5CeHtLcS1a0JERurlVzNx4kTh4uKil33nR2pqataV5ubiy1q1hLGRkTAxNhZqtVpMmzZNPH36NNd9ARA7d+7M13E1Go1o2bKlmDlzps76Dh06iJ49e+bazs3NTfTv3z9tXUpKiqhfv76YNWtWvo6d0dChQ8XQoUPzvb0hxL1z505hKG+vjh07JiZMmCAACABi8ODBYs+ePUIIIaKiokSNGjXE7du3s7Q7cuSIGDFihAAgatSoIX7++WcRFhams42jo6OoUaOGSElJEULIa3XWrFmiX79+YsWKFWL27Nli8+bNWfadmJgoqlatKo4dO1b0E+zfXwgrq/z9L3F0FOLZMyGEEMOGDRPDhg0r8OH8/f3FpUuXBAAxbdo0nccKew0V9z1TkPtcK7fzKkqMJXRfeRnG3UZEREREhiMhQYiLF4XYsUMmEN5+W4j27YWoUqXgSQlTUyFq15ZvKLTJjubNhbC3F6Jy5cInOzIfo04duf8+fYQYM0aITz8V4ptvZPJjyxYhfvtNCB8fIa5eFSIkRCZycuHn5ycAiICAgBL6peeDmZnoAwjVqzeoAISJWi0sLSzEkiVLREJCQrbNCvImx9fXVwAQ27dv11k/ZcqUXH8fx48fFwDEoUOHdNbPmTNHVKpUScTl8fvOrKDJDEOI25CSGXn56aefxIcffliotrGxsSIqKirL+pSUFPH48eMc23l5eYkBAwYU6phZ9OhRsP8Rb74pREpKoZMZQshkTHZv+gt7DRX3PVOYZIYQOZ9XUWIsofvKizUziIiIiEiXmRnQsqVcMouKkt2279zR/Xr7tqyvkVlSUvb1OTKqWFEWI61cGTA1lW8/kpJkAdK4ODlbQW5dk5OSsi90mhcTE1nI1No6y+JapQocq1eH57RpaDt2rOzabm6eHmPlyunrrKzkOkvLgh2/oITARcgshlayRoPkuDh8MXs2fly6FEu+/x6jx46FqpA1SW7cuPHqUEJnffv27QEAPj4+aNu2bZZ2e/fuBQA0b95cZ32zZs0QHx+PI0eOYNiwYYWKKT9Ka9xKmThxIkaNGoULFy6gdevWBWqbUw0StVqNmjVrZvvY9evXsXXr1mzrwBSYRpN9rZ7c/PknMHNm0Y+djcJeQ6Xh2jP0c2Myg4iIiIjyz8YG6NBBLpnFxuomOe7fB0JCgAcPZC2O58+z3+eLF7JwaV4qVZLJh0qVZMLF1FQWNk1JARIT5dSzz58DL1/m71ySk+XsLzkUQxwLYFlEBP7j54d8j/CvWFHGZm0tkyXaBIe1dXqNEm0SBJCFVitXTm9fubJcB8httFNoqlSITUnB4xwOmyoEnkRF4V0PD/w4axZWLFyILhMn5jfqNNopOwMCAvD222+nrW/UqBEAWYA0O7df1SWoVauWznrtjCz6qu+hZShxuwLArl0FaqMEIwCb3N0xdcYMTOzRA+1f/Z704UFEBBZ7eWHj2LGo8NtvRd/h0aOFq6vzww94vV07HC9K8dFsFPYaUvqeyQ9DPzcmM4iIiIioeFhaAq1aySU7CQmyh8bdu/JrWJju9zdvyoRITuLj5ZJfZmZyWtuKFWViwNRUJgqMjGTvD41GJjQSE2UCJD5e9gR5ZQyArwAcBDA8v8d88UIueihiegW6vTIy085Xczk8HF0nTcLgjz/GsjFj4JBLm8y6dOkCU1NTeHt7QwiR1sMjOjoaAGBvb59tuydPnkCtVsPU1FRnfcWKFQEgzyKcRWUocX8CyNk2SgEzAOsAPPzf//R6HFMAmwCovL31epz8mBQYiPB8zG5TEIW9hpS+Z/LD0M+NyQwiIiIiKhnm5kDDhnLJSUSE7M3x6JH8/vFjOXwl8/cREbrTzWYnMVEukZEFj9XSErXNzNArLg6eRkYYXq+e7GlhbCyTIWq17GmhUsnECCB7iKSmyuXly/SvRkYySSOE3D4hQS4FdAXyxXtKHttpHz/w4gUO/fQTPgXQ/vPP5e9vxAggh6EAAGBnZ4eFCxdi5syZ8PDwwPDhw/HPP/9gx44dAICW2Q09Qs5DD7QzF+h7iltDiPvly5ewVKtzHxJlgOrpef+18t5E75IAPABwTwjU9PbG33364I0FC4BXw5CKorDXkNL3TH4Ywrm9fPkyredVZkxmEBEREZHhqF5dLnmN409NlcNDIiJkguPx4/Tvw8Nlz4hnz+SwE+33ufX6yCw2FoiNhQfRcO9xAAAgAElEQVSAkQCCr1+HXVHOKy9WVumJkYzDTjK8Kbj6zz8wyqZpZirIT8OTIRMb3wE4fu8eNn38MZru2QOsWgVkGsue0YwZM9ChQwccPXoUPj4+GDlyJM6cOYNbt27lWF/Bzs4OGo0GiYmJMDMzS1sf++p37uzsnI/Ii0bpuCMjI6GpUCHX3y0Vk5s3dZKUAkAYgLsA7mVYbrxaF470Xk09hMChP/4Arl8H5s0Dxo4tUiiFvYYM4Z7JiyGcW2RkJGxsbLJ9jMkMIiIiIip9jIwAW1u55PfNo0aTfZIjp+9fvsSAly9hc+kSfq1UCbPValmXQx+fvL8aDpHl+wzOQ37CrKVCek8NAVkHoS6AlgCaAXB+tagtLHDDyQlNd+8G6uXvc/hu3bqhW7duAIB79+7h4MGDWLZsGSxzKHLq5OQEAAgODkbjxo3T1j99+hRAyb0xUzLuq1ev4t1KlYDTpwsbPuXTSgDXAdwBcBvAQ8jkHSDvA1PI+yJjLyYVgI4qFTYAMFergRYtgNGjixxLYa8hQ7lncmMI53b16tW0/WXGZAYRERERlQ9qtZw1pVq1fDcxBTBy6lR4/vknPr9xQ9ZiSEmRPTfi4+VwkehoOZwkIUEmQxIT5WOxsXLb6Oj0ITFF+P7a3bvyNADUh0xauLxanAA4QtZBAAA4OwPDhgFvv42vf/0Vv/76qxwqU0BJSUkYMWIEmjZtig8++CDH7caPH49vvvkGvr6+Om9eAgMD0apVKzg4FKRyR9EpEffx48cx3cYm+1l9qFjdBLA6h8dSAWQexGViZIQWDRrgB09P1H/tNZw7cQLtTEzk36pW0QbCFPYaMrR7JjuGcG7Hjx/HO++8k/2D+Z7glYiIiIioHAoICBAAhK+vr2IxJL14IbwAcRUQSXIwStalUSMhvvxSiMuXddqeOXNGABDnzp0r0DHj4uLEmDFjxPDhw8WTJ0+y3WbGjBli/PjxQgghPv30U+Hi4iJSU1OFEEK8fPlSODg4iMDAwAKf79ChQ8XQoUML3C4/cWeMubji9vf3FwDE2bNnCxUzFcyj/v2FqeyQlOdiYmIinJ2dRWRkpEhNTRX16tUTs2bNKvAxHz9+LACISZMmZXksv9eQPq49LQBi586dBW6X23kVJEYF7isvlRCZJmMmIiIiIiIdrVq1Qvv27fHzzz8rE0BSkpydJbO6deXsGSNH5lrMsFmzZmjfvj08PT3zPFRkZCQOHDiADRs24LPPPsOgQYNy3NbJyQlRUVF49OgRjIyMMHv2bAQFBaFXr14ICwuDk5MTRheiK/+wYcMAALsKMM1pfuPOGLNarYYQoshxe3h4ICAgAFeuXMl3GyqCESMwzcsLPyF9eEl2TExM0KhRI5w6dQrVXvXImjdvHtasWYN79+6lza6Rl99//x2//PILdu7ciRo1amDRokXo169fWiHL/F5D+rj2tFQqFXbu3InhBZhNJ6/zUvrc8rivdjGZQURERESUh+XLl2POnDkICwvLsVK/XiUmytlgAMDGBnjrLWDMGOCNN2T9kDz8+uuvePfddxEQEIBWOU2d+8r+/fvRokULNMxt1plX4uLikJycjCpVqqSt02g0ePr0KWrmMmtKXgqTzMhv3NnFDBQ+7osXL6Jdu3bYtGlTzt3hqXiNGIEwLy/YQ7eOTEYmJiaoU6cO/Pz8UCvDUJLw8HA4ODhg2rRpWLBgQbGGldc1VNzXXkaFSWYUREmfWz7uKyYziIiIiIjyEhkZidq1a2P9+vWF+tS0yBITgQ8/lFOrvvGGrP9RAEIIdOvWDampqTh16pSs/WHACpPMUEr37t2RlJQEX19fg/+9lhlz50KYm6PJTz/hwaNHSEnRnbDYxMQE1atXh5+fH+rXr5+l+Q8//IAvv/wS165dQ4MGDUoqar3SdzKjpOXjvtqVn9mdiIiIiIjKtapVq6Jv3775GqahF2ZmwPr1QM+eBU5kAPKNzvLly3H69GmsXLlSDwGWTytWrMCpU6ewcuVKJjJK0vz5UM2ejU1bt2b5vRsbG6Nq1arw8fHJNpEBAFOnToW9vT0mTJiA5OTcBqqQEvJ7XzGZQURERESUDx4eHjhx4gTu3LmjdCiF0rZtWyxcuBDTp0/Hb7/9pnQ4pd6ff/6JTz/9FIsWLULbtm2VDqdccnNzwwcffAATExMAMpFRuXJlHD9+PNceFyYmJti9ezcCAgIwefLkkgqX8qEg9xWTGURERERE+dC3b1/UrFkTW7ZsUTqUQps9ezZGjx6NUaNGwd/fX+lwSi1/f38MHz4c77zzDj7//HOlwynXZs2aBZVKBZVKBUtLS/j4+MDR0THPdi4uLvj111+xadMmLFy4sAQipbwU9L5iMoOIiIiIKB+MjY0xatQobNq0CampqUqHU2hr166Fm5sbXn/9dezevVvpcEqd3bt34/XXX4ebmxvWrl2rdDjlXq1atfDhhx/CysoKJ06cgJOTU77buru7Y9WqVZg3bx4mTZrEIScKKsx9xWQGEREREVE+eXh44MGDB/D29lY6lEIzNTXFwYMHMX78eAwfPhxz5sxBQkKC0mEZvISEBMyZMwfDhw/H+PHjcfDgQZiamiodFgGYOXMm/vrrL7Ro0aLAbd9//33s27cP27dvR+/evXH//v3iD5ByVJT7iskMIiIiIqJ8cnFxQbt27ZQrBFpM1Go1VqxYgdWrV2P58uVwcXHBvn37lA7LYO3btw8uLi5Yvnw5Vq9ejRUrVkBdiEKspB+2trZFqlvi7u4OHx8fPHr0CM7OzpgzZw5evHhRjBFSdop6XzGZQURERERUAB4eHti9ezeeP3+udChFNnnyZNy4cQOdO3fGkCFD0KZNG6xevRohISFKh6a4kJAQrF69Gm3atMGQIUPQuXNn3LhxgwUjy6iWLVvi8uXLWLhwIVasWAF7e3vMmjUL586dgxBC6fDKjOK8r1SCfxkiIiIionyLjo5GrVq1sGLFCkyYMEHpcIpNQEAAVqxYgb179yI+Ph52dnZo3LgxbGxsYGRUsp+Bnj59GgDg6upaosfVaDR49uwZbt26hZCQEFSqVAlDhgzB1KlT0a5duxKNpTBOnToFb29vXL9+HcOGDcOAAQMQGxuLbdu24d69e2jcuDH+/e9/o2LFijnuIyUlBf7+/ujcuTMAIDExEd7e3rh48SLc3NzQsWPHfH16nlu78+fPo2rVqjlOnZqTu3fvYs+ePZgyZQoqVKhQoLYFER4ejjVr1mDjxo14+PAhKleuDBcXF1SrVg3m5uZ6O25R7Nq1C506dYKdnZ3SoWShp/tqF5MZREREREQFNHLkSAQHB8PX11fpUIpdQkICfHx8cP78edy7dw/Pnj0r1QVPC8LIyAjW1tZo2LAh2rRpAzc3N4N985pZYGAg5s+fj927d2PJkiX49ttvcfr0afTt2xeWlpZ48OABkpKS0KhRI/j4+MDW1jbLPqKjo7F69WpMmTIFlpaWCA8PR6dOnfDFF19g4MCBWLp0Ka5du4YDBw7kmtDIq11KSgqmTp2Kt99+G6+99lq+z3HRokX48ccf8ejRIxgbGxfq91RQly5dwpkzZ3Dt2jU8e/aM9WUKQU/3FZMZREREREQF9eeff6J37974559/8jUNJJG+9e3bF507d8ZXX30FIQTCwsIwYcIELFmyBC1atEBERAS++OILrF+/HuPGjcOGDRt02oeGhuL999/Hli1bYGVlhdTUVHTr1g02NjY4cOAAAPkJe6NGjTBy5EgsWbIk2zjy206j0cDd3R3fffcdmjdvnq9zbN26NTp16oQ1a9YU9tdEZccu1swgIiIiIiqgnj17ws7ODr/88ovSoRABAIKCgtJ6S6hUKoSFhWHUqFFpM3xUr14dCxYsgJGREfz8/LK0nz59OgYNGgQrKysAwMmTJ+Hj44OJEyembaNWqzF27FisWrUK8fHx2caR33ZqtRrTp0/HpEmT8nV+d+/excWLFzF06NB8bU9lH5MZREREREQFZGRkhNGjR2Pz5s3QaDRKh0PlmLe3N1avXo3g4GD4+/tj7dq1OHjwIOzt7fHvf/9bZ9tatWqhbdu2qFKlis56f39/HD58WCdRsHfvXgDI0muiWbNmiI+Px5EjR7KNpyDtevTogdjY2LQ2udm5cyeqV6+Obt265bktlQ9MZhARERERFcK7776LsLAwHDt2TOlQqByrX78+nJ2dIYRAzZo10bZtWzg4OKBq1apQqVRZtg8ODkafPn101i1duhSurq6wtLRMW3f79m0AMgGSUY0aNQAAN2/ezDaegrbr0qULFi5cmOd5btu2DSNGjCixWhlk+JjMICIiIiIqhCZNmqBz587w9PRUOhQqx+zt7dGmTRsAQJ06ddCuXbsc67icPHkSxsbG+OSTT3TWX758GbVr19ZZ9+TJE6jVapiamuqs186EEhYWlu0xCtrOxcUFV65cQVJSUo7nGBAQgKtXr2L06NE5bkPlD5MZRERERESF5OHhgf379+Pp06dKh0KUK41Ggzlz5uDgwYOwsLBIW5+UlIS7d+9m6UmRcZvM+wGQ7WwohWlnZWWFlJSUtB4d2dm1axeaNm2KDh065LgNlT9MZhARERERFdKIESNgamqKnTt3Kh0KUa4+++wzTJ8+Ha1bt9ZZHxUVBY1GgwoVKuist7Ozg0ajQWJios762NhYAICzs3O2xyloO23yIyQkJMfYFyxYgD179uT4OJVPTGYQERERERWShYUFBg8ezKEmZNDWrVuH1q1bo3///lkes7W1hbW1dVqyQcvJyQmArLGRkbYXUk7JjIK2e/bsGQCZBMmJmZkZXFxccnycyicmM4iIiIiIisDDwwOBgYG4dOmS0qEQZbFv3z4IITBmzBid9d7e3mnfu7i4IDw8XOfx8ePHw8zMDL6+vjrrAwMD0apVKzg4OGR7vIK2CwsLg0qlQoMGDQp8blS+MZlBRERERFQE3bp1Q6NGjfDLL78oHQqVU6GhoQCAx48f66z/66+/8N133yE5ORmrVq3CqlWr8OOPP+K9997D5cuX07br2rUrrly5otPW1tYWU6ZMwbJlyyCEAAAkJCTg0KFD2LBhA4yM0t9Kzpw5ExMmTChwOwC4f/8+evXqBXNz82L6bVB5oRLaK4yIiIiIiApl/vz5WL16NUJCQmBiYqJ0OFSOnDlzBkuXLsW+fftgZ2eHhQsXYsCAAbhz5w5ee+01xMfHZ2ljbm6O0NBQ2NjYAJBDPRwdHeHn54dGjRqlbSeEwOzZsxEUFIRevXohLCwMTk5OWWYVcXJyQlRUFB49egS1Wp3vdklJSahduzZ27NiBHj166OG3Q2XYLiYziIiIiIiK6MGDB2jYsCH27t2LAQMGKB0OUYGtXbsWV65cwapVq7I8ptFo8PTpU9SsWTPbtnFxcUhOTkaVKlUK1G7Xrl3YunUr9u/fX/QToPJmF4eZEBEREREVUf369dG9e3cWAqVSa+LEiYiMjMSFCxeyPKZWq3NMSACyEG7mREZe7a5fv46tW7di+/btWR7LPBMKUXaYzCAiIiIiKgYeHh44fPhwlroFRKWBkZERNm3ahDVr1uDcuXN6PdaDBw+wePFibNy4McuUsKmpqejXrx/mzp2r1xio9GMyg4iIiIioGAwZMgQWFhbYtm2b0qEQFYqZmRnWrVuXay+M4mBqaopNmzal1ezIaPHixfD29kbfvn31GgOVfqyZQURERERUTCZNmgQ/Pz9cvXpV6VCISh1fX190794dy5Ytw8cff6x0OGTYWACUiIiIiKi4nD59Gp07d8a5c+fQrl07pcMhKjUePXqE9u3bo23btjhw4ABUKpXSIZFhYwFQIiIiIqLi4urqCkdHRxYCJSqAhIQEDB48GJaWlti8eTMTGZQvTGYQERERERWjsWPHYuvWrXj58qXSoRAZPCEEJkyYgJs3b+LQoUOwtrZWOiQqJZjMICIiIiIqRmPGjEFcXBwOHTqkdChEBi8lJQXGxsbw8vJCkyZNlA6HShHWzCAiIiIiKmZ9+/aFEAK///670qEQEZVFrJlBRERERFTcPDw8cPToUQQHBysdChFRmcRkBhERERFRMRswYABsbGzw66+/Kh0KEVGZxGQGEREREVExMzU1xciRI+Hp6QmO6iYiKn5MZhARERER6YGHhwdu3boFHx8fpUMhIipzmMwgIiIiItKDNm3aoHXr1vD09FQ6FCKDkJSUhNu3bysdBpURTGYQEREREemJh4cHvLy8EBMTo3QoRIpbsGABXF1d8eLFC6VDoTKAyQwiIiIiIj0ZNWoUNBoNvLy8lA6FSFGBgYFYunQpFixYgIoVKyodDpUBKsGKREREREREejNy5EgEBwfD19dX6VCIFPHixQu0adMGdnZ2OHr0KFQqldIhUem3iz0ziIiIiIj0aNy4cfDz88M///yjdChEipg9ezaePHkCT09PJjKo2DCZQURERESkRz169ED9+vVZCJTKpTNnzmDVqlVYsWIF6tatq3Q4VIZwmAkRERERkZ7NnTsXa9euRXBwMExMTJQOh6hEpKamwtXVFebm5jhx4gR7ZVBx4jATIiIiIiJ98/DwQEREBI4cOaJ0KEQl5vHjx1CpVFi7di0TGVTs2DODiIiIiKgE9OjRAxYWFti/f7/SoRARlXbsmUFEREREVBI8PDxw+PBhhIWFKR0KEVGpx2QGEREREVEJGDJkCCwtLbFlyxalQyEiKvWYzCAiIiIiKgHm5uZ4++23sWHDBnCkNxFR0TCZQURERERUQjw8PHDz5k2cPn1a6VCIiEo1JjOIiIiIiEpIu3bt0LJlS2zcuFHpUIiISjUmM4iIiIiISpCHhwd27tyJ2NhYpUMhKlbr1q3D8ePHlQ6DygkmM4iIiIiIStA777yD5ORk7N69W+lQiIrNo0ePMH36dAQGBiodCpUTKsHqQ0REREREJWr48OEICwvDqVOnlA6FqFiMHz8eR48exc2bN1GhQgWlw6Gybxd7ZhARERERlbBx48bBx8cH169fVzoUoiL7559/sHnzZixevJiJDCox7JlBRERERFTCUlNT0aBBA/z73//G4sWLlQ6HqEjeeusthIWFISAgAEZG/LycSgR7ZhARERERlTQjIyOMGTMGmzZtQkpKitLhEBWar68vjhw5gu+++46JDCpR7JlBRERERKSAe/fuoXHjxjhw4AD69eundDhEhfLGG28gOTmZ9V+opLFnBhERERGREho0aIBu3bph48aNSodCVCgJCQmoWbMmFi1apHQoVA6xZwYRERERkUK2bNmCcePGITg4GLa2torFERUVhaCgIDx79gyJiYmKxWGIzMzMUKVKFbi4uMDGxkbpcIhI2sVkBhERERGRQl6+fInatWvjq6++wqefflqixw4KCsLGjRvx22+/4ebNmyV67NLKwcEB7u7u8PDwgIuLi9LhEJVnHGZCRERERKSUChUqYMSIEVi/fn2JHfP27dsYMGAAmjVrhoMHD2LgwIH4/fffERISgoSEBAghuGRYEhISEBISgt9//x0DBw7EgQMH0KxZMwwYMAC3b98usb8bEelizwwiIiIiIgX5+/ujY8eOOH36NDp16qS34yQkJGD+/PlYvnw5mjRpgqVLl6J3795QqVR6O2ZZJITAH3/8gZkzZ+LWrVv45JNPMHfuXJibmysdGlF5wmEmRERERERKa9myJTp16oS1a9fqZf/h4eEYOHAg/vnnH3zzzTeYPHkyjI2N9XKs8iIlJQU//fQTvv76azg5OWH//v2oUaOG0mERlRccZkJEREREpLR3330XO3bswIsXL4p930FBQejYsSMiIiJw+vRpTJkyhYmMYmBsbIwpU6bg9OnTiIiIQMeOHREUFKR0WETlBpMZREREREQKGzNmDBITE7F79+5i3W9wcDB69uyJunXr4syZM3B0dCzW/RPg6OiIM2fOoG7duujZsyeCg4OVDklvhBDYvn07kpKSlA6FiDUziIiIiIgMwdChQ/H06VOcOHGiWPb34sULdO/eHXFxcfDz84O1tXWx7JeyFxsbiy5dukCtVuPUqVOwsLBQOqRit2fPHgwfPhyXLl1Cs2bNlA6HyjcOMyEiIiIiMgQeHh44efJksc2QMWHCBDx48ABHjhxhIqMEWFpa4uDBg3j06BEmTZqkdDjFLjU1FQsWLMCwYcOYyCCDwGQGEREREZEB6N27N+rWrYtNmzYVeV8nTpzA9u3b4enpCXt7+yLvr6TExcVh48aNmDNnDo4cOYLk5GSlQyoQe3t7eHp6Yvv27cXWw8ZQeHl5ISgoCHPnzlU6FCIATGYQERERERkEtVqN0aNHY9OmTUhJSSn0fjQaDT766CO4u7ujb9++xRihft24cQOtW7eGra0tZs6ciejoaDRu3BgnT55UOrQC6du3L/r164cpU6YU6e9oSDQaDebPn4+3334bTk5OSodDBIA1M4iIiIiIDMbdu3fRpEkT7N+/H+7u7v/f3p0GVV09YBx/WJJFNCnBcqR/YYhIombuzkC90BE3xIVsUISAKMqpGcRpmXphjk46qTM0EwIaaoloKS7klo5b4piOmZSKQ4YkLqAksi/3/6KJicLkXsHfvZfv5+Xxd+59zvDqPp7fORZ9xoYNGxQTE6P8/Hz5+fm1c8KOExoaqt69eys9Pb15bN68eSosLLS5QqOgoECBgYFas2aNIiMjjY7zwL744gvFxsYqPz9f/v7+RscBJM7MAAAAAKyHr6+vXnrpJaWlpVn8GZ9//rnCwsJsqsiQpJKSkn9dberi4qLa2lqDElnOz89PYWFhSk1NNTrKA6uvr9eiRYsUExNDkQGrQpkBAAAAWJG4uDjl5uaqqKjI7LnXrl3T8ePHNWfOnA5I1rHCw8OVl5enDRs2SPrz/IytW7fq7bffNjiZZSIjI/X999/r+vXrRkd5IKdPn1Z5ebk++OADo6MALfCaCQAAAGBF6urq5OPjo8TERH344Ydmzc3KytLcuXNVXl4ud3f3DkrYMa5fv67g4GBduHBB77zzjvLz85WQkKBp06YZHc0iVVVV6tGjh9avX6+IiAij4zyQ6upqubm5GR0D+DteMwEAAACsSZcuXRQVFaX09HQ1NjaaNffs2bPy9/e3uSJDknr16qUjR46ob9++WrFihSoqKjR69GijY1nM3d1d/v7++umnn4yO8sAoMmCNKDMAAAAAK/Paa6+puLhYe/bsMWteSUmJfHx8OihVx8vIyFBwcLBiYmJ0/PhxjRgxwqLXbaxFnz59VFJSYnQMwC5RZgAAAABWpm/fvgoODjb7INCqqip17dq1g1J1rLVr12rTpk1KTU1VRkaGMjIy9PvvvysxMdHoaBbz8PDQ3bt3jY4B2CXKDAAAAMAKxcXFaefOnbp69Wqb55hMJjk4OHRgqo6TmZmpCRMmyNnZWZIUExOjuLg47d27V+Xl5Qans4yDg4M4ohDoGJQZAAAAgBWaMWOGPD09tXbtWqOjPBRnz579V2kxdepU1dXV2fyNIADaH2UGAAAAYIW6dOmiyMhIrV692uyDQG1RWFiYtm7dqqampuaxvLw8BQUFyc/Pz8BknUtBQYHKysqMjgHcF2UGAAAAYKXi4+N15coV7d+/3+goHS4lJUUTJ07UoEGDtGrVKsXFxen06dPatm2bHB352fIwmEwmRUVFKSYmxugowH05Gx0AAAAAQOv69++vsWPHKi0tTePHjzc6Todyd3dXenq6qqqq9Ntvv2nu3Lny9PQ0Olansn79ep04cUInT540OgpwX1ScAAAAgBWLi4tTTk5Op7ni093dXQEBARQZD1lpaamSkpKUmJio559/3ug4wH1RZgAAAABWbObMmerevbsyMzONjgI7lpiYKDc3Ny1evNjoKECbUGYAAAAAVszV1VWRkZFKS0trcTgm0F527dql7OxspaSkqFu3bkbHAdqEMgMAAACwcgkJCSosLNTBgweNjgI7c+fOHSUkJGjOnDmaPHmy0XGANqPMAAAAAKxcQECARo8erbS0NKOjwM4UFhbK29tbn376qdFRALNQZgAAAAA2IC4uTlu3btWNGzeMjgI7MnjwYJ06dUo9e/Y0OgpgFsoMAAAAwAZERESoa9euHAQKAKLMAAAAAGyCm5ubXnnlFaWmpspkMhkdBwAM5Wx0AAAAAABtEx8fr88++0yHDh1SSEhIq88cP35cM2fOfLjB0Kq8vDyNGjXK6BiAXWJnBgAAAGAjgoKCNHz4cLs6CLS4uFhbtmwxOgYAG+NgYo8aAAAAYDPS09OVmJio4uJieXl5yWQyadeuXVq6dKk8PDzUvXt3ZWdnGx2zzbKzsxUREWGXr87MmjVLkqzm77F//36FhITI2ZkN+rB5m9mZAQAAANiQ2bNny9XVVevWrdOXX36pwMBATZ48WceOHVN1dbXR8WClNmzYoPHjx2vr1q1GRwHaBZUcAAAAYEOcnZ01ZswYLV68WOXl5XJwcJAkOTo6UmagVenp6UpISNCCBQs4TwV2g50ZAAAAgA2oqKjQqlWr5OPjoz179qi8vFwmk0lNTU2SpEceeUQ1NTUGp4S1WbFiheLj4/Xee+9p6dKlRscB2g07MwAAAAAr99FHH2n58uWqq6tTQ0NDq880NTWxMwPN6uvrNX/+fKWmpuqTTz5RUlKS0ZGAdkWZAQAAAFi5F154QXV1dc27MFrT0NCgqqqqh5gK1qq6ulqhoaE6efKktmzZovDwcKMjAe2OMgMAAACwcpMnT1ZOTo7CwsJkMplavfnDZDJZXGaUlZUpJydHRUVFCgoK0rhx4+Th4XHfebW1tTp06JDOnDmjsWPHasSIEXJycrIog6WuXbum8+fPKyQkpN3yWcO6HoSbm5uGDh2qlStXatCgQUbHAToEZ2YAAAAANiA0NFRZWVlydHRsPvTznyx5zeTMmTMKCQnRgAEDlJycrEuXLmnMmDEqKU/6w/UAAAfYSURBVCn5z3k3btxQQECAioqKFBMTo23btmnq1KlqbGw0O4Mlbt68qaSkJPn6+rZ6Q4el+YxeV3tZvnw5RQbsGmUGAAAAYCPCw8OVlZUlBweHVguNurq6Vndt3EtTU5PmzZun0NBQjRw5Uu7u7kpOTparq6uioqL+c9706dM1cOBAxcbGqmfPnlqyZInOnTun999/36K1mevy5cuaO3duqwWOpfmsYV0A2oYyAwAAALAhM2bM0MaNG1stM0wmk2pra9v8WXl5efrxxx81ZMiQFuPDhw/Xvn37dOrUqVbnHT58WEePHlVcXFzzmJOTk6KiopSSkqLKyso2Z7DUsGHD1L9//3bNZw3raqu6ujrV19cbHQMwDGUGAAAAYGNmzZqlNWvWtFpomPOqyYULFyTpX7s5hg0bJkk6evRoq/O++eYbSdLAgQNbjD/33HOqrKxUbm5umzN0BEvzWfu6JKmkpERLliyRn5+f1q5da3QcwDCUGQAAAIANioqKarXQMKfMcHNzkyT98MMPLcb79u0rSSoqKmp13qVLlyRJTz75ZItxb29vSdLFixfbnKEjWJrPWtdVXl6ujRs3aurUqXrqqae0fPlyTZ8+XRMmTDAkD2ANuM0EAAAAsFHz5s1TU1OTYmNjZTKZ5ODgYFaZMWbMGHXp0kWHDh1qni9Jf/zxhyTp6aefbnXe9evX5eTkpC5durQYd3d3l6T7Hh7a0SzNZ23rKiwsVHx8vA4fPixJevHFF7Vu3TqFh4fLxcXloWYBrA1lBgAAAGDDYmJiVFtbq8TERJlMJrPKDB8fH3388cdKTk5WdHS0Zs2apV9++UVZWVmSdM/bMO51betfN3488cQTZq6ifVmar73XZTKZ5Oh4783wFRUV6tat2z3//dFHH5W3t7cyMzM1YcIE9ejRw6zvB+wZZQYAAABg415//XU1NDRo/vz5qqioMGvuggULNHz4cO3du1dHjx7Vyy+/rLy8PBUUFPzrYNC/+Pj4qLGxUbW1tS12CPz13QMGDLB8Me3A0nztva47d+6ooKBA48ePV1NTk6qrq1VVVaWbN2/q5s2bMplMqqmpuedVu48//ri++uors74T6CwoMwAAAAA78NZbb2n79u3Ky8sze25wcLCCg4MlSb/++qu2b9+uZcuW3XPXQEBAgCTpypUrevbZZ5vHS0tLJRlfZliar73XdfXqVbm6uqpPnz5ydnaWi4uLPDw81LNnT3l5ecnLy6vF6z0A2o4yAwAAALATsbGxOnjwoKqqqprPeTBHXV2dIiIi5O/vrzfeeOOez7366qtatGiRjh071uJH/6lTpzR48GD169fPovztxdJ87bmuyspKXbhwQevXr1dERITliwHQKm4zAQAAAOxEcHCwTCaT9u/fb/bcyspKxcXF6ZlnntH+/fvl7Nzy/z2Tk5MVGxsr6c+zI958800tW7as+VrXmpoa7dixQxkZGf95TkR7un37dvN3/525+f5aW3uu67vvvlNjY6NCQkIeYIUA7sXB9M9LpQEAAADYrLFjx6p3797Kzs5u0/NlZWXKyclRRkaGkpKSNG3atFafCwgI0K1bt3T16lU5OTnJZDLp3XffVX5+vsaNG6eSkhIFBARozpw5ZuXNzs5WRESEzP1Z8u233yozM1ObNm2St7e3Fi9erEmTJjUf0mlOvr+vzdHRsV3WNXPmTF27dk1Hjhwxax6ANtlMmQEAAADYkQ0bNigmJkb5+fny8/O77/Pbtm1TUFCQfH19//O5u3fvqr6+Xp6eni3GGxsbVVpaql69elmU19Iyo63akq+1tT3IugoKChQYGKg1a9YoMjLSotwA/hNlBgAAAGBPGhsbNXToUPn4+GjHjh1Gx7mvji4zjDBp0iRdvnxZZ86c+dfrOgDaxWbOzAAAAADsiJOTk1auXKmdO3cqNzfX6DidTm5urnbt2qWUlBSKDKADUWYAAAAAdiYkJESzZ89WdHS0Ll++bHScTuPy5cuKjo7W7NmzOfgT6GCUGQAAAIAdSk9P1//+9z+FhoaqvLzc6Dh2r6KiQlOmTFHv3r21evVqo+MAdo8yAwAAALBD7u7u+vrrr1VeXq7JkyerrKzM6Eh2q6ysTKGhoSotLdX27dvl4eFhdCTA7lFmAAAAAHbKx8dH+/btU3FxsUaOHKnz588bHcnunD9/XiNHjlRxcbH27dsnHx8foyMBnQJlBgAAAGDHAgMDdeLECXl5eWnUqFFKSUlRQ0OD0bFsXkNDg1JSUjRq1Ch5eXnpxIkTCgwMNDoW0GlQZgAAAAB2ztvbWwcOHFBCQoKSkpI0ZMgQ5ebmqqmpyehoNqepqUm5ubkaMmSIkpKSlJCQoAMHDsjb29voaECnQpkBAAAAdAKurq5asmSJzp07J19fX02cOFH9+vXTwoULtXv3bhUXF6umpsbomFanpqZGxcXF2r17txYuXKh+/fpp4sSJ8vX11blz57RkyRK5uroaHRPodBxMJpPJ6BAAAAAAHq78/HytXbtWO3bs0MWLF42OYxP69eunKVOmKDo6WgMGDDA6DtCZbabMAAAAADq5W7du6eeff9bt27fZnfEPLi4u8vT0VGBgoB577DGj4wD4E2UGAAAAAACwKZs5MwMAAAAAANgUygwAAAAAAGBTKDMAAAAAAIBNcZa02egQAAAAAAAAbZT3f6L8sv/xEfX6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto_reduccion.pert()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El coste de la reducción ha sido:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2 * datos_proyecto.loc['A', 'cur'] + 2 * datos_proyecto.loc['H', 'cur']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apartado 4\n",
    "> Si el número máximo de recursos durante las 6 primeras semanas es 4, determinar si será posible realizar el proyecto en el tiempo obtenido en el apartado 1."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Situación inicial de partida"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Representamos la demanda de recursos por periodo utilizando un diagrama de Gantt."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col8 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col9 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col10 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col11 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col0 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col1 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col2 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col3 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col4 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col5 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col6 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col7 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col8 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col9 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col10 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col11 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col0 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col1 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col2 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col3 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col4 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col5 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col6 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col7 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col8 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col9 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col10 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col11 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col0 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col1 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col2 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col3 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col4 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col5 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col6 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col7 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col8 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col9 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col10 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col11 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col0 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col1 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col2 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col3 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col4 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col5 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col6 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col7 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col8 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col9 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col10 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col11 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col0 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col1 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col2 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col3 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col4 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col5 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col6 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col7 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col8 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col9 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col10 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col11 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col0 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col1 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col2 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col3 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col4 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col5 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col6 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col7 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col8 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col9 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col10 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col11 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col0 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col1 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col2 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col3 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col4 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col5 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col6 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col7 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col8 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col9 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col10 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col11 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col0 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col1 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col2 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col3 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col4 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col5 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col6 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col7 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col8 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col9 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col10 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col11 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col0 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col1 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col2 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col3 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col4 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col5 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col6 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col7 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col8 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col9 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col10 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col11 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col0 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col1 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col2 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col3 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col4 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col5 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col6 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col7 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col8 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col9 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col10 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col11 {\n",
       "            background-color:  white;\n",
       "            : ;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            : ;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col0 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col1 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col2 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col3 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col4 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col5 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col6 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col7 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col8 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col9 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col10 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col11 {\n",
       "            background-color:  sandybrown;\n",
       "            : ;\n",
       "            background:  #f7f7f9;\n",
       "        }    #T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col12 {\n",
       "            background-color:  sandybrown;\n",
       "            background:  #f7f7f9;\n",
       "            background:  #f7f7f9;\n",
       "        }</style>  \n",
       "<table id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >1</th> \n",
       "        <th class=\"col_heading level0 col1\" >2</th> \n",
       "        <th class=\"col_heading level0 col2\" >3</th> \n",
       "        <th class=\"col_heading level0 col3\" >4</th> \n",
       "        <th class=\"col_heading level0 col4\" >5</th> \n",
       "        <th class=\"col_heading level0 col5\" >6</th> \n",
       "        <th class=\"col_heading level0 col6\" >7</th> \n",
       "        <th class=\"col_heading level0 col7\" >8</th> \n",
       "        <th class=\"col_heading level0 col8\" >9</th> \n",
       "        <th class=\"col_heading level0 col9\" >10</th> \n",
       "        <th class=\"col_heading level0 col10\" >11</th> \n",
       "        <th class=\"col_heading level0 col11\" >12</th> \n",
       "        <th class=\"col_heading level0 col12\" >H_total</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row0\" class=\"row_heading level0 row0\" >A</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col0\" class=\"data row0 col0\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col1\" class=\"data row0 col1\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col2\" class=\"data row0 col2\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col3\" class=\"data row0 col3\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col4\" class=\"data row0 col4\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col5\" class=\"data row0 col5\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col6\" class=\"data row0 col6\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col7\" class=\"data row0 col7\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col8\" class=\"data row0 col8\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col9\" class=\"data row0 col9\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col10\" class=\"data row0 col10\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col11\" class=\"data row0 col11\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row0_col12\" class=\"data row0 col12\" >0</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row1\" class=\"row_heading level0 row1\" >B</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col0\" class=\"data row1 col0\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col1\" class=\"data row1 col1\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col2\" class=\"data row1 col2\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col3\" class=\"data row1 col3\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col4\" class=\"data row1 col4\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col5\" class=\"data row1 col5\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col6\" class=\"data row1 col6\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col7\" class=\"data row1 col7\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col8\" class=\"data row1 col8\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col9\" class=\"data row1 col9\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col10\" class=\"data row1 col10\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col11\" class=\"data row1 col11\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row1_col12\" class=\"data row1 col12\" >0</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row2\" class=\"row_heading level0 row2\" >C</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col0\" class=\"data row2 col0\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col1\" class=\"data row2 col1\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col2\" class=\"data row2 col2\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col3\" class=\"data row2 col3\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col4\" class=\"data row2 col4\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col5\" class=\"data row2 col5\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col6\" class=\"data row2 col6\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col7\" class=\"data row2 col7\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col8\" class=\"data row2 col8\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col9\" class=\"data row2 col9\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col10\" class=\"data row2 col10\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col11\" class=\"data row2 col11\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row2_col12\" class=\"data row2 col12\" >0</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row3\" class=\"row_heading level0 row3\" >D</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col0\" class=\"data row3 col0\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col1\" class=\"data row3 col1\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col2\" class=\"data row3 col2\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col3\" class=\"data row3 col3\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col4\" class=\"data row3 col4\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col5\" class=\"data row3 col5\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col6\" class=\"data row3 col6\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col7\" class=\"data row3 col7\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col8\" class=\"data row3 col8\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col9\" class=\"data row3 col9\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col10\" class=\"data row3 col10\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col11\" class=\"data row3 col11\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row3_col12\" class=\"data row3 col12\" >1</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row4\" class=\"row_heading level0 row4\" >E</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col0\" class=\"data row4 col0\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col1\" class=\"data row4 col1\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col2\" class=\"data row4 col2\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col3\" class=\"data row4 col3\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col4\" class=\"data row4 col4\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col5\" class=\"data row4 col5\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col6\" class=\"data row4 col6\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col7\" class=\"data row4 col7\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col8\" class=\"data row4 col8\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col9\" class=\"data row4 col9\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col10\" class=\"data row4 col10\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col11\" class=\"data row4 col11\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row4_col12\" class=\"data row4 col12\" >0</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row5\" class=\"row_heading level0 row5\" >F</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col0\" class=\"data row5 col0\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col1\" class=\"data row5 col1\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col2\" class=\"data row5 col2\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col3\" class=\"data row5 col3\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col4\" class=\"data row5 col4\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col5\" class=\"data row5 col5\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col6\" class=\"data row5 col6\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col7\" class=\"data row5 col7\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col8\" class=\"data row5 col8\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col9\" class=\"data row5 col9\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col10\" class=\"data row5 col10\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col11\" class=\"data row5 col11\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row5_col12\" class=\"data row5 col12\" >0</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row6\" class=\"row_heading level0 row6\" >G</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col0\" class=\"data row6 col0\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col1\" class=\"data row6 col1\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col2\" class=\"data row6 col2\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col3\" class=\"data row6 col3\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col4\" class=\"data row6 col4\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col5\" class=\"data row6 col5\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col6\" class=\"data row6 col6\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col7\" class=\"data row6 col7\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col8\" class=\"data row6 col8\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col9\" class=\"data row6 col9\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col10\" class=\"data row6 col10\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col11\" class=\"data row6 col11\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row6_col12\" class=\"data row6 col12\" >3</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row7\" class=\"row_heading level0 row7\" >H</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col0\" class=\"data row7 col0\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col1\" class=\"data row7 col1\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col2\" class=\"data row7 col2\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col3\" class=\"data row7 col3\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col4\" class=\"data row7 col4\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col5\" class=\"data row7 col5\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col6\" class=\"data row7 col6\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col7\" class=\"data row7 col7\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col8\" class=\"data row7 col8\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col9\" class=\"data row7 col9\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col10\" class=\"data row7 col10\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col11\" class=\"data row7 col11\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row7_col12\" class=\"data row7 col12\" >0</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row8\" class=\"row_heading level0 row8\" >I</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col0\" class=\"data row8 col0\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col1\" class=\"data row8 col1\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col2\" class=\"data row8 col2\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col3\" class=\"data row8 col3\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col4\" class=\"data row8 col4\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col5\" class=\"data row8 col5\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col6\" class=\"data row8 col6\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col7\" class=\"data row8 col7\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col8\" class=\"data row8 col8\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col9\" class=\"data row8 col9\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col10\" class=\"data row8 col10\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col11\" class=\"data row8 col11\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row8_col12\" class=\"data row8 col12\" >0</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row9\" class=\"row_heading level0 row9\" >J</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col0\" class=\"data row9 col0\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col1\" class=\"data row9 col1\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col2\" class=\"data row9 col2\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col3\" class=\"data row9 col3\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col4\" class=\"data row9 col4\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col5\" class=\"data row9 col5\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col6\" class=\"data row9 col6\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col7\" class=\"data row9 col7\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col8\" class=\"data row9 col8\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col9\" class=\"data row9 col9\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col10\" class=\"data row9 col10\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col11\" class=\"data row9 col11\" >1</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row9_col12\" class=\"data row9 col12\" >0</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row10\" class=\"row_heading level0 row10\" >K</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col0\" class=\"data row10 col0\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col1\" class=\"data row10 col1\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col2\" class=\"data row10 col2\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col3\" class=\"data row10 col3\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col4\" class=\"data row10 col4\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col5\" class=\"data row10 col5\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col6\" class=\"data row10 col6\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col7\" class=\"data row10 col7\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col8\" class=\"data row10 col8\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col9\" class=\"data row10 col9\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col10\" class=\"data row10 col10\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col11\" class=\"data row10 col11\" ></td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row10_col12\" class=\"data row10 col12\" >1</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771level0_row11\" class=\"row_heading level0 row11\" >Total</th> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col0\" class=\"data row11 col0\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col1\" class=\"data row11 col1\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col2\" class=\"data row11 col2\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col3\" class=\"data row11 col3\" >4</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col4\" class=\"data row11 col4\" >4</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col5\" class=\"data row11 col5\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col6\" class=\"data row11 col6\" >4</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col7\" class=\"data row11 col7\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col8\" class=\"data row11 col8\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col9\" class=\"data row11 col9\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col10\" class=\"data row11 col10\" >4</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col11\" class=\"data row11 col11\" >2</td> \n",
       "        <td id=\"T_89dc1fc0_4584_11e9_a868_3c0754343771row11_col12\" class=\"data row11 col12\" >nan</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0xa162a9eb8>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proyecto_asignacion = proyecto.copy()\n",
    "proyecto_asignacion.gantt(representar='recursos', total='fila', holguras = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Se concluye por tanto que la restricción de recursos impuesta no implica ningún problema."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
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