macroeconometrics/3 unit_root.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Series raiz unitarias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "import statsmodels.tsa.api as tsa\n",
    "from statsmodels.tsa.arima_process import arma_generate_sample\n",
    "from statsmodels.tsa.stattools import arma_order_select_ic\n",
    "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n",
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "\n",
    "from arch.unitroot import ADF, DFGLS, PhillipsPerron\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Primero vamos a generar una serie estacionaria que servira de ejemplo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(12345)\n",
    "ar_p = np.array([1])\n",
    "ma_p = np.array([0])\n",
    "\n",
    "# Incluyo una constante. Para el caso del AR debo colocarlo en negativo\n",
    "ar = np.r_[1, -ar_p]\n",
    "ma = np.r_[1, ma_p]\n",
    "\n",
    "serie = arma_generate_sample(ar, ma, nsample=2000)\n",
    "serie = pd.Series(serie)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "fig = plt.plot(serie)\n",
    "\n",
    "plt.savefig(\"./figures/ur_generated.pdf\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cuando una serie es raiz unitara, aun se puede estimar por un modelo ARMA, pero provocara lo siguiente:\n",
    "* La estimacion sera sesgada\n",
    "* Los residuos contaran con autocorrelacion serial\n",
    "\n",
    "Una de las maneras de saber si una serie tiene raiz unitaria es mediante la revision de la ACF. Las series con raiz unitaria cuentan con una funcion que decae muy suavemente y cuenta con niveles significativos por muchos periodos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(14,6))\n",
    "\n",
    "plot_acf(serie, ax=ax[0], lags=50, title=\"ACF\", alpha=0.05)\n",
    "plot_pacf(serie, ax=ax[1], lags=50, title=\"PACF\", alpha=0.05)\n",
    "\n",
    "plt.savefig(\"./figures/ur_acf_pacf.pdf\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "No obstante, la forma mas comun de saber si una serie cuenta tiene raiz unitaria es mediante tests:\n",
    "1. Dickey-Fuller ($DF$)\n",
    "2. Dickey-Fuller aumentado ($ADF$)\n",
    "3. Phillips-Perron ($PP$)\n",
    "4. Estadisticos M\n",
    "5. Elliot-Rotenberg-Stock ($DF_{GLS}$)\n",
    "\n",
    "Con la libreria `arch` se puede estimar el $ADF$, $DF_{GLS}$, $PP$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "adf = ADF(serie)\n",
    "df_gls = DFGLS(serie)\n",
    "pp = PhillipsPerron(serie)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El resultado de los test es el siguiente"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Augmented Dickey-Fuller Results   \n",
      "=====================================\n",
      "Test Statistic                 -1.962\n",
      "P-value                         0.303\n",
      "Lags                                0\n",
      "-------------------------------------\n",
      "\n",
      "Trend: Constant\n",
      "Critical Values: -3.43 (1%), -2.86 (5%), -2.57 (10%)\n",
      "Null Hypothesis: The process contains a unit root.\n",
      "Alternative Hypothesis: The process is weakly stationary.\n"
     ]
    }
   ],
   "source": [
    "print(adf.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      Dickey-Fuller GLS Results      \n",
      "=====================================\n",
      "Test Statistic                 -1.812\n",
      "P-value                         0.069\n",
      "Lags                                0\n",
      "-------------------------------------\n",
      "\n",
      "Trend: Constant\n",
      "Critical Values: -2.58 (1%), -1.95 (5%), -1.63 (10%)\n",
      "Null Hypothesis: The process contains a unit root.\n",
      "Alternative Hypothesis: The process is weakly stationary.\n"
     ]
    }
   ],
   "source": [
    "print(df_gls.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Phillips-Perron Test (Z-tau)    \n",
      "=====================================\n",
      "Test Statistic                 -1.771\n",
      "P-value                         0.395\n",
      "Lags                               26\n",
      "-------------------------------------\n",
      "\n",
      "Trend: Constant\n",
      "Critical Values: -3.43 (1%), -2.86 (5%), -2.57 (10%)\n",
      "Null Hypothesis: The process contains a unit root.\n",
      "Alternative Hypothesis: The process is weakly stationary.\n"
     ]
    }
   ],
   "source": [
    "print(pp.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En dos de los tres test se encuentra la presencia de raiz unitaria. Por lo general, esta se puede solucionar con primeras diferencias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "fd = serie - serie.shift(1)\n",
    "fd = fd[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(14,6))\n",
    "\n",
    "plot_acf(fd, ax=ax[0], lags=50, title=\"ACF\", alpha=0.05)\n",
    "plot_pacf(fd, ax=ax[1], lags=50, title=\"PACF\", alpha=0.05)\n",
    "\n",
    "plt.savefig(\"./figures/ur_fd_acf_pacf.pdf\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "adf = ADF(fd)\n",
    "df_gls = DFGLS(fd)\n",
    "pp = PhillipsPerron(fd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Augmented Dickey-Fuller Results   \n",
      "=====================================\n",
      "Test Statistic                -45.953\n",
      "P-value                         0.000\n",
      "Lags                                0\n",
      "-------------------------------------\n",
      "\n",
      "Trend: Constant\n",
      "Critical Values: -3.43 (1%), -2.86 (5%), -2.57 (10%)\n",
      "Null Hypothesis: The process contains a unit root.\n",
      "Alternative Hypothesis: The process is weakly stationary.\n"
     ]
    }
   ],
   "source": [
    "print(adf.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      Dickey-Fuller GLS Results      \n",
      "=====================================\n",
      "Test Statistic                -38.221\n",
      "P-value                         0.000\n",
      "Lags                                0\n",
      "-------------------------------------\n",
      "\n",
      "Trend: Constant\n",
      "Critical Values: -2.58 (1%), -1.95 (5%), -1.63 (10%)\n",
      "Null Hypothesis: The process contains a unit root.\n",
      "Alternative Hypothesis: The process is weakly stationary.\n"
     ]
    }
   ],
   "source": [
    "print(df_gls.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Phillips-Perron Test (Z-tau)    \n",
      "=====================================\n",
      "Test Statistic                -46.224\n",
      "P-value                         0.000\n",
      "Lags                               26\n",
      "-------------------------------------\n",
      "\n",
      "Trend: Constant\n",
      "Critical Values: -3.43 (1%), -2.86 (5%), -2.57 (10%)\n",
      "Null Hypothesis: The process contains a unit root.\n",
      "Alternative Hypothesis: The process is weakly stationary.\n"
     ]
    }
   ],
   "source": [
    "print(pp.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tanto de manera grafica como con los test, ya no existe el problema de raiz unitaria"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Aplicado con data peruana\n",
    "Realizaré el análisis con la serie del consumo privado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>Consumo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980Q3</th>\n",
       "      <td>10.221229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980Q4</th>\n",
       "      <td>10.260693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981Q1</th>\n",
       "      <td>10.248834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981Q2</th>\n",
       "      <td>10.175354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981Q3</th>\n",
       "      <td>10.286910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019Q2</th>\n",
       "      <td>11.419034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019Q3</th>\n",
       "      <td>11.400895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019Q4</th>\n",
       "      <td>11.384192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020Q1</th>\n",
       "      <td>11.324953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020Q2</th>\n",
       "      <td>11.157640</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>160 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Consumo\n",
       "1980Q3  10.221229\n",
       "1980Q4  10.260693\n",
       "1981Q1  10.248834\n",
       "1981Q2  10.175354\n",
       "1981Q3  10.286910\n",
       "...           ...\n",
       "2019Q2  11.419034\n",
       "2019Q3  11.400895\n",
       "2019Q4  11.384192\n",
       "2020Q1  11.324953\n",
       "2020Q2  11.157640\n",
       "\n",
       "[160 rows x 1 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dta = pd.read_excel(\"./data/PeruData.xlsx\", sheet_name=\"Trimestral\", skiprows=1)\n",
    "dta = dta[['Trimestres', 'Producto bruto interno por tipo de gasto (millones S/ 2007) - Demanda Interna - Consumo Privado']]\n",
    "dta.rename({'Producto bruto interno por tipo de gasto (millones S/ 2007) - Demanda Interna - Consumo Privado': 'Consumo'}, axis=1, inplace=True)\n",
    "dta = dta.loc[2:161, :]\n",
    "\n",
    "# Seting index\n",
    "dta.index = pd.period_range(\"1980Q3\", \"2020Q2\", freq=\"Q\")\n",
    "\n",
    "dta = np.log(dta[[\"Consumo\"]])\n",
    "dta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "dta.index=dta.index.to_timestamp()\n",
    "\n",
    "# Suavizamiento\n",
    "dta_sa = seasonal_decompose(dta, model=\"aditive\").trend\n",
    "\n",
    "dta_sa = dta_sa.dropna()\n",
    "dta = dta[(dta.index >= \"1981-01-01\") & (dta.index <= \"2019-10-01\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "dta_sa.plot()\n",
    "\n",
    "plt.title(\"Logaritmo del consumo privado\", fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Se puede realizar una revision de si existe raiz unitaria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(14,6))\n",
    "\n",
    "plot_acf(dta_sa, ax=ax[0], lags=20, title=\"ACF\", alpha=0.05)\n",
    "plot_pacf(dta_sa, ax=ax[1], lags=20, title=\"PACF\", alpha=0.05)\n",
    "\n",
    "plt.savefig(\"./figures/ur_consumo_acf_pacf.pdf\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Augmented Dickey-Fuller Results   \n",
      "=====================================\n",
      "Test Statistic                 -0.315\n",
      "P-value                         0.923\n",
      "Lags                                6\n",
      "-------------------------------------\n",
      "\n",
      "Trend: Constant\n",
      "Critical Values: -3.48 (1%), -2.88 (5%), -2.58 (10%)\n",
      "Null Hypothesis: The process contains a unit root.\n",
      "Alternative Hypothesis: The process is weakly stationary.\n"
     ]
    }
   ],
   "source": [
    "adf = ADF(dta_sa)\n",
    "print(adf.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`No se puede` rechazar la raiz unitaria en la serie del consumo privado. Se podria solucionar con primeras diferencias o con variaciones anuales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1981-04-01    0.825228\n",
       "1981-07-01   -0.370167\n",
       "1981-10-01   -0.870944\n",
       "1982-01-01   -0.449250\n",
       "1982-04-01   -0.383813\n",
       "                ...   \n",
       "2018-10-01    0.798274\n",
       "2019-01-01    0.780265\n",
       "2019-04-01    0.800857\n",
       "2019-07-01    0.023703\n",
       "2019-10-01   -3.622914\n",
       "Freq: QS-OCT, Name: trend, Length: 155, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "consumo = (dta_sa - dta_sa.shift(1))*100\n",
    "consumo = consumo[1:]\n",
    "consumo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(14,6))\n",
    "\n",
    "plot_acf(consumo, ax=ax[0], lags=10, title=\"ACF\", alpha=0.05)\n",
    "plot_pacf(consumo, ax=ax[1], lags=10, title=\"PACF\", alpha=0.05)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Augmented Dickey-Fuller Results   \n",
      "=====================================\n",
      "Test Statistic                 -4.242\n",
      "P-value                         0.001\n",
      "Lags                                5\n",
      "-------------------------------------\n",
      "\n",
      "Trend: Constant\n",
      "Critical Values: -3.48 (1%), -2.88 (5%), -2.58 (10%)\n",
      "Null Hypothesis: The process contains a unit root.\n",
      "Alternative Hypothesis: The process is weakly stationary.\n"
     ]
    }
   ],
   "source": [
    "adf = ADF(consumo)\n",
    "print(adf.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Luego, ya se soluciono el problema de raiz unitaria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "El mejor modelo seleccionado por AIC es (2, 1) y por BIC es (2, 1)\n"
     ]
    }
   ],
   "source": [
    "criterias = arma_order_select_ic(consumo, max_ar=4, max_ma=2, ic=[\"aic\", \"bic\"])\n",
    "\n",
    "print(f\"El mejor modelo seleccionado por AIC es {criterias.aic_min_order} y por BIC es {criterias.bic_min_order}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Siguiendo el criterio del BIC, el modelo seleccionado deberia ser un ARMA(2,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                               SARIMAX Results                                \n",
      "==============================================================================\n",
      "Dep. Variable:                  trend   No. Observations:                  155\n",
      "Model:                 ARIMA(2, 0, 1)   Log Likelihood                -153.562\n",
      "Date:                Sun, 25 Dec 2022   AIC                            317.124\n",
      "Time:                        17:44:55   BIC                            332.341\n",
      "Sample:                    04-01-1981   HQIC                           323.305\n",
      "                         - 10-01-2019                                         \n",
      "Covariance Type:                  opg                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const          0.6349      0.348      1.825      0.068      -0.047       1.317\n",
      "ar.L1          0.9971      0.068     14.722      0.000       0.864       1.130\n",
      "ar.L2         -0.3374      0.069     -4.921      0.000      -0.472      -0.203\n",
      "ma.L1          1.0000     55.620      0.018      0.986    -108.013     110.013\n",
      "sigma2         0.4039     22.444      0.018      0.986     -43.585      44.393\n",
      "===================================================================================\n",
      "Ljung-Box (L1) (Q):                   0.13   Jarque-Bera (JB):               149.15\n",
      "Prob(Q):                              0.72   Prob(JB):                         0.00\n",
      "Heteroskedasticity (H):               0.26   Skew:                            -1.02\n",
      "Prob(H) (two-sided):                  0.00   Kurtosis:                         7.35\n",
      "===================================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n"
     ]
    }
   ],
   "source": [
    "model = tsa.arima.ARIMA(consumo, order=(2,0,1))\n",
    "model = model.fit()\n",
    "\n",
    "print(model.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_f = model.get_forecast(steps=10)\n",
    "\n",
    "# Proyeciones\n",
    "model_mean = model_f.predicted_mean\n",
    "model_ci = model_f.conf_int()\n",
    "\n",
    "# Generando los DataFrames\n",
    "fc_series = pd.Series(model_mean)\n",
    "lower_series = pd.Series(model_ci[\"lower trend\"])\n",
    "upper_series = pd.Series(model_ci[\"upper trend\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAzkAAAIOCAYAAACbGsO4AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAA9hAAAPYQGoP6dpAACBxElEQVR4nO3dd3xUVfoG8OdOT530BEgh9N6R3hFpir3gshYsrGDftaz+FF13sWDvriuWXRV7FwHp0nvvCZAE0pNJmXrv+f0RZiSSNsn0PN/P5qNM7tx7Zq5L5sl7znskIYQAERERERFRiFD5ewBERERERESexJBDREREREQhhSGHiIiIiIhCCkMOERERERGFFIYcIiIiIiIKKQw5REREREQUUhhyiIiIiIgopDDkEBERERFRSGHIISIiIiKikMKQQ0TkIxs3bsRVV12FNm3aQKfTISUlBVdeeSU2bNjg1nnmz58PSZKaNYZVq1ZBkiSsWrWqWc9vqrFjx2Ls2LFevUZTtG/fHpIk1flVWVnp7+F5VXV1NebPn+/1e01EFIg0/h4AEVFr8Oqrr+Kee+7BBRdcgGeffRYZGRk4efIkXn/9dYwcORIvv/wy5s2b16Rz3XLLLZg8eXKzxjFgwABs2LABPXr0aNbzg9GIESOwcOHC8x4PDw/3w2h8p7q6Gk888QQABETgJCLyJYYcIiIv++2333DPPfdg6tSp+Prrr6HR/P5X77XXXovLLrsMd999N/r3748RI0bUe57q6mqEh4cjNTUVqampzRpLdHQ0hg4d2qznBquYmBivvGYhBCwWC8LCwjx+biIiahlOVyMi8rIFCxZAkiS8+eabtQIOAGg0GrzxxhuQJAlPP/2063HnlLTt27fjyiuvRGxsLDp27Fjre+eyWq24//77kZKSgvDwcIwePRrbtm1D+/btceONN7qOq2u62o033ojIyEgcPXoUU6dORWRkJNLS0nD//ffDarXWus4TTzyBIUOGIC4uDtHR0RgwYAD+85//QAjh9vty6aWXIiMjA4qinPe9IUOGYMCAAa4/f/755xgyZAiMRiPCw8PRoUMH3HzzzW5fsy4lJSW444470K5dO+h0OnTo0AGPPPLIea9dkiTMmzcPb731Frp37w69Xo8PPvgAAHDkyBHMnDkTSUlJ0Ov16N69O15//fXzrlVWVob7778fHTp0gF6vR1JSEqZOnYqDBw+6jmnqe7xixQqMHTsW8fHxCAsLQ3p6Oq644gpUV1cjOzsbiYmJrvM5p+id+98CEVEoYyWHiMiLZFnGypUrMWjQoHqrL2lpaRg4cCBWrFgBWZahVqtd37v88stx7bXXYs6cOaiqqqr3OjfddBMWL16MBx54AOPHj8f+/ftx2WWXwWQyNWmcdrsdl1xyCWbPno37778fa9aswT/+8Q8YjUY89thjruOys7Nx++23Iz09HUDNOqM777wTubm5tY5riptvvhkzZszAihUrMHHiRNfjBw8exObNm/HKK68AADZs2IBrrrkG11xzDebPnw+DwYATJ05gxYoVTbqOEAIOh6PWYyqVCiqVChaLBePGjcOxY8fwxBNPoE+fPli7di0WLFiAnTt34scff6z1vG+++QZr167FY489hpSUFCQlJWH//v0YPnw40tPT8fzzzyMlJQW//PIL7rrrLhQVFeHxxx8HAFRUVGDkyJHIzs7Ggw8+iCFDhqCyshJr1qzB6dOn0a1btya/x9nZ2Zg2bRpGjRqF9957DzExMcjNzcWSJUtgs9nQpk0bLFmyBJMnT8bs2bNxyy23AIAr+BARhTxBRERec+bMGQFAXHvttQ0ed8011wgAIj8/XwghxOOPPy4AiMcee+y8Y53fc9q3b58AIB588MFax33yyScCgLjhhhtcj61cuVIAECtXrnQ9dsMNNwgA4rPPPqv1/KlTp4quXbvWO2ZZloXdbhdPPvmkiI+PF4qiuL43ZswYMWbMmAZfs91uF8nJyWLmzJm1Hn/ggQeETqcTRUVFQgghFi5cKACIsrKyBs9Xl4yMDAHgvK9HHnlECCHEW2+9Vedrf+aZZwQAsXTpUtdjAITRaBQlJSW1jr3oootEamqqKC8vr/X4vHnzhMFgcB3/5JNPCgBi2bJlTR5/fe/xF198IQCInTt31vvcwsJCAUA8/vjjTb4eEVGo4HQ1IqIAIM5ORfrjNLQrrrii0eeuXr0aAHD11VfXevzKK688b3pcfSRJwsUXX1zrsT59+uDEiRO1HnNWXYxGI9RqNbRaLR577DEUFxejoKCgSddy0mg0+NOf/oSvvvoK5eXlAGoqXx999BFmzJiB+Ph4AMDgwYNdr++zzz5Dbm6uW9cZOXIktmzZUuvrjjvucL2eiIgIXHnllbWe45zW9euvv9Z6fPz48YiNjXX92WKx4Ndff8Vll12G8PBwOBwO19fUqVNhsViwceNGAMDPP/+MLl261Kpa1aUp73G/fv2g0+lw22234YMPPsDx48fdek+IiEIdQw4RkRclJCQgPDwcWVlZDR6XnZ2NiIgIxMXF1Xq8TZs2jV6juLgYAJCcnFzrcY1G4woKjQkPD4fBYKj1mF6vh8Vicf158+bNmDRpEgDg3//+N3777Tds2bIFjzzyCADAbDY36Vrnuvnmm2GxWPDpp58CAH755RecPn0aN910k+uY0aNH45tvvoHD4cCf//xnpKamolevXvjkk0+adA2j0YhBgwbV+mrbti2AmvcuJSXlvHCZlJQEjUbjem+d/ng/iouL4XA48Oqrr0Kr1db6mjp1KgCgqKgIAFBYWNhow4imvscdO3bE8uXLkZSUhLlz56Jjx47o2LEjXn755Sa9J0REoY5rcoiIvEitVmPcuHFYsmQJcnJy6vyQm5OTg23btmHq1Km11uMA51d26uIMMvn5+WjXrp3rcYfDcd6H9Jb49NNPodVq8cMPP9QKRN98802zz9mjRw9ccMEFWLRoEW6//XYsWrQIbdu2dX3Qd5oxYwZmzJgBq9WKjRs3YsGCBZg5cybat2+PYcOGNfv68fHx2LRpE4QQtd7rgoICOBwOJCQk1Dr+j/cjNjYWarUas2bNwty5c+u8RmZmJoCa9TA5OTkNjsed93jUqFEYNWoUZFnG1q1bXW3Kk5OTce211zZ4HSKiUMdKDhGRlz388MMQQuCOO+6ALMu1vifLMv7yl79ACIGHHnqoWecfPXo0AGDx4sW1Hv/iiy/OW3DfEpIkQaPR1ApiZrMZH330UYvOe9NNN2HTpk1Yt24dvv/+e9xwww3nhT0nvV6PMWPG4JlnngEA7Nixo0XXnjBhAiorK88LER9++KHr+w0JDw/HuHHjsGPHDvTp0+e8itGgQYNcIXTKlCk4fPhwgw0TmvMeq9VqDBkyxNXNbfv27QBq3ivn84mIWhtWcoiIvGzEiBF46aWXcM8992DkyJGYN28e0tPTXZuBbtq0CS+99BKGDx/erPP37NkT1113HZ5//nmo1WqMHz8e+/btw/PPPw+j0QiVyjO/z5o2bRpeeOEFzJw5E7fddhuKi4uxcOFC14fp5rruuutw33334brrroPVaj2vzfFjjz2GnJwcTJgwAampqSgrK8PLL78MrVaLMWPGtOjaf/7zn/H666/jhhtuQHZ2Nnr37o1169bhX//6F6ZOndro+hkAePnllzFy5EiMGjUKf/nLX9C+fXtUVFTg6NGj+P77712h5p577sHixYsxY8YMPPTQQ7jgggtgNpuxevVqTJ8+HePGjWvye/zWW29hxYoVmDZtGtLT02GxWPDee+8BgGvMUVFRyMjIwLfffosJEyYgLi4OCQkJaN++fYveMyKioODfvgdERK3Hhg0bxJVXXimSk5OFRqMRSUlJ4vLLLxfr168/71hnB7XCwsJ6v3cui8Ui7rvvPpGUlCQMBoMYOnSo2LBhgzAajeLee+91HVdfd7WIiIgmXee9994TXbt2FXq9XnTo0EEsWLBA/Oc//xEARFZWluu4pnRXO9fMmTMFADFixIjzvvfDDz+IKVOmiHbt2gmdTieSkpLE1KlTxdq1axs9b0ZGhpg2bVqDxxQXF4s5c+aINm3aCI1GIzIyMsTDDz8sLBZLreMAiLlz59Z5jqysLHHzzTeLdu3aCa1WKxITE8Xw4cPFU089Veu40tJScffdd4v09HSh1WpFUlKSmDZtmjh48KDrmKa8xxs2bBCXXXaZyMjIEHq9XsTHx4sxY8aI7777rtb1li9fLvr37y/0ev15nfaIiEKZJEQzdnAjIqKAt379eowYMQL/+9//MHPmTH8Ph4iIyGcYcoiIQsCyZcuwYcMGDBw4EGFhYdi1axeefvppGI1G7N69+7zOaURERKGMa3KIiEJAdHQ0li5dipdeegkVFRVISEjAlClTsGDBAgYcIiJqdVjJISIiIiKikMIW0kREREREFFIYcoiIiIiIKKQw5BARERERUUgJ6MYDiqIgLy8PUVFRkCTJ38MhIiIiIiI/EUKgoqICbdu2bXSj64AOOXl5eUhLS/P3MIiIiIiIKECcOnUKqampDR4T0CEnKioKQM0LiY6O9vNoiIiIiIjIX0wmE9LS0lwZoSEBHXKcU9Sio6MZcoiIiIiIqEnLWNh4gIiIiIiIQgpDDhERERERhZSAnq7WGFmWYbfb/T2MkKLVaqFWq/09DCIiIiKiZgvakFNZWYmcnBwIIfw9lJAiSRJSU1MRGRnp76EQERERETVLUIYcWZaRk5OD8PBwJCYmcg8dDxFCoLCwEDk5OejcuTMrOkREREQUlIIy5NjtdgghkJiYiLCwMH8PJ6QkJiYiOzsbdrudIYeIiIiIglJQNx5gBcfz+J4SERERUbAL6pATaGw2Gx588EF06tQJ3bt3R69evbBo0aJ6j3/sscewePHiRs/71ltv4cUXX2zR2ObPn4+//vWvLToHEREREVEwCMrpaoHqxhtvhNVqxa5duxAREYHs7GxMmTIFdrsdt912W61jHQ4HnnzyySadd86cOd4YLhERERFRSAr6kCOEgNkue/UaYVp1o9O4jh49im+++QanTp1CREQEAKB9+/Z4/vnncfvtt6NLly645557MHr0aGzZsgX33XcffvzxRwwaNAjz5s1DeXk5br75Zuzbtw9t27ZFu3btkJycjIULF2L+/PmorKzEwoUL8f777+OTTz5BXFwc9u7dC71ej88++wwdOnTAmTNncN1118FkMsFisWDChAl4+eWXOQWNiIiIiFqVoA85ZruMHo/94tVr7H/yIoTrGn6rtm/fjs6dOyM+Pr7W48OGDUNOTg4KCwuxe/duvPbaa3jllVcAAD/++KPruCeffBKxsbE4ePAgSktLMWDAAFxxxRV1XmvTpk3YtWsXMjIy8NBDD+GZZ57B22+/jZiYGHz//feIjIyELMuYMWMGvvzyS1x55ZUtfAeIiIiIiIIH1+R4UGMVky5dumDkyJF1fm/lypW46aabAACxsbG49NJL6z3PyJEjkZGRAaAmRB07dgwAoCgKHnzwQfTt2xf9+/fH1q1bsXPnTvdfCBERERFREAv6Sk6YVo39T17k9Ws0pn///jh8+DCKi4trVXM2bNiA1NRUJCYmNrjBphCiydPKDAaD69/VajUcDgcA4IUXXkBxcTE2bdoEg8GA++67DxaLpUnnJCIiIiIKFUFfyZEkCeE6jVe/mhI+OnfujIsvvhi33XYbqqurAQDZ2dm4//778cgjjzT6/HHjxuGDDz4AAJSVleHbb791+70oLS1FSkoKDAYD8vPz8fnnn7t9DiIiIiKiYBf0ISeQfPjhh+jQoQN69+6N7t27Y/r06bj//vub1B3tscceQ0FBAXr06IGZM2dixIgRMBqNbl3/rrvuwvr169GvXz/cfPPNmDhxYnNfChERERFR0JKEEMLfg6iPyWSC0WhEeXk5oqOjXY9bLBZkZWUhMzOz1tStYGa32yHLMgwGA0wmE0aOHIkXXnjB50ElFN9bIiIiIgp+9WWDugT9mpxQUVpaiilTpkCWZZjNZlx//fWsxBARERERNQNDToBISkrCtm3b/D0MIiIiIqKgx5BDRERERBRkhBCw2WywWCwwm83QarUICwuDXq+HWt14Z+BQx5BDRERERBQEFEWB1WqF2WxGVVUVLBYLHA4HVCoVFEWBSqWCTqdDREQEwsPDYTAYoNG0zo/7rfNVExEREREFCWeoqaiogM1mg6Io0Gq10Ov1iIiIcB2nKApsNhtKSkpQXFzsCjwREREICwtrVYGn9bxSIiIiIqIg43A4kJ+fD7PZ7AotKlXdu8CoVCoYDAYYDAbXdLaysjKUlpZCr9cjOjoakZGR0Ov1Td6EPlgx5BARERERBSiTyQSz2Yzo6Gi3gokkSdDr9dDr9RBCwGq1orCwEKWlpYiIiEB0dDTCw8PrDUzBjiHHQ9q3b+9KzgAwdOhQvPXWW34eVW07d+7E4cOHcfXVV/t7KERERETUCLvdjrKyMuh0uhZVXiRJcn1OtdvtqKiogMlkgsFgQExMDMLDw6HT6Tw4cv9jyPGgL774Ar169XL7eQ6HwydzJHfu3IkffviBIYeIiIgoCJhMJlit1kY3vnSHVquFVquFoiiwWCw4ffr0ec0KQiHwBH99SgjAVuXdLyGaNbQlS5ZgwIAB6NOnD8aMGYP9+/cDAFatWoV+/frhrrvuwrBhw/D111/jyJEjmDZtGgYPHoy+ffvijTfecJ1nw4YNGDVqFPr27Ys+ffrg22+/BQD87W9/w+DBg9GvXz+MGTMGR44cAQAUFhZi0qRJ6N27N/r06YObbroJBQUFeOyxx7B8+XL069cPc+bMaeEbT0RERETe4lxPYzAYvLJ+RqVSITw8HNHR0VCr1SgvL0dubi5OnTqF3NxclJeXw2q1QjTzc7C/BX8lx14N/Kutd6/x9zxAF9HoYVdeeaVrutrDDz+MuXPnYuXKlejduzf+97//4eqrr8bevXsBALt378Zrr72GV155BbIsY+jQofjoo4/QrVs3VFdXY+jQoRg6dCjat2+Pyy67DF999RWGDx8ORVFQVlYGAHjwwQfx3HPPAQA+/fRT3Hvvvfjhhx/w3//+F+3bt8fSpUsBACUlJYiLi8OTTz6JH374AV988YUX3iQiIiIi8pSysjLYbDYYjUavXkeSJOh0Ouh0OgghYLfbUVVVBZPJBI1GA4PBgKioKBiNxqBqVhD8ISeAnDtd7fvvv0e/fv3Qu3dvAMD111+PuXPn4vTp0wCALl26YOTIkQCAQ4cOYd++fbj22mtd56qoqMD+/ftx+vRp9OjRA8OHDwdQk7rj4uIAAEuXLsWrr76KiooKKIoCk8kEoGY90Isvvoj7778fY8aMwUUXXeSbN4CIiIiIWsxiscBkMiEsLMyn1z038AA1SyrMZjNsNhsiIiKg1Wp9Op6WCP6Qow2vqbR4+xpuEkLUmXadj0VGRtY6NiEhATt37jzv+B9//LHO8588eRJ33XUXNm/ejA4dOmD37t0YP348AGDYsGHYuXMnli9fji+//BKPPvooduzY4fZrICIiIiLfKy8vh91uR3i4+59BPclZybHZbH4dR3ME/5ocSaqZSubNr2aU5pxB48CBAwBqppOlpqYiJSXlvGO7du2K8PBwfPjhh67Hjh49ipKSEgwfPhwHDhzA+vXrAdRs8lRSUoLy8nLodDqkpKRACIHXXnvN9dysrCxERkbi6quvxquvvorDhw+jsrIS0dHRKC8vd/u1EBEREZFvmM1mlJeX+z3gBLvgDzkBKjExER999BGuv/569O3bF2+++SY+++yzOo/VaDT4/vvv8dlnn6FPnz7o2bMnbrnlFpjNZsTGxuLrr7/G3/72N/Tp0wf9+/fHunXr0Lt3b1x11VXo2bMnxo4di/T0dNf5Vq1ahYEDB6Jfv34YMWIEnnvuORiNRkyYMAFVVVXo27cvGw8QERERBRghBMrKyiCECKqpYYFIEgHcMsFkMsFoNKK8vLxW6zyLxYKsrCxkZma6FvqTZ/C9JSIiIvKPqqoq5OTkICwszCfbizSFw+GAzWZDRkaG34NXfdmgLqzkEBERERH5mbOKAyBgAk4wY8ghIiIiIvKzqqoqVFRUcC2OhzDkEBERERH5kaIoKC0thUqlglqt9vdwQoLPQs6CBQsgSRLuuecej50zgJcTBS2+p0RERES+VVVVhaqqKlZxPMgnE/62bNmCd955B3369PHI+bRaLSRJQmFhIRITE4Nq99VAJoRAYWEhJEny+8IyIiIiotaiuroakiRBpeIkK0/xesiprKzE9ddfj3//+9946qmnPHJOtVqN1NRU5OTkIDs72yPnpBqSJCE1NZWlUiIiIiIfEELAbDaz2YCHef3dnDt3LqZNm4aJEyd6LOQAQGRkJDp37gy73e6xc1JNlYwBh4iIiMg37HY7HA4HdDqdv4cSUrwacj799FNs27YNW7dubdLxVqsVVqvV9WeTydTg8Wq1mh/IiYiIiChoOUNOWFiYv4cSUrw28e/UqVO4++678b///a/Jm0ouWLAARqPR9ZWWluat4RERERER+Z3NZgMArjH3MEl4qZ3WN998g8suu6xWpUWWZdeiKqvVel4Vpq5KTlpaWpN2NSUiIiIiCjZ5eXmorKxEZGSkv4dSJ4fDAZvNhoyMDL83pjKZTDAajU3KBl6brjZhwgTs2bOn1mM33XQTunXrhgcffLDOaWZ6vR56vd5bQyIiIiIiChiKosBisbDpgBd47R2NiopCr169aj0WERGB+Pj48x4nIiIiImptbDYb1+N4CZtxExERERH5gd1uh6IobKTlBT6tja1atcqXlyMiIiIiCljnrkUnz2Ilh4iIiIjID7gJqPcw5BARERER+ZizaxlDjncw5BARERER+ZhzE1CGHO9gyCEiIiIi8jGbzQZFUaBS8eO4N/BdJSIiIiLyMavVCkmS/D2MkMWQQ0RERETkQ0IImM1maLVafw8lZDHkEBERERH5kMPhgN1u53ocL2LIISIiIiLyIZvNxqYDXsaQQ0RERETkQ3a7HUIIrsnxIoYcIiIiIiIfMpvNUKvV/h5GSGPIISIiIiLyEUVRYLFYOFXNyxhyiIiIiIh8hJuA+gZDDhERERGRj7DpgG8w5BARERER+YjNZmPDAR9gyCEiIiIi8hGLxcKmAz7AkENERERE5AOyLMNisUCr1fp7KCGPIYeIiIiIyAe4Hsd3GHKIiIiIiHzAbrdDURSoVPwI7m18h4mIiIiIfMBisbDpgI8w5BAREREReZkQAmazmVPVfIQhh4iIiIjIyxwOBxwOB5sO+AhDDhERERGRl9ntdtjtdlZyfIQhh4iIiIjIy2w2GwBwTY6PMOQQEREREXkZmw74FkMOEREREZEXKYoCs9nM9Tg+xJBDRERERORFdrudm4D6GEMOEREREZEX2e12yLIMtVrt76G0Ggw5REREREReZLfbAbDpgC8x5BAREREReZEz5JDvMOQQEREREXmR3W7nVDUfY8ghIiIiIvISIQTsdjtUKn7s9iW+20REREREXqIoChRFYSXHxxhyiIiIiIi8RJZlKIrCSo6P8d0mIiIiIvISWZYhyzJDjo/x3SYiIiIi8hJZliGEYMjxMb7bREREREReoiiKv4fQKjHkEBERERF5ibOSQ77FkENERERE5CVsH+0ffMeJiIiIiLyEIcc/+I4TEREREXmBcyNQ7pHjeww5RER1sDpkLNl7GieKq/w9FCIiClKKorB9tJ9o/D0AIqJAs/JQAZ78fj+yiqrQJTkSS+8d4+8hERFREHJuBKrVav09lFaHIYeI6KwTxVX4xw/7sfxAgeuxw/mVOFFchYz4CD+OjIiIgpEz5LCS43t8x4mo1au2ObDwl0O48MU1WH6gABqVhFtHZaJ/egwAYM3hQv8OkIiIghI3AvUfVnKIqNUSQuDHPafxrx8PIK/cAgAY1TkBj1/cA52SovDmqmPYcbIMqw8XYtaw9v4dLBERBR1Zlv09hFaLIYeIWiWTxY47/rsd644WAQBSY8Pw6LQeuKhnMiRJAgCM6ZKIZ5YcxPpjxbA6ZOg17I5DRERNx5DjPww5RNTqyIrAXZ/swLqjRdBrVLhjbCfcPqYDDNraIaZ7mygkRulRWGHF1uxSjOiU4KcRExFRMLLb7a5fnJFvcYIgEbU6zyw5iFWHCmHQqvD5nGG4e2Ln8wIOAEiShDFdEgEAq7kuh4iI3ORwOLhHjp+wkkNErcrnW0/hnTXHAQALr+qLPqkxDR4/pksivtiWg9WHCvH3qd19MMLA8Mnmk/h+Vx6EqP+Ybm2iMG9cJ8RH6n03MCKiIOHcCJRNB/yDIYeIWo1tJ0rwyNd7AQB3TeiM6X3aNvqckZ0SoJKAQ/kVOF1uRhtjmLeH6XfZRVX4v2/2wqE0kHAAbDhejC+35eCvF3XFzAvSoVHzBzkRkZMsy5BlmZUcP2HIIaJWIbfMjNs/2gabrGBKrxTcM6Fzk54XG6FD37QY7DhZhjWHC3HN4HQvj9T/Xlh2GA5F4ILMOMwamlHnMVaHgvfWZWH/aRMe+3YfPt50Ek/O6IULMuN8PFoiosCkKAo3AvUjhhwiCnlVVgdu+WAriipt6N4mGs9f3RcqVdMXgo7pkuhqJR3qIWdvbjm+25UHAHj84h7o2dZY77GX9W+HjzefxMJfDuHgmQpc/fYGzOjXFn+f2h3J0QZfDZmIKCA5NwJlJcc/OLeAiEKaogjc/9kuHDhtQkKkDu/eMAjhOvd+vzO2axIAYO2RIjhkxRvDDBjP/XIIAHBJ37YNBhwAUKskzBqagZV/HYvrLkiHJAHf7szD+IWr8PbqY7A5Qvu9IiJqiDPksLuafzDkEFFIe+nXI1iy7wx0ahXenjUQ7WLcX1PTu50RseFaVFgc2HmqzPODDBAbjhVj9eFCaFQS7ruwS5OfFxehw4LLe+O7uSPRPz0GVTYZC34+iCH/Wo57F+/E97vyUG62e3HkRESBh3vk+BenqxFRyPp+Vx5e+fUIAOCfl/XCwIzmrRdRqySM6pyI73blYfXhQgxqH3rrToQQeGbJQQDAdReko31ChNvn6J1qxJdzhuOrHbl4ZslBFFZY8fWOXHy9IxdqlYRBGbEY3y0JE7onoWNiJH+7SUQhTZZl/j3nRww5RBTUhBA4Y7LgaEEljhZU4sjZfx4rqERxlQ0AcOuoTFw1KK1F1xnTpSbkrDpUiPsndfXE0APK0v352HmqDGFaNe6c0KnZ51GpJFw5MBWX9muLbSdKseJQAVYcKMCRgkpsyirBpqwSLPj5INLiwnDvxC64fECqB18FEVHgYPto/2LIIaKgIoTAwTMVWHmoAKsPFWJfngmVVke9x1/Wvx0emtLy/W1GdUkAAOzJLUdRpRUJIbQ3jKwI11qc2SMzkRTV8qYBGrUKQzrEY0iHeDw8pTtOlVRjxcEC/HqwABuPFeNUiRkPfLEbF2TGITU2vMXXIyIKNDabjSHHjxhyiCjgVVjs+O1oMVYdKsCqQ4U4Y7LU+r5aJSEjPhydEiPRKSkSnZMj0SkxCh0SIxCh98xfc0lRBvRsG419eSasPVKIy/qHTgXiy+05OFpQiZhwLW4b08Er10iLC8cNw9vjhuHtUWV1YPYHW7DxeAleX3kMCy7v7ZVrEhH5ixACDoeDIcePvBpyFixYgK+++goHDx5EWFgYhg8fjmeeeQZdu4beVA8i8qwKix3f7MjFT3vOYEt2Sa2NKQ1aFUZ0TMDYrom4IDMemQkR0Gm8/4NkTJdE7MszYfWh0Ak5FruMl5YdBgDMHdsJ0Qbv7+cQodfgvgu74uq3N+Dzracwd1xHVnOIKKSwfbT/eTXkrF69GnPnzsXgwYPhcDjwyCOPYNKkSdi/fz8iItxf1EpEoe/AaRP+u/EEvt6Ri2rb751pMhMiMKZLIsZ1S8KQzDgYtL7/wTGmSyLeWHUMa44UQVGEW3vtBKr/bjyBvHIL2hgNmDWs7o0/veGCzDiM6BSP344Ws5pDRCHHGXJ0Op2/h9JqeTXkLFmypNafFy1ahKSkJGzbtg2jR4/25qWJKIhYHTJ+3nMG/914AltPlLoe75gYgesuSMeE7snIbEa3L08bkBGLSL0GJVU27M0rR5/UGH8PqUVMFjteX3kUAHDvxC4+D453T+iC346ymkNEoccZcjhdzX98uianvLwcABAXV3f7VavVCqvV6vqzyWTyybiIyD8KTBYsWp+Nz7accnVC06gkXNQzBdcPTcewDvEB1X5Tq1ZhRKd4/LIvH6sPFQZ9yHl3zXGUVtvRMTEClw9o5/Prs5pDRKFKlmUIIQLqZ1hr47N4KYTAfffdh5EjR6JXr151HrNgwQIYjUbXV1pay1q+ElHgKqq0Ysbrv+HNVcdQXGVDSrQB913YBesfGo/Xrx+A4R0TAvKHw5guSQCA1YcL/TySlimssOLddVkAgL9d1A0atX9+23j3hJpNRz/fego5pdV+GQMRkadxI1D/89lPtXnz5mH37t345JNP6j3m4YcfRnl5uevr1KlTvhoeEfmQQ1Yw7+PtOF1uQUZ8ON7600Cse3Ac7prQGUnRLW9f7E2jz7aS3n6yFOXVdj+PpvleW3EE1TYZfdNicFHPZL+Nw1nNcSgCr6885rdxEBF5EkOO//kk5Nx555347rvvsHLlSqSm1t+RSK/XIzo6utYXEYWeZ385hI3HSxCuU+PdPw/C5F4pfqskuCs1NhydkiKhCOC3Y0X+Hk6zlFbZ8OmWml8iPXhRV79XzFjNIaJQw41A/c+r774QAvPmzcNXX32FFStWIDMz05uXI6Ig8OPu03hnzXEAwHNX9kXn5Cg/j8h9Y7okAgBWHSrw80ia57Otp2B1KOjZNhrDOsb7ezis5hBRyGHI8T+vvvtz587Ff//7X3z88ceIiorCmTNncObMGZjNZm9elogC1NGCCvzti10AgNtGd8C0Pm38PKLmcYac1YcLIYRo5OjAIisCH208AQC4YXh7v1dxnIKpmmNzKDhaUBF0956IfIMbgQYGr777b775JsrLyzF27Fi0adPG9bV48WJvXpaIAlCFxY7bPtqGapuMYR3i8cBFwbsp8AWZcTBoVcg3WXEov8Lfw3HLrwfykVNqRmy4Fpf0bevv4bgESzUnq6gKl7y2DhNfWINbP9yKM+UWfw+JiAIMNwINDF6frlbX14033ujNyxJRgBFC4G+f78bxwiq0MRrw6sz+QbMGpy4GrRrDOtRM81p9KLi6rH24oaaKc83gdL9sqNqQQK/mLN13Bpe8ug4Hz9QE2+UHCnDhi6vx2ZZTrOoQkYssy5BlmZUcP+O7T0Re99bq41iy7wx0ahXeuH4AEiL1/h5SizmnrK0MonU5RwsqsO5oEVQS8Keh6f4eznl8Vc0RQqCwwtrkYOKQFTz980Hc9tE2VFgdGJQRi49vGYK+qUZUWBx44Mvd+PN7mwMymBGR73Ej0MDAd5+IvOq3o0V47peDAIDHL+mB/umxfh6RZ4zvVtN2eUt2KcqqbX4eTdN8sL6mijOxezJSY8P9PJq6ebuaU1hhxa0fbsPgfy7HxBdW463Vx1Bgqn/KWVGlFX9+bzPeWl0Tum4ekYlPbhuK4Z0S8OVfhuPvU7tBr1Fh7ZEiXPTiGny08QQUhVUdotaMG4EGBoYcIvKa3DIz7vxkBxQBXDUwFTMvCLzqQXOlx4eja3IUZEUERTXHZLHjy+05AIAbh7f372AaULuac9Sj516y9zQuemkNlh/IBwAcK6zC0z8fxLCnV2D2+1uwZO8Z2ByK6/htJ0ox/ZV1WH+sGOE6NV6b2R+PXdwD2rNTLTVqFW4b3RE/3z0KgzJiUWWT8X/f7MXMdzfiRHGVR8dORMFDlmUGnADAkENEXrHyYAGueXsDSqps6NUuGv+4tFfI/aV/YY+aas7y/YEfcr7cloNqm4zOSZEB0Ta6IfdMrKnmLN5yCgdOm1p8vnKzHfct3ok5/92OkiobuqVE4cu/DMOCy3tjQHoMZEXg14MFmPPfbRi64Fc8+f1+vLHqKK59ZwPOmCzomBiBb+eOwPQ+dTdq6JAYic9uH4bHL+6BMK0aG4+XYPJLa7HrVFmLx05EwcfhcPh7CASGHCLysLwyM+Z8tA03vb8FOaVmtIsJw5vXDwy4Re6eMPFsyFl1qABWR+Dubq0oAh+dbTjw5wBqG12fwe3jMLV3ChQBPP7dvhYt6l93pAiTX1qDr3bkQiUBd4ztiG/njcDAjDhcd0E6vrpjBJbfNwZzxnREUpQeJVU2vPdbFp5dcgh2WWBa7zb4dt7IRvdzUqkk3DQiE7/cMxqD28fCbJcx9+PtKDfbmz12IgpO3CMnMPAOEJFH2GUF/15zHBNfWI0l+85ArZJw2+gOWHrvaKTFBeb6j5bq086IpCg9qmwyNhwr9vdw6rX2aBGOF1UhSq/B5f3b+Xs4TfLItB4waFXYnFWC73bluf18s03G/O/24U//2YTT5RZkxIfj8znD8MDkbtBragfuTkmReGhKN6x/aDzeu3EQpvRKQUKkHo9O647XZvZHpF7T5Oumx4fjPzcORnpcOHJKzXjgi13svEbUythsNoacAND0v7mJiOqxNbsEj36z19Vad1BGLJ66rBe6pUT7eWTepVJJmNgjGR9vOonlB/IxtmuSv4dUpw/WZwMArhyUigg3PrD7U7uYMMwd2wnPLzuMf/10ABO7Jzd57EcLKnDbR9twvLBmXcyfhqbj4SndG32+Rq3C+G7JrqYSzRVt0OL1mQNwxZvr8cu+fCz6LRs3j8xs0TmJKDgoisI9cgIEYyYRuc0hK8grM2PbiRI8+MVuXPnWBhw8U4HYcC2evaIPPrt9WMgHHKcLu/++LicQf2N/orjK1Rhh1tAMP4/GPbeO7oD0uHDkm6x4dUXTmhAUmCy44b0tOF5YheRoPT64+QI8dWlvn4e73qlGPDKtOwBgwc8HsJPrc4haBbaPDhzB8Ss9IvI5RRHYl2fCpqxi5JaZcabcgrxyC86Um1FYYcUfu+ReMygND07phrgInX8G7CfDOsYjXKfGGZMFe3LL0Sc1xt9DquWjDScgRM2+Ph0SI/09HLcYtGo8Nr0HbvlwK/6z7jiuHpTa4Guosjpw8wdbkFtmRoeECHw+Zxji/bgn05+HZWBTVjF+2nMG8z7ejh/vHAVjuNZv4yEi73NuBKrTta6fhYGIIYeIXCqtDqw7UogVBwuw8lAhCius9R6rVUtIjjYgMyECd0/ojEHt43w40sBh0KoxunMiluw7g+X78wMq5FTbHPhs6ykAgd02uiETuidhXNdErDxUiCe+34/3bxpcZ+MEh6zgzk92YG+uCfEROiy6abBfAw4ASJKEp6/og725JpwsqcZfv9iFd2YNDPjGD0TUfM7paqzk+B9DDlErl1VUhV8P5GPloQJsziqBXf69RBOhU2NYxwR0SopEG6MBKUaD658JEXqoVPywBtS0kl6y7wyW7s/HfZO6+ns4Lt/syIPJ4kBGfDjGdEn093CaRZIkPHZxT/x2dA1WHy7E8gMFrtbdTkIIPPH9fqw4WAC9RoV/3zAIGfERfhpxbeeuz1m2Px/v/ZaN2VyfQxSyZLmm0yZ/meF/DDlErdhLyw/jpeVHaj2WmRCBcV2TML5bEgZnxp7XiYrON75bElQScPBMBU6VVAdENzkhhKvhwKyhGUEdSDMTIjB7VCbeXHUMT/6wD6M6J9RqSf7u2ix8tPEEJAl46Zp+GJAe68fRnq93qhGPTu+Ox77dh6d/PoCBGbHolxbj72ERkRfIshyQ6zNbI9bSiFqp11cedQWc4R3j8ei07lhx/xis/OtYPHZxD4zsnMCA00SxETrXdL3lB/L9PJoaG4+X4FB+BcK0alw1KM3fw2mxeeM6ISXagFMlZryz5rjr8Z/2nMY/fzoAAHhkandM6d3GX0Ns0KyhGZjaOwV2WWDu/7ajvLp5++cUV1qxOasEe3LKofxxYRwR+Z3D4WAVJ0CwkkPUCr279jie++UQAODhKd1w+5iOfh5R8JvUIxmbs0qwbH8+bhrh/+lI76/PAgBcNqAdjGHBv9g9Qq/B36d1x12f7MDrK4/i8gHtkG+y4t7FOwEANwzLCOhpYM71OfvyTDhRXI15n2zHJX3bIlKvQbhegwidGuE6DSL0akToNbA6FBwtqHR9HSuoxJGCCpSeE47iInQY1TkBY7okYlTnRCRG+XcNEhFxj5xAIokArqmZTCYYjUaUl5cjOrp1tKMl8rYPN2TjsW/3AQDuu7AL7prQ2c8jCg0niqsw5rlVUKskbH/0Qr920dqbW47pr64DACy9dzS6JEf5bSyeJITAte9sxKasEgzvGI+DZypQUmXDxO5JeHvWIKiDYEre3txyXP7GethkpdnnaBcTBpPZjgqro9bjvdsZMaZLIsZ0TUT/tBho1PygReRrJ06cgMPhQFhYmL+H4jEOhwM2mw0ZGRnQav37SzN3sgErOUStyOItJ10BZ+64jrhzfCc/jyh0ZMRHoHNSJI4UVGLV4QLM6NfOb2N5YdlhAMAlfduGTMABaqohT8zoiWmvrMP6Y8UAaj7Yv3Jd/6AIOADQq50R7904GJ9sPolKqwPVNgeqrHLNP20yqqwOVNtkaFQS2idEoFNiJDol/f7VMTESYTo17LKCHSfLsPpwAVYfLsTeXBP25JZjT245Xlt5FN3bROP9mwYjOdrg75dM1GooigJZllnJCRAMOUStxNc7cvDQV3sAALeMzMRfJ3XlvGEPu7BHMo4UVGLp/ny/hZyt2SVYcbAAapWEey/s4pcxeFO3lGjMGpqB99dno11MGP5z4yCE64LrR9nIzgkY2Tmh3u8rioAAGgxuWrUKF2TG4YLMOPztom4oqLBg7eEirD5ciJWHCnDgtAlXvLke/509BO0TAqPTHFGoc24E6u9qB9Vg1CRqBX7cfRr3f7YLQtQsgH5kWncGHC+YeLa18epDhbA5mj8dqbmEEHj27FqrqwelIjNEP9w+NKUbnrikJxbfPhRJUaFXqVCpJLcrU0lRBlwxMBWvXNcfP901Cu3jw5FTasaVb23AgdMmL42UiM7l3AhUrWbTnkDAkONB7HRDgWjpvjO4+9MdUETNB98nLunJgOMl/VJjkBilR6XVgY3Hi31+/bVHirA5qwQ6jQp3jg/dtVYGrRo3DG+P1Fj/t+oORGlx4fh8znB0bxONokorrn57A7Zml/h7WEQhz9k+mtPVAgPvgoe8tuIIOj/6M6a+vBZPfr8fS/edaXaL0GBSWGHFp5tP4m+f78L2k6X+Hg79wcpDBZj38Q44FIFL+7XFgsv7BPV+KYFOpZIwsXsSAGDZft+2khZCYOHSmirOn4ZkoG1M6Cx6JfclRunx6W1DMSgjFhUWB/70n01YdajA38MiCmnOjUApMATXROYAtnjrKciKwP7TJuw/bcJ7v2VBkoDuKdEY2iEewzrG44LMuIBt5eqsQjXlA/CJ4ios3ZePX/adwbaTpXD259t6ohTL7xsTNAuAQ92aw4W4/aNtsMkKpvZOwcKr+vLe+MDE7sn4ZPMpLD+Qjydn+K5q9su+fOzOKUe4To07xrElOAHGMC0+mj0Ef/nfNqw6VIhbPtiKF67ph0v6tvX30IhCEkNOYGHI8YC8MjNOlZihkoCFV/XFthOl2Hi8GMcKq2qFnnCdumaudIDNky+utOLiV9ehoMKKpCg9EqMNSI7SIylaj+QoA5Ki9YiL0GNPThl+2ZePQ/kVtZ7fJ9WI7KIqZBVV4ac9p3Exf4D63fqjRbj1w62wORRc2CMZL1/bn+1kfWREpwSEadU4XW7BvjwTerUzev2asiLw/NkqzuyRmUiI5H4pVCNMp8Y7swbhr5/vwne78nD3pztgMtvxp6EZ/h4aUcix20N/Bk8wYcjxgE1ZNXPve7Uz4vIBqbh8QCoAoKDCgk3HS7DxeDGW7s9HYYUV3+/Kw50Bti/JV9tzkVduAQDklVtc/14ftUrC0A5xmNQjBRf2SEbbmDC8vPwIXlx+GK+vPIrpfdpwzYcfbTpejNkfbIXVoWB8tyS8NrM/tAw4PmPQqjG6SwJ+2ZePpfvzfRJyvt2ZiyMFlTCGaXHLqA5evx4FF51GhZeu6VdT2dl4Ao9+sxdFlVbcNb4zp68SeZDD4WDTgQDCkOMBm47XLOgc2iG+1uNJUQZc3LctLu7bFn1SjXjwyz1YdiA/oEKOEAJfbMsBADw4uRuGdYxHvsmCggorCkwWFJisKKio+XNabDgu6pWMcV2TEBOuq3WeG4e3x7/XHsfBMxX49UCBq8sU+dbW7BLc9P4WmO0yRndJxBvXD4Bew79wfW1i92T8si8fy/fn4z4vt3G2ORS8uLxmX5w5YzoG7JRY8i+VSsKTM3oiJlyLV1ccxUvLj2DnqTK8cHU/xEXoGj8BETXKbrez6UAAYcjxgE1ZNSFnSGZcvceM75YMSdqD3TnlOFNuQYoxMNqe7ssz4VB+BXQaFWYOSW/2ByRjuBZ/GpqBt1Yfw2srj2JC9yRWc3xsx8lS3LhoC6ptMkZ2SsA7swbCoGXA8Yfx3ZKgkoD9p03IKa32ahewz7aewqkSMxIi9bhhOKcgUf0kScL9k7oiLS4c//fNXqw6VIhpr6zFq9f1x6D29f/8IqLGOdtHM+QEDt6JFiowWZBVVAVJQoM/JBKj9OiXFgMA+PWgb7suNcRZxbmwR3KLfwM8e2Qm9BoVdp4qw29Hfd8+tzXbnVOGP7+3GZVWB4Z1iMe//zyIAceP4iP1GJgRCwBY7sUuaxa7jFd+PQIAuHN8p6DbFJP84+pBafhm7gh0SIjA6XILrnlnI95ZcwxCBOY2CLIicKywEj/tOY0Xlx3G/O/24duduSioaHhqNdWWVVSF+z7biddWHMG2EyWwy77fyyuUKYoCRVE4XS2A8CdiC208W8Xp0Sa60ZBwYY9k7DhZhuX783H9EP//xtXmUPDtzlwAwJUDU1t8vsQoPa67IB3vr8/GayuPNLijN3nO3txyzPrPZlRYHLigfRz+c+MghOn4l6y/XdQzBVuyS/HfTSfx52HtvbL24cMN2SiosKJdTBiuvSDN4+en0NW9TTS+u3Mk/v7VHny3Kw//+ukgNmeVYOFVfc+bjuxLFruMzVklOHjGhINnKnA4vwJH8ith/cPmuu+vr/lnp6RIDOsQj+Ed4zGkQzyn3tWjvNqOmxZtRnZxteuxcJ0ag9rHYXjHeAzrEI+ebaPZoKYFWMkJPAw5LeTc8G9IZnwjRwIXdk/Gs0sO4bdjxaiyOhCh9+/bv/JQAUqr7UiM0mNUJ88EkttGd8D/Np3AxuMl2HaiBAMzOAXCWxRF4PvdeZj/3T6Um+0YmBGL924azN/mB4irB6fh5V+P4GhBJX7eewbT+rTx6PkrLHa8seoYAOCeiZ259orcFqnX4OVr+2FIhzg88f1+LD9QgGmvrMNrM/ujf3qsz8ZhlxWsO1KE73flYen+fFRaHecdY9Cq0CU5Cl2ToxCh12BLdgn2nzbhaEEljhZU4qONJwAA3VKiMLpLIq4elIZOSZE+ew2BTFYE7vx0B7KLq9EuJgx9Uo3YeLwYpdV2rDlciDWHCwEAUXoNhnSIw22jO+KCBqbfU91kWYaiKAw5AYSfhlpokzPkdGj8L4ROSZHIiA/HieJqrD1SiMm9PPuhx11fnp2qdnn/dh777U3bmDBc3j8Vi7eewmsrjmLRTRd45LwtsSenHMsP5KPcbEe52Q7T2X+e+9XGaMDzV/dzTTEKZEIIrDpUiGd/OYQDp00AgL5pMXj/psGI9HNwpt9FG7S4eUQmXv71CF5dcQRTeqV4tJrz7toslFXb0TExApf1b+ex81LrIkkSrh+Sgb6pMZj38XZkF1fj6rc34IGLumH2yEyvdV+TFYFNWcX4ftdp/Lz3NMrO2Ty7jdGA/ukx6Jocja4pUeiWEoW0uPDz9vkqq7Zh49kOpuuPFeFwfiUOnqnAwTMVeGfNcQztEIfrh2Tgop4p0Gma9jNOCAG7LCArAg5FOftP8fs/ZYFkoz6ofqnw7C8HseZwIQxaFd7580D0bGuEoggcyq/AhmPF2HC8GJuOF8NkcWD5gQIsP1CAawen4aEp3fxa1Qs23CMn8EgiUCfhAjCZTDAajSgvL0d0dLS/h3OewgorBv9zOQBgx/9diNgmlMn/8cN+/GddFq4YkIrnr+7r7SHWq7jSiiH/+hUORWDpvaPRJTnKY+fOLqrC+OdXQRHAD3eO9EkL3fp8sS0HD325Gw6l8f/MdWoVnrmyNy7r3/Kpe96yJbsEzy45iC3ZpQBqfvM2Z2xH3Dwik1PUAlB5tR0jnlmBSqsDb/1pICb3SvHIeUurbBj17EpUWh14feYAj1eJqHUyWex46Mvd+GnPGQDA8I7xeO6qvmgXE+axa2QVVeHDDdn4cfdpFFRYXY8nROoxvU8bXNy3DfqnxTYrXBVVWrHhWDG+3ZmHFQfz4fxrPyFSh6sHpeG6C9KRFle7CUhplQ27csqwO6ccu06VYVdOOYoqrXWc/XdJUXp8OPsCdEsJvM8lf/Ttzlzc/elOAMCr1/Wvdx87WRHYn2fCx5tP4JPNpwAA8RE6PDq9Oy7t167BRkJCCOzOKceX23NQWm3HDcMyWmUji9LSUuTn5/v086pkr4I+Zz0MJ1ZBZS6Etd1wWDIvhBzl2V98ORwO2Gw2ZGRkQKv1bwdPd7IBQ04L/Lj7NOZ+vB3dUqKw5J7RTXrOxuPFuPadjYgN12LLIxP9Nv910W9ZeOL7/ejdzojv7xzp8fPf9ckOfLcrD1N7p+CN6wd6/PyNEULgxeVHXIuyR3VOQJ9UI6INWhjDfv+KDtMiQq/Bv346gGVnF4jfMbYj/jqpa0DtH3HgtAkLfzmEXw8WAAD0GhVuHNEefxnTkb9pC3ALfzmE11YeRY820fjxrpEe6Tq44KcDeHvNcfRsG43v540MqP9WKbgJIfDx5pN46ocDMNtlRBk0eHJGz0Y/6DbmcH4FXltxFD/sznOFD2OYFlN6peDivm0xJDPOoz8P88rM+HTzSXy65ZQrTEkSMLZLIgZnxmF/ngm7c8pxsqS6kTPVUKskqFWSq9ITH6HDp7cNRWcP/oLQ0/bmluPKt9bDYlcwZ0xHPDSlW5OetzW7BA9/tQdHCioBACM6xeOpS3sj8w8bmRdVWvHNjlx8vjXnvE3CJ3ZPxoOTuwb0++NpxcXFKCws9PrnVVXlaRhOrITh5Cro8zZBkm3nHWNL6AlL5oUwZ06CHJPZ4msy5HhBoIecx77diw83nMANwzLwxIxeTXqOQ1Yw8KnlKDfb8dntw/w273XaK2uxL8+EJy7piRuGt/f4+Q+dqcBFL62BJAHL7h2NTkm++4vO6pDx8Jd78NWOmqYKc8d1xP0XNhxaFEXguaWH8ObZNQ6TeiTjxWv6+W3dlF1WcPB0BXacKsVvR4uwdH8+hKj5QXv1oDTcPaFzwLQhp4aVVtkw4pkVqLbJePfPg1q8h1S+yYLRz66E1aFg0Y2DMa5bkodGSvS7rKIq3Lt4J3aeKgMATOvdBk9d2qtJMxbOtS+vHK+tOIqf955xPTa+WxKuH5KOUZ0TmzyNrLnssoJfD+TjvxtPYt3RojqP6ZAQgT6pRvRNi0Gf1Bh0TIyAVq2CWiVBczbcOANeebUdM9/diH15JiRE6rH49qHomBh4a3+KKq2Y8dpvyC0zY2zXRPznhsHnTfdriM2h4N9rj+OVX4/A6lCg06hw57hOmD0qE78dLcZnW09h5cEC1ywJvUaFi3qmwKBV4YttOVAEoJJqmhrde2EXtDF6rhoYqPLz81FWVoaoKM9/3pEsZYjc+yEMJ1ZBW3yg1vcc0emwpI+FHNkGhhMroDuzDZL4vVGHPbYjLO0vhLnDZDjiuzbr+gw5XhDoIeeiF9fgUH4F3rx+AKb0bvp0kXsX78TXO3Jx2+gO+PvU7l4cYd0OnjFh8ktroVVL2Pz3iW7/0GqqWz/cimX783H5gHZ44ep+XrnGH5VX23H7f7di4/ESqFUS/nlpL1x7QXqTn//V9hw89OUe2GQF3dtE490bBnl0qkZ9TpebseNkGXaeKsOOk6XYnVN+Xjeh6X3a4L4Lu6BDAP5ApYY9/fNBvLX6GPqkGvHt3BEt+o34/32zFx9tPIGBGbH4Ys4w7kdFXuOQFbyx6hhe+fUIHIpAUpQez17ZB2O7Nh6sd54qw2srjmD5gQLXY5N7pmDe+E5+m8KcVVSFTzefRE6pGT3aRqNvagx6pxrd3j6htMqGme9uwoHTJiRH67H4tmFo/4cqhz/ZZQXXv7sJm7NKkJkQgW/mjmj2FhEniqvw6Dd7sfZITUDUqKRa07/7psXgqoGpuLhvW9c1jhZU4LlfDuGXfTWzI5wzD+4Y0wnG8NDdrDgvLw9VVVWIiPDwfwtCIP77WdCf2VbzR0iwJfeHNWMsLBnj4IjpWFOmPEtlLoYh+1cYspZBn7sRkvi9kYctuR+qel4Pc+YkQN30z34MOV4QyCGnpMqGAf9YBgDY9uhExEfqm/zcn/acxh3/247MhAisuH+Mzz+k/PPH/fj32ixM7pmCt2Z5byrZrlNlmPH6b1CrJKz669jz5kJ72qmSaty4aDOOFVYhUq/BG9cPwOguiW6fZ9uJUtz+0VYUVdqQEKnH27MGerQhgRACp0rM2Hi82PWVV37+fg/GMC36pcWgf3oMLuyRjJ5t/be2iVqmqNKKUc+shNkuY9FNgzGuCR8S63KqpBrjn18Fuyzwya1DMaxj410diVpqd04Z7l28E8cKqwAAfxqajvHdklBllVFtc/z+T5uMaqsDRwoqsf5YTVMelQRM79MWc8d1QteU0Jm6VFxpxXX/3ojD+ZVoYzRg8W3DkB7v3Z9xTeWcZRKp1+CbucNbPJNCCIHvduXhHz/sP/tzUYfL+rfDVYPSGlzPu+1EKZ7++YBrDWm0QYNZwzKQHheO2HAd4iJ0iI3QIS5cB2OY1jXbQlEESqttKKq0oajSiqJKKworrCiusqFfWgwu6umZtY2edurUKVitVoSHe/a/A/2JlYj/5Q4ItR5lIx+HNX0MlLCmzQKSrCYYTq6CIWspDCdWuwKPHJaA6u5Xoar7NVAiGp9dwJDjBYEccpbsPYM5/92GzkmRWHbfGLeeW2l1YMCTy2CTFSy/b4xP21w6ZAVDF6xAUaUV//7zIFzYwqkzjZn1n01Ye6QIM4ek41+X9fbadXaeKsMtH2xBUaUNbYwGLLppcIsWheaWmXHLB1tx4LQJOrUK/3dxD1zUMxlJUc2bInaqpBobzgaaTcdLkFtmrvV9tUpCt5Qo9E+PQf+0WPRPj0FmQgR/Sx9CnL9c6JcWg6/vGN6se3v/Z7vw5fYcjOqcgI9mD/HCKInqZrbJeGbJQby/PrtJx6tVEi7t1w5zx3UM2epzYUVN0DlaUIl2MWH49LahXv9lXmMWbzmJB7/cAwAe/xlfYbHjRHE1uqZEQdvE9VNCCKw4WIBnlhzE4fzKeo9TSTW/2NOoVSipskGup1mQWiVhyyMTA24/JCEETpw4AUVRYDB4cCq5IiPxy8ugLT2Cir63oGLI/c0+laq6AOEHPkfEgcVQV9e0DReSGpbMC1HVcyZsKYNqVYTOxZDjBYEccp74fh8W/ZaNPw1Nx1OXuv/h/c/vbcaaw4V4aEo3zBnT0QsjrNuKg/m4+f2tiI/QYePfJzT5L6rm2nS8GNe8sxE6tQprHhjXrHUkJ4qr8P76bFRaHBAAhAAEBM7+D4oQ+GXfGVjsCnq2jcZ7Nw5GcnTL/5Kpsjpw7+KdWHrOjvXtYsLQN82Ivqkx6JsWg97tjK51O0II5JusOFZYs2+D859HCyprdRECAK1aQt/UGAztEI9hHePRPz2G+9uEuIIKC0Y9U7OW5qPZF2BUZ/eqjEcLKjDpxTVQBPDN3BHolxbjnYESNWDtkULXOo1wnRoROg3C9RpE6NQI12kQoVcj2qDFRT1TAqay4U0FJguufWcjjhdVIS0uDItvG4a2Ppji/EenSqrx5fYcvLHyGGyygvsu7IK7JnT2+TjqIysC3+7MxbojRSittqGk2o7SKhtKq2yoqGNfJACIDdciIVKPhEg9EqP02JxVgjMmC168pm/AdUGVZRknTpyAJEnQ65s+s6cxYYe/Reyqh6DoopF/3VIIvQdmdCh2GLKWI2L/x9Cf3up62B7bEeYOU2BpPxGOuC61Ak+whhx+qmqmTcdLADRtE9C6XNgjGWsOF2L5/nyfhpwvzu6NM6NfO68HHAAY0iEeg9vHYkt2Kf7+9R68PWugW9fNKa3GNW9vxBnT+dO5/mhc10S8NnOAx5oFROg1eOtPA/HWmmP4ZkcujhRUIrfMjNwys6vFqkqq2f8oTKfB8YLKev+y1qgk9E2LwdAOcRjWIQEDMhhqWpukKANmDknHot+y8fLyIxjZKcGtas6Ly45AETV/dzDgkL+M6pzodkAPZUnRBnx861Bc884GnCiuxnX/3ojFtw3zSWOYapsDP+85gy+25WDD2T37AGBKrxTMG9fJ69d3h1ol4fIBqbh8wPnhxOZQUGa2obTKDrusIDFKj7gI3XmfFZ775SBeX3kMvx4oCLiQoygKhBBQqz24lYNsQ9S2VwEAlf1u8UzAAQCVFpaOU2DpOAWa4kOI2Pcxwo5+D23pMWi3vYboba/VNDNoPxHmzImwJ/lvu5OWYiWnGcqr7ej3j6UQAtj8yIRmTWE6XW7GsAUrIEnAlkcmIsGNNT3NVVZtwwX//BU2WcGPd4302RqPHSdLce07G2F1KJjWpw1eubZ/k7q8FFdacdVbG3C8qAodEyNwxcBUSJAgSYAEnP1nzZ8To/SY1ruNV1tyV1od2JNTjl05ZTX7KZwqO28tjUoCMuIj0DExEh2TItApMRIdkyJdu3RT65ZvsmDUsythcyj4+NYhGN4xoUnP25tbjumvroMkAT/fPSoo9ucgak3yysy45p0NOFVihkGrwgWZ8RjZKR4jOiWge0p0o909jxdVYXdOGfbmmqAIgaRoPZKiDEiK0rv+Pfbsov0t2aX4Ytsp/Lj7NKpsNRtQSlLNvkZXDEjFJX3b+m17Cm/adqIUV7y5HlEGDbb/34U++UVtU1mtVpw8eRJ6vR4ajYd+0br3vzCu/yfk8CQUXLsEQuO9CqFkNdU0K8heDkPOulptqeXwRFSnj4ep3VgkDb4UWoN/K7Ss5HjZ5uwSCFHTdrK5azTaGMPQq1009uaasOJgAa4elObhUZ7v+92nXV3DfLmIvX96LN6aNRC3fbgVP+4+jTCtGs9e0afBv/QrrQ7c9P4WHC+qQlujAR/NHuKXKQDnitRrMKxjfK3F3gUmC3bnlMMuK+iYFImM+PCg2gmbfCs52oBrB6fhww0n8MqvR5occp5feggAcEnftgw4RAGobUwYPrl1KG5atAVHCiqx5nAh1hyuWfcQF6HD8I7xGNkpASM6JUAIYHduzQakzmBTWc8sgHNp1RLCdRqUm+2uxzLiw3HlgFRcNqAdUmNDe3pgv7QYxEXoUFJlw9bs0oBqvCKEgKIoUKk8E7wkWxUit78JAKgYONerAQcAhD4a5q6Xwdz1spoNRk+thSFrOQwnV0FdXYiog4sRdXAx7F0GAIam7bcUCBhymmHT2bLwkA4t2+Pmwu4p2JtrwvL9+T4JOc6palcM8OxOuE0xrmsSXr2uP+Z+vANfbMtBhE6N+Zf0rHO6jtUh4/aPtmJ3Tjliw7X4MAACTn2Sog2Y2IP71VDTzRnTEZ9sPomNx0uw6XgxhnRo+Af11uwSrDxUCLVKwr0Tu/holETkrtTYcCy9dzQO51di3dEi/Ha0CBuPF6OkyoYfdp/GD7tP1/tcg1aFnm2N6N3OCINWjYIKCworrCgwWVFQYUFptR12WaDcbEeETo3pfdriykGpGJQR22oa1KhVEsZ2TcRX23Ox4mB+QIUc53Q1T92LiD3vQ20pgcOYgequl3nknE0ltBGwdJgMS4fJgGyDPncD9MeXQVV+Ato43y2v8ASGnGbYlNWy9ThOE3sk4cXlh7H2SBEsdhkGrfcqAEcLKrDrVBnUKgkz+vk+5ADA5F5tsPAqGfd9tgsfbDiBMJ0GD07uWusvBVkRuHfxTvx2tBjhOjXev+kCn3afI/K2tjFhuGpQGj7edBKvrjjaYMgRQuC5X2qqOFcNTA2ovTiI6HySJKFrShS6pkRh9shM2GUFu06VuULPjpNlUEkSureJQu9UI/q0i0GfNCM6JUY2OMXM6pBRVFmzUL9DYkSrXdM5vlvS2ZBTgEem9fD3cFwUpWZfO0+EHJW5BJG73wMAmAbdDaj8uNBfrYM1fQyq2o6oaTzgv5E0S+v8f0kLmCx27MsrB9DySk6PNtFoFxOG3DIzfjtahAndvdfO+YttuQBqFucnRnl//U99LuufimqbjEe+3ou3Vh9DpF6NeeNrOsAIIfB/3+7FT3vOQKdW4Z1Zg9CXC6wpBP1lTEd8tuUU1h0twrtrj2NU50R0Soo8b63auqNF2JRVAp1aFVCdkoioabRqFQa1j8Og9nG4Z2IXWOwyVJIEnca9aU16jRrtYsJ8sjl1IBvVOREalYRjhVXILqoKmF/8OEOOJ0TueBsqezVsCT1h6XCRx87bGgXOqq0gsS27FIqomQfbxtiyv2wkScLE7jWbAi4/kN/I0c0nKwLf7KgJOVfU0dnE164fkoFHp3UHACxcehj/WZcFAHhh2WF8vOkkJAl46dp+GNm5aesViIJNWly46/+LT/14ABe9tAa95/+Cq9/egH/+uB/f78rDyeJqLDxbxbl+aHrATtkkoqYzaNVuBxz6nTFMi8Hta37BvOJggZ9H8zvndLWWUlfkImL/JwCAigvuBST+t9ISrOS4aWPW2fU4mS2r4jhN7JGMDzacwPIDBfinIhpcjN9cP+zOwxmTBTHhWozv3ryd1j3tllEdUGWV8eLyw/jHD/uxNbsEP++tacv81KW9MLV3Gz+PkMi7Hr+kB5Ki9diUVYK9ueWotsnYnFWCzWenwzqFadW4Y2xgtYMlIvKXCd2TsOF4MVYcLMDNIzP9PRwAnqvkRG17DZJih7XtUFjbDffIOVszhhw3tXR/nD8akhmPKL0GhRVW7MopQ//0WI+c18kuK3hh2WEAwC0jMwOq89ddEzqh2u7A26uPuwLO/Rd2wfVDgm3WJ5H7wnUa3D+pK4CaauuxwkrsOlXTcWlXThkOnDbBLgv8ZWxHv04xJSIKJOO7JeGpHw9gU1YxKix2RBn8uzklULNZZks7q2lKDiPs8LcAANMF99XajJOahyHHDVVWB/bkemY9jpNOo8KYron4YfdpLD+Q7/GQ88W2HJworkZ8hA43jQiM33g4SZKEhyZ3g9Wu4P312bhlZCbmjedvrKn1UaskdEmOQpfkKFx1ttOi1SEjv9yKtDhOUyMicuqQGInMhAhkFVVh3ZEiTAmAmR8Oh6PFTQeitrwCCQLmzEmwJ/X20MhaN4YcN2w9UQpZEWgXE+bRfvQX9kjGD7tPY+m+fEzr3RY5pdXIKTWf/ap2/TNSr8Hi24chLa5p17bYZby8/AgAYO64TgG5GaUkSZh/SU/ce2EXGMP8/9sYokCh16iRHh/a+14QETXH+G5J+M+6LPx6sCAgQo4syy2q5GjzdyLsxK8QkgoVg+/24Mhat8D71BvAPLU/zh+N7ZIEtUrCkYJKTH1lbb3HmSwO3P/5Lnx669Amrd3578YTOGOyoI3RgJlD0j05ZI9jwCEiIqKmmHA25Kw6VADFS+uZm0oI0eKQE3b0BwCAudPFcMR08NTQWj2GHDc498cZ6qH1OE7GcC0u698OX2zLQUKkzlUpSo0NO/sVDoNWjdkfbMHmrBIsWp+N2Y0stqu0OvDmqmMAgLsndPbqHjxEREREvjKofRyi9BoUVdqwO7cc/fy43YQQAoqitGi6mq5gFwDAkj7aU8MiMOQ0mdkmY3dOGQDPV3IAYOFVffGvy3o32FrykWnd8cjXe/HskoMY0yWxwU0yF63LQnGVDZkJEbhioP/bRhMRERF5gk6jwuguifhxz2msOJDv15DjbB+tVjfzl8kOC7RFBwEA9qS+HhwZsQF3E20/WQq7LNDGaEB6E9fEuKux3vkzL0jHqM4JsDoU3P/5LjjkulsWllXb8M6a4wCAeyZ2hraBXZSJiIiIgs24bjVbYvzq5/1yFEVpUSVHV7QPknBADkuAHNnWw6Nr3fjpt4lc63Ey41rcQaO5JEnCs1f2QZRBg12nyvD22SDzR2+vOY4KqwPdUqJwcR/+H4aIiIhCy9iuiZAkYF+eCWfKLX4bhzPkNHdNjja/ZqqaLbkf20Z7GENOE+WW1fwfaEgHz67HcVcbYxieuKQnAOCl5Ydx4LSp1vcLKixY9FsWAOCvk7r6dTEeERERkTckROpd09RW+LGa45yu1uxKztn1OJyq5nkMOU30/NV9se3RiZjex/+tCi/r3w6TeiTDLgvc99ku2By/T1t7fcVRWOwK+qXFYEL3JD+OkoiIiMh7JpydsrbiYL7fxtCikCMEdPk7AQC2ZIYcT2PIcUN8pD4gdtaVJAn/vKw34iJ0OHDahFdX1OyFk1NajY83nwQAPHBRV79NqyMiIiLytvHdkgEA644WwWKX/TIGRal7fXRTqKrOQF1dACGpYU/s5cFREcCQE7QSo/R46tKa/0O8seoYdp4qw8vLj8AuC4zoFI/hnRL8PEIiIiIi7+neJgptjAZY7Ao2HCv2yxhaEnJcU9Xiu0Jowjw1JDqLISeITe3dBpf0bQtZEZj38XZ8uT0HQM1aHCIiIqJQJkkSxru6rPlnylqLOqudnarG9Tje4ZOQ88YbbyAzMxMGgwEDBw7E2rVrfXHZVuHJGT2RGKVHTqkZigAmdk9G//RYfw+LiIiIyOuc649XHiyEEMLn13c4HC1uOmBL7ufBEZGT10PO4sWLcc899+CRRx7Bjh07MGrUKEyZMgUnT5709qVbhZhwHZ65ojeAms6D90/q4ucREREREfnG8I4JMGhVyC0z41B+hc+vL8ty80KObIO2aD8AwMZKjld4PeS88MILmD17Nm655RZ0794dL730EtLS0vDmm296+9KtxvhuyXj1uv548/qB6N4m2t/DISIiIvIJg1aNER1r1iH/esD3raQdDkez9sjRFh+AJNsgG2IhR6d7YWTk1ZBjs9mwbds2TJo0qdbjkyZNwvr167156Vbn4r5tMblXir+HQURERORT41ytpH0fcppbydHln7M/DrvheoXGmycvKiqCLMtITk6u9XhycjLOnDlz3vFWqxVWq9X1Z5PJdN4xREREREROg9vHAQCOFlT69LqKokBRlGZVclz743Cqmtf4pPHAHxNufZsmLViwAEaj0fWVlpbmi+ERERERUZCKDa/Zw7DCYoei+K75QEs2AtW6mg4w5HiLV0NOQkIC1Gr1eVWbgoKC86o7APDwww+jvLzc9XXq1ClvDo+IiIiIglx0WE3IUQRQZXP47LrNreSoqgugqcyDgAR7Yh8vjY68GnJ0Oh0GDhyIZcuW1Xp82bJlGD58+HnH6/V6REdH1/oiIiIiIqqPQauGTlPzkdZk8W3IEUK4HXKc63EccZ0hdBHeGBrBy2tyAOC+++7DrFmzMGjQIAwbNgzvvPMOTp48iTlz5nj70kRERETUCkQbtCiqtKK82o52MWE+uWZzp6u5pqpxPY5XeT3kXHPNNSguLsaTTz6J06dPo1evXvjpp5+QkZHh7UsTERERUStgDNOgqNIKk8Xus2s2N+RwE1Df8HrIAYA77rgDd9xxhy8uRUREREStjHNdjsns25Dj/pPs0BbsBXC2fTR5jU+6qxEREREReUu0oSbklAd4yNGWHIZKtkDRRcMRk+mFUZETQw4RERERBTWjs5Ljw8YDQrjfrlqb71yP0weQ+DHcm/juEhEREVFQiw6rWYHhy0qOw+F+oHJuAsqpat7HkENEREREQc05Xc2Xa3JkWXa/fTQ3AfUZhhwiIiIiCmq/T1cL3JCjspRCYzoJ4Ox0NfIqhhwiIiIiCmr+6K7mcDjcah+tdU5Vi+kAoTd6aVTkxJBDREREREHt9+lqvmk8oCgKFEVxK+Q4p6pxPY5vMOQQERERUVDz9XQ1Z8hxZ7qaLp+bgPoSQw4RERERBTVfd1cTQkAI0fSQo8jQFu4GANhYyfEJhhwiIiIiCmpGH6/JcXe6mqbsGFT2aijacDhiO3l5dAQw5BARERFRkHOuyamyyXDIitevpyiKW5Uc1/44iX0AldqLIyMnhhwiIiIiCmpRBo3r300W7zcfcIacplZyXOtxOFXNZxhyiIiIiCioadQqROprgo4vpqwpinvVIi03AfU5hhwiIiIiCnrRZ6s5vuiw5qzkNIVkLYe27BgAto/2JYYcIiIiIgp6zg1BfdFhzZ1Kjq5gDwDAEZ0OJSzOW0OiP2DIISIiIqKgFx3muw1BZVlu8nocbdE+AIAtsbc3h0R/wJBDREREREHP2WHNF9PVHA5HkzurqStyap4Tk+nNIdEfMOQQERERUdDz5Yag7lRyNBW5Nc+JaufNIdEfMOQQERERUdDz5Yag7lVyzoacyLbeHBL9AUMOEREREQU9X01XE0JAUZSmVXKEAnXlaQCs5PgaQw4RERERBb3fu6t5t/GAoihQFKVJlRxVdSEkxQ4haSBHJHt1XFQbQw4RERERBT1fTVdz7pHTlJCjOdt0QI5MAVQar46LamPIISIiIqKg56vNQJ2VnKZMV1Oz6YDfMOQQERERUdDz1WagzkqOWyEnkiHH1xhyiIiIiCjoGX20Gag7a3KcIccRxc5qvsaQQ0RERERBL/qcNTlCCK9dR1GUJh+rqeR0NX9hyCEiIiKioOdck2OTFVgdTQ8i7nIn5Kgr8gAw5PgDQw4RERERBb1IvQaqs8tkvNlhrcl75Cgy98jxI4YcIiIiIgp6kiT5pPmALMtNOq7WHjnhSV4bD9WNIYeIiIiIQkK04ey6HC+2kZZluUmVHNd6HO6R4xcMOUREREQUEnzRYc3hcLjVWY1T1fyDIYeIiIiIQkJ0WE3FxJvT1RwOB/fICQIMOUREREQUErw9XU0IwT1yggRDDhERERGFBOM5e+V4gzsbgWpc09VSvTIWahhDDhERERGFBG93V3PukePWdDWuyfELhhwiIiIiCgnebjzQ5ErOOXvkOBhy/IIhh4iIiIhCQrShpvGAt9bkOENOY5UcVXUBJOGAkDRQuEeOXzDkEBEREVFI8MV0NSFEo5Uc13qcyDaASu2VsVDDGHKIiIiIKCQ4Q443KzlNwfU4/seQQ0REREQhwdVC2otrcppCXcn20f7GkENEREREIcHo5c1AhRBNOo6VHP9jyCEiIiKikOCcrlZhsUNRmhZI3CHLcpOO01Tk1RwfyZDjLww5RERERBQSnNPVFAFU2Tw/ZU2WZe6REyQYcoiIiIgoJBi0aug0NR9vvTFlzeFwcI+cIMGQQ0REREQhw5sbgjalksM9cgIDQw4RERERhQxvbQgqhIAsy03YIycHAPfI8TeGHCIiIiIKGd7aEFRRFCiK0mglh+txAgNDDhERERGFjN+nq3m+kiOEaLSS4ww5XI/jXww5RERERBQynB3W/FXJcbWPZsjxK4YcIiIiIgoZ0WHONTmebTzgDDmNVnIqOV0tEDDkEBEREVHI8NZ0NUVRIITgmpwgwZBDRERERCHDOV3NLyFHcUBdeQYA4IhkyPEnhhwiIiIiChnO7mqebiGtKEqjx6ide+SotFDCEz16fXIPQw4RERERhQxvbQbapJDjnKrGPXL8jiGHiIiIiEKGN7urNX09TluPXpvcx5BDRERERCHj9+5qng05DoejySGH63H8jyGHiIiIiEKGt7qrybLMPXKCCEMOEREREYUM53S1KpsMu9z4Opqmcjgcje+RU5EDgCEnEHgt5GRnZ2P27NnIzMxEWFgYOnbsiMcffxw2m81blyQiIiKiVi7KoHH9e4WHNgQVQkCWZW4EGkQ0jR/SPAcPHoSiKHj77bfRqVMn7N27F7feeiuqqqqwcOFCb12WiIiIiFoxjVqFSL0GlVYHTGY74iJ0LT6nEKLxxgPcIyegeC3kTJ48GZMnT3b9uUOHDjh06BDefPNNhhwiIiIi8ppoQ03I8VSHNedGoA1VctRV+ZCEzD1yAoTXQk5dysvLERcXV+/3rVYrrFar688mk8kXwyIiIiKiEBIdpkVeucVjHdYURYGiKNBqtfUewz1yAovPGg8cO3YMr776KubMmVPvMQsWLIDRaHR9paWl+Wp4RERERBQioj28Iagz5DRYyalkZ7VA4nbImT9/PiRJavBr69attZ6Tl5eHyZMn46qrrsItt9xS77kffvhhlJeXu75OnTrl/isiIiIiolbN0xuCOqerNbQmx7VHDkNOQHB7utq8efNw7bXXNnhM+/btXf+el5eHcePGYdiwYXjnnXcafJ5er4der3d3SERERERELq69cjw4Xa2xkKNxTVdjyAkEboechIQEJCQkNOnY3NxcjBs3DgMHDsSiRYsabbtHRERERNRS0WE1H3E9tSFoo53VcM6aHFZyAoLXGg/k5eVh7NixSE9Px8KFC1FYWOj6XkpKircuS0REREStnLemqzWEe+QEFq+FnKVLl+Lo0aM4evQoUlNTa32vsf9IiIiIiIia6/fpap5rPNDkPXIYcgKC1+aP3XjjjRBC1PlFREREROQtv3dX80wlx+FwNNx0gHvkBBwukiEiIiKikBJtqJms5KnparIsN6mzmhzZBpD48ToQ8C4QERERUUjxdHc1h8PR8B45bDoQcBhyiIiIiCikeHoz0MYqORrukRNwGHKIiIiIKKScuyanpevBFUWBoigNV3IquUdOoGHIISIiIqKQ4pyuZpMVWB1Ki87VlI1AOV0t8DDkEBEREVFIidCpoTqbSVrafKBJlRyGnIDDkENEREREIUWSJI+1kW405CgOqKvyAQCOqNS6jyGfY8ghIiIiopDjqQ5rjU1Xq71HTkKLrkWew5BDRERERCEn2lATcjwxXa3BkOOaqtaWe+QEEN4JIiIiIgo50WE1G4K2tI20ojTcuMAZchzsrBZQGHKIiIiIKOR4crpaQ9SVeQAAOTKlRdchz2LIISIiIqKQ45quVt3ykNNg++jqwprjwpNadB3yLIYcIiIiIgo50R6q5DgcjgZDjqq6CAAghye26DrkWQw5RERERBRyXNPVWrgmR5blJlZyGHICCUMOEREREYWcaENN44GWdldzOBwNbgSqOhtyWMkJLAw5RERERBRyPDVdrcFKjhBQm2umq7GSE1gYcoiIiIgo5Hgi5CiKAkVR6q3kqKxlkJSa87OSE1gYcoiIiIgo5HhiM9DGNgJ1TlVT9EZArWv2dcjzGHKIiIiIKOR4ovFAY5UcNdfjBCyGHCIiIiIKOdFhNY0HKix2KIpo1jkana7GzmoBS+PvARAREREReZpzupoigEqbw/VndzQ2Xc2flRxFUWC322G1Wl1j1Gq10Ol0UKvVPh9PoGHIISIiIqKQY9CqodeoYHUoMJntXgk5vm4fLcsyrFYr7HY7JEmCTqdDTEwMwsPDYbfbUVFRgerqaiiKAq1WC71e32oDD0MOEREREYWk6DAtCiusNetyYt1/vqIoDX7fVxuBms1m2Gw2qNVq6PV6xMTEICwsDAaDoVaIiY2NhdVqRXV19XmBx2AwNLjfT6hhyCEiIiKikBRt0KCwwtrsDmuNhRxfVHIcDgccDgeSk5MRHh4OvV5ff2VJpUJYWBjCwsJcgcdsNqOiogJVVVUAAIPBAK3W/apWsGHIISIiIqKQZGzhXjmKotS/ESh8U8mprq6G0WhEbGxsg2P5o3MDT0xMDMxmM0wmEyorK1FdXQ29Xt9gYAp2DDlEREREFJJcG4I2s5LjcDjqDwFCeL2SY7fboVarERMT06IwolKpEBERgYiICFitVlRWVqK8vBwmkwkajea8aW+hgCGHiIiIiEJSSzcElWW53nAh2augcpgBeK+SYzabERsbi7CwMI+d01nBMRqNqKqqgslkcq3d0el00Ov1IbF2hyGHiIiIiELS79PVmrchqMPhaHyPHG04hDaieQNsgNVqhUajQUxMjMfPDQAajQZGoxHR0dEwm82orq5GZWUlqqqqanVnC1YMOUREREQUkpwbgjZnupoQArIs1xtyvLkeRwgBi8WCxMRErwcNSZIQHh6O8PBwxMXFwWKxwGw2o7KyEmazGQ6HAzqdzqtj8AaGHCIiIiIKSc7pas0NOQ01Hvh9I9Ck5g+wHlarFTqdDtHR0R4/d0NUKtV5gcdiscBqtQbdmh2GHCIiIiIKSS3prubcCLSx6WqebjoghIDVakVycrJfKyiSJLm6swWj4F9VRERERERUB2d3teY0HlAUBYqi+Hy6mtlshsFg8HkVJ9Qw5BARERFRSPp9upr7jQcaCzneqOQoigK73Y7Y2FhoNJxw1RIMOUREREQUkjwxXa2xNTmerOSYzWaEh4cjKirKY+dsrRhyiIiIiCgkOburNXe6WkMhx9OVHEVRIMsyYmNjg26RfyBiyCEiIiKikOScrlZtk2GXFbeeqygNH+/pSk51dTUiIiIQGRnpkfO1dgw5RERERBSSogy/r2upcHND0AZDjsMClc0EwDOVHFmWIYRAbGxsvWuAyD18F4mIiIgoJGnUKkTqmzdlreE9cooAAEKtg9C1vAtadXU1IiMjERER0eJzUQ2GHCIiIiIKWdFnqznubgjqcDiath6nnmPcoSgKIiMj670euY8hh4iIiIhCVnQzO6zJsuyTzmrONtX+3PgzFDHkEBEREVHIau6GoA6Ho/E9csJaHnLsdjs0Gg1Djocx5BARERFRyHLtlePGhqBCCMiyXG/I8WQlx263w2AwsG20hzHkEBEREVHIcraRdme6mhCikcYDntsjR1EUhIeHt/g8VBtDDhERERGFrOZsCNroRqBmz4QcIQSEEJyq5gUMOUREREQUsn6fruZeyHE2BKiLp6arORwOaLVahhwvYMghIiIiopD1+3S1pq/JaSzkqDw0Xc1ut0Or1UKj0TR+MLmFIYeIiIiIQlZzuqs1OF1NcUBlLqn51xaGHFmWERERwf1xvIAhh4iIiIhCVnOnq9UXclTmYkgQEJIaSlhci8amKAqnqnkJQw4RERERhaxoQ81UMHe6qymKUu/3XOtxwuIBqfkfpWVZhlqtZsjxEoYcIiIiIgpZ0c3YJ6ehkOPp9TgMOd7BVU5EREREFLI6J0Vi52MXIlLf9I+9TdkjxxOd1aKjo+ttbkAtw5BDRERERCFLo1YhJty9aonD4ah/jxwPVXJkWYbBYGjROah+jI5EREREROeQZdmrlRxne2pOVfMehhwiIiIionM4HA6v7pHjcDig0WgYcryIIYeIiIiI6CwhBGRZrjfkeKKSY7fbodPpuAmoFzHkEBERERGdJYRoUuOBllRyZFlGeHh4s59PjWPIISIiIiI6q6GNQCEUqKqLADQ/5AghIISAXq9vyTCpET4JOVarFf369YMkSdi5c6cvLklERERE5DZFUVyNAf5IZSmDJGr221HC4pt1flmWuR7HB3wSch544AG0bdvWF5ciIiIiImq2BkOOc6qaIRZQNy+kODcB1Wq1LRonNczrIefnn3/G0qVLsXDhQm9fioiIiIioRRqaruappgPh4eH1rvkhz/BqS4f8/Hzceuut+Oabb7i4ioiIiIgCXkMhxxPto7kexze8FnKEELjxxhsxZ84cDBo0CNnZ2Y0+x2q1wmq1uv5sMpm8NTwiIiIiovMoilLv91payeEmoL7j9nS1+fPnQ5KkBr+2bt2KV199FSaTCQ8//HCTz71gwQIYjUbXV1pamrvDIyIiIiJqtoZCTksrOc71OAw53icJIYQ7TygqKkJRUVGDx7Rv3x7XXnstvv/++1qlPlmWoVarcf311+ODDz4473l1VXLS0tJQXl6O6Ohod4ZJREREROS2kpISFBQU1PnZM3bZPQjL+gXlw/+Oql6z3D53ZWUlIiMj2ZCrmUwmE4xGY5OygdvT1RISEpCQkNDoca+88gqeeuop15/z8vJw0UUXYfHixRgyZEidz9Hr9ZyjSERERER+43A46m0K0NJKjizLCAsLa/bYqOm8tiYnPT291p8jIyMBAB07dkRqaqq3LktERERE1GyyLNcbclqyJsfZzIBT1XzDJ/vkEBEREREFA4fDUeceORCiRZUch8PB9Tg+5NUW0udq37493Fz+Q0RERETkM0IIyLJcZ8iR7JVQyRYAzavkOJsOaDQ++/jdqrGSQ0RERESEmpCjKErDG4HqoiA07q+rkWUZERER3ATURxhyiIiIiIjw+0agdVVyWtp0QFEUNtjyIYYcIiIiIiLUBJFGKznNXI+jVqu5HseHGHKIiIiIiPB7yPF0JcfZdECr1bZ4jNQ0DDlERERERPh9upo3KjlhYWF1d20jr+A7TURERESEhkNOSyo5sixzPY6PMeQQEREREaEm5NSnJZUcAGwd7WMMOUREREREaDjkNLeS4+zWplarWzQ2cg9DDhERERERUG9nNQBQVxXUHONmyHFuLspKjm8x5BARERERoaZBQF0hR3KYobJXAnC/kiPLMtRqNSs5PsaQQ0RERESEmkDSUNMBRW2A0Ea6fU6GHN9jyCEiIiIiQk0lp642z7WaDtQzna0+iqLAYDB4ZHzUdAw5RERERNTqCSFc62f+qKXto3U6XYvHR+5hyCEiIiKiVk8IUW/jgZa0j5YkiVPV/IAhh4iIiIhaPedGoJ6s5AghAHCPHH9gyCEiIiKiVk9RFI9Xcth0wH8YcoiIiIio1XOGHE9WcpznYyXH9xhyiIiIiKjVc05X82Qlx+FwQKPRsJLjBww5RERERNTqNRRyWlLJ0ev1HhkfuYchh4iIiIhaPUVR6v6GbIPaUlpzTDNCDttH+wdDDhERERG1evWFHJW5GAAgJA0UQ4xb5xRCcD2OnzDkEBEREVGr13hntQRAavpHZ+fUN4Yc/2DIISIiIqJWz+FwNBhymttZjU0H/IMhh4iIiIhaPVmW6w45plM1349q5/b51Go1Kzl+wpBDRERERK2ew+Goc48cTdmxmu/HdHDrfLIss320HzHkEBEREVGrJoSALMv1hJwsAM0LOeys5j8MOURERETUqgkh6m08oCmtqeTY3Qw5bB/tXww5RERERNSqOTcC/WMlR2UphdpaBgEJckx7t84phIBWq/XgKMkdDDlERERE1KopilJnJcdZxZGj2kJowpp8Pmf7aK7H8R+GHCIiIiJq1Zwh54+VHE3ZcQDur8dxnoud1fyHIYeIiIiIWjXndLXzKjnOkGPMdOt8zvbRrOT4D0MOERERERFQf8iJ7ejWeRhy/I8hh4iIiIioDr9PV3O/kqPX6+vs1ka+wZBDRERERPQHksMMdUUeAMAR414lh+2j/Y8hh4iIiIjoD9Rl2ZAgoOiNUAyxbj+fTQf8iyGHiIiIiOgPnFPV7DEdATemnQkhIIRgyPEzhhwiIiIioj/QlmUBcH89jqIobDoQABhyiIiIiIj+QFNWsxFoczursZLjXww5RERERER/oGlmJYftowMDQw4RERER0bkUGZpyZ8hxv5Kj0+nYPtrPGHKIiIiIiM6hrsyDJNsg1DrIkW3dei7bRwcGhhwiIiIionO41uMY2wMq96adCSGg1Wq9MCpyB0MOEREREdE5fl+P08Ht50qSxPU4AYAhh4iIiIjoHJrSs5UcN0OOoiiQJImd1QIAQw4RERER0TmclRy7myHH4XBAo9Ew5AQAhhwiIiIiIichoC1rfiWH7aMDA0MOEREREdFZKkspVNZyCEiQY9q79VxZlqHVatk+OgAw5BARERERneXsrCZHtYXQhLn1XFmWodfrvTEschNDDhERERHRWS3prMb20YGDIYeIiIiI6KzmdlYD2D46kDDkEBERERGdpSlvXiWH7aMDC0MOEREREdFZmrLjANwPObIsQ6PRsJITIBhyiIiIiIgASA4z1BV5AABHbEe3nivLMlQqFSs5AYIhh4iIiIgIgLosGxIEZH0MFEOsW8+VZRk6nY7towMEQw4REREREQBtM6eqAWwfHWgYcoiIiIiIcM56nFj3Qw4ATlULIAw5RERERERoftMBoGaPHIacwMGQQ0RERESE5occRVGgUqnYWS2AeD3k/PjjjxgyZAjCwsKQkJCAyy+/3NuXJCIiIiJyjyJDU54NoHnto9VqNSs5AcSrd+LLL7/Erbfein/9618YP348hBDYs2ePNy9JREREROQ2bdVpSLINQq2HHNnWrecy5AQer90Jh8OBu+++G8899xxmz57terxr167euiQRERERUbPoTNkAAIexPaByb9qZLMsIDw9n++gA4rXpatu3b0dubi5UKhX69++PNm3aYMqUKdi3b1+9z7FarTCZTLW+iIiIiIi8TV+RDaD57aO1Wq2HR0Qt4bWQc/x4zcKt+fPn49FHH8UPP/yA2NhYjBkzBiUlJXU+Z8GCBTAaja6vtLQ0bw2PiIiIiMhF18z1OEBNZzWdTufhEVFLuB1y5s+fD0mSGvzaunUrFEUBADzyyCO44oorMHDgQCxatAiSJOHzzz+v89wPP/wwysvLXV+nTp1q2asjIiIiImoCXcUJAIC9GXvkSJLEzmoBxu01OfPmzcO1117b4DHt27dHRUUFAKBHjx6ux/V6PTp06ICTJ0/W+Ty9Xs+dYomIiIjIt4SA3rkmpxntoyVJYtOBAOP23UhISEBCQkKjxw0cOBB6vR6HDh3CyJEjAQB2ux3Z2dnIyMhwf6RERERERN5QXQy1zQQBqabxgBsURYFarWYlJ8B4LXJGR0djzpw5ePzxx5GWloaMjAw899xzAICrrrrKW5clIiIiInKLqvgwAECOagdoDG49V5ZlqFQqVnICjFfvxnPPPQeNRoNZs2bBbDZjyJAhWLFiBWJjY715WSIiIiKiJlOVHAUAOGIy3X6uLMvQ6/VQqbzWz4uawashR6vVYuHChVi4cKE3L0NERERE1GxSsTPkdHT7ubIss7NaAGLkJCIiIqJWTVVyBEDzKjmKojDkBCCGHCIiIiJq1VyVnFj3KzlsHx2YGHKIiIiIqPWyVUFlygHgfvtoIQQAsOlAAGLIISIiIqLWy1nF0cdAMbjXHEuWZbaPDlCMnURERETUetmqoMR3hlVtdPupiqKwfXSA4h0hIiIiotYrYzgss9fg1IkTiHbzqbIsQ6PRsH10AOIdISIiIiKSJLef4mwfLTXjueRdDDlERERERM3A9tGBiyGHiIiIiKiZuB4nMDHkEBERERE1gxCCISdAMeQQEREREbmJ7aMDG0MOEREREZGbnCGHlZzAxJBDREREROQmRVFYyQlgDDlERERERG6SZRlarZbtowMUQw4RERERkZtkWYZer/f3MKgeDDlERERERM3A9TiBiyGHiIiIiMhNbB8d2BhyiIiIiIjcoCgKVCoVmw4EMIYcIiIiIiI3sH104GPIISIiIiJyAzcCDXwMOUREREREblAUBRqNBioVP0oHKt4ZIiIiIiI3sH104GPIISIiIiJygxACWq3W38OgBjDkEBERERG5ge2jAx9DDhERERFREwkh2D46CDDkEBERERE1kSzLUKlUrOQEOIYcIiIiIqImYvvo4MCQQ0RERETURAw5wYEhh4iIiIioiRRFYfvoIMCQQ0RERETURIqiQKfT+XsY1AiGHCIiIiKiJmL76ODAkENERERE1ARCCEiSxPU4QYAhh4iIiIioCRRFYfvoIMGQQ0RERETUBOysFjwYcoiIiIiImoAhJ3gw5BARERERNYEsy9DpdJAkyd9DoUYw5BARERERNQHbRwcPhhwiIiIioiYQQkCr1fp7GNQEDDlERERERE3A9tHBgyGHiIiIiKgRiqJAkiS2jw4SDDlERERERI2QZRkajYaVnCDBkENERERE1AhZlrkRaBBhyCEiIiIiagTbRwcXhhwiIiIiokbIsszOakGEIYeIiIiIqBFCCO6RE0QYcoiIiIiIGsH20cGFIYeIiIiICIDdbq/zcbaPDj68U0RERETUqmm1WkRGRsJsNqO6uhoajQZ6vd4VahRFgVqtZiUniDDkEBEREVGrptVq0a5dO9hsNpjNZlRWVsJsNqOqqgoajQaSJLF9dJDhnSIiIiKiVk+SJOj1euj1ehiNxvMCj06ng0rFlR7BgiGHiIiIiOgcdQUeCi4MOURERERE9XAGHgourLkREREREVFIYcghIiIiIqKQwpBDREREREQhhSGHiIiIiIhCCkMOERERERGFFK+GnMOHD2PGjBlISEhAdHQ0RowYgZUrV3rzkkRERERE1Mp5NeRMmzYNDocDK1aswLZt29CvXz9Mnz4dZ86c8eZliYiIiIioFfNayCkqKsLRo0fx0EMPoU+fPujcuTOefvppVFdXY9++fd66LBERERERtXJeCznx8fHo3r07PvzwQ1RVVcHhcODtt99GcnIyBg4c6K3LEhERERFRK6fx1oklScKyZcswY8YMREVFQaVSITk5GUuWLEFMTEydz7FarbBara4/m0wmbw2PiIiIiIhClNuVnPnz50OSpAa/tm7dCiEE7rjjDiQlJWHt2rXYvHkzZsyYgenTp+P06dN1nnvBggUwGo2ur7S0tBa/QCIiIiIial0kIYRw5wlFRUUoKipq8Jj27dvjt99+w6RJk1BaWoro6GjX9zp37ozZs2fjoYceOu95dVVy0tLSUF5eXuscRERERETUuphMJhiNxiZlA7enqyUkJCAhIaHR46qrqwEAKlXtYpFKpYKiKHU+R6/XQ6/XuzskIiIiIiIiF681Hhg2bBhiY2Nxww03YNeuXTh8+DD+9re/ISsrC9OmTfPWZYmIiIiIqJXzWshJSEjAkiVLUFlZifHjx2PQoEFYt24dvv32W/Tt29dblyUiIiIiolbO7TU5vuTOvDsiIiIiIgpd7mQDr1VyiIiIiIiI/MFr++R4grPIxP1yiIiIiIhaN2cmaMpEtIAOORUVFQDA/XKIiIiIiAhATUYwGo0NHhPQa3IURUFeXh6ioqIgSZJfx+Lcs+fUqVNcH9TK8N63Xrz3rRPve+vFe9968d4HByEEKioq0LZt2/O2qfmjgK7kqFQqpKam+nsYtURHR/M//laK97714r1vnXjfWy/e+9aL9z7wNVbBcWLjASIiIiIiCikMOUREREREFFIYcppIr9fj8ccfh16v9/dQyMd471sv3vvWife99eK9b71470NPQDceICIiIiIichcrOUREREREFFIYcoiIiIiIKKQw5BARERERUUhhyCEiIiIiopDSqkLOggULMHjwYERFRSEpKQmXXnopDh06VOsYIQTmz5+Ptm3bIiwsDGPHjsW+fftqHWO1WnHnnXciISEBERERuOSSS5CTk1PrmNLSUsyaNQtGoxFGoxGzZs1CWVmZt18i1cGX9/3cY/v16wdJkrBz505vvTRqhC/v/eHDhzFjxgwkJCQgOjoaI0aMwMqVK73+Gqlunrr377zzDsaOHYvo6GhIknTe3+PZ2dmYPXs2MjMzERYWho4dO+Lxxx+HzWbz9kukOvjqvjv9+OOPGDJkCMLCwpCQkIDLL7/cWy+NGuGJe19SUoI777wTXbt2RXh4ONLT03HXXXehvLy81nn4GS84tKqQs3r1asydOxcbN27EsmXL4HA4MGnSJFRVVbmOefbZZ/HCCy/gtddew5YtW5CSkoILL7wQFRUVrmPuuecefP311/j000+xbt06VFZWYvr06ZBl2XXMzJkzsXPnTixZsgRLlizBzp07MWvWLJ++Xqrhy/vu9MADD6Bt27Y+eX1UP1/e+2nTpsHhcGDFihXYtm0b+vXrh+nTp+PMmTM+fc1Uw1P3vrq6GpMnT8bf//73Oq9z8OBBKIqCt99+G/v27cOLL76It956q97jybt8dd8B4Msvv8SsWbNw0003YdeuXfjtt98wc+ZMr74+qp8n7n1eXh7y8vKwcOFC7NmzB++//z6WLFmC2bNn17oWP+MFCdGKFRQUCABi9erVQgghFEURKSkp4umnn3YdY7FYhNFoFG+99ZYQQoiysjKh1WrFp59+6jomNzdXqFQqsWTJEiGEEPv37xcAxMaNG13HbNiwQQAQBw8e9MVLowZ46747/fTTT6Jbt25i3759AoDYsWOH918UNYm37n1hYaEAINasWeM6xmQyCQBi+fLlvnhp1Ijm3PtzrVy5UgAQpaWljV7r2WefFZmZmR4bOzWft+673W4X7dq1E++++65Xx0/N19J77/TZZ58JnU4n7Ha7EIKf8YJJq6rk/JGz/BgXFwcAyMrKwpkzZzBp0iTXMXq9HmPGjMH69esBANu2bYPdbq91TNu2bdGrVy/XMRs2bIDRaMSQIUNcxwwdOhRGo9F1DPmPt+47AOTn5+PWW2/FRx99hPDwcF+8HHKDt+59fHw8unfvjg8//BBVVVVwOBx4++23kZycjIEDB/rq5VEDmnPvW3It53XIv7x137dv347c3FyoVCr0798fbdq0wZQpU86b9kb+46l7X15ejujoaGg0GgD8jBdMWm3IEULgvvvuw8iRI9GrVy8AcE0rSU5OrnVscnKy63tnzpyBTqdDbGxsg8ckJSWdd82kpCROXfEzb953IQRuvPFGzJkzB4MGDfL2SyE3efPeS5KEZcuWYceOHYiKioLBYMCLL76IJUuWICYmxsuvjBrT3HvfHMeOHcOrr76KOXPmNH/A5BHevO/Hjx8HAMyfPx+PPvoofvjhB8TGxmLMmDEoKSnx0Cug5vLUvS8uLsY//vEP3H777a7H+BkveGj8PQB/mTdvHnbv3o1169ad9z1Jkmr9WQhx3mN/9Mdj6jq+Kech7/LmfX/11VdhMpnw8MMPe27A5DHevPdCCNxxxx1ISkrC2rVrERYWhnfffRfTp0/Hli1b0KZNG8+9EHKbp+99ffLy8jB58mRcddVVuOWWW5p1DvIcb953RVEAAI888giuuOIKAMCiRYuQmpqKzz//vNaHYvI9T9x7k8mEadOmoUePHnj88ccbPEdD5yH/aZWVnDvvvBPfffcdVq5cidTUVNfjKSkpAHBeEi8oKHAl/5SUFNhsNpSWljZ4TH5+/nnXLSwsPO83COQ73r7vK1aswMaNG6HX66HRaNCpUycAwKBBg3DDDTd47XVR43xx73/44Qd8+umnGDFiBAYMGIA33ngDYWFh+OCDD7z50qgRLbn37sjLy8O4ceMwbNgwvPPOOy0bNLWYt++78xcXPXr0cD2m1+vRoUMHnDx5siVDpxbyxL2vqKjA5MmTERkZia+//hparbbWefgZLzi0qpAjhMC8efPw1VdfYcWKFcjMzKz1/czMTKSkpGDZsmWux2w2G1avXo3hw4cDAAYOHAitVlvrmNOnT2Pv3r2uY4YNG4by8nJs3rzZdcymTZtQXl7uOoZ8x1f3/ZVXXsGuXbuwc+dO7Ny5Ez/99BMAYPHixfjnP//p7ZdJdfDVva+urgYAqFS1/0pVqVSu3/iSb3ni3jdVbm4uxo4diwEDBmDRokXn/XdAvuOr+z5w4EDo9fpaLYrtdjuys7ORkZHR8hdCbvPUvTeZTJg0aRJ0Oh2+++47GAyGWufhZ7wg4rMWBwHgL3/5izAajWLVqlXi9OnTrq/q6mrXMU8//bQwGo3iq6++Env27BHXXXedaNOmjTCZTK5j5syZI1JTU8Xy5cvF9u3bxfjx40Xfvn2Fw+FwHTN58mTRp08fsWHDBrFhwwbRu3dvMX36dJ++Xqrhy/t+rqysLHZX8zNf3fvCwkIRHx8vLr/8crFz505x6NAh8de//lVotVqxc+dOn79u8ty9P336tNixY4f497//7eqgt2PHDlFcXCyEqOm016lTJzF+/HiRk5NT61rke76670IIcffdd4t27dqJX375RRw8eFDMnj1bJCUliZKSEp++ZqrhiXtvMpnEkCFDRO/evcXRo0drnYef8YJPqwo5AOr8WrRokesYRVHE448/LlJSUoRerxejR48We/bsqXUes9ks5s2bJ+Li4kRYWJiYPn26OHnyZK1jiouLxfXXXy+ioqJEVFSUuP7665vUepQ8z5f3/VwMOf7ny3u/ZcsWMWnSJBEXFyeioqLE0KFDxU8//eSLl0l18NS9f/zxxxs8z6JFi+q9Fvmer+67EELYbDZx//33i6SkJBEVFSUmTpwo9u7d66NXSn/kiXvvbBle11dWVpbrOH7GCw6SEEJ4oiJEREREREQUCDhxmIiIiIiIQgpDDhERERERhRSGHCIiIiIiCikMOUREREREFFIYcoiIiIiIKKQw5BARERERUUhhyCEiIiIiopDCkENERERERCGFIYeIiIiIiEIKQw4REREREYUUhhwiIiIiIgopDDlERERERBRS/h/Mm3qzp70X8AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "plt.figure(figsize=(10,6))\n",
    "\n",
    "plt.plot(consumo[(consumo.index >= \"2000-01-01\")], label=\"Original\")\n",
    "plt.plot(fc_series, label=\"Forecast\")\n",
    "\n",
    "# Fill\n",
    "plt.fill_between(lower_series.index, lower_series, upper_series, color=\"grey\", alpha=0.2)\n",
    "\n",
    "plt.title(\"Original vs Forecast\")\n",
    "plt.legend(loc=\"upper left\", fontsize=8)\n",
    "\n",
    "plt.savefig(\"./figures/forecast_consumo_out_sample.pdf\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Referencias:\n",
    "* https://www.statsmodels.org/stable/tsa.html"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.3"
  },
  "vscode": {
   "interpreter": {
    "hash": "fb4569285eef3a3450cb62085a5b1e0da4bce0af555edc33dcf29baf3acc1368"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}