diff --git a/create_nb.py b/create_nb.py
index c1c17d2..04f8476 100644
--- a/create_nb.py
+++ b/create_nb.py
@@ -127,8 +127,8 @@ estatisticas_trechos = demanda_diaria_completa.groupby('Trecho').agg(
     Dias_Operados=('PAX', lambda x: (x > 0).sum())
 ).reset_index()
 
-# Ordenar pelas rotas de maior média de PAX diário
-estatisticas_trechos = estatisticas_trechos.sort_values(by='Media_PAX_Diario', ascending=False)
+# Ordenar pelas rotas com maior número de dias operados
+estatisticas_trechos = estatisticas_trechos.sort_values(by='Dias_Operados', ascending=False)
 
 # Definir número de trechos alvo
 NUM_TRECHOS = 5
@@ -138,9 +138,9 @@ display(top_trechos)
 
 # Gráfico
 plt.figure(figsize=(10, 6))
-sns.barplot(data=top_trechos, x='Trecho', y='Media_PAX_Diario', hue='Trecho', palette='viridis', legend=False)
-plt.title(f'Top {NUM_TRECHOS} Trechos Mais Relevantes (Média de PAX Diário)')
-plt.ylabel('Média Diária de Passageiros')
+sns.barplot(data=top_trechos, x='Trecho', y='Dias_Operados', hue='Trecho', palette='viridis', legend=False)
+plt.title(f'Top {NUM_TRECHOS} Trechos Mais Relevantes (Por Dias Operados)')
+plt.ylabel('Número de Dias Operados no Ano')
 plt.xlabel('Trecho (Origem - Destino)')
 plt.xticks(rotation=45)
 plt.tight_layout()
diff --git a/modelos.ipynb b/modelos.ipynb
index 7765ed1..a418d86 100644
--- a/modelos.ipynb
+++ b/modelos.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "90710a92",
+   "id": "4c8870e1",
    "metadata": {},
    "source": [
     "# Alocação de Frotas (Fleet Scheduling) - Aeronaves C-97\n",
@@ -21,13 +21,13 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "5e2bab53",
+   "id": "05ab3533",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:11:56.681238Z",
-     "iopub.status.busy": "2026-06-07T23:11:56.680938Z",
-     "iopub.status.idle": "2026-06-07T23:11:57.169135Z",
-     "shell.execute_reply": "2026-06-07T23:11:57.168256Z"
+     "iopub.execute_input": "2026-06-07T23:14:33.557540Z",
+     "iopub.status.busy": "2026-06-07T23:14:33.557102Z",
+     "iopub.status.idle": "2026-06-07T23:14:34.031487Z",
+     "shell.execute_reply": "2026-06-07T23:14:34.030774Z"
     }
    },
    "outputs": [],
@@ -52,7 +52,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "01b6d291",
+   "id": "4fa3e096",
    "metadata": {},
    "source": [
     "## 1. Leitura e Limpeza dos Dados\n",
@@ -62,13 +62,13 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "39011534",
+   "id": "c3db41e8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:11:57.170725Z",
-     "iopub.status.busy": "2026-06-07T23:11:57.170545Z",
-     "iopub.status.idle": "2026-06-07T23:11:57.534804Z",
-     "shell.execute_reply": "2026-06-07T23:11:57.534327Z"
+     "iopub.execute_input": "2026-06-07T23:14:34.033030Z",
+     "iopub.status.busy": "2026-06-07T23:14:34.032852Z",
+     "iopub.status.idle": "2026-06-07T23:14:34.384932Z",
+     "shell.execute_reply": "2026-06-07T23:14:34.384238Z"
     }
    },
    "outputs": [],
@@ -100,7 +100,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7727e9ca",
+   "id": "eb0597db",
    "metadata": {},
    "source": [
     "## 2. Análise dos Esquadrões e Matrículas (Aeronaves)\n",
@@ -110,13 +110,13 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "1e40e4de",
+   "id": "645a0fe0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:11:57.536360Z",
-     "iopub.status.busy": "2026-06-07T23:11:57.536237Z",
-     "iopub.status.idle": "2026-06-07T23:11:57.547915Z",
-     "shell.execute_reply": "2026-06-07T23:11:57.547430Z"
+     "iopub.execute_input": "2026-06-07T23:14:34.386323Z",
+     "iopub.status.busy": "2026-06-07T23:14:34.386204Z",
+     "iopub.status.idle": "2026-06-07T23:14:34.397293Z",
+     "shell.execute_reply": "2026-06-07T23:14:34.396780Z"
     }
    },
    "outputs": [
@@ -175,7 +175,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7cf32f02",
+   "id": "064c1b5d",
    "metadata": {},
    "source": [
     "## 3. Análise Estatística das Demandas Diárias\n",
@@ -186,13 +186,13 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "6ac506ed",
+   "id": "41750d35",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:11:57.549463Z",
-     "iopub.status.busy": "2026-06-07T23:11:57.549345Z",
-     "iopub.status.idle": "2026-06-07T23:11:57.812722Z",
-     "shell.execute_reply": "2026-06-07T23:11:57.812187Z"
+     "iopub.execute_input": "2026-06-07T23:14:34.398764Z",
+     "iopub.status.busy": "2026-06-07T23:14:34.398643Z",
+     "iopub.status.idle": "2026-06-07T23:14:34.668556Z",
+     "shell.execute_reply": "2026-06-07T23:14:34.667962Z"
     }
    },
    "outputs": [
@@ -242,14 +242,6 @@
        "      <td>34</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>72</th>\n",
-       "      <td>SBBR-SBGR</td>\n",
-       "      <td>0.487671</td>\n",
-       "      <td>2.420831</td>\n",
-       "      <td>178.0</td>\n",
-       "      <td>21</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>272</th>\n",
        "      <td>SBGR-SBBR</td>\n",
        "      <td>0.476712</td>\n",
@@ -258,12 +250,20 @@
        "      <td>21</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>237</th>\n",
-       "      <td>SBGL-SBGR</td>\n",
-       "      <td>0.460274</td>\n",
-       "      <td>2.575601</td>\n",
-       "      <td>168.0</td>\n",
-       "      <td>19</td>\n",
+       "      <th>72</th>\n",
+       "      <td>SBBR-SBGR</td>\n",
+       "      <td>0.487671</td>\n",
+       "      <td>2.420831</td>\n",
+       "      <td>178.0</td>\n",
+       "      <td>21</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>253</th>\n",
+       "      <td>SBGL-SBSJ</td>\n",
+       "      <td>0.263014</td>\n",
+       "      <td>1.619550</td>\n",
+       "      <td>96.0</td>\n",
+       "      <td>20</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -273,9 +273,9 @@
        "        Trecho  Media_PAX_Diario  Desvio_Padrao_PAX  Total_PAX  Dias_Operados\n",
        "223  SBGL-SBBR          0.980822           4.097998      358.0             38\n",
        "69   SBBR-SBGL          0.794521           3.483710      290.0             34\n",
-       "72   SBBR-SBGR          0.487671           2.420831      178.0             21\n",
        "272  SBGR-SBBR          0.476712           2.481277      174.0             21\n",
-       "237  SBGL-SBGR          0.460274           2.575601      168.0             19"
+       "72   SBBR-SBGR          0.487671           2.420831      178.0             21\n",
+       "253  SBGL-SBSJ          0.263014           1.619550       96.0             20"
       ]
      },
      "metadata": {},
@@ -283,7 +283,7 @@
     },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA9gAAAJICAYAAACaO0yGAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjksIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvJkbTWQAAAAlwSFlzAAAPYQAAD2EBqD+naQAAeKZJREFUeJzt3QmcjeX///GPfZd9iSyRNVu2lDUltCG+USRFKyIpbRJFi2xZK0pJKlSKRCkqQqHIUpay7/u+nf/jff0e9/mfGTNjhnvMmTOv5+NxHjNnnfvc5zr33J/r+lyfK1UgEAgYAAAAAAC4KKkv7ukAAAAAAIAAGwAAAAAAnzCCDQAAAACADwiwAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAABsAAAAAAB8QYAMAgIsSCATYgwAAEGADSKl69eplpUuXjvPSrl27RN2GJ598Msa/O3PmzBgfr+053zbrfSWmqVOnur+zefNmSwo33HCD+/s9evSI9TH/+9//3GPeeuutBL/2xew/7ZOYPpOrr77arr/+euvcubNt2LAhQa+5cOFC9xr6GY4OHjxoTz31lP3222+X7G/++eefdvPNN9vJkyfddW8/Dxo0KMbHnz171urUqeMeo/YbW5tp0KCB7d69+7x/X+1Kr+VRm1HbSQzR/5afx7vy5ctb7dq1rWfPnrZt27ZznqPvmB43bty4c+47evSo+wz0/H379p1z/5w5c6xMmTI2ceLE836XvUvZsmWtWrVq1qZNG/viiy/OeXxc32l9fvXq1bOdO3cmyjFswYIFdscdd9ipU6fi/RwAKVfapN4AAEgKjz76qLVu3Tp4feTIkbZy5UobPnx48LasWbMm6jasXr3abr311nMC+WLFisX4+BdffNEOHz4cvP7SSy8Fb/fkypXLIl3q1Knthx9+sBMnTliGDBmi3KeT5j/++OOCXlefvR+f+SOPPGL169cPXj927Jj99ddfNnr0aLv//vtdB0r07U6uVq1aZV9++aXdeeedl+Tv6TN/+umnXVCYPn36KG1C+/WJJ5445zmLFy+OM/D68ccf7Z9//rGPP/7Y8uTJc0HHknvvvdfCXd68eaMc306fPu06fAYOHGhLly61r7/+2jJmzOjuO3TokH333XdWqlQp++STT6xDhw6WKlWq4HMzZ85sb7zxhguGdfwZNmxY8L4tW7a4gL5Ro0Z29913x7lNCoq1/7ztUbD+zTffuM9YbeuZZ54JPlbbUaBAgVg/PwXz+fLlO+9+0HdTrxWfx3pq1aplhQoVcv8nHn/88Xg/D0DKRIANIEUqUqSIu4QGpjphr1y58iULFHRy2759+3j/zZIlS0a57gWDl2qbw8U111zjRkznzZtnN910U5T7ZsyY4UbCdHKeUOXKlfNl+9Suon8mOkHPkiWL9enTx3799VcXWCDhFESlTZvWbrzxxhjbhDrJon+O06dPj7NNKMNAwXn+/Pkv6CMJPY6Es5iObxoxTpcunQtov//+e7vlllvc7Qq25bnnnnPHKLVZteFQFStWdJ1JGlX+/PPPrXnz5m6Et1u3bu7Y9PLLL593m3Tcjb5N+k6rM+D99993QXrVqlXjPM4l9PPT37yQjki9V3UYqFMhIcE5gJSHOdgAEIdffvnFnVTpJK9mzZoubTI0ndJLN9SoqU4wddJ52223xZrm7fn777/diI1O/P2mE16dpGq0qkaNGi6N88CBA+6+zz77zJ1E66RUIzl67JkzZ6I8f+7cuW50Xye0em7v3r1dKnAovV89pkKFCu513n333Sj3awRswIABLhDSYzRSP3ny5CiPWbFihTt5176tUqWK3XfffbZs2bLzvr8rrrgieFIdnQJsL0iIPrKtVGa9H6XGKljQ9dD01ugp4goybr/9dveZXnvttS6lf8eOHXahsmfPfs5tW7dudaOu+pwqVark9oeCxPO1nYceesgFlbo89thjtmnTpmDHjfbna6+9FuU5amt6D17Qc/z4cXvzzTddAKN9qdfRKGVoEKp9oc9kypQpLh1Yj1OarDo2RGnr3sitfoZmYmj0s0WLFu6zV3q8/q7Sij36++psqFu3rnvdxo0b29ixY+N830oJf++991xbiq569epu9Dl6m9D7njVrVoxtYv/+/a5t6zNWO1WasVKBQ2l/qh3rPaiNakRVt4WKniIen30bk/j8LVFHQtu2bV17UbtRcLx37167UPqMvJFnjz5zfUfUZooWLWqTJk2KNejUturz1fOVpq/3OXjw4Bjbe3xpOoWyPEL/bvQUcWUA6XFqD9r/mgag7dD+D32OjoNqi/oe6/eYUsTPd5z39tPll1/u2iAAxIUAGwBioXmASuktWLCgO3HUCa9SKe+66y7bs2dPlMcq4GnYsKE7gStevLgbxVGgGhudHHoBr4I+nYjrBO9C05tjCtz093Wiq+2+7LLLbMyYMfbCCy+4E2elK99zzz32zjvvuNs8Sr3We8mdO7cNGTLEBZUKlrp37x7l9RUcKWh5++233Qm20kX1XNEJrt7LV199ZR07dnRplTpx1WiY/q4o1V335cyZ0500azuVSv3AAw+44Px8mjZtGkwT96xfv97t1+jBlF5XAeC6detcOqsCOV3XyKb+bkx+//13F4ArSNI+0j7UKF5cc79D5/wqsPMueq86gVfQpTRTjRqKgiJ1Uih9XJ+B7tdz9bloW2OirAc9R+1PQfQrr7zigmuNquk2BSUKhpVmG1p4TH9fnQkKkEXvTUHUgw8+6ObY6v0pzVbvL/R56gTR/uratauNGDHC0qRJY126dHEdNuqoUIAq+ulNVdDnrqD/yiuvdM9REDRt2jSXCuy9dv/+/V2gruBQr6/vzuuvv+62KTYK6NXBoc8kOm2X3nf0AFsBs9pI9DnSuk2dGRq1VdvW91bpx2qToUG2UtE//fRT953Q90HvWyOrcYnvvo0uPn9L6e7q9FAqtx7z7LPP2qJFi1x7Dg0sE8KrC+CNxGtbly9fbs2aNXPX9VP7Kab56drv+tzUbvX5ant17FPwfzGyZcvmAmJ9D2OilH99T/TdfvXVV913VN/7Dz/80D744IMoj9UxR52eSmNXG7mY47w6grzRfQCIVQAAEHj66acDDRo0CO6JM2fOBK6//vrA/fffH2Xv/Pfff4Hy5csHXnvtNXd9ypQpgVKlSgWGDx8efMzZs2cDd9xxR6BVq1ax7tmXXnrJPa9nz56BX3/9NTBz5sxAixYtAhUrVgysWrUqXp9I27Zt3SW6YcOGuddevHhx8LaDBw+61+7du3eUx3766afusX///be73rx580CzZs3ce/BMnz490KhRo8CuXbuC73fixInB+48ePer2Sf/+/d31jz76yD1myZIlUf7Ws88+G6hQoUJg3759gaVLl7rH/P7771H27euvvx7Ytm1brO9Zn5E+qy1btgRKly4dmDVrVvC+t956K9C6dWv3u15b+0FWrlwZaNOmTWDjxo1RXuuhhx4K3Hzzzee8towZMyZQpUqVwIkTJ4L3//jjj+5vhO6bUJs2bXJ/N6ZL5cqVA4899liUbRg0aJDbH5s3bw7epr/XsGHDQJcuXdx1tQ09Xz/liSeeCFx33XWBQ4cOBZ+j/Vm1atXAq6++GuU5oZ+/2lnjxo2Df0PtWp9rqHHjxrnn7dy5013XvtB1fS6eRYsWudvUXmPaPu2bunXrBh544IEorz1//nz3uB9++MFd135//vnnozxG3yHv/piobVSrVu2c273PWu9Xv//111/B+3r16hXo0aNH8LNR+5VPPvnEXV+2bFnwsdr2e+65x30PRd+J6G1dx4WmTZu622M6dsR330YX37911113BW699dbA6dOng7etX78+ULZs2cCECRNi3XfeNp46dSp4UbuZN29e4IYbbnCXY8eOuccOGDAgUKNGjWDb37p1a6BMmTKBUaNGxfr6H3zwgdtOHT9i+35EF/p9i8njjz/uvh+e0O/0Tz/95D6r0O+BaN+EHrP1nPbt20d5jHcMU5uI73HeM3v2bPfctWvXxus9AkiZGMEGgFhGdXbt2nVOOqpGeTRiq1GjUEoP96gYkFK0Ve04tlElpXgqrVqjP0pJ1MiKUg8zZcoUHOW9WKHp5xqR0bZoJC90dNUb2dMIp+5XerLSZUMLGmm0+Ntvv41SAMobhRVts+7z0si1bzRSq/0USqm4GjnUKP1VV13l5kE+/PDDbvRz9uzZ7jU0ihdTIaPolKqpFPbQEUulh8eUPqz9oLm72qZ///3Xjexr1FQj3l4l6phSjjU6ptfTyLLScpVpoNHY0H0TEz1G6fDKTtBopua+anRNI45Kb/dopFTbprmj3uehYl1Km54/f36Mr61RdKUFawTTe47mu+rz8J6j+7V/NEIv2ufKQvBGr7U9ev/6XDUirNdUKq6XgRC6T/QZhc4x9j4b7ZuYaJ9u3779nHam/antVDsTtXmN1nbq1MkmTJjgRuE16h1aHC46PUafYWyUJaF96bUJvQ+975jahPa95vlqFN7bRk2VUCVxjdpr9NirjB46+q3PJ6ZRUE9C9m2o+Pwt7XN9dzR/XyPh3narTZUoUSK4b2OjFG69X++iz0Aj9spWUaaB2pTmUCvbQMcAHQ/0nVbtAO1bfV4aqY5OtykNX9+LNWvW+JaFo/cY23dN30W1G2VsrF271o2wjxo1ymWFRN/HcU3DSehxvnDhwu5nUq2iACB5oMgZAMRA8zMlpqrCui36PNnoRW900qoTRJ2gepV5Qyl9VpdQmrOo+Zpe+vjF0olx9PejtNXYUi4VVGibte3no6A6lIIBL/1Vr6PgJTpvX3on7R999JE7KVY6s6r6aj8pCHz++eejVIiOTZMmTWzo0KHBgnEKnpXCGRN1XqjjQvtB26GUfL2H2NLRdXKt9HelvOq5+l3PU4fA+ZZvUxDozWtVmqvS4JV2qnRar/K7aFv+++8/F+zEJKYgVs9RR4Iu0XmFmxSUKCVWAb72pYI7zX/WbZ6ffvrJpWkrINZnoSWVVBlaQtOYo3/OXsATU6DlbZ/ofYa+V49XzVvTBRSsK5jr16+fu2ifa+qBtiUmSrWPvj3Rt02fv1dNXO9R7VJzmqPPndd2KrCKbd/rPq9ugT6/UDG17VDx3beh4vO39L3Rflc6tC7Rna8yvV5L3zePvmP6DDR9JLQit9Ki1UEUvWaC996iF+jTFBAFouqIUrq2ppUo7fpiK/LrM4uts037QencOoaobSu9W9+1mPaBt+/9OM577S8+01gApFwE2AAQgxw5crifMc071Ml39BNhL3Dz6HkKqLzXiU4BkgJqjcSEUrCYGEtteQWHtCRPTMuAadt1QqwgJXrBJG2TRuLiO69SJ+wKHGPab+LtO3UwaO62Rg412q/lnrRUkkaPNLJ2PgqmdEKvk37NGVVBppg6BzQnWI/T6LiKHXn7V8vt6HmxUdEkXRTo6v1rbqeKKGk/6GQ+vvQ3lQGgkUxlNnifueaZarRZo9wxiamTQc+57rrrXNGs6FRd26OOCs2517xltTWNIHujvxs3bnSjxRql1GM0AqrPXcGK9qUf7UzvSe8tOi+Y03tTgSxdVC9AnQAK1DRP2Rt5j07t5nzrHGvkePz48a7Qlt635murSnZM+1HfA30fYqKRSq+d6rusjIDoQVlMLnTfxudvKVjXa2kOdkxF2+LqfPD2udfxExvNHdc2a25/KHUMKDNDbTg0wNbIuz431QDQKLD2qzrx9D3Rd+5CqcNBtQm8rIvovM4vdeLoM9bflZYtWybqcT62jhAACEWKOADEQIXKNOITvaCN0lRV6VojzaGUihp6MqqUSaVVxjYSqxNVFYUKTWfUiM2SJUtc6qbfFBQq0NDf0Em2d1FQppEgpTzqBF7plF46q0fFqHTSfL7gxqNgTumoSksPpdFKbYOCU40yKiDWSaw6IrzRSwVoCrjiQ+nA2sd6LY2CxxR0iAol6XUVtHvB9ZEjR9ztsY3EqoCY1nbWZ6nARanDKsgl8d2+UCpiptE1BR5KwxUFoBp5V1sL/UzU0aDRQ+2X6PQcpcTqc/Ier9F4BRtKs/coZVijswpWlRKv9HyPUqDVaaLPVJ0Z3qi0FwDGVYgruujbqE4TdXKoPYW+J31WGuHUiKBSj5X6rAJgooBSBav0+cW1b/U4pZ/HtX2aNqCOBO3DOXPmxNomtB9VJVrbGrqdSrPW1A29L7VPiV44Lfr3I9SF7tv4/C11gGkJMo2Mh26zpluoUKA6Uy6GvovaTu0zHYNCL9o+dWipLXnZAAr+1SGijgqv+r6CbwXbWrZL38kLpWwTfU9UaCwm+u5q2UJ9R73gWtulCvuxfaf9OM577z20EwQAomMEGwBioNRSpZkqtVcnkQpQVIVZ1YY1Chd9BFFzqXVirRM2peaqCrRG0mKjirt6Df1UBWCNjOi1NaKiirZ+04iLAkylVCvVVifNOlnUdQUBXlquqkVrVFHvXdWDNbKjAFwjcqVKlXIBRHxGbDXnWSN5ej2NBirY0eiYRsG8VHidCOsxCkYU3OuEXKmXMVWJjitNXEsb6T3E9jwF9BoZ14iaAmV1FGierN5baHpsKAUUSg1X4KDPXif7Crz0+XjBUEJoH6hCukb71C70WWgkUoGgfuoz12ekUVfNdVW7i4nai6qIq9K0AhkF7UqvVwePqiSH0uifOgrUiRKaOq/AW7cpe0B/V508WrpI6cESupzW+XjBjZ6rfal2pKrcmlevIFX7W6nNet9qb/rbmgqgn2rv6nDRkknqaFBQFtf8ZqV6a+RSQZSeExu9V2Ub6LOKaRTda6Oaw6vvoNL+lWKsOexKvVZ9BG2XlqdSgKdK896Sevq8NM84Nhe6b+P7t/S91PfFOyYp+0MdFZr3rLZxMZTWrb8dW6eEjgc6tql9qpK82qjSyTVSHzoNRh1RmuOuDkR1nMVVU0HZMt7SfHovej1leyjg1ecS24i7vtNqU2oP6lRRxoy2Q/s7tvoAfhznFdjru6zjPADEhgAbAGKhk3AFfjpxUyCoESSlDOuELPo8TI2+6nEa+dAok056QwuBRacgTY/RyJMCEp3o6bU1f9ELWvym5XO03Qp+FSzqBFJLdun9eH9TAZFGj3SCqfesEV/N3dUJdXxpxFfL5WjE0gvoNbKptFMvhVNz1rUNul/zcXVS7I3EJSSAVTCl11VxrNj2mwrQaURVAb7eu0ZTNdKmpcQ0sqzOEI34htL9Sh/WZ+QVNtNouRe4XQgFRgpiFBjoRF7boUwG7Se1H3XQaDQwdD9FpwBW6cYKxJSGrRFRdXyoSJWWugqllF11/OgzDd03Cub0N/UZqzNF7UBBij4zzS9X2m9cAWwofWb6O14KtAKjVq1aue+NPl8F/5oDqw4V7U+vyFvfvn1d0TftX42caiRZ71lp+7HR90mP0yhqXNunNHF1oKjzRd+rmGibtM3aDwqG1bGjkW8FWaEdXAoSNX1Cwbg6wfQdVeCnbY/Jxezb+PwtTS/Qe9Prq/NKHQEK6tUZpL9zMdQRoM9T7Skmav8KLhVkq5NMnWYKpqPPmdf3X/tUHUBqo8quiO1z0GfpLWeo75heV8fP2JbU8qiDSYGwvo9q++ogUYeSXkPHYXXqxHcd7oQc59XGY6vzAACeVColHrwGAEjwSalGP1TF1qswCyBxKCBXNoJXtRq4VNQ5os4XZYtEL2oJAKGYgw0AAJIFZR1oakH0ucpAYlNGRvv27QmuAZwXATYAAEgWNNdX6cdKkY9tTWnAb5pTrgJ8CZkqAyDlIkUcAAAAAAAfMIINAAAAAIAPCLABAAAAAPABATYAAAAAAD5I8etgL1261K0jqrUkAQAAAAAIderUKbc8ZJUqVex8UnyAreCapcABAAAAADFJSLyY4gNsb+S6QoUK8d5pAAAAAICUYfny5fF+LHOwAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAABsAAAAAAB8QYAMAAAAAEGkB9pgxY6xdu3ZxPmbfvn3Wo0cPq169utWoUcNeeuklO3bs2CXbRgAAAAAAwnod7I8++siGDBli1apVi/NxXbt2dQH1+++/bwcPHrTnnnvOjh49aq+99tol21YAAAAAAMIuwN6xY4e9+OKLtnDhQitWrFicj126dKktWrTIZsyYYSVKlHC39e3b1zp27GhPPPGE5c+f/xJtNQAAAAAAYZYi/tdff1m6dOls2rRpVqlSpTgf+9tvv1nevHmDwbUoTTxVqlT2+++/X4KtBQAAAAAgTEewb7jhBneJ72h3wYIFo9yWPn16y5Ejh23btu2CtyEQCLg0cwAAAAAAoseLGtRNFgF2QmjutQLq6DJkyGAnTpy44Nc9deqUrVq16iK3DgAAAAAQiWKKQ5N9gJ0xY0Y7efLkObcruM6cOfMFv65S1EuWLHmRWwcAAAAAiDRr166N92OTVYBdoEAB++6776LcpoB7//79li9fvgt+XQ33X0yADgAAAACITPFNDw+LImcJobWvt2/fbv/991/wNlUVl6pVqybhlgEAAAAAUrqwDrDPnDlju3btsuPHj7vrqjJ+zTXXWPfu3e3PP/+0X3/91Xr37m3NmjVjiS4AAAAAQJIK6wBblcFr167t1r32huaHDx9uhQsXtvbt21u3bt2sbt261qdPn6TeVAAAAABACpcqoJrjKdjy5cvdzwoVKiT1pgAAAAAAknHMGNYj2AAAAAAAJBcE2D46e+asny+HFIp2BAAAACRPyWqZrnCXOk1qG9j/E9u0cVdSbwqSqSuK5LUnn70rqTcDAAAAwAUgwPaZgut1/2z1+2UBAAAAAGGOFHEAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAkRBgnz171oYNG2Z16tSxypUrW6dOnWzTpk2xPn7Pnj3Wo0cPu/baa61mzZrWvXt327FjxyXdZgAAAAAAwi7AHjlypE2cONH69etnkyZNcgF3x44d7eTJkzE+vlu3brZ161Z777333EW/P/bYY5d8uwEAAAAACJsAW0H0uHHjrGvXrla/fn0rU6aMDR482LZv326zZs065/EHDx60RYsWuVHusmXLWrly5ezBBx+05cuX2/79+5PkPQAAAAAAkOQB9urVq+3IkSNWq1at4G3Zs2d3gfPixYvPeXzGjBktS5Ys9sUXX9jhw4fd5csvv7TixYu75wEAAAAAkFTSJtlfNnMj1VKwYMEot+fLly94X6j06dPbq6++ar1797Zq1apZqlSp3GMnTJhgqVMnebY7AAAAACAFS9IA+9ixY8HAOVSGDBnswIED5zw+EAjYqlWrrEqVKm6e9pkzZ1xK+aOPPmoff/yxZc2a9YK2Q6979OhRuxgK9jNlynRRrwGEfjfULgEAAAAkLZ2XK94L+wBbKd/eXGzvdzlx4kSMweo333zjRqt/+OGHYDA9evRoa9CggU2ePNnuu+++C9qOU6dOucD9Ymh7ldoO+GHDhg3BDigAAAAASSv6oHBYBtheavjOnTutSJEiwdt1vXTp0uc8/rfffnPzrUNHqi+77DJ323///XfB25EuXTorWbKkXYz49mgA8aE2HS4j2LRt+CFc2jMAAEBCrV27Nt6PTdIAW1XDFSwvXLgwGGCrUvjKlSutbdu25zy+QIECNn36dDfCrTRyUWr35s2b7fbbb7+oACJz5swX8U4Af4XTdIMzZ89aGmocgDYEAABSqFQJGExNm9TD7AqkBw4caLly5bJChQrZG2+84QLpRo0auTnWe/futWzZsrkU8mbNmtnYsWPdWtiPP/64e40hQ4a4YLtFixZJ+VaAiKXguu/Yz+2/bbuTelOQDBUtmMd6P9A8qTcDAADgkkjSAFu0Bvbp06ft+eeft+PHj1v16tVdEK20bY1MN2zY0AYMGOACaFUMnzhxogvC27dv7yqHq5q4blMQDiBxKLj+e9O5lf0BAAAAhFGAnSZNGuvZs6e7RFe4cGFbs2ZNlNtKlCjhCpsBAAAAABBOWDwaAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAICkDLCPHj0a/P3bb7+19957z/79918/tgkAAAAAgMgPsNevX2833XSTvf322+76kCFDrFu3bvbaa6/ZHXfcYb///ntibCcAAAAAAJEVYA8cONDSpk1rDRs2tJMnT9rEiROtSZMm9ttvv1mdOnVcwA0AAAAAQEqT4ABbgXSPHj2sQoUKtmjRIjt06JDdddddljVrVmvdurWtWLEicbYUAAAAAIBICrBPnTpl2bNnd7/PmzfPMmXKZFWrVnXXz5w540a3AQAAAABIaRIcYJcqVcpmzZplu3btspkzZ1rt2rVdUK3A+6OPPnL3AwAAAACQ0iQ4wO7atatNnjzZ6tatawcOHLBOnTq522+++Wb79ddf7bHHHkuM7QQAAAAAIKwlOJ/7+uuvt6+++sqWL19ulSpVskKFCrnb27dvb9dee62VLl06MbYTAAAAAICwdkETpq+44gp3WbdunS1btsxy5szpAmwAAAAAAFKqCwqwv/76a7fu9e7du4O35cmTx1UXb9asmZ/bBwAAAABAZAbYc+bMsZ49e7p08CeeeMIF1jt37rRp06bZM888Yzly5LD69esnztYCAAAAABApAfaoUaOscePGNnjw4Ci333nnnda9e3cbM2YMATYAAAAAIMVJcBXxv//+25o3bx7jfbp99erVfmwXAAAAAACRHWCroJmW54rJ/v37LX369H5sFwAAAAAAkR1g16pVy4YPH27bt2+Pcvu2bdtsxIgRbhkvAAAAAABSmgTPwVZhM823btSokVWpUsUVOVM18aVLl9pll13mKokDAAAAAJDSJHgEO2/evPb5559bu3bt7NixY7ZixQr3U9d1e6FChRJnSwEAAAAAiKQR7BdeeMFatmzpluoCAAAAAAAXOIKt9a6PHDmS0KcBAAAAABDREhxga971woULE2drAAAAAABIKSnipUuXtrFjx9rMmTOtTJkyljlz5ij3p0qVyvr37+/nNgIAAAAAEHkB9uzZsy1fvnx26tQpW758+Tn3K8AGAAAAACClSXCAPWfOnMTZEgAAAAAAUtIcbAAAAAAAcIEj2A0bNrQRI0a4Odc33HBDnGnguu+7776Lz8sCAAAAAJCyAuwaNWpYlixZgr8zzxoAAAAAgAsIsAcMGBD8/dVXX43PUwAAAAAASFESXOTMs27dOvvll19s586d1q5dO9u0aZNLIc+aNau/WwgAAAAAQCQG2GfPnrXevXvblClTLBAIuHTxJk2a2MiRI23jxo02YcIEK1CgQOJsLQAAAAAAkVJFXIH0V199ZS+//LIbwVaQLT179nTB9+DBgxNjOwEAAAAAiKwAWyPXXbt2tTvvvNNy5MgRvL1s2bLudgXdAAAAAACkNAkOsHfv3u2C6Zjkz5/fDh486Md2AQAAAAAQ2QF20aJFbe7cuTHet2jRInc/AAAAAAApTYKLnLVv394VOTt16pQ1aNDAFTn777//bOHChTZu3Djr1atX4mwpAAAAAACRFGC3atXK9u7da6NGjbKPP/7YFTl74oknLF26dNaxY0dr06ZN4mwpAAAAAACRtg72Qw89ZPfcc48tWbLEDhw4YNmzZ7dKlSpFKXoGAAAAAEBKckEBtmTNmtXq1q3r79YAAAAAAJBSAuwbbrjBzbuOSerUqS1z5syu0Fm7du2sevXqfmwjAAAAAACRV0X8tttus127dtnRo0etRo0a1rRpU6tZs6adOHHCtm7dasWKFbNt27a5YmgLFixInK0GAAAAACC5j2Dv37/fypUrZ2PHjrUsWbIEbz9+/Libm503b14bOnSoPfvsszZy5EirVauW39sMAAAAAEDyH8GeOXOmPfjgg1GCa8mYMaPdd9999tVXX7nrGtleuXKlf1sKAAAAAEAkBdhy5MiRGG8/dOiQnT592v2eNm3aWOdqAwAAAABgKT3Avu6662zQoEG2atWqKLevXr3ahgwZYtdff727Pnv2bCtRooR/WwoAAAAAQCTNwdbc6nvvvddatGhhV1xxheXKlcv27NljmzdvtiuvvNKee+45mzVrlk2cONHNxQYAAAAAICVIcICtImZffvmlTZs2zRYuXGh79+51I9WPPfaYqzCeJk0aF2h/8sknVrFixcTZagAAAAAAknuALenTp7eWLVu6S3SBQMBKlizpx7YBAAAAABDZAfaMGTNs0aJFdvLkSRdQi35qbexly5bZvHnz/N5OAAAAAAAiK8AePny4u2TLls1VDE+XLp2rGK5U8dSpU1urVq0SZ0sBAAAAAIikKuKff/65NWvWzI1ga93rBg0a2Pz5823y5MmWI0cOu+qqqxJnSwEAAAAAiKQAe8eOHa6Ymda4Llu2rC1dutTdfvXVV9vDDz9sn332WWJsJwAAAAAAkRVgZ86c2QXXUrRoUbc81/Hjx911Bdy6DgAAAABASpPgALtChQr2xRdfuN+LFy/uluVasGCBu75u3TpXYRwAAAAAgJQmwUXOlAbeoUMHO3jwoI0ePdpuv/12e/rpp61mzZr2888/24033pg4WwoAAAAAQCQF2NWrV3cFzdasWeOu9+7d21UPX7JkiTVu3Nh69eqVGNsJAAAAAEDkrYNdpkwZd5EMGTJYv379/N4uAAAAAAAiew62aImuZcuWud+3bt3q0sZVWXzEiBF+bx8AAAAAAJEZYKvAWfv27W327NnBFPGFCxe6iuKak/32228nxnYCAAAAABBZAfb7779vzZs3t549e9quXbts/vz51rlzZxs+fLh1797dpkyZkjhbCgAAAABAJAXY69evt2bNmrnf586da4FAwBo2bBhcwmvbtm3+byUAAAAAAJEWYGfPnt0OHz7sfv/pp5/s8ssvt2LFirnrGzdutJw5c/q/lQAAAAAARFoVca13rXTwtWvX2vfff+/WxJZvv/3Whg4darVr106M7QQAAAAAILJGsJ977jk3Sq0gu1atWvbQQw+52wcMGOBGs3v06JEY2wkAAAAAQGSNYOfKlcvGjh17zu0TJ050ATYAAAAAACnRBa2DrTnYO3bscL+fOnXKxo0b5y6LFy/2e/sAAAAAAIjMAPuPP/6wBg0a2IQJE9z1l19+2V5//XWbNm2aWx9b87IT4uzZszZs2DCrU6eOVa5c2Tp16mSbNm2K9fEK6N98883g49u2bWurVq1K6NsAAAAAACBpA+whQ4ZYiRIl7H//+58dO3bMvvzyS7v77rtt0aJF1rJlSxs9enSCXm/kyJEuvbxfv342adIkF3B37NjRTp48GePj+/TpY1OnTrX+/fu7NbeVsq6g/NChQwl9KwAAAAAAJO0I9iOPPGJXXHGF/fLLL3bixAm744473H1Nmza1f/75J96vpSBaqeVdu3a1+vXrW5kyZWzw4MG2fft2mzVr1jmP18i2gupXXnnFjWAr0NcIevr06W3FihUJfSsAAAAAACRdgJ06dWrLkCFDcB1srYtdsWLF4NzsjBkzxvu1Vq9ebUeOHHHVyD16vXLlysU4n1sBfbZs2axu3bpRHj9nzpworwEAAAAAQNhXEb/66qvts88+c4H0zJkz3chzqlSpbM+ePfbOO++4++NLI9VSsGDBKLfny5cveF+oDRs2uJFzjW6//fbbrtCagvFevXq50ewLFQgE7OjRo3YxtA8yZcp0Ua8BeDT9Qu0yqdGuEWltGgAAIKF0DqPz4kQJsHv27OnmSE+fPt3Nf1a6uNx6661u/nRMS3jFdcIlSvEOpRHyAwcOnPN4jZD/999/bt72U0895UavR40a5eaAz5gxw3Lnzm0XQoXTLrZQmoJrBfuAH9SZ5H0/khLtGpHWpgEAAC5E9JjVtwC7fPnyNnv2bFu3bp1dddVVljlz5mDxsWuuucby5s0b79fy0sk1Fzs0tVzzumMaDU6bNq0LsjVP2xux1u/16tWzzz//3AX+FyJdunRWsmRJuxjx7dEA4qN48eJhMdpHu0aktWkAAICEWrt2bbwfm+AAW7JmzWqVKlWKctvNN9/sfq5fv96uvPLKeL2Olxq+c+dOK1KkSPB2XS9duvQ5jy9QoIALskPTwRWYK2188+bNdjFBhNdRAIQDphsg0tCmAQBAcpWQQacEB9hK3daosZbl0sizNyLhzWPW/fFNt1bVcAXrCxcuDAbYBw8etJUrV7r1raOrXr26nT592pYvX24VKlRwtx0/ftxVF7/lllsS+lYAAAAAAEi6KuJaf3ry5MlWtGhRS5MmjavqrWBX85gVHPft2zdBeewKpAcOHGjff/+9qyrevXt3N1LdqFEjO3PmjO3atcsF0VKtWjW77rrr7Omnn7bffvvNDdVrLra2w1sqDAAAAACAZBFga2muLl26uOJid911lwuGhwwZ4iqKK607IfnpojWwW7Zsac8//7y1adPGBcsqlKZ50du2bbPatWu7Amaet956y2rUqGGdO3d2z9Oc7A8++MAVXAMAAAAAIKkkOEVco9RVqlRxv2su9Lhx49zvWbJksfvvv9+GDx9uzzzzTLxfTwG1KpPrEl3hwoVtzZo1UW5TSrkKqukCAAAAAECyHcHOmTOnHTp0yP1erFgxt/71/v373fX8+fO7takBAAAAAEhpEhxg16pVy0aPHm1btmxxhckuu+wyt0SW/PDDDy4ABwAAAAAgpUlwgP3444+7UWsVGlO58oceeshee+01q1mzpr3//vt25513Js6WAgAAAAAQSXOwCxUq5IqO/fvvv+56hw4dLE+ePLZkyRKrWLGiNW/ePDG2EwAAAACAyAqwJWPGjG4Na89tt93mLgAAAAAApFTxThH/9NNPrWnTpla5cmUXTOs6AAAAAABIQIA9ZcoU6927t505c8YaNGjgltZ68cUX3ZrUAAAAAAAgniniH330kTVp0sQGDRrkCptJ//797cMPP7QuXbqwHwEAAAAAKV68RrA3bNhgrVq1CgbX0q5dOzt48KBt2rQpxe9EAAAAAADiFWAfP37csmTJEuW2/Pnzu5+HDx9mLwIAAAAAUrx4BdiBQCDK6LVoHracPXs2xe9EAAAAAADiXUUcAAAAAAD4sA723Llzbf369cHrGrnWqPaPP/5o//zzT5THNmvWLL4vCwAAAABAygqwR4wYEePt0ZfqUtBNgA0AAAAASGniFWB///33ib8lAAAAAABEeoBdqFChxN8SAAAAAACSMYqcAQAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAEjKAFvrYK9evdrmzZtnhw8ftv379/uxPQAAAAAARPY62KG+/PJLe/PNN23nzp2WOnVq++yzz9x62OnSpXO3p0+f3v8tBQAAAAAgkkawZ8yYYU8//bRde+21NnjwYDeSLTfddJPNnTvXRo4cmRjbCQAAAABAZI1gjx492lq3bm19+vSxM2fOBG+/8847be/evfbpp59at27d/N5OAAAAAAAiawR7w4YNbrQ6JpUqVbIdO3b4sV0AAAAAAER2gJ07d25bt25djPfpdt0PAAAAAEBKk+AAu2nTpjZs2DCbOXOmnTx50t2WKlUqW7FihZt/3bhx48TYTgAAAAAAImsOtuZX//333+6nKohLu3bt7OjRo1atWjV7/PHHE2M7AQAAAACIrABbS3C9++679ssvv9iCBQvswIEDli1bNqtRo4bVq1fPjWYDAAAAAJDSXNA62HL99de7CwAAAAAAiGeAPXz48ATtq86dO7NvAQAAAAApygUF2EoDDwQCliZNGsuZM6dLEz916pSlS5fOLrvsMgJsAAAAAECKE68Ae/Xq1cHfNe/6iSeesBdeeMFuvvlmF2TLvHnz7LnnnrNevXol3tYCAAAAABApy3T17dvXunbt6pbr8oJrqVu3rqsgPnjwYL+3EQAAAACAyAuwt23bZoUKFYrxvty5c9uePXv82C4AAAAAACI7wC5Tpox99NFHdubMmSi3nzhxwi3fVbFiRT+3DwAAAACAyFymS/OvH3jgAbvxxhutTp06rsjZ7t27be7cuXbs2DGbMGFC4mwpAAAAAACRFGDXqFHDJk2aZGPGjLE5c+bY/v37XZB93XXX2WOPPWZFixZNnC0FAAAAACCSAmwpX768DRs2zP+tAQAAAAAgpczBBgAAAAAA5yLABgAAAADABwTYAIAU58zZs0m9CUjmaEMAAN/mYAMAkJylSZ3anv1iiq3fvTupNwXJ0JV58lj/Zncm9WYAAFJCgB0IBCxVqlR+vywAAL5ScL16+zb2KgAASNoAe8aMGbZo0SI7efKkC6hFP48ePWrLli2zefPm+beFAAAAAABEYoA9fPhwd8mWLZudPn3a0qVLZ2nTprW9e/da6tSprVWrVomzpQAAAAAARFKRs88//9yaNWvmRrDvu+8+a9Cggc2fP98mT55sOXLksKuuuipxthQAAACxOhOgeB8uDm0ISIIR7B07dthtt93m5lmXLVvWpk+f7m6/+uqr7eGHH7bPPvvM2rZt68OmAQAAIL7SpEptry74xDYe3MlOQ4IVyZ7PetW6iz0HXOoAO3PmzMEiZkWLFrXNmzfb8ePHLWPGjC7g1nUAAABcegqu1+7byq4HgOSSIl6hQgX74osv3O/Fixe3NGnS2IIFC9z1devWWfr06f3fSgAAAAAAIm0EW2ngHTp0sIMHD9ro0aPt9ttvt6efftpq1qxpP//8s914442Js6UAAAAAAERSgF29enVX0GzNmjXueu/evV318CVLlljjxo2tV69eibGdAAAAAABE3jrYZcqUcRfJkCGD9evXz+/tAgAAAAAg8gJszbmuV6+e5cyZMzj/Oi5axgsAAAAALtTZwFlLnSrBJaOAJG1H8Qqwlfb96aefugD7fCngqjBOgA0AAADgYigo+ubvt2zv0S3sSFyQXJkLWZNSXexSileA/f3331vevHmDvwMAAABAYlNwvevIBnY0ko14BdiFChUK/q6iZh07drRatWol5nYBAAAAAJCsJDgZXdXClQYOAAAAAAAuIsCuU6eOTZs2zU6dOpXQpwIAAAAAELESvEyXluVSgP3NN99YiRIlLHPmzFHu1+j2+PHj/dxGAAAAAAAiL8Devn27ValSJXg9EAhEuT/6dQAAAAAAUoIEB9gffvhh4mwJAAAAAADJmK8rbh89etTmzZvn50sCAAAAABCZI9hbtmyxPn362KJFi+zkyZMxPmbVqlV+bBsAAAAAAJE1gq1g2jNgwAC3VFerVq2sbNmyds0119j9999vpUuXdgXOhg8fnpjbCwAAAABA8g2wFUBPmTLF/b548WLr3r27Pf/889aiRQtXVbxnz57u/urVq9v333+f2NsMAAAAAEDyDLDbt29vr7zyim3cuNGOHDniRqvlyiuvtJUrV7rf06RJY3fffbf9+uuvibvFAAAAAAAk1wBbI9Tfffed5c6d2/Lly2e7d+92txctWtQOHDhgu3btctdz5Mhhe/bsSdwtBgAAAAAgOVcRz5Url2XJksXq1atnQ4YMsaVLl1qhQoWsQIECNm7cODt8+LBLE8+fP3/ibjEAAAAAAJGwTFfXrl0te/bsNnToUHdd87HHjx/v5l9/9dVX1qFDh8TYTgAAAAAAImuZrpw5c9pnn31mO3fudNdvv/12u/zyy23ZsmVWsWJFq1GjRmJsJwAAAAAAkRVgezQX21OtWjV3AQAAAAAgpYpXgH3vvffaiy++aCVKlHC/x0VrYStlHAAAAACAlCRec7ADgUCU3+O6nD17NkEboMcPGzbM6tSpY5UrV7ZOnTrZpk2b4vXcadOmuSXDNm/enKC/CQAAAABAkoxgf/jhhzH+7oeRI0faxIkT7dVXX3UVyd944w3r2LGjK5iWPn36WJ+3ZcsW69u3r6/bAgAAAADAJasiLtu2bbM///zTli9fHlwD+0KcPHnSLfGlyuT169e3MmXK2ODBg2379u02a9asOEe9tTZ3+fLlL/hvAwAAAACQJEXOFAy/9957NmnSJBcAhypSpIjdfffd1rZtW0uTJk28//jq1avtyJEjVqtWreBtWgKsXLlytnjxYrv11ltjfN7o0aPt1KlT1rlzZ/v111/j/fcAAAAAAEjSAPvEiRNufeslS5a4edItWrSwPHnyuDnXO3bssPnz59uAAQPsxx9/tLffftvSpUsXrz/uBeoFCxY8p0J59CDeo5FzjXpPnjzZ/W0/6H0cPXr0ol5Dxd0yZcrky/YAx44di1L7IKnQrhFpbVpo1/AL7RqRKFzaNcdqhFO71nPVJn0LsN99911bsWKFjRgxwho2bHjO/d27d3fBdbdu3eyjjz6y++67L95vVKLPtc6QIYMdOHDgnMcrCH7yySfdpVixYr4F2BoNX7Vq1UW9hoJrjbwDftiwYUPw+5GUaNeItDYttGv4hXaNSBQu7ZpjNcKtXcdVHyzBAfbMmTPdCHZMwbVHc6jbtWtnX3/9dbwD7IwZMwbTz73fvRHzmEaDX375ZStevLi1bt3a/KQR95IlS17Ua8S3RwOID7XzcOk9BiKpTQvtGn6hXSMShUu75liNcGrXa9eujfdj4xVgaxmsatWqnfdx1atXdyPY8eWlhu/cudPN4/boupbfim7KlCmu56BKlSru+pkzZ9xPzdV++OGH3eVCv8CZM2e+oOcCiYHpBog0tGlEIto1IhHtGpEo00VO5U1Ih0+8Auzjx49btmzZzvs4FShLyNC7qoZnzZrVFi5cGAywDx48aCtXrnQF06KLXln8jz/+cNXENe+7VKlS8f67AAAAAAD4LV4BtobTU6dO7Xsqh0ajFUgPHDjQcuXKZYUKFXLrYGs97EaNGrkR6r1797rgXinkRYsWjfJ8rxDa5Zdfbjly5EjQ3wYAAAAAIMnXwfaT1sBu2bKlPf/889amTRu3zNfYsWPdvGitt127dm2bMWNGUm8mAAAAAAD+rIP92GOPnbdymoqVJZQCaqV56xJd4cKFbc2aNbE+t2bNmnHeDwAAAABAWAXYzZs3T/wtAQAAAAAg0gPsAQMGJP6WAAAAAACQjCX5HGwAAAAAACIBATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAACAS7kOdqgdO3bY77//HmXd67Nnz9qxY8fst99+s8GDB/uxbQAAAAAARG6APXPmTHvyySft9OnTlipVKndbIBAI/n7llVf6v5UAAAAAAERaivjo0aOtfPnyNnXqVGvRooXdcccdNn36dOvZs6elSZPGnn322cTZUgAAAAAAImkEe8OGDfbmm29auXLlrGbNmjZu3DgrUaKEu+zevdsF4Ndff33ibC0AAAAAAJEygp06dWq77LLL3O9Fixa19evXu/nXUrduXVu7dq3/WwkAAAAAQKQF2JpjvWTJkuDvKnS2evVqd/3gwYNRCp8BAAAAAJBSJDhFvHXr1vbiiy/a0aNHrXv37nbttdfaM888Yy1btrQJEya4+dkAAAAAAKQ0CR7BbtWqlT333HPBkeq+ffvaiRMn7JVXXnGVxXUfAAAAAAApzQWtg33PPfcEfy9SpIh98803tm/fPsuVK5ef2wYAAAAAQGQF2Fu3brW8efNaunTp3O9xPU4uv/xy/7YQAAAAAIBICbAbNmxon3zyiVWsWNFuuOEGS5UqVZyPX7VqlV/bBwAAAABA5ATY/fv3tyuuuCL4+/kCbAAAAAAAUpp4BdjNmzcP/t6iRYvE3B4AAAAAACI3wF68eHGCXrR69eoXuj0AAAAAAERugN2uXbtgWnggEIiSIq7rEnobc7ABAAAAAClNvALsDz74IEql8BdeeMHuvPNOa9Kkiasuvn//fpszZ45NmjTJrYsNAAAAAEBKE68Au0aNGlFGs++77z7r0aNHlMdcc801ljFjRnvvvfesadOm/m8pAAAAAABhLHVCn/Dnn39arVq1YryvSpUq9vfff/uxXQAAAAAARHaAXaBAAfvpp59ivG/mzJlWpEgRP7YLAAAAAIDISxEP1aFDB+vTp4/t3LnTGjRoYDlz5rTdu3e74PrHH3+0QYMGJc6WAgAAAAAQSQF269at7fTp0zZq1CibPn168PaCBQvawIEDXeEzAAAAAABSmgQH2NK2bVt3Wb9+vR04cMCNYhcrVsz/rQMAAAAAIFLnYHsUWG/YsMFWr15t2bNnd8G2tyY2AAAAAAApzQWNYCs9fMyYMXb8+HFLlSqVVaxY0YYMGWL79u2zcePGuYAbAAAAAICUJF4j2L/99lvw9wkTJthbb73lip19+umnwVFrpYxv2rTJhg4dmnhbCwAAAABAcg6w77vvPps6dar7/cMPP7QHH3zQHn/8cStfvnzwMfXq1bNu3brZnDlzEm9rAQAAAABIzgF2+/bt7eWXX7aNGzfa1q1brUaNGjE+7sorr3RLdgEAAAAAkNLEK8Du2bOnfffdd5Y7d263HNfSpUtjfNyKFSvc/QAAAAAApDTxLnKWK1cu97Nly5ZuDnbGjBmtfv367rajR4/at99+6wqfaW42AAAAAAApTYKriHfq1Mk2b95sAwcOdBe599573c/bbrvNHnroIf+3EgAAAACASAuwtSxX37593Uj1r7/+6tbDzpYtm1WvXt1KlSqVOFsJAAAAAEAkroMtxYsXdxcAAAAAABDPAPuZZ55J0Ah3//792bcAAAAAgBQlXgH2559/7gLn/PnzW+rUcRce1+MAAAAAAEhp4hVgN2nSxH788Uc7efKkNW7c2G655RarWrVq4m8dAAAAAACRFGAPHjzYjh07Zj/88IPNmDHDFTjLkyePNW3a1AXbZcuWTfwtBQAAAAAgEoqcZcqUyQXUuhw+fNhmz57tgu3333/fChcubLfeeqsLtil8BgAAAABIiS6oinjWrFmtefPm7rJ//34XbH/zzTc2evRot1TX1KlT/d9SAAAAAADCWNwVy+LhxIkTLn38+PHjdubMGduyZYs/WwYAAAAAQKSPYO/YscNmzpzpLn/88YdlzpzZbrzxRnvooYfs+uuv938rAQAAAACIlAA7NKhetmyZm5PdoEED69ixo9WpU8fSp0+fuFsKAAAAAEByD7DbtGnjRqozZMhg9erVs6FDh7qfug4AAAAAAOIZYC9dutTSpEljJUuWtL1799qECRPcJSapUqWy8ePHs28BAAAAAClKvALs6tWrB38PBAJxPvZ89wMAAAAAkGID7A8//DDxtwQAAAAAgJS8TBcAAAAAACDABgAAAADAF4xgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAAiIcA+e/asDRs2zOrUqWOVK1e2Tp062aZNm2J9/D///GMPPvig1axZ02rVqmVdu3a1rVu3XtJtBgAAAAAg7ALskSNH2sSJE61fv342adIkF3B37NjRTp48ec5j9+3bZx06dLCMGTPahx9+aO+8847t3bvXPf7EiRNJsv0AAAAAACR5gK0gety4cW4Uun79+lamTBkbPHiwbd++3WbNmnXO47/77js7evSovf7661aqVCm7+uqr7Y033rB169bZkiVLkuQ9AAAAAACQ5AH26tWr7ciRIy7V25M9e3YrV66cLV68+JzH63Ea8dYItid16v97CwcPHrxEWw0AAAAAwLnSWhLSSLUULFgwyu358uUL3heqcOHC7hLq7bffdgF39erVE3lrAQAAAAAI0wD72LFj7mf69Omj3J4hQwY7cODAeZ+vedgTJkyw559/3nLlynXB2xEIBFzq+cVIlSqVZcqU6aJeAwj9bqhdJjXaNSKtTQvtGn6hXSMShUu75liNcGrXeq7aZNgH2F6qt+Zih6Z9q2BZXMGq3uDQoUNt1KhR9sgjj1i7du0uajtOnTplq1atuqjX0PYqtR3ww4YNG4IdUEmJdo1Ia9NCu4ZfaNeIROHSrjlWI9zadfRB4bAMsL3U8J07d1qRIkWCt+t66dKlYw2Gn3nmGfv666/dz/vuu++ityNdunRWsmTJi3qN+PZoAPFRvHjxsOk9BiKpTQvtGn6hXSMShUu75liNcGrXa9eujfdjkzTAVtXwrFmz2sKFC4MBtoqVrVy50tq2bRvjc5566imbPXu2vfnmm3bLLbf49gXOnDmzL68F+IHpBog0tGlEIto1IhHtGpEo00VO5U1Ih0+SBtgaZlcgPXDgQDeHulChQm7ZrQIFClijRo3szJkzbp3rbNmyuRTyqVOn2owZM1yQXaNGDdu1a1fwtbzHAAAAAACQ4pbpEq2B3bJlS1eorE2bNpYmTRobO3asS9vetm2b1a5d2wXVorRw0TrYuj304j0GAAAAAICkkKQj2KKAumfPnu4SnZbkWrNmTfD6uHHjLvHWAQAAAACQTEawAQAAAACIBATYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAAAgEgLss2fP2rBhw6xOnTpWuXJl69Spk23atCnWx+/bt8969Ohh1atXtxo1athLL71kx44du6TbDAAAAABA2AXYI0eOtIkTJ1q/fv1s0qRJLuDu2LGjnTx5MsbHd+3a1f777z97//33bejQoTZ37lzr06fPJd9uAAAAAADCJsBWED1u3DgXNNevX9/KlCljgwcPtu3bt9usWbPOefzSpUtt0aJF9tprr1n58uWtVq1a1rdvX/vyyy9tx44dSfIeAAAAAABI8gB79erVduTIERcoe7Jnz27lypWzxYsXn/P43377zfLmzWslSpQI3qY08VSpUtnvv/9+ybYbAAAAAIDo0loS0ki1FCxYMMrt+fLlC94XSqPU0R+bPn16y5Ejh23btu2CtuHUqVMWCATszz//tIulQL/VPdXs9OkzF/1aSJnSpk1jy5cvd20yXKhd33dDRTt1pnxSbwqSoXRpwq9Ne+360QqV7FS5Ckm9KUiG0qVJHbbtuk3u6nY6J+chSLi0qcPveK02fdXZ2+zKjKeTelOQTKU5m9aXdq2YUe0x7ANsrziZguRQGTJksAMHDsT4+OiP9R5/4sSJC9oGb0fFd4edz2U5svjyOkjZ/GqPfsmRLXNSbwKSuXBr05IzM8drRF67zpGBdo3IateZ0mVP6k1ABEh1ke1az08WAXbGjBmDc7G930XBcqZMmWJ8fEzFz/T4zJkvLACoUqXKBT0PAAAAAICwmYPtpXvv3Lkzyu26nj9//nMeX6BAgXMeq4B7//79Lq0cAAAAAIAUGWCranjWrFlt4cKFwdsOHjxoK1eudOtcR6fbNDdby3R5VFVcqlateom2GgAAAACAMEsR13zqtm3b2sCBAy1XrlxWqFAhe+ONN9xIdaNGjezMmTO2d+9ey5Ytm0sPr1Spkl1zzTXWvXt3t/b10aNHrXfv3tasWbMYR7wBAAAAALhUUgWSuFSgguhBgwbZ1KlT7fjx426UWkFz4cKFbfPmzdawYUMbMGCAtWjRwj1+z5499tJLL9lPP/3kips1btzYnnnmGfc7AAAAAAApNsAGAAAAACASJOkcbAAAAAAAIgUBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAiFMgEGAPxQMBNgAASFJnz57lE0DEoV0j0oLqVKlS2ZkzZ5J0e5KDVAG6IhAhpk+fbuvWrbODBw9amzZtrEiRIpYuXbqk3iwAQDQzZ860f//9144dO+aO1wUKFHDBSOrU9Psj+aJdI9J89tln9vPPP7ugukaNGnbvvfe62xU+KthGzAiwERFef/11+/zzzy137ty2detWu+yyy+yNN96watWqcRBAskXAgUg0cOBA++KLLyxDhgy2f/9+S5s2rU2ZMsUKFy7M8RrJFu0akea1116zL7/80ipWrOjOrf/++2/r3LmzuyBuBNhI9vr37++C63feeceuuOIKd4LWoUMHy58/v7377rtJvXlAgi1YsMBKly5tuXLlIuBAxB2vFVyPGDHCihYtaps2bbLnnnvOSpUqZUOGDHEjIoyKILmhXSNSz611Hl2pUiXbs2ePC7jXrFlj7733nuXMmZNjdRzSxnUnEO5eeeUVdwCYMGGClSlTJni70lg2bNiQpNsGXGhw3bNnT2vSpIk9+uij7p8YqViI1ON1njx5XHB96tSpYHo47R3JCe0akdimNXI9fvx4K1eunJ0+fdpliJYvX95WrlxpmTNnJrg+DwJsJFuDBg1yJ2vTpk2zyy+/3B0AlGronaBpTh+Q3NSqVctuueUW+/XXXy1NmjT20EMPnTfIJiBBuBs6dKibyzdjxowox2sF1Xnz5o3yWK+da86fvgNAuKJdI9KMHDnSPvzwQ3esvvLKK+3kyZOWPn16d9+hQ4fc8TtjxowxTmHjXOT/I8BGsvTff//Zt99+61Jo9WUPPSn76KOPbOLEiVa7dm03JypTpkxWqFAhd10ndQTeCHfPPPOMvfrqq66wiMQWZO/atcv981P7BsLVX3/9ZZMnT7arr77asmfP7m7zAmcdq3XMvvnmm92JnQpTapREc/40qq12D4Qj2jUizd69e+27776zq666ymWBKsD2gusPPvjAhg8f7m7r2rWrO/e49tprrVixYu4cRFN+vMeCOdhIpvTFVipt3759XUGzqVOnuttHjRrl5mIr/VBzsPUPcOfOne5ETaMhuv3jjz92QTcQLtavX2/bt293HUAKMDSK7RXvmzdvnusc8oLs0OD6hRdesD/++MN+/PFH94+NuasIVzo5+/rrr11K+IsvvuiOz2PGjHEX1c7QSdrixYtdVXFdpGbNmu6YrnREIBwphVYrmNCuESlWrVrligQfPXrU2rVr5zLqxo4d647VN954o+XLl89Wr17tzlk0H1sd/wqwP/30U5dGjv9DkTMk+yD7pZdecidrDRo0cIUXFJToxEwBh4JqHQRU/XDhwoVulEQ9c0C40KjdDz/8YLt377YjR464+gGa/uD1BKuoiBdka062OpR27Njh2vncuXNdm69QoUJSvw0gXkG2CpwVL17cZR5pVFvtW21eKYcqonPixAlbtmyZ63TieI3kgHaNSKPBKR2bRUHz/PnzbdiwYe7cOno2qTr7dQ6ujlL8fwTYSDZmz57tvswapbv++uvdaLROxhQ4q7ftn3/+caPXderUCc4ZYQ4fwpmmMCj7QpkYCpLVnpVCmyNHDvvzzz9dmqzoH91PP/3kguw777zTxo0bZ998843LxihbtmxSvw0g3lkZKnCmudha7kXt+vbbbw8ep5m/h3Cnzs6NGze66WnqKPKOvwqytdQc7RrJjeq9bN682datW+cC5ZYtW1rWrFndKPWAAQNcllzbtm3tySefdI/36mdwvI4bATaSBZ2Iac615k8fPHjQtmzZ4kbuKleu7IJp9a7pQKDgRCdvElr0DAg3GsnT6LWCbC+Q9igdS51G9957rz377LPB74DmZKv9HzhwwM1dVXVPILllZWjOtY7TRYoUcUt06aSOzlCEOx2T1bGponw6B1Fa7OOPP27XXXddsF0rK0MjebRrJAeDBw92c641/Uwj0VoeVOck3rFaFcNVD0bH5zZt2titt97qbie4Pj8CbCSbtfgUdCigUO+x/tFpXp6CDgXRCrI1kq05qUpnUU+yEGQj3Hj/mPr06ePSvXWCJl41ztGjR7sKno0bN3btWL3Jzz//vLuvX79+Li1cawjrHyGQnLIyli9fHpzOoDau47pSxXXcVpAdU1VaIJyWLdLx+ZprrrHffvvNrduuziMVfPLQrpGcgutPPvnEFS5TJkaWLFlc573OS1Qvo3r16u64rOO2zrlVy0hzsps2bZrUm54s8J8MYU1fao30TZo0yY3yKZhWBUNVo1W1w23bttmKFSvcY5Ua/vLLL7sRvkaNGrnbGMFGuFFwrX9i33//vQs6FFB4QcWsWbPs3XffdfOrFXToolERpYSLrquQCME1wpGO1WrDCkJUDEcnZxqlVjtXB2mrVq1ch6noRK158+auCOXTTz/tfhJcIxy9+eabrm0ra0jBtTpJq1Wr5jqLFi1a5Dr9lUbrtesWLVrQrhHWVBhV5yAKrtWWvRFrBdfvv/++Swe/44473Dm22nnPnj1dcWBlJymbFOdHgI2wpR40nZS1b9/eSpQo4W5TmoooiFYPsv6ZaYSvR48etmnTJjfPr1evXq5gjq4D4UjtOEOGDK6depkWonl9GgFRjQFRkJItWzY3l9WjxwDhRAGHqDhZkyZNXAeoRqM9CrjVSXTPPfe4DiJ1hIqO3zfddJP7PoQ+HggXmsqg2i6aqlOyZMko7V3V7v/99183P1VtWcsriq7r2E27Rrjx2q4GplTwV8dqUZ0M0aoNumiKg9q7ar54QXa3bt3c9Acto4h4CABhas2aNYG2bdu6y5QpU4K3jx49OlC5cuXA1KlTA6tWrQpMnz49ULp06cD48ePd/adOnQocOXIkCbccOL8uXboEWrRoEdi3b9859509e9b9/PHHHwNNmjQJLFmyhF2KsLZ///5A7dq1A+PGjYty+7fffhuoWrVq4Oeff3bXJ0+eHChTpkyUx+m5QDjS8blevXqBVq1aBRYuXBi8fcyYMYGKFSu69jx37tzARx99FChbtmzwPERo1whHZ86ccefVL730krt++vRp93P+/PmBm2++OfDLL7+463/99VegUaNGgdatWweOHj3qbjtx4kQSbnnywgg2wlapUqXc3FOleWvUQ3NPNQqii+Y+Kb1QlcQ1H0S9cBrRVo+xHs+6qQgnWiZOS2up6JNHy11oZFpt+/Dhw+421RIQbz1rpXFpzUmtEQxEUlaGRkU8SksEwpGmN6hWgI7dmt6wYcMGe/vtt1123VtvveVG+OrWrevOQ1RVXOsCe2jXCEeaiqPjtFblEa3gIJp6pmwjr2ifah7pmK5juNLDxUslx/lRYhlhRRUL9+3b54KKggULui+85uepmJmK5uifnP65KTjxCpip8IK+/ArIvQMFEC40x0lLbOmfmVKuNK9Jc1GVLquq4PqHpsBa11XJU9TOFZR89dVXbt6fdzsQrnQSphMyVVFWmrgCE9H8vtDifkojz5Mnj3sMEI60XNGhQ4dcOqzOLXT8VbtWMK0paTrvUDE/1X3xzkNUIEqPK1y4cFJvPnBe6vDUOcaCBQuCSyjqGO5NQdPxWst0KXX8lltuCd7mdf7j/AiwEXbLBezZs8dVnVVRM8170ii15oOo91gj07o/tICZAhStuaoKy0A40dJxqjyrtquOoyVLlrgCIuo4UvvWXKcuXbq49axVeVmjIGrL6ijST/0DVMcREI5ZGWqnuihgFnV8qgiOsjLuvvtut5aqOo806kFWBpKDoUOHuqW4lFWkznstlXjXXXe5Nq5CZ+oIVfCt0WkvY07U7tWJ6hXxA8Jt4ErL3OqizqBrr73Wdf7rHEMDWl6dI4+O19OmTXO1MapWrRq8DfHHMl0IC/qnpEBEqd+qOqt/cNOnT7dHHnkkWBFcvWkayT569Khbj69Zs2buAKERbQUoFF5AOFFwrdRCBdTeetUqLKJludTetbyL9w9r9uzZ9ssvv7iUcZ2wqfCTlsjQEkZAcsnKEB2ztWTi/fffH2NWhqriKyuDjiOE63mIVnFQwKECZ1rGSOcY6hAVBSqqEq5BgN69e7vgg/MQJJeBq0qVKrlifBqp1u1aYk6j2eoQbdCggXuOOvd17uIdqzXIhYQjwEaS0z8z/SObMGFCcPkh9Zqp19hbY1I9yRoNWbt2rVuPUmlZGhVZvHixOwB4lRCBcDBs2DAbM2aMW15O1TePHz8enJuqkzP1GO/fv9+19w4dOgTnWLNuO5JjVobSvnW7F4QoK0O3a/5e9KwMpdZqzVUgnLz66qs2ZcoUGz9+fLBD1DteK/Do1KmT69xXYKIlQpUu7tXH0IAA5yFIjgNXP/zwg+so0jm3llXUOYg6RU+cOGF9+vQhuL4IpIgjSannV0XLVDBEwYa3DJdOxgoVKuRGSTS6J0888YQ1btzYLcOllHEF2+pd5mQN4UT/oH799Vf3z2rLli1uhM8rEKLpDH///bdr60o51D87FT/T7eLVEGCuE5JLVobastq7lizy2q2KP3lZGTpOKytDxc3IykA4eu+991yb1tKgOl7rGK5CULqoY18d+TpWK/BQh6iCEwXjqiOg9a/1neA8BOE2cKV2GTpwpawirWGtNluvXj03cKXOI3UOKbvur7/+cucgtWvXdgX7vKk/uDAE2EhSCqJFJ2hFixYNFghRSpaXvuKNVCutRf/8dLDQKIhuJ4UW4UbBhNZN7dy5s+tA0ui1pjN4FfB1W/369d1jVa1THUeqgK9iUF7KOHOdEI5ZGTpZU1aGgmsvK0PZQ5qPqiBF6YheVoamOehCVgbCmYIMbw1gnXPoHMObV/3uu++6Y/Njjz3mOpD+/PNPVxdGBViVmaTHKxNJxdCA5DxwpTZM4Ul/EWAjSWmpLX35tRyXTtg0Oq0TNR0YRowY4XrZRFUO58+fb/PmzXP/AFm2COFGKVVqy7poGSL9k1OQrZRDpWGpWqdu07QHj+ZEqZPIq7gMhCOyMhCpFFwr3Vudmpp+pvOQbt26BZfiUnaRluESBSaa/rBp0yYXYOs4rwuQXAeu1GF01VVXRSlyRgadPwiwcclp/pJ6fZV6pflMWvZC/9yU9r106VKXVqs5IwqqvdEP/RNT9UNGrBGOVAzEm4uqeXlPPvmkK36jTiIVNVNalkb1vOBa852Ufrho0SI3+uctjQGEI7IyEGkOHjzoqoHrvEK1AlSQT4GFgmwV6VMBvzfffNOly3rnIerY19Qf1gJGJA1cqeMoNMAmg84fBNi4pNSDpi/z8uXLXYDdsWNHa9++vetBVk/yU0895dJnvTkjXqqWiqDpgKEKiEA4UWV7zd3zKiYreFYPsk7KtKycUmuVYqg1r9VTfOutt7oTNHUiffDBBy7llgAb4YisDEQipc/++OOPbmUSL6jWvOr//e9/7jxE81cVWOsSeh6itbAVfGj0GoiUgStd4D8CbFzSQETr6in9SoH1mjVr3NwPz+233+7mQ+mAoDUl9Rh98RWgqOdNgYjmPgHhQssOffXVVy6N0Ktk7637qw6hI0eOuDUnvXRxndip4JlO7NSjzBIYCFdkZSBSz0N0zFYl5QceeMDNsfYK9um4rQ5QBSAvv/yyDRo0yM1R9dbHViE0LQmqUWwgXDBwFZ4IsHFJKLCeNWuWjRo1KriUi+Y1qYdN66OK5qFqJFsjgC+88IIroKNgRf/QdAldOgNIShr1UOqVTs40Jy90mbjDhw+79j5nzhy3jJE6jrTEi4JsPVYnbAqyWdYF4YqsDEQiVf7WdJ3QDlEvXXbXrl1u9E/nJMpGUgepqubrWK1zEhU84zwE4YaBq/BFgI1LYuXKlS7dyguu9Q9r8+bNbhmBqVOnumBFhRi0vEurVq3cPznNH9FP/VMkuEY4UbtURU4Vu1FA7VFbVptW8RBV5dRIh+bxaUREIybKxtCakw899JCVKlUqSd8DEBOyMhCpVq1a5VLBvSW1dB6ybds2t1awLqLliTRV7d5773XH+H79+rnbdR5Svnz5JN1+IBQDV+GNABuJyqtGqH9ioZWSdRL3xRdfuFRZFX7SPzUVidJInwIUzR/R41UBUfNWgXCjkzPNudaIiJZw0Wi2Lmq3/fv3d2v+KshWWqHauub35c6d2wXcQLghKwOR3LbVyan1f3VcVuAsGpFW4KwBANV3UYeoipu9+uqrrjO0RYsWbp6qRruvvPLKpH4bQBQMXIU3AmwkKq8aoYqCaO1qpWGtX7/e/v33X1cRXCnj+semQEWFGLTW9caNG91SXDfeeCOfDsL2hE1TGDSVQWnfSvdWeqGyLx5++OFz5ujpJE3BNRCuyMpAJLdtFS+7+eab3XnIgQMH3Gi26sDkzZvXVVbWeUiePHlcZ6jOS44ePeqKRd12221UVUZYYeAqeSDAxiU5EKhgmUb5vv/+e1e4rFmzZi4YUdChx4juV5ERrQ0MhDO1ac3R07ItCq537NjhludS0K02rNFt0VJcSiNXJobqCegkjyUwEK7IykAkUwEzBdcatVZ2kc5L2rVr5wJr75itgFuFKXXsFo7XCDcMXCUPBNhI9AOBF2RrpO/uu+92QbW3DrD3U+bOneuCFC1tBIQ7pRkq7VCj07qI6gqoloDatCqIq7qnKtYqCGftVIQzsjIQ6dS536NHD+vQoYMbnY7pPESDADoP0drYQDhi4Cp5IMBGolNwreW3NHrnpclqvrXmNOmfnOZnKwDRGpNaGkaptkA4/2MTby3JgwcPukJnOknTFAcvA0PXlYaoOdia8gCEM7IyEOmUdaSOUZ13yN9//+2O15qupiwknYeocJR+qno4EI4YuEoeCLBxSf6pKbjW/GtdND91+vTp7qJ/bLpPAcqECROsTJkyfCIIGyrCp6W2ihQp4jqHlAKuIFvBs4JrjVir2uyzzz7rlp1r27at6yTSyZkK4yjg1nOB5ICsDER6cK1AWuccyiiaNGlScNqagpb9+/e7Aqys8IBwx8BV+EsV8CbAAon4T23Lli1u/lPnzp3t/vvvd4XOVH1Z86EUVF977bVWsGBBPgOEDS0Zp2W3dEKmyuCqGaAq916Ghdq01ku97rrr7JVXXgmObHvphqGj3UAkZWWMHDmSpRMRdubPn+86RNWemzZtGrzda9dbt251y3RpmURNWfvpp59cZXFl0anI2fXXX2+FChVK0vcAJOTcOnTgavjw4ecMXA0aNCi4LB0uLQJs+CJ0DlN0CkQ0slevXj1XddlbIgMIV1pmS6mCTz/9tCuGo5TBX375xd555x23lrsqzKqjqHTp0tanT59ggOL1V4amcAHJJStDx+boWRk//PBDlKyMO+64g6wMhJ3Bgwe74mUnTpywQ4cOuUD69ddfd+1bVGxSBc0aNmzoOo0UcAPJEQNXyQMBNi7KihUr3ElXbEG2TtyefPJJd3LWr1+/KIFITL8D4RBca+Q6dMqC2miVKlVcBoYqz8qff/7plp+j7SK5ICsDkXrM1vJaGq1TtoWC6V69elnXrl1d1pGO37qukWwt08UxG8kBA1fJG114uGCau/TSSy+5f2DqGY5ejVP0j0z//KJX5Az9B8c/O4QLjXh8+eWXbsRa8/B0Qqb2rJ8KprUsl0cj2d7SLrRhJMesDM1B1Yiel5WhCsvKNIqelUH7RnLqEFUBVaXFKiVc1H5ffPFF19FPW0ZyGbiK6ZzaOyarM0lTGtSuGbgKTwTYuGBajqh69eouLUsHAM1HjX5AUCoLy10gOZg1a5aNGzfOBgwY4IJr/RPz0gh1Avf777+7Nr58+XI3D7t48eKxTosAwj0IqVq1qsvKWLRokQuwtTyi0sKjZ2XQGYpw7hBVp9Enn3xiJUqUCK5WouOzltrSXFSPt/ynjuu6cOxGOGLgKnIQYOOCaf6pioVoXqpGQiR6kO3Nt1bRHP3jY+kLhCt1FinoGD16tBvhq1atmrtd7XvIkCGu7SrFdt26de52BdiXXXaZm68aWlAHCCdkZSASLV682MaPH2+33367C67FO99QdsZ3331nV111lQvAFWyrUKU6l9Tpz/xrhCsGriIHc7CRILt373YXUbXNbNmyuYBDQYmK57Ru3doF2aF27tzpipupV/mNN96g5xhhSx1BjzzyiKsqq/WrZ86caWPHjrXevXu7Ub6TJ0+69q+2/ttvv9nGjRvdnD6dyAHhmJWheajKymjevHmUdG91ivbt29elGupY7mVlAMmB0r8//vhj++qrr+y2225z0xtkzJgxrpqyOj+1MokyjkQdpDlz5nSrPoTWgwHCjdZnV8d+9HPq6OniDFyFNwJsxJu+8AsWLLClS5e6nmLN1fMKhoQG2XfddZerGi7bt2+3N9980/Umq7dZQQoQLtRu9U9LHUVaC9X7p6XMDJ2YqQKtqtPWqVMnxudr3qqXegiEG1ULV2E+dQppKbnoWRlq32r3ZGUguQbZSg/X9AdlEqk9K7hW1oamOuTKlcsVPFuzZo1r4+oUVSDuTZMAwgEDV5GJABvx8tprr7lUq6eeesqKFi3qRkI02qG0Ky3rorSWDRs2uPVRvV63Zs2auSJoGkVRTzNr8SGcDB061LVNBclaL7Jnz572v//9z92n9dm1lIvSEN97771gpXxvBDCu6p5AOCErA5EciOzYscOlhKsWjO5TZkblypWD87GBcMbAVeQiwMZ5KTjWQWDYsGHBQMPz7rvvusJQSqFt3LhxlCBb/+D0z09rqJYrV449jbChlFkt66IMDKUOemtc60TNy7JQYPLggw+6KQ7KwtBJG2mFCHdkZSClBSKhQbYy6Lp06RJlvWAPFfERThi4imwE2IiT5pxqJK98+fJ2//33R/kH9fbbb7t5qhrR/ueff9y8piZNmrgTPP3jW7VqlUsbJx0L4USpssrGUOeQ0gi9dq4UwzvuuMPNVVURHF00sq11r/fu3euep0JoQLgiKwMpLRDZsmWLG83etWuXq5KvIPvOO++07t27u+eSbYRwxMBVChAA4rBp06ZA5cqVA7Nnz45y+6effhooW7ZsYP78+e56r169Atdcc01g8eLF7vqGDRsC27dvZ98irIwfPz5QunTpwMaNG931Y8eOBe9r3rx5oH379oHGjRsHunfvHpg+fbq7/dChQ4Fbb701cNtttwWOHz+eZNsOxKV///6BGjVqBObNm+eOw0OGDAmUL18+8McffwQfc+DAgcBdd90VaNCgQWDJkiWBs2fPslMR1iZOnOja6/Lly8+575133gnUqlUr8M0337jrO3fuDAwaNChQv379wCuvvJIEWwuc34kTJwJPPPFEYOzYse566HF4zJgxrk23bt06ULVq1cCMGTPc7WvXrg08/PDDgXr16gVWrVrFbk4GmESIOCnFKkuWLJY9e3Z3XWnfp0+fdsVDlPpdq1Ytd/sTTzxhR44csRUrVrjrxYoVs/z587N3ETY011rVwdV2lR4uKorjpR8qC0N1AurXr29//fWXy9BQNoaqKyv9cNSoUazpjrCk7Aq1aWVlqCCfipmpGr6m9KgtHz9+3B23dRzXY7Rs0dNPP+2KPgHhSplFaqMqmqq2rJFrj47Pmp6mEe3nn3/erfiQN29eu/vuu+2mm26yn3/+2WUeAeFG087mzJljRYoUcde9rNDPPvvMFZ/UlDSNcKsdq23rO6Cl6HTMVlE/skKTBwJsRBH6D0wUJKuYk5bCEBUNUersDTfcYFWqVAk+Tv/MVOhMtwPh2KZV7bt9+/buBOzTTz91S8aJTtIUYI8YMcKlIOqf2LPPPuvqCKiAn6iYjtIQgXDzwQcf2IcffmiTJ092Ux4UTEv69OldgPLtt9+6aQ9q2zNmzHAdRgqyM2TI4Kb1nDhxIqnfAnDRgchzzz3nAhGds2haj9LF1ZkKhBsGrlIGAmxEcejQIXfCpRMzUTCtk7OffvrJvvzyy+DjNJIdSv/YNPrHPzSEY5tW0KF2rSWJND9P1cLVaaRq9xoJ0dIudevWdfP1RMG0sjDU/oFwRVYGItmFBiLK0OBcBOGCgauUibNHBGlUQyPRqp6sXmCNbuTJk8cVLvvhhx9cQTP9c1OAotER0T81jf7Nnj3bpdFqdAQIxzatky616YIFCwaX49JItgqX1ahRI8rzVFBHmRulSpVKoi0HYucVm/SyMhSEKHVQHUlabi40K0Mp43rstdde69Z3V1aG0g2VlaELEC6iV/kOzaDTMdpbdkuZcqGPI4MO4d7Jr4whtVmdO3sDVxq00kXFVb0OJO/cWhi4St4IsBFctkhBhSpvqirn/Pnz7YEHHnBpVprv8eKLL7rHKK32+++/d6N9WpJL604uW7bMBd8lS5ZkbyKs27RSBzXyoRO30CBbVWqVGq4lXQYPHuzaswIWzekDwvGETSdiOmHzsjIUnCh19vfff7d///3XZWUoKPGWKiIrA+GOQASRhoGrlIsAG8ECOe+9915wnetrrrnGBSgKoDXKUbVqVTffae7cufb555+7oESjJ1qLslu3bnbFFVewJ5Fs2rQyLRRk33PPPe4+BdMqeKY1sfUcZWNoygMQbsjKQCQiEEGkYeAqZWMd7BROoxyqjqwKnAqSlWKoQEOp302bNrXbb7/dNm3a5Cora9Ra85o0IqL5rAqwgeTYppUmqzatDiKlIKpI1JgxY9wUCHUeeUE5EO4nbKqXoawMdRrt2LHDtV9dbr31VpeVIcrKUMeROpLoOEJyadfKoFMHv7Iy9Bgdt9VRGj2D7q233rJy5col9dsA4uzk1wCV2rHOT7SOu/z333/BgStv2o/OSxo3bszAVTLHCHYKpXRC/bOaOnWq+8e0Z88e92X2li1SwKHbVq1a5eav9urVy83f02i10g294Dr6nCkgubRpBR8PPvigK5DTokULN7+vUaNGrrgZEG7IykAkIoMOkdjJryy46J38Wj7x2LFj7hwldODq3nvvddl0DFxFFkawU7iFCxfawIEDXS9xp06dXFVOFcfRaJ5u1xw+BdP6J6hlYDT/muqciKQ2/d1331nu3LmDc1WBcENWBiIRGXSIxE5+FZ7UOYWWjqtcuXLw/tGjR7s2r4KT6uT/888/gwNXoQNVDFxFBpbpSoEWLVrkUgU1oqcq4X369HFfdl3X+r9jx461YcOGud41zUkVpRXqsdGX5wKSe5tWWrgQXCPc6ERLIx2hWRkSU1aGUmuVlaEK4lrWSFkZnTt3dmtfM+UBybVdb9261WXQjR8/3j0vegYdEC4UJGvEWmngonOOBQsWuN/Vya86Awqwdbum8bRr184++OAD27dv3zmvg+SPEewURnPxNGKnL/DOnTvdMkSa56Q5IEOHDrV//vnHunTp4lJnResCa47qyy+/bGvWrHFzR1iKC+GENo1IR1YGIhEZdIikTn7VBVDtgOuuu86lhWv1HS0PmiNHDpszZ44NGjTI3eeNUKuDSefUOgdX0VVEFuZgp7BARKN8CqTVa7x///7gaJ6KKqhXWD1vWntP99euXdsF10OGDLEpU6bYpEmTCK4RVmjTSCknbMrK0AmbRve0LrBO2DQS4p2wCVkZiOR2TQYdkkMn/7fffuuCZg1W6Xz7p59+cr+rTYsXYK9cudIts5glS5akfgtIBATYKcSKFSvcl1xf9po1a7rbNEfV60VWikrRokXdnFWtAayLvvT6Z6iUQxVsKF26dBK/C+D/o00jUnHChkhEu0akoZMfsSHATiG0fMvhw4etZMmSwdRvjVRraQBdPB07dnQFGjTf6dFHH3VLGym4Zg4fwg1tGpGIEzZEIto1Ig2d/IgLAXYKkT59esuQIYNbM1Ij2Cq0oOI3hw4dsg4dOriqhpoz8vjjj9vHH39sPXv2dKnhSt266qqrknrzgXPQphFpOGFDJKJdIxLRyY+4EGCnECpmpuqbqqh84MAB93uFChWCAXTatP/XFLSkwOLFi12Rs7fffjtYrRMIN7RpRBpO2BCJaNeIRHTyIy4E2CmEKhRq1FrzsDXfukqVKi7tW/OwvWWKdu3aZenSpbNixYq5614BNCAc0aYRaThhQySiXSMS0cmPuBBgpyCFCxe2Nm3anHO7N3qt9fhUAbFixYruOmvxIdzRphFJOGFDJKJdIxLRyY+4EGCnUBrJXrdunQumlTKu69OmTXNBtpYNAJIb2jSSO07YEIlo14hUdPIjNgTYKZRGrd966y23Hl/u3LntiiuucNXC1dMMJEe0aUQCTtgQiWjXiHR08iNUqoAiLKRImzdvtt27d1uOHDlckO2tiw0kV7RppJQTtnLlyiX15gEXhHaNSLRgwQLr3LlzlIGrXr16MXCVQhFgAwAQhjhhQySiXSNS0ckPDwE2AABhihM2RCLaNYBIRoANAAAAAIAPUvvxIgAAAAAApHQE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAEAMAoEA+wUAkCAE2ACAsNOrVy8rXbp0nJd27dol6jYsXLjQ/R39TEwPP/ywffbZZ1Fu27x5s7344ovWsGFDq1ChgtWuXds97ueff47Xa+r52vapU6daJIj+2ZcrV85q1qxp999/v/3www+J8jf/+ecfa9OmzTnb8dZbb/n+t5566il75513fH9dAMCllzYJ/iYAAHF69NFHrXXr1sHrI0eOtJUrV9rw4cODt2XNmjXZ70UFwDt27LA777wzeNuCBQvsscceswIFCljHjh2tRIkStnfvXvv666/tgQcesPbt29uzzz4b5+vmy5fPPvnkEytSpIhFipYtW1qrVq3c76dOnbJdu3bZlClTXMfDc889Z/fee6+vf2/mzJm2dOnSKLdpn+pz8VuPHj3stttusxtuuMF93gCA5IsAGwAQdhQYhgaHuXLlsvTp01vlypUtUhw/ftwGDhzoRqpTp/6/hDIF2127drVrrrnGRowYYRkyZAg+vnHjxvb+++/bgAED7KqrrgoGmzGJtH0lCmyjv6emTZtaly5d7PXXX3fBaeHChRN1GxJrn+bPn99uvfVWe+ONN2z06NGJ8jcAAJcGKeIAgGQ9Aqx0YaVYX3/99VajRg1bu3atu++7776zFi1auBRr3ffyyy/b0aNHozx/2bJlLs1YAe21115rTzzxhAtyQ61fv96NHFeqVMm9joLi06dPB+8/ceKEC4YVAOtvNWrUyN5++207e/ZsnNuu0Vc9t0GDBsHbFEBrG7WtocG157777nNB3qhRo4Lzg5Uq/+STT7rAXPd16NAhxhRxjcbec8897jH169e38ePHu9dTOn7oe1GwWq9ePbv66qvdqOqMGTOibIMCWWUS9O/f36VpV6lSxY3AHjlyxL3vunXrWtWqVV3gu2/fPkts3bt3dyPakydPTtD7WLFihcsG0LbqPWhfqD2I0sC9bInQtPDQ370pBMo4UBvy2oeC5DNnziS4fWgbf/zxR/v7778TcW8BABIbATYAIFlTMDNu3Dh75ZVX7JlnnnEptl999ZVLs77yyitdcNO5c2ebNm2aSz33AlOlnLdt2zYYjL300ksu6FIwHRpAa8RYQZhGFps0aeLmyk6aNMndp9dSivK7777rRpT1GAVSQ4YMcSPTcdH2KNDVaLNHc6zLli0bZxqytmHLli22atWq4G3ffPONZcmSxQXeSiuPbt26dS6AlEGDBrngV0He77//HnyM3ov2md6bgnS9lgJPBbBffPFFlNfT/t62bZsNHjzYHnnkEZe+rjR3bX+/fv1cR8X3339vw4YNs8Smz/jyyy8Pvpf4vI/Dhw+7/ZQzZ04XMOt9HDt2zH32hw4dcp+lUtK9tPC4sgXUueG1D41Cqy14c+oT0j60jRrJ1r4EACRfpIgDAJI9BTEKVr2gRqPMderUcT89xYoVc0Hm3Llz3WMV7OTIkcMFi95oseYuazRWBa48mturwFw0yq2R8V9//dUF5/PmzbP58+e7oPWWW25xj9EoZsaMGW3o0KHuuUrnjk4B3vLly12wHEojzxoBjkvRokXdTwXZGr2XdOnSuQ4CL1jX64QaM2aMZcuWzQV6mTJlCgamofPc9T5++uknF2wq9Vq0DxV4aj8qeEybNm1w/rsep+vXXXedff75527kX4Gl/o7otZYsWWKXQp48eWz37t3xfh/KctDouj4fZS94+0PBtEbi1cHhdXKcLy1cgbMCeqlVq5ZrHxqJ1r5NaPvQaLtGxAEAyRcj2ACAZE+jvqEp3du3b3epzBqJ9i7Vq1d3geEvv/ziHqcRTwWzoanYGkWcM2dOlNerVq1a8PdUqVJZoUKF7ODBg+76okWLXJCpUclQt99+e/D+mGj0VyPv0ecMq3PAC2JjkyZNmuBjPQoOQ0fCo1OHgN6rF1x771XvxaPATu9PadWh+037UQXFQjsdKlasGGU7FeAWL148GFyLOi80Ghwbvf/Qv3O+lPq4aF9o2+P7PhTUal6/OmZ69+5ts2fPdu+hZ8+eCS5ipv0YSs/3piIktH3o84jeOQIASF4YwQYAJHuZM2cO/r5//373UyO6ukS3c+fO4ONy58593tcODUpFBcm84PbAgQMuzdgLej158+Z1P2MLML3bQ7fbC7A0Mh2XTZs2uZ9Ki/YoPTwuqkIe03tVUOnR/tD78kZ0Y9pvXsdDTBXco7+X87npppuivNfmzZvbq6++ahdCHSqlSpVK0Pv46KOPXPq40us1cq1R5TvuuMOef/75ODsrotPz/GofamtxdUoAAMIfATYAIKJkz549uLawip5Fd9lll7mfGm1V4BmdUshDR7DjotdSqrFGY0ODKC+IV3AVE+92byTco1FWpawr8AwdXY6+fFTBggWD6eHxoVFVL4U61J49e9zot7c/FCR/8MEHcaam+0XB7cmTJ4PXY9tX56N0b41Mq4BbQt6H3rdXkOzPP/+0L7/80j7++GNXvT6meewXIqHtQ+3hQvcDACA8kCIOAIgoCpw0WqtUW1Vt9i4qIPXmm2+64mZe6rfSxUODPN334IMP2l9//RWvv6UAXunHCnqjFzATFb+KibZFAZdGXkOpIrhGh1WsTct4RTdx4kSXVvzQQw8Fl/aKD6XHa16yCrqFvtfQdGS9F6U2a/Q1dL+pqrUKxYUWfvODKnCH/p0LXWJLhdQ0iqwR8Pi+D31emk+vwFyfg9K8+/Tp4zpntm7d6l4nIfvXr/ah9hBbxwoAIHlgBBsAEFEUMKlitObW6nctg6WRwZEjR7pCXOXLl3ePU+Gyu+66ywWrKjalgFbVnTW/WIWotKzV+Whes5aqUlqxXrtMmTIuAFalcQV8JUuWjPF5GmFVCrPmgXvVvb0iayp+pSW3tMSYtktV0ZVqrFTm6dOnu5HaNm3aJGifaK6xlqnSyKyWlNL+0N9REOnNXdacZQXi2i+66O9qZFcBrIqEac5yUlLw6S2jpaBV+1vF1VS5vG/fvsG50/F5H9r3mvOt4mTqUFGKvfav0rO1jFZoJoSqemsJriuuuCLB25yQ9qEOAbU5Fc8DACRfBNgAgIijys4KmlQ1W/NrvYBWVaS9QEkp1h9++KEb1e7WrZsbOVZwpmWX4jsHV8GpKnQreNMa1ko510islqnSElFxufnmm90SURpVDi20ppFVLSel13vvvfdcQTQFexqFVWCmIDGhlBY9duxYtxyZgneN8KtjQWna3vxtBdtaukuBt96T0sc10q734VXJTkpa59pb61rbqiJqCny1j1S92xOf96GODLUNPea5555zFcZV+Eyfh/a/KNBW2rjWCdeSXRrhTqiEtA9VlVc6efSCaACA5CVVILQMKQAAuCQU1N14442ucnWzZs0S9W+psraW8gqtiK5RbC2xpbnqGilH0nr22WddgTZlWgAAki/mYAMAkARUMbpLly5uZFlFsBKT5pQrNVyjqIsXL3bLUiltXAXBtC40kpayFGbNmmWPP/44HwUAJHOMYAMAkIQ6depkDRs2tNatWyfa39B849GjR7uUZwVzSplXAa4ePXr4Xh0cCadpCUpRV9o+ACB5I8AGAAAAAMAHpIgDAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAGAX7/8B6VE+XNj00TIAAAAASUVORK5CYII=",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA9gAAAJICAYAAACaO0yGAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjksIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvJkbTWQAAAAlwSFlzAAAPYQAAD2EBqD+naQAAehBJREFUeJzt3QmczdX/x/GPfSdbpCS7iCKKihRRKqFfiRSlUmTLrk2ypcgSIcqetNMqWUtZKkt2smeXfY35P97n//jO484YzPKd5s53Xs/HYx4zc++de8/93nPvfD/nfM7npIqIiIgwAAAAAACQIKkT9ucAAAAAAIAAGwAAAAAAnzCDDQAAAACADwiwAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAABsAAAAAAB8QYAMAAF9FRERwRAEAKRIBNgCYWdeuXa1kyZIX/XrssccS9Vh17Ngxxsf97rvvYry92nOpNut5JabPPvvMPc727dstKdx5553u8Tt06HDB2zz88MPuNkOHDo3zfSfk+OmYxPSaXHfddXbrrbfa888/b5s2bYrTfS5cuNDdh76Ho8OHD1vnzp1tyZIl/9ljLl++3GrXrm2nT592v8d0zMuVK2f33nuvvffee3bu3LlEfS+EfpUtW9b1o5dfftl27doV5fbqj7rNf0X98dVXX7UaNWq4dt1222327LPP2k8//WTJSULflzH55JNP7JlnnvH1PgGkXGmTugEAEA5atmxpjzzySOTvw4cPt1WrVtk777wTeVnWrFkTtQ1r1qyx++6777xA/pprronx9jpZPnr0aOTvr732WuTlnly5clnQpU6d2mbPnm2nTp2yDBkynBdULFu2LF73q9fej9f8ueees+rVq0f+fuLECVu5cqWNGDHCnnzySTeAEr3dydXq1avtyy+/tAcffPA/eTy95l26dLFOnTpZ+vTpIy//3//+Zw899FCUYz5jxgx766233CDAxQZkEkr9Jm/evJGPu379ehs1apTNnDnTPvroI7v66qvddWpf1apV7b/wyy+/WKtWrSx//vz21FNPWdGiRe3AgQP21VdfWfPmza1p06bWvXt3S6nUXydNmuQCbfUdAEgIAmwAMHMnvd6JrxeY6oT9hhtu+M8CBc1m6kQ3to9ZrFixKL97weB/1eZwUaFCBTdjOm/ePLvrrruiXPfNN9/Ytdde6wK/uCpdurQv7VO/iv6aVKlSxbJkyWI9evSwX3/91W6//XZfHiulmTx5sqVNm9Zq1qwZ5XIFkjEd87/++ssFUm3atLF06dIlSpvU36666qooj6tZ1wYNGrjBrw8++CCyjfpKbLt373bPV++TYcOGRRnMufvuu23s2LHWt29fK168eJRBiZQkVapU1qJFC+vZs6cb5MyYMWNSNwlAMkaKOADEwc8//2yNGze2G2+80W6++WY3E7Zz587z0kQ1a1q/fn2Xmnr//fdfMM3bs27dOvv333/dybnflIqqwFMzazfddJNLDT106JC77uOPP3aps0pb1iyrbnv27Nkofz937lw3u6+ARX/7yiuvuFnAUHq+uo1ST3U/o0ePjnL9kSNH3Em8AiHdRiexmi0K9eeff7oBBh3b8uXLW7NmzWzp0qWXfH4FCxZ07Y/pGCvA1vOLTjPbSmXW8ylTpowLgvT7P//8c8FUVM321a1b172mlStXdin9Cl7iK3v27Odd9vfff9sLL7zgXqfrr7/eHQ9lUlyq7yg4UAClL81Ubtu2LXLgRsfzjTfeiPI36mt6Dr169XK/nzx50gYMGGC1atVyx1L388QTT0QZmNCx0Gvy6aefupRs3e6BBx5wAxuitPXHH3/c/azvoZkYmr1VgKnXXunxetzjx49HXq/H12BDtWrV3P0q8BszZsxFn7dSwhWsqi/Flu772LFjkf1fx0dBpx5PbdPz12xzaBq5nodeawWpeg/ouMSVAu6GDRvaggULbOvWrTGmiOt9p8fW81Ef02PpPaUBmIQcJwXQOtY65jFlSug11WO9++67kWvn9Zz1eivL4pZbbnF9SFk+O3bsiHXfC13SMGXKFLvjjjvcbfQZ6n32qE/osfV81Ze+/fbb87J6dLz1eaC/nzZt2nntj81rqGOudHh9Zut9pddCn2uhdP+6L/VvAEgIAmwAiKUvvvjCpfReccUVNnDgQOvWrZv98ccf7mRt//79UW6rk06tdVRQW7hwYWvXrt15J3TRTyS9k04FfTp5ViAf3/TmmAI3Pf7bb7/t2p0jRw4bOXKkWxuq4FIn0o8++qhbo6rLPEq91nPJnTu3DRo0yAUaCpbat28f5f510q9AVie2Ohl+88033d96QYGey/Tp0116qtLvdcL+4osvuscVpbrrupw5c7rAQ+1Ueq3SVxWcX0qdOnUi08Q9mq3UcY0eYOt+FQBu3LjRzSgqQNHvX3/9tXvcmPz2228uANfJu46RjqECn9ikGutEXwGt96XnqiBDAe2VV15pFStWdLdTyq4CKqWP6zXQ9fpbvS5qa0yU9aC/Uf9TEN27d28X4DRq1MhdpoBKwbACl9DCY3p8DSYoqBE9NwUWWof6/vvvu+en1GY9v9C/0yCIjpeCTQU1adKksdatW7uAVQMVGnwRffeWKuh1V+BVpEgR9zdae65ASQGbd999+vRxgbrSvXX/eu/079//osGOgjcNcOg1iS0dL2UOqD/rsRV0aTBIM7fqiwrS1M9Dl1mIjp/+TkGo+ml8aGDB60sxUfq63hv6PFGbXn/9dTt48KC1bdvW9dn4HietsdbA3cVmy++55x4XPIcOqPz4449uwPCll15yy090nQJvry2X6nuh9DmoNqtf6PNBWQT6WQNu+hzSc1fGkD5fvLXqem2bNGni3v/6PNFx0O1CB7Vi8xrqPaTPMLVbx0rH+LLLLnNLN7Zs2RJ5X3qvKMhWfwWAhCBFHABiQSdpOrlT8KvAx6MZGQV3OtlVkOLRiaiCCtE6S81mK7i4UCqwd2Krk0Ddv06sFawq8NO6zVKlSiXodVJgpxNcL5jTSat3Mq8TaNFz04mnfteskVJGFezq5FwnyEqjFJ0IDx482Pbt2xd5/5p11Ym1aEbqhx9+cAGoTlh1kq6ZLs1i6eTaOyZqk9qgk/TNmze7gE/PV8dUFJDpuWvGMVu2bBd9fgoQdBIemiau2Ws9XoECBaLcVo+lYENBgWa/RbO5GsxYtGhRjPevoEhpowpAvbW+OlYrVqxwJ/nesYmJBhL0FSpz5swu4NJrosBNxo0b5173Dz/80AXeoplK9S8d7yFDhpx333pdMmXK5GYpvSUCGjBR4KKgQ/evIFoBmJ6D9/prMEHHVzN+mgnWMdbrrscSzaBrIKBfv37udfbWFKvf6PX0llPoeSgI0mutQN5btqDv+tKx0ftGr7e+h9YV0MypBn2U8aDjruPhDYZoplH3rUD4QvSYygLQANaFBjVEbdBzUOA0a9YsFyDr9dJja0ZZg2Xe46oNep11vNUX9R4QpZMryAxd5x1X3jHcu3dvjNfv2bPHDVyFzvwr6NMAxtq1a937Kj7HSdka6kcXU6hQIfddQba3NEKfRXqtvfeI+os+xzTQqPd6bPqeRwNsCnw9CsQ1eKZBFo/6vGa01U/1/HS/3qy+V0tCr7WKFnr0fr/Ua6j3qQbb9Fje569mzNV+rzCeR+8HfW6o7yd2zQ0AwUWADQCxoNkanRhHn7FUoKEgLnpgphNRj07mFfQpWNVsbkzr+xSkKBgNLXqkk1XNzmlWRjMyCRWafq6Zd7VFadBeICL63Zvh1Im10pN1gh8aQCoI8wIxjxe4iU668+TJE5lGrmOjk2cvuPYo3Vpp4gps9fc6idZslE7EdRx0oqziVbGhIFoBiNLEQwNszf7GdBy0dldBmIJtzWJt2LDBnYSHHotQlSpVcrPbSt9VIKkTdQ1IxGbttGZsFUQq0Fu8eLF7LRUMaNZf64dDC1Gpbfny5Ytshwq4KTiKKTXWCzIVDKtPeX+jwEDHU4GH6HodHwXVulyz/MpC8KomK2j00ow1O6i+ruPiZSCEBiF6jUJrFXizot6sZnQ6ppqR1Axi6LHV8VQ71c90bBQoagBGt9Ux1Zc3QHUhCtK8gYjoNHCjr1A6RhpQUn/2+qWOf2jg5/VLBWe63guwFVwmJLgWb7b+QoMx3sCdMhl03NQvo78G8TlOetzQfhYTZSKEtlE00OUF16LAW7+rDyvAjk3f80Rf+uItvdBnhPdcvcr43nNVoK33dGihRqV3hw6YxeY1VHCvwR5lhWg2X+9bvaeUpRGd+pOCeh3f6DUuACC2CLABIBY0sygKHKPTZdHXyV5++eVRfvdSUnVCGVOArRN4fYXS7JxOcr308YTyZkpDn8+FtqbRbJrSftXmi82OhQbVoRQYeifruh9v9i6Udyx1TNQ2pY0qBVfpuJq51nHS7KtmVmMT3GgWWyfVXsE4BYnRT7w9WrurgQsdB7VDKfl6DhdKR9fggGbSNKumv9XP+jsNCFxq+zadtGtmzJs5Uxq8Tu4V1HiV30VtUaChVOuYxBTE6m80kKCv6LzARAGd6gBo+YGOpYI2rcnVZZ758+e79GMFO3otlDGhmdHoQVf019kLFi+09ZXXz/Q8Q59raD8TzfArWNdAglKj9aVjrkGIC2VvaJYxens8muX0ZjrVRj0nrYMOLWymfqnXwgsuPaGz9TG9d+LLS32+UKq2siF0jPRdz0sBnhdMeq9BfI6T+l/0tdPReeumQ4NXDfREp88Cb/16bPqex+tLoWuilSKuQSW9Jvrs89of+rkRWizOE/pZEpvXUK+/lj3os0WZNZqB12Nqpl3HW8tlorczNstSAOBCCLABIBaUZiihadEezWzrJC+UF7h59Hc6CfTuJzqdpCqg1uxKKAWLibHVlldgS2m7MW0DprZrNkonp5pRi94mzV5pNik2dAIbutbR46XKesdOJ9lK89YMkvY21nZPSpfWjGls1r0qmFZKs4JFBSlK+45pcECpwrqdZseVkuodX63x1N9diGbV9aVAV89//PjxrnCUjoMC59jSY37//fduJlKz7d5rrjR4zQiGLjUIFdMgg/5GRahiKrwVOmupgQqtddUsofqaZpC92V8FO5oF9dbDapZSr7sGPHQs/ehnek56btF5wY2em9bE6kv1AjQIoBloZYxo5j0m6jdegB6dBri8QY0L0WNrWYL6W2iA5t1n9Pd0QmlWV8c1NNvD49UgUEEwL31fg1RKY1df8cTnOCkrRQGmguwLzfgr80O1JUIr54cW/Av9HPMyGGLb96LTYIwG9hTkKoNFs9u6vbJI9J736PjH9HnrDdrE5TXUYIEGIbQuWwOWer6qpaDrQ9fbe4MHfr/2AFIWipwBQCxo7Z9mRVRJOvrMjypde+uGPUrB9WhGRnvwqrDXhWZiFWzpRC80HVfpur///rtLC/WbgkKd4OoxFIh4XzrR1XpGrdvUrJ1Ofr001dB1jzpBvlBwE52COZ3cKy09lGbh1AYFpzrhVUCsoFsnyt6snAI0BRKxoZNoHWPdl2bBY6oe7qWe6n4V0HjBtdYg6/ILzcRqvbb2ytVrqdlFpfN7a0xj275QSlfV+loF6GfOnHGXKQDVzLv6WuhroqBDgUj0WTrvbxSY6HXybq/ZeM20a7bOo32PNTOuIExBm1JoQwuXadBEr6mCJ29W2guuQ2ewLyV6GxUoapBD/Sn0Oem1Ukq0Mj+0VEFp9woCvVlUpfbr9bvYsdXtNCscl/ZFP3ZKbY5efd5Lx1df8ovaqQwCpcMrkI1OmQMKHLVmWDPXCq7Fq9Cufhnf46QMCw2WKWtC9xGdlksolVpp/N7jit4PoUG2+oleRy1diUvfi073qX6u/aa9z5zoz1X0eaDPjNCiZnq80CrlsXkNdR8aCNCgnfq22qu17iVKlDjvuOmx1Idjmr0HgNhiBhsAYkEnnirkpZNUzRYpQNGJogrlaBYl+iyOqtUqaFGwpBNrVYFWEasLUQEe3Ye+6yRbMym6b814q3K53zRDowBTKdWaPVMQr5NL/a6TUC9dU9WiNVum516vXj03o6QAXLOdOkHVSXdsZmx1Eq9ZUt2f0j5VbEqFt7Q+2UuF14m1bqNAT8G9gmSlasalSrTSxLUdmJ7Dhf5OAb1mxjWLrUBZAwVag6znFpouGkon+0oN19pRvfYKilXISa+ProsrHQMVedLso/qFXgsV/VIwre96zfUaabZ56tSpMa4XFfUXFYlTcKR1sQralV6vAZ7oRdE0i62BguhrVhV46zJlD+hxNcij4lZz5sxx14dup3UpXjE6/a2OpfqRghmlAytw0fHWkgA9b/U3PbaWAui7+rsGXDSLqwDs888/dwHlhWiNvlL1VUAvdLur2NI6XPV7pc2rLWqrAk3NbKqGQnzX4KpgoTfzqmwHFShT0Knn6VVZj06fEwqCtWxBr4W+NHPtbWWn+4nvcdJsvt7Xeu/pvajPFw246DNG7zENuihQ94oUevSY6pd6/2sASjUI9J73tkWLS98LpQEXzaQrQ0Lp7nr/azBHGSHe44q2qNPz1/tE6+Y1S602hKb5x+Y11Oewjp2yKHQ/ys5RNoFeJ29bOY9XCPBCSw8AIDYIsAEglnRyqsBPabQKBHVCrJRhBZ/R1xhr9lW302yL0i416xRTaqhHQZpuo0JoCkgU0Ou+tW3NpSpox5e2DlO7FfwqWFRApNkpPR/vMRUQ6aRfJ/V6zprx1dpdr1BUbOhkdcKECW7G0gvoNbOpbX00i+UFAWqDrtc6U51ke1XM4xLAKnDU/Wqm8ELHTSfemolTgK/nrtkqFYtSMSTNLGswRAFIKF2vdHq9RhoUUACv2TEFBRdK+78UDSRoPaiCTQXtaocyGXSc1H8UGCh9P/Q4RaeAQoGKAg8FEJrNVRCkivXawimUAiMN/Og1DT02qiCtx9RrrGBK/UDFpfSaafZzyZIlsQ5g9Zrpcbz0cmV8aPskvW/0+ioA0zpXDajoeHpFtHr27OmKv+n4KotBQZies9L2L0TvJ91OM/LxCbD1Guo9qmBQAbCWQmjgQ/0/Pntde9Q/PAoGFUxqKYBe75hqEYheD/UDvT56zl72yMSJE+3pp592r4FSveNznETvIfU1r4bAzp07XWCrGWQFo6HFFUOPr/7Oq4Cvx1cf87Jw4tL3otNzVb/WgJXuT4Gw1kirDoCeq/qdBpg0EObdTsdEAX/omu/YvIYK/HW81Md1Xxrg0ftKx1Kf6R6937SEQp+LAJAQqSLim1sFADiPZv4026g9ZGMq0APAPwqcFIRpCcbFtkpD3HiF+zTIklJoAEKDPpqBj6kQJQDEFmuwAQBAsqSsAy0tiL4GF4gL9SEvO4XgGkBCEWADAIBkScGQ1o4rTTm0QCAQF1ouovR9rSkHgIQiRRwAAAAAAB8wgw0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPkhx+2D/8ccfbq9G7U0JAAAAAMDFnDlzxm0HWb58ebuUFBdgK7hm628AAAAAQGzEJX5McQG2N3NdtmzZpG4KAAAAACDMrVixIta3ZQ02AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAABsAAAAAAB8QYAMAAAAA4AMCbAAAAAAAfECADQAAAACADwiwAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAABsAAAAAAB8QYAMAAAAA4AMCbAAAAAAAfECADQAAAACADwiwAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAADsBzp0958drgBSOfgQAAAAEQ9qkbkByljpNanurz0e2bevepG4KkqmCV+e1jt0bJnUzAAAAAPiAADuBFFxvXP+3H68FAAAAACAZI0UcAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4IK0lsf3791u/fv1s/vz5durUKatUqZJ16dLFihYt6q5/6aWX7OOPP47yN1deeaXNmjUriVoMAAAAAEAYBtitWrWyc+fO2ahRoyxLliw2ePBga9asmc2YMcMyZcpka9eutWeffdaaNGkS+Tdp0qRJ0jYDAAAAABBWKeKHDh1ys9G9evWycuXKuVnrli1b2p49e2z9+vUWERFhGzZssOuuu87y5s0b+ZUrV66kbDYAAAAAAOE1g50jRw4bMGBA5O8HDhywsWPHWv78+a1YsWK2detWO378uBUpUiQpmwkAAAAAQPiniHtefvllmzp1qqVPn97effddy5w5s61bt85dN2HCBJs3b56lTp3aqlWrZu3bt7ds2bIldZMBAAAAAAi/ALtp06bWsGFDmzRpkluXPXnyZBdgK6i+/PLLbcSIEW5Gu3///i59fNy4ce66+FDquWbGEyJVqlRujTjghxMnTrh+CQAAACC86Dxd8V+yCrCVEi69e/e2ZcuW2cSJE93PjRs3tpw5c7rrSpQo4dZgP/zww7ZixQq7/vrr4/VYZ86csdWrVyeovQquS5cunaD7ADybNm1yQTYAAACA8KNM67APsLXm+pdffrHatWtb2rT/3xTNSivYVqEz/ewF157ixYu777t27Yp3gJ0uXbrIgD6+YjuCAcRG4cKFmcEGAAAAwpAKb8dWkgbY+/btsxdeeMFGjx5tVatWjZxdXrVqld15553WuXNnF2ir8JlHM9eSkABZwbHWeAPhguUGAAAAQHiKy+Rqkm7TpZRvFS3TNl2LFy92a667du1qhw8fdntha2ZbM9zvvPOOW389d+5c6969u913331uSy8AAAAAAMJFkq/BHjhwoNuqS5XBjxw5YhUrVnSFzgoUKOC+Bg0aZKNGjbL33nvPVQ6///77rV27dkndbAAAAAAAwivAVtDco0cP9xWTe+65x30BAAAAABDOkjRFHAAAAACAoCDABgAAAADABwTYAAAAAAD4gAAbAAAAAAAfEGADAAAAAOADAmwA5zl77hxHBQlGPwIAAClNkm/TBSD8pEmd2nqO+dy27NyX1E1BMlXoijz2SvP6Sd0MAACA/xQBNoAYKbhet20XRwcAAACIJVLEAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAABsAAAAAAB8QYAMAAAAA4AMCbAAAAAAAfECADQAAAACADwiwAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAABsAAAAAAB8QYAMAAAAA4AMCbAAAAAAAfECADQAAAACADwiwAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAABsAAAAAAB8QYAMAAAAA4AMCbAAAAAAAfECADQAAAABAUgfYJ06csL1799qZM2f8aAsAAAAAAMlW2vj80ZIlS6x///72559/WkREhLusXLly1r59e6tcubLfbQQAAAAAIHgB9u+//27NmjWzggULWsuWLS1Pnjy2Z88e+/rrr+2pp56yCRMmWPny5ROntQAAAAAABCXAHjRokFWsWNHGjBljadKkibz8+eeft+bNm9vQoUPt/fff97udAAAAAAAEaw32ihUr7PHHH48SXLs7Sp3amjRpYsuXL/ezfQAAAAAABDPAzpIli/37778xXqfLvTXZAAAAAACkJHEOsCtUqGCjRo1yFcRDHT9+3F2u9HEAAAAAAFKaOK/B7tChgzVo0MBq1Khh1atXt7x587qtuubMmWMnT5603r17J05LAQAAAAAIUoBdqFAhmzp1qitmNnfuXDt06JDlyJHDbrrpJlforFixYonTUgAAAAAAgrYPdtGiRV01cQAAAAAAkIAA+8iRI/brr7+6ddcxFTWrV69efO4WAAAAAICUE2DPnz/f2rRpc16RM0+qVKniFGDv37/f+vXr5+731KlTVqlSJevSpYubJZfVq1e7dd1//vmn5cqVy5o1a+a2CQMAAAAAIFkH2AMGDLAiRYpYt27dLF++fG7/64Ro1aqVnTt3zlUg1xZggwcPdkH0jBkzXNG0J554wu6880577bXXbOnSpe67bvfggw8m6HEBAAAAAEjSAHvjxo02fPhwX7bjUoG0K6+80lq0aGElSpRwl7Vs2dIeeOABW79+vf3yyy+WLl0669mzp6VNm9bNam/ZssUF4wTYAAAAAIBwEufp5wIFCtjRo0d9eXBVH9eMuBdcHzhwwMaOHWv58+d31ciXLFniqpMruPZUrlzZNm/ebPv27fOlDQAAAAAAJEmArdnmYcOG2fbt281PL7/8slWpUsW+/vprt+Y6c+bMtmvXLhdsh7r88svd9507d/r6+AAAAAAA/Kcp4tOnT7fdu3fbXXfd5YqOZcyY8bwiZzNnzoxzQ5o2bWoNGza0SZMmuXXZkydPdmuw06dPH+V2GTJkcN9VEC2+VPlcFdATQs8zU6ZMCboPwKOigTFV5E8K9G0EtW8DAADEh85ldI6cKAG2ZpSjzyr7QSnhotnrZcuW2cSJE13wfvr06Si38wJrzXDH15kzZ1x18oRQcF26dOkE3Qfg2bRp0wUr8//X6NsIat8GAACIr+gTv74F2H379r3kHtmxpTXXKmRWu3btyHXWqkquYHvPnj0ukNf3UN7vqmAeXyqc5gX08RXbEQwgNgoXLhw2s3z0bQS1bwMAAMTHhg0bYn3bOAfYF7J8+XL78MMP7bvvvrM//vgjVn+jQmUvvPCCjR492qpWrRo5u7xq1Sq3NVeePHlsypQpdvbsWUuTJo27/tdff3UnbLlz505QAJGQGXDAbyw3QFDRtwEAQHIXlwmoBAXYWsc8bdo0++ijj2zNmjXuskqVKsX671U9vFq1atarVy/3pariI0eOtMOHD7u9sLXeWsH3iy++aE899ZQL4lVlXHthAwAAAAAQTuIVYGv9smarVfFbQXahQoWsbdu2bv/qK664Ik73NXDgQLdVV/v27V16ufbXVqEzbQcmCrC1Lrt+/fqWN29e69y5s/sZAAAAAIBkGWCruNhXX33lZqtXrFhhWbJksRo1ariq4q+//nqcZq5DZcuWzXr06OG+YlKuXDn3mAAAAAAAJPsAW+nbSgU/evSo3XzzzfbGG29YrVq1XIVvXQ4AAAAAQEoXqwBbW2aVLFnSzTKXL18+8nIVJAMAAAAAAGapY3MQWrRoYYcOHbLGjRtb3bp1XaExbbEFAAAAAADiEGCrANns2bNdhW9tkaXCZKr+3a5dO1eynD1OAQAAAAApXayLnCmQVlCtL81ma+31Z5995oLr5557zhU8u/fee+22226L3LMaAAAAAICUIl7bdGm/6scee8x9acuuTz/91FUYV9B92WWX2a+//up/SwEAAAAASO4p4hdz7bXX2ksvvWTz5893qeNly5b1p2UAAAAAAAR9Bjsm6dKlszp16rgvAAAAAABSmgTPYAMAAAAAAAJsAAAAAAB8wQw2AAAAAABJtQb79OnTrnL4okWL7PDhw5YzZ06rWLGi1atXzzJmzOhHuwAAAAAACHaArYD68ccftzVr1liBAgUsb968tmnTJrdN16RJk2zy5MmWLVu2xGktAAAAAABBSREfMGCA7dq1yyZOnGizZs2yjz76yH3X7/v377fBgwcnTksBAAAAAAhSgP3jjz9au3btXEp4KP3epk0bmzFjhp/tAwAAAAAgmAH2sWPHrGDBgjFep8sPHjzoR7sAAAAAAAh2gF2kSBGbPXt2jNfp8kKFCvnRLgAAAAAAgl3krHnz5tahQwc7e/as3XvvvZYnTx7bt2+fK3I2depUe/XVVxOnpQAAAAAABCnArlOnjm3evNlGjBhhU6ZMcZdFRERY+vTprWXLltawYcPEaCcAAAAAAMHbB1uBdJMmTeyPP/5w23blyJHDrr/+evcdAAAAAICUKF4BtmTPnt1uv/12f1sDAAAAAEBKCbAPHDhgvXv3tjlz5tiJEydcenioVKlS2apVq/xsIwAAAAAAwQuwe/bs6aqFq8BZ/vz5LXXqOBciBwAAAAAgcOIcYM+bN8+6d+9OMTMAAAAAAELEefo5Xbp0VrBgwbj+GQAAAAAAgRbnAPuuu+5ye14DAAAAAIAEpIiXLl3aBg0aZNu2bXNbc2XMmPG8ImetWrWK690CAAAAAJDyipzJ4sWL3Vd0BNgAAAAAgJQozgH2mjVrEqclAAAAAAAkY+yxBQAAAACADwiwAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAACRFFXE5evSoHTt2zPLly2dnzpyxCRMm2N9//221a9e2SpUq+dEuAAAAAACCPYO9bNkyu+OOO2zixInu9169eln//v1t2rRp1rRpU/vxxx8To50AAAAAAAQrwB40aJAVLVrUHn74YTtx4oR9+eWX1rhxY1u0aJH973//sxEjRiROSwEAAAAACNoM9nPPPWcFCxa0n3/+2U6dOmUPPPCAu65OnTq2fv36xGgnAAAAAADBCrBTp05tGTJkcD/Pnz/fsmfPbuXKlYtcm50xY0b/WwkAAAAAQNCKnF133XX28ccfu0D6u+++s+rVq1uqVKls//799t5777nrAQAAAABIaeI8g92pUydbsGCBPfLII5YmTRqXLi733Xefbd682dq1a5cY7QQAAAAAIFgz2GXKlLEffvjBNm7caMWLF7fMmTO7y3v06GEVKlSwvHnzJkY7AQAAAAAI3j7YWbNmtcKFC9uSJUvsyJEjljNnTrv11lvd5QAAAAAApETxCrBHjRplw4cPdxXEIyIi3GXp06e3Fi1aWKtWreJ0XwcPHrSBAwfanDlzXJG0kiVLWocOHaxixYru+ieeeMKlpIe66aabbMKECfFpOgAAAAAA4RFgf/rppy4g1p7XdevWtTx58tjevXvdftjvvPOOFShQwOrXrx/r+3vhhRfc3+s+c+fO7QLn5s2b2+eff25FihSxtWvXuvTzmjVrRv5NunTp4tpsAAAAAADCK8AeO3asNWrUyF599dXIyxQI33zzza6y+Pjx42MdYG/ZssXtpT158mS78cYb3WUvv/yy2/5r+vTp1qRJE1ed/Prrr2dtNwAAAAAgWFXEFRSHziaHqlGjhv3111+xvi+t3Va6edmyZSMv05Zf+jp8+LCbvdbPWu8NAAAAAECgZrDz5ctnf//9d4zXbd++PU6FzrJnz2633357lMu+//57F8R3797d1q1bZ9myZbOePXu6mW5VLL/77rutZcuWbs13fGnd+PHjxy0hFPhnypQpQfcBeE6cOBFZzyCp0bcR1L4NAAAQHzqX0TlyogTYd955pw0ePNgVIytXrlzk5cuWLbOhQ4e66+Pr999/t27dulmtWrWsevXqLshWITU9joqdrV692vr37+8CfH2PrzNnzrj7SggF16VLl07QfQCeTZs2uUAkHNC3EdS+DQAAEF+xneCNc4DdunVrV9W7YcOGduWVV7oiZ/v27bMdO3ZY0aJFXQXw+Jg5c6Z17NjR7aX91ltvucs0c92lSxfLkSOH+71EiRKuwFn79u2tc+fO7rHjQ/dRrFgxS4jYjmAAsaFlEOEyy0ffRlD7NgAAQHxs2LAh1reNc4CtFPBPPvnEVRNfvHixHTp0yK2hfvLJJ61Bgwau0FlcTZw40Xr37u3Sv994443I0YG0adNGBtee4sWLu++7du2Kd4CtAELp5kC4YLkBgoq+DQAAkru4TEDFax/sDBkyWOPGjd1XQqmC+Ouvv26PPfaYvfjii1Ear8uuuuoq69u3b+RlK1ascDPQ11xzTYIfGwAAAAAAv8QqwNb+1nHx/PPPx3ptXp8+feyuu+6yFi1auFRzj2bCa9eu7a7XGuzbbrvNBddae619suNSTA0AAAAAgLAMsDXLrDV1adKkcVttKU1chcM0s6yU7tgG2KoYrr/74Ycf3Fco7aXdr18/91gTJkxwgXbevHmtWbNm9swzz8TlOQIAAAAAEB4B9po1ayJ//uWXX+yFF16wl19+2c0wK8iWefPmuRTvrl27xvrBn332Wfd1MY8++qj7AgAAAAAgnKWO6x+osnebNm2sTp06kcG1VKtWzdq2bWtvv/22320EAAAAACB4AfbOnTvd9lwxyZ07t+3fv9+PdgEAAAAAEOwAu1SpUjZp0iQ7e/ZslMtPnTplo0ePdgXJAAAAAABIaeK8TZfWX6uKd82aNa1q1aquyJmqf8+dO9dOnDjh9rQGAAAAACCliXOAfdNNN9mUKVNs5MiRNmvWLDt48KALsm+55RZr1aqVFSpUKHFaCgAAAABAkAJsKVOmjA0ZMsT/1gAAAAAAkJICbK23Xrt2rZ0+fdrthy3nzp1zKeJLliyxjh07+t1OAAAAAACCFWAvXLjQbcd16NChGK/PkiULATYAAAAAIMWJc4Ctfa615vr111+3adOmWerUqa1BgwY2b948+/DDD+29995LnJYCAAAAABCkAFup4b169bK77rrLjhw54gqe3X777e7rzJkz9u6779qoUaMSp7UAAAAAAARlH2yttc6XL5/7WRXD169fH3ld7dq1bdWqVf62EAAAAACAIAbYV199tZvFlsKFC7vCZn/99Zf7/d9//7Vjx47530oAAAAAAIIWYN9///321ltv2cSJEy1Xrlx23XXXufXY2hN72LBhVqxYscRpKQAAAAAAQQqwn3rqKXvkkUds2bJl7vdXX33VVq9ebS1btnQz2Z07d06MdgIAAAAAEKwiZ5s2bbIuXbpE/l62bFmbOXOmC66LFCliWbNm9buNAAAAAAAEbwa7cePG9sUXX0S5TEF1uXLlCK4BAAAAAClWnAPsdOnSuX2wAQAAAABAAlLE27Zta/3793d7YJcqVcoyZ8583m0KFCgQ17sFAAAAACBlBdg9evSws2fPWqdOnS54GxU9AwAAAAAgJYlzgN2rV6/EaQkAAAAAACkpwK5fv37itAQAAAAAgJQUYMvp06ftk08+sQULFtjevXutT58+tmjRIitTpoyrJg4AAAAAQEoT5yriBw4csAcffNB69+5tW7ZsseXLl9vJkydtzpw59thjj9kff/yROC0FAAAAACBIAbYqiB87dsy++eYb+/zzzy0iIsJdPmTIECtbtqz7DgAAAABAShPnAHv27Nluq65ChQpZqlSpIi/PkCGDPfnkk7Zy5Uq/2wgAAAAAQPAC7FOnTtlll10W43Vp0qSxM2fO+NEuAAAAAACCHWArDXzy5MkxXjd9+nS77rrr/GgXAAAAAADBriKu9PBmzZrZAw88YLfffrtLE//qq69s6NCh9tNPP9no0aMTp6UAAAAAAARpBrtixYr2wQcfWKZMmVwwrSJnY8eOddt1jRw50ipXrpw4LQUAAAAAIGj7YFeqVMmmTJnituc6dOiQZc2a1bJkyeJ/6wAAAAAACHKALUoHX7x4sR08eNDy5MljVapUcbPbAAAAAACkRHEOsDVj3aJFC1u6dKmlTZvWVRRXkD18+HCrVq2aW4udPn36xGktAAAAAABBWYPdp08f27Rpk73zzju2YsUKN5O9fPlyGzx4sAu633777cRpKQAAAAAAYSzOAfacOXOsY8eOVrNmTVdB3N1J6tRWq1Yta9++vduqCwAAAACAlCbOAbaqhmvNdUyuuOIKO378uB/tAgAAAAAg2AF2/fr17d1337Vjx45Fufzff/+1iRMnuusBAAAAAEhp4lzkTPtfb9682WrUqOG+8uXLZ//884/NnTvXdu3aZTly5LBu3bq52yqFXGu2AQAAAAAIujgH2NOmTXP7Xssvv/wS5br8+fPb77//Hvm7t0YbAICkdvbcOUuTOs6JW0DY96OzEecsTarwahOSH/oRkEQB9qxZs3x6aAAA/jsKirp/8an9tW8fhx3xUiRPHutT78GwO3oKrvv98pFtPbwnqZuCZOrq7Jdb1yoNk7oZQMoMsL29sHfu3OkKnqmwmfbCBgAg3Cm4XrNrZ1I3A/CdgusN//zNkQWA5BRgKyV8+PDh9ttvv7ng2nPjjTfas88+a7fddltitBEAAAAAgOAE2GPHjrU33njDzVg3adLEChUqZGnSpLGtW7fajz/+aE8//bR16tTJnnzyycRtMQAAAAAAyTXAXr58ub355pv22GOPuSA6Xbp0Ua7v2LGjDRgwwH1VrFjRypUrF+sGHDx40AYOHGhz5syxo0ePWsmSJa1Dhw7ufrxZcz32xo0bXXDfunVru/fee+P6PAEAAAAASFSxKjk5btw4q1SpknXv3v284NrdSerULvC+5ZZbbPz48XFqwAsvvGB//PGHC7I//fRTu/baa6158+b2119/uaC6RYsWVrVqVfvss8/soYcess6dO59XvRwAAAAAgGQxg62ttzSrfCkNGjSw/v37x/rBt2zZYj///LNNnjzZreOWl19+2ebPn2/Tp0+3/fv3uxnt9u3bu+uKFi1qq1atstGjR1uVKlVi/TgAAAAAAITFDPa+ffvcHteXkjdvXjtw4ECsHzxnzpw2atQoK1u2bJS9s/V1+PBhW7JkyXmBdOXKlc8rsgYAAAAAQLIIsHPlymXbt2+/5O10GwXZsZU9e3a7/fbbLX369JGXff/9925mW2nhu3btOi+wv/zyy+3EiRP2zz//xPpxAAAAAAAIixTxm2++2aZMmWL16tW74G3OnTtnH374oVuHHV9KRe/WrZvVqlXLqlevbidPnowSfIv3++nTp+P9OJr9Pn78uCWEZtkzZcqUoPsAPBo0CpesDPo2gti36dcIYr8W+jaC2re9/g34IaH9Wn8f2/4YqwBbRccefPBBe+WVV+zFF1+0DBkynPdm1HVr1661Pn36xKvRM2fOdNXIK1SoYG+99Za7TI8TPZD2fk9IcHvmzBlbvXp1vP/ee/zSpUsn6D4Az6ZNm9z7KBzQtxHEvk2/RhD7tdC3EdS+rcLKZcqUtjRpYr2rMBCjs2f/tZUrV7kYMCGiT/xeSKx6rAqN9e7d2wXXSuHWLPWVV15padOmtR07dti8efPcm7Ffv36uEFlcTZw40d3/3Xff7fba9hqvbbn27NkT5bb6PXPmzJYtWzZLyBu2WLFilhCMqMFPhQsXDpsRY/o2gti36dcIYr8W+jaC3LcVXH+7bqgdOL4jqZuDZCpX5ivtnhKtrXjx4gnq2xs2bIj1bWM9JPTAAw+4ho0YMcJV+dae1d7I6Z133um20ypRokScG6sK4q+//rrbY1sBfOg/Cu2FvWjRoii3//XXX90st7YGiy89hoJ0IFyw3ABBRd9GENGvEVTh2LcVXO89timpm4EU3rdTxWG5QpxyLpQSPWTIEBf9Hzx40H1XAbSEpKEopfyuu+5yAbqqlXsyZszogu769eu7lHF9nzt3rn333Xdumy4AAAAAAMJJ2vhG8NpiK6GUbq5c+B9++MF9hVJArZTz4cOH25tvvmnjxo2zq666yv3MHtgAAAAAgHCTpFUDnn32Wfd1MdWqVXNfAAAAAACEs/gvZAYAAAAAAJEIsAEAAAAA8AEBNgAAAAAASRVga+uspUuXup///vtvt476/vvvt2HDhvnRJgAAAAAAgh9gf/HFF9a0adPIqt+vvPKKLVy40AoVKuT2yB41alRitBMAAAAAgGAF2GPHjnVbaHXq1Mn27t1rCxYssOeff97eeecda9++vX366aeJ01IAAAAAAIIUYP/1119Wr1499/PcuXMtIiLCatSo4X4vW7as7dy50/9WAgAAAAAQtAA7e/bsdvToUffz/PnzrUCBAnbNNde437du3Wo5c+b0v5UAAAAAAIS5tHH9g5tvvtmlg2/YsMF+/PFHe+KJJ9zl33//vQ0ePNhuu+22xGgnAAAAAADBmsF+8cUX3Sy1guwqVapYixYt3OV9+/Z1s9kdOnRIjHYCAAAAABCsGexcuXLZmDFjzrt88uTJLsAGAAAAACAlinOA7dm/f7+dPn3aFTmTc+fO2fr1623JkiXWqFEjP9sIAAAAAEDwAuw1a9ZYx44dbePGjTFenypVKgJsAAAAAECKE+cAu3///nbo0CHr0qWLzZ4929KnT2933HGHzZs3z32NHz8+cVoKAAAAAECQipwtW7bM2rZta82aNbM6derYiRMnrHHjxjZixAirWbOmTZgwIXFaCgAAAABAkAJsrbv29r3Wd6WMexo0aGBLly71t4UAAAAAAAQxwFal8G3btkUG2EePHrXt27e735UurvRxAAAAAABSmjgH2LVq1bIBAwbY999/b/ny5bMiRYrYoEGDbO3atfb+++9bwYIFE6elAAAAAAAEKcB+/vnnrUKFCvbJJ5+437t162Y//PCD1atXz3799Vdr3bp1YrQTAAAAAIBgVRHPkCGDDRkyxM6cOeN+r1q1qk2fPt1WrlxpZcqUsauvvjox2gkAAAAAQLACbE+6dOkif1ZQTWANAAAAAEjJYhVg16hRw4YNG2alSpWyO++801KlSnXB2+q6mTNn+tlGAAAAAACCEWDfdNNNliVLlsifLxZgAwAAAACQEsUqwO7bt2/kz/369UvM9gAAAAAAkDLWYJ86dcpWrFhhe/fudTPZ+fPnt9KlS7s9sAEAAAAASKliHWAfPHjQBg4caF988YWrIB4REeEuV5CdOXNme/DBB61NmzaWNWvWxGwvAAAAAADJN8A+dOiQNWrUyLZv3261atWyW2+91fLkyeOC7N27d9vPP/9skydPdvtgf/jhh5HrtQEAAAAASCliFWCPGDHCpYQriC5btux51z/88MO2evVqa9asmb3//vvWunXrxGgrAAAAAABhK3VsbjRr1ix75plnYgyuPddee60LsGfMmOFn+wAAAAAACE6AvWvXrosG155y5cq5NHIAAAAAAFKa1LGtHK5CZpeitdcnT570o10AAAAAAAQvwPaqhftxGwAAAAAAUnSADQAAAAAAfNgHu2HDhrG9KQAAAAAAKU6sAuznn38+8VsCAAAAAEAyRoANAAAAAIAPWIMNAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA/Jf7YIc6cOCAjRkzxhYsWGB79+610aNH28yZM61UqVJWs2ZNP9oFAAAAAECwZ7C3bdtmdevWtalTp1q+fPls//79dvbsWdu0aZO1adPG5syZkzgtBQAAAAAgSDPYb7zxhuXOndsmTJhgmTNntuuuu85dPmDAADt16pSNGDHCqlevHq/GjBw50n766Sd3356XXnrJPv744yi3u/LKK23WrFnxegwAAAAAAMIiwP7ll1+sT58+lj17djdzHaphw4bWrl27eDVk0qRJNmjQIKtYsWKUy9euXWvPPvusNWnSJPKyNGnSxOsxAAAAAAAIqzXYadPG/GenT5+2VKlSxem+du/eba+++qotXLjQrrnmmijXRURE2IYNG+yZZ56xvHnzxqepAAAAAACE5xpszTArlfv48eORlymoPnfunH344YdWoUKFON3fypUrLV26dDZt2jS7/vrro1y3detW9zhFihSJazMBAAAAAAjvGewOHTpYo0aNrFatWnbzzTe74FoVxTdu3GhbtmyxyZMnx+n+7rzzTvcVk3Xr1rnvWpM9b948S506tVWrVs3at29v2bJli2vTAQAAAAAInwC7RIkS9umnn9rQoUNdWrfWQ2u7rkqVKrkCaCVLlvStcQqwFVRffvnlrniaZrT79+9v69evt3Hjxrnr4kOp56Ez8PGhgYVMmTIl6D4Az4kTJ1y/DAf0bQSxb9OvEcR+LfRt+Im+jaA6kcDPbf1tbJdCx2sNttZKq2p4YnvuueescePGljNnzsjgXmuxH374YVuxYsV5KeWxdebMGVu9enWC2qbgunTp0gm6D8Cjbe70xg8H9G0EsW/TrxHEfi30bfiJvo2g2uTD53b69On9C7D//vvvOD14gQIFzA+aofaCa0/x4sXd9127dsU7wNaa72LFiiWobXEt5gZcTOHChcNqNgQIWt+mXyOI/Vro2/ATfRtBVTiBn9sqvB1bsQqwtUY6Lh/gCZ0d9nTu3Nn27NljY8eOjbxMM9eSkABZz0V7eAPhguUGCCr6NoKIfo2gom8jqDIlcGlvXGLhWAXY2vfau9NDhw7ZW2+9ZVWqVLF77rnHpWwfPHjQZs2aZXPmzLGuXbuaX2rXrm0tW7a0d955x+rWreum9nv27Gn33XefFS1a1LfHAQAAAAAgoWIVYDdo0CDy51atWlm9evWsV69eUW5z//33W+/eve3bb7+1hg0bmh9q1KhhgwYNslGjRtl7773nKofrcdq1a+fL/QMAAAAA4Jc4Fzn7+eefbdiwYTFeV716dZs6dWq8G9OvX7/zLtMsub4AAAAAAAhncd7nSkXHli9fHuN1v/76q+XLl8+PdgEAAAAAEOwZ7IceesjNYJ88edLNWCvg3rdvn3333Xf24YcfWvfu3ROnpQAAAAAABCnA1t7UR44csTFjxri10aKS5xkzZrS2bdvao48+mhjtBAAAAAAgWAG2qol36dLFVfdeunSpqyquWezy5cuz9RUAAAAAIMWKc4DtUUXvqlWr+tsaAAAAAABSSpEzAAAAAABwPgJsAAAAAAB8QIANAAAAAIAPCLABAAAAAEiqImenT5+2Tz/91BYtWmSHDx92VcQrVqxo9erVc9t1AQAAAACQ0sQ5wFZA/fjjj9uaNWusQIECljdvXtu0aZN99dVXNmnSJJs8ebKrMA4AAAAAQEoS5xTxAQMG2K5du2zixIk2a9Ys++ijj9x3/b5//34bPHhw4rQUAAAAAIAgBdg//vijtWvXzqWEh9Lvbdq0sRkzZvjZPgAAAAAAghlgHzt2zAoWLBjjdbr84MGDfrQLAAAAAIBgB9hFihSx2bNnx3idLi9UqJAf7QIAAAAAINhFzpo3b24dOnSws2fP2r333mt58uSxffv2uSJnU6dOtVdffTVxWgoAAAAAQJAC7Dp16tjmzZttxIgRNmXKFHdZRESEpU+f3lq2bGkNGzZMjHYCAAAAABCsAHvjxo0ukG7SpIktXbrUDh06ZDly5LDrr7/efQcAAAAAICWKc4DduHFj69atm9WrV8+qVauWOK0CAAAAACDoRc7SpUtnOXPmTJzWAAAAAACQUmaw27Zta/3797cjR45YqVKlLHPmzOfdpkCBAn61DwAAAACAYAbYPXr0cBXEO3XqdMHbrF69OqHtAgAAAAAg2AF2r169EqclAAAAAACkpAC7fv36idMSAAAAAABSUoAtp0+ftk8++cQWLFhge/futT59+tiiRYusTJkyVq5cOf9bCQAAAABA0KqIHzhwwB588EHr3bu3bdmyxZYvX24nT560OXPm2GOPPWZ//PFH4rQUAAAAAIAgBdiqIH7s2DH75ptv7PPPP7eIiAh3+ZAhQ6xs2bLuOwAAAAAAKU2cA+zZs2e7rboKFSpkqVKlirw8Q4YM9uSTT9rKlSv9biMAAAAAAMELsE+dOmWXXXZZjNelSZPGzpw540e7AAAAAAAIdoCtNPDJkyfHeN306dPtuuuu86NdAAAAAAAEu4q40sObNWtmDzzwgN1+++0uTfyrr76yoUOH2k8//WSjR49OnJYCAAAAABCkGeyKFSvaBx98YJkyZXLBtIqcjR071m3XNXLkSKtcuXLitBQAAAAAgKDtg12pUiWbMmWK257r0KFDljVrVsuSJYv/rQMAAAAAIMgBthw9etQOHz7sflaQrS9PgQIF/GkdAAAAAABBDbDXrFljnTp1sg0bNlzwNqtXr05ouwAAAAAACHaA/corr9g///xjnTt3vuB2XQAAAAAApDRxDrDXrVtnb7/9tt1xxx2J0yIAAAAAAFJCFfGCBQvaiRMnEqc1AAAAAACklAD7hRdesMGDB9uiRYtcFXEAAAAAABCPFPHChQu7va+bNm0a4/WpUqWyVatWcWwBAAAAAClKnAPsbt262cGDB61hw4aWJ0+exGkVAAAAAABBD7A1O923b1+rU6dO4rQIAAAAAICUsAb78ssvt0yZMiVOawAAAAAASCkB9tNPP22DBg2yzZs3+96YkSNH2mOPPRblstWrV1uTJk3shhtusDvvvNPGjx/v++MCAAAAAPCfp4jPmDHDtm/fbvfcc49lz57dsmbNel6Rs5kzZ8a5IZMmTXKBe8WKFSMv++eff+yJJ55wgfVrr71mS5cudd+zZMliDz74YJwfAwAAAACAsAmw8+bNa7Vq1fKtAbt377ZXX33VFi5caNdcc02U66ZOnWrp0qWznj17Wtq0aa1o0aK2ZcsWGzVqFAE2AAAAACB5B9gqcOanlStXuiB62rRpNmzYMNuxY0fkdUuWLLGbbrrJBdeeypUru1Tyffv2UcUcAAAAAJB8A2y/Kf1bXzHZtWuXlShR4rwia7Jz5854B9jax/v48eOWEEqFp9gb/HLixAnXL8MBfRtB7Nv0awSxXwt9G36ibyOoTiTwc1t/q8/bRAmwS5Uqdck7V2EyP5w8edLSp08f5bIMGTK476dOnYr3/Z45cybBbVRwXbp06QTdB+DZtGmTe+OHA/o2gti36dcIYr8W+jb8RN9GUG3y4XM7elyaoABbadxlypRxP7dq1eq8APvYsWP2+++/29atW61jx47ml4wZM9rp06ejXOYF1pkzZ473/SolvVixYglqW2xHMIDYKFy4cFjNhgBB69v0awSxXwt9G36ibyOoCifwc3vDhg2xvm2sAuxHH33UevXqZffdd5+1bt36grfr3Lmz/fnnn74VIMufP7/t2bMnymXe7/ny5UvQP6OEBOiA31hugKCibyOI6NcIKvo2gipTpkz/2WBmrPbBbtSokb3yyiu2bdu2i96ufv369s0335hfKlWqZL/99pudPXs28rJff/3VjUDkzp3bt8cBAAAAACChYhVgd+nSxe1tfamgVini//77r/lFM+FHjx61F1980U3Lf/bZZzZ27Fhr0aKFb48BAAAAAIAfYl3kLFeuXO77O++8c951586dcxW/NXt9xx13mF8U0I8ePdp69+7tZse1B7fS0PUzAAAAAADhJM5VxGMKsCVr1qxWs2ZN69atW7wb069fv/MuK1eunH300Ufxvk8AAAAAAMIywF6zZk3itAQAAAAAgKCvwQYAAAAAAD7MYMcl7VslzPv06RPr2wMAAAAAkGIC7IULF17yNv/884+dOHGCABsAAAAAkCLFKsCeNWvWBa/TtlzDhw+3UaNGWZ48eaxHjx5+tg8AAAAAgGAWOQu1evVqlz6+du1au/fee+3ll1+2HDly+Nc6AAAAAACCHGBr1nrYsGH23nvv2WWXXea27qpRo4b/rQMAAAAAIKgB9qpVqyJnrevWrWsvvfSSZc+ePXFaBwAAAABA0AJszVprpnr06NGWM2dOe/fdd+2OO+5I3NYBAAAAABCkAHvlypXWtWtX27Bhg9WrV8+6d+9u2bJlS/zWAQAAAAAQpAD74YcftnPnzrmgeseOHdaqVauL7oM9btw4P9sIAAAAAEAwAuwKFSpE/hwREXHR217qegAAAAAAUmyAPWHChMRvCQAAAAAAyVjqpG4AAAAAAABBQIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAdpLRnYvXu3VatW7bzL+/btaw0aNEiSNgEAAAAAkOwC7DVr1liGDBls5syZlipVqsjLs2XLlqTtAgAAAAAgWQXY69ats2uuucYuv/zypG4KAAAAAADJdw322rVrrWjRokndDAAAAAAAkneArRnsAwcO2KOPPmq33HKLNWrUyObNm5fUzQIAAAAAIPmkiP/777/2119/WbFixaxr166WNWtW+/rrr+2ZZ56xDz74wKpUqRLn+4yIiLDjx48nqF1aC54pU6YE3QfgOXHihOuX4YC+jSD2bfo1gtivhb4NP9G3EVQnEvi5rb8NrQWWrAPstGnT2sKFCy1NmjSWMWNGd9l1111n69evtzFjxsQrwD5z5oytXr06Qe1ScF26dOkE3Qfg2bRpk3vjhwP6NoLYt+nXCGK/Fvo2/ETfRlBt8uFzO3369MEIsCVLliznXVa8eHH76aef4nV/6dKlczPiCRHbEQwgNgoXLhxWsyFA0Po2/RpB7NdC34af6NsIqsIJ/NzesGFDrG8b9gG2ZqobNmxo7777rt18882Rl//555/xDpL1zyhz5sw+thJIGJYbIKjo2wgi+jWCir6NoMqUwKW9cRnMDPsiZ6oeXqRIEevZs6ctWbLENm7caH379rWlS5fac889l9TNAwAAAAAgecxgp06d2kaMGGEDBgywdu3a2eHDh93aZxU4K1GiRFI3DwAAAACA5BFgS548edysNQAAAAAA4SrsU8QBAAAAAEgOCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAAAAAIAPCLABAAAAAPABATYAAAAAACklwD537pwNGTLEqlatajfccIM9/fTTtm3btqRuFgAAAAAAySvAHj58uE2ePNlef/11mzJligu4n3rqKTt9+nRSNw0AAAAAgOQRYCuIfv/9961NmzZWvXp1K1WqlL399tu2a9cumzFjRlI3DwAAAACA5BFgr1mzxo4dO2ZVqlSJvCx79uxWunRpW7x4cZK2DQAAAAAAT6qIiIgIC2OapW7durUtW7bMMmbMGHl527Zt7eTJkzZy5Mg43d/vv/9uesrp0qVLcNtSpUplhw4es3//PZvg+0LKlDZtGstxWRbXJ8OJ+vbBI8ftzFn6NuInXZo0dlm2zGHVt9Wv/zl+zM6cPZfUTUEylS5NasuZOUw/s08ds3/P8ZmN+EmbOo1dliE8+/aJM4ftbMS/Sd0UJFNpUqW1TOmyJ7hvnzlzxvXHChUqXPK2aS3MnThxwn1Pnz59lMszZMhghw4divP96cCEfk8oBUdAQvnVH/2k4AgIWt9WcAQErV+LgiMgiH1bwRGQ1H1bfx/b+wj7ANubtdZa7NAZ7FOnTlmmTJnifH/ly5f3tX0AAAAAACSLNdhXXHGF+75nz54ol+v3fPnyJVGrAAAAAABIZgG2qoZnzZrVFi5cGHnZ4cOHbdWqVVapUqUkbRsAAAAAAMkmRVxrr5s0aWJvvfWW5cqVy6688kp78803LX/+/FarVq2kbh4AAAAAAMkjwBbtgf3vv//aSy+95CqHa+Z6zJgxvlQCBwAAAAAgRWzTBQAAAABAchD2a7ABAAAAAEgOCLABAAAAAPABATYAAAAAAD4gwAYAAAAAwAcE2AAAAAAA+IAAGwAAAAAAHxBgAwAAAADgAwJsAAAAAAB8QIANAACSxLlz5zjyCCT6NoJgx44dSd2EZCltUjcAiK+vv/7aNm7caIcPH7ZGjRrZ1VdfbenSpeOAAkCY+u6772zz5s124sQJ97mdP39+F4ikTs14P5I3+jaC5tNPP7WPP/7Y2rRpY7fccktSNydZSRURERGR1I0A4qp///72+eefW+7cue3vv/+2HDly2JtvvmkVK1Y0delUqVJxUJEsEWwgqN566y374osvLEOGDHbw4EFLmzatO4G76qqr+NxGskbfRhDNnDnThg0bZpdffrk1a9bMqlSpktRNSjYIsJHs9OnTxwXX7733nhUsWNCdmD3xxBOWL18+Gz16dFI3D4iXX375xUqWLGm5cuUi2EAgP7cVXOtkrVChQrZt2zZ78cUXrUSJEjZo0CA3KMrAKJIj+jaCbN68eTZkyBC77LLLrHnz5gTZsUSKOJKV3r17u+B64sSJVqpUqcjLb7rpJtu0aVOStg1ISHDdqVMnu+eee6xly5aWM2dOgmwE+nM7T548Lrg+c+ZMZHo42UdIbujbCCrv87hatWru56FDh9qYMWPcdcxkXxoBNpKNgQMHupO0adOmWYECBezff/91KYaiN7/W8gHJkf5Z3Xvvvfbrr79amjRprEWLFpcMsglGkBwMHjzYreH75ptvonxuK6jOmzdvlNt6ff3s2bPufQCEM/o2gib0vELfvd9vv/12dxlBduwRYCNZ2LJli33//fcufVYnaeJ9CEyaNMkmT55st912m1sHlSlTJrvyyivd7zqZI/BGctCtWzfr16+f/fTTT+73CwXZe/futdOnT7s+DoSzlStX2ieffGLXXXedZc+e3V3mBc76zNZnd+3atW348OGuQGWZMmWsXLlyblZbfR8IV/RtBJF3ruGdd1woyB43bpxlzZrVypYtm8QtDl+swUayoIBCabQ9e/Z0Bc0+++wzd/m7777r1mIr7VBrsPVPb8+ePe4ETbMguvzDDz90QTcQTv766y/btWuXGwRScOGlXKmAn9Y8aYDIC7JDg+uXX37Zli1bZnPmzLH06dOzbhVhTSdi2vFBKeGvvvqq+5weOXKk+1INjWuuucYWL17sqorrS26++Wb32Z45c+akbj5wQePHj7evvvqKvo1kTwP7msjSOUblypXdV6jQgf758+e7pRH33XefPf/880nU4vBHgI1kF2S/9tpr7iTtjjvusA8++MAFJDohU7ChoFpBiyqLL1y40M2OFC9ePKmbDkShGbvZs2fbvn377NixY66GgJZAqA/LG2+8ERlka022BpV2797t+vrcuXNdv2fkGMkpEFGBs8KFC7sMJM1qq4+r32fMmNH2799vp06dsqVLl7qBJz63kVzQt5Hc6dzjhx9+cBNR+ixW1qfOMS42wKnz8NWrV9uECRPYHvcCCLARtvSG14iaRs1uvfVWNxutkzAFztqSa/369W72umrVqi749gJs1u4hnGkZgzIwlI2hIFl9WumzqtC5fPlylyIrCkA0Uqwg+8EHH7T333/fvv32W5eRce211yb10wBipIGhrVu3uuU8Cqi9vqpARFtyrVu3zvXtunXrRn5eU08AyTnrSMX7VGeAvo3kWEdgypQpLu1bu5joM1mfx9GX6Ogce8OGDVa6dGn3e69eveyff/6xvn37Rk4MICoCbIQlnYBpzbVG0g4fPmw7duxwI2o33HCDe6MvWLDAvbEVmOgfm4QWPQPCkWbxNHutINsLpD2qzqmBo8cff9y6d+8e+T5Q6pbeA4cOHXLrVr1/cEC4Uf/VIJCKl+kzW3UC2rZta7fccou7XmuuNXut1HBt0aVMJAZFEYSsI/VtnYtcffXV9G0kC5qk6tKli3Xs2DHyM9qjbNGdO3e6gX/V0Dh+/LgbFFVGqD7ff/vtNzd7HbqbD6IiwEbY7nOtgEPBhGZDdOKmdBUFHAqiFWRrJlvrUXPnzu1mRoQgG+HIm6Hr0aOHS/dW0CHe9kQjRoxw/6zuvvtu15f/97//2UsvveSue/31111auPYP1ggzEI60Ju/LL790fblChQq2ZMkSt7+1ApE2bdpE3k79XJ/vShXX57eC7HPnzkW+F4DklHW0YsWKyOU69G0kJz///LP7DJ46daqrI6DzFO1konMQ1Rbw6LxES9V0Lj5z5kyXndSgQQMrVqxYkrY/7EUAYaR///4RlSpVitiwYUOUy995552IZs2aRWzdujVixYoVEadOnXKXz58/P6JmzZoRd911VxK1GIidgwcPRtx2220R77//fpTLv//++4gbb7wx4qeffnK/f/LJJxGlSpWKGDNmTORt9u/fz2FG2HrrrbciKlasGLF+/Xr3+7lz59z3fv36RTz66KMRW7ZsiVi6dGnk7SdMmBDx0EMPRTRt2jRi9+7dSdZu4FI+//xzd36xbNmy864bPXp0RMmSJSN69+4dedn48ePp2whr3uez+nStWrXcOYfOT15//fWIW2+9NaJ8+fIRAwcOjFi4cGHE3Llz3e/ffvtt5N96f4+LY8gYYUMjZpq1btq0qRUtWtRdpvRBUYqsZkQee+wxN7vXoUMH27Ztm1sD1bVrV1coR78D4Up9OUOGDK6vetkWotFgzXyozoDUrFnTsmXL5tb6eXQbIBwpLVa1MLSswZvR0EyIqCr45s2brUmTJu6zW1vRiX5XP9d7QrPXQLjx+rAK791zzz0uTTa0rypTQ3UxHn30UTcDqDWpon5+11130bcRtrxq4Moe0pIGbQ+qQsFai61dHVTnRVl2yj6qVq2a2z5x1apVkX8bum0oLowFqwgbJUqUsEqVKrkUlSuuuMKloKgAjrZz0T8wpWepYI4Kjbzwwgvutlqvqr35FGizpQvCmYJkLXnQGlSdsCm9UCpWrBgljVwndErX0m2AcKdgQssXdFKmNdc6KVO696hRo1wq+CuvvOLW7G3fvt0FIfoM1+f2M888Yw0bNnRLJoBwo89i1b348ccf7cknn4yyhGHGjBk2evRoVyBKA6P6XNeSHvX/J554wp5++ml7+OGH6dsIKwqSVZhMgbXqG+m7UsRVDVwTVFrao/Nw7W+tCQD1+QMHDriCfqy1jjsCbIQNvbH1T0qjaQqotbZ648aNbpRYa/m8Te71RtdlmtHW6LHWZFPcDOFGW8VpgEhfCphFo8QqlqP+3bhxY/ePzKuA740Ka3/ryy+/3I0kA+FOA0UKpFXpXvUz3n77bbcDhLKRVJlWMyBy8OBBVwhq7dq1kX9LcI3klnWkcw0v68irkK9sDNWHUVEoD30b4USfy1o/rW24VD9ARVaVdaQZbH1Fz9zwzqnHjRvn1l6rwDDihgAbYTGipoBCs9Yq4qSqhvpnpRlrVezUTIgCE++f25kzZ9x+fQrI2ZIL4eidd95xW2xpmzmlzT7wwAP20EMPuQEhVQVXeqECa/3ubYehvq6TtunTp7tq4dG3yQDChQY+jxw54qqB67NYfVWZGQqytYRHn9MqDKUtFL3P7SxZsrjbXXXVVUndfCBWyDpCEGjgUwUoNVGlYFo7PXz99deuErgykDw6N1HRPm9LXFUS/+abb1yQraKUiBsCbITdiJre3NrCRR8KSvvW9aEjagpOlCau6spAuNH2cfpnpv6rwaPff//dxo4d6waP1Mffffdda926tUupVWXaOnXquP6swSJ9V5CtwSMgHCktVidoR48edYOdSvdWqreyNLQNnQaNFHxrBk8zgN7ntjI3NOCk9wUQjsg6QtD079/fZRhpr3ZvFxItedA2uFqOpsxQDYLqXFsZdbqdtuTSsp5ChQq5rCPOR+KHbboQViNqzz33nNWqVcvdZs2aNW4mW2/2Ro0aWb169dzMoGa0FZyo8AIQThRc65+ZAmpvv+o///zTFQxRn9f6VC8VXGm02iZDxcwUhGgkWXUFGClGuH9u66RNhShV4Oyjjz5yn8nevu4aVFL9DA2aav31jTfeyOc2km3Wkei8RNuCKjCJKetIQYiyjghEEG59Wl9arqNaAV7RYA3mt2vXzg3onzx50p2TqK5R7dq13SCT9nlXsK3PcGUeIX4IsPGf08mZTsxCR9RUnVOzIN6eqZoZ0Rt8w4YNbn9VjbBpnerixYvdPzJV9ATCyZAhQ1xBPlXi1L6o+sflrd1TwKFlEFqHqj6vQjjeGmv2bkdyoNoY2h9V6YLe4JHXt++44w5X2EmDoUqrVWEcpYt7tQQ0gMrnNpJT1pFm93S5N3CkrCNdrjXZ0bOOtBzCW48NhAsN9mvnBn026/zaW56jAVGdr+hc2zuvXrBggTsvZ29r/5Aijv+URtNUoEwjago0QkfUVIFTI8ia2RONqGmDe23DpZRxBduaLeEfGcKNgmRVv1dVzh07drh/Ulqb6i1pWLdunevvSqNVpsbu3bvd5eLVEfCqiAPh5oMPPnBZGdpKUX3bqzCrLw2E6gRN/Vozexo8UhaSgnFVwl+2bJk70eNzG8kl60if1fo81zZz3ueyCvZ5WUc6F1HWkYqbkXWEcFW/fn13jq3iwRrw17m0Pst1/q2dH7zCwdqFRwG2zr8JsP1DgI3/lIJo0T8vre8IHVHTeuzQETWNvOnNrn92GiHW5aTPIhzpZEt7AT///PNuEEn/zLSkQYNJ+tJl1atXd7e95ZZb3OCRquBriy4vqCa4RjhSNpG2aRF9Rusz2VtXra2K1I9btWrlgpHly5e7OhoqWKksDt1eWRsqhgaEG83iKZNOWUcKrr2sI2XIqYaAghHVivGyjrSMR19kHSFcKXtIn7ka+FQ2kYpO6txCk1R//PGHmwDQ0kwF1V4/zpYtm9u2S5/b8A8BNsJ6RG3evHnuhI4tixCOVGlT/Vlf+ielQFpBttJoZ8+e7apw6jItffBoXZMGirx9sIFwpuBa6d46SdNyHX1ua/2eBkX1ua1MDG8rLs2AKJVWe6oqwNZ7Ql9AuCHrCEGjz2R9BqsSuALsp556ypo2beo+v/U53rlzZzfQ7y3N9AZKlRquc5jrr78+iZ9BsBBgI6xH1JixRrhSYRtvrZ7Wmnbs2NEVdNJAkYqaqUqnZj284Fp1BpRSu2jRIjc7ovcCEK4OHz7sqoHrc1jrTlXcSemyCrJV8EnFoAYMGGC33XZb5Oe2BkK1TELZRkA4I+sIQaKCwNOmTXODnwqs165d65ZYeurWreuykXTerR0ddBt9tiuLQwOlyuJgBttfBNhIVIyoIaj/zLQe1asoq+BZyx+87S70T0tps9pXsnjx4nbfffe5oEMDSePHj3f/zAiwEa60rGHOnDluJwcvqNa66ocfftjNhKhQpQJrfYXOhGgvbA2eavYaCEdkHSFoFFjPmDHDbQHqFeVTVpE+i1XpXpQxp5lsnau8/PLLbinE6dOn3Y48+gotXAl/EGAj0TCihiDStizTp093qbFeNXv9o1IArTQrbXGhrS28dHEFKyp4pmBFyyFUTVl7vQPh+rmt/q2tiZo3b+7WWHsnX+rjGizSQFKvXr1s4MCBrp6Atz+2CkXpZE2z2EC4IesIQbRq1So32OkF1wqit2/f7or3ffbZZ25Zj+odqVCftp5T4K1lmvquYpQE14mDABuJghE1BI1m8vSPSgGH1pmGbhV39OhR1+dnzZrltnlROpa2xlCQrdsqCFGQzVZFCGc62dLShtDBI68uxt69e90yH52UKXNDg0mqwKx+rRM6FTxjJgThiqwjBI1X4X7nzp1RarpoEuCLL75wg/paola4cGG3nE3nJAq6tUxTt1ehYWXYIXEQYCNRMKKGoNE/Mm2ppQJOCqg9GiHWPy1Vvle1ZM3eaW2qZvk0C6h08VdeecVatGhhJUqUSNLnAFzM6tWrXSq4t6WWAmedvGmPYH2JTtZULOfxxx9374fXX389MjgvU6YMBxhhh6wjBJG384iW5GinHQ2Cal/2zZs3u/pFShlX4TItY1O9I+3Ms3XrVlc4WFvMIXERYMNXjKghyBRw6J+VZvm0LZFms/Wl0eA+ffq4PVEVZCtVViPIWrOaO3duF3AD4fy5rQEh7VmtPuztza4ZaQXOGjDViZoGj1TcrF+/fm7gqEGDBq4gpWa7ixQpktRPA4iCrCOkhPNtFSzT+ciPP/7oCpdpi1ClguvcQ7cRXa8lPtrFBP8NAmz4ihE1BJX+UakwiAqEKO1b6d5KmdU/smefffa8dacKPPQPDkgOn9sqXla7dm03E3Lo0CE3m61KtHnz5nWV8RVg58mTxw0caWbk+PHjrlDf/fffzx7uCEtkHSHo/dsLsnVO0rhxY3fO4e1Y4n2XuXPnut1OVIQV/w0CbPiKETUElf6Jad2ptiJScL179273D0tBt0aG9c9M9A9NaeRa36TiZwpcvIEnIJypgJmCa81aKxNDMyOPPfaYC6y9/q2AW0X8vBM3+jbCGVlHCDJ9/mr7LZ1neAP6Wm+tjCINgGqJj85XtMODivxpUgD/DQJs+IoRNQSZUmeVSqvZaX2JqnWqQqcCDlUQ19Z0qsKsf2rsB4zkROmFHTp0cPu36+QsppkQpSFqYEl7YwPhjKwjBJ0G/RVca/21vpRJ9/XXX7svrcPWdaoZM3HiRHYv+Y8RYMN3jKghiFkZouBae/4ePnzY/dNS4KHCId66Jv2u1FqtwVYhESC5naxpEMnbo33dunWub+tETRkbGjRStXx9V/VwIJyRdYSU8Hm9Y8cOl32kbUGffPJJa9Kkics0UjaStgStXLmyXXHFFUnd3BQnVYS3Ah7w+U0fOqKm7Yqij6hpD1WvWi0QLrS1hbbauvrqq13KlVLA9TGp4Fn9WjPWqqDcvXt3q1atms2ePdulXingULGnBx54wP0tkBw/txVI6zNa2Rdaj+0VzlGwcvDgQbffNZ/bSE68gVGPl3UkXtaRCvpp4IiBUYSb0Ayi6BRcK6DWdoqqD+MVqETSI8DGfzKipq0DVHmZETWEs6FDh7pttxRkqDK4Cphp70hv3ZL6tfYAvuWWW6x3796RM9veP8DQ2W4g3CxYsMANHqmP1qlT57wA5O+//3bbdGlLORXNmT9/vqssrnV8KnJ266232pVXXpmkzwFIjKyj4cOHW+nSpTm4CBt//vmnG7S/UJCtft6xY0c3uK/tEr0+H9r/OSdJOgTYiBdG1BA02mZL6a9dunRxBZ40m/Hzzz/be++9Z+XKlXNVkzVYVLJkSevRo0eUf2DR6w8A4ebtt992xctOnTplR44ccYF0//79XYaGqDCfCprVqFHDBSChM35AOCPrCEGjzKHXXnvNDfDrc/lC5936PKceRngiwEacMKKGoAbXmrkOLQSiYLl8+fIuC0PVlGX58uVWtmxZgmgku/6t7bW0LEczdwqmu3btam3atHEncOrr+l2zfUoLZ5AIyQVZRwgibZGopQsbN250mXTKnIseZHsZowhPBNiINUbUEESaxdPM3oQJE6xEiRIuyNA/MH1v3ry5NW3a1GrWrBl5e/2DUwBCEILkOnikVFllY5QpU8ZeffVVd5kyNJRqSL9GckHWEYJMRSaVQacMjUceeSTGIFu0/EF1Myg8GV7IAUOsqShIpUqVXDCiN7fe7NG3cNGIGukqSC5mzJhh77//vvXt29cF15rJ81JjFZT89ttvrp+vWLHCrcMuXLjwBYuNAOE4eKRlDx999JEVLVo0cr9U9WVttaWik57MmTO773oP6It+juQ2cHTjjTe6rKNFixa5ZT3q0ypGGT3r6EI/A0lp37597ktU60LnJM8++6yNGDHCpkyZ4i73zrs9e/bsccXN9Jn+5ptv8rkdRgiwEWtae6riNxpRi/5m94JsL12FETUkBxow0kmZ/oFp3XXFihXd5erjgwYNciPCSkFUmpYowM6RI4erIh5aJAoIN4sXL7Zx48ZZ3bp1XXAt3uez6gvMnDnTihcv7gJwBdsq6qdARYOkrL9GuA8cffnll64fR886UjB9zTXXRN5WgbbOT4RgGuFK5xy//PKL/fHHH+5zWlXBtVxHn92hQbYGP1U1XHbt2mUDBgxwA0r6rGdQNLyQIo44jahly5bNBRt6s0dPW/EwoobkRINBzz33nKuUrP2rv/vuOxszZoy98sor7uTs9OnT7j2g/r5kyRLbunWr+8en4AQIV6oIrq2Hpk+fbvfff7916NDBXT5y5Ei3baIGirQ3qrIzRINJOXPmdBXyQyvSAuGWdaTaAco6ql+/fpTCkgpAevbs6WoN6HzFyzoCwtkbb7zhBjo7d+5shQoVcn1a/VaDnt6Wcps2bXKV7r3z7nr16rkiaHo/6HOerRPDDwE24jyipn9moUF2w4YNzxtR0+yIRtQUoADhRH1XMxoaLNL+vl6QrewMBRuqqqyKy1WrVo3x77VW1UunBcI9yFZ6uFJplXWhvq3gWjOAmunLlSuXK3imgjp6X2gASYG4l3ILhBttM6fCkxr01FaJ0bOO1Mf1uU7WEZIDBcfqu0OGDIncksszevRot4RNg/133313lCBby320neikSZPYXi5MEWAjRoyoIYgGDx7sRnwVJKvQU6dOnezhhx9212mPdm1PpNTaDz74IPKfnTdDcrGt6YBwzTjSSZhSaVU7Q9dplu+GG26IXI8NJDdkHSEIlB2ncw4Vm1TRydBsDFUQV0adZrTXr1/vsoruueceN3CkiS7t3a5JLgZDwxcBNs7DiBqCSCmF2qpI/5yUDuvtca3gw8u00InbM88845Y5KBNDgQipskjuGUehQbYyjlq3bh3jNi/s445wRNYRgkjp31q+o+JkoTuVfPzxx253By1Vq1KligvCNTGg5T3K2Ni8ebM7h8mXL1+Sth8Xx3QMzhtRU5qgUr41g6cTLo9G1JSuohG1l156yb799lu3TkQFGLRG5OTJky44L126NEcVYUWphAqulXKl1G/9k9K6a/XxlStXur6rAjnaI1i3UdGnLl26uPcCkBwyjjTb8cADD7jsCwXbqiyr4HrHjh3uREyf6Q8++KBLGdcSCFFw7RWAEgaTEI5ZR1pzrYFPBSNTp051l+uzWjN41apVc/1W9QM83nmL17dZ0oNwpAHOLFmyuL4syirSeYiW7ij1W8G1vPDCC3bs2DH7888/3e8q4kdwnQxEACG2bdsWccMNN0T88MMPUY7L1KlTI6699tqIBQsWuN+7du0aUaFChYjFixe73zdt2hSxa9cujiXCzrhx4yJKliwZsXXrVvf7iRMnIq+rX79+RNOmTSPuvvvuiPbt20d8/fXX7vIjR45E3HfffRH3339/xMmTJ5Os7cClTJ48OeKOO+6IWLFixXnXvffeexFVqlSJ+Pbbb93ve/bsiRg4cGBE9erVI3r37s3BRVjr06dPxE033RQxb948d64xaNCgiDJlykQsW7Ys8jaHDh2KaNiwoXsP/P777xHnzp1L0jYDFxK9b+pcpGrVqhEvvfTSRW/32WefRdSoUSNiy5YtHNxkhBlsRMGIGoJEa61VHVwjwprBFhXBEc3yaW2Tqm9Wr17dzWQrS0PpiKo+q5Tad999l33dEYiMI1XHz5s3rzVu3Njuuusu++mnn+zAgQNJ2n7gQsg6QtAcOXLETp065T63RdshqhL+/Pnz3bZzHs1kh9JnvM5TdB6D5IN9sFO46GvulHaiQk7a2uWmm26KLIJz5513RrmdTs6UFq7LgXDt10oNbNq0qUvDUmqsUsFV2EyBhwLsYcOGuZRx3bZy5cqukrjWRWnvSRWI0hcQrlQrYNasWa74jXif0VrDp4rKoWv4XnzxRcuTJ49bHvHUU0+5pT2csCEcjR8/3iZMmGA//PCDFSxY0H1ua2A0ffr0Ljj5/vvv3W0UdGjtap06ddzSnkaNGrliUOr/GTJkSOqnAURS/9R5s+q86Dxb/VSfx/rsnj17tlvio/RwLeNRPxelhes8Re8DDfhr4B/JBwF2CqcRNf0j0omZ3tTeiJpG0/SlNX3eiJr3phdG1BDu/Vr9Vf1aW7bon5aCbp14/fbbb65IiLYr0iCSV+hJVZe1tknvASC5Zhypz3tr+MqXLx+5hu/zzz93a/gUYKvGAJAcso5UkC961pEyNhRca3Dpr7/+spIlS7pBUQUhCmAIrhFuBVa1z3X79u1dTYwFCxZY8+bNbeLEia4KuAqa6TYqdvbjjz+6ugLakku7PixdutQF38WKFUvqp4E44kwyBWNEDUHv1wokNFJ8xRVXRG7HpSI5lSpVcsF1KP0DVPZGiRIlkqjlwMWRcYSgIusIQV7qELr1Z4UKFVxArQBaWXI33nij27Vk7ty5biBU5yjKvtNOEO3atXNZHEh+2KYrhYppRE2pVxpR0xtes3y6jdJl9WEQfURt6NChVAtHsunXms1TepW2K9I/L33dd999rlK4qKqy/gEqjVwzI0A48mbnvIwjpRTqs1jZRurzXsaR+nxoxpHSw/W3en+QZohwpP7pZR2pj2sW+5NPPnFZRwUKFHBZR0OGDImSdbRhwwZ7/vnnXcX8W2+9NamfAhCFsuRUx0X1L0KXOij1W8sa6tata9u2bXM1YHSOrawN9W2t06byffLHDHYKxIgaUmK/VmChtU+PPvqou07BtP7ZaT9J/Y3SCwmuEa7IOEJQkXWEoGVjaHLqs88+cxNR+/fvdwG2t9RB9QV02erVq93AUteuXV39F81Wa+DIC66jZywheWEGO4VhRA0ptV/rH55GipV2pVRw/ZMbOXKkmwXUjLYXlAPhhowjBBVZRwiqhQsX2ltvveWyQp9++mlXcFJ1BHTeocuVjaFgWpMDytbQ+msKTwYHM9gpBCNqCKK49mulhD/zzDOu6FODBg1clfxatWq54mZAOCLjCEFF1hGCZtGiRW45pZbp3HLLLdajRw9XxEznItqdR4X5tNRB13nbKipzThXFo2/PheSNGewUhhE1BFFc+/XMmTMtd+7ckWv5gHBExhGCiqwjBI1quejcQmnd2kJRBVNV10jFywYPHuwq4Ksqvgb55dy5cy6brlevXrZ27VqXhUeNjOBgBjsFYEQNQZSQfq20cCG4Rjgi4whBRdYRghpcq66LAmll0x08eNDVdxEtS9MAv5ZDaItbXX/bbbe54HrQoEH26aef2pQpUwiuA4YZ7IBjRA1BRL9GSkDGEYKKrCMExZ9//mmvvPKKW4J28803n9fP//nnHytUqJCrhK89rZVp16pVKzdJMGzYMFdglRowwcMMdoAxooYgol8jyMg4QlCRdYQg0vafR48etWLFikWmfmumWnta68vz1FNPWdOmTW3cuHHWsmVLV4SV4Dq4CLADPKI2f/58l67ijahp1Cz6iJrWq2pETV9ZsmRx/wDff/9996YvWbJkEj8LICr6NVJSZsb333/v1vBp3Z4+y/WZrp+17CF0G5dVq1ZZ/vz53Wc4EI7o2wgq7d+uvduXLl3qzrdVX+Cbb76xI0eO2BNPPGGVK1d2O5u0bdvWPvzwQ+vUqZNLDdeStuLFiyd185FICLADihE1BBH9GkFFZgaCir6NIFMxM9Vz6d69ux06dMj9XLZs2cgAOm3a/w+1brjhBlu8eLErcjZq1KjI/a4RTATYAcWIGoKIfo0gIjMDQUXfRtDly5fPzVorw0jZoeXLl3drqpU16hVU3bt3r9sW1NsS1CuAhuAiwA4oRtQQRPRrBBGZGQgq+jZSgquuusoaNWp03uXe7PX48ePdsp9y5cq537W0B8FGgB1QjKghiOjXCCIyMxBU9G2kNJrJ3rhxowumlTKu36dNm+aCbNXKQMpAgB1gjKghiOjXCBoyMxBU9G2kNJq1Hjp0qCtCmTt3bitYsKArHKz3AlIOAuwUghE1BBH9GkFAZgaCir6NlKZKlSr25Zdf2r59++yyyy5zQba3iw9SDgLsFIIRNQQR/RpBQWYGgoq+jZTY5/WFlCtVhHIYkCJs376dETUEDv0aKSkzo3Tp0kndPCDe6NsAUgJmsFMQRtQQRPRrBA2ZGQgq+jaAlIAZbAAAwgyZGQgq+jaAoCPABgAAAADAB6n9uBMAAAAAAFI6AmwAAAAAAHxAgA0AAAAAgA8IsAEAAAAA8AEBNgAAAAAAPiDABgAAAADABwTYAAAAAAD4gAAbAAAgREREBMcDABAvBNgAgLDRtWtXK1my5EW/HnvssURtw8KFC93j6HtievbZZ+3jjz+Octn27dvt1VdftRo1aljZsmXttttuc7f76aefYnWf+nu1/bPPPrMgiP7aly5d2m6++WZ78sknbfbs2YnymOvXr7dGjRqd146hQ4f6/lidO3e29957z/f7BQAknbRJ+NgAAETRsmVLe+SRRyJ/Hz58uK1atcreeeedyMuyZs2a7I+aAuDdu3fbgw8+GHnZL7/8Yq1atbL8+fPbU089ZUWLFrUDBw7YV199Zc2bN7emTZta9+7dL3q/l19+uX300Ud29dVXW1D873//s4ceesj9fObMGdu7d699+umnbuDhxRdftMcff9zXx/vuu+/sjz/+iHKZjqleF7916NDB7r//frvzzjvd6w0ASP4IsAEAYUOBYWhwmCtXLkufPr3dcMMNFhQnT560t956y81Up079/4lkCrbbtGljFSpUsGHDhlmGDBkib3/33Xfb2LFjrW/fvla8ePHIYDMmQTtWosA2+nOqU6eOtW7d2vr37++C06uuuipR25BYxzRfvnx233332ZtvvmkjRoxIlMcAAPy3SBEHACTLGWClCyvF+tZbb7WbbrrJNmzY4K6bOXOmNWjQwKVY67pevXrZ8ePHo/z90qVLXZqxAtrKlSvbCy+84ILcUH/99ZebOb7++uvd/Sgo/vfffyOvP3XqlAuGFQDrsWrVqmWjRo2yc+fOXbTtmn3V395xxx2RlymAVhvV1tDg2tOsWTMX5L377ruR64OVKt+xY0cXmOu6J554IsYUcc3GPvroo+421atXt3Hjxrn7Uzp+6HNRsHr77bfbdddd52ZVv/nmmyhtUCCrTII+ffq4NO3y5cu7Gdhjx465512tWjW78cYbXeD7zz//WGJr3769m9H+5JNP4vQ8/vzzT5cNoLbqOehYqD+I0sC9bInQtPDQn70lBMo4UB/y+oeC5LNnz8a5f6iNc+bMsXXr1iXi0QIA/FcIsAEAyZKCmffff9969+5t3bp1cym206dPd2nWRYoUccHN888/b9OmTXOp515gqpTzJk2aRAZjr732mgu6FEyHBtCaMVYQppnFe+65x62VnTJlirtO96UU5dGjR7sZZd1GgdSgQYPczPTFqD0KdDXb7NEa62uvvfaiachqw44dO2z16tWRl3377beWJUsWF3grrTy6jRs3ugBSBg4c6IJfBXm//fZb5G30XHTM9NwUpOu+FHgqgP3iiy+i3J+O986dO+3tt9+25557zqWvK81d7X/99dfdQMWPP/5oQ4YMscSm17hAgQKRzyU2z+Po0aPuOOXMmdMFzHoeJ06ccK/9kSNH3GuplHQvLfxi2QIa3PD6h2ah1Re8NfVx6R9qo2aydSwBAMkfKeIAgGRLQYyCVS+o0Sxz1apV3XfPNddc44LMuXPnutsq2LnssstcsOjNFmvtsmZjVeDKo7W9CsxFs9yaGf/1119dcD5v3jxbsGCBC1rvvfdedxvNYmbMmNEGDx7s/lbp3NEpwFuxYoULlkNp5lkzwBdTqFAh911BtmbvJV26dG6AwAvWdT+hRo4cadmyZXOBXqZMmSID09B17noe8+fPd8GmUq9Fx1CBp46jgse0adNGrn/X7fT7LbfcYp9//rmb+VdgqccR3dfvv/9u/4U8efLYvn37Yv08lOWg2XW9Pspe8I6HgmnNxGuAwxvkuFRauAJnBfRSpUoV1z80E61jG9f+odl2zYgDAJI/ZrABAMmWZn1DU7p37drlUpk1E+19VapUyQWGP//8s7udZjwVzIamYmsWcdasWVHur2LFipE/p0qVyq688ko7fPiw+33RokUuyNSsZKi6detGXh8Tzf5q5j36mmENDnhB7IWkSZMm8rYeBYehM+HRaUBAz9ULrr3nqufiUWCn56e06tDjpuOogmKhgw7lypWL0k4FuIULF44MrkWDF5oNvhA9/9DHuVRK/cXoWKjtsX0eCmq1rl8DM6+88or98MMP7jl06tQpzkXMdBxD6e+9pQhx7R96PaIPjgAAkidmsAEAyVbmzJkjfz548KD7rhldfUW3Z8+eyNvlzp37kvcdGpSKCpJ5we2hQ4dcmrEX9Hry5s3rvl8owPQuD223F2BpZvpitm3b5r4rLdqj9PCLURXymJ6rgkqPjoeelzejG9Nx8wYeYqrgHv25XMpdd90V5bnWr1/f+vXrZ/GhAZUSJUrE6XlMmjTJpY8rvV4z15pVfuCBB+yll1666GBFdPo7v/qH+trFBiUAAMkHATYAIBCyZ88eubewip5FlyNHDvdds60KPKNTCnnoDPbF6L6UaqzZ2NAgygviFVzFxLvcmwn3aJZVKesKPENnl6NvH3XFFVdEpofHhmZVvRTqUPv373ez397xUJA8fvz4i6am+0XB7enTpyN/v9CxuhSle2tmWgXc4vI89Ly9gmTLly+3L7/80j788ENXvT6mdezxEdf+of4Q3+MAAAgvpIgDAAJBgZNma5Vqq6rN3pcKSA0YMMAVN/NSv5UuHhrk6bpnnnnGVq5cGavHUgCv9GMFvdELmImKX8VEbVHApZnXUKoIrtlhFWvTNl7RTZ482aUVt2jRInJrr9hQerzWJaugW+hzDU1H1nNRarNmX0OPm6paq1BcaOE3P6gCd+jjxHeLLRVS0yyyZsBj+zz0emk9vQJzvQ5K8+7Ro4cbnPn777/d/cTl+PrVP9QfLjSwAgBIXpjBBgAEggImVYzW2lr9rG2wNDM4fPhwV4irTJky7nYqXNawYUMXrKrYlAJaVXfW+mIVotK2Vpeidc3aqkppxbrvUqVKuQBYlcYV8BUrVizGv9MMq1KYtQ7cq+7tFVlT8SttuaUtxtQuVUVXqrFSmb/++ms3U9uoUaM4HROtNdY2VZqZ1ZZSOh56HAWR3tplrVlWIK7joi89rmZ2FcCqSJjWLCclBZ/eNloKWnW8VVxNlct79uwZuXY6Ns9Dx15rvlWcTAMqSrHX8VV6trbRCs2EUFVvbcFVsGDBOLc5Lv1DAwLqcyqeBwBI/giwAQCBocrOCppUNVvra72AVlWkvUBJKdYTJkxws9rt2rVzM8cKzrTtUmzX4Co4VYVuBW/aw1op55qJ1TZV2iLqYmrXru22iNKscmihNc2sajsp3d8HH3zgCqIp2NMsrAIzBYlxpbToMWPGuO3IFLxrhl8DC0rT9tZvK9jW1l0KvPWclD6umXY9D69KdlLSPtfeXtdqq4qoKfDVMVL1bk9snocGMtQ3dJsXX3zRVRhX4TO9Hjr+okBbaePaJ1xbdmmGO67i0j9UVV7p5NELogEAkqdUEaHlSAEAQKJSUFezZk1XubpevXqJ+liqrK2tvEIromsWW1tsaa26ZsqRtLp37+4KtCnTAgCQ/LEGGwCA/5AqRrdu3drNLKsIVmLSmnKlhmsWdfHixW5bKqWNqyCY9oVG0lKWwowZM6xt27a8FAAQEMxgAwCQBJ5++mmrUaOGPfLII4n2GFpvPGLECJfyrGBOKfMqwNWhQwffq4Mj7rQsQSnqStsHAAQDATYAAAAAAD4gRRwAAAAAAB8QYAMAAAAA4AMCbAAAAAAAfECADQAAAACADwiwAQAAAADwAQE2AAAAAAA+IMAGAAAAAMAHBNgAAAAAAPiAABsAAAAAAEu4/wN25CO5pjI1UQAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 1000x600 with 1 Axes>"
       ]
@@ -314,8 +314,8 @@
     "    Dias_Operados=('PAX', lambda x: (x > 0).sum())\n",
     ").reset_index()\n",
     "\n",
-    "# Ordenar pelas rotas de maior média de PAX diário\n",
-    "estatisticas_trechos = estatisticas_trechos.sort_values(by='Media_PAX_Diario', ascending=False)\n",
+    "# Ordenar pelas rotas com maior número de dias operados\n",
+    "estatisticas_trechos = estatisticas_trechos.sort_values(by='Dias_Operados', ascending=False)\n",
     "\n",
     "# Definir número de trechos alvo\n",
     "NUM_TRECHOS = 5\n",
@@ -325,9 +325,9 @@
     "\n",
     "# Gráfico\n",
     "plt.figure(figsize=(10, 6))\n",
-    "sns.barplot(data=top_trechos, x='Trecho', y='Media_PAX_Diario', hue='Trecho', palette='viridis', legend=False)\n",
-    "plt.title(f'Top {NUM_TRECHOS} Trechos Mais Relevantes (Média de PAX Diário)')\n",
-    "plt.ylabel('Média Diária de Passageiros')\n",
+    "sns.barplot(data=top_trechos, x='Trecho', y='Dias_Operados', hue='Trecho', palette='viridis', legend=False)\n",
+    "plt.title(f'Top {NUM_TRECHOS} Trechos Mais Relevantes (Por Dias Operados)')\n",
+    "plt.ylabel('Número de Dias Operados no Ano')\n",
     "plt.xlabel('Trecho (Origem - Destino)')\n",
     "plt.xticks(rotation=45)\n",
     "plt.tight_layout()\n",
@@ -336,7 +336,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "eadb21ce",
+   "id": "0cb78b22",
    "metadata": {},
    "source": [
     "## 4. Fleet Assignment Model (FAM)\n",
@@ -353,13 +353,13 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "c485ad06",
+   "id": "5747cb28",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:11:57.814188Z",
-     "iopub.status.busy": "2026-06-07T23:11:57.814061Z",
-     "iopub.status.idle": "2026-06-07T23:11:57.912503Z",
-     "shell.execute_reply": "2026-06-07T23:11:57.911927Z"
+     "iopub.execute_input": "2026-06-07T23:14:34.670051Z",
+     "iopub.status.busy": "2026-06-07T23:14:34.669927Z",
+     "iopub.status.idle": "2026-06-07T23:14:34.764631Z",
+     "shell.execute_reply": "2026-06-07T23:14:34.763920Z"
     }
    },
    "outputs": [
@@ -369,7 +369,7 @@
      "text": [
       "== RESULTADO DO FLEET ASSIGNMENT ==\n",
       "Status: Optimal\n",
-      "Distância Total Minimizada: 7722.27 km\n",
+      "Distância Total Minimizada: 7591.01 km\n",
       "\n",
       "Alocações (Voos Diários):\n",
       "\n",
@@ -379,13 +379,13 @@
       "Trecho: SBBR-SBGL (Voos necessários: 1)\n",
       " -> ETA3 (Base SBGL): 1 voo(s)\n",
       "\n",
-      "Trecho: SBBR-SBGR (Voos necessários: 1)\n",
-      " -> ETA6 (Base SBBR): 1 voo(s)\n",
-      "\n",
       "Trecho: SBGR-SBBR (Voos necessários: 1)\n",
       " -> ETA6 (Base SBBR): 1 voo(s)\n",
       "\n",
-      "Trecho: SBGL-SBGR (Voos necessários: 1)\n",
+      "Trecho: SBBR-SBGR (Voos necessários: 1)\n",
+      " -> ETA6 (Base SBBR): 1 voo(s)\n",
+      "\n",
+      "Trecho: SBGL-SBSJ (Voos necessários: 1)\n",
       " -> ETA3 (Base SBGL): 1 voo(s)\n"
      ]
     }