03.Compare_Groups.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7a0f535b-f393-4fa5-b5eb-6049b9a20a15",
   "metadata": {},
   "source": [
    "## Assessing Differences Between Groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7baeac12-9ae3-4ef4-9c8f-0c954eb659ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from scipy.stats import kruskal\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a8334774-055a-4cfa-be42-9a9eebc5f34e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get data loaded back on this script \n",
    "df_filtered2_norm_log = pd.read_csv('data/df_filtered2_norm_log.tsv', sep='\\t') \n",
    "\n",
    "# Re-do the following to get them back on this script\n",
    "## Group columns based on their location (e.g., CITO_, MEMB_, NUC_) and ensure they end with '_MaxLFQIntensity'\n",
    "cito_cols = [col for col in df_filtered2_norm_log.columns if col.startswith('CITO_') and col.endswith('_MaxLFQIntensity')]\n",
    "memb_cols = [col for col in df_filtered2_norm_log.columns if col.startswith('MEMB_') and col.endswith('_MaxLFQIntensity')]\n",
    "nuc_cols = [col for col in df_filtered2_norm_log.columns if col.startswith('NUC_') and col.endswith('_MaxLFQIntensity')]\n",
    "\n",
    "## Combine all columns into a dictionary by group for easier plotting\n",
    "compartments = {\n",
    "    'CITO': cito_cols,\n",
    "    'MEMB': memb_cols,\n",
    "    'NUC': nuc_cols\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7507118f-1b3c-4ab9-b9e1-25974b2262b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 Protein Protein_ID   Entry_Name      Gene  Protein_Length  \\\n",
      "0   sp|A6NEC2|PSAL_HUMAN     A6NEC2   PSAL_HUMAN  NPEPPSL1           478.0   \n",
      "1  sp|A8MWD9|RUXGL_HUMAN     A8MWD9  RUXGL_HUMAN  SNRPGP15            76.0   \n",
      "2  sp|E9PAV3|NACAM_HUMAN     E9PAV3  NACAM_HUMAN      NACA          2078.0   \n",
      "3  sp|O00148|DX39A_HUMAN     O00148  DX39A_HUMAN    DDX39A           427.0   \n",
      "4  sp|O00186|STXB3_HUMAN     O00186  STXB3_HUMAN    STXBP3           592.0   \n",
      "\n",
      "       Organism                            Protein_Existence  \\\n",
      "0  Homo sapiens  2:Experimental evidence at transcript level   \n",
      "1  Homo sapiens                          5:Protein uncertain   \n",
      "2  Homo sapiens     1:Experimental evidence at protein level   \n",
      "3  Homo sapiens     1:Experimental evidence at protein level   \n",
      "4  Homo sapiens     1:Experimental evidence at protein level   \n",
      "\n",
      "                                         Description  Protein_Probability  \\\n",
      "0    Puromycin-sensitive aminopeptidase-like protein               0.9628   \n",
      "1  Putative small nuclear ribonucleoprotein G-lik...               0.8712   \n",
      "2  Nascent polypeptide-associated complex subunit...               1.0000   \n",
      "3                  ATP-dependent RNA helicase DDX39A               1.0000   \n",
      "4                         Syntaxin-binding protein 3               1.0000   \n",
      "\n",
      "   Top_Peptide_Probability  ...  CITO_EGF_R2_MaxLFQIntensity  \\\n",
      "0                   0.9990  ...                     0.027552   \n",
      "1                   0.9962  ...                     0.000000   \n",
      "2                   0.9990  ...                     0.031506   \n",
      "3                   0.9990  ...                     0.040632   \n",
      "4                   0.9968  ...                     0.000000   \n",
      "\n",
      "   MEMB_CTRL_R1_MaxLFQIntensity  MEMB_CTRL_R2_MaxLFQIntensity  \\\n",
      "0                           0.0                      0.000000   \n",
      "1                           0.0                      0.000000   \n",
      "2                           0.0                      0.022132   \n",
      "3                           0.0                      0.023457   \n",
      "4                           0.0                      0.000000   \n",
      "\n",
      "   MEMB_EGF_R1_MaxLFQIntensity  MEMB_EGF_R2_MaxLFQIntensity  \\\n",
      "0                     0.000000                     0.000000   \n",
      "1                     0.000000                     0.000000   \n",
      "2                     0.052310                     0.028974   \n",
      "3                     0.000000                     0.042575   \n",
      "4                     0.037485                     0.030358   \n",
      "\n",
      "   NUC_CTRL_R1_MaxLFQIntensity  NUC_CTRL_R2_MaxLFQIntensity  \\\n",
      "0                     0.008386                     0.000000   \n",
      "1                     0.026602                     0.035917   \n",
      "2                     0.032488                     0.000000   \n",
      "3                     0.030143                     0.039527   \n",
      "4                     0.000000                     0.000000   \n",
      "\n",
      "   NUC_EGF_R1_MaxLFQIntensity  NUC_EGF_R2_MaxLFQIntensity  \\\n",
      "0                    0.010342                    0.016145   \n",
      "1                    0.031408                    0.033722   \n",
      "2                    0.033255                    0.029313   \n",
      "3                    0.043705                    0.036338   \n",
      "4                    0.000000                    0.000000   \n",
      "\n",
      "   Indistinguishable_Proteins  \n",
      "0         sp|P55786|PSA_HUMAN  \n",
      "1        sp|P62308|RUXG_HUMAN  \n",
      "2                         NaN  \n",
      "3       sp|Q13838|DX39B_HUMAN  \n",
      "4                         NaN  \n",
      "\n",
      "[5 rows x 87 columns]\n",
      "['CITO_CTRL_R1_MaxLFQIntensity', 'CITO_CTRL_R2_MaxLFQIntensity', 'CITO_EGF_R1_MaxLFQIntensity', 'CITO_EGF_R2_MaxLFQIntensity']\n",
      "['MEMB_CTRL_R1_MaxLFQIntensity', 'MEMB_CTRL_R2_MaxLFQIntensity', 'MEMB_EGF_R1_MaxLFQIntensity', 'MEMB_EGF_R2_MaxLFQIntensity']\n",
      "['NUC_CTRL_R1_MaxLFQIntensity', 'NUC_CTRL_R2_MaxLFQIntensity', 'NUC_EGF_R1_MaxLFQIntensity', 'NUC_EGF_R2_MaxLFQIntensity']\n",
      "{'CITO': ['CITO_CTRL_R1_MaxLFQIntensity', 'CITO_CTRL_R2_MaxLFQIntensity', 'CITO_EGF_R1_MaxLFQIntensity', 'CITO_EGF_R2_MaxLFQIntensity'], 'MEMB': ['MEMB_CTRL_R1_MaxLFQIntensity', 'MEMB_CTRL_R2_MaxLFQIntensity', 'MEMB_EGF_R1_MaxLFQIntensity', 'MEMB_EGF_R2_MaxLFQIntensity'], 'NUC': ['NUC_CTRL_R1_MaxLFQIntensity', 'NUC_CTRL_R2_MaxLFQIntensity', 'NUC_EGF_R1_MaxLFQIntensity', 'NUC_EGF_R2_MaxLFQIntensity']}\n"
     ]
    }
   ],
   "source": [
    "print(df_filtered2_norm_log.head())\n",
    "print(cito_cols)\n",
    "print(memb_cols)\n",
    "print(nuc_cols)\n",
    "print(compartments)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f38bc746-95dd-44fc-b0e0-a18dac7ccfc9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CITO Compartment - Kruskal-Wallis Test:\n",
      "Kruskal-Wallis Statistic: 0.957\n",
      "p-value: 3.279e-01\n",
      "\n",
      "MEMB Compartment - Kruskal-Wallis Test:\n",
      "Kruskal-Wallis Statistic: 58.803\n",
      "p-value: 1.742e-14\n",
      "\n",
      "NUC Compartment - Kruskal-Wallis Test:\n",
      "Kruskal-Wallis Statistic: 18.032\n",
      "p-value: 2.172e-05\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Computing differences between control and EGF treatment \n",
    "\n",
    "## Kruskal-Wallis test function\n",
    "def kruskal_test_between_conditions(compartments, condition1='_CTRL_', condition2='_EGF_'):\n",
    "    results = {}\n",
    "    \n",
    "    for group, cols in compartments.items():\n",
    "        # Filter columns based on the condition\n",
    "        ctrl_cols = [col for col in cols if condition1 in col]\n",
    "        egf_cols = [col for col in cols if condition2 in col]\n",
    "        \n",
    "        if ctrl_cols and egf_cols:\n",
    "            # Extract data for each condition and compartment\n",
    "            ctrl_data = df_filtered2_norm_log[ctrl_cols].values.flatten()  # Flatten to a 1D array\n",
    "            egf_data = df_filtered2_norm_log[egf_cols].values.flatten()  # Flatten to a 1D array\n",
    "            \n",
    "            # Perform Kruskal-Wallis test\n",
    "            stat, p_value = kruskal(ctrl_data, egf_data)\n",
    "            results[group] = {\n",
    "                'Kruskal-Wallis Statistic': stat,\n",
    "                'p-value': p_value\n",
    "            }\n",
    "            \n",
    "            # Display results\n",
    "            print(f'{group} Compartment - Kruskal-Wallis Test:')\n",
    "            print(f'Kruskal-Wallis Statistic: {stat:.3f}')\n",
    "            print(f'p-value: {p_value:.3e}\\n')\n",
    "        else:\n",
    "            print(f'Not enough data in {group} compartment to perform the test.')\n",
    "    \n",
    "    return results\n",
    "\n",
    "# Run Kruskal-Wallis test for each compartment\n",
    "kruskal_results = kruskal_test_between_conditions(compartments)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1438580d-2553-4438-9898-de7671b08caf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install scikit-posthocs "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7691cf94-4159-4f1d-86b7-ab6173d18f52",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      Condition  LogNormalizedValue\n",
      "0  MEMB_CTRL_R1_MaxLFQIntensity                 0.0\n",
      "1  MEMB_CTRL_R1_MaxLFQIntensity                 0.0\n",
      "2  MEMB_CTRL_R1_MaxLFQIntensity                 0.0\n",
      "3  MEMB_CTRL_R1_MaxLFQIntensity                 0.0\n",
      "4  MEMB_CTRL_R1_MaxLFQIntensity                 0.0\n",
      "                     Condition  LogNormalizedValue\n",
      "0  NUC_CTRL_R1_MaxLFQIntensity            0.008386\n",
      "1  NUC_CTRL_R1_MaxLFQIntensity            0.026602\n",
      "2  NUC_CTRL_R1_MaxLFQIntensity            0.032488\n",
      "3  NUC_CTRL_R1_MaxLFQIntensity            0.030143\n",
      "4  NUC_CTRL_R1_MaxLFQIntensity            0.000000\n"
     ]
    }
   ],
   "source": [
    "import scikit_posthocs as sp\n",
    "\n",
    "# Filter the data for MEMB and NUC compartments; melt = long format\n",
    "df_memb = df_filtered2_norm_log[[col for col in df_filtered2_norm_log.columns if col.startswith('MEMB_') and col.endswith('_MaxLFQIntensity')]]\n",
    "df_nuc = df_filtered2_norm_log[[col for col in df_filtered2_norm_log.columns if col.startswith('NUC_') and col.endswith('_MaxLFQIntensity')]]\n",
    "\n",
    "# Melt dataframes for compatibility with Dunn's test\n",
    "df_memb_melted = df_memb.melt(var_name=\"Condition\", value_name=\"LogNormalizedValue\")\n",
    "df_nuc_melted = df_nuc.melt(var_name=\"Condition\", value_name=\"LogNormalizedValue\")\n",
    "\n",
    "print(df_memb_melted.head())\n",
    "\n",
    "print(df_nuc_melted.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a875407c-6f03-440f-b17f-8999d9530d17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dunn's Test Results for MEMB Compartment (Bonferroni-adjusted p-values):\n",
      "\n",
      "Dunn's Test Results for NUC Compartment (Bonferroni-adjusted p-values):\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NUC_CTRL_R1_MaxLFQIntensity</th>\n",
       "      <th>NUC_CTRL_R2_MaxLFQIntensity</th>\n",
       "      <th>NUC_EGF_R1_MaxLFQIntensity</th>\n",
       "      <th>NUC_EGF_R2_MaxLFQIntensity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NUC_CTRL_R1_MaxLFQIntensity</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.025825</td>\n",
       "      <td>0.000521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NUC_CTRL_R2_MaxLFQIntensity</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.224791</td>\n",
       "      <td>0.009783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NUC_EGF_R1_MaxLFQIntensity</th>\n",
       "      <td>0.025825</td>\n",
       "      <td>0.224791</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NUC_EGF_R2_MaxLFQIntensity</th>\n",
       "      <td>0.000521</td>\n",
       "      <td>0.009783</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             NUC_CTRL_R1_MaxLFQIntensity  \\\n",
       "NUC_CTRL_R1_MaxLFQIntensity                     1.000000   \n",
       "NUC_CTRL_R2_MaxLFQIntensity                     1.000000   \n",
       "NUC_EGF_R1_MaxLFQIntensity                      0.025825   \n",
       "NUC_EGF_R2_MaxLFQIntensity                      0.000521   \n",
       "\n",
       "                             NUC_CTRL_R2_MaxLFQIntensity  \\\n",
       "NUC_CTRL_R1_MaxLFQIntensity                     1.000000   \n",
       "NUC_CTRL_R2_MaxLFQIntensity                     1.000000   \n",
       "NUC_EGF_R1_MaxLFQIntensity                      0.224791   \n",
       "NUC_EGF_R2_MaxLFQIntensity                      0.009783   \n",
       "\n",
       "                             NUC_EGF_R1_MaxLFQIntensity  \\\n",
       "NUC_CTRL_R1_MaxLFQIntensity                    0.025825   \n",
       "NUC_CTRL_R2_MaxLFQIntensity                    0.224791   \n",
       "NUC_EGF_R1_MaxLFQIntensity                     1.000000   \n",
       "NUC_EGF_R2_MaxLFQIntensity                     1.000000   \n",
       "\n",
       "                             NUC_EGF_R2_MaxLFQIntensity  \n",
       "NUC_CTRL_R1_MaxLFQIntensity                    0.000521  \n",
       "NUC_CTRL_R2_MaxLFQIntensity                    0.009783  \n",
       "NUC_EGF_R1_MaxLFQIntensity                     1.000000  \n",
       "NUC_EGF_R2_MaxLFQIntensity                     1.000000  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Perform Dunn's test for MEMB and NUC\n",
    "dunn_memb = sp.posthoc_dunn(df_memb_melted, val_col=\"LogNormalizedValue\", group_col=\"Condition\", p_adjust='bonferroni')\n",
    "dunn_nuc = sp.posthoc_dunn(df_nuc_melted, val_col=\"LogNormalizedValue\", group_col=\"Condition\", p_adjust='bonferroni')\n",
    "\n",
    "# Print results\n",
    "print(\"Dunn's Test Results for MEMB Compartment (Bonferroni-adjusted p-values):\")\n",
    "dunn_memb\n",
    "\n",
    "print(\"\\nDunn's Test Results for NUC Compartment (Bonferroni-adjusted p-values):\")\n",
    "dunn_nuc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "78826363-7a7d-4b0d-9b82-c0996602f067",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_56856/2660120854.py:45: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(data=data_to_plot, x='Column', y='LogNormalizedValue', palette='Set2')\n",
      "/tmp/ipykernel_56856/2660120854.py:45: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(data=data_to_plot, x='Column', y='LogNormalizedValue', palette='Set2')\n",
      "/tmp/ipykernel_56856/2660120854.py:45: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(data=data_to_plot, x='Column', y='LogNormalizedValue', palette='Set2')\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Kruskal-Wallis and Dunn test results to annotate\n",
    "kruskal_results = {\n",
    "    'CITO': (0.957, 0.3279),\n",
    "    'MEMB': (58.803, 1.742e-14),\n",
    "    'NUC': (18.032, 2.172e-05)\n",
    "}\n",
    "\n",
    "dunn_results = {\n",
    "    'MEMB': {\n",
    "        ('MEMB_CTRL_R1_MaxLFQIntensity', 'MEMB_EGF_R1_MaxLFQIntensity'): 1.110216e-06,\n",
    "        ('MEMB_CTRL_R1_MaxLFQIntensity', 'MEMB_EGF_R2_MaxLFQIntensity'): 5.910738e-08,\n",
    "        ('MEMB_CTRL_R2_MaxLFQIntensity', 'MEMB_EGF_R1_MaxLFQIntensity'): 1.918779e-06,\n",
    "        ('MEMB_CTRL_R2_MaxLFQIntensity', 'MEMB_EGF_R2_MaxLFQIntensity'): 1.075717e-07\n",
    "    },\n",
    "    'NUC': {\n",
    "        ('NUC_CTRL_R1_MaxLFQIntensity', 'NUC_EGF_R1_MaxLFQIntensity'): 0.025825,\n",
    "        ('NUC_CTRL_R1_MaxLFQIntensity', 'NUC_EGF_R2_MaxLFQIntensity'): 0.000521,\n",
    "        ('NUC_CTRL_R2_MaxLFQIntensity', 'NUC_EGF_R2_MaxLFQIntensity'): 0.009783\n",
    "    }\n",
    "}\n",
    "\n",
    "# Function to generate labels by removing the '_MaxLFQIntensity' suffix\n",
    "def generate_column_labels(cols):\n",
    "    return [col.replace('_MaxLFQIntensity', '') for col in cols]\n",
    "\n",
    "# Significance level function for easy marking\n",
    "def get_significance_label(pval):\n",
    "    if pval < 0.001:\n",
    "        return \"***\"\n",
    "    elif pval < 0.01:\n",
    "        return \"**\"\n",
    "    elif pval < 0.05:\n",
    "        return \"*\"\n",
    "    return \"ns\"\n",
    "\n",
    "# Function to plot boxplots with significance annotations\n",
    "def plot_boxplots_with_annotations(compartments, kruskal_results, dunn_results):\n",
    "    plt.figure(figsize=(18, 6))  # Adjust figure size for three compartments\n",
    "\n",
    "    for i, (group, cols) in enumerate(compartments.items(), 1):\n",
    "        plt.subplot(1, 3, i)  # 1 row, 3 columns for compartments\n",
    "        data_to_plot = df_filtered2_norm_log[cols].melt(var_name='Column', value_name='LogNormalizedValue')\n",
    "\n",
    "        # Plot box plot\n",
    "        sns.boxplot(data=data_to_plot, x='Column', y='LogNormalizedValue', palette='Set2')\n",
    "        \n",
    "        # Add dots to show individual data points\n",
    "        sns.stripplot(data=data_to_plot, x='Column', y='LogNormalizedValue', color='black', alpha=0.6, jitter=True)\n",
    "\n",
    "        # Kruskal-Wallis p-value annotation\n",
    "        kw_stat, kw_pval = kruskal_results[group]\n",
    "        plt.title(f'{group} Distribution\\nKruskal-Wallis p={kw_pval:.2e}')\n",
    "        \n",
    "        # Dunn's test annotations for specific pairwise comparisons\n",
    "        if group in dunn_results:\n",
    "            y_max = data_to_plot['LogNormalizedValue'].max()  # Get max y-value to position annotations\n",
    "            for (col1, col2), pval in dunn_results[group].items():\n",
    "                x1, x2 = cols.index(col1), cols.index(col2)\n",
    "                y = y_max + 0.2  # Adjust spacing for each comparison\n",
    "\n",
    "                # Draw the annotation line for significant comparisons\n",
    "                plt.plot([x1, x1, x2, x2], [y, y + 0.1, y + 0.1, y], lw=1.5, color='black')\n",
    "\n",
    "                # Add significance label\n",
    "                sig_text = get_significance_label(pval)\n",
    "                plt.text((x1 + x2) * 0.5, y + 0.15, sig_text, ha='center', va='bottom', color=\"black\", fontsize=12)\n",
    "                \n",
    "                # Update y_max for next annotation position\n",
    "                y_max += 0.4\n",
    "\n",
    "        # Rotate x labels for better readability using simplified labels\n",
    "        simplified_labels = generate_column_labels(cols)\n",
    "        tick_positions = range(len(cols))  # Set tick positions as the range of column indices\n",
    "        plt.xticks(tick_positions, labels=simplified_labels, rotation=90)\n",
    "        \n",
    "        # Labels and grid\n",
    "        plt.xlabel('Columns')\n",
    "        plt.ylabel('Log-Normalized Values')\n",
    "        plt.grid(axis='y', linestyle='--', alpha=0.6)\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "# Plot with significance annotations\n",
    "plot_boxplots_with_annotations(compartments, kruskal_results, dunn_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4802b384-cfcd-492f-ac68-d5cb25a78952",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'CITO': ['CITO_CTRL_Mean', 'CITO_EGF_Mean'], 'MEMB': ['MEMB_CTRL_Mean', 'MEMB_EGF_Mean'], 'NUC': ['NUC_CTRL_Mean', 'NUC_EGF_Mean']}\n",
      "\n",
      "Mean intensity values for each condition and compartment:\n",
      "\n",
      "CITO Compartment:\n",
      "CITO_CTRL_Mean:\n",
      "0    0.023942\n",
      "1    0.000000\n",
      "2    0.031831\n",
      "3    0.025842\n",
      "4    0.000000\n",
      "Name: CITO_CTRL_Mean, dtype: float64\n",
      "\n",
      "CITO_EGF_Mean:\n",
      "0    0.029293\n",
      "1    0.000000\n",
      "2    0.033928\n",
      "3    0.047359\n",
      "4    0.000118\n",
      "Name: CITO_EGF_Mean, dtype: float64\n",
      "\n",
      "\n",
      "MEMB Compartment:\n",
      "MEMB_CTRL_Mean:\n",
      "0    0.000000\n",
      "1    0.000000\n",
      "2    0.011066\n",
      "3    0.011728\n",
      "4    0.000000\n",
      "Name: MEMB_CTRL_Mean, dtype: float64\n",
      "\n",
      "MEMB_EGF_Mean:\n",
      "0    0.000000\n",
      "1    0.000000\n",
      "2    0.040642\n",
      "3    0.021287\n",
      "4    0.033922\n",
      "Name: MEMB_EGF_Mean, dtype: float64\n",
      "\n",
      "\n",
      "NUC Compartment:\n",
      "NUC_CTRL_Mean:\n",
      "0    0.004193\n",
      "1    0.031259\n",
      "2    0.016244\n",
      "3    0.034835\n",
      "4    0.000000\n",
      "Name: NUC_CTRL_Mean, dtype: float64\n",
      "\n",
      "NUC_EGF_Mean:\n",
      "0    0.013243\n",
      "1    0.032565\n",
      "2    0.031284\n",
      "3    0.040021\n",
      "4    0.000000\n",
      "Name: NUC_EGF_Mean, dtype: float64\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Re-do previous plots using mean intensity values for replicas\n",
    "# Calculate the mean of R1 and R2 for CTRL and EGF conditions for each protein\n",
    "mean_cols = {\n",
    "    'CITO': ['CITO_CTRL_R1_MaxLFQIntensity', 'CITO_CTRL_R2_MaxLFQIntensity', 'CITO_EGF_R1_MaxLFQIntensity', 'CITO_EGF_R2_MaxLFQIntensity'],\n",
    "    'MEMB': ['MEMB_CTRL_R1_MaxLFQIntensity', 'MEMB_CTRL_R2_MaxLFQIntensity', 'MEMB_EGF_R1_MaxLFQIntensity', 'MEMB_EGF_R2_MaxLFQIntensity'],\n",
    "    'NUC': ['NUC_CTRL_R1_MaxLFQIntensity', 'NUC_CTRL_R2_MaxLFQIntensity', 'NUC_EGF_R1_MaxLFQIntensity', 'NUC_EGF_R2_MaxLFQIntensity']\n",
    "}\n",
    "\n",
    "# Compute mean values for each compartment by averaging R1 and R2 for both CTRL and EGF\n",
    "df_mean = df_filtered2_norm_log.copy()\n",
    "\n",
    "for comp, cols in mean_cols.items():\n",
    "    # Calculate mean for CTRL and EGF\n",
    "    df_mean[f'{comp}_CTRL_Mean'] = df_filtered2_norm_log[[cols[0], cols[1]]].mean(axis=1)\n",
    "    df_mean[f'{comp}_EGF_Mean'] = df_filtered2_norm_log[[cols[2], cols[3]]].mean(axis=1)\n",
    "\n",
    "# Update compartments dictionary to use the new mean columns\n",
    "compartments_mean = {\n",
    "    'CITO': ['CITO_CTRL_Mean', 'CITO_EGF_Mean'],\n",
    "    'MEMB': ['MEMB_CTRL_Mean', 'MEMB_EGF_Mean'],\n",
    "    'NUC': ['NUC_CTRL_Mean', 'NUC_EGF_Mean']\n",
    "}\n",
    "print(compartments_mean)\n",
    "\n",
    "# Print the actual mean values calculated for each compartment\n",
    "print(\"\\nMean intensity values for each condition and compartment:\")\n",
    "for comp in compartments_mean:\n",
    "    print(f\"\\n{comp} Compartment:\")\n",
    "    for col in compartments_mean[comp]:\n",
    "        print(f\"{col}:\\n{df_mean[col].head()}\\n\")  # Display the first few mean values for each column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "474a437e-bcfc-4f1b-b83c-3d492b5c5847",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        Condition  LogNormalizedMean\n",
      "0  MEMB_CTRL_Mean           0.000000\n",
      "1  MEMB_CTRL_Mean           0.000000\n",
      "2  MEMB_CTRL_Mean           0.011066\n",
      "3  MEMB_CTRL_Mean           0.011728\n",
      "4  MEMB_CTRL_Mean           0.000000\n",
      "       Condition  LogNormalizedMean\n",
      "0  NUC_CTRL_Mean           0.004193\n",
      "1  NUC_CTRL_Mean           0.031259\n",
      "2  NUC_CTRL_Mean           0.016244\n",
      "3  NUC_CTRL_Mean           0.034835\n",
      "4  NUC_CTRL_Mean           0.000000\n",
      "Dunn's Test Results for MEMB Compartment (Bonferroni-adjusted p-values):\n",
      "\n",
      "Dunn's Test Results for NUC Compartment (Bonferroni-adjusted p-values):\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NUC_CTRL_Mean</th>\n",
       "      <th>NUC_EGF_Mean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NUC_CTRL_Mean</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.001114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NUC_EGF_Mean</th>\n",
       "      <td>0.001114</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               NUC_CTRL_Mean  NUC_EGF_Mean\n",
       "NUC_CTRL_Mean       1.000000      0.001114\n",
       "NUC_EGF_Mean        0.001114      1.000000"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Re-do processing and dunn test\n",
    "## Filter the data for MEMB and NUC compartments; melt = long format\n",
    "df_memb = df_mean[[col for col in df_mean.columns if col.startswith('MEMB_') and col.endswith('Mean')]]\n",
    "df_nuc = df_mean[[col for col in df_mean.columns if col.startswith('NUC_') and col.endswith('Mean')]]\n",
    "\n",
    "# Melt dataframes for compatibility with Dunn's test\n",
    "df_memb_melted = df_memb.melt(var_name=\"Condition\", value_name=\"LogNormalizedMean\")\n",
    "df_nuc_melted = df_nuc.melt(var_name=\"Condition\", value_name=\"LogNormalizedMean\")\n",
    "\n",
    "print(df_memb_melted.head())\n",
    "\n",
    "print(df_nuc_melted.head())\n",
    "\n",
    "## Perform Dunn's test for MEMB and NUC\n",
    "dunn_memb = sp.posthoc_dunn(df_memb_melted, val_col=\"LogNormalizedMean\", group_col=\"Condition\", p_adjust='bonferroni')\n",
    "dunn_nuc = sp.posthoc_dunn(df_nuc_melted, val_col=\"LogNormalizedMean\", group_col=\"Condition\", p_adjust='bonferroni')\n",
    "\n",
    "# Print results\n",
    "print(\"Dunn's Test Results for MEMB Compartment (Bonferroni-adjusted p-values):\")\n",
    "dunn_memb\n",
    "\n",
    "print(\"\\nDunn's Test Results for NUC Compartment (Bonferroni-adjusted p-values):\")\n",
    "dunn_nuc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ef69472a-f833-4c2c-9d7b-ce96341be039",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'MEMB': {('MEMB_CTRL_Mean', 'MEMB_EGF_Mean'): 1.238235e-07},\n",
       " 'NUC': {('NUC_CTRL_Mean', 'NUC_EGF_Mean'): 0.001114}}"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dictionary with p-values obtained from Dunn's test for MEMB and NUC\n",
    "dunn_results = {\n",
    "    'MEMB': {\n",
    "        ('MEMB_CTRL_Mean', 'MEMB_EGF_Mean'): 1.238235e-07\n",
    "    },\n",
    "    'NUC': {\n",
    "        ('NUC_CTRL_Mean', 'NUC_EGF_Mean'): 0.001114\n",
    "    }\n",
    "}\n",
    "dunn_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "90a385da-f8af-4d5d-a4d2-e946d77a49a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_56856/2407165645.py:21: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(data=data_to_plot, x='Column', y='LogNormalizedValue', palette='Set2')\n",
      "/tmp/ipykernel_56856/2407165645.py:21: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(data=data_to_plot, x='Column', y='LogNormalizedValue', palette='Set2')\n",
      "/tmp/ipykernel_56856/2407165645.py:21: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(data=data_to_plot, x='Column', y='LogNormalizedValue', palette='Set2')\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1200 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Function to convert p-values to significance labels\n",
    "def get_significance_label(pval):\n",
    "    if pval < 0.001:\n",
    "        return '***'\n",
    "    elif pval < 0.01:\n",
    "        return '**'\n",
    "    elif pval < 0.05:\n",
    "        return '*'\n",
    "    else:\n",
    "        return 'ns'\n",
    "\n",
    "# Function to plot boxplots with mean-based data and significance annotations\n",
    "def plot_boxplots_with_annotations_means(compartments, kruskal_results, dunn_results):\n",
    "    plt.figure(figsize=(20, 12))  # Adjust figure size for three compartments\n",
    "\n",
    "    for i, (group, cols) in enumerate(compartments.items(), 1):\n",
    "        plt.subplot(1, 3, i)  # 1 row, 3 columns for compartments\n",
    "        data_to_plot = df_mean[cols].melt(var_name='Column', value_name='LogNormalizedValue')\n",
    "\n",
    "        # Plot box plot with error bars\n",
    "        sns.boxplot(data=data_to_plot, x='Column', y='LogNormalizedValue', palette='Set2')\n",
    "        \n",
    "        # Add individual data points for visibility\n",
    "        sns.stripplot(data=data_to_plot, x='Column', y='LogNormalizedValue', color='black', alpha=0.6, jitter=True)\n",
    "\n",
    "        # Kruskal-Wallis p-value annotation\n",
    "        kw_stat, kw_pval = kruskal_results[group]\n",
    "        plt.title(f'{group} Distribution\\nKruskal-Wallis p={kw_pval:.2e}')\n",
    "        \n",
    "        # Dunn's test annotations for specific pairwise comparisons\n",
    "        if group in dunn_results:\n",
    "            y_max = data_to_plot['LogNormalizedValue'].max()  # Get max y-value to position annotations\n",
    "            for (col1, col2), pval in dunn_results[group].items():\n",
    "                x1, x2 = cols.index(col1), cols.index(col2)\n",
    "                y = y_max + 0.2  # Adjust spacing for each comparison\n",
    "\n",
    "                # Draw the annotation line for significant comparisons\n",
    "                plt.plot([x1, x1, x2, x2], [y, y + 0.1, y + 0.1, y], lw=1.5, color='black')\n",
    "\n",
    "                # Add significance label\n",
    "                sig_text = get_significance_label(pval)\n",
    "                plt.text((x1 + x2) * 0.5, y + 0.15, sig_text, ha='center', va='bottom', color=\"black\", fontsize=12)\n",
    "                \n",
    "                # Update y_max for next annotation position\n",
    "                y_max += 0.4\n",
    "\n",
    "        # Rotate x labels for better readability using simplified labels\n",
    "        tick_positions = range(len(cols))  # Set tick positions as the range of column indices\n",
    "        plt.xticks(tick_positions, labels=cols, rotation=90)\n",
    "        \n",
    "        # Labels and grid\n",
    "        plt.xlabel('Condition (Mean Intensity)')\n",
    "        plt.ylabel('Log-Normalized Values')\n",
    "        plt.grid(axis='y', linestyle='--', alpha=0.6)\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "# Call the function with the updated data and results\n",
    "plot_boxplots_with_annotations_means(compartments_mean, kruskal_results, dunn_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "2231ecab-eb57-4116-8182-5c040b5eb32e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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n6NKlC/r27YuPP/4Yq1evRt++fbFp0yaMGzcOn3/+Ofr164dFixahd+/euHfvnngbXnx8PN5//30xSGNpaYm//voLQ4cORUpKispthfPnz4eWlhYmTpyI5ORkLFy4EP3790dUVBQAYNq0aUhOTla69ba0WzePHTumMmgsSXl9Jho1aoSdO3e+1DGIiMqCY6TnOEbiGIljJI6RXgbHSBwjcYykrCyfibi4OAAQv4sKK5cx0kvNW3+LFb1VbufOnQIA4dtvv1Wq17t3b0EikSjddgBAACCcPn1aLLtz546gp6cn9OjRo0ztKOmWEUNDQ2HIkCEq5X/88YcAQNizZ0+Jxy58y0zjxo2FoUOHCoIgCE+fPhVkMpmwfv16tbcUde/eXZDJZMKtW7fEsocPHwrGxsZCmzZtxDIPDw+hc+fOJbbhRW5JHD16tFCjRg3xts29e/cKAIRz584p1SvLLYmzZ88WDA0NhevXryuVf/3114JUKhVvB4qOjhYACCYmJkJCQoJSXW9vb8Hd3V3IysoSywoKCoQWLVoIzs7OYtm4ceNUbj1JSEgQTE1Ny3RL4rVr14TExEQhOjpaWLt2raCrqytYW1uLtx16eXkJAIQ1a9Yo7R8UFCQAEDZu3CiW5eTkCM2bNxeMjIyElJQUQRBKviVR074q3j+HDh0SyxTt2rBhg1iWnZ0t2NjYCL169RLLPvroI41u6SpKcc5q1aqJfREEQfj1118FAMLy5cvF9jo7Ows+Pj7ie0kQBCEjI0NwdHQUPvjgA7GsuFsSFbdV/fnnn4IgCMLFixcFAMLHH38sNGvWTKzXrVs3wdPTU3yu6fstMjJSACBs2rRJqd6ePXtUyu3t7QUAwpEjR8SyhIQEQVdXt9jbCRV69OghABCePn1aYj11NLklMSQkREhMTBQePnwo7NmzR3BychIkEolw8uRJpfovektiXl6eym1zT58+FaytrZW+IxWfXwsLC+HJkydi+a5duwQAwm+//SaWNWzYULC1tRWSkpLEMsV3jaa3JCr+LSj6GDFihCAIgpCcnCwAELp3766y/9OnT4XExETxkZGRIW5TfAcUfZTlljlBUP33pTy+37KysoT8/HylfaOjowVdXV0hMDBQLCvplkTFa/fzzz+LZf/9958AQNDS0hJOnDghlv/9998qxxk6dKhga2srPHr0SOm4ffv2FUxNTcXXUvH+dHFxUXr/LF++XAAgXLp0SSwryy2Jubm5gkQiUfu5K/r9HRMTI4SEhAj6+vqCpaVlibeNa9KGuXPnCgCE+Ph4jdpKRFRWHCNxjCQIHCNxjCTHMVLxOEZSj2Ok5zhGeu5lxkiCIP+udHV1FRwdHYXc3FyV7eUxRmLaFg39+eefkEqlGDNmjFL5V199BUEQlG41AoDmzZujUaNG4vOaNWvio48+wt9//62yAuyLyszMhK6urkq5np6euF1T/fr1w/bt25GTk4Pw8HBIpVK1v4zn5+dj79696N69O2rVqiWW29raol+/fjh69Ki4mrmZmRmuXLmCGzdulLVrxcrLy8OWLVvwySefiLcvtm/fHlZWVti0adMLH3fr1q1o3bo1qlSpgkePHomPDh06ID8/X+V20l69eom37AHyXzcPHjyIPn36IDU1Vdz/8ePH8PHxwY0bN/DgwQMA8vfS+++/r7T4kKWlJfr371+mNtetWxeWlpZwdHTEiBEj4OTkhD/++AMGBgZiHV1dXQwePFhpvz///BM2Njbw8/MTy3R0dDBmzBikpaXh8OHDJZ63LH0tjpGREQYMGCA+l8lkaNq0KW7fvi2WmZmZ4f79+2pvFdPEp59+qrQgRO/evWFra4s///wTAHD+/HncuHED/fr1w+PHj8V+pKenw9vbG0eOHCn1NlFPT08YGRmJ74/IyEhUr14dn376Kc6ePYuMjAwIgoCjR4+KvxwDmr/ftm7dClNTU3zwwQdK9Ro1agQjIyOVW+5cXV2VzmNpaYm6desqva7qKD6zFbXI4JAhQ2BpaQk7Ozv4+voiOTkZP/30k3hb2suSSqXigksFBQV48uQJ8vLy0LhxY5w9e1al/ieffKL067XiNVO8TrGxsTh//jwGDRqktHDNBx98AFdXV43b5eDggH379qk8FL/qK153db/Qt23bFpaWluJDcft2Ydu2bVM67st8Bxb2Mt9vurq64ky//Px8PH78GEZGRqhbt67av0VxjIyMlFZgr1u3LszMzODi4qI0A0Xx/4q/nSAI2LZtG7p27QpBEJQ+Nz4+PkhOTlZpx+DBg5UW7Cr6fiirJ0+eQBCEEmdIKL6/HRwcMGTIEDg5OeGvv/5S+v5+EYpzqpvNQ0RUEThGkuMYSY5jJI6RAI6RNMUxEsdIHCMpe9Ex0ujRo3H16lWsXLkS2tqqCVbKY4zEtC0aunPnDuzs7FS+OBUry9+5c0epXN0q7nXq1EFGRgYSExPLZfVkfX19tTn7FCu/l+UWt759+2LixIn466+/sGnTJnTp0kXtPxKJiYnIyMhA3bp1Vba5uLigoKAA9+7dg5ubGwIDA/HRRx+hTp06qF+/Pnx9fTFw4EDxtrYXsXfvXiQmJqJp06ZK+ZbatWuHX375BQsWLFC5RVMTN27cwMWLF5W+DAtLSEhQeu7o6Kj0/ObNmxAEAf/73//wv//9r9hjVKtWDXfu3FF7+5G617Qk27Ztg4mJCXR0dFC9enW1eaOqVaumsor7nTt34OzsrPI6FfdeLqosfS1O9erVVXI3VqlSBRcvXhSfT5kyBfv370fTpk3h5OSEjh07ol+/fuJtfaUp+hmUSCRwcnISb/1RDFgGDRpU7DGSk5NL/HKXSqVo3rw5IiMjAcgvDFu3bo1WrVohPz8fJ06cgLW1NZ48eaJ0wabp++3GjRtITk5We2tw4XoKNWvWVKlTpUoVldx/RZmYmAAAUlNTYWZmVmLdFzFjxgy0bt0aaWlp2LFjBzZv3vxCn9OSrF+/HkuWLMF///2H3NxcsbzoZxVQfZ0Uf2PF66T4DKj7Hi/LBY6hoSE6dOhQ7HbFd2xaWprKtrVr1yI1NRXx8fFKg6jC2rRpo/a2tJf1Mt9vBQUFWL58OVatWoXo6GilQEjh26VLo+47wtTUVCWvoeLCXfG3S0xMRFJSEtatW4d169YV29bCSns/vCihSK7fwhTf34mJifjuu+8QHR390relFz6nprlxiYheFsdIchwjyXGMxDESwDGSpjhGUo9jpOJxjKRq0aJF+OGHHzB79mx8+OGHJZ7zZcZIDJ6/wWxtbREbG6tSriizs7Mr07Hatm2LJUuW4J9//sG2bdteun1t2rTBrVu3sGvXLuzduxc//vgjli1bhjVr1uCzzz57oWMqfjUsbpGew4cPo127dmU+bkFBAT744ANMnjxZ7fY6deooPS/6AVb8+j5x4kT4+PioPYaTk1OZ21USTf5RKI9gTFHl0VepVKq2vPAXqYuLC65du4bff/8de/bswbZt27Bq1SrMmDEDs2bNesHWP6fox6JFi1TyvSmUlrMLAFq1aoU5c+YgKysLkZGRmDZtGszMzFC/fn1ERkaKOSMLXxhq+n4rKCgoccZQ0QtLTV5XderVqwcAuHTpklI7y4u7u7t4gdS9e3dkZGRg2LBhaNWqVbks8rJx40b4+/uje/fumDRpEqysrCCVSjFv3jy1C+686OtU3kxNTWFra4vLly+rbFMMHhUDmVfpZb7f5s6di//9738YMmQIZs+eDXNzc2hpaWHcuHFlWvCruL9RaX87xTkGDBhQ7KCvaHCivN8P5ubmkEgkJV5YFv7+7tq1K9zd3dG/f3+cOXPmpQZNinNWxICBiOhNwTGSKo6RlHGMVDyOkZ7jGEmOYyQ5jpGUj1lWFTFGCgsLw5QpU/D5559j+vTpxR63PMZIDJ5ryN7eHvv370dqaqrSbIP//vtP3F6Yutvwrl+/DgMDg2J/SS2rhg0bIjIyEgUFBUpvpKioKBgYGKhczJSmX79++Oyzz2BmZlbsLzaWlpYwMDDAtWvXVLb9999/0NLSUvqiNzc3x+DBgzF48GCkpaWhTZs2CAgIEC8My/LLT3p6Onbt2oVPPvkEvXv3Vtk+ZswYbNq0qcQLw+LOV7t2baSlpZX4C2hJFLdn6ujolHoMe3t7te8Pda9pRbC3t8fFixdV3jdF38vFvVZl6evLMjQ0xCeffIJPPvkEOTk56NmzJ+bMmYOpU6eKt94Wp+hrLAgCbt68Kf6joJiFYmJiUmo/Snqftm7dGjk5Ofjll1/w4MED8cKqTZs24oVhnTp1xAtExbk1eb/Vrl0b+/fvR8uWLSvkIl+ha9eumDdvHjZu3FghF4ZFzZ8/Hzt27MCcOXOwZs2alz5eeHg4atWqhe3btyv9rWbOnPlCx1N8Bl7F57Rz58748ccfcfLkSaXblF8nZfnMh4eHo127dggODlYqT0pKUrpYqaiZ0ZaWljA2NkZ+fn65fj+Vpb3a2tqoXbs2oqOjNapvZGSEmTNnYvDgwfj111+VbsUsq+joaFStWrXcrjOIiErDMZIcx0jqcYxUMThG4hhJExwjVSyOkSp3jLRr1y589tln6Nmzp9r0PYWVxxiJOc819OGHHyI/Px8rV65UKl+2bBkkEom4+rXC8ePHlW5buXfvHnbt2oWOHTsW+wtOWfXu3Rvx8fHYvn27WPbo0SNs3boVXbt2VZvrr7TjzZw5E6tWrVK5jU1BKpWiY8eO2LVrl9KvffHx8fj555/RqlUr8famx48fK+1rZGQEJycnpdsoFaspJyUlldq+HTt2ID09HaNGjULv3r1VHl26dMG2bdvU3qZZ+HzqztWnTx8cP34cf//9t8q2pKQk5OXlldg2KysrtG3bFmvXrlU70yUxMVH8/w8//BAnTpzAyZMnlbaXVy6u0nz44YeIi4vDli1bxLK8vDysWLECRkZG8PLyAgAxr1TR16ssfX0ZRd8/MpkMrq6uEARB6Zaz4mzYsAGpqani8/DwcMTGxoqf1UaNGqF27dpYvHix2lvCCvejpPdps2bNoKOjgwULFsDc3Fxcsb1169Y4ceIEDh8+rHKxpen7rU+fPsjPz8fs2bNV6uXl5Wn0udFE8+bN4evrix9//FHtKtQ5OTmYOHFiuZwLkF/w9urVC2FhYeKq2C9D8Z1a+FfwqKgoHD9+/IWOZ2tri4YNG2L9+vVITk4Wy/ft24erV6++XGOLmDx5MgwMDDBkyBDEx8erbH/VMz3UKctnXiqVqrR569atKjk+y/LdXxZSqRS9evXCtm3b1M5WedHvJ0NDQ6X3QmmaN2+O06dPa1y/f//+qF69OhYsWPAizROdOXMGzZs3f6ljEBGVBcdIchwjqccx0nMcI3GMVBqOkZ7jGCmpXNv6to2Rjhw5gr59+6JNmzbYtGlTqXfulscYiTPPNdS1a1e0a9cO06ZNQ0xMDDw8PLB3717s2rUL48aNU8mlVr9+ffj4+GDMmDHQ1dXFqlWrAECjW6l+++03XLhwAQCQm5uLixcv4ttvvwUAdOvWTfxVuHfv3nj//fcxePBgXL16FVWrVsWqVauQn5//QrdsmZqaIiAgoNR63377Lfbt24dWrVph5MiR0NbWxtq1a5GdnY2FCxeK9VxdXdG2bVs0atQI5ubmOH36NMLDwzF69GixjmLBoDFjxsDHxwdSqbTYWXebNm2ChYUFWrRooXZ7t27d8MMPP+CPP/5Az5491dZp1KgRVq9ejW+//RZOTk6wsrJC+/btMWnSJOzevRtdunSBv78/GjVqhPT0dFy6dAnh4eGIiYkp9RaP77//Hq1atYK7uzuGDRuGWrVqIT4+HsePH8f9+/fFv+nkyZPx008/wdfXF2PHjoWhoSHWrVsnznaoaMOHD8fatWvh7++PM2fOwMHBAeHh4fjnn38QFBQkzhrS19eHq6srtmzZgjp16sDc3Bz169dH/fr1Ne7ry+jYsSNsbGzQsmVLWFtb499//8XKlSvRuXNnjRZtMTc3R6tWrTB48GDEx8cjKCgITk5OGDZsGABAS0sLP/74Izp16gQ3NzcMHjwY1apVw4MHD3Do0CGYmJjgt99+A/D8fTpt2jT07dsXOjo66Nq1KwwNDWFgYIBGjRrhxIkT6Nq1q/jra5s2bZCeno709HSVC0NN329eXl4YMWIE5s2bh/Pnz6Njx47Q0dHBjRs3sHXrVixfvlztDKMXsWHDBnTs2BE9e/ZE165d4e3tDUNDQ9y4cQObN29GbGwsFi9eXC7nAuSvwa+//oqgoCDMnz9fLM/NzRW/7wozNzfHyJEj1R6rS5cu2L59O3r06IHOnTsjOjoaa9asgaurq9qLfk3MmzcPnTt3RqtWrTBkyBA8efIEK1asgJubm8bHTE5OxsaNG9VuU+Toc3Z2xs8//ww/Pz/UrVsX/fv3h4eHBwRBQHR0NH7++WdoaWmhevXqL9SP8qLpZ75Lly4IDAzE4MGD0aJFC1y6dAmbNm1SWjwNkA8OzMzMsGbNGhgbG8PQ0BDNmjVTm3+xrObPn49Dhw6hWbNmGDZsGFxdXfHkyROcPXsW+/fvx5MnT8p8zEaNGmHLli2YMGECmjRpAiMjI3Tt2rXY+h999BF++uknXL9+XaMZjjo6Ohg7diwmTZqEPXv2wNfXFwBw8eJF7N69G4A8r2JycrL4+fDw8FBqQ0JCAi5evIhRo0aVuX9ERC+KY6TnOEZSj2MkjpE4RtIcx0gcI3GM9Jy6MdKdO3fQrVs3SCQS9O7dG1u3blXap0GDBkopaMptjCSQWqNGjRKKvjypqanC+PHjBTs7O0FHR0dwdnYWFi1aJBQUFCjVAyCMGjVK2Lhxo+Ds7Czo6uoKnp6ewqFDhzQ696BBgwQAah+hoaFKdZ88eSIMHTpUsLCwEAwMDAQvLy/h1KlTGp3Hy8tLcHNzK7HOoUOHBADC1q1blcrPnj0r+Pj4CEZGRoKBgYHQrl074dixY0p1vv32W6Fp06aCmZmZoK+vL9SrV0+YM2eOkJOTI9bJy8sTvvzyS8HS0lKQSCQqr7lCfHy8oK2tLQwcOLDYtmZkZAgGBgZCjx49BEEQhNDQUAGAEB0dLdaJi4sTOnfuLBgbGwsABC8vL3FbamqqMHXqVMHJyUmQyWRC1apVhRYtWgiLFy8W2xwdHS0AEBYtWqS2Dbdu3RI+/fRTwcbGRtDR0RGqVasmdOnSRQgPD1eqd/HiRcHLy0vQ09MTqlWrJsyePVsIDg5Waa86M2fOFAAIiYmJJdYr6e8bHx8vDB48WKhataogk8kEd3d3lfeWIAjCsWPHhEaNGgkymUwAIMycObNMfVW8fwq/94tr16BBgwR7e3vx+dq1a4U2bdoIFhYWgq6urlC7dm1h0qRJQnJycon9Vpzzl19+EaZOnSpYWVkJ+vr6QufOnYU7d+6o1D937pzQs2dP8Tz29vZCnz59hAMHDijVmz17tlCtWjVBS0tL5e80adIkAYCwYMECpX2cnJwEAMKtW7dUzqvJ+01h3bp1QqNGjQR9fX3B2NhYcHd3FyZPniw8fPhQrGNvby907txZ5TxeXl5K7/OSZGRkCIsXLxaaNGkiGBkZCTKZTHB2dha+/PJL4ebNm2r36dy5s9LfrbDivj8U2rZtK5iYmAhJSUmCIJT83Ve7du1i211QUCDMnTtXsLe3F79vf//9d5X3VEmf36Lvb0EQhG3btgkuLi6Crq6u4OrqKmzfvl3lmMXx8vIqti/qvudu3rwpfPHFF4KTk5Ogp6cnfmd+/vnnwvnz55XqavodUBpDQ0Nh0KBB4vPy+H7LysoSvvrqK8HW1lbQ19cXWrZsKRw/flzt+3DXrl2Cq6uroK2trfTvW3HfEcW9xxX/5hYWHx8vjBo1SqhRo4ago6Mj2NjYCN7e3sK6devEOsW9PxWvQ+HvxLS0NKFfv36CmZmZAKDU90B2drZQtWpVYfbs2UrlJf3tkpOTBVNTU6XXSfHvmLpH4b+dIAjC6tWrBQMDAyElJaXEthERvQyOkeQ4RuIYiWMkOY6ROEbiGIljpFc5RlK0r7hH0fdreY2RJILwGtzv8JaRSCQYNWqUyu2LRERE9G6YPXs2QkNDcePGjXJLRVAST09PtG3bFsuWLavwcxERvQiOkYiIiN5tb+oYiTnPiYiIiMrZ+PHjkZaWhs2bN1f4ufbs2YMbN25g6tSpFX4uIiIiIiKiF/GmjpGY85yIiIionBkZGSEhIeGVnMvX1/eFc1cSERERERG9Cm/qGIkzz4mIiIiIiIiIiIiIimDOcyIiIiIiIiIiIiKiIjjznIiIiIiIiIiIiIioCAbPiYiIiIiIiIiIiIiKeOcWDC0oKMDDhw9hbGwMiURS2c0hIiIiqnCCICA1NRV2dnbQ0uLcCSJSxjESERERvWs0HSO9c8Hzhw8fokaNGpXdDCIiIqJX7t69e6hevXplN4OIXjMcIxEREdG7qrQx0jsXPDc2NgYgf2FMTEwquTVEREREFS8lJQU1atQQr4OIiArjGImIiIjeNZqOkd654LniNkQTExNeGBIREdE7hekYiEgdjpGIiIjoXVXaGIlJL4mIiIiIiIiIiIiIimDwnIiIiIiIiIiIiIioCAbPiYiIiIiIiIiIiIiKeOdynhMRERGRqvz8fOTm5lZ2M4ioBDo6OpBKpZXdDCIiIqJ3BoPnRERERO8wQRAQFxeHpKSkym4KEWnAzMwMNjY2XACYiIiI6BVg8JyIiIjoHaYInFtZWcHAwIABOaLXlCAIyMjIQEJCAgDA1ta2kltERERE9PZj8JyIiIjoHZWfny8Gzi0sLCq7OURUCn19fQBAQkICrKysmMKFiIiIqIJxwVAiIiKid5Qix7mBgUElt4SINKX4vHKNAiIiIqKKx+A5ERER0TuOqVqI3hz8vBIRERG9OgyeExEREREREREREREVweA5ERERERHB398f3bt3r+xmEBERERG9Nhg8JyIiIiKqJP7+/pBIJJBIJJDJZHByckJgYCDy8vJe6pgvEgRfvnw5wsLCXvi8RERERERvG+3KbgARERER0bvM19cXoaGhyM7Oxp9//olRo0ZBR0cHU6dOVaqXk5MDmUxWYe0wNTWtsGMTEREREb2JOPOciIiIiKgS6erqwsbGBvb29vjiiy/QoUMH7N69W5xBPmfOHNjZ2aFu3boAgEuXLqF9+/bQ19eHhYUFhg8fjrS0NABAQEAA1q9fj127dokz2iMiIgAA9+7dQ58+fWBmZgZzc3N89NFHiImJEdtRdMZ627ZtMWbMGEyePBnm5uawsbFBQEDAK3pViIiIiIgqH4PnRERERESvEX19feTk5AAADhw4gGvXrmHfvn34/fffkZ6eDh8fH1SpUgWnTp3C1q1bsX//fowePRoAMHHiRPTp0we+vr6IjY1FbGwsWrRogdzcXPj4+MDY2BiRkZH4559/YGRkBF9fX/Fc6qxfvx6GhoaIiorCwoULERgYiH379r2S14GIiIiIqLIxbQsRERER0WtAEAQcOHAAf//9N7788kskJibC0NAQP/74o5iu5YcffkBWVhY2bNgAQ0NDAMDKlSvRtWtXLFiwANbW1tDX10d2djZsbGzEY2/cuBEFBQX48ccfIZFIAAChoaEwMzNDREQEOnbsqLZNDRo0wMyZMwEAzs7OWLlyJQ4cOIAPPvigIl8KIiIiIqLXAmeeExERERFVot9//x1GRkbQ09NDp06d8Mknn4jpUdzd3ZXynP/777/w8PAQA+cA0LJlSxQUFODatWvFnuPChQu4efMmjI2NYWRkBCMjI5ibmyMrKwu3bt0qdr8GDRooPbe1tUVCQsIL9pSIiIiI6M3CmedERERERJWoXbt2WL16NWQyGezs7KCt/fwSvXCQ/GWkpaWhUaNG2LRpk8o2S0vLYvfT0dFRei6RSFBQUFAubSIiIiIiet0xeE5EREREVIkMDQ3h5OSkUV0XFxeEhYUhPT1dDKz/888/0NLSEhcUlclkyM/PV9rvvffew5YtW2BlZQUTE5Py7QARERER0VuKaVuIiIiIiN4Q/fv3h56eHgYNGoTLly/j0KFD+PLLLzFw4EBYW1sDABwcHHDx4kVcu3YNjx49Qm5uLvr374+qVavio48+QmRkJKKjoxEREYExY8bg/v37ldwrIiIiIqLXE4PnRERERERvCAMDA/z999948uQJmjRpgt69e8Pb2xsrV64U6wwbNgx169ZF48aNYWlpiX/++QcGBgY4cuQIatasiZ49e8LFxQVDhw5FVlYWZ6ITERERERVDIgiCUNmNeJVSUlJgamqK5ORkDhSIiIjonVDc9U9WVhaio6Ph6OgIPT29SmwhEWmqIj63HCMRERHRu0bT6x/OPCciIiIiIiIiIiIiKoLBcyIiIiIiIiIiIiKiIrQruwFvo3xBwImkNCTk5MFKpo33zYwglUgqu1lEREREREREREREpCEGz8vZH4lJmH7jAWKzc8UyW10dfOtcDZ0tzSqvYURERERERERERESkMaZtKUd/JCbhs8sxSoFzAIjLzsVnl2PwR2JS5TSMiIiIiIiIiIiIiMqEwfNyki8ImH7jAQQ12xRl/7vxAPmCuhpERERERERERERE9Dph8LycnEhKU5lxXpgA4GF2LiKfpr66RhERERERERERERHRC2HO83KSkJOnUb2+F26jmq4O7PV1Ya8vg4Oe/L/2+rpw0JfBTFsKCRcXJSIiIiIiIiIiIqpUDJ6XEyuZ5i/lg+xcPMjOxbEk1W0m2lrPAurPguv6urDXk8FeXwY7XRm0tRhYJyIiIiIiIiIiIqpoDJ6Xk/fNjGCrq4O47Fy1ec8lAGx1dfBnI2c8yMpFTGY2YjJzcCcrG3cyc3AnMwdxOblIySvAxbRMXEzLVDmGtgSooScPqNd89t/CAXZDbWmF95OIiIjobRAREQF/f3/ExMRUdlMqTFhYGMLCwhAREVHZTSEiIiIieiNVas7zI0eOoGvXrrCzs4NEIsHOnTtL3SciIgLvvfcedHV14eTkhLCwsApvpyakEgm+da4GQB4oL0zxfLZzNdjoytDI1BC9bMzxlaMNvnOxx673nHG+pRtut2mAw03rYYO7IwKd7DC0WlV4m5vA2UAXuloS5AlAdGYODj1JxfqHjzHr1kMMuRyD9qeuoXbkJdQ/ehldzlzHqKt3sDA6FltinyAqKQ3x2bkQuFApERERVaD8AgHHbz3GrvMPcPzWY+QXvHnXHhKJRHyYmpqiZcuWOHjwoFKd77//Hg4ODtDT00OzZs1w8uRJleMcP34c7du3h6GhIUxMTNCmTRtkZqpOjMjOzkbDhg0hkUhw/vx5sTwmJkapLYrHiRMn1LZ78+bNkEgk6N69e4n9K3pcCwsLdOzYEefOnSv2nIUfikC8RCJBlSpVkJWVpXT8U6dOiXXVqVevHnR1dREXF1diO4tq27Ytxo0bp1IeFhYGMzMz8XlAQAAaNmxYbL8Vr3FF9aFt27aQSCTYvHmzUnlQUBAcHBxK7CMRERERvZ4qdeZ5eno6PDw8MGTIEPTs2bPU+tHR0ejcuTM+//xzbNq0CQcOHMBnn30GW1tb+Pj4vIIWl6yzpRl+rO+A6TceKC0eaqurg9nO1dDZ0qzE/Q2kWqhrqIe6hnoq2woEAbHZubiTmYOYrGzczcxBTOazWetZ2XiSm49HuXl4lJuH0ykZKvvra0lQ89kMdcWMdUWe9Rp6Muhqce1YIiIiejF7Lsdi1m9XEZv8PBBpa6qHmV1d4VvfthJbVnahoaHw9fXFo0ePMG3aNHTp0gWXL19GrVq1sGXLFkyYMAFr1qxBs2bNEBQUBB8fH1y7dg1WVlYA5IFzX19fTJ06FStWrIC2tjYuXLgALTXXWpMnT4adnR0uXLigti379++Hm5ub+NzCwkKlTkxMDCZOnIjWrVtr3EfFce/fv48xY8agU6dOuHLlCmJjY8U6ixcvxp49e7B//36xzNTUFFFRUQAAY2Nj7NixA35+fuL24OBg1KxZE3fv3lU559GjR5GZmYnevXtj/fr1mDJlisbtrSgV0Qc9PT1Mnz4dvXr1go6OToW2n4iIiIgqXqUGzzt16oROnTppXH/NmjVwdHTEkiVLAAAuLi44evQoli1b9loEzwF5AN23qilOJKUhIScPVjJtvG9mBOlLLgKqJZGgmp4M1fRkaAEjle0pefm4o0gFk5mNO1nPg+sPsnOQWSDgWnoWrqVnqewrAWCnq4Oaz1LAFF7E1F5fhipcxJSIiIiKsedyLL7YeFYlbV1ccha+2HgWqwe8V2EB9PDwcMyaNQs3b96EgYEBPD09sWvXLowaNQpJSUnw9PTEypUrkZ2djX79+uG7776DTCYr8ZhmZmawsbGBjY0NVq9ejWrVqmHfvn0YMWIEli5dimHDhmHw4MEA5Nemf/zxB0JCQvD1118DAMaPH48xY8aIzwGgbt26Kuf566+/sHfvXmzbtg1//fWX2rZYWFjAxsam2Lbm5+ejf//+mDVrFiIjI5GUlFTaS6Z0XBsbGyxevBgtW7bE6dOnla6njYyMoK2tXez5Bw0ahJCQEDHwnJmZic2bN2PMmDGYPXu2Sv3g4GD069cPXl5eGDt27GsRPK+IPvj5+WH37t344YcfMHLkyArvAxERERFVrDcq5/nx48fRoUMHpTIfHx+1t3FWJqlEgpZVjF/pOU20pXA3NoC7sYHKttwCAQ+ynwfTC89Yj8nMQXp+gbiI6fGkdDXHli9iqgiu2+vLxOfVuIgpERHRW0UQBGTm5mtUN79AwMzdV9Su9yJA/gN9wO6raOlUFVINrhf0dTT/wT42NhZ+fn5YuHAhevTogdTUVERGRoqp6g4cOAA9PT1EREQgJiYGgwcPhoWFBebMmaPR8QFAX18fAJCTk4OcnBycOXMGU6dOFbdraWmhQ4cOOH78OAAgISEBUVFR6N+/P1q0aIFbt26hXr16mDNnDlq1aiXuFx8fj2HDhmHnzp0wMFC9dlPo1q0bsrKyUKdOHUyePBndunVT2h4YGAgrKysMHToUkZGRGveruD6WxcCBA7Fo0SLcvXsXNWvWxLZt2+Dg4ID33ntPpW5qaiq2bt2KqKgo1KtXD8nJyYiMjCzTbPmKUBF9MDExwbRp0xAYGIhBgwbB0NDwVXWHiIiIiCrAGxU8j4uLg7W1tVKZtbU1UlJSkJmZKV78F5adnY3s7GzxeUpKCgAgLy8PeXl5AOQDHy0tLRQUFKCgoECsqyjPz89XyhleXLlUKh/wKY5buByQzw7SpFxbWxuCICiVSyQSSKVSlTYWV164T5KCAlTXkaK6jgHamBkptV0QBDzJzcfdnFzczcpFdEYW7mTm4G5WDmKychCfk1fqIqbVdWWw15M9X7xUXxc1dLVhr6cDw2d9LO8+vY1/J/aJfWKf2Cf2iX2qqD4VrVOSzNx8uM74W+P6JREAxKVkwT1gr0b1rwb6wECm2eVpbGws8vLy0LNnT9jb2wMA3N3dxe0ymQwhISEwMDCAm5sbAgMDMWnSJMyePVttCpWiMjIyMH36dEilUnh5eeHRo0fIz89Xey3633//AQBu374NQJ57e/HixWjYsCE2bNgAb29vXL58Gc7OzhAEAf7+/vj888/RuHFjtQuWGhkZYcmSJWjZsiW0tLSwbds2dO/eHTt37hQD6EePHkVwcLBSrvSySkpKwuzZs2FkZISmTZuWaV8rKyt06tQJYWFhmDFjBkJCQjBkyBC1dTdv3gxnZ2cxBU3fvn0RHBxcpuD5qlWr8OOPPyqV5eXlQU9PNd1hZfdh5MiRWL58OZYuXYr//e9/L9y+isQxEvvEPrFP7BP7xD6xT+96nzQdI71RwfMXMW/ePMyaNUul/Ny5c+JMEEtLS9SuXRvR0dFITEwU61SvXh3Vq1fH9evXkZycLJbXqlULVlZWuHz5stLiT/Xq1YOZmRnOnTun9Ado0KABZDIZTp8+rdSGxo0bIycnBxcvXhTLpFIpmjRpguTkZHEgBshnBXl4eODRo0fiwAyQ5550cXHBw4cPcf/+fbH8RfrUxMYKFy5ceN4nKeDgUQfJugbYf/EyHuYLiCuQIF6Q4KlMH/ezc5EtCIh5FmhHkurrbwoBNloC6ltawFpSAO3HibCRyMvs9PXQsGHDCu3T2/h3Yp/YJ/aJfWKf2Key9qkswfM3hYeHB7y9veHu7g4fHx907NgRvXv3RpUqVcTthWd1N2/eHGlpabh3754YbFfHz88PUqkUmZmZsLS0RHBwMBo0aICHDx+W2ibFwGDEiBFiahdPT08cOHAAISEhmDdvHlasWIHU1FSlGexFVa1aFRMmTBCfN2nSBA8fPsSiRYvQrVs3pKamYuDAgfjhhx9QtWrVUttVVIsWLaClpYX09HQxl3vRHwU0MWTIEIwdOxYDBgzA8ePHsXXrVrUz4ENCQjBgwADx+YABA+Dl5YUVK1bA2FizuzX79++PadOmKZVt374dc+fOLXO7K7oPurq6CAwMxJdffokvvvjipdpXUThGYp/YJ/aJfWKf2Cf26V3vk6ZjJIlQOJxfiSQSCXbs2IHu3bsXW6dNmzZ47733EBQUJJaFhoZi3LhxSi94YepmVdSoUQOPHz+GiYkJgDfj15DX8ReeAkHAg2cpYO5m5eBOVg7uZeci5llqmKd5Jb8J9bQkqKmnC3t9HdjrylBTnL0ug4OhPnSAN+5Xq9fx78Q+sU/sE/vEPrFPqampMDc3R3Jysnj9AwBZWVmIjo6Go6OjOIO3LGlbTkY/gX/oqVLrhQ1ugqaO5qXWK0vaFkDe1mPHjmHv3r3YsWMH4uLiEBUVhVmzZuHu3bs4ePCgWPfChQto2LAhYmJiYG9vj4iICPj7+yvN/JZIJFi9ejU6dOgAU1NTWFpaittycnJgYGCA8PBwpevVQYMGISkpCbt27UJ0dDRq1aqFn376SSnQ+sknn0BbWxubNm1C9+7d8dtvvyn1Mz8/H1KpFP3798f69evV9vX777/Ht99+i9jYWJw/fx6enp7iewB4fs2kpaWFa9euoXbt2ggLC0NYWBgiIiIAyBcXdXR0xO7du+Hq6goLCwuYmZmpPV9AQAB27typMrM9IiIC7dq1w9OnT2FkZIQaNWqgXr16sLS0xK+//oqdO3eiR48e4nv76tWrcHNzg5aWlkqf161bh2HDhqk9f2Ft27ZFw4YNlcYAABAWFoZx48aJud6XLl2KFStWIDo6Wqme4vW6ffs2HB0dK6wPhdtZUFCAhg0bon379nBwcEBQUJDauwxehLrPbVlxjMQ+sU/sE/vEPrFP7NO73qfixkhFvVEzz5s3b44///xTqWzfvn1o3rx5sfvo6upCV1dXpVxbWxva2srdV/yhiio8MNGkvOhxX6RcIpGoLS+ujWUtL48+SSUS1DTUR01D1XQ5wPNFTMU861k54qKmD7JzkFUg4HpGFq5nqF/E1FZX53kqGD35fxV519UtYsq/E/tUXDn7xD4B7FNxbSxrOfv0ZvapuHOpI5FINE6d0trZErameohLzlKb91wCwMZUD62dLTXKeV5WEokELVu2RMuWLTFjxgzY29tjx44dACDeTadI63fixAkxUFoSGxsbODk5qZTLZDI0atQIBw4cEIPnBQUFOHDgAEaPHg0AcHBwgJ2dHa5du6a07/Xr19GpUycAwHfffYdvv/1W3Pbw4UP4+Phgy5YtaNasWbHtOn/+PGxt5Quv1qtXD5cuXVLaPn36dKSmpmL58uWl9rFGjRqoXbt2iXU0oa2tjU8//RQLFy4sdtHT4OBgtGnTBt9//71SeWhoKIKDgzUKnmuqbt26uH//PuLj45Vm0p89exZ6enqoWbPmK+uDlpYW5s2bh549e76Ws885RmKf2Cf2iX1inwD2qbg2lrWcfXoz+6TpGKlSg+dpaWm4efOm+Dw6Ohrnz5+Hubk5atasialTp+LBgwfYsGEDAODzzz/HypUrMXnyZAwZMgQHDx7Er7/+ij/++KOyukAl0GQRU0VgPSYzW55nPfP5IqYPs3PxsIRFTO315IuX2uvrwkFfJj7nIqZERESvhlRLgpldXfHFxrOQAEoBdMW/xDO7ulZI4DwqKgoHDhxAx44dYWVlhaioKCQmJsLFxQUXL15ETk4Ohg4diunTpyMmJgYzZ87E6NGj1V68a2rChAkYNGgQGjdujKZNmyIoKAjp6eliihaJRIJJkyZh5syZ8PDwQMOGDbF+/Xr8999/CA8PBwCVAK6RkREAoHbt2qhevToAYP369ZDJZPD09AQgT08SEhIi5vzW09ND/fr1lY6jmEFetLyizZ49G5MmTYKFhYXKttzcXPz0008IDAxUaddnn32GpUuX4sqVK2Ie8Zfl4+ODunXrws/PD99++y1sbGxw9uxZTJ8+HWPHji12gFRRfejcuTOaNWuGtWvXvlBaHCIiIiKqfJUaPD99+jTatWsnPlfkdhw0aBDCwsIQGxuLu3fvitsdHR3xxx9/YPz48Vi+fDmqV6+OH3/8ET4+Pq+87fRydLQkcNDXhYO+LrygnCdSEAQ8zn02a/1ZQP1O5vNZ63E5uUjJK8CltExcKm4RUz0ZHPSez1R3eBZkt9eTwUhb89l3REREVDLf+rZYPeA9zPrtKmKTn99NZmOqh5ldXeFb37ZCzmtiYoIjR44gKCgIKSkpsLe3x5IlS9CpUyds2bIF3t7ecHZ2Rps2bZCdnQ0/Pz8EBAS81Dk/+eQTJCYmYsaMGYiLi0PDhg2xZ88epcDouHHjkJWVhfHjx+PJkyfw8PDAvn37yjzTe/bs2bhz5w60tbVRr149bNmyBb17936p9lcEmUxWbN713bt34/Hjx+jRo4fKNhcXF7i4uCA4OBhLly4tl7Zoa2tj7969+Oabb+Dn54fExEQ4Ojpi7NixSjnkX2UfFixYgBYtWrxYh4iIiIio0r02Oc9flZSUFJiampaaz4ZeX5n5BfIc64qgepY8qH7n2ez17IKS39IWOtpKwXQHfV0xPYyVTBtaZci1SkRE9CYo7vqnPHInK+QXCDgZ/QQJqVmwMtZDU0fzCplxrgl/f38kJSVh586dxdZRl/P8bVM05zm9Hcrzc6vAMRIRERG9azS9/nmjcp4TAYC+VAt1DfVQ11B1sFAgCIjLzlU7Y/1OVjae5ObjcW4eHufm4UxKhsr+ikVM5cF15QB7DT0Z9KQvfqs3ERHR20yqJUHz2qppL4iIiIiIiN5UDJ7TW0VLIoGdngx2ejI0NzNS2Z6Sl4+7z4LphfOs38nMwf0yLGJqr1coFUwJi5gSERERUfEiIyPFxVTVSUtLe4WtISIiIiJSxuA5vVNMtKWob2yA+hosYqpICaN4nlZ4EVOoLmJqLNWCg/7zPOuFU8JwEVMiIqJXJywsrNQ6Dg4OGDduXIW3pTI1bNgQ/v7+ld2MEjVu3Bjnz5+v7GYQEREREanF4DnRM5osYno3MxsxWYVSwTxb1DQ2Oxep+aUvYmqv93ymun2hIDsXMSUiInq13pXgecOGDSu7GSXS19eHk5NTZTeDiIiIiEgtBs+JNCCRSFBVpo2qMm28Z2qosj0zvwD3spRTwRRdxFSeKiYHeKp6fAsdbaVgeuEAu7VMh4uYEhERERERERERvWIMnhOVA32pFuoY6qFOMYuYxufkPs+zrkgL8yzIXngR07MlLGIqD6g/X8TUXl8XNbmIKRERERERERERUYVg8JyogmlJJLDVlcFWV/0ipql5+c/TwDxLCaPIs67pIqY19Yqkgnm2qKm5DhcxJSIiIiIiIiIiehEMnhNVMuNSFjF9mJ0jpoCJKWER0xPJ6hcxtS8UTHfQ5yKmREREREREREREmmDwnOg1pqMleRb81gXULGL6JDdfXLQ0pphFTC+nZeKymkVMpRKgum6hmer68uC6/bNZ7FzElIiIiIiIiIiI3mUMnhO9oSQSCSxk2rAoZhHTrPwC3M3KUQquK2asKxYxvZMlTxWjbhFTcx0pHPR1lRYxVQTYuYgpERERERERERG97Rg8J3pL6Wm4iKkix3rhAPvj3Dw8yc3Hk9yMYhcxrVEkz7oi7zoXMSUiekcV5AN3jgFp8YCRNWDfAtB6fe9iioiIgL+/P2JiYiq7KRUmLCwMYWFhiIiIqOymEBERERG9kRjhInoHKRYxbW5mhL62FphSyxarXO3xZ6M6uNKqPm60dsf+xnUQXN8B/6tth0/tLOBVxRj2ejJIJUBWgYAbGdnY9zgFP95/hOk3HuDTS9Foc/I/OBy5CM9jV9D97A2M/fculsXEYXv8U5xNTsfjnDwIglDZ3SciovJ2dTcQVB9Y3wXYNlT+36D68vI3iEQiER+mpqZo2bIlDh48qLbu/PnzIZFIMG7cOKXyrKwsjBo1ChYWFjAyMkKvXr0QHx+vVOfAgQNo0aIFjI2NYWNjgylTpiAvL0/cHhERgY8++gi2trYwNDREw4YNsWnTJqVjhIWFKbVXIpFAT0/1B/PCYmJiIJFIIJVK8eDBA6VtsbGx0NbWhkQiEX9QUNRXPIyNjeHm5oZRo0bhxo0bKu0xMzNTe16JRIKdO3cqlR06dAgffvghLCwsYGBgAFdXV3z11Vcq7VInIiICEokESUlJKtscHBwQFBRU4rkBwN/fH927dxeft23bFhKJBPPnz1ep27lzZ0gkEgQEBKhs++WXXyCVSjFq1Khi2+nm5ob8/HylbWZmZggLCyuui0RERET0mmDwnIhUKBYx7WxphlE1rbCwbg1saVgbUc1dcaeNB6Led8GvHrWxsE51jKpphc6WpqhvpA+jZzPOY58tYLol7gkWRMdh5NU7+PDsDbj9cxnOkZfQ4dQ1DL0cjcCbD7HhwSMcfpKKO5nZyCtgYJ2I6I1zdTfw66dAykPl8pRYefkbFkAPDQ1FbGws/vnnH1StWhVdunTB7du3leqcOnUKa9euRYMGDVT2Hz9+PH777Tds3boVhw8fxsOHD9GzZ09x+4ULF/Dhhx/C19cX586dw5YtW7B79258/fXXYp1jx46hQYMG2LZtGy5evIjBgwfj008/xe+//650LhMTE8TGxoqPO3fuaNTHatWqYcOGDUpl69evR7Vq1dTW379/P2JjY3HhwgXMnTsX//77Lzw8PHDgwAGNzlfU2rVr0aFDB9jY2GDbtm24evUq1qxZg+TkZCxZsuSFjlkeatSooRLQfvDgAQ4cOABbW1u1+wQHB2Py5Mn45ZdfkJWVpbbO7du3VV5vIiIiInozMG0LEZWJdqFFTNsUt4hp1vP86oXzrD/MzkWaBouYKlLB2D/Lt+7wLN+6MRcxJSKqeIIA5Kqm7FKrIB/4azIAdT9+CgAkwJ4pQK22mqVw0TEAyrCmRnh4OGbNmoWbN2/CwMAAnp6e2LVrF0aNGoWkpCR4enpi5cqVyM7ORr9+/fDdd99BJpOVeEwzMzPY2NjAxsYGq1evRrVq1bBv3z6MGDECAJCWlob+/fvjhx9+wLfffqu0b3JyMoKDg/Hzzz+jffv2AOTBeBcXF5w4cQLvv/8+tmzZggYNGmDGjBkAACcnJyxcuBB9+vTBzJkzYWxsjG+++UbpuGPHjsXevXuxfft2dOnSRSyXSCSwsbHR+PVSGDRoEEJDQzF16lSxLDQ0FIMGDcLs2bNV6ltYWIjnqVWrFrp27Qpvb28MHToUt27dglSq+b/P9+/fx5gxYzBmzBgsW7ZMLHdwcECbNm3UziZ/Vbp06YJff/0V//zzD1q2bAlA/qNCx44dcffuXZX60dHROHbsGLZt24ZDhw5h+/bt6Nevn0q9L7/8EjNnzkS/fv2gq6tb4f0gIiIiovLD4DkRlRulRUxN1C9iek+RW/3ZYqbyvOs5uJuVjaxCi5geeZqmsr9iEVN7RX51RZBdTwYbXS5iSkRULnIzgLl25XQwQT4jfX4Nzap/8xCQqf77oU5sbCz8/PywcOFC9OjRA6mpqYiMjBTTgx04cAB6enqIiIhATEwMBg8eDAsLC8yZM0fj1uvr6wMAcnJyxLJRo0ahc+fO6NChg0rw/MyZM8jNzUWHDh3Esnr16qFmzZo4fvw43n//fWRnZ6ukV9HX10dWVhbOnDmDtm3bqm1LcnIyXFxclMrS0tJgb2+PgoICvPfee5g7dy7c3NxK7Ve3bt2wZs0aHD16FK1atcLRo0fx9OlTdO3aVW3wvCgtLS2MHTsWPXr0wJkzZ9C0adNS91HYunUrcnJyMHnyZLXbi0v98irIZDL0798foaGhYvA8LCwMCxcuVJuyJTQ0FJ07d4apqSkGDBiA4OBgtcHzcePGYePGjVixYgUmTpxY0d0gIiIionLE4DkRvTJ6Ui04G+rBuYRFTAvPWC8cYNd0EVN7fV35THW954uZ1tCTQZ+LmBIRvVViY2ORl5eHnj17wt7eHgDg7u4ubpfJZAgJCYGBgQHc3NwQGBiISZMmYfbs2dDSKv3fhIyMDEyfPh1SqRReXl4AgM2bN+Ps2bM4deqU2n3i4uIgk8lUAsDW1taIi4sDAPj4+CAoKAi//PIL+vTpg7i4OAQGBop9UufXX38VU8Uo1K1bFyEhIWjQoAGSk5OxePFitGjRAleuXEH16tVL7JuOjg4GDBiAkJAQtGrVCiEhIRgwYAB0dHRKfV0U6tWrB0CeF10RPE9OToaRkVGJ+924cQMmJibFpkEpC3X9zMjQ8K6JYgwZMgStW7fG8uXLcebMGSQnJ6NLly4qwfOCggKEhYVhxYoVAIC+ffviq6++QnR0NBwdHZXqGhgYYObMmfjmm28wbNgwmJqavlQbiYiIiOjVYfCciF4LikVMbXVleN9MdeCdmpePu1nKqWDkAfZs3M/KERcxvZGRrfb4tro6sH8WXFcE1R30ZKiprwsLHSkknLVORCSnYyCfAa6JO8eATb1Lr9c/HLBvodm5NeTh4QFvb2+4u7vDx8cHHTt2RO/evVGlShVxu4HB8+M1b94caWlpuHfvnhhsV8fPzw9SqRSZmZmwtLREcHAwGjRogHv37mHs2LHYt29fqQtzlqRjx45YtGgRPv/8cwwcOBC6urr43//+h8jISLVB/UOHDmHw4MH44YcflGaVN2/eHM2bNxeft2jRAi4uLli7dq1Gs8eHDBmCFi1aYO7cudi6dSuOHz+utGhpaRQz/Av/+2lsbIyzZ8+q1HV2dlbar7z+zY2MjISxsXIKueJm7mvKw8MDzs7OCA8Px6FDhzBw4EBoa6sOmfbt24f09HR8+OGHAICqVavigw8+QEhIiNrXf+jQoViyZAkWLFiAuXPnvlQbiYiIiOjVYfCciN4IxtpSuBnpw81IX2VbXoGAB9k5YjA9RpFn/dl/U/MLEJudKy5kWpSRVOt5nvVCM9bt9WWopiuDjhYD60T0DpFINE6dgtrtARM7+eKgavOeS+Tba7fXLOd5GUilUuzbtw/Hjh3D3r17sWLFCkybNg1RUVEvddxly5ahQ4cOMDU1haWlpVh+5swZJCQk4L333hPL8vPzceTIETGvuo2NDXJycpCUlKQ0+zw+Pl4pN/mECRMwfvx4xMbGokqVKoiJicHUqVNRq1YtpbYcPnwYXbt2xbJly/Dpp5+W2G4dHR14enri5s2bGvXT3d0d9erVg5+fH1xcXFC/fn2cP39eo30B4N9//wUApVnWWlpacHJyKnG/OnXqIDk5GbGxsS89+9zR0VFlln/RQLexsTGSk5NV9k1KSip2BviQIUPw/fff4+rVqzh58qTaOsHBwXjy5ImY2geQz0a/ePEiZs2apfJDiLa2NubMmQN/f3+MHj1ak+4RERER0WuAwXMieuMVXsQUahYxfZqX/3ymuiLP+rNFTWOfLWJ6JS0LV9KyVI4tlQDVdOWLljro66Km3vPAugMXMSWid52WFPBdAPz6KQAJlAPoz3549J1f7oFz8QwSCVq2bImWLVtixowZsLe3x44dOwAAFy5cQGZmphjcPHHiBIyMjFCjRsn5121sbNQGgL29vXHp0iWlssGDB6NevXqYMmUKpFIpGjVqBB0dHRw4cAC9evUCAFy7dg13795VmiWuaLudnTy3/C+//IIaNWooBeYjIiLQpUsXLFiwAMOHDy/1tcjPz8elS5fEmdCaGDJkCEaOHInVq1drvA8gDxJ/9913cHR0hKenZ5n27d27N77++mssXLhQacFQhaI/PLysunXr4syZMxg0aJBYlp+fjwsXLuCzzz5Tu0+/fv0wceJEeHh4wNXVVWX748ePsWvXLmzevFnpboD8/Hy0atUKe/fuha+vr8p+H3/8MRYtWoRZs2aVQ8+IiIiI6FVg8JyI3moSiQTmOtow19F8EVN5Wpjni5jezcrB3RIWMbXXe5Zn/VlQXfGci5gS0TvBtRvQZwOwZ4p8cVAFEzt54Ny1W4WcNioqCgcOHEDHjh1hZWWFqKgoJCYmwsXFBRcvXkROTg6GDh2K6dOnIyYmBjNnzsTo0aM1yneujrGxMerXr69UZmhoCAsLC7Hc1NQUQ4cOxYQJE2Bubg4TExN8+eWXaN68Od5//31xv0WLFsHX1xdaWlrYvn075s+fj19//RVSqfxHhkOHDqFLly4YO3YsevXqJeZLl8lkMDc3BwAEBgbi/fffh5OTE5KSkrBo0SLcuXOn2ICwOsOGDcPHH39carD68ePHiIuLQ0ZGBi5fvoygoCCcPHkSf/zxh9hmTdWoUQPLli3D6NGjkZKSgk8//RQODg64f/8+NmzYACMjIyxZsqRMxyzJhAkTMHToUNSrVw8ffPAB0tPTsWLFCjx9+rTY16pKlSqIjY0tNgf8Tz/9BAsLC/Tp00clBc2HH36I4OBgtcFzAJg/fz58fHxerlNERERE9MoweE5E77TSFjFNyMlTyrOuyLtedBHTc6mqC5TpaklQU5FnvdCMdftnM9i5iCkRvTVcuwH1OstzoKfFA0bW8hznFTTjHABMTExw5MgRBAUFISUlBfb29liyZAk6deqELVu2wNvbG87OzmjTpg2ys7Ph5+ensuhjRVi2bBm0tLTQq1cvZGdnw8fHB6tWrVKq89dff2HOnDnIzs6Gh4cHdu3ahU6dOonb169fj4yMDMybNw/z5s0Ty728vBAREQEAePr0KYYNG4a4uDhUqVIFjRo1wrFjx9TOlC6OtrY2qlatWmq9Dh06AJAvfGlvb4927dph3bp1paZoKc7IkSNRp04dLF68GD169EBmZiYcHBzQpUsXTJgw4YWOWRw/Pz8IgoClS5fi66+/hoGBARo1aoQjR47A2tq62P1K+kEhJCQEPXr0UJu7vVevXhg4cCAePXqkdt/27dujffv22Lt3b5n7QkRERESvnkRQrPbzjkhJSYGpqSmSk5NhYmJS2c0hojdYWl6+OFtdKc/6s0VM80r5drWR6cBBX4aaigVMnwXZ7bmIKRGVs+Kuf7KyshAdHQ1HR8eXWgTzdePv74+kpCTs3Lmz2DoRERHw9/dHTEzMK2vXqxYWFoawsDAx4E5vh4r43HKMRERERO8aTa9/OPOciOgFGWmwiKkimB6TWTgljHwR07icXMTllL6IadE861zElIiIiIiIiIio4jF4TkRUAQovYtq6hEVM72Y+z7eueP6wDIuY2heare7ARUyJiOgt0KlTJ0RGRqrd9s033+Cbb755xS0iIiIioncVg+dERK+YpouYFg6oK/KsF13EFCUsYirOXNeXwYGLmBLROyQsLKzUOg4ODhg3blyFt6UyNWzYEP7+/pXdjDL78ccfkZmZqXabYsFUIiIiIqJXgcFzIqLXTEmLmAqCgPicPDHP+p2s56lg7mTm4JGGi5jW1Hs+U52LmBLRu+hdCZ43bNiwsptRZtWqVavsJhARERERAWDwnIjojSKRSGCjqwMbXR00M1PdnpaXj7tZz2eqK/Ks38nKxr2sHGQXCLiRkY0bGdlqj28j03kWTJeJC5gqZq9X1dHmIqZERERERERE9M5g8JyI6C1ipC2Fq5E+XItZxPRhdo58pnqhGeuKRU1T8p4vYhqlZhFTQ6mWPM+63vPZ6orn1fW4iCkRERERERERvV0YPCciekdoa0lQU18XNUtYxPROodnqigD7ncxsPMzORboGi5iKedafzVhXLGpqwkVMiYiIiIiIiOgNw+A5EREpLWLqaWKgsj0rvwD3s3OUUsHEZGbjTlYO7mZmI7PQIqaRxSxiqsizbv8sz7rDsxnstlzElIiIiIiIiIheQwyeExFRqfSkWnAy0IOTgfpFTBNy8sRgumLxUsWipoUXMT2vZhFTmUSCms/SvzgUyreuKOMipkRERERERERUGRg8JyKilyKRSGCtqwNrXR00U7M9PS9fKagek5ktLmp6LysHOYKAmxnZuFnMIqbWMm354qVKAXb5cy5iSkQvKiIiAv7+/oiJiansplSYd6GPREREREQVidP5iIioQhk+W8T0Q0szfFHTCgvq1sAvHrVx/H1XxLTxwMn3XbDVozYW162B0TWt0NXSDA2M9GGiLf8nKj4nD1HJ6fg17ikWxcRh1L930eXsDbj/cwVOkZfQ/uR/GHIpGgE3HyDswSNEPElBdEY2cguESu450bslvyAfp+JO4c/bf+JU3CnkF+RXdpPKTCKRiA9TU1O0bNkSBw8eVKrz4MEDDBgwABYWFtDX14e7uztOnz4tbg8ICEC9evVgaGiIKlWqoEOHDoiKilI6xpw5c9CiRQsYGBjAzMxMbVvu3r2Lzp07w8DAAFZWVpg0aRLy8vLU1v3nn3+gra2Nhg0bltpHTc6t8PjxY1SvXh0SiQRJSUli+dGjR9GyZUvxNahXrx6WLVumtO/q1avRoEEDmJiYwMTEBM2bN8dff/0lbg8ICFB6vYs+Zs2aVWpfwsLCiu2DRCLBzp07AQAxMTGQSCQ4f/68Sr22bdti3Lhx4nMHBwdIJBJs3rxZpa6bmxskEgnCwsJUts2bNw9SqRSLFi1S206JRAJfX1+l8qSkJEgkEkRERBTXRSIiIiKqZJx5TkRElUZ5EVNlgiAgKS9fKc/6naxs8bliEdOr6Vm4mq66iKkWgGp6MvlM9Wf51RUz2B24iClRudp/Zz/mn5yP+Ix4sczawBpfN/0aHew7VGLLyi40NBS+vr549OgRpk2bhi5duuDy5cuoVasWnj59ipYtW6Jdu3b466+/YGlpiRs3bqBKlSri/nXq1MHKlStRq1YtZGZmYtmyZejYsSNu3rwJS0tLAEBOTg4+/vhjNG/eHMHBwSptyM/PR+fOnWFjY4Njx44hNjYWn376KXR0dDB37lyluklJSfj000/h7e2N+Ph4lWMVVdq5Cxs6dCgaNGiABw8eKJUbGhpi9OjRaNCgAQwNDXH06FGMGDEChoaGGD58OACgevXqmD9/PpydnSEIAtavX4+PPvoI586dg5ubGyZOnIjPP/9c5ZxTp07Fzp070a9fv1L7UlFq1KiB0NBQ9O3bVyw7ceIE4uLiYGhoqHafkJAQTJ48GSEhIZg0aZLKdm1tbezfvx+HDh1Cu3btKqztRERERFS+GDwnIqLXkkQiQRUdbVQpZhHT7IIC3MvKeb54aaHgumIR03tZObiXlYNIqC5iWkVbCnt95TQw9nrywDoXMSXS3P47+zEhYgIEKN/tkZCRgAkRE7C07dIKC6CHh4dj1qxZuHnzJgwMDODp6Yldu3Zh1KhRSEpKgqenJ1auXIns7Gz069cP3333HWQyWYnHNDMzg42NDWxsbLB69WpUq1YN+/btw4gRI7BgwQIxsKrg6OiotH/RoO/SpUsRHByMixcvwtvbGwDEWdXqZjADwN69e3H16lXs378f1tbWaNiwIWbPno0pU6YgICBAqQ+ff/45+vXrB6lUKs60Lklp51ZYvXo1kpKSMGPGDKUZ4wDg6ekJT09P8bmDgwO2b9+OyMhIMXjetWtXpX3mzJmD1atX48SJE3Bzc4ORkRGMjIyU6mzatAk//fQT/vjjDzg7O5fal4rSv39/LFu2DPfu3UONGjUAyIPj/fv3x4YNG1TqHz58GJmZmQgMDMSGDRtw7NgxtGjRQqmOoaEh+vTpg6+//lrlTgQiIiIien0xeE5ERG8kXa2yLWJ6VxFkz8pBYk4enubl42lq6YuYymeqPw+w19TThQEXMaW3mCAIyMzL1KhufkE+5p2cpxI4ByCWzT85H81smkGqVfrdHvra+hqvYxAbGws/Pz8sXLgQPXr0QGpqKiIjIyEI8vMeOHAAenp6iIiIQExMDAYPHgwLCwvMmTNHo+MDgL6+PgD5bG0A2L17N3x8fPDxxx/j8OHDqFatGkaOHIlhw4ap3T8nJwfr1q2DqakpPDw8ND7v8ePH4e7uDmtra7HMx8cHX3zxBa5cuSIGrkNDQ3H79m1s3LgR3377rcbHL83Vq1cRGBiIqKgo3L59u9T6586dw7Fjx4ptQ35+PrZu3Yr09HQ0b95cbZ0zZ85g2LBhmD9/Pnx8fF6q/S/L2toaPj4+WL9+PaZPn46MjAxs2bIFhw8fVhs8Dw4Ohp+fH3R0dODn54fg4GCV4DkgT1Xj5OSE8PBw9O7d+1V0hYiIiIheEoPnRET01tF0EdM7mc/SwIj/X7ZFTGvqy+BQJCUMFzGlN11mXiaa/azuk/Ni4jPi0WKzaiBRnah+UTDQUb3TRJ3Y2Fjk5eWhZ8+esLe3BwC4u7uL22UyGUJCQmBgYAA3NzcEBgZi0qRJmD17NrS0Sv8BLCMjA9OnT4dUKoWXlxcA4Pbt21i9ejUmTJiAb775BqdOncKYMWMgk8kwaNAgcd/ff/8dffv2RUZGBmxtbbFv3z5UrVpVo34BQFxcnFLgHID4PC4uDgBw48YNfP3114iMjIS2dvld0mdnZ8PPzw+LFi1CzZo1SwyeV69eHYmJicjLy0NAQAA+++wzpe2XLl1C8+bNkZWVBSMjI+zYsQOurq4qx0lISECPHj3Qq1cvTJw4sUztTU5OVpnBXh6GDBmCr776CtOmTUN4eDhq166tNqd8SkoKwsPDcfz4cQDAgAED0Lp1ayxfvlylXXZ2dhg7diymTZuG7t27l3ubiYiIiKj8MXhORETvHMUipq5G+irb8gUBD7JycDcrR8yvLv43KxspeQWIz8kTFzJVObZUC/Z6z2eqO+jriulgqunpQKZB0I6ISufh4QFvb2+4u7vDx8cHHTt2RO/evcX84x4eHjAweB6Ib968OdLS0nDv3j0x2K6On58fpFIpMjMzYWlpieDgYDRo0AAAUFBQgMaNG4t5xz09PXH58mWsWbNGKXjerl07nD9/Ho8ePcIPP/yAPn36ICoqClZWVuXS9/z8fPTr1w+zZs1CnTp1yuWYClOnToWLiwsGDBhQat3IyEikpaXhxIkT+Prrr+Hk5AQ/Pz9xe926dXH+/HkkJycjPDwcgwYNwuHDh5UC6Lm5uejduzesra3xww8/lLm9xsbGOHv2rEr5y6Z96dy5M0aMGIEjR44gJCQEQ4YMUVvvl19+Qe3atcU7Cxo2bAh7e3ts2bIFQ4cOVak/ZcoUrF27FiEhIejTp89LtZGIiIiIKh6D50RERIVIJc8XMW1VRXX709w8tXnWy7KIqSKYbv8sHYzDs3zrpjr8Z5kqn762PqL6aZaT+Uz8GYw8MLLUequ8V6GRdSONzq0pqVSKffv24dixY9i7dy9WrFiBadOmvXQ+6WXLlqFDhw4wNTUVF/hUsLW1VZk57eLigm3btimVGRoawsnJCU5OTnj//ffh7OyM4OBgTJ06VaM22NjY4OTJk0plisVAbWxskJqaitOnT+PcuXMYPXo0AHlgXxAEaGtrY+/evWjfvn2Z+q1w8OBBXLp0CeHh4QAgpsGpWrUqpk2bJuZMB57ne3d3d0d8fDwCAgKUgucymQxOTk4AgEaNGuHUqVNYvnw51q5dK9YZM2YMbty4gVOnTkFPTzUNV2m0tLTEcxTHxMQEgHyWelFJSUkwNTVVKdfW1sbAgQMxc+ZMREVFYceOHWqPHRwcjCtXrijN/i8oKEBISIja4LmZmRmmTp2KWbNmoUuXLiW2m4iIiIgqH0fpREREZaBYxLRhMYuY3n82Y13Ms571LMheZBHTo0nFL2JaeMa6IsBux0VM6RWRSCQap05pYdcC1gbWSMhIUJv3XAIJrA2s0cKuhUY5z8tKIpGgZcuWaNmyJWbMmAF7e3sxyHnhwgVkZmaKectPnDgBIyMjcQHI4tjY2BQbjG3ZsiWuXbumVHb9+vUSZ7ID8mBqdrb6NFDqNG/eHHPmzEFCQoI4W33fvn0wMTGBq6srdHR0cOnSJaV9Vq1ahYMHDyI8PFxlEdOy2LZtGzIzn+e8P3XqFIYMGYLIyEjUrl272P006WPROuvWrUNISAgOHTqE6tWrv3CbS2Nubo6qVavizJkzYgoeQJ5y5ebNm8XO3h8yZAgWL16MTz75RLyjobBLly7h9OnTiIiIgLm5uVj+5MkTtG3bFv/99x/q1aunst+XX36J7777DsuXLy+H3hERERFRRWLwnIiIqJzoammhtoEeapewiKk8/Ys8mC4PqssD7JouYlqz0Kx1By5iSpVMqiXF102/xoSICZBAohRAl0D+Y8+UplMqJHAeFRWFAwcOoGPHjrCyskJUVBQSExPh4uKCixcvIicnB0OHDsX06dMRExODmTNnYvTo0RrlOy/O+PHj0aJFC8ydOxd9+vTByZMnsW7dOqxbtw4AkJ6ejjlz5qBbt26wtbXFo0eP8P333+PBgwf4+OOPxePcvXsXT548wd27d5Gfn4/z588DAJycnGBkZISOHTvC1dUVAwcOxMKFCxEXF4fp06dj1KhR0NXVBQDUr19fqW1WVlbQ09NTKS+qtHMXDZA/evQIgHyGvZmZGQDg+++/R82aNcXA8JEjR7B48WKMGTNG3G/q1Kno1KkTatasidTUVPz888+IiIjA33//DQD4559/8OWXX2LGjBmoVauWmMtdQV9fX+2M8Bc1YcIEzJ07F9bW1nj//ffx+PFjzJ49G5aWlujZs6fafVxcXPDo0SOl9D+FBQcHo2nTpmjTpo3KtiZNmiA4OBiLFi1S2aanp4dZs2Zh1KhRL9cpIiIiIqpwDJ4TERG9AoUXMW2qZnt6Xv6zPOvZzwLqzwPsqouYpqrsby3TFmet2+vJU8FwEVN6FTrYd8DStksx/+R8xGfEi+XWBtaY0nQKOth3qJDzmpiY4MiRIwgKCkJKSgrs7e2xZMkSdOrUCVu2bIG3tzecnZ3Rpk0bcRHMgICAlzpnkyZNsGPHDkydOhWBgYFwdHREUFAQ+vfvD0CeSua///7D+vXr8ejRI1hYWKBJkyaIjIyEm5ubeJwZM2Zg/fr14nNPT08AwKFDh9C2bVtIpVL8/vvv+OKLL9C8eXMYGhpi0KBBCAwMfKn2a3JuTRQUFGDq1KmIjo6GtrY2ateujQULFmDEiBFinYSEBHz66aeIjY2FqakpGjRogL///hsffPABAODHH39ETk4Opk+fjunTp6ucY9CgQQgLC3vxjhYxefJkGBkZYcGCBbh16xbMzc3RsmVLHDp0SLw7QR0LCwu15Tk5Odi4cSOmTJmidnuvXr2wZMkSMT9+UYMGDcKSJUtw9erVsneGiIiIiF4ZiaBIZPiOSElJgampKZKTk8X8h0RERK+zfEHAw+xcMZgeo1jE9FlKmOS8/BL3N3i2iKlSnvVni5pW5yKm74Tirn+ysrIQHR0NR0fHF8o3XVh+QT7OJpxFYkYiLA0s8Z7VexUy41wT/v7+SEpKws6dO4utExERAX9/f8TExLyydr1q70If30Xl+blV4BiJiIiI3jWaXv9w5jkREdFrTiqRoIaeDDX0ZGoXMU3KzXueZ73w7PVni5hm5Bfg3/Qs/FvMIqZ2ejpw0NNVCq7b68vgwEVMqQykWlI0sWlS2c0gIiIiIiIqNxwRExERveHMdLTRUINFTMU861nPZq5n5iCzoAD3s3JxPyu32EVMaxZawNRBX1d8bqurAynTwRBRBXFzc8OdO3fUblu7dq2YLoeIiIiIqKIweE5ERPQWK20R08ScPPlM9UIz1lUXMc3EhdRMlf1lz2bEi6lgngXVaz5LCcNFTKmyaJIr28HBAePGjavwtlSmN72Pf/75J3Jzc9Vus7a2fsWtISIiIqJ3EXOeExERkVrp+fm4qwimZ2arLGKaW8olhJVMWwymOzwLriuC7FzE9NV6FTnPiejVYM5zIiIiopfHnOdERET0UgylUrgY6cPFSF9lm7pFTBWz1+9m5iApLx8JOXlIyMnDyeR0lf0LL2JaNC0MFzElIiIiIiKi1wGD50RERFRmmi5ieidLkQomW3z+MEvzRUzt9ZUD7FzElIiIiIiIiF4Vjj6JiIio3JW0iGlOQQHuZeUozVgXg+sqi5iqOba29Hme9Wf51e25iCkRERERERGVMwbPiYiI6JWSabCIaeEFTMWFTLOykZCTh6S8fCSVsohp0VQw9vryMkOp9FV0kYiIiIiIiN4CDJ4TERHRa0MikcBKVwdWujpoYmqosr3oIqaF86zfzcpBjiDgVmY2bmVmA0hV2d9Kpg37Z+lgFLPVFUF2SxkXMSUiIiIiIqLnGDwnIiKiN0Zpi5jGZuc+n6memY2YZylh7hRZxPRUiuoipvpaWs8C6s9SwRSatV5DT1aui5jmCwJOJKUhIScPVjJtvG9mxHQzRERERERErxkGz4mIiOitIJVIUF1PhuolLGJaeKa6mBbm2SKmmQUF+C89C/8Vs4ipra7Os5nqz/Os2+vJn5uVYRHTPxKTMP3GA8Rm54pltro6+Na5Gjpbmr1Az18PQn4+Mk6fQV5iIrQtLWHQuBEkr3GanIiICPj7+yMmJqaym1JhYmJi4OjoCEEQKrspREBBPnDnGJAWDxhZA/YtAK3X9zuCiIiICJCPBYmIiIjeemY62vAwNsBHVlXwpb01ltSriXBPJ5xu7oYYrwY41swFPzeohXl1qmNEDUv4VjWBi6Ee9LW0UADgQXYu/klKw6bYJ5h7OxYjrtyB75nrqHf0MupFXkLH09cw/EoM5tx6iE0PH+Po01Tcy8pBfqHA5R+JSfjscoxS4BwA4rJz8dnlGPyRmPRqX5RykrJ3L256d8DdQYPwcOJE3B00CDe9OyBl797KblqZSCQS8WFqaoqWLVvi4MGDSnUePHiAAQMGwMLCAvr6+nB3d8fp06fF7WlpaRg9ejSqV68OfX19uLq6Ys2aNUrHWLduHdq2bQsTExNIJBIkJSWptOXJkyfo378/TExMYGZmhqFDhyItLU1tu2/evAljY2OYmZmV2kcHBwelfioe8+fPByAPuKvbPmDAAPEYY8aMQaNGjaCrq4uGDRuWeL569epBV1cXcXFxKtu2b9+Ojh07wsLCAhKJBOfPny+1/UX7EhQUpFIeEBCg1C5/f390795dpV5ERITS6x8WFgaJRAIXFxeVulu3boVEIoGDg4PKtszMTJibm6Nq1arIzs5W206JRIITJ04olY8bNw5t27YtqYtvj6u7gaD6wPouwLah8v8G1ZeXExEREb3GOPOciIiI3nkyLS3UMtBFLQNdlW2CIOBRbh5iFKlgns1av/tsFnvhRUwvqlnEVEexiKmeDk4mZ0DdHGABgATA/248gG9V0zcqhUvK3r14MHYcUGR2c158vLx8eRBMOnaslLa9iNDQUPj6+uLRo0eYNm0aunTpgsuXL6NWrVp4+vQpWrZsiXbt2uGvv/6CpaUlbty4gSpVnt/qMGHCBBw8eBAbN26Eg4MD9u7di5EjR8LOzg7dunUDAGRkZMDX1xe+vr6YOnWq2nb0798fsbGx2LdvH3JzczF48GAMHz4cP//8s1K93Nxc+Pn5oXXr1jh27JhGfQwMDMSwYcOUyoyNjZWe79+/H25ubuJzfX3lVElDhgxBVFQULl68WOx5jh49iszMTPTu3Rvr16/HlClTlLanp6ejVatW6NOnj0p7KouhoSESEhJw/PhxNG/eXCwPDg5GzZo11e6zbds2uLm5QRAE7Ny5E5988olKHT09PUyZMgWHDx+usLa/tq7uBn79FCj67ZcSKy/vswFw7VYpTSMiIiIqDYPnRERERCWQSCSwlOnAUlb6IqZ3srLFIPudZ4uY5goCbmdm43am6ozUwgQAD7NzcSIpDS2rGJdYtyIJggAhU/VHALV18/MR/+0clcD5swMBEiB+zlwYNm+uUQoXib5+mRZtDQ8Px6xZs3Dz5k0YGBjA09MTu3btwqhRo5CUlARPT0+sXLkS2dnZ6NevH7777jvIZLISj2lmZgYbGxvY2Nhg9erVqFatGvbt24cRI0ZgwYIFqFGjBkJDQ8X6jo6OSvsfO3YMgwYNEmcUDx8+HGvXrsXJkyfF4Pm4ceMAyGc+q/Pvv/9iz549OHXqFBo3bgwAWLFiBT788EMsXrwYdnZ2Yt3p06ejXr168Pb21jh4bmxsDBsbmxLrWFhYFFvnu+++AwAkJiaWGDwPDg5Gv3794OXlhbFjx6oEzwcOHAgAr1XqHG1tbfTr1w8hISFi8Pz+/fuIiIjA+PHj8csvv6jsExwcjAEDBkAQBAQHB6sNng8fPhxr1qzBn3/+iQ8//LDC+/HaKMgH9kyBSuAcgPiz4Z6vgXqdmcKFiIiIXksMnhMRERG9BE0XMd0Z/xQbY5+UeryEnLyKaKbGhMxMXHuvUTkdTD4D/XqTphpVr3v2DCQGBhrVjY2NhZ+fHxYuXIgePXogNTUVkZGRYn7vAwcOQE9PDxEREYiJicHgwYNhYWGBOXPmaNx8xWzrnJwcAMDu3bvh4+ODjz/+GIcPH0a1atUwcuRIpVnTLVq0wO7duzFkyBDY2dkhIiIC169fx7JlyzQ+7/Hjx2FmZiYGzgGgQ4cO0NLSQlRUFHr06AEAOHjwILZu3Yrz589j+/btGh//VUhNTcXWrVsRFRWFevXqITk5GZGRkWjdunVlN61UQ4YMQdu2bbF8+XIYGBggLCwMvr6+sLa2Vql769YtHD9+HNu3b4cgCBg/fjzu3LkDe3t7pXqOjo74/PPPMXXqVPj6+kKrHBcgfq3dOQakPCyhggCkPJDXc3z93xtERET07nlHrtqIiIiIXj3FIqatqhijh7WaVUzVsJJxboMmYmNjkZeXh549e8LBwQHu7u4YOXIkjIyMAAAymQwhISFwc3ND586dERgYiO+++w4FBQUaHT8jIwPTp0+HVCqFl5cXAOD27dtYvXo1nJ2d8ffff+OLL77AmDFjsH79enG/FStWwNXVFdWrV4dMJoOvry++//57tGnTRuO+xcXFwcrKSqlMW1sb5ubmYu7wx48fw9/fH2FhYTAxMdH42AAwZcoUGBkZKT0iIyOV6rRo0UJp+7lz58p0js2bN8PZ2Rlubm6QSqXo27cvgoODy3QMTajry9y5c1/qmJ6enqhVqxbCw8MhCALCwsIwZMgQtXVDQkLQqVMnVKlSBebm5vDx8VG6M6Gw6dOnIzo6Gps2bXqp9r1R0uI1q3dlO5D+qGLbQkRERPQCODojIiIiegXeNzOCra4O4rJz1SYwkACw1dXB+2ZGr7ppyu3Q10fds2c0qptx+jTuDR9Rar0a69bCoNAs6pLOrSkPDw94e3vD3d0dPj4+6NixI3r37i3mH/fw8IBBoVnszZs3R1paGu7du6cyK7gwPz8/SKVSZGZmwtLSEsHBwWjQoAEAoKCgAI0bNxaDs56enrh8+TLWrFmDQYMGAZAHz0+cOIHdu3fD3t4eR44cwahRo2BnZ4cOHTpo3L/SDBs2DP369StTUF5h0qRJ8Pf3VyqrVq2a0vMtW7YoLZxZo0aNMp0jJCREaZHRAQMGwMvLCytWrFDJr/4y1PXlu+++w5EjR17quEOGDEFoaChq1qyJ9PR0fPjhh1i5cqVSnfz8fKxfvx7Lly8XywYMGICJEydixowZKrPLLS0txW3qUru8lYxUZ+urdToEOB0KVG8C1PUF6nQCrFyAN2j9ByIiIno7MXhORERE9ApIJRJ861wNn12OgQTKGYAV4aHZztUqfbFQiUSiceoUw5YtoW1jg7z4ePV5zyUSaFtbw7BlS41ynpeFVCrFvn37cOzYMezduxcrVqzAtGnTEBUV9VLHXbZsGTp06ABTU1NYWloqbbO1tYWrq6tSmYuLC7Zt2wYAyMzMxDfffIMdO3agc+fOAIAGDRrg/PnzWLx4scbBcxsbGyQkJCiV5eXl4cmTJ2Ie8oMHD2L37t1YvHgxAHmu+oKCAmhra2PdunXFzpQGgKpVq8LJyanENtSoUaPUOsW5evUqTpw4gZMnTyrlOc/Pz8fmzZvLdXFQdX0xNzdXem5iYoI7d+6o7JuUlASpVApDQ9W1DPr374/JkycjICAAAwcOhLa26rDp77//xoMHD1QC4fn5+Thw4AA++OADlX0mTJiAVatWYdWqVRr1741n3wIwsZMvDqr2Z0MAusaAmQMQfwm4f1L+OBAImNUE6vjKHw6tAG3VBZ2JiIiIKhrTtlSA/AIBx289xq7zD3D81mPkFxRzoUhERETvlM6WZvixvgNsdHWUym11dfBjfQd0tjSrnIa9IIlUCutvpj57UiTo/+y59TdTyz1w/vwUErRs2RKzZs3CuXPnIJPJsGPHDgDAhQsXkFlo4dMTJ07AyMio1BnUNjY2cHJyUgmcA0DLli1x7do1pbLr16+LM9lzc3ORm5urMuNYKpVqnC4GkM+ST0pKwpkzz+8AOHjwIAoKCtCsWTMA8rzo58+fFx+BgYEwNjbG+fPnxZzolSU4OBht2rTBhQsXlNo4YcKECkndUpq6deviypUryM5WXrT37NmzcHR0hI6Ojso+5ubm6NatGw4fPlzsDxHBwcHo27evUh/Pnz9fYooaIyMj/O9//8OcOXOQmpr68p173WlJAd8Fz54U/WFQIn98tAr44igw/irQeSng7ANo6wFJd4GT64CNPYGFtYAtA4Bzm4C0xFfcCSIiInqXceZ5OdtzORazfruK2OQssczWVA8zu7rCt75tJbaMiIiIXgedLc3gW9UUJ5LSkJCTByuZNt43M6r0GecvyqRjR2B5EOLnzkPes3zcAKBtbQ3rb6bKt1eAqKgoHDhwAB07doSVlRWioqKQmJgIFxcXXLx4ETk5ORg6dCimT5+OmJgYzJw5E6NHj36phRrHjx+PFi1aYO7cuejTpw9OnjyJdevWYd26dQDkM5y9vLwwadIk6Ovrw97eHocPH8aGDRuwdOlS8ThxcXGIi4vDzZs3AQCXLl2CsbExatasCXNzc7i4uMDX1xfDhg3DmjVrkJubi9GjR6Nv376ws7MDAKWUKgBw+vRpaGlpoX79+qX2IzU1VcydrmBgYKBx7vSbN28iLS0NcXFxyMzMxPnz5wEArq6ukEgk+OmnnxAYGKjSls8++wxLly7FlStX4ObmhidPnuDu3bt4+FC+oKTihwkbGxtxhn156N+/PwIDA/Hpp59i8uTJMDU1xZEjRxAUFISFCxcWu19YWBhWrVoFCwsLlW2JiYn47bffsHv3bpV+fvrpp+jRoweePHmiMgseAIYPH45ly5bh559/Fn8Meau5dgP6bAD2TFFePNTEDvCdL98OAKbVgCZD5Y+cdOD2YeD6HuD630BaHPDvb/IHJED1xs9npVu7Mb0LERERVRgGz8vRnsux+GLjWZUbEuOSs/DFxrNYPeA9BtCJiIgIUokELauUX97nymbSsSOMvb2RcfoM8hIToW1pCYPGjSpsxjkgD1QrAqApKSmwt7fHkiVL0KlTJ2zZsgXe3t5wdnZGmzZtkJ2dDT8/PwQEBLzUOZs0aYIdO3Zg6tSpCAwMhKOjI4KCgtC/f3+xzubNmzF16lT0798fT548gb29PebMmYPPP/9crLNmzRrMmjVLfK7IWx4aGirm7960aRNGjx4Nb29vaGlpoVevXvjuu+9eqv0KM2bMwIwZM5TKRowYgTVr1mi0/2effYbDhw+Lzz09PQEA0dHROHPmDB4/fqx29ruLiwtcXFwQHByMpUuXYvfu3Rg8eLC4vW/fvgCAmTNnvvTfqjAzMzNERkbi66+/Rrdu3ZCcnAwnJycsXboUQ4cOLXY/fX196BeTh3/Dhg0wNDSEt7e3yjZvb2/o6+tj48aNGDNmjMp2HR0dzJ49G/369XvxTr1pXLsB9ToDd47JFxE1spandNEq5jtCZgjU+1D+KCgAYs/Lg+jX/wJiLwD3T8kfB2cDpjWU07vo6L3SrhEREdHbTSII6hJUvr1SUlJgamqK5ORkjWfXaCK/QECrBQeVZpwXJgFgY6qHo1PaQ6rFmRFERET06hR3/ZOVlYXo6Gg4OjpCT+/tCTj5+/sjKSkJO3fuLLZOREQE/P39ERMT88ra9arFxMTA0dER79jl/luvIj63FTVGqhApD5/PSL8dAeQVGn/pGAK12z0LpvsARlaV1kwiIiJ6vWl6/cOZ5+XkZPSTYgPngHx5nNjkLJyMfoLmtVVv/SQiIiIiIqJSmNgBjYfIHzkZQPQR+Yz0638DqbHAf7/LHwBQrRFQpxNQ1xewrs/0LkRERFRmDJ6Xk4TU4gPnhcWnaFaPiIiIiOhdtWnTJowYMULtNnt7e1y5cuUVt4heSzIDeWC8ri8gCPKULtf3ANf+kqd6eXBG/jj0LWBSXT4bvW4nwKE107sQERGRRhg8LydWxppdfM367Qou3E9Clwa28KxRBVpM4UJERERUrsLCwkqt4+DggHHjxlV4WyqTmZkZZs6cWdnNeCHdunUrdjFNHR2dV9waeiNIJIBdQ/mj7ddASixw42/g2h55epeU+8DpYPlDxwCo1U4edHf2AYytK7nxRERE9LpizvNyosh5HpecpbJgqIIEUNpma6qHD91t0bmBLTxrmEHC2wiJiIioArxrOc+J3mbvfM7zF5GbKU/vck2R3uWh8na79+Qz0uv4AjbuTO9CRET0DmDO81dMqiXBzK6u+GLjWZUgueLS6zu/hjCQaeOPi7HYezUesclZCD4ajeCj0ahmpo8P3W3QuYEdPKqbMpBORERERERUHnT05Slb6vjI07vEXZTPSL++B3h49vnj0BzApNqzup0Ax9byfYmIiOidxZnn5WzP5VjM+u2q0uKhtqZ6mNnVFb71bcWyrNx8RN54hD8uPsS+q/FIz8kXt1Uz00eXBvIZ6e7VGEgnIiKil8OZ50RvD848L2epcfLZ6Nf/Bm4fAnIznm/TMQBqtX0WTPcFjG0qrZlERERUvjS9/mHwvALkFwg4Gf0ECalZsDLWQ1NHc0hLyG2elZuPw9cT8cfFWOz/Nx4ZhQLpNcz10dndDl0a2MLNzoSBdCIiIiozBs+J3h4Mnleg3Ewg5uiz9C57gJQHytvtPOVB9Dq+gK0H07sQERG9wRg8L8brfmGYlZuPiGsJ+P1iLA78m4DM3OeBdHsLA3R2t8WH7gykExERkeYYPCd6ezB4/ooIAhB36dms9L+AB2eUtxvbPk/vUsuL6V2IiIjeMAyeF+NNujDMzMnHoWsJ+ONiLA78F4+s3AJxm4OFATo3sEVndzu42BozkE5ERETFYvCc6O3B4HklSY0HbuyVz0i/dVA5vYu2vjyArpiVbmJb/HGIiIjotcDgeTHe1AvDjJw8HPxPHkg/+F8CsvOeB9JrVTWUB9Ib2KKuNQPpREREpIzBc1URERHw9/dHTExMZTfllWjbti38/f3h7+9f2U2hl8Tg+WsgN0ue3uX6X/KFR1PuK2+39ZDPSK/rC9h4AFpaldNOIiIiKpam1z/8V/wNYSDTRpcGdlg9oBHO/u8DfOfnCR83a8i0tXD7UTpWHLwJ36BIdFh6GEv3Xcf1+NTKbjIRERG9QwoKBDy49hTXT8XhwbWnKCh4M+dn/P777/Dy8oKxsTEMDAzQpEkThIWFFVv/8ePHqF69OiQSCZKSksTyo0ePomXLlrCwsIC+vj7q1auHZcuWKe3r4OAAiUSi8hg1apRSvePHj6N9+/YwNDSEiYkJ2rRpg8zMTHH79evX8dFHH6Fq1aowMTFBq1atcOjQoRL7GRAQoPbc9erVE+u0bdsWEokEmzdvVto3KCgIDg4O4vP8/HzMnz8f9erVg76+PszNzdGsWTP8+OOPKufNzMyEubk5qlatiuzs7BLbWJSDgwOCgoLU9qVhw4bic39/f3Tv3l2lXkREhNLfKSwsDBKJBC4uLip1t27dColEotRPTfug+LueOHFCqXzcuHFo27ZtSV2kN4WOHuDcAei8BBh/Gfj8H6D9dKBaYwASIPYCcHg+sK4tsNQF2D1Gnkc9J6O0IxMREdFrRruyG0BlZ6irjW4edujmYYe07Dwc+Dcev1+MxeFribiVmI7vDtzAdwduwNnKCJ0b2KJLA1s4WRlXdrOJiIjoLXXrXAIit9xAetLzQKKhmS5af+KM2p5WldiyslmxYgXGjRuHKVOmYPXq1ZDJZNi1axc+//xzXL58GYsXL1bZZ+jQoWjQoAEePFBeWNDQ0BCjR49GgwYNYGhoiKNHj2LEiBEwNDTE8OHDAQCnTp1Cfv7z9W0uX76MDz74AB9//LFYdvz4cfj6+mLq1KlYsWIFtLW1ceHCBWgVmsnapUsXODs74+DBg9DX10dQUBC6dOmCW7duwcbGptj+urm5Yf/+/Upl2trKwwM9PT1Mnz4dvXr1go6OjtrjzJo1C2vXrsXKlSvRuHFjpKSk4PTp03j69KlK3W3btsHNzQ2CIGDnzp345JNPim3fq2BoaIiEhAQcP34czZs3F8uDg4NRs2ZNtfto0gc9PT1MmTIFhw8frrC202tCIgFs6ssfbSYBaQnP07vcPAikxQFn18sf2nqAo5d8RrqzD2BarbJbT0RERKVg8PwNZ6SrjY8aVsNHDashNSsXB/6VLzZ65HoibiSkIWj/DQTtv4G61sZiapfalkaV3WwiIiJ6S9w6l4A9ay+rlKcnZWPP2svwHVG/wgLo4eHhmDVrFm7evAkDAwN4enpi165dGDVqFJKSkuDp6YmVK1ciOzsb/fr1w3fffQeZTKb2WPfu3cNXX32FcePGYe7cuWL5V199BZlMhjFjxuDjjz9Gs2bNxG2rV69GUlISZsyYgb/++kvpeJ6envD09BSfOzg4YPv27YiMjBSD55aWlkr7zJ8/H7Vr14aXl5dYNn78eIwZMwZff/21WFa3bl3x/x89eoQbN24gODgYDRo0EI+zatUqXL58ucTguba2donbAcDPzw+7d+/GDz/8gJEjR6qts3v3bowcOVIp6O/h4aG2bnBwMAYMGABBEBAcHFzpwXNtbW3069cPISEhYvD8/v37iIiIwPjx4/HLL7+o7KNJH4YPH441a9bgzz//xIcffljh/aDXiJEV4DlA/sjLBmIi5YuOXtsDJN8FbvwtfwCATQOgbif5wqO2nkzvQkRE9Briv85vEWM9HXT3rIYfBzXG6f91wNI+HvCuZwUdqQTX4lOxdN91eC85DN+gI1h58AZuJ6ZVdpOJiIjoNSMIAnKz8zV6ZGfmIXLL9RKPF7nlBrIz8zQ6XlmW4omNjYWfnx+GDBmCf//9FxEREejZs6d4jAMHDojlv/zyC7Zv345Zs2YVe7zw8HDk5uZi4sSJKttGjBgBIyMjpUDq1atXERgYiA0bNijNAi/OuXPncOzYMaXAeGE5OTnYuHEjhgwZIq5fk5CQgKioKFhZWaFFixawtraGl5cXjh49Ku5nYWGBunXrYsOGDUhPT0deXh7Wrl0LKysrNGrUqNR2lcbExATTpk1DYGAg0tPT1daxsbHBwYMHkZiYWOKxbt26hePHj6NPnz7o06cPIiMjcefOnZdu48saMmQIfv31V2RkyFNqhIWFwdfXF9bW1ip1Ne2Do6MjPv/8c0ydOhUFBQUq2+kdoa0LOHUAPlwEjLsIfHEM8J4BVG8KQALEXQQOLwB+aA8srQfs/hL47w8gR/1njYiIiF49zjx/S5no6aDne9XR873qSM7Mxb6r8fjj4kNE3niE/+JS8V9cKhbvvQ5XWxP5jHR3WzhUNazsZhMREVEly8spwLqx5ZdqIj0pGz+OP6JR3eHLvaCjK9WobmxsLPLy8tCzZ0/Y29sDANzd3cXtMpkMISEhMDAwgJubGwIDAzFp0iTMnj1bbbD7+vXrMDU1ha2trco2mUyGWrVq4fp1+Q8F2dnZ8PPzw6JFi1CzZk3cvn272HZWr14diYmJyMvLQ0BAAD777DO19Xbu3ImkpCSlBT0Vxw0ICMDixYvRsGFDbNiwAd7e3rh8+TKcnZ0hkUiwf/9+dO/eHcbGxtDS0oKVlRX27NmDKlWqlPgaXrp0CUZGynckDhgwAGvWrFEqGzlyJJYvX46lS5fif//7n8pxli5dit69e8PGxgZubm5o0aIFPvroI3Tq1EmpXkhICDp16iS2y8fHB6GhoQgICCixnYVNmTIF06dPVyrLycmBq6urxscoytPTE7Vq1UJ4eDgGDhyIsLAwLF26VO3ftSx9mD59OkJDQ7Fp0yYMHDjwhdtHbwmJBLB2kz9afwWkJQI398lzod86CKTFA2c3yB9SXaCWl3xGeh1fwLR6ZbeeiIjoncWZ5+8AU30d9G5UHaGDm+L09A5Y2LsBvOpYQltLgquxKVj09zW0XRyBLisisTriFu4+5kI2RERE9Hrz8PCAt7c33N3d8fHHH+OHH35QyrHt4eEBAwMD8Xnz5s2RlpaGe/fuvfS5p06dChcXFwwYMKDUupGRkTh9+jTWrFmDoKAgtWlAAHkqkE6dOsHOzk4sU8xYHjFiBAYPHgxPT08sW7YMdevWRUhICAD5nQKjRo2ClZUVIiMjcfLkSXTv3h1du3ZFbGxsiW2rW7cuzp8/r/QIDAxUqaerq4vAwEAsXrwYjx49Utnu6uqKy5cv48SJExgyZAgSEhLQtWtXpR8K8vPzsX79eqXXbMCAAQgLCyvTzOxJkyaptPnzzz/XeP/iDBkyBKGhoTh8+DDS09PVplopax8sLS0xceJEzJgxAzk5OS/dRnrLGFkCDfsBn/wETL4NDNwBNB0BmNUE8rPledP/+ApY5gasaQUc/Ba4fwbgnQxERESvFGeev2PMDGTo07gG+jSugafpOdh7NQ6/X4zFsVuPcflBCi4/SMGCPf+hQXVTdHa3xYfutqhhblD6gYmIiOitoC3TwvDl6lOLFPXwRhJ+X3mh1HpdRnvAztlMo3NrSiqVYt++fTh27Bj27t2LFStWYNq0aYiKitL4GIXVqVMHycnJePjwoVIAG5DPbL516xbatWsHADh48CAuXbqE8PBwABBTxVStWhXTpk1TSg/j6OgIQD4rPj4+HgEBAfDz81M6/p07d7B//35s375dqVwxC77orGoXFxfcvXtXbMvvv/+Op0+fwsTEBACwatUq7Nu3D+vXr1fKlV6UTCaDk5OTBq+OPEi8ePFifPvtt3BwcFDZrqWlhSZNmqBJkyYYN24cNm7ciIEDB2LatGlwdHTE33//jQcPHqjkB8/Pz8eBAwfwwQcfaNSOqlWrqrTZ3Nxc6bmJiYnaVCpJSUmQSqUwNFS927J///6YPHkyAgICMHDgQJWFUwG8UB8mTJiAVatWYdWqVRr1j95R2rpA7fbyR6cFQOJ/8hnp1/cA904CcZfkjyOLAEMroE5HoE4noFZbQJfrWREREVUkzjx/h1UxlOGTJjXx09BmODWtA+b1dEcrp6rQkgAX7ydj3l//ofXCQ/jo+3/ww5HbuP+UM9KJiIjedhKJBDq6Uo0eNVzNYWimW+Lx/s/efcdVWf5/HH8dDluWbFCGyBAFnGlqriRGaJn2zcyF+vWXpZXja2a500pNs8xsoTbNMrMSxYGR5sCc4AhcuDjgQPaG8/vj6NETQ1AUgc/z8bgfyX1f931f18GO13lz8bnNGhvh0tK6Ste7Weu7On3t2rUrs2fP5tChQxgaGvLLL78AcOTIEfLy8rRt9+7di5mZGS4uLuVea8CAARgYGLBo0aIyxz799FNycnK0offPP//MkSNHtCufv/zyS0Czynzs2LEV9re0tJSCgoIy+1euXIm9vT1hYWE6+93d3XF2diYhIUFnf2JiorZUzc063f8uRaOnp1ejtbb19PR49913Wb58OUlJSXdsfzPwv1knPSIigueff77MqvHnn3+eiIiIGusnaFbUHzt2rMxrffDgQZo1a4aBgUGZc6ytrXnqqaf4888/GTlyZLnXvZsxmJmZMX36dObNm0dWVta9D07UfwoF2PtCt4kwagtMPgX9PoWWT4OhOeRchkPfwprBsMADvh0A+76A9Hv/rRohhBBClCUrzwUA1o0MGdTRlUEdXbmWXUDUsRQi41TsPXONIxfSOXIhnXkbT9DGxYo+AZoV6c5WJrXdbSGEEELUIj09Bd0GehH12dEK2zz2nBd6etULxasiNjaW6OhogoKCsLe3JzY2litXruDr60tcXByFhYWMGjWKadOmkZSUxMyZMxk3blyFD/d0dXVlwYIFTJo0CWNjY4YOHYqBgQG//vorb775JpMmTaJTp04ANG/eXOfcm6VMfH19sbKyAmDZsmW4urrSokULAHbs2MH777/Pq6++qnNuaWkpK1euZPjw4WVWOysUCiZPnszMmTNp3bo1bdq04auvvuKff/7Rrnrv3LkzjRs3Zvjw4cyYMQMTExO++OILzp49WyaM/7fi4mJSUlLK3LO8B2UChIWF0alTJz777DOdNs8++yxdu3alS5cuODo6cvbsWaZOnYq3tzctWrTgypUr/P777/z222/4+fnpXHPYsGE888wzpKWllVlBfrcGDx7MnDlzGDZsGK+//jqWlpbs2LGDJUuWsGDBggrPW7VqFZ988gk2NjZljt3LGP7v//6PDz74gO+//177d0iIKmtkC20GabbiQji3S7MiPWETpJ+DU9s028b/gYOfpka6dwg0aQ9VeJixEEIIISon4bkow8bMiMGd3BjcyY0rWTeD9GRiz6Zx+EI6hy+kMzfyBO1crQgLcOZJf0ecLCVIF0IIIRqi5m3tCXnRj51rTpKTfmulr1ljIx57zovmbe3vy30tLCy0gWhmZiZubm4sWrSI0NBQ1qxZQ+/evfHy8qJ79+7aB3ze6cGU48ePx8PDg/fff58PP/yQkpISWrVqxfLlyxkxYkS1+ldaWsrUqVM5e/Ys+vr6NG/enPnz5/Piiy/qtNu2bRvnz5+vcLXz+PHjyc/PZ8KECaSlpdG6dWu2bt2qDfBtbW2Jiorirbfe4vHHH6eoqIhWrVrx66+/0rp160r7eOzYsTIPSDUyMiI/P7/Cc+bPn0+XLl109gUHB7N69WreffddMjIycHR05PHHH2fWrFno6+vz9ddf06hRI3r37l3mer1798bExIRvv/22zA8W7paVlRU7d+7kjTfe4KmnniIjIwNPT08WL17MqFGjKjzPxMQEE5Py57T3MgYDAwPefvttXnjhhbsflBAA+obQvJdmC3kPriRA4iZI3AwXYiH1qGbb+T40sgOvYM1DR5s/LuVdhBBCiLukUN8s0thAZGZmYmlpSUZGhrYupKiay1n5RB3VrEjfl5TG7X9zOrg1JuzGinQHC+Pa66QQQgghyqho/pOfn8/Zs2dp1qwZxsb39u93aaka1cl0cjILaGRhhJOX1X1ZcV4V4eHhpKens379+grbxMTEEB4eXqUSJPVBz549CQ8PJzw8vLa7Iu5RTf5/e5N8RqoHcq7Bqa2aVemnoqEg89YxpSG4d9OsSPcJ0TyUVAghhGjgqjr/kZXnosrszY0Z1tmdYZ3duZyZz6YbQfrf59LYf+46+89dZ86G4zziZk1YgBOhfo7YS5AuhBBCNAh6egqa+DSu7W4IIUTD1MgGWj+v2YoL4fxuzYr0hE1w/SycjtZsmyaDfStNiK4t76Ks7d4LIYQQDy0Jz8VdsbcwZngXd4Z3cSclI59NR1VExqnYf+46+5LS2JeUxqzfj9HR3Zo+AU6E+DlhZ175A8WEEEIIIUTD9N1335UpaXOTm5sbx44de8A9EqIO0zcEj56aLfgduJp4o056FFzYC5ePabadi8DUFryCNGF688fByLy2ey+EEEI8VKRsi6hRqow8NsZraqQfPJ+u3a+ngE7NbAgLcCLEzxFbMwnShRBCiAflQZRtqWuSkpJYv34948ePr+2uPBCrVq2iTZs2tGnTpra7Uq6srCxSU1PLPWZgYICbm9sD7tHDS8q2iHuSm6Z5wGjCphvlXTJuHdMzAPfHwCdUsyq9sfx/J4QQov6q6vxHwnNx31xKz2NTvIoNcSoOX0jX7tdTQOfmNoT5OxPcygEbCdKFEEKI+0rCcyHqDwnPRY0pKYLzezQr0hM3QdoZ3eN2vjfKu4RC0w5S3kUIIUS9IuF5BWRiWDsupOVqS7scuXhrdYNST0GX5jaE+TsR3MqRxo0Ma7GXQgghRP0k4bkQ9YeE5+K+uXpSsyI9MQrO7wV1ya1jpjaa8i7eN8q7GMvfEyGEEHWbhOcVkIlh7buQlktkvCZIj7+kG6R39bQlzN+R4FaOWJlKkC6EEELUBAnPhag/JDwXD0RumqasS+ImOLmtnPIuXTUr0r2DwbpZ7fVTCCGEuEsSnldAJoYPl3PXcrRB+rHkTO1+/ZtBeoATwS0dsTQ1qMVeCiGEEHWbhOdC1B8SnosHrqRIsxI9MUqzXTule9yuhWZFuncIuHSU8i5CCCHqBAnPKyATw4fX2as5bLxRI/2E6laQbqBU8JinLWEBzjzR0gFLEwnShRBCiOqQ8FyI+kPCc1Hrrp7SrEhP3AznduuWdzGxBq8nNEG6Z28wtqy9fgohhBCVkPC8AjIxrBvOXMnWBun/pGRp9xsoFXT3siMswInAlg5YGEuQLoQQQtyJhOdC1B8SnouHSt71G+VdouDkVshPv3VMTx/cumjKu/iEgLVHrXVTCCGE+DcJzysgE8O659RlTZAeGaciIfVWkG6o1KO7tx19Apzo7WuPuQTpQgghRLkkPC8rJiaG8PBwkpKSarsr901DGGNDJOG5eGiVFMOFWM2q9IQouHZS97itj6ZGuk8oNO0ISv3a6acQQghB1ec/eg+wT0LcFU97M17t7cXmCd3ZOqE74wO98LQ3o7CklG0nUhm/5jDt527j/77ez6+HL5FdUFzbXRZCCCEanNLSEi4ci+PErj+5cCyO0tKSO5/0kFEoFNrN0tKSrl27sn37du3x5cuXExAQgIWFBRYWFnTu3JlNmzbpXCM/P5+xY8diY2ODmZkZAwYMIDU1VafN+fPnCQsLw9TUFHt7eyZPnkxxse785bvvvqN169aYmpri5OTEyJEjuXbtmk6b9PR0xo4di5OTE0ZGRnh7e7Nx48Z7GmN4eLhOm5tbSEiIto27u7t2v1KpxNnZmVGjRnH9+nVtm5iYGJ3zHRwcGDBgAGfOnNG2+fzzz+nZsycWFhYoFArS09Mr7Xt5Y1m/fn2Z/eHh4fTr10/7dc+ePRk/fnyZdqtWrcLKykr79axZs8qM9aaFCxeiUCjo2bNnmWMXL17E0NAQPz+/CvtpbGzMuXPndPb369eP8PDwcs8Rok5S6mseJBo0F17ZD68chOB3wL2bZhX61QTY/RGsDIX3PeHn0XD0Z8jPuPO1hRBCiFoi4bmoU7wczBkf6M22iT3YMqE7r/b2wsOuEYXFpWw5nsprPxym/dtbGfPNAX4/kkyOBOlCCCHEfXcydjdfjB3Fj3PeZONHC/lxzpt8MXYUJ2N313bXqm3lypWoVCp27dqFra0tffr00Qa+TZs25b333uPAgQPs37+fxx9/nKeffppjx45pz58wYQK///47P/30E3/++SfJycn0799fe7ykpISwsDAKCwvZvXs3X331FatWrWLGjBnaNrt27WLYsGGMGjWKY8eO8dNPP7Fv3z5Gjx6tbVNYWMgTTzxBUlISa9euJSEhgS+++IImTZrc0xgBQkJCUKlUOtvq1at1rjFnzhxUKhXnz5/nu+++Y8eOHbz66qtl7pWQkEBycjI//fQTx44do2/fvpSUaH6wkpubS0hICG+++eYd+/ygODk58ccff3Dx4kWd/StWrMDV1bXcc1atWsVzzz1HZmYmsbGx5bZRKBQ632MhGgSb5tB5LIRvgMmn4dkV4P8cGFtpyr3E/whrR8ICD1jVB/Ysg2una7vXQgghhA4Jz0Wd5e1gzsQnvIme2IOo8d145XFPmtk2oqC4lKhjKbyy+hDt527l5e8OEBmnIrdQgnQhhBCipp2M3c1vi98hO+2qzv7stKv8tvid+xqgr127Fn9/f0xMTLCxsSEwMJCcnBztyuPZs2djZ2eHhYUFY8aMobCw8I7XtLKywtHRET8/P5YvX05eXh5bt24FoG/fvjz55JN4eXnh7e3NvHnzMDMzY+/evQBkZGQQERHB4sWLefzxx2nfvj0rV65k9+7d2jZbtmzh+PHjfPvtt7Rp04bQ0FDefvttli1bpu3fnj17cHd359VXX6VZs2Y89thjvPjii+zbt0/bzxUrVpCWlsb69evp2rUr7u7u9OjRg9atW9/TGAGMjIxwdHTU2Ro3bqxzDXNzcxwdHWnSpAm9evVi+PDhHDx4sMy97O3tcXJyonv37syYMYPjx49z6tQpAMaPH88bb7zBo48+esc+Pyj29vYEBQXx1Vdfafft3r2bq1evEhYWVqa9Wq1m5cqVDB06lBdeeIGIiIhyrztu3Di+/fZbjh49et/6LsRDzcQK/AbAgC80QfqITdDlVU0pl9JiSNoJm9+Epe1gaQfYMg2S/tKUghFCCCFqkYTnos5TKBS0cLRgUpAP2yf1YOOr3RjbqznuNqbkF5WyMT6Fsd8fpP3b2xj7/UE2xavIK6x7v0ouhBBCPAhqtZqi/PwqbQW5OWxf+Vml19u+6jMKcnOqdL3qPIpHpVIxaNAgRo4cyYkTJ4iJiaF///7aa0RHR2v3r169mnXr1jF79uxqvRYmJiYA5YbuJSUl/PDDD+Tk5NC5c2cADhw4QFFREYGBgdp2LVq0wNXVlT179gCaYNzf3x8HBwdtm+DgYDIzM7Ur2Dt37syFCxfYuHEjarWa1NRU1q5dy5NPPqk957fffqNz586MHTsWBwcH/Pz8eOedd7SrumtijFV16dIlfv/9dzp16nTf7/UgjBw5klWrVmm/XrFiBYMHD8bQ0LBM2z/++IPc3FwCAwMZMmSI9u/Ev3Xt2pU+ffrwxhtv3M+uC1E3KG88SDTobRi3D149BMHvQrMemvIu107C7qWwKgwWNoef/wvxazWr1YUQQogHTJ7QIeoVhUJBS2cLWjpb8L8gH44lZxJ542Gj59NyiYzT/NnUUElvXwfC/J3o6WOHsYGytrsuhBBCPBSKCwr4aPizNXa97LRrfDxiYJXavvrVWgyq+ABElUpFcXEx/fv3x83NDQB/f3/tcUNDQ1asWIGpqSmtWrVizpw5TJ48mbfffhs9vTuvH8nNzWXatGkolUp69Oih3R8fH0/nzp3Jz8/HzMyMX375hZYtWwKQkpKCoaGhTh1tAAcHB1JSUrRtbg/Obx6/eQw0Qet3333HwIEDyc/Pp7i4mL59+7Js2TLtOWfOnGH79u0MHjyYjRs3curUKV5++WWKioqYOXNmlV7Disa4YcMGzMzMdNq++eabOuVVpkyZwrRp0ygpKSE/P59OnTqxePHiCu+lUql4//33adKkCT4+PlXqX1UMGjQIpVJ3HldQUFDuKvGq6tOnD2PGjGHHjh20b9+eH3/8kb/++osVK1aUaRsREcHzzz+PUqnEz88PDw8Pfvrpp3Jrmb/77rsEBASwc+dOunXrdtf9E6LesfaAzi9rtvwMOBUNiZvh5BbIS4P4nzSbQqkJ3b2DwTsUbD1ru+dCCCEaAAnPRb2lUCjwa2KJXxNLXg/24eilTDbEJxMZp+Li9Tx+P5LM70eSaXQzSA9wooe3BOlCCCFEXdC6dWt69+6Nv78/wcHBBAUF8eyzz2rLi9x82OZNnTt3Jjs7mwsXLmjD9vLcDGPz8vKws7MjIiKCgIAA7XEfHx8OHz5MRkYGa9euZfjw4fz555/aAL0mHD9+nNdee40ZM2YQHByMSqVi8uTJjBkzRlsWpLS0FHt7ez7//HOUSiXt27fn0qVLLFy48I7h+Z3G2KtXL5YvX65zjrW1tc7XkydPJjw8HLVazYULF3jzzTcJCwtjx44dOmF206ZNUavV5Obm0rp1a37++edyV3DfrQ8++EBnpT9ogv3qrsC/nYGBAUOGDGHlypWcOXMGb29vndfnpvT0dNatW8dff/2l3TdkyBAiIiLKDc9btmzJsGHDeOONN9i1a9dd90+Ies3YEvz6a7bSEriwDxKjNNuVfzTlXZJ2asq62HiCd4hmc30UlAa13XshhBD1kITnokFQKBT4N7XEv6klb4S0IO5ihnZF+qX0PH47ksxvR5IxM9In0NeesABnunvbYqQvQboQQoiGRd/IiFe/WlulthdPHGXde7Pu2K7/G7No6utXpXtXlVKpZOvWrezevZstW7awdOlS3nrrrQof2FhVN8NYS0tL7Ozsyhw3NDTE01Oz2rF9+/b8/ffffPjhh3z22Wc4OjpSWFhIenq6zurz1NRUHB0dAXB0dNSpXX7z+M1joFmh3LVrVyZPngxAQEAAjRo1olu3bsydOxcnJyecnJwwMDDQCap9fX1JSUmhsLCw0oD6TmNs1KiRdowVsbW11bbx8vJiyZIldO7cmT/++EMnzN65cycWFhbY29tjbm5e6TXvhqOjY5m+mpubk56erv3awsKCjIyMMuemp6djaWlZ7nVHjhxJp06dOHr0KCNHjiy3zffff69ddX+TWq2mtLSUxMREvL29y5wze/ZsvL29Wb9+fRVGJ0QDp6cEt86a7YnZkHZWsyI9cRMk7YJrp2DPx5rN2BI8AzUr0r0CwaTxna8vhBBCVIGE56LBUSgUtHaxorWLFVNDW3D4QjobbwTpyRn5rD+czPrDyZgb6fNES82K9Me8JEgXQgjRMCgUiiqXTnFr3RYza9syDwu9nbmNLW6t26KnV/P/jioUCrp27UrXrl2ZMWMGbm5u/PLLLwAcOXKEvLw8bZ3tvXv3YmZmhouLS6XXLC+MrUxpaSkFBQWAJkw3MDAgOjqaAQMGAJCQkMD58+e1ddE7d+7MvHnzuHz5Mvb29gBs3boVCwsL7er13Nxc9PV1p+k3Q/KbNd27du3K999/T2lpqbYMTWJiIk5OTndc2V3dMVbFzf7l5eXp7G/WrFmZMjYPmo+PD1u2bCmz/+DBg+UG3ACtWrWiVatWxMXF8cILL5TbJiIigkmTJpVZZf7yyy+zYsUK3nvvvTLnuLi4MG7cON58802aN29e/cEI0ZBZN4NHx2i2/Ew4vV2zIv3kFsi9Bkd/1mwKpWYluncI+ISCrVdt91wIIUQdJuG5aNAUCgVtXRvT1rUxU0N9OXwxXVsXPSUzn3WHLrHu0CXMjfUJaulInwAnunraYqgvz9oVQggh9PSUPB7+f/y2+J0K2/Qa/n/3JTiPjY0lOjqaoKAg7O3tiY2N5cqVK/j6+hIXF0dhYSGjRo1i2rRpJCUlMXPmTMaNG1eleucVmTp1KqGhobi6upKVlcX3339PTEwMmzdvBsDS0pJRo0YxceJErK2tsbCw4JVXXqFz5848+uijAAQFBdGyZUuGDh3KggULSElJYdq0aYwdOxajGyvv+/bty+jRo1m+fLm2bMv48ePp2LEjzs7OALz00kt8/PHHvPbaa7zyyiucPHmSd955h1dfffUeX1lNzfCb9ddv0tfXx9bWVvt1VlYWKSkp2rItr7/+OnZ2dnTp0qXK90lJSSElJYVTp04Bmnry5ubmuLq6likTcy9uvlavvvoq//3vfzEyMiIyMpLVq1fz+++/V3je9u3bKSoqKjf8P3z4MAcPHuS7776jRYsWOscGDRrEnDlzmDt3bpkfgoDm79EXX3zB2bNnGTiwas8DEEL8i7EFtOqn2UpL4OJ+zYr0hCi4cgLO7dJsW6eDdfMbQXoIuHaW8i5CCCGqRcJzIW7Q01PQzrUx7Vwb89aTvhy6cJ0NcSo2xqtIzSzg54MX+fngRSyM9Qlu5UjYjSDdQClBuhBCiIbLq1MXnpr4JttXfa6zAt3cxpZew/8Pr05VD1Orw8LCgh07drBkyRIyMzNxc3Nj0aJFhIaGsmbNGnr37o2Xlxfdu3enoKCAQYMGMWvWrHu65+XLlxk2bBgqlQpLS0sCAgLYvHkzTzzxhLbNBx98gJ6eHgMGDKCgoIDg4GA++eQT7XGlUsmGDRt46aWX6Ny5M40aNWL48OHMmTNH2yY8PJysrCw+/vhjJk2ahJWVFY8//jjz58/XtnFxcWHz5s1MmDCBgIAAmjRpwmuvvcaUKVPuaYwAUVFRODk56ezz8fHhn3/+0X49Y8YMZsyYAYCdnR2PPPIIW7ZswcbGpsr3+fTTT5k9e7b26+7duwOwcuXKcmuG3y0PDw927NjBW2+9RWBgIIWFhbRo0YKffvqJkJCQCs9r1KhRhcciIiJo2bJlmeAc4JlnnmHcuHFs3LiRp556qsxxa2trpkyZovMAViHEPdBTgmsnzRY4C64n3SjvEgVnd0Laadi7TLMZWYJnb82KdM9AMK25H9QJIYSonxTqm7/72UBkZmZiaWlJRkYGFhYWtd0dUQeUlqo5cP66ZkV6vIorWQXaY1amBgS31ATpnZvbSJAuhBDioVTR/Cc/P5+zZ8/SrFkzjKtYqqUipaUlXDpxjOz065hZNaaJb6v7suK8KsLDw0lPT6+0rnRMTAzh4eEkJSU9sH49aA1hjA1RTf5/e5N8RhL1VkHWjfIumzVb7m1lxhR64PKoZkW6dwjYeoNCUXt9FUII8UBVdf4jK8+FuAM9PQWPuFvziLs10/u0ZH9SGpHxKjbGp3A1u4A1+y+wZv8FGpsaEOLnSJi/M496WKMvQboQQogGRE9PiUurgNruhhBCCHGLkTm0fFqzlZbApQOaFekJUXD5GJzfrdm2zoDGzTQr0r2DwbUL6Ff+/AghhBANg4TnQlSDUk9BJw8bOnnYMLNvK/adTSMyPpmooylczS5k9b4LrN53AetGhoT4OdLH34mOzSRIF0IIIYSojnfeeYd33im/ln63bt3YtGnTA+6REKLO01OCS0fN1nsGXD+nedhowiZI2gnXz8LeTzSbkYWmvIt3CHgFSXkXIYRowKRsixA1oLiklH1n09gQryLqaAppOYXaY7Zmhtoa6Z2a2aDUk18FFEII8WA9iLItdU1SUhLr169n/Pjxtd2V+6YujzEtLY20tLRyj5mYmNCkSZMH3KOHh5RtEeI+KMiC039oSruc3Aw5V24dU+iBSyfNinTvULDzkfIuQghRD1R1/iPhuRA1rLiklL1nbq1Iv55bpD1ma2ZEqJ8mSH/E3VqCdCGEEA+EhOdC1B8Sngtxn5WW3irvkhgFqUd1jzd216xI9w4Bt65S3kUIIeooCc8rIBND8SAVlZSy5/Q1IuNUbD6eQvptQbqduRFP+jkSFuBMB7fG6EmQLoQQ4j6R8FyI+kPCcyEesPQLt4L0szug5NZvGWNoDp6Pa1akez0BjWxrr59CCCGqRcLzCsjEUNSWopJSdp++RmScZkV6Zn6x9piDhRGhfk70CXCinasE6UIIIWqWhOdC1B8SngtRiwqy4UwMJG6CxC2Qc/m2gwpNPXXvEM2DR+1aSHkXIYR4iEl4XgGZGIqHQWFxKbtOX9WsSD+WQtZtQbqjhTFP+jsRFuBEWxcrCdKFEELcMwnPhag/JDwX4iFRWgrJh24E6VGQEq973MrtRpB+s7yLUe30UwghRLkkPK+ATAzFw6aguIRdp66yIU7F1mOpZBXcCtKdLW8F6W1crFDIygUhhBB3QcJzIeoPCc+FeEhlXLxR3mUznPkTSgpuHTM0g+aPa1akewVJeRchhHgISHheAZkYiodZQXEJOxOvEhmvYuvxVLJvC9KbWJkQFuBEmL8TAU0tJUgXQghRZRKeC1F/SHguRB1QmHOjvMuNMD079baDCmj6iGZFuncI2LeU8i5CCFEL6kx4vmzZMhYuXEhKSgqtW7dm6dKldOzYscL2S5YsYfny5Zw/fx5bW1ueffZZ3n333SpPHGViKOqK/KISdiReITJexbbjqeQUlmiPNW2sCdL7+Dvj18RCgnQhhBCVkvBciPpDwnMh6pjSUlAd0oToCZsgJU73uKUreAdrwnT3blLeRQghHpA6EZ6vWbOGYcOG8emnn9KpUyeWLFnCTz/9REJCAvb29mXaf//994wcOZIVK1bQpUsXEhMTCQ8P5/nnn2fx4sVVuqdMDEVdlF9UQkyCJkiPPpFK7m1Buqu1qXZFeitnCdKFEEKUJeF5WTExMYSHh5OUlFTbXblvkpKSaNasGQ3sF03rPQnPhajjMi7Byc2QEAVn/4Ti/FvHDBpB8143yrsEg5ld7fVTCCHquarOf/QeYJ/KWLx4MaNHj2bEiBG0bNmSTz/9FFNTU1asWFFu+927d9O1a1deeOEF3N3dCQoKYtCgQezbt+8B91yIB8vYQEmInyNLB7XlwLQnWD64HWEBTpgYKDmflsvymNP0WfoXPd+PYUHUPxxLzpAPykIIIR4odama/NPp5B6+TP7pdNSlde/fIYVCod0sLS3p2rUr27dv1x7fsWMHffv2xdnZGYVCwfr168tcQ61WM2PGDJycnDAxMSEwMJCTJ0/qtHF3d9e5l0Kh4L333tNp8+OPP9KmTRtMTU1xc3Nj4cKFZe61bNkyfH19MTExwcfHh6+//rrCscXExJS557+3mJgYVq1ahZWVVYWvz+1jLu812LBhAz169MDc3BxTU1MeeeQRVq1aVWG//i0pKQmFQsHhw4fLHOvZsyfjx4/Xfu3u7s6SJUvKtJs1axZt2rTRfh0eHo5CoWDMmDFl2o4dOxaFQkF4eHiZY3v27EGpVBIWFlZhP+3t7cnKytI51qZNG2bNmlXREIUQDZ1lE+gwEgb/CK+fhUE/QLvhYOYIRTnwzwb4dSy87wVf9IYdCyHlKMjnOyGEqBX6tXXjwsJCDhw4wNSpU7X79PT0CAwMZM+ePeWe06VLF7799lv27dtHx44dOXPmDBs3bmTo0KEV3qegoICCglsP6sjMzASguLiY4uJi7X319PQoLS2ltLRUpz96enqUlJToBJEV7VcqlSgUCu11b98PUFJSUqX9+vr6qNVqnf0KhQKlUlmmjxXtlzHV3zGZGCoJamnPE7525BYWE5N4lU1HU/kj4TLnruXyScxpPok5jbvNrRXpXnamOivSH7Yx1cfvk4xJxiRjkjE9TGP6d5ualnf0Kum/n6Yko/BW/ywNserbHBO/uvVQtJUrVxISEsLVq1d566236NOnD0ePHsXDw4OcnBxat27NyJEj6d+/f7nnL1iwgI8++oivvvqKZs2aMX36dIKDgzl+/LjOKuE5c+YwevRo7dfm5ubaP2/atInBgwezdOlSgoKCOHHiBKNHj8bExIRx48YBsHz5cqZOncoXX3zBI488wr59+xg9ejSNGzemb9++ZfrVpUsXVCqV9uvXXnuNzMxMVq5cqd1nbW19Tyvxly5dyvjx45kyZQrLly/H0NCQX3/9lTFjxnD06FHef//9u772vXJxceGHH37ggw8+wMTEBNCs4P7+++9xdXUt95yIiAheeeUVIiIiSE5OxtnZuUybrKws3n//fWbPnn1f+1/T5DOSjEnG9JCMSd8YPZ9QSjyDUIeWQEoceombUZzajEJ1BC7t12zb56K2aAreISh8Qil2eRT0b/2b8lCNqT5+n2RMMiYZU70cU1U/I9VaeH716lVKSkpwcHDQ2e/g4MA///xT7jkvvPACV69e5bHHHkOtVlNcXMyYMWN48803K7zPu+++W+5k9tChQzRq1AgAOzs7mjdvztmzZ7ly5Yq2TdOmTWnatCmJiYlkZGRo93t4eGBvb8/Ro0fJy8vT7m/RogVWVlYcOnRI5xsQEBCAoaEh+/fv1+lDhw4dKCwsJC7uVs0zpVLJI488QkZGhs7rYGJiQuvWrbl69SpnzpzR7re0tMTX15fk5GQuXryo3S9jajhjsgfe7dMCg/+05ovIPey+kM+h1EKSruWy7I/TLPvjNM5mejzaxIjOTQxpaq7p+8M8pvr4fZIxyZhkTDKm2hzT/QzP845e5dq3J8rsL8ko5Nq3J7AZ4nvfAvS1a9cye/ZsTp06hampKW3btuXXX39l7NixpKen07ZtWz7++GMKCgp44YUX+OijjzA0NKz0mlZWVjg6OuLo6Mjy5ctp0qQJW7du5cUXXyQ0NJTQ0NAKz1Wr1SxZsoRp06bx9NNPA/D111/j4ODA+vXref7557Vtzc3NcXR0LPc633zzDf369dOulPbw8GDq1KnMnz9fu1L6m2++4cUXX2TgwIHaNn///Tfz588vNzw3NDTUuZ+JiQkFBQUV9qG6Lly4wKRJkxg/fjzvvPOOdv+kSZMwNDTk1Vdf5T//+Q+dOnWqkftVV7t27Th9+jTr1q1j8ODBAKxbtw5XV1eaNWtWpn12djZr1qxh//79pKSksGrVqnI/c7zyyissXryYsWPHllt28mEln5FkTDKmh3hMjXrj8cxo7I2LubA9ArNLO7G8dgi9zIuw/0vY/yUKpTEZNu24bv8o6XaP4PtIz4d7TPXx+yRjkjHJmOr8mKr6GanWap4nJyfTpEkTdu/eTefOnbX7X3/9df78809iY2PLnBMTE8Pzzz/P3Llz6dSpE6dOneK1115j9OjRTJ8+vdz7lLeqwsXFhWvXrmnr2dSFn4bUx5/wyJju35iyC4qJSbjCpmOp/JFwhcLiW9dubteIPjdWpHvYmtaZMd2+H+rH90nGJGOSMcmYHtSYsrKysLa2rlLNc7VajbqolKpQl6pJXXyA0szCCtvoWRjiMLE9Cr07P5NDYaBX5Wd3qFQqXF1dWbBgAc888wxZWVns3LmTYcOGMW7cOH7++WfCwsKYPn06SUlJjBgxgtGjRzNv3jyg/JrnCoWCX375hX79+gFw/fp1rK2t+eijj3jllVd0+/qvtgBnzpyhefPmHDp0SKdsSI8ePWjTpg0ffvghoCk3kp+fT1FREa6urrzwwgtMmDABfX3NupYBAwZgamrKN998o73Gl19+yejRozl79izu7u60b9+eJ598krffflvbZtq0aSxYsICcnBwMDAwqrXkeHh5Oenp6mbIrq1atYvz48aSnp5c5599jvv3rDz74gIkTJ5KcnIyTk5POeYWFhdjY2DBq1Khyy6zc7maf//0agqZsS5s2bbTXcHd3Z/z48TqlXEBTtmX9+vXa0i83x9qjRw8iIyPZtm0bAIGBgfTp04eYmBisrKx0ysusWLGC5cuX8/fff7NhwwbGjx/PyZMntX8/b/bz4MGDjBw5kq5du/Lxxx8DmrIt/fr1Y9Z9Kt1SEzXP5TOSjEnGVMfGVJSLImkneie3oDi5GbJu/SYRgLpJe/AOoaT5E+DgBzfeqx7qMd32uteb75OMScYkY6pTY6roM9K/1drKc1tbW5RKJampqTr7U1NTK1wBM336dIYOHcp///tfAPz9/cnJyeH//u//eOutt9DTK1vC3cjICCOjsk+r1tfX135AuenmN+rfbr7wVd3/7+vezX6FQlHu/or6WN39Mqb6PSYrfX36tXOhXzsXsvKL2P7PZTbEqfgz4Qqnr+TwYfQpPow+hbeDGWH+zoQFOOFpb/ZQj+le9suYZEwgY6qoj9XdL2Oqm2Oq6F7lUReVkjxjd5Xb30lpZiGqWeWX5Ps35zldUBhWra8qlYri4mL69++Pm5sboJkb3mRoaMiKFSswNTWlVatWzJkzh8mTJ/P222+X+336t9zcXKZNm4ZSqaRHjx5V6lNKSgpAub9ZefMYwKuvvkq7du2wtrZm9+7dTJ06FZVKxeLFiwEIDg5mwoQJhIeH06tXL06dOsWiRYu043Z3dyc4OJgvv/ySfv360a5dOw4cOMCXX35JUVERV69eLRNgV0dGRgZmZmbVOicxMRFLS8ty72toaIiHhweJiYlVvl6XLl3KfJ/y8vLKBOrVMWTIEKZOncq5c+cA2LVrFz/88AMxMTFl2kZERDBkyBAAQkJCyMjI4M8//6Rnz5467RQKTb36vn37MmHCBJo3b37X/XuQ5DOSjEnGVMfGpG8BvmGaTa0G1RFI3AyJmyD5EIpLB+DSAfT/mAcWTcE7GLxDoFl3MDB+OMf0L/Xi+1SFPlZ3v4xJxgQypor6WN39d/sZqdbCc0NDQ9q3b090dLR29UppaSnR0dHaWo7/lpubW+YFvznQWlpAL8RDz9zYgKfbNOHpNk3IzC8i+kQqkXEqdiReJTE1m8TURD7YlkgLR3PC/J0IC3DCw656H5iFEEKIB61169b07t0bf39/goODCQoK4tlnn6Vx48ba46amt37DqnPnzmRnZ3PhwgVt2F6eQYMGoVQqycvLw87OjoiICAICAmq07xMnTtT++eavnL744ou8++67GBkZMXr0aE6fPk2fPn0oKirCwsKC1157jVmzZmnnwtOnTyclJYVHH30UtVqNg4MDw4cPZ8GCBVX64UBlzM3NOXjwYJn9Xl5e93Td6lizZg2+vr46+26WW7lbdnZ2hIWFsWrVKtRqNWFhYdjali0plJCQwL59+/jll18AzYevgQMHEhERUSY8B80POx577DGmT5/O999/f099FEKIO1IowLmNZus5BTJVcHILJEbB6T8g8yLsj9BsBqbg0etGmB4M5jVTqksIIRqSWgvPQfPBYfjw4XTo0IGOHTuyZMkScnJyGDFiBADDhg2jSZMmvPvuuwD07duXxYsX07ZtW23ZlunTp9O3b99qragSoqGyMDbgmbZNeaZtUzLyith2PJXIeBU7T17hn5Qs/knJYtHWRHydLOgT4MST/k40s21U290WQgjxACkM9HCe06VKbQvOZnBt5bE7trMZ0QqjZpZVundVKZVKtm7dyu7du9myZQtLly7lrbfeKrf0X3V88MEHBAYGYmlpiZ2dXbXOvfnbk6mpqTorsFNTUytdMd2pUyeKi4tJSkrCx8cHhULB/Pnzeeedd0hJScHOzo7o6GhAUw8SNHUnV6xYwWeffaa93+eff465uXm1+/1venp6eHp6Vuscb29vMjIyyn2wZmFhIadPn6ZXr15Vvp6Li0uZPtx80OdNFhYWOrUyb0pPT8fSsvy/byNHjtQu1Fm2bFm5bSIiIiguLtYZh1qtxsjIiI8//rjca7/33nt07tyZyZMnVz4wIYSoaRZO0H64ZivKg7M7NSvSEzdD5iVIiNRsAM7tNCvSfULAMUBb3kUIIUTFajU8HzhwIFeuXGHGjBmkpKTQpk0boqKitL/qev78eZ2VM9OmTUOhUDBt2jQuXbqEnZ0dffv21dauFEJUnaWJAQPaN2VA+6Zk5Bax5XgKkfEq/jp5lROqTE6oMlm4OYFWzhaE3aiR7mYjQboQQtR3CoWiyqVTjL0ao7Q0pCSj4prnSksjjL0aV6nmeXUpFAq6du1K165dmTFjBm5ubtrVwkeOHCEvL08buO7duxczMzNcXFwqvaajo2O1g+ObmjVrhqOjI9HR0dqwPDMzk9jYWF566aUKzzt8+DB6enplHjipVCpp0qQJAKtXr6Zz585lgnEDAwOaNm0KwA8//ECfPn3ueeX53RgwYABTpkxh0aJF2hIzN3366afk5OQwaNCgGr2nj48PBw4cKLP/4MGD+Pj4lHtOSEgIhYWFKBQKgoODyxwvLi7m66+/ZtGiRQQFBekc69evH6tXr9Y+yPV2HTt2pH///rzxxht3ORohhKgBBibgHaTZ1GpIidesSE/YBMkHb20x74C5s2Y1uk/ojfIuJne+vhBCNEC1Gp4DjBs3rsIyLf+uP6ivr8/MmTOZOXPmA+iZEA2HpakB/+ngwn86uJCeW8iWY6lsiFex69RVjiVnciw5kwVRCfg3sdQG6S7Wpne+sBBCiHpNoafAqm9zrn17osI2Vn097ktwHhsbS3R0NEFBQdjb2xMbG8uVK1fw9fUlLi6OwsJCRo0axbRp00hKSmLmzJmMGzfunoLl7OxsTp06pf367NmzHD58GGtra1xdXVEoFIwfP565c+fi5eVFs2bNmD59Os7OztoyhXv27CE2NpZevXphbm7Onj17mDBhAkOGDNGWnLl69Spr166lZ8+e5Ofns3LlSn766Sf+/PNP7b0TExPZt28fnTp14vr16yxevJijR4/y1Vdf3fX47sXNh7dOmjQJY2Njhg4dioGBAb/++itvvvkmkyZNolOnTjV6zwkTJtCtWzfmzZtH//79KSkpYfXq1ezZs4dPPvmk3HOUSiUnTpzQ/vnfNmzYwPXr1xk1alSZFeYDBgwgIiKi3PAcYN68ebRq1arC2ptCCPFAKRTgFKDZerwOWalwcjMkRMGZPyArGQ6s1Gz6JuDRU7Mi3StYs5pdCCEE8BCE50KIh4uVqSHPPeLCc4+4cD2nkM3HNCvSd5++RvylDOIvZfDepn8IaGpJmL+mtIsE6UII0XCZ+NliM8SX9N9P66xAV1oaYdXXAxO/sjWla4KFhQU7duxgyZIlZGZm4ubmxqJFiwgNDWXNmjX07t0bLy8vunfvTkFBAYMGDWLWrFn3dM/9+/frlB65Wbt8+PDhrFq1CoDXX39d+0D79PR0HnvsMaKiojA2NgY0D2r84YcfmDVrFgUFBTRr1owJEybo1EEH+Oqrr/jf//6HWq2mc+fOxMTE0LFjR+3xkpISFi1aREJCAgYGBvTq1Yvdu3fj7u5+T2O8F+PHj8fDw4P333+fDz/8kJKSElq1asXy5cu1ZRlrUpcuXdi0aRNz5sxh0aJF6Onp4e/vT3R0NH5+fhWeZ2FhUeGxiIgIbdmefxswYAALFiwgLi6u3Gt4e3szcuRIPv/887sbkBBC3E/mDtBumGYryoeknZoV6YmbNXXSEzdpNgCnNpoV6d7Bmj9LeRchRAOmUDewJ21mZmZiaWlJRkZGpRNnIYSua9kFbD6WSmR8MntOX6P0tneO1i5W9PF34skAJ5pYya/7CSHEw6ai+U9+fj5nz56lWbNm2nD3bqlL1RSczaA0qxA9c0OMmlnelxXnVREeHk56ejrr16+vsE1MTAzh4eEkJSU9sH49aElJSTRr1owGNt2v92ry/9ub5DOSEA2YWg2pRzUr0hOj4NIB4LZ/N8ydbjxwNASa9QBDWTglhKgfqjr/kZXnQogqsTEz4oVOrrzQyZWr2QVEHU1hY7yKvWeuceRCOkcupDNv4wnaulppV6Q7S5AuhBANhkJPgXFzq9ruhhBCCCGqQ6EAR3/N1mMyZF/WrEZPjILTf0CWCg6s0mz6xpryLjfDdAvnO1xcCCHqPgnPhRDVZmtmxJBH3RjyqBtXsgqIOpZCZFwysWfTOHQ+nUPn05kbeYL2bo21QbqjZc2sjBJCCCFE3TVmzBi+/fbbco8NGTKETz/99AH3SAghhA4ze2g3VLMV5UPSX5ogPTEKMi7c+jMTwKm1JkT3DtGUd6mFB1YLIcT9JmVbhBA15nJmPlHHUtgQp+LvpDRuf3d5xF0TpIf6O+FgIUG6EEI8SA+ibEtdk5SUxPr16xk/fnxtd+W+SU9PZ8mSJfdc670mXb58mczMzHKPWVhYYG9v/4B7VPdI2RYhRK1QqyH12K3w/OJ+dMq7mDneWpHu0VPKuwghHnpVnf9IeC6EuC9SM/PZFK8iMl7F30nXtfsVCnjE3Zo+AU6E+Dlib96wwhohhKgNEp4LUX9IeC6EeChkX4GTWzQPGT39BxRm3zqmb6ypj34zTLdsUnv9FEKICkh4XgGZGArx4Kky8tgUn0JkvIoD53SD9E7NrAkLcCaklSN25ka12EshhKi/JDwXov6Q8FwI8dApLrhV3iUhCjLO6x539AfvUPAJAae2Ut5FCPFQkPC8AjIxFKJ2JafnsfHGivRD59O1+/UU8KiHDWEBToS0csTGTIJ0IYSoKRKeC1F/SHguhHioqdVw+YRmRXriZriwD93yLg7gFQQ+oTfKuzSqrZ4KIRo4Cc8rIBNDIR4eF6/nsik+hQ3xKo5cSNfu11NAl+a2POmvKe1i3ciw9jophBD1gITnQtQfEp4LIeqUnKua8i4Jm+D0dt3yLkojaNZdsyLdOwQsm9ZeP4UQDY6E5xWQiaEQD6cLabnaFelxFzO0+5V6Cro0tyHM34ngVo40liBdCCGqTcJzIeoPCc+FEHVWcQGc26Up7ZK4CdL/Vd7Fwf9WkO7cTsq7CCHuKwnPKyATQyEefuev5bLxqIrIOBXxl24F6fp6Crp42tLH34mgVg5YmUqQLoQQVSHhuRD1h4TnQoh6Qa2GK/9oVqQnboaL+0Bdeut4I3vwDtIE6R69wMis9voqhKiXJDyvgEwMhahbzl3LITJeE6QfS87U7tfXU/CYly1h/k4EtXTE0tSgFnsphBAPNwnPy4qJiSE8PJykpKTa7soDFx4ejru7O7Nmzartroi7IOG5EKJeyrmmKe+SGAWnoqEw69YxpaGmvIt3CHgHg5Vr7fVTCFFvVHX+I78DI4R4qLnZNOLlnp5EvtqNP/7Xk8nBPvg6WVBcqiYm4QqT18bRYd5WRq76m58PXCQzv6i2uyyEEA1SaWkpZ8+eJT4+nrNnz1JaWnrnkx5CGzZsoEePHpibm2NqasojjzzCqlWryrSLjo6mS5cumJub4+joyJQpUyguLtYej4mJQaFQ0KpVK0pKSnTOtbKy0rmmu7s7CoUChUKBqakp/v7+fPnllzrnLF++HCsrKy5cuKCz/5VXXsHb25vc3NwyfRwzZgwKhYIlS5ZUOuZVq1Zp76+np0fTpk0ZMWIEly9f1rZRKBSsX7++zLnh4eH069dP5+ub1zI0NMTT05M5c+ZoX5v8/HzCw8Px9/dHX19f59zy7Nq1C319fdq0aVNpu8r6dNPN70l6erp23FZWVuVe4/bxJiUloVAoUCqVXLp0SaedSqVCX18fhUJR7g9igoODUSqV/P333+X2U6FQ8N577+nsX79+PQqF4o7jFEKIeqWRDbQZBM99Ba+fgWG/QqeXoLE7lBTCqW2w8X+wxB8+6QLRc+DC31BH5xtCiLpDwnMhRJ3RzLYRY3t5sum1bkRP6sGkJ7xp4WhOUYma7f9cZtJPR+jw9jb++9Xf/HLoIlkSpAshxANx/PhxlixZwldffcXPP//MV199xZIlSzh+/Hhtd61ali5dytNPP03Xrl2JjY0lLi6O559/njFjxvC///1P2+7IkSM8+eSThISEcOjQIdasWcNvv/3GG2+8UeaaZ86c4euvv77jvefMmYNKpeLo0aMMGTKE0aNHs2nTJu3xMWPG0LFjR0aNGqXdFx0dzfLly1m1ahWmpqY61/vll1/Yu3cvzs7OVRq7hYUFKpWKixcv8sUXX7Bp0yaGDh1apXP/LSQkBJVKxcmTJ5k0aRKzZs1i4cKFAJSUlGBiYsKrr75KYGBgpddJT09n2LBh9O7d+676UdOaNGlS5nv51Vdf0aRJk3Lbnz9/nt27dzNu3DhWrFhRbhtjY2Pmz5/P9evXa7y/QghRZ+kbgkdPCH0PXj0MY/dB4Gxw7QwKPbh8DHYugohAWOQN61+G479BQdadriyEENUm4bkQok5qbmfGK729iBrfnW0TuzMh0BtvBzMKS0rZduIyE9Ycof3cbYz+ej+/Hr5EdkHxnS8qhBCi2o4fP86PP/5IZmamzv7MzEx+/PHH+xqgr127Fn9/f0xMTLCxsSEwMJCcnBztyuPZs2djZ2eHhYUFY8aMobCwsMJrXbhwgUmTJjF+/HjeeecdWrZsiaenJ5MmTWLhwoUsWrSI2NhYANasWUNAQAAzZszA09OTHj16sGDBApYtW0ZWlu4H91deeYWZM2dSUFBQ6VhurmD38PBgypQpWFtbs3XrVu1xhUJBREQEsbGxfPrpp2RmZjJy5EgmTpxIly5ddK516dIlXnnlFb777jsMDKpW1kyhUODo6IizszOhoaG8+uqrbNu2jby8vCqdfzsjIyMcHR1xc3PjpZdeIjAwkN9++w2ARo0asXz5ckaPHo2jo2Ol1xkzZgwvvPACnTt3rnYf7ofhw4ezcuVKnX0rV65k+PDh5bZfuXIlffr04aWXXmL16tXlvpaBgYE4Ojry7rvv3pc+CyFEnadQgJ0PPDYeRkbB5NPwzOfQ6hkwsoCcK3D4O/hxKCzwgG+egdjPyz6MVAgh7pKE50KIOs/T3pzXAr3YMqEHWyZ057XeXjS3a0RhcSlbj6fy2g+Haff2Vl78Zj+/HUkmR4J0IYSokFqtprCwsEpbfn6+zuro8kRFRZGfn1+l61XnUTwqlYpBgwYxcuRITpw4QUxMDP3799deIzo6Wrt/9erVrFu3jtmzZ1d4vbVr11JUVKSzwvymF198ETMzM1avXg1AQUFBmVrTJiYm5Ofnc+DAAZ3948ePp7i4mKVLl1ZpXKWlpfz8889cv34dQ0PdB2O7uLiwZMkSJk+ezJAhQzAzM+Ptt98uc/7QoUOZPHkyrVq1qtI9y2NiYkJpaalOKZp7uVZlP7goz8qVKzlz5gwzZ8685/vXlKeeeorr16/z119/AfDXX39x/fp1+vbtW6atWq1m5cqVDBkyhBYtWuDp6cnatWvLtFMqlbzzzjssXbqUixcv3vcxCCFEnWdqDa0Hwn9W3Sjv8hs8+jI0bqYp73J6O2yafKO8S2fYNhsu7IPSkjteWgghyqNf2x0QQoia5O1gjvcT5owP9CIxNZvIuGQ2xKk4czWHzcdS2XwsFSN9PR5vYU9YgBOPt7DH1FDeCoUQ4qaioiLeeeedGrteZmZmmZrOFXnzzTfLBMYVUalUFBcX079/f9zc3ADw9/fXHjc0NGTFihWYmprSqlUr5syZw+TJk3n77bfR0yu7fiQxMRFLS0ucnJzKHDM0NMTDw4PExERAU8d6yZIlrF69mueee46UlBTmzJmj7dftTE1NmTlzJm+++SajR4/G0tKy3PFMmTKFadOmUVBQQHFxMdbW1vz3v/8t027EiBF8/vnn/P7778TGxmJkZKRzfP78+ejr6/Pqq69W9vJV6uTJk3z66ad06NABc3Nz7f5BgwahVCp12hYUFBAWFlbuddRqNdHR0WzevJlXXnmlWvd/44032LlzJ/r6d/dv9IYNGzAzM9PZ9+/a89VlYGDAkCFDWLFiBY899hgrVqxgyJAh5a7u37ZtG7m5uQQHBwMwZMgQIiIiyi2F88wzz9CmTRtmzpxJRETEPfVRCCEaFKUBePTQbMHvwNWTkLgJEjfD+T1w+bhm+2sxmNqCVxD4hIBHLzCWhyMLIapGVp4LIeolhUKBj6M5E4N8iJ7Ug02vdWNcL0+a2TaioLiUTUdTGPf9Idq9vZWx3x1kY7yKvEJZjSCEEHVF69at6d27N/7+/vznP//hiy++0Kkb3bp1a5064J07dyY7O7vMAzer42awHxQUxMKFCxkzZgxGRkZ4e3vz5JNPApQbzI8aNQobGxvmz59f4bUnT57M4cOH2b59O506deKDDz7A09OzTLsjR45w8OBBTE1N2blzp86xAwcO8OGHH2ofAFodGRkZmJmZYWpqio+PDw4ODnz33Xc6bT744AMOHz6ssz311FNlrnUzuDY2NiY0NJSBAwcya9asKvWjpKSEF154gdmzZ+Pt7V2tMdyuV69eZfr674ew3o2RI0fy008/kZKSwk8//cTIkSPLbbdixQoGDhyoDf8HDRrErl27OH36dLnt58+fz1dffcWJEyfuuY9CCNEgKRRg5w1dX4MRGzXlXfp/AX4DwMgScq/Cke/hx2Ga8i5f94O9n8L1pNruuRDiISfLLYUQ9Z5CocDXyQJfJwsmBXlzXJVJZJyKyHgV567lEhmv+bOJgZLHfe3p4+9ETx97TAyVd764EELUMwYGBrz55ptVanvu3LkyAWt5Bg8erF0dfqd7V5VSqWTr1q3s3r2bLVu2sHTpUt566y1tXfLq8vLyIiMjg+Tk5DIP2SwsLOT06dPaVcQAEydOZMKECahUKho3bkxSUhJTp07Fw8OjzLX19fWZN28e4eHhjBs3rtz729ra4unpiaenJz/99BP+/v506NCBli1b6vRj2LBhDB48mB49ejBmzBj69OmDj48PADt37uTy5cu4urpqzykpKWHSpEksWbKEpKSkCsdvbm7OwYMH0dPTw8nJCRMTkzJtHB0dywT65ubmpKen6+zr1asXy5cvx9DQEGdn52qtHs/KymL//v0cOnRI+1qVlpaiVqvR19dny5YtPP7443e8TqNGjcr09d9lUSwsLMjJyaG0tFTnhx43x1Pebwn4+/vTokULBg0ahK+vL35+fhw+fFinTVpaGr/88gtFRUUsX75cu7+kpIQVK1Ywb968Mtft3r07wcHBTJ06lfDw8DuOTwghxB2YWkPAc5qtpEizEj1xMyRsgrTTcOYPzRY1Bex8wTsYfEKh6SOgJ58DhRC3SHguhGhQFAoFrZwtaeVsyeRgH44lZ7IhTkVkfDIX0vI0oXqcClNDJb19HQjzd6Knjx3GBjKBEkI0DAqFosqlU5o3b46FhUWZh4XezsLCgubNm5e7IvteKRQKunbtSteuXZkxYwZubm788ssvgGaFdl5enjYE3rt3L2ZmZri4uJR7rWeffZYpU6awaNEiFi1apHPs008/JTc3l2HDhpW5/82gffXq1bi4uNCuXbtyr/+f//yHhQsXVlp3/SYXFxcGDhzI1KlT+fXXX7X758yZQ1paGh988AGWlpb8/PPPjBgxgr/++gs9PT2GDh1KYGCgzrWCg4MZOnQoI0aMqPSeenp65a50vxvlBddVZWFhQXx8vM6+Tz75hO3bt7N27VqaNWtWE10EwMfHh+LiYg4fPqzzfTt48CBAhSvfR44cycsvv6wTjN/uu+++o2nTpqxfv15n/5YtW1i0aBFz5swpU/4G4L333qNNmzbaH4YIIYSoIUoDaNZdswXPu1HeJQoSojSh+pUTmm3XEjCxvlXepXlvKe8ihJDwXAjRcCkUCvyaWOLXxJIpIT7EX8rQrEKPU3Hxeh6/H0nm9yPJNDJUEthSE6R395YgXQghbtLT0yMkJIQff/yxwjYhISH3JTiPjY0lOjqaoKAg7O3tiY2N5cqVK/j6+hIXF0dhYSGjRo1i2rRpJCUlMXPmTMaNG1dhX1xdXVmwYAH/+9//MDY2ZujQoRgYGPDrr7/y5ptvMnfuXPz8/LTtFy5cqB3bunXreO+99/jxxx/LDUVveu+993RWr1fmtddew8/Pj/3799OhQwf+/vtv5s+fT2RkpHZF9GeffYafnx8ffPABkyZNwsbGBhsbG53rGBgY4Ojo+FAFssePH6ewsJC0tDSysrK0K7fbtGmDnp6ezusMYG9vj7GxcZn996pVq1YEBQUxcuRIFi1ahIeHBwkJCYwfP56BAwfSpEmTcs8bPXo0//nPf7Cysir3eEREBM8++2yZ/rq4uDB16lSioqLKrRPv7+/P4MGD+eijj+55bEIIISph66XZurwCuWmah4wmbIJTWyEvDeJ+0Gx6BuDWRbMi3TsErGvuB7hCiLpDwnMhhEATpAc0tSKgqRVvhLQg7uKtIP1Seh6/Hk7m18PJmBnp88SNIL2bty1G+hKkCyEatpYtW/Lcc88RFRWlswLdwsKCkJAQnbIjNcnCwoIdO3awZMkSMjMzcXNzY9GiRYSGhrJmzRp69+6Nl5cX3bt3p6CggEGDBt2x7vaECRPw8PBg0aJFfPjhh+Tk5ACaVeXPP/+8TttNmzYxb948CgoKaN26Nb/++iuhoaGVXv/xxx/n8ccfZ8uWLXccX8uWLQkKCmLGjBn88ssvDB8+nBEjRhAUFKRt4+TkxNKlSxk1apRO+ZaH3ZNPPsm5c+e0X7dt2xbQPGD0QVuzZg0zZ87kxRdfJDk5maZNm/LMM88wffr0Cs/R19fH1ta23GMHDhzgyJEjfPHFF2WOWVpa0rt3byIiIip8yOqcOXNYs2bN3Q1GCCFE9Zlag/+zmq2kCC7EaoL0xCi4dgrO/qnZot4AWx/NinTvUHDpKOVdhGggFOramKXWoszMTCwtLcnIyMDCQn79RghRObVazeEL6doa6aqMfO0xcyN9nmjlQJ8AJx7ztMNQX57BLIR4OFU0/8nPz+fs2bM0a9YMY2Pje7pHaWkp586dIzs7GzMzM9zc3O7LivOqCA8PJz09vUzZjNvFxMQQHh5eaR3wtLQ0evfujYWFBZs2bdJ5AGldFh4ejru7e5Uf4ikeLjX5/+1N8hlJCCHKcfWUJkRPjIJzu0FdcuuYSWNNeRfvEPDsDcZln5MhhHi4VXX+IyvPhRCiEgqFgraujWnr2pg3n/Tl0I0gfWO8ipTMfNYdvMS6g5ewMNYnqJUjYQFOdG1uK0G6EKLB0dPTq9F61A8Da2trtm3bxrJly9izZw+9e/eu7S4JIYQQ4kGx9QTbcdBlHOSlw6ltmiD95FbIuw5xazSbnr6mvIt3qObBozbNa7vnQogaJOG5EEJUkZ6egvZujWnv1phpYb4cPH+dDTeC9MtZBaw9cJG1By5iaWJAcCsHwgKc6dLcBgOlBOlCCFFX2djYMGPGjNruhrjh/PnzlZYCOn78OK6urg+wR0IIIRoEE6vbyrsUa8q73FyVfjURzu7QbJungq23ZkW6dwi4dAKlRG9C1GVStkUIIe5Raama/eeuExmXzMajKVzJKtAeszI1IOTGivTOHjboS5AuhKgFD6JsS12TlJTE+vXrGT9+fG135YFbv349VlZW9OzZs7a7Um3FxcWVltpxd3dHX79+hxRStkUIIR4y105D4mZI3KQp71JafOuYSWPwfEKzIt0zUBPCCyEeClWd/0h4LoQQNaikVM3fSWlExqnYdFTF1exC7bHGpgaE+DkS5u/Mox7WEqQLIR4YCc+FqD8kPBdCiIdYXjqcjtaE6Se3aMq73KSnD66dNSvSfUKlvIsQtUzC8wrIxFAI8aCUlKqJPXuNyDgVUUdTuJZzK0i3bmRIiJ8jffyd6ORhg1JPUYs9FULUdxKeC1F/SHguhBB1REkxXNynKe2SEAVXE3SP23hpVqT7hILLo1LeRYgHTMLzCsjEUAhRG4pLStl3No0N8ZogPe22IN3WzFC7Ir1jM2sJ0oUQNU7CcyHqDwnPhRCijko7o1mRnrAJzu3SLe9ibKkp7+ITCp69NeVehBD3lYTnFZCJoRCithWXlLL3TBqR8clsOppCem6R9pitmRFP+jsS5u9EB3cJ0oUQNUPCcyHqDwnPhRCiHsjPgNPbNSvST26BvLRbxxRKTXkXnxsPHbX1qr1+ClGPSXheAZkYCiEeJkUlpew5faO0y7EUMvJuBen25kY86e9EWIAT7V0boydBuhDiLkl4LkT9IeG5EELUM6UlcPFvzYr0xM1w5YTucevmmhXp3iHg+igoDWqnn0LUMxKeV0AmhkKIh1VRSSm7Tl0lMk7F5mMpZObf+jU+BwtNkN4nwIm2LhKkCyGqR8JzIeoPCc+FEKKeSzurCdEToyDpLyi9tcBKU94lELxvlHcxta69fgpRx0l4XgGZGAoh6oLCYk2QviFOxZbjKWTdFqQ7WRprV6S3dbFCoZAgXQhROQnPhag/JDwXQogGJD9TU94lcTOc3Ay5124dUyg1K9G9byvvIp8NhagyCc8rIBNDIURdU1Bcwl8nNSvStx5PJavgVpDexMpEUyM9wJnWTS0lSBdClOtBhOdqdQnp6X9TUHAZIyN7rKweQaFQ3mvX75uYmBjCw8NJSkqq7a7cd+7u7qxatYqePXvWdldEDZDwXAghGqjSEri4X7MiPTEKLh/XPW7toVmR7h0Mbl2kvIsQd1DV+Y/eA+yTEEKIu2Ckr6S3rwOLB7bh72mBfDGsA/3aONPIUMml9Dy+2HmWfst28dj8P3h34wmOXEingf1cVAhRyy5f3syu3d05eGgwx45P4OChweza3Z3LlzfXdteqRaFQaDdLS0u6du3K9u3bddosW7YMd3d3jI2N6dSpE/v27dM57u7urr2GiYkJ7u7uPPfcc2Wuk5SUpHM/GxsbgoKCOHToEABFRUVMmTIFf39/GjVqhLOzM8OGDSM5OVnnOk899RSurq4YGxvj5OTE0KFDy7QpT0pKCq+88goeHh4YGRnh4uJC3759iY6OLtP23XffRalUsnDhwjLHVq1ahZWVVYX3CQ8PR6FQMGbMmDLHxo4di0KhIDw8XLtvx44d9O3bF2dnZxQKBevXr7/jWG7Xs2dPxo8ff8d+zpo1izZt2pRpd/P7cvjwYUDzQxaFQkHjxo3Jz8/Xafv3339rv3/ladGiBUZGRqSkpJTbT4VCwQ8//KCzf8mSJbi7u1c6RiGEEA2UnhJcO0HgTHh5D7wWB6ELofnjoDSEtDOwdxl8/RQsaA4/jYAjayA37c7XFkJUSMJzIYSoQ4wNlDzR0oElz7flwPQn+Gxoe55q7YzpjSD9sx1neHrZLrot+IN3N50g/mKGBOlCiPvq8uXNxB8dS0GBbkBYUJBK/NGxdS5AX7lyJSqVil27dmFra0ufPn04c+YMAGvWrGHixInMnDmTgwcP0rp1a4KDg7l8+bLONebMmYNKpSIhIYGvv/4aKysrAgMDmTdvXpn7bdu2DZVKxebNm8nOziY0NJT09HRyc3M5ePAg06dP5+DBg6xbt46EhASeeuopnfN79erFjz/+SEJCAj///DOnT5/m2WefrXSMSUlJtG/fnu3bt7Nw4ULi4+OJioqiV69ejB07tkz7FStW8Prrr7NixYrqvpwAuLi48MMPP5CXl6fdl5+fz/fff4+rq6tO25ycHFq3bs2yZcvu6l73i7m5Ob/88ovOvoiIiDL9v+mvv/4iLy+PZ599lq+++qrcNsbGxkybNo2ioqJyjwshhBCVauwGnf4Phv4Cr5+B576BNoPB1BYKMuDYOvjl/2Bhc1gRAn8tgSsJIJ8PhagWCc+FEKKOMjZQEtzKkY8GteXg9Cf4dEh7+t4I0i9ez+OzP8/Q9+O/6LEwhvlR/3D0kgTpQog7U6vVlJTkVmkrLs4iMXE2UN57i2Zf4sk5FBdnVel61X2PWrt2Lf7+/piYmGBjY0NgYCA5OTmEh4fTr18/Zs+ejZ2dHRYWFowZM4bCwsI7XtPKygpHR0f8/PxYvnw5eXl5bN26FYDFixczevRoRowYQcuWLfn0008xNTUtEyqbm5vj6OiIq6sr3bt35/PPP2f69OnMmDGDhIQEnbY2NjY4OjrSoUMH3n//fVJTU4mNjcXS0pKtW7fy3HPP4ePjw6OPPsrHH3/MgQMHOH/+vPb8CRMm8Oijj+Lm5kaXLl1444032Lt3b6WB7Msvv4xCoWDfvn0MGDAAb29vWrVqxcSJE9m7d69O2z///JO8vDzmzJlDZmYmu3fvvuNr+G/t2rXDxcWFdevWafetW7cOV1dX2rZtq9M2NDSUuXPn8swzz1T7PvfT8OHDdb7PeXl5/PDDDwwfPrzc9hEREbzwwgsMHTq0wh86DBo0iPT0dL744ov70mchhBANiJE5tHwK+n0C/zsJo7ZBt0lg3wrUpXB+D2ybCcs6wkdtYNMbcCYGiu88NxKiodOv7Q4IIYS4d8YGSkL8HAnxcySvsISYhMtsiFex/cRlzqflsjzmNMtjTuNuY0pYgBNh/s74OplLjXQhRBmlpXnE/OlfQ1dTU1CQwp872lSpdc8e8SiVplVqq1KpGDRoEAsWLOCZZ54hKyuLnTt3agP46OhojI2NiYmJISkpiREjRmBjY1Pu6u+KmJiYAFBYWEhhYSEHDhxg6tSp2uN6enoEBgayZ8+eO17rtdde4+233+bXX3/l9ddfv+P9ypORkYFCoaiwTEpaWhrfffcdXbp0wcCg/DqnaWlpREVFMW/ePBo1alTm+L+vHRERwaBBgzAwMGDQoEFERETQpUuXCkZZsZEjR7Jy5UoGDx4MaFazjxgxgpiYmGpfqzYMHTqUhQsXcv78eVxdXfn5559xd3enXbt2ZdpmZWXx008/ERsbS4sWLcjIyGDnzp1069ZNp52FhQVvvfUWc+bMYfjw4eV+P4QQQohq09MDl0c0W+8ZkH5e88DRhE2QtBOuJ0Hscs1mZKEp++ITCp5PQCOb2u69EA8dWXkuhBD1jImhklB/J5a90I4D0wNZ9kI7nvR3xNhAj6RruSz74zRPfrST3ov+ZNGWBP5JyZQV6UKIOkelUlFcXEz//v1xd3fH39+fl19+GTMzMwAMDQ1ZsWIFrVq1IiwsjDlz5vDRRx9RWlpapevn5uYybdo0lEolPXr04OrVq5SUlODg4KDTzsHBodya1v9mbW2Nvb19hQ8oTU9P5+2338bMzIyOHTuWOZ6fn8+UKVMYNGhQmQcaTZkyhUaNGmFjY8P58+f59ddfK+zHqVOnUKvVtGjR4o59zszMZO3atQwZMgSAIUOG8OOPP5KdnX3Hc/9tyJAh/PXXX5w7d45z586xa9cu7XVr2ieffIKZmZnOVl7N9eqwt7cnNDSUVatWAZrwf+TIkeW2/eGHH/Dy8qJVq1YolUqef/55IiIiym378ssvY2xszOLFi++pf0IIIUSFrFyh42gYug5ePwsDv4U2Q6CRHRRkwvH18MuL8L4nRATDXx/A5RNS3kWIG2TluRBC1GOmhvqaleYBTuQUFLP9n8tExqn4I+EyZ67msHT7KZZuP0Vzu0aEBTjTJ8AJbwfz2u62EKIW6emZ0LNHfJXaXk//myNHyg8Qb9e69QoaWz1SpXtXVevWrenduzf+/v4EBwcTFBTEs88+S+PGjbXHTU1vrWLv3Lkz2dnZXLhwATc3twqvO2jQIJRKJXl5edjZ2REREUFAQECVHsJ5J2q1usxv/HTp0gU9PT1ycnLw8PBgzZo1ZQL6oqIinnvuOdRqNcuXLy9z3cmTJzNq1CjOnTvH7NmzGTZsGBs2bCj3t4uq88PS1atX07x5c1q3bg1AmzZtcHNzY82aNYwaNarK1wGws7MjLCyMVatWoVarCQsLw9bWtlrXqKrBgwfz1ltv6exbt24d77zzzj1dd+TIkbz22msMGTKEPXv28NNPP7Fz584y7VasWKHzg4EhQ4bQo0cPli5dirm57r+xRkZGzJkzh1deeYWXXnrpnvonhBBC3JGRGfj21WylpZB8ULMiPXEzpMbDhb2abdsssHLTrEj3Dga3x0DfsLZ7L0StkPBcCCEaiEZG+vRt7Uzf1s5kFxQTfSKVyDgVMYlXOH0lh4+iT/JR9Em87M0IC3CiT4ATnvYSpAvR0CgUiiqXTrGxfgwjI0cKClIpv+65AiMjR2ysH0OhUNZoP5VKJVu3bmX37t1s2bKFpUuX8tZbbxEbG3tP1/3ggw8IDAzE0tISOzs77X5bW1uUSiWpqak67VNTU3F0dLzjda9du8aVK1do1qyZzv41a9bQsmVLbGxsyi3HcjM4P3fuHNu3by+z6vxm32xtbfH29sbX1xcXFxf27t1L586dy7T18vJCoVDwzz//3LHPERERHDt2DH39Wx8ZSktLWbFiRbXDc9CEz+PGjQO4rw8EtbS0xNPTU2efvb29ztcWFhZkZGSUOTc9PV17jX8LDQ3l//7v/xg1ahR9+/bFxqbsr7YfP36cvXv3sm/fPqZMmaLdX1JSwg8//MDo0aPLnDNkyBDef/995s6di7u7e1WGKIQQQtw7PT1o2kGz9Z4O6RcgMUoTpJ/dAennIPZTzWZoDp6Pg3cIeAVBo/vzA3AhHkZStkUIIRogMyN9nm7ThM+HdeDAtECWDGxDoK8Dhko9Tl7OZsm2kwQu3kHwBzv4KPokp69U/1f0hRD1n0KhxNtrxs2v/n0UAG+v6TUenN+6v4KuXbsye/ZsDh06hKGhIb/88gsAR44cIS8vT9t27969mJmZ4eLiUuk1HR0d8fT01AnOQVMGpn379kRHR2v3lZaWEh0dXW5I/W8ffvghenp69OvXT2e/i4sLzZs3rzQ4P3nyJNu2bSs3rP23m2VpCgoKyj1ubW1NcHAwy5YtIycnp8zxm+FxfHw8+/fvJyYmhsOHD2u3mJgY9uzZU6Xw/d9CQkIoLCykqKiI4ODgap9fk3x8fLh48WKZH4YcPHgQY2NjXF1dy5yjr6/PsGHDiImJqbBkS0REBN27d+fIkSM6r9vEiRMrLN2ip6fHu+++y/Llyyss6yOEEELcd1YumvIuQ9bC62fg+e+h7VBoZA+FWXD8V1j/Eiz0hIgg2LkIUo9LeRdR78nKcyGEaODMjQ3o17YJ/do2ITO/iG3HNSvSd5y8QkJqFglbs1i8NZEWjub0CXDiSX8nPOzMarvbQoiHhL19MP5+y0g8OYeCglu1v42MHPH2mo69/f0JSWNjY4mOjiYoKAh7e3tiY2O5cuUKvr6+xMXFUVhYyKhRo5g2bRpJSUnMnDmTcePGoad392tHJk6cyPDhw+nQoQMdO3ZkyZIl5OTkMGLECJ12WVlZpKSkUFRUxNmzZ/n222/58ssveffdd8usiK5IUVERzz77LAcPHmTDhg2UlJRoa6tbW1tjaGhIbGwsf//9N4899hiNGzfm9OnTTJ8+nebNm1ca6C9btoyuXbvSsWNH5syZQ0BAAMXFxWzdupXly5dz4sQJIiIi6NixI927dy9z/iOPPEJERAQLFy4ENKuqDx8+rNPGyMgIX19fnX1KpZITJ05o/1ye7OxsTp06pf367NmzHD58GGtr63ID7bsVHByMj48PgwYNYu7cuTg6OnLw4EGmTZvGa6+9VmH/3n77bSZPnlzuDzKKior45ptvmDNnDn5+fjrH/vvf/7J48WKOHTtGq1atypwbFhZGp06d+Oyzz8qU7RFCCCEeOCMzaBGm2UpLQXUIEqIgcROkxMOFWM0WPUdTU907RLO5Pwb6RrXdeyFqlITnQgghtCyMDejfrin92zUlI6+IrcdTiYxLZufJq/yTksU/KVm8vyWRlk4Wmlrq/k642zaq7W4LIWqZvX0wdnaBpKf/TUHBZYyM7LGyeuS+rTgHTdmNHTt2sGTJEjIzM3Fzc2PRokWEhoayZs0aevfujZeXF927d6egoIBBgwYxa9ase7rnwIEDuXLlCjNmzCAlJYU2bdoQFRVVJuycMWMGM2bMwNDQEEdHRx599FGio6Pp1atXle916dIlfvvtN0BTa/x2f/zxBz179sTU1JR169Yxc+ZMcnJycHJyIiQkhGnTpmFkVPEHVw8PDw4ePMi8efOYNGkSKpUKOzs72rdvz/LlyyksLOTbb7/VKTtyuwEDBrBo0SJtDfHs7Gzatm2r06Z58+Y6IfhN5ZWdud3+/ft1XqeJEycCMHz4cO3DOmuCvr4+W7Zs4c0332TQoEHakjqvvfaa9p7lMTQ0rLBW+2+//ca1a9d45plnyhzz9fXF19eXiIiICh8OOn/+fLp06XJ3AxJCCCHuFz09aNJesz3+FmRculHeJQrO/Anp52Hf55rN0Aya9wLvUE15FzO7O19fiIecQl2dpwbVA5mZmVhaWpKRkXHHybsQQgiNjNwiNh9PITJOxa5TVykuvfVPRyvnW0G6m40E6UI8jCqa/+Tn53P27FmaNWuGsbFxLfawZoWHh5Oens769esrbBMTE0N4eHiDKJPh7u7OqlWr6NmzZ213RdSA+/H/rXxGEkIIcVcKczQBeuKNh45m314OTaGpp+4donnwqH1LKOdh5kLUlqrOf2TluRBCiDuyNDXguQ4uPNfBhes5hWw5nkJkfAq7Tl3lWHImx5IzWRCVgH8TS22Q7mJdtQcOCiGEEEIIIYSogwwbQYsnNVtpKagOa1akJ2yClDi4+Ldm2/42WLqCdzD4hIB7NynvIuoMCc+FEEJUS+NGhgx8xJWBj7iSllPIlmMpRMar2H36GvGXMoi/lMF7m/6hdVNNkP6kvxNNG0uQLoQQ4t7s3LmT0NDQCo9nZ8vDrYUQQohao6cHTdpptl5vQmbyjfIum+FMDGSch7+/0GwGjW6UdwnRBOpm9rXdeyEqJGVbhBBC1Ihr2QVsPpZKZHwye05f47bKLrRxsaJPgBOh/k40sTKpvU4K0UA1tLItVZGUlMT69esZP358bXflvluyZAn9+vXD3d29trtyT/Ly8rh06VKFx6v6MNa6Tsq2CCGEqHMKc+Hsn7fC9CzVbQcVmnrq3iGaVekOflLeRTwQVZ3/SHguhBCixl3NLiDqqKZGeuxZ3SC9nasVYQHOPOnviJOlBOlCPAgSngtRf0h4LoQQok5Tq2+Ud9msKe+iOqx73KLpjfIuoZryLgYyRxX3h4TnFZCJoRBCPFiXs/LZfDSFDXEq9iWlcfu/Oh3cGmtLuzhYyKRIiPtFwnMh6g8Jz4UQQtQrmSo4uRkSojTlXYrzbh0zMAWPXpoV6V7BYO5Qa90U9Y+E5xWQiaEQQtSey5n5bLqxIv3vc7eCdIUCHnGzJizAiVA/R+wlSBeiRkl4LkT9IeG5EEKIeqsoD87u0KxIT9wMWcm6x2+Wd/EOAUd/Ke8i7omE5xWQiaEQQjwcUjLy2XRURWSciv3nrmv3KxTQ0d2aPgFOBPs5Ym8ugZ4Q90rCcyHqDwnPhRBCNAhqNaTEaVakJ26C5EO6xy2aaMq7eIdCs25gICVBRfVIeF4BmRgKIcTDR5WRx8b4FCLjkjl4Pl27X08BnZrZ8GSAEyGtHLEzN6q9TgpRh0l4LkT9IeG5EEKIBikrRbMaPXEznPkDinJvHTMwBY+eN1alB4O5Y611U9QdEp5XQCaGQgjxcLuUnsemeBUb4lQcvpCu3a+ngEc9bAi7EaTbmEmQLkRVSXguRP0h4bkQQogGrygPzu6ExCjNlnlJ97hzW82KdO9gcGot5V1EuSQ8r4BMDIUQou64eD2XTfEpbIhXceS2IF2pp6DzjSA9uJUj1o0Ma6+TQtQBEp6XFRMTQ3h4OElJSbXdlftm1apVrFq1ipiYmNruiqhBEp4LIYQQt1GrISX+VpB+6YDucXPnG+VdQsCjh5R3EVpVnf/oPcA+CSGEENXStLEpo7t78OvYrux8vRdTQ1sQ0NSSklI1f526ytR18TwybxtDI2JZ8/d5rucU1naXhWiwStRqdl3P4pfU6+y6nkVJHVyfoVAotJulpSVdu3Zl+/btOm2WLVuGu7s7xsbGdOrUiX379pV7LbVaTWhoKAqFgvXr12v3r1q1Suc+t2+XL1/WuY+vry8mJib4+Pjw9ddf61z/iy++oFu3bjRu3JjGjRsTGBhYYV9uSkpKQqFQcPjw4TLHevbsyfjx47Vfnz17lhdeeAFnZ2eMjY1p2rQpTz/9NP/880+VX6/w8HCdNjY2NoSEhBAXF6dz73nz5tGlSxdMTU2xsrKqdAz3MiZ3d3eWLFlSpt2sWbNo06ZNmX6PGTOmTNuxY8eiUCgIDw8vc2zPnj0olUrCwsIq7Ke9vT1ZWVk6x9q0acOsWbMqGqIQQgghKqNQgFMA9HgdRm+HSYnw1FJo0UdTziUrGQ6shNUDYX4z+P552L8SMlW13XNRR0h4LoQQok5wsTblxR7N+W3cY+yY3IspIS3wa2JBSamanSevMuVnTZA+fMU+ftx/gYzcotrushANRuSVdDrsOc6Aw6d56fg5Bhw+TYc9x4m8kl7bXau2lStXolKp2LVrF7a2tvTp04czZ84AsGbNGiZOnMjMmTM5ePAgrVu3Jjg4WCf0vmnJkiUoyvkV4YEDB6JSqXS24OBgevTogb29PQDLly9n6tSpzJo1i2PHjjF79mzGjh3L77//rr1OTEwMgwYN4o8//mDPnj24uLgQFBTEpUuXytyzuoqKinjiiSfIyMhg3bp1JCQksGbNGvz9/UlPT6/y6wUQEhKiHWd0dDT6+vr06dNH5xqFhYX85z//4aWXXrrnvtcUFxcXfvjhB/Ly8rT78vPz+f7773F1dS33nIiICF555RV27NhBcnJyuW2ysrJ4//3370ufhRBCCAGYO0C7YfD8d/D6WRi8Fh75L1g0heI8zcNHN4yHxS3gsx7wx7uah5HWwYUf4sGQ8FwIIUSd42pjyks9m7PhlW7E/K8nk4N9aOlkQXGpmj8Tr/D62jg6zNvKiJX7WHvgIhl5EqQLcb9EXknnv0eTUBXo/n+WUlDEf48m3dcAfe3atfj7+2NiYoKNjQ2BgYHk5OQQHh5Ov379mD17NnZ2dlhYWDBmzBgKC+/82ylWVlY4Ojri5+fH8uXLycvLY+vWrQAsXryY0aNHM2LECFq2bMmnn36KqakpK1as0LnG4cOHWbRoUZn9ACYmJjg6Omo3pVLJ9u3bGTVqlLbNN998w4svvsjAgQPx8PDg+eef5//+7/+YP3++ts13333Hyy+/TJs2bWjRogVffvklpaWlREdH3+3LqXXs2DFOnz7NJ598wqOPPoqbmxtdu3Zl7ty5PProo1V+vQCMjIy0Y23Tpg1vvPEGFy5c4MqVK9o2s2fPZsKECfj7+99z32tKu3btcHFxYd26ddp969atw9XVlbZt25Zpn52dzZo1a3jppZcICwtj1apV5V73lVdeYfHixeX+wEUIIYQQNczAGLyegLBFMOEojPkLHp8GTToAClAdhj/fg897wmJf+O1VSNgEhbl3uLBoSCQ8F0IIUae52zZibC9PNr7Wje2TevC/IG9aOJpTVKLmj4Qr/O+nI3SYu5VRq/5m3cGLZOZLkC5EZdRqNTklJVXaMouLeSvxEuWt07m5b9rJS2QWF1fpetV5FI9KpWLQoEGMHDmSEydOEBMTQ//+/bXXiI6O1u5fvXo169atY/bs2dV6LUxMNDUxCwsLKSws5MCBAwQGBmqP6+npERgYyJ49e7T7cnNzeeGFF1i2bBmOjo53vMfXX3+Nqakpzz77rHZfQUFBmVrWJiYm7Nu3j6Ki8t/DcnNzKSoqwtraulpjLI+dnR16enqsXbuWkpKSKp93++tVnuzsbL799ls8PT2xsbG5537ebyNHjmTlypXar1esWMGIESPKbfvjjz/SokULfHx8GDJkCCtWrCj37/OgQYPw9PRkzpw5963fQgghhCiHQgGO/tB9MoyOhv8lwtPLbpR3aQRZKjj4Fax+HhY0g++eg/0rILP83yYTDYd+bXdACCGEqCkedmaMe9yLcY97cepyNhvjVUTGqUhIzSL6n8tE/3MZQ6Ue3b3t6BPgRG9fe8yNDWq720I8VHJLS2m+I75GrqUGVAVFeO88WqX2p7v700iprFJblUpFcXEx/fv3x83NDUBn5bKhoSErVqzA1NSUVq1aMWfOHCZPnszbb7+Nnt6d14/k5uYybdo0lEolPXr04OrVq5SUlODg4KDTzsHBQacO+IQJE+jSpQtPP/10lcYRERHBCy+8oA2eAYKDg/nyyy/p168f7dq148CBA3z55ZcUFRVx9epVnJycylxnypQpODs764T7FenSpUuZ1yAvL09b97tJkyZ89NFHvP7668yePZsOHTrQq1cvBg8ejIeHR7nX/PfrddOGDRswMzMDICcnBycnJzZs2FCl70F13GlMd2PIkCFMnTqVc+fOAbBr1y5++OGHch/AGhERwZAhQwBNqZqMjAz+/PNPevbsqdNOoVDw3nvv0bdvXyZMmEDz5s3vun9CCCGEuAdm9tB2iGYrLoCknZBw46GjGRfg5GbNxgRwDACfUM1DR53aQA3PY8TDTcJzIYQQ9ZKnvRmv9vbi1d5enEzNIjJexYY4FacuZ7PtRCrbTqRiqK9HT287wgKc6O3rgJmR/LMoRF3RunVrevfujb+/P8HBwQQFBfHss8/SuHFj7XFTU1Nt+86dO5Odnc2FCxe0YXt5Bg0ahFKpJC8vDzs7OyIiIggICKiwhvXtfvvtN7Zv386hQ4eqNIY9e/Zw4sQJvvnmG53906dPJyUlhUcffRS1Wo2DgwPDhw9nwYIF5YbO7733njbU/feK9fKsWbMGX19fnX2DBw/W+Xrs2LEMGzaMmJgY9u7dy08//cQ777zDb7/9xhNPPKFtV9HrdVOvXr1Yvnw5ANevX+eTTz4hNDSUffv2Vfp9qK6qjKm67OzstCVY1Go1YWFh2NralmmXkJDAvn37+OWXXwDQ19dn4MCBRERElAnPQfPDkccee4zp06fz/fff31MfhRBCCFED9I3AM1CzPbkQLh/XlG9J3AwX/4aUOM3253wwcwTvIPAOBY8eYNiotnsv7jNJCYQQQtR7Xg7mjHcwZ3ygN4mpWWyIUxEZl8zpKzlsOZ7KluOpGOnr0dPHjrAAZ3q3sKeRBOmigTLV0+N096rVnt6bns3guLN3bPddQDMetTKr0r2rSqlUsnXrVnbv3s2WLVtYunQpb731FrGxsVW+Rnk++OADAgMDsbS0xM7OTrvf1tYWpVJJamqqTvvU1FRteZbt27dz+vRprKysdNoMGDCAbt26lVmx/OWXX9KmTRvat2+vs9/ExIQVK1bw2WefkZqaipOTE59//jnm5uY6fQJ4//33ee+999i2bZtOaF0ZFxcXPD09y9zz38zNzenbty99+/Zl7ty5BAcHM3fuXJ3wvKLX66ZGjRrp3OvLL7/E0tKSL774grlz51apvzU1JgsLCzIyMsqcm56ejqWlZbnXHTlyJOPGjQNg2bJl5baJiIiguLgYZ2dn7T61Wo2RkREff/xxudd+77336Ny5M5MnT658YEIIIYR4sBQKcGil2br/D7KvwMktmhXpp7dDdgoc/Fqz6RtDs+6aFenewWDZtLZ7L+4DSQaEEEI0KN4O5kx8wpwJgV4kpGYRGacp7XLmag6bj6Wy+VgqxgZ69PKxp0+AM71a2GFqKP9cioZDoVBUuXRKT2sLnIwMSCkoKrfuuQJwMjKgp7UFSoWiRvsJmr527dqVrl27MmPGDNzc3LSrf48cOUJeXp42QN27dy9mZma4uLhUek1HR8cyISxoysC0b9+e6Oho+vXrB6B9QOfNcPWNN97gv//9r855/v7+fPDBB/Tt21dnf3Z2Nj/++CPvvvtuhX0xMDCgaVPNh7AffviBPn366Kw8X7BgAfPmzWPz5s106NCh0nHdK4VCQYsWLdi9e7fO/oper8quo6enR15eXk138Y58fHw4cOBAmf0HDx7Ex8en3HNCQkIoLCxEoVAQHBxc5nhxcTFff/01ixYtIigoSOdYv379WL16NWPGjClzXseOHenfvz9vvPHGXY5GCCGEEA+EmR20HazZigsg6S/NivTETZB+XhOsn9wCkWhqqnvfKO/i3FbKu9QTkgYIIYRokBQKBS0cLWjhaMHEJ7w5ocpiY7yKDXHJJF3LZdPRFDYdTcHEQMnjLewJC3Cil489JoZVCxWFaAiUCgVzvZrw36NJKEAnQL8Zlb/t1eS+BOexsbFER0cTFBSEvb09sbGxXLlyBV9fX+Li4igsLGTUqFFMmzaNpKQkZs6cybhx4+6p1vbEiRMZPnw4HTp0oGPHjixZsoScnBztQyQdHR3LfUioq6srzZo109m3Zs0aiouLtXWyb5eYmMi+ffvo1KkT169fZ/HixRw9epSvvvpK22b+/PnMmDGD77//Hnd3d1JSUgAwMzPT1hi/W4cPH2bmzJkMHTqUli1bYmhoyJ9//smKFSuYMmVKta5VUFCg7dv169f5+OOPyc7O1vlhwvnz50lLS+P8+fOUlJRw+PBhADw9Pe95LLebMGEC3bp1Y968efTv35+SkhJWr17Nnj17+OSTT8o9R6lUcuLECe2f/23Dhg1cv36dUaNGlVlhPmDAACIiIsoNzwHmzZtHq1at0NeXj2RCCCFEnaBvBJ69NVvofLh8QrMiPTEKLuyDlHjNtmMBNLK/Vd6leS8p71KHyUxNCCFEg6dQKGjpbEFLZwsmBXlzXJVJZJymRvr5tFwi41VExqswMVDS29eePgFO9PSxx9hAgnQhwuys+NLPnWknL6EqKNLudzIy4G2vJoTZWd2X+1pYWLBjxw6WLFlCZmYmbm5uLFq0iNDQUNasWUPv3r3x8vKie/fuFBQUMGjQIGbNmnVP9xw4cCBXrlxhxowZpKSk0KZNG6Kioso8RLQqIiIi6N+/f5kSLwAlJSUsWrSIhIQEDAwM6NWrF7t378bd3V3bZvny5RQWFvLss8/qnDtz5sx7HmfTpk1xd3dn9uzZJCUloVAotF9PmDChWteKiorSPuDU3NycFi1a8NNPP+nUAp8xY4bODwbatm0LwB9//FFuzfC71aVLFzZt2sScOXNYtGgRenp6+Pv7Ex0djZ+fX4XnWVhYVHgsIiJCW7bm3wYMGMCCBQuIi4sr9xre3t6MHDmSzz///O4GJIQQQojao1CAQ0vN1m0i5FyFk1s1K9JPbYecy3DoW82mNIJm3W6UdwkBq8p/E1I8XBRqtbq837KttzIzM7G0tCQjI6PSibAQQgihVqs5lpypqZEen8yFtFtlBhoZKunt60BYgBM9vO0kSBcPtYrmP/n5+Zw9e5ZmzZpV6UGTlSlRq9mbns3lwmLsDfV51Mrsvqw4r4rw8HDS09NZv359hW1iYmIIDw8nKSnpgfXrQVu1ahWrVq0qU2td1G01+f/tTfIZSQghhKhBxYVwbpdmRXrCJkg/p3vcwU8TovuEgnM7Ke9SS6o6/5GV50IIIUQFFAoFfk0s8WtiyZQQH+IvZWhXpF9Kz+O3I8n8diQZMyN9An3tCQtwppuXrQTpokFSKhR0bWxe290QQgghhBCidukbakq1NO8FIe/BlQTNivSEKLi4D1KParad70MjO/AKBp8Q8OgFRjVXsk7UDAnPhRBCiCpQKBQENLUioKkVb4S24MjFDCLjkomMU5Gckc/6w8msP5yMuZE+T7TUrEh/zMsWI30J0oUQ4m6NGTOGb7/9ttxjQ4YM4dNPP33APRJCCCGEqAaFAuxbaLbHJkDONTi1VbMi/fR2yLkCh7/VbEpDcO+mWZHuHQxWrrXde4GUbant7gghhKjjSkvVHL6YTmScio3xKlQZ+dpj5sb6BLV0pE+AE109bTHUl1/HE7XjQZRtqWuSkpJYv34948ePr+2u3DeHDx/m8OHDhIeH13ZX7trly5fJzMws95iFhQX29vYPuEe1T8q2CCGEEPVEcSGc361ZkZ64Ca4n6R63b6VZke4dAk3ag54szKpJVZ3/SHguhBBC1JDSUjWHLlxnw40gPTWzQHvMwlif4FaOhN0I0g2UEqSLB0fCcyHqDwnPhRBCiHpIrYariTfqpEfBhb2gLr113NRWsxrdOxiaPw5GUi7xXkl4XgGZGAohhHgQSkvVHDh/Xbsi/XLWrSDd0sSA4FYOhAU406W5jQTp4r6T8FyI+kPCcyGEEKIByE2DU9s05V1ORUNBxq1jSkNwf0yzIt07BBq71V4/6zAJzysgE0MhhBAPWkmpmv1JaUTGq9h0NIUrtwXpVqYGhNxYkd7ZwwZ9CdLFfXCn8Nzd3R0TE5Na7KEQoqry8vJISkqS8FwIIYRoKEqK4PyeW+Vd0s7oHrdveWNVeig07SDlXapIwvMKyMRQCCFEbSopVfN3UhqRcSo2HVVxNbtQe8y6kSHBrTQ10js1s5YgXdSYiuY/JSUlJCYmYm9vj42NTS32UAhRVdeuXePy5ct4e3ujVNbMh2P5jCSEEELUEWo1XDulWZGeGAXn94K65NZxUxvwCtKsSG/+OBjLv+sVkfC8AjIxFEII8bAoKVUTe/YakXEqoo6mcC3nVpBu08iQED/NivROzWxQ6ilqsaeirqts/qNSqUhPT8fe3h5TU1MUCvm7JsTDSK1Wk5uby+XLl7GyssLJyanGri2fkYQQQog6KjdNU9YlcROc3KZb3kXPANy7alak+4RAY/da6+bDSMLzCsjEUAghxMOouKSU2LNpbIhTEXVUxfXcIu0xWzMjQm8E6Y+4W0uQLqqtsvmPWq0mJSWF9PT02umcEKJarKyscHR0rNEfdMlnJCGEEKIeKCnSrERPjNKsTE87rXvcrsWtOukuHRt8eRcJzysgE0MhhBAPu6KSUvaeubEi/VgK6bcF6XbmRjzp50hYgDMd3BqjJ0G6qIKqzH9KSkooKioq95gQ4uFgYGBQY6VabiefkYQQQoh66OopzYr0xM1wbrdueRcT6xvlXYLBszcYW9ZeP2uJhOcVkImhEEKIuqSopJTdp68RGZfM5mOpZOTdCjcdLIwI9XOiT4AT7VwlSBcVk/mPEKIy8h4hhBBC1HN512+Ud4mCk1shP/3WMT19cOsKPqGaMN3ao9a6+SBJeF4BmRgKIYSoqwqLS9l1+iqRcSo2H0shK79Ye8zRwpgn/Z0IC3CirYuVBOlCh8x/hBCVkfcIIYQQogEpKYYLN8u7RMG1k7rHbX00NdK9Q6BpR1Dq104/7zMJzysgE0MhhBD1QWFxKX+dusKGOBVbj6WSVXArSHe21ATpT94I0uUBkELmP0KIysh7hBBCCNGAXTt9q076+T1QeuuzJSaNbyvvElivyrtIeF4BmRgKIYSobwqKS9iZeJXIeBVbj6eSfVuQ3sTKhCf9NTXSWze1lCC9gZL5txUlUwABAABJREFUjxCiMvIeIYQQQggA8tLhdLRmRfrJLeWUd+ly66GjNs1rq5c1QsLzCsjEUAghRH2WX1TCzpNXiYxLZuvxVHIKbz0UpmljE8JulHbxbyJBekMi8x8hRGXkPUIIIYQQZZQUw8V9mhXpiVFwNVH3uI3XjfIuoeDSqc6Vd5HwvAIyMRRCCNFQ5BeV8GfiFSLjVGw7kUrubUG6i7UJYf7O9AlwopWzhQTp9ZzMf4QQlZH3CCGEEELc0bXTkLgZEjfBud265V2MrcDrCc2KdM/emnIvDzkJzysgE0MhhBANUX5RCTEJl9kQpyL6xGXyim4F6W42ptoV6S2dJEivj2T+I4SojLxHCCGEEKJa8jPgVLRmRfrJLZB3/dYxhVK3vIutZ+31sxISnldAJoZCCCEaurzCEv5IuExknIrof1LJLyrVHmtm20gbpLdwNJcgvZ6Q+Y8QojLyHiGEEEKIu1ZaAhf2aVakJ26GK//oHrfxvBWkuz4KSoOKr3NuN2SngpmDJoDXU963bkt4XgGZGAohhBC35BYWs/0fTZC+/Z/LFBTfCtI97BrRx9+JsABnvB3MJEivw2T+I4SojLxHCCGEEKLGpJ25Ud4lCpJ2QWnRrWPGluB5o7yLV+Ct8i7Hf4OoKZCZfKuthTOEzIeWT92Xbkp4XgGZGAohhBDlyykoJvqfy0TGJfNHwhUKbwvSPe3NCPN3ok+AE14O5rXYS3E3ZP4jhKiMvEcIIYQQ4r7Iz4TT0TfC9M2Ql3brmEIJrp3BsinE/VDOyTcWbz339X0J0CU8r4BMDIUQQog7yy4oJvpEKhviVPyZcIXCkltBureDGWH+zoQFOOJpL0F6XSDzHyFEZeQ9QgghhBD3XWkJXPxbsyI9IQqunKjCSQrNCvTx8TVewkXC8wrIxFAIIYSonqz8IradSCUyTsWOxKs6QXoLR3PC/J14MsCJ5nZmtdhLURmZ/wghKiPvEUIIIYR44K4nwZ5PYN9nd247fAM061ajt6/q/Ee/Ru8qhBBCiHrH3NiAZ9o25Zm2TcnIK2Lb8VQi41XsPHmFf1Ky+Ccli0VbE/F1sqBPgBNP+jvRzLZRbXdbCCGEEEIIIcTDqrE7uHSsWnienXrfu1MRCc+FEEIIUWWWJgYMaN+UAe2bkpFbxJbjKWyMV7Hz5FVOqDI5ocpk4eYEWjpZEBbgRJi/E+4SpAshhBBCCCGE+Dczh5ptdx9IeC6EEEKIu2JpasB/Orjwnw4upOcWsuW4prTLrlNXOa7K5PiNIN2viYWmRrq/E642prXdbSGEEEIIIYQQDwO3Lpqa5pkqoLzK4jdqnrt1edA9u9UDqXkuhBBCiJp0PaeQLcdT2BCnYvfpa5SU3ppqBDS11NRI93fCxVqC9AdF5j9CiMrIe4QQQgghas3x3+DHYTe+uD2mVmj+89zX0PKpGr+tPDC0AjIxFEIIIR6ctJxCNh9LITJOxe7TV7ktR6e1ixV9bjxstImVSe11sgGQ+Y8QojLyHiGEEEKIWnX8N4iaApnJt/ZZNIGQ9+5LcA4SnldIJoZCCCFE7biaXaAN0veeuaYTpLd1tdKuSHeWIL3GyfxHCFEZeY8QQgghRK0rLYFzuzUPBzVz0JRq0VPet9tJeF4BmRgKIYQQte9KVgFRx1KIjEsm9mwat89G2rs11gbpjpbGtdfJekTmP0KIysh7hBBCCCEaGgnPKyATQyGEEOLhcjkrn6ijmhrpfyfpBumPuGuC9FB/JxwsJEi/WzL/EUJURt4jhBBCCNHQSHheAZkYCiGEEA+v1Mx8NsWriIxX8XfSde1+hQIecbemT4ATIX6O2JtLkF4dMv8RQlRG3iOEEEII0dBIeF4BmRgKIYQQdUNKRj4bbwTpB87pBumdmlkT5u9EiJ8TduZGtdjLukHmP0KIysh7hBBCCCEaGgnPKyATQyGEEKLuSU7PY9NRTY30g+fTtfv1FNCpmQ1hN1ak25pJkF4emf8IISoj7xFCCCGEaGgkPK+ATAyFEEKIuu1Seh6b4lVsiFNx+EK6dr+eAjo3tyHM35ngVg7YSJCuJfMfIURl5D1CCCGEEA2NhOcVkImhEEIIUX9cSMtl01EVkXEqjlzM0O5X6ino0tyGMH8ngls50riRYS32svbJ/EcIURl5jxBCCCFEQyPheQVkYiiEEELUTxfScomM1wTp8Zd0g/Sunrb08XciqJUDVqYNL0iX+Y8QojLyHiGEEEKIhkbC8wrIxFAIIYSo/85dy9EG6ceSM7X79fUUPOZlS5i/E0EtHbE0NajFXj44Mv8RQlRG3iOEEEII0dBIeF4BmRgKIYQQDcvZqzlsvFEj/YTqVpBuoFTQzcuOMH8nAls6YGlSf4N0mf8IISoj7xFCCCGEaGgkPK+ATAyFEEKIhuv0lWw2xqmIjFfxT0qWdr+hUo/u3raEBTgR6OuAuXH9CtJl/iOEqIy8RwghhBCitpWUqtl3No3LWfnYmxvTsZk1Sj3FfbvfAwnP8/PzMTY2vtvTa4VMDIUQQggBcOpyNhtvlHZJSP13kG5HnwAnevva14sgXeY/QojKyHuEEEIIIWpT1FEVs38/jiojX7vPydKYmX1bEuLndF/ued/C89LSUubNm8enn35KamoqiYmJeHh4MH36dNzd3Rk1atQ9d/5+komhEEIIIf7tZGoWG26sSD91OVu731Bfj57edoQFONHb1wEzI/1a7OXdk/mPEKIy8h4hhBBCiNoSdVTFS98e5N8B9c0158uHtLsvAXpV5z961b3w3LlzWbVqFQsWLMDQ0FC738/Pjy+//PLueiuEEEIIUYu8HMyZ8IQ3Wyd0Z/P47rza2wsPu0YUFpey5Xgqr/1wmPZvb2XMNwf4/UgyOQXFtd1lIYQQQgghhKjTSkrVzP79eJngHNDum/37cUpKa6/qeLWXT3399dd8/vnn9O7dmzFjxmj3t27dmn/++adGOyeEEEII8SApFAp8HM3xcTRnQqAXCalZRMZpHjZ69moOUcdSiDqWgrGBHo+3sCfM35leLewwNaybK9KFEEIIIYQQorbsO5umU6rl39SAKiOffWfT6Nzc5sF17DbV/qR36dIlPD09y+wvLS2lqKioRjolhBBCCFHbFAoFLRwtaOFowcQnvDmhyiIyPpnIOBVJ13LZGJ/CxvgUTAyUPO5rTx9/J3r62GNiqKztrgshhBBCCCHEQ+9yVsXB+d20ux+qHZ63bNmSnTt34ubmprN/7dq1tG3btsY6JoQQQgjxsFAoFLR0tqClswX/C/LhWHImkTceNno+LZfIOM2fTQ2V9PZ1IMzfiZ4+dhgblB+kP+gnyQshhBBCCCHEw6SkVM3fSWlVamtvbnyfe1OxaofnM2bMYPjw4Vy6dInS0lLWrVtHQkICX3/9NRs2bLgffRRCCCGEeGgoFAr8mlji18SS14N9OHopkw03VqRfvJ7H70eS+f1IMo0MlQS21ATp3b1vBem18SR5IYQQQgghhHhYJKRk8frPcRy5kF5pOwXgaKlZbFRbFGq1utoV13fu3MmcOXM4cuQI2dnZtGvXjhkzZhAUFHQ/+lij5EnyQgghhLgf1Go1cRcztCvSL6XnaY+ZGenzREsHHC2M+fTP0w/tk+SFEA2TvEcIIYQQ4kEoLC7lk5hTLPvjFEUlasyN9Hm6jTPfxZ4H0Pmc9LB8Rrqr8Lwuk4mhEEIIIe43tVrN4QvpRMap2BivIrmSh+DcdHNVxV9THq/xEi4y/xFCVEbeI4QQQghxvx25kM7ra+NISM0CINDXnrn9/HG0NK6V386t6vyn2mVbhBBCCCFE5RQKBW1dG9PWtTFvPunLoQvpfLnzDJuOplR4zsPwJHkhhBBCCCGEqEl5hSV8sC2RL3eeoVQNNo0MmfVUK/oEOKFQaBYNhfg58URLx4fyuVB61T5BTw+lUlnhVl3Lli3D3d0dY2NjOnXqxL59+yptn56eztixY3FycsLIyAhvb282btxY7fsKIYQQQjwIenoK2rs1JsTPsUrta/NJ8kIIIYQQQghRU/acvkbohzv4fIcmOH+6jTNbJ/agb2tnbXB+k1JPQefmNjzdpgmdm9s8FME53MXK819++UXn66KiIg4dOsRXX33F7Nmzq3WtNWvWMHHi/7N35/GN3PX9+F8zumXLki8d3sPrY3e9Xlvew0coUBIIAQKBkPAtLdCkhPLtr1CgJJQcUMIRctEj4SqllNCW0sI3CTcEGu6UZG3vYdl7+tjbknxKsnVrZn5/SB57Vt5de9e2bO/rycMPktFH48/H3mhHb73n9bkbX/nKV9DR0YEnnngCr3vd63D8+HE4nc688alUCq997WvhdDrx9NNPY8OGDTh9+jQcDsdil0FERES0oha6Q3whd5InIiIiIiK6WpFEGo/+9Bi+lcsyd5eY8dm3NuE1O1wFntniLbp4/pa3vCXv2Nve9jbs3LkT3/72t/Ge97xnwef6h3/4B7z3ve/Fu9/9bgDAV77yFfz4xz/G17/+ddx3331547/+9a9jYmICv//972EwGAAAW7ZsWewSiIiIiFZce00ZPHYzAuFE3oahwOrYSZ6IiIiIiOhq/PJYEA8824dAJHtH7Ts6NuO+NzSgxGwo8MyuzKJjWy7muuuuwy9+8YsFj0+lUti/fz9uvPHG2cmIIm688Ua8+OKL8z7nBz/4AV72spfh/e9/P1wuF5qamvDwww9DkqSrnj8RERHRctKJAh68pRHA7M7xM2b+/cFbGlfN7YlEREREREQLNRFN4a//+yDu+kY3ApEEqsut+K/3XoeH39q8ZgvnwBJtGBqPx/H5z38eGzZsWPBzxsbGIEkSXC5tu77L5cKxY8fmfc7Q0BB++ctf4p3vfCd+8pOfYGBgAO973/uQTqfx4IMPzvucZDKJZDKp/nskEgEAZDIZZDIZANmivSiKkGUZsiyrY2eOS5IERVEue1yn00EQBPW8c48DyCvyX+y4Xq+Hoiia44IgQKfT5c3xYse5Jq6Ja+KauCauiWtafWu6saESX3rHbnzmx0c1O8m77WZ84k3ZneSXY01sNCCiufgeiWvimrgmrolr4pq4pqVakyiK+MGh8/jkD49gMpaGKADveUUN7n7tdpj02vmspjUt9D3SoovnpaWlmkB3RVEwNTUFq9WKb37zm4s93aLIsgyn04mvfvWr0Ol02Lt3L86fP4/Pfe5zFy2eP/LII/NmsR88eBBFRUUAgMrKStTV1eHkyZMYHR1Vx2zcuBEbN27EiRMnEA6H1eO1tbVwOp3o6+tDPB5Xjzc0NMDhcODgwYOaX4DX64XRaER3d7dmDq2trUilUvD5fOoxnU6HtrY2hMNhzYcIFosFLS0tGBsbw9DQkHrcbrdjx44dGB4exrlz59TjXBPXxDVxTVwT18Q1rc41tdbW4oV7X43/er4TwUgCDpOIHRV6NG6yAMCyrInFcyKai++RuCauiWvimrgmrolrWoo1pfVF+LfDSTx/NAgA2FSiw1/sLsLLtplgMeowODi4ate00PdIgjK3nL8A3/jGNzTFc1EUUVlZiY6ODpSWli74PKlUClarFU8//TRuvfVW9fidd96JUCiE73//+3nPedWrXgWDwYDnn39ePfbTn/4UN998M5LJJIxGY95z5uuq2LRpE8bHx1FSUqKuYS1/wrMeP7Ximrgmrolr4pq4Jq5p6dY0NTWFsrIyhMNh9fqHiK5dfI/ENXFNXBPXxDVxTVzT1axJURR8Z/95PPrccUwlMjDoBLzvVbX4iz+shVEvrok1LfQ90qKL50upo6MD7e3t+MIXvgAg21m+efNm/NVf/dW8G4Y+8MAD+Na3voWhoSGIYjau/cknn8Rjjz2G4eHhBX3PSCQCu93ON49ERER0zeD1DxFdCl8jiIiIaKHOjMdw37M+/H5wHADQssmBx2/3YrvbVuCZLc5Cr38WFNsyt9X9crxe74LH3n333bjzzjvR2tqK9vZ2PPHEE4hGo3j3u98NALjjjjuwYcMGPPLIIwCAv/zLv8QXv/hFfOhDH8IHPvAB9Pf34+GHH8YHP/jBBX9PIiIiIiIiIiIiIlo4SVbw1P+exN/9/DgSaRlmg4iP3LQd7355DXSicPkTrFELKp7v2rULgiDgck3qgiAsKlPz7W9/O0ZHR/GJT3wCgUAAu3btwnPPPaduInrmzBm1wxwANm3ahJ/97Gf48Ic/DK/Xiw0bNuBDH/oQ7r333gV/TyIiIiIiIiIiIiJamBPBKXz0aR8OnQ0BAF5WW45Hb29GdXlRYSe2AhYU23L69OkFn7C6uvqqJrTceEsiERERXWt4/UNEl8LXCCIiIppPKiPjK78ZxBd+2Y+0pMBm0uOBN+7AH7dt0uyJuRYtaWzLai+IExEREREREREREdHS6Dkbwr3P+HAsMAUAeE2DEw+9tQkeu6XAM1tZCyqez+fIkSM4c+YMUqmU5vib3/zmq54UEREREREREREREa2sRFrCP/7PCfzL74YgK0BZkREP3tKIN7dUrflu8yux6OL50NAQ3vrWt6K3t1eTgz7zw1tM5jkRERERERGtf4qsIHkyDHkqBdFmhKnGDmEdby5GRES0Fr00NI77nvHh1HgMAPCWXVX4xJsaUV5sKvDMCmfRxfMPfehDqKmpwS9+8QvU1NSgs7MT4+PjuOeee/B3f/d3yzFHIiIiIiIiWqPifWMI/XAQUnj2rmWd3QjHLXWwNFUUcGZEREQEAFOJNB796TH8574zAAB3iRkP3dqEGxtdBZ5Z4S26eP7iiy/il7/8JSoqKiCKIkRRxCte8Qo88sgj+OAHP4iDBw8uxzyJiIiIiIhojYn3jWH8m0fzjkvhFMa/eRTl79rBAjoREVEB/erYCB74bi/84QQA4E/aN+P+mxtQYjYUeGarw6KL55IkwWazAQAqKiowPDyM7du3o7q6GsePH1/yCRIREREREdHao8gKQj8cvOSY0A+HYG4sZ4QLERHRCpuIpvCZHx3Bdw+eBwBUl1vxyG3N+IM6fqg916KL501NTejp6UFNTQ06Ojrw+OOPw2g04qtf/Spqa2uXY45ERERERES0xiRPhjVRLfORwknEekdh9VZek5uQERERrTRFUfDjXj8e/P5hjEdTEAXgrpfX4J6btsNi1BV6eqvOoovnH//4xxGNRgEAn/70p/GmN70Jr3zlK1FeXo5vf/vbSz5BIiIiIiIiWnvkqUsXzmdM/tdxhL47CIPHCqOnGAZPEQzuIhjcVggGvoknIiJaKsFIAh//Xh/+50gQALDNVYzHbvdi9+bSAs9s9Vpw8by1tRV//ud/jne84x0oKSkBANTX1+PYsWOYmJhAaWkpOwWIiIiIiIgIACDajAsbKABKIoPUyQhSJyOa4/oKS7aY7imCwVMMg7sIOruR7z2JiIgWQVEUfKf7LB768VFMJTIw6AS87/p6vP+Gehj1YqGnt6otuHje0tKCj370o7jnnntw++2346677sL1118PACgrK1uu+REREREREdEaZKqxQ2c3XjK6RWc3wXXPXmTG4kgHokj7Z7/kaBqZ0Tgyo3HEfWPqc0SrPteZXjRbWHcVQTDwzT8REdGFzozHcP93ffjfgXEAQMtGOx57mxcN7pICz2xtEBRFURY6OBaL4Tvf+Q6+8Y1v4He/+x1qampw11134c4778SGDRuWc55LJhKJwG63IxwOqx30REREROsZr3+I6FKW8zUi3jeG8W8evejj5e/aAUvT/BuTSVOpXCF9Gml/FCl/FJnROCDP8xZWnOlSn419MXqKIJawS52IiK5NkqzgG78/hb/72XHE0xJMehEfuWk77npFDXTcqHvB1z+LKp7PNTg4iKeeegr/8R//geHhYdx00014z3veg9tuu+2KJ70S+OaRiIiIrjW8/iGiS1nu14h43xhCPxzUdKDr7CY4bqm9aOH8YpSMjPRIbLZDPZAtrsvRzLzj1S71mdgXTxEMTiu71ImIaF3rD07ho8/4cPBMCADQUVOGx273YktFUWEntoose/F8hqIoeOaZZ/AXf/EXCIVCkCTpak637PjmkYiIiK41vP4hoktZidcIRVaQPBmGPJWCaDPCVGOHsERdb4qiQM51qafmxL5kxmKAPM8TREBfadV0qBs8xRBtBnapExHRmpaWZHzl14P4wi8HkJJkFJv0eODmHfjjtk0Q2W2usdDrnwVnns/n17/+NZ566ik888wz0Ov1eO9733s1pyMiIiIiIqJ1SBAFmOscy3NuQYCuxARdiQnm7bP7cSnpmS71aU2nuhzLIBOMIROMIY5RdbxYpFc3JVWz1J1WCNxIjYiI1oDec2H8zdM9OBaYAgC8usGJz761CR67pcAzW9sWXTw/d+4cvvGNb+Ab3/gGhoaG8MpXvhJf/vKX8X/+z/+BxcJfBhERERERERWeYBBh3FAM44Zi9ZiiKJAjqdkO9VzsS2Y0DjmaQXIghORAaPYkogB9pUXtTp8pqutsxpVfEBER0TwSaQn/+PwJ/MtvhyArQKnVgE++eSfe3FLFO6qWwIKL59/5znfw9a9/Hb/4xS/gdDpx55134q677kJ9ff1yzo+IiIiIiIhoSQiCAJ3dBIvdBEvD3C51CengbJb6THFdScx2qePQnC71YoMa+6LmqVda2KVOREQrat/QOO57thcnx6IAgFtaqvDJWxpRXmwq8MzWjwUXz9/1rnfhjW98I7773e/i5ptvhijyooCIiIiIiIjWPsGgg3GjDcaNNvWYoiiQwqls7EtgbpZ6HPJ0Gsn+EJL9odmT6AQYZrLU53zpitmlTkRES2sqkcbjzx3Hf7x0GgDgKjHhoVub8dpGV4Fntv4suHh+7tw5OJ3O5ZwLERERERER0aogCAL0DhP0DhMsO8rV43JKQibXpZ6aU1hXElL2nwNR4ODsedQu9Vzsi9FTBH2lBYKODWlERLR4vzo+go8924vhcAIA8Cftm3DfG3bAbjEUeGbr04KL5yycExERERER0bVONOpg3GSDcZMNRbljiqJACiU1G5Om/VFkxi/Rpe68oEvdzS51IiK6uMloCp/50RE8e/A8AGBzmRWP3taMP6ivKPDM1rdFbxhKRERERERERLMEQYC+1Ax9qRmWRm2X+kw3ulpY90ehJCX1n+cSbUa1mG7M/b++gl3qRETXMkVR8JPeAB78QR/GplMQBeCul9fg7pu2wWpkaXe58SdMREREREREtAxEow6mzSUwbS5RjymKAmlypkt9NvYlM5GAPJVCciqF5InJ2ZPoBBhc1mzsi3tOlnoRb88nIlrvRiIJfPx7ffj5kSAAYKuzGI+/zYvdm0sLPLNrB4vnRERERERERCtEEAToy8zQl5lh2TmnSz0pIR3UdqinA7ku9eEo0sPaLnVdiTEv9kVfYYWgE1Z6SUREtMQURcH/6z6Hz/z4CKYSGehFAe+7oR7vv6EOJr2u0NO7prB4TkRERERERFRgommeLnVZgTSZULvTU7mCujSegBRJQYqkkDg+p0tdL2a71Od0qBs9RRCt7FInIlorzk7EcP+zvXhhYAwA4N1ox2O3e7HDU3KZZ9JyWFDxvLS0FIKwsE+vJyYmrmpCRERERERERAQIogB9uQX6cgssO2c3hJOTGaQDsWzsy9wu9ZSM9PlppM9Pa86jsxvzYl/0FRYIIrvUiYhWC0lW8O8vnsLjzx1HPC3BpBdxz03bcNfLa6Dn3hcFs6Di+RNPPKH+8/j4OB566CG87nWvw8te9jIAwIsvvoif/exn+Nu//dtlmSQRERERERERZYkmPUzVJTBVz9OlPtOhPtOlPpGAFE5BCk8gcWxOs5tehMGd7VI3zol+YZc6EdHKGxiZwkef9uHAmRAAoL2mDI/d7kVNRVFhJ0YQFEVRFvOE22+/HTfccAP+6q/+SnP8i1/8Ip5//nl873vfW8r5LblIJAK73Y5wOIySEt7uQEREROsfr3+I6FL4GrG+yYmMGvui6VJPy/OO1zlMmg51g6cI+nJ2qRMRLYe0JOOffzOIz/9iAClJRrFJj/ve0IB3tG+GyNfdZbXQ659FF8+Li4tx6NAh1NfXa44PDAxg165dmJ6evsgzVwdeGBIREdG1htc/RHQpfI249iiygsxEQhv74o9CCiXnHS8YROhnOtTnFNZFM7dRIyK6Un3nw/ibp3046o8AAG7YXonPvrUZVQ5LgWd2bVjo9c+i/6YrLy/H97//fdxzzz2a49///vdRXl5+kWcRERERERER0WogiAIMFRYYKixAc6V6XI7P6VIPZONfMrku9fTZKaTPTmnOo3OYNB3qBk8x9GVmdqkTEV1CIi3hief78S+/G4IkKyi1GvDgLTvxll1VC95zklbOoovnn/rUp/Dnf/7n+PWvf42Ojg4AwL59+/Dcc8/hX/7lX5Z8gkRERERERES0/ESLHqYaO0w1dvWYIivIjMfzYl+kUFL9ShydzVIXDGJe7IvBzS51IiIA6Dw5gfue8WFoLAoAeJPXg0++eScqik0FnhldzKL/9vqzP/sz7NixA5///Ofx7LPPAgB27NiBF154QS2mExEREREREdHaJ4gCDJVWGCqtgHdOl3osrXapp3IF9XQgBiUtI3V2CqkLu9TLzGpRfWaDUl0pu9SJ6Nownczg8eeO4d9fPA0AcNpMeOjWJty0013gmdHlXNFHvx0dHfjP//zPpZ4LEREREREREa0BotUAU60DplqHekyRFWTG4poO9bR/GlI4BWkiAWkigcSRcXW8YNTB4LZqYl8MbitEE7vUiWj9+PXxEXzsu304H4oDAN7eugkPvHEH7BZDgWdGC3FFfyMNDg7iqaeewtDQEJ544gk4nU789Kc/xebNm7Fz586lniMRERERERERrXKCKMDgtMLgtAIts13qUnS2S10tqgejUFISUmemkDozT5e6R7tBKbvUiWitCcVS+PSPjuDZA+cBAJvKLHj0Ni9eXl9R4JnRYiy6eP6b3/wGb3jDG/Dyl78cv/3tb/HQQw/B6XSip6cH//qv/4qnn356OeZJRERERERERGuQrsgAXZ0D5jqHekyRFGTGYtqiuj8KKTKnS/3wnC51ky4/S91VBNGkK8CKiIgu7Se9fnzi+30Ym05BEIB3/0ENPvK6bbAaeWfNWrPo39h9992Hhx56CHfffTdsNpt6/NWvfjW++MUvLunkiIiIiIiIiGj9EXQCDK5sARwts8elaDov9iUdjEFJSkidjiB1OjLnJIA+16WeLawX57rUTRAEdqkT0cobiSTwie8fxnOHAwCAemcxHn+bF3s2lxZ4ZnSlFl087+3txbe+9a28406nE2NjY0syKSIiIiIiIiK69uiKDNDVO2Cud6jHFElWs9RTc7rU5akUMuMJZMYTiPdd0KU+t0Pdnf0SjexSJ6LloSgK/t/+c3joR0cQSWSgFwW87/o6vP/V9TDp+dqzli26eO5wOOD3+1FTU6M5fvDgQWzYsGHJJkZEREREREREJOhEtUvdumv2uDSdmtOhnvsayXWpn4ogdeqCLvVyy5wu9VyWuoNd6kR0dc5OxPDAd3vxu/5sU3HzBjseu92LxqqSAs+MlsKii+d//Md/jHvvvRf/7//9PwiCAFmW8b//+7/4yEc+gjvuuGM55khEREREREREpKErNkK31Qjz1tk4BEWSkRmNz+lQn852qU+nkRmLIzMWR7x39q55wayHwWOFwV0EYy72Re+yskudiC5LlhX8+4un8PjPjiOWkmDSi7j7tdvwnlfUQK8TCz09WiKLLp4//PDDeP/7349NmzZBkiQ0NjZCkiS84x3vwMc//vHlmCMRERERERER0WUJOlGNacHu2ePSVCpvc9L0aAxKIoPUyQhSJyOIqicB9BUWbeyLpxg6u5Fd6kQEABgYmcK9z/Ri/+lJAED7ljI8enszaiuLCzwzWmqCoijKlTzx7Nmz6O3txfT0NHbv3o2tW7cu9dyWRSQSgd1uRzgcRkkJb58gIiKi9Y/XP0R0KXyNoGuVkpGRHonlFdXlaHre8YJFn+tQn5On7rJCMLBLnehakZZkfPW3Q3jy+X6kJBlFRh3uu3kH3tm+GaLID9fWkoVe/yy68/y3v/0tGhoasGnTJmzatEk9nk6n8eKLL+IP//APr2zGREREREREREQrRNCLMFYVw1il7RSVplJziunTSPmjyIzGocQzSJ0MI3UyPOckgL7SAoOnWM1SN3qKIJawS51ovek7H8ZHn/bhiD+7n8L12yvx2bc2Y4PDUuCZ0XJadPH8+uuvh8vlwne/+11cd9116vGJiQnccMMNkCRpSSdIRERERERERLRSdDYjdDYjzNvmZKnPdKnPFNUD2cK6HM0gMxJHZiSOeM+oOl606jUbkxo8xTA4rRAMzEEmWmsSaQlP/qIfX/3tECRZgcNqwIO3NOLWXRv4Idk1YNHFcyC7aehrXvMafOlLX8Kf/dmfqcevMAGGiIiIiIiIiGjVmq9LXVEUyLku9dSconpmNAY5lkFyKIzk0JwudRHQV1jnFNRzXeo2dqkTrVZdpyZw79M+DI1ld0V4o9eDT96yE5U2U4Fntv5IsoQDIwcwGhtFpbUSe5x7oBMLH4u16OK5IAi4//778cpXvhJ33HEHfD4f/v7v/159jIiIiIiIiIhovRMEAboSE3QlJpi3l6nHlfTcLvVptaguxzLIjMSQGYlpu9SL9JrYF4OnKNulrmeXOlGhTCcz+Nxzx/DvL52GogCVNhMeurUJr9vpLvTU1qXnTz+PRzsfRTAWVI+5rC7c134fbqy+sYAzu4Li+Ux3+W233Yaamhq85S1vwZEjR/Dkk08u+eSIiIiIiIiIiNYSwSDCuKEYxg3FAFwAcl3qkZSmQz3tn0ZmNA45mkFyIITkQGj2JKIAfaVlzuakxTB4iiAWG9i4SLTMfnNiFA8824vzoTgA4I9aN+JjNzfCbjUUeGbr0/Onn8fdv74bCrSJJiOxEdz967vxD9f/Q0EL6FcU2zJj9+7d6OzsxK233orXvOY1SzUnIiIiIiIiIqJ1QxAE6OwmWOwmWBrmdqlLSAe1WeopfxRKPINMMIZMMAYcmtulbpjtTnezS51oKYViKXzmR0fxzIFzAICNpRY8epsXr9haUeCZrV+SLOHRzkfzCucAoECBAAGPdT6GGzbdULAIl0UXz++8805YLLO7yLrdbvzmN7/B//2//xe//e1vl3RyRERERERERETrlWDQwbjRBuNGm3pMURRI4VQ28iUQVQvrmbE45Gg6v0tdJ8BQqc1SN7iLoLMZV35BRGvUT3v9+NvvH8bYdBKCAPzZH2zBR27ajiLTVfUd02UcGDmgiWq5kAIFgVgAB0YOoM3dtoIzm7XoPwFPPfVU3jGTyYR/+7d/W5IJERERERERERFdqwRBgN5hgt5hgmVHuXpcTknIzHSpB6JI5fLUlYSULbIHosDB2fOIxXO61D3FMHqKoK+0QNCxS51oxshUAg9+/zB+2hcAANQ7i/HY7V7srS4t8MzWt3AyjO5AN75z4jsLGj8aG738oGWyoOK5z+dDU1MTRFGEz+e75Fiv17skEyMiIiIiIiIioizRqINxkw3GTRd2qSeRHp6bpR5FZjwOeTqNZH8Iyf7Q7El0AgxOqzb2xVMEXTG71OnaoigKnt5/Dg/9+CjC8TT0ooC/vL4Of/Xqepj0hYkHWc+mUlPYH9yPzkAnugJdOD5xfN6olouptFYu4+wubUHF8127diEQCMDpdGLXrl0QBEHdOBSA+u+CIECSpGWbLBERERERERERZWW71M3QO8ywNGq71Ge60dU8dX8USlJS/3ku0WZUC+nGXGGdXeq0Xp2bjOGB7/bhtyey3cxNG0rw2O1e7KyyF3hm60c0HcWB4AF0BbrQGejE0YmjkBVZM6bWXou9rr34+amfI5wKz3seAQJcVhf2OPesxLTntaDi+cmTJ1FZWan+MxERERERERERrU6iUQfT5hKYNpeoxxRFgTSZnNOhno19yUwkIE+lkJxKIXlicvYkOgEGlzXXoV4826VeZCjAioiuniwr+I+XTuOx544hlpJg1Iv48I3b8N5X1kDPD4quSiwdw6HRQ2qx/PDYYUiKtsG6uqQabe42tLvb0eZuQ4UluxHrH1T9Ae7+9d0AoOlGFyAAAO5tv7dgm4UCgKDMbSG/BkQiEdjtdoTDYZSUlFz+CURERERrHK9/iOhS+BpBdG2TkxLSQW2HejqQ7VKfj1hizHanz4l+0VdYIeiEFZ450cINjk7j3qd96D6d/YCobUspHrvdi9rK4gLPbG1KZBLoGe1RY1h6x3qRkTOaMRuKN6iF8jZ3G9xF7oue7/nTz+PRzkc1m4e6rW7c234vbqy+cVnWsNDrnwV1nv/gBz9Y8Dd+85vfvOCxRERERERERERUOKJpni51WYE0mVBjX1K5gro0noAcSSERSSFxfE6Xul6AwaXNUTd6iiBa2aVOhZWWZHz1t0N48hf9SGVkFBl1uO8NDXhnRzVEkR/4LFRKSsE36lM7y32jPqTklGaMu8itFsvb3e2oKq5a8PlvrL4RN2y6AQdGDmA0NopKayX2OPcUtON8xoKK57feeuuCTsbMcyIiIiIiIiKitU0QBejLLdCXW2DZWaEel5MZpAMxNfJF7VJPyUifn0b6/LTmPDq7MS/2RV9hgcCiJa2AvvNh3PuMD4eHIwCAV22rxGff2oSNpdYCz2z1S8tpHB47jM5AJzoDnegZ6UFCSmjGOC1OtHlmY1g2Fm+EIFz5f9s6UYc2d9vVTn3JLah4Lsvy5QcREREREREREdG6JZr0MFWXwFQ9T5f6TIf6TJf6RAJSOAUpfGGXugiD26p2qc9sUMoudVoqibSEL/yyH1/5zRAkWYHDasAn3tSIt+7ecFXF3fUsI2dwZPwIugJd6Ap04cDIAcQzcc2YMnOZprO8uqT6mvh5Lqh4TkREREREREREdCFNl3rTnC71REaNfVE3KZ3pUj83jfS5C7vUTWp3utqlXs4udVqc7lMT+OgzPgyNRgEANze78ak3N6HSZirwzFYXSZZwbPIYuvzZGJYDIwcQTUc1Yxwmh5pX3u5uR6299pooll/oiorn0WgUv/nNb3DmzBmkUtp8mw9+8INLMjEiIiIiIiIiIlqbRLMepi12mLbY1WOKrCAzkdDGvvijkEJJSOHsV+LYhDpeMIjQu6wwzol9MbiLIFrYC0pa0WQGn/vZcfzbi6egKEClzYTPvGUnXt/kKfTUVgVZkdE/2a/GsOwP7sdUakozxma0odXVqnaXby3dClEQCzTj1WPRrzYHDx7EzTffjFgshmg0irKyMoyNjcFqtcLpdLJ4TkREREREREREeQRRgKHCAkOFBWiuVI/LiYymQz3ljyITiEJJX6RL3XFhl3ox9GVmdqlfo357YhT3P9uL86FszMj/2bsRH39jI+zXcBSQoigYDA2iM9CJrkAXuoPdCCVDmjFFhiLsde1Vi+XbS7evig06V5tFF88//OEP45ZbbsFXvvIV2O12vPTSSzAYDHjXu96FD33oQ8sxRyIiIiIiIiIiWqdEsx6mGjtMNRd0qY/HNR3q6UCuSz33lTiq7VKfyVHXdKmb2aW+XoVjaXzmx0fw9P5zAIANDgsevb0Zr9xaeZlnrj+KouBk5CS6A91qwXwiMaEZY9FbsMe1B+3udrS729FQ1gC9yP8+LmfRP6FDhw7hn//5nyGKInQ6HZLJJGpra/H444/jzjvvxG233bYc8yQiIiIiIiIiomuEIAowVFphqLQC3jld6rG0mqWeUrPUY1DSMlJnp5A6q42i0JWaYMjFvsxsTqpjl/qa91yfH3/7/cMYnUpCEIA7X7YFf/O67SgyXRvFYEVRcHbqrBrD0h3oxmh8VDPGrDNjl3OX2lm+s2InDOK1241/pRb9J8pgMEAUs3k3TqcTZ86cwY4dO2C323H27NklnyAREREREREREREAiFYDTLUOmGod6jFFVpAZi89uTOqPIu2fhhROQZpMQppMInFkXB0vGHUwuK2a2BeD2wrxGim8rmUjUwl88geH8ZPeAACgrrIIj93uReuWsgLPbPmdnz6PTn+2q7wz0IlgLKh53Cga0eJsUTf4bK5ohlFnLNBs149Fvyrs3r0bXV1d2Lp1K171qlfhE5/4BMbGxvAf//EfaGpqWo45EhERERERERERzUsQBRicVhicVqBltktdiqbnFNNzhfVgFEpKQurMFFJnLuhSLzOrcS/GXGFdV8ou9dVAURQ8e+A8Pv2jIwjH09CJAv6/V9XiA6/eCrNhfeZ0B6IBtVDeFejC+enzmsf1oh7eCq9aLG9xtsCkMxVotuvXoovnDz/8MKamsi8un/3sZ3HHHXfgL//yL7F161Z8/etfX/IJEhERERERERERLZauyABdnQPmOod6TJEUZMZi2qK6PwopkoI0kYA0kUDi8JwudZNOm6XuzmWpm9ZnwXY1OjcZwwPf7cNvT2RjSXZWleDxt3mxs8p+mWeuLaOxUU2x/MzUGc3jekGPnRU71RiWXc5dsOgtBZrttWPRxfPW1lb1n51OJ5577rklnRAREREREREREdFyEHQCDK4iGFxFQMvscSma1nao+6eRDsagJCWkTkeQOh2ZcxJAX2aeU1QvznWpmyAI7FJfKrKs4Jv7TuOxnx5DNCXBqBfx1zduxXtfWQuDTiz09K7aeHwcXcEudZPPk+GTmsdFQURjWSPaPNnO8j3OPbAarAWa7bWLYU5EREREK0yRJMS69yMzOgp9ZSWsrXsh6Ni9RERERFQouiIDdPUOmOsd6jFFktUs9dScLnV5KoXMeAKZ8QTiF3apz3Snz+lUF428zluswdFp3PeMD12nJgEAbVtK8ejtXtRVFhd4ZlculAihO9itdpYPhAY0jwsQ0FDWoMaw7HHtgc1oK9Bsacaii+fj4+P4xCc+gV/96lcYGRmBLMuaxycmJpZsckRERETrTeTnP0fw4UeQCQTUY3q3G64H7kfJTTcVcGZERERENJegE9Uudeuu2ePSdCov9iU9kutSPxVB6tQFXerllryius7BLvX5ZCQZX/3dEJ54vh+pjAyrUYf73tCAd3VUQ1xj2fORVAT7A/vVYvmJyRNQoGjGbC3dqsawtLpaYTetryiaxZBlBf7+EKKRJIpKTPBsdayK3/mii+d/+qd/ioGBAbznPe+By+Xif+hERERECxT5+c9x/kN/DSjai+ZMMJg9/uQTLKATERERrXK6YiN09UaY60vVY4okIzMan9OhPp3tUp9OIzMWR2YsjnjvmDpeMM9mqRtzsS96l/Wa7lI/PBzGvc/40Hc+++HDH26rxMNvbcLG0rURVRJNR7E/uF/NLT82cQyyom06rrPXZTvLPe1odbWi1Fx6kbNdWwYPjuB33+5HNJRUjxU5THjl27eibrezgDMDBEW54N3bZdhsNrzwwgtoaWm5/OBVKBKJwG63IxwOo6SkpNDTISIiomuEIkkYeM2Nmo5zDUGA3uVC/S+eX/IIF17/ENGl8DWCiGj5SFPzdKmPxgBpnnKcAOgrLuxSL4bOblzXzauJtIQv/nIAX/nNIDKyArvFgL99UyNu37NhVa87lo7h0MghtbP88PhhSIqkGbOlZIsaw9LqbkWFpaJAs129Bg+O4Ll/7rvo46//i6ZlKaAv9Ppn0Z3nDQ0NiMfjVzU5IiIiomtFZmwMcZ8PkZ8+d/HCOQAoCjKBAGLd+1HU0b5yEyQiIiKiZaOzGaGzGWHeOqdLPSMjPRLLK6rL0TQyo3FkRuOI++Z0qVv0MLiLYPTMyVJ3WSEY1n6X+v7TE/jo0z4MjkYBAG9ocuNTb9kJp81c4JnlS2QSODR6CJ3+bLG8b6wPGSWjGbOxeCPaPdkYljZXG1xFrgLNdm2QZQW/+3b/Jce88J1+1LRUFizCZdHF8y9/+cu477778IlPfAJNTU0wGAyax9mpQERERNcqOR5H4vBhxH29iPt8iPt6kBn2L+ocmdHRZZodEREREa0Ggl6EsaoYxirt5pfSVGpOMX0aKX8UmdE4lHgGqZNhpE6G55xkTpd6LvbF4CmCrmRtdKlHkxl87mfH8W8vnoKiABXFJnzmLTvxhmZPoaemSkkp9Iz2qDEsvlEf0nJaM8ZT5FE7y9vd7fAUr575rwXnjk+oUS0KFKSNYchiCqJshCFlhwAB05NJ+PtD2LC9MBE3iy6eOxwORCIRvPrVr9YcVxQFgiBAkqSLPJOIiIho/VAkCcnBQSR8PrVYnuzvBy68FhIEmOrrofe4Ef3t7y57Xn1l5TLNmIiIiIhWM7VLfds8XeozRfVAtrAuRzPzdqmLVr1mY1KDpxgGpxWCQSzEkub1u/5R3P9sL85NZpMt3rZ3Iz7+xh1wWI0FnVdaSqNvvE/tLD80eghJKakZ47Q61UJ5m7sNG4pXd7TMapNKZBA8GcHwQAj+gTD8AyEAQNI0humSAci6lDpWlIwojtTDlKxANJK8yBmX36KL5+985zthMBjwrW99ixuGEhER0TUjHQwi7vNli+U9PiT6+iDHYnnj9E4nLC1emL1eWJq9MDc1QVdcNJt5HgzmbRgKQM08t7buXYHVEBEREdFaMF+XuqIokHNd6qk5RfXMaAxyLIPkUBjJoTld6iKgr7DOKahnI2BE28p2qYdjaXz2J0fwne5zAIANDgsevq0Zr9pWmOaRjJzB4fHD6Ap0oSvQhYMjBxHPaKOqy83l2UK5J9tdvtm2mbXQRYhFUvAPhuDvD8M/GMLo2Wkosva9UNI0hojjSN5zZTGFiOMISkKNKCoxrdSU8yy6eN7X14eDBw9i+/btyzEfIiIiooKTpqO5+JUetbM8EwzmjROtVpibmrLF8uZmWFpaYHDNn2so6HRwPXA/zn/orwFB0BbQcxfgrgfuX/LNQomIiIhofREEAboSE3QlJpi3l6nHlfTcLvVptaguxzLIjMSQGYkh3jMbESgWzXSpF89uUuqyQtAvfZf6c30B/O33+zA6lYQgAHdcV42/eX0Dik2LLk1eMUmWcGziGDoDnegMdOJA8ABiGW0zTKmpFK3uVrW7vMZew2L5AimKgvBoXO0o9w+GEQrmNxvZyszw1NvhqXegcksxvvqvX84+cOGPWQCgAFHHIFx1ty/7/C9m0X9CW1tbcfbsWRbPiYiIaF1QMhkkBwYQ7/HliuW9SA4OArKsHSiKMG3bBovXC4u3GWavF6a6ukUVu0tuugl48gkEH35Es3mo3uWC64H7s48TEREREV0BwSDCuKEYxg3FALINHYqiQI6kNB3qaf80MqNxyNEMkoNhJAfndqkL0Fda1O50g6cYBncRRJvhiorIo1NJfPIHh/Hj3uw+QLWVRXjsdi/atpRd5plXT1ZknJg8ocaw7A/ux1R6SjOmxFiCVleruslnvaMeorB6Im5WM1lWMH5uOhfBko1hiUVS2kECUF5VBE+dA56tdnjqHLCVZTeDnZ6eRk9PDyThEpEsAiAhibNnz6CmpmYZV3Nxiy6ef+ADH8CHPvQh/M3f/A2am5vzNgz1er1LNjkiIiKipaQoCjJ+f24zz95ssfzwESjxeN5YfZUHFm8LLM3N2c7yxkaIVutVz6Hkpptge81rEOvej8zoKPSVlbC27mXHOREREREtOUEQoLObYLGbYGmY26UuIR3UZqmn/FEo8QwywRgywRjih+Z2qRtmu9Nn4l+cF+9SVxQF3z14Hp/+0RGEYmnoRAF/8Ye1+OBrtsJsWJ7rXkVRMBAaQGcgWyzvDnYjnAxrxhQbirHXtVfd5HN72XYWyxconZIwcjIC/2AIwwNhBIbCSCe0+z2JegGu6hK1s9xda4feJGBsbAzBYBAvdvsQDAYRCAQQjUYX/L2np6eXejkLtuji+dvf/nYAwF133aUeEwSBG4YSERHRqiNNTSHR26tu6Bn3+SCNjeWNE4uLYW5uyhbLW7ywNDcv68adgk6Hoo72ZTs/EREREdGlCAYdjBttMG60qccURYEUTqnd6TOF9cxYHHI0jeRACMncBo8AAFGAwWnRxr54ihCQJHzsu7349fFs8b3RU4LH3+ZF0wb7kq5BURScDJ/UFMsnEhOaMVa9FXtce9QYlu1l26EXVy4qZi1LTKfVQrl/IITRM1OQJW1eudGsg7vOAU+9HVX1DlgrBIyNjyIYDOJAvw/BF4IYHR2FfOFdvTk2mw1TU1PzPjZXcXHxZccsl0X/aTl58uRyzIOIiIjoqijpNBLHTyDR68tFsPiQGhrKH6jXw7xtG8wt3myx3NsMY00NBJEdJ0RERER07RIEAXqHCXqHtktdTknIzHSpB6JI5QrrSkJCOhBDOhADDs6eZwIy3gwZzYIZ9U2VeO31NbC4iq56foqi4MzUmWyx3N+FrmAXxuLaxhizzozdzt1qDEtjeSMMouEiZ6QZiqJgajwB/2A4F8MSxqQ/vzO8yG6EZ6sDrhobzBUZJJQpBIMBHAn24Fd9wYt2k5tMJrhcLvXL7XajsrISBoMBTzzxBCKRyEXnVlJSgurq6iVb62ItqnieTqfx6le/Gj/60Y+wY8eO5ZoTERER0SUpioL0uXOI+3zqhp6JI0egJPPz8gwbN2Zzylu8MDd7YW7cAdFsLsCsiYiIiIjWHtGog3GTDcZNF3apJ5EeznanT54OY3wohIqMgjKIaIeIdgVAbxgTvYcAnQCD06qNffEUQVdsvOT3Pjd1Dl2BLnWTz5HYiOZxo2jELucuNYaluaIZBh2L5ZejyArGh6O5rPLs5p7Tk/nvpRxuCyq2mGEqT0MyxRCeHsFgwId9/zt20W7y8vLyvEK53W6/aGb+61//enznO9+56Fxf//rXQyxgo9OiiucGgwGJRGK55kJEREQ0LykUQry3T93QM97bC2liIm+caLdnM8pzG3pavF7oy5Z/MyIiIiIiomtJtkvdDNiM+LfREP5x6BySGRllBh0+3rEFr620IxOIqtEvSlJS/3lul7poM6ixL0Z3EcKOOLoyPegMZqNYhqPDmu+rF/XwVnjR7snGsHgrvTDpTCu8+rVHSssIno6oG3sGhsJIxjKaMYKowLYJMFdkoJhjiKbDOD82gv5TMeBU/jlNJhPcbremUO50OmE0XvoDkQs1Njbij/7oj/Dcc89pOtBLSkrw+te/Ho2NjVey5CWz6NiW97///Xjsscfwta99DXo9M4KIiIhoacmpFJLHjmWjV3p9SPT4kDp9Om+cYDDAtGOHuqGnxeuFobr6oh0NRERERES0dI4MR/DRZ3rQdz5b8Hzl1go8/NZmbCqzasYpigJpMqnGvszkqWcmEpCn0khOTSJ5YlId3ywUw25sRJ25BKfNfsBphLt2M3Zt2YuWyhZY9JYVXedalIyl4R8MZ78GQhg5NQUpk+0UV6BAFlNQiuKwODOAJY64FEF4ahIjSRk4n3++mW7yucXyS3WTL1ZjYyMaGhpw+vRpTE9Po7i4GNXV1QXtOJ+x6Op3V1cXfvGLX+DnP/85mpubUVSkzSx69tlnl2xyREREtL4pioL06dO5zTyzm3omjx6Fkk7njTVWV6vd5JYWL0wNDRAX2dVARERERERXJ5mR8MVfDuCffj2IjKygxKzH376pEW/bu3HeYqogCNCXmaEvMyNaq6A7cASdgU74zh+CMJZGTWIjapIbUJvYgJrkBlhlC+qSm1CX3ASEAQQB9AJiiYBp9yBSc2Jf9BVWCDo2z0xPJtUIluGBMMaHpwEFUCAjo49B0k8D9jiEogQS8hRSmWyyyGQcQHz2PGazed5s8sV2k18JURRRU1Oz7N9nsRZdPHc4HLj99tuXYy5ERES0zmUmJnI55dlCeby3F3I4nDdOV1oKs7c5Wyj3tsDS3ASdw7HyEyYiIiIiItX+05O49xkfBkamAQCv3+nGp2/dCadt/j2FJhOT6A52o9OfjWEZDA9qHhcsAoQNFjjddbB46uCp2A1LVJ/rUI8iletWl8YTkCMpJCMpTZc69AIMriJNlrrRUwTRun5zzxVFwWQgpkawDA+EEBmPQxZTyOijkAxRZEqmoZjjSAlRAMrsk1PZ/xMEYd5s8pKSEt7Je4FFF8+feuqp5ZgHERERrTNyIoHEkaNI9PpyESy9SJ89mzdOMBphbmzMbuiZ6yw3bJy/a4WIiIiIiFZeLJXB5352HN/4/SkoClBRbMJn3rITb2j2aMaFk2HsD+5XN/k8MXki71zbSreh3d2ONncb9rr2wm6yaweYAX25BZadFeohOZlBOhDL5aZPqxEwSkpG+vw00uenNafQlRhzxfRiGDxWGDzF0Jdb1mSXupSRMXpmCv6BMPyDIQwPTGA6Gc4WyfW5L+c0FDEz7/PNZnNeNvlKdZOvB1ccWj46Oorjx48DALZv347KysolmxQRERGtLYosI3XqVLZIntvUM3H8OJDJv4Az1taq0SvmZi/M27dBMKzfzhAiIiIiorXshf4x3PesD+cms/ket+/ZiL990w44rEZMp6ZxYOQAOv2d6Ax04tjEMShzO50B1Dvq0eZuQ7u7Ha2uVjjMjkXPQTTpYaougam6RD2myAqkycRsh/pMl/pEAlIkBSmSQuL43C51EQaXVdOhbnCvvi71VCKDwFAYw/0hnOkPwD8cQEqYUgvlUnEMsOU/b243+dxiObvJr86ii+fRaBQf+MAH8O///u+Q5WzQvE6nwx133IEvfOELsFqtlzkDERERrXWZ0VHEe3sR7/FlO8t7+yBPTeWN01VU5KJXvLB4m2FubobONs+VHhERERERrSrheBoP//govt2dvXt0g8OCB99SD2vJGTx19EvoCnThyPgRSIqked6Wki3ZznJPG9pcbSi3lC/L/ARRgL7cku1Sb5rTpZ7IqLEv6iall+pSt5vUgrqapV5ugSCuTME5Gk7i3PFxDBw9g/NnhjEZGUdGP42MIZrtJi/Jf47FYpk3m9zApqQlt+ji+d13343f/OY3+OEPf4iXv/zlAIAXXngBH/zgB3HPPffgn/7pn5Z8kkRERFQ4ciyGxJEjavRK3NeDzLA/b5xgscC8sxGW5mxXucXrhd7jYZcDEREREdEa8/PDAXz8e30YmZ6Cznoau7aNw1g8hHu7jiCjaO8u3WTbpMawtLnb4LQ6CzTrLNGsh2mLHaYts3EwiqwgM5HQxr74o5BCSUjh7Ffi2IQ6XjCI0LusMHqKYXBbc/EvRRAtVxziAQCQZRnnT47ieO9JnDt9HmPjo4jLEUi6GDDztqlodrwgCCh1lKGqygOXe7ZQbrPZ+D5rhQiKoiiXHzaroqICTz/9NK6//nrN8V/96lf4oz/6I4yOji7l/JZcJBKB3W5HOBxGSck8H90QERFdwxRJQnJwEAmfD/Hcpp7J/n5A0naTQBBgqq/PberZAkuLF6b6egj6q7uYpOXB6x8iuhS+RhAR0YzzoQg++qMfoivQBV3RIPSWc4CgLZZXFVVlY1g87Wh3t8Nd5C7QbK+enMhoOtRT/igygSiUtDzveJ3jgi5198W71NPpNIKBIAaPncGZk+cwOjaK6WQIspCe99wGnRFljkps3OTBxuoNajY5u8mXx0Kvfxb9DjcWi8HlcuUddzqdiMViiz0dERERFVA6GES8pweJmQiWvj7I8/x9rne5srErXi8s3haYd+6ErrhonjMSEREREdFakZbS6B3rRWegEz/pfwEnpw8DQgamOVsbuqwutbO83dOODcUbCjfhJSaa9TDV2GGquaBLfTyujX2Z6VLPfSWOznapwyAgWSkiVJLEhC6K4alxjIbHMZ2M5H9DAYACmHQ2lJaUY8NGD+oaNmPj5g3sJl+lFl08f9nLXoYHH3wQ//7v/w6z2QwAiMfj+NSnPoWXvexlSz5BIiIiWhrSdBSJvj7Ee31qZ3kmGMwbJ1qtMDc15Tb0bIalpQWGeT44JyIiIiKitSUtp3F47DC6g93o9Hfi0OghxDPx2QECIMoluM7TjtfWvhzt7nZssm26poq6gijAUGmFodIKeGc/RZBjacTOheAfOI/AOT9GJkYwGp/EJKaRnMgAE/nnMsoGWOVi2MwOVLhd2NJcg+3eLTBbTCu4Iroaiy6eP/nkk3jd616HjRs3oqWlBQDQ09MDs9mMn/3sZ0s+QSIiIlo8JZNBsr8/F73Sg4SvF8mBAeDCtDZRhGnbttkNPb1emOrqIOh0hZk4EREREREtGUmWcHTiKDoDnegMdOJg8CBiGe2dpopUhEy0FojX4127Xo2PvvqVMOqv7fcDiqIgHA4jGAyqX4FAABMTE9AkYM98pqAIsMpWOORiuGCDUylGuVwMC4wQIADTAAYA4cwYIvvjiM+JfTF4iiCaGH+5Wi36N9PU1IT+/n7853/+J44dOwYA+JM/+RO8853vhMViWfIJEhER0aUpioKM34+4z5fb1NOHxOEjUOLxvLH6Kk82o7y5OdtZ3tgI0WotwKyvbZIs4cDIAYzGRlFprcQe5x7oxGv7DQoRERERXT1ZkXF84jg6A53oCnRhf3A/ptPTmjF2kx07HLtw8pwHQ2fdkJMu7Nlcisf/zIt6p61AMy+cVCqFkZERTaE8GAwikUjMO16QDNBnirJf6WKUOipQXV+FjdvK4amzw1ZuhhLPIDUT+zIT/RKMQknJSJ2ZQurMlOacujKzWkg35grrulLzvFnqtLKu6GMNq9WK9773vUs9FyIiIloAaWoqm1E+Z1NPaWwsb5xYXJztJm/2wtLihaW5GfrKynnOSCvp+dPP49HORxGMzUbmuKwu3Nd+H26svrGAMyMiIiKitUZWZAyEBtAV6EKnvxPdwW5EUtqsbZvBhr2uvWhzt2GvsxW/O2zAPz4/gGRGhtWow0dv2Y4/fdkW6NZ5oXammzwQCGiK5OPj4xd5ggBdxporkmeL5QbZBtfGMlRtLUVVvR2eOgfMxfkbegpWA8x1DpjrHLOnkxRkxmJqhvrMlxRJQZpIQJpIIHFkdi6CUZfrTrfC4ClW/5ld6itrwT/t3/72twsa94d/+IdXPBkiIiLSUtJpJI6fUKNX4j4fUkND+QP1epi3b4fZ25ztLPc2w1hTA0EUV37SdFHPn34ed//6bijQxueMxEZw96/vxj9c/w8soBMRERHRRSmKgqHwkNpZ3h3oxmRyUjOmyFCEPc492U0+PW1oKG2ATtThqD+Ce7/tg+9cGADwivoKPHJbMzaVrb87Ued2k88tlieTyXnH62GEmCqCLj1bKNdlrDCaDHDX2dVCubOmBAbjld0xKugEGFxFMLiKgJbZ41I0rdmYNO2fRjoYg5KSkDodQeq09sMQXbkZxlyXevarGLpS0zWVS7+SFlw8v/766y/62MwvRxAEZDKZq54UERHRtUhRFKTPnUPcl9vQs8eHxNGjUOa5wDNs2jQbvdLshblxB8TcRt60OkmyhEc7H80rnAOAAgUCBDzW+Rhu2HQDI1yIiIiICED2PcLpyGm1WN4V6MJ4QtspbdFbsNu5G23uNrS729FY3gi9OFvyS2YkPPn8cXz514PIyApKzHp8/E2N+D97N675gquiKAiFQvNmk89HFERYDCXQpa2QIqZcobwYomwEAFhKjKhqtMNT70BVvQPlG4og6pa3IUlXZICu3gFzvWN2XZKMzFgcaX9UE/8iT6UgjScQH08gfnhOl7pJp8a+GObkqYtXWOinWQsunk9OTs57PBaL4cknn8TnP/951NbWLtnEiIiI1jspFEK8tw9xX0+uYN4LaZ6/b0W7PVso93pzneVe6MvKCjBjuhoHRg5ooloupEBBIBbAgZEDaHO3reDMiIiIiGi1UBQF56bPZWNYcgXzkdiIZoxJZ8Kuyl3ZYrmnHU3lTTDo8qNDAODAmUnc+7QP/SPZ3PPX7XThM29pgrNk7TXepFKpvFzyS3WTWy1W2Cyl0KWLkJ40IhMyQpexQsBsMdzhssJTly2We+rtsFdaVsUHCoJOVLvUrbtmj0vTqbzYl/RIDEpyni51AdCXW7SxL54i6BzsUl+MBRfP7Xa75t9lWcbXv/51fOpTn4IoivjSl76EO++8c8knSEREtB7IqRSSx45lN/TMdZanTp/OGycYDDDt2AGL1wtLrlBuqK7mxc0alZEzODJ+BPv8+/DjoR8v6DmjsdFlnhURERERrSb+aT86A51qsdwf9WseN4gGeCu92RgWdxtaKltg1Bkvec5YKoO///kJfP1/T0JRgIpiIz715ibc3Oxe9e8tZrrJL8wmv2g3uSiisrIS9qIy6KViZMJGTJ0TkAmIkAHIuXEGUUBldTE8dQ54tmZjWKwll/45rja6YiN09UaY60vVY4okIzM6t0t9OtulPp1GZiyOzFgc8b45XepmbZe60VMMvcvKLvWLuKKE+WeffRYPPPAARkdHcf/99+MDH/gATCbTUs+NiIhoTVIUBenTp7Mbevb4EO/tRfLoUSjpdN5YY3U1zC1eWHKbepoaGiAa19YFHM1SFAUDoQHs8+/DvsA+dAe6MZ2eXtQ5Kq3c1JWIiIhoPRuJjaiF8k5/J85Nn9M8rhf0aK5sVmNYWipbYNYvvFP8fwfGcN+zPpydiAMAbtuzAX/7xkaUFq2+9xnJZHLebPJUKjXv+OLiYrhcLlSWO2FEMeQpM8JnFYwemcZkWtaM1RtFuGrs8NTbUVXvgKumBEbz+ttsU9CJ2WK4uwjW3bPHpal5utRHY1ASElKnIkidmqdLfU7ki6GqCDo7u9QX9SfmN7/5De6991709vbiQx/6EO699968jnQiIqJrTWZiQo1difuyxXI5HM4bpystVWNXLN4WWJqboHM4Vn7CtKTOTZ1Ti+Wd/s68DEqb0YZ2dztaXa34Wu/XMJGYmDf3XIAAl9WFPc49KzV1IiIiIloBY/ExNYalO9CNU5FTmsd1gg47y3eqxfJdzl2wGha/iWc4nsYjPzmK/+46CwCospvx2duaccN251Is46rIsjxvNvnFYqJ1Oh0qKyvhcrngcrlgLy6DMm3G5NkUhgdCGPr9NBQlCWA2ssVcbFAjWKrqHajYXAzdMueVr2Y6mxE6mxHmrXO61DMy0qNxtTt9priu6VLvHVPHCxY9DO4iGOdmqbusEAzXTpf6govnN998M55//nncdddd+N73vge3272c8yIiIlqV5EQCiSNHkej1qREs6XPn8sYJRiPMjY3ZDT293mz8ysa1vyEPZd/8dPqzt9W+5H8J56fPax4368zY49qDDk8HOtwdaChrUDcAdRe5cfev74YAQVNAF5D9c3Fv+73cLJSIiIhojZtMTGoyy4fCQ5rHRUFEQ1mDGsOyx7kHxcbiq/qe/3MkiI9/rxfBSLaYfMfLqvHR1zeg2LTyndbJZHLebPJLdZO73W61UO5yuaDLWDByahr+/hAGD4QRGR3Oe15JhTmbVV5nR9VWBxwuK99vXYagF2H0ZIvhc0lTqTkd6tNI+aPIjMahxDNInQwjdXJOc5gA6CvmdKnn8tR1Jcar+vkrsoLkyTDkqRREmxGmGjsEsfC/T0FRlPzWp3mIogi9Xo+ioqJL/iAulj+0WkQiEdjtdoTDYZSUlBR6OkREtIopsozUyZOI+3oR9/Ug0eND4sQJIJPJG2usrc12lLd4YW72wrx9GwTD/Jv20NoylZpCd6BbLZYPhAY0j8/cVtvh6VBvq71UBuXzp5/Ho52PajYPdVvduLf9XtxYfeOyrIHXP0R0KXyNICK6OuFkGN3BbrVg3j/Znzdme+l2tbN8r3svSoxL83o7Np3EJ39wGD/yZXPSayqK8NjtXrTXlC3J+S9lppv8wmzyhXSTzy2WW8wWjJ6dhn8gBP9AGP7BEOJTF0ReCkD5hmJU5Tb29NQ5UFzKCOnlpGRkpEdis0X1QLawLkfz3w8DgGjVa7LUDe7shqeC4fLd//G+MYR+OAgpPPsBi85uhOOWOliaKpZsTXMt9PpnwR8/PfXUU0syMSIiotUqMzqKeG9vrqO8B4nePsjT+XnVuoqKXPRKdlNPc3MzdDZbAWZMyyEpJXFw5CA6/Z3Y59+Hw+OHISmSZsxMp1CHpwN7XXtRZCi6yNny3Vh9I27YdAMOjBzAaGwUldZK7HHuYcc5ERER0RoxlZrCgeABtbP82MSxvFi+ekc92t3t2WK5ay8cZseSzkFRFHz/0DA+9cPDmIyloRMFvPeVtfjrG7fCvAyRGolEIi+bfGRk5KLd5DabTdNJ7na7UV5eDp1Oh3RSQuBkGP4jYfT+4AQCJyPIJLXX2zq9CFdNSTaGZasD7lo7TJb1l1e+mgl6EcaqYhirZu+KUBQF8lRa7U6fKapnRmOQYxkkh8JIDs3pUhcBfYV1Tpd6EYzuIohzutTjfWMY/+bRvO8vhVMY/+ZRlL9rx7IV0BdiwZ3n6wW7KoiICADkWAyJI0fU6JV4rw+ZYX/eOMFigXlno7qhp8Xrhd7j4e2A60hGzuDw+GG1WH5w5CBSsvZNQHVJtVosb3e3o9RcepGzrU68/iGiS+FrBBHRpUXTURwIHkBXsAtd/i4cmTgCWdFuTlljr1FjWFpdrSi3lC/bfIZDcXz8e3345bERAMAOTwkev92L5o1Xvy+hLMuYnJzU5JIHg0GEQqF5x+t0OjidTk2h3OVyoahotrkkPpWCfyCM4cEQ/P0hjJ6dhiJry5Emq17NK/fUO+DcbINuAR3LtDoo6bld6rN56nLsEl3qniLoXVbEDo5Cic8/DgB0dhPc97YteYTLkneeExERrVWKJCE5OIiEL5dT3tuLZH8/IGm7GyAIMNXX5zb1bIGlxQtTfT0EPf+6XE8URcFAaCC7yad/H7qD3ZhOa+8wqLRUZjPLc7nlnmJPgWZLRERERCstnonj4MhBNYbl8Fj+nYibbZvVGJY2dxsqrZXLPi9ZVvBfXWfwyE+OYTqZgVEn4gOvrsf/d30dDFewMWYikZg3mzydTs873maz5WWTz3STz1AUBZGxBI75/PAPhDA8EEYoGMs7V3GpKbexZ7ZgXuYpWhX51nRlBIMI44ZiGDcUA3AByHWpR1LZDvXAbJ56ZjSe7VIfDCM5GL70iQFI4SSSJ8Mw1zmWdxEXwWoAERGtO+lgEPGeHiRyESyJvj7IsfwLNr3LlY1d8Xph8bbAvHMndMULj9+gtePc1Dm1WL4vsA8TCe0eLTajTe0s7/B0oKakhncXEBEREV0jklISPSM9agyLb8yHjKzthN1QvEFTLHcXuVd0jqfGorj3GR/2ncxex+7e7MDjt3ux1XX5+MiZbvILs8kX0k0+t1hutVrnObeC0TNT8A+GMNyfzSuPhfOjXMqqijSbe9rKzIv7AdCaIwgCdHYTLHYTLA2zGfxKWkI6mO1Sj/lGkewPXfZc8tT88UArgcVzIiJa06TpKBJ9fYj3+tTO8szISN440WqFuakpt6FnMywtLTC4XAWYMa2EsfhYNoYlkC2Yn58+r3ncrDNjj2uPWixvKG1g5jgRERHRNSIlpdA71qsWy3tGevJi+9xFbrVQ3uZuw4biDQWZa0aS8fX/PYm///kJJDMyLAYd/uZ123HnH2yBbp5O7Xg8Pm82+cW6yUtKSvKyycvKyjTd5Jr5pCQET0WyG3sOhOAfCiOd0HblizoBzmqbGsHiqbPDXGS4+h8GrQuCQQfjRhuMG23QlZkXVDwXbcbln9hFsHhORERrhpLJINnfj7ivN7uhp8+H5MAgcOH2HaII07Ztsxt6er0w1dVBuMgFIK19U6kpdAe61WL5QGhA87he0KO5slmNYfFWemHUFe4CjIiIiIhWTlpO4/DYYbVYfmjkEBJSQjOm0lKpdpa3u9ux0bax4HciHgtEcO/TPvScy0ZbvLy+HI/e5sWmMitkWcbY2HheNnk4PH8Mhl6vnzebfL5u8rkS0TT8g7lC+UAII6enIEva918Gsy6bV17ngKfeDteWEuiNfO9Fl2eqsUNnN0Ka526FGTq7Caaaq8/zv1IsnhMR0aqkKAoyw8OI56JX4j4fEocPQ0kk8sbqqzzZjPLm5mxneWMjxMtcBNLalsgkcGj0kBrFcnj8cN6mTQ1lDehwZzvL97r2wmrgnwkiIiKia0FGzuDo+FG1WH5g5ADimbhmTJm5TBPDsqVkS8GL5TOSGQlf+tUgvvyrAWRkBWVm4APXVaKxVMHBF57HcwvoJr8wm/xS3eRzTU0kMNwfUgvmE8PRvDFWuxFV9dlCuafegfINxRCZV05XQBAFOG6pw/g3j150jOOW2oLm4S+6eH733XfPe1wQBJjNZtTX1+Mtb3kLysrK5h1HREQ0HykSycav+Hy5znIfpLGxvHFicXG2m7zZC0uLF5bmZugrl39zHiqsjJzB4fHDarH80MihvFtrq0uq1WJ5m7sNpebSAs2WiIiIiFaSJEs4Pnlc3eDzQPBA3obwdpMdba42tWBe56hbNcXyGbIs44XDp/BPP9mPxNQEXqWLwWNNQZ+J4/RLwOkLxs/tJp9bLLdYLAv6foqsYMIfVTf29A+EMD2ZzBvncFnVjT099Q6UVJhX3c+O1i5LUwXK37UDoR8OajrQdXYTHLfUwtJUUcDZXUHx/ODBgzhw4AAkScL27dsBACdOnIBOp0NDQwO+/OUv45577sELL7yAxsbGJZ8wERGtfUoqhcSJ/lz0SrZQnhoayh+o18O8fTvM3uZsZ7m3GcaaGgji4neSp7VFURT0h/rVYnl3sBvRtLbrxWlxqpnlHZ6OFd+0iYiIiIgKQ1Zk9E/2q8Xy7mA3plJTmjE2gw173XvVGJatpVshCqvnfUQ8HtdErgQCQfiDQUCWsB2Yrdjl9i212+3zZpOLi3hvJKVljJyZUiNY/INhJGPajVEFUUDlpmJ4tjpQlYthsRQwb5quDZamCpgby5E8GYY8lYJoM8JUYy9ox/mMRRfPZ7rKn3rqKZSUlAAAwuEw/vzP/xyveMUr8N73vhfveMc78OEPfxg/+9nPlnzCRES0tiiKgvS5c4j3+JDozW7omThyBEoqP9PMsGnTbPRKsxfmxh0QzdyF/Vpxduos9vn3qRt9TiQmNI+XGEvQ7m5Xi+Wr6dZaIiIiIlo+iqJgMDSoFsq7Al0IJUOaMUWGIux17VVjWLaXbl8VG8LLsozx8fxs8kgkMu/4jCICFjtatlVj8wbPorvJ50rGMwgMheHPxbAET0UgpbVRh3qjCHftTFe5He4aOwymwv/c6NojiALMdY5CTyOPoCgX7rJ2aRs2bMD//M//5HWVHz58GDfddBPOnz+PAwcO4KabbsLYPLfbF1okEoHdbkc4HFaL/0REtHSkUCibU+7L5ZT7eiFNTuaNE+32bKHc6811lnuhZ+TXNWUsPqZ2lncGOnF++rzmcYvegj3OPejwdKDd046G0oZV8QZoLeL1DxFdCl8jiGi1URQFpyKn1M7yrkBXXmPFzLXiTAzLjvId0IuF3dovFoupRfKZr5GREWQymXnHl5TYMQkr+iaACdkKfZEDH3trG17deGV3VEZDSQwPhOAfCMM/GML4uWlcWPWz2Azqxp6eegcqNhVDp1s9HflEK2Wh1z+LflUJh8MYGRnJK56Pjo6qn5o5HA6k5ukoJCKi9UVOpZA8elTNKE/4fEidvjCJDxAMBph27IDF64UlVyg3VFeza/gaE0lF0B3oVovlA6EBzeN6QQ9vpTdbLHe3o6WyBQadoUCzJSIiIqKVoigKzk2dQ2egM9tdHujGSHxEM8akM2GXc5caw7KzYicMYmGuFSVJwsTEhNpFPvN1sW5yg8GQl01+dFLAgz85gWAkmzH+rus2497XN8BmXtiaFEVBKBjTbO4ZGUvkjSuptKCqzg7PVgc8dXY4XFa+DyNahCuKbbnrrrvw93//92hrawMAdHV14SMf+QhuvfVWAEBnZye2bdu2pBMlIqLCUhQF6dOnsx3lPT7Ee3uRPHoUyjw7vBurq2Fu8cKS29TT1NAA0cicvGtNIpPAwZGDarH88PhhyMrsbaICBDSUNajF8r2uvbAarAWcMRERERGtlOHpYbWrvDPQiUA0oHncIBrQUtmixrB4K70w6lb+PcXcbvKZYvno6OhFu8kdDkdeNnlpaamaTT4+ncSnfngEP+gZBgBsKbfisdu96Kgtv+Q8JEnG2JnpXGd5tmCemNa+FxMEoHxjMTz1DlTVZ4vlRQ7TEvwUiK5diy6e//M//zM+/OEP44//+I/VFwq9Xo8777wT//iP/wgAaGhowNe+9rWlnSkREa2ozMSE2k0e9/Ui3tsLORzOG6crLVVjVyzeFliam6BzOFZ+wlRwGTmDvrE+dAY6sc+/D4dGDiEla+9E21KyRS2Wt7vb4TA7CjNZIiIiIlpRwWhQUyy/MLJPL+rhrfCqMSzeSi/M+pXb/0iSpHmzyaempuYdbzAYNEXymS/zRfZsUhQFP+gZxid/cBiTsTREAXjvH9biwzdug9mQH02YSmQQPBlRY1iCJ8PIpLR55TqDCNeWEnjq7aiqd8Bda4fRUtjoGqL1ZtGZ5zOmp6cxNDQEAKitrUVxcfGSTmy5MM+PiCifnEggceQo4r4eJHIRLOlz5/LGCUYjzI2N2Q09vd5s/MrGjbzt7xolKzL6J/vVYnl3sBvRdFQzxml14jrPdepGn+6iK8tvpKvD6x8iuhS+RhDRchiLj6HT36lu8nk6oo131Ak67KzYqXaW76rctWJ3IcZisbzIlZGREUiSNO94h8Ohxq3MfM3tJr8cfziOj3+3D784lo2iaXDb8PjbvPBudMzOKZKCfzAEf382r3z07DQUWVuyM1n16saeVfUOVG62QadnXjnRlVi2zPMZxcXFKMtt7LZWCudERAQosozUyZO56BUfEj0+JE6cAOa57dBYW5vtKG/xwtzshXn7NggGZlBfq2ayKPcFZjf5vHDjJrvJrnaVd3g6sKVkCz9cISIiIroGTCQm0BXoUjvLT4ZPah4XBRE7ynaoxfI9rj0oMhQt65xmuskvLJQvpJt8pljudDov2k1+ObKs4L+7zuKRnxzFVDIDg07AB169FX/xh7WITyZx9Pd+NYIlFIzlPd9WZlY39vTU21HmLoIg8tqaaCUtunguyzIeeugh/P3f/z2mp6cBADabDffccw8+9rGPLfhTNyIiWhmZ0dFsTrmvN9tZ3tsHOff6PZeuoiIXvZLd1NPc3AydzVaAGdNqMhYfwz7/PvVrODqsedyit2CPcw86PB3o8HSgoawBosBrASIiIqL1LpwMozvQrW7yeeFm8AIEbC/brsaw7HXthc24fO8votHovNnkF+smLy0tzcsmdzgcS1bXOjUWxX3P+vDS0AQEBXhlZQnu3OpBZjCOb/3sRcQi2nhDCEB5VRE8dQ54ttrhqXPAVrZysTVENL9FF88/9rGP4V//9V/x6KOP4uUvfzkA4IUXXsAnP/lJJBIJfPazn130JL70pS/hc5/7HAKBAFpaWvCFL3wB7e3tl33ef//3f+NP/uRP8Ja3vAXf+973Fv19iYjWGzkWQ+Lw4VyhPNtZnhn2540TLBaYdzaqG3pavF7oPR52CBMiqQi6A91qsXwwPKh5XC/o4a30qsVyb4UXBh3vRiAiIiJa76ZSU9gf3K/mlh+fOA4F2liRraVb1c7yVlcr7Cb7ks9DkiSMjY3lFcqn52kQAgCj0ThvNrnJtDwbaUqygn/99SC+/bMBVCYFvF0yYTN0wEAaxwfOqONEvQBXdYnaWe6utcNcxOtqotVm0cXzf/u3f8PXvvY1vPnNb1aPeb1ebNiwAe973/sWXTz/9re/jbvvvhtf+cpX0NHRgSeeeAKve93rcPz4cTidzos+79SpU/jIRz6CV77ylYtdAhHRuqBIEpIDg0j0+nIRLL1I9vcDF3ZWCAJM9fW5TT1bYGnxwlRfD0HPjWQISGQSODhyUC2WH5k4AlmZ3YhIgICGsga1WL7HuWfFsiiJiIiIqHCi6Sj2B/er3eVHJ45qrhMBoNZeq3aWt7pbUWYuW9o5RKN5kSuX6ya/MJt8KbvJLyYxnYZ/MITDPaPoORiELS7jNhjnjFBgNOvgrpvNK3dusUE/z0ahRLS6LLpyMjExgYaGhrzjDQ0NmJiYmOcZl/YP//APeO9734t3v/vdAICvfOUr+PGPf4yvf/3ruO++++Z9jiRJeOc734lPfepT+N3vfodQKLTo70tEtNakg0HEe3qQyEWwJPr6IMfyc/H0Llc2dsXrhcXbAvPOndAVL2+WIK0dGTmDvrG+bLE8sA+HRg4hLac1Y7aUbFGL5W2uNjjMjsJMloiIiIhWTCwdw6GRQ2pn+eHxw5AUbZG6uqRaLZa3udtQYalYku+dyWTmzSZfSDf53Gzy5eomn0tRFEyNJ+AfDGN4IAT/QBiT/qj6uAMAIECw6lC3oxyeegeqttpRVlUMkXnlRGvOoovnLS0t+OIXv4jPf/7zmuNf/OIX0dLSsqhzpVIp7N+/H/fff796TBRF3HjjjXjxxRcv+rxPf/rTcDqdeM973oPf/e53i1sAEdEaIE1HkejrQ9znUzvLMyMjeeNEqxXmpqbchp7NsLS0wOByFWDGtFrJioz+yX61WL4/uB/RdFQzxml14jrPdejwdKDd3Q53kbtAsyUiIiKilZLIJNAz2qMWy3vHepGRM5oxG4s3os3dphbMXUVX/15jenp63mxyWZbnHV9WVpaXTW6321dszz1FVjA+HM1u7Jnb3HN6Mpk3bkyUcV4vw765GP/f7Y2o3WJnLCbROrDo4vnjjz+ON77xjXj++efxspe9DADw4osv4uzZs/jJT36yqHONjY1BkiS4Lij0uFwuHDt2bN7nvPDCC/jXf/1XHDp0aEHfI5lMIpmcfVGLRCIAsp9qZjLZvxREUYQoipBlWfNiPXNckiQoinLZ4zqdDoIgqOedexxA3m1FFzuu1+uhKIrmuCAI0Ol0eXO82HGuiWvimtbOmkRFQbK/H7FDh5Do7UOitxepwUFA0eYHQhRh3LoV1pYWmJubYWzaCWNtLYTceWfmPvf8/D1de2sSBAGnw6exz78v+0Yo2IXJ5KRmbnajHa2uVlxXlS2Yb7Ru1FzYz5xztaxpPf6eVnpNF7u1mYiuTXyPxDVxTdfmmlJSCr1jvTgwegCdgU70jPbk3YHoKfKg1dWa/XK2YoNtg2ZNi3mNyGQyajb56OioWjCPRrWNHDNMJhOcTiecTic8Hg9cLhfKy8thNM7Gn8xd09zvu5S/p3Qyg8CpMAKDYQQGIwgMRZCKX/AeThRQtqkY53QSngtO4pxOhsVmxINv2oFbWjZAFEX+2eOauKZVvqaFvkdadPH8Va96FU6cOIEvfelLaoH7tttuw/ve9z5UVVUt9nSLMjU1hT/90z/Fv/zLv6CiYmG3Bj3yyCP41Kc+lXf84MGDKCrKxhhUVlairq4OJ0+exOjoqDpm48aN2LhxI06cOIFwOKwer62thdPpRF9fH+LxuHq8oaEBDocDBw8e1PwCvF4vjEYjuru7NXNobW1FKpWCz+dTj+l0OrS1tSEcDms+QLBYLGhpacHY2BiGhobU43a7HTt27MDw8DDOnTunHueauCauaXWuyW6349D//A/QPwD90CB0Q0MwnDkDJZHfuaD3eGBs2onxsjJItXWQtlRDZ7Wirq0NoVAIvceOAQcPFnxN6/H3tNbWFMqEcCx2DOfF8/CFfBiODmvmaNaZsde9FxvSG7Ddsh0bTRshCiK8m1fvmtbj76mQa2LxnIjm4nskrolrujbW1LK7BYeCh/Dj3h/jROwEBuIDSCvaYrlD78B2y3Y0O5pxW9ttMMaMOHnyJDABDE8MI2qPLmhNyWQSU1NTEEURiUQCp0+fRiQS0RTB5rJarbDZbKitrUV1dTWCwSCMRqPa0NHY2Lhiv6dMUkF0VIY8ZUJ8XEDwZBjyBZdOepMONpcO5jIFNpeI05DwhWNhnJtIAgbgFRuNuKO5CCXJ84hEbNf8nz2uiWtaC2ta6HskQbnYK9kinTt3Dp/+9Kfx1a9+dcHPSaVSsFqtePrpp3Hrrbeqx++8806EQiF8//vf14w/dOgQdu/erX6KAED99EIURRw/fhx1dXWa58zXVbFp0yaMj4+jpKREfe5q/zRkPX7CwzVxTdfCmjLhMJKHDyPh60Wyrw/x3l5IY2O4kFhcDFNTE8zNzTB7m2FuboYpd1fOalvTevw9rbU1TWemsX9kP14afgmdgU4MhWcvXgBAL+rRXN6MDnc2hqXF2QKj3riq17Qef0+raU1TU1MoKytDOBxWr3+I6NrF90hcE9e0PteUTCdxdOIouoJd6A524+DoQSQyCc3YMnOZmle+t3IvNts2QxCEBa9JkiSMjY1hZGQEIyMjCAQCGBkZuWw3udvthtvtRmVlJSoqKtRu8kL8nqLhFEaGpjA8MInhgTAmhqPABZUxi80Ad50d7roSbNhaispNNihQEImn8NhzJ/Df3dkiocduxmfe3Ijrt1dq5nit/dnjmrimtbimhb5HWrLieU9PD/bs2bPozqaOjg60t7fjC1/4AoBsMXzz5s34q7/6q7wNQxOJBAYGBjTHPv7xj2NqagpPPvkktm3bprmdZz6RSAR2u51vHoloySmpFBIn+hH39SDR40O8txepOZ/IqvR6mLdvh9nbDIu3BZYWL4xbtkAQVyazj9aeeCaOgyMHs1Es/k4cmTgCWZlzwQIBDWUNuM5zHdo97djj3AOrwVrAGdNqw+sfIroUvkYQrU2SLOHY5DF0+bvQGejEgZEDeXvbOEwOTWZ5rb12QTnciqLMm00+NjamKYTNVV5ePm82eSFzvxVFwWQglssrz27wOTWeyBtnr7TAs9UBT50dVfUO2J2WvHn/4mgQH/tuHwKR7PPf2bEZ972hATazYUXWQkRLa6HXP4uObVlqd999N+688060traivb0dTzzxBKLRKN797ncDAO644w5s2LABjzzyCMxmM5qamjTPdzgcAJB3nIhoOSmKgvS5c4j3+LLFcl8vEkeOQEml8sYaNm2Cpbk5u6mn1wvzjh0QzeYCzJrWirScxuGxw3jJn+0sPzRyKC+PckvJFnR4OtDh6UCbqw0Os6MwkyUiIiKiFTGzEXxnoBOdgU7sD+7HVGpKM8ZmtKHV1ap2l28t3QpRuHSTTiaT0WSSzxTKY7HYvONNJhPcbremUO50Oi/bzLgSpIyM0TNT8A+E4R/MFswTUe11tCAAFZts8NTb4alzwFNvR5HddNFzjk8n8ekfHcH3D2WjEbeUW/Ho7V5cV1u+rGshotWh4MXzt7/97RgdHcUnPvEJBAIB7Nq1C88995y6ieiZM2cgshuTiApMCoUQ7+1F3OdD3OdDwtcLaXIyb5xot2cL5V5vtlje3Ax9WVkBZkxrycwboX3+fdgX2IfuQDdiGe2bFZfVpRbL293tcBe5CzRbIiIiIloJiqJgIDSQ3QQ+kI1iCSfDmjHFhmLsde1VO8u3lW6DTtRd9HzT09NqcXzm62Ld5IIgoKysLK9QXuhu8rlSiQwCQ+FssXwghODJCDJp7Vr0BhGumhJ46rOFcnetHUbz5cthiqLghz4/PvmDw5iIpiAKwJ+/shYfvnEbLMb5f8ZEtP4UPLZlpfGWRCK6HDmVQvLoUcR9M8XyHqRPn8kbJxgMMO3YkS2Ue7MFc0N19aq5kKTVS1EUnJ06q3aWd/o7MZnUfhhjN9nR7m5HhztbMK8u4Z8tunK8/iGiS+FrBNHqoCgKTkZOqjEs3cFuTCQmNGMsegv2uPag3d2Odnc7GsoaoBfzC8HpdBpjY2N5hfKLdZObzWZN3IrL5UJlZeWq6CafKxpOarrKx85O4cKqlqlID0+dA1W5YnnlZht0+sU1ZQbCCXz8e714/ugIAKDBbcNjt3vRssmxRCshokJb8tiW22677ZKPh0KhBU+OiGi1UBQFqVOnkOjtzUWw+JA4dgxIp/PGGqurYW7xwtKc7So3NTRAXGUXk7R6jcZGsS+wL9td7t8Hf9Svedyit2Cva69aLN9etv2yt9gSERER0do101AxE8PSHejGaHxUM8asM2OXc5caw7KzYicMokFzjkgkMm82+Xy9koIgzJtNXlJSsuoaNRRFQXgkjuGBEPyDYfj7QwiPxvPG2crNaqHcU+dAqdsKQbyytSiKgv/uOouHf3wUU8kMDDoBf3XDVvzl9XUwLrIAT0Trw4KL53a7/bKP33HHHVc9ISKi5ZSZmMjFrviyxfK+PsjhcN44XWkpLF7v7KaezU3Q5fZYIFqIcDKM7mC3WiwfCms3j9WLengrvLjOcx06PB1ormiGQcfNhoiIiIjWs/PT59Hpz8awdAY6EYwFNY8bRSNanC1qDEtzRTOMumzDTjqdxmggP5s8Hs8vKAPZbvL5sskNhtV5zSlLMsbOTasRLMODYcQjF+wpJQDlVcWoqrerMSzFpUuzn9Tp8Sjue6YXLw6NAwBaNjnwubd5sc1lW5LzE9GlKZKEWPd+ZEZHoa+shLV1LwRd4SOSFlw8f+qpp5ZzHkRES05OJJA4cjS3oacPcV8v0ufO5Y0TTCaYGxth8TbD7PVm41c2blx1nRe0usUzcRwcOagWy49OHIWszOYtChDQUNagFst3O3fDarAWcMZEREREtNwC0YBaKO8KdOH89HnN4zMNFe2ebAyLt9ILo2jE1NQUAoEA9p3Yp8kmv1w3+dxi+WrsJp8rnZIQPBmBfyAE/0AIgaEI0kltFLCoF+Dakssrr7PDU2eHybq0xX9JVvDU/57E3/38OBJpGWaDiI/ctB3vfnkNdFfYwU5EixP5+c8RfPgRZAIB9Zje7YbrgftRctNNBZzZKtgwlIhoKSiyjNTJk7nolR4kfL1InDgBZDJ5Y411ddlNPVu8MDd7Yd6+DcIq7b6g1Sstp3F47DBe8r+Eff596BntQVrWxv3U2GvQ7m7HdZ7r0OZug9106bu4iIiIiGhtG42NqoXyrkAXzkxp907SC3rsrNg5G8NSuhPTk7lNPA8G8V/B/7pkN7nFYpk3m3y1dpPPFZ9OqV3l/sEwRk9PQZa1HwYYLfpskTzXWe6stkFvWL7O0xPBKfzN0z70nA0BAF5WW45Hb29GdXnRsn1PItKK/PznOP+hv8aFGxhkgsHs8SefKGgBncVzIlqTMqOjuc08e7PF8t4+yNPTeeN0FRW5DT2zm3qam5uhs/G2O1o8WZHRP9mvFsv3B/cjltFuuOSyutDh6cB1nuvQ7m6Hq8hVoNkSERER0UoYj4+jK9ilbvJ5KnJK87goiGgsa0SruxUttha4JBdC4yEEBgPY//v9+Pn4zy/aTV5RUZGXTW6z2VZ1N/kMRVEwNZ7I5pXnCuaTgfzNSoscpjkRLA6UVxVdcV75YqQyMv7p14P44q/6kZYU2Ex6PPDGHfjjtk1r4udLtF4okoTgw4/kFc6zDyqAICD48COwveY1BYtwYfGciFY9ORZD4vDhXKE8u6lnxu/PGydYLDDvbMxmlHubYfF6ofd4ePFDV2RmA6eZYnlXoAuTyUnNGIfJgTZ3mxrFstm2mX/eiIiIiNaxUCKE7mC32l0+EBrQPC5AwA7HDuy27ka1UA1rwoqJ0QkE+4J4IfHCvOe0WCx52eRrpZt8hiwrmBiexnB/GP7BEPz9IUTDqbxxpZ4ieOrt2Q0+6+ywlZtX/Pq552wI9z7jw7HAFADgxh1OPHRrM9z2pclOJ6KFi3Z3a6Ja8igKMoEAYt37UdTRvnITm4PFcyJaVRRJQnJgEIne3IaePh+S/f2ALGsHCgJM9fUwt3hhafbC0uKFqb4egp4va3TlRmIjamZ5Z6AT/qj2QxqL3oK9rr1qsXxb6TaIglig2RIRERHRcoukItgf2K8Wy09MnoCCXIekAlgkCxqNjajX1aM0XQopImHy1CQSSgLHcVxzrrnd5HOL5Wulm3yuTFrCyKkptbM8MBRGKq6NzBRFAZXVNnjqHaiqt8NdZ4el2FigGQPxlIR/fP4Evva7IcgKUFZkxCffvBO3eNlwRbRSlEwGiaPHENvfjVh3N6IvvrSg52VGR5d5ZhfHKhMRFVQ6EEDc58tu6NnjQ/zwYSix/Nv59C4XLF4vzN5mWLwtMO/cCV0xc+jo6oSTYXQHuvGS/yV0BjoxFB7SPK4X9WipbFGjWJrKm2DQrZ0OICIiIiJanOnUNA6MHECnvxNdwS4cmzgGWZGhk3UoSZegOlWNzdgMp+SELqpDJpUtGGeQwShmiztWq3XebHL9Gm32SUTTCAzl8soHwgiejkDOaGMWDCYd3LlNPavqHXDWlMBgLEzMwoVeGhrHfc/4cGo8+17zLbuq8OAtO1FWVLhiPtG1QE4mkfD5ENu/H7GubsQPHoQ8T83ncvSVlcswuwV+74J9ZyK65kjTUST6+rLF8lxneWZkJG+caLXC3NSU3dAzl1ducDE7mq5ePBPHweBBvBR4CZ3+ThydOApZmb2rQYCAHeU7ssVy93XY5dwFq8FawBkTERER0XKKpWM4OHJQ7Sw/MnYExowRjpQDJakStKXaUJGpgDmpjfRQoCCDDERRnDebvLi4eE13M09NJHLxK9kYlvHhKHBBJLGlxKjmlVfVO1C+oQiibnXdlTmVSOPRnx7Df+7LbtzqLjHjs29twmt28P0l0XKQpqcRP3gQse79iHV3I+HzQUmnNWPEkhJY9+yBtXUvLHv24PyH787WhubLPRcE6F0uWFv3rtAK8rF4TkTLQslkkOzvz3aT92Y7y5MDg/kvhjodTFu3Zjf0bPHC3NwMU11dwTaCoPUlLafRN9aX7Sz3d6JntAdpWfsXd429Bh3ubGd5q7sVdpO9QLMlIiIiouWWyCRwaPQQOv2d6D7fjbP+syhOFsOetqM0WYqb0zfDKM/fjWy1WufNJl+r3eQzFFnBRCCqbuzpHwhjaiKRN87hssJTN7O5px32Ssuq/oDgV8dG8MB3e+EPZ9fyjo7NuO8NDSgx805SoqWSmZhArLsb8VxneeLYsbzYXV1lBaytrbDubYW1rRWmrVshiLMftLk+9gDOf+ivAUHQ1oxyry+uB+4vaI1obb/CE9GqoCgKMsPDuc08s5t6Jg4fhpLIv+DSV3lyG3p6YfE2w9zYCNHKzl5aGrIi48TkCTW3fH9wP2IZ7S1h7iI3Otwd6PB0oN3dDlcRu06IiIiI1quUlMKhkUPYd3Ifjpw6gomxCdgSNtjTdtSka1CL2rznzO0mn1ssX+vd5DOkjIzRM7N55f7BEJJRbV65IAqo3FQMT50Dnq12eOocsJasjYiTiWgKn/7hYXzv0DAAoLrcikdua8Yf1FUUeGZEa196eBix7m61szw1NJQ3xrBpU7ZY3roX1tZWGDZvvuRrZ8lNNwFPPoHgw49oNg/Vu1xwPXB/9vECYvGciBZNikQQ7+1Forc311neC2lsLG+cWFycLZDnNvS0NDcXNKeK1h9FUXBm6oxaLO8KdGEyOakZ4zA50O5uR4cnWzDfbLv0X9xEREREtHZF41G81P8SeoZ6MOwfRjKchC1lg1E2wpX731xmqxlV7ipNobyiomLNd5PPlYpnsnnlg2EM94cQPBWBlNZ2huqNIlw1dnjqs3nlrpoSGM1r62egKAp+5PPjkz84jPFoCqIAvOcVNbj7tdthWSXZ60RriaIoSJ08iVhXt7rBZ2bYnzfOtHUrrG2tsOzNFcuvIHa35KabYHvNaxDr3o/M6Cj0lZWwtu5dFakEa+uVkIhWnJJKIXH8RDZ6JVcon++TRej1MG/frm7oaWnxwrhli+ZWHKKlMBIbUYvl+wL7EIgGNI9b9Ba0ulrVYvm20m0QBf45JCIiIlpPFEVBKBTCcGAYfSf7cOr8KUyNT0GX0EFAtlGiOPc/AFAEBWa7GRs9G1G7sVaTTb7eRMNJNYJleCCE8XPTeemZ5mKDGsFSVe9AxeZi6FZZXvliBCMJfOy7fXj+aBAAsN1lw2Nv82LXJkdhJ0a0hiiShMSxY4jPdJbv3w9pYkI7SKeDeedOtbPcsns39KWlS/L9BZ0ORR3tS3KupcTiORGpFEVB+uzZXPRKDxK+XiSOHIGSSuWNNWzaBEtzs7qpp3nHDohm8zxnJbo64WQYXYEutVh+MnxS87hBNKClsgXtnnZc57kOTRVNMIjMMSQiIiJaL5LJJEZGRhAMBhEIBHDy/ElMjE5AyWgrwvpciSOpS0JXooPT5URjdSOaaprWXTf5DEVREArG4B8Mw98fwvBgGJHReN64kgpzNqu8zo6qrQ44XNZ1cTemoij4dtdZfPYnRzGVyMCgE/D+G+rxvuvrYdSv3Q8DiFaCnEoh0dub6yzfj/iBA5CjUc0YwWSCpaVltlje0gKxqKhAMy6M9fc3BxEtmBQKIa5Gr/iQ8PVCmpzMGyfa7dlC+ZxNPfVlZQWYMV0LYukYDo0cwkuBl7DPvw9Hx49CwewbIwECGssbs53l7g7sdu2GRW8p4IyJiIiIaCnIsoxwOIxAIIBgMKh+TVzY+TgzHjIixghi5hgcFQ7Ub6pHx9YONG9oXrd3HsqSjNGz0+rGnv7BEOJTae0gASjfUIyq3MaenjoHiktNhZnwMjozHsN9z/rw+8FxAEDLJgcev92L7W5bgWdGtDpJ01HEDx1CrLsL8e79iPt8ec2Sos0Gy57d6gaf5qadEI1rY7+D5cLiOdE1Qk6lkDx6VM0oj/t6kD59Jm+cYDDAtGOHuqGnxeuFobp6XXQl0OqUltPoHe3FvkA2iqVntAcZWbthUa29Fu3ubGd5q7sVdpO9QLMlIiIioqUw001+YaE8Nc9drwAQ18URNoYRNoaRtCSxuWozdtfsRseG9R3Tl05KCJwMqzEsgZMRZJKSZoxOL8JVU5KNYdnqgLvWDpNl/ZZ7JFnBN35/Cn/3s+OIpyWYDSLuee123PWKGuhEvm8lmpGZnER8/361szxx9CggXfD6UVEBay6r3Nq6F6Zt21ZFzvhqsn5fTYmuYYqiIHXqFBI+Xy6CxYfEsWNAOp031lhdDXOLF5bcpp6mhoZr/lNFWl6yIuPE5Ans8+/DS/6XsD+4H/GM9tZSd5EbHe4ONbfcaXUWaLZEREREdDVkWUYoFFKL4zPF8sl57ngFAFmQETFEEDKGEDFGEDaGkbKk0LShCR3uDrS729FQ1gCduD6LO/GpFPwDYQwPhuDvD2H07DQUWRtPY7Lq1bxyT70Dzs026Azr88ODC/UHp/DRZ3w4eCYEALiutgyP3ubFloprK0aCaD5pvz+bVd6d3eAzNTCYN8awcWO2WJ7b4NO4ZQubJS+DxXOidSAzMYF4Tw8SMxEsfX2Qw+G8cbrSUli83tlNPZuboHM4Vn7CdE1RFAVnps6oxfKuQBdCyZBmTKmpFG3uNnR4OnCd5zpssm3iX+BEREREa0wymdR0kQcCAYyMjFy0m1w2yggZQhjVj6pd5VOGKZgNZuyq3IWbPTejzd2GxvLGdbmnjaIoiIwlchEsIQwPhBEKxvLGFZeacht7ZgvmZZ4iCNdYh3UqI+MrvxnEF385gJQkw2bS4/6bd+CP2zZBvMZ+FkRArmny5CnE9nerG3ymz5/PG2faWg/L3r2wtrbB2roXBre7ALNd21g8J1pj5EQCiSNHst3kuc7y9LlzeeMEkwnmxkZYvM0we73Z+JWNG1mQpBURjAbRGejES/6X0BnoRCAa0Dxu1Vux17VXLZZvLd26bm+1JSIiIlpvZrrJL4xcuVg3uagTYSoxYdo8jVPyKZwXzmc7ynXZorpRNGKXcxfe7H4z2t3taK5ohkG3/orlsqxg/PxsXvnwQAixcP4HC2VVRZrNPW1l5gLMdvXwnQvho0/7cCwwBQB4TYMTD721CR479z2ia4ciSUgePz6ns3w/pPFx7SCdDubGxtnO8j17oC8tLcyE1xEWz4lWMUWWkRoaykWv9CDh60XixAkgk8kba6yry27q2eKFudkL8/ZtEAzr74KTVqdwMoyuQBde8mc3+TwVOaV53CAa0FLZohbLd1bsXJfdQ0RERETrTSKRyMsmv1Q3uc1mg6PCgZQ1hWFhGL2JXgxlhqAIs9EjBtEAb6UX7e52tLnb4K30wqRbfxtaZlISgqcial65fyiMdEKbNyzqBDirbWoEi6fODnMRr5MBIJGW8I//cwL/8rshyApQVmTEg7c04s0tVWwKo3VPTqWQ6OvLFcu7ED9wEPL0tGaMYDTC0tICS2sus3zXLohFjDBaaiyeE60imdFRxH2+3KaePiR6+/JeHIHshg6WXDe5xdsMc3MzdDbuKE4rJ5aO4eDIQezz78O+wD4cHT8KBbNviAQIaCxvVDPLdzt3w6JnZwgRERHRaiXLMiYnJ/OyyUOh0LzjdTodnE4nXC4XisqKMKobxfH0cfxi4hc4O3UWmJM+ohf1aKpoQpu7De2edrRUtqzLa8NENA3/YFiNYRk5PQVZ0uaVG8w6eGpn8srtcG0pgd64PvPbr8a+oXHc92wvTo5FAQBvbqnCg7c0orx4/X3IQgQAcjSK2KFD6gafcZ8PSjKpGSMWFcGydw+se1thbWuFuamJe9atABbPiQpEjsWQOHw4WyzPbeqZ8fvzxgkWC8w7G7MZ5d5mWLxe6D0eftJOKyotpdE71qvmlvvGfMjI2jsgau21arG81dUKu8leoNkSERER0aUkEol5s8nT6fS84202G9xuN1wuF1wuF0wOEwZTg+ga6cKPAj/CqZOnNON1gg6N5Y3ZYrm7Hbudu2E1WFdgZStraiKB4f6QWjCfGI7mjbGWGLN55Vvt8NQ5UL6xmBndlzCVSOOx547hmy+dAQC4Skz47K3NuLHRVeCZES2tzOQk4gcOqDEsiSNHAEl7Z4qurCzbUZ7rLDdt3w5Bxw/bVhqL50QrQJEkJAcG1eiVuM+HZH8/IMvagYIAU309zC1eWJq9sLR4Yaqvh6Dnf6q0smRFxvGJ49lieeAlHAgeQDwT14zxFHnUYnm7ux1Oq7NAsyUiIiKi+cx0k1+YTb6QbvK5xfKkmER3sBv7/PvQNdiFwfCg5nkCBOwo34E2V7azfI9zD4qNxSuwwpWjyAom/FF1Y0//QAjTk8m8cQ6XFZ56O6pyneUlFRY2Pi3Qr46N4GPf7cVwOAEA+JP2Tbj/5h0oMTPGhta+dCCQLZTnNvhM9g/kjTFUVWWzynMbfBprtvD1YxVgRY5oGaQDAcR7fEj05iJYDh+GEsvfNV3vcsHi9cLsbYbF2wLzzp3QFTOfilaeoig4HTmtxrB0BboQSoY0Y0pNpWj3tGcL5u4ObLJt4l/kRERERKtEPB6fN5v8Yt3kJSUlanF8plBeVlYGnU6HcDKM/cH9+E7gO+js7cSJyRN5z99eul3tLN/r3osSY8lyL3FFSWkZI2em1AgW/2AYyZj2zktBFFC5qRierQ5U1TngrrPDWsIIhcWajKbw6R8dwXcPngcAbC6z4tHbmvEH9RUFnhnRlVEUBalTp7IRLLnO8vS5c3njjHV1s53le/fCUFVVgNnS5bB4TnSVpOkoEn19ufiVbGd5ZmQkb5xotcLc1JTd0DOXV25w8dYzKpxgNIh9gX3Zgrl/H4KxoOZxq96KVncrOtzZ7vKtpVshCmKBZktEREREQLabfGJiIi+bPBwOzzter9er3eRzv6zW2RiV6dQ09gf3o/NAJ7oCXTg2cUyznw0A1Dvq1WJ5q6sVDrNjOZe54pLxDAJDYfhzMSzBUxFIae2dwnqjCPecvHJ3jR0GEyMUrpSiKPhxrx8Pfv8wxqMpiAJw18trcM9N22FhDjytIYokIXnihFooj+3fD2lsTDtIFGHesQPW1tbsBp9790JfVlaYCdOisHhOtAhKJoNkf3+2m9yX7SxPDgwCivbCEjodTFu3Zjf0bPHC3NwMU10ds6mooMLJMDoDnWqx/FTklOZxg2jALucutVi+s2InDCJvkSQiIiIqlHg8Pm82eSaTmXd8SUmJJm7F5XKhvLwcoqhtgIilY3jh/AvoDHSiy9+FIxNHICvaQvGWki1od7ejzdOGNlcbyi3ly7bOQoiGkhgeCME/EIZ/MITxc9N5b+ssNgM8ddlCuafegYpNxdDp2EyyFIKRBP72e334+ZFsA882VzEeu92L3ZtLCzwzostTUinEDx/OFsq7uxE/cBDy1JRmjGA0wuxtznaW722FZfcu6IrXV5zVtYLFc6KLUBQFmeHhbEd5jw/x3l4kDh+GkkjkjdVXeXIbenph8TbD3NgI0br+NsShtSWWjuHAyAF0+jvxkv+lvA4iURDRWNaYzSz3ZDdysugtBZwxERER0bVpppv8wmzyhXSTzy2WWyzzX8vFM3EcGjmErkAXOgOdODx2GBlFW4DfbNuMNneb+rWe9rNRFAWhYEyzuWdkLP99XUmlBVV1dni2OuCps8PhsjKmcIkpioLvdJ/FQz8+iqlEBnpRwPtvqMf7bqiDSc9mM1qd5FgM8UOHcpnl+xHv6cmrDYlFRbDs3q3GsJibmyGaTAWaMS0lFs+JcqRIJFsg7+1Vi+V5t9kAEIuLswXy3IaeluZm6CsrCzBjIq20lIZvzKcWy31jPmRk7ZuiOnudWixvc7etu2xKIiIiotVuppv8wmzyi3WT2+32ebPJL+wmnyspJeEb9aEz0IlOf+e814UbijeoMSxt7ja4i9xLus5CkiQZY2emc53l2YJ5Ylqb/S4IQPnGYnjqHdnNPevsKHKw0LWczk7EcP+zvXhhIPs+27vRjsff5kWDm+9JaHWRQiHEDhxQY1gSR44AF7xG60pLs1nlra2w7G2FuWE7BD3LrOsRf6t0TVJSKSSOn0C814dELoIldfJk/kC9Hubt29UNPS0tXhi3bIFwiQtVopUiKzKOTRzLFssDL+FA8ADimbhmjKfIk93gM7fJZ6WVH/QQERERrQRJkubNJo9EIvOO1+v1ebnkl+omn0ttoghkM8t7RnqQklOaMS6rSy2Ut3vasaF4w5KsczVIJTIInoyoMSzBk2FkUtoYGp1BhGtLCTz1dlTVO+CutcNoYUlkJUiygn/7/Sl87mfHEU9LMOlF3HPTNtz18hroGYNDq0A6OIJYd1d2g8+ubiT7+/PG6D2eXFd5trPcWFvLO1OuEfybgtY9RVGQPnsWcV9vdkPPHh8SR49CSaXyxho2bYKluVnd1NO8YwdEs7kAsybKpygKTkdOZzPLA/vQGehEOKm9lbfUVIp2Tzs6PB24zn0dNto28i90IiIiomUWi8XysslHR0cv2U1+YTb55brJ50rLaRweO6zGsBwaOYSEpI0QqLBUqJ3l7e52bLJtWjfXhbFICv7BEPz92bzy0bPTUGRtYLnJqlc39qyqd6Bysw06PQu1K60/OIV7n/HhwJkQAKCjpgyP3e7Floqiwk6MrlmKoiB95kwurzwbw5I+cyZvnLG2Fta9e2Fta4V1714YNqyfDxxpcVg8p3UnMzmJRF9fLnrFh4SvF9LkZN440W7PFsrnbOrJnY5ptQlGg9gX2Kdu8hmMBTWPFxmK0OpqRbs7WzDfWroVosA3BURERETLYaab/MJs8ot1kxsMhnmzyc2LbNDJyJnsHYeBTnQGOnEweBCxTEwzpsxcpl4XtnnaUFNSsy6K5YqiIDwaz27smYtgCQVjeeNsZWZ1Y09PvR1l7iII4tpf/1qVlmR85deD+MIvB5CSZBSb9Lj/5gb8SdtmiPy90ApSZBnJ/n7EuroR25/d4FMavSCiVxRhbmiAJRfDYt27F/ry9bVJMl05Fs9pTZNTKSSPHlUzyuO+HqRP539iKBgMMO3YoW7oafF6YaiuXhcXk7S+hBIhdAW71GL5qcgpzeMG0YBdzl3ocGejWHZW7IRBNBRmskRERETr2Ew3+dxC+aW6yR0OR142eWlp6YK7yeeSFRnHJ46rMSz7g/sxnZ7WjLGb7GhzzW7wWe+oXxfvb2RZwfi5OXnlA2HEIhfcNSwA5VVF8NQ54Nlqh6fOAVsZ7xheLXrPhfE3T/fgWGAKAHDD9kp89q3NqHJcPoKI6GopqRQSR47MdpYfOAD5gg84BYMBZq9X7Sy37N4NXXFxgWZMqx2L57RmKLKM1OnTSPh8uQgWHxLHjgHpdN5YY3U1zC1eWHKbepoaGiAajQWYNdGlxdIxHBg5oBbLj00cg4LZW05FQURjWaOaW77buRtmPd8YEBERES0VSZIwPj6el00+NTU173iDwTBvNvliu8nnkhUZ/ZP9agzL/uB+RFLaYo/NYMNe9141hmW93HGYSUkInozAPxjC8EAYgaEw0glJM0bUC3BVl6id5e5aO8xFbCBZbRJpCU88349/+d0QJFlBqdWAB2/ZibfsqloXH+zQ6iTH44j39OQ6y/cjfugQlIQ2xkqwWmHdvVvd4NPs9UI0cYNgWhgWz2nVykxMIN7Tky2S+3oR7+3N+7QQyO5wbPF6Zzf1bG6CzuFY+QkTLcDMZk4zxXLfmA8ZWdu9VGevU4vlre5WlBi5+zwRERHRUohGo/Nmk0uSNO94h8ORl01+pd3kcymKgqHwkNpZ3h3oxmRSGzVZZCjCHuceNYalobQBOlF3Vd93NUhMp7N55QNhDA+EMHpmCrKkzSs3mnVw183mlTu32KA3rP21r2edJydw7zM+nByLAgBuaanCg7c0oqKYBUpaWlI4jNiBA4h1dyPevR/xw4eBC+4I0jkc2QiWvdkNPs07GiDoWQKlK8M/ObQqyIkEEkeO5ArlPsR7fEifP583TjCZYG5shMXbDLPXm41f2cgNEWn1khUZxyaOqcXyAyMHEM/ENWOqiqrUYnmHpwMVlooCzZaIiIhofZjpJr8wm3wh3eQzxXKn03lV3eRzzWz8PlMs7wp0YTwxrhlj0Vuw27lb3eSzsbwRenFtv2VXFAVT4wn4B8O5GJYwJv3RvHFFdiM8Wx3w1DlQtdWOsqpi5mKvEdPJDB776TH8x0unAQCuEhMeurUZr210FXhmtF6kR0YQ379f7SxPnjgBKNoP3PRudzarPNdZbqythXCVH3ISzVjbfxPTmqTIMlJDQ7nolWxnefJEf94nhQBgrKvLburZ4oW52Qvz9m0QDLw9j1YvRVFwKnJKLZZ3BbsQToY1Y8rMZeoGnx2eDmws5gdARERERFdqppv8wmzyi3WTl5aW5hXKHQ7HVXeTz6UoCs5Nn1NjWLr8XRiJj2jGmHQm7HLuQpurDe2edjSVN8GgW9vvdRRZwfhwNJdVnt3cc3oymTeu1G1VN/asqnfAVm7m9fAa9KvjI/jYs70YDmcjMv64bRPuv3kH7Ja1/eeYCkdRFKTPns1mlXdnN/icb18745YtsLZlu8ote1th2MBoIFo+LJ7TskuPjCDR25vd1NPnQ6KvD/L0dN44XUVFbkPP7Kae5uZm6Gy2AsyYaHEC0QD2+fehM9CJl/wvYSSmfWNUZChCq6tVLZbXO+rXRT4lERER0ULJsozTp09jenoaxcXFqK6uXnSxWpIkjI2N5WWTT8/z3gIAjEbjvNnkpmXKufVP+9EZ6FS7y/1Rv+Zxg2hAS2VLNobF3QZvpRdG3drel0lKywiejqgbewaGwkjGtE1RoiigstoGT102r9xTZ4fFtrbXfa2bjKbwmR8dwbMHs3eLbyqz4NHbvHh5Pe+gpcVRZBnJ/gHE9ncjntvgMzOifT8NQYCpoSHbWb53L6yte6Gv4J81WjksntOSkmMxJA4fRnzOpp4Zvz9vnGCxwLyzMZtR7m2GxeuF3uPhJ4W0JoQSIXQGOtWC+anIKc3jRtGIXc5darF8Z/nONX/LLREREdGVOnLkCJ577jlE5uxfVFJSgte//vVobGyc9znT09PzZpPLsjzv+NLS0rxs8qXuJr9QMBrUxLCcmz6neVwv6NFc2azGsLRUtqz5jd//f/buPbyN+z4T/TszuA0AkiAAXgGQkngVJVEXUpLjOKljO4nbNGniuMnZ3dOm7e62p9t223q3sZM2aW51HLcnze62u027u22z5/Rs0yTNpWmd1HbujiWRulAiRYqkKBIErwAIkgBmcJn5nT8GHHAEgKJlkuDl+3kePqSBGXIgyeDgxXfeXyqZwez4svYxFsPCnVUoWePfickqoOFIZW6y3IW6Q5UwW6mvfD9gjOGfbszho1+7gXA8DY4DfumNh/Ef3tYOu4Ve75B7Y5kM5KGh/GT55ctQl41XasNshnjihBaUn+2FePo0DVaSsqJnt22gqgpCNwcRjy3B6aqG7+gx8PtgYZe7MUVBamwc0sA1bUHPgQGkRkeBu09oOQ7W1lbYTnZDPNEN8WQ3rK2ttFgD2TOSmST65/v1sHw4OgyGfMcaz/E45jmmh+Wnak7t+RdGhBBCCCFbYWhoCF/84hcLbl9ZWcEXv/hFPPnkk6ipqSnoJt/MNPn6bvLtmiZfLyyF8zUsc5cwuTJpuF/gBBzzHNPD8lO1p2A327f9uLZTfCmlV7DMjC0jMhMHjFXDECvMaMwF5Q2tVfD6neAFuspyv1lYkfGRr93AtwbnAQBttU585slunGmqLvORkd1MlSRI1waQ7O/TFvi8eg1MMq4BxtntsJ86CbE3V8PS3Q1+i9abIGQrUHq5xUYvvIKX/+rPEY+G9ducbi8e+YVfRtv5B8t4ZK9fZm4O0rUByNe1BT2lwUGwZLJgO1NdHcTubti6T0DsPgnbsWMQnI4yHDEh9yejZHBt8RouzF3AxdmLGFgcQJYZLz9tdbXifMN5nKs/h976XlRaKst0tIQQQgghu5OqqnjhhRc23OZLX/pSyfvcbnfRbvKdulp1SV4yhOW3l28b7uc5HkfdR3G2/izO1p9FT10PHOa9+7qHMYaluaRewTIzFsNqRC7YrqpGzC3uqfWVV9WKdAXxPsYYw9/1T+NT/zCEFTkLE8/h3z3cgl97pBVW0/4bEiSvj7KyguTly/oCn9LgIJDJGLYRqqog9vToC3zajh6lte3Irkbh+RYavfAKvv7ZZwtuj0fD+Ppnn8W7nvrwngnQlXgc8o0b+qKe8sD1wt4pALzdDtuJE1pHea6v3FxHq2qTvUVRFQwvDePirFbFcnnhMqSs8d1wn9Onh+XnG87DK1LHGiGEEELIRiYnJw1VLaWYzWY0NDQYKld2app8veXUMvrm+/TAfHRp1HA/Bw4d7g59svxM3Zk9PUChZFUsTq1idmwZs+NaYC4njCEXxwHeQAUaWqvQ0KJNljuqdvbvhZRPMJrEh//+On4wqg0HnvBV4fknu3G0Ye/+uydbK7u4iGR/v17DkhoZAZjx8hRTXZ0elNt7e2FpaQG3jZVahGw1Cs+3iKoqePmv/nzDbb7z13+OlrPnd12FC8tmkbp1S+8ol68PIDU2XvCEB0GAtb0d4okTEE92w3biBKwtLeCE3fV4CLkXxhgmVib0sPzi3EWspI0v7Nw2N87Xn8e5Bi0sD1QEynS0hBBCCCF7U6nqlbu9853vRHd39zYfTaHV9Cr65/txce4i+ub6Cqr5AO1qw3P15/SrDausVTt+nFslLWcxd3tZC8vHYpifWEE2c1dfuZlH3eFKvYKl/kgVLDaKDQ4aRWX4wo/v4A+/NYJkWoHVxOOpt7bjXz90GCaq5DmwGGPIhEJIXurTFvi81If05GTBdpbmZohne2Hv6YX9bC/MPh9dnUL2NPotuEVCNwcNVS3FrEbCCN0cRODYzp8YrtGe7Gby1SvXr0MeHASTCy/HMzc26tPkYvcJ2Lq6wNv3dmcfObjmEnO4MHtB/1iQjFdSOMwOnK07q4flba42+gVPCCGEEPI6OJ3OTW1XsUMLwSUyCVyev6xPlt+M3oTKjOHx4arDOFd/Dmfrz6K3rhce0bMjx7YdEsspw1R5OLhaMB9ldZjQ0OLKdZZXoaapAoKJwtGDbGxhFU9/+Tr6J5cAAOcOu/GZ93bjsHfvVhKR+8NUFenxcW1hz9xkeXZ+3rgRx8Ha0ZGfLO/pgammpjwHTMg2ofB8i8RjS5va7uuf/TTqW9rg8Tet+wjAat+eX0TKyooWkA8M6JPlSiRSsB3vdBqqV8QTJ+gJj+xpax2VF2Yv4MLchYIFnSy8BadrT+th+THPMZh4ekokhBBCCNkqzc3NqKys3LC6pbKyEs3Nzdvy86WshCsLV/SwfDA8CIUpxmOsbEZvXa8emNfY9+ZrIMYYlhckzIzFMDu+jNnRGJYXpYLtKjw2PShvaHGhut4OjqeBEQJkFBWf/944/vNLY0grKpxWE575yU78y3NN4OnfyIHAslnIN2/mJsv7IfX1QVleNm5kNkM8dgz2s71ab/mZMxAqqcaH7G+UFG0Rp2tzK0zL8VXcuXYZd65dNu7v8cKbC9I9/ubc56bXFKqzdBryyC29o1waGEB6YqJwQ5MJto6OXPVKN8ST3bAcOkSdU2RPS2aS6J/v18PykeiI4bJbnuNx3HNcD8tP1ZyCzUQreBNCCCGEbBee5/H444/ji1/8YsltHn/8cfBb9DokpaRwbeGavsDnQHgAWdW46LvP6dOD8rP1Z1HvqN+Sn73TVEVFeDquV7DMjC9DWkkbN+IAT6MTja1Veg2Ls5rOf0mhG6FlfPBLAxia1d7oerijBs++5wQaXWKZj4xsJ1WWIQ0MINnXB6mvH8mrV8GSScM2nChCPHVSmyzv6YV4shu8SP8uyMFC4fkW8R09Bqfbu2F1i9PtwU/9xu9gaXYakeAUwtNTiE5PIb4URTwSRjwSLgzV3R54/E3wBprg9mmfPf4mWEQ7MsFgrnplAPK1Acg3b4Kl0wU/1xwI5KtXurthO3oUvI1OmsjellEyuLZ4DRfmtBqW64vXkWXGF0etrlacbziP8/Xn0VvfiwrLzlwSTAghhBBCNF1dXXjf+96HF154wTCBXllZiccffxxdXV33/b3TShoDiwP6ZPnA4gDSqvH1UL2jXg/Lz9WfQ6Oz8b5/Xjll0grmJ1YwOxbD7FgMc7dXkEkZp+h5E4e6Q7m+8pYqNLRUwWo3l+mIyV4gZxT8p5dG8effvw1FZXDZzfj9d3bh3aeoo3o/UlZXIV25kp8sv34dyBgXCearqmA/c0avYbF1dYEz0/MIOdgoPN8iPC/gkV/4ZXz9s8+W3OaRX/gVBLqOI9B13HC7HI8jEgoiMj2JyHQQkekpRIKTWqgejSAejWBy4IphH1tWgVNKwSmn4ZTTqJDTcGazsFZV6bUra4t6mtzubXnMhOwkRVUwvDSsd5ZfWbgCKWu8FNXn9Olh+bmGc/CK3jIdLSGEEEIIWdPV1YXOzk5MTk4iHo/D6XSiubn5NU+cZ9QMBsODuDh3ERfnLuLawjXIinHtphqxRg/Kz9Wfg7/CvydDQCme1qfKZ8eXsTi5ClU1FpZbRJMWkucmy2ubK2AyC2U6YrLXXLoTxdNfGsDtcAIA8I7uBnz8XcfgdVrLfGRkq2QjEb2rPNnfh9TwCKDetUhwTY1WwZKbLLe2tVIrASF3ofB8C7WdfxDveurDePmvPo94NN8rXuHx4i0f+GW0nX+w6H42pxO+jqPwdRwFAKipFFI3byLW34+Fq5cRvjOOWCKOuM2CuNUC2WKCbBIgV9gRrjAu4OmodsMbqIOn0gpPVoJnYQ4eqwU2x+YW6yFkt2CMYWJlQg/LL81dwkra2Jfptrlxvv68Fpg3nIe/wl+moyWEEEIIIRthYAiLYSyyRdSINWhC0z33yapZ3Izc1GtYLi9cLhiecNvcelh+tv4sDlUe2nNhOWMMqxFZq1/JBeZLc8mC7Rwu67oKFhc8jQ7qKyevWTyVxfMvDOMLP9bWhKqtsOKT7z6Otx/bmxVGRMMYQyY0A6m/T1/gs1iNr7m5CfaeXn2y3BwI7LnnTEJ2GoXnW6xuOY633JzCwmoMKbMJ1kwWtfMJ1C3Hi27PVBXpO5OQrw/kKliuQx4e1i+dsQBozH1Ymptha+uGcPQopLoarJg4LM3NIBycQiQURDwSRmIpisRStGBS3VHt1upfDAuVNsHmpFCd7B5ziTm8OvsqLsxewMXZi1iQFgz3O81O9Nb16mF5q6uVftETQgghhOxyL06+iOcuPof55Lx+W529Ds+cewaPNT+m36aoCkaWRvQalsvzlxHPGF9Huawuva/8bN1ZtLha9tz5oKoyRGe0vvKZsRhmx5aRiKUKtqtucKChtUpb4LOlChUe2557rGR3+d6tRXz4K9cRimlvQr2/N4APv+MoqkSq5dhrGGNIj4+vmyzvR3Z21rgRx8Ha3g57T482XX6mB+a62vIcMCF7GMcYY/febP9YWVlBVVUVlpeXUbnFKwKvfPvbCP3mbwF3/5HmTnB8/+lzsPf0QBoYgDQwoC3qef061CKrzwvV1RC7u2E72Q3xRDfEE8chuFwb/vxUMpGvfcl9hKenEI+U7mF3VLvh8QXgCTTB62+G2x+A199MoTrZEUvyEi7OXdTC8rmLmFyZNNxv4S04XXtaD8u7PF0w8fSeHyGEvFbbef5DCNn7tvM54sXJF/HUd58yLOQOABy010j/ofc/gOd4XJy7iP75fqymVw3bVVgq0FvXq0+Wt1W3gef2VqVANqNg4c6qHpTP3V5GWjKu1cPzHGqaK9DQ6kJjaxXqW6ogOi1lOmKy38SSaXziH4bwlcshAIC/WsRzT3TjoTaqudwrWDYL+eYwkrnJcqn/MpSlJeNGJhPEY8cg9vZok+VnzkCoqirPAROyB2z2/IfC8y3CFAVjjz6G7Nxc6Y0EAVCUgps5qxW2ri59QU/x5EmYfVu3QEcqmdTC9NAUIrkp9UhwCquRxZL7OFzVhgl1T26hUtFJCy6S+5fMJNE336eH5cPRYcP9PMfjuOe4HpafrDkJm4kWtyWEkNeLwnNCyEa26zlCURW8/ctvN0yc34vD7EBPXY8elndUd0Dg91aPt5zIYO52rq98bBnzkytQs8aX3WargPrcop6NrS7UHq6E2bK3HifZG/7x+iw++rUbCMfT4DjgFx88jP/49nbYLTSUtJupqRTkgQEk+/uRvNQH6coVqEljnRNns0E8dSo/Wd7dDd5uL/EdCSF32+z5Dz1bbpFkX//GwTmgB+eWlpb8gp7d3bC1t2/r6sVWux2N7Z1obO803J5KJhENBRFev1Dp9BRWw4tIxJaQiC1h6sY1wz5aqB6Ax9+c+5wL1SvohTgplFbSuLZ4TQ/Lry9eR5YZp2xaXa14oOEBnG84j566HlRY6A0aQgghhJD94PLC5U0F58c9x/FY82M4V38ORz1H99yVhqtRGbPjMcyOLmN2PIbITAJ3DdpDrLTofeWNrS54fA7wwt6aoCd7y8KKjI9+bRAvDGo5RWutE595bzd6mqvLfGSkGCUeh3TlCpKXtAoWeWAALFfnu4avrIT9zBnYc5Pltq4ucBa6QoWQ7ba3zkp2sexi6Snu9eo/9UlUP/nkNh/N5ljtdjS0daChrcNwe1pK6tPp4ekpRHP1L8ZQfcCwj73KBW+gCW5fE7yBJnh82rQ6heoHi6IqGI4O49XZV/WeSlmRDdv4nD480PAAztWfw7mGc/CKdKkgIYQQQsh+tJjc3Gukn+v6OfzUkZ/a5qPZGkxliM4lMDuWnyxfjcoF27nq7GhoWVvcswpVNSL1lZMdwRjDl/qn8cl/GMKKnIWJ5/CrD7fg1x9phdVEVzfsFtloNLewZx+kvn5t7TtVNWwj1Hi1+pWeXtjP9sLa1gaOpzfdCNlpFJ5vEVNNzaa2swTuvap8uVlEOxpaO9DQWiJUv6tXfWVxAcnlGKaWY0VDdW06XZtW9/qb4PYHYK+k3q39gDGGieUJXJi7gAuzF3Bp7hJW0sYOf4/Ng3MN5/TA3F/hL9PREkIIIYSQnVRj39xrpM1uVw5KVsXiVL6vfHY8hlTCeCUlx3OoCTjR0OJCQ1sVGlpcsFfSNCjZecFoEh/+++v4wai27tkJXxU+895udDXSUFu5ZUIhrYIlt8Bn+vbtgm3MgYAWlucmy81NTfSmGyG7AIXnW8Te2wNTfT2y8/OFC4YCAMfBVFcHe2/Pzh/cFtkoVI+GphFeF6hHpoNYWZxHcjmG5HIMwcEioXpuodK1KXWPv4lC9T1gNj6rT5ZfnL2IBWnBcL/T7ERvfa8elre6WukXPiGEEELIAXSm9gzq7HVYSC4ULBgKaIuG1tnrcKb2TBmOrri0lNX6yseXMTMaw/ydFSgZ4zSoycKj7nAVGlq1vvK6w5Ww2OilNSkfVWX4wo/v4PlvjSCZVmA18fjtt7bj3zx0GCaqB9pxjDGkb9/Wg/Jkfx+yM7MF21nb2rSu8p5cWF5XV4ajJYTcC/2G3yKcIKDuwx9C6Dd/C+A4Y4CeCw7rPvwhcML+u0zKItpR39qO+tZ2w+1pWUI0NI3I9BTCwUmtXz04ZQzVh64b9hErq3LT6U3wrk2sB5opVC+jJXkJF+cu4sKsNl0+tTpluN/CW3C67jTO12uLfHZ5uvZcTyUhhBBCCNl6Ai/gmXPP4KnvPgUOnCFA56C9Rnr63NNlXRA0sZzSK1hmxmKITMcLZqFsTrNewdLY6oK3yQmBAkmyS4wtxPHMlwfQN7kEADh3yI3n3nsCR2qcZT6yg4MpCuThYUi5GpZk/2Uo0ahxI0GA7dgxfbJcPH0apmrqnydkL+AYKzYmvX9t10ry+vf/9rcx/+ynDYuHmurrUffhD6HybW/b8p+3F2VkOVf/MmX4WF4ovZiQWFGZm07XFir15hYqtVe5du7AD4hEJoH++X49LB9ZGjHcL3ACjnmP6WH5qdpTsArWMh0tIYSQzdju8x9CyN623c8RL06+iOcuPmdYPLTeXo+nzz2Nx5of2/KfVwpjDLH5JGbHlzE7GsPM+DJWFqWC7Sq9Nq2rvKUKjW0uuOrsdCUl2XUyioo///5t/KcXR5FWVDgsAp75yU78q/PN4Hn697qd1FQK8vXr+mS5dOUK1ETCsA1ntUI8eTIflp88Cd7hKNMRE0KK2ez5D4Xn24ApCpJ9/cguLsJUUwN7b8++nDjfahlZRnRmGuHgZG7B0snNheq5IH2tAsYbaIJYWUUnuJuUVtK4tnhND8tvhG8gy4w9jm3VbXpY3lPXgwpLRZmOlhBCyP2g8JwQspGdeI5QVAWXFy5jMbmIGnsNztSe2faJc1VRsRiM6wt7zo7HIK1mjBtxgMfnRGNuYc+GFhec1TQYQna3G6FlfPBLAxia1dab+on2Gjz7xAn4XGKZj2x/UuIJSFeuINmvTZbLA9fB0mnDNnxFBcQzp/UFPm3Hj4G30NoHhOxmFJ6XQC8e9561UD0yPWXoVV9eKNEvD8BWUZmvfVkL13OT6gc9VFdUBcPRYbw6+youzF7AlYUrkBXZsI3f6cf5Bi0sP1t/Fl7RW6ajJYQQshXo/IcQspH98hyRSSmYm1jWa1jmJlaQTSmGbQQTj7rDlVoNS5sL9UeqYBWpcpDsDXJGwX9+aRSf//5tKCqDy27GR3+6C+857Tvwr3O3UnZpSZsoz02WyzdvAqpx7QPB64U911Vu7+2Btb2dhiYJ2WM2e/5DZwlk1zPbbKg70oq6I62G2zMpWe9UXwvWo9NBxBbmIK+uYPrmDUzfvGHYx1ZRCY8vAG+gCe7clPp+D9UZY5hYntDD8kvzl7CaXjVs47F5cK7hHB5oeADnG87D5/SV6WgJIYQQQgjZHGk1jdmxZcyMxzA7GsNiMA6mGodrrHaT3lfe0OpCbVMFBDP1lZO9p+9OFB/88gBuL2r1IO840YCPvesYairoSonXKzM7q3WV58Ly9Ph4wTZmv18Ly3MLfFoOHdq3GQIhxIjCc7Jnma0bhOozIWOnenBKD9VDw4MIDQ8a9rE5K3LT6YF8r3qgec+G6rPxWS0sn7uAi7MXsSgtGu53mp3ore/VwvL682hxtezJx0kIIYQQQvYGVWWYHY0hsZKCo9KKhjbXa+plZoxhJSznKlhimBlbRmw+WbCds9qaW9hTC8zdDQ5w1P9M9rBEKovnXxjGF16dBGNATYUVn/yZ43j8eH25D21PYowhPXEHyb5LkPr7kbzUh8zMTMF21rZWiD09sPeehb23B+Z6+vMm5KCi8JzsO2arDXWHW1B3uMVweyadQjQ0jahe/xJEZHoSsfk5yPHV4qG6w6l3qXsC+foXh6t6V4XNUTmKi3MX9d7y4GrQcL9VsOJU7Sk9LD/qOQoTT//7E0IIIYSQ7Td+ZQE/+NtRJGIp/TaHy4o3vb8NLadri+6jqgyRUL6vfGYshuRyumA7d6PDsLhnhdu2bY+DkJ32/VuL+NBXriMU0xa2fV+vH7/7U12ospvLfGR7B1MUpEZG8pPl/f1QIhHjRoIAW1dXfrL8zBmYqqvLc8CEkF2H0jNyYJgt1pKh+tJMSFugNBREODiFaGgKsbk5yIk4QsNDCA0PGfaxOZxw+5vW9apr0+qOaveOhOqJTAL98/14dfZVXJy9iJGlEcP9AifgmPcYztefxwMND+Bk7UlYBbqcjxBCCCGE7KzxKwt44fM3Cm5PxFJ44fM38PivHEfL6Vpk0woWJlcwM6ot7Dk3voy0bOwr5wUOtc0VegVLQ0sVbA4KEcn+E0um8alv3sSX+qcBAP5qEZ9+4gTe1FZT5iPb/dR0GvKNG0he6kOyvw/S5StQ43HDNpzFAvHkSYi9uc7yU6fAOxxlOmJCyG5H4Tk58MwWK2oPHUHtoSOG2/VQfX39y3Q+VJ8ZGcLMiDFUtzoc+doXf5MesL/eUD2tpHFt8Zoelt8I30CWZQ3btFW36WF5T10PnBbnff88QgghhBBCXi9VZfjB345uuM1Lf3UTV749hcWpVaiKsa/cbBPQcGStr7wKdYcqYbLQgnxkf3vhxix+76uDCMdT4DjgA284hN95ewccVopvilETCSSvXtUX+JQGBsBSKcM2vMMBsecM7D29sJ/the34cfAWS5mOmBCy19CzLyEllArVs+k0ojPTiISCiATXh+qzSCUSpUP1teoXvQImAGe1p2iorqgKbkZv6mH5lYUrkBXZsI3f6cf5Bi0sP1t/Fh7Rs/V/CIQQQgghhNyn2dGYoaqlmExKwfzECgDAXmnR+srbqtDQ4oLH73xNveiE7GULqzJ+/2uD+KcbcwCAlhoHnn+yGz3N7jIf2e6SXVqCdPlybrK8H/LQEKAYr1IR3G5tojw3WW7t6AAn0BtvhJD7Q+E5Ia+RyWIpGaovzYYQnp7SetWDU4iEgojNzWih+q2bmLl107CP1e6A2x+Ax98EeBwIWZdwAxN4dfUKVjOrhm09No8elp9rOAef07ftj5UQQgghhJD7lVjZODhfc+xNjTj9tiZUesVdta4QITuBMYYvXw7hk/8whGUpA4Hn8Ks/0YJff6QVNjMFvpm5Oa2rPLfAZ2p0rGAbc2Oj1lWeW+DTcvgQPZcQQrYMheeEbBGTxYKa5sOoaT5suD2byWBpNtepnluoNDw9pYXqyQRmbw1j9tawvr0PwDtNLqxWVMBS50ZjcyuOt5/D8c4HUOHx0kkAIYQQQgjZExyVm1tzp623DlU19m0+GkJ2n+mlJD789zfw/VuLAIBjjZV4/sluHGusKvORlQdjDOk7dyD19+uT5Znp6YLtLC0t+cnynh6YGxvLcLSEkIOCwnNCtpnJbEZN0yEItZW40yjhStNtXJidQigWRGXCDFdc+/DEbaiVHLCuqLBkeXiWeGBpFavDV/Djb13Bj/F5WES7YYHStV51CtUJIYQQQshu09DmgsNl3bC6xVltRUOba+cOipBdQFUZ/terk/jMC8NIphVYTDx++7F2/Ns3HYZJ4Mt9eDuGKQpSt27lJsu1sFwJh40b8TxsR4/C3turLfDZ0wOTm6psCCE7h8JzQrZJIpNA31wfLsxdwIXZC7i1dMtwv2AS0NzShfMN53G+/jxO1p6EVbAim8kglqt/iUwHEZmeRCQ4haW5GaSlJGZHRzA7OmL4XhZRXNelnv+gUJ0QQgghhJQLz3N40/vb8MLnb5Tc5qH3tVGvOTlQxhfjeObLA7h0ZwkAcPZQNZ57bzdaapxlPrLtx9JpSDcGkezv0xb4vHwF6qqxrpSzWGDrPqFNlvf0Qjx9CoJz///ZEEJ2LwrPCdkiKSWFgcUBvDr7Ki7MXsCN8A0ozLhwSXt1ux6W99T1wGkpPAkwmc3wNh2Ct+mQ4XYlm8HSTAiRUBDhYK5XPVf/kpYkzI6NYHaseKjuzk2pewLaxHqFp4ZCdUIIIYQQsu1aTtfi8V85jh/87ahhAt1ZbcVD72tDy+naMh4dITsno6j4ix/cxudeHEU6q8JhEfD0T3bi/zzfvG/fQFKTSUhXr+qT5dLAAJgsG7bhHQ6Ip0/rNSy2EyfAWzdX+UQIITuBwnNC7pOiKhiKDOmT5VcWriClGC9JDVQE9LD8bP1ZeETPff88wZQP1TvesO44shkszc7k+tSnEMktVLo0GyoZqpttYq7+RZtQ965NqnspVCeEEEIIIVur5XQtDp+swexoDImVFByVWlXLfg0MCbnb4MwyPvilAQzOrAAA3txeg2ffcxz+6v3V9a/EYkhevqyH5fLQEJDNGrYRqqu1rvLeXog9vbB1doAzUTRFCNm96BmKkE1ijOH28m19srxvrg+rGeMlZl7Ri3P15/BAwwM433Aejc7tX7hEMJnhDTTDG2g23K5kM4jNzSIcnMoH69NTWJoNISNLmBu7hbkxY5WMHqrrFTABeP3NWv0Lf3C69wghhBBCyNbieQ6+jupyHwYhO0rOKPgvL4/iz753G4rKUCWa8dGf7sITZ3z7YmgpMz+vTZTnFvhMjY4WbGNqbIC9p1efLLccObIvHjsh5OCg8JyQDczEZ3Bh9gJenX0VF+cuIiwZFy+pMFegt74X5xvO44GGB3CkavecCAgmsz5Zvp6SzSI2p02qh3NT6pHgJJZmZ0qH6labYVLdE2iCx9eESm8NheqEEHIfGFMQi11CKrUAq7UWLtdZcJxQ7sMihBBCyBbpn4zig18awPhiAgDwUyfq8fF3HUdNxd6sJGGMITM1pS3smZsszwSDBdtZjhyBvacH9rO9sPf0wOzzleFoCSFk61B4Tsg6ESmCS3OX9Ony6fi04X6rYMXp2tN6WH7UfRQCv7fCDsFk0kPw9gfyt2uh+qy2QOl0EOFprVc9OhNCJiVjbnwUc+PGSQKz1Qa3LwBvoCn3WetUr/TWUqhOCCElLCx8C7dGP4FUak6/zWqtR3vbR1Fb+/YyHhkhhBBCXq9EKos//NYI/vrHd8AY4HVa8al3H8PjxxvKfWivCVNVpEZHkbzUpy/wqSwah8nA87B1dkLM1bDYe3pg8tx/VSkhhOxGFJ6TAy2ejqN/vl8Ly+cuYHTJGA4LnIDj3uN6WH6y5iQsgqVMR7u9tFA9AI8/YLhdD9VDuT71XP3LWqg+f3sU87eLh+qGXvVAE4XqhJADb2HhW7h+49cAMMPtqdQ8rt/4NZw4/qcUoBNCCCF71A9GF/HMl68jFJMAAD/b48fvvaMLVXZzmY/s3lg6DXloKD9Zfvky1JUVwzac2Qxbd7c+WS6ePg3B6SzTERNCyM6g8JwcKCklhWsL1/QalhvhG1CYYtimvbpdD8t76nrgMDvKdLS7gyFUP/9G/XZVUbA0N4PodBDh6cn8QqUz0yVDdZPVCo9vXf1L7qOqhkJ1Qsj+x5iCW6OfwN3Bee5eABxujX4SNTWPUYULIYQQsocsJzP41DeH8Hf92pXLPpeITz9xAm9urynzkZWmShKka9dyk+X9kK5eBZNlwzac3Q776dP6Ap+27m7w1r1ZO0MIIfeLwnOyrymqgqHIEC7Mab3lVxeuIqWkDNsEKgI433Ae5xvO41z9Obht7jId7d7CC4IWhPsCaDv/oH67qiiIzc/qU+r5+pdpZFMpzN8ew/ztMcP3MlmscPv88Pqb4MlVv3j8zRSqE0L2NMYUyPIcJGkSkhzE0tKPDVUtRfZAKjWLWOwSqqsf2GA7QgghhOwWL9yYw0e+dgOLqylwHPCBNxzC77y9Aw7r7opblOVlJC9f1hb47OuHNDgIZLOGbQSXS6tgyS3waTvaCc60ux4HIYTsNHoWJPsKYwzjsXE9LO+f68dqZtWwjVf0amF5vRaYNzoby3S0+xMvCHA3+uFu9BcP1aen9Cn1SHBSC9XTKSxMjGNhYtzwvdZC9fVT6l5/E6pq6yhUJ4TsCoqShCQFIUlTuY8gJGkSSWkKshwCY5nX/D1TqYVtOFJCCCGEbKXF1RR+/+s38I/XtTfGj9Q48Px7u9F7aHcMY2UWFiD19+uT5albtwBmvPrNVF+vdZXnJsstR47Q6yxCCLkLhedkzwvFQ7gwewEXZi/g4txFhCXjIiYVlgqcrTurV7EcrjoMjuPKdLQHlyFUP3d3qD6nL1Sa71S/R6je6Icn0KRNv+em1atq68DvsQVcCSG7G2MM6UxEmx7XQ/L81+n04ob7c5wZouiHKDaB4ywIh//5nj/Taq3dqsMnhBBCyBZjjOErl0P4xD8MYVnKQOA5/F8/cQS/8UgbbObyvBZhjCETDGpd5X3aAp+ZyamC7SyHDsF+VpsqF3t6YfY10mtjQgi5BwrPyZ4TkSK4OHdRD8yn49OG+22CDadrT+tVLEfdRyFQoLpraaG6D+5GH9rO5W9XFQXLC3O52pcgwsFJY6h+ZxwLd+4K1c0WVK/Vv6x9BJooVCeEbEhV05Dl0F0T5LkPOQhFSW64v8lUBVFsgigGIIrNsItNsIkB2MVmWK11en85Ywp+9MqbkUrNo3jvOQertR4u19mtf5CEEEIIed1CMQkf/sp1fO+W9uZ5V0Mlnn+yG8d9VTt6HExVkRodQ7K/D1Jugc/swl1XrnEcrJ2d2mR5Tw/svT0web07epyEELIfUHhOdr14Oo6++T4tLJ+7gNEl4yKUAifghPeEHpafrDkJi2Ap09GSrcILAqobfKhu8AFn36DfrqoKlufnDFPq4ekpLIWmkc2ksXjnNhbv3DZ8r7VQ3eMLwBtozgXrAVTV1VOoTsgBkc2uIilNGqpV1r6W5RkA6gZ7c7BZG3IBeeGH2by5F8wcJ6C97aO4fuPfra0PmscAcAztbR+hxUIJIYSQXUZVGf7fC5N47p+GkUgrsJh4/OajbfjlNx+BWdj+mhOWyUAeGtKmyvv6kbx8GerysnEjsxniiRNaUH62F+Lp0xAqKrb92AghZL+j8JzsOiklhasLV/WwfDA8CIUphm06qjv0sLynrgcOs6NMR0t2Gs/nQ/XWs/kF9VRVwfLCvL5QqfYRRDQULBmqC2azVv+ybkrd42uCq55CdUL2GsZUpFJzd4Xj2iR5UppCNhvbcH+eF3OT4+uDcW163GZrBM9bt+Q4a8MpnBhcxa1WO1LW/POMNaWgfTyJ2voUQK0thBBCyK5xezGOZ758HRfvRAEAvc3VeO693WitdW7bz1QlCdK1Ab2CRbp6DUySDNtwdjvsp05C7M3VsHR3g7fZtu2YCCHkoKLwnJRdVs1iKDKEi3MX8ersq7i6cBUpJWXYpqmiCecbzuNcwzmcqz8Ht213LMJCdg+eF1Bd34jq+saCUH1lYQHh6XWhenAqH6pPTmBxcsLwvQpCdX8AHn8zXHX14AUK1QkpF0WRIclFqlWkKUjSNBhLb7i/xeKFaNOqVfI1K00QxWZYLN7t7/xUFeCFp1G7kkJNJIVYlRkpCwdrmsG1nAEHDnjhGaDzHQC9gUcIIYSUVVZR8Rc/mMAfv3gL6awKu0XA04934uceaAbPb+05g7KyguTly3oFizQ4CGSMi44LVVUQe3r0BT5tR4+CM5u39DgIIYQUovCc7DjGGMZiY3pY3jfXh3gmbtimRqzRwvL6c3ig4QE0OBvKdLRkr+N5Aa76BrjqG9Dae16/fS1Uj4SmEA5OIZqrf4mGtE71kqF6gw9uf5PWqx7QwnVXXQOF6oRsAcYYMplo0WoVSZpCKj2/4f4cZ4LN5jNMj2v9400QbQGYTGW+SmnyR8DKjHasAKqXM3dtwICVEDD5CnD4TTt+eIQQQgjRDM2s4INfvoYboRUAwJvavHj2PScQcNu35PtnFxeR7O9H8lIfkv39SI2MAMy4Hoqprk4Pyu29vbC0tIDjt78ihhBCiBGF52RHhOIhXJi9gFdnX8XF2YuIyBHD/RWWCpyrP6eH5YerDtOq32RbrQ/VW3ruCtUXFxGZntR61YOTiISCiEwHtVB96g4Wp+5gZN33EkwmVOuT6gF4/c1w+wOorm+kUJ2Qu6hqBrI8s26CfHLdQp1BKEp8w/0FwQm7PjlunB63WuvB87vs1CYZBcZf1j5ufmNz+8Q3fpOAEEIIIdsjlVXwX14aw599bxxZlaFKNOMjP92F957x3ffrU8YYMtPTWld53yVIff1IT04WbGdpboZ4thf2nl7Yz/bC7Lv/n0kIIWTr7LJXmGS/iEgRXJy7qAfmoXjIcL9NsOFM3Rk9LO90d0KgS9TJLsDzAlx19XDV1RtCdaaqWF5cWNennvsIBZFNpRCeuoPw1B3D99JDdV9An1L3+JsoVCf7XjYbL1GtEoScCoHdtY6FEQerta5ItYo2RW4yuXb3C0lVAUKXgbEXtY9QP7TVQF8DZ922HBohhBBCSuufXMLTXx7A2IL2Rv5PHq/Hx3/mGGorXluPOFNVpMbGIK2bLM/O3/XGOMfB2tGRnyzv6YGppmarHgohhJAtROE52RKr6VX0z/frYflYbMxwv4kz4UTNCZyrP4fzDedxsuYkLIKlTEdLyGvH8fy6UP2cfjtTVayEFxCZDiIcnNQXKo2Epoyh+o/z34sXTHA3+oosVNoAwURPy2T3Y0xFKr1QtFpFkqaQyUQ33J/nrVogbrt7gc4m2Gx+CMLWLM65Y1ZmgfGXgLGXtAlzOWa8v7YLaH0UOPww8PVfB1bnUDxQ54DKRqD5wW0/ZEIIIYRoEqks/ujbI/irV+6AMcDrtOKTP3MMP3lic9WhLJOBfPNmbrK8D1J/P5TlZeNGZjPEY8dgP9ur9ZafOQOhsnIbHg0hhJCtRikNuS8pJYWrC1dxYfYCLsxewGBkEMpdk4Sd7k49LO+p64HDXOauWUK2AcfzqKqtR1VtPY6cOavfroXqi4WT6tNBZFIywsFJhIPGyzV5wYTqhkZ4As1ap/raQqUUqpMyUJQUZHm6oFolKU1BloNQ1dSG+5vN7qLVKqIYgNVSC47bw52d2TQQfDU3Xf4SMH/DeL+1Cmh5GGh9DGh5FKjy5e/7yeeBL/48tNbz9QF6bpr+8edosVBCCCFkh/xwNIxnvjKA6SUJAPDeM3585KePwmUvPeilyjKkawNI9vdpC3xevQaWTBq24UQR4qmT2mR5Ty/Ek93gRXFbHwshhJDtQWkM2ZSsmsVQZEgPy68sXEFaTRu2aapowvmG8/pCn9W26jIdLSHlp4XqdaiqrSseqoemEAnmptRz/eqZlKyH7LfWfS89VPfnq1+8gSa46hspVCf3jTGGbDaGZJFqFUmaRCo1j43qRjhOgM3qKxqOi2IAJlPFzj2YnRCdyE+XT3wfSK/vZueAxtNaWN76KODrBYQS/292vQt43xeAF57WFw8FoE2cP/6cdj8hhBBCttWylMEffHMIX+ybBgD4XCKefeIEfqK9sDpFWV2FdPlyfrL8xg0gY1z0m6+qgv3MGb2GxdbVBc5s3pHHQgghZHtR6kKKYoxhLDamh+V9832IZ4yLuNWINXpYfr7+PBqcm7usjZCDzBCqnzaG6quRMML6QqVTWsA+HURGlvRQfT1eEFDd4NMXKvX4m+HxB1Dd0AjBRCfrBFDVLFKpuaLVKpI8hWx2dcP9BcFRUKuy1j1utTaA5/fxv7N0Erjzw3x3eXTceL+jRpsqb30MaHkL4PBu/nt3vQvofAcw+Yq2OKizTqtqoYlzQgghZNt9a3AOH/nqDSysalfRfeANzfidxzvhtGrxSDYc1oLyfi0sTw0PA8w4UGCqqdEqWHKT5da2VnD8Hr6qjhBCSEkUnhPd9Oq0HpZfmLuAqGzsrK2wVOg1LOcbzuNw5eHdvWgbIXsIx/OorKlFZU2tMVRnDKuRxdyU+hTC6+tfNgjVXfWNWvXL+oVKKVTfl7LZBCQ5aKhWWfuQ5RAYy264v9VSV2J6vAlms/vgPM8zBiyO5MPyyVcAZV01DW8CAue1yfLWx4C6E8DreZHMC8DhN73+4yaEEELIpiyupvCxrw/im9dnAQBHahz4zBMncNIsI/lP/4DZ3AKf6Tt3CvY1NzfB3tOrT5abA4GDc45ECCEHHIXnB1hYCuPi7EVcnLuIV2dfRSgeMtxvE2w4U3dGD8s7qzsh0FQcITuK4zhUemtR6a3F4dO9+u16qD4dRCQ4iUgoP62eliREQ0FEQ0Hgwo/0fdaH6u5c9YvHF0B1o49C9V2MMYZ0erFotUpSmkImE9lwf46z6FUqBVPkNj8E4QD3b0oxYOJ7+e7yFePvQVQF8mH54TcDtqqyHCYhhBBC7h9jDH9/JYRP/MMQYok0DiUW8KvVK3hDaBqpX/w4xufmjDtwHKzt7bD39GjT5Wd6YK6rLc/BE0IIKTsKzw+Q1fQq+ub6cGFOmy4fi40Z7jdxJpyoOaHXsHTXdMMilF4ohRBSPoZQ/VSPfrsWqoeLLFRaOlTneB7V9Y2GKXWvvwmuBh9M1NW4I1Q1BVmeQbJYvYoUhKpKG+5vMrlgNyzO2ax/bbXW7+3FObeSqgJz1/JhefAisH6xa8EKHHoo113+GOBtA2iqjBBCCNmzpsOr+JM//0ekLvfjNyITOLk0AYecAAAk1jYymSAeOwaxt0ebLD9zBkIVvWFOCCFEQ+H5PiZnZVxdvIoLsxdwcfYibkRuQGWqYZtOdyfO12uT5WfqzsBhdpTpaAkhW0EL1WtQ6a0pCNXj0Yg+pR4OTukLlaalJKIz04jOTGP0wiv577UWqq/Vv/gC8ASaUU2h+n3JZJaLVqtI0hTk1Cw2WpwT4GGzNRatVhFtTTCbK3fqYew98UVg/GUtMB9/GUiGjfd72/Pd5c0PAhZ7eY6TEEIIIa+bmkpBHhhA4lIfxl/+ISzDg/hANmXYhrPZIJ46lZ8s7+4Gb6ff/4QQQoqj8HwfyapZDEYG9bD8ysIVpNW0YZvmymY9LD9bfxbVtuoyHS0hZCdxHIcKjxcVHi8OFQvV102oh6enEAlOGUP1i8ZQXe9U9wfyneqN/gMdqjOmIJWav2t6PP91Nru84f6CYIdoK1KtIgZgs/nA83Ql0KYoWWD6Ur67fPaq8X6LEzjysFbH0vIoUN1cjqMkhBBCyBZQ4nFIV64geakPyf5+yAMDYJkMAGBtdlyy2mHvOYOaB8/D3tsLW1cXOAudVxFCCNkcCs/3MMYYRmOjuDh7ERdmL6Bvvg/xTNywTa1Yi/MN53Gu4RweaHgA9Y76Mh0tIWQ3MoTqJ8/otzPGEF+K5BYqDepT6pHpKaSSCSzNTGNpZhqjF9d/Lx6u+gY9TPcEtPqX6gYfTPvkBYqiSHf1jk9pAbkchCSFwFh6w/0tlpqi1Sqi2AyL2UMLT92vWBAYf0kLy29/H0jd9UZFfXe+u9x/DjDtj3+PhBBCyEGTjUSQ7O9Hsq8PUl8/5OFhrZZtnaitAtc9RzBa24JzP/MonnzyJyCYaO0uQggh94fC8z0muBrUw/ILcxcQlaOG+ystlThXf04PzA9XHqYwhhDymnEchwq3FxXuEqH6dH6BUi1gz4XqsyEszYYwdunH677XWqgegMffrE+ruxv9uy5UZ4whnYlAlqaQvKtaRZKmkE4vbrg/x5lhs/ly/ePNdy3SGYAg0CXBWyIjA1OvaL3lYy8Ci8PG+0U30PKIFpa3PAJU1JXnOAkhhBDyumRCIS0sz02Wp2/fLtjGHAgg3dWNv0t78YLQgFmHB29qr8Gz7zmBgJvOvQghhLw+FJ7vcmEprIXluUU+Q/GQ4X7RJOJM7Rk9LO+s7oTA07vqhJDtYQjVu0/rtzPGkFiK6lPq4en8xHoqsT5Uf3Xd9+Lhqq/PT6rnPrY7VFfVDGQ5VFitIgchSUEoSmLD/U2myiLVKlr3uM1WD46j5+AtxxgQGc9Xsdz5IZBdt4gqxwP+s/nu8sZTAP0uJIQQQvYUxhjSt28j2adNlif7+5CdmS3YztrWpnWV9/TAdOo0/mxwFf/tu+PIigyVNhP+8Ke78GSPn4bICCGEbAkKz7eBoiq4vHAZi8lF1NhrcKb2zKYD7dX0Kvrm+vSwfCw2ZrjfxJnQXdONcw3ncL7+PE7WnIRZOLgdw4SQ3YHjODjdHjjdHjR3n9JvZ4whEVsyTqnnPsuJOJZmZ7A0O1MQqlfV1cHjb4Z3/UKljT6YLdZNHU82u5rrHl9XrZL7WpZnAKgb7M3BZm2ATQzAbqhW0abJzeaqDfYlWya1Ckz8IB+YxyaN91c05KtYjjwMiLSGByGEELKXsGwW8vAIpP6+XFh+GUrUeGU1BAG2Y8dg7+2FvbcH4unTMFVrv/MvTy3h6b8dwOiCVl369mN1+OTPHEdtpW2nHwohhJB9jMLzLfbi5It47uJzmE/O67fV2evwzLln8FjzYwXby1kZVxevajUssxcwGBmEyvKhDgcOne5OvYqlp64HdjNdekYI2Rs4joOz2g1ntbt4qL5uodLIdD5Uj83NIjY3i/G+YqF6E9z+AKp9FXB4eZidEtKZ2Xy9ihxEJrO04XHxvG1d73jAMD0uij7w/OZCerKFGAPmb+TC8peAqVcBNZO/nzcDzQ/mA/PaLoAmygghhJA9Q02lIF+/rk+WS1euQE0Yr/jjrFaIJ0/mw/KTJ8E7HIZtkuks/uhbt/CXr0yAMcDrtOATP3McP3WiYScfDiGEkAOCwvMt9OLki3jqu0+BgRluX0gu4KnvPoXPPvxZPBx4GIORQT0sv7pwFWnVuMDcocpD+d7y+nNw2Vw7+CgIIWT7GUL1E6f02xljSC7HEA5OIjw9juj8Dawuj0FOTYO3rsJSOQlz5Q+RqshgIcuAudI/w2z25LrHCz8slhq6lHc3SEaB29/JdZe/BMTv+gutPgS0vlULyw89BFidZTlMQgghhLx2SjwB6coVJHOT5fLAdbC08bUvX1EB8cxpLSzv6YV4/Bi4Der7fjQWxjNfGUAwqtW3PXHGh4+8owvVjt21jg4hhJD9g8LzLaKoCp67+FxBcA5Av+2ZHzwDgROQzCYN99eKtTjfcF7/qHfU78gxE0JIOTHGkMlEi1arSNIUUtZ58E1AFbSPgv1VDpmEBXLMhPSKGakVS/7zqhlq1gRXbTXcfhe8fhc8fhd4vwsOXyUF5+WiKkDocr6KZeYysO5qK5jtwKE3aWF566OAp6V8x0oIIYSQ1yQbjSLZ3w8pN1ku37wJqMaqPMHrhb2nR58st7a3gxPuXXG6LGXw7Ddv4m/7ggAAn0vEH7znOB7uqN2Wx0IIIYSsofB8i1xeuGyoaikmpaQAAJWWSn2y/HzDeRyqPERBDiFkX1LVLFKpGSTXKlX0Dy0kV5T4hvsLghN2sTnXP26cHrdaG8BxApLLMX1xUu3zFMKZKcirK4jNzyI2P4vb/Rfz35TjUFVbpy9Q6l1bqNTnh9lKHZlbbnUuN1n+IjD+MiDHjPfXduWrWJreAJioMocQQgjZCzKzs1pXeS4sT4+PF2xj9vu1sDy3wKfl0Gt/7fvtwTn83ldvYGFVez39829oxgcf74TTSnEGIYSQ7Ue/bbbIYnJxU9v9+9P/Hr90/Jc2vYAoIYTsdtlsfF0gPmkIx+VUCIwpG+5vtdYba1VsAYj2Zoi2AMzm6nu+wHK4quFwVaPpeLfhdq3+pXChUml1Bcvzc1ienysM1Wtq9VDd42+CN9AMd6MfZhuF6puWTQPBV/Pd5fM3jPfbqrQFPlsfA1oeBap8ZTlMQgghhGweYwzpiTtI9l2C1N+P5KU+ZGZmCraztrVC7OmBvfcs7L09MNff/1XV4XgKH/v6IP5hYBYAcNjrwGfe241zh933/T0JIYSQ14rC8y1SY6/Z1Hanak9RcE4I2VMYU5FOL+amx43VKpI0hUwmuuH+PG+BzdYEu9i0boJcW6jTZgtAELZn0the5UJTlaswVF9ZRiQ4ifD0lGFiXVpZxvLCPJYX5nH78qX8DkVCdY+/CR5fgEL1NdEJYDzXWz7xfSC9/ooCDmg8natieQzw9QACnX4QQgghuxlTFMjDw1pQ3tePZH8/lEjEuJEgwNbVlZ8sP3MGpurq1/+zGcPXrs7g498YxFIyA4Hn8MtvPoLffLQNNjO9liaEELKz6NXrFjlTewZ19josJBeK9p5z4FBnr8OZ2jNlODpCCNmYqqYgSdPGahU5H5KramrD/c1mN0QxsG56PPfZ3gSrpRYcx+/QI7k3e2UV7Me6EThWJFSf1qbTw9NTiE5rn0uG6gAqa+rgDTTB7QvAG2iGxxeA2x+AxSbu5EPaeekkcOeH+e7y6F2XaTtqtKny1seAlrcADm95jpMQQgghm6Km05Bv3EDyUh+S/X2QLl+BGjfW63EWC8STJyH25jrLT50C73Bs6XHMxCT83ldv4OXhBQDA0YZKPP/ebpzwF1sBhxBCCNl+FJ5vEYEX8My5Z/DUd58CB84QoHPQKgeePvc0TZ0TQsqCMYZsNgZJCiJ5V7WKJE0ilZoHirzxt4bjBFitjUWnx0WxCSZTxc49mG1ir6yCvesEAl0nDLfrofpdverJ5RhWFuexslgsVL+r/sXftLdDdcaAxZF8WD75CqCse0OFNwGB8/nu8roTAL973jAhhBBCiJGaSCB59SqSfX2Q+vohDQyApYzDErzDAbHnDOw9vbCf7YXt+HHwFsv2HI/K8DcXp/DcPw0jnsrCIvD494+24ld+ogVmgc4pCCGElA/HGCudluxDKysrqKqqwvLyMiorK7f8+784+SKeu/icYfHQens9nj73NB5rfmzLfx4hhKxhTIEszxZWq8ja52x2dcP9BcGRmxxfmyDXesdFsQk2WyN43rxDj2RvSK4sIzodzNW/5D+Sy7GS+1TW1MLjC8CTm1L3BLRwfVeG6lIMmPhevrt8JWS8vyqQD8sPv1nrMie71naf/xBC9jZ6jtj/sktLhgoWeWgIUIzr0ghutzZRnpsst3Z0gBO2f/hrIpzAM18ewIUJrQrwTJMLzz/ZjdbavT+cQQghZPfa7PkPhefbQFEVXF64jMXkImrsNThTe4YmzgkhWyKbTUCWpyFJk7kO8vwinbI8A8YyG+5vsdRCFNf6x5tyE+RaYG42e+65OCe5N2l1RQ/Sw8EpREPa541C9QpvTW46XZtS1ybWA7CI9p07cFUF5q7lw/LgRWD9Yq+CFTj0UL673NsG0L+XPYOCMULIRug5Yv/JzM3pFSzJvj6kx8YLtjE3Nmpd5bkFPi2HD+3ouWBWUfE/fzSB//vbt5DKqhDNAj74eAd+/g2HIPB0jkEIIWR7bfb8h2pbtoHACzhbf7bch0EI2YMYY0inw3ogvr5aRZKDSKfDG+7PcRaIor/o9LgoBiAIu3DCeZ8RKyrhP3oc/qPHDbfnQ/WgYVI9EVvCangRq+FFTFztN+xT4anRp9M9/gC8/ma4fQFY7VsUqscXgfGXtcB8/GUgede/L297vru8+UHAsoNhPiGEEEI2hTGG9J07egVLsq8PmVCoYDtLS0t+srynB+bGxjIcrebm7Aqe/vIABqaXAQAPtXrx6SdOIOCmcw1CCCG7C4XnhBCyw1Q1DVkOQZKmctPj6z+CUFVpw/1NJpcejucnx7UPq7UOHEdXuuxGJUP1+Kq+UGkklPu8FqpHFrEaWcSdYqG6P6CF6oEmeHxawH7PUF3JAtOX8t3ls1eN91ucwJGHtTqWlkeB6ubX/8AJIYQQsqWYoiB161ZuslyrYVHCd70BzvOwHT0Ke2+vtsBnTw9Mbnd5DnidVFbBn35nHP/1O2PIqgwVNhM+8o4u/Gyvn66AJIQQsitReE4IIdsgk1k2BOL6JLkchCzPAlA32JuHzdagBeK2gDY9bs9/bTbT5dT7ieisgL/zGPydxwy3r4XqWq96fqHSxFI0H6pfu2zYx+nx5mpfAvD4m7VwvYKHdeYVLSy//X0gtWw8gPrufHe5/xxg2p6FwAghhBByf1g6DenGIJJ9Wg2LdPkK1FXjWjacxQJb9wltsrynF+LpUxCczjIdcXFXppbwwS8NYHQhDgB4W1cdPvnu46irtJX5yAghhJDSKDwnhJD7wJiCVGoeSWkSshTMTZDnF+rMZpc33J/nxVzveAB2sTn3uSm3OKcPPE8B5kFXKlSX43FD7Ut4egrR6SnEl6KIR8KIR8KFobopBY81Ca/VDbfTA2/rcXhOPgbrsceBirqdfFiEEEIIuQc1mYR09aoWlvf1Q7p2DSyVMmzDOxwQT5/Wa1hsJ06At1rLdMQbS6az+L+/fQv/80cTYAzwOi34+LuO46dO1NO0OSGEkF2PwnNCCClBUaR1neNTkOT19SohMJbecH+LxZuvVLHlPtu1ry0WL71YIPfF5nTC19kFX2eXdgNjQGQc8o1/RGTgu4jcuYWIZEYkZUckZUc8a9U/JhPVQBTA1BLw8t/B6X4516e+/iMAm2N3TaoRQggh+5kSiyF5+bJewyIPDgKKYthGqK7Wusp7eyH29MLW2QHOtPtfzr8yFsYzX7mOqWgSAPDEaR8+8tNdqHbQoAghhJC9Yff/tiWEkG3CGEMmE1nXPR40LNSZTi9suD/HmWGz+XL94825yfFczYoYgCDQgkdkm6RWgYkf5LvLY5OwAfAB8FUC8DUArQ8CrY9BrjuLSGTVMK0emZ5CPBrRPyYHrhi+vbPaDU+gGR5fILdgaTOF6oQQQsgWyczP56bKtQU+U6OjBduYGhtg7+nVJ8stR47sqcGLFTmDZ795E//7UhAA0Fhlwx88cQJv6agt85ERQgghrw2F54SQfU1VM7nFOdcmyCchyUE9IFeUxIb7m0wVuenx5nUd5Gv1Kg20OCfZGYwB8zdyYflLwNSrgJrJ38+bgeYH893ltV1A7gW2DYDPC/g6jhq+ZSqZ0GpfglOIhrTPkVBQq35ZiiK+FC0aqrv9Tble9fyHbZd1qhJCCCG7BWMMmclJbWHP3GR5Jhgs2M5y5AjsPT2wn+2FvacHZp+vDEe7NV4cmsfvfvU65le0qpmfe6AZH3y8AxU2c5mPjBBCCHntdkV4/qd/+qf4wz/8Q8zNzeHkyZP4L//lv+DcuXNFt/2Lv/gLfOELX8CNGzcAAD09PXj22WdLbk8I2f+y2VV9elzWp8i1cDyVmgFjygZ7c7Ba6/VAfK13fO3DbHbt1MMgxCgZBW5/RwvLx14C4nPG+6sPAa1v1cLyQw8B1tcWYFvtDjS2H0Vje7FQPZibUNcWKg1PTxlC9anrVw37OKrdeuWL198Md+4zheqEEEIOGqaqSN26hWRfv77Ap7IYNm7E87B1dkLM1bDYe3pg8njKc8BbKBJP4WPfGMI3rs0AAA57HXjuiRM4f2TvPzZCCCEHV9nD87/927/FU089hT/7sz/D+fPn8bnPfQ5vf/vbMTIygtrawku6vvvd7+Jf/It/gQcffBA2mw2f+cxn8La3vQ2Dg4Pw7eF35wkhpTGmIpWa1wNxvVolN0GeySxtuD/PWw2BeH56vBk2mw+CsDsXVyIHjKoAocv5KpaZywBT8/eb7cChN2lheeujgKdlWw5DC9U70djeabg9lUxqgXpoCpHclHokOIXVyCISS1EkioXqrmotVA80wePLffY3QXRWbMuxE0IIITuNpdOQBgchrU2WX7kCdWXFsA1nNsPW3a1PlounT0PYR28wM8bw9Wsz+NjXB7GUzIDngH/75iP47cfaYTPTVZqEEEL2No4xxsp5AOfPn8fZs2fxJ3/yJwAAVVURCATwG7/xG3jmmWfuub+iKKiursaf/Mmf4Od//ufvuf3KygqqqqqwvLyMysrK1338hJCtoSgyZHk6N0E+aVioU5aDUNWNF+c0m91677hNDOQ+a5PkFksNOI7foUdCyGuwOpebLH8RGH8ZkGPG+2u78lUsTW8ATLvvjZ5UMoloKIhwbkp9rVN9NbxYch8tVA/oXepawN5Mofo2ovMfQshG6Dli89RkEtK1a/pkuXTtGpgsG7bh7HbYT5/WF/i0dXeDt+6+3+FbYXZZwu/+/Q28PKytFdRZX4Hnn+xGt99V3gMjhBCy56iqgtDNQcRjS3C6quE7egw8v31vwm72/Kesk+fpdBr9/f340Ic+pN/G8zwee+wx/PjHP97U90gmk8hkMnC73UXvT6VSSKVS+n+v5KYAstksstms/jN5noeqqlDV/JTf2u2KomD9ewylbhcEARzH6d93/e2AFvRv5naTyQTGmOF2juMgCELBMZa6nR4TPabd9pg4joOiLCORuKOH4pIchJz7SKXuqqQoIOiLc9rFZlitftjEAERbE2w2P6zWqg0f0/o/G/p7osdUtsekZiCELoGN/jMw9hK4hUHDPsxWBXb4J8COPArW8hbwroDxMd31e2s3PCaT1YqGtg7UtbQZ/twzsoTY3AzCU5MIBycRCQURnQ5qk+qxJSRiS5i6MWD4/vYqFzz+Jrh9frh9TfD4AvA2NcNR5aJ/e6/zMd29DSHkYKPXSJt/TGx1FfFLfZD6+yH190MeGtJ/H+vbuVwQz5yB42wvxN5emNvawJnyL7U5QSg49nI+pq34e+I4Hv/7UhDP/tNNJFIKzAKHX3+4Bb/6ljaYBY7Ovekx0WOix0SPiR7Ta3pM432v4rt//d8Rj+arzpxuD97yC7+M9vNvLOtrpLKG5+FwGIqioK6uznB7XV0dhoeHN/U9nn76aTQ2NuKxxx4rev+nP/1pfPzjHy+4/cqVK3A4HACAmpoatLS0YGJiAouL+Uk5v98Pv9+PW7duYXl5Wb/9yJEjqK2txY0bNyBJkn57Z2cnXC4Xrly5YvgL6O7uhsViQV9fn+EYent7kU6nMTCQDw8EQcDZs2exvLxs+DMQRREnT55EOBzG7du39durqqpw9OhRzMzMYHp6Wr+dHhM9pnI8JsYUVFcz1NZymJrqw8rKOFS2AKYuAFwYqrrx4pyADTxXB46vhddzFK7qNgSnZDDmBcd5wHECOjvufkxxAMP090SPadc+ponL34Er3IeqcB+qoteArAQutx0Dh0RVGyTfQ6h54P9ACHWYnpkDFAC3ZlFTk92Vj+m1/D0pNgcS9kr4O07AD8BVWYEqiwk3L/dj/s5tSNEwkpFFpFaWkVyOIbkcQ3CwMFS3utywVbshumtg93hx8oEHUe8P0L+9TT4mCs8JIevRa6TSj2nlzh2Ybt2CcOsW7BN3oExMaAt3r8PX1sJ57hwWvF5k2lqhNjRgied37WPa6r+nubiC/2+cw4UJrTqxrdqEXzntQLNrBRYTj1gstuce0378e6LHRI+JHhM9pr3ymCKjwxj+hy/hbvFoBN/47Kfxrqc+jBhvLttrpLLWtszMzMDn8+GVV17BG97wBv32D37wg/je976HCxcubLj/c889h+effx7f/e530d3dXXSbYlMVgUAAkUhEH8mnd3joMdFj2vxjymbjkOVpyPIUUukQkslJSEltilxbnNN4DHezWOogik2w2QIQbQHY7U2w2w/BYvXBJLjAcdyOP6Z73b4X/57oMZXxMWWS4CZ/BOH2d8DGXgQXHTdsD0cNWMsjUI88Anb4YcDh3f2PKWc7/56yKRmx2RksTN1BdDrXqX6P+hd7lQtuXwBuXwAev/a5tukQxMqqXfGYdtPf0+rqKtxuN1UyEEIA0GuktdsZY8gEp5G6fBnS5ctIXrqETDBY8OdlPnQIYk9P7uMMrAHtyrDd+Jjuvn0r/54UleEvX7mDP35xDKmsCtEs4D+8tQ0/90ATBJ7bk49pM7fTY6LHRI+JHhM9pu17TKqq4C9/85cRj0ZQSoXHi1/43OexvsJlJ18jlTU8T6fTsNvt+NKXvoR3v/vd+u0f+MAHEIvF8LWvfa3kvn/0R3+ET33qU3jxxRfR29u76Z9JfX6EbIwxhnR6QV+YMylNQZaCSEpTkKRJZDLRDffneYsWjOsLdGo1K1pg7ocg2HbokRCyQxgDFkfyC31OvgIo+UACvAkInM93l9edAHjq4N+stCwhOh1EJBREODip9asHp7CyOF9yH7GyCl5/E9z+Jnj9+YVK7ZVVO3jkuwud/xBCNnJQniOYqiI1OoZk3yV9gc/s4l1v0nIcrJ2dsPf2agt89vbA5PWW54B3kZG5VXzwS9dwbVqbEnxjqweffk83mjz2Mh8ZIYSQvSw4OIAvfuLD99zufR99FoFjxQen79ee6Dy3WCzo6enBSy+9pIfnqqripZdewq//+q+X3O/555/HH/zBH+Bb3/rWawrOCSEaVU1BkkKQpEm9e1zvIZeCUFV5w/3N5motGNdD8maIova11VpHi3OS/U+KARPfywXmLwErIeP9VYF8WH74zYDt4Ia2r5fFJqK+tR31re2G2zOyrE+nr/9YXpiHtLKM4NB1BIeuG/YRK6sMC5V6/blQvcq1g4+IEELITmGZDOShIST7+rQFPi9fhrrusncAgNkM8cQJLSg/2wvx9GkIFRXlOeBdKJ1V8affGcN//e4YMgpDhc2E33vHUbyvN6BfMUoIIYS8VqvRMEI3B3Hju/+8qe3jsaVtPqLSyhqeA8BTTz2FD3zgA+jt7cW5c+fwuc99DolEAr/4i78IAPj5n/95+Hw+fPrTnwYAfOYzn8FHP/pR/M3f/A0OHTqEuTltkUGn0wmn01m2x7GeqjLMjsaQWEnBUWlFQ5sLPE8nFmRnZTKxdYH4VG5yXPvQFufc6KITHjZb47rpce3DnvtsMtELCnLAqCowdy0flgcvAmzdZWCCFTj0kBaWtz4GeNsAekG5rcw2G+pb2lDf0ma4PSPLiM5M64uURoKThlB9emgZ00M3DPuIFZXadLqvSf/sDTRBrKyiYIAQQvYQVZIgXRvQwvL+PkhXr4Gt64IFAM5uh/3USYi9vbD39kLs7gZvoysji7kajOGDX7qGW/NxAMBbu+rwqXcfR10l/XkRQgjZPMYYoqEgQsNDmB4eRGh4aMMriYtxuqq36ejurezh+fvf/34sLi7iox/9KObm5nDq1Cm88MIL+iKiU1NT4Ndd3v7f/tt/QzqdxpNPPmn4Pr//+7+Pj33sYzt56EWNX1nAD/52FIlY/pJ9h8uKN72/DS2na8t4ZGS/YUyBLM8aAnJtgnwSkhRENruy4f6CYM8H47ZAbnpcq1mx2XzgefMOPRJCdqn4IjD+shaYj78MJMPG+73tQEtuurz5QcBCly3vBmabDXVHWlF3pNVw+1qoHpmeQvjuSfXVFUwP3SgI1W0Vlfp0+vqJdXuV63WH6qqqIHRzEPHYEpyuaviOHjN0+BFCCLk3ZWUFycuXIeUmy6XBQSCTMWwjVFVB7OnRalh6e2A7ehScmc5zNyKlFXz2n0fwP344AZUBHocFH/+ZY3jHiQZ6U5kQQsg9KdkM5m+PIzQ8iNDIEEIjNyGvGjMqjuNR03wYjZ1HMfzD70GOr5b8fhUeL3xHj233YZdU1s7zctjOPr/xKwt44fM3St7/+K8cpwCdvCaKktS7x6V1veOSFIQsh8BYZsP9LZZavU5lrVplbXrcbPbQyS8h6ylZYPpSvrt89qrxfosTOPKwVsfS8ihQ3VyOoyRbLJOSEQ1N62F6eHoK0ekgYgtzWp99EbaKSnh8AXgDa8F6vv5lM8+roxdewct/9eeIR/NvyDjdXjzyC7+MtvMPbtljW++g9BkTQu7PXnmOyC4uIpnrKk/29yM1MlLwXG2qq9ODcntvLywtLeBorZFNe2U8jGe+fB1T0SQA4D2nffjIT3fB7bCU+cgIIYTsVqlkErO3bmpB+fAQZsduIZtOGbYxmS1oaOuAr7MLvs5jaGjrhNWuDaCNXngFX//ssyW//7ue+vC2vE7a7PkPhedbRFUZvvDhVwwT53dzVlvxc3/wIFW4EJ22OGcYkjwFKbk2PZ6fJE+nwxvuz3FmiKI/Nz3eZFikUxSbIAjiDj0SQvaoWBAYf0kLy29/H0jd1YNa353vLvefA0z0wvGgyKRkRGdCWqiuV8BMbRyqOysKptS9gWZDqL7bTwwJIQfTTjxHMEVBsq8f2cVFmGpqYO/tASeUvuKGMYbM9LTWVd53CVJfP9KTkwXbWZqbIZ7thb2nF/azvTD7fDQgch9W5Aw+/Y/D+P8uTgEAGqps+IP3HMcjnXVlPjJCCCG7TXwpitDwEEIjgwjdHMLi5AQYUw3b2JwVelDu6+hC3ZEWCKbSV34VGzCq8Hjxlg+Uf8CIwvMtEhpZwlf/+Mo9t/O1uxDocsPT6ITb50CF20Ynd/ucqqYhyyG9d1yWgkiuLdQpBaGq0ob7m0xV6wLxZtjFJtjEAOxic25xTrrMn5BNy8jA1Ctab/nYi8DisPF+0Q20PKKF5S2PABX0gpEYZdIpREPTiOr1L0FEpicRm79XqB6A2xfArR//EKlkouT3r/B48W/+5H9seYULheeEkI1s93PEyre/jflnP41sbr0qADDV16Puwx9C5dveBgBgqorU2BikdZPl2fm7+lA5DtaOjvxkeU8PTDU1W368B81LN+fxu39/A3MrMgDg/3ygCU8/3okKG9XbEELIQccYw9JsCNM3BzGTmyyPzc8WbFdZUwf/Wlje2QV3o/81X/m109WWmz3/KXvn+X6RWCk9cb5e6FYMoVsx/b8togmeRgfcPie8Pu2zx+eEVaS/mr0kk1nR6lTkYG6CPPe1NAVZngWgbrA3B5u1oWBxTlGvV6naqYdByP7DGBAZz1ex3PkhkF33hhXHA/6z+e7yxlMA9U6TDZgtVtQdbkHd4RbD7Zl0CkszIX1KPRycQjQ0hdjcHOT4qjaZMTx0z++/GtFWnQ8c696uh0AIITtq5dvfRug3f6vgDcbs/DxC//43sfrud0NdWYHU3w9l+a4rwMxmiMeOwX62V+stP3MGAr0BuGUi8RQ+/o0hfP3aDADgkMeO597bjQeOeMp8ZIQQQspFyWaxcGdcf/0SGhmCtHLX72eOQ03TIcNkeYXH+7p/Ns8Lu/J1ECW0W8RRad3Udkff2IBsWkV0Jo6luSTSUhaz48uYHTf+Q3RWW+HxO+FpdMLjc8Djc8JVb4cgUF9fOTCmIpWaMyzOmdS/DiKbjW24P8+L67rH89UqdrE5tzgnVUEQsmVSq8DED/KBeeyuS7wrGvJVLEceBsTyrdpN9g+zxYraQ0dQe+iI4XY9VJ+ewsiPf4jxvlfv+b3isaXtOkxCCNlRTFEw/+yni1+Zk7tt5atf1W/iRBHiqZPaZHlPL8ST3eBFqiHcaowxfP3aDD7+jSFEE2nwHPBv33QEv/3WdtjMNERACCEHSVqWMHtrRKtgGR7EzOgIsinjgLBgNqO+pR3+o1pQ3tDeCZvDWaYj3nkUnm+RhjYXHC7rPTvPH/5XnXrnuZJVEZtPIhKKIxJK5D7HEV9K6R+T1yP6/rzAobreDk9uOt3d6IDX74TDZaXqly2gKHI+HJfXFumcyi3YOQ3G0hvub7F4IdoCuYU5mwwLdVosXvo7ImS7MAbM38iF5S8BU68C6rrFdHkz0PxgPjCv7QLo/0eyQ9aH6s5q96bCc6eL3tAhhOwPyb5+Q1VLKa73vx+uJ94DW1cXODNVhWynuWUZv/v31/HS8AIAoLO+As8/2Y1uv6u8B0YIIWRHJGJLmBm5ienhQYSGh7BwZxxMNbYlWB0O+DrW9ZW3tMF0gH8/U3i+RXiew5ve34YXPn+j5DYPva/NsFioYOL1IHw9OZFBdCYXps8kEJmOIzITR0ZWciF7AkC+/89qN2lBus+p1754Gh2wUPWLAWMMmUwkF4av9Y/nJ8jT6YUN9+c4E2w2n2F6XOsfb4JoC8BkcuzQIyGEIBkFbn8n113+EhC/64V59SGg9a1aWH7oIcB6cN4VJ7uX7+gxON1ewyI4d6vweOE7emwHj4oQQrZPdnFR/5pxDOlWBqWKQVjmYBnjwDHttZH97FmIJ0+W6zAPBMYY/velIJ795k2sprIwCxx+45E2/F8/0QKLia5uJoSQ/Ygxhtj8LEI3BxEaGUJoeBBLszMF21V4avQKFn9nFzz+ptfcV76fUbq6hVpO1+LxXzmOH/ztqGEC3VltxUPva0PL6dpNfR+bw4zGNhca21z6bYwxrEZlREMJhENxRHPB+tJcEqlkFrNjy5gdM1a/VHhsepC+VgHjqhPB7+PqF1XNQJZnSkyPT0FRSi/SBgAmU4UWjNuM9Sqi2AyrtR48T//LEFIWqgKELuerWGYuA+tX8zbbgUNv0sLy1kcBT0vp70VImfC8gEd+4Zfx9c8+Cw4cvDY/RMEJSYkjLE+DgeEtH/jlbV0UhxBCdtLaYp7SKRXLP5uFuu7CGn4JqPo7E8SrPC36uc0mIwk88+Xr+PFt7armUwEXnn+yG+11FWU+MkIIIVtJVRQsTk4gNDyoT5Ynl2MF23kDzfm+8s4uVHo3l1ceVBxjxQro9q/tXkkeAFSVYXY0hsRKCo5KKxraXIaJ862kZFQszWvT6GsT6pFQomR9DG/i4G5wwNPohNunTat7fE7Yqyx7plYkm11dF4hP5ibIg0hKU0ilZsCYssHeHKzWuoJqFbvYDFEMwGRy7Zk/B0L2vdW53GT5i8D4y4AcM95f25WvYml6A2Da3NoThJTb+Fd+BPXVFYh8/ooISY2Df6ASLU+8cVt+5k6c/xBC9q7teo5gioKBX3sQ4Z/NXXGz/jQ79yrU+3dedP/pK+AEeuNwqykqw1/+aAJ/9O0RyBkVNjOP//i2DvziGw9D2KbXp4QQQnZOJiVjdvQWQsPaZPnMrWFkZMmwjWAyoa6lXQvLO7rQ2HEUopPePAU2f/5DY7TbgOc5+Dp2pq9UMPPw+ivg9VcA5/O3y4lMQZd6dCaBTEpBOBhHOBg3fB+rw6QtTurPTarnOtUttp3/J8KYilR6AVJyrX98at1CnUFkMtEN9+d5a256/O4FOptgs/khCBSwEbIrZdNA8NV8d/n8XTVYtiptgc/Wx4CWR4EqX1kOk5DXQ7oRhvWiCvDGKiGRdwIXVUjtYYjHX/9K9YQQsivwwPLPZrWv785qOQAMWPlZBdi/F8aWzcjcKj745QFcC8YAAA+2ePDcE91o8tjLe2CEEELuW3JlOVe/MoSZ4SHMT4xBVYwDpBbRDl/HUX2qvK6lDWYL5WCvB4Xn+5TNYYavvRq+9nyIz1St+iU8HUd0Jh+sx+aTSCWymBmNYWY0Zvg+lV6b3suufThQVfP6q18UJQVZDuqheHJdOC7LQahq6YVXAcBsdt9Vq9KUmyYPwGqpBcfRGTghe0J0AhjP9ZZPfB9Ir39jjwMaT+eqWB4DfD2AQL+2yN7FVIbYN8Y33Cb2jduwdXnA0UQgIWQfiMUuIcPFSm/AAWksYXbuq6ivexd4/uAuRrZV0lkV//W7Y/jT74whozBUWE343XccxfvPBugKW0II2UMYY1hemNemynMVLNGZ6YLtnNVuLSg/qi3u6W1qphrILUYpxAHC8RwqvSIqvSKOnMr3CmYzCpZmk/qE+toipcmVNFbCMlbCMiau5Rc3E8x8rvol36Xu9jlgr8xXv2iLcy5pvePJyXUd5FpInkrNFRyf4Vg5ATarr2g4rtWr0CUmhOxJ6SRw54f57vLoXUGio0abKm99DGh5C+CgCVyyP6hyFsmrC1CW0xtupyynkJpYhq3FtTMHRggh2yiVWtC/VsFjGEcRQzVcWEInboKHtn7JzZsfxPDw78HhOAKHox1ORzscTu2zzeajwZhNuhaM4YNfGsDI/CoA4LGjtfjUu0+gvspW5iMjhBByL6qqIDw1ienc4p4zw4OILxU2L7h9AfhzU+W+zmOorKmlN0e3GYXnBCazgJqmCtQ0GQNpKZ4u6FKPzsSRTatYnFrFYjAG8/UozI5FmJ1h2KsjsHuisDgXAdMcGDZenFMQHAW1Klr/eBOs1gaaPCFkP2AMWBzJh+WTrwDKuitLeBMQOJ/vLq87AdCq3mSPYiqDEkshu5hEZlFCdjGJ7KKEzKIEdXXj0Hy917ItIYTsZlartgDZJZzHF/BLiHL5N8XdLIyfx//EWVwAz1uhqinE48OIx4cxv+57CIIdDkdbQahusdRQWJAjpRV89p9H8D9+OAGVAR6HBR971zH8dHcD/RkRQsgulUmnMDd2C6HhIS0sH7mJtJQ0bMMLAuqOtGqT5bm+cntlVZmO+OCi8JyUJDotqG/JoKoxjoa13vHkFFZX7iCZnEJWmQW4wsU5169Am5FcUFN1MPGNEG1NqHQdhqeuFd6GNlitHjqZI2Q/kmLAxPfy3eUrIeP9VYF8WH74zVqXOSF7iJpSkA1r4XhmIal9vSAhE5aArFpyP040gUnZe35/vsKylYdLCCFl43KdxRXz2/G5zL8tuC8KNz6H38F/NP93PPXGzyGVmkcicQvx+C3tc+IWEolxKEoSKyvXsLJyzbC/yeSC09l+V6jeBrPZtUOPbnf48XgEH/rKAO5EtMDl3aca8dF3HoPbQb9LCCFkN5Hiq5jJ9ZVPDw9ifnwMqmJ8bWC2iWhs79Qny+tb22G20tVD5Ubh+QHHGEM6vZirU5mEJAUNHeSZTKT0zhzA8xbYbAHYrH5wagMyiVoko24sz1YhcseO5HKxCVIJJvMNuHMLk3p8Wu2Lp9EJeyWd5BGy56gqMHctH5YHLwJs3RtrghU49FC+u9zbBtAbZ2SXY4xBWU6vmx7XPmcXkxtXrwgcTF4RZq8IU60dphoR5hrtM2cRMPeZixvuL1RZYT1MbygRQvYHFTz+F/619h93/+7neICp+H/wS/htzgRR9EMU/fB6H8nvr2YhSZNakB5fC9RvIZm8g2w2hljsImKxi4Zva7XU6dPpDkd7LmBvhSDsr4UyV+QMnvunYfzNhSkAQH2lDc8+cRyPdNaV+cgIIYQAwMriAkLDg5jO9ZVHpqcKtnG4qvWFPX2dx1DTdAi8QH3luw2F5weAqqYgSSFIa9PjuYU518JyVZU33N9kcsFuWJyzWf/aaq3fsIMwuZI2dKlHc5+zGRULk6tYmFw1bC9WWrQu9XULlLobHDBZ6MmDkF0lvgiMv6wF5uMvA8mw8X5ve767vPlBwLK/XrCS/YNlFK1iJSwhu5DMf72YBEuXniLnHWZDMG6qtcPsFSFU28AJpd8ccr2zBZH/5+YG9x+hxUIJIfvGq7E45rMCUOppjeMxlwW+Mh/FE3VuCHcF7DxvgsPRAoejBaj9Sf12RUkhmRwvCNVlOYRUeh6p6Dyi0R8Yvpdoa9Kn07VQvQN2+2Hw/N4b3nl5eB4f/soNzK1or+P+5fkmPPOTnai0Ue0lIYSUA1NVhKenEMr1lYeGh7AaWSzYrrrRD19HF/y5xT2r6uqpkWEP4Bhj7N6b7R8rKyuoqqrC8vIyKisry304WyaTia0LxrVwPClNrlucc6O/Zh42W2ORhTmbINqaYDZv7Z+TqjKsLEqIhOIIh+KIhhKIhOJYDktFD5PjgKpaOzw+Y6he6REpYCBkpyhZYPpSvrt89qrxfosTOPKwVsfS8ihQ3VyOoySkKMYY1NWMYXp8rZNciaVK/4rkOZg8Nphq7DDXiFpInvuat99/QCHdCCP2jXHDBLpQZYXrnUcgHt+eRXL36/kPIWRrbNdzxN/PL+FXhyY3ta2V59Bmt6HTYUOHQ/vc6RTht5o3HSxks6tIJMYKQvV0Olx0e44zwW4/DIejzdCnLopN4LjdN7wTTaTxiW8M4qtXZwAAzR47nnuiG29o8ZT5yAgh5GDJZjKYG9f6ymdGtM7yVMK47h/H86g73KJPlfs6umCvcpXngElRmz3/ofB8GzCmIBa7hFRqAVZrLVyus6/75IsxBbI8p02Ly8G7gvIpZLMrG+4vCHaItkDRBTpttsZdMXGRSSmIziS0xUnXFimdTkBOZIpub7IK2pR6owPudaG66Cz/YyFkX4gFgfGXtLD89veB1LLx/vrufHe5/xxgov/3SHmxrIpsREJmQSqoW2GpwjU61nCiKReO22GuFWHy2mGqFWFy28AJ27OALVMZUhPLUFfT4CsssB6u2tY3hCk8J4RsZLueI360tIr3Xh2/53YWDkiXeFXqFPh8mO4Qc6G6DV6zadOhejodQSIxWhCqZ7OrRbfneSscjtaCRUqt1vIswMkYwzcGZvGxrw8imkiD54B/86Yj+O3H2iHSFbqEELLt5EQcM7du6pPlc+OjUDLGrMpktaKxrVOvYWls64TZRn3luxmF5yVs94vHhYVv4dboJ3LT3hqrtR7tbR9Fbe3bN9xXUZJ65/j6apWkNAVZDoGx4iHyGoulpmi1iig2w2Lem4tzMsbWVb9otS/hUBxLs0koJRZls1dZDBPqnkYnqhvsMJnpxJKQDWVkYOoVrbd87EVgcdh4v+gGWh7RwvKWR4AK6tQkO48xBjWRyQfjC1rNSmYxCSUql54i5wCTW5siN9St1IjgHZufatyrKDwnhGxku54jFMbQ++MhzKUyRZ+eOQANVjNefeAoZlIZDMdlDCckDCdkDCdkjCVlZEs8r7vNQj5Md+Qn1qvMm2smZYwhlZrLL06qh+qjUNVU0X0EwVlkkdJ2WCzbN/k9tyzj9756Ay/enAcAdNRV4DNPduNUwLVtP5MQQg661UhY7yoPDQ8iHJwE7opPxcoqfWFPX+cx1DQfhmCiduy9hMLzErbzxePCwrdw/cavofCVu/aC/PjxP4HL1atNjyenchPkk3pQnk4X9iEZvgtnhs3my/WPr6tWyYXk+20RnI2oiorlRQnh6bg2rZ7rVV8JF+9v53gOrlrRGKr7nKhw26j6hRxcjAGR8XwVy50fAlkpfz/HA/6z+e7yxlMAT29CkZ3BFBXZiFywWGdmUQKTsiX346yC3j9uql0XkntEcKbtmSLfCyg8J4RsZDufI765GMO/uXEHgPFV0toZ+H8/fgjvqHEV3TetqrgtpTAclzGSC9SHExLuSOmS75U2WM3G6heHiHaHDfZNXknEmAJJCmqhumGR0gkwVvz3j9nsMYTq2tdtMJkqNvUzix8Hw/++FMSz37yJ1VQWZoHDr7+lDb/6cAssB/j3GSGEbDWmqoiEgnpQHhoZwsriQsF2rvoG+DqOwXe0C76OY6huaNz3Azj7HYXnJWzXiSFjCn70ypsNE+eFOGzcPQ6YTJVFq1VEWxNstvpd2b23m6Tl7LowPR+qp5IlTnRtQr72pdEJr98Bd6MTNgcttkP2qdQqMPGDfGAeu6uHtKIhX8Vy5GFArC7LYZKDQ01m9P7xzKK2aGc2LCEbkQG1xO9MDhBc1nVd5Llp8lo7eOf+nyK/HxSeE0I2st3PEd9cjOH3RkOYTeWvpG20mvHJNl/J4HwjSUXFaDIXqOem1UcSMkKp4lfqcgCaRYuh+qXDYUOL3QoLv7kgWlXTSCYnCqpfJCmIUq/xbNZGfTrdkQvV7fYWCMLGl/FPRZJ45isDeGU8AgA4GXDh+fd2o6P+/sN4QgghGiWbwfztMYSGhzA9PIiZkZuQ48YaL47jUXPosGGy3OGi18b7DYXnJWzXieHS0qu4fOVfbWpbm7URNjEAu6FaRZsmN5urtuyYiIYxhkQsbexSDyWwNJeAWuI6UIfLaphQ9/icqK63Q6ApD7LXMAbM38iF5S8BU68C6roXlrwZaH4wH5jXdmmr9BKyhZjCoCzJ6ybI16bJk1ATG0yRW/giNSt2mL02cFTF9ZpQeE4I2chOPEcojOHVWBwL6SxqLSY84HJC2OJzjuVMFreSKa36Ja5Nqt9MSIhmiq97YeKAFrvNUP3S6RDRJFo2fWyKkiyySOnoBkNVPOz25oLqF1FsBoMJf/mjCfzRt0cgZ1TYzDz+49s68ItvPAyBrpYlhJD7kkomMXvrJqaHhxAaGcTc6C1kM2nDNiaLFQ1tHXpQ3tjWAYt4cNodDioKz0vYrhPDubmvY3Dot++5XdfRP0RDwxNb9nPJ/VMUFbH5JKLrJtQjoQRWo8WrX3ieg6vebuhS9/idcFZbacqR7C7JKHD7O7nu8peA+F0v3qoPAa1v1cLyQw8BVmdZDpPsP6qc1YLxBWPNSjYiAUrp0w2hyqr3j5tr7TB5RZhq7RAqLfT8ukUoPCeEbGS/P0cspjP52pd1vepxpfgaSiLPoU2vfsn3qjdaN391UyazXLBIaTw+gmw2VnwHzoywVI+xpVqE4g2ocHTg3z7yKFoa2sBxNMBDCCGbFY9GEBoZ0ifLw5N3wJjx+d5WUQlfRxf8ubC89vARCCZqIDhoKDwvodyT52dO/7+orn5gy34u2XopKYtoKI7IjDFUT5fo2LWIJr36xevLVcD4nLCKtFAE2SGqAoQu56tYZi4D608OzHbg0Ju0sLz1UcDTUr5jJXseUxmUWCofjOemyTOLSairGyxsbeJzFSuisW7FK4K30hT5dtvvwRgh5PU5iM8RjDGEUhkMJ9b61CWMxGXcSsqQS9SGVQi8FqY7jZ3qXsvmFylNp8OGRUpX4yOIrYxA4IoP8AiCHQ5HW5FFSmvoDWZCyIHHGEN0ZtrQV748X3jlT1VtHXxrFSwdx+D2+ek5lFB4Xsr2d57Po3jnHQertR5vfPB71Fu+BzHGEF9KGcL06EwcS7NJqCVOrp3uXPVLoxMevzap7qq3Q9jkYkWEbGh1LjdZ/iIw/jIgx4z313blq1ia3gCYrGU5TLJ3qSlFC8bD6yfJJWTCEpAtPqkHAHyFRQvGcxPk5lqtbkWostICzWV0EIMxQsjm0XNEnsIYJqW0Pp2+Nq0+LsklL6Lymk1akO40dqpXmDZ+3XctGMPTXx7AyNwy3LYl/FRnEu87nQGfzXWrJ8bBWLroviaTy7BIqcPRBqezHWaz63X+CRBCyO6lZLNYuDOO0M1BfbpcWl0xbsRxqGk+DF9HV66GpQsVbm95DpjsahSel7CdJ4YLC9/C9Ru/lvuvwrXkTxz/U9TWvn1LfyYpLyWrVb+sD9UjoTjiS6mi2/MCh+p6h6FL3eNzwOGi6hdyD9k0EHw1310+f8N4v61KW+Cz9TGg5VGgyleWwyR7C2MMynLaMD2+VreiLBd/sQ4AEDgtGF+/WGfuM2+jq252IwrGCCEboeeIe0upKm4nU/lAPderPimX/n3ps5oLJtXb7DZwKsMf//Mt/MUPbkNlgNthwe+/swvvOtloeE2gqllI0mTBIqXJ5B0Axd/Itlhq4XS0w+ns0BcpdThaIQjU3UsI2XvSsoSZW8MIDQ9hZmQQM6MjyKaMeYtgNqOhtUOfLG9s74TV7ijTEZO9hMLzErb7xHBh4Vu4NfoJwwIxVmsD2ts+QsH5ASInMojeVfsSmYkjIxdfrMhqN8Hd6IDX59RrXzyNDlio+uVgi04A47ne8onvA+n4ujs5oPF0rorlMcDXAwj074UUp6YVZMOSsYc8F5SzzAZT5E6zYXp8rW5FqLbRFPkeQ8EYIWQj9Bxx/xKKgluJFEZyk+pr3eqzqeJVZjwAQVagLKfBxTM456nAMw+14IynArFFDmUAAG6TSURBVOZN/m5VlBSSyfGCUF2WQyX3EW1NucoXrQLG4WyHw34YPE9XJxJCdo9EbEmbKM9Nli/cuQ2m3tVX7nCisbMrN1l+DHVHWmEyU185ee0oPC9hJ04MGVMQi11CKrUAq7UWLtdZqmohYIxhNSLrXerRUBzhUAKx+SRYqV5Fjy2/QGmuAsZVJ4Kn6pf9KZ0E7vww310eHTfe76jRpspbHwNa3gI46NIzkscYg7qazgfjC1rFSnYhCSVW/GoYAADPweSxGXvIa7Spct5OJ6H7BQVjhJCN0HPE1otlsvlFShMyBleTuBZLIlXiNN7McWi1W/Ueda0CxoaAzQJ+k1eoZrOrSCTGCkL1dDpcdHuOEyCKhw31L05nO0SxiV6/EkK2HWMMsbkZTA8P5ibLh7A0O1OwXWVN7boKlmPw+ALgeMpEyOtH4XkJdGJIdhslo2JpPoHIdH5CPTIdR6JEZYJg4lHdYNe61NcF6/YqC1W/7DWMAYsj+bB88hVAWRdy8iYgcD7fXV53AqCThAOPZVRkI1LBYp3ZRQksVfzqFgDg7SZDML72tcltA0dvyO17dP5DCNkIPUdsr+8ML+DDf38dM8syYOHxcK8PPSdqcSeV1qfVE0rxK8FEnl+3OGm+V73OYtr0uX86HUEiMVoQqmezq0W353krHPZWOJxtuT51rQbGam2g1xuEkPumKgoW7tzWFvcc0QLz5HLMuBHHwRto1sLyo8fg6+hCpbemLMdL9r/Nnv/QNf6ElJlg5uH1V8DrrzDcLicyBV3qkZkEsikF4WAc4WDcsL3VYcrXvjQ64PE74W5wwEL9w7uLFAMmvpfvLl+56/LaqkA+LD/8Zq3LnBw4jDGoiUxuelybIs8uJpEJS1CicvF1qQGAA0xubYrcVCvC7NU+m2rsEBw0RU4IIYTspGgijU98YxBfvapNUh7y2PHpJ07gwRbj1YMqY5iW80H62sT6aFKGpKq4uprE1dWkYZ8qk6AvTLp+Wt1tLjz3t1g8sFg8qK5+QL+NMYZUag6JxK27QvUxqKqM1fggVuODhu8jCE6t9sXZvi5Ub4fFQldDEkIKZWQZs2MjCA0PYXp4ELO3hpFJyYZtBJMJdS3t8Oemyhvbj8LmdJbpiAkpjibPCdlDmMqwEpG12peZOMLTCURn4lr1S4n/kyu9tnWLk2qT6lW1dvDUV7wzVBWYu5YPy4MXAbZuOliwAoceyneXe9sAmug5MJiiIhuR1/WQ50LyBQlMzpbcj7MJhpoV7bMIk0cEZ6IpclKIzn8IIRuh54itxRjDN6/P4ve/NohIIg2eA/71Q4fx1Fs7IFo2X4eSVRnuyCkMx/OLlI4kZNyWUlBKnPvXWkz5MD0XrLc7bHCaNvdzGVMgSUEtVDcsUjoBxoqfm5jNbi1MXwvVc59Npoqi2xNC9qfkyrKxr3xiHKpivDLWanegseOoPllef6QNJoulTEdMDjqqbSmBTgzJfpRNK1iaS66bVNem1ZMrJapfzDzcDQ5Dl7rH74S9kn5pbYn4IjD+shaYj78MJO/qmfS257vLmx8ELPbyHCfZMUoioy3YuWBcrDMblYBS63VygFBt0xbsrBFhqrXri3fyTjNdNk1eEzr/IYRshJ4jts78iozf++oN/PPQPACgvc6J5588iVMB15b9DFlRMS6lMByX9E714YSMoFz83B8AAjZLvvrFYUOnU0SLaIVtk9VtqppGMjlRUP0iSUGUuiTOam0w9Klri5S2QhBs9/OwCSG7CGMMywvzCA0PIjQ8iOnhISzNTBds53R74Os8Bn/nMfg6u+AJNIHnaU0FsjtQeF4CnRiSg0RaTedrX2a0z9GZOLLpEp2KFWa4G9ctUOpzwt3ogPk1TMgcSEoWmL6U7y6fvWq83+IEjjys1bG0PApUN5fjKMk2YwpDdknO95AvJLXAfDEJNbHBFLmFL1is01Rjh9lrA2em//fI1qDzH0LIRug54vVjjOGLfUF86ps3sSpnYRY4/LuHW/Frb2mFZYeuCotnFdzKBen5xUolzKeLn4cIHHBYtBqrXxw2HBatMG3yKlVFSRZZpHQUqdRciT14iGJTQahuFw+B56lijpDdSlUVLE7e0frKh7XJ8sRStGA7j79JX9jT33kMFd4aGvohuxaF5yXQiSE56JjKsByWEA0lEA7FEc11qccWksWHRjigqkbMTahrXeqeRicqa8SDXf0SCwLjL2lh+e3vA6ll4/313fnucv85wERT/fuFKmX1BTrXL9aZjUgoeQ01AKHKqvWQ6wG59jVfSYv9ku1H5z+EkI3Qc8TrMxVJ4kN/P4AfjUUAACf9VfjMk93orN8df5bRTDYfpse16pebCRnL2eILjVs4Dm0Oqx6mr4XrfpsF/CbPWTKZ5YJFSuPxEWSzsaLbc5wZDvuRgj51m80PjqNKOkJ2WiadwtzYLb2CZebWTaQlybANL5hQ19IKX0cX/Ee1vnKxYnc87xGyGRSel0AnhoQUl0krWJrNLUw6vTapHoe0mim6vcnMw924bkLd54DX54RYsU9D4owMTL2i9ZaPvQgsDhvvF91AyyNaWN7yCFBRV57jJFuCqQxKLKUF4wsSsmGthzy7mIQaL/7/BABwZh4mr5ifHl83Tc7TFRykjOj8hxCyEXqOuD+KyvBXr9zBH31rBFJGgdXE4z++rQO/9NBhCLt8yIQxhvl0FsMJaV2nujaxLqnFr1J1CPy6KfX8pHqNxbSpQQDGGNLpcJFFSkehKImi+/C8WGKR0loaPiBkC0mrKwiN3NRrWOZvj0NVjFetWEQRje1H4ctVsNS3tMFspRomsndReF4CnRgS8tokV9L5HvWZBCLTcURnE1AyJapfKi2GCXWPzwF3gwOmvRYcMgZExvNVLHd+CGTXvdPO8YD/bL67vPEUQN1te46ayhZOkC8mkQlLQLb0r0e+0gKzN9dDXpOfJheqrOB2+YtlcjDR+Q8hZCP0HPHajc6v4oNfHsCVqRgA4PxhNz7z3m4c8jrKe2Cvk8oYgnI6N6UuYySpTauPJlPIlIgO3GYBHQ4bOtYtUtrpsMFlNm3qZzKmQpZn9EVK9XA9MQ7Give4m0xVxkVKc6G62ey634dOyIHBGMPK4oJhcc/I9FTBdo5qtxaUd3TB19mFmuZD1FdO9hUKz0ugE0NCXj9VZVhZlBCejiMyE9crYFbCUtHqF44Dqmrthi51j8+BSo+4u4LG1Cow8YN8YB6bNN5f0ZCvYjnyMCBWl+UwyWvDVAZlJaUF42sLduYW71RKLKoLABA4fYFOUy4oN9eIMHlF8LbNvRgkZLeg8x9CyEboOWLzMoqK//bdcfzJy2NIKyqcVhM+/FNH8X+cDezrSsOMyjAhpfQe9ZFcuD4hpUqufV5vMWu1L878pHq7wwqHsLnwTVWzkKTJgkVKk8k7KLXiusVSawzVc4uUmkx7+00NQl4PVVUQCU5henhQ6ywfGUI8Ei7Yzt3o1/vKfZ3HUFVbR1d4kH2NwvMS6MSQkO2TSSmIziTWTaprFTByokT1i1XQptQbHXD7nPDmgnWbc4cWC2IMmL+RC8tfAqZeBdR1x8qbgeYH84F5bZf2TgDZldS0klugMzc9nvucXZTASlwpAQC802yYHl+rWxGqbbvrzR1CXgc6/yGEbISeIzbn+vQyfudL1zA8twoAeKSzFn/wnuNoqBLLfGTlIykqxpL52hetAkZCKFW65q7ZZkGnM1/70umwocVuhYXfXLe5oqSQTI4XhOqyHCq5j80WKFik1GE/DJ63vubHTMhul02nMTd+Sw/KZ0ZuIpU0ViPxgoDawy16BYuvowv2yqoyHTEh5UHheQl0YkjIzmKMrat+yQfrS7NJKNnigaa9ygKvzwl3bkLd43PCXe+AYN6CxYKSUeD2d3Ld5S8B8Tnj/dWHgNa3amH5oYcAq/P1/0yyZRhjUFfTev/4+roVJZYqvSPPweSxacF4rQiT164t3ukVwdt36M0aQsqIzn8IIRuh54iNyRkFf/ziLfzF929DZUC13YyPvesY3nWykaYyS1jNKhjJdagPJyQ9XF9MZ4tub+KAI6INnU4bOuy2XLhuwyHRCmGTf8bZ7CoSiTG9R30tWE+nF4tuz3ECRPGwIVR3Otshik3gOKqmIHuHHI9j5pbWVz49PIT58VtQssb/18xWGxo7juoVLA2tHTDbqK+cHGwUnpdAJ4aE7A6qoiK2ICESiiM6k0B4Oo7oTBwrYbno9hzPwVUrGrrUPT4nKjy2jV+0qAoQupyvYpm5DLB1ob3ZDhx6kxaWtz4KeFq2+JGS+8EyKrIRad2CnfmQnKWUkvvxdpO+QGd+klyEyW0DJ2zBmy+E7FF0/kMI2Qg9R5R24XYEz3zlOibC2tTmO0824mPv7ILHSRPL9yOczmIkF6aPrE2rJySslBiqsfEc2uy2/EKlTm1a3Wc1b/qNi3Q6ikRiVJ9Qj8dHkEjcQja7WnR7nrfCYW+Fw9m2rk+9A1ZrA71ZQnaFlfCioa88HJzUrqpex17lyk2UH4P/6DHUNB8Gv8nKJEIOCgrPS9iJE0NVVTE5OYl4PA6n04nm5mbwm7wEjZCDLi1n11W/5CfVU8niUypmm3BX7YsD7sokbDPf1cLy8ZcBOWbcqbYrX8XS9AbARC9+yoExBjWeKVysc1GCsiQX7c8HAPCAyS3qwfj6uhXBQVPkhBRDwRghZCP0HFFoVc7g+RdG8L9e1dbAqau04lPvPoG3dtWV+cj2H8YYZlOZfPVLLlwfTciQ1OInhE6B13vU16bUOxw21Fg2dy7IGEMqNZcP1fX6l1GoavFhHkFwwuloK1ik1GLx3vdjJ+RemKoiMj2lheXDQ5geHsRquPBqiuqGRjR2dMGfq2Fx1dOVMYTcC4XnJWz3ieHQ0BBeeOEFrKys6LdVVlbi8ccfR1dX15b/PEIOAsYYErF0rkM916UeSmBpNgFVKXFCzYfhNk3CY56ER1yE50g9qk/0QGh/FKjy7fAjONhYVkU2Kud7yBeS2iT5ggQmF39TBAA4m1DQQ26qtWtT5CZ6Q5KQ14KCMULIRug5wug7Iwv43a9cx8yyFqL+i3MBPPOTR1El0pv0O0lhDFNSOr9Aae5jLCkjWyLF8JhNeo96x7rPVebNLfbOmAJJmtYm1NeF6snkbTBWYpjH7C5YpNTpaIfJVHG/D50cYNlMBvO3xxAaHkRoeBAzIzchJ+KGbTiOR+3hI4a+coerukxHTMjeReF5Cdt5Yjg0NIQvfvGLJe9/3/veRwE6IVslOgFl9CXErl9GdGIeYbkO0WwzIplmrKq1RXfheQ6uejs8a13qjU54/E44q630rvwWUBKZdT3k+U7ybFQCSq3XyQFCtU0LxvW6Fe1r3rn5y3EJIRujYIwQshF6jtAsJdL45D8M4StXtIUnm9x2PPfECTzYSpPFu0laVXFbSmE4bqx+uSOlS1642Gg156tfctPqbXYb7Jus9VPVNJLJOwWhuiRNodTlklZrQ5FFSlshCNQzTfJSyQRmbg3nwvIhzI3dQjaTNmxjslrR2NaBxo5j8HceQ0NbOyyivUxHTMj+sdnzn829/UruSVVVvPDCCxtu88ILL6Czs5MqXAi5H+kkcOeH+e7y6DgEAB4AHjPQ5qoBWh4FWo8g1XgM0ZgVkZl87UsklEBa0iphojMJjF7Kf2uLaIKn0aGH6tpCpU5YRXqKvBtTGLJLsjY9flfdilqiWgcAOIugL9Cph+S1dpg8NnBm6t4jhBBCSPkwxvCP1+fw+1+/gXA8DZ4DfumNh/HU29pht9D54G5j4XktAHeIhtuTiorRpIzheL76ZSQhYyaV0T++E833nHMADomW3PfKTao7bWgRbTDzxgEOnrfA6dRqWtYX9yiKhERirCBUT6XmkErNIpWaRSTyvfXfCaLYVBCq28VD4Hm6suEgiEcjmM4F5aHhQSxO3SnoKxcrKrWJ8txkee2hFggmei4ipFxo8nyLTExM4K//+q/vuV0gEEAgEIDH44HH44Hb7UZFRQVNVxJyN8aAxZF8WD75CqCk8vfzJiBwPt9dXncC2OCNKcYY4kspQ5geCcURm0tCLdWl6LbmAvX8pLqr3g7hACw8qUrZgh7y7GIS2YgMlKjKAQDBZS3oITfXiOArLfQ8R0gZ0VQpIWQjB/k5YmFFxu999Qa+PTQPAGirdeL5J7txuokqEPaL5UxWn1Bf+3wzISGaKb4IvZnj0GK33lX/IqJJtEDY5PlsJrOSD9QTtxCPa58zmaWi23OcGQ77kYI+dZvND47b/6899ivGGKKhaYRGBvXFPZcX5gu2q6qrh7/zmNZZfvQYqht89NqJkB1AtS0lbNeJ4fXr1/HlL3/5vvY1m81wu92GQH3ta7vdTk+a5OCQYsDE93KB+cvAyrTx/qqAFpS3PgYcfjNge/3/DytZFbH5ZEGoHl9KFd2eFzhU1zu0MH1dsO5w7b3qF6YyKEsyMmEJ2QVjSK7GMyX348w8TN5c/7hXhLk2N03uFcFbaIqckN3oIAdjhJB7O4jPEYwx/F3fND75zSGsylmYeA7/7i2t+LW3tMBqovOZg2AxncnXvqybVo8rxfsGRZ5D2/rql9zXDdbNVQ0yxpDORJCIj6ybUh9FInELipIoug/PiyUWKa3dc689DgIlm8HCxO38ZPnIEOTVFcM2HMejpvlwfrK84yicbk+ZjpiQg43C8xLKPXl+7tw5AEA0GkUkEkEsFsNGfwVWq7UgUF/7WhTFkvsRsieoKjB3LReWvwQELwJs3QSIyQY0vzEfmHvbgB06SZQTGUTvqn2JzMSRkYtPqFjtJi1Ib9RqX7x+J9yNDlhs5b+8Tk1lcxPkxpqVTFhCydWWAPCVlru6yO0w1YoQKq3geDpZJ2QvOYjBGCFk8w7ac0QwmsSHvnIdPxwLAwC6/VX4zHu7cbRh/z92sjHGGEKpTC5Qz1e/3ErKSJW4WrXSxBurX3LhumeTlT+MqZDl2SKLlI5BVdNF9zGZqoyLlOZCdbPZdb8PndyHtJTU+spHhhAaHsLs6AiyaeMQlslsQX1bO/ydx+Dr6EJD+1FY7dRXTshuQOF5Cdt1YqiqKj73uc9hZWWl5DaVlZX4rd/6LUPneTabRSwWQyQS0QP1ta+Xl5c3/Jl2u10P0u8O161W65Y9NkK2VHwRGH8ZGH9JC8yTYeP93vZcWP6oFpybd8+bRIwxrEbkgi712HwSrMTJdIXHlq998Tm16pc6EfwWV78wlUFZSSG7YAzIs4sSlJXiJ90AABMHkyfXP76uZsXkFcHvguCfELI1DlowRgh5bQ7Kc4SiMnzhx3fw/AsjkDIKrCYe/+Ft7filNx6G6QDU8pH7pzCGO1Jq3ZS6FqqPS3LJRsMai0mfTl8L19sdNlRs8soGVc1CkqaKhOoTAIpPx1sstcZQPbdIqcnkuM9HTtZLxJb0hT2nhwexeGcCjBn/LmzOCm2qvKMLvs4u1B1phWCiPntCdiMKz0vYzhPDoaEhfPGLXyx5//ve9z50dXVt+vtlMhlEo1E9VF8frsfj8Q33dTqdRafV3W43zGZ64iY7SMkC05fy3eWzV433WyqAIz+hheUtjwLVzWU5zNdDyahYmk8gMp2fUI9Mx5FYLh5aCyYe1Q12eBqdhmDdXnXvXnA1rSAbzk2OL0ja1wtJZMMSWKb4STQA8E5zPhjXJ8lFCNU2miIn5AA4KMEYIeT+HITniLGFVXzwSwO4PBUDAJw77MZn3tuNw14KFcn9S6kqbidzoXoiV/0SlzEplx5e8VnNWpjutOnheqvdBnGTb+AoSgrJ5O2CUF2Wp0vuY7MFChYpddgPg+dp6K4UxhiWZmdyfeVDCI0MIjY3W7BdZU0dfJ1d2mR5ZxfcjX5wG6zFRQjZPSg8L2G7TwyHhobwwgsvGCbQKysr8fjjj7+m4PxeUqlUQai+9jmZTG64b2VlZdFp9erqaphoBWeyFZantanysReB298DUnddRVHfna9iCZwDhP35ho4cz2hB+rou9chMAtlU8eoXm8MMj88Bd6MDNR4RVaIAu8qAWEqfJldixbvYAQACB5PHViQkt4MX6f9tQg6ygxCMEULu335+jsgoKj7/vXH855fGkFZUOK0mPPOTnfiX55rA0wAB2SaJrIJbyZTeoz6Sm1afSxdfV4gHcFi0otOZX6C002HDYdEK8yb/nWazcSQSYwWhejq9WHR7jhMgiocNobrT2Q5RbALHHbzef1VRsDAxrlewhEaGkFyOGTfiONQEmuE7eiw3WX4MFR5vWY6XEPL6UXhewk6cGKqqisnJScTjcTidTjQ3NxuqWrabJEkFFTBrn2VZLrkfx3FwuVxFq2CqqqogCAfvFyjZpIwMTL2SD8wXh433i26g5REtLG95BKioK89x7gJMZViJyFqQHlxFfHIVmfkEuNU0nDwHJw9UCBxMG02g2wRY6hz5HvKa3OKd1TZwAr0IJIQU2s/BGCHk9duvzxE3Qsv4nS8N4OasNtj0lo4a/MF7TqDRtXtqAcnBspTJ5hcpzfWqjyRkLGWLD9dYOA6tdis6nfkFSjscNgRsFvCbXAsqnY4ikRjVAvXELcTj2udstnjlLM9b4bC3wuFsW9en3gGrtWFfLVKaliXMjo5oQfnwIGZHR5BJGfMSwWxGfUt7bnHPLjS2H4XN4SzTERNCthqF5yXs1xPDzWCMIZlMFp1Wj0QiyGSKvwsOADzPo7q6uqACxuPxoLKyckffHCC7AGNAZDzXW/4iMPEDICvl7+d4wH82313ecArgD+abL4wxqPGMVrOSW7Rz7WtlSQZKPAMzAEkGrGRVxBWGuMoQV4C4ypBmgGDm4W5wGLrUPX4n7JWWHX18hJC94SCf/xBC7m2/PUfIGQWfe3EUf/GD21BUhmq7Gb//zmP4mVON+yr8I/sDYwyL6Wy+9mVduJ5Uitcy2gUe7fZ87YtWASOizmLa1L9xxhhS6Xl9Ol3/nBiFqhYfuBMEJ5yOtoJFSi2WvTF5nVyO5abKtc7y+YlxMNX452t1OODr6EJjh1bDUnekFSYLvb4iZL+i8LyE/XZiuFUYY4jH40Wn1aPRKLLZbMl9TSZTQbC+9nVFRQWdoO4XqVUtJF/rLo9NGu+vaNCC8tbHgCMPA2J1WQ6zXFhWRTYqI7uwFpJrNSuZxSSYXHySBAA4m6At1unVpsfNuc8mtw2ciYe0ms7XvuS61KOzCWTTxU+kxQoz3I1OeH1OuHPBurvRAbPlYL55QQjR0PkPIWQj++k54uJEFM98eQC3wwkAwE93N+Bj7zoGr5O6ncneojKGaTmtL066Fq6PJlJIl4hxXCZBn05fP61ebd5chSNjKiQpWGSR0ttgrHgmYDa7CxYpdTraYTJV3Pdjf70YY1ien8N0LigPDQ9iaTZUsJ3T4811lWt95V5/E/WVE3KAUHhewn46MdwpqqpiZWWlaBXM0tISVLX0IoVms7notLrH44HdbqdgfTdjDJi/ka9imXoVUNddnSBYgKY35LvLa48CB+DvU0lkDMF4dm2aPCqVWvQe4ACh2lbQQ26qEcE7za/5/wOmMiyHJT1Uj+a61GMLyeKT7BxQVSPmJtQd8Pi1SfXKGpG6Pgk5IOj8hxCykf3wHBFPZfGZfxrG/3pVG/CorbDiU+8+jrcdqy/zkRGytbIqw4SUMkyqjyRk3E6mSr4cqbOY9B71jtxCpR12GxymzQ3YqGoayeSdglBdkqZQ6lJaq7WhyCKlrRAE2/098A2PT8HinQltsvzmIEIjQ0jElgq28/ib4F/rKz96DJXe2i0/FkLI3kHheQn74cRwN1EUBcvLy0WrYGKxGDb652W1WotOq3s8Hogi9RCWRTIK3P5OLjB/CYjPGe+vPpwPyw89BFj3Z98bU/7/9u48PrKyzhf/55w6tZ9UKpV9604nnU46zabQrCqiKFxZlKsXhjsOjMOMd5TRy+B63RhkdEDhN6jDdUZU3IVxA2HmtjO0gIwioIDSnc7SS7o7WyepqlSl9jrnPL8/qlKVqjpVHZrs+bxfr7zSqTqn6hzoPnmeb33P5xHQAvFcYTxfJI/BiJW/C0OyWaA0ZAvjdc78n2udkKzL38GQTukITmQXJh2N5hYrjc+ZRzIpVhm+lmzsS6uai4BxVvHWRKKNhuMfIqpkvV8jnhycwid/tg9js5kYwevOaccnrtiJaufGXJSeyExCN3AonsRApDD65XgiVXafdoctH/2S7Vbf7rLDvsjua12Pmy5SmkxOltlDgtO5taSo7nJ2QJYX/+81nUxg8uBQrrN8YngAqXi8YBvZoqCpqzubV74LLT074VRXrxueiNYeFs/LWO8Dw/VE0zTMzs6aRsGEQqGK+7pcLtNudZ/PB7udt1wuGUMHxl7IZ5eP/R4QC/oVrC5g2xvyC33Wdq3esS4DI5ZGeiYObSoObSaG9FQ2biWQAPTyl0aL1164WGe9C9YGJ+Qq25q8myIWno9+ieS71Sei0NNlol88NtS1uuHLZqnXtamoaXJBYfQL0brF8Q8RVbJerxHBaAp3/Fs/fvpCJo6h3efEnf/9DFy0fX1kMBOthIimY2jhIqXZbvWplHlTkEUCOp32TPRLtlu9V3Wgw2GHssi7VtPpcL6gvmCR0nS6tBscACTJCrersyRP3eFogyTJiIVDGB88kMssP3H4EAy98PhtThdaenZmYlh6+tC4vRtWG2sHRFQei+dlrNeB4UaTTqdzeerFxfVIJFJxX1VVTaNgfD4frFZ2l5zU3GQ+iuXwE0C8aADT0JfPLt9yAaCs7wGHMAT0YKIkh1ybjsOIlF8kV7LK+cL4grgVpc4JeQMUkQ1DIDQVy2WpB8aimBmLIDwTN73zUpKA6gZXfoHSbKe6p9YJidEvRGsexz9EVMl6vEb8+8sT+Mwj+zATSUGSgPdcuA0fvmwHXLbFZTsTbXb+lJbNUo8X5KqHNPP1muyyhO7sIqU9CzrV2+yLi6EUQiCV9iMaGVzQpT6MaHQIuh4138dQkAq7EJmUkAjYkQjaEQ/YocUUqDW1uazy1t5dqNuyFbK8/udpRLRyWDwvYz0ODDebZDJZEgEz/z0Wi1Xc1+PxmHar19TUQFE26UBaSwHHf5uPYjnxcuHzjmqg85J8d3l16+oc56tkJLVsYTwObSoGbSaO9FQMmj8OaBW6yD22zAKddc5MkbwhUyS3eOybsiicTuoIjEfzXerjmQiYRLRM9IvdkslRX5ClXtuqwqHygyyitYTjHyKqZD1dI6bCCXzmkf3Ysz8TC9HdoOKud52B127ZXIvVEy0HIQROpLRMQT2S71YfjCYQL7PWmWqRc8X0hd3q9TZlUUV1Xdcwcfh5jB1+CsGZPyCeOgLFHYbDm4KsmM/jLJYqqGov1IJO9W5YrbwOENHisXhexnoaGFKpeDxu2q3u9/uRTCbL7idJErxer2kUTHV1NSyWDfYJdXAk01l+cC9w5FdAamE3vwS0vCafXd56NmBZHx8sCENADyVLcsjT03EY4fJZflAkWOtKF+tU6p2Q7evj3FeTECIf/bIgSz04EYOumQ+i3dU21Laq8LWquQgYX5MblhXIfieiUhz/EFEl6+EaIYTAj34/ir9/rB/hhAZFlvD+N3bh5jdth32Rix4S0akxhMDxRCpTTI/ku9UPxpJIlykp+ayWwuiXbHFdFQYmDw7lIljGhwaQjBV2nssWCxo7O9GyqwU1W+1w+BJIpY9lFykdgRDm3fE2W0MuR33hIqWK4l7y/yZEtP6xeF7GehgY0isnhEAsFispqM//OZ0uH88hyzJqampMo2A8Hg/kRS6WsqpSMWDkv/LZ5f6Dhc+76/PF8s5LAHft6hznIhkpvaAwPh+3os3EIcrkdAOArFpz+eNKnSu3YKfFuzm7yJeboRuYnYrDPxZBYDyKmdEIAuMRhGcSpttLsgRvg3NBh3omAqaq1rEms+KJNhKOf4iokrV+jTgeiOETP3sZTw/PAABOb63GXe88A30ta+9YiTaTtCFwOJ7MdarPR78ciSfNkiABAFXRMGr9k6gLTKE+eAJ1gRNojEfQ0dmViWDp2YXm7h2w2h2m++t6ErHY4ZJFShOJ0bLH6XC0lyxS6nZtgyyv74hSInp1WDwvY60PDGnpCSEQiURMu9UDgQB03fxTawBQFCVXWC8urldVVa1ewU8IYHow213+OHD0N4C+oPNeVoD28/LZ5Y2nA2vsQwAhBIxwakEHebabfCoOPVT+LgJYJCi1jmwWeb6D3FrvguxkF/lakEpoC6Jf8hEwyZj5okRWRzb6ZUGWuq9FhcPN6BeipcLxDxFVslavEYYh8J1nRvCFXwwiltJhV2Tc+pYduOl126BY1tbYlogywjNTOHygH787MoKX/UEcERbM+Box42tEuMpruo8EYKvTlu1Qd+ZiYLpcdtgWOY/VtAii0YMlRfVUatr8PSULnM5tBUV1Vd0Bp3MLJIl3sxBtBiyel7FWB4a0OgzDQDgcNu1WDwaDMMrkugGA1Wo17Vavra2Fy+Va+sJ6fBY48lQ+uzxc9Ml6dXu+u3zbGwDH2vj7LdIGNH82f7ygmzwOkSr/wYXsVjIxK3VOWBtcucU7lRoHJAu7lNcbIQSis6mSLPXgZBSGbv5rSK2xw9eioq4tU0yvbVVR0+SCReFkmeiV4viHiCpZi9eIg1Nz+NhPXsbvj2YWtz+3w4c733k6OuvVVT4yIponDAP+0WMYHchEsIwN9GPOX1qsrmluRWvvLlT37EJs63aM2d0YjCVyueozafMmG0UCOp0O9KqOXPRLr9uJrU4bLIucb6dSAUSjw5mCenQIkUjmu6aFTbeXZRvcrm641e4Feeo9sNubebcs0QbD4nkZa3FgSGuTrusIhUKm3eqzs7Oo9E/HbrebdqvX1tbC6XQu7gAMA5j8Qz67/PhzwMJsN8UBbL0oXzCv6wZW6Ze5EAJGJJ0vjM8v2Dkdhx5MoOw9ezKg+Jy5wnhuwc46JyzsOt4UdN3A7IkYAmNRzIxFEMh2q88FzKNfZFmCt8mV61Cf71ZXa+wczBJVwPEPEVWylq4Rad3A1351GF96fBgp3YDbZsHH37YTf3ruFsiM4SNaVVo6jROHhnN55WOD/UhGC/PKJVlG47Z8BEtrbx9c1d6KrzudSuciXwazueqDsTjCZdZXcsgSdrgc6FELM9Vb7NZFzQmEEEimTuS603Pfo8MwDPN5iMWiQnV35/PUs53qNlvdSd+PiNYmFs/LWEsDQ1q/NE3D7OxsSbd6IBBAKBSquK/L5SroUl9YXLenw8ChX2azy/cCsZnCnet2ZIvlb84Uzq2LLMQvEaFlusgzESv5LPL0dAwiUb6LXHIomRzy3IKd2T/7HJDYRUwmknEtU0gfj8I/mu1UH4siFTfvSrE5lUwxfUGWuq9VhZ1RPkQAOP4hosrWyjVi31gIH/3xH9E/kekIfWNPPT53zelo9a7smJeIMhLRCCaGBjCa7SqfPDQEvWg9McVuR0t3b6ZY3rsLzd09sDle/b9ZIQQmkunMIqXR/CKlw9EE4oZ5GavKImeK6aojF/3S63aizra4OYEQBuLx4wXRL9HoMKKxwxDCfB01q9VXskip6t4BRak65XMnopXB4nkZa2VgSBtXOp1GIBAwjYKJRCIV91URRS2C8CGIWszCpyRR294NX+9FsO54C1CzdUXOQY9musi1qTjSM5nv2nQMWjABlEuykQBLjSNfGM/mkCsNTsjuxXUAEFUihEAkmMxHv2Tz1GcnYzDKDKBVnx112UL6fHHd2+SChTmptMlw/ENElaz2NSKR1vGlvcP42q8OQzcEvC4rbruqD+84q5VjSKIVNBeYwdiBTEf52IH9mD5+NLPe1gJOTzVae/rQtnMXWnv6UN/RCYuycg0ruhA4Fk/liunzX4diCWhlqlu1ViUf+6Lmc9U9yuKyzQ0jjVh8BNHIYEGnejx+DOVus7bbmwsXKXV3w+3eDouFHwYSrRUsnpex2gND2tySySQCxw7AP/BrBI4NwO8PwG+4EYAXMbgq7uvxeEy71WtqaqCcwmBF6Aa0QKIkh1ybjsEos7AjAEh2S74wvjBupdYJycqCJK08XctEv8yMRhAYzxfVI0HzhWdli4SaJndB7EttqxtuL6NfaOPi+IeIKlmJa4RuCDx3JICpuQQaqhw4d5sPFlnC8yMBfOzHf8ThmUz0wxVnNOP2q3ehTrUvy3EQUYYQAoGx4xgb6M91loenT5Rs521qzsWvtPbuQk1zy5ocM6cMA4diyVz8y3xx/Wg8VTZFtNVuzXaoO3O56t0uB5yLbLTR9XjhIqXRYUQiQ0gmJ8rsIcHp3FLYqe7eAZdrG2SZsaVEK43F8zI4eaQVl04Ax36TXejzcWB6oPB5pw/oehPiWy5BoOZM+OOiJGc9mTQvAgKAJEnwer2mUTDV1dWQkgbSM/Fc93gubsWfAMp06wKAxWuH0uCCtc4JpSFfJJerbGtysERULBFNIzAeLexUH48gXSZiyO5SMoX0Fjdq2zJFdV+LGzYHo19o/eP4h4gqWe5rxJ59E7j90X5MhPJZwo0eO3Y2efDU8DSEAOqr7Pj7d5yGy3Y1Lfn7ExGga2mcOHwol1U+NngAibnCRTMlSUZ9xza09vahrXcXWnr6oNb4VumIl0ZMNzCcW5w0nstVH0+ax7BIALY57eh1Z6Nfsp3qnU47rItcdyGdDiMaGy7JVE+nA+bvKVnhcm0rKao7ne2QJDaoES0XFs/L4OSRlp0QgP9QNrf8ceDI04AWzz8vyUDb7nx2efNZgFz+djEhBGKxmOnCpX6/H+m0+S99AJAhocpwwiNcqBbz312oNlxwww7ZainsHp/vJq9zQrYt7hY2ovVECIE5f6IkS332RAyizIdJnjoHfC2FC5R6G5yQGf1C6wjHP0RUyXJeI/bsm8D7vvdC2c5PALjunHZ84m07Ue1i5yXRUknGYpgYOpBd3LMfEweHoKUKm7IUmx3N23egNRvB0rKjFzZn5TuiN4pQWlvQpZ7vVg+kzRttrJKELpc9H/+S7Vbf4rBBXmRzWSo1g0hkqCBTPRIdhq6bx7vKshNu9/aSTHW7rZENbURLgMXzMjh5pGWRnMsUyQ8+nvmaPVr4fFVzplC+/VKg842As+aU3sZIaLkFOrXpONJTUYSmZhEIBhASUYSlOEJSDGEphrAUhy6VCygHFIuCGl+NaRRMVVUVfxnTpqKnDQQmo5lFSsfy3erRUMp0e4sio6bZle1UzxbW21S4PLwzg9Ymjn+IqJLlukbohsDr7vplQcd5MZ/bhuc/eSksi+zoJCJzkWAAYwP9GBvcj7ED/Zg+egRCFM4HHVUetPb05TrLG7Z1wqLwQ6t5QgjMpLVsl3php3pEN59bO2UZO9z2TDF9Qa56k21x634JIZBMTiASGVxQVB9GNDYMwzCfiyiKJ5OlviBTXVV3wGo9tToD0WbF4nkZnDzSkhACOLEvH8Vy7LeAsaAD3GIDtlyQ7S6/FGjYCSyyoCYMAT2UzBbHY9Bm4tCmMnErxpz5L08AgCJnIlbq818xp4aQFEMwPFvQrR4MBmEY5QvrVqu1oKC+8M8ul4vFQdo0EpF0ppC+IEvdPx6FljTvSHG4rQUd6r5WN3zNjH6h1cfxDxFVslzXiGcO+XH9/b896XY//KvzcUFX7ZK9L9FGJ4RAcGIsUyzP5pXPnijN2a5uaMwUy3fuQmvPLvhaWiHJvHvylRJCYCyZzhTUI/mC+lAsgWSZu1erFUs++sWdX6S01ra4eYFhaEgkjiMyH/0SHUIkMoR4/AiEMJ+L2Gz1JdEvbvd2KIp6yudOtJEtdvzD2TzRYsUCwOEnsgXzvUBksvD5mm35YnnH6wB75V9QRkovWqwz002uzcQh0uUL23KVtXSxznoXLF47pKKOHTeAepPX0HUdoVDINApmdnYW6XQak5OTmJycLNnXbrebdqvX1tbC6eTK4bSxOFQrWntq0NqT7+IQhkDYnyjIUg+MRzB7IoZENI2xoVmMDc3mX0QCPHXOTJb6ggVKqxtckNllR0REG9jUXPmO81PZjmiz0jUN0yOHcwt7jg32Ix4OFW4kSajf0oHW3vnFPftQ5atbnQPeYCRJQpvDhjaHDZfW5gtsmiFwNJHMFtXz3eqH40mENB3PhqJ4NhQteK0Gm1JQUJ8vsKtKYWyqLCtwubbB5dqGBlyWe9wwkojGjuTz1LNF9UTiOFKpaQRS0wgEf13wWg5Hm0lRvROyzIWZiRaDnedE5Rg6MPZCPrt87PfAwtverC5g2xsyxfKuNwG1XSUvIYSAHk7lCuP5TvI49FD5RUBhkaDUOgtyyK0Nme/yMnewapqG2dnZkmx1v9+PcDhccV+Xy2Xare7z+WC38xczbWxaSkdwMgb/WAQzY5FcBEwsXCb6xSrD1+wu6FSvbc1EvxAtNY5/iKgSdp4TrS2pRBwTQ4OZCJaB/RgfHoSWLJw/WqxWNG/vyRTKe/rQ0rMTdpd7lY6YFkoaBg7FkgWd6gPRBI4lyt9J3uawFka/uB3Y7nLAsch1ljQtimjsYMkipanUlOn2kmSB09lhskjpFsgy+2xpc2BsSxmcPFJFc5P5KJbDTwDxYOHzDX357PItFwBKpiAs0jrSM4l8kXy+i3w6DpEyv6UKAGS3NVMYz3WSZ/5sqXFAsqy9jtR0Oo1AIGC6cGkkYr7IyTxVVU2jYHw+H6xW5uzRxhWfS+U61Oe71QMTUWipMrmJVVb4WlTUZWNfaltV+FrcsHIRX3oVOP4hokqWO/N8MpQwXTBUAtBU7cB/fexNzDynTS06G8T44IFcZ/nUyCGIophNh1tFS8/ObGf5LjR2bofCedS6EtV0DMWS+Sz1bLf6ZCptur0MoNNlL+lU3+a0Q1nkNTOdDiISGS5apHQQmmbeGCfLNrhc20uK6g5HC+NbacNh8bwMTh6pgJYCjv82H8Vy4uXC5x3VQOclwPZLITovgWFpyHSPF8Wt6LNJmM4IAEAGlFonlDonlIZ8zIpS54TFvXEGO8lkMldILy6ux2Kxivt6PB7TbvWamhooCj/1po3HMATCM/F87Eu2Wz00HTe/lkhAdb2zIPaltkWFp97J6BdaFI5/iKiS5bxG7Nk3gfd97wUAhb/i5n97ffXdr8XlpzUv6XsSrWVCCMyemMDYgf0YG8xklgcnxku2q6qrR9t8BEtPH2rbtjCvfIMKpjUMRhO5DvX5bvVZrUy2uSShO7tI6XxhvcftQLvDBnmRi5SmUlOIRIaKiurDMIy46T4Wiwq3uxuquztfVFd7YLPWsqhO6xaL52Vw8kgIjmQ6yw/uBY78Ckgt7JiWIJrPgdZ8BbSq85E2mqH5k5ki+VQMoswigQAgORRYGxbErMx3k/sckJTNPciJx+Om3ep+vx/JZPn4GkmS4PV6TaNgqqurYbGwE5c2lnRKR3AiipnRCAJj0exCpRHE58y7URTbfPTLgqJ6qwpnFaNfqBDHP0RUyXJfI/bsm8Dtj/ZjIpTPNm+uduC2q/pYOKcNz9B1TB89grGB/bnO8lhotnAjSUJd+9bM4p7ZvHJPXcOqHC+tDUIITKW0XI76fK76YCyBmG5+B6vLIqPH5UCvWtip3mBTFlXgFsJAIjFaUlSPxg5DCPP5iNXqyxTV1UyH+nynutXK8SatfSyel8HJ4yaUigEj/5XPLvcfhBCAAQ800QbNuhPpqvOgWbqgxaugBVPlu8glwOJzZArjdU4oDfkiuey28hPXV0gIgVgsZtqt7vf7kU6b/4IGAFmWUVNTYxoF4/F4ILMrgzaQWDi1YIHSbLf6RBR6mcWFnR4b6lrd8LWqqG1RUdemoqbZBcXKD5w2K45/iKiSlbhG6IbAc0cCmJpLoKHKgXO3+RjVQhtSOpnAxPAQxgYyneXjQwNIJwq7eS2KgsauHWjt7UNb7y607NgJh6qu0hHTemIIgdFEKhP7Es0vUjocTSJVprxXo1gyHepqPlO9x+1AjXVxd3kbRhqx+EjJIqXx+FGUK57Y7U0mi5Ruh8XiPNVTJ1pyLJ6XwcnjJiAEMD0IHHwcYviX0EYOQ9MaoIk2pEUbNNEODVthGOUv2pLdUpRF7sp0ldc6N30X+UoRQmBubq5sFIyul78LQFGUXGG9uLiuqio/5KANwTAEQlOxTJb6eAT+0Qj841GEZ8yjXyQJqG5wFXSo17aq8NQ6ILF4seFx/ENElfAaQXTqYuFQNn6lH+MD/Thx5CCMormKzelCay6vvA9NXTug2HinIC0dzRA4Ek8WdKoPRhM4HEvCvN0GaLJZM4V01ZGPf3E54FYW13Cj63FEY4dKiurJ5ESZPSQ4nVtKiuou1zbI8saJtKX1g8XzMjgw3JiMwAzSLz8LbWgQ2oQf6UR1pqtcNAMo82mqBFi89kxhPLtYZ+bPLshV7CJfywzDQDgcLiiqz38PBoMwjHLDA8Bms+UWKi0urrtcLv5/p3UvldAQmIhmYl8WdKonomWiX+wW1La4C7LUa1tVOFQOYDcSjn+IqBJeI4gWRwiB8PQJjM7nlR/Yj8D4aMl2qq82Vyhv692F2vYtkGXeAUgrL6EbOBhbkKeeLa6PJsrf5b3FYct1qM93q3e57LAv8u5uTZtbkKOe/55OB0y3lyQrXK5tJUV1p7MdksTmRVo+LJ6XwYHh+iUMAT2YyOSPn4hCOzaK9HgAWtgCQ3eX3U9SAKXBnS+SN2QjV+qckG0cwGw0uq4jFAqZdqvPzs6i0iXPbrebdqv7fD44nby9jNYvIUQ++mU0n6UemIjC0Mz/TbirbahtVeFrVXMRML4mNyxWDmDXI45/iKgSXiOIzBmGjpljR7N55f0YH9iPSLC0AFjbtiWTV75zF1p7+uCpb2BTDq1pEU3HUFFBfSCawFRKM93eIgGdTnsuR30+V73DaYdlkX/XU6kZ00VKdT1iur0sO+F2by8sqqs7YLc18t8XLQkWz8vgwHDtMxIatOk40tMxaNNxaNOxTMF8Jg7o5f+6WixBKB4dSnMNrNu2QWnyQKl3weKxMZKAAACapiEYDJpGwYTD4Yr7ulwu0251n88Hu92+QmdAtLQM3cDsVLwwS308gvBMwnR7SZbgbXTlO9TbVNS2uFFV6+AAdo3j+IeIKuE1gigjnUrixMHhzMKeg/0YHzyAVDxWsI1sUdDY2ZXtLN+F1p6dcFbx3w1tDP6Uls1Sjxfkqoc089hUuyxhh2tB7Eu2W73Nvri7+YUQSCYnEIkMLiiqDyMaG4ZhpEz3URRPZnHSBYuUquoOWK01r+rcafNh8bwMDgzXBmEI6LPJfGE8WyhPT8dhzJlfIDOSsErjUKTjUJRpWJuroWzfAeWMCyE3blux46eNJ51OIxAImC5cGomYfxI+T1VV0251n88Hq5XRF7T+pBIaAuPZ2Jdslrp/LIJkzLwTxeqwZONe8vEvvhYVDjf//q8VHP8QUSW8RtBmFY/MYTybVz46sB8nDh2EoReOd2xOJ1p27Mx1ljd1dcNqd6zSEROtPCEEJlNpDEQKO9WHognEDfOSomqRcwX1hd3qdVZlkUV1HfH4MURKFik9AiHMC/k2W73pIqWKwsV4yRyL52VwYLiyjKQObSZeWCSfiiM9Ewe08rnUshKFVRyFghEo0iis0igUaRSW5mZI3W8Gtl8KtJ8LWFiYoeWXTCbLLlwai8Uq7uvxeEyjYLxeLxRlcaubE60FQghEZ1P5LvXxTARMcDIKo8xdQWqNHb4WFXVtmWJ6bauKmiYXLFx4ecVx/ENElfAaQZtFeHoqG8GyH2MD/fCPHivZxu2tyXeV9/ahfksHZAvjPomKGULgWCKFgUiioFv9YCyJdJlSo89qyRfTF3SrV1sXNzc2jCSisSMli5QmEsfL7uNwtJkU1Tshy7yDfLNj8bwMDgyXnhACejgFbSpWEreihyp0kVskKLUOWF1RKOIIlLlnYY38Doo0ClnKFiSdPqDrTZliedebgKrGlTkpokWKx+OmC5f6/X4kk8my+0mSBK/XaxoFU11dDQsH6LRO6LqB2ROxfOzLWAQzYxFEAuZ//2VZgrfJlV+gtDVTVFdr7Ix+WUYc/xBRJbxG0EYkDAMzo8cwNr+450A/5vzTJdvVtLShrbcvG8HSh+rGJo5JiF6FtCFwOJ7MFNMj+eiXI/EkyhUgW+zWgk71HrcDO9wOuCyLXaQ0imjsYMkipanUlOn2kmSB09lhskjpFsgym9w2CxbPy+DA8NSJtJ7LHtemYkjPxHNFcpGq0EXutkKpd8Ja74JS74BiD8EaeQ6WiT2QRn4FaPH8xpIMtO3OFMu3vxloPgvgquS0DgkhEIvFTLvV/X4/0unyq5vLsoyamhrTKBiPxwN5kaucE62mZFxDYEGWemaR0ihScfPoF5tTyWepZ4vqvlYVdicHr0uB4x8iqoTXCNoItHQak4eGMDbQn4liGexHMhot2Ea2WNCwrSsTwZItmLs81at0xESbS0w3cDCWjX2JZDrVB6MJjCXN58YSgK1OW0H0S4/bgS6XHbZFzonT6SAikeGiRUqHoGkh0+1l2QaXa3tJUd3haOGHahsQi+dlcGBYmRACxly6dLHO6Rj02STKfkwoZ7rIlXpXtlDuhFLvgrXeCdmSAI48DRx8PPM1e7Rw36rmTKF8+6VA5xsBJxd5oI1NCIG5ubmyUTC6bp7hBgCKouQK68XFdVVV+Qud1jQhBCLBZMECpf6xCGYnYzDK5SX67KjLFtLni+reRhcsi+xCoQyOf4ioEl4jaD1KRCMYHzqAsYF+jA3sx+ShYehFDSpWuwPNO3rRlo1gad7eA6uDeeVEa0lY03OxL4O5wnoCM2nzphtFArpcjoLol163E1ucNlgWuUhpKjWFSGSoqKg+DMOIm+5jsahwu7uhurvzRXW1BzZrLefg6xiL52VwYJghNAOaP470VBzaTDaHPFswF8nyhTvJqeQL4w1OKHUuKA1OKD4HpPlChhDAiX3Awb2ZYvmx3wLGgkGMxQZsuSDbXX4p0LAT4MWGCABgGAbC4bBpFEwwGIRhlL/Lw2az5RYqLS6uu1wu/lKnNUvXDAQnM9EvgfEIZkajCIxHEAmWiX5RJNQ0ulHbNt+pnvlye238e14Gxz9EVAmvEbQezPlnsnnl/Rgf2I/p40czc88FXNXeTEd5T6ZY3tDRybxyonVqOpXORb4MLuhWn9PN58ROWUJ30SKlPW4HWuzWRS5SaiCRGC0pqkdjhyGEeXe81erLFNXVTIf6fKe61crfpesBi+dlbKaBoRACRjRdlEOe+bMeSJTvIpcAxbewizzzXal3QnaXuejEAsDhJ7IF871AZLLw+Zpt+WJ5x+sAO1c7JnqldF1HKBQqiYAJBAKYnZ1Fpcu5w+HIFdKLi+tOp3MFz4Jo8RLRNALj+Q71+fiXdML8Q167S8kU0lvcqG3LFNR9LW7YHIx+2UzjHyJ65XiNoLVGGAb8Y8czXeWDmc7y8HRpdnFNcwtashEsbb274G1itALRRiaEwHgynYl+me9WjyQwFEsgUeZO1iqLnCmmq46CXPU622IXKU0jFh8pWaQ0Hj+KcoU1u73JZJHS7bBYOPdeS1g8L2MjDgyFbkALJAq6x+fjVkSZbFkAkOwWKA0uWOucUBoWFMlrnZCUk9wOb+jA2AvAoWx3+djvAbHg0z+rC9j2hvxCn7VdS3S2RGRG0zQEg0HTKJhwOFxxX5fLZdqt7vP5YLdzBXJaW4QQmPMn4B+Pwj8ayWWpz56IQZQZMHvqHPC1FC5Q6m1wQt5E0S8bcfxDREuH1whabbqWxonDBzE20I/Rgf0YHzyARGSuYBtJktGwrTOTV74zs7in28vITyICdCFwNJ7KR79kvw7FEtDKVD3rrEqmkK4WdqpXKYu7W0XXE4WLlGaL6snkRJk9JDidW0qK6i7XNsiy9dROnF4VFs/LWImBoTAEkkdCMOZSkKtssG+rhiS/+k+/jVg6lz+ens4v1qn5E0CZggEkwOK15/LHF3aTy1WLu3UlZ24yH8Vy+AkgHix8vqEvn12+5QJAYdGNaC1Ip9MlRfX575FIpOK+qqqadqv7fD5YrfwFT2uHltYRnIwhMBbBzFg0t1hpNJQy3d6iyKhpdmU71dVMBEyrCpdnY0a/sDBGRJXwGkErLRmLYWLoAEYH+jE2uB+Tw0PQ0oW/sxWbHc3dPWjN5pW3dPfA5nSt0hET0XqUMgwciiUXFNTjGIgmcDSeKhvG0Gq35jrV5zPVt7sccC6y8UbT5goWJ53/nk4HTLeXJCtcrm0lRXWnsx2StHmafVYDi+dlLPfAML5vBrOPHoK+YLJuqbbBe1UXnKfVnXR/oQvowURJzIo2HYcRNc9YAgDJJpvErLhgrXNAsp5ixpuWAo7/Nh/FcuLlwucd1UDnJfnu8urWU3sfIlo1yWSyZMHS+e+xWKzivtXV1aZRMF6vF4rCmAxaGxKRdCbyZWH8y3gUWpn1PRxua0GHuq81k6tuta/vvFQWxoioEl4jaLlFAv5s/Eqms3zm6AiEKMwtdlZ5snnlmc7yho4uWDimJKJlENV1DEeTuWL6fHF9Imled5MBdDjtue70+W71Tqcd1kU2y6ZSM6aLlOq6eUObLDvhdm8vLKqrO2C3NW7IZp/VwOJ5Gcs5MIzvm4H/ewfKPl/77p25ArqR0DKF8akYtJk4tKlsN7k/Dujl/5dYqu25/HFrgwtKnRNKgwuWpeqUC45kOssP7gWO/ApILfxHLAEtr8lnl7eeDVg4mCHaqOLxuGm3ut/vRzJpvpAjAEiSBK/XaxoFU11dDQsXbaJVJgyBsD+RzVHPF9VDU7HidccyJMBT58xnqWcjYKobXJBP8c4ywxCYGJ5FNJyE22NHc7f3lF9rMVgYI6JKeI2gpSSEQGB8NJNXPrAfY4P9CJ2YLNmuurEpUyjPdpb7WtpYECKiVTWb1goXKc12qwfS5o03VknCdpc9v0hptlu93WGDvKhFSgWSyQlEIoMLiurDiMYOwjDM59yK4sksTrpgkVJV3QGrlTFWrxSL52Us18BQGAKTdz1X0HFeTLLJsLaq0GbiMObKd5FDkbMRK87CuJU6J+Sl7nxLxYCR/8pnl/sPFj7vrs8XyzsvAdy1S/v+RLTuCCEQi8VMu9X9fj/S6fLXN1mWUVNTYxoF4/F4IMu8LY1Wj5bKRL/MZLPU5yNg4uEy0S9WGb5md0Gn+nz0SyWHXpzC0w8NIzqbHxC7vXa8/rpudL2mYUnPaR4LY0RUCa8R9GromoapkUMYO7A/110enytac0eSUL91G9qyhfLWnj6oPs4tiWjtE0JgJq1hIFIY/TIQTSCqG6b7OGV5weKk+U71RpuyqA8JhdARjx8rjH+JDiMWOwwhzAv5Nlu96SKliqK+qvPfyFg8L2O5BoaJQ7OYuf/lk2+4gFxlKyySZzvJLV77kmSkmxICmB7Mdpc/Dhz9DaAv+DRLVoD28/LZ5Y2nAyxmEdEiCSEwNzdXNgpG181/0QOAoii5PPXi4rqqquxEolUTn0sVdKj7xyIITEShpcoMlqusuSx1X6sbdW0qaprdsNosOPTiFPb8y76y73X5/zptWQroLIwRUSW8RtArkUrEMT40gLGBfowP7sf48CC0orsSFasNTd070NqzC229fWje0Qu7y71KR0xEtPSEEBhNpjEQKYx+GY4lkCyzLqFXseSiX3oWdKv7rItLdTCMJGKxkQWd6sOIRoYQTxwru4/D0WaySGknLBauU8jieRnLNTCMvTSFwIODJ93OfX4T3Gc3Qal3QnasUORJfBY48lQ+uzw8Wvh8dXu+u3zbGwAHB8xEtPQMw0A4HC6JgAkEAggGgzAM80IkANhstoLC+sLiusvlYmGdVpxhCISn44VZ6mMRhKbjMF19SAI8dQ5EZ1PQ0+X/rqs1dvzZ5y5c8ggXFsaIqBJeI6iS6Gww11E+NrAfUyOHIYrGbQ63ipbevlxnecO27VC4uDwRbUKaITCSSOY61Qez3eqH48myKc0NNiUf/ZLtVt/hdkBVFpc+oWlRxGKHSjLVk6kTpttLkgVOZ4fJIqVbIMubJ56ZxfMyVrvzvO6vToejy7tk72vKMIDJP+Szy48/Byy8rUNxAFsvyhfM67oBFp6IaBXpuo5QKGTarT47O4tKv6ocDodpt7rP54PT6VzBsyAC0ikdgfFMMT0wFsXMWASB8QjileLairzjb1+D1p6lzSxkYYyIKuE1guYJITA7OY7Rgf3ZzvJ+BCfGS7bz1Ddkssp7+tDa24fa1nZIvGOZiKispGHgUCyZiXyJ5KNfjiXKxz+3O2z56Be3A72qE11OOxyWxV1v0+nZXHd6JvplCJHIIDQtZLq9LNvgcm0vKao7HC0bsmGNxfMyVjPz3FJtR9PHdi9PJEtkGjj0y2x2+V4gNlP4fN2ObLH8zZnCuZUFJSJaHzRNQzAYNI2CCYfDFfd1uVwFRfWF3+123qZGKycWTuEPvzyOF/YcPem2b7mpDzt2Ny3p+7MwRkSV8BqxeRm6jqmRw5mu8sFMwTwWmi3cSJJQ374VLQvyyj119atyvEREG01U0zEYy3apL8hVP5HSTLe3SECn014Y/eJ2YJvTDmUR9UYhBFKp6aI89Uymuq7HzN/TosLt7obq7s4X1dUe2Ky167qovtjxz+bpxV9mkizBe1UX/N87UHYb71WdS1c41zVg9Pl8dvnES4XP26qAzoszxfKuNwM1W5fmfYmIVpiiKKivr0d9fekkLZVKIRgMmi5cGolEEIvFEIvFcPz48ZJ9VVUtiYCZj4ax8jZjWmIujw1bdvoWVTx3e/jBDhERLY90IoGJg4MYG+jH6MB+TAwNIJ1MFGxjURQ0bd+R6Szv7UNL9044VC44R0S0HNyKBa/1uPFaT+G6EIG0lstRH4jEc3+e1XQMx5IYjiXx2HS+g9wmSeh223PF9PkFS9scNsgLCtySJMFub4Dd3oBa3+tyjwthIJEYMymqH4KuRxAOv4hw+MWCY7RafZmiuprpUJ/vVLdaT+2DeCF0zM4+j2RyCnZ7A7ze3ZCkxUXXLCd2ni+x+L4ZzD56qKAD3VJth/eqTjhPq3t1Lx4azeaWPw4cfgpIFt1m0XRGPoql/VzAwuIPEW1eyWSy7MKlsZj5J+rzqqurTaNgvF4vFIWfO9OpMQyB73ziN4jOJstuw8xzIloNvEZsXLFwKJNXfmA/xgb7MXXkEIyiBdztbjdae/rQko1gaershmKzrdIRExFROUIITKW0XHd6prCewGAsgZhuvq6S2yLnCukLc9XrbcqiusYNI414/GhJUT0WOwrA/D3t9qaS6Be3ezsslvIpGFNTv8DQ8GeRTE4WvM6O7s+goeGykx7nqWBsSxkrMTAUhkDySAjGXApylQ32bdWn1nGeTgDHfpMvmE8PFD7v9AFdb8oUy7veBFQ1Ls0JEBFtcPF43HThUr/fj2SyfGFTkiR4vV7TKJjq6mpYLKv/qTitbYdenMKef9lX9vnL/9dp6HpNw5K/LwtjRFQJrxEbgxACoakTGBvYj7GB/Rgd6EdwfLRkO7W2LrOwZ08fWnfuQl3bFuaVExGtY4YQOJ5I5TvVs93qB2NJpMqUfX1WS0Hsy3y3ute6uGYxXU+YLlKaSJauk5EhwencUlJUd7k6MDPzBF7edzOA4mPN1FJPP+2+ZSmgs3hexpoeGAoB+A9lc8sfB448DWjx/POSDLTtzmeXN58FyCzUEBEtFSEEYrFYSUF9/s/pdPlFH2VZRk1NjenCpR6PBzInpZR16MUpPP3QcEEHulpjx+uu7V6Wwjmwxsc/RLTqeI1YnwxDx/TRkUxe+UCmszwaDJRsV9u2Ba29fZmCee8ueOqX53cNERGtLWlD4Eg8metUH4wmMBhN4HAsWaZnHGiyWTOFdDXfqb7DbYd7kY1imjaHaHQYkYJFSoeQTvvL7KFAkgAhzDPeAQl2exMuuvCpJY9wYfG8jBUZGBo6cPQ3QOQEoDYCWy8sX+ROzmWK5PPZ5bNFWahVzZlC+fZLgc43As6a5TlmIiKqSAiBubm5slEwetEt0AspipLLUy8urququq4XWaFTYxgCE8OziIaTcHvsaO72LnlUy0IsjBFRJbxGrA/pVBKTB4dyESzjQweQiscLtpEtCpq6ujMLe/ZmolicatUqHTEREa1FCd3AwdiCLvVscX00Yd4sJgHY4rChVy3sVO9y2WFbZJNYKjWDSHS4IPolEhmCrkcWtf9rX/N91NScv9hTXBQuGLpa+n8O7PkYEF5wm4KnBbj8LqDv6kx3+Yl9+SiWY78FjAV/OS02YMsF+ezyhp0AiypERKtOkiR4PB54PB50dHQUPGcYBsLhsGm3ejAYhKZpmJqawtTUVMnr2my2kqL6/HeXy8XC+gYlyxJae/iBOBERlRefC2Ns8ECuq/zEoYMw9MLOPJvThZaenWjtyXSWN27vhtXGhaeJiKg8h0XGaVUunFblKnh8TtMxtKCYPl9Yn05pOJpI4WgihV/MhHPbKxLQ6XRki+r5TvWtThssRfNYm60OPlsdfDUX5B4TQmB09LsYGr4dAGBAxgB2YhY18CKIXhyAnO2RTyZL59IrhcXzpdT/c+Bfb0BJRk94AvjXPwM6Xg/MDAORycLna7bli+UdrwPsXMmciGg9kWUZXq8XXq8XXV1dBc/puo5QKGQaBRMKhZBKpTA5OYnJycmS13U4HKbd6j6fD05n+cVWiIiIaH0RQiA8PZVZ3HNgP8YG+uEfPVaynbvGh9beXWjr7UNr7y7UbdkKmVGeRES0BKoUC86uduPsanfB4zMpDYPZYvp89MuBaBxhzcBQLIGhWAI/X7C9Q5bQ7XLkFypVM93qrXZrQXOYJElQ1R0AgOdxHr6Dv0BAqss97xMzuAHfxG48C7t99SLHGNuyVAwduPe0wo7zcqwuYNsb8gt91nadfB8iItpwNE1DMBg0jYIJh8MV93W5XKbd6j6fD3Y7O86oECMZiKgSXiNWnmHo8B8/htFsoXxssB8R/0zJdr6WNrTuzCzu2bZzFzz1jbwrjYiIVp0QApOpNAYihdEvQ9EE4oZ5qVm1yLnu9Plu9R6XDd9+7m9xd/qvMhst/B0nDAASPmz9Oj70ui8z83ylLNvA8MjTwLevPPl2b/174Nz3AgoLG0REVF4qlUIwGDSNgolEKufCqapa0KU+/93n88Fqta7QGdBawsIYEVXCa8Ty01IpTB4ayhXKxwcPIBmLFmwjWyxo3LYdLdnFPVt6dsLlqV6lIyYiInrldCFwPJHKFtXz0S8HYwloZSrQEgSEgHlstTDQZBX4/eteWxIF82ox83ylRU4sbruqZhbOiYjopGw2GxobG9HY2FjyXDKZNO1W9/v9iMfjiEQiiEQiOHr0aMm+1dXVJREwtbW18Hq9UBQOC4iIiJZCIhLB+FAmr3x0oB8nDg1B1wrzyq0OJ1p29GYW9+zZhebtO2B1OFbpiImIiF49iyShw2lHh9OOy+vzHwCnDAOH40kMRPLRLwPRBA7HkxCQMquSmpFkTGrAb2cjuKhmdRbA5ix5qailxY1XtR0REVEZdrsdzc3NaG5uLnkuHo+bdqv7/X4kk0mEQiGEQiEcOXKkYD9JkuD1ek2jYLxeL+RFrqJORES0GYVnpjN55Qcyi3vOHD8KFN3k7ar2oq13V6ZY3rsL9Vu3QbYwr5yIiDY+myxn4lrchWt3PTjhxy0Dx0+6/1RKO+k2y4XF86Wy9ULA05JZHLR4wVAAgJR5fuuFK31kRES0iTidTrS1taGtra3gcSEEYrGYabd6IBBAOp1GMBhEMBgseU1ZllFTU2MaBePxeFhYJyKiTUUYBvxjx3MLe44O7MfczHTJdjXNrblCeWtvH7yNzcwrJyIiWqDdYVvUdg221Sths3i+VGQLcPldwL/egMy9BgsL6NkB0uV3ZrYjIiJaYZIkwe12w+12Y8uWLQXPCSEwNzdn2q0eCASg63ru8WKKouTy1IuL66qqskhARETrnpZO48Thg9li+X6MDx5AIlq4/ogky2jo6ELbzkwES0vPTri9Nat0xEREROvD+V4VzXYrJpPpcq3IaLZbcb5XXelDy2HxfCn1XQ1c+x1gz8eA8Hj+cU9LpnDed/XqHRsREVEZkiTB4/HA4/Ggo6Oj4DnDMBAOh0271YPBIDRNw9TUFKampkpe12azlUTAzH93uVwsrBMR0ZqUjEUxPjSQ6yyfPDgELZ0q2Eax29HSvSCvfEcPbA5nmVckIiIiMxZJwt93t+Iv942Ua0XGHd2tS75Y6CshCSHKrHW6Ma3ISvKGDhz9TWYRUbUxE9XCjnMiItpgdF3H7OxsQZf6fHE9FAqh0hDD4XCYdqv7fD44nSw+LLUVGf8Q0bq12a8RkYAfo9lC+djAfkwfGynJK3d6qtHa04fW3j609e5CfUcnLFxom4iIaEn82/QsPjU8holkOvdYi92KO7pbcUW9d1nec7HjHxbPiYiIaMlpmoZgMGgaBRMOhyvu63K5TLvVfT4f7Hb7Cp3BxsLxDxFVspmuEUIIBMZGMTa4P7e4Z2jqRMl23sbmgrzymuZW3jFFRES0jHQh8NvZCKZSGhpsCs73qsvacb7Y8Q8/KiciIqIlpygK6uvrUV9fX/JcKpVCMBg0jYKJRCKIxWKIxWI4frx01XVVVU271X0+H6xW60qcGhERrSO6lsbUkcP5zvLBfiTmCj/ElSQZ9R3bchEsrb19UGt8q3TEREREm5NFknBRTdVqH0YJFs+JiIhoRdlsNjQ2NqKxsbHkuWQyadqt7vf7EY/HEYlEEIlEcPTo0ZJ9q6urTaNgvF4vFN5aT0S0KaTisUxe+WA/xgb6MTE8CC2VLNhGsdrQ3N2T6yxv7u6F3eVapSMmIiKitYwzSSIiIloz7HY7mpub0dzcXPJcPB437Vb3+/1IJpMIhUIIhUI4cuRIwX6SJMHr9RYU1Of/7PV6IcvySp0eEREtsehsMLew5+jAfkyPHIEQRsE2DrUqH8HS04fGzi5YFN6tRERERCfH4jkRERGtC06nE21tbWhrayt4XAiBaDRqunBpIBBAOp1GMBhEMBgseU1ZllFTU2MaBePxeFhYJyJaQ4QQCE6MZ/PK+zE2uB+zkxMl23nqG9GWyyvfBV9LKyRez4mIiOgUrIni+X333YcvfvGLmJycxJlnnomvfOUrOPfcc8tu/6Mf/Qif/vSnMTIygu7ubtx1111429vetoJHTERERGuFJElQVRWqqmLLli0FzwkhMDc3Z9qtHggEoOt67vFiiqLk8tSLi+uqqr6qheMMw8DRo0cRiUSgqiq2bt3KQj0RbWiGoWPswH5EZoNQvTVo3bkLsmypvI+uY2rkcK6zfGywH7HQbOFGkoT6LR0FneVVtXXLdyJERES0qax68fyhhx7Crbfein/+53/Geeedh3vvvReXXXYZBgcH0dDQULL9b37zG1x//fX4h3/4B1x55ZX4wQ9+gHe84x144YUXcNppp63CGRAREdFaJUkSPB4PPB4POjo6Cp4zDAPhcNi0Wz0YDELTNExNTWFqaqrkdW02W0GX+sLiusvlqlhY7+/vx549exAO5xes83g8uPzyy9HX17dk505EtFYMP/sb/PJbX0MkMJN7TPXV4U1//l50n3dh7rFUIo6J4cFMoXxgPyaGB5FOJgpey2K1oqlrB9p2ZgrlzTt64XCrK3YuREREtLlIQgixmgdw3nnnYffu3finf/onAJmJbHt7Oz7wgQ/g4x//eMn21113HaLRKB577LHcY+effz7OOuss/PM///NJ3y8cDqO6uhqhUAgej2fpToSIiIg2DF3XMTs7axoFEwqFUGn45HA4TLvVfT4fjhw5gn/9138tu++11167LAV0jn+IqJLlvEYMP/sb/Pz/+3zZ58+5+r9D6DrGBvpx4sghCKMwr9zudqO1Z0FeeVc3FCvzyomIiOjVWez4Z1U7z1OpFH7/+9/j//yf/5N7TJZlXHrppXjmmWdM93nmmWdw6623Fjx22WWX4eGHH17OQyUiIqJNxGKx5Irf3d3dBc9pmoZgMFgSAeP3+xEOh5FIJDA+Po7x8fGS1z1Z1MuePXvQ29vLCBci2hAMQ8cvv/W1itv87uc/Lfi5qq4erT19uc7y2rYtzCsnIiKiVbOqxfOZmRnouo7GxsaCxxsbGzEwMGC6z+TkpOn2k5OTptsnk0kkk8ncz/O3SGuaBk3TAGQK9rIswzAMGAs6HeYf13W9oMOs3OMWiwWSJOVed+HjQKaLbTGPK4oCIUTB45IkwWKxlBxjucd5TjwnnhPPiefEc+I5Lc85zS8yWlNTU3JOyWQSwWAwF/2ysLgeiUQqdqwDmXHK4cOHCyJmluKcirchos1tpeZIo/0vF0S1lLPttbux4/zXoaWnDzWNTQDy1y3dMADD4O8gnhPPiefEc+I58Zx4Tkt6ToudI6165vly+4d/+AfcfvvtJY+/+OKLcLvdAID6+np0dXXhyJEjmJ6ezm3T1taGtrY2DA0NIRQK5R7v7OxEQ0MD9u3bh3g8nnu8t7cXXq8XL774YsH/gDPOOAM2mw2/+93vCo7hnHPOQSqVwh//+MfcYxaLBbt370YoFCr4AMHpdOLMM8/EzMwMDh8+nHu8uroaO3fuxPj4OEZHR3OP85x4TjwnnhPPiefEc1rdc9q2bRte//rX48CBAwiFQhgdHcW+fftwMvv27cPMTL7YtBTnxOI5ES20UnOk6YGTX/MAwNrYiojdjaGRozinrp6/g3hOPCeeE8+J58Rz4jkt+zktdo60qpnnqVQKLpcLP/7xj/GOd7wj9/iNN96I2dlZPPLIIyX7bNmyBbfeeituueWW3GO33XYbHn74YfzhD38o2d6sq6K9vR1+vz+XZ7MePg3ZiJ/w8Jx4TjwnnhPPiee0mc5pZGQE3/ve93Ay7373u5e883xubg4+n4+Z50QEYOXmSKP9L+Mnn/v0SY/nnZ+8A219pwNYG9frkz2+Hn8H8Zx4TjwnnhPPiefEczq1OdKaWDD03HPPxVe+8hUAmQVDt2zZgr/5m78pu2BoLBbDo48+mnvswgsvxBlnnMEFQ4mIiGjNMgwD9957by4ewYzH48Ett9wCWV7afF+Of4iokuW6RhiGjvtvvqlidEtVbR3+8p++AVm2LNn7EhEREZ3MYsc/q77yyq233or7778f3/72t3HgwAG8733vQzQaxXve8x4AwA033FCwoOj//t//G3v27ME999yDgYEB/N3f/R1+97vf4W/+5m9W6xSIiIiITkqWZVx++eUVt7n88suXvHBORLRaZNmCN/35eytuc8mN72XhnIiIiNasVZ+dXXfddbj77rvxmc98BmeddRZeeukl7NmzJ7co6LFjxzAxMZHb/sILL8QPfvADfO1rX8OZZ56JH//4x3j44Ydx2mmnrdYpEBERES1KX18frr322pLOBo/Hg2uvvRZ9fX2rdGRERMuj+7wLcfWtn4Dqqyt4vKq2Dlff+gl0n3fhKh0ZERER0cmtemzLSuNty0RERLTaDMPA0aNHEYlEoKoqtm7duqwd5xz/EFElK3GNMAwdYwf2IzIbhOqtQevOXew4JyIiolWz2PGPsoLHRERERETIRLhs27ZttQ+DiGjFyLIF7bvOWO3DICIiInpFVj22hYiIiIiIiIiIiIhorWHxnIiIiIiIiIiIiIioCIvnRERERERERERERERFWDwnIiIiIiIiIiIiIirC4jkRERERERERERERUREWz4mIiIiIiIiIiIiIirB4TkRERERERERERERUhMVzIiIiIiIiIiIiIqIiLJ4TERERERERERERERVh8ZyIiIiIiIiIiIiIqAiL50RERERERERERERERVg8JyIiIiIiIiIiIiIqwuI5EREREREREREREVERFs+JiIiIiIiIiIiIiIqweE5EREREREREREREVITFcyIiIiIiIiIiIiKiIiyeExEREREREREREREVYfGciIiIiIiIiIiIiKgIi+dEREREREREREREREVYPCciIiIiIiIiIiIiKsLiORERERERERERERFRERbPiYiIiIiIiIiIiIiKsHhORERERERERERERFSExXMiIiIiIiIiIiIioiLKah/AShNCAADC4fAqHwkRERHRypgf98yPg4iIFuIciYiIiDabxc6RNl3xfG5uDgDQ3t6+ykdCREREtLLm5uZQXV292odBRGsM50hERES0WZ1sjiSJTdaCZBgGxsfHUVVVBUmSlu19wuEw2tvbcfz4cXg8nmV7HyIiIlqfVnKsIITA3NwcWlpaIMtM7SOiQpwjERER0VqwFudIm67zXJZltLW1rdj7eTweDgyJiIiorJUaK7DjnIjK4RyJiIiI1pK1NEdi6xERERERERERERERUREWz4mIiIiIiIiIiIiIirB4vkzsdjtuu+022O321T4UIiIiWoM4ViCizYbXPSIiIqpkLY4VNt2CoUREREREREREREREJ8POcyIiIiIiIiIiIiKiIiyeExEREREREREREREVYfGciIiIiIiIiIiIiKjIpiueT05O4gMf+AA6Oztht9vR3t6Oq666Cnv37oUkSRW/nnzySXzrW9/K/SzLMpqbm3Hdddfh2LFjBe/zxje+EbfccsspHePC9/R4PNi9ezceeeSRgm0mJibwP//n/8SOHTsgy/IpvxcRERGZ+/M//3PT8cDll1+e2+bFF1/Eddddh+bmZtjtdmzduhVXXnklHn30UcwvKzMyMmL6Ou9+97tPegzF+/p8Plx88cV4+umnC7bbv38/3vnOd6KjowOSJOHee+9d0v8WRLSxbZQ50k9/+lO85S1vQX19PTweDy644AL84he/ONX/LERERFRkPc2R7r//frz+9a9HTU0NampqcOmll+K55557xee8qYrnIyMjOPvss/HLX/4SX/ziF/Hyyy9jz549uOSSS/BXf/VXmJiYyH1de+21uPzyywseu/DCCwEAHo8HExMTGBsbw09+8hMMDg7if/yP/7Gkx/rAAw9gYmICv/vd73DRRRfhXe96F15++eXc88lkEvX19fjUpz6FM888c0nfm4iIiDKKxwITExP44Q9/CAB45JFHcP755yMSieDb3/42Dhw4gD179uCaa67Bpz71KYRCoYLXevzxxwte57777lv0cczv+6tf/QotLS248sorceLEidzzsVgMnZ2duPPOO9HU1LQ0J09Em8JGmiP96le/wlve8hb8+7//O37/+9/jkksuwVVXXYUXX3xxSY+DiIhoM1svc6Qnn3wS119/PZ544gk888wzaG9vx1vf+laMjY29ovNVXtHW69z73/9+SJKE5557Dm63O/f4rl278Bd/8Rfwer25x5xOJ5LJpOkEVJKk3OPNzc246aab8MEPfhDhcBgej2dJjtXr9aKpqQlNTU2444478KUvfQlPPPEETj/9dABAR0cHvvSlLwEAvvnNby7JexIREVEhu91uOhaIRqO46aabcMUVV+CnP/1pwXM7d+7ETTfdlOuqmFdbW3vKhe35fZuamvCJT3wCDz74IJ599llcffXVAIDdu3dj9+7dAICPf/zjp/QeRLQ5baQ5UvFdN5///OfxyCOP4NFHH8VrXvOaJTkGIiKizW69zJG+//3vF2z/9a9/HT/5yU+wd+9e3HDDDYt+n03TeR4IBLBnzx7cfPPNBYPCeQsHha/E1NQUfvazn8FiscBisbzKoyylaRq+8Y1vAABsNtuSvz4RERG9cv/xH/8Bv9+Pj370o2W3kSRpyd83Ho/jO9/5DgCOC4jo1dvocyTDMDA3Nwefz7fkx0BERESF1vocKRaLIZ1Ov+JxwabpPD948CCEEOjt7X3VrxUKhaCqKoQQiMViAIAPfvCDpgPOU3X99dfDYrEgHo/DMAx0dHTg2muvXbLXJyIiopN77LHHoKpqwWOf+MQncsWgnp6e3OPPP/88LrnkktzPDz74IK688srczxdeeCFkOd+38PTTTy+6E3J+31gsBiEEzj77bLz5zW8+pXMiIpq30edId999NyKRCOdRRERES2i9zpE+9rGPoaWlBZdeeumiXn/epimeF98W8GpUVVXhhRdeQDqdxv/7f/8P3//+9/G5z31uyV4fAP7xH/8Rl156KQ4fPoy//du/xZe//GV2TBAREa2wSy65BF/96lcLHvP5fLj//vtLtj3jjDPw0ksvAQC6u7uhaVrB8w899BB27tyZ+7m9vX3Rx/HQQw+ht7cX+/btw0c/+lF861vfgtVqfQVnQkRUaiPPkX7wgx/g9ttvxyOPPIKGhoYlPQ4iIqLNbD3Oke688048+OCDePLJJ+FwOBb9HsAmKp53d3dDkiQMDAy86teSZRnbt28HkMnsOXToEN73vvfhu9/97qt+7XlNTU3Yvn07tm/fjgceeABve9vb0N/fz4EfERHRCnK73bnf+Qt1d3cDAAYHB3H++ecDyGT/mW07r729veLzlbS3t6O7uzs34Lzmmmuwb98+2O32U3o9IiJg486RHnzwQfzlX/4lfvSjH73i7jIiIiKqbL3Nke6++27ceeedePzxx3HGGWe84vfZNJnnPp8Pl112Ge677z5Eo9GS52dnZ0/5tT/+8Y/joYcewgsvvPAqjrC8c889F2efffaSd24QERHRqXnrW98Kn8+Hu+66a8Xf+13vehcURcH//b//d8Xfm4g2lo04R/rhD3+I97znPfjhD3+IK664Ylnem4iIiEqtxTnSF77wBdxxxx3Ys2cPzjnnnFN67U1TPAeA++67D7qu49xzz8VPfvITDA8P48CBA/jyl7+MCy644JRft729Hddccw0+85nPFDw+PT2Nl156qeDrxIkTp/Qet9xyC/7lX/4FY2NjucfmXzMSieTeq7+//5TPg4iIiAolk0lMTk4WfM3MzEBVVXz961/Hv/3bv+GKK67AL37xCxw+fBh//OMf8YUvfAEAlmWRPCCzyM4HP/hB3Hnnnblc4VQqlRsXpFIpjI2N4aWXXsLBgweX5RiIaOPYSHOkH/zgB7jhhhtwzz334Lzzzstdt0Oh0CmfBxERERVaL3Oku+66C5/+9KfxzW9+Ex0dHbljjUQir+zFxSYzPj4ubr75ZrF161Zhs9lEa2uruPrqq8UTTzxRsN2NN94o3v72t5fs/8ADD4jq6uqSx5955hkBQDz77LNCCCEuvvhiAaDk64477jjpMQIQP/vZzwoeMwxD9Pb2ive9730F2xV/bd269aSvT0RERCd34403mv6u7enpyW3z/PPPi3e9612ioaFBKIoiamtrxWWXXSYefPBBYRiGEEKII0eOCADixRdffMXHUG7faDQqampqxF133VWwXfHXxRdffKqnT0SbyEaZI5V7/RtvvHEx/xmIiIjoJNbTHGnr1q2mx3rbbbe9oveThFjCVWKIiIiIiIiIiIiIiDaATRXbQkRERERERERERES0GCyer7DPf/7zUFXV9Ou//bf/ttqHR0RERCvor//6r8uOC/76r/96tQ+PiGhFcI5ERERE89baHImxLSssEAggEAiYPud0OtHa2rrCR0RERESrZWpqCuFw2PQ5j8eDhoaGFT4iIqKVxzkSERERzVtrcyQWz4mIiIiIiIiIiIiIijC2hYiIiIiIiIiIiIioCIvnRERERERERERERERFWDwnIiIiIiIiIiIiIirC4jkRERERERERERERUREWz4mIVsgb3/hG3HLLLbmfOzo6cO+991bc5+/+7u9w1llnLetxERERERERrRbOk4hoLWPxnIg2ncnJSXzgAx9AZ2cn7HY72tvbcdVVV2Hv3r0rehzPP/883vve9+Z+liQJDz/8cME2H/7wh1f8uIiIiIiIaPPhPImIqJSy2gdARLSSRkZGcNFFF8Hr9eKLX/wiTj/9dKTTafziF7/AzTffjIGBgRU7lvr6+pNuo6oqVFVdgaMhIiIiIqLNivMkIiJz7Dwnok3l/e9/PyRJwnPPPYd3vvOd2LFjB3bt2oVbb70Vv/3tbwEAx44dw9vf/naoqgqPx4Nrr70WJ06cyL3G/C2C3/3ud9HR0YHq6mr8yZ/8Cebm5nLbRKNR3HDDDVBVFc3NzbjnnntKjmXh7YgdHR0AgGuuuQaSJOV+Lr4d0TAMfPazn0VbWxvsdjvOOuss7NmzJ/f8yMgIJEnCT3/6U1xyySVwuVw488wz8cwzzyzRf0EiIiIiItpoOE8iIjLH4jkRbRqBQAB79uzBzTffDLfbXfK81+uFYRh4+9vfjkAggKeeegr/+Z//icOHD+O6664r2PbQoUN4+OGH8dhjj+Gxxx7DU089hTvvvDP3/Ec+8hE89dRTeOSRR/Af//EfePLJJ/HCCy+UPbbnn38eAPDAAw9gYmIi93OxL33pS7jnnntw9913449//CMuu+wyXH311RgeHi7Y7pOf/CQ+/OEP46WXXsKOHTtw/fXXQ9O0Rf+3IiIiIiKizYHzJM6TiKg8xrYQ0aZx8OBBCCHQ29tbdpu9e/fi5ZdfxpEjR9De3g4A+M53voNdu3bh+eefx+7duwFkOhu+9a1voaqqCgDwZ3/2Z9i7dy8+97nPIRKJ4Bvf+Aa+973v4c1vfjMA4Nvf/jba2trKvu/8rYlerxdNTU1lt7v77rvxsY99DH/yJ38CALjrrrvwxBNP4N5778V9992X2+7DH/4wrrjiCgDA7bffjl27duHgwYMVz52IiIiIiDYfzpM4TyKi8th5TkSbhhDipNscOHAA7e3tuQEhAPT19cHr9eLAgQO5xzo6OnIDQgBobm7G1NQUgEy3RSqVwnnnnZd73ufzoaen51Udfzgcxvj4OC666KKCxy+66KKCYwOAM844o+DYAOSOj4iIiIiIaB7nSZwnEVF5LJ4T0abR3d0NSZKWZLEbq9Va8LMkSTAM41W/7lJZeHySJAHAmjo+IiIiIiJaGzhPWjvHR0RrD4vnRLRp+Hw+XHbZZbjvvvsQjUZLnp+dncXOnTtx/PhxHD9+PPd4f38/Zmdn0dfXt6j36erqgtVqxbPPPpt7LBgMYmhoqOJ+VqsVuq6Xfd7j8aClpQW//vWvCx7/9a9/vehjIyIiIiIiWojzJCKi8ph5TkSbyn333YeLLroI5557Lj772c/ijDPOgKZp+M///E989atfRX9/P04//XT86Z/+Ke69915omob3v//9uPjii3HOOecs6j1UVcVNN92Ej3zkI6itrUVDQwM++clPQpYrf17Z0dGBvXv34qKLLoLdbkdNTU3JNh/5yEdw2223oaurC2eddRYeeOABvPTSS/j+979/Sv89iIiIiIiIOE8iIjLH4jkRbSqdnZ144YUX8LnPfQ4f+tCHMDExgfr6epx99tn46le/CkmS8Mgjj+ADH/gA3vCGN0CWZVx++eX4yle+8ore54tf/CIikQiuuuoqVFVV4UMf+hBCoVDFfe655x7ceuutuP/++9Ha2oqRkZGSbT74wQ8iFArhQx/6EKamptDX14ef//zn6O7ufkXHR0RERERENI/zJCIic5JYzMoQRERERERERERERESbCDPPiYiIiIiIiIiIiIiKsHhORERERERERERERFSExXMiIiIiIiIiIiIioiIsnhMRERERERERERERFWHxnIiIiIiIiIiIiIioCIvnRERERERERERERERFWDwnIiIiIiIiIiIiIirC4jkRERERERERERERUREWz4mIiIiIiIiIiIiIirB4TkRERERERERERERUhMVzIiIiIiIiIiIiIqIiLJ4TERERERERERERERX5/wERr/K7Io1SdgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1500x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate absolute differences between _CTRL_ and _EGF_ columns for each replicate\n",
    "df_differences = pd.DataFrame()\n",
    "df_differences[\"Protein\"] = df_filtered2_norm_log[\"Protein\"]  # Add protein names for labeling\n",
    "\n",
    "for col in df_filtered2_norm_log.columns:\n",
    "    if \"_CTRL_\" in col and col.endswith(\"_MaxLFQIntensity\"):\n",
    "        # Find matching _EGF_ column for the same replicate\n",
    "        egf_col = col.replace(\"_CTRL_\", \"_EGF_\")\n",
    "        if egf_col in df_filtered2_norm_log.columns:\n",
    "            diff_col_name = f\"Diff_{col.split('_')[0]}_{col.split('_')[2]}\"  # Create a new column for the difference\n",
    "            df_differences[diff_col_name] = (df_filtered2_norm_log[egf_col] - df_filtered2_norm_log[col]).abs()\n",
    "\n",
    "# Identify top N proteins with the largest difference in R1 and R2 separately\n",
    "top_n = 10\n",
    "most_altered_r1 = df_differences.nlargest(top_n, \"Diff_CITO_R1\").set_index(\"Protein\")\n",
    "most_altered_r2 = df_differences.nlargest(top_n, \"Diff_CITO_R2\").set_index(\"Protein\")\n",
    "\n",
    "# Plotting the differences for the most altered proteins in separate grids\n",
    "fig, axs = plt.subplots(1, 2, figsize=(15, 8), sharey=True)\n",
    "\n",
    "# Plot for CTRL_R1 vs EGF_R1\n",
    "for protein in most_altered_r1.index:\n",
    "    values_r1 = [\n",
    "        df_filtered2_norm_log.loc[df_filtered2_norm_log['Protein'] == protein, 'CITO_CTRL_R1_MaxLFQIntensity'].values[0],\n",
    "        df_filtered2_norm_log.loc[df_filtered2_norm_log['Protein'] == protein, 'CITO_EGF_R1_MaxLFQIntensity'].values[0]\n",
    "    ]\n",
    "    axs[0].plot(['CTRL_R1', 'EGF_R1'], values_r1, marker='o', label=protein)\n",
    "\n",
    "# Customize the plot for R1\n",
    "axs[0].set_title('Top 10 Most Altered Proteins between CTRL and EGF Treatment (R1)')\n",
    "axs[0].set_xlabel('Condition')\n",
    "axs[0].set_ylabel('Log Normalized Value')\n",
    "axs[0].grid(axis='y', linestyle='--', alpha=0.7)\n",
    "\n",
    "# Plot for CTRL_R2 vs EGF_R2\n",
    "for protein in most_altered_r2.index:\n",
    "    values_r2 = [\n",
    "        df_filtered2_norm_log.loc[df_filtered2_norm_log['Protein'] == protein, 'CITO_CTRL_R2_MaxLFQIntensity'].values[0],\n",
    "        df_filtered2_norm_log.loc[df_filtered2_norm_log['Protein'] == protein, 'CITO_EGF_R2_MaxLFQIntensity'].values[0]\n",
    "    ]\n",
    "    axs[1].plot(['CTRL_R2', 'EGF_R2'], values_r2, marker='o', label=protein)\n",
    "\n",
    "# Customize the plot for R2\n",
    "axs[1].set_title('Top 10 Most Altered Proteins between CTRL and EGF Treatment (R2)')\n",
    "axs[1].set_xlabel('Condition')\n",
    "axs[1].grid(axis='y', linestyle='--', alpha=0.7)\n",
    "axs[0].legend(title=\"Protein\", loc='upper left', bbox_to_anchor=(1, 1))\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5d42b85b-28c7-4e9c-ba3f-522378168468",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 Protein Protein_ID   Entry_Name      Gene  Protein_Length  \\\n",
      "0   sp|A6NEC2|PSAL_HUMAN     A6NEC2   PSAL_HUMAN  NPEPPSL1           478.0   \n",
      "1  sp|A8MWD9|RUXGL_HUMAN     A8MWD9  RUXGL_HUMAN  SNRPGP15            76.0   \n",
      "2  sp|E9PAV3|NACAM_HUMAN     E9PAV3  NACAM_HUMAN      NACA          2078.0   \n",
      "3  sp|O00148|DX39A_HUMAN     O00148  DX39A_HUMAN    DDX39A           427.0   \n",
      "4  sp|O00186|STXB3_HUMAN     O00186  STXB3_HUMAN    STXBP3           592.0   \n",
      "\n",
      "       Organism                            Protein_Existence  \\\n",
      "0  Homo sapiens  2:Experimental evidence at transcript level   \n",
      "1  Homo sapiens                          5:Protein uncertain   \n",
      "2  Homo sapiens     1:Experimental evidence at protein level   \n",
      "3  Homo sapiens     1:Experimental evidence at protein level   \n",
      "4  Homo sapiens     1:Experimental evidence at protein level   \n",
      "\n",
      "                                         Description  Protein_Probability  \\\n",
      "0    Puromycin-sensitive aminopeptidase-like protein               0.9628   \n",
      "1  Putative small nuclear ribonucleoprotein G-lik...               0.8712   \n",
      "2  Nascent polypeptide-associated complex subunit...               1.0000   \n",
      "3                  ATP-dependent RNA helicase DDX39A               1.0000   \n",
      "4                         Syntaxin-binding protein 3               1.0000   \n",
      "\n",
      "   Top_Peptide_Probability  ...  NUC_CTRL_R2_MaxLFQIntensity  \\\n",
      "0                   0.9990  ...                     0.000000   \n",
      "1                   0.9962  ...                     0.035917   \n",
      "2                   0.9990  ...                     0.000000   \n",
      "3                   0.9990  ...                     0.039527   \n",
      "4                   0.9968  ...                     0.000000   \n",
      "\n",
      "   NUC_EGF_R1_MaxLFQIntensity  NUC_EGF_R2_MaxLFQIntensity  \\\n",
      "0                    0.010342                    0.016145   \n",
      "1                    0.031408                    0.033722   \n",
      "2                    0.033255                    0.029313   \n",
      "3                    0.043705                    0.036338   \n",
      "4                    0.000000                    0.000000   \n",
      "\n",
      "   Indistinguishable_Proteins  CITO_CTRL_Mean  CITO_EGF_Mean  MEMB_CTRL_Mean  \\\n",
      "0         sp|P55786|PSA_HUMAN        0.023942       0.029293        0.000000   \n",
      "1        sp|P62308|RUXG_HUMAN        0.000000       0.000000        0.000000   \n",
      "2                         NaN        0.031831       0.033928        0.011066   \n",
      "3       sp|Q13838|DX39B_HUMAN        0.025842       0.047359        0.011728   \n",
      "4                         NaN        0.000000       0.000118        0.000000   \n",
      "\n",
      "   MEMB_EGF_Mean  NUC_CTRL_Mean  NUC_EGF_Mean  \n",
      "0       0.000000       0.004193      0.013243  \n",
      "1       0.000000       0.031259      0.032565  \n",
      "2       0.040642       0.016244      0.031284  \n",
      "3       0.021287       0.034835      0.040021  \n",
      "4       0.033922       0.000000      0.000000  \n",
      "\n",
      "[5 rows x 93 columns]\n",
      "{'CITO': ['CITO_CTRL_R1_MaxLFQIntensity', 'CITO_CTRL_R2_MaxLFQIntensity', 'CITO_EGF_R1_MaxLFQIntensity', 'CITO_EGF_R2_MaxLFQIntensity'], 'MEMB': ['MEMB_CTRL_R1_MaxLFQIntensity', 'MEMB_CTRL_R2_MaxLFQIntensity', 'MEMB_EGF_R1_MaxLFQIntensity', 'MEMB_EGF_R2_MaxLFQIntensity'], 'NUC': ['NUC_CTRL_R1_MaxLFQIntensity', 'NUC_CTRL_R2_MaxLFQIntensity', 'NUC_EGF_R1_MaxLFQIntensity', 'NUC_EGF_R2_MaxLFQIntensity']}\n"
     ]
    }
   ],
   "source": [
    "print(df_mean.head())\n",
    "print(compartments)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e4a1c60c-57b2-4631-a908-72f6398e508b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 Most Altered Proteins (CITO):\n",
      "              Protein  Diff_CITO\n",
      " sp|P13693|TCTP_HUMAN   0.320538\n",
      "sp|P63104|1433Z_HUMAN   0.212550\n",
      " sp|P06454|PTMA_HUMAN  -0.197416\n",
      "sp|P68104|EF1A1_HUMAN   0.185756\n",
      "  sp|P04406|G3P_HUMAN  -0.169739\n",
      "sp|P0DP23|CALM1_HUMAN   0.155176\n",
      " sp|P40925|MDHC_HUMAN   0.143968\n",
      " sp|P10599|THIO_HUMAN   0.138971\n",
      "sp|P04792|HSPB1_HUMAN  -0.122581\n",
      "sp|P30086|PEBP1_HUMAN  -0.113566\n",
      "\n",
      "\n",
      "Top 10 Most Altered Proteins (MEMB):\n",
      "              Protein  Diff_MEMB\n",
      "sp|P08758|ANXA5_HUMAN  -0.583965\n",
      " sp|P62328|TYB4_HUMAN   0.386673\n",
      "  sp|P14174|MIF_HUMAN   0.361366\n",
      "sp|P04792|HSPB1_HUMAN  -0.233778\n",
      "sp|P04075|ALDOA_HUMAN   0.216377\n",
      "sp|P07355|ANXA2_HUMAN   0.212929\n",
      " sp|P01111|RASN_HUMAN   0.207858\n",
      "sp|P63313|TYB10_HUMAN   0.207689\n",
      " sp|P51858|HDGF_HUMAN  -0.205037\n",
      "sp|Q16777|H2A2C_HUMAN  -0.193654\n",
      "\n",
      "\n",
      "Top 10 Most Altered Proteins (NUC):\n",
      "              Protein  Diff_NUC\n",
      "sp|P08727|K1C19_HUMAN  0.154627\n",
      " sp|P05787|K2C8_HUMAN -0.142759\n",
      "sp|O60814|H2B1K_HUMAN -0.130766\n",
      "sp|Q96AG4|LRC59_HUMAN  0.123442\n",
      "sp|Q16777|H2A2C_HUMAN -0.096036\n",
      "sp|P06899|H2B1J_HUMAN -0.076465\n",
      " sp|P62328|TYB4_HUMAN -0.076028\n",
      "sp|P68104|EF1A1_HUMAN -0.073052\n",
      " sp|P63261|ACTG_HUMAN  0.069626\n",
      "sp|P07355|ANXA2_HUMAN  0.066529\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Calculate the difference (log2 fold change) between EGF and CTRL for each compartment\n",
    "for compartment in compartments:\n",
    "    # Define the column names for CTRL and EGF mean values for each compartment\n",
    "    ctrl_mean_col = f'{compartment}_CTRL_Mean'\n",
    "    egf_mean_col = f'{compartment}_EGF_Mean'\n",
    "    \n",
    "    # Calculate the difference (log2 fold change) between EGF and CTRL for each compartment\n",
    "    df_mean[f'Diff_{compartment}'] = df_mean[egf_mean_col] - df_mean[ctrl_mean_col]\n",
    "    \n",
    "    # Calculate the absolute difference for this compartment\n",
    "    df_mean[f'Abs_Diff_{compartment}'] = df_mean[f'Diff_{compartment}'].abs()\n",
    "\n",
    "    # Sort by absolute difference for the current compartment\n",
    "    df_sorted = df_mean.sort_values(by=f'Abs_Diff_{compartment}', ascending=False)\n",
    "\n",
    "    # Select the top 10 most altered proteins for this compartment\n",
    "    top_10_proteins = df_sorted.head(10)\n",
    "\n",
    "    # Display the top 10 most altered proteins for the current compartment\n",
    "    print(f\"Top 10 Most Altered Proteins ({compartment}):\")\n",
    "    print(top_10_proteins[['Protein', f'Diff_{compartment}']].to_string(index=False))\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "41419dd8-d4a3-4531-baf9-5ad055f66f05",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the top 10 most altered proteins for each compartment\n",
    "fig, axs = plt.subplots(1, len(compartments), figsize=(15, 8), sharey=True)\n",
    "\n",
    "for i, compartment in enumerate(compartments):\n",
    "    # Calculate the top 10 most altered proteins based on absolute difference (already sorted in the previous block)\n",
    "    top_10_proteins = df_mean.sort_values(by=f'Abs_Diff_{compartment}', ascending=False).head(10)\n",
    "    \n",
    "    # Determine colors based on the sign of the fold change\n",
    "    colors = ['pink' if diff < 0 else 'skyblue' for diff in top_10_proteins[f'Diff_{compartment}']]\n",
    "    \n",
    "    # Plot the differences with color indication for positive/negative changes\n",
    "    axs[i].barh(top_10_proteins['Protein'], top_10_proteins[f'Diff_{compartment}'], color=colors)\n",
    "    axs[i].set_title(f'Top 10 Most Altered Proteins ({compartment})')\n",
    "    axs[i].set_xlabel('Log Fold Change')\n",
    "    axs[i].grid(True, linestyle='--', alpha=0.7)\n",
    "    # Add a black horizontal line at zero\n",
    "    axs[i].axvline(x=0, color='black', linewidth=1)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "8dd5d26e-d74c-44e1-acb0-abdc30f39c91",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 Protein  CITO_CTRL_Mean  CITO_EGF_Mean  MEMB_CTRL_Mean  \\\n",
      "0   sp|A6NEC2|PSAL_HUMAN        0.023942       0.029293        0.000000   \n",
      "1  sp|A8MWD9|RUXGL_HUMAN        0.000000       0.000000        0.000000   \n",
      "2  sp|E9PAV3|NACAM_HUMAN        0.031831       0.033928        0.011066   \n",
      "3  sp|O00148|DX39A_HUMAN        0.025842       0.047359        0.011728   \n",
      "4  sp|O00186|STXB3_HUMAN        0.000000       0.000118        0.000000   \n",
      "\n",
      "   MEMB_EGF_Mean  NUC_CTRL_Mean  NUC_EGF_Mean  \n",
      "0       0.000000       0.004193      0.013243  \n",
      "1       0.000000       0.031259      0.032565  \n",
      "2       0.040642       0.016244      0.031284  \n",
      "3       0.021287       0.034835      0.040021  \n",
      "4       0.033922       0.000000      0.000000  \n"
     ]
    }
   ],
   "source": [
    "# Extract columns starting with 'Mean_'\n",
    "df_mean_columns = df_mean.filter(regex='^.*_Mean$')\n",
    "\n",
    "# Create the new DataFrame with 'Protein' and the '_Mean' columns\n",
    "df_mean_columns = df_mean[['Protein']].join(df_mean_columns)\n",
    "\n",
    "# Show the first few rows of the new DataFrame\n",
    "print(df_mean_columns.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "bd3976e1-c1bf-437e-8d08-e5a458cf9120",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Membrane Mean DataFrame:\n",
      "                 Protein  MEMB_CTRL_Mean  MEMB_EGF_Mean\n",
      "0   sp|A6NEC2|PSAL_HUMAN        0.000000       0.000000\n",
      "1  sp|A8MWD9|RUXGL_HUMAN        0.000000       0.000000\n",
      "2  sp|E9PAV3|NACAM_HUMAN        0.011066       0.040642\n",
      "3  sp|O00148|DX39A_HUMAN        0.011728       0.021287\n",
      "4  sp|O00186|STXB3_HUMAN        0.000000       0.033922\n",
      "Nucleus Mean DataFrame:\n",
      "                 Protein  NUC_CTRL_Mean  NUC_EGF_Mean\n",
      "0   sp|A6NEC2|PSAL_HUMAN       0.004193      0.013243\n",
      "1  sp|A8MWD9|RUXGL_HUMAN       0.031259      0.032565\n",
      "2  sp|E9PAV3|NACAM_HUMAN       0.016244      0.031284\n",
      "3  sp|O00148|DX39A_HUMAN       0.034835      0.040021\n",
      "4  sp|O00186|STXB3_HUMAN       0.000000      0.000000\n",
      "Cytosol Mean DataFrame:\n",
      "                 Protein  CITO_CTRL_Mean  CITO_EGF_Mean\n",
      "0   sp|A6NEC2|PSAL_HUMAN        0.023942       0.029293\n",
      "1  sp|A8MWD9|RUXGL_HUMAN        0.000000       0.000000\n",
      "2  sp|E9PAV3|NACAM_HUMAN        0.031831       0.033928\n",
      "3  sp|O00148|DX39A_HUMAN        0.025842       0.047359\n",
      "4  sp|O00186|STXB3_HUMAN        0.000000       0.000118\n"
     ]
    }
   ],
   "source": [
    "# Split the mean columns DataFrame by compartments\n",
    "df_memb_mean = df_mean_columns[['Protein', 'MEMB_CTRL_Mean', 'MEMB_EGF_Mean']]\n",
    "df_nuc_mean = df_mean_columns[['Protein', 'NUC_CTRL_Mean', 'NUC_EGF_Mean']]\n",
    "df_cito_mean = df_mean_columns[['Protein', 'CITO_CTRL_Mean', 'CITO_EGF_Mean']]\n",
    "\n",
    "# Make sure to reset index if you plan to combine data back later\n",
    "df_memb_mean.reset_index(drop=True, inplace=True)\n",
    "df_nuc_mean.reset_index(drop=True, inplace=True)\n",
    "df_cito_mean.reset_index(drop=True, inplace=True)\n",
    "\n",
    "# Display the first few rows of the DataFrames for each compartment\n",
    "print('Membrane Mean DataFrame:')\n",
    "print(df_memb_mean.head())\n",
    "\n",
    "print('Nucleus Mean DataFrame:')\n",
    "print(df_nuc_mean.head())\n",
    "\n",
    "print('Cytosol Mean DataFrame:')\n",
    "print(df_cito_mean.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "451c6875-5272-4424-a579-ada7594b2b20",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_56856/1793855164.py:14: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[f'LFC_{compartment}'] = df[egf_mean_col] - df[ctrl_mean_col]\n",
      "/tmp/ipykernel_56856/1793855164.py:34: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[f'P_value_{compartment}'] = p_values[compartment]  # Add p-values to the DataFrame\n",
      "/tmp/ipykernel_56856/1793855164.py:14: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[f'LFC_{compartment}'] = df[egf_mean_col] - df[ctrl_mean_col]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Log2 Fold Change (LFC) for MEMB compartment:\n",
      "                 Protein  LFC_MEMB\n",
      "0   sp|A6NEC2|PSAL_HUMAN  0.000000\n",
      "1  sp|A8MWD9|RUXGL_HUMAN  0.000000\n",
      "2  sp|E9PAV3|NACAM_HUMAN  0.029576\n",
      "3  sp|O00148|DX39A_HUMAN  0.009559\n",
      "4  sp|O00186|STXB3_HUMAN  0.033922\n",
      "\n",
      "Top 10 proteins with the lowest p-values for MEMB compartment:\n",
      "                   Protein  LFC_MEMB  P_value_MEMB\n",
      "0     sp|A6NEC2|PSAL_HUMAN  0.000000           1.0\n",
      "457   sp|P62910|RL32_HUMAN  0.000000           1.0\n",
      "458   sp|P62913|RL11_HUMAN  0.000000           1.0\n",
      "459    sp|P62917|RL8_HUMAN  0.024907           1.0\n",
      "460   sp|P62937|PPIA_HUMAN -0.106183           1.0\n",
      "461  sp|P62942|FKB1A_HUMAN  0.000000           1.0\n",
      "462  sp|P62979|RS27A_HUMAN  0.058702           1.0\n",
      "463   sp|P62993|GRB2_HUMAN  0.019784           1.0\n",
      "464  sp|P62995|TRA2B_HUMAN  0.000000           1.0\n",
      "465   sp|P63000|RAC1_HUMAN  0.060322           1.0\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_56856/1793855164.py:34: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[f'P_value_{compartment}'] = p_values[compartment]  # Add p-values to the DataFrame\n",
      "/tmp/ipykernel_56856/1793855164.py:14: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[f'LFC_{compartment}'] = df[egf_mean_col] - df[ctrl_mean_col]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Log2 Fold Change (LFC) for NUC compartment:\n",
      "                 Protein   LFC_NUC\n",
      "0   sp|A6NEC2|PSAL_HUMAN  0.009050\n",
      "1  sp|A8MWD9|RUXGL_HUMAN  0.001306\n",
      "2  sp|E9PAV3|NACAM_HUMAN  0.015040\n",
      "3  sp|O00148|DX39A_HUMAN  0.005186\n",
      "4  sp|O00186|STXB3_HUMAN  0.000000\n",
      "\n",
      "Top 10 proteins with the lowest p-values for NUC compartment:\n",
      "                   Protein   LFC_NUC  P_value_NUC\n",
      "0     sp|A6NEC2|PSAL_HUMAN  0.009050          1.0\n",
      "457   sp|P62910|RL32_HUMAN  0.005151          1.0\n",
      "458   sp|P62913|RL11_HUMAN  0.022847          1.0\n",
      "459    sp|P62917|RL8_HUMAN  0.046920          1.0\n",
      "460   sp|P62937|PPIA_HUMAN  0.036953          1.0\n",
      "461  sp|P62942|FKB1A_HUMAN  0.000000          1.0\n",
      "462  sp|P62979|RS27A_HUMAN  0.010225          1.0\n",
      "463   sp|P62993|GRB2_HUMAN  0.000000          1.0\n",
      "464  sp|P62995|TRA2B_HUMAN  0.000000          1.0\n",
      "465   sp|P63000|RAC1_HUMAN  0.000000          1.0\n",
      "\n",
      "\n",
      "Log2 Fold Change (LFC) for CITO compartment:\n",
      "                 Protein  LFC_CITO\n",
      "0   sp|A6NEC2|PSAL_HUMAN  0.005351\n",
      "1  sp|A8MWD9|RUXGL_HUMAN  0.000000\n",
      "2  sp|E9PAV3|NACAM_HUMAN  0.002097\n",
      "3  sp|O00148|DX39A_HUMAN  0.021517\n",
      "4  sp|O00186|STXB3_HUMAN  0.000118\n",
      "\n",
      "Top 10 proteins with the lowest p-values for CITO compartment:\n",
      "                   Protein  LFC_CITO  P_value_CITO\n",
      "0     sp|A6NEC2|PSAL_HUMAN  0.005351           1.0\n",
      "457   sp|P62910|RL32_HUMAN -0.007750           1.0\n",
      "458   sp|P62913|RL11_HUMAN  0.000474           1.0\n",
      "459    sp|P62917|RL8_HUMAN -0.017209           1.0\n",
      "460   sp|P62937|PPIA_HUMAN -0.010492           1.0\n",
      "461  sp|P62942|FKB1A_HUMAN  0.012750           1.0\n",
      "462  sp|P62979|RS27A_HUMAN  0.008775           1.0\n",
      "463   sp|P62993|GRB2_HUMAN -0.007746           1.0\n",
      "464  sp|P62995|TRA2B_HUMAN  0.000000           1.0\n",
      "465   sp|P63000|RAC1_HUMAN  0.000633           1.0\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_56856/1793855164.py:34: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[f'P_value_{compartment}'] = p_values[compartment]  # Add p-values to the DataFrame\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import wilcoxon\n",
    "\n",
    "# Create an empty dictionary to store p-values\n",
    "p_values = {'MEMB': [], 'NUC': [], 'CITO': []}\n",
    "\n",
    "# Loop over each compartment and calculate Log2 Fold Change, Wilcoxon test\n",
    "for compartment, df in zip(['MEMB', 'NUC', 'CITO'], [df_memb_mean, df_nuc_mean, df_cito_mean]):\n",
    "    \n",
    "    # Define column names for CTRL and EGF for the current compartment\n",
    "    ctrl_mean_col = f'{compartment}_CTRL_Mean'\n",
    "    egf_mean_col = f'{compartment}_EGF_Mean'\n",
    "    \n",
    "    # Calculate Log2 Fold Change (LFC) for the current compartment\n",
    "    df[f'LFC_{compartment}'] = df[egf_mean_col] - df[ctrl_mean_col]\n",
    "    \n",
    "    # Perform Wilcoxon signed-rank test for each protein (CTRL vs EGF)\n",
    "    compartment_p_values = []\n",
    "    for i, row in df.iterrows():\n",
    "        # Extract CTRL and EGF values for the current protein and compartment\n",
    "        ctrl_value = row[ctrl_mean_col]\n",
    "        egf_value = row[egf_mean_col]\n",
    "        \n",
    "        # Perform Wilcoxon signed-rank test (make sure both values are non-zero)\n",
    "        if ctrl_value > 0 and egf_value > 0:\n",
    "            stat, p_value = wilcoxon([ctrl_value], [egf_value])\n",
    "        else:\n",
    "            p_value = 1  # Assign a non-significant value (1) if no data or both values are zero\n",
    "        \n",
    "        # Store the p-value for the current protein and compartment\n",
    "        compartment_p_values.append(p_value)\n",
    "    \n",
    "    # Store p-values in the dictionary for the current compartment\n",
    "    p_values[compartment] = compartment_p_values\n",
    "    df[f'P_value_{compartment}'] = p_values[compartment]  # Add p-values to the DataFrame\n",
    "\n",
    "    # Display Log2 Fold Change and p-values for the compartment\n",
    "    print(f\"Log2 Fold Change (LFC) for {compartment} compartment:\")\n",
    "    print(df[['Protein', f'LFC_{compartment}']].head())\n",
    "    \n",
    "    # Sort DataFrame by p-value and select the 10 proteins with the lowest p-values\n",
    "    top_10_proteins = df.sort_values(by=f'P_value_{compartment}').head(10)\n",
    "    print(f\"\\nTop 10 proteins with the lowest p-values for {compartment} compartment:\")\n",
    "    print(top_10_proteins[['Protein', f'LFC_{compartment}', f'P_value_{compartment}']])\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "57e8db1e-2fa7-4a1b-80ff-7f41b3a4d7c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 Proteins with Largest LFC (MEMB compartment):\n",
      "              Protein  LFC_MEMB  P_value_MEMB\n",
      "sp|P08758|ANXA5_HUMAN -0.583965           1.0\n",
      " sp|P62328|TYB4_HUMAN  0.386673           1.0\n",
      "  sp|P14174|MIF_HUMAN  0.361366           1.0\n",
      "sp|P04792|HSPB1_HUMAN -0.233778           1.0\n",
      "sp|P04075|ALDOA_HUMAN  0.216377           1.0\n",
      "sp|P07355|ANXA2_HUMAN  0.212929           1.0\n",
      " sp|P01111|RASN_HUMAN  0.207858           1.0\n",
      "sp|P63313|TYB10_HUMAN  0.207689           1.0\n",
      " sp|P51858|HDGF_HUMAN -0.205037           1.0\n",
      "sp|Q16777|H2A2C_HUMAN -0.193654           1.0\n",
      "\n",
      "\n",
      "Top 10 Proteins with Largest LFC (NUC compartment):\n",
      "              Protein   LFC_NUC  P_value_NUC\n",
      "sp|P08727|K1C19_HUMAN  0.154627          1.0\n",
      " sp|P05787|K2C8_HUMAN -0.142759          1.0\n",
      "sp|O60814|H2B1K_HUMAN -0.130766          1.0\n",
      "sp|Q96AG4|LRC59_HUMAN  0.123442          1.0\n",
      "sp|Q16777|H2A2C_HUMAN -0.096036          1.0\n",
      "sp|P06899|H2B1J_HUMAN -0.076465          1.0\n",
      " sp|P62328|TYB4_HUMAN -0.076028          1.0\n",
      "sp|P68104|EF1A1_HUMAN -0.073052          1.0\n",
      " sp|P63261|ACTG_HUMAN  0.069626          1.0\n",
      "sp|P07355|ANXA2_HUMAN  0.066529          1.0\n",
      "\n",
      "\n",
      "Top 10 Proteins with Largest LFC (CITO compartment):\n",
      "              Protein  LFC_CITO  P_value_CITO\n",
      " sp|P13693|TCTP_HUMAN  0.320538           1.0\n",
      "sp|P63104|1433Z_HUMAN  0.212550           1.0\n",
      " sp|P06454|PTMA_HUMAN -0.197416           1.0\n",
      "sp|P68104|EF1A1_HUMAN  0.185756           1.0\n",
      "  sp|P04406|G3P_HUMAN -0.169739           1.0\n",
      "sp|P0DP23|CALM1_HUMAN  0.155176           1.0\n",
      " sp|P40925|MDHC_HUMAN  0.143968           1.0\n",
      " sp|P10599|THIO_HUMAN  0.138971           1.0\n",
      "sp|P04792|HSPB1_HUMAN -0.122581           1.0\n",
      "sp|P30086|PEBP1_HUMAN -0.113566           1.0\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Add the p-values from the dictionary to the df_mean DataFrame\n",
    "df_mean['P_value_MEMB'] = p_values['MEMB']\n",
    "df_mean['P_value_NUC'] = p_values['NUC']\n",
    "df_mean['P_value_CITO'] = p_values['CITO']\n",
    "\n",
    "# Loop over each compartment to find the top 10 proteins with the largest LFC\n",
    "for compartment, df in zip(['MEMB', 'NUC', 'CITO'], [df_memb_mean, df_nuc_mean, df_cito_mean]):\n",
    "    # Define the corresponding columns for the compartment\n",
    "    ctrl_mean_col = f'{compartment}_CTRL_Mean'\n",
    "    egf_mean_col = f'{compartment}_EGF_Mean'\n",
    "    \n",
    "    # Sort proteins by the absolute value of Log2 Fold Change (LFC)\n",
    "    df_sorted = df[['Protein', f'LFC_{compartment}', f'P_value_{compartment}']].copy()\n",
    "    \n",
    "    # Calculate the absolute value of LFC for sorting\n",
    "    df_sorted['Abs_LFC'] = df_sorted[f'LFC_{compartment}'].abs()\n",
    "    \n",
    "    # Sort by absolute LFC in descending order to get largest changes\n",
    "    df_sorted = df_sorted.sort_values(by='Abs_LFC', ascending=False)\n",
    "    \n",
    "    # Get the top 10 proteins with the largest LFC (positive or negative)\n",
    "    top_10_proteins = df_sorted.head(10)\n",
    "    \n",
    "    # Display the top 10 proteins with LFC and corresponding p-values\n",
    "    print(f\"Top 10 Proteins with Largest LFC ({compartment} compartment):\")\n",
    "    print(top_10_proteins[['Protein', f'LFC_{compartment}', f'P_value_{compartment}']].to_string(index=False))\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "a5266bec-1522-4d71-b94a-abd440788130",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'MEMB': {'df':                             Protein  LFC_MEMB  P_value_MEMB\n",
       "  0              sp|A6NEC2|PSAL_HUMAN  0.000000           1.0\n",
       "  1             sp|A8MWD9|RUXGL_HUMAN  0.000000           1.0\n",
       "  2             sp|E9PAV3|NACAM_HUMAN  0.029576           1.0\n",
       "  3             sp|O00148|DX39A_HUMAN  0.009559           1.0\n",
       "  4             sp|O00186|STXB3_HUMAN  0.033922           1.0\n",
       "  ..                              ...       ...           ...\n",
       "  688            sp|Q9Y4Y9|LSM5_HUMAN  0.020989           1.0\n",
       "  689           sp|Q9Y5S9|RBM8A_HUMAN  0.000000           1.0\n",
       "  690            sp|Q9Y624|JAM1_HUMAN  0.007590           1.0\n",
       "  691           sp|Q9Y696|CLIC4_HUMAN  0.000000           1.0\n",
       "  692  tr|A0A494BZU2|A0A494BZU2_HUMAN  0.000000           1.0\n",
       "  \n",
       "  [693 rows x 3 columns],\n",
       "  'top_10':                    Protein  LFC_MEMB  P_value_MEMB\n",
       "  0     sp|A6NEC2|PSAL_HUMAN  0.000000           1.0\n",
       "  457   sp|P62910|RL32_HUMAN  0.000000           1.0\n",
       "  458   sp|P62913|RL11_HUMAN  0.000000           1.0\n",
       "  459    sp|P62917|RL8_HUMAN  0.024907           1.0\n",
       "  460   sp|P62937|PPIA_HUMAN -0.106183           1.0\n",
       "  461  sp|P62942|FKB1A_HUMAN  0.000000           1.0\n",
       "  462  sp|P62979|RS27A_HUMAN  0.058702           1.0\n",
       "  463   sp|P62993|GRB2_HUMAN  0.019784           1.0\n",
       "  464  sp|P62995|TRA2B_HUMAN  0.000000           1.0\n",
       "  465   sp|P63000|RAC1_HUMAN  0.060322           1.0},\n",
       " 'NUC': {'df':                             Protein   LFC_NUC  P_value_NUC\n",
       "  0              sp|A6NEC2|PSAL_HUMAN  0.009050          1.0\n",
       "  1             sp|A8MWD9|RUXGL_HUMAN  0.001306          1.0\n",
       "  2             sp|E9PAV3|NACAM_HUMAN  0.015040          1.0\n",
       "  3             sp|O00148|DX39A_HUMAN  0.005186          1.0\n",
       "  4             sp|O00186|STXB3_HUMAN  0.000000          1.0\n",
       "  ..                              ...       ...          ...\n",
       "  688            sp|Q9Y4Y9|LSM5_HUMAN  0.015511          1.0\n",
       "  689           sp|Q9Y5S9|RBM8A_HUMAN  0.011691          1.0\n",
       "  690            sp|Q9Y624|JAM1_HUMAN  0.000000          1.0\n",
       "  691           sp|Q9Y696|CLIC4_HUMAN  0.000000          1.0\n",
       "  692  tr|A0A494BZU2|A0A494BZU2_HUMAN  0.000000          1.0\n",
       "  \n",
       "  [693 rows x 3 columns],\n",
       "  'top_10':                    Protein   LFC_NUC  P_value_NUC\n",
       "  0     sp|A6NEC2|PSAL_HUMAN  0.009050          1.0\n",
       "  457   sp|P62910|RL32_HUMAN  0.005151          1.0\n",
       "  458   sp|P62913|RL11_HUMAN  0.022847          1.0\n",
       "  459    sp|P62917|RL8_HUMAN  0.046920          1.0\n",
       "  460   sp|P62937|PPIA_HUMAN  0.036953          1.0\n",
       "  461  sp|P62942|FKB1A_HUMAN  0.000000          1.0\n",
       "  462  sp|P62979|RS27A_HUMAN  0.010225          1.0\n",
       "  463   sp|P62993|GRB2_HUMAN  0.000000          1.0\n",
       "  464  sp|P62995|TRA2B_HUMAN  0.000000          1.0\n",
       "  465   sp|P63000|RAC1_HUMAN  0.000000          1.0},\n",
       " 'CITO': {'df':                             Protein  LFC_CITO  P_value_CITO\n",
       "  0              sp|A6NEC2|PSAL_HUMAN  0.005351           1.0\n",
       "  1             sp|A8MWD9|RUXGL_HUMAN  0.000000           1.0\n",
       "  2             sp|E9PAV3|NACAM_HUMAN  0.002097           1.0\n",
       "  3             sp|O00148|DX39A_HUMAN  0.021517           1.0\n",
       "  4             sp|O00186|STXB3_HUMAN  0.000118           1.0\n",
       "  ..                              ...       ...           ...\n",
       "  688            sp|Q9Y4Y9|LSM5_HUMAN  0.012200           1.0\n",
       "  689           sp|Q9Y5S9|RBM8A_HUMAN  0.013671           1.0\n",
       "  690            sp|Q9Y624|JAM1_HUMAN  0.000000           1.0\n",
       "  691           sp|Q9Y696|CLIC4_HUMAN  0.003631           1.0\n",
       "  692  tr|A0A494BZU2|A0A494BZU2_HUMAN  0.000000           1.0\n",
       "  \n",
       "  [693 rows x 3 columns],\n",
       "  'top_10':                    Protein  LFC_CITO  P_value_CITO\n",
       "  0     sp|A6NEC2|PSAL_HUMAN  0.005351           1.0\n",
       "  457   sp|P62910|RL32_HUMAN -0.007750           1.0\n",
       "  458   sp|P62913|RL11_HUMAN  0.000474           1.0\n",
       "  459    sp|P62917|RL8_HUMAN -0.017209           1.0\n",
       "  460   sp|P62937|PPIA_HUMAN -0.010492           1.0\n",
       "  461  sp|P62942|FKB1A_HUMAN  0.012750           1.0\n",
       "  462  sp|P62979|RS27A_HUMAN  0.008775           1.0\n",
       "  463   sp|P62993|GRB2_HUMAN -0.007746           1.0\n",
       "  464  sp|P62995|TRA2B_HUMAN  0.000000           1.0\n",
       "  465   sp|P63000|RAC1_HUMAN  0.000633           1.0}}"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a dictionary to store results\n",
    "results_dict = {\n",
    "    'MEMB': {\n",
    "        'df': df_memb_mean[['Protein', 'LFC_MEMB', 'P_value_MEMB']],\n",
    "        'top_10': df_memb_mean.sort_values(by='P_value_MEMB').head(10)[['Protein', 'LFC_MEMB', 'P_value_MEMB']]\n",
    "    },\n",
    "    'NUC': {\n",
    "        'df': df_nuc_mean[['Protein', 'LFC_NUC', 'P_value_NUC']],\n",
    "        'top_10': df_nuc_mean.sort_values(by='P_value_NUC').head(10)[['Protein', 'LFC_NUC', 'P_value_NUC']]\n",
    "    },\n",
    "    'CITO': {\n",
    "        'df': df_cito_mean[['Protein', 'LFC_CITO', 'P_value_CITO']],\n",
    "        'top_10': df_cito_mean.sort_values(by='P_value_CITO').head(10)[['Protein', 'LFC_CITO', 'P_value_CITO']]\n",
    "    }\n",
    "}\n",
    "results_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "a81e6d3a-6e6a-4476-8429-dfb9bf58e33f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   Protein      MEMB       NUC      CITO\n",
      "0    sp|Q9NVA2|SEP11_HUMAN  0.000000  0.009050  0.005351\n",
      "1     sp|P34897|GLYM_HUMAN  0.000000  0.001306  0.000000\n",
      "2    sp|Q5JWF2|GNAS1_HUMAN  0.029576  0.015040  0.002097\n",
      "3     sp|P00558|PGK1_HUMAN  0.009559  0.005186  0.021517\n",
      "4    sp|P62995|TRA2B_HUMAN  0.033922  0.000000  0.000118\n",
      "..                     ...       ...       ...       ...\n",
      "688   sp|P06576|ATPB_HUMAN  0.020989  0.015511  0.012200\n",
      "689  sp|P09467|F16P1_HUMAN  0.000000  0.011691  0.013671\n",
      "690  sp|P08133|ANXA6_HUMAN  0.007590  0.000000  0.000000\n",
      "691  sp|P61981|1433G_HUMAN  0.000000  0.000000  0.003631\n",
      "692   sp|P23588|IF4B_HUMAN  0.000000  0.000000  0.000000\n",
      "\n",
      "[693 rows x 4 columns]\n"
     ]
    }
   ],
   "source": [
    "# Find the common proteins across all compartments\n",
    "common_proteins = set(results_dict['MEMB']['df']['Protein']) & set(results_dict['NUC']['df']['Protein']) & set(results_dict['CITO']['df']['Protein'])\n",
    "\n",
    "# Create a dictionary to store LFC data for the common proteins\n",
    "lfc_data = {'Protein': list(common_proteins)}  # Start with the common proteins\n",
    "\n",
    "# Add LFC values for each compartment, ensuring proteins are aligned\n",
    "for compartment in ['MEMB', 'NUC', 'CITO']:\n",
    "    compartment_df = results_dict[compartment]['df']\n",
    "    # Filter the compartment data to include only common proteins\n",
    "    compartment_data = compartment_df[compartment_df['Protein'].isin(common_proteins)]\n",
    "    # Sort by protein to align correctly with the common proteins\n",
    "    compartment_data = compartment_data.sort_values('Protein')\n",
    "    lfc_data[compartment] = compartment_data[f'LFC_{compartment}'].values\n",
    "\n",
    "# Convert the dictionary to a DataFrame for easier manipulation\n",
    "lfc_df = pd.DataFrame(lfc_data)\n",
    "print(lfc_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "50f6c7c4-c5c6-4681-9670-b40e09a58a45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x800 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ensure the 'Protein' column is set as the index for clustering purposes\n",
    "lfc_df.set_index('Protein', inplace=True)\n",
    "\n",
    "# Create a clustered heatmap\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.clustermap(lfc_df, \n",
    "               cmap='coolwarm',          # Color map for the heatmap\n",
    "               metric='euclidean',       # Distance metric for clustering\n",
    "               method='average',         # Clustering method\n",
    "               standard_scale=1,         # Scale the data (standardize across rows)\n",
    "               row_cluster=True,         # Cluster rows (proteins)\n",
    "               col_cluster=False,        # Don't cluster columns (compartments)\n",
    "               cbar_kws={'label': 'Log2 Fold Change (LFC)'},  # Colorbar label\n",
    "               yticklabels=False          # Hide protein names\n",
    ")\n",
    "\n",
    "# Customize the title and show the plot\n",
    "plt.suptitle(\"Clustered Heatmap of Log Fold Change (LFC) by Compartment\", y=1.05)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "856bf126-003d-4c46-a127-47f32716ced7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       Cyt. Membrane  P_value_MEMB   Nucleus  P_value_NUC  \\\n",
      "Protein                                                                     \n",
      "sp|A6NEC2|PSAL_HUMAN        0.000000           1.0  0.009050          1.0   \n",
      "sp|P62910|RL32_HUMAN        0.000000           1.0  0.005151          1.0   \n",
      "sp|P62913|RL11_HUMAN        0.000000           1.0  0.022847          1.0   \n",
      "sp|P62917|RL8_HUMAN         0.024907           1.0  0.046920          1.0   \n",
      "sp|P62937|PPIA_HUMAN       -0.106183           1.0  0.036953          1.0   \n",
      "sp|P62942|FKB1A_HUMAN       0.000000           1.0  0.000000          1.0   \n",
      "sp|P62979|RS27A_HUMAN       0.058702           1.0  0.010225          1.0   \n",
      "sp|P62993|GRB2_HUMAN        0.019784           1.0  0.000000          1.0   \n",
      "sp|P62995|TRA2B_HUMAN       0.000000           1.0  0.000000          1.0   \n",
      "sp|P63000|RAC1_HUMAN        0.060322           1.0  0.000000          1.0   \n",
      "\n",
      "                        Cytosol  P_value_CITO  \n",
      "Protein                                        \n",
      "sp|A6NEC2|PSAL_HUMAN   0.005351           1.0  \n",
      "sp|P62910|RL32_HUMAN  -0.007750           1.0  \n",
      "sp|P62913|RL11_HUMAN   0.000474           1.0  \n",
      "sp|P62917|RL8_HUMAN   -0.017209           1.0  \n",
      "sp|P62937|PPIA_HUMAN  -0.010492           1.0  \n",
      "sp|P62942|FKB1A_HUMAN  0.012750           1.0  \n",
      "sp|P62979|RS27A_HUMAN  0.008775           1.0  \n",
      "sp|P62993|GRB2_HUMAN  -0.007746           1.0  \n",
      "sp|P62995|TRA2B_HUMAN  0.000000           1.0  \n",
      "sp|P63000|RAC1_HUMAN   0.000633           1.0  \n"
     ]
    }
   ],
   "source": [
    "# Extract and combine the top 10 proteins for each compartment from the results_dict\n",
    "top_proteins_combined = []\n",
    "\n",
    "for compartment in results_dict:\n",
    "    # Extract the 'top_10' DataFrame for each compartment\n",
    "    top_10_df = results_dict[compartment]['top_10']\n",
    "    \n",
    "    # Rename the columns to include the compartment name\n",
    "    if compartment == 'MEMB':\n",
    "        top_10_df = top_10_df.rename(columns={'LFC_MEMB': 'Cyt. Membrane'})\n",
    "    elif compartment == 'NUC':\n",
    "        top_10_df = top_10_df.rename(columns={'LFC_NUC': 'Nucleus'})\n",
    "    elif compartment == 'CITO':\n",
    "        top_10_df = top_10_df.rename(columns={'LFC_CITO': 'Cytosol'})\n",
    "    \n",
    "    # Set 'Protein' as the index for each compartment\n",
    "    top_10_df.set_index('Protein', inplace=True)\n",
    "    \n",
    "    # Append the compartment-specific DataFrame to the list\n",
    "    top_proteins_combined.append(top_10_df)\n",
    "\n",
    "# Concatenate all top 10 DataFrames into a single DataFrame\n",
    "top_proteins_df = pd.concat(top_proteins_combined, axis=1)\n",
    "print(top_proteins_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "d839d7bc-4ac5-412e-aad9-6d32804b922a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x800 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Filter the DataFrame to include only the LFC columns (excluding P_value columns)\n",
    "top_proteins_lfc_df = top_proteins_df[['Cyt. Membrane', 'Nucleus', 'Cytosol']]\n",
    "\n",
    "# Create a clustered heatmap for the selected proteins\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.clustermap(\n",
    "    top_proteins_lfc_df,  # Use the LFC data for heatmap\n",
    "    cmap='coolwarm',      # Color map for the heatmap\n",
    "    metric='euclidean',   # Distance metric for clustering\n",
    "    method='average',     # Clustering method\n",
    "    standard_scale=1,     # Standardize across rows\n",
    "    row_cluster=True,     # Cluster rows (proteins)\n",
    "    col_cluster=False,    # Don't cluster columns (compartments)\n",
    "    cbar_kws={'label': 'Log2 Fold Change (LFC)'},  # Colorbar label\n",
    "    vmin=-1, vmax=1,      # Set the color scale to range from -1 to 1\n",
    "    yticklabels=True,     # Show protein names on the y-axis\n",
    "    figsize=(10, 8)       # Control the figure size\n",
    ")\n",
    "\n",
    "# Customize the title and show the plot\n",
    "plt.suptitle(\"Clustered Heatmap of Top Proteins by Log Fold Change (LFC) in Each Compartment\", y=1.05)\n",
    "plt.show()\n"
   ]
  }
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