{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cell-1",
   "metadata": {},
   "source": [
    "# Tutorial 1: Merge Multi-ROI Chromatin Trace Data\n",
    "\n",
    "This tutorial walks through the standard workflow for merging chromatin tracing data from multiple regions of interest (ROIs):\n",
    "\n",
    "1. **Collect** trace files from all ROIs into one folder\n",
    "2. **Assess quality** by computing Pearson correlations between ROIs\n",
    "3. **Remove** ROIs with poor correlation (outliers)\n",
    "4. **Re-assess** the correlation matrix after removal\n",
    "5. **Merge** the remaining trace files into a single table\n",
    "6. **Statistics** on the merged dataset\n",
    "7. **Next steps** — link to Tutorial 2 for quality control"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d776dfbb",
   "metadata": {},
   "source": [
    "## Step 0: Set-up your data and output path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cell-0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f7d0189",
   "metadata": {},
   "source": [
    "\n",
    "Set up your folder data path:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b78d25aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_path = \"/home/devos/Documents/data_to_compare_pdx1/PDX1\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4caa4da",
   "metadata": {},
   "source": [
    "Set up destination folder for output:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bdca0af8",
   "metadata": {},
   "outputs": [],
   "source": [
    "dest_path = f\"{data_path}/\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2546525a",
   "metadata": {},
   "source": [
    "Check ROIs detected:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "757b6dd0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data path: /home/devos/Documents/data_to_compare_pdx1/PDX1\n",
      "Output path: /home/devos/Documents/data_to_compare_pdx1/PDX1/\n",
      "\n",
      "Available ROIs:\n",
      "  016_ROI\n",
      "  017_ROI\n",
      "  018_ROI\n",
      "  019_ROI\n",
      "  020_ROI\n",
      "  021_ROI\n",
      "  022_ROI\n",
      "  023_ROI\n",
      "  024_ROI\n",
      "  025_ROI\n",
      "  026_ROI\n",
      "  027_ROI\n",
      "  028_ROI\n",
      "  029_ROI\n",
      "  030_ROI\n",
      "  031_ROI\n"
     ]
    }
   ],
   "source": [
    "print(f\"Data path: {data_path}\")\n",
    "print(f\"Output path: {dest_path}\")\n",
    "print(f\"\\nAvailable ROIs:\")\n",
    "for d in sorted(Path(data_path).iterdir()):\n",
    "    if d.is_dir() and \"ROI\" in d.name:\n",
    "        print(f\"  {d.name}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-2",
   "metadata": {},
   "source": [
    "## Step 1: Collect trace files from all ROIs\n",
    "\n",
    "`collect_files` scans each subdirectory of `--root` for a file matching `--example-file`.\n",
    "The `--variable-part \"13\"` indicates that the ROI number varies; fixed-length matching naturally excludes Matrix files (different filename length)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "cell-3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matched (16):\n",
      "  016_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/016_ROI/Trace_3D_barcode_mask-mask0_ROI-16_Pdx1_filtered_Pdx1.ecsv\n",
      "  017_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/017_ROI/Trace_3D_barcode_mask-mask0_ROI-17_Pdx1_filtered_Pdx1.ecsv\n",
      "  018_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/018_ROI/Trace_3D_barcode_mask-mask0_ROI-18_Pdx1_filtered_Pdx1.ecsv\n",
      "  019_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/019_ROI/Trace_3D_barcode_mask-mask0_ROI-19_Pdx1_filtered_Pdx1.ecsv\n",
      "  020_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/020_ROI/Trace_3D_barcode_mask-mask0_ROI-20_Pdx1_filtered_Pdx1.ecsv\n",
      "  021_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/021_ROI/Trace_3D_barcode_mask-mask0_ROI-21_Pdx1_filtered_Pdx1.ecsv\n",
      "  022_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/022_ROI/Trace_3D_barcode_mask-mask0_ROI-22_Pdx1_filtered_Pdx1.ecsv\n",
      "  023_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/023_ROI/Trace_3D_barcode_mask-mask0_ROI-23_Pdx1_filtered_Pdx1.ecsv\n",
      "  024_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/024_ROI/Trace_3D_barcode_mask-mask0_ROI-24_Pdx1_filtered_Pdx1.ecsv\n",
      "  025_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/025_ROI/Trace_3D_barcode_mask-mask0_ROI-25_Pdx1_filtered_Pdx1.ecsv\n",
      "  026_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/026_ROI/Trace_3D_barcode_mask-mask0_ROI-26_Pdx1_filtered_Pdx1.ecsv\n",
      "  027_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/027_ROI/Trace_3D_barcode_mask-mask0_ROI-27_Pdx1_filtered_Pdx1.ecsv\n",
      "  028_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/028_ROI/Trace_3D_barcode_mask-mask0_ROI-28_Pdx1_filtered_Pdx1.ecsv\n",
      "  029_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/029_ROI/Trace_3D_barcode_mask-mask0_ROI-29_Pdx1_filtered_Pdx1.ecsv\n",
      "  030_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/030_ROI/Trace_3D_barcode_mask-mask0_ROI-30_Pdx1_filtered_Pdx1.ecsv\n",
      "  031_ROI -> /home/devos/Documents/data_to_compare_pdx1/PDX1/031_ROI/Trace_3D_barcode_mask-mask0_ROI-31_Pdx1_filtered_Pdx1.ecsv\n",
      "\n",
      "Copied 16 file(s) to /home/devos/Documents/data_to_compare_pdx1/PDX1/raw_traces\n"
     ]
    }
   ],
   "source": [
    "!collect_files --root {data_path} --example-file \"Trace_3D_barcode_mask-mask0_ROI-18_Pdx1_filtered_Pdx1.ecsv\" --variable-part \"18\" --copy-to {dest_path}/raw_traces --force"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-4",
   "metadata": {},
   "source": [
    "## Step 2: Compute Pearson correlations between ROIs\n",
    "\n",
    "`trace_pearsons` computes a pairwise distance map for each ROI (median 3D distance between every barcode pair), then calculates the Pearson correlation between these maps.\n",
    "\n",
    "A high correlation between two ROIs means they share similar chromatin organization. An ROI with low correlation against all others is likely an outlier (imaging artifact, poor segmentation, etc.)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "cell-5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analyzing 16 trace files...\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-16_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-17_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-18_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-19_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-20_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-21_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-22_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-23_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-24_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-25_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-26_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-27_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-28_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-29_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-30_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-31_Pdx1_filtered_Pdx1.ecsv\n",
      "$ Saved correlation matrix as /home/devos/Documents/data_to_compare_pdx1/PDX1/trace_correlation_matrix.png\n",
      "$ Saved correlation matrix data in NPY format: /home/devos/Documents/data_to_compare_pdx1/PDX1/trace_correlation_matrix.npy\n"
     ]
    },
    {
     "data": {
      "image/png": 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aaNGiBX7++Wf88ccfAPJ+P3799VccOHAAnTt3vuG4+0qVKmHq1Kn45ZdfXL+rW7ZswdNPP41jx45hzJgxrqEFFStWxJo1a/DQQw9BURRMnjzZ9Vq3bt2Ke++9t8Bz79ixAz/99BM+/fRT13O/9dZbRdZis9nwxhtv4M4778TXX3+NL774Aqqqun7f3333XYSFhWH69OklOps/ERHpkGZxn4ioBN2spTs8PFweOHDAbctobm5uoZbs/O3Dhw+XQghXq3j+9gEDBkghhBw4cKDMzMws8Lyqqkqn0+nalpGRITt06CAtFov8/PPPCxxLVVWZkJAgmzZtKgMDA+Vvv/1W7NdeVEu3qqoyJyfH7Wu+evWqbNKkifTz85P79u1zbc9v6QYgGzRoIC9evOh6vKqq8vLly7Jx48bSYrHIxYsXu+5z19Ktqqpcu3attNvtsmnTpvLy5cuF3qe5c+dKi8Ui+/fvL3Nzc2/6WtPT02Xfvn2lyWSSAKS3t7esVauW7Natm3znnXfkrl27ZFZWVqHXfLOW7qCgoAKtpFJKeeHCBRkdHS0ByM6dO8vU1NQCtX/11VdSURTZvXv3Aj/T4rZ0OxwO6XA4CtXsdDrlJ598IhVFkYMGDSpwjPyWbqvVKhctWuT2Z/zXlu58X375pav3h7vHHTlyRIaGhsrq1avLS5cuFbjv7NmzsnLlyjIsLEweP3680GPdub6lOzs7W3722WfSZDLJd9991/W7Mnz4cGmz2eS6detkQkJCkS3d7j7PqqrK5ORk2bp1a+nl5SW3bdtW4D18+umnpclkkosXL3ZbX35Lt8VikfPnz3f7nrhr6c4/9qZNm2RISIgMDw+XO3bskGfOnJENGzaUNptNzp492+13CxERlW1s6SaicqlNmzaoU6eO2xZAs9kMRVGgqqpr2am0tDRkZWXhnnvugRAC+/btc7X6JSQkYMOGDfDx8cHw4cNhs9kKPK8QosAMzCdPnsTOnTsRExODhx9+uMAYXyEEgoKC0LVrV6SkpGD79u23bWkiIYRrLLDT6URmZqbrtVmtVtx5551IS0vDsWPH3D6+Z8+eBcapCiEQGhqKXr16weFwYN26dTesVUqJFStWIDs7G0888UShsc9CCHTo0AFhYWHYtm0b0tLSbvqavLy8MHPmTEybNg2xsbEAgOPHj+Pbb7/F+PHj0b59ewwePBgXLlwo1vvYtGlTNGzYsEB9wcHBqFGjBgCgV69e8PHxKVD7HXfcAS8vL5w9exbZ2dkeH+uvTCaTa0x7Tk4OMjIykJaWhoyMDDRu3Bi+vr44dOiQ22NUq1YNHTp0uK1zAVSvXh0dO3bE6dOnC/yM5Z89ReLi4tCxY0dUrVr1lp6/Q4cOiIiIwJIlS5Ceno74+HisWbMGdevWxV133VXk44r6PKenp0NRFDRt2hSZmZk4fPjwLdUVHR2NTp06Feu9FELgnnvuwYQJE3D16lU8//zzGDlyJA4cOIB+/fqhT58+ZWblACIi8hwnUiOicql27dpFnvw6nU78+uuvmD9/Pvbs2YMrV6641gHPyMiAqqpISkqCqqowmUy4fPkyrly5gqioKFSrVu2mJ+knT55EWloaUlJSMGHCBLd1/P7771BVFefOnfv7L/ZPUkpkZWVh7dq1WLp0KY4cOYKkpCQ4nU4AwNWrVwHA7VJKJpMJjRo1KrRdCOGa+Ozo0aNQVbXI91VVVRw4cABA3trQJ06cKLRPTk4O0tPTkZOTg6SkJAQGBt7wNQkhEBAQgJEjR2LQoEE4fvw4fvvtN+zevRubNm3CkSNHMG/ePCQmJmLBggXw8/O74fPli46Ohtlc8E+koijw8fGB2WxGVFRUoZ+z3W6H1WpFdnb23xoWIP+cufurr77Czz//jIsXLyIrKwtSSjgcDqSlpSE5OdntMSpVquTxa/SUyWTCU089hSVLlmD+/PmuCdWysrKwYMECmM1mPPnkkx5PfvdXkZGR6NSpExYsWIB9+/bh3LlzOHv2LCZOnAh/f39cu3bN7eOklMjJycGPP/6IxYsX49ChQ0hKSnK9L/mf41tdGiwqKqrY3eWBvPfrmWeewY4dO7Bw4UIAeRdx3njjDbcT0RERUdnH0E1E5ZK3t7fb7aqqYu7cuXjxxReRmpqKiIgIhIeHw8vLC4qi4OrVq7h8+bJrrCaQF8Rzc3Ph4+Pj0Ul1UlKSaybxBQsWFLmfv7//rb24ImRnZ2PMmDH49NNPoSgKoqKiEBoaCqvVCiEEHA4HkpOTXSH8eiaTCb6+vm4vKOTPsp6RkQGn01korOZzOBxISUmBlBKbN2/G1q1bi6w1ICCgwJJmNyOEgL+/P5o0aYI777wTAwYMQGJiImbMmIHJkyfjhx9+wNatW9G5c2ePns/da7i+hb+o1yiE+Fs9E6SU2Lp1K/r164czZ84gJCQElStXRnBwMEwmEzIzMxEXF+d2uSsg73N9u5f4EkKgZcuWuOOOO7B161YcPHgQjRs3xt69e7F79240aNAALVq0uOXjKoqCXr16Yd68eViwYAHOnTsHHx8fPPLIIzd8ztzcXLz66qt4//33AQCVK1dGaGioq6eJlBKJiYluP8+eyP+dvxXe3t5o3749Fi9eDFVVb7oyABERlW0M3URULhV18hsfH48333wT2dnZeP/99/Hoo4/Cz88PZrMZQgh899136NmzZ4HHeHl5wWw2IzMzE7m5uTc9tpeXF4QQaNKkCb744osiAxwAj5dfuhkpJbZs2YLZs2cjKioKs2bNwp133ukKFkIIjBo1CjNnznT7eFVVkZGRASllofcuLS0NUkrY7fYbtnaaTCbXPv/617/QoUOHIvdVFAWVK1e+pdeaX19QUBD++c9/Yvny5di7dy/27t3rcejWSk5ODiZNmoQzZ85g5MiRGDFiBEJCQmCxWCCEwPHjx3HPPfeUel1+fn544oknMHr0aCxatAiNGjXC119/jYyMDPTu3ftvXSASQqB58+aoU6cO5s+fj+zsbLRu3Rp16tQp8jFSSuzevRsffPABQkNDMWvWLNx9993w9vZ2fZ5fe+01vPPOO3+rrlshpcSRI0cwZcoU1/fGrFmz8OCDD6JBgwYM3kRE5RBDNxHRdY4dO4YLFy7gnnvuwcCBAwu0XEspcfr06UItZxUrVkRwcDDi4uJw7tw5BAQE3PDEOiYmBna7HUlJSa7HloYdO3YgKysL/fr1Q/v27QvU6HA4cOrUqSIf63A4cPDgQTz44IMFtkspcfDgQTidTlSvXv2GLYMmkwm1atXC9u3bkZ6ejho1apR4APHx8UFoaCgA/K1x1qUlMTER+/btQ0REBEaPHl1oreeLFy8iIyPjth7z+ue/0T7dunXDtGnTsGzZMvTp0wcrV65EcHAwunXr9rd/jgEBAejWrRvefPNNV8v3X9dW/6tdu3YhLS0Nzz77LLp27VqgBqfTecPPM3Dj13urpJRITU3FmDFjcPbsWYwZMwYmkwlTpkzB6NGjsXDhwpsOmSAiKmnXf//xQmDp4GweRETXye/S/NfwKKXEtWvXXGM0r1exYkW0atUKqampmD17dqHlqvK7Audvq1mzJho2bIhTp05h5cqVbrtRSynhdDqL1cX6ZvLHurp7bfv27cO2bdtu+PglS5YgMTGxwERaycnJ+Oabb6AoCu67774b/vEWQuChhx6C2WzG119/jStXrhQKPvnvkydLfkkpERcX52ppd3f/xYsXceLECSiKgpo1a97w+fRAVVWoqlpo8j0grxV83rx5rvkFbhcfHx8IIVzDHooSHR2Nrl274uTJk3jllVdw9uxZdOjQAdWqVfvbNQgh0L9/f7z11lt4++238dBDD930RDD/4pe7z/Phw4fx008/uX2cr68vVFUt8Fm+XZxOJ/773//i+++/R/v27TFu3DiMGTMGHTp0wI8//ojp06ff9mUAiciYrj83yMjIQHJyMpKSkpCenl5iFwUdDgdOnDiBFStW4LPPPsNXX32Fbdu2ITk5uUSOSf/D0E1EdJ2YmBgEBwdjx44dWLBgARITE5GWloajR49ixIgROHjwYKEwYDKZMHLkSISEhODjjz/GpEmTcPbsWaSnpyMlJQXHjh3Dhx9+iAsXLgDIO+kfN24cbDYbxo0bh48++ggXLlxwzSQeFxeHtWvX4vnnn8f58+dv22uLjY2FxWLB3LlzsW3bNqSmpiI5ORmbN2/G0KFD3a7PnU8IgcOHD2PcuHE4c+YM0tPTce7cOUyYMAE7d+5Eo0aNCrU2unuOzp07o2vXrti7dy8GDRqEnTt3IikpCRkZGUhMTMThw4cxY8YMvP/++x6dAMydOxddunTBxx9/jGPHjiE5ORmZmZlISkrC7t27MXz4cJw6dQq1atVCu3btbuVtK1WBgYGoVasW4uLi8N///heXL192vdeTJk3Ct99+e9tnv46JiYGvry82b96MRYsWYe/evdi/f3+hGd/NZjP69u0Ls9mM7777DiaTCU8++eQNh0cUt46XX34Z48aNQ8WKFW+6f8OGDWGz2bBo0SJs3LgRqampSElJwbZt2/Dss88iNTW10GOEEK4u3vPmzcOGDRuwf/9+/Pbbbx6tM38jUkqsX78e//73vxEZGYl///vfCAgIgL+/P/7973+jcuXKeO+997B27Vqe3BKVYzk5OTh79ix++uknvP/++xgwYADatWuHFi1aoGXLlnjxxRdv6wV3IO/76eTJkxgyZAhatGiB7t27Y/DgwejXrx/uu+8+tG/fHgsXLkRubi6/n0oIu5cTEV2nUqVKGDFiBN58800MHToUU6dOhd1ux/nz5+Hr64sXXngBU6dOLfAYIQTuuusuzJgxA6NGjcLkyZPxySefICIiArm5uYiLiwMA3Hvvva79H3zwQfzrX//Cq6++iueffx6TJ09GxYoVoaoqrly5gqtXryIwMBAvvvjibXldQgjcd999ePDBB7F8+XJ07doV1apVg8PhwNmzZ9GkSRM89thjmDdvntvHW61WPPfcc5gzZw5Wr16NsLAwxMfH4+LFi4iKisJ//vMfj7rJ+/j4YMaMGXA6nVi7di02btyIqKgoeHt7Iy0tDZcuXUJ6ejqGDRvm0euy2+349ddfsX37dvj7+yMiIsL1XOfPn0dGRgZq1qyJmTNnIiIioljvmRa8vLwwZswYPP3005g6dSoWLFiAChUq4PLly8jMzMSIESOKHHd/q+rUqYM+ffrg888/R79+/VzjkJ999ln8+9//LrDvXXfdhcaNG2Pbtm2oW7cuWrVqpUnXxPzJ3Xr06IGvv/4ajzzyCKpWrQopJc6ePYv69eujT58++PTTTws97sEHH0SLFi2wdetWPPDAA1AUBSaTCXPnzkW3bt1uqZ78444ePRrZ2dmYPHlygfHb9erVwzvvvINBgwZhzJgxqFevHqpWrcpunUTl0HfffYdhw4YhMTHRbc+lW11+sSj5vX+eeOIJ/PbbbwDyhvSEhIQgOzsbly5dwp49ezBo0CCcPXsWo0aNum0XU+l/+I4SUZnUtWtXhIaGom3btgW2t2jRAi+99BLuvvtut48zmUwYNWoUYmJisGDBApw9exbe3t546qmnMGjQIJhMJjgcDjRo0KBAi6OiKOjZsyfuuOMOV3eta9euwd/fH82aNUPXrl0L/CE1m80YMmQIWrZsiYULF2LHjh24cuUKbDYb7r77bjRp0gSdOnVCdHR0sV+73W7H8OHDkZmZicjISNd2X19ffPLJJ2jRogW+//57XLt2DZGRkejfvz/69++PXbt2ISIiwrXedf7r6tGjB2JjYzFgwAB069YNn3zyCX7//XdUqlQJ3bp1w9ChQ1G/fv0CAcLLywsjRoyAEAJ2u921XQiBqKgoLFiwAKtXr8Z3332HY8eOIScnBxEREWjXrh3atm1baMx5UQYNGoSmTZtiy5YtruWm0tLSEBAQgDvuuANt2rTBI488gsqVKxd4vipVqmDcuHGoW7dugeerX78+xo0bh+bNmxc6vhACPXr0wB133OH251KhQgW88MILCAgIKDAeuWbNmhg7diwaNWpU4Dlr1aqFcePGoXHjxgWO8eCDD2Lp0qWYPXs2Dh8+DCEEOnXqhP79+6NevXpQFAW+vr4FjhEdHY0xY8agVq1aRb5vNWvWxJgxYxAbG1tgH5vNhunTp6NHjx7Ys2ePazm8Fi1aFHoOb29v1K5dG9u2bUOvXr0QEBDg9lg3kl9rRESER8uMeXl5YejQoUhLSytwYSd/jfZmzZph1apVuHLlCoKCgvD4449j4MCBOHToECpUqFBore/w8HAsW7YMGzduxOHDh5GZmQkArjXYo6OjMXr0aNSoUaPIXgXVq1fHuHHjcMcdd7jey1OnTuGhhx5ClSpV0KtXr0Jr0Hfv3h2pqak4deoUTp48edtPrInIGJKSknD58mUAeecCgYGB8PPzw+nTp0uklTklJQUvvPACfvvtN5hMJvTq1Qvjxo1DtWrVkJGRgXXr1mHChAm4cOECJk2ahHr16uGBBx7gRcHbTEj2ISAiKiR/TLXT6XQtEeXuD5C7baqqusZjCyFgMpkKjc/967EcDoerO5nJZILJZCqxP3jXH09RlBsuj+Xusaqqusal5s+qfSu1/vW5rn+fi/t8+c/ldDpdM6znt2Aa8cThr++N2Wx2GwBL+7XFxcXhnnvuQWpqKrZs2VLoooUW3H2e/7p0mxE/A0RUNq1evRoLFixAo0aNEBsbi+rVq+PMmTPo3LkzcnJy0LVrV6xcudKji5I3I6XEF198gSFDhsDpdOL+++/H/PnzXUt9AnnnLCtXrkSfPn2QkZGBli1b4vvvv4efn9/fPj79D1u6iYjcyA+At9LFSlGUYo27FULAYrEU+zi36u8cL/8iwu04GdDrc+mBnl7P9ZPbzZkzB2fPnsXjjz/uahnWWlGfZwZtItKjLl26oHPnzgUuxue3fN9uWVlZmDNnDpxOJ7y8vDB27NgCgRvIO2fp0qULOnbsiOXLl7uGbHXo0IHfo7cRJ1IjIiKiIp0+fRpDhw5Fjx49MHnyZAQFBeGFF17gmD8ioltQmr2wTp06hX379gEA6tatiyZNmrg9rtVqRY8ePSCEQHZ2NtasWVPitZU3/ItJRERERbp27RqWLFkCIG9c+Lhx49C0aVO2gBAR6dzvv/+OlJQUAEDTpk3h4+Pjdj8hBBo3bgx/f38kJydj9+7dyM7OLjAnC/09DN1ERERUpAYNGmDfvn0QQsDf3x9+fn4M3EREOielxKFDh1zzW9SrV++G+0dGRqJChQpITk7G6dOnkZaWxtB9G7F7ORERERXJZrMhKioKlStXLjQWkIiI9ElKiQsXLgDIa8m+fjUTd2w2G0JDQwEAqampSExMLPEayxO2dNNNOZ1O5Obm6mJCHyIiIiIqOfkrb+SvTqFn+atWaF3DXydPLWrFk9KkqiqSkpIA5K2KcrNeSiaTCf7+/gCA3NxcpKamlkaZ5QZDN93UmjVrMGXKlAJrwuqNvv8kAND5Hy0iohKh51VJhes/+qXr90/n7x3dMofDgWbNmmHKlCm6njBRSonVq1dj+vTpmtbhcDgKrKAQHByMDz74ACEhIRpWlff+ZGdnA8ibvO1m5/FCCNc+qqoiJyenxGssT/T7m0S6kZSUhK17DkOp2FCXf2QjnNnom3lBt2MlRFAFKM8OhbCW3pJQxeFvUhFlc2hdRpGuOCxIcur3qyrb4USmQ9W6jCJF+9vgZ9NnLxUhAB+bDYqiv+8VAJDOXDhTr+o3+AgBCH3+bAEg7cRJXFj0rW7fv9BWzRDcPFbrMoqUevgorm3fqXUZRbJ0fBim6nW0LsMtCSAxMxdOnX72AIFgLzMsJn2eufy8cQNOnjypdRkeuXjxIjbuOAAltL4m56hqahzuqhGI559/3tXabbfbi5ywzEi0bqkva/R7Jku6YTabAbMXRGAVCKG/PxB+jnS0VNKg21PPoDCY7+sC4eWldSVuhVgcqOedo8frKQCAs9k2XHbot5dFWo4DqTnadm27kQah3gjx1ucFHwEg0NcLpmKsaV6aZG42HFfPaV1GkSQAKBZdXgwFgMSde3Dkh81al1GkKg3rI6pLe63LKFKCjx0Xzp7Ruowi2Vq2hKVZK63LcEuVEhdTc+BQ9Rq6gcr+NtjN+vvuk1Ii8epV7N2+xTihy+INEVhVm3qdOYiMrIhHH31Ud8MwhRCuidBUVXW1ehdFSomsrCwAeV3NbTZbiddYnjB0ExERERGRMQkBoSjQZLiIji9MKIqCoKAgAHnzMyUnJ0NKWeTFifx9AMBisbjGd9PtwdBNRERERESGpk3LvH5DtxACUVFRAPJasc+du3HPrYyMDCQkJAAAAgICEBgYWNIllisM3UREREREZFAib/ijFqFbv5kbQgg0aNAAiqJAVVUcOHDghi3d58+fx7Vr1wAA1atXLxPj0vWEoZuIiIiIiAwpbyECocm8Q0LPqRtAgwYNEBQUhISEBOzevRspKSluW7CllNi+fTvS09MBAHfffbeuVy0yIv3N4EBEREREROQxfYffkiClREpKCpKSkpCUlASHo/BKNFFRUWjevDkA4MSJE9i8eTOkm1n9MzIysGjRIkgp4e3tjfvvv984E+kZBEM3EREREREZU/5EakKjm0ZSUlLQpUsXNGjQAM2bN8eRI0cK7WO1WjFo0CDYbDbk5OTg7bffxsWLFwsEb6fTia+++gq//PILAKBt27Zo3Lhxqb2O8oLdy4mIiIiIyNCM0jKbkpKCl19+GVeuXHFtu3r1qqulet++fejTp0+B19OjRw/06NGjwPNIKXHx4kVcuHABPj4+yM3NLXQsIQS6dOmCRx99FF9//TV27tyJJ554AmPHjkW9evWQmpqKZcuW4T//+Q9ycnIQGhqKV155xbXUGN0+DN1ERERERGRYeQHVGEuGZWdn47vvvsPp06fd3n/x4kUsWrSowLa6desWCt2e8vLywrRp03D16lWsX78emzdvxrZt2+Dj4wOHw4H09HRIKRESEoLp06fj7rvvNswFDCNh6CYiIiIiImMSAhCKNhOp3UI4VRQFkZGRUFXV42MEBAS4fZ5KlSpBVVX4+PjccOKzSpUqYf78+fjwww8xf/58nDt3DikpKTCZTAgJCUHLli0xevRotGzZEorC0cclgaGbiIiIiIioFFSoUAFr1671OHQDgM1mK7TNz88P33//PVRVhRAC3t7eRT5eCIGQkBC8/PLLGD58OM6cOYPk5GRYLBZERkaiUqVKsFgsbOEuQQzdRERERERkSEIICMWk0Trdt9bS7evrexsOLYr9PIqiICgoCEFBQX/7+FQ8DN1ERERERGRcQpuJ1NgyTJ5i6DY4KSUcDgeSkpIQFxcHKSXq168Pi8VSYD9VVXHu3Dns378f2dnZiImJQYMGDdx2VyEiIiIiMgYBIRSNAjBDN3mGodvgVFXFW2+9hfnz5yMhIQF+fn749ddfERoa6trH6XRi3rx5ePfddxESEgIvLy8kJibi448/RqNGjTSsnoiIiIjo7xFCGGYiNSqfGLoNTgiBO++8E40bN8aRI0cwY8aMAgveSymxe/duvPXWW5g2bRq6du0Ks9mM5ORkeHl5aVg5ERERERFR2cfQbXBCCDz88MMAgLS0tEL3Sykxe/Zs3HXXXejcuTOysrJgNptRoUIFXp0jIiIiImPLn0jNIOt0U/nEhdgMLq87jSgyQGdkZGD37t0IDAzEM888gzZt2qBDhw745JNPkJOTU2h/KSWcTiccDofrVpwlDYiIiIiISkv+GfD158SldeOYbvIUW7rLuMzMTCQlJWHhwoUYPXo0XnzxRWzevBmvvPIKgoOD8dhjjxUI7FJKvPfee/jpp59c2+Li4gBIN89ORERERKQtBmDSO4buMi7/SlxsbCxGjhwJu92O+vXrY9OmTViwYAG6desGk8lUYP/mzZujYsWKrm3bt2/HvhPfalA9EREREdENCAEIhROpka4xdJdx3t7eqFChAqpVqwar1QoAMJvNiImJwfbt25Gbm1sodLdq1QqtWrVybbNYLPhw7vJSr52IiIiIiMjoGLrLOLvdjqZNm+LkyZPIycmB3W6Hw+HA6dOnERYWVmg9byIiIiIi4xAQigJtJlLj9FjkGX5SyoAzZ85g8+bNOHLkCLKzs7F9+3b8/PPPSE1NhRACAwYMwJEjRzBr1iwcPXoUX3zxBX7++Wc8+eSTUBR+BIiIiIjI2LSYSI2dy8lTbOkuA3744Qd88skncDqdiIqKwltvvQW73Y5Zs2ahXr16aNasGaZPn47//Oc/+PTTT+Hr64u33noLDz74IMeiEBEREZFxCfw5nluLlu7SPyQZE0N3GTBw4ED069ev0HazOe/HazKZ0L17d9x///1ITU2Fr68vvL29GbiJiIiIyNAEkLdWtxZdvXkuTR5i6C4DTCZTgcnQ3BFCwNvbG97e3qVUFRERERFRSWPwJf1j6CYiIiIiImMSgBAmTVqdNWldJ0Ni6CYiIiIiIoMSfwZvtniTfjF0ExERERGRYQmhaDO+mkGfPMTQTURERERExqXVRGocT04e4kAEIiIiIiIyKAZf0j+2dBMRERERkTEJQJhM0CJ8C0UBIEv9uGQ8DN1ERERERGRQeWGbE6mRnjF0ExERERGRIQnXzOVahG4BtnSTJxi6iYiIiIjIuISiyURqbF0nT3EiNSIiIiIiIqISwpZuIiIiIiIyKAEhTFynm3SNoZuIiIiIiIxJiLwZzDUJwAzd5BmGbvJItDMT3dLPQNHhFb0soeAD7ypal1GkCk4bnl32BSxmk9aluJWZkY3dV5K1LqNIXlUrIjAiUOsyiuSd7YB/Vo7WZRQpO8eBy059TvKiWK3wGzwEpsBArUtxKzcpEXHzF0A6HVqXUgQBqWpdQ9EunozDjlNJWpdRpKsrfkHS0fNal1GkuLMX8cfhy1qXUaToj79GwMpNWpdRJCXACqtJn6MoBQBL3QhYfOxal+KW6cQerUsoFgFACEWT0M0x3eQphm7ySLCai/tyrsKkwy+X4yZvfOYVBVWHtQFAJZmL4Xt+gV3RZ/BJScjAhSPXtC6jSFXvikJQg3CtyyiSLSsH3joN3VJKpF9OQ2ZGrtaluKV4eUHt2xdAoNaluOVMz0DS9u2QDn2GbiklpEO/qTv+cjpOJmRqXUaRrHtPwPbHOa3LKNLZtBz8kZKtdRlFsiXtAOw6PY0UQIWqATBb9XmxGwDMak2YK/hoXUYhUkool88AphCtSykWIYRGE6mV+iHJoPR5CZCIiIiIiIioDNDpJUoiIiIiIqKbEFpOpMb2S/IMQzcRERERERmXZhOpEXmGoZuIiIiIiAxKQORNp6bJsYk8wdBNRERERETGpSgaTaTG0E2e4UAEIiIiIiIypLzgy/BL+saWbiIiIiIiMiyhKNAkeHMiNfIQQzcRERERERkau3qTnjF0ExERERGRQYm88dwahG4GffIUQzcRERERERmTwJ9rdWvR1ZuhmzzDgQhEREREREREJYQt3UREREREZEgCAkKYNOlerskxyZAYuomIiIiIyLiENuOrOaabPMXQbXBSSiQmJuL48eM4fPgwAKB3797w8vICADidTixbtgyXL18u9NjmzZujSZMm/MIgIiIiImMSIu9cluezpGMM3QanqipefvllrFy5ElJKSClx//33u0K3qqo4ePAgTp486XpMfHw8NmzYgC+++AJNmjTRqnQiIiIior9PKH+u1V3ax2XQJ88wdBucEALPPfccRo0ahY0bN+L1118vcL/ZbMbEiRMhpXRt++9//4ujR4+iXbt2bOUmIiIiImPT7HSW59HkGYZug1MUBfXr1wcA7Nixo9D9Ir/LzZ/S09OxdOlSdO7cGWFhYaVWJxERERHRbSe0m0hNKAzd5BmG7nLmt99+w5EjRzBp0iS3rdxSSqSnpyM7O9u1LS0trTRLJCIiIiIqFvbeJD1j6C5HVFXFkiVLEBMTg6ZNmxYZuidNmoTvvvvOtS05ORkVIQvtS0RERESkLZHX4qxJ6GbQJ88wdJcj165dw6pVq9C/f3/4+vq63UcIgREjRuCpp55ybVuzZg2+fnVSaZVJREREROQZAQAKhOBEaqRfDN3lhJQSW7ZswbVr1/Dwww8XuZ8QApUrV0blypVd2w4cOFAaJRIRERERFR+zL+kcQ3cZcP3M5H/dlt+F3Ol0YuHChWjevDlq1KjBcS9EREREZHgCIq+VW4OWbk1a18mQGLrLgO3bt2Pr1q3Ys2cP0tLS8OGHHyIwMBC9e/dGeHg4AODMmTPYsmUL3n33XVgsFo0rJiIiIiK6XQQblEjXGLrLgISEBBw5cgTe3t7o1asXzp8/j/j4eGRmZrr2uXbtGh5//HF06tSJX0pEREREVDYIAUWBJl3MeUpNnmLoLgMeeughPPTQQzfcp1mzZmjWrFkpVUREREREVPLEn//VplGJqZs8w4EIRERERERkXMy+pHNs6SYiIiIiImMSf04crEX3cjZfkocYuomIiIiIyNA4ZxHpGa/PEBERERGRYTFvk96xpZuIiIiIiAyME6mRvrGlm4iIiIiIDEurlm62sJOn2NJNRERERESGJITQbiK10j8kGRRDNxERERERGRonUiM9Y+gmIiIiIiLDEgq0aXZm0CcPMXQTEREREZGBaTSRGjM3eYgTqRERERERkXEx/JLOsaWbiIiIiIiMSUC7idTYvZw8xNBNnlEEYLFoXYVbwmSGVUg4tS6kCGYAuRIwSa0rcc8pFCgWHX8VmM1wCpPWVRRJVUxQFf3WB7MZMOvzwyfMFgg9N08IAWHW5/ceAEAC0O03HyBMOv69QF59Qqd/1wBAMTuh6PjXQzGb9XteIACYzZBmfX4GhRCAyQyp178dirE6wub/mjAAk57p+Eyb9ETUqQvzm/+GSYcnUTUux+HTxZ8Bqqp1KW5dcyp4IT4UOVKffwzaNqyGN9+5T+syirQ/XcH3mfp87wDALATMOj0/EQDqBXkjyK7Pr3rFZIJSIUjrMopkDY9AldenQEp9XrQAJIRTv6E7Z9MuYPubWpdRpMg+3dHk6Z5al1Gk6J9+QvTXX2tdRpH8+g6EvVETrctwSwLIhIRD60JuwBHqC5NVf+dUAODMXgjs3691GcWiUUM3kcf0eSZG+uPtBVGtGoRZfx8Zu0UizJoLodPQfT7XjFO5FmRJfSazBl7+CKhVTbdXiJ1xuUhK0G+wsJgEbBZ9njgBgBrpD4ufTesy3MpvjdIrYbHCFlVF6zKKJiUgnbo90bRUPKN1CTdkDQmGb52aWpdRpKzjhxDoa9W6jCLZKkfCXKuG1mW4JaVEZrYDur1eBkD6WaHHK7ZSSsDHX+syiknk/Z8G5zF6/f4l/dHfbzsREREREZGntEq/TN3kIf02MRAREREREd0IJ1IjA2DoJiIiIiIiQ2MAJj1j6CYiIiIiIkMSAIQCdvUmXWPoJiIiIiIiYxJ5/9GkpZtBnzzEidSIiIiIiMi4GH5J59jSTUREREREBiWgcCI10jmGbiIiIiIiMjSu0016xtBNRERERESGJISGE6kxdZOHGLqJiIiIiMjQ2NOb9IwTqRERERERERGVEIZuIiIiIiIyLK0mNONEauQpdi8vJ6SUcDqdcDgcsFgsUBSFXxREREREVCbwvJb0jKHb4KSUOHDgAH7++Wfs3bsXZrMZU6ZMgb+/v2uf7OxsLFy4EEuWLEFKSgrCw8MxYMAAdOjQASaTScPqiYiIiIj+hj8nUtMkczPnk4fYvdzgVFXFhx9+iM8++wz79+/Ht99+i6ysLNf9UkrMmzcPY8eOxT333IMxY8agYsWK6N+/P7Zt2wYppYbVExERERHdOgFAQEAIDW5av3gyDIZug1MUBZMnT8bGjRvx3HPPFepaI6XEqlWr0LZtW4waNQr3338/3nzzTYSEhOCnn37SqGoiIiIiIqLygaHb4IQQqFChAnx8fIocyxIWFobExERkZWVBSomUlBRkZ2ejcuXKpVwtEREREdHtJRSR3+RdqjeOIydPcUx3GSeEwMiRIzF06FA8/vjjqFmzJnbv3o327dvjsccec9syfurUKVy9etW17eTJk6VdNhERERGRxxiASc8YussBh8MBq9UKs9kMRVFgsVhw5coVpKamwt/fv8CXlJQSn376KVatWuXalpSUhNCoGC1KJyIiIiIqmhAQCrSZ1Iw5nzzE0F3G5eTkYOzYsYiKisKMGTNgt9tx9epVPPLII5g+fTr+/e9/F9hfCIGJEyfipZdecm1bsmQJ/u+zL0u7dCIiIiIiDwhtWroZuslDDN1lXEpKCo4ePYpu3brBbrdDCIHg4GDccccdOHDgAJxOJ8zm/30MhBDw8vKCl5eXa9v1/5uIiIiISC+Ye8kIOJFaGaCqKhwOB1RVhZQSTqcTDocDUkr4+PggJCQEO3bscE2kdvXqVfz222+oUqUK1+kmIiIiIuMSgPLn8l2lf2PkJ8+wpbsM+Oabb7Bo0SKcPXsWiYmJeOaZZ+Dn54c333wT1atXx8iRIzF69Gj07t0b1atXx+7du3Ht2jUMHTpU69KJiIiIiP42TqRGesbQXQbUrl0bDz30UIFtZrMZgYGBEEKgZ8+eqF27NjZu3Ihr166hb9++6NixI6pVq8YvKCIiIiIyNJHf9KzFcYk8wNBdBjRq1AiNGjUq8n6TyYTY2FjExsYW2M7ATURERESGJzSaSI3dy8lDDN3lBAM2EREREZU9Qrvsy9Nr8hBDNxERERERGZIQeY1LQin9BMw2LfIUZy8nIiIiIiIiKiFs6SYiIiIiIsMSijatzkIIQJb+ccl4GLqJiIiIiMiYRN562Zy/iPSM3cuJiIiIiIiISghDNxERERERGZKAdhOasXGdPMXu5UREREREZGjsXk56xtBNRERERETGJcA1s0nXGLqJiIiIiMiw8tbq1uLAt+dppPzfFOil0WJ//fFK65jlHUM3EREREREZk9AyNN76caWUSEhIwI8//ohffvkFly9fhs1mQ926ddGxY0fExsbCbDbfltcmpYSqqjh58iQ2bdqEffv2IT4+HlJKhISEoGHDhmjTpg1q164Nk8nEEF4CGLqJiIiIiMiQ8pYLA4RS+kHxVrOpqqpYu3YtXnrpJRw8eBBOp7PA/VOmTEGfPn3w5ptvIjQ09G+FYCklkpOT8e6772L27Nm4cuVKoZZuAAgKCsITTzyBiRMnomLFigzetxlDNxVT4V9SrQkAkIW7yuiHhCKEbocaCSEg9fz+6bSsfHr/oyTyf0F0Sd/vHQBASh2/exLQ6++tEQjo+/3T8/eyAeR99en0/fvfiYvWlRRigG9lw5NS4vvvv0f//v2RkJAAi8WCxo0bo169ekhLS8O2bdtw8eJFfPzxx4iPj8dnn32GwMDAWz5eRkYGnn/+eXz11VdQVRVeXl5o2LAhatasCSEE/vjjD+zbtw/Xrl3DBx98gNOnT2Pu3LmoUKHC7XvRxNBNnvEzqWjomw2zyaR1KYWkIgO/H0yA/MtVQr1QQkOw+M0+EFar1qW4deTsFTwwbo7WZRTpsftbo1urRlqXcQNCt6EMAELsAl4mfVYoBGDS8xleehLUnasAVdW6EvfMVliq1QV0+L0MABVlEtrXDtK6jCLF+EmYM69pXUaRMhMSceFkktZlFKlqZi78zPr8BRYSiMyOhwm5WpfingSsGSYoGrTMesI3S7+/F27lt3Jr8HYW97q7lBIXL17EmDFjkJCQAC8vL7z11lsYPHgwfH19oaoqTpw4geHDh2PDhg1YsWIFZs2ahbFjx0JRir/Ss5QSy5cvx9dffw1VVREZGYmZM2eiU6dO8PLyAgBkZWVh48aNGDZsGM6cOYM1a9Zg7ty5GDFihO4bFoyEoZs8YhESgWYnzDr8A6vCgYzkbN2Gbh9/Ffc0iIbZ20vrUty6lpqJLftPa11GkTq1vhOV/e1al1Ekp5RQ9ZlpAUjYhQqz0GuBeq3rT45cIOE8oOrzu0VabRCR0RBmff4pt8schPnbtC6jSL4WQHHmaF1GkZzZOchM12loBCCdEmadhkYhJfyRBQv0+fOVAOBUAFV/75+UEmY1W+sybok2AbH4x5w3bx4OHz4MAOjXrx+ee+45WP9smFEUBbVr18bMmTPRsWNHXLhwAbNmzULfvn1RuXLlYh/L4XDgm2++QW5uLhRFwYQJE9CtW7cC75W3tze6du2KN954A4MGDYLT6cSyZcvwzDPPwG7X7/mX0RT/kgkREREREZFu6O8ChjtpaWlYtGgRpJQICAjA0KFDYbFYCuwjhEDt2rXRq1cvAMC5c+ewbt26Wxpukpubi5MnTwIAfH19ce+997q9OCGEQJs2bRAUlNc76fz588jKyir28ahoDN1ERERERGRYWvWCLu5x//jjDxw9ehQAUL9+fdSuXbvIEPzAAw/AarVCVVX88MMPhSZb85TpzyFIiqLAZiu695HVanXta7FYbqk7OxWN7yYRERERERmYgBClfysOKSUOHDiA9PR0AEDjxo2LDMFCCNSpU8c1mdnvv/+OzMzMYr8rVqsVdevWBQCkp6fj0KFDblvMpZQ4duwYkpKSAAANGjSAt7d3sY9HRWPoJiIiIiIiQxJCQFHyWp1L+1bcpu7jx4+7Qm+NGjVuGNz9/f0RFhYGALhy5QquXSv+BHcmkwlPPfUUfHx8kJubi6lTp+LMmTMFgreUEhcuXMDbb7+NrKws+Pn5YciQIa5Wb7o99Dn7ChERERERkYe0mEituEeMi4vLe5wQCA8Pv2HNdrvd1dKdlpaGlJSU4tcnBNq3b4/x48fj7bffxi+//IKuXbuiZ8+euOOOOyCEwKFDh7Bo0SIcOnQIQUFBeP3114sc+023jqGbiIiIiIiMS8OAmJGRgTNnzrhahk0mE8LDw2F2s7JEcnIygLww7Ofnd8PnNZvNri7eOTk5t9S9HMgbnz127Fg0atQI06ZNw88//4xJkyYV2EdRFHTq1AmvvvoqmjdvzlbuEsDQTUREREREhpXX1VubA//yyy/o0qWLq2W4YsWK+Oabb1xdw6+Xm/u/ZQD/Omu5O9fvc/1ji0NKiZSUFPz++++4dOkSpJSwWq3w9fWFEALp6enIysrC7t27MWvWLISEhKBmzZps6b7NGLqJiIiIiMjQtAqJrVq1wqxZs1yzfZtMJoSEhLjd9/oWZE9mI79+n1tpfZZS4tKlSxg4cCB++OEHWCwW9O3bFwMGDEBMTAwURcHZs2exYMECzJkzB3PnzsWvv/6KRYsWoV69egzetxFDNxERERERGZIQgCKEJj3MFQF4eXmhcuXKHoViX19f1//On8W8KKqqurqUm81m2O32YtfndDrx1ltvYd26dRBCYMyYMXjllVcKzJoeHR2N5s2bo1atWhgzZgwOHTqE8ePHY+HChfDy8ir2Mck9zl5ORERERESGlTebuL6XDAPyup4DeS3QCQkJN9w3OzvbNXmat7d3gcDuqTNnzmDx4sWQUqJ69eoYMWKE22XKLBYLBg4ciDvvvBMA8NNPP+HQoUPFPh4VjaGbiIiIiIgMKW/lLoH8Yd2leitm7q5evTqAvNB96tQpt2tm50tLS0N8fDwAoEKFCggKCirewQAcOXIEV69eBQDExsYW2e0dAPz8/NC8eXPXsRm6by92LyciIiIiImMSAooAhKLBkmHFTN316tWD3W5HVlYWfv/9dzgcDrcTqkkpcebMGVdreM2aNW8627k7SUlJrmDv5+d3w3qFEAgICHD9+1aWKKOisaW7nJBSwul0wuFw3PCqGhERERER3V5CCNStWxeVKlUCAOzbt8+1brc7GzduREZGBgCgbdu2bpcgu5mAgABX0L548SIcDkeR+6qqivPnz7v+nb9GON0ebOk2OCklTp8+jV9//RX79++HoigYM2ZMgXEfubm5WLNmDZYtW4b09HQ0b94cAwYMQFBQEGclJCIiIiLDEgAURbuJ1IojKCgIXbt2xcyZM3H58mUsXrwYo0aNcs18nu/q1av46quvAOSF3wceeMDtOfvhw4cRHx8PIQSqV6/uCvT5YmJi4Ofnh+TkZPz66684fvw46tat6/a5zp8/j02bNgEAfHx8ULt27eK9OLohtnQbnKqqmDJlCl5++WUsWbIEn3zyieuqGJAXyj///HMMHz4cUVFRuO+++7B06VI8//zzyMrK0rByIiIiIqK/zzWuW+cTqQkhMHjwYISGhkJVVUyfPh2bN2+GqqoA8s7b09LSMHnyZPz+++8AgEcffRR16tRx+3yTJ09G+/btce+992LJkiWF7o+JiUHLli0BAPHx8XjxxRdx9uzZAr1e85cVGzduHE6dOgUAuOuuu1C3bt1ivz4qGlu6DU5RFLz22mt4++238d1332HChAkF7k9JScEHH3yA/v3747XXXoOiKGjRogW6du2K7du3o127dmztJiIiIiJDEgLIm0ZNk6MXb28h0KBBA9fSXRcvXkTv3r3x5JNPomnTpkhJScGyZcuwYcMGqKqKevXqYcKECUV2LVdV1RXY3bHZbHj55Zexd+9eXLp0Cd9//z06dOiARx99FA0aNICiKDhy5AiWL1+OgwcPQkqJkJAQTJw4kcuF3WYM3QYnhEBkZCQAuF0fMCUlBZcuXULTpk1d91erVg1+fn7YtGkT2rVrV5rlEhERERHdVoqC4ubf23PcWzimoih47rnnkJ6ejunTpyM+Ph7/+c9/CuwjhEDjxo3x0UcfISYm5pYbyIQQaNGiBT7//HO8+OKLOHz4ME6cOIFp06a53bdWrVqYNm0a2rZty0a524yhu4yz2Wzw9vbG+fPnXV1JkpOTkZKSgj/++KPQ/lJKXL58GWlpaa5tly9fLrV6iYiIiIiKyyghUQgBLy8vvPLKK7jvvvswZ84c7N69G1evXoXVakXVqlXxwAMPoE+fPggLC7vh67rnnntcz1mrVi23+yiKgs6dO6NRo0ZYvnw51q5dixMnTiApKQlA3mRrMTEx6NSpEx599FFERkYa5r00EobuMi44OBidO3fGhx9+iNq1ayMyMhL/93//h8TExAJjv/NJKTF9+nSsWLHCtS0lJQX1a9cozbKJiIiIiG5KQEAR2kyk9neOaTab0bp1a9xzzz3IyMhAbm6uK5BbrVaPgu/w4cMxfPhwD+oUiIiIwLPPPovBgwcjMzPTNZO52WyG3W6H2Wxm2C5BDN1lnKIoeP311/HGG29g5MiRMJvNaNeuHZo2bep2KQAhBCZMmIBRo0a5ti1fvhxLvv6qNMsmIiIiIro58ee4bg0C4+0YS64oSoFVh0qSEAJms/mW1vymv4ehu4wTQqBixYp4//33kZqaCiklpJRo27YtGjdu7Hb/wMDAAtsCAgJKqVoiIiIiIs+5Zi7X4thsGCYPMXSXAflBOn/MtpQSqqq6ljNwOp1QFAWBgYFQVRXz589HdnY2unbtqnHlRERERER/j0kA4lZmNfubGLrJUwzdZcDq1auxatUqHDt2DElJSXjppZcQEBCAkSNHomrVqli6dCl+/PFHVK9eHSdPnsSPP/6IiRMnomrVqhy7QURERESGxTNZMgKG7jIgMDAQVapUQZUqVdCxY0cAeZMi2Gw2AEBsbCyOHDmCEydOIDQ0FPPmzUPTpk2hKIqWZRMRERER/T0Cmk2kpjDyk4cYusuAe+65x7VkgDs1a9bExIkTIaV0tWyzhZuIiIiIjC5vTLdG57Y8nSYPMXSXAwzaRERERFR28RyX9I2hm4iIiIiIjEkImBRokrs1mLuNDIqhm4iIiIiIDOnP/pzs0Um6xtBNRERERESGpSjahG4hOCkxeYahm4iIiIiIDI0t3aRnDN1ERERERGRIQoi8JcM0ObYGByVDYugmIiIiIiLDEiKvi3mpH7fUj0hGxYEIRERERERkWAy/pHds6SYiIiIiIkMSQF73ck2WDGPcJ88wdBMRERERkTGJvJsmE6kxc5OH2L2ciIiIiIgMKS9zM/2SvrGlm4iIiIiIDEtRtJlJXIO528igGLrJIxICDikAqcWxb9x7RxUKzDYTpNPdvQKaFH0dk9WELCdgcmhbR5EUEyr4+2hdRZFUKXEtOU3rMoqkmM1QzPr9KjWZJSD0+dnT/ZqqQgBmK6A6tK7ELWG2QlVMgDBpXYpbDijIdqi390lv9gfhRvf/5T6HCqg6bh0T5ry/bXolFcCh6vS7RUrkSAVS6rdDp6KY9PkdKPLOq4xGwAB/U6hc0++ZIulKqtOEA5k+MJn0dwJg9g5C7KMNAPU2n9zdJhk+QZh3ygGnOVvrUtyKqFwDP899WesyivR/C9aj1VOTtS6jSI3vbowW7VtoXUaR7qzkjzBfm9ZluKUoAnW9JGw6Pb8TXr6wxrYDpD6/W5yKGRe9o3V7gnwqNw6rD1zR+rpnkdpck/C1BGtdRpF8akahSbf6WpdRpAt+dly8kq51GUU6KkP0e0lFADWCvOBj0d85FQCk2kMBHNO6DI9pu063bj9lpDMM3eQRCSBXCkgdTgMghAKL3QKh0xPjbJsZGQ4Jtw3xeqCYEVrBT7d/OJyqxJXEVK3LKFJiWiYycvX52QOAHKeEbjtZ6LSVzEUICIsNuk2NwgSnYobUaeh2SAVZOv7dyFWh2/cOABSzCVYvi9ZlFEnPLd0AoELR7d81SMApzHk9VXRGSqnr34sb0eLnrdNPGOkQQzcRERERERmSa8kwrQshugGGbiIiIiIiMiwh8oYslTau002eMmb/ESIiIiIiIiIDYEs3EREREREZkhCASQhNlgxjQzd5iqGbiIiIiIiMS3AmcdI3hm4iIiIiIjIkgbwlwzQY0s0x3eQxhm4iIiIiIjIkIQBFaBOAGbnJU5xIjYiIiIiIiKiEsKWbiIiIiIgMS7uJ1NjWTZ5h6CYiIiIiIkMSf/5HiwDMyE2eYugmIiIiIiLDEhDaBGCmbvIQQzcRERERERmSEICiAIoG05drMWM6GRNDt8FJKSGlREZGBnJycuDj4wOr1Vqoi42UEpmZmcjKyoKfnx/MZjPHoRARERGR4fGMlvSOodvg9u3bh//+9784ePAgcnNzUaFCBQwZMgQ9e/aExWIBADgcDixYsACzZs1CWloaqlWrhtdeew2xsbEM3kRERERkYHnrdHMiNdIzLhlmcAcOHEBwcDDeffddzJkzB126dME///lPrF69GkBeC/eGDRswfvx4PPnkk5g9ezaCgoIwePBgXLlyRePqiYiIiIj+pj8nUivtG5Gn2NJtcL169cKTTz7p+uWvU6cOfvzxRyxfvhwPP/wwVFXFp59+itatW2PIkCEwm81444030Lp1a6xbt871WCIiIiIioxEC2rV0l/4hyaDY0m1wNpsNiqK4grOUEg6HA1arFQCQkpKC33//Ha1bt3aN4w4LC0PdunWxdetWLUsnIiIiIvpbBP4XvEv7xnYr8hRbussQKSXWr1+PAwcOYNy4cRBCID09HcnJyYiIiHAFc7PZjIoVK+LChQtun2P37t04d+6ca9vOnTtL7TUQERERERGVJQzdZYSUEnv37sXo0aMxcOBAtG/fHgCgqiqcTifM5v/9qIUQMJvNcDgckFIW6F6eH9zXr1/v2nb58mV4B1UsvRdDREREROQJAZg0anVW2NRNHmLoLgOklDhy5AgGDx6MNm3aYOLEia6Zy61WK7y8vJCSkuLa3+l0IjU1FQEBAYXGcwshMGbMGIwePdq1bdGiRXj/o9ml82KIiIiIiIpDcCZx0jeO6TY4KSVOnjyJp59+GvXq1cO0adPg4+Pjuj8gIACVKlXCwYMHIaUEAGRmZuKPP/5A/fr1Cz1ffiu4xWJx3UwmU6m9HiIiIiIiTwkAAuLP/1/KN+Z88hBDt8FduHABTz/9NIKDgzF16lRYrVZkZWUhJycHUkrY7XY89NBDWLFiBU6fPg2n04kffvgBFy9eRJcuXbQun4iIiIjolgkIKAJQFFHqN8H5y8lD7F5ucPPmzcPWrVtRo0YN9OjRw7X9nnvuwZQpU2A2m/H0009j8+bNePjhh1GlShUcPHgQ//jHP9CoUSN2xSEiIiIiY9PqdJan0eQhhm6De/zxx9GiRYtC24OCgqAoeR0ZQkNDMX/+fPzyyy+Ij4/HxIkT0bhxY3YbJyIiIiJj03QiNcBZ+oclA2LoNriqVauiatWqN9xHCIHAwEA88MADpVMUEREREVEpYu9N0jOGbiIiIiIiMiSBvKW7tMjcHNNNnmLoJiIiIiIiQxIi76bFmtlsXCdPcfZyIiIiIiIyLoZf0jm2dBMRERERkWFpNZEaW7rJUwzdRERERERkUHnJlxOpkZ4xdBMRERERkSEJASiKVkuGMeiTZxi6iYiIiIjIsPJnMCfSK06kRkREREREhiRc/yHSL7Z0ExERERGRYZk0WjGbrevkKYZuIiIiIiIyNE6kRnrG7uVERERERGRIQmgXuBnzyVNs6SYiIiIiIoMS2k2kxtRNHmLoJo+oEsh1qlCFqnUphTlVqE4nhKrD2gBIpxMmRUDq9ItZKIAEIKXUuhS3AgIDEBkdqXUZRTKZTLhw5oLWZRQpI9gGp69N6zLcUwT0+an7k1AgzVZAp1VKmKBKQNVpfRaLCWFBXtDr+2e1mpCe49S6jKLlOICsXK2rKJIZgM2k1w6TEuk5KlSpz/MCIYBshwqzos8TA4eqz99ZIiNj6CaP5KoqrmbmwmTW3xexV0YOglMzIXT6x9UpvGG3KHCaTVqX4pbFpMCpvx+rS2yLxnBGV9e6jCLt+nkXFny8QOsyilR7bD9EBPtrXYZbJhXQ6bUeAIBUzHD6h+m2SIcEctL1G7qDA214uE2U1mUUKS3EG8cTs7Quo0g+V9LhfzFJ6zKK5CslfHytWpfhliqBXUlJyMjV53mBABBoM8PXps/T8OQsHV+MciOvlVubMbN6vexE+qPP33aiMkZA3xN8SCn1W58QUBT9/lkTELrtJQDoNi8ai15/N/T+sxWc2ffv0PuPF9Dx3zUpdf3+Sej355v390yv1RUt7zxL6yqIisbQTUREREREhiUUoUno1u2FJ9Idhm4iIiIiIjIkIfTfo5BIv302iYiIiIiIdIoxnzzFlm4iIiIiIjIkAcAkhCYBmI3r5CmGbiIiIiIiMjR2Lyc9Y/dyIiIiIiIyLK0Ctzbt62REbOkmIiIiIiLDylurW4vpy0v/kGRMbOkmIiIiIiLj0ij8MnOTp9jSTUREREREhiQEYII2AZihmzzF0E1ERERERIbGedRIzxi6iYiIiIjIkAQEhCI0Cd0M+uQphm4iIiIiIjIsAa1mMGfqJs8wdBuclBIAkJubC4fDAZvNBkVRCnzx5O9zPa5lSEREREREVPIYug3u2LFjmD17Nvbs2YOMjAxERkZi8ODB6NixI0wmE6SUOHXqFNauXYtff/0VycnJmDx5MmrVqqV16UREREREf4sQecuFadGcpLANizzEJcMM7ueff8bFixfxzDPP4K233kK1atUwcOBAbNiwwbXP2rVrMXv2bMTFxWHNmjVITEzUsGIiIiIiottLCFHqNyJPsaXb4B5//HH0798fJpMJQgi0aNECu3fvxuLFi9GhQwcAQL9+/dCvXz8cO3YM7du317hiIiIiIqLbRxHatCQyd5OnGLoNzsfHp8C/TSYTLBYLVFUFkHfVL38fRbn515G78d9ERERERHok8m9azF5e+ockg2LoLkOklNi6dSv279+Pf/zjH7fU7UVKiYULF2LPnj2ubUeOHLmdZRIRERER3T5Mv6RzDN1lhJQSx44dw8iRI9GtWzd07dr1lp9LURSYTKYC/yYiIiIi0h8BBdpMpKbNUcmIGLrLACklzpw5g8GDB6N27dqYMmUK7Hb7LT2XEAK9evVCr169XNsWLlyIKTNm3a5yiYiIiIhuK05sRnrG0G1wUkpcvHgRQ4YMQYUKFTBz5kwEBgbe8vPxC4uIiIiIjEKI/JnLtTk2kScYug0uISEBzz77LJxOpytwOxwOCCFcM5qrqgqn0wmHwwEAcDgcyM3NhclkYtdxIiIiIjI05c+1uksbG6vIUwzdBjdnzhysXr0ajRo1wtChQ13bmzVrhokTJ8JsNmPnzp2YPHkyEhMTkZaWhjFjxiAwMBAvvvgi7rvvPg2rJyIiIiIiKtsYug2ua9euqFKlSqHtERERrlbs6OhoDBgwwLWMWL4aNWqUSo1ERERERCUhb7kwrSZSI/IMQ7fB1a9fH/Xr17/hPpGRkejevXspVUREREREVHrygzeRXjF0ExERERGRIQn8OaZbi2Mz55OHGLqJiIiIiMiYRH5LtyaHJvIIp64mIiIiIiIiKiFs6SYiIiIiIsPSbiI1tnWTZxi6iYiIiIjIsDiRGukdQzcRERERERmSgMhr6dZiTDdzPnmIoZuIiIiIiIxJ/Dl7uQYJmKGbPMWJ1IiIiIiIyJCE6z9E+sWWbiIiIiIiMiwF2uRuZn3yFEM3EREREREZGrt6k54xdBMRERERkSEJ5I3n1mLMLGdMJ08xdBMRERERkaFpEYAZuclTDN3kEZMQ8LYoUEz6m3vPZhJw5johVFXrUtySDhU+VhNUi0nrUtzyMitQBABIrUtxy24S8LXq870DgOAAH1SODNW6jCKlZ2Th3IV4rctwy2JS0DjSD9Dp7wakE8hI0elvBiAkYFWtUKU+T/scqgNOrYu4AasiIRX9VmiFCtWpz79rAACp38ChCCDAZobNpM/3TwDwNgN2RZ/fLha9/mBvwIAlUznD0E0e8beZ0CTCFyaT/j4y2Rk2XIxLgXTq8+TJ5PBGq6hACJtd61Lc8jJJeAt9vncAUCfUC8G++nzvAKBFlTYY+PA9WpdRpCnvL8B/P16idRlu+Xnb0eKrV+EbGaJ1Ke5lpELuXQvo9IKeyWxBlco1AUV/F0MBIDUrDme0LuIGomy5CPHL0LqMIl0RGTiXlKV1GUXycqowm/QZdYRQ8EDNYFh0Wh+khCknDYqaq3Ulbu20O3Fc6yKKIW+NbqHRRGo6/YyR7ugvQZEu5Y+XMSn6+3JRAEhV6rWhNu+PqxAQOnzvALhaufU6LEmBgA47WLhYTCbAps8CpZRQVRU5OQ6tS3Er2+zQ7a+ti9MJSH2GbqgKhFR1e9IndP7TFZDQayYDjNFyp9fxrAKASREw6/TvLmTe3149vn1SSkN89tzR6+exPJBSQkqJ9PR0pKSkwPmXhjBFURAREQGTSac920oBQzcRERERERmWVhcxmPPzAndaWhr++9//4ptvvsHVq1cLhe7AwED89NNPCAsL06hK7TF0ExERERGRIQnkhV8tOjYwdOeZOXMm3n33XXTt2hVNmzaFzWYrcL/NZoOvr69G1ekDQzcRERERERmWkbOv0+lEZmYmcnNzoSgK7HY7rFZriXaXl1LC6XQiKysLTqcTQgjYbLZbOm52djbWrFmDvn374r333oPFYgHA7v5/xdBNRERERETGJKDhRGq3zuFwYNu2bZgzZw527dqFa9euwWKxoFq1anjggQfQp08fhIWF3dbwKqVEfHw8li9fju+//x7Hjx9HamoqbDYbKlWqhNjYWHTq1Alt27aFl5eXx8/pdDrRsGFDWK3W21ZrWcPQTUREREREhmakltXMzExMnToV06dPR2pqaoH7Tp06hZ9++gnz5s3DRx99hKZNm96W1+Z0OrFq1SpMmDABhw8fhvqXlTmOHTuGn376CbNnz8b69evRrFkzj57XbrejTZs2+PXXX5Gbmwuz2Wyon0VpYegmIiIiIiJDyl9hR4t1RG4lXDqdTsycORNvv/02cnNzUbFiRTz55JNo1qwZkpOTsWzZMmzYsAF79+7FgAEDsGLFCsTExPytIKuqKr766is8//zzSE5OhqIoqFy5MurVq4egoCBkZWXh3LlzOHnyJLKzswtNhHYzjz/+OIYPH45Jkybh0UcfRUBAQIH7849nNpff6Fl+XzkRERERERle3mRqpd+6WtwjSilx4MABTJs2Dbm5uYiIiMD8+fPRpk0bKEreZYO+ffti4sSJeP/993Ho0CG8/fbbmDVrlmusdHFJKbFt2zaMHj0aycnJqFChAsaOHYu+ffuiYsWKsFgsUFXVFbw3btyI0NDQYh1j6tSp2LNnD7Zv34733nuvULgODAzE1q1bER4efkuvoSxg6CYiIiIiIsMySmdmKSU+/fRTXLlyBYqiYNSoUQUCNwD4+vri5Zdfxk8//YT9+/dj2bJlGDlyJO64445bOmZ6ejpee+01XLlyBT4+Ppg5cyZ69+5dYM1sk8kEHx8f1KlTB7Vr1y72MZ5++ml06NChyPttNhv8/f1vqf6ygqGbiIiIiIgMKb+V2wgTqV27dg1r1qwBAISFhaFnz54FAne+4OBgPPnkk9i/fz8SExOxevVqNGjQoNit+VJKbNq0CVu2bAEA9OzZEz179iwQuP+quMcQQtwwcFMeLYY/EBERERER3TZCiFK/FYeUEkeOHMGFCxcAALGxsYiMjCxy/3bt2sHb2xsAsGnTJjgcjmK/J6qq4ptvvkFOTg7sdjv69+9/y93Ub0ZKieTkZOzbtw8//vgjtm3bhri4ODidTkgpS+SYRsKWbiIiIiIiMiQhAJMCKBo0dRf3mAcPHkRWVhYA4I477ihyYjEhBKpUqYLg4GBkZGTg2LFjSE1NRVBQULGOl5qaim3btgEAwsPD0aBBA0gpkZmZiQsXLiA1NRUWiwWhoaEICQmByWS65cnhvv32W7z99ts4fvy4ayK2kJAQ9OvXD2PGjIGfn1+5ntWcoZuIiIiIiAxNkzxXzGOePHky72FCoFq1ajcMob6+vggLC8O5c+eQmJiIxMTEYofuuLg4XLp0CQAQHR0Ni8WC+fPn44MPPsDhw4eRnp4Os9mM4OBg3HPPPRg+fDhatGhxw+7nf5XfhX3o0KGoX78+pk6diujoaKSkpOCHH37AzJkz4XA48NZbbxXrecsahm6Dy1+QPjk5GUlJSfD29kZISEiBriP5V7SuXr2K3NxchISElPurTURERERUFmgznjv/2FLKAmte36j7+eXLl137hISE3PCZr598LCMjA2lpacWuLiEhwfU4u92ON998E//3f/+H7Oxs2O12WCwW5Obm4ty5c/j666+xdu1aTJ48GUOGDPF4eS8pJWbPno3GjRtjwYIFCAoKghB570uPHj1Qp04dfPDBBxgxYsQNu9OXdQzdBhcfH4/Ro0dj7969rgDerFkzTJ48GdHR0ZBSYtGiRZgxYwauXr0KIQTsdjtGjBiBp556qlyvl0dERERExqb1RGq7d+9Gv379XCG7QoUKmDRpkttW6euDs4+Pzw2fW1EUeHl5AQAcDgcyMzOLXV9SUpLrgsD27duxceNG+Pr64sUXX8QDDzyAwMBAnDt3DvPmzcPixYuRmJiIcePGoXLlynjwwQc9aqDLysrCyZMn0adPH1fgBvJ+JhaLBQ8//DBmzJiBixcvMnSTcWVkZCA6OhrPPfccoqOjcf78eQwfPhzjxo3DnDlzYLFYkJycjCFDhqB169aw2WxYuHAhxo0bh5iYGLRp04Yt3kRERERkaFqdzwYHB6NFixauWch9fHxgtVrd7ps/1hmAR12tr9/n+sd6Kjc31/W/U1JS4Ovri48//hiPPvqoqzW+bt26aNu2LaKiojB16lSkpqZi8uTJaNu2rUfLfJlMJthsNsTHx7u9PykpCU6nE3a7vdj1lyUM3QZXpUoVTJo0yfWLEx4ejsGDB2PSpEmuCRcGDRoERVFcX0ZDhgzBF198gS1btqBNmzYavwIiIiIiolunWfuRAGJiYjB8+HC3S3/91fXDP68PxEW5fp9bmXX8r+H/0UcfxcMPP1ygViEEbDYb/vnPf2L58uU4dOgQ9u3bh71796Jt27YeHaNNmzb44osv0LJlS7Rp0wZeXl5wOBw4ffo03nzzTURFRSE6OrrY9ZclDN0G5+4XPD4+Hr6+vrBYLBBCFLqSlp6ejrS0NAQGBhZ6bH4X9fyp/fP/TURERESkO38Gbi2C9/WH9KSlPSAgAEDe+XVqauoN93U4HMjIyACQF2zzu5oXh5+fHxRFgdPphKIoeOSRR9yG9/wx5h06dMChQ4eQnZ2NX3/91aPQDQDPPvssNm3ahN69e6NevXoICwtDeno6Dh06BCEEPv30U/j6+ha7/rKEobsMkVLi6NGj+OKLL9C/f3+3H26Hw4GPPvoIQgh07drV7XNMnToV69evd22Lj49HxfCIEq2diIiIiOhWGGWg5PVjmi9dugQpZZFhPSsrC4mJiQDyZjL3pKv3XwUFBcHLywtpaWnw8vJC1apVi9xXCIHatWu7/n3u3DmPjiGEQGRkJBYtWoR58+Zhw4YNuHTpEry9vdG7d2/0798fDRs2LPfDWRm6ywgpJeLi4vCPf/wDDRo0wHPPPVeoFdzpdGL+/Pn49NNP8e9//xsxMTGFfgGEEOjSpQvq16/v2vbzzz9jz959pfEyiIiIiIg8JpA3f7miQfQu7vRtNWvWdM3sfeLEiRuG7pSUFNds56GhocVeLgwAwsLCEBgYiLS0NNfEZjdis9lc/zsnJ8fj4wghEBYWhlGjRmHEiBFwOp0QQsBqtXrU7b48YOguA6SUuHLlCoYOHQqz2YwPP/ywUNdxVVWxfPlyTJw4Ea+++iq6d+/u9pdcCIEmTZqgSZMmrm1ZWVkM3UREREREt0gIgQYNGsDHxwdpaWnYu3cvsrOz3XYbl1LiyJEjrpbuO+6445a6lwcGBqJOnTo4f/48cnJyXM/njpTSFfKBvAnibrRvfrBWFAWqqrqGpiqK4graqqq6Zk83mUzlurWbodvgpJRITEzEc889h+TkZMydOxfh4eEFPtRSSqxduxYvvvgi/vnPf2LgwIHlenF6IiIiIio7tMpyxT1u9erVUbt2bfz66684ePAgjh49ikaNGhUKo1JKrFq1Cjk5OVAUBR07drylc3er1YpOnTph/fr1yMnJwc6dO4tcuSg3Nxfbt28HkBec77jjjiKfd//+/Xj55ZfRokULvPzyy5g8ebLrse74+fnhww8/vKXW+rKC7f0Gl56ejlGjRuH333/H1KlT4e3tjYSEBFy9etU1IdqWLVvwj3/8A4899hh69eqFxMREXLlyBWlpaa6rUkRERERERiVE6d+Ky9fXF7169YIQAsnJyZg1a1ahWczz52hatGgRACAqKgqdOnVyG5QXLVqEl19+Ga+88gq2bdvm5j0R6NatG8LDwwEAX375JeLi4gqd/0spsW3bNmzatAkAUKlSJdx99903fC3uhqgWdSO2dBveH3/8gRUrVsBms2HQoEGu7RUqVMCiRYsQERGBefPm4dq1a1ixYgXWrFnj2qdv374YP368FmUTEREREd0WRop1ffv2xZw5c3Do0CF8+eWXqFmzJoYMGQJfX1+oqooTJ07gueeew4ULF2AymTB06NACE7Bd79tvv8WCBQsAABUrVkSLFi0K7RMTE4NnnnkGb731Fg4ePIgRI0bg3XffRZUqVWAymZCbm4tdu3bhueeeQ0pKChRFweDBg1GpUqUiX0OjRo2wfPly179ffvnlm77u8j62m6Hb4GrXro2dO3cW2q4oCipWrAghBN58802MHTu20D75yxYQERERERmRwJ8tzxodu1j7C4GIiAhMmzYN/fv3R0JCAsaPH4+vv/4a9evXR2pqKrZt24aLFy9CCIGHH34YQ4cO/VuB1WQyYeTIkdi3bx9WrlyJZcuWYefOnWjWrBkqVKiA8+fPY+fOnUhOToaiKOjWrRuef/75Gx7z+iWJ81vJ/fz80KhRo0L7JiQkYOvWrejYseMtjUsvKxi6Dc5ut6NGjRo33Ce/SwkRERERUVlklF7M+SsFffnll3jppZdw8OBB7N69G7t373bt4+fnhz59+uDNN9+8LY1kgYGB+PTTT/H666/jq6++woULF3DhwoUC+wQHB6N///6YMGFCsY/5r3/9C3Xq1HEbuo8dO4Z//OMf2L17N0M3ERERERGRERklcOdTFAVdunRB06ZN8eOPP2Lr1q24dOkSbDYb6tati44dOyI2NhZms/mGY6KHDRuG+++/HwDQtGnTIvcTQiAkJATvvfceBg8ejPXr1+PgwYNIS0tDYGAgGjVqhPvuuw+1atW6pVnGpZRu54mSUrqWHivvY7sZuomIiIiIyNA0yXR/45hCCISGhqJ3797o3bu32/tvplWrVmjVqpXHx7NYLIiNjUVsbGyR+3jq8uXLrhnLL126BLPZXGCcN5C31vfixYsRGhoKb29vj5+7LGLoJiIiIiIiw9KqDfV2HLe0W4Bv1/H279+P/v37Q0qJzMxM7N+/H+vXry90rMDAQLz66qvw8/O7Lcc1KoZuIiIiIiIyJPHn/ykaRO/y3GG6efPm2LBhA6SUGDduHKpUqYLhw4cX2MdkMiEsLMw1uXN5xtBNREREREREHgsICMCdd94JKSVmzJgBLy8vVK1aVeuydIuhm4iIiIiIjEkYbyK1skQIgbp160JKCafTiezsbDgcjkL7+Pj4lOu1uhm6iYiIiIjI0Bi8teN0OrFx40Z88sknOHr0KHJycgrMZh4QEIAVK1YgNDRUwyq1VX4vNxARERERkeFpNpEagz6klNi0aROeeuoppKSkICkpCf7+/mjevDmklIiPj8ddd90Fm82mdamaYugmIiIiIiJDEsgLvwKlf6O80D179mw0b94cX3/9NerWrYtOnTph9uzZ2LBhAzp06AAA5X7JMIZuIiIiIiIyNCFK/0ZAVlYWTp48ifbt27vGbTscDgghEB4ejlGjRmHlypU4f/681qVqiqGbiIiIiIgMy8jrdBudEAJCCFitVggh4O/vj0uXLkFVVQghEBAQgNzcXFy5ckXrUjXF0E1ERERERIbG7uXasNlsqFq1Kk6ePAkhBBo3bozNmzfjwIEDuHbtGpYuXYqcnBwEBQVpXaqmOHs5eURRBGwWM0wmk9alFKIEVUDwve0BVdW6FLeUgArw8bZBmPX562ZRAJNZ3nxHjfjaJVSTfutzqhJOqd/67mtWB9HBflqX4ZbdZoGPl44nVrFYYYqsAUh9frdAMUMEhEIIfV4/t1ZyoEKrdlqXUSTvarUg7L5al1Ek72o1EHLffVqXUSRrVCWY7Baty3BLCMBiNsGk6DUWSQhph9DpeYsw6/PneiPa/aT1+hkrPUIIdO3aFatWrUJ2djZ69uyJefPmoVOnTggICEBcXBwGDhyI6OhorUvVlD5TAOmOSVHg52WDWY/BsVpVBI1/ResqqIRUtAMVtS7CwF4d8qDWJRiW4uUHa6x+Q4/e+UTWhk/TtlqXYVhBbcMR1LaD1mVQSbHq84KjlBImu4/WZRRL3vhqAUWDQdYc15333j/++ON45JFHYLPZUKVKFSxduhRLly7F5cuX0bhxYzzyyCP6zBClqHy/eiIiIiIiIrplFosFFsv/ekhUr14dY8aM0bAi/WHoJiIiIiIiw9Kqxbm8NnTn5uYiLS3N4/3zJ1hTFH0OhyoNDN1ERERERGRo7Opdenbv3o1BgwZBejinjb+/P1auXImKFcvvgEGGbiIiIiIiMizm7dIVGhqKhx9+2OP9vby8YLfbS7Ai/WPoJiIiIiIiw9JqCa/yGvarV6+Od955R+syDIWhm4iIiIiIDEn85f9TyRNu+vJLKZGVlYWrV69CVVVERUUBABwOBxRFKdfjuQGgfL96IiIiIiIyNHchsHSOq8lhdUdVVaxZswb3338/7rrrLvTv3x8OhwOqqmLatGn417/+5fH477KKoZuIiIiIiAxNCFHqN8pr4d6yZQuGDBmC8PBwtG3bFqmpqZBSQlEUREZGYs6cOUhOTta6VE0xdBMRERERkWEx/mpHSomPP/4YLVu2xGeffYa2bdu67hNCoHHjxkhJScGlS5c0rFJ7DN1ERERERGRIAnndvPMnUyvtW3mXlZWFP/74A+3bt4eXl1eh+319faEoClJTUzWoTj84kRoRERERERkae3trw2QywW63u7qUX09KicuXLyM3NxcBAQEaVagPbOkmIiIiIiJjEtoFbgZ9wGq1onnz5li+fDni4+ML3JecnIwPPvgAVapUQaVKlTSqUB/Y0k1ERERERIbGAKydZ555BmvWrMFjjz2GwMBAXL58GW+88QY2bdqEw4cP4+OPP4aPj4/WZWqKodvgHA4HLl26hBMnTiA5ORlRUVGoW7cu7HY7hBCQUiIpKQmnTp1CXFwcAKBmzZqoXr06TCYTZ14kIiIiIkPj2ax2hBCIiYnBggUL8M4772DLli1ITU3Fxx9/jNq1a+OTTz7Bww8/XO4zB0O3wX3zzTd47bXX4OfnB39/f5w5cwbNmzfH+++/j5CQEEgp8a9//QsrV65ESEgIcnJycP78eTz11FN45ZVXYLPZtH4JRERERES3TECbMbPlO0bmcTqd+PnnnxEUFITPP/8cCQkJSEpKgtVqRXh4OLy9vct94AYYug2vSpUqmD17NmJjY2Gz2fDbb7+he/fu+OyzzzBmzBgIITB06FCMGjUK/v7+cDqdWLJkCV544QXcf//9aNGihdYvgYiIiIiIDCgrKwvjxo3Dk08+iQYNGiAiIgIRERFal6U7DN0Gd/fddwOA6wpSbGwsYmNjsX//ftf2qKgo1/4WiwV33303LBYLEhISSr9gIiIiIqLbJG/JMM6kphWbzYaKFSsiLS1N61J0jbOXG5wQosAXTWJiIv744w9Ur169wH5ZWVk4c+YMDh06hI8++giVK1dGkyZNCj2flBKqqsLpdLpuqqqW+OsgIiIiIrpV+efEpXmjvCXDBg4ciJUrV+LgwYNwOByFlg4jtnSXKbm5uXjvvfeQmZmJp556qsCXwYEDBzBgwACkpqbC4XBgxowZCA8PL/QcUkrMnDkTmzdvdm07d+4cAgMDS+MlEBEREREVi1bxl7E7T1xcHK5cuYIuXbrg7rvvRkhICBTlf227Pj4+eOWVV8r1Wt0M3WWEw+HAJ598gi+//BIffPABatSoUeD+hg0bYv369UhJScFXX32F0aNHIzo6Gk2aNCkQzoUQuOOOO+Dl5eXatmvXLpw5c6bUXgsRERERkSfEn+t0axGAGbrzHDt2DD4+PvDx8cHx48dx/Phx131CCPj7+yMnJ0fDCrXH0K0T+d0wcnJyoCgKzGazx91WnE4n5s+fjylTpmDq1Km4//77Cz02fwbB8PBwjB49GitXrsSKFSsKdTEXQqBdu3Zo166da5ufnx8+//zzv/cCiYiIiIhKCHt7a+fll1/GhAkT4O3t7fZ+IUSR95UXHNNdyqSUOH36NFavXo1r1665tmVkZGDatGno3LkzHnzwQXz55ZceXRFSVRXLli3DxIkT8dprr6FXr14FunNIKV236/+tqipMJpPb5+R4FSIiIiIyCp6taicrKwvDhg3D0qVL4evrCz8/v0I3X1/fAvmkPGJLdymTUmL69OlYt24dNm3a5No+a9YsTJw4ERUqVIAQAlu3boXJZMKTTz55w+C7ceNGPPfcc+jatSvq1KmD3bt3AwACAwNRq1YtZGRkYMGCBWjUqJFrZsEvv/wS8fHx6Nq1a4m/XiIiIiKiksbgrQ0hBOLj4zl52k0wdJeynJwc7Nu3Dw0aNEBoaCgAIDk5GXPmzEGtWrWwaNEiWK1WPPXUU/joo4/QvXv3AuOr/+rQoUMICgrC3r17MWLECNf2Vq1aYfr06RBC4Ndff8WMGTPgdDohpUTlypUxe/ZsNG3alC3ZRERERGRomk2kxtNo2Gw2tG/fHps2bcKAAQPg5eXFfOEGQ3cpczqdSEhIwJ133gkhBKSUOHHiBE6dOoXRo0ejTp06AIDHHnsM06dPx7Vr11CpUqUin+/ZZ5/FoEGDCm03mUwwmUzw8vLCjBkzkJaWhtTUVFitVgQGBsJqtfIXgoiIiIgMTwhA4WmtZjp16oSVK1fimWeeQY8ePRAWFlYgZ5jNZjRs2BBWq1XDKrXF0K0BRVGQlZXl+veOHTvgcDjQunVr1wc0KCgIWVlZNx3XbbFYYLFYbriP2WxGYGAgl/0iIiIiIqLb6r///S8OHTqEAwcOYNmyZYUa9ipUqIBdu3a5Xa64vGDoLmUWiwXVqlXDjh07cOnSJXh5eWHZsmUICwtD3bp1AeSN+7506RLsdjtsNpvGFRMRERER6ZOAdhP/Co4kBwCMHz8egwcPLvJ+s9mMChUqlGJF+sPQXcosFgt69eqFoUOH4oEHHoCXlxd2796NZ599FhUrVgQA5ObmYseOHYiMjCzXi8gTEREREXmCwya1IYRAbGys1mXoHkN3KRNCoGfPnoiPj8e8efOQkJCAJ598EuPHj3dNpX/69GkcPHgQDz300A0nUSMiIiIiKu80i9vM+S6qqiIuLg6//fYbrly5Ah8fH9SpUwe1atWCxWIp9xdFGLo1YLfbMWrUKDzzzDNwOBzw8/ODyWRyfRijo6OxadMm+Pv7l/sPKBERERFRUQTyJlLT4oyZZ+l5cnNz8fHHH2PatGm4fPkyzGYznE4n7HY7unXrhilTpiA0NLRc5xqGbo0IIeDr6wun04mMjAyoquoK3zabDZGRka79iIiIiIioaDxl1oaUEqtWrcIrr7yCjh074qmnnkJkZCTS0tLw448/YtasWbBarZg5cybM5vIbPcvvK9eQlBLp6elYunQpvvnmG5w+fRpWqxXffPMNqlativPnz+Pjjz/G/fffj7vvvpvBm4iIiIioCJqt063RcfVEVVXMnTsX7du3x+effw4fHx/Xfa1bt0ZUVBTeeOMNTJgwAdHR0RpWqi2Gbg0kJydj2LBh+PbbbxEZGQmz2Yy4uDjk5uYCAPz9/fHdd9/h1KlTuOuuu2AymTSumIiIiIhIvxiAtZGdnY0LFy6gX79+BQI3kLdMctu2bSGEQHx8fLkO3YrWBZQ3Ukp8/vnnWLFiBV5++WVs27YNo0ePLrCPn58f2rZti7179yI1NVWjSomIiIiIdE6j8dyUx2w2w9fXFydPnoSqqgXuk1LiwoULcDgc8PX11ahCfWDoLmU5OTlYvnw5WrRogRdffBGhoaGFxjcIIVCrVi1cuXIFKSkpGlVKRERERKR/QggoGtw4AjRvOeROnTph7ty5mDNnDq5cuYKcnBykpqZi27ZtmDBhAurWrVuuW7kBdi8vdQ6HA5cuXULnzp1hs9nc7iOEgNVqhcPhgNPpLOUKiYiIiIiIPDNo0CDs3LkTI0aMwFtvvYUKFSogKysL58+fR0REBP7zn/+U+2WQGbpLmaIoCAgIwMWLF6Gqqtvx2qqq4ujRo/D394e3t7cGVRIRERER6V/+kmFaHbu8E0IgKCgIn3/+OdasWYMNGzbg8uXL8PHxwaBBg/DYY48hOjq63E8MzdBdymw2G1q2bIkFCxZg165daN68eYH7pZQ4evQoli5diiZNmiAoKEijSomIiIiIjKGcZzpNCSHg5+eHnj17okePHpBSAshrbCzvYTsfQ3cpUxQFQ4YMwfLly/Hkk09i2LBhSEhIgMPhwO7du/HDDz/gww8/REpKCp5//nndrGcnHblwplyB0Ek918u5ehUJP/4IqFLrUtwy+fkj+JEeunzvAADJ8ZBnfte6iiIpwZFQAkK0LqNI0mKHtOq0R4oE5MUTQHqi1pW4JRQTzDWaQFjtWpfi1oX4RPz7izVw6HSYj5+iYoBfCmxCp999NjPsFXxuvqNG7BERsIVV1LqMIiUeOoPL2w9qXUaRIlvWgV90qNZluCdMyI1qAOj0uwUSsDgyIKQ+v1ucWWlal1BsQkpA6vO7sKzKysrC559/juDgYHTv3h0mkwlCiAIh+9ixY/jmm2/QvXt31KpVq1wHcJ2mgLKtbt26+OyzzzBq1CiMHz8eqqpCVVX0798fqqoiOjoa77//Plq1aqWfD6eaCzUjGaoOg2PO5QtI+P474C8zJuqFpWI4Aro8BEUvP8u/kMlXIY//qnUZRTLlZkOY9Dvno2r3gyr093sB5PWcweVTwNULWpfinskCU9U7dBu6ryWl4eNvNiIn16F1KW6FmRzoFHYRvoo+TzQtvjb4VQ7Sz9+xv6pXDxbU1rqKIqXs2oGzc9doXUaR/Kwd4Y2aWpfhllRMyAmJgdTpdzOkhMhOg0nV33eLlBIyJ0vrMm6JTr9pyqzt27fjjTfewPz586Eo7s/TwsPDsXHjRpw8eRIfffRRuV4GWaffRmWbEAJt27bFunXrsHHjRuzYsQNXrlyBj48PGjVqhE6dOqFKlSr6PVEhIiIiItITtnSXGiklVq1ahcaNG9+wkdDPzw9DhgzB+PHjce3aNYSG6rR3TClg6NaIEAIhISHo3r07unfv7vZ+IiIiIiK6ASkBqUKTtm6pz16WJc3hcODYsWNo2rQpLBZLkfsJIdCgQQPk5OTg4sWLDN1UcuQtXnW7/nEM4EREREREpAdSSmRmZt4wcOczm82QUiIry5jDFm4Xhu4SJqXEJ598grNnzxb7sVWrVsWgQYMYuomIiIiIiqTNRGrl9QzdZDIhNDQUR44cKXIJZCAvB509exa5ubnlfkUmhu4SJqXEwoULsX379mI/rlWrVnj66adLqDIiIiIiIuMTUkJAgzHd5XQcuaIoaN26Nd58803s378fjRs3LtRImN8a/tlnnyEmJgYREREaVasPDN0lTFEUfPDBB0hLK/7yC35+fkXOBkhERERERH8qpwFYC0IIPPLII/jwww8xYMAAvP3222jVqhV8fX0B5I35Pn36NN577z189913mDlzJry9dbq8ailh6C5hQgjUqVNH6zKIiIiIiMogDSdS06J1XSfCw8PxwQcfYMiQIejduzeqVKmCypUrw2q1IiEhAX/88Qeys7PxwgsvoFevXuV+uCxDNxEREREREXlMCIGWLVti1apV+OKLL7Bu3TqcOHECDocD/v7+6NixI/r37497773XownXyjqG7hImpcTOnTuRmJiIWrVqISYmBocOHfJoYrWgoCA0a9as3F8ZIiIiIiIqktRmIrXyTgiBqlWr4vXXX8f48eORkpICp9MJb29v+Pr6QlEU5pg/MXSXMFVVMWbMGGzduhWTJk3C+PHj8eGHH+LDDz+86WNbt26N9evXFzkjIBERERFR+aZh2GbQd4Vqu90Ou92ucTX6xdBdwoQQrrEMd999NwCgR48eqF279k0fW6lSJU6kRkRERER0MwzApGMM3SVMCIH27dvju+++Q0hICACgTZs2aNOmDZxOJxwOB2w2m8ZVEhEREREZkAQnUiPdYzNqCRNC4OLFixg2bBj27Nnj2iaEwIIFC/D4448jNTXVtc3djYiIiIiIiIyJLd0aOn/+PHbu3Inc3Nxbfg5VVZGcnIxz584hNTUVERERiIqKgtlsLnKR+oSEBAQEBMDf35+hnoiIiIgMK+9MVqOJ1NjQTR5iS7fBrVy5Eu3atcMTTzyBF154AR07dsSoUaOQmppaaF+Hw4FXX30VDRs2xKeffqpBtUREREREt5OEkBIC2twoj5TSdVNVtcAtf3t5xpZug/Px8cGbb76Jli1bwsvLCzt37kS/fv1Qu3ZtDB8+3NWSLaXExo0bsXnzZvj4+CA7O1vjyomIiIiIbpNyHuq0pKoqDh8+jO+//x6nT58u1IvX29sbr732GgICAjSqUHsM3QZ33333AfjfdP1t27ZFkyZNsH37dgwfPhxAXuBOSEjAO++8g1GjRmHy5Mma1UtEREREdNtIqd1Eagz6kFJiw4YNGDhwILKyslCxYkWYzQUjpr+/P3JycjSqUB8YukuJlBJbtmxBVlaWa9v+/fuRmZmJJUuWwNfXt9BjatSogWbNmt1w3PVf70tNTcX58+fRoUMH1zZVVTFjxgxUr14dXbt2xdtvv33DOjMzMwtcocrIyPDoNRIRERERUfnhdDoxc+ZMREVF4aOPPkJMTEyh0A0AVqtVg+r0g6G7lOQH3+tDcv4Yh2HDhrkN1oMHD0bTpk09nuzM4XDgk08+wZUrV9C3b18IISClxPbt27FmzRp8/fXXsFgsN3wOKSUmTZqEVatWubYlJSWhdkwVD18pEREREVEpcrV2l/qBNTimvuTk5ODixYvo27cvGjRowEmai8DQXQpCQkLw0ksvweFwFOtxxQncqqpi0aJFeP/99zFlyhTUr18fAJCcnIw33ngDQ4cORUxMDDIzM2/4PEIIPPPMM+jRo4dr27p16/DTutXFqp2IiIiIqHQw/GrFarUiOjoaycnJWpeiawzdpSA0NBQTJ04ssedXVRUrV67E+PHjMWHCBDz++ONQlLyJ6Xft2oU9e/YgPDwcO3fuhMPhwIULF/Dtt9/C4XBg7NixsNvtrucSQqBatWqoVq2aa9vx48fxU4lVT0RERET0N3F8tSZMJhOGDRuGV199Fffffz8aNGjgtnu5EKJct4IzdJeCkvyASSmxfv16jBw5Es8//zwGDx7sCtwAEBMTg5deegmqmtflJjc3F1arFUFBQYiKiiqwLxERERGRsXAiNa3t2rULly5dwv33348777yz0Czlvr6+ePfdd1GhQgWNKtQeQ7fB7dixA0OGDMG9996LTp064eTJkwDylhKrVKkSYmJi8OKLL7r2z8zMxMKFC9G6dWsMGDBAo6qJiIiIiIyOoRsAEhMTERERgcjISKSlpSEtLa3A/f7+/q4GwPKKodvgfvnlFzgcDmzduhU7duxwbW/Xrh1mzJhRqHuHEAKhoaHw8/Nz/ZuIiIiIyLCkZKuzht54440bhmohBGcv17oA+nuGDRuGgQMHFtpusVhgMpkKbbfb7Vi6dGm5/+ATERERURmQH7i1CN0M+q5ALf98L5xOJ3JycmA2m12rJrGRj6Hb8Ly8vODl5eXx/kKIQuMsiIiIiIgMjQFYM1JKxMfHY+7cufjxxx9x9epV2O12NG7cGAMGDECjRo3K/TxS5fvVExERERGRoQmpIm98dSnfGPQhpURcXBx69eqFSZMmISkpCVFRUbDb7Vi8eDEefPBBrF271tUSXl6xpZuIiIiIiAyNHZi1M2vWLJw+fRoLFixAu3btYLVaoaoqTp8+jZEjR+L1119Hq1atXHNKlUds6SYiIiIiIgP7c9mw0r5x9nLk5ORgy5Yt6N+/P7p06QJvb2+YzWZYrVbUrFkTr776Ks6dO4ezZ89qXaqmGLqJiIiIiMiYOHO5ppxOJ7KzsxEaGlpowjQhBAIDA2EymZCdna1RhfrA0E1ERERERMZ2/SzmpXUj2O12xMTEYMWKFbh27VqBsdu5ublYsWIFTCYTwsPDNaxSexzTTURERERExqVVAGbwhhACgwcPRu/evfHoo4+id+/eqFq1KpKTk7Fu3Tp8++23GDZsGMLCwrQuVVMM3URERERERFRsQgi0adMGH330ESZPnozx48cjNzcXiqIgNDQUL7zwAkaPHl3ulwxj6CYiIiIiIoPK7+6tanNsgslk+v/27js+ijr/4/hrdrPpDVKo0nsRxAIKilhQQbECeoBiQRQVQT1ExHI2sOLpWc6CBTsqp2dDkbOBikeTjgrSCYEkpCe7O9/fHzH7kyOBgMnOLL6fj8feye5k57Ob7Oy859s455xzOPnkk1m3bh05OTnExcXRsmVLMjMz//SBGxS6RUREREQkoin8OqlyHHdSUhLdu3fHGENpaSm7d++muLiYhISEvSZZ+7PRZQcREREREYlsmkjNEcYYPvvsMx555BH8fj/GGLZs2cLQoUM54ogjOO2001i4cOEeE6z9GSl0i4iIiIhIxLJCa2aH92b9yYMkVITu559/np9//pmoqCiMMTz11FMsWrSIkSNHEgwGmThxIiUlJU6X6iiFbhERERERiWiWAzeBsrIyNm3aRJcuXfB4PBQXFzN79myuvPJK7r33Xh544AFWrVrFli1bnC7VURrTLTVkYSwvxnLhdRrLg7ENBJ2YQGP/jG1XTO7hyAQf+2fFxuNp3NLpMqpVntyAwqgUp8uoVtDEECxzuorqJcWnEm37nS6jSpY3CsvjdbqMatXzBrk4aTcBf8DpUqpkATMLk5wuo1qNCgOcsGub02VUq2mL7iRktnK6jGr5Gm8ipVmy02VUK6pZa+xmXZ0uo2qWh6A3Gtt2aSukAQJ+sMudrmQvFoDtzmNetcxvLc+OtDq79G8sjGzbJhAI4PVWfJ9v3bqVLVu20K9fPzweD02bNiUqKorc3FyHK3WWQrfUkAUeL3jc9ydjLA8maINLv1yNbbCM/VvXJ/ex4uLxNm3j2iu2BTENyPfVc7qMavltQ6DcnX97GIhPSCUqxqXB1uMFr0trA+p7bK5I3o0JuPMEdHvAy/CsRhQZF14MBQ4vyaX5zi2uPbYknhJNw0btnC6jWtFNfiG1hXsvOPpatsW0PMLpMqpkjCHgN2691l0RDoN+PEH3hW5jDFakhW74/+DtyH7/3GJiYmjYsCHfffcdI0aM4NNPPyU+Pp62bdsCUFhYSCAQIC4uzuFKneW+BCUiIiIiInIgFIAd4fV6GTp0KNdddx2rVq1i3bp1XHTRRWRkZGCMYcmSJaFg/mem0C0iIiIiIhGqco1uJ/rVKOhblsUFF1yAMYbPP/+cs846i9GjR+PxeLBtm61bt3LhhRdSr557ey2Gg0K3iIiIiIiIHLBAIMDcuXPp0KEDw4YNC91vWRYej4ebb77Zwercw50DwURERERERGrCmP+ftDasN7V0l5WVcccdd/Dtt98CFWHbsqw9/vv39/1ZKXSLiIiIiEhkMqH/EQfExMTQpEkTdu/e7XQprqbQLSIiIiIikc2Y8N8Er9fLFVdcwQcffMDChQvx+/0YY6q8/ZlpTLeIiIiIiEQkC/PbsqwOdF/+kwfJSqtWrWLHjh0MGDCA7t27k5GRgcfz/227CQkJTJ06ldTUVOeKdJhCt4iIiIiIRLQ/94hhZ2VlZdGgQQMaNGhAQUEBBQUFezyelJREIBCB67/XIoVuERERERGJXI5191ZLN8C9996LbdvVPm5ZFtHR0WGsyH0UukVEREREJEI5OMZa3csVqGtIoVtERERERCJbBAfg308yFolLaxljCAQCbNy4kU2bNlFSUrLHa/L5fBx//PHExsY6WKWzFLpFRERERCQyGSIycBtjKCoq4ocffuD7778nKyuLmJgY2rdvz/HHH0/Lli3xer11WoPf72fTpk0Eg0EA4uPjady48QEFf2MMBQUF3HbbbcycOZOcnBwsy8Lj8eD3+7EsiwYNGrBgwQIaNmxYVy/F9RS6DwHGGILBIMFgEJ/PpwXoRURERERcyhjDggULmDhxIt9++y1lZWWhxyzLIjMzkyuvvJKbbrqJ5OTkOqvh7bffZvz48fj9fgBOOukk3nrrrQN+rhdffJF33nmHe+65h+eee47OnTszdOhQZs+ezTvvvMOtt95K/fr1a/slRBSF7gj366+/8sYbb/DDDz9QWFhIs2bNGDlyJMceeywejwdjDB988AGzZs3a4+e6dOnC+PHjFc5FREREJMIZMNVP5FV3uz3wFnZjDPPnz+eiiy5i06ZNeDweWrduTatWrSguLmb58uVkZWVx7733smXLFh577DESEhJquWzDxo0bufPOO8nKygrd/7+zjtdEIBDgww8/ZOjQoVx88cW8/fbbNG7cmJNPPpl+/frRuHFjZsyYwdChQ//UY789+99E3OzTTz/lm2++4ZRTTmHUqFEYYxg6dCjz588PbbNkyRK+++47OnXqRNeuXenatSstWrRwrmgRERERkVrh1MzlB2fXrl2MHz+eTZs2ER0dzV//+le++eYbPv74Y+bMmcPHH39Mjx49sG2bGTNm8NJLL+0xPro2BAIBpk6dyk8//UR6evofaoQrLy8nNzeXDh06YFkWPp+PkpISALxeL2eccQbr169nw4YNtVV+RFJLd4QbOnQol1xySejK0RlnnMHpp5/Oq6++Su/evUPbtWrViuuvv56oqP//lauVW0REREQOCREQvI0xvPnmmyxcuBCA888/nzvuuIO4uDigIqT26tWLZ555hjPOOIPs7Gz+/ve/c/7559OgQYNaq+HTTz9lxowZJCUlcdNNNzF58uSDXkfb5/ORmJhIUVERlmXRqFEj1qxZg9/vx+fzUVhYSFlZGaWlpbVSf6RSS3eES0lJISYmJjSOOzo6msTExL3+sEtLS/npp5/45ZdfKCoqcqhaEREREZHaZRnDbzOqhfVmHWCX9pKSEl577TVs2yYxMZGxY8fuNaO3ZVl0796dc889F4BffvmFuXPn1kprtzGG7Oxsbr/9doqLixk5ciQnnHDCH3pOn8/H4Ycfzo8//ogxhpNPPpl58+bx8MMP8+677zJp0iRSUlJo1qzZH64/kil0H0KMMSxatIjFixfTv3//UEu2ZVmsWLGCoUOHcvrpp3Paaafx+eefV/nhrRzj8eOPP4ZuGzduDPdLERERERGpIYNlwn87UOvXr2f58uUAdOjQga5du1bZ89Tj8XD22Wfj8/kIBoPMnj0b2/7jY9Zt22batGksXryY9u3bc9NNN+3RC/ZgjRgxgi5duhAIBBgwYADDhg1j2rRpXHrppaxfv5777ruP9PT0P7yfSKbu5YcIYwybNm1i3LhxnHTSSQwaNCj02ODBgxk8eDANGjRg586dTJ06ldGjR/PZZ5/RsmXLPT7sxhiefPJJ/v3vf4fuy8/Pp0ObVmF9PSIiIiIi+2Uqx3S7u3u5MYbly5dTWFgIQI8ePULdyv+XZVl06dKFlJQUdu7cyeLFiyktLf1DE6oZY5g3bx5PP/000dHR3HbbbTRt2pTt27cf9HNW1nrkkUdy5JFHAhAdHc2DDz7INddcQ35+Pk2aNKFBgwZ/+mGtCt2HAGMMWVlZXHnlldSrV49p06aFPpSWZdG+ffvQtqmpqdx+++189NFHfPPNN7Rs2XKP57Isi8mTJzNhwoTQfbNmzeLNV14Oz4sRERERETkgTgXuA9vv2rVrQy3Wbdu23WcQTU1NpWHDhuzcuZMdO3aQk5Pzh0L37t27ue2228jLy+OCCy7g3HPPrdUgXLmEcX5+PrZt07Zt29D9lf//Zw7eCt0RzhjDrl27uPrqqykvL+fll18mMzNznz+TnJxMbGxs6Erb71mWRWJi4h731fYyBSIiIiIitSoCJlLbsmULQGjCsX2F0NjYWOrVqwdULOWVn59/0Pu1bZunn36aefPm0ahRI26//fa9xpL/EbZt89133/HII4+wbNkyWrduzXvvvYfH4+Hxxx8nNjaW0aNH19r+IpHGdEe43bt3M3bsWLZv384zzzxDo0aNsG0b27ZDV5zy8vIIBoOhf3/++efs3r2bzp07O12+iIiIiMgfULlGtwOTqRmD3+8nNzeXnJwccnJyyMvLq3b8dW5uLlARulNSUvb5qqKiokINX+Xl5RQXFx/wOwMVDXRLlixh2rRpANxwww107ty51lqdjTEsXLiQv/zlLxQUFNC2bVt27NiBMQaPx0NcXBxPPvnkH7pocChQS3eEe+mll5g5cya9evXizjvvDH2Aunfvzrhx4ygqKmLkyJHUq1ePpk2bsmXLFj777DOGDRtGz549/9TdPERERERE/ogvv/ySvn37hv6dmZnJG2+8UeUSX+Xl5aH/9vl8+3zeylWJoCLY/v5nD0RRURG33347O3bs4IQTTuCKK67A46m9dldjDE899RRdunThtdde47XXXuO5554LvYZjjjmGu+66i+3bt+/3QsOhTKE7wh133HE8/vjje93fvHlzLMsiPj6e6667jv/+979kZ2fTokULXnjhBfr06UNMTIwDFYuIiIiI1CJjoBZm9z6IHXPMMcfw0EMPhYKsz+ejfv36VW79+7BbkyXAft9i7vV6D7g627aZMWMGs2fPJjk5mb/97W+1HnzLyspYvXo1w4YNIykpaa/Hk5OT8Xq97N69u1b3G2kUuiPc0UcfzdFHH13t4x6Ph5NOOomTTjppj/vVwi0iIiIiEc9Udi934NzWGJKTk+natWuNQvHv50naX3dx27YpKSkBKgL3wTSWrV27lqlTpxIMBrnsssvo06dPrWcAy7KIioqirKysysd37dpFIBCoMpD/mWhM95+AZVl73UREREREDhXGmLDfDlRGRkao1l27du1z2/LycgoKCgCIj4/fa6Lj/SkvL+eee+5h48aNdOjQgRtuuAGPxxOa++n3c0D93r4eq0pMTAxHHHEEH3744V6t2cXFxUyfPp2GDRvSpEmTA6r/UKOWbhERERERiVjGNmCFf/byAw3erVq1Cv3chg0b9rmMVlFRETt27AAqlg+rnMm8poqLi/n2228BKCkpYcyYMVVut3v3boLBIACLFi3inHPOAaBTp07cfffdoXHl+3LllVdyzjnnhLqY5+Tk8NRTTzFnzhy++eYbHn300T99S7dCt4iIiIiIRDATEUuGdezYkejoaMrLy1m+fDmBQKDKCdWMMWzZsoXs7GygIqwnJycf8P4qLwr8+uuv/Prrr/vdPjs7mw8++AComGm9Mozvi2VZdOrUiRkzZnDnnXfy2WefUVxczOTJk2nWrBkPPvggF1100Z++p61Ct4iIiIiIRKbKMd1OZO4DCPqV4bRhw4Zs3LiRRYsWkZ2dTePGjavc/uuvvw6N++7Tp89+Zzv/X9HR0QwfPpydO3fuc7sdO3bw7rvvYozhsMMO48wzzwSgdevWREXtOyoaY7Btm9LSUrp3786sWbPYtGkTu3btIiYmhhYtWlCvXr0/feAGhW4REREREYlkjrVyH9h+MzIyOPnkk3nhhRfYunUr//73v7nyyiv3CqUFBQW89tprGGNISkpi4MCBVQbXrVu3snv3bizLIjMzc49Z0+Pj47nrrrv2W9MPP/zAe++9RyAQoFOnTjzxxBM1CsnGGBYvXszDDz/MqlWriIuLY+DAgVxzzTW0bdtWQft/aCI1ERERERGJbMY4cDuwEj0eD6NGjSIlJYVgMMgDDzzA0qVLQ93AjTGUlZXx2GOP8cMPPwBw+umnc/jhh1f5fJMmTaJHjx706NGD119//Q+9fQdq06ZNDB8+nA8//BBjDNnZ2dx9993cd999eyx1JhUUukVEREREJDJVrtFtHLodAMuyOProo7n66qvxer2sW7eO888/n4cffpj//Oc/vP/++4waNYp7772XQCBA8+bNue2226qdzKy8vJzS0lJKSkpqNP66Nn3yySfs2rWLN954g/nz5zN//nwuv/xyZs6cGRqLLv9P3ctFRERERETCwOv1csstt5Cfn8/06dNZt24dEyZMwOOpaAutDM+tW7fmqaeeokuXLq7sqr1y5Up69erFKaecQlRUFLGxsYwePZqZM2eyY8cOGjZs6HSJrqLQLSIiIiIiEcpgjH2gjc61tOsDH0tuWRZJSUk8/PDDnHzyyUyfPp1ly5axe/dufD4fjRs3pn///owePZrWrVvvM3B36tSJE088EcuyDnod7OTkZPr27UswGKRbt241/rmioiLq16+P1+vd43V5PB78fv9B1XIoU+gWEREREZGIZAzg0DrdBzuBm2VZxMbGcu6553LWWWeRm5tLSUkJXq+XlJQUEhMTQ9vty6RJk5g0aVKNtq1Ou3bt+PTTTw/qZwOBAEVFRaF/FxcXY4yhuLiYwsLCPbaNj48Pteb/GSl0i4iIiIhIBIuMdbr/l2VZ+Hw+MjMzD+rnayPEWpZ10IH9o48+4rjjjgv92+/3k5OTw2WXXUZcXFzo/pSUFN59910yMjL+cL2RSqFbREREREQilIm4lu5DQbdu3dixY8de97dr126v+xITE0Pd0P+sFLql5gyhJQ1c5XfLLLiSAYNxbX3Wb8teuLO6itU43PreARXvnUvrs8C9n1t++9uTgxZql3Dp+1hZnzurq+DWz0YF9x5boHLFJPfWV/H+OV1D1dx+bHb1h3Zf3Pp+HqLGjBnD1VdfXePt/8xdy0GhW2qo8Jf1rL7rAbwe982emJdTwLzvt2Bsdx5srZgc4jeOw3LpwSYj3kOXDPceClbtCvLr7vAug3EgWjZOol2zZKfLqNZ2u5QoO+B0GVXyxMRw2Lh2+OrFOl1KlbzRXpIOq48JuPT9Kwlyzaqf8AfcuR7qTm8M09I7OF1GtYYu/JGEB+92uoxqZa/ZyKb/bnW6jGr5tjyJJ+U1p8uokmVZpKfEEOXCc5ZK0ZTjwZ2f3a1r1kCjRk6XUXPGgAmCceA8608c9P/sIfpAufdMW1wlkJ9P3sIleF24ZMGuwnI2ZRW5+MJsMWye73QR1SqsF0vj1qmuXI4CYOvGfNZnFe1/Q4ckt62HKTy4sVjhUOJ0AfvgiYvDdvEMp5bHwpcQC0F3hm5DGV3KdhP0u/Oi1NLYVJbFpoJLjy29s3dRtHSD02VUK39TPrk7ip0uo1p21grXfu9aFkRnJhDtc28o8ER5sFx4UcAYQ9Gu7MgK3eBg67xbPwXiNgrdIiIiIiISwdw9HENEoVtERERERCKTMRjb/t1EF+HctYK+1IxCt4iIiIiIRDYFYHExhW4REREREYlcxtZEauJq7p1hQkREREREZH80kZq4nFq6RUREREQkQhkcm0hNmVtqSKFbREREREQik8GxidTUvVxqSqFbREREREQimwKwuJhCt4iIiIiIRCjz20RqTqwZZod/nxKRNJGaiIiIiIhEJoNaucX11NItIiIiIiIRqmIiNWeCt8K+1IxCt4iIiIiIRC7jUOhWC7vUkEL3IcAYE7p5PBUjBixr73Etxhhsu2LsicfjqXIbEREREZGIYnBmyTCRGlLojnBZWVl89NFHLFiwgPz8fFq2bMmFF15I586dQ6HaGENhYSGzZs3iiy++IBAI0LFjR6666irq1avn8CsQERERETlIxmDsIE5MVWVsBX2pGU2kFuFmzZrF9OnTadiwIX369GHlypWcffbZLFq0KLRNUVER11xzDU8//TQdO3akV69ebNu2jZycHAcrFxERERH5Y0zof0TcSy3dEe68885j+PDhJCQkAHDRRRdx2mmn8dJLL9GjRw8A3nrrLZYtW8Z7773HYYcdBlS0fqt7uYiIiIhEPk2kJu6m0B3hMjMz9/h3YmIiGRkZ5OXlARAIBHjjjTc4/fTTCQQCzJkzh/r169OpUydiY2MdqFhEREREpJaYynW6Hdq3SA0odB9CjDGsWrWKxYsXc/fddwOwe/du1q1bR0xMDEOGDCEuLo6tW7dy7LHH8vjjj+81ptsYw65duygqKgrdt3PnzrC+DhERERGRA6IALC6m0H2IMMawY8cObrjhBo444gguuOACLMuivLyc4uJili5dyjvvvEOXLl348ccfGTx4MC+//DJjx47do5u5MYb777+f999/P3RfQUEBTXQcExERERHXMWDb4HFg2KSCvtSQJlI7BBhjyMvL47rrrqOkpIQnnniC5ORkAKKiooiOjqZfv3706NGDuLg4jjrqKE444QQ+//zz0BJilSzLYuLEicyZMyd0mzx5Mhr+LSIiIiKu4+hMagrdUjNq6Y5wxhgKCgq44YYb+PXXX3n11Vdp1qxZ6PGkpCQaNmxIYmJiqEXb4/GQkJBAdnb2XmsaWpZFWloaaWlpofvq168fnhcjIiIiInKgjHFmnW61dEsNqaU7whUXF3PLLbewaNEinn/+eVq3bg1UhHFjDLGxsZx88sksWrSI3bt3Y4whNzeXxYsX06VLF7xer8OvQERERETkYP0WuB24KXNLTamlO8LNmDGD5557jn79+vHiiy+GWrM7duzIyJEj8Xg8XHHFFXz00Udcfvnl9O3bly+++ILi4mJGjRrlcPUiIiIiIrVACVhcTKE7wrVv356JEyfudX/lcmCWZdGiRQtmzpzJjBkzWLRoEd26deP++++nbdu2WqtbRERERCKXwbmJ1LD3v4kICt0Rr1+/fvTr12+f21iWRevWrbnzzjuxbRuPxxO6X0REREQkcpnfbk7MXh7+XUpkUuj+k6gM2BrDLSIiIiKHlMpx1uHfsQP7lEik0C0iIiIiIhHKgLGdyb8aRy41pNnLRUREREREROqIWrpFRERERCQyGTC2wTgxqZlauqWG1NItIiIiIiIRTOFX3E0t3SIiIiIiEqF+m0TNqKVb3EuhW0REREREIpPht4nUnOjAq9AtNaPQLSIiIiIikU2tzuJiCt0iIiIiIhKhDNg2eCwHdq2gLzWjidRERERERCSCORR+FbqlhtTSLSIiIiIikckAxmAUgMXFFLpFRERERCQiGQzGdmDmcsA4MWO6RCSFbqkRy+PFGx+L1zrQEQkGqMkYm5put/e2UUEPPo+F7dIrnJbHgzchnpq/vvCKSYohKiHB6TKqFZ0UJKbEne8dgDchETs2zukyquUFLJe+fd7YOCy3FgdgWXh8PoxLS/REG3xJiVj+oNOlVCnGF0eix4DlzmMzQEHQpb9coBzLkSGqNeWJjcGKcudppGWBlZiAFeXeUZTeKAvLpb9gT+Fup0s4OC49DxQBhW6poeT2rTjigVuI8nqdLmUveT9txP/XRzFBd15tjG3SiMOnP4Y3NtbpUqrks8uIDxY4XUa1Wph4ConZa7SWxf+P4Pr9fx+sg32OfH+Q7HJ7Pz99sNVWnpDt69Xve5+d48pI8wVquL8w83iJSkl1uopqRSUmknFSv4oJev7A7+CPqf5vx0TFkHZNd4zHnV/lR69cRu9nn6rm0QO90EoV29fkOarfZlZ+PH/ZklmD/e/v81s3R6N+5V4uSi/5g89Vd9reMJq03kc7XUaVDLA5mIjfpVMXWRgO8xUTZ7nzgtmSme+yYcVap8uoOVM5kZoDv29bQV9qxp3f1OI6li+KmPqpRLnwqnbsjlziojyubY2KjY4itXEDvPHubA21/CVElUa7tB0eEryJeLzxTpdRrdKicuxCv9NlVMPgSSjF59bQbVlYTpwk1ZTlwRsXV7H+qwsZXyxxjTLB63O6lCrZWZtoEOXOUAFgsNgRdN93WqUi4yXK697PR1y9ZBIbZThdRpVsA1H+BGzjvoaCCoboqEJiPO77fBhjiEp0b+83kUjl3m8bERERERGR/THGoQukaumWmlHoFhERERGRyFQZuI0DPUM0jlxqSKFbREREREQimpYMEzdT6BYRERERkQj125JhTswGbw5kUkj5M3PvDB0iIiIiIiL75Uwrt9GYbqkhtXSLiIiIiEjkMupeLu6m0C0iIiIiIpHJgNFEauJyCt0iIiIiIhLR1NItbqbQLSIiIiIikckYTNAGT/hbuo2toC81o4nUREREREREROqIWrpFRERERCQiGaho7Xai1Vld2qWGFLpFRERERCQyVQZujxOhO/y7lMik0H0IqGriCMuyHKhERERERCT8NJGauJlCd4Tz+/0sWrSIefPmsWnTJurVq0f//v05+uij8Xq9GGP49ttvWbhw4V4/27RpUwYNGoTX63WgchERERGRP8j8NqGZIyuGKehLzWgitQi3bt06rrjiChYsWEBycjI///wzF1xwATNmzAgdCLZu3cqiRYtCt++++45bb72VDz/8UC3iIiIiIhLhFH7F3dTSHeEaN27Mv/71L5o3b47X6yUQCDBx4kQeeeQRzj//fBITEznvvPM499xzQz+zcOFCZs+ezeDBgxW6RURERCSCGbANxongrZZuqSG1dEe4pKQkWrduTVRUFJZl4fP56Ny5Mzk5OZSXl2NZFh6PB6/Xi9frxbIs/vWvf9G0aVN69eql0C0iIiIiEcuY37p5O3BT93KpKbV0H2JKSkr44IMP6N69O4mJiXs9npeXx/vvv88FF1xAcnLyXo8bY1i6dClbt24N3bdkyZK6LFlERERE5A9RABY3U+g+hAQCAZ555hl++OEHXn/9daKjo/d43BjD/Pnz2bFjxx7dzf93m3//+9/Mnj07dN/OnTtpllmvTmsXERERETlgxmCCzkykhhNrg0tEUug+RASDQV5//XUefvhhHnjgAY477ri9uo4Hg0HeeustevToQYcOHarsWm5ZFhMnTmTChAmh+2bOnMnLzzxR569BREREROTAGUBDJsW9FLoPAbZt869//YvJkydz++23M2TIEDyevS/3bdmyhf/85z/cdddde7WCV6ocF/57UVH6MxERERERdzIOja9Wl3apKaWpCGeMYfbs2dx4443ceOONjBw5Eo/HEzoIVLZmV27n8Xg49dRTNYGaiIiIiEQ+YzC27cyiYQrdUkMK3RFu3bp1jB49muTkZAoLC5k2bRoAcXFxjBgxgpSUFADKysqYOXMmp5xyCo0aNXKyZBERERGRWqVWZ3Ezhe4IFxUVxZlnnkkwGGTDhg2h+xMTEwkEAqF/FxYW0r17dwYPHlxl13MRERERkUhjAGPb4MD5rYK+1JRCd4Rr3rw5Tz755H63S09P58EHHwxDRSIiIiIiIlJJoVtERERERCKTMb+N63ag1Vkt3VJDCt0iIiIiIhKxjG3A48Ts5WHfpUQohW4REREREYloGl8tbqbQLSIiIiIikamya7kTq+Eq6EsNaRprERERERGJSAacC7/K3FJDaukWEREREZHIZZzpXm6UuqWGFLpFRERERCQyGTDGBuNAB151L5caUugWEREREZGIponUxM0UukVEREREJDIZgx00WE40dDuxNrhEJE2kJiIiIiIiEUzhV9xNLd0iIiIiIhKRzG//40irs8GZpcok4ih0i4iIiIhIZDIGY9vgCX8HXmMcWh9cIo5Ct9SMMdiBIG4cumIHK+py6wQatjHYfj9WudfpUqrkCfixy8qdLqNaxufHGL/TZVTLCgQg4N76jN+PTcDpMqpmeXB3l0CD7Q+AsZ0upEqGAMYfAHeWhwkEsN34pfEby9j4XPq7BbAwlLv4bD4YDGL73XnsM1gQDLp2ZmmLis+vW4/NJhh0uoSD4tbzQBFQ6JYaKv51Iz89+gRRlvtOAHbtLOT7HYWuncwioWQTqX+9kagod4bu4oJSdm7Z7XQZ1WrctTEZrdOdLqNa0fklpOcWO11GtbJKSskOuPMEyhMbR4cpDxCTkeF0KVUq3pbD4tufd22w8MZEkXHEB1hed07Pkrslh1U/bHW6jGodExPLkTExTpdRrUXeJMbHtHW6jGpN+GAOxy/4j9NlVM3joV6X1njjop2upGoGNn2zkvKcQqcrqdLWX36Bli2dLqPmKruWO3GKqqAvNaTQLTUSLC+ndNt2ohzourM/JXmlFPqD7j3ulZZTunEDUS49MS7KK2X3xnyny6hWWmoQk+zelngrrxhfbpHTZVTJGEN5QTm2352h2xsXjwm4s6UHwPYHKNy0A+Pa0O0lJdPCE+XOY0tZVhElRe587wDqWxb1ot36xQHLTAIbPHFOl1GtvNwcygKlTpdRJctjEXVYEr5ArNOlVMnYhvItWyjJLnC6lL0YYyjPyY2s0A0V4deFDUMilRS6RUREREQkQpn/H9cd7j27tsVH3Madl8dFRERERET2wzg5r48yt9SQWrpFRERERCSiORO8lbqlZhS6RUREREQkQhlM0DjSf1fdy6Wm1L1cREREREQimMKvuJtaukVEREREJDIZ/n/ZMCf2LVIDCt0iIiIiIhKxjG2DE8vaqnu51JBCt4iIiIiIRDSNrxY3U+gWEREREZGIZIypuDm0b5Ga0ERqIiIiIiISsZR9xe3U0i0iIiIiIpHJAMbG2Fb4d+3E5G0SkRS6RUREREQkQhmMjfrviqspdEc4YwzFxcXs2LGDoqIi0tPTycjIwOv17rFNeXk527Zto6CggPT0dDIzM/fYRkREREQkMhlnupirX7vUkEJ3hPv000+58847yc3NxefzUV5ezpAhQ5g4cSIJCQkYY9i8eTM33HADS5YsITY2lrKyMgYPHsytt95KfHy80y9BREREROTgmN+WDLMc6F6u0C01pNAd4fx+P6NHj6Zfv34kJibyzTffcNVVV9G8eXMuv/xyjDE89NBDrFmzhrfffpvDDjuMuXPnctVVV3HUUUdxzjnnYDlwkBIRERERqRUG0OmsuJhCd4QbMGAAlmWFgvPAgQM56qij+PLLL0Ohe8WKFfTu3ZuuXbvi8Xg47bTTyMzM5JdffnG4ehERERGRg1exWJi6l4u7acqBCOfxePZoqS4pKWHHjh1kZGSEHu/Tpw8//PADa9euZffu3Xz11VcUFxfTs2fPvZ4vtNbh724iIiIiIq5kfptF3DhwE6khtXQfQmzb5tVXX2XTpk1cdNFFWJaFMYaxY8fyyy+/cMopp1C/fn127drFpEmTOPbYY/fqWm6MYdasWSxdujR034oVK3RgERERERGXUku3uJtC9yHCtm0+/PBD7rvvPm677TZ69OgReuy9995jxYoV/O1vf6NNmzZ89tlnPPnkkxx55JH07Nlzr+BdXFxMXl7eHv8WEREREXEdYzBB40j/3droEWqMIRAIYNs2lmXh9Xr36slaGyprDQaD2LYNENrf74eqSt1Q6D4EGGP44osvGDduHNdccw1XXHFFaDmw3bt388gjjzBy5Eguu+wyLMuiZ8+eLFq0iH/+8597dTG3LIvhw4czbNiw0H1vvfUWf1/0Q1hfk4iIiIjIocq2bVatWsWbb77Jt99+S3Z2NtHR0bRr146BAwcyYMAAkpOT/3AYtm2bnJwcFi9ezDfffMOPP/7I1q1bCQaDpKWl0blzZ0477TR69+5NQkKCwncdUeiOcMYY5s+fz1VXXcXw4cMZN24cUVH//2stLS0lPz+f+vXrh+7z+XykpqaSm5uLMWaPD1flf+sDJyIiIiIRwZiKcd1h3+/B/Vh5eTnPPfccd911F1lZWXs89sMPP/Dmm29y4okn8o9//IN27dod9Hl5fn4+U6ZM4d1332X9+vX4/f69tvn000958skn6du3L/fffz/dunVTDqgDCt0R7scff+Syyy7jmGOOYcSIEWRnZwMQGxtLWloaqampdOzYkddee42+ffuSkZHBwoUL+frrr7nuuuv0oRIRERGRyFU5kZrHgXPag+hebts2L7/8Mn/9618pLi4mOTmZAQMG0KNHD/Lz8/noo49YsmQJc+bM4ZJLLuHdd9+lcePGB1VednY2zz77LLt27QIgISGBJk2akJGRgWVZbNu2jY0bN1JWVsann37K+vXrefvtt+natasyQi1T6I5wn3zyCdnZ2cyfP58zzzwzdH/l1bGYmBimTJnCuHHjOP3000lKSiI3N5dTTz2VK664wsHKRURERERqRySsuGOM4eeff+Zvf/sbxcXF1K9fn+eee46zzjorNDR03Lhx3HDDDcyYMYMFCxbwwAMP8NBDD+3Rk/VAREVF0aVLF4YOHcoZZ5xBy5YtSUpKAiAvL4/Zs2czefJkNmzYwE8//cStt97KzJkziY2NrbXXLQrdEe/qq69m+PDhe90fGxsbmhihe/fufPjhh2zYsIGCggIyMzNp2rQpPp9PV7FEREREJGIZY0KTkIWbfRBd2p9//nk2b96MZVlce+21DBo0KBS4AerXr8+UKVP4/vvvWbNmDa+99hpjxoyhXbt2B7yv5ORkHn30UU499dTQUNPfv08ZGRkMGzaMBg0acMEFF5Cfn88XX3zBqlWrOOKIIw54f1I9rdMd4ZKTk2nSpMlet7S0tD3GZycmJtK5c2d69epFq1atiI6OVuAWERERkchnKsJ3uG8HKi8vj3//+98ApKenM3z4cDyePeOYZVk0atSIiy66CICdO3fy8ccfH9T+0tPTGTp0aCgXVHXub1kWffv25fjjjwegsLCQVatWRUTPgUii0C0iIiIiIhHKgLErxlc7cTsAa9eu5ddffwXg8MMPp3nz5tU2gp166qnExsZijGHu3LkEg8EDfmdquhSYz+ejTZs2oX8XFBQc8L5k3xS6RUREREQkYkVCo6wxhhUrVlBaWgpAt27d8Pl8VW5rWRatWrUiLS0NgNWrV1NYWFhntVUuKwbg8XjIyMios339WSl0i4iIiIhIBAt/1/KK7tcHlvZ//vnn0HK9rVq12mcrdFJSEg0aNAAgJycnFIrrQlZWFvPmzQMqxpRr9vLap4nUREREREQkIpnKJcOcWDHMrqxh7zHeVYXW7du3h/57f63JMTExpKSkAFBUVFRnLd3BYJB//vOfrF+/HoAzzzyTli1b1sm+/swUukVEREREJHIZHAndAMuXL2fixImhkJ2SksJ1110XCsy/VzlWunKS433xer3ExcUB4Pf7KSkpqeXKKy4WzJ49m8ceewxjDM2bN2fChAl7zKYutUOhW0REREREItNvE5pVtjqHe9+WZYWW6QX2mo389wKBQOi/a7Lu9u+3+f3P1gZjDIsWLeLaa68lLy+PxMREpkyZQocOHdS1vA4odIuIiIiISMRybCI1A507d+bee++tUevwgYboAw3pNWWMYeXKlYwcOZL169cTFxfH3/72NwYPHqzAXUcUukVEREREJHIZMAc4qVltqunSXMnJyUBF6N3fGO1gMEhxcTFQsaRXZVfzP8oYw9q1a7n44otZvnw5MTEx3HLLLVx77bXqVl6HFLpFRERERCQiVUykZmMcaKE19oEF/UaNGoX+Oysra5/blpaWsnv3bgASExNJSko68AL/hzGGX375hYsvvphFixbh8/m48cYb+etf/4rP51Mrdx1S6BYRERERkYhlYK/Zw8O13wPRpk0bLMsKhd/K5cOqUlBQEJrtPC0tLbRm90HXagzr1q1jxIgRLFiwgKioKK6//nomT55MTEyMAncd0zrdIiIiIiISmYwB2/yWvMN8O4DYbVkWnTt3DnUTX7p0KeXl5dW8JMPPP/8cWpu7U6dOxMfH13hfVT3fr7/+ysUXX8x3332H1+vlqquu4s477yQ2NlaBOwwUukVEREREJGI5Npr7AHfcrl07WrVqBcCPP/7I+vXrq22hnz17NmVlZViWxUknnXTQ462NMWzcuJFLLrmE+fPn4/F4uPzyy7nvvvtISEhQ4A4TdS+XGrF80XjSG2B53PfB9FJIrHfrAY+rCZcYXxRWRiaWSyeniIotJ8be91qRTjLpmZQl1nO6jGoFiMdYB3/1ua5ZsX4sf9DpMqpkxcWBSz8XAJ4oD3HpSdjlfqdLqZI3xkdUeiYerzuvn3uLczBsdfBseN+ikhKJbZjqdBnVSvXH0bisdpcIqk2lxmKL352fX4/XQ/24ZDzxtTPxVK0zEJXRgGhvgtOVVCmqrNTpEg6cwxOp1VRycjLnnnsuK1asIDc3l+nTp3PfffftMTN5ZUh+/fXXAWjYsCGnn356leH4888/56effgKgd+/edO3adY/HjTFs3ryZkSNH8vXXX+PxeLj44ot54IEHamWMuNScQrfUiLd1e+InP4i3FpcrqC3WytUcveBaTMCdwcLXtDEJdz2MJzbW6VKqlOiBZi68mFJpa1E5K0vde+KZHO2lXoz7PheVYj0WHpdexfZ4LDz1/tgYtboUl5nK0RMHY2x3HluIScAcNRCifE5XUiV77jzsz25yuoxqNT5/IN1GDXa6jGq1+PprBsx6x+kyqjVlRwoPZac4XUaVYmOieePoi2jWOMPpUqpkWdDkdIhy56GZBi+/zM/fzXe6jBozBmy7+rHRdck+iAafkSNHMmPGDH799Vf++c9/0rVrV4YMGUJ0dDTGGLZv385NN93EunXrsCyLSy65hBYtWlT5XM8//3wonP/973/fK3Tv2rWLyy+/nC+++AKA4447jquuuoqsrKx9TuRWG2PIZU/uPVMUd/F4IDYOy42hOzoGr2WBS4Oj1+PBio2taNVzIY8FnqiaLXXhiKAHO+jOlkYAEx0Fse4MPQB4LFf2UIGKE0/c+ndHxfg7b4wPjDtb80yMDzs2FqKinS6lSpbPnXVV8viiiHJrSygQHRNFvMe9LXdBLEqMO3tZGGNhe33g0r9BA3hivHi97jv+GWOwol38nRbhLMuiZcuW3HvvvVx11VXk5+dz1VVX8cYbb9C9e3fy8/OZM2cOa9asAaBv376MHz/+oLuW//TTT3z55Zehf3///ff069dvvz936623MmnSJPeeG0Yg9yUoERERERGRmrINxol8eBDXxSzLYsiQIQSDQW677TY2btzIRx99xEcffRTaJiYmhjPOOINp06aRkXHwPTaMMXuMGff7/fj9+2/IqMk2cmAUukVEREREJDL9T7AM884P6qeioqIYNmwYvXv3ZtasWcyfP5+srCxiYmJo3749AwcO5MQTTyQ+Pn6frc1Dhw4NdSk/9thj93q8WbNm3H333di2fUD19enT58BekOyXQreIiIiIiEQupyZS+wO79Hg8tGrVihtuuIFx48aFLhx4PB4sq2bD/s4++2zOPvvsah9v2rQpN99888EXKbVGoVtERERERCKToWIFGwfGH9dGA7tlWQc9ZlsihztnwBARERERERE5BKilW0REREREIpKhoqXbdmAiNXMQS4bJn5NCt4iIiIiIRCZTO928ReqSQreIiIiIiEQo49xEaiI1pNAtIiIiIiKRyYCxbWcmUlP3cqkhTaQmIiIiIiIiUkfU0i0iIiIiIhHJAMY41Llcg8mlhhS6RUREREQkYpmKYd3h368D+5TIpNAd4Ywx2LZNYWEhu3fvJi4ujnr16hEVteev1rZt8vPzyc/PJyUlheTkZCwHxr6IiIiIiNQag3MTqSl1Sw0pdEe47OxsJk2axA8//EAgEMAYQ+/evbnzzjtp0qQJAGVlZfzzn/9k+vTp+P1+YmNjGTt2LMOGDdsrnIuIiIiIRA5TMaGZE41JCt1SQ5pILcIVFhaSmprK448/zieffMKzzz7LwoULmThxIn6/H2MM7733HlOmTOGvf/0rH330EWPHjuX2229n/vz5GI1FERERERERqTNq5oxwLVq04IEHHsCyLCzLomnTpowePZp7772X/Px86tWrx8yZM+nTpw9DhgzB5/Pxl7/8hVmzZvHyyy/Tp08fdTMXERERkYhkTMXSXbYV/oYkNV5JTamlO8J5PB48Hs8ewXnXrl3Ex8cTFRWFMYacnBwyMzPxer0AREVFkZ6ezuLFiykpKdnj+Ywxe91ERERERNzKVM6kFuabzpOlptTSfQgxxvDzzz/z0ksvceGFF5KUlARAu3btWLJkCQUFBSQnJ5OXl8eyZcvIycmhrKyMhISEPZ7n888/Z+3ataF/L1y4MKyvQ0RERETkQCgAi5spdB8ijDFkZWVx7bXX0rp1a8aOHYvH48EYw2WXXcbgwYO54oorOOGEE/j666/Jzs6usiXbGMPq1av5+uuvQ/dt2rQJT0xcuF+SiIiIiMi+GYMJOjSRmh3+XUpkUug+BFR2Ib/mmmsoLS3llVdeoX79+gBYlsWRRx7JrFmzeP3111m4cCGnnHIKbdq0Yfbs2cTGxu7xXJZlMWbMGK6++urQfW+99RZPPvNcWF+TiIiIiEhNqaVb3EyhO8IZY9i9ezfXX389W7du5ZVXXqFp06Z7jPH2eDwcccQRdO/eHWMMfr+fIUOG0LNnT+Li9mzBrpyQ7X/vExERERFxG2MA2wDhP19V0Jea0kRqEa64uJibb76Z//73vzzyyCPUr1+fvLw88vLyCAaDoW02bdqE3++npKSEN954g2XLlnH55ZcrUIuIiIhIRFP2FbdTS3eE+/nnn3nzzTeJjY3lyiuvDN1fr1493njjDRo3bsymTZsYMmQIKSkplJaWUlJSwpQpUzjiiCMUukVEREQkshmDI7lbYV9qSKE7wrVr14758+fv1b2lclkwgFatWvHGG2+wYcMGfD4fnTp1omHDhgrcIiIiIhLZjMHYBuPAaa26l0tNKXRHuLi4ODp16rTPbXw+Hx07dqRjx45hqkpEREREJDwUfcXtFLpFRERERCQyGSpau51I3mrplhrSRGoiIiIiIhKRfsvczuxbmVtqSC3dIiIiIiISuYzGV4u7KXSLiIiIiEhkMmDbxpEJgpXzpaYUukVEREREJKKppVvcTKFbREREREQikjEGbBtwYM0wW0FfakYTqYmIiIiISMRybCI1LVYmNaSWbhERERERiVzGoQCszC01pNAtIiIiIiKRyVDRzduBidQUuqWm1L1cREREREREpI6opVtERERERCLTb0uGOTGPmmZMl5pS6BYRERERkYhkKgZ0O7VzkRpR6JYaCRoo8Qfx2g5cRtwPv22ISfRhgu4cLeGN9+EPGqyg7XQpVfJaQeJNmdNlVMsXBEcuX9dQiT9Itu3O3y1YNEmKJsHnzs+GZVmODMGrsSgfwbTDwLjz92t8MQSNhXHpkjWWxyIxLsq1J6XGG0V+0L2nQYHYOOIyUpwuo1rdM1tjk+Z0GVXyej0sWfUrP2/Y7nQpVbIsOP6IttRPTnC6lCr5gy790O6DMc7MIx5575Q4xb3fNuIq5UGb7CI/3ij3HV48QUNS40QIBp0upWqZ8RQFglDuzvpiTSEZuPPEBCArUA8PSU6XUa2dxeXsKvY7XUa1DkuuT4N4dx7qLcvC6+LQbcckUt7xBOfWotkPw2+HlYA76/N4PDRNi3Nt98tgTDybAnFOl1GtpHrppB/e0ukyqnXVMWdR1rSj02VUqbTMz3lXP8CvW7KdLqVKHo/Fiw+N5fCOLZwupUqFfneer+yTY2uGufP4Ju7jzjMxkYNgubTJLFIOx+589yq49XcbKfT+/UFuff8i5GTP3X9/bq7N5e+d5e76IuPT4T5uvUhWE5Fcuxz6FLpFRERERCQyGYNtGzwOXERz6/AecR93DvQTERERERHZD2NQ1wZxPbV0i4iIiIhIxDKoe7m4m0K3iIiIiIhErqBxZP4Nly5uIS6k0C0iIiIiIhFNLd3iZgrdIiIiIiISmQwY28ZyYjUCBX2pIU2kJiIiIiIikckY5yZSU+aWGlJLt4iIiIiIRKyK3B3+BOzEPiUyKXSLiIiIiEhEMlSsl22cmEhNmVtqSKFbREREREQimiZSEzdT6BYRERERkchkKlq6HZlIzVbQl5rRRGoiIiIiIhKZDJrQTFxPLd0RLhAIsG3bNjZt2kR+fj7p6em0b9+exMRErN/Gthhj2L17N8uXL8fv99OpUycyMzNDj4uIiIiIRCqDQ93LFfalhhS6I9wvv/zCkCFD8Pl8xMfHk5WVRaNGjXjqqafo0KEDAD///DNXXHEFOTk5+Hw+gsEgjz/+OMcff7yCt4iIiIhELIPBGIcmUgv7HiVSqXt5hGvSpAkzZ87kyy+/ZM6cOcyePZuysjLuv/9+bNsmGAxy9913Exsby2effcZ//vMf+vTpw80330xBQYHT5YuIiIiI/GHGmLDfRGpKoTvCJSYm0q5dOxISEoiOjqZ58+YceeSRbN68OdT1fO7cuYwaNYoGDRqQkpLClVdeybp161i6dKkOGCIiIiISsQwQNAYbHLjpPFpqRqH7EGCMYdeuXWzevJkvvviCr776irPOOovo6Gg2bNhAWVkZHTp0CHUlb968OQkJCaxevbrK56psIa+8KZiLiIiIiIgcHI3pPgQEAgEmTJjA119/zc6dOznjjDMYMWIElmWRl5cXGu9dyefzkZiYyK5du/Z6LmMM//znP5k3b17ovg0bNoDRn4qIiIiIuE/FRGoO7FftUlJDSlKHgKioKKZMmUJRURHLly9n8uTJ3HfffUydOhWPx1PluBPbtvF49u7oYFkWrVq1ory8fI/nX/7Lhjp/HSIiIiIiB8Lw23LZDswNrMwtNaXQfQiwLIvMzEwAWrRoQVZWFn/729/461//SkZGBuXl5eTn54e2LykpoaCggIYNG1b5fP3796d///6hf7/55pssf+KfdfsiREREREQOkoZDiptpTHeEq6oV27IsjDFYlkXz5s1JTU1l4cKFoW1Xr15NaWkpXbp02WvJMMuy9rqJiIiIiLiSqZjQzImJ1JTzpabU0h3h5s2bR2FhIZ06dcLr9bJy5Uoee+wx+vfvT7169fB6vZx//vk88cQTdOvWjaSkJKZOnUrPnj3p1KmT0+WLiIiIiBy0yvHcTrQTKXNLTSl0R7icnBzuueceioqKgIqW6lNOOYVbbrkFn8+HMYYJEyaQm5vLiBEjAGjfvj0PPfQQMTExTpYuIiIiIvKHhcZ1O7BfkZpQ6I5wZ555JieddBK5ubkEAgFSU1NJTk7G6/UCFSE8LS2NJ598kuzsbAKBAJmZmcTExKjruIiIiIhEtMrA7VFLt7iYQneE83g8JCYmkpiYWO02lmXh8/lo3LhxGCsTEREREQkPTaQmbqbQLSIiIiIiEckAQWPwONCDU0Ffakqzl4uIiIiIiBwgRW6pKbV0i4iIiIhIZDL/P4O5iFspdIuIiIiISEQKzVzuxERqCvpSQwrdIiIiIiISoSqSrxPjq5W5paYUukVEREREJCI5OpGaYrfUkCZSExEREREREakjaukWEREREZGIFRrX7cB+RWpCoVtERERERCJSZeD2aCI1cTGFbhERERERiWgKwOJmCt0iIiIiIhKZDNg4smIYtgP7lMikidRERERERCQiGdTKLe6nlm6pkWiPh7R4H16v1+lS9uKpF0dsh8Zgu/N6o6mXQSDeB9Hu/LglBr1Qbrl2MpDUWB9NvTFOl1GtxGgPCT73fS4qJVgBrPJip8uokmVZWDHRTpdRLY+xiS4vxK1T5RgDPn+ZS6sDf6AAy+tE21PNJHkDpHtLnC6jWmXZO9n2wzqny6hWYvtiElq6s+0mxvJx+ZCTyS1w57EPY/jiu+XM+Wap05VUafV/l9LIvYfmKlUEb82kJu7lzhQgrhPltUiNjSIqyn1/MlZSLDEtM7GMS0N3Un0CcT7wue+9A4gt92L8Hke6ZdVEUowXT6x7v/3jojzERrk1dBvirACeQMDpQqphubx5wsYXcOlJO4CxscqLXPvZLQ0U4fG6M5QBJHiDpHvLnC6jWttz89i1YrPTZVQrobCEeJ87f792lMV5p/Uk4NLDSzBoM/Kmx1i2eoPTpezFGIO9ay3n9WrsdCk1VjGRmgEH1ul255mnuJE7U4CIiIiIiEgNufoarvzpKXSLiIiIiEhEMkDQoSXDnFgbXCKTO/sFiYiIiIiIiBwC1NItIiIiIiKRyfxuXLcTOxepAYVuERERERGJUAbbGDwOTKSmyC01pdAtIiIiIiIRTROpiZspdIuIiIiISEQyVCzd5cTyiZpITWpKE6mJiIiIiEhEMqiVW9xPLd0iIiIiIhKxnJpITVlfakqhW0REREREIpZzE6kpdkvNKHSLiIiIiEhEqoy9WjFM3EyhW0REREREIpOBoAGPAzOpOTWBm0Qehe5DgKni0p7lQBcbEREREZFwUmOzRAKF7ghXXFzMN998w5o1a8jLy6NBgwaceOKJtGnTBo/HgzGGwsJCNm7cyE8//YTX66V///7ExMQ4XbqIiIiIyB/m5ERqauaSmlDojnAbNmzg7rvvpmXLlqSkpPDll18ydepUnnnmGU4++WSMMdxwww189NFHlJaWkpqayvfff6/QLSIiIiKHBMcmUlMzu9SQQneEa9OmDR9//DHx8fFYlkVRUREXXXQRTzzxBH379iUqKorLL7+ca6+9ls8//5ynnnrK6ZJFRERERGqV8q+4mUJ3hPP5fPh8vtC/4+PjadiwIVu2bMEYg2VZ9OrVC4Dvv//eqTJFRERERGqdwbnAraAvNaXQfQiwbZtly5axc+dOli5dyrfffss999yzRxivKWMMZWVlBAKB0H1lZWW1Wa6IiIiISK3R2GpxO4XuQ0AwGOT555/n22+/Zdu2bRx11FH06NHjoJ7LGMM999zDRx99FLovNzeXw1q0qq1yRURERERqRWVLt1MTqYnUhEL3ISAqKopHHnmEQCDA5s2bueaaa7jhhht49dVXD3jCNMuyuPjiixkwYEDovjlz5jDni69qu2wRERERkT/MsYnUFLulhhS6DwGWZREVFUVUVBStW7dm5MiR3HDDDezatYvGjRsf8HO1a9eOdu3ahe7buHGjQreIiIiIuJYjM4krc0sNKXRHuGAwiMfjwfrt6p4xhs2bN5OQkEBsbKzD1YmIiIiI1B1jwMaZMd3K3FJTCt0RbtasWaxatYqjjjoKn8/Hf//7X5544gmuvPJKUlJSMMawcOFCfvzxR+bPn09+fj6vvfYa9erV48wzz6RevXpOvwQRERERkYNmDDjQu1yhW2pMoTvCNW/enA8//JDPP/+cYDBIRkYGU6ZM4fzzz8fr9WKMYfXq1Xz44YcA9OnThy+//JLY2Fj69u2r0C0iIiIiEaxiZLVxpH+5SM0odEe4o446iunTp1NWVoZt28TExOzR3dyyLIYNG8awYcMcrlREREREpHaFZi53ZCI1kZpR6I5wleF6X+O3LSf624iIiIiIhIkTDd1qXJeaUugWEREREZGIZICgAU8Ej+n+fdf4cDWWVe5TjXPhodAtIiIiIiISRsYY/H4/a9euZfHixWRnZxMdHU2bNm3o0aMHGRkZtRqIjTHYts3mzZtZuHAhGzduBKBp06YceeSRNGvWbI8hqlK7FLpFRERERCRihcZ1h32/B7dPYwxr1qzhjjvuYPbs2RQUFGDbNgA+n4+WLVty/fXXc+mllxIXF/fH6zSGnJwcHnjgAWbMmMGOHTsIBoMAeL1eMjIyGDZsGDfffDPp6ekK3nVAoVtERERERCKSMRWB2+PERGoHkbmNMSxbtoyLLrqIlStXYlkW6enpNGrUiLKyMjZs2MDatWsZP348GzZs4K677iImJuYP1ZmTk8Oll17Khx9+iG3bJCUl0axZMyzLYtOmTWzfvp1HHnmElStX8tJLLyl41wGP0wWIiIiIiIj8EcaE/3Yw8vPzGT9+PCtXrsTr9XLppZfyzTff8N133/Hdd9/x1ltv0bZtW8rLy3nsscd4++23/9ByaIFAgKlTp/LBBx9g2za9e/fmk08+Ce1vzpw5nHrqqRhj+OSTT7j33ntDreBSexS6RUREREQkIhnAdvB2QLUaw6xZs/jqq68AOOOMM5g2bRpt27YlLi6O1NRUzjzzTJ555hlSUlIoLS3lgQceICcn5yDemQorVqxg+vTpGGNo3bo1L7zwAsceeyyJiYkkJCRw5JFH8txzz9G5c2eMMbz00kssXbpU657XMoVuERERERGJWJGSD8vKynj55ZcJBALExcVx4403kpSUtEdXbsuy6NOnD4MGDQJg5cqVfPXVVwcVgo0xvPnmm6HQfuWVV9KmTZu99nfYYYdxzTXXYFkWeXl5vP7663/wlcr/UugWEREREZGIZagImOG/HVidGzduZMmSJQC0a9eOI488ssqx016vl3PPPZeoqCgCgQAff/zxQYXu4uJiPvvsMwCSk5MZMGBAlfuzLIvTTjuNtLQ0AD7//HMKCwsPeH9SPYVuERERERGJSAaDbYwjXcsPZPZyYwzLly8nPz8fgB49ehAfH1/ltpZl0b17d5KTkwFYuHAhZWVlNd5XpW3btrF+/XoAmjdvTvPmzavdtlGjRrRt2xaAX3/9la1btx7w/qR6Ct0iIiIiIhLRImEitTVr1oQmKWvfvj0eT/VRrH79+jRs2BCA7du3H9S47i1btrB7926gInRXF/IBYmJiaN26NQCFhYVs2LDhgPcn1VPoFhERERGRiBRJE6lt2rQJqGjJbty48T6X5YqLi6N+/fpAxYznleH5QGzbti0U8hs1arTPkG9ZFo0aNQIqZjzfvn37Ae9Pqqd1uqVGbNumrKyUYMB9fzJWWRkEAmAf6KEvTAIBAmWlmKA767P8ZQfVZSlcSq0ySil1uoxqlZUFKCsLOF1GtUq9AUpd+reH5SFYWorldd9xBcAEyvGXlXEAvQfDy9hY5eVYLp1BqNTvp9y2Xfv2lQX8lJa699hX5g9Q5tbvNaDM76e01J3HZmOgrMxPwHbnX1/QtjHBAMZ26XeHsSNq5moDBDBYDhxtbCAYDFJaWorX6w3dHxMTU2Wgzs3NBSoCbmpq6j6fOyoqioSEBKBiArbi4uIDri83Nzf0u9zf/v63pspapXa480xHXKW0tJTlSxcz/Lyz9nlFrqaMMRjb4PHWUkeLQDmevOzaeS4qLjAA+7waeEA8UZiXZkMtvHcA9m99mmqrPo+x8drltfJcUPH+WYBVS/UFPT5sy7v/DWv6fLaNx/LU1q+DoKFWT+zsYBDL46mVzxpArMcQZdVOfQawgzYer4faqc6qCNy19FqNMdi2vceJzx98Qkyg9j4bhorPh8dTW+8fYGovlBm74kTbU0vvX6ComJKtO2rlueC3Y4sFllU7x5aYfzxF9Gu1N0NvbR+b/bvzKcveVSvPBWDbQSyr9o4tMbdMxJuUVCvPBRC0g799NmqnPr99IKNt963ivMWutc8GxrB+8w4oqZ2LPpXHFm8t/e1ZgVL8/szaPZ7WEcuy2OEN8CE7a++4egBKsfHOm8dJJ50U+mylp6czffp0MjMz997+dxeqoqOj9/nclmWFtjHGUF5+4N9HB7I/qLhYUNXPyh+n0C37ddJJJ/HKjBnVXrU7UN9++y0zZ87kvvvux+fz1UKFtccYw4svvkhZWRmjR4+utZOT2vSvf/2LVatWcfPNN9fehYFaYts2U6dOpXPnzpx99tlOl7OX4uJixo8fz7hx4+jYsaPT5ezF7/czYcIELhx8IT179nS6nL1kZ2czYcIEpk6dSoMGDZwuZy8LFy7kpZde4qGHHqrRyUW4/fTTTzzwwANMmzaNxMREp8vZy0cffcSCBQu4/fbbXXlseeSRR2jevDmDBw92upy9GGOYPn06wWCQUaNGue67IxAIMGnSJM466yyOP/54p8vZS25uLjfccAP33HMPTZo0cbqcvSxbtoynnnqKRx55hNjYWKfL2cuGDRu46667mDZtWmjirT/C7/dTr1491wduqFjnusUnHzm2f2MMfr9/j++cmJiYan8Pvz+21qQ3we+3OZjjSrj3J9VT6Jb9atasGc2aNau15yspKWHOnDmcfPLJrjsxNsbwxRdfUFJSwimnnOK6A44xhlWrVpGbm8vJJ5/sui/EYDDICy+8QIcOHTj55JNd9/4VFBSQlJTEMccc48pQW1ZWRmpqKt27d+eUU05xupy9bN68mfj4eHr37k2LFi2cLmcvxhhmzZrFSSed5MoT4/r165OYmMiJJ564325+Tli/fj2//vqrK48ttm3zxhtv0LZtW1ceW4wxzJ07F7/f78rvDr/fT/369Tn88MNdeWzJysoiISGB4447LjR7sptUhqh+/fqFuvu6yYoVK0hISKBv376hJZ/+DCzLokmTJq68UFOduLi40H/vryXZGBMa/ufxePZohT6Y/ZWUlOx3+99vs69J1+TAuetStoiIiIiIyCEoPT0dqAjUu3bte/hIeXk5BQUFQEV4PpgLPunp6aGLgPub/fx/a6qsVWqHQreIiIiIiEgda9myJVARcDdt2rTPLt9FRUVkZ1fMWZSamkq9evUOeH+NGzcO9SrdunUrgUD1k/cFg0G2bNkCVPTuaNy48QHvT6qn7uUSdq1atWLw4MGuGzNYqXfv3vj9fqfLqFb37t2pV6+e67ovQkVXrwEDBoS+VNzG5/MxfPjw0LqXbuP1ehkyZIhr37/ExEQuueSSWhkzWBeaNWvGhRde6Lqu0ZUyMzMZMWLEQXURDIeuXbsSFRXl2mPLqaee6trPLkCfPn1CS/O4jcfj4bzzzqNNmzZOl1Kl+Ph4LrnkElcOuwBo0qQJF110kevmoamUlpbGxRdf7MphNbKnDh064PP58Pv9rFixgmAwSFRU1XFs+/bt7NhRMRll8+bNSUlJOeD9NW3alPr167Nt2zbWrVtHQUFBaBmy/1VSUsLatWsBSE5OduUwskhmmUhaE0AOCW6epOF/Pw5uqw8i5/1zW22g+v4o1ffHqL6D5/ZjcyTV57baQPX9UW6vT/7fli1bOOaYY9i6dSutWrXiu+++IyMjY6/tjDE8//zzjB49Gtu2mThxIvfdd98B/37Lyso488wzmTNnDrGxsXz22Wf06dOnym0XL15M3759KSgooG/fvnzyySe6kFOL3NnUKIc0y7JCN7f5fW1urA8i5/1zI9X3x6i+P0b1HTy3H5sjqT43Un1/jNvrk//XoEEDTjjhBAA2btzIp59+WmUX85KSEl5//XVs2yYuLo6BAwdW+Xy7d+8mKyuLrKysKtfxjo6OZtCgQViWRWlpKW+88UaVPXJs22bmzJkUFBRgWRZnnXWWa3tlRSqFbhERERERkTrm9Xq54oorSEhIIBAIMHXqVNavXx8K3sYYgsEgL730Et988w0Affv25cgjj6zyosqECRPo3LkzXbp04ZVXXtnrccuyOOecc2jVqhUAr732GnPmzNkj6BtjmD9/Ps8//zxQMVTrggsu0EWcWqbQLSIiIiIiUscsy+L4449n+PDhWJbF8uXLueCCC3j99ddZvnw533//PZMmTeLmm2+mvLyczMxMbr/99mq7eRcUFLBr1y527txZ7RJkTZs25ZZbbiEmJobc3FwuvfRSHn74YRYvXsySJUv4xz/+wfDhw9mxYwcxMTFMnDixVpcKlgqaSE1ERERERCQMfD4f99xzDzk5Obz77rssXryYiy++mJiYGGzbDoXnzMxMHnvsMXr27PmHWp0ty2L48OFs3ryZBx54gG3btjFhwgRiY2ND3c4ru7HfcMMNjBw5Uq3cdUChW0QOaZVdqILBYGgck9frDc1wrS+WQ4sxBtu2XTvGsXId1KSkJNeNl3PzZGCVv9eysjIsyyImJsbR32/le+Wm9+h//e/kWsYY/H4/lmW5Zpb6yt9rZa0ej8dVn9vfd/kFXFWbRC7LskhLS+O5557jxBNP5MUXX+Tnn3+mqKgIr9fLYYcdxvHHH8/48ePp0aPHPlf7adq0KZ06dQKodlZyqFgCbNKkSfTo0YMnnniCJUuWkJeXB1Ssx92tWzfGjBnDgAEDXDtLf6TT7OVSpyq/UCu/SI0xlJWVsXbtWrZv3069evXo0KEDiYmJjnyR2bZNQUEBiYmJoRrdxhhDfn4+fr+fevXq4fF4yM/PZ82aNXg8Htq0aUNKSoqjJ5/BYJDc3Fx27dpFeXk5MTExZGZmkpKS4ujScMFgkMWLF/POO++wePFidu3aBVQsr3LEEUdw3nnnccQRR1S7XIfTiouLmTFjBoMHD97nl2ldCQaDrFmzhp9//pmmTZvSuXNnoqOjQ39rO3fu5Ntvv+WMM84I+3tojGHHjh189tlnBAIBTjvtNFJTU3nzzTf5/PPPSU9PZ9iwYdWOgwtHfVV9vQYCAYYMGcJNN93EcccdB4T/RN4YQyAQwOv1hj6fZWVlfPnll8ybNw+oWP7qhBNOcOTCgDGGNWvW4PV6Q0tcLVu2jEcffZSlS5fi8Xg49thjGTduHC1btnTk9/vaa6/h8Xg48cQTyczMdFUYM8awceNGXnnlFfLy8jjnnHM48sgjeeGFF3j99dcBGDhwIGPGjCEpKcmRGoPBICtXruSDDz7gxx9/ZNeuXURFRdGiRQtOOeUUTj31VMfOCyrPW9avX8/XX3/N2rVrKSgoIDo6mqZNm9KrVy+OOOKIUCuh2xhjWLt2LXFxceoiHAGMMRQVFbF161YKCgqIiooiMzOTjIwMvF7vfv/GysvLQw0KPp9vv9/FxhjKy8vZtm0bubm5GGOoX78+jRo12uP7XWqfQrfUqby8PKZOncqYMWNo1qwZ27Zt4/rrr2fu3Ll4PB6CwSBdu3blH//4B507dw77hz0nJ4dBgwbRtWtXBg8ezFFHHUVSUpJrDjrBYJDXXnuNBx98kNLSUi644AIuvfRSxowZw8KFCzHG0KlTJ5555hk6deoU9rqNMSxdupRp06Yxb948du7cSXl5OQkJCTRo0ICBAwcyduxYGjduHPbabNvm2Wef5Z577qFly5Z069aN9PR0oCIs/vjjj6xbt45bb72VK6+80pXrxu/cuZMTTzyRWbNm0bZt27Du27Ztnn76ae6++26gIiyeccYZ3HfffTRp0gTLsvjvf//L6NGj+eabb4iLiwtrfbt27WLIkCGsXr2auLg4WrZsSb9+/XjmmWfo0aMHWVlZbN++nXfeeYfu3buHtTaAFStW8MQTT+x1v23bvPfeexxzzDE0adKE9u3bM3bs2LB+Pvx+P5deeik33HADPXr0IBAIcO+99/KPf/wjdJK+ceNGrr/+eiZOnBj2CyqBQIDzzz+fIUOG8Je//IUNGzZw5plnkp6ezsknn0wwGOTTTz/F4/Ewa9asKpfbqWvDhg3jvffeo1GjRpx22mkMHjyYHj16OBYUfy83N5fzzjuPLVu20LhxY7Kzsxk8eDBvvvkmAwYMwO/3M2vWLK688kpuvfXWsB/7bNvm+eef57777iM1NRWv18u6deto0qQJzZs3Z/Xq1XTs2JEnn3ySpk2bhv399Pv9/P3vf+fxxx8PXUBOTEykvLycXbt2sWPHDvr06cNjjz1Gw4YNHf99/y/bthk7diytW7dm/PjxTpcjIr9xZ/OOHDLWr1/P7NmzmThxIrZtM23aNNavX8+rr75KmzZt2LlzJw899BA333wz77zzTtjXAwwGg2zcuJGioiLefvttWrRowXnnncegQYNo06aN41f9fv75Z26//XbOPfdcOnfuzCuvvML8+fNp0aIF999/P2VlZdx5551MmTKFF198Mawnx8YYVq1axbBhwzj88MMZN24cu3bt4s0336R///506tSJt99+m7/85S+8/vrrNG7cOGy1AWRlZfHoo49y9913M3To0FB31Mray8rKmDlzJvfddx+DBg0Ke32BQIC5c+dWucRHpYKCgn0+Xpc2btzItGnTuOWWWzjrrLP46aefuOuuu/jLX/7C888/T5s2baptza1rxhg+++wzdu3axaeffkpaWhoTJ07kqaee4sUXX6Rv376UlJQwevRoXnjhBR599NGwf443b97M888/T9euXUlLSwvtv3K83rZt2ygrKyM5OTmsdUHF+/fzzz9TWFgIwNq1a5k+fTqPPPII559/PgAzZ87kzjvvZOjQoWG/4FNcXMy2bdto06YNlmUxe/ZsMjMzefvtt6lXrx4AV199NYMGDeKrr74K1Rxu119/PRkZGbzzzju89dZbtGrVivPOO4+zzjqL1q1b4/P5HPn+WLx4MTt27OCTTz6hadOmzJgxg0mTJjFjxgxOOeUUAHr16sW0adMYP348iYmJYa1v48aNPPzww0yZMoWzzjoLr9fLggULmDBhAlOnTiUpKYkJEyZw55138vTTT4e9q+u8efN48sknue++++jfvz+pqamh32NJSQmrVq1iwoQJPPTQQzz44INh/x1nZ2eze/fuah83xpCTk0PLli3DWJWI7I9Ct9SpvLw84uLiiImJwe/38+2333LLLbfQv39/LMuiVatWTJ06lbPOOovt27fTokWLsNeYmJjIK6+8QkFBAe+++y4zZszgscce4+ijj2bo0KGcdNJJZGZmOtL9fOnSpbRs2ZL77ruPmJgYWrVqxcUXX8zzzz8fWv7htttu47rrrqOwsJDU1NSw1jdz5kyOOOIInnvuuVA31JNOOil0wjRkyBBGjBjByy+/zM033xzW92/79u34fD4GDRq0VyusZVnExcVx1lln8dBDD7F9+/awh+7S0lKuueYadu7cWW0X3soxrE5Yu3YtGRkZXHHFFcTHx9OiRQu6du3KuHHjGD58eGhpEaesXr2avn37hsaynXPOOaxYsYJjjz2WqKgokpKSOO+883jmmWdCQx7C6aijjmL06NH8+OOPXHfddZxyyin4fD4CgQD9+vXj7rvv5sQTT3RFK9nq1atp3rw5gwcPDl34HDp0KM899xyrV68Oe+iOiorC5/ORl5eHMYa8vDw6deq0R/jJzMykdevWbNu2Lay1/d5hhx3G6NGjufLKK1m6dClvv/126CJPz549GTp0KKeffnrYj8vbt2+nVatWNG/eHK/XS69evUhJSaFbt26hVu0jjzyS8vJyioqKwh66f/nlF+rVq8fZZ58dOjb37t2bVq1a8f3333PZZZcxefJkLrzwQnbu3EmjRo3CWt+CBQs44YQTuOiii/bqBZCUlMTRRx/NTTfdFLrwHe5ePtOmTeP5558PzUtSlfz8fI488sgwViUi+6PQLXWqcePG5OXlsWXLFpo3b05ycvJeLWNOtZb9XlxcHJ06daJnz57cfPPNfPPNN7z55pvcfPPNxMTEcNZZZ3HPPfeE/eSkvLyc+Pj4UItJ5eRL8fHxoZPPxMTE0LjqcDLGkJ2dTfv27fdoRW7bti15eXnk5ubSokULzjnnHD7++GOCwWBYW+IzMjJC41TPPPPMPSYOqhzT+tVXX1FaWupI91Sv10t6ejp/+ctfGDVqVJXb5ObmMmTIkDBXVsEYs9eEcw0bNuTpp5/mxhtvZMSIEVx11VWOfXZ///u0LIvk5GTq169PdHR0aJuEhASCwaAjNdavX5+HH36YOXPmcP/99/PRRx8xYcKEUNd8y7L2edIcDmVlZRQVFeH3+0lJSdmjRdHn85GcnOxIT4u4uDhOOukknnrqKbp160bv3r25+eabWbt2La1btwYquu8vWbKESy+9NOz1/Z5lWcTHx9OrVy969uzJxIkT+frrr3nzzTe58cYbAbjwwgvDWlODBg3YsGEDW7dupWHDhixevJjdu3ezatUqMjMzAVi+fDlRUVHEx8eHtTaAlJQUdu/ezY4dO2jWrBmWZVFYWMjmzZtDF8fS09PxeDyO/P2lpKSwdetWCgsLq+yJYts2v/zyC4mJiY58hqOiomjUqBF33313lfs3xvDkk0+GvS4R2TeFbqlTLVu25LjjjmP8+PFMnjyZ8847j0ceeYTY2Fjatm1LdnY2jzzyCO3bt6dhw4aO1lp5Ap+WlsagQYMYOHAgGzdu5OOPP2bOnDkUFxeHPXS3b9+eFStW8M4779CxY0f++c9/YlkWr7/+OpdddhmBQICXXnqJBg0ahH1CHMuy6Ny5My+//DJDhw6lefPmlJeX8+abbxIVFUVKSgpQcQLgxERljRo14vLLL+faa6/lpZdeokePHqFwnZ2dzeLFi1mwYAHXXXdd2Fu5oWIm0cMPP5z169eHgtj/iouLc2yMaMuWLdmxYwcbN24MtXRalkVqaip///vfueWWW5g8eXLoJN6J+r799lv8fj/R0dH07NmTZ599NnQSaozhl19+ISMjw5GZWC3Lwufzcfrpp3PkkUfy6KOPMmTIEEaPHu1Y74Xf8/v9jB07lsTERAoKCoiJiaGwsDD0uS0uLiYrK4sGDRo4Ut91113HVVddxWmnnUbPnj0pLCzk1FNPpXv37ti2zfLly+nfvz+9e/d2pL7/VXkhJSMjg3PPPZdBgwaxYcMGRyaiO+KII0hJSWHgwIE0a9aM1atXc/nllzNu3DgGDRqE3+/njTfe4C9/+QsJCQlhr69Dhw60aNGCYcOGhYb+fPjhh6Gx0lDRBd3j8YSGE4TTaaedxpNPPsmFF17IkCFDaNWqFfHx8fj9frKysvj888/517/+xQMPPODIsaV79+689dZbHHfccaSlpe31uG3bfPDBB2GvS0T2TaFb6pTP52PKlCnccccdDB48mKioKLKysjj//POJj48nKiqKnj178sgjj7hq+ZzKJVVatWrFmDFjuOKKKxz5cj388MM5//zzueaaa7Asi44dO/L0009z/fXXM336dPx+PwUFBTzzzDNhr8+yLC644AJmzZrFKaecQuvWrcnPz2fz5s3cfffd1KtXD2MMq1ev5uijjw57i4DX62XcuHF0796dN954gw8++CC0PEZqaiqdO3dm+vTp9OvXz5HWCsuyuO6668jKysIYU2WwTklJYfr06TRt2jTs9TVr1oy+ffuydOnS0NhaqKg7MTGR+++/n5SUFFauXBn2iwKWZdGnTx/y8vJCPTwSEhL2CBDBYJDNmzczcOBARyfJsyyLzMxM7r77bvr378/dd9/Nxo0bHW3l9nq93HnnneTk5ITu+30PAYCtW7fSpk2bsHctB0Lh9cUXX+Rf//oX77//fuhCXnZ2Nm3atOHhhx9mwIABYe/aW+nwww/nsMMOq/Kxyu+Pylb5cKtXrx4vvPACzz//PNnZ2Vx11VWcfPLJNGnShJdffhnbtrnooou46aabHLmgl5CQwBNPPME999zD448/jt/vp3Pnzjz33HM0b94cqGjpfuSRR0IXgcKpefPmvPbaazz88MPcddddFBUVhY7RXq+XTp068eijjzJo0CBH3r+jjjqKs88+m0AgUOXjlmVx4YUXOvLeiUj1NHu5hIXf72ft2rX897//ZcuWLQA0bNiQrl270qVLF8dOnEpLS5k7dy4nnHBC2Fuxa6qsrIwVK1ZQWFhI586dqV+/PmvXruXjjz/Gtm1OPPFEunXr5shJfOWaw//+979ZtmwZSUlJnHLKKaFxtcaY0FIr4Z4k7/ds26akpAS/3w9UXAyKi4tz5YzlblGTNX0DgQDl5eXExcW5Ymzy71UuixIVFeV4N+5Kxhh2797NunXraNOmjSOTqNVUMBgkEAg4Pplk5dCZ0tJSbNsmKioqtFSTk3UFAgE8Hk9EHUOMMaHu2m44/gUCAQoLCzHGkJCQ4NjEc1Wp/LvLy8sjKyuL4uJifD4f6enppKen7zGkSkSkJhS6xXG//xN045eY6jt4TtdWuX/btkMn6b+vw7bt0CRbTq5zXl19lbOsR0dHO3KC7Pb3r3I+CGNM6P35fR2BQIBgMOhYL5r91ed0sHXz397v6wP2msjSDRdValKf1+t1ZHjN/j67wWAQv9/v6Gd3X/W54dhSWlpKMBgM9aApLCxk06ZNxMfH06RJk2ovRoaDbdsUFxfj9XpDF7R37txJVlYWaWlpNGjQwPGLKiKyJ30ixXFbt25l8uTJlJaWOl1KlXJycpg0adI+l+hw0ooVK5gyZUro5M9tPvjgA1577bWw77dy2ZS//e1v9O/fn+HDhzNnzpw9uuRlZWUxYsSIPbrZhlN+fj4PPvggp59+OkOGDOG9996jvLw89Pju3bsZOXIkmzdvDnttxhg2b97MjTfeyKmnnsqoUaNYsGDBHn9nq1ev5oorrnBkjLIxhoULFzJy5Ej69+/PxIkTWb9+/R4Xet57773QOuNO1Ldq1SpGjx7NqaeeyvXXX8+qVav2qO/LL7/kpptucqS+4uJinnjiCQYMGMB5553HG2+8sccxuKSkhCuvvJLVq1c7Ul95eTkvvfQSZ511FmeffTbTp08PtYpCxQWVcePG8f333ztSXyAQ4O233+bcc89l4MCBPP7446HZ1qEiFN1xxx188sknYa/NGMP69eu57rrrOPXUUxkzZgxLlizZ47O7ZMkSxowZU20X5bqub9u2bUyYMIFTTz2Vyy+/nPnz5+8xGegvv/zCpZdeSklJSdjrs22bmTNncsopp9CvXz+ee+451qxZw6BBg+jTpw+9evVi/Pjxe/w9hlNJSQlTp06lb9++nHHGGcydO5fPP/+cE088keOPP55jjz2Wxx9/3JHfrYhUT6FbHJeXl7dX2HCT4uJi/vWvfzny5V8TW7du5eOPP3Z8Bvjq/PjjjyxYsCDs+w0EAkyaNIlXX32V9u3bU1hYyCWXXMKDDz5IaWlpqCVq+fLljpycBINB7r//fp588snQ8m9jxoxh8uTJoZO5QCDA8uXLHQm1xcXFjBkzhs8//5zOnTuzYcMGLrjgAl588cXQ+1VUVMTKlSvD/rdnjGHDhg1ccsklbNmyhY4dOzJnzhwGDRrE119/HaonOzubdevWhbW2StnZ2YwcOZKVK1fSuXNn/vvf/3L22Wfz4YcfhsJPbm4ua9euDfv7Z9s2Tz31FPfffz+HHXYYcXFx3HTTTYwfPz4UHG3bZuXKlRQVFYW1Nqj4/b7++utMmjSJjIwM0tLS+Nvf/sbo0aPJzs4O9R5Ys2aNIxdDjTF88sknXH/99SQkJNC0aVMeffRRhg8fzqZNm0L1/fLLL+zatSvs9eXn5zNq1Ci+++47OnfuzKpVqzjnnHN48803Q8E2Pz9/r4tA4VJaWsrYsWP55JNP6NSpE1u2bGHo0KE8++yz+P1+jDGUlJSwYsWKsK/KAbBy5Ur++te/0rlzZwYNGsSTTz7JNddcQ+PGjZk1axbTpk3js88+45VXXgl7bcYY3nvvPZ566ilOO+00jjzySG6++WZuueUWzjvvPD744APGjh3LI488wg8//ODa8wKRPyNNpCZ1Ki8vj5deeik0lrYqWVlZ+3y8LhUXF/Piiy/uc1mSvLw8R5YtAdi8eTNvvvnmPr84165d61gr9w8//MCXX365z22++eYb2rVrF6aK/t+2bdv4z3/+w4svvsixxx6L3+/n/fffZ9KkSeTn53PbbbeFvabfq7zY9MQTT3DGGWcQDAaZO3cuN9xwA/n5+dx///2O1rdq1Sp++ukn3n//fdq0aUNpaSkvvvgid911FwUFBVx99dWO1vfpp5/SsGFD3nnnHZKTk8nJyeHee+/l8ssv5/HHH6d///6O1jdv3jxs2+bdd98lMzOT/Px8Hn30Ua677joKCwsZPHiwY7UVFxfz5ptvMnXqVC688EKMMXz77beMHTuWMWPG8Nhjjzk6B4Pf7+fVV19lwoQJXHvttViWxdKlSxk7diyXX345Tz/9NOnp6Y7VZ9s2r7zyCpdddhl33HEHHo+Hn376iXHjxjFixAiee+45WrZs6Vh9ixcvJisriw8//JBmzZpRVFTEM888w8SJEyksLGTkyJGO1Qbw008/8eOPPzJr1iw6duxIWVkZr776Kvfccw8FBQWMHTvW0fq+/vprunTpwmOPPUZMTAwNGzbk3nvv5YUXXghNnpeTk8NHH33EqFGjwjp8wLZtPv74Y6644gpuu+02jDFcffXV/PLLL9xyyy3Ex8fTs2dPfvzxRz7//HN69eoVttpEZN8UuqVO5eTkcOedd5KWllbteqClpaWOdYMqKirinnvuISYmptolt/x+v2NL/Pz6669MnjyZ5s2b7zW7cKXCwkLHllv7+uuvueOOO2jZsmW148eys7MdCd27du0iISGBLl264PF4iImJ4fzzz6dhw4ZcddVVFBcXc+WVV4a9rkqVLXRHHHFEaEKm/v3788orrzBq1CjGjh3Lrbfe6lh927dvp0mTJqHfbXx8PKNHj6Zhw4bcdNNNFBcXc/zxxztW3+bNm+nevTspKSlYlkVaWhpTpkwhMzOTa665hocfftjRIReVLfCZmZmhdcQnTZpEZmYmt9xyC6WlpY6skQwVx4zS0lKOOeaY0HjoPn368PrrrzNq1ChGjRrFgw8+6EhtUPGdkJubG5qQESo+J6+++ipXXXUVl1xyiaPrEPv9fnbs2MHFF18cWjWiffv2vPTSS4wdO5YRI0bw7LPPOlbftm3baNGiBU2bNg2tNjB27FgaNGjA5MmTKS4upmPHjo7Vl5WVRWZmJm3atMHj8RAXF8dll11Gw4YNGTduHMXFxZxxxhmO1ZeTk0PLli1D48nbtm1LZmZm6LMM0KlTJ15//fXQvALhYts2+fn5tGvXLjQOvm3btgSDwdCEtF6vl44dO7Jx48ZqV8YQkfBT6JY6lZSURHp6Ovfccw8DBgyocptVq1Zx2WWXhbmyCrGxsTRo0IDLL7+cSy65pMptNm/ezLnnnhvmyiqkpaVRv359nn32Wbp3717lNnPnzuWhhx4Kb2G/adq0KU2bNuWjjz6qdj3VBx980JEuoCkpKaGT98qlUzweD3369OGll17i8ssv5+eff3bsgkpiYiLGGHbu3EmjRo1CJ1Ddu3dnxowZoTXGCwsLHakvLS2NnJwcioqKSE1NBSpO5s455xwSEhK49tpr+e677xzp/gmQkZHB2rVrCQaDoQmNYmNjufHGG0lISGD8+PF06NDBkXV+K+vbvn17aB3xynW7R40aRUJCAnfccQddunRxpPtnfHw8Pp+P7du3h5aDsyyL9u3bM2PGDEaNGsUVV1zh2FwHMTExJCQksHXr1lBosCyLZs2a8cILLzBmzBguvvji0BKA4RYVFUVqaiqbN2/eo77MzEyeeuopbrzxRkaMGOFY2ElPT2fnzp2UlpaGJgGLiorioosuIj4+nptuusmxvz2oOLbk5+eH1oeHimPzgAEDiI+P5+qrr2bRokWOXYxPT09n2bJl2LaN1+ulUaNGnHXWWXuE65KSEqKjo8M+iZ/H4yE1NZXs7OzQfYcffjjp6el7/L0VFRURHx+vwC3iIhrTLXUqNTWV9u3b88svv5CYmEhSUtJet+TkZOrXr+/YeqHdunXj559/3md9aWlpjswE2qRJExo1asTmzZurrS8lJSUUisKtS5cuobXCq6otMTGRevXqObIcW8OGDUlPT2fOnDl7zaJ+5JFH8sorr7B9+3bHQm1qaiqtW7fmww8/3ON+y7Lo0KEDM2bMoLy83JExoQCtW7fG7/ezYMGCPd6/yhb55557jhUrVjg2F8NRRx3F0qVL95pkLjo6mjFjxjBp0iTHJtmCihPhDRs2sGbNmj3uj4qKYtiwYTzwwAOOjblMSEiga9euvP/++3t9Npo3b86LL75IYmIiW7duDXttUPE7PProo3nvvff2uKhjWRYNGjTgmWeeoXXr1o6N1/d6vRx77LG8//77e1y0syyLevXq8fe//53evXuzcuVKR+pr3749eXl5LFmyZK/P7tlnn82TTz7JkiVLHAu1zZs3x+PxMH/+/L3q69evHy+88AJr1qxx7IJop06dyM7ODs1n0K5dOyZPnhwK2JXDMdq1a1dtD7S64vF4OOKII/YYj9+/f/89hgyUl5ezaNEiOnXqFNbaRGTftGSY1CljDD/99BMej4fWrVtXGaz9fj+5ubmkp6eHPdhWTshUUlJChw4dqqwvGAyya9cu0tLSwn5V27ZtVqxYQb169WjSpEmV9ZWWllJYWEhaWlrYL1yUlZWxbNky2rZtG2pN/j1jDIWFhdi2XeXjdckYw3//+1+CwSDHHHPMXn9blTP8LliwgLPPPjvsa8UbY1i2bBl5eXn06dOnyvq2bdvGF198wcCBA8P+/tm2zddff039+vXp0qXLXn9bxhiWL1/OTz/9xKBBg8K+LFJJSQlz586le/fuNGnSZK/Hg8EgX331FZZlceKJJ4a1Nqg4rs2dO5e2bduGJsr7Pdu2+f7779m9ezennXZaWD+7xhjWrl3L5s2b6du3716/u8oeGJ999hmnnnoqGRkZYautcv8bNmxg9erV9OvXb68l34wx5Ofn8/HHH9OnTx+aNm0a1vqgogv3okWL6Nev317DBCrXw/7444/p1q0bbdu2DWttwWCQL774giZNmtC+ffsqP7uLFy9m8+bNnHnmmWH/3rVtm/nz55OYmEi3bt2qrG/VqlWsXLmSs88+O9SFP1z8fj85OTmkp6dX+Z0fDAb55ptvaNiwYaibdzgVFxdTXFxc7Xd+SUkJ//nPfzj66KPD/tkVkeopdIuIiIiIiIjUEXUvFxEREREREakjCt0iIiIiIiIidUShW0RERERERKSOKHSLiMghxbZtAoFAtTfbttm0aRN///vfWbRoUWgW4OLiYp599lnef/99R9f4FhERkUOLJlITEZFDyqeffsodd9xR7eMXXnghXbp0oX///jz44IOMHz8ey7LIysqie/fuHHPMMbz99tthnzVZREREDk3hXeNFRESkju3atYvvvvuOzp07061bt70eT0tLIykpiR49epCZmelAhSIiIvJnotAtIiKHpLPPPpu77rprr/sr17adN29elevwioiIiNQmhW4RETkkWZaFx+MJhezfy83N5ccff6RVq1Y0bdp0v89VXl7OkiVL+Oqrr9i+fTtpaWn07duXo446iujo6NB2xhh27NjB3LlzWbFiBaWlpaSlpdG5c2d69+5NWlparb5GERERcT+FbhER+dNZvHgxp512Gg888ADjxo3b57b5+fncfvvtvPDCC/h8PtLS0sjLy2PKlClcffXV3HnnncTFxWGMYfXq1QwfPpyVK1eSmZlJfHw8+fn55OXlce+99+53XyIiInLoUegWEZFD0o4dO/jxxx/3uC86Opo2bdpgjMG2bfY3l2gwGOThhx/m6aef5vLLL+f6668nIyOD3Nxcpk6dyuOPP06nTp24+OKLsW2bxx57jDVr1vDEE08wcOBAoqOjKS0tZdmyZcTFxdXlyxURERGXUugWEZFD0ksvvcTrr7++x31Nmzblyy+/rPFzbNq0iWeffZY+ffpw//33k5CQgGVZpKamMmXKFL799luee+45hgwZgtfrZe3atTRu3Jizzz6b+vXrh7q2N2zYsFZfm4iIiEQOhW4RETkkDRo0iIsuumiP++Li4khOTq7xcyxcuJAdO3YwatQo8vPzyc/PDz1mjKFDhw588803ZGdn06RJE1q3bs28efO4//77GTFiBC1atCAxMRGgyrHlIiIicuhT6BYRkUNS+/btOffcc/9Q2N2wYQO2bfPwww/zj3/8Y6/Hi4qKiI2NpaioCI/Hw/jx41mxYgWPPvoo//znP2nZsiW9evXioosuonfv3kRF6WtXRETkz0bf/iIiIvtxzjnn0KtXryof8/l8NGjQAMuy6NChAx9++CHz5s3jyy+/5Ntvv+W1117jtddeC0285vF4wly9iIiIOEmhW0REpBotWrTA4/HQvn17rrnmmv22mleO9x44cCADBgygtLSUBQsWMGzYMJ544gmGDRtGampqeIoXERERV9DldhERkWocffTRNGnShHfffZesrKy9Zjs3xlBeXo4xBmMMpaWloW0syyIuLo5jjz2WVq1aUVBQQFlZmRMvQ0RERByklm4REZFqNGnShBtvvJGJEycyYsQIbrzxRtq2bYtlWezYsYMvv/yS3Nxc7rnnHoLBIKNHj+aII47g+OOPp379+vj9fj799FOWLl1K37591cotIiLyJ6TQLSIih5TExERatWpF/fr1q93G6/USHx+/x8RmlS3TMTExofs8Hg+jR4/G4/Hw8MMPc95554WWDSspKSEuLo7LLrss1O08Ozub2267DaiYKT0YDFJWVkbPnj25//77iY6OrqNXLSIiIm5lmf/tKyciIhLBysrKyM/PJz4+nvj4+CrHYRcXF7NlyxbS09NJTU3FsiwCgQAbN24kNjaWRo0a7fFztm2zbds2Fi1axObNm/F4PDRp0oROnTpx2GGHhcJ7fn4+69atY82aNeTk5BATE0P79u3p3r17KKyLiIjIn4tCt4iIiIiIiEgd0URqIiIiIiIiInVEoVtERERERESkjih0i4iIiIiIiNQRhW4RERERERGROqLQLSIiIiIiIlJHFLpFRERERERE6ohCt4iIiIiIiEgdUegWERERERERqSMK3SIiIiIiIiJ1RKFbREREREREpI4odIuIiIiIiIjUEYVuERERERERkTqi0C0iIiIiIiJSRxS6RUREREREROqIQreIiIiIiIhIHVHoFhEREREREakjCt0iIiIiIiIidUShW0RERERERKSOKHSLiIiIiIiI1BGFbhEREREREZE6otAtIiIiIiIiUkcUukVERERERETqiEK3iIiIiIiISB1R6BYRERERERGpIwrdIiIiIiIiInVEoVtERERERESkjih0i4iIiIiIiNQRhW4RERERERGROqLQLSIiIiIiIlJHFLpFRERERERE6ohCt4iIiIiIiEgdUegWERERERERqSMK3SIiIiIiIiJ1RKFbREREREREpI4odIuIiIiIiIjUEYVuERERERERkTqi0C0iIiIiIiJSRxS6RUREREREROqIQreIiIiIiIhIHVHoFhEREREREakjCt0iIiIiIiIidUShW0RERERERKSOKHSLiIiIiIiI1BGFbhEREREREZE68n/tXNnthyyq6AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!ls {dest_path}/raw_traces/*.ecsv | trace_pearsons --pipe -O {dest_path}\n",
    "\n",
    "# Display the correlation matrix\n",
    "img = mpimg.imread(f\"{dest_path}/trace_correlation_matrix.png\")\n",
    "fig, ax = plt.subplots(figsize=(10, 10))\n",
    "ax.imshow(img)\n",
    "ax.axis('off')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-6",
   "metadata": {},
   "source": [
    "## Step 3: Remove poorly-correlated ROIs\n",
    "\n",
    "For each ROI, we compute its **mean Pearson correlation** with all other ROIs. ROIs below the threshold are removed from the working folder before merging.\n",
    "\n",
    "A threshold of **0.70** is conservative: it removes only clear outliers while preserving the vast majority of the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cell-7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Kept    Trace_3D_barcode_mask-mask0_ROI-16_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.457)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-17_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.140)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-18_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.475)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-19_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.377)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-20_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.504)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-21_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.534)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-22_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.432)\n",
      "Removed Trace_3D_barcode_mask-mask0_ROI-24_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = nan)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-25_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.347)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-26_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.393)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-27_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.106)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-28_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.414)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-29_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.150)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-30_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.452)\n",
      "Kept    Trace_3D_barcode_mask-mask0_ROI-31_Pdx1_filtered_Pdx1.ecsv  (mean Pearson = 0.494)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_85188/2373448959.py:7: RuntimeWarning: Mean of empty slice\n",
      "  mean_corr = np.nanmean(corr, axis=1)\n"
     ]
    }
   ],
   "source": [
    "# Load the correlation matrix saved by trace_pearsons\n",
    "corr = np.load(f\"{dest_path}/trace_correlation_matrix.npy\")\n",
    "traces = sorted(Path(f\"{dest_path}/raw_traces\").glob(\"*.ecsv\"))\n",
    "\n",
    "# Mean correlation per ROI (exclude self-correlation on the diagonal)\n",
    "np.fill_diagonal(corr, np.nan)\n",
    "mean_corr = np.nanmean(corr, axis=1)\n",
    "\n",
    "# Remove ROIs below threshold\n",
    "threshold = 0.10\n",
    "for trace, mc in zip(traces, mean_corr):\n",
    "    if mc < threshold or np.isnan(mc):\n",
    "        trace.unlink()\n",
    "        print(f\"Removed {trace.name}  (mean Pearson = {mc:.3f})\")\n",
    "    else:\n",
    "        print(f\"Kept    {trace.name}  (mean Pearson = {mc:.3f})\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-8",
   "metadata": {},
   "source": [
    "## Step 4: Re-run Pearson to verify improvement\n",
    "\n",
    "After removing the outlier ROIs, the correlation matrix should show higher overall values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cell-9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analyzing 12 trace files...\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-16_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-18_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-19_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-20_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-21_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-22_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-24_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-25_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-27_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-29_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-30_Pdx1_filtered_Pdx1.ecsv\n",
      "Processing Trace_3D_barcode_mask-mask0_ROI-31_Pdx1_filtered_Pdx1.ecsv\n",
      "$ Saved correlation matrix as /home/devos/Documents/data_to_compare_pdx1/PDX1/trace_correlation_matrix.png\n",
      "$ Saved correlation matrix data in NPY format: /home/devos/Documents/data_to_compare_pdx1/PDX1/trace_correlation_matrix.npy\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!ls {dest_path}/raw_traces/*.ecsv | trace_pearsons --pipe -O {dest_path}\n",
    "\n",
    "# Display the updated correlation matrix\n",
    "img = mpimg.imread(f\"{dest_path}/trace_correlation_matrix.png\")\n",
    "fig, ax = plt.subplots(figsize=(10, 10))\n",
    "ax.imshow(img)\n",
    "ax.axis('off')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-10",
   "metadata": {},
   "source": [
    "## Step 5: Merge trace files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cell-11",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of trace files to merge: 12\n",
      " $ Merged trace file will contain 31407 traces\n",
      "Read and accumulated 12 trace files\n",
      "$ Saving output table as /home/devos/Documents/data_to_compare_pdx1/PDX1/merged_traces.ecsv ...\n",
      "Finished execution\n"
     ]
    }
   ],
   "source": [
    "!ls {dest_path}/raw_traces/*.ecsv | trace_merge -F {dest_path} -N merged_traces.ecsv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-12",
   "metadata": {},
   "source": [
    "## Step 6: Compute basic statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "cell-13",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "$ Importing table from pyHiM format\n",
      "Successfully loaded trace table: /home/devos/Documents/data_to_compare_pdx1/PDX1//merged_traces.ecsv\n",
      "Statistics for /home/devos/Documents/data_to_compare_pdx1/PDX1//merged_traces.ecsv:\n",
      "- Number of unique ROIs: 12\n",
      "- Number of unique chromatin traces: 3388\n",
      "- Number of unique barcodes: 23\n"
     ]
    }
   ],
   "source": [
    "!trace_stats --input {dest_path}/merged_traces.ecsv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-14",
   "metadata": {},
   "source": [
    "## Next steps\n",
    "\n",
    "The merged trace file is ready for downstream analysis.\n",
    "\n",
    "Continue with **Tutorial 2 — Quality Control** to:\n",
    "- Generate detailed quality metrics with `trace_analyzer`\n",
    "- Interpret barcode detection, neighbor distances, and barcode frequency plots\n",
    "- Decide on filtering thresholds for Tutorial 3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-15",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "| Step | Script | Output |\n",
    "|------|--------|--------|\n",
    "| Collect | `collect_files` | `raw_traces/` (one .ecsv per ROI) |\n",
    "| Correlations | `trace_pearsons` | `trace_correlation_matrix.png` + `.npy` |\n",
    "| Filter ROIs | Python (numpy) | removed outlier files from `raw_traces/` |\n",
    "| Merge | `trace_merge` | `merged_traces.ecsv` |\n",
    "| Statistics | `trace_stats` | stdout |\n",
    "\n",
    "**Output location:** `data/output/`"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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