02_workflow_compositionspace.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "de8493fd-f3ae-4689-a219-03b035557777",
   "metadata": {},
   "source": [
    "<font style=\"font-family:roboto;color:#455e6c;font-size:18px;text-align:justify\"> <b> Analyze data with CompositionSpace <br> </b> </font>\n",
    "CompositionSpace discretizes the reconstructed volume into a set of voxelized regions of similar composition using different machine learning methods. These are chained into a workflow that is instructed with a single set of parameters based on which automated routines probe the parameter space and decide which number of compositions or objects are best to assume present in the reconstructed volume. A regular grid of cubic voxels is used. Local regions where neighboring voxels were assigned dissimilar composition values can be used as a support to run additional algorithms (here not shown) for creating proxies of the interface network if these are present in the reconstructed volume. Further details about CompositionSpace were summarized by A. Saxena et al. [here](https://arxiv.org/pdf/2304.08761). Stored in an HDF5 file as groups, fields, and attributes, the [results](https://www.github.com/FAIRmat-NFDI/nexus_definitions/NXapm_compositionspace_results.nxdl.xml) and the [configuration](https://www.github.com/FAIRmat-NFDI/nexus_definitions/blob/fairmat/contributed_definitions/NXapm_compositionspace_config.nxdl.xml) are reported according to the semantics of the [NeXus](https://www.github.com/FAIRmat-NFDI/nexus_definitions) data model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2e3a3938-f943-4752-ab38-f49d745efca6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyiron_workflow import Workflow\n",
    "import nodes.compositionspace as ncp\n",
    "import nodes.visualize as nvis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c6a5202f-df69-4e2a-a4b7-dea74622208a",
   "metadata": {},
   "outputs": [],
   "source": [
    "config_file_path = 'experiment_params.yaml'\n",
    "results_file_path = 'CompositionSpace.Results.1.nxs'\n",
    "recon_file_path = 'Si.pos'\n",
    "range_file_path = 'Si.RRNG'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1e6371d2-9f4b-46cb-9bbd-da7d483a8dc5",
   "metadata": {},
   "outputs": [],
   "source": [
    "wf = Workflow(\"compspace\")\n",
    "wf.voxel = ncp.compositionspace_voxelize(\n",
    "    config_file_path=config_file_path,\n",
    "    results_file_path=results_file_path,\n",
    "    recon_file_path=recon_file_path,\n",
    "    range_file_path=range_file_path)\n",
    "wf.autophase = ncp.compositionspace_autophase(\n",
    "    config_file_path=config_file_path,\n",
    "    results_file_path=wf.voxel)\n",
    "wf.segmentation = ncp.compositionspace_segmentation(\n",
    "    config_file_path=config_file_path,\n",
    "    results_file_path=wf.autophase)\n",
    "wf.cluster = ncp.compositionspace_clustering(\n",
    "    config_file_path=config_file_path,\n",
    "    results_file_path=wf.segmentation)\n",
    "wf.xdmf = ncp.generate_xdmf(wf.cluster)\n",
    "wf.results = nvis.visualize_hdf(wf.cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "801f0781-4336-42db-808f-91fc5dc9d31b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 25 ranging definitions, performed reduction to 25 unique ones\n",
      "Si.RRNG parsed successfully\n",
      "shape (945211,)\n",
      "dim 0\n",
      "\tnp.min(xyz[:, axis_id]) -20.433578491210938 >>>> -23.0\n",
      "\tnp.max(xyz[:, axis_id]) 19.706375122070312 >>>> 22.0\n",
      "\tself.aabb3d axis_id 0, [-23.  22.], extent 45\n",
      "dim 1\n",
      "\tnp.min(xyz[:, axis_id]) -17.857210159301758 >>>> -20.0\n",
      "\tnp.max(xyz[:, axis_id]) 21.282995223999023 >>>> 24.0\n",
      "\tself.aabb3d axis_id 1, [-20.  24.], extent 44\n",
      "dim 2\n",
      "\tnp.min(xyz[:, axis_id]) -75.08065032958984 >>>> -78.0\n",
      "\tnp.max(xyz[:, axis_id]) -0.020034153014421463 >>>> 2.0\n",
      "\tself.aabb3d axis_id 2, [-78.   2.], extent 80\n",
      "np.max(self.voxel_identifier) 153609\n",
      "np.prod(self.extent) 158400\n",
      "ion1, ('Si ++', 1, array([13.8745, 14.241 ])):\n",
      "\tSi\n",
      "\t1\n",
      "\t{'Si': 1}\n",
      "ion2, ('Si +', 2, array([27.856, 28.595])):\n",
      "\tSi\n",
      "\t1\n",
      "\t{'Si': 1}\n",
      "ion3, ('Si +', 3, array([28.826, 29.255])):\n",
      "\tSi\n",
      "\t1\n",
      "\t{'Si': 1}\n",
      "ion4, ('Si +', 4, array([29.783, 30.252])):\n",
      "\tSi\n",
      "\t1\n",
      "\t{'Si': 1}\n",
      "ion5, ('Si ++', 5, array([14.407, 14.643])):\n",
      "\tSi\n",
      "\t1\n",
      "\t{'Si': 1}\n",
      "ion6, ('Si ++', 6, array([14.912, 15.171])):\n",
      "\tSi\n",
      "\t1\n",
      "\t{'Si': 1}\n",
      "ion7, ('Cr +', 7, array([51.699, 54.243])):\n",
      "\tCr\n",
      "\t1\n",
      "\t{'Cr': 1}\n",
      "ion8, ('Cr +', 8, array([49.612, 50.526])):\n",
      "\tCr\n",
      "\t1\n",
      "\t{'Cr': 1}\n",
      "ion9, ('Cr ++', 9, array([25.771, 27.211])):\n",
      "\tCr\n",
      "\t1\n",
      "\t{'Cr': 1}\n",
      "ion10, ('Cr ++', 10, array([24.895, 25.445])):\n",
      "\tCr\n",
      "\t1\n",
      "\t{'Cr': 1}\n",
      "ion11, ('Cu +', 11, array([62.567, 63.496])):\n",
      "\tCu\n",
      "\t1\n",
      "\t{'Cu': 1}\n",
      "ion12, ('Cu +', 12, array([64.619, 65.548])):\n",
      "\tCu\n",
      "\t1\n",
      "\t{'Cu': 1}\n",
      "ion13, ('C +', 13, array([11.866, 12.198])):\n",
      "\tC\n",
      "\t1\n",
      "\t{'C': 1}\n",
      "ion14, ('C ++', 14, array([5.896, 6.193])):\n",
      "\tC\n",
      "\t1\n",
      "\t{'C': 1}\n",
      "ion15, ('O +', 15, array([15.858, 16.48 ])):\n",
      "\tO\n",
      "\t1\n",
      "\t{'O': 1}\n",
      "ion16, ('O +', 16, array([17.838, 18.304])):\n",
      "\tO\n",
      "\t1\n",
      "\t{'O': 1}\n",
      "ion17, ('Cr O +', 17, array([67.622, 69.574])):\n",
      "\tCr O\n",
      "\t2\n",
      "\t{'Cr': 1, 'O': 1}\n",
      "ion18, ('Cr O +', 18, array([69.781, 70.156])):\n",
      "\tCr O\n",
      "\t2\n",
      "\t{'Cr': 1, 'O': 1}\n",
      "ion19, ('Cr O +', 19, array([65.76 , 66.264])):\n",
      "\tCr O\n",
      "\t2\n",
      "\t{'Cr': 1, 'O': 1}\n",
      "ion20, ('Cr O ++', 20, array([32.892, 33.275])):\n",
      "\tCr O\n",
      "\t2\n",
      "\t{'Cr': 1, 'O': 1}\n",
      "ion21, ('Cr O ++', 21, array([33.898, 34.802])):\n",
      "\tCr O\n",
      "\t2\n",
      "\t{'Cr': 1, 'O': 1}\n",
      "ion22, ('Cr O ++', 22, array([34.917, 35.231])):\n",
      "\tCr O\n",
      "\t2\n",
      "\t{'Cr': 1, 'O': 1}\n",
      "ion23, ('Cr O O +', 23, array([83.595, 86.555])):\n",
      "\tCr O O\n",
      "\t2\n",
      "\t{'Cr': 1, 'O': 2}\n",
      "ion24, ('Cr O O ++', 24, array([41.869, 43.181])):\n",
      "\tCr O O\n",
      "\t2\n",
      "\t{'Cr': 1, 'O': 2}\n",
      "ion25, ('Cr Cr O ++', 25, array([57.819, 61.159])):\n",
      "\tCr Cr O\n",
      "\t2\n",
      "\t{'Cr': 2, 'O': 1}\n",
      "/entry1/voxelization/element1, C\n",
      "symbol C, idx 0, np.sum(elem_cnts[symbol]) 706, np.sum(total_cnts) 706\n",
      "/entry1/voxelization/element2, Cr\n",
      "symbol Cr, idx 1, np.sum(elem_cnts[symbol]) 174852, np.sum(total_cnts) 175558\n",
      "/entry1/voxelization/element3, Cu\n",
      "symbol Cu, idx 2, np.sum(elem_cnts[symbol]) 683, np.sum(total_cnts) 176241\n",
      "/entry1/voxelization/element4, O\n",
      "symbol O, idx 3, np.sum(elem_cnts[symbol]) 89981, np.sum(total_cnts) 266222\n",
      "/entry1/voxelization/element5, Si\n",
      "symbol Si, idx 4, np.sum(elem_cnts[symbol]) 785076, np.sum(total_cnts) 1051298\n",
      "n_ions 945211\n",
      "Composition matrix has 5 elements\n",
      "Populating composition table for element1\n",
      "Populating composition table for element2\n",
      "Populating composition table for element3\n",
      "Populating composition table for element4\n",
      "Populating composition table for element5\n",
      "Composition matrix has 5 elements\n",
      "Populating composition table for element1\n",
      "Populating composition table for element2\n",
      "Populating composition table for element3\n",
      "Populating composition table for element4\n",
      "Populating composition table for element5\n",
      "Composition matrix has 5 elements\n",
      "Populating composition table for element1\n",
      "Populating composition table for element2\n",
      "Populating composition table for element3\n",
      "Populating composition table for element4\n",
      "Populating composition table for element5\n",
      "Using results with automated phase assignment\n",
      "np.shape(X_train) (158400, 2)\n",
      "GaussianMixture ML analysis with n_cluster 1\n",
      "Using results with automated phase assignment\n",
      "np.shape(X_train) (158400, 2)\n",
      "GaussianMixture ML analysis with n_cluster 2\n",
      "Using results with automated phase assignment\n",
      "np.shape(X_train) (158400, 2)\n",
      "GaussianMixture ML analysis with n_cluster 3\n",
      "Using results with automated phase assignment\n",
      "np.shape(X_train) (158400, 2)\n",
      "GaussianMixture ML analysis with n_cluster 4\n",
      "Using results with automated phase assignment\n",
      "np.shape(X_train) (158400, 2)\n",
      "GaussianMixture ML analysis with n_cluster 5\n",
      "DBScan configuration: eps 3 nm, min_samples 5\n",
      "['cluster_analysis0', 'cluster_analysis1', 'cluster_analysis2', 'cluster_analysis3', 'cluster_analysis4', 'result', 'sequence_index']\n",
      "cluster_analysis0\n",
      "ic_run_id 0 >>>>\n",
      "np.shape(all_vxl_pos) (158400, 3) list(set(phase_identifier) [0]\n",
      "\tLoop 0\n",
      "\tnp.shape(trg_vxl_pos) (158400, 3)\n",
      "\tnp.shape(trg_vxl_idx) (158400,)\n",
      "\t1\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[0]\n",
      "cluster_analysis1\n",
      "ic_run_id 1 >>>>\n",
      "np.shape(all_vxl_pos) (158400, 3) list(set(phase_identifier) [0, 1]\n",
      "\tLoop 0\n",
      "\tnp.shape(trg_vxl_pos) (110080, 3)\n",
      "\tnp.shape(trg_vxl_idx) (110080,)\n",
      "\t1\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[0]\n",
      "\tLoop 1\n",
      "\tnp.shape(trg_vxl_pos) (48320, 3)\n",
      "\tnp.shape(trg_vxl_idx) (48320,)\n",
      "\t1\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[0]\n",
      "cluster_analysis2\n",
      "ic_run_id 2 >>>>\n",
      "np.shape(all_vxl_pos) (158400, 3) list(set(phase_identifier) [0, 1, 2]\n",
      "\tLoop 0\n",
      "\tnp.shape(trg_vxl_pos) (110080, 3)\n",
      "\tnp.shape(trg_vxl_idx) (110080,)\n",
      "\t1\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[0]\n",
      "\tLoop 1\n",
      "\tnp.shape(trg_vxl_pos) (39046, 3)\n",
      "\tnp.shape(trg_vxl_idx) (39046,)\n",
      "\t2\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[-1  0]\n",
      "\tLoop 2\n",
      "\tnp.shape(trg_vxl_pos) (9274, 3)\n",
      "\tnp.shape(trg_vxl_idx) (9274,)\n",
      "\t2\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[-1  0]\n",
      "cluster_analysis3\n",
      "ic_run_id 3 >>>>\n",
      "np.shape(all_vxl_pos) (158400, 3) list(set(phase_identifier) [0, 1, 2, 3]\n",
      "\tLoop 0\n",
      "\tnp.shape(trg_vxl_pos) (110080, 3)\n",
      "\tnp.shape(trg_vxl_idx) (110080,)\n",
      "\t1\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[0]\n",
      "\tLoop 1\n",
      "\tnp.shape(trg_vxl_pos) (39046, 3)\n",
      "\tnp.shape(trg_vxl_idx) (39046,)\n",
      "\t2\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[-1  0]\n",
      "\tLoop 2\n",
      "\tnp.shape(trg_vxl_pos) (4339, 3)\n",
      "\tnp.shape(trg_vxl_idx) (4339,)\n",
      "\t2\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[-1  0]\n",
      "\tLoop 3\n",
      "\tnp.shape(trg_vxl_pos) (4935, 3)\n",
      "\tnp.shape(trg_vxl_idx) (4935,)\n",
      "\t2\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[-1  0]\n",
      "cluster_analysis4\n",
      "ic_run_id 4 >>>>\n",
      "np.shape(all_vxl_pos) (158400, 3) list(set(phase_identifier) [0, 1, 2, 3, 4]\n",
      "\tLoop 0\n",
      "\tnp.shape(trg_vxl_pos) (110080, 3)\n",
      "\tnp.shape(trg_vxl_idx) (110080,)\n",
      "\t1\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[0]\n",
      "\tLoop 1\n",
      "\tnp.shape(trg_vxl_pos) (39046, 3)\n",
      "\tnp.shape(trg_vxl_idx) (39046,)\n",
      "\t2\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[-1  0]\n",
      "\tLoop 2\n",
      "\tnp.shape(trg_vxl_pos) (1183, 3)\n",
      "\tnp.shape(trg_vxl_idx) (1183,)\n",
      "\t5\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[-1  0  1  2  3]\n",
      "\tLoop 3\n",
      "\tnp.shape(trg_vxl_pos) (4194, 3)\n",
      "\tnp.shape(trg_vxl_idx) (4194,)\n",
      "\t2\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[-1  0]\n",
      "\tLoop 4\n",
      "\tnp.shape(trg_vxl_pos) (3897, 3)\n",
      "\tnp.shape(trg_vxl_idx) (3897,)\n",
      "\t2\n",
      "\ttype(db.labels_) <class 'numpy.ndarray'> dtype int64\n",
      "[-1  0]\n",
      "result\n",
      "sequence_index\n",
      "Inspecting CompositionSpace.Results.1.nxs...\n",
      "Found dimensionality, uint64, (), 3\n",
      "Found extent, uint64, (3,), [45 44 80]\n",
      "Found origin, float64, (3,), [-23. -20. -78.]\n",
      "Found cell_dimensions, float64, (3,), [1. 1. 1.]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'xdmf__result_file': 'CompositionSpace.Results.1.nxs.xdmf',\n",
       " 'results__visualize_hdf': <jupyterlab_h5web.widget.H5Web object>}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wf.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad11d55d-51ec-4bb6-a945-342d9777da5e",
   "metadata": {},
   "source": [
    "<font style=\"font-family:roboto;color:#455e6c;font-size:18px;text-align:justify\"></font>\n",
    "The resulting NeXus/HDF5 file contains specific groups and fields which store the geometry and scalar field data.<br>\n",
    "In combination with a descriptive XDMF file this can be used directly to visualize the results e.g. with Paraview.<br>\n",
    "The figure shows the top region that is enriched in Chromium as typically are the silicon holder<br>\n",
    "onto which APT specimens are typically mounted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4761f1df-8216-4a3c-9e92-2d5fca059795",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PLwj6aNWfWiFhMMR0fCH9dxpqbHVKnEQOYbUKC9TMbZ873yRcVL81f5WUkkYnF8jlutYg6/DKaIofvzzCP/7VL0Ip4JGHfgI/9zP345Gav2cEQRAEQVw7qCopccOw0GsQxc3bH3n4bnzygQ/g1ltvwaGdLg4f1I7Y2fN9nLvQx0uvXMJvfPGr8zsZhEdRn7mEub55y1AmdiocQ1MLCC5cdDfevfycSshea8bYnDC07NjZqyneigrtjAevIywI3zS6dzWun6kiKuMWepvvqx5riWqrrrcF7yr1qBz1T0BBodU+CMtZg5IKSknj/TBXGXfZYxZUsgWAz3/uHnz6U/fi+NGN9Pes03FWOhZBEARBEMtDjiFxQ1AU+mkqEPLlR/8Ojz72DLqbd9Q/gGGx7ra24ba2IWWA0O9jPDyTvrcgFvezBUWZYwjteBWRhnQW5QkuWzBFAUEwf62zorDTvVkXZcmPU1I5tKjaqlcjfHM6vggunOrQzfg4xiIyWUFfkaNowjS2sEq8yCaFhnKEwRBB7KD2/QEsew1eewcAQxRNzU7kivelyXX91tMX8eR3/mZu7p01Z87F/6m/91HKUSQIgiCIawQJQ+KGIA39zCxyy9ogcNHe1+NzbiMMBnOvjQangMGpWfhm08V3xfZlIsi0WOfCNY/fNIw1s1/ZtZ4ThdnjXIV+jVn31na6cLwtLfJMhVWKishkQzdRvF+KybH1i4U5AIhVXOQS8jmiYTDAYHcQhwOvwXa64MIBY2Jx54xYHw5OACpXpXWJzylSiwL4wtmXcdrfxfM/1u7lH/3pV/Hx++7ET37+kziwuYbN9RY21ltYX/ewud6C562Wl0sQBEEQxAwShsTbltNn9nDi5Gk8/+MzutcgUFgttIimeVUAKsMJTWIgmO4Chry+VZgXQYutMopI3aomi/zkvEv2MV3rus5do3mY3s7l0QV+H4HfLy1QU1pEpk5OpGE+fqaC6tzm3ALnlnm8Kpb4DCx7Dba7XmvcMBymeZtJAaXW2rHSwkm2002L0WRZaCnC9Ph5nvzW8/jBC8Vje56FjfUWNnotbGy0sLneQtsd4GMffU/tfGGCIAiCIDQkDIm3BefO9/F7f/gUXjt5GafP7OL0We1Q9S8/Bykl1roHINGpXf3RuN0yYYPx67a7XphrVbtfYdkc8sVGFkRQ3CrD6aLVPgTb6VU7YXVZwdFbSoAviUkYReF4fw7QoI+jUSib2musSFkPyiYOZb4qahgMMRmeRbt7k+HA88VoomiKKBhiPDxT3FKkIZNJiLOTPs6emz102b30LP7g//mPAHS+8Cc+fiduPr6DY8eOUB4jQRAEQZRAwpB4W/Cbv/M4/urRH82VpQzDIaTUuWiD/hsA9KLWdtfhtQ7Ctrtx/0BzD8F8kZO5noBNKl0COlx07fhCoY9a4iib81d0zNxrJuEhIx+cu/XaKRTNgQHjwek0R1G33OhVNpMvFKINeijWoswtjMK0Mbxx94KCNkW5jHWOV4ap5QTnNtz2IfOONe63YV+HeTreFuxMiK7pfphzKGsctygkuCxMOO+oCuGmAjVtKZJxHU33SRMcbzN1KJN8YYChu6lzFTsdB4cPdnFop4vtzSkeuO82chcJgiAIAiQMibcJ3/nuYkVF0wI8CifgwtF96KrCD5cVBqZav0oLU2SEYaGTk59XvhdDxbxNPQdlNF3eiUrEQdBP5xxMd1MXdC4kM1dApq4QrV0cpiGj4SlIGRS+VyZOkx6JKfuQ82gSUl77UHkvyxrHlZEPGU1n7UecHhx3A1E0hWV34gchxQ9B6hy3MOcyEW5V14ZpMTgevD73ctZ1TO+TFa7znEMZTiGjCUaDU+hffgFe5zCG6OGlVy7hpVcuYffSs/jSv34UALmLBEEQBEHCkLjuuXhpmDbXzrYyMC3A53Kd9jFcLyW7qM0LxIJCLAtFaArmxRgHWEaoZguz5BbRod+vV1xmCcr63SEroJYsHJN19RbyIpcUC2Whm5zb8DIuXb4BvJJq3knMfgZLzKfMXRMrnieAwjw+QMGyu7BaO1oM5sVnUQVaA6UCv8b+k9G5QoG+cF326fdSWC6E5QID/WBgOr4Af3IZlt2BEC4cdxNRNIGMfPz133wPjz72XQgh0O69N62SmriLB7ck7vrAe3HLTQdw9PA6jh7Z34cXBEEQBPFmQ8KQuO7522dOpj9nRWHSSB2o0Uy9LnX2q8j/M4mDKJwsDlUQ3rhwnMzYw/6JWVP3AirD8irOTxbMMWEhJHZF0ZTNi6zV49CAyT0FAK9zOBVKSkmoCOU5nNn3liiMYw4jzYR0Fonq/PEL5pgXhQlhOIbXPgouDF/3eTd6GWq2Mlm6CNGK80nc2ER8R8FQf0dwGy3vKLiwF6uxMmA49FN3EQD+3V+dmNvk6OEeNjqX8Y53HMJPf/4eaq1BEARBXNeQMCSue7782PMLr5mqPgKxOFpiUb/g2uXeL6TgdXP+X25hv0TfwLJCKtodO1gyYMnxVCw6Df0PgRWL6CggmF4p3CwVunknNitolqjGCRjmXHSMZcRgbswy53IhnNVU3bTEiQ3LPnuTKDQdrwllfScz45e5zUVVUVUUYjTUIdeOd6DZ/ZWbh9vanvs3d9fTPN8oHM233pibBBbvhwwnTp7Bc3uv4pvf/hH++M++hvvvvR2f/czd2N45grWOg+6aG//x0O3qnwmCIAjirQoJQ+K657HHX1xYtHHhwQIKcqocuK2CypsNxN1C3lndcVC+OF4I84xFaKlrWHdsbqOzfmt5DhtQ6kyVicKFXoR1yOVQmtp5pIKgyMUrej27SZkYqSs0MuM3LlCTbgT4k2LnsrDoTMOHDVIGmI7OF25uWQV9GvezP2SZaM4cJ2oo0Mfjs6mQTnMms+HWhuMUUuLaJ4K9rG0JUDx+3gF+8qnn8NS3f4Tu5h3GYVKx2PXSn7m6gPVeB5/9zIfIdSQIgiDeNEgYEtc1jz3+ov4hJ2KSXKiqRftocArBdBe204XtbiwuULNuoYkiR8GwUC1bHC+EecZjGM8h7xaWjJ0WNqlRICT9OyMOg8CcG9fp3rycMMxQFv5aWLU1dw6mojVL96qs0RIknYqpQE02PJMV9+gD4s+G5QT7ErmZRbl7nNvwOofS8dL7OP53LVGbpeT+yf6OFOXCmkKoTQK96LMzfp41HMssRXMpfIAQ7zf7npjPey0aR8r4gzfMpz+Yoj+YAnFLnTAYYrj3KgDgX33pr/Hx++7ET//UJ7FzwMKRo0ews9XBzvaa4cQIgiAIYv8gYUhc18yFkS5ZmASYNTsH9EI1m3tWRKlrWDIXpUJDdcjYyawTljc34Gy7WoVN6pILnyzqv5jA67QTKDmfsrxIy+7UamlRVLSGMVZajbNWq4yCMNLaBWoyDwnK3NzGn00BJsHktg/O3ceNhWAVmeujlCx2cSvuz6Iw0qWocCyzFF2vpNJqEbPviTjv1e7AdjfmitcAuSqtNecT+n1w4UJGU3Dh4ns/OI0fvPA1jPaeR7v3vnS7ne017Gx10HHfwJHDm/j8Ix8hd5EgCILYV0gYEtc1+TYVhaGXhsWhiooX64G/B6UidHrvqBZnDUPyHG8LjrdVuZ1UASaDswj8vdjN3JzrSzd37ApHhuULmxRR4XbWGruMkmtUlhc5F/ZruNb5ENS5xbuzPl+Ns+7nZQiPVEpChYBChMnwLBxvHbbbQ6neYkDkr9BHsAwFSFUiOstEe1WBmyJMYqdom5oPLUyO4X70NCw6v9LKugUUhSOHwRBgHI6zDsfbBBfOYvGasvlkBLTXPgyvKLpACuxeehaW3YHjHcCFi8Dp119PcyO/9Mdfwf333o5f+oWHqA8jQRAEsS+QMCSuWy5cHMzaVGRInYuKgiGm0L4i8oKz0HnZxxyuyehcupieczNLWlo43hZk7F4Ye9WZ5pV3eOLtpuOLADOfSKXrtsJ1WHALDeMEfrGbGUVTtJxuPeHVZJ4MGA/OIJjuwp9eAWMsdim30vnmHWWzU1yjj2DFPEvDk3lJsZMm4q9sjKLQ2XxOn8FxLsvzrOx9Wbd6bHauMF8vLop7FhrdWG9L52/uR65mSZXZsqJFOqfxeTAGfO7he/DJT34Uhw/2UndxZ3tNf0/GLX3Onu/j0a88Dz+I8N/+Vx/BvR997z5MniAIgni7QMKQuG4pamqfUmOxZhIUAOC4m/UmYRKDedekoUAyLQQLX0/zKg9XD9xA/ADAdHKptKCNly+aUud4uWtS6AwJD267oEhQAWV5hHOisKwlQ4MwRGAmLpKWKIlL6Xrb8PKfg6rvFFdSIHZM7Ti4cOcFW9Vnv6zAKXoAU9NxLi0AVDcftmouOQJDESVhEOlShRBWa8G5rOyvWdeRLXILDa1HOLfhJg54riflN77Txze+81jhfvn5yOAsfv6rj5LjSBAEQcxBwpC4bvna119aaX9TFUygOO+rMj+ryombGwzFi0Y0D3WrNX7V6w3nYaxyWlX9skA8VzpDAMbDM7DttUZFbgpbQDTp12fKE5UhlIrm+mQmzIU6Jue6xIOBupS5SXO5bsl5m6rOXqX5ASvkvl6l+dRuGRLjeltwi0R99vMtIvf6aDgrdJV1l4swhVe31o4t71Jm9hmPdT/SJ596Dk8+9RwA4JGH78Yv/8JDlLdIEARxA0PCkLhuKXUMa2C764jCibExeMp+L5orxFNZaGBp6GadfntVYrHmPNIqp1XjV/27Jv7kjbQ1QL4ypMlxLOzZWCdn1LBdEkocRhPj7sIU+rrMedeocptvl5Cw0LMy//nmxWDZA4z8GEXzK6F2fmrdlhrLPvTAPhcBqvvQJyYJp01Cw8vaYygVlbuUK+K2dhYE8pcf/Tt8+dG/w/333o5/+t98gQQiQRDEDQgJQ+K6ZCG/sGxRaViotdeOp+9F4RRhMMBkdBaAFkU8qZa4au6gqTiH4d+m0ECgIsQ1HicRMLUrUBoW2U0d1fz++yWm88IiLS4TL6zrOI6F86qTb5mrujnqn0AYLOa1AvNCJ732y16HqnDDioJDC8K9yBmsM6+825jdr+Z51XbomjxEKMkhLMP0sGPpIkAriOOyqIBKl/IqkriI9997Oz77mbuxvXMEax0HrZaNlqf/uK4FxxZwHAutlo12q6I/KkEQBHFdQMKQuC5ZcAvLxFuNPCVhuZhOLqQvjwangMGpxdYVK4ZwzWFY5HHhwQLmC5VwB+C80jHIFsgx9terOWdTcZ5ai+g64YlVYYwV4qesmmmteeUFoklsZF4PwzGUmin9JJxUKQVLeItifNW8vYQCQdsoRNPkFDaZyxKipMyhK80vrDOfpiggMIj6ud+rJuG1ZQ8WsvdNwUOWtD1Gw9/L/RCH/vRK5TZP/e3L+PZ3XkBn/bb5N0wP2lo2Wi0bti3gOhZc10LLs+F5WjhydQHrvQ7uved9lNNIEATxFoWEIXFdMte/MM+Si6YiZyPw9wDGZpVAVw13y2J4v7CITFHVQhlgPHgdgG7WXrnQ3ienoXARvczxEoeTG6q9JovqkpDWpRbJTecbv14kchKR2OneAsspaUK+n05PPI4pjLRSuF9lxwnAzIkv+exqCcNVfr8KyD5MyIr6hVYwWG58E2HZQ4xVHp4siTGHsXMEwu5AiPlqtsP+CUDJ0u+Z0TjAaBwUvhcGQwz3XgUA/Ksv/TUAymkkCIJ4K0LCkLgueezxF+tvXMO5KusFNydM6oav7cciriLsbzI6l84tDIZp2wSvcyR1OBdcwwbHtZ0uwmC0kIPJeaasf9Nwv4LXC3tPxpQ5Tpa9T60Csg5P/t+Z8ctEDrcMbSFMBUrKWi2UzTGmrOiMbXfKx1pWZBQJlIpwXHM10u5KD0+WnX9RPjFjDJa9NgvBRsPfl5LjJRQd19Qeo3CMuhEQNSmaT9IvsRAl5+65ubY5NY9n2WuQMoCSWjw++pVn8ehj38UD99+Fz3324+j1WljrOOiuufEfD92u/rk/mKLfn6I/mKQ/D0Y+9vYm+M4zJ/HY4y/i0w++C1/43Dvx8Kfvan5BCIIgCAAkDInrhOHQx9nzfZy70MdLr1xqtnONxaepAXklhsVtXug0FmcoHjeL0eEE0DYUtdCTqRg7fq/VOZq+FEVTupzdWwAAIABJREFURMEQ4+EZTMcXEIWjapeyzqI+nsuwfyKu2NiD7fQg4sqLoaG1AJDLt6wrWEpYcC5z+5vaHDBugbNrm2NlcgsBwHY3y0XnCtdpOrkALlzYdq9Y8OYwCUPH27o2zmUGUwsI7bCu+PmVVHk1FbcytcdY6fg1MF0HoyhEJuw1OVzV91luPo53QI9fMM/vPRfge899tXy8/JgF1/krT7yE/+8v/wOklORGEgRBLAkJQ+ItyW988at46ZVLOHehj7Pn+xgO/eqdKigLhyor+LKQ11fh5BW5X6XO3T7nbmUX44XHbOJUxQjhzh1vFfcgPWY8lzAYZio27s3NP++qGPMt6zq5NSn6vEqLqCwZnrosJsFl2Z3iPNT9mIcCJqPz6T/z1WGLcLwDixVjc9U1V36IUvP3xxQ+aVmzuSwcu67zWhLuaQojnQs9XjVU1LBv8p3ntnb0NVdAFBTPZ+EhT1bcyvkQ0YXvnrp53XXPsSzfNztOXoRL/fklFVY/ft+d+Ptf+DQOH1rHzvYadrY62NkuCfkmCIK4wSFhSLwl+dKfPq1/aOoEleTkJAUgUkETL2wTLKsDKTMFX+Im0m5r1midMZ6OW7WA1evdOI9J5kuTZjcsHaaQlXO3lji+STyHwXClhW1pFVbvAITwwLkDLmJXJ+8cIPfvGveHlAEmw7MI/L34PtiA7awvNf/SSrEVZEVRYQij4f53vM3CMN/svVq4f9XrJeSr1OarwxZRp2LsUm56lprnka8mm+SHWvZatSCsUwW16IELgMBQ6GXp4js1CYPh3HeeZXfgeluQ0i9shbGAQRSaXiul7vd2FVlxmH0txnZ6cw9NvvHNZ/GDFxaH2dleQ9s+h52ddRw9fACff+Qj5C4SBEGAhCHxFmQuf9D01LjqiXQ+DLCgKmC6sLU7ekGtAG45pWFlSsnKRUyyyBxeOQEFBbe1BdvuFbuGdYpLFLxXJKbSha6zvvpiu4DSIjBNRWFm+7JxC0v2Z69XU6cwfn8yOpcuIAN/Lw5ZPRm7nzfpTXOf12K/RBdW7H4tlcuJGqLIcH5FYb7TySWgqCpqVauKmot2f2oI4a5qzVF30d9UrDZ8aGS6zwpbr+Sv0wrz4sKFUHKhz2YYDGDZa8XjZ8WP6fuh4vzz4cb6/Blst4eWcwRcOGBMVJ5OPowUKHAMa/7emRgPX4eUwSyao0ao+2wys9dsdx2BvwfGWPp9GPj9heJCFy4O0L9yBvIHrwIAvvTHX8m4ixs4uN3BNrmLBEHcgJAwJN5y/PFfPFO+wRLOVODvlr7fqHF0zeMnYjT0tVNRJ/Su7vG4cMBlWJi/VFhhcUVUVRGYdEM0+nxktEI7g6Kco5qYREIw3QViYZgXbYn7ZSqU82aRhPnKyMewfyItIpJevypxE78+515KWSAm+aLTJDy47Z1GhXNKadq6oeZxTKHXaQXXq1A1FgCg5l1TpSLIyEcUTRD6g/KKqCVBBgvHKfh3UbhxGAzQ6d1iHrOo+nGBMGRV7WqqHhLk3g+CAZQMlwtPzzmG6cuMAQyYjs+BcwFhtefmkf/ufPJbz+MHLyz+fh/cXsP2dgdt5xKOHNrE5x/5MLmLBEG8bSFhSLwlOH1mD6fP7uL5Fy/g20+fmH9zHxZtZa5UWdGFZY9ftChLHErX24KXtKRYxpGAuTAMoMWN7TYMi8yHZOYou362nVnYmkI8DUSGXolAhTCsIwoMn1te5CZtCyqP+VYiv7DOhCsum/9Z1Coke4zO2s2179Pp+OJCLuH8wdBI2FXuW4Ep9NqyKiq4rjqP3PuMCQjRgrBa2B08C0y0C2s7XTjeVpoHuOCGLzE/U35nk/kCiyG4AKqL9ZiczILcwCLRvvB9k7vWJod+8XuXQckQ48EJCLsDx9uGEC1Ecgou3OJqsZyD8dnBLl0Z47VXn0XgD6Gg8P/+yVdw/8duwz/5x1/A/R8jgUgQxNsLEobENefc+T5+7w+fwmsnL+P0mV2cPmtu1D0dXwQXzqwKYhVL9P2aEwOrLFgz+5c2H69anDVECBdCuKkwHA1OAYNT9RzK7CK0xKEwVeQESkLxqhyPZcZdxVGKyS86k5Azxhhsd6Pm4Llp1Qkj3c8WErltTQVOTG5sJSv+Hkwnl6BkuOhemo5R5/zz92qdnLX097E4YsB2V3gQUOdhhOE65r8fAr+PwO/PPzRakTr5nSkKGA5yhWrSuS1+ly04his4xmX50mUUicO5uTI9Me0cMshojMnoFCyrBS46cFtdBD5H6I9h2S1Yjg4JZ5xBWNkQWwXLacdj+IhCH089/TKe+kf/Ag/efxd+6ic/gUMHe9jZisNPtxpGhBAEQbyFIGFIXHP+t998DI89UdCHsEDUTUbn0rdtpwfbXS9fZBYtyhRgO+uQ0QQyyhSX4Q6YyP0KrJIjldm/zGErFDzZY+XnUVIKP6G2Q1lGSe6O6XxKm6nXuGa1xq2oArtAxedlKnajlCouRHK12QdH3NQSoVFhnJpVNiuHyThAhe5lHfG06gOa3HkU5RgDBod41VzHonnkMM2HWw1aWDQtzFUG0yGjMprOCtXEhYwcdxNR/N0JxGHs3F7ufsl+v8XbShUWF8MpyYllHFAFD57y3yds3mYEY4CUEwABWmvH0F0/BstpQSmJpD6YkjJtXaOkzinv9I5BSQUm9IGTYmI/+LHCD37r8czJ6WPsbK9h+0AHO9sd9DpDfPze2/Dwp6i/IkEQb31IGBLXnFJRiNnfi0/VZ60MKkPkcmFYrSJh1LQS3lz4U4Dp6Dwsp1vtOGaHKhNS2WOVLYwLxq90KJdZNCYLt7L8whVC8Sqb1+fmUZuK7bnwYAGZhwS64qmosSi/KvmFK4pCU186oOQhxDJVNk375V4vz98s+J1d5vwN+4wGp2b9MOOHSCa30DLl4tacT3ovsExOJlD+cCfG1DrDGE2w7OfVgOzDhUTQW3YHtrsOx9usLlZTJlJNxaKgC0ylRaYMD78SJy85zGhwGlE0hettp7mDUoZ6lzi3kIGDMcSCMN43/llBod3b1odUAIOASJQh52CCxe/F5xu/xwTTTmXm85ZSgSkgkhIMClAMV/oBrgx38d3vfxe+v4c/+YsnwBjw8Kc+iAc/fiduvfUWbG+2sbPVQad9bXugEgRBlEHCkLimPPb4i/P/8weM4WFJb7siCqvirRiOV2vbjJMZTHfhx7ld+bDNQodSOODZptam+TZY8CWL0ygcpYsflXuULpbps5ehtDWGWxLiWxHWWzquXaOATpWTajhu9iGBvmbzG5U5hsl7o/4JKBVXnK2Tl9gkbLLhfWwSGau6uY32y/7eGsKDF4rh7FfBmhhTP8xsL0wuXAirBcfdaF4EKkf2PmE8roJZdj6Z8zU3vXfN+xsnUvD+EoWZTDl3tV3nMme/4vhZkZ3ffvH3kSEKRgijsa7sauncQQAQVke7giqCrpYbAZDp7wLjApzbkBgjmA7geD0kKcaKzY7DBQfnYu74SikIIebCTJO+iUqq9OfkfGQUQDEflm3FrwFf+cYP8OR3XsDGobugpEQUKngOx/aGhwObHrZ6Ezxw3/vw0CfJXSQI4s2BhCFxTfnyY88vhh8ZniaXuWCFBWOWWewu6XblXZF8T7dChzJPwzCwyeg8hOWlC+w67lWlQ1mFKu8zaNs1RJFBHDbOLywat+jv/PslKKXmis/M3kDp55NWnA1mFWe9zuHqohzJvMpEc9FxS/MTI1h2p/whxLIskbNrcgwXCiLVGa+BiDbdp663BWF3zKJrRRZ7YlZXHi4SYXzZ+VVdx5qfm2W3EUKL1kRAe+2D8xvVvQ+qHtIUjJMt+JJuJlXh95x2yfWNGQZDBP4gFfuMC/29x/TfjInCMfwx0L/8PNY2D6HV2YBSHEoCjANCCHDB4+8GkT5sE5aI35s9hFNSQUFBRvpvPWcGxmzYexZkNHtgwBhDb+ud6PRaUFIhDCLISOHcro/Tl8Y4d/Jp/Nm/ewJKAg9/6gP4xZ//FO65+z01LjhBEMT+QMKQuKZ857un5l8wLDLKRCFgECRFIVzJ63UW4TBsk9+kJAQyaSi93+5lGAwxHV9I/207PbitrbQPWtahjCJ/Jg6yQqVscWa6Rqwo9DIjPMrmzQw/Z86pcLcyMVungEuTa1/m2hocEFM+JwC0uzcVH8d039Vd1Jds53hbcIr6PSbkHPqkyIixKMwy86zBwrFqFmopJfN+WZ/CpURhzfso3xMzfUCUr+Ka+dmyO4gYL64Yug85p00fOgGZSsfLOrllv+8158Pyb8R6LsnpA7Kh02r2nQ/AstfgtYt/D4pEJwBEwRiXz76Ay4yjtbaB9a13zN0rjGv3UOc1Mu0YCh6Lxtgplto5VEqLQyklGGOQMoLb6iCYxv9PiB9AtXvrcFwBxxYII4UolIgiifFwF622CxmLzcef+hG+9tRzuPcj78V//UuP4MMffGfxRSMIgthHSBgS14yLl4a4cDFX+tywSMg3Z86SOg9Nih0AaUEBIJcTVLRPwXvJU+cwDtvMh2wCDdod1MjVypJ3Q8KgjzDoxw7lLWkFwoWwq+wUyxZnRQIg3rfVPlw/LC33flpVtkEbiKVD/EznUCEW565ZjXvK9NCi6mHG4oHjv/dBdM2NWSJCw2CYPrxIi8I4XbTaRxcLMS1zXKV/B2q1SWgiAis+F1XSD3Npp7CmM1YkSKNwXPr9UloxtM53WsPvrlXI5m3WrnK8hLhkYIsCLvnV5LNtZqHTs6cdjDEIuw3GWWEEAGMFYwNQCHRoKGMIpnsY7L6O7uYtkJGEihTCKIQKpRZ7nMGyLQjbguO5EILBdm3tIlocMtSiMAojRPE+lr0NKUdzp+16NjzXhuNycMEQTCUkgMHlF9HqOJBxWKqSQBhE+N4PX8Wv/vrv454PvxsPf+L9OLi9jsOHD6PXcbHevTouOEEQNy4kDIlrxt8+c3LxRYNYyTZwT8Ka7Hyhl7Kxyl5b5vUMiQAoyulLRWsd58q0iC943eSGLOSXFQm+hiJ0bt+m5PbJV5Wdz8MsEBDChdc6ZJ5f0zlVOV5LjG8MlTQVM0kwifEqqnIps1SMWRRuGfh9gJ2t31C87LisYZuELGW5cvHrw36x2xka+mEuhGcW5TevQsn+UobzzndJAZZC6rrZZbl9RduXjZ0boyhvMwmXL9237oOkZPOMaJsTdjwOJ4UuGAMAwTR5AKPmPkvL9sAY0w5fThwyzsEZ5kJKpZyJQh63tIgC/dDPsm1IEQEhg+IRojCCjCSiIAJjDFEYgnMbSgKcMzAwcM6gOIfigBLJ/xcUQl/CcjhsR0AqQEYjWHYbjsPhuRyhyzEaDMHZCK2WFQtDhSCIxajFYdscP3zhNbzw8gm0PBs3veej8H2Jqa/Q9mx0PAvdlgNbXcIn77sN99z97uqLThAEUQAJQ+Ka8bWvv1S+Qeb/5bXCmgCMB6fTXDXL7sB21qsX6ICxQXIdss5Q3jWcE64NwuCMrytdzr1OPzolDedT0/motV2DhbSpquwsD7NCQDRd0JawUEX2KjgrpeGcWOF4NR8eACWvxxhFbVLsp+l1WTbnrIgaLli2pQIQP2xwNxBF08U8S+6AW878WE2FeY15Fz/g8PRDrawwXObhTB2W3b+WO75YACw5z7KxkiqiDCzN1UvEXxIWmnx3Jnm+2Xw9BQWlIoz2TgAAvM4hXQEZ+ntEZRU+YxDC1Y5jLPCEmM8pZELo0M+MMAwne+BCxPskG+ptuGDgwgJjESTnYIwjElKLSyHAuQ4n5YKBc65DTsGhhIJSDAoMSnFMp2+AMQUh9HVoORw8Oo9e7wgmkwh7/RCTcYjJhMHrvh/TaQDpR5B+CPAIDBGmkxCjfogD2xfgtGzYTgu2paBtVInRJMCVvQmm0wgnf/wd/NGffQUfueud+Ef/5Wdx70ffW/4BEwRB5CBhSFwz0vzCZRaTBjchCPqpaAqmu+nTbdtdR7tzPN1n1TYD2f0db6s4n69JsY+yRWLOAYj8xcV8sqiyrQZtHYqchaYuRt3xYQ6tjMLx8kJ0yXkuVpHtwvG2ysPiDMcyhUomC9dauZxlmNysOk5wydhlubFpsZ9lHdmFg+XeX1UUx+eaL9ii7zEFy+7Cau3M59U2dVYNv39G4u2yDziUiuLvhQmm4wuYji8sNIyvnEf2vaJ7oe5DgbLzqPl5FInAwoqqufGUkoDks2qtAJhWXUi/SqX+HuNxiD9jDIrNxOKofxpROIJSwODKK7CcNbjuBtzWAUTRBFGo58EtB5YVh5FyBhYLOcUUOOMzsZe+F1cTZRJuuwsV+Xoewo3/JGJPC03JJSIOcCnAOFJXkovZ3/pyK3DBoZSev+IKUTCEEFqoWhaDZTF4noO2qyC4gB9oUSwsjulYt8IIrQiRYyEMIkROhDAIsffGy3j9tT202jbe/xM3QXAG7gCJOAR0pVTtLlr41jMv4utPPYdP3nc7fu+3/0m9D5sgCAIkDIlrxFx+Yd0n59lFWsE+ZU5aGAznFlYKcjlxmOyvZk2Pjfl8ORbdzF51AQ4s/ru0Kqi7Ud/5rOHIFO6WuW6lx8qNYXKn6h536X1qhOIGfh+B3y8PizMcq5bTGZOvJFvq9mX3V4btGoqWLEsV+1mWrKipmFchBSLN1K8xDMfwOkcXz6Hpw6emIrZgO8YEhKUbpifXO+kH2Fo7tli1dpmHZHXFbp17rYIiYZiE55q+T7PfEQpK65YkJFRocQiltIMoof9O+gwmLqJUkNFUCzlooRWFQ/iQaPeOgYFBWC4Yn7WO0PtIqDBCGO+joMVh4vCxuNqosDjaawdhOUfTfXXxGAkZKURhEJ+LgpL6nJQCVBBhNDwJzoCto++E6zngnOlehhyAnA8pFULAspkWh1yL4s2DxyEEQ8dCLBoF7Hgby+aYTjmiSGhhGEr4EwkpR7BdC2Gk8L2nf4DTr5/He+68E65rw3E4giCEP96FQgQRi0MlFSbT6kgTgiCILCQMiWtCYX5hliZP9mPK+uDV2R9Aea7RiouqUjczyecyhbYZ8i0XptiwcMoCDcXFQgiu4fqVuVNW0lcxLxzqOCFLuIxlc0EDoduUokqydVoZlB67jnOUJ95OqRCW1YGUhrYW+x1eWzTWCmLN1K8RwPLCtul8apI40wlhMMRkdB7ttWPNjr/K51EnJ7UCKYOF1woLCRUcN3ENwbVbqJQCUwpMiDTsnXHELqLOAQTiXvJMQqpppqk908KSCzitHixbpG0h4g10sZgwBOKQVGA+1F8BEEy7gZyLuFehLiiTCkDIWCSm+nUW4qr0n2F/BCU43jj3I4wHGzh0/L1gieDnKhNSCtiOA859CMERRTYchBjuSbS9EN01Ac4ZbAEIzlNhKGyB0I8Q2BxRqMC4hOPas7RJxjAYDPD66SmE8KEUdF5iZKO7+X74kxHeOPdD2K6FL/zkPc0/dIIgbmhIGBLXhC8/9vy+j1lWBbJo8a3UzDVMxU2Vc2PYf/aiYdsSMRJMd4FMmOvCeDmHNM23hHZNomCI8fAMAN1o3bI79VoPlLFKoZeC7crcwrRhdsnxaruUNag1l6tA3umtVbyjSdhp3fdiceB4W3DcraUewlxTDPMIcmIroZbQXkX0LrFfkYgtE7ZXhaYOaI5EFM6JL6kWcrizhWO0eJs9PFJKgkHM3EIASs6iL5Kf08IwnEFIhTCapCGmei56PK99EDwuDpMvPiqlBDiDiiIk3S1mAjQ+hmBxCCiLnUMByxZx24lE/CXnweKwUwUoIAqjuF+iDSY4LMEBOcJw9yS2j7wHfhAhDBTCMELgBwj9CLZ7M/xpgNEwgpQR+rvA2dfPQEYSgf8yDh7exnvueCd2Dh/UwtASsASDbzFYoUAURLCdDq64Vvo5MsagpIRtK7iem173SCrIUEKIKVxPC9V/8bt/iSe+9UP8g5+5Hw9+7PblbgSCIG4oSBgS14THHn9x38csE4YmkdRIZBQsJpV+rFy56CoTI7bTa7Y4zxxPCBeciVQYJsdKi3Fk3cgmNHAW5lxDw3ylCgubroPx5u0oVnRzy+4TsUxrjJrHNt4DdV3KVYXaKmGSmG9TYLvr9fsQmsRtmTtfAy5cCCUXiry47Z3qnfdT9Nb4/Ivc/cLcvJrHKQrbrPouWzWvWslwThQCAOcCob8Lr7WZfpxaUJnnIqMIABD/NQfnHOPRaaytH4bT6mmxJxikP10oVgMAjtcFt3SeoOPZaeEaAIhC/eAuDACmoK3HRFzGIk+7hMkflv5suzye68xl1E3qMRu7ZeONcyfheBZ47PBxwSCjIYQt4HEOn+uqpXrsEIHPoBQQhRxMCqgoAuIcxcFuhNdefh2vvfw6Dh87iHe8+xb0Ng9C2BbaLYHBwIcfhpgMJ3A8kX4MWusqBNMQ7baC6wkADGGoXc7B7nl4bb20Uwr4/o9ew/d++BoYU/jEfXfg575wLz54x611bgGCIG5ASBgSV52rIQoBwPE2EQajwgVXuojNL1abOAem7Wvsv4xoLaXmvIPpLrBs24GC8WstLvNzY4DrbcEtqtJZlHdWNKSUGA0rhElNTJ/F0rl1NcI5ZYljbHQpr2YoZ1WYbu79ojYFQEkYdPbfJnG7TBhshrnczroFWK4GFd8jplzIudYZdeZZ8X76gMYQ8r0qUvozYYr8ePoiZEXbMscO/CGCyRVc8ffgtHrobh7XBV8iH5bd1tdSKQjL1fmZjCEKI3DOEU4ZLNeCZVuIIgnGdZ6fEEJXNc1oVca1qE3FoUjCSVlabMayuA5DVcl56P9wxiB1TCmgJnCcuMl9fJrC4nBsDim0Kyo4g58RnYwx+BOASUBxDiYkomACxiUE04Lv4vlLuHzpCjYPfXDmUsaCWyoFGR3WeZksRBTqAw92z+OUAqajV9A7sIlb3/cuWJYAk0O0PJGeRxRpN5Fzjm8/8zye/v4LuPuud+Hzn30Qm+ttrLVd6olIEEQKCUPiqjMXRrqia5ClLMTSn16GZXdnC/9lw6rKFoEli7vaLpVhjLmQ19z7lW5kFbljFroRcvG46Xt5dyC/XdNqkAZKhUmDcbJVZLV76YALG8JqUEXWdE4mcVDyGQlT9dKm92bThxym/QrGMRU8qtM2pfF8SuZRPImS7TKvVzqeq1AyT1PI6FxuXtl5mr4Tcg3aU1FWEnpc1NS9LklvyLwodLxNqJInPKZjsoKTCoNdIG5lEQVD7F76MVrtA3C8dbitA4DkiKSCinTj+OloDG4JBBM/bYHB4hxFJD8rlYalJi0qlATCaJYvmVQChWLw2puwBINt8zSvUO/H4m2RttNwXZ0fyXl8qRlDZ20dts0gJSAspkNWOYPgEbJfrWHAICMFrhjCIIxbZaQTArccOJ4NLrguopPmNurvXCkVlJSwXC0c4wKuGPUlLp07i0vnzmL9wAYOH2nBthUiyeGHNjgiCBGAcwYhFDhj+OHzL2MQdeF5bUx8wPclJlOJlqt7Igb917Cz2cVDn/gA7vnwe8pvFIIg3laQMCSuOmmbCmAmtKpo+ORfCHdu0ToenNaH4xYsuwOvfWixIuASx6lLmZs5R4VLV9RvsdSNdNerJ5cThUULzmyeUGP24XoGfr/w9SiczL9QwwlrdQ7PpqZtgPlN6xTwMZyTqeG6SVgxboGLffraLRD36bmsKM5NDx+uZk5m4UOYKsfecJ61HM+rhFIRhNVaLuQVaOT+VYZ1r0AUjOZEoYI+jrDbpfPRU1mcTJFglNFE5//F7SE4Ywj8AdY2joNxCzJSYGGEiMt0DMdzADCA65BN/R2WHD/+d+ZBYOLaAUjzCJO57F0+hYtnnsP61g4OH78FnW5Xz57pxvUAUqEHAL31LqbTIWTo6wdLzEPvwBGEQQgGXVlUWdqd5EzPcXZtdEiqlAxhcDkOiY2PwRmEJWC7FkTcW1FKOVcQR8ZVV4FZuGsU+OA2wKH/3zYcDnHqJNDbei8YCyElICOpf7VkACklZKSro546cUr/r1gpuC0btjPC5sEtSMVx/uQL8P0Qf/Jvvo6Pfuhd1BORIG4gSBgSV5ULFwezNhUJpgXMKmGfKF6MKxnGC0SmKwKu6tJkKdm3zM2MgiF4HQGXJTPvyjDVOtetxLlNCjFcVSrmGASLjbWBgjythuInm5PUZL/5QfR2YTBEGAvYWcP1LmxnHZw7sGws5FjOPZyoe+9lP4q6DxLqOnIFD2pq9TtclqYFdZYJt1SAP6npeNaJYKiac+59Yxh12X5F88hW9wSgCnL08qQuqduD19qG5awVirQ6ZG+NRBQyZoHBqvX9kBeCMwdu9rpUQdxfkMX3rn5dV8tlYIktFgKwLXAAlmtr8cTnG9oX5QYKS4/JwNJiNgpaYIXBAEGwB8ezEPp7OHvyWXR7G7j5XXfqsYF0HC0UgSM334apLzGdSkxGQwShjfPnA4TBnhZ9UQQl4/2UAhOA1xFwWx0wzuBPfHDFEQYDCEvoY8Tn0VrrwnG1Y5icjxaGcRsOhYyTGH8ung378mwZxxgDEwqtNS8t2CMjlV6b0A8XcjeTa3725A9w+uTLgFTw2i68tgvHA57+TyfwzX/6f+K+e+7AL/0Xj+DB+26t/OwJgrh+IWFIXFXm3MIq8mKwYbhZaYilvVZ/HkXzWoG8mzkanAIGp2q3L8i7houhkbm2A0uEF2YXjwpJj7EG+YXLOK9LfJZzeVpLjr0y8bhFDyICvw8pIzjuBmyxvigGy9bTpqItFdd3Ls+syinMvG9yO69pv8NlKXMW2SwMMs9Sjucy4nSZYxTdGw3v48RRD/0+BsEAlt1Bp3tTcbREBZbTRRROEEUTMAhwrp3PhSkWRBakoi37WiIMY2ESRdO06Xy2xKjlrMVjCh3umSC14LNsC45np+MlIhGYiR2WhpGy9OdEGMpIgguOy+dOwnUtWDaHbelQUsiJblifhpPO6tcAgOMwAImA7YDdLYMyAAAgAElEQVRPIyilYDsCSgJRpHsPRlGEMIgQhgHOnXgJXFjY2D4Kx1vHcPcShIjdQgbtLDKG9e2bYDsWhKV7G3IGRHGhGSRVR6WCjPQ5SikxGV2B7cx+JznXY7Y6LqRU4Jwh9CMkKjcKovR6RJEE5zy9Zv3L3qyXo5SYToBO71Z4bQ7VE3juVYn/8X/5aygl8eC9t+DvfeYWfPqBO8puIYIgrkPeIv+XJ96u/Ju//E/Ndsgvgmo6fKW96pBxOq6WWJibDBaOVSwidIib623B6xyuHf6XDY00Hp/pcvPT0XlY9hqE3Zlf1OdEIeMMYbDYs2zUP6Fza1pbsJ2euSprE8dlBdFW2UMtoURU1Qq3rIFRQDEGxzMIkCLxlhcEyxQ8qvM55N5fdDt7cNwNRNHU0O/QSXOtCtmHgiq1xyt5iNTI8dyv74MyYV43PLnq3zWu77yjrhAGA4wHp9Hp3VK+YwHttWNxLuGsyTuAtG2PdtUYGBdpKGi2318iMJSSGA9OgjGg3TsC2+2CcQ4ZxA3sWTJbfV+5Le22KqnALZ6KQya1CLQdC7Zj60IrfCb49NxUGhWQOIfJNiLTfoIxhijsw3UFLIvBsnVuoBAMltAVVLOiMHUgOYBYHKbXPP51EIIhihRkGCGMtIC7eOZ5KDVFFExw6cyPATAoKC0MdY8OOG4bQlhod3R/Rkvo/EeRtPfQuhAqUpBSIpJxKKlUGO5ehuPMWllwzuB4a2i19YMAzhhkK7uPleZiZq8ZAHhtW4tbGbuTYYj2Wgdc2FCQqfMoI4lnnjuLv/ryX0NKiYc+eRcevO92HDtyAEePHsbOgTbareYPIgiCeGtAwpBYiXPn+/id338SL71yCSdOafFz8/FNHD8c4c473oFvP33imsyjzC3cF6ejSQGagqf/ZfNLxU6ZI9SEeJzJ6ByC6W7abDufb5nNLywShQAQhmMoGSIMdDhwoybtufkY/12A7fQQhePl87TyLJmrZhyurOqod6B852Ud1n2kKBw58PeglITjbcKyOuBWxu1MwxpnN/ZC7htb4l7NkDiYbmtH31/LiEz1JjueJgG47OddFUGRIamGmnfqfH8XbYNVXSfMdO4jNZyHFh0F43OGcDpGEPTBGcfeGy/B9rrodA9DSR+W007FLOcuOBewMjmMSikIS1fuRAhYjgUukjxGBUtwXfCFz0SUUoCuJorUKWQccRsJnec37I/guroSqWVpQcUZ0FnrQuRva4Z0LAZAG3QMSsUOpNKCUYs9IAothJGCP5mAYYhW247nlYRuMnQ3boHltGA5rVRM+9MQF888D84VDh27Bb2NA7rIDdOCUwGQEddFaJQWuFGwB9vhs9BXznD0lnfDcrQjaQkGKfnsumQ/xPj3WUZA6O+h1bLjCqgKQSAhOUNnvZP2dMyGtb5x7sepU/nEt57D17/9HFqeh7UDdwJMoeVY2NrwcGCzhSM7bXz4A1v4xH3vq7zXCIJ48yFhSKzEb/7O4/irR38099oz33sRX3/i1fTfiSBx3E294GuySKq5qFIqgmWvQcoAKmnMzG1wbkMk4Yd1j1sz92fh9fy8Y8paFwCLLkbyRH5V8gvkNN9SKbS7N1XuXzTvBZdzPyhw0OZaE5TOMXZFnS5su1f8OdX5zBuKxJUrw9Zwwa8KSX6kobhPGAyK3aX9mGPFdY3ShxBDWHZnJhCbjMMAZeihuUw4ZW32wymt6xQbzr+4GipbaEg/P5SqJQ5L51NB4F9BUsSGMV191J+8Abe9Cbe1AS5cMHDtVEmJYOIjACAsAW4JiPiP7VrgnCEKJcJgirFUkEoCUlchFRaPi7dwCFsASjtvlpDwgwgykpiMpvCnIYJpiCjcwXR0AgcPeWi1LXAGbB08rEWgSMI450Vh4kC6TnIx9HlppzEuPgPdImLq2PBa8RIrboMRSYXNnXfDdtYR5XL8lFL6YRginD/1I1w6y7G+uYWbbr1NO4ZSQSo9tozF5PqBbYTBBGEwhuO0YFkWer0OoojNxKKlW3JAAmA6RjYKdKhrEEYIJiH6l5+H6wkoqRBGSvdotLpot3WLEIbYGVUKQRAAaggvdgUTp3fz8HvQ7rTSkNcLfR9n3hjjuVcu40//4j8gkhKffuBO/PzPfhx33/XO5jcSQRDXBBKGxEqkOYSZxUo+bDIRJMF0F5bdRad7c+ZNVC9+8uKwYB/HO1DLqZkTEqYFfNGivcGT+zxlrQtSF2Ofwx3LHK3ELVJK6jzCrAbNHK+85YIhpHOZsFGT41rjoUDeFZ1zNK+G4EqdM4P4KMjBajIugEbzzj5AqFVdNX4vNLRUaNLSIf8Ao9ItLDmv/P0aBkMtEJ3c94VpnMz5Ot4WnBV6aJay5O/jdHwJXNjl17ds3Bq51wsPK5T+j2X3jMViytpZlLWkAJA6Sem/DSHGqWCNc+kYYwiDEbruLXBbrTj8E7DUrLCKlDr/TYvC+G+h+w4CcUEVSKjUDVMQlgUuBLgVN62Pw1AZ1wLR93V8qLBCCCvAeDBFEPg4eyZEu+Pg0KEWHMfFcKTzBhkAsJnos+3YeYzPK3EOuRCxY4j07yhi8FwPLY/Fwi9uQB8prPV6ALMQhTINEwWAMPTBmYxdTA7bZoAcg3MFSAbJGbhUQHINJHDo+PtiJ1GlTmJ/IFOX1w8iBH4EJSXCQCKY+hgNp2kRG/25ARbfQRBw+JOXsH7Ag20LbB66Ca5rQdhaGKq4j0cwlfC82dJRKX2nbB3cBhTAhR4zCHVLDakUrpzncJjAU3/3Ar71zI/x4Q++E7/4n30Cd3+ABCJBvNUgYUgszcVLw1nF0cz6osxNAeT8gr+G47bw7xUW/KVCoowqkVKSWyRVmJavV7nSglZV7qPh9aoF+VKOVu4cgqDYVQJKqlMuETZa6pRUXPf8eSaOZioomuR81XEYq8RHU8qOWfEwpNRVrrifTG1UarU7qaJKPBW8b7pfTc5m6Xh1c/r24yFGzfn408vpNV/4ztmnMNNEgOUr71b166zjGppEv4IOIWVifn/GGMBjlyvyZ4Vg0vkyWI6jQ0O5zlvVffoUdHN6/WdOGFpi1lPQUlBKxG0cpA6btAUsW6TFW7QwnB3TsjmmU13xU1gco73LcD0HTHAocFy4GODKk9/BwZvvRuBHCPwQ/jRAMA0R+AG4kpj6Eo7NYTsctm1BWBzcElDyDbzjnYewvbMBoVso4vIbb6DlamEYRgBjCpbtoLPWQhgpRCFHGKV2IcLpELbNdc6jYBACCPxJLh+w+PNJrm0i3piADpUNGHyLxwVoIig4cCUQTIOMU6kL/Ux2X0EUhbjyxgTCFhhPXsAdH/wI3Jan8zIBBKFExHx4Hk/no2In0R+P0dtow3FEXNxGIYyA6XgP7Y6VPn+UUuG5H7+G//5//kPcdds78A//wSfxkQ+9q/T+Iwji2kHCkFiav33m5MJrVUVgyly9/EK3tgMyt1P5dpVCou64+X+XLESz5euViiAjH2E4wnR0AZw75mPWRDdwnm9RYOqjB8x/BkrJWRn8mov1uVyt/ciVW3L/snutVFDUEeH7mAMoZYDJ8CwCf69Zs/WGxy/qeWmCC7dQHDZtAr9UTmHBeZkeQtS+Tss4rvv1EKPGuNlrvfCds+x9l9sue4yse8e5U1w5lPFZ/ljTkFKglluoc4QZ0jhMaBHjuN2036DjxTl42cI1SkJFem5CxOJQiPi4egztGiooqV1ByxKwbO22CUtXGhUZwWrb2v3zLQ4ghJJDuC07bvye5ClKuJ4FEfdI1K0jtCgNpgEsFUFxwA+BIIoARGAswt7l13D54hkcOnoAd95+C2xLAcEVrHc9DEdjcGHD5R4gXHAuwSMGbjNYFoPvS4xHU1y5+Cqs+DXBk+u0GJmRd3/T25/FlzjOeeQMaLf0NQlsDsvn8G0en5cOyU3G067fFJZtQdhCV2hVEidffQE7R29HGEoEgUQUSgQBB3PvQBRIRFGIKC4ydPpkHydfuwLOGFz7Cm59zzFYFkf/0ovotHh6d0mpXUVA4Hs/fAVP/fMX8PCDH8D/+j/9QqP7jyCIqwMJQ2JpvvzY8/qHTNhfuVuYWejVCBNcqnlziStQJiQW8nOqhN+SooExAWG1MJ1cglIRpuMLiMLRQsuA5gPP/5MLDxYK+ugJr1nhmALm9i9zYfLhoE3FVoWDV8sVXVbc7aNInIzOpeG7Szdb3yeRCgBQ+jOMGJ8v7lM3PLiKJeZq+ixrO5hVjut+scR4Jnd27uFFnVzm/DbZsG/DMcrauygpwThfCAmd32ZR8DXJf5bhGIypWeP7WBx67R1wwcC5iAWQlWnorjIiMWn+zuNG9fEcOCCsuCBKHL5ozwlD7bpZOSdTCBY7hh24rUQAzhy31tqGdtrS7XgqELlgEH6UOpTZ9hu2Y8F2BaajAX703A+xc6CDQ4cPYmPrIBRfw2AYYm8wQahaGA0jTKYRJuMQk5EPfxLAn/oIpwcxHr6Ig4dbsOKqol6rXpslxgEV6fPgTLep4Jzp62EDvmD6ugS6giznHNOJn4acRjIA5yoVhZYlYDscG1uHMkV6tDjknCGyFCJLQkqhi+CE+rrISP98/szreOPiWTiejWNHXLRc7ZjqK6YfQyjFACWgFPDlr32fhCFBvEUgYUgszWOPvzj/Ait3qhaET+b/2enCIfsUuqyJ8j6Gq5WyT05lnuxcknwqoKFYyJB3i0pbWtScq+10EQajhYVtY5ezqZOT389AUWXNhH0JiVyGBvddmbN+tUmL+9S4F8bD1+FPrxS7nVdDfGXYz4clc2/VEDelbmiD8zbnc3bnH37kv+5M4xc8MCkuPFPR3iU3ftY1rMovXJiS4btaqgjCbkPJIHb/XHBLwHY7utm63gpKRjpUlDMIxgDBEUcogjEt6JLeiCyuOKrH126lJZgWNZZ23Gxbizue+5htm8G2FDgL4LpxC4tM3uDOoaPwHI5QaHHFBIPgM5EYWhHCcPZ7y8ARhX3YsaByHAbHUpDhGL1eF4p7GPu6mqrXWsNoHCGSulKqYwsoz0l7LXIucOXiFGdPR+h0XWxtt9DpzkfYlH0q2VYyPC6Ew5kulGNbHL6vYNvajRSxaxj4oc4xhFgQhY7F0Ot1YTscUgFBEAtriyMKIkRSQEUSkVSIoplAnI4ncFu2LvxjMVy6HKLdbmH7+Pvh///svVusLct1HTZmPXq99t5nn/c59817RVKkFEsyaYmGHn5FSBDDsT9sBwGsBPpJgsR/QYDkJwkQIP4JEAeJkw//BEgCGAHy5QAxFJiyKDqSIomURFIURV4+Lu/73nPP2a/16K6qmY9Z1d2rd3evXmvvQyH3rAGcs/d6dFd1da21a9SYc47lEsuVQb5yWC1zrJYrXJx+F9lI48u//U38whc+M3TK7bHHHk8Je2K4x05YI4W1BYbSGVRwrbvknbvXcaHTVwih7f29aCEjfUTikop21bC0HvQWhlmdAE1iuCHX7HIDG94zsK+T2XPl796v4IsLLC7e6Vc568rgVfu5Ab3EMDvaGP47uHDKpgV623vjCi5wj61Fn9n6gLHZuXrtNnMJQBGtSlrVzmsihZftSUYwidTskgt4DSg3W/ru8wB0hTXb0fF2n5eedpOdzKU2bIviVI+iiHOoqRoSYnhp9CZsHld/Xx9G49sYT+9cen5xfgGtNfIF4fw0nqdG+ACUZElpJX6GWmG1eAc2y3Dr7n3MDo8AEtXQ2KiOaarIoSmjV9fHxBBWiwXGI7XeHgG379yE84B2BKNZ8vwiKRViqOGcLsMwiYDlxWPYTGwvjAEUMQgMazO4IEqZIskZTEpeCl9FIqZEADtkYxttIAgnJwXsux+A9Y14rxpjn+5h47lkryG+jPEneVgtPpCKpB8U++F9gC+KS6TQWMLB4TRaYwBGazjPMEWAMyREMNpnBM+xGqnG/PQjZCNThvMqRbhx50VkmQWRBkhyF9K8OvlwBe88/qP/5B/jC3/hU/jX/9XP4ZVXXsLt4wnu3JzsPRH32ONHjD0x3GMnlGGkDZRkgoVMcChwcfYDAOgmFC2LjbRj3Zo3tWPYWB+R6F2kXwdq/esPgWwpLd9yXZ0VIdMq4ZqVTq1HrVUjgd1Vzq3CS1vel41vlWSiWdSnyM8uj+UQcrFN2Gvf++JrvZVdrxjSe2UMGHf27cTWu+Xu7baETdbtSSREr75ix3oObU+/kxdiNr7dadOwNZneZX7WHnd97wwKqx+YO9n1ndI6x5pKYe27pK4abvwevtTVlrBT0JoB/dprWkOrmAyHRGqknaQUMqQoTcg9Vu4EF6fvwliD+dl7OLhxE8+/8uOwWRaJYFQKDWC1kLQuKJ7j4GAK53JxcDBjsJtjOT8BlJBppQijkZacQEUoCg9nFJxTcEUoQ0pDEJI5zpSEcRJwcHBYFmbRhBiuGiucGiVVVLWwOPFXlLzHbJLBWgVrJSzW+6UUcklf741boDUkhcOJzYTYUATMCShyj3zpsFzmUZ1lgAMevffHGE+nmBwc4vjOPYwnN3GxenyJFGaGwH6OLBNyyACcl5xPV4SadUb0VPQMV+QI7hTZSMdcSdlYmExnovqSWiO4ITjYzIBZFMyvfP37+Nq3foh7L3xOQlMDYzKKnojHY9y/PcHP/MRN/NIX9p6Ie+zxtLAnhnvshNKmIqElJ0+bEVyxvqjcRCjqO9Bru9Vt2LLghB3dgHfLzpyfp4qByqXNNoRADlVKh6BtMdrzXFeY8CWSMHQhPfS9zffF/qx5HXJACDny1Qny5SMs5+8A6CDaAKixWC0Xvs35tKmfG/rfNWYbzdb7zttQfJ4mnGsnHFf6DG1UQterag45BojfLVGdK79jsiOMZw929jC8RIj6cmg7+lvfwAA68jm7PodDyHtHBAIpA0WXrXC6z9NeiCZ9D9c/M4OjO7reTwStFHSmq1y9krDrSA557bXFxUnM9ZMcuXx5hkfvvo4HL30m+gte7lOsV3MJ9597HrfuPY9VDiwWBQqnsFwFvPuhx3I+R5E7gD2WywLFyoODx5P3/wQHN4/x4MWXMT28CecCgi+kQmkWohIXlcd79yWPLranqCoIYy0hxNzIFO6pFcDBYjQyUX0U9dPnS5liAWv2EglKEUaZgtYM7RlOSZhq4QIYHlAEExmyyx2cA0JQWMzPUBQLzM8fwViN0XhckcLRBJlawRjGk48cjL2A1jF3UysYrWHGCvkqILiAUHjkuUdReKyWObJMSGG1v0MYT2flOGAk91mIpYG2gCJTKqda2UiKAQqMZe7w5nvneOPtUyh4/G//5I/AYPzVX/xJ/N2/9fP43N4TcY89rhV7YrjH1vjgw/PKpmID+nIO28Im06KkvlvdeMP64n2LMLPprAp9q4dGAsDi/C2MZw+2z2naIaytjxhqM1xFetqkoIkuVWIQSWgr5rNdGtP6sZeeU9BmCl4+in0qMD97A8AVyUGzn0NzW+PPviJAW2HTJsgOObdD0DVX+4qa/EjQcj1t3zVFfgoihcnB89ffh4GbUmsbGJvQc5+SB6sdHcOYWTnPuj6XZsvvksEhpa3djqSlWTEznYtojVgqApTRUEoqjspbKPaFwVy1l84RwlKqhBoVC9cQzk4e47bjqLpJcROlCEEJ8VBchVyu9QuA0UDQQBhZkIrKlw8SMuoIRc6RkAXkKwfnPE4evY/52Uc4unUb91/4BIgI09kRFC5AykHpCYguENjg7IJBCljmAYEJwQtpSyGlLneiQuYB+dJhtSgwGmkJi9UUFUePEDxIafiiGtuKHMrFZZmC9hzJKYM0lZ6QYgGiwEEKvYAKGGtKew9jFG7dfxmj0aEY3q8KLJ2Bzj/E+6+fwztfI6ZcVaBdqyIrnZJ8z2NcnP4Ao4nG8W2xr/BuAWsnYEXIavNrNV9FewvJB5ViQwrGxgq0xNUcJODkwzfABGil8Ju/8038y9/9Fj7/06/hV/7OX9oTxD32uCbsieEeW6PN1L4792W4n97G0umbcn22IInN0MgQCszPflj2azCR6FoU9ihN2fhma1GXIf3uxLYKXBfayDb150VeIglD78NV+3oJDFdcXCqdX+SnYPaYHb2y6fDN/Ryq2MafvUWAGkgLf5Md9hZq6m1319c70EUMTV9Rky5sMa9bVboN3zdDwylTNc6t8TRyG5uf257rW87fR7F6gnz1BMbOMJrcBRHB+1XpkwpIpIbSI4yn97fqb31c2r6Dt1UJm1jL54tm9UpT5U8Y38DRqF2ITY0ccg5ttOTHEcG5gOnBTXgX4KNSpgjwgaACQCKYwXSohkYBbOUWhEBRydMoioB8BRDUWrEb5hxaW2ijkS/P8M4PvoGDGzdx887zMHYCIovAjFVg/NHrALODKwKc83C5FK1hzyhyB1c4qcLqGT4EcAhgHxDCbdy88yGM0eXo+2IJZWdyzX79uy09siYWlCElxJAY7LW0gWoAvFtGr0ct9h5GwVqFoxvHIGWh8gCtMuSFR5HfRTYu4J1G8KFSLEMih4QQhDRqoAwBBiycI/DS48MPFshGFsd3T3Hn3lT6EBhayQf64uzd0veQ4wWNp0ewcbPAex/DdQMIWuZ6LAaUNgf+4Ovfxe//4ev483/uVfw7f+cv4XM/tfdE3GOPq2BPDPfYGr/x5dfllw3rhLDB07BeObK5WKurhZfC/OQN/SRxU/8YyJftauZOKkNz8drT9loeZlhXLl1xBmMPJczw2olTA1uER/YR/LWwuG3J+3WBpeR68MWwt7cVbnna4w30hh/WF/5AixH6nwHawyDHQjq2RVfY5ZDj6j9b0Ldx0Ra2ObRwzxpB/VHMj7Lhy+3VK4+mkHxjZ7CjG5hkD6H1CKRMSbA2FYZpEr01xS4azQOJCDSiE2r90y3xml3jS/G9yTJBqWgDofVa++JRGEpi6N0SSmtoHQlDLP4ymtyB95LfJoQIIMWl/YTyEt7Z5LTpsTWiUvkAMBS8ZwnjtBqu8DW1sijbl+Ix8vPwxl2MpzdKxUwFUStVYAQQlAZUEAKsgoIPck6lpQJrIAYCAUHBq4D84k18+N4CBzfGmEwMspGCKxYYZbOq2EwkhxStOITYAlYLYfOOwcGDEEAMqRzqHXzuEQKVhFCsLBRG4zEm03EcQ0Ieq9ekMQyG4V0Ao+57mO6TqhF4XSqZygQYa2GthtaEJ48/wnh2F3kuOZCFk5+j6SsotMfZ42/Dmhx2pHF06z6MFYXZFYBHgCcFVgBCvkYKpVKtKMNf+aPv4vf+4HV8/qdew9/+G1/AL37hs5fm3x577LEZe2K4x9a4lF9YR23B0Fd4A0BrAZo+T6017BJO1yBuXflTAGDaqvkN6c8QElTrg9YjaDWqQlov3pbTKANjZxhPHgwjidexaO0LY2NXqhLNQi/Z6Li9H0PI+3X1kwCfd9/Pp15caCh6SE7TcuCSEXpCnVx2nKsTbTlyPegKg5RFP19SZzeia35wy3uGKs894ZQAoNVTCnvd9PkeQoKHbM7E87RFGHi/wiRtJG2JZqhm271sDR9tXNf5yQ+Qr05gR0fIRjd7vzsTuRG1sMoXTCGiSY1SGuCgSpJYhBVUDI/0ruqTzg7hvYd3qIzbY0ilJ7FmSIbql/6sCP9BZpLtBVCkAjY2+SZKwZTAK1DsJ5XkkDCeHggxARBAILVODjmGjia/RQ6A0ilXkCRUMsjzCATvlxhPUmglwSgC5+/g9gt3sVwpLBYBy1XAcuFRLDxOPirgC4/VokCeF/Cewc6LChlVPo6VY8TEngF+Aca+X3o+Hh4dirUHRVsQqmw6UtVSqTwaSuKX7lPwsmkQQvVd4F0OYw20FVXSWoVQXERFtsov5HjdnAHL+RmWkM2Ji7Nv4qVPfgbTg9rflcAIIUBp+cOZ7EtUtOggRSCWTYA//Ob38ZWvfRd57vGLP/fj+Lt/8+fxs3/+xzrn5B577LGOPTHcYytsk18YgoPSo0sLGiKCyQ4vFXboynMZjK3CpvrVzM6KkdsoHl2Lw8bzRXE5XI+DkxxMEKZPIz+qDT2L8NH4Nkbj2/ISewSfw7sFVstH3eP4tBSWjvP25bO23c8fdY7mJnSHFndU5b3q+O6o5IZQYHnxLor8tN3bsA994bpNDjJUeabue6/0qPO6BvkU9o1LT38uvb6pnT5Qt4E9ACGFtfPUQ/I3gbCeO9j2vbupKnQRSXmxOkWxinYm2WFn6LaQQLGh0FqX6pvWCtBRiQqVyT0pBhYexkzgihXAgLYj2GwG7wJWgREcixJVSNGWLJK7EAjgaBFR7zdVRFGrqBwGwFmFImPYlYbJNPJVASLArU6jSpW8D4WEZqNpGqXL5JBEudRGxaqeSYlVpecgUQB5gBVAkTTqWJHUWEKWAQ8fPsRsrGJUhIYLgFp5eB/gCsnHVFYjUwrBB3jnoUOAKzzYyyaeEDG5j8Gv8OSDcygN3Ll/gNH4CNYSfCCESKophuWSEqKd/ArrBDDdo4o0Sk5jcOcwyRPRKmSZxigjZJYQghjb21iZlRlYLp5AmUpdLlyO7/3JH+Lgxk3cefASRtMboMLDk8ZoMoPLz0pSKAVuCCowoABtNDIrOaIA8Ju/8yf457/xNfy9v/1L+I///r/ZOh/32GOPdeyJ4R5b4fe++ubgxdJochujiZCJerEXZoZSI4RQiK9RDZ1FEOqeYo12LqHrPbV+9ykMZTW/Ddc3CAPGSQhgO1p9yHZFmwLT6EuJnusk0tBmIjvFPsf8/E3g/M3NoY9PK4w0QukRdOxTU9Uc1I9N/Rva/20Uo4i+hf9WamdbmwNygbcZj+X8vTL3sO5tOBrfxrieU7lJMd5VTW49r4IxM4SwY5Gflrzarfq067weOj9aDOyJCNYeyHdjCvPbcnOttKOIHRlcBTo91bHBxggxH1AUNmMMKKmE6nLoaRn+GiVFpQCp6in5cgfHDzC78WCtj6IeegQieBdENZqvn0fvTjsAACAASURBVNe7IPl8PsBojhVAGd69j4PDMV565SFu3bqBTANsAeMAo6MnotExpNQhz09gMwOla+GLRHD5AnY0QfrA18khmKStsB5SqlnHKwtlDiMzA4UTmwpTVSXNDOPoaAaluPRmNJqgrYbWPnoeAiHokqAFz/DeQxuHYuXAHKAAMMu4nz95C847qEB47+0zvP/uV3Hn/lt45ZOfhbamDJfNMlVTDCl6FUZlOTACGMFD8hhDzGdkxsXpk1jURiMbaWQZ4fDoEFlGYFZRnQ0wLGTQrZ7A6FrYMYn6u5yf4q3vfQPTg2Pcee41aG2RjScI7jwSQ5RjF4gwGilkmdiWrIr1gkY//ukd7JT22OMZxZ4Y7rEVfu3Xv7XTolrrERTpMmRytfgAq8UHVcjk9H5Z7KW+uGnFkHBFbnmtFqJWdJhOA9tV86v3o1nQYqgi1Vul9Drzy7rGaUc0VZrO0Mdme0+JlNXDHpOq6dwc+eIRgltAJeuKPiW3D0P7vYMS17bwT/gz8zvs6HfXpooyDRL2I1SMZ4cvbRVaOz9/E8XqpFI87dF2Gxe7zuNtzxdRxLzThLTgHU1uXT7Vpu/PBoaqi23965oL2ei2hENaA62UVCCNiluTBK5vANYaUjH/TthWlWNHEpaZ1E6Vwh9bcitTGw4OeeHhCgdXeJw/eQeTWYb3338f9x/cxGd/4tPIbIZco/JDtJJrqJTC9OAWQlhGg3iOBXCA1XKFbDxFuoFEiKRJiEuAGN7XQ0qlX6L0ESQvkllCMHVU2jJLMBowmnEwG2NZSMEWk/pnSIrIlGMn5vPJ+887XY6Ld6H8WySqXi45nSoSdSLM5yu8/dZFTQWU/E6lgCcffAvj2RTj2Qy37z3AZHYEDlIQxmsI2QuhzDd0+ankLkaiNrKEh889hLUSPhtYIXhGYClD6op5DBFFGUJb/iklQr46xelHb+LmvVdxeOMl2PFzWJ6fIM813OoM+dzh/OS7uPfcAQ4PxtAqQCZNLKTEGp/dE8M99hiMPTHcYyt88UvfaV+A7bgILEMmmTE9fHHgQbX2hiogjWP68gttdrg9Sdnx+vtIYel1d1WlbWg43JboWhS6HtK9s2K1ZT+TqrlaPkIIBS7O3oCxM2TjWxL2uOl8Q0lG3+tdr7Wcu7nwL09Bm0qIDGjzqgRtLUxxiyIvV2hnq/fVcnaHInlv1hXPbHxTCkP19aOrrR36sIYNx9XVcCKC0hlIaZhsBg61iIp6Xwaii0B2Ko71MPiuqrV2Gj3pKlKYFMTevnA7OSzzIMFr4a9MiCpkRSzqRWzaqs8Gv4DJTBnuuJif4a0ffg8vv/pJaK2gNZVG9FqLncbB8SslYQqeUbiAIme8/Tu/haNbt/Dypz6NgyPJiVOKhBxqgvKoQkoVIWgCoEGUfBqrHMPV4pGoglbBGMLIMqwKyFcX0OYgEkXAGIrqoZLSqmnMQ4APGuwDnOGySE6Ru1qopweogLZaQjFjWOzhzedgrBHCFjwUS1hqCAEBjOX8FEVxgdXFIxzcuInnP/FZMGtRED1LiKiRiqOHx3cAnsMaj/Fogswsol8jIzME7wk+SxFACsGvoLUSFVbXQkSBMlSU/RJGA94oaKdgsgP4kMMVEzCtkOceP/zuI/zwe4Sbt8e4e2+GyXQEQMJ4P/HSvd55t8cee1TYE8M9BuOLX/qO/NKlyG1AX/hmc4ExtGrgLrv8m6qlblRorlER6COGZUhmXeHqClN8SuSvC30EoctUfmtcQ7/rcy5VcgSkIu70oGUXedsF/q73o7EWbwuDLdUON9+cw3ddYbBd/Y3oLfLS5224bc7ewP5sdVwNbfmcrpivn28LBXLt/UP6tc18QU0Nr7+PxXcPEGJIpNZUs/n5O9BmMqiQVtt37ZCIjbbvL6UstMmkLyoSwpIYrl9kara5/aE0EHyNHGL9fSnMVEGBolWFVCQFVHxPQDxHY5UzP32MLNOwmRBDawjL+RkIouoln0GlAG0kH5LjWCtWCKoKrVR6hPn5Cb799a/g+NYtPHjxVUxmR1VBGgWAhRQFraARK6ZGMkgUQEGIrjYaWTaFtR5EMyi1gNU5lhdzHNw8gFYcSSuk31nz/igJJw0KxgUojRj2SnCFAzPgCleqhWWenlaYHtwAkUbQjODl2qTapwK4gLZGiLJRIHKlskfEYIVISCUf9O7znwJi/mBgmbKv/5CBsMDpR38KIsL9519CNj5CsVpBG7mrquxTzP8sJWIGh1VUm7ksMiT3SIPgAXgpDESE05MCZ6dPMJ1a3Lo7xWg8whtvfoCXXrjbPp/32GOPNeyJ4R6D8Wtf/Fb1YOiiZsDuMnDZ07ATfYvCgYvOvmqppUrXhi3Dx9Z28Tv61evzaA8vE5Xmz6sqFUPQcn39/pQ3Bs+JrvMPem3D+/vI66CCOUPa7lI0t1Qa28JgmT0uTn+A5cW7AOgy4d5GUb0O0sgbirwMaX9bEt1o/zrmeVc+5yWyOFR93SWsdJfPL9d+No5p5hYWxTlWyw/TizD2sNublVHmKG6LNTsTilWWzVRUPZaiJSCGNqZcyA/FGjlsgHRSF5NtQSKH8n5FAAJDgeGpel5QwGZSpETrlKuG0ptPq6TKKSgtBU0AIOhEBqOapgKUCVFV1FguzvDW976OG7fu4sGLn0IIUqBFKTGAZ88wmiTUMygg/pTcQMbNe5+U4jHe42LFOJsHvIcVfvCBw09+5hHuPrgDowhWA4WWnLomQpC2XCEXpRAJlFbwzsPlKyijSkKYqqsaq0Ck4X2Iyp2MfbFaRHsLHYkhYbWcgxkwRshcCHWCWB9PVMb3AVjMT7C4OAWI8P1vfx0Hh8eYHt6UiqgpZzAS8vrtCkzg4KHIC1FPIbBKQ2mHwCu5R0TVxgEHXJznOD1ZQhPw3e+9uyeGe+wxEHtiuMdg9NpUNNHY2QZtSQx3WawMXDQWRU9+4S75XNS+474JV1Yud8EViFYdfWOo7bTzNaDlfNdJamtzrpe81i02+s51TWRkI2rtpDDY1P8QCszP3gAgn5NygX9d/WojaR3h0kqPYQAEv2ORl2Z7bY+HHrcJHfeuK5+zl9zuonT2kd9d5lWL0lxHFWXBlUdrrCDZ6816hXmUNjRErZSTpcW5L7xYKcyXUFrBjixGk1EkJqpUrRBVNBCteSIqEKAZHNo7KHYPYuxOuqqiCSCGIwaxrECIfdPg4EBUQGst5E/4BGazw5KNJMVKqeT5J2Qp+KQWpqIxAUohFlqRYjVaE6aHtzAeVbYMPvoOel9lckrIphA5H20glgsXq6CStKMJ3o2xygv8+q9/DcoQnn/hHl54+QVkk+NY6qYxJtFj0EWyVehEABXyFSCkeATAQ5WkmuByj+lsFNsW8koEUfSshNNqXYXwrpYXMOYg2lvwGkFMIaHSn3SvGKcffQRtVKkG5stT5MvTkoCnMa+LyoEBYpa80rCC0VM4o6AKKnNWvTuTEOVUyCcEMNK8ApwP+NX/4B/i57/wWfy7f++v4Zf/yk8Pm9x77PGMYk8M9xiEXpuKvp31AWohEEnQpnCzemjXNmFejfP1EYa1sKtmP7ZcQPWZQgNbKJfXGSa6aXHad821+9M1htLvFlViG2ybW9hBYnqL+gzNh7sGEr1rO23qXJGfgtljdvjK9ams9WPaxr12vkm96ui2qJ1ntfgQSmetG0KX2t8VTVUuoisHtndOXLU/XWR4iJK75fcQBwk/TqQw2Qs4t3iqGx0cAFKQEM9LhbgY+TJHvswb6t06JH9SlYv+FB64Wr4LO8pwePM2Dm5IpWuCkEfSClohEkuqCB4UQAwmUedgAnzBkluYaVBUpogYhzdull6GAMo8Q60gappCLcxSCGLBqzU1LRV7GU+m4nE4QqziSfBehl6K5sjvdcIYgoSJMgtRDJ7gHYGgcHL6BqAAYxQeP36Mi/MTHN86xguf+GzLWMZrj3YNiXAnFU/dfgGTgwdSaXV5AVcs4YsM737/EcazcxzdOsRoakEAijzHxen7MFFZDLU/ZxcnDkQrHB6NoWMFWaoV5akTPOGSBA5LGLOeQwhIBVqlEH0T5XdwIoWIBWuA5YIxOaSYB6pKH0xXXEBFVZcDV3JlrRFtLP7fr3wHv/P73waY8ct/9afxn/9n/zYe3BuwQbjHHs8Y9sRwj0HYSi1swaAiK8Dw3KwNu+eXjovY6F9YXxw+jR3/GgYrl09Lseoj9D3XG7h7DC8prruECW6r1HX0s5cYbgp9bOvXNv24KjYonr1t/SgUziui7n+5ZnOyaaOiiW3CfSO65kVWV5GbpGxN0a1Iz8bKw9exWVBvv+uzEZ9LqmFwq0uG9Z0+mVfpZ6Pd8ukgIZdt6CWGqjKx9zFixBUXki9pDc6fvAdjNQ5v3sW9Fz4taiHFMNIYFqriOTjm8nkAhgBPGsAKxlZ5bHIsMJ1W31sMVORGKxgrhDd4iJoWCWKRF6WalggRCJhMZ6IkamCUQZRBrtQzuU5IZU8GXC1c1nuL5cLBQ0hm0FJF1FoVi9KIvyE4FnzhNKbr45hZgKCgKFSehJEveRegfLIcysQ2SgesFjk+eOejmK8qFVOBuwApLBcOnArYMOP8yXtIvoyk3sWNWzfx/Msv4ejW7So8N5JD8XAEwCtYU5HCxN0SidRRNbz78BVMjh7i5GSBs9MzLOc5VosCH/zpY3z07pdw49Zt3H7uJdjRERgOoACllSiF8fMhvRcl2lhThpqCGYEZX/zNr4P0/45/9N/8ez2Te489nk3sieEeg/BrX/zW8FyaLXPSLpGgoQpZ870DFje9i210EIa2NrYlL1v2xdiD69vd32Vx3fO4T+m0tpEH16E4DmqvqR5tSc6z8U24Yr62IE6L0uBXm/Piuvq/CdcQrttHvrfyNRyKlv5SVRmkxFALlr42mpszvTYnW5K+XsT5tJYXB0DpLBZpadmM2XD/1/KIh/Zv182SvnPWP59ueYkUAjFUdsj36jb9bLx+2X/28gk6q52W9hXrhLKYn4qxfFSISMdKlnVSqGqhiBKrWIZDSlVLBhCQL08khLJGSBQBo/EEha8UQ8mhE9XQxvBHr2L4ZySI+eIRjIlFb6j6s1Cs5phND6AUMMlifiFHxS22lxBYiKPzgPdS5AbMWK2AEAiuKEDIS1XSGunzzTsPQFSpjnWk6xpl6TOc7BtEwXTOSyEdraBCKMeWSMi13IroA1i7FQ5OTgCUFiLLxTvw/hSr5QKPP3wfN+/ewSs/9ipu3bm9livIDGTWwJMvrztBK/mnxL0Ck+lhbDuDzY6xWCwQeAWiOYgIJ48/wPnpR5geHmN6eBsq+UBSRc45hpGSkfxPkxTF2JkQGP/8X/xR+zzcY49nHHtiuMcgfPFL39l5Ubwpl26tyAowjHQNIRct7w/BQelR5+6596vL5LCPjGJdQSib21A6fpByeV0k5DoX17iC7+I297f+vubxXY8bz01mz5W/e7+CL+ZYXLwdHy+HEcNN7SVccxhpH/l+6rmn1xluuMUmUZ+X4zbn70ScT5PZw+2vsYUcc3CYn0skRTa+Pbwa71AStuP3oHfz1rdubSey5eZXswAO0EECOwggUJGm+ndqCMsyT06paPvgl9BaITDHwjNUEbR4qLwPAJJ6qOCKuShaJpFDYDKZll8zXAsnFR8/EsVQa5AL4EDwiuEdYoXOTL7HY34bEXB+6kCYA0cGY60wHlEVRlonkSJgITCwcgrMBGaNEGIIqg8IXgquGENSvTNe6+HhEaI//BrJSrfNByGGcVRBSrLuQmC4QotqqAnKSwhsCDqG7lJUDNfvHQdAc4AHQMxSDVcBIazKkE5ShIuzE7z+J1/HD6zC7Tu38fyLL2B2eBhDbC0WFytR9OK1p3uglEw0BqDNCEUAjBbVTxsdlWQPQIr9KE0oVuc4LS4u/52IY6u0KavKaiPViuT+sqi9mvDrv/k1/JVf/Fcuz9E99niGsSeGe2xEaVPRRF09S9hykQsA2jRCyLZZDG1JnkaT2xhNJEdFyMIFFhfvVH11cxDpYf6BQ9ruuK6tlMs+pWzIOF0lHK/ltS5ieKmi6yaFeVtyuEUfm9B6BEUaizjs87M3Aby5HsY45NxdbdWv5xpIVVf1z6uiMwyy4zO8vjjkdoVsSPh37WdfCPVW2DRv0fL6Nt8bG7CYv1t+jjfaoKQ+DSWFCUM/H2sqlIc2k3VFVI8wmta83IZuBDSe3xRG22oz1FANU2jjpabScY0XORQwVsiHjpYJ49lMiBInhSuRw8r4gghAzPsLkT0Fv0RmFUy0fdCKMZ5MwaCSYCWLBQBl3iARA1BiyUABRBr3nvsM8sIjXy5R5Cu4QmOZF3jj9UfluQhiLTGdWkwmGkY/xo+9dgsvvXATKhZqCUwwSgNsYkEaBWaD5cJhuVzBWFVV4yRR14jibVMEn6/fBwIAI6Q4s4mMSr6i94ws03BFgHceSks+qDYcq3xSVGDX/SClqE2IIbEpdJPB7KBIlWG3WWaQZVLYZ3H+BN//zgmOj4/x/MufwHQyRb44j6pdLWSXZAJKBdNKRWVIXqVS0vfgF+UcSH1EPFd9qjEhhvhqKTIUx4+DXEueOxAB95+/iX/0P/8zaKvxS1/47OUJuccezyj2xHCPjVizqdgBfQvBVnuI61C4BpCniixUxHBx/nbZL2sPrreK39rizZWLt+RbV8eacjlEKetrbxOx2UIZGOS72Gx/m371Ea+ngBTGOBrfxritsMo2Y3+NfWzzNUwIbgG1rVfk0DDI+L42FZxUVZVw/YUNbTfud9emSCs5vwppGnqeHdF2Hd4tuw/omt+79KsnwmI0vo3R+Hb3+5ttUksxoI750ny8KbSYA4M0ramDqj6/mr6GDcXQ+5WQFV0RQ2MUphOpiKmiApSM7evhi0oRFAAPUTDdYlEjhEIKiYDZ4THAUdVDpRoGliEQhw2SarwEUFCAC2BSEFFuDFIWpIrYd4IrfHk9AQrn84CLZcD547fx1jvv4fAow6svHuMzr93CjaMDKLJiywBdUw4Z+txhOjsEgvj9WTuGojkWiwvYsYUrpLO+dhu0lrBVjml1WVkLjJB5hcJpWOfhnEYIobTjqI9xKh5EJBYdqdqp5CgKOQT5tUJBWWaQjTWyTMEYUfyMBrQqMB6NcOPea9CzT+Ds5AmW8xWW8wKL+QofvfunIGLcf3iI6UGG5XIF0gYhcAyJZihN8P6s7JvSqjVcWq5fSV6h1TBpMyHahBS5ByFuFjDjg0en+E//q/8V3gX8ws/+OP6tv/Xz+NnPfbJ3Tu+xx8cde2K4x0Z0Fp5pLmg61JWN+YW7Lth22YEfeurgUBTnmDyFBSWwvnjj4BFCDufm0bMOCG4pxPC62x+yyK6rLY3358uPOk892Iuyq/1dSeFAYts3D5WJdgtP437vME/bfA29W2Bx8Q4uzt6AsTNk41u7+39u0c/KVFwmxiVCMPT6uD938lJ+6tB+t2GIyrsJPcd1hYKXIepdilyLgrqxD+m4OrYllxteX87fK3/fqKLXTzuAHALr/I9SQiDWxcR6XltSq1whVhdiLyG5cMYoHN95IFU8gdLOIlUZVbXGVFQNQ2B4N1+rNpowns7gI+kpMwAaGyA6msUj3fKoQDVTKAkqElSFEMt4ltdFQjKt1bCGcHJ6gm988xGev3+ET7z6almkJQQNBoFhADyHo1vPrfkBBmZ8dMLwj1coci85gy7AOVHCsoxwfINw/+EthACMakWinSNkVsFbDZdVqiGAcpwTEU9Ko6cQCSuDWYv/IgDvCoA4WpEYZCODcaaQZQSjEMkhwxfLqLjKYAWeIncaRciRF8BiERB8gYvzjzA7GCObnuD2g1lVJZYT2Z5H/8K6ai19Lz8mqlIvTdxEsFaey/NQ+y6T6qZFEaDjZPiN/+eP8X//+h/i8z/1Kv7r/+JX9hVL93hmsSeGe/Tiw0cXl20qhi60aEB+4VXJRFuftlgEbgrpHHKuSxX5tlw0J9+61fJR+fL8/E3g/E3Y7BDj2cPLFhBdIY7XQWzSeVrQp2Rd6V6mdrtQuz5S/eFsXXBFh90Kdsi/avar6zFaHm96vvk2ShUEq2t1xcXW4YutKmB9Yd9c5LbE+5Wq4ZDPW8s4+Hxg7uTQEN4hr18HuWyg63tD1VT+tuI9a49rz3fO4+Zn8SlsXDSjANZU9OmDK20q1NFGCJtFTkT5q4gUsxN7gmwGbXIAUyidI18xDg4l/DAQl3mBiRSWuYqKkJwRlxcfQWvAqKqvzEA2msH5SilMSMVrSqIZGDAE8tI3T4CuSZQpx5AU4AoxlE9qpjTmkY0yGKtidc4ABcbh4RHGtATWvuI1ZEvGYJWHSIBjWGfsY5GHyooEgAoaRV5gOS/wzg/+FN/+JuHh8/fw6qsv4ujGAZgJWUYoHMFlGlkR4KyOvoySi5fyDJVWVWhuqvJquaxKyqsA5gLaaGSjDKOxxWiskY0UMgMYwzAKIGJoYqioPDrHcj9NVISLQrwl43f6xcUKX/2t3wWRwu0H93Hn4cuw40OEUIBDUZLCNrUw9VXr5LtYUwvL2GCUeZ7OB1gr5ysKQrBSlOZ3fv87+O/+x3+Kf/Bf/krbNN5jj4899sRwj1787ld/eKXjN+UXtpKJXRY/W4aVpT9Erjhby6WoYyez+75+dS2m4+9ti80iPwNIdS/829p7SionuF3Jcm6OfPEILj+DSSGOXUrHwHZaF9N94ZBtrzceu57iJpfCduv934Z0bDkPN56/9lpX3uFGW4t4jtb8r77uNSpMrp1WDcg1bLmuooOcXwopvw5FrEu12xW1c3RtMqQNhm3GOb2/lxy2/b4tOsag6PR1HK8TXOBSzikQX6eK3BprYvVQLWGjWghHer2NDKZwxhQSmtqa6QcYTe7AO4/gPIo8YHHu8eG7b2Nx8Zu49/wDPP/Kyzi+fbfsV93oPvXWaMLy4jGMSSQNAElxk8V8Dp1NpeALYn5bJIllWCpJvmHgSjQsC6go8eaDSuGj0Xhda3hfbZ6JYglkRkJerZb2prMDANRKDgkEpTV8DOcEaK3YTGj8zWJmnJ+8ASKGzQwuTh/j239ygtu3j/Dyaz8B54AsU3CeURQa1hm4wovVRySDiRxqQ1BJYbO6JKUcGGyBMJ/DZhrZ2GA00hiPCCMLWMMwSuJwFRijyVhIsJIiOiF6NXJgFPnF+ncMRZ9DpfDk0Yc4ffwoVh+9I/YnLRuWzByPkX8qksH0jxllWGo5ZwGwDzDjWK2UCd4raK9grMYv/cJPXm5ojz2eEeyJ4R69+I0vv375yS125vty0jpJ4Ta4Ioms949S2euItdC2De0MUq56Fs19VUo3qpp97TSxhdq76bm60hlCsR7iaDvUwyHt76r8bCATXZVoW6uT1pWaTaRjyPNtr2+pcG89DxJ22Cyok0hu+VC2zvcBZL6r8uiVN2GGKrVXIYi16+naZGheR6c1Q71LbXmbTwMdXem6J9pOO0lh/XGdIMrCXMMYU5KNRJQkb64iT+UxhKhW0dp5CQqexFqBtZASYoAogEMOgPHko0eYX5xiNDa4c+8eXnztM2uXWiqTinB4fBurxRmYi7Vcwvc/9DBGqpwqo6G0rgqj1K03FEEFhtEED5RhrMy8Hr6qCE4FKO2hnChlpIDFxRMYC2hD0IpjTiNhPJkgIMcISyHYpn4uDaWBxZIAUNnnNGPqf69E1dPgsILNJFzVWIIxQLF8AqNFIbNeyKnLFJzTcIWp5e6J/YeOJAsAnOeyGI2EwyqQ9+CQI5tYjMYGo5FCZgkjyzBKNuoIUlhmMh5HixAqw2sVqUjYzivFFTVypygWKSLky3MUq540gDjHkmJodLI2odLwPniWXMloVUFK4fxMPC0nEwM2UpgnBI3gGZ//mdc629tjj4879sRwj1783h+8uX1YVw2DiOGOYaC979+QH1QUF5d2ypuKYRna9jQUuMb5rkz++hbBVxnfAaj3fWOI4xXb3xgO2YE+c+9LYaTXGR7aJJdDrr/lfvVtHAwiVek8fWHPbV1pqIatJGYLRbXrPhh70NuPjRi6adCnLG+xadF1HbuEJKfw3KH5ep3Y8Xuq7VqICFqPy/6Vz9caKHNOa0WJpFqkgs50WeWSSAhi8AFU8wos1bioVBlr1tRCAEAOBBMQot8eFIO1QlE8jjlxqgwb9H4Jqp23qRreefgpLJcBy/kS+fIMReEQ8hXe+9MzBM+iSoYA9h5KEaxVyFfvYHo4w3MvvYAbN2/K9dQVO+LSo9BmMTwyWmo4r+B1gPcezIDLTzE+sJBgFSoVuIv5CtmBAkNhEubiERhXZlKFVIhaUaAktD4IKQ2ZqsJfy89mIXmMViEzQtZuHR8hMwwXgMwAzipYx8isRpgYUfNSRdKYg6mU5Ga6nOBdJPmeShIGKmD0CEYTbCSFVodYZVTuA4Fx88ZMigJpsRCRmRNDYPOlEEICKFYarYewKqXK3ykSYgaDkAh57fXkS1lTCuVzLWQwBIb3kcSTzMdH78/hnMd4bDCeZjBGI2T6qQTc7LHH/1+wJ4Z7dKLML2wuogaijxQCNeL1NL6F0znjH4f5+ZuYn72NIj8FB6keF3yBbHwDxkxhsuZOfy20rW/ReE2kcatqn0PxFMlgQh9hKVYnwKYQ2CtsOgzCBoUHAGyTlAxR9LYhF9ew2dG3cWCzG5vPWesXcxg0zhxCq9fcJQxUSP025Pxpouv+DLxPvZsMqlKfK2LSf2IGd1d83QY7fG7a7omQwlEnIaw/VyeH5bFKQSkNY3VZxEQpDU8+WkdU5DeRRiGRVe6ZqEeyERGCgndKcpqjksRhBW0jMYxhj75YlgVpLimGBMBDfACNBekjBOeQhwJKFQjeS/GaSD6KwiNfFjg/eYSz04/w5KP3cevuLfzYj/8EjM1AsR1FsXopcSQ0Ct4TCkUgz6LAOYL3AdPDWyCcIfAUzAs4cn8hvAAAIABJREFUb8Em4PR8heODGULsdSKHZFmIIWmpnq2UEEIGJEKVwFwjhvGX0TiDtQxrCVnGGJmAe/duwWpGphnOkqiGXsE5BmBLMqi1glJS2VQRkDtGNtLICx+JngKpIBYiRpc5fCaa1KexFnLIUABmszECAZoQq8aqktj5YtmqElZELyqXyZ+DAQSAiUvTegANMilEnUjCWSU8mCWXUsn8BCRHFCRzcLXyWFycw1iNw5szfPVr38Mv/+Wf6v/w7LHHxxR7YrhHJ8r8wh0Vpz6y02pTsSsGKBbF6gQ2m8FmM3Bw8H4JV8zhigVcPgcWj6D0CNODh+L7NXShek0kZquQ245cu/LlbVWHtINfJvZ3HN/Sbj9hGVCMpm2RvkPYY/WgcWz8vbfwTJdNQl9/hpKLbUhvz+td9iZEhGx0tK52b+rv0H6UamUHYdnyevoM7HVbOO/Qdq6CHc7dtcmg9CguNLfML6wTrKuqhn1oudb6PSmLpADQdlL2ba2vzfDR+Hrqv+QWUgwPlYImVZifLMYpkKiHsT2pIikLeh3VwwSTSXEUkzF4BTF1VwzAQWtbqoVGE6YHE2jNCKlKaVIkmzWAhLkg2RZImGTtGkmBFBBcDqgApSxIERYXZ3j/7e/jhU98WnwRIzNUgVuqrCooEmKnINd6dPNVeO/hXcDpysNfBBCv8PpbHn/tL57hUy+OEEhhXMwBk0hsgFKZkDXFWBZa8hyV8MBgCQwl5Cd+TEfjEYxeIbPAyDAy7XD7xhRBezhDyIKGs1Kh1FoSUh7JYCKEkmsIAAErRTBWwbtQqxi7gtJaSKGuqci1UFdNgKaA8WiERfT+0EZJm5qkMB3CeqEbqsKP031J8yHETwoUwRpdVhNdm39rxWnicVEtlBBZxLDmWBSIqCSpAOAKjw/feYIvffkbe2K4xzOLPTHcoxOlf+GOi7KNNhVDsEV4V9dxTdKltIXSFjYWSjH2CDY7hDYTKJ1tbuMKC9XHH/whmAMOb7wKbYWkrnosIIAWgnXdi+TGYpZIRZ+qy+8rEcdg6xzSxvHXorDVz9fxuGsudm5QNBTnK5OTvuMbRKwNa/YmNfuKfPkIxeoEpj7WQz4vA8M/2wrWdFUx7TsP0E3OW3M8m+d5muRwG3B3Qa20mZTGrK94z5B2nsbnvIn0uShJYfxhssM1UrgxvzC9V1U+c3XVkAODEmELocznToVnknG9NlJVUhHg44JeGyGH3okS5Pwcyij5l7wNNWEyPYgEY+Bw1IrfKK3K6pxixgCEsCyvRSshTflqLtedwhoDl4QsRK8/ITiSV0gBQkKDePExVCRPjEAM7y2K1Vv4v/7FBX77psVnXhrhp1+wuDvzIBOgzBSKAjQYmgwUAYWnMkdPQktJch2DQg5gOj2AgsLYLpBpj0w5ZLqAUx6ZVnCaYI1CZgHnFNhijQwmn0dFQAgKo7GGdwG+YClUQ0CRn0uFV6PAELVUBL3KDzKAkRkDYwx4JTOkXgjGFytR+LSohCAhbSoqhCk0tNxAiN8D4mWpoQ2JvUj5XS1VT6s9Mi7bU0RQJqmSJO+NiqIDoFGpjwDw/TfeHzaJ9tjjY4g9MdyjE1/80nfklx0WKRttKto8y9qw6+KotpjcFKY5O3oJQItS1nXdV1iwaTMGByd2FAAWF+/BuyWUzhB8Dm3GmMzug0gPVi53MZ4GcLXFZwfprqNViWscv037vUpM83y1+79zfl6bUs6Nx0PR9/4tz5WK/ihlo6+hKPud/nO7ku9y/Fo2CfrO3zGvusj5IHW+sXnRGg67y3ze9ngaVnhmU/GeQf1q68/Qaxz4vjUVt+SGCsZM5fdLBvSREHIVQlqSw5hblxb7pBD95KIlQrR/8E6UnxB8mUeW/OmUqipKkgsIhqC9QvAaxkoBEaIQ1aroVRdDSQ8Pj2Fi4cq64buQzLVLFGJaFs1JZE4BkHBVxbKRUfVPSEWRL4T0USQ5DVLIQCSEFDd7KgsL4qRSJjIqoaDz+RmOjg2sITw6XeD3vvMIL84CfvK1F0BgkBavQaIMihiLwkTyqyqFjhUCBzATpsevIM8dRvgKRtohowLf/SFD2yWU8YDOkGUjOANYS2UYrOQzoiSHREDhgawgrIwCaZRKnvcrWCOTVClVzvA0JhQHezIZldMRqIg0B8AXSyFqce7UQ0cTOUyEEQCIIab1NnoTUtUmA2Je3zLnVTxfuocpdxIIAFRi1+W88AS8/V57Beg99ngWsCeGe6zh5HSJN958jG98893qyaZ6MgCbbCp6ScN1oNbXPuUyG93qPn7DebdFG1mezO6Xv5vsCNYewI6OQKSbh1+5/UvoOU+rHUFLP7LxTbhi3pt31XbcpcdPUSHpDXe1h8M2AOqq3pB1/tNSuHrOm/znTHaI2eFL1Qtt7x9CqoaS9wGkM/g+Y/vtC8+IstOYn9c53n1hvVsUnrmSavgjUEg7r6WZY9hYcdcJYnqfFC7RZUGQpP4YTQhawTsuwzc9BVHTgGrBHouTaE0wMddQB0h4qBFyqI2HdxfRvFyURmPlmIPDGZQW0kHtzgbSXhI3daNwiRZFMk0r5xYwWSKFci3j6RTpS6AZYl2RH6RoVTARmKRcCtNl1ZAVQxsWI3YDGOVhyIG9h3ZLMCk51mgERVLoxtTvhbr0u+SIEs5Wn8cyfxu+CPjgLSBfnsMVoWSzo5ECGSlS4917uHE8xfMv3MHde7ehROqE1YCxSTU08AVLSCkXsZJp1RdmGTpiAohhKWAyGQmRrs8dGT2EMG8UjqnlGtbCj5MarQwhyzSMoUhoq3bznIVIquo5mZMVMaSkiCqKOZryN46ZoLkax8CMd97pj+LZY4+PM/bEcA/8g//2i/jGN9/FG28+xsnpsnqhuTjaYqFSFO3eWACuL79wQDhcGxmr52NpO+09vrW9HclMH1k2dobZ4YvtLz5N8lQ//zbviz8ns+fKl71bwfs5Fudvy+PiAmrUKIyyDfkYcN1DlNG+uajtbJgqs+3nYBuFbZvXa+PRRXj7cvnK8zfbGaKcXaHf3g00tv9Rou37rS+slwEfegrPNEJi6yGlXWiSxiGbMYNeH7CZ551cS5P0peuok9q6Ubsyulp5owonNZmBsRomM7Dxn7FK8tOC5No5YlCQ6/YuVWONuWVRTUsqW2ljUPc2JBI/QFOFkKbiJ9PZVAhXUvNioZZWFSmpUFERDFT1Q9pWADsoMlUOnCKMJ5WSSgzAc6kWgteGpVIKUzgpGMRCUlgRWCl45BiNxsiM+P9ZCiAOuH/nFkAKxi0BEAIpsAJYC1FsXE2tyI6C1hLGCiLkq+eRB4fROBVcW5bjsyoYWBVYApifv4+L8wynTz7AD6YaDx8c4xOvfVrsLZz4QIpa5wHyWCvNCpTKpeTsBRgVoFTAzcNJReDSvyBzpigWVeVRCQko/5WkMP4uZFAUYmsBq0VJZAbyoupLChNNuYm6phJKxdLyndJfU0+hqFTk5x7evjxp9tjjGcGeGO6Bf/J/fLX9hW3IQuPn1vmFQxejXYvZjvf3kTFSBkS6fTF2FQWlA31hl9no5m7tMsDYzri8id7Kk5vGuwZtRqDqL6+Ey56/2R3i2NVO2bFh7W5C11xU2kK35ZRSbYH+FJXMQa/3jEsf4R10/i6+smGzZeN507lrjwcb23edekebkkvY9X7G43zRTbq9X/UX0Wk7bZM0Xkd47EB431FEx4xbny/tAZQqq3ECAGmAQ4C2FjazkRBKyF9mRdWDZzCJ3YR3iCqSFN0hREUnhpOWNUUaHn3pJ4cCWptywa8VMJ1NYJT0KXBFCOuef02CmEhg/Wciic7PRSlMVVVj1c7pwQ05T+22Vbl+632lFAZJciyCqIZlO4pB5GGzEYzNoSjIPw64OYtWIcFBuyUypcCkSoLYctfkf0oVReUepX+JWAcfUOSFkDMOgCZ4dwFtNIwRddRoIF+cQ6sAo0U1tIaiL6IGkYPSacOgGorAkFxIxTAUYMjjYJqJihhVQwklreUYliSQSpWVAIBQqss2U7BGwWaEzEj/jBEyXhTp3lVkn4lKpVqIIUqimOYtM5cVbDWn6q4+Elvghec6Ion22OMZwJ4YPuMo8wiB/kXIpnC72s++nC6goyjJAIWk9fGG8+xsA9G2OOtSUAcu3gbl47WQ7F60vL6V6tDRxqUCI0P61EE0WkMc6+d5iotf7ghhJKLe+1+SjqH34ToxkIx3EV5jZjvPnZ2wSWFFj7H90L5eF9o+v12vtzzP8K3VYQGAfQ50qIY79W9If/uO3XDMpfkT74Oxs5KwdYXCktbQdVKrVFQLpeBMIofaaiFFROCYH0ik4b1fUyopFjupql7WupVIIQK8W4JSaGeyWFCEg4OphBGyFC1NRUOZAefTeeRnRR4bSlOtLxxWZVijjsVRlCJMJlWESes+XUlg47CQEJVADNIKBC+5hirZW3gotYQ1CppYKpmG9Xml3QogLSGlNrGclsajckiF9I6UrsIoCWC2CCEg+IBAARwZ5mp+KmG8OlUBjdcCBa24zPlM/4BcQnmtKquYguVajeJSLdTwmIwzzKlBypnhvQOzLwlhqRCvqbYSxlonhdYAmZVxyt36HUj3UBPKvNOyymqcW8wQu4v4u2I5IDQ2aF55+T722ONZxZ4YPuP4p//sG9WDIWRoADaZtQ+yMehDH3lqKhVDq2Z2KJ9le/Wfbf3ZgK2sO3ZQynYucX+dC3ICfN5z77v6+BRJgWuEMNYXndYOnIdPk7QMIFVt6CvulKrt/sgw4Hui09g+Oxh0vVsTrKui43q6qsNKEaA3YOwM2fjW2nfLlcJDd+znELSSdQaUHmbVo0wVbaG0gskMtNaVWpgpWJMW+oxAAAVRDwEN1cgRrYeRMseQwwbRCn5V5vvpsqAIcHB0DK1YIhyZoBAJYNzbCbFWUQhyMo7/5NxVvmBqN8/P1vz1VCzKko0mUCqepz5sjb6uk87YJ2KwkorPSTX0bgljRvBhjNzlKEwBhYDH5zkeHlebDNotEZSCVRocwyihUHofVqGkFEmsFJKhkkEaCa/14ue3muexnwHeLzHOdDxW3j2ZHcHHKrJap38k6m9YlITNWFHmVKxkWlcLRd0zYucR+5jIm1sty7zCRAibaqGNRWbqpNAahlEcvSOx9rcyKaPGkFRM1VQW0VFpTsX3ByYoxdBMcI7L+5mU48//zGtd036PPT722BPDZxxrimEdQ0kRsDsZG4qunfANi+q+flzqy9Dr3XEhdiUD+01tbtOnXRWwvnGpkeki7w5v7AyX7Xtc+71JDjrDPWuPN+YX9uBSqOIVwxAHP98DV8zh3RyumHe+p8ybHHL+Ms5uu37UQVIhQk7XMl4bje0HjkPn/d944IbzbzMfa0jVYVHrkysuyo0xO7qB6cEL/X276qbDFY5PZH0t9BG1HMMW1bCyEEAMJ9RgZhhrYiGYKoTUGCGHIR5PviJ/ihihyfMTOSBaI1b134v8VEiarsia0cDh4az0DSyrgwYhLD7I+zjaJHAAEDiSudRGndgFOLcUwhMLoShFMMbAWgMfSi4joYnUdo44xlxdV8pj1Ery20gxJgcP4N09LIqAs4XD248eYEzn+MrbhH/jzz3BZx8qAAHkHUyxrBiglnvPDTVXUQwjTWSW6t5+OlqAZJLjlztwUCByABmpKhtDRKeHNxECwSclMBItownBLSW01FahnYpYiJbiUi2cZiYWsZFpmiJrmQFXLJHyCssw0JpamCqPZk1SqJMhBq3lcyrEOWGkjyZWVlUqzony/kg7WqVNAC59DoPnco78w//p/8Td20f4uc9/quvjs8ceH1vsieEzjC9+6TvXE8bVWERdOzEc0m4Lnko/ho5VY1w3Vsa8jjZ72r90vvj61ipMHxmnywpdHWvhsn3Ylrx2Kb3Ywb+whkuWCLt+TvruwwYsLt5F8EtcnL0l85kZIRQgZTCZ3o3VI6vrWLuuH4HS2WuVEtsfZGy/a4TCJtK9S0jtpscNdOUVerdsfb4VV9102PL4NrIueVfrhWc2hZQm0iE5ahI+ao2GsUIcUihfYMAD6+ohX668nAiN95KLhlqIn5CZOYxJIZ6RBGjGbDoGwOBYETMwysqkZX5dJAaBGQGMZCNS7i8xV3M3FCCbLDSEWE5nk5IIJvVLxXBEjh56ITGQ2nkBSPhrrILpFUVLegWPIOGdwQtJ8YwzN0ZwHv/Ll05x49YYP/0S4S88DLg7WUITUBafieQwiYIEhiIdQycTQURUYOVNPgAhBDALGXL5IlqKVPYPADCZHMBHxTVwXTEkMK9iVdh1cq6JoSlAU4CCx3h6XParJgxCawWiRTWfUgipvBnWamSZbCpkhmBqpFCBhRCnsY3TQ0htpRJqxSVh5UQi06YBpzGJ4xEJYfLNZADvvv8Ev/of/vf42c99Ev/+r/5r+Is/++lLc3WPPT6u2BPDZxilgf11LcYAFEW/SrdVBcIrKi29ZOw6CWodqW+1/m3ydLxyVca2sbgC+epVYnrO22dJ0EvEUl/q5+8gY519a3l/M9e1Hka6UaVtnrcP17G50oEiPwEHh9H4GKPxcVSk5shXJ1jOPywVBJsdYXb4PJRuLxzSiRZltsSmzYUuXCLnA4ztE8nsUR4vPd/Xj/p8GHp/dryPXYroRguXXclw83hsOL5FAe0i69pMOsN2qUwGqz2nUtVIA5PpGF6ooLUoPloTIleL56jUwzot5PL19TYDuKxiCQAc8lg0SkiK0cBsOq5IDcnCnrimHCYVSgPLyAzSOasQ0upnCB5A7Ge0OzCGMJlMJGQSFcHgmmpIBLCLhLZxUToSVWKpZqoQC9EoMWkX1SpA7BMCAgcoK+2+c8H48lsLfHq2wmefO27cMIBjzqGCieobl8VniMQ7UcZCwXsGeyttekaxOom5d7z2/WjH05IUpjBLYwB2S2jyQvpVsoOQnD+tOJLCACaF2eERAhQo5U6m/ijAuSW0UWvTkohgrS5DSE0khVmpFEK+JxrzUsUkR6OrwjQmhrVyvKdRExfnQsXwXqxJfE0xZC8kPambIMJv/+638C9/64/xl3/hJ/GP/4e/jz32eBawJ4bPMH7vD95cX5QPRcsipMjPpMjI6kn3YXVysMtO/hbYVADnR1kif1Nl1Gux7tgF10Rmgs/hiovesM2NRGzTPNwp7HJ93OshcxtV2m3wlEhh2xw2dgZjZzi48QkYO4M2U5guy5VtsGlzYYvxb3pg9hrbd4ZpXlYed8Y2yvMO6CJZalOF0qehRPcp+rXHnfek9jltqobl4aRq/wg6+glqreJPUQtNDPcM8WiCEKjA8pM7Pu+l6NZ4g3dLKF21I+oQY3YwharZJ3BkD8wMH6RtFZW2pBSFGiFMfpiJJAa3KvPflKqu6eDwRiwmk5QvgJnKIiZEJCbz0cQ9nV8rIW+UCrUohocUoknfeYmkBs9gz8iX72I0ibmCxJJ3eHoOujuD9mJpUf4zUtRnBRsVUUIKuCyT6tLAAmXkMykqQ//LCqoARg1SGBgIXnIIwbn4RpahqkL4tIKQQgoIIDBr2MkhCmRx/GMeHwmRc6sLGN2INlC1vEJLyBqksOmHyBzVSkhIrdaA1bEqqhKVkuN8YKrmk2OCCynfksu8SzmfglyBAikGBQWlGMtV0T5Z99jjY4g9MXxG8eGjC3zwYdzJ33Fhsrh4uzQ3X1y8J3+4lQWzhzZjaDOGMZMy1M2Y2gL2Kou9rmNri6I+tfCpkrE20nwVwjQEV1RWt0UIBVbzD+D9EsHnmJ+/A++XZYyO1iPY7GDt2sr8wj70KVY7XEfXuDMzlJluX7DnquO55fF9c3g8e7C1NcJOqCvgO1x/b5Ecu6HwzLZKX5No7EhsB/cjPu868mq3yZ/cqi91NO/LwPHqUwwBlKphPYRUQg4NlNHRykHsHJJ1wSWQhOolouS9dN77qthHa/eYq7BPjxhqKXl/0odoRRBVwBtHN0QdKseGS3IYOBUlieMEgg+N4jN15TBEVVIBFNuyUZk8OJxFMgholmqndRFV1DpCHsughvJmKRAFaKVAWphlCnFMChqAUjH0IcAXZ9AHE7lOxdDwoOAAZqjVXAhhCFBB7C3IBIzUCLmbIDDFkFHJEfQlyZNx9yUhChJKmgzl4zWMx9N4vAxZ8DEUuBybKn9Rq1SNNEATI7D4LCow9GiG3Bs4lmqpxoiKV+Tzcs4klVKsUGROGSP3NRWaka8fLvvH8T5qFcliipowUbVUDE1cFTGiKiLZs0IIUoU0hZGGGFZLioAg5JCDr1VHJfzNv/5z3RN2jz0+ZtgTw2cUv/vVH64/sWVYkysukC8fl48nMynvzMHB+xWW8w/hijlW0RZgPLktZuhPY6H0Z0HGNrRfx5XyC4egq/0B93OXao/L+XsoVifl4+mB3HtXzLG4eB8uP0dwK+T6FDY7wvTwud3GfEcyknCV/MJBysu22PL43sI5Q0nhdYZRttyPtvlTJ9x9anldnWoNXVRb+hQ+BdW5PG/P8125zNYeXF8f+tD2OdnQTleYa31e1e8tQzZ9KBJCUQlFKayKm9QIXTR9L1WZSAyFaNRM4dv6xgB7LglcCrPMFyc1FYjFjkAxDg+jYhhVwTQAzJUSlkgFkdhbpMIza5VJY3+K4rxUr0QtRMxjjIRJASqg9FvkSPRKkqcIrgjleWECPGnAc2mh4IHSeK9OjtgzOJZSTR58WolieDwdCXP1AbSYQwUhh4i2KZmdQtEIgXUkhylcskEOfZB74BnerWCz2I6WvkxmN8ow3EQKE7FaLc5iQZsYQlqqhozAhAAl6qnV8GoCHxRcUPCBSvLniyWMrRWRCowQqpzR5E0pNidCChHvXdKvlcTjgsqxF6sMXQtrLTcIouKdKrgyEtGN8zBIv0JIcwglKSSlQMz41I891/VR2mOPjx32xPAZxW98+fX1J7ZUZvLlR63PkzKweoTJwQuw9hB21EN80sKgazd+SH+o/fetyNiui7UBZPrPJKR1k4LQ199NpfXR459np7h576dgraiFtKsqe0WlEOhXqq68MdC1CL/mRX/XOG8MUaxjaH82kB8A7dfHAKN7c+GqxvaD0PEd0PmeHszPfoiLszeRr57A2BlsdoRsdAxjp9BmUipqvljA+wWcG1Addod+ABi2OVFXdAe240M7KeyaV7Jwjsb2OhVkSZUvVRlu2UQigM5zDEesCGGIVUHbkML6xHOvCrHMV3NkmYR46uRZCMZ4Mi3/XDTJJqFSDFM+ZPlaxxh5t0I20tA1dXI2G0OpSEpiCCOzFNRRKp5bRfIcq6oGzyAFBE9l3h17LkNKE5Gsh3EyBwS3LAmsFHUJ0OH/Y+/demXJ1uyg8c05IyJv67Lvtat2VZ1TVafPabpt90XQBl4wPPBghBr/AORnS/gBIYTEC+LJSCBLWI0ERvjFD0jwgjAyalkHudWYptumG7V86OM+16o6te977b1WXiJi3nj45oxLrojIyLVWVfepnV9pVe7MjMuMGTMz55jj+8YwOD2N9YUOKMoqlVTBASSRJAUyOcVKJxVbGNNAjWFgbuO9cA7WlAH8K0TlVEHAZDYL970xBkJaab5ZVv3G27MaaUxfJe/hyCNLZiiNgnEE4wSMC9ciAO8NpKD6uILvowzCMawo6uvU0QjswQBQ8I2v/CpdTCkVsZbRtVKLHWrbx9Yt94AxrsEU8rZkw/30AnAWgggffnC/e7Ac4hBfwzgAw7c0/ukffc7/uCKjMKT4OZ0/RJKdXKd5u1f/B2JvMLYneLq038D+o1NabzJNcR8wDbTVN3cxjDv6dn70fvu4u6LrvNcBWWG/IaZqL5a2r33NuCaI7TztQD9HcDJ8gJ727MksjY2+e91rbP8V1vgCGH3dxqyRZsdIs+Mg9HOBzfILbm8L/IYDeAdjNgBY0TNmTnzptcNj729H7EojbR0usIbRpoK3CzWFSlagUAhRA6IGa2ish7UxjdFXgLACfx3f8d46OPhWGikDrQIkksBWsQ/dZDoNKY/UyUA2jx9NzmPKonMMbL0AhIzsJEBCQyYpVEMAZbGYQQb/PEkEFxRPZTh+xOaVmToRnLMgsAqrDRYZVUpprPOrLBqo0d4Egk0IQVHp01mcZBLU8H70qyXIWghrIYVCahdIpUYqU+RahLRRcD1duBfee1jr4JyH1nklsEOBbSUCsmxS23g0+tB7oCw3SETNwPLrDEIZwDGDp7IFSsuA0IRHbUP/+BWrm0bvR89XJYPSrJB1f4ZKyRaIr8AhgYV8PCqmMP5JcnWdJYLfY+Oa6sUJ3z5wGCPkQ22qoMrP8RCHeFviAAzfwhhdX9gzGR7yqgNGsGDbq9x9oGTs9/HWfjvBGI0Y9tf9LQj7j05pvaHzDcbQ5HgMuKFhO4rRpt49xx58vmdcx7+wOv8NMJeD0TGJr30Kh/p5BLAdy5xddVGkj6nair6UxTHgfO8x1GzXdoy4n9tgPAr9ZJPbkGoKISeQMoWQWfXobAFry+pRyhSri89AdgvUj82A2Ce6Fs5GLKr0M/7z+rg9+zPLRRCiDQpFUAltRmRzKlDSEPmw4c2oOtrar5VCyvvoYs21cKi9BYk8JrM5pzB6utQdfJ5QO9fA9NHEXAgBLxkMCkFwLCvK1htSVL59SnocHZ1WwM9Htsrxc3upj2og46wL4JAA52GJAOshJIF8DkAFAEggFJD+BfL8BdKZRJZJZtLIgTz7AqLMw33nIkC/WXOtYZohMQUSWSKTEwhSlXiMtYEtNB7WxDRSB6vz8BFmFrYCiL5+jH/OAWW+qT8+DVDoq5TNeN8J2ewEhREwVkBbrsc0BtAWKPI1BBGc8IDjekQSBJnUJvet2k3UAHEb/McUYgaDTcbQcduI4L0IbGPNUjJArutML+HDMM7J8+NPP3uOv/hLH+IQh3gb4gAM38L4g//ns/0Ysa0o85f9u+xaKR99hqPiAAAgAElEQVRiAa86aWpOhjxL/PeF2k7v2rXyflWGZQRjODg53pfJvcr97LquHccpi7NLr8UfV5UcXX8yvy+D1ZPeuHd94TUZykvPt4FA1/Gp9il0tsTq4nO2PghehWl2cknACbim1co1Pvf79s+QXcOu+sI/ixj6rC5OPup8XcgspGDWn+VsercftO0TOxZp9nqvcd93MoZb49nDgYSqlEgB1OIzDVAohOAUwWAPYAIYiaDQWhfqulyrxq9lZt/02QtA0lkPE83dKUCZ8M/54lYAhgxImuEcsz3WNV9j1k8ERdHIGjrhIKSAR95SPQ0lg5jN+xeTokhLZNesq8FtdV2etU+jRcf5y0+RyQvcn57j5YvHyNavkGuPc+0xTQlzSNwrngOTOyAoHCXUHlOOT+yLEhACVOZQZoM0K5FKjUwlWOWyao9ppvWGv3z9KjBkFMkyCALKMkc64frYJluY5+3F5BpMURwoVQ3oZLqACX1vG8yljcBQAHANcCibbGuwtois4MBY9+B7nEob9mMfRQq2JdYz8GwCVx9FeIy7VOtaAeIAJOPfD370+AAMD/HWxAEYvoXx2//H9680CdblBXTxZnACpdR8ePLZt5q/K3YBuAYTMMRoXgJjQ+3cF5xt7X+t+sJ9wd729vuwPs3jdGzjXLSjWA7e+9H1kh0gtAIHNMAU9fTz9vMr1RdedVz2LRqMZOaMXlYAKqYhNr0KRRBwEiKphHyqc41t4652XCVGjC3TA0C+ElXgroWOjgWE5mt9foujgfgV7v+1FiN27d/TnjHCM1WE/USQoWxOlqWUl0AhVRKgjZrCCAqNqwU/opcgOJ2vFoFhlo0Zw5rd2qxeBJER3wIK0/mchU3AQLCFnUL6YgSGjVI+BoPkKtZQOAEvPKxesQiK4uuSYZhmk1nr2Je6OtZM+lrx1AVm0G/fKO+hiyVm8w0SYfHthxKTcw/z9Cnu3r2L908ziOkEP8kVfvDiJ3j+bI0Pf/kjCLiavmuEfX0OlWWQZY402yBVM2TKIlUSm4Lvg7WANdyn1lo4Z+EBCJUBlMK6BM4ZOOexWQPppP6Kiadbnte6As4DcOAayjBQovJrIh1mswnWZahzDMI33gP5Zl2xkADX/jmBYH8RfSOBePb649w90LXlFGJDop1iGmo6a7MVBq7W8lGNcTBBhCdGVCCNyjvR/5AI+K2/+w/x7ju38Zf/5V8YGAWHOMTXIw7A8C2M7/7OD/rfbPyGOaeRr55UYgz8vodK55Ayu8RkAEA6uXVzk88rxI2luQL7Tbo6JmlXsswYe/7Og/b8e8z2W7Fefo71xRfQ5TmcCx5O3mMyuwsps0v3fa/J/tZ5RzNGI/tjVH3hPpPqsXGFcd81Sa+8Ck8/roR8hEj3v7/XiR4mdtfCQ+VpWS5hdHcd8ldeX9gX25/XvnrIMam7Hcf70mLs90PX/TH7Cc8A9eeTAZmvhVwEWqBQSrZjkCKCEV+DEccqo7G+LYJB79H4d6w/tBVAzNevUWzOUGzeYDqfhNo9X6UcZtksgA4GIb7BGpoACo2pwaEI/oRE1MkaWpsjSZgFjUByMp1W5+iKWCvpHF8zeoR1vAO8iBScrrz/JCzgLG6dLPDL78wgphPQdIJfyWb4S995Fz6dwCQTOKtBJCCImCUMX5tiKgCl4JSCFQmcZxVQG4BQZAsZnEc1Uof50TfgnIWzDsXGY71y8NbiJz/+DLdur/H+R49w58GD6hpX5y8hJdUppiA4H+0kOFi9NauUQQvdUEa1QL5eoelRGYVhov1FPJZoHDSCyOaCgPcIdYu1T2X0naQA6CKYDLI4vB9FJtvBaluzuoR6mwAKUZ2X8OTZa/z1v/Ff4zd+7Vv4L/7zfx/vPBhhv3SIQ/ycxgEYvmXx3d/5wTDb0HgtXz2BLs8rMQbvDIzZwNoCxeYVivBNrZI55kePQCS/nEnfHgzktdJcO47X244hRiBsdyXLjOtMLq/KQHScXxdvkKRzpNkCzhlYs4E1OXR5gcK8hCdWIZ3OHkDIdJwgSs+5Lr1Me9oUbF13V7prjGphYBezeh3QuM3o9Gzfpw4JALPFo8sCTjdxf8dGV7t7/r1ZPYY1m+Bp+QWnwzaiKcoCAGl6RWGqfa5/CDz1gto+Jm06fP5978t2lsNVjnHFfYwdSCPtOZ5UElIqqCSBShVUoqCUhEpEAEAejliRUvoItoL6pQ9+cc41xGe6QeH5q0/hfYnN8hWKzRvoYomyXMM7IElnsCZDlj3grBQA09m0SiF1FWsY2CnE2joGJdrw6wxqozpmzRo64YPthoZSqpW2OZnOa4GVLXDYwDgBTPgqXba1na871zsLQTYIpjiQtYBUePe9B5DHUyBNgWwCl81qUCgSgCQDpqAQSyRAECAp4NMJrJpAiwTaJiitQFEAxjBYNbYG5pxC6Qa/Y7/47As8f/YMk1mK+w8f4G4FED3X7jnAC77X3vNiQSo9lHCYz2fB35CvuRIj8sB6+Rox1Th2iQgWHk0LjKqGMbSHGv0MMFNoHEGbqPAagCGxmqj3VAHDuBsL4RCM8eGPq0Ob4j8xjTSGIAa/Mf6v3/8T/Ef/6d/D3//v/8PevjvEIX7e4wAM37L47e9+v5707Yht5VESCkl6hARHUCcf1WyGTHmDrmMOTV7Gpj72vN4SfjAlnMt762eAG2Aq9pyUDguIXKNObMd5rxUe0FtMj5AKQh4hDUAlSY8h0znSlFdNr1RX2DjfXpPtxuveWzhbhjHA48C5sncM9KrA7jvB3gJNlxjPbVBC3X00NFal+nPAqo0Av+xnWqeYNQFgkt1Clt0GiD+rF29+BCLBDNyOPu8cUzfF8HaA3j5QSERQSUftXbOdXSB63++zq3x2r7BPX7psrL3uYu+FEJAZK5EqpaASBoWJkgwy4CFi+p0juNAfPlhNeOsqBcohplAXS3iUmM2nOLk1R7G5gC4vsHzzCiRKEGkUK4fp5B4W9z/EdD6BcQRUoA1V6qIPbJlugMPoLSgEwQvBoi2BNRSOYFwJKev6xVDOiOn8pAKFHt1KqjFqwZaejZyHRcHWDMTG9U4m8GmG2ekpMJ/ASwmfTuCSCUw6hVYTOJJQQkJKCUkCkgQgJINCqWDnx7Aqg0aGwkoUWiIvAzsWGTLjWHTGWlhje9vo7BoAVfYeF29eoczfIEmorSQb+pxASIMZvRIOD+/fDkIwEYAHwG491utlvT+hsgNRgk3t2Z7DV6mf1Xd9o33GMlNoLEEbtrcQAjBEoQ62LQgULzPXAmXpYUJfeOdbViH1Dazbx4/UYhS/qrW5QxzizyoOwPAti8qmYsekeMiOAmBLilGpg/uu8He0J18/hbMlAwFnsFk+Dv5oBKWmqHJqvIM1G3h4CKGQZqeQMq3SHiumYlea3A3ErvrCLwUYXicaLEa897XnF8/0PBzmRx8gzU6r2qBRxxwCYSMmz/n6KZzT8M5is3oCo9fhuanTXBuRpIvAXs9aiwGdKrAjF0k6r2uP6GJBTU/aMwkFITs+W2PPuQ/Yvs6496hTzDtitqhNoaWa4Pb9X63fvOnZ1b7H29q+K42U0w2HPSNb93U7o2AHYzyWWd4rdpyrb7FqiDEkKSClYmCYygAMJQMHKWLhVgANvrJwcM4xo4eGVUXDSJ73ibWGDsZwGid/DxEWxydIklv4+Bd/Hae372C+mGM2zYLhPFsUjAGFLdZsW0I0XqOgsFDDiFDKuiOyCTOGLpzHtdqPwFT6CjTFa4zAqpmiCADe5pUBu4aCkhmkKpHdugWXJHBSwokEVk1QJlNowWPQkYByEh4ETzLYXjCI1OkR8mSO0icorEJhgLJ0KEsHrV3wMAx1noaBYV/o8pxr/aQIKcNcc8kZrHW/RBCcJpw2qoSDIoflJsXdhWNGNKSIRoGeMl9XqqdK1kb2MtxPKdo1pK3vZkKlcqoNBaVTDyiCsLUPo6CaLYzhXACUxiPPLXRpuB52615Wp2r6XaKpaOrx7/7V3+jtu0Mc4usQB2D4FkXLpmLHJGQIGPYyL/umRnVNhjr2KTYvWs+z6W1k09sAABVYS6lmUMmsIfe/Rlm8Rh72nc4f1rVCX8aSX7iOqsaqZ2Ue2AKFV50M7su07TpOA7hdnjzWv5gymbVSbTonxTG6xkVXE3yHQXrjeGXxugLZSbpAki7gnYG1BTbr55cAuC6XzGKTgHMOSk0wmT9gtciuuMZ4uLKipu//jLUA7FXGxxDYvuEFkD7WsxrjI87Xef97N8bNXMfW/ttMWpwIqrEp0l0LDLvG//Z13DBo3z7+kChTp/AMEEABi8zEFNJECSQq1Lh5D+8FW08QQYb8QGs5hdRbB2ebbCGqBaUmY8XWCQzKqkk5EabzIzx8/1tQigGEi0bkjgFAvNaYrljZK/jLoDD+uwZKFka7ik1bL8/qAwAB1AFpNmmBQldvwv9ugMJ4Xc6yymnVj0QV4FktzzFRHqUV0DZBIlNQNgMWpyiEghcSVigYkaCkCTQSEBwUSXgpGPSQAIgtQ3R6hDydY4MpCpegNAJFCRSlhzYeRjsYbfk6rQ3iPv1Dx5gNVMppmTJYdkgZFkoimwoeV3fe+RgivYvN8gxv8in85jn+5PcNNssnuHf7HO9+8AC37nEWwWa9YkVYQpU6yrWpbGjfBIXN+sAYzlNIC2aAZwzbcBBFtjD0MYlLn0XjCKVmsGy0A4jHNd+v7UFf37MWcAxPfuGTd3GIQ3yd4wAM36L4gz/8rH6yY9IyqDw6wu9qNGjZASZ3MZfz4w+32jaDUjNkU2CODwb3HZyUjQznNPL107ZQS/il6RNqSSe36ydXnfhdt997tne+Y/IYfhyFTCBEsv95+5jDvv0ar/dNZkkoJDJDNr3PNY5b/nK9bRkT29uOZTl3BBHBmiIsHPTXn6ZZQ9jgq2DWxvRNTx/0pWB2LsLsC+qusdiwM7YZw8b3XZMtkMli96Eia9jXpqFFnD3a2Btd32ONx+ZiWVfEz0slMtNghaIaKXsWRoAooEJaoRcC0rO4TKw/s7ZOGY2vb9cXAm22UJdrJuuAKo1TEHB86wEoME5E7B9Ys3TcxlhT6Bvv1TYJbVBoI1DUFta2AVORr6Ckr1IfvffhO0/VlhQReLru2xevqfdWeY8iX0FkHmlCKJ1EIhLIeYJNdgwnFFiORsJBQHuF3KVIyMILAw9iRpEEEhIQUiFP51jTHBs7wbpMUBiBvACnTGoLbewlcDiUD+uhIWTK3oLBz1E2LC0QmTnhsTi5h+XKQbsFrDPYFMdwNoctc/zwB5/jpz99jHSS4O6Dezi9fR8EBoXM+lLF/KpYV8gkcONnos1Q2oYwqza+FiIKbKZwoYFbkZeEomAGlQSQJLJSHY0Hr1KNiWp2lxqLGOHvww/u99/gQxziaxAHYPgWxd//H//g8osdk/dOcNCIig24CkO45/u66Pck7E3HHDrP9iTqmsxDvn5aCbUk6bwl0JOvXyAugUaBHqmmw7WON8zoAPsdb0jRU6rZ7vTRrvN2Tea3GJa+OsWh9kznDy8LtNxEDC1ebMUutss5jWL9DLbyKvwC1uatbaTMMFu8W4n4jKqFvWmm+QqxLTLTjE4xoq7PXXjcu6ZwV+wBQgeZtBGM4c4a277vyauC4x3bb1Y/w3r5GFpfwOpNlW5NQmE6uw+VzFq7DF2jECKk1HLtllQCMpGQUsA5H2YQPP6tcXBEEK4WYHGOVTB9S3QmTLYDKPTOo8zP0UzZEwGFTGY1MI+gL87Rt+vIqvcjeOgAhdowQDI61to5GG0YMJU55FS1zpNmExhXp6g2j+/RMI8PXo18zdFmwwa/Rw/has9HXeRIBKEsBUopkAgFMVtgIxawEKwq6iWcFzBeoLQSXhKL7AiCIwEnCD5872wCKFyWKValwsUaKEIKqYl/xlZsIduGdI9ZZwtuZ2DUlBKsPBtJSvBPmpQe88UppKhTg12859ahyF8EURpmXc/PXmGzfI0kFRUolJLBJRN37d+VrjVE5ymI3YSFAvBxEICcsW1Q14yYdsptF0E4x1cnMKH2shKiIaBKAQ7/8x44OZ7j9OTPQf33IQ7xJcYBGL5F8fDuGf5483/j6bOXEFLhzv2/CGNVRxpm/2Qc6AFkNw1mAAyl2/W2Y1fsMenvjcav1nZftQR6jj9Ckm4J9Ow43iDYvgqzMxAt8Z5KxKdmFbbFCZKrqkn2RfOXv4dZHLr/o30T47n2ZaxiXANM5esn0MWbqi+n83q1WaVHSJKjy+NjiGG66esYO1ZcCec0i/y4Es7qwTF9KTWxyRBf9To8QKIG4d4NsHRDiz9bzwcXQ3bUGO4dNznu4vtbn6OyeA2VTKGSaWCnVyzSZHLk6+cAUb1QJSfIZvd6mso1hCpJWPREysDyEJKEa7xgACcB8ryt9z7U+tUppLUiKYORCAj53zwwdLFGJfIRHgXYjqJ1yb5OJ90GAJymWqeRskUDLqWP2gACmEHjR659q+sgo2Rmkk7DsdrANKaTWte0qmA7CGscPAI4dICw0e/Rw5gS3js4H8znPcE4gWR+Dys7ha2sJupHPh8hEQQLgVQYOAoAERJrO8FKB1C4IWwKoCgcjHE1EC75T5ca3lr+7DTCOQ0hEhBJCEGsRKtEYA057TMyhVwLCNy5ewdSCgjhKh/HCIy13lTiPRHsu2AsH9cWZRCcGSLam/+oFgRcBHihrlAyWyhDBqlprvGEg5clH0QpAedjfTyFelQPW/AYrRYnKLDl4cRxTHz4fvdn5RCH+DrFARi+RfFf/q2/Cfytv4knT17gn/zeH+P3/uB7+PGPf4onT36MLx4/x3JZgwJrLdLsCKAM0/k7ICHDj8aOIbMLzOwxmb22J+GYGDsJb0Z4PsQ0AEGgp0tEZPu8Q+fZl2Ho2KYp3rNePoHRKzhX8jXYsrUte+YpZq7UpJUGq9RiuKbwqjHALPYBw2uZpO/b7h3jd4g1NHrVq/43X3zQ3ZYxYKdvu6H7suO6N6vHyNfPYU3OINDpyoZiO4RIsDj5EN6ZS6nSQmaX29FkiMdcx4j2k+gQfhnzOdoKXbazEiLTsUt45s88Oq5r+/MSPTEBQKXHl5Wkew/NB5UyePoJBParZpAEAV6EukJJnI5nwfWGtraoiDV39a1yjTpDfs3anAVtqPa0y6azS+1yvpFOug0MsQXWPN/LmD4aawqZMaxBoTUOulyxLcGWOE42O0bMvIxeiBEkOo/APPqQuuoDGHQVO+qsh5eAB9s68Hdv3fYI+tLZEQqrakDo2I7BOr4P1hGcIjjv4CXBkoATXG9YWsn2FJpQlECe20baqKvSR1l0hoEbic+wuXiG1cUrCJHCOwcSEyRJBpUdQUoDpTIkiirVTyIfxGI8JHkcLebYWFSpnMxIhj4wJVTKwjuxHwBAOg9nCU6GVGB5mR2k5me5fggAnIGmCPWIsU4xAsRm7WczuYXZbrbZEJ7HLTO+HrbgvnHWhTTmwBoGVtFX48If6gsP8VbEARi+hfHOO3fx137zr+Cv/eZfab1+cbHCz754hi8eP8cPfvgFfut/+OHVJtFDoGfECrguLqDLc+iyX/GQhIKgGxi+oT3NiX2rXmigvUNMQ6+yJLAfWL4m+DJ61RLvySbHyCbHcM5ACIXl65+2lD2tXsMR/8LGVWSpJpjM7l+e6He1fw/A6J2D96ZSGPXOwnkbXjPwHYqjMcYKtLTuK0baauxaLOh6qyOd0DkDZ7uvIRlrmr5v7GLgBu5Vmb+CEBKikRJNJFB2AEPnNJZvfgoh0zBGppjOH4CE5DrUIcB7xcWiQYGaMWC557xdC1Dee0g54fs6lrnb9f6+iynb/bUL9PZcCwBMF+8hzU4HT9dc4PBgU3BTGpR5CakEklTBGAmjHQiCjcutq+0QXM0URgDCqaSRPavVS/mR/2HKDUAEIWIaH/9NppxGGgFA1U40hF62PnYRHHpX1zU657AtNBNBIaeRWqwvngOw8F61VDEnkwVMQ+m0TicNQjbBE6+VRtq47siYCisgpMfy9QsIcvBeVODFeYJKFyiMgPVUAUPrCNryrbWSVVGtJNgGe8jAMoLJ2rtRm7YliLPcLjgPXTzDZE745rc+ROqOQZufQW82eLVZQzuF0r5EuRZweoajo0+qlE8p2EpCBGA4nU1QhJ9AIUR1Hms0PCx8mF7aiKhJNO5J8J/0zAx7EAQYfMYbGXFdnarKTB57JPK+UtQLCc104npM8yKPDKyidzElle9faUKarbHcV2H4ScnnqgSTwiLDr/3qJ4OfoUMc4usQB2B4iCqOjub4zre/ie98+5v4N/8N4Lf+3n81fucxYLBnUsoCLs9gzQar80+5dsl7kJCQMoNUEyg13WKvRgjgXDGIxHCaWoihNMfBOrEeBrIVN3RdfWbvQihM5+8iSU95cl8Jt6QgklUjev24mrE1OQWixYRBvn7GbGUAfc7mFdO6qzarryYKGCfQcmXF0B1McSsG7tPQwsHOtNzr3P+h/XrA/TagqFOigdniURgbCYRIKzC4i3UC0A1qxvTryOiyAbm8ET90pcNG5rwrVFct9cDxAQyPm6HtxtzvocWjsH+fSuyYWsmqKc5XAjTeB9ATwB8zbr7qc+fC6+H9mFJZg0EGJNa41vHjsQFA6zUvRIWvmihyMpmftK0L4v4eCBgT299OMdU0gq5KhMbE9jMYNNqiLHJslq+Qr95Al+dIJ2lgjeqTynTG9WsmpEJG0OmDsI3xVcqmC+mrVU2l9xUgFkJCOIcyv0A6oRZAyrIpSiuhgz/fNsgjEWrkpIBRnt+XhMS7AK6a+4T+bwJz5yrmy3sHo88h5QyCPG7dWuD2nfuYr57h6MEjHN++g8mde9j4GX70syUKN8Vnn/4ESjTZQgdBHqZYA3QMKamqWXTOwWq2/SAwiwhIAA4kiPtDejhPQLhXPrDPLuxFl+5ssAqBhxS1l6LwARQKFj3qisgmugAkvfAQHrCWUJY1o2q0Db6GgEhkbU/h6n4DDoqkh3g74gAMD9EZ3/2dH+y3w5jJXs+kNAq4ALVBdlPEpdi8QhG+qNPsFPOjR5jMH1wfUF2Tqbvx+scYNwh2B9Vl0+O2Qup2M8aAQqBzkhtZShkUQysGCr6ljkiNHZs2GEIokEhgzIbr2VSG6eweENKZVTK/DDp29NsoEFE37Nrb9YFyIKRBj2H1xrzftf2YMdTYZjudshlHpx917zvmPH1gcAyrubXNGFuL6HmZr57BmA2802EMdQNAXny416ke3GJ14/VeFbzFY1wFHI8Zi6G/+lRix9ZKxj5ugkOjNYxWMMbAGAltZKUIGmu+mmmL2yxhZA8vnSsgwXz1pvVdE/+ZZf1gVvfb8NUAKTB5PrTl1dM/xcXrL2DKApvlK5TFBtZaCJFgtngP3pUQMmOlS0FIs7q+0DXAYPQsjKCwqfgZWcLanoNTaI3VEE7AWgP4JBwzsIWTIxRawASGkG0YABPAoQhef8ZwSqlVDHKMC4I0kWFspLw6BMVX51usobXBqiERnH4JD0EOH//CJ7j34D426RHWNAfsFA/eu4MXZ2UFOoXwEMRsoSSH1fkrpMfHSBJClkm81hcoNucAZYD37cUACLbvIDDyj8xrAHQOrD/K7CHQHPQRpyvJPpnOART2i6DQx/0CuxfZRCkD6IwgNFhelKVjUaLAHjtr4T0glUQzfPU/joMi6SHehjgAw0N0xm9/9/v77bDnJL0ZXeClKeKSnH6CJD0en363zyTOoyVocfbs/4X3FvPjD0AigfcWUk4g1YRrr6yGMStYk/cfF9cEhvsyCT3hB2ogr1yjN4JJ60pni/cTAGZH71fnFyKFEBIkkgAGVYOx3BG7mKjrxL79HrZv+lj2gXIhE0iZ9APvfcHHDTCLfW291jj+M4joeSlVBqkyGL0CkUDRAwy9MyiLNxAiBQkFpaaYzO/327JcJ244s2E7rOsGhYO1kiPHeRQwsWlg3cBMlgA12ELXSCF1FVCq0hiByyn7AEy5RiNJAQBP6rPptFNhEqjVQFuXUqUcemhdM3k6pAsaU+D49ASzmUK5mcPqCxhd4Oz1Es4+RZl7pOltTG5/hOl8hslsxiArgMEIDK2NwJBBYWUH0VD+jCb3kW3y1kObDbxzMNZVAMc5YDK/hdLUoLA09fVF3z8hWAAmKqQ6Jyo/xwh6IiB2NrKXzbTWmFpasF2EANIESKSFh8BktkCppihogsKlKIxCrgWMTxmkUjg/EQvpEPDqyY/x5Hvfx9Nnr3D26k2wgzCQ4ggqmQJoZ3o4y/2lpIBXNfPHgJDTOyPx12SKm0tBsZbQeQaSzTrCZhqpCqAwUfyK84AjTkc1tr43kWE12kIlMpyb6t+WhoruQZH0EG9LHIDhITrjn/7R5/vtMCZdqiOGwAvAIGLn5PQ64IDqVXJTXkBICUAiXz+B9x6b1dMgy09sdh0nNt7BmA0AjyRZYLp4yMCGZH+K3VVA3p4guxmXFFMbv7bNVNfRLFpsT7Vjd7u07mefZotHbDHR2HebBbpye24y9mDs1svPL/lYOqeRZifsqxn6ujJNT+aobuzYRYyB8+/d/q3o9YokQtpnBzLm+Fdl5Ac+y9usYXOsdH2XRPGV6aV02Dotdmdbd7X3Kw7vbUiD1Y2UWA3fU8/aSiPtGm8jmFkfVDxNaVEKAok66Q9AZf2wzRLG55yiKQBYNA/tHWBNDtVQDpGCkKQJlFINsNeuM3S+9rFr9w1va4xrpI4GUKsLJErCWo+jk1MsZqeYpg4nt9/FdH6M+fFdlBbQBihKfmyCQhOFVVz0QmyDQlPydTdTSKOZvPcOzgpOrfQK1vgADgnZ7ASFDumilhU0dRDM8WAwpCTXYFoXlTQZPEWGML7GILiRPhpZQ+/grYN3CkIKJEoEZVeClwLJ4giFmqF0KQqbYKMl1qXApuQ0YSGosoOwRBAQ8ADu3JoikaaOmTYAACAASURBVKdYTAnPnp0hmdzG67NzaL1CkTsQpZgfPwr32gdGr8EOOwAiADwixBLD+qfKs03G1uevVVNY0YXhvaB2qqSHEqEPPcERUER12Qjcg7ysVBJEovUbuc1yH9jCQ7wtcQCGh7gUL16u8PzFsvvNsSAlApodsbc1xgjG6qpRBrGb5g9XTG0F2MdPiAxS7TBT72vvVSf/zUmbs/BwQRTDwXvLr3kL55rCLaY3rQy4IeuJnlTeoXt6I0qyfXGF1MObiE4fS5OjLN5w2iy9RJIsMD+O9gA8wSAS8Ohxyh6KGwYpXbWQcYIkk8XuFNy+74Trgscx0dh/aNx1psPedFvGxMhzNGt0o0qsDWnV3nfnUfbV5A6Kzoz8ngZCSqlRoEC+RvVGrh1zlSplVHisgaGDt5aFRUIxWZx/G1PUE/vARgkBZJNJOEfNBAIBAIUJfbShaAYDwxq4xTTPIuffMxfqyCi4qb/7/se4c+8+1/eZABqiVgragIRQ71cJ7oR0RL5eFjHZLD+HII18s0S+fgprSuhSQ4gMgIMzGZR6AOcUhErhfAptmC00xqPUDO608RVbyCmlHlISjAZMIqrraaa46pLvg6+YTlvfB+9RFo8xXYiwIApYEKRSsNkChU+R2xQbrZBribwALt6smTEUoR0OcIIFcFhpFZgtjjCZH+Hbv/QruPPed7DaAK/fFHj5/DVevThDsXE4f/WTy/cpgsBYzk91f0dl0pDNfIk5Dtmo9fHC/0Sog0wUoISHErEOE7CGKiDpqjHnASJIKUBSBPsN/ovgOp7/UF94iLclDsDwEJfiD/7ws/4395k4jWBd9q7Tuyq42jEh46L8fmuBQeZyexV+DzAYJ4DwFpv1czhTMNjzFtaWAfyxL5Z3A4U1WzFUOwXcUA1kR586PzJ9tbE/S6UHNcQmANl3ov5VsTqN82yP3yoFOj3C4vTjlj1AL0jd1e6h8dV83tdfXfepmfLauIbmirmQClIpeIc2OLyp9N0rArE+yxStuxU5Bz+3fZkO26/t1cCO4+2ZUaHLCzhbVDW6Rq9AAIqBFHYiAaNXsLZspcS2hLCuCuDBk2Nd6Fb9IYNDfp+FaGybLbMepjKW48+5oIgDBWy5qtogBYWUSUI2nVUMYZcXe0yfNNq3mJ1mzaNznpk8bdgnMShUxjYTAZPptPIk9I1jtLpHEKPR+DxcsLHRu9BVjKkpN9DFG6SZwvGtGe698zGksHj04cf4/Mffx+r8NS4uXqPcPIGd3MV0dh+lYXbSaIfSREDroY0LxvLRS7D+M6Emrqp/dDWT6SygyzWKvECxWaPYrFFuVijzDYxeYnZ0CqPZS9F7QjqZo6QJCpthYxLkWmJTAJsCuFiuYYzntFURbCaC9yJnWnJ9XyIcHj16iFVgPUkkyKanODqdwblXtQUEIohjxs6BB4MI318VMGyCwq17vz1c4/tCAFJ6JBJQwgW/RQ/yLDYTMkMrFtUG5RvBlCyEFNy/UkAQwXtqfR/+6//qL14eiIc4xNcwDsDwEFX88Mcv8b3vP8Hf+W//z70mmVeK8EMwCAybaWzbk9990+maK+Md+w1ZCwAjgdQeQDRGrIkCAKUmgJrAOwNrC2i9Gkyz3Q6pZvBOMwAhCaPXsKbg9FaVYTZ/AJBo1U/tlbYZY2ByO6jE2ccWUk87rjLOOljDoffHHqcvhsbv/Oj9EScaEdusTh9jPpS26YHN+jEr/158XrNrQf1XyBRJskCS1qI4KjkCwB52vpmyd9XFma52XSe29u9jDNW+1iBDLNrY750x31MDx9lm+/tTYvdQiO1qf893oo85flvBqZK6WuSgAFwABIuINksY2UMgqMKaAs6XsLaEtQWsXiGdZDwZl5ExJCyOalGsWEtXtcHWDJnzHqW2FcsX6+libZ0pOZU0X50BcHWbw/Wm2RTOUSWCMqS3xdcaDhM2jMxoFDHZrJ7XLFP4zGRpgjt37+H+O+8xOGn6GIKBVFQ6jW1wnkVzrCBIADbs5yQgvcerpz+BFAVW52+w2aygiw1WqyV0voE2OvQDApMbfSQdJrMpjJmCRAYfFE3VZIHcp8gtM4XrkrDOgfXGYvnmVajDIzjFNXrO+4ot9J6QSIdEWsymGdarIJwTU26NBVFadzo1fiJ9nZ3jI4sbQCLFziFqLdY2GVx+marXpahBoZIeihyIPKyTFYiOCwAusItCCZAOdZOBLSQRFg4ctzkuJPwrv/at/sFxiEN8jeIADN/iePrsAn/nv/tdfO/7T/HDH79sv9nHSIyIzeoLbFZP2czXlrAmD9YTLOIi1ZRr8kjBe9srNtICY9uT35Er750TtI7th60FdqSz9k3Ud0RffSUJBSUUTu/crUVZSLFIC0lQeAQJrouAAAk53A+IK903SKt1LN12Cs+EX/NL/XhVgDYGJPUdY+zl75rch9f6RVsug5Gh+rje9jbbM/T+riD2KQSAyfQOaHYXzhlYUyBfP4cxF3AmZ9n+7KRW/m0eoi+ltAkutoHGDQ63oRiqVd5p1dB1n3eA7M5x0bX/FRbXhlLAR6XE9p1r17jabodjiwEfLCgUCXjiWrlmrSA5ApHAZvUzSJGj2JxhdfECzhqAMugihy7WAcxZNAU9prNbUOltCDEJKXwEIYGjUwaGERNs1xc6Vyt/soG9q70LG4qoznkYbZCvX2MyS/g4AaOohL1mrWNCsAJmaANRQm2n0OrawHo1U2d1sUK0ryVBkIIwnabIJmkNTAQqgBg/LyQIIhTYVayZDN6AnsFgExUV+RKpzHHrhPDu3Sk2ywKff3oGI30Ab/w3mR7hYrlGojKkkwkmkxTTiUWaLfHO/Q9xMgfeee8uCsMppJtSYJ0Dm9whX1usLi4A74LyKarjIrCsifRIpMXRLOPUTRlYWbBgkbWO2drwganSeIN9ROvj4/n97YLCOAaabGITwHO6rYcSbVCohIXxonGMegGDUD/nvqcaFEaqMgLUjjYd4hBf5zgAw7c4/vZ/8zv4h//oT3Zv2JzkjACHZX52yaaA62QMytUTAECRvwKBKgGXmPI0WzxsC7jsywyOiY7th6wFvixlxl31lYuTgUngFcBDNPvdeZxd0bcPAcb0C96MqlcbE3ssUrS2v8Ikvdp/ex8A3vaDEbXvmNkHvI65ju00yw5mUwgFkSrMFu8hyU6gkkn1ueuzEdnZpq9g/sQ+hG0/QtujOgoMWDV0gbjrfN8M7bfH/TU9XoRftUKsD4CAiECeU+8kBLwIzJsPiwXwIGGh89eQswQnd27j4Xv3oMsLvHryQ+gpAXSC9SqHUFOsl0uYQvMC2CSFlABQQqoUaZrh6OSoSiN0VVvqdkWFTfYoZIZQF6YFBp110EWOYvMGKj1q1YoFbIhJlsEGEOU9VcCtL4QgeFsfh9viKo9HayysKSCVAiiI6CSEo+MF5HZarAc3xDXINEEg8He0IIIP9W+uo03WbECKQsqlx51bM3z86C9BphOodAqZTDGZH2E6O4Z2EsYJENhugj0JHQQ5yADWNlqiMAK5BorCI88tNhuNsiihVExXpUr9NILCVFqkwmIxzyCE43MIQl64StFVa7YpwvbCpEelQloBZKqfxtTPWNcJXP7oEPlgeO8rYBpBIR+IayGBWgW1rmWNf7wgQeF5RJ4OkS3ks/6T3/8T/OZf/Y3+AXKIQ3xN4gAM3+LYW3l0RAzVXAG8ei/kpBJuGRRwuYm01YHJ2BhrAaBDMGVoBX6PGK6v7Eh/uwrztSuuwtr17NOnbgng6vYYu5ibmzjOFc+9DYKbcUkJMk54vNubudkZI47XxeTGmB096jjkiM6N572phYXG69GP0DvLysBmA+c0hEjg4Svf02akk1tQatKqqdspDtU87wiGuBX7XPcenzPTc6/2TondPm/f99bA95h3Hg7B9J0cT+RtBISAFw5EgClW1TEI7Et3cnKMjz7+tzBbnCKdP8By7XF+YbC6KLE8XyNflcimCaaLCSbTBLOZwmwqMZlQVffXjAjcojG8r1JGGZydv/oxzl99Bq0L6GKFfPUG6eQUKp0hTVVQNs0QUxrTbFaZw0fbB791XmqAwapPKrN4H9oVhGfKuv5TSgGVEJQEjk9uQ4q6k5tqmk6E/ozni30owF593l9K6DXlBiLWSQZgJ8jho2++h8n8BMYrGKdgvIC2IlwjYKyEFB5GeEghKrN67wnaCmhDKDWrvZalQ1EUsFZDSlnVdDoHGEtIlUemHBLhkAiDu8cZFPlQ18cqqgRWqzVlt5BdFB0iCqmk3UOw6pftNU1OHwUkBcAbQKEUlwWJItC0QYSHScDAFEpRgcL4uo/3IpwzyxL87b/7D/AvfvQY//F/8JsDLT3EIX7+4wAM39IYVB7til0pSSG6JmwxVDLH/Pgb+5/vJiIcb7N6HNT9SqyXX7AVRaizkjKDVBMoNa0EWwYBzTXbN1xfeet6B++d6G0JvezLkAxsv52O22ePMVTrebnBA9t9iewUG1OboAJpOlVfrVn37j9oKD6WWep6vu/xQtiRLFRTWORS07aZ3usysD0LDkavUGxeNNrIiq8AMJ2/C+cNNssncDaHtSWcLWBtgTI/g0vmMCaHUjNM5w84xXpXDAG+m/4eGjpueN73vbAzJXbX8bfO0/u8eRjP1uPOOUhBbJAOBi4igESQQL4+Q1NeUggGW7fuvofZYoG8BKQkqOChJ6VEOkkqds/bwDB5VMxUsw4PQLBdCBYNleppBIoW+foMi5MTZBOFYnMOo2c4P3sF7zewhmCKKcp1jofvfhsnx1Pcf/ioZsEawGcoakYrgjxunTUOZbkGkYBUAioRSBRBSY/joxlkBBmCGbfqeD7U1AVgJASxeisR9y9xTV8TrWq9rsRZKpN6OEwnGRwIzgtYBMCLOq3UOkJpCVJE1pABonWAtoJFcHQwfy8t8tWqBugRyHqu5UtlDQoVNE6mEpY8lAwiMIqCMI+FLta4pLsV0nBjh9LgOLy8SEUUAGEAhhHkysBa8uHq5S3vAWe5/tFZX9VAAjwuEUAiIgDdqi8UUsAahz/+3qfDA+QQh/gaxAEYvqUxqDzaFUNMVWMSMgR20n3AztjJ2BiQ0WhfrLMCaiuKKPaSr1/A6DUKIgiRIEmPMTu6WYlqZ0uYcgVthkF5izHcxczsM3mlrQn+PiBlx/Z9qpAAkCQj6gu7GJsvYVLeVIL13mGzfhbUYKNOfZzFXJ6QeO+qxY8kPQKRhFRZazFhFEvVFX39fQPgZLtuLU5oVbKorjvWP0bRjKaoyGAbt9vbFyOZ57J43XuIdMLfIZPpvd3n2bffura9of5vtSsc91opsbtYzau2t+O43nl4+OBFSIFFs7BEvMjkHXS5RprVOzoLOAUINYGxCOl+bE4ulIRKJNfPOceiKp4ZwKaBfGxObAOAyk+QGbAoduNQbM4BERejPI5PbyHLbuM7v/yrODq5hZPTE0ymkwqgydDUWF9oI2jwNXDbrmWr+sMD3izhHd8PazYoNs+xOn+MbJZBJRKJovDnsZhPYONnyDH4cGCWzDWsO+pHrjd0MjCGrk2Xrc5fgchX20lyyBRBSYkSMQUzAERHFdi2DigNH18KZjOl8JVVhzaA1g5aO5Taosw3gPMBkDMyFBSAvfBQwkKRgXIlFqnEkixUsIog1GDK2hJKtIdV/AUSW7WTzSD0vhWAIANCERnDS6CQaqbQAToAQhNTf62Dsa4WuyFU4NCTb517tkjhAfz00+fdDTrEIb5GcQCGb2n849/9If/jBtM1h0AhcMMednuCIaC/fZXYy72HLXuBnecb2YYuA3QAmMzudtpJDIq07AJrN8lw7Hmc7XTcZk2jbHqr7WIyrspEdUXHfk0lWCCopYaxKdU8CCQxcyzVFNbksDaHNTmMXkOX57ChbtbaHEavYBTX56lkXoGXveMqzOiufvGAdf1iJkLWLFQfQBzdlq72XAGk9bObI1MpvwQQd9W4akqslOn+iw1fBrOJmjWM6ZNUyfjXTBarISfBX86HLIwEHgpa81qLlECiBJQiSCnhE1+ZvjunguE7pzLGiKxOBGgVcGwojzrrka9fNczRA8sjCO++/wH7z0oGfj4ynVSDQOsCMGw9+kopNHoFege8ePJD6PwFJinh4myN9fIZ1ssNylLDGg3pZpD0DpTKoCRwNM9CGunWjQpguGYK40JMbegu+GLgqNEBADarM0wnBCkjMHKYTurfq6g2WrGFjtnCCgA7BupGch9pjcoyIy8dytJBlxZl/hrwjvlIj5BuiQqIEfG5M0GQCStdx/pDKeOikgk2SxJ1QieCBQ7CQuVlANj7VUgIYDgyntwGSREGMiisvnPA128sQeuG96TlBYVYS1iBQyCw3b4xlghJIlEUDujxED3EIb5OcQCGb2lU9YVjJ21D24T3mmzcdvSmZF4VcF1h0jYEXFUy320vMJLx2N6+zwBdlxfIzQuACFJmmB9/AKmmmAQD9M7oul9Dk9irsidjIxy3r77Qew8SCkTyeqIzVxkjHdc+pF7ZSnVuzOUiUETWkU45Jq7I9G6WX2C9eszqvqaAh4cQClJNoZIZkvSos16XUyvZGsC6Es72e99JdRlwNNON946+RYs9xl6fKqfaZp274iZZs2t+Zq6TEquSOawtIUQKpSZIJ7fbB/+SQGDfcZ214e3AxUQfQ09sX4GGVUVg9FSSQcd5dGANpSRIJZCkAiRUbS0RgZjzDOCAyoKiKRxTsz1sx8B+hRZlsQrgCgBxKqsSwHQ2g9YBFAYQ4gUTd84FU/kAZoxpGMUbX3kEes/XA++xPD9DInnf+/enmLz7PjJl8dEnv4Cnz17hyc8+w9nZK5w/+wzZ/XewePQtEBwECfjWR4oq4Zlm10eA0hRcEeHN9fI11stXobaO74QgDyEcZpN54yio7BkY/Nag0HkGgKVnoE7E6aNaOxSlR1EwKDSlxWb1JggDUfCYDMxvBQ4dhLdQswUKkUFbhcIIrDce67WBLg2s9fWYqnHhuI9WB1hkBdJGG+Ah4asDRlBI8HBgxtQ4ZkRNGDfV+AnrGhR37mkUhRM75/CN9wYyFQ5xiK9JHIDhWxit+sId39AXr38AZzWmswcgydYJ8ASZTFpMCv/1i3GofdjC6zAkAzEkMLMzzbX+nR4ftFuMJ8lOkaTHu9mQoQnvTYD7PcJ7yzYktuQ0OFtANRnBrei89/u25SoLCB3vXWsMjG3XDW2v9QWLqQRvSxNqY/P1MwBAkh2DaOgrPE54HIzZQMq0Sp8GBlgoYnA4iom+7vVvPbcDVg171djt245m3BDo0j0psU1WuTcldmy/XvEz/ebVnyBfP4PRK6hkHr6DjoM/ooIgVX3fs2VOAmdrNpnCfx5M9zjnAoFYC7NINWW2sNE+9hInKMWCHwwKQ8phAGHGtMFgRVx7ntQbyybw1jDrY42DMznUJAGBzeCVAmbzWeU9aHUDGIZ2GANoW/siRrDA4JNTDiMzySqoHrooITKuy4u2EIvFEU5v3cLJ6S186xc+QTR959pMj9LKhshNEIIJYLSuq0R1fueA1y9+hESWOD97heX5S1ycPQtAxmNxfBsTeQw1P+I6O3jcu3OKWqaGO7xiC1sgkf/K0lWsXtlkCbVFWWjowIAKqaAk1WCskbop4GChoOYnKDGBdgrec6qx1g66MDDa1kC3aQURaMJut8zLY5qoBoOyxVh6GM9CSDICZc+CSM4TjGNRHWMZ7BvDLHNU//HOg2SDtuz6LBFVyrOffPxwn4/ZIQ7xcxkHYPgWRqu+cMfkz3sLwGGzfly9tlk95boBNUVVjxUmn4BHkizYpzAwRSQUsundrQOHc+07qbnipG1IMRMYmebaXPkcO7kfYClni0dIspNxgHPo3EOvXYM92aweI18/C1YjOqi4rsOYqEOIBIuTD+GduZQWC/QArn0ZmT4maig6xtjQ/WiNgWr+0vYe7Dz+rjY0jjeWcd5mNuOCAgBMF494Ak8qMPGy9rsMjzzedeORhXOkmsI7W4HL3rjqfdl3+63vn740UqCb3Yz7Nft3lFfkmPHXt81IRrHPdiLNTgdOOiL6FolGfjeY8gLwFpPpHfjshDMY9Apl/qoW3aq2blJaFiRENdH33iJJT4PATwGSJ1DpSWDdgMniHoz120eBkASVSshgnG6Fh5Cs7sn1fXHSzkbvfB1cd6iNrVIBOS2Q6xtBbEcggsCNkoT5fApJgGVMwiCMOKnRgUGhMQEIbv81zxFEb8rKi9FXAA8ATu/crwReauN3BobWCRRaMgB1EQAGMOi5XaUGTACiWnuU2mF98RLzKXD/jsSdWYpinuDFy9fwIMD+DOuXzyDLBZJbx/jmx+/h1vEs1BcGxrACh5xaytYRtfiKtaw86j1QFMwQltpClxa61MjXFwCCbQY4vVIKqmv7yMF6CU+E+eIEhU2RGwljCUXJZ7fWQuePUUnAhAcW0yHAsbUF4BlQUmRK2yOvFtrxrT9JHsYTjJO8RFG9znwh23QQjAWM5sUETguOqcH14kM8oegR3tIl26D8+q980vn+IQ7xdYoDMHwL47e/+/3uN7ZBYQ+YiqzD3tYTA+e6sfCAx2VGa6hGZ1B5tGuytUfbR9lgXLcvOlc5r3dIEyaK7HW3qBgrEgpl3vZ8dE5j+eanoR8TqGSG6fwdkJCVP+Xodt9kdEzeh+pMW2OgmX46BC6uGrtAxcC4mR9/EJj7/mMIoQChcEmTM+yTTe/s197GvjcR64vPoNIjSDWFlBl0eQFdnEOX3SzbYI1dE7v0gfgd+w2CvX1TyEN0pcQSUbvedlefXrfPO/YtG5+B5oKDkNPqO1wlGYRMIUUa6q0NID2IDOANAAvvS+jyHLq8QFmU0OUZdOEgxBy37n4DSXYErevPTpx0K0lwiuAEQJIBYgRaNlBpTabQhyfWtQFhka+wWb6BVMcgAFKxIqgQBCmB09t3w0JBAIYIKaXhuBEUau0Ca1inGjYFSqxx8N4jXy0DeGUlUwbIwHQ2rRnBJjgEWzuUFsiLdg2ji4CZ6hTZsnTQxiNfnoVG8nlOjueY3XqIX/2lT3BycoSjozmOj+rvVA++Nge2pjC+ViI1jipQagJbaAJw19rhZz/6Z3j17GfYrM7hoTCZ3sL85JuwJR9RKgFZef7VAM04yQBMENL5CTYmwUZLrHPABPEaoy3KvGFjEmr32AIFfLCAjpWomeW2NUXtU1ilkQaW1AY7DuOC7USoO/TgOtjSChSaUGq+xyx0VDOFfI88KAwS0aS2I4i1rvI2tMbi42/WGReHOMTXNQ7A8C2M7/7OD/gfO9K6rmXAvh1jGaI9JkJR2KESdbAazpWwpl1TtYvRqoDLviBwR1uH6tlu3Ndvj3aNibJog78qBRbA/OgRhOAJpJBpmEymIMgvH+wNRGUx4TT3/SWLCd277yXwuud1tFiqOGsc+nw13++4X30Kr61xc5W+3pep3d53KMamm3oEQFEDFM5CqIGUlBmm8wcQIoGQKYSc7HfO2GQS4+pC+5j12F9D+3REV0psJcQkJw0F3JHtGUolH9GeVtt6mMz58SNIOQlG63ywmPonRAaRKKhEQiUJVCKDLYMKjzJYNPCjlJxOGK+ZHyIYatgAkGcvP88Te2M459GFbX3DtuLs2Q9wfvYEm+Ub5JsLmDKHTOZIkjmyaQolJyFNlWvhbt8+gbZtoBHFUSIYi6DQGFbj9I4BoW6AQmssnHO4OHsKDwfvRG1KD48sm9SWED4yhsy0sT8gs4KlbrOSrPAa01o51dFqi/PXz0O6I4uiMPCT+PDjjyFSTqeu72A9QJwX0E7BOBnsJ0IaZTi/1gzaIiu5WS0hhcM3PnoPxXoGW7yGLl/i7PXjANItyJ5CiEeQsk4lNU7AC+YBpSNQcoJNKbEuBTaF5+stDHSpYXQOlSkQUV2vaX3F2kIQZGQERS0CE0F3pWYr2oyh9QTtBIxlQC5FnSocFyDK4MtYlHyfCTzmbASH1Xis1UibwjOx/nU6TTkttjT44NGhxvAQX/84AMO3LCpQCPRPgsLrg/YD28qZNxVdE6GeiOqS23VYVk1YUS1EZLQQbChUMsds8fBymuvQpPkKoHEIWI+uubzKJP4qk/49FgVmRx9cDdTucf7t15oWE5v182AvwXYT3lsYvdoJAEgoTGf3OpVgL6W77tHvl1iqsYsJAxP9vv7fq1a3LwYWg3bGrs/HiM+J1pdZ25iFoIIqsFSzwbrVP++xDb4iQBIhHbYCrAP9Pyol9grfD31MpkqmlwBhBezipL3RpsrOxAcAF20nHAAZQFjD97BxMkgR3+fUPh8ZwVgDBmYKuYs8dLHE6uIlkjRFdvc+8lWGIr/A8vwVtL+AdwmyrECazHHyzgc4PZkEE3i2WIhKn4S6lk9rB2MYqPC/XYslNNrCWluBw/XyDNk0qbrdeyBJFIRMYFytAOoawLCsQJnHZmOhjQ+2HC70KVWCOaa00MZis14iS0JfArBeQKgMPlmgsBIWzXFRdSkEPLSTKK1EaQXKYENR6FpgpjQMCk1pcf7qMR/fehyfnuJ4ssBUlTi58x4Wxyc4Ob2Ns/MCxius1waFLvHksz+FF+H6iQHi2UUJTRPkBYOw1bLk1NT1Cj6MTecchBN8PwUqcEiiXiSI18H9wWm3QqCqJYyCN85TYAoFtI21np4FcoggvIfzhLIklBEUEkFIHksigHhYZguFqEFhZHCdj6q3bKdS5CUWswwnxz+/30mHOMTYOADDtyz+1//9nw9vMBIcdALDMTU7Y2OIcfGA85fZuJrVOsL86P3+NNehdg69PjD5rZQgm48DBug7gXU8x0gGZidDNXQOtLe7caZzTLsGQCGAlrqjUhNA1QzSZPYAm9XjwBgbZghts76OmUJBEkavYa3mFFmZYjK7DyFUG3Bdk3ElEm3xlqF72RFD/Z8kIywbbmpxo2u7XaBwxZTliAAAIABJREFU6PwhdNm/4DQ//vDycfuex/bsyxo2t2/UF/XV1AJoMeORLU+yYyQNEGv0GtasYfQaprGoVtVNEaDUDMTWf9wudAO+0YsNNwQKpWJQeAkQBt9CkrIWnqEaFMbnHiE1zweg5wneeuiQhtmsHRME2DCJj3WFbHAfVUld5Z0Xgc/5y8dsLxBA0WR+gtnRKd7/5Ndx6+5d3Ll7F1lGmKRAlgKZsnxrfaU5WRnJG2Pw//3hP4ZzwDsf/gWo9BTGOBjtYIwNdYsFdL5CWWxQFmvocg1rLEBpOC43bDKp2cJYN2gcBcuIwNKZmpEsNqbyXxRCVEBICAHnQhvKAmkiuS+C1cRkforcJjBOMmMX02wjkEftu8e+hIIBqWmDQh3M68vSIt8skSZVMiU8CNP5Cd7/8JsoncTGCMgshTUCyQx48qN/AW0IXobFAEEAHM5eX0DOjrHeMPh9c/YS52fn8F7VaZsxhdR7kGOgJiWPLSERPBmb4J0fneOUY+EBkId1DAgrpVEbaks9BSDJAFEbqkCwIACSgngSnweCYHRDXZdif4LbGcagMw5a85j48OMDW3iItyMOwPAtixZjOBBDk1OgR6zlGpPpzuibxBJgy2ukuV61nQSsLj4FgUKaosFm+RhaLwFQrxhPTItrxijGtTFpvZH2j4wbYTqbMab9A5P7MQI+l8SN+o47BvR9yf3bjL1Nzrf7f4ipw9brX9Z1NY/fl3bZiH6fwh2fiRHgqEss6BLbRlv/Dm3W5XldU+strNlAiARlfgZn8kvtTrITEHEVJ5FgESCSAAlOWycGU9PFfRCxPQOrkI7sqGYzx6bE7ohtQRwKOZEqmVbsTfU6AgBsTKap8tsDCKIF+JoRAR4zbr51TCEBAQLJ4Je5BQqj2milTOqAIl+FurwaHApBuH3/fUiVIi/j67E9fF+MRcunrywdHn/6p0jSKaQALl7+EJuNRb5ZY3X+nI/vAYDPz6qpLrRNw9kU8+kHkPIISgFplUaKWoDGs+AJm6qzL2NRcg1hUbDqp/eegWFgqYQUIBCKfMXntQ7GCv6TAtPjuyhswqmpNtYz1v0da/+IGBgW4XqLsg0KdWAltbbQRQ6luJ8iA3p6+wG0E9iUMjCODMC0Ac5en3P3eIKTsQZU4NkXP8ar19/Hs6fPsVxtsDxfoSwNlDpCkszg3Qzei9CfDGVVIrbqFus/7jsGeC7URQoCjBOV/YY2BGvZtD6mj0pRA8RCA0XBdYlOEITzgAhMrvdwJnhyEgCqU6ffvPwCzgFJeqdiDK3hwtRvffzu6M/ZIQ7x8xwHYPiWxb/37/wyfvf3flLbVWxFverdDw6uXB8H9IOdPeNG0lz3YYY8YMyKFf0akU1vI5uyx1jbHH0GqWpLDyIBZ0sWaRkjkDGmXdtM1J4sXN85tusLmzGKseo6167YBjeN56OVRLvOPdQn12QGB6PR/s3qZ8yobJmcO2cgZdrJoKWTW5wi3bi+zs9d13VuM5VfZYxgqHt9CrctW7aO1fe5uWStsU+E76Nt1WIGiEdIUmAWa2qFAiIA3FKB7QsGhHwxcfIZfQC983sBvt5td2QQMPO5Cn/LcCyqJsREQDY5rWr/gAYjSMRKpFIGhqsNHFvNiIox3geRleA1GMzEK2AoBITkyToJVsuMZvWVBYW1lUCL9x5lvoKQAgz+HISQUAmzt9Y4FAX3LpGoUhOdZ+Ypqn5qw+BseXEBHwAFOSDNBKbTIzx8711M53PM5zNMp1PM5jNIyWqkxXqNIl8j36zx5uwpnn7xPSy++QneffSNOoW0+gugMKRwshVEAGWlQZGXQdREVGBcSAJBwHsBZy2cF+yzaBkIZdNT5FqEmkVCaXAJGMbrjt6Epb4MCkttoQuHfLUMzGdz2BDS6ZxTUY3ApkRVH6m1R74uIBWDX+UJUB5JYA/vnCa4d+shXr9e4ic/+Slu3/0Qr86WeH32Epv1c1Ce4fjWBxBOgGQEhdEfkSrmNIJCts30gVUmGAS21zJLaCqLEYR77QNjyABRax/SlQkCHk6E8RFrTJudF8I5j7sP3gNAKHKNL158CniJJLsH74F/7S//Yv+H8xCH+BrFARi+ZfGf/Sf/NgDg+Ysl/tkffYr/6X/+X/AP/rd/BO89jk4eYr3ehNqXbu8zgNOhdjIVfbH/Ynk7wvn2TnPta8sesa3G2YyWOTrqSWxljg5mLm5Pbu99/fn6KZwtsVk9hTHroLRaAkSQMqtSZWUyx+mdf+nyAXpSGbv8CFm8Z8Ay4CZq3MZGaG/fve5doBh7Xwcm0zujsb1Hj6VFTO3Sywp0NE3OnS0xXbyLzepZp8m5S+YwJodSMxZikenIC+u4vj8PQV+NT+GgxUhP2IHvk6PTj1vH3rs9rk4k+FKiY/Fjvfwc64svoMvzipWONbZKTQCRVKAQREgnJ7xrAxDycwG5lfJYg8fmKfk1F1JKI8iLQM9UTvcNYBgAAsDbO1uDwiZraMoN+yTG/ZUKYPYopK0CRW5QT2cEs1rBHqJS/NTs11dscgYmMqQvOkBlhA+/9RcgJQueSIFKcOUoPcF0fgIlYs3b/8/em/zKsu35XZ/VRES2uzntbc+99/m9V1TZrnLZLjfICFk2koeIMQMYMwMhGYkBTGDACCGEhBgh8QcgBggjFXIDMsLINghMld+reve+e889/e4yM5rVMVgrIiPbnXuf80rwbv6krdw7MzJixYoVsdd3fX+/7/fPoKWPVg4i0Nio/umciMqfyRbCpmNHUJrqFq3F1IZq/pyq9zw3TYnOhpG5FQYpH5FnY6wDoXKcGNI0YoUBtbb3aE+AMBCZNohiN9tAoWksTT3vGNHYXxEwyWxEYyPjWNbEGj0bqMqGxgZ0W0OKIM82h+L5+ZgvvvyX+OTL32RWK+YlvHp9xeuXF1Sl5eLlL5Z932MMhUh9lhRTrY3px17G83QJ2FnX9ilJwCd+H6InYkgAsV2MUcR6Q3wAIbChTVNeXdzoBGd8TPsNSM4ff45zAWvis/v3/vzRquIYP4w4AsMfaDx+NOFv/c3f4m/9zd8C/j3+s//iv+W/+m9+xuQ8ppG6NEH1rkbKnMXsOxaz7xhNPmU4+eR+6Wl3rLXaGgK8ew9PwvuwKC0YtXvM0QcPVr+yNjldmVDuYvK2tM2aeVdf104c2utTLl4ntumGLJ/uBA59xioES/COxex5Ah299Ffi7GDXgkAHxD5UOuYBDOY+/8kPIsRyG+u6Kw7cfl/788E5g9FTBqMdEui/Qsbv4vU/JQTPePoMIRXOlgihkUIhZPpJaZFCSESQHXu00cwkHRnw8XfvCbg03g5XhlX7LCl60a9vCz4g5CaTthfAbWGUd2UgbCwy3fGa9J8DYcuKUNfOtUyKneB23/F7i2amvuoWISJTuKCpr6jKt4h0XiorGE0+QqlsKyAElimkHVO6KhYSv9K/Hok0TOmXMRWvVfZMSpzCIaVCKt+BwxYYtkxhZ1zvHXW5TCNVKfVRIBiOH0DypMMHmtr1QIZIjGHoJvumcSzms8hgeoH0EZzkhWI8jeJT3sfvy9CVEeLCEuwpFRUsnVQoGSDIpRVEHxDaltEKySdxKWRjmgVNdcn4ZMpwdI5tbvD2muvLCwhzQoD55RwtH/Hg4U8YTEaUJtXUtQxeYj+7NsslQGzVPc0OUGgaw+zyFVI6ECqdp0BqTRB5ZCVTfWJZR7ZzflNiGk/QAiVlFM1JQ251VAuefvxJqnOMbdXZhJOzAuevYnuTl0cLZtv0UZ+YwtYr0rl4hBVVWRfZQJdSUoWMNYYisYtymWncgUPpA0GIJFTWps2Gbrz7pIIrRMteRjB48eYX5MU5So949GjKk8enO268Yxzj1yuOwPAYAHz3cjkUhNToNUGOYviQ88e/ff8D9CY01eIFzjWUs++xZo5zdRR1EDoxbEOy/ASdjaLPWWISnC1xtsTuEXXZ50d33/Yibq+5fC+V1j0gY1taZ3t9Hjz5lCw/6XzIdkWfsWpjMIqF9CqlvEpVoJOnHLTMjkhCLpGtbOuptsZ9+nnb9msgeR+Ts7fP/4TTKHcBkX3t31BCXY9fUfttM+vukWrxAmjtIpq1hYJ+bOaAh+Aw9dWdji2lZjB6sqE4utf/tA9C1gyo25TMW+OW8bDOSrcTx3566/vU+EUAuwpoD2nXapt6IHLbd9J7688MnY3R2Zjp2Y/J8lOK0SkC2QN5m6BwiRNlqoFbGpBLJTeuQ9cEGfsuppEmM/j0apv4DJJKIlVAuMgckeq1TVNhmwZrakzTYJsaa2MGgyCgtIaWIRJQjKZLwRsCrl4+44wUOLe0R3AuYBrH/OYGZ2Naa1ACpTVSwOT0UQJVvf6Gjklr00OdizWSSkYWK4SW6UppkG4dEJKAcegAcl2+ARE6tnN6dsZ4cM5Pf+t3GI1PGU2mjCbTdM3j+dV1W6+YUlNNqy5qKW++5eLNt5h6gTU1i/k1pi7R+SAu9qgCkZ7vk5PPsTawmF0wGEqCz2gzgLNsSGMldWIkm8ZTV466tMxnM4xxgMLlveHSDmMRgbgkINN+TEpBNcnXkJDFxZHUsZ2fpF+mhToXkp0EXf+14DEQwe6SKYz3ftTAEXgRQIoVUB/tIGNDferLuDAQx4D3nlb/qSh0XPwS8Ob5H1KVJU254Mdffcpf+b2fbB3vxzjGr2McgeExAPhH/+TbDz+Z3sGE1eVbALJ8QtYzT48AJE5U+8IO6zuL9XoGIRVKDRiOo7gDQu2uwdr2977z3cLc7YpdrMLBrMWe2HfcwejprbWetwHayelXAKzL0Ld2DiF4yNYY0T2T0tvCe0NdvqGcv0jekymV1RuUKpapsXrAaPwJVfly5772sjnr1/l92t0fx/3vHHAN99XCqnX/zPumZx8aab/NFhP5lh1WerjVoxLYSDt2vsGZ+aoabMdK+44lxLtuwUYI3al+SlUwHD1e3re7auVYZaUgMkZ9Bm6l/m5b//X7de367btHpBps+lLekzXcCmD3LAptZQ3743BH7HpmFMmqJXgiJZbYFSFacN3WPnociTUMHoXE4Qiqf2AVGeEEBJUOBGIN4Ns3/xxvK7yrqCtHU5eYpqGpy+QzuvQa9c4iROzQmNUAwftke+GRQjOcPCLLRyBS7qIQ6CxHqQznAR9oL31T2w7UOt+Kx5AUPx03l6+wxiN7oFBKwXA07kBhyyq14VNdmvNgPCi/TDV1WwBhC16cCxEQur4Qj8PUC3QmVtJZ8yzw45/+Jo1bgtEluIkm9W1aZ5sWa43nzfc/xzYXDIcF52cDqvklJ2PHmzclhCrux83wFqoSbP0crQsmY0leFBS65vzBY8ajjMFQLb3/6kBdR7GcxaLh+t3rTqwluWusjdXEAMqMILIIYl0vjbf2VItZT7k21QUm9dp+/0XgBtLRATUpoiWFba0nJLgEGH1rSyJFZJC9WDaKOMx9q4yaLm7wId37yytdnMYFkRDgP/oP/i3+3J/9MT/9yRf7b7ZjHOPXMI7A8Bi8fjOLYjQfejK6ZdKzTUiktZkAGE4+Q6qsm0R2Qg9CI5RGiuxwcNeP2yaLvbiz9USxlmKyrz39493S9n1piIcKAB0CaLd5k+2M9wQt1eIlpr6KNZEq79QfnW1oqouV9tblG5xrUhpbhs5GDMcfpRTHLTvfB/Lb///vw2yuT8oPuM4H1UceOl7eN1L793kk9utk16PP3t/50FtYyFsZOBFZyau3/4xq8QqBoBg9IitOUDJDSJ1SXjWC1qhOIoRKKbE6go8QU1oJnuBd/Nu79Fm0Ntl5zn0m8z7PnfeMW/torR37nhntucR03yXr16XVQWJPlgARwHqPRuPXrDViDVhAekEICukCQQfqxQzv65SmKRmOp1SLGy5efQ/4roYvogu98jgkqXUqnSFkRvSalQhpkaJCygGnZ5+gi7xjndq6xhAiK1elc2rTU9v6Rmcd86u3SCXRWYbq1bkVg1HvvBIw8xBEBIa+zxomYCjb1FHbsoPrgNBjrOuxhSml1taIPI+pj1KQZ4LT02lMTU32C33GKxCPUzfRd7GtlTSNYzG7Qut0rkEwPT1jkJ/w5Y9/gywvGI1OUHlBnhVkefRv9Sn1smVfBXEMCQJlE9M/G9MTzKkddblIthKxg0TbT4AneQciGBTDThzGJtbR2mgD0lTzzrJiCdDoUn6XADp0aaXt+JZSxHTixOq2TCIystRSiNQWkCF0bO/yvliy18Gnz71fGft5JrvH++/9xT/LV8+ebL2PjnGMX/c4AsNj8I/+8T3ZwnswHfsUJnU2Zjz98m7tWN/2ljSrfvStJxaz77FmgfcNgujrRapLMPUV+eCsx2it1vLdKY10F8jYEvvSEA+tr9vX3+vtvhUUwv7J8a6+772/Dkr66o/RezIyVEJmHVu1whzvY/92xTqTeNfFhPt8X9yjPnIbe/SBwcc2/8822tTWnSDutvO+L1ja871y9hwhBMPx02Vt7bufJWuI1p5gOShuuaUIwWLqzXuiGJxHNeHeddmZ3noPgLjRf4Gt9ZoH7XPP+Nj1zNh2LoEla7hsZ/Ic7AFEiN5/Kqwaq7eskVRRvEQqj/eSupyjtKRzQsczGk85/Rf+KjrLybIclWUJnGkyrZFKoXSG0hmyq8lsmbrICEbPQ9HVL0a2MBqQt0AwhMCb53/Au1c/w1nL6ekpxfgZQj2kqa5xzsfaRlnQejQOhqOOLVyKmawydy4J2fiUIqpUK4ayCgiN8el314FDZ2PKZ8sWksz6pBLkWpBngQcPH3UefM71gCF9NhKaOqZlWpPqBU2NECoB1+gf+fTTH/Pw8ZNYe5l8HFtwa5NKays8JHriLyCSmmx7TN8xndZUFGppr0GvjwSRtZMhoPNxtNiwsW9inaPDNIZy/jYuNoSl2E1I19H5JSi01tO/kUMIkcEWolOx7QNElfopPgpaEZpl/wFd/7iWNeyN45ZJ1FpibFxkOILCY/yQ4wgMj8Hf/Z9/fr8v7kmD2hX7GKxba64+YFizaj2RFycUgyXzlw8eMxw/ZTF7TrV4mYzRG0wdvyN1gc7GjMYfxy/cJ83slu322kYcCEYPtXo4CBSux6ET5HYScVta61n0njxIkv8usc7Q3gJeIS0aCEW9eIW1VUqBMz3D8wwps5R2mX5XGXnxgGL4EICmerezSTvH+q+KiUr73bfYcKvi7AFgeOfh9ymF7vlev564q32eDFFqiFRZZxchZfo9XYvoDWkI3iRrkJju6p3BDuYbKrB1dYF+XxXY22Ij/W4HG/ge13/XM2OF6Q0QiKxhcn9YDbkEiMG15vRxct7toqe02nr9Ka0IocS5JIqiQAWBVIpiOOHp57+FsyBaNdDEBAFdqrBzrBynY3p8BF7B+y5FFFatLqKqacCYmqeffsrJRNGUlwT7M7z5P5jdzJHBUy8gV2dMH/+U0WhAMVytd43taY+/ZAsDdO1wyUqjYwvtKiC0JoroWNOKzjhsY7BNSTR3l+S5Is8FmfKcTocJGMaUSBsJ7niMDhhGUNjaXlTzeQKDdIyhD5AVY1xKp2zbvwTZy3rIlvVbX59owZmxDts4TF2nxsiub1pWlZTiKYng8PT8YTSfd9EqwxmHNQ5TW8qbC7JCd2DMh4DzIoJCuwSF3vkVKw6ALOstSqQ6Re8iuA6981tJA25TSQNdnWsLAtfXZaWkE7H64rOjkf0xfthxBIbHiPWF8P4r/rdlId4CDFQ2PpyRuAMzuC3WJ1D9Giadjbuaq+H4I4bjj3a3Y/3vW45fzp6zmEfRHW9rAgEpNUoP0dmIwegJw/HHCYzeUXil1w5nK+o9wGRZ87U6K1iv3dr63XUD8V0+cmv9tH4+/T5fOZ99IPsujNX6fm5jYXrpn7a5iRM4XaCyQQQWtsG5BBJtTTaa4r3D2kVXO1WX75hd/zFSxLyr4F1MhVU5g9ETEJIQ3HbG8ADG9d6Rvr8LOAipY7p2urYbyp/7/PYOZY77mxwg5LLveTGcfrpXxTSC9i16+isH4F7s313u94Niz3hfV3ztp8SuK756Z/Buu9XMikDV+jHW7/f20nQ1dwkk2iVkE0noow0pI0AxzU0HDGUAlSuEEExOnya/PwcenBBR2bJLBghsW5vqbC88BNeCwpgSKCQdk9gHhvgGZyXWSs7OTjkbDhnrAWePfoezh09RgxNKm7GoFYsaFtXWLkvnvsoWtiDLmtimPiA0tcE0NdbY9FpjmwZjopCOMw2L2QXDyYAsV+SZQCvIlWcyHlDbgJYBI0RiQZeMYcdMWk9TW2zjqMtZAjye4GXEbgFUNsC45ZBqxXNCiOmdxkJVuXTdYqe3fd8xazZ0KbCmKSGJFCVica3GcAkOY5/EY0SBHMf8+h2Xb17gQ0zdjMAvJLZwCbRbUOisX0kDzdIYWr0wcdxGw/o+uxtWvgtLRnCfSJXOVHcf/OZPPt09II5xjB9AHIHhDzy6+sL7xh0mU/uAznrN3IbVwweeNO9nLh9svrlvMnjg5NKaOU19EY3L9aAT3XGuoVq8AqCuLri++Bmtj+RGfZ1Uuye8AubX37CYPcf7huBtYrJytB50gjKwPZVR3HeWewtTCEAA06wqWPZTenQ23QQL6/u9S4pd/+87ntY28CSlRuUR3LXXYDD6aKPNIuVZCblqaA5pgrLPjP2u769FCL5jNoO3dwIOes+izMHKnyuN2Wz3XVU9992jh1pb3Ck+ENO/LarFyyjEE2LhVDl/nXxD7dose3Xnd1V+3ZYSC9sXktpaw433uxrDsDKGhRT4Dhz6FUsL5xwheOZXr3FpG9VLPSyGE9qaQGd9ssAQqN6QcLCOODrQtc4M9twG0j5dFJhpqsTIieRDGBAEPvsipleWLqeySWTFQW0i6+dcSPfskskUAl5++wdI4Qm+ZnZTUtUV12+/BwICjxDR89endEhjo9WBdSG1ecl4eucZDguy4ku0suisIM8CmfQ01QKVT1AyoBVYFVM+l33QgtBYp9jUDTeXLwBH8Copbsb/owgd6/O665wAYqesmtJSm1iot0wlBWcj4DfGraSRkmoSRdp+G4gPwNc//2cIAW8vGt68esVivmB2M8caR15MkeoUnU8jY+iBjm1t/S59xwaHEMhy3XkerpzPOvpL2/vQa1japKst3Gxy3Mx7siyDIAgh8Lu//dWOLY9xjB9GHIHhDzw6tvCAyc5WmwmZJ8Yr2UwUp2TZGKVH6GwUUzDNAmsX2D0KjSsTmV1M0TZwto9B3AEktjERXW0NoNak9D9UeugGS5lEdzJgPP1sqxrkXouILTE+ecb45Bne1dTlW+ryDaaZUS5eA3GCOJp+suKdty2NdAUM3HL+HZt0SzqpaQ5Q6GTHPvYtCtyH6dnRRtgGSJZTiunZj1aA3sYheuMosJxYrx/jLm2NSq5vE1vkKBevE9scmSNWFlH2A4ldwCEvzg+/zhsfbNt4/zltjbXruSsNemft313jrgBvX/tvef409WX3zBFCRJVNRig9TqI+A6TMUXqAsxXOVfHVllgz21R+9SaxhvF9KXVUhEyLA6aZIVXBYPR4r0jVTrDul96LnUiNXx3PQqQJfPrcOU+1uIyAUKsEOuIiSZYPsCYJjfhAcAGpILgtHdqjr6xbeiH2WcEodSLX0llDl+otpOw86TyCwWiE8RnWKxonMU7SNCS/voAxgRCiWmkfHF5dvEUpyJRgUMBkVPDls9/h/HTE+cmQB6c5uWyoZtfMr665vF7w6u07Lq6uubiaU1YGHyQuCEKQBCy4n1FdCUI9In84Rhbw3Tc/JxuckA3PQY+BHGscZVkxn5UsSstiYShnCxazGdWiolpcMhgWHfvmQyAvBtj1tQbogGNk8qIgTNNE4CeljIxw8q3wBHzPXiM+t5d+grFvNp99rlMDhfOzggdnn3Nxccmbl6+YL0qsq7BNxXX5gqyYMD19SDGcLuswTfKxTM9VnankcynXGMPYxuUYjsg3iOX/rP7Wvj/EW+Gb9s/Ub+Np3v3+5efH+sJj/LDjCAx/4PF3fv8PDt72fjYT0M6QgjcIoVB6wHD8tLOYEEJ1dVnAhihDNyG960RuD3O3LUIIKb1SrU6YDpnkHgBO9jEgo+mzw83jDwgpC0bTzxhNP1s2ccckcN1jbT18MFTzlyxunmOaawTR/zDLJ+h8mia1GVIWKB3B7aay6+58ra0Kq4f0w/uk8+1aNHBriwa9bbJ8uhsUru2v7dN9IPLQNtaLVzT10mJC6wHoQWrTaVyMyaeY5oamvsTUl0tbCW+SvYTB+wZj5oTgcc6g9ZDB+ElipDfrTVfZIthL+N2WXrl++vvShNPrLmC4Xi/3XvfLfdNJD4l2nrwnJba1i4Hl/RkX2QZwC/7dxk5DSrFL4+02lnYx+7a7ryEgVREXq/JTVKrXFFJHUai2njPkMVW6bUenburwzkUTekH3UxTDmM6YJuUxpdEhvWAjRbB3bi1D2Kl5JvDnXXtOrvNibFMUq8UlUvqOBWvXGVQ+pvGKxilMz6uv7nkCOusTkE1pl801jQloH/cfiAqmnz37ksFwSKE9QVmCzDl5UPDowQlfAA6NDRIbNIvK8u5ixqs3F7x98UuMqWjKGU1dUlcX3Ly7YqEUN1fXvLu6xgWF9xFIei+TkEo0e7eWWPtnotLqcDTG+4cQsvbCo7IhdlfGd+izj5GJrcvNBdK2BtBaF1NXyxn5QHRiPTGldPWGjrWC7bVb9v3p2RmnZ2fc3My4urigqhuaqqGq59xcVFy+AUTGaPIkMp02AsMs08gE7lvlWEgpvX6ZLtqlOQfwNnTH779uYxfjvmIGR/CB4TDrUoM//ejh1u2PcYwfShyB4Q88fv/v/eyg7e5sM9H+nmp9hJAfdtIFd2aMTHODaa4x9aaPWxtqG3O5bxK76++1ONh64g6M0jqAvhXMbttNTxSkz3D1gUxrMZHlY7J8nBaVIS/4AAAgAElEQVQEKkxzQ1W+SSmquy9EO4EN3qJ0wXD0lFizssN7sneOH2S8tPvZnbHXhbXzXpvb78Zz08UOwZ91ULhPaOXQaLsTsHZ7+iewAvyzbBrvx+nn+9t4h35dzL5jMXuOaWZR+MMsEErHhYFsTJafLEVgkkVEazEAMtlJSAQi2Ue4g+vldsW+erk7R+/7cTwu/75T6uueduxaELqTmvGW2MZO31YfvK1t7X1tzRxrSprqgqa6RMolwBMQ74NOhGQ5iETMMSTg8a5kOHmIlKcMRgVSCrJitLkwAFjjdgLD9vximmEUcnHWpfdinqQQcgkCkp1BU80YjmUHcHwApTKCHNBYRWMljRUYk3wBW1BoHI1xnaiORPD6+69j2qoXEBJAEVAMooG79wmQaEFAEJTAB4H1ChskzkucGjI+P0FczBlOTjiREzJ1SoZF+4ZPP37Cs2ef8s+/fsE3z99Q1oamsdTGYYzDmIamqbHG0DSGPM+QeoDUA4Qa4FEEGlCKh08+Q+qc68t3lIsZWVaQ5QNGkyiq5vySLTSJobMmAm7TWKSUOBuvibMRdJumIgSLEDlSiqXVSP86enAuAsMWELbgUMk4IoejKcVwSmsD8smPfofZzHB5ccnVuwtePf8j5lcvGE2eRpZQyaWdiBJp6K36EPYXM50LK/dDf1j5zhtxlWVsGUIlQSiBM4HhYMDJ9H6WPMc4xq9LHIHhDzi2gsIdk8ZbbSb2+J91cZe0v0PiFoYiMl0vmN98u2RckqS2UoONujvYoRZ5SPrbLXFn64lbaip3St33N70DQFlnuPqxIRojNVk+AUAmdcgV38kEEDq2YQvwO2jS/aGYnDt8b7s4S5vaFK/TBhuzY//rLOF9LR+8q7dumuUntzN12+KWfu1PuprqIgrw6ILgLDYb4GxNXb6hLt+Q56dbx+LqmW9HpPdNe90470PiQzx3tj2/DtivWUuhbyewugdwN+6H9j4/wP9x37270vy1fbW1qG3obNz1tdJDtB6gdI7KCnQ+QOsCmeUokeFcg7M11sZX7xqiybjHmGuq8gJrr3nw5BkPn36FJ4HKnhBIFBkJO8Gh7+oLI2PY/h5cSOmmLgGQmFLqbayrDUEkWwIAQVYUNC6mkNaJLaxTCmljfFTetK0FRLtPwfzmCq0lQUuUUkgBg+GoU/8sjSCgokl7EHgEzkts9yOSp5/k7cUcEVqWNQMFSlqePfsUJxRffvmMZ19+hUWl1NO4rRQeJTwCj8Jjmoa6MdzUgutSMCs9NwvP9axBZgVNNcc2c968/I66nGNMjXOOpiqpqhKlBwhZIEQOIkeIDKWnCDlAqSFKFZFZNIukxF1CSidWKqZ09i+XdZEt9I5OSXSZbgoiEPsmLAVwhqMTsnzIYDRgGobkxWMmZ19x8foFb7//wy4NuGUMlRSJbSbVS4blbRdiCnMI7T2zyhp2iq1uWcd4/e6PIcBg9ClFrsgLFQVzjOfZx39yyujHOMb/V+MIDH/A8d/99//X5ps7Jj33spk4hGnb9rUPxLhU85eY5pq8OCEvTliaqaf6u/TfI/onfpaUQW+pddtynEPiztYTu/a7Njldqf/ZUgN2mPqj3z65D34v0wmx5m7zi3va39+GPdutT8LTa7/erlq8wtmqsyNwnZVEm/a2aiWhs0lXz6XUYEs9V4VLjOHKhDXQgd+tKaHbwNWuMbwH7G98LnaDQkjj5j5g8JD3iWJBoZWoDHFBQGcTdDbpMgSUzFOqoU62Ebozno+KkTGVNaZTJnP5HivohvOVtNfgLN7Hv61ZbE173WDyDwFr9wCFW2tnd4zLfbHt2RlCQKrB7vtzByhc3Qmx1m7Hdrfd+84sVkBZO+aVHjE++RKpVJqcS4SSCRgkwRmpIdNINYR8eU/kwwHFME8/GcUgIyCjbYFrjeB9xwTuSmO/ufiG4GuqxYymnmObiqq8wTZlZO90HkGrKsiLMdOzLxECvHcpJTSPYCSAzsc0TlGZHig0gbreBIW2cUlIx0QWTWhEJjvBlcFgtDS7d7DwAh+iMbr1ogOEzguMjbYN1sJ8YSgyQXTdAyUlZ+dnOKFwZHgkDoULEhckPshkHC9xwiNFwAuPyBVFPsYPc9Qko2gUg1oyqeD6pubdq+eAYTwecnY6pFxc8+Lbrwne8fmXX1FXhrqO7GPTXNPUDUK8jCnASqN0ey9LlNIUA81g4BgMo8xpX3jGOvAphdSlFM8WVCvZgjLRMbdtRufpg8cRLPpYKegJqdYxZhbJhCyFjHWeHfvbLSosx79L+1iRIu2hQh/ofC+9i8I2z756xngyYDod4LykqgOL0mOt46svjvWFxzjGERj+gOP3/36PMdwzmTrIZmLbfj4QM3hfX7vdZupTJqc/Isun6Gy8wRqu7H8PgLl4/U8JwTM5+aLzUwMRAYepcL6Kr24JOLbFbdYTu6I/obqXcmT35XTILd/fx3TuTIVbT8/btc1tzd1y/m1aK4BKIj2d8XnyG3S2wrFZ05gVJwixqnwrEPhgUarA2SqmPiKRumA4ehTrZZMybH8YrgCGHUz4wamIe5j0fWmkt/oOsmW/d2DOmtYIvlfP00Z/QSAyNsu0wo65EgEpMmR2i21EL9q045VTuM3vbx8I/NDp6+3+D9zvvmfnVmXVLfvdaR3Sa8eh937/OWHMahaISHmAxfBBPIaP3EwQAZEm2TItFGyU2Lb7bExUkUzpgFLKTtTEuli3ZhuHtdFyQUixsTMhBE05A2EYDDMmJw+oy2smVnJ9YVKdm0eKCiEq4Iq6fEdRDDgZZxTDIcPc8PjJU8YDAVLxzTffcvLoCxoT1T6rxmOa6NVnat+1yzQmpVea6EeoPEXqNyHh5OwhoTWND2BNZMRCUDRSYlJKZTR4jz/z+YLGLBeasnQ9Tx88xJFFQNiCQi9xSLxPYDNEEClEQBEBoguS2moqIyPYraGsAmXpqKqaLJORrXMwGk/57b/wVxEq56PPf4PGQN1EdqxuImOqREAqmczuYz2fSmmzSkuUikqpV5fv0NKDb3j94pukcJrM6f1yLCqZbCSS6G0iigG6VNyW/SOllhJEFFuTYvmTageN8V3dY7SoiF+2CW3G/Wwf/761x0j1hN4HHjx6iFJEYaIE3K2JtZt/7s98ddB9dIxj/DrHERj+gOOv/7Wv+J/+wR/HP/ZMcu5iM7FzP3ecoB2icrkvbmO6hpNPunbvSuPad3zb3HTfL+ffd++Xi9ddzU23kxA66wmdjRlNPkIIfav1xEa08+0eu7deV7TXb25X7GEedqUQCyHIi9PN9h00WfZLQHXHdm4bi63x+dnDR6nWTadx2aa1ptfkLShS7dtGu7dNyvel8q2xe+8VO76/qx52r2DPvsUZsbbtnnA9UNoHhVk+3Vgw2ZnOeMfnwb7Uwq0gd98xbvmsbyERgqdavE5Ky62YR4gsJkBI6ozt+BEShOzqKZdp1Ik5VRmD8UdIsf1frFTFvZjNzkaiBw53Mf4r3+uN4xZoOrvoHW8J7HU26o7TTsSDDyA8vneckHID+6DUG4vVCqUtSimUlslnL6YA9kGhNS7Vj22etDVl9JZL4258ckamH/Dxs99kPBkzGg8YDgpGowHjcUGet6mX6dEi4O2bNxAsTXnF119/y/U//idcX91QVTV5cUI2OGM4fpyscjJCyKnLG5rqmqae412r9hpBoRBwev4A41JaZGLKyjoCH4HAOTqW0LqAMZ5y4WhMPA+t2t4OjMeTDhRaH1NIbYjpqC0LGRA4FyIgFBIpPMZpKquojaJq4vGr2nNzfR1tN0ToQF4Igs+++g2EzGlsbG8Lan1Sh228j0BSCZSM9197mZV1aBXtP0aTCKhMNaMxy314H88VIqAMPawv/BKztf8Ss2xA7dLt26aHJnAXjeaTPUWIIkUdKAxhRXgmMoIh7WM7MAw+dEqnwQfGkxznY5qr92CSf6K1Hm8dPzoyhsc4xhEY/pDj3/93/xVM+V/y9//B/8rLV2+RSvPo6Z/DhWGncnibWEuXevmrWplv47b9r32+znT1Jx/9SfVe+f09x2ua7bVRw9FjlB6+v/XE3vNd/bAFh7cqR+6KLvNm88vrwLDrRyFQ2WQViH7o678WPuwG+zvrXHf1Yx9UfEiGOx2vDzrKxWucrWL9k7cduI01mFkHJLaBCtNcbx03W+tS2/hA18G5aiurm+WnK4zvtrTZg9nruzw3DtnuTozoJas1dtFiR+cnZNmk62Nr5ulZeLVpGxFsZCJChe2NTyE1prlBCIX3psdCP6YTXDqgndsVYteyA8Qd2OkUbfr1chfpOAKUioq3bMGaoa/93wOF/Ym5rZsuBbUFfu3nzrkOFEYxGbEiIgPE9PAWMLAEDvlwyidf/GmUEmRaoLVAZ+BCVBj1SfxEJg2h6dkTrG14/vw5uphwlk2QsuDmZsbl21eE69eUw+dJZTOKIDkfECh0ljGaDBmOJI+ffMx4nDEcZiu1cu0laJqoGgrREzECwtApiC7mJcZCvrYGWAzHHSh0QaZXEVNJfQSFbZ2kECBFQAlJZRVVo1jUkf2rG09VOa7fvcTagJABYYmATucg85j2mbwNfTKUj6DO0xiHxMd0YUlMHe5de6UEOpNoGwHii19+Q91Ec/rQqoSSQCEB37LACdzBKmAPJKCXvB9DUqu1to6LLbR96eI4SKCuVdvtBJda64kQmcGt4zzVFUZg6RmN8wQwI2i2NnlP2sgaf/7po637OcYxfkhxBIY/4Hj0cMp//p/+OwC8ePGG/+Uf/p/8x//Jf831PGN2WeGDxbum859bN1qPNhPpQXobiPsVMSq7Pt9rpq5HywnOHRiUfhxkPbErDknv2/J5Of8urbL6WF/nqlS3FY3sQ/B4UyFkFtnINbCh9DiB1Lb+LtXiqXzF0iDWeBmca1ab1IFCkFKhtL4fED00bgH7/ciKs+0f3JNx7ppw13rXtN+6fNO9pXUUOgreMhh/RLV4tQEwYq2kJfj4fl1dpppG27GeUuUMRk9Yt3e56zl12+4Zh85uB4XQS2FdO97O+sttbeuD8bV2tNkChwgs7WVEt33etXX3IsNw/HFk+tJ3c5WTD84P2u+9Yu3859ffoLNxqvVSkcUUWafwGmft7QQ6ZiccMkarxWuiIbrtwGob7a0dxUnSH4nlC36ZTrq1+Wvve+cxjUFphVR2ZZvgA9Y4rDEEFxIwDImRi8c1zSKCTtpUwfg6nj5OtX0+TexlTFnMYkpjW1PYt6rwHuZz07Fb2eCE03zKx89+gzwfMBgVjIYFg0HGcFgwGeVorQihBz66yxRrB9vjRPuH+FrVPqbKGo81AWM91eKGxc0bLt8+ZzTOaesLAYbDQawrTPWEERhGmwrnRQcKl8BYIGVACiiNpGyIbGHpKctoOzG/uY4ptha0imxrMZxiE2j2qb0ty9eBbw+1cUjlk9iLX/GSFEqiGk+WRaXQ2fUM0/iUphkZPKVb/0cBDoRasv/t9WjHeFNXBDFJ19UnRtrjbN0d1jS2YwJbxrrd3zowbMeWqV8mNdYxeXGOkHlatEnf95680HEMtcex6Zo1jslwwOnJmofxMY7xA4wjMDwGAB999Ih/7V/96wzHj/nb/+H/wGCyY8P3TN+6d9wRuO0zU+9EO/rzmTvse9+kcpcK5+pGt/y9Y3tjZt1xO68z4kR6NPmMEBzl/PsV0OFcjU3edVoP03/o5WQr7j/6oMVay9ClyyGixYRUOVoX3bYAWo9pO3FX+ure+sJDYgPs71bGVeqeEuMfiunu7Wdn+q3UZMUZg9HTu+93H/N5ByZ9W6z4HXbgtNm67cb4TvvfC6B77d9gFvf4k3Ypx/ti1/mt399rsWth59b7d9t+7zOGdnzHNjOsucH2lEzLxat4fwrJ6mCIrxvNCQ5vK5aprgopNFJFteBy9gIpNaPJU3SWJsKdENeoY/hi/V+7z75/YPsVsTIx74drDEYvgVD7fGj3Y40jeI8KsX4OuVS7LGfv0uKAiqxcelRlxbgTIDEm7jMgE7hMwNAlARQZgcr8+obGRABjE7uVa8FnX/wpdD5C68jkaQW5jvVxrf0CgA/LixRYrR00FpomAsJX3/4hUJGJipvritn1G0RwLBYljWnw9YDp5CcMBzmnU8VkqrFB4ZK1RQsKrZcx3TPVMbagMAAkA/mqEZR1AoVVZAtnswV1WZPlEq1lB/pG0wc411pK0AO1MY3U+cgcOuewlk4NtL1N42VzKC2xjQAc81kZGdOUIqy0RPo4VFoAKFJbpWz/n6QxAwgV67VDy776+Em1iD7J1ti0ALpMH22HvOz5VoY2hTTA2fAXNEpS5BmNqamr50g5RKoTgld4H+J3pUzMcojsrvUde/35l3d4Lh/jGL/GcQSGx1iJ3/vzX+3f4Dam65DPetGm3IXgqOYvsbZMK9qxvsN7s0NhcorORkllMoKCqDhaYu1i7zE70ZR7AoJ9bOHeFL827jGR3AtGhYzKsIIlg3uf4+3ZzppZmtw56vKC0ST653VpbXc5p3uCsb3AUO9xA+8fb9fve+Ku1hr7AWyx2Ya17+/a7/t8Hu8z03kGlvMXOFsnBmqVvhMIvDcoVSCVRqmlrYvWo637h14/9c9v/XU9tl2P254r7f5uu457Pl+3kGhj4/49JPvhPuC1Jd+Td2LLkq5nOgAMR09QetSx/G1qulQ5EIF9p+zqapxvsM0c7+ol+29LTBPBvtYjlM7xwdHU16hsyGjyNNZA6zGmuYrpwgBymcq3nlq6q66r/czWTbKnWN4/LansGoMQAhcCiFgjqRJDXFeX6Ex3i1exzhF0Nuxq2SLTlJgjLTpG0CcGrLWkfPXiBXXtIwBygTyX6EwwmYywPWJsmSEfCF7SWDrGrjsnH1NWbbI2iCmIEVzMrq/ItUMOJA8eFHzy5GMG2vHwySc8eHDK2ckYQar/A+q6WgGF3Y9rGcPUVwkU1nUdrSrqmrJyzOcNZeUpFzXzm5LFfIZzFh2yBKQiGzsYnWDcEhQuU0hTfV6XyhmFgwSb6b/xokQAKKSnqW1Xs6cyhfAe52Tqv0TVErrrAxH4yzSe/uk//B/R+ZhPvvxdEEMCgcXse5rqpgN63bUP7eKRQIqoABs9MJbbADz66Kd88rTg4vKay8sLLq9r5ouGun5FXVmEKJicfBxBsI//t5yLojPWRrXSH//oo53j+RjH+CHFERge48PGHSb91sxXU+5SjQ/Eyc5w8slG2p0xDaGxqGbWMVXtT/dvPMRGCCFSXc8TbjVTv8N57bWeyKY7P+viUHDdi31gdK9twV1A2J7tdKonFFJQDB+xYaa9AkCWtXXe1QTvkVIR8Cm1x+Fdk4Qdsg3Rjiw/7RRj23M3ZrazbXKbuuOB5/WriF3Xqmtnvz23MFsfKvr3mRCCYhBTb1UW+zmChUH0LrOLeG9WF5jmmqp8h87GDIYPGU4+iTvZB+Lu0N9C3kMsaWMnvd8PbM9O0/n2/r2Nof1QTHOKFiA6V7FuIQFRLGuriimsLI7t239kgdrsAJHeF5TzF8nTVXZKtLOrb7CmjBkHzRyXbFOUKpLdSxHtffJJWrjTtP6lrdCTEBKVZfGY6e823dh7n5gpkdIDPUHJVIfbTx+Mj3OdD3E2fberV0yfI/EJ8DhP9DkkgsPZzQ1N7SIoHCiyTDKdRqZQhlh3t7520aZZNmaZVNG+b0ysIWyaCAydiVYXTdMghUyWHAKnBMX4hMeffIUQMDdJWIUIDF+9fE5jXtGktNNvv32OsY4sG3JzfQF4JD6mlAJJvQfnGsr5FcYpjBMYG5VRjXGMRxN89hA4WUl1JTGlLtmF+JBEaPySMYy1eAFnG+S6gz1xW6kkAk9dmQgKtUI4jxQKL1Ltn2j/B0PEhS3zGdAqMtCPnzxCyoCd/TPevi559+Y5VdlQV5a6KlF6RJZNEaLoLDCklHgpertffWiOxgU2SE7PTpienPLYauaVYF56FnOLNZYsj6BZJN/FponXzie10n/xL//m3nvoGMf4ocQRGB5jJf63f/zL3R+uT4b2rdIfMGnaB7DywTmD0dO7p91ta8tdo3ee3tVpNb59rVbUGtdjp3XHjv0f2sZdDAf0GND3nKR3sWfSu89MewPo6wGkdNe8OCcfPAAiSGmqiySA0Ut5tXOC910acAsY2hS6WBe1CfZ3qljuOq/29UMDxgA+mJ3Mrt41eT+kHe/R1n0M5mjy6YoQk85GaD2iGD5ifPLF7e25BSR5b6gXr1jMvseYG5wpo82IHqHzCVk+TSI87eLAUkm2S4VEpknn0kdvaxwI2rzbYyGxXj+56366CzjcwVxuO5ddvpUtKDzE8H5Xu1ombT1Gk4/T1yyL2Yt4nwlBlo+g8QRddFkY1ram5zF0PoniSC2CalkiEZeOYkZ6BA2xZnCpUBq8j0I3QkZgqTRKZTg7Z8AJWk872i7LhzF1MR2mK2cNrgM9S6Djo+G6a1jMSnyqLcu0JMsE08mIXEfRGidWwV9nxp6URZ1bfuhcFCoxxscUUuuxxlMtZtGXUYsIKl3cz+mDj2icxNjIcinR9gV88/01dWNivZsHkZ9S5HB6dsLnX37FZDJkOh5yMh3QVDOqxRxTXlPNr3j14jmvv/uGxc0NQltCkWP0kCZ4arPg6rVA5ydMplO+/cUfkOVDpBog1QCVjRAywzYVdW1wVhC87FKCnfVYY3v9Ebo0zNjdNaYySC0RXiB99COM9+ZyYTbWRPbGoxT4RPb5APhYW/rk8ZCPnvwpLi+uuHj7hncXLnksvsY0Fq1HaD0hqCEyiOX4XWOr84HG+kAmo3hPY1kyusYzv37NYDRlNJkifMCLxJ529YeBv/i7f2rz5jjGMX6AcQSGx1iJv/sPfr76xi4Qsz75uMcK+j4WLC/O77YzWJ2A3SGiafqbmK4ZHN5bytn3iaUSqTZPkvJXsDZObofjVdB6UH1hv513iH19tUsMZCW2Xa87tuU29cl9QL8YPen6ZjT9rEtFfW9wdtu4uw2E35f52QHCXbM9jVkIQbZu7/GriG1pk3tqHreO1zum2u7r19Z3UmfDmApo5jhbUZWvoXydvCXVLQfa3ZDNerrt1hF5cd6lWdfVu+2ncZdsgkP75oBFoM4+wlVpm7RhmvzeyojvO056v3/vhpQuvG1BxftVmizLJ0nx9xlKZUidpz7VsX9V9G4ViAgKRRQ98dYiFehcI7PkjaeScnKwWFNjm5q6usY0C0y9wDQz6qoiz0cEGryvcK7gZPoJQuZcXbyiqUu0ytFZHk3uswJpJE1VYpoaU1c4a2iaCmtqjHHkuSLPFVkuyDU8fPSQTAekFygR6+/annBhWYfnQ1T8bKNTsGxcxzaZxlLOEzB0Mil0RpYsH04xVrKoo9G7lBEwKgXXM4tPQjYusWJf/fgnPPv0HC0DmfRo6dHSMprkuPEA658w1DW//ad/wiAsMFdvef38O37x/QWzoLlsNBczx6x0XF1dM7+pefH1PKXHRmayXMzxfpmmEK0bhgQUwcso6uMBIdH5kMHoMUrH55atL5hfv0RqFYFdYhuFD4kpjOm98SceIf4IMhlZSyni/oOMfSJkIAg4Oz/l7PyEHwm4eHfFq5cvubkpYz/bG6rZS6QckA/ON5jz4UjjfASNPgiME1iXFEcbT9NUNNU76vIdl29hMJwwGJ2TD0461dKH51OePPoTeD4f4xj/P4gjMDzGSvyjf/Jt/OU2VuUuzNSWlfzbfAYPMu/u7/vQtmyJvml6G8XwAcUwMlxaT1DZEKWGqCzVM5oSIQXeNcxvvqUu36yYfh/c1gPivcVuYJPhWG/HoQsArILB/nZ3EvTYlkJ5n/65bfu1z+MiwFtCcDHddZ7SXZOXXbskHe6Z7mq3gLDO2Do/6WrJ7pyO+B4gbf26tOp+UUCofW+Pbct92iu2H1tnY3Q2Zjj5LNUM6w2msO1nkVRZW1a5rY9sbSK8t6l+br6p8upqgi+77XT2FnH1R0iZI0TLPq9aSBA81fxF18a2hm/ZSey+f/rbcMB2W8LZarmT3r3Rpom2wG7drkIISWBHOu6We7f7fk8JFMA2m/dvCIHx9DPywXlM+Vwvyltu2KWAQoiKyFIgVI7WGTpTZEVGlusuVdG7VpESAq5TOFZaRtVjJZBKsbh5gXeWytRcvvklpl7gbIO1dUw9lA6pJMEvRUm8D5w//gqlHHl+is4EWgkyHXj86AznozegFdEzz3tARKarTSX1Ke3SJoN1ZwONcZjGYRqLqaMn4+Wb71DKp/o9lumv2ZhFA7WBqgpIJdJzcsGiXto1SGAwEIzHI5QIDLRFSY8WDi0cSjgan3NtiliHqBVeKYrzjC8mU34x+3/IxIATl5OdaKZG8uPpQ07PznhwfkKmPIvZJdcXb7m6eE25mFNXC6pqwez6GkFkgD0C5xXGK2xKUy1vnhO8SHWJiZ2tQGUDBsMzpJikMeTjwkBo2UcZ+0GlR4eHIEWP6aUtFexApEheFmfnp4xPzri8nPPuzTuqylCVGXVZU1evkFIxmX4Wx1SmKIooKONFBIbWiygQZD3Oea7f/iKqnMbDUpcXBNswVDXPHp/y7Ks/y3h4wOLLMY7xA4kjMDxGF2/eznn9Znct171jy+Ron/XAwWBnX9xhErvXemLy2apvW9qnLJLJt6ZLkdw4foqVurv5q+TTFYVAYn1OhksqkO3f6352ITju7Ge3Hh8gtXY7a+j3Av2dbdwG6Hcx0R+I2asXr2h6vpw6G0AW012z4pyin+5aX2wqvLbprvUNPlhayX8hJd4ZWoXXNt01+tXJzjR9ZRJ/l/PpA+k7fG/XdQkhoLPJ3er77tj/+xY0RtNPd9bMrRxSatT7Pgva9jgbvTATyPTBEbxD6UG8F1XO7OqPmF1/ndLFA1IVZPmULD/dCWQ7tlJIRIhiPt09sj5+18ZjtXjRiQJ5XyOQKU27z1ISAegAACAASURBVNpNN9NQ5fKPnTYhG9htt3KskNCsKTm39Y39+sUWWK5tuGV/ScDEObxXhKC6OrYQXNoXqe64pzAJBONRKjJPMkA2OOHy1c+xbRryKMM5i22q+J6UHRuoFWTS4YNAyl9SFENyWTFUUz755EuGA83s6i1CBMYnj4iWexEgwrK+sAWXPtUTRsbNYerIEprGYI3DNIZqdk0xyshz3Qng5MWQ2kDTxFrFqvE4G5nBalFSlb5jCocDhRQwHg+RwpJJRyYtSjg0Do3FCYWSgesqw+YCm0mcVry8mbNgRGVzKqNYNJJMBT599lX0ztUBpT0PHj3l6ZPHaPljfJBI4chkwNuScn5DNb/h8uqa58+/p2qi9+K8rJmVNimlCowVeC9xPuBcQ129pJx/T5ZPGYxPyfMJXoEMItX9x/sgqAgIZepTUq1gCwp9b6jGERAFePLBmPPHI+rGU1cWKQVZFlVXWx9LqQRaJYAtBc6DtaLzk/TO87f/7X+Tzz55xKOHZzx6dMajh2eMR/dUsT7GMX4AcQSGx+hipb7wrpPwtYlICD5NeEy3sh+CjfU9we6spYE9QGIXO/gerOG+ySsk5nLX6v++lLseY7IqsBNT6tooBo8ZjJ5QLr6nLt/gbPQRNKbCVw1Nddn1ZazF0mg9ZDB+ghB6u5/drjbtiv6269/bso8NMCHA2T3iOIcI8uw6Xr/v75O+vPa53VMfOmqFVUjprtPP9u/7gPaIvoHXbd+/LfaxVDvug30LMBus/K723HNBYW/68yHpkYfGrnavgymlUUHvHOuLm192wjzBT7C2jBkB19+QFadrCzO7On0dvUdVzm3prkrq6C0oIgCO6qP5RkprV0O8JzYsY/ZlBGzfw1bGEOhscVb3F1ZYwyVbuLaZDwkcxjRF7x2CJePZAsL+99t6N+kFKiikzKnLddZbMRyfcfrwM04fnHB+PuHsNGc6dDycKk5GCh8k86qhLBvmZYPOR1hruHz3CiUDf/TP/5D5fE5ZVcxu5lTVguBB5uNof6MG6GzIZPoIoc/xPsM6RV1eYeoGU89oap3+p2l88F29o8rHNFYkcOgxjaecGwBefvtz6spEUDjMEBJG4yFK0AnU5MKgsGgsylukLNDS47yI4NBLnJf88Ys5c1NQGkVZR5A0HWvGQ8VNCVIIjJBE+CUBjfESH7KUqppRnEwYnz7luvxDJqcPmADicTssAp98/lNevbvh+xdvmM1KFmXDYlFRLkrKcoFzC6pZydzHRYST889ARVDYqpf6jpUFkWoQ+45JMd15eX19sgRxLtY9RhsN0Y0Z6+L40yLghUj7DwTRsoWhUxz96//yX+JHXxytKI5xjEPjCAyP0cXf+f0/OHjbdfVJZ6uuRm85sWkf5G4lVVNIzWD4qJNdX4+d9YWHprXeIfZNXj9EzeC+uruOjSSaag/HH9+fGbutTfv2+77HC/vP8+C04NviPVOGYbe4xyGT75U4cDFiK8PS275/H4XgKRev8LamNfduU1vjxN+tHCQkxisqTmpkUoVs2ebh+GOqxcvDz+mQ/rzD+NxV2yjXLTveN/aN6zuM+77NjZA6MnWwkfYafQGzVGcXX5f+j+3r7nTXKLpkME2FSJY8IoCpZzgbF3+UKihGjzeeP52aaPtsJdXtHUj8huDBy40x2bZpuV1iC1XRpR7v2OHan5vg0DmPdJ6gkiddCwp7CqV91jP6nluUVom5W+B6HoohBLIi48FHP2I0fchgkDGaaEYTyWgcyAYWKxwWhSzGDHNBcUI0p/eCX37zNZn05NozOi+Y3TTM312QBRvHhJlD6oomKObVCc566rpMsD9gE9C1FpR0hCZHDB7j3QTvo71SbaAxkXFsakddO5racH15iRSCwSiPipsCRuNRNLAnoKRHYcl9hQoO6V18TwS08ry9lhinsF7w5spyU2nKOpApGBae8+mEYeYxTlE1EE9KRuXXIDtBHCklWga0CmjpeXNZY2zew/uBH/3oK84fPmH84BM++fI3qYykNoImpcgaE5jNFixmc+azOeViTiDj5t0vkR5Q8XJLHwiSmO4rete5tRwJ/esvouekDR0TGMeiQCmJlNHP0IeAb8WCfCskJJIybGR7vfNHUHiMY9wxjsDwGF38/t/72UETtm3qk7q3qhzrr07JiimmuaGpL2mqy6jomRQ+TXND3XoUqhytRwzHT9PvHwhIbIu189sHaO7EXO7Y7lbRmH6KIGv7/ZOYPLOe6voa51ZBfpveFkJc7ZcqW6m3Gwyf0FQXW0H+XnB9h378EP2wl6Xekq638/iHbseO7XrR1JcrjHWWjSGNO5VNlvYAcoDSA5yr4o+N6rjWzBLgMBGAmFn3e7V4jXMN7QBTqlgRTDLVJT7YZD8w2M4MrcchzG36excwVHr4Ya77IdflwOuxL3NgfPJsOYa3HSMQP5eazWTvPfGe43p+/TU3V1/jXU0xeIjOo5BPJwwjVaqPXQLY5aFDBy5nV1/jQ0JCqxKdq2mk6wCxZfjWUlm3LYYEF9VCnXUb23ZedawDBJDeY5rZEhiGQF5kZJlkNJmSaUVTWZpcUhtJYQXGRU9AkzwBIyCMwjI3V5c0VuClxCuBD4LJZMpf+2t/hfFkysl0zPRkwvzmmtnNjKurG7795S9pjGV23XBzfQUhIGRqZw5eKCwGayrKC8nsreT5L/5vzh99ytPPfgOZPaE2OYubNyxu3mJqw2BUJBsGgRBw+vATpIigUOKRBDLXoLwhIFFYpPQoGQHg9Qyq0nJxbanqgFIwHASG2vLR4ymFdhRaURuJccT0ZiRWBIyT1CamXGotyBQoJbleJCQXN0fJgCzOqKzCekljJY1dgsLGRHZUyIJ8kIGYoHNHXZZc+V9G4OYCUoZYX+iXJHObWrr0ilyOF+8TU9iK1UhQUqCk6EBhKmVNtYstAxm9CV1iGq3zfPHpY45xjGPcLY7A8BhAAoUHxm1gajT9rAM7sT5nynj6+f0aliZPi9m3LG6ed5NNpYfkxSk6G3fgI6rkZT3BkFjX5b0h9Fbr+yv53u1OLdzJIvUnx3vS+Hw4UDTmQ4G/e8Rmqusg1t2lyIsHkcEVy7q79XTXurzA2UU6pwylhwzHTyOzkq7B1n469LwP7O+V2PL5vjTSDR+4+zCsO0mV7bVde2vwJp+tqpiGtp0JwB0iVBl8ND33pjM6j/V0lmrxkqp8STl/2XnUxQmv6kCi0kN0Nunuqbb+VcgsvZd1oDQ4gw8tQLUr7NN6tEzcrXHHNOF7RbrOdxJO+lBxl/andvbtYqwtKYbnEALOVtxc/ozB8BFNfdUxzRs7AJTKIoCUkf2sq7dYM6cYPkCrATpfLojlxdn+ZnUpoVvqDHtiNc57pAuA29iuFaCJvy+ZQe88KihmV69wJn4vH0QhG60V48mkq9szxid2TtBkEhfA2Cig0lpCOA/ff/c9TSPwOvZhAAbK8OWXX+DUBEGgcYF89JCH43MG4xuubq6RBJ4+PkMKz83VNb/45jmmiWNcBE9GTQYEJfFKETKBn/0Rl9+8RilNkAoVFBOtGD2RICxKD3nyycfkRYZrFly+vWHwaIjMIuKR3qFMiVc5kihEIwRIBXXtqXxgUcb002EBw8wx0A2PTzOMtAwyRWMlNx0RHtPaGwPGQt1AqEBrCLZiUS+VapUMZFpgw4BFo6Noi1kFhdGyI2Ctj6I81mNtrLuMdecCL5O/pIuprEJEgZik8Y0Pm7dBBIZp/IiAFPH3qGybQL6P7/dTUo2F77/9jrdvXnN6+gj0OX/+d24RhDvGMY6xEUdgeAygl0Z6wKT7IJuJD8x0mfqKLB+TpUmLdw3OllSLlwihexOh2+ic3ufBEwhRlXBL7PUHXH9/y+f76rsOEo25a53QPWrwbk117YGT0eSzJehfHye3HWtXPx3Kmqx//7b9bNmn6YnOrEdX87ZeIrZjX1tjT38Evyk4c5AFyV3asF5TJ2QEeKwygd7VXYppyyAGH8V1Ylr4JSSsuFlbt+2g/Uamv0PYeW9tLLjclzm7y/jbFe3zZQe7uXGfbjvGrmfmXRnoWxYj2gWG4AMBu2ItIVXR+RGOpp+nNP2Y0ihV3mVmxIWCBm8TiA8GnU1p6ktMdUXjr8nMBKWHjKefYm2V6ps11lWopBYrVTKzZwmcW3DYCs+sh/cRHGwTPAotSlgLGxzVPN63xSCPoDCLoFDrmB7pvEqpnp6mUJHVshEoNCbWm/kQWaR3b9+hdWQKQTDQgUGh0FkWDeO9RhAVSwWB715cYFyGFB4lPALP5OSEv/qXnpDnGXmWkWUZWabItEJrDToqsWZaE5A01nbAqTSCeR2N159++oyvf/kWYx2L2RVff/eH/O9Xr9DCMB1qPppkfH5WMD09RT0EP8mRXlLOKmaXCy7eXeG9ZzySDDLPQBkKaopQIdUQ4zVFJqlzhYm6WDi3BIXGeOomso1NOaes2swCyHRM0Zw3smPofIDGRlBYp7pJZ6MNhjUeaxy2cdTlDO890onIFLoIDkNgbcFCJNC3ds1dBPtCgkw3hBAkQaIkCpQWSNp0UmMD1gSCesBoMuYv/4Wf8m/863+D3/vdn+y4oY5xjGPsiiMwPAbQs6mAvROsD2YzcYfYNmmTqT5RZyOkGm7WAMk+c7i/BkjrYWJQ4sp5Xpwx7guPHDDh9K7u0mTja4N31c7t7zU5vo0xu2MaIxwATg5l+N5ngp7mgz6sWkl0NXeuIXi3NqnYnF0H7xLDs2ot0Sq7muZ6K8hZ8YnrYZuNNu7q//b3O573nf0Fb4sDweM2XzwhNf8ve28WY9u2n/X9RjPnXF01uztnn/a2trGvDcY2wbjBhmAHsBKCZDlyIgVFIVGkKMkD6VCEUCQiJ0qkPKG88WJFeQiRCAkkAoISAgQM2BYYd/fcc09/dl/NamYzujyMMedqas1Vq2rvS0xYf6l27Vq11uznrPGN7/t/n5aa03v3V+SHmzES0YGz7WUM3uKDixMsqd+xc/tcubfK+SOqxROkyhkfv7vfdu87GfOKZMZ95+JGxkmbtS+zfIvtt818KeVcYeti5uAXez/XPjdZbwOP/12Jw2iqMwRgmlmMggiecp7uRXxki70h4GNoeVJjCKEQpJ5XpTtmWWUFeT6JgFW3QDXrAGyMh2jNyiLD7Wx8jgbnyQY5OtMJGEqG4xFKEY18bEAKmYLnJXMVDUiaJuYONk2MkjBNQ914nI/M1WgASnomkyMCsZ+xtrI7LFIELqYVxkukEDghyaRFiMD3fPd3YlErl+IS7DbkBCQmQEBALshzUF6ivCZziqGVLGrF0Z3XWCwaPnv6Gaenx7x1P6e+eEp18ZxmCr/4uEZmOV69jxOa2mvmjaBsJPPFnHxwjCs1xakCJIW2TJ8/5ejNMbnKGGSK2krqRmAMGBfBctP4aIpjIqh7+mmMdFBaJuAMk8ERtdGdutj72FNYNxGEOxOzHK0LiSm0WGsp58+j4UyITGHYMCpqmcP2OAvRfkWgCJEFjUc1ip6VjJe7SyDTu2Umokus5dFozJ/80z/Dj/2e79rvJjrUoQ61tQ7A8FA3qr1jJl5hf1zfoA16BkJb1n1dD1AxvM+18bYBqvIx3jWU88dYu0hSuobYe5djkuX7dQY7V4DhTWSVN3n/jrp1PuKubbjpYH3lfdX8ap5k23On9AilB0hVxL47WYAA52qcqyMgtzXWzAlJNulsGftb60sIHmvLLh8vOru+3knq9t7ObfvXdxx2/cwNWKpX3IvpdvRaDidvdcf2uhJSo/b4E9IGy3d1w97AcvYpi9nnGDPF2QqlBkiVk2VjdH7cEyOhOxdfIOUhmq531nuXgG2UlPfV3hNdNwG3m7+/gRKgZQ3ba2dTwpnlUfq5Vbrc51q6Zf1tbMti9lk3iNd6AMlRuRjeJR+eUgxPcc2UqjqLfeQdoLM4azDNDG8d4JFKRRmrlElmGqM9pIzCQudrZFpZ3K8UCigEw6Mvo3PVRRXcufeQLJOxx40Ylu6cT4H0EmMDxgQa41cC6RtM7SPoG2qk8GgRuHvnlNiyFhmpyqhOwng5r5ApKiKTDiECd+6cEoQgBIlrGa30lyUAxmc0XgEp7D0dU+sljYt9f5UR1A1UTcw4rGtDJiUOzcmdYx6O4Pd85xf45PmUk3v3GN25y4t5zdnc8PS85uvf+IjLS0s5+xxmnqeXjmfBIYPjF375N3j9nXd59ytfRQ/v4LI7eDeitDmBAWUZzWLqsqRczKnKBbPLC6SSaBeSg6zE+4LFwndErrUeIURkZmuHNQ7nElPYfjWWan6JkB7hRCd9lkIsH6ECIGYPRlaQdB2khkOZAKMEEdLrLJnCDhyGAC71OlrPf/rv/aEDKDzUoV5BHYDhoQD4Xb/zbf7yX/31rb+zZoGzC6xZYM1063vghpl6fbWtN2wf6epq9Q2ytskEb1htP14bOyGEiANNZxgdvUM5f4Q1Jd7VWLuI/T4Q87eyMaPxw61Aceu2viJgvXV5YfdxvfZcXteDd4vt37U9k5MvbV2/lnptW69kLN4kp69bSPw2v/yA6fn7FMP7jCZvIaTCmXLFAXQ9x26TSQstm7YlmD3s7MF7yUmDa8rt6rV82RiJfZnvG1RTn3f3W/C2i5GYXX64h9R118bFKAlTX1AM7iTjq2EHJjdjI155XSeP3nxfqhB8nADZ0td3pVd2dTGbkRawnR1PFRn2tQUArAXeB+9R+RHHg5OYT5dC4oOLoIHgO3dIIQVKK5RWyPS9/RIYRkdHKC2QwiBlQAiDaypMU6H0gOdP3ufF49/k9be+DTBU8xcImZEXky6+wJjIUjXGU83nVNWcal5SlXOGkzcx1jEcKZQEJQJSeE6OR7hkXhKCwDhwTmCaBbWJERAAeYqSuHPnFB9kDIQPau3wuCBpvKJxGutlx7YFBMYJGhuNX5ag0DG7uExOmiIG2EuNVxl2MOGNrz7EqIIFOfr4lNOjjNFrmqfnC07vPsDzFWYX50znFS+ePY6SVzwff/6URW1QUlF7hXES5x34yOBZH7AWPJrpbEFjNVk2IB/ewftJZOTyU+YLF4Fh6gONLGDANA5ro3TUWY+1FttY6mqBtTVKqWhWJiKrK6+44ILXETAiIju7eiDXQKRomcIlOAwhMoWNc0mq6vner32x/2I+1KEOtXcdgOGhAPi5P/1T/Nyf/in+z//76/z8f//n+V//0l8jhMBofJeqjqxS8Cb1q+i1AVRbayBtc0Z687W+2hwE3Va6uo/U8oZlzDrD0/bRCKEohscMRq8zGL1+OzDCNQY7Qq+7DW4L104D5JBkmKvApA3zXgKT3VmSWX58Pfhra99j3ceQhN1GPVt7PV8laO4pa+ZdD161eJS+P40r35VPuKW2RbYMRw9Qqtgvt27XubghQ2ub7ZM72ySme9Vtz8sezKHZ2NZdMRL7sIWb94F3BltcYswca0rq6gylBmT5EaPJG5jmAiEUzpZbzK10xxTtxRrftq70q/aznEovz+GqM+imc2hfrX5ml6tslzWYXnOAQsZH/crczOqjMPgIEBEp404EhAiAQ+mMprbkIkNmA7JckeUKxnQZdvffeBcpf5yL559y/vwJWiusNcwuL6mqObYx1NUUJQMC27FLzjqMcRSj1wlujhjfQasTtAoMC0nip/BEdi8EKGuYXy4wNoLdXMdtFcDReNQxjJ6YJwggRMAGhXG6YwZde9iDoLZ05i117alqT1U5nnz+CZkK2Dyyih6FyoeE0QmlHGHIaLzG+Ljs52eXVFZ3bKQe3ef+JPDOl76d4SBjMsoZDzTjoY7fB5qqamjqOaaqaMqSqqpZLBre//BTFkXD8/mcJpTU9ZTpVIAoOLn/RRYXXyfIDCGiWkOqHITC1A11VWLqkqZusE1NUy8wdUVwHpuYQoFASI9Uy4siHuNACPG1TdAoWn0pdMYzrs1DTDJSH0LscUyTDvfuTLh/74aRQ4c61KG21gEYHmqtfvxHv40f/9E/CfxJ/uJf+pv8qZ/7u4wTY2jMHFNfYM2cqnqBsxVZfsx48hZI2c8ytWDgJpUGQzfKGXwFjOCu2pQ5rlZe3H0ly99msFPOH8f93CIPi3WdJm3JjLS1C5jADXsgXwGjtdOop3Wx3GM9VxxAb8m89g2KB6MHKz2trTvnsmcKxBUn0DY+wg5mOFulPtSaujoDxBqbLKSmrp4jhca5KpmHLE1EttaeMsTr9m0X23Rj46N9ahtjtrEc02y/567rpVtbTY+ce61W1tsqJBAC72pCCFRdr6tFSJ1iQOgmWFqguBnlovR4HbxuYZrXJnW8I5AmdXz8fnVSZzsobIH9NhmpkEnWt4017PmMM1eZZSFEdLZNofQeH3FgCDjiQB637iPTBdeTmEMhcNKDFwgPIUSDkivr93TmJFJKhIq9ZqPjN3n6+d/pAIQABoMxcghHX/gK9+4d8+DehAd3h9jyjHJ2xvmLc549f8b0wjOdfcT0saK4f4/jN97hYjpDF4qg8yglXcx5+vkTnj7+nCyLfW9SgIxiU4ajITZIAhIfBA4Z8/hCwHpF41KsQzLBaSMZ6gbqOvboNU0EhXVlmF1cMDnOsE7ivMB6xeDuXUo5ogoDKptHFtLGCI5PPn1C2bRspECrwJ2TAV/69u+hcZJMBXLlyKQnSEsVHCYbo/IT8mPPsXAoPE05pbQV2h2hbc3ziwXPzy64rAyLoJl+8BeprKBxAutUcv8M0eHVxXxK7yJD630gOIt1njw/QakhSg+7cxd8mkAJkXX0WuFdij/ZeG50/YdiPdTe+7i+EALT80d4B/ngDt56vv3737hy/RzqUIe6XR2A4aF664d+8HcCfxedjdDZ6GqvUFs7jCKqxSOcbyhnn2PNHOdqVJp5bKMNsuKELPWR6Wx0e+lqX9/Xvr081+zPrl5HlY32WHB/XWewo/RoPZZjS0aZd5YQ+kO27WC+liXZ1JfJcTCLMSOTNzrGpalepPBtG3v6VBHdX19FbWEXd7mjrgKW1QFsHzN7pZfqFr1efawabOTabVnOFSfQHcxY8BZn69hflWSozjW4UFLNn2BtmRgvG39PIHi75jSpUvan1IPY0yoLlM6RqsD7TVOkfkOkndEEu47fq5yI2VPuvFVCvvK5W4NU6J53i9kn3WSKSse5XXeeevDaCJc2vD6E6O5q7ZzgPVoP00g3JJbEse/DKASLqa8+F+KkzmvojWfOTmDPEhzuy/A6Vy+lpG2MwQarvASHEnC4tncw7sDVfSLK/oRzBAG+AwHhyv3sV9Cl0hIlACmje2rjO9MSkmnJw3e+jZO7rzEeScigNJ7R6A7HJxPefOvtBFAj82eaOmYSInjx4oy6+ozPnsx5/OQZZWXxKMqqYVgUTL70FQQtYxiYLxqyYdYFtMdA9rjPjYvAsE6S0aqJIMoHOjDYht3XlaGcz7HWxy8nsV7ggmR0+hpVGFDanIXJumB5Y+H5WUnTxAOnJYxyz8PX7qNkwNQS4wJOg1USpwTSRwbTeYGSMcxeiYDOh5RhiFYZmcw4vVtw72SEqhc0synnl1POZwsqb5lmA5wqsCLHhAxrY3+l9RLTCFwAaxTWepydY5oZTRPQekym7+K9T8+ugAoqAkQhrjiSttdajOWQ606kznfM98ndNygXDaa2/Nn/5t/mx3/ka/0X8qEOdagb1QEYHurla8fgoq6eA5DlE7J8AiQmzDVU5TOCt1v7hNpFtk53XTaeECBUkm/eW35gF/h7iUFiu7xtwK2dCY/gTMWBzStmqABGR2+T5dda46QA6xuEbKdxl/M13jYIKTsZqjNzQvAs5o9wZo5zTcqVSo6vKXh9NefuxuYfe+ZJ9vW99bEfV9/IjWWxfZmHe5nyXPf6ys9CanSu0cRJDmvmlPPPgSgLbKWBIThGk3fwwVLNH3VAxLs6TqCoRbej8ToMhOSUGMG06EC1T5Lw4ei1+Foy4FmbaLnpJMo+hjL71MrndsmLd5rCvCI5ay8oHdzrzsvoKEW43GSV3kaQSOzBax1dt8lcTX4eoyRWJiqCt9Tlc+ryeZwY0EW8L1XBYvpJMmnKu+tHijih0JaQYmt/Yvd7xLpBUSeZF1fAZyCAZwUchs4wBti6nggMxcpyJQGH9wJouvfJZE4jBFBHyaHSkueff4gxrgMVUkqyXKLzMcYE5os2M6+VeMZNcj4uSxCQcsjg9IT3v/7rzC/nSBGYjAuOv/wGUni+8O4XePP1u3z++Dkeza/841/j40+e8OUvv82z8xlZ6ZB6wGzRcHrvdXwCh7VNQfAGyspSlpb5vMIaR7moqOqGqqypFxWD0UPq0mGNiaDKhQ4YDid3WZgICstGMa8j47hY1FxOKwigtWA0gVw7TiYZiICSgVklcE6R64DVkVFtw+kBlIrnSPg5c1OQK42VGqstuVTkQO4drwfHfaExlyWvTQa8dVejjwZ8GoZ8MF3wbF7x6dkCl2c4kWGCxnqFsZrGtiHzDmseYSuPtiN0fkwIo/h8SvdaF22SrhtBAoU+GuGETka6fNaXZzX/2X/403z8ydMDKDzUoV5xHYDhoXrr7/3Sx7f7YAumzHaw0zJhg9GDdWv8jXD6KLHa00xk1wx4O9i7zcA1vaepXvS+ZW2Qekv2pDdgWwh0Ntn94ev6z/q2K72mZIEqluBrlSnJshFZYia8axhO3kyyOhNlkd5GXBB8GuiG1N/o9+61DN4kSava2rvasswvVfvKIFtQ0tN/+VIGSzuY9e4662FOhVCRJRMwGG7P3XyldVN58G0mY7aBypWf++TFe8V57HN/75C374rl6fr4bgl+Y/7fzcs0U0x9QV0+7eIhOpmyvcTZmig3jxsmiAylNWXHLEemuVUijCO7rQqUHqZ7MAOgXHEjXa1ieJWp9T6CQt9ORIT1HMPN/sbgA64Nug8BhI8so2dNgxpCSOAwPb5ldDCdX150jOP59AAAIABJREFUTKFSApFFJlTpQXTJtK0EVaavCAqNE905Cx60Djx+NkMKjZQhmdFEGebJg7eZesHxgxEC+NEff41nT5/y0Ycf8P6Hj6KoNAiev7ikrBsmRydcnJ9BAvfWQWMDxnim0xLrwCb5pbMeZzz58A5KFRTDCaYpcVYn1lCysDlWJFBYwryCRemoFpaqdGgtGQ0lufbk0jEeaio8SsYdXFRgc0HuFd63+YMRXOoEFk1ZM28URktypRgoSZAgdEAUFuUd0nsy4Cvv3GdyMkFOxtwthnzt6ARbTPj1xzO++flTFrVnWjqePL9kOqtQKrqO+iDwQWMtGGtw9imLOqDUKMqsZcFqi4RAILVEJamyTICwY49D4Pzxb/L7fv9P8K/+9I/e4O451KEOtW8dgOGheuv/+pvf6P/l5qBuy+D6RjETt2UYNqpaPMZ7C50BS6BaPI49QSGs/BHaNiqMDqN5ssAvhvcZjt+gWjy+3hn1Jba/z2AnWrpH5m0nyLoGbNy0+vY1gvlosNOto2/97WZsy7rbwhjaZooxM8rFU3wCiq3xi22mOFmmqIJipecuS6zhTRtYeypdx87vMOW5Ltfupr2YG+/vO/ZZfvxqJZt9tXFOvV/PliwXT3G2IgSHFAq/cl2G4OLArrfPbktPZiCGrYf1nswosV1s3UStx1eP823lo505yPrn+0Cp0oPkRBz2U4S+7HNt5fNZfpSiKi6u9EzqbJKA3qYcf45ppjEjMESpq7ULQnOBqS+IKXHQ5r8616BkhnULisE9lMrIi2OkVOkc2a2KBO89yWokLrMn5L4Fid7Fa6UtIaJrqXVu4xPL5cRvDmPis1IpmZQaAZ0NcSt9iovSdTEJIBMwiV9SRjZLCsO8in1sSoKS0WTm5PQOC5vTWBmD7hPLqMYPKe1nUdoYosQxn9wlnwiOj0/5yrd9O3eOR9w5KTh79pimKvmH/+hXuRw1XE7nuKBwPgI/5xXWzSDMCPY58wuBq8eEe6f4RvPe+x+RDe8hsztMZw3nFzMuzy6Zz6YEL8hzSZ4FCuXIpEEJj0zAUCmYLWJmoc3BJlBYVQ5joyxTacGjjz4BB0UucXncn6AFUgVk5hDeIQE1GDB4+23kIMcPxrjhhCafUGVjsnunNE9q5FAyKSSDk4dcXlzy2Ufv46XAB4kL0dk1zwTOK4wFaypMs8BZsMYiZE6WHZMXY0KQBCeRWiG9j+627b0A/Pyf+y/4sR/93mtvnUMd6lC3qwMwPFRvrYXer9a2HpXNQdKO/iDY0iP0iga9bZzEamX5ERmsZeHpNEMOyyw8ZyP4MM0MZ2vK2ecsZp/hXdNJuWI/3ojh+GEX+u1djU09REoPbxxOvu04tYOhli3cWzbZLWDj+56AZZcL7G3cQffNulst75pkx++oFo+pFo8BKOePO4mbQKD1KMnQIltgzByth8vw7BXjD9my0B04yTq2JQKR9P+b5Nq9YtnyLpbqxk6lt62N5VWLJ5j6vPtZ60HMswOy/CT2B+dHmGYaJY/VOc7HYHJjKnzVoFSRpIybSA4IAWdLQvD4DVOVCIRUlCzrQcck58XJ9cf9toznjkmtpZQyaRNbFcKrMGa6bvtSNSvnYrUG44drrPq2vnCRnHRbt0igk5i2gG31GSOEREqJtVNib56irp7x5NNfIC9OGR+/izULBJrB+HWCi5M4Qun0WR0ZvyDbxPK1avvO2m1pwaTxTboefDSdSZM/QgiCsJjKIHUMnQ9JuarzUQSGaZLImjSxRuytaww46zE2OpXGqA3HfOFRSpDpyKRJCaPj1yibGAxvXWQfXQDhA/Na4VNvYYxxgJOTCQ/e+RqZDnjtmTae8d13mLiSe4+ecvf+AwRwdj7lYlrx7NkzlBTkGpY5hwHhp8wvai6e1Xz64fuR1XOR6bQWxsdvI5VmUDi0OmKQ6Wgyg8FUC/TwKDqyClAKytLjnOwAYWM8VWlj/qCtOHt2QZ5LnFMEL2AQIb/UOVJHgC6zIdJbeONdaqnwKqfKRpRiTOkK3vv4PeamwHmRvkAP73Jn8D714oIgFF5KgpDY5K7aKEmTZMLgCEHgbEVVlpRzR5ZPKAanZIPJlesU4Dt/25d6bpZDHepQr6IOwPBQ35LaNciFlQH2NYPbVZfJ63r4djGUcDULr11um4W3tvwt64l5hbE/UkrVsV/O1ZhmymL2GdbMgOgQ2ILILD9B6xEqG3Y9OhGExq/2M3GbRPsfIAZJd6YR/wRqF5jvwMkrZig3S6qcXOUEbztQCHQMYrc9xSlZfhyBST2lac4x9XlkIE2Jc2aLzLVlkj1bZzOSziwQGI7WJZsxv3DlkfmKmKC2djmzbu2pe1nGbFe1cs6eXstoVvT2GpuV5UcweWf7/ROIjKA30bU1Obc611CXT+J9ZOvY2+njoNQ28b7omK0EDKUqkPV5J0EXUi3dPhNT+VIZhGH9WbK8JxMohdSP67vXty2jV1HxEtV3PjpQuINJbcFVfHm/50kgoPVRknEKZhcfMBq/HiMd5p9Tzp6QD+5ycfaby9WKTsiKNQu8a4AQz09IgKAFjkp3+Z/tz0oXZPkxOp9EmacuUGrQbbuzFiGzyNomyeFgfB+XHCsB8IH53CAE1I3AmBhtYI3HWBcz+WzFYmHRWuJyyUBEcxeZTZjXsssalDLm7jljmVci5ejFI5hrwej4DaoaylqQZ4oiU+RaUWgdQ+XTJhWTe7w2ga9+x3cxPjphND5iPJkwm82ZzaZMLy/57KNvMJ9dJGMcGEgYZOmw+m+CD3gLl/PA5WdwejzhtTF8MjkiOypRk7cQYYRWOT7A2dmCujaUiwXlvKQuF9RVzXD8JvNphRvm6UpQ8cQNFEpmIKDROQrP3ZMxZ6OHBKFxSBqfU5qMucn45PEisZ/xGAG8PT7jtS+/zfsfP2I2mxOQ+BRlooVPo87U94xCSoGVAuc8wUucK1nMK/yFjd4Eg2Oy9Px7cP+E1x5c329/qEMd6vZ1AIaH6q3e0Ps+FmpVimX3jJnYY9B0xWWyp3YBw62My9aN619Pa4KzasCwahaSF8cUgxN8cpqsFk+pF0/RxXFnALJcloiDWhENX6TUMT9tcIJIs+RSZmvg+sas4bb9uqZ2O6/u4QL7rWCxttRw8taai2ZWHJEVR3D0zl6fD94naZ3rlbhqPaScP6JaPEGqnPHxuy8vG9zW75qqt79wWyzLLoZs4/f7OLn2bWtfr2Xb73h1Y7dsT/q57S1m5TqyZr40HmqxjY/OntUi9tJ1m5P+P59+smJWtd8FF8O2VTJHWspc48TCcdc72kovu81eAYUAWXGctmULsOpTUmw7HresbedjLX9yD+Y0pIy5K69vXBshePASZBzCN9UlrWlInGiJ8S0qGzMcP0TpYZpga+LEjJmzmH2KNWWUrybjqY6llBLvIyspZHQzFU5AA4v5klGO6wsoOUDpghAsWV7gh2N8GIIYMLt8BsjOqTUEwAXmc4sUYKzDGo81rvt69tkvobQkL7IUqwBaSZwcU1fLAHprI6D2XjCfuy62IcskUoAqjqkaMDaglCDPoMgk+Ip5nWJI0jHVEu4+/AI6XUezBsjuMLlzh2LScHlxwf37dyiUYX7xgmp2wdMnT5Pgl/g9LUwGT3U258NzwQefPSMIiUPThIzGxlB776Ps2TrwLmBtwFnPaPI6Ug2jsUtrBIOK8RtOk2lFrqI09eG9r/K4vhvZXCcwTjKvFLNFw3SRTGZsILWDIu9mBHK+8JUTnp9N+eZnJbaJUmZjaoKPbGsgMBhqmtpGcGjj+YnS4DG1u6BpphhTURQZTV3xgz/wh65e0Ic61KFeaR2A4aF6qy/0fnz0gLKsaf9CBe8YjF6jGN5lOHqDqnxCXT7tXe7OmInb1jXS1W3A8Aob2bPcXdu3zZRGSo3MNYPhirmO0iu9VfnW3DAAZxdxW4RHyZxq8ZRnn/99iuF9RpM3EUJh7YJtQfdSRKakb9n7VB8w3MvwY1vtCxS3MB27zmcHzm9rACIkQl6TbQf9ES0rFftaDcE7yvmjyJIkWWQro1Sd6UdBnuSXa2DEzHr390pP3XX7e5vjvaVcDyiEa1xBb7Aes0UaKaQmUwXF8MHViJaOGVy63wJL0LGrj9UscyRNc4lzNTobJ5C5ZIvj/SWTKUlkrKJ5S0Y5/Yx8eBcpizhR4/3287Jrv2/5u77zcV1Mxepyr+R87lnBB+rqvANpJHAEMBy/0TGWcdlRgSF4gDWzjmWNE2YV5eJJkqwHisHd2IPsHaaepYiC2F+mVPtsbtflCCxAgLWGsCgpFwEpBS8efx2EIMuGHN15g9O7D1HZON5jssA7SVPNMfWMpp4T3IRyWpIPc6SUGCXQOkpHzy8WBIZUjaeuHHVp8QRcUzKfGwigswhmpQHrMqzzGBNojGdQSIpcEpxnXi0dYLUShCwQxJiyEdjYet3to7NQGYEUEonm+PSU+6dDfvtv+xKnx2OOJ2NOjkZcTudczBZcXkx57/0PuZjXTOcLauORwlGIQJ4JQra8kDpgGaLrqfFPoyFOIzibw3B0hD25z9HxMdZFgKyURMlAKd/g/DzEzzpoTIT25xeO6dR2vZ1SRtfXhR10LOlZ84BsWKMKyWSY8R/8Wz/B93/vdxKAv/+Lv8ov/P1/zOMnZ7w4v+Ts7IInT854+uyM0+OMO+9+kbt3Tnj7ne/g3t0xP/n7v4cf+sHffuNr91CHOtTN6gAMD3VtbQu9n3ibMvGqaHRgFtTlU6p5NHoxZop3zdWMvDSYs2a2X0/eqhnGjkHTLmt76B/IXsugXDN43hkzsZJ3t3U9W/ZHpb45IUUCDFOGk9cgxExIgHL+JH7wNgO8FXOdLD8lH5x2PWKtE+m22mr4scf+7C073Ty/AsyODMtOOnfbSYV9mb09qqnPu2tvNZYFYDh+Cx8M5exznC1pqheY5nILO2NTrIBPjryiu1eUNzT1GTob7w5q32ObO9b5uvMiwPVEiNxokuAasNQXCzIYP9ydq7haAcR1AfY962/ZSWfrmPloK6rFY0Lwsd/YLhC2jNJR75iefwCpp7UYPCArTnriWlYC7JEJzMqrx6Rv+7ZJjXuOVZb1qCF2TCZcy3i2L62whtaUHVO4avi0KmMNLIFn01x07KBApAmzCYPRgy7KZjB62K3HmjkqyylGEwajIbAgL3JGkyOGoxHW1tG90xlcU9LUc6ryEu8MUjigQQSD9y9YnJ9FI5sQswej7NTjfMA6j7OB4BuCGWGatxEsUHJClhWcPb8kG+bUle1C6Juq4cXjX8M2NTrXCAnWCIrBhLKKOYTGxO91BVpL8E1kGEmgMIc8S312BmpDCmyPwLBcTGmMQCuJlKCcRirP21/9beh8gCAwA9TpMXdPA/r4kpOF4TR4RPDYpmE6K3l+MeXi/JKAIIilPKH9WQlBJi1BC3wuMV5h3SXTF1POnsBgdEw+PCHPBwyGQz574jtW0DmPNZ6mtlTlgtll6vlOUmOEYFpFYCglPH00paosD+54fv6/+zPcv7u8Vv/wT/4If/gnf2T7tXuoQx3q/7M6AMND3aj+pZ/6Ef7Uz/3dJH08JuMYMV660QFJnhIHvm2wdiuZjAOxirp8HnvyUh9R20eidEFenCKQ0d1Q5UiRDENaF8NkGLLqYthnGNI6eyqVLQczr0juuAsUrg6e95LvXdmmsGQjO1VV/M9g9ACphnsZq4TW0t6bjjlxNuYS+vJZZ30fkulKG3jf5UYm6V0xvLcfU7XPse37/SZo6HVHfcnoil11Q/C7y6xnNHmbLLEl2yImnI0TK87Gr7p8mlivkAbKEQg01QVCakKIjIvOxqmnbx2UrPbatQzyNiDZuWpe+cX6j9vYPGB73uE+vXRbXu+Tql7Lgt2EQd2xfiF17DHWcZ+cr5duqMWylylGtbwV2eGUIelcSags1pYoNQD6olr6D0q/xHVj0qa57D0fWd7jlNtzXHpZw/b8bXw2BI8IsffrCijcdGltP+MDTd0+H8MKQJRMTr4ASQrcAdSwvK5CkjvmxRE6z0FkGOsRIicfFF2MhpAgESAFg4FiMFAMB4phAXkeHUaDrePfIFvjTYVtapq65P33fhNfXzBb1Mzr93CV5HwuOHuqefHkEa+/8z14jjFWU06fUZWB2fk5KlMIKTDJKCeIAWVpkwzSY63DNg6dK558/A8hBJSWsXfPCVADyhqaJlA3nqbx6RjD448/RobIgEohUUJR5EOcPqZyqmPhhABJ4P1PP6F0A6Tw0T21KDguxpzeu4P0jouLSx4/PWM6m69JUVuw6JFI4VHK4aQi1xKbSYy5ZFpdYkzA2cBv/sov8uDNrzAYvYXKjtDZhHL2gnJ+TjWvo0w8SYGlEEwXA1ql8otH7/G7f/cP89/+l398DRQe6lCH+q1bB2B4qBvVX/8b78X/bMwO95kZSFVcGchfPP/HQOzJy9ueneDwzjA6egdbX2LsjNC0MQcxEDoGQPvOQGStthiGdM6eesTaqOemoLBnXLeNYetkQ3p0Mzbyyow+GDO7AgrbGh+/G41Qtg3GAx1YfKm6CYDe0Tt3q1XvzJHbIiN9Vb2N14GNjeO9U+56jdwyToQMoGhldhvLSrdNMXjAYPwa5exz6upZBCbO0NTncXNWzXW8I+BXrpeQGKsV9koIrC3xwaH1qAMjeXEnSmcD1PWL/oD3TUfh9risft+j+kBhPDY94P8VX2ddid3rlSonH9xlMHqtf5s2X94zqqUun3V9yt3mSH3l+o8ZhLqTo8skU1/MPuncYfeqtkdwW23uR9o3a+s1UNg+W1uX1ujy6dfkqs4sIuJp4yYQKBWvteDD+t+MlfU657CNQWmJbRxKqbV1tq6qHQErBPgl8xZSr5x1AsEQrYfkBWTKo1XAlJcsZufk6g4ZhtAsuLxc8OL8nPPZFO8uefHBx7ggY7yEkxgXjVPKeUD6IUqc0Picpjri2aOPUWqMD4rF7AVZdoqfeebTEq0VxSDD2WiwghxQ1REU1rWnrizOxnNxeX7OcKijnFYKpFTcGZ0wNwXGS6xfBnwIAc8uLM5myJS/qERACYeUHiU94zsZ33bnlCdPXvDRJ4+QwSUQLwgIFJ4gJB4V40IQKBEIKh5TKQReR7fR82cf4N37OB+jRrwLeOdTvuoEpU/J8gydKeZzF8GrEPz8n/sz/NDv/u79rstDHepQvyXqAAwPdaP6K3/9N+J/+majr3HP7O1hE4pieEwxuMsg9XVdtVUPBL9k4IK3HdvVDrqkKtKMfRyQVYunSDWIg+hkACOExDuz7F+6ri+vZ19vZHbTB1x65FshOIKzW5mdZd/VVWlar0zwNnWT5ay8t8uSxEPwMWbCVgTvaB0JNz+4KnEdjB9GWWViUzarkxjuK1N91bUCDvvkrnvJLfdkWFvWcTh5g+HkjfjiNZ8LwW/pu/MdWGkZ5dnFNxJAabqJhLY/Mt4bGUplSFV0EsmqfIo28xSKPkSq2/0Z6ZORfksZ4WuqD6zeuMc2sHdUy9HplwG6aJYI/Bucqzsg6WzZublCnPhJKe/U1VlnmJPlR+TFKVlx2itxFaJllFUHQHsBbPeMNVdAIYJuYq/9efUAdMcysYlCCNSKzLp756as2ge8dbjG4ZTDGot3CiGTAmQVIKZ1mgacj38fvAfvJEqJdKwg05Bpidbw8Xsf463CA0EKskJw/37Gg3tHeKl4dlHy4qKmNpbpxSW5CigcemBwJxrjPY2rsf6Iz775CdZER03nAt5asvwYqQfkRQTqykqkESglyYf3KEtHUyc5Zm1pKkPwUFcuZioqgU5fxeQhs0ZH0xcbTVt8gOAaLuYWKVSUnYqAVgElJMqHmGsoPUp4zipBI4oIIPEIHDL4jkWEyEAifHo0i9RjG/ManRc4FY+p8+CswEmPEzAY3WE4voNSGpAIJZnPGqSAf+53fvUACg91qH8K6wAMD3Wj2pZtuAkGr7J5dIPgPjkULJmIPqnT5mKF1Cipe2VsQkh0Nqapz7CmWQ58gqeaP4lgJb6xd5vi9jiGo9fJ8pMoqQTqLaYzq3UFGPYxWz2rjjl+20H2FfOe6+qfBFhaqbbnrh3AZcVRN4DU2QSVjcjzU5yL8QRR6lVhminWlMwvPowOds009qGqHJWNGY0fJma5xgQXw7ZVgVLFMp6gh0F9Jfu/Rb7Yaxhzk3MUromq0FuA0i5QHOK13/Xdbdv/dGkNx68zv/wAoAMjzkZAYpopeIuz5RoQsc08gfskHQ9xAiC6Uo7I8mOUGiR5eHElL9TbNje0L0R+h4x0V39e+/sbTMJs/q4PrK712O55D9+0BqPXqctnKB2zG1f5fqXH6Gy05oq8jLtZYM10ReJa0Uw/JMsmKwzlNeqFZLrTAs/NElKnZ+AovRC/tZMWwYc112RrK7p4DBElpAD5nu7QzrnIHBqH0govl1EbcW5JdMuM27fs1/PeE4JeAlggyyLQyjLBi7M5RR4hUlCRPQvJUtMHyfBozMNJDGY/Pj7l7umIBycZD8aS5uwpsxfPefx0yt/+5V8hnOQsgqYJBbXTVE2BtRXOV9jmHNMIXDNETI5R6j4XL54g1RwXcpyVzC5fUM6mFMPXaOoGpQVKR1ArpYD8mGkpsTYG1hsTj31TWeZllHBmKn7XKqCkQMuAkhLpA0IE7j38Evcefon55RmfffYZ1pi4zxDn7kh5kOl7e9iUhNijGQG4ay9+FZ8DIUjK+QtmF0/Ji0nKNR2n9g3Bv/4zP77XuT7UoQ71W6sOwPBQe9fTZzOePputvbaXy93KYHrVCn6zeg1iViRHWwc4O3ppQnBbnUPbeAOpR52kb9sgtu3/isYhz6nKp5jmMrqDNtNu25Qq1nL26vJZfF2POgv1jZ3aOaDcts3dtq8MrlZt5zcHZ8s3bVnIy4Klns9fya8U8c0ByLIJk5Mvxo4jH9BSXwUBW3r4nK1xvkYmdsO5mmDmLOaPcGaeelgFUubE3LVRHFhnk9inKrOVPq6XcHHd2N8bB9Kv7t/GfvbdFzdiz/rknHue5zZOopUkTk6+iFSD6Kiqiu572zfsbZ3C7CtsOg9tbl0IAeeq3pWHZBbVLlepouuHXDOduc11uksGfGVD1l+3PedhTab5LZpk6VMg6GzM+OiLV64bmR+RZUew5fGy7bjF69WsfF+XtFaLz7ssyc3rOnhLOfuMEtB5BKlS5swvPkzun0OEyDH1ZeybdVX8YAKFcU5BkBWTKGfsaT1YvRedsZ1jqBByCQg7gCiuxG6EEPA+iy6fziNlkk3KuP4881SVxwcZJZVZYsWUTI6dIklIY9f8/Te+zGA4hNwwlzXDexkPT455980ZZTAYVbBwkudTy/MLy5OnzynaOZR0Irxf4JqK+YvnXDz5VXwA62LMg7PRsGY4eoDSE5pyilLHKBUZxvkCPGBtwLqAMQFro3nOovQoKTBaoBQdyyhlQCuSnDPgQ9TdZON73H8j58P330+y1ICPCnSMa5ngeKwJLvYJShABpFLcf+1NjM9xTlHXjj/x7/wk/+hXfp333v+Ejz76nE8++YS33nzA22++zu/43u/nd33fV7ee40Md6lC/tesADA+1d11hC9PgY99stH3NWtZXsVuaur6Qqy/tAlg6GzM+/tL236XQ+23VWdQHkpNhg/c1UuV413SSsHL+uLOYj8Bz0BmHRBleAqR6cMWIZFcOZB/oEFJcK+VdvnmP9+xi3no+3zJf4goLG8gGp9efz42PCanRuUazjHZo+7GybETW5ZY5RpN38MFSzR/hne3AVifNvRJyf/2xWnNxLU6jTC87wpjdLq69wHDz+LXMY8/51nq4Hzi6KYBqJXg7GPzJyZevroOVvuHretrSNrVh9vF7NIxyrqFafI53BtPMaMLyWC5mnzM5+fJOt881UH/bSY4t13PfM0pl4/57Ydv695QJr36+F5QWp+vbeZ3hT896pdQgNVfF2UmW70rEIH7QhzaL9UmUgIfls9glSasQCtNM4zkJcaUhMY+EwHD8IJrTyBhqv/pM2Pqs2thu5xzCWoSRCOE60LiUlK5P6AgBzsb+t7Zvb7WUlixoKCsX5ZhB4L3EZQkQ+vYrLktLENmYWS0xTmJyhckUVmumFxWL7AQTMhqpKSaKB0PJu1/9GsdHE44mI46ORijhKRczXjx7zjfe+zqXl5fMZlMIkbELQeCDxPkXOH+GreFs8SnzYsLR8Snvv/cNsmJCMbyLMYHF/JJyNmVy+iblwqCURGcSrUTsS1RLkBgCSzltkoU2LsN5ER1GPbgEOLN8zGBwhFIZPhR832//Aj/9L34/P/B934kA/sEv/xp/5f/4e/zNv/VLCCn4yd/3z/Ov/cxPwM/8xJar6VCHOtQ/zXUAhofau548nfHg/mTJGt5wMHYdSGtru4z0mkF8z2ColWReASoC8uHd3cu8rsSquc5R2k5LtXgMsMYgRplew2L6CSobIoTu3WghBN4ZlB4wHD9cDoKEInhLU19QDJYGIOt9mGxnDW+5fzt/3lJXBtYrEr9NoH2bbewNgReKPB2T1gF08zraFuC92Yfnux6rJZPS9uFx+XEcMYaw7MO7YggSAcv88qMuq3BnxAT9zKMQIkr1bgIy9q1rpJO9wPYm1TJbW4LtCSyD7VO190hdPmc+/Whrf+n2unpwwoaxjtYTlB5EhlKvKANMG1NRL1muffdt1QinD6Ttu+mh/1xcYdV7Jheu/P4lSkqNynOGo9eQMkeoLMqDZd5dz6302HtDcE2SsbaAv6FaPEs9jQKpcnQ2YH75aZIlp17HICLQl1l01mX9nvXWYWkisJSx7627r+VSWrr2GRewVkdzlJZRDC3baClLG/sQfTSX8V5grMIl9iwE0BoGgyG1icYzi1rSuAzjJSZTfPNJw8yOaLyithJjo5TzrS99d1RbqkATAloGismI+vELTu894PTefQS/mIzIAAAgAElEQVRweXHB2fkli/mMpolmLSrJZZUUODvn/PmcF88+jT2XHrwP3VcxOEFpTZZPGI6PUDpFXEiJVBEgShEPkdQiycvh0w8+4+zMdMyr1pKH73wXzjqa2mGM5c/+1/8mv/eHvmvtmP7BP/DD/ME/8MMvf2Ed6lCH+i1fB2B4qL3rj/3sD/DHfvYHePpsxj/45Y/4H//8/9yF3h+dvMFiEQc2rVueVBk6m5AVJwhEJ8HcVludDlNdN7MMW34mDrh9GnCvgUMR/7lxr96VDdu+3m3VDo4HowcIkSHVChOSjlf7fVXyJaXq4guCd0iVc/Hi15ghmZx+ITEqCufqpblEkGmwpZe9d69y33b8rt9cSCPQ+zOaPdXX03cbILPWh9fWaq9aqsHoPovpx8BqH16V+vBmWw1BTD2l7cNr5dZZfkQxuEeWHaHz9XD7q9sm1var10Wy3eZbyi37zFay/Pj65d4WBAHGXL1O1u4RuY0t1F3+HSSWy5sO3G9KI01zEftWF/MUq6BTL10ZNyYB/NWonSw/QgjVgccWBDkzR67EV8DGvm8DaXuweKuf643u+FaZ8axs07b7KuAZHr2ZojiWz+FWMdEB/pVlOVevAf7gHc6VSap6jmnKNfAXQoj5jCHgg0nPw+V5lipGDYkO4BdkxaSL5WljWuJ1kiF1jjUOU22XhwslqOY13nmc03iv8U4iFXgbEDIybkIIZHZEZcBaaAw0RmCsxgwEnz8rqW1GYwSNjeY2k+O7NAaMjY6c0UQGtIKzywpnFO0DJh/f5Y3JXQbaInzJYjbl+bNnTOc1Lkgap2mswFoIUoCI2yaDSJMqU6yBavGCixeBwfCYweiELB+ishyZZLZCQF4s/+aenL7Dn/qP/g2++2tf4du/+i5f/8ZHfP2bT/gLf+Gv8pf/t7/BH/2j//IVUHioQx3qn60SYR891aEOtaPa0HtgGRjtYn6UdyaaGtgaY2apP6kmy48YTd7sBgHRQCTrZvqjBIk1w5mO8dlTWmeaCxazpfx1FRhKqTm++53Lwc6uZd/AzMLU6+tcrShd/eI1G76jAixmH28FX+XiCdHDVa5NoV93c0djndeQarAu3WtB5r6DcRedC7eFcAshyPITRkfvbKz7Zoyh95bp2W9s/d1w8tbWQPRV1nDn+lYZn+7Dy/+2ESubpdK1KlN/qpJFN0Bu74ForHOJNYvIBm+YgXSuut6isiFK5gilkUJTDB900uM15vEVgDbvaqbn72393dGd77iZC+cNazH7ZKsU98o98rJGQity1haE1+XTzm3TJ6YrpP+3JZSOH0xuHFJqJidf2ZkbKYTqnD77tqOv+s6FVAVHpyu9Wq+SOV5ZVns+olnM8kY4vf89y7evPit3nJe+eyXLT9DZOE3ICayZYcyMav45wcc8SGcXnexUJJawZbekbJUTAK00VazJXCGxbkqR5XmarEmOmSJKj4UskEpRDHLygaYoYkOeFDGYXmuB1vD2F7+D0dE9jCWGutvAeKgYZA3v/do/oG4CjQlkWpBpwZvvfpXJyQPqJvYP6q73D77+j/4f5IrqWUrQKjDIPIWyFMqQUfPi2QXf+PgxAYEJGuMUxgoaE/sMt53COMGx/FJ6wGB4zOjofmQOV/oy//P/+F/hJ37sd9zoMjnUoQ71z1YdGMNDvXS1offAMjB6Wwj2SjlbAaFjx5yr8WZGOfsca+Z4V0fpkirQ+ZgsP04GBDG0W6XZ6jVZk217mKK8qQuqZh0UAuhsj1DoVakYW17fUn3xBbCbFd2rBLF/Z0tFcDeM0QIiQ6i8m1VfPUYx6L7pwuyjNX40D8HAqnPr8muXq+ESUUWWOI8W6isgJoRAVpy+tLx1t3PndifLtXXuA/C3yAF39caOjt7ZCqC60PSe68Qnt8/oKjmjLp8lhttQp2gVKVQKt5dEx0DXMY+b4fZbWbWwm1ULSQ67WWv9vruOGdt/tw8Y35mR2NfL+hLMqFQ5ucrR+RG2uYQtLJzOj8mySffssmaewuUvEgN5GdnFjfvD+2aPDYvMsVI5q0H2xfA+w/EbND29nltlpDfsXbyWrWTjfKS54p1MZY981vWwntsmbnJ1Z3k+WDqcOltSLiJ4FyEggwSZAtllQEqZnDuje2c0s1luNyTGT1q0tuQZ5CpGN9igWFRj8AvmFwJbT3DDY1Q2IssLhEhyfAT58B5VHTDGY238XleO8VhzMfWYxpFlEicEQgRUPqZqoEnB9RGgQvAVZR1aMUGUd0pBrmOQvRQKKQLIwPtPAhfNCdaablukgBjlKPA+RNMaF0FgOmFJAhvSJNwInU2wxsVn+kp979e+1H9OD3WoQx2KAzA81CuoLvQe9pZ5Kh3lSYoNQ5F8QraRdTUcvwUh0DQXWHO5lsvmg+lyt4ClnBKZZu4DurX7b2eaEVvZpSt13eBry+9fJvB8a60cz12h72tMS89AUOkBisHNt6HdlI3cyM1+vOAt1sxp6gtc+RyIksTR0Zs4V8WBnlR4Z5YB3df0363uS19/IRCZuuuq73xuDp43WeA+eex12XY7rh8pdXSVzI9YzMz6RMoKFsiLu7F3MkBdPaOpz7aDFDzBXwfilxWCw5kFg9H99bgPbhGHsqO29bvuuo67e2QbqNkF6m/b47dS4w1GO1d517e6s9I6r7s/vKu5eBEZ73b/p+fvd4sRQkWwn1xa488DyvmjzrxK6cHe6oW9jhvL87HZh6308GoUUWu81bP8bYoBAKV2RJBsvlcPObn3XWg9QGmNLgYUgzH5YEQxGCK1YHw8Ic8hywJaGYKr+Pi9X2Qxn2GqBc6b1I8Yc/+Mk3gpUdJzPLzEB5DDgCfKjRcLgfOavBgzHE1QOuPDb/wqWXFEMbxLXTWUixmL2ZSTu68znxqUFggZIyGkFCCGNCm43jSexji0EhhTUlYx7KEFsi3QkzKCQ9AYrxje/TInrwsIhqaaMb14wWw6RbaRtUkeGoPq1yM8vI8AsanOqRZnKDUkKx50x/W1Byc8uP8KeocPdahD/f+6DsDwUC9d/8v/viIdusXgbJcpzWjyNlkeDTjy4Z1rDUXWfxm3I4K1kN7rsGZBlh9d75B5w9o14L1xQHb3weV/d4HONTbyVUnNNjelzY28rlble80cRMC5BhdKgncp8L7Ee5OkXpvnNMpbs/yYYngfiLmRu/bfuXqd4bipzHLH+6/NKtyUoe57/NP7+wbTOhsvA+2BUfY2o6O391v0BkjZ1oNnmynGzGjqxNjkx4wmbyJlTlOfI4TC+yYajsgsRn+0PcIvcY31Hc9b3SO7wM+W6mOds+scVuHq+d1QFFy5PzauM9tMuz7CVjrpXUNdxQmPEBzOuuhKnO4LZ6ut94dAJEfjITqbXGWPZRadW9XVvuXNqIqWOd7sKtHb+navAZl9zqpbszjpPx/D0cPU55lcibMMqRQBgXeCemEQ5Cido/MxubaMT+4znNzHO4+xBlOXBAq8s1jbYF1DY6MjbnALlIqGL0oGRrnHBYN1FyymCxrjePHkg/gc8+BcMrVxASkUdx68RS5i9IYUASFhNp0TREHTeGzjqGtHReD55+/hjEVIUEp2IfYEiRQxGqNxqluHU5DpjMnxKZPjU0KA6eUlL549oZzPQcaeWO9EF8khhEDplH0YYDB+jWJ4EvsjK8t/8u//ET748PHWY32oQx3qUKt1AIaHeulaYwxvUbukelds4m9R7QA+9pcIBsMtCwxQlY+T7C4OmhazR90gVqmiG6BpPWAwfrjGMDhb7Qy9fxUszLXHaVu9KgORWyxHqpx8kGPtkhEGyPIxWTJf6ZXvmRl19ZyqfNaZFsX4iaXMbdX11ZoZzizQ+Rgpr2Ehb3A97QL7WZ8ced9KYLLPdORG0uON49+BlD3Pb9uDByHlEc4JwVHNH6dcuxQXsAWktHEeOpt0YGUzEzSCoOT+2RfN8QqZyr7qk3pneTKW2XW8dvSg9r5/pZpm2VMppO7A6HDydpLGZ8n1s/2e90R9VFy8+A2MmSUWXvdeo/tUDK9/sIU5ntxY/r3tGbUri7PvfLTXjvce7zxWWJCii62oQ017OSoJYqhpah9BnA94pwhizGB4hM7y5IpaRCCpC1SWIxAgDRJDsDOCN1hT8ezRB1TlHNvMCb5BiRDXgY+9f85jq0+4nAnywRGj8RiXFTx99BHF6DV80Mynl5TTSxbzC2w9TaY2EqEkOoHDKIH1aR/iz84HlI9g1HaRFjAYnfDwnRPms0sef/ZZvLRcA3iM8R2ze+/BWzS2oFwEytmnTM9e8Ad+4l/gZ3/6997oPB7qUIf6Z7cOwPBQL1VbQeENBt43yjYMxD+ktwwkXy5mQx4VojyqDaVvqxicUgyi5DTLT8iKkyvMwnz6MdX8EdZWkDK8onlOsfZeZxuq+ZNoLqKHt2IP+45VyxZs2dGr7MZm7XuutvVZrr4uet4rdktAh+OHSJF1n9kq31vZ9i5c3W3mRj7qciOlzFB6SF5Es4v2OtrHBbaPTdlWalcf7Z5A2vntoPDK8ncsA3asa8/z2/bgeW+pLr7RAQ2djdApK3IbiG/qC86T2Ugbm+J3HDOIcvHo/DlYD7bP+897b22+55r397GV3bG+TvHwLWBKx8fv9j4P1qI+WgVEM9vJPN60grcsZnHiRkiN1kOULpiev78BWBNzLPMIUjcAa+y1vFp9/b+E7cdEqmIpcw0+5hkKQXAOJ0CqQAiCumxSL6HEmIq69smAxeNddPE8vv9FMn1VPh88OAKSIl7jg1N0JlEYFosZR6f3UbKVdE6Zz6bU5RRcQ64dwyyC0CAMZn7OwkmePf4Am0xinHPJ+dQzGN5BZSN0VqB1jtMKGZEmdR1ZRCFFAofgbASDUsbvIR2rEAA5Znz8BYyxHI9y/sS/+4f4Xd8XXUT/zt/7Ff7aX/8F/tbf/kVyKfihH/1Rfvanf5gf+sHvubL/hzrUoQ7VVwdgeKiXqv/hf/qlm33gBsYeVxiElcFC3/KuW2/wYZlttVLXbUefhG989E7HHJpmSlO9wK7ED5g0iDNmjtajNcYlDroKsvy4M25Z7SXaDL3fVkLE2I2t2YXfIknpXrUqL9slHVwBhX2fX62b5EYKIagWj3FuE6hs0Xy2MQbBrwEbITWD4f3O7OiVVWvW0SMj3TYpslX+etueuh2f62OfhuM31rapNXNpGcCls2Sdojy2s0GmifeHNNGBMn44UM4fMz7+4v7B9tv2Z8d+9eZFbh7r2zDo15yHPub5NvLZPuZxdPR2AnDFmkEXLDMifZpUcb5hdv6Nzpl1dTuj4c6UarE+UXZd9TGPff3cPmw/JptA0juHlxLn4vMtGcXiXUAqiVSS4OfUtY19dim/UCGRssC65UTgplzWBov3ntzHHMM8y7AmEJQgqICUGYPRXUaTO/ggMI2hrqZcnp/TNFOU9EgRyLUj14ImEzgnMEZhrUxAdYotp5QzR0CR56Mo82wmMYJCSqSWDAYanUmCBemj6cwSGMYsw8XCUFeGcl7xZ/+rP84P/sB3dPvyR37q9/JHfurADB7qUId6uToAw0O9VH3hnTs8fzHnG9+MZiPXDlQ3frerb+xKNt0+rpI71tvmyW3L0tsFDPeV9GX5Eaa52HhtAkwohvfQiW1ROrIw1ixwdpGkev8ve28eL0ld3vt/vrX23mdfZt8Y9mUAI2BYwqphuSiJghgHRG+MmpiYaLxec6NR+UUjud6YXDQ/Y8TwI0YjikoUFVRQcRlhQAeGYfY5M+fMnL336tp+f3yrqqu6q6q7z5zZnzeveZ1zuqtr6z6H+tTzPJ+PwUWlUQVzguz9oeuMMR5n4IXeuyY7rH1WYdz56XYuzqW5rS5izq6dYU5HhiLdVOIcBFGBmhxy3DubLpRt50LZalwoW1YdtcohZ87LjZqoO8Jz0jM3co1BRElFubC34fzqBdw7+WpCZ+HseoQbZdRNkRa6ed86cPuMmvnqRMC4IsUVKpn8qoBQkaRESzi6aWieULGMGr+pUrc90cDnJP03PJwPmJtByATHhENwbjSI3r4KogxF7Q3MqYbRtoU1rH20y7bqtnOqXRB1MyGV9VUem/ZBlJItgiuZGka5sBuAL6x+0SuPSUjVKZhGtfXvXhfznpZlgRmOwZjNRRMTAa2qgTGG+ald0Os6LNOCIApcFKoJGLovFqa5U8T5/4Bl2bAtQLIAU9eh6xYsi8GyHJMYiUEEg2kBNpMgKr3IDfTAMm3oWhGl4hy0WtmJ7LHBwF1HJZl54fS2bTvrtGEYZdTnirBME0oi78xTy5BlwakU8oB65ghDy7QA8Nd+8kNvhqpI+N73fxoQhQRBEIsFCUPisPjgX1zrfb9j1zRe2DqOBx/6Mn7wgx8j37sClUrVq8D4g++VRB8SqaHYdbcIw6hWyE48ZNoIisN2Ew0Y3YSTzCwNXFy7bXqBCZyI/XSjJWxLd6IILNiwYdsmjHoBE3se59b3mSVO4LMI06j5stYkXyB0U7XlCFYWY4W/f0YvyoXyMN43JdEbLmYYILIkRNa4UDb0cuOC2/eGWGYdyfQS1KqHnHY5x9DFtnkenhfnYUccBH+fYVue66QbUVCrHIyPbVgMumw3jZr5ihIwcREimfyawPb9VT5XqNhKZw6qzRWvZiFvGJWO5uzcFmJRlCGIKv/9EJOoVQ45s5FJCKIUft78b3EcIaI7qp16IXOqYTOpC6o8+m5K+KN/eOUxAVFSnHxO/pXPiNZhWW47dw26VoRhVLzoFct5D9zKo22bmJvircZhLcZKogeiqEKSkt4Nrpa/++BVQ7dVmTELtsDAbMA2TWiMoVqedyqIfFbPYjZEMQHT5GKyOa3Zf3PQtm1YJm9DZbbGhaEtwHKqdcwxoLFswDJsGBa82AhByiDfn+Vtn6aBWrWI6UP7+A07AILIIEoAbAbLBkzDhiDYMAUGkwHJdA5KQuHtsHUTgmhDcDIb3Q4X29lf07IxOtyLNSuHcfEF60AQBHEkIGFILBprV/dj7ep+3Pyac/DDJ5/Fuz/wBFL5+NfUa7Mw9KrjfsjzD907xqX5XTzLUFI9MwsW1l7XibAJa0N1V7MYbqKsi/XEtaFFHItbiQqs07nQrpXHkcwMw7Zt1CoT3vO6XoZpaE0b4N+7LXo8d4wBtuW1pAqiDElKOy6UvPoVNpsXOtvVbLgRFzHhFxtRx9/m5ygh022URFSOnCAqSKSGkfC1qYbBxYsB29Y910+/A2itMu4ImCrKhX0AnvXdMAmKFYGJ0CqT0KViMKZgIUZC7aqtTRXeyCpOmIhHnJlLrmX7tmUFbkp0amzC5xFbK17NQt62DJim5mXghWFZBuBkSHJHXAatMh0QLYIgedvjN2+y4a6f/jlVW4dtGE6ls3VONTLGQUp3JjbBl4nKCey4wuyjo8qjj+Y2bgAtn59APqdRgVadarjimhpMM3gu6rU5zzyHCZIjphIQJdVXfeeOuIAKGxIYGARRALNs2ALD3P4XYJk6RFGAxQQwwQYsC7Kah2m47ad8R5s/cjb4A3wm0IZplGEYFheSNo+SMJk7O+tkCFo2TMPmgpIxCIINS2AQmOT8/jJuVuMa4ziniRc8/X/oRJTmD8Ca3Q81kYWa7IGipiDJMpgoOPtr83+OeF2zMv7vEEEQxOFCwpBYdAqFGp7+VbRDp59Mfg206mTL44ZRRamwt2UuD4BnnS8IMtREH5//6+Diyl91s7x/8QYjLRdcMduJq15JzSKok0pOG2zb8uYZm2dnACCRHHTOVcjMkeFUYCxn5sis8Xk8R7ww5z/L0iNjPfwXxvyrGAjvTqSGoFWngzEHXR8kYsXNYrXoRV0ky0q2o/eHixcRQKsDI2/RqwYEjN8wxLIMMMuEZdQgiFUAAp93DDVZ4tmFieQgNzHyCZaW6rAggUHo+HMWNYMHRFfNo9sBFykvLeL3Laz1mwkSZFGFmhxyPoO+z72gAKx11s6y6qiWxwPtw5ZlwHLm7BaDxZxTjfycHqvKY9N748/nBMIryrKSh6zkoSRyfC5bm0O5sBdadRo2gOLcy2BwKoyMeeKTz+M5pkVSw8G1Wj6IRKofkpKALCfBGAODAFnNwTTNpuogfN+7YtFpKTVtzE/vhWWagAynPZnnFNrOjJ9pWk7AvAXb4m2flsAD7hljGN+3B3VNB2BDFAWIjjKUJG4uIwoARMAGnwm3Rf61rpUgMAOleQ1gAhQlBVnJQU5kYFu8mrlmRXyHDUEQxGJAwpBYdHK5BPp7O7swj7pQkqQkMrkVEKW0cyHgq5yEwYBKaT90bd65Q81b/HjItOFr92tFlFTIERe+LS19MRfXcdWxjtpiXbowFNG1ucjjSmWXR17kiXISotyowFRKY9wkIiBearBMDVpt1glSbsy9ADaff7QMmBH7Vi1PwNArANAU3q2AMRGV4j6IUsJpVwupCCP+PMRGSXQpTEIvkhmDrIaUvLs0fBGb7PqbowoEUebunIIMUVYgCioEUXayyuq8fc/UuXBxbm6YRpWLI9viQsbSWytwtgXT1JzKsu2YtkhBAS/IUFO8tbVem+7sgHzVoa6EJOugShjndusjKi8vkR6JNDsB4LWL+iukplFtaR8WRAWl+T1eJZE17Ug3Gai2ZaBablTy/XOqldLejg1jePU53IQq9HzHfE47rjweBlFz22qiH6KchG3bXPwoOWTyK1GvzaJaOgDL4vOOer0AQ696ZmG2bcM0DdiowLJFbtpiCVCSCiyrAK1aQK1iOzehGCQlxf++OI6qosRvEIiSAkN3bgQYdajJPmd/ddTKBUiyBENgPA7DrQg6VULT5I6nhjPv6MZOuMHztXLZc1E1mQkw5qyDQWAMzGl1ZYxBliQsXX1WwEn1T992LTZteh47du7D/v2TGBvbg+XLR3DaWRfgzPWdZZgSBEEcDiQMiUXHsmw8/uTL/Ic2boFRd8BdMvlVHW83lVkKZJYCCM4zAXCEouXkFLa2+ylqD2YPbYbpXHjJcgaymkOtcigwZxOYt3Ed/tyvRiVy3zyh0u2MUhsWKyy8eT1cvHDjnGRmmRM27Qo7GaKk8DZTJvHweqMOy9Bg2Y1KLBcw5cbFrWNvb1gVWBafDWupitkWANsRkipEKcFjQlzTHslvXtHB+W4mpAIZFhnBnPYxUUq1Or52WeGNuggHglEFbs4m3wT/peHRJgnYlhXcdsjnyG2l5JUvDabBq8C2bfoERtkz0nEpzu/0HbdfwKtONVhCtTzemjfpc9/1s6Cgeu/F6Ghm2IhszYyORggTm2EtxLx9eNQxLuKVKTdWo5EtWOfGOV62YD3QLhw372g570W3zp9Rrp/RL0D03129y8pjl+7PACIrroIUfjPQFcSiqECUVKiJPAy9gmr5IK+qM9aYBzQtuPakoiiCOdU5QRR5K6lt4dDYs/ymme0IeTf3wb+7NpBMD3odKIZRhppIQU1mIAgqGLPAdDimMXy7psFjKPgsIxeEcL5+4H33YLA/h0wmhXwug1wug1wujXyWfy0UyygUyyg6X+umiHJZQ6FYxv4DM7j9tmtw+23XdHCiCYIgjgwkDIlF5+Udk9i23WkPbXPnP+4Cp+t2tDYXL4wJvHrTHLhsA5XSPu/OsZ/S/C5+B7pNdmJc1TFwHP6LtW4s70OesxzXxjCkLmaX2jmHpnOr+K47woU7oTp38S3baRWVYEdVcyMID+9uXGDreolXb5zZSsvSuWDyHZMoJgAm8Lkw54JZECRUimNO9mQ2um3Xebz55oQrCsEASVYbc0kLjIboOJIC8OJUWipS7WYvnfVJzpwu4FbDWsWzbZtIZZbDsg3UyhOeqY7bXm2bOky9ysWDUynWtaLvd8AGbBu2bQSiVlwkKeUt1q2Y6LQQF1bhBVqrsx5RlbOI90ZS0sG/Bza8+UhXIIrucYKf6+Z24XbzjuG7GV2ZDHf9TIAxAZXivvZt4x1VHlPxs6ptbvT5Hws7t4LzmffaOH1O0XW/G6rNj1ySU0jnlqNWmYReLzV+NwH+2WTO74ppwXCcS5nzOF+E+VYZ/HC5z9UqUwCDV8nT63MoFxlESYKippBM9UJNZp02UguWYcEwzEa1kDHv9X/01teFnleXXDaNXHbxqrIEQRCLDQlDYtH5/o9ehhUSCRFGPcJCHkB4G18cfqML54Kj8QCiL1IZYERU+5LpYQhiMjzo2ase6E77mey1V1ZK+6FVp5DtWQNBVFHX5hoRE0wEbEdQQQzsRzfEOULKai68utSFlT4Q7Y4ZFvkRXKB1O80Ewrt9++K/wAYaLXW16hS/yPZt2s13NAFYjjBkogzLMqFVpwDnnCtqnleUfeh6EXq9EIiM8ItCgME0NQhMDc+J7JCotsfmtr2WzyxCznMX4jTSCVPJQUnw9zWRHIxdh21ZMM1aYC6Xf8Z11MrjsKw69HoBlmV4ralMUFAu7vN+9huINBsoAZ0fj0uUKBTCRGGbmzBdC8wIms+1K9J7+ge8Wbi4vx3ejRGjhlr1EEyjxquiTaLSE462CUMveTPGtfKhjttb4yuPLF74AQsW74wxR6z6ysI2N4BhTPCqwG5OoSsOBUFCKjMKgFchK6WJhsiz7cb3PhHYIiDR+va3WJUGdxZMAARWwhwOgTEGNZWDoub4zSiIsLxKIT9n1151XmcnhiAI4jiGhCGx6Iztn0UmLaNUjjZ1AQBdK8TeTe+q/dKPs3yn7X9xFTMAyPasidyPMHEDAGqyHwCga/MwjCoMvezlEtq26c3fiaIaqEYqah62bSGRHOCmOk1YZt1r4zNishdbqpT+75suluMyHL3ZJecCDpYA7mfiVAzhuuY1iabm893hexgmZtxznEgNNsxumCM6RMkTHp6oitlWubgPWmUSplmDZZngwfYVSHIKoqhC8QlqBoZaZRKKkofUiblHF0YpQHRFPFZ0d/p7YEcL/m6iMJggQBKCFUDGhH2eDKgAACAASURBVIahjrs5m89DWrYJrTrJz21gfyx+4e98TgRBBvNnQDqGRZKcaXEiBtBokTU0r927mdA20qiOBRbd4usJzKZKc5hwd4k616nMilYHX287zt8OqZHnWS3th2LlAeemWHPl0fYJKr5bPjHk+52MI7zyqDpzv76ZR2ceT3Bmgt3z0AnN57bRmp1wfnZutHjrs2EZNUeXCvBrPVf48Vk9BZZhAY7ZCxdwQrAaaNstNyYZA+zGgHRjUTAwuErUt6+2DdsEDLvx/wW9Pg1g2hG4EtRkD5LpAQAMoyO9+MCf3dbZySEIgjiOIWFILDpnrlOgKKfjV5vHsH98vuV/0txNsxwrSA6rjbRLERmbtecPW45bb0RFQlbzqJTGWhZXE71QE70tofdh4qJc3IfS3E6vYsPX7wv1dlr5BM8hVEK1dABKoq9h1hN2frxZoPD3IW5WLPLis117bBuBGOcy6ra0tl1PzPrT2eVIZ5cDaIjsujbntVzatg2jXvKcWe3yBBgEz+UzkR7xXh+23dbZ03ARA4R/xkOrhguoVC7EYZRvDG1/f2zb8gSb/4JcEBUIAKTUcOg8Yq084VTIeGyBpVdgNO1jp1UvWclwJ1hv9i+kEtmG6AgJR2CGnIew9yLqXHcTdePSPDvpVh57B0dDz6lWnfRubBkRVcY43LxBdx6wWj4YvotMDLSouuJRVnON+d+I8Hp/FV5J9PJWacsOVOHdyj8AL0KCQQgIORvuHCKvEnqC0Wsv9837wW1VhbM8X0FjHlBAMj0MWcmgXptHtXLIqT4CYL7PoLvvto1EQkU+n0VPPoOenhyWLFuPnnwa+Z403rrxegwPRZseEQRBnCiQMCQWnTffeT0APrC/f3wev9o8hi0vjuP73/sOpuZkaHWedeUaL4iiAjnRA4Hx8CcGIXih14nQW8Dsl/u6eIGa76zaFTGTE7duLnZWxq8HQDqzHKKgQKtNOXlgutNeqcG2TdS1eS+TzV2JXi9CKI8HIz18uKLIiDAQcfcvsF/+qmEUUbNJHYj2uMqtovZ2LTLbLSeIChRRgWGUYfo2K/vs9mWlB7KagyRlAusoF/ehVp5wLmj5zJ1h1BxhYztVCy7i1USv1z7oj+7Q64VIcdgxkaZOCzQlijufgfmxWqQbbrNwVkQFSqI3ssKtJgeRSA2hWh6HVp0KnXkM3BQBoNf559b/uS8XxjA9sQnJ9CgSqUEni7DhZmwaNV4pNmowTS3ys++5mnbSTsmiW7oluVEJ7PSzGtbaKsnp0HMqK1l+Th2RLvuqjLxLoeIZ4RyOqyrA51LdfMJOkeS0kwmpeq209dosbNuEJAUr8N56/YU/ZgO2OysITyQKkuLks/qOxTOWYTwv0xOL3kIAbFi2DUEQkM6tBGMMomChWplGMpFE/+BqvOOt1yDfk0ZPPouefBb5Hv61tycLVT28qBGCIIgTARKGxBFDEBiWL+3B8qU9eMWGpbjg3AF84CNPIOlovkx+DQDegmaDX9AwJvD5pcoh1CpTSKSGvLk8xgRYptYatN5M2EVYzKxRfCtlKvK5Tohbd8ctfQywbMc238nLE6UEXOmcyfsiPYQERDk8DL1S2o96bRaWqTsXxTZs2/QqVIKoBiqktmVCrxeDVVO0ES4LNGgB4iu3ov8iu1vaiMnQ6gb4ha0rqD1XUAd/5dHQS9C1Auq1KViWCcs2PPFuWQa02mxAwIhSApKURLV80IkCEWLD0zs+Nh9R84WLFUcQ5cAbVemP+z1IpHg+WzI9imR6NHYmNiqL1DJ1z7SoVp3k86XO8n78AklS0l7VkTl5kIIgw9BLQVHXhrhZzk5wf/+iWmTlmPiN0PU5cSju7y1vR62jUjrQ1XoOF+/3SmtU9Urzu73nFbUXspJDKrsUtUqwUum1c7rVO5ufo7/54BuwefOvsXvPfhwYn8T+A4cAAMuWDmPtaedh6Wgv1qzqwdBgLwb6e9Df34PBAf51enoOk1OzmJqeQ6Fo4tDkHH74wx/j0W/vxHXXXYePfejNGB3pP+LnhSAI4niGhCFxVFi6pBdff/SFkGdYY6bH+SoiiUpxHwCgVpkILF2tTDoXGQz+KzdBkGHbpnOBLXqtf0qih5uONFWsGrN67UKsI8wYOhRAsWJHirhI79IgptNIj1RmqWfAwpiAen2Wt03Wi177lm3b0GsFGEYNprHHHfKBKCWgqD2Q1Z5AqHrXQiaGqAvs0CqX+550S5PgiGu5VFSfK2XYZ8DBzWLT63MQBQmCrQT+sja3C3vtdk41R68XAlWysDxC27bABJ7PFsghFGXIag9/b5QsbwvU5jubL4y7gRKG77moKIJoYdjB8u76m2difc+7M4nNdOoK6q+U6fUSGBj0pscxux0AGpVHMQlRbq08mob7L/xcR875RmAaNe/GhL8aGxXBEfc3wY/bjiqrORh6pSuX1MWiUdVroNVmoNVmUCrs9h4TRAWSnEIiOQCgIeRtxn8nrrvmYrzpjmsXtA/9jlD0c9ebFrYugiCIkxUShsRRQdMMPPClTR0JqrjqQjI1CFFKtVqzC4pz4RxNpTiGWnXKm/8C4JmPJJKDkOTWC7B6bRqJ1HC7wwslrjWSCRIEsbNfvwUHubdxI1WUXshKFoWZeW8ZBsbnhlS+Xrdl1TCqqFUneVA3EyBJSdiwoWvzjX1R8w2TCgCSlIDpxE24IkZJ9AXdQW3HHTRGzASqXJ3OkkZ9zprOSXMboN/ootNqMZ+ZLQVe7yeZWRoQtpLMBaIasZ9xeYQ8/67qZXECjRZC/3vB58Bcgx7Fu2GiVadgGtXGTGs3+PYz6nc0an4xqgWx61niCJrzCBcym9f8O1Ytj6NaHm+7bXfekf89alQea5WDbf92+OdJ9YgbI1EOqe1vagVJOpVZ2zJ4PmDlUFevPxpYZh2QU7x7xIm14NVDYHioh+b4CIIgjjAkDImjwgP/vgmaZnR05zxOGKYyy7qPsXBfm10WmLXzGyX45430epHfWbctlAp7IUkppLLLkc2viRUl3gW9ocGytIChQjOxLX1dVAslOSKvsM3PQZOThltfs7BxnRMDLaa+HLzS3C5Uy+O+ua4ED6YXVYiCCtYkfvk2bZQLe1EtH/RZ1DfmoEQpEdieZeqo12b5zJLY4ZxPVIWvQ+MdMN6+bNtWayUrZL11bS5UFHY009e0PsYkSHIjj5CLw/DWTTU5gERqGNXyOGqVSWcOjFe0DJ2/xt/G6ppsuC2WkpSCKKcgy2meSSglnBstquNIqXZlqBNFZCzEorW2hgvPRGooIKwUUYEopwKzeUqCiw3L4rPP/O+CFula2ow779hCc+UxZObRsupO1bEaWXk0TS1UHHZaMWyGCVL3NwWOIka94M2j5nMZrF23ASMjvVi/bskx3jOCIIiTHxKGxFFB13329W1a2NrOmi0SkpziF8ZSMiAM/fM5AJBML/UuHl1c8xHDFX+uHb9nJ88vvpVEL0RR8dwTXRTFEbcdVFCjWiwBgIXlwvlp5wJaL0eKwshtMhGSkoUgSK05eB212DKkcyuRzq2EbVte+6Nenw8spdeLjklIhYemO0JWkhJQk4PcfMOo8AoNc1pZRbelVUZUtEBwG+HCMMx4J+6mQNtqZ1wrcpv1h+bzObjzZ958XtP6m9seG5VHxxnUqsOoVqBVp5wqMYOhBc9JmFFJlKGOqZchNN24iRJYLaK5W4MnH93kEUZV4ARBguD87ru/C17F3Gfk0i2dVh4VJQsmcPdPty1bEGTo2hzEpspju4gdP4yx1nB3x734WLSVCoKATH4NCo5wBoBUKoWBoTX403e+BiuWD2PJ6CCWLhlClsLgCYIgjiokDImjwlceeb7xQ9gFnjv71679Mqr60u28lO/5OOEVWqG0g+YjrrCp16Zh2SZsy3AMMXjV0DLr0MwZgDGIoopkehSSKzz9oiDiYj6qkgAgMiPNI2Yu0rYt1Gvhla44Wt4Hn0PjQgxiZCULQVRahKGsZCEjCyS5O6ys5htzdPUiLKvumOnUnXxIw6n68EoMgEa4utPK6p/NS6SGYBq1gLBx6SbrL7bVV/a9z37a/ewjSvQAESLH9z67pkTu7F3UZ8lfeawUxgJCJiwfT6s1BbozEYIoo1I6gFzfGS0zj2F0ZITj/2xF0DaPsMPlvU02R3D4KuZhjp+LRT1iDtNfeUznliOZHoVWm267vkZMRKMjIIBttj52mPT0jqKndxDv+sPrsGR0EKMj/Rge6sfIyAAmJqZw8NA0xiemcWiqjKee+hl+8vSzEBjDFVf8Dv7q/XdgdJTMXwiCII4lJAyJo8Lv3XI2/v2rz6JUdi6komz227VNLiYLrVA2VXjcCqNen4cIyWtR86Mk+qAovdwx1Ad3Cp2JNh+xLdi2iWQ6fFapbcWweb+biGvbjaLlfejCCCYqJDyqiuNuz98CLCtZSFISxfkdEAQRgsBnQy2z7jmuevlopgZECIFaZdKZNeXxEm61RhQViJWDjaBvUYEoKBAkxdsOb6nk7ZXNzpeB41qEz2xztp1LZCUxQkTFO4Pyz1cyxSuPjAmoFPdDr896TqBuhbFem2t5PY8z4EJj5uAzIfsanHnk5zqJWuWQ02KZjG+5jbnJE9VGKknJ0Ept8/LeHBvaV83DHD8Nowq9Xlpwa2enNFceXTEuiAokKQlJSoI559CfHRj1y/nXH3wHhod6kM2kkMtnkM9lkc9nkM9lkM9nMD9fwnyh5HwtojBfQrFUwdxcEVtf2oXtO/dh374J7N03gRXLR7BixSjOPPN8/Om7bsXoSF/L9kZGBjAyMoDzz+M/v/mN1y3m6SEIgiAWARKGxFHhtlvOQy5dwa+eeR6bn9+Buer6lmW02gxqMS1XkVWcw4hIaGsQ01wZi2j3W+hcpN8p1L9PQfMRzav06FoButP2ypiIfP/Z0Qfng0cnuBEKdUeI1jt6bTOynG09512cf9uyWpaPq+JEve/N75tb3cmnBrx2Uv5P4V8lLqItQ4dl677zwIWPVp1CtTwOU5BR97dT+mbywmCCxE2RRNW7MO+IDmNVjIhKUpRbZRRRn9EW90xvptI14pEgSpK3vUx+TaihS7U4BsOoOp/b4GfLcoS0n2op6DjMM++4SJTkFGQl58zjqd7cKoDG74YzBxhWBWWMOWHqQvBGCws/n91Wzb3VNQnFem0ONScq40jjinHTqEF3Pq9MkCCJKlLZJc7nh4HHvQerg5ddcib+5J1viF1/Ps8FIpbHLkYQBEGcRJAwJI4KoyM9ePOdr8ab73w1LNvG/gM8+P753+zHmhUMe/bsxfYdRUwcTOIXv/wNBDEBUXScR515GK06Dcusd2dC0oa2xi5+YsRPfBZid1Uj11HRf+FdLvD99DuGNouQSnEMWm3aq2g1Vx69GUhH6DBBQiI5wM1GujifAbfOqHzI2ANsfSguODvs/MW9b6nsitbqk7+9UhYhItHyumzPGsAGatWDPGjdl5HHK4NG6HZty4BWnYFpavy9k5IQJRWMiagU9wYrj865Zkzs+HxFC7ps6ONRRJ2zMGdQ27ZgGtVQwRRn6OJ+NoFGZbVWneqo5dKyDFhOm7BLJ8HsriuoO8crSgoAEZapAyEF9YVUyTulU8OaI4VtGdAtA3q9DFFU+BxhyHLv+sObjvq+EQRBEMc/JAyJo47AGsH3t954jve4bhjYsWMfNj/3Eu79+OcxMy/wi3GjBsvSoWvFhvW+MzemJHpbKm4egXk6M6QF0Ih1WPQumJvFTxc5g21dKf3rjyBqBjKQ52a3uq66Louu06JWm3Jm8UxnjlFDvTbrzSDZsCGKKiQ51WKWE9xfBgjo6Lx0iq61ticC0ecvyqqfOUY0rU+ELBzhWqqq/dCqU43MPF9lTlJyodWySnEMglMt0+tFXh1jDNXyQYTB2wAbQtEVj0qiNZMwim6iHuIq42JzHIhDlKtup4YubgU3kRoKxsvEtuXWedXW0Dqe4Wt2BWVgYExAYWY71OQA0vmVUBN8dk2rzbRd3+Hgtv02C1qXMGEbhSAIWLbiXKxaOYy1a4Zx7VVn4TU3vAqPfvsp/Pinz2JurohiqYJyuYJCocz/FUsoFMqwzRmkUmnkcmnkchkMjaxDOqUik0liZKgXl11y5qIcL0EQBHFyQcKQOG6QJQlnnL4aZ5y+GmvXnY63/snDnb/YucgvFfagXNgLWck4ode8VdB25vf8uBWzhjFJ0IDEu/Bubh9tuuaLM8xpqTp2Ei3RRJzojFu332WRz1b51uNrbfU7L3ptgE1iUZQSYEwEE0RUymOem2tgNqxD8cXbY+s80sONQYiIY4iaK411AY0x3AkQ8bgd834k06P8eJ31KqICJdHL7fXDqmVWeLWMi/NqS6WUFVudIqMyCcuFPZDkdEeZhB3fuHAE/mIaumTyqyOfcz9D/v00jWBQfbeZezZs2I6xSq06iVp1MvA8NySSIIoy337cTZAF4heAYSLRdeYszu3wqrK9fUuR7+nHn//JjThj/UqsWbMMvT2t4v/G11yOG19z+aLuL0EQBEEAJAyJ4xTbjg+rb8G5oM3kViKTW8mNM8S5lnZA2za9CgNvAZwGGHNa0RSnFS2JZHoEpfndvqqO6lQ6VD7bZPlz3aIviluqOl1W1OIqPYGKYRv3VV2Pbp8Lyyr0twHq9SKvHjFuO2rUy4BnIGPzvD/L8HLakhkem1AtTcAya74MvNbZMwCxLa2B+UJHjMW6gMad77jICB9RBkgBEeV7XVhrYqBaJqqNz5AYnQ1YqxxyBCM/V7bJb2TYjvGLgaB4LhfHAj/7MwnV5ADU5AAAXnGuR1TKQoU3i27tjZprXKwA+7CgelFqbfvtFr84c28SmUYV8M2SCk6sDI+xSXY3L+qt3IQgCFh72oW4aMMaXLxhOZaODmJkZADDQ30Bd86p6Sr27N2DH/zwF/j2Yz/BlVf8Fj72oY2hxi0EQRAEcTQgYUgclzz8zV93/6KAGQq/Cx/WDpjJp4JB7M2mFqbmXLzzYHXbMmDZBmxLh+W0Yvo3JooqZCW8stX2wrhdzmDcDKTUeUi1rnU3V+UK5ERquCGOw0LPDf7VNCuoVQ5B1+ZQcQRLnGGLH1egC762SklKIJEe9uIomls3o4g932GV2hCx2Byb4RIqouxocxhJTiOdWxX6nCCoTvWNi3FuouKIK6daxhiDZdaRTC913GtnUY+ZjzOMCgyDZxKWCnsCzzEmeMLWX3kUpRTqtdmW82t0YlTj33bEOWhZPurz7kW1tArMxajmddLC6RrkuDOO7rxo29Zqh5HhHvzvv/0wLn3lORgZGYheznHn5FyAt2z8bx0fB0EQBEEcSUgYEsclmzaPRT/ZwUxbnKDK5FaHVo78hi8AoCbC79yHzSsKogKtOom6VoBeL0BWclDUnPd9YL+jjieEuIzFjk1tGGDEZCFGkUyPRrqp8nkxFXCqjJXSGBRnWTXZyCKzLB3p7EpYtoHizMt8vZkRbi7kVGC9SmxTFU0QZNRqsygV9sA0qlxoOsY5kpzyza01wsBrlYNe9EIkcWH1DAHzEz9eJmHT8lFxEm74fCf70Tyj58YNCKICJdmPhBNXYtuWN3uoVSe9iBPuNmt4jrYtm7It2CHOoJVSuAuwkujl1TMpEaicRRneRBm6tMwvtmnrDau+h1WZjwa2ZXjVcibwDoZUKoVKeR7pXGt77N//7dtodo8gCII4oSFhSBx3TE2XMTkVXRWKvKh3iG81DL+47xibG4c0z0ZVivsAAIrKBaGLrs1DktOoFPejUjoAy9Ihiip0nRuUuFEKTHBbWRNIpAaQTI+iVjnYfTZayMV33PmIoxs31aj9VNQeKAneDppYOgjGWGQ0gCc2fVU0QZuDmugB0OPNQvIAewN1bZ5Xg1njgEuFvYBtI5EahJLod0Sj7HxVvO9hoxFV4YutcNs3uzkfUa3E3cRJRM3ohZnv+HMzw6pYkpKFLGcDVUCtOoVycV9kO29gm2DQa3PwzoQgOk6rSZSL+0LNdzqize9Z1Dk4Vk6fYRXDvt4UPvPp9+E1N1yG7z7+DB7692/g2995Eq+77TYShQRBEMQJDwlD4rjjl8/uC3+iQ9fLODElK74K2EJcNbsMD9frBaTYcqRzK5DOrYBp1FCvzUCrTTuzTo2KT92owramoVUnUZjd3oiYsC1HOCYgiNx4hEchjEGUEvyfyL+G7d9Cgrc9QeJquJjzEme+o6i9gfPaTV6cKKgB0dU8CymrPZCVXMDBs1o+4LmxFma2enORkpQEmMBnTGOcPruN8IibLw1z6mxsCE0OoFEh7Q0x6o8fifq8SXIa6cyKwPuliAoMvYRkulFJdUW2Vp2G1fTetbRdOpUzvV5ELcIERpLTjomT6xosQWAiauUJyGq+o2iNqHOgNZnHHEkkOeW0Tif455+xwPv4j3//Tk8AXn/Nhbj+mguP2r4RBEEQxJGGhCFx3HFgPGKOqsPKXtv2yyhX0IVGLcTMfTXPWHFzliWoa7NgEeIjTPCUi/tgmRoMvQrbNsEgoFaZbJnj84tEUUoilVmCWuUgfw3r3NAnyg00jCizFsB3vhcQZWFa0aIrlVkWaHOVlSxEKRmYD/S3tKqJQSTSQ6iWx1GrHOIOrI4rqF8Y2ZbRMEAJuLImUS0dgKwEK3FRbacAr3SJgtp63GFxJ03rcQW0JGeCeZQOUZ+5gFmPf/1Nrq+uyBalJLTqdEeVxDgibz7M7/a+lZUsFLUHarIfspLreK7x4//Pe7F9+47YeAZNW/i+uw6hLpXibsiihr6ePPp6cujr78HSZadhyWg/VQUJgiCIkxpmd3MLnyCOIj986mV87ZH/wjPPPIddu8fRv+Ta0OUCeX1GJVaoZHtP77gSFknThX2lNBZZhWoWMAC/qHdbTztZHgDmp7cEfu40PFxWsjDNOvzlKVFUA9WjMNK5VfzCPe48OeehUtwXKlSYICHXe3rsdprX5T+3dW0O1dL+0MW999H3WssyUJx9qf3yTTR/frRqI++Rz+7pYEwCGPhXd5ed6mNUtUxJ9DeqZf7PTMj3ze9vu/0uzL4U+r5ne06HIAaXjzsvLefCrMMwqqhVFl6lcx1Au8nsA/jnkjnRMYlkw7xl94ufb/tara6jMF/yhGKhUEK5XEWxVMHcXBFbXtyBF7fuws6dY2ACwznnvhLr1gxj/bp+9PflMTw8gt7eLPp6M+jJp5BMHr4TKkEQBEGcaFDFkDhuuery03DV5e/2ft6xaxovvDSO73//cTzzzHPY9jJ3XrRtG8lUHsXCNAB/W5sKUZTBBNm7uDbqRT7z1tTK15UxTIfh9kD4XFpchbHT5RtxCIPe8bkOrMybqZOdNlXdcVTVvfgOSUqiMLsNplGFbVuQ5Qxk32xkrToJSS87OW/JFrHhPw9xbY1d0aQjopwuAyH2vveno5iJEPx5j6apRa5HVvKe0NPrRdS1ORRmtjoRKDWv9RC2zefiQqtlA8GqY70M3YiuOoYR1bobdZxxN0qaEUTlsP+n0K0gdDFNDTA1QOefHUlK4vprO2vVVBUZg4O9GBwMr5gSBEEQBNEeEobECcPa1f1Yu7ofN7/6HO+xrS/twqZnXsLf/dMW2OzXgdw8Qy9D13RuOuIIKdseg2lUkMwsbYq3iNhom3xAHmMRXrGLulDvOGzcIU5I+lvgwvDiOkLoEWRUSq3ur4ZeRamwl8dhMAFuVqG7HlnJQEn0IZkeQa1yMHLbUW2NoYTMesYKzpD2VF2Pjo0IEJNnGDcXqKYG+fN2wwBGTfShXNjNV2ObTl4mr7r52zPdGb1yRKXYq5Y1VR6r5fGOzV6ksDZpxH9+whBEJZj7t0Ch1w2MMWR71qI0vxOWZUGrTEDKrcbGN159xLdNEARBEASHhCFxQnPG6asxMDCEv/unLegdPDd0GeYYkDCBBdrcbItf8Nq2heLsy6jXC447pRtDUffMJxrh5AmoiV4vPFyLCA4HwitmcUYtURW2KCHZbXh4ADvaZVOSk8jIK4KzjloRep2bu+j1Iiql/Zg59Cxg2xBExTtXgiBDUXJggsAzIG0rUGHTKpM8CqFNjqSp1yJ33ROcHVZuW2ImmkWlbz1xDpieaIy4WcDdakWIUiJQfXWNXnStEBlt4VXLmigXWoVklEGOooRHi3QrDBljYKJ8VGIiEskBKIke/M0Hfw+XvPJ8rF+3FFtf2oXnnn8ZW1/ajVddetYR3weCIAiCIDgkDImTG5u3mjIh/GreNfawrDokKQFIiUblxzJQq045BiONapRWy4PN73JW4DiHOlUVQZAgKzkwJkSGh0cRFgYeV5EMFYb+qhsQWwllMYWgFnMXNQtZzXrmLrKSCSyvJgeQSA2jWp5ArXwQ1fI49HoJpqE5FScbsC1YlhFZNWs9vgyvVDZlFRp6qUVEx0VyhArgiPMS5YwpRFQSPaOaGPxuqoZRhaEVYBg1PrsYsiPtKnS2ZaBangis37YtiFIaimUcVpsq4Bi52t3Hm7i4rbJe9ZvxGzKWZUCSU15VsLcnh3XrRnDxxa/Em+/8Xe/1Z5y+Gmec3poTSBAEQRDEkYWEIXHCExlvAbTMErZcdNuArgcrKl7lB0AiOehc2MuNllRB9qpkjXDxRhaers2jUp6ArnNh5O2A4/OkJvudlkE54BTaIvQYYNa7m1/shq5mI0POkx8lwR1Ak+kRJNMj6GMbUCnuh16fdc6Rwc+RwYPYmwVyWOuiXo8Q0bPbnW2NIp1bjmR6FFptOnLf3P0PbR9t+ho11xiVSRglJKOQpCRkOQXAZ3qj81zGhcSKAI0A+NnJ50Kf97epKone2HlLABgazOPfPvd/YJomvvGtH+LAgUMYn5jGwUPTmJiYwpLRQaxeex6GhnowMpTHb196Gl5zw6vw6Lefwg9+uAm79+7H+PgUDozzaIulS4axZt25WLFsEOeesxLrVg9gzZplhI8QxAAAIABJREFU6O05jIo3QRAEQRCLDglD4oTnRz/eEb8AcyqDluBVDt02UjDE5tqlcisiL6TdShBCBFovgFrlILTqlGf44s2fOQLANGpeq2oyPRp4vWnUUNdmUY9pVY061k6JajEMZBj62i3bLt/yBK/GNuYck4BTeJOVHshqDpKcCWQQ2pYBw6jBMKqxbqsMDLXyBKrl8cDjfDZPhijKEES1fd5jU1tp1DG2OIs6xOUYhu43a6zAb3rDtxF+TriAbH9OovC3qRp6GWqy3wtsD+MD730DXnXp+QCAK36785y+G19zOW58zeVd7x9BEARBEMcHJAyJE55Nm8c6zsnzBKGPrgRPF3l8idQwtOpUQxg1VZ2URB8Ulc/buZSLe1Eu7PXy8QQmggkiTEODIMq8qsgAgUmolvZDktIQ5RQkpwrVDW3dRDuc4QubjbRtK3L5ZGYZFLXHW841cvHaVJ0WVi4Sq9DrpZZ1RbVbWpYBOJU4QZABJoTmDTbnPSYzoxCYFJn3KCu5FtfUuHnEbpHkNFLZZQAa50QUlUYuo/+c6BVUI4Lmo5CVDPR6CZZloFrmhkGiqAKMQVZyUHwzka98RYcRIwRBEARBnFSQMCRODkLaAtth21ZsQHmoGUxYFl0EcaYfYXmFhl6GUS9yc5tEr1ddsiwd6exK2LaFavkgDL0Ew6jBLO13wtl9O2JbSKZHoSb7YVl6QACZRg2mWeNfjQ7MXXzEzfC1mLs4s5GWqQMIVskABISwS1QOouyrqHGBV4JparCddfPNNRRb7+B5UNSewFynVp1Cubgv4BLqnQNH25XcmVHAmWvk7cKiqEIQJJQLe7sKt4/CjY1tPidh5zxsrpEJEmQ11yIM27mINrflZrO9YFJ/y3LDQz0YHuqJOQKCIAiCIE5WSBgSJzyv2LAM//W9ra3ZhEBAwLlGM37qMbNpgZm/MCHYxuCl27zCujYbuqwgyJCUHARBgpocaDmOZsFnGmXUKhOolg86QsgGmABRSoBBAMDFpm1bvngE2YtIqGvzYBAhyg0BFz+PmGo5P/7sPFcMNY5HaTmGTkSWJKcDYt1z+3QqioIgI5MPmpYoogJDLyGZHg68Li7E3bZNmIYJ06jBlZ+V0njoskqix3NWjWrNDN9G0zmRUrBtC4wJvv2MrkgyxgLr6DRSQlHzkNUcmKji4x+5C1ddcR4A4Oe/3IoHH3oEstrX8TEQBEEQBHFywezmKxSCOEH54VMv45vfegy/2fICdu8+gLl5px1TlDAwfD4MU2lxCDVixFu+/+yg0AwThjFVw8LsS5FB5Lne1na95uXdqhJf/gy+yRBx68fQy16uXjOK2gslwS/8teoU5mdeDF2fW00UpQTU5AAyuZWoVQ5Gtllme06HIAbvMZULu0PFpCCqyObXtZy34tz2ruf1mpGkNNK5VS3rDnsfbMtA0RdAv1i4VUZZzUGKMKxpJurzUNfmUC3tb3l8ZLgH9927EaZl4lv/9SQmJqZwaHIGhyZnMDnJby4MD/Vj5epzMDiQx+BABuefuxyPffcnePpnm8EEAddeez3+98ffdngHSxAEQRDESQUJQ+KkZXaugJ07x7B1215semYrXnhhW0AwWpYNQAwEizNBhMAkMEGEkuiDLGUhKWkIgtKVMLQtA4XZl0Kfk9U8UpllbZd3haGs5JHKLufLtRGGldJYpJmOJ3RdoxVt3gu494ezm1Yd9VojhkFWsjDNOmBbEAQZtm06LaoKmCAhmV4CWc0H8g692biWY+9BKrO05fH56S2xx9UJqcwyyEq+qbM2+n0oze/hLbJtqm3+7MtukKQkZDXXtpoY9nkAgEpxX2jV+R8++Ye45cZXdrUvBEEQBEEQ7aBWUuKkpbcnh4suPAsXXXgW7rz91d7jrmB88aVd+NGTv8JPnt6MiYkpCIIASVKgmRYAhnpt3plDLEAQFEhKGrKShaL28IB2QYUoqRAFlUdL+APaO5nh84m0sOqae89GUnKwLStemLpxC1Eh725brG8G09+WGQhnB5DJr4EsZ1oqrLXyOHfJdFo4AQatMs1bU33Cyc2xa25T5W2atcacoQ2Y1uKYuIhSuuPzwZdPdNTC2q0gdDGMaiDQ3q0milIykMvY6HVG4D2OakUmcxiCIAiCII4EJAyJUw6/YHzTHTcCACYmpvCjHz+Hez+1uWlmrwq9XoRp1GCZGrTqtCMmmtxubJuLANuCZfHJNJ4ZJzeJACd3rmnGMGq+EPBFJTTTHJ0QZxDjn5d0dzn6FCGZHg04sipONIe/9ZYx5nMOLcM0al4Frl0mnygloCb6kcmtAhNa21O7hQlSsJ21TfwEwPMk3f0/GlhmnVdkjapjGuS4o5bHMD+1GYqion/Jtd7ygsCcqnYDMochCIIgCOJIQcKQIACMjAxg9erTAGz2Mu+gILZVtLlC6M7hmY4A0LUCr5QxEaZVh20ZEAQJhdntSCQHkOlZg2R6FLXKQej1YsB4xMV15AwNZ/fDALPeRWB9zPKBmA7ftsLEq+scKskZ77wYRhWGXgm4gDZjGjVUSvtRcWbo+DpS0DUu5JRkX8czekCEgyzihaEgSEhll8LQy5HmMmEwQQJsE8PDy1Gs2Dz2AcAH33crduzcjbm5Iubni5ibK2JuvoQ553sA6OvNYcmysyAJs+jJZzGyZC1yWRWnrR3AGetXYt26NQCAvWOzeHHrDjz55NN4dvMWbN++F+dveBVecdFpHe8nQRAEQRBEN5AwJAiHh7/56+ADMcYyTJAgCRIkp33RtgyYRqVlOdewJZEaRqmwB1p1CrAM1KpTqGvzANsM2DaYIMIy6415R4HHJQhiAtXyOATH+VIUVS5MQoiqOkYF0LfNMWyiXRXQ3ZY/YgJouIcaeiUypF2vFwNtnUZxP5/RU7LOeZBDjW9cBCbx7EJnls8y6x3tL+C0vTIBjDFketagNLcTpmUCAJLJBPr78ujry2PZijPR15tBbz6J885dge9+7yf46c82I5UZxpWXn4u33n1LR9vrhHPPGsW5Z43i9a/77UVbJ0EQBEEQRBwkDAnCYdPmsfgFIip1cTAmepmFanIAAK+WabUZ1GvTsC0DlmXAsrjxi22bXuacICo8C7CpkmjbBmzLdExNVIhSAsn0MLTqdKiA6raaFtZ2atmtbaq2bbfEJoQhOG2orlh0q4paddprqQyjeUbPny8oK9lARVGrTUMLiR4x9DK02mxLiLufkeEe3PPeP0V/bxZDw6PI52T09ubQ35dHMtmauehy261XxR43QRAEQRDEiQQJQ4IAMDlVwuRUqf2CEcTn/PmEmc3nyhQ1D12bBXNEk59MPu21s4aG05s1FGe3wzRqMOpFmJaOcnEfREHh7qKW4QtoT0CU0qjXZjsOZ5eVXFAEx7SdLsTU2K0qilISleJYrDgMbsuXL6gVIElJKEkev6FrBchKpkUEN2cfhvGB976BXD4JgiAIgjjlIWFIEOigWgjEVgd1PVxodTOv55LJr2p5zJt75ONsUBN9qJYa+2yadV55NHWYZo23UtbLsMQ66jW+LdcUxyXoHMpdQwUmolIc4/ETcha6zls84/IeF4ogSEikBrua7/NjGFUYxUbOnyt2JTkNJdHT8YwiuXwSBEEQBEGQMCQIACHzhV0SGRPhr1b5hGXbWIk2+Ktgtm07kRAyICUB5HzPNfIJtdpMoDoXWeVsCn5ngoRkagiSnOpo37qhXTVvIRh6GYZedgxt0hBDqrIu5PJJEARBEATBIWFIEADWrOpHtapj79gs5gvRGYRhRMVEMMYgq62iw24XK+F2Z8bNLzotnO1aOf35hKKcgladjjSAidyUZaBSOgCgUY0DnPZNNdeVe2j4PrafU+wWQZAwODSCg+M7A+sWBQGr1l6AocE8hoZ6sGbVyKJulyAIgiAI4kSF2Yt9RUYQJzjzhRr2js1ix85JPPXUk/jNlhewe/cBzM3zVkXLtiErfZDkFJKZJRCYhHJxj5dTCHCxAwD5/nMAALZtec/p2jwqpfDW1Wzv6aEOos3EraMTvFgJo+rk6+mwbXNB6+rGPTSMP//jV2PJaD93/+zP86+9vOo5M1vA9Mw8ZqbnMT0zj+npOezcNYaDh6YxNT2H6el5TE7NYna2gBWrz8dAXw5JpYily9djsD+LVSvyGB0dwOhIP4aH+jEyMrCgYyQIgiAIgjjZIWFIEB0yO1fAzp1jePGlXfjFL36DF1/ahb17JzA3X4Rpmo5Lp+SF2otSAqnscihqHpKcQb06C8OsQNfmIrcREIZhLqgOleLeWAOZheBvO3VFYzeVRZeAe2gb85fLLjkTD/3rew9ntwmCIAiCIIhFgIQhQRwmfsH4iU8+gEPTmjO/x5w2SxuGUQNgA7bNRZObU+gzfWGCBFnthZro40YzMcJwfnrLUTk22zJg6BVUK4cOaz1KogeJZGu17rOffhduuPbCw1o3QRAEQRAEcfiQMCSIReSXz+zCW//kYQCNkHW9XoJWm/QyCw29AkMvQxBkzymUOQrQdgYMRSkBNdGPRGrIM1EBnKgJvXREXELjKM7tWPAcIGMMI6MrMV/QYBjVgEDc/eLnF2sXCYIgCIIgiMOAzGcIYhGx7cZ8nSAqUBxHTEMvACLPmlDUPABAEnXMTu+FbdueIHQxjRoqpf2olPYjDFFUeaVRlEMrcYvNlx+6D7Is4NH/ehLjE1OYnJxFRcticnoeAJBS5jE40IuVq8/C4EAGG85fjsteeR4A4Kc/ex4/euoZvLh1O3buqiCTS2PVymGcf+7qI77fBEEQBEEQRGdQxZAgFpH3f+hRfPv7WwOPVUpj0LX50OX/1/tfi/PPXYs1a5YBQGOG8Ze/wYtbd2HnzjHMzsVXB1OZUYAJ0LUCDKMKANwYJzW0CEfEocoeQRAEQRDEyQ1VDAliEdn0bKtTaFRe4GWXnIm3bLw58NhFF56Fiy48C2+640bvsYDpTYhgrJYnWto8da0AUVQhiuqCnEL9XE8zgARBEARBECc9JAwJYpGYmi5jcqrEf3BMY+IyC2//vSs6Wm9vT25BglGrTnmC0e8UKomJrqIlbvtvl3W0nwRBEARBEMSJC7WSEsQi8e3vbcX7P/Qo/8ERhnF5gz//0d9jeKhn0fcjLFbDLxj9gfKMiRAECbKa82Yfm6E2UoIgCIIgiJMfqhgSxCJxaLKEwcGMVzUUBQvzEaJwaDB/REQh0FmF8Te/2Y6Dh6YxPTOPWj2HqZkCZmaKSCqz6O/rwbIVZ6CvN4sVywePyD4SBEEQBEEQxxdUMSSIRWZyqoRfbd6LH/zgh9ixcycmJqYxV0oBAJaM9GFkpBfr1y3BB//y9mO8pwRBEARBEATBIWFIEARBEARBEARxiiMc6x0gCIIgCIIgCIIgji0kDAmCIAiCIAiCIE5xSBgSBEEQBEEQBEGc4pAwJAiCIAiCIAiCOMUhYUgQBEEQBEEQBHGKQ8KQIAiCIAiCIAjiFIeEIUEQBEEQBEEQxCkOCUOCIAiCIAiCIIhTHBKGBEEQBEEQBEEQpzgkDAmCIAiCIAiCIE5xSBgSBEEQBEEQBEGc4pAwJAiCIAiCIAiCOMUhYUgQBEEQBEEQBHGKc9IJw/e85zHcfPNDGBsrhD4/NlbAzTc/hPe857GjvGcEQRAEQRAEQRDHJ8y2bftY78RiMjZWwDXXPAAAePzxjVi2LNfRcwRBEARBEARBEKcqJ13FcNmyHO6//yZs2zaNjRu/5j1OopAgCIIgCIIgCCKck04YAsDVV6/G1VevxhNP7MITT+wCAGzc+DVs2zaN+++/iUQhQRAEQRAEQRCEj5OuldTFXyF8+9svxnve8xiuvno1Hn984zHeM4IgCIIgCIIgiOOLk1YYAsATT+zyxCEAfO1rt+PWW884hntEEARBEARBEARx/HFStpJGQaKQIAiCIAiCIAiilZNaGH7sY08Gfv7617ceoz0hCIIgCIIgCII4fjnhWkl/dskleKm3F3P79uFX4+OwLAv9y5ahb+lSLFu9Grd98IPoWbrUayNdtiyHj370Gtx7LxeJ5EhKEARBEARBEAQR5IQThn9z001Y+73vIVGvo+h7/GXna9+KFfjt+z6Pt/7P51CH7AlBVyiSAQ1BEARBEARBEESQE66V9PY3vAF2vY48gLUARp1/pzn/+vfuxYu/fy1e2lkMRFOERVgQBEEQBEEQBEEQJ6Aw7L3wQuwAMAFAA5ByHncFosvrr+7D1VevDrz2gQdei/Xr+/FHf/QtjI0Vjsr+EgRBEARBEARBHO+ccMJw8OyzsVUUW8RhQCCOLsf9D9zR8tply3J4/PGNWL++H//yL88ctX0mCIIgCIIgCII4njnhZgwB4M/POQe5LVuwFsCI85jqe/6cxx9H79VXH4M9IwiCIAiCIAiCOPGQjvUOLIT+V7wCB7dtA3QdABeHGrg47Ln0UiipVNzLTyr+4i8ew7Zt0zhwoIjx8SIOHChiyZIsRkezWLIki/Xr+/HJT95wrHeTIAiCIAiCIIjjmBOulRQA3v7Rj4ItXer9POF+s3w5Vv31X0P5zneA6eljsm9HG8OwUCxqmJ6u4MAB7tN64EARv/rVAXzzmy/hvvt+eoz3kCAIgiAIgiCI450TspUUAOb378f33/te7H3qKaywLIxeeSUu/Lu/Q2LpUi4KP/1p4IYbgEsvPda7elTZvXsOu3fP4dlnx/Ge93wHt956Jr72tduP9W4RBEEQBEEQBHEcc8IKw7ZMTwP/+I/8+3e9C+jvP7b7cxQZGyvgmmu+AAB4/PG7vMgOgiAIgiAIgiCIME5eYejy9NPAY48Bf/zHp4Q4JFFIEARBEARBEES3nPzCEGi0lp4C4vDmm/8/bNs2TaKQIAiCIAiCIIiOOSHNZ7qmv5+Lwk9/mlcQT1KeeGIntm2bxv3330SikCAIgiAIgiCIjjk1KoYuJ/HcodtCun59P775zTuP9e4QBEEQBEEQBHECcWoJQ5cTfO7wrs134YFdD+D2+u14x++8A6Kl4O2vfRLavIDHv/s2qhYSBEEQBEEQBNEVp6YwBE7YSIsnqk/gmplrgGcB6IAkSDAsA+K3JfzHu/4Lt5133bHeRYIgCIIgCIIgTjBOXWEInJCtpdfPXo/vVb4XfLAKIAmknkvhqqVX4Y51d2CDsgFny2cfk30kCIIgCIIgCOLE4tQWhi5PP43JZx/DN946DFlJI4ccMsggjTRSSCGJJBJIQIUKxfefDPmwN61DR933nwYNNdRQRRUVVFBGGSWUUEABfXYfbsbN0SuzAcmUYBwy+M+/AC746D/hkt9ajvvvj3kdQRAEQRAEQRCnNNKx3oHjgksvRf6iMyBX/gEvKDOoAqihBs35r446dOc/w/efCfOo7uY4xoFa/DKWZUGekqFbOob/5/+CLpDuJwiCIAiCIAgiHqoYBjgHNTyNBLJHbYvdVAxn7Vl8svZJjGGMv3gewHhjXemfp3HVaVfh9g23Y0NqA85OUCspQRAEQRAEQRDtIWEYgAE4vk/Hk6UnceXLV3o/J55OoFat4Y35N+Ltr347Ll92+THcO4IgiFOLubkaPvGJn+BnPxvD5s0TkGUBp58+gLvuugB33nkuVPXwGnN03cRHPvIkvvjF5zA9XcHZZw/h/e//bdx66xmLdASHB2MfwubNb8f5548csdcNDn4C//mfr8eVV65a4F4SBEEQnUCtpCcYV2SuwF2zd+GhXz+EW864BXe++k7cuubWY71bBEEQpxzf/e4O3H3313HmmYN4y1s2YMOGEViWjU2bDuBTn/oZPvvZTfj612/H6OjCu1DuvvsR/PKX+/HpT78GZ589hB/9aDfuvvvrKJd/F3feed4iHg1BEARxqkMVwwDHf8WQIAiCOPbs2TOHc8+9Hx/5yO/g3e++pOV5w7CwcePXsGfPPJ588m4IAut6Gy+8MIkLLvgMtm37Y6xa1eM9/oUvbMaHP/xD7Nr1p4d1DIuBphlQFBGMdXd8VDEkCII4/hCO9Q4cP5AoJAiCIDrjHe94FDfdtD5UFAKAJAn43Oduwcc/fi2qVR0AF0OPPbYdr33tl/DWt36j7TaeeWYcZ5wxEBCFAPCqVy3H7t1zKJXqbddx000P4ROf+EkHRwRs3TqFbPZelMt8vQcPlnDPPY/gtNP+Adnsvbjssn/BV7/6QuA1q1Z9Ci+8MOn9vHfvPN70poexZs3/wdDQ3+GWW/4dP/nJXvznf76Ad77z0cBrZ2aqeNObHsbSpfdh+fK/x+23/yf27y94z2/Y8Bkw9iFMTVVw1VVfAGMfws9/PtbRsRAEQRDdQ8KQIAiCILqgXjfx/e/vxF/+5atil0smZbzqVSuQTiveY2972zdx+ukD+LM/CxeUfu644xxs2vTfWx7fvHkCPT0JpNPtI5M2bjwfDzywOfBYtapj1apP4ac/3Rd4/Atf2Izf//2zkU4r2Lp1Cuec838higIefPB12LTpv+Oeezbg3e/+Dv75n3/lvWZiogTDsABwIXveefcjm1Xw4IOvw5NP3o2bblqPN77xq/j8558NCEgAeP3rv4IVK/L49rffhC996fdQqei46KJ/xqFDZQDAD35wF6am3oe+viQeeeQOTE29DxddtKTtMRMEQRALg2YMCYIgCKILtmw5BMYYzj57qOvXbtx4Pj7ykas7WlYUBYhi8LGZmSre977v4T3vubSj9s1bbjkdf/iH38KmTQdw8cVcVH33uzuwZ88cvvKVLbjssuUAANO08G//9hy+9KXfAwC85S2P4J57LsTf/u213rpOP30Al1++Er/1W/8vzjyTf+9i2zbuuecRvPvdr8SHP/w73uNnnDGAq69ejQsu+Axe8YqgqLv77g24995rvJ8feWQ5Lrzws/jsZzfhr/7qSvT0JAAAgsCQz6vo7091ctoIgiCIBUIVQ4IgCILoArdCtpAR/euvX7vg7c7OVnHDDf+G888fwQc+0JkDtapKeMMbzg5UDb/2ta246ab1ePjhF73HvvvdHUilZFx++Urs2zePTZsO4O1vvxjz87XAv+HhNG677Uw8+ODzge3s3j2H558/iPe+t7WKum5dH+6445yWx2+88bTAz4wx/O7vnoYtWyZbliUIgiCOPFQxJAiCIIguOO+8YViWjeefP9h1a2Mupy5om5OTZVx33b9h5co8vvzl34codn5fd+PGC3DTTQ/hvvtugCAwfOMbL+HHP34Lrr32i14l8V//dTPuuusCAMCLL05B102sXv2pyHXecMO6wM/btk1jaCiNTEYJXX7t2j5s3z4TeCyfT7QsNzCQwtNP0xwhQRDEsYCEIUEQBEF0gapKuOaa1fjIR57E179+e+Ry9bqJp5/ehw0bRhcsCAHgwIEirr32izjvvGE8+ODrIEndNftccskyDAyk8Oij25DNqhgeTuOsswZx661n4OGHX8Tatb341re24b77rgcArF3bi3RawczMX0JRxDZr56xb14eDB8uYn6+FCr7m+UIACOuEFQS2oEosQRAEcfhQKylBEARBdMlnPnMTfvCDXfjYx54MFTK6buIP/uBhfPCDT3RkEmOaVujje/bM4Yor/hWXXLIMDz10W6wojFoHALz5zefjgQeew8MPv4jXvvZMAMDrXncmvvrVF/DQQ7/G5ZevwPLleQC8unfaaX34h3/4ect6XnxxEkuX3ofvfGd74PG1a/tw3nnD+OhHn2x5zUsvTeHLX94SuW8EQRDE8QEJQ4IgCILokpUre/DVr74Bn/nMJlx55Rfw0EO/xtatU9iy5RA+//lncfbZ/xe7ds3hK195fdu2zy98YTMuvvifWx7fvn0GV1zxr7jssuW4777rUSxqgXm/Ttbh8gd/cB6+853t+MpXtuC1rz0DAHDVVaswOVnBvfc+hbvv3hBY/sEHX4ePf/zHeMc7HsUvfrEfe/fO48tf3oIbbngQt912Fl796nUt2/jiF1+Lz33uGbztbd/Az38+hu3bZ/D5zz+LK6/8Aq67bk1X7a8EQRDE0YdaSQmCIAhiAVx77Rq88MI78YlP/ASf+9wzeP75g7AsG6ed1od3v/uVuOeeC5FItP/f7H33/RT/43+0msn8x3/8Bnv3zv//7d15dBRVvgfwb2dhywIkYZGdCQlLFsAnGIRwOCCDzANcUByeMi4RnCC44Dt6HDMMiiw+DdsbgZF9CDjg4IDggBKCoE+IhH0LIQuYEAiQEJCEkE73fX+ELrrS1aTTadJ9u76fc/qczr23qn7fLkjVTVd1Y+3ao1i79qhNf0VFEho39rvnOiw6dmyO+PhOyMy8qnw6qZ+fD8aM6Y4tWzLxxBM9VOOjolrj+PHJSEpKw4QJX+HixZuIjm6N+fNHYOzYXprbiI1tgxMnJuP999Pw3HNfobS0Ao880hErVozBgQOFOHHicq2vBRERuY9B8GJ+8MvtiYjIHXbsyMakSVuRm/tGne8ddOU6XGH48L/j8cd7YMqU/qr2iooqxMUtx4sv9sGbb9b+/Y1EROQenBgC4MSQiIjcobzcCJPJjKAg5z+cxhXrcIWffsrHyJEpmDr1YbzyyoMIDW2Kw4cvYebMPSgouIGMjEkICND+1FIiInI/TgwBcGJIRERUfxkZhUhKSsP335/D7dtV6Ny5BUaO7IZPPvmt3a+yICIiz8CJIQBODImIiFxHCIGyMiMng0REEuHEEAAnhkREREREpGf87GgiIiIiIiKd48SQiIiIiIhI5zgxJCIiIiIi0jlODEnFaDQhKSkNsbFLEBw8B/HxK7F0aYbLl2mIOu9XXe+9lwqDYQYMhhkYP/6fTtXmCYxGE6ZP340uXRYgKGg24uKWY/PmTJsxMmQBgDVrjiAy8n/RvPkcjByZgrNni1X9MmWxtmbNERgMM7BhwwmlTZYsZrNAQMAs5f+L5ZGc/JMyRpYsNSUmbsPgwatQ8zZ9WfL4+39os18MhhmIiVmzoTymAAASbklEQVSsjJElCwBs3pyJPn2WIihoNgYMWI69e8+r+mXJUlVlxqxZexETsxjBwXMwYMByrFt3TDXGk7O44vjoKflqy+LIGE/JAjhWqzedE2hxZJ/ei9bx2NUc/T9S275ymiAhBF8Gi8ceWyuioz8T27adETk5JWLTplOiU6d54u23v3XpMg1R5/2qq6ysUly9WiamTdshfv/7L52qzRM899wmERm5SHz9dabIySkRK1ceEi1azBEpKUeVMbJk2bv3nAgMnKXUmZCwRURGLhKVlVXKGFmyWCsquilCQuaKxo1nin/847jSLkuWs2eLRaNGH4qiopvi6tUy5VFeXqmMkSWLte+/zxPNmn0kzpy5atMnSx7r/WF5vPzyZvH885uUMbJk2bPnnAgKmi02bDgh8vKuiYUL94uAgFkiO7tYGSNLlrFjN4g+fZaI777LFrm5JSIl5ah44IFPxfTpacoYT87iiuOjp+SrLYsjYzwliyO1etM5gT2O7FN77B2PXc2R19iRfeUszoj4Eih2784TgYGzRHFxuao9M/OK8PP7QOTklLhkmYaosyHqSkraZfOLxR2vhzNOnrws/P0/FHl511Ttq1YdFl26zBdCyJNFCCGmTv23GDduo/Lz5cs3hZ/fB+LgwUIhhFxZrI0bt1GMH/9PER39mXIgkinLpk2nRGzsYrv9MmWxKC+vFN26LRQff/yjTZ+MeSxKS2+JoKDZUv6fSUjYIt54Y7uq7dFH14hPPvk/IYQ8WVJTc0TLlnPF5cs3Ve0HDlwQjRpV/76WJYuzx0dPzKeVxZExnphFCO1ave2coDaO7NOatI7HrubIa+zIvqoPXkpKiqNHL2HgwE4ICWmqau/ePQxdurTA8eNF9VqmqOgmEhK2ICJiEYKCZuORR1Zg06ZTduuJj1+Jjz/+0altOpPFFdy13bo6dOgievSorsnawIEdce5cKW7erJQmCwDMmDEEy5ePUX728/OBEEBQUPV3qMmUxWLr1jNITc3FggWPqdplynLsWBGioloDACorTTb9MmWxmD59N5o3b4LXX3/Ypk/GPBbLlh1C375t8eCDDwCQK0tFRRVu365StZnNAgZD9XNZsvz44y8YOrQrWrUKULU/9FA7RESEYv/+AmmyaPHkY/f9IFMWbzsncDV7x2OLhjy/dWRf1QcnhqQoKiqz+cdoERbWDMXFt5xeJjPzKqKjF8PX1wcpKU8hI2MSEhL64o03duDzzw+6vE5nsriCu7ZbV+PHRyMjY5JN+5Ejl9CiRRMEBPhLkwUAQkKaIiioMbKyivHXv/6MoUPXYPToSEREhAKQZ79Y3LhxG4mJ3yA5eQRat1afJMqU5fjxIpw8eRnt2yejceOZiIhYhPnz9yn35cmUBQAyMgoxf/5+XLz4K4KD56Bjx3mYPn03qqrMAOTLY1FVZcaiRel4660BSptMWV54oTfWrDmK1auPICenBPPn78OhQxcxalQkAHmy3LpVBX9/7dOyJk38YDSapMmixZOP3feDTFm87ZzAle51PAYa/vzWkX1VH371Wpq8ihACvr4Gzb7qd2CETbujy7z88hYkJDyIuXMfVfq7dw9DfHxn9O+/DD17Vj93VZ3OZHEFd223rnx9feDrq24rKbmFd97ZiWnTBsBgMEiTxVp6egHWrz+OY8eKMG5clNIuW5Z33tmJHj3C8OKLfWz6ZMpy/PhlBAY2wsaNzyAmpg3S0wswefI3yM+/gXnzRkiVxWwWeOWVr9GvXzssXDgSPXuG4eDBi5g8+RsUFv6K5cvHSJXH2pdfnoS/vw/GjOmutMmUZfjwcDz1VE+89NJmpW327GHo3j0MgDxZ+vdvj9Wrj+DGjdsIDm6stJ89W4zjx4vQr197nDp1RYosWjz52H0/yJTFW88JXOFex2Og4c9vHdlX9cGJId13+fnXkZFRiPXrx+L69QpVX5s2ARg7tidSUo6hX7/2yMkpUfrKyoy4dOkmTp68DADw9/dFZGRog9auF9eu3cKIEWvRu3db/OlP8e4ux2kTJvTGhAm9sX9/AZ5//ivcvm3CjBlD3F1WnezZcw5r1x7FsWOJ7i6l3nbunICwsGYICKi+pHf48HBs2TIeffsuxZQp/d1cXd18800WCgt/xZkzU9CyZfVfdIcM6YKvvx6PqKjP8PbbA2pZg+eaN28f3nwzDj4+9TuhcJfExG3Izb2GgwdfRffuoThwoBCvvroVQkCq32dPPNEDyck/YcyYLzB//ghERIQqf0wZNSoSPXqEubtE0glvOSeor9qOx55wfuvqfcWJISl8fAzKJVE1VVWZNU8aHFnm9OmrMBpN6Np1gd1tjxjRDWfOXEWfPktV7YcPX8SCBfsBAF26tEBe3psObdOZLK7gru3Wx5UrZRg+fC06d26OjRufga9v9aVMMmaxiIvrgE8//S1eeOFfmDFjiDRZKiqqMHHiVvzlL0MQHh6iOUaWLADQuXMLm7ZevVqhR48wpKcXSJVl//4CDB3aVZkUWnTrFoLo6Nb4+ecLUuWx+OGH8zh7tgQvvdRX1S5LltOnr2DZskO4cGEa2rQJBFA9YV+x4nEMG7YGU6b0lyaLj48B27c/j7fe2oGhQ9fg1q0qBAU1gtFoxu7dv1PGyJBFiycfu+8HWbN44zmBMxw5Hrvj/NaavX1VH5wYkiIsrBnS0y9o9l29Wq4cdOu6THh4SwQENEJJybto1MhXc6yFEDOU5/HxKzFqVCTefXdQnbdZWlpR5yyu4Mxr6E6Fhb/i0Uf/jtjYNkhJeQp+fnd/qciSZd26Y9i1Kw8rVz6uag8Pb4nyciOMRpM0WT744Hv4+fng5Zf7qv76aDIJlJUZUVkpT5ZFi9KRm3tN82Z9o9GMRo18pckCVF9qpfUBOkD1AbtJEz+p8lgkJ+/DxIkPIjCwkapdliznzpWibdtAm3r69GmLykoTLl8ukyYLAAQHN8aKFY9j+fIxKC6+hb59l2LOnCFo1y4IgDz7RYsnH7vvBxn3lTecE7iKI8djd5zfWtxrX9UHP3wGgNlsdHcJHqFfv/bYty8fxcXlqvacnBLk5ZUiKqoVgOproE0ms8PLhIeHICIiBIsWpdts8/TpK2jfPhk7dmS7tE5Hs7iau7brjPPnSzF48CrExXXA+vVjbX6pyJKlc+cW2LTpFEpK1De+p6bmIja2Dfz9faXJsmNHNk6fvoJWrf4HLVrMVR6nT19BQsIWLFt2UJosffu2xerVR3Dhwg1Ve0ZGIfLyriEuroM0WQAgPr4T0tLycOnSTVX7yZOXkZVVjIcflisPAGRnl2D79rOYOtX2E1ZlyRId3RoXL/6K8+dLVe379uWjWTN/dO3aQpos1gwGA95/fxciIkKRkHD33VwZs1h48rH7fpAti7ecE9SH9fmtI8djd5zfArXvq3qp9xdeSC9KTJ68QDzzzAa7I/Lzr4u33tput9+bjBu3UcTELBY7d+aIX34pFVu3nhHh4QvFCy/8SxmzfPlB8dBDf6vTMidOFImwsI9FYuI2kZ5eIM6fLxUbNpwQHTvOE1On/luzlkGDVoi5c39wuk5HxtSHve/Bud/bdYWzZ4tFp07zxIQJX4mSknJRWnpL9bCQIYsQQrz00mYRG7tY7NqVK86fLxVLlx4QgYGzxM6dOcoYWbJoqfm9SbJkmTPnBxEV9Zn47rtskZ9/XWzYcEK0a/epmDlzjzJGlixCCPH00xtEdPRn4ttvq/Ns2ZIpunZdIN57L1UZI1Oe1177RvX9nzXJkiUxcZuIjV0sUlNzREHBdbF582nRoUOy6vghSxaLtLRcERAwS2RnF9v0yZClPsdHT8vn7PcYCuF5WYTQrtXbzglqY29/1Ty/1VLzeNzQ57eO7itnGYTw0o8RcogBgEBa2kkkJu7CkiWjMHTob1QjCgpuYNiw1YiMDMXWrc+5p8wGZDYLzJy5B9u3Z+PUqSsID2+JJ5/siaSkwcq1zStWHMLSpRk4cGCSw8sAwKVLN5GUlIYffjiPixdvIjq6Nd5+ewDGju2lWcuqVYcRGRmKgQM7OVWno3U5689/TkN2dgm++OLpOtfmbrNm7UVSUprd/oqKJDRu7CdFFqD6r3xz5/6IzZszkZl5FTExbfDRR0MxZEgXZYwsWbTExCxGUtJgPPtsNAC5sixcuB+LFx9AQcEN9OrVCq+//jAmTOit9MuUxWQyIzl5H9atO4bc3GuIjAzFH//4ECZO/A9ljCx5rl27hY4d5yM19Q+Ii+ugOUaWLCaTGQsXpmPVqsPIyytFt24hmDq1PxISHlTGyJIFAMrLjYiJWYzXXuuPadNsP9RIhiz1OT56Wj57WRwZ42lZ7NXqbecEtbG3v2qe32qpeTwGGvb81tF95SxODFEdf/TodcjKKsauXS+iQ4dgZYS9diIiIiIiIm/BewzvWLJkNAAgMXGr0paWlousrGIsWTKKk0IiIiIiIvJanBje0aFDMJYsGYWsrGJs25aFtLRcJCZuQ2RkqM3lpURERERERN6El5JCHX/06HXYti0LABAZGcpLSImIiIiIyOvxHcMannyyp/L83XcHcVJIRERERERejxPDGqKiWms+JyIiIiIi8lacGNYQERGq+ZyIiIiIiMhbcWJYQ0hIU9WD7i+DYYa7S3AZZvFMzOKZvCkL4F15mMUzMYtn8qYsgPflcRdZX0fnvwFRYibT1/DxmQmTKRl+Gq8A3ykkIiIiIiI90dXE8Oefp6Jt27No2/ZbmEyAwZCB/PwU+Pi0RmFhZ/Tr9zcAQKtWzdxcKRERERERUcPR1cQwN3c7AgNzVG1G42Fcvw4cOwZlYrh163PuKI+IiIiIiMgtdHWP4e3bt1Q/m0zVj0OHgKZNJ7ipKiIiIiIiIvfS1cSwVatRqp/Lyu4+HzIksYGrISIiIiIi8gy6mhgOGvQ0AMBoBAwGoKQE2LsX8PV9Gu3aDXBzdURERERERO6hq4lhcPBw5OZ2hb//3bbWrXvh2Wc/d19RREREREREbqarD58BgAceGAiT6RcYDCYAwLBhK9G0aUs3V6Vvg0bvAQAYfO7+ncLgY7j73FDd7mPdZj3WYNtusDPWp9axtW3Xtt+6fezr2Q7Xpa7F9rn1+rVqsF6/ql9jvQ5t9067ZV2TPymF1VBlbG3LV6/Dfi3W67CKqLm8Vl3VbVr92usCgJnrq1TrsO720choPaZO/dbr1ajH7nZrWZf167QyTaNfY73qfuHcdjWWs35lNfvtLK+qEdXt2w8ba9mW9vKqsXfG2N3unX5VRtV6bcdq1Wp/7N22Q1nFNmNVy9e2rlrG2u3XeG6AWXtbQqNf2C5/PvsMDMJsu35hthlr3a61Lvv92jWglrGwZBD3Xt7i+qFUVS3QWs6BdWmNtbuc2ayqtWa9cGZdACq+W6WxnLAZp9lvpy7VWPO961L6rdut2kStY+/2l6/+4J51CfO9Mwit9Vu3Wy0v7LyeQiOv9XpFbXWZBYB2KPlwktIuHHg9NMdq1FVrRrvrqnv/3fZ+yH7+d5r9ZpNtXVp128tgNtVvrDBZ9Vsvb7Ktx2zS7lcy2O232m5Vdbu5Sti0AYDZeGddlVZtty3Px0NGunrHEAAiIp5AQUFzmEyNAfwBzZo97O6SiIiIiIiI3Ep3E8NmzQbAaCxFYaFAhw6T3V0OERERERGR2+nuUlI/v3bw92+HJk1+g6ZN+W4hERERERGRQaguvNaH4uJP0bz5f8HPr527SyF41z2G9u/1k+8ew+o22IyV7R5D9X1/8t9jqH0vX239nnmPYe3bkuseQ631ynqPYXW7/PcYamWQ9h5De/cFSnqPoeZ9f1LeY6hul/8eQ/v9vMewLvcYAv9pPAPZ6O4dQwAIDf1vd5dARERERETkMXR3jyERERERERGpcWJIRERERESkc5wYEhERERER6RwnhkRERERERDrHiSEREREREZHOcWJIRERERESkc5wYEhERERER6RwnhkRERERERDrHiSEREREREZHOcWJIRERERESkcwYhhHB3EUREREREROQ+fMeQiIiIiIhI5zgxJCIiIiIi0jlODImIiIiIiHSOE0MiIiIiIiKd48SQiIiIiIhI5zgxJCIiIiIi0jlODImIiIiIiHSOE0MiIiIiIiKd48SQiIiIiIhI5zgxJCIiIiIi0jlODImIiIiIiHSOE0MiIiIiIiKd48SQiIiIiIhI5zgxJCIiIiIi0jlODImIiIiIiHSOE0MiIiIiIiKd48SQiIiIiIhI5zgxJCIiIiIi0jlODImIiIiIiHSOE0MiIiIiIiKd48SQiIiIiIhI5/4fUZIs5WdasvUAAAAASUVORK5CYII=",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename=\"CompositionSpace.Results.1.nxs.xdmf.pvsm.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9cd420d2-8a6a-4d6c-80d2-5a263be94a9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<!-- Generated by graphviz version 12.0.0 (20240803.0821)\n",
       " -->\n",
       "<!-- Title: clustercompspace Pages: 1 -->\n",
       "<svg width=\"1152pt\" height=\"424pt\"\n",
       " viewBox=\"0.00 0.00 1152.00 424.20\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(0.428374 0.428374) rotate(0) translate(4 986.25)\">\n",
       "<title>clustercompspace</title>\n",
       "<polygon fill=\"white\" stroke=\"none\" points=\"-4,4 -4,-986.25 2685.24,-986.25 2685.24,4 -4,4\"/>\n",
       "<text text-anchor=\"middle\" x=\"1340.62\" y=\"-7.95\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">compspace: Workflow</text>\n",
       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>clustercompspaceInputs</title>\n",
       "<defs>\n",
       "<linearGradient id=\"clust1_l_0\" gradientUnits=\"userSpaceOnUse\" x1=\"8\" y1=\"-503.75\" x2=\"351.59\" y2=\"-503.75\" >\n",
       "<stop offset=\"0\" style=\"stop-color:#a5a4a5;stop-opacity:1.;\"/>\n",
       "<stop offset=\"1\" style=\"stop-color:#e4e3e4;stop-opacity:1.;\"/>\n",
       "</linearGradient>\n",
       "</defs>\n",
       "<polygon fill=\"url(#clust1_l_0)\" stroke=\"#a5a4a5\" points=\"8,-33.25 8,-974.25 351.59,-974.25 351.59,-33.25 8,-33.25\"/>\n",
       "<text text-anchor=\"middle\" x=\"179.8\" y=\"-956.95\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">Inputs</text>\n",
       "</g>\n",
       "<g id=\"clust2\" class=\"cluster\">\n",
       "<title>clustercompspaceOutputs</title>\n",
       "<defs>\n",
       "<linearGradient id=\"clust2_l_1\" gradientUnits=\"userSpaceOnUse\" x1=\"2673.24\" y1=\"-720.75\" x2=\"2424.35\" y2=\"-720.75\" >\n",
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