{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "q00",
   "metadata": {},
   "source": [
    "# Mantispy in ten minutes\n",
    "\n",
    "This page runs an image-based profiling screen from the raw object to a mechanism call, on one dataset, in one\n",
    "narrative. Every analytical step names a biological question, runs a few lines, draws a figure, and reads it back\n",
    "off. The other tutorials each take one of these steps in depth; here the point is the whole shape of the workflow.\n",
    "\n",
    "Everything is a scverse object. `adata.obs` records where each profile came from, `adata.var` records what each\n",
    "feature measures, and `adata.uns[\"mantispy\"]` holds every result table. scanpy's PCA, neighbours and embeddings\n",
    "work on it unchanged, so no result exists only in a notebook variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "q01",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:17:59.160362Z",
     "iopub.status.busy": "2026-10-27T17:17:59.159934Z",
     "iopub.status.idle": "2026-10-27T17:20:15.892702Z",
     "shell.execute_reply": "2026-10-27T17:20:15.890999Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scanpy as sc\n",
    "\n",
    "import mantispy as mt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q02",
   "metadata": {},
   "source": [
    "## A screen in one object\n",
    "\n",
    "BBBC021 is the field's reference compound screen: MCF-7 cells, 38 compounds at one to seven concentrations, with\n",
    "published mechanism-of-action labels. `mt.ds.bbbc021()` downloads and caches it, and hands back an ordinary\n",
    "`AnnData`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "q03",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:20:15.897518Z",
     "iopub.status.busy": "2026-10-27T17:20:15.897249Z",
     "iopub.status.idle": "2026-10-27T17:20:16.357913Z",
     "shell.execute_reply": "2026-10-27T17:20:16.356106Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 632 × 467\n",
       "    obs: 'Metadata_Plate', 'Metadata_Well', 'Metadata_Compound', 'Metadata_Concentration', 'Metadata_MOA', 'Metadata_CellCount', 'Metadata_SiteCount', 'Metadata_Row', 'Metadata_Col', 'Metadata_Control', 'Metadata_Control_Type', 'Metadata_ConcentrationUnit', 'Metadata_Perturbation', 'Metadata_Perturbation_Type'\n",
       "    var: 'object', 'feature_group', 'feature', 'channel', 'scale', 'angle', 'gray_levels', 'radial_bin', 'params', 'is_feature', 'feature_kind'\n",
       "    uns: 'mantispy'\n",
       "    layers: None (.X)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata = mt.ds.bbbc021()\n",
    "adata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8e52e755",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:20:16.361941Z",
     "iopub.status.busy": "2026-10-27T17:20:16.361766Z",
     "iopub.status.idle": "2026-10-27T17:20:16.367113Z",
     "shell.execute_reply": "2026-10-27T17:20:16.365059Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "632 wells x 467 features, resolution=well, grouped_by=['Metadata_Plate', 'Metadata_Well']\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    f\"{adata.n_obs} wells x {adata.n_vars} features, resolution={adata.uns['mantispy']['resolution']}, \"\n",
    "    f\"grouped_by={list(adata.uns['mantispy']['grouped_by'])}\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q04",
   "metadata": {},
   "source": [
    "Rows are wells, columns are CellProfiler features, and every `Metadata_` column in `obs` says what a well is: its\n",
    "plate, its compound and concentration, its mechanism label, its cell count. Nothing here is mantispy-specific yet.\n",
    "A scanpy user already knows this object."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q05",
   "metadata": {},
   "source": [
    "## Quality control: is the data worth analyzing?\n",
    "\n",
    "This first step is quality control. Two questions decide whether the screen is usable: do treated wells look\n",
    "different from the negative controls at all, and how much of what we see is the plate rather than the biology?\n",
    "Putting every plate on the scale of its own DMSO wells is what handles the second, since it removes each plate's\n",
    "own baseline; we then keep the informative features and look at a PCA to check the first."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "q06",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:20:16.370585Z",
     "iopub.status.busy": "2026-10-27T17:20:16.370383Z",
     "iopub.status.idle": "2026-10-27T17:20:49.742504Z",
     "shell.execute_reply": "2026-10-27T17:20:49.741110Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<path>:1: UserWarning: 2 of 467 features have no spread in at least one group of 'Metadata_Plate' among the rows selected by reference='negcon'. Adding epsilon=1e-18 to their scale multiplies them by up to 1e18, so they dominate every distance downstream. They are flagged in var['degenerate_scale'], and pp.feature_select drops them by default; to drop them now, adata = adata[:, ~adata.var['degenerate_scale']].copy(). A variance or outlier cut does not catch a feature that varies across a plate but is constant among its control wells; the flag does.\n",
      "  mt.pp.normalize(adata, method=\"mad_robustize\", by=\"Metadata_Plate\", reference=\"negcon\", keep_raw=True)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1455.6x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mt.pp.normalize(adata, method=\"mad_robustize\", by=\"Metadata_Plate\", reference=\"negcon\", keep_raw=True)\n",
    "mt.pp.feature_select(adata, na_cutoff=0.0)\n",
    "adata = mt.pp.subset_features(adata)\n",
    "\n",
    "sc.pp.pca(adata, n_comps=30)\n",
    "adata.obs[\"Well type\"] = np.where(adata.obs[\"Metadata_Control\"].to_numpy(), \"control\", \"treated\")\n",
    "sc.pl.pca(adata, color=[\"Well type\", \"Metadata_CellCount\"], ncols=2, show=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q07",
   "metadata": {},
   "source": [
    "The controls cluster near the centre and many treated wells spread away from them, so there is a signal to call.\n",
    "Some wells sit apart regardless of whether they are treated, and cell count varies smoothly across the same map,\n",
    "both reminders that a well can move for reasons unrelated to the compound, a confounder we return to under hits."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q11",
   "metadata": {},
   "source": [
    "## What normalization did\n",
    "\n",
    "BBBC021 ships at well level, so there is no cell-to-well aggregation step here (on single cells it would be\n",
    "`wells = mt.tl.aggregate(cells)`). The effect of the normalization above is easiest to see as a before-and-after\n",
    "of a few features, split into control and treated wells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "q12",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:20:49.746836Z",
     "iopub.status.busy": "2026-10-27T17:20:49.746593Z",
     "iopub.status.idle": "2026-10-27T17:20:50.362326Z",
     "shell.execute_reply": "2026-10-27T17:20:50.360806Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mt.pl.feature_distributions(adata, features=list(adata.var_names[:3]), groupby=\"Well type\", group_label=\"Well type\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q13",
   "metadata": {},
   "source": [
    "Before normalization each plate's controls sit wherever that plate's staining landed, and the raw features are in\n",
    "their own units: an area in pixels, an eccentricity near zero for a near-circular cell. After normalization each\n",
    "plate's control wells have a median of zero by construction (the centring is per plate, not per well), and a\n",
    "treated well is read as its distance from that shared baseline. The values are then multiples of the controls'\n",
    "own spread rather than raw measurements, so features on different scales become comparable and every downstream\n",
    "distance is measured on this cleaned scale."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q14",
   "metadata": {},
   "source": [
    "## One profile per treatment\n",
    "\n",
    "A treatment here is a compound at a single concentration, so the same compound at two doses counts as two\n",
    "treatments. Its replicate wells are noisy, and a screen is easier to reason about as one signature per treatment.\n",
    "`tl.consensus` collapses the replicate wells of each treatment, taking the median by default (what pycytominer does)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "q15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:20:50.368219Z",
     "iopub.status.busy": "2026-10-27T17:20:50.367758Z",
     "iopub.status.idle": "2026-10-27T17:20:53.097351Z",
     "shell.execute_reply": "2026-10-27T17:20:53.096000Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "302 treated wells -> 103 treatment signatures over 12 mechanisms\n"
     ]
    }
   ],
   "source": [
    "treated = adata[~adata.obs[\"Metadata_Control\"].to_numpy()].copy()\n",
    "signatures = mt.tl.consensus(treated, method=\"median\", min_replicates=1)\n",
    "signatures = signatures[signatures.obs[\"Metadata_MOA\"].notna().to_numpy()].copy()\n",
    "print(\n",
    "    f\"{treated.n_obs} treated wells -> {signatures.n_obs} treatment signatures\"\n",
    "    f\" over {signatures.obs['Metadata_MOA'].nunique()} mechanisms\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q16",
   "metadata": {},
   "source": [
    "One row per treatment now, each the median of its replicate wells. These signatures are what the mechanism step\n",
    "compares."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q17",
   "metadata": {},
   "source": [
    "## What is a hit?\n",
    "\n",
    "A hit is a treatment whose profile moved away from the controls by more than the controls vary among themselves.\n",
    "`tl.hit_calling` scores that distance in the controls' own covariance and gives it a permutation p-value;\n",
    "`tl.effect_size` then says which features moved.\n",
    "\n",
    "Some of mantispy's plots have an interactive plotly version, used where hovering over points helps. When the `interactive` extra is installed (`pip install 'mantispy[interactive]'`) those plots are drawn with plotly instead of matplotlib, which is why the style changes here; the rest stay matplotlib either way."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "q18",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:20:53.100671Z",
     "iopub.status.busy": "2026-10-27T17:20:53.100476Z",
     "iopub.status.idle": "2026-10-27T17:21:11.953288Z",
     "shell.execute_reply": "2026-10-27T17:21:11.952165Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        </script>\n",
       "        <script type=\"module\">import \"https://cdn.plot.ly/plotly-4.1.1.min\"</script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mt.tl.hit_calling(adata, groupby=\"Metadata_Perturbation\", use_rep=\"X_pca\", n_permutations=1000)\n",
    "mt.tl.effect_size(adata, groupby=\"Metadata_Perturbation\")\n",
    "\n",
    "hits = adata.uns[\"mantispy\"][\"hits\"]\n",
    "mt.pl.hits(adata)\n",
    "mt.pl.feature_volcano(adata, group=hits.nlargest(1, \"distance\")[\"group\"].iloc[0]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q19",
   "metadata": {},
   "source": [
    "Most treatments clear the threshold and the DMSO control does not: the assay separates active from inactive. The\n",
    "volcano for the strongest hit names the individual measurements carrying its phenotype, which is the handle for\n",
    "asking what the compound does."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q20",
   "metadata": {},
   "source": [
    "One caveat before trusting a strong morphological hit: a compound that kills most of the cells also moves the well\n",
    "median. That is real biology, a viability hit, but not the morphological phenotype the screen is reading, so the\n",
    "two are worth telling apart. `tl.cytotoxicity` reads distance against viability to do that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "q21",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:21:11.957136Z",
     "iopub.status.busy": "2026-10-27T17:21:11.956893Z",
     "iopub.status.idle": "2026-10-27T17:21:12.053075Z",
     "shell.execute_reply": "2026-10-27T17:21:12.051896Z"
    }
   },
   "outputs": [
    {
     "data": {
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   ],
   "source": [
    "mt.tl.cytotoxicity(adata)\n",
    "mt.pl.cytotoxicity(adata);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q22",
   "metadata": {},
   "source": [
    "Groups in the upper left are far from the controls and have lost most of their cells: their distance is a\n",
    "viability hit, not the morphological phenotype being screened. A large distance with intact viability is the\n",
    "morphological hit worth following."
   ]
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  {
   "cell_type": "markdown",
   "id": "q23",
   "metadata": {},
   "source": [
    "## What does it do?\n",
    "\n",
    "Mechanism is a retrieval question: does a treatment's nearest neighbour share its mechanism, and where the assay\n",
    "fails, which mechanisms does morphology confuse? `tl.nn_moa_classify` with the not-same-compound rule answers the\n",
    "first. The rule excludes every well of the same compound, its other concentrations included, so a treatment must\n",
    "be recognised from a *different* molecule with the same mechanism rather than from another dose of itself, which\n",
    "would be an easier task."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "q24",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:21:12.056083Z",
     "iopub.status.busy": "2026-10-27T17:21:12.055909Z",
     "iopub.status.idle": "2026-10-27T17:21:12.596321Z",
     "shell.execute_reply": "2026-10-27T17:21:12.595231Z"
    }
   },
   "outputs": [
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   ],
   "source": [
    "mt.tl.nn_moa_classify(signatures, scheme=\"nsc\")\n",
    "mt.pl.moa_confusion(signatures);"
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  {
   "cell_type": "markdown",
   "id": "q25",
   "metadata": {},
   "source": [
    "The diagonal dominates: most treatments retrieve a different compound with the same mechanism. The largest\n",
    "off-diagonal block, Eg5 inhibitors against microtubule destabilizers, is biology (both arrest mitosis and look\n",
    "alike here) and not a failure of the classifier."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q26",
   "metadata": {},
   "source": [
    "The whole map at once: `tl.edistance` gives every treatment-by-treatment distance, and `pl.distance_heatmap`\n",
    "orders it by mechanism so related treatments form blocks on the diagonal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "q27",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-27T17:21:12.599595Z",
     "iopub.status.busy": "2026-10-27T17:21:12.599432Z",
     "iopub.status.idle": "2026-10-27T17:21:13.131291Z",
     "shell.execute_reply": "2026-10-27T17:21:13.129959Z"
    }
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Vr6XzlzQEYmLHSjsXJAlSLOE2jcc0AV5\\u002f7tWSZyQPpdkMpZCHFAPnICJnn3cUB9hA1o6aVwQBvvsijz8nFA0pc5W5\\u002fmcUC0lLHYCShyQCpV+nUDr3JAsvFBVx5vc0A55iE+4pJ0QH3s2944pXJAafd7EuX9d0DPaEiXAmV6QG7\\u002flYnxSnhApOJVAvMreEBeQNDWclp5QF7rI14UonhAUMpTdRa9fUDxiAlJ+Cx4QNNjBK0BcHlAaugvluELeUAB05cQEth5QBbmhi2Hy3xASyAkVOpeeUBWhxS1jp16QAiZy1FDpHpAiuAHsJ3OeEABI6cc8iZ5QI+v7hFFXnpAiShm6xVDfkBhJXIGjjl6QGU49gh+SXVAgJcr7d30dECLjjMVLmF2QB9TFdGkfHRABvD10\\u002fHOdUCVMq6fFzB2QEJsIWZfDntA2XkPxel7fECjnh497gd7QGNvsKiy9HtADc7oHesWgEDkCKnqsAt+QO\\u002f3Y3xEnoBA+6Lxc2zkekAgYiE\\u002fLs96QKYqh9ntw3xA9wowAzN4e0BjHHg9vNt8QJIFyOly239Ai9O7zIvvgEAJelM6RRB+QFUZc87i2nxAF+U2i6NMe0CLnL2ABfaDQJ61yFjdjoNAiZldL\\u002fZCh0DyZ6DG7uCIQCiNufHVN4hANw88k69VfEBORy70EM5zQBXPkwOs53RA3vwFw32WfUA\\u002fOWrr\\u002fLR1QCl7ZDonOnRAvIc1aLN8dUAWcDfXOhp9QNYYQG1vj4JAJuT4zxcQgkCGkdzvlD1\\u002fQHkvz4lUsINA36On7\\u002fl8f0Cx703c6kWAQDF5AMw+HYFAFgB7cngRg0BzB8URR6OIQNhQH2orl4dA8ID6J9Twd0B+6GmVFZ6BQEqqCTYoil9A4Bk66TPaY0B04V9\\u002fGXRaQMZpNGEPT1tAAAAAAAAAAACKIVFEGrddQHxSBFC49mpAYDwCztNvaUA333afIoJoQJvEjja1xHBAtniyhHabcEA9B6eoMVtvQBIAGSOv7npAtXKZw6aMg0DnKUmvwDKBQDbZ6aZClnxAStVHQ34TgkDMt6x53th\\u002fQFD9pZzgGnNA3AOkZCMNc0D1XmmzWxFzQOawwdSrm3NAib0Vrv\\u002fPckDr2JJEy9pzQAMznQvvZXJAcm04eHrncUAxkyxF5pxyQPL\\u002fi4ooXXFAjnmkg8xockAW5zmlxoNyQO3nhgPbD3NAcsKjGwDmc0DcQmRRQE10QOhut2JPwnRAurieO0src0Cg7+ML0jB3QHk7kMZcEXlAE0mFwyMld0DpA8MMRFB3QGLqrebpHnhAwqKKCKDPd0Bj+sAP\\u002f9B8QDfg1SaBdHdAlFpmEWZ6eEDfLfjoQkx4QGoTG42GEnlAfN435arfe0DQItNWwBh5QPFpMYOoe3pAt5UY\\u002faYlekAwqZMDinl4QCzSGdsl23hA3tkG7QbneUCLG4AvSYN9QNrjSdLMsnlARf9TAIEJdkAnFmJo5Yx1QN782682wXZA9TZnJ6\\u002f\\u002fdEAup7uIADd2QMan6cP2iHZAPje4c1JYeUASNzbxT\\u002f56QGLyLjRtinlAjPAWHBaFekCxoe0ijjh\\u002fQP4nA7kqHH1AonAB88Vxf0BXZxJLnZx5QOMML6pZTnlAarkRwGefe0DeVX3YXxN6QOj6uyTE4ntAJR8dUw\\u002fIfkDQEMT0uLyAQMU7nZMqx31AbBdAJox5fEBHXDmubZN6QMjxqHrqmYNAzYX\\u002fyDQVg0Dby\\u002f6RvJiGQCUsDzfhZYhACt8\\u002feV2zh0APvx9CrLp7QGgobPGz03NA9yi0tDkAdUApth4NevR8QIFcuFGqdHVAMBLkPaQWdEDjdqAyGZl1QIVMzA2zY3xASWt7rSfvgUAVcWcMbpeBQHjuLSIgrX5AfYYc\\u002fdQ3g0B\\u002fO2LJQ7x+QNCjrTGCh39Apxft\\u002fV6fgEBfD7MmCI2CQGxpW2VfU4hA9MaEnr+Lh0B2Rkg6ANt3QDUvTAeTLoFAUBYOg8qsYkC2ZQImg3dlQN+Vpe8KYWFAh528MblDWECKIVFEGrddQAAAAAAAAAAAOOwPaQpca0DsHbxgvTtqQJ3x7dm9rGhA+MaIl\\u002f\\u002fvcECvkrILeA5xQDG\\u002fOHGREXBA\\u002fiQAqrBWekDSUm0THmmDQPgfYI6R2oBAWV06SNTve0CgHDo0qbqBQDj7h6rDF39A4bzO4as2c0BHJum9voRyQIiBbIPNxXJAgeCcI1eKc0COSNi\\u002fdr1yQFKLj8UXGHRAHtN7BSNsckAgfLoBa\\u002fxwQKtSxG2rRHJAbr3KJKGWcUBXFEB44IZyQADQRg30J3JACHF2dU5WckCUwHZIGtNyQHX5OuODanNAd\\u002fOL\\u002f9RHdEAfPbaXyqNyQI4kZnjoa3dAkhcbj9dkeUA8aPO1Jpd3QOfI3L5uZ3dASuZml+2ZeEB1rGWUIUh4QBjxcvTz\\u002fXxA0YWeZBPed0AwCD6N4gZ5QECuy\\u002flPwXhA6+ncvqh6eUAoDRkw7VN8QDvKooz1bnhAxwF6IuKZeUAya1mEiYt5QBgTBmKE83dAoKtdkgEgeEA3Y2e0BDV5QLS\\u002f96swLX1Ago2NhYNleUAReqgcX3Z1QLx9JpVpHHVA8MdhvgGedkAGQArNbcN0QKYdUckY63VAcz03npHldUBJKJ1xCB96QBlA2n5rfXtAKpbyQckDekCqyLOGdSJ7QLFY8xosl39AyOaRwdxsfUAmRnX4arl\\u002fQCWQ0P0ZFHpA9qHE1JfpeUB3DZzqlAV8QMm2JwDc4HpArDpDkq0JfEDVavGUTU5\\u002fQK\\u002frqFyGkYBA2cYX9TCQfUA7mJXZRH98QLqaw91iEXtAUaVOPhzUg0Dmw8LId2qDQDIKwFceQYdA+COWSp7qiEDYse3b3CmIQO3X9nYogntAKT5l8JDec0Ch6a+XY\\u002fF0QEhHx\\u002fzFHnxAuoZlOiqndUCoGlH47R10QGmlvMujQXVAzTuJY0PMe0BqDnJnGdKBQDxPJnmWUoFAjfjhgVL4fUDzIabC6eyCQC7qNc+SVX5A+NoGOlAmf0CBkoeGgWKAQD2YmsLAooFA4VOrVWE4h0BZeLlTFCqHQBhMguGkiHRAYhTF11sRgECCqVGdDUlnQNOvaryKxmZA0zsNNeRzZkCcQCvbjzFtQHxSBFC49mpAOOwPaQpca0AAAAAAAAAAAGVYV2Aex1RAoANnoI5zWEBRn4aNNJdsQE+d3f7yq2tAh4exnT+baEAcYHKUbxZ6QJTuaQfYoYJAGKT9OLNNgEAiqIxuL157QAiuL0KRJYFA8uQs3NI5fkCvDoveudl1QGuDBXQ+8XRA5mftm7audEDT+9nuJYp2QIpUAWwGo3VA9kwI5c+KdUCmCFm5V1B0QG5NN\\u002fF3PHNAAezSiW6fc0BnlgZ44I51QCCv9ffji3VAlriYIL4xdUDi70fP5yR1QK7EZtlcaXVAXPVZS4N7dUAsX4fvpsF1QKIdtj+NmXRAerQuRueOdkBBpMZhagV3QHKH3JRCV3ZAuJmfkMEMdkBDq4FORt52QEsyVkwgoXdAp0fcfoVRe0AuQn0eH2l4QO1v5KrI1HhAAElnrZjveEARLtQ7bpV5QB9yjXOnG3xAGTs3I1tveEB8PuGRuKB5QOxrWS4tEXlAvqzHBmD7d0D+OMvhgRl4QMmILVfje3hABao3INeMe0DMFQbzTwN5QDKSJSDwF3hAsdL7FA++d0DEH6KBNAh5QCaktQXzVHdA0rxRvnv6d0AjIcSO90B3QE0NC9P9kHZA3Y4IRk1NeEBLmC48xKd2QD\\u002fLBACaMXhAQe3dK9KMe0Dkf5\\u002f9PEF6QFL\\u002fx8aix3pARksPk2fmdkCUhnWo9+p2QCJ3ezz9uHlAu4NF84YHeUD\\u002fbzYR24Z5QCrvrZ+yRXxAtKFgN3jTfUCgPAiuQpV6QGuiqG8unnlAF8bnoZc\\u002feUDZrPiGXXeCQJ7YT+I+HYJA9i6xrHtThUACdSs+vhyHQKwuaHBxIYZAXlRqg5cxe0DbwhpQs7Z1QL7nK+PcwXVACUp2lbx1ekCiiuPYhJ92QGMrT9AVmXVAF6K5lqRqdkBEAa7V4FZ6QIUqeo+vroBAV6oQdd9QgEBwpcPoOXh8QD48OlQo2IFAWV5mgNN2fED9l4TK\\u002fz18QIE3lE6jQX5AfZHe48\\u002flgUBOZf25TXOHQAGl07NKQodAr\\u002fqwMSYodUCpuplE0EyAQOSBE0vQgWdAYweGHWSFZ0DfRVSYFBNmQFt+h\\u002f94kmtAYDwCztNvaUDsHbxgvTtqQGVYV2Aex1RAAAAAAAAAAAADnZmWjDVRQNKYdUIAKm5AqgSCs0EcbUC8hUvnIhxqQLzm3BuCDnpA1xt+IIHMgkCLv4Up1HeAQPGh733koHtAMawJdcFYgUDndCiU6Il+QA4TWHaPM3VA+jlPmMRWdEDOB+DZqkJ0QMeISPW6w3VAiqULeRYMdUAPzvSxOJ10QKBrKYgqSXNAvEluiM2dckDer7x\\u002fh8hyQJXT0Umm0HRAM+XqIeANdUCt3bLnnsJ0QDxHxlf2fnRAukuRJAfgdEAXvGcUkvx0QI0lTJFqcnVA39GrobcpdEDeSEBI4qJ2QIkBT9KWpXdAl3CQTdJudkCXFCw8B0F2QAanObCgJ3dAzIQPEjyWd0CrAje6GaV7QGFBdxWxKXhAjxY0xqS9eEDmYpphwL54QLdjz4QVdnlAjtLFRufye0A00MUWzHt4QFvJqoaoz3lA+\\u002fMstU1SeUD9OwmXAeJ3QKesKb\\u002fMGXhAXe0Vtdq9eEAGE\\u002fJlD8l7QBv1DD\\u002fr9XhAIbIFM89xd0BrEHXbCgR3QPbu2xcJP3hA9EBYRWiFdkAdOoL7rXB3QDLo291U0HZAG2XPbq+kd0Ch9mf+9zp5QJGJWmLDu3dA2bkJfLzxeECoUrfSKGt8QMBcE8GmFXtA4C61bAUjfEBRZ0Diwpp3QJ6xuoj4iXdA4ZtFtHk1ekCv+ObcBT55QGF\\u002f9Uh4KHpArIwoK63YfEBtv8npTyB\\u002fQE0V23VwZntAivVTKd5ZekA6TlGKcGp5QG0Pop\\u002fBt4JA1FGrR3lYgkCjFO3TWZaFQGzK3Uf7WIdAlMnhkeFyhkDPWY+nM3l7QOZFeTMNEXVAOJkY\\u002f+FMdUBE513VqFp7QIiKp\\u002fl7OHZAx3exAG0udUAg0mKPUFt2QLev1cRzynpA3oH3g9YJgUBqXJaIycmAQJNdIecRHn1ACdr+RvFFgkCACzXWa\\u002f18QInkCofn\\u002fHxAZOkt96ryfkAsc8DnhWOBQB02NTA4DIdAx7Bz1vjOhkBv0TYw0Qh1QIffuGD38X9AzpNVkLBNZ0DNu7f4mddnQO9i3cHk4GVApAOug6HxaUA333afIoJoQJ3x7dm9rGhAoANnoI5zWEADnZmWjDVRQAAAAAAAAAAAzRwdzXS8bUAomuI1N8ZsQJDPknESjmlASdfI1JK8eECZR7KnoFWCQPku1s47yn9Ao8DC5RJhekALRC0H2MyAQAna42yFSn1AkA0VJACdc0CPIRgaeLxyQIWIPuZL03JAexGZDCM1dEC5niH3jo5zQHvV7yMUBnNAuXJdYwC2cUCuavbt+wFxQDybJVnwNHFANIpfthAQc0DlmiPTN2ZzQPFll\\u002fU1BnNABuaEw2rZckAOj1VLYGhzQHAEv6JeXnNApfQZf+7Ac0C1UjUk2W5yQGoVOBzsmXVAk10W4O4gd0BmgH89jql1QGMnFRR2UXVAzf6jkEePdkC0j2aD2Jh2QG1DZtz1unpAHnO8lqI0d0Cd6ITAatJ3QLCIOT7\\u002f6XdAjB3dIWB2eEDfjQ\\u002f5ngh7QETqfyssKHdAmeVfbpVyeEAVQmefdwZ4QEZ\\u002fEFgSq3ZAtKZfmlLRdkAgH9jMyap3QKIUBDgI03pADBoxnDe+d0AidR5iL+R1QDOvVNi\\u002fgnVA5PfAE62fdkB2sn0l1gF1QIjkROIT53VAkeHqQFJPdUAd4oc+ylx3QB\\u002fsyNcH4HhATo8rX4lrd0BDCQaBXp54QKoomGyF6nxAAoMJqIZCe0BUnwHjfGd8QNcPsEh5jndAG7J4775ud0BvYGUHmO15QMAdguIxy3hAfWX9FHf9eUDwPDcJaLl8QNB\\u002fv\\u002f0PPH9Al1kaOHc+e0DLcLbtRR56QPN50jR473hAxYktzn6qgkBDsg8nO2GCQPpflLvPhYVAqt1Gm0ZDh0CpfPVPwXuGQDkuNsUjIHpAuTfFbQ2Vc0B6oQxO4s5zQDL\\u002f+fD2dHpAUJxWKjG2dEB50rF1WpVzQMLzkMoT5nRAIr0F1T13eUAiES5JuIaAQLGXh2rmMoBACnrgZBnNe0CeDhiTrrmBQIZ8BjK8vntArut4aH\\u002ffe0A2AAcBVNx9QJ40t9FOGX9Anys8+vQIhUDxMCAm29mEQHLOCRMLzHBAYXrGQZiUe0AwghXZwShuQFlHUVQa6GxA+Dl2Tp3jbUBUq0N0jmdyQJvEjja1xHBA+MaIl\\u002f\\u002fvcEBRn4aNNJdsQNKYdUIAKm5AzRwdzXS8bUAAAAAAAAAAAK57Qri3CFVA6IeQ4SacXECA6xwuT551QPkJ5tSzMoBAYu6ZKXzKe0DyL3SJzSd3QJSi4d6otn1AL33WRYKueUBoOBhneiJ1QGvezqUo+XNAKz4wr9eLckDv+RVsfVt2QGFo+QygpXNA1R697AZmdUAAIpeT2390QNnJNx2mQ3NAnxYKfXLxdEDN\\u002fFSwNs51QCtrN8iAS3VAbEy5WjHBdEBcOqYvMwZ0QIiLOHeNXXRAOb92jgzuc0AIUlpUV8JzQPRzyrOCiXNAZ9FhRqtmcEBd5kjeNrlwQINPBrJL1HBAo4USLYEycEBfddYRC6twQIXYnO+tN3JAnY1qd889dUB00qrixoV0QIHZvb4I63RA4ZfXqA5JdUCsWdjHXK91QMcfFuR0NHhAetgOAmj8c0DYC7XZbQx1QPjwZc2GZ3RAkII4xwgEdEDaohLh6tVzQGIGKt7mOXRAQXxTfor3dkA5+hDNhPx0QKoasBHghXZArUfISTGudkCDWcjFjzN3QKcwAjNCXXZAyqeUCL76dUCAT8sfsZJ0QI9Oh55DhXJA540rPrEgdEBFjZQzDYdyQLJ4S1OSM3RAyn9w4RVueUBEELNowDx4QKjPm+5JyXNAZj86VewhcEB2pSMr72RwQMuolw\\u002fNcnNAHOsGYOgoc0DN1hhzERVzQB2CK8CeznZAjAiXd4KMe0Bizxo+VjJ3QEpZfJcFXnZA5tv7OQWcdUDxg9w+E+OAQE4essFJooBA06NQX3UUhEC\\u002fAqCh6hGGQEBKCHPy3YRAuZGSnuNPdkCJ\\u002fLkPl5tzQLQEiyAGcXNAiKTJgmj+dECARRxV+\\u002fFzQNGqEDSWcXNA\\u002fgiiAEENdEBvjEuO2Ql1QIrBYuB6K3xAa4DANuIYfEDbDdB46td3QDkq4FOhUX9AUmSyYOdTd0Dxc5rJYfF2QMyQfeIr83hABdnDOKUof0BmBWSjdiaFQNv0yw9f\\u002f4RAR+423AS3cEBVxFWq6957QFzgrAdF+WxA1sQVGscebEC1ZKc5pgVtQNQNvmmtTHJAtniyhHabcECvkrILeA5xQE+d3f7yq2tAqgSCs0EcbUAomuI1N8ZsQK57Qri3CFVAAAAAAAAAAAAFhvGg7tNTQBZP+buge3VA3I4OvIksgEDANyoDgrB7QBBR7My4A3dA4eQHdW\\u002fafUD5GvSFz8N5QP\\u002fpCUPyr3RAU8ccM7Bzc0ALv0LMKxByQFWMuHnvDnZAmia+P47lc0DEh+fNkfF0QHjEjbKpFnRAA4EbHPcKc0CYwPxKgIR0QOLz3jAQlXVAm4hb24gYdUD9f4Eofb50QI6tn\\u002ffN3nNA728ItdMndED8Mey26IVzQKneOoCkVXNApCtVpGMcc0CsH0KZXfxwQPFPLYYr7XBAvocJyjw0cUDNl+oBJapwQKtU7fkd9HBASvhrnnK7ckDqvkhMsqp1QP8QzZJNoHRAyCbRW7DodEDmVg6PVmt1QEg2muqtuHVALkJhBk1FeEBaihYAlfZzQJErwULQ7XRA3hcmGaxSdEB+KfgxZLRzQHfUVoKQm3NAZZDWLdf1c0CG8WeHX+B2QJHHuAyP8nRA3BRbSSVCdkA3J2iBRTh2QCYJm0Zt5HZAFm5c2qHDdUA1bX6\\u002fc7p1QIaEneeIXnRAl8cmlNBRckCPdZ6pwfhzQCj7G0YPVnJALFWphuUkdEAVJ+2eHo55QJjW4LEG8ndAeg0tCtRvc0CfAnhLu0FwQEJ64AkMqXBANXMRj2P9c0A9j7rSIsFzQJaMMhPafHNA2XpNrC0Wd0Bn2zoFhyR6QGt0jKy\\u002fgHZAjJ5mzkbtdUBOFKEM8OV1QCJS7n8S6IBA1nHhWqrUgEAPYL0kNQ+EQOvr+WH7F4ZAGykP7\\u002fDkhEDynFlpWG52QHWXsLgjZXNA70n0Ots7c0Ar+asUlt90QB+9k7MqiXNAycU4f3INc0CCV1MeOvtzQFItXiazNHVA1g8Q\\u002fa60fECrvSOsFod8QGBajtdT\\u002fXdAOZxHQArbf0A+tPHSnGd3QJhU0Oq+PHdAmvPUf4JLeUCCROUSkheAQIuPn+pLrYVA1JMEbWaRhUA5iBDfu\\u002ftxQMcnx4ClL31AGioZIrAha0AL0sLBIlprQEGtKBe7LmtAWPVsNO4ycUA9B6eoMVtvQDG\\u002fOHGREXBAh4exnT+baEC8hUvnIhxqQJDPknESjmlA6IeQ4SacXEAFhvGg7tNTQAAAAAAAAAAAPo0I6ep4dkBEV1BvKcCAQN65VaWPz3xAHH3gzqfkd0BRnhQrrth+QALLknJHpXpATCtfHYwcdED\\u002fdvNIBfxyQDmxtjNp\\u002fHFA5cEceYJKdUDSRtUvfc1zQE5l0APbinRAIFLSd4OTc0CamFoDTqtyQOAasDbi5XNAT\\u002fl8fT7tdEBZfcfZL5d0QNmWP6UJWnRAomgQ7Aqbc0Cb1V4OHOdzQHVa3xAmYXNAEOYltghQc0CcI9MSiMNyQDfgSHBuuXFA16uNRhheckA69wSkXRpyQLNQUCp9jXFAwU3ckPVEckDYugFyUWNzQOdHtpCwpXZA9dkaB+AmdUDVrxmlLYl1QI+PfJu88XVA9GsDTdM+dkDnKCD+us94QO2RvLa9\\u002fnRA8CT+XdkHdkAuOglcW4R1QOBvPxgAbnRAVHWdCNpVdEAyjIgm4OV0QPLhoAT3K3hAKQxa+3LvdUBqElF6wCR2QJVX0KAi7nVAl0gr39msdkDilqEmMFd1QA\\u002fQO+8vsHVALLOLp6WddEDHI+z+GztzQMsvDHj+BnVA0F542cA0c0A9a+CDPf90QDvNGMu2onpAymqTdSK0eEA8RSjRq0x1QNUiHKb5lnFAJvOCoV3jcUDkuMy0HwF1QPsbnRxun3RAT09y9ci1dEBt7uNCUCp4QDeXFh3cbXtARrA9+buxd0CsQ8oP6+V2QFAu1tLotHZAc2WEV5VkgUBPRn5Gc12BQN07KnLhg4RAQamzRoJ\\u002fhkB1TXWii2eFQMeGRrqXZHdA6D41AhVwc0CzKTd18X5zQAF4nzcGw3VAmQGHttawc0BB42viFxpzQAkwOGpGG3RAuQy+hLlqdkCSVYXkihN+QIzD62dik31AgDAUTu8JeUAJa581e2mAQPtWejEwgnhAAS2tgYxweECKU4Iv\\u002fnl6QB7ZoIb5x3pAwaPzBnJCgkDOA5onS+KAQMwsB2expHNATnR\\u002fbFiRdkBgCFaIPoJ7QOgK1z2ar3pAXOzlx7rwekCfuixgAht7QBIAGSOv7npA\\u002fiQAqrBWekAcYHKUbxZ6QLzm3BuCDnpASdfI1JK8eECA6xwuT551QBZP+buge3VAPo0I6ep4dkAAAAAAAAAAAGLyBncFOnNAmyB6hy0takD1AAMi6JZgQOWkaGv3SHBAS3audzMDZUAp0aaGjdZuQAORLPz1b2xA\\u002f9YnhbDLaUDdJGB1SudwQKWg\\u002fkCS221ACCPr2kC5bUBPk0eS\\u002f99uQFso2DNPam5ADtYYZ7kUcEDpQvQjqaJ0QBlWect2j3JAU+T+fwPhcUBiP\\u002fjgf\\u002ftsQDaHQG1BC3BAf0i5cjDEaUC3LbrLRPNnQFU1TnLVK2tA0nI2h\\u002f5UcECo3HjQIiFzQFkzvmKXi3JAi674IgXGcEBu025wmeFyQABYOZYSDXJAdT0la+5Mc0Cggct1WONxQHCK4UaPK3JAi0+le2TtckBh8cvl4mhyQCIjtn8ExnNA55qDpmqdXEA9i+91KVtgQIwmmm7UqWBA3C8isez\\u002fXkA3+jJhF7thQHW6MSvutGNAKufHVBG6aEDca0GNjuJiQI0h5nszcGxAvAenk53kbUAyHuVz7p5rQJb89glJO29Anfv7DxKvakDsuNPF4aNjQOT+ulOp33ZAs7CaX\\u002fwJdkDs6O\\u002fGlmh2QP+Ig8oNjnZAV2HgI4rDfUCZ91AgZGR7QNi6+aai2nlAeOZOvCD\\u002fdUBcQGjhdfN0QK2i35ii6nVAodnEI5hQdUCaUL5KaGl2QNEmcXKyznhAgpDHKLU4fkD6osAp\\u002fAR4QGxOPTmrSXdAvZM0lKH\\u002fdEC72qyUbYWAQKUvdQNeC4FAZWncHen1g0AUr5pYAdOFQOVy1lqfZoVAlEVwo\\u002frQaEBp8CDMi+dnQCHoWKuMJWhAPhNiY3B4c0CcYVH8IGpkQGF7VVFro2ZA5i4lgHy3aEDYsayT365oQM2vUC0dfnhAQ59w76sCd0CEAwEp+HluQNyxFxUkRHtA\\u002fAfYJvYvb0A3PtAVkD5yQIYeDwp+VHRAZdMKBlLqekDB5pn1O\\u002fF+QKMmZeDRKn1Ah5xbtXkne0C\\u002fT2dmApR1QDd3SxtEhINAWx4InmYSg0DVRITA9kCDQDOIBLTyzINAtXKZw6aMg0DSUm0THmmDQJTuaQfYoYJA1xt+IIHMgkCZR7KnoFWCQPkJ5tSzMoBA3I4OvIksgEBEV1BvKcCAQGLyBncFOnNAAAAAAAAAAADbWMKFcZNjQDGDL80s7HRAAgjLr3C5bkDThdeBt5JwQLEQTcEinX5Ac+YJGEtvfUDyUCXfUuF8QOCMo0RjaH9AszagTEkQfkAnzhoWgDd+QF5qsYUP435ATSby3YWxfkBu1acgFwR\\u002fQHc9KHfjWYFAG2Y\\u002fmz08gEBdckuIEv5\\u002fQGvht1NNaH1AyHTgBIzVfkC74NndBwt9QL8jVX8FVXxAI6ulLFA8fUBD848opLF3QH6wKGI9h3hA\\u002fBQVppS8eEB+cHttP3d3QGVwfbzjV3hAgV7vApcveEAC4QdawkJ1QCsS7KA743hAWMQvpCkveEBYXBb4qih5QKcGv55e6HdAVyk80tDQd0B9Q+lOY4N2QOarg7Iqv3VAQtUMxIN1dUAxUAUM+ap2QHFH0DyIPnZAfWWVaIrMdUCz7fRukWF2QCYjl2JlBnhA1j3+95cXfkCu+luKjqV+QN6nQCPbo31AABGn7E5Kf0Bb0iI3iiV9QFbToaQwzXpAz8biGv5RfEByIdEthlp6QBD8icSGTntAgCbvJAc2e0D1Mqmx+giBQPBptCzsbn9AbguNbwajfECZcSgWYQ17QOKFBnfr93lAWe0PzQxReUAMl3P58Ml5QDVmsZdcOXlA1PnCCDCVekAmyXuKlw+BQD7uu0Xu\\u002fntAnkWtoesde0Dqp11y6zB3QP+3qhWwKH1A2iF8Nhd8f0CxLWAFyrmBQC1Tss7H74NAReYhM+qRg0B3nWVdoJRyQHGgd8ywxXpAl4XF4hwxekCDd6NQt2R6QAVroIh7Q3lAauNe+dyZekCS8q1cwY14QBiBBvTP+nRAsQt2YYyJeUDoAYy6SU15QGq+qYXL+HZAwRnZuSGse0Cjd1mFtiF0QO7wzYyI6XVA4BU2Mms5dkAGo8fEzTd5QJj+JVtsIYBAcXufG6gMf0DG4Rmy7hB3QNjMyFV1InRAtsCZ\\u002fZcmgUAOa\\u002fVex76AQHO\\u002f\\u002fWsC8oBAUw6FzHI9gUDnKUmvwDKBQPgfYI6R2oBAGKT9OLNNgECLv4Up1HeAQPku1s47yn9AYu6ZKXzKe0DANyoDgrB7QN65VaWPz3xAmyB6hy0takDbWMKFcZNjQAAAAAAAAAAAOxbQgAHabUB63AxsdFJnQFeSpvheN2VA5gbEXlHQeEAcgn\\u002f4LGR3QEW9I9CH1nZAcLfCv2+YeUCJwBBTLx94QD4uj4uSWXhAf9OM7Gj4eEBYKapnFoR4QM7RqYHOGXlAjWHhw\\u002fsMfUBjl8GSHvF6QESW4vbWWHpAwGlXWt1Gd0BOMz+F+9F4QAbpSXaAl3ZAJh8+ayXhdUD7cw4+8O52QLXYTHEuF3RA3mjooW6JdUDtTJXADrd1QGnYrUp\\u002fBXRAUSrh7rGIdUB1NrgaWwZ1QFfGRi63fnNA\\u002fyznvCVidUBj3kitKw91QO6NpeS7HXZAELgCVwfadECoyb0FXHZ1QDIXrxGOaXBA+7JS\\u002fSUhb0ADQUjFWERvQNKCipPFqXBA1TsFCLSbcEC\\u002fQszAxE1wQPYo0BlqcXFAAf+d0Gk+ckDIfFwDbN93QAxoG03xjXhAX5F5WVWLd0D3rHa\\u002fqjJ5QKf9Ztbo9nZAnP6Eb4pvdECU2olNiJd5QKM9DLrKzHdAEiNbGXqfeECS2W\\u002f+Yb14QLpx+mHYWH9AZK+gSGyhfEBTmJtmA7Z6QBROKWAqcHhATwx4BVZtd0D\\u002fxBMkEjl3QDZ9Vj+dn3dA4DYzDnAVd0BgCmy8dBt5QDwahcWTSH9Ay6YNSikqeUCUmX7eWGN4QOPIJiUdzHRAg9fksk2GfUCULdEgurN\\u002fQB0sNqOHR4JAoIJaALJJhEBAvLDhbOmDQDgGRyCtwWxAf3\\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\\u002f8qHFAHr+oayq\\u002fbEDzDN9INEtrQKySVSmPu25Au2kjgrFKc0AG4V5FPe50QMBbZGpaFHVA53tnvR5vc0BWKjikkfF0QIj98gyyj3RAF93xouqGdUA5jHnmqsp0QJWp4+ILw3RAUvb3yySydUDSHUrOvvx0QIiF9O9xhHZA0pMwrxYkZECxXEokHDplQD4f6Hi282VAWXPIlF2TZUDIms4Tz\\u002f1nQKhiAP6nlWhAOfufjqDlbEBRGUzqHxxoQOHjvOjWqG9AswU0Uq7KcEATGG2GL45vQMLbZbYnsXFAqhSNoTvxbUAHVN9q1Z9nQJhz28UGvXhA5kRwv7oNeEAU813xEkF4QDtz6d+gtHhApRn6XkSDfkBlJrFkTIB8QBY0mkk4u3pAVz423vIoeEBa9E3S4zd3QIKUaprHVXhAycqIFVvld0BXQUvCVpZ4QMIyMzddHHtA9u4DZGjzfUASzRMkyS15QOaon0aFvnhApMpEfo5ed0AmdxudfV6BQPSx6gQoBoJAoilTvXGwhECUSG1o4ouGQAtOnHpf\\u002fIVAxmq0KH63a0BMnqWdDF5tQIOLnNz1vG1A8pmeUonAdEA7HQ6BeChpQGX6sCLmT2xApTxv98IzbUDflfobM0VtQP+Zshp4tXpAzywOg4LweEAySQ1gDTpxQJPJ20DrO31A9gk90ok+ckCLqahnX6N0QMppgLKCmXZAkizuF5J9ekBfkLsQz76AQIAfbGs\\u002fLIBAWNhIAnnxeEC+4\\u002fZNkNp1QEHODaswA4JAyDUk3TmRgUDPZe+z+ciBQP03xi2DHoJAStVHQ34TgkCgHDo0qbqBQAiuL0KRJYFAMawJdcFYgUALRC0H2MyAQJSi4d6otn1A4eQHdW\\u002fafUBRnhQrrth+QOWkaGv3SHBAAgjLr3C5bkB63AxsdFJnQEQTZYjLM2xAAAAAAAAAAABVTOZct\\u002fpeQBVijukbMXpA+v6MprY4eUCYkN1BHZF4QBa+QhwfHntA7q1VlKPFeUDeRhaOihV6QNaX30nLnnpATgifAn4sekBPpFlgH896QKiVcm\\u002fZu35A\\u002fzLTbayVfEBizPkI\\u002ffB7QCMe0wGibXlAVTcdQNjoekBuPJCoazt4QId8mwDjrndAnZrh0lvKeECL1TByQ+t2QPg\\u002f2LlrTnhAbOxMWodReEAhYlPcvbx2QO4UH5fV\\u002fndApSyjnb2cd0AQ1wL3++V1QCfYSIEuDnhAsU\\u002fiKmLpd0Dmc\\u002fOtf6t4QDOoB\\u002fUYc3dA+SYBApYpeEDBhJrciCdyQDM3xoBMYnFA8pTSC\\u002fGJcUCDUswt\\u002ffByQAu5xpZ6AnNAjbEJ+kX2ckBtFtCuaaRzQFA6dy3mSHRAFcKD0TdxeUC\\u002fbT0Doip6QKwxRJF2DXlA7rpqZBbqekDEbCvib314QHTBF5YGM3ZAG4gF\\u002f0XZe0CcpQBTolN6QBb7L3102HpAhK1PoM0Ke0DuU6wyeSqAQB69KXiAH35AFV2hXbXXfEA0DkeApwd7QN9\\u002fbP6uM3pApugelEXWeUBjxOHwtTF6QCBIo5anz3lAcZyieiCke0BuMdqzB5GAQGs1IxfY6ntAE6AAatxCe0DfzDsDf9l3QHYoFlegKIBAV9wYIAQYgUAq3EzLqTeDQF1vMFeJEoVAr+hYoS+mhEBWDMC3fkFwQOS6rmfnKHdAiJ04Jo3qdkD7pcrE64l4QHxjWa\\u002feZHVAhyPosK7kdkBBEEq05hR1QD1Y1c\\u002fbM3JA4nnvU9AtekDk81mYJVF5QENzOOboeHRAX8HdsD9yfEBmK2\\u002ftfd9zQMEkQ5YdG3ZAildhsMWydkBVxEsptaB5QKisQSojGoFAo6IEV7RigECdFlEw4ux1QM9dcOlck3VANt43qLfmf0BPrGp0sPZ+QIlPRLxXan9A8Uxgnxrmf0DMt6x53th\\u002fQDj7h6rDF39A8uQs3NI5fkDndCiU6Il+QAna42yFSn1AL33WRYKueUD5GvSFz8N5QALLknJHpXpAS3audzMDZUDThdeBt5JwQFeSpvheN2VAVDbO7UpPYUBVTOZct\\u002fpeQAAAAAAAAAAAIvO6aDTldEA8WAqxGL1zQBuAJEFR9HJALHQUGjn8dUDnb1RY74R0QCTYgrXfoHRAfikE7BEvdUANOk1oi7p0QBxI9y3zb3VA6AZVVdrMeUCUWlx2r4p3QLpwllej3nZAr4LTKr0LdEBpPRjrnI51QAZx4ggQmHJA8SRuEqXccUBtWTRLriRzQD+VTyuTh3NA5xy+yr2GdUCp6Ej\\u002fmW91QL+wwY9amnNAwClg5lxLdUBLbIrrFqN0QHALXWquJHRA7utiHHD3dEBhOueCnwZ1QLEy5u4MyHVAWXNfQwrLdEADC1fbLtV1QKA7VpVTXmlAZVQ3HUDFaECEIEJsT0ZpQFucPTa2mmpARRQgV4WZa0CVCLx87QRsQNkwiA1S0m5AwMf3jna0bUCIhUF9teVzQKN6uJKTt3RA6fZHW4+Pc0A6zpNrdXx1QGL+COMG8nJAf17oc7FYcECrp5qVpDR5QJGEpfpp93dADPrI7JpoeEBUwZR+A7V4QM4zSMHTUn5AKXfCxcj8e0DWoOZZXAR7QJndlu78ZXhAXWsJ4gl2d0Cz+zGoi4x3QANxJzoVlndAO1K76yuxd0A9IOHLP\\u002f55QEBPlseGQX9Aw7uDW76neUCj2M1rp+N4QO6qIdY+6nVAQ27DomEugEDuhPpfOPaAQJ3L4aYgSoNA4a7HHtYchUCI3KcqC7qEQD0qFn9d72pAtJkspjDPcUDc1dW91KxxQJkNK7N\\u002fmnVA2V9ylbnAb0A3E2OvzGlxQCzmSOSkMXBAg5S198N8bUBO3gzyyxt5QH\\u002fwekGMwXdASsVlZHBscUBzw+\\u002fV3YB7QHlnoh9NOnFAgfo7fKC\\u002fc0DgpOg0jQN1QHCunvi3gIFA6nktHVmmhkDd\\u002fWbnm6WEQCbuEPgnEnlAcmjLKEzVf0CS5cmtKeh1QL5eOb7O0HZAUr3ExVwodUCwLp4GM\\u002f9yQFD9pZzgGnNA4bzO4as2c0CvDoveudl1QA4TWHaPM3VAkA0VJACdc0BoOBhneiJ1QP\\u002fpCUPyr3RATCtfHYwcdEAp0aaGjdZuQLEQTcEinX5A5gbEXlHQeEBDvwi8dr9wQBVijukbMXpAIvO6aDTldEAAAAAAAAAAAO\\u002f6eqbXwlJAu\\u002f6\\u002fpQ\\u002fUV0BlLLB11cNXQAcAkXnoFVtAnm43p8OJV0BsYzg30wtXQKyS98\\u002fBSltAVPCLwTntXECBX10pUAFlQMuih6Bp8GJA57UswVf3YkCbC0NsMWxcQALw3CWDbmNA1XO8HPvDXEA0XlMdjcRcQOL3rGezyVlAHQNjJtWKc0BC1y9ISbJ3QBcrFO2\\u002fQnVABxq+cn6FdEC0lwO+kjh2QFkrMSrkRXRANSx9uef2eEAOpS2kOq9zQFXZQdjq8nRAlXsoSN\\u002f7dEB5CkOg7u50QMgGKOBKcndARlBTOydubkDwz1\\u002fa8w1xQED31VjjZHFACscws71obECURwUdlLNvQKFl0vS9ynFA0w64istQdUA7uCnPxHVvQL6hvTKio19Aw3xRKlyZYEDRVR6TK3VgQP7WLC7htGFAXyDmdL27YEDHrHbBPrJgQCJwNpMIWXpAr\\u002fA94L58ekDzTHzIN\\u002fR5QKqaIbhthnpAp5P5UYPSgECFavrwf8d+QASmLsd7EoBAGVgVAMz7eUAMZn4byAF5QDGDx3KXfnpA7519CKi6eEDMu52KsSx7QPMTtKDo7n1A+suxDB4EgUBNNMkK\\u002f\\u002fp8QByiEhvkgHtA1XsdN0F8eUC1P+MUfoSDQBFR01l+qoNA\\u002f9RVNL\\u002f\\u002fhkAU1ydNwLyIQD4HzULRaohAHo8+EJRic0BlDDlkLj1gQC9Lc+45nWZAXqILHK\\u002fjeEBCvQ+9WgVgQDwukqLzBmBA\\u002fcUYbD+mZkD3OgQcLdR0QIaTfymPOIBA2aafjKv4fkD2moRs+3V3QDaFHTZRgIFAR\\u002f3WE8\\u002fFeED534TPP5V7QOGtP7NlgX1AO9OO6XF9gEBXDr82JsSFQB7EEhDtBYRAUlET54tbd0B+OBxTuhh+QHCuNHO8G3VAJIbS5IK9dUCARuk1lo50QAdZAct7hnJA3AOkZCMNc0BHJum9voRyQGuDBXQ+8XRA+jlPmMRWdECPIRgaeLxyQGvezqUo+XNAU8ccM7Bzc0D\\u002fdvNIBfxyQAORLPz1b2xAc+YJGEtvfUAcgn\\u002f4LGR3QOmXkEgv5G9A+v6MprY4eUA8WAqxGL1zQO\\u002f6eqbXwlJAAAAAAAAAAAB8I5YeLy5YQNcjIZLow11AZBh24sMCYECAVRclY7FbQKGZp+rBiVlAqLEV8lIiWUCgXLkrqaNcQF0C+xqAeGZA74x9VsGpY0AMy48+cRJjQDuhSKiNEVpAwBtYY8rKYUA+HZL2vdhYQLP+KGLX41pAZBZuWULLVkAT0X\\u002fg2ydyQMkVZXO+YnZAZgjBJdIadECfAd1GygxzQM3LhJ7I9HRAtQPpNJAPc0BbTDhnCo53QKc\\u002flzNponJAAri3YK7kc0Av7I8lcfRzQIN1+UMp8nNAMXYeNaxrdkBay\\u002frMDOBrQGyG2z7ABm9AfRgv74\\u002f9b0D0+ZgjQNxpQP3X1fiKk2xA3Xt7kXI6cEAe98uBxRZ0QKizdgl4pW1ALEkNGjsgYED13pOMuTlhQCWhRHKx\\u002fWFAyrVGpCqyYUAblMMXRN1hQB8YfG3\\u002fql5AX5+DXggVeUACeeW0\\u002fht5QNuBb0XahHhApfy\\u002fATApeUCh07ALhAqAQGR8ifzDWX1Aby8o0M22fkCGdAolLYB4QCNsDUSSr3dAxnPp8s\\u002f1eEBjePYDBXh3QCetK8Xsm3lAbcyF0y17fECcbBpMi0iAQLS5MAYDJXtAfjWbQk22eUDAzME2Ssx3QKtxg8HOs4JABru5dUXngkDib0NwPDeGQInysYOY5YdAHjVWebyVh0C8Wk5hjDlyQLUJJ15cxV1AUxz6sO2zY0DkNcj5CY13QKxwS\\u002f7QEF9AdlAExnTKXUBCQfSgOw1lQNGzIKbvanNAnnib\\u002fxH6fkDmfZnOant9QDcvRl3+DHZAgGHBBuaxgEBiWf+j1ix3QANMqB8g8nlAnRs7O9vFe0D+5qlzoICAQNwGc3NvyIVANKIVNHIJhEBS0c9RYbx2QGReu295131Atr3A7\\u002fAKdUASIngcC3Z1QO+2vVmjSnRAFFnCsbMSc0D1XmmzWxFzQIiBbIPNxXJA5mftm7audEDOB+DZqkJ0QIWIPuZL03JAKz4wr9eLckALv0LMKxByQDmxtjNp\\u002fHFA\\u002f9YnhbDLaUDyUCXfUuF8QEW9I9CH1nZAZkdmIMINbUCYkN1BHZF4QBuAJEFR9HJAu\\u002f6\\u002fpQ\\u002fUV0B8I5YeLy5YQAAAAAAAAAAATwUG2G\\u002fPXUBjWpAtqqFYQBCzYSjdJVlAqN9wYS3EWEC8VJFnXSVYQKHbg2nkRF9AwpjPmRAQZ0DSzgMhRvZjQKPExvIfk2NAB+F\\u002fYqjkXEB+vvuyURtiQDptKXN6OVZA9VNe+E+JVEBOzd4cKVJVQEQm9Szct3FAvWI6I6uVdUCRipp2nrRzQHFu9+Myk3JAd3dr1ZhpdEBhh6TxoMhyQAab0u5tRXdAMN1wanZtckDHbmsmwJFzQEXiWpr0ynNAo4NzWxKnc0CGYITnTk52QOE55V\\u002fAZmlAbmiHxus+bUB\\u002fjSfUYgZuQEGHeS5Yp2dABr0ON8AFa0DlOe6W\\u002fIFuQC85FGprA3NAPbx57RJIa0DBsauYRGBdQOFhvpqCb19AiQlS93+UYEBpcnKG2f1gQOhVdFm4g15ACw31xcV6WEAEK9ONdnd4QHh\\u002fRUazinhANieNVxoZeED1p7WRy7p4QEQ1F7l3039AZd96qHDYfEAMIQAu43R9QHAAA+C4v3dAokUH1n0Ed0Abw2Jy94R4QMKNUuLqPXdA\\u002f54YN74WeUBtUqWznzp8QHXD7xe3l39AJ7mfLMDLekAtGp6rI5R5QCPcKuLdvXdAZ95EIuWzgkCWIaNwy+mCQIZnUwYBWIZAhG0q5KgfiECm0gxzmaaHQCVuhW+sx3FAo4JaHgRHXUBKVaeaWgplQLVVaVTHZ3ZApSYVH\\u002ftmW0CbwTlyh\\u002f1cQMT3+hLBYWVAukb0pcCSckCN08D4bpd+QM9pv632QH1AiW9QL0SCdUCh7ZUaja2AQAnxkFUIf3ZAxtgCr54JeUDRl2V58yp7QJ8yMlx844FAuZQgqd7yhkABwksv4heFQKXh2u2lOHpA6yTPrHpqgECz3L1T4NR2QBfjF01213dAuhD40Wj9dUB+QVr6XzlzQOawwdSrm3NAgeCcI1eKc0DT+9nuJYp2QMeISPW6w3VAexGZDCM1dEDv+RVsfVt2QFWMuHnvDnZA5cEceYJKdUDdJGB1SudwQOCMo0RjaH9AcLfCv2+YeUDHSTBzz3ZyQBa+QhwfHntALHQUGjn8dUBlLLB11cNXQNcjIZLow11ATwUG2G\\u002fPXUAAAAAAAAAAANl26HZwIFpAAkhhBF1\\u002fXUDqMRCzZb5cQGdG65ovg11AEiEAujT0XkBnQeVckBdjQHjvBdapqGBAgSLnd3ZoYUANmdY\\u002fRX9eQISmbEWyFGRAWftKe\\u002fOsYUAyuVOB89FhQFTY3EdPR11Aa9OBVvcWdECcNBnQjaR4QGygkwUW+HVAhjNr04grdUA7+6n1ZSV3QIdwcjL+5nRAb7Peg2X3eUCvEBR7SyF0QB96cEu8iHVABcU8vJZvdUAf6Yr7xIF1QIC23tH0DXhAnCs1NdQacUD48Zqd5MxyQLyyYrCYPXNAWSKtsmTGb0D\\u002f6zX7qGNxQK3QI2YtLnNAFKWTrjRBd0DgqemmkMZxQFuc+VhLxGFA6cmCJGeCYkA04KQ39BljQBrgRp5PoGNAZCNYyqyiY0BQbeYaw71kQATnRM1ScXtATQl9yNJ7e0BOOTeANRp7QDOs9QysZntAO28KjXU8gUAKKuB1SU1\\u002fQEfa6o9l7oBAGrYqZILwekCMAxaqsQV6QDH9UJdnJ3tAHVSdsYKFeUCWy\\u002fFdsu17QDYmwNx0wX5AZNLO1O6ogUCuAOBfG1V+QJUYBOHapXxAsOLk5riReUATgBMgJa+DQLdpaqe6z4NA1Y5XlqNQh0CzHXkPyvyIQFtl\\u002fwMYz4hACNLu2zyEdECuo5D+zMphQL+hqab3jmlAy5sx+x1UekBIQ5i1l2pjQEfuv0fjBmNAbwBJKzqLZ0DNkRAMFWN2QFavxk+XuYBAZPN0YDsRgEA6WFjVWBF5QOeH7oiI\\u002foFAH91Lpe+weUDoHwX794l8QA+2hO4ZYH5AbZsPNQ8pgUBNqd7Q+EeGQD\\u002fzDh\\u002fRX4RA\\u002f4Lqeprdd0Dm2CEvi95+QGcXtencrHVAC2G\\u002ff21YdkB0RtULq9B0QEYmLHSjsXJAib0Vrv\\u002fPckCOSNi\\u002fdr1yQIpUAWwGo3VAiqULeRYMdUC5niH3jo5zQGFo+QygpXNAmia+P47lc0DSRtUvfc1zQKWg\\u002fkCS221AszagTEkQfkCJwBBTLx94QFlGipkSwnBA7q1VlKPFeUDnb1RY74R0QAcAkXnoFVtAZBh24sMCYEBjWpAtqqFYQNl26HZwIFpAAAAAAAAAAAB+cPr5EkNeQFU7v75dWV1ANc\\u002frsmrfW0CPmF4dpUhhQL1wX2vW4mRAtWCzgoDhYkD3jhe\\u002fItNiQB+wLXZPSl5Al1vjQ9UaY0BFVIkQTmJgQA+gJhRRo2BAOWnxlimtXUCshlHmE3lyQAw35W7GxHZApRCDQp4edEBGEowkxGtzQIYJbMugU3VA0s3F3pCBc0Ab9PZJ+2p4QD1QXbPnG3NAkEqYlOJ\\u002fdEBeqM6Y2mp0QOKIlK2NiHRAjzeql50dd0CY9xq2i7ptQD8oapdlvnBA1l663Fj2cEBX0b8H5KhsQKGLb5dhlW9A7sviNRCJcUAk88Hxjt90QN0hOMO5v25A2dEUxslpYUAaTnu2e0djQDTve1fZAWNAtCrOd970ZEBwWFe2gRxiQKDoxSd0m2FA80g2FJCueUA5y5UL3a15QH8vc11QeXlAQvVp32\\u002fIeUCutLUkskqAQHk1M\\u002f7P+X1A+zi54el5f0BMR6I8Bs14QKYfhnLjD3hA935VEgNNeUBitomKNcp3QAMwUc7v6XlADCBd0DzhfEAULK5KadOAQGJfju8NnnxAnWZBwwwde0CNRJDht2Z4QLeLAeUo\\u002foJAm\\u002f9k79cTg0ByezPihrWGQA32m6h9aohAdDtmXEUYiEDzGCFQwt1yQDIW5v0pEF9AXan82mHkZkDwGclE33t4QD05iX9mzmFAGIT9w6e1YUAcgxK3fJ1mQAS0gutMZXRAr8qW23Nwf0D+fpv1qlJ+QB9yawmxOndA\\u002fbKcQZMogUDKuHlXwyR4QG7a4aAToHpA\\u002f5F5+D+gfEBDcDuSjG+BQITIk9RXe4ZAvaque4ePhEDP235MXMp4QALvWsL6en9AfLviiYl2dkCOTjwAoTp3QNApRC64q3VAlSLOE2jcc0Dr2JJEy9pzQFKLj8UXGHRA9kwI5c+KdUAPzvSxOJ10QHvV7yMUBnNA1R697AZmdUDEh+fNkfF0QE5l0APbinRACCPr2kC5bUAnzhoWgDd+QD4uj4uSWXhAEycvrqOTcEDeRhaOihV6QCTYgrXfoHRAnm43p8OJV0CAVRclY7FbQBCzYSjdJVlAAkhhBF1\\u002fXUB+cPr5EkNeQAAAAAAAAAAA8WoZB18eS0BwLIkXspVZQLyYgNVl+VNAJVmxlv9xZkCTYy2ybbRkQGWZyJKBamRA3RJhqyQ+X0D0NVaUFItkQC+2j5+dSlxAf4VU09XBW0CjQCbk3T5bQJuaPgTPpXNAkacbp7epd0ALewRXJo51QBb4D7COg3RAUDn15OdudkC99IkAumB0QK1juS9eAHlATQTY9VWoc0AwNlnbUe90QFBSndB3\\u002f3RAyXQ5rNzSdECKpY2eAFF3QFnMfXCJBW5A\\u002fcPh4DXvcEBwFCyYETRxQD0Ypz60gGtAq27HeaAbb0DciPjMU2ZxQKzlPe8a4HRAmbwgF8qUbkA+DYOrBdVdQNAUWxagCF5Ahph9NAsEX0B6Lr3+ms9fQN+7WZBri19AADfBRQurXkB1bXowve96QJCXT0Ja\\u002fnpAzuH+PNakekBNjPHiaR57QGDuazOdCoFA8wPEXoxif0Dch1hCnwiAQFn6yP0cRXpAwRHMz1BTeUCEKNngLNp6QOinUdNVG3lA\\u002fCsJG2KGe0DxtAiLxyZ+QNsmWOQq\\u002fIBAp7v6Zg2QfED2Lyorax17QKTVKdWd+XhA8UtIFFMwg0ClJLFD8FeDQCcVp6ouqYZA1ALKyABjiECYohc6yRSIQGnauS7diHNAGKvCEKlZYEDxTultCRJmQNk81HkV4HhAWmN0lL0aX0CFNvbyR75gQO5xhn8wA2hA9Ld0RTG8dEA81ifymjOAQCmzOAmRYX9At2FTHNXAd0BY3ZLEOaeBQGSK7salYnhAU0fyJ8Ike0BikcQwRUR9QLzGplYke4FA52\\u002fVYb+6hkAhfUPn68qEQFq8dMhFUXhA51ykGTmff0CvICMAqCF1QC\\u002faoHcnzXVAxabRM0dNdEAV5\\u002f7tWSZyQAMznQvvZXJAHtN7BSNsckCmCFm5V1B0QKBrKYgqSXNAuXJdYwC2cUAAIpeT2390QHjEjbKpFnRAIFLSd4OTc0BPk0eS\\u002f99uQF5qsYUP435Af9OM7Gj4eEA7rSflGxJxQNaX30nLnnpAfikE7BEvdUBsYzg30wtXQKGZp+rBiVlAqN9wYS3EWEDqMRCzZb5cQFU7v75dWV1A8WoZB18eS0AAAAAAAAAAABt9cZbyTVRAWZX226qWUkAjg+dbpNZkQK+jXd6TiWNAhJJM+sgLY0BoOHNc4JxbQN9n7nYMnmJAXD9yPc0+W0C0rhS0QhpdQBr5Irbs21lAqsBDo3mEc0DBH3d3wI93QNEoz55XRXVAhe6o+484dECGVNUFbUJ2QAxI6YKoQ3RAIN\\u002f3M9oMeUChKPA3YqlzQCDYkHyCAXVAQ9y3nqkEdUAEcFZDefl0QNPfGYcOkndAUq+N4Yc7bkBML33SbARxQOhuF5UnY3FAIQCE29EubEDF91qabZBvQHrF7AEiqHFAqF4V8qFBdUBUIkC4ektvQGV2hYEUkF1AJCiXOVX8XUAjyF4IoD9gQF8CYxu4yV9AfYNz68jOX0DvL\\u002fQ4fZ1fQFub4K75mnpAb\\u002fiSxffMekCt33YGlFV6QFkVVDBc1XpAPt7kpjjBgEDwBmCec95+QPB4wSW7BYBAXMZkjF7seUAcDLG\\u002fwg15QMkgAU4zoXpAwq7MIbDyeECgAE62mkl7QESlCqI\\u002fFX5ADTahz7fLgEA8FdXqvXt8QMTEvkkSDXtAu1tIDm\\u002fyeEB+xqWOhkWDQDA6zNFXaINA\\u002fAx1c\\u002f3GhkAot4C1Q3uIQHz9bz68J4hAGsKGL9gGdEB2YxlH1mVgQMgXM6bHT2ZAfMyQzwIKeUCr9pyTGyJhQKE4vvCMaGFA6DBWFW6raEA2n\\u002fLI6h91QFMtUMqzXIBAZeUaQyPAf0D169g0aDN4QA2Xk3dV1IFA5ZizOJnXeECVYWx8L3h7QCYRgCmFhX1A8J5lWeLtgECQQ8+JhUWGQLK44xM5uoRADnB8wuhOd0AxCzdDba5+QPSu\\u002f6NGGXRA8HDHRP26dEAjyA3kQmJzQPpdkMpZCHFAcm04eHrncUAgfLoBa\\u002fxwQG5NN\\u002fF3PHNAvEluiM2dckCuavbt+wFxQNnJNx2mQ3NAA4EbHPcKc0CamFoDTqtyQFso2DNPam5ATSby3YWxfkBYKapnFoR4QKLRvKe+wnBATgifAn4sekANOk1oi7p0QKyS98\\u002fBSltAqLEV8lIiWUC8VJFnXSVYQGdG65ovg11ANc\\u002frsmrfW0BwLIkXspVZQBt9cZbyTVRAAAAAAAAAAAANvNUDTxhWQJA3ENgpEGRAZ3XDym4VYkDmgx4XKFhgQAVAJJMgAVhAD1d7E7a6X0B3cef87NFZQHLTXHIPmVxAjtpQvVjVVkDGZgdahNFyQJ5vCeCHj3ZAC3iHqIyWdECCfKIf22RzQGwfJRmuhnVAwABIjMjNc0CLD58qWYB4QNcsGJAER3NAfytnBXmKdEC9Bx6wyp90QMXm1Mssr3RA1yYFeG1ld0Asm2jl75FtQE+xr5\\u002f9gnBA03AM26YJcUDvNLaDydRrQKc7Jcvry25A7ysD+LQKcUBcSLb+gB51QDnkoa5Ahm9A3KRPLVwMYEDOJvBEaU1hQC5RFv4S8mJAF2mVv9VaYkC71\\u002fmGed9hQK8j\\u002f0ZwPGBAP\\u002fvnC0SdeUChLK49Erl5QMbCrvHQPHlAuE953WLieUAO4KCAOiGAQDnuRN+ann1A\\u002fGYKcisqf0BmbzLxMep4QEQApcZ6OXhA9iaeA0WreUC5pW6zkFF4QCi5qmeRLnpAm6NxZRomfUCvjkiUxiaAQO9bMkZ4ZHtANtyU7bUJekBpH9FuRzZ4QGBlkptj7YJAqh3+A\\u002f0Pg0Ds93M7lJGGQCNoq2qdNohAA2qQQozVh0BheL50QotzQPx+kt7ZQ2BAhQweSGLmZUDKfxs0BCF4QIR8aIKEXmJAN01kO3uQYUAGo7spV9dmQC\\u002fORujhR3RAGwO6aL\\u002fBf0D\\u002fCSJfUJp+QOCC0WrcJndAfJDvTl5DgUC10CqqWQh4QDVlIe4VenpAiP\\u002fwu811fECMD2o0+EmBQFYlxVKPfoZAV8jSQVzwhEA2uycSTVh4QCB\\u002feYWWcH9Ag+9m8Q4SdUC4wCbzH+p1QO4Ln0zJbnRAPnICJnn3cUAxkyxF5pxyQKtSxG2rRHJAAezSiW6fc0Der7x\\u002fh8hyQDybJVnwNHFAnxYKfXLxdECYwPxKgIR0QOAasDbi5XNADtYYZ7kUcEBu1acgFwR\\u002fQM7RqYHOGXlAD3wnSjSpcUBPpFlgH896QBxI9y3zb3VAVPCLwTntXECgXLkrqaNcQKHbg2nkRF9AEiEAujT0XkCPmF4dpUhhQLyYgNVl+VNAWZX226qWUkANvNUDTxhWQAAAAAAAAAAA\\u002faNOL5ywZUDfabND4ONjQF5ZQIUdFmNAxOwKqXdvXkBdLBb+\\u002f\\u002fpjQJdpLlfSC2BAiJNh962RYEB6CJm7FUxcQFQ63geu1HNAzK3UvWvEd0CTyO0WtK51QAoQBOydo3RATXCGHX2VdkDu90qkJKl0QCdZXPa5SHlA9V8CF9P6c0Dp8NKONi91QFsWfGF8N3VAzNZmX\\u002fYrdUC+DkvaCtF3QGEICvdbxG9A5BlbhiWjcUAdHq6\\u002fZf9xQEhlNI0IWm1AenJmH2s\\u002fcEAmVAuDMNVxQNT3yfDwrnVAd3aDmzxOcECT8o4JtLZhQN3okjoL+GFAklCPOrGsY0BgR+gANMdiQB13ChxZimNAQj630Y3XYkAFV2PkKdR6QMWRhR47+npAPHip6PllekCDhXGS0BV7QNAn3w+1p4BAb\\u002fSGe7e2fkB8uV5bQyOAQAyQDQnFK3pAzyRU1KReeUAeFBD6v816QBjvqOrpQHlAqam3s9JYe0Af3PvSYhN+QIsjMtqXqIBAmFVFwMwbfEBVHuR1ial6QGTO5TitrnhADUVoBkEFg0AsHpyfHDGDQMUUgiMJkoZAr3z+\\u002fdI+iEA\\u002fASCdb+yHQDxsav+aVnRA52Bw3jHmYUCdHr6J7XlmQFyXmFdgMXlAkl8gwBm5YkDTBngvNPhhQKDp23i7bmdAezElF29RdUAqrg8WS0aAQD+SVyziXn9AJ9W24IYBeEBjRTH+UZKBQINoPokar3hAxFAuY0pTe0CipDi7olZ9QEs\\u002fK1zIUoJA+M1zm1mOh0AhLLo+5fmFQNutD0lqzXpAWlCg\\u002fmQogUCq5wzPfpt0QKHM3EUMNnZAs9dggH8NdEB9hA1o6aVwQPL\\u002fi4ooXXFAbr3KJKGWcUBnlgZ44I51QJXT0Umm0HRANIpfthAQc0DN\\u002fFSwNs51QOLz3jAQlXVAT\\u002fl8fT7tdEDpQvQjqaJ0QHc9KHfjWYFAjWHhw\\u002fsMfUAsmBOxXmB2QKiVcm\\u002fZu35A6AZVVdrMeUCBX10pUAFlQF0C+xqAeGZAwpjPmRAQZ0BnQeVckBdjQL1wX2vW4mRAJVmxlv9xZkAjg+dbpNZkQJA3ENgpEGRA\\u002faNOL5ywZUAAAAAAAAAAADAx0WPKylZAqh\\u002fv0MXtW0CeWj3mhA5jQNSIwCAG1mZAcQLL2icDaEC\\u002fJFGbiLVoQObtin5LMmRAGnBuHGM\\u002fdUA4mflCHi95QOQ65iJXYnZA1JTPwLb5dUBdlnuJ7653QF5HFAQsuHVAdkOXJ6Qpe0AGLMvBQgt1QCiFeectpnZAFWe2C6xYdkAMhPDKaZh2QAe+fAMAgnlA\\u002fb3DxZkRdEDaIa4mRYh1QNk2E8Q65HVA5ECZDzlac0BmKoAnK3J0QN6x5uk\\u002fS3ZAxlpCtj8sekDNBLiFQOZ0QAeXf9mWQ2hAo1Yeh0oCaUDyUfMyXpNpQKPcH7xNlmhAD+zfvswiakA51Pl8q35sQB5aSAFo63tAuOu\\u002fiElxfECZBmUSls57QLpEBQTILXxAQKT2TqZhgUDSUiJcJex\\u002fQKnZl0hqOYFAGW0xIS9re0BbXdUTNIx6QC46jlBc9HtAjk7EqtplekC8zUojlK18QC6lFUWLWn9AjvPOULDTgUCuiDyzv6t+QNzRmh0Q7XxAl+ijY6djekDtobmZjvuDQFBEivCG8YNA3QAT0Opnh0DNmOb08fSIQPIeZxXwwYhAyn196MUPd0AfzoouP+JnQMgwyf3M8mxArOXVgb58e0BOUNW\\u002fypBqQFpERlgxbmlA7EFhg+s7bkDXvxI1I7t4QAL4nxygZIFAugCRNACzgED8niFYLQJ7QDlriL3JiYJAzFapD0q5e0BUAE0YHzt+QNfuklmKDYBA1MesIF6PgUBOWcPMCq+GQLV0THM77oRAgRytadnZeUBYPKiZEmOAQCPFbEIdY3VAOt5lYlFxdkB\\u002f\\u002f\\u002f12h510QBvvsijz8nFAjnmkg8xockBXFEB44IZyQCCv9ffji3VAM+XqIeANdUDlmiPTN2ZzQCtrN8iAS3VAm4hb24gYdUBZfcfZL5d0QBlWect2j3JAG2Y\\u002fmz08gEBjl8GSHvF6QHfIYNRWOXRA\\u002fzLTbayVfECUWlx2r4p3QMuih6Bp8GJA74x9VsGpY0DSzgMhRvZjQHjvBdapqGBAtWCzgoDhYkCTYy2ybbRkQK+jXd6TiWNAZ3XDym4VYkDfabND4ONjQDAx0WPKylZAAAAAAAAAAABlWsJtQrRQQEeEdlSYXWFA3Xb+HvsrZUAivVQuzwdmQC549iivTmVAIDt0KsZ\\u002fYEC8L6UjFM1zQGbAMiTa+ndASMXBwMIydUBiaS52u5F0QMfSiXcPW3ZAHukUA7RzdEBmbyIa5mx5QPw+1m\\u002fNAnRAQ\\u002feISIF5dUDzQ2c62UZ1QFFt8XTUhnVAFYdjGy04eECm3rp9TTJyQBm9XYwlr3NA8xAwxpgCdEC5UF0IWHhxQGfJAqp5qnJAWUP0Eg1ddEBTIVM79kh4QHk0YsQ1G3NAMnBJ4TgjZkC\\u002fqQ7Fk7xnQCKJEg7zwGhA2MmDWy8LaED29m6BbIVoQJjt\\u002fB3bhGlAZD+Se+NvekClhAb\\u002fCr96QOfYrKQPRHpANEjrVuGOekCVOPAcwpGAQCNbhjHlOX5AfyfseXR5gEAZPXySkd55QIqKtSPFAXlADxSTgks2ekDvfE5yFMZ4QJyLhL6Oy3pA9gghD0WffUB2EK+5g1yBQKDsgQ13i31AxFzDGArEe0D+2nYTGAB5QApx2+5yWINAVlgDXdlfg0Ba5UuTxMqGQHE6vMCwYIhACp6hxzAwiEBrvJwQ\\u002fr90QAPvrM\\u002fPTWRA\\u002f4HEDKJFakBZuKlG4gd6QDJOsm5sEWdAjtFRk1PSZUAWSAHnR2ZpQOdyIe7\\u002fbXZAQNeuVRtOgECS47eHqTl\\u002fQDJF2u5Bz3hA3gK+OdZ7gUApMuV20XR5QPil8GFAD3xAhG4mp3bbfUDR+6oNqUuBQAbZFkzEa4ZAchTT02fNhECHJZpedn55QPZgPN57E4BAntyRqsA6dUBLOSNZxDR2QBnyQc9qf3RA0pc5W5\\u002fmcUAW5zmlxoNyQADQRg30J3JAlriYIL4xdUCt3bLnnsJ0QPFll\\u002fU1BnNAbEy5WjHBdED9f4Eofb50QNmWP6UJWnRAU+T+fwPhcUBdckuIEv5\\u002fQESW4vbWWHpA8aA0whiac0BizPkI\\u002ffB7QLpwllej3nZA57UswVf3YkAMy48+cRJjQKPExvIfk2NAgSLnd3ZoYUD3jhe\\u002fItNiQGWZyJKBamRAhJJM+sgLY0Dmgx4XKFhgQF5ZQIUdFmNAqh\\u002fv0MXtW0BlWsJtQrRQQAAAAAAAAAAAq3sUNGK4YEAHnxnFhjRkQNxyLMUI3mRAWpq8q6V3ZEA8DT7ysvxfQL+c28qTeHNA0s2QEWGLd0CUvDH6vfB0QN2pBkKAS3RAztS\\u002f\\u002fkAddkB8PTXmKVR0QDmJgTOXJXlA9lEbXyUpdEBnIPxqZ491QP8fnvpObHVAFBlnsL+3dUARXRamFEt4QAviDUs5pXFAQzq47KAtc0A45En6T2xzQATkNh7F8XBAfesxQPstckBMU4UzBtRzQC9um0PstXdAOZGSka6GckDJFJY4QrllQN+XLBaNk2dAfTvibMX\\u002faEDYgbP5z3hoQOYdZ6XOKWhAsS0EHgV\\u002faEDM3oRfnRd6QI7QCEk4V3pAZWzL6zvReUD9Wnq9dzF6QA001FDTPIBAYz2Ar7irfUA\\u002fkoO1yDKAQC1Y2+3Md3lAZuTxoqSkeECI6lnqeM55QJWAKxSPWXhABOXfyo9LekDSrLYUmiJ9QGuB67+ZM4FA3irNDrMAfUCD\\u002fWN\\u002fIUh7QB+wxap8xnhAMytml1Y9g0BzXPMQDziDQNiI7tW3oYZAIQf754U5iECGKGDnEvuHQHhsBCR6H3RAJqcnDjISZECGNUWh7ZBpQALcerevbHlAjYGf+VS6ZkCVwAu3i5VlQOOqBAzMKGhAEnz5GEaqdUAXTMta0\\u002fd\\u002fQNfl3hkJw35AKPCmqWkyeEBGRx4fH0KBQE0iidhlyXhA6NN5OGBXe0DTC4LMsBl9QHGcmmCskYBA54dweC7xhUAG\\u002f7Ftg1GEQG\\u002ftcj5SJHdAGOMsxhwLfkBOUNd0F1t1QEpCrLFX\\u002fnVA2IPYQBu1dEC0lLHYCShyQO3nhgPbD3NACHF2dU5WckDi70fP5yR1QDxHxlf2fnRABuaEw2rZckBcOqYvMwZ0QI6tn\\u002ffN3nNAomgQ7Aqbc0BiP\\u002fjgf\\u002ftsQGvht1NNaH1AwGlXWt1Gd0Bpvzz8qaBwQCMe0wGibXlAr4LTKr0LdECbC0NsMWxcQDuhSKiNEVpAB+F\\u002fYqjkXEANmdY\\u002fRX9eQB+wLXZPSl5A3RJhqyQ+X0BoOHNc4JxbQAVAJJMgAVhAxOwKqXdvXkCeWj3mhA5jQEeEdlSYXWFAq3sUNGK4YEAAAAAAAAAAAGB8lSXkxFlA9b9YdzzQWUB197fzAexcQL+oIE779VVAQA8IDQHtcUCX3gIaIx12QMHvsZSStnNACLFwDLazckAilpyyR7h0QImWLu+r2nJA2jjRnlOnd0BDJp72qVxyQOVDg4SFunNAN1nUf9u8c0C2v6EHLNtzQG3pFUWJanZAe7ZEuPuXbEBi6J9CksRvQKRxu+6FfXBAWwGwP72Za0AHScRikYFuQKadFYbmCXFAf772PHC\\u002fdEC\\u002f3JbC4qZuQAkYUhyl7V1Au340yK7MYEAAZ+ABmDNhQNdnHIT2D2JARgZCSHHOYEANdTpX8+9fQCOcjQk7T3lAnlik\\u002f6pQeUChaGwqSeF4QFMUJveLW3lA46nNNJzUf0Cv3+3DdiV9QIfNPgQtAX9AsVD9kIp\\u002feEAnjRHdv3d3QF2knXdA6XhARmTmlFRyd0BxoTMTq3Z5QHWz6t+rVnxAzi8afSRSgEDbQgT5WCl7QFp5YsN6o3lAXjEpHwxsd0Bz\\u002fGyjGJeCQLGomvMwuIJA5jkzWpA5hkCW\\u002flwI99eHQPmf9pgWiYdAF\\u002f1nVICHckDJdYa8KnJeQHzxAKAoQ2VAoy\\u002fndg7Md0BnUHl+PGtgQFnDbob\\u002fKWBAenwS1y78ZEAWhcwctCB0QCXJNlOQeH9AdWAqXYc5fkBwp4nFkw13QAw3wLWSEoFA9qXThieFd0BhFjKPXEp6QPgxaa9zK3xAfrRLNKT7gEDEYY9oXUOGQJxWpBlQroRAByeihJbUd0AgwB7zmi5\\u002fQJVBXNh2jnVAQnapp40IdkCSUNPTzOx0QCpV+nUDr3JAcsKjGwDmc0CUwHZIGtNyQK7EZtlcaXVAukuRJAfgdEAOj1VLYGhzQIiLOHeNXXRA728ItdMndECb1V4OHOdzQDaHQG1BC3BAyHTgBIzVfkBOMz+F+9F4QNgRq4\\u002f8qHFAVTcdQNjoekBpPRjrnI51QALw3CWDbmNAwBtYY8rKYUB+vvuyURtiQISmbEWyFGRAl1vjQ9UaY0D0NVaUFItkQN9n7nYMnmJAD1d7E7a6X0BdLBb+\\u002f\\u002fpjQNSIwCAG1mZA3Xb+HvsrZUAHnxnFhjRkQGB8lSXkxFlAAAAAAAAAAABou6N63FdhQNX+OT+8s2JAgfPvnZJpXkBKMa97tAdzQMeE1qpoYHZA4YCiyguHdEDcxzXsxJZzQFyereQHh3VADbgsNWAidEDTpzueWb54QBOqWUJzs3NAGJ\\u002fk2Im0dEA4vOCx6ct0QH2WE0B0IHVAecVIzeSdd0AT2UEc6itwQH4I5LypknFAU5psW2AXckDfaA7lPilvQBLcLDM2zXBAUC22JIc3ckBH2x4nyPl1QGiijlEaCXFA\\u002fc6cJJwHZEB721+4IjlmQEZ032dYEGdAdCKdQbk4Z0CZq2SFlTRmQLXxuK5v7mNAB\\u002ffLDnedeUBoIXsabaZ5QNBgjXD2RnlA8zvHlTS\\u002feUCgrkWfd4d\\u002fQGuRxNySHX1AkQ4zHzT5fkDr+kaCjrp4QPJj4Pt5+HdAMEDhUuaGeUA0Nol0jCt4QFFnoTgW9XlA854s1krHfEAvnYIOuAmAQA+0VUrcHHtA8K9NNmLGeUCbZir9pWp4QL7zUAWQxoJAi0amkUfqgkD46BslgmiGQOpo9rTg9YdA76a+TXuUh0DABfLGl+lzQAdNcHvVqWRAZWvUxThDaUCXlRJXrW14QPjTh6Qx\\u002f2VA91NZ7omgZUA9iXmSFq9pQGuFgDYWNXVA1aUgW8D9f0Cc68uxa\\u002fp+QHSpUhClHXhATT2KxFhrgUBc5QBA1YV4QPWRRg7E7HpA\\u002fP7oEJLkfEBnmPwLEW2AQMNsz+yg5YVA3VFFMhlAhECMfdfP09J2QI\\u002fRyFeY2H1AmZWfoGPfdUBHadFN8jZ2QMqCK4+XRXVAsvFBVx5vc0DcQmRRQE10QHX5OuODanNAXPVZS4N7dUAXvGcUkvx0QHAEv6JeXnNAOb92jgzuc0D8Mey26IVzQHVa3xAmYXNAf0i5cjDEaUC74NndBwt9QAbpSXaAl3ZAHr+oayq\\u002fbEBuPJCoazt4QAZx4ggQmHJA1XO8HPvDXEA+HZL2vdhYQDptKXN6OVZAWftKe\\u002fOsYUBFVIkQTmJgQC+2j5+dSlxAXD9yPc0+W0B3cef87NFZQJdpLlfSC2BAcQLL2icDaEAivVQuzwdmQNxyLMUI3mRA9b9YdzzQWUBou6N63FdhQAAAAAAAAAAAjiH3qUz2VED+k\\u002fR1v8VWQNyPG4wSpnJA+2GT0NeIdkCDEj6C\\u002fqR0QBKtCAyUc3NAKu96C\\u002fhrdUBELc5C1Z5zQDuy6sQI8XdArHPg\\u002fN6Nc0D2Skxt47B0QIBc55gP4nRAnt0lJt7KdEAMVSEb71h3QD4da9NirGlAxnbrNFcTbUBuAchdF4NuQElyC\\u002fvYZ2hAXVgCyjbQa0D8922Ut7ZvQIZMH6A7MXNAF5wahSB\\u002fa0A6e7skVrRaQLziigelH15ABlefogwaYEDVNZWli2hgQL3yw\\u002f8eN11AbWgf90IyV0AdohPou6t5QMbFM+MqmXlAGT8mtpQ3eUDIvhBmkdZ5QDj3zFbw3X9A8ncHO4E2fUASKcRqG1l+QDRXBXwOu3hAb4xvXEXyd0BYFSE55nN5QGUxIphZJ3hAXdZ9\\u002fLQTekBd\\u002fzshc\\u002fd8QLrMDplfFIBAld\\u002fdMfcDe0BJATz7G\\u002fF5QM+Wh+95J3hAhAydWjTtgkA2jSj0wR6DQEJu5JQKeoZAmhXRxSQgiECOXHQoHr2HQKFqwyrBO3JAXfcvQDIKYECd+Snpi05lQJhLlw5z8HZAkGchuGfpXkBGdQ3Y3N5fQF\\u002ffJMtkZ2ZAM8BavW12c0Bz+IzclMZ\\u002fQIXJZUmnKX5A2+FKBSc2dkDiXSI4XCKBQJ1kabovFndAZYTOqzbKeUB18mFUedx7QEbEB5WTI4BAwrMNduSFhUCNZA703yGEQAX32cXfvHZA8026Kol3fUAOLh\\u002fHHFZ2QHRHqQCFjHZAf6gxTOuqdUA55iE+4pJ0QOhut2JPwnRAd\\u002fOL\\u002f9RHdEAsX4fvpsF1QI0lTJFqcnVApfQZf+7Ac0AIUlpUV8JzQKneOoCkVXNAEOYltghQc0C3LbrLRPNnQL8jVX8FVXxAJh8+ayXhdUDzDN9INEtrQId8mwDjrndA8SRuEqXccUA0XlMdjcRcQLP+KGLX41pA9VNe+E+JVEAyuVOB89FhQA+gJhRRo2BAf4VU09XBW0C0rhS0QhpdQHLTXHIPmVxAiJNh962RYEC\\u002fJFGbiLVoQC549iivTmVAWpq8q6V3ZEB197fzAexcQNX+OT+8s2JAjiH3qUz2VEAAAAAAAAAAAMm\\u002fWi5FrVFA87qF+ahJckCec5V7Nwt2QBjWxf98YnRA6civ2+Qbc0DAYRboIAl1QBAQenQbaXNAG0UykNJfd0Cy3U3dngFzQKJyDlaqJXRAJCAet2JqdEBpDHlLICl0QGJ8FOJxrXZAuEn8UwxIZ0BZC8hYxwprQJ+sSlbKLGxAUif7ncoZZkB+kB2\\u002fMzJqQAFpzqcNaG1A\\u002fzdjc883ckBXD0KP2q5pQG2g6SzNVV1AmaENFfMuYEAd9HKR32lgQHYjEp+\\u002fhGFAswuyTp7sXEA1P22E7t9XQOygasSOAHlA+DvHDrHreEBbxPKb3o14QPJhlV1QOnlAik5lN4TUf0Ax3UL12+p8QGTC6X2TqH1AiKF9V\\u002f57eEAcW8mIoqZ3QKdk6HBPHXlAtsOIDZjod0Ahg2J9mbF5QKeCbH3on3xAcg9AcrTqf0A6YzbXQdh6QETZpQ\\u002fPxHlArm7DT4Tod0DOs3bQqsKCQA4y\\u002fmiyAINAZgAhMeA1hkAhUhX9Y\\u002fKHQLOq9gTsgodAZ0H+ERsycUAfvEFgyRpgQHCgpAcpAmVA0XgNZHdGdkDGbo0lPoxZQHg9VcbJmltA\\u002for6\\u002fyXSY0BayzoFpN1xQKDI3hJweX5AsC\\u002fEh2GjfEC2eB+xL5l0QMUghwBTZIBAb+zSpJbXdUChY5C++ZF4QAyfyiqTqnpA5lWDBYBFgEDz0mXvHaOFQLOpBcGDKIRAoZoltPDjdkA7POoQj+l9QNNVFRyXFHVA8mHfr02WdUDjMuqP+Fl0QH3s2944pXJAurieO0src0AfPbaXyqNyQKIdtj+NmXRA39GrobcpdEC1UjUk2W5yQPRzyrOCiXNApCtVpGMcc0CcI9MSiMNyQFU1TnLVK2tAI6ulLFA8fUD7cw4+8O52QKySVSmPu25AnZrh0lvKeEBtWTRLriRzQOL3rGezyVlAZBZuWULLVkBOzd4cKVJVQFTY3EdPR11AOWnxlimtXUCjQCbk3T5bQBr5Irbs21lAjtpQvVjVVkB6CJm7FUxcQObtin5LMmRAIDt0KsZ\\u002fYEA8DT7ysvxfQL+oIE779VVAgfPvnZJpXkD+k\\u002fR1v8VWQMm\\u002fWi5FrVFAAAAAAAAAAABYbhViFBhyQNn6TZTRBnZA1boUjp38c0Cna90NieJyQLSd++3T43RAKD09xLcoc0AscwI9l4d3QMEX432XtHJA0t6BMlToc0Dv9Bx\\u002fUQd0QMfjx2xX7XNAxhh7SrybdkDAKVCL245qQLWYXXjg9G1AQfPv1U\\u002fvbkB4PwI5GBhpQP0KHXx2CmxAamxNvdVvb0DfMOdwtahzQMlupWZ\\u002fx2xAABjobQ6FXkC1XteMDhRhQHNfR65KsmFAiifbB1XrYUAJ9xMIi5hgQJWeWr2vYV1ACStUi73FeEDZOc4ksdd4QGVOyveFYHhA13IOac0AeUDovVh7XLB\\u002fQAD2ai41mnxA2ucd45pEfkBgU6vNM1N4QOMb9j2mendAHXa8D2vheEAvndcfa5F3QFCV1SoJcXlAxbZ9u85ufEBM6eM2XhSAQJFNQSAk\\u002fHpAtiWxtU23eUAkViG7xqR3QKd8hvznqIJAkDuOWXXkgkCRJ17msS+GQBOdbTCa4IdAYsACJqyKh0CXOxY\\u002fO+ZxQLTb6E8vNV1AtJDILCWVZED8xYth4wV3QGWI8BmaQl1AD\\u002feo8wuGXEBhsWGATpljQCRR+HQr63JAw39Fxr2dfkDf+RCQAQd9QPvKRd\\u002fHj3VA9Yi5FkmCgEBO27rClYJ2QCbKmpvkKXlAfDOujzUpe0Cc+w8qCDB6QPKfRXmqdYFAZwxkXquTf0BUkTLyymNyQKiZyAcMC3dA5KVgGPaQd0Bm1XJtEjJ3QMFPjm+XJXdAafd7EuX9d0Cg7+ML0jB3QI4kZnjoa3dAerQuRueOdkDeSEBI4qJ2QGoVOBzsmXVAZ9FhRqtmcECsH0KZXfxwQDfgSHBuuXFA0nI2h\\u002f5UcEBD848opLF3QLXYTHEuF3RAu2kjgrFKc0CL1TByQ+t2QD+VTyuTh3NAHQNjJtWKc0AT0X\\u002fg2ydyQEQm9Szct3FAa9OBVvcWdECshlHmE3lyQJuaPgTPpXNAqsBDo3mEc0DGZgdahNFyQFQ63geu1HNAGnBuHGM\\u002fdUC8L6UjFM1zQL+c28qTeHNAQA8IDQHtcUBKMa97tAdzQNyPG4wSpnJA87qF+ahJckBYbhViFBhyQAAAAAAAAAAAPgFzsmdkZUAJXyYn2I5aQC8ktUgYZVhANlrjIwwkXUBK5zz+FLRWQI0UyONFT2JA1CRKpbz1ZkBFI5bhIt9mQKjz9yG6wGdAe6F7HwE2aEC8PjTlLX5rQFQtvAJIQXBARfRKu5GfcEDb\\u002fUwDFwpwQGsZBgSrvG9A3bRECyYgbkBQGPdPV89vQBsBeTgnR3NA36CCaGS9cUCv4FmjQ2J0QOhhD8DnqXRAsw193srtc0BEmjFd30t0QEhsQTLKnnNAYz9IvokockB1t6VBG0ZvQNVnYV3vKm5AZj9\\u002f6GIob0BvGQguJaBuQBtO5aoWwHlA\\u002fQmenC\\u002fNdkDFHHQq9KJ0QM+PGYBR42dArD0NaavzZkDmeRgN85xlQLKZxS70aGNAPT8qw5hGaEBk1yIaaIFuQH29RGnVeHxA0kQJj5O3dUAR2tRYK5VzQH8IGMaIbm1A+DfGrF9Fe0BC7ApvsEZ7QIeU7HjkSIFA5j532kEgg0A8QLHs+LuCQPY0vKPBBGxAZTETMvM6b0AK28oPcEJvQJO4+6rEm3NA8fbxiYILb0DbKyN+68BvQHols+qAwW5ApV7Zl7o6b0AyXnZQXBx2QCbO2du2sXZAmGnKelMjc0DiV9KRYXF5QIEo331zO3BASf5bSxXecUAsRtIvQhhzQKlB8GXngXlAeXdZ8I7agEBd7L\\u002f7SlOAQOBPHjJ\\u002f23BAFj+ZlO0AdkBKjIxMGT54QABl5tqNf3dAMtVkt0cJeEDPaEiXAmV6QHk7kMZcEXlAkhcbj9dkeUBBpMZhagV3QIkBT9KWpXdAk10W4O4gd0Bd5kjeNrlwQPFPLYYr7XBA16uNRhheckCo3HjQIiFzQH6wKGI9h3hA3mjooW6JdUAG4V5FPe50QPg\\u002f2LlrTnhA5xy+yr2GdUBC1y9ISbJ3QMkVZXO+YnZAvWI6I6uVdUCcNBnQjaR4QAw35W7GxHZAkacbp7epd0DBH3d3wI93QJ5vCeCHj3ZAzK3UvWvEd0A4mflCHi95QGbAMiTa+ndA0s2QEWGLd0CX3gIaIx12QMeE1qpoYHZA+2GT0NeIdkCec5V7Nwt2QNn6TZTRBnZAPgFzsmdkZUAAAAAAAAAAAAKJZNgWSGRAvcYrjsUVY0CEVsUcu7NgQLxxfqXlUGdAbmb8ddbmaEDgVsCPs\\u002fRvQPPHCONDfmxA6WtPuBSNb0DnkiVaj3hvQIBR3vKPZnFALAdi4+1Rc0CRp9iWfGdzQBGWIh2MYXJAiI\\u002f+HQEVc0CBaol7vEhyQHtBEtTom3FAhyPQEPMZdUAs5bsDAt50QFL\\u002fhKEmmXhAw7uq32LQeEClNT2AvlF4QJOQhNrBb3hA\\u002fM8MHWe8d0BOEx18sQh2QIzpFyQzBW1AMrBgfXvxbEBrarBnrjttQMQgIQbL2m5AjqScXO4WeEDWzYB9ea91QLmtk2vysW5A5WDw3wbVZ0DKrGdbDn5jQL4lWvuMFmlAsmdLyqnJaUBYXlAeN31pQJDChRXAKXBAiTDneMiaeEAfpdAekH5zQChAjYAgO3JAq7KhQDvXbkCs6wKzuXx5QKq\\u002fabyVNHlA3FdcGnfof0AmmXU02RSCQEmYAlZoUIFAvuknHJvwcEDGJHqd8X10QIIi8hUQnHNAvyd4yAXtckA4sRW3e9FzQL6eur0VQ3RADJVdTZBqc0DpoN+mQFBxQHMDBBbn\\u002fHVA3944hk2xdkA4vMqlvWZ0QDTgzG0sanlA97u0vZFjcUCs6zack7txQOsFUq7UOnNANYe3IzfxekAvYTR9bpeBQPa444nTvn9AQdKhFmg1ckCxeuPw2WR3QMvdEtjxandAAhIF7N\\u002f6dkA8aAfX2vp2QG7\\u002flYnxSnhAE0mFwyMld0A8aPO1Jpd3QHKH3JRCV3ZAl3CQTdJudkBmgH89jql1QINPBrJL1HBAvocJyjw0cUA69wSkXRpyQFkzvmKXi3JA\\u002fBQVppS8eEDtTJXADrd1QMBbZGpaFHVAbOxMWodReECp6Ej\\u002fmW91QBcrFO2\\u002fQnVAZgjBJdIadECRipp2nrRzQGygkwUW+HVApRCDQp4edEALewRXJo51QNEoz55XRXVAC3iHqIyWdECTyO0WtK51QOQ65iJXYnZASMXBwMIydUCUvDH6vfB0QMHvsZSStnNA4YCiyguHdECDEj6C\\u002fqR0QBjWxf98YnRA1boUjp38c0AJXyYn2I5aQAKJZNgWSGRAAAAAAAAAAACuyaU5TjRcQNkxgTRKslZALg9CoRVDW0CNDYFOMgpkQLr7qz3VGGpA\\u002fZsT9JkAaUCjmAm2ExJqQJJA0H+152pA3uOXYe3SbUDZ7Vz4L2ZyQDSJkDbSynJAqBdyggvlcUD1Ms+AK2ZyQNDJ5+Krl3FAT3DuDs0lckDzDrXGLxl1QP6Utecd7XNA\\u002fPo4yEeidkCdI2SEmtx2QOmm6w+HHHZAoQayIWl2dkAJA2R0ur11QEu8gQ\\u002f6d3RA\\u002flZBbMsDbUC8y5CmRIhsQBDLQkm9LG1A9pT06bDfbEDKyGqOct54QDTw33u0UXZAe5VIP9W\\u002fc0BjuCOTD4pmQLMh5C0d0GVAnYsPjmNAZUDyG5KFtJljQJj3erQb0WZAWhj\\u002fUzQcbUB5El5OurV7QPdofL4LbnVAoOd43xBvc0CoHyl7AnVtQIvExcqOO3pAs+D3NN\\u002fueUBtbIXug+uAQBtjCX+gzoJANumwgvJDgkC3S7TflvRuQFqtlBAqpnFAxjqx\\u002fZ2FcUBuhju6evdzQA29hTIawHFAnUuNGFXfcUB5Ycvbny1xQAyyzOrZonFAgmuqbAqidkBbpL4IPyh3QCti4fsIn3RAXmGiBVjMeUB3cudbqdBxQJ3LBmLu2HJAq19s7rwbdEAvZdZkARl5QFtPPcmYAYFA1gCdyb9Uf0BV+Ypz+rJxQItIHu\\u002ffC3ZAp+kDYYFWd0BGFVqgybZ2QAVUeP4q43ZApOJVAvMreEDpA8MMRFB3QOfI3L5uZ3dAuJmfkMEMdkCXFCw8B0F2QGMnFRR2UXVAo4USLYEycEDNl+oBJapwQLNQUCp9jXFAi674IgXGcEB+cHttP3d3QGnYrUp\\u002fBXRA53tnvR5vc0AhYlPcvbx2QL+wwY9amnNABxq+cn6FdECfAd1GygxzQHFu9+Myk3JAhjNr04grdUBGEowkxGtzQBb4D7COg3RAhe6o+484dECCfKIf22RzQAoQBOydo3RA1JTPwLb5dUBiaS52u5F0QN2pBkKAS3RACLFwDLazckDcxzXsxJZzQBKtCAyUc3NA6civ2+Qbc0Cna90NieJyQC8ktUgYZVhAvcYrjsUVY0CuyaU5TjRcQAAAAAAAAAAAZKR8CPCUXED4MWLWvnJcQGAYeRVGUWJAd\\u002f4df4y3aEDZr4bcu9BnQIDxWeeSWmlAzJij6lFQaUDqZsOLhKFsQBj9JqXkrnBA9DISe\\u002f3YcEBTrmWSwkJwQMLSVyhkmnBA1nTowGNlb0CI6AVFoDJwQABWpfuXwXNAZj\\u002fFfQmIckCKKiv6LlV1QM77dg0kpXVAEwnUOajpdEDnamz2Sjd1QHj0jKwsgHRAQc4tqJnuckCqROiABNluQNKcid6IFW5AwcEibYjxbkDnsNwk75luQPhe9nmjWXlAeriXts1pdkBVgWMGejB0QCg8qlosAmhA7IUKHINBZUAdeVT5+pBmQOHEW80jTWZAz0tkHMSuaED0sq++RtVuQIdtIQ60Y3tA2NzrhddBdUBZCjFBDzNzQLS8T+wDRm1ArPVPDILwekB5mQnZpOx6QOIFfT4144BAZukwk6K5gkAEa0c5GkGCQJtY4vHi8WxANMUoaT3EcEA7l\\u002f3+aXFwQOAJ7RiZjHNA9iUjb\\u002f+mcEAsdrqrgfdwQFAH2JtAU3BALC0XNKb2bkA39vedNXd1QHBKpCvBLHZANncu9wwCc0AT4ROiAgZ5QMIeLuMCnHBAVdBsybmicUCm84yAbBtzQEHmicm7m3pAkbKNnwV9gUD0bUNd8p9\\u002fQHXvG5PD\\u002fnFAQ7BI4CP5dkBgcx2uPPN3QDUMVtNedXdAqenUcKajd0BeQNDWclp5QGLqrebpHnhASuZml+2ZeEBDq4FORt52QAanObCgJ3dAzf6jkEePdkBfddYRC6twQKtU7fkd9HBAwU3ckPVEckBu025wmeFyQGVwfbzjV3hAUSrh7rGIdUBWKjikkfF0QO4UH5fV\\u002fndAwClg5lxLdUC0lwO+kjh2QM3LhJ7I9HRAd3dr1ZhpdEA7+6n1ZSV3QIYJbMugU3VAUDn15OdudkCGVNUFbUJ2QGwfJRmuhnVATXCGHX2VdkBdlnuJ7653QMfSiXcPW3ZAztS\\u002f\\u002fkAddkAilpyyR7h0QFyereQHh3VAKu96C\\u002fhrdUDAYRboIAl1QLSd++3T43RANlrjIwwkXUCEVsUcu7NgQNkxgTRKslZAZKR8CPCUXEAAAAAAAAAAAIYzgRZ\\u002fC1xAigXk4ufxYkCRi+c1EhxrQHf9pdlmfWlARNEw4HUfa0BIQ\\u002fygk0drQBOSTEoOYW5A3hwdGoSmckDU8S7Yv9dyQKOwI77P93FAt8GegQ6RckBz\\u002fvWcfa5xQBBtOpS54HFAu+DxitcEdUAZCE\\u002fLBDd0QEa1yxrDcHdAU70KX+mzd0Az4k1RNv12QIanFihMSHdA6pgWNnp9dkCOBkCcQSV1QOtymIRyW21AxLltcV6xbECIrr4VIyttQKTK+XJOrW1A8oNAkhgEeUDGpow\\u002fGH92QK6JNThasHFAZbX+lnInZkDpu4\\u002feEqBkQNUNR9r9j2VACAAzRdnxZEBXddzaQKBmQP+ZOiboBG5AYz\\u002fD+8azekCH52bAbPF0QCL3yvL4JHNA\\u002f6tq69dcbUDiMKa9vvJ5QBMu7N9mmnlAArmolNm6gEBbmDsI+reCQBrHgQgFCoJAtnim8p4Rb0DjpNI6pMxyQLyJPO7LfHJAnoDceopUc0Dlh4NXrG5yQJtbPICj7HJA+n69LYcgckCokXTfAV9xQM\\u002fn+2Evd3ZAr2GP\\u002fMIDd0D96QOx0pB0QF8iIE\\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\\u002fC1xAAAAAAAAAAABzl8NBaS5hQAWeToeWwGdA9SeL46I\\u002fZ0BliZ97hhNoQNqZSyVdsGdAAk3ToQK\\u002fa0BCtjc\\u002f+OZxQHZbDxBBHnJAvPrOnJqXcUATdm0Sf6BxQAG8xPjd1nBAPjQ94aG8cUCGKOH1Iux0QE2j3aTMXnNAWw6gt8Y+dUChgdZPSpB1QKx5Gu3Jn3RAVvX6MiP8dECVawPbiH50QMZWPUC2bXNAbR3wvNL2cECNDrO6xFxwQF1s2jGavXBAch7nkhqHcEA7ycYdxhN7QIEt3eD123dA2YzHd\\u002fgfdkC3B88zPyNrQLYY0r+65GlAsKIHAPKZZ0DZMrEgfotlQD+kVCqajWpA2PN2BJY+cEB9KxQnvi19QJ506+uqdnZA+oRwEU9GdECu70zblQ9tQCRjUNofsXpA4Gjhaqi7ekC9mFUqf1KBQBufBGpTL4NA\\u002fcMZZeDRgkDNaqI0OLNtQFns+FZWtXBA6uu2kQG2cEBPogFWQI50QJWHA+9QjHBANVvacwQFcUCz8xqnnYpwQAVUm7JSi3FALavMlRe0d0DF1HK4W913QM9nYaCltXRAr5lZxyduekAfdT9K1RJyQGrTmbGN+HNA\\u002fh+T8pr+dEA2yQovWIl4QOJiLplMnn9AODQophbde0CgzLNFw7F0QO5dtp4Ca3VAr5fmAFmbfEBpmWscLeB7QNSDekf7KXxAUMpTdRa9fUBj+sAP\\u002f9B8QBjxcvTz\\u002fXxAp0fcfoVRe0CrAje6GaV7QG1DZtz1unpAnY1qd889dUDqvkhMsqp1QOdHtpCwpXZAdT0la+5Mc0AC4QdawkJ1QFfGRi63fnNAF93xouqGdUAQ1wL3++V1QHALXWquJHRANSx9uef2eEBbTDhnCo53QAab0u5tRXdAb7Peg2X3eUAb9PZJ+2p4QK1juS9eAHlAIN\\u002f3M9oMeUCLD58qWYB4QCdZXPa5SHlAdkOXJ6Qpe0BmbyIa5mx5QDmJgTOXJXlA2jjRnlOnd0DTpzueWb54QDuy6sQI8XdAG0UykNJfd0AscwI9l4d3QI0UyONFT2JAbmb8ddbmaECNDYFOMgpkQGAYeRVGUWJAigXk4ufxYkBzl8NBaS5hQAAAAAAAAAAAyXqElCKGbUAQy2Oi1OxrQA54Y3YfEm1AJ588pRLca0D\\u002fYm5rHj1tQDWyCoUrjXNA2zmAJTsjc0Ca0guC1H9yQJJ260fhmXNAg2Sg2c9vckB8qZAXibhyQHGl60hmVXVAkOyZAqaDdUDYoe7rj815QDoy9QjsIXpAyXlQgucleUA9xggPy8R5QIjNXJPz3nhAHb6PHTsgd0AIQHsRgkpxQFzICR5lEHBA+AXk5CkccUBjgdlUTb1wQHougt07PHtArcOQqyPod0Cq04zziH50QPt+1AzP1WpAip8LR\\u002fD6aUB\\u002fnPZzKOxlQDSM\\u002ff566mVAi56v1c2paECtQTGVyzJtQHmk3KBxUX1A3iGUzJ+ldkA0KmhVbO10QEbFo5uA3m5Ad065cQ34eEDV8guKIHh5QGAsxDCJIIBAPyV\\u002ftvX7gUB\\u002fCZEiWauBQPze7tDezW1Au2zOylchdUCBcMFIapF0QC04Z3JzW3VA5DZKIwiRdEBamVbpzgh1QDpH3BZA0XNARwKodSTrcEDvAVFQ76x0QFFdJ0KMUnVA\\u002fxUE6rK0c0DlRk1VwlF3QIy\\u002feEimQHBALnsG0wmycUC2YGyGRfFxQOxZBPOPpHtA9ySSSVoEgkBwckS\\u002fXaOAQFJ5HwtKKHRAlZnqPcffd0C7p5KfrVV4QG4Um2VfJHhAMhBEoGf5d0DxiAlJ+Cx4QDfg1SaBdHdA0YWeZBPed0AuQn0eH2l4QGFBdxWxKXhAHnO8lqI0d0B00qrixoV0QP8QzZJNoHRA9dkaB+AmdUCggct1WONxQCsS7KA743hA\\u002fyznvCVidUA5jHnmqsp0QCfYSIEuDnhA7utiHHD3dEAOpS2kOq9zQKc\\u002flzNponJAMN1wanZtckCvEBR7SyF0QD1QXbPnG3NATQTY9VWoc0ChKPA3YqlzQNcsGJAER3NA9V8CF9P6c0AGLMvBQgt1QPw+1m\\u002fNAnRA9lEbXyUpdEBDJp72qVxyQBOqWUJzs3NArHPg\\u002fN6Nc0Cy3U3dngFzQMEX432XtHJA1CRKpbz1ZkDgVsCPs\\u002fRvQLr7qz3VGGpAd\\u002f4df4y3aECRi+c1EhxrQAWeToeWwGdAyXqElCKGbUAAAAAAAAAAANa\\u002fkwEmCFhA52eDniULUEBH1ZD02MBSQLMfG6S8Y1pAWzKMGFCHcUAHeH36sbRxQCSLaVblVHFA3oLc9Jr5b0BGXauG0NJtQApzWPiR7m9ANuX1RGrkdEA8fxPGbANzQIcp6p7+l3RAcZSveN5idEDxz95P8RlzQJIb9Ut1kXNAzrSZzvG1c0D9NcX0iNByQEAqmtTLOXRAsXec7F5dc0C+vc7V+eVzQJTWMxSbZXNAMuyvNJt3fUCIECAFBKd6QPGoa0vdm3lA19\\u002f15eFbckDW62JZ9wByQIWnVcu3n3FAfWlsq2iMcEDbme5JKBxyQPk9xL1h03RA74\\u002fIMQ+9fUARJY9\\u002fsIt2QAsSS4mYVHRADPJsG9zgbkDfv4nvsLN7QEov5EKpfHtARq+dGQW0gUChJZHbGJmDQLPD+o3cNINAI8eMWLrmb0D27wpPmQ9wQI9UmxfuCHBAqR2tJMHUdkCt+A0VQwRwQJSrg6xzaXBATGgyUtW4cEB5\\u002fN\\u002fr9fJxQFz25v1HyXhABgS1QlfCd0C8aE4lZi90QCBzOQUqk3pADQo4qjaOckAvUIu7hbt0QNRhT4kTzXVAXEvpOj\\u002f2ekAdRbzsYW2BQK\\u002fxto2I8X9Agf5qZxYQdEC2bLdUt6h3QLPYmvQh9HhA49gjTSC4eEDkvc3wjqx4QNNjBK0BcHlAlFpmEWZ6eEAwCD6N4gZ5QO1v5KrI1HhAjxY0xqS9eECd6ITAatJ3QIHZvb4I63RAyCbRW7DodEDVrxmlLYl1QHCK4UaPK3JAWMQvpCkveEBj3kitKw91QJWp4+ILw3RAsU\\u002fiKmLpd0BhOueCnwZ1QFXZQdjq8nRAAri3YK7kc0DHbmsmwJFzQB96cEu8iHVAkEqYlOJ\\u002fdEAwNlnbUe90QCDYkHyCAXVAfytnBXmKdEDp8NKONi91QCiFeectpnZAQ\\u002feISIF5dUBnIPxqZ491QOVDg4SFunNAGJ\\u002fk2Im0dED2Skxt47B0QKJyDlaqJXRA0t6BMlToc0BFI5bhIt9mQPPHCONDfmxA\\u002fZsT9JkAaUDZr4bcu9BnQHf9pdlmfWlA9SeL46I\\u002fZ0AQy2Oi1OxrQNa\\u002fkwEmCFhAAAAAAAAAAAAlQrCUbHJVQK9HerCb2VVAaIkcojy9WkBsr42skfJxQGwgDk3IA3JA0YD6hP1wcUCQPzOI8IJwQH5m33x+o25Af3KUQ1I5b0CTd9Y1+bR0QIB4IY+Pb3NAxJVuvGv\\u002fdUB3lZBQo9V1QKXMl9+6g3RACUTfKv0UdUCMupMqTv10QFmrjJra13NAeu\\u002fZt1NCc0BLshMDkGlyQDr+nuwS9nJAZl+ev+CVckDHkP58J718QH4ANd8n8XlAqZO4hyQzeEA3HKqjJblxQFoiB\\u002f44NXFA4J\\u002fu0DH4cEALIFZGHSFwQA5O9Qjon3FALXrES1BcdEBXlkRvMJp8QGQ9O4ee\\u002fXVAmHx545\\u002f1c0DMxfju\\u002fZduQDvnoi7VfnpAP4F5LIWvekD2I7vmJOiAQCJa1DVV8IJAHhsLHPOHgkCCTiM6mL9vQAG0W5pAb3FAOM3QE3AScUDAfyLw3VZ2QI+o2JzJDHFAM1GvTSKgcUBCqWBBP6txQFbGv2oL6XFAXQftAmDud0Dbvx\\u002fzh+J2QAyLsYbt8HNAv\\u002fhJqHKseUCcg9VN5ddxQGvecsQN+HNAFEfBGcb1dEDqbl\\u002fGa+17QGhPNOBv5IFAJUmPPU14gEAOAJBZHZ90QCyizpP5LnhAequ\\u002fCDr7eEBsKN+F2Lp4QOGGJ+9nnHhAaugvluELeUDfLfjoQkx4QECuy\\u002flPwXhAAElnrZjveEDmYpphwL54QLCIOT7\\u002f6XdA4ZfXqA5JdUDmVg6PVmt1QI+PfJu88XVAi0+le2TtckBYXBb4qih5QO6NpeS7HXZAUvb3yySydUDmc\\u002fOtf6t4QLEy5u4MyHVAlXsoSN\\u002f7dEAv7I8lcfRzQEXiWpr0ynNABcU8vJZvdUBeqM6Y2mp0QFBSndB3\\u002f3RAQ9y3nqkEdUC9Bx6wyp90QFsWfGF8N3VAFWe2C6xYdkDzQ2c62UZ1QP8fnvpObHVAN1nUf9u8c0A4vOCx6ct0QIBc55gP4nRAJCAet2JqdEDv9Bx\\u002fUQd0QKjz9yG6wGdA6WtPuBSNb0CjmAm2ExJqQIDxWeeSWmlARNEw4HUfa0BliZ97hhNoQA54Y3YfEm1A52eDniULUEAlQrCUbHJVQAAAAAAAAAAAMciXZdKuUUDBV14Wot1WQFjIu2HxsHJA8geJgVrUckDkcDT240VyQIaEgvOHInFAj5z+BmHeb0DPyV\\u002f967BwQJohiBSdoXVAxo+lSw4UdEChBOIRrvt1QPeA3RN3wnVAq1bZ75yBdEA+noVZK+h0QHdX7FbmLXVA8swLHwkodEA58CX5q+lzQEppTj8XD3NAudGeWkCzc0CebgQxWStzQLUzz2PoRX1Ae\\u002fFUKD6BekBkcp2PL2B5QKgar7RMFHJAgzO12W\\u002ffcUBBA\\u002fxZGkRxQPEpai14JHBANtbBphO9cUA8hHNdfzd0QAU+l0Qiln1A5OeLt4VCdkAhdaVIERB0QHEQUBnH4m5AQQwjjxilekDZLnKoH2V6QMS2+KYGRoFAuoVAgBkrg0ALQ3uQqL6CQOzfeHEzunBA9X1y2p5bcUCUUdYxHhFxQFcl3iOnU3dAm1ORqiBUcUCLnpbfIbxxQP8xbpWmsHFAtLMtHpujckCKcFTtNoR4QND4jsVxqndAnHLzTbm7dEAUHHNMEEV6QEUcQZ1U6nJA+45oapL4dEDY0JWG5ul1QCAVwUVnNntASbvdZkV6gUDPn\\u002fuDJxSAQPxYNCqsv3RA7WtUsvFnd0Dg2OKKxbt5QLxe3Tp0nHlAim+jMvBdeUAB05cQEth5QGoTG42GEnlA6+ncvqh6eUARLtQ7bpV5QLdjz4QVdnlAjB3dIWB2eECsWdjHXK91QEg2muqtuHVA9GsDTdM+dkBh8cvl4mhyQKcGv55e6HdAELgCVwfadEDSHUrOvvx0QDOoB\\u002fUYc3dAWXNfQwrLdEB5CkOg7u50QIN1+UMp8nNAo4NzWxKnc0Af6Yr7xIF1QOKIlK2NiHRAyXQ5rNzSdEAEcFZDefl0QMXm1Mssr3RAzNZmX\\u002fYrdUAMhPDKaZh2QFFt8XTUhnVAFBlnsL+3dUC2v6EHLNtzQH2WE0B0IHVAnt0lJt7KdEBpDHlLICl0QMfjx2xX7XNAe6F7HwE2aEDnkiVaj3hvQJJA0H+152pAzJij6lFQaUBIQ\\u002fygk0drQNqZSyVdsGdAJ588pRLca0BH1ZD02MBSQK9HerCb2VVAMciXZdKuUUAAAAAAAAAAAHbzB1Dj7lZABSPUlMAockDFwrTjdAlyQFB6TgIWnnFAXdM6fNSvcEA\\u002feJivRaluQMrodzPRMnBApdlXA6U3dUDVCYaphNZzQJ6iEVJm73VAejUlM7u+dUD0nf0DCkN0QJRe5Sto6HRAN20RfoDudEDT2NUQ6vFzQN4Z\\u002fk1MonRAM8Kk+16fc0DIF10dlyV0QJGRwkBK63NAK5DXxPAyfkAKBrdz\\u002fP56QGpbL2wPYHlAUg0t9HTVckD4\\u002fthudl9yQJilH4dh23FAq6U32OYFcUA+npYtp3NyQHYYcEHWMnVAzZ92XBuAfUDDj0HuyKB2QDfkJ5Uwp3RA3S4Bw2vPbkC7uYuEb8d6QF4R8Bn7C3tAK5\\u002fHywVpgUAwB5iTA2SDQAkd1dMOAoNAo4CYb8\\u002fzb0BfOKHQf35xQP3jfpEyOnFAyIF6kloBd0DHEudbEQlxQEEm0ixxtXFAmG6w3LmucUASNE+VaSxyQEH1SKAbfHhAuhWfkypAd0DqnpoFByB0QBJ3TXBB43lAuegQ0lhhckC8uxHDFq10QEKnooVjinVAiD3H0y5Ve0C4x2dcDh2BQMPPNzT8+X5ADXNKvow3dkCCu9s0GMJ3QJF1DITAg3xA0AszcREUfEArgagbKg98QBbmhi2Hy3xAfN435arfe0AoDRkw7VN8QB9yjXOnG3xAjtLFRufye0DfjQ\\u002f5ngh7QMcfFuR0NHhALkJhBk1FeEDnKCD+us94QCIjtn8ExnNAVyk80tDQd0Coyb0FXHZ1QIiF9O9xhHZA+SYBApYpeEADC1fbLtV1QMgGKOBKcndAMXYeNaxrdkCGYITnTk52QIC23tH0DXhAjzeql50dd0CKpY2eAFF3QNPfGYcOkndA1yYFeG1ld0C+DkvaCtF3QAe+fAMAgnlAFYdjGy04eEARXRamFEt4QG3pFUWJanZAecVIzeSdd0AMVSEb71h3QGJ8FOJxrXZAxhh7SrybdkC8PjTlLX5rQIBR3vKPZnFA3uOXYe3SbUDqZsOLhKFsQBOSTEoOYW5AAk3ToQK\\u002fa0D\\u002fYm5rHj1tQLMfG6S8Y1pAaIkcojy9WkDBV14Wot1WQHbzB1Dj7lZAAAAAAAAAAADcvvDxiMhzQBVRT2tZhXNA+yUpSxPsckCy1ARxL1FyQJ9pUxg9xnBAFWQT2fROcUCF+tkWBRF2QAa5fADnNXVAxh9nBltmeECygPEJyjZ4QDKEDMXWn3ZAWWSIc5pzd0CzL6jcSF53QOK3vhAsHXZAqC6g04dndUDFMGUutSl0QLGI0VwjJXVAGh\\u002f5lBVadEBhU49\\u002f6OR+QCtqxeIeEnxAu3JcmslUekDnbABPxuNzQHVcaT5ojHNAFNI6ie55ckBdUkCt9J1xQJTP1QIu63JAuyMM610\\u002fdUCcKxbQQRh\\u002fQOKuV\\u002fWwpHdA5hrV6O6LdUCksHM5I89wQHpBUWjftHpAn4LAdKrRekC+y\\u002fAFyfqAQLoDwkDv44JAow4lxTWXgkAMBP2IgwNxQLB4eJK+xHNA7nQMqOdmc0BZDH9H4Fl4QBQXh4x1WXNAK5zJV7r\\u002fc0Ci++b25ftzQE6+TRfV6nJA496VyHvQd0AAAuf3QiJ3QEGUTrpv3XRAeCC8GfmEeUArME4pg4NyQLWSHb9lpnRASBQQ\\u002fMNMdUAgJ3zA\\u002fyF6QJTZPiz\\u002feoJAuiNb62VMgUCkcqbneT5yQDlff+ywt3ZA\\u002fN5gRQaheUCFNmlgpId4QPsIcoBnC3lASyAkVOpeeUDQItNWwBh5QDvKooz1bnhAGTs3I1tveEA00MUWzHt4QETqfyssKHdAetgOAmj8c0BaihYAlfZzQO2RvLa9\\u002fnRA55qDpmqdXEB9Q+lOY4N2QDIXrxGOaXBA0pMwrxYkZEDBhJrciCdyQKA7VpVTXmlARlBTOydubkBay\\u002frMDOBrQOE55V\\u002fAZmlAnCs1NdQacUCY9xq2i7ptQFnMfXCJBW5AUq+N4Yc7bkAsm2jl75FtQGEICvdbxG9A\\u002fb3DxZkRdECm3rp9TTJyQAviDUs5pXFAe7ZEuPuXbEAT2UEc6itwQD4da9NirGlAuEn8UwxIZ0DAKVCL245qQFQtvAJIQXBALAdi4+1Rc0DZ7Vz4L2ZyQBj9JqXkrnBA3hwdGoSmckBCtjc\\u002f+OZxQDWyCoUrjXNAWzKMGFCHcUBsr42skfJxQFjIu2HxsHJABSPUlMAockDcvvDxiMhzQAAAAAAAAAAAXA5dqoIgUEAP3kaHxspRQDP6ZSjXd1dAgvoQiYC3XEAUJpZAFIpgQKCRzuWTZmdAyze9o\\u002fg3YUDcQ\\u002fRjLvxsQOd73CL1DW5AQlQAG0Q+a0AXSTtxU59uQIw3dnZiTmpAWXVNoRE7ZECwd7OUi7d2QP5d9DWcQnZAk\\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\\u002fSUhb0CxXEokHDplQDM3xoBMYnFAZVQ3HUDFaEDwz1\\u002fa8w1xQGyG2z7ABm9AbmiHxus+bUD48Zqd5MxyQD8oapdlvnBA\\u002fcPh4DXvcEBML33SbARxQE+xr5\\u002f9gnBA5BlbhiWjcUDaIa4mRYh1QBm9XYwlr3NAQzq47KAtc0Bi6J9CksRvQH4I5LypknFAxnbrNFcTbUBZC8hYxwprQLWYXXjg9G1ARfRKu5GfcECRp9iWfGdzQDSJkDbSynJA9DISe\\u002f3YcEDU8S7Yv9dyQHZbDxBBHnJA2zmAJTsjc0AHeH36sbRxQGwgDk3IA3JA8geJgVrUckDFwrTjdAlyQBVRT2tZhXNAXA5dqoIgUEAAAAAAAAAAAD41AwbVQUxA9ItuDHgrXUAGOSZqPJpeQEpxTP\\u002frCmFAx\\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\\u002fWHpA6pxSUdsJeUDHpvtq6895QAiZy1FDpHpAt5UY\\u002faYlekAya1mEiYt5QOxrWS4tEXlA+\\u002fMstU1SeUAVQmefdwZ4QPjwZc2GZ3RA3hcmGaxSdEAuOglcW4R1QIwmmm7UqWBAQtUMxIN1dUADQUjFWERvQD4f6Hi282VA8pTSC\\u002fGJcUCEIEJsT0ZpQED31VjjZHFAfRgv74\\u002f9b0B\\u002fjSfUYgZuQLyyYrCYPXNA1l663Fj2cEBwFCyYETRxQOhuF5UnY3FA03AM26YJcUAdHq6\\u002fZf9xQNk2E8Q65HVA8xAwxpgCdEA45En6T2xzQKRxu+6FfXBAU5psW2AXckBuAchdF4NuQJ+sSlbKLGxAQfPv1U\\u002fvbkDb\\u002fUwDFwpwQBGWIh2MYXJAqBdyggvlcUBTrmWSwkJwQKOwI77P93FAvPrOnJqXcUCa0guC1H9yQCSLaVblVHFA0YD6hP1wcUDkcDT240VyQFB6TgIWnnFA+yUpSxPsckAP3kaHxspRQD41AwbVQUxAAAAAAAAAAADIQvdRvNldQOJh+7rZsV5A8PGRF7lXYEBgVVBDoeFmQIt09kENyGNAhfAwECQOcUBJzCjs\\u002fohxQC3IfQzuE3BA\\u002f8cRAviXcUCGprj\\u002fdoFvQGlwfRRuTGlAON6dUlqBdUBkkCMLKP90QO2djHmiKnVAyQOGaDuZdUAQIXdbEtJ8QKTRLqs\\u002fp3pAkGmTUBxseEDC5lBnGGZ1QD8UPAGcXHRAaAao25dvdUCDFM+3k\\u002fd0QLcpBYTPwXVAxcMdBhaUeED95yHZ4yR9QIzgEtYwJndAMv+e6l61dkBL47qmx2t0QIv5Y9p\\u002fPYBAqVYbiYykgEAcatjhGWaDQD7C\\u002fkVyVIVABXKy9F\\u002fQhEB64MLhwnRpQBn66MAOk2tA\\u002fmF3zEjdaUCQmypGM2RyQI+TCh89n2hAoUCIotc5akCFrq\\u002fqt99sQMPuGbdChmVAcU2gygqMdkDRX3W1Gb90QPIW+LJ0DmtA6KDP7eL2eECz8Pi9lkVuQFkim9VYCXFA6r7NGhP5ckASxwBgPn56QNd6MMwJfYJAi2BH7\\u002fhngUBxSU40ELtyQGk4VshRKXdAXS7Xx0oxeUAVkTKsD2Z4QI6BmMf5m3hAiuAHsJ3OeEAwqZMDinl4QBgTBmKE83dAvqz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6mZB5qBQMYnOYbGWIBARFdze9RugEBPhRj4swh7QKZR\\u002fGHbL3pAJRsjPa2ve0BZCsmfcBh6QELnzBosRnxA9dvvA4XNfkAypQvJDu+AQPxcrAyncXxAGLTLO7gde0DoZ2c+4YR5QDjg2BRfboNAiodfN+yUg0BFivdLBvuGQGnyaUDlnIhAuxhrRL9ZiEAY0levfM90QIm\\u002fx2DuaGNA66x7jpwDZ0ADAb0DXCh5QIxah+a9qmJAJFkdCf2yYkBdmv0RmhFrQA5O8iTgxHVA9v2J6EvjgED8ioye88d\\u002fQLU7\\u002fk7bEnhAmdbBVlfhgUCFLSoPukV5QLXRbVtuI3xAvzIjBqpBfkD5\\u002fDQjWBmBQJ6wpWO\\u002fWIZAzJgublx8hEAt1QTOT5d4QK3eNBo3\\u002fX5AIN\\u002fMj9FZeEC4VVZJeMh4QAQeOhIbwndABvD10\\u002fHOdUAup7uIADd2QKYdUckY63VA0rxRvnv6d0AdOoL7rXB3QIjkROIT53VAyqeUCL76dUA1bX6\\u002fc7p1QA\\u002fQO+8vsHVAnfv7DxKvakBb0iI3iiV9QKf9Ztbo9nZAqhSNoTvxbUDEbCvib314QGL+COMG8nJAXyDmdL27YEAblMMXRN1hQOhVdFm4g15AZCNYyqyiY0BwWFe2gRxiQN+7WZBri19AfYNz68jOX0C71\\u002fmGed9hQB13ChxZimNAD+zfvswiakD29m6BbIVoQOYdZ6XOKWhARgZCSHHOYECZq2SFlTRmQL3yw\\u002f8eN11AswuyTp7sXEAJ9xMIi5hgQEhsQTLKnnNA\\u002fM8MHWe8d0AJA2R0ur11QHj0jKwsgHRA6pgWNnp9dkCVawPbiH50QIjNXJPz3nhAzrSZzvG1c0CMupMqTv10QHdX7FbmLXVAN20RfoDudECzL6jcSF53QIw3dnZiTmpAuWdAsoo3bkCGprj\\u002fdoFvQJfSpcR9AmlAkuOH+o5lbUBYg2xCJItwQD\\u002fBNPmnwXNAV13WwCnfa0DtcXIo4ZtTQPdabyiVlldAqlsQLYQ1WUA4K8K44zpdQAAAAAAAAAAAWx\\u002f8nHGhW0CQuZY\\u002f9mN7QFBJ213BL3tAfbdWq5gKe0Cxoo0gc2h7QNtJJWXHDIFAIjM2fydlf0BwRE1xjOt\\u002fQOvddjCgb3pAXBfppZNmeUBAAPJDPdF6QMgnAE3ei3lAfbIegYuIe0BjYs758VF+QIwWyA6s5IBAI\\u002f4TY9yefEDdmsfkSlZ7QHlzxWm1MHlARNq2v41bg0D56gta85qDQHS\\u002ftF0H1IZALYiYVcCGiEDuikXezjSIQGD0Kv\\u002fktnJAWNhmpxCLYkA\\u002f914XA01nQHE3F9zaO3hAELxMBVOXX0B+rGbbjsVhQAAwlgp+NWhAI\\u002fzeUMBpdEDCokhUyXqAQHe6aaZi\\u002f35AY2g4LKERd0BtsTMaGpyBQLkz5P4nFHhApGHhMVT9ekBNmk0UGC99QGHsyDaQ2H9AwWdaRmQihUCg+u67AVODQKkA+pkYcHZAHlctzrtZfEBTyVBjCA54QHCcj8mjAXhAYbmm6f9xd0CVMq6fFzB2QMan6cP2iHZAcz03npHldUAjIcSO90B3QDLo291U0HZAkeHqQFJPdUCAT8sfsZJ0QIaEneeIXnRALLOLp6WddEDsuNPF4aNjQFbToaQwzXpAnP6Eb4pvdEAHVN9q1Z9nQHTBF5YGM3ZAf17oc7FYcEDHrHbBPrJgQB8YfG3\\u002fql5ACw31xcV6WEBQbeYaw71kQKDoxSd0m2FAADfBRQurXkDvL\\u002fQ4fZ1fQK8j\\u002f0ZwPGBAQj630Y3XYkA51Pl8q35sQJjt\\u002fB3bhGlAsS0EHgV\\u002faEANdTpX8+9fQLXxuK5v7mNAbWgf90IyV0A1P22E7t9XQJWeWr2vYV1AYz9IvokockBOEx18sQh2QEu8gQ\\u002f6d3RAQc4tqJnuckCOBkCcQSV1QMZWPUC2bXNAHb6PHTsgd0D9NcX0iNByQFmrjJra13NA8swLHwkodEDT2NUQ6vFzQOK3vhAsHXZAWXVNoRE7ZEBmufEDTe9nQGlwfRRuTGlAPH3RTb97Y0DVamWX+mZnQGAfh2pzTmtAoEQHGtDCcEB+lm1v+XtmQHXsTIefTFtAL4aIz31CX0ADZ6rAab9cQH26+R1MjGFAWx\\u002f8nHGhW0AAAAAAAAAAAPDKgMSUiXlARniwfeZDeUAnFTMGOSx5QH9Qh94FiXlAbE2CldgcgEBS3ENNzd19QIwlrSAuvH1AKYl084qKeEABdaBtOLV3QJPvtnAZJHlA9LW5Zwvfd0BXZyMR3Kl5QEOvmU1+V3xAmYpIPLrsf0CIXQOk\\u002fVd6QMmoMIL4OHlABUhR7kzUd0CLrkWd14aCQBOU\\u002fYZS3YJA8WVc230LhkCjoPmsrb2HQFHu85EuXIdA\\u002f1BfXjrCcEA5ntD8fRhfQK9tI2RinWNASUO2GVpPdkComy\\u002fsvqdZQEH0n1ehDV9ApI2yWgpjZkBUZj2w4CxxQBXtY+0C131AR1SRy31afEDPO8DLIA50QMZaRHSFRYBA9nc8ZaBhdUCJnPclgxZ4QJtR5Jv9QnpArJFNA8khfEA4R4SPMjeCQL0LyW9DGYFAhc9JoIDScUB74tCVsC55QKvUktyPwHdA\\u002f3VK6JRJdkCmjjsQjoN3QEJsIWZfDntAPje4c1JYeUBJKJ1xCB96QE0NC9P9kHZAG2XPbq+kd0Ad4oc+ylx3QI9Oh55DhXJAl8cmlNBRckDHI+z+GztzQOT+ulOp33ZAz8biGv5RfECU2olNiJd5QJhz28UGvXhAG4gF\\u002f0XZe0Crp5qVpDR5QCJwNpMIWXpAX5+DXggVeUAEK9ONdnd4QATnRM1ScXtA80g2FJCueUB1bXowve96QFub4K75mnpAP\\u002fvnC0SdeUAFV2PkKdR6QB5aSAFo63tAZD+Se+NvekDM3oRfnRd6QCOcjQk7T3lAB\\u002ffLDnedeUAdohPou6t5QOygasSOAHlACStUi73FeEB1t6VBG0ZvQIzpFyQzBW1A\\u002flZBbMsDbUCqROiABNluQOtymIRyW21AbR3wvNL2cEAIQHsRgkpxQEAqmtTLOXRAeu\\u002fZt1NCc0A58CX5q+lzQN4Z\\u002fk1MonRAqC6g04dndUCwd7OUi7d2QCciv7f43HZAON6dUlqBdUA6DcKGyu92QGGQlsF8CHZAHXPRPCPQdUAEXcCtFLJ3QJALvG\\u002f4+ndA46EjPdMUfEBCMsS+uDt8QIQxDQD+UHxAUE\\u002f8IkoIfECQuZY\\u002f9mN7QPDKgMSUiXlAAAAAAAAAAACx1SUSm8ZWQAYvdluh2VRAIxmTjK5dWEDNEJfz\\u002fwRzQJfL6NsSsXBA067n34licEDqRTr3u1ZnQAqas4e74mZAjjKIW6VHaUDJNeFHqaBpQED3FinKtWlA2\\u002fcladITbUALdGHJ2Tt5QGixSul4pHRAFc8Udl2Jc0D195gm8ipzQOC85UCI13tAuLDD6BU9e0BSxUBJGTiAQIwV5aHsJYJANkzTbyo7gUDeyFpALc9zQGX2NOAqaXdA3SrBvjo5d0Cufmv9WrJ0QBtxXycDa3dAmjYS5ZUCd0DOOPV+CFF2QHnTyQcoPXRAhpomdeq+dkBkP6vSA154QCp4WBWOMndA5dSEE3XCekDOmcZ9E6JyQDiz7\\u002fjhsXFAxXmA0qbJckAsFlVCy417QLnzzo0msYFAJ0F9KmZEgECRB1ifp3dyQBwjv2EbOHhAw4LZZuyWeUCFrZ2cLUN4QP+S6wIgS3lA2XkPxel7fEASNzbxT\\u002f56QBlA2n5rfXtA3Y4IRk1NeECh9mf+9zp5QB\\u002fsyNcH4HhA540rPrEgdECPdZ6pwfhzQMsvDHj+BnVAs7CaX\\u002fwJdkByIdEthlp6QKM9DLrKzHdA5kRwv7oNeECcpQBTolN6QJGEpfpp93dAr\\u002fA94L58ekACeeW0\\u002fht5QHh\\u002fRUazinhATQl9yNJ7e0A5y5UL3a15QJCXT0Ja\\u002fnpAb\\u002fiSxffMekChLK49Erl5QMWRhR47+npAuOu\\u002fiElxfEClhAb\\u002fCr96QI7QCEk4V3pAnlik\\u002f6pQeUBoIXsabaZ5QMbFM+MqmXlA+DvHDrHreEDZOc4ksdd4QNVnYV3vKm5AMrBgfXvxbEC8y5CmRIhsQNKcid6IFW5AxLltcV6xbECNDrO6xFxwQFzICR5lEHBAsXec7F5dc0BLshMDkGlyQEppTj8XD3NAM8Kk+16fc0DFMGUutSl0QP5d9DWcQnZAIZ7DJMUxdkBkkCMLKP90QJhmTx7pXXZA18M5PrdUdUDcBskEiBt1QEApYq75G3dAPcp3jz2cd0ChdwIGIel7QG35KdLWJ3xAbXkfviUifEBZGZMKagp8QFBJ213BL3tARniwfeZDeUCx1SUSm8ZWQAAAAAAAAAAAQgbLuHcBV0B3hD9DalhUQKmf3XsgqnNAzGsaL2kBcUCkKwnOusxwQHluEOzqq2dAUEBg2uVSZ0Ao407iwKdnQBgpt8OvyWhAvflI3k1vaECSpyk4yeRrQHqHuMhKPXlA3z\\u002fLRO85dED5u\\u002ffb\\u002feVyQHn\\u002fgJL2M3JAzTlTr67LekBdCwysV3F6QHu4dzEn\\u002fn9AQDiQUPzwgUDco3CN6CGBQMVKyzl2dHJA3bhvSOI5d0B0ss83qTJ3QHVCvMeP8HRAGu+qXYUkd0BiSASwJe12QECQ+CUJzXVANFT+jFF7c0BTEtCwxBp2QFmrVHUDp3dAQs285lCddkCdvH9mnuh5QCiKWxaVFnFAJ8BpsBzIcEA3rxROB4hxQOzXA69MyXtAtTW\\u002fBUH+gUDjRuTJ5RuBQCu3pjhJxXFAi9sflxaAeEBjoKw3wd13QLFh87v\\u002fonZAMkDAKmPBd0Cjnh497gd7QGLyLjRtinlAKpbyQckDekBLmC48xKd2QJGJWmLDu3dATo8rX4lrd0BFjZQzDYdyQCj7G0YPVnJA0F542cA0c0Ds6O\\u002fGlmh2QBD8icSGTntAEiNbGXqfeEAU813xEkF4QBb7L3102HpADPrI7JpoeEDzTHzIN\\u002fR5QNuBb0XahHhANieNVxoZeEBOOTeANRp7QH8vc11QeXlAzuH+PNakekCt33YGlFV6QMbCrvHQPHlAPHip6PllekCZBmUSls57QOfYrKQPRHpAZWzL6zvReUChaGwqSeF4QNBgjXD2RnlAGT8mtpQ3eUBbxPKb3o14QGVOyveFYHhAZj9\\u002f6GIob0BrarBnrjttQBDLQkm9LG1AwcEibYjxbkCIrr4VIyttQF1s2jGavXBA+AXk5CkccUC+vc7V+eVzQDr+nuwS9nJAudGeWkCzc0DIF10dlyV0QLGI0VwjJXVAk\\u002fT2lYpjdkDuFuxOjFh2QO2djHmiKnVAWIUfSaWHdkC3YP0YQ4l1QExVl0RDWHVAuCTpaMxqd0Cxk8+xg7V3QCZfI25YqntAcyxFtETVe0DsaJb65f17QLC9nMf5rHtAfbdWq5gKe0AnFTMGOSx5QAYvdluh2VRAQgbLuHcBV0AAAAAAAAAAABPDOOM\\u002fNVhAiXIv09Fkc0Dfh\\u002fK3DtdwQMZUAeILOnBACPhFY5vsZ0A1TMDGneBnQAVXOHPqKGlAuzgNDK9iakDMwmWBZmNpQItpYtRllm1AZqnosueWeEDCDqC0kYxzQASgT4unUnJADkg7vSxZckDMhymYQOZ6QBCdhyz+snpAvXk8\\u002fuUcgEBORKrtayGCQGTIOxr2HYFAxy1FbIQSc0BSpVRDUCx3QBRyB0SJ1XZAFtfDiWXpc0BKaV2kA\\u002fF2QLspZZVgoXZAJp8RsFaddUBlpcicqcdzQGE+YESd03ZAkcGk+5MAeEA1ebvBP8V2QCEzNxPtVXpAWXxtV+XQcUAi61cAumJxQLOby3wxPHJATSU4Cp\\u002f7e0Dkr8QaxfSBQOY8MPkkhoBAhd6ScSjQckC6JPySV6d4QMK4FRdDM3lAeFUid4Xqd0A2E8884\\u002fd4QGNvsKiy9HtAjPAWHBaFekCqyLOGdSJ7QD\\u002fLBACaMXhA2bkJfLzxeEBDCQaBXp54QLJ4S1OSM3RALFWphuUkdEA9a+CDPf90QP+Ig8oNjnZAgCbvJAc2e0CS2W\\u002f+Yb14QDtz6d+gtHhAhK1PoM0Ke0BUwZR+A7V4QKqaIbhthnpApfy\\u002fATApeUD1p7WRy7p4QDOs9QysZntAQvVp32\\u002fIeUBNjPHiaR57QFkVVDBc1XpAuE953WLieUCDhXGS0BV7QLpEBQTILXxANEjrVuGOekD9Wnq9dzF6QFMUJveLW3lA8zvHlTS\\u002feUDIvhBmkdZ5QPJhlV1QOnlA13IOac0AeUBvGQguJaBuQMQgIQbL2m5A9pT06bDfbEDnsNwk75luQKTK+XJOrW1Ach7nkhqHcEBjgdlUTb1wQJTWMxSbZXNAZl+ev+CVckCebgQxWStzQJGRwkBK63NAGh\\u002f5lBVadEDcfO93IMl2QD8xod3Bx3ZAyQOGaDuZdUBL6M\\u002fmVuJ2QO9iIuwnznVApGWG0nTBdUDVoQWAptx3QCO+e4ZlJXhAyoon0HgIfEBm\\u002fAUhxzR8QF76siqUNHxACeBCgUsJfECxoo0gc2h7QH9Qh94FiXlAIxmTjK5dWEB3hD9DalhUQBPDOOM\\u002fNVhAAAAAAAAAAAC\\u002fUY8\\u002fkQt0QOghVbaGtXFA7pRjxEQJckD3vyBqm1xoQBnWaKwzhWhAvufWY\\u002f8zaECTIhL9A7VoQPKDLf86O2lAgNGCZ5jla0Dvr+s5dSN6QAzaXR6r5HRA7c7TErhoc0AoEfmYOW5yQMt71geBQntAsyqGHUPAekAPGUW+dz6AQDCajcsSK4JAuaDtPpxbgUBC+jboehRzQI1pXJMjV3dAthUFglIvd0BXtiRfGe51QAe27UReSndAEI5ZWFj6dkC+xvB+lRl2QKIfwNg44XNAKHlc92kXdkC25Z42HeV3QCOJVWGZ9HZA6LrHCu8SekDJz8lyuXBxQF7lwYRa7nBAdlRyvRbBcUDgg76LdoZ\\u002fQAmr2j7FjoNAn0jFHdkkhEAQFv8UK5p3QA0tSPTlGn9A8pZulOF\\u002ffECapxXhzCx6QKxEwEhyeXxADc7oHesWgECxoe0ijjh\\u002fQLFY8xosl39AQe3dK9KMe0CoUrfSKGt8QKoomGyF6nxAyn9w4RVueUAVJ+2eHo55QDvNGMu2onpAV2HgI4rDfUD1Mqmx+giBQLpx+mHYWH9ApRn6XkSDfkDuU6wyeSqAQM4zSMHTUn5Ap5P5UYPSgECh07ALhAqAQEQ1F7l3039AO28KjXU8gUCutLUkskqAQGDuazOdCoFAPt7kpjjBgEAO4KCAOiGAQNAn3w+1p4BAQKT2TqZhgUCVOPAcwpGAQA001FDTPIBA46nNNJzUf0CgrkWfd4d\\u002fQDj3zFbw3X9Aik5lN4TUf0DovVh7XLB\\u002fQBtO5aoWwHlAjqScXO4WeEDKyGqOct54QPhe9nmjWXlA8oNAkhgEeUA7ycYdxhN7QHougt07PHtAMuyvNJt3fUDHkP58J718QLUzz2PoRX1AK5DXxPAyfkBhU49\\u002f6OR+QDubZlBbnX1APrqNyhvefUAQIXdbEtJ8QC9q\\u002fbknQ35A6gCIWlnmfUCNecf4Cm19QEP3ZN36VH1A4T5RlR0ffkADcfq6zTKBQM1rTfH7dIFAqKA4hXfIgUAAz6mZB5qBQNtJJWXHDIFAbE2CldgcgEDNEJfz\\u002fwRzQKmf3XsgqnNAiXIv09Fkc0C\\u002fUY8\\u002fkQt0QAAAAAAAAAAASjqWFJB5Z0AOO8G9Vw13QHUGyWBQaXRAr9KJLMbKdEDAx4Uq\\u002fHp1QN1X8O+h2HZAve+h2R8adUAa4T9yuax1QGSZ+tGrPHxAff9CTxeDeUC1EuzMDst4QGZlY+7F03lAV9eeG\\u002fcngEA9hmcTm7l\\u002fQO1z5t+TFIBATDt2VeVGgUAVQug\\u002fq1KAQDfO2oyLzntAouaEsiXwfkBfChOmPZh+QGMbNgCymH1A2PxJnIAlf0DbB1jJa7F+QONHUOu\\u002fdH1ACnqS\\u002fprhfEARAX60Fi9\\u002fQGZCJfyBAoBAzjHVp6S5fkDF3V2K4DGBQO3qGuiK73tAkC65kykae0AZ26sWg7V7QCMc38jTun1A65QyIEnJgkAIexCPfhWDQE+zRm+KuHZAeLJN0PeyfUBTN07GQMl6QFGWzn95BnlA63bPnXKAekDkCKnqsAt+QP4nA7kqHH1AyOaRwdxsfUDkf5\\u002f9PEF6QMBcE8GmFXtAAoMJqIZCe0BEELNowDx4QJjW4LEG8ndAymqTdSK0eECZ91AgZGR7QPBptCzsbn9AZK+gSGyhfEBlJrFkTIB8QB69KXiAH35AKXfCxcj8e0CFavrwf8d+QGR8ifzDWX1AZd96qHDYfEAKKuB1SU1\\u002fQHk1M\\u002f7P+X1A8wPEXoxif0DwBmCec95+QDnuRN+ann1Ab\\u002fSGe7e2fkDSUiJcJex\\u002fQCNbhjHlOX5AYz2Ar7irfUCv3+3DdiV9QGuRxNySHX1A8ncHO4E2fUAx3UL12+p8QAD2ai41mnxA\\u002fQmenC\\u002fNdkDWzYB9ea91QDTw33u0UXZAeriXts1pdkDGpow\\u002fGH92QIEt3eD123dArcOQqyPod0CIECAFBKd6QH4ANd8n8XlAe\\u002fFUKD6BekAKBrdz\\u002fP56QCtqxeIeEnxA87dmXrJje0BbPbRlfo97QKTRLqs\\u002fp3pAMr0ZNfS\\u002fe0ACg8yUYlJ7QODls1u1AHtAq1oaHFKze0ANBC4AIkJ8QMFP3qJH739AJ7a+31UxgEBFf9A78neAQMYnOYbGWIBAIjM2fydlf0BS3ENNzd19QJfL6NsSsXBAzGsaL2kBcUDfh\\u002fK3DtdwQOghVbaGtXFASjqWFJB5Z0AAAAAAAAAAAFADNF4pQ3ZAWJy46DmjckBLHZ01mVZyQKJLFu\\u002fGw3JA6nHS3lw1dEBVWuK3ksxyQJsPJR0ucnRATuLe\\u002fJ5BekCp6DOwu4N4QIUe\\u002foQhzHdAT9MOii5td0A\\u002fDpk5pPZ+QPC3eo4ftn5Ax\\u002f2nCtMWgEDRvVgikoKBQLoQaDjgyIBAJYcdyzQPeUAsSMnmp0B8QIIJ60jExXxA7TBda25DfEC32WVO8UV8QOPu2OBr5ntA2HM5r9VbekBHD2pVOol6QBeCwZrR031AN6GBR0u2fkBBhsRteBx9QI7LdmaekIBAsEdBpsPNeUAN5eOzGXd5QPse97XMDXpATbELwkbsfUAIrN70ccGCQNQxsVQ9voJASUJwJiMDc0Ao8xLdfkx5QGuceGfRwnxAmkNo\\u002fOpMe0Bke5bBmN98QO\\u002f3Y3xEnoBAonAB88Vxf0AmRnX4arl\\u002fQFL\\u002fx8aix3pA4C61bAUjfEBUnwHjfGd8QKjPm+5JyXNAeg0tCtRvc0A8RSjRq0x1QNi6+aai2nlAbguNbwajfEBTmJtmA7Z6QBY0mkk4u3pAFV2hXbXXfEDWoOZZXAR7QASmLsd7EoBAby8o0M22fkAMIQAu43R9QEfa6o9l7oBA+zi54el5f0Dch1hCnwiAQPB4wSW7BYBA\\u002fGYKcisqf0B8uV5bQyOAQKnZl0hqOYFAfyfseXR5gEA\\u002fkoO1yDKAQIfNPgQtAX9AkQ4zHzT5fkASKcRqG1l+QGTC6X2TqH1A2ucd45pEfkDFHHQq9KJ0QLmtk2vysW5Ae5VIP9W\\u002fc0BVgWMGejB0QK6JNThasHFA2YzHd\\u002fgfdkCq04zziH50QPGoa0vdm3lAqZO4hyQzeEBkcp2PL2B5QGpbL2wPYHlAu3JcmslUekCAL1XoANl5QPF4i+AetHlAkGmTUBxseEAk4Kx0I+15QDuqohDaJ3lAzdUpVW4oeEDsZ854PzB5QAbHqRdr+HpAnQfqFbB2gEBmvPRDCnyAQPXuoQq\\u002fkoBARFdze9RugEBwRE1xjOt\\u002fQIwlrSAuvH1A067n34licECkKwnOusxwQMZUAeILOnBA7pRjxEQJckAOO8G9Vw13QFADNF4pQ3ZAAAAAAAAAAACpmlGmb\\u002fxrQHmtEGd8GW1AuvCVZzCWcUD2YDUEIiZzQMcK4Qe6WnBAedwUsO7VckAvEhknvph3QATVgtAdEHVAqP8zQ9Y0dUCuke+Y93l2QJhUP107YXxAizbGpdNEfEA7CYJTWQyBQOsbsy\\u002faOoNAy21ioFiwgUCaI\\u002fMYQh94QGju7rOyZn1Aqp\\u002ffP46IfEAvG+GV7D51QEKJ54MESXxAYemiUjXGfEAz8frBTN17QKzeH6iZJHdA3lFDBE\\u002fUeUBHjI5QeAJ7QFJvW\\u002fgDq3lA10R8rX8ufUD\\u002fXnOe5pR2QEbMUhyeQnVAgiSIMjRedkBiSgERJ\\u002fh7QF45+39P\\u002fIFA4hW\\u002fgrvkgEBc5jVA1TdyQD4uIdUpxHhAq8QbIMxNeED5FslWeyl3QJG3ezbgHnhA+6Lxc2zkekBXZxJLnZx5QCWQ0P0ZFHpARksPk2fmdkBRZ0Diwpp3QNcPsEh5jndAZj86VewhcECfAnhLu0FwQNUiHKb5lnFAeOZOvCD\\u002fdUCZcSgWYQ17QBROKWAqcHhAVz423vIoeEA0DkeApwd7QJndlu78ZXhAGVgVAMz7eUCGdAolLYB4QHAAA+C4v3dAGrYqZILwekBMR6I8Bs14QFn6yP0cRXpAXMZkjF7seUBmbzLxMep4QAyQDQnFK3pAGW0xIS9re0AZPXySkd55QC1Y2+3Md3lAsVD9kIp\\u002feEDr+kaCjrp4QDRXBXwOu3hAiKF9V\\u002f57eEBgU6vNM1N4QM+PGYBR42dA5WDw3wbVZ0BjuCOTD4pmQCg8qlosAmhAZbX+lnInZkC3B88zPyNrQPt+1AzP1WpA19\\u002f15eFbckA3HKqjJblxQKgar7RMFHJAUg0t9HTVckDnbABPxuNzQNviSTrLMXZAR3usWwtXdkDC5lBnGGZ1QC6e+Us14HVAsfKXBhj5dED\\u002f2RJcwP10QJbxW4PfTndAUwLGkYhbd0BhKVJo6fZ6QAqEd1hkNXtADiGo3SxPe0BPhRj4swh7QOvddjCgb3pAKYl084qKeEDqRTr3u1ZnQHluEOzqq2dACPhFY5vsZ0D3vyBqm1xoQHUGyWBQaXRAWJy46DmjckCpmlGmb\\u002fxrQAAAAAAAAAAAEjF3qWH1WkDN94qhRdVcQD8PuOsdZGFA4cHuXartW0DZ4Y8KkddjQPAGAV+7hHlAWSP4a75GdEAmCLtGSpxyQBLKLkYoSnFA9MLoDsejekAZjOnhcVd6QE9O6tljeIBA\\u002fijZkvI5gkBb2KXazW6BQGjuVBcWgXNAPw\\u002f3002YdkCnwdHXqXN2QJCOPIY4l3VATDG9T6ifdkBU2EQisZN2QAdNHTTVq3VAdd2l7msXdEBmIwWUnR93QCaqVC4uE3lAzHqDZ29Vd0ClUMUBElh7QJDsprs0q3NAkSOMvQiXc0A6akTThX50QM\\u002fWmPLOKXtAEgdx1t+jgUDxquC8PXGAQELeO6xHsHFAwUCYQBf2d0Bil3tgpoF4QLmNtopUWndArMjiK18QeEAgYiE\\u002fLs96QOMML6pZTnlA9qHE1JfpeUCUhnWo9+p2QJ6xuoj4iXdAG7J4775ud0B2pSMr72RwQEJ64AkMqXBAJvOCoV3jcUBcQGjhdfN0QOKFBnfr93lATwx4BVZtd0Ba9E3S4zd3QN9\\u002fbP6uM3pAXWsJ4gl2d0AMZn4byAF5QCNsDUSSr3dAokUH1n0Ed0CMAxaqsQV6QKYfhnLjD3hAwRHMz1BTeUAcDLG\\u002fwg15QEQApcZ6OXhAzyRU1KReeUBbXdUTNIx6QIqKtSPFAXlAZuTxoqSkeEAnjRHdv3d3QPJj4Pt5+HdAb4xvXEXyd0AcW8mIoqZ3QOMb9j2mendArD0NaavzZkDKrGdbDn5jQLMh5C0d0GVA7IUKHINBZUDpu4\\u002feEqBkQLYY0r+65GlAip8LR\\u002fD6aUDW62JZ9wByQFoiB\\u002f44NXFAgzO12W\\u002ffcUD4\\u002fthudl9yQHVcaT5ojHNAJZPqLRIgdUCwfo6icGl1QD8UPAGcXHRA1k6FeyoGdUD78w3fYUR0QJkRhy+iLHRA4q0ZCVhqdkCmvULI10p2QJoRXp43FXpAImYYvZ1kekAc1tp85jd6QKZR\\u002fGHbL3pAXBfppZNmeUABdaBtOLV3QAqas4e74mZAUEBg2uVSZ0A1TMDGneBnQBnWaKwzhWhAr9KJLMbKdEBLHZ01mVZyQHmtEGd8GW1AEjF3qWH1WkAAAAAAAAAAALgYoEC9yF9AhC2J0HC+YUA4H89TXpxhQG\\u002fKxV8V8mZAhPYYakrJeUCLzS95UNx0QHhq\\u002finEL3NA+NtpBH4KcUDWKO5Mu2p7QPdTP6qMz3pAA+hudVlegEDOgxLdFkaCQB+40GPRm4FABHFoylKAckBd0E8kUrx1QMlbmRUewHVA2\\u002fBjc0nSdECLFBg1R4Z1QFHr1d\\u002fbnXVApWO4zGWqdEDNmZg99TJzQImp+VuBznZA55bKHv3MeECWoSLUpuB2QNIIWy9lYXtAtbPnNL8kc0BrQs5xJjlzQCgmgw4kZ3RAxlImQpZ4ekBn2y+IOrmAQGx9cWD7YX5AqjAUtmZRdEBBDfwpA3F4QN3+C6J5DntAO6Vqo7gGekC0LBweK7R6QKYqh9ntw3xAarkRwGefe0B3DZzqlAV8QCJ3ezz9uHlA4ZtFtHk1ekBvYGUHmO15QMuolw\\u002fNcnNANXMRj2P9c0DkuMy0HwF1QK2i35ii6nVAWe0PzQxReUD\\u002fxBMkEjl3QIKUaprHVXhApugelEXWeUCz+zGoi4x3QDGDx3KXfnpAxnPp8s\\u002f1eEAbw2Jy94R4QDH9UJdnJ3tA935VEgNNeUCEKNngLNp6QMkgAU4zoXpA9iaeA0WreUAeFBD6v816QC46jlBc9HtADxSTgks2ekCI6lnqeM55QF2knXdA6XhAMEDhUuaGeUBYFSE55nN5QKdk6HBPHXlAHXa8D2vheEDmeRgN85xlQL4lWvuMFmlAnYsPjmNAZUAdeVT5+pBmQNUNR9r9j2VAsKIHAPKZZ0B\\u002fnPZzKOxlQIWnVcu3n3FA4J\\u002fu0DH4cEBBA\\u002fxZGkRxQJilH4dh23FAFNI6ie55ckB6BnwiGk12QDK+fMgvUnZAaAao25dvdUAxnXSNBxR2QL8vyxTEDXVAPSEqWhgzdUCS5TzBdmF3QLkmoROVmndAVGmD3flse0Bk+yLmNdJ7QLHzscUtmXtAJRsjPa2ve0BAAPJDPdF6QJPvtnAZJHlAjjKIW6VHaUAo407iwKdnQAVXOHPqKGlAvufWY\\u002f8zaEDAx4Uq\\u002fHp1QKJLFu\\u002fGw3JAuvCVZzCWcUDN94qhRdVcQLgYoEC9yF9AAAAAAAAAAABRQB3c35tZQEjH\\u002f0opf1ZAggD\\u002fjBA3YUA+77CDQhV8QBuKJr5K1HVACeZ6qP7hc0AMOPeATbZwQLKlMte423lANf+aX8CseUB9FfqbMK9\\u002fQMsqCsjwcoFAa6mxCX0VgUCWJENWly5yQL8VsRhpqXZAbpmeKaCedkCOq4K5y2d2QBaaUEMgwXZArG0YbxDBdkCeYQEVSml1QETRXv0W0XNADFD3bfv6dUDZNMY4hRx4QN\\u002fcT+IJ\\u002fnZANhypxSwFekAkO40crX1yQCo8u2mOBHNAq4np1lxic0BOMiCTJeB7QI\\u002fsRU3ZjoFAHdbl2izmfkDQ13IpCYN0QC8vbR3TDHlAhj8ad2H6eUDLHEgfFix5QI4iQdCnhHlA9wowAzN4e0DeVX3YXxN6QMm2JwDc4HpAu4NF84YHeUCv+ObcBT55QMAdguIxy3hAHOsGYOgoc0A9j7rSIsFzQPsbnRxun3RAodnEI5hQdUAMl3P58Ml5QDZ9Vj+dn3dAycqIFVvld0BjxOHwtTF6QANxJzoVlndA7519CKi6eEBjePYDBXh3QMKNUuLqPXdAHVSdsYKFeUBitomKNcp3QOinUdNVG3lAwq7MIbDyeEC5pW6zkFF4QBjvqOrpQHlAjk7EqtplekDvfE5yFMZ4QJWAKxSPWXhARmTmlFRyd0A0Nol0jCt4QGUxIphZJ3hAtsOIDZjod0Avndcfa5F3QLKZxS70aGNAsmdLyqnJaUDyG5KFtJljQOHEW80jTWZACAAzRdnxZEDZMrEgfotlQDSM\\u002ff566mVAfWlsq2iMcEALIFZGHSFwQPEpai14JHBAq6U32OYFcUBdUkCt9J1xQNbRjBBAqXVAWgM65hjudUCDFM+3k\\u002fd0QHgnSZg7aHVAcTyc1i+PdEACn7hpTAJ1QDqPHl1e8XZA4QRtcqWWdkC0\\u002fjUpbw56QJMg8MPtWXpAwx7k\\u002fLv5eUBZCsmfcBh6QMgnAE3ei3lA9LW5Zwvfd0DJNeFHqaBpQBgpt8OvyWhAuzgNDK9iakCTIhL9A7VoQN1X8O+h2HZA6nHS3lw1dED2YDUEIiZzQD8PuOsdZGFAhC2J0HC+YUBRQB3c35tZQAAAAAAAAAAAIp9AqSLIYEBBYiQdfW5jQI85wOvyFH1AlK+rFt99dkDfSJ3QclF0QErgtFLdrnBAP+pFv4ueekDNqPq3WgZ6QPPj0lx3VoBALsv\\u002fI0YQgkBR0kbbfaeBQFvG9IEywXFABNi76gIedUBJ8gmkTRV1QKT5J1bygXZAD23G81tNdUDk3wKMfFF1QAVmJOFWYHRAU1nBr8+Bc0DXAAzQgCt2QJJ7R1fGdHhADWfL7gHsdkAgGT6PHGJ6QMBx79Opm3JARYgIJ7xhc0D6kba+RuRzQPMw0yXLiHpAtMg\\u002fKXnGgEDTRUyOt3Z\\u002fQEh2orP9iXNA6PAB1NGcd0A++XAUM+J6QE1vhh4023lAlq\\u002fGBf+jekBjHHg9vNt8QOj6uyTE4ntArDpDkq0JfED\\u002fbzYR24Z5QGF\\u002f9Uh4KHpAfWX9FHf9eUDN1hhzERVzQJaMMhPafHNAT09y9ci1dECaUL5KaGl2QDVmsZdcOXlA4DYzDnAVd0BXQUvCVpZ4QCBIo5anz3lAO1K76yuxd0DMu52KsSx7QCetK8Xsm3lA\\u002f54YN74WeUCWy\\u002fFdsu17QAMwUc7v6XlA\\u002fCsJG2KGe0CgAE62mkl7QCi5qmeRLnpAqam3s9JYe0C8zUojlK18QJyLhL6Oy3pABOXfyo9LekBxoTMTq3Z5QFFnoTgW9XlAXdZ9\\u002fLQTekAhg2J9mbF5QFCV1SoJcXlAPT8qw5hGaEBYXlAeN31pQJj3erQb0WZAz0tkHMSuaEBXddzaQKBmQD+kVCqajWpAi56v1c2paEDbme5JKBxyQA5O9Qjon3FANtbBphO9cUA+npYtp3NyQJTP1QIu63JAWq5vFrfNdkDmb27uW8R2QLcpBYTPwXVAyszZGsN9dkAOu1gRGYJ1QJhqdqxAVnVAUlQMNoyed0Dx60aeYgF4QOwj0+OXAHxA8k9bz3dhfEC6bsqoM1d8QELnzBosRnxAfbIegYuIe0BXZyMR3Kl5QED3FinKtWlAvflI3k1vaEDMwmWBZmNpQPKDLf86O2lAve+h2R8adUBVWuK3ksxyQMcK4Qe6WnBA4cHuXartW0A4H89TXpxhQEjH\\u002f0opf1ZAIp9AqSLIYEAAAAAAAAAAACh0qyfYRmBAQcCeSGhDekDPeWLnvgp0QKzjyItAO3JASKVQaowqcECpb1Me+KB4QDoVNz9qp3hAFLaChYsrf0BeQKIIh0yBQOkyfXHvrYBANEhPu9+wckBw561PzWB3QLbgBtFuDHdAnJMBTBP+dUD9OXiw0113QCAocK00ZXdABt0JFLm3dUBv5oR8U\\u002fJzQOssKgba13VAbigj\\u002f+oAeEDE25juvSJ3QJ8FNGEQ6nlAYa7Fh+zRckAZg9HpjAlzQGHIXpDqeXNAVhhrGvSxe0DLNySWzcWAQPBlsLKte39A+Iwf0zEvdkCVKk2OUF55QOezDtZjqX1AtzYoTiKdfECU21UdIop9QJIFyOly239AJR8dUw\\u002fIfkDVavGUTU5\\u002fQCrvrZ+yRXxArIwoK63YfEDwPDcJaLl8QB2CK8CeznZA2XpNrC0Wd0Bt7uNCUCp4QNEmcXKyznhA1PnCCDCVekBgCmy8dBt5QMIyMzddHHtAcZyieiCke0A9IOHLP\\u002f55QPMTtKDo7n1AbcyF0y17fEBtUqWznzp8QDYmwNx0wX5ADCBd0DzhfEDxtAiLxyZ+QESlCqI\\u002fFX5Am6NxZRomfUAf3PvSYhN+QC6lFUWLWn9A9gghD0WffUDSrLYUmiJ9QHWz6t+rVnxA854s1krHfEBd\\u002fzshc\\u002fd8QKeCbH3on3xAxbZ9u85ufEBk1yIaaIFuQJDChRXAKXBAWhj\\u002fUzQcbUD0sq++RtVuQP+ZOiboBG5A2PN2BJY+cECtQTGVyzJtQPk9xL1h03RALXrES1BcdEA8hHNdfzd0QHYYcEHWMnVAuyMM610\\u002fdUCKpEDD2qt5QFkvGXRhoHlAxcMdBhaUeECzyZuG3I55QDqjABuXpXhAFXyfrmOxeEA2uvAIuwB6QKQ83kVAi3pADPAMq\\u002fupfkAFrW80Ffp+QNTFOBbc1X5A9dvvA4XNfkBjYs758VF+QEOvmU1+V3xA2\\u002fcladITbUCSpyk4yeRrQItpYtRllm1AgNGCZ5jla0Aa4T9yuax1QJsPJR0ucnRAedwUsO7VckDZ4Y8KkddjQG\\u002fKxV8V8mZAggD\\u002fjBA3YUBBYiQdfW5jQCh0qyfYRmBAAAAAAAAAAACADuAaYFZ8QDIxgV7VZHVAcKnAskVKc0CHJ1fF23RyQNQd3q5ixHhAUXpRJDaMeEAEgrnr1+J9QJmH62xLW4BACmDtOsXYf0D0hYmkzvZ0QOO2jfMM+XlATssvh+hGeUC5BMzxVbx4QBw7i1Y3C3pANn3FUrwMekDO1llOxXJ4QCXq2DUMOXZArLIjFUKJdkBUF4pAjvh4QNAesAFPuXhAvu3ZostYekBrvNx1Ya10QFUg5YJ3g3RASeZS663HdEBuUhwCI36BQKDHTXCQJIVAlGrJOOJvhUAZIfYJwNJ4QL+Z7NR7rX5AkKdAdkJzfkDbfSHVJy99QIDt5s2VFn9Ai9O7zIvvgEDQEMT0uLyAQK\\u002frqFyGkYBAtKFgN3jTfUBtv8npTyB\\u002fQNB\\u002fv\\u002f0PPH9AjAiXd4KMe0Bn2zoFhyR6QDeXFh3cbXtAgpDHKLU4fkAmyXuKlw+BQDwahcWTSH9A9u4DZGjzfUBuMdqzB5GAQEBPlseGQX9A+suxDB4EgUCcbBpMi0iAQHXD7xe3l39AZNLO1O6ogUAULK5KadOAQNsmWOQq\\u002fIBADTahz7fLgECvjkiUxiaAQIsjMtqXqIBAjvPOULDTgUB2EK+5g1yBQGuB67+ZM4FAzi8afSRSgEAvnYIOuAmAQLrMDplfFIBAcg9AcrTqf0BM6eM2XhSAQH29RGnVeHxAiTDneMiaeEB5El5OurV7QIdtIQ60Y3tAYz\\u002fD+8azekB9KxQnvi19QHmk3KBxUX1A74\\u002fIMQ+9fUBXlkRvMJp8QAU+l0Qiln1AzZ92XBuAfUCcKxbQQRh\\u002fQD7EJPBARX5AE5vbUd7OfUD95yHZ4yR9QCpWoSjVFX5AHRjFv963fUASrpl2O7B8QMiDEjg85H5A+V43221Bf0C\\u002fwBbr2geBQJgCUFtZA4FAhSXSk1pogUAypQvJDu+AQIwWyA6s5IBAmYpIPLrsf0ALdGHJ2Tt5QHqHuMhKPXlAZqnosueWeEDvr+s5dSN6QGSZ+tGrPHxATuLe\\u002fJ5BekAvEhknvph3QPAGAV+7hHlAhPYYakrJeUA+77CDQhV8QI85wOvyFH1AQcCeSGhDekCADuAaYFZ8QAAAAAAAAAAArGglDbCCcUAiKF0agVFzQGEFC1+N0npA4WqZyPA9fkDluuOMeot\\u002fQA0uUgWPGYJA9s4IrgwshEBdAddSC12CQM60a7A7gn1Az7y9+uAJgEBQHtKPTc1+QI7rdKis7XxA+VT\\u002fMmBkf0BIEX3Agkt\\u002fQOmmx9Q9kX5A8QShoJhpfUDHlkEv4eqAQJVXFS9LnoBAPj8Yf0cnf0DkONVVd9KBQOL+EcEIgn1Aodyg1dJVfUAKcsTeKHp+QK87olAgtXxAjk5P4ncbgkCFCaScN7KCQHl67YCoonNAMjr7\\u002fMxteED8+Zmmzi97QF7NbtF8TnpAyxmTFda3e0AJelM6RRB+QMU7nZMqx31A2cYX9TCQfUCgPAiuQpV6QE0V23VwZntAl1kaOHc+e0Bizxo+VjJ3QGt0jKy\\u002fgHZARrA9+buxd0D6osAp\\u002fAR4QD7uu0Xu\\u002fntAy6YNSikqeUASzRMkyS15QGs1IxfY6ntAw7uDW76neUBNNMkK\\u002f\\u002fp8QLS5MAYDJXtAJ7mfLMDLekCuAOBfG1V+QGJfju8NnnxAp7v6Zg2QfEA8FdXqvXt8QO9bMkZ4ZHtAmFVFwMwbfECuiDyzv6t+QKDsgQ13i31A3irNDrMAfUDbQgT5WCl7QA+0VUrcHHtAld\\u002fdMfcDe0A6YzbXQdh6QJFNQSAk\\u002fHpA0kQJj5O3dUAfpdAekH5zQPdofL4LbnVA2NzrhddBdUCH52bAbPF0QJ506+uqdnZA3iGUzJ+ldkARJY9\\u002fsIt2QGQ9O4ee\\u002fXVA5OeLt4VCdkDDj0HuyKB2QOKuV\\u002fWwpHdAq44vWPZVeEDvCSNNMeF3QIzgEtYwJndAd8V83CgFeEAH2R1JWGV3QNq8W1u6q3ZAjLup3k3meEBLic7fVyJ5QCrKwUuQynxAfGKhmojQfEARvS95GEB9QPxcrAyncXxAI\\u002f4TY9yefECIXQOk\\u002fVd6QGixSul4pHRA3z\\u002fLRO85dEDCDqC0kYxzQAzaXR6r5HRAff9CTxeDeUCp6DOwu4N4QATVgtAdEHVAWSP4a75GdECLzS95UNx0QBuKJr5K1HVAlK+rFt99dkDPeWLnvgp0QDIxgV7VZHVArGglDbCCcUAAAAAAAAAAAL5BXskGeFhA3hZMD3npckD7+o7Z1I92QHDEZFz613dAg9eWkAt9fUClL5Ohlr2AQFEYsDmvKn5AECYImpvGdkBpEVri6Mh5QKbGQRlfcndAf37rNdk1d0BNdR6k3UF5QDMxex1l8XhA3MgUd2P8d0CYbvsiI5J2QNmhNNTI3XpAIRJ0aOzCeUCQTUJDWt13QI4a4\\u002fJGOXxA4BABHffndUAkl1DROxB2QFELLb25bXdA+CCpC6aNfEAweScznN2BQPCsyGfuJoJAzb2mpkmzc0AN\\u002fSuz9Fd4QJlX24UVUnpAp5IPbUmveUD8dwHOf8x6QFUZc87i2nxAbBdAJox5fEA7mJXZRH98QGuiqG8unnlAivVTKd5ZekDLcLbtRR56QEpZfJcFXnZAjJ5mzkbtdUCsQ8oP6+V2QGxOPTmrSXdAnkWtoesde0CUmX7eWGN4QOaon0aFvnhAE6AAatxCe0Cj2M1rp+N4QByiEhvkgHtAfjWbQk22eUAtGp6rI5R5QJUYBOHapXxAnWZBwwwde0D2Lyorax17QMTEvkkSDXtANtyU7bUJekBVHuR1ial6QNzRmh0Q7XxAxFzDGArEe0CD\\u002fWN\\u002fIUh7QFp5YsN6o3lA8K9NNmLGeUBJATz7G\\u002fF5QETZpQ\\u002fPxHlAtiWxtU23eUAR2tRYK5VzQChAjYAgO3JAoOd43xBvc0BZCjFBDzNzQCL3yvL4JHNA+oRwEU9GdEA0KmhVbO10QAsSS4mYVHRAmHx545\\u002f1c0AhdaVIERB0QDfkJ5Uwp3RA5hrV6O6LdUBu57NsWsh3QMk2kpo6dHdAMv+e6l61dkDddZuu3E13QCWBPXmJknZArdEnUC00dkDSz2f0DJ94QInLOVEQd3hAntxyGQJve0CYJB7DYXx7QPyRa\\u002f2l4XtAGLTLO7gde0DdmsfkSlZ7QMmoMIL4OHlAFc8Udl2Jc0D5u\\u002ffb\\u002feVyQASgT4unUnJA7c7TErhoc0C1EuzMDst4QIUe\\u002foQhzHdAqP8zQ9Y0dUAmCLtGSpxyQHhq\\u002finEL3NACeZ6qP7hc0DfSJ3QclF0QKzjyItAO3JAcKnAskVKc0AiKF0agVFzQL5BXskGeFhAAAAAAAAAAAD6+lP4Ju5wQM11Cg4Sn3VAH3C1AYeddkB75yR65VF8QM4FCFSqJ4BAAMBGySVlfUCyBi21z2t1QL3w94KnEnhAbsY2vD\\u002f8dUCHbNo6sxh3QD52gzbbx3dAjUaZ2Gqad0ABzXNcWm52QOyHUynO8XVAfxFlzoFIekAn059AmFt5QMgpj8CGcXdATsSKborBe0CsLhiaiTh1QJ7iov\\u002f+pXVADCyXwlTzdkCEH9C\\u002fsQV6QHoYPw3MpIBAwEtepfXxgEDu01EP0nZwQPEGG8XAqHNAJinP7e34eUA1qt2KVFp5QCUgLZ0wxXlAF+U2i6NMe0BHXDmubZN6QLqaw91iEXtAF8bnoZc\\u002feUA6TlGKcGp5QPN50jR473hA5tv7OQWcdUBOFKEM8OV1QFAu1tLotHZAvZM0lKH\\u002fdEDqp11y6zB3QOPIJiUdzHRApMpEfo5ed0DfzDsDf9l3QO6qIdY+6nVA1XsdN0F8eUDAzME2Ssx3QCPcKuLdvXdAsOLk5riReUCNRJDht2Z4QKTVKdWd+XhAu1tIDm\\u002fyeEBpH9FuRzZ4QGTO5TitrnhAl+ijY6djekD+2nYTGAB5QB+wxap8xnhAXjEpHwxsd0CbZir9pWp4QM+Wh+95J3hArm7DT4Tod0AkViG7xqR3QH8IGMaIbm1Aq7KhQDvXbkCoHyl7AnVtQLS8T+wDRm1A\\u002f6tq69dcbUCu70zblQ9tQEbFo5uA3m5ADPJsG9zgbkDMxfju\\u002fZduQHEQUBnH4m5A3S4Bw2vPbkCksHM5I89wQMdkrRVsdHVACZzsVKMxdUBL47qmx2t0QM0ecqLV33RAcQQ7bvMldEBnTWLt0Sx0QIjNerc2FndAQzbXrBLAdkDctBQl9NJ5QBUTkbRX63lATwOO+SupeUDoZ2c+4YR5QHlzxWm1MHlABUhR7kzUd0D195gm8ipzQHn\\u002fgJL2M3JADkg7vSxZckAoEfmYOW5yQGZlY+7F03lAT9MOii5td0Cuke+Y93l2QBLKLkYoSnFA+NtpBH4KcUAMOPeATbZwQErgtFLdrnBASKVQaowqcECHJ1fF23RyQGEFC1+N0npA3hZMD3npckD6+lP4Ju5wQAAAAAAAAAAAJYUScdqTcUAEdOIGfY9xQA2RFMawz3xAmgDhxxJjgECRANiVS5R\\u002fQHAXf+fJMHJAcdPMLe6EdUDGNZ45gAx0QOl+eJlMXHZAyaTyBpQ+dUCcuqYOuYd1QDEURqJ44HNAtJAAjBZidEBIlKB8mqV4QJFiIUQs7ndA8CHi7KhmdkDWtbCfk0B6QHc0TTMuDnNAJejZTBRudEABwXb3v011QNLmDxLVv39AY0k6ugkDgUDpoGDrxVSCQEuydCnaJ3tAH\\u002fXBLez+eUAwP7O5KsuCQI27lCUqZ4JAxEJ8MU7ngkCLnL2ABfaDQMjxqHrqmYNAUaVOPhzUg0DZrPiGXXeCQG0Pop\\u002fBt4JAxYktzn6qgkDxg9w+E+OAQCJS7n8S6IBAc2WEV5VkgUC72qyUbYWAQP+3qhWwKH1Ag9fksk2GfUAmdxudfV6BQHYoFlegKIBAQ27DomEugEC1P+MUfoSDQKtxg8HOs4JAZ95EIuWzgkATgBMgJa+DQLeLAeUo\\u002foJA8UtIFFMwg0B+xqWOhkWDQGBlkptj7YJADUVoBkEFg0DtobmZjvuDQApx2+5yWINAMytml1Y9g0Bz\\u002fGyjGJeCQL7zUAWQxoJAhAydWjTtgkDOs3bQqsKCQKd8hvznqIJA+DfGrF9Fe0Cs6wKzuXx5QIvExcqOO3pArPVPDILwekDiMKa9vvJ5QCRjUNofsXpAd065cQ34eEDfv4nvsLN7QDvnoi7VfnpAQQwjjxilekC7uYuEb8d6QHpBUWjftHpAICRo98QZgUBJvz15xLiAQIv5Y9p\\u002fPYBA9JQhQRjlgEA0GZ9dTGKAQF1PEVqcCoBA5wvgtNrSgED8g45wr2qBQE+FB9AuoINAV+iYZFObg0CQMx\\u002fjlI2DQDjg2BRfboNARNq2v41bg0CLrkWd14aCQOC85UCI13tAzTlTr67LekDMhymYQOZ6QMt71geBQntAV9eeG\\u002fcngEA\\u002fDpk5pPZ+QJhUP107YXxA9MLoDsejekDWKO5Mu2p7QLKlMte423lAP+pFv4ueekCpb1Me+KB4QNQd3q5ixHhA4WqZyPA9fkD7+o7Z1I92QM11Cg4Sn3VAJYUScdqTcUAAAAAAAAAAAH83l\\u002fsD7GNAYlxsyxwpd0BJSJBB1HN6QPEeXU\\u002fhmXhAMh3B1bUwfUBmTmWBi46BQFis+RE2ZoBAQ5C5BUhyf0D\\u002femXt3FWBQDiAJyI5i4FAsUDaX857gEDbH3SsaTR\\u002fQECBveZlcn5Au2j\\u002fgv7CfUAe5Kans61\\u002fQPkVlymvXn5Aa4G2WZMAfEB8tyuYbXJ8QAaDHM4Md3xAPeL6HKc0gEDnImcoSYWBQCvnW8IZ2oJAGd6W5xWIekAxW2OluzJ6QD1Htq7UZYJAzkQUlIrpgUBjGp1Wx26CQJ61yFjdjoNAzYX\\u002fyDQVg0Dmw8LId2qDQJ7YT+I+HYJA1FGrR3lYgkBDsg8nO2GCQE4essFJooBA1nHhWqrUgEBPRn5Gc12BQKUvdQNeC4FA2iF8Nhd8f0CULdEgurN\\u002fQPSx6gQoBoJAV9wYIAQYgUDuhPpfOPaAQBFR01l+qoNABru5dUXngkCWIaNwy+mCQLdpaqe6z4NAm\\u002f9k79cTg0ClJLFD8FeDQDA6zNFXaINAqh3+A\\u002f0Pg0AsHpyfHDGDQFBEivCG8YNAVlgDXdlfg0BzXPMQDziDQLGomvMwuIJAi0amkUfqgkA2jSj0wR6DQA4y\\u002fmiyAINAkDuOWXXkgkBC7ApvsEZ7QKq\\u002fabyVNHlAs+D3NN\\u002fueUB5mQnZpOx6QBMu7N9mmnlA4Gjhaqi7ekDV8guKIHh5QEov5EKpfHtAP4F5LIWvekDZLnKoH2V6QF4R8Bn7C3tAn4LAdKrRekD9UaoYEHiBQL46QWlmNIFAqVYbiYykgEA\\u002fibo07z+BQJFhxQ2zyIBAa05dZcZ6gEAD6\\u002fz0jEeBQEpVxkkywIFArbkYxFLhg0BZuGyUKNSDQHYN6u3syoNAiodfN+yUg0D56gta85qDQBOU\\u002fYZS3YJAuLDD6BU9e0BdCwysV3F6QBCdhyz+snpAsyqGHUPAekA9hmcTm7l\\u002fQPC3eo4ftn5AizbGpdNEfEAZjOnhcVd6QPdTP6qMz3pANf+aX8CseUDNqPq3WgZ6QDoVNz9qp3hAUXpRJDaMeEDluuOMeot\\u002fQHDEZFz613dAH3C1AYeddkAEdOIGfY9xQH83l\\u002fsD7GNAAAAAAAAAAACkb0xHCs53QC47g608F3tAxPxbw0HJeEChPSVATBx+QFHq9oAUu4FAoJWl13CogEAxzlsBcBiAQEKs3HN5qIFAhJJboT67gUBAor9HNbmAQJvculWu039ACqfZezCCfkDOIWtQD69+QL5HVgMuU4BAvslwqI5Gf0BKkbOm0j99QC+Mzfv2VX1Asxq8QwtjfUBp4\\u002ftMujJ\\u002fQGxLtTKr731A0YxMA\\u002fg6g0APZdyGQj6BQA\\u002f05JhoqIBASQQ7JkZ3hUAo4NGMBuSEQA59kcDrpIVAiZldL\\u002fZCh0Dby\\u002f6RvJiGQDIKwFceQYdA9i6xrHtThUCjFO3TWZaFQPpflLvPhYVA06NQX3UUhEAPYL0kNQ+EQN07KnLhg4RAZWncHen1g0CxLWAFyrmBQB0sNqOHR4JAoilTvXGwhEAq3EzLqTeDQJ3L4aYgSoNA\\u002f9RVNL\\u002f\\u002fhkDib0NwPDeGQIZnUwYBWIZA1Y5XlqNQh0ByezPihrWGQCcVp6ouqYZA\\u002fAx1c\\u002f3GhkDs93M7lJGGQMUUgiMJkoZA3QAT0Opnh0Ba5UuTxMqGQNiI7tW3oYZA5jkzWpA5hkD46BslgmiGQEJu5JQKeoZAZgAhMeA1hkCRJ17msS+GQIeU7HjkSIFA3FdcGnfof0BtbIXug+uAQOIFfT4144BAArmolNm6gEC9mFUqf1KBQGAsxDCJIIBARq+dGQW0gUD2I7vmJOiAQMS2+KYGRoFAK5\\u002fHywVpgUC+y\\u002fAFyfqAQM3ZSt9jSIRAVMoxvBf5g0AcatjhGWaDQOJJV2tKK4RAOJqlLLe4g0CfToGDCDODQDIPwqz+noNA70IwjlR3hEDPeT35VymHQHEmZsEEMIdAONt80VsBh0BFivdLBvuGQHS\\u002ftF0H1IZA8WVc230LhkBSxUBJGTiAQHu4dzEn\\u002fn9AvXk8\\u002fuUcgEAPGUW+dz6AQO1z5t+TFIBAx\\u002f2nCtMWgEA7CYJTWQyBQE9O6tljeIBAA+hudVlegEB9FfqbMK9\\u002fQPPj0lx3VoBAFLaChYsrf0AEgrnr1+J9QA0uUgWPGYJAg9eWkAt9fUB75yR65VF8QA2RFMawz3xAYlxsyxwpd0Ckb0xHCs53QAAAAAAAAAAAGu3WJVRxZECs73Kf7h5kQGDRotFC2IFAyLbn\\u002fi0ThUDyV8zYUtSDQBPIag3MZINAZjEVaMndhECZzBzDru+EQEQwX4vqFIRAtUd1zMlJgkCmEP01kcWAQAiBvVPWqoBAM08PF8BBgkAoGnTmOKOAQJzYu0gviIBAZ1YSmn0xgECD+PTt6g2AQK2pV3WI4oBA8Pr8rIPkf0CKmpDrDo+EQFWWrYkYQoNA1a\\u002fG86epgkApC7fk6lOHQKszY0rKroZAU1UKSl16h0DyZ6DG7uCIQCUsDzfhZYhA+COWSp7qiEACdSs+vhyHQGzK3Uf7WIdAqt1Gm0ZDh0C\\u002fAqCh6hGGQOvr+WH7F4ZAQamzRoJ\\u002fhkAUr5pYAdOFQC1Tss7H74NAoIJaALJJhECUSG1o4ouGQF1vMFeJEoVA4a7HHtYchUAU1ydNwLyIQInysYOY5YdAhG0q5KgfiECzHXkPyvyIQA32m6h9aohA1ALKyABjiEAot4C1Q3uIQCNoq2qdNohAr3z+\\u002fdI+iEDNmOb08fSIQHE6vMCwYIhAIQf754U5iECW\\u002flwI99eHQOpo9rTg9YdAmhXRxSQgiEAhUhX9Y\\u002fKHQBOdbTCa4IdA5j532kEgg0AmmXU02RSCQBtjCX+gzoJAZukwk6K5gkBbmDsI+reCQBufBGpTL4NAPyV\\u002ftvX7gUChJZHbGJmDQCJa1DVV8IJAuoVAgBkrg0AwB5iTA2SDQLoDwkDv44JAD33lBaYmhkAdR7hozM+FQD7C\\u002fkVyVIVAYAvqoC8QhkC2gRg7yKGFQEb80OMmPIVAFVNQYEaKhUCN1rbwEFOGQPt3k7J4x4hA02NDu93RiEDp6AdxramIQGnyaUDlnIhALYiYVcCGiECjoPmsrb2HQIwV5aHsJYJAQDiQUPzwgUBORKrtayGCQDCajcsSK4JATDt2VeVGgUDRvVgikoKBQOsbsy\\u002faOoNA\\u002fijZkvI5gkDOgxLdFkaCQMsqCsjwcoFALsv\\u002fI0YQgkBeQKIIh0yBQJmH62xLW4BA9s4IrgwshEClL5Ohlr2AQM4FCFSqJ4BAmgDhxxJjgEBJSJBB1HN6QC47g608F3tAGu3WJVRxZEAAAAAAAAAAABKTBpDqmWZA6YpYtwfZg0BJzGwJLMuGQMOwLx9BiYVAetFBoCNYhUBtFPOmF7aGQFjGN\\u002fZFvIZAoBhGa1XkhUCtfIdGcz+EQKZRIYhrhIJAHElEwqxzgkClphDQyhyEQAZBWvXjU4JAqeIZgAuEgkAJGnMVcz+CQJo4pXjEDIJASIvnWoMXgUBIPvWBDsOAQC9DNpRILYVAusZ9Xcc7gkDKKYvDdu2BQHFZacD7Q4ZAgzI1MQKghUAfG4XbAo2GQCiNufHVN4hACt8\\u002feV2zh0DYse3b3CmIQKwuaHBxIYZAlMnhkeFyhkCpfPVPwXuGQEBKCHPy3YRAGykP7\\u002fDkhEB1TXWii2eFQOVy1lqfZoVAReYhM+qRg0BAvLDhbOmDQAtOnHpf\\u002fIVAr+hYoS+mhECI3KcqC7qEQD4HzULRaohAHjVWebyVh0Cm0gxzmaaHQFtl\\u002fwMYz4hAdDtmXEUYiECYohc6yRSIQHz9bz68J4hAA2qQQozVh0A\\u002fASCdb+yHQPIeZxXwwYhACp6hxzAwiECGKGDnEvuHQPmf9pgWiYdA76a+TXuUh0COXHQoHr2HQLOq9gTsgodAYsACJqyKh0A8QLHs+LuCQEmYAlZoUIFANumwgvJDgkAEa0c5GkGCQBrHgQgFCoJA\\u002fcMZZeDRgkB\\u002fCZEiWauBQLPD+o3cNINAHhsLHPOHgkALQ3uQqL6CQAkd1dMOAoNAow4lxTWXgkAlB5ib7amFQNdjZ7SoVYVABXKy9F\\u002fQhEAe7Oo5XKOFQNRDra9qM4VAhQZMbaashEBkfk5\\u002fcuGEQNV14duExoVAtcFVb8Z8iEDTNQKY+IWIQB+HJk5+c4hAuxhrRL9ZiEDuikXezjSIQFHu85EuXIdANkzTbyo7gUDco3CN6CGBQGTIOxr2HYFAuaDtPpxbgUAVQug\\u002fq1KAQLoQaDjgyIBAy21ioFiwgUBb2KXazW6BQB+40GPRm4FAa6mxCX0VgUBR0kbbfaeBQOkyfXHvrYBACmDtOsXYf0BdAddSC12CQFEYsDmvKn5AAMBGySVlfUCRANiVS5R\\u002fQPEeXU\\u002fhmXhAxPxbw0HJeECs73Kf7h5kQBKTBpDqmWZAAAAAAAAAAAASXMdsinODQD7PHMpTlIZALlVB3P4+hUBIBtonNEuEQMoATbkEXoZAYzOUKmBvhkAB9+4hNI+FQFur+vROoYNALgDTzGEegkD\\u002fGVzmjBCCQNbf0MN5kYNAf7ofg5UHgkCiYuuMKS2CQIqouF6MqoFAl0Ktm9SdgUDYzlFRM+l4QK5zW8OqgoBA0n4SGrjye0CAcaKdRnx0QIy76bIzPnVAuY4LBscDfECa95D2VVd7QDySKzyBc3tANw88k69VfEAPvx9CrLp7QO3X9nYogntAXlRqg5cxe0DPWY+nM3l7QDkuNsUjIHpAuZGSnuNPdkDynFlpWG52QMeGRrqXZHdAlEVwo\\u002frQaEB3nWVdoJRyQDgGRyCtwWxAxmq0KH63a0BWDMC3fkFwQD0qFn9d72pAHo8+EJRic0C8Wk5hjDlyQCVuhW+sx3FACNLu2zyEdEDzGCFQwt1yQGnauS7diHNAGsKGL9gGdEBheL50QotzQDxsav+aVnRAyn196MUPd0BrvJwQ\\u002fr90QHhsBCR6H3RAF\\u002f1nVICHckDABfLGl+lzQKFqwyrBO3JAZ0H+ERsycUCXOxY\\u002fO+ZxQPY0vKPBBGxAvuknHJvwcEC3S7TflvRuQJtY4vHi8WxAtnim8p4Rb0DNaqI0OLNtQPze7tDezW1AI8eMWLrmb0CCTiM6mL9vQOzfeHEzunBAo4CYb8\\u002fzb0AMBP2IgwNxQDBzGfSfZmtAR5+l3r6dakB64MLhwnRpQEaSX4v7GmxAkciDm+rfakBwQbLooltsQMDx5DtIkHBAlHBJKZLebkByYxf\\u002fkaFzQBpugqVqeXRAyGj2oPl\\u002fc0AY0levfM90QGD0Kv\\u002fktnJA\\u002f1BfXjrCcEDeyFpALc9zQMVKyzl2dHJAxy1FbIQSc0BC+jboehRzQDfO2oyLzntAJYcdyzQPeUCaI\\u002fMYQh94QGjuVBcWgXNABHFoylKAckCWJENWly5yQFvG9IEywXFANEhPu9+wckD0hYmkzvZ0QM60a7A7gn1AECYImpvGdkCyBi21z2t1QHAXf+fJMHJAMh3B1bUwfUChPSVATBx+QGDRotFC2IFA6YpYtwfZg0ASXMdsinODQAAAAAAAAAAAZWZOrGYCb0BHz18BJ9tvQD2+XbL\\u002fWXNA\\u002fsOcL9dEbUCXU7Mq8dduQAalQJbH02xAzGSN0od6aUDPAD0mgWp1QLarkgyAS3RA0XooHv7Ib0CiB+wVW+F3QAZpQ7DZ52pAsqzS60ZlcED4\\u002fqhm+DBxQIwpwX8uH39A8HlHILSchEBKavOFOHuCQB5YL5pomnVAdehR+231e0D3Y6Mw0y52QBu1TRjZZnZAuOI+FUphdUBORy70EM5zQGgobPGz03NAKT5l8JDec0DbwhpQs7Z1QOZFeTMNEXVAuTfFbQ2Vc0CJ\\u002fLkPl5tzQHWXsLgjZXNA6D41AhVwc0Bp8CDMi+dnQHGgd8ywxXpAf3\\u002fHoGIRdUBMnqWdDF5tQOS6rmfnKHdAtJkspjDPcUBlDDlkLj1gQLUJJ15cxV1Ao4JaHgRHXUCuo5D+zMphQDIW5v0pEF9AGKvCEKlZYEB2YxlH1mVgQPx+kt7ZQ2BA52Bw3jHmYUAfzoouP+JnQAPvrM\\u002fPTWRAJqcnDjISZEDJdYa8KnJeQAdNcHvVqWRAXfcvQDIKYEAfvEFgyRpgQLTb6E8vNV1AZTETMvM6b0DGJHqd8X10QFqtlBAqpnFANMUoaT3EcEDjpNI6pMxyQFns+FZWtXBAu2zOylchdUD27wpPmQ9wQAG0W5pAb3FA9X1y2p5bcUBfOKHQf35xQLB4eJK+xHNAxFPcyTWRZ0BenwZMPRFrQBn66MAOk2tApW\\u002fKMm+zZUAx6ZoEV0toQBfjyw3ZZ2xAH+5Ih3AdckAGXsxYJMJpQHCaleGo2mFARE6ChEolY0BIbK7GbxFiQIm\\u002fx2DuaGNAWNhmpxCLYkA5ntD8fRhfQGX2NOAqaXdA3bhvSOI5d0BSpVRDUCx3QI1pXJMjV3dAouaEsiXwfkAsSMnmp0B8QGju7rOyZn1APw\\u002f3002YdkBd0E8kUrx1QL8VsRhpqXZABNi76gIedUBw561PzWB3QOO2jfMM+XlAz7y9+uAJgEBpEVri6Mh5QL3w94KnEnhAcdPMLe6EdUBmTmWBi46BQFHq9oAUu4FAyLbn\\u002fi0ThUBJzGwJLMuGQD7PHMpTlIZAZWZOrGYCb0AAAAAAAAAAAFQDrLlRhF5AUNsJhv6XdkAT+8Hfg2NYQDgJ+CttUVdA\\u002f0bnn9D6YUDl0Zi33VFxQJAzL1pZgXxAwSQ\\u002fYokme0D2EmuQqxt0QJ9eFigSHn9ATUr0euu4dECWBymcol93QGgM0YcSaXlAE94Xxc8VfUAAf7yz64WDQPkR\\u002f2cjbYJA1FD9B+M8dEBtCrNwQPd5QJ859zCqWnZAgVHWG6pndkBCO3AQb+Z1QBXPkwOs53RA9yi0tDkAdUCh6a+XY\\u002fF0QL7nK+PcwXVAOJkY\\u002f+FMdUB6oQxO4s5zQLQEiyAGcXNA70n0Ots7c0CzKTd18X5zQCHoWKuMJWhAl4XF4hwxekAJA0M05J90QIOLnNz1vG1AiJ04Jo3qdkDc1dW91KxxQC9Lc+45nWZAUxz6sO2zY0BKVaeaWgplQL+hqab3jmlAXan82mHkZkDxTultCRJmQMgXM6bHT2ZAhQweSGLmZUCdHr6J7XlmQMgwyf3M8mxA\\u002f4HEDKJFakCGNUWh7ZBpQHzxAKAoQ2VAZWvUxThDaUCd+Snpi05lQHCgpAcpAmVAtJDILCWVZEAK28oPcEJvQIIi8hUQnHNAxjqx\\u002fZ2FcUA7l\\u002f3+aXFwQLyJPO7LfHJA6uu2kQG2cECBcMFIapF0QI9UmxfuCHBAOM3QE3AScUCUUdYxHhFxQP3jfpEyOnFA7nQMqOdmc0C0E+GrizRnQLLZTYXzrGlA\\u002fmF3zEjdaUBQm+O1sddlQKnVgMLYE2hAge\\u002fG\\u002fGZEa0DXDkRPt0dxQKiBUu4nWGlA1Brfip0gZ0ApybzjRJ1nQBF53kTMnWZA66x7jpwDZ0A\\u002f914XA01nQK9tI2RinWNA3SrBvjo5d0B0ss83qTJ3QBRyB0SJ1XZAthUFglIvd0BfChOmPZh+QIIJ60jExXxAqp\\u002ffP46IfECnwdHXqXN2QMlbmRUewHVAbpmeKaCedkBJ8gmkTRV1QLbgBtFuDHdATssvh+hGeUBQHtKPTc1+QKbGQRlfcndAbsY2vD\\u002f8dUDGNZ45gAx0QFis+RE2ZoBAoJWl13CogEDyV8zYUtSDQMOwLx9BiYVALlVB3P4+hUBHz18BJ9tvQFQDrLlRhF5AAAAAAAAAAACrDsdaspJ0QKVEAfgAn2BATWOT5RtoX0CpbKcDC25kQL0JkYua8W9AcqIYJpu4ekDHzsnQ7G54QCadSTNnlHFA\\u002fSCfKK51fEB5Mh6RtxJzQLbO0t\\u002f8lHVAgErbBGC7d0DJno7YGOB8QDY8pCxZ04JAoJrW25itgkCBGrbGDFV0QCOSF+ihi3hAj9eVueXOe0APrvftCzV7QHSrKCntrntA3vwFw32WfUApth4NevR8QEhHx\\u002fzFHnxACUp2lbx1ekBE513VqFp7QDL\\u002f+fD2dHpAiKTJgmj+dEAr+asUlt90QAF4nzcGw3VAPhNiY3B4c0CDd6NQt2R6QL2ziH+3XnZA8pmeUonAdED7pcrE64l4QJkNK7N\\u002fmnVAXqILHK\\u002fjeEDkNcj5CY13QLVVaVTHZ3ZAy5sx+x1UekDwGclE33t4QNk81HkV4HhAfMyQzwIKeUDKfxs0BCF4QFyXmFdgMXlArOXVgb58e0BZuKlG4gd6QALcerevbHlAoy\\u002fndg7Md0CXlRJXrW14QJhLlw5z8HZA0XgNZHdGdkD8xYth4wV3QJO4+6rEm3NAvyd4yAXtckBuhju6evdzQOAJ7RiZjHNAnoDceopUc0BPogFWQI50QC04Z3JzW3VAqR2tJMHUdkDAfyLw3VZ2QFcl3iOnU3dAyIF6kloBd0BZDH9H4Fl4QKTB9z79KHNA5DsaMjoXc0CQmypGM2RyQJBZwsJ\\u002fn3NAxEDNOpJpc0DgxWSM5gRzQItLSoNza3RAgERkPbVpdED8w5CS5eJ4QKnRt4gVG3lAnL\\u002ft+LoVeUADAb0DXCh5QHE3F9zaO3hASUO2GVpPdkCufmv9WrJ0QHVCvMeP8HRAFtfDiWXpc0BXtiRfGe51QGMbNgCymH1A7TBda25DfEAvG+GV7D51QJCOPIY4l3VA2\\u002fBjc0nSdECOq4K5y2d2QKT5J1bygXZAnJMBTBP+dUC5BMzxVbx4QI7rdKis7XxAf37rNdk1d0CHbNo6sxh3QOl+eJlMXHZAQ5C5BUhyf0AxzlsBcBiAQBPIag3MZINAetFBoCNYhUBIBtonNEuEQD2+XbL\\u002fWXNAUNsJhv6XdkCrDsdaspJ0QAAAAAAAAAAA28vrKp5TdUB+ExCAS5t1QCTE6ptuH3VAhiQA\\u002fccrc0APPlV9\\u002fAF6QLwGdGdw9XdAdIz+lu4idEAUG95AbCx7QIS0VQZpFXNA7uL4I7G1c0D1IEbNHk11QL86tIsFo35AdCC\\u002fCgpXhEB7QYM\\u002fqbCCQLA\\u002fTp0dkXVAT7wlMYw8e0AjX58RaUh3QGy9TcS8m3dA4hfn7tigdkA\\u002fOWrr\\u002fLR1QIFcuFGqdHVAuoZlOiqndUCiiuPYhJ92QIiKp\\u002fl7OHZAUJxWKjG2dECARRxV+\\u002fFzQB+9k7MqiXNAmQGHttawc0CcYVH8IGpkQAVroIh7Q3lA2pxJvqhkc0A7HQ6BeChpQHxjWa\\u002feZHVA2V9ylbnAb0BCvQ+9WgVgQKxwS\\u002f7QEF9ApSYVH\\u002ftmW0BIQ5i1l2pjQD05iX9mzmFAWmN0lL0aX0Cr9pyTGyJhQIR8aIKEXmJAkl8gwBm5YkBOUNW\\u002fypBqQDJOsm5sEWdAjYGf+VS6ZkBnUHl+PGtgQPjTh6Qx\\u002f2VAkGchuGfpXkDGbo0lPoxZQGWI8BmaQl1A8fbxiYILb0A4sRW3e9FzQA29hTIawHFA9iUjb\\u002f+mcEDlh4NXrG5yQJWHA+9QjHBA5DZKIwiRdECt+A0VQwRwQI+o2JzJDHFAm1ORqiBUcUDHEudbEQlxQBQXh4x1WXNA9yHbbN67ZED+l1KwnjloQI+TCh89n2hA5IdqqgS9YkDO6Ht7ArNmQK+Cw4Q0DmpAKIKkvUHXcEDXAYn6ji9nQFINDLfGSWFAEqtyf6w+YkBHIbsfNpNeQIxah+a9qmJAELxMBVOXX0Comy\\u002fsvqdZQBtxXycDa3dAGu+qXYUkd0BKaV2kA\\u002fF2QAe27UReSndA2PxJnIAlf0C32WVO8UV8QEKJ54MESXxATDG9T6ifdkCLFBg1R4Z1QBaaUEMgwXZAD23G81tNdUD9OXiw0113QBw7i1Y3C3pA+VT\\u002fMmBkf0BNdR6k3UF5QD52gzbbx3dAyaTyBpQ+dUD\\u002femXt3FWBQEKs3HN5qIFAZjEVaMndhEBtFPOmF7aGQMoATbkEXoZA\\u002fsOcL9dEbUAT+8Hfg2NYQKVEAfgAn2BA28vrKp5TdUAAAAAAAAAAABfyeGDqP1VA0Ix6LHiKYEDohc\\u002flrBNwQAcbqzIdR3xAT7P4D6WBekAKmNYSwfhyQCXXaX20mX5AyupgfOa1c0CTBWsXmqZ2QAmO9zwcwXhAqHpDFwFffkB3PfZujF6EQKIqgN3m24JASbslLPUwdUD7KuIkTHF7QLby2R0DEHZAoAhojdRGdkC9rrqukWN1QCl7ZDonOnRAMBLkPaQWdECoGlH47R10QGMrT9AVmXVAx3exAG0udUB50rF1WpVzQNGqEDSWcXNAycU4f3INc0BB42viFxpzQGF7VVFro2ZAauNe+dyZekBkxZDDN8N0QGX6sCLmT2xAhyPosK7kdkA3E2OvzGlxQDwukqLzBmBAdlAExnTKXUCbwTlyh\\u002f1cQEfuv0fjBmNAGIT9w6e1YUCFNvbyR75gQKE4vvCMaGFAN01kO3uQYUDTBngvNPhhQFpERlgxbmlAjtFRk1PSZUCVwAu3i5VlQFnDbob\\u002fKWBA91NZ7omgZUBGdQ3Y3N5fQHg9VcbJmltAD\\u002feo8wuGXEDbKyN+68BvQL6eur0VQ3RAnUuNGFXfcUAsdrqrgfdwQJtbPICj7HJANVvacwQFcUBamVbpzgh1QJSrg6xzaXBAM1GvTSKgcUCLnpbfIbxxQEEm0ixxtXFAK5zJV7r\\u002fc0BtIfVryUlmQDjWzpo2vGlAoUCIotc5akAQqOr9Z1JkQFGClIQgz2dAmzInSC1Wa0CnUJu6X35xQLsoI+rev2hAsRnLh1yZYUBHUDZj8HNiQKk5q9aJnmFAJFkdCf2yYkB+rGbbjsVhQEH0n1ehDV9AmjYS5ZUCd0BiSASwJe12QLspZZVgoXZAEI5ZWFj6dkDbB1jJa7F+QOPu2OBr5ntAYemiUjXGfEBU2EQisZN2QFHr1d\\u002fbnXVArG0YbxDBdkDk3wKMfFF1QCAocK00ZXdANn3FUrwMekBIEX3Agkt\\u002fQDMxex1l8XhAjUaZ2Gqad0CcuqYOuYd1QDiAJyI5i4FAhJJboT67gUCZzBzDru+EQFjGN\\u002fZFvIZAYzOUKmBvhkCXU7Mq8dduQDgJ+CttUVdATWOT5RtoX0B+ExCAS5t1QBfyeGDqP1VAAAAAAAAAAAA8N53b4p9cQFI1\\u002f4okZHBAlGN0jp4MfEBzU0ZY9Dp6QJke5Prn43JA3vU7TOhDfkD4FTWGKJtzQL1wQkvYa3ZAkvl7Ach2eEADPQy2cZt9QGQ49kkGpYNA3+awE7PIgkBBliLVLS51QCZofkmwIHpAQxwHvpwXd0C8BZGyXV93QM\\u002fgA8XPb3ZAvIc1aLN8dUDjdqAyGZl1QGmlvMujQXVAF6K5lqRqdkAg0mKPUFt2QMLzkMoT5nRA\\u002fgiiAEENdECCV1MeOvtzQAkwOGpGG3RA5i4lgHy3aECS8q1cwY14QBUEiHsQ4nJApTxv98IzbUBBEEq05hR1QCzmSOSkMXBA\\u002fcUYbD+mZkBCQfSgOw1lQMT3+hLBYWVAbwBJKzqLZ0AcgxK3fJ1mQO5xhn8wA2hA6DBWFW6raEAGo7spV9dmQKDp23i7bmdA7EFhg+s7bkAWSAHnR2ZpQOOqBAzMKGhAenwS1y78ZEA9iXmSFq9pQF\\u002ffJMtkZ2ZA\\u002for6\\u002fyXSY0BhsWGATpljQHols+qAwW5ADJVdTZBqc0B5Ycvbny1xQFAH2JtAU3BA+n69LYcgckCz8xqnnYpwQDpH3BZA0XNATGgyUtW4cEBCqWBBP6txQP8xbpWmsHFAmG6w3LmucUCi++b25ftzQOfMKdGF3WlAR9OhMe7ebECFrq\\u002fqt99sQEOd\\u002fKFcNGhA9leBKwlRa0DiRgqaioxtQDTJhMVya3JAfcVM2TKWbECn+0D0uTxoQBvNOZppnGlA\\u002flM5UAzPaUBdmv0RmhFrQAAwlgp+NWhApI2yWgpjZkDOOPV+CFF2QECQ+CUJzXVAJp8RsFaddUC+xvB+lRl2QONHUOu\\u002fdH1A2HM5r9VbekAz8frBTN17QAdNHTTVq3VApWO4zGWqdECeYQEVSml1QAVmJOFWYHRABt0JFLm3dUDO1llOxXJ4QOmmx9Q9kX5A3MgUd2P8d0ABzXNcWm52QDEURqJ44HNAsUDaX857gEBAor9HNbmAQEQwX4vqFIRAoBhGa1XkhUAB9+4hNI+FQAalQJbH02xA\\u002f0bnn9D6YUCpbKcDC25kQCTE6ptuH3VA0Ix6LHiKYEA8N53b4p9cQAAAAAAAAAAAoXDZPJ1lcEB0PrKWGjx7QIjkTaKZRXlApzw8C6PLckDxV7SZcxZ9QHsE+3QowHJA9\\u002ftRTuSldUAIY7zat0F3QHVhyL1D0nVAguBjknBQf0CFDP7mXKp+QOhtF7LKlHJA29jwK+z3ckAwgSXPK\\u002ft7QP6cqV7r3HpAFDjjtvWBe0AWcDfXOhp9QIVMzA2zY3xAzTuJY0PMe0BEAa7V4FZ6QLev1cRzynpAIr0F1T13eUBvjEuO2Ql1QFItXiazNHVAuQy+hLlqdkDYsayT365oQBiBBvTP+nRAiTFraTy4cEDflfobM0VtQD1Y1c\\u002fbM3JAg5S198N8bUD3OgQcLdR0QNGzIKbvanNAukb0pcCSckDNkRAMFWN2QAS0gutMZXRA9Ld0RTG8dEA2n\\u002fLI6h91QC\\u002fORujhR3RAezElF29RdUDXvxI1I7t4QOdyIe7\\u002fbXZAEnz5GEaqdUAWhcwctCB0QGuFgDYWNXVAM8BavW12c0BayzoFpN1xQCRR+HQr63JApV7Zl7o6b0DpoN+mQFBxQAyyzOrZonFALC0XNKb2bkCokXTfAV9xQAVUm7JSi3FARwKodSTrcEB5\\u002fN\\u002fr9fJxQFbGv2oL6XFAtLMtHpujckASNE+VaSxyQE6+TRfV6nJA6DRyMtDDZ0BJemIMY7lmQMPuGbdChmVAuW3ONmRKaUB5XMZ+ouVnQBFF0rCL42dA+wLf\\u002f8kSbEDHS0UmRQBsQDIBpvhAPnVASwuQA+rLdUAPh1+nDId0QA5O8iTgxHVAI\\u002fzeUMBpdEBUZj2w4CxxQHnTyQcoPXRANFT+jFF7c0BlpcicqcdzQKIfwNg44XNACnqS\\u002fprhfEBHD2pVOol6QKzeH6iZJHdAdd2l7msXdEDNmZg99TJzQETRXv0W0XNAU1nBr8+Bc0Bv5oR8U\\u002fJzQCXq2DUMOXZA8QShoJhpfUCYbvsiI5J2QOyHUynO8XVAtJAAjBZidEDbH3SsaTR\\u002fQJvculWu039AtUd1zMlJgkCtfIdGcz+EQFur+vROoYNAzGSN0od6aUDl0Zi33VFxQL0JkYua8W9AhiQA\\u002fccrc0Dohc\\u002flrBNwQFI1\\u002f4okZHBAoXDZPJ1lcEAAAAAAAAAAAD1Z7j7bI25AHrcKPxyqcEDrUFsTDMhlQN9tAV4nR3RA6Jo7\\u002fGfqZkDtIXBYNx5pQJ8CC3Q+n2xAX2OLbHqPdUBO+vnYY+F6QPE8IYvaantAxWAPVcx1eEA4Ot66P9d0QJI\\u002f5+jKh4FACxAn\\u002f4jJgEBFaqOj8k2BQNYYQG1vj4JASWt7rSfvgUBqDnJnGdKBQIUqeo+vroBA3oH3g9YJgUAiES5JuIaAQIrBYuB6K3xA1g8Q\\u002fa60fECSVYXkihN+QM2vUC0dfnhAsQt2YYyJeUAZRYMOfM14QP+Zshp4tXpA4nnvU9AtekBO3gzyyxt5QIaTfymPOIBAnnib\\u002fxH6fkCN08D4bpd+QFavxk+XuYBAr8qW23Nwf0A81ifymjOAQFMtUMqzXIBAGwO6aL\\u002fBf0Aqrg8WS0aAQAL4nxygZIFAQNeuVRtOgEAXTMta0\\u002fd\\u002fQCXJNlOQeH9A1aUgW8D9f0Bz+IzclMZ\\u002fQKDI3hJweX5Aw39Fxr2dfkAyXnZQXBx2QHMDBBbn\\u002fHVAgmuqbAqidkA39vedNXd1QM\\u002fn+2Evd3ZALavMlRe0d0DvAVFQ76x0QFz25v1HyXhAXQftAmDud0CKcFTtNoR4QEH1SKAbfHhA496VyHvQd0C5f4akt314QBXz5PK4ondAcU2gygqMdkBPuFTDMht5QBv3TjQoUXdAf9dyXU\\u002fTdkC5juCV2ql3QKGfgGM8m3lAPfztCBe8gEAW5S\\u002fdN\\u002f2AQOCFwCVjcIBA9v2J6EvjgEDCokhUyXqAQBXtY+0C131Ahpomdeq+dkBTEtCwxBp2QGE+YESd03ZAKHlc92kXdkARAX60Fi9\\u002fQBeCwZrR031A3lFDBE\\u002fUeUBmIwWUnR93QImp+VuBznZADFD3bfv6dUDXAAzQgCt2QOssKgba13VArLIjFUKJdkDHlkEv4eqAQNmhNNTI3XpAfxFlzoFIekBIlKB8mqV4QECBveZlcn5ACqfZezCCfkCmEP01kcWAQKZRIYhrhIJALgDTzGEegkDPAD0mgWp1QJAzL1pZgXxAcqIYJpu4ekAPPlV9\\u002fAF6QAcbqzIdR3xAlGN0jp4MfEB0PrKWGjx7QD1Z7j7bI25AAAAAAAAAAAAHiTSxHvhuQDFGz1LER3JAxlyRF2H\\u002fb0AYtbKvdaxwQP+uMdOzQG5At22Y6wWGbUC+RdAprrR0QG4Mq3GN5XpA71K68RwNfkBU45uEcRV4QDMyh6k203RAnYCs40kQgUBGozLI92yAQOt0PJb9+IBAJuT4zxcQgkAVcWcMbpeBQDxPJnmWUoFAV6oQdd9QgEBqXJaIycmAQLGXh2rmMoBAa4DANuIYfECrvSOsFod8QIzD62dik31AQ59w76sCd0DoAYy6SU15QB5mlwXxiHdAzywOg4LweEDk81mYJVF5QH\\u002fwekGMwXdA2aafjKv4fkDmfZnOant9QM9pv632QH1AZPN0YDsRgED+fpv1qlJ+QCmzOAmRYX9AZeUaQyPAf0D\\u002fCSJfUJp+QD+SVyziXn9AugCRNACzgECS47eHqTl\\u002fQNfl3hkJw35AdWAqXYc5fkCc68uxa\\u002fp+QIXJZUmnKX5AsC\\u002fEh2GjfEDf+RCQAQd9QCbO2du2sXZA3944hk2xdkBbpL4IPyh3QHBKpCvBLHZAr2GP\\u002fMIDd0DF1HK4W913QFFdJ0KMUnVABgS1QlfCd0Dbvx\\u002fzh+J2QND4jsVxqndAuhWfkypAd0AAAuf3QiJ3QKI4R2tXrHZA0kw6UYGodUDRX3W1Gb90QMbW5\\u002fWIMXdAXJm9lV19dUBJrB2n+CF1QOCpVo1TzHZA\\u002f2PGy3Y9eECZ41yU9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       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mt.tl.edistance(signatures, reference=None)\n",
    "mt.pl.distance_heatmap(signatures, groupby=\"Metadata_MOA\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q28",
   "metadata": {},
   "source": [
    "Mechanism blocks stand out along the diagonal (compounds that share a mechanism sit close) while the off-diagonal\n",
    "shows which mechanisms the assay cannot separate. This is the same structure the confusion matrix summarised, now\n",
    "laid out treatment by treatment."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q29",
   "metadata": {},
   "source": [
    "## Everything is on the object\n",
    "\n",
    "Nothing above returned a result that lives only in a notebook variable. Hits and effect sizes are on `adata`, the\n",
    "mechanism call is on `signatures`, and each result is a table under `uns[\"mantispy\"]`, beside the provenance of the\n",
    "step that wrote it."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q31",
   "metadata": {},
   "source": [
    "`mt.io.write` saves the object and every one of these tables in one `.h5ad`, and `mt.io.read` brings them back,\n",
    "the same file a scanpy user can open."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q32",
   "metadata": {},
   "source": [
    "## Where to go next\n",
    "\n",
    "Each modality has its own tutorial that goes deeper than this page:\n",
    "\n",
    "- **Compound screens**, [hits, effects and cell loss](compounds/hits.ipynb): activity, what moved, and whether a\n",
    "  hit is a phenotype or dead cells.\n",
    "- **Genetic screens**, [CRISPR knockouts](../case_studies/crispr.ipynb): which knockouts have a phenotype, and whether\n",
    "  the map recovers known biology.\n",
    "- **Single cells**, [what the well median hides](single_cells/heterogeneity.ipynb): the same questions asked below\n",
    "  the well.\n",
    "- **Across laboratories**, [cross-laboratory reproducibility](../case_studies/cross_laboratory.ipynb): does the screen\n",
    "  reproduce at another site.\n",
    "- **How-to recipes**, [from a CellProfiler run](data/cellprofiler.ipynb) and the other short data-loading\n",
    "  examples."
   ]
  }
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