{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3576925f",
   "metadata": {},
   "source": [
    "# Getting started: the NiSpace object\n",
    "\n",
    "This notebook introduces the core NiSpace API through a complete, step-by-step colocalization analysis. If you haven't already, have a look at the [Spatial Colocalization notebook](intro01_spatial_colocalizations.ipynb) for the conceptual background.\n",
    "\n",
    "We'll use a NeuroQuery meta-analytic map for \"pain\" as our input and test whether it colocalizes with a set of PET-derived neurotransmitter receptor maps. This is a clean, self-contained example with a nice biological story."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6d3262c2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:02:49.145848Z",
     "iopub.status.busy": "2026-06-01T13:02:49.145651Z",
     "iopub.status.idle": "2026-06-01T13:02:49.195469Z",
     "shell.execute_reply": "2026-06-01T13:02:49.195108Z"
    }
   },
   "outputs": [],
   "source": [
    "# make progress bars render as text in the docs\n",
    "import tqdm.notebook\n",
    "tqdm.notebook.tqdm = tqdm.tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e5b0ea4",
   "metadata": {},
   "source": [
    "## The input map: a NeuroQuery pain map\n",
    "\n",
    "We need a brain map to start with. I downloaded a meta-analytic map from [NeuroQuery](https://neuroquery.org/query?text=pain) — a tool that generates brain activation maps from text queries against the neuroimaging literature. The map for \"pain\" is a z-score image reflecting how consistently the pain literature reports activation across brain regions.\n",
    "\n",
    "Technically this is not a T-map from a single study, but it serves our purpose perfectly: it's a plausible spatial pattern of pain-related brain activity, and it lives in MNI space like all our reference data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1121ec75",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:02:49.197172Z",
     "iopub.status.busy": "2026-06-01T13:02:49.197040Z",
     "iopub.status.idle": "2026-06-01T13:02:52.249159Z",
     "shell.execute_reply": "2026-06-01T13:02:52.248736Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mWARNING | 01/06/26 15:02:51 | nispace.plotting: Brain plotting in NiSpace is experimental. If things look off, feel free to raise a GitHub issue!\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 720x180 with 6 Axes>, [<Axes: >])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x180 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from nispace.io import load_img\n",
    "from nispace.plotting import brainplot\n",
    "\n",
    "# load the pain map\n",
    "pain_map = load_img(\"neuroquery/pain.nii.gz\")\n",
    "\n",
    "# plot it\n",
    "brainplot(pain_map, title=\"Pain (NeuroQuery)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea6671ec",
   "metadata": {},
   "source": [
    "The map shows the expected pattern: activation in regions associated with pain processing, including the insula, anterior cingulate cortex, and somatosensory cortex.\n",
    "\n",
    "## Reference data: PET receptor maps\n",
    "\n",
    "For our reference maps, we'll use NiSpace's curated PET receptor dataset. This collection contains group-average receptor density maps for a wide range of neurotransmitter receptors and transporters, derived from PET studies in healthy subjects.\n",
    "\n",
    "We fetch the data already parcellated into our target parcellation. This is much faster than loading the volumetric images and parcellating them on the fly — NiSpace ships pre-parcellated versions of all reference datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "897e609c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:02:52.250820Z",
     "iopub.status.busy": "2026-06-01T13:02:52.250615Z",
     "iopub.status.idle": "2026-06-01T13:02:52.270936Z",
     "shell.execute_reply": "2026-06-01T13:02:52.270666Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.datasets: Loading pet maps.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.datasets: Loading integrated collection 'UniqueTracers' for dataset 'pet'.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.datasets: Filtering maps by collection.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.datasets: Loading data parcellated with 'Schaefer200Parcels7Networks'\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PET DataFrame: 29 maps x 200 parcels\n"
     ]
    },
    {
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       "      <td>0.518188</td>\n",
       "      <td>0.542567</td>\n",
       "      <td>0.537646</td>\n",
       "      <td>0.528138</td>\n",
       "      <td>0.485648</td>\n",
       "      <td>0.587230</td>\n",
       "      <td>0.521042</td>\n",
       "      <td>0.562560</td>\n",
       "      <td>0.627642</td>\n",
       "      <td>0.603664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016</th>\n",
       "      <td>0.651551</td>\n",
       "      <td>0.606582</td>\n",
       "      <td>0.616104</td>\n",
       "      <td>0.570561</td>\n",
       "      <td>0.536395</td>\n",
       "      <td>0.509607</td>\n",
       "      <td>0.563901</td>\n",
       "      <td>0.675601</td>\n",
       "      <td>0.618253</td>\n",
       "      <td>0.649548</td>\n",
       "      <td>...</td>\n",
       "      <td>0.702999</td>\n",
       "      <td>0.730201</td>\n",
       "      <td>0.606722</td>\n",
       "      <td>0.638996</td>\n",
       "      <td>0.551071</td>\n",
       "      <td>0.654981</td>\n",
       "      <td>0.587189</td>\n",
       "      <td>0.631831</td>\n",
       "      <td>0.721953</td>\n",
       "      <td>0.708995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 200 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                            hemi-L_div-Vis_lab-1  \\\n",
       "set     map                                                                        \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...              0.677147   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...              0.602272   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016              0.651551   \n",
       "\n",
       "                                                            hemi-L_div-Vis_lab-2  \\\n",
       "set     map                                                                        \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...              0.666611   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...              0.624987   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016              0.606582   \n",
       "\n",
       "                                                            hemi-L_div-Vis_lab-3  \\\n",
       "set     map                                                                        \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...              0.633823   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...              0.600528   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016              0.616104   \n",
       "\n",
       "                                                            hemi-L_div-Vis_lab-4  \\\n",
       "set     map                                                                        \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...              0.712379   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...              0.611747   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016              0.570561   \n",
       "\n",
       "                                                            hemi-L_div-Vis_lab-5  \\\n",
       "set     map                                                                        \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...              0.604150   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...              0.642787   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016              0.536395   \n",
       "\n",
       "                                                            hemi-L_div-Vis_lab-6  \\\n",
       "set     map                                                                        \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...              0.590683   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...              0.490786   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016              0.509607   \n",
       "\n",
       "                                                            hemi-L_div-Vis_lab-7  \\\n",
       "set     map                                                                        \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...              0.707724   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...              0.707251   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016              0.563901   \n",
       "\n",
       "                                                            hemi-L_div-Vis_lab-8  \\\n",
       "set     map                                                                        \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...              0.684077   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...              0.654593   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016              0.675601   \n",
       "\n",
       "                                                            hemi-L_div-Vis_lab-9  \\\n",
       "set     map                                                                        \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...              0.621863   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...              0.710693   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016              0.618253   \n",
       "\n",
       "                                                            hemi-L_div-Vis_lab-10  \\\n",
       "set     map                                                                         \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...               0.791744   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...               0.726193   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016               0.649548   \n",
       "\n",
       "                                                            ...  \\\n",
       "set     map                                                 ...   \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...  ...   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...  ...   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016  ...   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PFCm+1  \\\n",
       "set     map                                                                                 \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                       0.694831   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                       0.518188   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                       0.702999   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PFCm+2  \\\n",
       "set     map                                                                                 \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                       0.702473   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                       0.542567   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                       0.730201   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PFCm+3  \\\n",
       "set     map                                                                                 \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                       0.573170   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                       0.537646   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                       0.606722   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PFCm+4  \\\n",
       "set     map                                                                                 \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                       0.615872   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                       0.528138   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                       0.638996   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PFCm+5  \\\n",
       "set     map                                                                                 \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                       0.563187   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                       0.485648   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                       0.551071   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PFCm+6  \\\n",
       "set     map                                                                                 \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                       0.712010   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                       0.587230   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                       0.654981   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PFCm+7  \\\n",
       "set     map                                                                                 \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                       0.677833   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                       0.521042   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                       0.587189   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PCC+1  \\\n",
       "set     map                                                                                \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                      0.759205   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                      0.562560   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                      0.631831   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PCC+2  \\\n",
       "set     map                                                                                \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                      0.874840   \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                      0.627642   \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                      0.721953   \n",
       "\n",
       "                                                            hemi-R_div-Default_lab-PCC+3  \n",
       "set     map                                                                               \n",
       "General target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...                      0.805161  \n",
       "        target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...                      0.603664  \n",
       "        target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016                      0.708995  \n",
       "\n",
       "[3 rows x 200 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from nispace.datasets import fetch_reference\n",
    "\n",
    "# fetch the PET maps, pre-parcellated into Schaefer200\n",
    "# collection=\"UniqueTracers\" picks one representative tracer per receptor target\n",
    "pet_maps = fetch_reference(\n",
    "    \"pet\",\n",
    "    parcellation=\"Schaefer200\",\n",
    "    collection=\"UniqueTracers\",\n",
    "    print_references=False  # suppress the long reference list for now\n",
    ")\n",
    "\n",
    "print(f\"PET DataFrame: {pet_maps.shape[0]} maps x {pet_maps.shape[1]} parcels\")\n",
    "pet_maps.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ac60d8a",
   "metadata": {},
   "source": [
    "The DataFrame has a two-level index: the first level is the neurotransmitter system (\"set\"), the second is the full tracer identifier. These sets are used later for X-Set Enrichment Analysis ([XSEA notebook](intro10_xsea.ipynb)) — for now we just treat the whole thing as a collection of maps.\n",
    "\n",
    "## Initializing the NiSpace object\n",
    "\n",
    "NiSpace follows an object-oriented design. We first create a `NiSpace` instance, passing all the data and configuration options. Processing happens later when we call the analysis methods.\n",
    "\n",
    "The two central arguments are:\n",
    "- `x`: the reference maps (here: PET receptor maps)\n",
    "- `y`: the input map(s) we want to analyze (here: the pain map)\n",
    "\n",
    "We also specify the parcellation, which tells NiSpace how to parcellate `y` (since it's a volumetric NIfTI image) and how to align it with `x` (which is already a parcellated DataFrame)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b344d86b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:02:52.272278Z",
     "iopub.status.busy": "2026-06-01T13:02:52.272174Z",
     "iopub.status.idle": "2026-06-01T13:02:52.274228Z",
     "shell.execute_reply": "2026-06-01T13:02:52.274011Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<nispace.api.NiSpace object at 0x168d168e0>\n"
     ]
    }
   ],
   "source": [
    "from nispace.api import NiSpace\n",
    "\n",
    "nsp = NiSpace(\n",
    "    x=pet_maps,        # reference maps\n",
    "    y=pain_map,        # input map — will be parcellated automatically\n",
    "    y_labels=\"Pain\",   # a name for our input map\n",
    "    parcellation=\"Schaefer200\",\n",
    "    n_proc=4,          # use 4 parallel processes where possible\n",
    "    seed=42            # for reproducibility\n",
    ")\n",
    "\n",
    "print(nsp)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4038e15b",
   "metadata": {},
   "source": [
    "## Fitting: parcellation and data ingestion\n",
    "\n",
    "Calling `fit()` is where actual data processing begins. For the pain map (a NIfTI image), this means parcellating it into the 200 Schaefer regions. For the PET maps (already a DataFrame), it validates and stores the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "88570d64",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:02:52.275487Z",
     "iopub.status.busy": "2026-06-01T13:02:52.275368Z",
     "iopub.status.idle": "2026-06-01T13:02:56.676041Z",
     "shell.execute_reply": "2026-06-01T13:02:56.675690Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.api: *** NiSpace.fit() - Data extraction and preparation. ***\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.core.parcellation: Building multi-space Parcellation for 'Schaefer200Parcels7Networks' from library.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.core.parcellation: Available spaces: MNI152NLin2009cAsym, MNI152NLin6Asym, fsaverage, fsLR\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.core.parcellation: Parcellation 'Schaefer200Parcels7Networks': validation passed.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.core.parcellation: Lazy-loading parcellation image for space 'MNI152NLin2009cAsym'.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.core.parcellation: Parcellation 'Schaefer200Parcels7Networks': active space set to 'MNI152NLin2009cAsym'.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.api: Checking input data for 'x' (should be, e.g., PET data):\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.io: Input type: DataFrame, assuming parcellated data with shape (n_files/subjects/etc, n_parcels).\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mWARNING | 01/06/26 15:02:52 | nispace.io: Parcellated data contains nan values!\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.api: Got 'x' data for 29 x 200 parcels.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.api: Checking input data for 'y' (should be, e.g., subject data):\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.io: Input type: list, assuming imaging data.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.io: Background (bg) handling: ignoring bg: True (bg value: ['auto', 0.0]); dropping bg parcels: False\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:52 | nispace.io: Parcellating imaging data.\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Parcellating (4 proc):   0%|                                                                                                                                     | 0/1 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Parcellating (4 proc): 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 100.79it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:56 | nispace.api: Got 'y' data for 1 x 200 parcels.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:56 | nispace.api: Z-standardizing 'X' data.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parcellated pain map:\n",
      "\u001b[32mINFO | 01/06/26 15:02:56 | nispace.api: Returning Y dataframe: \n",
      "| Y_TRANSFORM | \n",
      "| False       | \u001b[0m\n"
     ]
    },
    {
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       "      <th>hemi-L_div-Vis_lab-1</th>\n",
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       "      <th>hemi-R_div-Default_lab-PCC+3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Pain</th>\n",
       "      <td>-0.436623</td>\n",
       "      <td>-1.075635</td>\n",
       "      <td>-0.893094</td>\n",
       "      <td>-0.887707</td>\n",
       "      <td>-1.139506</td>\n",
       "      <td>-1.259002</td>\n",
       "      <td>-1.339256</td>\n",
       "      <td>-1.083586</td>\n",
       "      <td>-1.389717</td>\n",
       "      <td>-0.828569</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.463824</td>\n",
       "      <td>-0.154211</td>\n",
       "      <td>0.643321</td>\n",
       "      <td>-0.584073</td>\n",
       "      <td>-0.205924</td>\n",
       "      <td>0.174392</td>\n",
       "      <td>0.172215</td>\n",
       "      <td>-0.319737</td>\n",
       "      <td>-0.818837</td>\n",
       "      <td>-0.344202</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 200 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      hemi-L_div-Vis_lab-1  hemi-L_div-Vis_lab-2  hemi-L_div-Vis_lab-3  \\\n",
       "Pain             -0.436623             -1.075635             -0.893094   \n",
       "\n",
       "      hemi-L_div-Vis_lab-4  hemi-L_div-Vis_lab-5  hemi-L_div-Vis_lab-6  \\\n",
       "Pain             -0.887707             -1.139506             -1.259002   \n",
       "\n",
       "      hemi-L_div-Vis_lab-7  hemi-L_div-Vis_lab-8  hemi-L_div-Vis_lab-9  \\\n",
       "Pain             -1.339256             -1.083586             -1.389717   \n",
       "\n",
       "      hemi-L_div-Vis_lab-10  ...  hemi-R_div-Default_lab-PFCm+1  \\\n",
       "Pain              -0.828569  ...                      -0.463824   \n",
       "\n",
       "      hemi-R_div-Default_lab-PFCm+2  hemi-R_div-Default_lab-PFCm+3  \\\n",
       "Pain                      -0.154211                       0.643321   \n",
       "\n",
       "      hemi-R_div-Default_lab-PFCm+4  hemi-R_div-Default_lab-PFCm+5  \\\n",
       "Pain                      -0.584073                      -0.205924   \n",
       "\n",
       "      hemi-R_div-Default_lab-PFCm+6  hemi-R_div-Default_lab-PFCm+7  \\\n",
       "Pain                       0.174392                       0.172215   \n",
       "\n",
       "      hemi-R_div-Default_lab-PCC+1  hemi-R_div-Default_lab-PCC+2  \\\n",
       "Pain                     -0.319737                     -0.818837   \n",
       "\n",
       "      hemi-R_div-Default_lab-PCC+3  \n",
       "Pain                     -0.344202  \n",
       "\n",
       "[1 rows x 200 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nsp.fit()\n",
    "\n",
    "# inspect the parcellated pain map\n",
    "print(\"Parcellated pain map:\")\n",
    "nsp.get_y()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1052d55c",
   "metadata": {},
   "source": [
    "The parcellated data is stored internally. `get_y()` returns the input maps, `get_x()` returns the reference maps — both as DataFrames with maps in rows and parcels in columns.\n",
    "\n",
    "## Colocalization\n",
    "\n",
    "Now for the core step: computing correlations between the pain map and each PET receptor map. We use Spearman rank correlation, which is robust to outliers and doesn't assume normally distributed data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "12231b33",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:02:56.677901Z",
     "iopub.status.busy": "2026-06-01T13:02:56.677767Z",
     "iopub.status.idle": "2026-06-01T13:02:59.351354Z",
     "shell.execute_reply": "2026-06-01T13:02:59.350977Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:56 | nispace.api: *** NiSpace.colocalize() - Estimating X & Y colocalizations. ***\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:56 | nispace.api: Running 'spearman' colocalization.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:56 | nispace.api: Pre-ranking X and Y data.\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Colocalizing (spearman, 4 proc):   0%|                                                                                                                           | 0/1 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Colocalizing (spearman, 4 proc): 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1451.32it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.api: Returning colocalizations: \n",
      "| METHOD   | XSEA  | X_REDUCTION | Y_TRANSFORM | \n",
      "| spearman | False | False       | False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results: 1 input maps x 29 reference maps\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Pain</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>set</th>\n",
       "      <th>map</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Noradrenaline/Acetylcholine</th>\n",
       "      <th>target-VAChT_tracer-feobv_n-18_dx-hc_pub-aghourian2017</th>\n",
       "      <td>0.435971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Opioids/Endocannabinoids</th>\n",
       "      <th>target-KOR_tracer-ly2795050_n-28_dx-hc_pub-vijay2018</th>\n",
       "      <td>0.339014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Noradrenaline/Acetylcholine</th>\n",
       "      <th>target-NET_tracer-mrb_n-10_dx-hc_pub-hesse2017</th>\n",
       "      <td>0.309315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Histamine</th>\n",
       "      <th>target-H3_tracer-gsk189254_n-8_dx-hc_pub-gallezot2017</th>\n",
       "      <td>0.304823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Glutamate</th>\n",
       "      <th>target-mGluR5_tracer-abp688_n-73_dx-hc_pub-smart2019</th>\n",
       "      <td>0.219451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serotonin</th>\n",
       "      <th>target-5HTT_tracer-dasb_n-18_dx-hc_pub-savli2012</th>\n",
       "      <td>0.176491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Opioids/Endocannabinoids</th>\n",
       "      <th>target-MOR_tracer-carfentanil_n-204_dx-hc_pub-kantonen2020</th>\n",
       "      <td>0.151909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dopamine</th>\n",
       "      <th>target-DAT_tracer-fpcit_n-174_dx-hc_pub-dukart2018</th>\n",
       "      <td>0.129229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GABA</th>\n",
       "      <th>target-GABAa5_tracer-ro154513_n-10_dx-hc_pub-lukow2022</th>\n",
       "      <td>0.111743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Opioids/Endocannabinoids</th>\n",
       "      <th>target-CB1_tracer-omar_n-77_dx-hc_pub-normandin2015</th>\n",
       "      <td>0.102278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dopamine</th>\n",
       "      <th>target-D1_tracer-sch23390_n-13_dx-hc_pub-kaller2017</th>\n",
       "      <td>0.078620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serotonin</th>\n",
       "      <th>target-5HT1a_tracer-way100635_n-35_dx-hc_pub-savli2012</th>\n",
       "      <td>0.073410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General</th>\n",
       "      <th>target-VMAT2_tracer-dtbz_n-76_dx-hc_pub-larsen2020</th>\n",
       "      <td>0.062397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dopamine</th>\n",
       "      <th>target-D23_tracer-flb457_n-55_dx-hc_pub-sandiego2015</th>\n",
       "      <td>0.059017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Noradrenaline/Acetylcholine</th>\n",
       "      <th>target-A4B2_tracer-flubatine_n-30_dx-hc_pub-hillmer2016</th>\n",
       "      <td>0.036321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dopamine</th>\n",
       "      <th>target-FDOPA_tracer-fluorodopa_n-12_dx-hc_pub-garciagomez2018</th>\n",
       "      <td>-0.000303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General</th>\n",
       "      <th>target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016</th>\n",
       "      <td>-0.068091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serotonin</th>\n",
       "      <th>target-5HT4_tracer-sb207145_n-59_dx-hc_pub-beliveau2017</th>\n",
       "      <td>-0.089016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Noradrenaline/Acetylcholine</th>\n",
       "      <th>target-M1_tracer-lsn3172176_n-24_dx-hc_pub-naganawa2020</th>\n",
       "      <td>-0.122528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Glutamate</th>\n",
       "      <th>target-NMDA_tracer-ge179_n-29_dx-hc_pub-galovic2021</th>\n",
       "      <td>-0.127164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Immunity</th>\n",
       "      <th>target-TSPO_tracer-pbr28_n-6_dx-hc_pub-lois2018</th>\n",
       "      <td>-0.134217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target-COX1_tracer-ps13_n-11_dx-hc_pub-kim2020</th>\n",
       "      <td>-0.142131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">General</th>\n",
       "      <th>target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castrillon2023</th>\n",
       "      <td>-0.162803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target-HDAC_tracer-martinostat_n-8_dx-hc_pub-wey2016</th>\n",
       "      <td>-0.170727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GABA</th>\n",
       "      <th>target-GABAa_tracer-flumazenil_n-6_dx-hc_pub-dukart2018</th>\n",
       "      <td>-0.202272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serotonin</th>\n",
       "      <th>target-5HT6_tracer-gsk215083_n-30_dx-hc_pub-radhakrishnan2018</th>\n",
       "      <td>-0.264142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General</th>\n",
       "      <th>target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith2023</th>\n",
       "      <td>-0.274733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Serotonin</th>\n",
       "      <th>target-5HT1b_tracer-p943_n-23_dx-hc_pub-savli2012</th>\n",
       "      <td>-0.316360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target-5HT2a_tracer-altanserin_n-19_dx-hc_pub-savli2012</th>\n",
       "      <td>-0.328132</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                    Pain\n",
       "set                         map                                                         \n",
       "Noradrenaline/Acetylcholine target-VAChT_tracer-feobv_n-18_dx-hc_pub-aghour...  0.435971\n",
       "Opioids/Endocannabinoids    target-KOR_tracer-ly2795050_n-28_dx-hc_pub-vija...  0.339014\n",
       "Noradrenaline/Acetylcholine target-NET_tracer-mrb_n-10_dx-hc_pub-hesse2017      0.309315\n",
       "Histamine                   target-H3_tracer-gsk189254_n-8_dx-hc_pub-gallez...  0.304823\n",
       "Glutamate                   target-mGluR5_tracer-abp688_n-73_dx-hc_pub-smar...  0.219451\n",
       "Serotonin                   target-5HTT_tracer-dasb_n-18_dx-hc_pub-savli2012    0.176491\n",
       "Opioids/Endocannabinoids    target-MOR_tracer-carfentanil_n-204_dx-hc_pub-k...  0.151909\n",
       "Dopamine                    target-DAT_tracer-fpcit_n-174_dx-hc_pub-dukart2018  0.129229\n",
       "GABA                        target-GABAa5_tracer-ro154513_n-10_dx-hc_pub-lu...  0.111743\n",
       "Opioids/Endocannabinoids    target-CB1_tracer-omar_n-77_dx-hc_pub-normandin...  0.102278\n",
       "Dopamine                    target-D1_tracer-sch23390_n-13_dx-hc_pub-kaller...  0.078620\n",
       "Serotonin                   target-5HT1a_tracer-way100635_n-35_dx-hc_pub-sa...  0.073410\n",
       "General                     target-VMAT2_tracer-dtbz_n-76_dx-hc_pub-larsen2020  0.062397\n",
       "Dopamine                    target-D23_tracer-flb457_n-55_dx-hc_pub-sandieg...  0.059017\n",
       "Noradrenaline/Acetylcholine target-A4B2_tracer-flubatine_n-30_dx-hc_pub-hil...  0.036321\n",
       "Dopamine                    target-FDOPA_tracer-fluorodopa_n-12_dx-hc_pub-g... -0.000303\n",
       "General                     target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016 -0.068091\n",
       "Serotonin                   target-5HT4_tracer-sb207145_n-59_dx-hc_pub-beli... -0.089016\n",
       "Noradrenaline/Acetylcholine target-M1_tracer-lsn3172176_n-24_dx-hc_pub-naga... -0.122528\n",
       "Glutamate                   target-NMDA_tracer-ge179_n-29_dx-hc_pub-galovic... -0.127164\n",
       "Immunity                    target-TSPO_tracer-pbr28_n-6_dx-hc_pub-lois2018    -0.134217\n",
       "                            target-COX1_tracer-ps13_n-11_dx-hc_pub-kim2020     -0.142131\n",
       "General                     target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril... -0.162803\n",
       "                            target-HDAC_tracer-martinostat_n-8_dx-hc_pub-we... -0.170727\n",
       "GABA                        target-GABAa_tracer-flumazenil_n-6_dx-hc_pub-du... -0.202272\n",
       "Serotonin                   target-5HT6_tracer-gsk215083_n-30_dx-hc_pub-rad... -0.264142\n",
       "General                     target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith... -0.274733\n",
       "Serotonin                   target-5HT1b_tracer-p943_n-23_dx-hc_pub-savli2012  -0.316360\n",
       "                            target-5HT2a_tracer-altanserin_n-19_dx-hc_pub-s... -0.328132"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nsp.colocalize(\"spearman\")\n",
    "\n",
    "# get the results\n",
    "colocs = nsp.get_colocalizations()\n",
    "print(f\"Results: {colocs.shape[0]} input maps x {colocs.shape[1]} reference maps\")\n",
    "\n",
    "# show sorted by colocalization value\n",
    "colocs.T.sort_values(by=\"Pain\", ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e0b763d",
   "metadata": {},
   "source": [
    "The result is a DataFrame with one row per input map (here: \"Pain\") and one column per reference map. The values are Spearman ρ.\n",
    "\n",
    "We can see which receptors show the strongest positive and negative colocalizations. But these bare correlation values don't come with reliable p-values yet — we haven't accounted for spatial autocorrelation. That's where permutation testing comes in.\n",
    "\n",
    "## Permutation testing\n",
    "\n",
    "We call `permute()` with `\"maps\"` to generate spatially-constrained null versions of the PET maps and recompute correlations 10,000 times. This gives us an empirical null distribution for each receptor.\n",
    "\n",
    "We pass `p_tails=\"upper\"` because our hypothesis is directional: we expect *positive* colocalizations with receptors involved in pain processing (opioids, noradrenergic/cholinergic pathways).\n",
    "\n",
    "Null model details are covered in the [Null Models notebook](intro05_null_models.ipynb). For now, just note that by default NiSpace uses spin-based surrogate maps if possible (Alexander-Bloch method), which preserve the spatial autocorrelation of the original data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b4360716",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:02:59.352949Z",
     "iopub.status.busy": "2026-06-01T13:02:59.352823Z",
     "iopub.status.idle": "2026-06-01T13:03:03.439422Z",
     "shell.execute_reply": "2026-06-01T13:03:03.439133Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.api: *** NiSpace.permute() - Estimate exact non-parametric p values. ***\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.api: Permutation of: X maps.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.api: Using default null method 'alexander_bloch' (parcellation null space: 'fsLR').\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.core.parcellation: Lazy-loading parcellation image for space 'fsLR'.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.api: Loading observed colocalizations (method = 'spearman').\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.api: Returning colocalizations: \n",
      "| METHOD   | XSEA  | X_REDUCTION | Y_TRANSFORM | \n",
      "| spearman | False | False       | False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.api: Generating permuted X maps.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.core.permute: No null maps found.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.core.permute: Generating null maps (n = 1000, null_method = 'alexander_bloch').\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.core.parcellation: Lazy-loading parcellation image for space 'fsaverage'.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.nulls: Null map generation: Assuming n = 29 data vector(s) for n = 200 parcels.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.nulls: Using provided precomputed spin matrix.\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Spin null maps:   0%|                                                                                                                                           | 0/29 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Spin null maps:  83%|██████████████████████████████████████████████████████████████████████████████████████████████████████████▊                      | 24/29 [00:00<00:00, 233.97it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Spin null maps: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 29/29 [00:00<00:00, 234.44it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.nulls: Null data generation finished.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.core.permute: Z-standardizing null maps.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:02:59 | nispace.api: Pre-ranking X and Y (null) data.\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Processing null arrays (4 proc):   0%|                                                                                                                        | 0/1000 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Processing null arrays (4 proc):   1%|▉                                                                                                               | 8/1000 [00:00<01:56,  8.50it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Processing null arrays (4 proc):  20%|█████████████████████▊                                                                                       | 200/1000 [00:01<00:03, 258.59it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Processing null arrays (4 proc): 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:01<00:00, 888.56it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Null colocalizations (spearman, 4 proc):   0%|                                                                                                                | 0/1000 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Null colocalizations (spearman, 4 proc):  50%|██████████████████████████████████████████████████▍                                                 | 504/1000 [00:00<00:00, 4724.59it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Null colocalizations (spearman, 4 proc): 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:00<00:00, 7792.89it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.core.permute: Calculating exact p-values (tails = {'rho': 'upper'}).\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: *** NiSpace.correct_p() - Correct p values for multiple comparisons. ***\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Correction method: 'meff_galwey', alpha: 0.05, dimension: 'array'.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Returning X dataframe: \n",
      "| X_REDUCTION | \n",
      "| False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Meff_X (galwey) = 12.28 (from 29 maps).\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Returning p values: \n",
      "| METHOD   | PERMUTE_WHAT | XSEA  | MC_METHOD | X_REDUCTION | Y_TRANSFORM | \n",
      "| spearman | xmaps        | False | None      | False       | False       | \u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Pain</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>set</th>\n",
       "      <th>map</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Noradrenaline/Acetylcholine</th>\n",
       "      <th>target-VAChT_tracer-feobv_n-18_dx-hc_pub-aghourian2017</th>\n",
       "      <td>0.020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Opioids/Endocannabinoids</th>\n",
       "      <th>target-KOR_tracer-ly2795050_n-28_dx-hc_pub-vijay2018</th>\n",
       "      <td>0.031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Noradrenaline/Acetylcholine</th>\n",
       "      <th>target-NET_tracer-mrb_n-10_dx-hc_pub-hesse2017</th>\n",
       "      <td>0.068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Histamine</th>\n",
       "      <th>target-H3_tracer-gsk189254_n-8_dx-hc_pub-gallezot2017</th>\n",
       "      <td>0.075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Glutamate</th>\n",
       "      <th>target-mGluR5_tracer-abp688_n-73_dx-hc_pub-smart2019</th>\n",
       "      <td>0.167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serotonin</th>\n",
       "      <th>target-5HTT_tracer-dasb_n-18_dx-hc_pub-savli2012</th>\n",
       "      <td>0.227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Opioids/Endocannabinoids</th>\n",
       "      <th>target-MOR_tracer-carfentanil_n-204_dx-hc_pub-kantonen2020</th>\n",
       "      <td>0.254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dopamine</th>\n",
       "      <th>target-DAT_tracer-fpcit_n-174_dx-hc_pub-dukart2018</th>\n",
       "      <td>0.272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Opioids/Endocannabinoids</th>\n",
       "      <th>target-CB1_tracer-omar_n-77_dx-hc_pub-normandin2015</th>\n",
       "      <td>0.325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GABA</th>\n",
       "      <th>target-GABAa5_tracer-ro154513_n-10_dx-hc_pub-lukow2022</th>\n",
       "      <td>0.334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dopamine</th>\n",
       "      <th>target-D1_tracer-sch23390_n-13_dx-hc_pub-kaller2017</th>\n",
       "      <td>0.347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General</th>\n",
       "      <th>target-VMAT2_tracer-dtbz_n-76_dx-hc_pub-larsen2020</th>\n",
       "      <td>0.376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serotonin</th>\n",
       "      <th>target-5HT1a_tracer-way100635_n-35_dx-hc_pub-savli2012</th>\n",
       "      <td>0.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dopamine</th>\n",
       "      <th>target-D23_tracer-flb457_n-55_dx-hc_pub-sandiego2015</th>\n",
       "      <td>0.410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Noradrenaline/Acetylcholine</th>\n",
       "      <th>target-A4B2_tracer-flubatine_n-30_dx-hc_pub-hillmer2016</th>\n",
       "      <td>0.443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dopamine</th>\n",
       "      <th>target-FDOPA_tracer-fluorodopa_n-12_dx-hc_pub-garciagomez2018</th>\n",
       "      <td>0.448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General</th>\n",
       "      <th>target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016</th>\n",
       "      <td>0.652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serotonin</th>\n",
       "      <th>target-5HT4_tracer-sb207145_n-59_dx-hc_pub-beliveau2017</th>\n",
       "      <td>0.657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Immunity</th>\n",
       "      <th>target-TSPO_tracer-pbr28_n-6_dx-hc_pub-lois2018</th>\n",
       "      <td>0.731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General</th>\n",
       "      <th>target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castrillon2023</th>\n",
       "      <td>0.745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Noradrenaline/Acetylcholine</th>\n",
       "      <th>target-M1_tracer-lsn3172176_n-24_dx-hc_pub-naganawa2020</th>\n",
       "      <td>0.756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Glutamate</th>\n",
       "      <th>target-NMDA_tracer-ge179_n-29_dx-hc_pub-galovic2021</th>\n",
       "      <td>0.761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Immunity</th>\n",
       "      <th>target-COX1_tracer-ps13_n-11_dx-hc_pub-kim2020</th>\n",
       "      <td>0.783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GABA</th>\n",
       "      <th>target-GABAa_tracer-flumazenil_n-6_dx-hc_pub-dukart2018</th>\n",
       "      <td>0.846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">General</th>\n",
       "      <th>target-HDAC_tracer-martinostat_n-8_dx-hc_pub-wey2016</th>\n",
       "      <td>0.853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith2023</th>\n",
       "      <td>0.873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Serotonin</th>\n",
       "      <th>target-5HT6_tracer-gsk215083_n-30_dx-hc_pub-radhakrishnan2018</th>\n",
       "      <td>0.882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target-5HT1b_tracer-p943_n-23_dx-hc_pub-savli2012</th>\n",
       "      <td>0.884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>target-5HT2a_tracer-altanserin_n-19_dx-hc_pub-savli2012</th>\n",
       "      <td>0.952</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                 Pain\n",
       "set                         map                                                      \n",
       "Noradrenaline/Acetylcholine target-VAChT_tracer-feobv_n-18_dx-hc_pub-aghour...  0.020\n",
       "Opioids/Endocannabinoids    target-KOR_tracer-ly2795050_n-28_dx-hc_pub-vija...  0.031\n",
       "Noradrenaline/Acetylcholine target-NET_tracer-mrb_n-10_dx-hc_pub-hesse2017      0.068\n",
       "Histamine                   target-H3_tracer-gsk189254_n-8_dx-hc_pub-gallez...  0.075\n",
       "Glutamate                   target-mGluR5_tracer-abp688_n-73_dx-hc_pub-smar...  0.167\n",
       "Serotonin                   target-5HTT_tracer-dasb_n-18_dx-hc_pub-savli2012    0.227\n",
       "Opioids/Endocannabinoids    target-MOR_tracer-carfentanil_n-204_dx-hc_pub-k...  0.254\n",
       "Dopamine                    target-DAT_tracer-fpcit_n-174_dx-hc_pub-dukart2018  0.272\n",
       "Opioids/Endocannabinoids    target-CB1_tracer-omar_n-77_dx-hc_pub-normandin...  0.325\n",
       "GABA                        target-GABAa5_tracer-ro154513_n-10_dx-hc_pub-lu...  0.334\n",
       "Dopamine                    target-D1_tracer-sch23390_n-13_dx-hc_pub-kaller...  0.347\n",
       "General                     target-VMAT2_tracer-dtbz_n-76_dx-hc_pub-larsen2020  0.376\n",
       "Serotonin                   target-5HT1a_tracer-way100635_n-35_dx-hc_pub-sa...  0.400\n",
       "Dopamine                    target-D23_tracer-flb457_n-55_dx-hc_pub-sandieg...  0.410\n",
       "Noradrenaline/Acetylcholine target-A4B2_tracer-flubatine_n-30_dx-hc_pub-hil...  0.443\n",
       "Dopamine                    target-FDOPA_tracer-fluorodopa_n-12_dx-hc_pub-g...  0.448\n",
       "General                     target-SV2A_tracer-ucbj_n-76_dx-hc_pub-finnema2016  0.652\n",
       "Serotonin                   target-5HT4_tracer-sb207145_n-59_dx-hc_pub-beli...  0.657\n",
       "Immunity                    target-TSPO_tracer-pbr28_n-6_dx-hc_pub-lois2018     0.731\n",
       "General                     target-CMRglu_tracer-fdg_n-20_dx-hc_pub-castril...  0.745\n",
       "Noradrenaline/Acetylcholine target-M1_tracer-lsn3172176_n-24_dx-hc_pub-naga...  0.756\n",
       "Glutamate                   target-NMDA_tracer-ge179_n-29_dx-hc_pub-galovic...  0.761\n",
       "Immunity                    target-COX1_tracer-ps13_n-11_dx-hc_pub-kim2020      0.783\n",
       "GABA                        target-GABAa_tracer-flumazenil_n-6_dx-hc_pub-du...  0.846\n",
       "General                     target-HDAC_tracer-martinostat_n-8_dx-hc_pub-we...  0.853\n",
       "                            target-rCPS_tracer-leucine_n-42_dx-hc_pub-smith...  0.873\n",
       "Serotonin                   target-5HT6_tracer-gsk215083_n-30_dx-hc_pub-rad...  0.882\n",
       "                            target-5HT1b_tracer-p943_n-23_dx-hc_pub-savli2012   0.884\n",
       "                            target-5HT2a_tracer-altanserin_n-19_dx-hc_pub-s...  0.952"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nsp.permute(\n",
    "    \"maps\",\n",
    "    n_perm=1000, # increase to >=10000 for final analyses\n",
    "    p_tails=\"upper\",  # one-tailed: test for positive colocalization, default is \"two\"\n",
    ")\n",
    "\n",
    "# multiple comparison correction across the 29 receptor maps\n",
    "nsp.correct_p() # mc_method argument to specify method, default is \"meff\" (effective number of tests)\n",
    "\n",
    "p_values = nsp.get_p_values()\n",
    "\n",
    "# show p-values sorted ascending\n",
    "p_values.T.sort_values(by=\"Pain\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42e6e809",
   "metadata": {},
   "source": [
    "After correcting for spatial autocorrelation (via permutation) and for multiple comparisons across the 29 receptor maps (FDR), the cholinergic transporter VAChT stands out with the lowest p-value — consistent with the pain neuroscience literature.\n",
    "\n",
    "Notice that the effect sizes haven't changed: permutation testing and `correct_p()` only affect the p-values, not the correlations.\n",
    "\n",
    "## Visualizing the results\n",
    "\n",
    "NiSpace has an integrated `plot()` method that picks a reasonable visualization automatically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f1ec2256",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:03:03.441193Z",
     "iopub.status.busy": "2026-06-01T13:03:03.440974Z",
     "iopub.status.idle": "2026-06-01T13:03:03.939841Z",
     "shell.execute_reply": "2026-06-01T13:03:03.939406Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: *** NiSpace.plot() - Plot colocalization results. ***\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Returning p values: \n",
      "| METHOD   | PERMUTE_WHAT | XSEA  | MC_METHOD | X_REDUCTION | Y_TRANSFORM | \n",
      "| spearman | xmaps        | False | None      | False       | False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Returning colocalizations: \n",
      "| METHOD   | XSEA  | X_REDUCTION | Y_TRANSFORM | \n",
      "| spearman | False | False       | False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Returning p values: \n",
      "| METHOD   | PERMUTE_WHAT | XSEA  | MC_METHOD | X_REDUCTION | Y_TRANSFORM | \n",
      "| spearman | xmaps        | False | None      | False       | False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Returning p values: \n",
      "| METHOD   | PERMUTE_WHAT | XSEA  | MC_METHOD  | X_REDUCTION | Y_TRANSFORM | \n",
      "| spearman | xmaps        | False | meffgalwey | False       | False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Creating categorical plot for method spearman, colocalization stat rho.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.plotting: Significance annotation: 2/29 p_uncorrected < 0.05, 0/29 p_meffgalwey < 0.05\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x730 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 500x730 with 1 Axes>,\n",
       " <Axes: title={'center': \"$Spearman's\\\\ Rho$ colocalization\\n(permutation of $X\\\\ maps$)\"}, xlabel='$Rho$'>,\n",
       " <seaborn._core.plot.Plotter at 0x3193e8bb0>)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nsp.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ddf4dd6",
   "metadata": {},
   "source": [
    "We can also visualize the input and reference maps as above, but here directly from NiSpace object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "709166d1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:03:03.941811Z",
     "iopub.status.busy": "2026-06-01T13:03:03.941711Z",
     "iopub.status.idle": "2026-06-01T13:03:07.180377Z",
     "shell.execute_reply": "2026-06-01T13:03:07.180019Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: *** NiSpace.plot_brain() ***\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Plotting Y data (Y_transform='False').\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.api: Returning Y dataframe: \n",
      "| Y_TRANSFORM | \n",
      "| False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mWARNING | 01/06/26 15:03:03 | nispace.plotting: Brain plotting in NiSpace is experimental. If things look off, feel free to raise a GitHub issue!\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.plotting: brainplot: threshold='auto' → 0.005351351574063301\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:03 | nispace.plotting: brainplot: kind='glass', img_mode='None', surf_space='None', mni_space='MNI152NLin2009cAsym', surf_mesh='inflated'\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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bXYnBaKSluQmbPQFNVbFYLBxx9LHM2nc/3nj5RZYsWsimzZtpdXtYv349J5xwAkcddVR8MvEHEP/GY9Dc3MyCBQuYP38+mzdvBvQAVZPZTDDgR9GiH4oGg4GsrEz2mzOH8eP3YGReSp8enK1uNwkdLC+dRV1lTR1vffIll59zauQ1waPf0JI9hXGjRzJu9EjOPf1kNhYVM3/BIhYsXkIoFKKqpBhFVXnl+Wd47bXXmDBhAvPmzWPKlCnxh/oOUFVVxVdffcV3332Hs7o86j2DQWLqHmM4YOY0xo3oWTRlpKdx+AGzOeyguRx31OHcdPvdrF2/EV8gSG1tLXvuuSc+n4+ysjIG5WZibGzhwskTGZ6W1u0+OzIgOZkHnj6Xkqoa3v/2Z35evgYNjYDPy7cfv8faVSuwJyYzd+5cZs2aha2HmL04XWnLVPziiy9Y8fN3tEWyGMPZhBazkRkTxzJryh4UDshnw2OvQ2pqt/t7YeUqDhs2jDRb7BjZBJsNT/iBbDQaMRqNJNj132xAv1wmjh4RdW7FZRWsXLeJ5RVOWpxOZEVBCVv6lKA+gSgrK0OW270Kw4cPZ5999mH69Olxkfc7oKoqz736Ju+99QZyODFCFET2P/AAJkycRII9ISK8mv0KNkcStgQHXncrBoMBs9VK0O9DlAwkpqSRmZuPIIqoqu72F6X2CYTUQVT5A+3Crs0a5/N68Xs8aEBaRhZmi4XaqgpczmZqKsvJzMmjobYat6sFTdMwGk160laHSUp6aioXXXo5M2buwzmnn4Kiqnh8fl555RVKSko46aST4skVvzNxYRfG6/WyaNEifvzxR1auXBkZsFVFQUUABPyBII6ERBxJSQwYMJD+AwYwaPBghg0rjJoBCaGWbo7SjizLBIJBEhLsPa6z+LfVqKrapWaQ4GkmVLEFgJCqkRDQ+MeUQs486TiWrVzN1z/8xOp1G9A0DTXgZdmiBSxbtICCfnmccNpZTJ8+PV6HqBdUVWXp0qV8+umn1G7dQFVNPZrfE3k/Oy2ZufPmst/eU0lK7Orm1DQNRdUQ3U0ICdEPd0EOMLhfDk8/8n/8+4ZbqKyuQTSaufzyy3nvvfeoL91Ca3Ep+w8a2KOo0wQBDRh13rFRgnJAbjaXn3osJx60H5/9tJjvFizG6/eg1JWxZdMaHlu5hJdf1mtSzZs3Lz6r7gVZlvn5559568mHKK+JtswJgsCYYYPYf9pkJowcRlATaA3IrHvizR57Nsqqyuq6eg4ZNpSRFxwPgOZuibLaORJsuL0+NE3rdUImCAJD+uczpH8+xwCtGYVs2rSJ4i1bKCkpobS0lNbWVlpaWtCvGp3169exfv06nnzyv4wbN44ZM2Ywc+aseELWbkBRFG66/S6WLPol8lp+fn/OOv9CRg8bQtHmzdzxn1s58uhjIqETgiCQkZtP6eb1gEBiShopGdkIghB1TcjhEABJanfzG8Lxb4qm4fO2Czuzqd0VK4giAiBKEpk5eXg9blpbnDTUVdNYX8OSxUsQRYG99p6O0WRCkWVMMeK4Cwb0Z9SYsUyeOoXFCxeSnJbOdz/M57fffuOOO+5g8ODBu+Q7jNM7//OjeXFxMR988AGLFi2KlCAIyO0lRgr6D2DU6DEMHTiAgv79ycvLQzKauttdn6moqsZsMpHYQ9xTvxzdvVteVUP/ft3HK7hCGiVufVY+sXgVU5MF9r7mCurqG/j+51/47qdfqG9oBKCsopJ777iNV/sP4phjjolnT8ZAlmXmz5/PW2+9RfVW3WKbaTei+T1IksjUUYUcMHU8owfrrlZjWNQFQgounx+nN0CLN4A/KOOwmvAGQowYaiYphoi3myQOP3geTzz7AmoowIcffsjixYtpLS4lwWRi7pDuB8PW1DSa8/Iw+ny4Klqxm0QSzQaSzBKJZgMGUSA7PZWzjjqIf0zfg4VrNvHlkpXUNbdAKIirdBNP3nUzn332GWeddRaTJk2KW3M7EQwG+e6773j33Xep2bI+6r3s9FT222sSs6fsQXqKLsb8IYXV1S4ALHY71tbWbvdtPXQmGRXbmHnF6d2uk5KYiCSJ1NQ3kpO5feEUZrOZsWPHRtUaCwQCVFRUUFpaSnlpCatXraasvAzQJzIrVqxgxYoVPPnfJ9lrr7049rjjGDhw4HYdN05sNE3j/x57kmW/6skMgiAw96BDOfK4EzBIEpqmMXTYMAqHD+edt97kzLPPiWxrtSeQkJiM2+XE42ohLavr8yDg0+vWmTsIclGUIn/7/f7I36aoGDsFSZIi51QwcAhbizYCGj6Ph4z0DN5++02y8/qRl5Md3r6rsHv+maeZuc8+nHnOuRx0yOH89zE967a5xcWNN97IXXfdRf/+/bf7e4uz/fxPPtE1TeO3337j/fffZ/Xq1VFCDiAjI5Np06ez194z6NehJIXNoM+/ZbXnRGKnlEiy4upxnY2bNjNs6ODIDRULSZIYO2IYvyxb2aOwaw3HapslMEn6g1netJTMwsmccNThHH/kYSxdsYp3P/qMzcV6+5iq0q08+uijvPHGGxx11FEceOCBUVbH/0UURWH+/Pm89vrr1NTUIAbc7RY6ezKnHLQPsyeOISlBr+IeVKE1pOKtbcbp8eMNylhNBnzBdjdXMKQgqxrrisuZMGIQlhjf8egZB2B++TUCwSALFixAadVF+JiMDIzdWFV9DgfNYfeGYjShoeEOKriDCs0+EZ+skWCSSDZLOMwSNoOR2RNHM3viaLZV1fLRgmX8vFIXKuWrf+W22yqZMmUKl19+OXZ791bk/xWCwSCff/45H3zwAU1NTVHvjRg8gGMP3Ic9RgztIoTNBhGjKBBSNQK2noXdolXrGFc4uEcxbTQaGNI/nw1btm2XsAv2i1041mw2M3jw4Ij1xOlXKC8rZdEvC1ixeAENDQ369qEgP/70Iz/8+BOTJk7gqKOOYvz48XHhv4NomsZ9jzzO1198RkZGJi1OJ+dffBnjJ05CURQ2rVlBTl4egqpy+hlnceMN1zHngANxZLa7MG2ORNwuJ36vG01VqawoZ/nSJRx+9HF6LdSIsGsPr+g4aQ/6O7hiw8k7mqoiSRIJiYlIYeueZDAwZPgonE0N+Lxe8voPpP/QYdx/1+0cd/xxDB48NKYxoKqignkHHwLAwEGDuO3Oe7j3ztvZvGkjLU2N3HDDDTz88MOk9hCaEGfX8D8l7GRZ5scff+T999+nrKwsStAlJCQwbe8Z7DV9OkOG7nhweagX0Qf6Q+OHn35hyqQJva47b/Z0Hn3hdY475ICom6nNDQvQKuvHTDDEPmdBEJgyYTyT9xjHmvUbeffjz3Q3bdBHQ0MDTz/9NN999x3XXHMN2dld09z/F1i9ejVPPPEEFVv0Cu8igAZjhvTnsJlT2GPYIEIqNAY1alwKAQU84e9dkDtkxGpgMxlIsplxWMzIqkpJkxdBECirrmdY/66xJlarlez+gykt2kBTQx0Ooy7m7N0IbVUQcGVkggaGUIjEuhryJw/DFZBp8csEFQ3QcAdl3EEZrSmEpoHNAAkGSErL4qJjD+bgvSbwwmc/sKmsErWxkgULF1FZeQU33njj/3RMTGVlJXfffTclJSUAeoFYj5M9RgzjmANnMWpI9xYsQRBwmA00trgJ9iCQQ4rCN4uW8+8zju/1fMaPHMa3v/zKjMl7RGXJ7yxOvz7+5Rf0J7+gP8eecCJFmzay5tdf+HnBL3g8+nW9bPlvLFv+G0MGD+Koo45i5syZPU5I43TluVff5OsvPgOgsaGBCy69nPETJwHgdjkJhUKUbS3GYDCSlplJfv/+bNq8mVn98vEEdW9Mm5VMVTVUVaW2pppVy5dx+NHH4XG1F7O32BIix+34OwWC0VmxmqZRVVGCwWhCkRUkqUPZLUEgJS2DlDRAgLTMLI446mjeeuMNLr38CiSBqOTBtm2aO0yCLBYLV15zHXfdfivbioupa2jkkUce4eabb45PEHYz/xPCzufz8dVXX/HmO++iKAotLe0xcNnZORx06KFMn7nPTlus+iLq/H4/d9z/IA5HAofOOyDqPTUpu0sCxYTRIxBFkXWbixk3srDL/lRNiwiMRGP0zSJvWoqhcHLk/4IgMHbUCMaOGsGmLcW89/Hn/PrbSvyCkeLiYi699FIuu+wypk6d2ufP/FfH4/Hw4osv8uWXX6L52q2s40YM45gpIykc0I96v8b6FhVXqP33FSAS92QOekjOyCTFbiHRasLc6eGrmRMoramnrtlFSmICGSnRAeqpgXoyMjPZsqUIQRBo3LwNs0EiqERbkttoyc4hYLcjhUKklpdh8XrISTCRk2BCVVUCikZLQMHpl3EFFYIhMIngU/SlPgCiF5JTcrjijH+wcdMmnv7oW9wtNQjNBv518aXcevON/5PtghYsWMAjjzyil5xRZGRNYMawfhx9wEkMKehd7CqNNSSEoBEIWm1ogoAQo1TopqYmbBYzY4ZGi8TOWbEARxywDxuLS7jziee55rzTMZu3f5xqE3E9IQgCw4aPYNjwERx83Mks+HE+3335GXW1ek/SLcVbeemll3j55Zc56qij2H///eM1M/tASUkJ77zxWuT/p519LhMnt4+xAb8fEQjKMkajEbfLhc/j6VI2R1FCmMxmRMmAIAjUVleTlZMDQEuTnhFrMluwJeihIbIGdHDFBkPtngRRklBVBa9bF+8Z2TldxXon7TVj1j6sXL6Ud956iynTZiB1EmdHHnMsr7/6MuP3mEBCOMTIZrPx76uv49qrrqDF6WT58uV89tlnHHLIIX389uLsCH/r6PmWlhZeffVVzjjjDJ546mmampqwJ+izmWHDCrn0yqu476FH2HfOAbvcDemUEru85nZ7uPmOexAEgSsvvqDLMSV3PUKnm0sQBIYPHsDG4m2R1zpa69whaHtuODoJu46irjOFQwZz3eUX8e87HiAzOwdfSMbj8XD77bfzwgsvRGXN/V1ZvXo1F5x+Il988HZE1A3LTOY/px3BDccdQFpOHiuaFLa6o0VdolEg1yYyPEliUprEHqkGBipNZCTaokRdReIQKhKHoGUNRjE78AsmVpc3Utvo7HIuqenpJCYmoopGtHBge6iTsNMAZ3Y2reHSNRa3G4vXE7WOKIpYjRLZCSaGGrxMsAaYkAQDbJBtAVv48lI1aArCZo+AY8Bwbjj3FMYOHkBpWTnB6mKuue563v3o0539iv8yyLLM008/zT333IPH3YqqyGTm5nPHPfdz7n8e7pOoa8MRvgQ0USBoiZ2AUOJ0MnJw/z5ZLixmM1edexqBYIhbH3kGr8/f6zaGoAdDUL82+iLquhzTYmHOgXN5+NHHuOyKKxgyRC+1I0oGamrrePrppznzzDN58803ae3B3fy/jqIo3HHv/SjhjNWDDj2CmbP3jVpHDgXRBIHU9AyS09Lw+32UbNuKHPBHrHUAoUCAYCCAHAoiShJrV6+kYNAQ3G43LmczgiSRnJWDgkB4ro+m6aOJhu52bUMURbQ2Q4QArS1OlPCYbzOJ+mLskF0rgNVi4dDDDqe2tobPP/2ky2fde8ZMBg0ewisvvRB5ze/zYTBKnPXPcwEIygovvPAC5eXlXbaPs+v4Wwq7uro6nnrqKc4880zeeustmlraLTG5uXncdNvt3PSfO5g0eedLf9T79Bu2N2tddU0tN/znTpKSErnh35d3melK7vaK8p3FndvjIzEhgVi0hAWHQWx/aG8PAwYN5qbb72bS1L3whWd077//Ptdffz2NjY3bv8O/CN988w033XQTjc1OQH94nn3g3txx/skMLujHGqdKcatK27iaaBQYmCAyKU1iVLJEgV0k1azHU7XRUXAD9HPp/xdEkdyBgzEYjBjNZtZUNFLb5Iys12TOIBQI4nK5EMPdJAACnYRdc24eLRmZGP1+TD4fKeGC2LFQnHqslCDosZfpZhhog3FJMD4J8q1gDV8vHhkaDEkccfhhTCjUY6+EpkqeefIJHvnvU9S1eLo7zN+C+vp6rrnmGj755JOIlW7K3jO57c676b8DvXftErRdFoFu7lu70URruEl7G7GsdW3YrBZuvvgczCYj19//OLUNXe9NuXQTcukm1Ez9N2zBukOiriNeWWPPvaZx+113c8tt/yEnXHRWVlSanS289tprnHHGGTz77LOR+Lw47bzw+tts21oMQG5uPw498mjkUDCq2HTAp4dqmMxm8gcMpqKyklAoxJhx4+nYGMrTqj/HrDY7mzasp6KslGkzZ9NQpSe/iIJIQnJ0Bn3H7bUOmdCiKCIZDKRlZmE2W3G7Wigp3oyrpb0+XkBWkQRd1AGYrRaSU1I58aRTeOv1V9laXBx1LEEQOOucc1m14jc+ePcdtm3ZzMa1qyjbuhWL0cB+++seKrfXx/33308oRiHvOLuGv5WwczqdPP7445xzzjl8+umnBINBArKe8TNj1j7c88BDXHrlVQwrHN7jfkKqFnNpCSq0BLsOlG3irsv5hK12i5Ys5YrrbmLsqJFcdelFMS113bGpuIR1RcVMHDMy5vttwi7RKHQRqfKmpbE2iVAp6YOA1WbjvIsv4x+nnkFQBV9IZv369Vx11VVdAsf/6miaxksvvcTD99yO7NYHsfGjhvN/5x3P3L0m4FdgbYsScW87jAKjknUxl22NFnKx6Czu2rBYbQwobP8N11Y04fa2W15s4YxZUZJQ1K4WO3dKCu60NARACgbIKN6C2I2rtk3UdYdVgn5WGJcIQ+1gCY8CXtHMYYcfydy9JgJgaKnhs48/4sH7743KqPs7UV9fz7///W82bdpEUFbQJCNnnvNPzv/XxdvtZlQa9TAKUYDEsNXO342wG5mRzqrNW9laUd3n/ZvNJq6/8EyGDx7I5bf/H0tWru123RZ2XakSd1BBEARGjBzJ1ddex70P/B8zZs5EFEVkRcXj9fHRRx9x9tln8+STT+Jy9Zw49r9CTU0N77/9JqCLnjP+eR6upgY2rVnJxpXLKN9aRPnWIvxeL5IAjsQkQqEQP3z/PXvuuReNdTVIii5+FFnGH455LCkt44mH7uegw49E9nvwhV9PzcnruYRVB5EnhvtX5+YPIDE5GUEU8Xs9lBRtoqkp9oTebLYSCPjJyclm3sGH8H/33U1jY/RYk5KaykWXXM7bb7zKh+/poU+yHMJgMHLEkUeTm9cPgK1bt/Lmm2/u2Bf7F+OWW26JlKZpW4YP71mD7Cx/C2EXDAZ59913+ec//8mXX36JLxjSEyNEA3MPOoT/e/Rxzr3gX+T169ftPjoKuM6UOf1RS71PiSxtOAMqzkB0yx9Zlnn0lfd47OnnuOjcsznz1JOiEiAkd323ok6QJBpbXNz52LOcdvShZKbrmUQdhYOiabjDAiTJGFtwdCfu2kRd5HiCwJy5B3H1TbeSkqq/V1dXx80334zH8/ew2GiaxsMPP8w7rzwfee2wA2Zz3dH7kZmShKppbAwnRgAMTBAZlSR2iV3cXnKKfySn+EcKKhYzSWpEDJc2+K2sETV8vdntugDoaLELhmf1stFIc65+7Zp8fjLKypC6afHcm6jriCDolrxxSZAZrn7g0URmzd6Xcw6bgyiIGINuflu2lIsvu4LSit77nf6VaG1t5aabbqKypg5/SCEjI5Obb7uDfecc0GWS5Ozfe9yplJaNlKYnHyWFS4kFbHa0GF6BLLudE+bO5s5nXovyKPSGwWDg3BOP4vyTjuGh51/nxXc/6RI2oS79vM/76yvuDhPa/v3786+LL+GRxx7nwHnzMJqMyIpKIBjis88+45///CcffPDB/7RFpqyxlbvuf5BgSC+htd8BcxkyrBBfOHRC1TS87lbdhSqI2BISSUpJ4cXnnkESBWbMmoU9MRGzxYLVIOJqbkRWFL7/9mtefekFTjz1TA6Ydwi1leWoqobRasfkSMUfUqKWjhY7XyjaFQv6uJ/Trz+Dhg6PFDMu27YtZiiOKIqRVmQzZ85ij4mTePiB+yPPB71DRRWKHOCss8/ht9+Ws2zZckLBIF6PG7PFwgUXXYJkMBCUFd5//32qq/s+sdnd+P1+XC5Xn5btneiOGjWK6urqyLJgwYLd9Cl0/tLCTtM0fv75Z84//3xeeuklfD4fAVnBarFy1LHH8fATT3LyaaeTltZzmYCe3KhlzugfMN3ec0P1NnHX0FDPf26+kW3rVnD/Hbey19ToeLeerHQArW4Ptz/8FFP3GMOh++8Tcx1Xh/i67oRdT3F2sRg8dBg3/OdObEkp+EIyJSUl3H777ZEaf39VNE3j2Wef5dtPPwD0Ae3ck4/j1GmjI4OcK6hhFAVUTWOoQyTbKu6Qq747qx2AxSAy1uDE7GnE4KykcdMqgEiJEVEUUTT9GmpLnnCnpOpB+KpGWllJzGD89U+8tV2iriOiAINskGXW46UVFfaZvAc3XXMZNqsFY9BNVfFGbrjiYlatXYe7DzFef3b8fj+33norW7bp7ZyysrO59Y67GLQLiqhuev07Gj/XC9BqokCgm+4eR82ZwZihA7n72Tfw+Hwx1+mO6ZP34P7rLuW3dRu58f+epLE5uih6suLqteTSzpKRmcmZZ53N4/99iiOPOhqzxYysqLS4Wnn++ee58MILWbhwYZS4+F9hwY/zWbd2NQCpqWkcfdw/ANC0dnFlsdqwWKwkOBzkDxjEN199xaoVv3HMsccjiSLWcNkSTdOoryrjrddfpbi4mDvuvo99Zs1EkAMYzWYEUSQ5u1/MsSrYofJDx19B6OR5sDsSKRg0FAS9EH95aWnMz2W2WDGZzKiqwulnnk1GRiaPP/IQcijEti2bqa4oQ1UU8vsP4Ob/3MmSJYv55puvsVitWG02BgwcyEGHHKqfm8/Lc889t/1f7m7A7/eT4UgmKSmpT8vAgQO3S9wZDAays7Mjy+5u8fmXFXabN2/m6quv5t5776Wuro6ArBBUVPadsz/3P/woRx1zXCQzpyd2pahrY83qVdxw9b8pGDCAu2+7iZzsrD5t10ZJeSVX3HYfmemp/PPEo7sVFy3BcDsjESwx4ut6EnV5Svfxc8kpqVx+zQ0kOBLxhWTWrl3L/fffH7MJ+V8BTdN4+eWX+f6zD3Ak2BFFkasvOIuD95sZtV5TUKM1pGEzCKRbdv7W2GqP3ds11WIg2axb5irc+sy4LalH782orxdUFFRRpDUjE0FVcDTUY9xNAlsQdPesBjhl8KT2Y8LoEdxzzSVkZOmZd83NTm695kp++fTdv7S4k2WZe+65h1Vr9Tp+ScnJXHndDVgcXROetpc2d6zR74+4yv0JscchQRC44PjDcSTYuOqBp6mort2uY+VlZ3LXifPINChceu0trN2qB6S3Tj56Jz7B9pOUlMQJJ57IQ488xj6zZyMIArKiUl5RyV133cV1111Hcad4rL8zTqeTt157OfL/084+F0u4aHByagZoGiaTmay8fAaPHMPAocP5cf4PvP/O21x+1TWRtm6CoA/qZSXFPPnYo6iqyi233x3xPMmhEEGvF01VowoRd6SjqDaL0TF2nbHZE0jPzEYSBRrq6/DHmGwYjUaCwQCtLS2IosgZ5/yTDevW8skH7+IK969NcCQyeGghQ4YVcvoZZ7JyxQq+/+67yHPs8COPJjlF75+9ZMkSVqxY0cdvdvcRDAZxywFuGD+H2yfO7XG5YfwcampqaGhoiLLiBQKBbvdfVFREbm4ugwYN4qSTTqKsrGy3fp6/nLCrr6/n/vvv54orrmDDBr3mWEBWGD1mLHfccz9nnnMuScnJPe6jJ7drG51FXV/5deECHrzvXk485TTO6tDIuSPdWevWbiri/55+iQefeZnZe0/h2n+d02NXiLZMzSRT1/i6nSU7N5dLr7oWc7h20qJFi/jvf//7l5x9v/POO7zzyvO0uj2gaVxy1slMmzSeYOmmqPXa6jKZpZ3/LtusdjnFP8Z8P9EkoWlC5Brs2LPVmpMJhIWdJKGJApokYfa4Y+6rjTY34I5iEtsDpdvcwfnDRnH/bdczfJguUoPBII8+8wJPP3AXjc7eW+f92dA0jUcffZRly5YBYLVZueLa68nI1CdfwR7GhL64Yze9/h2gWz4t4VIS3SVQgF6A+PpzTmLPcSN54NnXeOiFN9iwZVu363dELt2E2WTkoqPncuKcadzxyocsWleEY+l7fdp+V5Oamsr5F/6Lu+69j5GjRunnqKisXbuWyy67jIceeuhvF7MbiydfeDlSA3CvvWcwdvwekfccycmYzBZCoSAuZxMGQeC9t9/kg3fe4vqbb4nUUNU0DXdrC3U1Ndx56830Kyjg7H+eR0ZW+z1udyQimUyIBgN+d2zrbFtbQ6A9C5bYwg4gKzcPg8GA1Wqlsa7rRCMxKRnQReWG1SspLylm5IgRLF+u309ZOXkMLhyBwWgkEPCT6EjgzLPOYvny5Sxc8DOgZ1yfcOLJyIKEGgryzDPP/GmqMCQZjCQbTT0uSQY9ziI/Pz/KinfXXXfF3OfUqVMjJbX++9//sm3bNmbMmLFbs8n/MnXsVFXl3Xff5a233qLV0z6TyMzJ5fiTT2XM+D2wSBKqCrGuWZ+sW5sMvQS/7wzff/U5H779BldeeWXUzdxGd4Ju/eZiXv/wM4pLK9h/5l4cc/ABFOTpVpLuHjNeub1+XWc3rGjWZ4cNpgwqWnuy8PR8Mw0cPIQLLruSh++9C1VV+PLLL0lJSeHEE0/scbs/C5qm8fbbb/PKM09EXjv56EOZPW0KAKb+hdHibhdeGuWFcwEoHTCL/iUxxJ0GFoOAOXw9JnSw6rRZRlVNQ1AUDIEACALarjzBbtAAwWiMHEnwNJGUmMpt11zBs6++ydff65/l+58WULythEuuvYlhPbQ9+7Px0ksv8f333+MPKRiMBi658moK+g+IWieoaphijBOKBo0FurhLK1sSc/8jLzoJze9lwzMfYHa78SYlEbDaCJlMXayt6594i5EXHI8oipxy6P7MaHbz/aJl/OfRZxk6IJ8TD59H4aDYLZjkTpOS/SePJdlh58G3P8ft9bE/IE3YP2qd1OXv0zTxqJ6+nl3CwIEDuemWW1m29Fdeefllamt0K+ZXX3/DggULOPHEEznyyCP/lkVqGxoa+PG7bwEwmcwcf/KpUe9LkiEyziiywssvPMdvy37l+ltuJ79At8Rl5uRSV1OFy9nMQw/cT1paGgcfcggDhhRGfWeiKCIH/JisNozdlNXpSMdJeXfCTpIMpGVkUFtdjdfvJ6/TvZGYnIIjMQlZlvF5PWiaRr/8fCoWVTBs5Ghs9vZJTGtLC0aTifz8/px7wUU8+9R/KRwxgrS0dPaeMZNvvvqS0qKNlJeX8/nnn3PYYYf1+hl2NwZR6FUjtL1fXl5OYmK7ld9sju3RmzdvXuTvsWPHMnXqVPr378/bb7/NWWedtQvOOsY57pa97mIaGhp44IEHWLu2PQssISGBo449gb1md+112ibu2sRcR2K1A+v8Q7ZZ6ybWLwZgecaevZ7jb78u5pP33+HSa2+kYMiwSKydkwQGGNwxRV1js5PHX3yDdZuLOeyA2Vz7r7OxdxOPA+1WIE3TKPG0CVVIMenn3ybodhX1XpnRY8dx1vn/4pnHH8YXknnjjTfIyMhg//33730HfyCyLPPkk0/y5YfvRF474/gjmbvP9Ehh4d+EfEIdWrW1VJVi9m/e6WO3iToAUzclaIKahl/WMJoEfLJKZsWyiJUs5NODkSVBRFRV5PCAocWw3o4450gABIt+3Uhp2RF34I4gGE34/H5UbyukhN3DnibMwAVnnsqIfpk8+do7BIIhSssruO7yi7jwrNOYfXjvHRT+aD7//HPee+89/CE9y/O8f13C8JGjul2/c2X9jjQWTO1W3IH+uwRaXaxogZaKepw5uWSUlnRZr03cAQzMz+Os/DyOO2gOH337Izc/+CRjhw/lvJOOJjW5+1IobUwePpgbTj2Su179iBRHApP4hlSgaeJRpC5/HyDyL+HXdxeCIDB5ylT2mDCRr778gnffeRuvx0sgEOCFF15gxYoVXHbZZX+r9lLlTW6ef+FVAqEQogBzDpxHUtjC1UZb8oTBYODdd96mqrKCG2+9nfSMzMg6yalptLY4een55xEEgVNOP5Os7FysnZ4NXrcbo9lK0O/vXiT3UO6kO9rifTVVjYyVbQiCwKBhw2lxNuNyNqNpMHS4wKJFi6NEHUCLs5lQMIjZYWHKnnuyauVvPPX4Y1x7o9554tQzzuSm666hIC2FL774gn333ZeEHqzbvwdmQcDcy4RDDb+fmJgYJez6SnJyMsOGDWPLlu5jsXeWP70rdvHixVx88cWsXbuWQEghKKsceNAh3PfQY8w5cG63rspYoq4nfD5fpCXLxPrFEVEX6/+xWLl8KQcfcTSDhgyLen1AzVKo2NBl/YXLVnLxTXeR5Ejg2ftu5aQjD+4i6rRuylk4g1okvq6fTS/BEUvU9Wyt6xv1Xpk9957O8SefBuilUJ544gk2bdrUy5Z/HG63m9tuu43Vi9stZacfezgTJkzk16JKFm+uoNbpZoIWXSRTQ8NpSWVXeZu7E3UA/vD1aRQFcop/RJJEzB497tHbrJvoDaKIAJFYrVCnGWGbqAOoy58SWaTkHQvMLfOEeOP9j7jzgUdwK10Ht61bt5KaN4ATTzqZ9HQ9c1pVVZ544RUeeuihHmNM/mjWrl3L008/Hfn/KWeezaSp3U/YenLJttFYMDWyOPtPhYIxaP722nRGEfLCFVN8iYn47bEfWuufeCvq/44EOycfcRBP3Xk9FrOJS257oMfSJh0ZOaAfR82YzOL1RZHXOoq5jnT3uizLvQaGN/tlmv29u88MBgMHH3Iojzz2BAfOmxdxC65cuZKLLrqIpUt7Lsn0V6Kqtp5f5uuueLPZwtyDD+2yjsfVgt/n4+0336C8tITrb74tStSBLp7KKipxud1cee31DBk+itRO6wC4WpqRgwEkgwGTNXb7ujYxp6haJ1ds7MHJZhKjxr9YoTeCIJCckkrBwMH0HzSYYDBESieBrsgy7nDZm8RwaNTJp51BQ309X3ymFz4fPGQoh8zZh+qaWraVlPL222/HPKffE5MkYO5lMe1kqI7b7aa4uJiccNeQ3cGfVtgFg0FeeeUV7rjjDlpbWwmEFNLS07nu5ts46dTTI8HmHQmoamTZHlrdHm6/6Xp++elHMormd7te/5IfY7rVNE1j1fKlFI4cDehirm1poy1jUZZlnnjpTR594XXOP+V4Ljn7FBwJXW9K1eNC83siC4Cx3xAUTaPEo99sVkkgy7IDWZuygi8o4wvKhGSFUDhzqu21jk3sQRd3Bxx0CLP31y1RrT4/d955J83NzV32/UdTUVHBFVdcwW8/f0dlZRWD87K5/J+nMXXqVMrqW/AHZUIhhdL6FhbL0TFpRRs38NKzz/Cbc8eP32ataxN1sWLs3KH20jiJJv0WNISLUpt9zsjDTwpbkttitdxpaajhmXZHUdeZugHTtkvcBUMyj7/3JVc98DRWi4VLzjubtJTomag/JFPt9OANyaSmpXHiiSex5+SJZGdm4PP6+PbzT7j2sn/RVLymz8f9vWhoaODuu+9GUfQSEHMPOZR99z+g1+2U7VD4igba5q4WvBwLpOVnANCcmxuz9El3JDkSuPzskzn7+MN5+IU3eOr191FVtYsbtjOjBuWzfFPf4vRi8eP333HnLTd2K+46CrqexF3H9xwOB2eedTY33HSz7spTVFwuF7fddhtvvPHGnybGamf44ZsvSE3Xf+v95x6EI2zN6VgFKzEljY8+/IDqqiqOO+44hBjBNpqm8elHH3L0scczcPAQzGZjzPCigF8PSTLbErq1wHUUZiGta7mTWLTFB5ot1p7r4oWprakhu5NIcTqbIhnAScm66LNarZx6xll8/unHJCluklUPxx55OCaTEUlT+OSTT6irq+v1eLsToyD0adkerrzySn788UdKSkpYuHAhRx55JJIk8Y9//GM3fYo/qbCrqanhwksu47U338ZsSyAQUpg8dU9uv/t+CoePANghAdcd3z52K7lqC0fk9G0gbxN4/Ut+ZEDNUvpVLEZwVjMmsC1KzHXGX1/DPQ8+zsbibTxy2zVMnzKhyzqqx4Xq6RoIq9RXEiwvosil4g/7iPonCIhCbGtdd4RkJcodLasasqp1EXNt/28TevVemRNOOY2hhfr339TUxN133/2nGpArKir493lnULlZt24kJtg54+hDmDF1IjVONxazAaOkX/I1QQk5EP3gKhy7B4OGFvLCU0/w+Ltf0OTavuDWpbn79O08W/X6XkZRINumW5yl8ACqKXLEJdv2WmI4iFmVJNy9lO7pSF/EXXOrm5uefYsKp4c7rryA4w6ZS35WOnazMWq9JrcfTdMIhmSMokiKw85hhx7KkQfPw2LRLYmbt2zl6lvvomrdsj6f4+4mGAxy55130tLSgj+kMHL0aI79x0l93l7RtMiyI4gC9LdBQl4G5sH5NOYXxIybXf/EW6jNsWNwZ02dyIM3Xs6aTVu47/6HkLux5LeRnGDH5fH2KdEpvWh+l2XWvvthtdr44J23et0e2q13na14KZau3pTRY8Zw7wP/x6TJk5EVFUdSMq++9hqXXXEl9fU9l4D6M7NofQnffvkFtdXVZGTlMGvuwQTUaFEH8MHbb+JudXPWOedgt9moq6qkrroy6rfauGE9LlcLe8+c1eMxZVlGFIVI/bmekEQBTdUQBD0D3mAQkUQiS1sbMU3TcDY1IYgCaWlpmA29S4S6uloys6IrPzjDSTL2BAfmDoW+R4wey+ix46nwCjRiR0grYPY8PbbO5w/w6quv9nq83YlZFPq0bA8VFRX84x//oLCwkOOOO460tDQWL15MRkbGbvoUf0Jht3jxYs674CJKt21DVRQkg8QZZ5/Lvy69IqaVbmdRFIUFK9Zx3P4zuzZB7oW2uCaDQUIQhC5NmzsSDIW465lXaXS2cNu5J5EqdRWlirMBLdTuPlVbnZFFC1vqmsMu2ByrSIpJ7FbUrc7Ze7s+Syw6i73mIJx/6eWkpKZFulO88MIL3Wz9+9LQ0MANl5wbadPUPy+HB665mNHDBuF3teD1h/AHZELZhbSaU5BMVmR/dEsne1IaM/eZxVnnnscGOZGTHv2A1778EU8vpT2W5u4TEXU1rf4erXWV7hCN4TZPeQmGiFXOGB6cNU3D6NB/U0N4Zmjy+ynon0pCbhrKhFFkHdXzgA+61a43y52madzz6kekJzv4z0VnoDjS8QsGVIMZizH6YeEPytjMRjISbeSk2PEoAi6vj9kzpnHnDdeQkpIMaFTX1HDrvQ/+KYpat9UuLCrS3ZJpGRlccMnl232f95WmYbOj/i/adYtNqlGvEQggjhxCS3ZOF3FXePwsVFeT3hIshsDLSk/j1uP2p7K+ifvf+JRQDxOqoCxjMhp3ODkhe9sCTps+nJXffhwlONwxuu7sCImJiVx51dWcefbZaJqGqmpsKSriggv/xQ8/797CrbuLb774JNJrdY/JU7HaHMgdgjQDKqz5bTk///gDV11/E+Mn7YndkYjP66GmspzaqorIups2bGDMuPG99i9vs4gpPVwLUS3FOhhCurs2mpsaCQaDaKoWKbvSGy6XK2rdYCBAa4sTk9kcsWC2kWUIcM55F2Kzt3upDjnsSMzhdno//vjjH9rK0iAKGHtZtjcB880336SqqopAIEBFRQVvvvkmg3dBvcye+NMIO1mWef7557npltvwhgNMs3NyufLq65k9Z//dlkElLfsYt8/H8IH5O7yPtkG2O7O1oijc/cxreP0BbrnwDBx2XRAqzoaopQ0tFERtdep/axqekMq6Og81Pv3GTDEJ9Lf/MRllSUnJXHjZlRgMRhKS0/jqq6/47rvv/pBzaaO1tZUbL/4nDeH+qwP65XLn5eeRmabXShIBLdyaR5QMCIKAEvQR9EaXD5GMRswJyaSlp3PooYdwzmX/ZnNZJf+672m2VW1fjbFY1HplSlz6eSQYxYi1DkAKWxI1Tf/NE3LTIha7wuNnUWDRMAh61uomrxiZEbfRXQhBd+JOSk7nu5JGXJqByy+7BI8liSa3LmCzk+1R95umaTR5/HgDIcwGKXJeYnidQQMKuPfm68hNSYRQgMqyEu64/ir8FX9sHOaXX37J/PnzyczMRBFELrnyqj7VttyViPZEBEHv05scNoKq40fS0H8AQbMlpvWuTeB1XpISbNx65jE0tbp54M3PurXIiYKAoqq9WvbExFREW0Jk6cjwnHSaW1wY1n+/3Z+5L7F3giBw4Nx5XH3tdRFrj9vt5t677uKpZ577S9XMbGlpYcEPeias0WRiv7kHR97rKO6+/fpLjjnuBLKyc7BYbfQfPJSEcO3E+pqqSGLFhvXrGFZY2OtxU1IzMJrNBD0t+Fpjlx7qeImonVyxKYF6EjzVqHVbaWxsoKqigpKtWwGw2e04EhMJ9CFW3evxYLcnoKh6cXNnsz42hYJBklJSI68rKjTSNezIZrez7/4H6ueoqnzxxRe9HnN3sTssdn8EfwphFwqFuOeee3jz7Xcjr03Zcy9uueNu8gva0/13NIauJ1IcCbp42s6Cq23WOoCN28pISXSQlhw7Q+aVj7+ivsnJTeefht3Ws9s0pKi4XK3UeWWKW4Isr/Ozst5Pq6yb0RONAkMT9Y4IO5IFazRsv7XCIAqROLx6r8zAwUM4/ZzzqK+vIxAI8Pjjj/9hBUhlWebWS8+jPFzcNSs9jZv/dWbU92w0iIiCQDNm5IAPs11/uAdanahK9EPIkdUPQZTQNJUkk8iNZ5/AYTOncNNTr7OxpILO9NX9WueV2dIcwGYQsBkERqaZI9Y6aI+x0zQt8sCWBIHC43XrnFWCkQkqBgFMgsZGj4g71Lf7oG7AtC6vuQQTr7z/KeedfCyqILKlxgmA3WwkLzX6Ie/yBSPW2xS7Bbdftypb2iwKjRVkCD5uuvAMHOGZ+Levvs+bH3zSp/PbHWzatImnn34an89HfX0951zwry5lTX4v2sTd0ARwGAANjGMKcc+Zhe+wuZiPO5j6oECrDJ2fo1/f8SFf3/Fh5P8Om5WbTj+a8rpG3vhuYczj5aQlYzUZ2VLRc3Z0ZzHXEbfXj6bIJHWK/+2LaOuJztsPGjSIu++9j0lTpkRe+/CD9/nPHXf+qcI8euLZN94jFC5lM2Pf/XEkRlu6ZEUjFAqxes1qxk+YGHndYDCSP3gookFC1TRqKvXxpbyslAEDB/V6XEdSEoSCSEBdSRENFdtwO5uQQ7GT5jRNw6gGMapBkuQWmlpaKa2uZ8O2CirLyqisKEdRFERJpKD/gF6NKUr4WvX7AxiM7YldrS4XmgZWuwNB7FvhjX33PwBEiZCsl9X6o9rRGSURo6GXRfpTyKYe+cPPMBgMcu2Nt/Djz3oLHslg4JTTz+LCSy6PFG3d1WIO2vt3WswmrGYzTa6ei792pKOokxWVj77/hT33GINPVnAHZVx+mWZfiAZPkM8XrWDBqo2c+Y9jaZEFqlx+Kl1+Klr8lLf4KHP6KGrwsLqiiSUlDSwpbWJ1Q4AiZ5Aaj0wgPOMTRIlhCSIjkkSkXkRdT27Yzu7V7aEt0aLeK7PXjJnss9/++EIyLq+PO++8c7cWXOyOjz76iI1bSwBIdCRwy0VnkZIULbBFQcCTmIdktBAK+LCELViapuJ3RSeASEYTjsw8AEJ+Lz+LAzhi1lROnrcPtz33FquK2oPSexJ1Hd2wrUGF4pYgCAIqMDLVjLHTrK+tObSGFpllZ4+LNtfbJSi0qwQ1AUWDjU2BqCLbPSX+GPsXRi3zFy1lyIB8xowYxtryekKKiigIDM1OiVji2qhx6pYEk0EiJcGCP6RgNZtIdtigsV3sZmekcd15p0ZE6pO3/R9blsYu0Lw7aWlp4a677ooIgz1nH8CYiXtR7wlR74l+YKh9yH7dHpqGze7ikgVd3JkSEhmd7aAwvX388Csa1R6ZLUEza90iS10iy1pE1rpFPvtwLfLgfORB/fj89aVUBQSqAwJu0cpZxx7O96uK+HbtNhqD0BwClwweBfyqwNTRhXz0y2+RRJzOGLILup5jB+tdc1AhKSkJMegnvWg+mZXLyKxcFjNuLhadBVzH+LvO8Xh2u50r/30Vp5x2WsRyvXjRIm79z+1/+n6zmqaxeMFPQFu/7UNirldSvAWrzY4lJR13WL2raBiMRhIS9J6wBqMRTdNobW0lsQ9uULPFyqDCkZjCReQ9zY04a8qp3LSGxqrSqEmiomp0rmPX4vZS3dCMP6ALQckgkZySwvARo3AkJuINqlHWts6Lvl+9c4vT2T6OBsJJN20t0fpCamoakybr4r6hsWm391LtDtEo9mn5s/OHnmFbv8bVK/WWIkaTiSuuvpb9587brcUrO8c+pSQm0NxDoHybO7TOK1PWGmJzg4dV1S6WlDu5/ZWPWbWtisFjJrC2ppVV1a2sqW1lfZ2bRUUVPPzq+0zecy+8Bhtbm7xsa/ZR0uyj1OmjzOmnvMVPnSeIK6jS0QAjoBewzbYbGJlqZkq2lfQkOwaLbYfr1YXk7Y+R6S6eIKjACaeezqAhQwGoq6vjscce+107U9TX1/P6048B+qB6/fmnk5PZ1e241DIcyWRGCfkJed0YTGZMNl38eRtro2JPAKzJ6dhSMhEEiZDfx0/GoeQefyVzzr2GGz9YxDfm0X221IVUjc3NQVRNL38xKtXcbUCy0WBA7WixizEzTDRAoU0/30AgQFFzoFOjby3mssY0KGpZtmYDU8aPYUNloy4qgWE5KTis0XE93kCI+lY9FjE72Y6sqLj9QXweN3a6WgZGDB7AoCo9W0/VNK48+mw+nL37i+K2oWkaDz/8cCROJ2/QMI464WTcPUxodrW46wlREEi3GZiSbWVEqplsmwGLQf/+MZjAYCKkQasMSl6mLuyGFCAP7c+y1bWU+AS2+QQCjgwm7TWNB9/9kqU1HjZ6RNa5RVa3iqx3iwyfMp1fS+u598ulLG0RWdMqUuQVKPcLNCVk4Q0qPd6rTS0uUjtMkNRw2IJtW/e1+zrTUcj1hiAIHHLoYVx59TUYwvGdy5Yu5aZbbv1T96neuHEjDeHkpoHDR2FMTO6yjkESWLzgJyZN3SvyXHPLKl5Zw93qwuVyEvD7ERDw+XxomobNFrt8SWfsCQ6GjhyDIz0Lg9mMoshomkrQ58Xvbo34YiVRiPq9JVHEZNTDUiwWEyPHjGXCpCkMLRy+3bHsmZlZVFdVRf5vCpdl8oYLGPeVA+YdTNut+Mknn/whXY4ks4RkNvSy7J4Y3V3JHybsPB4PN910E0uX66LObLFw1bU3MHrMuN/9XNKSEmlwRmei+mWVWq/MpuYAy8Lu0CJnkPLWEPWeIO6gwsp1G1i0dDknHXs0FoulS1zSh599yZhRIxgzYjiioGfItQVnmiQBkyRiFlQckkamTaJ/opHhKSbGZ1jYM8fKxEwrg5NMpFikLlaU7aVzNuzO7gtAE42cf8nl2BMc+EIyCxcu5Ntvv90lx+gLr732GjkZaRgMEvNm7UXhwK5WiKWW4QCRyuxKKICqyNjT9VInqqLg6xDf2EZCZh5mRxKqHMTnrMfTWMuU6bMYN3lP3nq+59ZqHScOpa4QfkXvGTE02Yylhyyz9ORE7BYLbT+1oZsg/2Qj5Fv04zf7Zep82y/Yq2rrEC2OiJt1YGYSGYldZ9iVzW5AwCCJ5KYk4Am0W1ASOmXOtjE9sx9p4clHldfNhpbfLxj6888/j9RGE812zvnXpV1qXXa03DX6dNGhqtrvKvAkQSDVIjE42cTETCt75lgZn2FheIqJAotG04+rEZ2tCL4Agj+IEAhCMET9+orIWDJ+5HCGDxnMx19Hx7gKgl5a4qSjDuPHRb+ytqgYtwINQYFKzcbmeje/VTpZWuFkc72b2tYAgU6TvsbmFlJssSvp51Uv7/Pn7E3UeYPRk6oJEyZyzbXXYzLrE4yVK1Zw6623blfD9d+T+fPnR/6eNG0GAO6QElkAli1eyK8LFzBzv/ai7pqm0VxXQ3lpCZqqIRkkUrJy8HjcCIKAI8GOJApR4RrdIUkSqTn55A0bQ96wMUiSgaDXg9/jioxTotC180RSgl2/VkwmWl2xW5L1hVFjxlJV2V4TtM0V7XW30ljft9jkUDBIWmoKuXm6t6SoqGi3FvDtDtEkhcVd94vYU4HSPwl/iLBrbW3lxhtvjPR6tdnsXH39TRSOGPlHnA5DC/JYv7WMoKJR6Q6xot7H8jo/W5xBGnwKwQ4BsGZJIMliwEaIb775hn/94whmjRrAqKwEhqcnMD7HwcS8RJSGckKtzdxy2hFM65/CXgX6MjU/mSn5yUzul8ykdCMTM62MSbcwNNlMvwQjaVYDdqO400IuFruynZrP04oiy6SmpXPaOedGXn/qqaeorKzcZcfpjuLiYr777jtKKqtx2O2ceEjPdckkY3vKvRIKYrIlYE1K062xDTVdYu0EQSAxuwCjRZ85u+qqkIMBjvjHqYSCQbZs6L1grF9WqQsLhxy7gRRLzwOCzx+g1etFDvs5DD3EcuSZNT1eC6hwhyIlUgo61Vl0B+WY1qqGZhcBTb8espPt5KZ0naW7fEFqnB4kAQrSHBglEX94X6IgYDZ2/TyfX/ggBlHkwNyBgN49Y21z/e8y+y4tLeX5558HwBOUOf3cC0hKTkGRZQLerqEWncXdrkTs331Hi5jrCwJ2o0ia1UB+ZgrGtVsw/boG88/LMf+0DPOPy7DMX4rlh19peex9piap7JmsctMRM3DXViBUb2EPh8pYh8oQm8rIBJXZg9I579DZfP3V19hlL4kGMHWYWARllTp3gKIGN0vLnayobKGirpmQorJuyzaG9e8XdY5qjO9wV+ANqlECb8zYsVx3/Y1YrPo9u3r1am666aY/RaZ1R2RZ5uef9f6nRpOJMRMmEwr4kIOBSMbqV199wQtPPsE5F11KfocYz6aaSuorywj6/ZgtVgoGD8NkNqOEQljM5igjQV/EXWRdg5G2maEoSj3ed3arGZvZjC8QpLEhOhO7s+DuiZGjRrNu7Voa6vUadGmZ2djCLRJrqyppaui+jI2iKFRXlrFxzQoqS7cxbMiQSKOAtn7OvyeSQejT8mfndxd2Ho+H66+/nqKiIgIhhYSEBK69SW9+HItdHVvXGVXTGDigPz+u3szSWi8lrhDeUDiuDT17MS/BwKg0M3tmW5mUZWVUZgJfff0NU0YO4ZC9J5BqNZJsMeKwGLCbDGiyzMsffsmZRx1Egj12nIHm9/Lm5c9GLTtD09DZrM7Zu9cyJ7tC3KmKQvW2Iko3rKKpsYkxE6Yyc/YcQrJCIBDg/vvv3+2Bzx988EHk76MP3Kfb77kNqUPpACUcXGxLzQRUVFUmEKOJtiCKJOUNQhAk0FRctRWYLRbyBw5h7W+9V8yv8shoGkgC9EuIbd3qiNFgQNOIiLTuLHagj935FhUUGb+s0bAdVrtQMEiDV8ZkMmE3GxmclRwz9KHOpbtgRVEkO1kXuP6wFcJslHoMlxiYkMSwRD0ruai1ebd3GAgGg9x3330Eg0E8QZl9D5jHmPETaG1upGTDKhrLt6IoSjjruOv2jT65W4EnCQJS58+qdVg6kR7YuSKrX179fJ/XTUqwcvL+03nxs+8RlBB2SXfXJxkgxQiHTx7JmIIsvv/hB8YN6ceU/BT26p/KqCwHeUlW7KZ2a6YnKFPiUVm0tY6fflvHwIEDehXkKRZD1LK92Eztj6COAm/EyJHceNMt2Ow2ZEVlzdp13Hhj90WT/wiWL19OdYMeWzZi/CQEJUR98Qaayoup3bwWd2MtGVk5nHv1jRSMGIfTL+P0y1RV19DY1ERIUcFkpf/QQuzh7NiArMb8ziVRiFmkuDNBvw/JYEA0GDBarFH7EoToHQiCQJJDv6+93ujST9uDzW4nv6CAreEEOkEQKBg0BFtCApqmUlG6leryUuQO8ZKqquJyNrNlw1pczc1omoaiyIwcPRqfTw/lWLly5Q6f047SuxtWX/7s/K7CTtM0HnzwQbZt20YgpJCYlMR1N/+H/gMG/p6nETmXWq/Mino/alIWLl+A6tp6BAFSLRKFKSYmZ1sZl2FhQKKJZLMUmTn9vGgpG7aWcu5xh8V8uH364yIy01KYNXl87GOHRd1fFW9TLYosoygKRpPurjnupNPIyc0lJCts2bKF1157bbcd3+12s3DhQip+WUrjujKaXo2dHdjmhgU9+cRgtiEZzahhYWcwWxENuuBTQrHbYUlGI4kZutvW79Jb+IwYtweb1qzs9Tybw/XqMmwGjH1oQ2My6cHTqgZIBgySiGDvvjxHogR2ixE0leZAtLDrzlIH4HY2omkqBkliUGYSoiCw2jioy9JmnUu0miIlTkKKgtVkwGGJFqqfX/ggn1/4YOT/giAwPjULJWy5uO/YU3r9/DvDyy+/TGlpKQB5/Qo46oSTATCYTARDIZRQEHdju+DqTq90TrCQBIEad5AadzjOq7OY6+Fn3V6rHfRd1H19x4cIdgeC3cEB+0wjKTmJr1Z17XMsCALnHT6H3zZvY9HKdYAuElJsJgam2tgjL4mpBSkUZiSQYtV/04qaOoIqBGxp/Fbvp84rdxEb2+OO3V7aBF5u/8Fcdf0tOMIlaoqKinj44Yf/kNirWPzyyy+RvydNm4GzqgQEAb+rGVUO4mmsI9GgkeKwE/S6CXhbcVaV4qwqQfZ7MSc4SOs/JBKTBvpkUu7BmNGbuPO7XYT8fjRVwWx3RCyHAMlaV/GmKComgwF7H2P6uiMtLYPmDiWYTCYzBQOH6mEQmkZ9bTUb16ygaMNaijetY8Pq3yjZsomA30cwGCAlLZ28goHYrFaSkpJITU0lEAj87kLeYJL6tPzZ+V2F3ZtvvsmSJUsIhBTsdjvX3/wf+uV3Xz9ud1jrNE2jzivzW73uavXLGpIkMWFkIYGmGiZl6kHN6VZDl8xFAFlWePnTbznz0P1IcnR1X6mqyte//MoR+06PKfp6EnU7YsFrGjqbpqFds/B6Ynusdm2dKdpQQiHkFj0mzZGShjk8IJgtFi6+5DIMBgMhWeH999+PPGh3NT/99BPb5utibnhSOgZR5PVz7u9xm7bfQgkFIha7jg2u1R4sjKaERATJgGSy4AsGyczOxdncFHEZxMIvt3cISTb37TYzGqSoTDZDuP9j2wO8s8gTBEgOWzxcwdgz/ZjHMRoRBBEnVpLtlm7Xq9YScIm2qOvYG9A7kfSl1dBQRwqp4Vi7Uo+LhoausYy7guLiYj7++GMAAqrA2RdeEinuarU7sIYth60NNShyu2jr6euq94SQENoFHeh/d7x1drFHZnssdR0RBIFDZ07l68UrIEYJk9TEBM78xzG8+MHnMa9ZoySSkWBmVHYik/NTCLY0Mm7kMERRxC9rFDmDrKj3U+/rKvB2N/0HDOTf19+CxWpBVlQWLFjA++/H7nH7e6JpGmvW6O3zjCYTQ0eORhAlUFVsKRmY7In6JE0O0lpbQcO2jTRs3YS3Wb8HJJOF5Nz+iFK09UcQ9CSHnurHiWLXJXJeqv77igYjkhTtihU7jfv+YJDGllaCstzlWu5oSe0LqWlpNDVF398ms5nBhaNITc9EEAS9HV4wiKe1NVJU2WS20H/QUPIHDiEtMxtBFBkwcCBl5RUUFxezeXPXycruRDT0ISu2D904/mh+tzNcsmQJr7/+OoGQgiAInH/xpeTk5na7/q4WdZqm0dLYQM3irygKCzrQe3WOSjOTKMpYkTFJAp9Zu7b6auOHZaswm4xMHz8qquF3Gys3bkFRVCaNbi8wqXpaUD0tu9xSt72CblfgaaiKCKK0nPYYHFmDgYMGceTRxwC6wH3qqad2y4OgY4LG6OS+t2WRjGHrXFC3zskBH4IoIkpGTLYeCtdqGnIoRNDvQ0AkISkZNA23K3ZRUCCqxlxiH2d4ZqMRVdUFmoYWM8aus7hr6zUbVLQ+Na4H/eEhSSIBnxdV1VhtjF0zy2xPxGA0Uy7bI4kF/pA+IHfuTNHdcUZ3KI78wOzYpSB2Bk3TePLJJyPX2aFHH0defnsSjTsok5SVp5eaURVc9dWdto9eOlLj2f5szI5u2AopnapBs6ga1HunkJ1lzzGFuH1+1haXdrlGDNkFzJ66B5qmsWD56h5j5cwGEYuokm41MirNjCN8fflkPbv7t9IG6t0BKrL1MbKvfWO7oy+xXPkFBZxz/sWR0i0vvfQSK1as2O5j7Upqa2sjE5XBwwoxGAzhcA99bEwfMIzU/EF6R4WwC1QQwGizY0vNJGPwCAymrpOqNmEH9Kk4cJftRX2sUWUZv6c1qtBzR1dsMBRi47ZKZEVBFASye3gW9wW73R4zBtJoMtFvwCCGjR5Hdl4+qemZpKZnkJGdy5ARoykcPY7EZH3iJUkSZouVgQMHRSyN69ev36nz2l4ks4ShlyWeFRumsrIyqgfcsSecyNhxe3S7/q4WdT6Pm60b1lBVuhVfWNA5woJudJqZDZs2s3ZLCVPHDO9xP4qi8P73v3D0ftMjFovO4m7B8tXsM2V8VNsiQTIiSMY/jajbkexYWdXw+7x4nXqGY3JGdsQN20azX+HQww4nKyuLkKywZs2aSHDxrqK0tDTSIirTaifD0u5C6Gi1W2oZHu1CAwzh8w35PGiqSsDdghzwoWkqph5cni2NevCvIIqIBiMGgwG7IxFXh9pNnQmqGpKglziJZfmNhclojHj5VFXD0E0x6Y4PbkvYxWsQVAJy335Xg8mCyWQiGAqyxNd9vSxrYgpyKEDQ72FZKAOPP6THBQE2kyHmxKYzozoIu3Uxso93lu+//56NGzcC4EjLYv95XcWjwWQhIUWfAHia6wkFunfvdCfyYq/c9/PcHeLuq+teifxtNBiYsccoFq7aELVOW706SZI4+oBZvP3ZN7olyevuVuDtNX4Uv63fRHFFNWPSzIxMNZMQrt3llTU21bvZtnEt/nCnhM49YreHvhadnzBpMkccfSyBkF6m5cUXX/xDG8avWbMGd0D/zAVDR6DIIULh76NtAmmyJZDWfyg5I8aTPmgEaQOGkd5/GMk5BYhiN/e2IGzXddWZhJQ0rI4kNFWlrqQIT0tz5GIWwpmx/mCIjSWVuMNF+Qf1y8Juj7b0bk/yBEAoFMRkip1FDWA2W8jMySMrrx/9BgwmIzuX8rKyiDdA0zRczmb8Xg8F+fmRGO1169Zt13nsLKJBRDRIvSxxix3BYJC7776bsrIy+vXrx6Spe3LwYUd0u/6uEHX1Xr1pfZ0nSHFJKZvXr0NorMTsacRhEhmZamZMmpkECT79+Vcefv0Drjj1aPIy0yPWus+sE7osj2yVKCGZGXuM7vbY5TV1DM7Pi3ptVyRHdEQc0P3xY7Ej9eti4a3XaxUFNYGgLTXmOiaTidPOODPy/+eee26XxkksXbqUil/0QPyRSbGtdZ/Ig7q40GrcQcwOfWaoqgoBtwst7JaSjGbEbhIVAoEAAZceO2JJzkAIC/rE5JQehV1A1lC0vos6AJPREJmta5oWiWuLRZtr1iTqrltZ1cVk2QBdQCSYureomaw2LDY7cjCEq746Kg4ner32eomqIvObz4FLsCGJQo8u3I6kma3kWPWHRo3Pwwt7H9Sn7fqCx+OJ9Cr2BGVOOPXMqNIm7qAcEWiOjJxIlqCrbieztgV98Suq7nIPLx2pkLrWU+zJerejbtiODMrLprw2PAkJXx9tAk71utlnbCFen59Vm7f2uJ/+udlcfMqxPPDCG3y9fB1JiXbGF6QxKjcZR7gESsDno7poHQ01Vb+be/bIY45j/ISJpGZms23bNu6+++4/rIBxcXFxpNbc4MLhtFSXoSoKIGBL0X/7yrJSZFlGEERMVjtme2Jk/OgOURR2qJ1aYeUCCisXMLJ2iR4TLAjYvA0ozdXIrgZ8Hg9lTj8tbi9ej4fmpWto/m0dgXe/pPjSO7f7eJ0JBkOYTO1xtxUXnB9ZYlFWWsL999zJ0/99jNqaaoo3rae8RE++SE5NITs7B9DrBP6eHUhEkwHR3MvSw9j6Z2G3C7snn3ySkpISPQvGH+Ksf56/24oPtwk6gFDAR8O2Tbjrq3H4mzCKAsNTTIxJM5NsFlm4aj0X3fsEXy9azrVnnsCkkcN6dMECbFm7ksLxk7q1pGiaRnlNHXlZ7YKjL1aNHSE9FKNRuG33XXAhr5ugR88ctaVmkZvcNdhW1nSr3YSJk5gwcSIhWaGpqYk333xzl53H6tWrI3/3T0ju8n5PsXYNsoQp3Jjd72qKPJC6ux5VRaG1qgQ0DUEQsaa0/65JKam4nE0xt6sdPIs2L6qs0ecHX5uwC3n8NBdVUfLeol63CWl6xwqEvpfIEQQBe2ISwVAQJRjAWV3ezTm2709VVTzNDYiShJw2YLtKMIxMTov8vcXVvRjeXl5//XVaWnR3+ITJUxk5Zmzkvc6JI5LBiCNcu9Draibo6710xvbqFb+sUiGlxxR1Heks7naFqFtyy+s0v72IFd8sY8ktr0deX3zjS5G/jQYDk0cXsmx9Ua/7m7bHaP591ol88sMvXHzHwyxZvZ4Uq5FxOYkUZiaQYAqL5JpySjevJ9iDFXRXIQgC/7zgIhRFwR+UKSoqipS3+T3RNI0vv/8Jj8dNano66ampkQ42CZk5tLS4eOmJh3j49hupKu97nLEAqIoaszB5dx1Ekjf9QPKmH6JeG+dcxQyHhwyrBBqoGqh+D+6iLQScLkJuH2JIJmnJKqylVQjohafblh0hGAxgNJp6XzHMoMFDuPPeB6gsL+W6f19GZXkpBoNRd8UOHRFpveb3+39Xd6zBbOzT8mdntwq77777jm+++QYAGYnzL7kC0WzFtwOxA31F0zTcjbXUF28gFB680ywSe2RYSLMa2LitnGseeZ7nP/yKo/ebzkNXnsu4YYN6FXWaplG8bjVDRo3rcd1gSMZqab/AO7Yf2xV0tNZ1FHeh8CyvL+Jue0ue6LXe9Ngk0WCKtOSKRZs38NTTz8BoNBKSFT7++ONIJ4CdQZblyE1uN5pIiRGjAtB6/gUxXxcEAZMtAdAIdihvIgf9yJ2q2yuhEM7yYpRQuD1Oejaiof2GdiQm4XI6uz3XBKOEKOilTmq87SJDVVVcAYVKd4iWQHSNxLZyJ6CXPJFEgSW3vM4v933Azw9+SqVHwdOpY0CFW9Y7FwjgHDw9+hx6mFla7Q7E8Pfnb22hqXJblw4cfndLxC2kBAMochBVVbA4kqPW65gNG4tBHQR4mWfHC6F2pLa2ls8++wwAs9nMsSedFnO9jlo3IS1Tr/MFtNT2brWr8wSpdetLBE2vZbmz7A7XrEmUCIVjNJfc8npE4C2+8aXIMnHEEJav39ynycbEUYU8cv0lHLbvdJ54/QOue/BpNpeUk2E3M37MaFKTk9EQUX1utm5YS3N97U5Z7/rikk1ISOCiS6/AYNR/x08//XSXh3v0RkVFBS3OZgRBICe3H0ajEdFowuVs4p0XnubOqy7CZDJx3T0PUTBwcK/7q3a3Wx3lUAipg9U5IKsxRZ2qqjibGrtYituwGkRW3f4q2VYRq0FEaWxBCgQQ/QEMLa3YN23D4I0txhVFwdnUuF3W0FAwiNkc2xUby2qXuPQ95A0LOW72ngwdMoRnn3kGbyDIsFFjcSQmMWZ8e6jW71nPTjAY+rT82dltZ1hXV8eTTz4JgDcoc9b555PXrz0D1ierWHehr7reK6OEgjRXlkQsS4IokZSdTyA5jeC273n6429YsGItR+23N4fO3BOLue8zjMbaKnw+D/mDC7u89/aFj3Lc4xchCAIpiQ6aWlrJSovtqtxexLaHaFq/mO+3ibtqqd0qkmUzsL5++yyFth7634U8LmRfuKVQejY5ST2L1XqfQnZ2DvMOOpiPP/oQr8/Pu+++y7nnntvjdr1RVFRE8fd6D8ECe1KPlt/W8y/A8d8nurzeggUJ0FAx2RJQQgEC7hacFVtISM9BMlkIelx4Gmv0DDPRgC0tG2tKZtR+RKnn4p/BkbNJXvY1TX6Vpd4ERFWv8q4GfKiqiqCpYDAQ+PxbWKHHiK2rKo60J9IAgyCiCQKt44YjyDKlrTI1koCGgs0gICsarbJuTbQNGoNhO2bMZosFS2Iq9pR0PM5GvC1NBL0eEjNzMVls+N0teqKBAPbkdISwq1oQRD0TWu6+6GhnMi02zJKBgCJT7m2NykbeUd56661Ihude+80jLb33JBpRlEjMyKG5ugy/x4Xf48JiT+x1OyAi7tr+7djvdUdpF3c7Z3WSkvSJVqscJNFk6vG7HTNkIA1OFzWNzeSk9z5GGQwG5s6YyqzJ4/ng25+4+dHn2GfKBE493E/m4OkYGupprNyGSVWoKS+ltcVJTsFAjKa+X4vbS/8BAznl9DN54ZmnMBslHn30UUaOHElaWlrvG+8CVq1aBYCsafQvHIXRasfpauXlF18gPT2DM848m4ysbFR3M0GLGVM4u71zSIyxg+en2h0iN8FISA5hNPRsEdI0jeaGemqrq6hq8pNkFhmQaMIeHsPfueK5yLobPl+K06VPqm2l1Uhu/bkQ6wqRVZWSJh8VdctQZJnc/P4kp6YjmYyIvaSAB4MhWp57joqvvo75fpu4G33WHDQNinwCQU0fT87YZw/WJSn897FHuPCSyxk3fg/GjB1HUFExSSJLly7lzDPPjLnfXY1klJB6cbVKyu/nGt5Rdouw0zSNJ554Ar/fjzcoM33Wvuw1fWaX9Tpa7oLBIE2NDShykFAohN2eQFZOTp+PGXC7aCrfiqaG06jtDpJzB2AwmVm9/Feeefk5MlOTefiq88lMTY7atjdrnfeCC6lubcZRW0bwkksJAu90WuftCx/l+PceJDN/AFVBAyOzB0U1SN8RREdyt4Luu6bO/WJ3zuXrDWdxdhZ4mqbhDVvrJJMFc2IqNa3tM71sR2yrWb1P4eBDD+Prr77E7/fz5ZdfcvTRR5Oe3rObqic6umH72Xp/IMcSd4LRgj+kIggCjd4gKQnJhHweVEWmpWpb9LqIWFOzsKZGizrQ3bSx4vL6JVrQL2uBqtzJ+OrKIBRE9bUHqosmM2rAR2jVaoTsNDS7FTw+Xci17V/TkASBYFYaqsWManYgGIwYTBLeoEJL+BnhsEu47bmkZETfKwYRjJKA1Wjs0vge9DIDwWCQlFw9uN7T3IAcCtBU2f4dGE1WkEPYk9PwtuhuZ8loRhBENL+3V0td5HsUBPJtDra0NuOVQ1RWVtKvX+zrui/U1NTw3Xd6Gy3RaI6ZMNFGZ+1tT0mntaEWORSgpbYS80BH7OLMnTJiM+0m6jzBHRJ0mxq83W63+tjYlsa+0ibqpj14MS0/LiL5vvbWTuVemfwOFvxyr0z5da/QWlTDa9e/EAllOP6/l0TW6S6hwgycsO9ezJ46gSde/4BLn/6Q406wMX7CRBIciXp8lNeF7HaybcNaxg8fTFKig+pA3ybvNVVV+HxePTHJbCEtPT1SsiYW++w7h00b1rNwwc+AjyeffJLrr7++T8faWdoK5xoEgaEjR9PU2MinH3/C1NkHMnPmTOylK2hQZfyuZvyuZiyJqSRm5YHY++NWDoUi1sjIa6oW5WVRVZWK0m2EQiGMqoYzoLK6wU+Bw0iuPfoYUSUXexD8Tl+Ioga3biE0mwkG/FRXlCEZjSSnpaN2k9HRJvgaP3yfnLTeJ1drn/sWT2Y66gz9mZtj1hhghcIZk8hMSuCtN1/HZrNQOHwEw4YVUlJcREVFBTU1NWRnZ/e6/51FMhuRenG1SuquiVnfnewWYffTTz+xfLlewDIlJZXjTjo16v1QKMTCn+azZOECLBYr5WUlNDc1YjAaMZvNGA1GvF4PM/fdj6OO+wcWa89N7z1NDTSWFeujuCCSmJmHPS2T1pYW3n/mCbZsWMeVc2cyY8Lo7bYUeC+4UP9XDmLrZSb11tGXMfWMA/l58a/M2WfGdh0nJt2IOhorQBi68/uPgTekRom7YKsTOaBXArel52zX95eUlMSBc+fx0Ycf4PMHeOeddzj//NjBtH2hY4ZUfh8tLZ1Rfa167Ls1AYxmbCnJGMxWXNUlKJGZmIDJ7sCR2Y+GkEisq09VVaRuMtvaEE0WrNkDCTbX6IkagoBoMGGwJyIYTDSvWQuBINjMurATRTQNFA00NCRBRDGbEEIyBl+AvQpScAVkmn0hQoqGiobNKJE0uDCqrlybqGsjw95V3JlMJoKBAIIgkpo3AFtSKs6aCoIdYkJFg0T6gCEYjGYUWSbk9xLwupGDgT6Lujby7YlsadXjkJ49+ARuWbVgu7bvyNtvvx0JMN9/3sHY7NHxnt0VZgbdQpCYmUtT5TaCPg/+Vmekzh10FXS9vd4Tmxq8UX93Fnc7K+o68/PyVYxK0q1W5WH3f7m363dhNxjxyDuWdJBlN3PbxWfxYbGHJx97hLHjx3PyaWcyuHAk9TXVNNeUYdBCrN+4iSGDBoKj54e91+PhvTdf55ef5mO12pAVmYDfD6pKaloa+QUD8Pm8TJ85i71nzIokxwiCwMmnncma1asI+jwsXryYhQsXMm3atB36XH1FlmXWrtXbCSY4HOSkp/L4hScwa/ggThosQeUvBEWBNNdWalQTLcn98Lua8LtdpBQMwWC2MuDTRyP7qzzi0qj9h0IhjMaenzOiKCKIIpLBQKpFxCvryVMlrhCuoKo3hg27b7UOgswiiWRbbCgdamUC+PKzWVvTHiKRlJKGs0m3yHcWmZ1R0ai6QA99MfShtqUqSbjyctHKGjC1unFv3EzbqD79rDm4fat45P/u57a77mH8hImUFOvxoEuWLOHwww/vdf87S1vma2/r/NnZ5cKutbWVZ555JvL/k844O2rgDQaD3H/HLfh8PvaZcwBJySkkJiaRmZVFUnIKUviBVFNVxSvPP8PN11zJv2+4hfSMrgOEIsvUVpbR0tgAmoZoMJJaMASjxcavP8/nozdfYfiYcVxz5wNM8/Te27MzbaIOwCOHsLcJO5sFrGb9X0Fo/zcYojAzieeXLWPbb4vJz0zj7Ysf3+7jtvH6UZdy4vsPRb32XZN1t4m6zmiqgqdBz4Q1WGyYErovjdEdBx96GF99+QV+v5+vv/6aY489doetdmVlZQBYDEaSuomv6wk16ENprNR/KzmEaLKEs2eNaJlDyDTr7cYMFhuiJEUyaxu8IdJt0QOcqqoIfYhVFA1GLBnRRbg1TSPkDLsyzSYIW/50i11bVqze9UAzGtGMBjSDgZ/uep3ZN5xMii3aklGxAyENZos1KuDdkpBI9pCRyMEQoaAPo9kaiUcDMNnshCp9IAg0lhejGQ0Iob67JPI7lGip9e94z8/q6uooa92BBx3c7brdecptSam0NtQQCvhoqa3EkpCEIIo7JN66o6Oo210c9PhlQNiFVlnL2i0lnDNiOOVmOxj1iv94/fpD3ucHXwC8fmydhN1b5z8M6JY7sUOB4+6sd5rPw4xZsxk9dhyvvPAc11xxCSeddgbTps8kweGgautGQrLM5uKtWFPcZOblR8WNtVFbXc19d9xKTm4et93zAJlhi4ymafhcLdRWV+NyteBsdvLZxx+x4Mf5XH3DzRFxl+BwcMrpZ/Hcfx8B9D7V48aNw27vmti1q1ixYkWkXtuI0eP4v4ceYmR2BifuMzWyjknUyCFIphCktmUrmxIHoykhmsu3MHHj/B73HwwGyc2LrqpgDt/fbbF2giCEY3ybUTQYn2Gh2BmkOaDS5Fdgj+F6eIeqYRYlUs1WRAQGHbcv8x/VS+Qo4ZvD1y8b79ABmAGzQWJYhp1yixVRlBAkEVunMijdoWhapMtMT7TmZqOFf7+k0vIoB+/a577lwDP3Y42YyZOPPcrpZ53DW2+8htkg8dVXX3HYYbE7Pe1KRFPvFjuxh8L0fxZ2ubB77rnnIplqw8dNZPzEyZH3NE3j9RefQ9M0brz9npimdlXVK2ln5+Zy+bU38eYrL/DYA/dy8133RtW8cTbUU1dVjiLLmMwWVBVSC4agIfDyfx9mW9FmTjrnQkbtoWfX0MdnSUcxF8FhwyimI4e8CHOm6oNm22dq9SA42geStasrGVI4nDtf/oD9Rk1CnL4HWl0TOFvRmlpgF5Ue2Z20We28DTWR9lu2jNyYN1VNq79bd2yzXyElMZG58w7iww/eR5blHbba+Xy+SAJGqqlnC25HIokUCVbMF58Fqm45k9Lyogp2CoJAfRDADD4F6Pl3iuWK7ZfY/j2oqoqmqlRXlLFm6UJamhpJSk1jn4OPQG1pQPG59Qev2wu1upvTED4fSdBnwpIgYCmvJpCbqRdEHjOUyhYfeUntn78ieyJ+n4/lvy5GkiSGFI7oMgmK5Yo1m80EAl3bqElGI1KMWbrBaCIpux/N1WW4Fi1CmDgS07J1CH28ntPN7efcGLYA7whvvfVWxFp34MGHRCaNvlDfg/YFQSA5qx/1ZUWEgn5cDdUkZeb1viHQ7JNJsf6xwdOaQUJNTaKk0UOTL4gnEOL5V99m+MjR0H8YQoeEHM3lQUjsIHRCMqHP6jHZk8BiBXf7b9FR4AGItoQeixmnpKRy8eX/ZumSxbz8wrOsXrmCs8+7kPzCMZQUbQqP03W4nE1k5RWQlJbe3ulFVXnk/nuYstc0jj3xlKixxSJJWFJSSUlpjwGcte9+/Oem63n9lZc49YyzIq9P3Wsaq5ctYunSpTQ1NfHiiy9y4YUxxvBdRMdEjQafTH11Jf88dmbMsVESIFcKUp3bn5aqbVgqi/BKZhKU9vsu78OHIn9XHnEpDfX1fUpASU5Lx93qItViwCQKjEg1U9wSotYrI2Smoo3XxZ1HDtEUvt86liORNRV/XhbeYQMAsJkkxmQnYpREGmx2zBYrFru92zJQncmw2qjtQ79Zf0oyANaGRoy+ruPAuue/Y7Ysc9/yX9mw114UFg6npLgIl8vF5s2bKSzsGuO+K5FMxqi+4jHX+Qs8w3fpCLVy5crIbBqDmRNPiw54/On7b1m1Yjk33n53j/ETbYlRgiBwwiln0NRYH7lxQsEA1aXb8LTqpmNJFElPzyA9M5vNtc0898j9iKLAlbfdTYJj+9x1EVFnkCAnHdKSEdKSwGTEUbKN1vVrokQdqqYLtVaPHsxgMpI7aRjjAn5e+PA9ChwZDOs/AAQQhuRHZtCaPwj+AJovoLviZAUUBU1W9L/bXge0qi36d2EOi4YO1rrSLZvoN2BwzNnwztLa6ibQrBcANSel9diZoTdxt/cBB/PJZ58TCu641a6ioj1eMdW8ndY6mwXzxWeDIoMgYMjsj2jZvll9g1cXR22WO1WLdsW2iTpVUaiqKOG7Lz5lxfLl1NbVM3zUaLL6FeBxu2gu3YxdEgiuXo1W0wjrt0ZMS5Iodqhjp/9fCgRJ/G0d7uGDUBIT2NbkJaSomA0SRbKDUM1S5n//PWvXrMZssdLsdDJ81Bhm7LMvU/faE5PJFNsVa7Hg83T/0I5F86XXIg/qB0MK0BITCE0YiXH5OgSl95m6zWDEKhnwKfIOC7uamhp++EEv7SAazew/t70mntWojw8dP6dekDX2viyOJGxJqXhbmmhtqMFrSEAy9zxhyLT3nhDQ2VInh0JUlW2jYPAwNjV42devt6Gq7Dc1aj0NwGxCs5jRDJJuxTVIaAYJzWQEq1l/z2JCs+rX2oovfyVj6khWrVlLXV09Jx59BP5ttdjlEEIwpH8BEigi7enBkhG/QSN91BBs+QX4vEF9wtnQDDWNICu8df7DPYq7zsXRJ0/dk6GFhTx4393cc/utXHLFVQwePoqGuhrqqitBUagt20ars4nscGKFKIpcctW1ZGRmRokiVSVmrQaz2cwlV/ybm6+7mkGDBzN95j6A/ow46sTTWLNmTSSWd5999mHUqO3v09sbgUCAxYsXA+AOKWxY8Sv3HTgGu6X7wrwAZkcySfUlhAB3J2HXkbwPH2KhmE1OTnbEStcRSRQiVruk5BQcY8eTXtwe0jA4yYiGRjUgZKWiDStA2dYevlLyxvftn8VuwVOo92jPHTeY0WFRB+BISSExOYXQdiQJDExK4qeK8h7Xkc0mlHDmrKXZ2e16FoOB44cN5/nLL2f/gv64hw6ioaGBb775ZrcLO8EgIfTiau3t/T8Du0wRBAIBHn+83e149AknkdxhxiXLMh+99zann3MeqWl9f6gLgkBGph687vN4KC/ehCLLiIAtwUG//oOwWK1UVlTw0O3/YcCQoZxw5nldsrJW5+zN2OpfYhxBx3vBhZCaCP2yEHLSu3RbdlhtuBqbUItKEZpawesDvy6+jvnsOYStvwG6NbHs4dXMtKbz3Vdfkb//QVjCsxQEAexWBLv+AOnRqKyq4Avw1svz0ZpaOOSCQ3CELYOaprHgq0/59qO3mTJrDgefsGtjdTRNxV+vm8lFyYA9Y+fazSQkONjvwHl89tH74A/w0UcfcdZZZ/W+YQc6CruU7bDYYTUjTR0TFnVgyChAtPbQPqyPdLTYtYk6WZZ5/bkn+farL8jKzmbylD0ZOXo0qmhEE8ItfTQNQTJg33sW7hvvilIeUckTaBELnsHtJXHVRlzjRmA1SpQ7fahJ2ZEOCrP2mc2sfWYjSiItLhfbSkv57KP3eeOl55i13xwOP/pYIHowMpvNOJu6lqDpTgyVn6r/XoatFSAIyIPzUZMdYXG3HqEPRVVTzVYqva20hoIEAoFuyyN0xwcffBDTWrejJGfnE3C7UBSZQH0F1rwh2+Xq6SkpAvT79NM3XmTFop+Ye8yJ7LnvXL63jAFgytZf9O8wJREtLNrYXjeTrJBg1K1Il558FLOG98M4qoBFlz8atZoGqGYTis1KKCkBd7MTh1U/b6vNhM+crk9kRw5Gq66H8lp+ueLxyPi053/axxcxRi9agOTkFK676TaeevwRbr3pOq68+nqyc/uRnJJKRelWvG43XlcLJZvWkT+kEIvVRmZWFgDmDmOtr4frKCMzi9PO+idvvPoS06bPjMSVpqdncOhRx/PO63rNvscee4xHHnmk11i17WX58uXYbDbsicmUNWzkpLGpjB3YexJQrSdErhrC34uhp/KIS1l/z80ccMABve5TFMUu/ZoFQWBIkomVNY0I2WkIA/NQjO33vanD+u5c/bsXAiHGZCdi6lQ7TxOIKvbdGwMTk3jDvYGgomDqxsonW9on5KZerHvDUlKZmJXFusZGvNm6B2LBggX885//7NEotLNIfXDFSr9jweQdZZcJu08++YSamhoARo0axcx950S9v2LZr5jNZsa2uUa3A1UFl8tF9bbNoOkZjTn9CkjPzEYQBNatWc09993LjP3nMveIY/s0OEdSwk1G6PclwswJYO8kGJytaI1OaGwho7GFYF0TnuNP5oxpXWPctEEdMmsDjzNcsrFRlfj8q684LL8Q0W5FSE0CmwXBagarGcFi1o8viV0HdVGMiEAhPZmiRi+VLjtBQwVff/IB65brhSR/nf8Nw8bswdBRY9lVBJvrUAN+JBHsmf26NKreEfabexBff/4poVCQL7/8kuOPP56EhL7FbwCUl7fPBtN6saxEsFqQpo4Gqxl59Wos+x2C2Ids2u7oGGenKmrUwLppw3pefPoJvK0tnHTqaXo9ppR03R3b5EQNBnT3KyBZbbhv6Frt3Si2CzstnBXbhhiSSVyxnhoBzDP3RvP7sSU4MNv0LhKiINJQU4XDnsD4sWM5+oRTqCjdytuvv8Z1V1zKISecxpgJkyL78/t8mC19s3y2ibo2pOJyNFFEGZiHmpJIaMIIjCs29Gq5SzVbqPS2Anqs3IABA/p0fICWlpZIj2CLxcJ+B8zt87bdIRmMJGX1o6mqBEn2EXLWYUrJ6tO2fYmh27T6N1Ys/BGAL995jYqSrRxw8BEYZS+bQz7kwfm97AFQFIRACMEfRAgEwBdA9PkRmlrQPD7ed25jj8JBzNlzj8i4N+3BiwFoyOma7V+8pYjUugoOuuLfFF12FaGUJAwpibTa7SCJCP2yoF8WlW4vWnktVNVRfsVz5NsMTHugZxen2Wzmosuu5K3XX+G2G6/lkiuuonDESAYXjqK+tpraqnLUUIjSzRvIHzxMv347iro+1DedNGUqr7/yIqtXrogUsQWYc+BcFi38mYqSrVRUVPDFF19w2GGH9f79bgc//fQT1bV1OLdtpF9iAifNPrLP2yqyQsBgIaR2n7SS9tFDlC74hrH/vqrbdWwGEW8P35MgCLB2CyTaQdNQ05MhXEi9JXxoxWYhJAoIgRAJ67dgOmrPPn+O7kgxW0gymylyNjOqG8ON2EEQqZIBiZ4TeA4dOIR7li0hV3VThRGPx8PSpUvZe++9d/p8u0OQDAi9PO96e//PwC45Q4/Hw3vvvQfoF9YhJ5zWRVz99P23zJg9Z4eCH1udTVSVFKNpemP0QUMKSUjUA/l/+flHXnj2aY486Qwm7921pEpH2qx271zxnJ78MLQAITcjWlT5g2gVtVBRq7tEAdsTuiVy2LOPsmnVMogh7DojCAIH5Q3hjW1r+bm2lFnZA9DCBSFjeockUXe/mAxgMSNY9QQNwWFDSEvGHwqxZOF3/DT/e2RFQzCZEYDZhx7NkJFjej2fviL73ASba5FEMCUkYepUjLYz3blgO5OYmMTes2Yz/9uvaHV7+PzzzznuuOP6fF5RFru+CLu0ZKQ9CnXhrGmoqzYjHrb9yR/doSgyoijibnXx/OvPsfzXxcyYOZMxo0djMJnJGTCUhspS3fXrbUa2pWBMztDLhRhNMUM+pXADcM3hQAspUcIO9KDd5OVryT73XFzOZhqrK/F6WklMTScrr4A8m41t69egygqu5kb6Dx7GtTffys/zf+Dl555k0M/DOeaUM0hJTaO5sYHc/P69fs4vjjiF0YnRM2QBMBSVgiii9M9BTU0iuOc4jL9tQPR134GgoyCvqqraLmH38ccfEwwXkZ4yYx8SHDtvdQWwhUu5+D0uAk01SJYEJGvPlsC+JkYUjp3AjHmH8/MXH6EBq375gQ2Lf+TQ2XuTMXkPUFTERieC24vgD7C1wY3i9aOFZEZYJVDVbq36mqbxVXUJYt4grj331C7jaixRB7B86RLGT5yI2Wxm9BMPs/mE0wFIsJoJ5GTiz83UXb9JdkgahK9wAFpVHeVFZSy84nGGvflij59ZEAROOOlUMrOyue/uOzjnvAuZutc0MrNzsVptlBZvxqAEKSvaSN6goZjDXp2+Fq2XJIlZs/fj+2+/jhJ2oihy+ln/5MZr/o3ZKPH2229zwAEHYOnj5KU3vF4vv/76K2JDOQ0uNxcccwgbhWTsikq2ECBBjH3+AWcrU+c/xSa7nhgi9hA/t7asipwps0hJ7bm+YG/ijpCMtrkUYXwhiiSC2YQYDJFjNYIgoFotyCIYmlswNbd02TzNItLo374mAoIgMC49g5X1dd0KO6ktvAgNd3YmydtKu1zfIZOJYHIissWCtaGRC84/hic//QFZljGk5u52YYfRBMZePAnG/5EYuw8//BC3W7dGzJ49O6oQMUBdTQ1FmzZwzr8uibV5jwT9firDok4yGMgZVEhCoj6o//DdN7z+ykuceOHlDOujuFmRMQVG/gD9slA0FUPY96TVNUF5LTQ0Y3v8cQ4o+TiyTVvJxcJxEyn+/gMqqvbB6/MjhM3VOVmZWDq4lU74/HnePOhMzJKBIwqGs7yxGlXTem75pKj6EgyB29duuQEqfa18u8pKUXkNaBoGQLJYOOrsixg5YUrfv8xeUOUQ/rpy0EA0mkjILog8MHoTcLGqoytEV+k/8KBD+fG7rwkqKgsXLuSII47os1k90rlCEEjs5cYTBuUhDskHgwFUFXXVZsanC/DEzWy54NY+Ha8jIzISqPdEx8W0NDdRtnULP37yLoUjRnLrPf9HfWUJmqqSmKpPFtwtzQS8biSTiVBLI7KnBcmWiDk1dj0mYzhmT2htRTVbkYQYwUaqhqfVRXNdDSarFUWWaW1qRJFD5A8uxOZIxNvqoqWpgZSMLGQVZs7el37Dx/Lx269z57VXcNCRx1JVUc7oHqznXxxxSuTvta5gbHG3aRuoKsrAPDS7ldCEERiKSpHqYrdacxja99HUFHudWPj9fn799VcAQirMPTh23bpYSSK9IQgCqf0GUlu8HhMh/PUVWHMHRXUZaWN7s2YFQWDO4ceSlZvHd889QEvIhxaCT7/8mi0b1jGhzIdTjn39rwu0f5a2777j76Ci1zq88fzTsXaK8WoTdQG/n8a6GhRFQUPDaDLz84/zOfWMsyPrdhZqm/5xOqG0FPy5mYTSU9AEkLPTMORkUF5eg3rK2Qx/pfe+1/vOOYDUtHQef/j/CIWCTJ+5D46kZAYNG8G2LZsQZJmakmJMZivGHprHQ1fRN3XmbD756AMaGupJ71CYuv+AgUzZcy9WLf+VlpYWPv30U4455phez7UvLF68mFAoRGOrh4zkJIaMHENAE2hSDbhFkURNoZ8YwCTo42BFQzNNdY0UpKcSlEyEwvd2ohw7vtRgNbOqtIrCvQ/dJedLdQMM7oeiKmA2IoVkDIKAagqLO1XFvrVs1xwrzPjMLP67egWyqsYsfSLJMo6KKjyZ6fjS05AtFmzV1YCAYrcRSEpClURkiwVBVTF4vcwcN4L3Fixn/dZy0lL14tC7osB5dwhGE0Ivhd4F4/+AK7a1tZUvvvgC0GdTex/Q1fz94/ffMH7iZBITt89iomkalWVb0TQNURTpN2QEJos+6//myy949+03uPKa6ykcPoIKd8+DrqrIuBtq8TTVIfTPocXdyrPvvc3lex8ApdUUvvhUZN1yZ/TNpwZ9qG4ngzMS+aG2kfc/+pSJEydgNpkIBIPU1jcwdNAA0lL0elibrr46sm2yycJ+OQMj/99jTAYr1vRetV9WVYpbm1jrrKPM3UKuKY8kswl3UGbcuLFMmnMoiZmZu+wi1zSNQH05mipjNJtxZBf02QXbXR/DzmRkZTFj9n6sXbWCNRs28f333zN3bt9cas5w+y6rZOheIBsNiHsMR0hPRvP4EEIyym8bocXNimr9ux/yxM3IBgNBq42A1YpsMiNoGoIsUz/7cL1JtyghGM0IJgsH+34DN9Rntrfr8rS2sva3pTibGrn40ssYt8dE/F4PdeH4IFtisn46JjOyHMJqcyAFvPg1CdnVhBrwQnICOKOD0nVXrP5dqmhd+rFqgK9/Lt6KUsxWG0G/j4SkZFzOZuRgkFAwSEJSMt5WFwGfN+racCQmcdLZ5zN52gz+7z83Ul9TzXGn6S5WTdNQQkF+vOQaJJsFwWDAPnIAosmoBxMjsNXlRv5/9v47TJKyXuPGP5U6p8k5b87LskvOGQTFAIoJREUBE5gQD5gz6jEg4hExK4pkRJCc0+YcJufUOVZ6/6junp6ZnrQs5/h73999XQ2909XV1V1Vz3M/33DfwShqMGo1+WARDuVAF2I0jrq0GdOmoK5bhtE9gLyvA2GqOHBBzVNoFju2qXj00Ufp7OzE5Q+w/qiNC6zRndvzVZIVSutaCPZ3kUlnSI/24ahqOmL31VnVIss++hEeefxJduzahUeRGBga4id726l1+Vnsq6DeHShO5LEIXbHnF9S3UVlWUuwthMbH6O08hGEYKHY7ajrNKy+/TDIew2mTGOjtpqSsYppG6PK/3gnA3ksuR7fbUGoruenJR/j4JZfhbq4l2FzD1hu+jLO7n6V/nN0xY936o/j09Z/nx7d8D1VVOe2Ms3B5vLQuWcGhvTsxdJ2B7nYa2pbN+FsXi+SVlpWzfPVann7icd5xybsnvfb2d72b7ZtfteobH3yQ888/H5frjbuEvPbaa6iDnQyMhfjEO85HkCR0AzyCRsKUGTNFxgwFv6hRLqh88w/3o+o6wUSKQGU1xx59NGsXt+KeoXHCNE22d/fzgY+vYzxp3V+lzum1amnDxC4Kc0ftAHM0hG4YoMhIgshoxsxLjRiJFFI2KqcNWgRPrm7Mv3chUbvaW2+l/+qrafB4cckKe8fHWFVegSkImIIAmAiGiQC4h4YYkQS2jAxzsKeHvsFBNq1Zw+mLLes1KZVCtyt4KvwILZVIksH7zj+NT3z/dkoMg9HRUfr7+6mrm18X+0Lx/0/FZnHfffeRyWSor69n9erVVFRNrlFRVZXnn3mKqz7xmQXtVzMhODxIKtu5V17bmCd1/3r4Qe75+9/43A1fZtHiJQDUe2xFyZ1pmsTHh4mODGDmunwME3qGMMdCmPu7WPbn30x7378azmdtx6OMahIlB59jxFWNBJx8+pk8/sRjnHjCcTidTlRNQ1U19h5oZ8WSRZQELPK6fvXMwpwzkbu0rjGUjNMRC7InPEpyiohoS1UJV733XYi+cvYkHWixMKpjFFtgbsXvuaCGR9HiUWQJ7L4SlIIi6WqvY97kbS6cdOoZPPOEVSt1zz33cM4558w5gZqmmScCM4pEO2yIm1YheLKDeCKFvnUvqNmwuSAQ9/mJlpaTLjLQC7qGERmd9LdKLchrkkC1U+Ro4xleqz6ZkcEB7vzJ93nrxW/nyo9dm69TS6TSyDYbpgmK3Y4gCBi6higI2JxOqlsWcairB0MbxdRU7B//AOlbfwfhCXKniNKkGju5YKI3gchRKzFsCh67A1mSqV26kuDwEJIkk0ml0DJpbA4Hss0GmKiZDLZsJDnXGbtkxSq+e+uv+ffDD/DLH36XDYqP1tXLERWZwKaJTkJD0xALiqcdVGaPwyTdP0riUB+mmkQApMFRiMbR1i/DVGT0xhpMpx1l2z6EguvGLSkEbA5kQZi3D6Wu69x3330AjI+OcfpZcxeWT8V8yJ3D48PpL0EbHSQTC6M6x7H5i1tU5bpj5xPBy4SGCSZVPB4317z37WTGT+T2vz9AZ79lHdefCNOfCOOQFNq85dS5/JQ63NjmEL+GLMnLCkXnNO0gF00+gGEYyIqCy+UmZpg89dSTXHjhRRi6zshgPyOD/TjdHkrLKvCXliIX3FvL7roTgB3v/ACOUBizdxAWNYMskmypJ1Vfzfbrv8Bp376eMdt0Z5YcVq5ew2e/8CV++P3voOsGZ559Dk6Xi+q6Rvp7OknHooRGhyipsKLY87GZdMoiZ599Dr+67Vbe+vZ3Tiryr62r44wzzmDfvn2MjIzw4IMPLqjkoxgMw2Dr1q0Eo3FkSeTCU46j37S8oJulFEHTxqBhwwTChkwYmcuv+hiyaTAWi3PwYDv/fPJpOnZtp/b4tZRMreUG2ofGSGVU2pZM7vrMkbwcSp1SntzNiWDUajaSRCRZQhYEzGwzhRmLQ1Hp9cOHIAgcU13DU709NK9YTqSpETmRRHM5UaIxxD17eXr/QV56+kkaa2tZuXw5Fxy9EXdJCaKqYovHcYyHUOIJlCo/bsm6aY9dtZSGqnKGh4eprq5m27Ztbx6xU2wIc0SQhVkE0P9T8IaIXTwe54EHHiCZTDIwMMDXvvY1pgoobHn1ZdweD8tWLKz9PJ1KMDZg1VW5vH58ZRWYpsnf//Q7tr78Al/8r5tpbmmddR9qOkmorws1b+ck4AyUEn3mdWyxOBgmzXdMtpzSMmm0sT6MWJDX5AYqMlZDSHVykDJJQzrjIsJ9HWzZ/DpXXv5BRsbGeX3bTqorK/C4514ZxjMZDgVDvBoZYUxNowsmqmkSikUJxqJF3+O3Ofjo287irE1rEUUR04yz31mGnoyTCY0gOtzIjumfrWvavKRQ9HSC9NgAsgQ2pxdfRQ0VnonU65EidQAtbYtYunwl+/bsor+/n5dffpljj529eDeVSuF2u/H7/Sz+xEfg4Vcmb6DISMetteomAWN/F+bBbLOF14VQWYpQWcpo/eRIj6SpKDktN9MkrtjBNKhODZKTAsvoIqMpg3DGxNn+B37zj+c55fQzefull00ipJqaQctkEAQhH+l0+QLEQmNExoYtAW3FhuIrJz3WDwgIRy3HfHZzXttQFkTE6mro7cbIChTnIQjI0RjRJS3IyQS+kjJGB/pIxGOASaC8EqfHSyqZQMvWoumaCnY7qm5OcqLwl5Ty1ne9m/Crr/Hoztc5u9zLosZm67fLqJiqhqFqaIaBqVlCzHLAgyjLCAg4aitw1FagBoOII0Gk0RBiPIntxW2oqxZjVJWhV5TCUStQXtuVr6NxywqhjFWD19/fP+s5z+GFF15geHiYlKqzet066hrm0XBwmPBX1pKJxyAZg9AAutONNIsQdq4jVtO0oh2EWjJO2fgBVCDgkGkrcSKUNnPL567mn8+9wjd33U5Ms66/lK6yKzTArtAAAgIBtwefx4sESKaAT7LhR6HS4cFWEDHIRfBW/HHC5ND5ia9Y0jdjIyxffBT+klJ+86tfsmzlas5/2zsIj48SCo5j6DrJeIy+eIzRPa9Q6RCpc4mk1p6X31fDr34KGzfQ1juIGAyTaG0gU1WOqcjY3n0BOw52s7hRxWm3MaoUX2AuXb6Cz3/pJn70/W+TGe/jvEuvoKyyinBonHg0wvhAL2UlJdgdMxONqYRvzdp1iJLE1s2vc/SmydIxl1xyCVdddRWmaXLvvfdy0UUXvaFau4MHDxKNRhkNxzhmaSuVCgxqJgYCfYaDxVKSKjHDmCkzaigkTYs8iaaJ3+vl6NUrOauuhPuefZEb7nqIy44/io3LFpORbMimjkvP8Oj2vWy45MpJ19FUUleIdHZMDi09jcC+J4tvFIqgZcV0Jbvdmjuy144ZT4DbyabPzZz6lUUBbYFj/4m19fx7aJDdskSDpmGKAulMhqe2b+Wl/ftY7XDx6fVHU+vxYGZ0jMFh6B+a1GladvYGwpqJYVoLMlEQuPSsE7npN/dQUVHBtm3bOP/882c5isOHoNgR5ir1+X97Kvbpp58mkW1bPv3004kJ02/MF557hhNPOX1BaQ3TMBjJpWAlicqGZjRN47e//DmdHYe48eavUVU93UfWo0jEVN1SLg+NERrohqwatt3tw1fdQPuHrmHpn+7ANE08H7qMVDKBw+lEy6SJjQyQCI9hZCZuKL9kUCFplEg6ogAtQ0+w8ZPXcN8DDzE0Mkp7Vw/O6Cgpnxd9z/PI0vTvaZomHeEITw0N8/rgEGkE1OwNo0iW8TNuBcERwEyrkEwh6iaLfaWsKqnk+h99dNLvJwgCZwfi7FbjdOoe0sPdSA1LJ20z1NfDX277MR/5wldxzdJ9aho6qaFunLKAKCnUtyxCttmOGJnL6b8V4py3XMSOnTtxAQ899NCcxC4ajRIMWnZUS5Ysmb6BTcGMJRBKvJBMI1SXI1SVWbIyWc2hMruJBhCNIA0NUm3oyFPa1qNvuYLzxp8h0teJvbWFuA7DGYGwavLitt088sgjXPuOc6i66BLGkhPv9dpllKy2nmmapOJRNMWFUlKNGY+jZ1TC4SCGpqHqJgICSDLus87FfukH86F9eWwE831vw/R6kUpLpxE7460X4DINRAzGBvutCKGh4/WXUFlv1UPGI9liaFHANove36s//glr167F4/Xwz8ce5ajSOhbZA5izrEYljxN7TTmu1lpEuw291I9RUWr9rqqGGY6yrbeLlbUVyLoJ6QymKOSjdoXR1pyI+Vx46KGH8s/Pe8vslkIV7on9T623m0/UThDEfL2dYegIYz2YVW1Wer4AhZ6xkUiYb910I5/+wpeorqnN/900TYZfe56UYeK2SSwpc+XvT0mSeMspx7G76SUGkhEORkbojgcxJRHJ5UC020hIIgnSSKJk1UmZKUxdRwwO0uwupVXyUG4rvpCM/eKbJGuacbWtoKfzEJqmYZomH7vmE3h9fhp7X0S3mYynTYaTBmHVxAAGkwZ9Sjklne1U1dRhs9uJx+MEjtnIyt//DoD9776ctZ/6IO19Q4RjCSLxBFv2trO4oYbyEnPG6F3bokXcePPX+cm3b2Z8PMg1H/0wDc1t7N+9HUPX6elsp23pimnzhFMWSWpGPiWbI3iiKHL66Wfw7DNPTSN2NTU1nHzyyTz99NNEo1Gee+45zjxzskrDQrB582aSySSxZIoLNq5GEUxqxAx9hp2wKdNj2GkQ01SLKlWCShKRaDJl1Spj4khEEW0CHz/jeJ7rHua3L27lod4QZ55wHC2lPiKpDC8f6OSLN85NVsaTej5F65JFFGGWQn7dyMsDiYJAnVPJW4obRdwTtMFu5OpGpEOvoLdtwpH9rWOZuZsFculYl6Jw1KpVPL19G+8+6WT2vPAim4cGEAIBLj/vAup9fsr2HQBNs6L9mYJa0iutcxRSTYZ1G2kgbZNxAm89eROf/fkf2blzJ36//82rs5Nk6zHXNv/heENH+K9//Sv//MILpzP/eCzG3l07eO/lH5722myIRcOksoSxoq4JVdW47b9/QCqZ5As3fwNXkVq9UNq6+EzTJDzQTTw4gqzYMHQdf3UDzkAZgiCw9E9WXYggCHjcLsxUnMhwmtjoYJ4EIgiI3lIkXznd8mqWFTRSAFRVVnJSmYO9LzwDgGSa1Hdsxr5iEQCt52+g/WHLK7cvkeL3+w9wMBKx6g1yk0SeOFkXpyhKVJRVUFNeTlWgjObRBM5wnPWrK4pewDZJpN5np2vczEtpyFkR4dGhAf546y2sP+7kWUkdQHq0D7tp3VwV9c3ZNN6RQTRdnCTULF5FWUUlYyPDbN26laGhIaqqZpaZiEYnIpneYt2QgmCRulTGeu5zYyZTeVLn9ygo0QhjW7bwx5de5tj6Oi5ePl3o8sSX7ySKdUYy7R0owLIVy/j3nl7ueeifXHHJxZx17DK2F7wnMtSL7rQTC40jyTK6ptHXeYiSuhZsLg+B6kZiY4OYhkEqGgJMBFlG9gQQFdukeg3FZsfMXoOabtD061vx+fxEs9e2J5UgFY+RCg6j6zp2hxO7s5TSqhpEUSQ8PsrYYB8ADqeL7oN78fgD2OyOSW4UuqZhq7Bqs6pSIqe663i8Yx+Oqjbq3IEZz4MeS5I40EPiYC+2qlLUxfXYygJ4ZQEUGdMm869tr9O2ZAkelwvT77VIbDbBLIsiNlEiY+hEIpEZPyeHvr6+vD9wbV0dy98E0dmpkG12SmqbGOttR00n8USHUP3TF5E5+Hx+Nh57HP/9vW/zmS/cmLfFikfDJFXrXDb6HXnx10Ks9tsRBD+1Lj96mZdglYvh0DhDo6OMBscxTIPCHnpBkjAliQ49SocaoVJ1sMFVhU+YXJ5g01RqRvoZMEETRfp0nXPPO4/SsnJKdj8CWNHgCodAhUMkpZsMJAyGUgaaaTI+MkxwbJSqmjpisdgki64lf7kTtzrCqrZGhsZCdPQPo8gS+7r7iSaStNYLM0buampr+c7XbuYb3/0B3/z+LXz+05+kpr6Jvq52ErEosUgYrz8w6/kpJHibjj2eB++/l1QqNSkiNxhKcOGFF/L005bUzKOPPvqGiN2WLVvYvXs3NkXm+OwYXyNmSCISN0WGdBsiJvVSxnKYxEAyJmrpcqPgqOLGv3I9H21bwdOvvMqv/vp3zj/lBEZCYVqbGqmumVsvtMo9ecpO6iIz5olkyaqxA2QElNzqRhCYLeaktx1+Q54hCqzdcBSP/u53fOfAAVpsdi5qbqW1oYHxyko0USQd8OEanbl5yuZ0Qco6QhPYcbCTO+7/Nx6Px1IiiMVob2+nra3tsI9zJgiyMnfzhHzkrAffLBw2sTt48CDt7e0ALF68mJaWFjpGJydiuzraWbR4WV5geL7weP3UtCwhEQuTzKj84jvfpLS8gutv/EK+pimqGnizZvU5UgdghEdJBEes1YBip7ylBWnKifJk6wwcDifd+3bR2NRk6eOJEu7SCjTZP2OBpGrCznv/QkSyopMOQ6NFDWPPWlBpo1btTNo0uX9olMcOHsLQNcwsoXPKChvq63CGDUqRcSAgI2AvCyBXlSPUVWLqOkKrSEs6CMHiN4Bgd1BmmtQKUfpND6M97XQPjtK+ZwcHd+9g0ylncuoFs+ssaYkoctKKnPjKKnH7rcn+zfbjEwSBTSedyj//cRcA//73v3nve9874/aFxM4dG5xeoxhLoD+3FaGixNIiNLPRIsNkWZUNW2+Crf0D/GH7Ti5ZuZxj6uYvuJxJJPjzP+7n1BOOo6m5ZVJqwtA14uPDpAVrANKyOm6SLDLWtZ+KtpXIdgeB2mbAWnSMJ9IgiEV/Y8Vmm2S5FEmoCPaJa9vmcJEUbdi9lhxCvXciZRANjdPfcQibw0EmlSSRTesn41Gcbu8kYpdJToitpPqGqXB4WF/WwMsjXVzk9CLPVd9lmmQGx8gMjiEoMsEyP62VXkBATmUwO3qxISIOj08TLnbJCv7FDfNqnnj00Ufzz5ceU9y26c2Ay19KKhYhHholFhxBsnmRnZMXSIXixG+/9DLS6TRf+dLnWLVmLSvXrKNVioPiwCGLlDhmH2adrXV4ljdRbZosFxeR6hki0TdCYiyEKQqkBIOooDMmZGgPjaAaOogCQ1qSRxO9vOOoFWRME1vB7+NOxWkc7KK/opZM+156d+xgdDxIoLMbUddZfe1E9NMhCbR4JepcIodKaxgdHsI0DMLBcQ7sP5AnTaIIiiiAat3D1eUl+L0u9ncNkMqo9I8GcTnsVJczI7kzS+r5xk038t0f/YQbbv4aH/vsjZRXVuP1B/ISVvNFXX09La2tdHa0s2z5ikmvLVmyhKamJrq6utizZw/d3d00NjbOsKeZEY/H2bNnD5qqIphm3hlGEKBZSHHAcJIWYMCwUypquITiDQdRyc6AIwCA1ybx4Y0rOLfKzXf+/TzD4Qhf+Pp3Zz2OzvaDvPLC8wwPDlBWXkFrXRUtbW0sX74CIVuGY6amyPBIEno2MieStSzMEzvre7zy/QcmpWO1wW6Etk2kjYlryWOT5hW1s9W7+efWDh7ds5Oa8jLeUV7Feo/Pum8TSaRsichUva9cpA5AcLoxVQNFgPFQiFseepq97Z2864wTWXraW/n2129GVVW2bdv25hC7eXXFvnkCyUcKC3cPz+KJJybsSWZSyh4bHUEsslKdC7og4vYHGA/H+O5XbmTFmrVcc/0X5hRUTcYijA1YtVWK00NZ0+IZSZ2aTqFnkoSD42TSKXyBUlqWr2HNkjZObi3npKYAJzUFJsmexIbG2RGEpGhpo5XoKZao43lSB9Z982LXKN9ob+eRAwfQTQNTEKlyOLh8ySJ+uOkormioZalpp8KU8JoiTlNAHA1j7DqE/sJWS/JEkRmvqSXtnLluL55MsXXz6/z5lz/m59/5Ku17d1Db3MqHP38zZ7/jPbNOhKZhkB6xahhlm53SmgYEQThik+dM0bocNp5wSv6z/v3vf+dTBsVQGN3xul20nl9EpiORwuwawNzdjrmnA7O9D7OzH0ciTiyV4o/bd3LFujUcW18343ccfL1j+t927mVZQzWnHG+lizMFPpzpeNRKvaZTqLoOoogzUEYqaqWNDW1qOlBAEKUZP1+x2RFFydKzMwxSqcnd2eEpadLeaJreqBUZMAwDVcuQTKWwefxWfYqhY+ommWQCNTMRQdCz/r+maaLHrZq3Jb4KnLJCVC3etTcTTFUjMzjG3u2dyJ192BJpzINdSH3DCOr0a2DVWZZ3dDweR5tFwV3TtLw9YThjcNSxJ864bTEUpmVzEITpj5kQqGnA5XBgE0Wc0cF8JLUYBEHgsg9+iC/e9DUam1vZsXULX/zhbfzsV79h29YtJFLFtf3O+9HVKGV+vGvaEBUFPZFm/MnNRLcdRB8NYzcFHDoENJEGVWFdxs2FjgY2OitxmxKCKKIoAvfv2MMNz29lZ0qfNGfatAyNg13IPVaNZ8bjYWzZYisK8rP72PGz+yYdj00SqG1oYtnqtfgCJSQTCULBMdKpJFrBdRF1TizUnXY7qxc14nFZY/OhviEi8QTl6syd/y6Xi//6wmdZvnQJX/nyDcSSKbz+wGGNPQIC42Oj0/4+FE5Ompdy4tYLxfbt2wmFQsg2O8cta+WnDzyBnlvAibBITiJn27/7jImFlj0wObMQkR3YdRXF0GhLjBDQkqyqreSrl76FxrpannnycVR1eiRobGSEW3/4PX74za8iCgIrVq9BsSls3bOP//7RD/nkey/mjw8+RmffYJ7g5WBKYjbqC5JpWZLl6hFma13KkbpcCh+serti0DSNHdu28quf/4TP3f8or42NcPYJJ3LN29/BOq8/f06Tfh+mJKE5HQjZfa668sxJpC6HVDrNg48/zQ9uuwOnw8HPP/9x3nbqsbylTsTr9TI2Nsa2bdtm+QZvALlU7FyP/3Ac9hFu3mxZaEmSxMknnzwtWgcQCYfx+uav9K8VjErPPPEYf/vDb3n3Bz7ECaeePuN78ilYw2CkpwPTNLHb7AQaWvHaFWKqnidzOeiaxkDHfuw2O+l0ivK6JnylVspzNKFR9uDP8tsWroHGRScp0frJqrUYVXpiksBicniQP7y8j7889gy6biDZFJySwGmBUi5oaUKZj6FyLInxyi7K33IsBgLGKcdM22RccvP3P97N069sobyighOOPYa1K5aiLT9t7v1n4U0H0bMB+fK6JqR5mj3PhrnIXCECJaUsX7OO3du2EOoZYMuWLWzYUFxXbVIqNtugMl/ZGIBHD7WztLyU1VULixwDlHhcvH/jWjqyA1Sh1EqOICkOFw5fCcnQGMnwOLJiR1RsZFIJbFMsmEqdCuPJ4sOqIAjI2YWIYRqkCkyyp5K6QvRG00RHgygON7qmkoyGrdR+TQPj2dSsmlGp8HgYiav5mrGpdZvn1a8ouv+FQBIE9FmK2fzeibReJBKhdAYx1ldffZVwOMx4IsOajcfi8fnoCFkEqcwxnbT5HBPX73hCm3QshbWKuWPL/20mLiHKeKsaGOk6iJZIEkiHqK+vz4sTb6j1TotiNDa30NhsSRuddMJx7N6xg9e2vMijTzzNaZvW8Y6zTqG8ZHJUqnnjUiII6MkUwRd2YGZm7xZWRIlWvDS6XYxo42w2ImiixOB4kO89/hzvPPZoLij3ImUndNE0aSFIb3+SaF0thk0hWV6Ga9TShcyRu8IIns1mp3nREkaHB3n11Vew22x0HNjHomUrULJG8lFnJWnNpFwdQRRFljfXs3V/B6qmc6B7gPVLWylXR2aM3MmyzFVXXkFJwyK+962v88EPfZiTTik+fuXq7IrB6/PNGP1dvm4TgvA/mKbJli1bZv1dZ8LmzZsZGR2jRDH56HmncNezr/KPFzbzrpMsFxdZAL+gEjIVUmbxIIbstJNBJi0peLUkSsEiod4hc/U738qtjzzNrbd8l/d+6CrKKyuJRSM899QTPHzv3Rx97PF880c/wzsloqnrOrHn/saLW3by+R/8gqbaKo5bt4pgJkWJzWGJE2chISAJIoJpYpgmmmmiGQZhNcOujl76R8fpHByla3CE4d8/QTQaIZVM4XK7WLR4CW6Pl7LyclLpDOlUilQqRSQS5sD+fbS0tFJ3cDs3nHUSicrFaB43tmh0UtTIkGUMUUBzOAg11uM4cyN74yalCpQpJpJgLTQfe2kLf/7X0zjLa/nkh95LQ3UVSjbiXVdRSnVtPQN9PezevftNqbMzRQVTnN1SbK7X/xNwWMRudHSUvj5rwliyZImlE5SYTux6ujtpyHbbzRemaXLXH+7kleef4xOf+xJLls9vsgmPDeWjEhUNLbhcVqp0KqkzDYOhrgOoaasuw+7x4y+zJvxCQjftuIAh2ZqUvEaGan1y2HsgqXLrXx9n296DAMiCycq6cj5x4WkYm7um7S9HTHKyKIXPAaJDA4jHrkczIa2b2CUBXTd48PnX+Ntzmzlm3Sq+/dmPI7kD9ATjpFxlNPknIprd4RSN/uIRzkw6RV/3AABufynurO7a/zaOPfl0dm+zBtwnn3xyXsTOlYkj+aqzUbvXi24/9bfcNjjM+9asmvVYqje0zPiaAUiREABCQUrTyMrniJKC01dKIjiKmkogKXYMTcXlL05aSp3WwDCeVClz2yZdo163k9CoZVmWzkbsZiN1OTj8pcQj4+hqGhNQ7A7s/jK0fisqG46n0GQndklElWWaAhIHu8NW2GEOK7DZMFW4WDUMlCLipOf96GoAOv5yb/5voVBoRmL31FNPMZ6wiPPGk06d9NpYSi1K7mCC1OUw1b1j6r9ng8sXwOkLkIyECA/34/KXsqF2IhLjsRVfDMkCOJ1O1h+1gUuPW0EqNMr9Tz7Ptd/8by674AzecspxiKJIIqNhSiJaJE5sX9eMpO6Sc1u565H2yZ8hSpxVXsfbli3lN5t3ciiWRAf++vzL7F3UwhXLWqjInoZwewgPkPb7yHg8RGurcY6OTeK0E9G7+2i87ReWR3dVDR6fD4fDQSqZoPPQAZYsXZa30rPLAqNUUK6OYLcpLG6oYXdHL8l0hsGxILUVpdPIXVnWc6VTtcbnS84+ieqaWn7241vo7+vlkve8r+hkPZMMSm1dPb09xYV2vT4fra2tHDp0iM7OTsLhMH7//NO9pmmyefNmotEorSUe1rU2UF3i46t/fABRFHj78UehIRIxZXQESmeIg2nJNA67nRgO4pKV38ldOTZTx+3z8sErruS555/j5z/8LslEnFBwnMbmVj75+RtZtHRZ0f1KksTapW2sXdrG+y46mxe37uTFrbv458GtlNqc+EoCDI+PE/B6EU05m4qFgbFRhoaG2C8fRBIEWv8eorosQHN1BWdsWEXJqe/C4/XgcXsIRyIMDQ7S2dXNeHAcm81OIODHbq/C5Xbxvg9cTkNjI9Hvf4mE3Um63IPN0CmVU/haAxO/gb8U2edEQkf0O4lq1mIyqEKHIFCjaNz72JPsPNTNx95xPs1tbRyK6CR02BbUCJSX4XPa2bCsib/u30ssFmN4eHjW2uzDgSlJ+c7h2bb5T8dhEbvCMOjatWtn3K794AFOOf2sBe37nr/+iW2vv8oNX/s25fOszdM1leCQJZ/g9gVweYvfvKZpMtLbSTJbf1RaWY05D70ogJigoGZ1xaq0iRqlkUiMu7bs5/E97YiSiCCAXTB5x7Gr+cCZxyNJIu1MJ3aL330Gi98NB/5ipZsu+eZkoU3VMHk9aMnVjmagQta45U/3MRDP8F/XfIiVi1utgacnSFzx4Z4SGZqJ1JmmyVhfZ77juLxu4XUnRwrLVq/DZreTSad58qXXuX6GFdikVKxr4nsVpmRzzSowWUMwnEoRSqVoLBjQZyNxxWAIAulspLaQGORSraIsozhciJKEoalIig13ScWcAs85ghfLau15FClfz2QYBqlUal6kDqA8EEAb8xALpdDVDL6yCmRZQcjalOn6xH5EQSBjs1NbU0JQEjEPk9hd/5Mr8s//9eU/YpomqqFz9o2XsOWWBwGorfaw+tq3YsTDiG4/Ps9ExG6mzljTNNmxYwcATrebRctnJ+U5TCV1RwKlNQ30xyKYhsF4fxeystjyqvbOXmdT4vcRDgUZtJWzscnB9Zdfyvb97fziL/eyt6Ob6z5gdVZXHr0MdnQwPjS7E8cl506Wdtr9gkXYm0oDfPn047lryy4e7epHt9nZ1dnNZzu7Oa2pjota6hCxApOe/kHGlyxCt9tR3W5s8WLGdtD9sY/nnwsnn0BFldUQEouE6enqoLG5ddJ9OqpY5K7E5yHgdROKxukeHKWyxI8sS9PIXY7U5bBy9Rpu/sZ3+M43voKi2Hj7uy6d9bcoxKLFS/jT73874+tr167l0KFDgJVWPemkk+a977GxMYaHh1lV5WNFYy2yolBWWcWXLnsr3/vbQ/RFUxx/8qmY2VrvUnHy9WcPeNFMCGVMBNO0CnZMCCluylTrtxcAj5HBFJJc9NaLKalpoL+3l/rGRjze+We7PC4nZx2/kbOO38j1l1/KLR/9DmNuBTk4aDkkmYI1dpkmVaVlNLp9fNhfw+k3XDzJ8xogU9CkVFpWRktLC+s3Wpmj2RrLEw43enbM8yYmS3eVhUfxJqKkbHY0UcZX5yeuC0Q1SKYyfOvP96EJEl+56v2UB7wYCJQHXPRHUqQNk9BQEFkUcfpKaWlbhCiKdHZ2HnFihyhZj7m2+Q/HYdXY7d+/P/88R+xqp5SChYLjBMfHaGlbNOf+NNN6PP34ozz/1BN88gtfnhepy6Vhxwf7MHTdsgeqtXSuNE2bVrcVjwSJBq16DG9pOVX1jYTmaW0UkqwJVzEN3KZK33iI2x59jk/+7j4e2bE/K1SscsaqNj7/9tO54pwTkYrUF1qE7owZ/52DIgoEFGvwHEga3PKn+wjHE3z/89dSddI7GK1eT7uzmdFsT5QnUFxMdSpiobEJYltdn0/9/V9AlmVaFlnyJZFQkMHBwaLb5SR1AFzO4hpDredvKFp7F0lnqGyqYuVbj6H1/A0LJnUAZkFsI7Znb/65YWQLk0UJUZKQ7U4CdS04PH485cVtwwohTKlbial6vo5UN3TGY9Oj4DMhnNEorWvE5S+lpKoOm8OV1dSzBqFCeQNBFNGyciCnL57fdVOIs5eUTiJ1AOd8472c/pVLqVhWx6HfPEpttYfa6ukd2QHvxN9mSqF1dXXlo7Qti5dNm3jAitoVPiKpN8e/UbbZCVRZzTapaIREJDiv95Vl3TESiTj95VbWYc2SVr573VUMjQb54e/uoj9qpZaXH7OEzz5864z7KoYVx9ez4vh66xhFkcs2rObD65azqaoUXdXQNJ3HDnXzxUee4i/79jCcSGCPRBGydY3JGRwrpqL99l/R1NJCoNS6TkZHhomEQ/nX7bKALBiEbJbqQEutNW5ruk730OTat6hqTCN1naqTMuJU19Tw2S9+mcceeZhnn56sy1YodzIVbYsWMzQ4QCwaLfr6mjVr8s/37ds3r++cQ0eHVXMriiKLG2vZp7vYo7oIlzXy7vd+gD2jMb736z9w/2NP0LlzC2osjGlC2JDo023s0Nxs0bx0uCoYsfvQBQm7qaNNcRjxGWlEATBNHHY7y1auWhCpmwq3w84yfzlrWxZR6vejCBKSKCCLIoJuIIkissPOmTe+o+i9NRtmi3erWTkju5qetp2Q/bs/HqEsOk6L02SVx2Cd1+DfL76KLtm47LL30CX42RIR2R4VGUtk8DlkbAIokogkirQ11qNmMsTjcbq6pgdM3jBEZX6P/3AcVsSuUFy0sbGRdDYNW+uC/uwc3H7wAHX1jdMsa2ZDOBjkAx/52LzavnPQ1AzRcavWyldWiS1rNP6T736Dk04/i43HTRgGp2IxawJWbFTUNVNd282LzzwFzJ6G1REIiRahSAz18d8vvMhrh7oxgLhoESOHInPhyhbOW9ZGidtJpHMg//7yFbW4a6yBPjMyURdmqyhef5JDrROCKjz76la2h0x+8N93kMzKlyQTCQZ7e0AQUGz2GaOUhTB0nfGs6LPd5cZXtvCasyON1qXL2bfLis7s3LmTmprp0hKFxM49RwPNVHLnGAuS/uX+Gba20iSFkIsQR6FgnVpoy56LyOVSsqWNixBFad61H6ZhTiN3jqxIq2FMrrGbD2wOFzVtywHTUpk3zXxXnFQQPZy04DFNzl5SyqP7Z1/gnL1kdmNygHQ2umibIVVhxMOU+LzUV5UjVzROOq+F2LlzZ/55y9Llc34uWEQvB7/tyBY3e8sqiQXHUFNJggM9OD1+BqKZWaN2gZJSbDY7aiZDT1cntsXrKe/fgs/j5uarP8hV3/gJ9rJtHL1+LXVeO/TsKbqfqZG62XBiayMrqisosyk82juEqhvEUHh5aJBXhgZYU17B8QEfnkVtJMtK8fb2Ic6hVzmcSHBabR0NLW2kElbDSzQSwR+YIIbPPvM0L734Al/80pfxMkx1WYDBsRADo0EaqspQZJmoOnNUuFN10qzEoaGBKz7yMQb6+6ZtM1Mq1uvzUVFVxaFDB1m7bv2015uamvLPBwYGpr0+G3LEDqC0opKkIFuhEEEgMZrivI2nkDBDRAZ72LlnD/c8+gRLWptZvGYDa9oaiKcmR/DceoZyNUapOvm6r1vazMCISiadIhYOUjqLUDNARRGrsam45KfX8PKhfhwHXkcSBdasaUPu0iF777+R2PZMI5ueve+lIhp5U6EstfyMd+3aS2fHIT571YcoCXgYjKbyDRsATkXG77DhskkIDjc1bpF4PI4iSxP+4UcSwjwidsL/SyN2uRvE5XIV1xUD9u/dTeviImKyU1DYMHHROy9l7YaN8z4OSRSIBcfyE2mgcoIQbjjmOP71wD35i8Q0DCJjQ+ialm+Jq6quZWhgbgX8YcnFSDjK3x/+Fz/6w128dsiq6VAFEbfDzunHbeLnH3wbl21YVdQuZiYUkrxi8CkC8eAojzz5NBe99a15e6hoOETHgT3EEglsDieVjW2IkjRrV6sgCIwP9lpuBIJARV3z/5p8xGxYtHSihjKXfpuKeDZllFZ1XHZrMpXmWRfosNlQNS3fyTYXtGR60gOYVOycKbipJclaueVr7bIDwhv5XSW7w6KRpklyhlTZTAhntOw1ICKIonVcuWaBAkX7XNMHpoGYjeCcvaR0RvI2H1K342f3seUX9xPpGJpUY1dYlC+6/XjdLnqHRuk8tJ+RGa7/QmLXNk9i92ZCEETK6ppAAF1VCQ3PPWaIokhr22IcDiepVJIDe3cTyk70DqeTt1xwHg/+6zHSsTBeu3VuPvfoL6ftZ2pt3VwodTm5bO1yvnfeaZx89FE4FBndpmCasG1khFsfvJ/7n36K8WSS+BzNRKZpMpJMYNz6C3quuRZBENA0lZGhwfy4ahgG9997D8cedzxgNVU0VJVPvD9YXK+wWUnSrExfuGw69jje+vZ35v8dVY05bcYWLV7Cvj27ir5WVlaGkvUoXiixGx8fp7y8nMqAj9ryEhTBJDESRtm5D/3lHRhPvIrjkV18/Jzj+cYVb+cX176fisZW/nzfgxzsHaQ0E6MhOc6S+BAro30siw9OI3VgRVydsjVm6PO02psPUtkSD1EQELNzQy7WpAnw8g8eLPo++/ZHDuvzbJk0tkwaYwbP46kwTZPb//BX3n/B6Ry9qI7GEhdravysqQ2wtjbAcc3lrKrxs6TSS33ARZ3D5FBHB+FwmEAgkK/zP5IwJXlej8PBz3/+c5qbm3E4HBxzzDG88sorc7/pMLFgYqdpGsPDwwBUV1cXncQ0TePlF55n47HHv/EjnAVeRcQwDEzDRLE5kAtMxo87+TQikTA7t1rdu4Io4q+oQRAEMskEfQd24ff7iIRDJGeIHAAMJtLc+dTL/Pdvfs/u3XsQswOa3+3kzFNP4TMf+RBvW7+SUvPwUkGzkbuMqvH3ex/gmJNOp76hnr07trB/93Y6Duwlmbbsq8qq63G43JPeN/Wc5OqsDF0nnUzgcLqxT3nP/xUaWtryxzuTzVQyG7kSBAG7beIcz4fcObLXROoNDJi27LlNI7K1dj3B3nYyiRiSzY6k2NALZAHeKBwOZ56MJeLzT8UWg5rJIEgiss2OJNuIBccY7NjPUNdBdElCyqjTVt+zEbxCFJPLyBg6Nqm4Rl8OgYKu2JlSsbkBW5Jlahqaim4zG+Zbl7gQ2F0eFIeTTDph6VLOcr5zi1WP10ttQwMCAhk1w+tRha2DUV7rj9Da3MzGo9Zz9733o2ZlYfrx8d5H/8znH7hl3sdVf9rR+UchKkWTi1Yv4xOXvY/TTjgBb1Z4XNB0du7eza1/u4t/dBwiNMu+Y6pKUtPwl5czsnIZ4y+/YunX1U5IBr3y8suk02lOPOnk/Psy/jocNgXTMKeVw0wldMXIXQ6zRfkKcexxJ/D8s88UlUwSBIHqrGj04ODggu7Trq4uevoH6R8L0VzmIzwUQdY0up2lSOuXIa5firCilWFNImaI+Ep8nHLUGk7ftJ6Xn3+WunSYgJbEbmhzTrT2rFPMVJeTQlQ4pUnROnfHS7PuM0fsJAEkUWTT5y6krLkC2WVHdNtYd91b5v1b2Gcg136S+EnS+PmbkEyDjM1OehbHm7seaeeuR9r57tu+yO79h4hE45x9glW/p0giXoeCz6Hw7PU/41+f+PGk9w6PBfnL3fezvKUeSZIYHZ0uc/NGYYpyvjN25sfCid1f//pXrrvuOm6++WY2b97M2rVrOeecc/Jc6khjwcQuFArlb47Kysp8GrYQ2za/ht1un9MfVnsDc6FumNkaOxNBAE1TJ920NpuNM865gEceuDf/t5Kq2nzKMp1MEBrsQRYFutv3M3rBNZP2n8io/Pm13Vz7+wd4YdtOBEPHYWq4FJl3H7OWz77v3Wxavx5FkoquwqYiPrCwi9A0TW6/71FczSt5z/s/iNPhsrTNsiRUsTuoaV2KawZyk4ve5QZgQRBQ7HYUm51kPEo4K6T8fw1ZlnG6cvZMxVf3uZSd0+maRBp0w2BElehVZfpUmXFNJGkIk6yjHNm0XDJ9+MROwip+dnqsaGwiPE5sbAhME13NYBr6RBTsDcJeULoQX0CNXTFomTSmbqBl0qiZFKHRQRLRMLJiQzD0CcHQIsgRvLlIXiG5y+g6NlFCdTlJlgSI1NXQE9cJpvX8vemfR/NE7jpwe7wLrgECcMhS3kvzSCEyOkgmEUdW7Cg2x7yjsiUlpSxaugx71lh8TPJhmuC2SXz07efiUCR+/Y+HJo1dffbaPMGbjeRNJXNT/+2PRbDbbBxz1AY+/daLubC1DZcsIyeTmKrKy/v28ZWdW/jXyBCpKekzE+gVwVlRTnT1SrTsdRkIlFKVLZUxTZP777uHt1x40SSPU0tTUYesbFoHc9dxTq29WwhWr12HaZps37a16OuV2XptVVUnddjPeUy9/YS7D3CwvY/g41spGexnvCs7jtsUhFI/YnMtL+wJsytl57WkkxgSG446iva+QXrHi1/fxaAaYKqpfN3ubDAp3sQwVaA4nfWgFgQBMVvyYc+eJ03TSM/Cm4tF7XLkzi6L2GURP5NJea7GTtGKj7VTo8//fvZFTjluI4oyM1F6+JofAda19os//YPjj1pNW53VMDE6OnrEFtR55Jon5nosED/84Q/5yEc+whVXXMGKFSu47bbbcLlc3HHHHUf2+LNYMPWMF6SHPEXsqkocEq8//xQnnHLarIPfGyV1OdidbstHU9fQNW1S1O6k08/ikQfu5dD+fbQtWYooilS3LCEeHme0vxtdVfH5vOx6/WXcNhn1+Ldjs9l57hff464XN+N0OrN1QyYeCS5as5xz1y5Hd3rodFk1Jl4tiduY36SeI3e5erscMiMjk+rtDMPgx68MsDMIN37lM5SVlVst8ONjlq9iQkf2l9OvihCcOB9tJbNH4TwlZUSDY2iZNKN9XeiqSkl1ccFeNZu6LGaFVAy5zs7DgdvjJRGPz0nsSvwT15tmmGwPg5kRSZkSgiggYaIZ4BZ0qsQM5Q4BURRRJIlEPIHusGMPeEmH5j+4a8k0stNOgxZlsO1U5JFBDF0jFQ1N+t20dBLZNrt59FRMra8DcBZEUpOHEbELZ7S8FEgmaf1ukqIQGu4nk0oiSrIV6d17EHEW0d2FYMfP7sOQJEIlfvSKckZWLkdKJtGdTnriBi4JhsoqWIGOz+O2IsgUJ3amaRKNRhlPZKgunbsBpRhSmo5DPjJ1MKZpEhrsJTI6hCCIKA477kAp1Z75F1D7/QEqF68iNDyIpqmIYg32kjJsHhef/1CGz/zPvcSe3M17PnDMpGuqz15LXbqf5musRae2++U5P6v+tKPpffI1AJzpBHY9QtrvI9XUwAnJJMfV1PJkTzePjwyRlCQyusELyRhPHhrjosVLWVNRgeFwkPb5ONTTRSA7Lomqir+rh9YPfyR/jDt3bGdkeJjTzpgsMquqKmlBRhYMwq4qclf0bNE5mHATmm+kLgdJkjjplNN45snHWbf+qIkXsj9loSVaPB7HNw9tVcMwCI6PU+b3Mj40xm+f2cna0mqrjKfUjxDwIHjd4HUjeJwMHBrB77VhS8QRnC42LmrglfZu6ktXz+s75NYviqkRsIuEZmBdM02bOVKX+78h26xInSAgChP6m3ZFsjTjdI0F/syAFaErVqDX9b2vEa+zGiXtmeKC3IUwTJM7f/J7/vyH78+57cPX/IjtwWGeG+jmY0vWcWDDEji4l3Q6TSqVwrmAOv65YEXs5pA7yb4+db6y2+3Y7dPngEwmw+uvv84NN9yQ/5soipx55pm8+OKLR+Cop2PBxC6TydDU1ISmaUU1geLjQ+zesY0Pf+SqI3KAUzHVnL5wMtW1zCRi53K7OeWMs/jXg/dy9XVfALIesYEynF4/4ZEhKquqrShkJsmuR+/nvseeoLu3FwORSDyBz+3ipOZqLlm3DJ/TCjEfsFvfWzE06pPz65IrRHxgdBq5y6G76WT+5/ZfMNjfz41f+Xq+u87pcuN0uXl9MIKyAP7gyNZupDQTm91J69IV9B7aTyqZIDwygK5rlNc1zUjCVd2Yk9y9EVIH4HJbhC3nRlC4+ocJYud2u3m88hQAtHiYTLyLMqMfEQPJgIxpyc3ETYl23Ul/wmCxmMDrtBOOJ6mbZyfgVGjJND7S+J7+A70XfYpgXwfJ8DiGrlmpWDVDOh7F4Q3Me5/FSB1kf4usLEGySDR8IUjGrIHH4fKQiFokqqSqFn95FfHIr9/QvguR8noILm6j99Ch/KRpKDJSJkPSU07SFCBuYGtej6zYkCqa0KKjBIPT7510Oo2aTZu7PcXrd+d1TJqe9wq2z/Bbz4Yqj8JgNMN4XxexbCe9zemisnkxdYGshdMMTTLylD+NJHVEUaK0um7S3zM62Nadyxdv3sD3v/EVguPjfODKjxYVdZ8PqZsKAQi0dzKyajmGohBpqKMiGuP8ljZOqK3n4eFBtiZjDI8HEQSBP255necbG7ngxJPwu10Ex8ep8Hjw9vXjHhxGNIxJ3/f+++7l3PPOn+TTClYJAIAm2VAWuNhZKKnL4eRTT+OLn/0M4XAI/xS/2UAgQF1dHbIsk07Pz1llfHwcXdexiSLN9hKeHe6mzVuKR7HBWAhzLDRBskQB3C6CbgfLGt3IqkZb3OSfB/dwkrOUipV1s30U469txbN0FWNMlF8E7NPH3KmkbpqFWAHSqRTxVAbNMBBNASnLHB2KjGFa9cppU5i2V8E9cc+5+i1XbKNybuuuhMOFZGgYgoA3PkF4ZqoRHUpGCCgO7vmvP7HGP/s1ElMzPNrfyYX1i3DKMu6CgFIsFjuixE7PPubaBqChoWHS32+++Wa+8pWvTNt+dHQUXdenSbNUVVWxd+/eadsfCSw4z6GqKl1dXfT19RWtafjb3+/m6A0bKCsvp8Qx86p56uA3H0wldUBersM0TTKp6SvC0845n727dtA3RcRSkmRKq+tYd+zJjIUidHR2cdsf/0JHbz8mAoqpcWxDJd8573g+fNy6PKlLigqpbNF8dTqCPKuyz/zx+2QjP3ypjxs+9xkcDgc3fe2blJWV8/pgZNJjNhwKTi62dxT8yA5ZwC5ZzgYNi5fhyja9xMZHCGZ17WZCLnqn6obVaafqkx5vFK6CGzU+pWFA07T8YOxyTWjqiHYXgs2JIIAoClRJKkulOC1iErdgHZNqChzQnbj9JbSPxxk3ZIYMhSFvOfuVElIL7G7qvehTAHmbOl3NYM8OhOn47OemEDOROiCflgZIJhbWFVsIXddIZz1h7U4PZs4M/DDlbZKlJYwsW0y4oZZ4RTnJgJ+U30e4oY5wcyOmKDIWDlFtt1Oy7wCBQ50sWteMgIAky7g8PqRsqsaXXRCGw+Fp112sIP3sdL+xOtBUNhW10LRslUfBMAzSwxOkrrw0wJrVq/KkLgezwD+0EBnDJDOPz83oUF5RwY1f/xaSJPPlz32G3//6V/R0dQJW1A5AXjHdgWYmFNbdSZqGrzfrPuJ2ozmsSdRvt/OehiY+U9/MaqcLMZ3GFAXa+/v4n3/cTce2bYzsP8CKcBRv/yDilLG+/dAh9u/bx9nnnjft85PJRP43aXNZ52CuaN0bRVV1DavXrOX+e/9hMdqCW0zXdfr6+ujq6prVxq4QhdHkereXVk8JTw12Ft/YMCEaxxwcw5FMImsqq6sqSaoaWweHGN09d7NNzvdczWTIZIqTT80wJ3lVz4aMPlHfKArkSxpkSUIULDmazJEJ2NP9va8RdfvIKHYUXcORjdjNROpM02RveJhSh3uSk89MeKS/gxaPn6VZwfdcIAAmjxdHAoY5vwdAT08P4XA4/yiMyP1fY8ERu0IyN7X+pau7m6efeYYf3XILTlEnabz5bcGSLOP2lZBOxhnqOkR4ZBDF7sTh9uD2l+APlHDMCSfz2MP3c/lV1057f9uSpdzyjf9i346t6BkVAQG/38c7Tj6eU2tL8OiTb7J0QZjWq80dcp4NqYzKC3sO8e8tu9mS/ier1h3F2e+/itrmNvYEk5hj1sQs2p3zrunJTWYADrn46ZUkmfrWpfR3HCAWCRMeH0XVdSobWmcs3p2JwBWT7FgoCifGqddUskDyYxKxkxVktw9jTMAwoVe3I2MJ8vrQ8AgaY6ZCCgnFX8b28SRNho2UKSFiYthsxB0i/lkaZ2aCka3nFCUZu9tHIjSGlk6hppMo9je2epQkidw6OhGff8o4h1waNlGgNeby+xkftDyUtRnqX+ZCorwMzekk4/UiYKXmjILouBRPEOnuprG+gXBrM7qioMUymD5LZsdfUZW/hr0+HyHFgaqqJJPJSef1/7pTO0fqug4dIBIKYpcF/CWlNLUumrPez8hex5mCuXc2cmeaJulEnJQAomTjio9+jPaD+3nq34/x9S/fQFNLC6eecTZvXd+MdOjwLLFWXXkm2+98ErLyjZrDgZyaGNOqXW6u2HgMrxk6D23bTDgWJ5VO86dnnyEYHOf9LcWjNQ/cdy+nn3EmXq+XTDpNKBQkFo2SSiaIx2M4HC5cbjeSJNEszUzq5qqtyxGe+eDS976fm274PGeefS41tRMKCYXnbTZP6kKEw2FsEasO2SEpHFtRz28PbqMjGqTFO3PkP+d6Y5Mk3rJkEfft28/qqkpGd/fTdMaEpt7UmmuPIuRDQYlYDFvpzFEsjxrGPFjcdSe/f83AMK36c1GS8gRKkSUkwUTVNeJHqMfIEARiTmuBu/vldl7ZPd1zuxD7IyOMpeIcNw9Xqj3hMbpiYa5asi7/t/Bv/0y8sQK3TV5QzeR8oBnWY65tAHw+37zS+uXl5UiSxNDQ5Lr2oaGhfGPPkcaCI3aFabJkMom9wPHgt7/7PWeffRY1NdV5UieL0x9HGnaXG021ukTTyQSx0Bij/d307NtB/6G9bDx6Iy8/9zSD/b2TSERX+0F+8p2vEhofIzw0gInA2uVLueZ976Fp0WI6XGWMKZOjBiYgGxqKoSMdZrSudzzMbX97hI/97Pc8/OoOlq1azcevuoozTjmJElEl1b2XVM9+0n0HSfcdJDPahz7PtFxKM0hlr7xQSsM0yT8KIYoidS2L8Wb1qBLhIKM9h1CyhtaF6de5Ih6mYWK+gWL1QvHcqWnYQmI3NeSulFaxXI4TEDVETBTBRDUFxkyFIdOOCNjRKQv4GQ+FAQERkxQipgmpw1P7QUunrNo9pxu7158nw8nQG9dVMk0TJdvBGAkGD7s4OCfE7XB5sGUXOrljPxxodhuGolh2OqaJmWvK0TSkVArTptCv6/jrajEUBSmTQRbAV1pB0/I1ePwTk6HNZiee7VxVp3Qr586/TRItaaI3iJSmT1rszIYqj4Kh63Qe3E8kZKWJA6VlNLYuQhDFfNF60ccCz1M8EmK4p4OeA7vp2b+brr07OLhrO2YmxcknncRVV32MJUuW8s8H7+Pd132FH20P0jsyPzH1qVj1gdMoaypHzGQwCoizCcSqKgguXUzb8mV89OJ3sKKlBUSRmGEQNk1+2dNFf0HNlGmadHZ28MILz3HUUUexf89udu/cTk9nB8HxUZLJBKIoksmkcXs8dKrOw26MKHFIyJLAnGW+2QhdXX09J596Gn/54+8nvZxKTRz/1PFlJuTqp0bsZTglGbds48SqRp4Y7ECdR4MDwDH1ddgliTu3bicxR1e+TRLwJq17Njj+xseRWMbANAzLbcLQ82L5NllGwpoPwqoxbV5YKCKCi4TDjZEdA1N9s3d5dkTHeH20mxOrW3FIs9epJjSVR/raOau2xUqBZ+EokBs50hE7PeejO8tjNi/sYrDZbGzYsIHHH388/zfDMHj88cc57rjjjujx57DgiF1d3US9QG9vb/755i1bOHDgIJ/51Cfn/lBxbla8EJRU1eIpKSMRCZFJJcmkEuiaippOk4xFkIDmhgbu/u3tnH/h21Bsdl5+8Xkeuv9eNE2joaERp6nxvlOP47TFjahGgmFDQhMl+h0BdEGgMmNdQIYgoIkywgJPrqYbbO7q5fGdBzg0PMam1gY+efoJlK9axW53VlNOlGDKoGGaJno0jB4NYiuvRfbN3GFW5rRNet9rLzzHktbmvDH5VAiiSG3zIga72wmPjxELh+hr309dy2JURBRJRNUN7KJwxLsMC2EYBm6Pl/IST15zKofCmpiphakn7fo7CLBYSmKIEDNFwqbCmKmgmgKZLHGrK/EycGgvy8U4kgCHdAdh5AUNark0rGkaqOkkpmki2+yIooQrUEY6FiUZDeGtLN6MMt+opq7rKIqNTDpNJp0mGY/hWmCtmZpJk04lUOwOPCVWjWYuBZtOWFFg9w9/Svy6T8x/p4KAqKl4+gfxDA5jSBJpv49oXQ26w4Gm6wSjUZavaWNRuZeAbOKWDITQVnoaJ19/UkFjgz6lG1NRFMrLyzHD8Xl1CB5J6LpOx4F9xKPWpF5aXkH9FPusqTh08AAjw8Mcc9zxM27nt4uEs8XwpmkSHh1ipK8bURIxTQNBKIwomUiShMPpZPmyZZxy2umMh8I8+9QTXP/zf7C8sY5zj13LxqVtRZ1tikEQrCiiYbNRyJJitdVE66zIlpjJUDU4xIcbmnnB4+WenduxSRL9qSTf2b+XCzZsYH1rG9HNr3H33X+nrbWVTDpJJm0tvGwOOzbFjtPlwul04g+UYLPbGU1a5zAme/BoC5+Ec4S58Kvqs9y3F7/zEj736U+we+cOVqxazWA4QU9PT/712tr5id/niJ26bTvObFPA6kAlu0IjvDzSx4lVxa0YC+0MRUHg2k0b+duuPXzrmec5XUqxqKYSj9OOx2FHHY9YnFQQiA2OYKZBlf1EQkHUdBqlSCH+fGCaJlHVwDAM5Oy4I2ejjIos5cug0qpGylCYS+9YHD5UtM4uIliR9oTDxcBwAj2RRAsX197UDJ1XRrvpiQU5uXoR1c65I12PDXRS4/SwOjC5Ht0ly1RU1VDmccy7ZnK+MIy8hvOs2ywU1113HR/84Ac5+uij2bRpEz/+8Y+Jx+NcccUVc7/5MLBgYuf1evH7/YTD4fwNE4/H+eXtv+I9774kL1jsFK0beqZAqSzCXAvplKrjUKS8Hk9hFGlqUb9is+MqqcCf/ZumZoiHgySiYTLJBCecdDK/+fWvOP7Ek3jsX4+we9cuDMNAEGCJ38l1p22kPuCFbHrVpyXpdJaTkhSGbV7shoZfS5GQrJvNZs4vmhBKJHlqzyGe3H0QSRQ4Y+Virj7rRAxvgIFANbuUgBUutzuxVTWCYWAaOuREZlMJ1OAQpqaTGenDUDMopcX1A3MIB8e59w930NNxiI9f+6lZj08QBKobrRRsaHSEeDRCT/s+6luXIEkydkkilnlzJ9hkIk48HiUkTG+ckApcDGZLo4gC+AQDH2nqzDSjpsKAYbMaKhxuRlSBQdNONZZ9j2EKhxWxyyTi+Xo1xWENbA5vCfGs+0kmGcPumkzEFpKqNgzDGtBjUQRBYGxkeMHELh4ex9R1NMPAnY2U2ZxuCI2TTiXQdW2SE8WcxySK6DYbCAKCYaLbFCIN9aRKJ6Jw0cEhygNOTq51I4qzM2axgMhMJXZOp5PR0VHiaW3BAs2zIZzRZnWkEAyd9n378sXr5VXV1DbM3FSUQywa4/bbf8UTTz/L1R+7ikDJzGk60zQZ7esmlJUaEgSJ6qZmHC43hqFjGgaCKCFJMgOdB0jFY/R2HMTudHPJey7jmjVlPPH6Tu546CnueOgpzt64hrOOXo3f45rxM63PAbtojcUZjwfX6DiJkhKiNVYaSInHKT1wCCmrp3eGqLBs6Uru6DzEQCqJpuvc99KLdASDnGyabH7qaa5828Uoig2X243PH6CktBRlSv1mjtTlf6si5K6w9q4wslfikA4rWu3z+3nr29/Jb/7ndr7+ne9jt9vz81RFRcW0Ro+ZEIlE6N9r1Sa6srWhgiBwZk0Lf+7YydrSKrxTutgKSV0OXruNK9avYffIKDt299A+OEI8lSaRyqDpBiYmgsOJ+exrpDIqwZSGu7SC+sYmWlrbqKysoqKykmUrVlBePrtTUQ5R1SClmRimmSdxgigiNy3FpshIIgg6aJrOcMZGk3PidxaKRdEEEXHESq8aFS2YpkkymWQkEUPXNJ47MI6txIc6OEZa1xCAlKGR1jVSuko4k+JAZBinZOMtjatwyxPXySpf8Zrfg9Eg+yLjfGzxumn34OKv/xdP/+zHJILyjJJJhwvdMIvW8k/dZqG49NJLGRkZ4aabbmJwcJB169bxyCOPHHmv2ywOS0K5oaGBcDhMMBgkHo/zuz/+mZqaGs4799wF7cchwVwWj6mC2q4cmUskU6RSSQzdQNM1BEMnlcmgazqCKOBwOPG4XTi9AXxllQiCQN3ilTz3wovc+vOfY+havpv2jPPewpWOIMoUGyTFNGhJjtLhKEMVJXocpWTSYUKyNfjMVl9nmiYHBkf59679vNbRy7K6ai459QSWNdWjyTYGFRe608W4rxbRNJH9FSglFQhFJlvR5kB0ecgMdmGkk2ihEQTZhuKfHLkrc9rQNI1Xn32Kh+/+C2s3HM23b/kxnnmQAkEQCNQ0oSMSHhkkHo3SeWAvNS1LJzkWFH2vKBx2GjZHeHLWWcW6mwqJ3o7+IEsLXnt25TutqN0UiAJUCirlgsqIqdAtiaTSGQZ0G0FRxomOaUICiXTWv3G+iAetVIOkKChOa0K1uTxIsoKuqaQiwWnEbiEwdD2fikWA4OgIDTPUORXDWEollU0jOr3+/Plz+wKMD/RgGgbR8VECFdXzjtqlSvwgCJiCgOp2kqiqQMtOkFI6jb+7F0ebl7bq0rxe1mwoJOtTiZ0gCNnJN0UyufD6x9lQKFxcSPIEQ2OgY39eHiZQUYO9rI7xLDEpc8mMJYov5OqXruam79zCXX+4ky9c/2kue98HOOHkU6YtUPx2kc6e/jypc7jc1LQsnrGZpa5tGWODvYRGhhBEgd6OdoZL17DpGDfHbzyaPQfbeeq1rfztqZc4buUSzjtmLUsaamYkogHZZBRIlJUiJ5NEGuoRNRUxoVK2/yDilPNQZ3fwxUXL+EdXO88PW8e8a9cu9uzYwdJACas6e5B+8Staf/kL0uk0iXiCZGqMeCKFiIksy0iyhKIoyJJMRJWt81qwltqbsLHMNSEVlSN5IdH9hvTJzr3gLWzZ/Bp//v1v+diVl+cbsqZ2Mc6GQsJQmDKscLhp9ZTw+tgAp1Y3z2tfgiCwsrKClZUVeV/wQmF6e53l+WuaJq/0hjgQhWg8htPtZXh4iK1bNnP7bbdSW1vH8WuXc3SFjWXNDTOe64Fs8ZwsmNgka5t8KtbtRQRsomU3OJwRqHeYSAKIvimalQULsGA4wrbd+9my+49s33uAYCiMIAi4XU727O7EFEBPpNAT1rwoIuCQFByyTLnDw7rSepo8pdOaJXZGMtPIXVrXeKj3EGdWN+Er0lXtdE4sZKY2271R6Jjoc5RYzfX6TLj22mu59trpdf5vBg6L2NXX1+dtf3p7eznvvPPwuedf4F+IQnKXmkeH5dj4OF/65ISUiiAIyNnBQ5QkTMMgnU7lJwxBELDbHdjtDnZt38LwYD/rNmzC5/Nw1TWfZOP+Z4DisWjZNGhMBznoqsAUBAYdAWy6iipKBIqIEqdUjZcOdvLYzv2MxRIcvXwpH//Ae3GUVwICQ6aBnr1Zwt4aJJcXyVuGqNiKkrocRNmGvbaVdH87hqaihoYpC/jzEaNUKsnT/3qIZx59GJvdwXs+cjUr1h6Fxz3/DkhBECiraUAURILD/aQTcQY7D1DdvAhFVlCkmRsoFkruCiNYiXiM8VFrkCu2eplc+LywyKEoQJWgslRKYjN1XKJOwpRIIhLWBWyGRq+jhKbk2Ly6m7VMmlQkBIC7pDKfQhMEAbvHaqLIJN7YQKOqGWzZwUwQRMZGFqZMbhoG6awMgqtAfkWxO3D5AiQiISKjQ/jLKhFEcU5ypzodRGpryTidmLKEYJqYgJJM4BwP4RkYYvWHzuC2+/7Niub6ae/vWXPxtL+JsxA7sARlu7u7iYwOk06nsM+iZH+4yOn9aWqGwa6DeVJXUl1HSeXkdN1MpC4Hr8/PlVd/io5dm/nz73/HP+7+G+e/5SJOOe30fIQoHosSHxvEaVdAtlPbtmzWZgxJlgmUV+H2BQiPDhPPlpkcsNXiiQ7gbFzC+Y1LOCM8xratW/n6b/9BdVmA845Zx0lrlmGbIvpaaTMZbiwnvr+XSGOW4Agipe0d00hdDookcWnrYpZ4fPxp3x6SiSRbx0YZHB1lZHyclK4jX/quPAkTJQmH3YEoCui6ga5raOpk4fi//voX+WaZZa4MIXH+nc+zpWALIYoiV13zCaKRyKQ0bH399OtzJrzWPmE/5piy6N9YXstdnbs5prwOp3x4hvC2igqEKaRFEATaKnyks5HwVes25OW74vE4O7ZvY9uWzdz54lNEYgkuOfsUTtu4dtI+0rrBWHZCLbFNXF8TzRPWdWEXQdU0NBNGMwI1FZMjzaZpsuv113ilvZ+tu/fR3TdAW1MDa1cs4boPv4+W+lrcLmshfucfHkeQJCK7O4ju67TGB2F2B5rZ8NRQD3UuD+tLi0ezCv3nkwv0054L8+k8nm9n8v8lDpvY5XDo0CHOP//8og4U88V8Inc5eH1+vv3T23E4nEiyPOPgqGka6VSSdDrNYH8ff77jl7g8Hnz+EnxeD1/8r6/Qtmgx5qZjEGYRSbQbGk3JcbqdpeiCiCbKtCRGcRoTg30wnuSf2/fwzN52yr1uTlyzipYVq1CnRG4MBGRDJ9i0Gpu/HNk9XQdwJgiihK2qiVTvAdA1Iv1dKGU1PP/4v3jhiceoqKnlbZddzqqjjl7wDZXOjpiCIFBaU2+lZYcHyKSS9B/aS03rUlJZ8psrRJ8qADs13ViM6BVLSXYePICZNa1fvny6L+gkRfsiE9BMUbtCKCJ4RZ0mMUWfYSeYMrAJEqooM2rzIJoGTanxSYlZE4hLdkTTIHnRx3BLIsMD/ciigI6Aq2Ry3YfidENoDFNNIQsmgigelgh3MBjMa39JssT4AomdlkqQyf5OSclGYSWLv7yaRCSEpmYIjw3hL6+2/GRv/hrqd7+FkpochdZsCsHWZhKV5QiGgZxKASau0XE2nrIYh1QPrAJgZ3sPl593yqT3FyN1MHvEDmDFihV0d3fjVkR62g+xaPnsDjaHCy2TZqB9H4ahI0gipZV1+CsOv0vt6I2bOGrD0bz68ks8eP+93PP3uzjr3PM486xzGOjpQlMzyIrM4iVLSJpzlwHYHE5sDiduX4BYaJzQyBBqJk3MW4MzMoAJ2PxlbDzlDE456UQO7t3NAy9s5rePPMOZG1Zx4QkbKMlauHlkWO42eCUbDRY1lZID7cjpucXV11dW4bfb+cXWzfjtNlyKQuDkk/jQR66iprYWh92Bw+mcFqXM1XcZhoGmaaSSSZxO63vvTdgWJPI8X1KXQ3l5BavamrjvvglnlIVE7AzTQFm7BnXb9mlRpiqnh1qXh63jgxxXObHPXEfsfGFm0tPInUcWUVLW4lAZ3IPZYHXSut1uzj12HccedzzuXct4cfse/ueef7KrvYuPvv08bDk/3LjVMCcKUGKbOG5RFDGCIxaxkxVkTcWRLScaNB1UZzUZ48kUT762jcde2sxYKMJxx27iXRecxdpli/F6ipNwdSyCvaoU76J60h39mPNsVsqhMGp3MBpk2/gwH12ydsZ5rOezX8bp14H56xLOF7oJc9mKL/Ra/L/AYRG7FSsmjNufeeYZzj///Dd8IPOJ1oFFPry+uQmRLMvIHi82u4Nbf/BtdF2npraeJctXcvX1NxCorpn3sXn0NEtjgwQVF34tmTeFH4sleHjrbp7e287qhmo+c94pOJsWE7a5wdAwAYehUqIm8KlJFFNn65kf43DjD6JiQy6tpvf1Z9m1dy979x1g0fJVXP6J62ldsuyISUWUVNUiSCJjfd1kdI3+g3vwNrRZMjKyNK8uw/nWlXUe3Jd/Xnhd5TDfGrvZIAoChmHiEQ2WiklG4mFGbF6GbR50QWTU7kMAGlLjmIJIXLITlJ1EFSeSYZDeux2bw5VfvJRVVuNzTh6QFZ+X+FDWQ0lNgd2FLCzcYSUSCmKz2axFiyAeFrEDK9on2Z2MpaxuvDKHgsPtwenxkoxFGR/oJR4JoaZSGJqGtnoFzrFx3COjKPEEuiwzvqSNZIVF6qRUiuUtAWrsJnZxchnAWDjK0HiI5U2zC7HmUCipU4zYLV++nEcesSyNOg/ue1OInZZO0j/QgZYV0y2ra8JfVvmG9jmW0ChzyRxz3PFsOvY4du/cwQP33csD997D0iVLWLpkCaeedQ42mw0b5Bsq5gNPoBRPwEqVmYaBqmZwbHuEEVUgoYEm26ldsZ5r1q4lNdTLgy+8xsdv+TXnbFrDW088mlKfB78ClTt2kSwJ4BoZm6ZNNxta/QGuP/oYfrljKylNI5VM8ec//J6vf/u7k+7RHGRxMqmw2WzYbDbChslg7MgZ3c+Fp59+Ov982bJl839jQZRRmOaoDEeX1fKv/kNsLK9DLrie5yJ3B/7yeD4dC9PJnV0CSRTQDZN4KkP9+H6MEiuQIgZ7KQV0WeKko1axvLWBW353N1/8yR18+cOX4fV6GMymYSucEuMFh50TKC6M5JZIKiqQ0Ex2943w2pbtPPzcK7TUVfPWU47jhHUrcVbXY0aDYGaA6cTOjAZ5y43X8ej//AbRbsO7uo3Ilv0zfv+ZsDOSIa1rPDt4iLNrmwnYZp4lZUHEX1NPiau408MbgVmgUzfbNv/pOCxit2jRIhoaGujp6WHXrl0MDAxQ6j/8uqI3Ey889TiD/Vb3blVNLZ/84s34AwHAGoibXvw9ZF0gZvNzlTApV62V1Fg0zgNbdvPc/g7WNdVy88VnU1tWQoernLCUNdsGmpJj+LRUfljYfObHDvt7CPEwm196nleffZKR3k5Wrd/Ap/7rm9Q0FO/Omi/SMyw/AuXVCILIaG8naibNaPs+ShpacHj8R9SuadfWzchZQlosYjcpujOHZMBMEEUhrzEGUFHlxzkwimTq9DtKyIgScdnObm8BMTFNMA1ish1R04gFR5FtdpweH4HKWtR0ilQihmkYuP2l2OzOvGOEmkrizcoAaQto/zZNk3g4hCTLOLJ1JGMjC/P0zcmZSFntQy2TRo2Fibtd2F0eKhra6Du4G0NTCY8M4nB5yKST2NJpUmWlpMqy5CH7X0OWkRNJNrT5qbIXv1Z2dvTQUluJu4DszhStA4gVWPHkmq0KUXgddO7ajvmWi4+ovl06Fiba15mX9qmob8FbWtwJZqHIkTtBEFi5eg0rV6+ho/0Qf/jNHfzxD3/ghRdf4pTTz+D4k07Ku8rkMF+iJ4giNrsDY9PbWLvtHsZU6ElZE/eoKuKtbOQL762na2CYvz31Elf/8A7OPHoVbztpI2vfb0VVd/763wv+bk2/+DWfvPaj/NbnYmRoiGg0wjNPPTnNUqwYCtNXC4nUvRF0dXVx4MABANra2mhubp73e20Oh2XvJ0qTxo4cGt1+bKLEweg4y/zzv3YKSV0OU8ld7uNy/xeDvdPeA1Ae8PP1qz/IrX97kBt+cgdXvvdSdIcPQYB6j8JIAXGXsuOJUjB2Dz3yEu6jN/Hozp28vHULJ3i9fKSpkTqnF7Z10L7NaphYcfWl1vFEi7ss1Qxu4YTjlzIUz3AI0OMp4vu7i247G14b7aba4WZtyewLLFkUGOzvI2qTaWpqWvDnzIaMbpCZI2Q31+v/CTgsYicIAmeccQZ33nknAI8//jjve9/73lA6NuCQCM03HztPpFMp/nX/P/L//uBVn8iTOsAidVnMRupyGInEeGDLbp7f38GGlnq+8vZzqC+1oof9dh/JLKkrzcSpSYfyqb3DIXRlThuaqrLllRd49bmn6Tp0gEXLVnLM0etpvOh8vGVVVM1B6obiGapmqLObidAVwl9WiSTLDHe3Y+oa410H8VU34HmDkY0c9u7YxnCfVQPT1NJGWdl0KRen04nD4SCVSs0ol/DsynfmnxdLywqCgD4lOiEAlZkY49lUbFqU85FYAIehUZGJoBg60eQY4ytPwu50IUoSvft2oKlWpMc0TYJDfYiSjJpOodjshx1ZjEUiaLq14vaXWgQrODpCMhGf5CE7G0zTANMkEwszfmgXALqaJvfLedwe/OVVZJIJvGWVYJr4yirxSUF27RrKiw4LgOpwoMTjKIkklbbpvtA5vLjzAEcvm2jwmI3UwYROlyAIlBTpIq2urqapqYmuri7G+jpp37eHtmXTo7kLhWmaJIMjxIf7ABNBkqlsbMPtC7zhfRciV5NX5rKG15bWNi686EKOO3YT/QND7Nq5g7/f9ReWLlvOyaeexrHHn4Asy5NkUeaL3rUX07D9HkoVg/akwEhGIKpBT0qgpbaSz192EZ0DI/ztqZe49ke/4fSjVnLxyRtZdeWZeXK36srJxGwq6cu/vud+Ku74DVft38fXb7oRgHvu/hsnnHQyNtvkceb/ug6p2u/ijrsndMPOOGM6oZoNmqqRTMRh9Uoo0sMjCAJrSqrYNj64IGI3E3LkLpg20Q0Dt13B75o7GiXLEp9490X85v5/87Vf3Mll73w7m5Y24ZDF/DgkuHwEfdZcYVMUKkr8xA70kKrW+NcD99Nlmlz5rnexPBrBVaTLdPetf82Tu5nQEnCQUK0uX0djNYamkWyf23Ejh9FUjK7YOF9cuWHORZxYEEEtFvF/I8hoBpk5FuNzvf6fgMOWCz7ttNPyJ+Dxxx8/7MnszcTTjz1CJGJdqOs3HktjSytgDbiFpG4upFSNu17eyg13PUxG0/j6O8/j6jNPyJO6uGRjLDvxBdQ4Hj1NQrKjIxwWqUslEzz1yAN86wuf4ql/PsCq9Udz4/d/yjvefjGLW1qwO12YppGX3ZgNQ/HpNTTzIXU5ePyl1LUtx26zAyaRwW6CfR1F690WAtM0efaxRyivqMQ0TT76wcuKbicIQn5VtrezF48w93cuJHpgpSGMKRONu6YcwTSwGRpeLUVjcpy6VJCm5BiL40MsSgwT0FK4DZXyTIzSXc+SjEcJDvXnSR1YMju6pqGmU8iKDW9pBTbH4Qmyjg4P5p9X1kzUsfZl7aXmA8Xpxu4rRZRldDWNrmasSGIWsXiM8YEeMlmdu7KaBmwOJzUOOP2oKo5fUcqGZaWsW1aGv6MLWyRG1ZJqZhprY8kUmw90ctKa+ae5xsfGcNtkSktLi6bxBEHgXe+yivKrq6t59rGH573vmWDoGtGBLuLDvYCJJNupbVt+xEldIXIET9d1BMDlctPW2sI73/lOfvSzW1l31Abu+8fdXP/Ja/jnQw+SSqXw20W8irggx4XOFRcS1azO1zLFus770wKxbBlwc00Fn3vPhXz345cRS6b4xI/v5M+Pv8Di958yjdTBZKJX7PXFS5ay7qgNgHUuH3/s0RmP7X8z7VqI3rEITz75JGCV5Zx66qkLer+tIMWXmaFpa0WgguFUnJHURMPUbGnYYtG6QqR0k0MZO4Jguel4nPNrfhMEgdNPPYVTTzyB3/zprzz37HNomo4gCNgUBVEUJ6UPR4Jh+qJRfr99B2Y8zsfOPY+KkhLCFVWHbZApiQLLy51sPGYJS09Yjm/NYryr22AOtxaw5oLNY70sC1Tlu2Bzwt/FkNQ1ysoraW5unqSreyQwlzhx7vGfjsOK2AGUlpayYcMGXnvtNUZHR3nppZfYsG7N3G+cBUcyaqdmMjz+yIOAdeFf8PZLJr0eO+MKPI//ZtZ9mKbJK+09/PnFLZR5XPzX286iqXxK9xAwYvMiGdbgjQndTiva4mxbjh6PILnnFmMEiEXCvPzEv9jx/FNU1tbxjvd/iBXrrBWMmowzloyjePyWpIQgoKtp5HlYWOXIXZXbtiBSl4Pd5aZu8QoGOw+QiMdIhsbIxGME6pqwz/O7TcX211/hwK5tACxbtXpWBe7Gxkb27bNq8Qb7emhqWwzAWHI6ac2Rutz/T9r1d4vYFbkZDdFqoABwplTcxuT9xSQbEdnJuOImU9uGmYgjKzbsTje+sgrsLg+GrhGPhDA0DdM08JSUYy9ox3fLIvF5rvD27tyWf7501Rq2v/oSAL2d7fOuM3OWVCAqNkRZQRBFq6Pa58c0TNREjOT4MIoImVSSsb4uQkN9eEoqqNbBKVlF9tYSxUQ7dSVdSYGkYf27GF7adYCWmgpqygLA3NE6VVWJRkK4bTLl5TNHOk488UQeeeQRdu7cSayrlz3bNrN87VHz+g2mIhOPEB3oxtCs86s4PfjqWiadpzcTmXQKWVHw+v1Wuj0aoa6xmfPfciHnXfAWXnv1FR687x7uvftv2WaL8/J+unMhFhpnuKeTdqkOZ2SASpuJIlhnqy8tsEQy86S8qaqc6y69gIO9g/zqwSd4esturjj/VDYtb5sWJSlG6ArxrndfxtbNlq3Vg/ffy1nnnIsgTp5OJPF/L+06Fa++/BKhUAiATZs2FU35zwZvoITyKqsO23H9hyhbtHTS62Mf+TgOSWaZv4It44OcXdtG2a9+wUwJyDOGn57hFQu6aXJAdaEZGURBYHld2bx8VMFyGxqIq5xx3NEcs6yFu+9/kF3tXRy9aikZ3UAwDMrjvYAfwzCIdA3QHY5wdmsLH9twFJnQOBG7DdXuIF5Siid4eA4niiSyqNTBzmGDtrXNsLYZ5yWnUFVRii9LUn99/a0IAgiKTEu5B1OWORgPo6W7uejid5ByOq3OD6xrWEimkPtHkA9NdDdHtQxjo8OkIuNs2rTpsI51Jqi6OWeqVf3/ge6JN2Twdc455+Sf33777Wjm/63PYyG2vvYy8Zglj3zUMcdTXTud2cfOuILYGZbys7umHHfNxEQTjCf5/kNP8ofnX+edG9fw5beeOY3UASRFhajsQBdFvGqCsGJNFnLjIivNFe1HT86eok7Eojz8599y282fJTrUzxWf/CzX3vAVVq6f6HCV7A5sbi/oGqZhUt62al6krhBD8Qyh1OGtoGXFZkU4si3ouppmrHM/4YEeq7NyARgdGuSvd/wy/+/3v/Nts4bfc7UxJU6Fof6JepMyp22S20YxPLvynYhFUrEACXFi0ikUnNYR6HGU0OGqYFxxkam10ozekjKqWxZT3bIYly+AJMsodgeBimpKa+opq218Q2Rh73aL2LkViWNOPj3/9z3bF+YTavf48VTV466oxVlSjigpSIoNh7+UQPNSymobcbgnJrrQcD8vCnX0poRJK3tHVmhYN2fuWn9m2958tG4uUgcw0Ddx/mbzSZQkibPPPhsAj13mrjtuIzg6MuP2xWDoGrHBHsI9B7OkTsBZWoW/YRHiYcpULBRjCQ2ny83yNesxDAND0/D6A9izMiiCILBx0zF85Rvf5pPXfZZDBw5y3Sev5vd33oGYnl3HLx4JMdh9CDNLulV/DSMZgVLFQDNhXBVIFJmjFtVX852r3sO7TjuWX9z7GN/6/b2EYguT6WlobGLDxmMwTQgFQ7z26mvTtjlSpUgLnUdj0Sh3/+l3+X/nrqOFQJYVRocGGB0aIFVEK63sV7+g7Fe/4LTb/4d94VGSh+nBDJbH8L6oSSxlLTzaqgJ4HPOL1hmmyYFQBgOBtG6yaVEt3//Mh1m3fDG/+ccj7OnqxzAMVE1jz6/uoe+p14mrKrIocl5bK7Io4oxGEQwDUxQI1dSiTmlImCsNWwibJLK2yk1ltgQooep0j0bY3j3CKwNJVn/2Co6++m0ENq1EW9JMqtTL050HOHb9UTjcLkxRwJRETIcdx6J6AuuXcMKV50z6jNYPTEQ+j7TXakYz5/X4T8dhR+wAjjnmGI466ig2b97M2NgYd955Jx++4oOTtqksaG4ZPjybysPCzq2brRZvw+Ck08+addscucthx7c+wy+ffIl1jbVce9aJuOwz32RidlDVsHTuPI2teH0+6mpr2b9/P2nNoNFuUFldfMX46ssv8Zdf/4qyhlY+eePXZ2yGEEUJV0kFmXgU0zQw1DTiGzScXyhEUaSusZlkaSn9XYfQ1Qzx8SES4TG85TW4SysmdTwWQzqV4o6f3kIymUAWBM4+7WSOP/74Wd9TWCDb29nBppNOm/R6jtwVi+ABvLrsQkY8z6HrBpIk0nfCB0gnE4z2dWIe2oHDUPP1dToCB92VZLLRB8k0Ka2uwx0oy8uQLBTzidpFQiG6Ow8B0NjUzFnHHsW/ly4nGg6y47WXuecPd3DquRdSMk/1+WIoc+TIjA2X108qESMeDhIdG8EwdPYpNcQSAyx1WVEeX3Z0EIDOpECry6RAGou+0XH2dvfzrq/8jJ6S0qkfNwm51OJob2e+WaatbXbh5VNPPZVnn32WV199FYeR4W+//AlXfO6/JgScZ4BpGCSDIyTHhjCyskSSYsdb04Ti8hT8Dv87GEtopJNxMC0ZnPKq6mkyTYIgsHLVapavWE1XZwd/+8ufuOFzn+GKD1/F+g1H57eLqhPXUSoexTRMBAkWL13O8EAfCUGgPZVEdMs44yMzKHSCbdkGzl22gWNWLOL2+x/nup/9nk+/63zWtM1etxt4/W5CG94BwOlnncXrr76MKIpsef01Nh5z7LTtdYO5vV7ngCQsjNw98Lc/5QWGc3PUQuHyTNSUJmIzG81X1TXQ+s530bl8NfNXyZuAaZq0x0wisvV51SQpi6VRY6DUL5rzvQdCGSIZ65po8CrYJREQed9bzmJRQx1f+PlvEUWRjnseZcXiRRimiddmw6MoSKJ1dQhASX8fQ22LMSSRkeZWqg4dQNI0ln9kYrGmh4rXoY9oIlVlJRNBCFFgcamTUqdMMKkykpk43nAoRLj3EL2hAdo7O+nu6WFkbJzPfOojuN0ekppu2Y1m1/kOWWQkrnHej67Of97P/nRP/vlCtAnnA425U63aYSes//fwhoidIAhcc801XHPNNaRSKR555BGOOXoDq1evKrp9peN/h9yNjQzz+ssvYLPZaW5bRNuSifqfXEFzMWiaxj/+9lcef+x5PnDi0Zy4tLjHaiFshoZbTyOv2kQqlcLQddyBcgy7B820RDuLCetGwmH+cOcd7NqxnfdfcSU1K+fWn1McLut6FwR0NbPgiB1A4AhMak6Pj4q2FUQGe0mExjB1jchQD/HxITzl1Tj9ZZNEaHNQMxl+/d/fZ6CvB1kQqKqp5dOf/vSc33vx4sVIkoSu6+zbtR0zq7k0FTmCZ2gqaiqJnklZdVoumVKXg/uMWha1LSa5fwdqOo1pmthaV+GqqIF/34kJ9DhL86SuPBPDfsEVswrJzhdzkbv77/ojYIXQ16xbhyRJfPj97+VbX70Zr8/PS0/+m1eefoJVGzaxdPU6mhctpqxydmu5QhQjMw6XB4fLg7+8mtHeThLREH2OGhKVEyK99qF+aH+doCbwekTAJYFXsqyKfr1thKUnnYPDyBAeHcbmcFLm8xStm8thcHCA2vp6nIo0J7ETBIHrr7+ez3zmMwwMDNDT1cHfb/8JV33qs0SKRBANXSMdHicxPoSRj6AIOAJluCvqqHAfeaHjuZAbb8JpnVFRxDRNXO7ijTC5oHJTcwvXf+FLPPfMU/zy5z9l3YYNvPf9l+P1+fAqYp7cGbqBXZEQRQmvz2/ZKMaiOJwu7A4nYkkptugeAJSlxclNybrj+YzDzr9f28F3/ngfF56wgUtPO3bGaz5H6gBWrV7LkqXL6Ors4Plnn+Zd77mMkjkI/puNbVu38MQTTwCW9tvVV199WB3VZ65s5sHs8/gsxA7guDPP4947b2f1xmPxF+munikNa5gmB+MCYxlwiHF8NoEmT4FtZu/BSdtPJXrdUZXRpM6YHEDxlVJrnxBVNjMpvDYJw1XKaAbUqc1jgjAp1WtLpSjr6WK0qRnNpjDS3MLJp6zEiEeYDXc/9RK3/uNf1JSV0FxTgcfpwKbIKLKMPfv/sOxiz0iSocEBpOgo1eUl1NVUc8Yx6xlaupjXduxCcbrJGCZORSKTZfEem0Sj30HAMXnO3tfRjdsmI0lzjyELhTqPrlj1/61dsYWorKzk8ssv57bbbgPg1ttu43vf+faMNQ12WST9JneVvPLCswBkMmmWrVxjuSrMQujAInW3/eTHDA30cfPbz6auZH41LiKw+pLLiYTDDI6FKK2ozEtVeP0ljI8Mk0xMpFRM0+SVF1/g7rv+QlNzC9/8wQ8JBKwUb3d4drFF0zCsugPTRBCPjORIDulUiv7eHiKREJl0Ji/unE6lyKRTpNNpdF239AFlBcHmAAEETMx0Er/HRUVFBbqaITY6hOJ04fSVYPf4ESUJVVW546e3cGDvLmRBwOly8YNvfrWojdhUuFwuVq5cyfbt2xkdHmKov5fquuJio+lomFBfhyU6m1tBygpLli7h2ccfo7JsYuKRFQV/eRWeQCmhd16HeM+tRGVr8q9IR6nORAgdAVI3G8ZGhnn8ofvY8vILBPwB0qkUZ5xjWfMtXb6Ct19yKX/5290ksx3n2199KV975/Z6aWxdTNOiJTS2LqK0vAKPz180ojWWUmeMVMmKQlXzIgY79pOMRQgO9uEtqUBWFAKVNQTN9UjDHRimSSIWJqELjAkunnvmaT5+9TUM9FqVRaZpMmZ30LJ42SR1+EK0HzxIf28vdkWal/yE2+3mS1/6Ep/73OeAFLu3b+VXP/kh77jqk8iyjKHrZGJhMrEQajKBoWVIpZKMjowQiSUxFDsmXZhsRtbSaKqKrmuIooTd4cBut2OzO3A4LHcam8OB1+ujrqFxUgH94aBwzLFccayScEM35hx5BUHgpFNOY+XqNfz+N7/mqzd9iXdf9n6O3nRMPvo5nEmiqRrllRaZKCmrwOlyMzYyjNvrxesLYE/OfX/Zlm3gLEFgSUMNP/jLgwyMBvnUO8/L21DBZEJXeIzLV65i/769ALz4/HOc/5aL5vy8hWK+0bpIOMxvbr8t/+8rr7yS0tLDI5o+30TtcCxcXOYjh8Wr1rF8/Ub+9qufcfl1N+bdImBmUpcxRQ5EDSKq9eXcikCrZ8KtwTBNBJhGSncozSw3e+mLafTGNMbkAJLLi72inqeEyWNiX0kZJvdgahrjpSX0L11OcCxIemQEKaNiTtEadUUilPT3E8w6zewZjrLUY0VMi8EwoWtwhKsvPoejlrbQOTBCIp0mo+qoukYmo5HRNOptJsdffDZywwoaw+30xVWSWd3a7Q8/QluzlZHx2CRKnDIem4zPLk/SQswhnkzSMzSC6CuntbV1Wjf2G8X/p50npuL888/n2WefZdeuXQwNDfHVr32Dm2/68iRyF9YmBgm7bD1/swjelldeyj8/+4xT5kXqfvbjWwiNj/GVr30Dr9dL8s7v4rz8CwAk7/zujO91Xv4FYpqB6A5Q6w5Mek2x2ZAkiVQijqHrRKIRfvfr/2Hf3j1c9v4PctwJJ06KbDX6rYlkJoInyjICVlGpmkpgc80sQTEXkokEr7zwLAf27qG3u5PhwYEF+TOWlJYxMjYRmjc0DS2TxuN2UV1bR1lpKc2trTS3LkJWbNx9159JpFQkwO5wcO1nv7SgMPrxxx9POBwm1T3A3h1bZyR2mppGUmxosTCCJCPb7Xgcdo4++hhuu/WnIEqUlJXjcHuwuX2IBQR5cMM5sOc1bIZGVWb2lerhwDRNIqEQg/29DPb2cGDPLnZv24yJiYjVPXnltZ/J65sJgsDb3vEuzjz7XD5+zdXseP0VSssrCZSWWSrx0Sh7tm1mz7bNkz7H7nDi8fnw+Px4fH68Pj9ur5fainJ82X97fT68fj9OpwtBEBAEgYqGFrr3bgfTJB4ex19eZbmRVNfT5FcJxpJEEl5GDQev3n8/y5cvp66+HsMwSCUTlr2frJBJp2Ykdv3ZGju/3z9p8pwNzc3NfPWrX+Wmm27CNE2GBvv44y1f54KL34maTtLRfoiuznbGx4IMDfYTi8eRbI5J57amqoqxBdToCYJAZXUN9U3NLFm2kqOPPR6n6/DrJxPxOGCCIMzpv1yI0tIyrv309Tz71JP8zy9v5aUXnuMDV3wYt9tNKpFAkiRk2wSRcDhd1DU25/894mmhItYx5+coS49i0VL47vrjuen7P+UnT23juo9+MO8mURHrYMQzPYNxwkmncN8/LImhl198viixOxLp2LkQCYf57je+xvjYGHZFYt26dZx55tz6ejOh0KViuKCudyac86738tsffYs///wW3vXRT/BWV7bDvbKezHAfqimQNiwx4KhmMpbW8/WslQ6BFs9kC669EYOoalLpEGnJRvHU3oOYzU10RFQG4hapE+0OnNVNxaOSago9GQfDIFq9HM2moEkShihh2gRGWxdRIQp4xkbzYtXesVE0m41oeTlhFXZFYbnHcu/JIZiBg3FLfH08Emf94hZaaqtoqZ3Z0F5pauFg1yEORifmNlkUyMTjHH/0Ko6t9yPNQ9T+QFcfSUcAN7B06dI5t18oVN2YMyL3/4mIHViD4Kc+9Sk+//nPEwqF6Ozu5nvf/wGf+fSnkHwzd77lCF4hqjwiQwtskXfaJgbwTCzE6EAvNkmkpa2NsjlqkjRN46c/+gGhYJAvffnmPBl1XP4FdKyInO3yL5CZQu78H/4ioZROYhZyarc7SMSi2BxO7vnrn3j44YdYtGgRl3/wgzgcDnZvfR27w0FdU+ukmo5Gv70ouRMlGYe/jGR4jEwsjLt0fnpyhelXXdd5/JGH+Od9/6C0vJz+HivaIgoTfY+iAIJkmXbbbHYrsuFwIAoiuqGjaxqKzWYRzEyGRDyGqSjYFIW0rtPe0cHB/ft46YXnUWw21EzGSnvaHbQsWcaXrvtkUZeJ2bB+/Xpuu+02kkmVHZtf49RzLyy6nYCAlkkhKQqy3YVsd1DX0kLzslW88NJLbN2+g0vefzkAmm5OIrOJaBgJCKiJIlrzFjHTNI1MJo2azpDJpK1H9rmqZvLPM5kMatp6PRIO09XTzWBvD/G4FXnTMhkkWUEQBUQsSYYzzruQFWvWTfvczo52hHSSVStXEs/onHb+Wxns76H70AESsemNOelUknQqydjwZHFjW5HZVZZlvP6ARfj8flDT2G0KpRWVNC9dhc8fwOf30+jWqS7xUl3iRTJK2b1nD1+48SZqa2vp7+lEkmXSySSpVGJG4hKLRglnOxUXYu8ElivJTTfdxO23387u3bvpSSbZs2MrUjYaLMsyNpsNHQl3tjFEEEVcLjeKzYYvUILd6cx6SouYhkk6ncIh6KRSKUZCMfSCJiDTNBka6M8/7vnrH7jg4ndx2tnnzZmaL7aQjIZDCIJISXnFrKnqQsRjUXo720mnU5T6PVxxxRU8+q9/cd21H+P8t1xAa0sr6XSSBsfshDNHyOZD8Pw+L1/73Ce46fs/5ZZf3snnPv6hWb9vdU0NDY1N9HR30dneTjwWw+2ZvuDMzYVvBsEbGxvlFz/9b7q7u3AoEmVlZXziE594Q6LWfr8fj9dHLBphqLdnxvKPHBSbjU9+7gae+5/v8sC3r6f6/e/B6XZbwYu0UbT5SBCg3iVS5xSm7VszpjsgGKaJtP1RBlTrR5QcLpw1LdOyN3omRSY4hB6ckE/SEVi2ooGn/hlF1DRMUcSUJUKVlUTKKyjt68GVFQ4PDPQjmAZmSz3xTJqdWXLnkCaOO9c/0D8apKZIU+FURJMZBrKkzuUvoVHJUOKQ+PnoECuazp4XqQPY1znRHftmELu0ZiDNEXB6szOORwJHhNgB1NTU8K1vfYsvfelLlJSUsGv3bj79+Rv40Ec+xvoNGxa0r6psi/xQTCWQvZpm0+10yRMXxbZdO/PPV66eW37l73/5E2MjI/zXV7+OO1v7YgK5j8v9v5Dcme/73JyyLKZpEhwbIa2qPPDQQxw6sJ+L3nYxK1asnLRNKpmk88BefCWlVNbUYpvD8NzM1uvNR8MuB7skYJomO7dv5e4//5Heni4ME0YG+lm+YiWNTc1sXLOc1tZWKioqcDgc03wf9w5NrjMpJESqqjI82M9Aby/9vT109XTT09lBcHSEof5eYtEIza1tyLLMZ6/92IJJHUBtbS1NTU2kDrbTdegAw4P9VFbXTtvOVVqBKMvERvrRMykkPUPX/t3Uty7hssuv5Os3foHjTj4Vr9/P2OgY8ViMeCxGJByi5+BeMl37EGNhEs2riUWjJF68lnTKImg5gnq4yBXlxqPWhF1eVsaiFau58ILzOe2MM/MSFwIT6SfTNPnLHyzNRVEQ+fSnruGU087IvzbQ18+B/Xvp6uwkHAoSiUQIh0JEwmESiZk7HdXsrKFpGsGxUYLZ6GsmlUTXVARRosx536T3OOx26pevZ9eObfj8Afw+H4f27cY0DCRZxuX2UNfUgstdPJLc1zsxKDc2LtwxZc2aNXzwgx/kxhtvxOl0sn//fkpKSmhoaKCmpoa2tjYaGxtpbGwk4yyhsroWJZsWy5GtSt/MJEjTNFKpFMPDw3R0dLBt1166OjvYv28vhmHwwF9/z8vPPcPF734vy1ctTNrJ0HVLe9Kcft9OvZXTqSRDA31EQ8FJAqxOh4OLLrqIXbt2ctdf/szS5Ss588wzGB8dxj+P2rb5Ru/8Pi9f//wn+eK3buEv9z3MZRe/ZdbtV6xaTU93F6ZpsnvXzqJNFHB4pG6uu+31V1/hjl/dRjQcYcXSxYTDYb71rW9RWfnGRdQr6xqI7d1FIh4jFg7hDUwnMKauo0bHURIhwpk0x596OkMPPsz3b7+Tj13xQRwOO0rBlxAEMFJJxoYG8Io6iTIfwYCPEq9nErnLPc11PKd1kwNRK4qHCKUOiXRt27RmNTUWJjXUhSBK+QWW6HQhugM0+Ww4IhHsyQSGKOHKdvsassRoUzMl/X14xsYQgMDgIIESJ+1DaVI67IxAmwdKlIlzkslkCEZj1JTNg9hht5pg7C7WLG5CliTGxoNETYmmjSeDY8q817On6H72d/bkU7RvBrHT5hGx0/6/ErHLoaGhgVtuuYUbbrgBUZKJhca55Xvf5uRTT+Oy930AzwK1hHIEr5Ah+2xivgvIl23RK8x579qxPf985RyD746tW9m+dQuf+eznJ5G6mWC7/AuIQHIejN00TZ5/5mkefuhBVq9dx6euux6X04Xd6cTj9eH2+lAzGcZHhlHVDMHREcLjY1TVNeCZIRJnmiaZuEWwFOfcadic60THoYPc/Zc/snf3BOlds2497//QRzh62dwNIgDLqoqfuz2DERRFoa6hibqGie5V0zR59aXn+e5NN1BZXYPT5eYbN3+ZdevWzevziuGss85i30FLJuXlZ57kwkveW3Q7R7a2Lz4+hBYcQlNVug/soaSqDqfLxZWXXsyZ517AwQP70HUNLZ3BMHQy6RSSrGB3upBj24vuez5QihSlqLpJWUkpDbXVPPv0UzQ0NOBwOrn0kndy1jnnzbivXTu2050VKG5ubeXkUydkUAQEauvqqJ1BpFNVVSKRMJFwmHA4TCQcmvQ8HA6jjfUSDIeJROP8P+2dd3gU9dqG79nesuk9pNF7V5pSpFkQjqIesXdEQBEbYAEV9eiHYjkqdlBRUFEUQaQISJHeW0glvZftdb4/NpkkJCFBaXr2vq69CFtm2+xvnnnL85qF6sXV7cQjilR6FSjlMjQqJTKZQJVbTkFeLocOHCApKZm35/2H/gMGEp+YSEyrBIJCwk4b1cjK9L2PltbXNUbfvn15+umn+b//+z9iY2PxeDzMmjWLAQMG/OWxYwqFAoPBgMFgIDk5WZpWUFhYyDvvvMOOXbspys1iwbyXaN2xK+NumkDPjm2b3F7dtUQfEIDNasFUWVHvPnVFnSiKlBQVUJibjdfrRaFUolGpCY2IRKlUYTZVYq6qomvXbrRObs2vv/7Ku2+/zZix40hq2zKD6JaKO2OAgScfuo/X3v2YLu3b0q1T0wfRzl27sXqlr9XgyKGDjQq7MxF1p67BdYM5NUu9qaqKLxd+ytbNv0u32Ww25s2b1+gEmz9DZFw86cd801uK8nLqCbtQrQqHuYrKvAyUChVupy8aZVIFccO11/DxspUs/XUjE+68l5yCAhwHfiM7L5+MnHxKK6uIDgtBp1FTUlFFhcmCVqNixCU9uGZQH0IDjZIPmd0tUmL3km721p7sRbcl3xjdYH/3ul04irOrTYG96CMTkGsNCIC7ehxjxIBuGLa5MJ8soO/lXYgIjyClwoHbK1Lh8SB3udFVm/rHGDUoZMGkllpxA8dMDmJDjSjcTxxmgAAAXOlJREFUvsheZnYO4UFGjPrm6zjVKiUete8Y63K5kau1bN9/iA5t26I5VdQBtOqI4LT53m9hpvS4ffm+419gYOBZtzoBn9aQufwRuwZEREQwb9485s+fz+7du8HtYdOG39i5fTtXXnMNo668WhJRLUWtkFG3jNmoqr9KKGQCbq8vrXb44EEAVColbdq1a3KbFrOZjxa8y/U3/pvoGF/kR1m9gvzVr81sMvHRgnfZ88c2rht/A0NHjCI4NBwEoUFaIzAklJKCPEqLC/F6vOSezEJfUUFsUluKbfX94QRBkM745c0Ujbrdbnb+sYvNG9Zz+GCt8W1kdAyT77+H/v37n5X5mx2jGq+TOlpQhb0omytHDuf48ePcdtttzdqaNMewYcN8Y+xsDnZu3sjIa6+X/MBORZDJMIRFYwgOJDcjlbTUE2z+7FOsFgtut5u0Eyk4rFa8ogev2xcVUSiUaPQG5HIFguCzd9HpDVJKWqVWVf+rRqZQolKpCTVqUSjVqOvcVvO3Wq1GpVKj1WmJiYmVTmw2bfiND977LwBfLlpIp85diT2l3rBGG/7y80/SdVdfW+3318KgoVKpJDQ0rMFM0rrUHOS9Xi9VJjMl5RWcOJlPWk4hFVVVmM1m7DYbbqcDCyo8Xi+dOnfB7XJy5OgRUtPSmPfWu779uxkyMtKkv9u0Ob2Vw+m4/PLLycrKYunSpXTo0IGjR48ycODAP7295oiMjOT5559ny5YtfPDRJxQWFpB29CCvz5lJ1+49GHrFcHr26t0gyl0XVY2jfhMRX4/HQ1ZaCubqg6pMLickLIKwyGhpu8ZqYeH1ehFFkeR2HVi7ehU//bScsopK7rr3gUbToKfS0tRsQlwMo4ddxtuffMHTr39AU7HODh07+br/PR4OHWx4QnQ20682i5l1v6xg5YoVmK21FguXDxrA1KlTW1y32RLG9u/OtrWrACjMOUnrTl2lznt7VTnlJ1NxO+0IMjkKtRqlRk+iUIlSruP2eyfy3FOP8fjkicS2iqdbmIqO8TFc1b8nrWOj0Gtr1y2X201qdj4/btrB8x8v4ZZRQ4hJak2VS6TMKVLh8iLgE7iJehllMQkUWRqWK7lN5SBXIDqs6OI74kGQSkrqjkAEMMRHIRMEDCoZ3cI07Cu2EdqmFZHdEjF9/bO0zQiDGq1STkqJBTtq8kwORFEFOMlIT6dPh+TaJrXQKDylBZyKolN/jG4PaqUcZAryK8wkGQLYtOUPLh/YeHQXQFRpKVcEQVI0wRnb+MNuxO6wo1bI6dWr11mdH12Dw+VBcJ0+G+do5vaLgbMu7ACCgoJ47rnnWLt2Le+8+z42uw2bzcqyb5ayeuXPDB46jMuHDCPuDOtsTodCJpCfl095WSmCAO07dESn8S2mjXWxfLHwUxISExk6bJgk6M4GB/bt5eMF7xIUGMiUR6YREBDgsx5ooq5GoVAQFRdPSHgEWenpWM0mLFWV5KanEJvcThKCNdMjlFqdb8pBEyO9igry2LHpNw7t2IKpqnbuX0xEGBMmTGDEiBGnPQCdLTpGGZnz229YLBZ0Oh3XXXfdX95mQECAbyLBmnWIDitrV3zP1eNvbvL+voilirJKE58v/Ayv10tUbBwdOnUhLi4WrVqNVqvFGBhIWGQ0gcE+t/mgoBAMAQFodbpmFw+jRo7nDLukLh8ylIy0NL5bugRjYCCffLiAp2c/3+C5TmZlcXD/PsrLywgPC6dv375n7OnVHDURHJlMRlCgkaBAI7Ex0fS02DHZHJSbbDjcbpwKHdFx8YRFRrNj6+98/ukn5ORko9boWPTZJzwx85lmP6uMtDTUSjkKheJPR+xquPHGG/n+++85duwYhYWF3HvvvX9pe80hCAKDBg2iX79+rFq1iq+//pqqqioO7NvLgX17CQwK4rLBQxg67AoioqIbPN7j8aDWaOs1OtRE67weD5mpx7GYfJEQgzGQuITkJrtya9YEjVZH9x49SUxKYsVPPzHzienc/+BDLSpBgZYJvEvG3sn6g1l8/cUi7r6/8fGIGo2Gtm3bcfzYUQoL8ikpLiIsPOKsCTqDSkZmZiYbfvuN39avx1LtMqCQC+h1OiZNmsSQIUPO+oE+OTmZSIOacpuLoszUembocpUaTWAIlpICZAoFIOCyWyn22BEAq6KCPn37kpeby2133Y1SayC0MotglYBWU/91KhUKOia1omNSK7YeOMb8r39k7JD+tOnRF4fHV9smFwTaBsjQKQTKm3ifHrsF0elAYQhGrtYi1AkHu1wu8pIHUx58GLsuC4CSpAEkOtIwuzx4RV95hkqrpdOUWzjy9pfSYwPUCrpHG0kvs1JscaJXyTGLCtJST3Dt+FHIQ2sjZ02JO5PNhtnmRKuRERocSElpGSmpaTz16JQmP/9yRVDt30n9OfD5IkICjVgslrM+caIGl0dE3swC+3eYPHHOjvCCIDBixAh69uzJh58tYtOG3/B4PFgsFlau+ImVK34iuXVruvfsRUJiEknJyYRUd/v9WTIz0qW/O3ZqegRT6okUdu/cziuvv1mvoLwlkbqm7uNwOFjy5eds+X0j464bT2yUr6MwLCoag7F56xRRrqZVmw4U5mRRUVKExVRFwcl0YhJ9kY1IvYpCixPRK+J2OvC4Xbjdboryc8nJTCcnM4PszHSyM32fgbo65NOpXRtGjhzJiBEjGg95nyMsFguW6hqOtm3bSrVOf5UJEyawefNmzDYHO9f/wrWjhuMJaDpaZLVY+Hbp19KZalhYGONvmgAe3xlvYGgYUXGJzRorN4axuv6zpvC3JQKvsqKC39atZcf2bRSXFKHRasjLyebI4UN07tK13n1XVUfrXE4nJrOJaVMmMejywYy6YijG8LM0I1GA4oAkwk21B3etSolWpSQqOIB8TRyZqcdxWszk55xEqVIRERHJbbffwQcL3sfl9nD44AFOpBynXfum04HHjx0lL9dncxIfH/+X9we1Wk1ycjLHjx+nvLwcp9N51q0PGkOhUDBmzBiuuOIK1qxZw+rVq8nOzqayooIVy39gxfIfSG7ThuTkNiQmJ5OU3JrYuDhcTgcOu63BSZUoimRnpkmiLiwymui4+BatgwGBQYRFRuF2ObnxxhvJzs1n/rxXGTJsODf8e0KLP4/TpWcFQeC+iZN4cvojXDFyFAmJjZdudOrSmZTjvrqok1kZREb++Ro3URQpKyul4GQGGenp7Nq1i8zqNH4NCrmcK4YP57Zbb/3TlibNkZCQQEhICOW5hZw4chCH3S5lCJQaHbrgMEAEsboJSxRxywx4RS8aUeTSQZfz5muv4PJ48ZgrcXpFcqwiJrdAe6MMeSPf8YBuHYgOC+blz74lp7CYCddeSaBGjkbu8507ltR0p2/N/O6aIIJMJkOuUOBxu6VBAU5nnTnXCiV5sYMx7/8Nl1fEqFMTpvPtM52m1C9zUcgE2oXpaRWowe72sm3XXoKDg+jdr5G0e7XQ85QWUNFzLKXFReRmFaM0BOFxWPB4PCz7cQV9enYnsJEIa11BV4PH42HL7xuxWyzExcXR+wzr9luKw+1FcDcTsftfTMWeSlhYGDMee5Q7b7mZDz9bxB9bt+B2+1KM6WlpZGZk4Ha7kcl87d56vR693oDe4PvXYDCg0+mRK3yGhDKZgFajxe1xI8hkKOQKNFothgADf2zdgt1uR6PREHMaK43vlnzFyNFXExvhEwRn+jVpFbJ6dXbpaakseOctAgKMvPDK/yEXIO9kps8/L6LldQCCIBAZl4AoerGZTZgqKygpLMDt9fo6K4tKyU89Qv7JLIpLSiitqJQ+S/CJObVcQK3WcOWIYYwaNYq2bduek5B1cxQX11pLnI1C5hqio6MZP348n33+JR6Phy8++5gnZj1LdlX9qRM19YVLvlhIRXkZgkxGUmISt95+J/bqpgKDMYioVkln7fNpSuCJosiJlOOs+WUVO3dsp2Onztx9/0TuFQQWvPsOLreHr7/8nBdeflV6jMfjYffOnQAkJbfmjXfeJTfjBOvXr+fxxx4jMSmJAYOvoN+AQaj/rN9aM2+7OCAJBZDYpj2pxw7jdNjJzkhHrdGg1Wq56pprWf6DzwV+88YNTQo7h8PBR++/60vFAEOHDm30fmdKZGSkNEO4uLj4rA8EPx06nY6xY8dy7bXXcuzYMVavXs3a9RtwuZykp6aSnuozlxUBlVKF0RhAeFgYicnJlFeZMAYGYjAEIhPAVFmJSq0hwBjYYlFXQ3hkNAU5JxEEgQGDBtH7kn4sePctnpv5JBMnT21SiJ1KsSEJBOoJ/BrCwiMYNnwk3y39mkefmFH/xuqXGhXjW2/tNhtbN/+O0+HAZDLhsNtxe9y+mkG5Arvdhtcr4vF4cLldWKtPAC0WM1az71+7zYooini9XuRyeb30tVKh4LLLL2f8DTeQ+CcacM4EQRC49NJLSVv2I263m2MH99G9b62QURsCURvqn7QHqmsPqcEuD7FJbRECQomKjkWXspEyh0ilUySlyksHo6zR7zopJpJXp9zJS599w+fLVjD9lrGkJNcfixZpUFFoPmXSjuj1dV3U6ZJVKJV43G6cThfRWnDXGX2mlKLHAoJcgc3lpcruAsHXbCcCouirGTaoFMhlAlqlHNHt4oe1G/n3lVectmNaHhqFw24n/2QmNQK4a/tkqiorWfPbJma/Op+KahHX3Cnx0cOHqKysRK2Q06pVqxb5n/4ZnO7mU7HOZoTfxcC5z8lVEx0dzbMzniQ9t5CtWzazacN6MjMyiIyMIj8/D/AdAM1mM2azGQqb3lZYeDglxfU9qWJj49ixfRuCIBAdE0tUnXRITQ0ewJFDh8jOzOCxxx4H/nw9nVYhw+xwseKHZaxY/j3XXjeeq68dh0wmo6ykqNnHi6JIeloqebk5mE1miotLMJmqMFVVUVVZQV52FmaTCUEmQ6OrrUl02G24HA5f/VeAEblcqH7PcSQmt6Zth47ccPWIc7bjt5SqqlofuODg5rumzoTx48ezfv16Tubmc+TQITasW8vQ4fXHxjncIgf372XLpt8A38H12rHjsJl9n6laqyUmseHw85ZSE61rjBqBZ7Ha2Lb5d9b8upqS4mIuHzKUl197XarpBAiPiCAjPZ2M9HQyMzJITPIdiDPS06Su1i7duqHX6+nZqxc9e/XCbDazefNmfv3lZ7796guGDruCy4ePICLC5yPVkoZpmayhnUJdigNqBYFCqSSpbQdOHDmI1+PBYjIhk8no0q0bv/yyCofdzvY/tnLrnXc3iBKJosjCTz6ksCAftVJO+/btufbas2NiW3e/qqqqOq/CrgZBEOjYsSMdO3bkvvvuY/PmzWzfvZeM9HTy83JBFHG6fPVI6Wmp7Nu3D7V2lXQks1rMiKIXozGQ2PhEAgOrPQYDjISEhhIQEEBMbBxJyY3vq3VFjyDIiI6J4enZL/LTD8t4/tlZ/Ov6G7hqzNi/PD1lzNh/Mf3hh0g9kUKbtu0anBRERkUhiiLFJSUsX/YdOdnZvvdfh4jISIoKT7OwV1Pz+5HJZERGRFBQWEjr1q0ZOmwYgwYN8p3sn6fsw4ABA9i1/yAFpRUc2L29nrA7lbqiDsCglKMzBFCYl0t8UmssHa8g6vh6CmxerG6RKpdIdrvadatL5loOJQ6nh7qSMGBOhz5MffFN/rM5k7s6yxEEAXudOaUJQVqyKmy1Tyh6fWPrhNrvWq5QAjasdgf5NnA5a4Wdonpesie+K7q0vRSbnRwqMiMTBLRKGbZTmgh0SjkJQRo++foHosNDGXJJjyY/i9Tw3gRrFRRlpOEVvchkclp36IxDpeK/735Gv6Ej6tUV192dGluWtm7ZjFrhW3MHDx7c5PP+VVweLzK/j92ZkxwbSfKN13PrjddTXFxMWlqaz5cqO5vKykpMJhMl5RVYrdYmC42FRq72iiKiVyQ0PAyVUkW39q1RKpWUm307vlLmOwtZ/s3XXH3tWHQGw19qkigoyOfNN9/EZrUya86LJCYlS7f5CqVFZHIFLqejnoWJy+Vi5Y8/sHnTRmmRqxGq3roWItWTHvB4EL1eKVWo0eqIjggnKiqKoUOH0rFjR5KSks5rmrUlWOoMztb9BWPXxlCr1dx///08/dwcAD7/9GMio6Lp1KV2lJ1aIbBi2VLAV2w++uqr0Rt0uD1u9DojkXGJTdY9NsfpRB349o01v/zC7xt/Izw8nBEjR9F/0GWNfkeDhw4jI92XPt+/d48k7GqagAB69+yOvk7DkMFgYPTo0YwaNYqMtDS+XfY9T0x7mG7dezBi1Gi6dOuOIAgtEng11KRj6wq6uqg1GqLj4ikqyMNRVYlSpUYG9L2kH5s3bcBmtXJw/z56961f+/L1l4vYvHGDVFv38MMPn5URbVB/v7LWme5yodDr9YwaNYpRo3xDy+12OxkZGRw6dIiNGzeSm5ePzW5HWV3+4fF48FRHUOx2OzlZGdS1wo2MiiI/31evFBEVxeWDh3LVmLH10rm+Tm4FbrdbEtUKhYJ/jb+Rrt17sOC/b7N/7x4eeGgKYeGniZxXH1mb+v6NQYGMvPIqvlmymBnPzG5we0xsHDK5nNDQEMpKyxq1dTldWEYQBAIMegICAtDr9QQFBREbF0eHDh3o0qkTYWFNNwCdS7p06UJZaSlOs4kj+/bUS8fW5VRRB1BhdxGbkEj6ieP0uHQggiBQ3n4ohsPryVOEYNGGUDeJfCjRl2ZN9YbQRlZGmjKW6TOe5pU5z/LVok+5+fa7pPuKoq8kx2WukCJ1HocVkCHUWddqSh7s1YLOVS9i59tfjIHBGEP0eEWwnybNaHV5+GL1ZrYfSeWDZ1r2O3Y4fA0uBmMgKrWa779dSm5ONg8+NLnZx9Zgt9vZuX07AFqtlr59+7b4sWeK3eVFbK4rtpnbLwbOu7CrS3h4OOHh4fRrJE8viiIWiwWz2YylupOxuMqXnxe9XrxeLx6PF7fHjVYm4nA4sFZVUFxcjAwvFosFUVE/RbV3z27yC/J56qqr//RrFkWR9evXseizTxkydBgTbr0Nj6z+x6hSqREEwRcCd9QKO6vFwluvv8bRw4el+wqCgDHAiE6r4URqGlHRMbTr0Im4mEgsFWXodDratGlD165dCQoKQi6Xs23bNkRRpH379uek5ftsYLfbadWqla8oPyjorG//0ksv5YbrxvHNsh/weDy8/fprPPPCS5L1R3paKhlpacgEnyVI965dsdus6AMCCAkOIiKk6bpHs7PxH65BdfqF7ERKCj//uJw9u3fRr18/npoxi3bt2xNYbQdQVNVQfHTt1h0AtUJObmYaEUYdxVVWDh+qFXZdu/pq7xqLUnTp0oX45DbkFhbx29o1vPfOW+j1BoaPGs1lg4eckahu6qAOgAghYRGUlxajVKqwWUzIBIHOXbqwedMGALJPZtUTdiUlxajVGsmLa/r06WdsTHw6goODSUhIQBTFi0LYnYpGo6Fjx44EBgYSERGBIAj0798fj8dDeXk5Bw4cIC0tDZvNRlRUFDk5ORw8dJi8/Dxat26DSq1CXug7IS0pLODbJV9x7OgRpkx7TIrIOx0OPG43giA08MBs07YdL7zyGl9/sYiZT0zntjvv5rLBfz4NfvWYsTw6ZRJHDh2k0yn1oGZTFV6P1zfruGsXrrpmLBqNz9y8xhS6pttcLpdXl9XI0el1RIYEoqvTqHS+onEtQaFQ0LdffzasXYPL5WLX1k0MHDay2cdV2H0CqmO3nnzz2Yf865a7qie8yCiP6IhQXoTLbmv0sWaXh3341qeg4BCmz3yWV+Y8jU6nZ8SYf1FRXICprASP24W9WmQIcjlepx2FMQRBWfv5KZQ+8VZm9v0+XHVr7KpFnyCTYdQo6BpVbexdc6n+PhxuL5V2Jwt/Wse6zVu54+abyLVDoFGsN2+2htTw2vo3vSEAl8OB2VTFz8t/YNWKn3ju+RcJOIPu5d/WrcVms6JWyBkwYMA5raV1tyBi9z/nY3c2EQRB8pSqoTk7wvT0dFauXAn4vKciYn01GF58gmzpkq8ZO+5ffzq6JYoiSxZ/yaYNvzH98Sekg/KpvnZKtdpX6yCKOOx2qXli8eefSaKuR69eXDFyNJ26dEWrUpKXm8vTTzyKraqcW8aPpWPHjqSkpJCfn49CoSA8vNaxPjw8nKqqKkpLSy9aYVdRUUF2ts+Q9k/XgDXDvffey4nMk+zbswe73canH77P5GnTCQwMYv2a1dL9ho0YiUarRZAJBIWEExN3+tqc5gRcXURRZM+unaz48UeyMjMYNnwEb7/zX8LCGzZ0NGaOGx6QTGRYKBUVFRw9ehSv10tYgJaU6tqxsLBwkhMTm00Zh4aGMf6mmxl73Xi2b9vK2tW/8M1Xi7l8yFCuHjv2tJYnLUUQBOKT25KZmgKIqDUaAoJrt1tQXVJRw8b161i+7FvcDjsDBo9k0KBBf/k11EWlUpGV5evwM5lOP6j9QlJWVoZGoyEoKAilUolSqSQ8PBy9Xk/nzp2JjY2lTZs2HDhwgM2bN6PXanniqRmEh0fgcrk4eGA/v67+hX1793Lk4H6WLv6CO+65D6iNiMhksnozSmvQaDTcee/99OjVmw/efZuS4mLGXX/DnypB0On1XDXmWr75ejHPvvBSvW0UF/nKT4xGI1dccQU3XedLtxc3cjJTl/DTGEZfLEy4fhwb1q5Bq5Dx+5pV9B8yvF60qiZaVyPm6tK6Q2ecTgdZ6akktvZ5HsoUSgSFqtmMQZi2epxbRATTZz7L87OeIjfLt8Z4q6ek1E2ZytV6dDFtEeq4PNTsE65qHzuXy4XbK6JQKLC4RALUYHJ4OBbaiyiDkqCs7Q1eh8th4/1FSyksLWfmpHtQGUOotLs5UWKlXVitIK8r6ADyTU4cCj2pGbtY+dNylCoNd0x5HFlwNDmn1ETHGWvFWs2rF6tf78qflktp2LPhrnA6XC4vQjMROdffIGJ3jif4nV/i4+NJSEggKiqK/Pz8ercdPLCf8vJyhlcPWD9TRFHki4WfsXnTJp6d87wk6oAGdimCIKDV+hasmm634qJCtmzaBMDQ4SN45PGn6NajJ9rqAtawOgtcjYCLqa7FcrvdlJfXDqJWq9XY7XbKysrqdTldTJSVlUl/n01vqbrIZDKef2YWbdq1IyQklJRjx3jj1VcoKSlm+9YtgC9d13/gILR6A62S2pCQlHRWUoFOp5P1a9fw2CNT+eTDD+nVpw9vv/8Bt95xZ6OirikEQZAmcVitVrKysrDZbMjwolLISU5sWTG9pno8n1KpZNDlg5k992VmPjebysoKHn94Kos++ZjyOt8J1Dd+bSkqlZrENu2IaZWESq0hJq6V9Pry6wg7U1UVv/6yErVSTkBAALfffvuZP1kzBAbWRl1LS0vP+vbPBg6Hg/Lycux2e70TnLKyMmmqRM3vvO5+GWTwrQdKpZJevfvw5IxZDB7ii7Zt3riO0ppJIVYTcpmA8ZTJBafSo1dvZj73AuvWrOabJYv/9ASVkVdeTUF+HsePHql3fVFhIfFxvukwCQm1RuXhRt1pL38HkpKS6NfXJ1pKigo5vHe3dFtjKdi6KBQKOvfsw55ttUbKiCIel6PJiN2pZFfaUShV3HzzzezbvYsVPy5HHxRCdFI7Ejv3okuffugSOmFI7oogk9WrsVNWR+w8LpcvfVst8Grq60yO2kaAArOLY6G96rxMkZ0HjzLtlXcI0Ol4/YmHGNIlmYjqxrQSq5NSq297p4o68B231v26is8XfkZCUjI3TZiAXu7F5bA3uG9OlbOB2ANfU1ZF9bGvX79+f2pizZng8XjxuJu5/A0idv8oYRcWFkZWVhYFBQXk5uYSbKhtINiwbh2Dhwz9U2FcURT59OMP2bn9D56dM4eYmOaLtA2BQSD4mh1Er5eD+/eD6EWhkHPzzRNQyWXEBOmlBa7u6yqsrr0zGAzSwaCyso4nXUwMQrXZcV5e/SjJxUJde4KzmX47Fa1Wy0MPT5PqEzPS0njmycdwOHyLxKDBQzAGBZPQph0h4REtntPZFGaTie+/+5apkyayetVKxv7rOt589z3GjB3XqPG2Udd8dLht29rpBbm5ufWiT4YWGM429RzJrdswZdp0Zs99mfLyMqZPncwXCz+TFsozoo5mUKnURETHkNS2A2q1WhKyebm50jzd/771Brbq9OjIkSPPSWND3f3qVDuMi4Xc3FzptxodXdvQVfN71ul0Urq8sE5jgUqlIsiglS7BATpunnALgiDgdntIO3YYtVzEXi0OAoOC0KlkDS51iWvVilnPvcDmjRv46otFPnFXk3drIRqNhoGXD2HD+nX1rs/Py6WwsJCsrKyzNvnhYmLcuHFolHKUMoE/1q0kUK2oJ+oai9bVcPmIq9i1ZZM0tk+lN6LSG/F63Fgrmj4hKbG5ya604zBVkJuZhjE4hPsmPURRSSmlFSZ0xqDasWEyWbWoq/9l1o3iHs6vxGL3TchQnuY4eCy0F5UmM0/Ne593Fn/PTVcOY/pdN6HTahAEgdahOnRKOSalkYPuoEZF3cnMdObNmcmhvbt57PnXGPfv21AqlTjtVgrTjlBZmCvZs9SlRuDlVDk5WW7j5x+Xo6qO1t1www1NvuazhdcrtuhysfOPEnZ1Dx41aUCAqspKdu3cweBhwxp72GkRRZGPFrzPgX37eO75F+p129ZQM3dTKROkizEwGLlMhtNuw24xkZGaAkBCYiKGgIAGZ6thYWGSaeu6dbWLZk1Uom6XqUajkcYp5eTkXHRRO1EUycjw2SYEBgae9a7YU+nSOoHXXp6LoVpY7dm1i4ryMmQCjBo1Woqo/hUj6sLCAj77+COmTprI0cOHmPjQZF75v9e5fMjQRg2fjTpNi0QdUE8QVlRU1PuuWxrtNOo0UtTuVOITEnh4+uM8+8JciooKmT51Mos/X0hVZeWZRe2EUy7VRFef6DjsdsrLy1j4yYecOHoItVKO0WhkwoQJZ/AkLSciIkKqNavZ3y4mHA4Hubm5eL1e4uLi6kXsar7jut/v2rVrAWjXrl29aGQN0eEhJMS3QibAiZTjVFVWYrfZkclkBDYyxxRoIO6iY2KY9dzz7Ny+jc8XfvKnIneDh17Bzu1/YK3TIJWXW9sBG3caq6m/K7169ZKiReknUkg/kSLddjpRBxAd14rOPXqzbsUPAChUakRRRC5XUpGXhcveMF1tc7qxOd2IXi/2ihLf/ZVqOvUewDOvvE7n7j1b9LprauzAN1asNmJ3+kijqd0QhvXrzYLZjzFq0CX1BKNMEHDG+LIMDosJi702AieKImtX/sS8F56le+9LePTZucQlJKALCsMYFo2AgNfrwVxeQmHaEWxVFU2+hrwjuyks9DUP9ejRg3anmSR1tvC4vHhcnmYu/ojdeSUqKko6+929ezf26h1u86aNtGvfnujohkPjm+PTjz/k2NEjPDP7eUJP01V2qmgIMOilH09lRTkpx44B0LZt45WCgiAwcqSvKHfPnj2cOHEC8C38Mpmsulmk9gynJn3j8XgoKGjo9H0hycrKkiISSUlnzyfudMTHx/PIY49TkJ9HTEwMOr2eNm3bNRgXd6aczMrirTfm8cSjj2CxmHlmzgvMfHY2PXo2PdKmpYKuBo1Gg8fjIT09nblz5/LII4+QmZmJ1+s9qx3FiUlJPPr4kzw9+3ny8/J4dMpDLFn8BeY/W59W/faj60Swly7+kq0b1yOTyVAqlTz99NPnzEBWEASSqruIi4uLL7rodV5eHl6vF0EQpN8r+FJUvgO7XBJ2R48e5dAh3yznmnWgMTpUDz4/cfwY5gpfal2pUp3W3uhUcRcZFc2s2c+zf89uvvp80Rm/r1bx8cQnJLBtiy+9aLVYpGafgIAAws+gFOHvgiAIjBs3ThpAv/ybrxBFsVlRV8PIsePZve13SooKEGQyAqPifbUQohdTcf312+as9SZ1Wk24rCZkCiX6yDjKXeIZZZ0UyloB53Y5pVo7pfL02xAEgVGDLkGjbni/wyE9UWlrT0Zr6v08Hg/ffrmItatWMG3WHEaPG4/DVEFJVhoFqYeoKsn3NT663dhNFViryqgsym20g1oURX6s9siE8xOtA/A2l4Z1e/H+DQyK/1HCTqFQcNlllwG+rswtW7YQbNAy5Irh3PNA4+NwTsfvmzbyx9atzHj6WUKbaLd3e8VGRYMgCISEhqPRaMk5eVJKs7Tv2LHJ2pIhQ4ZgMBgQRZG5c+dSXl6OXq/H6/ViNptxOBzSfbVaLcHBwWg0mnrWIhcDGzZskP6+9NJLz9vzDu5/CX369iUoKAitRsNDDz/yp7eVl5vL2/Nf57lZMwgMDOL/5r/FQ1MfISk5ufkHnyFqtRqn04nX6+Xuu+9m8uTJKBQKBEGoF71rjpYKyqTWrZn+5AxmPPscmRkZPDFtCuvX/nrm0Zvqu0dVpxjLyspY+eMy6eZHHnmEjh07ntk2z5C6+9dvv/12Tp/rTLHZbGg0GkJDQ+tF6+x2OxaLr8Nfp9NRUlLCSy+9BPgi3Jdffnmj21NrNHSsrsfMPnmSvPx8tFotoWFhzZ48nSruwsIjePLpZ9m0YT3bt2094/d2/6QpDLx8CADbtm6Wui3PxWivi4WhQ4eSFB+HQiZw5PAhtu/a1eLHhkdF07v/ZXy78GM8Hg8anQ5DiC9QYDdVSLY3p+J1Vq/5oohS5+taLbY46t2nnpfdKdSN2LlcLlzVM2OVqoaNNnUxOTzkxvQlNby3dDkc0pPDIb5IYd0GDdHrpaS8nDdeeYGck5k8/tyLJCa3xmExUZaXictuqV1bZAJqXQAKlRpEnyh0OxwNnr8k9RDZJ7NQKXzelzXOAOcab7XjRnOXi51/lLADGD68duTKmjVrEEURnU53xtG6nOxsPv3wAyZNmVqvGL7uV9rYDNq66AwG7HYbu3ftlBy/L7u0T5P3DwgI4Mknn0QQBEpLS3n55ZfriblTw+dhYWHY7XaKi4vrTaC4kHi9XknYyeVySWifLy7tP0D6++D+fWf8+MKCfN575y1mPvEYOr2e/3vzLe64+x7Cq6O1srM4V7gGi8WCVqulTZs2REVFMWjQIOLi4hAEgaKi5s2u/yyt27TlyVnPcN+Dk/l5+Q/MnvUU6WmpLd9A9UcREGDEbDaRcuyIFFW+9dZbmxQoZ5PBgwdLQmLDhg1/uingbONyuSguLsZutzeoOav7O7bb7bz00ktUVFQgl8uZMWPGaaNvNaOUnC4Xu3btwmG3YQgIaNFrOlXcRURGcd+DD/HJB+9TcEqzWXNEx8Sg0WgQRZFNv62XporUXX//aSgUCqkJSCmXsfLbr89ofxvz71sxV1Xy6/JvAapHkgGiF6fFFzWvG60DX+RKkMmRVZ/oNUZCUNP7S93RfW6Xs0HzxOmo21hxKi6HvXoyhcjBvXt47bkZGAKMTHr0SULDfMfLysKa9LxAWKs2RCZ3JDy+LQFhkQRFtSIsoQ2G0Ejkp0QP3W43S79eLNXW3XjjjeftZMHtFnG7mrm4L4415nT844Rd+/btpVq7w4cPs3DhwjNe7B0OB2++/n+MvupqevTsVe+2mg+sOVEHYAwMoqKiks2bNuJ2Ouh3Sd9Ga2fq0qNHD+6++27Al555+eWXpTmYp87XrPGHEwSh3givC8mePXukDsVevXo1+37PNj171Rbybt60qcXffXFxER++/y5PTn8UmUzGf15/g3vue0CyCZHJhHMi6sBXYF9DXFwcBoNBOrgXtsCp/6/Ss3cfXp43n+49ezF39rN8+uGCM0rPdurchVdffomhQ4aQnJzMVVddxY033ngOX3EtoaGhdO/u61AvKCjgYB1j5wtJUVGR1OV6qo9jzW/Z4XAwd+5cqezi/vvvp3Pnpmdcg+9krnv37jgcDtauXYvFYsHYglnU4DOflcmoVx/Zu+8lDB56Be+8MU9K07UUURT5ctFn5J3MBCA5OZnkcxDRvpgYOHAgXTt1QCETKMnPYc8fm1v8WLVaw91TH2PH7xtY/eP3yJWqatGmRBTFBqKuBtHr8249HQlB2kYFXt2IncNhl9bD0zVP1MXtFXF7RRyndII6LGaKC4tY/MUXfL/kS6667kbunPQw1Hk+r8eNIMjQhYShCwxGpdWjCQjEEBJOYGQsgRGxGMOiGti+7NuwisI8n1V3cnLyOTUkPhWP29Oiy8XOP07YCYLATTfdJP3/u+++Y/nSr84oorVyxU+o1Rquv/GmRm9viagD+G3dGn786UfAV9x9utqZuowdO5YrrrjC126+cycffvghAQEBDc5atFotkZGReL1ecqs7Ei80339fWxfR0vd7NrmkR1eSEuJRKeSkHD/Gvj17Tnv/srJSPv3oQ56Y9ggul4uXX5vHA5MmExsdjaJazJ0rQVdDTk7tvIHY2FjfzOBI33iwwsJC34i9c4hM8ImN6264iZdem0dZaSlPTJvChvVrm9+nBPBYKzh0+DBVJhP3338/EydOPK/puBEjascyLVu27DT3PD/U/B69Xi/R0dENfBxlMhl6vZ4PPviAPXv2IIoio0eP5sorr2zR9ocPH05aWhoKhYJvv/2WjXVKH07F7vZKF+n5T/lqbpxwC6IosuaXVS1+j263m88/+4RfV/0M+Nbd81UHdSERBIE777xT+v/6H7+rZ/rbHCHhEdw77Ul+W/UjG9f8Ul1z5vINZW3s+apPDkSPp95vUZoLfsqlXWj9Mp+6XbH2OibezTVPnA5TVSXffP4JH3/wHvFJyTz9nzfod1ltCr5GBHo8bkTRi0xoucwoys9j+TJfRFMQBKZMmXJe1xKvR2zR5WLnHyfswFcLMWnSJOn/P/zwAzOnP8KG9euaFXiiKLJ7505uu/POP22N4fV6Wfz5QlauWMHxY8c4ceIEoaGhfPTRR/WiM00hCAJTp05l+PDhUsSmKcuQmlE7NVM6LiTbt28nLS0NrVZLTEwMl1xySfMPOssIgsBtt90GgEohZ8lXXzb6nVssFpZ89SXTp07BVFXJCy//h0lTHq43x/V8IIqiFLFRqVRS4XlNFMrr9bJ9e0PT0MZobLLFmRIZFc2jT87g3okP8eOy73j+mZlkpKc1ef9gtYzNmzfz888/YzAY8Hg8f9lS5kwZOHCg1CF79OhR9jQj5s81VVVV2Gy+uqemRmHFx8fj9XopLCzk6quvZtKkSS06gJ08eZLPPvuMsLAwjh49yokTJ1ix/Hu+XtzQm+5046HqolAouPm229mza0ezQt7tdrN+7a88NvUh1v6yCrXCN8P04YcfPusG1Bcr3bp1Y2C/S1DIBMpLS9i2Ye0ZPT42PpF7Hn6CFUu/YN8eX52ei8Z/M/LqaSKi6MXraliL1hx1I3Z2a20tdnPNE01x/PBB5kyfTGV5Gfc/+BDX3XqX5NlaF4fHi0rju95haVn0XxRFfv7qE4TqZopx48bRpk2bP/U6/yzNethVXy52LtrJE3+VK6+8EkEQ+O9//wv4UiOffbiA77/7liuvvobLBg9p1HdMEASef+nlP21iazabef+/b7Nvj8/EMjY2DtHjJiIighMnTjB58mTeeuutZr3dZDIZAwYM4KOPPiInJ4c9e/YwdGjDcUAhISHI5XI8Hg+lpaUEtLDe5mxTXl7OW2+9hcViITAwkEmTJp21maBnyoABA2jXrh0pKSnkZJ/k3bfmM2nqIyiqZ2quX7uGZd8upVWreJ6Z8zzJresvHjWdb+fj53vo0CHJzLl79+7Swf2yyy5j+fLlAPz+++9cccUV5+HV+BAEgV59+tKlW3d++mEZLz73DMNHjuL6m26u15EXrJZRVVUlNS0IgtDoeMBzjVwuZ9KkScybNw+TycT8+fN55513zpkxdnPUfJ9KpbJJq58dO3aQn5+PWq1mwIABLRJ1GRkZPPzww5SVlUn2KYmJieTm5pK97Dtyc3OZOGkScnXTNVc1yASom3jo0q07nbp0bfJ1WMxmft+4gdUrV1BaUiJZ3tSIuvO5f14M3HHHHezZsweb0826n3+g76DBaHUNjydNkdimHRPuvJdP33kdBBlDWndr9H6KOt+ly25FrtIQrldz5Ogxdu/YRrDRiFavQ683oNXp0Ov1yAWB1GITbrebotxsykuKCQ4Lx1p94l9aXETOyUx2/bEFlUqN3WalvLSU0pIirhw3HqPRiN1iwutxo1Rr0ehrjylRMXFcf8NNxMVEoVBrUOubPt5oAgKxW6pwWEx43C7kzdT1bd2wlowTvok7UVFR3HLLLS3+PM8WHrcDmev0J6Ye95kL7PPNP1bYAYwePZqkpCQWL14sncVXlpXy9ecLWbL4S4ZcMZxBl11OcuvW9X16ThEkp8oTtUKGoxHVfmDfXj54/10qysuRCQIqpYIH7ruHLl26MHPmTMrLyyksLOTee+9l9uzZ9O/fv9HX7fF4yM7O5uDBg9IYovbtG7dJkclkBAcHY7VaL5ifnSiKzJ8/X+rg7NChA926Nb5QnQ8EQeDee+9l1qxZAOzY/gdHH7wftVpNVmYmbdu154EHJ9OjV61liUIm+EbtnOO066ls2LBBmnM6ZMgQ6frExERMJpNUVF9aWtqs8WuEUXdWonY1qFQqrr/x3/QbMIiP3v8vTz/5GPdOnES79h0IVsuorKzkjfnzJWubPn36nJO5wC2hV69etG3blj179kgnGbNmzbogHZpOpxOdTofB0PQ0iPbt26NWq5HL5Rw4cIDg4GDi4uKaPBn6/fffeeGFF6SofHR0NAsWLGDv3r18+OGHyESRXTv+4PHUE9zz4EN07tJ8F2HNrl4j8E59blEUSUs9wbbNm9mwfq0v5Vgt6NQKOX379uXmm2+uZ7D9v0JSUhJDhgzht99+w2yz8tuqn7jq+n+3+PGiKBIVFsqNE27h2yVLCWvdma69G2Y4ZHIFcrUWj8OGo6oCjdFnHSSvjpQWFuZjtVhqL1YLiCIKpRKFUklRQb7PJF8U0eKUnruoIJ9Na1fjdDpQqzUEh4ZhNBopzDxBVbVFilKjweWwE96qNWpjkO86mUhcjG+MZUBoRJP7tyiCzhhMZUEOIiKW8hKM4Q09YGsoLyvlx6WLqSlamDx58jkbRXk6RLcbUd5MVu8iaVQ8Hf9oYQe+BXTOnDkcPXqUxYsXs2/fPgD0Wg2//foLv678mYSkJAYMHETffv2IjKw/e/XUZVZevRqq65jBnszJ5aflP0hu7DJBQKfX8cysWfTo0QOAefPmMX36dFJTUzGZTDzxxBPccsst/Otf/yIsLExKX5WVlZGamorNZsPhcEgzc0/XhKDX6ykpKannc3c+WbRokSScg4ODmTp16gW3POjYsSOzZs1i7ty5ANjMJoqLiggPD+fl1+ZJn3ddIXc2RF2oofloSQ0mk4nNmzeTl5dHVVWV9B0XFBTw8ssvU1FRQVFREXFxcXzxxRc8/PDDf/n1NcWpEZy6xMbF8czzc1m14ieefeJR1Go1l1xyCUeOHJFOJgIDA5k8efI5e33NURM5mjJlClVVVWzfvp2vvvrqnJkjn46ysjJcLpdUJ9kYQUFBGAwGKioqsNlsZGRkUFhYSJs2baQon8fjoaSkhG+++Yavv/5a8sRr164d//nPfwgNDSUuLo6YmBheffVVrFYrRSUlvPzCHIaPGMVV115LRETTr6EpCgvy2bn9D7Zt3kz2Sd8sXq1Wi6v65zHg0kuYMGHCeTGMvZi59dZb+f3338HhZsMvK+jW51LiEpJa9Fh7ZRmCAEnJbbjh7gf4/vOPSWzbnoBGGmHUxhAcVWV47BZfPR5qEpPbkJjcBrX89GvW1t838sn77+D2itiqbbHCIiLpf/lQbrmnvgWYqayYkpwMREQEBNwuJ6IIFcX5hKg1IIqU5/uM/5UaHfrg+n6FLrsNUfSi1OgAAblShdYYhN1swmGuQgyLavS4IIoi3y76BNwOUMgZMWKEVIpyvvG67HiayTR5XQ1Hol1s/OOFXQ0dO3bkhRdeIDMzk1WrVnHixAlOnDiBUiEnL/sk3369mMVffE5ScjKX9h9A5y5diU9IQKdW4fGKkqCrwWKxcOjgAdb8+isHDxwAfIIOoGu3bjzx2PR69TXh4eH897//Zc6cOWzfvh1BEFiyZAk7duygT58+ko1BWVkZWq0WQRAICwuT0klWq7XR1DH4DG7BFyk43zVOa9as4dtva4tdH3300QuWAjuV3r17M3fuXN577z1WrVpF69at6dSpEzq1LyXQ2PfqqaNuZJxZOvZMRB3Al19+SVVVFRUVFYSGhvLqq6/y4osvMnPmTMxmM9HR0ZJlxrp16xgzZkyzXYd/JWp3qq6tK/RCtQpuveFfmEoKeOvtt5HJZNJFo9Hw2GOPnTMj4pYSEhLCtGnTeP755xFFka+++orY2FgGDx583l6D2+2WuktrfpeNYbFYEASBwMDAenWyf/zxB6GhobhcLvbv38+OHTs4efIkgiAgl8sZOHAgzzzzTL21oHfv3rz99tvMnz+fXXv3AbB2zWrWrf2Vbt17MHT4CDp17tKk2bXb5SQrK4vDBw+wY9s2TmZlSp2zNTYmbZITad++PVdeeeU5HRH4dyIiIoIbbriBr776CrPDzdJPFjD1mRdb2Jgg4rJZERQKeg4cyrHDh/nhi0+49cFHGogfdUAQ1uI8QMRWUQKBtWMGHdWF/E0JPLVajdMrIoN61lmnPofDaqE0NwuXzUpIbCJBkTF43G5KstNw2awUpR5GFARfd64gEBxTO8Pa7XJSmp2O02pGpTPg9bgJT2yPXKFEHxyBtaocu9WE3VSJtjryV5e03ZtJPbwXtUJOUFCQ5ApxIfB63JLh8unucy5JTEwkKyur3nUvv/wyTz31VIu38T8j7GpITEzkwQcfxG638/vvv/PLL7+QkuIbD6NSyMk9mcXX6enIBAGFQk5CQiLxCQmoqtMmToeDkpJS9u/b26DQWKVWcdttd3D9v8Y2emYSEBDAK6+8woIFC9i3bx/Hjx/n2LFjHDt2jJUrVzJmzBiioqJQKBT06NGDrl278vnnnwOQnp7epKN7zTzRmjq7iIimJ2ScTQ4cOCDVMAJMnDhRilBeLHTs2JEbb7yR9PR0BEGgc8cOGHUaqqz2BqIOaHCdtwkD6rqc6aQJ8M02XblypXRwj4uLo6qqiueff15Kt8XHx3PNNdewatUqRFHk3Xff5ZVXXvlLHW1ngkyAwFO8z6KioujUqRO5ubmoVCruuOMObr755nM+Nq6l9OnTh7vuuotPPvkEgPnz5xMREXHOjZJrKCkpwev1IpPJTjvnNy3N15Aik8kYOXIkFouFAwcO4HQ62bVrFytWrKCiogLwNTd06tSJ3r17c8899zR64hYREcHcuXNZ9t13fLroC5wuJ6Iosn/fXvbv24sgCHTv0ZPQ0DCUKhVejwe7w87JrExysrPrNxjViDqFnA4dOjB69GgGDRp0QVJjFzs33ngj27Zt49DxVEryc9ix9mcGjB7bgkcKyFVqPG4XLquZayfcwcJ35rF/+xbatWuH22pCFx6LQq1BrlShNgbjqCrDXlaEOzoGxSl2JRa7g6qSIgS5DINOj94YSJnDg0Ne+505q82O3V5ROnZVVlusGLValGoNSrUaQfA1XSiUKgLDoynLzQRAJlfiEV2EtUpGrfPt226ng+LMFNw123bY8XrclOVmEBbfFrXegFKtxeWwYS4vbiDs0lOO8enHH6Ku9qybOHFii+Zjnys8LgdCM128nj/RxHKmPP/889x3333S/8+0dv5/TtjVoNFoGDFiBCNGjCA/P58tW7awZcsWUlNTJWNEt9tDWlqatAjXEBQcXE/UxcXGMHr0aIYPH96sb5tCoeChhx5i8+bNvP/++1LaxmazsXjxYvr378/o0aNxu92Eh4cTHBxMeXk5hw8fbnKKg16vJzIykqKiIgoKCggPDz/nqdDc3FxefvllKf07ZswYrrrqqnP6nH+W2NhYunXrRl5eHseP+4pza8Rdc/yV+bJN4XA4ePPNN6WxUtOmTWPFihVYLBYOHjxI165dMRgMvPrqq+h0Ovbt20dBQQHHjx/nvffeY/Lkyaf9fs9Grd2pgg58kw86de4sjcgaNWpUve7zi4Vx48aRl5fHL7/8gtvt5sUXX2TevHlERUU1/+C/gCiKFBQUoFAoCA8PP63R8NGjRwGIjIzEYDBQWVmJUqlk8+bN7NixA6VSiV6vR6lUEhYWxp133tlkTW4NgiBw/fjxDLviCtasWcMPP/1MSUmx9NrS01LZt/f0HcNqhZx27doxcOBABg4ceNp0sh/fej5t2jSmTZtGlc3JquXL6N6rL3EJiZTbnARrVZTbGtY+qwxGxOI8BAEclaUExCQyYMhwvv3oHR6a/gRKmYDTakIXGo02JAJdWDROUwVKGRTnZBCV1E5aA8wVpRRlZyB6vSjVWsryczAEhaKPSURdHTV2e0VMNrtk1WVzeyRRB/j85gICqSwpwON2ExKTgCAIBIWGo1arKcvPQWcMRKE3SuPE3E4HRRkp1UJHIDAqFo/Libm0CLu5CqfVglpvQB8cRkVBNg5zFW6nwzd1Al8Tx+L330BePcLmqquuYuDAgefsu2oJXrcDb3Op2PPQPBEQEPCX1qv/WWFXl+joaMaPH8/48eMpLCxk586dpKSkkJqaSk5OToPInM1ipmOH9nTo0IE+ffrQs2fPMxZSgwYNol+/fhw4cIDvv/9eqv3bvn07l1xyiRS16dWrF+vWrWP9+vXcdtttDUyKwbegBwQEUFhYiNVqxW63n/ag8lfJzs5m9uzZ0mvs27cv99577zl7vr9Kq1atyMzMxGQyUVVVRXZ2Nq1atfpTkba/iiiKvPnmm6Sm+iY8REdHc9ddd5Gamsrq1aux2Wy43W4mTJggnSQ8/vjjPPXUU7hcLn799VcSExMZM2bMaZ8n4pSxdc0JvVPv3xSpqano9XpatWpFp+rxVhcbgiDwwAMPUFBQwL59+6iqquLZZ5/lueeek8zLzwVWqxWbzYbX68VoNDa5JjgcDqmTuFcvnwG62WympKSEnTt3SqUMvXv3Zty4cXTp0uWMorTBwcHceOONjB8/nj179rB79272HTpCemrDqSKCIBAbG0e3zh1p164dffr0OW8R/38KycnJ3HjjjXy08AsAln75GZMfm0mw1hdVa0zcyRVKtMZgrOVFuOy+2rc2yYmEhISwa+tm+g0YiCCTYS3Jw+tyoI9sRWRMLGUFuVhNlRRnZxAWm4DVVElZQa6UIvV6fGUAVVUV6GOoF2V11UnFNmZrI8hkIIqotTpARFEtcLQGI7Ftfb/1Go860eul5GSaJOpCYhPRB4ciil6cVitOm4WC1EPog8PwuJy4rBYUWh12cxWGkHBsNiuL3/V1sasVcnr06FEvQnWhEN0eRFlzzRO+YMap4x7VavVZi2q/8sorvPDCC8THxzNhwgSmTZt2RmuAX9idQmRkJNdcc430f6vVSkFBAR6PB6/XiyiKtGrVqsl6tzNBoVDQq1cvevbsyYcffshPP/2EIAisWbOGhIQEAK6++mrWrVtHZWUlmzdvbtTyBHwCITMzE6fTSUZGxjk76O7evVsq1AZfavvxxx+/YNYmLUGhUDB8+HC+//57XC4XL7zwAvPmzTvv1jCiKPLll1/6Cq7xRY1nzZqFSqUiISEBU/W0B4fDwbBhw6THtWvXjqlTpzJv3jwAPvzwQ0RR5Nprr23xc7dUuJ0Op9PJ+vXrsVgsHDt2jAcffPAvb/NcoVAoeOqpp3jsscfIyckhPz+fxx57jBkzZpyzju2MjAxpSkx0dNMdgBs3bpTmO1999dWA7yCxevVqKc16/fXXc8cdd/ylyLtMJqNPnz706eMbY2ixWMjOzkYQBGQyGXK5nJjq0WB+/ho33XQTf+w7TFZmBieOHmHpok+49V5fc4IoipLIq6Hc5kSh0SKKILqceFxOnJVlXDpwEOvWrmXULfdhK8rBZTNjryxFFEUSkpJx2m2YK8owlZdgrixF9IogCKh1BiLik6gsLqSqtAhEX7pVrak9wW/ONcFmqkKp0SHI5M2mIysLc3HZfceA4NgE9ME1HfsydEEhyJRKrBWluJ12XA47Sq2uuqnC5835w6fvkpOTjVohJzY2lieffPK8lZicDrfLAc385tzVqdhTa02fe+45Zs+e/Zdfw9SpU+nVqxchISFs3bqVGTNmkJ+fz+uvv97ibVy8R+OLBJ1OR3JyMm3btqV9e1+U7myIuroIgsAtt9yC0WhELpezf/9+jhzxzd1s27atZCfwzTffNDn2RyaTERsbiyiKlJeXn9Hw+JayYsUK5syZI4m65ORk5syZc06jg2eLCRMmkJTk61jLz8/npZdeOq/zdb1eLwsWLGDJkiWA7zt//PHHJQFvNBrrmdqeuo8NGTKE8ePHA74DxYcffshHH3103qaNiKLIG2+8IRX1JicnS5/nxYper+f555+XPmOz2cyzzz7L6tWrz/pzVVZWSjVxNXN+G8PpdErNRl26dCEhIQG3282hQ4c4fPgwcrmckJAQ/v3vf5/1cgq9Xk+HDh1o3749bdu2JTk52S/qzhIKhYLHp0zEbvOtjVs2rueXn76Xfp9itdCquQRrVRjVtWLPVl6MKHpp16Ej2oBADu/bQ3L7TqgMgchVGhxVZRSkpxAS3YqAEF+ttSCr7uxXKNFHx+NAgdliRpTJ0QaGIAiClIoFcDprS09OXTcqnW6sdituhx2PSlsvTVsXtVyGzVSJqdRnnK8LCsUQXN+E2xASQWBEDMbwaDQBQRiCw9EFhiJXqtDrtPz+0xL27d2DWiHHYDDw7LPPXtC6urq4bFU4rZWnvbhsvmNrdnY2lZWV0mXGjBlNbvepp55CEITTXo4dOwbAo48+ypAhQ+jWrRsTJ05k3rx5vP322/WaX5rjwktkP4Bv0b3lllt45513ANi8eTMjR44kMjKSm266iRdffJHs7Gy+/fZbbr755ka3ERcXR2FhIR6Ph+PHj9OnT5+zcnAwmUwsXLiw3gGxf//+PProo3+bA4NGo+GZZ57h0UcfpaKigkOHDvHGG2+ccYj7z2C323n99dfZtm2bdN0999xTbzJHVVWVtNg2Fe25/fbbUSgUfP311wAsX76crKwsJk+efM5rob7++ms2b/bNxdRoNEybNu2CW9q0hPDwcF577TVee+01du7cicfj4Z133iEjI4PbbrvtrJykeb1ejh07hkwmQ61WE3Oa6SVfffUV+fn5ANI83eLiYimKWzNo/u/yu/JTS3x8PDOmP8LzL78KwPKlX6FWaxgyYnSD+4qiiCAT0Ov12F1uHFXlAGiMIXTr258TRw8y8ophJLVpT1l+NpUlhditZvLTjxOV1BZjSDh2mxnR40FuDEOmUGAtL8Fls/g85KrFX92IXd3RZ42dECq1Blw2C4LNF00utbsI1SilvwG8bheV+Tl4kKFWKQmOjm/0s1CqtQRFNeye3rNlA8uX/4hS7uvynjFjxml/L+cLlUpFVFQUe7//vxbdPyoqirCwsBb/TqdPn15vFF1jNOV4cOmll+J2u8nMzGzSz/ZU/BG7i4hRo0YRHh6OUqnkyJEj0qipSy+9VCoqXbp0KSdPnmz08QqFgjZt2uByubBarZID/p+lJrpw33331RN1N9xwAzNmzPjbHXzCw8N5+umnpTrFTZs28eKLL0ppsXPBvn37eOihhyRRJ5fLefTRRxk7tn7nnLXOHMfG6iihNrI7ZcoUKfVds/0ffvjhnPkYrl69msWLF0uv4fHHHycxMfGcPNe5QKvV8vTTT9f7zH/++Wfuu+8+fvjhh79s7F1aWordbsflctGmTZsm7YbS09OlWbZDhw6lZ8+eiKLI8ePHOX78uJTCbarcws/Fz9ChQ3no/nuk/y/9/FO2blzf6H2tLi82qxXBZcfr9u2DqoAgWiW1piQ7E/BlYkJj4gmN9okkl8NO7omjeD1ugsKiCI6MRVZ9YuqsTo0qNVppnJdCoUAhr77dUWc/b6LGTvS6wVtr8lRqd0mizuNyUZmdhtthBQGi4pORNbGvN3bOt3fHVr789EPA16QzceLEC2pkXxeNRkNGRka9CNzpLhkZGWd0/AsPD6dDhw6nvahUjY9527dvHzKZ7IxqX/3C7iJCLpdz2WWXoVar8Xg8bN26VXL1f+CBB9Dr9bjdbl544QXKy8sb3UZISIhUwFnz2DPF4/GwZs0a7r//fhYuXCgJH5VKxbRp07j99tv/FtGaxmjfvj1PPvkkSqUSuVxORkYG06dPJz09/aw+T0lJCW+99RbPPPMMRUVFgG/xmD17doMDd83BHZDC8qdj5MiRzJkzR/I/czgcfPzxx0yaNImVK1eeUcj+dNjtdt555x0pigxw1113XZAZwH8VmUzGvffey+TJk6UIrclk4uOPP2bixImsX78er/fPDZGr+Z1ptdomJ2+UlJTwwgsvSI0VNc1GFRUVbNu2zVcPpVYzZMiQi7pe1U/zjB8/nivHXif9/8tPPmDXti317mN2eiT143K6UKk1KFVqjMYgurRrS2F+nhRVEwSBoIhoIhPaIMhkeD1uSnKzKCvMxXRKylSuVCNX1S/gr0nHOh026brGInY+82OQnTL6SxS92MpLKM846hN1gC40Co0+AJXgszhx2qy+KKRQK+pq/hYE2L99M18seAfR68WgVjBmzBhGj24YybyQaDQajEZjiy7nKqixbds25s+fz/79+0lPT+fLL79k2rRp3HrrrWdkKeVfQS4yhgwZgkqlQqfTsW3bNjIzMwFfp9uUKVMQBIGCggJmz55dL8pTQ02HrE6nO+MITm5uLl988QX3338/b731FqWlpdI2R4wYwYIFC+oV9f9dufTSS3nxxRfp0KEDZWVl5Obm8sgjjzB//nzpPf9ZcnNzeeutt7jvvvtYs2aNdH23bt14++23G/X5q5k6oFQqMRgMpKWlNfrd1qVHjx7897//5eqrr5aEYF5eHu+99x6333477733nlSneSaIokhaWhoLFy7kvvvuY+XKlVL9y7hx4xg3btwZbe9iY9SoUSxYsIChQ4dKn1txcTFvvPEGDzzwAIsXL5ZSpS3F6/Wi1WoJCAhoVJSbTCaeffZZSkpKEASBqVOnSp2vGRkZ/PHHH+h0OpRKZb2xcn7+vjw+6V6GjfY1xoiiyKfvv83Gdb/Wu09Ng4LH7cLtsKHU6hBkMsyijPikZCos9e2YDEEhxLbpiEqrw+N2UV6QS0VuhiTSZHI5HpcDt8OG21UbnVNrtMhkAm5XrQh02Otv2+Ny4Xb4rlPUSd963S4qsk5gLjiJIJMhIGCIbIUuNJK8khIyDu+hNCeDwrQj5Kccoqo439ehW4fdWzay6IN3EUURg1rByJEjL4oO2IsRtVrN119/zeDBg+ncuTNz585l2rRpfPDBB2e0HUE8X9XXflqEKIp89NFHfPPNN5jNZq666iqmTJkiWV+sWLGCBQsWANCpUydmzpzZwDsvJSWF/Px8jEYjPXv2bPR5LBYL6enppKamkpqayrFjxygoKGgQLbjkkku4/fbbpQL0fxIFBQXMnTtXEs/gi0rWpL579+7d7JmZKIrk5OSwdetWli1bhtlsrvcZajQa7r77bkaPHt3oQd/tdvPUU09x/PhxsrKy0Gg0REZGMnXqVEaMGNGi93Hs2DE+//xzDhw4QEVFBenp6URERBAXF4fBYKBHjx4kJSURExNDTEwMQUFB0sHA4/GQl5dHdnY2OTk57N27t4Gw6d27N717927WYuXvRkZGBgsXLmT37t31rhdFkejoaDp06ECbNm1o3bo1ycnJTU5u2L17N2azmbi4OFq3bl3vtrKyMubOnSuZoE+ZMoWRI0cCUF5ezptvvsmvv/6K0Wjkpptu4q677joH79TPhaDGVPzb5Suk60ZcfS3Dx92EIAh43C4Kj+/HYTWjVGsJSWiDLrDpedABal+k2e1yUnQyHZu5Co8oog0KJSgmEY/LQVlWKm6nHX1oJIHVNW7/mfUYBXk5yORK32QFr5eY+EQefu4ladu28hJMBSeRq9QExbdFrvSlBSuz03BafBFpdUAwurBoFGrfmmg7eRyn3YZcocTtcuJ2u5DJFUQktUdjMKKWy/jt11VsWvcrhfl5ANz4r2uZOHHi3zbj83fBL+wuQo4dO8bjjz9OeXk5crmcmTNnMmLECEkwfPHFF1J3ZUhICE899VQ9Z/309HSys7PR6XT07du33rb37dvHokWLpPq9usTGxpKbm4sgCPTo0YObbrqJzp07n8N3euFxu938/PPPfPXVVw1q7VQqlTSLMzo6WkqRezweysvLOXnyJNnZ2VitVqxWK4cOHUKlUhETE0NCQgLXXnstY8aMadK02mQy8f7777Np0ybp+axWKwqFAr1ezyuvvNLiWjaXy8Vrr73GF198QVlZGQqFgu7du/+ltJ5MJmPAgAFMmDDhHz1G6sCBAyxdupQDBw4giiJxcXHk5OQ0uF/79u25/fbbG9QF/fHHHzgcDhITE+udAB04cIDXXntN6pa97bbbpIYJj8fDqlWr+M9//oMoioSEhPDGG280EIZ+/t6Iosh/3l7A6hXLpeu69unHzfc8iEKppCIvE4fFhEqrJzA6oUHNmsftwuNyIleqCNJr62236GQaleW+DENgTAL64HDf6C/Riz4kAkOor6Fq/gvPkJV+Aq9XxBgcQlV5GfoAI8/Of1/anik/C3tlKQqNnuDE2gL98szjeJ0OFHoDxpikeoLMnHEEj8uJRm9ErpBTXpiHPjiMmOR2yGRyfvpuKb/8uMz3m4pPZEj/Ptxzzz1+UXce8HfFXoR06NCBa665hmXLlmEymViyZAnt2rWT7CVuueUWNBoNixYtoqysjKeeeoqbb76ZsWPHotVqJRuPut2excXFvPXWW5IR8qkolUq6devGqFGjGDx48AWf+3m+UCgUjB07lmHDhrFkyRLWr18v+ck5nU7S09NbVH9X8xiFQoHH48FgMOD1etm1axdxcXFER0fjcrkwmUwUFhaSmprKTz/9JIlJpVLJf/7zHxYvXszOnTuxWCzMnj2b++67j379+jVZkG82m9m+fTvLly8nIyOD1q1bEx8fT1RUFMnJyRw+fLjZtG5dBEGga9euXHbZZfTv37/ZSSr/BLp160a3bt0oKSlh48aN5OXlUVBQ0MAO5/jx48yaNYvevXszZcoUQkN90RWlUonD4ZCsiKxWK99//z1LliyRpovcdddd9XwHMzIyWLp0KR6PB6PRyLhx4/yi7h+IIAg8NXUiwaFhLFn0CS6Pl707tlFVWcFdkx/FEOazBNEEBDV4rMftouzkCVx2X21cZUAQMa0Sq8d+CUS0SsZis4FXxGGuQq03IooibqezXjo0wBhIcGgYCDLik9uSnZlOZXkpVosZnd5XZiHIZMgVahC91bVyPvElej14vW68jdTtqjRaLA4bNnMlgiCg0mh987U9Xr5e+AlbNqyTPoPRQwdxyy23+EXdecIfsbtIsdlsPPjgg2RmZuLxeLjnnnu47rrrpNocgEOHDvHqq69KjRQBAQFce+21JCcnY7PZpO7KQ4cO8eOPP9b7UbVq1YquXbtKqab4+PiLwiDyQlPjKbZlyxb2799PYWHhaYvqIyIiJCGVkZHB4cOHm32OkJAQUlJS8Hq9REREoFarmTx5MkOGDMFutzNz5sx6EdWwsDAGDRpEUFAQgiDg9XopLCwkNzeXo0eP1hMgSqWSe+65h6uuugpBEHC73Zw8eZK8vDzpUuOXB75FNzw8nFatWhEXF0d8fPxF4yl1IamxF6gpVzhw4AC5ubn17jNu3Dg6deqE1+vF7Xaj0+lISUmpJ9hDQ0N58skn60XUKysr+eabb1i0aBFyuZzk5GTeffdd/yzWfzg7duxgxuwXpS7skLBwbn/wYeKTGhf0NdE8l92KTC5HodLgcbsICY/EEBSKW6mhPDcTW0UJcpUGY1Qc5TkZPtHXphNyhS+d+t5rc0k5chCvV+SSy4eyY5Nv6sl902fSplMXAEx5mdirfC4KgkyOSheAXK1BplBiLswGQG0MxRARQ6hWjdNupyDzOE67HY/bhdZgQKXWoQkK49P33yYt5bj0Ph6dMukfV8ZxseMXdhcxa9eu5Y033qCyspKEhASeffbZBj425eXlvP/++2zdulW6riZCY7PZCA0NRRRFPB4PCoVCmjt5+eWX+8+eWoDb7aaoqIj8/HxpuLtCoUCn09GqVasGNXjHjx9n0aJFHDhwoMlt2u12Dhw4gFwu54knnuD222+vFyGtrKzkmWeeISMjA6h1jBdFEaVS2WR6tVWrVjz++OMXvXHw3xGv18uGDRtYuHChNN9ZoVAgCAIlJSXodDoEQZDMugVBYNCgQTzwwAMNop5Hjx5l9uzZ5ObmEhgYyJNPPsnll19+Id6Wn/PMiRMnmPrELMwmn8mtXKFgzA0TuGx4wxrc4vSjuOxWqS4ORBRKFeC7n0yhwOt2IwigMQYjCDKsFSUo1Boi23aVtlNX2I295U6Wf/kZAEOvHsfo63ylAV63m6q8DFxWU/WjBEAEhOpxZSBXqlB4fc1YcqUSj8uF1VSJXKEkKDwKh1fGB++8QUWZLz0cbNDyyCOP+PftC4Bf2F3EeL1epkyZwvHjx7Fardx6663cdtttjY7CysrKYunSpfz+++8cOnSIiooK2rRpIxnX9u3bl1atWnHttddKKSQ/546CggJycnLIzc0lJyeHgoICNBoNAQEBUrezwWDg3XfflSaL1EUURfbv38+KFSv46KOPsNlsqFSqBl21YWFhDBw4kEGDBtG+fXu/WD/HFBUVsWrVKtLS0ti7dy/gm2SSnp5OcHAwnTt3ZsiQIdxwww2N1iVWVlby2WefsWTJEvR6PZ07d+aNN97wf2//QxQXF/PEs8+TWicq36VnH/599wNSahTAZbdSmuVruvF6PIheDwgyZHKFL0XqdiPIfZ2qke26YirJx1ZRikpvJCyxnbSd1555gryckygUSpYtXsSYG25GFEVCIyJ5/KXXa9OuoheXxYTbYcdtt+I0VyKKXuRKNSqZgMd1it+jIOCwWtEZA8nIymbZ0q+k7EFCTCSzZs1qdG3zc+7xC7uLnJ07dzJnzhwqKysJCwtjxowZ9O3bt8kDQUZGBldffTWVlZV07NiR66+/nh49ekgF/X4uPD/99JPUvt6S7tc77riDzMxM1Go1M2fORKFQEBERQXR0NAaDwS8KLgCZmZnk5eWxd+9evvvuO44fP05ISAgrV65sstFEFEW2b9/OSy+9RHl5OYGBgbz44ouNWuD4+WfjdrtZtGgRny5eKl0XHBrGLfc9RHK7DtJ1oteLy27DUlaIraocmUJJQFg0dnMFlrLi6nSriD4kHGQynOZKlBodIfFtpG08PfleLBYz7RPi+Oijj7j9oUdJO+YrGZnyzIvEJTY+8cDrdmEqyMZhqkAtlxESHY9Krcbr9aJQqrBUlZGXkcbaX1dzLOUE8upSnr49ujJjxowz8l3zc3bxF1Vd5PTp04cuXbqwe/duCgsL+eGHH2jXrl2TRqjl5eUEBQURFBTEkCFDLupB7f+r1K2TtJ/iJ9UYCoUCo9FIcHCw3+fsIiExMZHExEQGDBhAYWGh9D1WVlY2KezKy8v5/vvvKSkpwWAw0LNnT7+o+x9FoVBw9913Y4hJ4uP3/ovVYqa8tIR3XplD/8FXcM0NN6PV6RFkMlQ6PUptEqIoYjdVUJZ9AoVah1KtxWW3IFdpsFaUAiKiCDJF7QQDl9OJxWIGkMo9ul/STxJ2+3f+0aSwkymUGGMTsWUdRwSqygoJi0lEJhcoL8pj26bfWLdmDVabFY3OF2kcP/YaHnjgAX+99gXG/+lf5AiCwIMPPsjDDz+Mw+Fg5cqVpKamEhcXh1arRSaTSV1MDoeD/fv3Y7Va0el0dO/e/UK/fD+NUNOc4HA42LhxI6GhocjlcslKpe6lrKyMffv2ERMT418sL1K6devG2rVrsVgsPPHEE3Tu3BmNRiN1xLpcLux2OydPnuTEiRMEBgYSEBDAxIkTL/RL93OBuXH0UIb16cqTz71ASvX0mW0b15GWcpRBw0bRb/AwqZbTEBaF3VSBXKlB9HrQGAKJaNOZqqJcbJVluOx2n8dcnSRcZloKiKD0OklLS+P+++9HrVZz4shBdPoA1v20jKFXXouuiYapMK0aS3Q8hVknsJmrsFVVUlxSyrq1v5KeloZcoSA0yLc/33PPPS323vRzbvEfKf4GJCQkcPPNN/Pxxx8TFBRETk4O+fn5eDweZDKZVNTv9Xrxer0EBQXh8Xho165d8xv3c96pGXotiiK7d++Wxok1Rk1HrsFgID6+8YHbfi4s7du3Ry6XExISQllZGVu2bGnwu6wR7vHx8TgcDm699VZiY2Mv9Ev3cxEQFhbGh2+/wftffMN3SxYTEhpOQV4Oy778lI2//syAIcPpO3AwBqMRY2QccoUKl8NKQFg0gkxGUEwiMrkCc2khgiCg1PqMtEVRZMU3X5Gecgy3w0br1q1xOp1ERkai1empqijDXFXJ6889SZ+Bg+k35AqCQmrrr0M1PlcFnTGQwMg49uz+gV3b/yC/oECyN1EoVQwZMoR7773Xn3q9iPDX2P1N8Hq9/Prrrxw6dIhffvkF8EV8ZDKZNF9UFEVEUWT8+PEYDAZuu+02f5TnIsTj8fDaa68RFRXFd99916LHzJ8/n8DAQGk+rJ+LB5fLxaJFizCZTHz//fcNfo9er1eyMhkzZgzt27dn1KhR/tpIPw0oKSnhtfc/Y+uGtfWulysUdOnZh/6XD6Ntpy4N9h1RFLGUFmIqziM0sR0nUo7z6/JlZKQeJ+XIIVRyGT179kSr1RIfH09KSgopGVmEhEcSGhFJZVkpMpmMqLh4olvFExufSESQkZLCQrIy00lLOYbVbPZlh2QCgiCjdXwskyZNonfv3ufzI/LTAvzC7m+GKIqYTCaqqqqkg0ZNVEej0aBWqwkICJA87PxcvGRnZ3Pw4EGsVquUtpPL5chkMulfo9FIeHg4CQkJqFSq5jfq54LhdDoxm804HA6p5k4mk0mXgICAJufJ+vFTl5SUFN547yMOHWxomxQcGkaHLt2JT25DdFwrtDodAgK5JzNJOXyA1OPHKC7yjQVUKBRo8KDRaHjwwQe57LLLJBP7Y8eOsXHjRr76YUWD+a4AKrmM0PAISouLpOsMagXJyclcddVVDBkyxO+9eJHiF3Z+/Pjx48fPRcjGfcdZv24tOzZvlLzvagiLiKSkqLDhg+qcN/Tq1J5bb72VPn36NHlCUVZWxpuff8PBXTsoys+lriSIjoqitLiI6LBgLr30Uq666iratGnjPzm5yPELOz9+/Pjx4+cixu12s337dlavXs3+/fvxer3Ex8dz8uRJACpsLum+giDQr2dXbrjhhtMKusZwOp3SxBWHwyHNyo6KivKLub8RfmHnx48fP378/E2w2+2kpKSQk5NDRkaGNKc4KiqKzp0707FjR/R6/YV+mX4uIH5h58ePHz9+/Pjx8w+h8aGTfvz48ePHjx8/fv52+IWdHz9+/Pjx48fPPwS/sPPjx48fP378+PmH4Bd2fvz48ePHjx8//xD8ws6PHz9+/Pjx4+cfgl/Y+fHjx48fP378/EPwCzs/fvz48ePHj59/CH5h58ePHz9+/Pjx8w/BL+z8+PHjx48fP37+IfiFnR8/fvz48ePHzz8Ev7Dz48ePHz9+/Pj5h/D/J/QISEKt52IAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 720x180 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 720x180 with 6 Axes>, [<Axes: >])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the pain map\n",
    "nsp.plot_brain(data=\"Y\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "23923ec7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:03:07.182148Z",
     "iopub.status.busy": "2026-06-01T13:03:07.182045Z",
     "iopub.status.idle": "2026-06-01T13:03:10.583469Z",
     "shell.execute_reply": "2026-06-01T13:03:10.583141Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:07 | nispace.api: *** NiSpace.plot_brain() ***\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:07 | nispace.api: Plotting X data (X_reduction='False').\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:07 | nispace.api: Returning X dataframe: \n",
      "| X_REDUCTION | \n",
      "| False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mWARNING | 01/06/26 15:03:07 | nispace.plotting: Brain plotting in NiSpace is experimental. If things look off, feel free to raise a GitHub issue!\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:07 | nispace.plotting: brainplot: threshold='auto' → 0.019260043278336525\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:07 | nispace.plotting: brainplot: kind='glass', img_mode='None', surf_space='None', mni_space='MNI152NLin2009cAsym', surf_mesh='inflated'\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x180 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<Figure size 720x180 with 6 Axes>, [<Axes: >])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the VAChT receptor map (strongest colocalization)\n",
    "nsp.plot_brain(data=\"X\", maps=\"VAChT\", symmetric_cmap=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "912a9272",
   "metadata": {},
   "source": [
    "## Saving and loading\n",
    "\n",
    "Analyses with 10,000 permutations take time. We can serialize the entire NiSpace object — including the null distributions — to disk with `to_pickle()`, and load it back with `from_pickle()`.\n",
    "\n",
    "We recommend the `.pkl.blosc` format: Blosc compression keeps file sizes manageable without the speed penalty of gzip."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e73a6edf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:03:10.584897Z",
     "iopub.status.busy": "2026-06-01T13:03:10.584780Z",
     "iopub.status.idle": "2026-06-01T13:03:10.810891Z",
     "shell.execute_reply": "2026-06-01T13:03:10.810575Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With nulls:    29.9 MB\n",
      "Without nulls: 7.4 MB\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "# save, including the null distributions\n",
    "nsp.to_pickle(\"nsp_pain.pkl.blosc\")\n",
    "print(f\"With nulls:    {os.path.getsize('nsp_pain.pkl.blosc') / 1e6:.1f} MB\")\n",
    "\n",
    "# save without nulls — much smaller, but you lose the shading in plots\n",
    "nsp.to_pickle(\"nsp_pain_no_nulls.pkl.blosc\", save_nulls=False)\n",
    "print(f\"Without nulls: {os.path.getsize('nsp_pain_no_nulls.pkl.blosc') / 1e6:.1f} MB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "117d5c52",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-01T13:03:10.812364Z",
     "iopub.status.busy": "2026-06-01T13:03:10.812228Z",
     "iopub.status.idle": "2026-06-01T13:03:10.876930Z",
     "shell.execute_reply": "2026-06-01T13:03:10.876560Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:10 | nispace.api: Returning colocalizations: \n",
      "| METHOD   | XSEA  | X_REDUCTION | Y_TRANSFORM | \n",
      "| spearman | False | False       | False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO | 01/06/26 15:03:10 | nispace.api: Returning colocalizations: \n",
      "| METHOD   | XSEA  | X_REDUCTION | Y_TRANSFORM | \n",
      "| spearman | False | False       | False       | \u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded successfully — results are identical.\n"
     ]
    }
   ],
   "source": [
    "# load it back\n",
    "nsp_loaded = NiSpace.from_pickle(\"nsp_pain.pkl.blosc\")\n",
    "\n",
    "import numpy as np\n",
    "assert np.allclose(\n",
    "    nsp.get_colocalizations().values,\n",
    "    nsp_loaded.get_colocalizations().values\n",
    ")\n",
    "print(\"Loaded successfully — results are identical.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "593f60b9",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "The complete NiSpace workflow in six lines:\n",
    "\n",
    "```python\n",
    "nsp = NiSpace(x=reference_maps, y=input_map, parcellation=\"Schaefer200\")\n",
    "nsp.fit()                                          # parcellate + ingest\n",
    "nsp.colocalize(\"spearman\")                         # compute correlations\n",
    "nsp.permute(\"maps\", n_perm=10000, p_tails=\"upper\") # permutation p-values\n",
    "nsp.correct_p(mc_method=...)                       # multiple comparisons correction\n",
    "nsp.plot()                                         # visualize\n",
    "```\n",
    "\n",
    "The next notebook covers [what datasets and parcellations are available, and how to bring in your own data](intro03_fetching_datasets.ipynb)."
   ]
  }
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