{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Measuring Synaptic Connection Probability\n", "\n", "In this notebook we use the [Allen Institute synaptic physiology dataset](https://portal.brain-map.org/explore/connectivity/synaptic-physiology) to measure synaptic connection probability and its relationship to cell subclass and intersomatic distance.\n", "\n", "For an introduction to the Jupyter Notebook interface interface, try [Codeacademy: How To Use Jupyter Notebooks]( https://www.codecademy.com/articles/how-to-use-jupyter-notebooks) or [Jupyter Notebook Quick Start Guide](https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/what_is_jupyter.html).\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from aisynphys.database import SynphysDatabase\n", "from aisynphys.cell_class import CellClass, classify_cells, classify_pairs\n", "from aisynphys.connectivity import measure_connectivity, pair_was_probed" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1. Load the data\n", "\n", "First, load up the \"small\" database from release 1.0 and query all cell `pairs` for mouse projects." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "loaded 82818 cell pairs\n" ] } ], "source": [ "# Download and cache the sqlite file for the requested database\n", "# (for available versions, see SynphysDatabase.list_versions)\n", "db = SynphysDatabase.load_current('small')\n", "\n", "# Load all cell pairs associated with mouse V1 projects\n", "mouse_pairs = db.pair_query(project_name=[\"mouse V1 coarse matrix\", \"mouse V1 pre-production\"]).all()\n", "\n", "print(\"loaded %d cell pairs\" % len(mouse_pairs))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A single cell `pair` represents a _possible_ connection from one cell to another:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cell pair: \n", " presynaptic subclass: unknown\n", " postsynaptic subclass: unknown\n", " synaptic connection: no\n" ] } ], "source": [ "# print some information about the last cell pair returned\n", "pair = mouse_pairs[-1]\n", "print(\"Cell pair:\", pair)\n", "print(\" presynaptic subclass:\", pair.pre_cell.cre_type)\n", "print(\" postsynaptic subclass:\", pair.post_cell.cre_type)\n", "print(\" synaptic connection:\", \"yes\" if pair.has_synapse else \"no\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2. Define cell _classes_\n", "\n", "We want to group together all cell pairs based on their pre- and postsynaptic cell classes. However, there are many different ways to classify cells so we must first define the criteria for all cell classes that we want to compare:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "cell_class_criteria = {\n", " 'l23pyr': {'dendrite_type': 'spiny', 'cortical_layer': '2/3'},\n", " 'l23pv': {'cre_type': 'pvalb', 'cortical_layer': '2/3'},\n", " 'l23sst': {'cre_type': 'sst', 'cortical_layer': '2/3'},\n", " 'l23vip': {'cre_type': 'vip', 'cortical_layer': '2/3'},\n", " 'l4pyr': {'cre_type': ('nr5a1', 'rorb'), 'cortical_layer': '4'},\n", " 'l4pv': {'cre_type': 'pvalb', 'cortical_layer': '4'},\n", " 'l4sst': {'cre_type': 'sst', 'cortical_layer': '4'},\n", " 'l4vip': {'cre_type': 'vip', 'cortical_layer': '4'},\n", " 'l5et': {'cre_type': ('sim1', 'fam84b'), 'cortical_layer': '5'},\n", " 'l5it': {'cre_type': 'tlx3', 'cortical_layer': '5'}, \n", " 'l5pv': {'cre_type': 'pvalb', 'cortical_layer': '5'},\n", " 'l5sst': {'cre_type': 'sst', 'cortical_layer': '5'},\n", " 'l5vip': {'cre_type': 'vip', 'cortical_layer': '5'},\n", " 'l6pyr': {'cre_type': 'ntsr1', 'cortical_layer': ('6a','6b')},\n", " 'l6pv': {'cre_type': 'pvalb', 'cortical_layer': ('6a','6b')},\n", " 'l6sst': {'cre_type': 'sst', 'cortical_layer': ('6a','6b')},\n", " 'l6vip': {'cre_type': 'vip', 'cortical_layer': ('6a','6b')},\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create a `CellClass` object to represent each cell class described above:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "cell_classes = {name:CellClass(name=name, **criteria) for name,criteria in cell_class_criteria.items()}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3. Measure connection probability between classes" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/luke/docs/aisynphys/aisynphys/connectivity.py:356: RuntimeWarning: Mean of empty slice.\n", " mean_cp = np.exp(-x_probed**2 / (2 * sigma**2)).mean()\n", "/home/luke/miniconda3/envs/py3/lib/python3.8/site-packages/numpy/core/_methods.py:161: RuntimeWarning: invalid value encountered in double_scalars\n", " ret = ret.dtype.type(ret / rcount)\n", "/home/luke/docs/aisynphys/aisynphys/connectivity.py:362: RuntimeWarning: invalid value encountered in long_scalars\n", " est_pmax = (n_conn / n_test) / mean_cp\n" ] } ], "source": [ "# Group all cells by selected classes\n", "cell_groups = classify_cells(cell_classes.values(), pairs=mouse_pairs)\n", "\n", "# Group pairs into (pre_class, post_class) groups\n", "pair_groups = classify_pairs(mouse_pairs, cell_groups)\n", "\n", "# analyze matrix elements\n", "results = measure_connectivity(pair_groups, sigma=100e-6, dist_measure='lateral_distance')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "At this point we have all data loaded and connection probabilities have been computed. For each combination of (presynaptic_class, postsynaptic_class), we have a result dictionary that includes the number of putative connections probed, the number of synapses found, and the connection probability with 95% confidence intervals." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**The results for a single connection type look like:**" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Connectivity results for l23sst => l23vip\n", " 12 synapses found out of 32 probed\n", " 37.50% connection probability\n", " 95% confidence interval: 21.10%-56.31%\n", " 49.12% distance-adjusted connection probability\n", " 95% confidence interval: 27.64%-73.75%\n" ] } ], "source": [ "# pick two arbitrary cell classes to display results from\n", "pre_class = cell_classes['l23sst']\n", "post_class = cell_classes['l23vip']\n", "\n", "print(\"Connectivity results for %s => %s\" % (pre_class, post_class))\n", "print(\" %d synapses found out of %d probed\" % (\n", " results[pre_class, post_class]['n_connected'],\n", " results[pre_class, post_class]['n_probed'],\n", "))\n", "print(\" %0.2f%% connection probability\" % (\n", " results[pre_class, post_class]['connection_probability'][0] * 100,\n", "))\n", "print(\" 95%% confidence interval: %0.2f%%-%0.2f%%\" % (\n", " results[pre_class, post_class]['connection_probability'][1] * 100,\n", " results[pre_class, post_class]['connection_probability'][2] * 100,\n", "))\n", "print(\" %0.2f%% distance-adjusted connection probability\" % (\n", " results[pre_class, post_class]['adjusted_connectivity'][0] * 100,\n", "))\n", "print(\" 95%% confidence interval: %0.2f%%-%0.2f%%\" % (\n", " results[pre_class, post_class]['adjusted_connectivity'][1] * 100,\n", " results[pre_class, post_class]['adjusted_connectivity'][2] * 100,\n", "))\n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 4. Display conectivity heat map\n", "\n", "Now we want to take the entire set of results computed above (for all connection types) and display a heat map where the color represents the probability of connection. \n", "\n", "To do this, we must first transform the results into 2D arrays of colors and labels, and then construct the heat map with a few calls to matplotlib. The function defined below " ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "scrolled": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/luke/miniconda3/envs/py3/lib/python3.8/site-packages/matplotlib/colors.py:1169: RuntimeWarning: invalid value encountered in less_equal\n", " mask = (resdat <= 0)\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.colors, matplotlib.cm\n", "import matplotlib.pyplot as plt\n", "from aisynphys.ui.notebook import show_connectivity_matrix\n", "%matplotlib inline\n", "\n", "# define a colormap and log normalization used to color the heatmap\n", "norm = matplotlib.colors.LogNorm(vmin=0.01, vmax=1.0, clip=True)\n", "cmap = matplotlib.cm.get_cmap('plasma')\n", "\n", "# define the display labels to use for each cell subclass:\n", "class_labels = {\n", " 'l23pyr': 'L2/3 Pyr\\nspiny',\n", " 'l23pv': 'L2/3 Pv',\n", " 'l23sst': 'L2/3 Sst',\n", " 'l23vip': 'L2/3 Vip',\n", " 'l4pyr': 'L4 Pyr\\n nr5a1',\n", " 'l4pv': 'L4 Pv',\n", " 'l4sst': 'L4 Sst',\n", " 'l4vip': 'L4 Vip',\n", " 'l5et': 'L5 Pyr ET\\nsim1, fam84b',\n", " 'l5it': 'L5 Pyr IT\\ntlx3',\n", " 'l5pv': 'L5 Pv',\n", " 'l5sst': 'L5 Sst',\n", " 'l5vip': 'L5 Vip',\n", " 'l6pyr': 'L6 Pyr\\nntsr1',\n", " 'l6pv': 'L6 Pv',\n", " 'l6sst': 'L6 Sst',\n", " 'l6vip': 'L6 Vip',\n", "}\n", "\n", "# create a figure/axes to draw on\n", "fig, ax = plt.subplots(figsize=(15, 15))\n", "\n", "# finally, draw the colormap using the provided function:\n", "im, cbar, labels = show_connectivity_matrix(\n", " ax=ax, \n", " results=results, \n", " pre_cell_classes=cell_classes.values(), \n", " post_cell_classes=cell_classes.values(), \n", " class_labels=class_labels, \n", " cmap=cmap, \n", " norm=norm,\n", " distance_adjusted=True\n", ")" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Connectivity results for l5vip => l23vip\n", " 0 synapses found out of 23 probed\n", " 0.00% connection probability\n", " 95% confidence interval: 0.00%-14.82%\n", " 0.00% distance-adjusted connection probability\n", " 95% confidence interval: 0.00%-24.64%\n", "0.0002956412760061835\n" ] } ], "source": [ "# pick two arbitrary cell classes to display results from\n", "pre_class = cell_classes['l5vip']\n", "post_class = cell_classes['l23vip']\n", "#post_class = cell_classes['l4pyr']\n", "\n", "print(\"Connectivity results for %s => %s\" % (pre_class, post_class))\n", "print(\" %d synapses found out of %d probed\" % (\n", " results[pre_class, post_class]['n_connected'],\n", " results[pre_class, post_class]['n_probed'],\n", "))\n", "print(\" %0.2f%% connection probability\" % (\n", " results[pre_class, post_class]['connection_probability'][0] * 100,\n", "))\n", "print(\" 95%% confidence interval: %0.2f%%-%0.2f%%\" % (\n", " results[pre_class, post_class]['connection_probability'][1] * 100,\n", " results[pre_class, post_class]['connection_probability'][2] * 100,\n", "))\n", "print(\" %0.2f%% distance-adjusted connection probability\" % (\n", " results[pre_class, post_class]['adjusted_connectivity'][0] * 100,\n", "))\n", "print(\" 95%% confidence interval: %0.2f%%-%0.2f%%\" % (\n", " results[pre_class, post_class]['adjusted_connectivity'][1] * 100,\n", " results[pre_class, post_class]['adjusted_connectivity'][2] * 100,\n", "))\n", "d = [p.distance for p in results[pre_class, post_class]['probed_pairs']]\n", "print(np.mean(d))" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# optionally we can save the figure at this point\n", "fig.savefig('mouse_connectivity_matrix.svg', format='svg')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It's important to remember that the measurements of connection probability shown above come with confidence intervals -- for example, L2/3 Sst cells were interconnected 4 times out of 112 probed (3.6%), but there is a range of possible connection rates that are statistically compatible with our results:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.008716160791083906 0.07928800565262084\n" ] } ], "source": [ "l23sst = cell_classes['l23sst']\n", "cp, ci_low, ci_high = results[l23sst, l23sst]['connection_probability']\n", "print(ci_low, ci_high)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The 95% confidence intervals above suggest that the probability of connection between L2/3 Sst cells is likely to be in the range 1-9%. Keep this statistical uncertainty in mind when interpreting the results above, and use appropriate tests when making comparisons between groups." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Connectivity in the human dataset\n", "\n", "The synaptic physiology dataset also contains recordings from human brain tissue. However, this tissue lacks the transgenic markers that we used to define mouse cell classes above. Instead, we will rely entirely on cortical layer and dendritic morphology (specifically, the presence of dense spines associated with excitatory cells) to separate classes. \n", "\n", "In the example below we filter only for cells with spiny dendrites, although the dataset also contains a smaller number of inhibitory interneurons as well as pyramidal cells for which no biocytin fill was available to judge the dendrite type." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "loaded 10400 cell pairs\n" ] } ], "source": [ "# Load all cell pairs associated with mouse V1 projects\n", "human_pairs = db.pair_query(project_name=[\"human coarse matrix\"]).all()\n", "\n", "print(\"loaded %d cell pairs\" % len(human_pairs))" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "cell_class_criteria = {\n", " 'l2pyr': {'dendrite_type': 'spiny', 'cortical_layer': '2'},\n", " 'l3pyr': {'dendrite_type': 'spiny', 'cortical_layer': '3'},\n", " 'l4pyr': {'dendrite_type': 'spiny', 'cortical_layer': '4'},\n", " 'l5pyr': {'dendrite_type': 'spiny', 'cortical_layer': '5'},\n", "}" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "cell_classes = {name:CellClass(name=name, **criteria) for name,criteria in cell_class_criteria.items()}" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "# Group all cells by selected classes\n", "cell_groups = classify_cells(cell_classes.values(), pairs=human_pairs)\n", "\n", "# Group pairs into (pre_class, post_class) groups\n", "pair_groups = classify_pairs(human_pairs, cell_groups)\n", "\n", "# analyze matrix elements\n", "results = measure_connectivity(pair_groups)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "class_labels = {\n", " 'l2pyr': 'L2 Pyr',\n", " 'l2int': 'L2 Inh',\n", " 'l3pyr': 'L3 Pyr',\n", " 'l3int': 'L3 Inh',\n", " 'l4pyr': 'L4 Pyr',\n", " 'l4int': 'L4 Inh',\n", " 'l5pyr': 'L5 Pyr',\n", " 'l5int': 'L5 Inh',\n", "}\n", "\n", "# create a figure/axes to draw on\n", "fig, ax = plt.subplots(figsize=(7, 7))\n", "\n", "# finally, draw the colormap using the provided function:\n", "im, cbar, labels = show_connectivity_matrix(\n", " ax=ax, \n", " results=results, \n", " pre_cell_classes=cell_classes.values(), \n", " post_cell_classes=cell_classes.values(),\n", " distance_adjusted=False,\n", " class_labels=class_labels, \n", " cmap=cmap, \n", " norm=norm\n", ")\n", "cbar.set_label(\"Connection probability\", size=16)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Connectivity vs intersomatic distance\n", "\n", "It is generally understood that two cells are more likely to be connected if their cell bodies are close together. This introduces a possible source of systematic bias in the connectivity measurements shown above because we do not always probe for synapses over the same range of distances. If one matrix element above was probed at sorter distances than another, then it may appear to have higher connectivity when in fact this is only the result of a sampling bias.\n", "\n", "To be more careful, we can look at the actual distribution of distances probed for each group to make a more fair comparison:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# sort all inhibitory cells into pv, sst,and vip subclasses\n", "cell_classes = {\n", " 'pv': CellClass(cre_type='pvalb'),\n", " 'sst': CellClass(cre_type='sst'),\n", " 'vip': CellClass(cre_type='vip'),\n", "}\n", "cell_groups = classify_cells(cell_classes.values(), pairs=mouse_pairs)\n", "pair_groups = classify_pairs(mouse_pairs, cell_groups)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "from aisynphys.connectivity import connectivity_profile\n", "\n", "# 20 um bins\n", "bin_edges = np.arange(0, 500e-6, 20e-6)\n", "\n", "profiles = {}\n", "distances = {}\n", "connected = {}\n", "\n", "# loop over all 3 cell classes \n", "for name, cell_class in cell_classes.items():\n", " # get all like->like pairs for this cell class\n", " pairs = pair_groups[cell_class, cell_class]\n", " \n", " # filter for pairs that were probed for inhibitory connections\n", " pairs = [pair for pair in pairs if pair_was_probed(pair, 'in')]\n", " \n", " # build an array describing whether each pair is connected\n", " connected[name] = np.array([pair.has_synapse for pair in pairs]).astype(bool)\n", " \n", " # and another list of distances\n", " distances[name] = np.array([pair.distance for pair in pairs]).astype(float)\n", " \n", " # generate a profile of connection probability vs distance \n", " # with confidence intervals\n", " profiles[name] = connectivity_profile(connected[name], distances[name], bin_edges)\n", " \n", " " ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "image/png": 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O4F/tziHua/oo0f/utiTX4r7PV3ew/Xb3/Te0k/OscD4mo45jEM5UYq8CPpwbq+eAGUBOkP2fBGqAjA7O+Z9u7D/t5Nr+z4Kpif7/sCVxC3CL+z74Rrv1i9z1h7l/7/de969z35cSsP5w9/38XBTxfBu4B9jlnrsEWAwcHGL/d3AG6U5vt/41nKnYMgPWbQFeabffFvc689qtv8xdvzDR/0eJWqwGsPv6napW+/9wf1+C84U0VVW/Ap4F/rNdbd2PgT5EWKOmqjtV9Q51psaZiHO3dzDOB0epiCwNUfvxqKqWBJynGbgDZ4zKH7jr2nBqQY4QkUkBx04FRkYaq+kRqoGDOqih8JeNU4M1g4gVVa1U1QdU9VhgFPArnJulh4FdIvKIWxMTGFcfYLpIyDaE/tiLRaR/vGI33cZ+tWjue2sG8Imqvh/GORarmzUBqOp7wAvACSLSN5JgVPUtVb0UZz7macDLOLXYH4rTVGlOkPjzge8FxD8GOBp4XMNr81eD8zQs0P3u+v+KJP7uxBLA7uuzIOs+dX+OdX8+BPTGqUr3OwuoBP4KICJ9RWR4uyWzowur6gZVvQbncdRyvq4FCdYWKpw4IfijgLMAf3JoTKB5OO+7j0XkcxF5UER+GPC46V7g/3C+BL4SkdUi8ovAdnYdEZHsIOWiw3ZNqrpNVRcD38F57JwNnInzReZ3I06t9lNAmYj8WUQuEJF+Aed5FafsngOUi8gbInKdiHwjnNhNz6Kqn+C8188MeP8fA4wm/JvnUJ/T6Tg3NrjtBAPLQ4dlSVVbVfXvqjoTJ7lbB/wbTrOJQI/jPBFq/9kvEcS/WVWb2l2/CeeR8Njgh3R/lgB2X8HG92lfo7Aap93QWQDidOI4FlgVUFgux3n8Grh8J9RFRaSP28j3GaAUOBenqv5CnKr8aOJEVT8GPgBmiKMPcCrwvKqWhorH9Eyq+jTOF9xMnPZy/4GTVL0iIpmqWgEcARyH8ziqH07N8wYR+XYYl/gZ+5eLn4Xa2W1kf7KIPAbsxmnv+iFO+8S9U5Cp6kacdlLTcb7cRuG0TVwnIuMC9jsb58vyN0AFsAAIVntiDDjvpULcNrDE5ua5/ef0O+xbHoJ93n99sMhocToPfgK8hVMjuAK345WfW1b/BpwScCM0A/hMVd8NM9ZQ49316J763XIqOAM4XyLt57b018Bthr3TIT0GzBWRscDp7H9X9RDwervzfBj4h/sI7XvAGcApQF+cO8brgEdUdWsncba3T5wBVuJ8SR+H80igH/b414TgNnN4BHjEfeR1E04D8B8Cf3SbFrziLrg9Dd/DSaqm+08T4vRrCHgk5dpnKjH3mv+OUy5+jNPB5EvgbuBhVf2UINybr9XugohMw/kCnA/MDtjvE+ATYLHbjONt4CYRuc99XGeDvBq/x3DaAp4lIm/gvB9fUNWdYR5/IE6Hqvbr2nBqrMGpzQ6sBW9ofxK3VvCnOGXi2+7xz+N0InxaVfc7xrUS57vlJyKyHqej1sIwYwcY59747X1cLM6YgWNwah57JEsAu6+LRWRvO0ARGQBchNPL9tWA/VYCc3HuCE8D1qvq2/6NqrqZ/ROxvUTkPuAnQB5Oo95lOElfuHdmZ4rI9f52gO7j5ctwPhj+2m7fvR9iOAlgNfB0mNcxPYSIpAP9VLXKv05VVUT+z/1zsIjkqmp5u0PX4XxpDQ5YV+uec7CbUPrP56/lCBXDb4GfA0U479M/4bT7+2dgW6ogxwWLy99Ga7A/FqBKVX0B8VSJyBfABJyekQ3+2Nu9HtMDqWqZiPwd+BFOL/b+RHbzfKWInOp/74rIYcAJwD9Utda9xhuhDhaRf8NpF/49nLzjHZxmGo+ralkY1/8bToePs4D1OB1QHokg/v7AJTg9mP0ucdc/FfSIHsASwO6rHHhbRJbj1Oqdi9Nh4gJVrffvpKr/JyIf4yRd/XEaqUfiHJwk7GGcx7FtER6/wY1zCU6P4DNwHs0tUtVtgTuq6m73Q+zHOF9yyzSFR603cdMP2Ok2Q/g/nEeuY3AamlfidH76vYgU4tQ+bMWpufiZe+xDAef6X5whYu4Xkb/htEV6W1W/6CSGme61F+D0qG/qZH+/50WkGudLehswkK978z7s7nMWcJmI/AXY5MZ0LHASTq9+fy3KOzhflL8WkUE4vfu/CLzBMz3KSpwe5LcR+c3zKGCNW6byccpEA3BFmMcfDkzCqYV/WFU3RHBtVLVFRB53r3s4TuK5PYJTfA5c43YKe889x3k4N313RxJLt5Lobsi2xHbh6y+LE3AewX6JM9zLJ8AZIY5Z4B7TBhRFeL2+UcY51b3mOcAvgI1unBuBuR0cd6p7nAJHJ/rf25bkW3CGEvpvnOGEKtz31RacDkkT3H1+hNNEosTdXoZTM35qu3OlAbe6+7X537NhxBBtufg5Tu/KUqAZp5ZxNc50bv59DsX5Mt+Ek9TV4DTLWAD0bne+s3Ea6ze7sa9I9P+PLYlZ3HJR4b4Pfh9k+wpCDwOTh3MDUgHU47SrPTyCa+835FEU8R8e8Nl/Zoh9thB8GJhXgMPcuOtwbgQfBoYl+v8lkYvNBdzNSIrM/ykiU3G6/5+rqisSG40xxpj2JIXnwvYTkS3AFlWdmuBQko71AjbGGGOM6WFSLgEUke+LM7/nJhHZrxeQOHPMVovIB+5ydSLiNMYrViaM2ZeVCWM6l1KdQNzefffh9CQqAd4RkWd0/+EUXlPVkz0P0BiPWZkwZl9WJowJT6rVAB4JbFLVzeqM57MKZ0wv41LVFaoqydz+D0BVX3HjXJHoWFKclQlj9mVlIkZU9ZxUbv8HoKqjrf1fcKmWABbgDI3gV+Kua+/bIvKhiPxdRA7yJjRjEsLKhDH7sjJhTBhS6hEwwadtad+N+X1glKrWuiPoP4UzOOq+JxKZhTM/LTk5OYdPmjRpvxM3NTXR1tZGSUkJTU1NjBs3br99/NLT0+ndu3f4r8SYEN57771yVQ1rTlo8LhPGJIKVCWP2FWGZCCrVEsASnJH1/QqBHYE7qGpNwO+rReT+YKPrq+oDwAMAU6ZM0Xff3X/iis2bN1NZWcldd93FqlWrWLFiBenp6UED69u3LxMnToz2dRmzl4h0NHVee56WCWMSwcqEMfuKsEwElWqPgN8BJojIGHfKsNNoN9+tiAx35+BERI7EeY0VXbloUVERLS0tlJWFnrGmtbW1K5cwJloJKRPGJDErE8aEIaVqAFW1VUTm4EzEng4sV9W1InKRu30JzjRhF4tIK85UNadpF0e7Lipybia3bdvG8OHDg+5jCaBJhESVCWOSlZUJY8KTUgkgONX1OFMjBa5bEvD7vcC9sbxmYAJ4xBFHBN2nrS3SKXCNiY1ElAljkpmVCWM6l2qPgBNi6NChZGZmsm3btpD7qCo+n8/DqIwxxhhjomMJYBjS0tIoKCigpKQk5D4iYo+BjTHGGJMSLAEMU2FhYYc1gJYAGmOMMSZVWAIYpqKiIrZt20ZH7YQtATTGGGNMKrAEMExFRUU0NTVRXl4ecp+WlhYPIzLGGGOMiY4lgGEK7AkcjKpaDaAxxhhjUoIlgGEqLCwEOk4ArQbQGGOMManAEsAwDR8+nPT09A57AlsCaIwxxphUYAlgmDIyMigoKOiwJ3Bzc7OHERljjDHGRMcSwAgUFhZ2WANobQCNMcYYkwriNhWciFwdwe6qqoviFUusFBYW8uGHH6KquPOI78MSQGOMMcakgnjOBXxtu78V2D9rctYDJH0CWFRURF1dHVVVVQwaNGi/7TYfsDHGGGNSQdweAatqmn8BJgNfAAuB0UC2+/Mqd/1B8YojlsIZCsbmAzbGGGNMsvOqDeC9wIOqulhVv1TVJvfnzcAy4D6P4uiSzoaCsengjDHGGJMKvEoAvwW8G2LbO8BRHsXRJSNGjCAtLS1kR5BoE8DS0lI+//zzroZnjDHGGBMWrxLAauB7Ibad6G5PepmZmQwfPrzDoWAiTQCrqqrYsWMH1dXV1NTUdDVEY4wxxphOxbMTSKDlwFUi0hf4I7ALGAb8FJgF3OhRHF1WWFjYYQIYyWDQDQ0NfPHFF6g6/WC2bt3K5MmTg/YwNsYYY4yJFa8SwKtxevvOAy5y1wlQh5P8XetRHF1WVFTEP/7xj6DbIpkPuLW1lQ0bNuzTaaS1tZWysjKGDh0ak1iNMcYYY4LxJAFUVR/wWxG5DTgYGA7sBD5S1ZR4/OtXVFREdXU11dXVDBgwYJ9t4c4HrKps3Lhxv2TR5/Oxfft2Bg8eTEaGV7m5McYYY3oaT7MMVa0C/unlNWPN3xO4pKRkvwQQwpsObuvWrTQ2Ngbdpqrs2LGDkSNHdi1QY4wxxpgQPJsKTkQKROR2EXlXRDaLyGR3/TwR+ZZXcXRVZ2MBdlYDuHv3biorK0OOF6iqlJeXh0wQjTHGGGO6ypMEUEQOAj4GZgI7gFFAprt5FDDXizhioaCgACDkUDAdtQGsqamhpKSk08GiVZUvv/wy+iCNMcYYYzrgVQ3gbcBnwBjgR+w7JdybpMg4gABZWVkMGzYsZA1gqASwsbGRzz//fG+P387U1dXZsDDGGGOMiQuvEsDvAjepai1fz/3rtwunU0jKKCwsDFkDGGw+4La2NjZu3BjRNHE+n4+tW7eGnTAaY4wxxoTLqwSwo8wnF2jwKI6Y6CgBbD8fsKqyadOmiMYH9PMPC2OMMcYYE0teJYD/As4Nse2nwBsexRETRUVFVFRUUFdXt9+2tLS0fR4Db9u2jfr6+qhq8vzDwgSrVTTGGGOMiZZXCeAi4Aci8jxORxAFThCRlcB/ATd4FEdMBA4FE4w/ASwvL6e8vDyiR7/tqSrbt2+P+nhjjDHGmPY8SQBV9VXgFJxOIMtxOoHcBPw7cIqqvu1FHLHS2VAwra2t1NbW8uWXX3a5DZ8NC2OMMcaYWPNsIGhV/RvwNxEZDwwFKlR1vVfXj6XOagDr6+spLS2NWQcO/7AwBxxwQEzOZ4wxxpiezatxAK8WkREAqrpJVd/0J38iki8iV3sRR6zk5OQwZMiQoDWA/ke2sW63Z8PCGGOMMSZWvGoDeA1QGGLbCHd7SiksLAyZAIpIkCO6xoaFMcYYY0yseJUAdpQRDQKawj6RyPdFZL2IbBKRhR3sd4SItInIjyMJNFxFRUUdDgUTD62trZSXl8fl3CZ1JUuZMCZZWJkwpnNxawMoIlOB4wNWXSgiJ7fbLRuYDqwN85zpwH3A94AS4B0ReUZVPw2y383Amuii71xhYSF//etfaWxsJCsrK16X2YfP56OkpITBgweTnp7uyTVNckumMmFMMrAyYUx44tkJ5FjgN+7vSvBxAJuBT4FfhHnOI4FNqroZQERWAT90zxHoUuDPwBERxhw2f0/gkpISxo8fH6/L7EdV2bFjx97rmx4vacqEMUnCyoQxYYjbI2BVvU5V01Q1DecR8Lf9fwcsWap6mKq+FeZpC4DAhncl7rq9RKQAZ2zBJbF4HaEEJoBeUlXKyspsWBjjlzRlwpgkYWXCmDB4MgyMmwTGQrC2hO0b3N0J/FJV2zrqjCEis4BZACNHjow4EP9QMKHGAownVWXbtm1MmDChw/1aW1tpamrauzQ0NODz+SgoKCA7O9ujaE2cJU2ZMCZJWJkwJgyeJIAici4wSlWvDbLtWuALVV0ZxqlKgMBnn4XAjnb7TAFWuYU6F5gmIq2q+lTgTqr6APAAwJQpUyLutdG/f38GDBiQkAQQoLa2lpqaGrKysvYmeI2NjTQ0NNDU1ERLS8s+PZIDZyOpqakhLy+PgoIC0tK86gdk4iRpyoQxScLKhDFh8Gog6LnAshDbdgPzgHASwHeACSIyBtgOnAacEbiDqo7x/y4iK4C/ti/UsdJRT+B48/l8bNy4EREhLS0NVQ065VywHsn+x8hfffUVo0ePZsCAAV6EbOIjqcqEMUnAyoQxYfAqARxP6J6+nwHjwjmJqraKyBycXlvpwHJVXSsiF7nbPW3PUVhYyEcffeTlJfejqlENOq2qtLa2snnzZvr27cuoUaPIzMyMQ4QmnpKtTBiTaFYmjAmPVwlgK041ezB5kZxIVVcDq9utC1qgVfWcSM4dqaKiIp5//nmam1tU+HEAACAASURBVJtTNnny+XzU1NSwdu1a8vPzGTZsWFwGsjbxk0xlwphkYGXCmM551QDsX8BFIbZdhFNln3IKCwvx+Xzs2NG+eUnq8fl87Ny5k7Vr11JbW5vocIwxxhgTR17VAN4A/ENE3gYexGmXUQBcAByGM2BnygkcCmb06NGJDSYGfD4fTU1NbNiwgcGDB1NYWEhGhldvEWOMMcZ4xathYF51p9q5E1gasGkLcKqqvuJFHLHmTwAT1RM4XlSVr776iqqqKgoLCxkyZIg9FjbGGGO6Ec+qd1T1aeBpEZkIDAHKVXWDV9ePh4EDB5KTk9PtEkD4unPJtm3bKC8v54ADDrAhY4wxxphuwvPne6q63utrxouIJHQoGC/4fD4aGhqoqalh4MCBiQ7HGGOMMTHgWZWOiHxTRJ4UkXIRaRWRw9z1N4rI972KI9aKioq6ZQ1gIJ/Px+7duxMdhjHGGGNixJMEUES+C7wFTAIea3ddH6F7CCe9wsJCduzYQWtra6JDiava2lpaWloSHYYxxhhjYsCrGsCbcAblPAiY327b+zg9gVNSUVERbW1tlJaWJjqUuKuoqEh0CMYYY4yJAa8SwMOA36kzL1n7ucnKiXAw6GTSXXsCt+efPi7Y1HLGGGOMSS1eJYCNQJ8Q2/KBao/iiLmekgACtLa20tDQkOgwjDHGGNNFXiWArwPzRCQ9YJ2/Kul84CWP4oi5IUOGkJWV1aUEcMuWLbz66qsxjCo+rDOIMcYY0z14lQD+Fucx8Ifu7wqcLSIvA0cB13kUR8x1dSiY5uZm5s+fz4IFC3j22WdjHF3sVVZW4vP5Eh2GMcYYY7rAkwRQVT8EjgF2Ab8GBJjjbj421ccGLCwsjDoBfOyxx/jyyy8ZO3Ys119/PW+99VaMo4u96uqUfWJvjDHGGDwcB1BV31fV/wD6AYVAf1U9TlX/z6sY4sWfALa1tUV03K5du1i2bBnHHnssy5cvZ9y4cfzyl79k3bp1cYq06+wxsDHGGJP6PJ/bS1UbVXWHqtZ7fe14KSoqoqWlhbKysoiOu+uuu2hra2P+/Pn07duXu+66i/79+zN37lx27NgRp2i7rq6uzsYENMYYY1KYlzOBjBWRhSJyv4gsb7cs8yqOeIimJ/B7773H888/z9lnn01BQQEAeXl53H333TQ3N3PppZcm9aPW8vLyRIdgjDHGmCh5NRPID4F1wPXAKcBxQZaUFWkC2Nrayi233EJ+fj5nn332PtvGjh3Lbbfdxo4dO5g/fz5NTU0xj7erbExAY4wxJrV5VQN4PfAKkK+qI1R1TLtlrEdxxMXQoUPJzMwMOwH805/+xKZNm7jsssvIysrab/thhx3GokWL+PDDD/ntb38bcdtCL7S1tVFf322e4htjjDE9ilcJ4FjgVlWNrJFcikhLS6OgoCCsnsBfffUVS5Ys4Vvf+hbHHRe64vOEE07gsssu46WXXuKOO+5Iuto2n88XcZtHY4wxxiSHDI+usw4Y4tG1EqKwsDCsGsD77ruPhoYGrrjiCkSkw33PPPNMSktLefzxxxk+fDgzZsyIVbgxUVlZyciRI0lL87wvkTHGGGO6wKtv7iuBX4lISj/q7UhRURHbtm3rsKbuk08+4emnn+aMM85g9OjRYZ33sssu44QTTuDOO+9kzZo1MYo2dqqqqhIdgjHGGGMi5FUN4LU4NYCfichG4Kt221VVj/UolrgoKiqiqamJ8vJy8vLy9tvu8/lYvHgxQ4YM4fzzzw/7vGlpaVx33XWUl5dz7bXXkpuby+GHHx7L0KPmHxNw8ODBiQ7FGGOMMRHwqgawDVgPvAmUuX8HLik/t1hnPYGfeeYZPv30U+bOnUvfvn0jOnfv3r257bbbKCws5PLLL+fzzz/vcryxUl9fT3Nzc6LDMMYYY0wEvJoKbqo760fIxYs44qmwsBAIngDW1NRw3333ccghh1BcXBzV+QcMGMDdd99NZmYmv/jFL5JqNg4bE9AYY4xJLV49Au72hg8fTnp6etCewEuXLqW6uporr7yy044fHcnPz+fuu+/m5z//OXPnzuX3v//93tpEn89HVVUVZWVllJeX7/3p/72srIyKigqampqYPn06p59+OsOHD486Fj//mID5+fldem3GGGOM8Y5nCaCIpAFHAiOB/Qa/U9WHvIolHjIyMoIOBbNx40b++Mc/8qMf/YiJEyd2+ToTJ05k8eLFzJ07l3POOYecnJy9iV6w8QIHDBhAXl4eeXl5jBs3joaGBlatWsWqVas44YQTmDlzJpMmTepSTD6fj7q6uogfbcdCfX09GRkZZGZmen5tY4wxJlV5kgCKyDeAp4BxQLBqIgVSOgGE/YeCUVVuueUW+vXrx8UXXxyz6xx11FEsWrSIhx9+mH79+jF27Fhyc3PJzc0lLy9v788hQ4YETYxKS0tZtWoVf/nLX1izZg1TpkxhxowZfOc734lqSBd/ZxCvE8D6+nrWrVtHTk5OTJJrY4wxpqfwqgbwfvdaPwU+BpJvfrMYKCws5MMPP0RVERGef/553n//fa666ioGDBgQ02udeOKJnHjiiVEdO3z4cObNm8cFF1zAU089xeOPP868efMYM2YMZ555JsXFxfTu3Tuic1ZVVdHW1kZ6enpUMUWqubmZDRs2oKrU19dTV1dHTk6OJ9c2xhhjUp1XvYAPAy5X1T+r6gZV3dp+8SiOuCoqKqKuro6qqirq6+u58847mTRpEqecckqiQwuqb9++zJgxg6effppFixbRq1cvrr/+ev7zP/+TZcuWRTTGn4h4NiZga2sr69ev3/vI2+fzhTULizHGGGMcXiWA5UC3HyskcCiY5cuXU1ZWxpVXXulZrVi0MjIyKC4u5tFHH+X+++9n4sSJ/O53v+Pkk0/m5ptvDiu58j8Gjjefz8fGjRtpaWnZZ319fT21tbVxv74xxhjTHXiVAN4BzBaR5M6Eusg/FMwbb7zBI488wsknn8zBBx+c4KjCJyIceeSR3H333axatYrvfe97/OUvf+HUU0/lk08+6fT4hoYGmpri93RfVdm8eTMNDQ37zbhitYDGGGNM+LxKAPOAicCnInKviPy/dst14Z5IRL4vIutFZJOILAyy/Yci8pGIfCAi74rId2P5QjoyYsQI0tLSWLFiBb1792bOnDleXTrmxo8fzzXXXMMzzzxDVlYWTz75ZFjHxXNMwJKSEvbs2RNyur2GhoYeWQuYzGXCmESwMmFM57zqBPKbgN8nBNmuwDWdncStQbwP+B5QArwjIs+o6qcBu70IPKOqKiIHA08AXRvnJEyZmZkMHz6cHTt2MGvWLHJzc724bFwNHTqU448/nhdffJErr7ySrKz9RvDZS1UpLy9nxIgRMR8TcNeuXZSXl+PzhZ40xl8L2NVhbVJJspcJY7xmZcKY8Hg1E0haJ0u4j4aPBDap6mZVbQZWAT9sd61a/bqKKAcnufTMxIkTGT9+PD/72c+8vGxcFRcXU1dXx2uvvdbpvj6fL+a1cJWVlWzfvr3D5M+vB9YCJn2ZMMZjViaMCYNXj4BjpQAInGutxF23DxH5LxFZB/wNOC/YiURkllv1/25ZWVnMAly0aBHLly8nI6P7TLJy+OGHM3ToUFavXt3pvrHuDFJbW8sXX3wR8rFvsOuHmo+5m0r6MmGMx6xMGBMGTxNAETlZRG4RkWUislhEpkd6iiDr9ssMVPUvqjoJOAVYFOxEqvqAqk5R1Sl5eXkRhhFaVlYWffr0idn5kkF6ejonnXQSb775JpWVlZ3uX11dHXRWkkg1NjaycePGsJO/wOP27NnT5euniKQvE8Z4zMqEMWHwJAEUkX4i8irwDDAXmAbMA54RkVdEJNwpJEqAooC/C4EdoXZW1X8C40Qk9RvjJdj06dNpa2vj+eef73RfEQkrUexIS0sL69evD+uxb3vJ0iO4oqKCdevWxfsyViaM2ZeVCWPC4FUN4I04g0HPBLJVNR/IBs5y198Y5nneASaIyBgRyQROw0kq9xKR8eL2QBCRw4BMoCImr6IHGz9+PBMmTODvf/97p/t29TFwW1sbGzZsoLW1NepzJLoWsKamhq1bt1JfX09zc1yHwLQyYcy+rEwYEwavEsBTgd+o6qOq2gagqm2q+ijwW3d7p1S1FZgDrAE+A55Q1bUicpGIXBRwrU9E5AOcnmA/00ifIZqgpk2bxieffMLWrZ1P3NLY2Mi6devYtm0bFRUV1NfXh1Wbp6ps2rSpy+MJ+tsCJuK/vr6+ns8//3zvlIA1NTVxu5aVCWP2ZWXCmPB41VNhCPBpiG2futvDoqqrgdXt1i0J+P1m4OYoYjSdOOmkk7j77rt57rnnuPDCCzvcV1Wpq6ujrq6OtDTnPsPn89GrVy+ys7PJyckhOzub7OxsevfujYigqmzZsoW6urqYJG5NTU3s2bOH/v37d/lckVxzw4YNe5Ndn89HZWVlXIcEsjJhzL6sTBjTOa8SwC+Ak4EXgmyb5m43SW7o0KEcccQRrF69mlmzZoU91l9gzV9LSwstLS3U1NTsTQxVlczMTHr16kV9fX3Mau38bQEPPPDAmI9LGEz7OYr9/INXexGDMcYYEw6vHgEvBS51e/8eLyIHishxIrIU+AWwpJPjTZKYNm0a27dv56OPPuryuXw+Hz6fD1WlqamJ2traqDp9dMRfCxhvPp+PDRs27DdHMTidYurq6uIegzHGGBMurwaCvgO4CTgDpxbwE5yR2M8CblLVu7yIw3TdcccdR+/evcPqDJIMvGgL6G+32NjYGDKG6urquF3fGGOMiZRn4wCq6q+AETiPgs8CpgMjVPXXXsVgui4nJ4epU6fywgsvBK3tSkbNzc1x64jhb7dYW1vbYZLZ1WFxjDHGmFjydCBoVa1U1b+7vYH/rqr2rZiCiouLqa6u5o033kh0KGHxtwWMRy3gzp07qaqq6vTczc3NKZMwG2OM6f68Ggj6lyJyT4htd4vIFV7EkaxEBBHZ2yki2R111FEMGjQorKnhkkU8agHLysooLS0Nq92iiPSk2UmMMcYkOa8yjnOBUL0GPnC391giwsEHH0xBQQFpaWlJ31s0IyODk046iddeey1lkppY1wJWV1dH1LbQPxyMMcYYkwy8SgBHAhtDbNsMjPIojqQjIgwbNoyMjAyGDh3KwQcfzNChQ5M+CZw2bRotLS28+OKLiQ4lbM3NzTHpjFFXV8fmzZsjTiZramoSMjC1McYY055XCWA9UBBiWyHQtWkfUpg/AfRLT0+nsLCQyZMnM2jQoKRNBA888EBGjRqVUo+BY1EL2NjYyMaNG6MerqahoSHqaxtjjDGx4lUC+BpwhYj0Dlzp/r3A3d7jpKWlMXz4cNLT0/fblpmZydixY5k0aRI5OTlJ1z5QRJg2bRrvv/8+O3fuTHQ4YWtpaYm6FrClpSXoQM/hUlUbDsYYY0xS8CqruBaYAGwQkRtE5BIRuQHY4K6/2qM4ks7QoUM73N6nTx8mTZrEuHHjyMzMTKpEsLi4GCBlxgSE8GsBVRWfz0dzczMNDQ3s2bOHDRs20NraGvW1VdXaARpjjEkKnkwFp6ofishxwK3AL3ESTx/wOnCqqn7oRRzJJC0tjfz8/KC1f8H079+fyZMnU1FRQUlJyd4ZNILx9yr2/66qexf/tWMx48aIESP45je/yerVqzn33HOT9nF1ey0tLZSUlJCWlkZLSwutra20trbS1ta2d/H/+wT+W8ai/V5jYyNtbW1h/78bY4wx8eDVXMCo6r+AY0QkGxgEVKpqj20QJSKd1v4FOyY3N5fBgwdTWlpKRUUF6enppKenk5GRQa9evcjIyCAjI2PvusCf6enpqCp79uyhsrKS6urqvTVd0SouLubGG29k3bp1HHjggVGfx0s+n4/du3eHtW9g4hwLIkJNTQ2DBg2K2TmNMcaYSHmWAPq5SV9KJH7xetzqr/2L9vxpaWmMGDGCESNGRHX8wIEDGThwIKpKfX09VVVVVFZW0tzcjIhElBCecMIJ3HLLLaxevTplEsBE8vl8VFVVWQJojDEmoZKnQVkSGj58eFySQBEhLy8v5ueNJo6cnBwKCgqYPHkykydPpqioiH79+oU9MHX//v357ne/y/PPP9+l9nE9ib/mNRW1tbWlbOzGGNMdxOoz2BLADmRlZTF69OiYtm3z194lU2cOv8zMTHJzcznggAM49NBDGTt2LEOGDOn09U+bNo2Kigr+9a9/eRRpalNVGhsbEx1GVLZu3cpXX32V6DCMMabHqq2tjcl5ki8LSTKDBg0iNzc3ZglbWloaubm5MTlXPKWlpTFgwABGjx7N4MGDO9z36KOPpn///inVGziRUnk4mNbW1ph9+BhjjIlcrL4/LAEMQ1FREb179+58x04kc+1fRzpLgDMzMznhhBN4+eWXqa+v9zCy1KSqVFVVJTqMqNXV1SU6BGOM6bFi9f2RWplIgogI48eP73Liliq1f+3l5OR0OmzJtGnTaGxs5OWXX/YoqtRWX18fk6F4EqGxsdHaARpjTAK0tLTQ3Nwck3N51gtYRPoD03DmBc5qt1lVdZFXsUQjMzOTcePGsWnTpqi+/NLS0igsLEyZsfIC+YefKS0tDfnaDznkEAoKCli9ejXTp0/3OMLUIyLs2bOHAQMGJDqUiKkqTU1NZGW1L8bGGGPiqaamJmZ5hCcJoIgcDTwLDAyxiwJJnQCC0+N12LBh7Nq1K+IkMD09vdO2dMlsyJAhlJaWhtwuIhQXF7N8+XLKysqSopdzMvMPB5OKCSA4NZiWABrj3BCl4o29SU1VVVUxe3rk1SPgO4EtwBFAlqqmtVtSZlqEESNG0KdPn4iOSeXaP7/evXt3+oVfXFyMz+djzZo1HkWV2lK1IwhYO0Bj/D7//HNqamoSHYbpAVQ1pu81rxLAA4HfqOp7qhqbh9cJIiKMGzcuoqm8MjIyusXAv0OHDu2wHeSoUaM46KCDWL16tYdRpa7W1laampoSHUZUrCewMQ7rGW+80tAQ2zk0vEoAvwS63o02SfTq1Yvx48eHVaPXHWr//Pyzh3SkuLiYDRs2sGnTJo+iSm2pWnNgHUGMcaiqJYDGE7GeRMCrBPA6YKHbEaRb6Nu3b1jTufXq1YuBA0M1fUwtGRkZ9OvXr8N9TjzxRNLT021MwDCoKpWVlYkOIyqqSktLS6LDMCYp2PBXxguVlZUpmQCeDAwDvhCRv4rIQ+2WlR7FEVPDhw8nJycnZO1ed6r98+vsMfDgwYP59re/zXPPPZeyw5x4qba2NiX/nUTEvvSMcbW1tdlUmCau2traYj6DlFcJ4HdxevrWAAcB/x5kSTkiwtixY0O2B8zMzEzZXp6h9O/feSVucXExu3bt8mRMwLfffjulHzeLSEp2qPD5fCkZtzHxYjdEJp727NkT88okTxJAVR3TyTLWizjiISMjgwkTJuz3H9Mda//ASVg6G87m2GOPZcyYMfzqV79i5cqVcWkr1tTUxE033cTs2bOZO3duzBvHesXn86Vsb2Br92TM1+yGyMRTLId/8bOZQGKgT58+FBUV7fNotHfv3mHVlqWivLy8Dh8DZ2Vl8Yc//IGpU6dyzz33cPnll7Nnz56YXb+kpITzzjuPP/3pT5x44ons2rWLFStWxOz8XkvVdoCpmnQbEw92Q2TiKR4VBZ4lgCLSR0TmiMgfReRFEXlCRC4RkcgG1UtSubm59O/fHxHptrV/ftnZ2Z0Og9O3b19uuukmFixYwOuvv87MmTNZv359l6/9j3/8gzPPPJOdO3dy++23c+ONN1JcXMxDDz3Etm3bunz+RGhpaUnJDhU+ny8l4zYmHuwRsImXpqYm2traYn5eTxJAERkOvA/cDUwB+uAMCn0v8J6IDIvgXN8XkfUisklEFgbZfqaIfOQub4rIITF6GZ3FxejRo+nVqxdZWVmd9pZNZSJCXl5epwmuiHD66afzwAMP0NzczLnnnstTTz0V1TWbm5tZvHgxCxcuZPTo0Tz66KMcc8wxAMydO5devXpx++23R3XuRBORLg0Hk6gyYR1BTLJKRJlobW2Ny5e0MfEaLsyrGsDFwCDg3902f99W1TE4nUMGAjeHcxIRSQfuA4qBbwCni8g32u32BXCsqh6MM73cAzF6DZ1KT09n0qRJjBs3rtvW/vkNGTIk7H0POeQQHnnkEQ499FCuv/56rrvuuoh6M5WUlHDBBRfwxBNPcMYZZ/Dggw+Sn5+/d3tubi4///nPee2113j99dcjeh3JwOfzRf0YOJFlwufzWQJo4i7Sno+JKhNpaWlWHkxcfPXVV3FpS+9VAlgMXKWqbwSuVNU3gd8A08M8z5HAJlXd7M4osgr4Yftzqqr/2/R/gcIuRR6hXr16kZmZ6eUlEyIzM5Ps7Oyw9x88eDD33HMP559/Ps8++yznnntuWI9sX375ZWbMmMGXX37Jrbfeyvz58+nVq9d++5122mmMHj2aW2+9NSVn19izZ0+0BTyhZSKWbTuNaU9V2bJlS6SHJaRMqKolgCbm4jniglcJYF9gR4htJe72cBQAgVlDibsulPMBG5E4TjobE7C99PR0Lr74Yu666y52797NjBkzQg4V09LSwm233cYVV1zByJEjefTRR5k6dWrIc/fq1YvLL7+ckpISHn300UhfSlKI8ssjoWXCOoKYeKqsrIzmPZaQMmEzgph4qKuri9sTRa8SwPXAzBDbZgDrwjxPsH+FoNUmInIcTsH+ZYjts0TkXRF5t6ysLMzLm0DhTA0XzNFHH80jjzzCqFGjuOKKK7jrrrv2GUR1x44dXHDBBTz++OOcfvrpPPjggxQUdPT57TjqqKM47rjjWL58OaWlpRHHlUhdGA4moWXCBsA18dLW1saXX34ZzdAXCSsTNhSMibXq6uq4TRbgVQJ4K047jH+IyHkiUiwi54rIGuAM4JYwz1MCFAX8XUiQmkURORh4EPihqlYEO5GqPqCqU1R1Sl5eXkQvxjjS09OjHug6Pz+fBx98kB//+Mc8/PDDXHzxxZSVlfHKK69w5plnsnXrVhYvXsyCBQsieqQ+f/58VJW77rorqrgSKcp2gAktEyJitYAmLkpKSqL94ktYmWhpaUnJmX1M8qqqqorbub0aCPoR4CJgMk6B+xuwDDgYuEhVHwvzVO8AE0RkjIhkAqcBzwTuICIjgSeBmaq6IUYvwYTQ2ZiAHcnMzGThwoUsWrSIzz77jJ/85CdcfvnlFBYW8sgjj3D88cdHfM78/HzOOeccXnjhBd55552o4kqUpqamaGrTElomVNVqPUzM1dfXU1FREW272ISVibS0NLshMjHT0tJCc3Nz3M7v2TiAqvoAMIKvp4I7CChQ1d9HcI5WYA6wBvgMeEJV14rIRSJykbvb1cAQ4H4R+UBE3o3l6zD76tevX5fbJxQXF7Ny5UpGjx7NaaedxrJlyygsjL5N9syZMykoKOCWW25JqceT0QwHk+gyYe2eTKypKl988UXUvR4TWSasI4iJpZqamriOKJIRtzMHoao+nALZlXOsBla3W7ck4PcLgAu6cg0TPhFhyJAh7N69u0vnGTduXMxm88jKymL+/PksWLBg79AxqcDn80VV3Z/oMmFfeCaWysvLu1zrkagy4b8hsmZFJhbiMf1boLglgCJyFvA3Va1wf++Qqj4Ur1hMfOXm5lJeXp5UbV+OOeYYvvOd77B06VJOOumkiMYtTKR4DfgZTy0tLbS1tXU6O4wxnWltbe1K27+kYE0iTCyoaty/D+L5CHgFMC7g946WP8QxDhNn2dnZQcfmSyQRYcGCBTQ1NXHvvfcmOpywxWOwz3izdk8mVrZt25aSZSBQc3NzSiewJjl48ZkazwRwDPBBwO8dLWPjGIfxQG5ubtLNfjJq1ChmzJjBs88+y0cffZTocMKSil9+1u7JxEJtbS2VlZUpWQYCiUjEs5cY0151dXXcy0LcEkBV3eqOwu7/vcMlXnEYbyTrI9bzzjuPoUOHsnjx4pSYpzMVv/ysI4jpKv+MH6n4/g/GbohMV3lxM+RJL2ARaRORI0NsO1xEkv+b2XSoV69e5OTkJDqM/fTp04e5c+eybt06nn766USH021ZuyfTFbt376alpSXRYcSEz+ezGyLTJW1tbZ7UIns1DExHzwbTCTFKu0ktXRkTMJ5OPPFEDjvsMO677764DqrZk1m7JxOt5uZmduzY0a3eP3ZDZLpiz549njSpiuu3tYikiYi/a2Ca+3fgkgMUA+XxjMN4I9qp4eJNRLjyyiupra1lyZIlnR9gIpaWlmbtnkxUopzuLak1NTUl5WehSQ3xHv7FL24JoIhcA7QAzTg1fG+4fwcuNTgDcv4xXnEY76SlpTFw4MBEhxHU+PHj+clPfsKTTz7JunXhTj1twmUdQUw0ampq2LNnT6LDiDnrCGK6Isp54SMWz4GgX3F/Ck6StwxnjsZATcCnwF/jGIfxUF5eXlwnr+6KCy+8kDVr1rB48WKWLVuWdL2WU5m/I0hubm6iQzEpwufzsWXLlqT8rIiF+vp6srOzEx2GSTFNTU2edViMWwKoqq8CrwKIyEDgFlXdHq/rmeTQt2/fpE2s+vXrx5w5c1i0aBGrV69m+vTpiQ6pW7F2TyYSpaWlKdEzPxo+n4+6urqkHR3BJC8vJwOIe4t9EcnAmZfxsHhfyySeiCR1LdAPfvADJk+ezOLFi/n4448THU63Yu2eTLiampooLS3ttrV/gPUENlHxcizMuCeA7sTcu4Dueatn9pOMg0L7paWlcfPNNzN48GDmzJkT1ySwp42PZ+2eTLi2bt3a7W8WGhsbu/1rNLHl9XeGV2N2PEIcJ6M3ySUrK4s+ffokbRI4bNgwlixZwqBBg5gzZw6ffPJJzK9RW1vL3LlzmT59ekrO7xst6whiOlNVVdUjmguICE1NTYkOw6SQ2tpaT783vUoAtwBHiMg7IvIbX0CKAwAAIABJREFUETlfRM4LXDyKw3hk/PjxSTc/cKBhw4axdOlSBg0axOzZs2OaBG7fvp3zzjuPN998k7q6OtauXRuzcyczf7snY0Lx+Xxs3bq1Wz/6DWQ3RCYSXneg9CoBvA8oAA4H/h/we+DBgOX3HsVhPJKRkcHEiRPJyIhnR/Ou8dcEDhw4MGZJ4AcffMDZZ59NWVkZt956KyLSYxJAsHZPpmO7d+/uth0/2rMbIhMprycq8CoBHNPJMtajOIyHMjMzOeCAA5JydhC/4cOHs3TpUgYOHMicOXO6lKytXr2aiy++mP79+7NixQqmTp3KmDFj4vKIOVlZuycTis/no7S0tEe9P+yGyISrpaWF5uZmT6/pyTezqm7tbPEiDuO97OxsJkyYkBJJ4IABA5g9e3bESaDP5+P+++/n6quv5pBDDuEPf/gDo0aNAuCggw5i7dq1PeZLT0Q8/xAzqaG8vLzHlAM/uyEy4aqpqfG83byn38oiMllEZovIb0XkEhGZ7OX1TWL07duXsWPHJm2nENg/Cfz000/DOq6xsZGrrrqK5cuXc8opp3DPPfcwYMCAvdsPOuggKisr2bFjR7xCTzrW7sm05/P5ut18v+FQVVpaWhIdhkkBXk3/FsiTBFBEMkTkEeBD4B7gOuBe4EMReThgvmDTTQ0YMICRI0cmfU3gkiVL6N+/P7Nnz+azzz7rcP+ysjJmzZrFSy+9xLx58/j1r3+9X8eXyZOde5ye8hjY2j2ZYCoqKnpkTZiI2A2R6ZSqJmS0CK++ja8BfoozJdwYINv9eTXwM/en6eZyc3MZNmxYUieB+fn5LF26lH79+nHJJZeETALXrVvH2WefzRdffMFtt93GjBkzgtZwjh8/nt69e1tHENNjqSo7d+7scbV/YDdEJjwNDQ0Jua5X38QzgEWqeoPb5q/J/XkDcD1wlkdxmATLz89n8ODBSf04OD8/nyVLltC3b19mz57NunXr9tn+8ssvc8EFFyAiLFu2jGOOOSbkufy9oXtKDSA4H2Y9sbbHBFdZWdljev4GYzdEpjPV1dUJ+cz0KgEcAbwVYtub7nbTA4gII0eOpH///l1OAtPS0vYusTZixAiWLl1KTk4Ol1xyCevWrUNVWbFiBVdccQXjx49n5cqVHHDAAZ2ea/Lkyaxfv57W1taYx5mMrN2T8VNVtm/f3iNr//wSVbtjUkdVVVW3TgB3AEeH2PYdd7vpIUSEsWPHRj1biIjQp08fxowZw6GHHkrfvn3jUqPYPglcuHAh9957LyeeeCJLliwJe87jgw46iKamJjZt2hTzGJORtXtKrNbW1qRJuKqrq3vMjU8oPp/PbohMSG1tbd3+EfCjwK/d3r9jRSRbRMaIyFXAr4GHPYrDJIm0tDQmTJhAZmZmWMmbiCAiDB48mAMPPJADDzyQgQMH7k0m4zXgtD8J7NOnDy+++CKzZs3ihhtuICsrK+xz9MSOIJYAJs6GDRtYv359wh+7qiolJSVJk4wmit0QmY5UV1cnrEmUV9M0XIsz2PN17u9+Ajzurjc9THp6OhMnTuSzzz4LeYfsf8Q7bNgwcnNzgyZ66enpTJgwgXXr1sXly2bEiBGsWLGC7du3c8ghh0R1/MCBA1m7di0//vGPYx5fMtqzZ0+iQ+iR6urqaGpqQlVZv349BxxwQMJm46mpqbGaL77uCBI4PJQxkPgmEp58MqhqK3CGiNwAHAsMAr4CXlXV8AZcM91Sr1699iaBgTUWIkJ2djb5+fkMGDCg0zuk7OxsioqK2LZtW1wKU25ubtiPfNsTESZPntyjegJbu6fEKC0t3fv+b2xsZN26dUyaNCkhSWBPb/sXyDqCmGAqKioS2kTC008FVV0L9JxvQROW3v+/vTMPj6o6H//nzU72DcjGvn5JBLUIaNWij1qpVi3+qghVBKVAoSBKVUAqCrhRELcqRRYRqNatLm0FWi22VbRqWQJJICyyhOwhZJ1MZs7vjzszDmGyz5bkfJ5nnpm5yznvPfe+9773Ped9T2gogwcPJicnB6UUcXFxJCUl0a1bt1aVk5iYSGVlJaWlpX4XhZqRkcF//vMfKisriYyM9LU4Hsc+7qlhXkSN5zCbzZSXlzv+K6UwmUxkZ2czZMgQr56LiooKTCaT1+rzd/QLkaYhVqvV5y9JXjMAbcme7wIuBVKBUxgRwK8rpbpujgANAOHh4aSnpxMQENAub0Xv3r2pqqqitrbWjdK1n/T0dJRSZGVlcckll/haHI8TEBBATU2NNgC9SGFhocvlzkZgSEiIV2Tx9YPN37BYLNTX1/usO17jfxQVFflcR7w1E0gfDM/fOuB6oIftez2QaVuv6eKEhIS0+wYZEBDAwIED/S7Z9LBhw4CuEwhisVh0AlwvYrVaKSwsbNTzXVdXR3Z2tlfmaa6qqtJBDw3QgSAaZywWi19Mjeitp+SLQDRwuVKqt1LqEqVUb+AKIAZjejiNxi2Ehob63dzD9qnwutI4QD3uyXuUlZU1u43ZbCYrK8vjXbOnTp3yuyEYvkYppQ1AjYOCggK/0BFvGYBXAwuUUp87L1RK/QdYaFuv0biNmJgYevTo4VeewPT0dDIzM/1C8b2BfuB5h9ZMtVZfX092drbHhkjU1NRow98FSindLhrA0MGuZgBWAq4HqBjLW/ykEJHrRSRHRHJF5GEX64eKyBciYhKR+W2UV9MJSE1NbXUgiSdJT0+nuLiYgoICt5brrzphsVh8nouuK1BVVdWqdCt2I9ATgQn+4v3zR53QL0QagNOnT/uFjoD3DMDNwIxG1k0HNrWkEFsgyUvAOGAYcIeIDGuwWSkwB/hd20TVdBZEhAEDBhAYGOhrUYDvE0K7sxvYn3VCj3vyDi31/jljsVjIyclx6/mpra3l7NmzbiuvrfirTpjNZv1C1MWpq6ujqKioyxmAucBFIrJPRJaIyEzbdyZwIZArIlPtnybKGQXkKqWOKKXqgDeAm503UEoVKqX+C+gMpBqCg4MZOHCgX4wHHDx4MMHBwe4OBPFbndDjnjxPXV1dm5Nu241AdwXr5OXl+cuDzS91wh4Z74/Y5+8+e/YshYWFFBcX+8u57FT4kY4A3ksD85LtOw1Id7H+906/FUZ0sCtSgRNO/08Co9stnaZTExkZSWpqqs+jrkJCQhg8eLC7A0H8Vifs45569uzpa1E6Le0dTmC1Wjl48CCDBg1qV35Kk8nEmTNn2iWLG/FLnbC/EPkyD6g9N2RtbS01NTVUV1dTU1PjiA4XEZRSiAgmk4nU1FSfyeprCgsLCQoKIj4+3i3lmUwmSktL3VKWu/CWAdjPTeW4cuO0yZwWkV8CvwQjd5ymc9OjRw8qKio4e/asT9/A0tPT+fDDD7FYLO7qmvZrndCpYDyH1Wp1i6fGarVy6NAh+vTpQ1xcXJu85f40rgk/1QmlFBUVFfTo0aNd5bQGs9lMQUEB1dXV1NbWYjabHYFxrl6G7edQKUVhYSEBAQEkJyd7TV5/obS0lJMnTwKG5zY2NrbdZZ44ccKfdATwUhewUuq71nyaKOok0MvpfxqQ10aZ/qCUGqmUGtm9e/e2FKHpQIgI/fr183ki1oyMDGpqajh69Ki7ivRrnTCbzT7PddVZKSkpcVtZVquV7777jj179nDq1KlW5Qs0m83+5tnwW53w9pCIo0ePUlBQQEVFhSNQyGq1tkgnrVYr+fn5bg9a83cqKyv57rvvUEqhlOLIkSPnzLDTFqqrq/1ifGxDvJojQ0QyRGSWiCwWkV+JSEYri/gvMEhE+olICDAB+MD9kmo6I4GBgQwaNMinqWHS040REG4cB+jXOuHP4546Mkqpc+b9dQdWqxWLxUJBQQGZmZkcPHiwRR7z06dPu00GN+G3OlFXV+e1F6Ly8vJ2e+Dt05UVFRW5SSr/xmQykZube845shuBbR1rC/7p/QMvdQGLSBCwEbiDc93zSkS2Ane3ZDo4pVS9iMwGtgGBwHql1H4RmWFb/4qIJAFfYySetorIfcAwpZT/md8ar9OtWzd69+7teMPzNr179yY6Opr9+/dzyy23tLs8f9cJ+7iniIiIFm1vtVopLS0lPz8fEaF///5+lcrHX6ioqPDYJPJ2vaioqKCqqoqAgAB69uxJYmLieR70+vp6vwsY8GedsL8QtVQf2ordo+sOY1MpxYkTJwgICCAhIcEN0vkn9fX15OTkuIzUtlqt5ObmtmmsbGVlpd8Gw3mrP+xR4DbgtxgpYfKBJOAXtnVHbN/NopT6K/DXBstecfqdj+Hy12hckpCQQGVlJSUlJV5/cImIIyG0u/BnnbAHgjTXfVZbW0thYaGjW9P+4MrKyiI1NZUePXr4RSS3v+Bu719j2LsL8/LyyMvLIzY2lp49exIeHo6IkJ+f73EZ2oK/6kRrX4jaSkFBgVtTziil+O677xARtwVF+BP2cbBNvVTZtxkyZAjh4eEtKtduPPvrMBhv9YX9AliqlFpuG+dnsn0vB5YBd3lJDo0GgF69ehEWFuaTutPT0zl8+HCX6RptrBtKKcWZM2fIzs7mwIEDjsnRG3a/5OXlcfDgwVYlO+7MmEwmr88qYR8PVVZWxsGDB9m/fz9FRUV+ldOsI+CNGUHq6uo88oKglOLYsWPtHg/nbyilOHr0KDU1Nc1ey1arlZycnBbfu8+ePeuxWXfcgbcMwBTgi0bWfW5br9F4jYCAAAYOHOiTJNEZGRlYrVaysrK8XrcvaDjuyWw2k5eXx549ezh69ChVVVVN3nitViuVlZXs37/fn1KN+Iz8/HyfGl1WqxWTycTJkye18dcGPB0Zf/z4cY95nJRSHD582C8DGtpKXl5eq7JD2I3A5gw7f/f+gfcMwDzgh42su4w2RmhpNO0hJCSEAQMGeL1r0QOBIH6NiFBbW0tlZSW5ubns27eP/Px8LBZLq26OFouFo0ePcuzYsS47o4LFYnFr9G97sFqt2gBsA3V1dR5rN3uqK09iNwLbExThL9in5mzrTDomk6nRbcrKyvy+18JbBuAWYJEt+re/iHSzRWgtABYBr3tJDo3mHKKiokhOTvZqZHBcXBypqanuTgjt1xw8eJBDhw5RXl7u6E5sC/Ygkf3797fbk2LvjistLfXrt3RniouLfS2Cpp2IiEeGf9jH6XnDKLcHRXTkPJ8VFRUcP368ze1ln1PbVcokpRQnT570+/uKt4JAlgD9gcdsv+0I8Efbco3GJyQlJVFZWUlFRYXXPBrDhg1j7969XqnL13hiLJLZbCYnJ4ekpCSSk5Nb7MU1m82Ul5dz5syZczwYJ06cIDU1lYSEBI94hJVS1NXVERIS0ubylVIUFBRor1snoLq6usWBBC2lqKjIqx4n+ywyrQmK8BdqamrIzc1tty7ZjcD/+7//Izg42LG8uLi4Q/RSeMUAVErVAxNFZDlwJRCPMRn3TqXUAW/IoNE0hj3dyP79+712A83IyGDHjh0UFxeTmJjolTo7G3aDqLy8nP79+xMaGupym8rKSsrLyx1dMiJynlFqtVo5ceIEp0+fJi0tjdjYWLcYglarlbKyMk6fPo3JZCI8PJx+/fq1KQDp7NmzHeKhomka+5hWd+p9fX09p06d8rrHydkI9Ea6JovFQllZGWFhYURERLRJR81mMwcPHnRbW9lfRocOHUpQUJAjd6K/e//ACwagLRFnPkauvw+ArtPvpekw2JNEZ2dne0VxnccBjh071uP1dVasVivV1dUcOHCA3r17k5CQQF1dncPgq6ysPM/ga+yt32q1UldXx7FjxwgJCaFXr15ER0e3SS6z2UxRURGFhYUopRz122VtrecSjITLHeGhomked3ed+jLRsH083NChQz2WWaGmpoaCggJKS0vP0Zno6Gji4+OJjo5uUUCf3WB1dw5Nk8nkaIOOFBnvcQNQKVUnIvWA/8ZCazR4N0n00KFDCQwMZP/+/doAdANWq5Xjx487ou6cjb7Wnkur1UptbS2HDx8mLCyM3r17tzhvW3V1Nfn5+Y5oZVd122fxKCkpoX///i0qu6amxm+TyWpaj8lkQinlFi9zVVUVZWVlPjU6LBYLWVlZxMXFERcXR1RUVLvHVdvTROXn55+TosX5OM+cOeOI4A0PDyc+Pp7Y2FhCQkJclnf48OEmAzfag90INJlMHeZFzVtjAP8M/D9gu5fq02jahD1JtDsCA+w3d1c35rCwMAYOHNilAkE8TUu8fK0tr7q6moMHDxIREUGvXr1cdnPZH1SnT5+mtra2RXXbxwTm5OSQkJBAWlpakx4MPfavc2GPjG9vt6k3Az+aw2q1UlJS4jBGIyMjSUhIIDo6+pzxcc1RX19PUVGR45pv7j5sX19VVUV1dTUnT54kJCSEuLg4YmNjHUnLT548SWVlpcfaSinl1zn/XOEtA/BvwPMi8jaGMXgaOOcsKKU+8ZIsGk2T9O7dm6qqqjZH6okIIkJycjJlZWWNem4yMjL4+OOPsVqtPp2fWNM0VquViooKsrKyiImJIS0tjdDQUMc0aPY0Em15YVBKUVJSwpkzZ+jbty8xMTHnbVNfX09paWmLyrNYLDz11FMkJydz99136+vKjykpKSE1NbVdXsCSkhKPebTail0P7FMJKqUIDQ0lPj6euLg4QkNDXR5zVVUVBQUFTXrPm8O+j8lkIj8/n8LCQkSEiIgIKisrPe6Z8wdDvDV4ywB8x/Y93vaxozAigRXGnI0ajc8REQYNGsT+/ftbNeje2fDr3r07gYGBREZGcujQIZc3noyMDN555x2+++47+vXr585D0HgAu6evvLyciIgIxziu9t70lVLU19dz5MgRoqKi6NOnz3kRhS3lD3/4A++99x4ABw4c4PHHH+9wEZpdAavVSlFREWfPnqVfv35t8gRaLBa/TzVil622tpbTp0+Tn59PYGAgsbGxxMXFERER4fCeN0wY7876O1PianfiLQPwKi/Vo9G4heDgYAYMGMChQ4eafcC7MvzsREZGEh4e7nL6J3sgyP79+7UB2IHw1HReVquV8vJyMjMzSUtLc0SJtrT799///jfr1q3jpptuYvDgwaxatYqpU6eycuVKUlNT3S6vpn1YrVZqamrIyspqU1BQR4k0tWPP/2k3fktKShy9Hx3pODoT3koDs9Mb9Wg07iQqKoqUlJRGoy+bMvycSUtLIycn57yHeN++fYmIiCAzM5Mbb7zRI8fQUTl27BhnzpxhxIgRXp+pxddYrVZOnjxJcXExcXFxLXo45uXl8dvf/pbBgwfz4IMPEhYWRt++fVm4cCF33XUXTz/9NCNHjvSC9JrW0tagoOLi4g7X5eiM/brWxp/v8OoAERGJFpHLROTntu+25VjQaLxEz549iYqKOscIERECAgJISUlh+PDhJCUlNTmAPyIigsjIyPOWBwQEMGzYsC4zJVxLMJvNrFmzhttvv517772Xe+65hy+//LJDP+jagj0ApSVenrq6Oh5++GEsFgtPP/20IxXHmDFjeO2114iPj2fWrFm89dZbXa4dOwrOQUHNzR/rT4Efmo6Nt7qAEZHfAg8AkRjj/gAqRGSFUmqZt+TQaFqDiNCvXz8OHDjgSCLcnMfPFWlpaWRnZ593087IyGDTpk3U1tZ6LIdWRyEnJ4fHHnuMgwcPMm7cOEaMGMGGDRuYNWsWF198MdOnT+cHP/iBr8X0O1atWsWBAwf43e9+R69evc5Z16tXLzZs2MAjjzzC008/zcGDB3nwwQdbFZWp8R5KKYqKiigrK6Nfv35ERUWdt82ZM2faPZWcUorq6mrOnDnjGNfq/DsyMpIJEybo66ST4xUDUEQeAxYDrwJvAAVAT+AO4DERCVJKLfGGLBpNa7EniS4vLycxMbFVhp+d8PBwoqKizhuMnJ6e7kikOmLECHeJ3KEwm82sX7+e9evXExsby+9+9ztHbsSbbrqJP//5z6xfv57p06czatQoZsyYwfDhw9tVZ319Pf/73//45z//yYkTJ7jpppu46qqr2nRufcnf/vY33n77be68885G80lGRkaycuVKXn75ZTZu3MixY8d45plniIuL866wfO/ZdOUR1xjYpzo8dOgQ8fHx9OrVy3Fd2vNdtrTbNDs7m/fee8+loddYMmT7mLzPP/+cFStW6HPVifGWB3AasFIp9RunZfuBT0SkHPgl584RrNH4FWFhYe320KWlpZGVlXWOFzAjIwMwAkG6ogHY0Os3f/78c1KhhISEcNttt3HTTTfx7rvvsnHjRqZOncpll13G9OnTHYE0LaGmpoYvvviCf/7zn/z73//m7NmzhIaGEhsby8MPP0zfvn25++67uf766wkK8lrnSJs5fPgwy5cv56KLLmLWrFlNbhsYGMjs2bMZOHAgS5cu5a677mLlypUMHjzYS9JCZWUlDz30EPv27WPDhg0MGDDAa3V3RJRSlJaWOlIExcbGcvr06RZnJiguLmbOnDnU1NSQlJTkSGGUkZFBTEwMsbGxxMbGnvc7KiqKv/71ryxdupR77rmH5557jqSkJA8frcYXeOsuFwNsa2Tdx8BML8mh0fiMbt26ER0dTXl5uWNZYmIiPXv27HLjAJvy+rkiLCyMiRMn8rOf/Yw//elPbNq0icmTJ3PFFVcwY8YMhgwZ4nK/0tJSPvvsM3bu3MlXX32FyWQiJiaGK6+8krFjxzJ69GhCQkL45JNP2LBhA0uWLGHNmjXcdddd/PSnP/XbbvmqqioefPBBIiIiePLJJ1tssF5//fX07t2b+fPnM3XqVJYsWcI111zjYWmNSOb77ruPI0eOEBERwYIFC9i0aZPftq+/oJTCYrFw9OhRIiMjqaioaNHYP6vVypIlS6iqqmLTpk2tNrZvvPFGevTowW9+8xumTJnC6tWrG9UxTcfFW0EgXwKXNLLuEtt6jabTk5aWdl5Ua3p6epeaESQnJ4fJkyezdu1arrvuOv70pz+1eDq8bt26MXnyZD744ANmzpzJ7t27mTRpEg8++CC5ubmAMS/q5s2buffee/nxj3/MsmXLyM3NZfz48bzyyits27aNJUuWMHbsWLp160ZgYCDXXnstW7ZsYfXq1XTv3p2nn36am2++mU2bNrV73tbKykp27drFli1bOHnyZLvKAsMoWLZsGSdOnGD58uWOdDEtZdiwYWzatIlBgwbx8MMPs2bNGo9GYh46dIgpU6aQl5fH888/zxNPPMHRo0d55plnPFZnZ8NqtTqmPGsJmzdvZteuXdx///1t9rSOGjWKdevWERAQwLRp0/j888/bVI7Gf/GWB3AO8J5tTuC3+H4M4G3AVOBmEXEYo0opHReu6ZSEhYURGxtLWVmZY1l6ejqffPIJZWVlPhmX5S1a6/VrioiICO655x5uu+02tm7dytatW/n0009JTU11GFmDBw9m2rRpjB07lkGDBjWbTkZEuPzyy/nhD3/IN998w/r163n++efZuHEjt99+OxMmTHA5U4czSilOnTrFnj172Lt3L3v37iU3N9fx4H7ppZeYPHkykydPbrP3680332THjh3Mnj27zaldEhMTWbNmDU8++SRr164lNzeXxx57zO1Jo7/88kuHp/LVV19l0KBBAEyZMoX169czcuRIfvKTn7i1zq5OZmYmL730EldffTXjx49vfocmGDhwIBs3bmTu3LnMmzePBQsWcMstt7hJUo2vEW+EkouI3aBzVZk0WK6UUl4dgDNy5Ej19ddfe7NKTRfGZDKxf/9+h1HwzTffMH36dFavXs3ll1/OyJEjv1FK+TRpW2M6cfDgQSoqKlpdXnNj/dpLeXk5mzdvJicnh0svvZQf/ehHpKSktLvczMxMNmzYwM6dOwkPD+fWW29l0qRJDq9bXV0d2dnZ7N2712H0lZSUAIaResEFFzB8+HBHuqC1a9eybds2kpOTuf/++xk7dmyr8hzu27ePadOmcemll7Jy5cp2T/WmlGLr1q0899xzJCcnM2fOHK6++mq35F786KOPWLp0Kf369eO5556jZ8+ejnX19fXMnDmT7OxsXn/9dfr27dtkWf6sE1lZWY1O9+htKisrmTRpEhaLha1btxId7Z5Ma1VVVSxYsIDPP/+cqVOnMnPmzC6Xn9PfcIdOeMsAXIJr488lSqnHPCfN+WgDUONtjh496pjftbq6mrFjx3LPPfcwffp0v37YtdYAVErx2muv8fLLLxMbG8uCBQva7PXzJbm5uWzcuJHt27cTFBTE2LFjKSgoICsri7q6OgBSU1MZMWIEw4cPZ8SIEfTv399lVPHXX3/NihUrOHz4MGPGjGH+/PnNGkBgpP+YNGkSQUFBvP766257uNtleuaZZzhy5AgXXXQR8+bNY9iwYW0qSynFunXreOWVVxg1ahTPPPOMy0jSwsJCJk6cSGJiIhs3bmzSI+rPOuEvBqBSisWLF7Njxw7WrFnDhRde6Nby6+vreeqpp/jzn//MuHHj+O1vf6vTxPgQd+iEt2YCWeKNejSajkJKSgplZWUopQgPD6d///6dbhyg1WplxYoVvPXWW1x77bU8/PDDbvX6eZOBAweybNkyZsyYwWuvvcY//vEP+vbty+23387w4cO54IILWjwWb+TIkWzZsoW3336bl19+mQkTJnDHHXdw7733NjoLhMVi4ZFHHqGsrIz169e71fizy7R161bef/99XnnlFe666y5uuOEGfvWrX53juWuO+vp6nnzySd5//31uuOEGHnnkkUaNhB49evD4448zZ84cVq5cyaJFi9x1OF2Sjz76iI8//pgZM2a43fgDCAoKYtGiRaSkpPD73/+eoqIiVqxY4TJXYUdn7969vPrqqyQnJzN//vxOa+h6dSYQjUZjEBoaSnx8vON/RkbGOd3CHR2z2czixYt56623uPPOO3niiSdaZfwFBAQ4ZlzxJ9LS0li0aBGffPIJ69evZ+7cuVx11VWtDsQICgpiwoQJvPvuu4wbN47XX390s0PvAAAZ70lEQVSdW2+9lY8//tjlNbBu3Tp27drF/PnzGTp0qLsO5zyZbr31Vt577z0mT57M9u3bGT9+PGvWrGlR4uGqqirmzZvH+++/z7Rp01iyZEmzD87LLruMyZMn895777FtW2OJIjTNYc/t+IMf/IApU6Z4rB4RYerUqSxdupTdu3dzzz33cPr0aY/V520OHTrEvHnzmDp1KpmZmbzzzjvMnj37vPytnQX/urtqNF2IlJQUxzia9PR0ysvLOXHihI+laj81NTU88MADbNu2jV//+tfMnTu3xeOFAgICCAsLY9CgQVx44YX069eP2NhYtxuD9nmcAwMD6datm+O/t0lISODRRx9lw4YNdO/enUceeYTp06dz6NAhxzZffPEFa9eu5YYbbuBnP/uZx2WKjIzk17/+NW+//TZXXnkla9euZfz48Xz00UeNRgsXFRUxbdo0vvrqK8cxtLQ9Z86cyfDhw1m+fDnHjx9356F0Cerq6li0aBEhISEsXbrUK8nMx40bx4svvkhhYSF333032dnZHq/Tkxw/fpxFixYxceJEdu/ezaxZs/jLX/7C448/zt69e5k6dapbIvj9Da+MAfR39BhAja/47rvvKCkp4eDBg9xxxx0sXbqUxYsX++14p+bGAJaXlzNv3jwyMzNZuHBhiyMG7QZeWloaCQkJ5xkP9jQYJSUllJeXIyKtTl0SEBCAUorIyEhiY2OJjo4mNDQUEaGuro6SkhKKioqwWCw+maDeYrHw/vvv89JLL1FRUcHPf/5zbrnlFmbMmEH37t2bHScH3xu29vu6O+7ve/bsYdWqVezfv5+hQ4cyb968c6bkO3z4MHPmzKGiooKnn36aSy+9tNV15OfnM3HiRJKSktiwYQOhoaHnrNdjABtn5cqV/PGPf2TVqlVceeWVXq37yJEjzJ07lzNnzrBs2TJ++MMfuj2JelVVFadPn+b06dPk5eVRXFxM3759GT16dKs97w3Jz8/n1Vdf5cMPPyQ4OJiJEydy5513ntOt/e233zJ//nwCAwNZtWoVF1xwQXsPyS10mCAQf0cbgBpfYTab2bdvH2azmbFjx3LzzTfz5ptv+u3DrikDsLCwkNmzZzvy01199dUtqktE6N69OykpKS3yXrTUGLQbfPbZPmJiYoiIiGjSM2WfI9U+H6u9Pm9SXl7OK6+8wjvvvIPVaiUiIoJNmzbRp0+fJvdzbkelFAUFBRQWFqKUarchaLVa2b59Oy+88AIFBQVcddVVzJkzh4KCAubPn09YWBirV69uV/f0Z599xv3338/Pf/5zHnrooXPWaQPQNf/617+YN28et99+O7/5zW+a38EDFBcXc9999zm8gDExMSQkJBAXF0d8fLzjt6vv0NBQKioqyMvLIz8/n7y8PIexZ/807H51fsEZMGAAo0ePZsyYMVx88cUtTq1UWlrKhg0bePvttwG49dZbmTJlCgkJCS63P3bsGHPnzqW4uJjHHnvMK8nTm0MbgG5CG4AaX3L8+HGKi4uZNm0adXV1ZGZm+u3DrjED8Pjx48yePZszZ86wcuVKLrmksbzv3xMQEEBkZCS9e/c+z+PTUhoag2CMZYuOjiY2NpaoqKg2d4lZrVbKy8spKiqisrISaJtHzbl7uTXGZHZ2NuvWrePmm2/m8ssvb3S7ptrRYrFQVFREfn4+Sql2G7O1tbVs2bKFjRs3YjabAejduzfPP/+8W6YLe/bZZ9myZQtPPfXUOQ9ZbQCeT1FREXfccQc9evRw6TWF7+f1he+vw4Yf5/G29m+TyYTZbG7x9VJdXc327dspKCigrKyMkpISysrKKC0tpbS01KE/DQkODnZcR3a6detGcnJyo5+4uDgOHTrErl27+Oqrr9i9ezd1dXUEBwczYsQIxowZw+jRoxkyZMh5w0YqKirYvHkzW7duxWQyceONNzJt2jSSk5ObPcaysjIeeOAB9u7dy5w5c7jzzjt9mgpHG4BuQhuAGl9i9wKuXr2aN954A7PZ7LcPO1cGYHZ2NnPmzMFqtfL88883mz4kICCAoKAg+vTp49ZoVqvVSn19PSEhIW4r047ZbKa0tJSioiLq6upQSp1j2Nm9bIGBgQQFBREcHExISAihoaEEBwcTHBxMYGCg44Fol7c92Nuxb9++zUZiWq1WSkpKHHPJtrfu4uJi1qxZQ3l5OYsXL3ZbJKjZbObee+/l2LFjbNmyhbS0NEAbgA2xWCzMmjWLzMxMNm/efF4aIbsxl5KSQmJiYqvHzyqlHJ656urqdnuQTSbTOQah/XP27Fni4+NJSUlxGHgxMTGtMqxqa2vZvXs3u3bt4ssvv3SMn42JiWHUqFGMHj2aiy66iE8//ZRNmzZx9uxZrr32WqZPn96i9EsNj2PJkiXs2LGD8ePH8+CDD/ps3vAOkwZGo9E0TnBwMD169CAjI+O8t2F/59tvv2XevHlERkby0ksvNXlDtRtMqampdO/e3e1vzwEBAR4x/sA4Rz179qRnz57U1NRQXl5OYGCgw7gLCQkhKCio2WOKioqiV69elJeXU1hY6JhmrjUP2La0Y0BAAN27dycxMZGysjJOnTpFfX19mw3BxMREj6RtCQ4O5sknn2TSpEksXLiQV1991WPntCPz2muv8fXXX7N48eJzdM7uwUtOTqZ79+5tDpwSEaKjo4mOjqa6uppTp061eB5iV4SGhpKUlOQWL3FDwsLCGDNmDGPGjAGgpKSEr776ii+//JJdu3axY8cOx7aXX345M2fObPO8xqGhoSxfvpy0tDQ2bNhAfn4+TzzxhMs8lx0BbQBqNH5AUlISGRkZvhajVezcuZOFCxeSnJzMiy++2OTNXURISEggNTXVZ2/M7qJbt25069atzfsHBAQQFxdHXFwcdXV1FBcXU1RUhNVqbdYgExESExNJSUlpUzuKCPHx8cTFxXH27FlOnTqFyWTySdBLY6SkpPDoo48yf/58XnjhBR544AFfi+RX7NmzhzVr1nDddddx0003ATgMveTkZHr06OHWiPnw8HAGDRpEbW0t+fn5Dg+2v/YeJiQkMG7cOMaNG4dSiiNHjvC///2PQYMGMWLEiHaXHxAQwKxZs0hNTeXJJ59k2rRpPPvssx4xbj1Nx74TazSdhKCgIIYPH05CQoJjKjF/xj7N15AhQ3j++eeJjY09Z709ACMsLMwxKLytc992ZkJCQhzdX5WVlRQWFroMbAkICCA8PJw+ffq4pR1FhJiYGGJiYqisrOTUqVNUVVU5Btj7+uE+duxYJkyYwB//+MdzIo67OhUVFTzyyCMkJSWxcOFCR1dvUlISPXr08GgKmLCwMPr27Utqair5+fkUFxf7xbXSFCLCgAEDGDBggNvLvuWWW0hKSuKhhx5iypQpPPvssx7L0ekptAGo0fgJycnJZGRksHPnTl+L0iSbN29m9erVjBo1ihUrVhAREXFOxG1MTAzR0dFERkb6XSJnf0VEiIqKIioqCovFQllZGQUFBZhMJoKDg+ndu7fHZlGJjIxkyJAhWK1WampqqK6uprKyksrKSurq6hzntrUP+oYpaYKDgwkLCyMoKIiamhpMJpNjLKWr8ufMmcOePXt47DGvzgzqtyilWL58OYWFhaxbt47o6GjHsARv5P6zExwcTK9evUhJSaGwsJCCggK3BBj5G/Z7V1PHNWbMGNatW8d9993HtGnTeOKJJ7jiiiu8JWK70QagRuMnBAYGMmbMGL81AJVSrFq1ijVr1nDNNdewdOlSoqKiHGOFIiMjvfog6qwEBgaSmJhIYmKiI7rRG9GGAQEBREREEBERQffu3QEcRmFVVRWVlZVUVVWdZxQ6PygDAwMJDQ2lW7duhIeHExYWRmhoKCEhIS6PwWw2U1tbS21tLVVVVdTU1FBbW+vwHj/11FNMnDjR48feHlasWIHJZPJ4PWVlZfz9739nzpw5XHPNNSQlJflU3wIDA0lOTqZnz56OHJpWq/UcQ75hPkpX6wDHteEcWNVwmfN/q9WKxWI5J6DJ1ctmwxcL57LsRquIEBQU5Ajesl+vwcHBKKWoq6vDZDJRV1eH2Wx2REfbyxk8eDAbN25k3rx5PPDAA/z0pz9tdEpHf0NHAQMiUgHk+FiMRKBYy6BlAIYopXw6wabWCS2Dn8mgdcLA1+dBy+A/MrRbJ7QH0CDH1ykGRORrLYOWwV6/r+p2QuuElsFvZNA6YeDr86Bl8B8Z3KETeoCORqPRaDQaTRdDG4AajUaj0Wg0XQxtABr8wdcCoGWwo2Xwff2gZbCjZTDwtQy+rh+0DHa0DAa+lqHd9esgEI1Go9FoNJouhvYAajQajUaj0XQxurwBKCLXi0iOiOSKyMNerPeYiOwTkd32aB4RiReRHSJyyPYd5+Y614tIoYhkOi1rtE4RWWBrlxwR+bGH6l8iIqds7bBbRH7iqfptZfYSkU9FJEtE9ovIXNtyb7ZDYzJ4tS2akK9L6ISv9aEJGbROaJ3oks+IJmTQOuEJnbAnSuyKHyAQOAz0B0KAPcAwL9V9DEhssOwZ4GHb74eBp91c55XAxUBmc3UCw2ztEQr0s7VToAfqXwLMd7Gt2+u3lZsMXGz7HQUctNXlzXZoTAavtkUjsnUZnfC1PjQhg9YJrRNe14cmrketE51UJ7q6B3AUkKuUOqKUqgPeAG72oTw3A6/Zfr8G3OLOwpVSnwGlLazzZuANpZRJKXUUyMVoL3fX3xhur98mw2ml1Le23xVAFpCKd9uhMRkawyNt0QhdRid8rQ9NyNAYWie+p6vqRKd+RjQhQ2NonfieVsvQ1Q3AVOCE0/+TNN3A7kQB20XkGxH5pW1ZT6XUaTBOPtDDC3I0Vqc322a2iOy1uf7tLnWP1y8ifYGLgC/xUTs0kAF81BZOdHWd8Ad9AK0TWif8Qx+aqlPrRAfXia5uALqaYNNbYdE/VEpdDIwDZonIlV6qt6V4q21eBgYAFwKngZXeqF9EIoF3gPuUUmeb2tRTcriQwSdt0VAsL9bVEH/WCW+2i9YJrRPg3/oAWifO2dRTcnhSJ7q6AXgS6OX0Pw3I80bFSqk823ch8B6Gq7ZARJIBbN+FXhClsTq90jZKqQKllEUpZQXW8r3L2mP1i0gwhkJtUUq9a1vs1XZwJYMv2sIFXV0nfKoPoHUCrROA3+gDTdSpdaKD60RXNwD/CwwSkX4iEgJMAD7wdKUiEiEiUfbfwHVApq3uybbNJgPve1qWJur8AJggIqEi0g8YBHzl7srtymTjZxjt4LH6RUSAdUCWUmqV0yqvtUNjMni7LRqhq+uET/UBtE5onfArfaCJOrVOdHSdaCpCpCt8gJ9gRNccBhZ5qc7+GNE6e4D99nqBBOAfwCHbd7yb6/0jhsvYjPG2cE9TdQKLbO2SA4zzUP2vA/uAvbYLONlT9dvKvBzDLb4X2G37/MTL7dCYDF5ti66uE77WB60TWif8SR+0TnQ9ndAzgWg0Go1Go9F0Mbp6F7BGo9FoNBpNl0MbgBqNRqPRaDRdDG0AajQajUaj0XQxtAGo0Wg0Go1G08XQBqBGo9FoNBpNF0MbgBpNB0NElohIm8L3ReQ+ERnvbpk6GiIy1taOAQ2W9xURJSJ3e7BuJSJLnP63+nx2tvMoIh+KyAs+qHeebUot/SzUdDn0Ra/RdDxeBS5t4773AZ3GcGgHY4FHOf8eeBqjbf/iRVnacj47zXm0TXF2LfCUD6p/BWM+18nNbajRdDa0AajRdDCUUieVUrt8LYcdEQn1tQzuQillUkrtUkoVebFOvzqfPuA3wIdKqVPerlgpVQNsAuZ7u26NxtdoA1Cj6WC46jK0dSsuE5E5InJURCpEZKeIpDttcwzoA0yyba9EZKPT+hEi8oGIlIlIjYj8R0SuaFDPRhE5KSKXisjnIlIDPGNbN1FE/icilSJSLiL7RGR6g/1/ISJ7RKRWRIpF5PUGUxshIsdEZLOI3CkiOTZZ/iUig2xTZK0RkRIRKRCRlSIS5LRvmIg8KyKZNjnybd2LQ53bD8P7B2C2t4VtncsuYBH5kYjssB1Xle0Y7mnmPAXazslpEakWkX86nw9neVycz7kikmU79jIR+VpEftbceRSRgbY2PWrb94iIvCwicY2cx4tsbVstIodEZIYL+frZyswXEZOtzOdctM8/bNddlYhsE5GMptrHtl8KMA7Y2lybOMl9zOm//XzNEJEnbTJW2K6fcFt7bLNdC7ki4srT9wYwTEQua05ejaYzEdT8JhqNpoPwC4wpgOYCIcAK4H0RGaqUqseYN/KvGNNLLbHtUwQgIhcD/wL+B0wDqoEZwN9F5DKl1DdO9cRgPDR/BywEakTkcmAz8DyGRycAGArE2ncSkV8Ca4A3gQVACvAEMFpELlZKVTrVcSUwAHjIdiyrMSZFPwLkYszHeiXwCMbUR7+37RcKRAHLMLpz44FfAbts7ZCP0eWahjHF1OWApalGFZGbbXX/B5gOFAPpGEZYUyyxtc8qYDswkhbMISsik4CVwOMY56QbMNx2LNDEecRo05MYXcRlGFOKLbRt37CbORrD8Fptq2sK8LKI5CilPrXJ0g9jPtFqDKP5EMaE89c5yXsDxpyof8G4BsE4b/8SkeFKqRNNHO61QCDw76ZbpVkWAP/E6ModhvFSYgUuAtZiXKszgQ0i8rVSar/TvruBs8D1wOftlEOj6Th4ek5D/dEf/XHvB+OhrxosUxgP52CnZf/Ptvwyp2XHgM0uyvwHkAWEOC0LtC37s9OyjbYyb26w/3ygtAmZA4EC4NMGy+3zXc5pIGMpEOO0bI5tu1cb7P9twzJd1BsOVADzGrYhENRg+7625Xfb/otNnq+BgFacozigEnilwfKHbOUvaex8Ai8C3zZTvsvz6GK7IKc2vsjFebzKaVkohnH7B6dlm2zHkdJEHbnAPxosi7aVtboZ+V4GTrXkGneS+5iL8/VJg+3etS3/RYNzUg886qLcfwHbW3p+9Ud/OsNHdwFrNJ2HHUops9P/fbbv3k3tJCLdgB8BbwFWEQmydasK8HcMT5sz9cBHDZb9F4izdb3dKCKxDdYPwRhsv8V5oVLq38B3tvqd+UIpVe70P9v2va3BdtkYHinn47lNRL4UkTM2WauASJsMrWUIhqfvVaWUtRX7XQBEAH9qsPyNFuz7X+BCEXlBRK4RkfCWVioiISKyUESyxeieN2MYN3D+8Vcrm6cPjPGPGC8RztfLdcBHSqm8RuobhOGp3WK/bmzXTjXwBedfOw1J4XvvZXv4W4P/510vSqkyoJAG14uNIpssGk2XQRuAGk3nobTBf5PtO6yZ/eIxPGWLMQwG589sDMPO+V5RqJQ6p9tUKbUT+DnGw/U9oEhE/i4iw53qAKNbtiH5TuvtlDX4X9fEcsfxichPMbqYs4CJwGjgEowHfHPt4IoE2/fJVu5nH9dY0GB5w/+u2ITRXTkaw4ApFZF3RaRvC/Z9EsN7thm4ARjF99HCDY+/YVuCcc04b5dA08few/a9jvOvnRv5vv0aI4zvr9P20KbrxYkajK52jabLoMcAajSaMxjjpV7CMD7Oo4H3y2XOOqXU28DbIhKJkWblaeBjEUnje+M0ycWuSRhdrO5gApCrlLrbvkBEgjnfwGwpxbbv1FbuZzd0ewLO4816NrejUkphjJVcYwveuA5jTOCbGEZhU0wANimlltkX2M5HWymm6WMvsX0vwPAWN6TOxbKG+/drbKWIBClj/Kqd9hxLU8Tz/bnWaLoE2gOo0XQtTDTwdCilqjC6CUdgjD37uuGnNRUopSqVUh9hGDHJGF6gHAzv1wTnbW2Rl32AnW09oAaEY3T7OnMnhofTGbvXqTmvz0GM8Xb3ioi0Qo69GF3PtzVYPsHFto2ilCpTSr2J0ZXsHFV73nm0EY7hfXNmSmvqbMB24EZpEKntRA5G+6S7um6UUnubKT8b6CVOkdwNcByzbZsftFL+ltIP41g0mi6D9gBqNF2LA8AVInIjRtdrsVLqGHA/8BmwTUTWYXiwEoGLgUCl1MNNFSoij2N4tz4F8jCibOcAu5Utp56I/BbDq7UZo4syFViOMe5sg5uO72PgFhF5FmOc4g9scpxpsN0B2/cDIvI3wOLK0FVKKRG5DyOo4BMReQWjO/n/gB5KqUcb7mPb74xNhkUiUoFhSF2CEXncJCLyB4yglS8wxqwNxjBitzeQ39V5/BiYLCL7MIIzxgPtSW/yKEZX8uci8oStzFTgeqXUL2ztMwsj2jwEw1AtxrgWLgOOK6VWNVH+Z8BjGFHO37pYv15ElmF00d5rq9ssIrcqpd5px3E5sI1XHYwRKazRdBm0B1Cj6VoswPB0/Akj2GAJgFLqWwwDpQQjlct24DmMYIbPWlDulxgRmc8COzC6f3diGA/Y6vgDhiFzAUbakGds2/5InZsCpj2sxTAqbwc+tNX/U6C8wXYfYaSO+RWGofXfxgpUSr2Pka4EjLFuHwC/xPB8NcUSjDQ3d9r2uc4mS3P8B8Nw/T1G+yzCMJidc9i5PI/Ar211LcfoMo4C7mhBnS6xGZWjgV0Y4ws/xkgZU+S0zV8xgj0iMFLsbMM4t0kYbdsU/8J4YWisXV4EXsBIw2MBbsLwfj7eluNphBswuqrfc2OZGo3fI8ZwE41Go9FovI8YibknAYNt4x8dybqVUq3pdm9r/X/D8KDe6em6NBp/QnsANRqNRuNLnsVIGH6rtysWkQuBqzC6oTWaLoU2ADUajUbjM2z5Hu/EmPHF2yQBU5RSuT6oW6PxKboLWKPRaDQajaaLoT2AGo1Go9FoNF0MbQBqNBqNRqPRdDG0AajRaDQajUbTxdAGoEaj0Wg0Gk0XQxuAGo1Go9FoNF0MbQBqNBqNRqPRdDH+P1OKOvDinAV7AAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig,axes = plt.subplots(2, 3, figsize=(10, 5), sharex=True, gridspec_kw={'height_ratios': [1, 4]})\n", "\n", "for i,name in enumerate(profiles):\n", " bin_edges, prop, lower_ci, upper_ci = profiles[name]\n", " \n", " ax = axes[0, i]\n", " dist = distances[name]*1e6\n", " ax.hist(dist, bins=bin_edges*1e6, color=(0.6, 0.7, 0.9))\n", " ax.hist(dist[connected[name]], bins=bin_edges*1e6, color='red')\n", " \n", " xvals = 0.5 * (bin_edges[1:] + bin_edges[:-1])\n", " ax = axes[1, i]\n", " ax.fill_between(xvals*1e6, lower_ci, upper_ci, color=(0.8, 0.8, 0.8))\n", " ax.plot(xvals*1e6, prop, color=(0, 0, 0))\n", " ax.set_ylim(0.001, 0.5)\n", " ax.set_xlim(0, 250)\n", " ax.set_title(name + \"->\" + name, size=18)\n", " \n", "\n", "axes[0,0].set_ylabel('pairs\\nprobed', size=12)\n", "axes[1,0].set_ylabel('proportion connected', size=16)\n", "axes[1,1].set_xlabel('intersomatic distance (µm)', size=16);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The plots above show much more frequent connectivity between pvalb-positive interneurons (in all layers) compared to sst and vip, regardless of the intersomatic distance. " ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.1" } }, "nbformat": 4, "nbformat_minor": 2 }