{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 23. Mixture models\n", "\n", "[Dataset download](https://s3.amazonaws.com/bebi103.caltech.edu/data/singer_transcript_counts.csv)\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "nbsphinx": "hidden", "tags": [] }, "outputs": [], "source": [ "# Colab setup ------------------\n", "import os, sys, subprocess\n", "if \"google.colab\" in sys.modules:\n", " cmd = \"pip install --upgrade polars iqplot bebi103 watermark\"\n", " process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n", " stdout, stderr = process.communicate()\n", " data_path = \"https://s3.amazonaws.com/bebi103.caltech.edu/data/\"\n", "else:\n", " data_path = \"../data/\"\n", "# ------------------------------" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", "
\n", " \n", " Loading BokehJS ...\n", "
\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "'use strict';\n", "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " const force = true;\n", "\n", " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", " root._bokeh_onload_callbacks = [];\n", " root._bokeh_is_loading = undefined;\n", " }\n", "\n", "const JS_MIME_TYPE = 'application/javascript';\n", " const HTML_MIME_TYPE = 'text/html';\n", " const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", " const CLASS_NAME = 'output_bokeh rendered_html';\n", "\n", " /**\n", " * Render data to the DOM node\n", " */\n", " function render(props, node) {\n", " const script = document.createElement(\"script\");\n", " node.appendChild(script);\n", " }\n", "\n", " /**\n", " * Handle when an output is cleared or removed\n", " */\n", " function handleClearOutput(event, handle) {\n", " function drop(id) {\n", " const view = Bokeh.index.get_by_id(id)\n", " if (view != null) {\n", " view.model.document.clear()\n", " Bokeh.index.delete(view)\n", " }\n", " }\n", "\n", " const cell = handle.cell;\n", "\n", " const id = cell.output_area._bokeh_element_id;\n", " const server_id = cell.output_area._bokeh_server_id;\n", "\n", " // Clean up Bokeh references\n", " if (id != null) {\n", " drop(id)\n", " }\n", "\n", " if (server_id !== undefined) {\n", " // Clean up Bokeh references\n", " const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", " cell.notebook.kernel.execute(cmd_clean, {\n", " iopub: {\n", " output: function(msg) {\n", " const id = msg.content.text.trim()\n", " drop(id)\n", " }\n", " }\n", " });\n", " // Destroy server and session\n", " const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", " cell.notebook.kernel.execute(cmd_destroy);\n", " }\n", " }\n", "\n", " /**\n", " * Handle when a new output is added\n", " */\n", " function handleAddOutput(event, handle) {\n", " const output_area = handle.output_area;\n", " const output = handle.output;\n", "\n", " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", " if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n", " return\n", " }\n", "\n", " const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", "\n", " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", " // store reference to embed id on output_area\n", " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", " }\n", " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", " const bk_div = document.createElement(\"div\");\n", " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", " const script_attrs = bk_div.children[0].attributes;\n", " for (let i = 0; i < script_attrs.length; i++) {\n", " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", " }\n", " // store reference to server id on output_area\n", " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", " }\n", " }\n", "\n", " function register_renderer(events, OutputArea) {\n", "\n", " function append_mime(data, metadata, element) {\n", " // create a DOM node to render to\n", " const toinsert = this.create_output_subarea(\n", " metadata,\n", " CLASS_NAME,\n", " EXEC_MIME_TYPE\n", " );\n", " this.keyboard_manager.register_events(toinsert);\n", " // Render to node\n", " const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", " render(props, toinsert[toinsert.length - 1]);\n", " element.append(toinsert);\n", " return toinsert\n", " }\n", "\n", " /* Handle when an output is cleared or removed */\n", " events.on('clear_output.CodeCell', handleClearOutput);\n", " events.on('delete.Cell', handleClearOutput);\n", "\n", " /* Handle when a new output is added */\n", " events.on('output_added.OutputArea', handleAddOutput);\n", "\n", " /**\n", " * Register the mime type and append_mime function with output_area\n", " */\n", " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", " /* Is output safe? */\n", " safe: true,\n", " /* Index of renderer in `output_area.display_order` */\n", " index: 0\n", " });\n", " }\n", "\n", " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", " if (root.Jupyter !== undefined) {\n", " const events = require('base/js/events');\n", " const OutputArea = require('notebook/js/outputarea').OutputArea;\n", "\n", " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", " register_renderer(events, OutputArea);\n", " }\n", " }\n", " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", " root._bokeh_timeout = Date.now() + 5000;\n", " root._bokeh_failed_load = false;\n", " }\n", "\n", " const NB_LOAD_WARNING = {'data': {'text/html':\n", " \"
\\n\"+\n", " \"

\\n\"+\n", " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", " \"

\\n\"+\n", " \"\\n\"+\n", " \"\\n\"+\n", " \"from bokeh.resources import INLINE\\n\"+\n", " \"output_notebook(resources=INLINE)\\n\"+\n", " \"\\n\"+\n", " \"
\"}};\n", "\n", " function display_loaded(error = null) {\n", " const el = document.getElementById(\"cdfd2107-6618-474c-a065-cc9b398a2270\");\n", " if (el != null) {\n", " const html = (() => {\n", " if (typeof root.Bokeh === \"undefined\") {\n", " if (error == null) {\n", " return \"BokehJS is loading ...\";\n", " } else {\n", " return \"BokehJS failed to load.\";\n", " }\n", " } else {\n", " const prefix = `BokehJS ${root.Bokeh.version}`;\n", " if (error == null) {\n", " return `${prefix} successfully loaded.`;\n", " } else {\n", " return `${prefix} encountered errors while loading and may not function as expected.`;\n", " }\n", " }\n", " })();\n", " el.innerHTML = html;\n", "\n", " if (error != null) {\n", " const wrapper = document.createElement(\"div\");\n", " wrapper.style.overflow = \"auto\";\n", " wrapper.style.height = \"5em\";\n", " wrapper.style.resize = \"vertical\";\n", " const content = document.createElement(\"div\");\n", " content.style.fontFamily = \"monospace\";\n", " content.style.whiteSpace = \"pre-wrap\";\n", " content.style.backgroundColor = \"rgb(255, 221, 221)\";\n", " content.textContent = error.stack ?? error.toString();\n", " wrapper.append(content);\n", " el.append(wrapper);\n", " }\n", " } else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(() => display_loaded(error), 100);\n", " }\n", " }\n", "\n", " function run_callbacks() {\n", " try {\n", " root._bokeh_onload_callbacks.forEach(function(callback) {\n", " if (callback != null)\n", " callback();\n", " });\n", " } finally {\n", " delete root._bokeh_onload_callbacks\n", " }\n", " console.debug(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", " function load_libs(css_urls, js_urls, callback) {\n", " if (css_urls == null) css_urls = [];\n", " if (js_urls == null) js_urls = [];\n", "\n", " root._bokeh_onload_callbacks.push(callback);\n", " if (root._bokeh_is_loading > 0) {\n", " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", " }\n", " if (js_urls == null || js_urls.length === 0) {\n", " run_callbacks();\n", " return null;\n", " }\n", " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", "\n", " function on_load() {\n", " root._bokeh_is_loading--;\n", " if (root._bokeh_is_loading === 0) {\n", " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", " run_callbacks()\n", " }\n", " }\n", "\n", " function on_error(url) {\n", " console.error(\"failed to load \" + url);\n", " }\n", "\n", " for (let i = 0; i < css_urls.length; i++) {\n", " const url = css_urls[i];\n", " const element = document.createElement(\"link\");\n", " element.onload = on_load;\n", " element.onerror = on_error.bind(null, url);\n", " element.rel = \"stylesheet\";\n", " element.type = \"text/css\";\n", " element.href = url;\n", " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", " document.body.appendChild(element);\n", " }\n", "\n", " for (let i = 0; i < js_urls.length; i++) {\n", " const url = js_urls[i];\n", " const element = document.createElement('script');\n", " element.onload = on_load;\n", " element.onerror = on_error.bind(null, url);\n", " element.async = false;\n", " element.src = url;\n", " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.head.appendChild(element);\n", " }\n", " };\n", "\n", " function inject_raw_css(css) {\n", " const element = document.createElement(\"style\");\n", " element.appendChild(document.createTextNode(css));\n", " document.body.appendChild(element);\n", " }\n", "\n", " const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.4.1.min.js\", \"https://unpkg.com/@holoviz/panel@1.4.4/dist/panel.min.js\"];\n", " const css_urls = [];\n", "\n", " const inline_js = [ function(Bokeh) {\n", " Bokeh.set_log_level(\"info\");\n", " },\n", "function(Bokeh) {\n", " }\n", " ];\n", "\n", " function run_inline_js() {\n", " if (root.Bokeh !== undefined || force === true) {\n", " try {\n", " for (let i = 0; i < inline_js.length; i++) {\n", " inline_js[i].call(root, root.Bokeh);\n", " }\n", "\n", " } catch (error) {display_loaded(error);throw error;\n", " }if (force === true) {\n", " display_loaded();\n", " }} else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(run_inline_js, 100);\n", " } else if (!root._bokeh_failed_load) {\n", " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", " root._bokeh_failed_load = true;\n", " } else if (force !== true) {\n", " const cell = $(document.getElementById(\"cdfd2107-6618-474c-a065-cc9b398a2270\")).parents('.cell').data().cell;\n", " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", " }\n", " }\n", "\n", " if (root._bokeh_is_loading === 0) {\n", " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", " run_inline_js();\n", " } else {\n", " load_libs(css_urls, js_urls, function() {\n", " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", " run_inline_js();\n", " });\n", " }\n", "}(window));" ], "application/vnd.bokehjs_load.v0+json": "'use strict';\n(function(root) {\n function now() {\n return new Date();\n }\n\n const force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n const NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded(error = null) {\n const el = document.getElementById(\"cdfd2107-6618-474c-a065-cc9b398a2270\");\n if (el != null) {\n const html = (() => {\n if (typeof root.Bokeh === \"undefined\") {\n if (error == null) {\n return \"BokehJS is loading ...\";\n } else {\n return \"BokehJS failed to load.\";\n }\n } else {\n const prefix = `BokehJS ${root.Bokeh.version}`;\n if (error == null) {\n return `${prefix} successfully loaded.`;\n } else {\n return `${prefix} encountered errors while loading and may not function as expected.`;\n }\n }\n })();\n el.innerHTML = html;\n\n if (error != null) {\n const wrapper = document.createElement(\"div\");\n wrapper.style.overflow = \"auto\";\n wrapper.style.height = \"5em\";\n wrapper.style.resize = \"vertical\";\n const content = document.createElement(\"div\");\n content.style.fontFamily = \"monospace\";\n content.style.whiteSpace = \"pre-wrap\";\n content.style.backgroundColor = \"rgb(255, 221, 221)\";\n content.textContent = error.stack ?? error.toString();\n wrapper.append(content);\n el.append(wrapper);\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(() => display_loaded(error), 100);\n }\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.4.1.min.js\", \"https://unpkg.com/@holoviz/panel@1.4.4/dist/panel.min.js\"];\n const css_urls = [];\n\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {\n }\n ];\n\n function run_inline_js() {\n if (root.Bokeh !== undefined || force === true) {\n try {\n for (let i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n\n } catch (error) {display_loaded(error);throw error;\n }if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n const cell = $(document.getElementById(\"cdfd2107-6618-474c-a065-cc9b398a2270\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import warnings\n", "import multiprocessing\n", "\n", "import polars as pl\n", "import numpy as np\n", "import scipy.optimize\n", "import scipy.stats as st\n", "\n", "import bebi103\n", "\n", "import iqplot\n", "\n", "import bokeh.io\n", "bokeh.io.output_notebook()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "In a previous lesson, we explored a Negative-Binomial model for mRNA counts. The data set we used came from [this paper from the Elowitz lab](https://doi.org/10.1016/j.molcel.2014.06.029) and featured smFISH performed in 279 cells for the genes *rex1*, *rest*, *nanog*, and *prdm14*. The data set may be downloaded [here](https://s3.amazonaws.com/bebi103.caltech.edu/data/singer_transcript_counts.csv). " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Multiple cell types?\n", "\n", "While the Negative Binomial model could work for some genes, exploratory data analysis shows an obvious bimodality in the distribution of counts of Rex1 transcripts." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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" const render_items = [{\"docid\":\"b3d0a2b7-58a0-404f-9c8a-e7da8cdaf837\",\"roots\":{\"p1002\":\"fa2c431a-3412-41be-a8d8-152747f5a2f0\"},\"root_ids\":[\"p1002\"]}];\n", " void root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " const timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " clearInterval(timer);\n", " embed_document(root);\n", " } else {\n", " attempts++;\n", " if (attempts > 100) {\n", " clearInterval(timer);\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1002" } }, "output_type": "display_data" } ], "source": [ "df = pl.read_csv(os.path.join(data_path, \"singer_transcript_counts.csv\"), comment_prefix=\"#\")\n", "\n", "p = iqplot.ecdf(\n", " data=df, q=\"Rex1\", x_axis_label=\"Rex1 mRNA count\", conf_int=True\n", ")\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can define a cell type by its expression profile. The bimodality of the ECDF suggests that there are more than one cell types present, since the ECDF clearly does not follow a Negative Binomial distribution." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## A Negative Binomial mixture model\n", "\n", "What is the story for a distribution of mRNA counts coming from more than one cell type? To be concrete, let's say we ahve two cell types, one with one level of bursty expression of the gene of interest, and another with a different level of bursty expression. We would expect the number of mRNA transcripts to be distributed according to a linear combination of negative binomial distributions. Such a linear combination of distributions is called a [mixture model](https://en.wikipedia.org/wiki/Mixture_model). For this mixture model, we can write out the PMF for an individual measurement of $n$ mRNA transcripts as\n", "\n", "\\begin{align}\n", "f(n\\mid \\alpha_1, \\beta_1, \\alpha_2, \\beta_2, w) &= \n", "w\\,\\frac{(n + \\alpha_1 - 1)!}{n!\\,(\\alpha_1-1)!}\\,\\left(\\frac{\\beta_1}{1+\\beta_1}\\right)^{\\alpha_1}\\left(\\frac{1}{1+\\beta_1}\\right)^{n} \\\\[1em]\n", "&\\;\\;\\;\\;+ (1-w) \\,\\frac{(n + \\alpha_2 - 1)!}{n!\\,(\\alpha_2-1)!}\\,\\left(\\frac{\\beta_2}{1+\\beta_2}\\right)^{\\alpha_2}\\left(\\frac{1}{1+\\beta_2}\\right)^{n}.\n", "\\end{align}\n", "\n", "Where, $w$ is the fraction of cells that are of type one (burst size and frequency are determined by $1/\\beta_1$ and $\\alpha_1$), and $1-w$ is the fraction of cells that are of type two. We can write this likelihood more concisely as\n", "\n", "\\begin{align}\n", "&n_i \\sim w \\, \\text{NegBinom}(\\alpha_1, \\beta_1) + (1-w)\\,\\text{NegBinom}(\\alpha_2, \\beta_2) \\; \\forall i, \\\\[1em]\n", "&b_1 = 1/\\beta_1, \\\\[1em]\n", "&b_2 = 1/\\beta_2.\n", "\\end{align}\n", "\n", "(Recall from the last lesson that we are choosing to parametrize the Negative Binomial distributions with the burst size $b$, related to $\\beta$ as $b = 1/\\beta$, so going forward we will use $b_1$ and $b_2$.)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## MLE for a mixture model\n", "\n", "Mixture models offer some unique challenges in modeling. They are revealed by looking at the log likelihood, which I write again here for a single measurement $n$ for clarity.\n", "\n", "\\begin{align}\n", "\\ell(n\\mid \\alpha_1, b_1, \\alpha_2, b_2, w) = \\ln(w\\,x_1 + (1-w)x_2),\n", "\\end{align}\n", "\n", "where\n", "\n", "\\begin{align}\n", "x_i = \\frac{(n + \\alpha_i - 1)!}{n!\\,(\\alpha_i-1)!}\\,\\left(\\frac{1}{1+b_i}\\right)^{\\alpha_i}\\left(\\frac{b_i}{1+b_i}\\right)^{n}.\n", "\\end{align}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The log-sum-exp trick\n", "\n", "While the logarithm of a product is conveniently split, we cannot split the logarithm of a sum. If we compute the sum directly, we will get serious underflow errors for parameters for which the terms $x_1$ or $x_2$ are small. To compute this is a more numerically stable way, we need to use the [log-sum-exp trick](https://en.wikipedia.org/wiki/LogSumExp). To do this, we re-write the $x_i$ as $x_i = \\mathrm{e}^{\\ln x_i}$.\n", "\n", "\\begin{align}\n", "\\ln f(n\\mid \\alpha_1, b_1, \\alpha_2, b_2, w) = \\ln(w\\,\\mathrm{e}^{\\ln x_1} + (1-w)\\mathrm{e}^{\\ln x_2}).\n", "\\end{align}\n", "\n", "For a moment, let us assume that $x_1 > x_2$. Then, we can factor the log likelihood as\n", "\n", "\\begin{align}\n", "\\ln f(n\\mid \\alpha_1, b_1, \\alpha_2, b_2, w) &= \\ln\\left[\\mathrm{e}^{\\ln x_1}\\left(w + (1-w)\\mathrm{e}^{\\ln x_2 - \\ln x_1}\\right)\\right] \\\\[1em]\n", "&= \\ln x_1 + \\ln\\left(w + (1-w)\\mathrm{e}^{\\ln x_2 - \\ln x_1}\\right).\n", "\\end{align}\n", "\n", "Provided $w$ is not too close to zero, the argument of the logarithm of the sum is now of order $w$. So, when computing the log of the sum of weighted probabilities, we should factor out the largest term and then proceed. This is known as the log-sum-exp trick. Conveniently, this is [implemented in Scipy](https://docs.scipy.org/doc/scipy-1.3.3/reference/generated/scipy.special.logsumexp.html) as `scipy.special.logsumexp()`. Be sure to read the docs to understand how this works, and we will use it below in our log-likelihood calculation." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model identifiability\n", "\n", "A **nonidentifiable model** is a model for which we cannot unambiguously determine the parameter values. That is, two or more parameter sets are observationally equivalent. This is the case for this mixture model because of **label switching**. In this mixture model, it is arbitrary which $(\\alpha, b)$ pair we label as $(\\alpha_1, b_1)$ or $(\\alpha_2, b_2)$. We can switch the labels, and also change $w$ to $1-w$, and we have exactly the same log likelihood. You can imagine that if we have a mixture of more than two distributions, the label switching problem gets worse, as we can have various combinations of label switching.\n", "\n", "There is no one way to get around this kind of nonidentifiability (or many other kinds of nonidentifiability, for that matter). Since we are finding a maximum likelihood estimate, and the value of the likelihood is identical upon switching labels, we do not really need to worry about it here, though this could become a problem when computing confidence intervals, since we need to do the MLE calculation many times with different bootstrap sample data sets each time. We will proceed to compute the confidence interval and check to see if the label-switching nonidentifiability presents itself in the results." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The log-likelihood\n", "\n", "With these two considerations in mind, let's code up the log-likelihood." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "def log_like_mix(alpha1, b1, alpha2, b2, w, n):\n", " \"\"\"Log-likeihood of binary Negative Binomial mixture model.\"\"\"\n", " # Enforce w as a probability\n", " if w < 0 or w > 1:\n", " return -np.inf\n", "\n", " # Physical bounds on parameters\n", " if alpha1 < 0 or alpha2 < 0 or b1 < 0 or b2 < 0:\n", " return -np.inf\n", "\n", " # Pieces of log likelihood\n", " logx1 = st.nbinom.logpmf(n, alpha1, 1 / (1 + b1))\n", " logx2 = st.nbinom.logpmf(n, alpha2, 1 / (1 + b2))\n", "\n", " # Multipliers for log-sum-exp\n", " lse_coeffs = np.tile([w, 1 - w], [len(n), 1]).transpose()\n", "\n", " # log-likelihood for each measurement\n", " log_likes = scipy.special.logsumexp(np.vstack([logx1, logx2]), axis=0, b=lse_coeffs)\n", "\n", " return np.sum(log_likes)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Initial guess\n", "\n", "The optimization problem is more difficult now, since we have five parameters. We should provide the best initial guesses we can. To come up with guesses, we note in the ECDF that the second inflection point occurs around a value of the ECDF of 0.2. We thus can guess $w \\approx 0.2$. To get guesses for $\\alpha_1$ and $b_1$, we take the first 20% of the counts and get an MLE using the single-Negative Binomial model. We do the same for the remaining 80% of counts to get guesses for $\\alpha_2$ and $b_2$. To do this, we need to borrow our MLE function from a previous lesson." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "def log_like_iid_nbinom(params, n):\n", " \"\"\"Log likelihood for i.i.d. NBinom measurements, parametrized\n", " by alpha, b=1/beta.\"\"\"\n", " alpha, b = params\n", "\n", " if alpha <= 0 or b <= 0:\n", " return -np.inf\n", "\n", " return np.sum(st.nbinom.logpmf(n, alpha, 1/(1+b)))\n", "\n", "\n", "def mle_iid_nbinom(n):\n", " \"\"\"Perform maximum likelihood estimates for parameters for i.i.d.\n", " NBinom measurements, parametrized by alpha, b=1/beta\"\"\"\n", " with warnings.catch_warnings():\n", " warnings.simplefilter(\"ignore\")\n", "\n", " res = scipy.optimize.minimize(\n", " fun=lambda params, n: -log_like_iid_nbinom(params, n),\n", " x0=np.array([3, 3]),\n", " args=(n,),\n", " method='Powell'\n", " )\n", "\n", " if res.success:\n", " return res.x\n", " else:\n", " raise RuntimeError('Convergence failed with message', res.message)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can now write a function to get an initial guess of the $\\alpha$'s and $b$'s." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "def initial_guess_mix(n, w_guess):\n", " \"\"\"Generate initial guess for mixture model.\"\"\"\n", " n_low = n[n < np.percentile(n, 100 * w_guess)]\n", " n_high = n[n >= np.percentile(n, 100 * w_guess)]\n", " \n", " alpha1, b1 = mle_iid_nbinom(n_low)\n", " alpha2, b2 = mle_iid_nbinom(n_high)\n", " \n", " return alpha1, b1, alpha2, b2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's give it a test run." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2.2311645373503657, 8.87458109227595, 6.5393762491360174, 25.47713821741079)" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Extract the values for Rex1\n", "n = df['Rex1'].to_numpy()\n", "\n", "# Guess for w\n", "w_guess = 0.2\n", "\n", "# Generate initial guess\n", "initial_guess_mix(n, w_guess)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The guesses seem reasonable, so we will proceed using this method of generating initial guesses." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Performing the optimization\n", "\n", "Now we'll code up a function to generate the initial guess, and then perform the optimization. Note that below I have decreased the tolerance down to $10^{-6}$. I found this to be necessary for this problem; the solver would be off by about 5% if I gave it similar, but different, initial guesses. The lower the tolerance, the closer to zero you require the gradient of the log likelihood to be." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "def mle_mix(n, w_guess):\n", " \"\"\"Obtain MLE estimate for parameters for binary mixture \n", " of Negative Binomials.\"\"\"\n", " with warnings.catch_warnings():\n", " warnings.simplefilter(\"ignore\")\n", "\n", " res = scipy.optimize.minimize(\n", " fun=lambda params, n: -log_like_mix(*params, n),\n", " x0=[*initial_guess_mix(n, w_guess), w_guess],\n", " args=(n,),\n", " method='Powell',\n", " tol=1e-6,\n", " )\n", "\n", " if res.success:\n", " return res.x\n", " else:\n", " raise RuntimeError('Convergence failed with message', res.message) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's get our MLE!" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "α1 = 3.497007\n", "b1 = 4.104918\n", "α2 = 5.089626\n", "b2 = 31.810367\n", "w = 0.160422\n" ] } ], "source": [ "popt = mle_mix(n, w_guess)\n", "\n", "# Check out optimal parameters\n", "print('α1 = {0:f}\\nb1 = {1:f}\\nα2 = {2:f}\\nb2 = {3:f}\\nw = {4:f}'.format(*popt))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Comparison to empirical CDF\n", "\n", "Let's now see how the CDFs parametrized by the MLE compare with the ECDF. The theoretical CDF for a mixture model is computed from the weights of each distribution in the mixture. If the CDF from the first Negative Binomial distribution is $F_1(n;\\alpha_1^*,b_1^*)$ and that of the second is $F_2(n;\\alpha_2^*,b_2^*)$, then the theoretical ECDF for the mixture model, parametrized by the MLE, is \n", "\n", "\\begin{align}\n", "F(n;\\alpha_1^*, b_1^*, \\alpha_2^*, b_2^*, w^*) = w^* F_1(n;\\alpha_1^*,b_1^*) + (1-w^*) F_2(n;\\alpha_2^*,b_2^*).\n", "\\end{align}" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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" const render_items = [{\"docid\":\"bd06d877-dc5e-4ed7-b0aa-4345b370d94a\",\"roots\":{\"p1002\":\"f3d3df34-5e23-4cae-9bb9-65b1ba1c7a7b\"},\"root_ids\":[\"p1002\"]}];\n", " void root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " const timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " clearInterval(timer);\n", " embed_document(root);\n", " } else {\n", " attempts++;\n", " if (attempts > 100) {\n", " clearInterval(timer);\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1002" } }, "output_type": "display_data" } ], "source": [ "# Unpack parameters\n", "alpha1_mle, b1_mle, alpha2_mle, b2_mle, w_mle = popt\n", "\n", "n_theor = np.arange(0, n.max()+1)\n", "cdf_theor = w_mle * st.nbinom.cdf(n_theor, alpha1_mle, 1/(1+b1_mle))\n", "cdf_theor += (1 - w_mle) * st.nbinom.cdf(n_theor, alpha2_mle, 1/(1+b2_mle))\n", "\n", "# Weave together to make staircase for discrete distribution\n", "n_plot, cdf_plot = bebi103.viz.cdf_to_staircase(n_theor, cdf_theor)\n", "\n", "p.line(n_plot, cdf_plot, line_color='orange', line_width=2)\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively, and in fact better, we can make a predictive ECDF plot. We will not do that here, as predictive ECDFs are covered in future lessons.\n", "\n", "We can, for comparison, also add the theoretical CDF for the Negative Binomial (non-mixture) model." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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" const render_items = [{\"docid\":\"c2ece3fa-8f1f-4d14-9b89-f7c7735291a2\",\"roots\":{\"p1002\":\"eaa69623-e971-4b41-8e47-175b415dba9b\"},\"root_ids\":[\"p1002\"]}];\n", " void root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " const timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " clearInterval(timer);\n", " embed_document(root);\n", " } else {\n", " attempts++;\n", " if (attempts > 100) {\n", " clearInterval(timer);\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1002" } }, "output_type": "display_data" } ], "source": [ "alpha_mle, b_mle = mle_iid_nbinom(n)\n", "\n", "cdf_theor = st.nbinom.cdf(n_theor, alpha_mle, 1 / (1 + b_mle))\n", "\n", "# Weave together to make staircase for discrete distribution\n", "n_plot, cdf_plot = bebi103.viz.cdf_to_staircase(n_theor, cdf_theor)\n", "\n", "p.line(n_plot, cdf_plot, line_color='tomato', line_width=2)\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will implement graphical methods of model assessment later in this lesson, but it is clear from the crude plot above that the Negative Binomial model is not commensurate with the data, but the mixture model is." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Confidence interval for the mixture model\n", "\n", "Let's now compute a confidence interval for the mixture model. To use `bebi103.bootstrap.draw_bs_reps_mle()`, we need to first write a function to generate data out of the mixture model. To do this, we first draw a random number to see which Negative Binomial distribution to draw the count out of (either the one parametrized with $\\alpha_1$ and $b_1$, or the one parametrized with $\\alpha_2$ and $b_2$). We then draw a count out of the distribution we chose." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "def gen_mix(params, size, rng):\n", " \"\"\"Generate data for the mixture model.\"\"\"\n", " alpha1, b1, alpha2, b2, w = params\n", " \n", " n = np.empty(size)\n", " for i in range(size):\n", " low_cell_type = rng.uniform() < w\n", " \n", " if low_cell_type:\n", " n[i] = rng.negative_binomial(alpha1, 1/(1+b1))\n", " else:\n", " n[i] = rng.negative_binomial(alpha2, 1/(1+b2))\n", " \n", " return n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have this function in hand, we can generate our bootstrap samples (in parallel). This can take a while." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "bs_reps = bebi103.bootstrap.draw_bs_reps_mle(\n", " mle_mix,\n", " gen_mix,\n", " n,\n", " mle_args=(w_guess,),\n", " gen_args=(),\n", " size=10_000,\n", " n_jobs=9,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have the bootstrap samples, we can compute our confidence intervals by taking percentiles. The columns are respectively for $\\alpha_1^*$, $b_1^*$, $\\alpha_2^*$, $b_2^*$, and $w^*$." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 2.00339497, 1.5458858 , 4.16832771, 25.1146269 , 0.11619696],\n", " [ 8.41091976, 8.45923126, 6.45015086, 38.94580183, 0.20824756]])" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.percentile(bs_reps, [2.5, 97.5], axis=0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can visualize the confidence region with a corner plot." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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/BgAAwAYAAMEGAADCBgAAwwYAAMQGAADFBgAAxgYAAMcGAADIBgAAyQYAAMoGAADLBgAAzAYAAM0GAADOBgAAzwYAANAGAADRBgAA0gYAANMGAADUBgAA1QYAANYGAADXBgAA2AYAANkGAADaBgAA2wYAANwGAADdBgAA3gYAAN8GAADgBgAA4QYAAOIGAADjBgAA5AYAAOUGAADmBgAA5wYAAOgGAADpBgAA6gYAAOsGAADsBgAA7QYAAO4GAADvBgAA8AYAAPEGAADyBgAA8wYAAPQGAAD1BgAA9gYAAPcGAAD4BgAA+QYAAPoGAAD7BgAA/AYAAP0GAAD+BgAA/wYAAAAHAAABBwAAAgcAAAMHAAAEBwAABQcAAAYHAAAHBwAACAcAAAkHAAAKBwAACwcAAAwHAAANBwAADgcAAA8HAAAQBwAAEQcAABIHAAATBwAAFAcAABUHAAAWBwAAFwcAABgHAAAZBwAAGgcAABsHAAAcBwAAHQcAAB4HAAAfBwAAIAcAACEHAAAiBwAAIwcAACQHAAAlBwAAJgcAACcHAAAoBwAAKQcAACoHAAArBwAALAcAAC0HAAAuBwAALwcAADAHAAAxBwAAMgcAADMHAAA0BwAANQcAADYHAAA3BwAAOAcAADkHAAA6BwAAOwcAADwHAAA9BwAAPgcAAD8HAABABwAAQQcAAEIHAABDBwAARAcAAEUHAABGBwAARwcAAEgHAABJBwAASgcAAEsHAABMBwAATQcAAE4HAABPBwAAUAcAAFEHAABSBwAAUwcAAFQHAABVBwAAVgcAAFcHAABYBwAAWQcAAFoHAABbBwAAXAcAAF0HAABeBwAAXwcAAGAHAABhBwAAYgcAAGMHAABkBwAAZQcAAGYHAABnBwAAaAcAAGkHAABqBwAAawcAAGwHAABtBwAAbgcAAG8HAABwBwAAcQcAAHIHAABzBwAAdAcAAHUHAAB2BwAAdwcAAHgHAAB5BwAAegcAAHsHAAB8BwAAfQcAAH4HAAB/BwAAgAcAAIEHAACCBwAAgwcAAIQHAACFBwAAhgcAAIcHAACIBwAAiQcAAIoHAACLBwAAjAcAAI0HAACOBwAAjwcAAJAHAACRBwAAkgcAAJMHAACUBwAAlQcAAJYHAACXBwAAmAcAAJkHAACaBwAAmwcAAJwHAACdBwAAngcAAJ8HAACgBwAAoQcAAKIHAACjBwAApAcAAKUHAACmBwAApwcAAKgHAACpBwAAqgcAAKsHAACsBwAArQcAAK4HAACvBwAAsAcAALEHAACyBwAAswcAALQHAAC1BwAAtgcAALcHAAC4BwAAuQcAALoHAAC7BwAAvAcAAL0HAAC+BwAAvwcAAMAHAADBBwAAwgcAAMMHAADEBwAAxQcAAMYHAADHBwAAyAcAAMkHAADKBwAAywcAAMwHAADNBwAAzgcAAM8HAADQBwAA0QcAANIHAADTBwAA1AcAANUHAADWBwAA1wcAANgHAADZBwAA2gcAANsHAADcBwAA3QcAAN4HAADfBwAA4AcAAOEHAADiBwAA4wcAAOQHAADlBwAA5gcAAOcHAADoBwAA6QcAAOoHAADrBwAA7AcAAO0HAADuBwAA7wcAAPAHAADxBwAA8gcAAPMHAAD0BwAA9QcAAPYHAAD3BwAA+AcAAPkHAAD6BwAA+wcAAPwHAAD9BwAA/gcAAP8HAAAACAAAAQgAAAIIAAADCAAABAgAAAUIAAAGCAAABwgAAAgIAAAJCAAACggAAAsIAAAMCAAADQgAAA4IAAAPCAAAEAgAABEIAAASCAAAEwgAABQIAAAVCAAAFggAABcIAAAYCAAAGQgAABoIAAAbCAAAHAgAAB0IAAAeCAAAHwgAACAIAAAhCAAAIggAACMIAAAkCAAAJQgAACYIAAAnCAAAKAgAACkIAAAqCAAAKwgAACwIAAAtCAAALggAAC8IAAAwCAAAMQgAADIIAAAzCAAANAgAADUIAAA2CAAANwgAADgIAAA5CAAAOggAADsIAAA8CAAAPQgAAD4IAAA/CAAAQAgAAEEIAABCCAAAQwgAAEQIAABFCAAARggAAEcIAABICAAASQgAAEoIAABLCAAATAgAAE0IAABOCAAATwgAAFAIAABRCAAAUggAAFMIAABUCAAAVQgAAFYIAABXCAAAWAgAAFkIAABaCAAAWwgAAFwIAABdCAAAXggAAF8IAABgCAAAYQgAAGIIAABjCAAAZAgAAGUIAABmCAAAZwgAAGgIAABpCAAAaggAAGsIAABsCAAAbQgAAG4IAABvCAAAcAgAAHEIAAByCAAAcwgAAHQIAAB1CAAAdggAAHcIAAB4CAAAeQgAAHoIAAB7CAAAfAgAAH0IAAB+CAAAfwgAAIAIAACBCAAAgggAAIMIAACECAAAhQgAAIYIAACHCAAAiAgAAIkIAACKCAAAiwgAAIwIAACNCAAAjggAAI8IAACQCAAAkQgAAJIIAACTCAAAlAgAAJUIAACWCAAAlwgAAJgIAACZCAAAmggAAJsIAACcCAAAnQgAAJ4IAACfCAAAoAgAAKEIAACiCAAAowgAAKQIAAClCAAApggAAKcIAACoCAAAqQgAAKoIAACrCAAArAgAAK0IAACuCAAArwgAALAIAACxCAAAsggAALMIAAC0CAAAtQgAALYIAAC3CAAAuAgAALkIAAC6CAAAuwgAALwIAAC9CAAAvggAAL8IAADACAAAwQgAAMIIAADDCAAAxAgAAMUIAADGCAAAxwgAAMgIAADJCAAAyggAAMsIAADMCAAAzQgAAM4IAADPCAAA0AgAANEIAADSCAAA0wgAANQIAADVCAAA1ggAANcIAADYCAAA2QgAANoIAADbCAAA3AgAAN0IAADeCAAA3wgAAOAIAADhCAAA4ggAAOMIAADkCAAA5QgAAOYIAADnCAAA6AgAAOkIAADqCAAA6wgAAOwIAADtCAAA7ggAAO8IAADwCAAA8QgAAPIIAADzCAAA9AgAAPUIAAD2CAAA9wgAAPgIAAD5CAAA+ggAAPsIAAD8CAAA/QgAAP4IAAD/CAAAAAkAAAEJAAACCQAAAwkAAAQJAAAFCQAABgkAAAcJAAAICQAACQkAAAoJAAALCQAADAkAAA0JAAAOCQAADwkAABAJAAARCQAAEgkAABMJAAAUCQAAFQkAABYJAAAXCQAAGAkAABkJAAAaCQAAGwkAABwJAAAdCQAAHgkAAB8JAAAgCQAAIQkAACIJAAAjCQAAJAkAACUJAAAmCQAAJwkAACgJAAApCQAAKgkAACsJAAAsCQAALQkAAC4JAAAvCQAAMAkAADEJAAAyCQAAMwkAADQJAAA1CQAANgkAADcJAAA4CQAAOQkAADoJAAA7CQAAPAkAAD0JAAA+CQAAPwkAAEAJAABBCQAAQgkAAEMJAABECQAARQkAAEYJAABHCQAASAkAAEkJAABKCQAASwkAAEwJAABNCQAATgkAAE8JAABQCQAAUQkAAFIJAABTCQAAVAkAAFUJAABWCQAAVwkAAFgJAABZCQAAWgkAAFsJAABcCQAAXQkAAF4JAABfCQAAYAkAAGEJAABiCQAAYwkAAGQJAABlCQAAZgkAAGcJAABoCQAAaQkAAGoJAABrCQAAbAkAAG0JAABuCQAAbwkAAHAJAABxCQAAcgkAAHMJAAB0CQAAdQkAAHYJAAB3CQAAeAkAAHkJAAB6CQAAewkAAHwJAAB9CQAAfgkAAH8JAACACQAAgQkAAIIJAACDCQAAhAkAAIUJAACGCQAAhwkAAIgJAACJCQAAigkAAIsJAACMCQAAjQkAAI4JAACPCQAAkAkAAJEJAACSCQAAkwkAAJQJAACVCQAAlgkAAJcJAACYCQAAmQkAAJoJAACbCQAAnAkAAJ0JAACeCQAAnwkAAKAJAAChCQAAogkAAKMJAACkCQAApQkAAKYJAACnCQAAqAkAAKkJAACqCQAAqwkAAKwJAACtCQAArgkAAK8JAACwCQAAsQkAALIJAACzCQAAtAkAALUJAAC2CQAAtwkAALgJAAC5CQAAugkAALsJAAC8CQAAvQkAAL4JAAC/CQAAwAkAAMEJAADCCQAAwwkAAMQJAADFCQAAxgkAAMcJAADICQAAyQkAAMoJAADLCQAAzAkAAM0JAADOCQAAzwkAANAJAADRCQAA0gkAANMJAADUCQAA1QkAANYJAADXCQAA2AkAANkJAADaCQAA2wkAANwJAADdCQAA3gkAAN8JAADgCQAA4QkAAOIJAADjCQAA5AkAAOUJAADmCQAA5wkAAOgJAADpCQAA6gkAAOsJAADsCQAA7QkAAO4JAADvCQAA8AkAAPEJAADyCQAA8wkAAPQJAAD1CQAA9gkAAPcJAAD4CQAA+QkAAPoJAAD7CQAA/AkAAP0JAAD+CQAA/wkAAAAKAAABCgAAAgoAAAMKAAAECgAABQoAAAYKAAAHCgAACAoAAAkKAAAKCgAACwoAAAwKAAANCgAADgoAAA8KAAAQCgAAEQoAABIKAAATCgAAFAoAABUKAAAWCgAAFwoAABgKAAAZCgAAGgoAABsKAAAcCgAAHQoAAB4KAAAfCgAAIAoAACEKAAAiCgAAIwoAACQKAAAlCgAAJgoAACcKAAAoCgAAKQoAACoKAAArCgAALAoAAC0KAAAuCgAALwoAADAKAAAxCgAAMgoAADMKAAA0CgAANQoAADYKAAA3CgAAOAoAADkKAAA6CgAAOwoAADwKAAA9CgAAPgoAAD8KAABACgAAQQoAAEIKAABDCgAARAoAAEUKAABGCgAARwoAAEgKAABJCgAASgoAAEsKAABMCgAATQoAAE4KAABPCgAAUAoAAFEKAABSCgAAUwoAAFQKAABVCgAAVgoAAFcKAABYCgAAWQoAAFoKAABbCgAAXAoAAF0KAABeCgAAXwoAAGAKAABhCgAAYgoAAGMKAABkCgAAZQoAAGYKAABnCgAAaAoAAGkKAABqCgAAawoAAGwKAABtCgAAbgoAAG8KAABwCgAAcQoAAHIKAABzCgAAdAoAAHUKAAB2CgAAdwoAAHgKAAB5CgAAegoAAHsKAAB8CgAAfQoAAH4KAAB/CgAAgAoAAIEKAACCCgAAgwoAAIQKAACFCgAAhgoAAIcKAACICgAAiQoAAIoKAACLCgAAjAoAAI0KAACOCgAAjwoAAJAKAACRCgAAkgoAAJMKAACUCgAAlQoAAJYKAACXCgAAmAoAAJkKAACaCgAAmwoAAJwKAACdCgAAngoAAJ8KAACgCgAAoQoAAKIKAACjCgAApAoAAKUKAACmCgAApwoAAKgKAACpCgAAqgoAAKsKAACsCgAArQoAAK4KAACvCgAAsAoAALEKAACyCgAAswoAALQKAAC1CgAAtgoAALcKAAC4CgAAuQoAALoKAAC7CgAAvAoAAL0KAAC+CgAAvwoAAMAKAADBCgAAwgoAAMMKAADECgAAxQoAAMYKAADHCgAAyAoAAMkKAADKCgAAywoAAMwKAADNCgAAzgoAAM8KAADQCgAA0QoAANIKAADTCgAA1AoAANUKAADWCgAA1woAANgKAADZCgAA2goAANsKAADcCgAA3QoAAN4KAADfCgAA4AoAAOEKAADiCgAA4woAAOQKAADlCgAA5goAAOcKAADoCgAA6QoAAOoKAADrCgAA7AoAAO0KAADuCgAA7woAAPAKAADxCgAA8goAAPMKAAD0CgAA9QoAAPYKAAD3CgAA+AoAAPkKAAD6CgAA+woAAPwKAAD9CgAA/goAAP8KAAAACwAAAQsAAAILAAADCwAABAsAAAULAAAGCwAABwsAAAgLAAAJCwAACgsAAAsLAAAMCwAADQsAAA4LAAAPCwAAEAsAABELAAASCwAAEwsAABQLAAAVCwAAFgsAABcLAAAYCwAAGQsAABoLAAAbCwAAHAsAAB0LAAAeCwAAHwsAACALAAAhCwAAIgsAACMLAAAkCwAAJQsAACYLAAAnCwAAKAsAACkLAAAqCwAAKwsAACwLAAAtCwAALgsAAC8LAAAwCwAAMQsAADILAAAzCwAANAsAADULAAA2CwAANwsAADgLAAA5CwAAOgsAADsLAAA8CwAAPQsAAD4LAAA/CwAAQAsAAEELAABCCwAAQwsAAEQLAABFCwAARgsAAEcLAABICwAASQsAAEoLAABLCwAATAsAAE0LAABOCwAATwsAAFALAABRCwAAUgsAAFMLAABUCwAAVQsAAFYLAABXCwAAWAsAAFkLAABaCwAAWwsAAFwLAABdCwAAXgsAAF8LAABgCwAAYQsAAGILAABjCwAAZAsAAGULAABmCwAAZwsAAGgLAABpCwAAagsAAGsLAABsCwAAbQsAAG4LAABvCwAAcAsAAHELAAByCwAAcwsAAHQLAAB1CwAAdgsAAHcLAAB4CwAAeQsAAHoLAAB7CwAAfAsAAH0LAAB+CwAAfwsAAIALAACBCwAAggsAAIMLAACECwAAhQsAAIYLAACHCwAAiAsAAIkLAACKCwAAiwsAAIwLAACNCwAAjgsAAI8LAACQCwAAkQsAAJILAACTCwAAlAsAAJULAACWCwAAlwsAAJgLAACZCwAAmgsAAJsLAACcCwAAnQsAAJ4LAACfCwAAoAsAAKELAACiCwAAowsAAKQLAAClCwAApgsAAKcLAACoCwAAqQsAAKoLAACrCwAArAsAAK0LAACuCwAArwsAALALAACxCwAAsgsAALMLAAC0CwAAtQsAALYLAAC3CwAAuAsAALkLAAC6CwAAuwsAALwLAAC9CwAAvgsAAL8LAADACwAAwQsAAMILAADDCwAAxAsAAMULAADGCwAAxwsAAMgLAADJCwAAygsAAMsLAADMCwAAzQsAAM4LAADPCwAA0AsAANELAADSCwAA0wsAANQLAADVCwAA1gsAANcLAADYCwAA2QsAANoLAADbCwAA3AsAAN0LAADeCwAA3wsAAOALAADhCwAA4gsAAOMLAADkCwAA5QsAAOYLAADnCwAA6AsAAOkLAADqCwAA6wsAAOwLAADtCwAA7gsAAO8LAADwCwAA8QsAAPILAADzCwAA9AsAAPULAAD2CwAA9wsAAPgLAAD5CwAA+gsAAPsLAAD8CwAA/QsAAP4LAAD/CwAAAAwAAAEMAAACDAAAAwwAAAQMAAAFDAAABgwAAAcMAAAIDAAACQwAAAoMAAALDAAADAwAAA0MAAAODAAADwwAABAMAAARDAAAEgwAABMMAAAUDAAAFQwAABYMAAAXDAAAGAwAABkMAAAaDAAAGwwAABwMAAAdDAAAHgwAAB8MAAAgDAAAIQwAACIMAAAjDAAAJAwAACUMAAAmDAAAJwwAACgMAAApDAAAKgwAACsMAAAsDAAALQwAAC4MAAAvDAAAMAwAADEMAAAyDAAAMwwAADQMAAA1DAAANgwAADcMAAA4DAAAOQwAADoMAAA7DAAAPAwAAD0MAAA+DAAAPwwAAEAMAABBDAAAQgwAAEMMAABEDAAARQwAAEYMAABHDAAASAwAAEkMAABKDAAASwwAAEwMAABNDAAATgwAAE8MAABQDAAAUQwAAFIMAABTDAAAVAwAAFUMAABWDAAAVwwAAFgMAABZDAAAWgwAAFsMAABcDAAAXQwAAF4MAABfDAAAYAwAAGEMAABiDAAAYwwAAGQMAABlDAAAZgwAAGcMAABoDAAAaQwAAGoMAABrDAAAbAwAAG0MAABuDAAAbwwAAHAMAABxDAAAcgwAAHMMAAB0DAAAdQwAAHYMAAB3DAAAeAwAAHkMAAB6DAAAewwAAHwMAAB9DAAAfgwAAH8MAACADAAAgQwAAIIMAACDDAAAhAwAAIUMAACGDAAAhwwAAIgMAACJDAAAigwAAIsMAACMDAAAjQwAAI4MAACPDAAAkAwAAJEMAACSDAAAkwwAAJQMAACVDAAAlgwAAJcMAACYDAAAmQwAAJoMAACbDAAAnAwAAJ0MAACeDAAAnwwAAKAMAAChDAAAogwAAKMMAACkDAAApQwAAKYMAACnDAAAqAwAAKkMAACqDAAAqwwAAKwMAACtDAAArgwAAK8MAACwDAAAsQwAALIMAACzDAAAtAwAALUMAAC2DAAAtwwAALgMAAC5DAAAugwAALsMAAC8DAAAvQwAAL4MAAC/DAAAwAwAAMEMAADCDAAAwwwAAMQMAADFDAAAxgwAAMcMAADIDAAAyQwAAMoMAADLDAAAzAwAAM0MAADODAAAzwwAANAMAADRDAAA0gwAANMMAADUDAAA1QwAANYMAADXDAAA2AwAANkMAADaDAAA2wwAANwMAADdDAAA3gwAAN8MAADgDAAA4QwAAOIMAADjDAAA5AwAAOUMAADmDAAA5wwAAOgMAADpDAAA6gwAAOsMAADsDAAA7QwAAO4MAADvDAAA8AwAAPEMAADyDAAA8wwAAPQMAAD1DAAA9gwAAPcMAAD4DAAA+QwAAPoMAAD7DAAA/AwAAP0MAAD+DAAA/wwAAAANAAABDQAAAg0AAAMNAAAEDQAABQ0AAAYNAAAHDQAACA0AAAkNAAAKDQAACw0AAAwNAAANDQAADg0AAA8NAAAQDQAAEQ0AABINAAATDQAAFA0AABUNAAAWDQAAFw0AABgNAAAZDQAAGg0AABsNAAAcDQAAHQ0AAB4NAAAfDQAAIA0AACENAAAiDQAAIw0AACQNAAAlDQAAJg0AACcNAAAoDQAAKQ0AACoNAAArDQAALA0AAC0NAAAuDQAALw0AADANAAAxDQAAMg0AADMNAAA0DQAANQ0AADYNAAA3DQAAOA0AADkNAAA6DQAAOw0AADwNAAA9DQAAPg0AAD8NAABADQAAQQ0AAEINAABDDQAARA0AAEUNAABGDQAARw0AAEgNAABJDQAASg0AAEsNAABMDQAATQ0AAE4NAABPDQAAUA0AAFENAABSDQAAUw0AAFQNAABVDQAAVg0AAFcNAABYDQAAWQ0AAFoNAABbDQAAXA0AAF0NAABeDQAAXw0AAGANAABhDQAAYg0AAGMNAABkDQAAZQ0AAGYNAABnDQAAaA0AAGkNAABqDQAAaw0AAGwNAABtDQAAbg0AAG8NAABwDQAAcQ0AAHINAABzDQAAdA0AAHUNAAB2DQAAdw0AAHgNAAB5DQAAeg0AAHsNAAB8DQAAfQ0AAH4NAAB/DQAAgA0AAIENAACCDQAAgw0AAIQNAACFDQAAhg0AAIcNAACIDQAAiQ0AAIoNAACLDQAAjA0AAI0NAACODQAAjw0AAJANAACRDQAAkg0AAJMNAACUDQAAlQ0AAJYNAACXDQAAmA0AAJkNAACaDQAAmw0AAJwNAACdDQAAng0AAJ8NAACgDQAAoQ0AAKINAACjDQAApA0AAKUNAACmDQAApw0AAKgNAACpDQAAqg0AAKsNAACsDQAArQ0AAK4NAACvDQAAsA0AALENAACyDQAAsw0AALQNAAC1DQAAtg0AALcNAAC4DQAAuQ0AALoNAAC7DQAAvA0AAL0NAAC+DQAAvw0AAMANAADBDQAAwg0AAMMNAADEDQAAxQ0AAMYNAADHDQAAyA0AAMkNAADKDQAAyw0AAMwNAADNDQAAzg0AAM8NAADQDQAA0Q0AANINAADTDQAA1A0AANUNAADWDQAA1w0AANgNAADZDQAA2g0AANsNAADcDQAA3Q0AAN4NAADfDQAA4A0AAOENAADiDQAA4w0AAOQNAADlDQAA5g0AAOcNAADoDQAA6Q0AAOoNAADrDQAA7A0AAO0NAADuDQAA7w0AAPANAADxDQAA8g0AAPMNAAD0DQAA9Q0AAPYNAAD3DQAA+A0AAPkNAAD6DQAA+w0AAPwNAAD9DQAA/g0AAP8NAAAADgAAAQ4AAAIOAAADDgAABA4AAAUOAAAGDgAABw4AAAgOAAAJDgAACg4AAAsOAAAMDgAADQ4AAA4OAAAPDgAAEA4AABEOAAASDgAAEw4AABQOAAAVDgAAFg4AABcOAAAYDgAAGQ4AABoOAAAbDgAAHA4AAB0OAAAeDgAAHw4AACAOAAAhDgAAIg4AACMOAAAkDgAAJQ4AACYOAAAnDgAAKA4AACkOAAAqDgAAKw4AACwOAAAtDgAALg4AAC8OAAAwDgAAMQ4AADIOAAAzDgAANA4AADUOAAA2DgAANw4AADgOAAA5DgAAOg4AADsOAAA8DgAAPQ4AAD4OAAA/DgAAQA4AAEEOAABCDgAAQw4AAEQOAABFDgAARg4AAEcOAABIDgAASQ4AAEoOAABLDgAATA4AAE0OAABODgAATw4AAFAOAABRDgAAUg4AAFMOAABUDgAAVQ4AAFYOAABXDgAAWA4AAFkOAABaDgAAWw4AAFwOAABdDgAAXg4AAF8OAABgDgAAYQ4AAGIOAABjDgAAZA4AAGUOAABmDgAAZw4AAGgOAABpDgAAag4AAGsOAABsDgAAbQ4AAG4OAABvDgAAcA4AAHEOAAByDgAAcw4AAHQOAAB1DgAAdg4AAHcOAAB4DgAAeQ4AAHoOAAB7DgAAfA4AAH0OAAB+DgAAfw4AAIAOAACBDgAAgg4AAIMOAACEDgAAhQ4AAIYOAACHDgAAiA4AAIkOAACKDgAAiw4AAIwOAACNDgAAjg4AAI8OAACQDgAAkQ4AAJIOAACTDgAAlA4AAJUOAACWDgAAlw4AAJgOAACZDgAAmg4AAJsOAACcDgAAnQ4AAJ4OAACfDgAAoA4AAKEOAACiDgAAow4AAKQOAAClDgAApg4AAKcOAACoDgAAqQ4AAKoOAACrDgAArA4AAK0OAACuDgAArw4AALAOAACxDgAAsg4AALMOAAC0DgAAtQ4AALYOAAC3DgAAuA4AALkOAAC6DgAAuw4AALwOAAC9DgAAvg4AAL8OAADADgAAwQ4AAMIOAADDDgAAxA4AAMUOAADGDgAAxw4AAMgOAADJDgAAyg4AAMsOAADMDgAAzQ4AAM4OAADPDgAA0A4AANEOAADSDgAA0w4AANQOAADVDgAA1g4AANcOAADYDgAA2Q4AANoOAADbDgAA3A4AAN0OAADeDgAA3w4AAOAOAADhDgAA4g4AAOMOAADkDgAA5Q4AAOYOAADnDgAA6A4AAOkOAADqDgAA6w4AAOwOAADtDgAA7g4AAO8OAADwDgAA8Q4AAPIOAADzDgAA9A4AAPUOAAD2DgAA9w4AAPgOAAD5DgAA+g4AAPsOAAD8DgAA/Q4AAP4OAAD/DgAAAA8AAAEPAAACDwAAAw8AAAQPAAAFDwAABg8AAAcPAAAIDwAACQ8AAAoPAAALDwAADA8AAA0PAAAODwAADw8AABAPAAARDwAAEg8AABMPAAAUDwAAFQ8AABYPAAAXDwAAGA8AABkPAAAaDwAAGw8AABwPAAAdDwAAHg8AAB8PAAAgDwAAIQ8AACIPAAAjDwAAJA8AACUPAAAmDwAAJw8AACgPAAApDwAAKg8AACsPAAAsDwAALQ8AAC4PAAAvDwAAMA8AADEPAAAyDwAAMw8AADQPAAA1DwAANg8AADcPAAA4DwAAOQ8AADoPAAA7DwAAPA8AAD0PAAA+DwAAPw8AAEAPAABBDwAAQg8AAEMPAABEDwAARQ8AAEYPAABHDwAASA8AAEkPAABKDwAASw8AAEwPAABNDwAATg8AAE8PAABQDwAAUQ8AAFIPAABTDwAAVA8AAFUPAABWDwAAVw8AAFgPAABZDwAAWg8AAFsPAABcDwAAXQ8AAF4PAABfDwAAYA8AAGEPAABiDwAAYw8AAGQPAABlDwAAZg8AAGcPAABoDwAAaQ8AAGoPAABrDwAAbA8AAG0PAABuDwAAbw8AAHAPAABxDwAAcg8AAHMPAAB0DwAAdQ8AAHYPAAB3DwAAeA8AAHkPAAB6DwAAew8AAHwPAAB9DwAAfg8AAH8PAACADwAAgQ8AAIIPAACDDwAAhA8AAIUPAACGDwAAhw8AAIgPAACJDwAAig8AAIsPAACMDwAAjQ8AAI4PAACPDwAAkA8AAJEPAACSDwAAkw8AAJQPAACVDwAAlg8AAJcPAACYDwAAmQ8AAJoPAACbDwAAnA8AAJ0PAACeDwAAnw8AAKAPAAChDwAAog8AAKMPAACkDwAApQ8AAKYPAACnDwAAqA8AAKkPAACqDwAAqw8AAKwPAACtDwAArg8AAK8PAACwDwAAsQ8AALIPAACzDwAAtA8AALUPAAC2DwAAtw8AALgPAAC5DwAAug8AALsPAAC8DwAAvQ8AAL4PAAC/DwAAwA8AAMEPAADCDwAAww8AAMQPAADFDwAAxg8AAMcPAADIDwAAyQ8AAMoPAADLDwAAzA8AAM0PAADODwAAzw8AANAPAADRDwAA0g8AANMPAADUDwAA1Q8AANYPAADXDwAA2A8AANkPAADaDwAA2w8AANwPAADdDwAA3g8AAN8PAADgDwAA4Q8AAOIPAADjDwAA5A8AAOUPAADmDwAA5w8AAOgPAADpDwAA6g8AAOsPAADsDwAA7Q8AAO4PAADvDwAA8A8AAPEPAADyDwAA8w8AAPQPAAD1DwAA9g8AAPcPAAD4DwAA+Q8AAPoPAAD7DwAA/A8AAP0PAAD+DwAA/w8AAAAQAAABEAAAAhAAAAMQAAAEEAAABRAAAAYQAAAHEAAACBAAAAkQAAAKEAAACxAAAAwQAAANEAAADhAAAA8QAAAQEAAAERAAABIQAAATEAAAFBAAABUQAAAWEAAAFxAAABgQAAAZEAAAGhAAABsQAAAcEAAAHRAAAB4QAAAfEAAAIBAAACEQAAAiEAAAIxAAACQQAAAlEAAAJhAAACcQAAAoEAAAKRAAACoQAAArEAAALBAAAC0QAAAuEAAALxAAADAQAAAxEAAAMhAAADMQAAA0EAAANRAAADYQAAA3EAAAOBAAADkQAAA6EAAAOxAAADwQAAA9EAAAPhAAAD8QAABAEAAAQRAAAEIQAABDEAAARBAAAEUQAABGEAAARxAAAEgQAABJEAAAShAAAEsQAABMEAAATRAAAE4QAABPEAAAUBAAAFEQAABSEAAAUxAAAFQQAABVEAAAVhAAAFcQAABYEAAAWRAAAFoQAABbEAAAXBAAAF0QAABeEAAAXxAAAGAQAABhEAAAYhAAAGMQAABkEAAAZRAAAGYQAABnEAAAaBAAAGkQAABqEAAAaxAAAGwQAABtEAAAbhAAAG8QAABwEAAAcRAAAHIQAABzEAAAdBAAAHUQAAB2EAAAdxAAAHgQAAB5EAAAehAAAHsQAAB8EAAAfRAAAH4QAAB/EAAAgBAAAIEQAACCEAAAgxAAAIQQAACFEAAAhhAAAIcQAACIEAAAiRAAAIoQAACLEAAAjBAAAI0QAACOEAAAjxAAAJAQAACREAAAkhAAAJMQAACUEAAAlRAAAJYQAACXEAAAmBAAAJkQAACaEAAAmxAAAJwQAACdEAAAnhAAAJ8QAACgEAAAoRAAAKIQAACjEAAApBAAAKUQAACmEAAApxAAAKgQAACpEAAAqhAAAKsQAACsEAAArRAAAK4QAACvEAAAsBAAALEQAACyEAAAsxAAALQQAAC1EAAAthAAALcQAAC4EAAAuRAAALoQAAC7EAAAvBAAAL0QAAC+EAAAvxAAAMAQAADBEAAAwhAAAMMQAADEEAAAxRAAAMYQAADHEAAAyBAAAMkQAADKEAAAyxAAAMwQAADNEAAAzhAAAM8QAADQEAAA0RAAANIQAADTEAAA1BAAANUQAADWEAAA1xAAANgQAADZEAAA2hAAANsQAADcEAAA3RAAAN4QAADfEAAA4BAAAOEQAADiEAAA4xAAAOQQAADlEAAA5hAAAOcQAADoEAAA6RAAAOoQAADrEAAA7BAAAO0QAADuEAAA7xAAAPAQAADxEAAA8hAAAPMQAAD0EAAA9RAAAPYQAAD3EAAA+BAAAPkQAAD6EAAA+xAAAPwQAAD9EAAA/hAAAP8QAAAAEQAAAREAAAIRAAADEQAABBEAAAURAAAGEQAABxEAAAgRAAAJEQAAChEAAAsRAAAMEQAADREAAA4RAAAPEQAAEBEAABERAAASEQAAExEAABQRAAAVEQAAFhEAABcRAAAYEQAAGREAABoRAAAbEQAAHBEAAB0RAAAeEQAAHxEAACARAAAhEQAAIhEAACMRAAAkEQAAJREAACYRAAAnEQAAKBEAACkRAAAqEQAAKxEAACwRAAAtEQAALhEAAC8RAAAwEQAAMREAADIRAAAzEQAANBEAADURAAA2EQAANxEAADgRAAA5EQAAOhEAADsRAAA8EQAAPREAAD4RAAA/EQAAQBEAAEERAABCEQAAQxEAAEQRAABFEQAARhEAAEcRAABIEQAASREAAEoRAABLEQAATBEAAE0RAABOEQAATxEAAFARAABREQAAUhEAAFMRAABUEQAAVREAAFYRAABXEQAAWBEAAFkRAABaEQAAWxEAAFwRAABdEQAAXhEAAF8RAABgEQAAYREAAGIRAABjEQAAZBEAAGURAABmEQAAZxEAAGgRAABpEQAAahEAAGsRAABsEQAAbREAAG4RAABvEQAAcBEAAHERAAByEQAAcxEAAHQRAAB1EQAAdhEAAHcRAAB4EQAAeREAAHoRAAB7EQAAfBEAAH0RAAB+EQAAfxEAAIARAACBEQAAghEAAIMRAACEEQAAhREAAIYRAACHEQAAiBEAAIkRAACKEQAAixEAAIwRAACNEQAAjhEAAI8RAACQEQAAkREAAJIRAACTEQAAlBEAAJURAACWEQAAlxEAAJgRAACZEQAAmhEAAJsRAACcEQAAnREAAJ4RAACfEQAAoBEAAKERAACiEQAAoxEAAKQRAAClEQAAphEAAKcRAACoEQAAqREAAKoRAACrEQAArBEAAK0RAACuEQAArxEAALARAACxEQAAshEAALMRAAC0EQAAtREAALYRAAC3EQAAuBEAALkRAAC6EQAAuxEAALwRAAC9EQAAvhEAAL8RAADAEQAAwREAAMIRAADDEQAAxBEAAMURAADGEQAAxxEAAMgRAADJEQAAyhEAAMsRAADMEQAAzREAAM4RAADPEQAA0BEAANERAADSEQAA0xEAANQRAADVEQAA1hEAANcRAADYEQAA2REAANoRAADbEQAA3BEAAN0RAADeEQAA3xEAAOARAADhEQAA4hEAAOMRAADkEQAA5REAAOYRAADnEQAA6BEAAOkRAADqEQAA6xEAAOwRAADtEQAA7hEAAO8RAADwEQAA8REAAPIRAADzEQAA9BEAAPURAAD2EQAA9xEAAPgRAAD5EQAA+hEAAPsRAAD8EQAA/REAAP4RAAD/EQAAABIAAAESAAACEgAAAxIAAAQSAAAFEgAABhIAAAcSAAAIEgAACRIAAAoSAAALEgAADBIAAA0SAAAOEgAADxIAABASAAAREgAAEhIAABMSAAAUEgAAFRIAABYSAAAXEgAAGBIAABkSAAAaEgAAGxIAABwSAAAdEgAAHhIAAB8SAAAgEgAAIRIAACISAAAjEgAAJBIAACUSAAAmEgAAJxIAACgSAAApEgAAKhIAACsSAAAsEgAALRIAAC4SAAAvEgAAMBIAADESAAAyEgAAMxIAADQSAAA1EgAANhIAADcSAAA4EgAAORIAADoSAAA7EgAAPBIAAD0SAAA+EgAAPxIAAEASAABBEgAAQhIAAEMSAABEEgAARRIAAEYSAABHEgAASBIAAEkSAABKEgAASxIAAEwSAABNEgAAThIAAE8SAABQEgAAURIAAFISAABTEgAAVBIAAFUSAABWEgAAVxIAAFgSAABZEgAAWhIAAFsSAABcEgAAXRIAAF4SAABfEgAAYBIAAGESAABiEgAAYxIAAGQSAABlEgAAZhIAAGcSAABoEgAAaRIAAGoSAABrEgAAbBIAAG0SAABuEgAAbxIAAHASAABxEgAAchIAAHMSAAB0EgAAdRIAAHYSAAB3EgAAeBIAAHkSAAB6EgAAexIAAHwSAAB9EgAAfhIAAH8SAACAEgAAgRIAAIISAACDEgAAhBIAAIUSAACGEgAAhxIAAIgSAACJEgAAihIAAIsSAACMEgAAjRIAAI4SAACPEgAAkBIAAJESAACSEgAAkxIAAJQSAACVEgAAlhIAAJcSAACYEgAAmRIAAJoSAACbEgAAnBIAAJ0SAACeEgAAnxIAAKASAAChEgAAohIAAKMSAACkEgAApRIAAKYSAACnEgAAqBIAAKkSAACqEgAAqxIAAKwSAACtEgAArhIAAK8SAACwEgAAsRIAALISAACzEgAAtBIAALUSAAC2EgAAtxIAALgSAAC5EgAAuhIAALsSAAC8EgAAvRIAAL4SAAC/EgAAwBIAAMESAADCEgAAwxIAAMQSAADFEgAAxhIAAMcSAADIEgAAyRIAAMoSAADLEgAAzBIAAM0SAADOEgAAzxIAANASAADREgAA0hIAANMSAADUEgAA1RIAANYSAADXEgAA2BIAANkSAADaEgAA2xIAANwSAADdEgAA3hIAAN8SAADgEgAA4RIAAOISAADjEgAA5BIAAOUSAADmEgAA5xIAAOgSAADpEgAA6hIAAOsSAADsEgAA7RIAAO4SAADvEgAA8BIAAPESAADyEgAA8xIAAPQSAAD1EgAA9hIAAPcSAAD4EgAA+RIAAPoSAAD7EgAA/BIAAP0SAAD+EgAA/xIAAAATAAABEwAAAhMAAAMTAAAEEwAABRMAAAYTAAAHEwAACBMAAAkTAAAKEwAACxMAAAwTAAANEwAADhMAAA8TAAAQEwAAERMAABITAAATEwAAFBMAABUTAAAWEwAAFxMAABgTAAAZEwAAGhMAABsTAAAcEwAAHRMAAB4TAAAfEwAAIBMAACETAAAiEwAAIxMAACQTAAAlEwAAJhMAACcTAAAoEwAAKRMAACoTAAArEwAALBMAAC0TAAAuEwAALxMAADATAAAxEwAAMhMAADMTAAA0EwAANRMAADYTAAA3EwAAOBMAADkTAAA6EwAAOxMAADwTAAA9EwAAPhMAAD8TAABAEwAAQRMAAEITAABDEwAARBMAAEUTAABGEwAARxMAAEgTAABJEwAAShMAAEsTAABMEwAATRMAAE4TAABPEwAAUBMAAFETAABSEwAAUxMAAFQTAABVEwAAVhMAAFcTAABYEwAAWRMAAFoTAABbEwAAXBMAAF0TAABeEwAAXxMAAGATAABhEwAAYhMAAGMTAABkEwAAZRMAAGYTAABnEwAAaBMAAGkTAABqEwAAaxMAAGwTAABtEwAAbhMAAG8TAABwEwAAcRMAAHITAABzEwAAdBMAAHUTAAB2EwAAdxMAAHgTAAB5EwAAehMAAHsTAAB8EwAAfRMAAH4TAAB/EwAAgBMAAIETAACCEwAAgxMAAIQTAACFEwAAhhMAAIcTAACIEwAAiRMAAIoTAACLEwAAjBMAAI0TAACOEwAAjxMAAJATAACREwAAkhMAAJMTAACUEwAAlRMAAJYTAACXEwAAmBMAAJkTAACaEwAAmxMAAJwTAACdEwAAnhMAAJ8TAACgEwAAoRMAAKITAACjEwAApBMAAKUTAACmEwAApxMAAKgTAACpEwAAqhMAAKsTAACsEwAArRMAAK4TAACvEwAAsBMAALETAACyEwAAsxMAALQTAAC1EwAAthMAALcTAAC4EwAAuRMAALoTAAC7EwAAvBMAAL0TAAC+EwAAvxMAAMATAADBEwAAwhMAAMMTAADEEwAAxRMAAMYTAADHEwAAyBMAAMkTAADKEwAAyxMAAMwTAADNEwAAzhMAAM8TAADQEwAA0RMAANITAADTEwAA1BMAANUTAADWEwAA1xMAANgTAADZEwAA2hMAANsTAADcEwAA3RMAAN4TAADfEwAA4BMAAOETAADiEwAA4xMAAOQTAADlEwAA5hMAAOcTAADoEwAA6RMAAOoTAADrEwAA7BMAAO0TAADuEwAA7xMAAPATAADxEwAA8hMAAPMTAAD0EwAA9RMAAPYTAAD3EwAA+BMAAPkTAAD6EwAA+xMAAPwTAAD9EwAA/hMAAP8TAAAAFAAAARQAAAIUAAADFAAABBQAAAUUAAAGFAAABxQAAAgUAAAJFAAAChQAAAsUAAAMFAAADRQAAA4UAAAPFAAAEBQAABEUAAASFAAAExQAABQUAAAVFAAAFhQAABcUAAAYFAAAGRQAABoUAAAbFAAAHBQAAB0UAAAeFAAAHxQAACAUAAAhFAAAIhQAACMUAAAkFAAAJRQAACYUAAAnFAAAKBQAACkUAAAqFAAAKxQAACwUAAAtFAAALhQAAC8UAAAwFAAAMRQAADIUAAAzFAAANBQAADUUAAA2FAAANxQAADgUAAA5FAAAOhQAADsUAAA8FAAAPRQAAD4UAAA/FAAAQBQAAEEUAABCFAAAQxQAAEQUAABFFAAARhQAAEcUAABIFAAASRQAAEoUAABLFAAATBQAAE0UAABOFAAATxQAAFAUAABRFAAAUhQAAFMUAABUFAAAVRQAAFYUAABXFAAAWBQAAFkUAABaFAAAWxQAAFwUAABdFAAAXhQAAF8UAABgFAAAYRQAAGIUAABjFAAAZBQAAGUUAABmFAAAZxQAAGgUAABpFAAAahQAAGsUAABsFAAAbRQAAG4UAABvFAAAcBQAAHEUAAByFAAAcxQAAHQUAAB1FAAAdhQAAHcUAAB4FAAAeRQAAHoUAAB7FAAAfBQAAH0UAAB+FAAAfxQAAIAUAACBFAAAghQAAIMUAACEFAAAhRQAAIYUAACHFAAAiBQAAIkUAACKFAAAixQAAIwUAACNFAAAjhQAAI8UAACQFAAAkRQAAJIUAACTFAAAlBQAAJUUAACWFAAAlxQAAJgUAACZFAAAmhQAAJsUAACcFAAAnRQAAJ4UAACfFAAAoBQAAKEUAACiFAAAoxQAAKQUAAClFAAAphQAAKcUAACoFAAAqRQAAKoUAACrFAAArBQAAK0UAACuFAAArxQAALAUAACxFAAAshQAALMUAAC0FAAAtRQAALYUAAC3FAAAuBQAALkUAAC6FAAAuxQAALwUAAC9FAAAvhQAAL8UAADAFAAAwRQAAMIUAADDFAAAxBQAAMUUAADGFAAAxxQAAMgUAADJFAAAyhQAAMsUAADMFAAAzRQAAM4UAADPFAAA0BQAANEUAADSFAAA0xQAANQUAADVFAAA1hQAANcUAADYFAAA2RQAANoUAADbFAAA3BQAAN0UAADeFAAA3xQAAOAUAADhFAAA4hQAAOMUAADkFAAA5RQAAOYUAADnFAAA6BQAAOkUAADqFAAA6xQAAOwUAADtFAAA7hQAAO8UAADwFAAA8RQAAPIUAADzFAAA9BQAAPUUAAD2FAAA9xQAAPgUAAD5FAAA+hQAAPsUAAD8FAAA/RQAAP4UAAD/FAAAABUAAAEVAAACFQAAAxUAAAQVAAAFFQAABhUAAAcVAAAIFQAACRUAAAoVAAALFQAADBUAAA0VAAAOFQAADxUAABAVAAARFQAAEhUAABMVAAAUFQAAFRUAABYVAAAXFQAAGBUAABkVAAAaFQAAGxUAABwVAAAdFQAAHhUAAB8VAAAgFQAAIRUAACIVAAAjFQAAJBUAACUVAAAmFQAAJxUAACgVAAApFQAAKhUAACsVAAAsFQAALRUAAC4VAAAvFQAAMBUAADEVAAAyFQAAMxUAADQVAAA1FQAANhUAADcVAAA4FQAAORUAADoVAAA7FQAAPBUAAD0VAAA+FQAAPxUAAEAVAABBFQAAQhUAAEMVAABEFQAARRUAAEYVAABHFQAASBUAAEkVAABKFQAASxUAAEwVAABNFQAAThUAAE8VAABQFQAAURUAAFIVAABTFQAAVBUAAFUVAABWFQAAVxUAAFgVAABZFQAAWhUAAFsVAABcFQAAXRUAAF4VAABfFQAAYBUAAGEVAABiFQAAYxUAAGQVAABlFQAAZhUAAGcVAABoFQAAaRUAAGoVAABrFQAAbBUAAG0VAABuFQAAbxUAAHAVAABxFQAAchUAAHMVAAB0FQAAdRUAAHYVAAB3FQAAeBUAAHkVAAB6FQAAexUAAHwVAAB9FQAAfhUAAH8VAACAFQAAgRUAAIIVAACDFQAAhBUAAIUVAACGFQAAhxUAAIgVAACJFQAAihUAAIsVAACMFQAAjRUAAI4VAACPFQAAkBUAAJEVAACSFQAAkxUAAJQVAACVFQAAlhUAAJcVAACYFQAAmRUAAJoVAACbFQAAnBUAAJ0VAACeFQAAnxUAAKAVAAChFQAAohUAAKMVAACkFQAApRUAAKYVAACnFQAAqBUAAKkVAACqFQAAqxUAAKwVAACtFQAArhUAAK8VAACwFQAAsRUAALIVAACzFQAAtBUAALUVAAC2FQAAtxUAALgVAAC5FQAAuhUAALsVAAC8FQAAvRUAAL4VAAC/FQAAwBUAAMEVAADCFQAAwxUAAMQVAADFFQAAxhUAAMcVAADIFQAAyRUAAMoVAADLFQAAzBUAAM0VAADOFQAAzxUAANAVAADRFQAA0hUAANMVAADUFQAA1RUAANYVAADXFQAA2BUAANkVAADaFQAA2xUAANwVAADdFQAA3hUAAN8VAADgFQAA4RUAAOIVAADjFQAA5BUAAOUVAADmFQAA5xUAAOgVAADpFQAA6hUAAOsVAADsFQAA7RUAAO4VAADvFQAA8BUAAPEVAADyFQAA8xUAAPQVAAD1FQAA9hUAAPcVAAD4FQAA+RUAAPoVAAD7FQAA/BUAAP0VAAD+FQAA/xUAAAAWAAABFgAAAhYAAAMWAAAEFgAABRYAAAYWAAAHFgAACBYAAAkWAAAKFgAACxYAAAwWAAANFgAADhYAAA8WAAAQFgAAERYAABIWAAATFgAAFBYAABUWAAAWFgAAFxYAABgWAAAZFgAAGhYAABsWAAAcFgAAHRYAAB4WAAAfFgAAIBYAACEWAAAiFgAAIxYAACQWAAAlFgAAJhYAACcWAAAoFgAAKRYAACoWAAArFgAALBYAAC0WAAAuFgAALxYAADAWAAAxFgAAMhYAADMWAAA0FgAANRYAADYWAAA3FgAAOBYAADkWAAA6FgAAOxYAADwWAAA9FgAAPhYAAD8WAABAFgAAQRYAAEIWAABDFgAARBYAAEUWAABGFgAARxYAAEgWAABJFgAAShYAAEsWAABMFgAATRYAAE4WAABPFgAAUBYAAFEWAABSFgAAUxYAAFQWAABVFgAAVhYAAFcWAABYFgAAWRYAAFoWAABbFgAAXBYAAF0WAABeFgAAXxYAAGAWAABhFgAAYhYAAGMWAABkFgAAZRYAAGYWAABnFgAAaBYAAGkWAABqFgAAaxYAAGwWAABtFgAAbhYAAG8WAABwFgAAcRYAAHIWAABzFgAAdBYAAHUWAAB2FgAAdxYAAHgWAAB5FgAAehYAAHsWAAB8FgAAfRYAAH4WAAB/FgAAgBYAAIEWAACCFgAAgxYAAIQWAACFFgAAhhYAAIcWAACIFgAAiRYAAIoWAACLFgAAjBYAAI0WAACOFgAAjxYAAJAWAACRFgAAkhYAAJMWAACUFgAAlRYAAJYWAACXFgAAmBYAAJkWAACaFgAAmxYAAJwWAACdFgAAnhYAAJ8WAACgFgAAoRYAAKIWAACjFgAApBYAAKUWAACmFgAApxYAAKgWAACpFgAAqhYAAKsWAACsFgAArRYAAK4WAACvFgAAsBYAALEWAACyFgAAsxYAALQWAAC1FgAAthYAALcWAAC4FgAAuRYAALoWAAC7FgAAvBYAAL0WAAC+FgAAvxYAAMAWAADBFgAAwhYAAMMWAADEFgAAxRYAAMYWAADHFgAAyBYAAMkWAADKFgAAyxYAAMwWAADNFgAAzhYAAM8WAADQFgAA0RYAANIWAADTFgAA1BYAANUWAADWFgAA1xYAANgWAADZFgAA2hYAANsWAADcFgAA3RYAAN4WAADfFgAA4BYAAOEWAADiFgAA4xYAAOQWAADlFgAA5hYAAOcWAADoFgAA6RYAAOoWAADrFgAA7BYAAO0WAADuFgAA7xYAAPAWAADxFgAA8hYAAPMWAAD0FgAA9RYAAPYWAAD3FgAA+BYAAPkWAAD6FgAA+xYAAPwWAAD9FgAA/hYAAP8WAAAAFwAAARcAAAIXAAADFwAABBcAAAUXAAAGFwAABxcAAAgXAAAJFwAAChcAAAsXAAAMFwAADRcAAA4XAAAPFwAAEBcAABEXAAASFwAAExcAABQXAAAVFwAAFhcAABcXAAAYFwAAGRcAABoXAAAbFwAAHBcAAB0XAAAeFwAAHxcAACAXAAAhFwAAIhcAACMXAAAkFwAAJRcAACYXAAAnFwAAKBcAACkXAAAqFwAAKxcAACwXAAAtFwAALhcAAC8XAAAwFwAAMRcAADIXAAAzFwAANBcAADUXAAA2FwAANxcAADgXAAA5FwAAOhcAADsXAAA8FwAAPRcAAD4XAAA/FwAAQBcAAEEXAABCFwAAQxcAAEQXAABFFwAARhcAAEcXAABIFwAASRcAAEoXAABLFwAATBcAAE0XAABOFwAATxcAAFAXAABRFwAAUhcAAFMXAABUFwAAVRcAAFYXAABXFwAAWBcAAFkXAABaFwAAWxcAAFwXAABdFwAAXhcAAF8XAABgFwAAYRcAAGIXAABjFwAAZBcAAGUXAABmFwAAZxcAAGgXAABpFwAAahcAAGsXAABsFwAAbRcAAG4XAABvFwAAcBcAAHEXAAByFwAAcxcAAHQXAAB1FwAAdhcAAHcXAAB4FwAAeRcAAHoXAAB7FwAAfBcAAH0XAAB+FwAAfxcAAIAXAACBFwAAghcAAIMXAACEFwAAhRcAAIYXAACHFwAAiBcAAIkXAACKFwAAixcAAIwXAACNFwAAjhcAAI8XAACQFwAAkRcAAJIXAACTFwAAlBcAAJUXAACWFwAAlxcAAJgXAACZFwAAmhcAAJsXAACcFwAAnRcAAJ4XAACfFwAAoBcAAKEXAACiFwAAoxcAAKQXAAClFwAAphcAAKcXAACoFwAAqRcAAKoXAACrFwAArBcAAK0XAACuFwAArxcAALAXAACxFwAAshcAALMXAAC0FwAAtRcAALYXAAC3FwAAuBcAALkXAAC6FwAAuxcAALwXAAC9FwAAvhcAAL8XAADAFwAAwRcAAMIXAADDFwAAxBcAAMUXAADGFwAAxxcAAMgXAADJFwAAyhcAAMsXAADMFwAAzRcAAM4XAADPFwAA0BcAANEXAADSFwAA0xcAANQXAADVFwAA1hcAANcXAADYFwAA2RcAANoXAADbFwAA3BcAAN0XAADeFwAA3xcAAOAXAADhFwAA4hcAAOMXAADkFwAA5RcAAOYXAADnFwAA6BcAAOkXAADqFwAA6xcAAOwXAADtFwAA7hcAAO8XAADwFwAA8RcAAPIXAADzFwAA9BcAAPUXAAD2FwAA9xcAAPgXAAD5FwAA+hcAAPsXAAD8FwAA/RcAAP4XAAD/FwAAABgAAAEYAAACGAAAAxgAAAQYAAAFGAAABhgAAAcYAAAIGAAACRgAAAoYAAALGAAADBgAAA0YAAAOGAAADxgAABAYAAARGAAAEhgAABMYAAAUGAAAFRgAABYYAAAXGAAAGBgAABkYAAAaGAAAGxgAABwYAAAdGAAAHhgAAB8YAAAgGAAAIRgAACIYAAAjGAAAJBgAACUYAAAmGAAAJxgAACgYAAApGAAAKhgAACsYAAAsGAAALRgAAC4YAAAvGAAAMBgAADEYAAAyGAAAMxgAADQYAAA1GAAANhgAADcYAAA4GAAAORgAADoYAAA7GAAAPBgAAD0YAAA+GAAAPxgAAEAYAABBGAAAQhgAAEMYAABEGAAARRgAAEYYAABHGAAASBgAAEkYAABKGAAASxgAAEwYAABNGAAAThgAAE8YAABQGAAAURgAAFIYAABTGAAAVBgAAFUYAABWGAAAVxgAAFgYAABZGAAAWhgAAFsYAABcGAAAXRgAAF4YAABfGAAAYBgAAGEYAABiGAAAYxgAAGQYAABlGAAAZhgAAGcYAABoGAAAaRgAAGoYAABrGAAAbBgAAG0YAABuGAAAbxgAAHAYAABxGAAAchgAAHMYAAB0GAAAdRgAAHYYAAB3GAAAeBgAAHkYAAB6GAAAexgAAHwYAAB9GAAAfhgAAH8YAACAGAAAgRgAAIIYAACDGAAAhBgAAIUYAACGGAAAhxgAAIgYAACJGAAAihgAAIsYAACMGAAAjRgAAI4YAACPGAAAkBgAAJEYAACSGAAAkxgAAJQYAACVGAAAlhgAAJcYAACYGAAAmRgAAJoYAACbGAAAnBgAAJ0YAACeGAAAnxgAAKAYAAChGAAAohgAAKMYAACkGAAApRgAAKYYAACnGAAAqBgAAKkYAACqGAAAqxgAAKwYAACtGAAArhgAAK8YAACwGAAAsRgAALIYAACzGAAAtBgAALUYAAC2GAAAtxgAALgYAAC5GAAAuhgAALsYAAC8GAAAvRgAAL4YAAC/GAAAwBgAAMEYAADCGAAAwxgAAMQYAADFGAAAxhgAAMcYAADIGAAAyRgAAMoYAADLGAAAzBgAAM0YAADOGAAAzxgAANAYAADRGAAA0hgAANMYAADUGAAA1RgAANYYAADXGAAA2BgAANkYAADaGAAA2xgAANwYAADdGAAA3hgAAN8YAADgGAAA4RgAAOIYAADjGAAA5BgAAOUYAADmGAAA5xgAAOgYAADpGAAA6hgAAOsYAADsGAAA7RgAAO4YAADvGAAA8BgAAPEYAADyGAAA8xgAAPQYAAD1GAAA9hgAAPcYAAD4GAAA+RgAAPoYAAD7GAAA/BgAAP0YAAD+GAAA/xgAAAAZAAABGQAAAhkAAAMZAAAEGQAABRkAAAYZAAAHGQAACBkAAAkZAAAKGQAACxkAAAwZAAANGQAADhkAAA8ZAAAQGQAAERkAABIZAAATGQAAFBkAABUZAAAWGQAAFxkAABgZAAAZGQAAGhkAABsZAAAcGQAAHRkAAB4ZAAAfGQAAIBkAACEZAAAiGQAAIxkAACQZAAAlGQAAJhkAACcZAAAoGQAAKRkAACoZAAArGQAALBkAAC0ZAAAuGQAALxkAADAZAAAxGQAAMhkAADMZAAA0GQAANRkAADYZAAA3GQAAOBkAADkZAAA6GQAAOxkAADwZAAA9GQAAPhkAAD8ZAABAGQAAQRkAAEIZAABDGQAARBkAAEUZAABGGQAARxkAAEgZAABJGQAAShkAAEsZAABMGQAATRkAAE4ZAABPGQAAUBkAAFEZAABSGQAAUxkAAFQZAABVGQAAVhkAAFcZAABYGQAAWRkAAFoZAABbGQAAXBkAAF0ZAABeGQAAXxkAAGAZAABhGQAAYhkAAGMZAABkGQAAZRkAAGYZAABnGQAAaBkAAGkZAABqGQAAaxkAAGwZAABtGQAAbhkAAG8ZAABwGQAAcRkAAHIZAABzGQAAdBkAAHUZAAB2GQAAdxkAAHgZAAB5GQAAehkAAHsZAAB8GQAAfRkAAH4ZAAB/GQAAgBkAAIEZAACCGQAAgxkAAIQZAACFGQAAhhkAAIcZAACIGQAAiRkAAIoZAACLGQAAjBkAAI0ZAACOGQAAjxkAAJAZAACRGQAAkhkAAJMZAACUGQAAlRkAAJYZAACXGQAAmBkAAJkZAACaGQAAmxkAAJwZAACdGQAAnhkAAJ8ZAACgGQAAoRkAAKIZAACjGQAApBkAAKUZAACmGQAApxkAAKgZAACpGQAAqhkAAKsZAACsGQAArRkAAK4ZAACvGQAAsBkAALEZAACyGQAAsxkAALQZAAC1GQAAthkAALcZAAC4GQAAuRkAALoZAAC7GQAAvBkAAL0ZAAC+GQAAvxkAAMAZAADBGQAAwhkAAMMZAADEGQAAxRkAAMYZAADHGQAAyBkAAMkZAADKGQAAyxkAAMwZAADNGQAAzhkAAM8ZAADQGQAA0RkAANIZAADTGQAA1BkAANUZAADWGQAA1xkAANgZAADZGQAA2hkAANsZAADcGQAA3RkAAN4ZAADfGQAA4BkAAOEZAADiGQAA4xkAAOQZAADlGQAA5hkAAOcZAADoGQAA6RkAAOoZAADrGQAA7BkAAO0ZAADuGQAA7xkAAPAZAADxGQAA8hkAAPMZAAD0GQAA9RkAAPYZAAD3GQAA+BkAAPkZAAD6GQAA+xkAAPwZAAD9GQAA/hkAAP8ZAAAAGgAAARoAAAIaAAADGgAABBoAAAUaAAAGGgAABxoAAAgaAAAJGgAAChoAAAsaAAAMGgAADRoAAA4aAAAPGgAAEBoAABEaAAASGgAAExoAABQaAAAVGgAAFhoAABcaAAAYGgAAGRoAABoaAAAbGgAAHBoAAB0aAAAeGgAAHxoAACAaAAAhGgAAIhoAACMaAAAkGgAAJRoAACYaAAAnGgAAKBoAACkaAAAqGgAAKxoAACwaAAAtGgAALhoAAC8aAAAwGgAAMRoAADIaAAAzGgAANBoAADUaAAA2GgAANxoAADgaAAA5GgAAOhoAADsaAAA8GgAAPRoAAD4aAAA/GgAAQBoAAEEaAABCGgAAQxoAAEQaAABFGgAARhoAAEcaAABIGgAASRoAAEoaAABLGgAATBoAAE0aAABOGgAATxoAAFAaAABRGgAAUhoAAFMaAABUGgAAVRoAAFYaAABXGgAAWBoAAFkaAABaGgAAWxoAAFwaAABdGgAAXhoAAF8aAABgGgAAYRoAAGIaAABjGgAAZBoAAGUaAABmGgAAZxoAAGgaAABpGgAAahoAAGsaAABsGgAAbRoAAG4aAABvGgAAcBoAAHEaAAByGgAAcxoAAHQaAAB1GgAAdhoAAHcaAAB4GgAAeRoAAHoaAAB7GgAAfBoAAH0aAAB+GgAAfxoAAIAaAACBGgAAghoAAIMaAACEGgAAhRoAAIYaAACHGgAAiBoAAIkaAACKGgAAixoAAIwaAACNGgAAjhoAAI8aAACQGgAAkRoAAJIaAACTGgAAlBoAAJUaAACWGgAAlxoAAJgaAACZGgAAmhoAAJsaAACcGgAAnRoAAJ4aAACfGgAAoBoAAKEaAACiGgAAoxoAAKQaAAClGgAAphoAAKcaAACoGgAAqRoAAKoaAACrGgAArBoAAK0aAACuGgAArxoAALAaAACxGgAAshoAALMaAAC0GgAAtRoAALYaAAC3GgAAuBoAALkaAAC6GgAAuxoAALwaAAC9GgAAvhoAAL8aAADAGgAAwRoAAMIaAADDGgAAxBoAAMUaAADGGgAAxxoAAMgaAADJGgAAyhoAAMsaAADMGgAAzRoAAM4aAADPGgAA0BoAANEaAADSGgAA0xoAANQaAADVGgAA1hoAANcaAADYGgAA2RoAANoaAADbGgAA3BoAAN0aAADeGgAA3xoAAOAaAADhGgAA4hoAAOMaAADkGgAA5RoAAOYaAADnGgAA6BoAAOkaAADqGgAA6xoAAOwaAADtGgAA7hoAAO8aAADwGgAA8RoAAPIaAADzGgAA9BoAAPUaAAD2GgAA9xoAAPgaAAD5GgAA+hoAAPsaAAD8GgAA/RoAAP4aAAD/GgAAABsAAAEbAAACGwAAAxsAAAQbAAAFGwAABhsAAAcbAAAIGwAACRsAAAobAAALGwAADBsAAA0bAAAOGwAADxsAABAbAAARGwAAEhsAABMbAAAUGwAAFRsAABYbAAAXGwAAGBsAABkbAAAaGwAAGxsAABwbAAAdGwAAHhsAAB8bAAAgGwAAIRsAACIbAAAjGwAAJBsAACUbAAAmGwAAJxsAACgbAAApGwAAKhsAACsbAAAsGwAALRsAAC4bAAAvGwAAMBsAADEbAAAyGwAAMxsAADQbAAA1GwAANhsAADcbAAA4GwAAORsAADobAAA7GwAAPBsAAD0bAAA+GwAAPxsAAEAbAABBGwAAQhsAAEMbAABEGwAARRsAAEYbAABHGwAASBsAAEkbAABKGwAASxsAAEwbAABNGwAAThsAAE8bAABQGwAAURsAAFIbAABTGwAAVBsAAFUbAABWGwAAVxsAAFgbAABZGwAAWhsAAFsbAABcGwAAXRsAAF4bAABfGwAAYBsAAGEbAABiGwAAYxsAAGQbAABlGwAAZhsAAGcbAABoGwAAaRsAAGobAABrGwAAbBsAAG0bAABuGwAAbxsAAHAbAABxGwAAchsAAHMbAAB0GwAAdRsAAHYbAAB3GwAAeBsAAHkbAAB6GwAAexsAAHwbAAB9GwAAfhsAAH8bAACAGwAAgRsAAIIbAACDGwAAhBsAAIUbAACGGwAAhxsAAIgbAACJGwAAihsAAIsbAACMGwAAjRsAAI4bAACPGwAAkBsAAJEbAACSGwAAkxsAAJQbAACVGwAAlhsAAJcbAACYGwAAmRsAAJobAACbGwAAnBsAAJ0bAACeGwAAnxsAAKAbAAChGwAAohsAAKMbAACkGwAApRsAAKYbAACnGwAAqBsAAKkbAACqGwAAqxsAAKwbAACtGwAArhsAAK8bAACwGwAAsRsAALIbAACzGwAAtBsAALUbAAC2GwAAtxsAALgbAAC5GwAAuhsAALsbAAC8GwAAvRsAAL4bAAC/GwAAwBsAAMEbAADCGwAAwxsAAMQbAADFGwAAxhsAAMcbAADIGwAAyRsAAMobAADLGwAAzBsAAM0bAADOGwAAzxsAANAbAADRGwAA0hsAANMbAADUGwAA1RsAANYbAADXGwAA2BsAANkbAADaGwAA2xsAANwbAADdGwAA3hsAAN8bAADgGwAA4RsAAOIbAADjGwAA5BsAAOUbAADmGwAA5xsAAOgbAADpGwAA6hsAAOsbAADsGwAA7RsAAO4bAADvGwAA8BsAAPEbAADyGwAA8xsAAPQbAAD1GwAA9hsAAPcbAAD4GwAA+RsAAPobAAD7GwAA/BsAAP0bAAD+GwAA/xsAAAAcAAABHAAAAhwAAAMcAAAEHAAABRwAAAYcAAAHHAAACBwAAAkcAAAKHAAACxwAAAwcAAANHAAADhwAAA8cAAAQHAAAERwAABIcAAATHAAAFBwAABUcAAAWHAAAFxwAABgcAAAZHAAAGhwAABscAAAcHAAAHRwAAB4cAAAfHAAAIBwAACEcAAAiHAAAIxwAACQcAAAlHAAAJhwAACccAAAoHAAAKRwAACocAAArHAAALBwAAC0cAAAuHAAALxwAADAcAAAxHAAAMhwAADMcAAA0HAAANRwAADYcAAA3HAAAOBwAADkcAAA6HAAAOxwAADwcAAA9HAAAPhwAAD8cAABAHAAAQRwAAEIcAABDHAAARBwAAEUcAABGHAAARxwAAEgcAABJHAAAShwAAEscAABMHAAATRwAAE4cAABPHAAAUBwAAFEcAABSHAAAUxwAAFQcAABVHAAAVhwAAFccAABYHAAAWRwAAFocAABbHAAAXBwAAF0cAABeHAAAXxwAAGAcAABhHAAAYhwAAGMcAABkHAAAZRwAAGYcAABnHAAAaBwAAGkcAABqHAAAaxwAAGwcAABtHAAAbhwAAG8cAABwHAAAcRwAAHIcAABzHAAAdBwAAHUcAAB2HAAAdxwAAHgcAAB5HAAAehwAAHscAAB8HAAAfRwAAH4cAAB/HAAAgBwAAIEcAACCHAAAgxwAAIQcAACFHAAAhhwAAIccAACIHAAAiRwAAIocAACLHAAAjBwAAI0cAACOHAAAjxwAAJAcAACRHAAAkhwAAJMcAACUHAAAlRwAAJYcAACXHAAAmBwAAJkcAACaHAAAmxwAAJwcAACdHAAAnhwAAJ8cAACgHAAAoRwAAKIcAACjHAAApBwAAKUcAACmHAAApxwAAKgcAACpHAAAqhwAAKscAACsHAAArRwAAK4cAACvHAAAsBwAALEcAACyHAAAsxwAALQcAAC1HAAAthwAALccAAC4HAAAuRwAALocAAC7HAAAvBwAAL0cAAC+HAAAvxwAAMAcAADBHAAAwhwAAMMcAADEHAAAxRwAAMYcAADHHAAAyBwAAMkcAADKHAAAyxwAAMwcAADNHAAAzhwAAM8cAADQHAAA0RwAANIcAADTHAAA1BwAANUcAADWHAAA1xwAANgcAADZHAAA2hwAANscAADcHAAA3RwAAN4cAADfHAAA4BwAAOEcAADiHAAA4xwAAOQcAADlHAAA5hwAAOccAADoHAAA6RwAAOocAADrHAAA7BwAAO0cAADuHAAA7xwAAPAcAADxHAAA8hwAAPMcAAD0HAAA9RwAAPYcAAD3HAAA+BwAAPkcAAD6HAAA+xwAAPwcAAD9HAAA/hwAAP8cAAAAHQAAAR0AAAIdAAADHQAABB0AAAUdAAAGHQAABx0AAAgdAAAJHQAACh0AAAsdAAAMHQAADR0AAA4dAAAPHQAAEB0AABEdAAASHQAAEx0AABQdAAAVHQAAFh0AABcdAAAYHQAAGR0AABodAAAbHQAAHB0AAB0dAAAeHQAAHx0AACAdAAAhHQAAIh0AACMdAAAkHQAAJR0AACYdAAAnHQAAKB0AACkdAAAqHQAAKx0AACwdAAAtHQAALh0AAC8dAAAwHQAAMR0AADIdAAAzHQAANB0AADUdAAA2HQAANx0AADgdAAA5HQAAOh0AADsdAAA8HQAAPR0AAD4dAAA/HQAAQB0AAEEdAABCHQAAQx0AAEQdAABFHQAARh0AAEcdAABIHQAASR0AAEodAABLHQAATB0AAE0dAABOHQAATx0AAFAdAABRHQAAUh0AAFMdAABUHQAAVR0AAFYdAABXHQAAWB0AAFkdAABaHQAAWx0AAFwdAABdHQAAXh0AAF8dAABgHQAAYR0AAGIdAABjHQAAZB0AAGUdAABmHQAAZx0AAGgdAABpHQAAah0AAGsdAABsHQAAbR0AAG4dAABvHQAAcB0AAHEdAAByHQAAcx0AAHQdAAB1HQAAdh0AAHcdAAB4HQAAeR0AAHodAAB7HQAAfB0AAH0dAAB+HQAAfx0AAIAdAACBHQAAgh0AAIMdAACEHQAAhR0AAIYdAACHHQAAiB0AAIkdAACKHQAAix0AAIwdAACNHQAAjh0AAI8dAACQHQAAkR0AAJIdAACTHQAAlB0AAJUdAACWHQAAlx0AAJgdAACZHQAAmh0AAJsdAACcHQAAnR0AAJ4dAACfHQAAoB0AAKEdAACiHQAAox0AAKQdAAClHQAAph0AAKcdAACoHQAAqR0AAKodAACrHQAArB0AAK0dAACuHQAArx0AALAdAACxHQAAsh0AALMdAAC0HQAAtR0AALYdAAC3HQAAuB0AALkdAAC6HQAAux0AALwdAAC9HQAAvh0AAL8dAADAHQAAwR0AAMIdAADDHQAAxB0AAMUdAADGHQAAxx0AAMgdAADJHQAAyh0AAMsdAADMHQAAzR0AAM4dAADPHQAA0B0AANEdAADSHQAA0x0AANQdAADVHQAA1h0AANcdAADYHQAA2R0AANodAADbHQAA3B0AAN0dAADeHQAA3x0AAOAdAADhHQAA4h0AAOMdAADkHQAA5R0AAOYdAADnHQAA6B0AAOkdAADqHQAA6x0AAOwdAADtHQAA7h0AAO8dAADwHQAA8R0AAPIdAADzHQAA9B0AAPUdAAD2HQAA9x0AAPgdAAD5HQAA+h0AAPsdAAD8HQAA/R0AAP4dAAD/HQAAAB4AAAEeAAACHgAAAx4AAAQeAAAFHgAABh4AAAceAAAIHgAACR4AAAoeAAALHgAADB4AAA0eAAAOHgAADx4AABAeAAARHgAAEh4AABMeAAAUHgAAFR4AABYeAAAXHgAAGB4AABkeAAAaHgAAGx4AABweAAAdHgAAHh4AAB8eAAAgHgAAIR4AACIeAAAjHgAAJB4AACUeAAAmHgAAJx4AACgeAAApHgAAKh4AACseAAAsHgAALR4AAC4eAAAvHgAAMB4AADEeAAAyHgAAMx4AADQeAAA1HgAANh4AADceAAA4HgAAOR4AADoeAAA7HgAAPB4AAD0eAAA+HgAAPx4AAEAeAABBHgAAQh4AAEMeAABEHgAARR4AAEYeAABHHgAASB4AAEkeAABKHgAASx4AAEweAABNHgAATh4AAE8eAABQHgAAUR4AAFIeAABTHgAAVB4AAFUeAABWHgAAVx4AAFgeAABZHgAAWh4AAFseAABcHgAAXR4AAF4eAABfHgAAYB4AAGEeAABiHgAAYx4AAGQeAABlHgAAZh4AAGceAABoHgAAaR4AAGoeAABrHgAAbB4AAG0eAABuHgAAbx4AAHAeAABxHgAAch4AAHMeAAB0HgAAdR4AAHYeAAB3HgAAeB4AAHkeAAB6HgAAex4AAHweAAB9HgAAfh4AAH8eAACAHgAAgR4AAIIeAACDHgAAhB4AAIUeAACGHgAAhx4AAIgeAACJHgAAih4AAIseAACMHgAAjR4AAI4eAACPHgAAkB4AAJEeAACSHgAAkx4AAJQeAACVHgAAlh4AAJceAACYHgAAmR4AAJoeAACbHgAAnB4AAJ0eAACeHgAAnx4AAKAeAAChHgAAoh4AAKMeAACkHgAApR4AAKYeAACnHgAAqB4AAKkeAACqHgAAqx4AAKweAACtHgAArh4AAK8eAACwHgAAsR4AALIeAACzHgAAtB4AALUeAAC2HgAAtx4AALgeAAC5HgAAuh4AALseAAC8HgAAvR4AAL4eAAC/HgAAwB4AAMEeAADCHgAAwx4AAMQeAADFHgAAxh4AAMceAADIHgAAyR4AAMoeAADLHgAAzB4AAM0eAADOHgAAzx4AANAeAADRHgAA0h4AANMeAADUHgAA1R4AANYeAADXHgAA2B4AANkeAADaHgAA2x4AANweAADdHgAA3h4AAN8eAADgHgAA4R4AAOIeAADjHgAA5B4AAOUeAADmHgAA5x4AAOgeAADpHgAA6h4AAOseAADsHgAA7R4AAO4eAADvHgAA8B4AAPEeAADyHgAA8x4AAPQeAAD1HgAA9h4AAPceAAD4HgAA+R4AAPoeAAD7HgAA/B4AAP0eAAD+HgAA/x4AAAAfAAABHwAAAh8AAAMfAAAEHwAABR8AAAYfAAAHHwAACB8AAAkfAAAKHwAACx8AAAwfAAANHwAADh8AAA8fAAAQHwAAER8AABIfAAATHwAAFB8AABUfAAAWHwAAFx8AABgfAAAZHwAAGh8AABsfAAAcHwAAHR8AAB4fAAAfHwAAIB8AACEfAAAiHwAAIx8AACQfAAAlHwAAJh8AACcfAAAoHwAAKR8AACofAAArHwAALB8AAC0fAAAuHwAALx8AADAfAAAxHwAAMh8AADMfAAA0HwAANR8AADYfAAA3HwAAOB8AADkfAAA6HwAAOx8AADwfAAA9HwAAPh8AAD8fAABAHwAAQR8AAEIfAABDHwAARB8AAEUfAABGHwAARx8AAEgfAABJHwAASh8AAEsfAABMHwAATR8AAE4fAABPHwAAUB8AAFEfAABSHwAAUx8AAFQfAABVHwAAVh8AAFcfAABYHwAAWR8AAFofAABbHwAAXB8AAF0fAABeHwAAXx8AAGAfAABhHwAAYh8AAGMfAABkHwAAZR8AAGYfAABnHwAAaB8AAGkfAABqHwAAax8AAGwfAABtHwAAbh8AAG8fAABwHwAAcR8AAHIfAABzHwAAdB8AAHUfAAB2HwAAdx8AAHgfAAB5HwAAeh8AAHsfAAB8HwAAfR8AAH4fAAB/HwAAgB8AAIEfAACCHwAAgx8AAIQfAACFHwAAhh8AAIcfAACIHwAAiR8AAIofAACLHwAAjB8AAI0fAACOHwAAjx8AAJAfAACRHwAAkh8AAJMfAACUHwAAlR8AAJYfAACXHwAAmB8AAJkfAACaHwAAmx8AAJwfAACdHwAAnh8AAJ8fAACgHwAAoR8AAKIfAACjHwAApB8AAKUfAACmHwAApx8AAKgfAACpHwAAqh8AAKsfAACsHwAArR8AAK4fAACvHwAAsB8AALEfAACyHwAAsx8AALQfAAC1HwAAth8AALcfAAC4HwAAuR8AALofAAC7HwAAvB8AAL0fAAC+HwAAvx8AAMAfAADBHwAAwh8AAMMfAADEHwAAxR8AAMYfAADHHwAAyB8AAMkfAADKHwAAyx8AAMwfAADNHwAAzh8AAM8fAADQHwAA0R8AANIfAADTHwAA1B8AANUfAADWHwAA1x8AANgfAADZHwAA2h8AANsfAADcHwAA3R8AAN4fAADfHwAA4B8AAOEfAADiHwAA4x8AAOQfAADlHwAA5h8AAOcfAADoHwAA6R8AAOofAADrHwAA7B8AAO0fAADuHwAA7x8AAPAfAADxHwAA8h8AAPMfAAD0HwAA9R8AAPYfAAD3HwAA+B8AAPkfAAD6HwAA+x8AAPwfAAD9HwAA/h8AAP8fAAAAIAAAASAAAAIgAAADIAAABCAAAAUgAAAGIAAAByAAAAggAAAJIAAACiAAAAsgAAAMIAAADSAAAA4gAAAPIAAAECAAABEgAAASIAAAEyAAABQgAAAVIAAAFiAAABcgAAAYIAAAGSAAABogAAAbIAAAHCAAAB0gAAAeIAAAHyAAACAgAAAhIAAAIiAAACMgAAAkIAAAJSAAACYgAAAnIAAAKCAAACkgAAAqIAAAKyAAACwgAAAtIAAALiAAAC8gAAAwIAAAMSAAADIgAAAzIAAANCAAADUgAAA2IAAANyAAADggAAA5IAAAOiAAADsgAAA8IAAAPSAAAD4gAAA/IAAAQCAAAEEgAABCIAAAQyAAAEQgAABFIAAARiAAAEcgAABIIAAASSAAAEogAABLIAAATCAAAE0gAABOIAAATyAAAFAgAABRIAAAUiAAAFMgAABUIAAAVSAAAFYgAABXIAAAWCAAAFkgAABaIAAAWyAAAFwgAABdIAAAXiAAAF8gAABgIAAAYSA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\"},\"shape\":[10000],\"dtype\":\"float64\",\"order\":\"little\"}],[\"\\u03b12*\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"MzSMU+fdEkB2ntLgvI0VQFuNaTvicBdA9RSjAXIdFUCix03wfmkSQLJ5hT6g+hNA0quzytdsFUAw/lRNyFMUQHlXsCfJHhNA1AsSdpb/EkAVzdxbxP4WQHqEc98DZRJAmbt8F1RHEkD4HISg67MWQODEkozHohVA0f5xP91TFUCy0bn4DPgVQDKPEXAPKhZAdeLgDe5eF0B5WSofaf0ZQMARx0lwcBZAd3rmsz8JFUAVaRZTwg4VQHxlJwPuZxhATTvIDr2PFUA+u5uceUEcQLEDlzV4tBZANu/wQgXbFkA0tlwbXYARQLIeMRGwZBJAsm2i9hVfE0CkZMBA0qUVQDanDR0GlBZA8Y2iHpqFFEAz2kZEhHoVQFImDJd72RZAJOuMhuhSE0C1uMr6gwYTQPgAFrEk5BJAE/xV2hgqFEB2cMDm0v0UQNJeNPGXqxJAEoT04aJPEkA4yRLEgaoQQFq74qsuPRNA9Cle5VL1EkD+JRYQV5oXQCqfu0AK1xRAd/9AAAr4F0DgaotZYf8UQLLIJ6cMuRVAeOG73+GyFkC006lr1WYVQNP9TheyWhNAGTIcP/lSFEDwiSVXUGQVQHHsW6IGyhNA+4PWTL4uFEDdIF1AiisRQH74CDU+cxZAVZFWJBAAEUAq25uxnREOQFueI8etDBBAQYc0zq5OFkDwlMO26+QTQPc1uPf23BVAupjREVqQFUC3Uyrhw6oUQLA9vxs9mxNAMkr1x3g/F0ATA3a5Pj0VQHiK3Lu2YxVA/hVUgfP8FUA6+C+pLvQSQHvPuc2+zxdAUgo9oUM+E0BZ9YtacfgSQDEy6KLicRRA0hrK3+29FEDWoj85wmcbQDjNkBUUWBZAulweT7+EFUCwDqXBnakUQLHst6XEJBJAHVSGAvAIFED068NXGVIUQPgO6vZzaBNA9NsxkmuwEUA6dpdAptoYQHgkU0+HMxRAcqKPCtuQFkA0XCxw6mEQQDydIMOwshNAuXh+3Fz8E0C4OWhqBzEUQHKO/18ZgBlAcCB+139UF0Dqbx3o6jkTQLmOzHlT6xFAeJpv9xGxFkAwKLImMSoUQPNTBg6v6BJA55rQftgiEkDTjxiKBB0WQBbZcsqHgxJAMrXoSIQJE0BZiGt7xT4WQDJhvDTU5xBAsy8+BVIaF0A6TU+NS0wTQDgySOspURlA9Mkz2NA5E0BYDtBIoswXQHDz1zNVtRJAsIPgDvHOE0CxkO8ojEIYQFGY/UBPERlAuxh/JsAsFEA0b9PTcpIVQJwb36t4GxZApP9+3CKNFUA3RoY1jy4TQOFwM+rRyRZAe9vKmnxLE0DyUghLGOoTQPVgDFEAhBhAN0VmONZPFUCbOwEJjlITQPinRwMNuxJAOLmeOWYBF0CVmf26XBkXQPLVcmdbhxNAktnbn8AlFkBRxLD4PBgTQHHpdM5caxFAqbkY9KuEFEAdHcKor3kRQLCK92VbVRNA5OOqgajwEkCj7J0EBrkSQAErzKJq7hRAPcgnNjzIE0DnkkUctnoXQOJp+iyziRVAYvGz3rwAE0C5r0MIuqkVQDieir2vWRNAtVs0qSY5FkBAyZwwgdUWQJfBf5iyihRAtAi8YsTcFUB+iuqihX8VQJk/p+hb6xRAWE3J4bc6E0Ayi0sf93oTQBI4Lr9vHhhAJdfZm4AjFkD8Z60yTusQQLMgQoggkRRA3fP97kJDFUD9/ZcswoAVQCUyCNEALBNAkeYJWa6NFkCwc5be3S8ZQHwHruEEChVAtK2xrMIYFUBywdWGl1wUQLWM1chBEBZAU9oTjVdOFEBzTp/Bm5EUQHnRhJFl2RRAYmnEo6quEkCxUWW+FR0VQERr/LnjAhZA8pCKoOytEkA3cmoA19kSQLnSY8olEBdAGR13OWAZF0D2OsoxivMXQPPg/HffnhFA7IZ3rhQPGUC4Lrh5rkkSQDAJ7cyZeRRA3OlCcODGF0Ayq6e8nZcTQNuTlnloFxdAMicsGO1sEUD6QMVTS4EWQJqc+ReB1xBAcl88i5jbE0DxVv2LysURQBRlElw8lhJA+SJlk+WnE0DSertzjFITQLG29JqWUBdAPGHK4PajFEB1+doDul0VQBOqaAhIfBVAE4AlsNC2FkC3Kwmb4RAXQDD0eDxk7RZAekFw8YHoF0BgvX/tXNETQFM9E4cUxBNA+Y+EQqKAF0C7nvhKFv4WQFO30TqChRdAYuuXagUFD0CVnu27KZwXQH1lBFazAxNAslruKBP+FUDZpJLTwgkYQLObFBpbgRRAOAzKlG7WFEAj0v13RJwVQI7YqbJ0TxJAUn8MUMLfFkB1OXC3UHcRQP/Z7ZjkLxhA83gSfsvkFED5X1L7JE4ZQHLBPk0/zhNAmjuQNlctFUB5D/sOe68VQPMcKr83XxJAOLJcviv/EUBYA2U2B6IVQLYyr/4lEhhAeBRRhyuXFEDksxZkaFoRQPCvlwDa6BNA0pXsgERRF0Dx9eO508MUQHesqo0MchZAcbFOm6DTFEDv39e8LQcUQDvHszkZehdAd7s3yA/lFUChahmoAyEZQOBM7CxX7xVA8MCdFJvEE0C8W+yhrZoWQDLEo89cqRRAtkx0MUMEFUB2VE4RB3kUQPFxpZF5gRNAeDSxZ9hNG0BzkgWYl0YUQL5QC5ubjBZA06r98XhqEkD3fKAs9WYRQDLnParj7BFANYw/vS8AFUB4auEkAksRQPihV8k2eRNAfP5uCEZqFkBEJCPNCBIYQFNy8rCp1hJA+lgg5UR6FUA6ZAyK1BYRQJcJLM7qOBFAMHxGkoi2FUC5NduDpiIRQAr8HVTXoRZA9UpsSJB/GEB5XPXkWaoVQDOIx0a7FxRAMngaeyytEUCdkH6HCcsWQBWPtbWLOBVAespf+rNXGEA8Vqi5+fMXQOWfBNGqlBVA+nJVcvPXFkCxPTVnBnkTQDirHM9WaxRAsWKzktVNF0CV1ZgiXJoVQDBpdHKLyxNAEsK3wTh9E0C0XV6drIoWQFQ1gRecbBZAdfG1SCLbGEA0dBAbcYQXQNNg/RwiYBJAcAdVCGqxF0CzdHNd4vgWQBGv2mIzDhlAcfKuqal7EUCkvmaEcfMSQFYl5pH4PBdAv2nRh2lFE0DwW6p51HUVQNe+Wb/aPBNAmE5UE3SKFUD09z5wE0cTQJKAj+1i7BVAY6MK9H8GF0B1DrPx77cSQPWxWSYpSBNAktDfoENPFEDw4y6h+DkWQFVjvNQinxFAWQQv96LqFEDy39qPAG4VQDgv0xnLBRNA88yonBAkE0Cx2wqPbI8RQDZPMGz6ihRAZb6sKL82FECYyuqtqNEUQGEGVCrCxhRAulhxI+kbE0CS4lrvZ/YXQLp+CDBwBRVA4G6QyLPgFEC5aKBBIBAXQNH4bf6N3BNAvldCWZyTFEBhkC574fYRQBnDEOpsfxRA/56HVRG2FEC2YXmoNfoVQLwHosFV4hFAYSrx+HAeFECxps4MP34TQMAikBF1+RRAG45spCdDGECpRRrYBXwRQHIed5yTbxNANh+A91wxFED5hX+7w+sRQL23LMeinhRA38tDhnHFFUCyX1nBqJkYQBvwFgjsVhNA3RJkMI3iEkBwtiJ//nsSQBhk3AgeBhRAO+7uOpxwFEAj6n/UVcwRQDyIX697tRRAcLn3rwgiE0A2bzATnE4XQPOkSGMUUhRANLXt4KHIGEA9/UNTQ+8RQLZLTzN2sxVAML0z8w1HEkC9rVSBnPITQJQVwp1WZxhAWUmsbfRwFUA86WMb3eYTQPAg2FGRxBhAcx0d9bXdEUC1/CUQFzMXQNEAp/SkCBdAeOfnnxrXFEC7txQgGQATQLUgiYK2QBRA0QX78/4OFkBAmUTR4AAVQLk6tKLCyxJAczVcA3bIFEB2ou8ov6cWQFiIEBJPKhNALjnYkPxXEkA6V1qUjEcTQDmGb8hEvx1AlNNcei4HEkB2egJWmvETQDGl5WcrZBVAp6o9qQPTEUBxZ9p6hAgSQOD8ak0gYRdAOfR+TVDuEEDYAec9ajoTQDx05DoAFRJAeBuWRLQKGUCzTbBYgxIVQDbFFu6HgBRAPgtEX3BzGkDB3NeZ/MwUQGWdkJQAORVA0fErXPR1FEA0UtE5oF8VQLoSKHS0hhJAsIBv9mGQF0DS2ln3QtsRQDixMwsvmRRA8Oq1Br49FUCRW97uZwgVQDY8O4StfhlAMepRKrAkFUC8dWVTT7YUQDkQtb5g/hFAWyn/3TjlEkB4jxCZP2cTQNbIiGW/PxVAOGXpeY5sEkDy38yeqIoVQHJ0rRhNjhRAvhqac7WyE0Dxfv71B04SQHWO0wYsSRZAsCgeuC/3FUDUHnoE2iAUQPBL1BLDoRNAE48UPpKoGED53upCZQ0UQNbzekJFRxNAGLOmaINmE0Dk346A2x8SQFmcVyJFXxZAMgUrKkG4EkCyEvoCUQASQHo0u5RmQBJA8md4JN1+F0A7DogJaD4SQJJ0FHihOhFAWcHHy/KaFUD6ZyJsBAMVQOKsig3KMxRAHd1hBi3bEEA25K7j5gAWQLIfJdfmbBlAtxG4I5/SFkAaz7nH1X4UQFY0A75wGxdAqeKgo4FeFEDz9EfpFFYVQDBlhss7SRZAu1O4cZjZFkBzZqJNiCkRQHEK2jlGwxNA+SdGXMNbE0By0zpRkf8VQNMf7jCy4BRAnGJBmfIoGEAwv66NoM4SQICnJ0FXTBJAkgQoeAMqEUC2YgfyYSgSQCG1L4kJ7BdAudNlEl8SFkD0+/eyUW4cQBv1wBZO+BZANVMS/yNXEUC5KH78fxcWQLK5M2dqnRZAZjijHNzuD0B5DFgk6WYUQJKGnAdLmhZA9LnPaZDPFUBRKuf96cgWQDVRxPu6BBJAUZBTB0EuGUDT/AgRxdYVQLdeUPfpoRpAFGAdBMpXEkC6kwohWiMUQPeJgVoJfxFAcG/GaxwTFEA4bbud+kYXQJgHVbNpkhFAvcD4flp2FED4MpHxP9kXQFmSX9W1CxNAdH0ZSc7nDkAS+Ua7E/AVQGHyP6pxgRNAtDmAp1tPFUBkGYTBYhoVQDRnDy5fkRNA8Cw3IrDHE0CwGvJ+H5ETQNM4gKTT8BJAkVQ+6HQ8FUBzvBKDdxEWQHBe4FwQDBZAYcVXplkqD0B1teQJzOsXQHJ5gVcjZhNAZGdaADgIFkApmkqPlY0RQHjefT2iWRRAe+KJObmhFEBgpNFfxcYTQHI1cHH2HRVAUVMc7+RiE0CWHDengNkVQDtmyuvxphFAYdHTZuhFFUBUn1gbv1wXQOzZIHJliBFA4MZkhp6yEUD0nPD3AOwTQCjMcKYF4xRA05lbxZerFEBjGvDYzUgUQGF/DPE1GxFAYDjC+JB5FEC19O0YuzgSQGNSmwC1TxVAMavo7lwYFEA5j9OOb7MTQPKJEMRhZRVA3PGyTG9JEkB7dPp8T2AUQIEfOuh4ERJAEzl0mtArE0C+fmAoZKMUQHLhmrlgnBJAWj+/NT6xFEBh8BKk/5oTQHEm7Kp2ThRAk6Gb1YF2F0AXhqKdVCoVQLzkhBl1nBRAfa1++GytFkAWCNM5O+sSQDLqyUgbkRFAOvBhNVEnEkCkUKWUC5wYQHXKAhRDlBJAgaJbBa/EE0BgqHJ/tyQUQCKtFa6WHxZAMCpx6++SFUCzqyFCQ8gWQPbrTlCpeBNANRbNxgf0E0DyTpZMuOAVQJF+RiLlFxVAou3exde0EUBCDgHEN2sWQANvq5zOwxJAe9y+6OouFEBclC0Qod4YQNlznX/gPxRAYn63BsHfF0B6VwcILTgbQLHXY+WSyRVAWVNShKllFUAz4pi1qbUSQITdpLfvBhVA9Ir2cDOtEUBwhMZJ3SgUQHiteQ4HgxVA+OBcwd4jE0BwvD32zjMNQBGy/TkEohJAVD+awLh1EkAwAeuzeJgWQJOY6k6NwhZAVlUFU4PBFkD5gdSe4yoXQGq/SwUJZRNAOZxdQyobFUBxCNsMeEETQCMmOJi3XhFAYaMS4/w9FEDSTJ3Ax3QVQFS0VZh3kBtA1dNtFwHkEkD3WlHNaY4VQDMAlUMnGhdA0rwFc23BFUB5GLZY2FwWQBSpc8ZGABVAu2np6aWnEEBnLRK9cCQUQPWqZ4HEuxJAFWMtbKlzFEB5R7tBdQEWQPKf2wzL0xVAONevyqEbFUB6BYfWBFkVQORsom4aBhRAFXtBsPXUFkBRSnRrvysTQHbalyO6VRdAFP6QA3ppFUB2h1mFWOcSQDCeT/EyqRZAKjvhm1CJE0Dw+1yR2moWQD0hY86xuRRAdeZI1GIHFEB504IAXKISQDNvYKaRIBNAMXXQ2DlBFEBc1YJ62c8RQPamzSsD7hBAsBq6slKaF0D7nD2ReyEUQKlcOA40vhFAeewmWgq4E0D7uoYu7CgTQHS1K44KyBNA7V9JPMaME0B6T5jY+iQTQDCjLzChRhZAIahtPiVCFEChfXOQZdIRQFIQPfcHwxZAe8F99tc4E0AwSCHw9uYSQJFeIF8+BhpAGSAcrN1eFUA7WI4cbrgTQDz5b8s8VhhAtoghsYkMEkBwCs9eflISQHQ4xbyc/RFAalwuEk9XE0DyV29UFlMZQHKgxhrZsxJAIsB0QlE9EEDw8Ki6fnYTQP4G00JL9BZAcUPHklG9FEB8aJVlaRIUQLLXMtbfJxRAOniZ1DJ7EkCUCfe7o6YTQF53BE216hBA/JLSybZmFkAz65K5PmkSQJYt85/FaRpAdVuoKo2jFkD5rNOYVu8UQAEAuuRRohdAGByudrlCIUCzf+m2IyYXQJnI0vCnlBpAcIF+yDvQEkD2p6WMdHAUQPFoc70u0RJAcZHgJlE/EkBURZAPruwTQDH/dvv9HBdAv5B6EbotE0AxqF0XFEsSQJFki9jIZBZAU2aQ7vl0EkA3ducPFWwSQP0vkdqYLxJA5mr42K8dEEDgzgy+VnMPQPMf0Zdh/BZAt5mRP7fVE0DRmuUSdHYWQKKO0eZRchlAZk2PkfdpFkD7KeYxKl0VQHY4GgpaRBNA9wDgPoPjEECaJWC6jkcUQBxReUg//BhAc6lRWOhuFkCZlSpUXeISQDboI+eBERFA0kIIKWhWE0BW9RR3/EUTQObLiJz47RVA414YgzZrF0B2HDzSnewSQLBm2a6LAhNAOUAk1WJSFECq6AOyYUcTQHeypsYKnxhAKuTQhSSIE0C41DBby6IVQBNhi3N2zxJA6UoXTVFCE0CaVtxdc90XQPJ2B6gc/xZAdBFH6ru6EkCanan37A8VQJYKuFnzfBNApZ5smd0eFEDx+sg3WH8VQPsGUol36BJA8EDSR3qNE0D9Qeok2XsTQLThjMupBBNA0m3zPJmSFEBRgHdSXVUTQHwrtwYXzhNAsDXgl0lHFED66r5boe0TQJJpAyyXKhVAM+/q0zCUGkCwIf52fuUTQLxrjDC7OBRAOrvn8gnXEECzNhyfXjIWQPy4QO1xpBVAe26TfFCxFECjlOiaq8ARQD1yI7GYUhNA8oHPpaC5F0DRPcSoOYUWQBIBJfkSIRZAhcPSvqWcE0AwUpZUGhoUQLmculLRVxVA9YQT7f6UFUB5D9wuMF8SQLBlry1FbhNAtSqjq2jkFkAwFCliP4ISQNuwMHBRkxFAsm9deH44FkB8WqDio8kRQNHbHbHS+BZAIZWAh42iEUD2yAcY9EsSQKMDpFqjERNA2gVNczPHF0AWtuHwI18QQHLA1RzgfBdA0/sHQOIqEkD2enZU1TITQCPLy1IOoRJAfa3ElwwTFkBcN+9n5/0ZQHT+IKt5bhRAYKp75KMIEkBVjNqcgIUSQLm3Ak9swRZAuJR9qlhGEUAe0eZH69AUQNicNHBUiRdAse/PjhV1E0Ak3mhIc+ETQHHDhuEFVBRAcfiDU0DtE0D/Ijb/SPcXQDMIyt8KuRBAtbnw555HEUDzvI7KfCwUQGTu9xXgwhNANB9mWYdZFUASeKpE75QaQDRrYJVDIBNAshxqlOEnE0Dbi21dLQUUQNmeBXjAwRhAJCdiUXC6E0B63+xmursTQPlhQfdVYxJA+RI3xkRcFkAz/AHAgTITQDABnI8euxRAvlAHAH7rFEBxueiYzMMUQDuDFoDDIxNAIz8K3tjxFED6srITcXYTQLEkmaylHBVAVwiIgxLbEkA/OT1UVF8WQJPP+pmLhRNAY0xpyvRiF0DfQU3a7JkWQDJwy7BT3BlAntN4W6S2E0DaeFuJZPwSQHbYplRKjBRA9njInVLGE0D4fpwWZ9sVQLwgR9DXhRZA8DndmoT6FUB5b/J+ECUYQDX5RZ0+DBhAEcOtpnGAEkD4sNHRbpISQFhwBnNlFhZAU3hVyNklE0D9bKFnhLsVQJEm8JrXfBZAsRhK9AEtE0DwccyfLsUSQHDvxfNnohFAXnG/FvmTFUAy+eZphsgTQPUtqkep/BRAlkH1kyINEkD0iaq3sCgWQLKE00y17BRAOccVEINIFUD76WwKz2IUQPyPZnIaOBZAUvM6WOkzFkCddFFkifIUQLEtLZVX2hdAsYFhPTKeFEAzKOpuUswXQHl8ShkpOxNAtdnNYhNpE0AVYw4J/j4VQDN5I71X+BhA0ab6CKh5EkD4DhhwtHUTQGm+wF3Y5hZA84GNhy9bFEAqD5nyMPQOQPqptMUB8RRA8+Mbd3OOEkBhEv+pTWMVQPBmAFYMCRVAkX8r3Fa+FkBgCVOy1t4SQDQT7EuwkBVA0mCj+fYDFkD0DD18KoUZQNccLYenWBVAWLJCXvWhE0D0esFX924SQGRyHosXvBRAC74DjJk7FkDxkMSXukIQQDrvzROKyBRA9VP9BpIzEkCwX+KiWU0YQDtmDOrCuBJA/nJ1Rj8wF0ByKD5szkkWQJWLhnQSghVAPbJLjy5QFECwk3xm/3wSQLLtTw2seBhAOYD/WfttE0CiKsA+NO8SQGXM/2e9ThhAmqZ4m4owFED0EjU4FoAcQGd4Czra4w9AecsO7zgjFkDVb+11K+sVQLIvg1p9ZBFAIgSZHAFgFUDyEuRHD1gVQMF5Mb6aXRZAeVOFKTgzFUDy12jxGBYVQDR+TdeJmhVAfR6fOm0kE0Cxg6W7Qo8VQNWYX0RawhhAXDAOa38xFUAKPkZhZiATQLVM2pX4dRRA6PWhe5m8GEAipWtxvJYTQHVnHLJbcBFANe/c0iEpFUBhQWEGmdQUQBELr6GcDBVAJzWKnXGvEkDwDjeTr+8VQP05Sy5sbRVAZpO5CHJKD0DSbS3k/28RQHbEqJwJGBZAoVHg5bMMEUDRa0ETO6QWQPjwQJovpxZAdUoiNVlTEkCSfhUI70USQLoQ/CSMJRRAt4yLCOYHHUByM6d5z+EUQGFOYKiZeRVAsOgOYnk3F0Bw7Am3tPwQQLGp1Xq8GhJAPBups0CJFUA1Qw89IocRQOIaPQu0rhJA5N3sGOmFF0AzhheX5AISQFial+gFYxRAsYORxmC4FED88Hdk4AkWQPTr3hunrBRA8elh7IIDF0D50ZJLcJgaQPHVhGP6gBRA1KOBm5B2GEBw/IhgHNQSQBVrLikdBhhA+Vjp8HQKFUDyy9pSOoUUQHMTEtV+CxVAcDRh+jF/FkA0ALWAzv8SQJVJgVmWBBVA9KzFV3H2E0CaPpYeD6MVQHOfSKCCCxdAtramoZqMFED6sdLpy3MTQF0dbBxUTRVA/f+fSWhhGkBTqHnn9tYWQJYYEjylDRNAe+JJ2wNNFEA0S+enpGMWQBh10RMRyxVA8NDMDU0QF0Czm2q7VWcUQHMrXRJn3hZAYMzpff92EkD3vNVwU7IRQDTiJYzvHBlAcfd9VdoGGEASKHz0SokTQHpma4yPfBNAd+SrnnZVFEAy1mBFIckSQPic03LVTRRA0UjcWMQCEkBlZ7NKTe8RQNgP9uNnuRRAt0rvQUokE0By6OtRQNsaQOr/0cvA0xZAuM9ZfMXuG0Dyi4gsxxUXQHjOF3BsLBRA++YjhhhkFUBwBPwl9Y0SQDK0pVAI2BFA4dFbvheOFkCXhoB2hdgVQD1uneAzQRFA9JRpSHnmE0A4CxIohucWQPliOymBORZAelv0dAwFEkA03ALC/e4TQHgus8DVkhVAOdMg2YUlE0A5rP6yqbAUQBv3IEXD5RNAW4RL6IEUF0AxAJe3H1EVQJ9nKVkF/xFA8svg3oQuFECl/TFs8EkTQB98RhsMphdA0gi6n/OSFUA2zcsQYHgVQDnwZhNfrhRAkU03gmcoFUAzqa786PETQLCp73S9hRJAO+3sNYxlEkDRMqDA1IAYQPA9tqgH8RJAsQpHf/gdGEA9FUsMy2MWQAE2VoOHLBdAc9k2bsp0FkCySQZqDvgTQPjyt0YFsxFAFXgUShVgEkC0q+yDxM4WQJP4UBiGShVA4sryzP5iE0BUPQqsZCMYQFEDJsCPjxBA/SDRxik/FEDzlOmz0XQQQHCmddhQGxRAveq+FYqxFUA1KjcaaPQRQJECP3A8OhVAIs69msvZEkCRiIRMI+MVQBE51iCJTRdA0vp3EjWIEkC7+cntrGcTQHPp3ZYbXBVAsIaz2CJpFEAwzmYe1oIZQNRS3aWbXBRAtGpcBrOrE0D3x8NEaK4QQPvo9dmN7BRAMJQqwuQtE0Ch+Vh2l9IUQBhpYaOnbxNA8AbYFlVJFUA4luI/SkkVQL6SWBYM3BVA+KJgIcSvF0Bzd7+1WJsXQKHAwMWCHhZAVeHHLMjWEkAWtj0yrXgaQCE2+43w5hBAeane46lJFUCXwgXf+ssSQJiXkLxVSBRAIT6wtd9sFkB56rHMYL0WQDlGmCDlTxJAUnWYWuC8FECwkn17UNQSQGLqw81PwxFAmdYitG2EEkDp4u1RD74YQNGpkHA8rxZAhEQD+Ht1EkDxISbihm0OQBdeHrGtEBZA9IxM+gnJEUC5k2xGvKMQQPCAZuEE/RZAdtAFhd1nFEDSt6zYYCAUQFxXGXHtlhVAVZA1wzRyEkB9S2mKlY4UQPss4JyOwhJAIUPdz/UmE0A+kq9WHsETQBzAIzjuhxdAEiTOvCJ5FEDwHliDJTsUQPfFLj6LUhNA0+RrQ2L9F0D9mpHfx8oUQPp2X3NTeRJAysWWMp2cDUA1UZPMHmIYQOi6JgxQDxNA9QTJcz/qEUC4IvApRbgTQPWxbzI5NRJAeY01YxHDEkDYGLoKo0YUQPCRDILj/xVADOFXuheJFEBwu0QwYfoRQBGrVg8mbxJA8wp4ssOEE0Dmigngs1UVQL15XPMGNxNAQKGnDygVFkCabPcFXLgTQPVbcUdjlRJAubaO7s1mFUA7YfPT/y0VQLPwEYeHUBJAe0qDpsB8E0Bgd64GneoWQL6ZjDRvhxdA4JE/i7xLE0A1XsR41gsXQItpnuv9mRRA8mGix6JkE0BzrNlAYDARQJOXkJHYmxdAeCtU+JvVEUDwUXWQ55ETQHO/fcBFXBNA4cbDs8PAFEC/elR7t2oYQMx021j0uBFANcgj4fJhFUCxjsgI3c4XQD9bRXHQvhFAO+EUEnW/F0C6hpUlGD0WQPHFFhqJlBNAqkZ7/OlUFUD694SxG+YVQJpzVvCljBVAZQ32LRs1F0AbwPvF7k4UQFsl7wLCahZAtNwJVkIBFUCzx5VdXt4UQDTWnieoExJA8J5zkBShFECXtTmNBVcVQOCmhlcAyRRAdCXKNHvEF0BlAWK/WaYUQLPVAZbYTRhA9/eWvEU/E0C59C270VkXQD0wcptGmRZAsozVzdd7EkCYxfhGjhYXQPSqpbDGaRRA8CD0fi4wEkBwG8NNhqwSQLEy96MlchFAOQotkp0XE0Bi8jz81F4TQP0I35dluhJAfVBk3J6FEkDXQcvGVowSQMThbas6LxVA9zcfi14wEkC88hUsyCMTQBX+WhSkWRdAcgUtLetCE0AxJ8wPHFIaQLRdrnidnxRAcWLDEpmnF0Ck15z9O9MYQLiBnyB5ihNAuKuV9M8PE0BauZ+f7IIVQIIJDVW2JRNA8p1A80q5E0AZ/7Eo5H0VQPyue8rIcRNAO+BBrAqVEUC1GqSkdcMWQGBQYF++1A9AcIdga9JgG0CBDq70xvQSQPrGG0+NuhFAcP/Ugo1XFECSEcETiP8UQDm50U4BXBtAMUXku0H8FEAClpEH93IOQPIQq4UppBNAuak+UQ0VE0BzXTZiZL0TQP6kJ00k3RVAcK0UW5P9E0C32AxZ57sUQHj2XmSrVRNAmEUdQF5iGUD96PvZ1f0SQNtCP6b2IhZAGNZTv+GmFECYVI7VhBYWQFaoGYFDShZA37KGrTevFEC1VwFCmAEVQDQfUxF8ZxRAfjaWgeS1FkCwJhQafXwUQPjBSLQhfxVARPJufE7qFEBzlYekvXUWQDGQm9BSnhNAuQ5irQDnFkCw1ESVIrcWQHJNa99eaRNANifXQ/aTFUD8Ck6T63kYQGA3/IkPJhhAMzCr5+SiFEDxoom/GZIRQFInqHYfzhRA4vs8FI1oFUCe8v9sj1sUQDFjCCe/SBVAY90vy4PQEEA47hUjiEMSQDRsQbLsBBVA9I2rBvuTF0BRjbNBm88VQBE/UydlRxZAts5gOQDgEkAj1CV9DLERQDS6aEyMmxlA9FZ7lXR1FkA9fv0wGBcVQCKKwXvhbxVAsnlTAUHPF0D4+kl4q2cVQDwUfUicERJAkSNfJgz+E0CpwlIwncETQPiKeMSLBhdAlCKrap/nFEC4DmEcRTgWQHEYwxOJ0BBA+bSNQxunFkA98NGZDBgUQDL5OHtfHxRACpIYGD6iE0DwUBrbxWcSQBdkvlqjlhVAdQ9C+b4jGEAwOiygY3UVQBKCKYDmtBNA8f9Pop5FGEBW7kuFxSgUQLbzEa3bKBNActZuqz5YE0Ai4LFTsEoQQJ4q50+VlhJAvahG74JoE0AzuABMTbYVQHCZmTucxBNA4d0ZgLLEFkAwz6/lHBgUQLylNMCvvxRAVK82cwgfEUD38+gtwhAUQDpEhXENJxtAIZCQOotLFkDwOBg0iqoYQPgjxqwhDxdA1qm10AoPE0DNw4uhu+YSQPspDS+vvhFAXTHGIU6VEkC7wiTNYLgUQP0ulkotxBhA4tw4/yEAFkDhAhpaH2IWQD+J6ZihVBhAeDEUpoVqEkCTnq9QaJwSQDg9qmpZyhZAuTIqjUxoE0D0BuDtpKESQPXhp4j3vRJAMM3iWdjkFEA4LZpmz/kUQDyucmRtLxZAuCKT1AVEE0DwgtTZOs8WQFN9MxxUdxVAPrDw8a4rGkC5MMbRpKMSQDejRayzXxVAOIv0W3kiFUAxWa+u9w0UQFSnQLSCaRhAM5rCis6CEUC6oZ2qOvkTQJ/LzSfrhhhA2H6izKHAFEA22ODZHh8SQB1dr3nVTRZAeN7rwF6zEUAV5Bf691kSQKqc8HqYXBNAMCJTy11mEUDl3Q1ZC1cQQFTCuD9SuhJAtpOnD96SEUB3LQA6y84VQPrVl7vt1BNAtTLmqkkVGkA0Wz2nfasSQCY3dCzdRxhAIj4LxAYtEUDi5lk5AEQTQLStsear0xdAtVkLdCeeEUBwhlSbTjcWQJOBvlNJdhNAtgWBA/7wEkByk3ul1nYWQPi6Nuo8bxNAEez/cohrEUDyiZcBAQ4WQNm4Yv1OjhlA+tY5MRXkEkCYKJVlwkYWQLReIgzYSRVAsK8Sp/pLGEAzBalGUBwWQOCE0OHkexZAkmbyRDb6FkA0vJwMYO0TQLC+JVU1QRNAcgvkWBMoGkCYG90c3v8QQDmEF2sbbxRAt+ohG7riEUC5+IjriykTQFSgxAQ8QhRAdZBYnODSFEB1Vb04FtIWQOcnK5TCcxVANJJ7Sx5hFkA5kYxIIVYVQFWKMB34+hJANv/VwjoQFEDylNp9riYYQHWCgsXoJBVAkVte3Ps5FUAzTc1JIPYVQGT4tVJ2eBNAv5F4z7wTGEAxe3REGLYWQPW05aSRNRNAp0PyRcTfE0B5+xEHl1IXQNE5LUw/GxFAuUXBoMRrE0B56C/g8kIWQDgdNlFqKRRA4td4nIfBFkAxJPN/TOkTQCMfpI9xhBZA+0Am5W22EEBY/xF0ixsSQFSLANly0RJAcoc6WL24E0B46OqgVsYSQDtv5+PY4hJAeNOdoNdyEkBStCoV2csXQJIhvv3uBhZAsd4QESo4E0CzGyMxXFYaQNIM0JVuHhRA9ABKwTDbFUAxH8cyprcXQHW2pDidixNAlAtB494CEkC0M52yLZ0QQMkKNSGgARdAT3CJeBIKE0BkndRcnYsRQCoFZoG4YRZA1U2J4MO5F0B691Pk724UQDG1IKzbxRJAFPChr+qEE0D1Y1zYWBgTQEkijP7EUxVAN8ERqbsIFkDxnljkQHQSQCvoYHA13BVAsMMAT6AhFUB/JWFWn+UZQPPo2qSqgxVAckVKCdrUFUCrhDgdTA4UQPFFM/fWmxVA9Rp9kNw7FkA0bpRl0OMTQLonRxy87BZAMOBR9KFBEUAUV6cmVIYUQBL9qfjxAxZA9D4fqL3ZF0CzTREERogUQDkW0ukftRRAs4sPLnVWEUC2deoywR0VQCOo2KNapBVA0eRPPMyoFEC25zz9hSgXQMNqrN8oXhRAvBMtJtzGEUAj0nhkNYMSQEO84lhZwRRAtn1GDshDF0Cxwby3UcUUQHAlaoRkXBlA+GZDzrveFUBzQhlXkacSQEUtKt+hSxJAZE2D3KrQFUDZ9BGhfqcVQFlV7AlA7xNAmGT65FT6GEA82LVywP8RQBLo/r8nlhdAsU2VtlGFFkD0u6OvVOkWQNnWXgJsLBhAMAbuaEmwFkA/aQwvb10VQJaX8cpS+RVA4KNToHsVEUB421iRQHcYQLCAHh006BJAcy3VDs8FF0B1mu+QenAYQJMmUPGAOxVAd3QCbqIeEUDkRbnUTCsZQDDb2YSvChFABZceu+7XGUB0E+jX6lETQLKtRLWDDhdA03o9crZQFUAYSOI0V4oYQHONY6K2VxRAkamx75PpFEBTvde5LEwSQHM9lhtcBxZAWBZDUcdcF0Ax5vBShggTQL0ey3R9txFAlpg28l7aE0DlqD3SGtMTQNEeOfTHdRJAsJNIBIBrE0AwhnCwUKwUQHoWOlcLrhNA6n/+S4fEEkBhm7F6DiIWQGY3EYnTUBVAuLfrgkrHGEB5mt5zIL0VQB/79SYeRxZAc26mQXWuFkAxcqeWhAcUQH0x0siA9BRAfIoA2I/iFUCzcTrxyEoTQDDuB/3lKRJAumP0jn0SF0ASpCOrNygcQDdHFajgGRRA9uJqBrC0GkA7ujVERW4TQHJwVmKZKBNA8ZEYmYRvFkAy9jGHhCcXQDZRpaZ6FhdA+RsyWAvjGUDUPZZgPBsTQDmbaA/jfxRAGs0WCoUPF0Bxu1MxMnsUQPX7F49o7xZANMvytrlFF0A1pJ2E6hsVQDLJwKH83xhAYnBStzxGF0Da47JM9V8QQPrUPiZUzRJA0RSoW1HGFkAjE1lB6CMRQPKmsOIxqBFAsWlVjCvWFECSfJQHwAoUQBlIIke/VRJA0fbPMYkFE0ChnHDNaUcUQGPNdzzImBZAMHxzjhiLFUCrplGrMNMTQHZMhAYoxxJA9rdvPYAQE0A7qRag9/gRQPaox9tEyxFAOI6pJHn2FkAxVELrWDkUQDxmbITSPRZANnRgZP08EUDiTWE3SH4UQBM/PXl/qBZAo9OlF6SVFEBJ9XT4DxgSQHD4xoVMFxJAt3qgq6fsEkCzUPs8vqsUQHD06rXJOBNA9TdZFzZmFEBT3fKfwG0VQHoFtNeUoRBAGt/omR8KEkBZ2wmsLw0YQJHsFdbePxVA24IgTtocE0C0z5VZiLsaQBPC1ZKUaxZA/MLH8TX0FkARz38lnnkUQLl5GElG4xBAsf18fLhvGEA8Jkb/vA0TQPGfzc+SwRJAIgg0lSq0DUC0SnBhn4UWQOWR9Sz7LBRAlR9HjuSWF0CTZhJ9hkoWQFgMmJuy1hhAlPyarJyAFEDRtUWPdHgVQOJc9l1/OhVAAMGXaO91EkDSryqQHPYQQHusRbWTiBBAttEpj4omFkA4aTPxS4sXQEDOjWX2aBdAeyQDD0S0FUDwdCcSoM0VQGGX8PLRRxVAMraCqe03F0CX+KRzITIVQHCm+xxUSBFAIlOEr/3sFkDag3+oCYQSQBEhBewcjhNAe4u2jkQSFUAlEjVzV/4VQOrLCDmaqBJA079YJZt2GEATDJ+emi4TQLjqSUKTFRFAcoEl5j3XFED1e1Sn2iwVQBf4dXsnTBZAOmBfuEO2EkBwXwBmS+QTQEDOSQHzARZAMjnZajMJFEBWwE3nEpsSQD5rNJ2GJxVAVAoH3RkdFkC7bYiec58VQJZIDjDyghRAESjRnJ7IFUBYrTIGo9ATQNEcKRxXMRJANYaJb9nAFkA/C6SFCC8UQOrlEefuZxdAuPaLj0ANFEC8w3CXK1oUQJiBD5/17xJA28eiYQVDFEAxbaa5rD0WQPAtXLWfHxVA+iT0etr2FEB24k/LAQ4WQMPAebCKcxJA/rOk/iSZGEA9rQ/ojDMTQLFLXEKPLhBAtbyWY7HHFEDzbwMIgAsXQHawSoQ6TxdAOxJgnReBEkB1GlUpPTwZQHO20j1CjxZAOem8vLrUFUB8v2tJAowWQBhxX7/j1hBA+ZzhyMxvFEBX3Q99dmgTQBPxIwdoHRNAWg7B6M9nFUADYc7PcaoWQDaVn/Cx2RNAdOoTXW4uFUA4i3vugygTQHGydw/OrxVA0b2a/VLyFkD2NRkhDrsTQFEwlexs4BVAcoPUYuguFEC4QnPQ8/IYQFRe1qyMIBRA+x0mcMKfE0DSJc/S9TEQQJE1eaW+8BJA4ok1B7UKE0D5kr7Ym2MSQDRQwNFnHRNAMdtSazXqFUDwrhbIW3wVQPDgznkstxRAQcmU/kRDGkD3aYU5qtIWQPB9bOX9uRVA7EKBI6H7FEDa3tA71wcWQFkkR7D8ChNANtx81g0zFkB2ucqmqGUSQKQ61lYg7hdA1BI/L2QyEUCyKHtHMGgTQFoUHQtWXRRA8dBOjdLcE0BUSp7jhBsWQOJu6U/BFBRAGKsZ330QFkB5uMj3CGUWQHY2W+HOlxdAWZgvy7ajEkD1e0Jw/tEXQGAdkuSqjRRAVEswVSOME0D53DbvxG8TQLIGgfugrhNANhHELIZpEkDSz9WScAsWQPDb/FGUrBVA4vyX2PshE0A0hEXEGpcVQNGrFNnc3xNA8DRPoX8/E0A4a9rePrUTQDF44U7NWRNAGO4t+Ol8GECzYIcVSXoWQO9gIkM/8RpAcyZ7HGnnFUD1Sku2TWMTQDUu3SVbSRhAIl4c7okwFUD1TkUje4kYQHtTEWzMNRZAZ3kRwDLxE0CV13lbDREVQBIGlQSXIBRAnqh30xW7FEDcJK3ct1sUQHkiZ/KEURRAkds73YE6E0D6hbkoLP0UQPn1wwxtPhFAc1i0M8+VE0Aww+beUm0YQDYxEZP9fRRAMCz27tPREkAw+7ySYFsYQGWt+oRznhVAWPKckguOEEAVBJYhF8kUQBVVXAGufBRA2BzrufUEFEAw0KfrkmYSQDBJTkwr1hRAEVYven7iFUAzkkLu7MYVQBkL0mWyNBVAPZLU4Bw7E0C4TACbi9gVQGXY+mMfHBhAMfWwWTr0FUC1dqzpvxYTQOogE/BTqhNAIaSIM3flFED/7cQjxRkVQFIpLJz4lxFAGPLr6jmTFEA0G307Xu4SQLtGDPOmaRNAufbY86rTEkD9NoNvFrYUQO7G5C9I2RFAuaji3960EUC43ugYRXYUQBJdxNETWRJAPCxu/Th4F0D37ZJVITMSQPHl9azCXhVAlMtMJsvjFUBSwrCILpkXQOF+yfNAzhNAcGLdgUVVFUD0+ULf2dYPQDN7iVM4KBhAcCOxa3AVFEC07M9CIOoTQPCdm/ULMRFAcZ4SRNCAFkCz3tNinUEXQMLhlcCoghRAPZ5WYEJJFUD1e1i+1YIUQFkhlSj7QxJAJfjgMfDOFkCAZ4kqN6IWQHyLXe/6qxNAF6QMIHdoFkB2dpngTR0TQPLeS6wr8hJAtrVHktfOG0AyIk7E3eMTQPK3Ty24CRJA9E7Om57lFEA85eLxli8VQHLAZL+RPRdAtn0/YxwEF0DyGOZRqP4TQNxocpIImxFAfAr9Hh+OFEBwZZYkEk0SQLK0641ophNAGgBxKHLvFEBRPDsx3rwTQNJ8kHKg6xNAUtzKtlNXFUD3RjFIWE4VQDL5icy+ixZAsy+P6dY7EkD23mRNrp0XQEFGmVuzKBpA9umtZUfdE0BzRxstUP4WQFKsKi0Q6BdA0yr0QxoFFkDd2S0xZsMSQH765CJVexZAN9NVKBjLF0AypQv7ySYTQMLypxUgXhVA8D6pFO9TFUAxAqYvVfIUQJHN5LvRmxhA5MasIHmpHEDWJjPKKPAWQNFlpEZsVRpA+IlgnQAKGEB2iR2tCm8UQHmxbVIPuBZA/5ktDfwRFEB5CHd12WkUQDewguY1DBJAxPBaEuidEUCwPYWv60oVQLKw7/gNmxBAcP7lVA0XFkCXH9eEtf4VQPMs8Qet7BRAsSDkfezmEEAyMg9YXwkXQHUJtHaq4xBA+vd9Xf/zFEA9Dm0y+PIUQFKiJuaBEhNAIiyza8fjE0DSa+7zAdcUQLmnAGaU/xZAMeRy3/5VE0AU3+ix6/AVQNEIxgqrqBNAtCx6P+A3FUB6g/sVK1MWQHJk1y3eXBNAcJdC8KTyFkB8NKMmbwgSQBoHeHDgTBNAtNVBRHuOF0CxNNZlOxAWQHSBHyeR/xdAPJLxxGGmEEA5wqijj7QTQKlTndzjDBBA9HI8Q886FkA8+ai8is4TQKLP7Spu1hRAQeaSuafUGEDS0kPM8osTQHH1IgljehJAkUPun+fbFkAaZTmZ0gQVQCPHYnJynxhAesZ+FhhvFEC2YvK7pMYRQHR/Ct4X5RVA8l/IdX2bGEAySE5A4xERQGfM/1aLqhZAsLQls8EAF0DyP1Na8nUSQPLthp0jzxRA9ss4Uwx4FkCdKn5D5PwUQH9DsUg37RFAOgTxYMS3FUALhKCBKfETQJqFXphCyRdA5H1DAVTdD0C8tu474qkUQDvoGHrwjBNApA/IKlADFUB4zI4Q8kcYQPTAkRq2shRAOxiB+UWlGED2U+i2MQYWQHQZ1q6/CBJAsftqLUnjF0DgQWph5esVQDCXPXz3bRVA2BmaHmSYFEB5Lo6WCssTQJEARKjqJBRA+AaG1kggEUD3QlqiFocWQBEdsomwqhlAcrMnmnKdFUB6hPg6SiYTQPmiWK9bMxNAEzr7cihhF0DkxYPUKwwUQBJHL8YuOhZAUorbZAkyE0CRpLNMVWMQQONoycB1oxFAI4UFxZDsFEA7mlj3ykkYQCNWyqqQcBJAdPL9DTNLFUChGPHb7fUXQKUwWmrunRZAd/8/Ah28EEBEkTosdh4UQPPRlOTmhRRAdM4au7HSEUC4c9g//rQVQDrlYa3P2xNAYXMj07MPGED4ejimXykRQDqCGS36mhpAcCa2bORbFEDRsHbV9FgUQPqaLuD1DhVAsgxs9Uh6EkD5Tzz8/BkWQDlXwoK3vBFA+eXkbbdMFUC3IPD+wCMZQHLUxMxORBJAYHk4wZAIEkBgLuY6CA4SQHV48b+VeRJAbdgtJAzNDkD63TGOwOAUQLgmng5jBhNAtqutkeHNEECb1bK5tE4VQNnZJ+hIjRNA0jqM6JXYEkDUIrh2aW0TQLBhKjOd+xZABOcTHaN+FUCuMpA+QacWQBVxoyuTYRdAVbzUWjhPFEC1Zohiq0wUQDGgcn/SSRNA1H/EGUcZFUASMuMq+JwXQDWmX2itwxRA9Pxow5TXG0B/+jauViwVQGZJ+nJO+BZA+Txjw1DEFUD5klWbd+wTQJLeNSTQAhlAuGGWznfdFEAzq2aS6fwRQHBBkbGgFBZAdB7xTkfqE0D5JrIFYvQWQOms2c2aQRZAmk06SkzDF0CYKhzJcsgUQBrt7DLvgBVAsGlXgOSEFEApWum1H6QVQDObpBeU1RJA8Ieb0HdjFEAzvGDzmLoWQDmOJ1eo5RFAe3oVTSIdFUDdi2BIsewUQPrXyNyBsxJAuNzOxIFbFECYZ119ch8XQMt34oj7AhZAcHWaXUrsFEBTkxuScvMSQLHd4gEQEBVA+iLlUoGhFkBVi3I6Z1UXQPC+9nDHDxZAuaXkY71SFkAigyroE3MXQLNyBn8SwhRAUW6JO3CmFECzw9D1SHUTQHVos4lsWhdAt1aep+ZKFEA50/x6SVQTQGokD9IF3BlAgpljvMLrEkC2tVDSBWoSQHRZTSjzpxRAeVgVnpRUGEBSjxHr13AUQDEcryHpsRdAbUoz35ucD0CTOmBvC/8VQBl5v0TSVRdA5ZIZDNNtEkCEuUITsJYUQLriwOVzXBNAIsoaSzdpE0AaKEIrWuEQQHEr35iP9hNAd3eXBPY3FEBZQnootFEUQHYWr2HFeBRAcENfQTH8FED0e3adhLUUQBVyNtYu4BJA26Pf+hQYFkD8wIAroYcTQLCHvPL1vxdAcLruEdyxFECR/C8vCwoRQFdHmhXlDhdAuGtz3VHrEkBwoiLdHOoWQNfDLF9ozRNAw1GM5QhTEUBUgUQl9NITQPUX/GBy6hZAMqpHKuwiFEB++V/kyf0SQDUH6f/g/xlANVRJAXSEEkDSyxExT5ARQHwo3Wl0+RNAdXlNQ/8bEkBU13Mtt7sTQKOLJsSnRRVAshUFDc0qFkBMIKz8yncRQHCHVparjhNANjOe715xFECkb+sJoOgVQHtBYeu/ixVAvBseYs/bGECUt9C6jaoSQNgn0dkGfxpA6+Oj+qbsD0A6PZ0Lt8EWQDzynbBG5BRAsUijfgNFGEC4J6G9970UQLgr5py09xVAspZx7Em2E0CRQsdxnncWQHBDT36vBhdAVrM6Zp56FUB0wWgggMsWQHyJzbM3RxJAsQH9V9dFFkA/3Ry55DIUQFfZXMYZ0BJAdmrm+0IgFEA1vpyiiqMaQNRw9JfYihNAeMkvdJprFED3iyooPwIXQPogMIzPRRZA9JH736aJFEDgNPj2B4kTQHQyy5szGRNA/gimSoVHEUBZ0vsNJooUQOPo8+dDihRAsKQGITn0E0DVJUbEDH0YQBQQVd5qVhZA9c9qPA5EFUAw/Y4XC6kUQHhvY7pgPRRAWhsABxXWFEDNFK+b4p0TQDPm5KVQcxFA8zGLiqHtFkC0nCkrgv8QQFM9GNrKgBRA8lyCNUdZEUAiXvn8NisSQLMNM+HRNxNAM4fFJUoSE0DTsRw/Yx8VQP5K1YOiKhZAYC60cjskFkDn7twkxL0VQEKxx6lj1RZAIzrwgik8EkDhGyeZQ1oYQFcXuVTxwxlA02xwG2EsFkD60D72qG4TQPEbmQpsOBJAX9HAIATqE0DGof0JGR8UQLmdlTttUxRAdGnYBlKxFUD4oEhHSzMTQHFpPcSIOBZAmD2EmxHVFkDBY0zvjr4TQLjugVBfXhVAskFLaa3XEkCXFisZxAUVQLfkRdV/7RJAOGaWGhZgFEAa6qy9THgQQPCZLMU84BNA5ETtLDbmGEDwJdi2zDwWQJXNb4ORFhVA4Z+AaTI1E0BdPPSQJXYXQD3VjBlb4BhAOd2SeQfcE0BCTpvNsQoZQNM85T258RRAdloZCyGyFEB8CLwJdbkUQDCdH/LHmRFAQqj9+BJXDUC4pWwxJSURQHJI3b1MVhNAEqBN8nt1GECa1o6Xd+kRQDhlYRBuixdANIqEssAUFEDBJrdx6hkTQHgVX7VyRxVAtIOrgn/hFECwECWH0EETQOGPFKgfExNA+6XTJIvrEkCRzzWD/mcUQHR/GyzcERVAemTQ9G8CFkAafyg4jaIVQDW3rZqLnhhAexJ9EFJRE0CqB+/5KcYTQCmjNqMz6BhAPcxoKETkEUD4kgo2kWEVQHcWYrNCURNA3LjboZIKFkA1rug5zMsRQDnvxU96iRFAJ26+o+8pFkBjplRuJkwSQCls2P1pPxlAM97tZntiEkDicI6lBmQVQHdeTJ1ZFhNA+vwzaKHSFUB2qNOqXZ0SQDAzaQxOThpAAGxTpbykF0D0TiBu5OUUQLvnEa4P/xRAVSP6el9wFUA9BmICNpwYQBJkYRWPhhRAOB8AKZE+FUC1YhsWZGEXQDkn6w8vNhVAuevxymAzFUDp5sM+XmMWQDWvX0zogRRAO/Qw+esOE0CTUmW2aV8SQNUi52fQJhhAOMb7MHoiFkAZm76D5rwXQKU0r+kPCxVAuVxSMiREGECiEj8wmmcOQHaXNcub+BlA4SiSSShpEUC/ULImt8cRQPwsCV3SqhVA7G1vXbEmD0DAYfRQ8H0WQOTuscz3khFAM1uM1sPVFUAzAmyLdbAYQJjLWf8deBNANrMpfXoOFUCi7rPYfh8WQPHtNj+k3hNAUWGCqCshFEDzd3msvG8YQFRtcio7nRRAM3/Ik7SCFkBqb5qHBf0WQH4C4EYJARFAO2rvjeN8E0BWYzNkllYTQAEM3pF3kxVAct9vCwyfF0DVOj6ifuQYQKWDlvGsGRRAthoMyqM2FEDZw7jGWXwRQGDwuKJB1hZAEy/IoubQE0A3Xfsqew8RQJQ4ud5KAhpANFc9P50WF0B5AUcp2I4TQPV9WzIgrhJAEiVcPZKZEkDySlesaVoTQLiTK+MB4RZA8NoPw3zbFUAwKTeB6MAUQPwRRCw4RxRAuMl0CAw7E0B4CrzMjxkVQD7MQqeDLRdAeRo/7hszF0BiKLdOFzkOQGJUIuytYxZA+dJcrMMjEEBynrzQz5cUQJHyaN35chZA1I9LLOoZFUC0kAzSU9AVQDQj3saXeBdAWE9R9ueJFkD4OwgxO2sQQGGJ/sm3DhNA9KW95HmgE0ChFgpaBZ0UQPXjxHKX6hRAWdGBVYkREUA5MpdNW3wWQPVhSz+tIBhAdTGEeh5+FUDzR6sqhZcXQLlEane5fxRAcy0SuirXE0ARrFnwg2QSQPBwi7nZURhAQztTltWyDkBRmMRXRb4TQPmpQ/yF/BBAv/C1qR8ZE0CjFKkALxUTQGH7uadaixVAVeUM1gn0FkDyEFvZXQ0XQHJWnU5R9BVAmY3SHQskFkClTMWp9tcUQPmvcV8bPRZAOvO9uaVFEEDJPgCzM1MTQHAOzI9dYBJAWZynHoM7FUA28o6HXRgZQJh4JZEzmxRA882KcAzaGUBcUDxpkKgTQHR6+4kF/RJAEXbWSrsIGUApuhCW308PQK4kH3iLThhAMb+XRrIxEkAyFfPpZF4QQLj6r1ZthRVAHVv70OPRFEA+WbKmHw8WQDDuF5X6gRRAe64IPgzgFEAkRLeIju4TQBVvFsvJ1RFA5eE9MoB7FEBeywoI744SQDBdpagDPBRAd9zbk/pvFkBZOsKExBsUQFmM/g9BTBJAEk/JPhsTFUA2kWZyCJkTQPk38XJlJhVANVbjGQF3EkC6hmCG474UQPWHtNhGSBhAONev+d1MEkA6pKI+J1oVQDEIEIKoUBNANE9yC803FkD1FxFCm1gVQLTnccfANRRA8tlbs/mBEkAl6OdCQ+AQQPM86AiliBJA+E2M3+NaFkC9/O9lr7MVQLMuk7WVmRVAk/LBLKJPFECi6CadgAUTQNFSSvFZShRAMJl7517zFUDwgRqawtYSQPBEgTiFqRFA+RG+x/OiEkDG9e/7Ju0TQKoq+i5TvBJA6Uyfs5xNF0D1LxzWOFsUQHtHPXmkwBZA/1JztQ1AE0Cyng01S0AXQFSh6wncSxJAMmh+JvgnFUClAwarG6cXQLPQEKWbGBNAMA3EsDqFFUDx4rqiwccSQPT01NqjKBFAJdYne8uQFECp0ybfitAXQHDHb9Uu+hVAOodExmf1FkAyMQONxsMVQPuGLu0zxRJANXUuEYMGFEAxzLSvv58TQLK2k2mOyhdA5D+aLP5YFEDSNFNlYOcTQBLcK8vhaRdA8EjEwMLaEkDzga+qwpYVQHEuKNFFXBBAnk7KZynNEkBTPrhIEyMRQPKopz/9jBBA8KECL+d/FkCwiptidcUVQPwjET1WBRVAajfAt9bzEUD6Cwk6CPERQEAnL34v7RRA0bouRI7RFUDzn5Dc8dsSQLvUxiHfLhZAl8ERQKGDEkBY7IeQ5gQSQDi9Z+pSWBRA9fyp+JbkEkCdSnWmaqwUQLWS+sNakhVAEVSVmCGRFED4BkHBHuAYQHgaOrWh5hNAqynQsni7E0DR6pR01NQUQNj4PxK9GBdAkvy1clSjFUDoJU87pRcSQBdTwcXeFxZA/wIS/PjMEUC5Yr7IeiQWQLB+FLAb4BFAsHFMdnSSE0By+t312RMUQLqUzpZzZRNAuL1pXYWzFECjcW5qyTAUQLxeZpJ6HRhAZmh7agG5FUBy9vlP200SQBLqpstcYRZAMovsL7+3FED4Zs0eewsWQP2tG+7sBxNAaLxxKsihEUCVAtdREuEVQDFwRgsayBJAUjPI17e9F0C6rEa0QXATQLzkpsCPwxNA3xLL0hnUFUCyPT6uobESQHD3q+QbKRZA/Ku7B5I4F0DwUnRn5rcQQPU9YEhBGhhAuSqUPlrbEkB1rDdH7tUVQP17yl2ShRJAnDX6FXJSE0DS+2dQFfURQPBLCSxchhNA9OReOGYyE0CzKnAL+v8XQDJsUw9P7BZAs5db5T71F0CZtxzsfaAUQDI7yutaXxNA+FzA7m16FED2J5i811sTQPmwntRiFhZAdEnEqs1FE0A5emQCVNAUQPEGz1GqGxRAIdvLCqY4GEAwdCEA5I0UQKmEKRdz0BNAkdR/ghKEGUAUkaKeIpkWQPg4ncKX/xRA1q4YLV2+E0C8pfhjFjcUQDZl8RZUoxVA8i6ujyiaFUC1UAyZT1kVQLQCzTWcOBdAdxphrYiHEkAytG6IAKcSQLKmH64/LxVAlPWvHFenFkAi3+ZJGH4QQPNAoLrogBFAMWSxFYh/EkAY/teSdCcVQJOXAQMy8hVA/FJaG6L1FUBTfi2MV6kTQJflh6XJ+BJAkWD1tkVpGEAzbMhl4M8UQDi06G2u4BNAerXzhKMQEkB21RX6JGYXQPQ1htVD0hNAcZd/w/SwF0CwNEFj1Z8VQFnZDr4GbhdAaQbIM+XjEUCwyvnxZ5oTQGxx0RKpkhJAlVEhU71dEUCVo3crDGISQLfINvDAzBRAuLBooFHJEUDappVH648SQCqB7ScIuhVAuMcIgvVJEEBjWKuYce4UQHuvf4aqgBNAoRx0IHIaFUDTNiSSSrMTQLPot7vcuxZA6VfBUUIvEUBhhhTfdgURQFZyF7l5TRhAeZKRl0x8EUC8rdHEmlsUQPE1QDFmZRdA0U3KGO4SE0A4VBkzQa0TQDCn1PqYXxRAtPh49QxMEkC3LWvrhqEVQBHf+fplLxZAM/a8/KaOFUAptLeRTYMTQPjja/3+8hJAk7pjo23kGUC0OyRYPkUWQNM0JotbmhNA+tw6t4VcEkD70E9Qm2AVQLVHbQTsJxRAmm7Pilp6GUBDM6AdkccTQNiHSCdWJBVAdkBtVbSpFkA0drrD9zYWQLMwQzDEHBJA9Mr+kBvTFEARph8qLxAXQHlhwpnPRhJAUmLHT4bWFkB6fHYa7wwUQJjciYM5khlAQ3JJekRiE0ByMa6XSugVQLhzVTOc/RNAGoite3XxE0CUUO63rXkUQDR7PsLMHhZAMZ/ih0EME0CTCRMUk0oWQHwZBcn0KRRAwJ3kY5b0EUAxHLeH+JEUQNrnDp+YrxNAcQRYGtIpFEBRGE/noPQUQOWddvJgyRdAFHJLFoxBFEA9ClX0HM0VQDF3wZL4qhFAcibPs5cMFkDA4bw/61wWQHmwQ4DLjxJAsKEefsIiGUB5yeJOjd8VQHZ92gYT+BBAPPLRPjWZE0Ap2KXf3rkUQPIiQBr8YxlAwRKml9L1E0D4y+4Dda4SQPUTDVqbZBRAcc361prRFEDoxzlCKmkXQPFRDtqtSRhAcF5UdVRfFUASWsxOfjEUQPfLAUaoVhNAsZGaBr4SFUA3d9m+Z1sYQGD2h8f/GhRAMCGzgT4rE0Cp7uBSF34VQJrlLOCskRBAHWNsVtO1E0BX6VPNSUkUQLBGOu/iBxFApJbRhCuLFUBwghTElQ0UQJaVlFM4NRRAFTxTNlwuF0Ch1V7h2moPQN0hLBYFcxFA3MxwyUYyFEDwbZVVynoOQDMOxUrY5RBAE1F8zj+1FEBRzGZY9VAWQFoGplLgZRNAOpJwn2uRFEAztgrFBHISQDAoAFkIjxNA9f+m4gWDFkAhkq12kXYWQDQs7PiDqhFAWB5tZQvcEEByfu6DuhkUQDGV+as7pRRApBkrdDcdE0ATIItXAe8WQDMORAzuhBRAdjmpprjXGUDwNmRqgyMUQBJea+cHiBlANxypRNucE0AbShAmKtcUQDbRqyXt9xJAZbVxztX+E0BXkeiJKIgZQDWnEKBsvBNA9OeItc1iFEChjeHgUWYTQFLljHvdHhBAt/cm1AooFEAzOK3TBgcWQCJB5/NCIRNAU8d3hd6fGUCxrl/sZeITQDV+F0Ax5hJAYIuNSdaMFUAx+cnG1S4UQNJWP2zATRZA+I5Q8MMiFEAy7c6yKAkXQPH9nq9YchdAuCcNwAaCE0ASPz11q2oSQGXx0geBXhVA1eoSQSizFUDSLWISQ3IUQPTnOyjxBBZAMj9n5u2IFEB7sq8vdoUUQCT0/PsERhVAsibyghueEUCiecsO6lwSQLjeKwmWbBRAM3CBlRf6E0BZFJdlExEXQJUef08pqRJArK4r1/thEUB5LfYTMIwVQKKYngr4XRhAYELkgDkWFUCwrL5AzqsVQL5qaRtprBNAHq6BFIVTFkA6numxaqERQK7pKf/gjhVAeVUXNOvQF0DyrNhIdYYWQJktHDWnrxpAg/sOOr4YF0D/XKkvH3cVQFMZXpRbgxJA0ufDl3fGE0DUMvA8+e8RQDHJmfOfBRRAsnX8svl9EUCunKQD6r0TQLOzYFsPURdAs2W3KUenF0CKdiJ5O9YcQOSUj0fHbBNAseI0JUWKFkC4Rsa3YMwTQH2r9xrKkxVANa7iAQd9FEDZzv5Z+/waQPEVQxvr5hJA2fYQUIJ4FEBayM97Iz4VQDNjvZXgihVAOI/VBBvtEkD8doV+LUAUQHvLZRqH5xZAkRLrfaV7E0Dxar37Z88SQN0XuaVyuhFAOWaG1Xs6E0C4mySO5zITQHI4ASBHoxRA8MnOkbBYE0DzPtw1dJYUQCdDLo0sXg5AWRQInAxTGkA56R8KI7cWQH4QzANtXhdAc6LFbaDKEkCKf+RwpPoVQBP+Q5mHzRJAduXjME52E0DBOAX64Z8WQDE5aVc+VBRAeiJk88MRE0AzH58OkZwXQDcoLxVGfRhAsLS3L92uE0D2iWMmHLkTQFGU2Dc2AxRA99V47FFwFEB8NgqmmawXQBPbyHC2ohBAc1Deq07uFUBwuqR1FNkSQLNBS+eJmhRA+NjAaLBRFUAy96IPcg8ZQPQT7XJoFRVAk7UhNrMWFUCywhV8xHETQGWUX4cxCxFAOyKW3YWpF0BV8+dL2PgQQDagT4gepBZANi0zGBlUGUDyiEPRTOMXQOMKqZblHRRAs2dBugcOFUBTFzekGXsYQLMWuEImzBFAuoLU/AwcFkDDxCtVtUISQL80ksvfphNAUgrQagIsFUC+SSZohZwTQDd7M5uhtBZAs3y0YyfJE0D6cfA7p4UTQFpKH5WxsRJAuIdOAy6hE0C3auDWE18UQLNJkdGENBRAsgY+vXuOFUC55liIKRAVQPrtgWH8uRRAuC7S9cSnFkC57VLwkncXQDpGppfMGhVAM91AXKziEkA0L4Jm5y0TQLErKWK3VxhAMtVtIGzfFkB/Hlgt0cgSQPJUn6orRBJAEv6fx5kWEUARFqin7e0WQBilKnbVFBZAY5tYSzPlEUBTylc78OEVQLBDG6phRBZAOkFO89aNF0AKZ+QTjigVQPhFzgoKUxZA2KgxllQxF0D6h4ZuL6ATQIBZlLV44xFAksnozdIyEkAiqQRdzv4SQHrrklWtqRRA9UDQFQWiFUDilS8810sUQDmh+354PhtAv5a+84DIEUDxb7dxezYXQPJDtpwx8xNAdRx+pf1eFUAzDTfYBq8UQLqGHAya3BNAO1vblUHpFkBXlvK6bdQRQP3ZHcTEtxZAsRaOClTmE0CzBsNoR9oXQHhwUGSRyRVAdbiY3rBwEkD0Q2k2IiMSQPzRPtpXnhdAIp4W98bdFkDkxA5wgwAVQDExaocD4RRAWE3IEAe3FkA571iRN9sVQHN2vFBX5hFAWJeHGDHbF0B9/BSpQ+oVQHsZvebM/hhA8HPNKKCQGECwg4upEF4VQJG8YpJ0TBRAMjtd5+9GFkASoZCBd3wVQFbxuqnFkhBA8noK+fl6F0DwkLr59fQYQLirAA88rhZAuSICEKwKE0B6dWfOCbkWQPVV7ji75BRAN2y+mMaZFUADEn5gv9kRQDNWyb1c4hJAMoxH31AWFEDwC/A0z0wTQHbQb51WBBJAwTgE+8vYGED4gGeyCdQQQPHFdskqsxNAMt0hPEysE0A6gim5o+sTQL2YBAI2iBRAfiPRq2tSFED9fMsPHPITQDRJs11ZTBVApyon/H/nEkB1lBBnovQRQPFWDeu3pBNA6Uf/jIZOFUBRLlpwsTwUQLJkc/lxDhJAWvFr9MwPEkCS1yIit44bQNenegOc+BVA5npclM25EEAwm2eJNWUTQPJngDFYkRNAeWSyXvwLE0AwwmZfvZcSQL6tmBFObxRAdcd5c8SPEUDYxr5jvlwRQD+2MQQSrxVAvGPBqQRyFUBxapYzW4QaQPNcYT2APxVAOGDSM0+LEkA5QYnJF/sZQDVXIV/FchJA1xhIovS+FkC2EwOz/AwXQP9+TUrOEhNApjjsgdB3EUCjtGIpr04RQPIZMc3g5hhAsv4UbkkCFUC7HeAzavwRQPuBv0xtrxpA0k6YdumDEUByQHaEN0sSQLGjDL5v8xRA/wN5mHtLFkB6wr0VRukXQHk8xtPtjBJA8PbnH9COFUD4mVx5pPAVQFHvYz3B9hhAciqq4RmFFUB1ZMNIigwTQDCNF9Z7hBJAuNwHXp08E0BAz9xw5GsTQHJEdW3WehZA9dL5kqc1FUBdZKfX6qgVQHPZD0MrBBVAu4/ezl9aFUA5mfkFXeQVQLw8LeQYbhVAuRO6xNHtEECwdjWEadcUQPrWH+dp+RdA2UP5KjruFECx0qQgzfAUQLc6QfosARdAcPGllhVbFEATpeFB3ZUYQPdVAQPENBVAck8Ne/yGF0AJzQxtuEkVQLGIWDqQlhZAsQmOV3PlE0B4yx2hKyMSQLAUpOy9mhFA2siUr7DFGECydNqIoKoSQNtk+2eSNRlAtde4RYpXF0D4cJJUrGEUQHIGBtnneBNA3iJvT7FlFkAxCKflm88RQNnSdZADIRRA8hq8IJZXFEBARXajIDwUQPIUNEw7xhVAdZlHbthKFkBzoSBIhX0XQCmH6eqOGRRAMPkCUPVyFkBx2au9mokUQLZEYvKI6hNAeLej/9lIFED4fn6PTgYWQFXdGnnH8RVAsUi636dUEUD7FUu4gKASQPiX3TCSURRA8FN1kD5AE0B7b6N001cRQOnhGoagdxNAmYyyrd0VE0AJu26xKosVQBfNm6Y72hZA8dxoLrDyEkA5gUR7nYQaQD5WtfDxaxRAsI+/RR9zEkAzbIdhOY0UQJovMTk3hBRAASZbCgxKEUBp+rrk9gIWQHB/cPXvdxNAU9zPNR0iFUCzbKVxx/oZQJ0KQcIqUxhAfu5DTCTUEUAmBtoqzAoUQPiDIZDSTRZAuyiqhlkaFUBxcnAJuhYVQPpKsn2LIBdA5VK/JHSVFECpCDUmv7gYQHDu5ZLzKhNAFRBruLUqFkBTYiuvlcESQFImr5gFjBdAV42h5j7+E0CwWwzmQkwcQLhPTHXeMRNAPDYA8TEGEkB5kSAK6YATQJkgkEudDhRAeqyy9QTREUAJcO3IkXkXQBGwPsJzkhNA50cO4bnAFEASR3TyDdYVQLFHNKXvQRlAMr26uWoMEkBZZ3J6qc8UQHIY8W4HaBNA9NjCxicOFUCy8paT4c0YQGJHiIl/txNAcj0On64CF0BwtZvIA+oUQDQnQceAfhNAQHUBEjj1EUBRIAYEQ7QVQLH3BYxzCRZA9Lwo6iQEFUD4X78jyK8WQFgFxhsBYhlAHGDFhqv0E0Cr9wLVYb4UQHMY/tq4YBVAFz5/hgBCF0B39rZ6itgRQNKhE/YvzhhAMIXl+sBmFED4IaNx/7IRQLcJkipDNxRAkZrjMc+RFECyESbgmmEYQDEqsEz/6hJAubyWBVRnFUDREg12jeMWQHqhWoM8TRVAJe9KKxOtEkA6UOABPsMTQPlaa203fBZAc2sQ8ToREkCzacwEjekRQHe/Wl08ZhZAUyVDXbR3FkDzd346aigTQOBIlR11yBNAO7fGMvhQEkB1aGUgY1QRQPcaJLZeQBJAeWt/3PWCEUDgToEKsAEUQHOt4WBAuRRANtAEiXpEE0AwUgzlGOAWQBbDY7lDehNA/KKLsqJxGECT+H99SF0TQBGPndWMqxNA8GJIWAGjFUCkNpbd2HUbQHJbV4VCyBVAnOpqzvN0F0DyPwvRhMkWQPabEdRaHxRAuB6vhvvYFEDSmhF2K/IWQLBTOTbqfxpA9jwJq+0yE0A2CRzHGqUUQFP9sS+mLRRA4TYSuHtzE0DAKy/BnyYXQLvoCPw3uBdA8aH6VkuuFUChSRg0oIgSQCI3GdRoJxJAe1r5CBO8FEB9LNgW5XQXQHAZpC0CORBALCn93JCiFEAa4w6gzNoUQFad3rztiRlAPfdyXWO+FEChCZJ7DicVQDzrlugNrhJAtRXBQPJmFEAW38ZBZroYQPHEKnXGKBRAYuzFcHxGE0BwGQwIxs8TQDZp4CRlOhRAc4Ryb6NLFEAWEHYJNXATQHCNC5uCHRpAeOCt75nJFUA7YnOwOcoUQGJ6TX2LIhFA2J6lzsm+FkBwmdGB4UMWQP8jeJi+fRdAdCDm9Hm0FUCaSj18CD8SQHgWCDG7nBhANpvZM5WfE0D16ej68nYTQHcb3S8OhRtAO2hQnWHCFUD381jtnJkSQCog2EVKBRRAOlZlhhfwE0CSRu+uxcMSQPmqPTeiKRJAc3OS5pHHFED0XIehOFwVQPmBw0QNbBJAOKSAlAlcE0B/q8aYoTYXQPQb3DqwshNAcx9To6paFEByVA95JAwVQLu/aCEFYhhAuJsxlNCNEkBlCOo65a8SQPxjN7eUBRRA+2N4gYDyEUCaaHWrjGYSQL8ZLmNutRJA9XO0OkWdEkBR6X4dWk8RQOJ9+HcOxxNAIolDmIguEUAh64wfHvwTQB3i9aVNqBRAIeAQUZNNF0Az2FtyheQRQPGrFP01chtAkQvqJFBtFECWl4+ROvQTQJGxNol/wBJAJLiEwFU3EEAh+bbqzpkSQFcf/Uw0phhA97kqRhEnFEDSVx23vuYWQKIJG7d8fxNAgDXPyrIMEUCiLuSS+toRQH4U4Vw8XBRAo2OUUi+dE0D2zuDkml4YQLkV2eklrxZAo5cArOY2E0CRnbrTij8XQHWKFtwgPRRA8Vmj20EQFUAXRr3IEgoUQNie8DOgghFAuZPCp54XE0DApcD+SEgWQIQK+MMnFxBAslC8VIX+FUBzFjnXLuIQQPHbOj5JvxZAOSKMX4HeFEAqiw0eYtYTQGBGlQV5JRRA2uJicFNJGUC4jTAyTFoTQDLuyj/8jRNAfsevwjJOFUDAJFcJOeITQPDaBpN3uxRA0hq/eEPSEEB0TrMypbsRQOmY2YCSnxRAu4a70JfEEkCso5uHoEcVQHbIpnoQUxdAlpLfzDFlFkCrEXzSgEQSQKcnXrrhrhZAah3i+gNLFUDVB5sXtegTQOKnpwmlbhRAbv7FtgYgD0C2/ByqOBARQLT6V4RM2hdAed5zsRYmE0A0V6nek7sTQP0AkVO4cRZAIkVz97y7EkAy5yDZy8gWQFXYyuwAmRhAcQpugBPDGEBhXxzrJUAVQFnSAXe0WBNAcSf4rAeJE0DXC1zpuxEWQHnQ3up5oRVANUBtoI4ZFUCjepG/CVgVQJIZu2F0khJA+64J5AFBGEDgOic/9VYWQL5SYioUCxVAYlFLOo7hE0Dwu4Vxj9YTQDMPQoM9ohRAtjen4WZcFUBTQfABxigSQPDDuB/hKxlAkSgrZioLEUAxjvk/9qERQPK4bqFMKhVAFuyaPLfhE0A0ZfksdDsQQJx4/w/UyRVA9KQ8tj0IEUCfwCNRYWkUQGHSxeEmehtAOcT2S2ZtE0D3ywCZVzQVQHSpY8tZZRRA7d6hok2qFUDwFDVf5lQTQL71EHKEFRdA1gnzigBBEEByQjN9askUQIAO4057FhRAFf3tXMF/FkCwNuw1sdQRQBGrpIfLAxZAeFGHk8t7F0AUWHymrsEUQOkQN7BfwhJAVFVx0HGxFkC2gEBKzRIVQPrYDpVO8RJAnL4QicbGFkC4tFA98OIYQBfTPpoimxhAHeE8j/zcEkB6Urf+TToTQKZ7LY5SYhhAulnKOJdHFECZV3o4XgIWQDmEGozC5RBANB6hHB7iE0B3vqeRl80VQFn0LqWMBhRAcE4sKGH1E0CBEQDqBjUXQLDHnoTBHxJAuNfcO99MFUCvgNUSS/EVQFKGEKamPxZA2A6nrOJ8FEA7dokyx2gVQLW6M3l5EhZAtK/5hCIcFEBRvzTjv24UQJYdD+xepBJAin3y9WAqFkDwA9gaKVIPQDJsIJnHLhVAM2nKw5q0E0AyNeTKW7cVQLZ6QR73yxVA8ZUvN42oFUC86rPnDqETQDv7AZk3BRNAeSjUeeQTFEAhFJhCpokSQHlRz5P9kxZAsn5OTs9AEUB9DfiNxEAXQJiCWH3XaBJA4aZobSmOEkD0aYreT9wVQNr0V4DXHxRA9ekW0cwqF0CXNLg78+gSQBF4JPlHIhNAu2jRXRx5FkB4DV/OD10VQLL1dL1eAxVAk85OhsJWGEAXU0QWDxAUQIMHipTeNhVAOCzqQz+tE0D5o0b5KgwWQLbbiqbJAhNANePn5facFECCHhVHaIARQJvaSCmJNBZA+rInkAC4E0BRPJs5bV8WQLKbeQ7xCRNAMevtVKX1E0CjwHanfxQXQHBUiXLnixFAeZUoi6LvFkD1kiHoqeUTQBo5vyBAkBRAtHtDo3oqE0C5n67IdwsVQGBMKWBA2RZAO/vlW77REkCwOS1UKXUQQLj84AqqGRRA4T3QzbYzEUB7oUgBQJYUQDA5F/1gYRRAYR/Z6ISGFEASA8OOx5UVQFLMzmaIyxBA+O2pT2TYEkC4Tk/kRlcXQHGrQT42TxNAetl48mRlFECzAkTn/+wXQJPrkHQPuRZAbWOBqUixFkB73diowoYRQDXHg64lVxVA+DMamd3nEkD6qDcrGSobQKM0BJk7axdA8+qobKbHF0DZkZ1dvcIWQDTetJJ+xRFAeMHXm0oTEkB0pZgc6rIWQDxoEJdApBhA8hBjk/zcFEC42WXnnlUYQOLhv5gARxVAdKiH7oytFEB1UhzpQ8oXQJG23JPMGRNAuZ39AtwPFkA4qRjrB5oWQL7bXeZTcRVAcy7dl4OxE0D4IKkVB00SQPBn90RJkxhAq56vtFNmFkCwPz5SheMQQPimKHVxYxRAU5q/ylFqE0DtfuPv7BAVQDKrjwwZ7xZACK7zePXEEkAbsHcWHhIXQD1zUsd7HxZAsNz+C2joFEBXb7Xtnm4WQDqaF7w2bBBA+SXrVWewE0BUN6htXdEUQHmIGubXWhRAVJ/E1vrgEUC59LGOp98VQLBIrgVo4xVAfK6sd0iIE0C6/h8DF4ASQPQA2C7UNxNA/ZAAY4+uFEClgo2o4XcRQHMPEtKMkRdAtHuBiop/FkB4yWLUgtMSQDC+U+WBiRJAdEj9idzrFUCy92ls3ZcWQINGmWth8RdA0Ya14I4gFUCzGkRJR+oVQP12zHIsahVAdts14t4AFkCT1QArplASQNiz97fEfBJAdpRfJNhFFkABXst+beAaQPs9J83CnxZA8/U1l2dFEUC6BQCfRcwVQLanZqDBFRVAecJNQRCAEkDaUKnrXBgXQLliNtZvRhZAUqto5FTRFEA4f95AHKsVQJjy+W/+JBlAdDwntk4MF0BgZ4UdqGwTQGejvtY7QBVA/JVy3znlFEC6SuLgM30TQG9T6QW4dBZAmOgswVzvEkAfDXvG66gVQHg+qeamCxJA0oMGJioAEED1Q6NlfkkQQJbejo2KVxNAMGwhv2tUEUA14qxkmHAQQJhAaAjlyRNAYtswuVcSF0CD/PuB0hARQLlJeFfScxRAlsmJ7h1jE0DZKCr4CD8VQNPc0ZU7mRVAeeh50D5LFEDwKfZWQcURQPwuHmxXMBFAGC5WUyyeE0B07lC3zbMVQLfmyH6GzBRAcJJcRBKCGEDpsMhUf34WQL+S6zy81BdAZLT2UgNRFUAwOKj1lagTQHqr2oCylBJAcR7vqOU6FUA8mIM8aFEYQOBt6YGJ6RlAWGVS9Sl/GUC5HsbYtncVQLbVRwWn6BJAMEHHyj+iFEAzUn9QVCwVQLO3rgs58xRANMjQlB90FkDreo2xKnIVQPf+pnN/dRVANsd3AQWAEkAT0h+sJYkZQDkMdjQIphBAkwLKu9U+E0A0e67JQ2oUQJIPUr4eKBNAY8WCYJPnEkDRRNnBzXAPQPokqFnCVCBA/bZMiA6JE0BS1oirsu4WQLGTy6d4OBJAOjSeiqn6FkCbTE49E3oVQPIBltPHUxJA2zMyme+dFUCj4QHv7cgTQKxOFC5i/xVAqrpCHo9cFkDzMvG/+b0UQDlYUxEqoBdAUcqMFu2mFkDgU/3sduQWQL540mO0VRRAexQeMdRkFEB7VPlGhcIUQHi6/PmVjRNAdS511WS2FUAx68zkuQMUQPJ0UlBf/RVAP9rRAFUgFEBkeRZ2hWYXQFOMFFhYkhZA+cV4BZk1FUDS5GbfOskUQLUcv7vEgRJA/byL/7pyFUBSZx3Zhk0WQDiP76MLjRhAcXk308WiF0D4bvNcE+AQQLIVvltblRRAtDl8enhWGUA9eP7QLYAUQFUdpXsZGRVAVJjQUsTOE0D4uot0SB4UQLdqYlMESRJAcOB2G7WeFkCpNZFIjyoXQH5yz1e0iBRAGORRtB5pE0CUe2TW6U0WQJKT3vMYYhtAsZUqJUt4FEDznHnPxq8WQHuZVeIlJRBAeV4MrW4EE0AR8F4y32MSQCIt54uS4RBA+Rb3LIkEE0CRi+JQaLITQPep7hNL0xNAMYvnGiQIE0CS5ZXeiZ4UQDFOnh19qBhA9pfWn2f2EUCxkPoUTEgWQPln7mVTOxRA8eZlXvq0FECV4zjSnOoTQLoSZt00xxRA8jztHyIDFkA4AVaYNnMXQPclsdLOaRNAM69+BttCEUDRQwE8aVMSQNxGsh3JrBdAs2dSEHWhFUD68PHFEwkTQJgZEvFcwhRA9VTVQSk0FkD0wHP7cpsWQNjycvF4VxRA/qn/SCWSFkDjJgkZQo8WQNYVP6WJJBdAu0fuE4BbFUD5aEOAB0oWQCguMf2CpBRA40i6qGVhEkC0lti0Dc4TQDiLxqhBMhhAmHJ+D2qLEUB05WkuLWsTQDSo0iboNRJAYG4JDSKWEkDbbDmn1VARQPmMUwfdoRJAJFpB3dWOF0BxavjTPUkYQLX+lv/R3xRAcNh4nqEMFED9YKGlRUgUQHW4AVK62RNA/iD9hQ1WEkClK+a3F2wWQLANXtGquBBAeLjE/HymFUCwIoRIqk8SQKTpFba0cBhAOa7erzEUEkDwZ2VYgL4VQPPngeIn3hVAofVFh1rtEUDSPtWDsNASQLJTKG49FRNA1VnGYpFME0BgobfrJ+4TQDyraiCVLBVAgTCqUkljFEC4K94MOoYSQJI6/1U+OBVA1Ull98fIF0CUwPxL2isXQLi8gLHncxZA8sEzTcOXF0D3vQEVoYkQQGogDqvnEhVAeGEAC4VJGUCj/MllEocSQHe2je+s0hZALU8O6xN4EkAwdQ+KucsWQJPYNI5s3xFA/lM0B0FtEUB5yadVp7kSQNnH29rLfxZAebzM0d8ZEkA1q+vGVgITQHCBEiK78xVA4RSNqHiuFEDxwnpNEKwXQHVHrPcHhhRAGBdLKNR9EkB64vVXa5kaQDtp4OjBQhJAc8XRnOayFEBi5p4ZZAwVQDsmWbcrDhJA/LwEC2njE0D71BbJoScSQD4TTw3EBBJAkRlNfcrFFkBbKMJWe1YRQPe8Qy44FhZA8ArBtpZUEEDwER0XGP8TQHvWIndMYhNAfeEuGSgTE0ASTMKrJYoVQKGiPLe5UxVA9Ou6DBTFFEAy3mQZ4kAUQCq9q1Zi3BZAEjaTr3STEUDxRi+XDHYQQHcL5LxK/hJAMVTut4ESGEDTWWgKC3UTQPWGs+blUBVAkXuM8YsIFEBDIjZkrNIYQPDXSj/ZXxVA/OSuuoXlF0Dy2n6ttOgUQHCeaR70PhlAexIihavEEkDhwyw1gBgVQNivm49ihxFA+DWv05sbFUBRks1yvRkQQDMP4x93EBNAGrBpqaA+FUAkwnhVTkYUQGOAkoigchlAIRjLq2HsE0C63HRYPdgSQPBltQ3+rhZA8O96VeFJEUBx0+nroC8TQFNrwMX2GxVAd1RX5rOEEUAxUrWQYKMaQH5Hk3ObgRlAxMmppn/WF0By7rwDSUoUQHPbbucXoxNANtEZU9tiFUDzOfG5ra0WQNIeROhkeBFAFIA1pIo1FUBVFyK4MbIUQJItCJtZfhVAouHYpIDCE0C2/ptcd4wUQDtpew1KWxZAtlz5wlJUFEDaTy54MB4WQHigR8TqNhNA8OVR7uQzEED2EELsVjYWQPGuslRzHhRAf7N2Bx+uFEC6QD/XGzcRQHLywh7N3BdAmHpvtiHeFECicMnKJk8SQNIZJ5wH5RRAIhd5J9diFUC1gJdN51UVQB8Rr2kymxVAPEDEml0DF0AgIXIMhtQSQJHcO+Ln/RVAcF9aiDdME0C/uX32b4UVQNLZ6eqwthFAMoY9iw7zFUDRl8OqqVwWQFIpJTqVUhRAfQFUnqC1E0CR5Zm6evoUQNHcMyZ0mRVAYHZf8cj/EkD6buCueEoXQLLYjyMj+RJAuP8HbrRREkD8iQtLQpkYQPX0YbBROBhAEWaOwQJiFEB0B+l5dh0WQDYON+beJhFAMApHS57rEkAzGScEhVITQLSLMr9d6BdAMA4cpLb/EkB0y/6Xb8AXQPA8FWQK9xNAe19n5c5PF0BddooUv6AcQOM1XeKFpBNAkQL5Rga2FUD6GPhaxkgUQLtibQRH8RdAeMkQ6esmFUDgVua03n0SQLFq1jOrrhRA+tiFfQo0EkCRs+9siKYYQNH2wUO7GBhAua1j7kVJF0AYxD48n5EYQDa6Lvw9YRRA++haKu1pFECxhtvr7wYSQPWbudZc0hdA/AYI/KsOEkBwh96NXkcUQJKr//3L0hNA9hrF48WUE0C6ITSPZnYVQLSU5oHOHxVACQZC7XzWFEBwSZrqG/IUQHQCOz+AWBVAuv5sAP15FkAk7wHrge8PQLWtAB2wMBpAEbROHkM0GEBggpJLR2sVQDBelG3IEBRA1zSXyW9vE0DxnOOUT1wRQHg6+lc/QRZA8D8aaJaEFEDzPdU6CO8UQPvrG1OlVhVAdBzR+LLgFEAyCu9S72wTQHEKomX5WxVAtMBTC5HgEUAV0eZsRtsTQGsqcpPbghhAcVCzfZU6E0A3BBJ94N0RQFjRpvrPMBVAck4lWnjfFEC0LrhgKBoRQPBTPCz3dBNAOXG7E4PIE0B47jsqURcSQLhkNlL77BJANX9+GS6iFEC5B0xcC3wUQLKoPpRKthRAuhpvQ2dJEkDcj9RsgSQWQPfUksIg8RVA0tIP/9QuF0Bk2/lrtlwUQHnhAZgOtxNAsUrvsFUZGUCRP4+7iOUTQPCKiRkoNBNAsm690MOeE0CyyvJUn6gUQPHh+JmEkhJAUuH3zhPhFUDxCHWbiQsVQHYm5DpaUBRAsNsdsqf+E0A41pZqbycWQBwy+IegPhNA+O2YBZUxE0D5c6ZWmWsRQHp6oxeH1RFAIv/rvqdwEkBXZVhEdhMWQPf+snXxLxZAMSfaFjo8E0BxPXw4mIYRQLQYzluMEhRAsq4N67vBFEBSdbCqfB4TQDHMYTtJxxRAuTMKsoMiEkDxgL0sc38WQNyHFNIXbBVA8ITk5xYwFUDW55ZUThoTQHRD4C/+7RNAsYLvS3x5FUB0x9A60kEVQLx/J2DUOBhA9ftSAxioGEDzl9LhsVUZQK37Bac6HBRA8FASmMIcF0AdQiSnVvgVQL1wCxLUyRNAM0X66SyvE0DwGH5yQkgRQPf4hSp8UxZAcT15KwDkFECzR/4swzIVQBJvC6PkCxJAdXMCWDeTE0D56mfUDzEVQDel14W0QRJAptN+QokoFUAYOOr0UskSQFlUg+B7jBdAM+IoHbvLFkCxgDEZNpISQL7iU5BBDhZAPIJ+L6Y3GEB0G3r+7kcWQLbMB9s7IRNALZ0llpX7FECZCOED5UIXQLNnTS7bXBNA8HUXSPCyGEB4z+REm74TQLmJCClveBhA46aidPV2FECyyJfsHTgTQDHtuKwDuBFAsw1ZA2S7FEBpcVvykHIUQDmvCtk7/xNAXFAISYJ1FEC58Da2tygTQLw4cJCtzxBA/btEImuHEUA82Li9ItAXQHiw02j/OxRAunfSBEMmFEB+hVQUUmcRQDhOXuTZ7xVAWG5vMCuBFEC56YtuXt0TQPlk8iXaKBdAU3EEzP/kE0A4aNRHiWAUQPmsPIcSjxJA4j/9jpd/E0DkpSNYhyoTQFIcIf24fBFAMBVPpgfeFUCZEFhsANQSQDkxkiNwLxhAJAj01dOFFUCVLRrXXEIbQKI3DsyXxhVAXhOve/5BEUC2b8I1LysWQHDhJ8rgchlA5Jrpg8KSFUAhnckx5hQVQDabwFCenBJA8ueZafW1FUD2mhNJsgwTQOIl+sG9jBNAMqxL4PR7E0A0QS9IPXYZQHnwgkbkUxNA+TQD/mezEED6/KSPAa0VQHsxbg2oxBFA9ZTH8aT9FUBxeIzKcJETQDmqR93S6BBAITn7D6dfEkD0syv7wVcRQLmreNLNkhNAMRHPM9pKF0AUmsjFxeIZQFZtbesxuRZANqYoyFB0E0DRq/myaSEZQDLmvu4RSRhAM7QpHyDJFECwqrUnmh8SQOTPDv3HuhhAvjotfHiJF0C7TWqOJsIWQPhpPs70pxdAfnu0PqBjF0D6ChfDuRcUQFvgQvfoKBdAOy4K+A7tFUAR1u72WoEUQFG0ZPsGFhhA8LPs60bWE0AVcf9xK4ITQDSQLQITvxVA8V2eElIHFEB4ABm/sfwUQHDbuPlrUhRAC4uqjltGF0D09R3zOgsUQDQWp3ndYxZAMpgtuzR2F0A5F64PP8gVQPF6LjEDXhVA8sv0L86SFUB1QZOi6fYSQNhkc9GS6RVAqDtoiGssFEA4VcfO6y4ZQHCRpJxXjRJAfbWyxM4mGUB+SjJW9wwTQFjs7x4qSxJAc7YDVDguEkDs/SZ8ef4UQJQMQJJ4aRJA9A3PJf2oFkBTjhfvjgoWQNEzI8+gThRAMEW76m21EEC1ZdsGC08UQPeq6k6yChpA+g2vjVrOEEAYqOqXyD4WQHjYzaeKGBZAk6nFLIBzE0A5esnUqNwUQPVMHC+JzhNAuoFLE/qUEkATP/8x5y0XQEtgLpEFdhNA1FSUT+6+F0CywtEDspEXQLiozyZSZRlA//RKbW9dFECYlF5trAMTQDKhQORUmhFAlB2sxzhPE0A05lk//ooWQPpDMyhQPxJAsB3FTQvcEkDwnejjQE8UQLOP+Bp4gxdAvZRlMOX4EUCZz7KXPEgWQDBrlClyqBdAYdaijJLTEkB05xebW5EXQPe4BQPcGxFANucl4vuFFED3kLnN7lEZQFFqAwva+RJA8IlevOLRFEAwuRNL8eIUQLOFfoeSjRFA88LhGRAPFEAYPyTPldMWQDEjqBCsUhdAco3k2Lu+FkAT8VEU8lYWQLqhQPmZ0hJANO3GS6ZDFkCykMRd5CQUQNI37fPW2hZAiLnZcM1dEkC1Rtq7bdcXQHBa0yV2YBhAOAmyKIkKE0D1ciAEL38VQHEY6hmY+BNAfpbGeqydE0DXfG8HHygWQBzKFVYjsxVAos4ooLmAE0C4hUUK+lAVQDFIOIr1ghRACuCZgQTgFkCVNAVLRp0TQLkIVXCAuhFAapgYJZ+TFUC2dB2T6zIWQBjmbFBfkRZA9KjCnfoUFEBwzh0mglIVQPH85MpgORJA84bAUYA0FUCVYxTNVy0RQPy8XKXLOxBA+xScw8WHEUCybLI4wbEYQDyIS+0TYBRAb1kgq2qMD0DzcRlGfcYSQMGa4vQABhJA9KqXsWT4EUChHr7B0H0YQBrszMgplhNAYQwVtyG+GECUvCYNAHsUQDFOGI3v5hhAtnctnkcUE0B0xWOxsB8XQDR246ilDxRAGOznWIoIFECzXVBGOcYUQFqrvRYsOhNAlRMauCpAF0Bp/aytQuEVQLiuRvTXkxFAGD1Wpz04F0BzTKqa4fgTQHJdFMIU6hJA47Vdg4G4F0C5GfJsh1QYQHO83KSBoBZAcNExrT33FUDDzI4pxLIQQNrM0FufNBNAdNCCwXLdE0DaLPUsDmITQBTYLk2U2xVAq4oS4LzyFUCfKncf7QwWQHcRXOeXfRVA+pFsqM2MEkBi7zooP8wVQNlDV9m5yBFAdon18JSWEkCSeYakDD4SQBTforqsRBVAmzx1r9myF0ARv14KCh8UQFQh5Ws1ARdAM6GaifOKFED0LFJBKGcTQOK+4sOXhRFAuScQXDxpEEAi5Ol7FrsUQDM1SdV2fhlAMkCQ6Gs4F0A25D9i0R8RQHeQSkd+kBRA6OZT+4UrEUDX1+UQcU0RQGEn98AldxhAsblgKYwZFkB/TQBjBYAWQBETKmizKxRAdi7ENiN3E0BRUhmpX/8TQH928Fp+nBJA5kGht2gqFkCzN0834lQUQLD5mQP+1BNA9dAJ7k/bFUAtjLFq9N4VQOAEjZeOyxVAYseBFh1xFkD0ea3nv/oaQPie2wqDlhVAr0+WUBkwF0CYC2daSBYWQDbrmkbhYBJABR5kwvZ4EUBxqXnXN4EUQJFrzkD+RhRAdMFka5FcE0AU9OfN4rEUQDJ7ZLkkKhlAvJVnlXECE0Bpn/ABDl0SQFMue1NhfRdAuDyzeqJWF0CxoEN9S3MZQNEfSdhm6hNAFJ9JeCOJF0D2/ZFiHuETQPbIbMxSuBJAcCTk7UUGE0B0FYjE8P0UQPxso2DjehVAcXFIey3oEUBYH+IRVAwVQHP4kCLigRJAuA9R3SS4EkC6HroBBaESQLz8PucMcRJAIgZFQf8SFEByX9Lj6mcXQNEppS6RlBRAc1gFr7jqFUCTj4IU/1wUQLDLmXIDFBJANhEoN9r7FEB7rngohCkUQPwtPsjSzhNAO5fkr7ubEkC2A+Qwu+cTQBGxE3MtKxRA8MGQ0OJIEkAzVwtiHpoWQGJaLCR5/g9Asacx8SFuEkAyN4t5g9ATQHYTO66ryBVAfHmdR3UtEkA3HqxFHGQUQD88IDDX2RVAsK0T4BRHEUDTJf0qssQSQHfyQnhwBRhAcXlEpK8jFEDydNRYIqMXQFV3SmRNKBVAfcIDGCHwE0BiBUxK70cTQIwV+YQPmRFAcIYrBgHdE0CkQkeHRj0WQHQkQTGJ4hZA86NPNlAIFEBgJyW23N4VQF6OlhleFxZAPCdcXBnCFEBR0bmysLATQOBA4yRbdhJAoe4WD8r2E0BUaWJlkqUTQL6mp34z8RNAMmjkNhjJFUAxSmIxskoUQNPzQzlnchJAtH6dk9RLE0D0bZgc3WMUQDQ9O0I+gRdA4oL/an3+FUB7Fy+wf2cTQPC743ZZQBFAdlKLN8DWFEAxxrTYvMAYQHnxg2ndShFAWhiHl0U2FEBTUIyw93QVQHNNWG0vOBZAlKMYnFPjEUBize67x3gVQLFOYo/XDxVA4mpX6nROF0CkzKeyWSIWQNObw3/glBRA8UO00zrYEEBACMBTCJcVQNUxbDSsKhVAEZhqJmyOEEByBa1mf4EUQHCZWzUorRVA9vaEML6TEEC1URNt6zsXQLcpkICFLxRAuzSOLzBDFEABS5iJv0ETQP10xIlBChZAk0kd36bpE0A7y2rfDXkTQHHVBeGLFxNAtR+bN6iaFUA1KXKG6IsVQJQwI2Qx3xVA0RvXzDyWFUBqD1IWYwsWQLISJXms/xJA9oZjeTJsE0B3WsUMPecUQJdA4cb/4BdAltbHkh3yF0B2zVlzOOIXQHkFqk2EmBRAubQHIbSlEUD4PUT+URkXQDFZfif5ZhJA0dFqvsjaF0ChRxfVlLMRQP2fG2u4cxRAehvDCppfEkB52LLVC28XQPuR1mZNPBdAQAusmmm4FUARKdxCWtMXQHFXmVYKtxNAvhQ6IWtiFEB2LuklNdYUQPZ3ShUC8BNA4V1rqiqXEUCxh0jebPsWQHj4pimqGhNAMXR9GVFYEUBcR86y6cITQOENN034LBhAtVg6UwtZEkD1wAEaFCoVQPW8/yOGMBNA4Qi2+I5jE0B5I/U2Vm8UQFmzQiV35hpAs0ZAdCJ8E0DBra8KdskWQLE/STc7lRpAkuO5XyboEUDw6ERPmPwRQHGUFr+tsxNAv+DDtxceE0CtcBQke/ASQLaF+sAchxVASroqRywoE0ChuNoKyKEWQPoT0EH5DxNAtF5NgJtQFkB3wlB3QMEQQBQU1ZX/cBNAs51FlbI8FEDftj3kE8EWQOCu/CldFBdA2hIaLBa4FECye70dr8YUQFgRbsS7jxNAYEXebJnyE0CS1t8o1hgXQKrADCwOphRAsNgR30QkFEAc/f5wIKwTQPNWmI/bRBVA8Wm0RcduE0Ayx6A2fYQRQJiPSpv54hFAVRoIAoUJGEC3X5fHOwgYQASkEOTTGhRAsDAp1/YxFEDg+EbQKcwWQPfCSMWt+hhA8Gx6QiiCE0DxOygxrOkTQLR6yww06BVA01PQAVv4EkCxzVkxcVISQLm3GHx9MxVAOII4EWCSF0BwWUtaDFAWQNge+xG+3hRAOTqr0iKmGUDCvYeX91sSQOUdvH0VMBNAkQqwC1O5FEDxkyw/0uESQJa+a89RIxtAcn1Hfu3vFEBxfPoEajQVQGKg7ZemSxNAcuy7rjvzE0C0UnAXqMsRQCaqaltjvRBAsadmcKaeFUAwC2cQaJcWQLS7Yf19aRFAckL4r2pIFEDStt3CvMgaQLPv71lrbhJAeizYP6DNFkB5cfIESooTQH2WAmnIWBZAcG79sqe5EkA0G2pWb4oVQDEXQSLpBBhA0z4EPEybEkD0doMG2L4SQGihEEiBBhhAd+pepxuYF0ATJLvbJtUUQDOryn2AzxVAtVTmvvcFFkA6fcVjJTIUQNKazHCc7xFAHMOvjxpBF0BB+nPfD4EVQGZFKEdiQBRA5SIi0jw7EUAwDYx3T/8QQHAnBmcFEhVAFt08399xEUBRl8gAtPkUQHGrGkj+cRVAZpTsd7oFFEAwMuFP9OITQHHl4u3vOhZAszcg2eTwE0A1Ixa79wYZQCRrxxNkqBJAWdInzp27F0C0hRkBL80VQJFgKii9TRZAdi2sFYBvE0D1hqW5zRITQN2b3o+2uhNAsqAS1Or8FEC4xjPoVZURQDDaIAL/7hFAARyNgPNzEkAwgQenxecTQPXs5P7m2hZA8Ue0v22EEkAwUpn1hFERQN1dPioh1RhAtFZcpfO4E0AZX3ZRAdYTQPR6FpwOLxdAuhD4wjgIFEBT6diarF4WQHGvrSvcHBhAMinh1BgRFEBwju1qCsgTQKGMGkUhchJAODm19So+EkCK+/yoP4oYQPL0AOCXTxRAMuWU/PQVE0D/atdO/ycXQLZAJlNBhRRA9X2VEjBkFEB5Zz1b+sQWQHMUke5JORBAlUqSKI1BFkB3/nL1B8YTQDEdOjs6LRNAebbmWkZOGUA2fb5hQJoUQPs/Yn5z+BZAciOlnOwuFkD6ri2WSRcTQPvBOagUuxFAMONCrteSFkA/XLDBqhUUQLNAAd48gxhANqpUPEtNF0B5R/RJtAgXQD1co2hDVBhAYOVEvLJ+EkAx8ZJDgQ8TQGHakUzWIBZAdJbADHz3FUDYnJTSdKYUQPhH+Fu8WRZA49JKuOv/FUC5sXuuibsWQDJKFoOUCRhA3I9mxHjaFkCYW//NabYTQHFewAstmxpA8TsQ32H6GUDzzuUBriYWQHFv1G6EQRNAtokgY1/UEUD6OWHz9VQSQL4+lzmZQRhAfBeONcueFkDZ7P6hUWUTQDHX4VDLrRNA9tt4t0X7EkByZvlj60YVQDhNsU2jbRZAPHAmDJQwFEA3MTaZ/5gSQHZbl7CrRRZA1avVPyl6FEAeIdwdRVEWQDCZrp/ocBVAsGGrI0O1FkDxLK4GTnwTQAHH5Hbq6BhAvGtDUNtuE0AT+AVuq90UQP8xSDzL9hJAYoH2DDsYFUBzBv10AmsTQHYP+wF+bBJAI01sJi8OFkARAA9qIdoXQLjx6j2gLRZAZFG9kYTVE0A4Bs9wNJ8TQFIbwds6IBZAuP8kqtr1FUCzxB/iyZgUQLYDK4Yk/BRAeCGgIX6PFkAwIa3US2oVQJiNpXGmhBNA9dvLoTKJFkB221wsBmIXQPKBNS8zPBVAtBjNl6BDFUC61B+aoUEUQHzfp1xAyBRAu09RQQVCFkC0tmqP4X4SQF6c85gmDRJANdG18N0YFUBYr2Ik2wMUQJI5VZpgdxhAsIq3gxKEFECSh8NPdu8VQPXo+YDAmhJAXoXpDjlKEkBzHe+vpfkXQHeUJDNE3BRA8iJoxFE8FkC9YBstaLoTQLM5nLdQMxRAMuZ/4DZnGEA5teZ+r44UQJF793GGLRdAlaBI/VoPGUCzs1iK/K8UQPxH+sgoBRFAIcZgU683FkB8OaZ8k30WQPmbubKPEBVA9cmU0vd3EkDyTFR5f2sRQPJMhrRp8xZA0r2RMyaSFED4KHPmE7sgQMOiGY7UGhNAtUM6f5ddE0B8zD2Nr5IbQLR9S81gZhZAsGYN4mjPE0Djk0Z9QmcWQLatRhczGBlA8KCzzj2DGECZvEdFPAAVQLGCFelJphBAtQyHEnVDGkC1w5Ymq44VQHJnSjrbgxRA4GXE99KbEUCxVeFoXtoVQD75urm9bBlAOvbMGKOhFUD5EwgrK/YTQPQEF3WO4xRA/AP8Mqk0EUDR0MnDnZIVQODcb/S08hNA9k4TuKUMG0ASLWzIU1sWQPsgpBSCEhRAMOREndJZF0DRFmFg5CQUQHS7ds9T/RVAMBYIjwlEGEBwlvM3lfkUQPG2nGbwEhdA9gGGjoJHFkBRjnpfecIRQHF/31hYCRVAsAx2AVEcE0C7FfrOgVMRQBGnl7HB2hNAoXGhrlv4GECyMXwc5j4QQLwOA92cXxNAknooIQBRFkAzK1JkDHcVQOEMFlus8hZANMePkVamEUBYyxoVkfEVQPFhbf+xeBZA97JOYRz5EUBRwE28IpgUQDFM7sqHvxFAM5k83vcVEkDRwdkBJDsPQLJutjtwTBNAcRza4qmMFED4iXhD7CsXQDLbomf7nRBAOSr0Z7yBEkAz1fYi2s8XQPr0CkkIHRZAVNgnTKp4F0C3kaEjYBoUQKJChdAoKBNAIXrlmtj1FUDT3uBUEo4TQLhpjwzVexJANXdsO3ssFEDzFKJnnpcUQFLh8ga7hhRAeZNDyOD3F0CWaxSWtxsUQHXop3GUIxdAuaH0fHf2FkCqf+akYfEMQKkKeYzr+RdAupiLzeVyEkAxqgFMH+QVQDa+61EDCBRAtDlSRgAbFUCxJQd+V7gWQDqT6Ht47BNAcATsw6fmEkAWKCr04mYXQPNZNoHFFhJAIviLXeNbE0D9NV6e3dkWQHCDoi1TJRJA84yHDgk/EkCYfOPJxEIQQJLNKes3txJAtIqPga6+F0A5abRUiB8VQFFHhLJO9RFAaxuzaqgvE0A+G/mE2wUWQPKNzo/ZzBZAIWLdvChVGECz4SqkxskRQHlHLdFA1xdA9bTUubd8F0CD7kZ1H48QQDmRHYcTRBNAK+bJ6xdREkB6mP4AiOwVQNNhmcSMSRJAktHIUyVqE0BxetRXBjUQQFy0NdkELhdAEUG9HKO1EkDR9DQQbogQQHHnqFrQQBVAkeR7tqTLFUD3gNno6SIVQLenNfCA/RJA9NoxBUUJFUAyYMLMvQgWQLeBHc/8ixhA8YKyw6knFEAhMKozvbITQDUX3ocWpBZAGn+rD1sZE0Cy7uqylLwUQBb0TnqVdhVAOmoBaufiFEDT7oWUhPoWQHDZ0jCIEhRAM+L8Zim3E0BwRxR1oPsTQPaoXJVEuBJA0fXwVFXoEEAwUqsN6qMTQHHqqkLSZxJA0dlmyoJFEUB58Znp5PMVQDXpAkalAhNA2wWA0Z9mF0D5fEdCcVsTQNjM4kqyYRBAM7+8KmDVEkBm5KrpEPUWQLO544H1tRRA0jd7kTy0F0AydJ3FPxQTQHBrU2afyRRAU3LgFaMPFkCaxqhU88ITQLL61qipeBNAdd4qQOkSFkB6EPY65ZsTQCNTrGR/WRRAqAb5pb5NFEA1exac4q8SQNFcMwW1aBdA9sqqmRn8EUA3wEap1voXQLeqrwo9PBRANq08YYPYFECVtGbsoqAQQPVrpJaDghRA9sTWaddgFkA0sKn8iiMSQB/LY70UxBNAu3cQOmeeEkDBy4ajHv4SQLsoxQJVoRVAU2JxY4htFkCSDLtTlicXQPFNI52OEBdAsWAFLcYJEkAyGf1rF8sVQMDyi98kRBBAsbBrCUecEUBwzpxv92QUQHt7c2LjCRlAMyTPx963FUCykd1iHC4TQNb6GzB/FBRAMsQIbR28E0D/KYEDzt4VQFcYPlxwABRAc1l0hVIqFEC334cGSHsSQL51XUelFxVApgEbZ3VrEkD1+YckDrIVQLMPCJ3xLRNAOD8OR8uzFEA5yet+dhITQNJ0wk2yZBNA/EVm+nPkE0D8yoolJj4XQCIHO7UA8hNAZg6vuRuWEkA48mmATcoUQJVWQcJF3hRAekase6XHFUB5lcAwhHARQBMyD/738BZAWNlDKFesGEDxaQbZREERQBg/piCAdBFAvSceay3SFEDVYLkUQwMVQJKAR6DfLxdAcJp4m+uSFUA2QO5ga58VQDfzJ+xSNxVAvNBhEVYFF0Cw1KBX7S4XQGdb9M3O4hRAMwTTyVyOEkBWR9GaagQRQGCUmwdSNBRAPryvlpcOFUAyyp4SFUgTQGQXa7cQ+xVAI4vxkZWMEkByYoN3w5MUQHSxoPVRCBNAMTFGQctRGEDwRxVkZ3MWQJhIyZhEbRZAtDIJCQi0FkBx3fMmaTsVQDl9FXJUAhdAVtgJ9AToE0AVJWUsM3kVQLdBuavSiRVAeLjrh/7pEkBzDICH4ZYRQPGnLYXoNBNAZa787jdbFECzJEjitXESQDrUcRHWmxNAXkDlG5n0FUCwQHKbCFgTQHi6nawJbxVAvW/uyAviFED8CYRrkPQQQEkhGvpaTg5ANeio4TjuEkA6MzZZyqARQPgBHUPTZxZAI6LHZCcyFECXmGtbrr0VQPgep9rnNxZAdtpm9D26FEDSa7M9nWUWQL/+qv6JdRRAkbeJkruwFEAS0xqhrakYQOAzeAtG+hNAtbUEIo72FUAzlpItDU4aQPqRPhHjoRFAdDoF2gpyFkD1Fu1WjFcWQGYZS7WwxBdAMurz1lJ+G0C1R7yKwOMZQJIHLY80jxVAeqokNiPjEkD325ZG7EURQBo+oIvaZhVA/KOzXP4SEUAWf2xk0tETQDB6NljfuhNAdbodtz5yFUA4AQZ2Ck4UQBm2Fk+U6hZANzYOmOWJE0B5zPeTE8QXQHCJwclbThNA2hBp1fP5EUCRa5IZfs4VQHCYaSOIzRRAkigWxrJnFEDguUT27egXQCE4aZnaFRZA1ezQs3IJGkBSAp2ocQwTQHim8Ny/nBNAFFQqF+IyFkBZE/a7H3QTQBTvFppv7RVANQ3GwnhEFUBULAOzeI8XQHTpdLqcEhNAcMDcrcxVFkC1kdTlgXIRQLsvBM/abRZAJT467NKEFkD5j7+/pjAZQDHDHHRDHRVAwp+ZAAsxE0DxYSy/GmYVQDKe4b7F4RVAOtc2R6RmFEC+gOVtTfMYQHqSVrxm6RRAcLIa2pZkFEArx67KtqAXQPHPyXXApBFA7D1XxlwZFkC5PtT4z2USQNwXRm9+4hZAO5Qd3rTVE0B1KNhR0IYTQBWNOQDR0xFAGMwCcBNYFUD2TjwFgw0VQFy8PFyinBRAuOCOZnnDF0CyCT3kIFoYQJiJTdD0cxhAslPowPW+E0B8iqO8fcsVQOb5L2hDkRJA8R33r1C8FUDzAKpolKcQQDO/P1UUohNAco8WPMd4EUBxK/w3cVsYQP5DJRF9zhRAMpw6wk+UFEB6I3eVp8oVQLjlnUOhBhRA/cHI3WdJFEC2eafxIFIWQNL3vG2RaRNAfOxALb4/FUAU0Ee8YacWQPVykYQrsxJA9VCnsUlyEkAS0vpfDecUQFIwC2GPTBRAWEcy01bfFUA5nUQsxPQbQLw7J3UhnhZAUjPPgalHFEDSLPGW+osWQDf7N3bf3RVAFFACfMOUFUA1p8/a9D4UQHLvMoC1+RVAeuLg99LXEkBXwGYdIcgYQDfIGJw60BNAsVR7lEwCEUD9HMvMXwcWQPDkCzUruxVAZmkgiJQLE0A0pPlyhFoVQDKRP9izixdAdTStbM8LFUC3A+kKxA0XQNXkGz+NPBJAvbW6e+8jEkB0402j5HkXQLqtnw7uwhFAMn9BcH88HEDUSOiC9asWQDIPdVCQSRdAcgdzHrypE0C09c/AtxMUQLFcu+gvRxBApHnkvpMgFUAhfAu9WJYVQLMzSjetzBFA+y3g4Je9EkClCYffhtwYQDxbW89GpRJAMAaKe5P/GEB51lVH210TQHO6HSQUzhJAulOA5c7CFEBy5YQgv5AZQLqJpWZs1hRA+dj5JVzyFUBxoJLxfgEWQPJqwdv2dBFA9/cZ6W2sE0A1J7Ts7jMWQPTmQkWDfhdAFewycVARGkCRN0X/A4YVQFNxkgkK6RRAoaAas+rXEUD4jljubjISQGEKUNO3pBNA2XoZRQJPEUC4Uf7PJJsUQPeAIRZDEBVAMZ6cqlJXD0BSxkJ/BgkTQHDs0gBxjRdAUdp3jAcGF0Dxw+OgQkkTQPlaFQ2YehhAMjV65nNxE0Ah/ntn5wIVQPqjydB7xBNAl3iFBO/kE0A/vicO1AcVQHRvoZaJaRNA+WzwBIGEF0AR/9Z0VR4WQFGDarHXuxZAwEL/NU/WFEAZzNjxbAwXQPRYvHmM9RVAcZeVofjAFUBgAdWrDicRQEBLcyT2YRZAcH6nr/xKEkDwRxTiPA0WQPX30zaDYBNA/XranrJeEkB1oK54paASQFtbjk9rhRhAVgjZ5RJoE0CEpTMLDaYVQLD53lo2/xVACtRle5OTFUCZAQXxfZMWQGn6/6zAShVAOuo23qN5E0CyihweUJMTQFGig91yAxVAcleN41I1EUC7jT5Y5lwUQDWBsn5ihxBAEl2Jw9t+F0AhzhCvFEcWQCr68uX2+hNAsxLQXukvEkBVvyFPlhEUQPKPEppCqBBAeYL/ExlzGEC8/xIRRaQSQDqxQ9yHQxdAk/txiE9OFEDYoV7FWlQWQBKzh9SDiBVAM3LDZElIE0Bj8Oem49QUQDgMIm+sfxZAWDNw+gwwFEByv+0fPOgSQLAb+Dx14BRAODKDzcCDFEB1O6D2EYcaQGEBLVfN5RRAMwEtarOgE0DcK9X6kM8ZQNU0tCzRGBZAleo1uhQwFUC3fh8RdsQUQGHkkr1r/BVAsjkAFz5LFUB1KKFe6CAUQFM12rq5rBBAlb7IKdL5EUCltcRelmITQFbXCywagxJA6/bZsmidE0AjJtd5HlwTQFQrz7wCQhZA9CFcBBtzFkB8SX20WUYRQPGDR44ENxNAenn66P2wE0DxsicfPsgXQLijUNF4YxdAsE3d2fdMFUBTw04s+8EYQHnt/YtJxBRAc7YFjXBZEkCTXQV11n8WQJostKjOphdAYQ1mSWJ7GUBdkR/S2XUcQBRT4yKcpRpAsq+7oTKAEUDqLBzUlAURQGQsXL1KKxVAuGJ9bZd8E0DlgOK18e4TQBvLNfLKaxJAdco1kIT5E0DwtbluYyYPQLdriUODNhRAmd8OkjjsGEDhlnWTY7sQQLUz+Nf9PxNAMzE5nsMyFUC50QrpJvoVQH6Nl3EmzRJAmCMDuqAMFUBzf7DoEtMTQFEbKvtpwBBA/pOVeBvYE0D0J0Sp+mEUQFyXRsmKxRZAdgD+VCBgFkDYa97ggJAZQHS88J0IOxhAMDLMHaqbFEAwYLxrnRUTQHlnsiLaRBRA+1uvhouRF0D4Yo1v/4cUQBx/fjZRaRVAv/k+3ur8FEB3TfrIU6sUQHSvabbaQRNAtNQ9cMDUE0By45Tv1asXQHkF2UwHQxZAuHs2cgdiEkA2NjJXSHoUQBI014u2yhZAd/S9w0uLFUD0wjb4sp8WQDZXiTLW6BVANjHU65k1FkCVDfWjDD8VQLGuBxo9iRRA8AZNXVDnF0ARnVyxV8USQNmn0KwpMhZA89nSCvCREkA4SH0J9eIQQBtvkLJ+xBRAE3PEzTcqFEDhv4pSL+oVQCJcAac4YBNAO+/TYm28FEDdEwWvWocSQDFhNQXdlxJAeQbWzauKF0A3505QCEMTQKzyq9ts1RFA6Wsc03owFUBxc2Lc7HETQHawxoPhERZA8xmrT6nPFEBjF0xA8zwSQHmIE0OKZxNAsk+lFcVZEkB1DLRfIUUTQGH1Wyj3eBJAnWVzdvcwFkAS7AjGsIoRQP2eFZma2xRANcT7U920EkD1FlgdMP8RQLO5nv/51RZAc5UzumVuEkD+Y5WPddoVQPPB/Sr7XBVAcb8LRiq0EkAvYQPlhYISQHGSaNBQMhNA+m6ZmrAEFUCBy/Y4DnsVQFpG1pp8cxdAfj1JQpkwEEBPPjQx0EsSQKkJjX+hIhJAGwMOR96QE0ASkXz7wpgWQNN7oypUNBVA0aidPAjQFEDbsYU9ZZ4VQBJoLbbExhVAtsFqKSlWE0AUbHsExnMQQDDjMT330RNAc6XJJRU4E0BbpCRutccXQOAE3UdgkBJA04MkJwS3EkC4Q0wLGhEWQHRxe+AdQhpAWKDR+Fc6FUAxHC1kjOkTQLhJyvkUxRFAbuTLH1onG0CyzSlg1yIVQHMVzFm4kBJApSeE9/PvE0CkggutP7cQQPPM3e3Q6BFAvU8bwq2VFkBzKA9+j+QQQHUMIKwgjBNA8yttzic5FED4tgMdR74VQDrgJgt48RpAMwKOpHl8FkBxoLe38cwVQBRZ2VxF/hNAsO5le73+EkCyyTMX2fITQB4x1MrRHxZAMM1OtfWFE0A5cS+CZ0QYQNrEKG+2LRNAkwnvrbiRFEBUKg+/+0QVQDDQx8yK+xBAWl7MLAy8E0D1CI9gdxsSQLCmpUwwBxNAdZpCfzgDFkCwWDkv4boWQNRxZ5vcdxRAog9yOj5DFEB1lxP/kqMUQB198sEeBBdAl6qiUJWCFUByeb1ONKMVQHE8qMR4lRJA8DwPVgjzF0AyD0G6AAwTQDangfqXMhVAdBow5zXZFEAwc0B8RCASQL7e34gUihJA+YyXm1nDE0ArTOuON/AUQDnmbypd1RBAs3aKvjvJFEB7YC6uAY4UQObH8s6s2hVAMWyEXm8vFEBUz/60ydUXQLk3LMcFRRVA+pf2jNHwE0D08GNO+80VQPWQ0mCKnhNA/TqZeeaJGUDVFmN8hCQVQGFZnL3OxhVA2JLQHc1SF0ATdxmdCLYXQLAlM9QYMBJAWQUYXG0TE0AypGOXcfsRQLxYqFe98BJAFDG/4rrUFEDzUC7KxCESQDxE8Ir6hRRAERVw9pKwFUB0CrGSp6UWQLGHcDxwnxJAuSrkqF5/FkAyqfwbiHwXQCbfWV9G4BNA0oqYVsSZGEA/EbjEiqwUQLfbsKNEnxhAMojK3x6bFUCxLutefEATQLWbagnsxhRAbRkrp5PTD0AYOGQf0akWQBYmaFq40hNAs+x869JnFEBSQr4pqnQcQLHg+ccLDRZAY3E/nM2hG0Dzv3leUo4QQLYlDOOKRxdA9Ka+OR6uFECp12qhywYWQEDAMkrb3RFAMMVU8ISrFEA8q7Z+O+cUQPy3GcVIZBRA1KWwk/NeFkBSqh0L8F8QQJYXZNlQnRNAvOCs7nhRFUCy8F7rchUVQPeDnrOuJBNAYg85Hg+UFUCBJhQdzpcTQPj0GygymRdAmcVT2U5VF0DZbX0r8DkTQLK6YFLHDBRAMS7aZMa7EUC7anLcvM8WQBEKs0cnlRFA9H3d3mfZE0A34b/K5CkXQHr3S04BlBVA8kcaNfujEkBiWcsiA/0WQNJGUORinRRAcQxRrfVrEkAjDcFhqFgSQDl4HRGZOBdAVC7sy8T1HUBjz0c6xmATQLIix0DkeRhA8a6p/teDFUChcjI/YsAUQD0nVHQlqhVAdxLq6ZBREkB7wBQsZjESQFEJAixBWRdAcSXg9UcUFUBUjjanEp0TQGIJSoTCIhJAuchKoOmPE0DwFMmndQUUQCHsYl25oRRAc9+zKJEkFEDwZdNuyzUWQLJxHXmpGBNAsKiu114LFkAwOVdtvd8UQPdiOYCyGxNAMmeohK8wDUDwWc1GCEMTQNvOft/wnhVAc4nfgyhiEUC4DidAKW4WQHVU/fVYFxRA3IypUML1FUC1AmVp/QYWQJnhzdJaRRRAcTX8nP+eFECzNqQD+bATQH+HfhadtxNAY6X+xtDVFkDXYGiEbycVQH2Oib8aFBFA7ZQElg+EDED6OMDarlEXQD0lcou5thVAdilcF7KsGEC9IBuLIFkRQDfR6fLeVhNAumEm2HeMFUD2pKVIiCISQPCg6f4wJBdAMltbsW/DE0Bn9Rc7riwWQJuzivHwbBRAEnF2gHpsFUBUyHAMCcAVQFsw1xnlORVAMs9JIQGpEkBw3gT4pvUSQHnQAssS3RNA8bz77wAjFUA1q+4bJmUUQDHHBxpc4xRAGTS9gr5EEUByy5KeHCMVQHg9f4s0RxVAdg9FA7kLFEA7mgbap8cRQPpj9QEyvBhAPi9Xw3W8FUARYXi/kVMTQDVhgmpNRBRAc7qg4+L+EkCS52PjwCUVQCq3iyhWFhZAsZPWJuTXFEBwvlro8ukUQEEFHr9xiRRAUv8dBGFFFkB4ccAiC8oTQLP+Sgr5WBhAXMP39xI1FUDwCiZZAFEUQDCe1klb3hRAI2EAqrfDFEB3oteSKMQTQPHLfGWLYhhAcbJq+HE1FUB3Q0C1sPUTQFYWkKFPgBNA7XDx9EydF0C2Q223vZ4UQH3h99hrIxlAdky9eW1HEUAbfDrGJO8TQDksFzUi/xFA48gswW9qF0AZy9c2RCISQHohdB3kOBRA9/b6QNB1FUA69jDKXx0WQLaQNmt0IRJAudP/OngqE0A8A8f3bU0WQFH1ahpRGBRA+bXEphk0E0B4k3wCsAUWQHGczd9/3hJAdB1WFdEnEkC1dPl2dUIXQBmkZH0PlRVAuUAqVWYIGUBTAM6XaU4SQFG30mY1hBZA0s09HRrzEEAT9F7+XokXQHvDqGny/xVAmAnrMU/YFkCpbpe1BmUTQDO1W7ut2BFAf4jQzyO+EkC3HAEgf7ITQBLt4NKPxxlA9HXpGyvNFkD9JOdbEX4WQPAchkbZBxBAYUCHjUY3FEASGM1NNRYUQLjJYsgyUhVA9QoZr0mAE0DxhNslnZoTQOtXt/bfoxRAs5qJuLF9EkB0RzxjJ5QUQDtNrtQ6lhJA5MLuYqT8E0CxlkXUfgEXQPPvEtoxSxNANscQK8ZaFkAjkeqZi4kUQBJLNwEjrxVAE+u006wCFkBxFm1yzVEWQHdDHx8TwBZA+H7iJxbjFkD3EZrHt00PQPF0o6a4KBdAudPbFhq+FEB00vrGWxMXQDehrbLpXxdAFgWujOFcE0CRJdxDKj4XQHIOz7+2BhVA+QFH4hdXGUDUH3JOzU4ZQJH7PbnY8RRA8Xr63assGUD/KAfUUbEaQFiWcPUZvxNA0yZDSsNOFkA0iY+aBw0UQDHsGaeTbBdAMJyvuuDqGEC4Gasw09wUQLxYb9ezThZASmIacktnFUBVBamGEbYUQDg9oFGn6BJAsQlSRWFLEkASRrjFo/ASQBL4vfBq+BVAVHftg4pHE0B+42gay3QVQONwZb0J9xNAwB1Y7RrcFEAWzmCtRZISQBH9Va2bfxRAtLmYUK9gE0CW/rgx+foTQPAsQ2lvVhZAUyaQZhyeFkA55fZU1rcWQBLzy2GS5BVAusVz4gH8GED8MOhjvvIUQPq7XNZKZRhAccpPnbxKFUB0bR7/cMISQFMOHU4TghZA44aSMkUoGUA6/d5VqdoSQPYgEusaGBZAcSvPY0BlFEA0CyNAJ50UQNX5P2B0CBFA9FyoG6nTFEB9bZ2fOkEVQPObiLpvNRRAMJHOQuFJFUD5btEE7NUWQDzbLYzVlRNAs5V6lF+3FkBrsCaczSYZQHL68DDyhRNANPsyiSYrFkApivHq/esSQJSnAhRWaxVA86BKxO5eE0C1G5w1eKUTQDWfFKPrqBJAvKVPNEbNFkDydixN9DwTQDIGHReLbxFAWbUgkgnTFUC1Pv0S+I8XQPKnTBhtsxNAGORhuq3KEUCxR4jiRRoVQBwqt+TsfBVAtsgMg8MqFkDx+0x7orQTQPRWg60cUhJAkz1QW76zE0AkFptwEY0TQLHVLADRFxNAVCXQhRsGGECXzeNku5QWQHKVoy6UehRAeKs0UF11FEB+jco9AycTQDFOzJO/lRRAuh/xYTHeEkC2awb18MYOQCFmZj6UZhNAcjWVhtXJE0DzIZJtguITQKKFZ3xsMhRANTZ6BtwbGUBx8xS6E5oRQLIQ4CSiHxRAeMVucfTeE0CckO8AG3UVQGLIprfqVBJAN6l/1o6jE0CSq9IDj+0UQH4+vyWsABdAMhHBJarOE0AfRwDr8c4XQILrbN2GAhVAwYaA+0CgFEA8w60eRJgVQDuHaR0eKxJAOu1h9iywGECx5AEzEowTQLMHHpyfSRNA6ebLMBKLGECZkFdqLxcaQGF/ynqYOhJAuKJTYbmaFkB4uVpr2EcWQHVr1eZFyBFAsGcXn9biFEChF4kpN80SQLB2o02gFRNAMXZ3wUtyEUB7WEfZJv0UQLMoJz3c+BlAY6UULETFFkD7oBdrEdEWQHtXH/kpqhFAvAVvMPGaEkAU7NKtHJ4VQLojWVKT4xNAFjWPeZpcFkA1Al83PvESQHvUT0t+5BdAMNseJW2kGUA4oALyLxsSQLI3L33RMxJA/P5kVURNFED1B6ODJAYbQPdCXkXWLRNAVp7TqfbrFUDzEms6+LQSQEK3QW/aLRNA1DX0o3YIF0CAgx//PmoRQPNZkARaSBRA1JMi6EceF0B9WsMwzNATQBK0wJTA/RZAcNKle7nQFEAjvhNL90sUQPowv3F/ERtA9gKdupHeGED4giMs9AgTQHbKsVQC2RZAWLloTpLCFEASfjaaaU8TQEARINx24RJANPjlTjVbEEBk52ffMz4SQPOMgb5JehNANXXTpQgDFkCyHWkSdsgUQBpRk9PuUxJAuFwMgpk7EEBgU7UrJgcSQLiyTvTW+xJAFn6pnTmvEkDZWizxwbARQNf3KtaQWBVAdVdGHFUoGUBxI/Ip+JARQKIh2sp2sxVAOOPcXsK4F0Dw/NpD2DkSQLxqY638IhNAsstJGXnrEkCW3WrtWvYSQHXz0jS59A9AuUL238m8F0B3tebw+38RQDMUcbmFIhZA6d/iK3B3EUD6qRhvsnwWQNgLTCdqChRA9ZIcb1oCFECVx6671+oUQAG9A/g7YRNA2JkUCMmuFEA1sYUzm4wUQHdJ8PaaBxBAOsNzP/2PE0BR8P/Kk5wVQBi7veZg1BZAOdm8NC24EEDxyqFLLBMWQPDuy9ze9BVAcOi9EUAMEkA1SaLkrZsXQLSVHzPB+BFAu8Jt1qULFUC5jWPbuscUQOKq9NWzxBVANDTTnhqHFUDTAYxsgmsUQGiNRx7gBhZAWbrQFPHLFEC0y4FJGj4SQPO/3hjJ9BNAtUfDZS6jFUDeDwka6QAaQOJaM9HMtg1APteGh78YE0AwlIbD6HQVQLZx1lecFBRAOJbcELaDE0D4EpkpOXcQQHPvhufsXRNAD9DVa+4ZEkC1Wn8vLvQXQPnsX2wlaxlAEnilEGcYFED573aNyUYTQL3QbBvaxBRAcn36V5+iFUA1SwVwenIUQLUS74wYaRRA/czP8TS1EEDbspfOcYwUQBLkYb1U8xdAsUemzk+vFUDifJfVmZcWQDnbRNDlNhJAG9iz1MVQE0Bwf948n+sTQPYrhJ6zcBJA2OWoKMvUEkBJjI1YMcoTQNK6E4ZUJhRAsyHpn5isFkB0zf+Mh3MTQPy8cIUEBBRApO3SoMuhHkDpPnRSdS0WQDV1Fc+lNRVAcL5yWoisFEA5agGUlQMVQONCqCPkIA1ArYbENxr6E0AzUTqfr/UTQItebIxAlhZACsgnl6ilFUDwKlU7xhsYQHQZsYnP5hNAHLrXToTXFkAzih8YAGQTQLiWLZ9C2A5ANZG1DGNVE0AZ5u2Jij8SQOY6olwLUhdAHeKNxA2WFUAmP3MKFIEVQKTRSiNhYhJA4O+6Eh7QFUCoWbaPG6kTQPsXDIKzqRNAeCCLVsTzEkCWhDdfjuITQLHeHoQYURJA0o/YMqXLFkC7oHAZRYITQDDxPZsjJRJAcnODAdM5FUDRjJLarL8TQJF/6MwfkhJAmclIU1h0EkB6DTtIrTMVQPf3evnWSRFA86MX3w4MEUD1owNGxZAWQNQbiilGTBRAsCccxLtsE0A6L0wa4UYUQJIXet4RMxFAuUpAnaH2E0C9u+5pyCkVQF0EbNniHxZAEkE29VbiFUBThpMJ218ZQFHgA6uj3hNAIq8SNbpOFUD52fGirL4VQPELjn4cFBZA0Vck1fVwFEA677QUrLMVQGPYSGt9lhNAM9mNANNSEkDz2YLzZIQTQDsC4So0ORJAMMO7fEMeFEBhJ7MhVuAYQHBlWdjOKBZAAXmCiQqGFkDww5dlXlwWQL8MkAHvdBBAfGaOaUoKE0Bp/V1Yu3gUQDIfikm1AxJAo6/xjwqFE0D9xlCyICQVQPCCr5011BBAPRCAzE7UEkB5RjwKo04XQJFx4cs4GxNAOq7KlFv8FEA7b4fgyE0SQNGomwP+dRlAUd0XwLTxEkDXjOJVJekSQDZNbEHcSBVAiopJ97A4FUDabrY6cWcSQCOmUjWfLRFAtJ7Y4Hr4FEBiNswnGWcVQDFTYyDJ5hRAKmLW0erJFEByw5MCDp4UQAHI67PR1RBA8yfq3yspFUDlfVgY2pUWQHnHPRkD9BRAvcSrB0IsFECVv5nQLeIVQOinIyGswhZAs0plYZXIFUBx8OxC90oUQCIciE1SqRJA+h/70AmHEUD7jVkgh7sTQLkB4eNSvBVAFeAGikhgFEC4/idUa2cXQNHxIP3kdxZAsZxQLkSNF0Ci7j7b2PAWQLQI/E6M8BNAOJpKElTJE0A8a3zmZF4VQBtHYyFN+RJAc6XhwHLHEkBkBtccLQYYQHsq/ZoTiBVANGvEUTZcF0CjChTh7ZQQQLT5YAmBexRAVQRC47sSFUC5PWTR080UQDTE6NVnYRRAYBjb+cFlEkCYnkLRor8TQDCyg6ZNvBhAskMZ22CZFED4CwnfPD0XQHHFrFiTNhVAGFR/NkTgFkAhGZZwGbUSQNPV0ppmfhlAPQdlap0hEUASU4ixaZgYQJkVqB1clxZA0c80+HaaFUC83PXyx54TQCsTPpN8fxBAPE66+GQPFUA50sA6ewsUQJ22HjlPjRRAGXpj0WJhFUA3Vqs5IBcSQFUPSyReJBJAW0X6qjejFEBxTm5rvWEXQHD1rFS25BlA863lorUbFEAZ89zYyjcYQNF2mFKmDRhAeFyZAmoLGEDzICvnSpkUQKX55rXhCBNAVjgX45XYF0AtNQhNIJARQNgMt6Oj4hRAvE6Bx+ehEkBwSDES8mEUQJmrzokDcRNAdisGV4mHE0B8a7XGd+MTQBUq2Z08NhVA8Rq9fM4bGUATIZmGDwwcQPzbXy7lZBNAYHzMoypbFUBxncgeAK4VQDG2mrx/eBRAMZHoEBYMEUDdfHDPZOkQQHNiBGAzgxhAtPqSwzh7EUB2029WFCsYQKUMApx08xVA4aInzQVEFEAwxHHp52MbQLLGrLNS4BRAJHY8fdj+FUADhx4NUOMVQGHRUxjvvg5Av5FD/S9YFEATJvLG1xUaQProq7wNTxRAm7DHqiuhE0ACy1IzoYEXQKELHGBkghZAcpmk91gJEkAw9GkmHG8XQL5JFdwEOBhA0oH1RA//FEAxnqqIosUSQHG7K8jOZBVAd+x9J+fBF0A4w/aM6xEXQBtd4NftABBANlqw7hdSGUAkOVotMr8SQHon+pLF9hJAuTHdtGvJEkBwcsij7SwXQDL01W/O9RRAcUwWkDg5FUAWLjPJ7vAWQCOHZWYpjBJAOft6amdjFkAhncEF0QgWQLlmq1tEFxBAwbcMy4AxFkADyrLMy80SQHCADiOjZRRAaNIaDZ4aE0C4lvQmJv8TQJMDL8Pf8xdAMJ33Q0xvFUBwAut99R4SQLQ94SCWIRRA+ADSV15MEUB04LXGa2AWQJm0o1ElCBNAkYkG14SwF0Bjj3LYCt0WQABw829DehtA8iO80ScyFkAkanoYDHwSQLRfgoLnrRNAIlOi/q94FUDJQR9cWooaQMY6T34YShlAMWQWud4ZE0D+l+CrhuUTQHpHL4LlORZA9DxwRJi+FUCV+M0w4ksSQHdCVSAJ3hRAtFyODFh/FkD4FL38lhgYQDjBLNMZ1BVAMKviN7MuGUC0LGFvlK0TQLNpbcDpixJA1b2oLHrzE0B41g/1t+YRQLM/6LRbFBRAfUjSOYsTE0C66q1EwVISQLIu3puorxVAITe72aXIF0B710k9trERQIG86wY3dRBApWQJlg67E0CRvLLYIfQSQBXgkBY37RVAEmJzx2t/FkABpigLZvYXQKIbqvFvVBRAdtr8OsD7E0CA8bjYrTwVQCrEmwwyIhFAqjfVLAw4FUAv4ZmHZtoXQEEpfCRsmxJAQuWXQKD0EEB2ONDsMTQUQFUmeHQVVxNAd2P3XzkzFECAB7tiiK4QQDkz/MPxDRdAm8+hAtsGF0DRUIb8jzAVQIvT4unOkhJA2ZL0d65XF0A1j8Plv0IWQBUb9U2luBdAMURdgsAfFEB3mbA06d4UQHxdBiiozRVAmlhZEbCAFEAyHWCIiUoUQPnYDLselhNAmdlBmMxyE0DzManNirETQFgsKdr3BBRAHmYZEZU3F0ApoICXli0WQJhgffySxhJAsFWL0CHDF0Ahzn1FRWoTQNyldNn+YxNA2sNM2LNyFEDRZrAT5xwVQLa5sCrP1xVA9dHmRCalFUCRk0WcVwQSQHde0/QCVhZA2w1po9UcFkBRFyx/AncVQKoSJFbB1RdA8LtYIvo9EkD4zHiQU6EVQFizObWidxpA8242B7/hFkAisAmKQqkUQJgb2/lkxRVAUkIT9MivFEDz08pRKtoSQOPGhas6qhZAchB2P8/5GUDyzk2eUnETQNqyJZZPTRRAOS7vQggUFUB2U4Hq1tsTQFn4kzgmQhNA2/EhtfowFUC1J2vLdXcUQLYTDrJx2hRAftIJ5llgFkA5sC+bn0wVQPk6cCdR7RNAtrt0XQ+3FUC0k4iy37kVQBHkfC5REhhAeuG/zAQpGkBTcqGSO8cSQHisMQNnLBNAuTBxDFtJFEB2LvDiJ3wXQDHM5yQf/xRA8QmJgLlYE0DS+1KI3ZIVQGbxwUQHpxRAEXiYqECqE0B4ex8twooYQNJ7VlXt7hJAWoUXDfIpFEAys91EMAkWQPxA7YWe9hJA9zvhPkKXFkCTswV8B9IVQLSdpHK1GxVAclzYNOixGEBWGhMZBVIUQCGw0zLwlxFA5nKux4ajFUCx87EAnt4TQLrHaZReVBdAtjpQgJR1FED0Q+y9W/QYQPVmhV/uHRRA8ua6Oz4fEkB4tETidWYSQNN+QPTirBNAuqrjgmFDFEDYEbJrC0oTQDNZHBVmrRBAODmu9vkIF0BRI7JlwAUXQHZys4KRIRRAveI66eVtE0Azj7E4OkgTQHT2Qo0gcRZAG7LXV5o7EEC19mwoGRsZQMPvFdf3hxFAItVg1ridFUD5rcT04fYSQPIU6+9zqRpAcjvCHzs1EkA51rjWWj0XQLMoPk/WnhNAuggqyREQE0CyzSvjPxwVQFQj6VT+XRRA1AXxX+htEUBaVsrBxAUZQMNtj/CZTxhA4EHTHns/EUB4CdbbopQXQFFpFb9lGhRA41AUwcS0FkD4luF7ZJIZQHPHAD0ZIhdAESxOrC0uFEAX1Sye3kATQLU9meOV4RZAs9YLLRxNF0B3mMeYtk8YQDufxWIokxNA0Xr0Wp1/EkBYqeK10GYVQDkO8Dw6RhZAoUGvT3f9EUBwoTXRPSoWQJLa0m8cxRdANdxnijrJFkA7D9TReVEZQBuJF9og1hRAcRcufHTxEECW9PzsVmMYQNRIbnx2whNAtWUO4wfPEkAxK8guE/AQQNl/0ZatiBNAERdyBUDsE0DD4FAOvg0VQKZTxLP9zxRAUYtHW6duGUCx5MqOsh8TQHpWn8LOWBFAjCkUvDIOGEA0YTW9OR0UQHNlh51PDxVAMXs3zipNEkCwuGhmYEcUQDHcYEV0tRVAAN4XNACjEkClUsivoTASQDA0ESqmeBRAqCoCQTRzFEAcMSU/lOkSQPLSGT8MuRFA0s5PoxM5EUA5R7KolnMSQLM+lwDtYxFAf9ZRisu9EECxET0oxxQWQLujtOXOTBJAlF2Dd+M6FUBV3jxxBVwUQJErLFsLSxpA9cPLE0BsFUC1uK9M9h0WQNHis5J1NhRA3Oze1yYRFkCxdraA5qsVQHPd0UEm4hZAYu6He5vrEkBW8S5GMEwSQHocVsxTsBJAR/SGEc7IFUCwdQ3a8k0XQLBE0KYJIBNA/ILIKVeuFEClcmjVVJ0SQPoUyhnzqBRAO3O8rQwOFEBwOIt9MJ8XQPM1JLw5SRRA1TFeLrlgEUDgnu2G2ZQUQHcKT70r/xFA0d88BfSVFED3WF++wpoTQNGCiNP3EhVAYpvfn3cNFUBTcdfo/0cUQJPugYe1ShhAG9MUI0v+E0BzBrVuvhQTQODzAYx9uBBAcMj8QZiJEkCkQ8eZGz0RQBh2dDek/hRA93HsnR96EUCSYQfV4O8XQJPPqITCAxFAuQsCl6F5E0AzhOoKPn4WQLid/wJcNhNAekODdd8WGEA1z6BMjPUTQFP9s2za4BFAG2ZwjUTmEUD8Suwr6gEWQHEWPibh0xNAfWiOETBPE0CAhHM/3SgRQJXAsDH2jBZAk5/xvwp8FkB9h2ErJoASQDQ7e/FHTRNAMa1Y7oJuEUAde8eehloVQDXD1ZTVbBhAP6fPh9mJEkD5YqqW4ocTQHI0rkrwzRNAsJ0BcgcEEkD9WmXPcKAXQPX9vQXkfhVA+jXjUacBGECWNMoscP8WQHG2NX3arBRAvF6OXvU8FkCxlH2FP6wWQCph4nW17xFAOOrDQTUAFEC72RRIljUWQOZKTI4f4hhA9NCma99mEECy+To82VQUQGAgAKnDIxRAsx6kwBQKFUA2nLmT7xAWQBOtYb1xcRJAokCMXDtUE0AzoqQYAloXQHG6SPUcSxlAtO+ULGQcFEAynzeXIksYQJFJ2ycpgRJANHGzZUHUFkBxgz94ZmgUQDiUErtoEhRA8hA69lLxEkD3Xt6wZcYVQFSog2oc8BFArL5psbYzFEC6M+DW9oYYQHpLuOpGkBRAMazayeRCE0C1kG1wx1USQNtMrz/eKhZAcCx7ru3kF0A6XgsPX/0TQBaTDgV1QhNA9wN9g5BiE0D4jVn7wqEWQDDpTZ5qfRVA0fMOlngGGEA6ePVEFA8TQDxBBYATzhZAer8ENTNTFECVelCs9igWQJEtt/S1JxFAmIGYmgfgE0CdSzQrCTQUQGixt+2l1hNAIhMmn75AEkCTZnyQ7+cUQLcVpYbzyxNAUodQsYJ4FUB+mXy7oXQWQLIA1B91oBZAESkItD0YEkBx4E/RHyAWQDg47ltiGxVA9CPDHwrVFEBg4w3VWkoSQPCvlKBIFBRAmwICTmEIFkCwYvXedrQUQDE5XRRufRNA8KGtW/QgE0BxPLw2BJoVQOBaiNPFmBRAonkQpJm3EUDRiAav6U4aQFG5gr7VgxRAM3CP1j6oE0BSHWnWkj4UQF5KYGBPERRA+ZXhWfLnFEARvHhI54oTQCN6WuffuxNANgYEfFDFFUC7sTLYtmgSQGRTj5+3HBdAHByAHPEjFEC106ZgPJISQPIb3Sw40BJAVczXtiaLFUDw+zsEE8kRQOAu+P5EWBNA4/CjX+jwEUATK4DqFmASQLwJuk0DvRRAPOS1mfGwGkDxx7aJB0AXQHoQIHuQzBFA2Bk6lqXhG0Cys0mfKvwVQOIW4Nx3ABRAdYRxrLj8F0A4ds9oTQIYQPOdhMLBIxlAOAAAm0LYE0BzM7FSZkgSQPPMXJo9JRNA+advRm5lFUBC47lxz54VQLKjrGXAQRRA8/dRTtd8EUCV+BtIfIkVQHaMz1912xFAsoq+HmVGFEAsVpvso6cUQBSqiyckHxZAMovOkiiQE0C4a13JozsYQHFG7Jf1xhRA/KMi8yKPF0CSZL0to8IVQLH026f4oBRAvlEjC8sPFEDR1Pc9Na4UQHUuvZG6EhRAUmi3XNtyFEDRa575sIkUQDUUSNHluxBANXQ7WSx4FUAbRpcPXB0VQHiAkfYFEBhAsOvA/f7pF0A0ZJEoKBIQQDEgof7lLRVA6sFVhYPKFkCY5+Z0EzgTQHr8JHqtRxZAcP464YPaF0C4HNzZ4VwVQMlzZDS5uBRAJwnVQc5cEEAUp8tOA9MVQKuZUOjsrRRA2LMWYSwrE0C/iuQsrYMaQHCZSLLXLhdA0abhh+8WEEAYK5fBGUMWQNvsoBJsJRFAYlGsFH7AE0B4QbI0XVQVQKljdJ6ZABRAcaZIURw9E0ASqWzyUJ8TQJjJ7dwjfRBANQznq9Q9EEBeKfl4KeMTQBE56uGiJhJA87TPeDXUFEBUz+C2LmMWQOXpxpXrTRJAM3qcOeoGFEC6+TORmogSQD/jRAi3hxVAu1T2W3UUFUDzvfN5emIVQPk68A4g0RRAEfmyGHJ1F0AygFlZcsEWQNLKI7ar/BVAUy5pnt3nE0C5TEbEd3AVQH3kpi2A4hNAUglYV7JDFkDyzG85ppETQLzc9JpQwhJAMb/b1I0dFkDB5/tEHLEQQDPO6MqJxxFAflBOcTPQF0AnrmwVyfwVQOCT0ETUURFAMbcAWo7vE0A6RPrqUr4TQODqXgislxRAYyYJ+LKAEUC419e1kAYVQDiB+s+hsxVA8NwK5ksIFUCSR3vclCYVQDis8fZjPhRAeFIigMjZE0DgjtNgbLUVQLKvR9WbYhRAcePkKJi2EkAS1caz1fwUQBPM3ajtQBBAVfihVUAgGEBRDPhbn2oXQJHAh1kytRJAvNqkWQMpGkA1KGNXb7YXQPJSz4hTkBpAYIQfyAp4F0B2ITIRItsVQDgqRTQajxFAN7X3WO3IGEDx5TnpLoAUQLJgvl8J6RFAU9gG87ztG0DRz2zJ7JgSQDCi0NF+fRNAMnevCZMMFUCyPCj/UKAUQAEJUzgUoxRA+u3QmfslF0DxkxcfQ+oRQCGt4VrXqhVAMvSzCdhoEUB/tZ1YrFkVQH662nlhkhRAM/UuaEjKFkAXi6aEYf8WQJkLwKCXHRdA5g3hLFgmEkAw7fmeNt0RQHIMH4GPMxZAN+uZ5IUnHED/iFWRDOgXQHlBzafHChJAcQmKXORUFEAxUhS7rqMVQD2m8iE4pRdAtSqAHcXUE0C7oPV8GiMVQPk2JkVxQBdAsj9wcQ21EEBZksDw/WIRQLrPvPP2IxNAqKdZRkXXF0A4iEHhlYwSQJJ9xRWrvRJAEXKkyj8EFUCwmuYyeV4cQDtb2ZTAHRNAA2zUljLOEEBYrKxGepcUQCy1FwbFSBVAcecw7hqyF0AcgYKkaMkXQLYItRNfbRBAtHqAhinCFkCcNJedrxYXQPO3ErnWPBNA8q8LRuWSDUD+NQlWxIwYQGIkML6EsRpAk8ca7VvZF0Cz1AQNz5AUQOISznep0BZAKcEG7V//EECxppomFZYVQIQCzh0wOBZAdYflf/d5EkBscbQV5PAVQLTsbff0mRNA2O3hX+8iFUAT0mdGDqcUQL9GzP8TghBAV0AD5JHxFUASa3is2RYZQBiCGWfhohRAMltrK9mvEUBYZwK0RR8XQBg7PA7JzRRAHyOYxgZWGED1DLxI6XAYQLAOqxXBphZAsoDt11vpEkCxK5MtN4gQQOx1axMt4xFAsaDJ6YomF0A2lgEjQo8TQHXQ78mV2xRAtr8ZYuhRFEB5YLGBrvsTQPEv2JXJHBJAEb7i6uTZEkCpG2/VCdMXQNL8xawg7BJANfAnUasoFUC1TJgGCocWQKRwsUgzJhNAFzdN5vQSFEAaJ9cLhjoWQPIFUShbBRZAomJZYU8mEUAWDA31mFESQOnF34VVnBNAHk4WK7sWGUC4BSeNK5EWQHK2PPCzoRFAOBBCW0oSE0AyOeTW0yYTQPFZVleI5RVANfacJqVzFUB/NrV1khsSQLri1y3QfBZABbjeYoxuDkD0ftm4+s0WQPEUkdTLBxZACqDlgQklFUD3rNOAoioSQGLgulOM9BBAnl7gXxE5FUBxrcAHgD8UQKZOu5L8+RJA1UqRid8gFkBwpuA6zPkRQHNoRL5fKRNAcyl/va+VEUBjIYig/H8XQPQJ3O+vrBNAG4pVOra6E0D1k7uZCrEWQCFwOcjhhRhANTMmuiyOFkDtdvThWS4TQLhrHVxL1RNAY9n5wMhZFUCTihwjMpYTQFVzvKv3CxZAWFOP+iPfF0Az7QjHsRwTQPKdBoxaqhJA9nnOYis4FEA6Gn++rYkRQFQd463BhxZA0cwFCS+8FEC7toSXgu0SQLwZ7HyLHxVA5MPc87zRE0CyO5jjMdUTQPrADtlZjBpAHDTnLnVpFEA7CN4Ie0MVQBlWa2HkBhNAGKcvGgl7E0DaXDz9iT4WQPLZKv9DihNAmkfK6kRuE0A9P5uh6Z0UQLB4P+CYtRRAUKg63UedFUCwpXXcdI4XQHMlLAvhcBZA97wWcvlNFEDVBSoh7HYRQLjNi1/uQhRA6StAJg8DE0ByDMoe/dkXQHJhfXbMJhRAouKosaSdFUDBpcKTFFkVQCSx0rR+FBVAOMMus+ioFEAJR8G9qDcRQHjmG/I3URNAofJFRHbpE0AxeWVevkwWQDMaxGPN1RRAdeK3LbG+F0CR2WG2foMXQCT0YTSTARZA1ya6Ds5FE0CWewpcVdsRQKnu4J8+uhdAM21Cvav3FEDapb/FQs0UQPqtNeSCThJA+jOy3XlZFUDwxkReY9oTQHDxplNGJxRAV7uPFlLJE0BS4nbGqTwUQDAhH8djnBdAcYS3uSSaFUDhlU6dDSoVQLwnANsRtRRAetQnpzOJFkDYoS3HicwUQKIukAtaeBhAfh1Tvcj0EUAw317y6wAWQA1nbcn2tBRAMYZ/4TsnFEAw1AdBUX8VQHNWK1iCdRNA8wRICUIDGEBD/72ZPJIVQH/Nm3fduQ9A+KcDPfV5D0D/BqFavGMRQDhAtwUavRJAoeEFBTypFEC7jnv7PxkTQPmRW+FCcxNA+NxsKYNHF0Az3GD/PxwYQPCJHgq+GhBA8+IahxCMEEDYyobnPsMWQLlyDNLDHRVAOEus3wVUEkD6937OVa8TQDT1qtJiXBZAOIphpusdE0Bx6HhTMgMXQLS3XYwbaBJA++Mn66mnEkBlcLVAcOcTQPpvK+eYThJAswvClARzEkDyfIx1OpMTQDDxox0Y+hRAJHDStOW1EEBxMYLLVooVQHVl5yt36RNAFcTxZOEPFUBL9gYqqNcSQOBVnN5lDhhAs7rYtHerFUCyxRTQgXoYQHnUEM+X7hNAvbKh9r+1EUA0PEwAJUsVQJJMnzs+OxhAsUh59IoSFEDSu3+YxlAaQDAQHhhGQRFAFKdIp0fwE0DhwvHHEywYQHpPJAiQYxlAMvDpzocgFUD4D2shMzwXQOfSEOyW9xVA8QR844YWFEAzOMmhnYMTQHnlB5AODxVAeu4XV/ZNEkA07SIJSQAUQHI86+anUBJAcf1dbO9qEkBDKUa8gvQTQDXVEe7DWBNA0sRZ8jo6E0CZiZ3jpY0UQBlaMVcNQRVAVMu3Z7O3FED4obIWEdoUQNgk0cXJPxVAsaxNtjwMGEB00dsZ2qASQFX6OHaIFRZAVOkvzevaFED8/zNGLoUTQJgDNk28mBJA9N+ksT98FkC5GEyvSS4TQHkXORP1kBFA5TF5WwSaF0DzYml4AzUZQDx1k1q2jhRA0Wgap8PmEkB0Y1EPNYQTQOE5CaeGYRBA7B0VhwXIE0BwPiTp68cUQD+eObZnsRRAHHd3l6d2FEC1JtHEsF8VQLp9WQQsxRJAxfU09eQWFEBymG+r9R8XQNhQkuY3kBhAolQia4FTFkBw4w/Wp0USQDvOd0gXMxZAZGPCbKE9FUAR3UBomPgRQOmgkJx7ohlAYDsoFRnSEkB9enFIeQATQPx7KUrH1BJAsoRiWYbeFUBzTpXyW+sTQOALlTaZARVAErsJXD1NFkBzhTFZbv8WQLimP7ihuRRAUigvpX2wE0B38/00nvcRQDp2Pxz9kBNA9nQCiz9nFUC7TJ6o26gTQHubUMCq+hFAcyZ74bTrFkD5sLGzb40UQLT/FDfCVxVA41CRTIekEkCfc93aujgTQJKHCjZy3hZAs/UDozcXFkAyTTISBHEVQJEpENGwXBNAmYnyQdmsEkAgzuVc4j0SQBXxs54SjBJA94R3fxepFkC4pdmb1B8SQLyjtGrU3BJA1PNGjdugE0BnX1mOAjoPQMeAdHHN4xZA8LXgiqeoFEDTviKQhpMVQPJ28vFi4BJAa0qrzwCTF0A1Puh2AvYTQPqkg1Qa5xNAtFSoO4w0F0DwJfoorscVQLWAzpY4XRNAoukz05C7EkD41wKJpXUWQDrVlTRd7xZA+TQ0NyfHGkC5x9gFpaUVQLnx/JzL7xZAYFST7wL3F0BZqtwR31kUQDtm6G/cthFA0t2xbCdMFEDqECYjMD8VQDsjc/rm9xRANqQDzcDLEEBUOFVpR7IWQJjj2vNt7RZAuXdG0o+zE0Bz6f1YtDsUQPUtM4JBHxJAVWIQi1DvF0CiG3oNdesRQBranlMScxZAcWQb+CPWF0Dd4P83tkwTQFYoeYF/bhNA9oUEEgmJE0AyrVdBv9IVQPLFYgUEERNA0Ws+Vq+hE0BSSrpRmtIXQPjZFeHNDhRAs9hFkvR2FEAiArLRwSEWQHb0IdEL5hBA1KHJxqueEkCy4ZB1d2oSQJltSx2lYxZAc0MGofw4EUCSi+7L+I8UQPUxOtLQyBNA9rN2Ar3aFED0sSl8IHMSQKKHubZPPxVAdpeh1c9qE0Cp0Mcm/mYRQDJOrJl/KxtA1ljmY4gTFEBzCvOYH1kUQLwR5nAjuhRA6Ds9aC5lE0Cz50FkoxYUQLxqsUScbBNA5n7zfvchFkBx4yN16Z4TQHw4Olwv+xNAGlpywjJGFUB0UVdkWTgWQLwbGhcj6BNA4L83tY1lFUC3wt9FOQ8WQKrsUrEU5hFAezLI2/R/FUA7GwjlSJMVQLRnEh/G7hBAOCUJa8KyGEBxQmG3pF4RQNKuxa26SBhAYWbdDdWsEEDxulNgCooRQOOZu6zyyBBAQ5K02WSvGUDVeMCXIeYTQCF+eRqHqRhAse/8mwn0F0CYvivzCJMTQFur2T2E5xlAObGW9rKLEkC5SB4P/b4SQH08DZuK5xFANiHbEU9+FEDBP3pyZk4SQFmrq8foExNAcM9dXNqdFUDUfarBVTsVQDRz1yGacRNA+wPi4/d8F0AwM7GKqxgVQHsBM+iJWBNAeK5ucW9CEkC21iFNXagRQBT2SnnlxBlANd7oV0/lEkD4eB1YBvYVQOR3VOPl1hJAf+u0nreIGUCYFBEy/lQUQHJ1i9tD+BZAeYbdx19DFkB4ATrUFfIUQPQz6bEDIhZAcMjmxl4hEUAUBJ+7L7kRQP1/qanOjBZAMG6oCbyHFUB73sGpVqAXQDAipNABnxdA9e3SK657F0ATa+vNJJkVQHMrP4Ce/xNAs+Y2zNtLE0B8Y1f0DgYXQKW54eG41BNAZgX8WbJkEkBpaE3FlVURQBljwiveuRZAdK98nEnPE0CnQNmSD88SQDoM+JnnwhRAKd1VTZEOFEC4nqQdyaIUQOIPzGT9PRVAOKoFbN7lE0A0MczJ1SsUQPnbn1wiqBNAu7I/aqUvE0BzHRG/9dYSQLn955ncOBdAk8quwhX3F0AAJPjogUEVQLrxbzqW6BhAcGlEkgg0EkC0uUXjo7wUQDs/4HEgiRlA2ciLb8NZFEAEwSxc8LcSQDZy6+Y/HBVAM1DNjwB8FEAWBhRfD4EXQLAsv89KexJAFHEmceQEF0Dziamwe5QSQFgpTPvuVBFA2BfK+VerFECYngOyrksSQNg6adbrjxVAcbLpfiPhEUDgdNdw+wwSQJKsANsFnhhA+hJSxF+aEkAYyCgGp88VQNJRYLKgXhNA3pUbw7buFUD5a5Bn6kYWQHgIkkMbaRNANSRVrFcRFUAm+9gFA78WQFgVh6Og7hRAYbwe2iltFUB6QqpX3jsVQHX7jL3q/hRAuLX/pEL8E0DzI7uQvUwTQDxmME4OkBJA5qnhjbjpFkA2nFC1nSASQDWhMPl4xxdAQQOmkqMGFECxCNhgNX8TQPDHxx7xGxNA8SMsA5wGE0B7V+D+Y1kTQJ2jGPcc+xVA08JqkaikEkC8+V9NANYXQBmMxMwm2hVAePLfBBEEFUBwApNzGH0UQFKJmodIDxVAEXMFQshZFUDx0W9dvYUWQHZ6g5CPIhFAsLhEkMAGE0A2eotWySoTQHJmhLIOPhZAMrH4KAw4FkC/Nb3jzTQVQBl+niC2GRJAAJKG4yo4FkC65pNtUFoWQLyynhnPzBJAs/0fvwvmFEC2Yar2vZUYQPIq7WKUThNA8XXzXFOmE0CjbnE6Y18UQPLrQGBkDhNAOSCK9DZ3F0Ci126cjFQVQCnH8JyiKRJAWFFMrObIEkD4ymp/3lQfQDgTOvaldhVAPCYO/od2FEDx0OlaObUXQPlZEj14gBRA8ogbqV4LE0BZi7M/xPwSQDgwIaMcphZA5IYwzSjLFkDAGNSFxRoSQBQuo3dTWhNA857aPnv6E0C1iok3xkkYQKGyWEhvuRJAdPE0lHMEFUC0616iPBwTQPouJkTL4xJAYzdtnZ6jFkD2hb9eA3IQQHOvNniMQxRAg4lkJuzZE0Bb385H28gTQFHfmIvanRJAegeCWKfeFUD0RbWXUSwbQGCIDgab1RVAM0/wsgQaE0ASaDroEpsVQFFqbG0uVRVAN4KD++xCFkDjnX4pW98SQH1WmkVFABZAXXMK8uOJEkDBELLtDzoXQLXseybZqRJAlhP8ATXoFkDyYvX6uNgUQD4tNrQ7QBNAulmP35dCFkCy4N/bxkwTQLj0mEZ0xxBAsXplmWyqFUAhKymIXAgYQNsrGcGJNRhAk7c3WnXgEkAwkcR556oVQFX4TmcJ6xVAMcM7e1hEEkBxXi2yN+YUQLVl4bbwXxFAWPyNcJxwEEDynkkyTFoUQGKidZlrsRNANfcXGV+tG0BxkcSSYu4VQLARQzNVVRdAVIr/xyOQGEDzqvVwCUUXQLMJRgxuuhNAcTXYnWH9E0D6f+pI5mYVQPR2HN2moA5AtbpL6XqeE0CyzBp1tFsRQDIMc3DFhhZAd8qyKL5TFUCzZSAo29IUQPUBd4U2FRJA/sZ9Ck+VFUD0SATdsH0TQLE0AD7VWxVA+qEdqewvE0DxxKeWSoETQLQ741O1rBZAcmjthkm4FEA3U86CS1sTQPysS2v4NhRAebq0AMKHFUB2wnckLhcXQFe5bFqKqhFAesxd18JPGUBzwUGIajYVQHqVeahAyxRA/DXfaW2xE0D27e/1764VQGGq3/6z+hVAMb9C+uGVGED7SZZeLKsTQLmLRnL2YBZAtTpgw/zPE0D4kfcYqycVQHIFpwUc6BRAcvGdKRpBEkC0yDKtkdASQHdML9y0zhRA5UzWNfpbE0Dx+T/C6zEYQNWx4RxOMxVA9Yd414cPFkAA3GlzxzQVQLAnE1ntlxNAsXGSUV4jFkD5kMl6aXsWQLuCwmgk9BVAOgS6CF5ME0CxsO4r/vgYQLiUN1OeFxNAN5Qr4/r6EUAyOhN8vm0QQBHlO9ff0RRAvHajZ3o2E0Dw3dMnPaETQDNx08+uJhRAVQFGMOJXFUDwg/U+6iYVQLMzRhsBVhRAploK0YNJFUC0Axl4qMEVQLK+6u6hURZAPQ87kb/YE0C2YMMXeYoTQFoeBcRxYRNAEwtrgztZF0CZ79MTKtQSQLECLL+G6RFA04M/z6PLEkByZC/kYQUSQDN+TmGdExJA1L0ABeB6FkAydnWCfWcaQDRz349PxBRA+u77uKFcGECyUIL++9sRQHFHAri3UBNAmFQOfWS0FEBXoyPHSn0YQPOZ/4pW6BJAfgX8xrqBFEAiY/dS3fIWQGkJoKhiaxRAsz5kFo78FEB5vfpDAfIWQLOQ/r/IyhRA4in52DlAFUC4dT5wyXQUQDEAyOL8KBJA0raMuBgdGkAjdBRZO30UQPSsqPNyXBVA8skNspMAFEA5uoEryD0aQLDMHWNRCRVAMqrSybHKFkDYMiS/4VwUQFjfCbT1jhZAMaNSd1O2EUB0tvDo2iIYQLoJT/nsMBVAe+x+UJKdFUC2q6ZkOtEYQJIhMlMIHBRA09rIOJ5kF0A2Y0YDiNYTQOLZdRTkZRFAllh9Ev6hFUC5upkqglYVQGGR5+PNnxNAGp6G6X7pGUARJ+XCVDsSQNUfkUmuoxZAsEC8Fa5MFEBzo03+bFcXQHyFF91nIhdAM5yRPfikEkC58OMC8LURQHQw5FZGjBVAsLjltGdtEED4RiMy4mIQQDOSoOzoWRRAdM8xH4JsFUAxrNWJeBgWQLeJvhG0ZhJA0qdtXmcUFEATSsvHDLkTQCLdxXqBrhZAOeD43BsxF0DRC452uwEZQDS53eILXxVAMB0SgmmmFUBzgJoxZAAWQDWE1ujUBRdAXvFwVKv6GEDSJdijXaYPQPPt5z+AzxdAvSRUMRpPGkBTrRE/VjgTQDbf5X6OVRNAuBHc8Aq2GEAYVyHYjCIWQHyLD9nZVxZAMF92IBieFUCyFXDhI3EUQDB/iNBc7hVA+t22eIUrE0A1GmkxT48SQNtyUqTSWRZAlNpk2YtUFUBATWjsWJgWQHRDxUZHmBlA0RhF7hBtF0DjeJpNzZ0TQPot6kvSdhVAGnv7vTnHF0DjVC0VLPYQQDDKGIg/mxJAg/vjMkwpFUCbzMVwM7wRQLGN0mjN3RNAuXpdtq2BEkDTYjXg6vgWQKEYPlF0NhNA11tcPjuMFUB0LJI7tkASQJuyOOmbfxJAccFGatiTE0C3XhoYwg0SQBRYAcBNpxRA+zfbKonEEEBUJeCxZ1ARQNM0ygaovxFA/UwxPUMxFECz7oqntbITQDHxy9KH9BFAuwjDRwK0FUBdPCaLGhoYQD7LZrSPXRNAFIryH+fqEECTrE64JiQWQFnQI+IrqRRA/QNBmtJRF0A4tpjxj4QYQPntKpG7JhVAc7+yuxgFE0DCuLIMZSETQHOpRkNL1RRAsNGOSeYTFECxKe+p8PYSQH1zSqiYEBZA4++PhHz4EkD57mmsw68QQDPE6MrMZRBA2NY62Pk1FEDZJgXB3UERQLoG9e4+RhVAYeHcrvvpE0DwDGSwVFcSQPlMjwr7BBhAmT0Xs53JEUAVrwGRURAYQPh46NtclxFAefIQu+qjE0C61XVozIIVQPJ9OacJ0BZAs6dTwxBDE0Aw631e/IAeQDk8JKPHDRFAg7m3MZkHEkDzBa7qAu4WQBeptyCR/xBAMLHM6DCfF0BRYNcG3+ATQD49yNUK1xZA6LOhbDKgDUB9oUCmWtoUQFaK1yx/5BhA4adKwj3XF0Bztfq5/esWQBhbAiNs7BtAPMWKxw2EEkAYAYJo6sATQBijjqDB7hNA+B4qHuflGEDx1pxTAlkUQDDs1s9yxBJAuUrvLbljEkCRTaSL3jkRQLRxr6HjaBNAJTd+NHxjF0BS1zLrepoRQOSNJmX52RNAzJLxBNRlEkC5bZkvZZkWQBHiy9hDJhRA8EgFttUIEkARebxOQUEWQNg+JUPo+hRA8MTq9VvxEECxQkEqWXQSQGiUtwKIzBRA8CZsfHTDEkBwGM5X8vYRQKTehPngDg9A+Kx93Aw+FUDRc3mJ1xcXQNrzv6w9lxJAvYaDcfj7FEBgw+kZGboUQPPF8RGw1xRAMKXfpjNHEUD029rmgaoVQJlomJKgxhRA8RcJtWvMDUA327JdhOkWQKXfRl36MRFAkTHOXf6SEEDU24SF1mETQJxwgbpplRNAN0WNS5SIFEA0rFPfCrEUQJgHTIUn7xVAcUfdTYO+EkCXmjOfWvQSQNK2+6mIWhdA1Nzk80puF0ARpL4ftLATQJV55PTvaBVAWN3RPbZ+E0C0e3u4v4oUQHBdTIlToRNAd9rOkda5EUAuvc5ph6sVQHBZxNFy7xVAN19oU6YpFkAecRo3nhMVQLv2kr6l+xRAuQN5zqFsGkD5XJ2uKtMSQBRJvmlMoxJAka6hNTwkE0C19Jy4Il8VQHBUuqEqcBRA9OqcmS5YE0BcSx2M2skWQJHFoxqYvhdAeLCOfSGTF0DmrZJj6jUPQFS4BGU+rxVA7ZtglZkoFUBwpZ/kDacUQBGb/bDJWhNA2f1zym1NE0By4lv7u80TQNMho1ZLIRNA89oKqHQSF0Cyk0O89iMSQHlm9X1YwxRAMK6C+wKPFUBbKoDsOh8UQHowLCqkIRRA+raUgzIdEUA8LWfoz0gUQBIjSw5ZoRZAAii5+OXFEkDw8cO9nwYXQDH/I6WVexFAmC4SeLBgFkBUs8UkYKoSQLAIuuCW9RRAolNbQmesEEAYgrR4VSEUQCLn4zkJ/hNAwGQIR0cnE0DSGOjvvYcWQLvdcWtD0RhAEl3/nwQeGEA5rJZQRuMYQLo1pq62jBRAY74bNeGdFkCi1XOmptISQDFiRbCOQhBAXcx1VhsKFEC5GNcClUIYQHsupYefghJA8VMIruTLEUB8UhgSjZkTQHtx8m+5nRRAouPh7CGiEkA4TMLlPk0VQBxa8IeFSBpAgqaT6rU3EkAUQKsT/ZIVQLNl8r6VZRZAZw7LEP2kGkBjwZnxiGoSQHlPS41MihJA+F6F0AhRFEAVsq03RQcXQDZtM9EXeBRAc/pkPHLNEUDzFukKnjYTQNH3CxItLRNA4VqsypiFFECFu5i+or8VQJM4KU405xdACX0QFoobFUDSTdIBBhgXQDqVxur5IxJA8rdfcYyeFEAVGzz2X2QUQNeCbwCdEBRANLnbVXdoFUC78Iy+Jj8SQONBpvAUXhNA0j1BCuBGF0DqVTmgYGAVQPHtbhsIyRVAMxazKxkiF0CRmI0tBM0WQHUkZEVhKxVAdm1y+1HmFUDYMZX4SVwWQJM5rPQZuxRAEjIBIYbqFkB4ffAVXOwQQLJebnbq5xJAV2cUqzflFEAyhJEa0AwUQHIPPIcreBRAsbwafHQLGUCVl/V4GFkUQJLO+bj+WBJAtF+HEFYiE0BzkRTZEUkQQPjS7z452RVA9Edl9+mlE0DqmMi+5x4XQPHWhyGKBhdAZqiO+VWxFkB49n5FOpIUQNQ1QBhX1xJA/YkXJwZ1EkC4TjOPrwoZQBrh9L5dFhNAtHQKqtiiFkDxEduOV24VQFjJeHi1mxNA1ohgPdpYEUA+WNykrT4VQLCq3lfS3RVAcLM39Un4E0Bx5dgfklUVQHTn/0KtGBtAcVMeOze8FUCyQRrtCjEQQEFaLXZiERRAd7c7zQKqFUB+xDkyGkAXQDJa7XK9HhdAesrdVMyGE0D8eKaWPwMRQHLTp8jALxNA3c2XQbKNFUD0amJwtcUWQJKhlLnuKhZAEiNBd8XvGEAT9YtuavgVQHzb7Rjc1xFAU2ucgtBfFkC1sLyKnhoWQHEpoFdUJBFAsCleVvmBFEAY0Dt0sSUTQHxMRDQj6hRA1NI19Z6LE0CT+gCD6JwXQD5OojD4IxFAMTJ8cSdwEUB6CzQLw+wVQPbHFmYXGhlALNLcOpbFEkC6uYBolQ0SQPZkakhMDRlAfQjiu6+TE0A+r8qQUugXQBrPG3NkhhRAUwW4mDU8FED0b+m6GPQVQPlcuGuKjhFAsC7ABhzsE0A67CxSbDgUQJbxOntcBhBAIZfs2salEkAiQb3HwOUTQJgEbAKL6xNAsuzXKv6BFECUkrExvqwSQH7rQOQN0hVAMBMGx5GAGEDfSqv26moUQBlmYN+fMRJAYpMSvy9jFUBxJJTvFacUQPHKrxwJcRNAmjSEzAXrEkC4qcxFMBQVQPFh11rN4BdAcxLeuGGdE0AhiNydEtcRQK7Kzaz5jhFAsMu5eeATF0CyYQnzhicXQLXUY/haeRZAOvdoxfWlE0Bw7gMhFocSQLMDXBm+NRNAUznVvElBGEB6/0HsgnAXQKHnfVsaIhFAc7jCsFfVGUAYrM8Cyw4WQIl0rprXBxNAXAIzvff+FUC14QNCuHETQPzLISgFvRJA8Zc0m+pmFEC8bDzxUs0XQDSLAr+wDxVA98qi+Z37FkAcDy+einoXQIJZJaCgFhlAsGBLKty0FUC7mSxQHLsUQPTdm00R+hdAeGY+OOaIFUD4RX4bKYYYQCFXqkn0nRRAufo3eFnOEUD3M/yMaL0UQP7uzjCY3BRA+LTjARQnE0B7RsjPXTcWQPCdBlOwsxZAclROT49oEUBwH6fcsIMVQD6gU+YGqBNA4cPhpIEiGEBzWder2NQWQPjk7kkViBNAejDhachOE0ARrO9kxQcSQBmjDuRcpxVAkU4oCABKFEAiJO/SfDoZQLiNRwi0RRRAM5uxzy2eFEBwgU+/NKUVQCqNhjBl3RZA1FFWPPtsEkAwUNY2Q5ERQBRUFrXYAhpAMGMwipelE0Dw5u0BWzwXQLHvmYH0lxNANKsdf2rKGEAbKlXQYdYSQJab3TpaVBZAEeBEEdfhFUDT1mU47IsSQJpmTxjhdBRAUZ4u3Bp4FUA+t2p7ryoTQPejagcMIRdA+QiIb0mXFkByTFXneGsVQNOf++xINxdA8Zpb5iKCE0Cf69IRwfQTQDAuj5+OphRAWPWM1JVZFUCynY+I7n8YQNnPIiTrWxVAtcqmAWI+FkD4Np7jt5cUQLiVD6adxBFA1r6Sbc6pE0B0+gM3OMEUQHuFtYDxRBRA99McCc9CF0BZ+4WP5u8SQHaw9cEwMhRAt0bmYMN8FUB/gv79ElMWQNcLAZChlBNA9ynsYuaQFECzl5H1mSQWQHCGrxxjdhJA8H9qwBK5FUDytpTtHr8UQDRTiNhZCRRAcjG6Kh15FUBYbmHiJhYUQBUFbL0V1hNA9Iq9S3I+EkAYTWNy3zEYQLG7y9FRyxFAK16fgmqrF0AiMOk5HUEQQLU9R/UhXhdA/xIIAWQWFEA11cRjQWcTQDAnG0ECQBpA8+wfuJCUF0CzuDRLxoETQDIT6b6ueRFAF9v4ZkVEFEBC+42+Xa4TQJFQa7U9aRBAUodbae4hE0BzGx3eUdgUQNkJfWvDSBVAGFiC0x1bFED4CIVxAW0VQDvLcphsURJAKz6BXkPHFkDAzbLCXAAaQKHDlJUAPBZAd30TcIcWFED6ARLg3jUUQNKf0kVfjRRAW4NnMd6aEUB3eptZ9rkSQBVW5VcHwRVAFSggu1KmEkDkU1344mEUQODPqwSH0RBAdxmzAXQmEUCiGjYL0UIRQLo2WUzbpxJAMEaW9ExHE0CiR55MOIwSQLP3Dmv3shJAMYXJ3r1gE0DeW0SckGIVQCGIWzj06RlAlYaYCTk9FUDBr8NSSbwUQDIvTYCwdhZA02DAIk48FED2QOtlIAUVQHI5XinlyhJA+vssA+4JFEDxiskzgsIZQDE1aRzgkxFA/09Sv1SMEkD9lF95hWcTQLZve6C/UxhAlCOvJa6OFECxdAAZv/QXQInksfJkKBdA4nlSAcX4EUDk6tp2rK4XQDEBJFgCfBdAM9+DV7NkEUDgRAD1rNQSQHkQXvHKNhVAtIz5jr0fFkCyfifqk1wUQOCDgNYAYBdA9WbreylBE0BSyfX35nMRQLpKyUqz7BFA9tv15zZPFUA0DgEpW+kSQPiZp3+VUhNAVHXGHLu8FkD/7rwSjLYUQPJbN+5CDBRAWXQS4P2qEkDwLZABHjkSQPuOoEzGyBRA0RYfM4RHFUBAF3NyzAUaQHr4M6hoWBRANdTyN105GUDZDQziZiQXQFiN5ino3hNAUdr7M3swF0DSGN3SkZYWQLABPsMGlBFAeNjFF95IEUCzqQ/OjlUUQLV+VN3DFBVA9pqbzjJsE0AZmKhIUvETQPqY9lyRWBdAc14BHogvEUBzoQQHj94SQJFKlNsSXBJA84oxc4GNGUC2ifFd2O4TQLLiDj3yAxVA/PQwF5t5EUAx0prvWCESQDSXEpHcShZAo+6NN/0UE0B5H1ggXRwRQNGCt7VvzhVAKgrkN8TFEEBz/PNcjosYQFP6yHKnqRdAsSlxZjdeEUAkiwae5QoVQDkVyKJaIRdAE4gJM8mhE0B1glxvmFEWQCEEiypHLBdAMdzPWqUiFUDT8oaGeG8SQPM12HBqWRJA8qkrgiGQEkDAf3l+AXQUQDWasRqXdRVAagB3OZgbFUAxb12NsUgTQLbL9Bo0EhBA8rsfjd+nFUAzPnnxl8EUQLogqtjb9xFANAG2Hij8E0DyT4v6ewkVQLyXO+tatBBAfd1/++sCFUD2UZtEvoIWQJgrI2IG+RJAn+TGLBCaEEARuts2n6wTQDpOGW3MORdAsqdvGhpsEkAx4Qav+mESQDb3syBjchlA9cu9PnLgFUA0eOUgLnoXQDdURMmkIBJAsUQOkxJ4FUAbiQVp4YISQOBTnDttFxhA2EhjQNt7EkDyMF8rICcYQHJ844rM2hFANGedbtwkE0CSrdZDCqIXQLO6G2n1UxFAknYGxpprG0CRjdC5ZysVQKZaFeCSvRZAdO+Km0nIE0BSTNxOZI8SQOe7HYAgxhRA0W7NeOIZF0B+e1eLWxgVQHcxySkr7xRAxQl+oB/rFUDcsmWWO3gYQPRxJnqG7xZAcWWnzCPRE0A5V3qIswsSQDqTAbPGbhNA683LnJMWF0BeAr2BUO8XQBOCny7a4RZA9RllY1uBFUC8VXitMccUQPB28OD5XBdAnUlMRTnZF0CsEBapdAATQDQWh/9AFRJAOCwixVibEkDyYI+JlxwaQNOXn229sRNA8hI7ljqqFEDwdxSQQdQTQGJCTjpK1g5A8P4f+6XmFEC62b+AvgATQDSTS6NVKRNA1IHK20RKGEC2e8sENyYaQPA7BCpFRhVAU22Rd+ROGkA5Cz/5nTYTQLL92bjOVxRAnXI+oRyFFUDxBYdCXLYVQDIJohWF2hJAmmiipxoSFUBZIJh9reEUQDH1AvRV8RhALCbTnlWpFEDh1ES8XIgTQCQyuF5gkxVANoZd1LUNF0ATKJWw6s0bQDCSHQvc4hVAHoZY97CFFEBT23i9KX8WQFhtPr/laRRAPb33QTqfFUCxIMRehQIZQFZbWubZXxhAtzOSsKKAF0B6Q7s0yQ0XQBIN8SGIShRAt6kHjWREFUDwGldhOhkSQHEjNGE+yhdAdhIqz4QaFUAy7k1O+E0UQPofQ5VdRRRALy0tUA+IEkArd299v9QUQFhiAVjjqBNAc3i/OODOFED134Vs1fkRQJLLMB27BxNAsRyL1tzLFUC4LH/7Og0WQDy9kAHoBBVAfCgG0TtnFkDlc9WPGLcXQHmfEDvzNBZAEQOzk1ptEkAyPGIngJcTQLIJz7qIYhJAOQfZ55A0FEBzjA5sZ/kUQDRklE+oPBJA9srBDROyFkD5c4VeyGMUQHsRlfQrAxRAMHK0mG8mEkBzZaytDysSQFSptZQsRBdA2Yeh+07vF0B1U2c0Fo4WQOJJSKHqxxRA+1AEbb0CFUC3AOtgv9kWQOCXx2nc3Q9AtEo0rqs1E0C4RZi5D1UUQHKnhoAh9hNA08WYWvVcGkDwCl8b+MsUQJHm39R0ZBdA5JOlm55sEUBgx+DM3RQSQN1MQD68lBhAWEaQvkc5FUB1oGhOTAcWQKUTGTBYCxNAMeDNvbC8EEBgw7aglQkWQJbmIzCCxBZA8ehz3FgwF0Caqu3LBskVQLscn8O0jhNAs2ByUaSlFkCYOgdWGMYVQPxHetw1MRJA48gJAumQFEBwgwLqAtIVQPZJ97Ud2BNAteZc5qRYFkC9AOVFddoTQJXOui+ClxhAYRo0PAI4FUChEJ3bFgcVQJmOsQCjOhJAkXYaq81zEkCwFbtl8zsaQLGzwVBj4BZAuWw0rbA6FECR2HslP+QRQNP2PA30JBRAPh3nFjCaEkDk7nYhwowVQJKbhusb+RdAE2NxxwOiE0DysMG0kPkRQOGJiWjOwRRAeBkxoVjmFED5UcFRRQAXQHl1hvxTGBVAkVL3xz23FEAxS/kerrsVQLk0bKMjpxNAdQUWNI5kFUAUCjiRJagXQP3jHLoZNBJAQmwP4+yFEED2+fyyWjcWQHIr03+JrRZA9M6sak6xEEDginNatIMYQHbyRTxKShlAVoNCNWLDFEB+49/xlRYWQHdIOKeTDhFA+HjHV8sKE0B+F1fVKL8UQHEBmsca4RBA9+H8uia9FEBBMAOdxE8YQHohevyH4BFAExgAdUQyFUB7jZkBo3kUQPMa3JC0+RdAf+bja/0BFEC1KYE4cmEUQBhFXSem9hNApFh8SPN9EECy6/XsuZ0UQHiaCea6bhVAMQqtRVyCFUC4iouABf4UQDNEKpvp/BNAYnb5Gu+6FEBzXEYgyngZQDB+2rUTjBJA8mKcVylnE0A58Img+lkRQH/PH9NDUxRAGOkZJcDhGUASeDjCRAYVQDkaHo48pRVAcGS3N2rUE0B5lfXXAAMZQDbwjTPjQRNA1DN8COSnG0A7cvUtUugVQGBr3ehVIhVA0UzccPIRE0BVPYBVTbUUQOBDyU5iXRNAdWY09VR7F0DxSygW+B4TQDWVAuh2PxZAIiPNgrl2GEA2HyGxqgETQFMjRuOgThJA0xQV92e4FEA45faZEmAZQDOWz+NqGRVABVPtFXqLFUB4iBRnFt4TQPLq1PZl1RRAePtjonjtFkA8AMZO7ZIVQDw3vZAbeBFAdXe2eY37FUAZbpkbxPATQPCRWxUc5BRAsGGaWXj6F0BwhqFTa5kZQPdPlRgkchdAsB62+KfiFEBtw+UtLA8XQDHMnshQkRRAfm1XicajFkDyN1Bjz9wTQNMLd1ebQBVA/DZaXojGFEA2nxrOOoEUQBKeVc80UhRAce7im7JLEUCIEjW+R2QUQGcE/7+UuBNAZmOGTef8FkDx711GfPUWQPVk5bNtYRdAGUP2ucvAFED1Fbh2/j0WQPC0fRqhOxRA+YsW6NxWFEB8p/pszgAWQLJfdpvWihJANp9JqtZnGEAwQeaipUkTQHBHiyNAGxVAmKnTW6kwFkBRUwyHWnMZQHEavGPbmhtA565OHUldFUD6aDiILXUQQCJBhrh+zBZAkfD9/SpEFkD8Qtid9jgVQHKGVPXJHhNAYM7mn9PkEkCxdyi+pssWQDNZxvg4aBJAEWcp5fi+EkBivdWFYrcWQDOi8a3EIBJA4JRi2sRYD0B7Clh0/YcYQLudEuKUXRhAnurV64zOG0AxHD1UC7ERQDPLaw/coBRAeBLVqzIuFEBzdt94EgcWQJKbNWu1bRNAOOsYCY/ZFEC005MQP4kTQDdOKwwhMxRAM88Qw1jdFEBw8Dcf9GsWQHqQZEDWBxVAeLguWrbFFEBZHeFgjDQTQH8GfEbeChJANCG21XApFEB5sBoO/eEXQAzEtNmxvRdAVWQ50oIOFEBYJUvB+7UUQL3zuKyhZRJAsewJO240FUAyr6re+KoQQFPJUMbNcRFAeeHD+hqvFUA6X6L1c4ERQHogl4TLRxFAYcAz2d4vE0D9BeuoqIIXQLdM61RiExFA+AqxWAh1FkD0SF0AkDcSQNnfmMJl8RVAfbk2mod0E0CKi/whtHIWQLpSjLebABVAdJMb6z1qE0Bz+kL7cYQUQDyolAP/cRRAMqBYvpD5FUDsgXVqHgMTQJMXZjzJkRFAeFpmmStHEUB0crdVu5cSQJKqc4hI0hNA1N6734/UFkCUT/GohmEUQHEEozpsExRAYBBHNt57FEAy+l4Ex8gWQJI5M0soxBNAcHKkA7prEkAAj0iCsr0TQBR7cTE69BRAswYLV0ItFUCRbOhW/uEUQOhQ3aT0LRVAA7MHvqfwE0C4kGF3woIWQEAgRx2ExBBAcW+7aD8qFUA/3ot95k4YQP6spAGZfxJAtv+Ld4wnE0DlSQx3/28UQGnTJ/xE+hFAcJstnbDKE0D5h+Yu0NAPQHn91Spv+hRAv3utD/lVFEDxpPbTuTgSQLqSNNrPlhNA8Q+Tr6J/FEA0N2ki88sYQLIJ0jGOThZAVsjsGXVHFUBy8nvPE/QXQNTXp37uShVA+J+CiLFCFECy90Vqr0MWQPHGCvy6oBRAMigGqVZvFkC5bb8n5DIYQDmVysVlbRNAsG0yu95QFkBEBGruTogSQDBNp8y/wxNANaxMKEPvGED/gOO9tPwVQFRco1Y24hJAYVpZu1hRFUDxDmZa46QRQCOSIwjZSxRAcIb2ioacF0B0lIyYhXoWQBJcaTrk9BRAFWD5TaX3F0DzDvysIYQYQPg9dordBRFA8cFBSsLuEEC9aZ98hV4ZQDSPf3DCMxZA10QesKu0E0DRZaEIBEETQBRrt0NweBZAdvf/GbsDEUBxscYhqqEUQHA3nFg39htAMm93cEyPFUBzGIAQaD4bQLpi1uFtpRVAOkPjKSPrF0D4wO7d3yMTQPS0YX1zFRdANb2xSb6zEUD17VVHWcYRQLHp7Dk5dBdA8bJreekRF0Bz7eyGThIWQNJvA8MSKBRAMumlUzneFkAzm15KkkQUQHAgob4+RxdAlVz7Nc8JFUCzCd3d2ikVQPuf+L5Q6xRA8xMu0A92GEApvSETkpEXQPpohqsvHxVAMLG/qTz8FUAiyLpKg4oWQDzzo0UklhJA43WbfGYNGEDXfCBWxhQVQDQrY0EeRxVAkcdkXAmXFUB5jpf5lHgVQLdz0YyULhRAUlcyKnTDEkDYOYRL8UQYQONJSay0jRdAu1jD61EcFEAToUjvZxUUQDsC5MmYaRRAE22AJYoOFEB4BkWGSYESQHLLLb5SThJAPO93KZiHFUAwzIHnG/0WQPMp8Xd+7hZA8Pq4jUOmEUA5JA09aHEVQCGLUDSexhVAlL3I/uRIFUAoHwU4gJIVQMHRcAwPqRJAelkC9a3EE0DVzyd8CLQVQCSeKTWBRxJAOFUtIUHvEUDUuXhJuZMSQDDGflCmeRdAFoEmS2TpE0AyrC6XbVcUQBGFG7ohGBZAfH/mXpLqFkD6WTVKUpsXQIAl9eVdURZA/qfyFLqTFUCenVhB3v0QQOXAY5EMxRNAE0C65YJSFEAS5uvTvXsVQHG+xRWqKxNA+Dm5OsXAFECxwBhDIuYXQL7VO5gFIRVAJYHWqu6cE0B0P+fcZcwVQFH90P3cURNApWLQV/rRFUAztbXYtpoWQHcshEFudxlAWX8GnyNPFEDkZXSgziUUQJXEeS1ZeRhA0qUY6y0UFEDUni46Z5oUQHj4KlI0OhVA/aNaQ3/1FkCxWzMMiBIWQDo6c3UzfhRAs49ABhcNFUD4BTZXbfgTQHEgboSc2RJAk1pCDTmeEkCem9WhKqgUQMO0esy0uRRAeU9ZfyFMFUC2mBB/qW0XQDGZCbQVAhRAuenedQF4F0BkS8Gbk4APQPVY2qGlJBhAFGumzIBXEkD2MG0OXO4VQPG4SZ/GcxVA8Bfgb7IOFUAyrVrNLF4YQBgBhs4bcxdAcCyTaq2BFUDBmBvbIR8VQLM9H2aEihdAASjYqrKUF0B0pCjjOjoVQH+QsEw/6BVAsJIgCGGiEUC1MlINIaoVQPmODhKo5BJAWPCvjWf1E0Chl3K0GsIVQDK/SZlt3RFAZUCXaDvtFEA2+3qyji8SQLg3qtWpMBBAdIeIQ82fEUD6/NP7yMYTQHKk01pcDxRA92lXpf2EGUBDAYeoUqoNQLWSW9pTjBNA0aYc/lXJFED+6wXZ8gcRQBX5E5CBGRNAeWBxn4eKE0C733gIbSsWQFJMe0Ln2BRA+H1EVQSFFkB1OkD72scUQDUAJaE7zRFA8/9fYrkfF0C4TXc1V8IUQN7ev/jZCRZAeuObi1v4FEAwoqYzLwgSQDylfj6o6RNA9j4344ogEUC2wNOdc90SQHpW5SwdsxNAmpvM/EoiGEBwch+aY8AWQBJ2DPJD4xJAtgnbRGvGGkAy0QC/86kWQHwmoxdOphJA8EyYQpbOE0D19H5wJrUTQHT0/J5rDhRAN6JLrV3jFEB5YczKehsUQJK2PsrcqxRAEiqNUqRfFEC2RwCnvB8UQLCz3PSZBRRA4MmNQbUkFED0tsO4e8MRQG40uG0HkRJA2a6hkTJ8EUAzMmkT/rAUQCnOEE51MhJAGUBJ1IqkE0DYf6lSjkgUQJpNlnGUvBVAd9KRM5QnFUDaU3+3BHIVQLW1ejtNJhNAF505/sD6FEC8elW5SUMXQPIrTaU4/BNAXOZXR7MPEkDwApfOe50TQJX17CXWSBVAqesIKNfZFUA72TEPKI8VQPIgXpf4zhNAeWFiaXDWEkCSvomxLkQUQLXT1yK+rhZAODpoq/t7FUC5d/xDpWURQPbUmYUy0hVAUjlMhaCaFEC0edqPW88RQLO+iTUDcRdAMl4OzXlQFUD26MgDBWsRQB/uL+NNRhhAWfIg87eqEUC48WBgBkAVQDH3T17g/BZAloEEAPT2FED1WKUDqZcSQPexG102MxZAq9xos9z3EUATU8iz2gcYQBT7q7CrFhRAmLxvZqlhFkCxOWwdKeITQNTZRAKhwhVAotkbnsGuFEAUsG8cOYQWQNHuSyBDNBJA0dMkS7DWEkAUheARV3cUQBUWoMVrSBZA4qRYwDrZEUA6XJD1G+wUQL8j62TdvhRAfjILLmXuFkBRMntr5KYTQPOnR/yrgRZAuu7GP8LOEkCxONQceTQTQPG6TyCBRBVAYBs31YdjFkBUk3vEFWoUQPMxm2jFdBJA+Az4b+jaEECxhxT+GDAWQHErMn97kRBAuNe38FTyGED8WdUqQZkVQLnf4EJuhRFAAHe5UiilE0D00lBv2p8bQPZ0ecwd8hNA8TkP24D8EUD8ATRPRs8XQDWrMtDNMBNA/Masl7hrFkDxvLQp798XQFmh40NdNxdAe+p0iRpNE0D0eAw4+YoXQD7s9DIFoRJAMcxgX8dsF0Czi3lMyzwUQLOqDPaMNBRAaSIpI6VTE0BTiKGwCqYTQD0jnJ2nthdA4PrJGgbUEUA3n3AjMe4RQLaFTlMukhRAE/3Kj0EuF0B7a3V7I80VQLvr4ZtizhRAYoUsbggzFUDyULRVgZcZQHcejw2hXBRAMEnOcF0JFED4Vld+tU0UQPaj46aXhBJAJByGKHjgFkByt7W6J2gbQHM6vYtlWRdAeI79quXKFEAYG1Pba2MUQHDN9S7afBJAvqUUdd8UFkCixnO/JDMTQHXZxk+5YBVAW7cSNk4KFUDeBa1e7c4RQNInxgsj2hBANnHZHyzHFUAZvrldi/oZQLn4zx93dhVA4I0Hcv4jFUBg812XQzQRQHhjs3xScBdA1apdks9kFEB4V4oByg8UQH+GfSft6xVAeXPXdYHfGUCSwj8J45QXQLAMtMe+shVANtEqF/y5FUD6boAp6ucYQLENB808UhJAHV6gNZm8FEBygktCY6QVQBqTLT4u/BRAew76HIW+E0D3VUsUhzgUQBiOIhy6RBVAobJCaQdwFkAyI7sc1YYTQL3UaL67sBZAcXqE2DNzFUD+AHOdG74UQBdiAcH1sBVA8tiGH+TvGEBO5mwZeO0XQFPbAAUamRRA1C+9Hn7SFEA4Bur1YJoUQDKBTy001xNA/1Owruh8EkAzg/oS74YZQLeYCUMVHRJAuPJ0D3M3E0DCPoAvexoUQPkaepYJehJAsDEBzTNEGED60qmfVNYUQBnSUnJmERZAwvsrbQduEkC3tU4eliMWQHu05h6qnBtAIYy91ta8FUA8b+Sfv0oUQHLZLj+uoBdA8/UjCVp+F0C1hn7C77IWQHjKJwwrZBFAdakTeWxsF0DzQ3NE2nkWQLJH3Zog8BVAw3/crmtDFkByiRgydSsVQNKg2h2UZBJA9rGxRIFDFkA7rwoSoUsTQPW68WcwwBdAkYUYiBnvGEC/kMaY8VkSQNNpYKW1PhNAMoyfH1b0FEDSsL3CjjEWQPFXxLGh+hJAIZ1gYrhTE0CY+n26yEsWQGmSj/NdERNAdKbC0TRVE0B1D8xSGEIXQDHWVu+FjRVA/TBqyQGUFUD/dpWxcOgXQHHTtJjSZhZAcvWJyh8PEkD7hzubkrcWQOMUv3yPqxRAu/xiNjkYGEA6de286gQaQNLK46Yt8hRA9KCTiIY6EUBxktkHWl8VQBH5wtb7qRFAOXDfmd5TFECSwGPB1qsVQFTpEVNcnBRAs7JkzVMVFkDjuCBy/YEXQDl3sVkW5RZAdf77PzTRF0AbzfQ96K0UQLbRuwyP9hNAfDV4+7WDE0D00w5l3xkWQJFVqc/AlBdAYscNKSTjE0AB5lsMly4SQJjqB7wTcBNA/FNVf1oqFkCRiegd/LAVQLPB/QZlBhdAiguD2UnOE0A34mXLNO4RQF3h4XamtxRAe1jEix89GUC5tMiqxkMVQP7AJaqv2xVAN75KSD45FEA4fiyJEg4SQLBwoj2tTRRAMcdlEFAnF0CGIQTtlNoTQHK9s+8dWxdAv4JEuybGEkA657X+CsIWQFnXvIJKgRJAQQZO9WzLFUA1M+kLUr8UQO/7sECdORVAtYR5OelgFUDgOmNjSo8QQOxrqhy4Sg9AgSFAQJvwFEBwrL7gP4wQQPY26Jn+nxNAm8RgIOQ0E0B1fOxTo4IQQKOAq9KyziBA+pSPY/TMFEA40R+j82MWQGnOGp0A+BFA4eYjFVrNFUDw2Jqcyg8UQDTN1ggP+xFA05drMN9YGUAjFEqmVioSQN01TETltxJA46U8GIeoFUAwpcEWDlgVQJk8mbnCDxFAeTHLJ15sEEBw23IOJbgaQBGEDHjBuxNA4eVs7bznEkC0Jx7/O9YUQPbangPBKxFAONWzSqpPGkChb7BUVMsSQDUiUvXYIBZAH7rJXkW/EUCyNMGV79gYQDQ3+HMLHxZA8PBlF3FbFUAZVvafu3gSQGA12qoqFBVAOEHR0nvAF0DcC3JMaLIRQBLJc/LDBhRAuGvpNxsiFEB7i2elZkYSQHnlj7Yx+g9As+Qp8anKFEDcBvDbp1sXQHL8Bt6EORdAojaEeIY/FEBRhwgKODcZQLG5mAqGfxdA4Tg7Nba6FUCwWB1Z6k0UQHwHd1B16xVAUy/eOLdzFkBzLbYbEf4YQCnu8RzJuhFAYgg+u/PmEEDx+x258RsXQLJ5MBxVkhRAe2ToQbIOF0C6M0DDsMkSQFFxi9P5MxdAG8vT9A7oE0D3rHCtRV4UQLK+i86QnhJAF1s1N0zmFkB7Pxm+FiMSQGVZBL4UnQtAEjfFSAvrEkD+YAU7Q+ATQJTbJzkejBZA9siD7tgAFkCx81mkon8WQDMcScR1dBNAlcjutc79F0CXfmBAMtYVQDHBu1EcZhdAFx+VN6StFECANWHH6koUQJEYHeFyQRVA+lKZt1YsFEBoD/bE3oQVQHWM89RpdhhAslkVMz7+FUDXHxx6LVQWQHHdVcTT1RlAM+gi3U1kEEB+nCG17M0VQPLs/txVjRJA1L9Ib++oFUD8LLC/46QTQNa6+fHKIBVAYU8eCYAuEkDexv5XIBYVQNiMS2eIdw1Ab0uGWXUOEkD7w755V8cVQHjZGV0YtBZAOBgJWQnLFUCVkim4oy4TQPjkeQPeDBhAM/4v2pzpEUByUczFfTgUQHuQ7CzrlhVAsozRj74/FEAwcff3XXATQD3sHIrp+BdAsqAC/0PSEkA1/94QYXAWQNz0BGDFmxRA8UMWGFuTFUD1XgOEfmMUQLIV2IncPBZA2bzr4lQPFUD9NMvZ2O8RQDRr2cI+fhVA5FkMzL1lDkAy9zFyeS4YQHBRF/CMaBVAklq6vYdXFEDCKyoq/PEXQLEnfTTvpBBAcygiyWdGEUBZdBvgvmsSQNaq4wsn/BRAF07U6J8FEkAzS6n46cwUQNH5QXYR1RVAP+Q54z1ZFUCkK3NkCUMRQOu/K6VjMRNAMWMzfLPcFUB5UWcEYhgXQJGcZCs/7x1AUfiQUGHZFEAYGmB9xkQSQL1tZPY80BhAcMERYwb9E0BwyQ0UokIVQHMz1GUB+hNAsx8qhq3NF0C74+o8BbAZQBVsSJa48BBAkrXxbmA0F0Cn79mPqXIVQPIWdsLjsxBA9xu4o8QwE0DrGeamzLATQPRrpYRWNRlAmHhVxBzSFUDR3WGI8BESQGAC5vED3xVAkxIW01h2FECwbTBKt00TQLBCOSOkQxVANMsh2t2xFkCRZNXO1acVQHnjM6z9JRNAt16Y2sooF0C4p8adTyAWQB6DDyetFxVAYRcfOqsfFECZiOHAGwQSQP/mPreojRZAuL6wwj4cGkBwleolIFsRQLvaAOuH+BZA82w+5r8OEkCBjFrm7/EWQBVAUUHOWhVAsHqDBXlUEkBz1JCxZmUWQGbZDD7j2RNAEQKgDWz2EUD8Hn+8z4sUQC0YylxSHxdAN07+O8nTGEBy6sW/ILAXQP8H2UEzgRVA7aNToAXdEUD80H1YJsQRQPOdnycFihFAuUl9f5tIGkD3ZiS8ZlcTQPAKAZ2+ChRA9PIJI2L0FkD0/bLoMYsVQBfH6xdbPhtA/gFN8ZyvFUD4eTdKCw8UQLmStFh+5hNAXCi6aSRFFUC10Ict0E0UQFKnTWxAIxFAt77YbgNoF0CxZ2ilAEMUQPmyUQZHGBZA8hHU++ctGEDwrYn28EkWQLEDhq3b4BNAMrdATprqFUDYJWt/NpsVQDvSVHJaEhNAAQXqoliVE0Cw4wolpLwXQDhOA7DiOxhA+LqFab5mFEBU6afvhugUQBoYkklN1hdANUsRZtYAGEAx6vr53nMVQDL/5QzPvhNA8W1SR7UVFEC1S0/qPBMUQHFGZpFhGhZAEbtSyeoeF0BzU1ZoHHISQH0KXJENrRBAs2JvP0+JFkCSj1g71skSQHEeCFs5PxRAtgBEkLXnEUB4xOBfX9oVQBM+TICWwRNAcR7CKFbME0B8CZ/QvjcWQEI+oELxOBdActnqrWxoFEB21SWzoMQTQHvu+8tgYxRAkavvf3opF0Byp2HePZ8SQLLPWGwmxhdAu+0sxtKjE0AqzqBbzDoVQFKbi92UShVA9OP+SLXOEkAzzZRAoQMbQHEL44WDzxhAtvP4TklOFkBzsdzJEdQSQHYt50CpZRRAsjvJ8po1EkB3662jc90SQNm+NS21/BNAXhrqRVNlFUA5QqQwg7ESQBl3dpcvOxRA9YzJscmQE0D4fiSTP8EVQFJf8hr78RNAYda6aKgcGUC49h+0uHITQNu0pVYqKBRAuLV9UWPoF0A7z12VuycVQPmYYxsdOxRA1YwG3IJoFUD7al83WFUSQPMLvh1XdBVAFAkciEcyFEC5IzkebNkRQPu13AGF4BBAmPfiXEiNFEAbRUoOeesRQBH2AsGylBNALPfZ2099E0A40O999qkWQPNAaTUpJhdA+zuC795uEkCwQoOW4i0UQH/5LqmVNRRAOZOtKnvjE0BcxpiyeW0UQPUfeoCQdRZAOOomR1ksFkBwB9Ce8vURQIHtcqZRcBNAPPbnuqQTE0CmYBcUQhEWQPH4b9UGJxpA/+F8354aF0CROgDloGwWQHTbTH2xFhRA8zIPOJ6vEkC972T4sX0WQNh4VVnL/xNAfdEpUwE4FkB11UrI584VQDlLO0PArBNAcKVUuxkBFkAhWEnFmpsRQNmtlTuU3hNAvIIQrB1GFEBxscXuT8MWQC+InFaeohRA0jA3iK9pEEAS+tMqFh0RQFl2ITcLqRVAsrMMhNxOG0CUBYvr2xoWQP743egcgBVA1Seg1oBAFEAyqyjeRfIWQHakTJ7D4BZA/+a8dy55FUD6Kxj4Y1QVQDHQ812cshFAWfv8aShwEkDoU7yITr8PQDkXaubjcBFAtMdjcZbUE0C1uu0U9DoXQKlrSZXihBdAeF/L+8BTFUDU9sjVrdcVQL3wFQlkwBRAevClc0aBFUCWJHDzzRUVQNin4JMT7xRAYNJdEtq/FEA4CCQV+fMRQFQV+kMoghJAGmOvId/XEkD8LlQlwCEUQPVBUZUJDRdAC+dkFUFUFEDUpGomYJwTQDAIgZiykhBA/oXfhOiIEUBWBbb7eQ8XQPPznuuOixdA4aVVuzCWEkA6wWbQw7wTQDfFwZf83xdA0eTPL9MzGUCxbrQLzFYWQFY58rsggBRAfbnOtkpYFUCUEmZGIGAWQDYb6y8KsBNA88En+q8kGkCjOssT32YUQOJAx2NuhBVA9EfpWlMrFUDVwvZ70hcVQPIZ6RWCthJA8dFbyOYiE0C68Gfag60XQFnIPZjHRhRA826WhvuMFkDxf23izO0WQDUNtI1aOhZAVa/NsqzpEkD3lcB62bEVQFJWFguiGRVAuvzHwy5qEkCl+ezPOhIUQKIB6PjLbBRAfInDyVONE0CzBCzfGtwXQDMvAKGJKhRAWNuh8uipGEB4zl4My38QQPO2+cgfkxhAurkuI1t0FECoglSWR08VQNqgZasRvRRAPQYDgztBGEDy1+Q5jz8WQPMUlV7L2BRANZxGwF8WGEDZWyfFYsMWQCQFwG8B4RNAMBWWraRwE0Dw1Q7NYhITQLK60jif5BNAec/F3FUOFEByFfpXvOIUQP+3qExn4hNA/bltpcWgFEBpCjtD+fMWQGUg5LlaBhRAeK8c4P5vFUCzNHvWhokQQLJ+sx6TjxdAsUJv47MzFECS0ARu9vEVQDj8tR/FzBJAoDKvBy9GGEC6YldFw8QXQNmKobqJ4RdAsf7k8OMLFED+JfT558QWQPoHTlwVNRFAuwNxZDV7EUCeSyhmTbIdQHJML9HmxhRA9iqNi4KwFUDzcOkvWuwUQFFa8UHTOxxAk1szehGWGEDwBG2LrKkUQPs7SlG4KBdAfpDjjDV5FEC2KvoHdHUZQOCIA/BTtxZANN04nJjXFUDyN6GlZ7cSQDDXBwP97RRA2pU7AFe/EkDwJmBhypsRQDVrwZDc9hNAGflz1P2GFUD/ztwwf7wXQLyOLMs1BxZAPF+jZLPTFEBLcuFD0EISQHTZvHEvHxZAsjlRdnaYFUBTzvONuwAXQARjm83MWhdAmDqtl2EMFEDyRHdbCmsUQDPMNE9/lBRAcGq9CzwIFkBlQhR/K9oUQHPT8YP92hNAMIAHuTKPFED2XdIafTsSQNTuwRxlXxtAcHcG45sDGUD3SOsCby0WQFIPf0PijxdAugB1AU8BFUDhhDpNxGIUQPRNAH5NqRRAcoNROfW9FUAwsdZ/lnoXQDE3YtGV0RRAzbiHyjm8F0Cz+ru+1/MVQHM3FU7XzxBA+qIGsb5qG0CWqVlzRygVQBw2PUIHmBZAkslUZmxREkDwLtitqyMSQLVv5xmTaRNA4yqNow6oFUAJppQHufEYQOBg57A2tRNAtWxvfqa0FUBSW/pSN1wWQLb9olmELxZAufLyNy14FUBRjm5y16oUQAG3A7OVKhRAs2n3iMQCF0BgF//VDhYUQBXcgSw2eBRAQiCCR7vtFUC0nJ57r80UQLJRA47avxdAnrMOMjEvGEB34IUITecYQLrEoH4RfhNAgQmUa+SoFECxl+VH50cRQBkzM/H8iRJAcSmeQ5KbFEBh6kgi41MTQH2NrvXRYBlAshoLas60GEAeqUbtzuEVQHIXCMmHKhRAMJDiwXQnEUCxQajvDEAXQPS1B4sLYxRAcWHlg/s/F0B1Kn9pW/sRQFrfrM/nPxhAvTDXKnWGFEATDvxv2/MRQAHYXgvmuxNAfMmN/P11E0AwX63jXBARQLBYfFqwdRFAkxi/oJsoFUBw1sxDIQAVQBhyIqUvOxZA6mt8I5hqFED4TSx76asPQDmu2dJmixdAAnCchaUsF0DzbQGguD0aQNUHhJfcaxVAk/c0w66QEUD6UXH2I6ERQHXvoLBFcxdASqz6P/LMGUAjjJEQ8osWQPSLxHGavBZAdeI0/mJBEkCZq4dFFCMXQPOEpMhHzRFAuKhfMRktF0ADnnqA6TsVQNK2xMpTMhZAs/mWPDbXFkA8ytnREqsRQLNa8Qyl8xNA8Rwok8yzGUDaP8oJhsgUQKIYZ1ibrxRA1g2pIco8FUARdLCD0+oRQJN+MuO6oxJAeSKO3SgqE0BlJReB0XoTQLiWEsIg+hJAO8FXJjggEEDXwtnmDZ8TQPEw9jGIuhBA3mOy0T3ZFkB5Snt4WA4UQDUq3FKYFxNAdq91s7X8D0DzfTT8ibsVQCTHL4KfoRRAe4AmFiMCFUCwkHEevLYZQFF/mY+eQhZAaqFZjH25DkBmWgm2DQkXQDk71EjrqxJAYGJwLNYiFUCTsefgiGISQJO80zdjbBRApysxQDS6D0A1yfAv6NUSQPl7rDTHSBZAOKhYFEmtGkDpu3LjoioWQFjvbWHZoRJAEY7FMnQbEUAUB2XbtN0XQKf59jHjUhRAciPooXXpFUBT2HMcmIsWQDOimAe6vxNARwZrK+ZGFUDxckTJgO0SQPwYoGihmBRAdOwW281+GEBwaoJmlhIVQHCM/urDnhRAufnO0me0GEA0vEVHM1oUQJIGz2VaVhVAdz92rkZoEkCb0c7Jwy8WQGVJcrVdMhZA9TZdRVMmF0DxbU92zlcSQDH4/FORaBdAMPxtfwB5FEA0q1hvGXkVQInY6obSgAxAsAsjHBJxFkA2RzMCFnQWQLC3jUouqhNAUUbF16IdF0CU1Hol3EASQPeQmJ7w6hVA2ne9vA75FECxnv6pwrkSQHXTYKt9jhVAsXMysiUjFUDxEhM3jHcSQLxknJ28/hNAvjkR69a4GkASHyvne0cYQHItNXAZahpAet/MiQoBE0DWZp9BPY4VQDhehDpMthFAEc5w3RkTG0A4+fiq2kIVQDCSHUzy7hJAUSG/ENH/FUD3zgElUREUQJoRpu7TXxRAM1h6ASVtEkD9G7fq4sASQNl5B3OJ2xNAmBPkmm5vFEBZAsVq9MAWQDMF7ekFLxlAOMi6e8ItGkCn8VRtSIcSQOBBbPmNTRpAwSxf4zPJEUBx7s2M8eoUQH3ifesiKRZAERpgwLgYFEB3QngCl4QUQLiw7IrhihZA1K0fTAi6E0Cx6W29tm4SQHSpYw3fuhJAPxFVO7YgF0DxLvQdpIwUQCf7eu1xvxJA+PwXGI75FEA65fwD4wwUQDADDlccUxVAFGgCP7lFFUByjYMs1rEUQGvpn5hrQxhAOyaB4AakFkDTlbvaZ7UVQDXxZ3jbZhJAkecGxJ9NFEDxyzmH2TETQHlTPd51yhdAOrKnGr4cF0BzPTl65A4TQLjbi48U3xVA/HnqlKqnE0BWka0MMmcaQH6k4Clz3hNAu1p0wpU8FEBjwux0F6oSQDN3hyo9CxhANiBcD6l8FEAadfg8rDwWQHR1MZszKhVA8HiDaSdtF0A4ZlXzoaISQKsK64pDVhNAqbAQmDgJEkCbtCJmojkUQPq9sXF1UxJAJZbqY2OuFEByXlddd4sTQHvXWNcnDxVA8YWhK9bjEUBynTEa7xITQHIbvv/sgxFAWQd6kPyhFUABdhFcx6cSQLGXgdw4YBRAv4wZ5KfGE0Cy71kh9T4UQBJQY/0WKBlAsREq9jJJGEAZIC4geu4VQL1i3UwRchNA0RrfGSTUF0DT87wcS8YVQHZ6LZej1RNAcPXYgav4EUBcbIjV3R4VQJFvx52jxxdAoQFUuZ8gFEAxMVWKSf0SQPEdRIyACBhAeiZSgkoWGkA23lIQI7UUQHWfqg5EjxFA85qQUnvCEkAyk5EsRpQdQCKmLqoWHxNAsBkmARZ/F0DxP/eCR/kRQLAIHWG4JRRAMBcTLqW4E0A69FpZ1lESQHyN5weNyhJA8CObDdjHEUAYNtnrizYRQJuM5zcrThNAUmjweWM0FUB19xG6JNASQHtyiAqKBBdAvd/J5ScVE0CyJwOAewcXQHFSLkRTExJAsmVRAXDXE0C6aK6Zsr4SQLivUkz1IRVAsC/KS5vQFED4x4Q/lc0WQC1byS9NtBlAs+YEoWbOEkBaGrRSyBUUQLSzQB7HQhJAcaCpqYy4E0By/4vRRlwSQDeNu8TmyRNAlHFNvY3hEkAqBKnsK7kVQHqwbsvjsBZAYBnxZxzdE0C4kgNCFccUQLG+vtPBqhJA1zRtL93YE0BYWd3rhioTQHfsKBpa8BVAcpBypnk7GUDwMpawzZoSQLNLazlVvBJAEuTHoUdJEECwipcgJUcWQHVgoU4XjBZAgqSKM/fMEUD6pEicLBkTQHyE1cwiixdA1TKOlmVwFkDRmeKYXi8TQK4Shz7Y0RBAcqzzZnppF0Czb2oXb8QTQDhlLsiZJRdAaQ1e/vdmFkBjGuf2KLoXQPS5hnLh6RNAf7i+KPNPFUAnVKIRsYYUQGIZqYMGuxRAFuNCQOwQEkAUrpRP2VMUQLS4h4TXCBZAmRz91bcxE0D3450Ms88UQHP7a/df5RlAccpocy/8EUAYOSs45uYUQDj+Qf+EBxdAucIKVgHDE0Ai6axgYJ8PQDCUGXTMNBdA80eaWhsgGkA7UHcu6GMUQGPBlztdGBZA8ik7w+ZzGEA4kCc++NEWQDm4bLCO3BNAsueKRK7AEkA+c3FikHsUQFZQPBrVvhVA8xr9R+bEFEBxTHUyOboVQJJfIkr0MRVAfeM1LMqgE0DyrnsacRIYQH9FpEIMexRA8s99GhZzFkA6IffJ1U8TQDa0+2xJARZAcVNqIMWTFUB051qxGOIXQLrnNgAatBJAgT41zi8eGEABb0RW87ATQDrev8lo/RRAp3FJzXeUEUCymnk95bwVQDX/EmRxERRAMVTuGG1yFUCw40DTvFkUQGKnBz7M0RRA0gSQFcIAFkCFayhSTQQVQPZQjBFZPRJAp+xn3dnNE0CxDx5Qv0wVQLFKmXJwMxxAZo5MbxWTE0D/6vlkK4oTQPgu5AEL7RNAcTnK6667EkA1jkfQKN8WQN1U4Qm4hBFAgyPoOqo3FUAzVQ08Gd4WQFb/x4zzhBRAcYz//UaiEEAydAQ3+mUWQGIdebjWPBZAInDiHgjcFUA61NMw9KQVQHOwS0Vo5BhAcgEhVIRLFkCUxpAEc/EUQDPYLtmx0RdANEieDkcQFEA549F/nTgVQJmdTheCUhdAsdynIXV4FECW6KMzMxEVQPA0k8cBgBFAJy1+67H0EUASpm7YLzgWQDtpGuyjMxZAtfAkKzpGFkCx40eb5XESQD+UjEoSEhVAISQWXi5bFUBwMkgqkPITQOKKW8dmRxJACOyBes1BD0A2meBZf+ITQNJSESynahhAeFcQg4UXEUA0tgi2lDgWQB/x4KlpWRVAkSGeO6tgFUBsfl8X678VQJq9jl5oWRhAU7wC99lVGUD0s5owvkwWQLCehmZsfRhAueG79vkfFUDzzm6Pv6kTQD9/HCgFrBJAdYnW5WECEEB+HITkSXoUQHvJm9HvgBRA2mqUVE+5GUB2J5tgzZ0YQODDgD+FjxJAorFNWbgVEkCiXg3VH7EXQHCATgf7hhFAsm9DUwZlFEC34YiuRCMUQJq1vjdTmBJAqS9LguEIFUDym38EKGAUQPFmEhoftBBA1JDOFdAQEkBYtduq/MwWQLHH7excUhlAMl3EgWhME0A3po0sb0gTQPD1HsAO3RNAf+Nfq/yOFUC0S0+o0HsWQHz0KPg7qRBAuXuHJ4eNF0D5JeSdk5ASQDlNT0ttcxJAYpHx49vRFEC4g0d/StcQQH8g4pZh6Q9AN5I/Qn/GHkD0ypIPOuQSQPVTB5KfbRRAMT9qP0H0FEBmpvobngcVQOx7x1loFRhAMIRwECE5E0Ax/YTnHr4RQPBdwM79qBJAsxvsd7VPEkD6s2XtI8QTQPoBQIpW6BNA89nnXqkGE0D2buyFr6AUQFum04FsWBFAUdT2RCxeE0BhnhNMdusTQDgdtVaqqBdAN/L+vPxeFUDyBdmCI0IUQGQbBR3bIBFAMcHxavpNFUBpKNYFDMYUQHIY1XummRVAcpH4jBx/EkC1fuwHg/wRQPPsl0IWpBRAEq806yyqFkA01hl+HJgWQP2p9buiPhRAkcrPOpLoFkAUx7AxUKMWQLHhe4v+TBRA23rEe3wCFkBhJJQzm3UXQPNEIjsmmRFAPOyz6PZeFEB4yT6docMVQH24IGLm/RJAY/BvTypdEUATF0p5JhIVQDS2WIPw0xFAdfP5DMYIF0Dwo/iuWyoTQKJk9JwzuxZA9lvN/RymE0Bx3w7kfsASQDyGUreTlhNA+0JFGwrAIEBZD3+JHG0VQHXqXazS4RVAZfpsg5BjE0Cyy4A7AXYVQIDwo1nj+g9A/wQtHHkgE0AyuVi2dcwVQANlqQ/5QRRAkfXPWVckEkB9jXDbPswTQJW2J2ScGBVA8MGgGzYHGEC450Zkf2IUQHKSmtYHTxdA9yn6GjnQFUAwRXJT0BgVQN37E/Mk7xNAY+21whUhFEDfm9idMIkYQNqBNasmaBVAdVpqD7x9FUDZoOyw5k0aQDrydF2UMRBAWhMkAd+JEkDxmrTbc+kWQDTxEgEs7hJAWQl/VeQoFkB4ZbcgrdUYQPZ5PTlQxxVANC0fBDHiF0DwFmzbL9UZQFE4LOFMoBdAeu89MCSdFkB5wQkez00TQLBBWj4smhJAND30IIUlE0ChIXRaPP0VQLsKGUEuBBJAPY5/SL+RFEDYN8aCCLwSQD/eNFp6wRVAMINUR4JtFECyPhsM8W0TQDGygVNDcBVA89EdMYE5E0BmxIMZLA0ZQDhI0zqk3BlApcOZdSiwGUC7AV16qwoSQAD7xeIYUQ5AFdWQKfW5EUBpPt5LxT0TQDHW9IK6qxlA+bBNE23bFUAlkFqcrKsVQFZJ5kV+MxVA/wMYvYtGEUATKaOSQ9YVQLkNi/rsyBBANwH+regNEUAjJRd2/gEYQP4FWCDlSRNANTLzaAhFE0CSYpx+sU4VQHkvHHT7uxZAYna8Z4R4EkC4PVu9DkQUQJrK90gL0xJAE7T5kcV1EkCwjTnh3kATQHkzexnazhRAuHfksN4JFUBRSVGLrwkVQLIzB8wx/BJAFZ9nvNDZEkBb3LkBnUwSQOCd54LcSRVAGgxORSbEGEDEMitPQiMRQLX0OS0oaRJA+IRTXac7EkDseMvGDR4UQJzSTwuTMxFAM/RVgXgaEkBpaZNAZI4TQPC3FrES9RlAsLiUjE04EUDam/SPv7YZQPksfvjllxdAuWpmPINhHUA9aIzEppAVQHHB8WSrqxlA8/jJVZubFEA9kpeGtKsTQJEQnCBVXhVAEiZEB8XrEkDzF7FN8M8aQLsWWw4NPxNAMPD2Xz9qFECZKZ9JtUAZQDPahjZfyhVAk7b6AV+bEUB5ahnW/eESQDHYpYQRdhFAPyMctEjJF0BaNEz5HXkTQDYt1ZXvNhRAHEijWEFJE0AhyYZ/W1EUQLsx0I6EORNAOoU3CtxTFEDyYGZbcKkXQHLVwHarYxJA77yGcALjD0AmmHqc/KcUQHBarTOSaRZA8FjIgDUyEkBwc1G3cFwXQHD2IcTrnBZAfS2bYBjVE0D597Pguc4YQBf8tpIPdRdAsBqxDPPUF0B1L+KxqN4RQDyDN7YJqRdA8kNfJWd1EUBRrpNXUVoYQPPUWryq2BhA9y4/Xrz9FEDw0ITsknwUQOlecgpJDRNAu2iVcm98EED4+067s+wWQLuNSmMBdhVAqJ0u9GIOEkCS+wOWt0IWQBLiX4KQYxRA8XTQPXs/FUD6/1cxo7MRQLohcUKhnxVAsZQgSvtlHUCyHywaEJATQL6q31/2IxdAOVsCg2c8F0DSWHkfJJ4XQPPi6gGHfhVA9Q1SnC0OFkB+BXGJtNESQFVC+h9A0xVAc4cJ0EQ3FEAzz8060YcUQF9t5bA39hRAf4tFnLgQEkCwkWVBO4MQQDkpyVaDHxZAYJU6UebxFUBR94tAMYASQOA0B8uy4xRAE5rYLacdFEDwK18dvpQdQOIPaFuOqxJAGLoc1ww0E0Awhvcm+McUQDTUNBBrtxRAUw63BGyvFkDRIo4WfUQSQNlqpGbVyhRA1t0j1Nx6FUA0ElGrqtEbQDWUQl+MSBRAtPSiKAHbFkDRc0EJQ3AVQLF2FTwOfxRAs+d7JzooGEA0ql4eHbMUQLKNqBoYLhRAKe9+Q+WgFUCYTESxh3UYQBVzSGpOwRZAMM8Mu2OfEUDw0T4Tx/IRQP0kQg8TjBJAtAYsju/+FEC4SX2kzpcVQJN+xnBqRBRA8vxuAxiDE0ARCyTETUEXQLNMwlqEEhNAOvc1ZEaHFEB0W+r+7S4RQHzmAIWpWBVANH1nKU9XF0BBnwiIdG4VQDaOFJwZfRNA9+SiCWGNF0D4qOZ3rFcQQDtpNpJjBRpA8Wel1Z+eE0AYsvGxNhsUQPMdBhyPuRFAuDJV8tiGGUBK6KUdZBcXQBW9j4E6WBJAsZAp1eNoFUDVFsg4rs8QQFH2bZ2AqxNA8QWPBzUHFEBRWNBwTqgUQPO/Hhdb+hJAsl2dHw7gEUD0pRd1sd0TQJhpzG271hNAmsjX0600G0BYrYi7n9wTQPK4JbufChRA+ORIqFY5G0B1BKIpIccWQLd8N1v2ThJAlYS+h3H9FEDwKAsar9AVQDJe5+YdGBdANs33I9aYDUDw8nERT5MTQFtEHKu/yxRAYhuseah6FkC5h+/TKtQWQDfY6qiHWxRA1AI3d4NrE0Dx6UDQlLEUQFLWCYB9iBRAWeMSY2/fFUBxuGu98JkRQH0eGGM+pBVAFX/av2fQFEBqWHNO8FMVQLUu5K0DLBZAJAYBt6Q3FECxd8HJIjQTQPhatk+1rBJAfZDhsHrnFUA2CqYEhbgTQDD1C39zbBRAs5iGduKqFECA4qqCp/wTQKEWDAgdCxVAvyoVlKjbE0D0+MT5KD8TQONSn8WHmhVAcdLt06LyH0B1GXhJL/YbQDIwAlNCOBVA+RU/rhn3FkDx7p2dj/oUQLOy+O9hoxRAXXAIAHbNFkBwl4Ch4dsTQMDXrjCHsBVA54Px3sv8EUAzRp3VlXcXQHUlubhSNBdA0az3hw5fEkC1hgNEJYcWQLkaNROkZRZAv2wAmlmrFUDyFxLcy9wRQBIHHy15DRZAHK340CVDFECaXQpKTEgUQDJq6721+hJAkhX6wzxhEkA2dkT33wsRQDlVShLXtxNANmeHI17cFUBxakBFzc4XQBOnv+MbmxNAM4N3mGB+FUDbVONYKPoVQEPE+/vjehVAMeHnBPk9FUB5O94fkAoaQNPO4btPBRNAOTlvVbzFE0Dlhc8xJ98SQGr7H6AFoA9ANHdMLeXLFkCy9NLuEL0WQPlNjHlRPhZAeJEPpCjWE0CtsdiJujoUQDEfPgFDBRJAm0n5Xky6EED5TICG950TQDecYNmSdBRAcX+EkUrIFEBhvo/mC8ITQP1lr8tPiRVAWIXZ3pXgF0D1x9jsHh4SQJ0k7uQIhxRAsKPDd6lAFkDwWqwKn6wUQHEBy7MZ4RBAMRmvdynTGECTg2MXHX8ZQJR98vDeIRZAUYtC95kvFUC1taF8iDQSQP/HWlkA3BdAYrrCHSV7FUClgX0LAxwUQJJfEh8schVAE0w0Bpg8E0C0X7FpHqMUQJou6hrFehNANsEodZCNE0C+36ygG9EUQLohTM5w0xJAMTfulp85F0Aw3TrRA30UQBQdFmURSBVA9AS92KSBFEAREbYU0JQQQOlt33cT2BNAOJmLsyghFEAwZVe+S0QTQLB04VBU1hZA8NXPNPRYEEC0ZiTwo/0WQJNzk1LKRRdAcUZEC5f7F0Cc5PWTsZ8TQLUXZDwpsBRAsrRv8h0FFUAuAt0H7iUUQBFuqcEhCxZA5AFjoDUKFUCxBP9TtPgTQLR1N1qTNBVAA8LVk8r9EkAzjJ3TFl0WQJjAt0MKZBNA8x8n6a1JEEB+ZfR6DZcVQHHHzN3cCRZAckeJfgGdF0B0evmRNMIUQPpPLAK1dhhAeaOP0+u5GECr8Xa+Bt0TQCLvQPg7pRFAu66kI0atFECt1ih036oUQOlK22Yu8RNAsV0fLnMnEkA02ZtFv0gQQLmDLbPPzxBA9lY+WO2CEEBzu0IwmOoXQBO2IFqouRRA/qHdGAKpFkCwDKVFTlQTQDI+5Vef1BZAFNvaYfHREEBykRRGoX4VQHUiZ7xNUhhAXJtAXnsFFUASYwhvX9cTQPIp+0/Q6xZAsM5KscBdGkB4vBcg1eAUQPDKtM7jEBpAVwbkSyqhFUAzlkF4cFcSQPHqt49ptBVANFxvABU9EkDXxb0F90IVQLDR2BBuhxNAdw4ptuANFUDwOrFKXH8RQLqFb41kQhZA9Wk8A6GMFkBlztgFyfcSQKLSmK85FRVAMcm1sKCUEkDhQYGlZDEVQHD/H7i88hdAI6PVQHTxFUB437nO69QUQJXPb0/uXxNA6/84l3/RFUAz4oikBbAUQDHP9t6vxxNA8PJF22uaFEABfS3z+8ARQBkNfpRFrBNAfrXNDWwvFUBgHlP7d2EUQAutDQIVdg9AdSFPa3XxFUB2b1g4fGYSQPZAgUoRMBJA/R9tmcVmFEB2PrcUm4QTQHEzzfoSXRNAN1vuJ0bNGUC5GOcLdUUWQDC8wqrG7BRAUq0h9rGsGUAzZZNqZEEZQPOpyiksKRNA1bVj/0LSFECA6mj96DUSQPnby0wPsRRAuaVCgAmyEkASVILvOJcYQP6cIBTzhxNA4tQHHxINF0DzI/i7wQIWQHfv3gf0pRNAeatjTi4qF0B5GYiIrigZQDzbvn97bBNA92vprWVUFUDjx5NP6KkTQGddG8ja6BBAUU+nkw91F0Cxvkb9TOsVQP1pUQPWJhRAORiNzPIrFUBlD3bFBoETQPqyp7V7ZxZAvGEO5glDFUDwqSu0ITkTQHaC03a4WxlAsHN+GHUWEUC7DTD24FIXQHS0fOcSyBRA4Rxsm5l5FUD8m146MhMTQLRVd9WtbRVA2gR1vWjsFUBTeb6NbrkSQPGZW24eIxRA8VHtO013GUDyfbtZ6YESQDEueJuCxRhAsMrfHzMTFUAHTIN7W0gOQPh77Ie/hRJAsELLbaRtFkAqOYElIgEVQH3Gj2t+tBNANCV7YFLuE0AAbzoRQ3kSQCkO+pL+yhdAk4/XnCBLE0DzmQWrKIgWQP3+5vbnmRNAsFNp7SeYE0CzvVWY+bkVQHS8M6vucBNAcasWFNz5EUBhNAXjtrUTQKn0NepQ1hNAkWdVi9gOFEDxQmHsDosWQPSAwBL7/hNA/gO7WbSME0C39UMEqzUTQOo9CbJXvxRAWu9mMP4fE0B4KZEcpc0VQBWzHpfASRhAo0IZRaapFUAxgOeGfUsXQBZhjcbJChVAMZFJPvgZFkAeh7gPAfUTQFEkFLJOiBJANc2G4wtSE0AzAOeHFIoVQMEXK41rsxNAd6EnD2sfEkCyHX6WA0ccQHHKPr6kgxVAgCANL+GLE0A4++D9zSYSQLCEvPw8OhBAcNpAOp5SE0A4kgK2gMsRQO64Hmhpug5AV3JASZQBGkBTk1LTExUVQKV6MvQjABRA1G7KyfTEEUDy5y6qCwMXQKSBH2feZxhAAUfWmKRCF0C0ziYqpOMSQH0idwETtBNAlRaHN433EUA1me67pwgTQPispwJpxRJANJsmyJTKFEDgeg3XJPwSQOHDMJqYbhNA4a9TOE0EFkA2eDYqJX8TQB3Tg0aXMBhAOnN96wxSE0BiRYLcj6IXQKHx2phbcRRAsvqbBrKQE0BUyGPQ1YASQDJKIegSMhNAMCcObO5wEkAiDGBCzRATQH7kvtxNjxNAuAiX3vyJE0ClUSZ3OhYPQPrkjlvWvBRAtSiJcAwMF0BTYmKm58cXQDH0bT/fcBNA+slyHDkoEkB5fOnKi6IRQHHLfPgYxBNAtuOAXZejFED4p8oWBXMXQHC2DLhFkBlAYa0rkcAWEkCyF9pxnRgTQJ39tE534RNAcBSYp6kAGUCo2zS+CRMXQDH4v3jN4RJAuWYigC4PE0A0SPGGWHMVQNdCIA08/RNAPaVNyRxYEkC+kDWo3Y0TQH8LENfxzhFAPmmlnzy+F0DgUOhaIukVQEnkyiIgYBVAMfU6PGoCFUA4pw2sHqcXQMF9E7oXXRVAsKSyzXkeFECqIjMlWLUVQLceezw+rhVAUneAP1QbFED7UVX167MTQOEU/lDrShlAOSyHX0u2FEBwIDbHZCoTQP5czY8LlxhAuTOLwOIMGEBxzdZGJzwSQDnyb2lz1xZAvecM/4UQFUDR1/Z2p74VQLF9Fih3wRNAl0EvNbNcE0Czio5nhLERQHCcV2UrRhVAWhn68JtBFkCVtypzTzgUQDG6QAy4nBFA8OXnlKPnEUCkJk+z0aYUQDhCiqLSjRFAW77h//LcE0BxkrPbsQwSQHFgMnmk3xFA4DcpgePDEkB1UpOKKikWQDGZ3QJxOBVAOLzXVof4E0C7ppYuvE4SQBvf9OCmkhJA9H5W9TBlFEByUdmDq5gUQCWgt0CxWRBAcxKAwq7BFUC4gwUnY6MWQG0n5KX4CBVAuSB/2HniFUAi5ygbwugUQLemMuGg2xJAOLKNZ7BSE0BDh7gATH0SQNNC4+CV+BZAMbvfaELNE0D0KYIio4MXQLveqRS7yBNA8zWSDRr5E0C6hU4mzCUUQDXjGwtM6RRAuLKL4pWiEEDRFvFeQaIQQNRuUtMcNxhAsfWLu9GME0A3EE18AaQWQHLPrDBPpBJAOUkhUqEuFEB7Lxhx4hMVQH6deFY8qxNA05wnI/k3FEBwualU9nUTQFSdydPTZhZAawUK/qfbEkB7BTUTXRcXQPjUPCCnoRFAtObGSYccEUDywU+aK4QWQHEj7rcjuRNAMAOCt+1OFEC5sCr6VBYUQHCsbncfWhRA8ALgARKLFkAVN3I6zAoWQJsHeElH7xJAcUbBimDjE0Ayb7YIMfUQQDz8aw+RIhRA60gRVfl7FEAyATPRTQsUQLqJYZPtSRRAdUwulLHzFEA+sij4RjQYQLC4khqx+hZA8ydtsDmIE0B/QslSfuAQQHj+t7P8sRVAOY/QjYT+GEA0hrti7qoSQDN6sMp75xVAGR7siP82E0BUxhahlgkTQFI6QWZCLRlA4CfiJzxvGUA5iAqbc6MRQP56SDGZnBZAMdAAr4wRF0B868C28CUTQFbfIoptIRNAMoX9A3c8E0CxoCItYfASQFHN6CVnkhRAepOO+DW+F0A/6ia1U8kTQMHU9XdQNRVAMlHUPKQBF0A4zDr+0hoRQEwHGQnYMhZANvpTzh/dFkDBDjzkBRkTQPwKmESyAxFA9aYZVTExE0Cw1kre6R4UQFQ+YMROjhZAXjxFVndEF0B+k0Z4xXoRQNE8WhY+EhNAeuc+q9K5E0D4P+dON2YTQP4AowmMUxVA86xfplA5GED+9sEiZpQTQPNAFHHVfhNAMHC4nbqNE0ARXxgOOP0VQLCx6U1VehBAAPLCg2csFkDxnVzevQIVQCtAA0tUGhZAYrReVRgaFEBz0lA131cTQFhcfSa6PBVA8mguuIdPG0Bwb8HEIQwXQDipAmHbAhFA5S2FH61jFUA4ZTQhSq4SQBHOTwWelhlAEapKiKtSE0Dw1IwDS8ITQPhJzTdH1BdAOai85laVFkCbLqucv9wUQBgxrSTsoxRAeCfKVoC3F0D9XeCK76MWQFo47EXvThJAMGGJNEo2F0B3SAufl24UQMLGxfJXWBRAfJ+Y2rXfEUD2eqUV8T4WQDCLo0+93xhA5vphNdgCFkD9K7PYYowXQJsShu23YhVA2c3JEEumE0AwdM0dkKUTQHieAhwjmRRAWkOmiHShGUAjX0T2ra0SQDk7NBHa9RNA8uMGEC21E0DRRvEV094TQKKV5V94ARJANuHCUuMmFUBgA7yjWc8RQLT2PWuX9BZAGrwCSBxmE0BJ5oRTv+ATQHAdhZMDdhJAeq1XN6hgGEBwrlFnrHQRQOFGoub+RRZA9IQppX6IFkDijtf5y6QRQOnosjJZiRNAyMtUeU9RFkCig1ivq6wSQJc4diisZBVAcvspOR27GEAzGZPqqTEVQFgyZqJ18BNA0dVPQXKzE0C0hoG0p3UWQKP22MmGiRZAI8AdqZFDEUD40xVmIDkVQHUiX7ZebRNAs/ZtbC06FUDxwt8BhYMTQLo67tmH9RJA48O6mzQ7FEDxB0LPjr4UQLKjY68XBxRAuZ6j9qkQE0ATTNxF59oRQLUOgYhDIhhAspeeUvsrGED6xABQgP8TQFabfPBOkhRAtmTYzgB0EUD55Ja86scQQLNA+zH/nBVAqplwdyocFEARxsIsrlcQQD2FJAswnhZAayK8ECG5E0C7HfAGZI4TQDdpA8dPZRRAOOSCeAkGGEA8sfmGR8AWQPtWXoGQfxVAvPqxXfqoFUD5ahtokTcVQPUicWHbNRdA+tdg3voUGUCTkH0Vw8wWQBNQX5hgExJA+g8/9UvOFUAx3nkBju0QQDLVhp4NfxVAcceoNgwzF0DRcMAmwZcUQKlv3RKFZhdAvHHFwsdaG0CavA0F83QXQDBvDWUW7RRA2KnCPGe/EkC4y96aRkQVQLJTbDzCdhNA+b15XOo2F0C7foqH9OAVQGvG/MmLvhRAtN/MNL4NEkD62wNkPEATQMbcCLTZ+RZAE9eOkKlPFkBxQAGP1DsWQPErPTnF9hJA23esKTJYEUD16EkvJMkSQJaLntffMRZAGJIsPgn8EkB7Zm381gAWQMeYYypSXhVAdYBEU3nGEkCYROmLLnkXQHstfp9TbhRAp+HlpqsDFUA0+lopKvQUQLWU2BnrJRRAG4eQBmYeF0Dz3Ce9yfISQIcA/T8kkhNAcP9pIg3wFUAR4Tjstg8SQKKw+EOGJhJAeWy/v1hQFECj4eCHwnIWQL5jQKuRlhNAFdpp9zcxGkD20Xv/6uQZQHmjTm/xXBVAsI9TAZS6EkBRvPvJYNsaQPzwItYp8BZAcOEUPkRjF0B4sudKSyYUQBI9VoDO2hdAcT3Qwd/dE0CXFHPWuwcUQPl5owURDxRAWlaP1cnrEUDbJBDW8qQSQOCY9qTuFBdAF5uNqRN+G0CbTm3nb3gWQNnGyPXBmRdAc3KpDmYrEkAaUMRlTyQXQJj/8ykpkhVA8NztStV4FEBzo5n34rwUQPEztuvN0BlAtNQJgXZNFkDw13vUqisUQDLyu53DZBRAtJE+sgwiFUBWK5w+9vYXQDL/LDDMORRAmHanXw8QFUBXLQR8djYVQNug3XJLJBRA93AC54AmFUCYE05t8BYUQOFhoDrKkBdA6Qw3DkSTFkD7PMHjM+0UQJIbVdOsFxRA1TyISR61EkCxYcv2r8gSQHHqOqbiyBVAcy2sIig7FUCwOtjt0kIXQBFBvrvJyRRA8KFfHObCFED6u6bwC90SQKII3j2RPhNAkzEhY8L1FEC0Itf9cBwPQDMb2qjUHBRANag5v5NcF0CRLYRXXnAWQGCcL07TFRhAc/p2DxU4FECYW9eI9W4XQHjgr2JXNBRAdXG6KZfSDkAyp23TH78TQPAMczJ2zhVAdAFqbj8HGUC2uktuIQcUQFRihjKCOxZA80+kBt8hEkC0q1ObZiIVQNEhJ1l35BNAVvcl204zFUCTrwmvWKERQPhQm5k5VxJAPSXeVZ8WFEAzz/r0VYcUQLabJr7z1BdA02bQEZ5rE0BhllHHGHEUQHyT4LTTvxZAMBWP6XrtFkCxma7/yNsVQH09IYVn6BJA1BaFMUKsGUCS4MF6sw4VQLFsOZqLIBhAI3zR0mveFkCz7NAAwL0SQGQS9yDZeBJAeN+hjH/LFUA05SOawksYQPO3oO4HYRRAZGhVyItjE0C52vB3IJ4TQDXtG2xOsRZAMFXFl5IyGEDynwXruKIVQDo7ABAS3BJA85pjb6i3GUB0XY3xh5EVQOGdvkGfxhJA9vU3fPxxFECRFvFuRqQWQFEnHgKE5xJAuBDCuj2nE0Cd5saSelwVQHNVtnR18BlA+ClNX3lyF0A4o/AiD4wVQHYI1LNJ9RRAM+tNrMJYEkAyv6R7XpEYQNKwAERlChZAmhxc31LzGkCT38VGlmEVQPLqup74XxlA9TiqyZBLE0BX3YV93qwSQJTX1V8V3RRAo0289M78FEB82SEztCsWQBjPVfk3bBVAX3rM+Ri4FEA1UsOWplkSQHDwkMMLhRlAMVzheOLNFEB4Tmt2K/wRQDQSKgFiDhRAcNzG3i3TFkBxurdUnVgXQNHHb7+QcBhAOinRMKWyE0BgSJLSMxoVQLNRgPxi1RZAXdkQzW3AFEBUkX2v3fYVQPOgjDsdOhFARjdZ/pl2FkA2kqh1OegTQH12ULYggRZAuLgoT+poFkBx4BvDSR4WQGnTr16IHhNABNZU2gVeEkBc5GgrIB4TQHgTaCVfdhBAs/wgSE3PE0Dim+R9gBISQHdjyqDcoBRA8ufaeW9PF0CVBOsIs4sSQDT9YhAIJBdAMCO9+nbiFECXSbkX5XkeQPDJl9FbpxVA+CefETMDE0C3HbgEPgYTQJK0NqTqERNAIVLCBfAHEkA4GRlCwe4TQAGN24mTYxNA4DqgzL1MGUD1qdX6SW8XQGKjwX6AHBZAMzS+iaVIEkCyRhmTeGQTQLGU68BTIRRAwMcrH3hqFEC2h2y/ZK4VQPmHfU1CNRZAYm2hjO93GEA0DmqvTdgUQPDoiTtrhRJAkafauxEiFEC0PJut2yUVQHRKTtbGKhNAFGrMbYkPF0C+g5Os58oUQPVjRGHeyBFAkkMNN3eqE0B7pvvFGX8WQGP5fa9f5xRA8q0Gmx/sFEA6z+4g6xkUQNHmTNZD2BNAsL425GYbFUAwilzomywXQOKDpfMmkRlA8XL37pmgE0AXZXckFSQXQFSRLYvicBFAM0Vo76IkFEAqxvVDEQ4SQLZSpuFo8hNAGsH//kJWE0Bz5P5Iu3ITQPWfaLnS2BFAbscXJX66E0CymGCektAUQDTtGfL59xFA1Wr7JUWsEUCWAJtg+VEXQNSALFW4bxJA9ODbKpGhEEBSr6phS+8TQOCUHfPt1xFAM3nhkPn+EkAi17cyX8MUQKFlwtJbJBNAsadOOF3vFECbH0L2ou8SQJKXxULK0xRAtJYP2VFBGUBSjSqHsQ8XQNCxeTQEqw5AWlc79njnFUAMBYqV8skXQDU3fETFExFAcFwzASyaEkAS+yB5znkVQBhBLagkYBVA8yyj+J+MFkBYDlVCjl4WQECmw4arSxBA+ESEH9dyGkBziD7HfXsVQDvmupCCkBJAMNtY9MLCEECRlxW0+94UQMGBHAFMZRRAO2jicx1BE0B22QywmGwWQDq7IWaIphZA8jZCfFx+FUB1gG+FYRwWQOmTSp7GNRJAesI68zI3GUA6m2qGdo0RQNUxAP151hFA9ZJGVkmYFUBy55VAWH8SQNRRPD0IZRZAsOsm96IaE0D8i0cmkqIXQJitWtec8hNAurt1ZKLBEkBTt9yq9h4VQGC4z/9iJBRA80dCokahFECY2HBYCyoTQCJ8t8E1HRBAcPjDNOm/EUCZTJTfxxcRQLZqWkcQCBhAO1It1fLTFUA90FlosREVQLji7TzLDhNAUve8V+7SEkAYROUpMPgVQFFyDWy8BhdAPDH3Gm5zFUB3Y2nu424UQHCVt+syERVAsbiN1uFTFUAjRgw8oy4ZQPkW/lttBBdAmkG/ZN+tFUC6GkoNF/wTQLLC5KhEnRdAM8JMbBpEEkA=\"},\"shape\":[10000],\"dtype\":\"float64\",\"order\":\"little\"}],[\"b2*\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"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" const render_items = [{\"docid\":\"956e9b3c-991a-4a32-8241-87a6844d5d0c\",\"roots\":{\"p3294\":\"b838484f-24aa-4852-a898-0bc090b1cffd\"},\"root_ids\":[\"p3294\"]}];\n", " void root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " const timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " clearInterval(timer);\n", " embed_document(root);\n", " } else {\n", " attempts++;\n", " if (attempts > 100) {\n", " clearInterval(timer);\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p3294" } }, "output_type": "display_data" } ], "source": [ "# Package replicates in data frame for plotting\n", "df_res = pl.DataFrame(data=bs_reps, schema=[\"α1*\", \"b1*\", \"α2*\", \"b2*\", \"w*\"])\n", "\n", "p = bebi103.viz.corner(\n", " samples=df_res,#.loc[inds, :],\n", " parameters=[\"α1*\", \"b1*\", \"α2*\", \"b2*\", \"w*\"],\n", ")\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The corner plot of the confidence region shows that $\\alpha_1^*$ and $b_1^*$ are strongly correlated, as are $\\alpha_2^*$ and $b_2^*$. However, the MLEs of the parameters for the respective Negative Binomials are not correlated with each other.\n", "\n", "We note that because $w$ is always much smaller than 1/2 and unimodal, we are having problems with the label-switching nonidentifiability." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## A mixture model for all cells\n", "\n", "If we assume a Negative Binomial (non-mixture) model for the mRNA transcript counts, we can independently perform maximum likelihood estimates for the burst frequency and burst size for each gene. However, in the mixture model, we do need to take into account the fact that the mRNA counts for the respective genes are measured in the *same* cells. In our modeling, that is manifest in the parameter $w$, which specifies the relative fraction of cell types, being shared among all four genes. The generative PMF for a single set of observations $\\mathbf{n} = \\{n_\\mathrm{Rex1}, n_\\mathrm{Rest}, n_\\mathrm{Nanog}, n_\\mathrm{Prdm14}\\}$ is given by\n", "\n", "\\begin{align}\n", "f(\\mathbf{n};\\boldsymbol{\\alpha}, \\mathbf{b}, w) = w\\prod_j x_{1j} + (1-w)\\prod_j x_{2j},\n", "\\end{align}\n", "\n", "where \n", "\n", "\\begin{align}\n", "x_{ij} = \\frac{(n + \\alpha_{ij} - 1)!}{n!\\,(\\alpha_{ij}-1)!}\\,\\left(\\frac{1}{1+b_{ij}}\\right)^{\\alpha_{ij}}\\left(\\frac{b_{ij}}{1+b_{ij}}\\right)^{n},\n", "\\end{align}\n", "\n", "where $i$ indexes the distribution of the mixture and $j$ indexes the gene. We can code up the log likelihood of this by modifying our original `log_like_mix()` function to take in arrays. " ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "def log_like_mix_all(alpha1, b1, alpha2, b2, w, n):\n", " \"\"\"Log-likelihood of a mixuture model for\n", " all genes. Here, `alpha1`, `b1`, `alpha2`, and `b2` are\n", " all length 4 arrays, and `n` is 279 by 4. The\n", " parameter `w`, however is a scalar, shared by all genes.\n", " \"\"\"\n", " # Fix nonidentifiability be enforcing values of w\n", " if w < 0 or w > 1.0:\n", " return -np.inf\n", "\n", " # Physical bounds on parameters\n", " if np.any(alpha1 < 0) or np.any(alpha2 < 0) or np.any(b1 < 0) or np.any(b2 < 0):\n", " return -np.inf\n", "\n", " # The sum is over genes\n", " logx1 = st.nbinom.logpmf(n, alpha1, 1 / (1 + b1)).sum(axis=1)\n", " logx2 = st.nbinom.logpmf(n, alpha2, 1 / (1 + b2)).sum(axis=1)\n", "\n", " # Multipliers for log-sum-exp\n", " lse_coeffs = np.tile([w, 1 - w], [len(n), 1]).transpose()\n", "\n", " # log-likelihood for each measurement\n", " log_likes = scipy.special.logsumexp(np.vstack([logx1, logx2]), axis=0, b=lse_coeffs)\n", "\n", " return np.sum(log_likes)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The initial guess for this model is also a bit more challenging. While we can see immediately from the Rex1 counts that the lower mRNA counts account for about 20% of the cells, this is not obvious in the others. We can, however label a \"pseudo cell type\" for each row of the data frame; if the Rex1 expression is below the percentile corresponding to our guess for the value of $w$, we consider this one part of the mixture, and if it is above, it is part of the other." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "def initial_guess_mix_all(df, w_guess):\n", " pseudo_cell_type = df[\"Rex1\"] < np.percentile(df[\"Rex1\"], 100*w_guess)\n", "\n", " guess = []\n", " \n", " for gene in df.schema:\n", " n = df[gene].to_numpy()\n", " n_low = n[pseudo_cell_type]\n", " n_high = n[~pseudo_cell_type]\n", " \n", " alpha1, b1 = mle_iid_nbinom(n_low)\n", " alpha2, b2 = mle_iid_nbinom(n_high)\n", " \n", " guess += [alpha1, b1, alpha2, b2]\n", " \n", " return guess + [w_guess]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For speed later when we use bootstrap methods to compute the confidence intervals, we will compute this initial guess once and use it over and over to save on the four optimizations that are necessary to compute the initial guess." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "params_0 = initial_guess_mix_all(df, 0.2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Also for speed, we should extract the counts from the data frame as a Numpy array." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "n = df.to_numpy()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we can write a function to perform the MLE. First, we need to write a function to compute the negative log likelihood, including unpacking the 17 parameters." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "def neg_log_like_all(params, n):\n", " \"\"\"\n", " Negative log-likelihood.\n", " \"\"\"\n", " n_genes = n.shape[1]\n", " alpha1 = params[:n_genes]\n", " b1 = params[n_genes:2*n_genes]\n", " alpha2 = params[2*n_genes:3*n_genes]\n", " b2 = params[3*n_genes:4*n_genes]\n", " w = params[-1]\n", " \n", " return -log_like_mix_all(alpha1, b1, alpha2, b2, w, n)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, we can perform the optimization. Because we will use bootstrapping in a moment to compute confidence intervals for the parameters, we will encapsulate the MLE calculation in a function." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "def mle_mix_all(n, params_0):\n", " \"\"\"Obtain MLE estimate for parameters for binary mixture \n", " of Negative Binomials.\"\"\"\n", " with warnings.catch_warnings():\n", " warnings.simplefilter(\"ignore\")\n", " \n", " res = scipy.optimize.minimize(\n", " fun=neg_log_like_all,\n", " x0=params_0,\n", " args=(n,),\n", " method='powell',\n", " tol=1e-6,\n", " )\n", "\n", " if res.success:\n", " return res.x\n", " else:\n", " raise RuntimeError('Convergence failed with message', res.message) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's do it!" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (5, 5)
Rex1RestNanogPrdm14parameter
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7.1827468.9772115.3928180.956715"alpha1"
24.6003799.60768321.077646.468837"b1"
1.1124933.563551.2093950.440802"alpha2"
45.00128213.73650818.1329251.665332"b2"
0.6965190.6965190.6965190.696519"w"
" ], "text/plain": [ "shape: (5, 5)\n", "┌───────────┬───────────┬───────────┬──────────┬───────────┐\n", "│ Rex1 ┆ Rest ┆ Nanog ┆ Prdm14 ┆ parameter │\n", "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ f64 ┆ f64 ┆ f64 ┆ f64 ┆ str │\n", "╞═══════════╪═══════════╪═══════════╪══════════╪═══════════╡\n", "│ 7.182746 ┆ 8.977211 ┆ 5.392818 ┆ 0.956715 ┆ alpha1 │\n", "│ 24.600379 ┆ 9.607683 ┆ 21.07764 ┆ 6.468837 ┆ b1 │\n", "│ 1.112493 ┆ 3.56355 ┆ 1.209395 ┆ 0.440802 ┆ alpha2 │\n", "│ 45.001282 ┆ 13.736508 ┆ 18.132925 ┆ 1.665332 ┆ b2 │\n", "│ 0.696519 ┆ 0.696519 ┆ 0.696519 ┆ 0.696519 ┆ w │\n", "└───────────┴───────────┴───────────┴──────────┴───────────┘" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mle = mle_mix_all(n, params_0)\n", "\n", "# Put in a data frame for ease of reference\n", "df_mle = pl.DataFrame(\n", " data=np.concatenate((mle, np.array([mle[-1]] * 3))).reshape(5, 4),\n", " schema=[(col, float) for col in df.schema],\n", ")\n", "df_mle = df_mle.with_columns(parameter=pl.Series([\"alpha1\", \"b1\", \"alpha2\", \"b2\", \"w\"]))\n", "\n", "# Take a look at the results\n", "df_mle" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The MLEs converged on $w \\approx 0.7$, which corresponds to $w \\approx 0.3$ from before (we encountered label switching in this optimization). We can do a quick graphical assessment of the model." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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" const render_items = [{\"docid\":\"6492b581-adee-406b-9e75-cafd92ad2dfb\",\"roots\":{\"p2416\":\"c56661b0-faa9-46e6-81f2-98a9efc87fd1\"},\"root_ids\":[\"p2416\"]}];\n", " void root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " const timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " clearInterval(timer);\n", " embed_document(root);\n", " } else {\n", " attempts++;\n", " if (attempts > 100) {\n", " clearInterval(timer);\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p2416" } }, "output_type": "display_data" } ], "source": [ "def plot_theor_cdf(gene, p):\n", " \"\"\"Add a theoretical CDF to plot\"\"\"\n", " n_theor = np.arange(0, df[gene].max() + 1)\n", " w, alpha1, alpha2, b1, b2 = [\n", " df_mle.filter(pl.col(\"parameter\") == param)[gene].item()\n", " for param in (\"w\", \"alpha1\", \"alpha2\", \"b1\", \"b2\")\n", " ]\n", " cdf_theor = w * st.nbinom.cdf(n_theor, alpha1, 1 / (1 + b1))\n", " cdf_theor += (1 - w) * st.nbinom.cdf(n_theor, alpha2, 1 / (1 + b2))\n", "\n", " # Weave together to make staircase for discrete distribution\n", " n_plot, cdf_plot = bebi103.viz.cdf_to_staircase(n_theor, cdf_theor)\n", "\n", " p.line(n_plot, cdf_plot, color=\"orange\", line_width=2)\n", "\n", " return p\n", "\n", "\n", "# Make a list of plots\n", "plots = [\n", " iqplot.ecdf(\n", " data=df,\n", " q=gene,\n", " frame_height=125,\n", " frame_width=250,\n", " conf_int=True,\n", " title=gene,\n", " )\n", " for gene in df.schema\n", "]\n", "\n", "# Add CDFs\n", "for i, gene in enumerate(df.schema):\n", " plots[i] = plot_theor_cdf(gene, plots[i])\n", "\n", "# Show them as a grid\n", "bokeh.io.show(bokeh.layouts.gridplot(plots, ncols=2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The mixture model seems to fit all four reasonably well, with the theoretical CDF parametrized by the MLE mostly falling within the 95% confidence interval of the ECDF. (We will explore other ways to visualize and assess models in later lessons.) However, we note that the Rex1 data do see some deviations on the tail of the distribution for small counts." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Confidence intervals for the mixture model for all genes\n", "\n", "We can attempt to compute confidence regions for the MLEs for this model for all four genes. We again start by writing a function to generate the data from the mixture model." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "def gen_mix_all(params, size, rng):\n", " \"\"\"Generate data for the mixture model.\"\"\"\n", " alpha1 = params[:4]\n", " b1 = params[4:8]\n", " alpha2 = params[8:12]\n", " b2 = params[12:16]\n", " w = params[-1]\n", " \n", " n = np.empty((size, 4))\n", " for i in range(size):\n", " low_cell_type = rng.uniform() < w\n", " \n", " if low_cell_type:\n", " n[i] = rng.negative_binomial(alpha1, 1 / (1 + b1))\n", " else:\n", " n[i] = rng.negative_binomial(alpha2, 1 / (1 + b2))\n", " \n", " return n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can now draw our bootstrap replicates. I will only draw a few replicates for now, though, and the reason will be clear when we see the result." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "ename": "RuntimeError", "evalue": "('Convergence failed with message', 'Maximum number of function evaluations has been exceeded.')", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mRemoteTraceback\u001b[0m Traceback (most recent call last)", "\u001b[0;31mRemoteTraceback\u001b[0m: \n\"\"\"\nTraceback (most recent call last):\n File \"/Users/bois/miniconda3/envs/bebi103_build/lib/python3.12/site-packages/multiprocess/pool.py\", line 125, in worker\n result = (True, func(*args, **kwds))\n ^^^^^^^^^^^^^^^^^^^\n File \"/Users/bois/miniconda3/envs/bebi103_build/lib/python3.12/site-packages/multiprocess/pool.py\", line 51, in starmapstar\n return list(itertools.starmap(args[0], args[1]))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/Users/bois/Dropbox/git/bebi103/bebi103/bootstrap.py\", line 559, in _draw_bs_reps_mle\n mle_fun(gen_fun(params, *gen_args, size=len(data), rng=rng), *mle_args)\n File \"/var/folders/8h/qwnxpqcx6vldhxr71n1582d00000gn/T/ipykernel_41358/3990052399.py\", line 18, in mle_mix_all\n raise RuntimeError('Convergence failed with message', res.message)\nRuntimeError: ('Convergence failed with message', 'Maximum number of function evaluations has been exceeded.')\n\"\"\"", "\nThe above exception was the direct cause of the following exception:\n", "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[25], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m bs_mle_reps \u001b[38;5;241m=\u001b[39m bebi103\u001b[38;5;241m.\u001b[39mbootstrap\u001b[38;5;241m.\u001b[39mdraw_bs_reps_mle(\n\u001b[1;32m 2\u001b[0m mle_mix_all,\n\u001b[1;32m 3\u001b[0m gen_mix_all,\n\u001b[1;32m 4\u001b[0m n,\n\u001b[1;32m 5\u001b[0m mle_args\u001b[38;5;241m=\u001b[39m(params_0,),\n\u001b[1;32m 6\u001b[0m gen_args\u001b[38;5;241m=\u001b[39m(),\n\u001b[1;32m 7\u001b[0m size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m100\u001b[39m,\n\u001b[1;32m 8\u001b[0m n_jobs\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m,\n\u001b[1;32m 9\u001b[0m )\n", "File \u001b[0;32m~/Dropbox/git/bebi103/bebi103/bootstrap.py:649\u001b[0m, in \u001b[0;36mdraw_bs_reps_mle\u001b[0;34m(mle_fun, gen_fun, data, mle_args, gen_args, size, n_jobs, progress_bar, rng)\u001b[0m\n\u001b[1;32m 643\u001b[0m arg_iterable \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m 644\u001b[0m (mle_fun, gen_fun, data, mle_args, gen_args, s, progress_bar, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 645\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m s \u001b[38;5;129;01min\u001b[39;00m sizes\n\u001b[1;32m 646\u001b[0m ]\n\u001b[1;32m 648\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m multiprocess\u001b[38;5;241m.\u001b[39mPool(n_jobs) \u001b[38;5;28;01mas\u001b[39;00m pool:\n\u001b[0;32m--> 649\u001b[0m result \u001b[38;5;241m=\u001b[39m pool\u001b[38;5;241m.\u001b[39mstarmap(_draw_bs_reps_mle, arg_iterable)\n\u001b[1;32m 651\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39mconcatenate(result)\n", "File \u001b[0;32m~/miniconda3/envs/bebi103_build/lib/python3.12/site-packages/multiprocess/pool.py:375\u001b[0m, in \u001b[0;36mPool.starmap\u001b[0;34m(self, func, iterable, chunksize)\u001b[0m\n\u001b[1;32m 369\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstarmap\u001b[39m(\u001b[38;5;28mself\u001b[39m, func, iterable, chunksize\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m 370\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m'''\u001b[39;00m\n\u001b[1;32m 371\u001b[0m \u001b[38;5;124;03m Like `map()` method but the elements of the `iterable` are expected to\u001b[39;00m\n\u001b[1;32m 372\u001b[0m \u001b[38;5;124;03m be iterables as well and will be unpacked as arguments. Hence\u001b[39;00m\n\u001b[1;32m 373\u001b[0m \u001b[38;5;124;03m `func` and (a, b) becomes func(a, b).\u001b[39;00m\n\u001b[1;32m 374\u001b[0m \u001b[38;5;124;03m '''\u001b[39;00m\n\u001b[0;32m--> 375\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_map_async(func, iterable, starmapstar, chunksize)\u001b[38;5;241m.\u001b[39mget()\n", "File \u001b[0;32m~/miniconda3/envs/bebi103_build/lib/python3.12/site-packages/multiprocess/pool.py:774\u001b[0m, in \u001b[0;36mApplyResult.get\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 772\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_value\n\u001b[1;32m 773\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 774\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_value\n", "File \u001b[0;32m~/miniconda3/envs/bebi103_build/lib/python3.12/site-packages/multiprocess/pool.py:125\u001b[0m, in \u001b[0;36mworker\u001b[0;34m()\u001b[0m\n\u001b[1;32m 123\u001b[0m job, i, func, args, kwds \u001b[38;5;241m=\u001b[39m task\n\u001b[1;32m 124\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 125\u001b[0m result \u001b[38;5;241m=\u001b[39m (\u001b[38;5;28;01mTrue\u001b[39;00m, func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds))\n\u001b[1;32m 126\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 127\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m wrap_exception \u001b[38;5;129;01mand\u001b[39;00m func \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _helper_reraises_exception:\n", "File \u001b[0;32m~/miniconda3/envs/bebi103_build/lib/python3.12/site-packages/multiprocess/pool.py:51\u001b[0m, in \u001b[0;36mstarmapstar\u001b[0;34m()\u001b[0m\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstarmapstar\u001b[39m(args):\n\u001b[0;32m---> 51\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mlist\u001b[39m(itertools\u001b[38;5;241m.\u001b[39mstarmap(args[\u001b[38;5;241m0\u001b[39m], args[\u001b[38;5;241m1\u001b[39m]))\n", "File \u001b[0;32m~/Dropbox/git/bebi103/bebi103/bootstrap.py:559\u001b[0m, in \u001b[0;36m_draw_bs_reps_mle\u001b[0;34m()\u001b[0m\n\u001b[1;32m 554\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 555\u001b[0m iterator \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mrange\u001b[39m(size)\n\u001b[1;32m 557\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray(\n\u001b[1;32m 558\u001b[0m [\n\u001b[0;32m--> 559\u001b[0m mle_fun(gen_fun(params, \u001b[38;5;241m*\u001b[39mgen_args, size\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mlen\u001b[39m(data), rng\u001b[38;5;241m=\u001b[39mrng), \u001b[38;5;241m*\u001b[39mmle_args)\n\u001b[1;32m 560\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m iterator\n\u001b[1;32m 561\u001b[0m ]\n\u001b[1;32m 562\u001b[0m )\n", "Cell \u001b[0;32mIn[21], line 18\u001b[0m, in \u001b[0;36mmle_mix_all\u001b[0;34m()\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m res\u001b[38;5;241m.\u001b[39mx\n\u001b[1;32m 17\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 18\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mConvergence failed with message\u001b[39m\u001b[38;5;124m'\u001b[39m, res\u001b[38;5;241m.\u001b[39mmessage)\n", "\u001b[0;31mRuntimeError\u001b[0m: ('Convergence failed with message', 'Maximum number of function evaluations has been exceeded.')" ] } ], "source": [ "bs_mle_reps = bebi103.bootstrap.draw_bs_reps_mle(\n", " mle_mix_all,\n", " gen_mix_all,\n", " n,\n", " mle_args=(params_0,),\n", " gen_args=(),\n", " size=100,\n", " n_jobs=3,\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We got a runtime error that the solver did not converge. This can happen; finding MLEs for a large number of parameters is very difficult and can often lead to this kind of failure. We will therefore not pursue confidence intervals for this more complicated mixture model.\n", "\n", "That said, given the difficulty in finding MLEs for complicated models, we can't be too sure that the single maximum likelihood estimate we got for the nineteen parameters of this model is even a good one. This should raise a reg flag for you. **MLEs are very difficult to obtain for high-dimensional models, and when they are obtained, it is very difficult to verify that they do, in fact, give the maximum likelihood estimate.**\n", "\n", "We will deal with complex models and ways of investigating the failure modes in finding parameter estimates next term. For now, we will proceed by considering only the single-gene case of Rex1." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The expectation-maximization algorithm\n", "\n", "I close this lesson by briefly mentioning that the [expectation-maximization (EM) algorithm](https://en.wikipedia.org/wiki/Expectation–maximization_algorithm) is a commonly used effective algorithm for performing maximum likelihood estimates for mixture models. It alleviates some (but by no means all) of the problems for finding MLEs of complex models. We will not discuss it, but you should be aware of it." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Computing environment" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Python implementation: CPython\n", "Python version : 3.12.3\n", "IPython version : 8.25.0\n", "\n", "numpy : 1.26.4\n", "polars : 1.1.0\n", "scipy : 1.13.1\n", "bokeh : 3.4.1\n", "iqplot : 0.3.7\n", "bebi103 : 0.1.21\n", "jupyterlab: 4.0.13\n", "\n" ] } ], "source": [ "%load_ext watermark\n", "%watermark -v -p numpy,polars,scipy,bokeh,iqplot,bebi103,jupyterlab" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 4 }