{ "cells": [ { "cell_type": "markdown", "id": "aeb5ab4c-49ba-4249-81d7-3b4c1371e5b7", "metadata": {}, "source": [ "# Get Yourself Connected: Making Networks in Arbor" ] }, { "cell_type": "markdown", "id": "f4598b43-ee8c-4e6e-b378-d78b03dc1597", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "Producing and studying biophysical single cell models is a research topic in its own, granting access to biological feature like dendritic computation, just to mention one feature.\n", "However, the brain is a large network of cells. So, this chapter will demonstrate how to build networks of detailled cells.\n", "\n", "We will build upon the recipe we made in `02` and show how to use inheritance to organise simulations.\n", "\n", "Let's start with the usual ceremony:" ] }, { "cell_type": "code", "execution_count": 1, "id": "bd499131-1724-45bb-80ca-e508a9145ab6", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [], "source": [ "# begin by importing Arbor\n", "import arbor as A\n", "# we will also get support to plot things\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import pandas as pd" ] }, { "cell_type": "markdown", "id": "57b27145-08c0-4ec5-ab73-8d3b56ff855a", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "And copy over our single cell recipe class from `02` and make some edits to the decor\n", "\n", "1. Remove current clamps from the `decor`\n", "2. Add a spike / threshold crossing detector\n", "3. Add an exponential synapse" ] }, { "cell_type": "code", "execution_count": 3, "id": "ae1c93c3-ee1d-417e-85e8-565636ce4218", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [], "source": [ "class single_cell_recipe(A.recipe):\n", "\n", " def __init__(self):\n", " A.recipe.__init__(self)\n", "\n", " def num_cells(self):\n", " return 1\n", "\n", " def cell_kind(self, gid):\n", " return A.cell_kind.cable\n", "\n", " def cell_description(self, gid):\n", " # morphology\n", " mrf = A.load_swc_neuron('Acker2008.swc')\n", " # labels\n", " lbl = A.label_dict()\n", " lbl.add_swc_tags()\n", " lbl['ctr'] = '(location 0 0.5)'\n", " # decor\n", " dec = A.decor()\n", " dec.paint('\"soma\"', A.density('hh'))\n", " dec.paint('\"dend\"', A.density('pas'))\n", " # EDITS 1, 2, 3\n", " dec.place('\"ctr\"', A.threshold_detector(-10), 'det')\n", " dec.place('\"ctr\"', A.synapse('expsyn'), 'syn')\n", " return A.cable_cell(mrf, dec, lbl)\n", "\n", " def global_properties(self, kind):\n", " return A.neuron_cable_properties()\n", "\n", " def probes(self, gid):\n", " return [A.cable_probe_membrane_voltage('\"ctr\"')]" ] }, { "cell_type": "markdown", "id": "0da4748f-24e6-4ef6-8dc8-6432b35647f2", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "Note how every item `place`d gets a label that can be used a address it later.\n", "\n", "Before we start building something large, let's make a convenient way to run simulations and plot the results" ] }, { "cell_type": "code", "execution_count": 72, "id": "c23206eb-b5b2-43e7-8b9e-5d271e17ebe6", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [], "source": [ "def run_network(rec, tfinal=1000, dt=0.05):\n", " sim = A.simulation(rec)\n", " # attach to first probe on each cell\n", " hdls = [sim.sample((gid, 0), A.regular_schedule(1)) for gid in range(rec.num_cells())]\n", " sim.run(tfinal=tfinal, dt=dt)\n", " fg, ax = plt.subplots()\n", " for ix, hdl in enumerate(hdls):\n", " for data, meta in sim.samples(hdl):\n", " ax.plot(data[:, 0], data[:, 1] + 5*ix, label=f\"{ix}@{str(meta)}\")\n", " ax.set_xlabel('Time $t/ms$')\n", " ax.set_ylabel('Potential $U_m/mV$') \n", " ax.set_xlim(0, tfinal)\n", " ax.legend(bbox_to_anchor=(1.4, 1.0))" ] }, { "cell_type": "markdown", "id": "00e094a3-0137-41bd-b141-ec527250c696", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "Note that we pass in a fully constructed recipe instance and use the interface method `num_cells` to iterate through all ids and attach a sampler to each cell, storing the resultant handles in a list.\n", "We then --- after executing the simulation --- traverse the list to plot the voltage traces in a waterfall diagramm. Let's try it:" ] }, { "cell_type": "code", "execution_count": 73, "id": "8bdebabd-f9a8-4564-b260-96bf29602a92", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "rec = single_cell_recipe()\n", "run_network(rec)" ] }, { "cell_type": "markdown", "id": "753e12ec-4ca7-4c29-8cc8-1e15d3342a9d", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "Ok, this works, but is predictably not terribly exciting. \n", "Let's add an input by providing spikes to the synapse. \n", "This requires using an `event_generator` to be attached to the cell using a new callback.\n", "We simply re-use the cell by inheriting from the previous recipe:" ] }, { "cell_type": "code", "execution_count": 74, "id": "fdbbc357-b70f-4bc0-8b85-e45966451ea9", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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AlaEEcThxdY+A3+EEv5MFfgMAEAQAFIRl45MFficL/AYAIAiASObzxkMjDuB3ssDvZBEXvwGgMAQBAB7riEN4wO9kgd8AALkQBFQZUkhDOnzvbDEhsAG/kwV+JwvSsQDCAUEARAL/9whcpKoJficL/E4WxAAA4YAgACKB72sGF6nqgt/JAr+TBYcfIBwQBED0JvV5uIJzkbIDv5MFfieLuPgNAIUhCKgy1JUOz4WixoMeftuB38kCv5MFN/4A4YAgoMrUMJUslGUD651NHMRvG/A7WeB3siAEAAgHBAEQCbzUq87SYOJgdcHvZIHfyYKBAIBwQBAAweL5Yu5OxINGHMDvZIHfySIufgNAQQgCqkzcckhd9bD56bnbquFKDb+r226+StNXwYLf1W03X6Xpq2DB7+q2CwDlQRAAkcB7ugDXqKqC38kCv5MFxx8gHBAEADSSfV2ipyr+4HeywG8AgFwIAiy489m3q/0TIoOXHj0PF3B6quzA72SB38kiLn4DQGEIAiyY9MgSZ23HLYc0PtVD3IDfduB3ssDvZEEQBhAOCAIgEvjpHcyaOMhVqqrgd7LA72RB7z9AOCAIgEjgZ1jarx4UB7+TBX4nC44/QDggCIBA8VLojwtIaMDvZIHfyQK/AeINQUDVIYk0jBcjdxcm/LYBv5MFficL7vsBwgFBAEQCHzm82Xmq5KxWF/xOFvidLJiTARAOCAIgEni5ZLCYUGjA72SB38mCww8QDggCIHo9ep4nEUJx8DtZ4HeyiIvfAFAYggCIBP6rh3Blqib4nSzwO1lw+AHCAUGAJa4uGiwuYwmLCSUL/E4W+J0sCAIAQgFBgCX0XCRgMaHsiYP4XVXwO1ngd7JgYjZAOCAIsIRTVohK/XnQwHE78DtZ4HeyiI/fAFAIggBLyCFNQM4w1UNCA34nC/xOFhx/gHBAEGCJsxxSR+3GDd89UvhdXfA7WeB3siAGAAgHBAGW0HORhFJ15AyHBfxOFvidLBhZBwgHBAGW1HPSCtGwvt9JhFAc/E4W+J0s4uI3ABSGICABxKFsnY+h/Nw64hJZ8LsCDfyuKvhtD34DQKKDgGuvvVYOPfRQadeunXTu3Lngd5YuXSrHHXec+c4OO+wgF110kWzevLliTVcXjTic0H2Q8nyXgN/VBb+TBX4nCy9+A0Cz1EoE2bhxo5x00kkydOhQ+eMf/9jk8y1btpgAoGfPnvLMM8/IBx98IGeccYbU1dXJddddV5Emw8fVJafGtyMvfGiAHfidLPA7WeAFQDiI5EjAlVdeKRdeeKHss88+BT+fMWOGvPrqq/KXv/xF9t9/fznmmGPk6quvlt///vcmgKiEKA8fx67Kh+dyglAc/E4W+J0s4uI3AMQoCGiOOXPmmAChR48emfeGDx8ua9eulUWLFhX9uw0bNpjvZD/SRPk8FYsR6uyhfFcSUTY5C/y2lMDv8IDf1uA3AARFLIOA5cuX5wQASnpbPyvGpEmTpFOnTplHnz59nFcwqInHKd05Pib1+VhMCL/twO9kgd/JIi6TtAGiTmiCgHHjxklNTU3Jx+LFi53+hvHjx8uaNWsyj2XLlmU+q6dUWlXJuYA7yxl2r5Gjh99Fwe9kgd/JwoffABChicFjx46VkSNHlvzOgAEDrNrSCcHPP/98znsrVqzIfFaM1q1bm0dBPOWpUl0iOTnD+G0HficL/E4WxEoA1SM0QUD37t3NIwi0apCWEV25cqUpD6rMnDlTOnbsKIMGDaqoTS89R47a1VEUb2daRzq51SQ8rCjqSCNHz1G7+G2pgd/lg9/2eo7axW8AiF0QUA66BsCqVavMs5YDnTt3rnl/1113lfbt28uwYcPMzf7pp58ukydPNvMALr30Uhk9enTxnv5m8FFXuuEiRddR83WlPaQLuJoDgt9W4HeywO9k4cNvAIhpEDBx4kT505/+lNkePHiweZ49e7YceeSR0rJlS3nooYfkvPPOM6MC2223nYwYMUKuuuqq8PXqZL12Ne8gDpehlIfjlH0t8uEFfhcHvyvTiCr4XZlGVPHhNwDENAi44447zKMU/fr1k4cffjhSk7yYIGU5lO/Mi9ypg67B7+Lgd7LA72Thx28AiEx1oLDjpzqQRJ5UXDTw2wr8DpeGa/A7XBquiYvfAFAYgoAq9+qYSV6OiUOFCh81vnPL1rkBv+3A73I0JPLgdzkaEnl8+A0AzUMQYAs9R6HBS7IAfocG/E4W+J0sOEwA1YMgIFTDopwO7XqOUpHVyNHD76Lgd7LA72Th2wsAKAxBgCX0HCVnH+KUl+yaOOyDgt/J2QcFv5OzDwBQHIKAJCwWFoOicjmLy6Siq5Gr5wb8Do9Grp4b8Ds8Grl6bsBvAAgKgoBQjQRE/2zoKljKndQXXY1cPfwu2i5+h5Ioe4Hf5RMXLwCgMAQBltR7ySGFak7qy2k2wj2FcQC/kwV+Jwvfk7QBoDAEAZYwJ8COKA+ze9fAbzsN9xL4bQl+l6GB33Ya7iUAoAgEAWHCXRJpzFaYjK5GrqCjdvE7NBq5go7axe/QaOQKOmoXvwEgIAgCLHF1ospe+IXcSMvhYy+TtN1o4Lcd+J0s8DtZ+PYbAApDEGCJn4lkziUii/cVRUn/qir4nSzwO1mwYjBAOCAIsITcSDvickKPcraAT/A7XBquwe9wabgmLn4DQGEIAsJUHciRRgxSSHMuqc5WFPWgkaOH3yXAb1vw21YBv8ODXy8AoDAEAZbQc5SwdAE3Erl6HjSiCn4nC/xOFqQDAYQDggBL4pKnGo+JZI40PIjgtx34nSzwO1n48BsAmocgwJroVqzwSSo28zPw2wb8DpeGa/A7XBquiYvfAFAYggBLolxXOrtsXVTxscx8Tu8UflcV/LYHvy01iug5A7+r6jcANA9BgCXuhqhTzjXiQO6kvpgsWORGIhbgd7LA72Thw28AaB6CAEucXTQ8aMQBH5P6vOQlZ7/G76Lgd7LA72The5I2ABSGIKDKJULjNizqpdxbhMv74XdFIh4k8NsG/G6u3azX+G0r4l4DAApCEGBJlM+FNTGoLO2l58hz7xR+Fwe/7cFvWxEPGtly+F0URgIAwgFBgCXuJquRQxqanGHfGm4kYgF+Jwv8ThbMCQAIBwQBoVongLNhVauH5DTrIV0Av4uC38kCv5NF3NKmAKIKQUCVYSJZslKz8Lt88DtZ4Hey4DgBVA+CgAScqOJQVzqbKFcP8QF+l98ufocH/C4NfgNAUBAEhKk6EGfDqh6nuGjEgbh4gd/J8gK/7eA4AYQDggBL3J2nsieSRfNs6CP3NXfCnY9J2u77I/G7hAZ+hwb8Lk/FvYZb4uI3ADQPQUCY6kpzLrQjyjnD+F0++J0s8DtZcJwAqgZBQIjOU640XKeQeh9mj0ntavy21HAjgd+W4HeFeo7axW8ACAqCAEsoEVoc3xdUZ6MyPjTwu2wN/K4u+F2GBn6XrRHV4wQQBwgCrHGfp1rv6FxY47ichJcc0pT745R9BfexmBB+22ngd2nw21qk0MtgJfA7PH4DQLMQBFji6kTlYwGbuOGljniEFyyKG/idLPA7WTAQAFA9CAISsLiM8xzSnNepeGjgd1HwO1wa+F2BBn7H3m8AaB6CgFCVTYsmvlf4jEtlD/y208Dv6oLfFepJNImL3wAQ0yDg7bffllGjRkn//v2lbdu2sssuu8jll18uGzduzPne/Pnz5fDDD5c2bdpInz59ZPLkyRVrekhTjezJ0E9Pjt88VfwuDn6Xo1H4dZTA73I0Cr+OEnHxGwCap1YiyOLFi6W+vl5uueUW2XXXXWXhwoVyzjnnyGeffSY33nij+c7atWtl2LBhcvTRR8vUqVNlwYIFctZZZ0nnzp3l3HPPLVvTx0SyqA6L+u858pEu4H4iOH7baeB3dcHvcjTwu1wNqgMBVI9IBgHf+MY3zCPNgAEDZMmSJXLzzTdngoA777zTjAzcfvvt0qpVK9lrr71k7ty5MmXKlMqCAFcn9Bj0HGUTl2F2Zxr4Xb6Gewn8tgS/7RvGb0sN9xIAEKd0oEKsWbNGtt9++8z2nDlz5IgjjjABQJrhw4ebYOGTTz4p2MaGDRvMCEL2I4Pn3pFIzSTzgJdJfbmz1ZyD38XB7zLAbzsN/E6U3wCQkCDg9ddfl9/+9rfyX//1X5n3li9fLj169Mj5XnpbPyvEpEmTpFOnTpmHziNwXiI053U0z4beh48jXLECv8vXiLIX+F2+RpS9wO/yNaJ6nADiQKiCgHHjxpmFUEo9dD5ANu+9955JDTrppJPMvIBtYfz48WZEIf1YtmyZh7rSWTmkET0X+jiJ+zhOcdFwDX6HS8M1+B0uDdfExW8AiNicgLFjx8rIkSNLfkfz/9O8//778tWvflUOPfRQufXWW3O+17NnT1mxYkXOe+lt/awQrVu3No9C+KgrHQcinc/rQQO/k6WB38nSwO9wagBABIKA7t27m4cNOgKgAcCQIUNk2rRp0qJF7qDG0KFDZcKECbJp0yapq6sz782cOVMGDhwoXbp0CefJMKqLy3iePOZ7uDpqGvhdgV6ENfC7Ar0Ia+A3AMQyHcgWDQCOPPJI6du3r6kG9OGHH5o8/+xc/1NOOcVMCtb1BBYtWiTTp0+Xm266ScaMGVORprOScp5zI13sh/8AKbpe4LelBn5XqIffNhr4XaLNwFusjt8AELGRAFu0R18nA+ujd+/eBU+KOrF3xowZMnr0aDNa0K1bN5k4cWJF5UFNu4H88tLt+uqdqqlxmd/pasKdh3xeLxpZr/G7uAZ+V6aH31XWyHqN31X1AgBiGgTovIHm5g4o++67rzz11FOBaLobCcg6GTpRyNOLePvVGK4OtF38Ll8Dv+31It6+0cBve72It280CAIAqkYk04GqgZ9eHTciWlXJpYaXc7jnoXwfhuO3nQh+lwa/LSXwO1F+A0DAQUCxRbaSgJfhYzcSRfUCazMmE8l8eIHflhoe9PDbsk38DpVGMb3A2oyJ3wAQcBCw++67y9SpU531cISZlI8eEU85pME36qDNfImcniMPGh7uEvC7hAR+VyaH33Ya+F2iUQdtVsFvAAg4CNDKOhdffLEMHjw4sFz7qOBjgpSP06HzodeoXviaaOC3pYBz8LtSPScCzsHvSvWcCDgngX2KANEMAnRF3SVLlpggQGv0n3zyyaZcZxKI8gSp7OoRLjS8lMLLribhKmc4R8M9+G2ngd+lwe9KNNyD33YazAkAiNDE4F69epnFuZ577jl59913zeJb11xzjWzYsEHijLM81RgMi3of9vbhBX4XBb8r1JBogt8Vakg0iYvfAOCwOpDW3teUoD/+8Y/mseeee8p9990nccXLYmERHXr1PQEuqhPuTLv4XbYGflemF1ibwTdZUgO/K9MLrM3gmyypQQwAEOESoT/4wQ9k8eLFZmXeESNGyNe//nWJIykfw6I+ytY5PuX6GWb3cJy8LJKD31Ya+F2Rnpv23YPflem5ad89SSw0AhD5xcI2btxobv4XLlyYebRt21ZmzZolcSTKC9jUuO458nzRTsXkYoTfdhr4XRr8Ll/DB/htp0EIABCRIODKK6/M3PC/8cYbsnnzZunUqZPsvffeZnXeY4891jzHER8L2EQ10PA+fByXnGH8ttKIshf4Xb5GlL3A7/I1GAgAiEgQcPfdd8s+++wjZ5xxhnnWG/6+fftKEvCzgE00h8FzL3zuD5S71Kzs16nIauTo4beNBH6XbNNt+w0NF3zpSgK/S7bptv2Ghgu+BIAwBwE6ApBUfEwk81KTOeLt+xuu9tAufttp4Le9XsTbNxr4ba8X8faNBkMBANGaE7B27VpTJnT58uXSv39/2W+//czIQLt27SSuuDtRuc+NrMkqLO26rrS7jiMfOcPZeq7A77I13EjgtyX4XZaKcw38BoCqBgHf/e53Zd68eXLQQQfJgw8+aBYQU3bZZRcTEEyfPl3iRlTLvTUVcdumj7kTzuqIe7j45ejhd3EJ/K5QxG2b+F2GHn6HZsQEAAIMAubMmSOPP/64CQIUXShswYIFMnfuXBMcxBEvE4N95JA60Eh5HmaPshf4nSwv8DtZXuB3OI8TAAQYBOiE4NrarX/aunVrOfDAA80jrniZGByD3qk47INLDfxOlgZ+J0sDv8OpAQABLhY2efJkmThxohkBSAruekQ85JBm6zlo33cpPB8XcFfgt6WGBz38tgO/y9DAbzsNz3oAEOBIwM4772wmBw8aNMisGHzIIYfI4MGDpU+fPhJXfF9AoqThY5XM3Iur+zHqqHrhQwO/K5WLpgZ+VyoXTY3Y+A0AbkYCTjzxRHn77bfly1/+sjzzzDMyYsQIExh0795dhg0bJnGk3tXJMPu1h3NhfSqaVTdSjvehGhr4XUIj6zV+24Pf4dHA7xIaHrwAAEcjAbpegE4O1kpAaTQoeOWVV2T+/PkSS2IyQcq1RlxySOMyIQ6/q6uB38nSwO9wagBAgEGAVgX67LPPct7TkQB9nHDCCRJHvKww6SMX1kXPUc5rV8PHxRTdaOC3Xfv43YxGET1XGvhtp4Hf8fcbABylA51//vlyxRVXyOrVqyUpRLlHxPVktZz2nR0n9xpxqSOO37YK+F12+/htr4ffpVQ8aACAk5GA733ve+Z5t912Mz3/Bx98sJkYvPfee0urVq0kjqQiXE3Cde+UlxzS2Gjgd7I08DtZGvgdFg0AcBQEvPXWW2ZRsPTiYNddd52ZE6BrBwwcODCW8wL89ByRQ2qnEeFuvBwJ/LbTwG9rDfy2FfEggd92GoQBAJEKAvr162cexx9/fOa9devWmaAgjgGAvxUmxb2G8/Oth1xbJwqeNPC77FbxuwwN/K6uBn6X3SohAEBE5gToAmEvvfRSwc86dOgghx9+uIwePVriiI8yZtHNIS38Gg17vWDbxe+waBTTC7Zd/A6LRjG9YNvFbwCoQhDw7rvvyjHHHCO9e/eW8847Tx555BHZuHGjJAJHZ6rcEQYPvS4O9iNnwl3grVdLA7+Lt4/flWjgd5g08DvufgNAwEHA7bffLsuXL5f//d//NT3/F1xwgXTr1s0sHvbnP/9ZVq1aJXElHkO77jWiukpmUw337eJ3mDTct4vfYdJw3y5+h0cDAAIqEdqiRQuT9jN58mRZsmSJPPfcc6Y60C233CI77rijHHHEEXLjjTfKe++9J3HCy0XDjYTzrhbfebDO8J3P60gDv21FCr4MVgK/y9ZwBn4ny28AcLNOQDZ77rmnXHzxxfKvf/1Lli5dKiNGjJCnnnrKjBbEiUj3TjnWcN1+nDQkBvsRFy/wOxztx0lDYrAfcfQCAAKsDlSMHXbYQUaNGmUecSPSeao5E8lSbttPRXMfvGngd/kaET1O+e1GdT/wuwwN/C5fg1kBANEOAqZOnWrmC3Tq1En22WefzOPAAw+UuOCqOpCXSgxF9Jy0H3zzTfU8eOFqR/C7Aj38Lq1RRM9J+8E331QPv0trFNFz0n7wzTfVIwYAiHYQ8Itf/EJmzZplovuFCxfKggULZMaMGbFKCXLWI1LktSuca0R4mD1Hw0O7+G0pgd8V6UVTAL8r1YumAEEAQOSDgP3220969Ogh7dq1kwEDBuQsIgb2uBt6davheyKZu6H8bD33Vyb8ttXA79LtutXA7wr18NtSgygAILITg5UJEybIcccdJ/fdd5+8//77EkecXTO89Hpl51+6Uci88rCeQqTL++G3pQJ+20vgt5UGflsrxMFvAPAUBJxxxhkyaNAg+ec//yk//OEPzWjAkUceKXHCy0SyiF78/PccOdLwvUgOfldXA7/Lbz/45v1p4Hf57QffvDcNAPAUBHTu3Fl+//vfm8eTTz4pb775pvzlL38Rl2jKUd++faVNmzbSq1cvOf3005uMQsyfP9+saaDf6dOnj1nboFK8nNBjkEXqu963Mwn8tms9+rvQIIHfdq1HfxcaJPDbrvXo7wIAuA4CdLGwO+64I+e93r17i0u++tWvyl//+lezYNk999wjb7zxhnzve9/LfL527VoZNmyY9OvXT1566SW54YYb5IorrpBbb721Ij0fo8fxqCbhIQ82yhpF9KKkgd9laBTRi5IGfpehUUQvShpx8RsAPE0Mfuutt+SBBx6Qq666Sg466CDZd999zeNb3/qWuOLCCy/MvNYb/XHjxsl3vvMd2bRpk9TV1cmdd94pGzduNKVLW7VqJXvttZfMnTtXpkyZIueee27BNjds2GAe2YFEmnovE8lcNVzwZXDNpzyUUi2i54pIa+B3+XpR1sDv8vWirIHfABCmkYC//e1vJgVI02/GjBljKgU99thj4otVq1aZm/5DDz3UBADKnDlz5IgjjjABQJrhw4ebkYNPPvmkYDuTJk0yax2kH5pC5H74OPp5qjk9OVE+Tp4rhuB3CQ38ttfA77I1XIHf4TlOABBwEHDIIYfI6NGjTe/6vHnzZMuWLTmft2/f3qQGnX322fLrX/9aXHPJJZfIdtttJ127dpWlS5eaYCTN8uXLTTCSTXpbPyvE+PHjZc2aNZnHsmXLHO9BFcrWuc4h9XBKj3R5Pw8auXr4XU0N/K5AA7/L0MNvAPAUBBxwwAEmv/7HP/6xed2hQwdz06+pOc8995xsK5rSU1NTU/KxePHizPcvuugieeWVV8zCZC1btjRVirblhNK6dWvp2LFjzsNrzWeJQTUJH8PHEmEN/LbTKPI6chr4badR5HXkNPDbTqPIawAI8ZyAP/zhD+Z58+bNsmjRIhMQ6OPhhx+W3/zmN3LmmWfKbbfdZm7WK2Hs2LEycuTIkt/R8qNpunXrZh6777677LnnniZ959lnn5WhQ4dKz549ZcWKFTl/m97Wz5JUJcF1/qWXcm8+LkweNHIF3TeL3yUk8NuuffyuUNB9s/gNAN4nBtfW1ppVgvVx1llnmfdmzpwpp556qsnLT79XLt27dzePSqivrzfP6Ym9GgjoImbpicLp3zhw4EDp0qVL2e376Z1Keci/TDnOUXU1zO4519ZH9RD8ttNwooDf1u3jdxka4l4DvwEgTBODla9//etyzTXXyM033yyu0dSj3/3ud6bazzvvvCOzZs2Sk08+WXbZZRdz86+ccsopZlLwqFGjzKjF9OnT5aabbjITlyvBWXWg7BO6h7Ohaw0vJ/RIV2rC7/JF8LsCOTftu22+UQS/K5Bz077b5htFCAMAIh8EpCcOv/766+Kadu3ayb333itHHXWU6dnXG30tSfrEE0+YvH5Fq/voXAEtXzpkyBCTajRx4sSi5UGbI8q5ka5PsV5ySH3n2rrSEL8aTtrHb3sN8avhpH38ttcQvxpO2o+J3wAQcDqQrgis6wBoGlD6Zjubjz76KJN645J99tnH9P43hwYGTz31VCCaXlJI45ILG8E8WF8aOXr4XRT8rqxd/K6uRo4efofGCwAIIAi49NJLzQJaOidg0KBBcuCBB5qHLsT16aefmhKbWps/lnipDuRhGNxFDmlek5pHWunkcBsNH6tYugr78Lt8DfwuQw+/rTTwO/5+A0DAQYAusvXGG29kqgLp45577pHVq1ebz/fYYw+58cYbJY54mawW4d6pfI2ArxlN2neNu95I/K6kfdfgd3ka+F2kXfyuqH0AiEh1IJ18q4/vf//7mffeffddU4Wnf//+EleimhuZX93BiYb41XB30XCvgd/la+B3qfbxuxwV1xr4Xb4GQQBAxEqE5tO7d2+JO86qA2WT8jO060fD5fCxG7wPUeO3lQZ+2zeJ37Ya+B13vwHAc3WgOOPjwlTvQCS/SR8abnqOsl57mJ/h4jj50MDvMjTwuyIN/K6eBn4DQJAQBFjip2KFj5Ohew3XuxHRQZmGdnM08DsM7bvUwO/wte9SA7/D1z4AFIcgwBI/qz+6bb9h24OGiz3JOU6p6K4oit+2Im7bx+/KNfC7uAZ+24q4bR8ArCAIsCWivVO+h3Z97IePSX34XYYGfpevF1SbzWw70cDv8vWCarOZbScaEfUbAAKcGDxmzBjbr8qUKVMkbkR1YLfpJC/3Gi7wMnGwyGtX4LedBn6XaBO/7TWKvHYFfttpEAMARCAIeOWVV6y+F/SiImHBx2Q1HzmkfjRctx/d44TflbQf3eOE35W0H93jhN+VtE8YABD6IGD27NmSZJxVk3DcD+Kj5nN+q25WsXSba9ugIe418NtOAb8rah+/S2mIew38Do3fANA8zAmIecWKagwfO8+F9RCQ4XeVNYpuBKmB36HRKLoRpAZ+h0aj6AYARGaxsFdffVWWLl0qGzduzHn/+OOPl7jhrpqEew3nvTrNbEcmh9RHTyF+22ngd2V6+F1CxL0GfofIbwBwEwS8+eabcsIJJ8iCBQvMHID00F56PsCWLVskbvipK+1Go6igKwnHOxLlXFv8Dl/7LjXwO3ztu9TA7/C1DwABpwOdf/750r9/f1m5cqW0a9dOFi1aJE8++aQceOCB8vjjj1fSZGJxX1c6bzuqGo7b96aB33Yajtv3poHfdhqO2/emgd92Go7bBwCHIwFz5syRWbNmSbdu3aRFixbmcdhhh8mkSZPkpz/9qXUloSgR1Z6jJhPJnOSQ+tVwV0fc/Rg1fpevgd+l2sfvSjTwO/5+A4CjkQBN9+nQoYN5rYHA+++/b17369dPlixZInHEVXUg91UYPGg0+0bQeh4Csqjm8+J3Ge2618jVw287Pfwu2iZ+A0C1RwL23ntvmTdvnkkJOvjgg2Xy5MnSqlUrufXWW2XAgAESR5ydqLI7p7zkd3rQcF0mL8rHCb/Lbz/Kxwm/y28/yscJv8tvnxgAIFpBwKWXXiqfffaZeX3VVVfJN7/5TTn88MOla9euctddd0kc8TEx2Ef7XnJInQwfu23fm4abZou2j99V1nDTbNH28bvKGm6aLdo+fgOA9yBg+PDhmde77rqrLF68WFatWiVdunSJ74rBrtrNyY1MecjvdDF8nKcRuIKv4Xv3evhdmYYL8NtSA7/tNfC7Ig0ACHkQMGbMGLn66qtlu+22M69LMWXKFIkbUR3a9dFzlN+om4uf2/bz28VvexH8ttVz0GYz2y5E8NtWz0GbzWy7EImq3wAQYBCgFX82bdqUeV2MuI4EuBoLyO2dctC+h6uGlyFqx+3HRQO/k6WB38nSwG8AqEoQMHv27IKvk0KU81S9D7s7lohqL15+u/gdjvZdauB3+Np3qYHf4WsfAAIuEbp06dKiQ3j6WRypdzVEnXUSd3JCbzK060Ai5bc0no9KTe5GfvC7XA38LimQu4nfJUSKbgQogd/lajA/ACBiQYCWBv3www+bvP/xxx+bz+JIVHunvCwu0+TK5FbDXWWPOOQM43eYNHL08NtKA79LtInfAFDtIEBHAQrl/n/66afSpk0biSPOckhzekTcth8Xjah64UMDv5Olgd/J0sBvAKhaidB0VSANAC677DJp165dzirCzz33nOy///4SR3zkkProEvFRiSEOOaTuKpQU23ADfttq4Le9RrTbb9DAb3uNaLcPAAEFAemqQHriWbBggVklOI2+3m+//eRnP/uZxBHfdaxdtelHw/Wxcn8B93Fdwu9KFQNqFb8r1MBvKz0PbeI3AHgLAtJVgc4880y56aabpGPHjpIYoppD2mRxmehrkDNcqk38ttbA71Bq4HepNvEbAKq8YvC0adMkaTirDpR9MnRRhcHinaA1XByrOOTzNmjgt5UGftu1b/FO0Br4XUoDv8M4KgMAAQYBymOPPWYeK1eulPr6+pzPbr/9dokbzi4a2a8j2jvlW8NPHqyjoC9Hw4lErl4MNPC7DL0YaOB3GXox0GDFYICIBQFXXnmlXHXVVXLggQdKr169YrxKsN+JwU7yO/MadbIbPi5EHuS85Anjd9kS+G3XvisN/C5DA7/LliAEAIhYEDB16lS544475PTTT5ek4PsCEuW60m5ySN2270ujmF5gbeJ3qDSK6QXWJn6HSqOYXmBt4jcAVHudgI0bN8qhhx4qScLd8LHbHNKm6764ze90ppEzqc99X6Grihj4bamB37YCRfUCk8DvMhTwOzx+A4CTIODss8+W//mf/5Ek4eyy5HlcNKo9YDntu23eW28kflu277b5Bg38Do0GfleoF1ENQgCAiKUDrV+/Xm699Vb55z//Kfvuu6/U1dXlfD5lyhTxxYYNG+Tggw+WefPmmXUMshcrmz9/vowePVpeeOEF6d69u/zkJz+Riy++uDIhVxcNxxL5bUY1T9XHxdVLSkKR1y7ad6aB3/YaRV67aN+ZBn7baxR57aJ9Zxox8RsAHAUBenOdvtleuHBhzme+JwnrTf2OO+5ogoBs1q5dK8OGDZOjjz7azGHQxc3OOuss6dy5s5x77rmhKRGajYth0SYndBca4lfDfbKAu3SBHD38ttLA71JtetBooonfVnr4baVBDAAQsSAgvWhYtXnkkUdkxowZcs8995jX2dx5551m7oKWK9XVjPfaay+ZO3euGaWoJAjwMXxc7ySF1MckrzyN4CVyfriPNRtceNGgsfU1fpcUybzE7xLt43cZEvidJL8BwNGcAOWpp56S0047zUwQfu+998x7//3f/y1PP/20+GDFihVyzjnnGM127do1+XzOnDlyxBFHmAAgzfDhw2XJkiXyySefFE0t0hGE7If7nqOU3/xOLz1g0W6/QcR9w/gdjvYbRNw3jN/haL9BxH3D+B2O9gEg4CBAe971hrpt27by8ssvm5tnZc2aNXLdddeJa7SnYuTIkfKjH/3IrFVQiOXLl0uPHj1y3ktv62eFmDRpknTq1Cnz6NOnT5ZmoLtQsF0vlR6c9E41/06QGu4qe3jQwO+yNfDbrv1C24FoWLwTpAZ+27VfaDsQDYt3gtTwEcgAQIBBwDXXXGPy7G+77bacScFf/vKXTVBQKePGjTNzCko9Fi9eLL/97W9l3bp1Mn78eAkSbU8DmfRj2bJlmc+8dE55OKG7rvnsQ4M64iXa9KGB39usF1ibPjTwe5v1AmvTh0ZM/AYAR3MCNKVGU23y0d7z1atXS6WMHTvW9PCXYsCAATJr1iyT7tO6deucz3RU4NRTT5U//elP0rNnT5MylE16Wz8rhLaX36bPahJO2veR35mfp+pEIeW0/fx2fWg4aR+/y9AQrxpO2sfvMjTEq4aT9vEbAKodBOhN9Ouvvy4777xzzvs6H0Bv0itFy3jqozl+85vfmNGINO+//75JT5o+fbopF6oMHTpUJkyYIJs2bcqMVsycOVMGDhwoXbp0Cc9iYSm/i6b40XAt4Lh9/C5Tw7WA4/bxu0wN1wKO28fvMjVcCzhuHwCCTQfSCbnnn3++PPfccyZFR2/CtRrPz372MznvvPPENX379pW9994789h9993N+7vssov07t3bvD7llFPMpOBRo0bJokWLTIBw0003yZgxYyrSjGrvlPeazx5yYd3l80a/NxK/y9HA78o08LuoRpHXgbWP3wBQ7ZEAzd2vr6+Xo446Sj7//HOTGqRpNBoE6IJcYUBTk7R8qC4WNmTIEOnWrZtMnDixovKgbnuOCr92RlTzVB2330QvJnnJ+G2ph9/WTeK3Xbv4bafBnACAiAUB2vuvqTYXXXSRSQv69NNPZdCgQdK+fXupBpqWVOgmXVcz1lKmQeDnfO62x8WbhouLRk7PkRt8aOTo4beVBn6XaBO/Q6WRo4ffVhrEAAARCwKWLl1qymdquo3e/Od/puk6ccNdz1HKuUaungcNx6f1VIQPFH5X0H6EDxR+V9B+hA8UflfQPkMBANGaE9C/f3/58MMPm7z/8ccfm8/iSGRzSD1XenA3fOwjnzcGOcP4HTKNwq+Dax+/w6VR+HVw7eM3AFQ5CNDIXVOC8tG0oDZt2kgccdZb4TiH1PfQrjNSMcnnxW9LEfd6+F2ZhhPw2655/AaAaqUDpSvraABw2WWXSbt27TKfbdmyxVQL2n///SWO+DlROcjvbLLtQcNJz5F7/FeswG9bDRfgd4Ua+G2r6LxF/AYAb0HAK6+8kukVX7BggZkTkEZf77fffqZCUBzxspQ9OaTbPBoVXPuO2vWgkaOH35btO2rXg0aOHn5btu+oXQ8aOXr4DQC+goDZs2eb5zPPPNPU3O/YsaMkhahODPaxwmQTDR/7kdIRKYd5qvhtr4HfxTXwu2IN/C7dvtkOXiI2fgOAo+pA06ZNk9WrV8svf/lLee2118x7e+21l5x11lmmPn8c8dJz5GFo10fXkZsLk18NDynD+F2qTfwuu/2GN/DbRgO/t0EzIn4DgKOJwS+++KJZnfdXv/qVrFq1yjymTJli3nv55ZcljvgZEnXfppcTespHnqpbDR9l6/C7hEYTTfy2aRO/7TTwO/5+A4CjkYALL7xQjj/+eLntttuktrahic2bN8vZZ58tF1xwgTz55JMSN7xUrHAjUVTPmYZ7icj2HOF3eDVcgN/h1XABfodXAwACCgJ0JCA7ADAN1dbKxRdfLAceeKDEEXfpQK7zVFMeenV85JCW3g5GxHH7+G2vgd/WCjlb+F1CxHH7+B0uvwHATTqQTgjWlYHzWbZsmXTo0EHiiLPqQDk9R6lYDB+7KY2Xd2FyrIHf9hr4XUIDv+008Lvs9hs0gicufgOAoyDgBz/4gYwaNUqmT59ubvz1cdddd5l0oJNPPlniiJeeChc9LvnbEe3V8a2B3yU08LtCQfdNxsELHxr4HX+/AcBROtCNN95oavqeccYZZi6AUldXJ+edd55cf/31EkdSHtr10avjeJTdmYYPXHvhQwO/7cFvS41mtqMCfltqNLMNAAkPAnRhMF0nYNKkSfLGG2+Y97QyUPYKwnHDWfWCnN4p96fbqFbF8K2B3+VoOJfAb1s5/LZsH7/tNZxLMBIAEIUgoL6+Xm644QZ54IEHZOPGjXLUUUfJ5ZdfLm3btpW4467nKDtP1W37rmi68IuLXFgPOcNZGvhdQgO/7TXwuzIN/G62fVfExW8ACHhOwLXXXis///nPpX379rLTTjuZ0YDRo0dLEqiPaG+Il/zOZradaLjeD/wurtHMthMN/LZqE78tNfC7uEYz2040iAEAwh8E/PnPf5Y//OEP8uijj8r9998vDz74oNx5551mhCD2ODpLua4r3TSH1P1Vw8vFL6oriuK3nQR+l91+gwZ+22jgdymR0ppR8RsAAg4CtCzosccem9k++uijzQTh999/X+KOu+HjGOZ3VmHIOirt43eFGvhtp4ffVW0fvyvUYCgAIPxBgFYCatOmTc57WhVo06ZNEneczSNznKfatB6zew03nVM+9sNt+6Zd/K5IA7+LtI/fZWi4bd+0i98VaRACAERgYrCe4EaOHCmtW7fOvLd+/Xr50Y9+JNttt13mvXvvvVfihpeJS1HNIfU8lF9oO2iRyNYRx++KRPC7DI3gJfDbtkn8BoBqBQEjRoxo8t5pp50mScBDRTk/w64uqm7kb7tPU3XUO5X92kO6AH5ba+C3rR5+22jgd6k24+E3AAQcBEybNk2Sirt0IPcaxfRcUe8jF9bxVQO/7cFvu3bx2x78Ll/PFXHwGwACmBOQZLycCD0M7bogLsPHcbiA43dlGvhtr4Hf5euFuc24+g0AzUMQUEW8LJCTPwErFU2N/EtRKpK9j/hdjkrxraAU8DssGvhtqYHfABAgBAGhGnZ1/7t9aPjoOXIxMpPdpI+RH/y218DvwuB3ZRr4HX+/AaB5CAIscbOMfeltF0S1KkYTCccaXqpuxOA4NYh4kMDvijTdiHiQwO+KNN2IeJAgBgCoCgQBlnipkOCj0kNUNVJ+NXwcJ/wuoYHfFWngt50GfsffbwBoHoIAS9wMiebnXkZTI79RNwGT+zHqVAy8wO9yNKLvBX6XoxF9L/AbAIKEICBUZdLct+lFI7J5qltbjeooO36Xo4HfFWngt52ehzbxGwC2BYIAWzykA7mpwtBExL2Ec4WI5gw30cBvaw38thTF72q1j9/boEEUAFAVCAIs8TDqGh8NJ2Xr8rddXzV85MEGD34HpRhAi/htr9FkG79DoxELvwGgEAQBlvipxxy4RJPTrZc81eAlYrGYEH6Xo1F6O2gN/C6hgN927eN3GRqltwHADwQBlkQ2h7RJz5GHXh0fF1hxq4HfJTSa0QxGA7+t2sTvijTwu4RGM5pR8RsAmocgIFR1pT3kd3o52/rYj1T0Rn7wu3IF/K5I05GKewX8rkjTkYp7BYYCAKoCQYAlUV3RsGnuZUSHdn2nC0g0we8yJPDbTgO/QwN+A0CQEASEaiQgohrNbLvQEMcakfUCvyvSiKwX+F2RRmS9wG8ACJDIBgE777yz1NTU5Dyuv/76nO/Mnz9fDj/8cGnTpo306dNHJk+eLGHGzcqMKf8aTi5+fjW8DOXjd2g08LsMDfy208PvqmoAQPPUSoS56qqr5Jxzzslsd+jQIfN67dq1MmzYMDn66KNl6tSpsmDBAjnrrLOkc+fOcu655yaoOlATUQ8S0bzA5rbvok38DqsGfpcjgd+F28TvMGsAQMyCAL3p79mzZ8HP7rzzTtm4caPcfvvt0qpVK9lrr71k7ty5MmXKlKJBwIYNG8wjO5CIeu6lj6HdJpo+9sO1BkP59pr4Xbh9/LZv07cGfsfebwCIcTqQouk/Xbt2lcGDB8sNN9wgmzdvznw2Z84cOeKII0wAkGb48OGyZMkS+eSTTwq2N2nSJOnUqVPmoSlEfk/oLoZ287c9aASu4Ecju1EfebD4XV0N/K5QI3AF/LbWwG8ACJDIBgE//elP5a677pLZs2fLf/3Xf8l1110nF198cebz5cuXS48ePXL+Jr2tnxVi/PjxsmbNmsxj2bJlfodEnQQaqSpouEidEq8aUS3vh9+VaeB3ORr4baWH3yU08rYZCgCoCqFKBxo3bpz84he/KPmd1157TfbYYw8ZM2ZM5r19993X9PhrMKC9+a1bt65IX/+u2N/WOxk+9p9D6mI/8onDfuC3PXHYD/y2Jw77gd/2xGU/ACDkQcDYsWNl5MiRJb8zYMCAgu8ffPDBJh3o7bffloEDB5q5AitWrMj5Tnq72DyCUkQ1HahJPWYfQ9QeKla4GEDOqR7iYyVO/C6hgd+ViOC3nQZ+x99vAIhYENC9e3fzqASd9NuiRQvZYYcdzPbQoUNlwoQJsmnTJqmrqzPvzZw50wQIXbp0qUDB/cnWSe9UM5ouNOrrPWg43g83PYW52/hdhgZ+F9ZoRtOFBn4XaR+/K9cgBgCoCpGcE6CTfn/961/LvHnz5M033zSVgC688EI57bTTMjf4p5xyikkRGjVqlCxatEimT58uN910U04aUfiGRH0EGtHUEM/74SNHNape4HdlRNUL/K6MqHoRF78BIGIjAbZo3r5OCr7iiitMSc/+/fubICD7Bl+r+8yYMUNGjx4tQ4YMkW7dusnEiRMrWiNAcXKK8tBzlI+Pk62XgKnecfsu9gG/Kwa/7cBvy/bxO1F+A0CMgoADDjhAnn322Wa/pxOGn3rqqUA0/SwW5l7DzRB1vkYq8ho+9gG/w6OB3+Vo4Hdz7Ztt/K6qBgDENB2oGvjJIY1HXWkfx8rJCHVOukDwxwq/K9fAbzsN/LbTwO/4+w0AzUMQYImPWsleJmB5GHaNap6q6wsTftuD3+HRyAe/i7Sft43fVZ53AADNQhBgiY9TlJuTrYeh3VQ1hsHdO+JaA79LaOC3FfhdOfidLL8BoCkEAbY4GRLNP9mKc/xMVkOjEPidLA38TpYGfodbAwCaQhBgiYtzVJOhXQ8pR35ySKOaC+u2dwq/K9fAbzsN/C6lgd9J8hsAmocgwJKonmy91N8W/4vkRHEhHvwOtwZ+W0ngd7H28TtUGgDQPAQBlvg4Sbm5ZuT3fklEe/HiN1kNv+018LtIm/gdKo1SeoG0id8AECAEAZb4qJW8xcOJ0IuGh4ipvj56xwq/Kwe/7cBve/A7WX4DQFMIAiyJ7NCuj14dD71TUoVFclJBl9/D77JUXGvgt6UGftsK5IDfpVXcawBAcxAEVLE3xEtd6VQVNCI6fOxaA7+TpYHfydLA73BpAEDzEASEak6Ah0AjqhUrpBoT4lznDEdzH/C7Qr2I7gN+V6gX0X2Ii98A0DwEAVXMW2zaGyLOiYtGKpJ1xN22X4i4aOC3HXHRwG874qJBDABQHQgCyiD44eOUh2HXvDxYJ3Mb/O9HFPNt8bscCfy20sDvMjRKa25z+/hdhoR7DQBoHoKAalaT8NBzVJ1h9qjWlc6/MAXcOn6HSgO/K9UIXAK/bTXytvEbALYFgoAycN1Z4acec+ASsakr7XuyGn7ba+B3sTZzt/G7uhq5evhtq8FIAEB1IAioYoUgH706ElMNH8vMO68eEsF9qJYGftsRFw38tiMuGj78BoCmEARU86LRJC8y0ObTKnmaLhTc70c1hqiDPlb4XY5GLvhdVCVP04UCflu1j99laORCOhBAdSAIKIOgazLHZQjcj0Yq8hrx8cKHBn4nSwO/k6Xh3m8AaB6CgDJwn0PqoM2q1JUW58Shdwq/7cHvIm3mbeN3cfA7WX4DQPMQBFSxOlB18jujt55CXHKGfbffoOFcAr9D0n6DhnMJ/A5J+w0aziVi4zcANIUgoAziMHwcl4oVUTxWcdiHQhr4Hd99KKSB3/Hdhzj5DQDNQxBQzTkB+ROwAm6/kEbQFY4KabgZos7fj8AlmlxQg9bA78o18NtOA79LaOB3ovwGgOYhCIj58LGPXh2Jy2S1vG38LiaSr4HfNuB3CQn8tgK/ASBICAKquU5AFU6Ecci1jep+4Hey9gO/k7Uf+F05zAkAqA4EAWUQ9Hmqac9UsO3HSqMKPWD4XUUN/E6WBn4nS8OH3wDQLAQBVawOVKj3I/jJah7yO/PadDJZzUueqt/F4Yq9F6QGfpfSyAW/7TTwu0j7+B0qvwGgeQgCQrTMfINGoBJe2m/Sq1PvQcPJfuRfmAJuv8B7+G2pgd9W4HcpDfxOkt8A0DwEARa0qPFXL9n9gmTR34c47Qd+J2s/8DtZ+4HfdjAnAKA6EARY0LIxCgi85yiV236DRtDDx3mBjMNh9q0a4kwj44WT0ni5Gq7qiOO3vQZ+22ngd/ka+F1EIyZ+A0DzEARY0KLxRBV8TeaG9rKuGQ4mq6U13AQyuRcmNxfXhkbTGuJhP1xp4Le9SFqj4Rm/iyngt7UEfifKbwBoHoIAC1o66nXJP9k61ciMZrjoOUr506jxqOGoJCx+l6GB33Ya+F2+Bn7H2m8AaB6CAAtcngybDh87kZCWmV4dN+1na7js1dk6lO9ew5kX+G2vgd92GvhdtgZ+J8NvACgOQUAVT4aZvEgPPUctXfbq+NSo8acReM5w4zN+l6GB36U18LtiDfwOgQYjAQBVhSDAglpHcwLS572sa4akAi7Hlv7FaQ2XJ9u0hsMU0qz9iJ4GftuD35Yajc/4XX0N/A6X3wDQPAQBFrjKW0znRbqtJpGr4abmc8pDz5F7jfSVyZUGfodLA78r1MDvIs3jd5g0ACDGQcDf//53Ofjgg6Vt27bSpUsX+c53vpPz+dKlS+W4446Tdu3ayQ477CAXXXSRbN68edvmBDjqrnB50chouKz0kKfh8oTuqrxfIQ0/c0Dwu6QGfttp4HfZGvidDL8BoDi1EkHuueceOeecc+S6666Tr33ta+bmfuHChZnPt2zZYgKAnj17yjPPPCMffPCBnHHGGVJXV2f+ptKRgC2O8jtFasywqG4HrpFf5tRJpYc8DRe9U/leONFIuR35we/yNfC7tEbjM37baOB3kvwGgBgGAXrDf/7558sNN9wgo0aNyrw/aNCgzOsZM2bIq6++Kv/85z+lR48esv/++8vVV18tl1xyiVxxxRXSqlWrsjRrG2uEBn2+zW5PT4Z6Qg/8nN5kApZEbsJd1SbEBZ3Pi9/la+B3MyINT/hdgQZ+x9pvAIhhOtDLL78s7733nrRo0UIGDx4svXr1kmOOOSZnJGDOnDmyzz77mAAgzfDhw2Xt2rWyaNGiom1v2LDBfCf7kX0yDHxicOMZXZt3NfSan6fq5ISep+F2FUuX+5Gr4coL/LbRaAC/7TTwu3wN/I633wAQwyDgzTffNM/ao3/ppZfKQw89ZOYEHHnkkbJq1Srz2fLly3MCACW9rZ8VY9KkSdKpU6fMo0+fPl7WCajxULGiRaPTTleYdKiRFnFZ4zvlQUPBb3sR/C4Nfpcjgd9J8hsAIhQEjBs3Tmpqako+Fi9eLPWNY7gTJkyQE088UYYMGSLTpk0zn999993b9BvGjx8va9asyTyWLVuWUyLUVQ6pXjBcrWLpdZKXx4lkUZysht8VaOC3FfhdvgZ+h0CDdCCAqhKaOQFjx46VkSNHlvzOgAEDzCTf/DkArVu3Np9pRSBFJwQ///zzOX+7YsWKzGfF0Hb0kY8GGK7KsaVJF5QIfN5Bpn13F6WmQ7uBS8Sijng2+G2ngd+lwe9waaTBbzsN1gkAqC6hCQK6d+9uHs2hPf96o75kyRI57LDDzHubNm2St99+W/r162e2hw4dKtdee62sXLnSlAdVZs6cKR07dswJHmzJzAlw1XMkNc4rVqRTmpyc0PM0orjaZyENZyM/+G2tgd92GvhdvgZ+x9tvAIhQEGCL3sj/6Ec/kssvv9zk7OuNv1YKUk466STzPGzYMHOzf/rpp8vkyZPNPACdPzB69OiCPf3NsfWE6+ZEpedBVytAZiZ5OR3ada/hY7JaGtca+G2jgN824Hf54HfzKnHyGwBiFAQoetNfW1trbvK/+OILs2jYrFmzzARhpWXLlmbC8HnnnWdGBbbbbjsZMWKEXHXVVRXppecEBF3LOFNNIqfXRZzgun1vGjX+NIIfysfvsjXw2wr8Ll8Dv5PhNwDELAjQRb9uvPFG8yiGjhA8/PDDgei5Hj52WSotM7TrqGeqkIbLofytFSuCPk5b23OnsfU1fltq4LeVBn431z5+J8lvAIhYdaAw4+yikTXxeOtJXZxobK2IEWz72W26Le/XqOGqFy+rPVcL8eB3BRr4baWB33btZ2vgd3z9BgA7CAIs8JG3mKlA5Ojq52qimpEQHxpuJ6tlt+Z6XQgFv5vTaAC/mwG/y2rfpUY2+N2chj8vAKA4BAEWtHA1J6DxxNdQV1qcngz9TrhzJuG1PnbwQ/n4XbYGfluB3+Vr4LetRrT9BoDiEARY0NJZpYemi8sEP1nN7RB44aFdFzmkjb1Tji5MuTnDrtMF8Lt5DfwuRwO/7dp3qtH4jN/V9xsA7CAIKKdHpN79RDKXqxJvfc9dMOO6V8fVZLWcdAFXQR9+lw1+22ngd2nwuwyNGPgNAHYQBFS1jFnj8LH+r/FkuCXwQCOVE8i40ZAcjaDTpgpruLuAuwr68HtbNPC7oAJ+l9V+tgZ+F9OIvt8AEOMSodUKAoJeMViyh4/F7bBo9kXDtYbLXp2WjaWanOapOtbA73I08NsG/A6PBn6Hy28AKA5BQFUnkjU81zhclThV8KIRtEZu75TTFSadzc/Y2p4zDfwuXwO/S2s0PuO3XftONfC7fA0PKUcAUBzSgSxwNrRbQCP4CXG5oxnZ7wUnkqvhcrKaswl3BfN5A9bIeo3fzUjgt50GfpfVfrYGfhcTib7fAGAHQYAF7ipWZC8u4ygXVppeNIJOa8rXCD7XtmldaZc5pBm/HeXa4ncZGvhdWqPxGb/twe9k+Q0AxSEIKCMdaEu9gxlSjcPHtY0nw82ONFrXbrV68xa3Gpsc7YPSqlFjswcNV/uB3/bgtx34Xb4GfifDbwAoDkGABa3rGg7Thk3Bnqgy+aI1Im3qWjrVqG1Zk8nx3LDZjYar45St0abW1XHa+tqdBn6Xq4Hfdhr43Vz7W1/jd/z9BgA7CAIsaN14olq/eUug7aYK9LoEfUKXQhpBX5gy7bd0tg8ZjfSFKegLX5Yb7jS2gt+WGvhtDX6Xah+/k+Q3ANhBEGBB68ZenfWOeqdqsjQ2BB1oZGtkLkxuNNrUuWm/QaRRI3NhcrMPPjTw20akUQO/7TXwu3jz+J0ovwHADoIAC9o0nmzXb3JzotKJZK57jho03PXsKJkh8M31zmpLt/HQc+RaA7/L0cBvew38DoMGfpejwUgAQDUhCLAgPWQZ+EhAZoXJ7KHdLe40HPXspC8P6V4dvV5s2uKmYoWzXNus1+408LtsDfy218DvZtt3q4HfZWs48gIA7CAIKGckIOghy6zzqqtenewOHGc5pHkTydwMUTdqOBsCz8oZdqSB3xVo4HdpCfwuq32XGvhdgYYrLwDACoIAC1plKhi46XHRCqTOJ6vVOLwwNT63arn1P6fgR01ye45cte9DA7/tNfDbTgO/7dr3oYHf9hquvAAAOwgCyshbdHWiqpHsHNItkdXQinWuNZxOVvOkgd/24Hd4NPDbDvwOl98AUByCAAvSuZFBTwzeusJkVq+OqwpE2bWrg56ElXI/IW5rxQr3w+yuNfDbQgK/y9bA7+bb96GB39X3GwDsIAgop0Ro4BOwCuWpOqyP7ayudHYNbreT7pxV3SiUa+vDC/wuqYHfFWjgdyGBDPidAL8BwAqCAAvSJypX6wSIy0oPObWrHWs4HD5Oa6QvSlvqU7J5S73jC5+7WuX4baeB33Ya+N1M+/idKL8BwA6CgLJKhLpcJ8DtsGjOELUrDQ89O+nULB8aGyNc4xu/y9fA72Y08NsK/A6X3wBQHIKAsuYEOKom4XBot/BEMkcjGg4vflt7jrLL1tU7yhl2W9kDv+018NsO/LZrX8Hv+PsNAHYQBFRxJMBH7eqCGo4WsDEa6Quso1GTljU1UteyJvBjlV1CcOuFD78LauC3nQZ+lw1+V6CB3wBQIQQBFnRq28o8f7phc6BDyNl1pdNVEj7f6C6/07lG1qjJF44CJrMftcHvR/bFtW0rR8ep8Rm/bTTw20oDv8tqX8Hv+PsNAHYQBFjQuW2dqZmsfPL5xsDb1xNhl3YNgcbqzzcF3n5ao3OjxicONbpsV9eg8dlGNxpSI50bNVY78ELZvvE46UXJRe8Ufpehgd/WGvhtB34ny28AKA5BgAUtWtTI9ts1nHA//jTAE1WmxyWr/YBPtlv7v2qka6PGqs82ONHI3o9VjvZDL0zbb9c6cC+y0wU6tq2V2saoL9D9wO/yNfDbRgK/LdtX8Dv+fgOAHQQBlrg4GWbnXnZrv/WEXl+fCk4jq6mu7R1dmLI1Gk/oHznU6ObgApvdvlb3cBH04XdlGvhdQgO/y24fv+PvNwDYQRBgydaenQ1O8ju7NLav14vVX2wK/MLU0OPiYDSjUSWtkb74ffxp0L1TqSYXPxcBme5Dg0ZrZzci+G2jgN9WGvhdVvv4bacSdb8BwA6CAEvSF40P1wV7MlT0ulTXsoV0bFMb+PBu9iSvdK+OBjLZE+WC1EgP7QY+fJx1gU1rfBTkhSlrH5T0UHvQF7+0Bn5bauB3SfDbVqCx/cZN/I653wBgBUGAJf22b2ee3/74Myf1mJXuHRpOhsvXOLgwaa9Oh1aZ9Q7WfrHZiUZmH9auD7x9oyE1GY2Va10cpwYv0j1gKwLUwO8KNPDbCvy2bB+/E+U3AJSGIMCSXbq3N8+vr/w0sDbz+24GNGr8Z+U6JxrtWtVKr05tnGoM6L6deX73ky/kiyBL/BXQcLUPPrzwoYHfdu03aOC3jQZ+h0cDvwFgWyEIsGTXHRpP6Cs+DWzoNVMruXF79x4NGv9eEVygke6e0h4XZbceHczzf4IMZrI0urVvbXJV9a03PgxSY2vv1O6N+/DWR5/Jpi31gQ+BZ3uhfgdFMb+D9AK/y2y/cRu/S0ngt50GfttruPUbAOwgCLBkYM8OZoVGnUgW1Mkwb/RYBvbsaJ7nLVsdSPuFNPbo2XDCnbs0eI301W9g40n9lQD3I3uy2o6d2kiHNrWyaUtKFr2/1snEwbQXS1ask883bnbqtwsv8Lu51vG7XA38bk6jAfyuvt8AEOMg4PHHHze5nYUeL7zwQuZ78+fPl8MPP1zatGkjffr0kcmTJ1esqaszHrTz9ub1o4tWSJCke46+vEtXc1J89YO18t7qL5xoHLZrN/M8a8lK2Rxwr0tGY7cGjZmvBnucGjQafE7vx8xXlwfevrJz13bSu0tbs0L0k//+KGCNBvDbRgO/y9HA7+bbV/A7GX4DQGkayhdEjEMPPVQ++OCDnPcuu+wyeeyxx+TAAw8022vXrpVhw4bJ0UcfLVOnTpUFCxbIWWedJZ07d5Zzzz23It3vDN5Jnn79I/n/nnrTDGG2b10rH366waymqCME+qzLq+vJWHs1Nm6pN6+1TJz2e2SnEenLdDWE9GQ1rUB0SP+uMufNj+Wah16VscN2lzVfbJb3V39hqhLpioq6OuRnGzbL5vqUbK7X9vW54ZHffvZE5rTGwQO2N8O72t5Nj/1Hvr3/TuZ3fLDmC/lonbbfoLFe90Pb1X3Ies4mrbHw/TU5Gt/Yu6fcOGOJPPnvD+Vvc9+TQb06mollH6xZb8rZ6X7oSpq6WmdD2+l9qJctRTTWNJbZS/eAHbNPL3lk4XL5y7NL5fDdukuntnVmH1RDfdD29W90eHlT4+/XttWX+gLHKbNyaGP7ui/H7tNLbn3yTXOc+mzfVurrxVzMV65TjU3mWK1bvznLh61+FNLAb/zGb/zGb/d+68jPpi+CK+IBEFdqUkHWFqsSmzZtkp122kl+8pOfmGBAufnmm2XChAmyfPlyadWqoYrCuHHj5P7775fFixdbtauBRKdOnWTNmjXSsWNH02t0wh/+FfiQ5TF795SbTxtiXr/49ir5/i1zTOAQJBcNHyijv7qref3nOW/LxL8tClZA2z3rS3LE7t0b9O6eJ3e/9G6g7bdsUSPPjj/KVJPQC8Dxv3s6cC+0d/DpS75mXuuF9eu/esJcgIIEv+3Ab3vw2w78To7f9Rs+l2W//n7m+g0AMQ0C7rnnHvn+978v77zzjvTu3du8d8YZZ5ibeL3pTzN79mz52te+JqtWrZIuXbo0aWfDhg3mkUb/XtOIsk8i2svyyxlL5Pm3VpnefZ04peXmurRrZXpktGJDXcsaUydaH7Uta6RlY3eHPqV7PtLD0noiPHy3btK5XUOgkh52/dXMf8uyTz6Xjm3qZMfObWSHjm1k+3atpHO7OjMCUWvarzF/X9tCn1tIi0wv11YNfd22rqV8ZWB3aV3b0ryvlv/x6bfkzueWykfrNki3Dq1NlQk9GXdp1NiuVW1D2y21/RaNGg3tZfalcR9MKTnt9RrQVVo0/gjtebr+kcUyY9FyWbdhs2m/V6e2ZmEYo9G2Ttq2apn5/bo/+lqPVaHjpNtaoWnvnTpljpP22F3xwCJ5/q1PZEt9vWlfj5X6oBod29aZeRzmt+vxatwHfeQfp/T2AX27SJ/GcrDKwvfWyDV/f1UWL18nrVq2kF6d20qvjm3MYkBd2tVJhzZ1Gb+1XX3doqawhr7Wz/Abv/Ebv/Hbrd9ffLZOTjl8T4IAgLgHAccee6x5fvjhhzPvaSpQ//795ZZbbsm89+qrr8pee+1lnvfcc88m7VxxxRVy5ZVXNnmfkwgAAEB0yB/JB4CQTwzWdJ1iE37Tj/xUnnfffVceffRRGTVq1Dbrjx8/3pww0o9ly5Ztc5sAAAAAAGEjVBODx44dKyNHjiz5nQEDBuRsT5s2Tbp27SrHH398zvs9e/aUFStyqxmkt/WzQrRu3do8AAAAAADiTKiCgO7du5uHLZrJpEGA5v/X1dXlfDZ06FAzMVgnDac/mzlzpgwcOLDgfAAAAAAAgKQQqnSgcpk1a5a89dZbcvbZZzf57JRTTjFVgTRNaNGiRTJ9+nS56aabZMyYMVX5rQAAAAAAYSFUIwHl8sc//tGsGbDHHns0+UwnBM2YMUNGjx4tQ4YMkW7dusnEiRMrXiMAAAAAACAuxKI6kCuoLgAAABA9uH4DxDwdCAAAAAAAyocgAAAAAAAgYRAEAAAAAAAkDIIAAAAAAICEQRAAAAAAAJAwCAIAAAAAABIGQQAAAAAAQMIgCAAAAAAASBiRXjHYNel11HTREQAAAIgG6es266ECFIcgoAQff/yxee7Tp0+1fwoAAABUcB3XlYMBoCkEASXYfvvtzfPSpUs5iYSgV0eDsWXLlrEEfJXBi3CBH+EBL8LDmjVrpG/fvpnrOAA0hSCgBC1aNEyZ0ACAE3o4UB/wIhzgRbjAj/CAF+G7jgNAU/jXAQAAAACQMAgCAAAAAAASBkFACVq3bi2XX365eYbqghfhAS/CBX6EB7wID3gB0Dw1KepnAQAAAAAkCkYCAAAAAAASBkEAAAAAAEDCIAgAAAAAAEgYBAEAAAAAAAmDIKAIv//972XnnXeWNm3ayMEHHyzPP/98tX9S7Jg0aZIcdNBB0qFDB9lhhx3kO9/5jixZsiTnO+vXr5fRo0dL165dpX379nLiiSfKihUrcr6jKzofd9xx0q5dO9PORRddJJs3b/a8N/Hi+uuvl5qaGrngggsy7+GFP9577z057bTTzLFu27at7LPPPvLiiy9mPtd6DhMnTpRevXqZz48++mj5z3/+k9PGqlWr5NRTTzWLVnXu3FlGjRoln376aRX2Jtps2bJFLrvsMunfv7851rvssotcffXVxoM0+OGGJ598Ur71rW/JjjvuaM5H999/f87nQR33+fPny+GHH26u97ri8+TJk73sH0DV0epAkMtdd92VatWqVer2229PLVq0KHXOOeekOnfunFqxYkW1f1qsGD58eGratGmphQsXpubOnZs69thjU3379k19+umnme/86Ec/SvXp0yf12GOPpV588cXUIYcckjr00EMzn2/evDm19957p44++ujUK6+8knr44YdT3bp1S40fP75KexV9nn/++dTOO++c2nfffVPnn39+5n288MOqVatS/fr1S40cOTL13HPPpd58883Uo48+mnr99dcz37n++utTnTp1St1///2pefPmpY4//vhU//79U1988UXmO9/4xjdS++23X+rZZ59NPfXUU6ldd901dfLJJ1dpr6LLtddem+ratWvqoYceSr311lupu+++O9W+ffvUTTfdlPkOfrhBzyETJkxI3XvvvRpxpe67776cz4M47mvWrEn16NEjdeqpp5pr0f/+7/+m2rZtm7rlllu87itANSAIKMCXvvSl1OjRozPbW7ZsSe24446pSZMmVfV3xZ2VK1eaE/0TTzxhtlevXp2qq6szF900r732mvnOnDlzMheJFi1apJYvX575zs0335zq2LFjasOGDVXYi2izbt261G677ZaaOXNm6itf+UomCMALf1xyySWpww47rOjn9fX1qZ49e6ZuuOGGzHvqT+vWrc0NjPLqq68ab1544YXMdx555JFUTU1N6r333nO8B/HiuOOOS5111lk57333u981N40KfvghPwgI6rj/4Q9/SHXp0iXnHKX/BgcOHOhpzwCqB+lAeWzcuFFeeuklM6yYpkWLFmZ7zpw5Vf1tcWfNmjXmefvttzfP6sOmTZtyvNhjjz2kb9++GS/0WVMlevTokfnO8OHDZe3atbJo0SLv+xB1NN1H03myj7mCF/544IEH5MADD5STTjrJpFQNHjxYbrvttsznb731lixfvjzHi06dOpm0xWwvNPVB20mj39dz2XPPPed5j6LNoYceKo899pj8+9//Ntvz5s2Tp59+Wo455hizjR/VIajjrt854ogjpFWrVjnnLU1N/eSTT7zuE4Bvaqv9A8LGRx99ZHJAs29kFN1evHhx1X5X3Kmvrzf551/+8pdl7733Nu/pCV5PzHoSz/dCP0t/p5BX6c/AnrvuuktefvlleeGFF5p8hhf+ePPNN+Xmm2+WMWPGyM9//nPjx09/+lNz/EeMGJE5loWOdbYXGkBkU1tbawJsvCiPcePGmUBWg96WLVua68O1115r8swV/KgOQR13fdb5HvltpD/r0qWL0/0AqCYEARCaHuiFCxeaHjbwz7Jly+T888+XmTNnmslxUN2AWHsur7vuOrOtIwH6b2Pq1KkmCAC//PWvf5U777xT/ud//kf22msvmTt3rumw0Mmq+AEAUYZ0oDy6detmenvyq57ods+ePav2u+LMj3/8Y3nooYdk9uzZ0rt378z7erw1PWv16tVFvdDnQl6lPwM7NN1n5cqVcsABB5ieMn088cQT8pvf/Ma81p4xvPCDVjoZNGhQznt77rmnqbyUfSxLnaP0Wf3MRqs0aaUUvCgPrXClowE//OEPTbrb6aefLhdeeKGpbqbgR3UI6rhz3oIkQxCQhw65DxkyxOSAZvfM6fbQoUOr+tvihs710gDgvvvuk1mzZjUZklUf6urqcrzQPE29GUp7oc8LFizIOdFrb7aWg8u/kYLiHHXUUeY4ai9n+qG90ZrykH6NF37QlLj8Urmaj96vXz/zWv+d6M1JthearqI5ztleaMCmwV0a/Tem5zLNmQZ7Pv/8c5NDno12FOmxVPCjOgR13PU7WopU5zxln7cGDhxIKhDEnypOSg51iVCtMHDHHXeY6gLnnnuuKRGaXfUEtp3zzjvPlHd7/PHHUx988EHm8fnnn+eUpdSyobNmzTJlKYcOHWoe+WUphw0bZsqM/uMf/0h1796dspQBkF0dSMELfyVaa2trTWnK//znP6k777wz1a5du9Rf/vKXnNKIek7629/+lpo/f37q29/+dsHSiIMHDzZlRp9++mlT9YmSlOUzYsSI1E477ZQpEarlKrX07cUXX5z5Dn64q1am5Yb1obcrU6ZMMa/feeedwI67VhTSEqGnn366KRGq13/990aJUEgCBAFF+O1vf2tueHS9AC0ZqjWGIVj0pF7ooWsHpNGT+f/7f//PlHDTE/MJJ5xgAoVs3n777dQxxxxjajvrxXns2LGpTZs2VWGP4h0E4IU/HnzwQRNQaWfEHnvskbr11ltzPtfyiJdddpm5edHvHHXUUaklS5bkfOfjjz82Nzta017LtJ555pnmpgrKY+3atebfgV4P2rRpkxowYICpXZ9dUhI/3DB79uyC1wgNzII87rrGgJbl1TY04NPgAiAJ1Oj/VXs0AgAAAAAA/MGcAAAAAACAhEEQAAAAAACQMAgCAAAAAAASBkEAAAAAAEDCIAgAAAAAAEgYBAEAAAAAAAmDIAAAAAAAIGEQBAAAAAAAJAyCAAAAAACAhEEQAAAAAACQMAgCACB0HHnkkXLBBRdU+2cAAADEltpq/wAASBY1NTUlP7/88svl3nvvlbq6OqkGF154obzzzjvmN+Rz5plnyk477STXXHNNVX4bAABAUBAEAIBXPvjgg8zr6dOny8SJE2XJkiWZ99q3b28e1eL555+X4447rsn7W7ZskYceekj+/ve/V+V3AQAABAnpQADglZ49e2YenTp1MiMD2e9pAJCfDqTbP/nJT8x7Xbp0kR49eshtt90mn332memd79Chg+y6667yyCOPZP6mvr5eJk2aJP3795e2bdvKfvvtJ//3f/9X9Hdt3LjRjD4888wzMmHCBPO7DjnkkMzn+r5+ftBBB8nbb79tPr/nnnvkiCOOMO3r+0uXLpWnnnrK/F27du3kqKOOktWrV+f8puuuu0522203adOmjdmPkSNHOjnOAAAApSAIAIBI8Kc//Um6detmeuo1IDjvvPPkpJNOkkMPPVRefvllGTZsmJx++uny+eefm+9rAPDnP/9Zpk6dKosWLTJpPqeddpo88cQTBduvra2Vf/3rX+b13LlzzYjFP/7xj8znDzzwgHzrW98yN//z5s0z7918883mpl4DhBUrVpj2r7/+evnd734ns2fPNt+bNm1apg39TXfddZfceuutZvTjvvvuM0EEAACAb0gHAoBIoD35l156qXk9fvx4c7OtQcE555xj3tO0Ir0pnz9/vgwePNjcnP/zn/+UoUOHms8HDBggTz/9tNxyyy3yla98pUn7LVq0kPfff1+6du1qtPL529/+Jr/61a8yQcL2229v0pn0+4q2qe1rwKGjAIqODixfvjzTxqOPPmoCia9+9atmu1+/fiaIAQAA8A1BAABEgn333TfzumXLlubme5999sm8p6k1ysqVK+X11183IwJf//rXm6T8aIBQjFdeeaVgAPDaa6+ZAEHTexTt4T/hhBMyAYCiqUA/+MEPMgFA+r1vf/vbme3jjz9eLrnkEnnxxRfNKMaJJ55o0psAAAB8QzoQAESC/GpBmpaT/V666pDm3X/66afmtU7i1V779OPVV18tOS9Av1MoCNBUIA0oNI8//b2DDz445zsaGGTPIVi/fr1J+clu72c/+5kJKDSY0FEFncfw1ltvVXA0AAAAtg2CAACIHYMGDZLWrVubnni90c5+9OnTp+jfLViwQPbff/+CqUDpHv21a9eaicHZIwp6I79mzZqc97StVCqVM1qh7L777nLxxRfLSy+9JOvWrTOBCQAAgG9IBwKA2KHVgrTXXScD68jAYYcdZm7SdeJvx44dZcSIEQX/Tr+rvfea+rPddtuZ6kWaXqTpOzoakO7x13SkvffeO/N36TkCmuOf/d4uu+ySKXc6efJkU/1I5wno/AOdm6DpRMwJAACAasBIAADEkquvvlouu+wyU5Fnzz33lG984xsmPUhLhhZDFwG74447chYEe/DBB+VLX/qSmYScDgIGDhyYSQ1Kv5c/10Dfy04F0vSga6+9Vg444AATlLz55psya9Ys5gQAAEBVqEnpeDUAABREJ/PqTbum8AAAAMQFRgIAAEqgAcDJJ59c7Z8BAAAQKIwEAAAAAAAkDEYCAAAAAAASBkEAAAAAAEDCIAgAAAAAAEgYBAEAAAAAAAmDIAAAAAAAIGEQBAAAAAAAJAyCAAAAAACAhEEQAAAAAACQMAgCAAAAAAAkWfz/5OKtXSY8DkQAAAAASUVORK5CYII=", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "class single_generator_recipe(single_cell_recipe):\n", "\n", " def __init__(self):\n", " single_cell_recipe.__init__(self)\n", "\n", " def event_generators(self, gid):\n", " return [A.event_generator('syn', # dispatch to synapse with label 'syn' (given on `place` in the decor)\n", " 0.1, # with this weight \n", " A.regular_schedule(50))] # every 50ms\n", "\n", "rec = single_generator_recipe()\n", "run_network(rec)" ] }, { "cell_type": "markdown", "id": "8231d740-b8e3-4e8d-a37e-1983d7d73544", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "Splendid, a spike train. \n", "Now, let's make something even more interesting and connect some cells in a ring. \n", "To no surprise, this is done using yet another method on the recipe: `connections_on`.\n", "This needs to return a list of `connection`s terminating on the given `gid`. \n", "Since we want to set up a ring, each `gid` has an incoming connection from the previous one `gid - 1` with the first `gid = 0` wrapping around to the last one `gid = n -1`.\n", "We could inherit from the basic single cell recipe, overriding only the methods we want to change, but I will write a new one to comment on a few details:" ] }, { "cell_type": "code", "execution_count": 75, "id": "7fad312f-0493-4128-947a-5d39663f05bc", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [], "source": [ "class ring_recipe(A.recipe):\n", "\n", " # parametrise with the number of cells\n", " def __init__(self, num):\n", " A.recipe.__init__(self)\n", " self.num = num\n", "\n", " def num_cells(self):\n", " return self.num\n", "\n", " # ignore the gid argument, so all cells have the same kind\n", " def cell_kind(self, _):\n", " return A.cell_kind.cable\n", "\n", " # ignore the gid argument, so all cells are clones!\n", " def cell_description(self, _):\n", " # morphology\n", " mrf = A.load_swc_neuron('Acker2008.swc')\n", " # labels\n", " lbl = A.label_dict()\n", " lbl.add_swc_tags()\n", " lbl['ctr'] = '(location 0 0.5)'\n", " # decor\n", " dec = A.decor()\n", " dec.paint('\"soma\"', A.density('hh'))\n", " dec.paint('\"dend\"', A.density('pas'))\n", " dec.place('\"ctr\"', A.threshold_detector(-10), 'det') # this is a possible source for connections\n", " dec.place('\"ctr\"', A.synapse('expsyn'), 'syn') # this is a possible target for connections and generators\n", " return A.cable_cell(mrf, dec, lbl)\n", "\n", " def global_properties(self, kind):\n", " return A.neuron_cable_properties()\n", "\n", " def probes(self, gid):\n", " return [A.cable_probe_membrane_voltage('\"ctr\"')]\n", "\n", " # inject spikes only into the first cell\n", " def event_generators(self, gid):\n", " if gid == 0:\n", " return [A.event_generator('syn', # dispatch to synapse with label 'syn' (given on `place` in the decor)\n", " 0.1, # with this weight \n", " A.explicit_schedule([200]))] # one spike at 200ms\n", " return []\n", "\n", " def connections_on(self, gid):\n", " # the source of the connection is to the left\n", " src = gid - 1\n", " if gid == 0: # need to wrap on the first cell\n", " src = self.num - 1\n", " # a single connection to src\n", " return [A.connection((src, 'det'), # connection source is the detector 'det'\n", " 'syn', # the target needs only the label, not the id which is implicitly given by the `gid` argument\n", " 0.1, # weight in a.u., often uS, determined by target \n", " 25)] # delay in ms; spikes from (src, 'det') at `t` will be delivered to (gid, 'syn') a `t + delay`\n", " " ] }, { "cell_type": "code", "execution_count": 76, "id": "14c7290c-e541-4dcf-b2c7-79ca4c6dc765", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "rec = ring_recipe(10)\n", "run_network(rec)" ] }, { "cell_type": "markdown", "id": "1aeb3ed9-8785-4f5f-97ee-62b234a0c178", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "We observe that the network is quiet until at $200\\,ms$ one spike is dispatched to `gid=0` which causes the cell to spike.\n", "And $25\\,ms$ later (the delay) the spike arrives at cell `gid=1` etc. \n", "This ring network will propagate a single spike forever." ] }, { "cell_type": "markdown", "id": "9caafb61-0318-4445-a64a-f8e2888e54ed", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "# Summary\n", "\n", "We have shown how a network is built in Arbor: By listing all incoming connections per cell. \n", "This constitutes an efficient if verbose interface. \n", "However, since version `0.10` Arbor also offers a high-level language for building networks, which is more convenient and powerful in many cases.\n", "It provides probabilistic and distance-based connectivity, as well as parametrised network delays and weights. \n", "You can find more information here:\n", "\n", "https://docs.arbor-sim.org/en/latest/concepts/interconnectivity.html#interconnectivity\n", "\n", "We have also --- somewhat sneakily --- introduced how recipes can make decisions based on the `gid` argument.\n", "It is straightforward to generalise to creating populations of cells and different connectivities.\n", "Further, `recipe`s can be composed and extended using standard (object-oriented) practices like composition and inheritance.\n", "From here, you can either try the advanced single cell tutorial `03a` or take a look at the ideas below for learning more about networks." ] }, { "cell_type": "markdown", "id": "d222b3e7-a198-43ad-a894-88e60a8a5b03", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "source": [ "# Ideas\n", "\n", "- Try to create different networks:\n", " - fully connected\n", " - randomly connected (keep in mind to return different connections per `gid` while being conistent between calls)\n", " - two fully connected populations with sparse connections in between\n", " - ...\n", "- Try to make a network of different cell _types_ (LIF and `spike_source` are options available in Arbor)\n", "- Try to vary the parameters and `decor` between `gid`s and see how it affects the ring network" ] }, { "cell_type": "code", "execution_count": null, "id": "38dc3b90-5a86-4249-88ff-7cf6f222e70f", "metadata": { "editable": true, "slideshow": { "slide_type": "" }, "tags": [] }, "outputs": [], "source": [] } ], "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": "3.12.7" } }, "nbformat": 4, "nbformat_minor": 5 }