{ "cells": [ { "cell_type": "markdown", "id": "49bcb5b0-f19d-4b96-a5f1-e0ae30f66d8f", "metadata": {}, "source": [ "### `A` up-regulates `B` , by being *the limiting reagent* in the reaction: \n", "### `A + X <-> 2B` (mostly forward), where `X` is plentiful\n", "1st-order kinetics. \n", "If [A] is low, [B] remains low, too. Then, if [A] goes high, then so does [B]. However, at that point, A can no longer bring B down to any substantial extent.\n", "\n", "**Single-bin reaction**\n", "\n", "Based on experiment \"reactions_single_compartment/up_regulate_1\"\n", "\n", "LAST REVISED: July 14, 2023" ] }, { "cell_type": "code", "execution_count": 1, "id": "c1ee6c54-9795-4fca-8972-e5ed4cb84019", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Added 'D:\\Docs\\- MY CODE\\BioSimulations\\life123-Win7' to sys.path\n" ] } ], "source": [ "import set_path # Importing this module will add the project's home directory to sys.path" ] }, { "cell_type": "code", "execution_count": 2, "id": "1dc1a2e7", "metadata": { "tags": [] }, "outputs": [], "source": [ "from experiments.get_notebook_info import get_notebook_basename\n", "\n", "from src.modules.chemicals.chem_data import ChemData\n", "from src.life_1D.bio_sim_1d import BioSim1D\n", "\n", "import plotly.express as px\n", "from src.modules.visualization.graphic_log import GraphicLog" ] }, { "cell_type": "code", "execution_count": 3, "id": "cc53849f-351d-49e0-bfa8-22f8d8e22f8e", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-> Output will be LOGGED into the file 'up_regulation_1.log.htm'\n" ] } ], "source": [ "# Initialize the HTML logging\n", "log_file = get_notebook_basename() + \".log.htm\" # Use the notebook base filename for the log file\n", "\n", "# Set up the use of some specified graphic (Vue) components\n", "GraphicLog.config(filename=log_file,\n", " components=[\"vue_cytoscape_1\"],\n", " extra_js=\"https://cdnjs.cloudflare.com/ajax/libs/cytoscape/3.21.2/cytoscape.umd.js\")" ] }, { "cell_type": "code", "execution_count": 4, "id": "23c15e66-52e4-495b-aa3d-ecddd8d16942", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of reactions: 1 (at temp. 25 C)\n", "0: A + X <-> 2 B (kF = 8 / kR = 2 / Delta_G = -3,436.56 / K = 4) | 1st order in all reactants & products\n", "[GRAPHIC ELEMENT SENT TO LOG FILE `up_regulation_1.log.htm`]\n" ] } ], "source": [ "# Initialize the system\n", "chem_data = ChemData(names=[\"A\", \"X\", \"B\"]) # NOTE: Diffusion not applicable (just 1 bin)\n", "\n", "# Reaction A + X <-> 2B , with 1st-order kinetics for all species\n", "chem_data.add_reaction(reactants=[(\"A\") , (\"X\")], products=[(2, \"B\")],\n", " forward_rate=8., reverse_rate=2.)\n", "\n", "chem_data.describe_reactions()\n", "\n", "# Send the plot of the reaction network to the HTML log file\n", "graph_data = chem_data.prepare_graph_network()\n", "GraphicLog.export_plot(graph_data, \"vue_cytoscape_1\")" ] }, { "cell_type": "code", "execution_count": 5, "id": "be6fabbe-bded-4ff6-b220-5610e73b401f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SYSTEM STATE at Time t = 0:\n", "1 bins and 3 species:\n", " Species 0 (A). Diff rate: None. Conc: [5.]\n", " Species 1 (X). Diff rate: None. Conc: [100.]\n", " Species 2 (B). Diff rate: None. Conc: [0.]\n" ] } ], "source": [ "bio = BioSim1D(n_bins=1, chem_data=chem_data)\n", "\n", "bio.set_uniform_concentration(species_name=\"A\", conc=5.) # Scarce\n", "bio.set_uniform_concentration(species_name=\"X\", conc=100.) # Plentiful\n", "# Initially, no \"B\" is present\n", "\n", "bio.describe_state()" ] }, { "cell_type": "code", "execution_count": 6, "id": "5562fea2-834e-40a9-9b1d-5ea28a0100bf", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
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" ], "text/plain": [ " SYSTEM TIME A X B caption\n", "0 0 5.0 100.0 0.0 " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Save the state of the concentrations of all species at bin 0 (the only bin in this system)\n", "bio.add_snapshot(bio.bin_snapshot(bin_address = 0))\n", "bio.get_history()" ] }, { "cell_type": "markdown", "id": "0b46b395-3f68-4dbd-b0c5-d67a0e623726", "metadata": { "tags": [] }, "source": [ "### Take the initial system to equilibrium" ] }, { "cell_type": "code", "execution_count": 7, "id": "bcf652b8-e0dc-438e-bdbe-02216c1d52a0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SYSTEM STATE at Time t = 0.015:\n", "1 bins and 3 species:\n", " Species 0 (A). Diff rate: None. Conc: [0.02617327]\n", " Species 1 (X). Diff rate: None. Conc: [95.02617327]\n", " Species 2 (B). Diff rate: None. Conc: [9.94765346]\n" ] }, { "data": { "text/html": [ "
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" ], "text/plain": [ " SYSTEM TIME A X B caption\n", "0 0.000 5.000000 100.000000 0.000000 \n", "1 0.001 1.828000 96.828000 6.344000 \n", "2 0.002 0.701002 95.701002 8.597996 \n", "3 0.003 0.281916 95.281916 9.436168 \n", "4 0.004 0.123519 95.123519 9.752963 \n", "5 0.005 0.063287 95.063287 9.873425 \n", "6 0.006 0.040331 95.040331 9.919337 \n", "7 0.007 0.031575 95.031575 9.936851 \n", "8 0.008 0.028233 95.028233 9.943534 \n", "9 0.009 0.026958 95.026958 9.946084 \n", "10 0.010 0.026471 95.026471 9.947058 \n", "11 0.011 0.026285 95.026285 9.947429 \n", "12 0.012 0.026215 95.026215 9.947571 \n", "13 0.013 0.026188 95.026188 9.947625 \n", "14 0.014 0.026177 95.026177 9.947646 \n", "15 0.015 0.026173 95.026173 9.947653 " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bio.react(time_step=0.0005, n_steps=30, snapshots={\"frequency\": 2, \"sample_bin\": 0}) # At every other step, take a snapshot \n", " # of all species at bin 0\n", "bio.describe_state()\n", "bio.get_history()" ] }, { "cell_type": "markdown", "id": "7dc56592-179d-4e4c-b75a-8eb81dcafe71", "metadata": {}, "source": [ "A, as the scarse limiting reagent, stops the reaction. \n", "When A is low, B is also low." ] }, { "cell_type": "markdown", "id": "962acf15-3b50-40e4-9daa-3dcca7d3291a", "metadata": {}, "source": [ "### Equilibrium" ] }, { "cell_type": "markdown", "id": "809b4afa-fb2f-4ac3-92c9-083fc487c81b", "metadata": {}, "source": [ "Consistent with the 4/1 ratio of forward/reverse rates (and the 1st order reactions),\n", "the systems settles in the following equilibrium:" ] }, { "cell_type": "code", "execution_count": 8, "id": "064d9592-d9f6-4d12-9f54-67f75bdf72ed", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "A + X <-> 2 B\n", "Final concentrations: [B] = 9.948 ; [A] = 0.02617 ; [X] = 95.03\n", "1. Ratio of reactant/product concentrations, adjusted for reaction orders: 3.99963\n", " Formula used: [B] / ([A][X])\n", "2. Ratio of forward/reverse reaction rates: 4.0\n", "Discrepancy between the two values: 0.009347 %\n", "Reaction IS in equilibrium (within 1% tolerance)\n", "\n" ] }, { "data": { "text/plain": [ "True" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Verify that the reaction has reached equilibrium\n", "bio.reaction_dynamics.is_in_equilibrium(rxn_index=0, conc=bio.bin_snapshot(bin_address = 0))" ] }, { "cell_type": "markdown", "id": "cbf6c9c7-8cec-400f-9e70-49ff1a9f485c", "metadata": { "tags": [] }, "source": [ "# Plots of changes of concentration with time" ] }, { "cell_type": "code", "execution_count": 9, "id": "665dfff9-e943-44e1-b76d-af363d94c9f8", "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "Chemical=A
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XvnC6k+RsMbBntgX1TzPbgiQQgmcCXJR4RslAFglQ1xYlg1A8E6CuPaNkIIsEyqmudzWXE83nHZ0tic9drWrtatXOtKb0js5djegdXS3a0ZlsUqc9HlRz2TRba6trVRetU211ndMY7v3eaSgnGsl1vc3l3b+vr25IPr+r6Zw4Pvm902xONJ1Tc2R+31hb2JtAWVS+/YZSTnVdDp7EaIcAdW1HHojCe4FSN7MzG9L9rSjbntnpdzmb8+ZfvURzL5zh7LGd+jDjpxrT2e6KzvVYfV2ds2d26s7s5m0tzp3hl86ePuCd5OnrMDFM2HtP5+5s7sz2vmYLGpFmdkFsnGSpABclliaGsIoSoK6L4uNkSwWoa0sTQ1hFCZS6rje1bVRz+xZtad+k5rYtau7Y4nze2rFFm3cmntvWsU0tndv6NKz92gt5UPVgDa4dosE15t9gDalp1KCawc73Q2qHaFDNEA2tHZpoCDsN5vQ7lhN3JJvHG6oHOXcK72pAJxrLzvfJZrWZi4/SCJS6rkuzKmapdAHqutIrILzrL9dm9patLbu9gWQqS6k7sXM1rpuGJX6xnH5cZjPb3Gl97Y13aOGCC5Q6PrMaUneApz8+UAz5VhN7ZucrluV4mtkeIDKENQJclFiTCgLxUIC69hCToawRoK6tSQWBeChQTF2/u2O903ze2t6sze0be5vTm3duUnP75mRjeqs2mSZ1x2Zt79hWVOTmjmbTcB5c2+h8Hlo7TA3VDRrkNKMTDWjTmB6SfH5wTeK41OPZGtZFBcTJ1goUU9fWLorAKl6Auq74EggtQKmb2flsM7Lq6Rd7txTJbDqbZvblC5foqvkX9LkzOz1RpWhmm7uwVz74uBZfc2lvHLnuDs+3mGhm5ytGM9sDMYawWYCLEpuzQ2yFClDXhcpxns0C1LXN2SG2QgVMXZutOtY1v+s0nxN3S2/WlvbNTpN6S9smbWkzjelEc9o8bo4p9E7pYXXD1VQ/UiMgk0t1AAAgAElEQVQaRqqpboSaGkZoRP2oxPf15mvzeWSfu6VNE7qxdmihS+S8ChTg9boCk14BS6auKyDJFbrEUjezB3oDyPS9qO99cJUGamabdOXa/sOLZvZA24yk9tc+5/Tj+2xBQjPbwh8m7sy2MCmEVLAAFyUF03GixQLUtcXJIbSCBajrguk4MWABszf0m9vW6c3ta/Vmyxt6c+sbia+3v6G3tq9Ta1dL3hGaN+FLNaOb6kaqKdmMNg3pkQ2jnSa1eT7RpE40qofXNSkaieY9FycgkK8Ar9f5inF8OQhQ1+WQJWIsRKDUzWwTY+rNHZfdMK+3CZxqGu8zbg/nbuxczWyz5Ue2u6JNA/ut9e/1u191rgZ35jYjJl4zzxOrX+5908pU033aiR/Soh/9r/bcY4Tz5pHmI/NNJ9kzO8+qNMXxxlvv9oKmTk8VyPMvrXEeSi+e9KIyX5964pQ+t/Sbx2hm55kIDrdagIsSq9NDcAUKUNcFwnGa1QLUtdXpqejgeuI9Wt/6L6cxbRrU67au0VumaW2+37ZWG9veG9Cnvrpew81d0ubOaOeOadOcTtwlnWpGZ95JzZ3SFV1y1i+e12vrU0SABQhQ1wWgcUpZCATRzDYwqTu039mwudcptc90qjc50J3Zqf2rU43x1CBjx4zs3fIjV+PazZ7ZqXFNQ/vm21fuFmtmj9WsIfVhGtw0s13+GKRvPJ5eCOb01C3wqXflNMWTvsdMJnL6rfGp6Wlmu0wEh5WFABclZZEmgsxTgLrOE4zDy0KAui6LNIU2yM3tm/TWtjcSd1Zve0Prtpk7q82/dVrf+pa6Y939rt3cRT1uyN4aP2yC9m6coPHD9tU+wyZon8YJOnjMfho5aLRadnaF1o6FVZ4Ar9eVl/NKWDF1XQlZrsw1BtXMrkztwlZdUXtmZ7szO/NdODOb26Z5PWHvPZ3b8c1Htt8g0MwurPg4y04BLkrszAtRFSdAXRfnx9l2ClDXduYlLFG1de907qxet32t3jJ3V5vGtWlWb3tDb7Ws046u1gGXOrphD+09bILGD002rIdP1D7m66HjNW7I+1QVqcp6PnUdlgpiHekC1DX1EEYB6jqMWWVNRoBmtv11UPHN7GzN6dTd13PO/7SuuHapUndtm3Rm3rltHqOZbX+hE6F7AS5K3FtxZPkIUNflkysidS9AXbu34sjsAqYhvXrD006T+o1ta5zmtWlUm21BzJ3XA30Mqh6svYeN1/ih+yburh5uGtcTtXfjeI0fvq/qqxoKYqeuC2LjJMsFqGvLE0R4BQlQ1wWxcVIZCNDMtj9JNLNXv6w7VzzUZx/szGZ2+rtw7tbMXvw+9dQ2KTZ0X8UaJyg+fJLz2XwfN99XF3Yhb3/pEGFYBeqqo1JE6uiKhXWJrKtIgXhcikYjRY5S2tOp69J6M1tpBKjr0jiHaZan33lSz7z7lJ5a/4T+vuFZvbjpHwMuz2wDMmHYRE0YPkEThu+b/NpsCTJeowft4QsNde0LK4MGLFCudR2LxRSJlNc1X8Cprqjpy7WuKypJLLYggaGDago6j5NKJ0Aze/XLum7x8t534DT0ed2Zfd3A/3GPN+yh2NCJiQb3sH0VN01up/G9r2JD9pL6+RPL0pUAMyHQV6C2JirTze7s6oEGgawCMdPMLrP/X0NdU8xhFKCuw5hV79b0+tbX9NyG1Xr87b/pyXee0JPrH886+AfHHK79m97vNKtN83pi0yTtM3S883UQH9R1EOrM6bdAudZ1OV7z+Z1Lxt8lUK51TQ4RyCXQSDM7F1Hgz1d8M7voPbM7tmrjupdU3fKGqlrfUFXLWlW3rFVV6zrnXyTW2W+S49Ea9QzaWz2N49VtmtuN+6q7cbx6hpjPExSrGxl4gRBA5Qnw52KVl/NKWDF1XQlZrrw1UteVl/P+Vry1vVlPb3hcz777pJ7d8JRWv/eUzGOZH3s17q3D9zhah+9p/h2lD+5xRMHbgfilT137Jcu4QQpQ10HqM7dfAtS1X7KMG7QA24wEnYHc81d8MzvzDR8ztxHJ3FM7ddf2JbOn9+r2v2d2XFU71qu6da2qWtapqmWN0/Cu3p5sfLe9Kynef7O7eoi6h0xQT+MEp9ndM3RCotHtPDZe8QL3IsxdFhxRyQJclFRy9sO7duo6vLmt5JVR15WZ/Y6edj238Vmt3vCUnnnnSefzmy1v7IbRWDtUk8cc2du8Pnrsh9RUP8J6NOra+hQRYAEC1HUBaJxivQB1bX2KCLBAAZrZBcKV8LSKaGabhvTMixb1YV12wzwdPflA57HmbS2aM+96Pf/SGuf79OfM93etfFjfvmap89ypJ07ps7+2eayYN4Cs3vqKqnesU9X2NYm7up27u9epumWNIt0Dv0t8rH4PdTdOVM+QfRIN7mET1TnmI+punFTCEmKqsAlwURK2jLIeI0BdUwdhFKCuw5jVvmuKK65/bnlZz2x40rnr2jSuX97yD3XHuvscWB2t0QdGHarJY47SEWOOcT5PatpfEfMmGGX2QV2XWcII15UAde2KiYPKTIC6LrOEEa5rAZrZrqkCO7Aimtl+6xbTzB4otmj7lsRd3eZu7pZ1irasSTS7t7+h6tZE493th7mLO149WLGaRudzvHaY8+aUsZohitcMVry6UbGawZJ5vibtuJohilWbY4YkzqtJHBevHuJ2ao4rMwEuSsosYYTrSoC6dsXEQWUmQF2XWcJchPtO69uJO65N83rDU3r+vWfU2rX7zQ3jh07UEXseldguZI+jdejoyaqpqnUxg/2HUNf254gI8xegrvM34wz7Bahr+3NEhIUJ0MwuzK2UZ9HM9kDbr2Z2rtCqWt9MNLedBndir+7ozncU7dymSPcORbtaFOnaoUjPjlxDFfS8aWjHnAb37o1u85jTBB88Tp2jjy5ofNcnRcxmLVEpWiWpSopEFTdvrBlJPBZPPtb7vXnceSx5rDkvnjzWeSziPBevqncdQpgO5KIkTNlkLSkB6ppaCKMAdV3eWd3R1arVG57Ws07jOtG83rDjnd0WNaJ+pD64x5E6YuwxOnzMUTpqzykyW4iE9YO6DmtmK3td1HVl5z+sq6euw5pZ1kUz2/4aoJntQY6CambnE3qkq1XR7laZz6bR3ef73ud2SF0tijrHmGPTGuLJ85wGuTm/py2f6UN1rLNXuWl2m6a48y/RGE98X5VoqsejipvPyWOc5nqq4Z5+rPN1soFu/hTYOd78SbBpyJume/L73nHMY4nnU2Mb3F2xRM03yYZ+6pjkuGbM3vN2zZV4bNeYtbU1zhydXT2hyhuLqWwB3m29svMf1tWbuo6P+IC2jDszrEsM3bp++8/lemjdn5zm9WvNr2Zd3xF7HuM0rA/b4wgdPuZITRhWWdvH0RwJXdmzILY7owZCKsDrdUgTy7JEM7tvEaS2bv7uZbN01rSpVlQIzWwP0lAOzWwPlrnbENHO7b1N74hpgpsmd7Jhnt4QV0+nFO9x/kUUk2KxxNfxmKQeKWaeiylijjHPm+ecx+KJ85Q81nkseaw5z5xvzkue74yVGjd1rJLjmrFiZv7UeYl5e2PoPc/EFKvoZr0ftcKYCCCAAAL+CTR//Ha1jaeh7Z9wcSM/v3G1lr94q+585Ta1dG7vM9ik4fs7W4Wk9rn+4B5HFDdZCM6mORKCJLKE3QSoa4oijALUdRizypqMAM3svnXwg8XLnQfefW/Lbu8hGFTF0Mz2QL5Sm9ke0JXdEM4d6U5DPd6nie404k1z3TTRU81381gslmjgp553mua7GuqJr03TPtGYd/5F4okme+qfEs8nGu/m367jI865ye8jyea+c17amM788WQcyXGdMdLmiew6vrYqzp3ZZVeZBJxLgDuzcwnxfDkK1MVbVfvcDxWP1mvztPvUOeqoclxGKGPe2t6sX71ym+548ed6afMLvWscM3isph/4BX3kfcfriD2P1uAa3oMkswBojoTyR6LiF0VdV3wJhBKAug5lWlkUzew+NdC8rUULf3ibvn7+mbrmx7dr7oUzNGn8uMDrhGa2Bymgme0BIkNYI8BFiTWpIBAPBahrDzEZyhoBU9e1z35fdasWKFY3UhvPeFQ9g8dbE1+lBRKLx/TwWw/o9n/8TH984x51mb9Mk1RXVa9PTjxdnzvoSzpu748r6mwjxkd/ArxeUxthFKCuw5hV1kRdUwNhFQjszuy1a6V160rPOnGitM8+Wec1W4w88vhzumT2dJk7tCfsvacVW43QzPagTGhme4DIENYIcFFiTSoIxEMB6tpDTIayRiBV11V/nKVBr9+q7sb9tPGMxxSvabQmxkoI5M3ta50GttlG5J3Wt3uXPHnMUZpx0Jf06fdPD/UbNnqdY16vvRZlPBsEqGsbskAMXgtQ116LMp4tAoE1sy+/XLr66tIzXHWVtGBB1nlNA/u4Yw/T0ZMPlGlsX7d4uW5adLGahgX7/zdoZntQJjSzPUBkCGsEuCixJhUE4qEAde0hJkNZI9Bb1zvaNfIP01S34RF1jDlOWz5xj+JR82a+fPgl0Na9U/e89hvd/uLP9Pj6R3unGT1ojD57wLk69wNfltkPm4/8BXi9zt+MM+wXoK7tzxER5i9AXedvxhnlIRBYM/unP5Vuu630SF/9qnTeebvN+/q69br2xju0cMEFTvPabDkyZ971unT2dKe5HeQHzWwP9Glme4DIENYIcFFiTSoIxEMB6tpDTIayRiC9rs0bMY++Z6qqt72itn2nq/ljy6yJM0yBPP3u404De8U/f6XWrlZnaTVVtTp5wjR97qAv6uPjT1FVpCpMSy75Wni9Ljk5E5ZAgLouATJTlFyAui45OROWSCCwZnaJ1ud2mrtWPqxvX7N0t8O/cu40Z9uRID9oZnugTzPbA0SGsEaAixJrUkEgHgpQ1x5iMpQ1Apl1XbXjbY3+3RRFOzarZfLlzj8+ihfY1LZRy1/6X/3ypZ/pteZXewc8ZNQH9bmDv6iz3n+uhtc3FT8RIzgCvF5TCGEUoK7DmFXWRF1TA2EVoJkttbV36oprl2rKkQf32SM7827toGqAZrYH8jSzPUBkCGsEuCixJhUE4qEAde0hJkNZI5Ctrms2PaNR956sSE+bmqcuU9vEYO+asAYrz0C6Y926/417dceLP9Of37xP5nvzMaJ+pD7z/hn6/CEzdeCID+Q5Koe7EeD12o0Sx5SbAHVdbhkjXjcC1LUbJY4pRwGa2ZJpWl++cImumn+BJo0f15vGVJP7nNOPD3SrEZrZHvxk0cz2AJEhrBHgosSaVBCIhwLUtYeYDGWNQH91Xf+vezXi/s8qHq129s82+2jz4U7g1S0vOw3sX7/yC5k7ss1HdbRaH9/nFM04+Es6acKnVM1+5O4wCzyK1+sC4TjNagHq2ur0EFyBAtR1gXCcZr0AzWzrUySa2R7kiGa2B4gMYY0AFyXWpIJAPBSgrj3EZChrBAaq6yEv/FBDn5qneE2jNp7+mLqH7mdN3LYFYva+/u2rv3T2wl694ane8N4/4iCngX32AZ/XqIbRtoUd2nh4vQ5tait6YdR1Rac/tIunrkOb2opfGM1s+0uAZrYHOaKZ7QEiQ1gjwEWJNakgEA8FqGsPMRnKGoFcdT3sb9/S4FeWqGfIeG08/VHF6kZaE3vQgcQV19/efkS3v7hMK1+7W+09bU5Iw+qG69Pvn+68meMH9zgy6DArcv5cdV2RKCy67AWo67JPIQvIIkBdUxZhFaCZbX9maWZ7kCOa2R4gMoQ1AlyUWJMKAvFQgLr2EJOhrBHIWdfxmEb+6QzVrX9QXSOP0KZTH1A8WmdN/EEEsr71X1r+8v/ql//4ud5secMJIRqJaureJzpv5vipfc9QTVVtEKExZ1IgZ10jhUAZClDXZZg0Qs4pQF3nJOKAMhWgmW1/4mhme5AjmtkeIDKENQJclFiTCgLxUIC69hCToawRcFPXke4dGnXPx1Wz9QW1jf+0mj9+m6SINWsoRSBdPZ1aueZuZy/sR//1kGLxmDPtxOH7O3dgf/bAz2vPwbve2KYUMTFH/wJu6ho/BMpNgLout4wRrxsB6tqNEseUowDNbPuzRjPbgxzRzPYAkSGsEeCixJpUEIiHAtS1h5gMZY2A27quatugUXdPUVX7BrUecrG2H3WVNWvwMxCzdcjCv16hX770c7V0bnemGlwzRGfs/1nnLuyj9/yQn9MzdoECbuu6wOE5DYFABKjrQNiZ1GcB6tpnYIYPTIBmdmD0rif2tZndvK1Fc+Zdr+dfWrNbQIceNFE3LbpYTcMaXQdr64E0s23NDHEVIsBFSSFqnGO7AHVte4aIrxCBfOq6pvkF5w7tSM8Obf3oYu3c74uFTFk256zd9ppm/f5zenXLS07MH95rqs49eKam7Xem6qsaymYdlRhoPnVdiT6suTwFqOvyzBtRDyxAXVMhYRWgmW1/Zn1tZv9g8XJH4JLZ0+2XKCJCmtlF4HGqdQJclFiXEgLyQIC69gCRIawTyLeuzd7ZI+87Q4pEtPnku9Ux7gTr1uRFQPe+frcuuv8CtXa16oTxn9Ci43+ovRr39mJoxiiBQL51XYKQmAKBogWo66IJGcBCAerawqQQkicCNLM9YfR1EN+a2eau7PlXL9HcC2do0vhw70NIM9vXGmXwEgtwUVJicKYriQB1XRJmJimxQCF1PfjlJRq26luKVw3WptP+rK6mQ0octX/T9cR7dNVj/1eLV/+X86aOlxxzuS46ep4iFbZHuH/CpRm5kLouTWTMgkDhAtR14Xacaa8AdW1vboisOAGa2cX5leJsmtkeKNPM9gCRIawR4KLEmlQQiIcC1LWHmAxljUChdT3sibka/OKP1VM/RpvOXKWehjHWrKnQQDa3b9Kse6brqXdXaWjdMN30yVt1/N4nFToc5wUoUGhdBxgyUyOQU4C6zknEAWUoQF2XYdII2ZUAzWxXTIEe5Fsz26zKbDMyYe89dda0qYEu0u/JaWb7Lcz4pRTgoqSU2sxVKgHqulTSzFNKgYLrOh7TiAfOUf2/7lXX8EOcO7Tj1YNLGbqnc5kG9ldXnquNOzfo4JGH6pbT7tT7GvfxdA4GK51AwXVduhCZCYG8BajrvMk4oQwEqOsySBIhFiRAM1tqa+/UFdcu1ZQjD+7T031y9cuav3CJFl9zaaC7cPjazH593Xrddtf9mjtnhhrqawsqonI4iWZ2OWSJGN0KcFHiVorjykmAui6nbBGrW4Fi6jrS06ZRKz6mmq0vOHtnbz75d1Ik6nZqa45b8vcf6XuPXa7uWLfOPuBcff/EG1UbrbMmPgLJX6CYus5/Ns5AoDQC1HVpnJmltALUdWm9ma10AjSzE9aZ20eb7+fMu16Xzp6uoycfWLqEZJnJt2Z2apHPv7Qm6wIPPWiiblp0sZqGNQYK4MXkNLO9UGQMWwS4KLElE8ThpQB17aUmY9kiUGxdV7Vt0KgVH1XVzre144ALtO1D/2XL0nLGsbN7h/7tjzN139rfq6aqVt897vv64iFfzXkeB9gvUGxd279CIqxEAeq6ErMe/jVT1+HPcaWukGb2rsybO7HvXPGQrpw7S/c+uEpvvPWuLpk9PfDS8K2ZHfjKShgAzewSYjOV7wJclPhOzAQBCFDXAaAzpe8CXtR19dZXNHrFRxXp2aHtRy1S6yHf9D3uYidYu+01ffF3Z8l8HjtkLy09dbkOG314scNyviUCXtS1JUshDAR6BahriiGMAtR1GLPKmoxAYM3sbWul7etKn4RhE6Wh/W/RZ7aQbt3ZrvXvbtLCBRdYcVMyzWwPyoRmtgeIDGGNABcl1qSCQDwUoK49xGQoawS8quu69Q9q5J/OlOIxbTnpV2p/36esWWNmIL9//Te66E9fk7kz+9ixH9HNp/5STfUjrI2XwPIX8Kqu85+ZMxDwT4C69s+WkYMToK6Ds2dmfwUCa2Y/ern0+NX+Li7b6B+9Sjp2Qb/z2rS9SCpI35vZ5pb0mRct6oOy7IZ5ge+v4mV10Mz2UpOxghbgoiToDDC/HwLUtR+qjBm0gJd1Pei1WzX80dmKVzVo06f+pK5RRwS9vD7zmz2x//PR+br5uR87j885/CLN//B3VRWpsipOgilewMu6Lj4aRkDAGwHq2htHRrFLgLq2Kx9E451AYM3s538qvXSbdwtxO9KhX5UOOq/fo82d2a+8/pa2teywZrtoX5vZppF93eLlfRZr3hRy9mXX6cLzz+zzjphujW08jma2jVkhpkIFuCgpVI7zbBagrm3ODrEVKuB1XQ996nINeeF6xepGauMZj6pn8PhCQ/P0vI07N2jm78/R6g1PaVD1YP3w5J/qU5PO9HQOBrNHwOu6tmdlRFLJAtR1JWc/vGunrsOb20pfWWDNbAvh0/fMvulnv3UiDPWe2W3tnbri2qU65/Tjd7sLOx2job7WwnTlFxLN7Py8ONpuAS5K7M4P0RUmQF0X5sZZdgt4X9dxjbj/s6r/173qbtxPG894TPGaYN+o+6l3V2nWPdO1uX2TJg3fX7ec9ivnMx/hFfC+rsNrxcrKR4C6Lp9cEal7AeravRVHlpcAzexEvsz2IvOvXqK5F87QpPHjnO/nzLtel86eHvhuG77dmZ256PTSNXdnX3vjHdZsHF7sjxXN7GIFOd8mAS5KbMoGsXglQF17Jck4Ngn4UdeRnjaNWnmyajY/o44xx2nLJ+5RPFoTyLJvevYGLfzrt9UT73HuxDZ3ZJs7s/kIt4AfdR1uMVZXDgLUdTlkiRjzFaCu8xXj+HIRoJktpW5QnnLkwX121TA3J89fuESLr7nUaXAH9eFbM5s7s4NKKfMiUJwAFyXF+XG2nQLUtZ15IariBPyq62jHZo1e8VFVta5T277T1fyxZcUFmufZrV2t+sZ9X9Z9a3/v7Im94MPf09cP/1aeo3B4uQr4Vdfl6kHc4RCgrsORR1bRV4C6piLCKkAz2/7M+tbMNku/a+XDWr7iIfbMtr8OiBCBXgEuSiiGMApQ12HMKmvys66rt7+m0Ss+okhXi1omf1stk+eXBPyfza/oS7/7jN5seUMj60dpyam369ixHynJ3Exih4CfdW3HComiEgWo60rMevjXTF2HP8eVukKa2fZn3tdmtlm+uQV95kWL+kgsu2Fe4PureJkathnxUpOxghbgoiToDDC/HwLUtR+qjBm0gN91XbfhEY3442mKxLrUPHWZ2iZO93XJv3/9N/rmfV9Ve0+bjtjzGN087Q7tMWhPX+dkcPsE/K5r+1ZMRJUgQF1XQpYrb43UdeXlvFJWTDPb/kz73sy2n6D4CGlmF2/ICPYIcFFiTy6IxDsB6to7S0ayR6AUdd2wZrmaHp7p7Ju9+ZP3qXOPYz0H6I5164pH5mrZ84udsb90yAX67tTrVB2t9nwuBrRfoBR1bb8CEYZNgLoOW0ZZjxGgrqmDsArQzLY/szSzPcgRzWwPEBnCGgEuSqxJBYF4KEBde4jJUNYIlKquG5+5Uo3P/T/Faodr02kPq3vofp4ZvLtjvb6ycoZWb3hKtdE6ff/EG3X2Aed6Nj4DlZ9Aqeq6/GSIuJwFqOtyzh6x9ydAXVMbYRWgmW1/Zmlme5AjmtkeIDKENQJclFiTCgLxUIC69hCToawRKGVdN/3582pY91v1DBmvjaf/TbG64UU7rFr/iNPI3trerPc17qNbTrtTB488tOhxGaC8BUpZ1+UtRfTlJEBdl1O2iNWtAHXtVorjyk2AZrb9GfO8md28rUVz5l2vL3/uk7rll3/Q8y+tyapw6EET+7wxpP1U/UdIM7ucs0fsmQJclFATYRSgrsOYVdZUyrqOxDo08t5Pqnbj4+ocfaw2f+oPikfrCk7Cfz/9fV2z6kr1xHt0/N4n6aZP3qqhdcMKHo8TwyNQyroOjxorsV2AurY9Q8RXiAB1XYga55SDAM1s+7PkeTM7tWTT1J5/9RLNvXCGJo0f10fCvCnknSse0pVzZ6mhvtZ+pRwR0swu+xSygDQBLkoohzAKUNdhzCprKnVdRzu2avSKD6mqdZ3axn9azR+/TVIkr0S0drXq6/d+QX9+8z5FFNHFR8/XJcde7nzNBwJGoNR1jToCpRCgrkuhzBylFqCuSy3OfKUSoJldKunC5wmkmf36uvW69sY7tHDBBWoa1lh49JacSTPbkkQQhicCXJR4wsgglglQ15YlhHA8EQiirqu3v6ZR90xVtHOrWg+5VNuP+q7rtby85R/68opz9GbLG85d2OZubHNXNh8IpAsEUddkAAG/Bahrv4UZPwgB6joIdeYshQDN7FIoFzdHIM3su1Y+rFVPv8id2cXljrMR8EWAixJfWBk0YAHqOuAEML0vAkHVde17j2vkH05RJNalrR9drJ37fTHn+n7z6nJdcv9sdcY6nH2xzf7YZp9sPhDIFAiqrskEAn4KUNd+6jJ2UALUdVDyzOu3AM1sv4WLH9/zZra563r2ZdfpnQ2b+41u7JiRWnzNpbttP1L8coIZgTuzg3FnVn8EuCjxx5VRgxWgroP1Z3Z/BIKs64Y1y9X08EwpUqXNJ9+tjnEnZF1kV0+nvv3Iv+vWF37qPH/2Aefq+yfeqNoi9tv2R5NRbREIsq5tMSCO8AlQ1+HLKStiWyhqILwCNLMTuTVbRM+8aFGfRH/l3Gm6ZPb0wJPveTM7taKB9swOfNUeB0Az22NQhgtUgIvtQPmZ3CcB6tonWIYNVCDoum5cfZXMv3jVYG08/VF1Dz+gj8e7O9br/BVn64VNf1dNVa2u/Og1Ov/QrwVqxuT2CwRd1/YLEWE5ClDX5Zg1Ys4lQF3nEuL5chWgmb2rmX3d4uW6adHFzhbRps87Z971unT2dB09+cBA0+tbMzvQVZV4cprZJQZnOl8FuCjxlZfBAxKgrgOCZ1pfBWyo66a/zFTD2uXqGbSXNp3+qHoaxjhrXrX+EX1l5UaSo+oAACAASURBVAxtbW/WHoP21M3T7tARex7jqweDh0PAhroOhySrsEmAurYpG8TilQB17ZUk49gmQDM7ezO7rb1TV1y7VFOOPFhnTZsaaNpoZnvATzPbA0SGsEaAixJrUkEgHgpQ1x5iMpQ1AjbUtdk3e+S9p6h24+PqGn6INp7+kG549oe67vHvKRaP6dixH9GSU2/XyPpR1rgRiN0CNtS13UJEV44C1HU5Zo2YcwlQ17mEeL5cBYJqZq/dulbrtq4rOdvEponaZ9ju72VjthnJvDN7/tVLNPfCGYFvG+1rM3ug/bMPPWhi763qJc+UxxPSzPYYlOECFeCiJFB+JvdJgLr2CZZhAxWwpa6jHVs16p6p2tHyms6Kj9SDOxLvm/L1w7+lBR/+nqoiVYE6MXl5CdhS1+WlRrS2C1DXtmeI+AoRoK4LUeOcchAIqpl9+YOX6+pHri450VUnXKUFxy3Ybd5se2bb8h6IvjWz028//+AH9tNtd92vuXNmqKG+Vj9YvFzHHXtY4HuseFUhNLO9kmQcGwS4KLEhC8TgtQB17bUo49kgYFNdV7eu1b/ffoRu7ejQkEhEiyedopOPvUpdTQfbQEUMZSRgU12XERuhWi5AXVueIMIrSIC6LoiNk8pAIKhm9k+f+alue/62kgt99Yiv6rxDz8vazE6/M9sckHm3dsmDTU7oWzM7/Q0gzVzX3niHFi64wNk03Cz+zhUP6cq5s5zmdrl/0Mwu9wwSf7oAFyXUQxgFqOswZpU12VTXG9ve0+SbJzhJ+ccg6eBoIj+do45U2/4ztXPS5xSvHkLSEMgpYFNd5wyWAxBwKUBdu4TisLISoK7LKl0Em4dAUM3sPEIsyaHZGtfpvd5J48eVJI5sk5SkmT1ieKMW/vA2zf/meU4z22w/kt7cDmz1Hk1MM9sjSIaxQoCLEivSQBAeC1DXHoMynBUCNtX19U9cre8/8T2dtt9ndPOHvqNBry7VoNd+oWjHRsfKNLLbJpytnQd8WZ2jeSNIKwrI0iBsqmtLiQirDAWo6zJMGiHnFKCucxJxQJkK0MxOJC5bMzv0d2Znvsul2Vpkwt57Ou94edfKh7Xq6Re5M7tMf7AJO9wCXJSEO7+VujrqulIzH+5121LX3bFuHXXLfjJ3Z9911p907LiPJOBj3Wp46/dqePUW1b99v3nAebhr+MFqO+DL2jnpC4rVDgt3klhd3gK21HXegXMCAgMIUNeURxgFqOswZpU1GQGa2bua2TMvWtSnKGx5/0Pf7szO/BEwt6LPmXe9nn9pjWzZMNyrH1PuzPZKknFsEOCixIYsEIPXAtS116KMZ4OALXV916t36Bv3zdL+TQfoofOezUpTtXO9Br12qwa98jNV7XjDOSYerVP7Pmc4d2t3jP2YpIgNrMQQsIAtdR0wA9OHTIC6DllCWY4jQF1TCGEVoJltf2ZL1sy2n6LwCGlmF27HmfYJcFFiX06IqHgB6rp4Q0awT8CWuj7ljin6x6bn9IMTf6LPHfSlHFBx1b3zFw165RbVv/k7RWIdzvHdQ/ZV2wEztXO/L6mnYYx92ERUMgFb6rpkC2aiihCgrisizRW3SOq64lJeMQummW1/qn1rZtuyKXgpUkAzuxTKzFEqAS5KSiXNPKUUoK5Lqc1cpRKwoa6f2fCkTr/zYxpe36RnZ61RbbTO9fKjndvUsOYXGvTyLarZ+kLivEiV2vf6hHYeMEvt7/uE8z0flSVgQ11XljirLYUAdV0KZeYotQB1XWpx5iuVAM3sUkkXPg/N7MLtes+kme0BIkNYI8BFiTWpIBAPBahrDzEZyhoBG+r63/44U7/953J986jL9H+mfKdgm5pNz2jQq7do0NrlinS1OOP0NIzVzv2+oJ0HfEU9Q/YpeGxOLC8BG+q6vMSIthwEqOtyyBIx5itAXecrxvHlIkAz2/5M+dbMNks3b/p43LGH6ejJB9ovUUSENLOLwONU6wS4KLEuJQTkgQB17QEiQ1gnEHRdmzd8NG/8GIvH9MysNRrdsEfRRpGeNjWs/Y3T2K5977HkeBFnT+2d7/+y2vc5U/Gq2qLnYQB7BYKua3tliKycBajrcs4esfcnQF1TG2EVoJltf2Z9bWa/vm69brvrfs2dM0MN9eH9Px40s+0vdCJ0L8BFiXsrjiwfAeq6fHJFpO4Fgq7rax//rm54cqHO2P+zuukTP3cfuMsjq1teV8Mrt2jQa7epqn2Dc1asboR2TjxXOw/8mrqH7e9yJA4rJ4Gg67qcrIi1fASo6/LJFZG6F6Cu3VtxZHkJ0My2P1++NbPNntlz5l2v519ak1Xh0IMm6qZFF6tpWKP9SjkipJld9ilkAWkCXJRQDmEUoK7DmFXWFGRdd8Y6dPjSidra3qy7z35QR42d4l9C4j2qf+te527t+rfvk+I9zlydo49x7tZum3iO4lWD/JufkUsqEGRdl3ShTFZRAtR1RaW7YhZLXVdMqituoTSz7U+5b81s+5fuXYQ0s72zZKTgBbgoCT4HROC9AHXtvSkjBi8QZF3f+fL/6qL7v6YPjDpM981YVTKMqrYNGvTPW9Xw6jJVtyZumIhXD9HOfc9R2wFfVueoo0oWCxP5IxBkXfuzIkZFQKKuqYIwClDXYcwqazICNLPtrwPfmtnmzuz5Vy/R3AtnaNL4cX0knlz9su5c8ZCunDsrFNuP0My2v9CJ0L0AFyXurTiyfASo6/LJFZG6Fwiyrk+5Y4r+sek53XDSEp1z4Hnug/bwyLp3H1HDq0vV8MbdisTanZG7hn/AaWrvnHSeYrXDPJyNoUolEGRdl2qNzFN5AtR15eW8ElZMXVdClitzjTSz7c97IM1ss5f2tTfeoYULLmCbEftrhAgrTICLkgpLeIUsl7qukERX2DKDqusn1v9Vn7nrJA2vb9LfZ61TdbQ6UPlo53Y1rLnD2YakZsvfnVji0Xq1jz9DOw+YpY49pwYaH5PnJxBUXecXJUcjkJ8AdZ2fF0eXhwB1XR55Isr8BWhm529W6jMCaWbftfJhrXr6Re7MLnW2mQ8BFwJclLhA4pCyE6Cuyy5lBOxCIKi6nv2HL+ie1+7SRUfP19xjv+0i0tIdUrPlOQ16dakGvX67Il0tzsSdo49VvKZRnSMnq7vpEHU3HayupkNKFxQz5SUQVF3nFSQHI5CnAHWdJxiHl4UAdV0WaSLIAgRoZheAVuJTPG9mm7uuZ192nd7ZsLnfpYwdM1KLr7l0t+1HSrx2z6ZjmxHPKBnIAgEuSixIAiF4LkBde07KgBYIBFHXG9ve0xFLJyoaieqpL7+m0Q17WCCRPYSGtcud/bVrNz7R29hOP9Lsr909/APqGvlBdY04VF0jJytePdja9VRKYEHUdaXYss7gBKjr4OyZ2T8B6to/W0YOVoBmdrD+bmb3vJmdmnSgPbPdBFZOx9DMLqdsEWsuAS5KcgnxfDkKUNflmDViziUQRF0v+tsV+tHT1+rT+0/Xjz+xLFeI1jxf1fqGajf/XdWbV6tm89+d7Uiq2t7JiC+i7iET1DXyMHWPOExd5l/ToeoZso8166iEQIKo60pwZY3BClDXwfozuz8C1LU/rowavADN7OBzkCsC35rZuSYO0/M0s8OUTdbCRQk1EEYB6jqMWWVNpa7rzliHDl86UVvbm7XinL/oiDFHl3USoh2bVLN5daLJvWm10+Cubnnd7LjdZ13mjSS7mhLN7e6Ryc/DD1Y8WlPW67c1+FLXta0OxBUuAeo6XPlkNQkB6ppKCKsAzWz7M0sz24Mc0cz2AJEhrBHgosSaVBCIhwLUtYeYDGWNQKnr+vYXl+nfH7xQHxh1mO6bscoaBy8DiXS3yuy7bRrbNRuTDe5tLykS6+o7TaRaXcMOcLYn6TbblJhm98jDFasb7mU4FTlWqeu6IpFZdMkFqOuSkzNhCQSo6xIgM0UgAjSzA2HPa1Jfm9lmq5E5867X8y+t2S2oQw+aqJsWXaymYY15BWzjwTSzbcwKMRUqwEVJoXKcZ7MAdW1zdoitUIFS1/Xxtx2ufza/oh+dslRnvX9GoWGX3XmRnk5Vb30x0eDu3abkeUV6duy2lp6GsYntSdKa3N3D9pMUKbt1BxVwqes6qHUyb2UJUNeVle9KWS11XSmZrrx10sy2P+e+NrN/sHi5I3DJ7On2SxQRIc3sIvA41ToBLkqsSwkBeSBAXXuAyBDWCZSyrv/69sM65zefdN7w0bzxY3W02jqPUgdUve1V1TQ/r5pNTyfu5t78rKIdzVnD6Bx9rLqGH+zcxd0+/gz1NOxZ6nDLZr5S1nXZoBBo2QtQ12WfQhaQRYC6pizCKkAz2/7M+tbMLqc3gDRN95tvX9knW9+9bJbOmjbVeeyulQ/r29csdb4+9cQpunLuLDXU1/YeTzPb/kInQvcCXJS4t+LI8hGgrssnV0TqXqCUdf3VlTN075rf6dJjLtclx1zuPsgKO7Jqx78SDe7Nz6pm07NOk7tqx1v9KvTUj3HeYLJn0FjFBu2lniHvU0/yc2zQWHUP2bfCBNmDteISXiELLuXrdYWQskwLBKhrC5JACL4I0Mz2hdXTQWlmSxroDvInV7+s6xYv790SJduxNLM9rUkGC1iAi5KAE8D0vghQ176wMmjAAqWq63da39YxPztA0UjUuSvb3J3Nh3uBaMfWtC1KnlVVy+uqbnlT0Y6NrgaJ1Y1Wd+M+ijXsqZ7Beyk26H3O557B5vM4dTdOcjVOuRxUqrouFw/iDIcAdR2OPLKKvgLUNRURVgGa2fZn1rdmtlm6afxO2HvP3jucbeUYqJmduYbM5rZZE81sWzNLXIUIcFFSiBrn2C5AXdueIeIrRKBUdf3dxxboJ8/eoLMPOFc/PPnmQkLlnCwC5k0lo23rVbXjbZk7uqt2rFe09V+qajPfJ/+1bZAUy+kXqxuZuKPbaXLvpZhpdPc2vcepZ/DeilfV5xzHhgNKVdc2rJUYKkeAuq6cXFfSSqnrSsp2Za2VZrb9+fa1mf36uvW67a77NXfOjD7bctjGkrnNSGqLkbb2Tl1x7VJNOfLg3oa8WdPlC5foqvkXaNL4cc5SaGbbllHiKUaAi5Ji9DjXVgHq2tbMEFcxAqauIxve1faho4oZZsBz27p36vCl+6qls0X3zVilD4w6zLe5GDi7QFXrW6rauV5VO03D++1Ew3vn26ra+Y6zhYn52s1HrHZYsuGd2MokZrY0GbyXukZ80Plnywev17Zkgji8FKCuvdRkLFsEqGtbMkEcXgvQzPZa1PvxfGtmmz2z58y7Xs+/tCZr1IceNLF36w7vl1X4iKZZPfuy67Rw/gU65MCJTjP7nNOP19GTD3QGzdbMLnw2zkQAAQTKT6CzO6ba6mj5BU7ECIRN4JOflP74R+nmm6VZs3xZ3eKnF+vr93xdU943RX/7yt98mYNBPRBofVtq+VfiX6v5t17a/qbkPP6mtH1dfpNUD5bqh0t1w6X6EVJtY/Jr8/3IXd/XDZMaRkm1QxLPm3+D2IYmP2yORsBeAa757M0NkSGAAAKVLOBbM7ucUVNbi3zqhCncmV3OiST2ggT4DXtBbJxkuQB1bXmCCK8ggXGjBvWet/lX96jj+BMKGmegk46/7XD9s/kV3XjKz3Tm+8/xfHwGLJ1AVdsGRc32JeaubnOHt9naxLnD+11FO7Yo2rVNkY6tinZtLzqoeLRe5k7weN0wxepGKVY9WPHa4YrVDnUeV12T89k5xnyuMV8Pd44fNHSkVDNILTu7io6DARCwRYDrEFsyQRxeClDXXmoylk0C3JltUzayx0IzO4tL+j7Z7JltfxETobcCXJR468lodghQ13bkgSi8FUhvZscbG7Xxjw+r+/0HeDbJI289qBl3n+a84aN548fqaLVnYzOQ3QLRzu2KdJrG9jZFO5NN7s7tinZtVcQ819Es88aWke7tzmfnmM5tzvPRjuaiF9cz9iPqjg3wF0CRqOJVdYl9wKvqFY/WKV5d73xvHld1Q/K5xDGJ5+tkmuzmOJlzk187n8335nHn69qy2V+8aGgGKJkA1yElo2aiEgpQ1yXEZqqSCtDMLil3QZP52sxO7Tn9+wdWaeyYkVp8zaUaN2bUbnc7FxS5RyeZ7VBWPrBK5511sjNi5jYimW/4mO3NItkz26NkMIwVAlyUWJEGgvBYgLr2GJThrBBINbO7DpusmudWq2fvfbTxgccUGzHSk/hm3vNZ/emNlbrs2P/Qt46e58mYDFIZApHuHU6DO9HkTjW7tyuabJCbZnikwzyfapAnjnUa493bpZ6OgKEifRrgchrlaQ3wZIPceTy9UZ5qppsmu9NQTzbTk8cpveme+tppqtclm/KJr+NVDQGvn+m9FuA6xGtRxrNBgLq2IQvE4IcAzWw/VL0d09dmdvp2HdfedIfOO+sk500TTYP4zhUP6cq5swJ/Y8j0hnuKdtkN83r3yDaP3bXyYX37mqXO06eeOGW3uGlme1uUjBasABclwfozuz8C1LU/rowarECqmf3uq29p9PFTVLX+bXVNPkKb7vmT4vXFNcPe3L5WH/75IaqJ1urZWWs0vL4p2MUye8UIpF6vW7c1KxJrV6S7XZEe869TMp/NY7EeRbpbE493dziPyTku+XVPl0xD3XzvnOP860h+3vV14rnOvvN0t1pjHa8esqshntYoN9u2KBKVojWKR82d5DVSxHxdLZnvozW7njOPmeZ6tCr5nDmmRnFzfFVt4ryqaimSHCf5nKqSx5ixzN3qEfO5Ovk5OUfy3HjVri2PrMGzLBCuQyxLCOF4IkBde8LIIBYK0My2MCkZIfnWzDZ3PM+/eonmXjjDuRs7vZlt7n6+9sY7tHDBBWoa1mi/Uo4IaWaXfQpZQJoAFyWUQxgFqOswZpU1pZrZ6zftVPWrr2j0J6Yq0tKi9lM+pS23/UqKRApG+s6jl2nJ6v/WOQd+QTec9D8Fj8OJCOQrYMvrdaRnZ6JRnmygy2madySa67FORXranK9lmuumUe48nmiuq6fNubu8t4GefDzRVDfndCrS3baruR7rUGL8tOZ8vnAWH2+2ckm8HkV7X5fiphnvPBZJNObN5+TXcedz2uPpx8Ujimc+1/t8RHEzR9pY6XM456U/lz6nE4N5OhVH37iceLOM22cdqbl741MiVkVUU21+YRBRV0884aBs69g1h7OO9HWnXs8jyTX2riXjuGhyjFS8KffUfM64zkL7GCfizH+NiVylxkuLpaA17oot4WriSX02Xsmve3MR3fVY2np6cxJPO964pc53Hk/kN7MO+auI/F5IbHm9zi9qjkYgtwDN7NxGQR8RSDPbpjuzvUgAzWwvFBnDFgEuSmzJBHF4KUBde6nJWLYIpDezTUx1f31EI84+TZGuLrV+4xJtv+J7BYXa1r1Thy/dVy2dLbpvxip9YNRhBY3DSQgUIsDr9S41sw2L0yxPu+s80TQ3DfMuReLmbnXzuUuKdSmS+rr3uW5FYl2Sed40y53jko85DfnEc72fzRjmePNcrDsxZu/3qXPNc7vOM3fI84EAAggggECoBC41v3jkw2YB35rZZtFme45VT7+o+d88Tz9a+htnm5ERwxs1Z971mn768Tpr2lSbbVzHRjPbNRUHloEA/yeyDJJEiHkLUNd5k3FCGQhkNrNNyA2/Xq6m2TOd6Lf+aLF2nvvFvFey7PnFuvwvF+vosR/Sb89+IO/zOQGBYgR4vS5Gz65znbvQZRoCcSkeS3ypuCLO16nH41Jk1/d9n0s7TjFzb3HiPHO+87X5lPi69zmlnks/zjzfd6zU/M58GWP1zhExsZpJ0uPNEmskfY2Jr53zetcYU31t4i9l2ju6sqwjbY7UnL1xpY2TbmfmTHeM9STXkbbupLtj02uX/nXS1HnexRrTY8qyxvRc756rXXMk4smogWR8ifwnc+IcE0vUS28N7Xo+kdPkOMm6cI5N1VNqLDNG6vzUOemWyeOc7Yr4QAABBIwAzWzr68DXZrZZvbkLe+ZFi/pAZO5Jbb1SjgBpZpd7Bok/XYD/E0k9hFGAug5jVllTtma2URl61Xc05PprpKoqbf7NSnV8+DjXWHHFnb2yzZ7ZP/nErTp9/7Ndn8uBCHghwOu1F4qMYZsAdW1bRojHCwHq2gtFxrBRgG1GbMxK35h8b2bbT1B8hDSzizdkBHsEuCixJxdE4p0Ade2dJSPZI9BfM9tE2PTlz6thxW8Vb2zUxj8+rO73H+Aq8D+vu09fWPFpjW7YQ8/MWqNoah9ZV2dzEALFC/B6XbwhI9gnQF3blxMiKl6Aui7ekBHsFKCZbWde0qPytZn9g8XL9e57W3Tl3FlqqK915m1r79QV1y7VlCMPZpsR++uDCCtQgIuSCkx6BSyZuq6AJFfgEgdqZkc6OzTyzE+q9snH1TNuL218aJViI0bmVPriis/owXV/1LwPXalvHDk35/EcgIDXArxeey3KeDYIUNc2ZIEYvBagrr0WZTxbBGhm25KJ/uPwrZmdalqfc/rxOnrygX0i4A0g7S8MIqxcAS5KKjf3YV45dR3m7Fbu2gZqZhuV6NatGn3Ch1T15jp1TT5Cm1Y+oHhtXb9gZmsRs8VITbRWz85ao+H1TZWLy8oDE+D1OjB6JvZRgLr2EZehAxOgrgOjZ2KfBWhm+wzswfC+NbObt7Vo/tVLNPfCGZo0flyfUF9ft17X3niHFi64QE3DGj1YRrBDsM1IsP7M7q0AFyXeejKaHQLUtR15IApvBXI1s81s1Wte06hTpjqN7bbTP63mpbdJkcQbkWV+/N+HL9Etz/1EMw4+X9edcJO3wTIaAi4FeL12CcVhZSVAXZdVugjWpQB17RKKw8pOgGa2/SnzrZnNndn2J58IEcgmwEUJdRFGAeo6jFllTW6a2UbJbDUy8oxTFOnqUuu3/l3bv/2fu+G1dLbo8KX7qq17px4671nt3+Ruj22ygIDXArxeey3KeDYIUNc2ZIEYvBagrr0WZTxbBGhm25KJ/uPwrZltpjTbicxfuESLr7m09+5sc1f27Muu04Xnn8me2fbXBxFWoAAXJRWY9ApYMnVdAUmuwCW6bWYbmoZfL1fT7JmO0tYfLdbOc7/YR+ynf/+xrnhkrqbs9VH9+jP3VaAmS7ZFgNdrWzJBHF4KUNdeajKWLQLUtS2ZIA6vBWhmey3q/Xi+NrNNuKnm9TsbNvdGv+yGebvto+390ko3ItuMlM6amfwX4KLEf2NmKL0AdV16c2b0XyCfZraJpvGaq5x/qqrS5t+sVMeHj3OCjCvu7JVt9sz+n0/9QqdO+rT/wTMDAv0I8HpNaYRRgLoOY1ZZE3VNDYRVgGa2/Zn1vZltP0HxEdLMLt6QEewR4KLEnlwQiXcC1LV3loxkj0C+zWwTubk729ylHW9s1MYHHlP3xP10/9qVOv/3n9XYIXvpifNfUTQStWeRRFJxArxeV1zKK2LB1HVFpLniFkldV1zKK2bBNLPtTzXNbA9yRDPbA0SGsEaAixJrUkEgHgpQ1x5iMpQ1AoU0s82+2Wb/bLOPds8+47Xx/kf1uUdm6uG3HtDlH/6eLjziEmvWRyCVKcDrdWXmPeyrpq7DnuHKXB91XZl5r4RV08y2P8u+NrObt7Vozrzr9fxLa3aTOPSgibpp0cVqGtZov1KOCGlml30KWUCaABcllEMYBajrMGaVNRXSzDZq0a1bNeqUqape85qeP+5gHXbii6qN1um5r76pxtryvy6jMspbgNfr8s4f0WcXoK6pjDAKUNdhzCprMgI0s+2vA1+b2T9YvNwRuGT2dPslioiQZnYReJxqnQAXJdalhIA8EKCuPUBkCOsECm1mm4VUvbVOoz/+If3bR7fqJ0dJ5x38ZV1zwo+tWyMBVZ4Ar9eVl/NKWDF1XQlZrrw1UteVl/NKWTHNbPsz7Vsz29yVPf/qJZp74QxNGj/OfokiIqSZXQQep1onwEWJdSkhIA8EqGsPEBnCOoFimtlmMR2r/qxD/naqdtZIT7XM0tj5/23dGgmo8gR4va68nFfCiqnrSshy5a2Ruq68nFfKimlm259pmtke5IhmtgeIDGGNABcl1qSCQDwUoK49xGQoawSKbWb/5Nkb9N3HFujja6UHfyY1L16mtrPD/dd01iSPQPoV4PWa4gijAHUdxqyyJuqaGgirAM1s+zPrWzPbLN1sMzJh7z111rSp9ksUESHN7CLwONU6AS5KrEsJAXkgQF17gMgQ1gkU08yOxWM65mcH6J3Wt3Vb9wx9/nt3KF5Toy2/vkcdHz7OurUSUOUI8HpdObmupJVS15WU7cpZK3VdObmutJXSzLY/4742s19ft1633XW/5s6ZoYb6Wvs1CoyQZnaBcJxmpQAXJVamhaCKFKCuiwTkdCsFimlm/2HNCn1l5ec0dsheeuL8VzTim3M06PZbFW9s1MYHHlP3xP2sXDNBhV+A1+vw57gSV0hdV2LWw79m6jr8Oa7UFdLMtj/zvjWzzZ7Zc+Zdr+dfWpNV4dCDJuqmRReraVij/Uo5IqSZXfYpZAFpAlyUUA5hFKCuw5hV1lRMM3v6bz6lx97+i779kav19cMvknp6NPIz01T310fUs894bbz/UcVGjAQZgZIL8HpdcnImLIEAdV0CZKYouQB1XXJyJiyRAM3sEkEXMY1vzewiYiq7U2lml13KCHgAAS5KKI8wClDXYcwqayq0mf3P5ld0/G2Hq6F6kJ6dtVaNtYkbCyItLRr9iamqfvUVdU0+QptWPqB4bR3QCJRUgNfrknIzWYkEqOsSQTNNSQWo65JyM1kJBWhmlxC7wKloZhcIl34azWwPEBnCGgEuSqxJBYF4KEBde4jJUNYIFNrMnvvnf9Mv/nGLvnjIV7Xo+B/2WU/V+rc1+vgpim7ZrLbTP63mW35hzXoJpDIEeL2ujDxX2iqp60rLeGWsl7qujDxX4ippZtufDUFcjAAAIABJREFUdd+b2U+uflkzL1rUR2LZDfN09OQD7ddxGSHNbJdQHFYWAlyUlEWaCDJPAeo6TzAOLwuBQprZW9ubdfjSieqMdeih857V/k0H7LbWmtXPaNRpJyvS3qaWS/6PWhZcURYeBBkOAV6vw5FHVtFXgLqmIsIoQF2HMausyQjQzLa/DnxtZptG9nWLl/fZG9u8KeTsy67TheefqbOmTbVfyEWENLNdIHFI2QhwUVI2qSLQPASo6zywOLRsBAppZv/309/Xwr/9h47b+wTdceY9/a61/r57NeK8z0rxuJoXL1Pb2dPLxoVAy1uA1+vyzh/RZxegrqmMMApQ12HMKmuimV0eNeBbM7utvVNXXLtU55x+/G53YZsm950rHtKVc2epob62PKQGiJJmdtmnkAWkCXBRQjmEUYC6DmNWWVO+zexYPKZjfnaA3ml9W8tO+5VOnjBtQMQhP75BQ69YoHhNjbb8+h51fPg40BHwXYDXa9+JmSAAAeo6AHSm9F2AuvadmAkCEuDO7IDg85jWt2Z287YWzb96ieZeOEOTxo/rE5K5O/vaG+/QwgUXqGlY4k2HyvmDZnY5Z4/YMwW4KKEmwihAXYcxq6wp32b2Pa/9RrP/cJ7GDtlLT858VRFFciIO/8ZsDbr9VsUbG7XxgcfUPXG/nOdwAALFCPB6XYwe59oqQF3bmhniKkaAui5Gj3NtFqCZbXN2ErH51szmzmz7k0+ECGQT4KKEugijAHUdxqyypnyb2Z+56yQ9sf6vuuKj/09fm/wNd4A9PRr5uTNV99CD6tlnvDY++DfFhg93dy5HIVCAAK/XBaBxivUC1LX1KSLAAgSo6wLQOKUsBGhm258m35rZZul3rXxYy1c8xJ7Z9tcBESLQK8BFCcUQRgHqOoxZZU35NLP/sek5nXLHFDVUD9Kzs9aqsdb9X8ZFdu7Q6JM+qupXX1Hn0cdq891/ULy2jgQg4IsAr9e+sDJowALUdcAJYHpfBKhrX1gZ1AIBmtkWJCFHCL42s83cZn/smRct6hPGshvm7baPtv1U/UfINiPlnD1izxTgooSaCKMAdR3GrLKmfJrZFz8wW8tfulXnH/o1Xf2xG/LGq1r/tkad9FFVvbdBbad/Ws23/CLvMTgBATcCvF67UeKYchOgrsstY8TrRoC6dqPEMeUoQDPb/qz53sy2n6D4CGlmF2/ICPYIcFFiTy6IxDsB6to7S0ayR8BtM3tre7MOXzpRXbFO/fVLL2ifofsWtIiaF1/QqFM+pkh7m1ounaeW+f9R0DichMBAArxeUx9hFKCuw5hV1kRdUwNhFaCZbX9mfW1m/2Dxcr373hZdOXeWGuprHY3UXtpTjjxYZ02bar+QiwhpZrtA4pCyEeCipGxSRaB5CFDXeWBxaNkIuG1m/9eTi3TN4/+p4/c5WbedcXdR66u/716N+MI5Uiym5sXL1Hb29KLG42QEMgV4vaYmwihAXYcxq6yJuqYGwipAM9v+zPrWzOYNIO1PPhEikE2AixLqIowC1HUYs8qa3DSzu2PdOuqW/bSx7T39/LS7dOKETxYNN/h/btSwBf+ueE2NNv/uPmcfbT4Q8EqA12uvJBnHJgHq2qZsEItXAtS1V5KMY5sAzWzbMrJ7PL41s5u3tWj+1Us098IZmjR+XJ+ZX1+3XtfeeIcWLrhATcPcvwGRrZzcmW1rZoirEAEuSgpR4xzbBahr2zNEfIUIuGlm3/3qnbrwvvOdrUXMFiMRRQqZardzhs39lgbfskSx4cO16b6H1T1xP0/GZRAEeL2mBsIoQF2HMausibqmBsIqQDPb/sz61szmzmz7k0+ECGQT4KKEugijAHUdxqyyJjfN7NN/dbyeefcJ/edx39dXPnihd2ixmP5/e3cCJEd153n8X0e3uktq3Te6xQ0SYjBezVhgIeHxAOZYZtDCMhgQgzV4NnY5AgKNg7UJByMsFkxMxJjRECODDQMjY3kY21p7bW68ZgBbGJnLLKAb3RKo765j472srK4uVVdlVr3KelX5LYeiuqtevvfy8/6kUz9lZU1YcYmMeP5ZSc2aLfuf/bUOtnkgUK0Ax+tqBdneRgHq2sZVYU7VClDX1Qqyva0ChNm2rszgvGoWZqshXnvjXVm95mFZt/a23NXZ6qrsVXfcL1+99lLumW1/fTDDEApwUhLCRQ/BLlPXIVjkEO5iuTD7rQNvyp8+uVja4wnZ8lfb9bPJR6S7Syb+2XmivhhS3Wrk4NM/k0zrCJND0FcIBTheh3DRQ7DL1HUIFjmEu0hdh3DRQ7LLhNn2L3RNw2y1+254/fHegzmNRx68U85edLL9Oh5nyG1GPELRrCEEOClpiGVikj4FqGufYDRvCIFyYfZ//8UN8sP3npCVC2+Sb557f032KbZvr0w8f4nEdu+Snosvk8Pf/ZeajEOn4RHgeB2etQ7TnlLXYVrt8OwrdR2etQ7bnhJm27/iNQ+z7SeofoaE2dUb0oM9ApyU2LMWzMScAHVtzpKe7BEoFWarL3xUX/yYSqf0vbLVPbNr9VBXZk+8YJlEujql8yt/I5/+3X21Gop+QyDA8ToEixzCXaSuQ7joIdhl6joEixzSXSTMtn/hCbMNrBFhtgFEurBGgJMSa5aCiRgUoK4NYtKVNQKlwuz7X71HHnj1Hlk+58/ke1/aWPM5j3julzLhikv0OOnRo6VnxdXSfe0NMnDKqTUfmwGaS4DjdXOtJ3vjCFDXVEIzClDXzbiq7JMSIMy2vw4Isw2sEWG2AUS6sEaAkxJrloKJGBSgrg1i0pU1AsOF2cl0Ul+Vra7OfvySp2XprC8EMufE44/KmDtukUhfb268/rPO1qF2z6WXS2bkqEDmwSCNLcDxurHXj9kXF6CuqYxmFKCum3FV2SfC7MaoAcJsA+tEmG0AkS6sEeCkxJqlYCIGBahrg5h0ZY3AcGG2uk+2ul+2urWIusVIRCKBzTnS2SmJp56UxGOPSMsbv82Nq4Lsnsv+XLqvuV76P/PZwObDQI0nwPG68daMGZcXoK7LG9Gi8QSo68ZbM2bsTYArs7051bMVYbYBfcJsA4h0YY0AJyXWLAUTMShAXRvEpCtrBIYLs//0ycXy1oE35Z7Pf1uuW7CqbvNteectSTy6XtqfekKiR47k5qFuPdJzzfXS/V/+UtJjxtRtfgxspwDHazvXhVlVJ0BdV+fH1nYKUNd2rguzql6AMLt6w1r3QJhtQJgw2wAiXVgjwEmJNUvBRAwKUNcGMenKGoFiYfZv9vyHXPLUedLR2iGbV34k7fFE3ecb6e+Xtp/8m75ae8RLL4hkMnpOmdYR0nvRJfpq7b5zPi8SCe4K8rqjMIFhBTheUxzNKEBdN+Oqsk/UNTXQrAKE2favLGG2gTUizDaASBfWCHBSYs1SMBGDAtS1QUy6skagWJj91f9zrTz9hx/IjYv+m3xjyVpr5upOJLZjuyS+/11JPPmYxHbvys0vOXuu9FxznXT/1y9LavIU6+bNhIIT4HgdnDUjBSdAXQdnzUjBCVDXwVkzUrAChNnBelcyGmF2JWoF2xBmG0CkC2sEOCmxZimYiEEB6togJl1ZI1AYZqsvfFRf/JhKp/S9stU9s619pNPS9uwvpP2xR6Tt55skMjDgTDUWk97zvyjdX16pn9XvPMIlwPE6XOsdlr2lrsOy0uHaT+o6XOsdpr0lzLZ/tQmzDawRYbYBRLqwRoCTEmuWgokYFKCuDWLSlTUChWH2t165W/7+9W/J+XMukEe/9ENr5lluItFDByXxxGOSeOy7En//D7nmqanTpPvKv5Tua2+Q1MxZ5brh/SYR4HjdJAvJbgwRoK4piGYUoK6bcVXZJyVAmG1/HRBmG1gjwmwDiHRhjQAnJdYsBRMxKEBdG8SkK2sE8sPs/nSfnLl+nhzpPSxPXvoTOWfmMmvm6Wcira/+WhLff0Tan94oke4uZ9NIRN9TW91bu/eiSyXT2uqnS9o2mADH6wZbMKbrSYC69sREowYToK4bbMGYrmcBwmzPVHVrSJhtgJ4w2wAiXVgjwEmJNUvBRAwKUNcGMenKGoH8MPtf3/me3PrMX8sJ406S56/ebM0cK51IpKtTEht/oG9D0vqb13LdpMePl+6/uEq6V35FksefUGn3bGexAMdrixeHqVUsQF1XTMeGFgtQ1xYvDlOrSoAwuyq+QDYmzDbATJhtAJEurBHgpMSapWAiBgWoa4OYdGWNQH6YvfTxM+X9w+/JmqV/L18+/a+smaOJicTfe1cS31sviR/8i0QPHcp12f+Zz+qrtXsuv0Iy7QkTQ9GHBQIcry1YBKZgXIC6Nk5KhxYIUNcWLAJTqIkAYXZNWI12SphtgJMw2wAiXVgjwEmJNUvBRAwKUNcGMenKGgE3zP7Rm7+Qyzd+QTpaO2Tzyo+kPd6cwa76ksi2Tf8uiccekREvPCeSTuu1yIwcJd2XXyE911wv/X/0GWvWh4lUJsDxujI3trJbgLq2e32YXWUC1HVlbmxlvwBhtv1rRJhtYI0Isw0g0oU1ApyUWLMUTMSgAHVtEJOurBFww+yLH/vP8pP/9yNZteh/yP9cssaa+dVyIrFdO3WonXji+xLbuSM31MApp0nPl6+X7hVXS3rMmFpOgb5rJMDxukawdFtXAeq6rvwMXiMB6rpGsHRbdwHC7LovQdkJEGaXJSrfgDC7vBEtGkeAk5LGWStm6l2AuvZuRcvGEVBh9s7RIrNvi+pJv3rtezJt1HGNswMmZppOy4gXntVfGtn2s59IpL9f95oZ0Sa9X7pEuq9ZKX1LzjUxEn0EJMDxOiBohglUgLoOlJvBAhKgrgOCZpjABQizAyf3PSBhtm+yYzcgzDaASBfWCHBSYs1SMBGDAtS1QUy6skZAhdl3ni/yrSUiX5z7JVl/0QZr5laPiUQPH5bEhsf1/bXVfbbdh7q3dnrsOBlYcIYkzzhTBhYslOTsufWYImN6EOB47QGJJg0nQF033JIxYQ8C1LUHJJo0pABhtv3LRphtYI0Isw0g0oU1ApyUWLMUTMSgAHVtEJOurBGYMDUh028TOdQu8q+XbZIlM5ZaM7d6T6T19VelXd2G5EdPSaSr85jpqFuQDJx+hgwsXCTJhYt00D1wwokisVi9px768Tleh74EmhKAum7KZQ39TlHXoS+BpgUgzLZ/aQmzDawRYbYBRLqwRoCTEmuWgokYFKCuDWLSlTUCP/1iQr5yscgJ406S56/ebM28rJpIMiktf3hXWn6/ReK/f1Nafv87/XP00MFjpplpa5eB0053ruB2A+7TTpdM6wirdqnZJ8PxutlXOJz7R12Hc92bfa+p62Zf4fDuH2G2/WtPmG1gjQizDSDWoYveVI+k0innTyYlyUxS0umUJNNJSan/qed02nkW53X9fiap26fTaRlID0habavaZLLb6N9Tzuv5far31bZ6jMH3U6mkZCSjBTIZ51n/nH2t5Ov5bYr0oXrJ9Tds34P4aszWeEQkEpG+/pTneUh+35Fjx/S0L3723UvbIvPId/ViPdRvqJOp9Rraj5f1Kl0jXqzLrZdfp8EZDa3hOvxnPeyQ8aiqa5FkKn+2Ns2QuSDgX+CD91+S/SNF/tey78hVp17nv4MQbxHb87G06HB7MOSOf/iBSDo9VCUel4ETTpKBhdmAe+Ei6V+wSDKjRoVYr7a7TjhSW196r48AdV0fd0atrQB1XVtfeq+fAGF2/ey9jkyY7VWqRDvC7OoQj/Yflb5Ur/Qme6Q32SsqZO5Tz9mf3deHtumVnoEu6U32OdulnG31dtmfne16pC+VbZPskc6BYz9qXN3s2RoBBBBAAIH6CYzrEXn91oPSFmuv3ySaZORIX6+0vPV7HXI7V3FvkZa3t0iks+DcIRLR99zO3YN74RnSv3CRpCdOahKJ+u4G4Uh9/Rm9NgLUdW1c6bW+AtR1ff0ZvXYChNm1szXVM2G2Acmwh9kfd+6SAz375UDPPtnfvU8OdO+TfV179e8He/brALl3QAXOTmDtBM690mVBsNweT0g8GpNoJCbxSFyi0ZjEo3GJRWISi8Qlpn+PSVSyr0djElPvq/+p52hUtx/yvtpOba/bZvtV/ev2Tr/5Y6rX3UckGh38WV1Gmn1EInk/e3k92yYyTFt9ieowfY9oieq3+wecq9OG68PL6+oKb91Hpop9KbLvw3m443mZ95D5ezHNm8dQPwfSi8ew61jFepWqEb91M8Qvu2Z++3Db53sYOMxW3UViREwvW3ev84kDHgg0g8CES78oE7tFxr/d3Qy7Y+0+xLd+mHcF95vS8tYWie3Yfsx8U1Om6ntwu7cp6V94hqRmzbF2v2ydGOGIrSvDvKoRoK6r0WNbWwWoa1tXhnlVK0CYXa1g7bcnzDZg3Ixh9vajW+VA1z7Znw2kVVi9r2uP7O/alw2u9+rg+pO+I1ULJuIjpS3eJiPibfrKMvVzW1w9t8uI2Aj93J59T7eJt4kKoZ02bTIi5rZ3ntV7rbFW533VX4vq1+l79IgxVc+32TvgpKTZVzic+0ddh3Pdm32vp09M6F3cfYAwO+i1Vldrt765WQfb8S1OwB1/522J9PcNmYr+okn15ZIL8r5o8sSTRPL+8Trouds+Hsdr21eI+VUiQF1XosY2tgtQ17avEPOrVIAwu1K54LYjzDZg3Qhh9qd9nzhXTvc4V06rIPpg937Z1529grr7gOzt3qOvpPZ7xfTE9kkyITFJJrVPlkmJyTKxfYpMHjlFJiYmy5TENEm0JrIhdV5QHWuTjtbRBvTpwrQAJyWmRenPBgHq2oZVYA6mBQizTYtW35++D/e770js7S3S+rvN0vK7zRI9MvQf/pMnniSpiZP1YOkJEyQ9ZZqkpx8nqanTJKWep0zVP2c6OqqfUAP2wPG6AReNKZcVoK7LEtGgAQWo6wZcNKbsSYAw2xNTXRsRZhvgtyHMVrfyeHnHc/Lmvt/Kns7dQ277sbtzp++9nDJymg6nVSCtAmr1+/j2CTKp3QmpdWitntudv4zxaB4BTkqaZy3Zk0EB6ppqaEYBwuzGWNXY3j36qu3WN9/Q9+KOffSBxHdsl+iB/SV3IJMYKalp0yU1fboOuNNTp0la/e7+UeH3zNmNgeBjlhyvfWDRtGEEqOuGWSom6kOAuvaBRdOGEiDMtn+5CLMNrFG9wuyXdz6vA+yXdj4nb+x9veSeqFtxuAG0upJahdAqoJ6QmJgNpZ2QWr03rm28ARW6aFQBTkoadeWYdykB6pr6aEYBwuzGXtXIwIBE9+yW2O5dEtu1U2K7d0tUPX+8y3lN/dm3VyTtfIdF0UckIulx452AW4XdKuCeNn0w9HZfmzRZ8r8XwWY5jtc2rw5zq1SAuq5Uju1sFqCubV4d5laNAGF2NXrBbEuYXa3zP/6jHG4bI8nZcyQ5d35NPxK6ee9r8n93vigv7Pil/GrnC8fMfMGkRXLOzPNk5ug5zlXVI51wWt32o6M1nB9VrXZ5w7g9JyVhXPXm32fquvnXOIx7SJgdjlWP7dwxJOCO7lTB9y6J7flYYrt26J+9PHKBtxt8T58hqalTZeC0Bfq+3rY8OF7bshLMw6QAdW1Sk75sEaCubVkJ5mFagDDbtKj5/gizqzWNRIb0kB47VlJz5kly5mxJzZmjv8U+OWeepGbNkuT8E3yN9v7h95wrr3c8K7/e/ZKo+17nP44fd6J8bsZSOWfGefqZLzf0xUvjYQQ4KaE0mlGAum7GVWWfCLOpAVcg9nH2Cm8Vcn+8S6LqdxV6q2cVeO/Y7gtL3eJEfXml+pMZO17So0ZJRv8+Vl8JnukY7fw+erSkx0+UzEi3/VhJT5zka6zCxhyvq+JjY0sFqGtLF4ZpVSVAXVfFx8YWCxBmW7w42akRZle7RjffLL3v/EFi27dKfNs2ifR0l+xRf7GPDrjn6NA79/OsObK7Q+SFHc/o8PrlHc/Lvu49Q/qaNuo4WaLC65nL5NyZy2RSYkq1s2d7BI4R4KSEomhGAeq6GVeVfSLMpgb8CKhblkTd25fs3uXc4kRd9b13j0QPHZLop59I5JMjEv30Uz/dFm2bGdHmBOFuAD5a/TzWCb8nTBQZOWowLB+tQnEnKFftE1MmiCQScrR7oOp50AECtghwHmLLSjAPkwLUtUlN+rJJgDDbptUoPhfCbANrlH/P7Oj+fRLf+pHEtm+T+PatEvvoQ4lt2+r8XHBVzJE2kWfmifxynsgzc0XenzB0MuMlIUtGLpBzpn9e/vj0y2TucYsMzJYuECgtwEkJFdKMAtR1M64q+0SYTQ3USkAF2k6w/YkTch9xQu7op0ckot47fFiin6ifnfejn6ggXP18RKKHD1c9rdSffE6SEj22n3hMMu0JUVeOZ9rb9XM60a7D8UwiMfS9kU6btG6rtsn709Ze9RzpAAE/ApyH+NGibaMIUNeNslLM068AYbZfseDbE2Z7MN+46UW5a+163fKi5Yvl7ttXSntba25Lr18A2ZPsltc3/1Be/uDn8tLh12RLaqekJZPrZ2S/yLnbRJZ9JLL8I5FFe0Qig2+LvoXJ7LmSnKWu6p7j/DxbPc+R5LzjPewJTRAoL8BJSXkjWjSeAHXdeGvGjMsLEGaXN6JFfQQiXZ064NYhtwq4cz+74fhhJ/xWf45mg3D9+xGJHjwQyKR1IJ4NuNOFQbh6b6QbjjvP0toqmXiLSGuL89zSIpkW9dwqmZa4SLxFMm4b/V48+16L8556rXXwZ3e7zMhRgewvg9RXgPOQ+vozem0EqOvauNJr/QUIs+u/BuVmQJhdRui1N96V+9dtkIfuvUXGjemQB9Zt0FvcumpF2TA7mU7KG/tel5f0fa+fk9/ufVUGUv257VpirfJHk8+WJbPO07cPOWvUqdK2fYdzVfdHH+gruvVV3dvUld7bJdLXW3K2qeNmSN8ff05Sc+cf006fsKsrVEZ1OPc1VB/3VFe0qI95jlLvdUh6/Phy9cL7IRDgpCQEixzCXaSuQ7joIdhlwuwQLHIId9E9Xnft3q9v3xfp7pJId7fzc2+fRDqPStT9Xb3X0yOifu9S7bokmn1Nb5dtr9ro33u6JXrkiLWq6vYs0hIfGooXCdB1u1h0MEBXoboOzPMCdB2oZ4N23T42GLyr97Lhe9Ht8sZ0AnunLz03/Z7qd3BMHfbzKCnAeQgF0owC1HUzrir7pAQIs+2vA8LsMmukwus5M6fK5Reeq1sWhtvqNffK7Ixk5N2Db8nLO5+Tl7Y/J/+x+2XpHOjMjRCNROW0iQt1cL1k1jL5T9P+RNrj3k/+9LfW71BB90f6OaYD721O2O3xm+y9lKS+x6EbequPbaov/VHPKgTXr4+STIcTijuvj5J0flCet426mpxHYwlwUtJY68VsvQlQ196caNVYAoTZjbVezNabQFDH68hRFYo7AbcOy9Wf3l5RV5U7wbcTgEe7ukV6e0T6+yQykBQZGJBIckAi/f0i6tl9baA/9570Z9sMDDiv6feSejv9e9625b5vx5uaXa10uK1uCaMC9FjceY7HdaCeiTnP+v1o3uvq/WhMMrqdCurjQ9/PbpeJqz4L+3XHGBxTj6ce0ahIJOL8rJ6L/SzZ17PvZY5pl/V1Xy/Sh97G7afIWG2tMT1270B6yDyOHSs714I55c/d2Sa7P1XtV4FLqf3KH2dYz8E5Vb5f5efkrOHgWg47lms03H65r5ewLqyZ6vdr+DrU/0jVYI+gjtcNxsJ0m0CAMNv+RSTMLrFGPb398vX71svis07NhdkfbNstX1vzsNyz+kaZP3u6bD2yVZ7askmH17/a+bwc7B360cj5Y0+QJTPPk3NmnCefm7FURo8YU7OqiH/wvsT27HHuX6iuTuk8mrtKRd/fUH3kU52gq/fUc2f29071mvNxUNMPdTLbf+ZZprsd2p86EYlGnBNkdVKsTlrVSW406pw8515zf486J8vZNrm2qp1+LVKwXfZEW/WrttP9542R2y7bv+oj4ryfyc7LnYNzUp+dm7udbi9Ov+4Jt9pezd/93X1PPUtksK3qX++/2zZ7wp7XXp906X6y/au2rlm2Xf7JEycltS1Xeq+PAHVdH3dGra0AYXZtfem9PgJhPl7rYL1/IBuSHxuED4bg6r1kNiR3gnMnJM/72Q3QVaCu3u/ry7bLhur9/RLJvpc/pn5NbZvO6E+Fur87z86Yue3UmJ2DF+7Up2IYFQEEEEAAAcMCmbz7/Rrumu7MCBBmewizr7h4qZy96GTdsjDMjtzt/uu509GM0TNk+dzlsmzuMjl/3vkyvWO6mZUKspcDB0TUian6c/Ro8Z+7ukTUt90Xa5e/nWrDAwEEEEAAAQRqJ8AJd+1s6RkBBPwJqNu+pFIiyaS550r7UsdG94/ai2I/u8dPm9oFOacgx8pfg1LjBjmnIMcqtv+9pW8j6u8/PlojgIAxAc6tjVHWqiPC7BKyXq7MPnPdmTJ/3HxZPm+5DrFPnHBirdaq8ftV/2edTjsntupPsZ/LvZ+/ndtWHWjck1yT/Q7XV7E5VNtW7Yv7R+1PNb+rbf30wUlU4/+3xR4ggEC4BTjhDvf6s/cIIIAAAggggAACCIRIgDC7zGL7uWd2iOqGXW1igTB/vLeJlzX0u0Zdh74EmhKAum7KZQ39TlHXoS+BpgSgrptyWUO/U9R16EugaQG4Z7b9S0uYXWaNCr/wUYXb6nHrqhW5Ld0vgLR/uZkhAuUFOCkpb0SLxhOgrhtvzZhxeQHqurwRLRpPgLpuvDVjxuUFqOvyRrRoPAHquvHWjBl7EyDM9uZUz1aE2R70N256Ue5au163vGj5Yrn79pXS3tZKmO3BjiaNJ8BJSeOtGTMuL0BdlzeiReMJUNeNt2bMuLwAdV3eiBaNJ0BdN96aMePyAtR1eSNaNKYAYbb960aYbWCNuDLbACJdWCPASYk1S8FEDApQ1wa4srmwAAATw0lEQVQx6coaAeramqVgIgYFqGuDmHRljQB1bc1SMBGDAtS1QUy6skqAMNuq5Sg6GcJsA2tEmG0AkS6sEeCkxJqlYCIGBahrg5h0ZY0AdW3NUjARgwLUtUFMurJGgLq2ZimYiEEB6togJl1ZJUCYbdVyEGbXajkIs2slS7/1EOCkpB7qjFlrAeq61sL0Xw8B6roe6oxZawHqutbC9F8PAeq6HuqMWWsB6rrWwvRfLwHC7HrJex+XK7O9Ww3bkjDbACJdWCPASYk1S8FEDApQ1wYx6coaAeramqVgIgYFqGuDmHRljQB1bc1SMBGDAtS1QUy6skqAMNuq5Sg6GcJsA2tEmG0AkS6sEeCkxJqlYCIGBahrg5h0ZY0AdW3NUjARgwLUtUFMurJGgLq2ZimYiEEB6togJl1ZJUCYbdVyEGbbvxzMEAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQKCYAFdmUxcIIIAAAggggAACCCCAAAIIIIAAAggggAAC1gsQZlu/REwQAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAgDCbGkAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBCwXoAwu8Il2rjpRblr7Xq99UXLF8vdt6+U9rbWCntjMwTMCrz2xrty3c336k4XnDJPHrr3Fhk3pmPYQcq1L1XvD6zbIP/8xKYhfX/zjpVy+YXnmt0pekOgQKBc3RaCeTluqzZbd+yRW1etwBuBQAT81rGX9h9s2y33fedJWfO3Nw459nO8DmRJGaSIgJe6zd/Mz3kH5xyUXFACfuu4VPv894r9fZLjdVCryjiFAn7rvNTxOv89NQ7Ha+otKAG/dVyqvTqvXnXH/fLx3oNF8z+O10Gt6tBxCLMrcFeFfv+6DbmAUBWvehB+VIDJJsYF1MH2a2selntW3yjzZ08XdRLxym/eHvYfXMq1L1fv1L/xJaRDDwLl6rbYiXmp43b+CcwNV13I8dzDGtCkegG/dVyu/eFPjspNd35btrzzYdF/yOR4Xf2a0YN/gXJ16+d43dPbLw89+m9y/ZUX6H+ocf+CuWb1jXL2opP9T44tEPAo4LeOy7VX5+czp0/Wdavq+uv3rZepk8fnzj84XntcGJoZFShXt9Ucr91zlNtWreB4bXTV6KxQwG8dl2uff7xWYxUenzle16cGCbM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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = px.line(data_frame=bio.get_history(), x=\"SYSTEM TIME\", y=[\"A\", \"X\", \"B\"], \n", " title=\"Changes in concentrations (reaction A + X <-> 2B)\",\n", " color_discrete_sequence = ['red', 'darkorange', 'green'],\n", " labels={\"value\":\"concentration\", \"variable\":\"Chemical\"})\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "bc4c0dd9-609a-40ba-93e7-910dd2550ba6", "metadata": {}, "source": [ "`A`, still the limiting reagent, is again stopping the reaction. \n", "The (transiently) high value of [A] led to a high value of [B]" ] }, { "cell_type": "markdown", "id": "f6619731-c5ea-484c-af3e-cea50d685361", "metadata": { "tags": [] }, "source": [ "# Let's again suddenly increase [A]" ] }, { "cell_type": "code", "execution_count": 15, "id": "d3618eba-a673-4ff5-85d0-08f5ea592361", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SYSTEM STATE at Time t = 0.035:\n", "1 bins and 3 species:\n", " Species 0 (A). Diff rate: None. Conc: [30.]\n", " Species 1 (X). Diff rate: None. Conc: [45.6272528]\n", " Species 2 (B). Diff rate: None. Conc: [108.74549439]\n" ] } ], "source": [ "bio.set_bin_conc(bin_address=0, species_index=0, conc=30.)\n", "bio.describe_state()" ] }, { "cell_type": "code", "execution_count": 16, "id": "359b153e-9b63-45a3-851a-6c49259909b7", "metadata": {}, "outputs": [], "source": [ "# Save the state of the concentrations of all species at bin 0 (the only bin in this system)\n", "bio.add_snapshot(bio.bin_snapshot(bin_address = 0))" ] }, { "cell_type": "markdown", "id": "0974480d-ca45-46fe-addd-c8d394780fdb", "metadata": {}, "source": [ "### Yet again, take the system to equilibrium" ] }, { "cell_type": "code", "execution_count": 17, "id": "8fe20f9c-05c4-45a4-b485-a51005440200", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SYSTEM STATE at Time t = 0.07:\n", "1 bins and 3 species:\n", " Species 0 (A). Diff rate: None. Conc: [2.31631253]\n", " Species 1 (X). Diff rate: None. Conc: [17.94356534]\n", " Species 2 (B). Diff rate: None. Conc: [164.11286933]\n" ] }, { "data": { "text/html": [ "
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" ], "text/plain": [ " SYSTEM TIME A X B caption\n", "0 0.000 5.000000 100.000000 0.000000 \n", "1 0.001 1.828000 96.828000 6.344000 \n", "2 0.002 0.701002 95.701002 8.597996 \n", "3 0.003 0.281916 95.281916 9.436168 \n", "4 0.004 0.123519 95.123519 9.752963 \n", ".. ... ... ... ... ...\n", "68 0.066 2.342097 17.969350 164.061300 \n", "69 0.067 2.333888 17.961141 164.077718 \n", "70 0.068 2.326989 17.954242 164.091517 \n", "71 0.069 2.321189 17.948442 164.103117 \n", "72 0.070 2.316313 17.943565 164.112869 \n", "\n", "[73 rows x 5 columns]" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bio.react(time_step=0.0005, n_steps=70, snapshots={\"frequency\": 2, \"sample_bin\": 0}) # At every other step, take a snapshot \n", " # of all species at bin 0\n", "bio.describe_state()\n", "bio.get_history()" ] }, { "cell_type": "markdown", "id": "81a8be4a-f374-494e-b647-184e35707295", "metadata": {}, "source": [ "A, again the scarse limiting reagent, stops the reaction yet again" ] }, { "cell_type": "code", "execution_count": 18, "id": "5d7ded33-8a16-4fdb-b099-a4ea11f7583c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Ratio of equilibrium concentrations (B_eq / (A_eq * X_eq)): 3.9485418139406785\n", "Ratio of forward/reverse rates: 4.0\n" ] } ], "source": [ "# Verify the equilibrium\n", "A_eq = bio.bin_concentration(0, 0)\n", "X_eq = bio.bin_concentration(0, 1)\n", "B_eq = bio.bin_concentration(0, 2)\n", "print(\"Ratio of equilibrium concentrations (B_eq / (A_eq * X_eq)): \", (B_eq / (A_eq * X_eq)))\n", "print(\"Ratio of forward/reverse rates: \", chem_data.get_forward_rate(0) / chem_data.get_reverse_rate(0))" ] }, { "cell_type": "code", "execution_count": 19, "id": "4229e039-b484-4849-a446-59409885deb4", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "Chemical=A
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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = px.line(data_frame=bio.get_history(), x=\"SYSTEM TIME\", y=[\"A\", \"X\", \"B\"], \n", " title=\"Changes in concentrations (reaction A + X <-> 2B)\",\n", " color_discrete_sequence = ['red', 'darkorange', 'green'],\n", " labels={\"value\":\"concentration\", \"variable\":\"Chemical\"})\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "e86e8319-2d19-4a59-91f1-9e45cf2dd333", "metadata": {}, "source": [ "`A`, again the scarse limiting reagent, stops the reaction yet again. \n", "And, again, the (transiently) high value of [A] up-regulated [B] \n", "\n", "Note: `A` can up-regulate `B`, but it cannot bring it down. \n", "`X` will soon need to be replenished, if `A` is to continue being the limiting reagent." ] }, { "cell_type": "markdown", "id": "837435d0-d2ea-4b98-85c4-6a6d44371ae8", "metadata": {}, "source": [ "# For additional exploration, see the experiment \"reactions_single_compartment/up_regulate_1\"" ] }, { "cell_type": "code", "execution_count": null, "id": "116d06a6", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "jupytext": { "formats": "ipynb,py:percent" }, "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": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 5 }