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"## Coupled pair of reactions: `A <-> B` , and `A` + `E` <-> `B` + `E`\n",
"A direct reaction and same reaction, catalyzed\n",
"### Enzyme `E` initially zero, and then suddenly added mid-reaction\n",
"\n",
"LAST REVISED: Nov. 4, 2023"
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"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"
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"id": "087c0d08",
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"source": [
"from src.modules.chemicals.chem_data import ChemData\n",
"from src.modules.reactions.reaction_dynamics import ReactionDynamics"
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"id": "23c15e66-52e4-495b-aa3d-ecddd8d16942",
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"Number of reactions: 2 (at temp. 25 C)\n",
"0: A <-> B (kF = 1 / kR = 0.2 / delta_G = -3,989.7 / K = 5) | 1st order in all reactants & products\n",
"1: A + E <-> B + E (kF = 10 / kR = 2 / delta_G = -3,989.7 / K = 5) | Enzyme: E | 1st order in all reactants & products\n",
"Set of chemicals involved in the above reactions (not counting enzymes): {'B', 'A'}\n",
"Set of enzymes involved in the above reactions: {'E'}\n"
]
}
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"# Initialize the system\n",
"chem_data = ChemData(names=[\"A\", \"B\", \"E\"])\n",
"\n",
"# Reaction A <-> B , with 1st-order kinetics, favorable thermodynamics in the forward direction, \n",
"# and a forward rate that is much slower than it would be with the enzyme - as seen in the next reaction, below\n",
"chem_data.add_reaction(reactants=\"A\", products=\"B\",\n",
" forward_rate=1., delta_G=-3989.73)\n",
"\n",
"# Reaction A + E <-> B + E , with 1st-order kinetics, and a forward rate that is faster than it was without the enzyme\n",
"# Thermodynamically, there's no change from the reaction without the enzyme\n",
"chem_data.add_reaction(reactants=[\"A\", \"E\"], products=[\"B\", \"E\"],\n",
" forward_rate=10., delta_G=-3989.73)\n",
"\n",
"chem_data.describe_reactions() # Notice how the enzyme `E` is noted in the printout below"
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"id": "0e771dda-1c0f-4fc0-ab21-049740643897",
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"### Set the initial concentrations of all the chemicals - starting with no enzyme"
]
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"SYSTEM STATE at Time t = 0:\n",
"3 species:\n",
" Species 0 (A). Conc: 20.0\n",
" Species 1 (B). Conc: 0.0\n",
" Species 2 (E). Conc: 0.0\n",
"Set of chemicals involved in reactions (not counting enzymes): {'B', 'A'}\n",
"Set of enzymes involved in reactions: {'E'}\n"
]
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"dynamics = ReactionDynamics(chem_data=chem_data)\n",
"dynamics.set_conc(conc={\"A\": 20., \"B\": 0., \"E\": 0.},\n",
" snapshot=True) # Initially, no enzyme `E`\n",
"dynamics.describe_state()"
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"### Advance the reactions (for now without enzyme), but stopping well before equilibrium"
]
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"execution_count": 5,
"id": "76f24d9a-a788-41d8-90a4-db87386f91aa",
"metadata": {},
"outputs": [
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"name": "stdout",
"output_type": "stream",
"text": [
"Some steps were backtracked and re-done, to prevent negative concentrations or excessively large concentration changes\n",
"9 total step(s) taken\n"
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}
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"dynamics.set_diagnostics() # To save diagnostic information about the call to single_compartment_react()\n",
"\n",
"# All of these settings are currently close to the default values... but subject to change; set for repeatability\n",
"dynamics.set_thresholds(norm=\"norm_A\", low=0.5, high=0.8, abort=1.44)\n",
"dynamics.set_thresholds(norm=\"norm_B\", low=0.08, high=0.5, abort=1.5)\n",
"dynamics.set_step_factors(upshift=1.2, downshift=0.5, abort=0.4)\n",
"dynamics.set_error_step_factor(0.25)\n",
"\n",
"# Perform the reactions\n",
"dynamics.single_compartment_react(reaction_duration=0.25,\n",
" initial_step=0.05, variable_steps=True, explain_variable_steps=False)"
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"#dynamics.explain_time_advance()"
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[
0.8888888888888888,
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[
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]
]
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"colorway": [
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"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
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"font": {
"color": "#2a3f5f"
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"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
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"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
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},
"scene": {
"xaxis": {
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"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
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"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
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},
"zaxis": {
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"gridwidth": 2,
"linecolor": "white",
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},
"shapedefaults": {
"line": {
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},
"ternary": {
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"baxis": {
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"bgcolor": "#E5ECF6",
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},
"title": {
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"xaxis": {
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"ticks": "",
"title": {
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}
}
},
"title": {
"text": "WITH zero enzyme.
Changes in concentration for `A <-> B` and `A + E <-> B + E` (time steps shown in dashed lines)"
},
"xaxis": {
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"autorange": true,
"domain": [
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"range": [
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"title": {
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"domain": [
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"text": "concentration"
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k9SuWifT15YpjUsyyitqkc028bK7ReD+drglzng2pbNb/+Wef0vThvNPXk5ljUXlZ9vt5PBZmvOrxeHkRhGmRd8Tyz616rZQ9I4RpZ4S7RZiq2Xfbmu4sopwFAQhAAAI+E0CYJkQvy4e/PQ98RdZetEbfgo8w9fkl4N7Yy77ALLv9Ton6JEyNEFO379++c6/EJU0nDIzoeOhrj3ScEWejDTN2V8V6J2zj55QtTM0H3ve/+x36LoWistJVYRrNXu1UoJtY/PiFlxKzLbPGO02Ymg/tqrZuJ3HwTZi2EuSuvvdnjXHaHxO65Tb2boxPkdjmObeK9/SqSm8VEaZ5mFVxbKv35Sr6pw8IQAACEIBAUQII0xjBTrJRjDC9dcsGuWnbrsYt/PFbHaMyI9pt0i2RWduMyg31gdB8nXHKm+TFg69KvLZR0hiSPuhG60iqNrPe0hi/4I9eLL3r7WfqmkbmK+8H7KRbG+MfgOPjTssQVoIr63iy9Bs/Jh7T6C2Sav7RWEXnkHb7pjnGrIs7/+Cjcuf/8zlRcu0Nxx2jb6P8zj/9a1O7qh/znKmH1qr9N7/pjVruJMm/MrhGXwNRaRJ9PMomzxguec9/0Js4KQlj+5bjeAbXvX/yV4VqGNuUnIZdtM1O599OmNqQxNFYZy2B0sl7yoL3s/D9sYx6tdHX+q+8822pr6k8v7xdE6Y2RGmaxFav2by/G1Rb7YRpp1LNN2Ga9gfcrL9bzJ0z0T9gxX9nmfjEX1dJcct6zZH2emh1LdJuTqrNeEmKpGuZPNdbSSUusor4duea99y7/q//Tf5075f07/dW11/x35vx3/dJpRnSMpDj7/d5x5IUv/ha7OS9O/O6SHhPT1ofcUam/XbXvHnWSNZ1p45LiqG6M+GENx7XtjRSUnxtXIO3u55NGrd6LO19u8jvrzy/JzkWAhCAAAQgUAYBhGmMaic1d5JqGSZ9eFMXqjvuvV8+dOmvNQr6p128Zm1TDT/ptqekC6mkuSWNM36R2+oWv/iiTLtYU3Vgo/Iyz22iaRJbzedrX/+2/N6HL5akMSbV5EyrLZg0njz9xm+fjjOMXhRHLyqTpFS72ybVhkhJF/3qPPUV3Z08T/tpa1bVo1Rf5vbOolzT3sjSMkw7iW2nkjDLm2z8tZVnLUfbL0OUxsdfRJymrcOysqBU/Ld9eo9s+diHGpvnJa1JG6/hTmOWZX3E+di4A6HIB06bcy1DlMaZpr1XtmOfJkyLZjj5JEzbzbXd75ZoBl30dRb/nWX+4Nfud1nWa45WUiw6pqTfBe3mFK/LmnR80vVWUl9Jr6Ws74dZzjWiKvr7Pe36K629aCZ10to1MVHMo5tLxbMa84wla/zyvHentZl2XZbGI8s1UZZr3qLX5EnrJOlutjzX23mEaZZr8DS2adez0YSMVr9nbP4Oavd7gOchAAEIQAACtgkgTFOEaZ5dJ1tldGTZLdrc3hu/eE26/Sf+wTntNqQk+ZR2m0/0Qu7o1y1NzYj60v5vygVrzpbRkaHUddjqr9vRnXrzfAjN8oEk7Zj4BWW7OnfRjWqy9JsUOwUn3m/aJhxJcWr3ATDPbWF52k9iUwbXvMK06Bhsv2nGx5PnA44Zi/kwmjVzu+gcouI0a73IpOwcM46qxq36i7/n5XkNt3t92s4wTVoLNnYytiFM09ZQlj8upMmzouuy1flRcZolgy8tQ9n00UnWqjo3z++qpPm0eh2p47O+HrOwbrfW8vxuSfsDVp7Hs1xzpO0G30r+Rq9F2v1+iL/Gs/yR2LCOi560a73v/fO/yejIcMud7bOcmzaX+PtYKzbxfuLvHernL//9t/QU/9df/kX9B9Y81wlp76lJ67NVhmmn14NF39Pjc826zrJe57e7Jjd3ZrR6X0l73cQZ5xGmabWdo9e87diaz0WtXnNj4xPy1l94U9NQ094zsryncQwEIAABCECgbgII05KFadJtgEkfoOIZg60uzqJtpl24pF0UJm2oE73Ae+spJ+sdrtWtYJ18wMwrTBX++MYU8RdFlovHtGPiF8PtZEt0PEX6jV8MtxOm0YvZPB9q0y6g1W2t0a92mUDq2LQPkj858PKCGBXhmvaml3ZRXTS2Nt9ks97O2K7PToRp0vtGFtkVlT7qdZ1V0LRbhyrTOYvIasci6fWu2o5+RQVt3tdw0h8Yyqp3l+cW2HavA5UR1O4ry3u0jeyeToRpmsDMumY6FaZJpSJMW+e89efb/r5Jum06KQ5pt/bGj83yh7d2cc76fLt13e41nZRhGr9myCpMW0mSduOMv2e1Wudpc2r1R4b475S0663469m8B2d9343GLcu5rYSpKmdkXjut+MXbiEqwVce9Xl/frTn3ND20R779ff16eP6FF3UJm6hczjqWVmszrzDNej2Y5z09fsu7Ga9ZU9E/JrZaZ3muydMSJaLrzjBPSs7Icu2p5mFDmGa55o1fz5r3yKx/OEWYZn0H5zgIQAACEHCRAMI0FpVOb8lPywaNyk1z0fDiy6803QqVN8M02mbaRVz8AiXtojE6fXMxnlRzrNMPh3nkRtILJEv2Xqtj4s+NT0wkZtDGj1Njid+KHh9fEqf4MUZOVSFMzS1j0Yv+PJkj8ViVwbVVdnLSWG2MweYbb7vXURaBZcbj6y35avytsnI65W3Yvv7o5U27yufNMDUfAFu9hrMIm07m0SqbMOt7aFK/NjJMs4rKVvP28ZZ8M59OxaWNDNNO66fmXYPt1nWVwrTde6WaW7s1meVaJG1O5vdhGsOo9Mx6HaXaSnqNZ33fb3duVkmZ5/bn6O/Vs05/s3xi2y751JYNGov5/uWDr+rNC039WjPPpHWb5w8wtoVpq+uBpLWf9ZooyzrLKkyzrrvvPf2srumf9BqoQ5ia35embm7S6yaprFb0uLQ/xiJM876TczwEIAABCLhEAGEai0ZaDZ9WQct6IZX1divVV542k/6anSfDtN2CTBMZaR/skyRx2u1ARm60EmlZLh6LZiEmXYgX6TfOpmxh2q79aJZQu6zkaKzK4Jq23nzIME17XWYR+2nzLkOcRtvsJBuq1Qdm9ZyJ1Qmrjm2bsdfu/cU8n/WWxzx/hElbv+3EUtYxR49rJZHb3Srdrj9XhKkZZxniNCrYsgqorPyjoqudpIvHwkdhmlZSqEphWoYkSboW6STDNB7jrBmmaWtDSaZO11X03KzCNE+GaXT9nnT8ykZWqRFkKtv0Bz/6icTvJMk6ljzXxnneu9PazfqenueaKO16LfrHu6LX5Gl9JJWFyXLtqdqrKsO03e8n85lF3RmS9N5dxntBljFxDAQgAAEIQMAGAYRpAsWkQuzxwx5+5Dt65/gVy5dmlptpF1xFMkzT/tofv0DJKnTUeepW0AvWnNU05azZOWXckp/Wt5rTw488If/xwvN11kdSNkT8gjLPBXuRftMujuMfZJPG06pGWKs1lJStkHShmtZ+0ljK4Jr2xpV2UV10DDbeKFUb7bIqTfZQ3g/OZnw2xKmNNsx4Wr3m27HIy7zV+1OnGabqjzDt1o7NGqatMq86+UNclKFrwtSMzYY4jYrSrOUiktZXuzWZ9XeYz8K0HYM8v1uy3npveHV6zdHq90GWa5G0ORXJhIyu7y3bdjXuCEqq4571jyFZzs0qKVvFOekawbSrdl9f9+u/0tgYUj0er2fa7v2/CNc8119p6yLre3rWa+Os17xZhWlWPu1imFQKKct1ZZFr8KzvkdHPP/HXf1JJlKxM8l43cDwEIAABCECgCgII0xTKRn7EP8CZixx1mrl9qciFlLmQ6LSGaZJoSKvJlFbHTR2/49775UOX/pokbfqUVbYqJkUu1tIWfJJsiGf9JB2TlAWX54I9T7+Pf+9fmsosGBbqf7WpQrtsh+hFZqsPYO1uHYy2Y+aqPnRG/+qfZyxlcM0rTIuOwdYbabuL/nayIus4OpVrSe9NWftMOq7VHwxUuYqkNW+7P/M+3GkN06SYRF8XncrtpHmmvTbjcrGTPl0VpvG55c0MNa+pIqI0zwf2TvrxKcNUsWi1DvP8bikqTNVYslxz5Nn0KelapN2ckmotq3X39Ue/K2bjoSRmSeWZWsnI6KadWd8f4u+xWYWpaj/pD/tpf7Qzc1HnRceZ9njStVwn72O2b8lXY8j6nt7uOPNelXRc2h1HWUpvmddglnWXFG8Twyx3htjOMDXzbnc9mzTuVtdHRX5/Fbmm4FwIQAACEICADQII0xYUox+so4fFP3RlFabRi1zTnmrrXW8/U6JZDK0+9CRdqMTrLyn5qjKnVE2q+IYNSbWaVH/ROSXVHsv6QbMMYWpYxWtDJV1Qxo9JE955SgRk6ddc5EbXSVTy5JGUSevESJZWH4bj61X1f+uWDXLTtl0L1kF8YxPV/pvf9MbE+q7RDwDRdRvd5TaPiE57yaV9QE+Lf9bY2nijzCox20kzG2Opqo2kNW36zvJhrpNxxvtUH2rVV7TsSN61lvS6uGHjOv2eayvDNEmuxOdfRKgX+cDZbhOjsmLZSfyLnJP2+9q02YmoVufaEKY3b9+dOrWsv1uzsmn3h52k9/7zzj5lgWi1IUyj/OK1EbPMO+u1SNqckn6XqseS/kAd32hOHRf/A0DS9VPWjW+ynJtHmKrxxfmk1UlO+uNxNDY/fP5AU/1S9VzesSStzzKEqeon63t61muiLOssz3V+1nVnOEffH9SaSyqRkMTXtjA1fbS7nk26Jmy39pIyT7O+p3EcBCAAAQhAoE4CCNM66ZfYdxk1+kocLk1DAAIQgAAEIFCQQJ47Qgp21TWnd9MfuromKEykKwhkvc2/KybLJCAAAQhAoCsJIEy7IKzqYl9lqaosEfOVtWh8F0yfKUAAAhCAAAQgEBLIWlcTYAEBhCkrAQL2CfA+ZJ8pLUIAAhCAQPUEEKbVM7feY/yWcdVBltvdrA+EBiEAAQhAAAIQqJ1AWh322gfm4AAQpg4GhSF5TcCUyeiWki9eB4PBQwACEIBAIQII00L4OBkCEIAABCAAAQhAAAIQgAAEIAABCEAAAhDoJgII026KJnOBAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEChFAmBbCx8kQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBANxFAmHZTNJkLBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgUIgAwrQQPk6GAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEuokAwrSboslcIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgUIEEKaF8HEyBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQg0E0EEKbdFE3mAgEIQAACEIAABCAAAQhAAAIQgAAEIAABCBQigDAthI+TIQABCEAAAhCAAAQgAAEIQAACEIAABCAAgW4igDDtpmgyFwhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQKAQAYRpIXycDAEIQAACEIAABCAAAQhAAAIQgAAEIAABCHQTAYRpN0WTuUAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAKFCCBMC+HjZAhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQKCbCCBMuymazAUCEIAABCAAAQhAAAIQgAAEIAABCEAAAhAoRABhWggfJ0MAAhCAAAQgAAEIQAACEIAABCAAAQhAAALdRABh2k3RZC4QgAAEIAABCEAAAhCAAAQgAAEIQAACEIBAIQII00L4OBkCEIAABCAAAQhAAAIQgAAEIAABCEAAAhDoJgII026KJnOBAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEChFAmBbCx8kQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBANxFAmHZTNJkLBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgUIgAwrQQPk6GAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEuokAwrSboslcIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgUIEEKaF8HEyBCAAAQhAAAIQgAAWXt4SAAAgAElEQVQEIAABCEAAAhCAAAQg0E0EEKbdFE3mAgEIQAACEIAABCAAAQhAAAIQgAAEIAABCBQigDAthI+TIQABCEAAAhCAAAQgAAEIQAACEIAABCAAgW4igDC1EM1DY9Ny6MiUhZZoAgIQWHn0qBw4OCazc7CAAARsEDj2dSPy8qEJmZ7hRWWDJ21A4Jhlw/La2JRMTM0CAwIQsEBgxZIhGZ+akbGJGQut0QQEILD8qEF93Xd4fBoYHhBYdcyoB6PszSEiTC3EXclSJU35ggAEihNAmBZnSAsQiBJAmLIeIGCXAMLULk9agwDClDUAAbsEEKZ2eZbdGsK0bMKdt48w7Zxd40yEqQWINAGBkADClKUAAbsEEKZ2edIaBBCmrAEI2CWAMLXLk9YggDD1aw0gTN2NF8K0YGxuueUWuX7TTWSYFuTI6RAwBPbsvlsuu3K9DI8sBgoEIGCBwF/vvU8ufPf7ZfmK11tojSbKIvDvP/w3efKJb8l7f/3ysrqgXUsEvvLQ5+Wst50vx646wVKLNFMGgZdePCD7v7pPPnDFVWU0T5sWCfzj/i/KG48/SU5cfarFVmnKNoGxI4flL++/Tz68/qO2m6Y9ywQef3S/LFmyTN5y+jmWW6Y52wR23b1dtm7dartZ2rNEoOeF6dj4pGzdsVse+tojDaT33bVZzjv7lMbPD+x7WG7evlv//L6L1sgtm9bL6MiQ/hlhamkl0gwEQgIIU5YCBOwSQJja5VlWawjTssjabxdhap9pGS0iTMugWk6bCNNyuNpuFWFqm2h57SFMy2Nru2WEqW2idtvreWF68JVD8sf3f1Gu+chvaAn62BNPy5Ztu2Tn9htk9Ymr9M+379wr9952naxYvlTu2LlXR+D6jesQpnbXIq1BQBNAmLIQIGCXAMLULs+yWkOYlkXWfrsIU/tMy2gRYVoG1XLaRJiWw9V2qwhT20TLaw9hWh5b2y0jTG0TtdtezwvTOE4lUK/ZfKfcsHGdzjJVgvSk41fKpWsv0IfGBap6jBqmdhclrfU2AWqY9nb8mb19AtQwtc+UFnubADVMezv+zN4+AWqY2mdKi71NgBqmfsWfGqbuxgthGovNM889L5/Ytks+tWWDrDru9fp2/TXnntYQptHnVQYqwtTdxc3I/CSAMPUzbozaXQIIU3djw8j8JIAw9TNujNpdAghTd2PDyPwkgDD1K26uCVNVkvKRb3+/qRSlX0SD0SYlO+adB8I0QszUMzWC1Px8+cUXNmqaLhCmj3xK5NFPydyiUZkbGBUZGNXfy+Di4P+BxTI3OCKyaHHwfPh4n3le/a8eV+cPmvMXB+0MmP/Dx9Vx0pc3xhwPAa8ILBkdkMNj0zLn1ajdGezc3Jz09fE+4U5E6h/JUSMDMjYxLbO8qOoPRg+OoBvfkxYPL5LJqVmZ5kXVgyuaKZdBYHRokUzPzMrUTPm/qObmRLhMKiOKtOkSgZHBfn3dNzk969KwGEsKgaWjA5WyUU5r4423y49feKnR7xuOO6ZRlrIuYWr828pjj26UwCwCBmFahF7s3KTgxAWqOiUuTNWmT1uX/IHFkbRpatFIKFJHQkkbl6oR2aqOHVwsfUraavmqzg0lbkPqjgRS1zw+EPkZOVtdXOmpQeAzf3iXXLX+92RkdDFUOiCgPmqgSzsA18Wn/Pmf/FdZ+/5L5Ohj/pcunqX/U/vBD56Vxx/7plx6+RX+TyYygznpk74u+xPYFz5/v/zi29fI8cef1FWx6rbJ/PSnB+RvH/p/5T9f9bvdNrWum8+X//ZBOfGkk+UXTjm99LnN9fVJn7KmfOUmcOTwYfnT+/6rXP3R/z33uZxQLYGv//3XZOmyZXL2286rtmN6y03gjh23ytatW3Of1+kJZkPz+EbnSi5+7sH9Oqv0i3/3CBmmIWAyTEWklcluV8NUCdPrr7tODh86JH0zY9I3c0T6Zsalbyr8X/88Jn1T4+FzY9I3PSain1fHq5+PSN/0ePB/4zH1XOSx6eBnqfBDx1y/EqzzYnYulLVKrpqM2sb3OoN2RGTwKNHH6YxZlWWrvg+ybVUGrf5f/xzIXNMmiqfTt7zuO49Nn7ovpsyoXgJs+lQv/6y9s+lTVlL1H8emT/XHIMsI2PQpCyU3jmHTJzfi0G4UbPrUjpA7z7PpkzuxaDeSKjd9Mpml27ZsaNxBnTQ+k2H6/ne/Q+/vo76iGajmHCNfzc9RCWuyO3/7N98j1//BPU1tfOef/lVu3r5bP3bGqSc3NlhPSlhUx8T7+Z0PrtUZqEmZsp+8cX3L/YfaxSP+fM8L07SgGFDxNF4lUNWXCpD60sJ0001yaGw6L/uOjg8Ea4Jc1UI1/Ddlvg+krUweDuRrQ95GRK2WspFzjbydGatYzg6HcjaUq7okQVCWoCFqjbDV5Q9UJqySs+a48H8jZHU2bdhWQ9YG8lb6+jtiz0nVEECYVsOZXnqHAMLUj1gjTP2IkxolwtSPWCFM/YiTGiXC1I9YIUz9iJMaJcLUn1hVKUyVeNz74P6GoEyjZASlEZPqOOXBfnLg5UZd0/ht+3EZqzzaVR+/TeJt/NFn9y14zPi1JDcXH7M65i8f+nv5wPt+WZ5/4UX52te/Lb/34Yv1VJLGcPvOvW3n22q19LwwTbLSClg0sFGj/b6L1iwofnvoyFRlwrTKl36Q4RqXqyZzNjkzVmfONgTskVhmbbrorTZzdiiQsUly1Yha/Vz4T9eWVfI1yKJtlrgRUduQu+Yx5Gwn65VNnzqhxjkQSCfApk+sDgjYJcCmT3Z50hoE2PSJNQABuwTY9Mkuz7Jbq2rTp7j0bCVM45s+RRMJ1Xlbbt0lm669QsxG6EaqGvmZVD+03WMjw8NNm64ffOWQznC9YeO6lhmx0XlE7xCnhmnZKzdj+90qTDNO38phgZxtLlsQiNfwsUbW7Lyolekwc9aUMmg6JkH06vZV5mx1xa/n+ociGbKRbNh4WYKIvA3KGkSPNSUQQmHbKHEQKXegatD2LbISi7obQZjWHQH67zYCCNNuiyjzqZsAwrTuCNB/txFAmHZbRJlP3QQQpnVHIF//vgnTl392aMGmUWbGJvGwnRxdsXypPiV6XFyYquTGHffcL9tu2iDm+DhZk8kafbzVGPJFRlTNa6pe54UWPx5hWpRgtef3zU5IX1Su6jIH4T9dbzZef3ZMJFpfNkHeNsodmHbCLNtq5ezgfFas3sgrVpZASdVFIzKrNgBbNCqz6mddRzZWU3ZBzdlY/dmS5SzCtNrXA711PwGEaffHmBlWSwBhWi1veut+AgjT7o8xM6yWAMK0Wt5Fe6tKmOa5Jb9VhqkSpp/Ytks+tWVDU4ZplEMVwlRlk+77u0dl5/YbGuOIltAkw7ToyrRwftU1TC0MmSYqJKDlbJjZ2tjcy9SSjclVLV2nx0WmVOZsmF2bIG+TNxcbE5mbqWxmc/2DgXxVNWGVfFVlC7SEVT8rURspaWDkrcmcXZA9azJng5q1f/KXX5Z1l/2GDC1eoQWw9A9UNi86gkA3EqCGqR9RpYapH3FSo6SGqR+xooapH3FSo6SGqR+xooapH3FSo6SGqT+xqrKGaatNn6K1Qb/4d49Iu1vy290qb0OYtrol39Q7vfziC5tu10eYOrb2EaaOBaSHh9M3M5m8uVcoYrWw1aUP1P9BRm0jczZF3jaO1Zm385uDlSlndxy+UT66+G5Z3HckiGbfQHPN2cFoKYKFWbQNWasErcqyDTNmteAdDISuFr0DYZZtVPQqEcwXBLqMAMLUj4AiTP2IE8LUnzghTP2JFcLUj1ghTP2IE8LUnzipkVYpTFV/Zn+e6I72RkyesOpYvV9PO2Gqbo9Pyu5UkvRHzx/Qu9TbEKZqvKqfbz7xdGPjJiN21170Drntv/y5rDz26MaG7PGNpsgwdeC1gDB1IAgMoXICfbNTzZt7qSzaiIid3/grWnNWidogizZJ3gYS94jc+eP/JNcs3yNHzR3Uglfmpqubn5KzOkNWZb2qLNmIkDVZs43NveZryqpNwUyWbWOzsOgGYibL1pQ7UM8hZ6uLa4/3hDD1YwEgTP2IE8LUnzghTP2JFcLUj1ghTP2IE8LUnzjVIUxVn0kbn8c3PW+VYWrqiUY3R1ftvuG4Yxq3x9sSpkaa/tFn9zUCa8ZqRO+TTz2rn1OPm6/rN65LlLZ5Vwc1TPMSSzieGqYWINIEBEIC8RqmSs7KzLj0Tx8RmRmTfp0ZOyb9M+rncemfCv/XPyvpOi59pqxBtDZtKGSTNxcLM24rlbOL5mvODiaUMIjK1Yh8lQGTORuUMJgXvJHM20Z74fOLhlhfPUyAGqY9HHymXgoBapiWgpVGe5gANUx7OPhMvRQC1DAtBWtpjVZVw7S0CXRxwwhTC8FFmFqASBMQSBGmlYKZnQ7rx85nxjaVJQg382raJEyXKzgcyZwNSxdEZK0WvVNjgfANRa8WwVV99Rk5OyJzeqOvFnLVPK/q0SZlxkYzZ5XUjW8uhpytKqqZ+0GYZkbFgRDIRABhmgkTB0EgMwGEaWZUHAiBTAQQppkwOXMQwtSZUCwYCMLUQmwQphYg0gQEXBCmVUZhbiYsaxDWlDU1YlVpA7NRmN4gTGXMhv8r2Tp1JMiy1dm2YXZt+L8pazBf9iCUt1XKWekPMmeNWG1sAJYgVyOZtVrOxjNjtbyNtKW+1z+HbfUPVxkxb/tCmHobOgbuKAGEqaOBYVjeEkCYehs6Bu4oAYSpo4FJGRbC1N14IUwLxoYapgUBcjoEYgT27L5bLrtyvQyPLIaNLQINOasE6hHpmxoP/jclDEz92XAzMFODVkzmbOPYoHSBlri6Hq35OczIVY/PTtoadYZ2jJw1tWZTas42ZcGOSKOsgS5pEEpYLWvD7NtGFm74mN48bCTDeNw8hBqmbsYlPipqmPoRJzXKrzz0eTnrbefLsatO8GfQPThSapj6E3RqmPoRK2qY+hEnNcrHH90vS5Ysk7ecfo4/g+7RkVa96VOPYu542gjTjtEFJyJMCwLkdAggTLtrDczNNstUU8bAyFhTS1bJ1UY27RER9b3JsjWZtXEhqzNvjegdq1jO9rXOdjU1Zwcj5Q4GRkVMlmw0MzYqahM3F7MrZxGmfrzEEKZ+xAlh6k+cEKb+xAph6kesEKZ+xAlh6k+c1EgRpm7HC2FaMD4I04IAOR0CCFPWQAECfVOvhXVnTeZsmEWr5GrWzFlT9mB2QvqmVT3a5szZ/qlXC4yws1OD0gPN8lWXOWiUJQhLFRgRqzJgB4+a3wRMPR6WOPiLv39W3r3mVFm+4hiZ61dZuMMiup0RmR1a3tkAOcs6AYSpdaSlNUiGaWlorTaMMLWKs9TGEKal4rXWOMLUGsrSGyLDtHTE1jpAmFpDWUpDCFMLWKlhagEiTUAgJLDy6FE5cHBMZudAAgGHCOjM2bAmrM6EjWS7xjNjdc3ZQLrqzNl4ZmzT5mFhfVojd9VzsxMVT1xlzyqROhIIVS1hlVQNv180HIraQLbq57V4HdHHiK5X23xusLGYkrLB8bqtsLSBPldl4vaPiPT1VzxXuoNAcQLUMC3OkBYgECVADVPWAwTsEqCGqV2eZbdGDdOyCXfePsK0c3aNMxGmFiDSBAQQpqwBCDQI6ExXJV0bMtbUiQ2zYKP1ZkMBG8jZUOpqARtk2Q73Tcr0+GERLXnDf2ZjsenXaqc+N7AkFLZB1mvjnxKxamMvLVqD73XWrJa6w0G5g1Dc6hqz5tzo8eb7UPRKv8qqXVb7nBmA3wQQpn7Hj9G7RwBh6l5MGJHfBBCmfsUPYepuvBCmFmKDMLUAkSYggDBlDUCgFALHvm5EXj40IdMzKWnbKnt2djzYDEz9r0XreChYlYCdCEWrkrbqe5UFq46Z0Bm0WsQqARs5NxCz8+eKFrzN56pjRGZLmXP7RtWGYZGs1zAbtpFV25RJG82wDTJqlXhtZMyGGbnR7NymrFoteOePF+lrPzyOcJoAwtTp8DA4DwkgTD0MGkN2mgDC1OnwLBgcwtTdeCFMC8aGGqYFAXI6BGIE9uy+Wy67cr0MjyyGDQQgYIGA65s+9U++ooVsQ6pq8apk6+T8xmCqvuyMKnEwnyUrOpvW/BwRsrqtUM6a47XgNTLYgazawaVBdqzOmA2E7DNTx8s3Xz1Z1v3c00FWbVhvVstWU3u2IWuHw0zbsExCo0RC+HijRMJwUDpB96H+2d1QzMLy9LIJapj6ETZqmPoRJzVKapj6EStqmPoRJzVKapj6EytqmLodK4RpwfggTAsC5HQIIExZAxAolYDrwrTUyac1bmrSRrNeTaasFrMTYcZss4hV2ba69EE0CzcqY00mbSh9dTta/ipZG2TqiiRn+j4z82b5xuQa+fDon5eIpC8QtCqDVtWQ1SULIpJVy9mwDEIuYWtq3obtNcojDAfZuPrn7hG2CNMSl6jFphGmFmGW3BTCtGTAlppHmFoCWUEzCNMKIFvqAmE6D/KxJ56Wqz5+m3zyxvVy6doLLBEu1gzCtBg/QZgWBMjpEECYsgYgUCoBhGmpeHM3bmRrUMIglLMz4/Kj//m8fOef/10ueccJYYmDiea6s0rW6qxbVd82fE5l3mopG5ZEUGUSGgI3lL4OZdYaWHMmw7axEViQCRuUMhgKBGtM2MqAenyxiJa9gXw1m42JkrHRrNxQ0gbHmpII6hw7dy4gTHMv+1pOQJjWgr2jThGmHWGr/CSEaeXIO+4QYdoxuspPRJjOI79j5179w08OvCy3bFovoyNDlccj3iHC1EIIqGFqASJNQCAksPLoUTlwcExmU8otAgoCEMhHoG0N03zNcbTnBHTGa5hBG9SfjYhVXfogrGGrha762dSwVdm1Y6HEbZa0pjRCUAohsrmYFrqmHq7qZ6J2enP9Q6IFa7QOrc66DUsXxCWrysTVcjbMyh0clcWLj5Lx2UGZ6gsfyyJslQgeOKr2+TMACLhIgBqmLkaFMflMgBqmfkWPGqYiB185JNs+vUeu/sglsv0PPyubrr1CVp+4qvZAIkwthABhagEiTUAAYcoagEApBBCmpWCl0Q4JNJUn0Nmwk+EmYkGWrJauZhOxhOxZXbu2UTJhXvjq+rYR4Rtk8KpM3Hnh26okQofTyX9a30BTiQJTriDYcCxW0sCUMYiWNBgYbZQ30DVpwzIKQYZtpNxCRPIG2buh3O0fyD9mzoBAyQQQpiUDpvmeI4Aw9SvklQvTnz0jcuhH1UN63WqRpccn9qtux//6o9+V6zeuE5VpetLxK524LR9hamGZIEwtQKQJCCBMWQMQKIUAwrQUrDTqKQG1mZgkiNVGlmyCjA02JQtr0E6PyeiiaZmeOCKzk2NB1myYSRuVwVr+xoRvIGxn6yXXtyh5Q7FoGYRG9m1YgzZSOiGoextk3Dbq00azcheF9WyNwI2XTugfrHf+9O4kAYSpk2FhUB4TQJj6FbzKhenDN4o8tqN6SBdsFzlvU2K/SpK+6+1nynlnnyJKnt6+c6/ce9t1smL50urHGekRYVoQPzVMCwLkdAjECOzZfbdcduV6GR6xU2sOwBDodQLUMPVjBfz7D/9NnnziW/LeX7/cjwH38CiL1DDtm50K5Gt0s7B46YJITVotWSOZuDIVSNoFpROiWbk6UzdSbiHyvczN1By5/oZwNfVlm2rN6qzacIOwaPZsmGUrOsNWZdaGdWwX1LoNH180Ii++Oi5f+/8el8su/U/BObr2bf310GoOgJPdU8PUybAsGBQ1TP2IkxolNUz9iVUtNUy/8xmRf/6L6iGddbXIL/zmgn6fee552XHP/bLtpg1akKrb86/ZfKfcsHGdFqh1fiFMC9JHmBYEyOkQQJiyBiBQKgGEaal4rTWOMLWGsvSGigjT0gfXroPZ6UDWxkofaMGqRey8jNXZs9GatKrEgSqJoB+LPhetXRtm4obHzNe0DTNxlTCu6OuF2ZXyhfHfkKsXfybSY19Y+mBIZ9oGGbMLa9rqx2MyVmfVDowGmbUJtW51HVzd1ry0bcrENSK4ovn71A3C1I9oIUz9iBPC1J84qZHWIkwdQ/TAvofl5u27F4zqdz64Vt+iX+cXwrQgfYRpQYCcDgGEKWsAAqUSQJiWitda4whTayhLb8hrYVo6nfYd9M0cCerQhpm0C0oXhNm3SZm4QYZtkD0bSN4wkzYUvo2atdPjcmBisTx48O3ye8vvn6+POzvZfoAlHxEI1YTSBWEd20b2bLQOrcmwVZmyOss2EL6mPm0gccNyCeEmZkb4BnVuQ8m7aLTk2XXWPMK0M25Vn4UwrZp45/2RYdo5u6rP7HVhOjY+KVt37JY1557WVLM0nnVadVxMfwhTC+SpYWoBIk1AICSw8uhROXBwTGbnQAIBCNggQA1TGxRpAwLzBI5ZNiyvjU3JxFTN9UgJSkcE+mbmNw5rKl0Q2zhMl0JIyMQNsm7nhW9D/kZq3TYya+PlFlTWbs1fc/1DYSZsgmRtKneQvImYDI7OZ9GGmbha8kazcpWg1XI3zN418ndRcrklapjWvCjovusIUMPUr5BWXsPUITxKjH5i2y751JYNsvrEVY2RGZF6+cUX1npbPsLUwmJBmFqASBMQQJiyBiBQCgGEaSlYabSHCSBMezj4FqYe3RwsqE/bXNKgsYlYU/ZsmFWrNxObF75BLdugJq7EhK8pvRA8bo5Twrbev0jPqY2/GmULgvIF/YMjMtuv/s3XsNWbi0Xr2ZrvdYbtfNmDIIM2FLbRc/Rj0XILwffSP2AhijQBAbcJIEzdjk98dL0sTF2PFMLUQoQQphYg0gQEEKasAQiUQgBhWgpWGu1hAgjTHg5+F0y9b2ZStJTVsjWUqSZjVmXJhgI2KmP15mPhMUEd21a1bifTyy2odqTmzOy+Rcn1aaOlC1qUOwgybAOZ2yifEM2kTSq3EM3EVcKYLwiUTABhWjJgy80jTC0DtdgcwrQgTGqYFgTI6RCIEdiz+2657Mr1MjySfNsWwCAAgXwEqGGaj1ddR1PDtC7y+fulhml+ZnWc8dKLB2T/V/fJB664qo7u6TOFQJ/a+EsJ17BWrZKxX//GY3L8ccvl5DcsTyx3EM3E1cJ2NpSy0+OSVDpBZ9xGsm+bMnHnZmqOTX+w8VhEsjaVLjDZs2oTMZUlG8ueDWrYhhuMNdWnDWrV6rbCerjxDc2CzN6hjudPDdOO0VV+IjVMK0fecYe9XsO0Y3AVnYgwLQgaYVoQIKdDAGHKGoBAqQQQpqXitdY4wtQaytIbQpiWjthKBwhTKxgraaTqTZ/6pl5rErZ9CbVmF5Q7CCWvzExJ3/ThRoZuLmE7c7gSnu06aWwCpgWrEq1DEckakbExsXt4dkT+9LtL5OpfGgjKIjRk7rA0Nh6LlkJo1LE1pRFUmYSj2g2P5y0QQJhagFhREwjTikB32A3CtENw5jSEaUGAnA4BhClrAAKlEkCYlorXWuMIU2soS28IYVo6YisdIEytYKykkaqFaSWTatGJFq669IGpPxvbRCzMvo1n4qrjZUpl2IY1bVUWbUqt20b7kdILQXuTHU//8NwSuffI1fL7R/3fHbehTpyvY9ucDTtfj7a59qzOjDWbiqmSB2Ed20ZJBF1CwbQVlkowZRX0/0OB0I3WuC00A/dPRpi6HyMzQoSp27FCmFqIDzVMLUCkCQiEBFYePSoHDo7JbL17EhAPCHQNAWqYdk0omYgjBKhh6kggGEbXEFixZEjGp2ZkbKLu2+W7BmnLifTNHJnfbExvGJZD2OpjxxJq3QZtmFq3OkNX18qdCDcki2xQ5gjmuYElYXmEoJxBU13ayMZiuoxBo66tErBH6c3DTGmFeRkbZurGSyOYzcx0mYURmR1aVjoBapiWjthqB9QwtYrTamO1CtODrxySazbfKU8+9eyCSZ1x6sly723XyYrlS61OuIzGEKZlUKXNXiWAMO3VyDPvsgggTMsiS7u9SgBh2quRZ95lEUCYlkXW3Xb7pg5FNh4Ls21VTVolWs2mYrpUgsnCDR9XWbZ647HgZ328OS7MuNVlE2bGwk3NYhucTR1yCsrs4DLRmbU6gzZa5mBUZNFQ8FikNEJwbHCcybQ1NWuDTNzg+MVLlsvMXL+MzQwEJRfU8YsGwzIKwyJ9Su4Ggpev+gkgTOuPQdoIahWmd+zcq8d1/cZ17hLKMDKEaQZIHAKBjAQQphlBcRgEMhJAmGYExWEQyEgAYZoRFIdBICMBhGlGUBxmjYCRrI0NxVRpAyNqdaZsuLFYpORBkD0bClxdGiGeVRvKWS1zJ4MNyaaN6I1k2BYsjWANQtjQfImEQKg2RG3/UETaqixbJViVrA1kq9lELCpjTU1c3YaSsgOqvq2SuGHbpo3web1JmT4ubM98Hwpd23N1tT2EqauREalNmKrs0i237pJN114hq09c5QQhJXBPOn6lXLr2gsZ4nnnuedl44+3y4xdeajwWzX6lhqkToWMQXURgz+675bIr18vwyOIumhVTgUB9BKhhWh/7PD1TwzQPrXqPpYZpvfyz9k4N06yk6j+u12qY1k+8sxGMHTksf3n/ffLh9R/trAHOaiIQlEaY1HVodaZsmE2rJevcpJatQcZtJIvW1K/VpRRUpm0odtU5Kvs2zLzdf+B4Wdb/mpy35H8EZRJmVT+TgQjWole1/5oXEQlKJ5gsWfV/8E/XsI3K2EZGbrPcNQJYy9lopq2qhxvK30ACx+VuRPRG2ra9cRk1TN1ehghTEXlg38Ny8/bdOlKfvHH9AmH6iW275FNbNiSKXYSp2wuc0flHAGHqX8wYsdsEEKZux8eMDmHqR5zUKBGmfsQKYepHnNQoEaZ+xAph6kec1CjzbvrUN/VaQ6SKFqpT8zVolWwNReu8cJ2S4LhQxuqM2smwXq0St+b8QNCq5xptzKqSCWF9W/P4nDo3LM2gSyoc9gL23ODSUNtw2QUAACAASURBVNrGyh7EZGwruXvHN5bK1q1bvZhvLw6yNmGqYCdldNYZhLQMU4RpnVGh714jgDDttYgz37IJIEzLJmynfYSpHY5VtIIwrYJy8T4QpsUZVtUCwrQq0sX6QZgW41fl2XmFaZVjy9NXkDUbZMcGcrZZxgbS1mTPzsvb+fMC+auOE52FG4hbfV7j+/Zt63q5Uek7Z2+Dulte+4OeF6aPPfG0XPXx25qWxu98cK0TpTtrFabqdvc9D3xVNl1zhYyODOV57ZRybJZb8pM2o6KGaSnhoNEeJUAN0x4NPNMujQA1TEtDS8M9SoAapj0aeKZdGgFqmJaGloZ7lMDyowZlemZODo9P9yiB8qetSyqEMlaXU1BlFMJMW5N5Gy2B0Cxp1YZmk/qciePeKa8/9aLyB+xwD0qY3r5zb2PTd7M5/A0b18l5Z59S68hrE6YGwpNPPZsIIElMlk0qS8arOuYnB16WWzatd0Lyls2E9iEAAb8ITE3PyuBAv1+DZrQQgEDXEpicnpUh3pO6Nr5MDAK+EZianpPBgT7fhs14IQABCHQtgbgwHRuflK07dsuac09rKpdZB4DahGkdk23XZxZhqrJid9xzv2y7aYOsWL5UN0mGaTuyPA+B7ATIMM3OiiMhkIUAGaZZKHEMBLITIMM0OyuOhEAWAmSYZqHEMRDIToAM0+ysXDhy1TGjlQ7jmYPPyI9e+VGlfarOVh+9Wo5fdvyCfpMyTF3ZIB5hGglXJ8KUTZ8qf53RYZcToIZplweY6VVOgBqmlSPvqENqmHaErZaTqGFaC/bcnVLDNDey2k6ghmlt6HN1TA3TXLhqPbhbapjWCrGiznfdvb3yGqY3fuVG2fGPOyqa4Xw329+9XTb90qZEYRqvYfqG446RndtvSNx4vcqB1y5Mkwq83nfX5lpqFSQJ0y/t/6a8+U0/1wiUOkZ9Xb9xnf4fYVrlcqWvXiCAMO2FKDPHKgkgTKuk3XlfCNPO2VV9JsK0auKd9Ycw7YxbHWchTOugnr9PhGl+ZnWdgTCti3z+fusQpp/51mfkL/7pL/IPtuAZV//i1fKbp/9mojCN1jBVB8SzTgt23fHptQrTJAjqlveNN94u137kksrqFTyw72G5efvuBsSozY4L3fddtKapfinCtOO1x4kQSCSAMGVhQMAuAYSpXZ5ltYYwLYus/XYRpvaZltEiwrQMquW0iTAth6vtVhGmtomW1x7CtDy2tluuQ5jankPR9pK8oNrzyIXb8msTpqaQ6+UXX7ggm1QB+9yD+73ZWIkapkVfIpwPgXkC1DBlNUDALgFqmNrlSWsQoIYpawACdglQw9QuT1qDADVM/VoDVdcwdY1OkjDt+QzTVsY4aWMl14IaHQ/C1OXoMDbfCCBMfYsY43WdAMLU9QgxPt8IIEx9ixjjdZ0AwtT1CDE+3wggTP2KGML0aYnXMD3j1JPl3tuua2y0XldEyTC1QB5hagEiTUAgJIAwZSlAwC4BhKldnrQGAYQpawACdgkgTO3ypDUIIEz9WgO9LkxdjlZtwlRBUbVD9z64v8kc11HDtEiAqGFahB7nQmAhAWqYsiogYJcANUzt8iyrNWqYlkXWfrvUMLXPtIwWqWFaBtVy2qSGaTlcbbdKDVPbRMtrjxqm5bG13TI1TG0TtdtercJUTSW+qZJ67L67Ni+oa2p32vZaQ5jaY0lLEFAEEKasAwjYJYAwtcuzrNYQpmWRtd8uwtQ+0zJaRJiWQbWcNhGm5XC13SrC1DbR8tpDmJbH1nbLCFPbRO22V7swtTud6ltDmFbPnB67mwDCtLvjy+yqJ4AwrZ55Jz0iTDuhVs85CNN6uOftFWGal1h9xyNM62Ofp2eEaR5a9R6LMK2Xf57eEaZ5aFV/LMLUAnNqmFqASBMQCAlQw5SlAAG7BKhhapcnrUGAGqasAQjYJUANU7s8aQ0C1DD1aw1Qw9TdeCFMLcQGYWoBIk1AAGHKGoBAKQQQpqVgpdEeJoAw7eHgM/VSCCBMS8FKoz1MAGHqV/ARpu7Gq3JhevCVQ3LN5jvlt3/zPfLHf/G38uRTzybSOePUk5s2g3IXoQjC1OXoMDbfCJBh6lvEGK/rBBCmrkeI8flGAGHqW8QYr+sEEKauR4jx+UYAYepXxBCm7sarcmFqUChxuuXWXbLp2itk9YmrmgipjaA+9+B+uWXTehkdGXKXnohQw9Tp8DA4DwlQw9TDoDFkpwlQw9Tp8DQGRw1TP+KkRkkNUz9iRQ1TP+KkRkkNUz9iRQ1TP+KkRkkNU39iRQ1Tt2PlpDB95rnnZcc998u2mzbIiuVLnSaIMHU6PAzOQwIIUw+DxpCdJoAwdTo8CFM/wtM0SoSpH0FDmPoRJ4SpP3FCmPoTK4SpP7FCmLodKyeF6QP7HpZHvv19MkzdXjuMDgKlEECYloKVRnuYAMLUj+CTYepHnNQoEaZ+xAph6kecEKb+xAlh6k+sEKb+xAph6nasKhemKnt04423y49feCmVzBuOO0Z2br9hwa36rqKkhqmrkWFcPhKghqmPUWPMLhOghqnL0WFsPhKghqmPUWPMLhOghqnL0WFsPhKghqlfUev1GqaqJOdVH79tQdA+eeN6uXTtBbUGs3JhambbqoZprUQ66Bxh2gE0ToFACgGEKUsDAnYJIEzt8qQ1CCBMWQMQsEsAYWqXJ61BAGHq1xpAmD4tt+/c6+Sm77UJU7+WcOvRIky7KZrMpW4CCNO6I0D/3UYAYdptEWU+dRNAmNYdAfrvNgII026LKPOpmwDCtO4I5OsfYYowzbdiPDqaTZ88ChZD9YIANUy9CBOD9IgANUz9CBY1TP2IkxolNUz9iBU1TP2IkxrlP+7/orzx+JPkxNWn+jPoHhwpNUz9CTo1TP2JVR01TGcPzsrsq7OVQ+pf0S/9y/oX9KtuySfDNCEcreqZnnHqyU6m5MangTCt/HVGh11OAGHa5QFmepUTQJhWjryjDhGmHWGr5SSEaS3Yc3eKMM2NrLYTEKa1oc/VMcI0F65aD0aY1oo/V+d1CNOxr47J+DfGc43TxsGjF43KyC+NJApTapjGsIyNT8rWHbtlzbmnyVmnv1n2PPBV2XTNFTI6MiR37Nwr73r7mXLe2afYiEupbSBMS8VL4z1IAGHag0FnyqUSQJiWitda4whTayhLbwhhWjpiKx0gTK1grKQRhGklmAt3gjAtjLCyBhCmlaEu3FEdwnTi2xMy+U+Thceet4Hhc4dl6PShRGFKhmkMS3TTJ/XUjnvul203bZAVy5eKSsn93IP75ZZN67VAdf2LGqauR4jx+USAGqY+RYux+kCAGqY+RIkx+kSAGqY+RYux+kCAGqY+RIkx+kSAGqY+RUuEGqbckr9gxUaF6dGvWyrbPr1HtnzsQ1qYqlv1owLV9eWOMHU9QozPJwIIU5+ixVh9IIAw9SFKjNEnAghTn6LFWH0ggDD1IUqM0ScCCFOfooUwpYZpwnqN3pJ/6doL9G34Jx2/UtT3D+x7WB759vfJMPXrdc5oIWCFAMLUCkYagUCDAMKUxQABuwQQpnZ50hoEEKasAQjYJYAwtcuz7NbIMH1aqGHaZpWpjNNrNt8pTz71rLzhuGNk5/YbZPWJq8pem4Xbp4ZpYYQ0AIEmAtQwZUFAwC4Bapja5VlWa9QwLYus/XapYWqfaRktUsO0DKrltEkN03K42m6VGqa2iZbXHjVMy2Nru+U6apjankM3t9c3Nzc3180TLHtuCNOyCdN+rxFAmPZaxJlv2QQQpmUTttM+wtQOxypaQZhWQbl4HwjT4gyragFhWhXpYv0gTIvxq/JshGmVtIv1hTAtxq/ss2sTptEapj5kkqYFAmFa9hKl/V4jgDDttYgz37IJIEzLJmynfYSpHY5VtIIwrYJy8T4QpsUZVtUCwrQq0sX6QZgW41fl2QjTKmkX6wthWoxf2WcjTC0QZtMnCxBpAgIhAWqYshQgYJcANUzt8qQ1CFDDlDUAAbsEqGFqlyetQYAapn6tgV6vYepytGoTpgqK2ujpXW8/U847+xSXGbUdG8K0LSIOgEBmAgjTzKg4EAKZCCBMM2HiIAhkJoAwzYyKAyGQiQDCNBMmDoJAZgII08yonDgQYepEGBIHUaswfea552XPA1+VTddcIaMjQ+5SajMyhKm3oWPgDhJAmDoYFIbkNQGEqdfhY/AOEkCYOhgUhuQ1AYSp1+Fj8A4SQJg6GJQWQ0KYuhuv2oSpqmF6zeY75cmnnk2kc8apJ8u9t10nK5YvdZeeiFDD1OnwMDgPCVDD1MOgMWSnCVDD1OnwNAZHDVM/4qRGSQ1TP2JFDVM/4qRGSQ1TP2JFDVM/4qRGSQ1Tf2JFDVO3Y1WbMHUbS/bRIUyzs+JICGQhgDDNQoljIJCdAMI0O6s6j0SY1kk/X98I03y86joaYVoX+fz9IkzzM6vjDIRpHdQ76xNh2hm3Os5CmNZBPXuftQlTlWG65dZdsunaK2T1iauaRvzYE0/L5x7cL7dsWu/8rfoI0+yLjSMhkIUAwjQLJY6BQHYCCNPsrOo8EmFaJ/18fSNM8/Gq62iEaV3k8/eLMM3PrI4zEKZ1UO+sT4RpZ9zqOAthWgf17H06KUxVbdMd99wv227a4Pwt+Qo1NUyzLziOhEA7AtQwbUeI5yGQjwA1TPPx4mgItCNADdN2hHgeAvkIUMM0Hy+OhkA7AtQwbUfIreepYepWPKKjcVKYPrDvYXnk29+vPMP0jp175aTjV8qlay9oipgaz83bd+vH3nfRmgXjQpi6u8AZmX8EEKb+xYwRu00AYep2fBidfwQQpv7FjBG7TQBh6nZ8GJ1/BBCmfsUMYepuvCoXpip7dOONt8uPX3gplcobjjtGdm6/YcGt+mVhjArRT964vkmYqvIAt+/c29iASklV9XX9xnWN4SBMy4oM7fYiAYRpL0adOZdJAGFaJl3a7kUCCNNejDpzLpMAwrRMurTdiwQQpn5FHWHqbrwqF6YGRasapnXhSsowjT8WF6jUMK0rWvTbrQSoYdqtkWVedRGghmld5PP1Sw3TfLzqPJoapnXSz943NUyzs6r7SGqY1h2BbP1TwzQbJxeOooapC1HINgZqmGbjVNdRtQnTuibcqt+4HB0bn5StO3bLmnNPa2SdqgzZT2zbJZ/askFnwCJMXYwkY/KZAMLU5+gxdhcJIExdjMrCMSFM/YiTGiXC1I9YIUz9iJMaJcLUj1ghTP2IkxolwtSfWCFM3Y4VwjQSnzRhevnFF8p5Z5+ij0wSpptvulkmp2fdjjSjg4AnBD5z951y1fqNMrJ4sScjdmuYc3Nz0tfX59agGE2tBP78vl2y9v2XyNGvP7bWcdB5awI/+Ldn5fFvPSqXXv7BrkLVje9JX/j8Z+W8898hP3fCSV0Vq26bzE8PvCB/u+9B+c9X/W63Ta3r5vOVLz4oJ570JnnLqW8tfW5zcyJcJnWG+cjhw/Kn9+2Sqz/68c4a4KzKCPzD/q/K0mXL5axzzqusTzrqjMAd2z8lW7du7exkziqdQK3CVN2Wf83mO+XJp55dMNEzTj25UTe0dAphB51kmKpTJ6ZmZHIKYVpVnOinuwksGR2Uw+NToi5o+cpPQGFDl+bn1s1nHDUyIGOTMzI7y4uqm+Ps6tzmpE/6pLvW3ujwgExOz8jMTHfNy9U1xLi6n8DI0CKZnp2T6QoSUOb6+qSPi8zuX1Q9PsPhoUX6um+qgtdUj6O2Mv2liwettEMj9gnUKkyTNlCyP8XsLXZSw1S1zqZP2RlzJATaEWDTp3aEeB4C+Qiw6VM+XhwNgXYE2PSpHSGeh0A+Amz6lI8XR0OgHQE2fWpHyK3n2fTJrXhER1ObMPVl06f4Jk9Jkhdh6u4CZ2T+EUCY+hczRuw2AYSp2/FhdP4RQJj6FzNG7DYBhKnb8WF0/hFAmPoVM4Spu/FCmIrIA/selpu3725E6Q3HHSM7t9+gN3VSX9Hn33fRGrll03oZHRnSz7Hpk7uLm5H5SYBNn/yMG6N2lwCbPrkbm+jI2PTJjzipUbLpkx+xYtMnP+KkRsmmT37Eik2f/IiTGiWbPvkTKzZ9cjtWtQlThSXpFni3cS0cHcLUt4gxXtcJIExdjxDj840AwtSPiCFM/YgTwtSfOCFM/YkVwtSPWCFM/YgTwtSfOKmRIkzdjletwlTtOL/nga/KpmuuaGRsuo0LYepbfBivfwQQpv7FjBG7TQBh6nZ8zOgQpn7ECWHqT5wQpv7ECmHqR6wQpn7ECWHqT5wQpu7HqjZhqmqYXrP5TnnyqWcTKZ1x6sly723XyYrlS52nSA1T50PEAD0iQA1Tj4LFUL0gQA1TL8LEID0iQA1Tj4LFUL0gQA1TL8LEID0iQA1Tj4IlItQwdTdetQlTd5HkHxnCND8zzoBAGgGEKWsDAnYJIEzt8qQ1CCBMWQMQsEsAYWqXJ61BAGHq1xpAmLobL4SphdggTC1ApAkIhAQQpiwFCNglgDC1y5PWIIAwZQ1AwC4BhKldnrQGAYSpX2sAYepuvGoVpmPjk7J1x2556GuPiNmZftVxr9ePrTn3NLl07QXukgtHxqZPzoeIAXpGgBqmngWM4TpPgBqmzodID5Aapn7ESY3yKw99Xs562/ly7KoT/Bl0D46UGqb+BJ0apn7EihqmfsRJjfLxR/fLkiXL5C2nn+PPoHt0pGz65HbgaxWmd+zcKycdv1Le+6trZMe998uHLv01WX3iKnnsiaflcw/ul1s2rXd+MyiEqdsLnNH5RwBh6l/MGLHbBBCmbsfHjA5h6kecEKb+xAlh6k+sEKZ+xAph6kecEKb+xEmNFGHqdrxqE6Zq06ctt+6STddeISqrNCpMn3nuedlxz/2y7aYNzm/6hDB1e4EzOv8IIEz9ixkjdpsAwtTt+CBM/YhPdJRkmPoRM4SpH3FSo0SY+hErhKkfcUKY+hMnhKn7sXJSmPqUYapCTA1T9xc6I/SHADVM/YkVI/WDADVM/YgTo/SHADVM/YkVI/WDADVM/YgTo/SHADVM/YmVGik1TN2NV23CVCF5YN/D8si3vy9bPvYh+S+7v6BvyT/6dUvlms13yrqLL/SihinC1N3Fzcj8JIAw9TNujNpdAghTd2PDyPwkgDD1M26M2l0CCFN3Y8PI/CSAMPUrbghTd+NVqzBVWFQ26VUfv62J0H13bZbzzj7FXWqxkZFh6k2oGKgHBBCmHgSJIXpFAGHqVbgYrAcEEKYeBIkhekUAYepVuBisBwQQph4EKTJEhKm78apdmLqLJtvIqGGajRNHQSArAWqYZiXFcRDIRoAaptk41X0Umz7VHYHs/VPDNDurOo+khmmd9PP1TQ3TfLzqOpoapnWRz9/v44/ulyVLlslbTj8n/8mcUSkBNn2qFHfuzmoVpnfs3Cs/OfCy3LJpvYyODOnBj41PytYdu2XNuad5cUs+wjT3muMECLQkgDBlgUDALgGEqV2eZbWGMC2LrP12Eab2mZbRIsK0DKrltIkwLYer7VYRpraJltcewrQ8trZbRpjaJmq3vdqEqRGjl1984YLb733a9AlhandB0hoEEKasAQjYJYAwtcuzrNYQpmWRtd8uwtQ+0zJaRJiWQbWcNhGm5XC13SrC1DbR8tpDmJbH1nbLCFPbRO22V5swPfjKIdly6y7ZdO0VsvrEVU2zeua552XHPffLtps2yIrlS+3OuITWqGFaAlSa7FkC1DDt2dAz8ZIIUMO0JLA027MEqGHas6Fn4iURoIZpSWBptmcJUMPUr9BTw9TdeNUmTLslw1SFFmHq7gJnZP4RQJj6FzNG7DYBhKnb8WF0/hFAmPoXM0bsNgGEqdvxYXT+EUCY+hUzhKm78apNmCok6tb7Ldt2yc7tNzSyTFV26cYbb5drP3KJFzVMEabuLm5G5icBhKmfcWPU7hJAmLobG0bmJwGEqZ9xY9TuEkCYuhsbRuYnAYSpX3FDmLobr1qFqcJiBOmPX3ipQem+uzYvqGvqKkJqmLoaGcblKwFqmPoaOcbtKgFqmLoameZxUcPUjzipUVLD1I9YUcPUjzipUVLD1I9YUcPUjzipUVLD1J9YUcPU7VjVLkzdxtN+dAjT9ow4AgJ5CCBM89DiWAi0J4Awbc/IhSMQpi5EIdsYEKbZONV9FMK07ghk7x9hmp1VnUciTOukn69vhGk+XnUejTCtk377vhGm7Rm1PAJhWhAgp0MgRgBhypKAgF0CCFO7PMtqDWFaFln77SJM7TMto0WEaRlUy2kTYVoOV9utIkxtEy2vPYRpeWxtt4wwtU3Ubnu1CtODrxySazbfKU8+9eyCWZ1x6sly723XyYrlS+3OuITW2PSpBKg02bMEqGHas6Fn4iURoIZpSWBptmcJUMO0Z0PPxEsiQA3TksDSbM8SoIapX6Gnhqm78apVmN6xc68mc/3Gde4SyjAyhGkGSBwCgYwEEKYZQXEYBDISQJhmBMVhEMhIAGGaERSHQSAjAYRpRlAcBoGMBBCmGUE5chjC1JFAJAyjNmGqsku33LpLNl17haw+cZW7hDKMDGGaARKHQCAjAYRpRlAcBoGMBBCmGUFxGAQyEkCYZgTFYRDISABhmhEUh0EgIwGEaUZQjhyGMHUkEAhT+4Gghql9prTY2wSoYdrb8Wf29glQw9Q+0zJapIZpGVTLaZMapuVwtd0qNUxtEy2vPWqYlsfWZsvUMLVJs9y2qGFaLl+brVPD1CZN+23VlmGqpqJuyT/p+JVy6doL7M+sohYRphWBppueIYAw7ZlQM9GKCCBMKwJdsBuEaUGAFZ6OMK0QdoGuEKYF4FV8KsK0YuAddocw7RBcDachTGuA3mGXCNMOwVV0Wq3C9Jnnnpc9D3xVNl1zhYyODFU0ZbvdIEzt8qQ1CCBMWQMQsEsAYWqXZ1mtIUzLImu/XYSpfaZltIgwLYNqOW0iTMvhartVhKltouW1hzAtj63tlhGmtonaba82YapqmF6z+U558qlnE2d0xqkny723XScrli+1O+MSWqOGaQlQabJnCVDDtGdDz8RLIkAN05LA0mzPEqCGac+GnomXRIAapiWBpdmeJUANU79CTw1Td+NVmzB1F0n+kSFM8zPjDAikEUCYsjYgYJcAwtQuT1qDAMKUNQABuwQQpnZ50hoEEKZ+rQGEqbvxQphaiA3C1AJEmoBASABhylKAgF0CCFO7PGkNAghT1gAE7BJAmNrlSWsQQJj6tQYQpu7Gq3Zh+tgTT8tVH7+tidB9d22W884+xV1qkZFRw9SLMDFIjwhQw9SjYDFULwhQw9SLMAk1TP2IkxolNUz9iBU1TP2IkxolNUz9iBU1TP2IkxolNUz9iRU1TN2OVa3CVMnS23fubapVqjaC2njj7XLtRy6RS9de4DY9EUGYOh8iBugZAYSpZwFjuM4TQJg6HyI9QISpH3FCmPoTJ4SpP7FCmPoRK4SpH3FCmPoTJzVShKnb8apNmI6NT8rWHbvl8osvXJBNqkTq5x7cL7dsWi+jI0NOE0SYOh0eBuchAYSph0FjyE4TQJg6HZ7G4BCmfsQJYepPnBCm/sQKYepHrBCmfsQJYepPnBCm7seqNmF68JVDsuXWXbLp2itk9YmrmkipLNMd99wv227aICuWL62Vosl4/fELLzXGccapJzdlxVLDtNYQ0XmXEaCGaZcFlOnUToAaprWHgAF0GQFqmHZZQJlO7QSoYVp7CBhAlxGghqlfAaWGqbvxqk2Y+pJhqoTpJ7btkk9t2bBA7JqwIkzdXeCMzD8CCFP/YsaI3SaAMHU7PozOPwIIU/9ixojdJoAwdTs+jM4/AghTv2KGMHU3XrUJU4XkgX0Py94H9ztdwxRh6u7iZWTdSQBh2p1xZVb1EUCY1seenruTAMK0O+PKrOojgDCtjz09dycBhKlfcUWYuhuvWoWpwqLqlV718duaCN131+YFdU3rQhi/JT9+Oz41TOuKDP12KwFqmHZrZJlXXQSoYVoX+Xz9UsM0H686j/7KQ5+Xs952vhy76oQ6h0HfbQhQw9SfJUINUz9iRQ1TP+KkRvn4o/tlyZJl8pbTz/Fn0D06UjZ9cjvwtQtTt/EsHN0dO/fKTw683NiQSgnTrVu3+jYNxgsBZwns2LFDPvrRj8rixYudHaPLA5uanpXBgX6Xh8jYKiZw7733ygc+8AE59thjK+6Z7vIQeOaZZ+Qb3/iGfPjDH85zmvPHTk7PylCXvSf92Z/9mbzzne+Uk08+2Xn+vTzAF154Qb7whS/I1Vdf3csYvJi7itPq1avlzDPPLH28U9NzMjjQV3o/3djB4cOHRV1T/P7v/343Tq+r5vSlL31Jli9fLmvWrOmqeXXjZPBJbke1VmEal48Klaltuubc0+TStRc4Ry++IRUZps6FiAF5ToAMU88DyPCdI0CGqXMhSRwQGaZ+xEmNkgxTP2JFhqkfcVKjJMPUj1iRYepHnNQoyTAtP1Zj00dkamZKJmYnZHJ6QqZmJ2VyZlIm1f/TEzKpHp+ZksmZCZmamQyOm5lsfK8eUz+PfGOOBLzyw9VxD7UJU182fYqTjQtT9TybPnW8/jgRAgsIUMOURQEBuwSoYWqXJ61BgBqmrAEI2CVADVO7PGkNAt1Sw1RJx4npyVBGKuEYSsjZUELqn4PnJ6LSMnxcna+l5oxqZzxoZzqUmlp0ht/r49PbDgRoKERnJmRmbsbaIvv98/8P2fHeT1prj4bsEqhNmB585ZBsuXWXbLr2igW7zydJSbvTzt7al/Z/U978pp9rjFFlxaqv6zeuazSCMM3OkyMh0I4AwrQdIZ6HQD4CCNN8vDgaAu0IIEzbEeJ5COQjgDDNx4ujIdCOQF5h+trUa82ZkFFJ2ZCMgZwMMiaTMysnpsYXZFZq6RlmVkazLrWgTGn7yPThdlN04vmlQ0tlqH9YBhcNydCiYRlaNKh/AkZwbQAAIABJREFUHhoYlqF+9diQDPYPybD+WR03GB43FB43JBee8G657Mz/6MR8GMRCArUJU18yTOObUr3vojWN+qUGJ8KUlxYE7BFAmNpjSUsQUAQQpqwDCNglgDC1y5PWIIAwZQ30IgF1S7cSkBMz4zI+M64zJNX3KptRZ0Sqx6fH9f/qZyUY9ffh8/r86eB8lT2pjlHtqONmZFLGpyaC803mZSRDUvV7eOo1L7AfNbhEi8dASCrR2F5CBrJyOJSVQzKyaFQGGrJyodTUxy4akuGI1Ix+H/SrROiQLB44yjq3VceMWm+TBu0QqE2YquErGbll2y7Zuf2GRgan2ZX+2o9c4mQN0zh2apjaWYi0AgFDgBqmrAUI2CVADVO7PMtqjRqmZZG13y41TO0zLaNFapiWQbWcNqlhWg5X2612Uw3T4FbvUDCGotLcth0IylBERkSmEZVaZE6NNaSmkZtGeAbSczKUoIHI1I8ZCRrWtLQdn2h775H3yM/kZ/KIPNK2m4H+QRnWwjAQiSobUmVFmgzJqKhUmZP6OSUXQ8moRWIoI4cHRhqSMjhuuKntqPg0mZdN7YVtaym6aKjt2LvhgF13b6eGqcOBrFWYKi5GkP74hZcamO67a7Ocd/YpDmObHxrC1IswMUiPCCBMPQoWQ/WCAMLUizAJwtSPOKlRIkz9iBXC1I84qVEiTP2IlU1hemjyUCMzMrhlO6gx2ZRpqR+LZloGG+lMTU+KumVbZ1ROhyKyIT3Vz1MyPjPWyLqcz8AcF9WvS19Lh5bJyKIRUaLRyEX1/fCiERkJb+NW3yuJqR9bNNLIchwcCKRl8PyIzo40x439y0sydNSIHLf6pJa3i6tz+aqXAMK0Xv7teq9dmLYboOvPI0xdjxDj840AwtS3iDFe1wkgTF2PUDA+hKkfcUKY+hMnhKk/sUKYVhsrdSt3NBtyPCIbG49reWluAQ9uC58cn5DBJ2blxTNflfg5Onsydo4RoY3bysN+qp1tem9LBpfMy0YlHZV8DMVk438lKBepW7pDKbloRI4aPEoWLRoIzx0OnguP0/IylJ1GZEZFqDpWSdKyvx5/dL8sWbJM3nL6OWV3RfsFCSBMCwIs+XSEqQXA1DC1AJEmIBASoIYpSwECdglQw9QuT1qDADVMWQMQsEug12qYdiosdUalvhU8qEupszGjt4xHbyUPa1pGsyuVAJ2ambQbvA5aU7eAj+h6lEpQBoJRCUqdPRnJkgyeC27pbhy3aFhGBkeDc/Rt4fPna2mp24lkXUaFZyRTs4Nhe3VK3k2fvJpcFw6WGqbuBhVhaiE2CFMLEGkCAghT1gAESiGAMC0FK432MAGEaQ8Hn6mXQqBqYap2BI+KxPnalfO3gEdFZJAhGWRbTs9MyeEpdTt4sNFOIC2D7Mqmc+Iic3pC30buwlf0Fu+GkIxkUGrhGBGZUSk5Ori4cev3vPAMsyzDc4L6ls2ZlsGxw6VsmOMCU9fGgDB1LSKtx4MwdTdeCFMLsUGYWoBIExBAmLIGIFAKAYRpKVhptIcJIEx7OPhMvTCB6VlVX7L5Vu/hoVl5deKwvDLWfKt4o35lKB/Vbd9Nm+3kFJZKaM7MzRSeQ5EG+vv6GxmVC27fjmRANmpSxrMwB4LsSlXfMp5dGb8VvKm+pa5/GewEzlf3E0CY+hVjhKm78UKYFowNNUwLAuR0CMQIUMOUJQEBuwSoYWqXZ1mtUcO0LLL222XTJ/tMy2iRGqbJVNUt2XFhGc2QTKxnqXYFb2y+ozbTiQrPcKfxhgQNn4ucE828nJ2bXTCwS+VS+Vf5V/mufLeMpdDU5qK+RQuEpbkdvCnzMrwdPFq7UgnI+dvBk+tdNtpq3E4+X/tSCUt1O7qvXzY3ffKVgS/jpoapL5ESoYap27FCmBaMD8K0IEBOhwDClDUAgVIJIExLxWutcYSpNZSlN4QwLR2xlQ5cFaZpt23rTXOUZEy4vTtas3J8OiIsI7d9R28bb9weHu4irjfsmZ7U7c/JnBW+nTZi6leaepPq/1+ZuEB+OvSSHDjqxflNd6I7g0fkYyAs52tUBhvuJNxCnlgLc0QG+gc6HXrPn4cw9WcJIEz9iRXC1O1YIUwLxgdhWhAgp0MAYcoagECpBBCmpeK11jjC1BrK0htCmJaO2EoHacJ0fGZeOOr6k7FsybTalEo4KlnZdE7s/LTMTXOO2jW87i91S3Z8U5yocDS3ekc33wmyLANJGReW+rGUmpfx28ZHBxYnTv8f939R3nj8SXLi6lPrxkP/LQggTP1ZHghTf2KFMHU7VghTC/GhhqkFiDQBgZDAyqNH5cDBMZmtNwGCeECgawhQw7RrQslEHCFADdNigShjh3AlInV2Zor8NJmbLuwQbkTk/K3ezTt6t9pwR50zMjAqQwPhpjopt43Hdx6f34V8tFjwSjq76k2fSpoGzULAGQLUMHUmFJkGQg3TTJhqOQhhagE7wtQCRJqAAMKUNQCBUgggTEvBSqM9TMBnYTo9Ox3s5B2/7TsUjkm1KZtu754aa5wf3AIeydCM3h4e+X7S1L6cmRC14U+dX33Sp7MkjXAcSagzqetUpuwQrmRlNNsyXvPSZG7qHcHDrMzglvH5DM065+9q3whTVyPDuHwlgDD1K3IIU3fjhTC1EBuEqQWINAEBhClrAAKlEECYloKVRnuYQBFhmrRDuJGX6bd6q+zJMINSC8v5DXf0OQk1L9Pa8mWHcCUck2pTKmHJDuHd9+JDmHZfTJlRvQQQpvXyz9s7wjQvseqOR5gWZE0N04IAOR0CMQJ7dt8tl125XoZHkutcAQwCEMhHgBqm+XjVdTQ1TKshb2OH8OX/MiIvH/MzeXn4lUBWquzMhGzLpN3Gk3YIr2bmQS82dgjX2ZMDRmjOZ042ZVQ6sEO4q5s+VRlvX/qihqkfkaKGqR9xUqOkhqk/saKGqduxQpgWjA/CtCBATocAwpQ1AIFSCSBMS8VrrfFeEaZJO4Tr+pOhcLS9Q/j8LeZBVqaNHcJ/S35L/kH+QZ6VZ3PHX+0QHuzw3byrd/y27egt3NHbxtvtED60KKht2XTbeERe9tIO4QjT3MuzthMQprWhz9UxwjQXrloPRpjWij9X5wjTXLgqPxhhWhA5wrQgQE6HAMKUNQCBUgkgTEvFa63xqoRp3h3CTf1JJR57YYfw4VA4NgnL2A7hR/1zvwycMCpDxywJ5WSz/NTn6s15wjqW4flpO4RbW0Q01EQAYerPgkCY+hErhKkfcVKjRJj6EyuEqduxQphaiA81TC1ApAkIhARWHj0qBw6OyewcSCAAARsEqGFqg6K9NoKdvIPNclSdyfEp8/2YTM9My5Hpw2G25YR+vtWGO5O6dmVYz3JmXCZnpiTYgTysaxk5/7Wp1+xNomBLS4eWhpvghJvhhNmWI4tGZdjs/h2RlE3yMeVWb7UruBKSg4tUBme5wrJIDdOC6DgdAl1JgBqmXRlWJlUjAWqY1gi/g66pYdoBtIpOQZhaAI0wtQCRJiCAMGUNQKAUAgjThVhVHUmTaamyJo28VKIxLjGNkNTHTU8EQjIUncGGOxEBGh4TtDcmqoalad+0Y+OW8E4Xitoh3NSfDCSkEotmN+95ednpDuHD/e1vNe907C6dhzB1KRqMpRsIIEy7IYrMwSUCCFOXotF+LAjT9ozqOgJhaoE8wtQCRJqAAMKUNQCBUgi4LkxfnVAb54zL2EwgJAMBOSaTM5NN2ZL6dvBQaAbCMvjZyMnGuWoX8dn5c80xRoYediDT0mRYBjt+D4v+fyCoO6l3B9ciM2EznYHR5tqU0WP0+Qvlp2l36dCyUtZXLzaKMO3FqDPnMgkgTMukS9u9SABh6lfUEabuxgthWjA21DAtCJDTIRAjsGf33XLZletleGQxbCAAAQsE2tUwVdmW0SzJaPZkU73LMHtSP6Zv9Z6QsakjQUam2SE8dou5kZhjCeeqNuraMby/rz+sMWlu3VbCMtj1O7gtPJSYoZDUj6nnBlVWZiAtjdQMZGcgKqPnRo8x56r/VZZn0ldVNUwtLKmeb+IrD31eznrb+XLsqhN6noXLAKhh6nJ0msdGDVM/YkUNUz/ipEZJDVN/YkUNU7djhTAtGB+EaUGAnA4BhClrAAILCKg6lkoyqixK/f+M+v+Irnep/9c/B8+b75W8HGv8fERLTPXYL/74LPnmsm/JT+XFoCZmWNdSZWy6UNdyyWC4cc5gKCW1pAzEZJB9GYpI9X14zGiYkdm4rTzMzgx2Bp8/N8iunBeg6nlXMy0Rpv68ESBM/YgVwtSPOKlRIkz9iBXC1I84IUz9iZMaKcLU7XghTAvGB2FaECCnQwBhyhrwgICqO6lE5bykDMXl9FiipIxKTC0uleRUx+rbyiP/hxmajeenxmRydsIqkWvlWvm8fF4OyIHEdlXGYzQDsiEYdRalybwMZGY08zIQmWHG5WCYqRnKyUBkzp+rjwuPma+dOSIq05OvgADC1J+VgDD1I1YIUz/ihDD1J04IU39iRYapP7FCmLodK4SphfhQw9QCRJqAQEhg5dGjcuDgmMzOgQQC7QmoDMlAQAYZldHv0yTlkanDzceq+plTaiOfCdHPqexNXR8zaPfQ5KvtB2L5CCUtlWBUu36r71VGpcquVOJRPzYwKqP6Z/XcYlk8uDj1+VUrVsjERJ8M9s/XxRwNbzFfNrzc8shpDgLdT4Aapt0fY2ZYLQFqmFbLm966nwA1TP2KMTVM3Y0XwtRCbBCmFiDSBAQQpl2xBlRNykYmZiSTMi4h1a3huv5lmH2pz4lIymCn8ta3o0/NTFbGTGVhakmpxGXT/0peBtmUgciMCE0tNRdHzokdq+SnEp3mHCU/w1vObU7M9U2fbM6VtiBQBQGEaRWU6aOXCCBMeynazLUKAgjTKijb6wNhao+l7ZYQphaIIkwtQKQJCCBMS1sDM3MzkVvB5yWlzqAMa14m3S5uMjHjmZqNW8xjmZhKclYpMdXt3DoTUwlHJR4Tsi/jmZjq2MWDRy0Qm1HhmSRE1W3kvn4hTH2NHON2lQDC1NXIMC5fCSBMfY0c43aVAMLU1cgkjwth6m68EKYFY0MN04IAOR0CMQJ7dt8tl125XoZHFnc1GyMxo7Urkzb2MRv36IxMnYWpNv4Zk7EZdcu4qqmpMjGPyJjeqXz+1vSo5JyenaqMpZGY5hZy/X9423jyLeZB1qbOxIzcYj4vQdNvRx/qH65sXj539Nd775ML3/1+Wb7i9T5Po+vHTg1Tf0JMDVM/YkUNUz/ipEbJpk9+xIoapn7ESY2SGqb+xIoapm7HCmFaMD4I04IAOR0CDgnT6dnptjuSmx3Lm24XV3UvE3Yvn9/dPNztPCI5q5SYi/oW6VvGdQZmwi3gjezKyPNKcupMzIQ6mnEJGhWiSEz3XtIIU/dikjQihKkfcVKjRJj6ESuEqR9xQpj6EyeEqT+xQpj6EyuEqduxQpgWjA/CtCBATodAG2GqxKLOolTZlEo4mrqW+ucwu7LpeVUbM9y4R+1I3qYOpnre7GiuhGlVX0pimnqYSbeANzb2SaiZqTMxTc3MFhLUbBY0uGioqmnRj4MEEKYOBiVhSAhTP+KEMPUnTghTf2JFhqkfsUKY+hEnNUqEqT+xQpi6HSuEqYX4UMPUAkSa8IqAqlOpN+VJuQW8uR5mWDNT3TaudjKPbfYT3wxoam5CXptQu5grkTkuVUrMgf6B+TqYLXYkj9fMbMrabLExUFSCDvQPehVzBusvAWqY+hs7Ru4mAWqYuhkXRuUvAWqY+hs7Ru4mAWqYuhmXtFFRw9TdeCFMLcQGYWoBIk0UJqAkZuN28chmPkEty3BH8rAOptnsJ9jNPHg+UXLq58KdyiP/q/qbVX0pidnqFnAtIXWNzFEZGQz/17uNx28nH5ERVSdzkdrRPNy5XB2vNw1SP48IErOqqNJPlQQQplXSpq9eIIAw7YUoM8cqCSBMq6RNX71AAGHqV5QRpu7GC2FqITYIUwsQu7SJydmJxNqW5hbwpNvF9c7kavfx8HZys9lPdEfzuARVz1UrMQe1YNSiUQnHqKiMi0slNFUdTCUwE8Rm87mL5fjXv06OHOmXof5AfiphyhcEINA5AYRp5+w4EwJJBBCmrAsI2CWAMLXLk9YggDD1aw0gTN2NF8K0YGyoYVoQYA2nK4k5pupWmtvJI7eIB7eHhxmZ+vZx9XPw2PwGPmqX8vFQagbfB7eaz0tOc+zs3GxlM1TZkaYmZnDr94gsrIMZk5wq41JnaC7cDKhps59IzUzVh6q/WdbXnt13y2VXrpfhkcVldUG7EOgpAtQw9SPc1DD1I05qlGz65EesqGHqR5zUKKlh6kesqGHqR5zUKKlh6k+sqGHqdqwQphni88C+h+Xm7bv1ke+7aI3csmm9jI4Em6ggTDMAzHDIhK6HGYrHhFvAk24X15mY5pxQbAZ1LwPJmSZEq5SYarMdLSO1wFS3iaudylXmZCg01Y7l+hbx+cf0zuQt6mBGj40K0TIlZoYQWjsEYWoNJQ1BQBNAmPqxEBCmfsQJYepPnBCm/sQKYepHrBCmfsQJYepPnNRIEaZuxwth2iY+jz3xtNy+c6/ce9t1smL5Urlj5159xvUb13W9MFUSU4tHnTmZXAczLjkbmZgtNgNKqok5J3OVvVKUxIzXxEyrg2kkp3o+LjnjEjQuOdXz/X39lc2rWzpCmHZLJJmHKwQQpq5EovU4EKZ+xAlh6k+cEKb+xAph6kesEKZ+xAlh6k+cEKbuxwph2iZGSpCedPxKuXTtBfrIuEBVj1VZw1TJy1a3gGuxGblFXAnNI5OqJmYkezNFgkZ3PFffVykxh/qHgzqXCzbwSb9dXGdiJm32Y2pmxtoymZ5ITLffmFYePSoHDo7JbHUO3W0gjA4CBQlQw7QgQE6HQIwANUxZEhCwS4AapnZ50hoEqGHq1xqghqm78UKYtojN2PikbN2xW9ace1pDmD7z3PPyiW275FNbNsjqE1dpqfjTVw/JTw8dSrwFvFHbMn6L+OTCmphpdTDNZj8q47NKiTmsbxWP3C7eqHMZ7kTedNt4cIt5cDv5SCAy1e3mpo6m/lntRh7eeh6rmdknfe6+ShhZpQQQppXiprMeIIAw7YEgM8VKCSBMK8VNZz1AAGHaA0FmipUSQJhWirtwZwjTwghLawBhmkGYXn7xhXLe2afoI+PC9G/u+xt554/eWVqAaBgCEIAABCAAAQhAAAIQgAAEIAABCECguwiMXDAio7882l2T6qLZIEwzCNNWGaZq06eP9X+si5YEU4FAvQR2ze6SD/d9WEb7+MVRbyTovVsI7JndI+/pe48c03dMt0ypK+fx3Nxz8t/n/rv8Rv9vdOX8umlSfzX3V3KOnCMn9J3QTdPqurm8KC/Kl2e/LFf2X9l1c+u2CX157stygpwgp/QFCSp8uUngiByR/zb73+R3+3/XzQEyqgaBr899XZbIEnlb39ug4jiBT89+WrZu3er4KHt3eAjTNrFvV8NUCdPrN90kh8ame3cVMXMIWCTApk8WYdIUBESETZ/8WAZs+uRHnNQov/LQ5+Wst50vx65CmLocNTZ9cjk6zWNj0yc/YsWmT37ESY3y8Uf3y5Ily+Qtp5/jz6B7dKS77t6OMHU49gjTNsGJb/KkBKr6un7jOv0/wtTh1c3QvCSAMPUybAzaYQIIU4eDExkawtSPOCFM/YkTwtSfWCFM/YgVwtSPOCFM/YmTGinC1O14IUwzxOeBfQ/Lzdt36yPfd9EauWXTehkdGWqceejIFBmmGThyCASyEGDTpyyUOAYC2Qmw6VN2VhwJgSwE2PQpCyWOgUB2Amz6lJ0VR0IgCwE2fcpCyZ1j2PTJnVjER4IwtRAbhKkFiDQBgZAAwpSlAAG7BBCmdnnSGgQQpqwBCNglgDC1y5PWIIAw9WsNIEzdjRfC1EJsEKYWINIEBBCmrAEIlEIAYVoKVhrtYQII0x4OPlMvhQDCtBSsNNrDBBCmfgUfYepuvBCmBWNDDdOCADkdAjEC1DBlSUDALgFqmNrlWVZr1DAti6z9dtn0yT7TMlqkhmkZVMtpkxqm5XC13So1TG0TLa89Nn0qj63tlqlhapuo3fYQpgV5IkwLAuR0CCBMWQMQKJUAwrRUvNYaR5haQ1l6QwjT0hFb6QBhagVjJY0gTCvBXLgThGlhhJU1gDCtDHXhjhCmhRGW2gDCtCBeLUxv/ISo2/L5ggAEihMgw7Q4Q1qAQJQAwtSP9YAw9SNOapQIUz9ihTD1I05qlAhTP2KFMPUjTmqUCFN/YoUwdTtWCFO348PoIAABCEAAAhCAAAQgAAEIQAAC/397dxcrR1XAAfw8EVCaSjGlNKkQiBFIqigBGz+wSojaiiY1XCG8YEmt8ERp2vRCCCEEb9OmwBO1aajwBJZINE2vTzWVxORGQkQbaR9KgaBQSAAJKB9P5kycdXe6d3Z37s6dj/3dJ+3OnI/fOcPM/nfODAECBAgQWEQBgekiYquKAAECBAgQIECAAAECBAgQIECAAIF6CwhM6z0+WkeAAAECBAgQIECAAAECBAgQIECAwCIKCEwXEVtVBAgQIECAAAECBAgQIECAAAECBAjUW0BgWnB83n3v/XD7jofDseOnkhIef2RHuPrKywqWZjcC7RX48KNPwn27D4TDR+aSTj6wfWPYsO7aeTuct332uIuFXHjB+WHfrq3h0otWthdRzwjkCBQ9Hz2072C4eNWK3OMRPIFJEXhm9tlw764DSXfXX7cm3L9tYzjn7LNyu//Sq6+H3Y8+FWbu3hTOW7qks208th57crZn30Hnvklx1s/JFBj1WjB7DDl+JnPe6HWvwCjnqedeOBFuvXNnp4Dsea27rHSj225eF+7aPIWdAIEuAYFpgemQnvTXXHVF8kUzXjDfM7M/PDi9SWhTwNMu7RaIF73xL56A02Bn6+apeX9gyNt+mP3bral3BHoFipyPui+SfQk1owiEEL9Y7tl3MOzduSUJPrvPQ/18un+kWH35JZ390m0H7c+cwKQJjHItGM9re5/4bfjpTd9Pjsf4PWvz9j1hZnqTm1MmbeLob0dg1PNUvNZbtXJ5csyk14orli/rBKLx87nnXxzqx0HDQGCSBQSmBUY/e0dB9gtrgSLtQqCVAvFL5fQv9odtd9zU+TEh74vkoO0Fpq2cJjq1AIGFnI/cYboAeLu2SiB7LGS/mM7X2bw7TNMfClsFpTMECggMurYbVKTvWYOEfD4JAkXPU6lNNiAVmE7CrNHHcQgITAso9ruQdjdBAUi7tF6g393XeSfoQdt/9PHHPY/CsBy/9VNIBwcILOR8JDA1vQiEzp036aqhaDLsyqFhl+S7k9tMm2SBQdd2gx594cfySZ49+h4F+v1oMOx5KhXMZhXZJfmW45trBPoLCEwLzIz4BfXpQ0d7bmEXmBaAtEvrBfp9mRwUmGafB5e3ffzs4KGjZyyHbD2sDhL4n8BCzkcCU9OIwP+/iN54w9rOct9hv4jOF5h2u1pObJZNusCo14JZL9+xJn0G6X8amBY5T0W9Qasm0h8lpm5Y67n2phuBjIDAtMCUWMgdPQWqswuBxgqMelfBqNv3W+bVWCwNJ1BAYCHnI4FpAXC7tE5gIXfuDBOYRjDHWuumjQ6NIDDqtV130fHYOf3WO56zOIK3TdsnsJDzVLxOnJ7ZP/AFufEmlFdeO+2lT+2bPnq0QAGBaQHAhTwzrkB1diHQWIFRn1s1ju0bi6XhBAoILOR8JMQpAG6XVgoUfTacwLSV00Gnxiww6rVdWr2wdMwDobhGCxQ5Tw0blkYYgWmjp4fGlyggMC2AW+StxAWqsQuBVggM89b77iUgedvHE3/8i298TE/u3vDYimmiEwUFBp2P8pZZCUwLotutdQKD3j48X3DTLzCNx9zskblwy4brE6dhl/e3DlWHCHQJ5F3bxc2yx5hl+KYPgV6BQeep7GPK8pbhx2vH3xz+Y/jx+m+F+Axhzwk22wjMLyAwLTg70v+wHDt+Kinh8Ud2dEKcgkXajUArBdJA5/CRuaR/3S+/6Bfm5G2fPgvujTffTspaffklnl/aylmjU6MI5J2P+h1j2Qf9e3naKNq2batA93Gx/ro1ZzynvntZcPaYiybpCzOy5zDXiG2dMfo1ikDetV02MM2+4DOtJ3tcjlK/bQm0QSDvPJUNTOOPDo89OdvT7e7rveznXk7YhhmiD2UICEzLUFUmAQIECBAgQIAAAQIECBAgQIAAAQKNFBCYNnLYNJoAAQIECBAgQIAAAQIECBAgQIAAgTIEBKZlqCqTAAECBAgQIECAAAECBAgQIECAAIFGCghMGzlsGk2AAAECBAgQIECAAAECBAgQIECAQBkCAtMyVJVJgAABAgQIECBAgAABAgQIECBAgEAjBQSmjRw2jSZAgAABAgQIECBAgAABAgQIECBAoAwBgWkZqsokQIAAAQIECBAgQIAAAQIECBAgQKCRAgLTRg6bRhMgQIAAAQIECBAgQIAAAQIECBAgUIaAwLQMVWUSIECAAAECBAgQIECAAAECBAgQINBIAYFpI4dNowkQIECAAAECBAgQIECAAAECBAgQKENAYFqGqjIJECBAgAABAgQIECBAgAABAgQIEGikgMC0kcOm0QQIECBAgAABAgQIECBAgAABAgQIlCEgMC1DVZkECBAgQIAAAQIECBAgQIAAAQIECDRSQGDayGHTaAIECBAgQIAAAQIECBAgQIAAAQIEyhAQmJahqkwCBAgQIECAAAECBAgQIECAAAECBBopIDBt5LBpNAECBAgQIECAAAECBAgQIECAAAECZQgITMtQVSYBAgQIECBAgAABAgQIECBAgAABAo0UEJg2ctg0mgABAgQIECBAgAABAgQIECBAgACBMgQEpmWoKpMAAQIECBAgMEaBZ2aLTMKNAAAIpElEQVSfDffuOtBT4urLLwl7d24JJ1/+Z7j1zp3h8Ud2hKuvvKxnm4f2HQx/fuFEst15S5eEvHLe+df7YfP2PeGNN9+et+UPbN8YVq1cntTX7y9tw3MvnEi2WX/dmnD/to3hnLPP6mye91nc6N333g+373g4HDt+at523HbzunDxqhU9JrFtG9ZdG1569fWkH59dtrTT77Sgfp+l7cnrzxiHUlEECBAgQIAAAQINEBCYNmCQNJEAAQIECBCYXIFs6JlKxH//5le/mISkMQg9eOhoT0AYw8F7ZvaHB6c3hUsvWhmGKadbOZY59/yLfQPP6Zn9Yd+urUm5/f7SEPLCC87v2e7Djz4J9+0+EA4fmesbps5X1p59B88IP+O2sZ5sW9JQNAa/2RA5Gjz25GxIw+YYIvcrY3Jnm54TIECAAAECBAhEAYGpeUCAAAECBAgQqKlAerfl1A1rk7sn5/tLg8gVy5eFuzZPhfT/r7nqimS/YcsZZ2AaQ87vfP3L4YN/f5i0KQ04nz50NJx77qfCBx/854wwdlyBaQyKf3D918LfXnypU0cMUnc/+lT4yurPhz/86S+dAFZgWtPJr1kECBAgQIAAgQoFBKYV4quaAAECBAgQIJAnkA1C87ZN76ycmd4UXnv9rZ47TkcpJ61joXeYxsB06+apsOeXv+65yzUupX/ltdPh9FvvlBqYbv35T0LahvQu3FhvrL/7blyBqWOQAAECBAgQIEAgKyAwNScIECBAgAABAjUWyD5js3s5ebbZ6ZLz+O/Z5eijlBP3zwtMh3mGabqM/ldP/T5p5o++943kDs+ZuzeF+G9lB6bxUQR//fvJ5LECW352Y7j/oSfCtjtuSv4tG5gO6k+Np4emESBAgAABAgQIlCAgMC0BVZEECBAgQIAAgXELdD//M5adfT5o/Ld06f01V17WWQafbccw5QwKTId5hmkamMaXScUl8vFv6offTh4REIPdxQhMl31mSfICqaVLPh2+cOmqxCT7vFd3mI57piqPAAECBAgQINB8AYFp88dQDwgQIECAAIEJE5hviX322aWDWPKW6o9jSf7enVtCfLFS9oVTixWYxpdSxX48+sTvOi+fEpgOmhU+J0CAAAECBAgQEJiaAwQIECBAgACBmgrEO0aPHT8Vrl3zpTNaGEPH+Je+UCn+7/k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""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_curves(colors=['darkorange', 'green', 'violet'], show_intervals=True, title_prefix=\"WITH zero enzyme\")"
]
},
{
"cell_type": "markdown",
"id": "9a793ebf-f544-43ad-a1d3-059f74f3c02b",
"metadata": {},
"source": [
"### The reactions, lacking enzyme, are proceeding slowly towards equilibrium, like reaction that was discussed in part 1 of the experiment \"enzyme_1\""
]
},
{
"cell_type": "markdown",
"id": "27401e5d-8f3e-4c27-8438-129d3e3408a2",
"metadata": {},
"source": [
"# Now suddently add a lot of enzyme"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "713dae1e-1c51-4d95-8439-c79d9dcce2e3",
"metadata": {},
"outputs": [],
"source": [
"dynamics.set_single_conc(30., species_name=\"E\", snapshot=True) # Plenty of enzyme `E`"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "e80645d6-eb5b-4c78-8b46-ae126d2cb2cf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0.275:\n",
"3 species:\n",
" Species 0 (A). Conc: 15.232227244425584\n",
" Species 1 (B). Conc: 4.767772755574415\n",
" Species 2 (E). Conc: 30.0\n",
"Set of chemicals involved in reactions (not counting enzymes): {'B', 'A'}\n",
"Set of enzymes involved in reactions: {'E'}\n"
]
}
],
"source": [
"dynamics.describe_state()"
]
},
{
"cell_type": "markdown",
"id": "0b46b395-3f68-4dbd-b0c5-d67a0e623726",
"metadata": {
"tags": []
},
"source": [
"### Take the system to equilibrium"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "dde62826-d170-4b39-b027-c0d56fb21387",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"*** CAUTION: negative concentration in chemical `A` in step starting at t=0.275. It will be AUTOMATICALLY CORRECTED with a reduction in time step size, as follows:\n",
" INFO: the tentative time step (0.005) leads to a NEGATIVE concentration of `A` from reaction A + E <-> B + E (rxn # 1): \n",
" Baseline value: 15.232 ; delta conc: -21.418\n",
" -> will backtrack, and re-do step with a SMALLER delta time, multiplied by 0.25 (set to 0.00125) [Step started at t=0.275, and will rewind there]\n",
"* INFO: the tentative time step (0.00125) leads to a least one norm value > its ABORT threshold:\n",
" -> will backtrack, and re-do step with a SMALLER delta time, multiplied by 0.4 (set to 0.0005) [Step started at t=0.275, and will rewind there]\n",
"* INFO: the tentative time step (0.0005) leads to a least one norm value > its ABORT threshold:\n",
" -> will backtrack, and re-do step with a SMALLER delta time, multiplied by 0.4 (set to 0.0002) [Step started at t=0.275, and will rewind there]\n",
"Some steps were backtracked and re-done, to prevent negative concentrations or excessively large concentration changes\n",
"30 total step(s) taken\n"
]
}
],
"source": [
"dynamics.single_compartment_react(reaction_duration=0.04, \n",
" initial_step=0.005, variable_steps=True, explain_variable_steps=False)"
]
},
{
"cell_type": "markdown",
"id": "b4f7e3b5-e4b5-4dd8-a8c3-4e0c231ecdb9",
"metadata": {},
"source": [
"#### Note how the (proposed) initial step - in spite of having been reduced from the earlier run - is now appearing _large_, given the much-faster reaction dynamics. However, the variable-step engine intercepts and automatically corrects the problem!"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "b0543cac-f3cd-453c-ae9b-c00f01e61fa8",
"metadata": {},
"outputs": [],
"source": [
"#dynamics.explain_time_advance()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "8cc14786-cc9f-4399-9203-290526d3a326",
"metadata": {},
"outputs": [
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"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_curves(colors=['darkorange', 'green', 'violet'], show_intervals=True, title_prefix=\"WITH enzyme added mid-reaction\")"
]
},
{
"cell_type": "markdown",
"id": "3171fd78-a103-4523-8c43-6e29695f49d2",
"metadata": {},
"source": [
"## Notice the dramatic acceleration of the reaction as soon as the enzyme `E` is added at t = 0.275!\n",
"The reactions simulator automatically switches to small time steps is in order to handle the rapid amount of change"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "c3afbcc8-bdae-4938-a3f1-ce00d62816f2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0: A <-> B\n",
"Final concentrations: [B] = 16.67 ; [A] = 3.333\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 5.00003\n",
" Formula used: [B] / [A]\n",
"2. Ratio of forward/reverse reaction rates: 5.00000519021548\n",
"Discrepancy between the two values: 0.0005779 %\n",
"Reaction IS in equilibrium (within 1% tolerance)\n",
"\n",
"1: A + E <-> B + E\n",
"Final concentrations: [B] = 16.67 ; [E] = 30 ; [A] = 3.333 ; [E] = 30\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 5.00003\n",
" Formula used: ([B][E]) / ([A][E])\n",
"2. Ratio of forward/reverse reaction rates: 5.00000519021548\n",
"Discrepancy between the two values: 0.0005779 %\n",
"Reaction IS in equilibrium (within 1% tolerance)\n",
"\n"
]
},
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Verify that the reaction has reached equilibrium\n",
"dynamics.is_in_equilibrium()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "47c6d97b-a778-47c1-9cad-e75433a32f66",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" SYSTEM TIME | \n",
" A | \n",
" B | \n",
" E | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" 0.000000 | \n",
" 20.000000 | \n",
" 0.000000 | \n",
" 0.0 | \n",
" Initial state | \n",
"
\n",
" \n",
" | 1 | \n",
" 0.050000 | \n",
" 19.000000 | \n",
" 1.000000 | \n",
" 0.0 | \n",
" | \n",
"
\n",
" \n",
" | 2 | \n",
" 0.100000 | \n",
" 18.060000 | \n",
" 1.940000 | \n",
" 0.0 | \n",
" | \n",
"
\n",
" \n",
" | 3 | \n",
" 0.125000 | \n",
" 17.618200 | \n",
" 2.381800 | \n",
" 0.0 | \n",
" | \n",
"
\n",
" \n",
" | 4 | \n",
" 0.150000 | \n",
" 17.189654 | \n",
" 2.810346 | \n",
" 0.0 | \n",
" | \n",
"
\n",
" \n",
" | 5 | \n",
" 0.175000 | \n",
" 16.773964 | \n",
" 3.226036 | \n",
" 0.0 | \n",
" | \n",
"
\n",
" \n",
" | 6 | \n",
" 0.200000 | \n",
" 16.370745 | \n",
" 3.629255 | \n",
" 0.0 | \n",
" | \n",
"
\n",
" \n",
" | 7 | \n",
" 0.225000 | \n",
" 15.979623 | \n",
" 4.020377 | \n",
" 0.0 | \n",
" | \n",
"
\n",
" \n",
" | 8 | \n",
" 0.250000 | \n",
" 15.600234 | \n",
" 4.399766 | \n",
" 0.0 | \n",
" | \n",
"
\n",
" \n",
" | 9 | \n",
" 0.275000 | \n",
" 15.232227 | \n",
" 4.767773 | \n",
" 0.0 | \n",
" | \n",
"
\n",
" \n",
" | 10 | \n",
" 0.275000 | \n",
" 15.232227 | \n",
" 4.767773 | \n",
" 30.0 | \n",
" Set concentration of `E` | \n",
"
\n",
" \n",
" | 11 | \n",
" 0.275200 | \n",
" 14.372651 | \n",
" 5.627349 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 12 | \n",
" 0.275400 | \n",
" 13.575171 | \n",
" 6.424829 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 13 | \n",
" 0.275600 | \n",
" 12.835300 | \n",
" 7.164700 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 14 | \n",
" 0.275800 | \n",
" 12.148878 | \n",
" 7.851122 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 15 | \n",
" 0.276000 | \n",
" 11.512043 | \n",
" 8.487957 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 16 | \n",
" 0.276200 | \n",
" 10.921213 | \n",
" 9.078787 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 17 | \n",
" 0.276440 | \n",
" 10.263435 | \n",
" 9.736565 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 18 | \n",
" 0.276728 | \n",
" 9.542527 | \n",
" 10.457473 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 19 | \n",
" 0.277074 | \n",
" 8.767428 | \n",
" 11.232572 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 20 | \n",
" 0.277419 | \n",
" 8.089086 | \n",
" 11.910914 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 21 | \n",
" 0.277834 | \n",
" 7.376689 | \n",
" 12.623311 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 22 | \n",
" 0.278249 | \n",
" 6.771007 | \n",
" 13.228993 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 23 | \n",
" 0.278663 | \n",
" 6.256054 | \n",
" 13.743946 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 24 | \n",
" 0.279161 | \n",
" 5.730676 | \n",
" 14.269324 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 25 | \n",
" 0.279659 | \n",
" 5.299738 | \n",
" 14.700262 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 26 | \n",
" 0.280256 | \n",
" 4.875569 | \n",
" 15.124431 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 27 | \n",
" 0.280853 | \n",
" 4.542897 | \n",
" 15.457103 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 28 | \n",
" 0.281570 | \n",
" 4.229802 | \n",
" 15.770198 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 29 | \n",
" 0.282430 | \n",
" 3.951341 | \n",
" 16.048659 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 30 | \n",
" 0.283462 | \n",
" 3.720982 | \n",
" 16.279018 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 31 | \n",
" 0.284700 | \n",
" 3.547589 | \n",
" 16.452411 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 32 | \n",
" 0.286186 | \n",
" 3.432586 | \n",
" 16.567414 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 33 | \n",
" 0.287969 | \n",
" 3.368656 | \n",
" 16.631344 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 34 | \n",
" 0.290109 | \n",
" 3.341352 | \n",
" 16.658648 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 35 | \n",
" 0.292677 | \n",
" 3.333912 | \n",
" 16.666088 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 36 | \n",
" 0.295758 | \n",
" 3.333265 | \n",
" 16.666735 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 37 | \n",
" 0.299456 | \n",
" 3.333353 | \n",
" 16.666647 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 38 | \n",
" 0.303893 | \n",
" 3.333317 | \n",
" 16.666683 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 39 | \n",
" 0.309218 | \n",
" 3.333343 | \n",
" 16.666657 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
" | 40 | \n",
" 0.315608 | \n",
" 3.333314 | \n",
" 16.666686 | \n",
" 30.0 | \n",
" | \n",
"
\n",
" \n",
"
\n",
"