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"cell_type": "markdown",
"id": "ef6b822a-73a9-4057-97ea-b55c1661c2bc",
"metadata": {},
"source": [
"### Reaction A + B <-> C, mostly forward and with 1st-order kinetics for each species,\n",
"### taken to equilibrium\n",
"\n",
"Initial concentrations of A and B are spacially separated to the opposite ends of the system;\n",
"as a result, no C is being generated.\n",
"\n",
"But, as soon as A and B, from their respective distant originating points at the edges, \n",
"diffuse into the middle - and into each other - the reaction starts,\n",
"consuming both A and B (the forward reaction is much more substantial than the reverse one),\n",
"until an equilibrium is reached in both diffusion and reactions.\n",
"\n",
"A LOT of plots are sent to the log file from this experiment; the reason is to compare two\n",
"graphic elements, \"vue_curves_3\" and \"vue_curves_4\"\n",
"\n",
"LAST REVISED: June 23, 2024 (using v. 1.0 beta34.1)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "434f6178-c89b-49ac-879d-ec05f0590fa0",
"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": "8a51735f",
"metadata": {},
"outputs": [],
"source": [
"from experiments.get_notebook_info import get_notebook_basename\n",
"\n",
"from life123 import BioSim1D\n",
"\n",
"import plotly.express as px\n",
"from life123 import ChemData as chem\n",
"from life123 import HtmlLog as log\n",
"from life123 import GraphicLog"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "6eae381c-b048-4345-904b-939c551ce1ef",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-> Output will be LOGGED into the file 'rd_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_heatmap_11\", \"vue_curves_3\", \"vue_curves_4\", \"vue_cytoscape_2\"],\n",
" extra_js=\"https://cdnjs.cloudflare.com/ajax/libs/cytoscape/3.21.2/cytoscape.umd.js\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "8e1ce9d4-e35c-4840-ae65-9c4f9a8f4542",
"metadata": {},
"outputs": [],
"source": [
"# Initialize the system\n",
"chem_data = chem(names=[\"A\", \"B\", \"C\"], diffusion_rates=[50., 50., 1.])\n",
"\n",
"\n",
"\n",
"# Reaction A + B <-> C , with 1st-order kinetics for each species; note that it's mostly in the forward direction\n",
"chem_data.add_reaction(reactants=[\"A\", \"B\"], products=[\"C\"], forward_rate=20., reverse_rate=2.)\n",
"bio = BioSim1D(n_bins=7, chem_data=chem_data)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "d3dfb8b7-f54a-4e56-915b-e1d9b89d2365",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0:\n",
" A B C\n",
"0 0.0 0.0 0.0\n",
"1 0.0 0.0 0.0\n",
"2 0.0 0.0 0.0\n",
"3 0.0 0.0 0.0\n",
"4 0.0 0.0 0.0\n",
"5 0.0 0.0 0.0\n",
"6 0.0 0.0 0.0\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "dc49e75c-6aa5-414d-831f-805461f04f3a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of reactions: 1 (at temp. 25 C)\n",
"0: A + B <-> C (kF = 20 / kR = 2 / delta_G = -5,708 / K = 10) | 1st order in all reactants & products\n",
"Set of chemicals involved in the above reactions: {'B', 'C', 'A'}\n"
]
}
],
"source": [
"chem_data.describe_reactions()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "37eb3a95-3d46-479e-9c93-2e81a2d3202d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Reaction: A + B C\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"# Send a header and a plot to the HTML log file\n",
"log.write(\"Reaction: A + B <-> C\",\n",
" style=log.h2)\n",
"chem_data.plot_reaction_network(\"vue_cytoscape_2\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "433d4426-ca90-4d48-a7e6-b83a98904f5c",
"metadata": {},
"outputs": [],
"source": [
"# Set the heatmap parameters\n",
"heatmap_pars = {\"range\": [0, 20],\n",
" \"outer_width\": 850, \"outer_height\": 100,\n",
" \"margins\": {\"top\": 30, \"right\": 30, \"bottom\": 30, \"left\": 55}\n",
" }\n",
"\n",
"# Set the parameters of the line plots (for now, same for single-curve and multiple-curves)\n",
"lineplot_pars = {\"range\": [0, 20],\n",
" \"outer_width\": 850, \"outer_height\": 200,\n",
" \"margins\": {\"top\": 30, \"right\": 30, \"bottom\": 30, \"left\": 55}\n",
" }"
]
},
{
"cell_type": "markdown",
"id": "3fbf21cc-79ab-4915-ac51-8a963f16dc88",
"metadata": {},
"source": [
"# Inject initial concentrations of A and B at opposite ends of the system"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "f9e1cf26-1df8-4f38-af51-10f162043c7c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"7 bins and 3 species:\n",
" Species 0 (A). Diff rate: 50.0. Conc: [20. 0. 0. 0. 0. 0. 0.]\n",
" Species 1 (B). Diff rate: 50.0. Conc: [ 0. 0. 0. 0. 0. 0. 20.]\n",
" Species 2 (C). Diff rate: 1.0. Conc: [0. 0. 0. 0. 0. 0. 0.]\n"
]
}
],
"source": [
"bio.set_bin_conc(bin_address=0, species_name=\"A\", conc=20.)\n",
"bio.set_bin_conc(bin_address=6, species_name=\"B\", conc=20.)\n",
"\n",
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "4a7f7fe9-a0f2-4233-a815-09668d44dac2",
"metadata": {},
"outputs": [
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"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0:\n",
" A B C\n",
"0 20.0 0.0 0.0\n",
"1 0.0 0.0 0.0\n",
"2 0.0 0.0 0.0\n",
"3 0.0 0.0 0.0\n",
"4 0.0 0.0 0.0\n",
"5 0.0 0.0 0.0\n",
"6 0.0 20.0 0.0\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "33f4d6c1-5d4b-4128-90dc-cb8789717eed",
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\n",
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\n",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"})\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "1fd5d82c-8523-418c-8132-cfc284605b1c",
"metadata": {},
"outputs": [
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"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"Initial system state at time t=0:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
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}
],
"source": [
"log.write(f\"Initial system state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "markdown",
"id": "358042af-afda-4935-baec-563b0e0fd370",
"metadata": {
"tags": []
},
"source": [
"### First step"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "a69f25a4-34c2-48d5-bd0a-17cd4f0d3656",
"metadata": {},
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"source": [
"delta_t = 0.002 # This will be our time \"quantum\" for this experiment"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "f3c1fe2b-61d3-429e-92d2-b922e8a2fad5",
"metadata": {},
"outputs": [
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"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0.002:\n",
"7 bins and 3 species:\n",
" Species 0 (A). Diff rate: 50.0. Conc: [18. 2. 0. 0. 0. 0. 0.]\n",
" Species 1 (B). Diff rate: 50.0. Conc: [ 0. 0. 0. 0. 0. 2. 18.]\n",
" Species 2 (C). Diff rate: 1.0. Conc: [0. 0. 0. 0. 0. 0. 0.]\n"
]
}
],
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"# First step\n",
"bio.react_diffuse(time_step=delta_t, n_steps=1)\n",
"bio.describe_state()"
]
},
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"id": "901b2e59-fea6-4190-af69-fc49f14d9a64",
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"source": [
"_After the first delta_t time step_:\n",
"\n",
" Species 0 (A). Diff rate: 50.0. Conc: [18. 2. 0. 0. 0. 0. 0.]\n",
" \n",
" Species 1 (B). Diff rate: 50.0. Conc: [ 0. 0. 0. 0. 0. 2. 18.]\n",
" \n",
" Species 2 (C). Diff rate: 1.0. Conc: [0. 0. 0. 0. 0. 0. 0.]\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "0efdf530-d562-4ff5-8629-e1096c42e681",
"metadata": {},
"outputs": [
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"name": "stdout",
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"text": [
"SYSTEM SNAPSHOT at time 0.002:\n",
" A B C\n",
"0 18.0 0.0 0.0\n",
"1 2.0 0.0 0.0\n",
"2 0.0 0.0 0.0\n",
"3 0.0 0.0 0.0\n",
"4 0.0 0.0 0.0\n",
"5 0.0 2.0 0.0\n",
"6 0.0 18.0 0.0\n"
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}
],
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"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "13d683c6-4264-4acc-88e7-d9043e0bc125",
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\n",
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"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-1,
19
],
"title": {
"text": "concentration"
},
"type": "linear"
}
}
},
"image/png": 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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"})\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "47bca5d0-c1f8-478d-ac9a-acb3a4ffbb3c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.002:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "markdown",
"id": "c2f8bbb7-ccfc-4490-8245-580f2d753e10",
"metadata": {},
"source": [
"### Several more steps"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "a2746d1b-48f9-4d57-980c-9ea807a4e989",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0.004:\n",
"[[16.4 3.4 0.2 0. 0. 0. 0. ]\n",
" [ 0. 0. 0. 0. 0.2 3.4 16.4]\n",
" [ 0. 0. 0. 0. 0. 0. 0. ]]\n",
"SYSTEM STATE at Time t = 0.006:\n",
"[[15.1 4.38 0.5 0.02 0. 0. 0. ]\n",
" [ 0. 0. 0. 0.02 0.5 4.38 15.1 ]\n",
" [ 0. 0. 0. 0. 0. 0. 0. ]]\n",
"SYSTEM STATE at Time t = 0.008:\n",
"[[1.4028e+01 5.0640e+00 8.4000e-01 6.5984e-02 2.0000e-03 0.0000e+00\n",
" 0.0000e+00]\n",
" [0.0000e+00 0.0000e+00 2.0000e-03 6.5984e-02 8.4000e-01 5.0640e+00\n",
" 1.4028e+01]\n",
" [0.0000e+00 0.0000e+00 0.0000e+00 1.6000e-05 0.0000e+00 0.0000e+00\n",
" 0.0000e+00]]\n",
"SYSTEM STATE at Time t = 0.01:\n",
"[[1.31316000e+01 5.53800000e+00 1.18493120e+00 1.36813108e-01\n",
" 8.13120000e-03 2.00000000e-04 0.00000000e+00]\n",
" [0.00000000e+00 2.00000000e-04 8.13120000e-03 1.36813108e-01\n",
" 1.18493120e+00 5.53800000e+00 1.31316000e+01]\n",
" [0.00000000e+00 0.00000000e+00 6.72320000e-05 1.90027530e-04\n",
" 6.72320000e-05 0.00000000e+00 0.00000000e+00]]\n",
"SYSTEM STATE at Time t = 0.012:\n",
"[[1.23722400e+01 5.86200882e+00 1.51504114e+00 2.28008774e-01\n",
" 1.98211433e-02 9.28816000e-04 2.00000000e-05]\n",
" [2.00000000e-05 9.28816000e-04 1.98211433e-02 2.28008774e-01\n",
" 1.51504114e+00 5.86200882e+00 1.23722400e+01]\n",
" [0.00000000e+00 4.44384640e-05 4.52470702e-04 9.37489304e-04\n",
" 4.52470702e-04 4.44384640e-05 0.00000000e+00]]\n",
"SYSTEM STATE at Time t = 0.014:\n",
"[[1.17212070e+01 6.07811756e+00 1.81983529e+00 3.33817478e-01\n",
" 3.75512896e-02 2.50955578e-03 1.00983808e-04]\n",
" [1.00983808e-04 2.50955578e-03 3.75512896e-02 3.33817478e-01\n",
" 1.81983529e+00 6.07811756e+00 1.17212070e+01]\n",
" [9.98666893e-06 2.62777001e-04 1.65200869e-03 3.01131931e-03\n",
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"SYSTEM STATE at Time t = 0.016:\n",
"[[1.11568507e+01 6.21598919e+00 2.09433486e+00 4.48347321e-01\n",
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"source": [
"# Continue with several delta_t steps\n",
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" bio.react_diffuse(time_step=delta_t, n_steps=1)\n",
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"SYSTEM SNAPSHOT at time 0.016:\n",
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"0 11.156851 0.000295 0.000058\n",
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"2 2.094335 0.060947 0.004379\n",
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"4 0.060947 2.094335 0.004379\n",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot (interpolated) at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "b8f59740-166c-4909-bd92-321f6e865479",
"metadata": {},
"source": [
"A is continuing to diffuse from the left. \n",
"B is continuing to diffuse from the right. \n",
"They're finally beginning to overlap in the middle bin"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "9974a579-14c5-447b-9616-b136e356ee90",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.016:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "markdown",
"id": "4dc3b1cd-3ef9-4882-abfe-479cfc0a25cf",
"metadata": {},
"source": [
"### Several group of longer runs"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "bb248152-bda9-4f70-b81d-52d982a2233e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"+ 10 steps later:\n",
"SYSTEM STATE at Time t = 0.036:\n",
"[[7.92576526 5.95824446 3.31917619 1.31581241 0.35918764 0.07038175\n",
" 0.01251229]\n",
" [0.01251229 0.07038175 0.35918764 1.31581241 3.31917619 5.95824446\n",
" 7.92576526]\n",
" [0.01555131 0.07914514 0.24409632 0.36133444 0.24409632 0.07914514\n",
" 0.01555131]]\n",
"\n",
"\n",
"+ 10 steps later:\n",
"SYSTEM STATE at Time t = 0.056:\n",
"[[6.29600683 5.06118233 3.15970431 1.44600532 0.47532616 0.12019317\n",
" 0.03045075]\n",
" [0.03045075 0.12019317 0.47532616 1.44600532 3.15970431 5.06118233\n",
" 6.29600683]\n",
" [0.07498099 0.28735559 0.78250579 1.12144639 0.78250579 0.28735559\n",
" 0.07498099]]\n",
"\n",
"\n",
"+ 10 steps later:\n",
"SYSTEM STATE at Time t = 0.076:\n",
"[[5.13609493 4.21433746 2.7454954 1.35328847 0.4992179 0.14748071\n",
" 0.04559633]\n",
" [0.04559633 0.14748071 0.4992179 1.35328847 2.7454954 4.21433746\n",
" 5.13609493]\n",
" [0.1615343 0.52706799 1.31954666 1.8421909 1.31954666 0.52706799\n",
" 0.1615343 ]]\n",
"\n",
"\n",
"+ 10 steps later:\n",
"SYSTEM STATE at Time t = 0.096:\n",
"[[4.2209458 3.50170661 2.34873485 1.23042685 0.50075376 0.16821567\n",
" 0.0606064 ]\n",
" [0.0606064 0.16821567 0.50075376 1.23042685 2.34873485 3.50170661\n",
" 4.2209458 ]\n",
" [0.25982593 0.75464804 1.76534285 2.40897641 1.76534285 0.75464804\n",
" 0.25982593]]\n"
]
}
],
"source": [
"# Now, do several group of longer runs\n",
"for _ in range(4):\n",
" print(\"\\n\\n+ 10 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=10)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "dfa3d4e1-a187-4231-b9f1-658fbfc7dedc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0.09600000000000007:\n",
" A B C\n",
"0 4.220946 0.060606 0.259826\n",
"1 3.501707 0.168216 0.754648\n",
"2 2.348735 0.500754 1.765343\n",
"3 1.230427 1.230427 2.408976\n",
"4 0.500754 2.348735 1.765343\n",
"5 0.168216 3.501707 0.754648\n",
"6 0.060606 4.220946 0.259826\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
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"cell_type": "code",
"execution_count": 27,
"id": "c962bc0d-b2b9-411c-8c61-f2a0a1fdeb27",
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"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
},
"title": {
"text": "A + B <-> C . System snapshot at time t=0.09600000000000007"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
0,
6
],
"title": {
"text": "Bin number"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-0.17052356207501188,
4.452075766293424
],
"title": {
"text": "concentration"
},
"type": "linear"
}
}
},
"image/png": 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e/xlrFWXdyM8aRV5XpwU3YtxJAa5mYwxCnGzGSV9XX/zvReT/3b/3vpb/mxaKgO3mH1u9fzUTxZpdN1tVf19oHc1WS1I0uoY0+2w38pNWBa+UU7Vo2sgPOhlXo89Ps894o4jyVkJodbq75yuN1sRt9H+WcTVfb7Kde5duPk+cAwEIQAACEIAABCAAgTAJIE6WaLeTtt1q/bBWk+aHONmsWvdC67uF6Ux+9tVoLUFtfyGRwLOhE3HSO6fZWnqtRKJWIkujNUwbCav160tWR9e0wyEocdIToerntZpHJ+Jko/a0rWaRk8qq2u8bifCN1v2r95FOxElPNHn98KnysJsVNKpfT3QhMbHeVrXzjaNnnDUK68+tLsrUjhhf7yfedSEocbIRJ32tHVv1ffWfjXYKZrVzfakvZtXo+rjQjzr114FG15xGn8tW89/o/c2WbKi/HrRiWu+DrTi2M65Gc6OvNavA7n3+q+emGQfGVSmk5PHyY74a/YjUzmeF90AAAhCAAAQgAAEIQMAmAoiTNs0GtsSKQKs14mI1EMuMhatlE4I5EIAABCAAAQhAAAIQgAAEIACBAAkgTgYIl6b7m0C3af79TaX30SFO9s6QFiAAAQhAAAIQgAAEIAABCEAAAnEhgDgZl5nCTqsI+FGIyKoBWWQM4qRFk4EpEIAABCAAAQhAAAIQgAAEIACBgAkgTgYMmOYhAAEIQAACEIAABCAAAQhAAAIQgAAEIACBxgQQJ/EMCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHESH4AABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiIYA4GQl2OoUABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQQJ/EBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICiJORYKdTCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAHHSBx+4eH3ah1ZoAgL2ExgfTTtG3pnO2W8sFkLABwL4vA8QaSJWBPD5WE0XxvpAAJ/3ASJNxIoAPh+r6cJYnwismxj1qSWaCYoA4qQPZBEnfYBIE7EgwM1MLKYJI30kgM/7CJOmYkEAn4/FNGGkjwTweR9h0lQsCODzsZgmjPSZAOKkz0ADaA5x0geoiJM+QKSJWBDgZiYW04SRPhLA532ESVOxIIDPx2KaMNJHAvi8jzBpKhYE8PlYTBNG+kwAcdJnoAE0hzjpA1TESR8g0kQsCHAzE4tpwkgfCeDzPsKkqVgQwOdjMU0Y6SMBfN5HmDQVCwL4fCymCSN9JoA46TPQAJpDnPQBKuKkDxBpIhYEuJmJxTRhpI8E8HkfYdJULAjg87GYJoz0kQA+7yNMmooFAXw+FtOEkT4TQJz0GWgAzSFO+gAVcdIHiDQRCwLczMRimjDSRwL4vI8waSoWBPD5WEwTRvpIAJ/3ESZNxYIAPh+LacJInwkgTvoMNIDmECd9gIo46QNEmogFAW5mYjFNGOkjAXzeR5g0FQsC+HwspgkjfSSAz/sIk6ZiQQCfj8U0YaTPBBAnfQYaQHOIkz5ARZz0ASJNxIIANzOxmCaM9JEAPu8jTJqKBQF8PhbThJE+EsDnfYRJU7EggM/HYpow0mcCtomTH3/2y2ZixRLzvW9+0eeRBt/coaNnzKc+/1Xzg299xezevsm3DhEne0X5wQ+arEma/P0bTe6BjSa/4QGTf0B3eS6vmXS61x44HwLWEOBmxpqpwJCQCODzIYGmG2sI4PPWTAWGhEQAnw8JNN1YQwCft2YqMMRPAsWcSU+fNynd710wqdkL5efJ3KRJf/SIn70t2NYffOHr5lcHjta8b8WycfPSiy84r0UhTr7405fNl//sL8zXnv+seeYjTy44hmZvQJzsGl3AJ46OGjMz07CT4sioya9bb/LrNzjHQtVj5/V1G0xhxYqADaR5CPhHgJsZ/1jSUjwI4PPxmCes9I8APu8fS1qKBwF8Ph7zhJX+EcDn/WNJS+ERSGZviuD4jrtPv22SepxxHzuvyeNEfqq5Qf9tMTRjd/72s6ZaiPQ6VsFyzcrl5k//+A8jESf9AoA46RdJv9s5e9ZcO3LKpN6RD0X9flE+NDduNO3RES9VuJy33y+vuaJmcWzcb4tpDwJdE+Bmpmt0nBhTAvh8TCcOs7smgM93jY4TY0oAn4/pxGF21wTw+a7RcWKABBL5u67QOFPaSyJk+bm83kp8LGSWmfyIaCvDsutxVHfRVfSx7Gs27AjQ+krTKkCePPN2OUKyWade5KT+3YuwbCZoVkdgVqdSP/XMc+bJx3ebl/cfMjcm7zhdfe7THzP3r1/tREh6m3dOI1GxPsJTz3/uM58wjSI/j/zd950mESdDcaXuOmm15mTqoqj4FyS0+K3zJn32jBwlxFiep+W5Hhfacg9tdlLEnVRxSRnPbZLnpRTywuo1C53O3yHgKwFuZnzFSWMxIIDPx2CSMNFXAvi8rzhpLAYE8PkYTBIm+koAn/cVJ411QCA5e9lNtZ7R1Gs9Sur1PdFI5DV93UhqdqstPyIBXKOyfN4i0URGRB8Z1d17vr7luWGtOalRkx/73Sec6MhWm4qTp86944iJKgbqpmLjw5s2lNehVIHw+o3b5j98/2vO31/47o/Nt//yJ8YTCfX9Kkp64qP39/r0cT1X26gXFeuFVP37n/+f/97pX//2R//j75fXlFR7m7XTgQu0fCtrTvpAstuCOMlbt0rRlm/VRF0mvQhMibxMZLNNLVRxMrdBfg3w9vVVj+W1wsRKH0ZHExCoEOBmBm8YNAL4/KDNOOPF5/GBQSOAzw/ajDNefB4fCIpAMntDUqxF25iWfaZ01Oe6BqQ+n73UvOtEuhTxWIl29KIenShIiYgsZJZ3bXoY4qQn/rWzpmOjNSe/9CffMW+eON9QSPQGroLkJz/6IUfQ9CInPSG0UUSjtqmRlbrWZfXftT0tatOOrZ4w+qO//tm8diiI07VL9naiTuxP/vaVeVWJuhUnF7ImMTtjUmfOlKMsNeoyffZ0ORJTxc1Wm7OupRbm0ejLBx9yC/bIYz0SdbkQff7eiAA3M/jFoBHA5wdtxhkvPo8PDBoBfH7QZpzx4vP4QC8EktnrEu0omoREP6an5CiFZ1JTolk4r73TsulCZqkIkKJJSLRjfpHoFMMS+bhY9Al9bdEDppga68W0lufGTZz0itc0GpQXbdlMnKwWHDWaspGoePr8RSf124vCbNSPF5lZ/Td9P2ndgblpew2rc/xfP/gbJ/S2vmR6UOJkS8uKRZN6WyMuZddj1Z52XpOoyzu3mzZB1GV78867aglwM4NHDBoBfH7QZpzx4vP4wKARwOcHbcYZLz6PD7QiUBP96EVAatRjORLy3aanq7hYWedRIiBlzcfciHvMD7tHk0hFMgFhiJM6sE7SuidWLCmncOu51ZGTnji5kHioa07WR076IU7qON6/b3vZvuqUcsTJSFy40qlOjoqSGvpqhTi5EI9czo249CIvnfUu5deNM/KLhhy7jrqUyMvCxMRCvfP3PiXAzUyfTizDakoAn8c5Bo0APj9oM8548Xl8YNAI4PODNuPzx9tL9KMKkLlFmyprPcq6j7lRydSUyEddC9JIeraNW1ji5EIFcVSAbFatu1Fad6u0614iJ3WOmqV1NxJGESct8WpdD+B/+NQ/NJs3rouPONmKXaHQMOrSjbgsRV3edas9Ndry962TojxugR7nKHvOeSy/hsjj4qLFlswcZvhNgJsZv4nSnu0E8HnbZwj7/CaAz/tNlPZsJ4DP2z5D2Oc3AXzeb6L2tZcoTMu6j5Ju7UQ+ytJwzmNd99E7vt3U6GJqsaRea5SjrvNYinp0ql5LFGQpAtIk7RQgW81EWOKk2qCBbfWVtz3BzyuWs9Cak9qOVzG7OnpSBcz379thnvnIk03XnGwnclLXilQbbkzeLlcW9wriaCGceuFSx6Qbad0Rft518i9fu+mEszYLX80XihFaGEDXEnVpzp0zidOnSsczztHI88Qpee3u3eadjowY8+CDprh5izFbtshxU81zk47fhSwAwrFtMpFwTZdVBdggMBAE8PmBmGYGWUUAn8cdBo0APj9oM8548fk+8QGtbH1XvrPf1e/n8j39rnxnl+dmSh7fkdfyM80Hmh4zxXH5vr7oQWPkWFz8gDFjenSf2xr92MvMpZKlL7K9NNLBuZ6wWH1KtWjYjjip5zZqp7pad7dp3V4hG69quGenZ6NXb8V7Xde59CqFk9bdgSP49VZVt7/x7R/WKMmN0rov32zxwffLGFvaEeFSC/OU93YNucAAACAASURBVLcvmGT1c3ls8vmG1hbHxsuRlhphWShFXWrRHue5VB9ns5vA2IgrLt+dkX+GbBAYAAL4/ABMMkOsIYDP4xCDRgCfH7QZZ7z4fHx8IJm9KhGPslSbRD0mvejHqmMi16xAbkIiHyWzUfZC6eg9z4+4rxWTQ/EB4YOla5ZLEBWb1QQSRdmstjBC49qpkKTmRVIQJ0IurbrWtSzLa1tKZfH0OVnr8oKEkp88blIXF6jeJeJkbpNU63r4EZN7UNax0Mri+vyhTfIrTnCVuyxFaaVZpIFYOS0YFSABfD5AuDRtJQF83sppwagACeDzAcKlaSsJ4PN2TUsif1cqXUu1a618LRWv0zPy+O4JV5RcqPr1kHx/1mrXY/L9eUS+P2sFbGf9R6kTIZWx2SoEwkzrhnt3BBAnO+DWLHwVcbI9iMnr10SolKI8GmkpEZeVCEy58MpryduNq4sXMxmJrJToyo0PuutbaqSlE21ZOq5Z254BvKtnAtzM9IyQBmJGAJ+P2YRhbs8E8PmeEdJAzAjg8zGbMMztmQA+3zPCjhtIZq+IAKkRkCo4use0Hqfcx4nibMM2i6lxKTIjEZAS7ViOfByWx44IKRGQQ6s7tmVQT0CctH/mESc7mCPEyQ5gdfrW6uriXsSlVBZPS5XxtDw3ug5mk03Twece3upEXOYlyjKnEZey5zdJxOUw4dudTkWr93Mz4ydN2ooDAXw+DrOEjX4SwOf9pElbcSCAz8dhlrDRTwL4vJ80q9qSNSA14jE9Ld9hJQIypdGQTkSkZBAuEAGpVa7zi+V7rEQ95hbLd9pRER+lIrbN1a8DohhYs4iTgaH1rWHESR9QEjnpA8QWTWhEpaaKp86fK0VeymOJwHR2eb1pxKVUDc8/IJGWXtSlRFuWH8trheXLgzW8D1vnZqYPJ5UhtSSAz+Mgg0YAnx+0GWe8+Dw+MGgE8PnuZzw5J0uYacTjvXMiQpaiIOWxvqYVsRO5Ow0bL6YlAlLXfhyRzD8RHh3xUY9SkEZfK2SWdW8UZ7ZFAHGyLUyRvglx0gf8iJM+QOy2CY241EhLibBMaaSlrHHpPD8p63SIeNlqy2m0pURa5nVdyy2yTodEXmoEJoV5mlPjZqZbR+W8uBLA5+M6c9jdLQF8vltynBdXAvh8XGcOu7slgM8vTC45e9mJfszcfdONgJToRycKUl4zWiW7yZYfWS+Rj/IdU6Ie86XIR42EJAJyYeZBvwNxMmjCvbePONk7Qwri+MAwiCYSszMiWJbEShEsU06KuOwLFOfR4jtOUR5ND9+2vVSkxxUyB70wDzczQXgqbdpMAJ+3eXawLQgC+HwQVGnTZgL4vM2zg21BEMDnXaqJwoyIjpKGLYVoXPHxpKRlSwq2pGVrhGSzrVBXhCY3Jt8TtQiNpGUXkywpFoTP+tEm4qQfFINtA3HSB75ETvoAMeQmUpcvmdS5sxJdKSH5zlFC8UvPU++83dAaXb8y/+BDJqeFeWTPbXyo9FyOGzeaoqSR9/vGzUy/zzDjqyeAz+MTg0YAnx+0GWe8+Dw+MGgEBsnnE4XpUgq2pF7fOyup1/K9b1pTsuU4dU4EynsNpz8/sk5Sr+X73qh8z9PUa+exHBfJ8+F1g+YyfTFexEn7pxFx0oc5Qpz0AaJFTSSvXDYZia50UsNLkZZexGUzM1W4dKItNUVc08U14rKUNt5P0ZaDdDNjkUtiSoQE8PkI4dN1JATw+Uiw02mEBPD5COHTdSQE+tHnK1GQ8h1Oi9I4EZFuKnYif7cpZ023dgrQLJbjqBSgkcdzYztNYXhNJHNDp8ERQJwMjq1fLSNO+kAScdIHiDFoInnjRiXS8rz88lYdcSnPG23F0UWSDq4Rlm4VcaeauEZf6lqXEnkZt60fb2biNgfYGy4BfD5c3vQWPQF8Pvo5wIJwCeDz4fKmt+gJxNnnU1KERgXHlEQ+umtAyuPSsZkI6Va+lu9j1dGPEhGpkZCFoZXRTwgWhEIAcTIUzD11gjjZEz73ZMRJHyDGvInk9etuIZ6jb5r0KfmlrlSUR9e3bLYVJibM3LadbsSlU5Bnq5nbvcfqgjxxvpmJuYthfkQE8PmIwNNtZATw+cjQ03FEBPD5iMDTbWQE4uDzWpAmc/sNSb/W9SDlu5UUpsnIepDJ7OWm3LwoSLcgjXy3GpNdHheGJiJjTcf2EECcdOdi528/a7Y8uN78h+9/zZ7JKVmCOOnDlCBO+gCxT5vwivI4aeLHRLiUVHEVLPWof2u0eQV55raLcLnlYTc9XAVMOUa9xeFmJmpG9N9fBPD5/ppPRrMwAXx+YUa8o78I4PP9NZ+MZmECNvm8RkJqRWwnBfvuUfcoe7OCNFpwRgvPzKkAuXhHWYDUdGyK0Sw894P8DsRJY1747o/Nf3zpVXNj8rb5N3/6R2b39k1WuQTipA/TgTjpA8QBbKI6ujJ9TP4ZO6Kl/DO+1bg6nLeu5dzuveU1Lee27TD5BzaGRs+mm5nQBk1HA00Anx/o6R/IwePzAzntAz1ofH6gp38gBx+Fz6dm3jGZOxIJWRIhM3eOOBGRzVKxi6kxd/3HcQnWWCTBGloRW55rJCQbBLohgDhpzMef/bL5nafeY147ctKsWbnc/Okf/2E3KAM7B3HSB7SIkz5ApIkyAacgzyH5562p4ZoiLqnimWNHjKaON9rKkZaSEj63VX5B1KOki2vauN9bFDczfo+B9iDQCQF8vhNavLcfCODz/TCLjKETAvh8J7R4bz8QCNLnNeIxc+egk4btpGKXBMlmkZCFzFJHcJwb3+OmYmtE5LgEX4ys7wfUjMEiAqGKk5cuGXPsWPijX7vWmG3bGvZ76OgZ86nPf9X84FtfMafPXzTf+PYPzUsvvhC+jS16RJz0YToQJ32ASBOtCRSLrlh55rRJnT4lR931+SmTOn9u/rmplLuOpaaFb5Zdj87zR0xhxYquaQd5M9O1UZwIgQAJ4PMBwqVpKwng81ZOC0YFSACfDxAuTVtJwA+fT85NlipiSyDFPfle4lTHPmFSUydNojg3b9z50QdEfNwiuxQI1aNWx9ZK2fLYJFJWcsKo/iIQqjj54ovG/N7vhQ/wmWeM+au/ativl9LtrTWpa0+qUGlTajfipA8ugzjpA0Sa6JpAOdJSUsIzx+UXSo261DUtp+7ObzOdlqhKia6U9Szndu12IiznHt3XdpSlHzczXQ+UEyEQAQF8PgLodBkpAXw+Uvx0HgEBfD4C6HQZKYFOfT6Zve5GQ97RojSHpFCNPNaU7ML89fNr0rHHtsvakPJdY4kU/BxeE+mY6RwCoYqTP/2pMV//evjQP/xhY55/vmG/Xkr3c5/5hPP3P/jC161L7Uac9MFlECd9gEgTvhNIXZAFpg+rUCmi5eFD7lGK8phcbl5fTuVwESkdsVJES0e8FBHTiJhZvXV6M+P7oGgQAiETwOdDBk53kRPA5yOfAgwImQA+HzJwuoucQFOfL+YkFfuEI0Rm7sh3B1kfcujWgcYVshNppxiNFqaZG3+MNSEjn1UMWIhAqOLkQsaE/Hcvpbu+2xXLxq1K7Uac9MExECd9gEgToRBI3rzpFt7RtSxPnSw9do/1mwqW5UrhmhIu1cKHd+0whc2bzZ3p+QJnKAOgEwiETIAvrSEDp7vICeDzkU8BBoRMAJ8PGTjdRU5AfT45ddbM3DgqkZBudWwvLTuZvTLPPicd2ylGI7uuCymipO6FzMrIx4IBEGiXwCCLk/Up3R4zTe3+2vOfNc985Ml2MQb6PsRJH/AiTvoAkSYiJaDFdjKvH3AK72iUZeawpGtIanijKMvi+vVmdq9EWe59zGjl8Oz7nzCFpUsjtZ/OIRAUAb60BkWWdm0lgM/bOjPYFRQBfD4osrRrCwGnSM3tV53iNJlbvzbDtyUa8t75huZpMRonFXupRENKVGR2iSz/REq2LVOJHT0QGGRx8qlnnjOf/OiHjJfS7WHU1G7dvvfNL/ZA1r9TESd9YIk46QNEmrCOQPLaVTeyUkRKJyVcd4m4TJ47V2NrcWjI5LZuNzlJA5/bVjnmNz5k3ZgwCAKdEuBLa6fEeH/cCeDzcZ9B7O+UAD7fKTHebzOB1PQFk5k6WqqWrZGRUjX7zlFZH3K6xuzCovvN3CKpjO1ERFaO+WGp9ssGgT4kMMjiZFymE3HSh5lCnPQBIk3EgsB4ImdSR9802YOyDs0xufGRNSwzx48aXd+yeiuOjIpYKYtga/GdsmC5w+Q33B+LcWIkBDwCfGnFFwaNAD4/aDPOePF5fCCuBFIz74gIWRIgVZB0CtaIEJmvLYqZH9kgadhyXz4m9+VyHJrYbQoSIXl7bjiuQ8duCHRMAHGyY2Shn4A46QNyxEkfINJELAg0uoFP3JuSdHBXqHTESucoguXFd2oFy7HxcmSlRlp6UZb5+9bFYuwYOZgE+NI6mPM+yKPG5wd59gdz7Pj8YM573EadzF4uRUHKvbaIkOlSdGQyd7tmKPnh+4ymZjti5OLSUR4X00vK78Pn4zb72OsHAcRJPygG2wbipA98ESd9gEgTsSDQyc1MWiIsh16X9W0OvmaGfrPf6PPE7My8cc7t2mPmHpM1LHfuMdn3Pi6VwneY4vBILHhgZP8T6MTn+58GIxwEAvj8IMwyY6wmgM/jD9YRkKrZmdtvSKXs/SJIyjqRk7IuvKRnG3m9eismR0SE3GGyyx6XqEi5n14m99Py3Egl7VYbPm/djGNQCAQQJ0OA3GMXiJM9AtTTESd9gEgTsSDQy82MUyn8uEZWelGWkoYiUZa6tmX1Vli1WoTK3aV9l8np4x275EYrEQtGGNlfBHrx+f4iwWgGhQA+PygzzTg9Avg8vhA1ATcdWwpS3jnsFK1JyzE1+27t/fHQClkbUtZ3lyhIFSS9NO3CUOcVs/H5qGec/qMggDgZBfXO+kSc7IxXw3cjTvoAkSZiQcDvmxmNpHQiLCWyMnNEfhl+TX4ZPvzGPBb5deudqMrs4x80c3Kc272H6MpYeEz8jfTb5+NPhBH0OwF8vt9nmPHVE8Dn8YlQCXhRkTdfkcjIXzvRkanp+ZWz58a9SEjJLFoqmUWSqq2Rkn5s+LwfFGkjbgQQJ+2fMSvFSS11fmPyTkN6R/7u+9ZRRZy0bkowKCACYdzMpN6SKoNH5Ndj2dN6PCzHM6dqRlRYuaocXZnbuct9rNGVyWRAI6fZQSUQhs8PKlvGbScBfN7OecGq4Ajg88GxpWUjkZBHpGiN3M/ell2OblTkpRo0+dGHzNwSuZcdk31cdnmsrwW14fNBkaVdmwkgTto8O65t1omTH3/2y2ZixRLzvW9+0X56JQsRJ2MzVRjaI4EobmYS0/dEqJQ0FxUrJaoy86Y8FsEyMVVbiXBux06T26Hp4CJWyjG3S27s1qztccScPugEovD5QWfO+KMlgM9Hy5/ewyeAz4fPvF97TM5dNZlbcq9697AjQmbuaKr2IRlusTzkYnLUER9zY3K/qtGRJTGymBoLDQs+HxpqOrKIAOKkRZPRxBTrxMmdv/2s+drznzXPfORJ++khTsZmjjDUHwK23Mykz50RoVJu+ByhUm4CRbhMnT9XM8jCxMradSu96MpUyh8YtDIQBGzx+YGAzSCtIIDPWzENGBEiAXw+RNh91pWuEVmJinTFyOTs5ZpR5kcfkIhIESKX7JHUbI2OlPXUFz8cKQl8PlL8dB4RAcTJiMB30C3iZAewmr2VyEkfINJELAjYfDOjIqWzduWrsn6PVgc/eXwe08LqNWb2t5422fd/0GQ/8ITRSuFsEGhFwGafZ+YgEAQBfD4IqrRpMwF83ubZscu29NRxM3zjJTOk++QrJjXzzjwDc4s2S9VsWSd96ftMdrnca7ZRPTvsUeLzYROnPxsIIE7aMAutbbBOnNS07t956j3muc98wn56JQsRJ2MzVRjaI4E43cykT51w0sHddStL0ZXvvF1DILf5YTO351HZ95aOj5nC8uU9UuL0fiIQJ5/vJ+6MJToC+Hx07Ok5GgL4fDTcbe81mbst60S+Jvvrsh+UqMjXJUryWI3Z+ZF1Eg0pUZFjkp7trBkpUZFSTdv2DZ+3fYawLwgCgyxOHjp6xnzq81+dh9W2jGXrxMkXf/qy+ca3f2heevGFIHwykDYRJwPBSqMWEoj1zUwuZzLHpDL4yz83w6/IL96/+LlJ3rpVQ7m4eEwiKiWqUqqCa2SlVggvDvtTGdHC6cSkNgjE2ufbGB9vgUA9AXwenxg0Avj8oM14k/FKFe2hWwckKlLuEyc1OvKXJpGvXd+8kFkq0ZCSgbNc7hOXyX3i0n1SwSEdO4D4fOymDIN9IIA4+VXzg299xezevsmh+aU/+Y55ef8hq3Q368RJXXOy1Ua1bh8+mTQBgS4J9NPNTGJm2mTekF/C35BfxL1dIiyrNy2oM7dboir3PlaKrHzU5O9/oEt6nBZHAv3k83Hkj83hE8Dnw2dOj9ESwOej5R9V75qS7URFSkSkGx35+rw07bnxnVKwRjJslugu94NyDLNwTVBs8PmgyNKuzQQQJ2vFSQ0K/PKf/YWxSV+zTpy02aGb2UbkZBxnDZu7IdDXNzOFgskcqhMr5Xkimy2j0pTvuT2eUOmmgmtqOFv/Euhrn+/faWNkPRDA53uAx6mxJIDPx3LaOjY6fe9MSYyUez1N1771uknOXau0k0iJEOkKkOVdnheTmY77sv0EfN72GcK+IAiEKk5OXzLmdu0yEEGMaV6bo2uNWbJt3steWnd15OQffOHrzvu+980vhmJaO50gTrZDaYH3IE76AJEmYkFg0G5m0kffFMHydTPkRFa6wmXi7p3yXGkauBtZqetWPmqyIlzmtu+IxVxiZHsEBs3n26PCu/qZAD7fz7PL2BoRwOf70y/SU8fKEZEqRGqEpK4j6W3F1CIzt1Tu38aqBEmppj0IGz4/CLPMGOsJhCpOvv2iMT//vfAnYcMzxjz9V03Fyfo/fO7TH7Oq1ouV4qQXYloNL6rFOjUX/yd/+0rNPNaHviJOhv+5o8doCAz6zUz67GmTOVhKA3eiLF8zyevXKze6mUw5/dsttOPuJpGIZsLotWcCg+7zPQOkgdgRwOdjN2UY3CMBfL5HgJacnrkjxQ9vSUTkHY2MdNO0E4WZsnWFzDKJiJTsF42OVFFSjrnFWy2xPlwz8PlwedObHQRCFScv/tSYo25kYqjb2g8bs/P5puJkdeQkad1tzMwL3/2x+fZf/qRmsU4vDDUKZVerh/+LL36mvHCo2vejv/5ZzcKhiJNtTCxv6QsC3MzUTmNKqn8761WqUHlQbojlmLr4Ts2b5nZJBceqNSu1MjhFduLzccDn4zNXWOoPAXzeH460Eh8C+Hx85sqzNFGYq4iQKkjedQVJUyyUB5MflnXDHSGyJEhKunZ+dGP8BhuAxfh8AFBp0noCoYqTltFolNatJmq9l2rBMmqzrYucfOqZ58wnP/qheeGljUTBKOA1mljEyShmgj6jIMDNTGvqyWtXS+nfrlCpUZbpc2dqTspt3e5GVJbSwbPyuDi+JIrppM82CODzbUDiLX1FAJ/vq+lkMG0QwOfbgBTxWxL5qUqKthMZqRGSR2qsUuGxvGZkSZBUgZJtPgF8Hq8YRAKIk7UFcbygQAritPg0qHrbKIXblrBTXTj05Jm3iZwcxCsaYzbczHTmBMnbt501K51U8FKxnfTxo7Vi5YObymtWemnghYmVnXXEuwMjgM8HhpaGLSWAz1s6MZgVGAF8PjC0XTeczN6UaMhSFW1nvciDJj11ovb+afEjbuEar4iNVNUuDC3vus9BOhGfH6TZZqweAcTJr85zBpuESTWOyMk2P68a0Xlj0i2EYdsktjkE3gYBCERNYHbWmAMHjHnttdpjtV3332/Mvn3GPPaYe9R9/fqoLad/CEAAAhCAAAQgEAyBGalse0Puj3S/KfdIepw6V9vX8r3GLJd7oxVyX+QdpagNGwQgAAEI9AcB68RJ29acrJ/mRuGvpHX3x4eBUSxMgF9aF2bU6TtSF86boV+9IvsvzfAvXjLpk8drmtD1Ked27zHZ33razD7xlMl+4INGq4SzhUMAnw+HM73YQwCft2cusCQcAvh8OJyre9FCNUOT+83Qjb8zQzflHkgeVxev0ffmFm022eVPyP6kmV3xNOtF+jhN+LyPMGkqNgQGOXIyLpNknTip4Gyq1t1oIusXDkWcjIu7Y2evBLiZ6ZXgwudr2nelyI6mg79uND3c2woTE26Bnb37TPbRfc7j/AaJtmQLhAA+HwhWGrWYAD5v8eRgWiAE8PlAsNY0mpq5KKnZsk6krhU5+aoZkmMye6X8nmJqrKaKtltVe2fwhg1oD/j8gE78gA8bcdJ+B7BSnLQJm6Zzv/TiC2WTvvQn3zEv7z/EmpM2TRK2hEaAm5nQUJc7St66ZTK/2W+GX3nJDP3i52bodUl1yuUqhqTTjkhZjqx88imqgfs4Tfi8jzBpKhYE8PlYTBNG+kgAn/cRZqmpSmSk3LvclL1BZOTcuGSFTEhWyHLJCln+tClklvpvCC02JIDP4xiDSABx0v5ZR5xcYI4+/uyXzalz79S8q37NSSIn7Xd0LPSHADcz/nDspZXU+XNm6KBEHnj766+a5ORkucnCylVuRGUpqlKP+fvW9dLlQJ+Lzw/09A/k4PH5gZz2gR40Pt/79Cezl83QrQMmo7tGR8qemn233HAxvcRkNRpyqdyfjOvxMSdtmy0aAvh8NNzpNVoCiJPR8m+nd2vESU2V/tynP2a+/Zc/aWm3jcVoECfbcTXe0w8EuJmxbxZT589KNKV8EZCISlewPGA02tLbCqvXmKymgVcJlvm199k3EEstwuctnRjMCowAPh8YWhq2lAA+3/nEaEq2pmY7YmRJkEzNXqwSI8ddMVKFyGUiSMrj3KItnXfEGYEQwOcDwUqjlhNAnLR8gsQ8a8RJ+1E1txBxMs6zh+2dEOBmphNa0bw3fe6MybzmCZUlsbJqzcr8mrXumpXVYqW8xtaYAD6PZwwaAXx+0Gac8eLzC/tAcu6arBV5QARJLzLygEnNVDLLiqnFIkDKEjMSEemsF6li5OJHFm6Yd0RCAJ+PBDudRkwAcTLiCWije+vESY2g/NrznzXPfOTJGvO1SvaP/vpnNWs9tjG+UN6COBkKZjqxgAA3MxZMQocmpM+cciMqS9GVmhKeuHun3IqmfLsFdlzBUlPCC6tWd9hL/74dn+/fuWVkCPL4AASUANf5+X6QzF53UrOHbr1aLmSTmn6r/MZiapETFZktRUW6YuRWHComBPD5mEwUZvpKAHHSV5yBNBYbcdKr4E1adyB+QKMQaIsANzNtYbL6TenTJ0tipURAqGCpYuXU3YpYuW59WazMPvoeESwfM7qO5aBu+PygzvzgjhufH9y5H9SR4/NGKmffEDFSoiKlorazdqSuGTl9oSJGJkeddSJVhPTWjswt3jaoLhP7cePzsZ9CBtAFAcTJLqCFfEpsxMlGVbJDZtW0OyInbZkJ7AiaADczQRMOv/30qRPl9Sq9tSsT0/cqYuX6DeXiOtm9WmhHxMqJleEbGlGP+HxE4Ok2MgL4fGTo6TgiAoPo88m5SVkrshIVqYJkavp8RYxMDJfXinQFyX0mN7Y9ohmiW78JDKLP+82Q9uJHAHHS/jmzQpz0oiIXwtUo3Xuhc8L4O+JkGJTpwwYC3MzYMAvB2pA+ccyJpnQqgmuRHYmuTMxMV8TK+x9wIiudIjuOWClp4CtWBGtUhK3j8xHCp+tICODzkWCn0wgJDILPJ+duSVRkpXjN0C2NjDxbESOTQ+W1IrWidnZcxMjxHRHOCl0HSWAQfD5IfrQdTwKIk+686TKK9Zst2clWiJPVcJqtOWnzRwBx0ubZwTY/CXAz4yfNeLSVPn7UFSu9auAqVs7OVMTKBza6YqUW2CkJloXly+MxuDasxOfbgMRb+ooAPt9X08lg2iDQjz6fzN1207TLFbVfM+npM1ViZKYiRjoFbGQZl/GdbdDiLf1AoB99vh/mhTEES2DQxUkvIPBzn/6Yee4znyjD1gxl3f70j/8w2Aloo3XrxMk2bLbuLYiT1k0JBgVEgJuZgMDGqNn0saMiVEoqmEZWlqIrE9lsRazc+GCVUOlGVxaWLYvRCGtNxedjO3UY3iUBfL5LcJwWWwL94POJ/J3yWpEZiYpUUTJ971RlThKp8lqRWshGoyPnxnfHds4wvDcC/eDzvRHg7EEkMOji5FPPPGc++dEP1QiTtvkB4qQPM4I46QNEmogFAW5mYjFNoRqZvHLZDP/i52boFy/J8SWTPnm8pv/i4jGT/cAHzezTHzLZ9z/hCJcmnQ7Vxl46w+d7oce5cSSAz8dx1rC5FwJx9fnMnTfM0PWfm+GbL5mhmz83mrpdveVHN5rZFU+b7PInnaM+Z4OAEoirzzN7EOiFQJji5KW7l8yxa8d6Mberc9eOrTXbVs4vVnbo6Bnzqc9/1fzgW18xu7dv6qrtME6yTpz0wDUbvC358NX2IU6G4ar0YQMBbmZsmAW7bcgcOSzrVFYiK3XtSpPLlY3Oaxr47r1mbs+jbjq4HAur11g7KHze2qnBsIAI4PMBgaVZawnEweeT2WuyZuTrEhFZ2dP3KmnaCndOitZ4lbTdyMi91jLHsGgJxMHnoyVE7/1IIExx8sVjL5rf++HvhY7xmW3PmL/6R381r18vpdtGLa3aWOvESQ03ffLx3eb9+3aYb3z7h+alF19w7P34s182v/PUe6wMQ0WcDP1zR4cREeBmJiLwMe52wcjK4RGTfe/jJvtbT7m7RFZqtKUtGz5vy0xgR1gE8PmwSNOPLQRs9PlEYcYMTe43QzckKnLyl87jRP5uDTIiI23xoPjZYaPPx48iFseNQJji5E9P/dR8/RdfDx3Rhzd/2Dz/5PPz+iVyFn4DogAAIABJREFUssup8AribN64zvyTL/15WZxUtbdarOyy+UBOQ5wMBCuNWkiAmxkLJyVmJumalZk3pMDOGxL9cVB2OSamKl+4ChMrJaJSoir3yJpYElWZlcf5jQ9FNkp8PjL0dBwRAXw+IvB0GxkBG3w+NX3BjYrU6EhZM3JIHiezl8tMislRWSdS/jcukX3cO7JmZGROE/OObfD5mCPE/BgSCFOctBGPFwRoQ+GbZnysi5ysrtatj73QU5tDUREnbfz4YVMQBLiZCYLqYLeZPn3SESg9oVKFy+TkZBlKYenSslDpipaPmtyWR0KDhs+HhpqOLCGAz1syEZgRGoEofD5973RNinbmjvzvy96oiJHpJSarIqQnSIoomVs8fx2x0CDRUV8RiMLn+wogg4klgUEXJ5tV637huz82Fy9fo1p3I6/W9O0dj2x04FQ/1hLnL+8/VI6ktOkTgThp02xgS5AEuJkJki5tK4HU+XMmc+igI1gOiVCpomXy6pXKF7ZFi0vrVbpCZVYiLHPbdwQGD58PDC0NW0oAn7d0YjArMAJh+Hx66liNGKmRkYnc7coPcUMTEhUpGQMaGTkm6zKLKJlbtDmwMdPwYBMIw+cHmzCjt5HAoIuTOieN6rusWDZujcZmXeRkvSNr9KS32VpdCHHSxssPNgVBgJuZIKjSZisCqXcvliIrRajUCEvZUxffqYiVQ0OuWOntUmRHC+74teHzfpGknbgQwOfjMlPY6ReBIHw+c0eKw92W/1teEZtbIkYWpssm54fXuunZS0uCpIiS+ZH7/RoS7UCgJYEgfB7kELCdAOKk7TNkjPXipP0IjUGcjMMsYaMfBLiZ8YMibfRCIHntqpsCfsgVKofkcer82Zom3UrglXUr9Xkxk+mqW3y+K2ycFGMC+HyMJw/TuyLQs88XCyJCSsR/ab1IXTtySB6bQq4iRo4+4FTPdiIjSxGSKlCyQSAKAj37fBRG0ycEeiSAONkjwBBOt06crF5zMoTx+9IF4qQvGGkkBgS4mYnBJA2Yiclbt5wCO9XrVqZPnagVK3fsrKxbWRIui6OL2iKFz7eFiTf1EQF8vo8mk6G0RaBTn08UZmvXi3QiJN+o6UtTsl0h0tsfM4XMirbs4U0QCJpApz4ftD20D4EwCCBOhkG5tz4QJ3vj55yNOOkDRJqIBQFuZmIxTQNtZOLeVEWodNaulC+Nbx6p/dL48NaadSu1MnhhyZKG3PD5gXanvhj8u3ffMbmqCK4bM9fNvbm75bHN5GbN1XuXys9HhlLO45lsvvzaqkVrzUh6uPx8UWbMrBiZKD9PJ9PmvrH1fcGLQQwegYWu84n8XVeMlNRsjYjUdO303aO1/1ekWE21GJkVUbIoRW3YIGAjgYV83kabsQkCvRJAnOyVYPDnWydOahGc33nqPea5z3wi+NH71APipE8gacZ6AtzMWD9FGFhHIDE3V16r0hEqNSVc0sGrt9yDm0pp4N7alSJWTrjCCz6PS4VNQMXEKREPr967bG7N3jK3ZyeNvjZbyDpHfa6v66aPb2fdx7qpCKnvsWFbvWiNGU6PlE1ZMrTULBle5jxfOuw+1vcsSi9yhM3FKniOTphVel5qxNy/ZKMNw8CGASBQf51Pzk1W1osUQVKFyfS9kzUk5sZ3VwrYlKIji8mKvw8ANoYYYwLc28R48jC9awKIk12jC+1E68RJrSD0T77059ZUDGpnJhAn26HEe/qBADcz/TCLjCF14bwZ/sXPzdD+X5qh//JLkz55vAZKcfGYyX7ggyb7nsdN6u//tsm/7/3mTjENOAh0ROC2CIi3RDxUkVHFRld0nDI3JXLxirw2m581b90+70QxajTjjenrzvv83lT408hGb9OIR4189DaNiNTISG/LpBLOw7l8sfyaRlZqhKW3eTZ7z4MSRT3B0rN5nYxlUWaxI2qOi9ipIqeOT8VMPS4VwXOJvMYGgU4IjA/lTOrWQZN792dmePIlM3Tjl0ajJau3/OhGM7viaZNd/qRz1OdsEIgrAe7n4zpz2N0LAcTJXuiFc6514mR1de5GCI783ffDIdNBL4iTHcDirbEmwM1MrKcP45sQSF657IqVv5Avpb/ZbzKHa9cOMyMjZlaEyrn3Pm5mn3jKES5VwGQbXAIqJL479Y4jODr71EXztgiNF+Xx23fOO69Vp1J3QqpWbGseYahtBpFe7dd1vp6BRnhqpKdurSJCq8XcTrh57/VSzDeMbzQqZirPtYvXOZGY+vi+xeudCE22wSWgwuPQ5H4zdFN+oLr5khm+td+Y/EwNkNzirSJCyvVe92VPSCVtli0YXI/pv5H7dZ3vPzKMqJ8JIE7aP7vWiZP2I5tvIeJkHGcNm7shwM1MN9Q4J24EtMjOkIiVw6+8ZEZlT+qalblK1VWTTpu5bTtM9smnXbHyt542haVEa8VtnpvZq1GNl6fedfZLpePluxfdx/fc16/eu9JyuMlE0iwbWW6WDi13jsv18bD7eNnICnl9mfOa81ii/Zz3yt+Xy55JDUWK0pbrfC4/Zyazk2Zy5obsN80teXzTeywip76ukanOa7Pyd31t2n2cL1bWy2wEc2JkpVmz+D6zduw+Oa5zH8uux+rHkU4EnftGIDkn1/Sb8gOUipGTr5ihWweMKVZd06WnwtK9Znr5U2ZW9uzSx01heI1v/dMQBGwjYMt13jYu2NPfBBAn7Z9f68TJZtW6X/juj82P/vpnVqZ7I07a7+hY6A8Bbmb84Ugr8SGgPp88d87M7v+NyUiBnSGnMvhBo9GW3lYcGXXXrNy91y20o/uuPfEZ5IBZquLjucnT5tyt05Wox1K0o0Y+ajr2QpumGztReLLfv+QBJxpvw7gcS695aygu1I6Nf4/7dX5WIuA0alNT5vX49p0LNVGub92+0Fb6vKaHe5GXXsSlzvGDSzebB5dtdlLL2ewkkLlzRKpnu2tFZm5LYTQ5VqdpF4ZWVorXjO01Q6vfawpjm82d6VrB0s7RYRUEeicQ9+t87wRoYRAJIE7aP+uxESdf/OnL5st/9heGtG77nQoL+5cANzP9O7eMrDGBRj6fuvSuI1RmDopQ6VQEf92k3rpQaSCRKImUKlY+VhYti0PRRsQNyhwXTdFcuH3OSbNWgeqCCI/OYzleuHVOIiAvtkShUYwaRbd2TCPqZF9Uiaqrjq7T6Mh+3Pr9Ol8sFmujYiUathwhK77hPdbU/Vbbalmn84GlD5r7JX1cU8bvH5fHIlQ7j5c8aFIJt+o5W8AEJEo2c8cVIMu7PE8U5soda0p2dSXtufG9kqa9ofz3fvf5gGeA5mNIAJ+P4aRhcs8EECd7Rhh4A7ERJ7/0J98xL+8/RORk4C5BBxBoToCbGbxj0Ai04/PJmzdFoCwJlaVq4OnTtZVdc9u2l4XKbCnKsji+ZNBw+jpejXA8K9GPGgGpkZDHbxx1HutrraIfNSLuIY1+k33eeoQS+TjoEXHt+LyvE2lpYypOqqDtrSuqoraK3Z36mEZZbl72cNnnWO+ytwlP5KfK0ZCuKCnX3juHaxrNjW4yc0slgl1EyLkl8gPRkr2mMLSqacf4fG9zwtnxI4DPx2/OsLh3AoiTvTMMugUrxEkvKnKhwX7t+c+aZz7y5EJvC/3vpHWHjpwOIyLAzUxE4Ok2MgLd+Hzinnx5lmhKTf92jodkP1L35fmhzSJWltLAd8uXaBEsCxMrIxunrR1fkrUeVSBydol6fEtSdCuPz5tCsdDQdI1q0wi2BySCjai2zma3G5/vrIf4v7tZdK5G7KqA2So614usdCIuJU38fo2+1GjLMSngM16J5os/JX9GkJyTH38cAVKup7fkWirH9NSJWjFyTH78GZfr6BLd95qsHIvp9n/8wef9mStaiQ8BfD4+c4Wl/hFAnPSPZVAtWSFOVg+u2ZqTQQHwo13EST8o0kYcCHAzE4dZwkY/Cfji81JMx12v8nWTll2P+ry6yE5+naQdeutV6lHWr8yvHxyhQqPUjt84Yo5df9OcnjzhHm8eN7o+ZLNtODViHlq2yV0D0Nn18SazdWLnwEc/9vIZ8MXnezGgD8711jU9dfOEOX/7jDklvuxEXE6eMbomZrNNoyq3rthptk3skGjLR5yjPh+kaMvUrCyb4QiRJUFS0rVT03XLZmhEpEZGjlUEyWJyuGvPwee7RseJMSWAz8d04jC7JwKIkz3hC+Vk68TJUEbtcyeIkz4DpTlrCXAzY+3UYFhABILyeY2kdCIqqyIsNeLS2zSKsixWOoV29prcpi0BjTK8ZlWoUYHm7OQpR6w54xzPOI8bRUEuHVnmRJTp2n4bnHX93GjIDc46fw8YLUzD5i+BoHzeXyvj2dp07p4TWalFerwoy7dK0ZZv3T1vbkq18Uabiu8qxD+0bIt5cIk+dnd9nJA1buO8pabPuWtFiiA5pBGSUsAmOVtVcCw54kRDOlGRjigpadpy9HPD5/2kSVtxIIDPx2GWsNFvAoiTfhP1vz3ESR+YIk76AJEmYkGAm5lYTBNG+kggLJ9PnzpRKrLjRlXqGpa6lqW3FcfG3cI6pfUqs1JoJ7d9h48j9bepRpGQGhnZrMiIioxblj/iREDuWLlbHm91nuuRLVwCYfl8uKOKR28q0mu0pUZa6hqqx68fcZ5Pzd1tOIA4Rlqmp47VVNHWqtrJuVvl8RUkHdtbJ9ITJHOSth3khs8HSZe2bSSAz9s4K9gUNAHEyaAJ996+leLkU888Z25M3mk4Oqp19z7ptACBbglwM9MtOc6LK4GofF6rf7vrVVaqgmuV8LJYmcm4kZWOYFmpCG6S4VaQdqIfb0pBmttuYRqNiNTISH2uVZHrt3VjGxwB8iFNwdbIL+exHCUqbDS9KK5u0ld2R+XzfQXRx8FoGrjzmSoVfzorxZ+8aGONwGy0bZTPl/MZcyIut5SiLN3Iy7CrzNdU0i6tG5koVFLbC0OrS5GRbkRkVtK186MP+Uhw4abw+YUZ8Y7+IoDP99d8Mpr2CCBOtscpyndZJ05+/Nkvm4kVS8z3vvnFKLmU+/6DL3zd/OrA0Rpb6gVSIietmCqMCIEANzMhQKYLqwjY4vPJK5edAjtDXlVwES5T58/VsJrbubtGqNRU8OKoP4LflXuXZA3IE7Ie5ClnTcgzN086KdlnJmurknsGaYEPbx1IJ/1UBUgnHXWTGUp1vzacVc7Rp8bY4vN9ite3YeXyc6Vq9Spcuj8IeOtanpfnDUXLJZvM5uUPO/umpaWjVBLXqvV+bInCbFUlbflxpVTAxpjKDxX50fvdFO2xSop2fmSdH9133QY+3zU6TowpAXw+phOH2T0RQJzsCV8oJ1snTtpWEEejOF968YXyZHzpT75jXt5/qOY1xMlQfJVOLCDAzYwFk4AJoRKw1ue1yM6xN83Qyz83w6+8ZIZ+8XOTvFVJjVRIhaVLTfa3njazTzxlsh94wszt2mNMOt2Sn6aPquioQqQKj5XHp8zdufkZDd5aeF5RGleIdCO2UolUqHNFZ/4QsNbn/Rle37eilcQ9kbJRtGX92q6LMotFqNxiNjmi5SNmk0RXajEePY4PLVzxOnPnDTN0Xa5DN+U6NLnfJLO1RawKGbkOLX9aIiLfZ7Ir9LjPmETr61DYk4TPh02c/qImgM9HPQP0HwUBxMkoqHfWJ+JkZ7zMoaNnzKc+/1Xzg299xezevsk5G3GyQ4i8PbYEuJmJ7dRheJcE4uLziZlpkznorVdZKrRz+I2aUec3PuikgmeddPBHzYnNy8ypxA1HhDytu0ZD3jppLt29OI/W6sVrzWaJtHKEixUqXIiQIbse2fqLQFx8vr+ohzMarwiVGwVd+szL8dJUg8/8ojVlkdITLrcsWmm2JW+71bS1iI3s6Xuna4yfG98p6dmVKtoaJVlM2V24Cp8Px//oxR4C+Lw9c4El4RFAnAyPdbc9WSdOalr37zz1HvPcZz7R7ZgCPe+F7/7Y/Oivf0bkZKCUadxWAtzM2Doz2BUUgTj7fOrCeTMsEZWTv/qP5tzZX5nT0xfM8QljTsh+fKV7LNQV+vWiqJwIKif1U8TIUjRVO1FUQc0D7YZHIM4+Hx6l/unpXm7K/WHCESs1YtpdrkFfaxQt/ciQMY9kjNkquz5+eHyN2bjmKbNizX9lssseN7nF8Stihc/3jz8zkvYI4PPtceJd/UUAcdL++bROnHzxpy+bb3z7hzXiny0YvajJrz3/WfPMR560xSzsgAAEIAABCDgEzk2eM69fet0cu3bMvPruq87x8JXDDemsnE6YXZeL5tFLIjRcM+a908vNtgf2mbG97zNmn6RePvaYMVu2QBYCEBgUAlPnjLlxwNlnrv3GHL4s++3r5uCsMYezxrw+mzDX8vMLXSmebSu3mV2rd5m9a/Y6R923rOD6MSiuwzghAAEIQAACvRKwTpzUNSdbbVFV6/aEyc99+mPzojpJ6+7VDTk/LgT4pTUuM4WdfhGw1effufOWG+V0y10f0k3RPGEaVe9dObqqsp6cri2nKdkSFfmICJIjh95wCu04lcGl2E5ycrKMrji+xE0B31uqCi6Pc1u3+4WWdiwlYKvPW4or1malp064KdpO4RpN05ZrwFzVNSAt1wAtXqO7VNLW4/G5VPm64xTGKl2DrtyrXWtSwawb21CzjqVGYetyEFowy6YNn7dpNrAlDAL4fBiU6cM2AkRO2jYj8+2xTpy0EZlGc375z/6iZp3JajsRJ22cNWwKggA3M0FQpU2bCdjg86duHjfHr79pjlw/JMcj5si1N8xbt883xKZf+reu2GG2Tew0e1Y9JsLAVrNFBIF0cuECFFr9O3PIFSqdquCyhmXy6pWKWDk84gqVzpqVIlTsfcwtssPWVwRs8Pm+AmrRYDJ3jjgCZPWakYn8VNnCwtCECJDyua5aMzK3aHNbIzgm16jTcq0K+jrVljEdvgmf7xAYb489AXw+9lPIALoggDjZBbSQT0GcXAB4O2nmiJMhey3dRUaAm5nI0NNxRATC9HktVuFEQN7QSEjd3ajIK/ck77puWz9+f7kojbMmpBSr0WhIPyOSUpfedSMqD4qYoUcRLlNvv1WxJJmsFSpLomUxI4vRscWWQJg+H1tIsTC8WC5ak7kln+G7bhGbRGGubH1+ZF0pIlIEyVKEZH5kg2+j0wjvSsEtjfR217Js9OOKRnhrlfDNK7TYVqnollYQl8dBb/h80IRp3zYC+LxtM4I9YRBAnAyDcm99WClOalGcU+fecUbmre+o6d7v37fdfO+bX+xtxB2c7aVyNzqlet1JxMkOoPLWWBPgZibW04fxXRAIwudvTF93xcdSOrZXfEJfKxQLNVZqERqnQrZ+aXcK1MiXdamWrY9HUqNdjKj7U5LXrzup355QqZGV6bN1lXp3SKXePSJ0qFC5R6Ir5VhctLj7TjkzdAJB+HzogxjADhOFGREfK1W03QjJN2pI5Bc96IqQY3slXVs+p0sfNYWh1aHSyuZnnaI77vWv8iOMPr49e2ueLe6PL25hLke0XO5eD1ct8s9ufD5UF6AzCwjg8xZMAiaETgBxMnTkHXdonTipwuTEiiWOCPnUM8+Z//lz/8gpPtOoSnbHow3oBMTJgMDSrHUEuJmxbkowKGACvfh8rpArrwWpX7yrv5BPztycZ/lDIkI6X8JVfFQxUkVJ+UK+etHagEfZXfOJO7cl/VvXqvTWrBSx8vjRmsZyWx6pESpVuCwsW9Zdh5wVCoFefD4UA+nEIZDIyedPIiEdQdJZL1I+f3frPn+L5fOnKdoiQrprRsrnL2Pn5+/qvStuZOUN2Z3rpRtlqY/rtyXDS12xshQxXh1pOZQa7thD8PmOkXFCzAng8zGfQMzvigDiZFfYQj3JOnFSIyR/8K2vmN3bN9WIk966j1EVxGk1K4iTofosnUVIgJuZCOHTdSQE2vX5S1MX3QI1GhHkRUXKF+vzt8/Os3tiZKUjQDqFaZziNJXIoGQiGck4/eg0MSuRW1VCpZMOfrgucmujRG7pepUSUZnVCEtZw7Kwyr8IKD/GMehttOvzg84p7PEnsxK5rNGQKkhqirYUsUnfq4tcHpfI5fFKivbckr2mmIp35HJNWrgjVrrFv65OV9bD9eZCl7UoR5iXiu/o9VUL87Ta8PmwvZn+oiaAz0c9A/QfBQHEySiod9andeKkRkv+mz/9o3niJJGTnU0s74ZAEAS4mQmCKm3aTKDe5+/NTTlfjt2oHk3N9qJ8Tpmpubs1Q0knM1KMRlKxHRGyKi1bviwvG1lu87D9sa0oa945kZWldStLxXYSc1Vr3q29z42s1OI6pTUr8xvu96d/WumKANf5rrD5flJqVtZ8VSFS14vUyEipqp2arlrzVX7I8FK055a6gqRW1jaJhYtf+W5syA3eyd52rr+n6iLSz9w8ZWbzMzXW6PIXKlg6PwI5PwZVrsdjmXHnvfh8yBNId5ETwOcjnwIMiIAA4mQE0Dvs0jpx8kt/8h3z8v5D5qUXXyhHTm7euM586vNfNR/73SfMn/7xH3Y4xODfTuRk8IzpwQ4C3MzYMQ9YEQ4BXf/swt1j5tCVg+bg5cPmjSsHzCn5QlwvQqo1izNjTlXsPav3lapl7zA7V+41mn7IViGQvHLZDP/i52boFy+Zod/snxdZadJpk310n8n+1tMm+/4Pyv6EKSyFYZg+xHU+TNqVvhL5u2boxi/N8KR8Nm6+IqLkASleUyu05RZvNbMrnjJZ3Zc+bvKjG6Mx1tJe9Zp9SiqGH5RrtUaw6/G4VBFvdM0eTo2YbRNynV61R67bu8zuNXvNpvFdXLMtnVvM8pcA13l/edJaPAggTto/T9aJk4rMS+Guxve5T3/MPPeZT1hJFHHSymnBqAAIcDMTAFSatIKAVso+Jl9i37z2hjlS2htVlFVjtyzfarbKl9ptK3aYHSv3OF9wH1y62YpxxM2I9OmTpcjKUoSlFNxJTk6Wh6HFdOZ27zFzu3SXdPDSYxUx2YIhwHU+GK41rWpU8d03SutF6lF2KV6j60h6WzG9xGS99SK1iI2sGZkb2x6Ccf3XhV7L9bp+/PoRc+T6IYm6PO5c7xtt942tlx+W9ohoudfsnNjtXOv1ms8GgX4iwHW+n2aTsbRLAHGyXVLRvc9KcTI6HN31jDjZHTfOih8BbmbiN2dYXEtAU/70S6lGQR6/8aYrRF59o2FkjUY97l39qBNR89D4NifCRqMjNUqSLRgCiSmJHvsvEj32ikSP/Uqix16T6DFZy7J6K6xeY2Y/8ITJPi6RlXJU4RKx0r/54DrvH8uK0pgTMfJNM3RdooZv/doMTb5iUjPv1OqVyRFJzd4jUZESNbxMfHuZRA1niBoOYDacJr3/BSpYnrx1xBy9esS8euk3DSuG6zVfRcq9EhmvS3ToUZ/zvyCo2aHdoAlwnQ+aMO3bSABx0sZZqbXJOnHyD77wdfOrA0dNfeEbLZTz/n3bnSretm2Ik7bNCPYERYCbmaDI0q7fBArFgpPep2nYetR1Ip2jPNf1yqq30fQipzCNRseo+Oge3ccrxhY5b70znfPbRNprg0Dy2lWT0bUqpbBO5pDsckyfOFZzZn79BjeyUgvtOMc9Jr/xoTZa5y2NCHCd790vUtMXnEhIt5K2GxWZmj5f03Bu0cOOGDk3rrtERcrj/PDa3junhY4JeD5/c2rG+Z+hkZWaFu79/2i0nIcKk/X/N1S41P8b6VSmYxs4AQJhEuA6HyZt+rKFAOKkLTPR3A7rxEktiPPJj35oXgo3BXHsdyYs7H8C3Mz0/xzHcYQ3p2+UBMjaL5Nnb52aN5zVi9bWiZCuGLl+vHERFnzeLo9IZGcrIqWKlkcOOc8TM9NlQ4vjS8oiZbVoaRIJuwZjqTX4fOcTk7lz2ClYk3YESRUjD5rkXNXyBMkhR4TMje0WQVJEdBUkRYwsptwfP9iiJbCQz797953yj13VoqW+Xr9tXLLJbFmhBdC8H7rc48TIymgHSe8QqCKwkM8DCwL9SABx0v5ZtU6c1AjJrz3/WfPMR56soeetQ1kfUWkDYiInbZgFbAiDADczYVCmj1YENOpRCxwck5RsTcfTFG09Xp+5VnNaUirZelEs1RGR+oVxfGhJ25Dx+bZRRfbG9KkTZcEyc1gESxErtfBO9Ta3U0ShUmRlzlm3ci+FdprMGD7f2pUTuTul9SLdiEgvOtJItLa3FTIra0RIV5hkvcjILhILdNyNz2uRnfmR+W60fq5QG2m/fHSF2bZ8p7tW8YQcZb1iPVIwzVaP6H+7uvH5/qfCCPudAOKk/TNsnThJ5KT9ToOFg0uAm5nBnfsoRp7Lzzki5LEbR1xBUkRIXSfynTtv1ZizdHhZTSq2J0ZuklTtXjd8vleC4Z+vwqSbAl5JB1cBs3rLP7CxVGSnkg6ev/+B8I21sEd8vnZSdG3IahFSoyPT987UvCm3aLMTCZkrpWirGJkfWWfh7GJSIwJ++rwWV3NSw5208MrSIjemr9d0rYV3tJja1hU73aOIlXocSg4zSRAInICfPh+4sXQAAZ8IIE76BDLAZqwTJzV9+9t/+RPzg299xezevskZ+qGjZ8ynPv9VY2vFbiInA/RQmraKADczVk1H3xmjX+TqoyL1C171putDetEnWi3brZq906xeHMxabfh8/N1MU7699Sp1/cq0lwouKeLeVli2rFwNPOdVBt+5K/6D72IEg+7z6btHnbRsr4K2k6KdrRKWkunSOpHeepFeijaFsrpwNytOCdrnr01frYn0P3ZTI/7fNHezd2rG/9CyLRXBsvT/7ZEVRNxa4SR9ZkTQPt9nuBhOnxBAnLR/Iq0TJxWZl8Jdja9RqrcteBEnbZkJ7AiaADczQRMenPbfvnPBiYJ0oiGroiLr0+E0kmTbxK5yGpyKkRuXhFfsBJ/vT5/UojrVRXZUtNTiO+UtmZxXZEfXryzNgQl4AAAgAElEQVSOjfcnkKpRDZLPJwr3KiJkqXiNRkYmCnMV4XpohVOwxlsn0ileM7aj7/1gkAYYhc+/dft8w/+B+WK+jD5hEuUf4Mop4SH/DxwkPxiksUbh84PEl7HaSQBx0s55qbbKSnHSfmy1FiJOxm3GsLdbAtzMdEtusM+bFzXirBcpUSNztVEjWkigOr3NS3eLkh4+HyX98PpOXXrXrQReVRk8faa2oFLuwU3GXa+ylAou61hqpfB+2/rZ51MzMs93ZZ69KtpSvCZ9r3ae86MPVapol4rX5Ef6b577zW97GY8tPn/y5rF52QNnJk/WDG1e9kBp/cqgsgd64cq59hKwxeftJYRl/UgAcdL+WUWc9GGOECd9gEgTsSDAzUwspilyI4/fOGrevPaG7IfMm9flePWQuXKvtkDJmsX3uYUBnLTsynpbI6nRyO2vNgCft2o6QjMmcW+qqsiOrl8pIpbsibmqiLqJCTcV3Cm24xbZyW2Pf0RdP/l8+q5EyJYraLvFa5JzVRGyUjjLjYiUeXQqabup2sV0+0WzQnNKOgqMgK0+P5fPuusuXzvsFoGT9Ze1CFx9lfCJ0ZVmx8o9ZsfEbrNj1W6zc2KP2b5yMJelCMxJ+qxhW32+zzAzHMsIIE5aNiENzLFSnNSiODcmayNqPNup1m2/U2Fh/xLgZqZ/57aXkR0RIXL/xVfMa5d/bfa/+4rRdLXqLS1rtGl10r1r9pk9q/aZfWsfd57r67Zv+LztMxSefVpoZ+g3+83wKy+ZjByHXj9gTK62Km/uoc0m+4EnzNx73mey733cibKM2xZnn0/fedMMTcrc3Pqlc0xPHa/Fn5D1IiUlOzvxtMkulTla9oQUrlkftynCXp8JxM3n9X/uwcsHzBtXD5gDl/Y76eH1S6Lcv2Sj2bfmcfPYmveZx9c9YXaKeBmH/7k+Ty3NNSEQN59nIiHgBwHEST8oBtuGdeLkx5/9splYscR875tfDHbkPrZO5KSPMGnKagLczFg9PaEYd/72GXNEIiHfvC77VYmKlGO9GKlrQu5cVYrikC9E+njDeDwrIePzobhVLDtJXZQqzhJNqetVuinhsp+rreKsFcDntu80OY2u3LFTHu8yuW12F7iIi8+r8Ji5c8Sk7xyWVG3Z5XFq+myNL+VHpSq7U0G7FB2pVbRH43ktiuWHJCZGx8Xnm+HUSEoVLDVj4YhkLByR/81nb9UuV7BufIMbWan/k1fqcbfZtOzhmMwQZvpNIO4+7zcP2hsMAoiT9s+zdeLkzt9+1thc/KbRlCJO2u/oWOgPAW5m/OEYl1ayhVlz5Ip82VEh0kvTli8+U3N3y0NIJzNml6aTSSrZDkkl0+gM/dIzNtQfhUPw+bh4qx12qkip0ZVDv/qlE12ZPnt6nmH5Bzaa7KP7TPbxD5o5Oc49ts8Uh0fsGIBYYaPPJwozIkJKVOTNVyQq8teSnn1A1oqczza3aLOkZgvb5R+UXSJYRYxkg8BCBGz0+YVsbvX36dw9Z1kVFSkd0VL+h+vj2fxM+TRdQsX9vy1p4KX/2/pDoq5pydb/BPrN5/t/xhihHwQQJ/2gGGwbiJM+8EWc9AEiTcSCADczsZimro28NHXR/UJTJUSeulmbFrl60RpHfNy5cm/5i80jK+yOBOsaiKVCTS/j4dxwCaRPnzTpN4+YzFHZjxxyHtcLlgVdu1IjKnfucqMsd8hRHkclWEZ9nU8UsiZ9V3hJRGS6FBGpj5PZKzWTl1/0oKRoC6txYbdYolKX6HFruBNMb31BIGqfDwPi6Zsnyv/fvf/x+j+/ento2Rb3/7uzdqWb/bB+/P4wzKOPkAkMgs+HjJTuYkAAcdL+SbJOnNS07t956j3muc98wn56JQsRJ2MzVRjaIwFuZnoEaNnpTsEaTQNzUrTd4jU3pq/XWKnCoxdV4URGrt5jVo2utmwkwZmDzwfHdhBbTsxMi0gpopsjWMpRHusxeeNGDY7cpi0iUorgpkKl7PpYXwtjC9vnNRVbU7Krxcj6tSILmaUiPAoLFSBFjJwriZHF1FgYSOijzwmE7fM24NT/9UeuHSwt0XLIHJbHx64fqTFt6fCyShp4SbDU+4GkFJJiizeBQfT5eM8Y1vtBAHHSD4rBtmGdOPniT1823/j2D81LL74Q7Mh9bB1x0keYNGU1AW5mrJ6elsbdnLlRTs3WNanctaneqDlnLDPuCpFeirZETmgERTqVie/Ae7Qcn+8RIKcvSCAxO2Myrx0wQ6/uN5lXf+2khet6lvVb7uGtThp4VovtSNGd3MOPBBJdGajPF3OyPqRbtCYj6dlDt1910rXrt8LQGilW87iTnu2kaS+V1HeEyAV9iTd0RyBQn+/OpNDPKhQLbvr3FVewdNauFMHy9uytGlu2rdzpVAPXCEt332NWjq4K3V467I0APt8bP86OJwHESfvnzTpxUtecbLVRrdt+p8LC/iXAzUx85tZL4fLWmtKjLppfvWk1T2e9qVWSol36oqHFbNgqBPB5vCEKAumjbzoRlRlNA5d0cE0LT739Vo0phYmVJrd1u5nbus05aqGdOTkWVvUW2eyXzyez16Vatozj7jFJzz4q+zFHmJyXnj28TqIhJUp0XIoGjUmEqEZGym5MIgr09DmABPzy+X5D9/adC6W1KyuC5flbtUW/Vi9aK/cQ7prT3hqW/bzUS7/MMT7fLzPJODohgDjZCa1o3mudOBkNht56JXKyN36cHR8C3MzYOVf3clOltGx30ftGi9+nEil3LSkVIp30rN1SyGavGR9aYuegLLEKn7dkIjDDqQiuUZWZgwecSMvMMYk4zOVqyaTTZm7bDqfIztzOPSb73sdNbvuOjiIsu/H5csGaW1IESCMjb0nBGjnq6/VbbnyHyS55j0REPuYWrRnbITpkmhmGQGQEuvH5yIyNsGMthufdYzjZF1pwR374nMtny1ZlUkPlauDVgiX3GhFOXIOu8Xm75gNrwiGAOBkO5156QZzshV7pXMRJHyDSRCwIcDNjxzS9fVuiGaoqaGv61blbtZVrJ0ZW1kREagGbbRMiArB1RACf7wgXbw6RQOrSuyZ9XCISj0tkohwzejxxdN76lYVlyySqcofJPbLNiazMaaSlPM+vva+htQv5fHL2sslMuZGQGhGZ0ahIea6RktVbISP9jkl/i6Xf0lGf50fWh0iJriCwMIGFfH7hFgb3HSdvHnOL6JXWrVbB8sq9yzVAHljyYDkF3PtxlCyNaH0Gn4+WP71HQwBxMhrunfRqpTip605++c/+omYcX3v+s+aZjzzZydhCey/iZGio6ShiAtzMRDMBb90+b/a/+4p57fKvzf6Lr5jjN940uUJtxNSK0Qnz+H1PmMfWvM857l2zzwynRqIxuI96xef7aDIHYCjJq1dEpKwIlipc6vPktau1wuFSKTDjCZWPSDq4pITr8/y69aba51MzIoBWC5FTKkhKavbczTohcoUIkRKxOSbCpwqRelws7Q2vHQDqDDHuBLjO+zeDs/kZJ6JS71l+/e4vzYFL++eJldqbrm+9b+3jZp/es6x7wjy4dLN/RtDSggTw+QUR8YY+JIA4af+kWidOvvDdH5tv/+VPzA++9RWze/smh+Cho2fMpz7/VfO5T3/MyireiJP2OzoW+kOAmxl/OLZqZXLmpltBU6IhDztFaw6ao9cO15yyKL3YSct2q2i7RWu0ivZQcjh4AwesB3x+wCa8H4crqd+aAu6kgh9xU8N1TUstxFN7YTEm//RGYx6bMGZTxhTHrpp04YK8pfaHkGJyxBEitWBNbvEjUqxGjpKqra+zQSCOBLjOBzdr+kOqE1np7JWlZ+5kb9d0unXFdrmnkWVn9N5G1q/UJWgmRlcGZ9iAt4zPD7gDDOjwESftn3jrxMmnnnnOfPKjH5onQqpo+aO//pmVVbwRJ+13dCz0hwA3M/5wrG5FK2G+KpEFv770Sycq8o0rB4yu61S9Lc6MmT2r9znRBU6UgURGLhle6r8xtDiPAD6PU/QbgeTcpMlcftUMnXvZZK6+btL3TplU6pJJLJkyJlU32kljijcXm0J2tckNbTZzK2QdyweeNNmH32cKEyJiskGgDwhwnQ93EvUeZ//FX0o2yH6JsHSjK+vvezTzQyMr3yP7++77IPc9Pk8RPu8zUJqLBQHESfunyTpxUqt1N0rh9lK9qdZtv1NhYf8S4Gamt7ktFAtOBMGRq6XKl7qYvDyvjyAoR0Q6BWwkOlKiCJaNLO+tc87uigA+3xU2TrKEgK4DmdHiNFPHZW1Iqfp9+6A8PtGwUE1haMLkkptNcmqZMecTpvDGLZP+zydN8krtWpLO0EqFd3Lbpcr2rt0m9/BWk310nymsXmPJyDEDAu0T4DrfPqsg3qn3QO69kVvQzyu2ky/my91pxojeD1Xuj/ZIUb89Jp3KBGFS37eJz/f9FDPABgQQJ+13C+vESSIn7XcaLBxcAtzMdDb37aRoq+jopDKpEOmkZ7vVtNnsIIDP2zEPWNGaQDJ7zREd3f2kREPK7hxPSOhjsebkwpCsDynp2LlFD7u7Pl7sHk0iVbPmpKNDnpI2T0lb1ceTJ0zy+rV5RuU2bTG5LdLWFmnzYdlLjwurVjOFELCWANd5+6bm2PU3y0vcqGB55MpBc32m9prjpYK7P+Lqj7mkgrc7k/h8u6R4Xz8RQJy0fzatEydZc9J+p8HCwSXAzUzruT9/+2z5l3+NjtRIgHfuvFVz0kPLtlSESLmRVlFy3diGwXUqy0eOz1s+QYNmnkQSlQVIFSIdEdIVJeuL1IjSWCM8OgLkIhUiHzEaJdlsa8fnkzdvlsTK+cKlyVeinbSPghbfUbHS2UvCpTzOy+NihqinQXNhG8fbjs/baPcg2XR56l25pxKRsrQmt65feerm8RoEaxevcyIrVaR0fuwV0VLvudjmE8Dn8YpBJIA4af+sWydOKjKqddvvOFg4mAS4mamdd/1lX9dKeu3KfnPw8gFHjKzftizf6qyb9L61H3SO2yZ2DKbzxHTU+HxMJ64PzE5mL9cKkXdLYuS90/NGVxhaVSdElqIhJTKy060Xn0+fPe1GWUpkZXWkZfLK5Xlm5Dc+JNGVFbHSES43P2zy963r1GTeD4GeCPTi8z11zMk9EVBxUu/BdM1uPeo9Wf2m91x677Vn1T7nqOIlm5kXIQ8TCAwCAcRJ+2fZSnHSRmxexfDqKuKenRTEsXHGsCkIAoN8A3/yxjG58T1ijt6QXX6xPybHC7fO1WBes/g+ufHd7VbQdipp7zYqTrLFl8Ag+3x8Zy1elicKWTcF24mEdNOyU140ZK62oq1JpMsp2OXUbCctW6IhM7JWpA+b3z6fvH3bESpTmhZ++lQl4vLkSZPIztZYXBwbF4FSU8OroixL6eHFkVEfRkcTEJhPwG+fh3E0BM7eOmXevHrIHPaqg0s6+MU7b9cYs378frNtxU7n/mzbyp1mu0RYanr4oG34/KDNOONVAoiT9vuBdeLkH3zh6+ZXB46a+sI3Wijn/fu2m+9984uhU9V1MG9M3nH6RZwMHT8dWkRgUG5mrt67IkLkYREhZS+JkXrM5efKs5FJDckaR7skEnKX3NzKLje5+njl6CqLZgxTeiUwKD7fKyfOb49AavZiXVp2SYy8d25eA/nhtaU0bIkmVAFyzFsnclN7nXX5rrB8PnXhfNValpX08NTFd+az2HB/XVq4G3GZl9fZINArgbB8vlc7Ob8zAjenb8gPyYelwM7hylF+ZJ7JTZcbSiaS7j2ccz8nYqWIltvlqD829/OGz/fz7DK2ZgQQJ+33DevESVsL4hA5ab8zY2HwBPrxZiZXmHNvXFWMdIRI97EKlNXbxiUP1dy4bl+5y2xeJgUk2PqaQD/6fF9PmCWDS+TvlQvSpDUd24uMnD5lErm7NVYWkyNuNKQjPuoukYOlIjXF9JLQRxSlzyfuTdUW36lKD09M36vlJpGUTiq4E1lZvZ6lrGW5eCx0bnQYXwJR+nx8qcXT8nO3Tlfu+fS+T8TKs5OnagazYnRCoit3SXRlrWA5nBqJ56AbWI3P981UMpAOCCBOdgArordaJ05qhOTXnv+seeYjT9Yg8dahrI+oDItbK3Hy8s2ZsMygHwhESmBsJO30f3cmF6kdvXSuqdhH5YZUBUnvWL+o+tLhpaVfz/XXdEn/WeX+kr44wxfeXtjH8dx+8Pk4co+Lzcm5SZOSNSBT987U7Omp0yY5++68YeRHNvz/7Z1bjCRXmedPZlZXVV+qurvafbH73u27McwaFnYskFjtasQ+LFg87PCC5IXRLjz4hXlgZi2xElrPwMPw4gfQCFhLSCtmHpBhHnY0L4OENQKL8WKM7+12uy/ue/Wturu6ujJzv/+JPFlRWZmVt8iMiMxfSKm45IlzTvzOV1kR//i+89W9IMu1DNnyiixvPJCZS86izZfOnI7Cwk2sLNXmtNR+6dTJNdwqu3a78uEjbvnIUVc+dMRv+49tV3a0TgSUmQGgI0MnkEWbHzqEMW1QXpQSKJVgp762+8Mri/OriBxRMkN5V5pgqZBw3RMe3nY0t9Sw+dwOHR3vg8Du7aPzgqEPDJk+NXPiZB49J8uVaqYHmc5BICkChUJUUzUnJr+wtOBePfc799uzv3WvnH3F/e7879zrF/6wBseeLXvcp/b+O/fk/ifdJ+77hPv4vZ9wWyYRIpOymzzXkzebzzPrTPfdvB0L195y7qZ5Pl61xFdhW+tqi5c1sw+76ox9tn/MOftUZz9iWQiynzk2VzZ/4oQrvPo75/7wB1v/3hVet9/3t2xMWi0P23g89LBzfm2e7499xFVt223h9z7Tf38D7lyubH7ALKjeWdj3ovvXD3/rfn3m1+7lMy+739j69PXVc1eK08P3POzvF5+49wn3CVt/bM8f5ebeEZvH0seRQKlYe5Adx4vPyTVnTpx8/kc/cz/4yS9Wze0YvBa/9uXPu2e++sVU0BLWnQp2Gs0YgSyHgZxdOOPevvyme/fKm+4d+2j7nfk33Y2l1QklNI+QD9WxkB3NLySvSE2OrnmHWCDQSCDLNs9oJU9g4rZ5QN487iZuv+89IifMI1Kf0q33XaGyMk9ZaLkyOeeWN5pXnn2WN5un3kbLQL3pqH3MS29qd/IdHEKNebf54qWLbuJ9GzNlDj/x/sq2HStevrSGYHVyKvK0PHS4trbtwzaWh20szdvSFfnfMASzS7WJvNt8qvDGpHFlAn/TEuwoMaK8LLX+cGG1YKnomgd3POIe3G6fuYft86hf75vJjmd8GC5sfkwMl8tcRYCw7uwbRObESSELIdxxfM1CvYeJF3FymLRpK6sEsnIzc/Pugnv94u/dqxdeca9d/H/u9Uuv2o3iG2uwTRQnLAvjo+5ju5+wcJyPuk/e96Tf13EWCHRCICs230lfKdMZgUL5thcbJURGwqPEyCBKHm9aSXnqXlc2wVGiY1hLhJQomVSW7M56P/hSo2rzyhpeOmFjfdzC8LWWcFnbbpaER6TLBw95gXK5FhqubYWHL5twWd20efCDQQtDITCqNj8UeGPayHJl2b09/4Z79fwr7o3Lv3evnHvZ34feKa+d6uvhHY+6x+75mHt857+xl+J2T7rr427Wpg9Kc8Hm06RP22kRQJxMi3zn7WZSnOy8+8MriTg5PNa0lF0CadzMnL5+0jwh3/IekcEb8l3bX1i6sQqUJjB/aLu9pdZb67lHTIR8xD1gH7JnZ9ee8tCzNGw+D1zy0Ec/H6QXIM2DzrwhS+YN6cVICZGLHzYXITcejDwfzQOybJ6Q3ivSe0KaGFXalIfL7ruP42bzhTuL5mUpD0uzE3lcSrj0npcSMFuI1bv31L0sy+Zx6cVLL1oedZW5ub7HgAqGS2DcbH64dMenNc1TKcHy3fm3/NpH81gEz8XbqxMsbpzYtMqzUves+hyYPTQ0WNj80FDTUIYIIE5maDBadAVxsoMx0jyY81dXhJC5bTPuVy8+Xz/zw8trQ706qJYiEMgdgUHfzFy/c82HynTrEfnEnk/6t9GjlEkxd8Yxoh0etM2PKLahXlbJEs94ETIIkJaMxntCmhBZvHtlbV8KE94DcsUL0jwga/sSI12hNNT+Z60xbL42Ija5ssTJ0vFIpJR4GQmWFvJv24WlpTVDV9m6tSZSBrGy5nUpj8v79mZtqOlPjQA2jykMikA3HpaHth51j+38qHti9781T8uPDtTDEpsf1IhTb5YJIE5meXSiviFOJjBGiJMJQKSKXBBI6mbmwq3z7v1rx9z7V46541dtbdvH9Zk/5pYqd1ax2D4950OxH7B5e7R+yDwjH7D5fHZu2pULZnQy3wSSsvl8U8hG71dCsDUfZBSSLa/IVvNBVkubvcej93xsmBMyS9mxs0F3pRfYfPsRUfbwSKyMPC6Dt6U8LgsLq736VVt8XsuQRdyHiDOvZXvYQyiBzQ8BMk3UCczfvuzevlLzsLRQ8LfNu1IelpduX1xFaaK4wSlLuD6Ht9pH29vtY9uaP72fBZvvhx7n5pUA4mT2Rw5xMoExQpxMACJV5IJAtzczemN87Mo77r0rb/sQl9cv/d7vH7P9ZkvjHJF4RObCLEa6k93a/EjDGMbFWeZrH4at8Gt5QN56x21YeMO8It92xaXLzXsgT8gtD7q7mx/yQuTdmcctOc1D9nnQVYvTw+j1SLWBzfc+nAoRn3j3Hfu8Ha3fesNtqG275eZZ3eVtufzAQ+7uRz7qlu9/0JUP2NQCSshz5IirTmG/vY9G52di852zouRgCDTzsNQ9s443W+7f/pC7f/uD9nnIkjw+bi/vH/P7nc6pjs0PZhypNdsEECezPT7qHeJkAmOEOJkARKrIBYFWNzO37t4078f33PEr70ZekFdt+2q0rTfEjYsyGh628JUj2x+I3gRre1u0LU9JFghkhQA38MmPRHHpks35eNKExw9sbZ/bJ+2jbTtm24XltZ5n6kV5yub58+HXtazYsTkhRy0pTfLUO68Rm++cVaclfTKeMKdlQxbx0tnm858q4U75wAG3vO+AFyzL+22939YSL227spPogU75tyuHzbcjxPdpELi2eHUlskhRRhZtFN1jH3M3lq6v6dK26e3ew7LubVnzuJS35ZYNM6vKY/NpjChtpk0AcTLtEWjfPuJke0ZtSyBOtkVEgREhMD1Zde/ZTdEfzr8diY8Ky5Yoadvnb55dc5UbSpNeePQCpMRHH5Zy1B01UXLXpj0jQoXLGGUC3MD3NrqFiiUZsTkgJ27L+1Gh17UwbPOALC2eWbfS8vTeyPMxZMa27btbHrXM2Ad76wxndUUAm+8KV9+FSyc/WPG2PGbelprX0rwtW2UQDw1qDkt5XPpkPBIuzdtSIePar27e0ne/xqkCbH6cRjv/16oEO9G0SHICeM+9b/fl72nbHAOaZQvftWl3JFp6hwC7J7ftx/c87I7avfnS3fGeYzn/1sAVdEMAcbIbWumURZxMgDviZAIQqSJTBOTtePL6++4Dfa6trE/deN+dvn6qaV8lQHpvyCBE1m6A9s8iKGRqcOlMVwR4aG2Nq3TnnPd29F6P3gtSno/BE9I8ICvNk8VVJ2ZNeDQxZco+G+2zybzBbHtZ2/apTO7saowonCwBbD5Znr3WVrx82ZVO29/XKfu7MgEzbGu/dOoDV7x2rWnVfn7Luqel/V1JuPT7Ne/Le+/rtUsjex42P7JDO1YX9uHC6VoEkzkNyMNS0UwmWMrbslKtrGGxd2av2z9z2B3YetgdtEzhB7cesXW0f89G/g+PlfGMycUiTmZ/oBEnExgjxMkEIFLF0AloHpsT9sb1xLXj/ublzMJJv9Z+qzkh1cmtU9vM8/FBn0nw6LYHfZbsx+75mJvbuGPo10CDEBg0gXF/aC0tflgPuZYIqbBrL0jWxMhCQwKrMB6VyTlXnjZRxD7LEh+17cXHaJsw7EFbbu/1j7vN905ueGf6MPGaSBmtTcA0wTJsFy9fai5cbtjgyiFM3ELGtb0cDxnfu294F5GhlrD5DA0GXUmcgE/AM/+6e8uS77x39R336oVXbC74d9y1O1dbtqXM4Ye3HXFaH5w94j0u980c9MemSsyFm/ggUeFQCCBODgVzX40gTvaFLzoZcTIBiFQxEAK6ITl14wMvQp66/oF5Qh639UkvPp5daB1aqRuPcFOiG5ND9jZVmbI/sudByxC4x9243XyC7oFcBJVCIEUC4/DQWlo8vTLnY010jM8DWajcbToClcldkbdjzfMxeEEue4/I/a46sXqOqxSHkaa7IDAONt8FjtwVLdy6WRMpT60SLOVt6cXL8+eaX1OptCJWSrDct78+v2XwuswdjA47jM13CIpiI0NANn/+5jn3h3NKUvmOfz5QiLgSWL5/9XjT8PBw8fdu2etFSz0n7NtywB0y4XK/CZf7LFJKIeQsEMgqAcTJrI7MSr8QJxMYI8TJBCBSRU8ENLeMREd5O66Ijx/Uj928u9CyXmX0C8Kj3ojqzaj25QmpG49mCzfwPQ0TJ+WYwKjYvBcbLfmM93yMCZA+DNs8IV213HSUNP+jFx3XeEGacGFekGTDzrFxt+j6qNj86I1M/1dUWFryIeGRh+Upvz1R87z0x8+cbt5IoeDntVyuJeSJkvNEn3DMWZm8Lth8XkeOfvdKoJ3Ny4FBjgx6vggRVdH2ey0ziKsvSni5f9YES3ue0LROe028DF6XOq7vWSCQFgHEybTId94u4mTnrFqWRJxMACJVtCQg0fG0eT96EdLmgDxta+8NaSHYF26dX5dcuEmIQjGO1m8S5AmpGwcJlN0s7W5muqmLshDIA4G82Hzx7rUo87Ulm/FzQHox0rYlSFpCmuLS5Za4K5M7THy0DMCWBXtZGbA3PWDekFoftfkfma4hD3aaZB/zYvNJXjN1RQQ0z+WEZRP3mcWVqOfYu7Us41niJjkAACAASURBVPYbYt+1Wipbt0YJecLcljavpZ/nUp9797rKjmz/jmDz/AWMG4F+bF4CpbwrJV5qSig9nwRHifWcIsRYnpXysJSnpTwu5XkZFzPHbRy43uESQJwcLu9eWkOc7IVawzmIkwlAHNMqrt+55j60t5MSH/WW8vSNk34t8dGv7R/+eovERQmPejupf+6DDq/o52ZmTIeYy845gSzYfGH5hivdsbkfNf+jrYu19er9sy1JV4s2z5xCrRV+7b0g91s4dtiO5oJkgUAgkAWbZzSyR0Beld7j0pL0+AQ9ftu8L2vbhaU7rcXLXbtNpDTBsvapxLaVdVzHqzOzqV00Np8aehpOicCgbL5xOik910QOFpGI2SybeByBIrf0THPv5mi9Z/N90b6O2/PO7NTWlIjR7CgQQJzM/igiTiYwRoiTCUAcwSr0D1gCYxAZvfB4M9rXR6KkxMn1Fs39WP+nXBMfwxvHcHyY6AZ1MzPMa6AtCHRDYBg2XygvRF6Ot+yh3zwdiyZAKty6aMei7Nfrv6TQ9VQmd9cSz9iDvnlBRiKkQrLlEXnEVUuEUnUz7uNcdhg2P858R/HaCzcXzOPyuCt9aL9jQbjUtsLGbb94Yf0oDzHxXpYSKhU67tf2G2brKGz8gKtuHtxvGDY/ilbJNa1HIC2bV8RXiACLIsO6Ey8lTt5nQqXESv8xEXPfzIGVfTtG6Di234oA4mT2bQNxMoExQpxMAGLOqlCm68jT8YPI89H+wZ69+WFdeJQIqbeH7ZYgPnqvR00mbf9gvRdkRieWTutmph1HvofAoAj0a/OFymJrb0cfdh15Q7aa89ELjxNbXWWjPaxPmefRlATHaLuifW1P2jbh14MygbGrt1+bHztgXHBbAsUrV7xwWTxrv3f+Y799/mOe4BIxtbYyLZdisbnXpXlcxr0wqxs3te1LswLYfE/YOCnHBLJq8/2KlxqSIGDquSoSMO+LPC9rHpjaJuN4jo23j64jTvYBb0inIk4mABpxMgGIGapC86VctDd7weNR/yjPxYVHEyPbzfWoy1HItf4B6p9jeMun8IT62z77Lm9Z7bJ6M5Mh86ErI0agnc0Xl+YbxEd70PYh2PYgrrXCsK3Mekt5ao+ryMtRYuO0Pg3iox2vljaPGFkuJ6sE2tl8VvtNv/JLoLB4O/K6lEgp8bK2HRcvtb3eUtm+3QuYkVgZhYqv7Ne2d9zTtApsPr+2Q897I5BXm9fzV4hA0zo8n8WnyJIDSbtlbuMO7wgSnsn0fKZnMgmYO229a9MeQsjbQczh94iT2R80xMkExghxMgGIQ6hCYdYXblo4gXk76p+bti/dvuC3FVqgf3ISJdtN5qyu6o1b+Iemf2T6h5Z34bGTIcjrzUwn10YZCDQjMFu45Ap3zrs7Nvl7lGwmynqt7QnLel1cah+uuF7ItUKwKxuYQwnryw4BfuezMxb0ZIVA8Zol/VJG8T5Cxyua+1Kh4hZCXtF6n4WO2/b04QOusnevuz7bXLxkHCAwagRG+Xe+UcC8aM96weGkm2c9hYdLqNTznpxMtO1FzM0SLy2xj4mb2sYLMz9/HYiT2R8rxMkExghxMgGIfVQR93TUmzMJjFcW5+uio/Yv3DrXdn7H0AW9TdM/ncb5THbaW7TwD2pcJ2Qe5ZuZPkyQU3NGQJmti3cvmGejfZYumnejre9etDkez7uS1kv6ztYqc/f6ulcnYdGHV8vbse79aNlpgxekhWETcp0zAxnz7vI7P+YGkNPLL86bF3vwvKyFjPvQ8Vg4+bqh43bd1S0zrrxzl6vs3GmfXa58j61N0KxorX0d99t2bNu2nJKi2xBwbtx/50NC0ov2fFhPSFrLCyDnlU6n55It6ZlwbvqeVSLmzk27vJgZIuf0/bg+O2bp7w1xMkuj0bwviJMJjBHiZAIQm1Qhb8b5xctebJy/fclPmqy3YTqm+Ry9B6T9A2mX+S1e9Yq7fiQ+xt34gxjJG7DW4znuNzODsXRqTYqATyxjXo4+pNo8GiOxUUJjdKy0dM5vF5fazwcb+lTdsM1VbV7HJWW79gJkLeu1n/vREjXYMRYIjBIBfudHaTS5ljgB73VZS9TjE/cohNzWk5aBvHD+vCtcvtQxsMqOHa4yd48ryxtTnpgSMefm/L68MuWhqe8rW/GM7xgqBYdGgN/59qjjiU3l/BIPI9ezaAgv7ySMXK3p+VKelnrenJveUQsflzemTfNlx8MxPauyDIYA4uRguCZZK+JkAjQRJzuHqDdV84uX6tmqJTKG0OrI1f5cJEB2kEwmtBr/sY/mCdntdm7cVfd8lMdj8IbsvKeUbEaAmxnsYtgECpXb3ouxJG9G83KMvBovRB6Oi5HHowTJ6LuLHXWvOrHFQql3WiIZ84CZMi8ZbU/bA6Wt/b4dL/vju9zmrbt8nTdut5/DqKPGKQSBjBPgdz7jA0T3EicQbP7m2UuueNH+n1yy/ysX7P+LrYsXbW2fktbat+MlWxcWbnTUDy9iei9MeWRGXpneO1P7u7Su7dvxXhP6dNQRCkEgRoDf+eTMQc+senYNXph6nr1yxyL4zIHGJ/jpwZkmPLduN4/LMH3Y9um5ujcm82L2Nn6Ik71xG+ZZiJMJ0B53cVKC47U7V/2Pr36gg7dj8HIMyWW69XL0IqN95jZGrvL6bJ+aq8/1Eb15wk0+ARPuuApuZjpGRcE2BIrLFlotUVHiYk1kjMKs7cGvHmYdiZCF5fVDq0NTlck5ExbNi0Ui43QkOkpsLE/adhAha+JjpwlmsHlMedwIYPPjNuJcb7c2X7h9ywRL+98VBMsgYNbESy9uSuS0MsUOvTF9SLkPGY9CyL1o2RhSHkRNS/7DAoF+CHRr8/20xbkRgfg0ZMERJ8yH6Z1zTMwMHpmdMgvJV/VMrGfmrRZifq95YmpbYeRhmjKelyOiiJOdWlZ65RAnE2A/iuJkCKm+bqKj3gDpx/L60vVa0phzdRFS33Xqzi7U+pHU26DwJkgu7HoTVP/xNCFSx/Qjy5I9AtzMZG9MMtOj6rIPnS4s3zRB0bxPLHTah1lbAplC9U4UWn3bwuj0XZeh1X5ex8k95s1owqOFUlc2mCeKFx3N29HP82hr+34QiWWw+cxYGB0ZEgFsfkigaSYzBAZp80rkU5y/FM19qc/ly5GoecH+Jyq03L7Tto53ujQLKa9OTbny/gOuOj0dhZhv3eYqs1t9eLmbmOi0asqNCYFB2vyYIBzoZYZnb01rpm2JmcqnoOdxPaNfsSjE4LHZTUfkhannbD2LK7JQz996Dg/P3rNT2+rbEj5HbUGczP6IIk4mMEZ5ECf1Q3Z96Zolhbnqf9SumbfjDds/ZfM46pj25fkoD0h5Qnaz6AdOb2TCxL9aIzh2QzA/ZbmZyc9Y9drTwvIN82a86opl+9y94gpLV/y6uGz7tl1YXtn23/uydsy+62aplrZEodMKrZZnow+llsgY7ZenbO09HxVunZ6XCDbfzahSdhQIYPOjMIpcQzcEsmDzxav2v/RSCCGvhZN7T0wTMevh5eaRqZDyG51FEwQGSt5T3brdJ/GpbLO1eV5KvKzWt6PvqjquYxI2tT8z2w1GyuaIQBZsPke4Mt3VQQmZylauZ/wwR6aEy/0zB9zM5FbvoSmhU8dmbV9l8iBmIk5m2pR95xAnExijYYuTmqBXrt8Kl5aoKFfwuGej3rJIiNSPVS9io5DoR0Y/PMHD0W9bSHXkNh7N4ai3LEzam4AB5agKbmZyNFjW1br3ojwaK4uRZ6MyVSuk2hLGFCp3vDej/67mzShvx14XJYeJRMfdrjph3o6WTEbiYrW4KUomI+9GP7fjjtwkksHme7UGzssrAWw+ryNHv3slkDeb94Kl97aMPDL1cUtLkXfmtauuYN6a+r5wx/63m3dmr0t1s83P7BP/2EfbSvKzeXPkmWlemVVL9lPetce56Sm3vP+gC+V7bY/zhkcgbzY/PDKj3VLwwpTXZZgjU/NjSk/wjkxyUpLzkm13u8TFTAmWmpZNnpkzk7NRPgjTD6QnRFO27XAqP+wFcXLYxLtvD3Gye2ZrzuhXnIxExGveRVtu2zeXbrpzN6NQ6pt3b676seg2jDp0VqKifgRCwpgwD4X/gai5d6vM7KS5c9sPBgsEmhHgZiYduwgio9ZFEw+LykZdvhmFR5evecFRmahd+Y6bkNioMl1kpG68qsrkDi8yLlsItStZqJiJilWFVpfsI0/Gkj2cmNhYsTIqG8qnQ2ewrWLzg+VL7dkjgM1nb0zo0WAJjLrNS6QsWjby4rzdQ9y0+wMTMQuL9nLyrK1v2r2EHS9dsHsIOzZxyu4hFq28iZu9LhI0JVQqpLw6NR2tTciUoClh04egW4Zz/532ayJor+1xXvcERt3muyfCGY0E4klsJWZKqwj6RAgpl3ah49Inul3CfJkSMuWBeZ90CBMvQ9byTRs2+2NylNps20k4RCFOdjtKwy+POJkA87g4qTcNEhSD0HhnedHCpU/6Y1GimHN+ux+vxsY/Zv2x6k2E/rj3mbv16jcXiI0JDDFV1AhwM9OFKVSWvZCoZC5FC5XW2ouGWvvQae3bcfv4Y7Hv/Dk618roXGfzOXa7VIsbzHvRPBc3WJIYeTDadtXCoyuT9pnQx/a1rWO+3PboeytbLU5329zIlsfmR3ZoubAWBLB5TGPcCGDza0e8sHTHFRRqftWmbbliH3lkxrbDcX/MvvNh6VfmzWvTypkXZ9dLqeQqMzM+lNyvLUFQ1dYV29d2+K6+7Y/puy0r54T9DRu6bn7cTsDmx23EB3+9EiyV9CeaJi6aSk4aiDwxg4CpYyHpTzc5K0LvJV5uNSFTzlXSO0KkpzSQPZYIaPPk5to8ms0FTcTJwdtBvy0gTvZJ8I9/9MfuzPWzflJa/UH2ssjVWW8M4m7O8TkdVnk9bt7tpkoIB71w5pz+CYzTzYy8EhXuHLwVC/JUXLrkXKVsIdDRG8LS4sloXfNaVLIXJYTp13OxcaTkxeg9FEOotCWCqdrvQHnaJr8vTkXejJP32LHNPlxa4qLWLP0TGCeb758WNYwCAWx+FEaRa+iGADbfDa32ZX2CH/PQVJi598y08HN5Z2rbe2su2DGVkah53aI/tLZQ9KSWinlpVjWnpoWgl+fu8QmBfGIgW5Q0SEvw4KzssHsnharLe9PC1+Nlk+pPFuvB5rM4KuPVpzBNnZ+arpaAN+TEOGsRpNqOws8tqtQ0ll68M0U0OG1JZ/nX//6b8YKcw6tFnOxz0Gb+esYtLK2IkhIaN8WVfBMdJS5umthUy1QdKfn7Zg7W/1j67AKnQ2BoBLJ+MxPCnwVE4c1a6qKibUeCo2WOroVCBxGxUMs0rfKagzHJRdml/Q2xRMPCRD0EWkKi5l4M4qIv06Jskv2hru4IZN3mu7saSkOgPQFsvj0jSowWAWw+G+NZUMi5ZS0vlJejeTR13yaBc9kiUfwcmnb/5sVM+zQp68+xskktCj3392Y+FN2yoNfC1b2YaUKmwtMlcmoJIqe2Nf+mliyHq2PzSVkJ9QyTQHAGk1CpSNSQd+OWpsHzkaoL6wqa1f9ZHWZ3aasHAoiTPUCLn/Lr07+20MttCI19cuT0fBBI6mZGgmGhcstuOBXmLE/DyNuwULZjPrxZ39vH/smEcloXrXxUduW7+DG7FUwEZLW0yUKiLWSoZGFFWk9Y6JB5L1ZtXbH96gZb1/bXlNtg39t5vpyVYck3gaRsPt8U6P04EcDmx2m0uVYRwOZHxw4Kt8wr84ZNmWMZzQsLdj+ptfYXbAqd2nG/ju3Hy/nydp7qSWqRSFndtMl7Z1Y32/2lX0fHvIBZW0v0jD6xY/XvonN9HbVj/fQPm++HHufmiYDmzlSCYAmaTz3+H/LU9bHsK+JkAsPeb0KcBLpAFRAYKIEQ4rxlesJu2E6423fKTT0S7f2yzwitpXjX5h2yrNBafJZo804sWKZ5ZYke1FKxpC2aZ1FL8FQMCV10zHsqmsdidaLmtWih0RULkdbik7/UznPm4cgCARHgBh47GDcC2Py4jTjXi81jA2sImAdm8N704enmzem9Ny1ZkDw3vQdnLZmQv+e10HXta1FSIS3Bu3NQdH1o+vS03deuhK37xEMW0u7vZxXKbnN5NvPw3Dhlxw8ccguLy76O4AE6qL5SLwSyQIA5J7MwCuv3AXEygTFCnEwAIlX0TCAIh/5GyOZILFnocnRXYpkYNReiP26hMOG47Ye5Ev0Nlc2jKE9EXy4W3pz0vImNF9ipkOgvZWM0R1CYe9Efs3kWfeIWExKZX7Fn8+HENgR4aMVExo0ANj9uI871YvPYwKAJ1IXNWMi6Fzltvk0tXggt24t/ha7XMqWnInjW5uv099nKsm7Cp7//Vii7zc8ZliB8at+HuNv3frs2h6c/3+b7DMcRQAdtYdTfCQHEyU4opVsGcTIB/oiTCUDMWRVxQVBdXyUK1q4lPtdh/fJiyVTCsTD/YX0/5nGoY/JALNY8EP3+kubj6S35Uq+YlYxFwmChYDcomw655YqFT5emXHlyT3QzUvNI9DcjCIm9Yua8DBLgoTWDg0KXBkoAmx8oXirPIAFsPoODQpfaEuhH8JwoFlzh5AlXtdt5eYMGQbRtowkVaJyPszK74vGpJuIeoPV9KxNfQlKjVceUCMkE1vgSF0l9XXiKJjSK+asGcTL7Y4Y4mcAYIU72BtGH/5qnXuOibMfKerxmiXn1NX4X1VVec4pCiOU1uKZ8Lbty4/GQRCV+fNChyL3RWzkrCIf+H66yNJtHoV9i4qFPulILX9ZXQUDUdmWD/SO3LND+/JgXYtxLMbTGDXy/o8X5eSOAzedtxOhvvwSw+X4Jcn7eCGDzeRsx+tsvgVY27xMSWbIh/xhRC2fXdsi6HtotnTpZ70JIVuTPuWARW4vRc1fJJzFa9NtpCKDdMAoh8o3nhORGq45Pm3PGrsg5Y9UyUXLle6Os8KsWC60P2eIbv/LHLZv8muMxr9PVbayE8HdzfZSNCCBOZt8SECc7GKMvPP2sO3Yimkfv/kN73c9feG7VWZ2Ik516u8lDTp5y7RbN5ddJuZCduFV9jV578XLxOQObna9EJMW7l9ft6qBDg9txGtT3EvqqNl9hWFaJgrWDPhvz5EoIhD9ctH9Qk6v/cYX5D+t1mYeiBMewKPFKfF9zKiokOo2FG/g0qNNmmgSw+TTp03YaBLD5NKjTZpoEsPk06dN2GgTStvnG+TiL85ddsSaKikc85L2+b/N8xpfSWWVnX+2YojB5nbuq3PzKfKC+rhQ8RYcxxiGb/HptNXqoNpZt9FiNf++/a/BeXQ26tQgbL6c5URu9W5v1WeXWba92UjeesIiTw7DE/tpAnGzD7yvf+K67PH+9LkhKqNwxN+t+/L1vRmf+H4tzZemJgJ8nsEniEYl15Q0Nol6thXItaUljgxXNP1iYWtMPf9y8BhsXH45snoVrjluf5D24amFOwzqOtG9mejI0ToJAHwSw+T7gcWouCWDzuRw2Ot0HAWy+D3icmksC2PzqYfNzfloSpMYlJDdaddw8Q72HaMMSny80/lWr4yrTqt1Sg6Bary+WqCmXhpd2pzWPAUumCSBOthmezzz1jPvzr/2pe+pzn/YlX/zHl9zf/ODv3K9efD46cx1xUt50Ese6WSoWXqsw23aLwnA7KddKtAv1N3rtxdttFtYb/77Ro69Zn9vV0e46+T5bBLiZydZ40JvBE8DmB8+YFrJFAJvP1njQm8ETwOYHz5gWskUAm8/WeCTRm3hIfqv6Gj1UG8s1eqzGvw9Z6lv21RI6hQz3611PM+/WZuVVrtjgLduOU/H8ylQCTcsiTrZDmPr3iJPrDMFrbx53X/r6t91Pv/8t9/gjR3zJZsdu3Vk712HqI0sHIDAAAhtKkafw3TJvngaAlyozSACbz+Cg0KWBEsDmB4qXyjNIAJvP4KDQpYESwOYHipfKM0pg01Qpoz2jW4EA4mQC4iTmBAEIQAACEIAABCAAAQhAAAIQgAAEIAABCHRPAHEyAXHy6sJS9+Q5AwI5JDA9Gb1xWlzCWziHw0eXeyCAzfcAjVNyTQCbz/Xw0fkeCGDzPUDjlFwTwOZzPXx0vkcC27ZM9ngmpw2LAOJkG9LN5px89js/dK//8oX6mZ1k6x7WgNIOBAZJgDlqBkmXurNIAJvP4qjQp0ESwOYHSZe6s0gAm8/iqNCnQRLA5gdJl7qzSoBs3VkdmZV+IU62GaO22brtfMTJ7Bs6PUyGADczyXCklvwQwObzM1b0NBkC2HwyHKklPwSw+fyMFT1NhgA2nwxHaskXAcTJ7I8X4mQHY/SFp591x06c8SXvP7TX/fyF51adhTjZAUSKjAQBbmZGYhi5iC4IYPNdwKLoSBDA5kdiGLmILghg813AouhIEMDmR2IYuYguCSBOdgksheKIkwlAR5xMACJV5IIANzO5GCY6mSABbD5BmFSVCwLYfC6GiU4mSACbTxAmVeWCADafi2GikwkTQJxMGOgAqkOcTAAq4mQCEKkiFwS4mcnFMNHJBAlg8wnCpKpcEMDmczFMdDJBAth8gjCpKhcEsPlcDBOdTJgA4mTCQAdQHeLkAKBSJQQgAAEIQAACEIAABCAAAQhAAAIQgAAEINCeAOJke0aUgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABAZAAHFyAFCpEgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEGhPAHGyPSNKQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAgMggDjZI9QvPP2sO3bijD/7/kN73c9feK7HmjgNAvkh8Nqbx92Xvv5t99Pvf8s9/siR/HScnkKgSwJf+cZ33W9eeXPVWa//8oUua6E4BPJD4C//6m/dL/7pX7D5/AwZPU2QQLB/7m8ShEpVmSPw4j++5J79zg/X9Iv7m8wNFR1KmMBjn326XuPXvvx598xXv5hwC1SXBAHEyR4o6qH18vz1uiApoXLH3Kz78fe+2UNtnAKBfBD4zFPPuPmrN3xnuXnPx5jRy94JyN5/9eLz9Qr04PrSy6+tOtZ77ZwJgewR0L3M//rmV+svnp7/0c/c3//DP2Pz2RsqepQwAQk2//un/9c7HXB/kzBcqssUAdn63/zg7/hdz9So0JlBEgiONc/9xZ+5pz736UE2Rd0JEECc7AGiHlr//Gt/Wjdwfuh7gMgpuSSA52Quh41OJ0AA208AIlXkigA2n6vhorN9EJBHjURJIkP6gMipuSDAM2suholOJkhAL17/42c+jqdkgkwHWRXiZJd0m92scwPfJUSK55YAtp7boaPjfRLAi6xPgJyeOwKKEnn3+Gk8bHI3cnS4GwJ6cP2vX/pP7ujB+xAnuwFH2VwSaBbWTUh3LoeSTndIQC+f5rbN1KP/dBoe8h3CS6EY4mSX0BEnuwRG8ZEigDg5UsPJxXRIgJCQDkFRbCQIxKfw4KF1JIaUi2hBQNN1nL90xU/LxP0NZjKOBBqnKhtHBlzz6BJodv8e5hfm/iab44442eW4IE52CYziI0WAm/eRGk4upgMCweaZPLsDWBQZKQLyFv7BT37huIEfqWHlYmoEGsNbub/BNMaRQLB7fufHcfRH/5pb/a7Lm5I5KLM5/oiTPYxLszknlfmMH/YeYHJKrghw856r4aKzfRII4U+Ef/QJktNzSyDMxff4I0dyew10HALNCLTKWqyyvIzCZsaFQPg74Bl2XEZ8/K6zmRCJOJldO0Cc7GFsyNbdAzROGQkCiJMjMYxcRAcEmDS+A0gUGSkCZKgfqeHkYrokwP1Nl8AonksCjb/zmnN1x9ysn9qABQKjSKBx/myFdb/08mvMp53RwUac7HFg9GN+7MQZf/b9h/a6n7/wXI81cRoE8kEgPg+ZeqzJhX/14vP56Dy9hEAXBMJDarNTCAPpAiRFc0Ugfl8TOo43Ta6GkM72QQBxsg94nJobAo2/85964hGEydyMHh3tlUDc7nl+7ZXicM5DnBwOZ1qBAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEGgggTmISEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAYPQJfOHpZ92OuVn34+99c/QvliuEAAQgAAEIQAACEOiJAOJkT9g4CQIQgAAEIAABCPRO4C//6m/dL/7pX9ZU8Pk/edL99f/4b/74i//4knv2Oz90z/3Fn7mnPvfp3htL8UzEyRTh0zQEIAABCEAAAhDICQHEyZwMFN2EAAQgAAEIDN4B/QAAB61JREFUQGB0CEicfOnl19yvXny+flGvvXncfenr33Zf+/Ln3TNf/eJIXCzi5EgMIxcBAQhAAAIQgAAEBkoAcXKgeKkcAhCAAAQgAAEIrCXQTJxUqc889Yz79Ccf996TQaz86fe/5R5/5IgLQp/K/eaVN32lc9tmVgmczVh3cp7KPPrgwbrXpur5yje+6y7PX3c/f+E5X23om0TV+as3/DEJqfv37vIenmEJ/dV+J22HtsI1ab9dHfHvsS8IQAACEIAABCAAgXwTQJzM9/jRewhAAAIQgAAEckigmTj5/I9+5n7wk1/Uhblm4uSxE2dWeVZKMHzgyL5153SUQNjuvE7FSYmSQRgM/Y0LpKpHSxA0m7XdWKZRBA31vv7LF3xdzerI4ZDTZQhAAAIQgAAEIACBFgQQJzENCEAAAhCAAAQgMGQCreacjAt9rTwn48llVM8b73xQFwObXUaz0OrG8zoVJ4NXp9pp7J+ONYquzdoOc2lK5NSiUPZGT0iJrv/lP/97H95OaPiQjZPmIAABCEAAAhCAwJAJIE4OGTjNQQACEIAABCAAgVZh3fIiVHizvAbzIk7GE/bI6/Hv/+Gf66HmzYTFcF06T0s8JDxuGWHuTcRJ/l4gAAEIQAACEIDAaBNAnBzt8eXqIAABCEAAAhDIIIFW4qS6+thnn/ah25998o9WeRV24gHZ7FI7Oa8fz8kkxMkQwt1p/zM4pHQJAhCAAAQgAAEIQKBHAoiTPYLjNAhAAAIQgAAEINArgVbiZDxj97DFyR1zs6vmrmyVEEfJerTEPSCf+tyn/bFOPCdDWHfcOzQucDYyxXOyVyvjPAhAAAIQgAAEIJAPAoiT+RgnegkBCEAAAhCAwAgRaCVOhuQvww7rbuxPEBDvP7R3TbbufsVJeYZ+/k+erGcGj4eyhyFWfz71xKNOoifi5AgZPpcCAQhAAAIQgAAEmhBAnMQsIAABCEAAAhCAwJAJZC0hji5fSWiUjVuLREl5Ul6ev963OKlM4fElLkyG40GgjJeLZ+tu9Ooc8nDRHAQgAAEIQAACEIDAAAkgTg4QLlVDAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACrQkgTmIdEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoEECdTwU6jEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAOIkNgABCEAAAhCAAAQgAAEIQAACEIAABCAAAQikQgBxMhXsNAoBCEAAAhCAAAQgAAEIQAACEIAABCAAAQggTmIDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQCoE/j9Orn3xpaoV9gAAAABJRU5ErkJggg==",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "461feca1-4016-44d8-ab71-bf36e437e121",
"metadata": {},
"source": [
"A is continuing to diffuse from the left. \n",
"B is continuing to diffuse from the right. \n",
"By now, they're overlapping in the middle bin sufficiently to react and generate C"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "cff27b4b-5cf3-4d70-80a7-8a13e1e3cd99",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.09600000000000007:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "c15dfca3-00fc-4b9a-80c4-01f565f30cf8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"+++ 30 steps later:\n",
"SYSTEM STATE at Time t = 0.156:\n",
"[[2.39736516 2.05453684 1.50075745 0.92781069 0.48529917 0.22472198\n",
" 0.11560109]\n",
" [0.11560109 0.22472198 0.48529917 0.92781069 1.50075745 2.05453684\n",
" 2.39736516]\n",
" [0.57202182 1.29674075 2.59761288 3.36115673 2.59761288 1.29674075\n",
" 0.57202182]]\n",
"\n",
"\n",
"+++ 30 steps later:\n",
"SYSTEM STATE at Time t = 0.216:\n",
"[[1.43652347 1.28435794 1.02979899 0.73906751 0.47257834 0.28028088\n",
" 0.18445971]\n",
" [0.18445971 0.28028088 0.47257834 0.73906751 1.02979899 1.28435794\n",
" 1.43652347]\n",
" [0.8597085 1.64384498 2.94653088 3.67276444 2.94653088 1.64384498\n",
" 0.8597085 ]]\n",
"\n",
"\n",
"+++ 30 steps later:\n",
"SYSTEM STATE at Time t = 0.276:\n",
"[[0.94369275 0.88396666 0.77535511 0.63019458 0.46959173 0.33300009\n",
" 0.25664867]\n",
" [0.25664867 0.33300009 0.46959173 0.63019458 0.77535511 0.88396666\n",
" 0.94369275]\n",
" [1.09382006 1.85282552 3.05530325 3.70365274 3.05530325 1.85282552\n",
" 1.09382006]]\n",
"\n",
"\n",
"+++ 30 steps later:\n",
"SYSTEM STATE at Time t = 0.336:\n",
"[[0.69798039 0.68111864 0.64213556 0.57196145 0.47435422 0.37878712\n",
" 0.32097915]\n",
" [0.32097915 0.37878712 0.47435422 0.57196145 0.64213556 0.68111864\n",
" 0.69798039]\n",
" [1.27482053 1.97696102 3.05404907 3.62102222 3.05404907 1.97696102\n",
" 1.27482053]]\n"
]
}
],
"source": [
"# Continue the simulation\n",
"for _ in range(4):\n",
" print(\"\\n\\n+++ 30 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=30)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "c4ae0ca5-2b98-4db4-b5e0-874ec2117ef0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0.33600000000000024:\n",
" A B C\n",
"0 0.697980 0.320979 1.274821\n",
"1 0.681119 0.378787 1.976961\n",
"2 0.642136 0.474354 3.054049\n",
"3 0.571961 0.571961 3.621022\n",
"4 0.474354 0.642136 3.054049\n",
"5 0.378787 0.681119 1.976961\n",
"6 0.320979 0.697980 1.274821\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "ea014eb8-5573-4e76-bb05-2dde0d4fedd7",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" SYSTEM TIME | \n",
" A | \n",
" B | \n",
" C | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" 0.000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" | \n",
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\n",
" \n",
" | 1 | \n",
" 0.002 | \n",
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" 0.000000 | \n",
" | \n",
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\n",
" \n",
" | 2 | \n",
" 0.016 | \n",
" 0.448347 | \n",
" 0.448347 | \n",
" 0.007451 | \n",
" | \n",
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\n",
" \n",
" | 3 | \n",
" 0.096 | \n",
" 1.230427 | \n",
" 1.230427 | \n",
" 2.408976 | \n",
" | \n",
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\n",
" \n",
" | 4 | \n",
" 0.336 | \n",
" 0.571961 | \n",
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"text/plain": [
" SYSTEM TIME A B C caption\n",
"0 0.000 0.000000 0.000000 0.000000 \n",
"1 0.002 0.000000 0.000000 0.000000 \n",
"2 0.016 0.448347 0.448347 0.007451 \n",
"3 0.096 1.230427 1.230427 2.408976 \n",
"4 0.336 0.571961 0.571961 3.621022 "
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Save the state of the concentrations of all species at the middle bin\n",
"bio.add_snapshot(bio.bin_snapshot(bin_address = 3))\n",
"bio.get_history()"
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},
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "ba4c44a3-3384-4f1a-b656-783c06eeb4af",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.33600000000000024:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "d7bd2795-9a78-4a2e-834c-477951677878",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"+++++ 50 steps later:\n",
"SYSTEM STATE at Time t = 0.436:\n",
"[[0.53513401 0.5437576 0.54867719 0.53174198 0.48696931 0.43256384\n",
" 0.39647767]\n",
" [0.39647767 0.43256384 0.48696931 0.53174198 0.54867719 0.5437576\n",
" 0.53513401]\n",
" [1.49508439 2.09028492 2.96849022 3.41695934 2.96849022 2.09028492\n",
" 1.49508439]]\n",
"\n",
"+++++ 50 steps later:\n",
"SYSTEM STATE at Time t = 0.536:\n",
"[[0.48751897 0.50165856 0.51768297 0.51798994 0.49498758 0.46076288\n",
" 0.4365229 ]\n",
" [0.4365229 0.46076288 0.49498758 0.51798994 0.51768297 0.50165856\n",
" 0.48751897]\n",
" [1.65797359 2.15520413 2.86719131 3.22213812 2.86719131 2.15520413\n",
" 1.65797359]]\n",
"\n",
"+++++ 50 steps later:\n",
"SYSTEM STATE at Time t = 0.636:\n",
"[[0.47470241 0.48869324 0.50591479 0.51120986 0.49756771 0.47365233\n",
" 0.45594669]\n",
" [0.45594669 0.47365233 0.49756771 0.51120986 0.50591479 0.48869324\n",
" 0.47470241]\n",
" [1.78774781 2.20070508 2.77778668 3.05983384 2.77778668 2.20070508\n",
" 1.78774781]]\n",
"\n",
"+++++ 50 steps later:\n",
"SYSTEM STATE at Time t = 0.736:\n",
"[[0.47257504 0.48488523 0.50040062 0.50652836 0.49733067 0.47935337\n",
" 0.46567693]\n",
" [0.46567693 0.47935337 0.49733067 0.50652836 0.50040062 0.48488523\n",
" 0.47257504]\n",
" [1.89367665 2.23536347 2.70338342 2.9284027 2.70338342 2.23536347\n",
" 1.89367665]]\n"
]
}
],
"source": [
"# Continue the simulation\n",
"for _ in range(4):\n",
" print(\"\\n+++++ 50 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=50)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "9bea764f-c52e-4346-a1e5-8a3e78bfca47",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0.7360000000000005:\n",
" A B C\n",
"0 0.472575 0.465677 1.893677\n",
"1 0.484885 0.479353 2.235363\n",
"2 0.500401 0.497331 2.703383\n",
"3 0.506528 0.506528 2.928403\n",
"4 0.497331 0.500401 2.703383\n",
"5 0.479353 0.484885 2.235363\n",
"6 0.465677 0.472575 1.893677\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
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"cell_type": "code",
"execution_count": 37,
"id": "420d2e10-a6e7-4c90-80ea-5995db2b5ed6",
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"bgcolor": "#E5ECF6",
"caxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"title": {
"x": 0.05
},
"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
},
"title": {
"text": "A + B <-> C . System snapshot at time t=0.7360000000000005"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
0,
6
],
"title": {
"text": "Bin number"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
0.32885882676839184,
3.065220802002373
],
"title": {
"text": "concentration"
},
"type": "linear"
}
}
},
"image/png": 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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "8ac79f33-0548-49ce-a165-24b9773a7c4c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.7360000000000005:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "b041f211-cc16-42a4-b0ca-2beb4e2c34aa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"+++++++++++++++ 150 steps later:\n",
"SYSTEM STATE at Time t = 1.036:\n",
"[[0.47744061 0.4845086 0.49346999 0.49747162 0.49331726 0.48423339\n",
" 0.47709743]\n",
" [0.47709743 0.48423339 0.49331726 0.49747162 0.49346999 0.4845086\n",
" 0.47744061]\n",
" [2.11014111 2.3007984 2.55138084 2.66782039 2.55138084 2.3007984\n",
" 2.11014111]]\n",
"\n",
"+++++++++++++++ 150 steps later:\n",
"SYSTEM STATE at Time t = 1.336:\n",
"[[0.48168804 0.48554921 0.49041386 0.49259511 0.49040626 0.48553552\n",
" 0.48167096]\n",
" [0.48167096 0.48553552 0.49040626 0.49259511 0.49041386 0.48554921\n",
" 0.48168804]\n",
" [2.2288825 2.33377315 2.46847456 2.52988061 2.46847456 2.33377315\n",
" 2.2288825 ]]\n",
"\n",
"+++++++++++++++ 150 steps later:\n",
"SYSTEM STATE at Time t = 1.636:\n",
"[[0.48405962 0.48615505 0.48878337 0.48995858 0.48878299 0.48615437\n",
" 0.48405877]\n",
" [0.48405877 0.48615437 0.48878299 0.48995858 0.48878337 0.48615505\n",
" 0.48405962]\n",
" [2.29360822 2.350868 2.42345244 2.45618991 2.42345244 2.350868\n",
" 2.29360822]]\n",
"\n",
"+++++++++++++++ 150 steps later:\n",
"SYSTEM STATE at Time t = 1.936:\n",
"[[0.48534444 0.4864795 0.48789956 0.48853323 0.48789955 0.48647947\n",
" 0.4853444 ]\n",
" [0.4853444 0.48647947 0.48789955 0.48853323 0.48789956 0.4864795\n",
" 0.48534444]\n",
" [2.32876222 2.35988613 2.39905402 2.4166151 2.39905402 2.35988613\n",
" 2.32876222]]\n"
]
}
],
"source": [
"# Continue the simulation\n",
"for _ in range(4):\n",
" print(\"\\n+++++++++++++++ 150 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=150)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "ef8f0e74-c8b0-4228-98a3-8357cc411471",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 1.9360000000000015:\n",
" A B C\n",
"0 0.485344 0.485344 2.328762\n",
"1 0.486480 0.486479 2.359886\n",
"2 0.487900 0.487900 2.399054\n",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "149c2dd1-ae24-42af-9cb7-ea3e3b7bc7ae",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=1.9360000000000015:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "c9a71254-b873-4f84-92e8-55110fd3e9e1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"++++++++++ ... ++++++++++ 1,000 steps later:\n",
"SYSTEM STATE at Time t = 3.936:\n",
"[[0.48683089 0.48684974 0.48687325 0.48688372 0.48687325 0.48684974\n",
" 0.48683089]\n",
" [0.48683089 0.48684974 0.48687325 0.48688372 0.48687325 0.48684974\n",
" 0.48683089]\n",
" [2.36959744 2.37011659 2.37076408 2.37105229 2.37076408 2.37011659\n",
" 2.36959744]]\n",
"\n",
"++++++++++ ... ++++++++++ 1,000 steps later:\n",
"SYSTEM STATE at Time t = 5.936:\n",
"[[0.48685551 0.48685582 0.48685621 0.48685639 0.48685621 0.48685582\n",
" 0.48685551]\n",
" [0.48685551 0.48685582 0.48685621 0.48685639 0.48685621 0.48685582\n",
" 0.48685551]\n",
" [2.37027551 2.37028411 2.37029484 2.37029961 2.37029484 2.37028411\n",
" 2.37027551]]\n"
]
}
],
"source": [
"# Continue the simulation\n",
"for _ in range(2):\n",
" print(\"\\n++++++++++ ... ++++++++++ 1,000 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=1000)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "665df78f-4f5d-4f49-bd1e-7fe92f6f9be1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 5.935999999999568:\n",
" A B C\n",
"0 0.486856 0.486856 2.370276\n",
"1 0.486856 0.486856 2.370284\n",
"2 0.486856 0.486856 2.370295\n",
"3 0.486856 0.486856 2.370300\n",
"4 0.486856 0.486856 2.370295\n",
"5 0.486856 0.486856 2.370284\n",
"6 0.486856 0.486856 2.370276\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "123afda8-993f-4d81-823b-dd4bca921727",
"metadata": {},
"outputs": [
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"# Save the state of the concentrations of all species at the middle bin\n",
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},
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"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
},
"title": {
"text": "A + B <-> C . System snapshot at time t=5.935999999999568"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
0,
6
],
"title": {
"text": "Bin number"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
0.3822197281848969,
2.4749353952225412
],
"title": {
"text": "concentration"
},
"type": "linear"
}
}
},
"image/png": 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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "ebc287ae-60de-4d52-9b34-6714b3813198",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=5.935999999999568:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "markdown",
"id": "1ede543d-6d62-4ede-bb7b-7b6022c69b09",
"metadata": {
"tags": []
},
"source": [
"### Equilibrium"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "1678d6bf-434f-476c-a966-998fbfa0e74a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Ratio of equilibrium concentrations ((C_eq) / (A_eq * B_eq)) : 9.999968840509963\n",
"Ratio of forward/reverse rates: 10.0\n"
]
}
],
"source": [
"# Verify equilibrium concentrations (sampled in the 1st bin; at this point, all bins have equilibrated)\n",
"A_eq = bio.bin_concentration(0, 0)\n",
"B_eq = bio.bin_concentration(0, 1)\n",
"C_eq = bio.bin_concentration(0, 2)\n",
"print(f\"\\nRatio of equilibrium concentrations ((C_eq) / (A_eq * B_eq)) : {(C_eq) / (A_eq * B_eq)}\")\n",
"print(f\"Ratio of forward/reverse rates: {chem_data.get_forward_rate(0) / chem_data.get_reverse_rate(0)}\")\n",
"# Both are essentially equal, as expected"
]
},
{
"cell_type": "markdown",
"id": "ee7d1b45-0e56-45fd-bd63-7a97b39eb8f0",
"metadata": {
"tags": []
},
"source": [
"# Plots of changes of concentration with time"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "790211a2-8f53-498a-8363-1c6e5f6f5d7e",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"hovertemplate": "Chemical=A
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "A",
"line": {
"color": "navy",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "A",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.002,
0.016,
0.09600000000000007,
0.33600000000000024,
0.7360000000000005,
1.9360000000000015,
5.935999999999568
],
"xaxis": "x",
"y": [
0,
0,
0.4483473209623955,
1.2304268485314716,
0.5719614476422076,
0.5065283645846138,
0.48853323167520946,
0.48685638687034016
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=B
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "B",
"line": {
"color": "cyan",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "B",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.get_history(), x=\"SYSTEM TIME\", y=[\"A\", \"B\", \"C\"], \n",
" title=\"Reactions: A + B <-> C . Changes in concentrations in the MIDDLE bin\",\n",
" color_discrete_sequence = ['navy', 'cyan', 'red'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\"})\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "4dbf45ff-5161-4265-a278-aca3121b8e37",
"metadata": {},
"source": [
"A and B overlap on the plot, due to the symmetry of the system. \n",
"Initially, in the middle bin, neither A nor B are present; over time they diffuse there... but then they react and get consumed (producing C), to an equilibrium value.\n",
"C gradually diffuses away."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "146f8c63",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}