From bf3f4a2a6c5e0fd3a120c8a01c41a77d1c3281a3 Mon Sep 17 00:00:00 2001 From: Johannes Hjorth Date: Fri, 23 Aug 2024 11:32:52 +0200 Subject: [PATCH] Updated example, bath on off for neuromodulation --- .../data/input_v6_bath_on_off.json | 23 + .../neuromodulation_bath.ipynb | 383 +++++++------- .../neuromodulation_on_off.ipynb | 166 +++++- .../neuromodulation_on_off_bath.ipynb | 495 ++++++++++++++++++ snudda/simulate/simulate.py | 2 +- 5 files changed, 846 insertions(+), 223 deletions(-) create mode 100644 examples/notebooks/neuromodulation/data/input_v6_bath_on_off.json create mode 100644 examples/notebooks/neuromodulation/neuromodulation_on_off_bath.ipynb diff --git a/examples/notebooks/neuromodulation/data/input_v6_bath_on_off.json b/examples/notebooks/neuromodulation/data/input_v6_bath_on_off.json new file mode 100644 index 000000000..6257fc438 --- /dev/null +++ b/examples/notebooks/neuromodulation/data/input_v6_bath_on_off.json @@ -0,0 +1,23 @@ +{ + "dspn": { + "cortical_background": { + "generator": "poisson", + "frequency": 1.2 + }, + "thalamic_background": { + "generator": "poisson", + "frequency": 1.2 + }, + "cortical" : { + "generator" : "poisson", + "start" : [0], + "end" : [10], + "frequency" : [10], + "conductance" : 0.5e-9, + "input_correlation": 0.75, + "num_inputs" : 20, + "parameter_file": "data/tmglut_DA_parameters.json", + "mod_file": "tmGlut" + } + } +} diff --git a/examples/notebooks/neuromodulation/neuromodulation_bath.ipynb b/examples/notebooks/neuromodulation/neuromodulation_bath.ipynb index 9fee0caa8..ef2218924 100644 --- a/examples/notebooks/neuromodulation/neuromodulation_bath.ipynb +++ b/examples/notebooks/neuromodulation/neuromodulation_bath.ipynb @@ -55,11 +55,11 @@ "Network path: networks/neuromodulation_bath\n", "Reading SNUDDA_DATA=None from networks/neuromodulation_bath/network-config.json\n", "Reading SNUDDA_DATA=/home/hjorth/HBP/Snudda/snudda/utils/../data from networks/neuromodulation_bath/network-synapses.hdf5\n", - "No n_putative_points and putative_density, setting n_putative_points = 63\n", + "No n_putative_points and putative_density, setting n_putative_points = 90\n", "(this must be larger than the number of neurons you want to place)\n", - "Generating 63 points for networks/neuromodulation_bath/mesh/Cube-cube-mesh-2.917951293943981e-05.obj\n", - "Filtering, keeping inside points: 4 / 26\n", - "neuron_name = 'dspn_0', num = 2, neuron_path = 'data/dspn/str-dspn-e150602_c1_D1-mWT-0728MSN01-v20211026'\n", + "Generating 90 points for networks/neuromodulation_bath/mesh/Cube-cube-mesh-3.6763882578080044e-05.obj\n", + "Filtering, keeping inside points: 5 / 35\n", + "neuron_name = 'dspn_0', num = 4, neuron_path = 'data/dspn/str-dspn-e150602_c1_D1-mWT-0728MSN01-v20211026'\n", "stop_parallel disabled, to keep pool running.\n", "\n", "Execution time: 0.0s\n", @@ -68,25 +68,30 @@ "Reading SNUDDA_DATA=None from networks/neuromodulation_bath/network-config.json\n", "Reading SNUDDA_DATA=/home/hjorth/HBP/Snudda/snudda/utils/../data from networks/neuromodulation_bath/network-synapses.hdf5\n", "No d_view specified, running distribute neurons in serial\n", - "Processing hyper voxel : 0/27 (2 neurons)\n", - "Processing hyper voxel : 1/27 (2 neurons)\n", - "Processing hyper voxel : 3/27 (2 neurons)\n", - "Processing hyper voxel : 4/27 (2 neurons)\n", - "Processing hyper voxel : 9/27 (2 neurons)\n", - "Processing hyper voxel : 10/27 (2 neurons)\n", - "Processing hyper voxel : 12/27 (2 neurons)\n", - "Processing hyper voxel : 13/27 (2 neurons)\n", + "Processing hyper voxel : 0/48 (4 neurons)\n", + "Processing hyper voxel : 1/48 (4 neurons)\n", + "Processing hyper voxel : 4/48 (4 neurons)\n", + "Processing hyper voxel : 5/48 (4 neurons)\n", + "Processing hyper voxel : 12/48 (4 neurons)\n", + "Processing hyper voxel : 13/48 (4 neurons)\n", + "Processing hyper voxel : 16/48 (4 neurons)\n", + "Processing hyper voxel : 17/48 (4 neurons)\n", + "Processing hyper voxel : 14/48 (3 neurons)\n", + "Processing hyper voxel : 6/48 (2 neurons)\n", + "Processing hyper voxel : 18/48 (2 neurons)\n", + "Processing hyper voxel : 25/48 (2 neurons)\n", + "Processing hyper voxel : 29/48 (1 neurons)\n", "Reading SNUDDA_DATA=None from networks/neuromodulation_bath/network-config.json\n", "stop_parallel disabled, to keep pool running.\n", "\n", - "Execution time: 0.6s\n", + "Execution time: 0.9s\n", "Prune synapses\n", "Network path: networks/neuromodulation_bath\n", "No file networks/neuromodulation_bath/pruning_merge_info.json\n", - "Read 90 out of total 90 synapses\n", + "Read 518 out of total 518 synapses\n", "stop_parallel disabled, to keep pool running.\n", "\n", - "Execution time: 0.6s\n" + "Execution time: 0.9s\n" ] } ], @@ -99,7 +104,7 @@ "connectivity_path = os.path.join(\"data\", \"connectivity.json\")\n", "\n", "snudda = Snudda(network_path=network_path)\n", - "si = snudda.init_tiny(neuron_paths=neuron_path, neuron_names=\"dspn\", number_of_neurons=[2], \n", + "si = snudda.init_tiny(neuron_paths=neuron_path, neuron_names=\"dspn\", number_of_neurons=[4], \n", " connection_config=connectivity_path, random_seed=12345)\n", "\n", "# si.network_data[\"regions\"][\"Cube\"][\"neurons\"][\"dspn\"][\"reaction_diffusion\"] = \"reaction_diffusion.json\"\n", @@ -135,16 +140,22 @@ "!!! Warning, combining definition of cortical_background with cortical_background input for neuron dspn_0 1 (meta modified by input_config)\n", "!!! Warning, combining definition of thalamic_background with thalamic_background input for neuron dspn_0 1 (meta modified by input_config)\n", "!!! Warning, combining definition of cortical with cortical input for neuron dspn_0 1 (meta modified by input_config)\n", + "!!! Warning, combining definition of cortical_background with cortical_background input for neuron dspn_0 2 (meta modified by input_config)\n", + "!!! Warning, combining definition of thalamic_background with thalamic_background input for neuron dspn_0 2 (meta modified by input_config)\n", + "!!! Warning, combining definition of cortical with cortical input for neuron dspn_0 2 (meta modified by input_config)\n", + "!!! Warning, combining definition of cortical_background with cortical_background input for neuron dspn_0 3 (meta modified by input_config)\n", + "!!! Warning, combining definition of thalamic_background with thalamic_background input for neuron dspn_0 3 (meta modified by input_config)\n", + "!!! Warning, combining definition of cortical with cortical input for neuron dspn_0 3 (meta modified by input_config)\n", "Writing spikes to networks/neuromodulation_bath/input-spikes.hdf5\n", "stop_parallel disabled, to keep pool running.\n", "\n", - "Execution time: 4.0s\n" + "Execution time: 1.1s\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 2, @@ -159,13 +170,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "aa0341ff-115d-43f9-a46a-dd6cf074ca69", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mpirun -n 4 snudda simulate networks/neuromodulation_bath --time 4.0 --simulation_config data/DA-bath-experiment.json --mechdir /home/hjorth/BasalGangliaData/data/neurons/mechanisms\n" + ] + } + ], "source": [ "sim_time = 4.0\n", - "n_workers = 1\n", + "n_workers = 4\n", "sim_config = \"data/DA-bath-experiment.json\"\n", "mech_dir = \"/home/hjorth/BasalGangliaData/data/neurons/mechanisms\"\n", "\n", @@ -202,7 +221,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "d84ee6f3-4193-4509-ad4a-0d93dff5e3d9", "metadata": {}, "outputs": [ @@ -210,7 +229,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Loading networks/neuromodulation_bath/simulation/output.hdf5\n" + "Loading networks/neuromodulation_bath/simulation/output.hdf5\n", + "WARNING. Depolarisation block in neuron - neuron_id: (name, parameter_key, morphology_key):\n", + "2: (dspn_0, p7aa400d6, mf702205f)\n" ] } ], @@ -230,7 +251,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "bd0f4edf-a622-490b-b39f-18f516975737", "metadata": {}, "outputs": [], @@ -242,7 +263,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "a63a7152-730e-4868-a81a-cc87fccaf9f4", "metadata": {}, "outputs": [ @@ -253,7 +274,7 @@ " scrolling=\"no\"\n", " width=\"1020px\"\n", " height=\"820\"\n", - " src=\"iframe_figures/figure_5.html\"\n", + " src=\"iframe_figures/figure_6.html\"\n", " frameborder=\"0\"\n", " allowfullscreen\n", ">\n" @@ -278,157 +299,110 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "1e49669a-1e97-4e19-8586-4acff6e21d69", - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import plotly.graph_objects as go\n", - "\n", - "fig = go.Figure()\n", - "for data_type in all_species_data:\n", - " yy = all_species_data[data_type][0][0].T[0]\n", - " fig.add_trace(go.Scatter(x=time, y=yy/np.max(yy), name=data_type))\n", - "\n", - "fig.update_layout(xaxis_title=\"Time (s)\", yaxis_title=\"Concentration\", width=1000, height=800)\n", - "fig.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0b572560-b42f-4920-bdf3-6718800d01f1", + "execution_count": 20, + "id": "d31a7d49-55b1-479c-942a-17cbd87fa412", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading networks/neuromodulation_bath/simulation/output.hdf5\n", + "WARNING. Depolarisation block in neuron - neuron_id: (name, parameter_key, morphology_key):\n", + "2: (dspn_0, p7aa400d6, mf702205f)\n", + "Saving figure to networks/neuromodulation_bath/figures/spike-raster.png\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "import numpy as np\n", - "import plotly.graph_objects as go\n", - "\n", - "fig = go.Figure()\n", - "for data_type in all_species_data:\n", - " yy = all_species_data[data_type][0][0].T[0]\n", - " fig.add_trace(go.Scatter(x=time, y=yy/yy[0], name=data_type))\n", + "from snudda.plotting import SnuddaPlotSpikeRaster2\n", + "fig_file_raster = f\"spike-raster.png\"\n", "\n", - "fig.update_layout(xaxis_title=\"Time (s)\", yaxis_title=\"Concentration\", width=1000, height=800)\n", - "fig.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "adb36614-f0e8-44ac-a36d-9119b48d4bee", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e6554026-bb50-4209-a1f7-37565af50529", - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", + "time_range_zoom = (0,sim_time)\n", + "spr = SnuddaPlotSpikeRaster2(network_path=network_path)\n", "\n", - "plt.figure()\n", - "for data_type in all_species_data:\n", - " plt.plot(time, all_species_data[data_type][0][0].T[0], label=data_type)\n", - "plt.xlabel(\"Time (s)\")\n", - "plt.ylabel(\"Concentration\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3febf45e-b1a0-45ce-b791-266ed03ed741", - "metadata": {}, - "outputs": [], - "source": [ - "all_species_data[data_type][0][0].T[0]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d98d057c-752c-458b-bd52-a726f42dc90a", - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", - "plt.figure()\n", - "plt.plot(time, data_da, label=\"DA\")\n", - "plt.xlabel(\"Time (s)\")\n", - "plt.ylabel(\"Concentration\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d3bda015-1674-45ae-96f0-69167fd2cc89", - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", - "plt.figure()\n", - "plt.plot(time, data_pka, label=\"PKAc\")\n", - "plt.xlabel(\"Time (s)\")\n", - "plt.ylabel(\"Concentration\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0e281a93-c7de-45cf-9723-98f3a19bbca0", - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", - "plt.figure()\n", - "plt.plot(time, data_da_external, label=\"DA from external?\")\n", - "plt.xlabel(\"Time (s)\")\n", - "plt.ylabel(\"Concentration\")\n", - "#plt.legend()\n", - "plt.title(\"DA from external?\")\n", - "plt.show()" + "spr.plot_spike_raster(fig_file=fig_file_raster, time_range=time_range_zoom)" ] }, { "cell_type": "code", - "execution_count": null, - "id": "20144fff-adf6-4c4b-956d-97deb916d7e6", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d31a7d49-55b1-479c-942a-17cbd87fa412", + "execution_count": 29, + "id": "35751562-8631-4430-9911-ffd1ffeda516", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Saving figure networks/neuromodulation_bath/figures/spike-frequency-pop-units0.pdf\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "from snudda.plotting import SnuddaPlotSpikeRaster2\n", - "fig_file_raster = f\"spike-raster.png\"\n", - "\n", - "time_range_zoom = (0,0.1)\n", - "spr = SnuddaPlotSpikeRaster2(network_path=network_path)\n", - "\n", - "spr.plot_spike_raster(fig_file=fig_file_raster, time_range=time_range_zoom)" + "spr.plot_spike_histogram(label_text=\"dSPN\", bin_size=0.25)\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "id": "fc082055-9e38-4ed1-b842-40e166548071", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading network info from networks/neuromodulation_bath/network-synapses.hdf5\n", + "Loading input info from networks/neuromodulation_bath/input-spikes.hdf5\n", + "Loading networks/neuromodulation_bath/simulation/output.hdf5\n", + "WARNING. Depolarisation block in neuron - neuron_id: (name, parameter_key, morphology_key):\n", + "2: (dspn_0, p7aa400d6, mf702205f)\n", + "Plotting traces: [0, 1, 2, 3]\n", + "Plotted 4 traces (total 4)\n", + "Saving to figure /home/hjorth/HBP/Snudda/examples/notebooks/neuromodulation/networks/neuromodulation_bath/figures/Network-voltage-trace--dspn-0-1-2-3.pdf\n" + ] + }, + { + "data": { + "image/png": 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IkSOK1/21fbPjpxn8+T6gHo+V2LNnj93R0U1WVhZiY2NNP9+rVy/V30aPHo3MzEzTYZulTZs2OHToUNDfawa3TUCbpWykksMpI1SrVg3vvfee5j2TJk2ydR+Jm3HzqoodQrPe9N97771YvHixrvgsWbLEcry0mD59Ojwej19vyw8++CC++uor7N692/S7cnNzTT/rVk6ePAkASE1NDcr7jNTjr7/+WvP3jIwMTaHeCHYc48Upycdt27aFOhoBo3r16rru81c/aF/ctm3bsDviqVy5cmjatGlAwv7nn38Urw8dOjQg76McP348oOFzjMMVWg7HgZhVtM6ePYtx48Zp3jNu3DhbPP0Z3W9SFnCKU6hAKuqsYOZPSIuJibH9/a+99hoIIX4V1blz5+K+++5D8+bNFX//4osv4PF4kJqaij59+tgeTzcyf/58/PHHH0F9p78Vf5ZgrIhwxdReRowYgTZt2mDNmjWhjkpASE9PtzW8LVu2iMfHGMUJE7RqY2Aw2i777tmzZ+t65rHHHoMgCCG36uBYhyu0HA6nzGJGeA0n8x2rApC/550sJLz66qsghGDdunWiB1I1jh49GqRYhZbffvtN/MwnqswhV9BpH+MEZcMOjKZjw4YNAIADBw4EIjqGmDBhAp555hnF39T6dbPlVlRUpPsouHAgFBNBv/76q2WT7/nz5wNQNh3fsmWLrr7f6W1bqW6HY/8ePpIZh8MpE7Rt2xaJiYkhc1zjFOwYkMx49XT64B0IPv7441BHIWwxIggHY7+i2fodThNd4cqLL76IyZMnByz87du3i5979eqFmjVriscH+XNcZLY/d4JFweLFi207JskIvXr1knivt6sNsubf/Og498B7YA6HYwk7FCsjg/KWLVuQnZ2NV155xfJ7KYQQWwZDp8x66hXKDx8+bCr8UApRdpu6O6XMAsWrr76KyMjw8P/o5EmscK9HVjGTP+np6Rg8eLDhZ+0sCyN9XatWrcTPdGWaxuXPP/8EAFu2+ziN22+/HdnZ2QBKjg/atGlT0N7NjnWvv/666XCsTDSEmxWGW+EKLYfD0c3Ro0dx8ODBUEfDNswosfSZYA9ew4YNsz1Mf2nwN+vODvZ2Krn+HFBx9PPWW2+5+nzNYKNUj71er+jxWk5OTk7A2kE4YCU/7rzzTnz++ef4/PPPxWuHDx9Gy5Yt7YiayO7du/Hcc88p/mZXP0/bIO1T165da0u4weTEiRN+y/PZZ59Fx44dTb/D6/Vi4MCBpp4ti5Y0RUVFOHbsWKij4Qi4QsvhcHyoVauW4rFB9erVQ6NGjQAgIGflmhEetmzZgrvuusv2uJghkErup59+qvtddgnVoZpxvv3221V/k8fp3Llzpt7BFQ9n4AZhbPDgwWjbtq2iUpuQkCBRsOyy9jDLwYMHA+JV+KmnnrI9TH/QMSYnJ0e8NnDgQPz777+2vmfEiBG4ePGirWFq8dJLL6Fz585Be59d/P3337rus7JCPn/+fHFfK8c/N954I+rWreszqVanTp0Qxio0cIWWw+H4cPLkSdGESIm4uLggxkabnj17iuf3WiGcFByziqgb88DfUS4c57Jt2zZcunRJ/G6XqeiOHTs0J0X0wLYhakKpZqK/c+dOx+yhbdSoEdq0aWN7uO+//76p52g+us0k266+UCndmzdvtiVsPe9yG8E819duQjEBrFaXyuKxQs7ogTkcDgD3HIXDDjqhjqtdzijcvP/FrtlYK3kQLIHejUq3GwlGewiUI5kbb7wRixcvNrX6a2f9CvVqrRuYMmWK3zOPQ9k32z2+qaWFEFKmvCLL2b59u2Ql3k04XXZQ20YRbvCelsPhOJ4WLVpgypQpAQvfyICktZc1VINEWZyN5YQnv/32m2WlMlCKsp5+gj2qh3NZmFZS7NPT0/H000/bbn5rdBLB7LYFPRjZ71uzZk3D4Qezrtk9OfPWW2+JY2arVq1w9dVX2xp+sAlluw9HBdUoXKHlcMIMp88WmmHHjh14+umnbQ/XzAD0+++/2x4Puwl0HXCCV0crA/iwYcMCKsRyzEEIceT+OaP9hJV2sXfvXnTr1i3sBFSl9NCjbPyt0LIEQmnYs2eP7WFS9u/fL/kuCELAFB9a7x588EGMGzcuIO+wiylTpmD8+PEYNWqUeC3UDietWsiFo+zlJrhCy+FwLGGH4OUEszy3raoEYvCU54FVL8hOZebMmUhPTwfAhRCKvB0HQ6GaNGlSQMMPRdmybciMyXHv3r2xatUqLF++3O6ohQVOb6+7d+9GRESEat9ICFFMg5F0+bt37ty5AW9bVjl58iSAEs/JTsCtE0h66o0T5KtgUDZSyeFwFKHC1+7dux2xfydUwoqZ9yo9E4pBsVmzZgEN/7333lP97Y8//gjou7UoK4O0VZw8URMoh16hTLPc5DiUZ6g6AT1lYXe/H8ry//jjj+H1esXV52Di5LbuVMpCnjn5/G474RIBh8NB8+bNw8rN+7XXXovu3buHOhoBhQqBe/fuDdg7BEHA6NGjFa8DkHjCLguCQVnCzRMGoV6Z1boWzowYMQJpaWmSa7QslMrETB0LloJsd9mx4QXa5DhQ7Nq1y/Ywnb7ibgSnbsH58ccfgxiT0OHeEYvD4ViG7YDpwe9GceKKwurVq7Fy5UosWbJE1/127WtyYl5YQcsjpxWOHj1q+ln5PicloTjcysEO/OVJKEyOg8XNN9+MO++809AzdqSfNTk22mbclv9Lly7F9OnT0atXL93P6E1jKPPCLiXFXzhuUOw++eQT28JSG2/dOJHmhrIrC7iv5nA4YYxbju1xC71799Z1n9q+JrspKirCxo0bbQnLbHy1vDTbyb333qt4/bfffkO9evXw4osvBiUeHP2EWpi0qw3KheVly5bhhx9+MPWsUawe1ePWVV165EpmZqbkOk2PmXSZeSY1NTWkK1KhbkPBhvoiMIpaW3ez7OOmtuvmfFajbLU8DocjwU0dsB20aNFCotAFO/233HILOnTogDNnzhh+1q64zpw503IYeswrFyxYoPgsPQj+zz//tBwPzmWysrIsPe/1esNSyDFKqFdb6PunT58OQRAc4dsgUARC+bPLyZDZ/latDQVqrLGyX9sOzBw1FA4Ew4TcCLzv5goth8NxAMGa1d6xY4eiQmfX2ZH+BpXt27cD8F3F0IMRQTvQg5vTB08j8XN6WvRSrlw5zd+NptOqYvfee++Z8oJtZ18QirKV9yM0PfLrRUVFqFWrlupq4urVqwEAhw8fDkAsg48Vx3uhWPUM9cSGW6Ar80ZxghLI4vV6+bE9LocrtBwOxxLhohCEE24oEz74Ow+7FIeFCxdi9OjRGDBggKHnnFBv7Ra0aZrk9f3w4cM4efIkhg4dGtD3W+Whhx6yFCfum0CK3f0eG144mDu7MQ1uHMvcGGd/RIY6AhwOh2OWjIyMkByPYBUzApqTBF2zQketWrXQqFEjm2PDsQO5ybGV+nb69GkAwPHjxy3Hywp2C8d62m0gFZZQoLZ1QC9W4m+mDoZaITL7fjvKOVCK//3334/z58/bGqaW92u34YSxOZwmfczCFVoOh+NaatWqhfz8fFvCcttKgta7nCoknDx5EidPngQAFBQUYOTIkabDomlUKjc+uPsSbJNjJxDMeqCmyIRawXIKdpWFv37arvfQcORm83aME3YqQMFQpr788ksAQN26dQP+rlARjo7czpw5g2rVqoU6GkEjYD3tjh07sHTpUnz55ZeYO3duoF7D4YQlbhLIteL61FNPoV27drrDMipEm9mLyhIqYTMchVyjg/o///yDjz76yPJ7w0HxcgJer9f2eunmsrF7ZVEent68dqqwLCdYfVqw6hS1Lvj9999tD1tPGtLS0hwnOwdCEXdK/bYiczm1n/vss89CHYWgYusK7dGjR/HWW29h/vz5uHTpkuS3wYMHS76fPXsWTz75JAghaNeuHcaNG2dnVDgcjgN4//33Qx2FoOKUiQinCAlaOCWvwh0zjpncgt5juZyI3vrvVGFZjj/vvmYU3lD2YzQ9dlkA6X0fpVOnTti/fz8GDhyIyEh9orpb6gqLG+PMcSa2KbTz58/H8OHDkZ2d7VNBlTqlqlWr4ty5c1i1ahWWLFmCkSNHIjEx0a7ocDgcjm6CPajaocxpxbmsCwll0cuxGlQg95dO+R5aO+pQoM8eXbJkieHwAxEPNVjv6UbDc8OklBGU6p8/JVepDvrLFzdYv+gpW3q0m7/0BLOehPu44uY2F+7jmB5safkLFy7EoEGDRGW2QoUKuOWWW9CkSRPN56h3v9zcXPzyyy92RIXD4QQZOzrSUAkhwR7AgvU+JxxXEm7vjY+PD8p7wgmjAjAhJKRC8969e5Geni7GxSxK/ZlRk+NwVx6AwKxSc8GeYwYrk3mhbKt2n5fsZixLkenp6Xj00UfFmciXX34Zp0+fxs8//4wbb7xR89k77rhDNKVYvny51ahwOByOIawMRErP+gvPzoHPSYNoQUGB6Nk2HDh16pR4ZjAlNzc3RLEJHnZNLLlhlUyJK6+8EgcPHlT9XU+bI4SEpbDoj0CUuRtXzAJ17JMTCER5hHrixo11jCXU+eckLJscz5gxA+np6aIy++KLL+p+tly5crjiiivw77//4p9//rEaFQ6Hw+Gg5DijYHLddddh/fr1QX2nFkaEQCWBoG7dumG391SPyXGw3hUsjMajuLhY8boeoZfek5WVheHDhwMI/pE1oUTtvF2K0vVAKMF2hUnz367VOreVJ0c/ZuuKnTilzw0llls+3cOSnJyM8ePHG36+adOmAIBDhw5ZjQqH43rK+qAX7AGBze9gHNsTrPI1u4VDb/zk6dyxY4ep95mBxjGQA3i4KbOhwmh9Z/echhql+qUnbqmpqYGITpnGjjqxc+dOG2JiHn/nrqpdD1dFJZy8HIcSrfwra6u3lhXavXv3QhAEXHvttYiOjjb8fMWKFQHAxysyh1OWcVPn6qa4ctyP3YO0UwSqUBOIdlzWBCo5bjvb2gp0ZVSeZjsUFzvq0dVXX205DD04wTOzm2DLtqz3FxxrWFZo09LSAAApKSmmnqcmPm7dc8PhcNwPH0jdh11jRlkpe6PCrhXh2GzZOF0gN1NXws35k1k/AUrXg1neBQUFQXuXEnziLPxx2mRGWatzliWC8uXLAyjZN2KGkydPAigxWXYTR48exZgxY9CsWTMkJCSgUqVKaN++PSZNmoScnBzb3rN06VL07dsXtWrVQkxMDGrVqoW+ffti6dKlusMoKirCxx9/jGuvvRZVqlRBXFwcGjZsiOHDh4fcDIfDAULX8do9kRZMAc1tgrBd6DE5drpi5ER4nkmxo28w00blfSGf7JcSDkK6Hi/YFKdsYwkGbk2LP3PyUOG0+AQay06hatasidTUVFNOnQoLC7F27VoIguD3iB8n8dNPP2HQoEESxys5OTnYtGkTNm3ahFmzZuHnn39Go0aNTL/D6/Vi2LBhmD17tuT6yZMncfLkSSxatAhDhw7F9OnTNQe81NRU3Hrrrdi4caPk+qFDhzBjxgzMmTMHU6dOFY9Q4nCMEg6CcFnr+K0SSsHjxIkTku95eXkhionzMdo23SpQynGTqa+/uIZD/2oVu89HDjV2lmk45AfFKU6VykKbC8c0Wp766969O4CSDffyYw788emnn4pK4Q033GA1KkFh69atuOeee5CRkYHExES8/vrr+Pvvv7F8+XI8+uijAIB9+/ahd+/eyMzMNP2eF154QVRm27Rpg/nz52PDhg2YP38+2rRpAwCYNWsW/vvf/6qGUVxcjL59+4rKbL9+/bB06VKsX78e77//PlJSUpCfn4/hw4cbWvHlcDihJ5wEGSPIB+L/+7//C1FM3IUeL8fhVqfcILQ5Pc/tmuTQKgs7PQPzFe3AEYwJL7eUX7hM/oUTlmvOwIEDxc8jRoxAfn6+rud27NiBcePGAQAiIyMxaNAgq1EJCk899RRyc3MRGRmJZcuW4fnnn8c111yDG264ATNmzMBbb70FoESpfeedd0y9Y9++fXj77bcBAO3atcOaNWtw7733on379rj33nuxevVqtGvXDgAwadIkHDhwQDGcOXPmYPXq1QCAkSNHYuHChejVqxc6dOiAJ554AmvWrEFSUhK8Xi+efPJJ7tkzTHC6gOREBEGwZSB1gwAdbly8eNHnGi8H9+JEQZGN0/bt23Httdf61DGleGv1xW7ZW+uEeLB55dYVbfZoF7eaHAejLji1/OQoObNyygozxYl9aSCxLMG1a9cO/fr1AyEE69evR48ePTSPcMjNzcXUqVPRtWtXZGRkQBAEDB06FHXq1LEalYCzYcMG/PXXXwCARx55BNdcc43PPWPGjMEVV1wBAHjvvfdQWFho+D1TpkwRlcsPPvgAcXFxkt/j4+PxwQcfACjZHzt58mTFcKhSXKlSJUyaNMnn90aNGuG5554DABw4cADff/+94bhyAoNbOnW7CdWA4AShzSihrCNumUXn6Mfr9YZcACKE2NoWrdRTNe+rt912G1avXo3169eHnSlssNHbh4WyrzNarmptKBj1I9DvCET/4JR2E44yl1behmN6bZFKZs2ahWbNmoEQgrVr16JVq1Zo0aKFxIy1b9++uOaaa1CpUiU89dRToqlxmzZt8O6779oRjYCzaNEi8fOQIUMU7/F4PBg8eDAAID09HStWrDD0DkIIfvjhBwBAs2bN0KlTJ8X7OnXqJJ7h+8MPP/hU3H379mH37t0AgAEDBiA+Pl4xnIceekj8zBXasoeb9poFAruPknBzXnA4LE4RNK1gd3v0er1imHqVZbdP/oR6ksMooc5vs+3Gbflc1lEqL16GocWWll+hQgWsWLEC3bp1E2dYd+3ahcOHD4sF/OOPP2LDhg3Iz88XG/wNN9yAZcuWISYmxo5oBBxqvpuQkIC2bduq3nf99deLn9esWWPoHYcPH8apU6d8wtF6z8mTJ3HkyBHFuPoLp1q1aqJDLqNx5dhPq8JCLAcQq2HloEVbAMuKioBNmzTvWQ4AmzahTXExlsuuye9RenYQ8znum290vUtP3L88c0bxXjactsz3/wHoIouXPH5seOw1r9eLxa+8gg0AZmzbhk5btmADgA3sM5s24fnS51aV/ra49PuizExg7lxsALCj9Lf4Xbs000zLN9qgvwEAuNrrxVel714J4NrSNs/mx0Ol/19h8oL+9iLzvV9pfDcx92HTJgwsLsYGAONKrz1CiPj8htJnfycEQ6dORVsAvxUXi/WI5t2w0rDkZSK/dl1BAZYDuEshv9g0sWWBG27Ag6XXE3/5BQBQ2+tFx9Jrg0v/C5s3S8IYBOX6vQFA+f37fd5HPz8qC6MFk/+YO1e9sEIAmyaaTq/Xi/al14U33gBuuKHkt02bcEvp9ZGl/z1btqDu+fNiHtY6c8ZyfD7au1dXX0TLp92uXah7/rxPW6blUot5BnPnSsptA/O5f24ulgOI+fdfxffI6wMbH1ofqx4/Ll6/Ki8PywFUOnQILUvrbULphDENu8Y//6AtgHmnT+O20uvT9+5Fwu7daAtg/rlziu/77tIlyfUW+flYDuCW0jQk7tmjmn968lRP36vF1V6vpB+R9I8K7/7s2DHJ71dkZ2M5gCpHj6o+82NWlmJ8m2VlYTmAlGPHxGtNMzP9po/21/K+R6kerMDlNkCvrwZwfWk5ND98WFLn+hUV4b7S7y8zYYr/d+7EcgDXM30nNm1C55wcLAdwdXo6GqWnYzmAnsxz1x05IsnjNqX1TK1fpHG96exZ9C/9TPNJ73iuF/p8j8xMtC2NH60Ham1QzPvSdiq/VvP0aSwH0PjSJfEdy4qLUeXoUdUw5XWvLYCBpb+9BN+yUJNf2Outi4qwHEDUP/+I7bziwYOq91Nou1gLoOLFi2gLYNahQ5bbm1GoDOfZskW8di1K4l2t9Bqb/7TsKvzxR1DjGRSIjXi9XjJ37lzSpk0bIgiC6l/z5s3JnDlzSHFxsZ2vDziVK1cmAEirVq0070tLSyMACABy9913G3rHTz/9JD47efJkzXvfffdd8d6ff/5Z8tuYMWPE37Zu3aoZzh133EEAEEEQSFZWlu64Xrp0iQAgly5d0v0MR5uZcXGEAOTCoEGmnn8PIAQg5Mkndd3zYUQEIYDPc2rh0OtbmWfymze3FB9CCFmxYoXmvexv7zHvPgSQj5jvWxXix4bHXjt58uTl7wA5FhMjfhafeeIJMpMNCyAX2e+tWl1+BiBn7rlHMx0z4+NNl+8HHg85zqa9fHkxTfTaP6X/9zN5QX87x3xfwcR5KxNf+jz9fbEs7fRzgSx/p0VGivcsYcpJHj57bXbp5z9VysknH594ghCAbC+9frxhQ0IIIfd6PGSa7F15w4dLwtgqC4tN095bbvF5H/28SxbG/+Rl7yDYNNF0FhYWkqk0TypVuvzbE0+Qz2R1JuuRR8jvV15JFpV+/+vqq03H5cMPPzTUF9HyOZ6cTH6/8kqftkzDuVOW/5JyYz7/W9qvpQ0erPgeeX1g4zOf3nP99eL1z0vzbs/NN5PZCQmEAOT0gAGkuLhYDHtd1ari56VMXE4PGKCYF4cOHVK8/ln58oQAZFVpGk7cdZehvFer82bxGSNUwvzuu+8U0zO/SpWSetatm88zZ8+e1YzvV1WrEgKQLdddJ177unp1zfT9888/qn2PWj3YK/ueBZAvSz+vKl9eUue+AshCWuZMmPT/icqVCQHIPFmf8l1pH/ldTAz5qX59QgDyDaT9OZvHH3k8JePrY49Jylaehv0JCWRB6ect114r3qfY35msC/T5P6OjfeqBWhsU8760ncqvrWnblhCAfF+3ruQdO2+8UTVMpXHiu9LraxXKQk1+Ya9/XDruZwwZQj6vWLGkPvTq5Tffppa2i2KA/K9RI8t5bJaPoqIIAUjOo4+K12jfvqFaNUKIQp8AkMP16wc1nmYxomcgUJE4ffo0+e6778jUqVPJ66+/TqZMmULmz59PDh06FKhXBpTc3FxCFcTevXv7vT8hIYEAIJ06dTL0no8++kh8zzfffKN57zfffCPe+/HHH0t+u+eee8Tfzp8/rxnOqFGjxHv37NmjO65cobWJI0cI2bSJkM2byTlBIAQghZUqEbJ5c8n1I0d0P3+GdlgpKdLn2XfQe5KSSHrpZ/G5cuUImTJFGs7ixYR8/jkhs2eT1NLrRcwzXkEg5LXXCJk8mZDVq/XFRxb3jdOn+977008lf2ycExNJGi4rZ8UAyQQk8SIA8QIkg3mGxu88vVa+PLk0bhy5xHTwxeygGRtLinv1IrkA+YXNn9J3ZLP3Mn+FcXGXw0xO9k2H0fI9cqTk2ZdeIuml8TjDxrdTJ5LLpL+Y+U/zgqbZW/o/ByD5SumOjBQ/Z5X+zwBIGnNvKhMWrTskOppcYO7JBgiJihLzn8aDxMSQTOYajZcYl3LlCHnpJUJee42kyevk0KGElE720DgWAIRcdRXZj5JJBvZdxRERJJeJu5jG+HhCxoyRlGd+dDTJYOJDEhLEtBXL8vsYcDmtgkDImDGX630ooPVj3jxJmki5coSMGEEKH36YnJXnQVQUIZGRYnrz6O9RUSTH4xHzMiM2lpB580rC99cHsfHZtIksGD9euy+aNYuQoUMV222OQl2m9XMjm/+l9fQi813eDgoTEwl56imf94hhJiSUCKAvvkjIlCkklQk/Oza2pN+YMoWkl7bbvIQEcr70c0FcHCl+7TXx/dlMfWPbZFFc3OW2kpws9qcnZs26nEfJySV5PXkyuVAafi6t54mJJc9o9RW0z1282CetpGJF/89rhEfTJKlf5ctfrhurVxOyaRNZ8c47vumZN49cLBX8s8uVu1wPSp+5OG+eb3yTkgiZMqXk2VIlMCc+viS8KVNIRml4PumbPZuQyZPJobFjfcOMjSXZuNxnyeuB0n/aV+UwZUn7RNrHZ+HyOCPvZzPZuhoXJ/apmQDJLC3jLKbOeCHta+mzxYmJJfXztddIOnzHumImDrnR0YS89trl91asSMi8eZe/q43DfuoAHW/zZO1Nnq+E+Z0dTzMUruWUlm1GRIQkjvkxMSQDyu2aACXj+ZgxhAwdSi4xecb2BWJfnpRUMqZMnkzI4sWK9ZM+X1S+PLlIJxHi4pTz7aefSvquefPEftULkJUREZfvpeO+kfZmFEbGOltal4qTkkr6K6b8cwBCunUT62sRk48FACGDBpXUrVCNXzowomcIhBAS0CXgMOH8+fNISUkBANxzzz346quvNO+vWrUqzp07h6uuugr/lpo96WHSpEmi9+elS5eiV69eqvcuXboUt956K4ASB1BjxowRf+vduzeWLFkCoMQRV2xsrGo448ePF70zb9q0SdWcOj8/X+LFOiMjA7Vr18alS5eQlJSkM4UcH5h9F16U7AMgACS7MbSaqcLzEATtZ2SIzxkIR/6M5j3ycOhnG+LO4pNvNqEnrUbC0V2+CntytOISqPRbQS1Oqnkh+11veP5+0xO2pXtDMZQqtR8Zavmsdp1+N9QHacXHQnsOBarpL8WuvsBfWKp1efNm32sKY7ah53WEZ6i/V8Bf2zTad+m534n9oaPQqgsa2+qchJEyDlbblaCnvRmFKRuleJiq9/J4NmsGqPjeCSYZGRkoX768Lj0jMkhxcj15eXni5+joaL/3033Bubm5AXsPu/dY/h67wmGZOHEiXn31Vc2wOCaYNw946CGgqEjsmMTOKDIS+Owzw8+LAiT7fOk9Ssg7RJ9wdDwDAHjsMaBLF33x8Rd36tzDgGOXQAkvlgZBJh2Gy3fePGDwYEkeaMXFicKbWpx88kLld73h+ftNT9im733sMQMh2ghTP9TiqZbPatcF+XWPR/9+Yb190QMPOFbJ9Um/DDtdDplqyzoVDavPy9GTbit9k9G+S8/9TuwPHYVLlFYtjJRxsNquhADnsVI8TNV7eTw3bwauvtpMSCGDK7Q6YVc4CwoK/N5PVzLlR+7Y+R52tVT+Hnk4Wiu0WuGwPPfcc3jmmWfE73SFlmOR++8HrrhCueNbv95/p6L3ebV79DBvHuDvrOh580riovUueXq04r5xY8l/tw+6WunwV75a+cNxBmy9DzbBqB8bN+oXbILRFwWC114DXnzR2e+bN68k39TYvVu7j/b3vNHw2DD13GvlGb3hHj4c3HJ0K3rrgt1lFCrsat/z5pX815MnRtubUewqm9deA0otPSU0a2Y97CDDFVqdlCtXTvyclZXl9/7s7GwAQGJiYsDeQ9+h9B55OFoKrVY4LDExMa7xSO1WigFEACCCAMHECgZ9Hh6P6sqmeI/GNbVw2PvEuEJ9RlBPfPTcqxo/A3GRPGfQDFIpz/yikQ4z5UufVUqr/JrSb0awwzTLn0mxTzpkZaIWb600yn9TC0NPG1C7bqfZmp34i78/k2P6n163mk4jfZFSHVEz/VXdHqHxrFb7AADUr+8THnsP+w55WIbyieZF6fuU8kitXHDFFbomFlTblc7n1cJTrF+yMDXTQ/s8lWeU+gGfZ6FQPmz61MIsRS1v/ZmZy1FqI1r9shXkY4VWm/GJV2neiN9puRisC/7SodfsVVecNcLUerdSWYhotDeltPm0bTbfZO/QvDcIK5xKMoU8TzTzsn59163EqmF5XH744Yct/Q0dOhTPPPMM/ve//+Gbb77xOX7GKcTGxiI5ORkAcOLECc17L168KCqJRlcwa9WqJX72957jzLEC8veYCUcQBMlznCCSkgJUq4btkZEYDiDvyiuBatVKrht4fjOAkR5PyeqH/HnmnvEAEBWFAgAZADYDGA6UdMIez+XvNJwmTcRn30BJJ07vIUDJwFl6/JP8XZJwlNKTkoKCSpWwGcBzFStK75XHOTISBaXvHl/6bgJgO4BLALJL/xMAhcwzqFQJqFLlcnxatgQRBBQAOMWEcwTA4dJoEQAFALJK3zcBJYMHex0AigDkl/73su9VSIep8k1JAapUwd7SsDcDGF0aB/p+mv6c0v9FTJrYcqJ/xQCOl/73oqQOgPntSGkaikrf8wbz+T9MHkwqfa6QybvC0mu7IS0Tet8bpe/8tzReF+jvLVsCVaoAlSqJZTwcACIiSupXo0aAICCXhlu6lYIovIuW0/bSMMQ0XnEFIAhi2EdKf2PzicYzUyX/tpfmPwDfeh8KSusHmyZERQEVKoAIAraWXi8ShJL4lu5zpfl/CZfrLWGunxCEkvLQ2wcx8clOSirpK+rUUe+LkpMl7Taj9P1FpZ9zSuNFyxuQlin7/XlcrpPjmWfyGjQAPB5J+5CEGRFRksYmTYAqVVAA4J/S8M95PEByMlClCnbGxmI8AG9EhJg/OfXqie8fj5I6VwDgc+bze5GRYl/0RlKSpD8tKi2zMQkJJderVAGqVMGO6OiS95fGMatBA319Be1jIGt3LVsaG0tk4e2AdIw4DpTUL7ZupKQgr0IFbAbwUkqKJD274+NL0lO7tjQeKSkorlIF20vDl8S39Nk9CQkYDuBsrVritYPx8erpa9IEhYLgmwcej6SfoPUgr/R/Pi7XC7YevoHLZTm+NFtoOMMBnEZJ2bL5Q78X4fI4BSa8Itln2r8S+Pa14wEUN28u6ReV2gwdc1JL27fYRlq2FOu/33FYCdn4S/vV45COk7QN0DTQ8qTjitK14tJnDicminF8TBBQXFpW8jDHg6l7lSoBlSqhEMC+0rSdYt4j9uWRkZfbt1weKa1P/0RElLwnMlLMx/Q6ddTzrbS/pf3qcZTUne0AXqF130x7M0pp2WzzeErqXcuWJfkiCNhVGrdzESWq+u7SfPGipG7RODti/LITqx6oBEEgHo/H1r/OnTuTH374wWrUbOfaa68lAEhCQgIpLCxUve/vv/8WZceXXnrJ0DsOHjwoPjt8+HDNe4cNGybeK/cePXv2bPG3+fPna4bTpEkTAoDUqVPHUFy5l2ObycsjVVNSCACy499/CcnLM/w8ABIZGUmI16v8fOk9AAjJzSUVYmNJNKPrEK+XkNJyFb/TcJhnE5lnju7dS4hSHWDfpRafUv787bfLdVB+ryzObHwTmbhEM/8rMd9Jbm5JeLL4nNy9W7ynZ/v2ZMSgQZd/T08nn73/PolmwqFhJ5b+r1qhAiE5OZL3rlm69PJ7FdJRrWpVAoDs2rnTWPnm5ZHoqCgSz8Sl3x13EHLunOT99H9UaTwryeJeiYk/vUb/yNmzJDkiQpLeOIV72c8RHg8h6emkYlyc5D0kPd0nTuTsWenzkZHSZ2h+5eVJ62RuLiGXLpEJr71Gfv3uO/H+5b/9Rsi5c6SKx+PzrvO7dknqaDT7DqZ+AyBfz54tuZekp0vyhV6neSfel5OjXO9DAVO32Tqfe/aseO38mTMl8c3NJYS5HlmarqP//kueGDxYvP7Mk08a74NK+fi99wgA0rZtW799EVtuox94gDw2aJB4jW3bJD1dUp/JxYukAvOdrdcplSuTaIDs2b1bLG/FMGnfUBoftrynTJok1scrmzcnAMhXn31GataoQQCQv9esIfknToj3v/HiiyQaIPXr1hXrTqtWrcim5ctJNEBq1qwpyYtDu3cTACQ5OVlS9xs1bEgAkCrJySQaICv++EN/OSjkqb++1194cbIxAvJ8K2XRggUEAGnSpIkkPW2vvpoAIB9OnerzzMlDh0rSmpSk2A907NCBACCT331XvNa1SxfN9O0olb8k9+Tm+owTicx/QVYv4gFSMSaGACAD+/a93KdfvEgqlvY3AEisQj/x7JNPloQhCJfz6+xZUq9aNQKAtGrShNzVq5dPn3r/jTdK4lw5MZEAIBdSU336Rfb/jV27it/ffuMN3/FbbTw3UAfo883q1vXpK9nvibI0RZfmmdK1F556igAgN990kxjHiIgIMnfGDMUwfepeaX4IpdejFMpC3r598iEvj1SqWJEAIId27SKtmjYlAMiXX3yhnW95eSQmOlr8/f7bbycASPPmza21N6Pk5ZGkcuUIAHL61KmS9zLxfmPCBEKOH/cZ6wGQpQsWOGf80sCInmGL5RQhRPKndM3I7+vWrUPfvn3xyCOP2BE92+jatSuAEhPdzRqey1atWiV+7tKli6F31K9fHzVq1PAJR4k///wTAFCzZk3Uq1dPMa7+wjlz5gz27dtnKq4cm4mJuewlVBBKvht9nqL2PHstNhYFHo+40ic+x3qSY8NhnmWN4UlMjPQZI/GhYbCOy+T3yuPMPJfFxKWA+Z/GfEdsbEkY8vgkJYn3ZEdGoog1yy9fHkXx8Shgw8HlldkCAAWCAMTFSd7rTUy8fL9SOsyWb+mzOey10tln9v30f2FpPNNkcU9j4k+viWlMSUFmRIQkvXmlq9jsvZLPggCUL48Cz+WhpAAAypf3iRNSUqTf5c/QPImJkdbJ2FggKQn/ffFF3Nyvn/T5KlWQXjoLLSmH5GRJHZXEV1ZXvQkJkntRvrw0X0qheScSF6dc70OBvC7ROs/Eb/nKlTh84ULJb8zqQRFK0kXKlUMeG05kpPE+qBRvVNTlL376Irbc8hISUMS0KUnbLl9eUp9RoQLSma9svQbt15jyVgyT5lNpfCT1Lirqcr9R2m6LIiOlbbhKFfH24uhoFACi5UcBSuQcb7lyin2Ch/VXwdR9gbYLNg16y0EhT02NJWx4TB8gwuab7N1g38mkx0uI6jMFpXkq7wfEvGCuQdYn+aRPVt60nOXjRBbzn0BaL3IA5Jf2K4WlVkEAgAoVkBVx2UA1D779hLf0/gLmPqSkiH1kYWQkiphyEuNTOt6I1xXSrtTXFzB9tiAfi7XGc70w9xdERPj0lex3cWxk41mhguK1Ylr/ZXH0RkcrhinCjOcFKCk7oGTMk5eFvH2LyOoTvbeQlpm/fGOfA5CnJb8EEiWZgo23xwOUWl3KxzRvYqJzxi+bsLyH9tNPPwVQYrb6+uuvIz8/H4IgoGvXrujYsSNq1aqFxMREZGdn48SJE9iwYQP++usvEEIQGxuLF154AVWrVkVaWhq2b9+On3/+GZculRgYffbZZ6hcuTLefPNNq9G0hTvvvBMTJ04EUJLujh07+tzj9Xoxt9QjZIUKFdC9e3dD7xAEAX369MFHH32EPXv2YN26dejUqZPPfevWrcOePXsAAH369IEgO96jSZMmuOKKK7B79258/fXXeOeddxCv4IL7M8bDat++fQ3FlWM/8nLkBAdBEHjeuwyPx5b5WNN4vd6Qx8EI9957L6KjoyVOALVwU9pCAc8fZ0IM+ibwRyDKWWmssSPedqe9rGFWBqDPhTL/vQZOgzBzvxuw3FIffPBBNGvWDFOmTEFBQQH69OmDgwcPYtWqVXjrrbfw5JNP4uGHH8YTTzyBN998EytWrMChQ4fQt29f5OXlYcqUKWjZsiXGjRuHefPm4cSJE3j88ccBlFSOKVOm4NChQ5YTagcdOnTAtddeCwCYPXs21q5d63PPO++8g927dwMAnnrqKUSxM9UAVq5cKQrPDz30kOJ7Ro8ejYjSmaInnnjC5yid3NxcPPHEEwCAyMhIjB49WjGcZ599FgCQlpYmnm3LcvDgQVFBb9SoEVdoHURZG5hCLRyaze81a9ZIvgdzkAhEHXGTUh+OA3Kg0fKcL1fQQ5G/hBBb+gJajwOZBr1hq7UpXn/1E8q8MvpuPfXXSN/t7/1u6rNZnBZvr9cbdnJXWetjLI8caWlp6N+/Py5evIiHHnoI33//PerWrav5TJ06dbBw4UI8/PDDuHDhgvg8ACQkJOD999/H0KFDAQBFRUX45JNPrEbTNt577z3ExcWhqKgIN910EyZOnIh169ZhxYoVGD58uKg4NmnSBGPGjDH1jiZNmmDs2LEAgE2bNqFLly5YsGABNm3ahAULFqBLly7YtGkTAGDs2LFo3LixYjgPPvigaEb84Ycfon///vj111+xYcMGTJ06FZ07d0ZGRgY8Hg/ef/99REZyp9cc49jRaTqh4z18+LDhZ25VcnfPCTlG6pMT6l6gCOe0aeEUwdSOeLitDOVp1qO42FleTlOU9OK2cuZcxo1l58Y4+8OyBjNr1iycPHkSSUlJ+OCDDww9+9577+Hbb7/FyZMnMWvWLFGJA4DXX38dc+fORWFhIVauXGk1mrbRpk0bLFiwAIMGDUJGRgaef/55n3uaNGmCn3/+WXJ0jlFef/11nDt3Dp988gm2bt2Ke++91+eeRx55BBMmTFANIyIiAosWLcKtt96KjRs3YuHChVi4cKHknpiYGEydOhW33HKL6bhyOHYRKkE0KytL0eJCC9YnACUcBwmOMm4zOfYHr7vqKClJHo9Hkmd2K1JOUcqtopUOvXXOKe1s4cKFKCws9H+jBl6vN2BKN2/D1nDrZAigXPZOaTfBwnJqFy5cCEEQ0L17d8U9mlokJCSge/fuIITg22+/lfxWpUoVtG/fHoQQx5gcU26//XZs374dTz/9NJo0aYL4+HhUqFAB7dq1w5tvvomtW7eiUaNGlt7h8Xgwe/Zs/Pzzz+jTpw9q1KiB6Oho1KhRA3369MGSJUswa9YsvxW2cuXK+PvvvzFt2jR07doVycnJiI2NRYMGDfDoo49i8+bN4mo4hxMqQt3xWhVSjGKH4OEEgdcJceAYZ8eOHX7vcXPZOsnk2Cqh7huNYkYpMPJMsJUONv/79+9vOhw23kptS629OcnkOBDvcko/E46TAeGYJi0sr9BSM72qVauaej6l1Nuikrlfo0aNsGbNGqSlpfn8Fmrq1q2Ld999F++++66h57p162aoAd96662WzRojIyPx2GOP4bHHHrMUDid4BKsjsmOAKmudphY8L5wBNznWpkWLFj7XApEPRoVVJ616G1E6tO5hT3YwQjCU8kCgZnJsRXEJZR4UFxfbGh5fydcm2BMWSu/TU9/cvJobrlgeObKyShxsnzlzxtTzZ8+elYTDElt6jEYse5wGh8OxjXAbDM0S7HywQ2h3Qtk5YVAPVRzcpmgYxQll62SMtmF5foZ7/TGCWl8WrnUwUF6Ow4FQ5oPV+uamMnRTXPViWaqqXr06CCFYsWKFolKqRWZmJlasWAFBEFC9enWf36mjqMqVK1uNJofDcTChEFxCuSIVLsKsEwZFpTgYyV+nrAgGAqP1zJ9ZpFGMtmtCiK19gd31k42bWt6qxd8JbcVtuDHP/NVfM1YLVt7H0YdRL8dOq5t8D60NCi09ZzUrKwujRo0y9Ozjjz+OzMxMACWmuHJ27twJQRBEs2QOp6xgRuGxeoxEWcZpg5Me3BhnO7Er/WYnF8JlUoLiBJNjs88EgnArXyfiBg/5RuujU+qvW+HyiX1otY1w7N8sK7TDhw8XZwHmzZuH22+/HQcPHtR85tChQ7jjjjswb948ACUVeMSIEZJ7Tp48iV27dgEAWrZsaTWaHA5HgbK8hzYQ8XZrXrgZs3ugOL7YJYybXRlwujKgx6s593xuH1y5MYbT24/TMeucjLdxZ2DZKVT79u3x9NNP45133oEgCFiyZAmWLFmCDh06oGPHjqhduzbi4+ORk5ODEydOYP369diwYYPkyIvRo0ejffv2knA//fRT0fyoZ8+eVqPJ4XBcAB+QQ4sbBUirdcas8hVuQow8PaFw4mN3nloJj60XbLtQayNK9ciOI2s42gTKkZjZvtDsc2a9HAeTcPZyzGLWgVsosduU3Y1YVmgBYNKkSSguLsaUKVPEaxs2bMCGDRsU72cz/qmnnsLbb7/tc0/FihXx8ssvAwB69+5tRzQ5HNfgps7GjriGeq9HqM1XOfbiRCEpFFjZQxsK7DqjM5CeZM3WLb3PhboM5NgVHyt9Yyjbs13vDlS5BnOl0M5ycFo9D+T5wJzgYItCCwDvvvsuevfujRdeeEFcgdWiffv2eP3111VXX43ux+VwwoGy3qEGU3DhSk94YLXNOGU1MdTYKdCFwwRVqMrXaf2SVUXcSp3S86xb2mEwyjXU7c4IND+cKPO4pU5xpNim0AJAjx490KNHD+zatQsrV67Etm3bcP78eWRlZSExMRGVK1dG69at0a1bN1x55ZV2vprDCSvcNJvt1s7f7Xto3ZrvFLvqqVUvx5zwxa56oMfk2Gwc1NqB0xTbQOAvjW52KmYUO0yO3djvubW8nIYby95ubFVoKc2bN0fz5s0DETSHw1GBd2jBJ9Dmhxx17KrvfA9tCfIjc0KRvkAooHbDtl2zyqrWs05bsbIrPoEy3XVLO6TxdnPfb2fddFo9t6MehaJs7d6z7WbcY5/A4ZQhrHQ2wR4o3HD0gr93BnK1MFC4fUAKZD0NxqqGGwRpN8TRLKHYLxiIdwbCVNeJmElPuOWBFmZXaMtSHjkVJ4zF4dzX64UrtBxOmOGEzrUswPPZGjz/nIWdXo6dghUhz6iiqXSdEMJNjksJVHrcJsgHslzdWGecGGcnxslu3NZu9MAVWg7Hgbips3Fr5x/KPbRuNW9yC8FoP25qo25C74pTqDy68nZnjECvIDrNs2+wTYvDaYU21N6sg31Uk53oORM73AnIHtqsrCz8888/SE1NRWZmpu4OZ/DgwYGIDofjGpzQMYaSstYBOw031T+7BFle50qQn+dpR74YDYM9n94OQjHpoPeIn7JmSqqU3kBMALphoslI2fprD+FWT4KNUv7pqUPsc7SM+FgSWmxVaL/88kt88MEH2Lhxo6lZLa7QcjgluGmFyQ0ChBJu83IcboKLU/bQOvkdVgmEya1T0JM2KwKmHqdNSveo5ZsZ5T4csLseBdsplNlyMJrucClvOWrlo+aML1RHD1k5tswJfaWRvihcsUWhzc3NxYABA7BkyRIA2g1TEISwbbgcjlWsdEBmBnandXhu6xvM5p8blKFAY7WseR7aj9Kqg13hBZNAvVdPnsjvcVufxrFGKM+CdVOfqGaaHew0mF2hZQnlCi33cnwZWxTaRx55BD///DMAIDY2Ft27d8fhw4exZ88eceU1MzMTR48exfbt21FYWAhBEJCQkIB+/fo5TqjmcEKNm1aY3DSIsoTCy7GdfV04Dkh24ab24xQCkR6jddTKKolaeGZh464nTnYpMvRd4XDMC6AvHWq/KeW7W4/toajt1bTjHFonoscpmhPS6HZrFr6H1gaFdv369fjqq68gCAIaNWqEZcuWoW7dunjiiSewZ88eAMCnn34q3p+RkYGZM2fif//7H7KysnDu3DksWLAA5cqVsxoVDidsCEZH5IRBhOLGjtdMnN2YzkDhBCEAcFY7CBeCsWrghnIzs6LrlHbhJNxUL+w6hknv/by+cMwQ6nYSCCxPKc6ZM0f8/Mknn6Bu3bqa9yclJWHMmDHYtGkTqlevjl9//RVDhgyxGg0OhxMi3Nox+luhNbPi4ta8CAVWlftQTw6EW1nLV0ftWt0MJcEsI6OKRbjVH39YcQplNFw7sbsu612hdUobYjGjPBstHzfuoXUCfA+tDQrt6tWrAQANGzZEly5ddD/XuHFjzJkzB4QQfP/996LJMofD4SaTTiCQ+cOP7QksvG6XEOp8CLXjr0Cn30gczB7/4jbsXHHWY3LsFgLlb8Hufe+hgE1jqPsswJ0O3JTiYMXLuhuxrNCeOnUKgiCgTZs2kutsIysoKFB8tkePHrjyyisBAPPmzbMaFQ7H9QR6sD58+LDtna9bO8ZAHEuiV/hwa57ZidW6Hqg8DOZZwk6CEGL76kioBD07+lGzK4pltX/1V3fM7KGlaOVBoPMnKyvL1vD0nm+sd6xwev1Yu3ZtqKOgCZvPbvRyrPXujRs3Ij093VB4Xq8XOTk5FmMVGizvoc3IyAAAJCcnS67HxcVJ7qlcubLi81dffTV27tyJzZs3W40KhxM2mBmk9DxzxRVXSO63oyO2U4ALpgBs1SlUqGdlA/F+Nw7oShjJm1CXYzhi1qGR3XslrZSt0nmyCxYswIULFwCUOMOsV6+eeM/nn38O4LJMBJScAEHjmZeXhwkTJqBSpUq45ZZbJGEvX74cLVq0wLlz58TnqSI1atQoVKlSBa1bt8bdd9+Nq666CklJSYiOjhbDKCoqwrZt2xTTO2nSJDzwwAOoVKkSioqKEB0djTNnziAzMxNVq1ZFpUqVDOfNtGnTMGzYMERG+oqQxcXFyMnJQXx8PIDLdcGoYK2GUl+TkZGBLVu2ICcnB4WFhT6/X3/99Ybfk52dDQBYvny5oecmT54MoCQfKE8//TRyc3MBAKdPn0ZUVJTPc3/++afkOy3/wYMH48iRI6oTBr///rv4eeLEiRKfNZUqVULVqlUlvx86dAinTp1CUVERBEFAixYt0LlzZxQXF0MQBOzYsQNVqlRBrVq1UKVKFcm7Ll68KPnerVs31XzQuqdx48Zi+jZs2IA77rgDQEmbHjZsmGZ49erVU8w/JR588EE0bNgQHo8HFSpUEK+PHz8eTz31FP7991+xXN5//33k5eUBAP79918sXLhQvP+ll15CZGQkNmzYAEEQ0LNnT0n/89tvvwEALly4gG3btqFly5bweDwoKCjA4cOHUbt2bbE9qFFUVKTYnvxB49GpUyfUr19fzEsA+PHHH1GxYkXF5x566CE89thjyMvLQ2RkJOLj45Gbm4ucnBy0bNkS//zzj+G4hBxikfLlyxOPx0OGDh0quf7GG28QQRCIx+MhmzZtUn3+gQceIIIgkMTERKtR4QSZS5cuEQDk0qVLoY5K2FC7dm0CgKxYscLws7m5uQQAiYiIUL0HgPiXmZlJypUrJ7kmv0/refq3YcMGv+/zx19//UUAkGrVqvkNRykOWn9q4fzzzz/i9/r16/s8M2vWLM1wy5UrRxITEyXXvvnmG800V69e3W+eqRETEyN5180332wqP7TyKT4+3tAzHo+HEEJ88kEpXvJr0dHRfstJqU7Sv59++okQQkhUVJTPb//++69mXWCvffbZZ5LvhYWFutJ+/Phxw2UYSJTSef78eb/lQP/WrVtHRo8eLX4fOXKk6bjMnDmTACCtW7fWHWcAZMCAAWTkyJGqZcd+z8zMVC2bGjVqEADkr7/+Uk2vUhtlf5swYQIZMWIEiY2NVa37drU9rT9BEEhERITi9ZiYGNX4aYUn/x4fH08SExNJkyZNSL9+/cizzz5LZs6cSbp3764aTkREBKlUqRKpUqUKqVKlCqlatarP71Q+pNeioqJIvXr1SJcuXcjVV19NWrdu7ROnuLg4Eh0dTVJSUkhCQoIkrZUrV/bpN8yk2chfvXr1DN0vH1P1/kVGRqr+VrFiRZKcnKz4G9tnJyYmSvriWrVqKdYPQRDEv0DX39tuu83nWmJiomr7kdcj+V9SUhJJTEwU64YT/uRpEQTBJ36CIJDY2FhSsWJFUqlSJVK3bl2fsqG6kMfjIQkJCaRBgwakS5cu5JprriE1a9YkcXFxJDExkVSoUIHExcVJ3hsXF+dThzp37kzuvPNOxTjXqlWLNGzYkLRt25Y0b96c1KhRg1StWpX079+fzJw503TfbzdG9AzLK7S1a9fGrl27xFlLSpMmTcTPa9euRdu2bRWf37Vrl9UocDhhh5scsjjd5EmNQDiFcjv5+fmhjoJuQmmG6BbKej5YSf/rr7+O3NxcVKtWDbm5ubh06RImTpyIDz/8ECdOnMCff/6Jxo0biytgb775JsaPH4/KlSsjNTUVQMkKWcOGDbFx40YkJCTgt99+w8mTJ7Fq1SqsXr0a27ZtQ1RUFEaPHo2zZ88iOTkZCxYswKlTp1ChQgWkp6dj6dKluPnmm7F3714sWLAAZ8+eRVZWFk6dOoVz586huLgYDRs2RKtWrQAAr732miQdixYtwvfff4/8/HzExsbi6NGjSElJQf369XHhwgUcOHAAp0+fRkFBAY4dO4Z9+/b5zZsPP/wQM2bMwIULF8SVPrp6FxkZiUGDBmHPnj04ffo08vLykJ+fj3bt2qGgoACHDh3C8ePHERERgaKiIgDS/rdu3bqIiYnBqVOnxFXS6tWrIzk5GampqT5levvttyMlJQWNGjVCQkIC1q9fjy+++EJyjxlrpMTERGRlZaFly5Y4cuSI7ucef/xxTJw4ER6PR4zrnj170KlTJ6Snp6NBgwaoVauWz4rs9ddfL1kNLl++PC5duoQdO3aIW/OU0nDdddfhl19+AQCMHTsWL730knjf8ePHJc+tWrUKMTEx6Nixo/j8jh078OeffyImJgYFBQVo3bo1Ll68iKNHjyItLQ0A8N///hdASTmcPn1afHbPnj1o1qyZZn4sWLAACQkJkmuZmZl45ZVX8Oqrr+KGG27Azz//jLi4OHg8HrzzzjsYNGiQaniXLl0SP/sr00uXLmHv3r0ASlbG+/TpA6Bk1X3OnDlo3LgxJk2ahIyMDEyfPh0vvPACUlNTceedd+Kmm27CyJEjAZSY7ubk5KBz587wer1YtGgRBg4cKK7C33HHHVi0aBFq1KiBQYMGYe3atTh27Bh69uyJJk2a4Pz58zh27BjOnz+P9PR0eL1eXLx4EdWrV0fr1q0RExODiIgInDhxAkePHkXNmjVx7tw5nDp1SlydFwQBDRo0QHFxMQoKChAfH48qVapg3bp1KCwsxOrVq9G6dWusXbsWXbt2BQDcfPPNkvrAMnHiRM18diOWFdoWLVpg586dYqWhdOjQQczEGTNmYMSIET7L6cuWLcOWLVvEguJwOMHDScKuk+JiBLNnIjoxvdu2bZOYyZUV5GXh5jKUYySObvPyqZU2O/aq5+bm4rXXXsN///tftG7dGv/884/EfBOQTnpR+YbdblWlShW89dZb6N69OxISEnDNNdcAAPr3748dO3agRYsWSEhIwFtvvSU+88svv+DUqVOiSTFNQ9OmTfHSSy/5jbdcoe3Tp48oyOvB6/Vi//792LJlCzp06ICWLVv67KkbOXKkKOxTlixZgt69e6NOnToSs9euXbtizZo1uOuuu/Cf//xH8sz+/fvRpEkTUXkEgN27d4u/X3vttVi9ejWeeOIJ8dmePXtKFL8ZM2agWrVq4vcuXbr4KLRWMDpBTOseq9A2bdoU5cuXR3p6OgRBQEpKiu7w7JxYve6663yuXXXVVbjqqqs0n6MKbWJiouR606ZN/b4zlP1kUlIS2rdv73P9hhtuwA033AAA+OCDD5CRkYFWrVqhTp06SE1NxS233IJhw4aJdbxdu3aS5wcMGICHHnpINFemxMXF4c033wxQapSpVKkSLl68CI/HA4/HI3HOG+zFjVBjuaXQBrJ3715xNgcoWbnt2rUrCCHYuXMn+vTpg61bt6KwsBCXLl3C559/jvvvv1+8//bbb7caFQ4nbHBTR+QGwV6JUMTbTqdQdtcRN63OApfTr6SEubVOhhq7FFqze2idRKdOnURBnmK0Xrkx/R6PB02bNsV9992Hhg0bWj4PVU9dUPstHOoRhc0fI+3MiJdjN+KUsrXiU8MJZWC0bwrHMdKyQnvrrbdCEAQQQrB48WLJb//3f/8nFvQvv/yCdu3aITY2FpUqVcJDDz0kKsCVK1fG6NGjrUaFw+EYwEkrMk7sXM3MjAdycHZKWSnh5Lj5w+wKrVMEMS2MrtCy2JE+o2FYia/V8OT07t1b/KykjBBCLIUfTvVMC7v7Bn9WMU4cS1iMlqeTyj9Q59A6pczM1lVaRqEoKzePvXZjWaGtU6cOnnnmGQwYMADnz5+X/HbNNddg5syZiIiIACFE8a9KlSr44YcfVL0gczhlkUB5Obb6jkCGE2xC6eXYjjyzeyBzazkqwc9xLsENcQwEwRDy5HlLJ8DYfsGq0htOuDUfnKRQhhNqbTRUviucdhauUZTibMYqws1Y3kMLlLiFV+Phhx/GNddcg8mTJ+OPP/7AqVOn4PF40KBBA9x+++0YPXq0j2twDqesUlZn25w4gOgpC6N7aO00oXPCgBTKOIT6HFqO/RipT6E4E1YrDrRtG+3D/cXRLfVRTRHRyg87zGkDnT921yGict6z2nuMpM8JY4IZ2DQ6wRmjnnx0g6zmlr7DLmxRaP1xxRVXYMaMGcF4FYcTFrhphdatg6hb460XuhWkLMJXaEswKgzbJUwqrVYafTbYsOfHqsGmRy1v7W5zbqhngP942mXR4gZFQguj8XfSHtpAmRw7AbePlW6Pvx2EfiqEw+GUecKlMw4nD7lOh6/Q+idU7cqsUmpX3ptxvjZv3jxD7/B6vZZWlsKpnrHI61ygnbe5bYWWE36Ea1t2G5ZXaOlZWjVr1kTDhg0NP3/48GHxrCwll+IcTlkkWCu0dszuurUzz8zM1Pw9kCtFbs0ztxAMIdQNZWjl2B6nC/J2O5v57rvvdD1r1qTYbH46vRysYKYN+ct/u/IrUB6WCSEB83Ic6LoSzk6hnBAHK3Avxzas0Hbr1g3du3fHe++9Z+r5adOmoXv37uKZUBwOhwvkwaBHjx62hxnOwqfTsCuv5eGU5XbhdnNOK2zdulX1N6V80ePwSauOOsmU1E7kaQ50OtzS55rNByf1R8HI61DVeycepacHO48CdDtB2UPrD7d0SByOkwlVh+YGszEzBHIloKx7mA40fA9tCXYfg2M0rEAKp3av/Fy8eFHy3aizJrv3Rhq9z6nY4WmVy4jqBFMBNFMOblmhDUe0rMzCMc/5HloOx4G4ySkU5zLBzNOy6nyG4rb4hoJQ55Fbztzcv3+/rnezZtnyPbRK2KHMhboM9RIIZUdtZdxIGFYxGr7dW1WcpMy71WpAD25doaW4pZ8IJCFXaHNycgAAsbGxIY4Jh8MxQ7iu0AZycHKSkEIpLi4O6vus5oEVc04tysrKmRw702NWqLfr2B6j+1ZXrVplKS6AeprV4hlu9Ydi99FLRrHbsVggsHMPrdl7g4WeSZ9QHtsTzkq6Fk6UQawScoV2y5YtAIDKlSuHOCYcjnNwk1OosoyaR09/97tR8HAqVuuwW9OtByurS3aY1JspGzv7JD3pP3bsGEaOHGkqbL3tXStuwXJyFGqsKCpa5Sj/ze72HKr852NzcGHL2Wzeh7Kthks/YQVDe2iPHTum+ltmZqbm7yyFhYU4efIkvvnmG6xfvx6CIKB169ZGosLhhCVu7JTsiHOolQo35HugBZxgr9BaxYiQq4VZE8ZQ11k9WMmHUGC3h1o93HzzzSgsLDQcnlVz6nCqZ2YJhGMsp+SXPO5mJy6ckh4g8BPtRj1AO4VQ9p1uzK9AYUihrVevnmrHPnfuXMydO9d0RO677z7Tz3I44UagnC9Yud+teL1eU6sDgRy8negUqqioyPSzTlCGOM4h1E65jFhCnD592lD4RsLWEjbDrc3Q/Ai2ybE8DDfkq50mx25IrxJsHrBpDFV67KiLoVQuleKvFZ9wlP9M2YAQQsQ/pWtG/oASZfbee++1J0UcThnFaAdl18DhdGcKZuPnxDgFKhwg+Cu0TjUV1huuGwTJUO+/c8PqwaVLlwAAdevW9Xuv1iqr2rmlVvPVDfUMCI5na8C492mrGE2PG+p8MAlHxUmOW9pouGNohbZOnTo+jfXo0aMQBAGJiYmoVKmS3zAEQUBsbCySk5Nx1VVX4a677kLPnj2NxZrDCXOCNQjwjlidYOxjtopTVmidJsTxel2C0XxwWjlqYadTKACIi4tTDEMtbPn7/VmBhPt5x3RCzEgdonlipd4Fag9toPoQt3j+ViJQcXFCW7ASBzvqsVVCtaDhJAwptEeOHPG5RjvxBx98EO+//74tkeJwOMYJlcmx070cmw07kKZedgwmhBBLSqgcf/sInUaohSsnCGH+MLpCa5dAZlbAs9tRnb/0WxViuTfty9g1AWh2i4iVeDgZt+2DlxNu5aFEKNPopknIQGOLl2MnNiIOx82UhUHASSj1YWZMcIPt5dgpJsehGAPscgoViPeHA+G6lYCloKBA/CwXDJXMidlrXq9X8R65t1Srx/a4pZ4F0u+DkSO67K5zgVAYAqWEuKWusDhFf7BjhTaUcB8qBldolTh8+DAAICkpyXJkOByOefgKrb1h6xmk8vLyTIVtF3bmW6BXaJ06gAb62I9QYuXYnlBgt2DoL/1s+5UrGXrywoozGycIwXZi1x5adoXWzV6OjeIGL8d2Tlqw7Us+URQK3N4e3R5/O7Cs0OpxpMDhcIzBvRzbh550KuW3v+eKiop8lEA3ezl227E9RlZtAoEb2k+onEIFy0GQVXJycsTPch8gaic6qFlZKKVZj5fRcDmH1q4xy+hWD7dMSJltC+Hq5VgNJzgn1JOnSs85rb8rS17WAZtMjjkcTtnFrv2gaoRKQPE3sDphQHCTQhvMcgzG3sZwJNQOdYw8p+def/fk5+eLn3/++WdD75XvYTfqiCrc6pk/Bd3KWb7BPgoo0ITaEsIsZtq1nmecsEJb1kyOwxF3tioOJ8wx0zkZ7VTd0gFadXwUzGN7AiGgaRFqk2MneHVUystgCBhuaD9GHco4sV4GEtbkWL5tSknp0BK81dJs1ZTULXlpNP16wtHTv8jDd+oeWrPhOEFZogQjLk5Ir5s8Bpt9t1v6FSPoMjlu0KBBoOMBQRBw8ODBgL+Hw+HYS6D30FoNP1Amx1YoiybHTh1Aw/k4FSv7Ou3w4m1UiLd7Jc7fPewKrR606ordQq2Zo4dCiZn+IxBtza4w1c4VNks4KB6B2grF3hOqrS9uXaG129Gkm9Gl0B45ciSgM/GEEMfZnnM4oSRYe2jdICwFo6O2y8txMAcVu4/tsTOsUO9hNZKWYK7gOxm5116rYZlFrzmmnjI2YnIsR8/eVqUVW7XnjK4kuq1+mZnEMLOH1t/9ThTs5WNtoJQ2t9UZJZxQfmXBwZsb4+wP3U6hwjHxHI5TMdOpu9nLMUWpn3GTybFenJj3ZoWsvLw8ZGVl+b3P7uM1ArWC5QSByi5C7TE0kCu07JE7ZjG6QssqJl6vVxIHu7d8uG3lJVgWLcGaCDDbv5jdH+sGL8dmcIuzSrfqOG7rJwKJLoWWHs3D4XA4gSDUJsd2PRfsPbR2DsJmFdp+/fr5XLNj5UXvs1ZX18PBFFANo16OA2U2Gwi0ylivkJebm6v6mz9lXL6irRSfsnQOrV2TsE5bobXDelC+L9hO03r5uceBJFDtOZCm+2ZwS5vzh9bkSrikkUWXQsuP5uFwgkswVmidqFQpwb0cq78v1E6hAODUqVM+14Kh0AaqXjhBoLILK32ClXywMomk91k7TOTZY3v0IM8Tts34U1zlygY3Ofbfp9HPERERusO0y5zXLgsS+XetSQ6r73ei92R/7ZQQIikzvofWvXEINc6r/RwOJ2g4pRPUikcgTI71mL8GYh+z3eZBTjA5VkIpXlZMRI2m00hagrmCH2yMrlSzabIiHJs1OQb056ueCRh/YWkptGz6lRR9QogkDmomqmploDedoe6jjR5DpHcPMfuMvzC1FFqn7aFVKm8zcTRj8uxEXzRq4zfNp4iICHFs0KvsBxo3nRjhL652eR93A1yh5XAcSLCcQtlBoDvzQJgcy5UrM8KWFeHBriOB7Mx7sxMHevc9W1Fo2eNVtN6r5zd/OEGgsgujq+5svhlZFZNjJQ/11kOt+/QqA9Tk+O6779a8j6ZHvnrI1mm1NFPBXT5B4G/l1ikCp9542DUhpmR+yuZRsFe27ZpMY+NlRKE18v5Ar9DaNW4B0nahdJ5zsLHSZ9H66YRj7OTY6ezR6XCFlsMJE9zifEGJQO6hVUK+MmPGGZVdq7pmka+oWcWswqmUZiUF1G6FVuv9Rt4VzntojeSDfA+tHSu0Zp7Tq4TboUDRevXII49o3kfLWp4utl4qpVkQBL8KjpppqlOcvdjlF8DMtgG1fNcKw678MluH/a3Q6t1DG2x/DIHC3wqtx+MxZXJsd7swO+EQiLiYQS0OamOAE+JsN7q9HBvht99+w4oVK7BlyxakpqYiMzMT5cqVQ+XKlXH11VfjhhtuQM+ePQPxag4nLHBTZxPouAbC5FjP3jmjHlCNxMWJq+NKDnKMOjChKA2iZvfoAspx00q7FWXHTW3PH0bz3C6TY/peM2HoNdG1w+T47NmzAIC4uDjNZ9VMjtk+wl+85as3/lZuld7tZALhFCoYlkp2h6eWJn8KkNrEhlHHbk7D395yj8djyuTYiWNoKFZo/U32lKUVWlsV2kWLFmHcuHE4ePCg6j2//fYb3nzzTTRq1AhvvfUW+vTpY2cUOJwyi5tXaANlPqqGlndTihkFzIhHSqNY9ebrD61VUC2U4qWUv4EyOba6Qmu2HbhB0bCS51aEM/reyEhjIobWCq28nOwQ1CZMmAAAiI+P17yPnYhiP7MKrVI90lqhpc+qKbRO6Z+NrhQaMaGmecM+o+QUSkvJ9fc92Phbkdfbrpxmeg6Yi4tafqit0Brds20VpYkDoyvoTmirahZjamOAk+qVXdhmcjxmzBjcddddOHjwIAghfv/279+Pfv364dlnn7UrChyO69FjYqUGFQStepk0ih1haK3o2LWHlg1HrnApvcPfCq2V1YNgzC4bjZ8eJV8vdq/QGl0tD8YKrROEGH8o5fmoUaMU75WvIlnZQ0vfazSMiIgI1bKT1ymtMjbaj1asWNHnmtKqLPter9er6BRKXi/UVmLV+mt5nN1QzwD/e4iVUFPqKWa2ddjt5dhoP2rW5FieB3buV7ULO1fM6YQUu4c21Cu0RtLH3hvKvbP++gs7zut2C7as0L711luYPHmy2FCjoqLQq1cvdOnSBfXq1UNCQgKys7Nx5MgR/P3331i6dCkKCwtBCMHkyZORkpKCcePG2REVDsfVWOmkjSq0ThKUlGbqKXaZHGsptEoDmRkFTO8+Mic6hTJjYq0mnCmFZWVgVQpPK+1G6kw4zFSr5YVSHZ42bZpqOHblBc1/owotIUS3QqvVPo1OHNWsWVPzd7bdsmGy9VJNAVKrizQ9/kyOQ41Rp1DyPlyrLFhFRn4/+1lpQkHpfsC8pYkcu/fWs6bnSnVcTal3Un0wExc9Xo5DuYeWbbdm96074bgkGme2nzRi8RIOWFZoT5w4gVdeeUUUbPr06YMPP/wQNWrUUH3m9OnTePzxx/H999+DEIJXX30VAwcORK1ataxGh8NxNVYcgRhVSNgO3Ap2dIxaynggZmLT0tIkv+lVyqxit8mxnXE0KwjqXd2WD6xG8kJr9diMQy8t3LhCqzZZIM9zrT3RdjoZo/ExqtDKPZ4qhUnRKmOj6YiNjfW5prRCy65iy4VFtckqNUXPn0LrFJNTve9XMzPXmsQzs0Lrr23bvSJltC4pxY81VTe6QuukPbRmVr/V6g+7QsuO/6EyOQaMH3Mmxwl7aOWe18vSCq3laYVZs2aJgtADDzyA77//XlOZBYDq1atj4cKFGDx4MIASQWr27NlWo8LhuB4rnTTrWEEvoRaWKFomx1rKrp600jxlFbbz58/7fc6Ml2O9XjvtGIw9Ho+tZsJmFFo1E7FgmBxr1d1gnEPrJNTKzqgwY9e+MLMmx/L9dCzyNGqVsRFl4IEHHvB7j9q+Tj0rtP4U2nAxOaZ5IS9zrfgr9e1KJqBa9TJQJpZ2mxyze2jV9lsrvd/M+wKFmbroz8uufBJL7zvsLmf5ZJXbUFqhBdTHXTem0R+WFdpff/0VAJCYmIgPP/zQ0LNTp05FYmIiAOCXX36xGhUOx/VYWaE1Y3IcrD20/tKjts8MML46p3ZPVlaWeC01NdVvOIGY2bRzwBQEwdYVWrNhKQlUWgqtmVlsLZNjq+bidpsWhgI1hVY+KaOV93Z6xDRrciwIgmoc5GWqNQFjpGySk5P9hsG2W7besXGi7UCvQquWR251CmVmhVZtlVr+bjYv/Clwdis6RlGrv2p7silGVqlZ/DlUsrMemQnLX9/ETmJptX+94RpFabJETzqVytNpK7RaTqHCEcsK7eHDhyEIArp37y4qp3pJTExEjx49QAjBoUOHrEaFw3E9wdxDCwRvls5fupT2UlGoQmt2hZaSnZ0tfj59+rTkN7sUWr17aM0gD9vj8dg2qANAenq6qeeU8knPNX+maCxUodVb3mXt2B61yQi5EugvbXJhyCxmV2gJIaoCrbyus+1ZKRz2vxZqCq1SeIA0D5Xyi/09MjJSNQ5qypw87lb76GDVZ7X0aLVFf3to9ShoTluhVcpvdvLY4/HoMlfVO7ntr6+z89gWO7dCsXto2X5K78SqXZO5bD6bNTk2O4FnB/J6Kt8GUZb20FpWaC9evAgAqFatmqnnU1JSAJgXpjiccMKK0yB/Qr+8jbH7eqxg5x5arRVas7OfNH6sALxr1y6/z+nxcmzUGYSVFXgnKrSCICgKkFacQimliZYdWwe02ogRIc5s/XWSyZZaPZBbN2jVVztn82l71jq2Rynf2TMp1cKkaJ0lbWSlRU2h9beHVm5yrBRv+eoTiz+F1ikrtXat0CqlQ6nfN+oUSo7dvg/s2EMLSFfx9DiF0vte+Qqt/Dk9Z67rxU6TY7ZdsJPxevsgu9Kl1M6N+hOg94ZCofXnFM3KVh+3YVmhpe7uz5w5Y+p5erB5hQoVrEaFw3E9VhQerVVOADhy5Ijq+wKN3llmpbjTDtqqQsuaHJ86dQrR0dHid6V8YO9XghDi40zGXzrtVmjtFN4yMjJ8runJc6UBU8lMXJ6fanVPSTm7dOkSAP3eJPkKbQnyPKf5p5aPdq3Q+uuLAGWBlBVu5civ61mh1YOeyXjWnJgVetk4KAnirAdXoybHdvXNVuuz3nioTWJotUV/JsdKcZeHJ4+fXQK82fynbVGumKut7FPUvEP7W81l88Pr9fr0n3ZOegbC5Bi43BdoTWjJsXuFVq7E+ouH0iRLKLwdyyeM5EeJqeWTkyZk7cJy7tevXx+EEKxYscKvACgnOzsbK1asgCAIqF+/vtWoBI2cnBy89dZbaN++PSpVqoSEhAQ0a9YMY8aMwdGjR219144dOzB8+HA0bNgQcXFxqFKlCq699lp8/PHHflchPvvsMwiCoOvvs88+szXeHHPYYeanJkQeO3ZM8t2uPbR6Bjm9JsdKAwKr0FoRzljhMy0tDfHx8Zrx0xKYKUa3WdhpchwREWGrsGJmxlttz5OSckzHB39Ksl6FVo+zGT2Ewx5avQotzXulEwW0zNOMQoVBrbxVq29qdVqeRq26zwqp/gRTNYWWLV+2jrPn0LL5q5R3Wiu0NP5yhZa+S21PbrCxukKrZbqr1O+z+U7zVGnV1l887MJo/qv5fGDLU23yQ+m9Rk2O5e3KTseBdpoc0/rPTgwZmaQNhMkxqxwaGQ9pGWhZpAQKefuST0rKT3QIZywrtDfddBOAkoFz9OjRhp59+umnkZmZCQC4+eabrUYlKBw4cACtW7fG+PHjsWnTJly8eBE5OTnYu3cv3n33XbRs2RKLFy+25V0zZ85E27ZtMWPGDBw6dAh5eXlITU3F6tWr8dhjj6FLly4+zm047sbK7Lw/hfbAgQOS7+xqQ6jR2oPCHu1gRoGjecoOUJmZmShXrpzPPSx6BIFKlSpJvut14GGXUyg7hTez59AqKbRUAWWRK7RqeaCU71RB1jsDrlVPzHivdjryyRclqwSW8uXLK16XH/lgFtrWtMJQKmetFQV5Xddqn+x7lSZXWPydygBcrjPylTY2f5VW5thJJ3nfRmUfuZWH3V5rg71Cq2Y6q+UNXW3MUjsCR+u73Su0RvsDNQd2as7EKHZ4OSaE+Chidk56WtkKJYeNF41zZGSk7vKzW6EFpHXJX74pPRfKFVqKPF+oFay/58IBy7n/yCOPiB3yp59+ivvuuw/nzp3TfCY1NRWDBg0Sj+qJiYnB0KFDrUYl4GRmZqJ3797Yv38/AODRRx/F8uXL8ffff+P1119HYmIiMjIycM8992Dbtm2W3rVkyRKMGDECBQUFqFq1Kt5//32sX78eS5cuRb9+/QAAGzZsQN++fXUNgL/++iv+/fdf1b8777zTUnw59mBFmPYnHPz111+W3qfWAeoxHbXL5NioFQj7bnagz8nJEbdLsO9n0aPQ1qxZ01Rc7MBuk2MzgrTauaFUWGfRa3KslCYaHqsUaNVdrbKTKzhm95w5SSCgvizkyPOBti/5RAzgu0JrpS/S03aU8llLoZVf13oHu4qqVBdZqlatqnhdyekLDZP+ztZp2v+y7YhVaOWrN0p1mn2XU/bQ6sXf8SxK0DKMiooSr7H5TuujkT20du2tNJvv7MojG5bSyjOLEbNrNSdagG+7sLpC689Jlz/U6gXNJ6/XK07IRURE6J6ktWvlWcnkmBDiN3ylOhlKp1A07uz45vV6y9Sil+X18Tp16uCFF17Aiy++CEEQ8PXXX2PRokW49dZb0blzZ9StWxcJCQnIzs7GsWPH8Pfff2PJkiXIz88HIQSCIOC///0vateubUd6AsqkSZOwb98+AMBbb72FsWPHir9dc8016NatG66//nrk5ORg9OjRWLlypan3FBYW4oknnoDX60VSUhLWrFmDhg0bir/36tULo0aNwrRp07B69Wp8/vnneOihhzTDbNKkCerVq2cqPpzgYUWIoR2wWqe6fft2n3cZGaCMKpPsxJZeMzGlQZ1doZULp0YOYqcdPV3ZrFKlivib1qqgFvKtEoHcQytHKT+CjcfjQWFhIZKTk3HhwgXxulJd0Vt/lNKkdE0rD7Vm19WUP4obHRTKzcq8Xi88Ho/Pyi0VhNm6z2LX6hZVKoxOOmiZCMvTokehBZStBVjkK6Ra4bFWLXKzRJp37LsjIyNVFVqaHnkeya043OLlWE2RpAq6Ujpou46JidH9rLx+yNNnV59o5wqtPBylSUC19xjZQ6ukiFmd9DQyMe3veRYaLzbO/hRaNt12WSepmbMbWaGln0Op0FLk/Z3aeOdGSyR/2GLw/cILL+D06dOYNm2aeDbiokWLsGjRIsX72YwcNWoUnn/+eTuiEVAKCwvx/vvvAwCuuOIKjBkzxueezp0745FHHsH06dOxatUqbNy4Ee3btzf8ru+//148xui5556TKLOUSZMmYf78+bh48SImTZrkV6HluAMr5mZUAVPbx3Hy5ElUrFhR0sFp7WtSC1+O2iAnPxpHCzqgKQk27Aqtnn2tavGjCldERASKior8mhrqEYyaNGliKC52CalASX74E9YDDd0jGB8f71eh1So7VlBhw5E/q1eg0lJ25MqfvCz8WRhRnLRyplYP5EoGTava3m+7nEIprVLJMarQyicatPaGqa2iymEn0LQsCNQUENYDu5JCy67QsquQgLoC6JS9s0ah+SePt5biQZ9h84ZtV3rPuGZR6mesOOEzq9CqrdASQhTTZXbsl6dN3i6sKrRsu/Bn7q2E2iSZGZNjdpywyzqJteZgJ6vMrNCGcg+t0gotIcTvBK6cY8eOoUKFCkhKSrIvkkFCt8nx3LlzNU05pk6diq+++kpcBaQzmUp/QMnKxoIFC0Ql0emsWLFCFBoefPBBVfMQVrH8/vvvTb2LnQhQU1Tj4+MxYMAAACVHkNCVY467sSLMKAkH7G/5+flo1qyZeE1tMFITFNUUPLW47t271++7KLRvYT0Py98bGRlpSqGlUEWJtl0lxziUbdu26ZoBbt26teR7MIVQQkhIFFq5uRshBAkJCZJ7lMpJa/zwp9DSui03f1NbTdUSdpSOr2Kx27FfMFAzo5bXD0JKjppSWpVU2n9nFj379pQELbX9hYBvGrUUWlbI05qYYldUjh8/rnqfmm8DVqGl/YXaHlp5v6y2Qit/l5njQ/xdCwRq6dFaofWnfMrNrwH/Zysr1WGzp3AAxvt0tbqv5mSMotZnGXEKpWRiatU0l20/8rjosWZRG7NZx3E0jkoKLStrs+OEFVmARW0CxYhFGg3DCSu0coVWTUZQq1fNmjVD586d7YtgENGt0D700EOoVq0aHn74YVVT2gEDBuDAgQNYunQpxo4di549e6JVq1Zo2LAhWrVqhZ49e2Ls2LFYunQpDhw4gLvvvtuudASc1atXi5+vv/561fvatWsnek9ds2aNpXc1bdpU80gBNh5m38VxFlaEDy2Fdvfu3QCA5s2bq76LDhbnz5/XDF8vrBMqvQqt0oBAO+To6GifuOkRNui7qQBNB8gGDRqoPvPll1/6DRcosdYwg11CZqBNjv2Zu1FYB1sAFPftUOHHX5hKig69Js+3EydOKMRaW6GSD/Byge/UqVOqz7I4aQVNzXpCSaGNjIxUnDgCpHlhJX1Kq1RylCYuAHULEXld12saLvfuzsL2lfK6pGSKKL/Gno+spHwB0i0TLDQ9agotJZDbQuzEn8mx1jNqaVRatfRnFq8Uj8OHD2s+o4XRlVOlMtDjFEotXf7KXz7xKu8/rW6hYMOT1021NsyiplCx8WYdp6ltk5B/tmsyl504YvdsG1nZ1PIBEmjklgTyflKvxRGluLhY1zYMJ2JofTw7Oxtz5szBnDlzUKdOHQwePBgPPPAAGjVqJN4jCAJuvvlm13gt1suuXbvEz+wql5zIyEg0atQI27dvF5UII2RlZYkzxVrvkf/u711DhgzB3r17kZqaiqSkJDRq1Ag9e/bEY489ZtixDSdwWNljSQcCLYW2W7du+PbbbxUHA9oZqw1SaibEanGlztP0oGWiSIX16Ohon85Zj7BH75ErVGy/FRMTI5khpwKQx+PRLAv5+dl69/UYVRaU4kAIsW2W2ghsntD/cq+5SpMiWsIPKwgorbzROiA34zt48KBieFoKrVzAkyu0GzduVH2WxUkmx2ortPLrhBBERUUpCixHjx61bYVWjzmg0RVauaKgZ487IUS1jgBSixB5/6ZkcszmDyFEUs+UVmgB9bwwuoVDD0p5Gqx6qtaHqyn6gPLqodKKmZb5t9qqOYvWpIY//HlFl6PWhliFVql/MmtC6++YFtrfmVW22DFXntd0a5wWapOubH1h5RH5mMae5cxOCtnl60Ctbhk57kbJeVmokJuIq6VDaxKJPdLQTeheoY2KipKYDR89ehQTJkxA06ZN0bVrV8yaNUvXAONW6OxtQkKCjxArhzq4On/+vOFOip0l1jKJZN8DaJtLAcDKlStx+vRpFBYW4sKFC1i/fj1ef/11NGrUCNOnTzcUR07gsNIh0oFUaeCiA0/z5s3x0ksvKb6LPqc2M2lkTywA/Pvvv+Jnf0KVllkUHRA9Ho/q6rEeaP9E48KuVstXT86dO+fXBb8gCEhMTJTsk9dq71acWKgN3oFekVGqj0qehlmP0YByHdK7QqtUz5RMjgGpWTuL1sq1fJySC5d6FVonoVYP5Ne9Xi/i4uIUV2gnTZpk2QEMRY9TKKU6bUSh1TuZo6XMsIq9llkqFajZIzC8Xq/iPkC5sxi11Wq1PadyjJSD0f1y/jDSZ/lTaJXwt8qm9Ky/FVOlsUTNkkMPRhVaJWVVvkKrlK/se5S8GKuVhby90DpAw6DtzOyRMmrHvgD6Jq3V9AK2nNh6IJ8QYOPNfjaqb+hx2MiaxxtZAbbztAGzyC3RAHPbkrxeb/grtGfOnMHUqVPRsWNH8RpVbteuXYvhw4ejWrVqGDhwIH755RdHzFTYCRWQ1JxpsLD7yYwKnKwg5u9det7ToEEDPPvss1i4cCE2bNiADRs24KuvvsLdd98NQRCQl5eHESNGYMaMGX7jlp+fj4yMDMkfJzCYaT9aqytHjhwBULKqTwcFeQdPFRW1GT01gU9toGAFSX+DidYKLWuaZ+aQcPpuuUKVkpIi3iM3db5w4YKq500KzcdWrVqJ17QUc9bszaiyoCaQ2Xlout79P6zjC5qXycnJknuU+galVVald+/YscPndzUHQmorBFoKrVzoVxJGevbsqfo8xUkrtPJ60LFjRxw7dkwxbQkJCYpCTk5Ojm1HYehxCqWmfKkpLPIy1bNP1+v1apqQx8XFiZ/lgruSF1O5lQGbv2p55+8YIrnVgRWU0molTCOmuv72jirVBVoP5ftAKUr7b+UKpjx9cllIEATDk7EsRhVapQkZ1n8MoKycstfY/pCmT+34FflRW3Sco2FYVWi1jn3R429AbbGFthdCiGSMl7cjNYXW6HYbPWMlWw+N5Bu7HzjUyPsxtX5JLa5KPjHcgu4aXrFiRYwcORJr167F3r178fzzz6Nu3boALjfWvLw8LFiwAL1790atWrUwfvx47Ny5M2CRDya0s1bbe8TCCsJGBQR2UPD3Ln/v6du3Lw4cOIBJkyahX79+aN++Pdq3b4977rkHX3/9NX788UfRPPXpp5/26zhh4sSJKF++vPjnhqOWyhLsACHn5MmTEARBMvMmH6iooqI2gBk5z6yoqAiZmZm692JozXCyKzFmBBMqENABzev1immlWyPk3gnT09Mlwq4SSgqglpDNKl9GBz6lLQWEEM3Zc6P4U+ApSh5JK1euLLlHqT/SWlFj859OvrCone2otvqmNZEozzOlMlPq2/RMZoYKubC2fft2TJgwwUc5JISopkO+4mhFONNz/I/SpAchRFUBk6/o6lk9JIRo7iFjLQv07Adk81m+0qY26aK0V9br9SrGX6mPNVIOdjs0U5owUjNdVVuV13J0SPNGzTLAzAqt0gqflX7S6FFWavHTUsrl71HKY7buqTnJ8nq9Yn2nYfg7/cAfWuO+P8tAoET2UIJVAlnlVN4fs2llxx6ji0X+rLu8Xq/i+dV6FFq7jjuzAq1f7JioZt6uBq2XYa/QsjRu3BgTJkzA4cOHsWLFCjz00EOiUxCq3J4+fRpvv/02WrZsiXbt2mHq1Km6BgyrCIJg+e+zzz7zCZcK5noGUVY49ycUq71Hz7v8vad8+fKa+yZuu+020fw0JycHs2fP1nzfc889h0uXLol/ejozjjnMzKprmZacO3dOnCChdUJtdUttNVBtQFASVP7++28AEI/GsbJCywpKVuocu0JIlbdffvkFgK9ympWVhXLlymkKk/QZto1pDbJW9nGpTQzaaSWh18xIaYVWfsa1Ut+lNbCyggo7TlBhQm2PktoknFY5yOux/N6oqChdQowTZuMpSvXghx9+ULy3fPny+N///udzvbi42MeLtFn0eGtXq7tqz8iVdr3OerTMcFkrDbl8QvOCVT7YPpYVgAH1STmliRx2gopNr5JCamQsUOq7razQKvW3ajKFGS+9dBLA37NKTrnUwpeHFRERYWgyVo4Rs2u1vJHH0YizK1o/2DSwdUYellx5p4qZWQ+8Wu1Hj/dotZVUNr3sJIR8QoLNO6097/7Qs0LLvou2dT0TAVqevIMFjbt8W4RavVJqS9TCQz5B7RbM2SAwXH/99fjkk09w9uxZzJs3DzfffLPYcKhyu3XrVjz11FOoWbMm+vbti0WLFhk24wg1VGHXMyvEDmBGZ/VZb6H+3mXlPZRhw4aJnfCqVas0742JiUFSUpLkj2MfVg8K1zLBSUtLE2fdqLCuphyqDRRG9iFRRZHuU/UnVGnFnV35MGPxQd/NKsa0vdA8lw9aeXl5qFixouYARZ/RawbF5p9RIXPPnj0+14qLi22dGTbTnmn+VK1aVXJdKX1aq/A0D7OysiRpomOJkgCotfqmpejLFRd5P6tmVeAkBVaOUr1Ty5uKFSv69QNhBbV9zXKUJri12oUZr6Zer1dzHK1evbr4WW2fOmvGq7QnGZDulWUhRPkopHXr1im+y+oKq9JKpBWFVqnPV1Pa1IR6LWWU9r/+9m7TMPWMQXLZ0uPxWNqawY7Levwq+EPNCsGfUq+2IMT2jYQQn/usbkvRUmj1+LRQk/WVnGQR4ntutFq/a3Ry29+CGlsuhBAxbXrKNFT6jNIksXwsMDJuUesotl90E7adAhwbG4uBAwdi4MCBOHPmDObNm4fPP/8c//77r5ihBQUF+PHHH/Hjjz+iUqVKGDhwIAYPHoy2bdvaFQ1TnoXlKBVmrVq1sH79emRnZyM9PV1TIKANrUqVKrrN+Cisx2F/nTfboM2a/6akpCA5ORmpqamqpiGc4MDmvxnhWcvJSEZGBipVqiS5Jq9f9Dk1QVjtutLgvG7dOgiC4LNyp4ZW3OnEDXVoZhQlpxq0/VLlXT57nZ+f73eWUmnmVsus1opjkr/++svnmt0OYOSeitVgB3hCSo6B0dPP6VlRW758uc81rZVdtTwwcg6tvMzi4+MVhRg1Qd0JqO2fj4+P9/mtcuXKuuJuNn3ssX5a/ZiSoK1Vbkb2zLGeuLXCpNumAOUjjgCpCXx2drYYttw0Xu09SqbI27ZtA+Db7yj1EUbGAju3IADKk5tKSh3bpvTGt6CgQOwTlCbmlOrf2rVrNe9TmsiKiIiwdMQLq6zExMRobiNTS7uSN2w58r2wcpTK1uPx+PSr8rRSxczshJzW5KAeT8Nq8ggL23bk+aMWb6Or7kpjBds3er1eybu0tirIxyQ9FimBYN++feJn2g7YuGmlQSmu1IqMWta5DdsUWpZq1arh2WefxbPPPott27Zhzpw5+Oqrr3D27FmJc4WpU6di6tSpuOKKK/DQQw/h2Weftfxuf0fdmKV58+ZYuHAhgJLVkk6dOineV1RUJB4TYOaMynLlyqF27do4fvy44qoMC/u72fMwgdCcncXxhZ2gMCNMajmFys3NFR330PJWWw1QUxqNzPTu27cPFSpUEIUffzOYWkICVXatHFGzY8cOEEIgCAIIIWJe0NUXpbD9WUgomRxrlQF7fIiRgS81NRVnzpxBtWrVJCZedjqEAvTvoWWh5tv+tlbQfPeHkkJL24U8DK/Xq6pEREZGIjIyUlEZlgt88jJT26rh5BVaNaVfqT7Onz8fEyZMCFhc1q9fL342qtBqCalGFNoKFSogLS0NhYWFKC4uVq1/9evXFz+rCe7sJHl+fj7i4uKQnZ2N3377TXKfUhkQcvloLfb9GzduhMfjEU+PoFg5LxVQVkCtTLworcAptY0tW7YoPi8/5ohlw4YN4mf50TOAsomt2so2hRXwKZGRkZbO62YVzcTERFOO09hyURvHlPKA/ay2IilXhOX1zerEp5ZCazZf5f4kaNqLi4t96olSXgDG99AqyTXyRRwaPnvcjVK/IW9noZrcVPIyzcZl06ZNhsKjE2rsRJ+bsGxy7I/WrVtj8uTJOHHiBBYvXoy7775bNOmiJsm7du3C+PHjAx0VS3Tt2lX8rGWau2nTJrFD6dKli6V37d27V3OPAhsPs+86f/68OHC4dVYmXLC6J1lJcKIUFhaiWrVqAC4rYmoeMdXMiNQGYqX3nTt3DvXq1RP3vPgzjVU72gK4LCjSe5TO2dWCECLuJ6SrkLSu0zxQEka3bt2qGS6NB7ti4W+FVs3DtBZ0v6O8jVPFzKz3Sjl6J7bkK7SJiYmmlGGl43/YFRiqhNCVMLmTPEKI6qpvo0aNVPNFrtDKhbLy5cvr2m/mlBVaNQdDgiAgKirKp70UFBTggw8+8BuuWQV+8+bNuvYhK62aHThwQPV+I85NqGUIFWLV6mfTpk3Fz2qmemycCgoKROsO+QotLQN5uuWTCnl5edi8eTPq1Knjo2iz++xpOzNSz+xeoVWaYFAq182bN4uf2fRoWX2xEx9K44OS7MMeBaf0PrUtKVbOV2YnY/2Z6hNCFPsOduVdrR6z71HyfK13z6g8fKt+FrTGNLP5Kh9badrVPETLSU9PN9z/KuWfllWc1qq+XHaizwZ70lM+MfDHH39IftfawqCUfzSP9FrWOY2AK7SUiIgI3HrrrViwYAHOnDmDYcOGAXDP6mC3bt1EYXjOnDmqFZd1KNW3b19T77rzzjsVw2PJycnB119/DaBk9bhJkyam3jVjxgwxLddff72pMDj2wA7gRjvGjIwM1VVQKpTQc42pYpCeni4xmy0oKEBERISqUJSfn6+rvZ47dw6FhYVo3bq1KEz7E0a1FF529hYocUpnBK/Xi9WrVwO4LJDQlRlqkqP0fn9ny9G0scKy1mx4amqq4fPdioqKMHPmTCQnJ6Nhw4aS37KzsxEREWHbIKp3H5C8DlSuXNmw8zsAPibwQMkkXmRkpOQddNCWKyVawnuVKlVUBR65gCYXXJKTk33MyfWuMIcCpVVtAHj99dfFNi2Hjh0sZr2gytm/f7+4dUYrz5Tal1YdNHLWIz1Ki9YRNa+drGVTbm6uorLGKrTFxcWoUqUKAF+BkKaVzcfs7Gwfh2bPP/88ioqK8MYbb0AQBEk4rBUHO/GvFyUTUCsTL0rhKeURPWrL4/FI4qvl2Z2e9xwbG6t4bA+rgNBrBw8e1OxrlI78UtvfrBe2Tho95YLCKk5qJsdqdZ/mjR6ngnJHZYD1s8q1FGK1CUV/csKuXbvEz+wZvUp5o7RCq2R6rgRb95Um8NkxRO7hXUuRl9ezUI0N8joxa9YsAJfroFEfG1QecuviVtAUWqCkUb/55pvo3LkzZs6c6RplFijpyJ588kkAJSZIb7/9ts89a9euFT0FX3/99Wjfvr1iWNSbstosSN++fdGgQQMAJUflsIMcZezYsaLwPHbsWJ/fjxw54neFafHixeLqT1xcHIYMGaJ5PyewWJld//nnn8XP8s6Vdr60vtHOzuv1Smac2c6fCm2U7du3S7wDs7AmWPPnzxcdBPXo0UMU7vx1rFp7UOS/6d3rybJr1y4kJSWJAyadAGKP8pHjb/sCVWjZFTB28K9YsSIWLFggfs/Ozhb35eodAF944QXk5eXhtdde85kNz83NRXx8vG2DqZZTMravlvfbNWvW9LtCS+PIPivv/8aOHYvMzEx4PB6JUkCFYirI0jCoyaeSwpaSkqJYpocPH0ZRUZEkHnLBRW3vtJoCE2qef/55CILg0y60JjmVZu6HDRsmMTUzk74FCxYgNzcXd999t98wjDpSMRKfHj16ALhsMqu2ssY6QisoKJDUY1reu3btkji6pBODanFj+wNqQszWt8WLFyM2Nhb33XcfBEEQ+7ecnBzs3LkTderUkcTNSD7l5OTYKldlZGT4hKfU3g4cOICIiAgfZVdr29TWrVsRFxfn8wzNd6U6evLkSR9/IWy7VDI5BoxNhshhx64OHTr4vV/JQef27dvFz2rlKV+hpflM++V//vnH77vlZ9ACxiwblLCqECvBmsqylhF66zqdDDFyvIyS5Rk7aSK3RtCqM0oTJ0DwxwQ2H71er2i1qWfiXCmux48fV2zHbiHgsc7JycHcuXNx4403ol69enj++efFPSnU5Dg+Ph4DBw4MdFQsM3bsWFFIGDduHIYPH44VK1Zg3bp1mDhxIm666SYUFRUhLi4OU6ZMMf2eqKgofPDBB/B4PMjIyECXLl0wdepUbNiwAb/++iv69++PadOmASgxT37ggQd8wjhy5AiuvvpqdO7cGRMnTsSSJUuwadMmbNq0CV9//TUGDBiAO+64Q+ws3377bYlDKk7wYVdojc6qU6/CSh083d/Upk0bAFKBi52Jo3tLZ82ahWuvvVYSxrx581TDp4rFuXPnxLpYrlw53HXXXeKMttbgoOW4QD6rquQEwx9erxenT59G3bp1xQGfCrxaTi1effVVzXBpPrKz9qzSmZ6ejnHjxomfvV6vKIwple/DDz+MDh06SJTiuXPnIiEhAY899piPw5jCwkJbz4vTu0dZHnd2HyJFbUBkhWP5PZMnTwZQIsCxeUrTTa9RYY0qukr1oUaNGop5TBUtVsGRC1EpKSlYsmSJYvxZpk6d6veeYLB3717UrVvXJz+ph3E5TZo0URRmWrRooXgGsBH+97//wePx4JVXXtG8T+6AhRIZGan77Got6DhNhVT29AC1+BQXFysKgseOHZNM8DVq1MjnHjYtbPzT0tJQq1YtREdHS/ZC0skctj8bNGgQvF4vWrduDeByu9Ir5Ofk5MDr9frkn5UV2qysLJ+Ve6UtHwcOHBDbFJsX7Oo2G4+CggIcPHgQDRo0UFXAWYWWEIIPPvgAhYWF6N27t2p8jx07pmsV1QhsvK+88kq/9ytNnrD5QH05yJF7K5YfFalk/SNvQ7T90nHh8OHDls1hrSrEShw7dgxRUVEQBEGyl16privFm67w+rMMYstOyXyerWPyPdtacoba1ohgK7Ty/prKkHrkAqW4njhxwrVn0AIBUmgJIfjtt98wePBgVK1aFUOGDMEff/whbvimGXnddddh9uzZOHPmDD7//PNARMVWypUrh59//lk0eZwxYwZuuOEGXHPNNXj++eeRlZWFpKQkfP311+KgZJZbb70VH3/8MaKjo3H27Fk88cQT6NixI3r16iU6p+rQoQO+//57zf1ea9euxfPPP4/evXujffv2aN++Pe655x5888034mTC9OnTMXLkSEvx5VjHqhfc2NhYRWGDdv4dO3YEIFXA5Ktk9evXxyOPPCK5tnLlSkyaNAkxMTHinjR2QF6/fj0aNGiA7t27o7i4GKtWrUJGRgZiY2N1KbRq+68AX2cjERERhmfb9+/fj8LCQjRu3FhcwaDCopZCq+bohEIVCLnZNps3x48fR15ennguL92zJx8s09LS8Omnn2Ljxo1i/ufk5ODMmTPi3lm5pUZxcbGtM6l6FVr5Sm6TJk0k++EAdfNVVsBg80luKseuNp45c0bitZYKelqC+qxZsxSFo82bN6NHjx4+z7LxPXjwoOIZzfJnVq1a5ZPuUJCdnY06der4xE/NNJ/d0sIir0tGhbOioiLs3r0b7du3FxVDtTJSm8QqLi72q3zqgfaDVMDzpxTSvpetd4QQ9OjRA3l5ebj55pvF6/4cMLKrvoQQ9O/fX/xeUFCAvLw8tGjRAkBJf0br/a+//oratWuLwjK9R+9xbr///jsA6dm6VsnLy/NRkOXK2P79+3Hu3Dm0bdtWsuIMSFcm2fo0a9YsFBcXY/To0T7vpHVGvv/2jTfeQGxsLF566SXF+4ESKye5kmPnXnc9/hvk1k2AvvNa5WMCrUcFBQVIS0tTVYRZaJ6lpKSAECJaElIniGYws7rtr+84d+6cuJJNx2BBEFBUVKQ5ocXua4+MjDTUR7HmubROsNdYxZoqt3ITeooVWc1Ozp49K1qVHDlyREyX3GJK79FDJ06cUJygdgu2KrQ7d+7E+PHjUadOHfTq1QtffPEFsrOzJUpsgwYN8Morr+DgwYNYuXIlhgwZYvoM1VDQqFEjbN26FW+++SbatWuHChUqID4+Hk2bNsXTTz+N7du347bbbrPlXY8++ig2b96MRx99FA0aNEBsbCySk5PRtWtXfPTRR1izZo2qeVzbtm0xb948jBo1Ch07dkSdOnUQHx+P6OhoVK1aFTfccANef/11HD58WNzPzAktZ8+eFTseIx11VlYWDh8+jI4dOyp2XAcOHIDH4xFnjtnOjpq3UaiCy4bz5JNPQhAEyaQHK/xeuHABhw8fxq5du9C0aVNcd9114m9UUdASypQcfch/o3GOjo7WtS+Ejf9XX30F4LIixAolWo4f3nzzTd3vYGEHZEIIpk2bJnobbNeuHQBfAZuaJguCgBUrVgAAvvvuOwBAv379ACh7QDVzDq2aEpyVlaU4OSZPp/ydLVq0kBzVooaSIEyh+VG9enWcPXsWVatWFdvAyZMnER0dLa4U6DkvV8sT6YQJE3zKna0Ty5YtU9xDqyQYK+1FDSZpaWnwer1o3LixT51Sm1RQi7PV1YXNmzeDEIJevXoBUM8zQN15D+uB3Aq0v6AWHkreQFno9hx2X3dubi7++OMPNGvWDC+//LJ4nV2li4iIEOs1zW95/KnSRggRTSVbtmwJ4PIK7dGjR5GTk4MePXqIcaXlobeN035DbmpuRaErKCjwkc/k9WT48OEAgClTpkgUWq/XizVr1iiaaNO4Dhw4ULUfZZXA3NxcnDlzBjfffLOmwnPx4kWf+Nqh0NI+U89qpdKxj3qODZLHk9aj/Px8cYFEbm4tLws64Vy9enXRGWJCQoKlSQ5/E6dmVsTT09NF2ZVaJEVHR6O4uBgVK1b0+/zp06eRlJTkMwkgr0vsGchpaWk+4xtbx9gVcDoxoJa2c+fOKeZJsFdoMzMzxfyiE1oxMTE+6VTaEiSvb1OnTkVxcTEee+yxAMU28FhWaM+dO4cpU6bg6quvRsuWLfH222/j5MmTEiU2KSkJjzzyCP78808cOHAAL730kmu9aAEly/njxo3Dxo0bcfHiRWRnZ2PPnj149913dbm7pnmjx7zrqquuwowZM3Dw4EHk5uYiNTUVf/31F0aMGKHpxKNcuXK4//77MXXqVKxbtw5Hjx5FdnY28vPzcebMGSxfvhzPP/+8rbO5HHPk5OSge/fu2Lt3rylvsdS8/fHHHwdQUr+OHTsmznyeOHFCYkrHvkO+GkL3jdKBIS0tDTt27EDbtm19PNBSPB6PuLIhd4SmZ4WW7rNSmnHdu3cvgMv7kuLj43UJeOxgs379ekRHRyvOkmsdO6DX9FGuSFChmHrL/eijj8RV8quvvhqAr4JPTca7d++OCxcuIC8vDz/++COAEvPo6667TnEvkxlzMLVBOjMzU9HMSj5LLU9vmzZtfFazlcJRE74iIiLE/GjVqhVSUlIkxz3t3btXPCoFkK6iaZURPRYFkKZ52bJlANT3Befm5kq836rFH1DfSxUs6Mr/mjVrJCvsSh6kKceOHUPz5s39mk8aFc7oMSy0jtMVFyWoVYbSBArdg68HNUGb1gtaD5X6H7bMaTmyyiidTHvzzTclq35svrFbNmha2P4pKioKdevWFd9Fj52h1jLU8oBaqLVt29bHiZRehXbz5s3weDy2jenUakKuYLD1Ij09HStXrsRVV12FK664QlLm8+bNQ3FxMQYPHuzz3L///ou4uDjEx8er7qE9f/68mKd0QrBPnz6K3s6By6vf8vjaodDSMVPPBJZc6QR8J9j0tC16KsE777wjnoBw4403aj6Tk5MjngtOCMHJkyfRoUMH0/uqCwoKQAjRVFrlK+JK75KXcW5uLqpXrw5BEMRtOtQfhB4Hg2lpaahcubJP21CrSxs3bgQhxMeh28mTJ8VnWIWWWpCo7UW9dOmSYQePdpOVlYXi4mJxqyC1KurQoYOPJYEer/3ff/89BEHAo48+an9kg4QphTY/Px8LFixA7969UatWLYwZMwb//POPRIn1eDy46aab8MUXX+DMmTOYOXOm5OgbDodTwoABA7By5UoUFxeL+7OMDMJz585FVFSUuJLn9XrRoEEDcR/hhQsXJCsPrEJLhVA6iEyYMAG//vqr+HtycjIIIRg+fLjoxAOQDhzvvfeeKEB+//33krjRjlVLKDt69CgEQVAUTo8cOSK5npSUpEvAYzvwtLQ0NGnSRAyLFSZYJYDuS6f4c1xHw5ELK3SGPj4+Hp06dcKBAwfwzTffIDIyUhwE5YL+1q1bUa5cOdx3330AgC+++AIbN25EQkICBg4ciL/++ksxDllZWYaP2zG6R0Y+OMrNwrxeL3bs2CHJc3/7nNk4x8XFiflBzWGVVkhpubN1OTo6WjH91apVQ/Xq1cV40HobFxeHjz76SHTMx6aJRemccSUh9I8//lB02hcsqKAvd76jNdnp9Xpx5513+ggu8j7HqCJAzUs7d+4sXlOrB3SFVklQVvJ+DSgLZWoTgHpMQwVBEAVX6nCHThAAJQKix+PBbbfdJqnv7B7JFi1aiPWIppWdOGPTQggRV4KvueYaAJdXaH///XcIgiA5N5LWt8zMTF1mx3Qfq5pQbxRqdqmlIN93330ghODdd98FAMnWgFmzZkEQBEULsJMnT4r9JI2vvB2fPXtW7C+psH7XXXepTmLQspM7R6PlYsWLN617mzdv9qtwUYeeSnEwAlWM8/PzERUVhUqVKvmt116vF+XKlZNMDtNVcDOrh9QqSEt5k1vMKJWPPN5er1dc1CosLITH4xHbsr+zmOnExaVLl3y2yailkU5EyCfxzp49K8af3UNL+wWl1WJ6/rmSdWQwV2jXrFkD4PLWErqA8eSTT0r6Sjq5IUd+7eDBg4r9h5swFPM///wTQ4cORbVq1TBw4ED88ssvKCoqkiiyV1xxBf7v//4Px44dwy+//IL77rvPFicPHE44cu+99+Lnn39GtWrV0KtXL7z++uuGnn/nnXewf/9+XHfddZKZxuLiYuTm5uLDDz9EVlaWxAyKFQLpKgQrTLzyyis+g//IkSORn58vmiiznd6bb76Js2fPomLFiti7d6/EqREVWLUEsqNHj6oOmEeOHEFiYqKozCjNyiohF35vvPFGXLhwwWcVmB0Q5QJ+v379cOzYMTzxxBOa75Lvp6EDdWJiIn7//XfUrFkTXq8XcXFxYn4UFRUhLS0NQ4YMwY4dO3D69Gk0btwYgwYNAgB8+eWXOH78OJo1a4a9e/eidu3aotMkFkKI4XN5je5RlCsNXq9XspI1ZMgQFBYW4v3339cVXlxcnKpp2O233w7At/zy8/PFcmNX8DIyMhS9XleoUEFi8krvqVChAs6cOYMqVapIjllh65QgCLjqqqsk4akJKkVFRYpO+YIF68k+OTlZzFd/QvegQYNUV13MnH8KXN7aQAU9j8ejukJLJwGU6q6aAiUIgk+/JO836O+szKG0pxEoSR89Cmvnzp0QBEFisZGWloaGDRvC4/GIeSUX9rp16yZ+pmll9+Kx7aS4uBiLFi1CuXLlRIuTiIgIeL1ebN++HSkpKfj999/FsqNK0BdffIHk5GS/5ZGamqroHMws1PRZbkJL28I777yDX375BS1atBBXDtkV2u3bt6NGjRriBBpNT15eHrKyskTFj8ZXPvl58eJFcUIgMzMT0dHRitsNaL7QiVj5hB393crebBp3QRD8roDrte7wB3tMGz0GT8/kZeXKlSX955133mn6eDdqWaQ2yQT4ti+liSel/qhJkyZiesqVKyfKCFrxJISI23OUToWQP0uPBJo3bx6ioqIkThnT09ORl5cn5jNrFk5XaytUqKBqNSY3pQ/2qS3UfwM9oozW0dtuu01SBhUrVtTVl58/f15xe4Cb0N3zUacvn376qVjwtKArVaqEUaNGYcOGDdi5cyfGjRvn2nOMOJxg4fV6sXDhQpQvXx579+7F0qVLxcFB7+Dz5ptvIiYmRjRPFQQBubm5KFeuHGJiYjB27FgUFRVJBllWQaGzkqzguXHjRh+hqLCwEHFxcYom9SdOnEBMTAyeeeYZAMA333wj/kYFQS2HQ3TPpJwJEybg2LFjqFmzphi/WrVq6Zrtlgu+3bp1Q3Z2tsTbKCD1SqwkLNeqVUtVOVA7RogKxeXLl0dsbCy+/PJLACWDI837jIwM1KpVC5999hk6dOiAoqIidO3aFbGxsahZsyZWrFghmvtlZmaiSZMmotkZS2xsrC5zIja+akeYqMEqB1QwYvder1u3DlWrVtXtWE7L+RAdN+Rpys7OFo+Zku9RpHs2WSpWrCh5D51pp2XMenSX14latWr5HJGk1R7Xr1+v23GPnXi9XixfvhwRERGIioqSrAyxwrtS3K+44gpV002K0WN1Tp8+LakrSmesUgsO6l1USaFVm6ApKiryibO87dH3s/fddNNNqnHOysrC888/j127doEQIlnBKS4uFusWDU8eN2oVQ2EtCYDLbU0QBJw9exbZ2dmS/bgejwcFBQW4ePEiWrRogZMnT4o+CNi8y8rKEr3JK5GXl4fCwkI0bdpUcTXMDHTSQcmEFig5GSEuLk6y3YDuoc3JycGlS5fQpk0bMe+8Xi+KiopEAZxOBNF2ShXRwsJCpKamIicnR7yXEKK5t7KoqAjTp08XJwhYaL1W8zdC460FLdOWLVv69A1y9HhC1oP82LjevXvrUppq1qwpOVKOKrhmFFpq+UH7ZaX3y2V9pYkyJT85V111lRhe1apV/eYr5bXXXgNQIsfI67pSGp966imcO3cOzz77rCT+P/zwA4DL1hI5OTlieDk5OeJeVOphe8eOHfj111/FbQNyb+d2ngmvB7oYwU6+ejweH5mgXr16fldoMzIyUFBQ4DOR6zZ0K7R0vyc7q33HHXdg4cKFOH36ND744APR4QmHw/HPxx9/jKKiIrz00kvizLOR2fV7770X58+fxy233CKuVFAhsmXLlpg9e7a4d4w1A1Q6a5EK5NTrJuukqHHjxvj777+xb98+cR+nvIM8deqUeE7z0qVLxet0gHjooYd89nv26dMHiYmJyMrKEj2H0nD//fdfvPjiiyCEoFGjRmI8mzZtqmvfqHyg69q1q2gqq6bQsugRHC5duoRt27aJe0Ep1GSKCmDXXXcd5s2bh3Xr1omD/fz585Gbm4vrrrtONFmmR5fdcccdYhzXrFkDQgjatm2rKNDSPU5GMHqOL7viQRUGdq91WlqaKHiyKCnadNBnhU46QcG+R01JHzFihOS3adOmYc6cOT73yVcp6Gx+Xl4eBEEQnaYAvgJYeno6XnjhBcX3K+H1evHBBx/ovt8uXn75ZWRnZ8Pj8aB27dqS9LLCu1zA//jjjwGomxHKTWj1kpqaKqlbco+3bdu2Rb9+/bBkyRLxTEgl83caPyXkk0vy56ngzPaj/fv3x7333qsa5sSJE8XP3bt3l/xGHaTQiRBaV6iZX8OGDSXtT818VhAEpKenIz4+HmPGjBGvFxQUiKaCdBJi6NChAHy3aVDndkpQIbtly5aWTGtZqBl227ZtJdepj4YzZ86gd+/ekvdRk2M6BrBOnAoKCnDLLbdg3759GD58uLi3lkL7y/z8fDHfWY/7aqtHXq8XDz74IC5evIiOHTv6eNCm9V/N67ce6OROjx49/CpedO+rVeTKxaBBgxTLVm4BGRERId5HJ1TMKlt0lZ7mvVK/LPeKqzQhpdTXLFmyRGwnDRs2FGUQLeuS4uJi0Qt4Tk6O4hFaLF6vF99++y2SkpLwxhtvSK7TFX3qwbyoqEjsT7xeL5KSkhAREYHCwkI8+eSTaNGiBXr16iX2T6FW/g4fPoyoqCiJPEf7P7aetGzZUrPsCwoKMHPmTAD+92g7HUO2KYQQtGnTBlOmTMHJkyexaNEi9O3b17DJG4dT1jl27BieeeYZREREiIogcFkg8idMbt++HQsWLECNGjUkK6K042rVqhXuv/9+9O/fHxEREeL5m4C2I51mzZrhlVdeEd9PCEH9+vVxzTXXoFatWuJKKxu/iIgIVKpUCUlJSUhISJAcw8N2tqxDjYyMDPz444/Izs5G48aNMW3aNIkQyK66ZWdni+9r06aN5lE7Su8FLh+gLh8s1ZxCyYU0JU6dOoVrrrnGZ38rNTlklYr7778fNWrUEAXijIwMVK5cGStWrEDlypURHx8vOooZO3as+BxVdm+44QbFvUV01cMIVhRaKhzSI0VofWNNLylKwg+7Gkp/p/FnhRO54PbAAw/gyy+/xGuvvSYx6bzpppsUhTzWsRRweV9jenq6ZAWDXmPjquUoTCl9ERERITmTdtGiRYiKihLNEVlzenYFWs0rrZppJsVovcrKypKYH7IK7Q8//CBadj355JPiRJuS7KD1Xnmc5W2TTgyyYdx2221+ne3RbQL0rG6gpK7Kj+hhlTMl81can/r160vKg5pfy4VgdjKMermn+8hZhTY2Nlayv1cOtdDp1q2brlUrf3z//fd49913IQiC4nnGdHVr//79kq0aHo8HFy5cwPz58wGUbCGg7XPnzp34/fff0bFjR8mkBZ2gpP1lYWEhli5dipo1a0pOjJCvWFIeffRRfPnll6hYsSJWrFiheN4oAIn3fTl686h///5+j7FRGy/YclGbdGDHQFYBj4mJQUpKii6F9ty5c+K7qKmw0sq1Ho4dOyZafQHKq6/yiQIlD/NKeTJjxgyxnbLHjmk5hcvKyhKdVHk8Hr/WSXl5eTh79qw4KcPGY8uWLeLJIRR2bExOTpbkN+17qHzDKulmTqewCvX0zPZt1JqCjbfSMXXA5f6+QYMGePbZZwGU7FF3M7oV2jFjxmD79u3YvHkznnzySU3zDQ6Ho02/fv2Qn5+Pm2++WdL50IHInzBJB/qlS5dKnqdCEB28v/nmGxQUFKg6hZKbb1aoUAEvv/yypGNnBRp6DAYbP3aQa9iwoeT8QHYQp27lgcsOmL755hvs27dPNGElhOCFF14Q31OtWjWsX79e7HypYuoPeQdO9xomJSUprtA+99xzkvvZNGmt1ubl5UkUrNjYWFFwVxqYWeGjXr168Hg8OHnypGQ/UP369VGtWjWJiV379u0VvRwDxhUPLcFGSWhkzVfpu+SCFXtOJ0Up3xITE0WBR+6J9tprrxXvkwsq/fv3x3333YfIyEiJ6XXt2rUVhaXTp08rXi8sLMTtt98uURYiIiJw6623Su7Ts8pF21G9evVw5MgRcW9VsDh48KDYfnv27CnJM3ZyQK281VZCaLkVFRUhJycHM2bM8CsMFxUVIT8/X2Keyiq08+bNA1BST6gpa1xcnOFjp+QKLXuOJHBZgGfbRGRkpN9JCuoMhZ0IaNeuHbZv347FixeLq4m0TZ4/f15s32x/QvNO7hiInWhkofnar18/7Ny5E1WrVhXrHs27iIgINGjQQPNUhIULFyIuLg7XXHONT92tV68e2rVrhwkTJmjmAQs165w9e7bPZAAhRHRI888//2DWrFmiUkpXohcuXIiaNWtK9vTSPnjx4sWS8KiCSPOeOvvp2LGjpA1T79lyLl68iLi4OPz000+Ijo6W7IVk2wTbv5ilffv2hvtbCtu3qk0qqk2k0lVf9neaNnnbPH36tHgfraNmV+3pNgI6PilZVMjHOSWFX03xpO2CnazVOgHF6/UiIiJCnDjzp9A2a9YMhBBx2wHbtx07dgy1a9eW1G92Qq5GjRpi+DExMcjKykLXrl3Fdql2jGGwuHjxIqpUqSKRsejxTmy+XHnllar9d2pqqiivtW/fXteReE5GdylMmjQp5EvsHE64sHPnTtStWxc///yz5Loer8AFBQU4ceIErr/+evE8Qwp9jjUdkXe2KSkposArf54KyKyi27JlSzz88MPo3LmzaCrIws5UdunSBYWFhaLQyu65pWcwAiWrtR6Px2cPGlDibCQiIgIxMTHo27evuH8S8BWG1JArfw8++CAAX+cW1MxJ7hCKVWj9nbNXVFQkDpSsF2YlhZYNi54XGR0d7bPH6NKlS6hatao42KqZG5oZSLVMtpWEXnbPLR3M5cI1HUj9wQpy7CQGAIkXfLmgwprMU0clgHrZLFu2TFXYGTVqlCT+8fHxkvoSFRWlS2ilwh1V4ujxWcHg1KlTyM3NFdveXXfdJRFa6Uqjkkk6bUtyM0B6H2tyfOONN2L48OF+TbCpOTy7CsbuoaVHkn322Wdi+C1atPC72sUiCIJEePN4PLjnnnsk91CBVL5v1p9Ce+HCBSQmJkqU/BYtWqBdu3a4/fbbxWN1mjRpAq/Xq2jumJCQINYb2h5o+mm7oflz8803o2nTpnjiiSfQtWtXvP3227h06ZKk36b9SHFxMbp06YKCggLFY6K8Xi9OnDghWk0orXpv3rwZL774ouh0zh+HDx9G7dq1MWTIEMXV7d27d/uk/YUXXpD4Spg0aZLknsLCQlSuXNlnMYTmGR0rli9fDqBkkoZFvlrOsnz5cnTp0gWAdIWQtonIyEhbhHV2stYoNH6A775Tipr1FE0729/RuipvQ6mpqWK9ow69zJocp6WlITExEfv27QPg6/U3KipKl0WA/Bxoj8cj6a927Ngh9gta5UzDpwq+P4WWWkBQOYfef+HCBeTm5uLqq6+W5Clr1l63bl3xfppuat0ix+PxaJ67HQjy8vJQu3ZtSf736dMHgHQCo379+hIHYxRCiLhd59tvvxVPvHAz7vXPzOG4lP379yMvL0/RWQnrBVeNb775BoQQnzNfgcsKmpZXQo/HI66Qyo8nkZ/TBpQoIZ9++qnkHFoWVjCmJivU5OzKK68UjyOiqylz587F1q1b0a5dOx+FLCcnB/n5+YiMjETlypXxn//8B8DlQXLTpk26DnKXO+mh6aErtJ06dULr1q3FcOXOrljBQo95GFXUWA+YM2fOFPfDKYWlpQTm5eWhVq1a4jtGjRqleB/1CmwEJZMwQN0Zj9Kea7q/DihZddV7yDxd7WXPH6R07NgRU6ZMQVFRkSQ8QRBEQbmoqEiyAqNGUVGRREllw3v44YclnqkzMzOxcuVK8XthYSGqVauGhIQETUuk+Ph4xMTE4MKFC4iOjpaEsWTJEhQUFCAjIwPdu3eXTObYwdtvvw2gZKWQmiOywh1t10rnZtLtB/68vl66dEk0c50+fbrmvT/99JMkbKCk3Pbt24fIyEgcOHAAlStXRrVq1URz03vuuUfV6kAJ6qSFQs94ZqECPOv9ecuWLaoKLW33x48fR9WqVdG5c2fR2mDfvn0oLCxEZGSk2A95vV4xT6gZI1UsqlatKtnrT1eoMzIyJKb5y5cvx7Jly7Bv3z707NkTf/31l7iHjRWY2clO2gaVJhb+/vtveL1eUQGU91ft27dHp06dULt2bcyfP1+X0J2RkSFOOMnvz8vLE49oov2e1+vFG2+8ISrh99xzj3gEGQvdVsFC84YK3dR7q9z8UWvlrn379mK82fjSzwkJCYad4Snx7bff+r3nqaeeAuBrocI6ZqSTmXLkK6DUoSBVhtmypQq60qQQnXCgirPSGe96uHjxIhISEkQzbnmfERcXp8shnvyeqKgoyV5j1qJGLW8o7JE/eh0ifvrpp+J7gcvHC954442ScY+dpGrcuLHPXuRBgwYhKirKx1qAxj1YCu2pU6dE/yKsrEL7LraexMfHKy5GFhUViZNOVBF2O1yh5XCCDBXohgwZ4vObHoWWHt/COsygUJMcf/z5558AfPc+0lVFavILXF61U/JwDEhNF7t37w5BEMRZdqCks2/Tpg1ycnKQkZGBd999FxERET57TwVBEJWVoqIi1KhRA3Xq1JG8Ny0tTddMu3yFu169enjjjTfEjn79+vWiUubxeHwUMlawUFOgo6OjxfCoiSG7gnLo0CHMnj1bdUWUeleUk5aWBkII6tWrh/z8fLFMlOKxaNEi1fiprd6qKYSVK1dWfIY64WDDZc9eZc00WeQCVGRkpBhXQRAkqx2CIKBTp054+umnMWzYMInSTfNi1KhRouMsPdCjFwCpA48NGzZIjpZSimunTp2QlZUlqQfyvElMTER8fDz+/fdfJCYmYv/+/XjvvfcwdepU9O7dG3369MHLL7+MlStX+jjAscKJEycwefJk8ZgZuv2AFWKokEMnlliolYNcQaDCGBXE6VmxXbp0wcWLFzW97C5ZsgTR0dESBzG03tMjxGg/sWzZMgAlZrZa3s/lxMfH+5yvKIdeY8tq5MiRqtZlN954o5jeJk2aIDIyUtyPSlel/vzzT0ycOFE8kmbGjBkASiZGgMt9Juv5u379+vB4PNi0aRPKly8vCvT//e9/Jauw3333HYASRUkQBMkqHsu6detQrVo1/PLLLxKhefbs2aK5PD3vVd4f/N///R/Wrl2Lxx9/XHSSI6eoqAi33347Fi9ejHPnzsHr9aJ58+bwer0+x6PQtCQnJyM9PR1dunTBlVdeKbEy+eyzzxTTQfcHK0EVnMOHDyM6OtrneBy58yEWtl9noSvj1atX1703Xgu615BFrrjS48vk/QWr0MotoyhyhZEqplRRYes/rXdq57cDkKxker1eyTnHWni9Xnz66afIz8+XtDN5/GJjY3H99df7lTnkK8+xsbGSrUyEEEk79AfNSz2WNNHR0Vi1ahWAy/WEThb17dtXEjc2TldeeaWYLqrQer1eFBYWol69epJV9sjIyKCu0K5YsQJAyUQOq5BT2Ujug0Vpe8kHH3yAs2fPokaNGrY5kgs1XKHlcIJIWloapk+fjtjYWEWFxt8e2qFDh2Lz5s3o0qWLj5kqnRnW46SNHpshXyWsWbMmtmzZIplR3bp1KyIjI3H+/HnFgevixYviSonH40FycrIoDAMlgi01Vf7mm29w+PBhiYMkCrtqR1d1AfiswuidlWXJzs7Gc889p7vjZpVmtWfi4uJEYUJrtVVuVk7p0KGD4nW6upSQkABCCB5++GG88cYbPt5f/TkQU1ulVzq/DygRkJSEI3ZyAyjJf9aTKBVy5Iq7XNBLTEwUhcqIiAhJHWf3aS1dulTR8de0adMkDtC0SExMlMRHy3Mma+pMoW2TzQ+v1ytJ086dO0WlOS0tDcXFxRg9erR4fNWqVavEiSMlh15GOHHiBIYOHYobb7xRXH0lhKBFixaigqK0UrJhwwZJGu655x4UFBSIpoRK0DRmZmZCEAQsWrQIgiDglVdeUbx/8eLFOHr0KO644w7JdXkfdujQIRQVFWHt2rUoX768ondqQHmfHuC7QqsUf5pWVvDesGED/vOf/2DRokU+91epUkU0w6VWELS90z6Lrv4RQrBs2TJ8/vnnSE5OFhUsJS+6jRs3ltQVOmEyZ84cEEJw5513Ijo6Gps2bcIVV1yB/fv3K5qhjhkzBikpKdi9ezfOnDmDgoICyTE5w4YNQ2ZmJurXry9O/Mn7VSqMU4WXmk+zTJo0CYsXL8add94pTlAdP34ckZGRPlY8FHo8zerVq7Fjxw6JNUBsbCzee+89H7Nj+V51FvaIN3/+B9SgChvdq0zLplatWpJ+TI8Xe/Yetg3JV47VJhTl/TI1CQd891hT5Ca99NgcuoWAtWqheSTftlO+fHmxn6VlSet0hw4dsG3bNsV3s3To0EGcsAEu54V8Mjk2NhbVqlVTPeuZQtste062fE8zLSulY4/k5dW6dWs0adLEx5RZicaNG+P8+fNITU0V82HNmjWoUKECKlWqJJGX2D3ujRs3Fn+jljp0wrpZs2Z46623xHujoqLg8XgMe4Y3C93D3qNHD8X6R/1M0Pi/8847qmHpsXhyC1yh5XCCyE033YTs7GyfgZ6itUJ77733Yvbs2ahRowaWLFki+S0jIwNTp04VPf9VqlTJZ18oy+nTpyEIgo9QWKtWLbz44os+96ekpCAnJ0dxsDl//rzEQULz5s0l+3hGjhwpmmPOnDkTGRkZip4zPR4P8vPzxcGPvuuWW26R3GfETBEoGQxpfOTK6eOPP664isUKFmoCS0xMjKhEsAqtXCmkqzByli9fjs6dO/ukh+5loauI3bt3x3PPPefjeCk6Ohpff/216qwwFcTlKO2DBkoEIaXJEPmxRB6PRyJYbdq0CV988YWP4j5lyhTJntkqVaqISist44SEBNSuXVtcka1YsSLOnj3rkydK5vVa1KlTRyJcsHtm5fuJlM7ZpIKNvCz1CMJFRUVo3749cnNzReUjPz/f5zgRI1x55ZWYPXs2fv/9d3Flu1KlSpg7d654DztRMXnyZIwaNQqpqakSIZSaqH/zzTeq8WHTWLVqVVSuXBmNGjVSXN3JyclB//79ERkZ6TPxRKGro16vF48++ihOnz6NVq1a4csvv1TMTzVvtHKFVskcXC5433TTTSCE4J577lHsU5OTkzF37lwcPXpU7GdomRcUFCAuLk5xQos9eoe2U1ahZffitWzZUoxXVFQU3nzzTXzxxReoVasWdu7ciT179iAxMVHiH6Bt27Z4+umn8fbbbyM5OVmykj179mwAEFdSAWl/JZ/wmzNnDq6//nocO3YMlSpV8lnFBC6bjBcXF4v5tGrVKhBCfFZKKfIVU7afnj59OkaPHo1x48ZJ+golpb1z585ISUmR9D1yJ31y7r//fsn4tnfvXjz99NOiKbTcI3SFChV8LEJYlMqYnQSj22patmzps8It34uupnizaVdbbZYrF3RSgcaP7RfpNbkSfPXVV4uez6nyTesJPalEqy/yer3Ytm0bypcvj3feeQdnz54V0yR3ZkVXb+V1Tj4pJT+zPTo62me1nsZRqT+Wh3/hwgXs379flyxA8+nDDz8U61hubi769+8vxoXCWnLUrFlTbAt08oBuHWnVqpXPWeZ0i8HixYsxbtw4v/Gywu+//47o6GjUqVNH0VKFTubSOqx1lFR2drY48ep6CIdjkkuXLhEA5NKlS6GOiis4e/YsAUBuuOEG1Xtong4fPlxyfevWrQQAAUCSk5PJkSNHJL8/+eSTBACpVq2aeB8Acv78ecX3tGzZksTExJDCwkLJ/f/88w8pX748iY+PJwBIZGQkAUAqVapEIiMjyVNPPUUAEEEQJM8BIOvWrSOEEPLKK68QAKR69epkwoQJpFmzZuI9ERERBAB57bXXfOKUmJhIIiIiSEJCAgFAli1bRgghJDc3V/IepXdr/cXFxREA5PfffycdOnQQ0/PDDz/4xIE+c++994rXpk+frhguG48XX3xR/OzxeCT31ahRQ/EdzZs3JwDIkCFDJL936tSJCIJA7rjjDgKA5OfnE0IIOX/+vCTc6OhozXTfc889hvKpT58+ZNmyZYaeoX/NmjUjQ4YMkVwjhEji0L59exITEyOJ+4gRI8R8oN/lYUdGRhJCCBk2bBiJjIwkPXv2lLyDzVP6d99990m+03oHgJw8eZI8+uijkrKWP3/y5ElCCCGNGzeWXJe3L6W/bt26kdzcXNKkSRMCgCQlJREAZPr06Ypt0R9///03AUAGDhxIJk+eTACQ1q1b+9xXt25dxfhUrlyZACCPPvooyc7OJgBI7969yXPPPSe5b/LkyYQQQmJjY8VrDz30ECGEkP/85z9iG2Kh+fzll1/6xIeG8fXXX5ONGzeSevXqidcmTpxIBEEQ2zr7R/sPpTp23XXXid+vvfZaQgiRlO3o0aMJUNK+AZA33niDdO7cWbWsPvvsM8U8p7/Xr1/f59ry5csl99I6/dNPP0nqJe0Hnn/+eVK9enUCgLRt21Z87rHHHiMASFRUlGrZX7x4UQyT9jdJSUmEEEK+/fZb8bfk5GTxmZdfflkxrU2aNCG9evUiAEhmZiZ56623yObNmwkhhCQlJZHq1auTypUrS/q1fv36EUIIEQSB9OjRQxLexx9/7BPfAwcO+Lz3448/9mmvcoqLi8nvv/8uplOpLOSsWLFC/I3mL+1b2OcAkKFDh5I33nhDsT8AIKnz9K9GjRri59q1axMApGvXrj5hN2jQQPK9adOmZMeOHeTHH3+UXGefo7KA1h8hhNSrV08s7w8//FDsSwCQW265hQAgY8eOlZTZBx98QACQefPmiXnVunVrAkAc10eMGKFaFjRfn3/+eVJcXEwEQRD7kJEjR0ri2KJFC0JIyZjFXi8uLibt2rWTlAkAUqVKFQKANG7cWMwPmvfjxo2TXGf/6BjOtkt/+Uf/EhMTSWRkJGnRooVknB45ciQhhJDMzEzFMiKEkK5duxIA5L///S8h5LKcdeTIEbJ69WpJ/YiPjyfNmjUTy+KHH34gy5cvJ4WFhap5bYb8/HwiCALp2LEjIUQqF1D++usvEhUVRWrVqiVeU8obmvdJSUnk5ZdfJvfeey+ZOHEimTlzpq1xtoIRPYMrtBzTcIXWGO+8847Y0alBlTdBEEiXLl1IdnY26d+/vyg0sX/NmjUTn2vatCmJjY31EcDfeOMNxffUrl2bVKxYkRAi7eiowNyiRQsCgFSsWJHs2rWLACDXXXedKCxFRUUpdpALFiwge/bs8RmM5IrAv//+6xOncuXKEQCkQoUKBADJzc0lhBDyww8/qA5san/sAE8FkxEjRpAbbriBACDvvfeeYr7QZ5555hnx2ieffCIJOzIyUlIegiCQtm3b+sSBTgbIBVagRKBiFdLi4mLx9/j4eFK3bl3StGlTEhcXJ15nB155GpX+WKVNz/0PPfSQREjU+qOCiTyd7D2EEDJw4EDxe48ePci0adNIy5YtxWtLliwR61pkZCTZuHGjz7sqV66sWk6UK6+8UvLM22+/rVovCCE+eSP/o7CTMa1btybdu3dXjB/7PTExkRBSIqQPGTJEFHzuuecexTqnBRWoAJDjx4+TNm3aEADk5Zdf9rm3YsWKimkpV64cqVu3ruS+lJQUnwkRqtCybWzs2LGEEEJOnz5NAJC+fftK3pmcnCxRppTKiE500f4PgKiYskou/fvtt9/It99+61OfWrVqJcn/W2+9lRBCJArFAw88IH6OjY0lubm5JD8/nzz++OMkOTnZpw38/PPPmnGnCh0hhAwZMkRRiaNhHj16VFJ/6OePP/5YVLAff/xx8bni4mLSu3dv8sknnyjGgRAiEZqbNm0qKsnffvutZEKCVQKpUs/+NWzYkERERJDPP/9c0hfExcWJCn+5cuVIvXr1iCAIouKzatUqMVz5xJ6aoD5lyhRy3XXXkVdffZUAECfm2HalxF9//UWAywqpvCzU8kZepkpK57hx40i/fv18+iz6R+s8G1arVq18Pt92220+YcuVuQEDBhBCLrcZtnzo9+LiYvL++++LE0VKfx988AEpX748qVOnDikuLvaZKKVtaMKECZJ403GiT58+Yl7VqVOHACCLFi0S5QQlqMIGgOzYsUOcTHvwwQeJx+ORTKwDIO3atSOElEz80TpDy4pOHgOXJ3npWNyyZUtCCCFVqlQhERERJCYmRrHM2T5Mfk1tAo/9o31IgwYNiMfjkaQPKJk8y8/PV2y3hBBxrHrhhRcIIUScRCCESMaqli1bkoSEBEnfSfvjHj16aNZ7o9B2OG3aNELIZTlc3kbi4+NJ8+bNVfMUALnqqqvI2LFjfa43bdrU1jhbgSu0nKDAFVpjDB06lAAgFy9eJGfPniVDhgzxWUEtLi6WdCx9+/YlwOUZ5YkTJ5JPPvlEVCgOHDhACCGkQoUKpHbt2qRp06YEKJlxEwSBdO7cWTEuFSpUIHXq1CGEKHd0jz/+OAFKZh5pJ75u3Try2muvqQ4wAP6/vTOPj6LK9vivl3SWzkZIAoSENQQQAgqERUAICrLJIiAiyiKMu464oOAGoig83IbnKIIKbgNPRBgEEUHkgYAggwjjIIMsExERMWIIMTTNeX/knZtb1Uu6s3S28/186pNOd3XVrdu3bt2zk9PpJCIyLCx5UaNrwb3B2ueoqCiKiopS7+taYV3r62+z2+00dOhQ6t27N3377bfkcDioXr16BIDi4uIMAqQOf//FF19U773zzjuGY0dHR6sHl91up+bNm3sVtCMjI9Xvlp6eTrm5uURE9NBDD3ns26lTJ3K73R4WjmbNmql26A9e3vxZaR944AGvD3ddy8/9DYCmTJliWED723RBa8aMGRQdHW343GazERHR+PHjDWPZ3M+FhYVqsZiUlOQx/gEYHspMmzZtlLBFRPT0008bvsOKGfPG40pf3HrbGN16fPXVV3tYqdq3b08HDx6ka665xrDgNBMREWFQQAUCW0csFgsNHDiQ9u7dq45v9tDwdU12u53sdrvS5hMRXX311V6veebMmTRhwgSDsoYtMERFwmtCQoL6n629LFiaufHGGwkAnThxgoiIevbsaThf48aNafPmzR7tOHz4MBGRxz3VtWtXw7gbOXIkERkt07pHwLfffuvRJrNQsGvXLq9t589ffvnlkn4mta8+dvX3V69ereaB999/v8Tj6fDcY7fbqU2bNpSamkoAqEOHDkpQ5Hl1//79REQ0ffp0jz6dMmUKAaB//OMfql91pZS+DRw4kHbs2EGPPfaYoS26Yo+VNiURGxur2uztvtDZsWMHAUUKTR1f39UFCovFQmvWrKEuXbqo9Ygu5M2ZM4datmxJ4eHh1LVrVw9FSsOGDSkqKsog6OreAN27dycANG7cOEObuL/0/+fMmUNERKdPn1bvscBmvpb333/fo//NXgsdO3ak/fv3G97Tlagvv/yyx9wTHR1tUGIlJyerMZKZmWlQsh4+fJhatmxJf/3rX9WzYcCAAURUbO3funWrx+8BFCsP6tSpQw0bNjS0gQV9i8VC3bp1I6DY0h0REUHz589XCipfv7k+3vh106ZNKTs7m7Zs2WIQor1tuuUegFeln24tN/9GzZs3N8wnbdu2pYiICCIiw3w8ZMgQQxv1sWcW1kvLqlWraMuWLdS9e3eyWCzKc0tfF6xYsUIpmmw2G3Xr1s1nnwJFnoC6B1zfvn1p0KBBdPLkyXJpc3kQjJwhMbSCECL+85//wGKxID4+HpMmTcKbb76J/v37G/Yxx+ytXr0asbGxcLvdqF+/Ph5++GFMnDhRxSu+/PLLAIoSuDRq1Eh9v169emjQoIFKYtCpUydDVuX8/Hzk5OQYYr2AotiiZcuWqRif6OhofPLJJ2jRogW6dOmi4lzMMUd83vz8fKxZs8ZQKxQoSmpz/fXXq/+9xeNxzOO5c+cMCTT0+mhdu3YNOI7xxhtvxKZNm9C6dWtkZ2erGMMNGzaUWL9Vj7M0x6jYbDYV85mYmIg+ffp4LYUTFRWlYoYOHTqEOnXqIDIy0lDehRM3ffXVV3jhhRdUOSWgKJ6Hy7MA3uO8EhISMG7cOK9Jj8xlKjiuqW7duup3t1gsKtY2ISHBZ7ywniwDMMYL9uvXD7fffrvhc45V0tust4d/Q4fDoeKjYmJiYLVaMXDgQENGUHO9T6AoOYeelMP8G+llhXS4D8xJp/Q6tzp67Fb9+vU9Yrm+/vprtGjRAn//+98NMax6UjSgKB6Ly1YFyq5du0BEmDZtGt5++20V//rtt996zTiux55yOzkmUs9o/NZbb3kt2fPkk09i8eLFhjIgeobrfv364ddff8XWrVtxyy23qL7s06eP1/Zz/FlycjLOnz+P7du3Iz09XY3VO+64A1dccQWefvppw/c4Ns18n0dGRhrawwlz9IzVXBZm2LBhJdaz5Lb5i8UzJ7ryxl133YWWLVvCarVi8uTJuOeeewyf6/Hc3kq1+YOTuyQlJeHo0aPqXvj6669VpnGuGb5u3ToAwIMPPmi4H6xWq7qO1atX4+eff8bx48fx888/q9j0sWPH4rbbboPT6cS8efPQpUsXPPnkk4a26DGuZ8+e9YhJHjt2LB5//HE0adIEzz77LICieeLEiRNBXbOvpGBm9Lmqffv2GDhwIHbs2KHip0nLXF63bl388MMPaNiwIbZv3+4xtpKTk5Gfn2+4Jm+JAb3FbZuT73G8ot4+cwIkxpyzgJML6Xz99dcqw/iVV14JoCjOlO/3yy67DBaLBRaLBc2aNcPzzz+PJk2aGPqdy8c1b94cvXv3hsvlwv79+3H+/Hm0aNEC3333He644w78/vvvGDFihMrRwc9eXxn5+V4+e/asRyIvPRHU559/jpycHPWb/PHHH3jggQdUhnZvcaA6esK77OxsfPbZZ+jRoweWLVuGQYMG+fxeXFycqkEfFRVlyHzP94u/hEn6vPDMM8/g5MmT6jmm/3YxMTEemfkBYNCgQSgsLPRIrOiPAQMGoE6dOvjpp5/Ue0eOHMHQoUPRs2dP7NixA2lpaWp86c/Ya6+9Vq2z3G63z/h3ZuDAgYiIiMD06dPRtWtXrF+/Hh999FGJ36uyVLBwLdRgxEIbHBy3SlTsAgSATp8+bdgPJi1a3bp1yWazKQsfY7PZqGPHjkoTPHHiRGrbti0BoKuuuoqGDRtG+H+rAB+LtXrmc/DGViSON2LLwrJly4io2OLWpUsXw/c4XhAodt9q0KCBsko7HA4qLCxUFq7Jkyd79I9ukdHddNhdDyhyw9K16Dt37vSq5eY2PfXUU0REym06JibG72+kH5dZsWKFTw16+/btDZYF3aWpadOmBvdab5seD2qxWJSm3Zc1z6xhZgva3LlzPY79yiuvGP5nC3VWVpay/DidToOmX3cp07X+upUFgMFV7tSpU5SXl2dwB+W4r7Fjx6r3dDfuvXv3qj5mq3uHDh0M18qu59OmTfP7mxER/fd//7fffuYtPT2diIiysrIM75vjDhnd7fCRRx5RMYjm/Rh2Px4yZIjhffa0YDf6QGBXsN27d6v7zdxH3vbH/1sF9HbOmDHDsG9BQYFy8SxpYy+QkydPksViobZt2xqsEcuXL/fann79+ilXS54fFi1aRC+++CJ16NBBeUmsXLnSa5+arf6DBg1SIQO85eXlGa6VxyzH35uv2XxtBw4cIIvFQklJSYZ9ff2+wcDHOHPmjJpHg+Xuu+8moNgKqHursGWW7zvdPVqPEQ0PD1fW/quuuoqIiiyDDzzwgHoObdq0qcS2LF261NB3S5cuVZ+tWbPGo28LCgrovvvuU3OxtzlfJy8vj+Lj4z3imq+66io1j+vwnA545iEgMj7jeIyxN4EeHwsUWWPN39HnLnbL5hAefT/OK8EbexjoljN2DzWPq7Vr1xq+27JlS6+hIXXr1lXHAYpcXN1ut7LKm/fn+y0nJ0edi+83fl5NnTpVxZT269dPfVf3IkhKSvJqPWVvnyFDhijPhBEjRhiur1evXgQUe+t46/edO3cSAI/7b8uWLWrsm7dnnnnG72+tbxyz3qlTJ0O/Wq1WIiqKf9fjcc2/ke75U79+fXI4HCp/ge5NpY+VQYMGqde8VvnLX/7i0WZvsNcLH5PhdRRvnNvA2/XHx8eruFo9Vtpb//jL51JVEAutIFRBTp8+rbIK//TTT0qznpKSourN6XD2xNOnT6Njx44eFreUlBQcPHgQW7duBVCU3ZAzSl5yySUqw+GoUaPUdz744AOl7dTrr+oWyYsXLyqNotvtRq9evXDdddcBAP70pz8hOjoaS5YsMWi53333XYwcORIWiwUFBQWw2Wz46quvsHDhQkyaNAnnz5/HL7/8gg0bNiAyMtJrTUtdC7tt2zZcvHgRv//+O3799Vf1ftu2bQ3WqRYtWqhshWYOHjyIRx99FP/7v/+L1q1bY+3atT4td2Z0rbuepZP7h0lJSUGXLl0QFhaG1NRUvPTSS8r6lZCQYNBax8TEqBrCjK4xJiK/pQuAorIrOmzNMrcR8LQmsBY8KSlJaZcdDofKoJqYmGjQ9nK2ybCwMI/MyHqZhieffBLR0dH47LPP1HucFVPP2vnxxx+r1+3atVOWYdbkmy0dXHrCW2ZUM94s1Po9w2OVLeazZs0yaNj169bHtW6tbN68eYklo/j31TM+nz9/XlkR9T4oiS1btsBqtSIxMRFffvklsrKysHv3bp/76xp9vga+rquuusqwb0REhNdyRR07dvR4b9GiRQCKrFj9+/fH/v37cfbsWdWXXGbKTG5uLux2O7777jscPHgQzZs3x8SJE/HnP/8Zu3fvVnPPd9995/OadHbu3KlqYjOrVq0yzBtcWumee+7xqDU8YcIEj2PecccdICKcOnXK4DlRnsTGxmLDhg145513gv4u/6ZDhw4FYLR6cSZTtnrrXgF6hm+2+sXHx+Of//wnNm7ciFGjRmHevHn4z3/+g/79+3vUI/eG2UPkrbfewrJly5Cdna0ssjpTpkxRz40RI0Zg4cKFfo8fHR2N3NxcZVFjPv30UzzyyCMe++sWUF9lcJg333wTQLGl1Dxf8LNYR5+Pnn76aYSFhXl91ujPZavVqryb9P4y33+M2TLZp08fZd2rX78+3G43EhMTcfr0aUOps6SkJFitVo/nRIMGDQAUj5sPPvjA0DagyIvBZrNh48aNWLhwIZxOp2Fe4uzDP/74I06dOuXhgXHw4EHcdNNNAIp+A/YUMP8GfP3eylcxnDHabO3v0aOHwQtIx5t3ii/4WZydnW04N/d7165d/ZZU4wzSjRs3VmWz+PfVnx/6sXXPBr4uziJeEm+88YZ6vXHjRgBF4//111+H0+nE5s2bMXbsWK9WZZ4bfvvtN/WcMHvgmdm+fXtA7ao2VKhoLdRoxEIbHNHR0ZSenq5iNiZMmKCsEFarVWUlxP9rzy677DKaOnUqtWrVyiO7KBHR0KFDCSiOd/32228pLi6OANCSJUsMFolx48YRABVTiv/X8LPFlRPzAEUWsT179pDFYvFr0YSm6WM4ZkWPQWULKsejsZXWHAfIx2IrV/v27T2yT544cUJpqfXzAp6xobz5SoDh75ry8vLUe2YLrd6m22+/nYiIWrdurZKZsKVMj/fT28sJsjg+Uv+ckxvNnTvXa/vMmYT5/GwJ0bd169YZ/ufkORMnTlTX1KBBAxVfd+DAAUNCL97fW2bft956y2v/8ntNmjQhomItvX79WVlZlJ2dTdHR0fTee++p+Kp69eqpZGF6PKI3a5sZc5wzUGR14sypbFHIzs72+ns/88wz6rVuUdC9A9avX6/uOQCGOG9vx+REInrGZXP2cn/ExsZSUlKSsiBwRlpf6NYPu91ONpuNjh075nMs6W3lbefOndS7d2+68847VUKs9u3bq/3Z0se/FwDq3LmzwRLEtGrViqKioqhv374EeE8ER0Q0adIkr3OJv/g4js8bP368R/IottL+6U9/ogEDBqgkfBzjd9111xn6ia2UbKXT+6UslMcx+vTpQ1arVT1rBw8e7LU/YmJiyGq1evXA4Tm8c+fOZLPZlFfI5MmTlfU9EPTkfNHR0ZSQkGCYG/S8ComJiRQTE6OSGemxfOWFHqPqLTbZWz/xM0ePjeSxYv6O7rXh79gvvviies3xleb99P/1fcxeEmyxBEDXXHMNERFt3LhRvZebm0uZmZkev5t+nj59+qh7lJNYmWnUqBFFRkYasuXyfcOWXM6W7K1v+Z694YYblPVbTxpGRMqbRU/yxZbjxMREstvt6p7k3Bs6vvIccJI5X7+Hvt10001EVBxvzZ4L9erVIyJjojNug34N7BGhrzmmT59ORMakX3qmfD7fxo0badmyZQQUeyyVRM+ePclisag5U/ckWrdundfv6M9KXjvxc0rPdO2rj/S1TlVEkkIJIUEE2uDgIP2FCxeqyebo0aOGRCa8SOTF1owZM7xmNCUiWrRokWExw+cAit2e9uzZQ3v37jUs+NmVh918du3aZcjmysJIREQEtW7d2uf16K5+DCeQ0jNgshsNJwXiZArmjKl8rFtuucXg1qu7z/HDdt26dXTDDTeo7545c8Yg1LFgzwvfY8eOBfQbeVvAmBMV6dfNrpx87i1btqjso5ywqV69emqBcfToUfXQ0X9rXkywS7GeXVRn5MiRhrY899xzRETKdVL/zJyxmBfujz76qFqENGvWjNxut+qfw4cPq/05kQi7UOnXzYJ1ZGSkKqtDVCxYhoWFUc+ePVVWXt70UiNAkSuznqCFE5mwYK2XOfGHN7fz/Px8lXSI3dnNrsC8r17OQU+Yoru379mzR7kOA/DqBklU7CoNQCVG4i0jIyOg6zG7d5bkrmlWugBFioiSMH9nypQp6jPuE70/9AV3RESEujetVquHUJuSkqLGpC4Um9Hd7vV7z1tmd32fsLAwuvTSSw1KBm9bTEwMbdy4kcLCwqhDhw6qb3mumj9/PjVr1syQUdzbPBAs5XGMSy+9VIWpxMXFUYMGDejRRx/1KDujzyP8u+lz6K5duwwCWsOGDYNui+4ea06OBhQpYB0OBzVr1kwlBfz222+pQYMGKqN+ecPZyr0lADO3Tx/HrVu3Nnz2+OOPe3znL3/5i8/fUN/v1KlT9OyzzxJQckKrPXv2GBJB6vcT78evdaVwcnKyh5upr/Pw7xwZGWlIDKUzdepU9R0uX8P/sys5uxDn5+d7fJ/vuc6dO6uQFf15Q1Qs0OoCPN/rPXv2NIQp6c8QIs/wAH6eA54hWkRkSMzFSp/o6GiDsGaz2dR83rx5cyIqFkq7du2qynF5uwa3262+u23bNiIyKlT057K338ZcisoXTqeTUlNTPUoC7d271+d3dCU0Gy5YuaQL/xyOxhsra3WhtyoiAq0QEkSgDRwWiq699lqlzdP7zVsMpL55y8apl3HhTLC8iDGjxwLypteyvPnmm9X7FotFPVDMAoCOrrFn2NJl1iY6nU5Dxt60tDQKCwujwsJCGjx4sKHc0Ntvv600k23btqVdu3bR3Xff7bFYMKPHdfbu3Zt27dqlHrKBWsb4+2atpd5vemZhjo3JyclRv68e+9O7d29yu92Unp6uFpK8GNXjbc3lYHzFWpoz1HJsMxF51HA1ZyxmbfiCBQto8eLFBBiz2OrXYbFYlMX7pZde8ihzARQpGjiTsh5zfM0116h9zA9Rc9ZJPhdQJHBz9kbOqBrow9Ych8ljkuvqcgyaHpek/676b6EvwPRY94KCAr8LF8b8W+pWMYvF4nWBqHPixAlD/Kjdbi+xliFnZGVvDSCwchHmPrvkkkto//79FBkZqeqkAkXCPJFnLJeeKZcznhIRbd682SCQ+luQmYULxmx5HTRoEN1zzz00depUIiIlKN16660e18HKGPN2ww03KKVKbGwsWa1WcrvdSgDjjMwl/caBUB7HaNq0qbLuXHHFFWSxWMjlcpHb7VYLd46V1xUpQHFGWb5uXUjwVc7NH7pA++mnnxruF6AoRr6wsJBcLpdaZA8ePJiuuuoqslgsPjPLlwVWBnu7P8y/vW4lO3DggMHabY5xBWBQKvk7NlFxjflhw4Z53c8X5jI4RMV5ErxlMvdF/fr1qW/fvkREtHv3bnVv2mw26t69uyFLMRGRy+VS8+7bb79tUGTycRo0aGBQ8uiYvSesVqsaX5z/gRWhcXFx6nv8/Bo8eLCaq1j40udF3XJ66aWXGjx9fMGf85gwK9EaNmxoyNPBShD92cZ9xwqfzMxMpVDauXOnqkdLZIx31RU8Zvg5ynOLN/Ly8lQcM2fSHjp0KDkcjhKV8bqxYvbs2Ya5z5x3RZ+vP/jgAwKKrdVVFRFohZAgAm3gcI3Ce++9l1q1auXhmkRUVG6BF/x6CnygqGyAzuHDhw0lUXiBsmnTJq9JE7gUjn7MUaNGqc/ZksXJZ1iDay7doKNP6AwvZO655x7Dvm3atFEPhpMnT6oFpLcSIqdOnaLk5GSPRBEloVsgdEGcrZ+B1AHl7+vlSYiKamjyQ0u3jrz99ttqn+TkZIqOjqYJEyYQAMNi4JtvvvG4TpfLReHh4ZSZmUnvvfeex8LGG5ychDfdkmsuem+u6co1YQ8dOqQWUvoDmqh4YWaz2dRCdcWKFYbFMW8ZGRnKfZ1dn4mIOnTooI7RtGlT1V/6g9bhcHjUTGZh6cEHH1QCWqCLutWrV3u0j6hojLZr1071jW710H9v/V7S3d90LTwRebiWecNcB7Rfv36GRYcvj4vLLrvMw/I2b948JUz6gq08bdu2NZRW8WXl17nlllsM53M4HEoxYrfblYJs/Pjx5Ha7qUOHDh6lb3hjoSU3N9fwfkkubWaXdsYs0JqvhwU8b264jz76KEVGRnpYb1944QWDIo6VbCzksoKqpN84EEaPHk39+vUrcT+3201z5syh48ePe3yWlJSkLO3sAsqhG5dccomaUx0OB2VmZhrueVYmWSwWVVdy8eLFdPXVV5dKuNTrXZ4+fZqaNGlCNpuNNm3aRP369fNQ1GRkZJDFYqH777+fgGLLVrCsWLHCZ1Kd7t27G0IEdLit3G/evAR4H05stmXLFqX80l19zcycOZM6depEs2bNUu8dPHjQY7+wsDC/ylRzOR6iIo8pb8/wQOGwAN0DyFxXdO/eveo+Pnr0qPIai4+Pp7CwMLX+8JWckIXhlJQUGj16tBpPBw8eVMoFfsbr6wx+3o8bN44KCgpo1qxZNGfOHAKKlOCLFy+mo0ePKmUaC4GHDx+mm266yW9yJfNzzrxm0pM1AcXeKHrZr3HjxlFOTo5SKNevX9/nOsTlcqnvsVDMnnI6fM0PP/ywz7brYSn+lH/e0BX5q1atUp4n3sYtC+wA6ODBg+q5x9bpqogItEJIEIE2cFi7/eKLL3pYK3U4pisnJ8cjsyzHRxEVx6KkpaWR0+k0WPTuvfdeioqKUi6AbMnlBQ5rRNnSQVTsXshWPRZ+fcVtEBkndB2bzWaoe0lEKuOy7vbDWX2tVqtBoOD2cdH2QOHMzPxQY9gdWI8x84WurV20aJHX4+sL+rVr16rP2VLENQvNv7HNZlMLAV6I8sPf7XYrYcafJZrjWvWHEsOCtP5g1P9fuXKlwZJh1t7yeyzYcHt2797tEQur93F4eLhhwRQWFkYJCQnUrVs3slgsZLPZKC0tzZCFlxdAderUUf25bds2DzfTQPHmcqzjdrtp9erVHt+bN28ebdu2zSDk6BYFIqNww4sl8/jWYfdf7rPLL79cKX+sVquq/6zD/W6z2Wjw4MHkcDh8WkfMcObfo0ePKst7MH3HGTF508MP9PHGloaYmBi16Of32fJx4403GiymgbjamWtaM2bh3gzHfmdkZKgxNHjwYIqLizO4JerXs2/fPkNGXnbl1j1SzPVkK5rnnnuOABjcQ48fP04bNmwgp9OpYtQLCgrU/HTDDTdQRESEytrdrFkzFdPNbu6cebVOnTo+472DhfvF5XIpS7EvOH6dXVfNyrNAcLlc6rflWGidFi1aeI2/1NtKRPTee+951HzX99GVJRwSomdRrig4U67FYqGUlJRyO25iYqLBYq/HsRIZhbgzZ84oZSLfU/yMKqlOsz+F96hRowgwekexovLee+9V77EShr1k4uPj6eqrrw7YTZfJzs6md955R7nd9u/f3/A5KzZ4u/zyy4mIDPOVOcQqMjLSb/1wjpEFiryPvHlWcVZpX+7fREVW3NjY2FIJlnp26cOHDyvlhK/+430LCwvp6NGjhnmwKiICrRASRKD1zpYtWzw0iRyP8+GHHxLg6ZpEVGwl4DIldevWpeTkZOWSx64oeswEYHT3JCp2O77++uuJqNgl5cknnzR8b8mSJeo7nIDB5XIZ3Cz9uUf6WvixxcXhcNDBgwfVgo1d/BwOh4dVxhxrCYAmTZoURK8XLwyB4iQfDFuu/CXIITLG4vTu3dvw2axZszzaqPc9Pxx405PMEBW5cDmdTrJYLCpOWYc1q94EL8a8+Nd/H3MSDV6QsRBtdjvzBgteumvW6dOnlQsYx7suXLhQKQfatm2r4tPYojlu3DiD29iwYcM8CtgzbAk+deoU7d27lzIzM6lRo0YeCxJ/cDy5PwGoJFiZU7duXcP7+vFYSDC7LuvwvHjDDTdQixYtyGaz0bhx48jpdKprffXVVw3f4bGlWxS9uYWuXr3aUC6FqCi2kq147H7qzVLgCz10gTen06li882f8ZaVlUWvvvoqud1u+vjjj73uE4g7m9kSy5hjws2wYMrCvz/has2aNapkC7uhA0arYUxMDDVq1Mjguu8t2VV5o5dMWbNmDREZkxZlZWWpfd9++21Dn/A8x54DJ0+eVM+RhQsX0tGjR0tVMsoXwd5bulBVmhIhemK7QYMGeXxet25datCgQanbyvscOHBAvceKKG8eSBXBE0884VW5WBbYe6GwsFDFGeveLnpiw5dfflklDCMqUq4tWbLE5/3Ez/20tDS/oRCsxL777rvVe+y9o+cf4OPpSe0yMjKU0jdYOL+DbhkmMnrb6HOT2+2mBQsWUJMmTTyUIxaLpcRxy8cryXpsjhMmKvKuYSXVAw88EOglGtBLEhUUFJDb7aZbb72V3nvvPb/tZcLDw/0K7ZWNCLRCSBCB1siLL75ImzZtUlam/v37U1xcHN1+++1qUcEWlKeffpqeeuopw0MjPj6ebDYbnThxQsW4ZGdn0/Tp09UkdPToUeXCwot4m81meLDwvuHh4eRyuZTrj26J6dixo0EYiomJUZP53r17aeTIkR4WSm94e+AvWbJEuTtdccUVhjjKefPmUX5+vnLBZgFCf9Bw/KDuzhsIei1Sc9wJZ9tkrawvUlJSKC4ujpKSkigxMdHwmf476L+HDi8eAM/6nD179lQWaXO2XaLiuoqsiPCGP6uV2X2bFR/x8fHUq1evEuMwiYqt7qxd18+Rk5NDLpfLIykHW163bdumxuQbb7xhsOCzm+3QoUM9LDW8oC8LZ86c8SkYBQpr0s1CmH48FjjNLvVmHA4HtW/f3qAEYYUOC7a6t0Dr1q0NngscE6+j37/cn3wfsTv9888/r4S8QOF6mVarVc1dqampKrkZAEOtRqDI2mBe8OoZoXkbM2aMYZ8TJ0543Ju+BFfzsczoMaElxdfr+HIlveyyy8hutxus0qWxKgYLe9lYrVaqX78+HT9+3HDdZsVOfn4+paenU0REhBKE2MNgzpw5SrHH1h7+35+iLBBKY7nmDMB8bcHC+QgiIyO9Cq52u91n4rhgBFpdoMzLyzMkCAomS35VgbPyTps2TSl+WJnLgjorQLt06ULx8fE+FQNm2JukpLwUrKB98MEH1XvsLbFw4ULDvmZFLeBZmzZQ2H3XW21iFuTT09M9BMwhQ4YQUOwJx9dZkmKd2+vP+4vzbpiVSr179yagKA49kOezNzgfSaD3pfm+yMjICNgbqDIQgVYICSLQFj0c7r33Xo/C8t6KowPFGYY5noOtsbyIYSssH++ZZ55R8a1AUfIBp9NJaWlpRFTsTssukPyw4gfHHXfcYdB2zp8/3xD3Q1TsGnbfffcFff18rd649NJLyWKxkNPppISEBEPWzf79+1Pfvn3JbrfTwYMHDWnxN27cSAMHDizRPdgMu9r4mtjr16/vN9umXmKCSx/oDxlOgKRv3izYLJiY0WMruZyAmYSEBJ9t1BN3eLtOdufiraCggBISEmjx4sU+r9kbLKgEunjldo0fP14tknhOGDJkCNlsNq+ZKZmCggKfJV2CwVf5l0BhgdacAVY/Hi9AZs6c6fdYDRo0oISEBMrPz1dx8byoYdf1mJgYOnjwIBUWFpLFYlFCY1xcHCUkJHiM/86dO6vjWK1W2rRpk4p1Y+v7U089pYTnQGFBJSwsTMVot2rVSilYbDabindOTk6mHj16eE1Uwont7Ha7T8tmbGwsRUREqDHGwrQ/gTYqKoo2bdrk9XjsSRCMu6ZeKkWH4/YiIyMpNTWVrFarwTpaFtxuN/Xt29fDMs/ZUzMzMw0u+UBxlmJfc4WuUOC4ye7du6vr4N/g4MGDBJSshCkJdo8N9t5iQQEILtEREVGPHj3IarVSx44dPQQQFjj08BKd9PT0Eq183C5f1siS3KqrMjExMZScnKwUixzPzfkaXn75ZWrTpo1aqwwYMCCg47KiVA9Z8gbnnNDdktn7y6xc0TOd87g3x/0GCo833TLMrF69moYPH65crPVETfPmzSOg2EuC10UleXUFck+wi7fuFed2uyksLIyaNWtWptI5cXFxqgRTILBSnGGvo3Xr1pVaqK5IRKAVQoIItGQoucOLoeuvv5727t3rkWmzWbNmlJWVRTabzeBSdskll6hF7ooVK4ioeHF+7Ngx9UCKiIhQFhS24rndbuWu+9xzz9G+ffsIKHKJjImJoaioKLJYLF7jUdeuXUtLly5V8av+svD5gh9A3tDdxXr16kUzZ8409EfPnj3pscceo6SkJJo+fbpyTyvtAmLJkiV+Hy69evXy6op58uRJys7OVi6yjz32mEpUoT949Qyy/s5z6NAheuONNzze1+vWefucqFi7PH36dOrfv79BqPGmxdYxZ9ctKzNnzqTOnTsHtK/T6aTGjRt7ddsKVjFRWvTEGsHGXxGRyohtjnVq166dsoByiQpOzOOL7t27G8aanh15xowZyq01PDxcxY7pZSwAo3WQF5Ft27alPXv2kNVqVTGt0dHRaj8eo4FaWxigyH2VXVrZOyEsLMzgnqjHvnljx44dPu9f3SW/a9eulJeX5xE+wdlmuU0sRPuCrakdOnQI+FpZcWFOJqTPV5dddhmlpaX5rcMdDLqyTRcsWQHBSYD0McyW1Tlz5gR0jubNm5PdbqdOnTp5XFt51ILlTOJ33XVXUN/TvXG8uQ0zhYWFdObMGTpz5oyyZKWkpFCdOnWU98mNN96o9ueM+vzMNKNniPYFC3M1kcsvv1zNQWyBdbvdas1y+vRpQ8z9ggULAjouh2aUlLiqZ8+eBBhDJzjUyBwmdfz4cXI4HNSpUye1HmHlfrCwx4+/JEw8z+nPYU7Qxa6/7I1jbqsZ7j9/llz2kuMM0kTFmZxLEphLIiwsjKKjowMOM9mxY4dBya1n8w4kM36oEYFWCAm1XaDVYwS9aQT1rJDz588nl8tF8fHxlJKSQg6HwxBfxItG1tR17NjRUDevTp06hoQ5+kPc7XZTVFQUJSQkGJLb6JvZfVd318vMzPQa3xEIU6dOpf379/v8nF1h7rnnHiooKKDw8HAaOHCgIV4GKLIOcR3D0qInBvIGL/bNVgJz2ZADBw6o8jW625K5ZElpFkLLly/3++DTE5EAULUHvVmyzOfPycmhvn370vPPP+/h7lzRdOvWTbUpGOGiPNFjiH1lPvVHbm4uhYWF+XV1Z88HvVySN9hdl10X9bjNq6++moiM45UX1uaY1VatWtHq1auVCzjH+rGlOCEhweDGNmPGDAI8XX0DpbCwkOrVq6cWes2aNTPMO2VxW2WFFitm+vfv7+HZosPv+bOScr9wPehA4CQ0Zjc7vZTJoEGDyqXczLx58+j48eMqnpC3mTNn0unTp6l9+/Zkt9sN57jpppuU9SsYiyYLeFar1UOhkZSU5FcxEAhsvS9N4pq//e1vhrHuzWskOTmZwsLCVJ6BRo0aUVhYGGVmZtKll17qcV936tRJlV3yRoMGDUp0Wz127FjI58pQwXPQpk2bVKJCfb1BVGzZ53jbQGDFhtnbwAzXgOda6UTFYQnePDzy8/PJ7XaTy+WiF198sdTWQo6B9udFw+Eb5tq+FotFldrjbM8lofdrUlISpaamergWcyiOnnAwLS2N7HZ7mRS+7F0TFxdnWC8GQ35+vpr3IiIi6NixY1XKK0EEWiEk1FaB9sSJE0ogi4yMpL1793oV6lj7DhTVGWWhhK2zt912Gx06dEjFm+oTUmJioiHmSHfJATzr7rGbGSc14oy6MTExKhmKjm4xADwT4ZQX7KpoTlCgl5d49NFHCShyVfTnElwS/KD1ZZ1jVyuODR4+fLgSAPTsxgyXwmDYkqa7TlcE9913H1ksFgoPD1f9wZlzeWFXkecvDXpCLr2YeyjRXY7LohjxR6dOnQgouSQOW+OHDh1KgwYNovXr15Pdbier1aqyX3PZJm+KCn2z2WyGOCe3263Ka5nLwrDbry8X3WDRLYZAUazq4cOHgz5OYWEhWa1WJSC2aNGC7Ha7IdTAl0DrL5lRYWEhvfPOO0EtwDj7t7e5Ji4ujoCiUA12AS6tOzxbfO12O0VERJDT6aQVK1Z4/Oa+Mt4Hix57a57zu3btWiolD8NWnMjIyFK5R+rx9ICnO6k5YY++3X333YY8DNu2bSO3200Oh8Nv39WtWzcggaSmwkpZACpzM4/H8ePHq/127twZlJKChbP333/f735s4dSVf5yHoiJdW70J0t5gJbpOfHw8NWzYUHl7BWI99TZmzbH3upfCrFmzVBz/iBEjgr9ADf6NExISyhQHu3PnTpXBHwC1a9euTO0qT0SgFUJCbRJoXS6XWlixu2Djxo391tZLTU0lh8NBDRs2JKfT6eESytp31qTqVlJz6RsWaAYMGOB1Me1yuSg2NlZp2m6//Xalwfb28GAXSLYIeavRVx7s3r2bOnfu7HVR2rlzZ5o0aZLBWhysq6QOFwr3JdBylt3Jkyd7WLL/8pe/UGxsrCEzcePGjSk6OprcbjeNGTNGLUT1eq8VhdvtVvU1CwoKVOZG3UWsKgm0Z86codjYWJ81VkOBy+VSyhF/ibXKwrFjx2jixIkBCVB6EfukpCSljGDrCLeVlVlcPiI1NZXi4uIoOjpaKZ4iIiIoKiqKsrKyDIJ727ZtDefk+tHffvttuVyvHjfJW69evYioSAh56qmnArIwsPWQrdN87WbLpQ6XLStvWJnmLe6W6y3PmzdPWY9LWhj7Qi9FpguuepmQyy+/POi4Un/wcc0u8WwdNyfjCRR+XpTlWR8fH0/169f36hH08ssve4yzhIQESkpKouPHj6s4dKCoLBpb5n3FFxMVhWg0b9681O2tCcyYMUPNQw899JDfqgWBwrGmJSnN8vPzS8w1UBFwCFZJFmTOc6DTrl07cjgcdPnll5PFYgkoMziPy5EjR9Ls2bPJ6XR6TVLnTVF58uTJ4C7OBJeDTEhIKHN4hC50+wqJqgxEoBVCQm0SaJs0aUIWi4Wio6MpOjraQxv2zDPPGDSRbAUYMWKEqg/KwqbT6TRMtvn5+WS322nw4MFE5Nsdht2vfMEJp4Ai10S2mnlL356VlWXI6GlOcR9qWKta2tT1RMUTsh5TaMZms3m4GANF5S7MQgoLlHptPqfTaShzUpG88MILBBS5l/ODlqlqAq3gCf9+utaeX7tcLkOpqueee07Ffj322GPKunH8+HGP7M28paamerircoKP8oxb3rlzJ02fPp0ee+wxFec7a9YsVYLDbCU2k5ubSxEREYZkUGxN5Izm3sazy+UqU7IUX5w5c4asVqvXMht9+/YloChDOSfY4/jpYGnRogVFRETQmTNnaOTIkSrZjMvlohkzZpSLcGGGBT/zQpnrufqrn+yPrl27ljoshenQoQPZ7XaVyFCvccqeRaxgZY8ZjtOMjIw0eNHwdvz4cZ/ni4iI8Pu8rC24XC4KCwtTiSTLCltZyyORX0XAnhW7d+/2ux8bGPTcIVlZWWpsBZqUyjx38fnNMcnmsRtMmIQv+BmTkJBQLl52M2fOLDFmONSIQCuEhJoo0K5bt44uueQSwyS3Z88epVHjySg+Pp4WLVpErVq1UslkuC/cbreKWTl8+DDt3r27xIewbkVlAWrdunWGfRo3buxXC6eX9SAqri+pJyJg0tLSKD4+XsWVzps3L+i+Km/KGrfBWS/9Ldr0+recqMGXYMgKAa5zuWfPHjXWZ8+e7aFwKG/YnWjy5MkUFxdnWJCIQFs9WL58udKi6yWdtmzZojL0Wq1WVbqFhVGOuX344YdVTJjFYqEJEyZQXFwczZo1ix577DECQGvXrlXn69OnT1A1aINl/fr1XjO4X3bZZT4FNM46ao475qRWAOiqq66iF198scLaHShnzpyhqVOnqrnIHHYQDCUpICuCb7/91udc3rBhw1JbcVq1akVRUVFlaZryLPj8888JKMrEzfkE2IsJAHXu3Jk++OADslgslJSUpOI8OVMsbyUlJQoLCws4qV1NZ8SIEQSUTzgIrxnKal2sSPxl1Wc4RCkmJoZcLpeyPPMWSIIk9i7TvcJcLhc5HA4Pb7PMzEw115UmASefb8WKFTR48GCKjIxUxpKEhIQyebdVZUSgFUJCTRFojx07RiNHjqRp06ZRy5YtCQANHz5cfc6WusOHDxuEV2+JXKZMmaKSZ/AE43a71eLVXEZg37591KpVK2rcuDHddttt1K5dO4qLi/O6eOjfv7+y7viiXr16hgVtgwYNyGq1egjHTqeT0tPTyeVy0YIFC6pUEoCysHbtWr/WKf4tWRht0aIFde/e3eu+elZWb3HIoSAsLIzatWtHFouFrrrqKvX+9ddfX6oyS0LlEBUVRY0aNVJldh566CGDMMevdSuYw+Gg5s2bq1qe5nqb7EI/dOhQ9V5mZqZyaa4odMXZ9OnTVZInb1lJc3JyyGKxeI11ZAtJWS1/FQln2Q0WTu4WbEbgioTddEtKaOaNlJSUMluAOIfBggULDEqRU6dOUVhYGEVFRannLFHRHAcU11t/9NFHqbCw0FBmxB++6n3XRtgjgr3AygIrgqtiiZdg4bwYDz74ILVv395DUVeSh4ivTMUcbqArG3Nzc1XVidJ4Z6xZs8arMjEyMpLi4uKoSZMmQR+zOiACrRASaopAq7u9sZaYs9EdP36crFarKuWhF5cPCwtTArDdbqeoqCglQAJFBdmnTJlCFotFxYPpSQAOHz7s053QW004TjK1YcMGn9fSokULQ9mUlStXksViUWU4GKvVqmLhahNut9trhkVf6Jb3yqBx48bKM0Cv5ydUL9jKyn+5Jm1UVBQVFhaq5Gm6N0X37t3JYrHQrFmzCPCeXTYxMdEgcKWlpZUpsVqgdO3alTIyMtT/DRs2JLvd7rFQ49rIK1eu9DgGLwZLU2IpVASaTGn48OEG4YnLsPmbq0ONrzrLgRAfH+9RzipY9LqxnNQMgKE+d9euXdX+HL/Ngi5n+NYTSLEbtzfKS4CrKdSrV4/sdjvFxcXRkCFDSn0cDoeoKURERFCzZs0oMjKS0tPTadSoUcry6S0sQYcTKZnnPV4b9+nTx/A+z4fBJoOaPXu2x1qRhdvdu3dTVFQUtWrVKqhjVhdEoBVCQnUWaDlFPD/k9YRNLJByinkAtHXrViIqrlV26623Uk5ODm3evJmAooQf3jR8vNlsNkpMTFSWUJfLpVyoNmzYQHv37qWYmBh6+OGHaeDAgV4ThfC5/dWCTEpKMmRHJirWdO/fv58KCgpUrdqKdpmtCWzcuJEOHTpUaednizIAvwnIhKrNnj17KDo62kPDfsMNNxBRcTkgnmeIijPLclIXb9YCdiXkMIa4uLgyCx6lYdmyZQQYS5cVFhaSzWbzudAqKCig6Oho+tOf/hSqZgYNW1pyc3PJ7XZTRkaGR01vPYMv/34DBgyoklas3r17B1WihSmveNTw8HBq1aoVFRYW0t69e8lmsxmyPptdYrmagLkkCStDevTo4fU8rHgeO3ZsmdtcU+AM6LwFkvDIG1deeWWFhjWEGn3dxmX6uCLFwIEDyeVy0RtvvEFut5sKCwvpvvvuo1OnThFRUa1dX33hzcU/Ly+PnE6noXxPSbAnDgu0Tz75JK1Zs4ZeeeUV5RnjcDg8MjbXFESgFUJCdRZonU4nhYWFUY8ePQgocgHkBysXcQeKytnoAuQ777xDAAx19O688061P7vf6Ru7Gfbs2VN9J9CEKmasVqtBi61z5swZslgsHguuAwcOqHNxEihvbjJC1UNPLFRT3MJrK1yqQd927NihLB5Nmzb1+A57j/iyErJC7fbbbyciqtSFTVxcnME6zHNlVYiNLS1/+ctfCACtWrVKZZoHjAlxWEGoW14aNWpU5qyjFQFfjzlR4Ny5c+m2227z+b3y8uhp2bKlwSVeV/B4q5P7wAMPEFAUb2umSZMmPkuVcFLGKVOmlLnNNYkpU6Yo62P//v1L5frapUuXKh0mECxc8hCAElSJiuazhg0bqkRxt99+u8pQzmVtzB5xOpzB3dzH7LIdqKKck6h16NDBQxnVqFEjstvtZLPZfIZOVXdEoBVCQnUVaLlGpK8tOTmZ4uPjqXfv3h7f5RI7cXFxdMUVV5Db7abw8HDlQmi2wDRr1kyV62DtH/ebL+2yP+rVq+fTpZBjpPS4DcZcvxQA7d27N+jzC6GFE0NVdFykEBrMpbs2bNhAQFFSJW8KC0785M86VqdOHSU8WSwWVRon1PD8wy79w4cPr5bPBx1OCDht2jRDFvkHH3xQ7bN69WqDApSIyG63e8Q8VwXY7XfYsGHqPU5ABnivLcrWzmuvvbbM5+fyY8eOHVNZpHnzxsmTJ8npdNJTTz3l8RknJ9KzJTPsxrxnz54yt7mmwesPAIa8DIESijj9UML3b7169Qzvd+zYkWw2m/LYS0pKUu7vQFHZorp163ot/0VUXIrKHLPOZcMCja9PTk4mp9PpVXjmclylMY5UF0SgFUJCdRRoFy9e7DNuVd8aNWqkvrNo0SJq3Lgx7d+/X5XW4C0uLo4A0OzZs5Ullq205jIDd955JxEVu0stWbIk6PazNad169Z04sQJysnJofz8fFWKwpe7ob542LFjR1BxpELl8sADD9CqVasquxlCObFt2zZldeUFUyBZOX3BWdE56U5lhRJwwrxp06Ypy7G/ElrVARbmBg8erNyIbTabIXvuX//6VzUn60qKqmod5HqwzJgxYwgwJjfU67tyEjD2AigLLDxnZGSo8erLOlsSHGN76aWXenzWpk0bDzdloZg5c+YQgFJlrk5PT6+S3gelxe120+jRoz0spnpstx5+xkoZh8NBDodDWWvNsOHEW7K8yMhIr2s1c4gCH2PUqFEUFxdnWJcSGRNX6olMaxIi0AohoaoLtG63mwoKCujkyZOUl5dHbrdbJX0KZHvuuedo69atSiuXlJREycnJhgc/W2FdLpeqM2m1WslqtdIrr7xCQ4YMoY4dO5LValVWFi5jURp3n3Xr1qnztmnThiwWC9ntdmrTpg0BoNWrV/v87uzZs+mKK64odX8KglA+PPPMM+o+1rMUl4a8vDyyWq0G5VplYbfbqW3btkq5VxPmm6ioKEpPT6d27dpReHg4NWzYkOLi4tTik+d9Fmx5q2r1HJlevXqRxWJR7W/VqhVFRETQX//6V6pbty4Bxdn4ubY3AJo5c2aZz+12u6lOnToEQMXHfvTRR6WO5+zdu7fXvo6MjKQWLVqUub01GXY95qzSgdKwYcNyqXla1WGlHABauHChel1YWKhK+gFFrtu+iIiI8DoO+/Tp49H3Z86cofDwcINnx5IlSwgoCnGz2Wx0+eWXexyLDTTeBOeagAi0QkioygLtqlWrKCEhgWw2GzmdTrLZbMp9T7ecmq21y5cvpyuvvNJDuNVjT9lVp1u3boaEJ/o+5uyKLVq0UG46qampXmOCAuXBBx801FNlN2dvMXiCIFRNcnNz6YEHHij1Yl6H47UA7yEHoaJNmzZkt9tVqZ7SKO2qGm3atCGHw0GNGzem+Ph4GjhwoJp3d+7cqeoLnzlzRs3LpbE4hgpejL///vvqmdW8eXP1OYfVrF+/Xr0uSVkaDC6XSz2zyuq6ygL3mDFj1Hu8Lhk9enRZm1qjYYFt2rRpQX0vMTGxxtY81eH6xw0aNCCXy0V2u12Fc7jdbrWOvPXWW30ew5enAMfd6/lOOEQDgPLY4ZhdLgPmzfuG55yqVCKsPBGBVggJVVmgrVevnlerq8ViUQ/TLl26UH5+Pi1ZsoRefPFFevjhh4moqJyO+XsHDhyggQMHKotoy5YtDW677PqRlZVF/fr18+iTyZMnE1CUCMBms3kkbgqW3bt3E1AUe7dt2zaqV69euS04BEGoXuiuZ3pik1Dz8MMPq3bMmzev0tpRnrBQZ7PZqGHDhjR//nx1jZdddplSJjCFhYVBZxEOJVz2plOnTl6tTJxVddCgQcq7yF95nNLA7tuLFi0q87Hi4uIM8Y+cHfzVV18t87FrOjabLejs1bGxsV7rStdEDh06pLLLm3Mc8P3jr5zeHXfcoQRSM5xPYf78+SphYHx8PAFFNZeJiLp160Y2m03F+XpLsMftmDp1alkutcoiAq0QEqqyQGuz2ahLly4UGxur3IDNQuqCBQt8fr9z586GfYmKE2pwAii97iDHVezevdvr8VgbyhnzyiO+6tChQ1WuLIQgCJVDvXr1Kr2cBicx060M1Z28vDylBG3VqhXl5uZScnIyJSYmElCUfTSQWrVVCS4FxQtysyWdFcIWi6VCykC53W5VaqqscFUCXoewVau8jl+TycrKUsonfR3Xr18/io2NNYwLt9tNZ86cocjISGrTpk1lNLdKcfjwYcrMzPQ7zrZu3erTCl5YWEjR0dEUFhZGTqeTrFYrNW3alGw2G6WnpxMRUYMGDSghIUF5F3oLY7jtttvEQvv/iEArlJqqKtByEouJEyfS7t27admyZYbYUwDUtm1bv2VQxo4da9h/9uzZHjFSNptNaeJTUlL8JkBxu92qBAdgLPsgCIJQVvLy8ujkyZOV3QxatmwZPfPMM5XdjHKF6wR36dJFvcfJvcrDdTbUcFkbX+1+6qmnyGq1ksPhMJSoq4q8//77BECNuU6dOtWosjIVyZYtW9QYTkhIUO/ze126dKHBgwfT8ePHqX///ur9snqY1RbYNTk5Odmr18aqVauUwYVdh8PCwshisVB+fj45HA5q3769ckf2ZsDIz8+na6+91mud8pqACLRCSKiqAi1n25wzZ456j+vZWa1WrzEPJ06cUK56s2bNIgCGFO16rCq7YwGgp556ivLy8ggAXXnllX7bdfjwYZo6daqUyxEEQahGcD1o80Kek1/FxcVVTsPKwLp16wKuhVmVcbvdBtfZunXrGrI4C/5hN1egqMyRXleZt7S0NOWZBsBrSUPBO7z2nDRpktfPV61aRQcPHvTwInzyySdVfHhmZiY5HI4Qt7xqIAKtEBKqqkDLGem4pt62bdtU8ic9xX9hYSG53W7Ky8uj8PBwCg8Pp8LCQmrQoAGFh4eT2+2mwsJCw0Suu9OFh4dT3bp1VcY6iWEVBEGoeRQWFlKPHj08Qko4vpazAguVQ4cOHVTZOgDUp0+fym5StSE/P19Z7EeOHEnJyckEgHr06KG82XSvNFboC4GTkpLiVyDlUo7sPgyAUlNTVZgDAGrSpEkIW1x1CEbOsEIQahhHjhwBALRq1Qq//PILLr/8crhcLgBAmzZtAADnz59H3bp1kZiYiJEjR6KwsBCFhYW45ZZbcOLECQwYMABWqxUOhwMdO3ZUx7bZbHA4HEhISMCUKVNw+vRpfPbZZ2jdujUGDx4c+osVBEEQKhSHw4EtW7agQ4cOhvcfeOABWCwW9O/fv5JaJgBFv8PFixdx7NgxAMDNN99cyS2qPkRFRaFdu3aIiIjA8uXL8fPPPyMsLAybN2/GiRMnsHv3brXvkCFDAAD/+c9/Kqu51ZIJEybg/PnzWLt2rdfP33jjDVgsFrz00kuIjIxEWFgYfvjhBwDAgQMHYLPZ8Nprr4WyydUSEWiFGsc333wDAEhPT0dGRgYAIDIyEgDQtWtXAMA999yDs2fPIjc3F5988gnat2+P8PBwLFmyBBaLBTNnzlTHmzBhgnq9ceNGnDhxAgDwzDPPYNKkSRg5ciTWrVsXiksTBEEQqggJCQk4d+4cVq5cWdlNqdWMGTMGcXFxsFgsKCwsxNixYyu7SdWOli1bAgBSU1Oxb98+WK1W1K9fHw6HA1lZWQCA//7v/0bjxo3xwgsvVGZTqx33338/AGD+/Pken128eBH/+Mc/kJ6eDofDgd69eysDDADY7XYcPXoUffv2DVl7qysi0Ao1iosXL2LNmjUAgNGjRyM3NxcAUFBQAACYPn06rr32Wrz33ntwOp3qe0888QRuvvlmWCwWvPLKK2jXrp367Oabb8bo0aOxb98+9OrVCwkJCeqzRYsW4f3330ejRo1CcXmCIAhCFSIiIqKymyAAOHToEL7++ms4HI7Kbkq1ZPLkyQCAF154QQm3zLZt27Bnzx6kpKTg6NGjuPLKKyujidWWhIQEpKSk4NNPP8WSJUsAAP369UNmZiY++eQTuFwujB49GgCwePFipKenw2azAQCys7ORmppaaW2vTliIiCq7EUL15Pfff0dcXBzOnDmD2NjYym4OAGD//v3IzMw0vPfBBx9g1KhRuHjxouH9Hj16wOl04ttvv1UuNBcvXoTVKnoeQRAEQRBqD2fPnkV0dHRlN6NG8s4772DChAlwu92oX78+fvrpJwBAUlISTp06hZMnTyI5OVntf+zYMQwZMgRLly5F69atK6vZlU4wcoas3IUaxbZt2wBACaXJyclITEzExYsX0bFjR5w+fRrdu3cHAAwfPhzr1q0zxIOIMCsIgiAIQm1DhNmK48Ybb8S5c+dw+eWX46efflL5WE6dOoXk5GSDMAsAjRs3xt69e2u1MBsssnoXahRff/01gOKY2SVLluDGG2+E1WrF2rVrkZCQgK1bt+LQoUO47777KrGlgiAIgiAIQm2Ak8u9/PLL2LdvH+69914AwIwZMyq1XTUFcTkWSk1VcjlevHgxJk6cCIvFAiJCZGSkylr86quv4rbbbsMrr7xSqW0UBEEQBEEQBAD48ccfkZKSUtnNqLIEI2eIQCuUmqok0O7atQudO3dW/9tsNsTGxuLs2bOIi4vDqVOnKrF1giAIgiAIgiAESjByhj1EbRKECoXTyjNut1tlOL7zzjsro0mCIAiCIAiCIFQwItAKNZbY2FiMHTsWjz/+eGU3RRAEQRAEQRCECkAEWqHGsm7dOnTr1q2ymyEIgiAIgiAIQgUhWY6FGoNecsfhcIgwKwiCIAiCIAg1HBFohRpDx44d1WtJgy4IgiAIgiAINR/JciyUmqqU5RgAzp49i/r168NmsyE3N9dgsRUEQRAEQRAEoXogWY6FWkl0dDTOnj1b2c0QBEEQBEEQBCFEiAlLEARBEARBEARBqJaIQCsIgiAIgiAIgiBUS0SgFQRBEARBEARBEKolItAKgiAIgiAIgiAI1RIRaAVBEARBEARBEIRqiQi0giAIgiAIgiAIQrVEBFpBEARBEARBEAShWiICrSAIgiAIgiAIglAtEYFWEARBEARBEARBqJbYK7sBQvWFiAAAv//+eyW3RBAEQRAEQRCEmgLLFyxv+EMEWqHU5OXlAQDS0tIquSWCIAiCIAiCINQ08vLyEBcX53cfCwUi9gqCFy5evIgff/wRMTExsFgsld0c/P7770hLS0NOTg5iY2Mruzk1Funn0CD9HBqkn0OH9HVokH4ODdLPoUP6OjRUtX4mIuTl5SElJQVWq/8oWbHQCqXGarUiNTW1spvhQWxsbJW4EWs60s+hQfo5NEg/hw7p69Ag/RwapJ9Dh/R1aKhK/VySZZaRpFCCIAiCIAiCIAhCtUQEWkEQBEEQBEEQBKFaIgKtUGMIDw/HE088gfDw8MpuSo1G+jk0SD+HBunn0CF9HRqkn0OD9HPokL4ODdW5nyUplCAIgiAIgiAIglAtEQutIAiCIAiCIAiCUC0RgVYQBEEQBEEQBEGolohAKwiCIAiCIAiCIFRLRKAVqgzHjh3D/fffj1atWsHpdCIhIQFZWVn4r//6L5w7d67czvPxxx9j1ZGy+wAAGONJREFU+PDhSE1NRXh4OFJTUzF8+HB8/PHH5XaOqk5F9vXixYthsVgC2hYvXlw+F1SF+Pnnn/HRRx/h8ccfx4ABA5CYmKiud8KECRVyzr/97W/o168f6tevj4iICDRu3Bg33ngjtm/fXiHnqwqEqp9nzJgR8Hj+/PPPy+28VYmvvvoKTz75JPr166fmzejoaGRkZGDixInYunVruZ+zNo7pUPVzbR7Tv//+O5YuXYr7778fvXr1Qnp6OuLi4uBwOJCcnIzevXtj7ty5OH36dLmds7auOULV17V9zeGPhx56qELu5yo5P5MgVAH+/ve/U2xsLAHwumVkZNC///3vMp3D7XbTpEmTfJ4DAE2ePJncbnc5XVXVpKL7+s033/Tbx/r25ptvlt+FVRH8Xe/48ePL9Vznzp2jgQMH+jyf1WqlGTNmlOs5qwqh6ucnnngi4PG8adOmcjtvVaFnz54BXfu4ceOosLCwzOerrWM6lP1cm8f0p59+GtB1JyYm0rp168p0rtq+5ghVX9f2NYcv9uzZQ3a7vVzv56o8P9shCJXMnj17MHr0aBQUFCA6OhrTpk1DdnY2CgoKsHTpUixcuBAHDx7EoEGD8NVXXyEmJqZU53nkkUfw+uuvAwAuu+wyTJ06Fc2bN8f333+PuXPnYs+ePVi0aBGSkpIwe/bs8rzEKkOo+pr55JNPkJKS4vPz1NTUMh2/qtOoUSO0atUK69evr5Dj33zzzVi7di0AIDs7G3/+85+RkpKCffv2Yfbs2fj+++8xY8YMNGjQALfcckuFtKEqUNH9zOzbt8/v502bNq3Q81cGP/74IwAgJSUFo0aNQs+ePdGoUSO43W5s374dzz33HI4fP4633noLLpcL7733XpnOV1vHdKj7mamNYzotLQ3Z2dno2LEj0tLS0KBBA1y8eBE//PADli9fjhUrVuCXX37BkCFDsHPnTrRv375U55E1R+j6mqntaw7m4sWLuOWWW3DhwgUkJyfj559/LpfjVun5uVLEaEHQYM203W6nbdu2eXw+d+5cpf154oknSnWO7777TmmqOnXqROfOnTN8np+fT506dVLtKKs1uKoSir7WtaVHjhwpW4OrIY8//jitXr2afvrpJyIiOnLkSIVYDjdu3KiOe80119CFCxcMn586dYoaNWpEACg+Pp5+/fXXcjt3VSBU/axbs2ojgwYNomXLlnmML+bUqVOUkZGh+mjz5s2lPldtHtOh7OfaPKZ99a/Ohx9+qPpn+PDhpTqPrDlC19e1fc3hjRdeeIEAUKtWrWjatGnlYqGt6vNz7ZvNhCrFl19+qW6QW2+91es+brebWrdurW6S8+fPB32e22+/XZ1n+/btXvfZvn272ueOO+4I+hxVnVD1tTxcjFSUoDVgwAC1GMrJyfG6z9/+9jd17rlz55bbuasiItBWHqtXr1Z9dPfdd5f6ODKm/VNe/SxjumRatmyp3GFLg6w5AqesfS1rDiPHjh2j6OhoAkCff/654X4vi0Bb1ednSQolVCorV65UrydOnOh1H6vVinHjxgEAfvvtN2zatCmocxARVq1aBQBo1aoVunbt6nW/rl27omXLlgCAVatWgYiCOk9VJxR9LYSGvLw8bNy4EQBw1VVX+XSjuvbaaxEbGwsA+PDDD0PWPqF2kZ2drV5///33pTqGjOmSKY9+FgKDw23++OOPoL8ra47gKEtfC57ceeedOHv2LMaPH49evXqVyzGrw/wsAq1QqXDWRqfTiY4dO/rcT78pv/jii6DOceTIERWfVNLNzZ8fP34cR48eDeo8VZ1Q9LUQGnbt2oXz588D8D+mHQ6HWkzt2rULLpcrJO0TaheFhYXqtc1mK9UxZEyXTHn0s1Ay3333Hb7++msARQJpsMiaI3DK2teCkf/5n//BRx99hISEBMybN6/cjlsd5mcRaIVK5V//+hcAID09HXa77xxl+kTH3wmUb7/91utxyvs8VZ1Q9LWZiRMnIiUlBQ6HA4mJiejatSseffRRHD9+vEzHre2UZkxfuHAB//73vyu0XTWdfv36ITk52VB24tlnn0Vubm5lN61S2bx5s3rdunXrUh1DxnTJlEc/m5ExXcS5c+fw73//G88//zx69eqFCxcuAADuvffeoI8law7/lGdfm6nNa47ffvsNf/7znwEAc+bMQWJiYrkduzrMzyLQCpXGH3/8gV9++QVAyZnn6tSpA6fTCQDIyckJ6jw//PCDel3SedLS0tTrYM9TlQlVX5v5/PPPceLECbhcLpw+fRpffvklnn76aaSnp2PBggVlOnZtRsZ05fDpp5/i1KlTcLlcOHXqFDZv3oxp06ahWbNmysWwtnHx4kU8++yz6v/rrruuVMeRMe2f8upnM7V5TOv1S51OJzIyMnD//ffj5MmTAICHH34YN9xwQ9DHlbHsSUX1tZnavOaYOnUqfvrpJ3Tv3h2TJk0q12NXhzEtZXuESiMvL0+9jo6OLnF/p9OJ/Px8nD17tsLOw4IcgKDPU5UJVV8zzZo1w7XXXotu3bqpye3w4cP44IMPsHz5cvzxxx+47bbbYLFYalTpjVAhYzq0ZGZmYtiwYejcuTNSUlLgcrnw3Xff4d1338X69evx22+/YcSIEVi9ejUGDBhQ2c0NKS+88AJ27twJoCh+yl84gz9kTPunvPqZkTHtm0svvRSvvfYasrKySvV9GcuBU9a+Zmr7mmPLli1YtGgR7HY7Xn31VVgslnI9fnUY0yLQCpWGngDA4XCUuH94eDgAoKCgoMLOw+cozXmqMqHqawAYPnw4xo8f7zGhZmVlYfTo0fjoo49w7bXXwuVyYcqUKRgyZAjq168f9HlqMzKmQ8e9996LGTNmeLzfpUsXjBs3DgsWLMBtt90Gt9uNyZMn4/vvv0dEREToG1oJbN68GQ8//DAAIDk5Ga+88kqpjyVj2jfl2c+AjGlm2LBh6NSpE4CicfT999/jf/7nf/Dhhx9izJgxePHFFzF48OCgjytj2ZOK6mtA1hznz5/HLbfcAiLClClT0LZt23I/R3UY0+JyLFQa+gOSg839wQkxIiMjK+w8etKNYM9TlQlVXwNAXFycX+3g4MGD8fjjjwMoiqXhwvNC4MiYDh3x8fF+P7/11luVe9ePP/6IDz74IAStqnz++c9/Yvjw4bhw4QIiIiLw/vvvIzk5udTHkzHtnfLuZ0DGNBMfH4+2bduibdu2yMrKwvXXX48VK1bgrbfewuHDhzF06FAsXrw46OPKWPakovoakDXH7NmzceDAATRq1AhPPPFEhZyjOoxpEWiFSoNTtQOBuSXk5+cDCMxltrTn4XOU5jxVmVD1daDccsst6gGkJzoRAkPGdNXi1ltvVa9rw3g+cuQI+vXrh9zcXNhsNixduhRXXHFFmY4pY9qTiujnQKltY1rnpptuwqhRo3Dx4kXcdddd+PXXX4P6vozlwClrXwdKTV1zHDhwAM888wwAYP78+QZ33/KkOoxpEWiFSiMiIgJ169YFYAw490Zubq66SfSA80DQA9hLOo8ewB7seaoyoerrQElOTlbtqQ3ZB8sbGdNVi0suuUS9runj+ccff8RVV12FH3/8ERaLBW+88QaGDh1a5uPKmDZSUf0cKLVpTHuD+zo/Px/r1q0L6rsyloOjLH0dKDV1zfHCCy/g/PnzaNasGc6dO4elS5d6bPv371f7f/bZZ+p9XfAsieowpiWGVqhULrnkEmzZsgWHDh3ChQsXfJaTOXDggHodbLkC/cGsH6e8z1PVCUVfB0N5Jy2oTZRmTNvtdrRo0aJC21VbqS1j+ZdffkHfvn1x+PBhAEUWgXHjxpXLsWVMF1OR/RwotWVM+yIpKUm9PnbsWFDflTVHcJSlr4OhJo5pdu89fPgwxowZU+L+s2bNUq+PHDkSsEW3OszPYqEVKpUePXoAKNLM7d692+d+uotI9+7dgzpH06ZNkZKS4nEcb/zv//4vAKBhw4Zo0qRJUOep6oSirwPl1KlTqowQ/zZC4GRlZanEDP7G9Pnz57Fjxw71nbCwsJC0r7ah1+irqeP5zJkzuPrqq9W1Pvvss7jzzjvL7fgypouo6H4OlNowpv2hW/GCdZuUNUdwlKWvA0XWHGWjOszPItAKlcqwYcPU6zfffNPrPhcvXsRbb70FoCixQHZ2dlDnsFgsyqXlwIED6mYzs2PHDqVZGjp0aI3T5oWirwPltddeAxEBAHr16lUh56jJxMTE4MorrwQAbNiwwacL0IoVK/D7778DKMoEKVQMen3Dmjiez507h0GDBuEf//gHAOCRRx7BQw89VK7nkDEdmn4OlJo+pkvi/fffV68zMzOD+q6sOYKjLH0dKDV1zbF48WIQkd9NTxS1adMm9X4wCpRqMT+TIFQyPXv2JABkt9tp27ZtHp/PnTuXABAAeuKJJzw+37Rpk/p8/PjxXs/x3Xffkc1mIwDUqVMnOnfunOHzc+fOUadOnVQ7Dh48WB6XVuWo6L4+cuQI/eMf//DbhtWrV5PD4SAAFBkZST/88ENpL6dacOTIkRLHp5k333zT7+9ARLRx40a1z5AhQ+jChQuGz0+dOkWNGjUiABQfH0+//vprGa+kalMR/fzNN9/Qv//9b7/HWLBggTpG/fr16ezZs6VofdWlsLCQ+vXrp67xz3/+c6mOI2PaP6Hq59o+pt98800qKCjwu8/zzz+vrr9p06Ye41DWHIERir6WNUfJPPHEE6oPN23a5HWfmjA/SwytUOm89NJL6N69OwoKCtCvXz9Mnz4d2dnZKCgowNKlS/Haa68BADIyMnD//feX6hwZGRl48MEH8eyzz+Krr75C9+7d8dBDD6F58+b4/vvvMWfOHOzZswcA8OCDD9bIuCyg4vv66NGjyM7ORrdu3XDNNdegffv2qsTE4cOHsXz5cixfvlxpSufNm4eGDRuW3wVWAbZu3YpDhw6p/9nNCQAOHTrkUZpgwoQJpTpPnz59cP3112Pp0qX4+9//jr59++Lee+9FSkoK9u3bh6effhr/+c9/AABz5sxBnTp1SnWeqkoo+nn37t2YPHkysrOzMWDAAGRmZqJu3bq4cOECDhw4gHfffRfr168HANhsNrz22msVlmWyshgzZoy6xj59+mDSpEmGJCNmHA4HMjIySnWu2jymQ9XPtX1Mz5gxA/fffz9GjBiBHj16oHnz5oiOjkZeXh727duHd999F1988QWAoj5+7bXXYLPZgj6PrDlC09ey5ggdVX5+Dqn4LAg++Pvf/06xsbFK+2PeMjIyfGqVA9GWEhG53W66+eabfZ4DAE2aNIncbncFXWXVoCL7Wv/c3xYVFUULFiyo4CutHMaPHx9QH/DmjUC0pURFWv6BAwf6PLbVavX7/epMKPpZ/9zfVrduXVq5cmUFX3HlEEwfA6DGjRt7PY6Maf+Eqp9r+5hu3LhxQNefmppK69ev93oMWXMERij6WtYcJVNeFlqiqj0/i4VWqBJcc801+Oabb/DSSy9hzZo1+OGHH+BwOJCeno5Ro0bhrrvuQlRUVJnOYbVa8frrr2PEiBF47bXXsGvXLvzyyy9ITExEVlYWbr31VgwYMKCcrqjqUpF93bFjR7zzzjvYvn07vvrqK5w4cQK//PILLly4gDp16qBNmza48sorMXnyZKVFFUpPZGQk1qxZg/feew+LFy/G3r178dtvv6FevXro2bMn7rrrLnTr1q2ym1ltGThwIF5//XVs374de/bswcmTJ3H69GkQERISEtC+fXv0798fEyZMQGxsbGU3t0YgY7piqe1j+pNPPsGaNWvwxRdf4NChQ+r6IyMjkZycjEsvvRSDBw/GddddJ2uOMhKKvpY1R2ipyvOzhej/7fCCIAiCIAiCIAiCUI2QLMeCIAiCIAiCIAhCtUQEWkEQBEEQBEEQBKFaIgKtIAiCIAiCIAiCUC0RgVYQBEEQBEEQBEGolohAKwiCIAiCIAiCIFRLRKAVBEEQBEEQBEEQqiUi0AqCIAiCIAiCIAjVEhFoBUEQBEEQBEEQhGqJCLSCIAiCIAiCIAhCtUQEWkEQBEEQBEEQBKFaIgKtIAiCIAiCIAiCUC0RgVYQBEEQBJ/MmDEDFosFFosFM2bMqOzmCIIgCIIBEWgFQRAEoQZw9OhRJXiW1yYCrCAIglDVEYFWEARBEARBEARBqJbYK7sBgiAIgiCUndjYWNx5551+99m5cyd27doFAEhJScHw4cP97t+5c2fs3Lmz3NooCIIgCOWNhYioshshCIIgCELFM2PGDMycORMA0KtXL3z++eeV2yBBEARBKCPiciwIgiAIgiAIgiBUS0SgFQRBEARBEARBEKolItAKgiAIguCTQMr2LF68WO0zYcIEAMDFixfx3nvvYcCAAUhLS0N4eDjq1auHESNGYPv27R7HOH/+PN5++21ceeWVSEtLQ0REBBo1aoTx48fjX//6V1BtdrlcePvtt3HdddehWbNmiImJgdPpRNOmTTFmzBh8+OGHkIgrQRCEmoEkhRIEQRAEoVz55ZdfMHr0aHz22WeG93/++WesWLECH374IV5//XVMnDgRAHDo0CEMGTLEQ3DNycnBW2+9haVLl2LZsmUYNmxYief+/PPPMXnyZHz//fcenx09ehRHjx7F0qVL0bVrVyxfvhwNGzYs/YUKgiAIlY4ItIIgCIIglBsXLlzAtddeiy1btiAiIgK9evVCo0aN8Ouvv2Ljxo347bffQESYPHkyWrRogYyMDPTp0wc5OTmIjY3FFVdcgQYNGuDkyZPYsGEDzp07h/Pnz+OGG27AP//5TzRt2tTnud9//32MHTsWLpcLABAZGYmuXbuiSZMmsFqtOHjwILZv344LFy5gx44d6NatG3bt2oV69eqFqnsEQRCEckYEWkEQBEEQyo3ly5ejsLAQQ4cOxWuvvYbk5GT1WW5uLoYOHYotW7bg4sWLePzxxxEXF4ecnBzcdtttmDt3LmJiYtT+P/zwA/r164d//etfKCgowKxZs/DGG294Pe8///lPjB8/Hi6XCxaLBffffz8eeeQRxMfHG/Y7fPgwxo8fj61btyInJwcTJ07E2rVrK6QvBEEQhIpHYmgFQRAEQSg3CgsL0bt3b3zwwQcGYRYA6tSpg7fffhs2mw0AsGnTJqxcuRLjx4/HK6+8YhBmASA1NRULFy5U/y9fvhwXLlzwet577rkHBQUFAIDnnnsO//Vf/+UhzAJAs2bNsG7dOlxyySUAgI8//hhffvllqa9XEARBqFxEoBUEQRAEoVx54YUXlNBqpnHjxrj88svV/+Hh4Zg7d67PY3Xv3h1paWkAgLy8PBw4cMBjn71796p43csuuwz33nuv3/Y5nU489thj6v93333X7/6CIAhC1UUEWkEQBEEQyo3mzZvj0ksv9btPZmamet2zZ08PS66Ztm3bqtdHjhzx+Fx3GR4zZgwsFkuJ7ezTp496vXXr1hL3FwRBEKomEkMrCIIgCEK5oQufvqhTp4563aZNmxL3T0hIUK9///13j8/1MkCbNm3CsWPHSjymXrYnJyenxP0FQRCEqokItIIgCIIglBtxcXEl7mO3Fy8/gt2fMxjr/Pjjj+r1xx9/XOLxzOTm5gb9HUEQBKFqIC7HgiAIgiCUG4G4+5Zlf2+cOXOmTN93u91lboMgCIJQOYhAKwiCIAhCtcbpdKrXK1asABEFvQmCIAjVExFoBUEQBEGo1tSrV0+9/umnnyqxJYIgCEKoEYFWEARBEIRqTZcuXdTrL774ohJbIgiCIIQaEWgFQRAEQajWDB48WL1esWIFTp48WYmtEQRBEEKJCLSCIAiCIFRrOnfujN69ewMACgoKcNNNN+H8+fMBfff8+fOS5VgQBKEaIwKtIAiCIAjVnvnz5yM6OhoA8Omnn+KKK67Al19+6XP/gwcPYtasWWjSpIm4KQuCIFRjpA6tIAiCIAjVnrZt2+Jvf/sbRo8ejXPnzuHLL79E165d0bx5c3To0AEJCQn4448/8PPPP+Obb77B8ePHK7vJgiAIQjkgAq0gCIIgCDWCwYMHY9u2bZg0aRJ2794NAPj+++/x/fff+/xOkyZNkJqaGqomCoIgCOWMCLSCIAiCINQY2rdvj6+++grr16/HypUr8cUXX+DHH3/Eb7/9hvDwcCQlJaFly5bo0qULrr76anTr1g0Wi6Wymy0IgiCUEgtJNXFBEARBEARBEAShGiJJoQRBEARBEARBEIRqiQi0giAIgiAIgiAIQrVEBFpBEARBEARBEAShWiICrSAIgiAIgiAIglAtEYFWEARBEARBEARBqJaIQCsIgiAIgiAIgiBUS0SgFQRBEARBEARBEKolItAKgiAIgiAIgiAI1RIRaAVBEARBEARBEIRqiQi0giAIgiAIgiAIQrVEBFpBEARBEARBEAShWiICrSAIgiAIgiAIglAtEYFWEARBEARBEARBqJaIQCsIgiAIgiAIgiBUS0SgFQRBEARBEARBEKolItAKgiAIgiAIgiAI1ZL/Az+K7p0VKiIGAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "%matplotlib inline\n", "\n", @@ -437,56 +411,57 @@ "from snudda.plotting.plot_traces import PlotTraces\n", "pt = PlotTraces(output_file=sim_file)\n", "# Use trace_id to specify which traces\n", - "ax = pt.plot_traces(offset=0, time_range=(0,1),fig_size=(10,4))" + "ax = pt.plot_traces(offset=0, time_range=(0,sim_time),fig_size=(10,4))" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "id": "0484dc59-0ae4-41fa-bfd5-441f8ddf6290", "metadata": {}, - "outputs": [], - "source": [ - "ax0 = pt.plot_traces(offset=0, time_range=(0,1),fig_size=(10,4), trace_id=0)\n", - "ax1 = pt.plot_traces(offset=0, time_range=(0,1),fig_size=(10,4), trace_id=1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "dafbc17d-34f0-413e-b26a-08e51e8fff35", - "metadata": {}, - "outputs": [], - "source": [ - "help(pt.plot_traces)" - ] - }, - { - "cell_type": "markdown", - "id": "e3532a44-6084-4701-a8a3-28df6e106524", - "metadata": {}, - "source": [ - "## TODO!! Also add ability to have external synapses affect RxD concentrations" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "97789ccd-8c45-47e8-aeec-3b752b4c9942", - "metadata": {}, - "outputs": [], - "source": [ - "sim.neurons[0].icell.soma[0](0.5).naf_ms.gbar" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7b2a5b48-6450-475e-b842-478e75d2cf32", - "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Plotting traces: [0]\n", + "Plotted 1 traces (total 4)\n", + "Saving to figure /home/hjorth/HBP/Snudda/examples/notebooks/neuromodulation/networks/neuromodulation_bath/figures/Network-voltage-trace--dspn-0.pdf\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Plotting traces: [1]\n", + "Plotted 1 traces (total 4)\n", + "Saving to figure /home/hjorth/HBP/Snudda/examples/notebooks/neuromodulation/networks/neuromodulation_bath/figures/Network-voltage-trace--dspn-1.pdf\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "sim.neurons[0].icell.soma[0](0.5).pas.g" + "ax0 = pt.plot_traces(offset=0, time_range=(0,sim_time),fig_size=(10,4), trace_id=0)\n", + "ax1 = pt.plot_traces(offset=0, time_range=(0,sim_time),fig_size=(10,4), trace_id=1)" ] }, { diff --git a/examples/notebooks/neuromodulation/neuromodulation_on_off.ipynb b/examples/notebooks/neuromodulation/neuromodulation_on_off.ipynb index 41fb8bbf3..f6c58f5d1 100644 --- a/examples/notebooks/neuromodulation/neuromodulation_on_off.ipynb +++ b/examples/notebooks/neuromodulation/neuromodulation_on_off.ipynb @@ -281,10 +281,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "d84ee6f3-4193-4509-ad4a-0d93dff5e3d9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading networks/neuromodulation_ON_OFF/simulation/output_neuromodulation_ON.hdf5\n" + ] + } + ], "source": [ "from snudda.utils import SnuddaLoadSimulation\n", "\n", @@ -300,7 +308,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "bd0f4edf-a622-490b-b39f-18f516975737", "metadata": {}, "outputs": [], @@ -313,10 +321,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "a63a7152-730e-4868-a81a-cc87fccaf9f4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import plotly.graph_objects as go\n", "import plotly.io as pio\n", @@ -332,7 +357,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "511489ad-b3d6-4301-a8bd-fa870cf456e4", "metadata": {}, "outputs": [], @@ -345,10 +370,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "d231b4e4-4a56-47b5-84f6-e13b6e721125", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import plotly.graph_objects as go\n", "import plotly.io as pio\n", @@ -364,10 +406,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "81722b1c-c30c-445e-a5f5-abaa823f0ce4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading networks/neuromodulation_ON_OFF/simulation/output_neuromodulation_OFF.hdf5\n" + ] + } + ], "source": [ "nd_off = SnuddaLoadSimulation(sim_output_neuromodulation_OFF)\n", "time_off = nd_off.get_time()\n", @@ -376,10 +426,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "1e9ce899-6243-448b-a4ac-2ba3e83f522e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig = go.Figure()\n", "\n", @@ -392,10 +459,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "c1c558be-b54e-41e7-a64c-6c98e955ed2a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig = go.Figure()\n", "\n", @@ -416,10 +500,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "fc082055-9e38-4ed1-b842-40e166548071", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading network info from networks/neuromodulation_ON_OFF/network-synapses.hdf5\n", + "Loading input info from networks/neuromodulation_ON_OFF/input-spikes.hdf5\n", + "Loading networks/neuromodulation_ON_OFF/simulation/output_neuromodulation_ON.hdf5\n", + "Plotting traces: [0, 1]\n", + "Plotted 2 traces (total 2)\n", + "Saving to figure /home/hjorth/HBP/Snudda/examples/notebooks/neuromodulation/networks/neuromodulation_ON_OFF/figures/Network-voltage-trace--dspn-0-1.pdf\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "%matplotlib inline\n", "\n", @@ -439,10 +546,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "191cf2cb-a61f-4b9e-89a9-4fe963f0343b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading network info from networks/neuromodulation_ON_OFF/network-synapses.hdf5\n", + "Loading input info from networks/neuromodulation_ON_OFF/input-spikes.hdf5\n", + "Loading networks/neuromodulation_ON_OFF/simulation/output_neuromodulation_OFF.hdf5\n", + "Plotting traces: [0, 1]\n", + "Plotted 2 traces (total 2)\n", + "Saving to figure /home/hjorth/HBP/Snudda/examples/notebooks/neuromodulation/networks/neuromodulation_ON_OFF/figures/Network-voltage-trace--dspn-0-1.pdf\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "%matplotlib inline\n", "\n", diff --git a/examples/notebooks/neuromodulation/neuromodulation_on_off_bath.ipynb b/examples/notebooks/neuromodulation/neuromodulation_on_off_bath.ipynb new file mode 100644 index 000000000..c5cdd3dc8 --- /dev/null +++ b/examples/notebooks/neuromodulation/neuromodulation_on_off_bath.ipynb @@ -0,0 +1,495 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "138f1fa5-37b6-4563-a588-309e5b21b9d5", + "metadata": {}, + "source": [ + "# Neuromodulation example (bath)\n", + "\n", + "This neuromodulation creates a small network of neurons. We also use the reaction diffusion model by Anu G Nair 2015.\n", + "\n", + "To generate the ```reaction_diffusion.json``` file in ```data/str-dspn-e150602_c1_D1-mWT-0728MSN01-v20211026/``` from the xml file we run ```data/convert_sbml_to_json.sh```\n", + "\n", + "Reference for DA modulation cascade:\n", + "\n", + "Lindroos R, Dorst MC, Du K, et al. Basal Ganglia Neuromodulation Over Multiple Temporal and Structural Scales-Simulations of Direct Pathway MSNs Investigate the Fast Onset of Dopaminergic Effects and Predict the Role of Kv4.2. Front Neural Circuits. 2018;12:3. Published 2018 Feb 6. doi:10.3389/fncir.2018.00003\n", + "\n", + "Here we use the data from Planert:\n", + "Planert H, Berger TK, Silberberg G. Membrane properties of striatal direct and indirect pathway neurons in mouse and rat slices and their modulation by dopamine. PLoS One. 2013;8(3):e57054. doi:10.1371/journal.pone.0057054" + ] + }, + { + "cell_type": "markdown", + "id": "1746feed-04de-4020-a2cb-f884e8e9698a", + "metadata": {}, + "source": [ + "## Network setup\n", + "\n", + "We have two neurons. The first neuron (Neuron 0) receives external input (cortical from t=0s and DA from t=0.1s). The cortical input will activate the first neuron, and through activation of synapses on the second neuron, we will see the dopamine level increase in the second neuron (Neuron 1).\n", + "\n", + "The first neuron also receives direct DA activation from external input (starting at 100ms)." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "5b55f23d-62ac-4433-8639-07870af8c40a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Adding neurons: dspn from dir data/dspn\n", + "Writing networks/neuromodulation_ON_OFF_bath/network-config.json\n", + "Writing networks/neuromodulation_ON_OFF_bath/network-config.json\n", + "Placing neurons\n", + "Network path: networks/neuromodulation_ON_OFF_bath\n", + "Reading SNUDDA_DATA=None from networks/neuromodulation_ON_OFF_bath/network-config.json\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/Snudda/snudda/utils/../data from networks/neuromodulation_ON_OFF_bath/network-synapses.hdf5\n", + "No n_putative_points and putative_density, setting n_putative_points = 63\n", + "(this must be larger than the number of neurons you want to place)\n", + "Generating 63 points for networks/neuromodulation_ON_OFF_bath/mesh/Cube-cube-mesh-2.917951293943981e-05.obj\n", + "Filtering, keeping inside points: 2 / 26\n", + "neuron_name = 'dspn_0', num = 2, neuron_path = 'data/dspn/str-dspn-e150602_c1_D1-mWT-0728MSN01-v20211026'\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 0.0s\n", + "Touch detection\n", + "Network path: networks/neuromodulation_ON_OFF_bath\n", + "Reading SNUDDA_DATA=None from networks/neuromodulation_ON_OFF_bath/network-config.json\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/Snudda/snudda/utils/../data from networks/neuromodulation_ON_OFF_bath/network-synapses.hdf5\n", + "No d_view specified, running distribute neurons in serial\n", + "No connections specified in connectivity_distribution.\n", + "Reading SNUDDA_DATA=None from networks/neuromodulation_ON_OFF_bath/network-config.json\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 0.1s\n", + "Prune synapses\n", + "Network path: networks/neuromodulation_ON_OFF_bath\n", + "No file networks/neuromodulation_ON_OFF_bath/pruning_merge_info.json\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 0.1s\n" + ] + } + ], + "source": [ + "import os\n", + "from snudda import Snudda\n", + "\n", + "neuron_path = os.path.join(\"data\", \"dspn\")\n", + "network_path = os.path.join(\"networks\", \"neuromodulation_ON_OFF_bath\")\n", + "\n", + "snudda = Snudda(network_path=network_path)\n", + "si = snudda.init_tiny(neuron_paths=neuron_path, neuron_names=\"dspn\", number_of_neurons=[2], \n", + " random_seed=123)\n", + "\n", + "si.network_data[\"regions\"][\"Cube\"][\"neurons\"][\"dspn\"][\"reaction_diffusion\"] = \"data/JSON/reaction_diffusion_D1.json\"\n", + "\n", + "si.network_data[\"regions\"][\"Cube\"][\"neurons\"][\"dspn\"][\"modulation\"] = \"test-modulation.json\"\n", + "si.network_data[\"regions\"][\"Cube\"][\"neurons\"][\"dspn\"][\"modulation_key\"] = \"abc\"\n", + "\n", + "si.write_json()\n", + "\n", + "snudda.create_network()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "41e96e4a-0f52-4d77-8a1f-ba8d270b9b78", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Setting up inputs, assuming input.json exists\n", + "Reading SNUDDA_DATA=None from networks/neuromodulation_ON_OFF_bath/network-config.json\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/Snudda/snudda/utils/../data from networks/neuromodulation_ON_OFF_bath/network-synapses.hdf5\n", + "Writing input spikes to networks/neuromodulation_ON_OFF_bath/input-spikes.hdf5\n", + "Reading SNUDDA_DATA=None from networks/neuromodulation_ON_OFF_bath/network-config.json\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/Snudda/snudda/utils/../data from networks/neuromodulation_ON_OFF_bath/network-synapses.hdf5\n", + "!!! Warning, combining definition of cortical_background with cortical_background input for neuron dspn_0 0 (meta modified by input_config)\n", + "!!! Warning, combining definition of thalamic_background with thalamic_background input for neuron dspn_0 0 (meta modified by input_config)\n", + "!!! Warning, combining definition of cortical with cortical input for neuron dspn_0 0 (meta modified by input_config)\n", + "!!! Warning, combining definition of cortical_background with cortical_background input for neuron dspn_0 1 (meta modified by input_config)\n", + "!!! Warning, combining definition of thalamic_background with thalamic_background input for neuron dspn_0 1 (meta modified by input_config)\n", + "!!! Warning, combining definition of cortical with cortical input for neuron dspn_0 1 (meta modified by input_config)\n", + "Writing spikes to networks/neuromodulation_ON_OFF_bath/input-spikes.hdf5\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 0.2s\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "input_config = os.path.join(\"data\", \"input_v6_bath_on_off.json\")\n", + "snudda.setup_input(input_config=input_config)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "ae7ebf60-1556-4e07-81c6-85156c90bfad", + "metadata": {}, + "outputs": [], + "source": [ + "sim_output_neuromodulation_ON = os.path.join(network_path, \"simulation\", \"output_neuromodulation_ON.hdf5\")\n", + "sim_output_neuromodulation_OFF = os.path.join(network_path, \"simulation\", \"output_neuromodulation_OFF.hdf5\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "d019b580-4193-4321-9ee8-9bdd3988209f", + "metadata": {}, + "outputs": [], + "source": [ + "# mech_dir = os.path.join(\"..\", \"..\", \"..\", \"..\", \"BasalGangliaData\", \"data\", \"neurons\", \"mechanisms\")\n", + "mech_dir = \"/home/hjorth/BasalGangliaData/data/neurons/mechanisms\"\n", + "sample_dt = None # 0.00005\n", + "\n", + "# sim = snudda.simulate(time=0, mech_dir=mech_dir, verbose=True, sample_dt=sample_dt, output_file=sim_output_neuromodulation_ON)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "207658ef-0747-4c87-babb-d3076e3f7a33", + "metadata": {}, + "outputs": [], + "source": [ + "# sim_config_on = os.path.join(\"data\", \"da_experiment_on.json\")\n", + "# sim_config_off = os.path.join(\"data\", \"da_experiment_off.json\")\n", + "\n", + "snudda = None\n", + "\n", + "sim_config_on = os.path.join(\"data\", \"da_experiment_on_bath.json\")\n", + "sim_config_off = os.path.join(\"data\", \"da_experiment_off_bath.json\")\n", + "\n", + "\n", + "sim_time = 1\n", + "n_workers = 1" + ] + }, + { + "cell_type": "markdown", + "id": "56760ccb-c832-4852-b696-323198f8d771", + "metadata": {}, + "source": [ + "## Running simulations\n", + "\n", + "To see progress of the two simulations in log files ```networks/neuromodulation_ON_OFF/log/network-simulation-ON.txt``` and ```networks/neuromodulation_ON_OFF/log/network-simulation-OFF.txt```." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "6b6b0fa2-93d2-4d0b-92ef-3c4949ac3355", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mpirun -n 1 snudda simulate networks/neuromodulation_ON_OFF_bath --time 1 --simulation_config data/da_experiment_on_bath.json --mechdir /home/hjorth/BasalGangliaData/data/neurons/mechanisms\n" + ] + } + ], + "source": [ + "run_str_on = f\"mpirun -n {n_workers} snudda simulate {network_path} --time {sim_time} --simulation_config {sim_config_on} --mechdir {mech_dir}\"\n", + "print(run_str_on)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "6bc7d396-09b0-46cc-89da-ff3c356b2b6e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2.3 ms ± 27.2 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "os.system(run_str_on)" + ] + }, + { + "cell_type": "markdown", + "id": "0c9d6057-e439-40e1-b7e7-4d55bdec3ce7", + "metadata": {}, + "source": [ + "### Rerun without neuromodulation" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "0f3648c5-2f5f-4b5b-b438-5eb15bffdd61", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mpirun -n 1 snudda simulate networks/neuromodulation_ON_OFF_bath --time 1 --simulation_config data/da_experiment_off_bath.json --mechdir /home/hjorth/BasalGangliaData/data/neurons/mechanisms --disable_rxd_neuromodulation\n" + ] + } + ], + "source": [ + "run_str_off = f\"mpirun -n {n_workers} snudda simulate {network_path} --time {sim_time} --simulation_config {sim_config_off} --mechdir {mech_dir} --disable_rxd_neuromodulation\"\n", + "print(run_str_off)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "e3cdbcb1-7520-4a7c-93d8-61071697b8ca", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "256" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "os.system(run_str_off)" + ] + }, + { + "cell_type": "markdown", + "id": "bfdb2c9a-4d32-453d-84b8-2c872bfd4050", + "metadata": {}, + "source": [ + "## Load the data and plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d84ee6f3-4193-4509-ad4a-0d93dff5e3d9", + "metadata": {}, + "outputs": [], + "source": [ + "from snudda.utils import SnuddaLoadSimulation\n", + "\n", + "nd = SnuddaLoadSimulation(sim_output_neuromodulation_ON)\n", + "time = nd.get_time()\n", + "data_pka = nd.get_data(\"PKAc\", 1)[0][1]\n", + "data_da = nd.get_data(\"DA\", 1)[0][1]\n", + "data_da_external = nd.get_data(\"DA\", 0)[0][0]\n", + "\n", + "# This is saved with add_rxd_internal_concentration_recording_all -- check that it worked \n", + "data_pka_all0 = nd.get_data(\"PKAc\", 0)[0][0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bd0f4edf-a622-490b-b39f-18f516975737", + "metadata": {}, + "outputs": [], + "source": [ + "data_types = nd.list_data_types(0)\n", + "all_species_data = nd.get_all_data(neuron_id=0, exclude=[\"spikes\", \"voltage\"])\n", + "time = nd.get_time()\n", + "voltage = nd.get_data(\"voltage\", [0, 1])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a63a7152-730e-4868-a81a-cc87fccaf9f4", + "metadata": {}, + "outputs": [], + "source": [ + "import plotly.graph_objects as go\n", + "import plotly.io as pio\n", + "pio.renderers.default = \"iframe\" # Do not save plots in the notebook, they can get BIG\n", + "\n", + "fig = go.Figure()\n", + "for data_type in all_species_data:\n", + " fig.add_trace(go.Scatter(x=time, y=all_species_data[data_type][0][0].T[0], name=data_type))\n", + "\n", + "fig.update_layout(title=\"With DA modulation\", xaxis_title=\"Time (s)\", yaxis_title=\"Concentration\", width=1000, height=800)\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "511489ad-b3d6-4301-a8bd-fa870cf456e4", + "metadata": {}, + "outputs": [], + "source": [ + "data_types2 = nd.list_data_types(0)\n", + "all_species_data2 = nd.get_all_data(neuron_id=1, exclude=[\"spikes\", \"voltage\"])\n", + "time = nd.get_time()\n", + "voltage = nd.get_data(\"voltage\", [0, 1])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d231b4e4-4a56-47b5-84f6-e13b6e721125", + "metadata": {}, + "outputs": [], + "source": [ + "import plotly.graph_objects as go\n", + "import plotly.io as pio\n", + "pio.renderers.default = \"iframe\" # Do not save plots in the notebook, they can get BIG\n", + "\n", + "fig = go.Figure()\n", + "for data_type in all_species_data2:\n", + " fig.add_trace(go.Scatter(x=time, y=all_species_data2[data_type][0][1].T[0], name=data_type))\n", + "\n", + "fig.update_layout(title=\"With DA modulation\", xaxis_title=\"Time (s)\", yaxis_title=\"Concentration\", width=1000, height=800)\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "81722b1c-c30c-445e-a5f5-abaa823f0ce4", + "metadata": {}, + "outputs": [], + "source": [ + "nd_off = SnuddaLoadSimulation(sim_output_neuromodulation_OFF)\n", + "time_off = nd_off.get_time()\n", + "voltage_off = nd_off.get_data(\"voltage\", [0, 1])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1e9ce899-6243-448b-a4ac-2ba3e83f522e", + "metadata": {}, + "outputs": [], + "source": [ + "fig = go.Figure()\n", + "\n", + "sct_on = go.Scatter(x=time, y=voltage[0][0][:,0], name=\"DA (0.3-1.3s)\", opacity=0.5)\n", + "sct_off = go.Scatter(x=time_off, y=voltage_off[0][0][:,0], name=\"No DA\", opacity=0.5)\n", + "fig.add_traces([sct_on, sct_off])\n", + "fig.write_image(\"example-trace.png\", scale=2, height=800, width=1200)\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c1c558be-b54e-41e7-a64c-6c98e955ed2a", + "metadata": {}, + "outputs": [], + "source": [ + "fig = go.Figure()\n", + "\n", + "sct_on = go.Scatter(x=time, y=voltage[0][1][:,0], name=\"DA (0.3-1.3s)\", opacity=0.5)\n", + "sct_off = go.Scatter(x=time_off, y=voltage_off[0][1][:,0], name=\"No DA\", opacity=0.5)\n", + "fig.add_traces([sct_on, sct_off])" + ] + }, + { + "cell_type": "markdown", + "id": "cd855cab-eb67-4c0c-a20c-56f23eb04d9e", + "metadata": {}, + "source": [ + "## Plotting simulation with DA modulation \n", + "\n", + "DA is active from 0.3 to 1.3 seconds" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fc082055-9e38-4ed1-b842-40e166548071", + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "from snudda.plotting.plot_traces import PlotTraces\n", + "pt = PlotTraces(output_file=sim_output_neuromodulation_ON)\n", + "# Use trace_id to specify which traces\n", + "ax = pt.plot_traces(offset=0, time_range=None,fig_size=(10,4))" + ] + }, + { + "cell_type": "markdown", + "id": "d5ab977a-2171-4f7a-8db8-0d4fcaff82a6", + "metadata": {}, + "source": [ + "## Plot simulation, with neuromodulation disabled" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "191cf2cb-a61f-4b9e-89a9-4fe963f0343b", + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "from snudda.plotting.plot_traces import PlotTraces\n", + "pt_off = PlotTraces(output_file=sim_output_neuromodulation_OFF)\n", + "# Use trace_id to specify which traces\n", + "ax_off = pt_off.plot_traces(offset=0, time_range=None,fig_size=(10,4))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "398790f7-d211-4fff-9249-77b28e14c859", + "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": "3.9.2" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/snudda/simulate/simulate.py b/snudda/simulate/simulate.py index 5621deab9..14d3e3b78 100644 --- a/snudda/simulate/simulate.py +++ b/snudda/simulate/simulate.py @@ -148,7 +148,7 @@ def __init__(self, comm = MPI.COMM_WORLD rank = comm.Get_rank() size = comm.Get_size() - print(f"MPI Rank: {rank}, Size: {size} -- NEUON: This is node {node_id} out of {total_nodes}") + print(f"MPI Rank: {rank}, Size: {size} -- NEURON: This is node {node_id} out of {total_nodes}") if simulation_config: