diff --git a/docs/_static/conductance_model_diagram.png b/docs/_static/conductance_model_diagram.png new file mode 100644 index 000000000..e9810cb97 Binary files /dev/null and b/docs/_static/conductance_model_diagram.png differ diff --git a/docs/_static/potassium_channel_equivalent_circuit.png b/docs/_static/potassium_channel_equivalent_circuit.png new file mode 100644 index 000000000..d782e8b6a Binary files /dev/null and b/docs/_static/potassium_channel_equivalent_circuit.png differ diff --git a/docs/tutorial_building/build_conductance_neurons.ipynb b/docs/tutorial_building/build_conductance_neurons.ipynb index c04fa2e27..a4793b6a7 100644 --- a/docs/tutorial_building/build_conductance_neurons.ipynb +++ b/docs/tutorial_building/build_conductance_neurons.ipynb @@ -2,72 +2,367 @@ "cells": [ { "cell_type": "markdown", - "source": [ - "# Building Conductance-based Neuron Models" - ], "metadata": { - "collapsed": false, "pycharm": { "name": "#%% md\n" } - } + }, + "source": [ + "# Building Conductance-based Neuron Models" + ] }, { "cell_type": "markdown", - "source": [ - "A Hodgkin-Huxley (HH) typed neuron model contains many ion channels." - ], "metadata": { - "collapsed": false, "pycharm": { "name": "#%% md\n" } - } + }, + "source": [ + "There are basically two types of neuron models: **conductance-based models** and **simplified models**. In conductance-based models, a single neuron can be regarded as a electric circuit, where the membrane is a capacitor, ion channels are conductors, and ion gradients are batteries. The neuronal activity is captured by the current flows through those ion channels. Sometimes there is an external input to this neuron, which can also be included in the equivalent circuit (see the figure below which shows potassium channels, sodium channels and leaky channels).\n", + "\n", + "" + ] }, { - "cell_type": "code", - "execution_count": null, - "outputs": [], - "source": [], + "cell_type": "markdown", "metadata": { - "collapsed": false, "pycharm": { "name": "#%%\n" } - } + }, + "source": [ + "On the other hand, simplified models do not care about the physiological features of neurons but mainly focus on how to reproduce the exact spike timing. Therefore, they are more simplified and maybe not biologically explicable.\n", + "\n", + "BrainPy provides a large volume of [predefined neuron models](../apis/auto/dyn/neurons.html) including conductance-based and simplified models for ease of use. In this section, we will only talk about how to build conductance-based models by ion channels. Users please refer to [Customizing Your Neuron Models](customize_neuron_models.ipynb) for more information." + ] }, { - "cell_type": "code", - "execution_count": null, - "outputs": [], - "source": [], + "cell_type": "markdown", "metadata": { - "collapsed": false, "pycharm": { "name": "#%%\n" } - } + }, + "source": [ + "## Building an ion channel" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we have known, ion channels are crucial for conductance-based neuron models. So how do we model an ion channel? Let's take a look at the potassium channel for instance.\n", + "\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The diagram above shows how a potassium channel is changed to an electric circuit. By this, we have the differential equation:\n", + "\n", + "$$\n", + "\\begin{align}\n", + "c_\\mathrm{M} \\frac{\\mathrm{d}V_\\mathrm{M}}{\\mathrm{d}t} &= \\frac{E_\\mathrm{K} - V_\\mathrm{M}}{R_\\mathrm{K}} \\\\\n", + "&= g_\\mathrm{K}(E_\\mathrm{K} - V_\\mathrm{M}),\n", + "\\end{align}\n", + "$$\n", + "\n", + "in which $c_\\mathrm{M}$ is the membrane capacitance, $\\mathrm{d}V_\\mathrm{M}$ is the membrane potential, $E_\\mathrm{K}$ is the equilibrium potential of potassium ions, and $R_\\mathrm{K}$ ($g_\\mathrm{K}$) refers to the resistance (conductance) of the potassium channel. We define currents from inside to outside as the positive direction.\n", + "\n", + "In the equation above, the conductance of potassium channels $g_\\mathrm{K}$ does not remain a constant, but changes according to the membrane potential, by which the channel is categorized as **voltage-gated ion channels**. If we want to build an ion channel model, we should figure out how the conductance of the ion channel changes with membrane potential.\n", + "\n", + "Fortunately, there has been a lot of work addressing this issue to formulate analytical expressions. For example, the conductance of one typical potassium channel can be written as:\n", + "\n", + "$$\n", + "\\begin{align}\n", + "g_\\mathrm{K} &= \\bar{g}_\\mathrm{K} n^4, \\\\\n", + "\\frac{\\mathrm{d}n}{\\mathrm{d}t} &= \\phi [\\alpha_n(V)(1-n) - \\beta_n(V)n],\n", + "\\end{align}\n", + "$$\n", + "\n", + "in which $\\bar{g}_\\mathrm{K}$ refers to the maximal conductance and $n$, also named the gating variable, refers to the probability (proportion) of potassium channels to open. $\\phi$ is a parameter showing the effects of temperature. In the differential equation of $n$, there are two parameters, $\\alpha_n(V)$ and $\\beta_n(V)$, that change with membrane potential:\n", + "\n", + "$$\n", + "\\begin{align}\n", + "\\alpha_n(V) &= \\frac{0.01(V+55)}{1 - \\exp(-\\frac{V+55}{10})}, \\\\\n", + "\\beta_n(V) &= 0.125 \\exp\\left(-\\frac{V+65}{80}\\right).\n", + "\\end{align}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we have learned the mathematical expression of the potassium channel. Next, we try to build this channel in BrainPy." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "import brainpy as bp\n", + "import brainpy.math as bm\n", + "\n", + "bm.set_platform('cpu')\n", + "\n", + "\n", + "class IK(bp.dyn.Channel):\n", + " def __init__(self, size, E=-77., g_max=36., phi=1., method='exp_auto'):\n", + " super(IK, self).__init__(size)\n", + " self.g_max = g_max\n", + " self.E = E\n", + " self.phi = phi\n", + "\n", + " self.n = bm.Variable(bm.zeros(size)) # variables should be packed with bm.Variable\n", + " \n", + " self.integral = bp.odeint(self.dn, method=method)\n", + "\n", + " def dn(self, n, t, V):\n", + " alpha_n = 0.01 * (V + 55) / (1 - bm.exp(-(V + 55) / 10))\n", + " beta_n = 0.125 * bm.exp(-(V + 65) / 80)\n", + " return self.phi * (alpha_n * (1. - n) - beta_n * n)\n", + "\n", + " def update(self, tdi, V):\n", + " self.n.value = self.integral(self.n, tdi.t, V, dt=tdi.dt)\n", + "\n", + " def current(self, V):\n", + " return self.g_max * self.n ** 4 * (self.E - V)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that besides the initialzation and update function, **another function named ``current()`` that computes the current flow through this channel must be implemented**. Then this potassium channel model can be used as a building block for assembling a conductance-based neuron model." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Building a conductance-based neuron model with ion channels" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Instead of building a conductance-based model from scratch, we can utilize ion channel models as building blocks to assemble a neuron model in a modular and convenient way. Now let's try to construct a **Hodgkin-Hoxley (HH) model** (jump to [here](customize_neuron_models.ipynb) for the complete mathematical expression of the HH model).\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The HH neuron models the cuurent flows of potassium, sodium, and leaky channels. Besides the potassium channel that we implemented, we can import the other channel models from ``brainpy.dyn.channels``:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from brainpy.dyn.channels import INa_HH1952, IL\n", + "# actually the potassium channel we implemented can also be found in this package as 'IK_HH1952'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then we wrap these three channels into a single neuron model:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "class HH(bp.dyn.CondNeuGroup):\n", + " def __init__(self, size):\n", + " super(HH, self).__init__(size, V_initializer=bp.init.Uniform(-70, -50.))\n", + " self.IK = IK(size, E=-77., g_max=36.)\n", + " self.INa = INa_HH1952(size, E=50., g_max=120.)\n", + " self.IL = IL(size, E=-54.39, g_max=0.03)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here the `HH` class should inherit the superclass **`bp.dyn.CondNeuGroup`**, which will automatically integrate the current flows by calling the `current()` function of each channel model to compute the neuronal activity when running a simulation.\n", + "\n", + "Surprisingly, the model contruction is finished! Users do not need to implement the update function of the neuron model as `CondNeuGroup` has its own way to update variables (like the membrane potential `V` and spiking sequence `spike`) implicitly." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now let's run a simulation of this HH model to examine the changes of the inner variables.\n", + "\n", + "First of all, we instantiate a neuron group with 1 HH neuron:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "neu = HH(1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then we wrap the neuron group into a dynamical-system runner `DSRunner` for running a simulation:" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "runner = bp.dyn.DSRunner(\n", + " neu, \n", + " monitors=['V', 'IK.n', 'INa.p', 'INa.q'], \n", + " inputs=('input', 6.) # constant external inputs of 6 mA to all neurons\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then we run the simulation and visualize the result:" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "7f512f1c74124a4ab1cf6606bd9a2f7d", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/2000 [00:00" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "runner.run(200) # the running time is 200 ms\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "plt.plot(runner.mon['ts'], runner.mon['V'])\n", + "plt.xlabel('t (ms)')\n", + "plt.ylabel('V (mV)')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also visualize the changes of the gating variables of sodium and potassium channels:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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ZvKzMDCzDPvY393Pa7NREzC6fKpfD4cDi9rG/uY9l5XnJfT4JzzuItv14sVLrKWKJ+Rh9Wgbm/BnkZZ54WxUn49E3ANPD/i8HmhJcey1RaRspZZP+uw14FJUKioGU8h4p5Rop5Zri4uIkbstA6CLV0u8lP1vtM9Lc3c+QJwX5bJ2rc9hPrlNxHWnvxedPQT5bT3EM+yA7MwOAmpae1OSYdQPmk2ayMx1Y8bO/OUU7B2o+pFA+ijPDjs2kcSCFXH59dkqGw06GWeNACo2KVxf6DIcDp0Wm1IB5tEiuAy2pM2Auv+LKtNvIsJDCOvQxFNgE1G7HYdJS1w4BTYJAIIRAIHF5T8yZN8kI/dvAXCFEpRDChhLzJ6IvEkLkAmcBj4e95hRCZAf+Bi4E9kZ/9rhDFymvZiLXqQTRjJ/qlhQ0ED168EszOTqX5vNS15GCmQi6UfFjJlvnGnK5aO5NwZSz4AwfE87MDCz4aOwZond4YgNUcSGVRw/gzHBgE34Otw/g9qVgP3Dpxy9VUJuZ4cBh0qhu6U/N4K/mx6cLvcNuJ9OcQpHS/Hh0TbLb7GRbZUq53H6wmgUWm51cG+xPlVHR/Az7IS/TitliI88uUhiBSfxSlUsIgcUkcHnH1wajtym+7777eN/73hf3vfFgVKGXUvqAW4DngP3AP6WUVUKITwshPh126buB56WU4Yo1BdgghNgFbAGeklI+O6E7TgXCRMrhUANfllQJfVB8TTj0HJwVPwdSwhUql92muCz4qG5NnQHTENitKnQ1o3EwFVyahqZ72TabHTN+fJrkcFtqjGXAo7da7diEn0GPn8aeFExV1Xz49S5ptdlwmCUdA246B1IwK0v68WHGZjFhtljJtEB95yDDnhQYS82PR5rIdlgRJivZVsmh1gH8KTKWHs1EtkOtxM2zw8HW/hTNlJJIwGQSgMAsGLfQpxpJzaOXUj4tpZwnpZwtpfyR/trdUsq7w665T0p5bdTnaqWUy/WfxYHPnnCQIUG06YKYbZWpEUQtlstuSpUgKqPiw4wtzKikyoAp8RVYg0YlhVxhgmiWqpwpMyo6l8Vmw4J6fikxzNKPDxM2iwmT2YZd6AP3rSk4FETz4ZWCbLsSxAyzhpRQ05YaLp8myLJbwGzBaZW4fRpHOlNgmKUS+iy7FcxWsm3QPeSlvT81U5ilFJj1/W7MJvD4NfzaiZe+Sa+MhYgUR2Cke1aBPUUiFeZl61wz86wpTRNpYUZlaraFgykqV8jLVh59nl2krFwaIS9baD6sZlJkmH34MGO3mDCbbZhJpVFRqRslvmasQglGdSrSHDqX024BsxW7SXGlJE8vlUfvtFvAZCXTrLzrVDkBHg2y7GplbJZF50pJFBvr0QMnZJ4+LfQQEl8ZSqekTOiD0UPIy55TZE9p9ODDFEynzC3OSFGayIfUm1PAqCwoyUiZ+PqFSYmvfhjzvKKMlD0vvzQFvVHh91Gen6o6jBRfk/SRl2mlOiUevRr4DYivVfixW0wpE1+vpkcPZisOk4YQqTLMAY9eGctMfVlASsqFRJMogRdhQp+KsaIJIi30EJbiMGHXc/QV+TY6Bz3Gh3xxcvSzChwc7RoyfpZPYLsFTNjtutAX2alpHzB+lo/U8AszDqvK+QLML3ZQ3ZKC/Kjmx485KL6gG5UUiZQfQZae80XzMX9KdoqiIh++gFExWRGal/lTslPj0Us/Xs0UFF/h9zF3SlaKxFfDo5lw2s1gsmCSPmYWZKbsebk1ETSWVvwUZdlTY5gBjZBHLwCTELjTHv0JCn0aooaJDF0QK/KUWBneGMMHfnXPtzLfipRwyGjPTfrDxFeVa3aBHY9Po77T4D1A9Lx5lt7BAOYWOegd9tJmuLHUvWyHEkSABSUOGnuG6Z/gMvR4XD5pxmnTuaSf+VOyONw+YPwWD9KPV4pQHfp9zC/N5mDrQAqMpQ+PFEHxRfMyb0p2CtMpgiyHNWQsS1PEJTXcfhE0lvi9LCjNTk2qTUqkVOKOPr3SYTWfkAOyaaGHsBSHOehll+cpYTQ8Z6lzWa2WoOc7M19xGe5NaT60oOeruCoLVPkMb/jhXrYuvnMKFZfh3pQ+aOm0hco1r0hFYoYPXGp+fFJERg9THPg0afyUWM2HN2jAlPjOL81mwO0zfpZPIMXhsOpGRQliW7+b7kGDz4+VftyaUHlznWv+lGzqOweNF0V9cVawzWs+5k1RQm/0LB+JRIPQ9gpS4rCYcHm1MRvm+vp6lixZYuj9hSMt9BBMp1itFiy655trg6Ism/Feh56jz7DZgyI1JcuCw5qC/KjmD3nZuvjOyLNiEikQX31qoDPMqMwKGJUUcPmCgqgGZecUqXUCqXhe3qjoYX6x4jLeCdDwamF1qAsipMIw+/AGBy0tQUGE1Dgcbr8IRUWaj/mlOWgpmOUjNT9uf2DswRI0YC6vxrGuVOxkKYIePbpH79M0fKnaZG+cSAs9BMXXESa++JU3lRovW+B0WIPCYZY+5pZkpyR6iBZfu9CoKHQavzJRhg0k6nuP59qhJNtu/OIYTXn04QZsaraKJoyvQ19o0DIQFeXbsZhESoylW4rgjBGQzCtRq6cNX8wkNdzBQUsl9AtKcwDjV61Kza/K5dCjIr+X+aVqTymjFzNJ3eHIdgQ8ei/zSpUBM7xtBGfdAAjl0VuVpI4nUvH7/dx4440sXryYCy+8kOFh46K4tNBD0KPPtIfEF83LgtIcqlv6jR241NTUwHDhwO9jybRc9jb2GZuLleHpFH1bI83L4mm57G00eKMn3ahkR5TLy5JpuexpMJpLzcsOr0Oh+Vg0NYc9KShXaBaH4rIJP/OmZBtfh9KPV4tME+VYYWZhpuF1KPW8eXj0MCXHTlGWjT2NxouvFjbIjOalsiiLTJs5Ze3QGczR+1hQmo3FJIxvG0gkoXn0AY8eYHgcQn/o0CFuvvlmqqqqyMvL4z//+c/oH0oSyWxqdvJDX+DgcIR59JqfZeW5uH0aB1sHWDQ1xyCusEHLMPFdVp7Lg1uOcqRziAqjtsDVvZusKPFdXl7Kk7uaaO93U5xtH/k7kuaK9ejRfCwrz+WV6jYG3T71nhGQGl4ZOR6A5mPZtFz+tukIXr+G1WyQD6MvLFL5Zf3+/V6WT8/l6T0tSCkRIt6+f2OHEt94dZjHtnpjd5bU/GFtw6vEVwBLp+Wyu6HHUC7pV2sRwgeZzSbBkqm57EqBExASejNoPhxWM/OmZLM7Ca6fbvkpB7oOJMflGcAjLZitdsyaW+mILZMhjx+TICj6CwoW8LW1Xxv16yorK1mxYgUAq1evnvDWxOFIe/QQ9OgzbLZQB/N7WTE9D4BdRjZ8qUU2ep1rmb6X+m4jvQ49xeGMEERvcCe/PUbuZBmRNw8T3/JcpMRYzy2B+C6bnofbpxmap5eaP5Q3j6rD3mEvRwycvRQhvuFc03Jp6nUZOtVX+uM4AZqfZeV51LQPMGDgATVSHysKGjBNzYxaVp7LvuY+vAZHzD7MochS51o+PZfdDb2pOzQGCGzqaxaC8aTow7cpNpvNE96aOBxpjx6Ce3MHp38BaF5mFGSSl2ll17Eerltr0NbJ+rxsZ5Q3Om9KNnaLid3Herhy+VSDuPwh8TXrncnvY/H0HEwCdh3r5dwFBm1Lq69+DE87KAOWB8Duhl7WzTLmEBJNX+yTFZVqWx4wlg29LJlmzCEkfr8+jz7cy/Z7WVauttjd1dBjWASmhN6huAil9QJOwJ7GHsOel9RnSTntFnCH2vzy6cowVzUa97zU6mJTxFoEgGXT8/BsqKO6pd+w56VWTYenbgJGJY8HtxwbNWJOxvNWPBo076JF5pNbXE7GYCO4+6F0Ce39bpp7h1lYlmNcZDlBnBh3cbwRSKc4Ir1sIQTLyvOMDS+1gFGJFESr2cTiqTlJhZdJQx8gzYpKBTjtFuaUZBkaomt+Hz4ZNrMCQPNSlGVnWl6GoVGR5vPq4bk5YpwjYJiNLpc/OgLT/CHDbODz0vzhTkBIfJdMyw0aZqMgNV9oLUJEZJkHYGw7DJ/9pU95RMoIw2wURPhAfYALgsbSsHaoRwYSoRZM6Tl6gEybnqdPxQZx48Q7QuhbBlt4u+VtjvUdix+6RQzghAQRYEV5Lgdbk9+bvnmgmbdb3qZxoDH+BZoPX0x+OeR17G3qTXq+b0N/A2+3vE3LYEt8Kr9X5c1t8bn2NCYXykopOdJ3hLdb3qZtKP5pWP6AIEYIR6iTJduZpZTU9tbydsvbdAzHP13JH5HiCAmiEIKl05LP+0opqemuYWvLVrpd8Q9/CaZTHJFcVrNJDf4myaVJjequara2bKXXHf8z0u+PU4feMRtmv+bnQNcBtrVuo98TP40l48xcQvON2TD7NB9VnVVsb93OoDfBugI9nRLZDsdumL2al70de9nRtoNhX5wZKVIi0CLHwHSPPmCYx/K8hrxDDHmHRjz0W6JSNeHnMzmsZgTJD8hqUqNkWglbdmwJcn35y1/me9/7XlKfTwYndeqmZbCFH236Ea82vBp8bWXJSr516reYlz8vdKEWvp9JqIMBLJ+eh1+T7G3sY21lQUKuhv4GfrDpB7zZ9GbwtVNKT+Fb677FrLxZISrNr7w2WyzXiul53PdmPdUt/SMO/tb11nHbW7extXVr8LXTp57OretuZXpO6IwYny9MpALHc+riu2J6Hv/e1sCxrmFmFGYm5DrYfZDvv/V9drfvDr529vSzuXXdrZQ6S4Ov+XUvOzgvG8Lyo3k8s7eFjgE3RVmJB3+rOqr4/lvfZ3/XfkAtKr+w4kK+vvbrFGUUhXHF90YD5frdq4cZcPv0FEh87GjbwW1v3UZNTw0AJmHissrL+MopXyHfkR+8Tgl9hnICZFTbKM/jobeP4vFp2CyJfaZNzZv40aYfUd9XD4BZmLl6ztX875r/JduWHbxOat6QAXOFBDHA9cL+VjRN6kvu4+P1hte5ffPtQUfDYrJwzbxr+MKqL5BpDXvOEZMCzJFc03PZcbQnIUcALxx5gZ9u+SmtQ+qwb5vJxvULr+eWlbdgN4ees9Bnf2VHRbHCbGV5eV5SXE8efpI7t90ZNP4Os4MPL/4wn17+aaymUKQF6vCbYLSnt0Gr2cSSabmjHmEopaTH3UPrUCt+/ftMwkRRRhFFGUWhgfeggxTm0euvmU0Cu9XM4CjjHFJKulxdtA21BQXebDIzP3++YQP8AZy0Hv3RvqN88OkPsrllM59Z/hnuueAevrLmK+r1pz7IpuZNwWv9gRxiHC975QzV6d8eYdbDoe5DfPDpD7KnfQ+fW/k5/njhH/ni6i9yqPsQH3r6Q+xo2xG81uf1qsHYqEFLgFN0Q7K5rjMhV1VHFR96+kPU9NTwv6v/lz9e+Ec+u/Kz7G7fzfVPX8++ztCZ7SOJ79okuLa3bueGp2+gsb+Rr53yNe654B4+vfzTbG7ezPVPXU9Nd02Iyx87Zz8giAGuLXWJ6/DNxjf5yLMfocvVxa3rbuWeC+7h40s+zqvHXuX6p67naN/R4LWavqNkvAjslIoC/Jpk25HEHfqloy/x8ec+zrBvmO+u/y5/OP8P3LDwBp6tf5YbnrkhIkKScQdIFde6ygJcXm3EQe2nap/i0y+oYxtuO+027j7/bq6Zdw2P1TzGh5/5cETUEsibR49zBOqwZ8jLoREWGP374L+55aVbyLBkcPsZt/O7837HVbOv4uHqh/n4cx+PjCR0Lzuec3NKRQGNPcM0dCceaL6/6n6+9OqXKMwo5Kdn/pS7zruLiysv5r6q+7jp+ZsY8oY+q4Q+elwqVK7q1n66RliN+/tdv+ebG77JtKxp3HHWHfzm3N9wzvRzuGf3Pdzy0i24/fogtf5cgmlYk1Xl0vVZdWsrC9jd0DtiSqV1qJWmgSYcZgfTs6czPXs6TquTtqE2jvUfC/PuQ5GwKejRh15z2iwMefwJI2YpJc2DzbQMtpBpzQxylWSWGC7ycJIK/ZB3iM++/Fm8fi9/u+Rv/M+K/2H91PV8ePGH+feV/6Y8u5zPv/x56nrrAPB5PXFESjWaAqeN+VOy2VQbXxB73b187uXPYRIm/nHZP7hx2Y2cWnYqH1/ycf55+T8pzCjkcy9/LuhheX1efU6xOcaTmpaXQXl+RsJDmjuGO/jcy58jy5rFg5c9yEeXfJRTy07lpmU38dDlD5FhyeCzL32W9qF2VQQ9nRJPfOeWZFHgtLE5gfg2DzTzhVe+QElmCQ9f/jAfWvQh1k9dz80rbuaBSx9AIrnl5VvocfXo1eWNO2ME1JS9DKuZzQnqsL63nv997X+ZmTOThy9/mGsXXMv6qev5wuovcP8l9zPsG+azL3+WAc+AXl3KG82OI76rZ+ZjNomEXNVd1XzjjW+wqGARD1/+MO+b9z5Om3YaXz7ly/z5oj8H69jlU6dwRaQ44ogvkLAOd7Xv4tsbv82qKat46PKHePfcd3P6tNO59dRb+f35v6ehv4EvvfolvPr3RUSWUXV4qj4wmsgwb27ezA83/ZDTp53Og5c9yBWzr+DM8jP53mnf41fn/Irq7mq+8tpXgl6qiB60DONaV6lzJWiHrxx9hZ9v/TkXzLyAv1/ydy6ddSnvKn8XPzrjR9zxrjvY2b6Tb274ZlDkhH7ISfSYiuJSdZjIkXq69ml+t/N3XDn7Su67+D4urriYs6efzc/O+hm3nXYbbza9yW1v3aa49IWP0mTGbontX2srC/BpMqFX3+XqonO4k3xHPjNzZpJjzyHHnsOMnBmUOkvp9/TTOtga+aGAKId59ABOuxlNyoTpm05XJ92ubgozCpmRPSPIVeBInDWYCJISeiHExUKIaiFEjRDi63HeP1sI0SuE2Kn/fCfZz6YCd267k7reOn521s+YXzA/4r2ijCJ+f/7vsZgsfHvjt/FrfrzewIBboHGIYKMHOHVWAVvru+NOA/vZ2z+jZaiF/3fO/6MytzLivbKsMn573m/xaT5+8NYPkFLi93l14bDGiC+oxrilviuuJ/CjTT+iz9PHr8/9NeXZ5RHvzciZwW/O/Q29nl5+skUdcBxM3cTpzEII1lYUxBUOKSXfefM7eDQPvz7310xxRs70mJM/h1+d8ytaB1v5xbZfqK+NN2ipd2ar2cTqmflxBVGTGrduvBWLycJvzv0NhRmRMz0WFy7mF2f9grreOn6787fq/vQIzBlHfJ12C0un5caNHnyaj29u+CZZ1ix+de6vyLVHzvRYWbKSn575U/Z37eePe/4Y5IreRiJQh4VZduaWZMUVRLffzTfe+AYlmSX88uxf4rRGzvRYP3U9t51+GzvadnD/vvv17/XHjj3o5SrPz6As1xGXa9A7yDc3fJOZOTP5+Vk/x2FxRLx/9vSz+ea6b/JW81v88+A/g1yJxHdBaTa5Gda4baPX3ct33/wuCwsWcvsZt2MNfFbHxZUX86XVX+Kloy/xZO2ToGkIJEIExDcyslxanovdYopbrvahdn6w6QesKlnF99Z/D0vgszrePffdfGb5Z3ji8BO8fPTloKBbLPp15sjntWZmPiZBXCfA7XPTMthCli2LMmdZjFddmFFIYUYhXa4u5XAEjFjwOt2j118PrBmJl75x+Vy0DbaRY8thSuaUMXvw45kiOqrQCyHMwF3AJcAi4DohxKI4l74hpVyh/9w2xs8ahuquav518F9cv/B6Ti07Ne41pc5SvnrKV9nVvosXjr6AL+iN6g0jbAoYKG9q2OuPGVDc0baDJw4/wUcXf5Tlxcvjcs3MmcnNK25mY9NG3mh8A5/ujTqDy9yJ5KospGvQE7MHyIbGDbx49EU+tfxTMcYrgPkF87lx6Y08f+R5trZsRfP5ImcgQDCPCbBuVgHHuoZpitow6/kjz7OpeROfW/m5GOMVwLLiZdyw+AYeq3mMfZ37lNDLsIUqUeVap4foPUORIfrjNY+zu303X17zZaZmxZ9WurZsLdfMu4YHDzxIbW8t0h9PfMO4ZhWwq6EnJkR/6MBDHOw+yDfXfTMi5x+Os6afxaWVl3Lv3ntpHmjWPfroWTeRXFvru2JWT9+7916O9R/jO+u/E2NQArik8hLOm3Ee9+y+h25XN0LG7hcUeF5CCNZVKsMc3dH/sOsPtA218f3Tvh9jUAJ439z3cWrZqfxmx28Y9A5ikn4QpijxVeUymQSnVBTENZa/3v5r+jx9/OD0H8QYlABuWHQDy4uX88ttv8SjD5qaYsRXcdktZlbNyI9rVH6x7Rd4/B5+cPoPYgxKADcuu5F5+fO4Y+sd+HwqhRPYLDDYNnRjme2wsmRaLpuiyuVwOKhtrgUJU51TEwpvSWYJNrONlqEW/RDBwObEhDx7HVazqttBd2QblFLSMtiCSZgoy4o1KKNBSklnZ2fwyNNkkYxHvxao0Y8F9AAPAVcl+f0T+ey48KvtvyLLmsX/LP+fEa+7fNblVOZW8uc9f8bn84W8G4gR+kCIHp2++e2O31KcUcyNS28ckevaBddS6izlr1V/xR++SjDYwSLFN5pLSslvd/yW6dnT+ciij4zI9ZHFHyHfns/f9v0Nze8Ny1fGim+8cmlS43c7f8ecvDl8YP4HRuS6aelNZFoy+fu+v6P543ijEYJYiJSReXqv5uX3u37PsqJlXDn7yhG5PrPiM5iFmQf2PxApvnG4Tq0sxOuPDNFdPhd/3PNHTi07lfNmnDci1+dXfR6/9PNw9cPBQUtngue1trKQQY+fvU2hbQP6Pf3cX3U/5804j9OmnjYi1y0rbmHYN8xD1Q+pXLJQ57jGNZazCukY8HC4PTS7pWO4gwcOPMCVs69kRcmKhDxCCD678rP0e/r5z8H/IKQ/TBDj1OGsAuo7h2gJO0i+aaCJRw49wjXzrknobIAavLxl5S10DHfw39ongTAvO27bKGBfcx+9Q6HI9nDPYZ6qfYoPL/4wM3ISr2GxmCx8ZvlnaBxo5MWG1wCwxpQr7HlVFLDzWE/EXjQDmQNsqtvEQOMANQdr2L9/f9yf6gPV9B3r48ihI+zct4f9R9o4cvSoer/mCPuPtEVc39lYy+FD1ezbF3ptV9UuDh88zEDjAIeqDyXkSvRz4MAB+vv7KS+PjOhHQzJCPw04FvZ/g/5aNNYLIXYJIZ4RQiwe42cNQU13DW80vsENi25I6EUFYDaZuW7BdRzoOkCNrw8tsBUt6KP1oYZQmGVnQWk2Gw6FBs52t+9mS8sWPrL4I5GzGeLAYrLwgfkfYHPLZo75h8LE10R0mmhGQSbl+Rm8drA9+Nqm5k1UdVbx8SUfT+jZBOCwOHjvvPfyasOrtGuesGltsR1sYWkOhU4br4dxvXL0FWp7a7lx6Y2YA2KTAFm2LK6acxXP1j9Lv/QkHLQENRvGaTNHlOuZumdoHmzmU8s/NapnU5hRyCWVl/Dk4Sdxa9444hviOqWyAKtZRHA9WvMoXa4uPrVsdK6pWVM5Z/o5PFrzKH7NjxSmhOJ72uxChIDXqkNcD1c/zIB3gE8t+9SIPKDSYOvL1vNEzRMgfZiDghhbh2fMUVFIeLn+sf8fePwePrn0k6NyLStexrLiZTxx+AnM+DGbwxwbiGiHpwe5QtNp76u6DwR8YuknRuVaV7qOOXlzePzwfwGwmBOL7xlzipASNtSE+tdf9v6FDEsGH1704VG5zp5+NtOypvF4/TMAWIPRQ2zbOH1uER6fFuHc/Hnfn/lj4x9ZvGgxCxcuHPFn2eJl3FZ7Gw+0/ImFz72f7VteU+8NbWLhc+9n4ewZwWu7rMV84vFmhjKnBF+7q+kuflj3Q5YuXjoqV6KfyspKrNaRdSAayQh9vF4RnSTaDsyUUi4HfgM8NobPqguFuEkIsVUIsbW9vT3eJaPi7/v/jt1sH9UTDeDCmRdiEiZe07pC0xAhuEdGOM6eX8Lb9V306Qdb3Fd1Hzm2HN43731JcwFspj+0lzpELOoA5Xmdu6CEjTWdQa/jvqr7KM4oHtXrDefSpMbbpuE4++qEuEwmwdnzS3j1YHtw7v69VfdSnlXOhRUXJs3l1bxsN3virEUIdWabxcQZc4t4+UAbUkqklNy7917m5c/jzGlnJs015Btit1VDC3i+cTpzlt3CuspCXj6gREqTGvdX3c+K4hWsnrI6aa4uVxfVVomIFqmwMZWiLDvLy/N4uVpxeTUvf9/3d06behoLCxcmx1VxIQ0DDdRaBMKc2POdXpDJ3JIsXj6gBgSHvEM8fOBhzp95fsIUW7xyVXdXc8xixqRvyR0vrbegNJuyXEewDnvdvTxy6BEun3V5xLTaRBBCcMHMC9jRsZsOkwlzQJgCxjKsDlfOyCcv08pLernahtp4uvZp3jP3PRFTXRPBbDJz3ozz2Ny+gwEhMOvHZsarw/WzCsmwmoPlOtp3lJePvsx1C65LmPYKh9Vs5Zzp5/BG23Y8gDXIFWuYz5xbjMUkglwHug6wqXkTNyy6IWL66WQgGaFvAKaH/V8ONIVfIKXsk1IO6H8/DViFEEXJfDbsO+6RUq6RUq4pLi4eQxEUBjwDPFX7FFfMviKpxgHKS5yfP5/dDODDEhLfqNQNwPkLS/Bpkteq2+lydfHK0Ve4es7VSTUOUIOlM7JnsNU0hA9LKHqIw3XughKGvX7equ2keaCZt5re4n3z3ofNbEuKa0HBAooyithqceGVUdMQ/bFcPUNedhztpranll3tu7h2wbUxA1+JsLxkOVnWLN62+tGEJaHnC3Degik097rY39xPVWcVNT01XLfguqTzlKeUnoLNZONtmwyJU5zODHDOghJq2gY42jnElpYtNA40cv3C65PmOm3qaZiEiS32kcUXVB3ubuihvd/N6w2v0+nq5PoF1yfFAwQN3TaHBWFJLFIBri11XfS7vLx09CX6vf1j4ypXXFsdjrDUTezzCjgcbxzqwO3z80zdM7j97jGXSyLZ7rBjic6bh3GZTYKz5xXzWrVyOJ48/CQ+6eO6BdeNqVxezccuhx2LLboOQ0bFYTVz+pzCoMPxWM1jCCGSdg4DXIP+YfbZbdhiuELGMjfDypqK/KDQP3roUawmK++d+96kuYxCMkL/NjBXCFEphLAB1wJPhF8ghCgVeg8SQqzVv7czmc8ahSxbFg9f8TA3Lb1pTJ9bWbKSatMwnkDOFyJW1AWvm5FPgdPGS/tbeabuGXzSx1VzxjbcsKx4GbUmT2jGSIBLixywOVX3Ol450MaTtU8ikUl786A66dKipRw2+6LEV8QIx5nzirCYBC8daOOxw49hFmYum3VZ0lxWk5XFhYs5bNHiiG9kHZ69QBnwV6rbeKzmMRxmBxdVXJQ0V6Y1k7n5c6mxgsk0sviet6AEgJcPtPJ4zeNkW7M5d8a5SXPlOfKYkT2DQ1YTJnO01xb5vM5dUIKU8Gp1G4/XPE5RRhGnTzs9aa4pzimUZJRwwGbBEjQq8Y3luQtK8PolGw518FjNY5RnlScdpQBU5FTgtGRSZbcFj5dMWIcLSxjy+NlS18VjNY8xP39+0lEKqMkBFmFhr92OZQQvG5Rh7hz0sPNYN4/VPMaqklXMzJmZNNfiQpUtrrLZsMWUK/p5TaGhe5gDrb08cfgJTpt6GiWZJUlzLS1aqrjstjCPPrFzc6Cln7rOXp6qe4pzZ5w7alo5FRhV6KWUPuAW4DlgP/BPKWWVEOLTQohP65e9D9grhNgF/Bq4VirE/WwqCgIwK3cWZVllY/rMnPw5uIWk1SLCxNca0zjMJsHZ84t5pbqdxw49xqLCRZGra5PhyptDh1mjz2QOraSMkyZSXkcRz+9r4fGaxzml9JSY6ZTJcDWYJd7wPHuc6CHHYeWUigKe39fMfw//lzPLz0w4IyUhV/4c6i0SLcAVZ3YKQEm2g2XluTxXdYyn657mvJnnRawMTbZcdRYRJ50SyVVR5GRWsZNn9tXz4pEXuaTykjGHy3Pz51JrM2MeRXwXT81hSo6dp6sO8UbDG1wx64qkI6IAFhTMp9pmjZNOieRaPTOf3AwrT1RVsaVlC1fNuWpMMzdMwsT8vDkctFmxWBOnpADWzyrCYTXx791bqeqsGrNjYzPbmJMzg4M2a5ggxhffs+eVYDYJHtq9kfq++jFzZduymZ45hWqbNY5HH2ssAe7f/iKtQ61cPefqMXGVZJZQYM2m2mbDbk8cPQCcu1Bx/Wnrf+l1946ZyygkNY9eSvm0lHKelHK2lPJH+mt3Synv1v/+rZRysZRyuZTyVCnlmyN99kRCRU4FAE02y4jiC3DR4lL6fC0c6D7ApZWXjplrdt5sANrsYR0zTvQAcMXyMtpcdRztPzourll5s9AEdDqiuOKU67JlZdT376N9uJ3LKpP35oNcubNwmQQDNhHigZjODHDZ0jKqunfQ7+kfdx12Wkx4bNEDibHlunxpGdvb38Lld3HprHHUYe4sjlnMCFt09BD5vIQQXLq0jLdaXscnfePiKndOpdFqwWYbOSVlMZu4eHEprze+DDCu5zXdOZVGiwW7fjh9okglw2bmvAVTeLXhJQSCSyovGTNXecYUGi0WHHZ9OmDQWEbWYW6mlTPmFPHy0RexmCxcMPOCMXNNc5TQZLXgdATKFb8OS3MdrJmZzyvHXiTTksnZ088eM9dUexFNFguZgWmOCQzz7OIsFpRm83LDS+Tb81lftn7MXEbgpFwZOxYEQrYe6+iCeM78ErILqgHGlAaI5uq1hVW7yRqX64JFU8jIOwCIcTXEKZlqkVNQfCGx0C8tw5qzDxNmzph2xpi5AuUaDBgwoZcvDteVK6Ziza7CKhwJ1zkkwzVk08f0RxD6q1ZOw5y1jwxTLiuKV4yLSwqBJxAIjMB19YppCGcVudYS5ucnnnqYCNOcUxg0mfAF2kaCSAXgqpVT0TL2MsVREbG3UbKYmlFMm8WCxT5ypAJw1YqpeO17qchaNOZID6DEXkiTxYLDPnKkAnD1iqm4bLtYkLtqzJEeQJElT4lvRsCoxI9UAK5cUcaAeTdLC9aNa2C0yJxLo8VMVmYUVxzn5ooVU+gXe1hTcsaoM9lShXe80BdnqLxxrzVcfC0xHgeomSMFxYfQ3KXkWUefeRCNgEj1xRiV2MaRabOQW3gQXDPJsiQ3uByOQLn6wmdhmeMLfV6mlayCA+Cai8M88lTRuFyZimsgwCVEwkhlSo6djLwDCNeC0GZUY+HSyzUcGJceQXxnFNix5VRjci0aVwcrsqt1BkMBrjizUwKYM8WKJasG0/DSce1VkmtRm9h5bfrCqxHEd16ZCUtmPebhJWPmAXAKdV6r3x5tLGOf1/xyP+aMRsQ4ubJw4jEJTI7oaC+2XHPLBzHZOmFoccx7ycBJJt0mExkx6ZTY5zV7Whcmaz9i3FwZdJnNZGVk6FyJn9fMqS0IswsGx8dlBN7xQp9pzcShQW+4DiQQ3153L13+arz9i3hsR4JtiEdAvj0fIaE/PH2bIE3UMthCv6zH1buQ/+5uHjNXwPsaCNfSBB59XW8dbtoY6l7Ai/vjb0M8EgodatuCQWvYzNkEkcrejr34RB+9HfPZWJN4Q7VEyLXp4msNCGJi4djauhUpXLS3zh1118J4yEB5lS7r6OK7qXkTCB+NjbPGdcKVyafEyRs0YIk9341Nb4CQHD5SwbGusZ9wZfYrEn8SUdGbza8DcKBmxrhOuAqUS4sxKnHqsPUNAHZVT6N3ONbojAar34oUAhFYNBpn6m0A2zo2Aia27J8yrn3jbX4rQyYTDkdUWi+Oc7O7eyMmaWPjngJjT9MaA97xQi+lJFMDd/g2swk83y0tW5BoVGau5i8b69HGeF6YJgUOKfFaoqOHWK63mt4CYJp9JfdurBvz/hY+vxUhJf6YSCUOV7PiKjIv596NdWPiARh26Z05hiu2AwV2Dc1l8bi4egeU2Ep72HgKJCyXxWQh0zef+zbWj5mrf0Bf5m6P8kbjdOa3mt8iw5KJxTOL+94cO9fwkCpHUKRGEsTmTeTa8pHucv761ti5XMOKy6Q7oyNFKm81vcWUjKm4XYX8Y/ORMXP5XOo5WQJcwXn0ccrVtImZWXMYGs7iX1uPxbw/GjS3+m57YMbzCHX4VtNbzMlZTO+Alcd3jt1pw6O4MrICXIkN86bmTczPW0Frn8aze+OfHZFqnDRCP+D28ZV/7eLZvWPzfpt6XTg08JhHz2Vvbt5MpiWT/1l/NnUdg7y4vzXmmpFQ1zFIpgaecI8+bM/scGxp2UKBo4BPrltPVVMfbyXYjTERatuHyJTgi4ge4ovv5ubNTM+ezsfWrWRzXdeYT2g62uFDSIkWMR4QP1LZ0ryF+fnz+eApi3m5uo2atrF5v82d+l45Aa5AmigB17KiZbx/zRye3tM84ra78dDapW8AZ4/KmydoG2umrObdK2fw6I6GMXu/PT36iUWjCL2Uki3NW1g/dR0XLynjobePjdn77e9VXqVwBLzs+MbSr/nZ2rKVM8rXc/b8Yv6+6eiYvd/BfhHFFV8Q3X43O9p2cNaM0zilIp97N9bj8Y3N+3UNqN/Spt9jgpRUn6ePfV37OL/idBaW5fDnDXVJH/YTQGAXZo/ZG8UVWT+tg63U9dZxyZwzmVmYyZ/eqE3xubXxcdIIfYbVzO6GXn78zIExNZBNhztxahJPEoOxW1q2sHrKai5fWs6MgkzufOHgmBrIptpOMjWJzxotiLEbH21p3sLa0rW8b/V0SnMc/OzZ6jE1EMWlRYlvbN480JnXlq7lurUzyM+08rNnq5PmAbVNr1PKkPgGuKI6WKAzry1by0fWz8Rps3DHc2Pj2lXfj5ASomcuRT2vXncv+7v2s65sHZ84oxKTSfDLFw6NievAMb03x6RTYjtzfV8968rWcdO7ZuH1S37z8ti4aprUnjJ+y8hpovq+etqG21hbtpbPnD2bfpePu187PCauY63KCHlNUemvqLZxoOsA/d5+1pWt4+Zz5tAx4OYvY4zCmtpVuYaJFsTIcu1q24VH87CubB2fOWcOjT3DPLjlKGNBm+4E9Ps9I3Jta9mGJjW9XLM51DbAo2NIxUop6e5W3zkQ5Ir/vLa0bAHg1LJ1/M9Zs9nV0MtzVWNzEI3ASSP0ZpPgG5cu4Ejn0JjC2Ud3NJIpJR5TeH7ZEhNatg21Uddbx7qydVjMJr528QIOtPTzzyRDTCklj2xvxCkl7vBajyNS4Z3ZYTXzxQvmsvNYD0/tSS5a0TTJYzsaydIkLhFVriiu8M6c7bByy7lz2VDTwavVyeXqfX6NJ3Y24tQ0hkWYgY3DFezMpesozLJz07tm8VxV64iHuoTD7fPzUpVeLsLENs7z2taqOvPa0rVMzcvgY6dV8MiOBqqakjtKbtDt462DnZikZEgGPMSRO/Pa0rXMKs7i2lOm88DmoxxuH0iKq3vQw65adV+DUv/uBLNTtjQrrnWl61g8NZerV0zlLxvqaIzagTQRWnpdHGpQm6INaCOL7+aWzYBakXxKRQHnLyzh7lcP0zGQXLRS2z5Ac4cSwsEkuMzCzKqSVZw9r5hTZxXw65cOJR2t7G3spb9PfeegjBbfSMO8pWULDrODZcXLuHRJGcvKc7nz+eqkjwvdXNeFZ0h954Cmb/oWtSVyOFeOLYf5BfN53+pyZhc7+dmzB3D7Jvc82ZNG6EHtR3PWvGLufOEgdR0Jzq8Mw8aaDjbUdJArBAOEi1Rs2iG8MwNcurSUUyry+fHT+5PqZM/va2XnsR5ypGQwWqRG6MwA711VzqKyHL73RBWdSXSyx3c1crB1AKfURuUK78wAHzp1BrOKnHzzkT1JdbIHtxyltWeALE1jUIZxRW0MF+AyC3NwJecnz6xkWl4GX/337qQ62V821NMz6CJTagyElyPB8wp0ZoDPnD2HQqedL/9rd1Kd7PevHsbt9uDUZEh8hQBhHrEzA3z+/Llk2sx85V+7YrYvjodfvXQIoWlkaFpSgljqLGV6tppW+b8XzsdsEnzt37uTGjP6+fPVOPRzJQe0gCAmNipz8uYEB/a/fslC3D6NWx/dM2p0KaXkjueqyRY612ieb/MWFhctJsuWhRCCb122iJ5hL99/YvT1lVJKfvZcNTm62A76Ry7XpuZNrCxZic1sw2RSXE29Ln789IFRufya5OfPVZOvb+kwqI0cPQQic5MwYTGb+Nbli6jtGOT/vTi2iG+iOKmEHuAn712K1Wzi5n9sD25AFg/Huob4wsM7qSjMJBfJYPgBwHFmjGxr3Ua2NTvYmYUQ3PG+5fg1yS0PbB9RqGraBvjaf3azoDSbbBkliHHEd1vbNkoySoKd2WI28csPrKBv2MctD+wYUaiqmnr59mNVrJyRFyu+cXL021u3U5FTEezMdouZOz+wgtZ+N198eOeIQrXtSDc/fGo/Z87KixREiCu+21u3s7BgIVk2NYKVabNwxzXLqOsY5CujCNWbNR3c+UI158/L18sVzhX7vLa3bmd58fLg/kC5mVZ+8p6l7G/u4zuPVY0oVC/ua+V3r9Zw2ZIiZSxlWDuK87y2t25n9ZTVmPT1AyXZDn5w9RK2H+3hR0/vH5Hr8Z2N3PdmPVcuLcGpyVgvOyxSkVKyvXU7a6asCU7hnF6Qya2XLWRDTQf/78WDCXlAGeV/b2vg6qVlulFJ7Pn6NT872nZEbK8wpySLL180j+eqWrnn9doRuf68oY5n9rbwniVqs9qhgJcdJ1Jx+93s7dzLmilrgq8tmZbLzefM4ZEdjfx908iDwL966RCvH2znygVqyvNA4GjBOCmpXncvNT01EeVaW1nAJ86o5G+bjvDojoaEPFJKfvrsAbYe6ebiefo6Ff0ksnhC3zLYQtNgE2tKQ+U6Z34J154ynbtfO8xzVZM3MHvSCX1Zbga/vm4lh9r6+fCft0Tspx3AxpoO3vv7N/H4NP5wwxqykvCy97TvYUnRkmBnBrXM/hfvX86uYz187N634w7AvXyglff/4S0sJsHdH1qNM574+mO5lpcsj5iPPb80m5+8dylv1XZy41+3RezdHcAze5q59g+byHZYuOu6FTpXYvGVUrKnY0/MoSkrpufx/SsX8/KBNm5+YDsDUafkSCl5dEcDH/rTZkpzHdzx3kW6IIZzRY4H+DQfVZ1VQQ87gNNmF/GNSxbw1O5mvvjPnTGDfVJKHtxylI/e+zYVhU6+e/kC3agkFt9h3zAHuw/GcJ2/aAqfPXcOD289xjce2RNjMP2a5C8b6vjU37exeGouXzh3lqrDcA8+KlLpcfVwtP9oTB1euXwqHzu9gns31nPbf/fFTKvz+TXueqWGLzy8k1Mq8vnEadOVARvBQ2wabKLT1RnDdf3aGbx/TTm/frmGO547EDNu5PFp3Pl8Nd94ZA/vmlfMB1aX6kYlmitUztreWoZ8QzFcnzxjFpctK+PHzxzgrldqYoyzy+vnR0/t44dP7eeixVO4fHEJGZoWK75h5drfuR+f5ot5Xp87dw7nLijh24/v5S8bYmeeDXl8fOuxPfy/Fw/xnpXTOH+OvnDPn1h893bsBdRmfOH46sXzWT+rkK/8azcPbTkaw9Xn8vKVf+/mntdrueHUmZw6LV/nCpQr1ljubt8NwLKiyHJ954pFLC/P47MP7hjfjJ9xYGwbcvwfwVnzivnt9av44sM7ueDO13jv6nKWTsuld9jLSwda2VjTyawiJ3/7xGrml2aT5fczKNVBvkKIGEEc8g5xqOdQ3ANGLl5Sxi8/sIKv/ns359/5GtesLmdhWQ7dQx6er2plS30X86dkc/cNq6kocuLU/AxEC6IvZCC6XF00DDTw/vnvj+F6z6pyPD6Nbz++l7N//gofOGUG80uz6Oj38PTeZnYc7WHJtBzuuWENU7PMODUt5CFCzAyfhoEGulxdMR0M4EOnzsTj0/jR0/s55+ev8oE105ld4qS1z81Tu5vZ09jL6pn53P2h1RSaB8nSJG1aYvE93HOYYd8wS4uXxnDd9K5Z+DTJz5+vZktdF+9fM52Kokyaelw8uauJAy39nDa7kN99cBU57macMqpcUVz7O/fjl/7g5lPh+NIF8/Brkt+9epgNNR28f810phdkcKxrmMd3NnK4fZBzF5Twq2tXkNl7UBmVCK7ItrG7Q+/MUXUohODbly1CSrh3Yz2vVbfz3tXlTM1zUNcxxOM7GznSOcSlS0v5xTUrsLds1cvlDnyBniYKce1p3wMQU4dCCG5/91IEgrteOcwL+1p5z6pypuTYOdw2yKM7GmnsGea9q8q5/T1LsNS/oozKCOIbEKnoOjSZBHe+fzkmIbjjuWqe2t3Mu1dOozDLxsHWAR7d0UBrn5sPnTqD712xGNOBJ+JzhTkBiQTRYjZx1/Wr+NxDO7jtv/t4fFcTVywrIz/TRnVrP49sb6RjwM0nz6jkG5cuxLxzD5laWB3GE9+O3QgESwojF4DZLWbu+fBqPvOP7Xz9kT38Z3sDly4tI9thZV9TH4/uaKB32Mvnzp3DFy+Yh9yk1hcM+PW0bdRpVgB7OvZgM9lYULAggivTZuHej57Cp/62jc8/tJOH3z7GRYtLybJb8Pg1rlub+KCV8eKkFHpQ+9L897Nn8IsXDvKPzUfw+pWFnl6QwdcuXsBHT6sgQ98vJVPT8CNx+V1kWDJihGNf5z40qcUVRICrVkxjQWkOd75QzX1v1uPTvZzKIiffumwhN6yfqY5sA7L8foakL8yoWOJ35jgiBXDt2hksmZbLz5+v5k9v1Aa55pRkcdtVi7l+7QwsZhN4lPjGeNlxuBKV6+NnVLJiRh53Pn+Q371aQ8B5W1CazY/fs5T3r5mO2SSgv4fMcG8UiN4YLiiIRbFcQghuPmcOa2bmc+cLB/n1y4eC5ywvnprDne9fztUrpmEyCRj26UYlnMscX6TiGBUhBF+9eAHrZxfyyxcO8ssXDwa5lk/P47fXr+SypfoRb90+ssK90UAdRnVmkzAFd08Mh8kk+N6VizljThG/fvlQcIaRELB6Rj63XrqQCxbpZ4ZqXmVU/OHlssQYFbvZHnczPYvZxE/eu5R3zSvmrldq+MkzKt9sEuqw7x+9ewlnz9d3aPT7lFEJlCtOOmVPxx5ybDlxd5C0W8z8+toVnLugmN+9cpgfPb1f3YNJqHr9wApOm10U/E6nJhmI8bJDbWNPxx7KnGXBFdbhyLCZ+cOHVvOvbce4+7VafviU4rKaBWfOLeYzZ89mTUVBkCtL0xj0JR4g3dO+h9l5s4Ppw3BkO6zc97G1/GPzEf74Ri3ff3IfADaziXMWFHPzOXNYVp4HqAPPnZrGgC8g9PGN5YLCBXEPC8p32vjHjeu4/816/rKhju/qYxE5DgvXnjJ9XKurR8JJK/QAs4qzuOv6Vbh9fpp6XDhtZkpyYs9azPJ7AQeD3kEl9FGHgQREaklR4mXg80uz+cMNa3B5/TT3usiyWyjOjtpDw+/DqflHNCq7O3ZjFmYWFSY+WnfJtFzu+9hahjw+Wvvc5DgsFGZFc3lUOkXzRhmVyA6WYclgTt6chFyrZuTz90+uY8Dto73fTV6GlXxn1L74fo8yKiN5vu27ybPnBccd4mHdrEIe/tR6+lxeOgc8FGTayM2M6iR+j0qn+KMjlcg6nJY1bcS9Wc6cW8yZc4vpHfLSNeShMMtGjiOKy+fBKSWtWmLxDQjHSKeMnb9oCucvmkL3oIeeYS9FWTayY7jcODWNxmijEsW1qHBRwq0jhBBctqyMy5aV0TXooXfYS0m2PbQrawB+t3peAS4R3/NdWpx4OwchBO9eWc67V5bT3u9mwO2jNMcRdJ7Cy5UltThCH9k2Ejk2oAzmB06ZwQdOmUFbn4tBj5+yXAcOayxXfKOiuAKpynOmn5OQy2wSfHh9BR9eX0Frn4thj5+yPEfQUQtxufR2GD8q8mpe9nXuG/FgIqvZxCfPnMUnzqikpc+F26tRmuswXOThJBf6AOwWM5VFCQ4IkRKn1w1kM+gdVOIQp4NNz55OgaNgVC6HdQQu3zBZulscMipR4tu+h7n5c0c9nhBUCFhZlOARel1kaRoakmHfsPo+kxm8IdHa3bGbhQULk9pSN8sedlhKTLn0Rq95ooxKpCe1tCi5fWByHNZY0Q2Wa1jPZY8giB17kt7ELDfTGmtMAvANx/HoQ5GKJjV2d+wOnh42GvKdtlgjGeRy6eIbNqYUVi6vXwnHtQuuTYqrwGmjIBGXVz2v7qBImdRGdLrxHPQOUtNdw/kzzk+KqzjbHuvUBMs1rCIVX3xB7BjuoGmwiesXJnegSTxHLYJLhnn0UVzH+o/R4+5JGMFGY8pIXF71vAZ8+lqLqDRRTXcNLr8rKS4hBGW5GaNeNxGcdIOxY4bPTZYeuw949XnPUYuY9nbuHdGbTxp6BwN1IpbiCgmilJK9nXtH9G6SRpRRUVzWCI9jf+f+pBv9iPAOkyVDRkVxhURq0DtIbW+tQeVy6V6bOzRgFjag3THcQctgizFc3iivDSIilWP9x+j39BvENaynU8KEPmwrjkM9h/BoHgPbhsagP2xacNjz2te5D4k0rM0rYxmd4lBtPjA4atzzknEGY/3Gc/lcZMmwvhWVJtrbqbgMqUMDkBZ67xBZuvgOegKCGMrD9rp7aRlsYWFB8ifrJERc8Q11sObBZvo9/TGDN+NCuFHxhhkVvVz1vfV4Na8xXLr4QlTD1zvYoe5DSKRB5VIiJSOMSkh8q7tUHnwsJyElRMAb9bvQZNgqUr0zB7gWFBpThyq/PBxpwKLKZVzbkKH8MkQ4AcE6NKjNOzWNwcCeAVHiG+AKTFueKFeWjGrvEGzz1d3VWE1WZuXNmjiXd5hMTLFcYXWYbc2mPKt84lwGICmhF0JcLISoFkLUCCG+Huf9Dwohdus/bwohloe9Vy+E2COE2CmE2GrkzRsCXwJB1B/YwW41N3k8e4zHwOvCKRNzBRr9WE+uigvda4NwoxKKVKq7DeTyhrgio6KoOjSkM8erwzCRMrRcrjhGxRLBZRKmEcc4kudSRsUn/XjCpz36Q3WYYckYcYwjafhUBDboHYwyKv4gV4GjYFz7z8fA68IpYTCY4tDTRGFtozyrPOmzl0flwhTpREHE85qdN3tc22PHwOciCxNDMQYsVK65+XNTkm8fD0YVeiGEGbgLuARYBFwnhIgeKawDzpJSLgN+ANwT9f45UsoVUso1nGjwJkpxRHoc8wqMEd9Yo2KO6GBgnEg5Y1JSYQas6yBWk5WK3IqJc+neKMSPVALeTZlzbMc8xkXY80pkmKdkTjHmXE7vUMioBFJtYZHKwa6DVORUjOvgihiE1WEorWeOEKk5eXOMObhCj/Z80o87fB64FvJ85+XPM0akdEGMNSqh52WIAwDKgI3gZR/sOmhM3wJlmIU5DpcfTWoc7DaQywAk49GvBWqklLVSSg/wEBBxoKOU8k0pZWDD703AiRGvJIMwjz7S8w11MOO8mwRGJSy0nJ49PamB2FER16OP7GBz8uYY493o3ijETxNVd1cb592EP6/wVFuYYTZOOFxxnldkpGJIpAcRqbboMRUpJdVd1cYJh28YZ2AbhChj6dN8HO45bGC5hnAKC37pxxWeO/d7GfIOcaTviLF1KCwhoxImvl2uLtqH2w2sQxdZwhLZBgH8XhoHGhn0DhrXDg1AMkI/DQjfuatBfy0RPgE8E/a/BJ4XQmwTQtw09ltMMRJ6vkqkjO3MwwkGYydJOMIWTAXE1xD4XGTJ+OKrSY1D3YeMa/RxjYryRj1+D/W99cZ6bQmMZZ+nj6bBJmMiPQjmlyFWfFuHWunz9BlYhy6cujBFtg0fR/uO4va7jSuXVwliBJfeNg73HEYiDTVgWSYrmtRUqi2YJvIamz4E1TZMFga8A1FGxWdsutcgJCP08dywuJt3CCHOQQn918JePl1KuQqV+rlZCPGuBJ+9SQixVQixtb29PYnbMgjeIexSYhGmmM7s03zUdNcY6yHKeMLhZ8g7xNG+o8Z6HAFBjEgF+Okc7qRjuCM1BixKpBr7GxnyDRnKFVOHukjV9tbikz7juMLrMCpSOdhlYJoNlCDq0VV0OzRcOLxDZAnFFZ1CNJzLN4xTL1e0cxMcTzHSqCSoQ0PHv0C1Q5MtNH4TLvRdBxEIZufNNobLACQj9A1A+AhQOdAUfZEQYhnwJ+AqKWXwlAwpZZP+uw14FJUKioGU8h4p5Rop5Zri4tgVcimDuw8BOC0ZkXlYqXGkpw6P5jGucbj6sEmw6OElEEwF1PTUKO/GqEbv6knojQbHAgzj6o2fugnvzEbVobsPZwLP19DxFFDlsqg0WvT4jeGC6Ool06IGJKNz9IFyGRaBufvI0tOD0TPNqrursQgLs3INmJkC4OojSx9ojdcOnVYn07JGShCMhas3OKgbj6s4oziptTBJwd0X5BrwDkSkiaq7q5mZM9OYFKxBSEbo3wbmCiEqhRA24FrgifALhBAzgEeAG6SUB8NedwohsgN/AxcCe426eUPgUvuAZ1uz6fP0qdf0Aa+DRouUqwcB5NiyQly6N2roQCyAqxcbYDfbw8plSRFXD1l6U4rkUiGzQDAn34CZKQDDPWRb1fL1Pnc4lxJfu9nOjGyD9gpx9ZJtU+fGRrQNvQ7z7HnBA98nztVDll0dEB40YGFtY1rWtOC9TJyrF6c1iiusbVTmVcZdtj8+rh6c+n1Hp0aru6qZmzc3YqPAiXH1kqVzRUfMB7sPGucA6FxOa1i5otJEhhllgzBqDUspfcAtwHPAfuCfUsoqIcSnhRCf1i/7DlAI/C5qGuUUYIMQYhewBXhKSvms4aWYCIZ7AMh35NPjVn8HrPPhnhpMwkRlbqUxXLpRyXPk0+3qDnFpXg73HCbDkmGcdzPcAxYHefa8MK5QiqPAUWCcdzPcg9WRR7Y1mx5Xj86lOlhtby3l2eVqFbARcPWQbc/BLMxhz8sMfi+Hew9TmVuZ1ErfpDDcQ54uvpHPS9Xh7LzZxk2fc/Xi1LmivdEAl2EY7iHLkRvFpdrG4Z7DzMk1yCiDEl97NJdqG3W9dcY5ADqX0xZrwDSfR3EZWa7hkGEOj4rcfjcN/Q3GTLk1EEn1CCnl08DTUa/dHfb3J4FPxvlcLbA8+vUTCrow5WcU0T7coV7ThaK+t47yrPLgnuYTxnAPWJ3kOwrodocJh9So761nZs5MA72bHnDkUhDBZQa/j7reOuOMFygDlpFHviM/xKWv6jSca7gHkyOfXDuRdaj5qO+tj7tp2rjh6iHTkY/D7IkxzHW9dZw34zzjuIZ7yM6ZCr4W+j39QS7N7+VIXyOnlp1qHJerl6zCChgkjMuM2++lyd3EVbOvGvHjY8JwD1mOPHCFcZkt9PiH6XZ3U5FTYRyXS+caIKIOm30DuP1uY6YSg5pN5h1UXERyHfH0IpHGtnkDkF4ZO9QFjjzyHQV0ufQj7XShr+s7YlzjABjugox88u3hHr1Z56qjMsfAxjGkcznyo7xsJYiGdrBhVYd5jrwIQdQ0H0f6jhjPlZGvDFhYpOLSvDQNNBnbwYa6Yg2YyUK35qXH3WOwAevCnllIpiUzrB2aadbcuP1uw8uVm1GCSZgi2vwRbQiJNK7Naxq4eijQ01vhXPU+5QUbVi7PEPhc5Mfl6jeWa0h9d5DLHeCyUudVUbuhbd4ApIW+twFyy4Opm8BUKQ040n/MWPHta4Kcspg0kVtA00CTsUalvxmyy8iz50U0+h40ut3dxgpHXzPklFFgL4gQ+mb8xotUXzPkTFXiG8Z1VGjGihTodTg1Mv1ltlCvH3RtWLk0P/S3QE4ZhRmFdA7rcxlMVuqk21guzyC4ezHnqLbR6QpwWajTho3lGmwHzUdmznQcZkdYuSzU+XWhN6p/9avzlAvy1SByBJdPpXEME99+NRelMK8yistMvVeN5cTb3vl4Ii30YULv9ruDU6WaLWbcmicl4hsQek1qYLJyxGI1PtzTBTEidWO2Um9ROWVjuZoge2qM51unty5DBXGgNWjAwlNSdcJvLJe7H9x9yoA5Ig1YvVDrHgwTqcF2kH7ILqPQURghvgGjYphI9ekHzOdMizQqZiv1ulExbDBbF0SRq3O5QoJYpw1jNVmZmjXVGK4+dVKTNac8yoCZqfcPkmPLMW5MSq/DnLxZWE3WSGPpG6DMWXZCzbiBtNBD7zEl9HZ1NFiXq0t1MKuadWCoSPUcg1y13bEmNXrdvapxWC3GcnmHlVHJnU6+I59B7yAev0d1sEC5jBKpoS7w9EPe9GDqJhAV1esjQIaJVO8xJYi55bHia1ZzLg3zpLr1c0r1OowwYMJvrEgFuPJmRHn0FurwGitS3fXqd255lFExUyc9xopUkGu64gqPVDQ3M3NmGrOlQzhXXhSX2UqdNkxlbqVxA+c6l8ifQYGjIOJ51fsHT7i0DbzThX6wUw1a5s0MdqRuV7cuvkoQDXto3fXgG4aSheTZ88K4zNTbFJdhnlR7NSAjuAIGrM5qNVak2tQpPJQspMBegFfzBucV15lNxopU2wGdaxH5jnx63b34NJ/qzGYoc5YZN7unbb/OtTAm/VVnksaKVFgdxoiv8FORW2GcSIVzxTEqhopU23415bBoHgUZBVGRisEpvbYDYMmAvIqo6EGlpAwtV/t+yCwEZ3EElzRbqPMPnXADsfBOF/rmHer31BVMcapT3VuGWlQYa7WQY80yUKQCHWwRUzJ1rsGWoPiWZZQY50kFRWoRpc5SAFqHWoPRw8zscuNEqjVUrsCc8tbBVj0qslCRY6RIVelcCyjJLEEi6Rju0D16A6fBgnpeJgsUzqXUWcqwb1jNpTdZqDcZPNjWtg9sWZA7naKMInrcPUEDVm/SjB0natsHWVMgs4BCR2HQgElhpl74jK3D1irIrwSrI8LL9prMHJNGG5UqKJ4HJhOFjkLVLoABk4l2jC7XPiheCEKoOhxWddhuNjOEPy30JxyObgYElC0P7qzYNNAUTHFUOMuME6n6jWBxwJTFwbnyTYNNQaNSYdT8eYAjG8CRC4Wzo8qlUlKVRkUOAEc2QvZUyC4LRglNg01Bo1Jp5KBU/UYomgeOXKY5VX01DjQihYk6i8lY4TiyEUqXgcUWKtdAE15hosFs8BhH/UaYthqECJ6b2j7UzoCAdhPGjRNJqbjKTwGgJLMkaMDaTIIhYWSqUoOjb0H5miBXl6sLr9/LMZPEbySXzwPH3g6WqzizmPahdqSU1JtV/zWsDt0D0LwzolytQ60A1FlMxnIZiHe20B94CmasB0cuObYcnFZnmCBaqMg0YFtdUB3s0HOKy+qgOLMYszDTNNCkPCmrlQqnQakUvw8OvQiV7wKTOUqkBA1WCxVGHYbgdUHtKzD7HBAiZMAGmhgQGu0WCxVGGRV3Pxx5E2ap8z7LskIGrA0fQyaTcR1ssAMatqpyQUQdHpMefEIYx9VzVHmjOld5tno2x/qPUS/12T1GefTtB6D3KMw6O5YrMOhrVLkat8FQZ/B5lWeXI5E0DjRSZ1JbcxhmmI9sAO9gBJfL76J9uD00IcCoOjz8stqEMOx5dbm6GPQOUmfWhT6doz+B0LRTdbBFVwLq3MapWVNpGmxiQPPRZrEwK7PUGK4jG6GrFpa9HwCLyUKps5SmwSba/S4GTSZmGSX0NS/CQAssVVxOq5Nce64SKd8gPiGoNCp6OPBftVhq6TUAFGYUYjVZaRpool6f0jbLiIMyAPb8S41x6HUYHqnU+9XhD7OM6sw7H1CDvnq5pjpDQl+vqa12DROOHX8HBCx+D0DwYJFj/ceokzpXnkFc2/+qVsAuujqSq+8YdRhsVLbfD9ZMWHAZEBp/Otp/NDhDyjCjsv2vkJEPc86P4DrWf4w6k4ZZYsyBLQGu7DKYeUYMV71ZkokpmJo9kWDQWvH/Y5ASXv0x2HNgRehQ4mnOaTQONFKfp3JulRkGPDAp4ZXbIbMo2MFACVVDfwO1FrXPfaURh3JoGrx6O+SUw/xLgi9PdU6lYaCBOosqT2WmAUbF74XXfgqFc6HyLABMwsTULJ3Lq7y2SiOiB+8wvHEnlK1QKQ7AYXFQlFFEw0ADuYF50kZED64+ePPXUHEmlKij9PLseWRYMmgYaMCtKaNiiEgNdsKmu2HexZCvUlylmaVYTBaO9h/FLN1YpDRGpHobYeu9sPhqyFLpocAxd8f6j9GBh0yJMXv3dB6GXQ/Byg+BQ20TEB09FGvCmL17WvZC1WNw2mfBqg7zDhqVvqPUCz/TsRizd8+xLVDzApxzq1r5DczICXHVmSQV2E6YU6XC8c706Pf+Bw4+C+/6ispl65idN5u63jqqh1sAqMwwYBfNrX9RHv053wRbaLB1Tt4cDnUf4rDLQKPy1m+geRec/93QYcVhXHUeNUWwwohI5bWfQsdBuOA2taGTjtm5sxWXtxeLlJRnGCAcL92mplZe+AMI60Sz82ZzsPsgdb5+MjWNEn2G0YTw3DfUvPYLvh98SQgRqkP/ICU+/8RFSkp46kvgGVDPS4fZZKY8q5wjfUeo9w9R7tcmfjiMpsGTn1dRyrnfCr6cac2kJKOE+r566qWLCr+cuEj5ffDEZ8Fsg7NDp44WOgpxWp3U9dZRJz1UakYcQuOGJ26BjDw444vBl8uyyrAIC0f6jlAnvFRIAyYeeAbhic9BVimc+pngywEjrLj8VJ6gvvM7T+gbt8Hjt0D52ogHBuqQZ5/m49mOnUqkbPkT46p7A579ugopV38s4q2FhQsZ8g3xau8BnJpGsb4j47hx8Hl48fuw6KpgyiGcq324nU2DRyjx+cia6NF3VY/C63fAig/BgktjuOr76tnlaqXc62PCftSOf8Cm38G6T6txhzAsKljEoe5DHPB0Uen1IqR/Ylyb/6BSKe/6SjByCGBhwUL2d+6nxtdHpderhHoieOMXsO8xOO87wcghgEWFi9jdvptD/gEqvRMsk5Tw8m3KE734x5BfEcO1q30XNf4hKn0TLJOUqr0f2QiX3wnZIYdCCBEsV510U6lNjEoZry9A0w648reQGZodZzFZmFcwj22t2ziCb+JGxe+Dx/5HjXG8+/dgD/VVp9VJRU4Fbza9SbPQqDTCqKQA7yyhr98If71aha7X/iMYfgWwsnglAsGmngMscnuwSt/4uWpfhQfeDwWz4D1/jPB6AVaVrAJgU+8hlrndCG0CXNXPwMMfhCmLVaOP8spWTVFcm/vrWO72gN8zfq49/4Z/fwKmr4PLfh7z9uopSiC3DB5juds9Ma7tf4PHb1aDhxf8IObtlSUr8WpetrtaWe7yBI8uHBc23Q3PfBXmXwZnfyPm7VVTVtHv7afK08Uytzt4KtiYIaUyki//QBnk0z4Xy1Wyivbhdur9g4prvJASXvo+bPglrP4orPlEzCUrp6zkSN8R2qSH5Z4J1J/mh2e+Bm//UaVRll8by1Wykv1d++nHzzLvBIyK3wtPfhZ2PQBnfxMWXh5zyaqSVexs34kXyXL/BGTO54ZHPgn7HocLfwizz425ZGXJSra2qg17l2sT8Oi9rtBaEYPxzhB6KWHbffC3dysv42PPQFZsSmGKcwqnTT0NgEsHB9VMj/Fwbbob/vYe5T195MkIbyOAitwKlhWrnRYvHRhSueHxcL1xJzx4HZQsgg8/HsyJhmNRwaLgtqmXDIyzXJoGL/8Q/vMJmL4WPvQfsMYuTlpVsio4++bSwSGVmhgr/D549psqLJ99Dlz3EFhidxA9Y9oZwXUOl4z3efk8yjN89mtK5K+5L7jRXDjOmX4O2fr+4xcNDo2PyzsMj35K1ePSa+Dqu2McAIDzZ56Pw6zyzRf294/PgLkH4J83hET+sl/GOAAAF1VchEVYMCM4t38cbRDUrqwPfAC2/AHW3xLXKANcVnkZAoEdE+8aHEe7ADUj6m/vVpHXWV+Hs74a97LLZynxz8bM+uHh8XH1NcN9l6kI9oLb4LRb4l52xewrACjCwqrxGsueo3DvxXD/FerZGQ0p5Qn3s3r1amkY+lul/OdHpPxujpT3XyXlQMeIl/e4euSrB/4j/d/NkXLrvWPj6mmQ8u/XKK4HrpNyuHfEyzuHO+Xrex+Q2ndzpNz9r7FxddVJed8ViutfH5fSPTji5a2DrXLjzvvU9dXPjo2r/aCUf75Iffaxz0jpdY14eVN/k9y89W51fd2GsXG17JXyD2epzz79VSl9nhEvP9p7VG7f/Bt1fdOusXE1bpfyrvXqsy98V0q/b8TLD/cclrs23KGu7zw8Nq4jm6T89Wopv5sr5as/ldLvH/Hy6q5qWfXqDxRXf9vYuA6/KuX/Wybl9/Kk3PgbKTVtxMv3deyT1S/eqrg8w2Pjqn5Oyl8slPL7hVK+/edRL9/dtlsefvpLUn4vf9T7ikHV41L+bI6UtxVLufPBUS/f3rpdHnn801L+eMbYeDRNyl3/lPInFVL+sEzKqsdG/ciW5i2y4d8fkfLOxWPn2na/lLdPl/L2cin3PTm2z4cB2CoTaOqJOXJgBDxDsO1eePUnypM67ztw+hfjelDhyLXnclbFheof/VCSUeEegM13w8ZfqZD+oh+rnPIoXAWOAs6coYeC+qEko8LVC2/dBW/+BoQZLv+lyv+PMohWkllCybTTx8Y11KXKtOn3ynu/+m4Vko/CVZZVRlnZ2rFxDbQp73PLH9UA+fvuhSXvGfVj03OmM71YP/IgsB3zaOhrUjnyrfeCsxiufTBmrCEeZuXOgsJF6p9k20bPUTVwveMfkDsdbngkbvgfjXn58yBwApirNzhTZkR0Hlbtfc8/Vcrwo0/BzNNG/djCwoUQmFbp6gFrEoP17dUqMtn/BBQvgPf/DcpXj/qxpcVLIWeGGhj2DIA9iUHtlr2K6+AzahHbDY9A6dJRP7ayZCVkTVP1p2mj9kcAGrerwf/aV2DaGrj6d1A8+nGRp5SeApmlybcLgKOb4KUfqHUAM8+Aq36jnlsKkJTQCyEuBn4FmIE/SSl/EvW+0N+/FBgCPiql3J7MZw1H52HY/U94+08w1KE61SU/g6IxHO1lc6rl76OJVEcN7Pib+hnqhHmXqAGvgjHMRQ7M+hlNpNr2q3B1x9/VtYuugotuh9wxTF/MyFO/R2qMUkLLHlWmnQ+qzrj0GpWfzB7DzKBkyiUlNG1XufjdD4PPpaa7nn8bOAvHwTXC85JSTY/b8Vc1zqD5YM3H4Nxvh+olGQSuHYlL0+Dom6pce/+jDOP6m1Xu3z6GQXdHgKtnBC4/1L2unlfVY2q2yxlfUimNOKm1hAhvG9kJhN7vUwK4/a9qDYU1U+XIz/gCWMYwwB8o13BPYqH3e+HQC4rr4DNgz4Xzv6dSQ2OZKpmRD0i1E2mi5+zzKI7tf1XrUDIKdGftU3HTeCNyefpVPZkTSKvXpepu231Q/wY4S5SztuqjyRmicWJUoRdCmIG7gAtQB4W/LYR4Qkq5L+yyS4C5+s864PfAuiQ/aww8g3DvJWp6IcDcC9WUqxnrR/VAYyCEegA9R9X/fq8S8q5a5cm07Iba16DrsPKq512kOtf0U8Z+31aHms8f4PJ5dK7Diqt5F9S9pjZFM1mV53nGl2DqirFzOXLVd/QGuNwq5xnk2qnK1XsMzHZYeAW868sxs0KSgrMYEGrHziBXO3TWQPtBNVui9lW1la0lAxa/G878XygaxxFsWboBCtSh1wWDbSGuxm2qDgdaweqEZR+AM78UMwMluXKVRHENq2ik85DianhbcQ11que6+qNKCMdikIPlKg5xla9RUepAq16uamjYokR+uFuJ57pPwemfTyzUyZSr95jyYL06V8chxXVss5pF5u5VG3qd9lk1kOwsGke5Alxqi3A8g4qrvRo6qpWnW79BORlZU+BdX4X1n9FFewLlcuSq7+xvUVztBxTXkY2qvNlT4ZxvqXqMM9Y1OldRiCu/QhmXvmY1Dbm9Whn/I2+phX+5M+D878PaG5VjmWIIOco0MSHEeuB7UsqL9P+/ASCl/HHYNX8AXpVSPqj/Xw2cDVSM9tl4WLNmjdy6detIl8TH4zerQclFV0PuBFd//udGFQLbc1XjDoctC2aergYKF797fB0rHA9eB9VPK2EIHHgdgD1HLd4JcI2nY4XjvsuVJ2HLVt5HOBx5agrj7HNUHcYZRB4T7jlbCbotK3ZQNrNQ5zpXRSdh6xnGhd+sVgJodarl8OFwlsCss2D2ecp4jcWrjoaUcOdCJRbWDCUQ4cgqVbOE5pyvVoWGrZ0YM/xeuGO2Gvg125VAhCOnXOc6D+ZfGlwwNC54BuFns9UsKbNVRVfhyJuhuOZeCHMvijs4njSGuuDneoQtzOCPmlmUX6m45l2k6nEii516G+CXS1SELkTsLLDCOWrrhHkXq3Y/kc3+2g/CXaeoqEpK0KIGZosX6FwXqUWGBnvwQohtUso18d5LJnUzDTgW9n8Dymsf7ZppSX7WOFx1l3HfdeEPlID73EpcM/JVAyyaq3KtRj6kS36qcnOaT62gzSxQHkHRPMiZZizXFb9SaS0pVXoks1CVq3i+Wtpt5Kq+q+9W4yTCpHgyC1U5i+crT81Irvfdq9IXJmuoXAWzFZez2DguIeADf1crPy12fbvaojCuCRricJitasbRXn2GU2ahah+FcxTXRA1xOGxOuO4B2P9f9be+Da/imjc+bzoRMgvgA/+AQ88roxvkmqv611hSaaMhtxzef7+KVO3ZiiurJMQ1Hs89EYrnqanURzep780sVE5G0VzVlyfiYEwQyXj01wAXSXUAOEKIG4C1UsrPhl3zFPBjKeUG/f+XgK8Cs0b7bNh33ATcBDBjxozVR44cMaB4aaSRRhrvDIzk0SfjKjYA4ZttlANNSV6TzGcBkFLeI6VcI6VcU1xswNYDaaSRRhppAMkJ/dvAXCFEpRDCBlwLPBF1zRPAh4XCqUCvlLI5yc+mkUYaaaSRQoyao5dS+oQQtwDPoaZI/kVKWSWE+LT+/t3A06iplTWo6ZUfG+mzKSlJGmmkkUYacTFqjv54QAjRDow3SV8EdBh4O0YhfV9jQ/q+xob0fY0NJ+N9zZRSxs17n5BCPxEIIbYmGpA4nkjf19iQvq+xIX1fY8M77b7eGZuapZFGGmm8g5EW+jTSSCONkxwno9Dfc7xvIAHS9zU2pO9rbEjf19jwjrqvky5Hn0YaaaSRRiRORo8+jTTSSCONMJw0Qi+EuFgIUS2EqBFCfH30T6TsPqYLIV4RQuwXQlQJIT6vv/49IUSjEGKn/jP6BujG31u9EGKPzr9Vf61ACPGCEOKQ/tvATU2Suqf5YXWyUwjRJ4T4wvGoLyHEX4QQbUKIvWGvJawfIcQ39PZWLYS46Djc2x1CiANCiN1CiEeFEHn66xVCiOGwurt7ku8r4bObrDpLcF8Ph91TvRBip/76pNTXCNqQ+jaW6ESS/0s/qMVYh1F769iAXcCi43QvZcAq/e9s4CCwCPge8OXjXE/1QFHUaz8Dvq7//XXgp8f5ObYAM49HfQHvAlYBe0erH/2Z7gLsQKXe/syTfG8XAhb975+G3VtF+HXHoc7iPrvJrLN49xX1/i+A70xmfY2gDSlvYyeLR78WqJFS1kopPcBDwFXH40aklM1SP3RFStkP7Eft4nmi4irgfv3v+4Grj9+tcB5wWEp5XHa0k1K+DnRFvZyofq4CHpJSuqWUdahV4Wsn896klM9LGTzBfhNqL6lJRYI6S4RJq7OR7ksIIYD3Aw+mgnuEe0qkDSlvYyeL0CfaJvm4QghRAawENusv3aKH2X+Z7BSJDgk8L4TYJtRuoQBTpNqXCP137Knpk4driex8x7u+IHH9nGht7uPAM2H/VwohdgghXhNCnHkc7ifesztR6uxMoFVKeSjstUmtryhtSHkbO1mEPt5m48d1OpEQIgv4D/AFKWUf6tSt2cAKoBkVOk42TpdSrkKdCHazEOJdx+Ee4kKoTe+uBP6lv3Qi1NdIOGHanBDiVsAH/EN/qRmYIaVcCXwJeEAIYeDG66Mi0bM7UersOiIdikmtrzjakPDSOK+Nq75OFqFPejvkyYAQwop6kP+QUj4CIKVslVL6pZQa8EdSGOYngpSySf/dBjyq30OrEKJMv+8yoG2y70vHJcB2KWWrfo/Hvb50JKqfE6LNCSE+AlwOfFDqiV091O/U/96Gyu3Om6x7GuHZHfc6E0JYgPcADwdem8z6iqcNTEIbO1mE/oTZDlnP//0Z2C+lvDPs9bKwy94N7I3+bIrvyymEyA78jRrI24uqp4/ol30EeHwy7ysMEV7W8a6vMCSqnyeAa4UQdiFEJeq85C2TeWNCiIuBrwFXSimHwl4vFuq8ZoQQs/R7q53E+0r07I57nQHnAweklA2BFyarvhJpA5PRxlI90jxZP6htkg+irPGtx/E+zkCFV7uBnfrPpcDfgD36608AZZN8X7NQI/i7gKpAHQGFwEvAIf13wXGos0ygE8gNe23S6wtlaJoBL8qb+sRI9QPcqre3auCS43BvNagcbqCd3a1f+179Ge8CtgNXTPJ9JXx2k1Vn8e5Lf/0+4NNR105KfY2gDSlvY+mVsWmkkUYaJzlOltRNGmmkkUYaCZAW+jTSSCONkxxpoU8jjTTSOMmRFvo00kgjjZMcaaFPI4000jjJkRb6NN5xEELkCSE+M8L7GfpSePMEeZYKIe6byHekkYYRSAt9Gu9E5AEJhR61b8wjUkr/REiklHuAciHEjIl8TxppTBRpoU/jnYifALP1vcfviPP+B9FXJwohzta9+38KIQ4KIX4ihPigEGKLUHv7z9avu0YIsVcIsUsI8XrYdz2JWqmdRhrHDekFU2m846DvHPhfKeWSOO/ZgKNSylL9/7OBx4CFqG1va4E/SSm/qx8cUSml/IIQYg9wsZSyUQiRJ6Xs0T9/Omqv8StSXrA00kiAtEefRhqRKAJ6ol57W6q9xN2o5ejP66/vQR1aAbARuE8IcSPqAJUA2oCpKbvbNNJIAmmhTyONSAwDjqjX3GF/a2H/a4AFQEr5aeBbqN0GdwohCvVrHPp3ppHGcUNa6NN4J6IfdZRbDKSU3YBZCBEt9iNCCDFbSrlZSvkdoIPQ9rLzOH47b6aRBpAW+jTegZBq7/GN+uBpvMHY51E7DY4Fd+iDs3uB11E7IQKcAzw1/rtNI42JIz0Ym0YaURBCrAS+JKW8YYLfYwdeA86QobNd00hj0pH26NNIIwpSyh3AKxNdMAXMQM24SYt8GscVaY8+jTTSSOMkR9qjTyONNNI4yZEW+jTSSCONkxxpoU8jjTTSOMmRFvo00kgjjZMcaaFPI4000jjJkRb6NNJII42THP8fcR+kWjLHRykAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(6, 2))\n", + "plt.plot(runner.mon['ts'], runner.mon['IK.n'], label='n')\n", + "plt.plot(runner.mon['ts'], runner.mon['INa.p'], label='m')\n", + "plt.plot(runner.mon['ts'], runner.mon['INa.q'], label='h')\n", + "plt.xlabel('t (ms)')\n", + "plt.legend()\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "By combining different ion channels, we can get different types of conductance-based neuron models easily and straightforwardly. To see all predifined channel models in BrainPy, please click [here](../apis/dyn.html)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" + "pygments_lexer": "ipython3", + "version": "3.9.7" } }, "nbformat": 4, - "nbformat_minor": 0 -} \ No newline at end of file + "nbformat_minor": 1 +} diff --git a/docs/tutorial_building/customize_neuron_models.ipynb b/docs/tutorial_building/customize_neuron_models.ipynb index 28a3b9d77..0f139118c 100644 --- a/docs/tutorial_building/customize_neuron_models.ipynb +++ b/docs/tutorial_building/customize_neuron_models.ipynb @@ -545,20 +545,24 @@ "outputs": [ { "data": { - "text/plain": " 0%| | 0/2000 [00:00", - "image/png": 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\n" + "image/png": 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\n", 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\n" 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\n", 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