diff --git a/content/Connectivity_Heatmaps.ipynb b/content/Connectivity_Heatmaps.ipynb
new file mode 100644
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--- /dev/null
+++ b/content/Connectivity_Heatmaps.ipynb
@@ -0,0 +1,491 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "b639813f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "from scipy import signal\n",
+    "from scipy.signal import welch\n",
+    "from fooof import FOOOF"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "016747eb",
+   "metadata": {},
+   "source": [
+    "# Jansen-Rit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0652ff64",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sigm(nu_max,v0,r,v):\n",
+    "  action_potential = 2*nu_max/(1+math.exp(r*(v0-v)))\n",
+    "  return action_potential"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a8b9047c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameter settings\n",
+    "A = 3.25\n",
+    "B = 22\n",
+    "C1 = 135\n",
+    "C2 = 0.8*C1\n",
+    "v0 = 6         \n",
+    "a = 100        \n",
+    "b = 50         \n",
+    "nu_max = 2.5   \n",
+    "r = 0.56      \n",
+    "\n",
+    "# Varying C3 (P-->I) and C4 (I-->P)\n",
+    "C3_tot = np.arange(0.100,0.699, 0.01) \n",
+    "C4_tot = np.arange(0.100,0.699, 0.01)\n",
+    "\n",
+    "# Simulation settings\n",
+    "start = 0.0\n",
+    "stim_time = 10\n",
+    "dt = 0.001\n",
+    "time_array = np.arange(start=start, stop=stim_time, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "noise = np.random.uniform(120,320,vec_len)\n",
+    "# We are using unifrom noise but could also use normal noise with Euler-Maruyama method\n",
+    "#noise = A*a*math.sqrt(dt)*math.sqrt(22)*np.random.normal(0, 1, vec_len) + dt*220*A*a\n",
+    "\n",
+    "# Output Initialization\n",
+    "y = np.zeros((6,vec_len))\n",
+    "\n",
+    "final_WELCH = np.zeros((len(C3_tot), len(C4_tot)))\n",
+    "\n",
+    "for ind2, C3_prop in enumerate(C3_tot):\n",
+    "  for ind, C4_prop in enumerate(C4_tot):\n",
+    "    C3 = C3_prop*C1\n",
+    "    C4 = C4_prop*C1\n",
+    "    for i in range (1,vec_len):\n",
+    "      y[0,i] = y[0,i-1] + y[3,i-1]*dt\n",
+    "      y[1,i] = y[1,i-1] + y[4,i-1]*dt\n",
+    "      y[2,i] = y[2,i-1] + y[5,i-1]*dt\n",
+    "      y[3,i] = y[3,i-1] + dt * (A*a*(sigm(nu_max,v0,r,(y[1,i-1]-y[2,i-1]))) - (2*a*y[3,i-1]) - (a**(2)*y[0,i-1]))\n",
+    "      y[4,i] = y[4,i-1] + dt * (A*a*(noise[i-1] + (C2*sigm(nu_max,v0,r,(C1*y[0,i-1])))) - (2*a*y[4,i-1]) - (a**(2)*y[1,i-1]))\n",
+    "      y[5,i] = y[5,i-1] + dt * (B*b*(C4*sigm(nu_max,v0,r,(C3*y[0,i-1]))) - (2*b*y[5,i-1]) - (b**(2)*y[2,i-1]))\n",
+    "\n",
+    "    out = y[1,:]-y[2,:]\n",
+    "\n",
+    "    if out[2000] == out[2005]:\n",
+    "      freqWelch = 0\n",
+    "    else:\n",
+    "      output = out[1000:] \n",
+    "      # Welch method\n",
+    "      freqsW,ps_vPN = welch(output,fs=1000, noverlap = 125, nperseg=1000)\n",
+    "      fm = FOOOF(max_n_peaks=2, min_peak_height=1, aperiodic_mode='knee')\n",
+    "      fm.fit(freqsW, ps_vPN, [1,50])\n",
+    "      cfs = fm.get_params('peak_params', 'CF')\n",
+    "      if np.isnan(cfs).any():\n",
+    "        final_WELCH[ind, ind2] = 0\n",
+    "      elif cfs.shape ==():\n",
+    "        final_WELCH[ind, ind2] = cfs\n",
+    "      else:\n",
+    "        pws = fm.get_params('peak_params', 'PW')\n",
+    "        final_WELCH[ind, ind2] = cfs[np.argmax(pws)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "159141ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Plotting JR result\n",
+    "data2 = pd.DataFrame(np.transpose(final_WELCH), index = np.round(C3_tot,3), columns=np.round(C4_tot,3))\n",
+    "ax = sns.heatmap(data2, vmax=11, cbar_kws={'label': 'Dominant Frequency (Hz)'} )\n",
+    "plt.xlabel('C4')\n",
+    "plt.ylabel('C3')\n",
+    "ax.invert_yaxis()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "733ecb89",
+   "metadata": {},
+   "source": [
+    "# Liley-Wright"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2c4a041",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def dynamics(p,X):\n",
+    "    dX = np.zeros((18,1))\n",
+    "\n",
+    "    # Calculate synaptic reversal potentials\n",
+    "    psi_ee=(p.h_ee_eq-X[0])/abs(p.h_ee_eq-p.h_e_r)\n",
+    "    psi_ie=(p.h_ie_eq-X[0])/abs(p.h_ie_eq-p.h_e_r)\n",
+    "    psi_ei=(p.h_ei_eq-X[1])/abs(p.h_ei_eq-p.h_i_r)\n",
+    "    psi_ii=(p.h_ii_eq-X[1])/abs(p.h_ii_eq-p.h_i_r)\n",
+    "\n",
+    "    # Calculate synaptic inputs A_jk \n",
+    "    A_ee=p.N_ee_b*S_e(p,X[0])+X[10]+p.p_ee\n",
+    "    A_ei=p.N_ei_b*S_e(p,X[0])+X[12]+p.p_ei\n",
+    "    A_ie=p.N_ie_b*S_i(p,X[1])\n",
+    "    A_ii=p.N_ii_b*S_i(p,X[1])   \n",
+    "\n",
+    "    # Calculate state vector\n",
+    "    dX[0] = (1/p.tau_e)*(p.h_e_r-X[0]+psi_ee*X[2]+psi_ie*X[6]) # V_e\n",
+    "    dX[1] = (1/p.tau_i)*(p.h_i_r-X[1]+psi_ei*X[4]+psi_ii*X[8]) # V_i\n",
+    "    dX[2] = X[3] # I_ee\n",
+    "    dX[3] = -(p.gamma_ee+p.gamma_ee_tilde)*X[3]     -p.gamma_ee*p.gamma_ee_tilde*X[2]   +p.gamma_ee_tilde*math.exp(p.gamma_ee/p.gamma_ee)*X[14]*A_ee# J_ee\n",
+    "    dX[4] = X[5] # I_ei\n",
+    "    dX[5] = -(p.gamma_ei+p.gamma_ei_tilde)*X[5]     -p.gamma_ei*p.gamma_ei_tilde*X[4]   +p.gamma_ei_tilde*math.exp(p.gamma_ei/p.gamma_ei)*X[15]*A_ei# J_ei\n",
+    "    dX[6] = X[7] # I_ie\n",
+    "    dX[7] = -(p.gamma_ie+p.gamma_ie_tilde)*X[7]     -p.gamma_ie*p.gamma_ie_tilde*X[6]   +p.gamma_ie_tilde*math.exp(p.gamma_ie/p.gamma_ie)*X[16]*A_ie# J_ie\n",
+    "    dX[8] = X[9] # I_ii\n",
+    "    dX[9] = -(p.gamma_ii+p.gamma_ii_tilde)*X[9]  -p.gamma_ii*p.gamma_ii_tilde*X[8]   +p.gamma_ii_tilde*math.exp(p.gamma_ii/p.gamma_ii)*X[17]*A_ii# J_ii% J_ii\n",
+    "    dX[10] = X[11] #theta_ee\n",
+    "    dX[11] = -2*p.nu_ee*p.Lambda_ee*X[11]           -p.nu_ee**(2)*p.Lambda_ee**(2)*X[10]     +p.nu_ee**(2)*p.Lambda_ee**(2)*p.N_ee_a*S_e(p,X[0])#d_theta_ee\n",
+    "    dX[12] = X[13]#theta_ei\n",
+    "    dX[13] = -2*p.nu_ei*p.Lambda_ei*X[13]           -p.nu_ei**(2)*p.Lambda_ei**(2)*X[12]+p.nu_ei**(2)*p.Lambda_ei**(2)*p.N_ei_a*S_e(p,X[0])#d_theta_ei   \n",
+    "    dX[14] = p.Gamma_ee-X[14]  # Gamma_ee\n",
+    "    dX[15] = p.Gamma_ei-X[15]  # Gamma_ei   \n",
+    "    dX[16] = p.Gamma_ie-X[16] # Gamma_ie \n",
+    "    dX[17] = p.Gamma_ee-X[17]  # Gamma_ii   \n",
+    "\n",
+    "    return dX\n",
+    "    \n",
+    "def S_e(t,v):   \n",
+    "    p = t\n",
+    "    spikerate = p.S_e_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_e)/p.sigma_e))\n",
+    "    return spikerate\n",
+    "\n",
+    "def S_i(t,v):\n",
+    "    p=t\n",
+    "    spikerate = p.S_i_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_i)/p.sigma_i))\n",
+    "    return spikerate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1c66769e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Standard Liley-Wright parameters from \n",
+    "class p:\n",
+    "\n",
+    "  S_e_max = 0.5\n",
+    "  S_i_max = 0.5\n",
+    "  h_e_r = -70\n",
+    "  h_i_r = -70\n",
+    "  mu_e = -50\n",
+    "  mu_i = -50\n",
+    "  sigma_e = 5\n",
+    "  sigma_i = 5\n",
+    "  tau_e = 94\n",
+    "  tau_i = 42\n",
+    "  h_ee_eq = 45\n",
+    "  h_ei_eq = 45\n",
+    "  h_ie_eq = -90\n",
+    "  h_ii_eq = -90\n",
+    "  Gamma_ee = 0.71\n",
+    "  Gamma_ei = 0.71\n",
+    "  Gamma_ie = 0.71\n",
+    "  Gamma_ii = 0.71\n",
+    "  gamma_ee = 0.3\n",
+    "  gamma_ei = 0.3\n",
+    "  gamma_ie = 0.065\n",
+    "  gamma_ii = 0.065\n",
+    "  p_ee = 3.460\n",
+    "  p_ee_sd = 1.000\n",
+    "  p_ei = 5.070\n",
+    "  p_ei_sd = 0\n",
+    "  p_ie = 0\n",
+    "  p_ii = 0\n",
+    "  N_ei_b = 3000 \n",
+    "  N_ee_b = 3000\n",
+    "  N_ie_b = 500 \n",
+    "  N_ii_b = 500\n",
+    "  \n",
+    "  # Varying N_ei and N_ie\n",
+    "  N_ei_tot = np.arange(1000,5100,1000)\n",
+    "  N_ie_tot = np.arange(100,1100, 500)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a0c231c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sim_time=50       \n",
+    "dt = 1e-4\n",
+    "steps= 1/dt           \n",
+    "white_noise=1         \n",
+    "\n",
+    "p.v_e_equil = p.h_e_r\n",
+    "p.v_i_equil = p.h_i_r\n",
+    "\n",
+    "h = 1000/steps        \n",
+    "T = sim_time*10**3 \n",
+    "N = T/h-1#\n",
+    " \n",
+    "final_connection = np.zeros((len(p.N_ei_tot), len(p.N_ie_tot)))\n",
+    "\n",
+    "for ind2, p.N_ei_b in enumerate(p.N_ei_tot):\n",
+    "  for ind, p.N_ie_b in enumerate(p.N_ie_tot):\n",
+    "\n",
+    "    X = np.zeros((18,int(N)))\n",
+    "    X[0,0] =   p.v_e_equil  \n",
+    "    X[1,0] =   p.v_i_equil   \n",
+    "    X[2,0] =   math.exp(1)/p.gamma_ee*p.Gamma_ee*(p.N_ee_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ee)    \n",
+    "    X[4,0] =   math.exp(1)/p.gamma_ei*p.Gamma_ei*(p.N_ei_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ei)\n",
+    "    X[6,0] =   math.exp(1)/p.gamma_ie*p.Gamma_ie*(p.N_ie_b*S_i(p,p.v_i_equil))#\n",
+    "    X[8,0] =   math.exp(1)/p.gamma_ii*p.Gamma_ii*(p.N_ii_b*S_i(p,p.v_i_equil))#\n",
+    "    \n",
+    "    for n in range (0,int(N-1)):\n",
+    "        noise = np.zeros((18,1))\n",
+    "        if (white_noise==1):\n",
+    "          noise[3]= p.gamma_ee*math.exp(p.gamma_ee/p.gamma_ee)*p.Gamma_ee*p.p_ee_sd*np.random.randn(1,1)\n",
+    "        X[:,n+1] = X[:,n] + ((h*dynamics(p,X[:,n])+math.sqrt(h)*noise).flatten())\n",
+    "    EEG=-X[0,:]\t\n",
+    "\n",
+    "    if np.round(EEG[2000],6) == np.round(EEG[2005],6):\n",
+    "      final_connection[ind2,ind] = 0\n",
+    "    else:\n",
+    "      output = EEG[1000:]\n",
+    "      X = signal.resample(output, 5000)\n",
+    "      freqs_new,ps_vPN_new = welch(X,fs=100, noverlap = 125, nperseg=1000)\n",
+    "      fm = FOOOF(max_n_peaks=2, min_peak_height=1, aperiodic_mode='knee')\n",
+    "      fm.fit(freqs_new, ps_vPN_new, [1,50])\n",
+    "      if not fm.has_model:\n",
+    "        fm = FOOOF()\n",
+    "        fm.fit(freqs_new, ps_vPN_new, [1,50])\n",
+    "      cfs = fm.get_params('peak_params', 'CF')\n",
+    "      if np.isnan(cfs).any():\n",
+    "        final_connection[ind2, ind] = 0\n",
+    "      elif cfs.shape ==():\n",
+    "        final_connection[ind2, ind] = cfs\n",
+    "      else:\n",
+    "        pws = fm.get_params('peak_params', 'PW')\n",
+    "        final_connection[ind2, ind] = cfs[np.argmax(pws)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2eda5f8d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Plotting LW results\n",
+    "data2 = pd.DataFrame(final_connection, index = p.N_ei_tot, columns=p.N_ie_tot)\n",
+    "ax = sns.heatmap(data2, vmax = 20)\n",
+    "ax.invert_yaxis()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "55fb886f",
+   "metadata": {},
+   "source": [
+    "# Robinson-Rennie-Wright"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "be61d93f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sig(v,Qmax,theta,sigma):\n",
+    " # sigmoid for voltage-rate relationship\n",
+    " firing_rate = Qmax / (1 + math.exp(-(v-theta) / sigma))\n",
+    " return firing_rate\n",
+    "\n",
+    "def sigr(v,Qmax_r,modtheta,sigma_r):\n",
+    " # sigmoid for voltage-rate relationship in reticular nucleus\n",
+    " firing_rate = Qmax_r / (1 + math.exp(-(v-modtheta) / sigma_r));\n",
+    " return firing_rate\n",
+    "\n",
+    "gamma = 116\n",
+    "t0 = 80e-3 \n",
+    "Qmax = 340\n",
+    "theta = 12.92e-3 \n",
+    "sigma = 3.8e-3 \n",
+    "Ic = 0.123 \n",
+    "taux = 0.15 \n",
+    "tauh = 0.60 \n",
+    "a_x = 0.003 \n",
+    "mu = 16.0 \n",
+    "Qmax_r = 100 \n",
+    "sigma_r = 3.8e-3 \n",
+    "\n",
+    "phin_0 = 1.0 \n",
+    "nu_ee = 0.00303 \n",
+    "nu_ei = -0.006\n",
+    "nu_ie = 0.00303\n",
+    "nu_ii = -0.006\n",
+    "nu_is = 0.00206\n",
+    "nu_re = 0.00033\n",
+    "nu_sn = 0.00098\n",
+    "alpha = 83.33 \n",
+    "beta = 769.23 \n",
+    "phin = 5e-4\n",
+    "\n",
+    "nu_es = 0.00206\n",
+    "nu_se = 0.00218\n",
+    "\n",
+    "start = 0.0\n",
+    "stop = 40.0 + t0/2\n",
+    "dt = 1e-3\n",
+    "\n",
+    "k0 = int(t0/2/dt) # the delay in timesteps\n",
+    "time_array = np.arange(start=start, stop=stop, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "np.random.seed(0)\n",
+    "noise = alpha*beta*nu_sn*math.sqrt(phin*dt)*np.random.randn(vec_len,1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "886d5834",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Varying nu_rs and nu_sr\n",
+    "nu_rs_tot = np.round(np.arange(0.0, 0.00045, 0.00001),6)\n",
+    "nu_sr_tot = np.round(np.arange(-0.0009, -0.0005, 0.00001),6)\n",
+    "iterables = [nu_rs_tot, nu_sr_tot]\n",
+    "\n",
+    "index = pd.MultiIndex.from_product(iterables, names=['nu_rs', 'nu_sr'])\n",
+    "final_Rob = pd.DataFrame(index=index, columns = ['freq'], dtype='float64')\n",
+    "test_pws = pd.DataFrame(index=index, columns = ['values'], dtype='float64')\n",
+    "\n",
+    "for nu_rs in nu_rs_tot:\n",
+    "  for nu_sr in nu_sr_tot:  \n",
+    "    phie = np.zeros(vec_len)\n",
+    "    Ve = np.zeros(vec_len)\n",
+    "    Vr = np.zeros(vec_len)\n",
+    "    Vs = np.zeros(vec_len)\n",
+    "    phiedot = np.zeros(vec_len)\n",
+    "    Vedot = np.zeros(vec_len)\n",
+    "    Vrdot = np.zeros(vec_len)\n",
+    "    Vsdot = np.zeros(vec_len)\n",
+    "    phie[0:(k0+1)] = 3.175\n",
+    "    Ve[0:(k0+1)]  = 0.0006344; \n",
+    "    Vr[0:(k0+1)]  = 0.005676;\n",
+    "    Vs[0:(k0+1)]  = -0.003234;\n",
+    "\n",
+    "    for i in range ((k0+1),(int(stop/dt))):\n",
+    "        Ve[i] = Ve[i-1] + Vedot[i-1]*dt\n",
+    "        Vedot[i] = Vedot[i-1] + dt *( alpha*beta * ( nu_ee*phie[i-1] + nu_ei*sig(Ve[i-1],Qmax,theta,sigma) + nu_es*sig(Vs[i-1-k0],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vedot[i-1] - Ve[i-1] ) )\n",
+    "          \n",
+    "        Vr[i] = Vr[i-1] + Vrdot[i-1]*dt\n",
+    "        Vrdot[i] = Vrdot[i-1] + dt*( alpha*beta * ( nu_re*phie[i-1-k0] + nu_rs*sig(Vs[i-1],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vrdot[i-1] - Vr[i-1] ))\n",
+    "        \n",
+    "        Vs[i] = Vs[i-1] + Vsdot[i-1]*dt\n",
+    "        Vsdot[i] = Vsdot[i-1] + dt*( alpha*beta * ( nu_se*phie[i-1-k0] + nu_sr*sig(Vr[i-1],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vsdot[i-1] - Vs[i-1] + nu_sn*phin_0 )) + noise[i-1]\n",
+    "        \n",
+    "        phie[i] = phie[i-1] + phiedot[i-1]*dt\n",
+    "        phiedot[i] = phiedot[i-1] + dt*( gamma**(2) * ( sig(Ve[i-1],Qmax,theta,sigma) - 2/gamma*phiedot[i-1] - phie[i-1] ))\n",
+    "\n",
+    "    # Remove initial t0-length from outputs\n",
+    "    phie = phie[(k0+1):len(phie)]\n",
+    "    Ve = Ve[(k0+1):len(Ve)]\n",
+    "    Vr = Vr[(k0+1):len(Vr)]\n",
+    "    Vs = Vs[(k0+1):len(Vs)];\n",
+    "\n",
+    "    \n",
+    "    X=signal.resample(phie,10000)\n",
+    "    output_Zhao = phie[1000:vec_len-1];\n",
+    "    freqs,ps_vPN = welch(output_Zhao,fs=1000, noverlap = 125, nperseg=1000)\n",
+    "    if np.round(phie[5000],6)  == np.round(phie[6000],6) :      # Case when time series is flat (this can be made more robust)\n",
+    "      final_Rob.loc[(nu_rs, nu_sr), 'freq'] = 0\n",
+    "    else:\n",
+    "      fm = FOOOF(peak_width_limits=[2, 8], aperiodic_mode='knee')\n",
+    "      fm.fit(freqs,ps_vPN , [2, 70])\n",
+    "      cfs = fm.get_params('peak_params', 'CF')\n",
+    "      bw = fm.get_params('peak_params', 'BW')\n",
+    "      if np.isnan(cfs).any():\n",
+    "        final_Rob.loc[(nu_rs, nu_sr), 'freq'] = 0\n",
+    "      elif cfs.shape ==():\n",
+    "        pws = fm.get_params('peak_params', 'PW')\n",
+    "        if pws>0.5:\n",
+    "          final_Rob.loc[(nu_rs, nu_sr), 'freq'] = cfs\n",
+    "          test_pws.loc[(nu_rs, nu_sr), 'values'] = pws\n",
+    "        else:\n",
+    "          final_Rob.loc[(nu_rs, nu_sr), 'freq'] = 0\n",
+    "      else:\n",
+    "        pws = fm.get_params('peak_params', 'PW')\n",
+    "        if max(pws)>0.5:\n",
+    "          freqY = cfs[np.argmax(pws)]\n",
+    "          final_Rob.loc[(nu_rs, nu_sr), 'freq'] = freqY\n",
+    "          test_pws.loc[(nu_rs, nu_sr), 'values'] = np.max(pws)\n",
+    "        else:\n",
+    "          final_Rob.loc[(nu_rs, nu_sr), 'freq'] = 0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d381fd0f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Plotting RRW results\n",
+    "new_Rob = final_Rob.unstack(level='nu_sr')\n",
+    "new_Rob.columns=new_Rob.columns.droplevel()\n",
+    "data = pd.DataFrame(new_Rob)\n",
+    "ax = sns.heatmap(data, vmax=12)\n",
+    "ax.invert_yaxis()\n",
+    "ax.invert_xaxis()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "alpha",
+   "language": "python",
+   "name": "alpha"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/content/Estimate_1_f_component.ipynb b/content/Estimate_1_f_component.ipynb
new file mode 100644
index 0000000..9765e13
--- /dev/null
+++ b/content/Estimate_1_f_component.ipynb
@@ -0,0 +1,988 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "c1dc1630",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from fooof import FOOOF\n",
+    "from scipy.optimize import fsolve\n",
+    "from scipy import signal\n",
+    "from scipy.signal import welch"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b337c96d",
+   "metadata": {},
+   "source": [
+    "# Jansen-Rit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "939377a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sigm(nu_max,v0,r,v):\n",
+    "  action_potential = (2*nu_max)/(1+math.exp(r*(v0-v)))\n",
+    "  return action_potential"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "0819c8a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameter settings\n",
+    "A = 3.25 \n",
+    "B = 22\n",
+    "C = 135\n",
+    "C1 = 1*C\n",
+    "C2 = 0.8*C  \n",
+    "C3 = 0.25*C \n",
+    "C4 = 0.25*C\n",
+    "v0 = 6        \n",
+    "tau_e = 10\n",
+    "tau_i = 20\n",
+    "a = (1/tau_e)*1000 # 100   \n",
+    "b = (1/tau_i)*1000 # 50       \n",
+    "nu_max = 2.5 \n",
+    "r = 0.56     \n",
+    "\n",
+    "# Simulation setting\n",
+    "start = 0.0\n",
+    "stim_time =100\n",
+    "dt = 1e-4\n",
+    "time_array = np.arange(start=start, stop=stim_time, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "# Input\n",
+    "noise = np.random.uniform(120,320,vec_len)\n",
+    "# Output Initialization\n",
+    "y = np.zeros((6,vec_len))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a6105f1f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Euler integration method to solve JR differential equations\n",
+    "for i in range (1,vec_len):\n",
+    "  y[0,i] = y[0,i-1] + y[3,i-1]*dt\n",
+    "  y[1,i] = y[1,i-1] + y[4,i-1]*dt\n",
+    "  y[2,i] = y[2,i-1] + y[5,i-1]*dt\n",
+    "  y[3,i] = y[3,i-1] + dt * (A*a*(sigm(nu_max,v0,r,(y[1,i-1]-y[2,i-1]))) - (2*a*y[3,i-1]) - (a**(2)*y[0,i-1]))\n",
+    "  y[4,i] = y[4,i-1] + dt * (A*a*(noise[i-1] + (C2*sigm(nu_max,v0,r,(C1*y[0,i-1])))) - (2*a*y[4,i-1]) - (a**(2)*y[1,i-1]))\n",
+    "  y[5,i] = y[5,i-1] + dt * (B*b*(C4*sigm(nu_max,v0,r,(C3*y[0,i-1]))) - (2*b*y[5,i-1]) - (b**(2)*y[2,i-1]))\n",
+    "\n",
+    "output = y[1,:]-y[2,:]\n",
+    "X = signal.resample(output, 10000)\n",
+    "freqs_Jansen,ps_vPN_Jansen = welch(X,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "a25df4ea",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Power')"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "X = freqs_Jansen\n",
+    "Y = ps_vPN_Jansen\n",
+    "pre_X = X[4:40]\n",
+    "pre_Y = Y[4:40]\n",
+    "post_X = X[110:]\n",
+    "post_Y = Y[110:]\n",
+    "full_X = X[10:]\n",
+    "full_Y = Y[10:]\n",
+    "\n",
+    "p1=np.polyfit(np.log(pre_X),np.log(pre_Y),1);\n",
+    "pre_y =np.polyval(p1,np.log(pre_X));\n",
+    "\n",
+    "p2=np.polyfit(np.log(post_X),np.log(post_Y),1);\n",
+    "post_y =np.polyval(p2,np.log(post_X));\n",
+    "\n",
+    "p3=np.polyfit(np.log(full_X),np.log(full_Y),1);\n",
+    "full_y =np.polyval(p3,np.log(full_X));\n",
+    "\n",
+    "\n",
+    "plt.plot(X,Y)\n",
+    "plt.plot(pre_X,np.exp(pre_y), color=\"red\")\n",
+    "plt.plot(post_X,np.exp(post_y), color=\"red\")\n",
+    "plt.plot(full_X,np.exp(full_y), color=\"orange\")\n",
+    "\n",
+    "plt.xscale(\"log\")\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xlabel(\"Frequency\")\n",
+    "plt.ylabel(\"Power\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "2375d5d5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-0.3342602995691549\n",
+      "-3.8971558026332307\n",
+      "-1.2561430773081517\n"
+     ]
+    }
+   ],
+   "source": [
+    "slope_pre, intercept = np.polyfit(np.log(pre_X),np.log(pre_Y),1);\n",
+    "print(slope_pre)\n",
+    "slope_post, intercept=np.polyfit(np.log(post_X),np.log(post_Y),1);\n",
+    "print(slope_post)\n",
+    "full_slope, intercept=np.polyfit(np.log(full_X),np.log(full_Y),1);\n",
+    "print(full_slope)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d1f1b9f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "==================================================================================================\n",
+      "                                                                                                  \n",
+      "                                   FOOOF - POWER SPECTRUM MODEL                                   \n",
+      "                                                                                                  \n",
+      "                        The model was run on the frequency range 1 - 50 Hz                        \n",
+      "                                 Frequency Resolution is 0.10 Hz                                  \n",
+      "                                                                                                  \n",
+      "                         Aperiodic Parameters (offset, knee, exponent):                           \n",
+      "                                   2.7828, 5384703.7922, 4.7496                                   \n",
+      "                                                                                                  \n",
+      "                                       2 peaks were found:                                        \n",
+      "                                CF:  10.73, PW:  2.555, BW:  3.25                                 \n",
+      "                                CF:  21.46, PW:  0.470, BW:  2.00                                 \n",
+      "                                                                                                  \n",
+      "                                     Goodness of fit metrics:                                     \n",
+      "                                    R^2 of model fit is 0.8881                                    \n",
+      "                                    Error of the fit is 0.2043                                    \n",
+      "                                                                                                  \n",
+      "==================================================================================================\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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22dW2KS0tje7du7N//34ATj31VK/8IsWbay9X9uyjoqKqPG4fk+f6teGvFOJERETEL+zcudNpu7i42GshzhNdEhuy/v37s2DBAjZu3EhpaWm1n+d169YBtvDn7gfw8PDwOrelqpBQ1wBR2256N998MytWrODMM89k5syZ9OvXjxYtWpgVwnbt2nH48OFqK5Ino0WLFtx44410796dESNGkJ6ezsqVKxkzZkyt7+XYTqvVCsDkyZOJjIys8jpPTNxSEyfz9WL/eCpT3bNvLEs3KMSJiIiIX3ANcSUlJT5qSeN3/vnn89hjj5GVlcUXX3zBZZddVum5hmHw/vvvA5V3U6wL+2LWrssH2GVlZXl0av/K5OXlsWjRIgICAli0aFGF5Rby8vLqdfzkaaedRlxcHOnp6ebYRUdJSUmVXmv/XDqO70tISGD37t08/PDDDB48uEZtsFerdu3a5dVuze6EhIQAtmUf3LFXCZu6xhFFRUREpMFTiKs/iYmJXH755QA8+OCDVYal2bNn89tvvxEUFMSDDz7osTacc845AHz00Udu1+f64IMPPPZeVcnKyqKsrIyYmBi36+XNmzfPoxW46u6VlZVFdnY2gNvJVn777Td+++23Cvu3bt3Kxo0bCQgIMD+3AOPHjwdgwYIFNW7j4MGDiYuLIy0tjc8//7xG19jD18mutWYP99u3b3d73D7Gr6lTiBMRERG/oBBXv2bNmkXnzp1JSkpi1KhRbN261el4aWkp//rXv7jnnnsA+L//+z969+7tsfe//PLLadu2Lfv27ePRRx916ia3Y8cO/vrXv3rsvarSunVrWrRowfHjx82Ko92aNWuYMWOGR99v6NChzJ49m8zMzArHUlNTuf322ykuLqZTp05OM2jaGYbB7bff7rSwd1ZWFrfffjuGYXDZZZeRkJBgHnvwwQdp3rw5//rXv/jnP//pdtbXpKQk5s2bZ24HBQXx6KOPAnDrrbeybNmyCtesX7/eaeydPXDu3r37pP7tjho1ioCAAL777jtz8hv7x/3yyy/zySef1PnejYm6U4qIiIhfcDcmTrwnNjaWFStWMGnSJH755Rf69u3L4MGD6dq1K/n5+axevZq0tDRCQkL45z//aYY5T4mIiGDevHlccMEFPPfcc3z66acMHjyYzMxMlixZwsUXX8zatWtJTk42qzzeEBgYyBNPPMGf//xnrr/+el599VW6dOlCcnIyq1at4tprr2XZsmUe68a3e/du7rzzTu6++2769u1L165dCQoKIiUlhbVr11JSUkJsbCzz5893O1Zx4sSJbNmyhS5dunDuueeai31nZmbSrVs3Zs2a5XR+hw4dzC6zDzzwAM899xx9+vShbdu2ZGVlsX37dvbs2cPpp5/Otddea153zz33sHPnTl5//XVGjBjBgAEDOPXUU8nOzmbHjh3s3buXxYsXm+GtY8eODB482OlrKSwsjLi4OP7xj3/U+POTkJDA9OnTeemllzjvvPM4++yziY2NZfPmzSQnJ/PII4/U6n6NlUKciIiI+FxxcbE5i56dKnHe1759e9auXcuCBQuYP38+69evZ/PmzYSFhdGpUyeuv/567rrrLq/NJjhq1CjWrl3LU089xdKlS/n888/p0qULf//737n77ruJjo4mICDAaU00b7j33ntJTEzkueeeY9u2bWzdupUePXrw6quvctttt1U5I2RtrVixgh9//JGff/6Z3bt389NPP5Gbm0tMTAxDhgxhxIgR3HvvvW6nwQfbBChr1qzh8ccfZ+HChRw9epTWrVtz7bXX8uSTT7r9XJ1zzjls3bqVWbNmsXDhQtavX09RURHx8fF07NiRa6+9tsK4SIvFwmuvvcbFF1/M66+/zpo1a9iyZQvNmzcnMTGRqVOnctpppzld88knnzBjxgwWL17Mhx9+SGlpKZ06dap16Pr3v/9Nx44deeutt1i1ahVRUVGcddZZLFiwgOzsbIU4wGJ4c5qdJio7O9ucEtc+la2vlJSUsGjRIiZMmOB2DRbxLT0f/6bn47/0bPxbXZ7P9u3b6dWrl9O+bdu2VbngcWUKCwtJSkoiMTGRsLCwWl/f2FmtVrKzs4mJifHrmfqWLVvGiBEj6Nu3r9sxYI1RVc9m7ty53HDDDUydOpW5c+f6poFNnOPzKS4urvH3GW9kA//9lysiIiJNhmtXSlAlrilIS0tzO9vili1buOWWWwC44YYb6rtZIn5P3SlFRETE51y7UoLGxDUFW7du5dxzz6VXr1506dKF8PBwkpKS2LhxI1arlTFjxjB9+nRfN1PE7yjEiYiIiM8VFhZW2KdKXOPXvXt37rzzTpYuXcrKlSvJyckhOjqaYcOGcfXVV3PLLbd4bcF3kYZM/ypERETE59wFNoW4xq9du3YVZlMU96ZNm8a0adN83QzxExoTJyIiIj6nECciUnMKcSIiIuJz7gKbxsSJiLinECciIiI+V1paWmGfKnEiIu4pxImIiIjPqTuliEjNKcSJiIiIzynEiYjUnEKciIiI+Jy6U4qI1JxCnIiIiPicJjYREak5hTgRERHxOXWnFBGpOYU4ERER8TmFOBGRmlOIExEREZ/TmDgRkZpTiBMRERGf05i4+telSxcsFkuVf1588cWTeo8lS5ZgsVgYOXJkhWP296iNadOmmdf179+/ynPXr1/v9LGsWLGiVu9VV507d8ZisbBv376Tvte+ffuwWCx07ty5VteNHDmy2md77733Aic+p3Pnzj3p9kr9CfJ1A0RERETUndJ3zjrrLE455RS3x3r16lXPram5zZs3s2HDBgYNGuT2+Jw5c+q5Rf6nX79+lYbdoUOHVnnt3LlzueGGG5g6daoCnh9SiBMRERGfU4jznZtvvplp06b5uhm1MnjwYH755RfefvtttyGuoKCA+fPn07ZtWwIDAzl48KAPWul7kyZN4qmnnqrynGeffZZHHnmEtm3b1k+jxCPUnVJERER8TmPipDYuuOACWrduzf/+9z8KCwsrHP/444/Jysri+uuvJzAw0ActbDjatm1Ljx49aNasma+bIrWgECciIiI+pzFx/q26cVNz587FYrHUW0UvKCiI6667jmPHjvHZZ59VOP72228DcOONN1Z5n9LSUl5//XWGDRtGs2bNCAsLo1u3btx9992kpKRUet22bdu4/PLLiYuLIzw8nD59+vDCCy9QVlZW7fu99dZbjBw5ktjYWEJDQ0lMTOT222/nwIEDNfjIPc/ds+3cuTM33HADAO+++67TWDp34xul/qk7pYiIiPhcvXWnNAzIz/f8fetTRATUckKQxujGG2/khRde4O233+aqq64y9+/Zs4elS5dy1lln0b1790qvLyoq4sILL+THH38kLCyMc889l5iYGFatWsUrr7zC//73P7777jsGDhzodN2KFSs4//zzycvLo0uXLowZM4b09HT+8pe/sGbNmkrfLycnh4kTJ7JkyRKioqIYNGgQrVq14vfff+f111/no48+4rvvvqNr164n/8k5SZMnT2bNmjWsXLmSrl27Mnz4cPNYjx49fNgysVOIExEREZ+rt+6U+fnw/POev299evBBiIz0dSt8rmfPnpx55pn8/PPPJCcn07FjRwDeeecdDMPgpptuqvL6J598kh9//JGuXbvy448/mjNAlpSUcPvttzNnzhwmT57Mjh07CAkJAaCwsJCrr76avLw87r33Xl544QWzu+Zvv/3GeeedR3p6utv3u+2221iyZAkXXnghc+bMIT4+3jz24osv8uc//5mrrrqK1atXn+yn5qS98MILzJ07l5UrVzJ8+HBNbOKH1J1SREREfE4Tm/jODTfc4HYK+obQbe7GG2/EarXyzjvvAGC1Wnn33XeJiopiypQplV5XWFjIq6++CsC///1vpyn8g4ODefnll2ndujVJSUl8/PHH5rFPPvmEAwcOkJCQwHPPPec03u60007j0Ucfdft+27dv53//+x/t2rXjgw8+cApwAPfeey8TJkxg9+7d/PDDD7X+PFRm5syZbp9tbZcsEP+jSpyIiIj4nMbE+U5lSww0hG5zV1xxBffeey9z587liSee4LvvvuPgwYPceOONRFZRrfzll1/Izc0lNjaWiy66qMLxiIgIrrzySl566SUWL17M1VdfDdjWvQOYMmUKwcHBFa6bOnUqf/7znyvsX7RoEYZhMH78eKKjo922aeTIkSxatIh169ZVGUBro7IlBuLi4jxyf/EdhTgRERHxOVXifKchLjFgFx0dzeTJk3n33Xf5+eefazyhiX3SksTExErPsY9Nc5zgxL5UQWXXtWjRgmbNmpGVleW0f+/evYBt7brq1q/LyMio8nht1GSJAWmYFOJERETE5+ptTFxEhG1MWUMWEeHrFlRgtVp99t433ngj7777Ls8//zyLFy/m1FNP5ayzzvJZe9yxf3769+9Pv379Kj3PMIxKFy8XcaQQJyIiIj5nD2xhYWHmul9eCXEWiyYFqQP7xB45OTluj+/fv78+m+PknHPO4ZRTTuG7774DMKfGr0r79u0BSEpKqvQce/XMfq7j63379rm95vjx4xWqcAAJCQmArevqrFmzKn1Pq9VKdnZ21Y0XQRObiIiIiB+wB7YIhyqTxsT5D3t42b59e4VjhmHwzTff1HeTnNx22220bNmS+Ph4rr/++mrPHzx4MFFRUWRmZvLll19WOF5QUMD8+fMBOPfcc839I0aMAGDBggVuf8nw3nvvuX2/8ePHA/Dll1+6XZzcH9mDu7squfieQpyIiIj4nP0HYsfJKDQmzn+MHj0agPfff59t27aZ+0tKSnj44YdZv369r5oGwP333096ejpHjhyhbdu21Z4fFhbGnXfeaV7rWEksKSnhnnvuITU1lcTERCZPnmwemzx5Mu3btyc5OZkZM2Y4dSPdsmULf/vb39y+34ABA7jssss4cOAAl156qdtKXl5eHv/97385evRoTT9sr+rQoQOA0/MW/6HulCIiIuJz9t/2h4eHm/sU4vzHWWedxcUXX8wXX3zB4MGDGT58OOHh4WzcuJHs7GzuueceXnrpJV83s1ZmzpzJL7/8wk8//UTPnj0599xziY6OZvXq1SQnJ9OyZUs++ugjsyIFtq/P//73v0yYMIF//vOffP755wwZMoSMjAyWLFnCRRddxIYNG9x2L33nnXc4fvw433zzDaeeeir9+vUjMTERwzDYt28fmzdvpri4mLVr19bnp6FSZ5xxBu3atWPTpk0MHDiQvn37EhwczKmnnsqDDX1caSOgSpyIiIj4nD2wKcT5rw8//JDHHnuMtm3bsmTJEtasWcPZZ5/Nxo0b3U5j7+9CQ0P59ttvmT17Nv369WP58uV89tlnBAcHM336dDZv3ux2kpERI0awdu1aLr30Uo4dO8Znn33GwYMH+etf/8qHH35Y6ftFR0fz/fff88EHHzB69GiSk5P57LPP+PnnnykoKOCaa67hk08+qXLGzPoUEhLCd999x8SJEzl48CDz5s1jzpw5LFy40NdNE8BiGIbh60Y0NtnZ2eb0sjExMT5tS0lJCYsWLWLChAlu1zMR39Lz8W96Pv5Lz8a/1fb5GIZBQIDt98pDhw5lw4YNlJWVMWjQIH755Zdav39hYSFJSUkkJiYSFhZW6+sbO/vkGTExMebnXfyDno1/c3w+xcXFNf4+441soK8OERER8SnHcUXBwcFm8FMlTkTEPYU4ERER8SnHsKYQJyJSPYU4ERER8SnHsBYUFKQQJyJSDYU4ERER8SnXSpx9NkCtEyci4p5CnIiIiPiU42LC6k4pIlI9hTgRERHxKXWnFBGpHYU4ERER8SlNbCIiUjsKcSIiIuJTGhMnIlI7CnEiIiLiUxoTJyJSOwpxIiIi4lOVjYkrLS3FMAxfNUtExG8pxImIiIhPVTYmDpyrdCIiYqMQJyIiIj5VVYhTl0oRkYoU4kRERMSnXMfE2Sc2AU1uIiLijkKciIiI+FRlY+Jcj4mIiI1CnIiIiPiUulP6h379+mGxWAgNDSUjI8PXzam1adOmYbFYmDt3br2838iRI7FYLCxZssQn7bBYLNX++fzzzwHo3LkzFouFffv2ebVNUn+CfN0AERERadoqW2IAFOLqy/r16/ntt98AWxfWefPmcc899/i4VVIT48aNo02bNm6PdezYscprp02bxrvvvss777zDtGnTvNA68RaFOBEREfEp1+6UGhNX/+bMmQNA+/btSUlJYc6cOQ0uxD377LM88sgjtG3btkm145FHHmHkyJFVnvPTTz9RUlJC+/bt66VN4n3qTikiIiI+pe6UvpWfn8///vc/AN5//32ioqL4/fffWb9+vY9bVjtt27alR48eNGvWTO1w0bVrV3r06OH0b0saNoU4ERER8SmFON/66KOPyM7Opk+fPpx77rlcccUVwInqnDuO48GWLl3K2LFjiY2NJSIigqFDh/L+++9X+Z4//fQTl156KW3btiUkJIT4+HguueQSVq9e7fZ8+xgvgHfeeYczzzyTZs2aOY3zqm4s2vz58znvvPOIjY0lNDSUTp06ceONN7Jr165K23ngwAFuvPFG2rZtS1hYGN26dePRRx+loKCg0muqa8eGDRuYOnUqiYmJhIWFERsbS79+/XjwwQfZv39/pfc9Ga5j4vbt24fFYuHdd98F4IYbbnAaS/fUU095pR3iOQpxIiIi4lO+GhOXl1f3P1U1Kz+/7vf1Re9Re1i78cYbnf6eP39+lWEF4LPPPmPUqFGkpKQwbtw4hgwZwoYNG7j++uu5//773V7zwAMPMHr0aL744gs6duzIpEmT6NKlC1988QVnn30277zzTqXvN336dG6++WaCgoK44IILOP30081wVxnDMJg6dSpXXXUVy5YtY8CAAVx66aWEhYXxzjvvMGDAAL799tsK1+3YsYPBgwfzzjvvYLFYmDhxIt27d+ff//435513Xp26+j7//PMMHTqU9957j5CQEC6++GKGDx9OSUkJL7zwAosXL671PesiKiqKqVOn0rVrVwDOOusspk6dav7p379/vbRD6k5j4kRERMSnfDUm7vnn637thAkwdKj7Y7Nm2YJcXYwcaftTX3bt2sXy5csJDg7m2muvBWDYsGH06NGDHTt28PHHH3PddddVev3LL7/MM888w4wZM8x9S5cuZfz48fzrX/9i7NixjBs3zjz2n//8h3/+85+ccsopfPLJJ5x22mnmsWXLlnHhhRdy2223MXz4cLp161bh/d577z1WrlzJGWecUeOP8Y033uC9994jLi6OH374wQwohmEwc+ZMZs6cyVVXXcWuXbto1aqVed3111/P0aNHmTJlCu+++y5hYWEAJCcnM2rUKPbs2VPjNgB8+eWXPPTQQ4SFhfHuu+8yZcoUp+Pbtm3DMIxa3bOu4uLimDt3LtOmTWPPnj3cfPPNmtikgVElTkRERHxK3Sl95+233wZg4sSJTgHGXo2rqkslwIABA5wCHMCIESO44447APjnP/9p7rdarWY3vfnz5zsFOIBzzjmHxx9/nOLiYt544w237/fAAw/UKsABvPDCCwA88cQTThUmi8XCk08+yWmnncbx48f5z3/+Yx5buXIl69evJzIyktmzZ5sBDmwzPtrvWRtPPvkkAH//+98rBDiAXr160bNnz1rf99xzz3W7vIBCWeOmECciIiI+pRDnG6WlpeaYKHtos7v++usJCgpi2bJlVVacrr/+erf7p06dCsCKFSsoKysDYNOmTRw6dIiuXbsyaNAgt9fZZ1lctWqV2+OTJ0+u/ANy4+DBg2b77W1yZLFYuOGGGwCcujLa1347//zzadmyZYXrLr744lpNXJKamsqvv/5KQEAAN910U20+hGqNGzfOqSuk/c/w4cM9+j7iX9SdUkRERHxK68T5xsKFC0lNTaV9+/ZOXR4BWrduzYQJE/jyyy95++23+fvf/+72HomJiVXuLygoICMjg/j4ePbu3QvAnj17qh3HlpaW5nZ/586dq7zOVUpKCgAtW7YkJibG7Tn2cWH2c8EW/qDyj89isdC5c2c2b95co3YkJycDtpkrPT1rZU2WGJDGRyFOREREfMpXY+IefLDu1zo0sYK77oK6Dm2qzxng7V0pCwsLGTFiRIXj9lAzd+5c/vrXvxIYGFin97GP87JarQC0adOmQmh0FRcX53Z/eHh4ndog0tgoxDn46KOPePXVV9m8eTPFxcWccsopXHPNNfz5z3/WuhoiIiJe4qvulJGR3rlvRIR37utJqampfPPNNwBkZGSwcuXKSs89dOgQ3377LRdccEGFY0lJSW6vsU9lHxYWZnZHTEhIAGxVscqm3/c0++LWGRkZZGdnu63G2SuEjgth21/bPw53arMcQMeOHQE4fPgwWVlZfrWGnDRMGhNX7t5772XKlCmsXLmSoUOHcv7555OcnMzDDz/MqFGjqp1iV0REROpG3Snr3wcffEBZWRmnn346hmFU+uehhx4CKp/gZN68eW73v/feewAMHz6coCBbzWDIkCHExcWxbds2tm7d6oWPqqIOHTqY3SXdBUfDMMz95557rrnfXpn89ttvyczMrHDdl19+yfHjx2vcjjZt2tCvXz+sVqtZAfUH9qq3479BaRgU4oDPP/+cl156iaioKNauXct3333HJ598wu7du+nbty8rVqzg8ccf93UzRUREGiXX7pQKcd733//+F3A/2Ycj+8QlX3/9tdtxahs2bOC5555z2rdixQpeffVVAP785z+b+4ODg3nyyScxDINLLrmEFStWVLhfWVkZP//8M2vWrKndB1SFBx54AICnn37aaQybYRj87W9/49dff6V58+bccsst5rGzzz6bgQMHkpuby5133klRUZF57MCBA+Y9a8M+O+Wjjz7KJ598UuH4tm3b2L59e63vezI6dOgAUG+hWjxHIQ545plnANvA0IEDB5r74+LimD17NgCzZs0iKyvLJ+0TERFpzFy7U9bXmLimaunSpezdu5fQ0FCuvPLKKs/t3bs3AwcOpKSkxKyuObr77ruZMWMGffr04eqrr2bkyJGMGDGC/Px87rnnHiZMmOB0/l133cWDDz7I7t27Ofvss+nTpw+TJk3iqquu4txzzyUuLo7zzjuPX3/91WMf75/+9Ceuu+460tPTGTx4MKNHj+bqq6+mZ8+ePPHEE4SHh/PBBx84LbEA8P7779OqVSvmz59Ply5duOKKK7jooovo0aMHLVu25Mwzz6xVOy655BL+/ve/U1hYyOTJk+nZsydXXnklF198Mb1796Z3796sXbvWYx93TUyaNImAgABefvllxowZw4033sjNN9/Ml19+Wa/tkNpr8iEuJSWF9evXA3D11VdXOD58+HASEhIoKipi0aJF9d08ERGRRk9LDNQve3e+Cy+8kBYtWlR7vr0a565L5SWXXMIPP/xAmzZtWLRoEevWrWPgwIHMnTuXF1980e39nnvuOVauXMk111xDbm4u3377LQsXLuTQoUOMHDmSt956iyuuuKLuH6ALi8XCe++9xwcffMDw4cPZsGEDH3/8Mfn5+UybNo1NmzYxfvz4Ctf16tWLX375hWnTplFWVsbnn3/Otm3bmD59Oj/99JPTLxtq6i9/+QurVq3iqquuIicnh08//ZQVK1YQHBzMQw89xKhRozzxIdfYaaedxieffMKZZ57J2rVrmTt3LnPmzGHjxo312g6pvSY/scmmTZsAiI2NrXQa2cGDB3PgwAE2bdrEVVddVZ/NExERafQ0Jq5+vfvuu7zyyiuVTrnv6p577uGee+6p9PioUaNqHT6GDRvGsGHDany+UYPpPufOnVvlhClXXXVVrX+O69ixI++8847bY/a15GrbjjPOOKPSBcutVivZ2dk1altNPid2VU3QMmnSJCZNmlTje4l/aPKVOPusSvZZg9yxz6ZU2QxMIiIiUncaEyciUjtNvhKXk5MDQGQV8wxHRUUBVPqbkaKiIqcBr/bzSkpKfP6fj/39fd0OcU/Px7/p+fgvPRv/Vtvn4/h/KEBAwInfMRcUFNT6OZeUlGAYBlar1VybTE6wV3Dsn6OToc+xZ3ny2YjnuT4fwzAoKSmpdg1Fb/xf1eRDnCc8++yzzJw5s8L+77//ngg/WSzmhx9+8HUTpAp6Pv5Nz8d/6dn4t5o+H8eeLqtXryY1NdXc3rZtW63HpAcFBdGmTRtyc3M1MUoV7L/Irgt7F9j8/Pwad/+TmjuZZyPel5OTQ3FxMQUFBSxbtqzaJRry8/M93oYmH+Kio6MByMvLq/Sc3NxcgEr7js+YMYP77rvP3M7OziYhIYGxY8fWuL+5t5SUlPDDDz8wZswYLVjuh/R8/Juej//Ss/FvtX0+H374ofl61KhRTuN3OnfuXGGGw+oUFhZy4MABoqKiCAsLq9W1TYFhGOTk5BAdHY3FYqnTPZYtW+bhVgl45tmI9zg+n6KiIsLDwznnnHOq/T7jjV90NPkQ17lzZ8C25kdl7Mfs57oKDQ0lNDS0wn7Xwdm+5E9tkYr0fPybno//0rPxbzV9PmVlZebriIgIwsPDzW2r1VrrZ1xWVobFYiEgIMCpa6bY2Lvp2T9H4j/0bPyb6/OxWCw1+j7njf+nmvxXx4ABAwDIyMiodOKSX375BcBpDTkRERHxDK0TJyJSO00+xHXo0IEhQ4YA8MEHH1Q4vmLFCg4cOEBoaGitu3OIiIhI9bTEgIhI7TT5EAe2hRcB/vGPfzgtbpiRkcEdd9wBwF133UWzZs180j4REZHGzFtLDNRmHS0Rkdrw9fcXhThsixzefffd5ObmcsYZZzB+/HgmT57MKaecwu+//85ZZ53F008/7etmioiINEqu3SkdQ1xdulPaxxI5jrUTEfEk+/cXX41dVIgr99JLL/Hhhx9y5plnsmrVKhYtWkSHDh34xz/+wc8//+w0yFpEREQ8p6oQV93U3e4EBwcTGBhIQUGBR9onIuKqoKCAwMBAn02u1eRnp3Q0ZcoUpkyZ4utmiIiINCmuY+KCgk78eFKXaprFYiEiIoKsrCxiY2OrXYhXRKQ2ysrKyMrKIiIiwmdLQSjEiYiIiE/ZK3H2absdQ1xdKnEA8fHx7Nu3j/379xMbG0toaKjW3SpntVopLi6msLBQ09j7GT0b/1ZWVkZeXh4ZGRlYrVbi4+N91haFOBEREfEpe4izd0tyrJzVNcSFhITQoUMH0tPTOXz48Mk3shExDIOCggLCw8MVbP2Mno1/MwyDvLw8WrVqRdu2bZ2WQ6lvCnEiIiLiU64hzhOVOLAtHN6xY0dKS0tP6j6NTUlJCcuWLeOcc87x2XgecU/Pxr+VlpayePFi+vfv7/PnoxAnIiIiPmUPWPbwdrJj4lwFBQU53bOpCwwMpLS0lLCwMJ//ICrO9Gz8W0lJCVar1dfNADQ7pYiIiPiYtypxIiKNlUKciIiI+JRCnIhI7SjEiYiIiE95Y2ITEZHGTCFOREREfKqqMXEKcSIiFSnEiYiIiE9VVYnzxMQmIiKNjUKciIiI+JRriLNYLGaQUyVORKQihTgRERHxKdfulIBCnIhIFRTiRERExKdcK3FwItApxImIVKQQJyIiIj5TVlaGYRiA+xCnMXEiIhUpxImIiIjP2KtwoEqciEhNKcSJiIiIzziGNMcxcQpxIiKVU4gTERERn6msEqeJTUREKqcQJyIiIj6j7pQiIrWnECciIiI+U12I08QmIiIVKcSJiIiIz2hMnIhI7SnEiYiIiM9oTJyISO0pxImIiIjPFBcXm69DQ0PN16rEiYhUTiFOREREfKaoqMh8HRISYr5WiBMRqZxCnIiIiPiMYyXOXYjTxCYiIhUpxImIiIjPVNedsqysDMMw6r1dIiL+TCFOREREfKay7pT2iU1A1TgREVcKcSIiIuIz1XWnBI2LExFxpRAnIiIiPlNdd0pQJU5ExJVCnIiIiPhMdbNTgipxIiKuFOJERETEZyrrTuk4Jk4hTkTEmUKciIiI+ExNulMqxImIOFOIExEREZ9Rd0oRkdpTiBMRERGfqcnslJrYRETEmUKciIiI+Iy6U4qI1J5CnIiIiPhMTRb7VogTEXGmECciIiI+o8W+RURqTyFOREREfEaLfYuI1J5CnIiIiPiMZqcUEak9hTgRERHxGS32LSJSewpxIiIi4jOanVJEpPYU4kRERMRn1J1SRKT2FOJERETEZ7TYt4hI7SnEiYiIiM+oO6WISO0pxImIiIjPaLFvEZHaU4gTERERn9Fi3yIitacQJyIiIj6jxb5FRGpPIU5ERER8xrE7pWNwUyVORKRyCnEiIiLiM/ZKXEhICBaLxdyvECciUjmFOBEREfEZe4hz7EoJmthERKQqCnEiIiLiM/bulI6TmoAqcSIiVVGIExEREZ9x7E7pSBObiIhUTiFOREREfKay7pSqxImIVE4hTkRERHymsu6UGhMnIlI5hTgRERHxmZp0p1SIExFxphAnIiIiPqMQJyJSewpxIiIi4hNWq9UMaFWNidPEJiIizhTiRERExCfsVThQJU5EpDYU4kRERMQnqgpxmthERKRyCnEiIiLiE/aZKUFLDIiI1EZQ9aeIiIiIeI5hGKxcuRKr1Wru02LfIiI1pxAnIiIi9erjjz9mypQpTvs0Jk5EpObUnVJERETq1apVqyrsc+1OqTFxIiKVU4gTERGRepWTk1NhnypxIiI1pxAnIiIi9So3N7fCPoU4EZGaU4gTERGReuUuxGmxbxGRmlOIExERkXqlSpyIyMlRiBMREZF6VZMQp4lNREQqpxAnIiIi9crdxCZa7FtEpOYU4kRERKRe1bY7pcbEiYg4U4gTERGReqUxcSIiJ0chTkREROqNYRg1mp1SY+JERCqnECciIiL1prCwEKvVWmG/KnEiIjUXVP0pjduiRYtYt24dGzZsYMOGDRw+fBiAAwcO0KFDBx+3TkREpHFxV4UDhTgRkdpo8iHu6quvJisry9fNEBERaRLczUwJWuxbRKQ2mnyIu/TSS+nWrRsDBw5k4MCBxMfH+7pJIiIijZYqcSIiJ6/Jh7i3337b100QERFpMmoa4jSxiYhI5TSxiYiIiNSbykKcFvsWEak5hTgRERGpNzWtxAUEnPgRRSFORMSZQpyIiIjUm8omNnENcRaLxazGaWITERFnTX5MnCcUFRVRVFRkbmdnZwNQUlJCSUmJr5pltsHxb/Evej7+Tc/Hf+nZ+Leqnk9lM0IHBARUOD8wMJDS0lK/+P+0MdG/H/+lZ+Pf6vp8vPE8LYZhGB6/az146KGH+PLLL2t93VtvvcXw4cMrPW6xWIDarRP31FNPMXPmzAr7P/jgAyIiImrdRhERkcbq008/5b333quwf9asWRX+373yyispLCykY8eOvPzyy/XVRBERj8rPzzeXNYuJifHIPRtsJe7QoUPs3Lmz1tdV1hf/ZMyYMYP77rvP3M7OziYhIYGxY8d67EHVVUlJCT/88ANjxowhODjYp22RivR8/Juej//Ss/FvVT2ftWvXur1m9OjRdOnSxWlfaGgohYWFhIWFMWHCBK+1t6nRvx//pWfj3+r6fOy99DypwYa4efPmMW/ePF83A7D9J+M6qxZAcHCw3/wD9Ke2SEV6Pv5Nz8d/6dn4N3fPp6CgwO25UVFRFc61j4mzWq16zl6gfz/+S8/Gv9X2+XjjWWpiExEREak3NZ2dEk6EOM1OKSLiTCFORERE6k1NZ6eEEwt+K8SJiDhTiBMREZF6U9PFvkGVOBGRyjTYMXGe8vTTT7Nw4cIK+ydOnGj+VnDgwIHMnj27vpsmIiLS6FQW4tyNGVGIExFxr8mHuD179ridKWvTpk3m67CwsPpskoiISKNlD3GBgYFOi3jbu0460mLfIiLuNfnulHPnzsUwjCr/LFmyxNfNFBERaRTsIS4qKqraczUmTkTEvSYf4kRERKT+2Cc2iYqK4h//+AcWi4U77rjD7bnqTiki4l6T704pIiIi9cexEvfwww9z++23ExMT4/ZchTgREfdUiRMREZF6YRhGhe6UlQU40Jg4EZHKKMSJiIhIvSgsLMRqtQIQHR1d7fn2EGe1Ws3rREREIU5ERETqiePyArWZ2ARUjRMRcaQQJyIiIvXCPqkJ1CzE2StxoHFxIiKOFOJERESkXtS2EqcQJyLinkKciIiI1AvHEFebMXGg7pQiIo4U4kRERKReZGVlma9rEuIcx8SpEicicoJCnIiIiNSL9PR083VcXFy156s7pYiIewpxIiIiUi8cQ1yrVq2qPV8hTkTEPYU4ERERqRdpaWnm69pW4jQmTkTkBIU4ERERqRfqTiki4hkKcSIiIlIvahviNLGJiIh7CnEiIiJSL1SJExHxDIU4ERERqRf2EBcVFUVYWFi15yvEiYi4pxAnIiIi9cIe4mpShQNNbCIiUhmFOBEREfE6q9VKRkYGUPMQpzFxIiLuKcSJiIiI1x07dgyr1QrUrRKnECcicoJCnIiIiHhdbSc1AYU4EZHKKMSJiIiI19UlxDlOfpKdne3xNomINFQKcSIiIuJ1jiGuVatWNbrmlFNOMV/v2rXL420SEWmoFOJERETE69LS0szXNa3E9ejRw3y9Y8cOj7dJRKShUogTERERr6uyO6XVCnl5tr8dnHrqqeZrhTgRkROCqj9FRERE5OS4DXGpqbBmDWzbBsXFEBgI7drBOedAt240a9aMtm3bcvjwYYU4EREHqsSJiIiI11UIcb/8Am++Cb/+agtwAGVlcOAA/Pe/8NlnUFJidqlMS0sz15kTEWnqFOJERETE6xxDXLsdO+Drryt0n3SyeTN8+ik9HLpU7ty505tNFBFpMBTiRERExOvsE5v0BWJ+/bVmF23fzliLxdxUl0oRERuNiRMRERGvS09PpyUwJTycgACX3yEPHQoDB8K+ffDTT1BSYh7qm5NDIpCEQpyIiJ0qcSIiIuJ16WlpTAKahYc7H7jgApgwAdq0gTPOgKuvBoeQFxcXx3hsP7AoxImI2CjEiYiIiFdlZWXRMSeHDkBUVNSJAwMGwJAhzicnJsL555ubMTExtAsK4nS04LeIiJ1CnIiIiHjV9t9+Y3T5a3N5gdhYWwXOncGDbUsNABaLhcjISM4GcjMzvd5WEZGGQCFOREREvCrt669pVv46Pj7e9mLcOAgOdn9BQIBTwAsNDSUc6Jqd7dV2iog0FApxIiIi4j2lpVhXrTI34+PjbV0mu3ev+roOHaB8eYGQkBAABhQVUWpfU05EpAlTiBMRERHv+e03slJSzM1WrVrBmDHgsHRApYYNA2yVOIDmQN769V5opIhIw6IQJyIiIt5hGLBqlblGXER4OJF9+pjj3arVsSN06GBW4gBK163zRktFRBoUhTgRERHxjj/+oODAAXJycwFbFc5y1lk1v95igdNPNytxAGV//AHHj3u4oSIiDYtCnIiIiHiFZeNGjh49am6Hd+4Mp5xSu5v06EFARIS5WVxUBL/95qEWiog0TApxIiIi4nGBBQVYdu82u1ICBJ5xRs3GwjkKDuZ4hw7mZlFREfz6q62rpohIE6UQJyIiIh7XbN8+sFrNSlwJ0Pq88+p0r5yuXc3XxcXFkJkJhw55oJUiIg2TQpyIiIh4lmHQbM8eADPEbQV6DRxYp9tZOnQgo/x1UVGR7cX27SfZSBGRhkshTkRERDwrJYWQnBwAszvlwbg44uLi6nS76JgY7JHNKcSpS6WINFFB3rrxkSNHSE1NJS8vj+DgYJo3b05CQgJhYWHeeksRERHxA5atWwHIz88nLz+fTKBZ3751vl90dDTbgeGUd6cEyMiAtDSIjz/p9oqINDQeC3GrVq3im2++YenSpWzatIn8/Hy35yUmJnL66aczduxYLrzwQlq2bOmpJoiIiIivGQaW8q6O9irc70DfPn3qfMvo6GgOAdk4VOLAVo1TiBORJuikQtyRI0d44403eOedd0hOTjb3G1V0b9i7dy9JSUnMnz+foKAgzj//fO644w7GjRt3Mk0RERERf5CcDNnZwInxcFuAK3v3rvMto6OjAdgOjLZX4gB27oQRI+p8XxGRhqpOIe7QoUM888wzzJkzh+LiYjO0BQYG0rt3bwYNGkR8fDyxsbG0aNGCgoICMjMzOXbsGLt27eKXX34hPT2dkpISvvrqK77++mt69erFk08+yeTJkz36AYqIiEg9Ku9KCbZK3FEgHejtgRC3E5dK3OHDkJcHkZF1vreISENU6xA3c+ZMXnjhBfLz8zEMg/j4eK644gouu+wyhgwZQnh4eI3uk5SUxE8//cQHH3zAsmXL2Lp1K1dccQWnn346b775Jn1OotuFiIiI+IDVCtu2mZtpaWlsKX/tiRCXDOSXlp44YBiwdy+cxHg7EZGGqNazU86cOZO8vDxGjx7Nt99+y6FDh3jppZc455xzahzgwDY27uabb+bnn38mOTmZv/71r7Ro0YI1a9bw6aef1rZZIiIi4mspKZCba26mpaWxFWjXrh0tWrSo823tIa4M2B/g8qPLH3/U+b4iIg1VrUPchAkTWL16Nd999x1jx44lwPWbaR20a9eOxx57jP379/OPf/yDVq1anfQ9RUREpJ7t2GG+LCgoYH9hIZmcXBUOICoqynz9h+u4+z17tNSAiDQ5te5O+fXXX3ujHQBERkby0EMPee3+IiIi4kU7d5ovs7OzsUe6kw1xAQEBREVFkZuby/aSEueDubmQmgpt257Ue4iINCRa7FtEREROXnq67U+5rKws7JHOE+Pc7V0qD+bnQ2ys88GkpJO+v4hIQ+KxEDdq1ChGjRrFO++846lbioiISEPhUIUDSMnO5lD5a0+GuJycHEhMdD64b99J319EpCHxWIhbvnw5S5cupXPnzp66pYiIiDQULiFuzbFjAISEhNC/f/+Tvr1jiDM6dXI+uH+/bWZMEZEmwmMhLj4+HoDmzZt76pYiIiLSEBQUwIED5mZhYSGrMjMB6N+/P6GhoSf9FvYQZ7VaKWjd2vlgUZFtXJyISBPhsRDXr18/AHbt2uWpW4qIiEhDsHev0wyRB1NT2Vf++vTTT/fIW9hDHEAOQFyc8wnqUikiTYjHQtzNN9+MYRi8/vrrnrqliIiINAS7dzttbsnNxb4kt1dCXE4OuA7f0OQmItKEeCzEXXrppVx77bUsXbqUG2+8kby8PE/dWkRERPyVYVRYcHvFkSPma0+FuJiYGPO12xCXnKxxcSLSZNR6nbjKvPfee5x33nn89ttvvPvuu3zxxRdcdNFFnHbaabRo0YLAwMAqr7/++us91RQRERGpL6mptrXayhmGwdfli363bNmSrl27euRtHCtx2dnZMHCg8wlFRZCWBq7j5UREGiGPhbhp06ZhsVjM7WPHjvH+++/X6FqLxaIQJyIi0hC5VOEyDIM/ymemHDp0qNPPBiejQnfK6Gho3hyOHz9x0oEDCnEi0iR4dLFvwzDMP67b1f0RERGRBmjvXqfN3Q7/pw90rZadhAohDqBjR+eTkpM99n4iIv7MY5W4JA0oFhERaVpKSpyWFgA46hC27MsPeYLbEJeQAL/9duIkl7aIiDRWHgtxnVwX3hQREZHG7cABKC09sW2xcDQ83NyMjIz02FtVGuIcHTsG9q6WIiKNmEe7U4qIiEgT4toLp107souLzc2IiAiPvZXj7JTZ2dm2F/Hx4LqQuKpxItIEKMSJiIhI3biMh6NLF6clhjxZiWvevLn5+rh9MpOAAOjQwfnEgwc99p4iIv7KKyFu9+7dPP7444wePZo+ffrQtWtX/nCZvWrLli0sWrSIpUuXeqMJIiIi4k2FhXDokPO+xESvhbhmzZqZr7Oysk4caN/e+UTXNomINEIeGxMHYLVaeeihh3jppZewWq3mrJMWi4Vih+4VAMnJyVx44YUEBQWRlJREe9dvwiIiIuK/9u2zLfRtFxQECQn+EeKsVluVTkSkkfLod7g//elP/Pvf/6asrIx27doxefLkSs+dMGECiYmJlJWV8fHHH3uyGSIiIuJtruPhEhIgONgpxHlyTFylIa5dO+cTi4shI8Nj7ysi4o88FuJ++ukn5syZA8Bf/vIX9u3bx4IFC6q85vLLL8cwDH7++WdPNUNERETqg2uIS0wE8FolLiIigsDAQMAlxEVHg8OkJwCkpHjsfUVE/JHHQtybb74J2Cpsf/vb38xvtFUZOnQoAFu3bvVUM0RERMTbcnPh6FHnfV26AN4LcRaLxZzcxJzYxM61GqdxcSLSyHksxK1evRqLxcJNN91U42s6lM8olZqa6qlmiIiIiLe5VuFCQ80g5a3ulHCiS6VTJQ40uYmINDkeC3FHy38j17lz5xpfExwcDECp40KhIiIi4t9cQ1ynTuZEIvYQZ7FYCAsL8+jbOoY4w3FSFddKXGoqlJV59L1FRPyJx0KcvctEWlpaja85WL6WS2xsrKeaUStHjx7lvffe4+qrr6Zbt26EhYURERFBjx49uPvuu9m3b59P2iUiIuLX3KwPZ2cPcaGhoVgsFo++rT3ElZaWUlBQcOKAa4grLa3Y3VNEpBHxWIjrUv4NfNu2bTW+5ptvvgGgd+/enmpGrdx3331MnTqVDz/8kIiICCZOnMi5555LZmYmr7zyCn369OGHH37wSdtERET80rFj4DomrXxSEzgR4jxdhYNKFvwGCA8H118Ia3ITEWnEPBbixo4di2EYvPrqq1it1mrP37ZtG3PnzsVisTBhwgRPNaNWYmNjmTlzJsnJyWzevJkFCxawcOFC9u7dy5VXXkleXh5XXnklx44d80n7RERE/I5rL5XISIiPNzcdK3GeVukyA6BxcSLSpHgsxN19991ERkayZ88ebrvttirHuf3www+MHTuWwsJCYmNjueWWWzzVjFp5+eWXeeKJJyosNB4VFcWcOXOIjo4mMzOThQsX+qR9IiIifmf/fuftzp3BodukNytxVYY41y6VqsSJSCPmsRDXunVrXn/9dQDmzJlD165dueOOO8zjL730Erfeeiu9e/fm/PPP59ChQwQEBDB37lyioqI81QyPiYiI4NRTTwXgwIEDPm6NiIiIn0hOdt7u2NF8WVZWRmFhIeCDEOdaiUtLg5ISj7dBRMQfBHnyZtdccw3BwcH86U9/4sCBA7zxxhvmoOa33noLwJxNKioqinfffZcLLrjAk03wmJKSEnNik7Zt2/q2MSIiIv4gJwcyM533depkvszPzzdf13t3yjZtbBVB+6yVViscPuwUMkVEGguPVeLspkyZwh9//MHMmTMZNGgQgYGBGIZh/unduzczZszgjz/+4JJLLvH023vMnDlzSE9PJzw8nPHjx/u6OSIiIr7nWoULDXU7Hg7qeWITgJAQp7YAGhcnIo2WRytxdi1btuTxxx/n8ccfx2q1kpmZSVlZGbGxsebacP7s999/58EHHwTg8ccfp3Xr1lWeX1RURFFRkbmdnZ0N2Kp5JT7uymF/f1+3Q9zT8/Fvej7+S8/GNyx79mBxWH/NaNcOo6zMXJPNMViFhoZ6/PnYlzMCyMzMrHB/S3w8FofgZhw8iKGvkQr078d/6dn4t7o+H288T6+EOEcBAQHExcV5/L4PPfQQX375Za2ve+uttxg+fHilxw8ePMhFF11Ebm4uEydO5JFHHqn2ns8++ywzZ86ssP/7778nIiKi1m30Bi2V4N/0fPybno//0rOpX52//ZZQhxmb08LDyVy0yNx2XF81LCzM489n586d5uuNGzeyyOG9AVrs3Uv87t3mdlF6OvsawC+PfUX/fvyXno1/q+3zcexq7ikeC3H5+fn1GlgOHTrk9M28pnJzcys9lpqaynnnncf+/fsZN24cCxYsqNFCpTNmzOC+++4zt7Ozs0lISGDs2LHExMTUuo2eVFJSwg8//MCYMWMaRBW0qdHz8W96Pv5Lz8YHCgsJ2LABHH4x23XKFKcxcWvWrDFfh4aGevz5tGrViqeeesp8XWGJot69CSjvDQNAYCC9xo2DwECPtaEx0L8f/6Vn49/q+nyyHb8veYjHQlyLFi0YPHgw55xzDiNHjmT48OFO3R48bd68ecybN89j9zt69CijRo1i165djB49ms8//7zGg7JDQ0PdnhscHOw3/wD9qS1SkZ6Pf9Pz8V96NvVo3z4IcBhKHxhIYOfOEHTiRwnHoQVhYWEefz6OPXtycnIq3rtDhwqBLfD4cdukJ1KB/v34Lz0b/1bb5+ONZ+mxEFdSUsKaNWtYs2YNzz33HIGBgQwcOJARI0aYoS46OtpTb+dRaWlpjBo1iu3bt3Peeefx5ZdfemVAtoiISIPluj5c+/ZOAQ6cJzbx9uyUFSY2AQgLgxYtwKHLJ6mpCnEi0uh4bHbKZ555hnHjxhEVFYVhGJSWlrJu3TpeeOEFLrzwQlq2bMnQoUN58MEHWbhwoVfKinWRnp7OqFGj2Lp1K+eddx5fffUV4eHhvm6WiIiIf3GdmdKhG6Wdt2enrHKJATvXwJaa6vF2iIj4msdC3COPPMKiRYvIzMxk7dq1/N///R8TJkwgOjraDHW//PIL//rXv5g4cSItW7Zk8ODB3H///Xz11VeeakatZGZmct5557FlyxZGjx6tACciIuJOaSmkpDjvc7P+mrdDXFhYGCEhIYBCnIg0bR6fnTIwMJAhQ4YwZMgQHnzwQaxWK5s2bWLp0qUsWbKEFStWcPz4ccrKyti0aRObNm3ipZdeorS01NNNqdbNN9/Mb7/9hsViITY2lttvv93teZMmTWLSpEn12zgRERF/kZJiLiMA2BbVTkiocJq3u1OCrRqXlpZWuxBnGLY2i4g0EvWyxMCgQYMYNGgQ9913HxkZGbz88su8/PLLZGdnYxiGt5tQqczMTAAMw2DBggWVnte5c2eFOBERabpcu1K2bm0bf+bC25U4sC34nZaW5n5MHFQMcYWFkJUFDguFi4g0dF4PccePH2fZsmUsWbKEJUuW8Ntvv2EYhlN46+SmX319WLJkiU/eV0REpEFxndSkkv+366sSB5i/CK6wFFBMDISHQ0HBiX2pqQpxItKoeDzEVRbaAPPvzp07m7NWjhw50mchTkRERKphtcKBA8773IyHA+cFbb0V4mJjY8ubZWXJkiWce+65zidYLLZqXFLSiX2pqdCjh1faIyLiCx4Lcffdd1+llbbExESn0Naxkm/+IiIi4meOHAGH9d+AGlXivNWdcvLkyXz//fcA3Hrrrfz2228VJyVzF+JERBoRj4W4F198EYvFgmEYJCYmmoFt5MiRJLgZ/CwiIiINgOt4uNhYiIpye2p9dKe86aabePfdd1m5ciV//PEHL774IjNmzHA+STNUikgj57ElBuwsFguRkZHmn4iICE+/hYiIiNQX1/FwVfSmqY9KXEBAAK+//rq57XZ8u2uIO37ceYyciEgD57EQd/3119OpUycMw2DLli28+uqrXH755bRu3ZrTTjuNu+++m08//ZSMjAxPvaWIiIh4k2HUaJFvu/oIcQC9e/emeflEJdu3b694QlwcBAY67ztyxGvtERGpbx4LcXPnzmXv3r3s27ePd999l2nTppGYmIjValWoExERaYgyMyE313lfDStx9kW5vcFisdCrVy8ADhw4QE5OjvMJgYEQH++87/Bhr7VHRKS+ebw7ZceOHbnuuuuYM2cOf/zxB8nJybz//vvcdNNNdOnSxW2o69evn6ebISIiIifLtQoXFWUbE1cJe4gLCwsj0LUS5mE9e/Y0X+/YsaPiCa5dKo8e9Wp7RETqk8dDnKsOHTpwzTXX8Oabb7J7924OHjzI448/TkxMDIZhmKFORERE/IxriOvY0TaFfyXsIS4yMtKbrQIwK3EA27Ztq3iCayVO3SlFpBHx+mLfALt27TLXjVu6dCmp5bNE2WezFBERET9Uw0W+7eozxDlW4tyGuNatnbfT0mxr3gV4/ffXIiJe55UQV1loA5xC2ymnnMLIkSMZMWKEN5ohIiIidZWbaxsT56iadV7tIa4+ZqZ2rMS5ndzEtRJXUgLHjkHLll5umYiI93ksxL355pvVhrbu3buboW3kyJG0bdvWU28vIiIinuRahQsNrVjdcmAYRr1W4hISEoiIiCA/P999JS4qCiIjwWGyFY4eVYgTkUbBYyHutttuq9A9skePHk6hrXUV3/xFRETEj7iOh0tIqLIrYmFhofkzQH2EuICAAHr27MmGDRtISkqioKCA8PBw55Pi4yEp6cT2kSPg0A1TRKSh8mh3yp49e5qhbcSIEcS7dmUQERGRhqEW4+H+/ve/8/TTT5vb9RHiADPEWa1W/vjjD/r27et8QuvWziFOM1SKSCPhsRB39OhR4uLiPHU7ERER8ZXCwoqzOVYyHu7XX3/lsccec9pXH2PiADo5BMtDhw5VDHGaoVJEGimPTdGkACciItJIHDgAjrNHBwZC+/ZuT50xY0aFfePHj/dWy5y0cVgL7rC7xbxdh3FkZtomOBERaeC8Ps9uaWkpaWlppKWlUVpa6u23ExERkZPlOh6ufXsIqth5Z8mSJXz77bcAdOzYkeTkZPbu3cv1119fH610miDNcVI1U6tWzuvaGQakp9dDy0REvMsrIW779u1Mnz6dnj17EhYWRps2bWjTpg1hYWH07NmTu+++2/1MUiIiIuJ7ruPhKulK+fzzz5uv//rXv5KQkEBiYqI3W+ak2kpcSAi0aOG8T10qRaQR8HiImzFjBqeddhqzZ89m586dWK1WDMPAMAysVis7d+7k1VdfpV+/fvzlL3/x9NuLiIjIySgthZQU532VTGqya9cuAKKjo7n22mu93bIKqq3EQcVxcZrcREQaAY/OTjl9+nRmz55tTjHcs2dPTj/9dPM3Zampqaxbt45t27ZRVlbG//3f/5GXl8dLL73kyWaIiIhIXR06BGVlJ7YtFtvyAm6kl3dNjI+PJzAwsD5a56TaShzYxsXt2HFiW5U4EWkEPBbiVq5cyauvvorFYqFXr168+eabDBs2zO25q1ev5rbbbuP3339n1qxZXHHFFZWeKyIiIvXItStl69YQFlbhtNLSUo4fPw74bnKziIgIYmJiyM7OViVORJoUj3WnfOONNwBITExk5cqVVYayM888k2XLltGlSxcAXn/9dU81Q0RERE6G66QmlYyHO3bsmPm6ZcuW3mxRlezVuEorca4hLicH8vO93CoREe/yWIhbvnw5FouFRx55hGbNmlV7frNmzXj44YcxDIPly5d7qhkiIiJSV1ZrxRBXyXi4jIwM87UvQ5x9XFxubi65ubkVT2jZsuLMmqrGiUgD57EQZ+/GMGDAgBpfM3DgQACOqH+6iIiI7x09CkVFzvsqqcT5W4iDSiY3CQgA1+6e+rlDRBo4j4W4sPL+8nl5eTW+xn5uaGiop5ohIiIideU6Hq5FC4iOdnuqv4S4Gk9u4kiVOBFp4DwW4uzrwnz11Vc1vsZ+rn1snIiIiPhQDbtSwomZKcHPK3FQcVycKnEi0sB5LMRNmDABwzB45ZVX+Omnn6o9f/HixbzyyitYLBYmTJjgqWaIiIhIXRhGjRf5BudKnK9mp4STqMSVL4ckItIQeSzE3XvvvcTExFBSUsL48eO566672LhxI1ar1TzHarWyceNG7rrrLs4//3yKi4uJiYnh3nvv9VQzREREpC6OHQPXiUGqqMT5S3dKx0pcjWeoLC6G8uURREQaIo+tExcXF8eCBQuYOHEixcXFvPbaa7z22muEhIQQGxuLxWIhIyOD4uJiAAzDICQkhI8++sin3/xFRESEilW4yEiIja30dH8JcY6VuEq7U0ZHQ3g4FBSc2Hf0qG3Mn4hIA+SxShzA2LFjWbNmDYMHD8YwDAzDoKioiMOHD3Po0CGKiorM/YMHD2bt2rWMHj3ak00QERGRunA3Hs5iqfR0fwlxjpW4Q4cOuT/JYtG4OBFpVDxWibPr378/69atY/369fz4449s2bKFzMxMAGJjY+nTpw+jR49myJAhnn5rERERqasaLvJt5y8hrmXLlkRGRpKXl8eePXsqP7F1a+dqo2aoFJEGzOMhzm7IkCEKaiIiIg1Bbi44hDKgyvFwcGJ2yoiICMLDw73VsmpZLBa6d+/Opk2bSEpKori4mJCQkIonqhInIo3ISYe4hQsX8u2337J//37Kyspo164dI0eOZMqUKQQHB3uijSIiIuJNrlW40NCKMzq6sFfi/GFcuz3EWa1W9u7dS48ePSqe5PrxZGRAaSkEee332SIiXlPn71xHjhxh0qRJrFu3rsKxt99+myeeeILPP/+cvn37nlQDRURExMtcJzVJSICAyofNG4bhdyHObteuXe5DXKtWzttWqy3IVRNWRUT8UZ0mNikrK2PixImsXbvWnKjE9U9SUhLjxo1zWgxURERE/FAtx8Pl5ORQWloK+F+I2717t/uTwsKgWTPnfepSKSINVJ1C3IIFC1i/fj0Wi4VTTjmFOXPm8Pvvv7Njxw4++ugjzjjjDMBWrfvnP//p0QaLiIiIBxUWguvU/A1kUhM710pcpdwt+i0i0gDVOcQBdO7cmXXr1nHDDTfQu3dvunfvzmWXXcby5csZMWIEhmHw0UcfebTBIiIi4kHJyWAYJ7YDA6F9+yovcQxxcXFx3mpZjXXr1s18XWWIc53cRCFORBqoOoW4TZs2YbFYuP/++2nevHmF44GBgcycOROApKQkcnJyTqqRIiIi4iWu4+E6dIBqJiZzHCrhD5W4Fi1a0Kp8zJtCnIg0BXUKcWlpaQAMHjy40nMcj2lcnIiIiJ9yDXHVLC0A/tedEk50qTx06BC5ubnuT3INccePQ1GRdxsmIuIFdQpxBQUFAERFRVV6TkREhPm6sLCwLm8jIiIi3lRcDIcOOe/r3Lnay/w5xEEVk5vExVWcdVPVOBFpgOoU4mrLcOxrLyIiIv7hwAHbVPt2AQG27pTV8McQ17VrV/N1UlKS+5OCgsC1vQpxItIA1UuIExERET+0b5/zdvv2EBJS7WX+NrEJQCeHbqDJrksmONK4OBFpBOq82DfA7NmziXf9ZljH85544omTaYqIiIjUVh3GwwEcPHjQfO0vlbiODssiVBniWreGrVtPbGutOBFpgE4qxL322mtVHrdYLDU6DxTiRERE6lVJCaSkOO8rD3GGYZj/h7s6duwY3377LQCxsbEkJCR4tZk1VeMQ564SZxhQyccrIuKP6tyd0jAMj/0RERGRenbwIJSVndi2WMiNjeX000+na9eu7N271+1lH3zwAUXlMzped911BFezHEF9ad++PQHlk5bUKsTl50NenhdbJiLieXWqxC1evNjT7RAREZH65NqVsm1bFnzxBevWrQNsYe2xxx4zD69fvx6r1cqcOXPMfTfddFO9NLUmgoODadeuHQcPHqw6xLVoYVsHr6TkxL4jR6CKGbfFe7Zs2cKLL77IFVdcwZgxY3zdHJEGo04hbsSIEZ5uh4iIiNQn10lNOndm2QcfmJuHHJYe+Pbbbxk/frzT6YMHD6Zv377ebGGtdezYkYMHD3LkyBEKCwsJCwureJLFYqvGOXYlPXoUHGa3lPozYsQIMjMzmTNnjnpnidSCZqcUERFpakpLbd0pHXXqxLJly8zNw4cPm69/+umnCrfwpyqcneO4uIOuH58jzVDpNzIzM83XpaWlPmyJSMOiECciItLUpKTYgpydxcLBgACn9dVSU1PN13/88YfT5QMHDuTaa6/1ejNryzHE7XftLupIIc4vFRQU+LoJIg3GSc1OKSIiIg2Qa8Bp3Zql5WPh7NyFuJCQEHJzc/1mMhNXmqGyYSsoKCA6OtrXzRBpEGpdibv77rudulh42scff8z8+fO9dn8REZEmz2E8XHFxMdktWjh1pQRbd0rDMLBarezZsweALl26+G2Ag1quFeeopASOHfNSq6Sm8vPzfd0EkQaj1iFu1qxZdOnShbvuuqvS6Ydrq6SkhP/973/07duXK664gl27dnnkviIiIuKirAwOHAAgKyuLf//73wy7+mrefPNNp9OKiorIysri8OHDZje3U045pd6bWxs1DnGRkRAR4bxPXSp9Tt0pRWqu1iHu2muvpbi4mNdee41u3boxbNgwZs+e7dTtoiZKSkr4+eefufnmm2ndujXXXnstW7duJTExkfPOO6+2zRIREZGaSEkxp9f/5ZdfKCgsJMlqdXtqamqq03g4fw9xncoXK4dqxsTZZ6h0pBDncwpxIjVX6zFx7733HnfddRePPfYYP/74I2vWrGHt2rVMnz6dhIQEhgwZwoABA4iPj6dFixa0aNGCgoICMjMzOXbsGLt27WL9+vX89ttvFBcXA7aFw1u1asXjjz/ObbfdRlCQhuqJiIh4RXkvGqvVyubNm0kFHDuxBQYGUla+CPjhw4fNrpQA3bp1q8eG1l6zZs2IjIwkLy/PaYkEt1q3dl5m4cgRr7ZNKnKdjVIhTqTm6pSWhg4dyvfff8/69et58cUX+fTTTykqKiI5OZkDBw7w6aefVnm94zoggwYN4tZbb+Xqq68mMjKyLs0RERGRmiqfgXLv3r1k5+SQBAwbNoyoqCiOHTvG2Wefzb/+9S+g4VXiLBYL7dq1Y/fu3dWHOFXifM41tCnEidTcSZW8hgwZwn//+1+ys7P54osvWLx4McuXL3f6rZ2riIgIzjjjDM4++2wuvvhi+vfvfzJNEBERkZoqLjbXh/v1118B2As898ADXHLJJQB84LDgd0MLcYAZ4rKyssjLy6v8F8SuIS4jw7bsgnoD1ZvCwkKnbU1sIlJzHvlOFRMTw3XXXcd1110HQFpaGgcPHiQtLY3MzEzCwsJo1aoVrVq1okuXLuouKSIi4gvJyVBWRkFBATt27MAK5LVsyQUXXGCe0qZNG/O1Y4gLCgpymjjEX7Vr1858ffjw4cqDp2uIs1ohPR0cPn7xLtcQp0qcSM15JU3ZA5uIiIj4kfLxcHv37qW0rIyDwJRrryUkJMQ8pW3btubrQ4cOmSEuMTGxQfwS1jHEHTp0qPIQFxoKzZvD8eMn9h09qhBXjxTiROqu1rNTioiISANVPh7ueHlwsY+Hc+RYidu8eTN5eXlAw+hKCRVDXJU0Ls6nNCZOpO4U4kRERJqC/HwoXw4oKysLsI2Hc+0i2bx5c0JDQwH4/fffzf0KceJpGhMnUncKcSIiIk3Bvn1QPjt0VlYWJUAKFUOcxWJxqsbZde3a1ftt9ADX7qBVat3aeVvLDNQrdacUqTuPdW4fNWpUra+xWCyEhYXRrFkzunXrxhlnnMG4ceMICFC2FBER8ajy8XBgC3HJQEBwsNvA1qZNmwqLZZ9zzjnebqFHnFQlLisLiops4+XE6xTiROrOYyFuyZIlWCwWDMPAYrE4HbOvC1eT/a1bt+af//wnV111laeaJiIiIuXj4cAW4vYCHTp0cPuLU9dg16tXrwazJFCtKnFxcRAQYJuZ0u7oUUhI8FLrxJHGxInUncdC3DnnnIPFYuHw4cPs2rULsIWzLl26mDNVpqWlsXfvXjPode/endatW5Odnc2uXbsoKCggNTWVa6+9lgMHDvDQQw95qnkiIiJNV1aWbR00oKioiILCQpKA7pUsGeAYhACuu+66Cr+I9VdRUVHExMSQnZ1dfYgLDISWLSEt7cQ+hbh6o0qcSN15rN/ikiVL+Mtf/kJaWhqxsbG89NJLpKens3v3blatWsWqVavYvXs36enpvPjii7Ro0YK0tDRmzJjBpk2byMrK4sMPP6RDhw4YhsGjjz7Ktm3bPNU8ERGRpsuhCpednU0BkErF8XB2rpW4q6++2ouN8zx7l8pDhw5RWlpa9cmtW1NWVsbBgwcpKSnRuLh6pIlNROrOYyFuz549TJ48GYvFwurVq5k+fTotWrSocF6LFi24++67Wb16NRaLhSlTprBr1y6CgoK4/PLLWbZsGc2bN8dqtTJ79mxPNU9ERKTpchkPtw8wqDzEuVbdGsIi347sIS4vL4/g4GDmzJlT+cnx8Xz++ee8NWcOCxYsUIirR6rEidSdx0LcCy+8QE5ODo888gjdunWr9vxu3brx0EMPkZubywsvvGDu79y5M3/6058wDIPFixd7qnkiIiJNk2G4HQ8HlYezCy64wHz9wQcfeLN1XtHaZdZJx58zXBXHxvL7li0A7P7jD1I3b2b9unXmuH3xHo2JE6k7j4W477//HovFwtlnn13ja0aMGAHAjz/+6LTfPtNlSkqKp5onIiLSNKWlQU6OuZmVlYU90lUW4gYNGsSiRYv45JNPuPLKK+uhkZ7VoUMHp+0dO3ZQVFTk9tzfXCpvr7/0EmNOP52//vWvfP3118ybN0+BzktUiROpO49NbFLt4OEqpJYvPmoXXz7lb2XfcEVERKSG/vjDaTM1P5+M8tdVdZMcP368FxvlXeeffz7PP/+8076dO3dy2mmnVTh3+ebNFADhDvvaAE899ZS5bRgG1113nVfa2pRpTJxI3XmsEte8eXMAVqxYUeNrli9fDkCzZs2c9ufl5QHQsmVLzzRORESkqdq922nzd4cfnBMa6SyMo0aNYuvWrdx1113mvi3lXSZdrVq9GtdRcC5LgHP99dd7toECqBIncjI8FuLOOussDMPgH//4B0kOfe8rs3fvXv7v//4Pi8XCsGHDnI5t3boVqNinXURERGqhqAiSk512rT9+HLBNNBYdHe2DRtWPXr16MW7cOHPbXYgzDIOVK1eS6rK/4vLnkJGR4WavnAzX0FbtTKIiYvJYiLv33nuxWCxkZmZyxhln8Prrr5OdnV3hvKysLF577TXOPPNMMjIysFgs3HfffU7nfP31127DnYiIiNRCUhKUlZmbVouFNeVjwBrajJN10adPH/O1uxC3detWDh8+zBGgRfPmREVGAhUrcQBffPGFl1rZdLlW4socvlZFpGoeC3HDhw/nmWeewTAM0tPTufPOO2nZsiWnnnoqw4cPZ/jw4Zx66qnExcVx1113kVa+sObTTz/NWWedZd5nz549LFy4EMMwvN4fPzs7m8cff5wLLriArl270qxZM0JCQmjXrh0XX3wxCxcu9Or7i4iIeJVLV8qsZs3IK692NIUQ17FjR6KiooATvXzsUlJSuPDCCwHbmnkDBw7kgQce4MorriAWCHG512effeb9BjcxrnMfKMSJ1JzHJjYBePjhh0lMTOSee+7hyJEjlJWVsXv3bv4oH1TtOLtTfHw8L774YoVZr7p27Vpv5fSjR4/yt7/9jaioKPr06UO/fv0ICAjgjz/+4Msvv+TLL7/kjjvu4NVXX62X9oiIiHiMYVSY1CQlIsJ83RRCXEBAAL1792bt2rXs3buXvLw8IsurbTNmzGD//v0AtOrZk8Gnnw6cGMoRDxx0uNeOHTvqs+lNgmtoU4gTqTmPhjiAKVOmMGnSJD7//HN+/PFHtmzZwrFjxwBb//vevXtz3nnncckllxAaGurpt6+VNm3asHr1agYPHkxQkPOnYvHixVx44YXMnj2biRMnOvWrFxER8XtpaZCV5bRrXfn/x9A0QhxghjiAbdu2MWTIEKxWK9988w0A0dHRfPfTT4R/9hkcPWpO1NYG5xBn70EknmO1Wp22NSZOpOY8HuIAQkJCmDJlClOmTPHG7T0mKiqKM844w+2xc889lyuvvJK3336b77//XiFOREQalvKulPZeMPuOHePON980Dw8YMMAnzapvXbp0MV+npKQwZMgQtmzZQnp6OmD7/75t27bQujUcPYrFYgFOjIsLDw+noKCArKwsiouLCQlx7WgpdaVKnEjdeSXENRb26pyvK4YiIiI1lZubaxsH9scfJCcn87///Y+CwkI2WiwUlge6a665htGjR/u4pfXDcbmizMxMAH7++Wdz36hRo2wv2rSB338H4IIJEzi4aBGDBg2iXbt2fPXVVwCkp6fTrl27emp54+daiVOIE6k5j01sUpnS0lLS0tJIS0trUGXy9evX8+GHH2KxWLjooot83RwREZFqzZgxg+joaO657TbYv5+ffvqJgvIZAHeWB7gxY8bw9ttvmxWnxs4xxNmXCVi8eLG5zwxxDssaDRkyhBcefJA1q1Y5LXekLpWepRAnUndeqcRt376d2bNn8+OPP7J7926zK4fFYqFbt26MGTOG2267jV69ennj7evkiSeeIDk5mYKCApKSkli/fj0hISG8/PLLnHnmmb5unoiISJUMw+C1114D4Ps33mDr5MnsL18jLjg0lLDERKacdhpvvfVWk+oSGBsba77OzMyktLSUJUuWABAXF0fv3r1tB9s4rw7XPCICcnKIi4sz99m7YIpnaEycSN15PMTNmDGDF154AavV6jQbJdj+g9m5cye7du3itdde48EHH+SZZ57xdBPq5Msvv2Tz5s3mdlRUFP/617+48cYbq722qKjIaZpc+/p4JSUllJSUeL6xtWB/f1+3Q9zT8/Fvej7+S8+mopSUFLLKJzLphvOU+AMmTeKh9983t739efOn5+O4oHl6ejo7d+40/58ePnw4ZWVltgpQaCgBYWGQl2eebz1wwCkEHj582C8+ppPlL8/H9f3Lysp83iZf85dnI+7V9fl443l6NMRNnz6d2bNnm+GtZ8+enH766bQp/+1Wamoq69atY9u2bZSVlfF///d/5OXl8dJLL9X6vR566CG+/PLLWl/31ltvMXz48Ar7f/31V8AWwHbu3MmLL77Irbfeyvz58/n888+d/hNw9eyzzzJz5swK+7///nsiHKZz9qUffvjB102QKuj5+Dc9H/+lZ3PCpk2bzNenAKXlXdMCLBYs3buzaNGiem+TPzwfxy6Q27Ztq7Dem+PnpUNqKpGpqeZ2xpdfklI+jg5g6dKl5s8DRUVFvPbaa+Tm5jJ9+nSaNWvmrQ/Ba3z9fFIdPtdg+5z64uvUH/n62UjVavt88vPzPd4Gj4W4lStX8uqrr2KxWOjVqxdvvvkmw4YNc3vu6tWrue222/j999+ZNWsWV1xxRaXnVubQoUPs3Lmz1u3Mzc2t8nhMTAxDhgzhv//9L82bN2f27NnMnDmTF154odJrZsyYwX333WduZ2dnk5CQwNixY4mJial1Gz2ppKSEH374gTFjxhAcHOzTtkhFej7+Tc/HfzXlZ5Oens79999Phw4d+Nvf/maObdtdPhtlPOD4P0+vXr0Yfdtt0KpVvbXRn55Pbm4ut9xyC2CbPdtxaYVhw4YxYcIEc9sSGopl5Upz+5SOHckcMMD8ZXN8fLx5/jXXXGN2y8zIyOCqq67y9ofiMf7yfN544w2nbYvF4vQ8miJ/eTbiXl2fj73670keC3H2f4iJiYmsXLmyyt9InXnmmSxbtoxBgwaRlJTE66+/XusQN2/ePObNm3dSba7ODTfcwOzZs/nss8+qDHGhoaFuZ7AMDg72m3+A/tQWqUjPx7/p+fivpvhs7r77bj7++GMARo8ezdixY4ETi1F3ByyAfUBD/5EjCW7bFnwwkYk/PJ/mzZsTHBxMSUkJx44dc6rMJSQkOLcvIQECA09sp6XR1j5mDtuYuuDgYDZt2sRHH31k7t+zZ4/PP8668PXzcR12U1ZW1iA/j97g62cjVavt8/HGs/TY7JTLly/HYrHwyCOP1KhLQbNmzXj44YcxDIPly5d7qhkeFRkZCcDRo0d93BIRERFYsWKFGeDA1r3Pbtu2bQD0ACZMmECAxULPHj3oOn68TwKcv7BYLOYMlZmZmRw+fNg81rZtW+eTXbfz8ogPCzM37RObvOmw3h5AQIDXJ/tulFxno9TEJiI157FKnL1fc20WDx04cCAAR44c8VQzPOqnn34CoHv37j5uiYiINHVWq9Wp6z7YhjKAraKxdetWooBe5cMCBg8ebOtq2aOHD1rrX2JjY0lNTSUjI4NDhw6Z+yus+daiBYSFQfmyDACtHIKFvYp38OBBp8tycnK80OrGz3V2SvukeE1l+QuRk+GxXx2Flf+mKs9hVqfq2M/11WLaH3zwARs2bKiw3zAMPv30Ux577DEAbr311vpumoiIiJM5c+awfv16p33r1q2juLiYlJQUsrOzORXbuC2wVaAIC4POneu/sX7GPsNkfn4++/btM/dXqMRZLBWqceHHjxMeHg6cCHGu68XVNcSlpKTwzTffNNmZCF1DXGX7RKQij4W4xMREAL766qsaX2M/t0uXLp5qRq18//33DB48mISEBC644AKuueYazj//fBITE7nsssvIysrizjvvVIgTERGfKSkp4cEHH3T6v6hbt24AFBQUsGnTJrZu3QrYulK2cpzApFs35zFeTZTjgt/2z1VUVBRRUVEVT3YNdocPm59Te3hzXS+uLiGuuLiY008/nQkTJvCPf/yj1tc3Bu4Cmxb8FqkZj4W4CRMmYBgGr7zyitkNsSqLFy/mlVde8elMRLfccgt33303bdq0YePGjXz00UcsX76c0NBQpk6dyvLly5k1a5bK+iIi4hOGYXDFFVc4Ta51ww038Oc//9ncXrlyJdu2bSMUSOREJQ5QV8pyjmu92WeJq9CV0q6KEJeRkYHVavVIiNu+fTspKSkAPPHEE7W+vjFwF9g0Lk6kZjw2Ju7ee+9l1qxZ5OTkMH78eG699VZuvPFG+vfvbw74tVqt/Prrr7z99tv85z//oaSkhGbNmnHvvfd6qhm1ctZZZ3HWWWf55L1FRESqs2fPHnNds+DgYF544QWmT5/O77//bp6zcuVKWrRowSlAIA6VuMBAOOWU+m+0H3IMcXYVulKeOOC8nZNDxxYt2IDt55gjR46Yi6qfOKX2IU4VJ1XiRE6Gx0JcXFwcCxYsYOLEiRQXF/Paa6/x2muvERISQmxsLBaLhYyMDIqLiwHbbxdDQkL46KOPnLo5iIiIiM3atWvN13/5y1+4++67AejduzcxMTFkZ2ezcuVKEhMT6Vl+nhniEhPBR2PO/Y27nzMqrcS1bAkhIVD+8wpAl4gI8/X27dsrXFKXNaBcg2BTpBAnUncenRN37NixrFmzhsGDB2MYBoZhUFRUxOHDhzl06BBFRUXm/sGDB7N27VpGjx7tySaIiIg0GmvWrDFfO66nGhgYyJlnngnYZnjetG4d3YHmzZoREhJiO6lnT8SmVpU4N5ObdC2f2AROjKlzVJdKnGuIa4rdCBXiROrOY5U4u/79+7Nu3TrWr1/Pjz/+yJYtW8jMzARs30T79OnD6NGjGTJkiKffWkREpFFxrMQNHTrU6dhZZ53Fd999B0AXq5VgoE2bNraDAQEaD+egViHOdhD27zc3E4JO/Ljk2JXVLicnp9ZT47uGuPT09BPPr4nQmDiRuvN4iLMbMmSIgpqIiEgdFRYW8uuvvwLQo0cPmjdv7nT8vPPOMyfE6AV06tjxRO+Wzp0hMrLe2urvatWdEipU4to6hDN3Ia60tJSioiJzuaWacA1xR44caXIhTpU4kbrzWogTERGRutu0aZO5ftgZZ5xR4fiwYcN4+eWXObB3L/eWltLOMaj06lVfzWwQ6lSJc7w+IIAIIB/YsmWL20tycnJOKsSlpqbSr1+/Gl/fGCjEidRdrUNccnKyN9pBx44dvXJfERGRhshxPNzpp5/u9pzp06fD9u3w4YcndlosGg/nwjXERUZG0r9//8oviIuD4GAoD9FRUVG0A/4AcnNzzdOio6PN8XA5OTnOa/RV4/jx407bR44cqfG1jYVCnEjd1TrE2Rf19iSLxaI+0CIiIg4cx8O5q8SZXCfaUFfKCuLi4ggKCjJ/1pg3bx4tWrSo/IKAAGjXzhwXFxUVRQdsIc5Rly5d2Lx5M1D7GSrddadsatwFNoU4kZqp9eyU9tklPf1HRERETrBX4iIiIujTp4/7k4qKYOdO533qSllBREQETz/9NKeddhoff/wxkyZNqv6i9u3Nl2FhYXQOqvh77y5dupivaztDpbvulE2Nu0qcfqkvUjO1rsS988473miHiIiIlEtNTWV/eRVo8ODBBLkJEIAtwJV3+QNsFSSFOLceeeQRHnnkkZpf0KGD+dJisXBqVBS4dIF07J10siGuKVbi1J1SpO5qHeKmTp3qjXaIiIhIuXXr1pmvq+xK+dtvzttdu6orpac4VOIA4iIjiT1+nMzy7eDgYNo7nKMQV3sKcSJ159HFvkVEROTk/eYQzgYNGuT+pLw82LvXeV/fvl5sVRMTEwPR0eamfVycXVxcHNEOx9WdsvY0Jk6k7hTiRERE/MyOHTvM170q6x65ZQs4VjKCg7XAtydZLE7VuKioKBxrcx07diQmJsbcPtkQl5mZWcmZjZfGxInUnUKciIiIn9m+fTsAAQEBdOvWzf1JrotO9+gBISFeblkT4zAuLjo62qkSN2XKFKdK3MnOTum63RSoO6VI3SnEiYiI+BGr1WpW4rp06UJoaGjFk9LS4OBB532nnVYPrWtiHCpxERERtOHEZALXXnttrbpTFhcXs2HDBqxWKyUlJRQUFDgdz8vLa3JVKIU4kbpTiBMREfEjBw8eJD8/H4CelS3a/euvztuRkeAw3b14SLt2tm6V2BYIDwDaYKvKxcfH1yrETZ48mcGDB3P77bdXWnWrbTWvodOYOJG6U4gTERHxI/aulAA93I1xKyuD8gWmTf36QWCgl1vWBIWGQqtWAJxyyim0jI3l1IgIFi9eDOAU4lJSUrj22mu54447KC4udrpNaWkpX331FQBvvvlmpSGuqXWpVCVOpO5qvcSAiIiIeI/jpCZuK3F//AG5uc77BgzwcquasA4d4OhRQkJCuPPOO7mjd28Cy2cMdZzYZOHChebruLg4nnjiCXN9v5SUFKdbKsTZaGITkbpTJU5ERMSPVFuJ27TJebtDB7NaJF7gMC4uICCAwEOHzG3HSpyjp59+mqioKJ577jkAc+F2u2PHjrm9rql1p1QlTqTuFOJERET8iGOIq1CJy82FXbuc96kK510JCc7bWVm2P0BYWBgRERFuLysqKuLll18GYN++fU7Hdu7cab5u1qyZw62bViVOY+JE6k4hTkRExI/Yu1O2adOG5s2bOx/ctKni2nC9e9df45qiVq0gPNx5n0NlrXXr1pVempKSgmEYFSpxS5YsMV+fffbZ5uusrCzKysq46KKLOPXUU53CXmOkSpxI3SnEiYiI+InMzEyOHj0KuOlKabXCL7847+vdG8LC6ql1TZTFAh07Ou9zCGVt2rSp8vKsrKwKIc4+MQrAyJEjnc796aef+Prrr9m1axcTJkyoe7sbAI2JE6k7hTgRERE/UeWkJrt3m934TEOG1EOrhE6dnLeTk82XrpW45s2bc/XVV5vbaWlpFUJceno6AB06dOCUU04x92dlZTl1qdy7d+9JN92fqRInUncKcSIiIn6iyvFw69c7b7dr5zTphniRa4hLS4O8PKBiiIuPj6eVw0QzR48erRDi7AYMGOA0w2VWVpY5o6VdY65MaUycSN0pxImIiPiJSmemzMy0LS3gSFW4+tO2LYSEOO8rr8a5hrhWrVoRHx9vbh85cqTSEDdw4MAKE5vYF3q3a8zj4lSJE6k7hTgRERE/sWXLFvO1UyVu7VrnE8PDoU+femqVEBBQcZbK8mDmOiauVatWTpW4LVu2VFj8265///5OIS47O7tCiNvkuqREI6IxcSJ1pxAnIiLiA3v27GHYsGFMmzaN0tJScnNzzVkL27RpQ3t7V8mCgoprw/Xvb5uZUupPJZObVFeJqyqEde3atdpK3MaNG+vaYr+nSpxI3QVVf4qIiIh42htvvMHq1atZvXo148aNIzg4mKKiIgAmTZqExWKxnbhhAzhWcgIC4PTTfdDiJs51XFxqKhQVVTsm7rfffqv0lgkJCURGRprb7kLc77//fhKN9l/uAhwoxInUlEKciIiIDziOk3r99ddPVN6ASy+91PairKxiV8pevcB1/TjxvvbtITDQ9kwADAMOHKi2O2VlM0xGRkbSrFkzLBYL4eHhFBQUuA1xu3fv9uzH4ScU4kROjkKciIiIDxw6dMh8vWzZMsLK13tr3rz5ibXDtmyBnBznC888s55aKE6Cg21BzmF5Afbto/UZZzid5tqdsjIJCQlmtTUmJqbSEJecnExhYaH59dFYKMSJnByNiRMREfEBxxAHUFhYCMCFF15IcHCwrdKzYoXzRZ06aVkBX3LtUrlnD1FRUU674uPjiYmJsT3DKnTo0MF8bR8Xl5WVRV750gV2hmGwZ8+ek2i0f6osxGliE5GaUYgTERGpZ4ZhVAhxdpdccontxfbttvXIHKkK51tduzpvHz5srhdn16pVKywWS7XVOHchLicnh9zc3Arn7tq1q44N9l+VVdxUiROpGYU4ERGRenb8+HGz8uYoPDyccePG2apwS5c6H2zdGk49tZ5aKG4lJFRcL85lzFuLFi0AnMbFub/ViSULmpePcTQMg9TU1ArnXnrppSxatKjC/j179rBw4UJKSkpq0nq/MXv2bK688kq3xxTiRGpGIU5ERKSeOVbh+jis9zZ+/HjbbIU7d8KRI84XnXMO2GesFN8IDITOnZ337dnDI488AkC3bt3MCWpcQ1xcXJzTtmMlrmXLlubrAwcOuH3rqVOnYhiGuf3GG2/Qs2dPLrzwQl544YVafyi+kpSUxJ133snXX3/t9rhCnEjNKMSJiIhUYseOHTz55JMsXbrU6Qfok+UY4i666CJmzZrFlClTePnll91X4Vq1ss1KKb53yinO23v2MPOpp/jmm29YsWIFgYGBAE6zjQK0bdvWaduxEucY8JIdJ05xkJ6eTnp6OgCrV6/mtttuMytw9vUFXaWkpHDdddfZvq78RHVdQzUmTqRmFOJEREQqcfXVV/PXv/6VkSNHMmzYML788kuPhDnHENeuXTvuvPNOPvzwQ9sP/lu32sZaOVIVzn+4jovLySEkK4vzzz/faRzc8OHDnU5zXYrAMdQ5hjh7N1uLxcJpp53mdI19WYpnnnnGaX9lE59cf/31zJs3j3vuuYcdO3ZU9VHVG3cTmlgcvrZViROpGYU4ERERN0pLS50Wal6zZg0XX3wxs2bNqvK6P/74g7Fjx3LHHXdUGvhcQ5yprAx+/tn55Lg46N279h+AeEdsbMV1+tyEqPPOO89pu23btnR1CIAdO3Y0X7t2tQSIiIjgo48+cupqmZyczNatWyt0RdyzZw/PPfdchclyfnb4Wtq+fXvlH1M9OnbsWIV9IQ7jDBXiRGpGIU5ERMSNlJQU8wfKgIAT/11++OGHlV5TVFTE5MmT+eGHH3jttdfYtGmT2/MqDXEbNkBmpvPJ550HAfrv2m9YLBWrcW5CXGeXsXPNmjXjk08+YcKECbz++uvExsaaxyoLcd27d+fFF1809yUnJzNnzhy3zXr44Ye57bbbKm12eHh4pcfqU6br1zc4LcegECdSM/pfQURExA171zWA6dOnc0r5WKh169ZVWJDZ7oknnmDz5s3mdkpKitvz3Ia4oqKKY+E6dIAePerSfPEm1xC3bx+4mSHSPlMlQG5uLv369WPhwoX86U9/cjqvshAHzhW7PXv28N///hewVa+uueYap2u++uorRo0axQcffFDhfgF+8ouA6kKcxsSJ1Ix//IsWERHxM/v27TNfJyYmMnLkSABKSkpYvXp1hfOXLVvG888/77QvIyPD7b0dQ5w5VmrZsgprjjFmjMbC+aPEROfnUloKSUkVTps/f775+qabbqr0djUNcW+//TZHjx4FYOLEiQwcOLDCdYsXL+aaa66pMPasoKCg0vevT+pOKeIZCnEiIiJuOFbiOnXqZIY4gKUuFbPi4uIKU8AD5myCruwhrlWrVrYfYNPTwTUYdu8OnTqdxEcgXhMeDg7hCrAtzu5i7NixLFy4kEWLFnHWWWdVeruqQlz79u3NKppjBfjSSy8lMTGx0nu6jo/zlxDnrhKnECdSe0G+boCIiIg/cg1xjut+uU7pvnTpUrNyFxcXZ4Y3d5U4q9XK4fLZJ9u3b29bUmDRInCsnAQGwrhxHvpIxCt69ACHrxF27rQ9Q5duixMmTKj2Vo6Tl9jZQ1xwcDDt2rXj4MGDTsfbtGnj1F3T1e+//+607c8hTmPiRGpPlTgRERE3HLtTdu7cmQ4dOpizC65du9bph+Jvv/3WfO043sldJS4jI8Nc36tdu3a2Cs7evc4nnXkmuPnBXvxIz57O2/n5UMkab9UJCwsjKirKaZ89xIFzl0q7Fi1aVFmJW7t2rdO2QpxI46IQJyIi4oa9EhcdHU3z8inlR4wYAdi6Tzr+kPzdd98BtskjrrjiCnO/uxDn2M2tU3y8rQrnKCbGti6c+LfmzcFlAW93XSpryrVLpWOI69ChQ4XzW7RoQbNmzXj66afd3q8hhTjH7pSa2ESkZhTiREREXFitVpLLqyqdOnUyFyN2HBdn71J54MABtm7dCsDpp59Ot27dzHPcdad0DHFn5+dDbq7zCePGgcMPteLHXKtx27fbusfWQVUhzrErr529K+Vjjz3GO++8U+G4v4a4YxkZ9AcuB64CzgKigk6M7lElTqRmFOJERERcHDlyhOLiYsAW4uzslTg4MbnJ999/b+4bN24cYWFhREZGAlVX4roD3Vxno+zWDXr18sjHIPXAdfmH7GxwmVCkpmoT4gIDA4mOjja3W7duXeF+rrNAVhfiDh8+zLhx47jpppsqzGzpMfn5XJSZycVAL2z/BkYDUzIzsX/0CnEiNaMQJyIi4sJ1PJxdx44dzXFIq1evprCw0Gk83Pnnnw+c+IHcXSUuJSWFCOBCcPpBnLAwuOgiLSnQkLRqVXHsYh27VNYmxDVv3tysDoP7EOequhD34IMP8v333/P222+7XWfupJWWUjZvHu3dhLRmhsG1QATqTilSUwpxIiIiLlxnpnRkr8YVFRXxxhtv8MMPPwAQGxvL4MGDgROzDWZkZFSoahxKSWESEI1LiBs3zjYeThoOi6Vil8otW+rUpdI1iFUV4lxnpfREiPvwww/N18uXL6/2frW2dCllDr8ccRQSEkIz4Hwgz7U6LSJuKcSJiEijl52dXWHdrKpUFeImTZpkvr733nvJysoCYMyYMQQGBgInqiplZWXmcbuYrVuxj5ozQ9wpp0D//jVun/iR3r2dt48fh0rCSlXOO+88p217l1yoPsTFx8dXe//qQpzj+3k8SKWlwcqVTlW2AiC7/LU9sPYFgurYHVWkqVGIExGRRi01NZX27duTmJjI/Pnza3RNZd0pASZOnMj9999f4ZpxDuu6OXaNc+pSefAgXcqXE7BQ/oNzVBRMmqRulA1VmzbgWgn79dda38Y1xDl2l6wuxDlO0V+Z6kKcY+XPcVFxj1i2DKxWM8SVAe8CbwKF2CpxQeW/AOnqsh6eiLinECciIo3aDz/8QG5uLsXFxUybNo3Vq1dXe01VlTiLxcLzzz/Pww8/7LTfMcQ5Lt5sTm6SnQ3z55OXkwNAVFQUAYGBcOmltiAnDZPFUrGKum0bFBXV6jYhISE0a9bM3M4p/zqB6kMcwA033FDl/QsLC93uT09PJzc313uVuPR0WxdTTkxasgo4AuQBS7AtzREeHg5AyMGDLP/oI8+9v0gjpRAnIiKNWmpqqvm6qKiISZMmOYU0d+zHw8LC3HZVs1gsPPvss/ztb38jMjKSO++807Zwd7kKlbiSEvjf/zBycsgtX1IgOjoahg+HLl1O6uMTP3DaaRDg8CNVSQmULztRG99//z1BQUEEBARw5ZVXmvtbukye4i7EvfXWW+zYsYP//Oc/bu/trhK3adMm2rVrR0JCglNodDchT50tX26OESwtLaUIW4iz2wAUh4SYIQ7gmSlT2LNnj+faINIIKcSJiEijdvjwYafto0ePcuGFF1ZabTAMw+xO2bFjR6dubY4sFguPPvoo2dnZzJo1y+mYY4hLP3oUPvsMDh+mqKgI+5QXx1q0gHPPrdsHJf4lMtK2PISjOnSpHDp0KFu3bmX79u3069fP3G8fa2nnLsQFBARw6qmnVjrJibsQd9NNN1FSUsLx48c5cuSIub8240erlJ0Nv/9ubpaWlrIOWxdKcx9wqE0bp+6cfYH/zZvnmTaINFIKcSIi0qg5VuLs3dK2bNnCe++95/b8jIwMc0yQ63g4dwICKv5X6lg5iVm+3Na9DlslECAD2Ny9u3P1Rhq2AQOct5OTbV0Ja6l79+507969ynPchTg7dwuDg/sQt6+SCViOHDlyUlP9//TTT1x55ZX8/t574DA7a4nFgrvOzIdbt3aqxEUA3eq4aLpIU6H/PUREpFFzDHHzHH67v2zZMrfnVzUerqbslbjRQMzu3eb+oqIiCoH/AeGxsXW6t/ipbt3AoZoEwJo1Xnkrx8DjqjYhzqgkKFmtVqfKXG3dcsstLPjwQ96ePp2vvvrK/OVFVseOuJtepSgykgKXdrc7erTO7y/SFCjEiYhIo2bvThkZGcmoUaPMbluVTXDiiRDXMjaWUcBZOM/0V1BSwgJslTjHSSykEQgMhIEDnff9+it4Yd2zMjcLZttVFuK2bdvGqaeeypgxY/juu+/Yu3dvhTUMHaWkpNSpbSUlJSQlJXEK0AzYsHEjK1asACC9kn9PAQEBHE9MdNoXnpIClUzGIiIKcSIi0sjZK3Ft2rQhKCiIIUOGALaw5m7sT1XLC9SIYdDh9985u3zTDHEWC/sGDSKpfL9CXCM0dKgtzNmVlsL69R5/m6qWFHBaQN7Frl27+PHHH7nooou4//77q1x2wHV9w5pKS0sDYJDrvdq1I8thBkxHgYGBHIiOxjGalhUXg0MVW0ScKcSJiEijVVBQwPHjxwFbiAM488wzzePuqnEnVYkrLYXPPqPZzp3mLjPEXXwxhxyCm0JcIxQTA337Ou9bt842W+VJ+vDDDwFbSLvqqqsqPa+yiXhcVdaV0q6yJQmqc+TIEaIBx1F9ZWVlMGiQ2a3SVUBAAMcLCtjrsK+0tBR27KhTG0SaAoU4ERFptBzH9bRt2xaAYcOGmfvchbikpCTzda1CXF4evPce/PYbwcHBBAcF2XYXFMDEidC/v1N1QyGukXL4JQEA+fl1mqnS1eWXX8769evZsWNHlRObeEp1i4NXJjU1lYHYFrO3K7RaoU+fSoNhQEAAl112Gdsd9pWUlNgqcScxwYpIY6YQJyIijZbj8gL2StwZZ5xh7nMX4raVzyQZERFB+/bta/ZGhw7Bf/5jm5GwXEREBFbgY6vVHCvlGOJiYmJq/HFIA9K6NZxyivO+FStOuhpnsVgYPHiw03qENeFuncOaqGslLvXQIVzm6WR3WBiEhlZZiRs/fjztzz3XXIKjtLQUioth716314g0dQpxIiLSaDnOTGmvxLVq1YpTyn/I3rBhg9MPlvn5+ewt/6GxV69ebpcPcGIYsGoVzJkD5d027YIjI5kPrDh+3Oy6lp2dbR5XJa4Rc6j2ApCVBWvX1tvbf/TRR4SFhXHZZZfRu3fvOt2jrpW4ou3bcf3K3hoWBlQeDAMDA23rLj7zDAfK95lLHKhLpYhbCnEiItJouavEwYlxcUVFRWzatMncv2PHDjNwVfvD7/HjMG8efP89uM4W2KwZy7t1Yze28UD2Cpy6UzYRiYm2P46WL/fKTJXuTJ48mePHj/Pxxx8TVh6gwLa+3B133FGje9S1Ehe6davT9mHAPn1QVZU4gLCwMOyRzQxxu3fbflkiIk4U4kREpNFyV4mDysfFbXX4AbTSEGe12qpvr74Ke/ZUPJ6QALfcQqBDV8yMjAxAIa7JsFhg7FjnfUVFsHRpvTUhNDQUODFbJEBiYiKXXHJJja6vUyUuN5fIAwecdm0ENm7cSPfu3XnooYfcXmYPceHh4dinBCqxdz/NyQGHX8aIiI1CnIiINFqOIc5dJQ6cQ5x9PBy4CXGGAbt2wWuv2apvrmOcLBY4+2yYNg2iomjZsqV5KD09HVCIa1LatoV+/Zz3/fJLvQcS1yUzIlwXJK9ETStxJSUl3H///dx3332UbthAXk6OeazUYuF3oLi4mN1VLBfgWInLxLaOYqnjhCa7dtWoLSJNSZCvGyAiIuItjt0pHStxffr0ISoqitzc3OorcYYB+/bZqigOPxA7iY6GSy6BLl3MXXFxceZrVeKaqFGjYOvWEzMsWq3w2Wdw660QVD8/gtl/gQC2EBceHl6j62paiXvzzTf517/+BcDE/fvN64KDgtgTHk6RQ6irTGD52nr2tu0ChrmGuJEja9QekaZClTgREWm07JW4gIAAWrVqZe4PDAxk6NChABw8eJAD5V3A7CEuKiqKjh06wPbttklL3n238gA3ZAjceadTgAPnEOdaiQsJCXEaqySNVLNmcNZZzvuOHoWff663Jtx+++3m64svvtjjlbj58+cD0AnYuWoVxcXFgO1rfEcNA6N9bTvHEFfiWOk+dMjWrVJETKrEiYhIo2WvxMXHx5u/7bcbNmwYP5f/ML1s2TIuueQSkpKSaAZc3aEDlhdfrPoHx7ZtYfx46NjR7eGqulOqCteEnHOOrZLk2I1y9Wro1q3i5Cde8OSTT1JQUECfPn0455xzzF9YVKemlbiQkBAAzsA2iY89xOWGh5NRw8BYVj4xkP0XG8lAvtXqfNKuXTBoUI3uJ9IUqBInIiINVmZmJn/6058YNWoUZ555Jv369eOGG26guLgYq9VqLvbtOB7ObtSoUebr7xYsYP9HH3GDYXAvMDY0tPIA16wZXHqprUtcJQEOqu5OqRDXhAQG2rraOnafNAxYsAAcujp6S+vWrXnnnXe4//77AaqsxDVv3tx87VqJO+6wVIajkJAQWgCn4hzi/mjenNAaVpvt49+Cg4MJDAzECiS5/NJF4+JEnCnEiYhIg/Xiiy/y5ptvsnjxYtasWcNvv/3G3LlzmT9/PhkZGeYPh47j4QAoKeHs9u25tFkzbgNOXbSIvI8+IqH8sNsFkps3hwsugOnT4bTTbBOZVMG1EmcYhrlOnBb6bmLi423j4xwVFMB//1tvyw7YVRXiEhISzNeOlbh//etftGjRgt69e7Nq1Sqna0JCQjgDsGDrAllaVkYhcCAuzpwhszplDkt02Ktxu13/fe3de9ILpjdUn3zyCVOnTmWH1swTB+pOKSIiDdbaShZQXrZsGQMGDABsP1x2bd4ctmyBlBQ4eBAOHSKorIxpXbuyYeNGSkpLnSY4cRw/R4cOMHQo9OkD1S3+7cC1Epefn2/+sKpKXBN05pmwfz/s3Hli37FjtrUGr70WIiPrpRlVjcW89NJL+f333wHnStx7770HwPbt27n66qudZryMtFjoXP7aHvw2AmExMRTXsE2OM1GGh4eTl5fHzrIySq1Wguz/5kpKICkJunev4V0bh/z8fCZPngzA0qVLnT730rSpEiciIg2SYRj8+uuvgK27ZG56Ou2CgugJFH3/PdaPPuJPwF+ASQcOwMcf28YiHThgLs7dq1cv834ZmZnm67iOHWHwYLjtNrj5ZlvlrRYBDpxDXFpammambOosFrjsMmjXznn/4cO2yXOOHaunZlgqzFDZpUsXrrnmGu69915zn2MlLiUlxXy9f/9+3n//ffLKK4hdDx0ipPxYSWkpVmAttsmBTqYSt23fPu78xz+clv1oil0qjx8/br7ev3+/7xoifkchTkRE/MLx48d5/vnnWb58+YmdpaWQnQ2pqbbuVFu2wPr1WJYuJeLHH5lw7Bh3AM/GxBD5yivMbN2a/2/vvsObqt4Ajn/TPelglAJllL333lOmgAzZQ1wI/AQ3ogKKiqIiCMpeIiAbFZAlyl4FBAEZsguUUejevb8/Qi7ZTduUrvfzPH1I7j335CSXm+TNOec9fYGyN24Qe/gwRdEOOfHy8jL7mKVLl8b98ZfGOOAU8IunJ76ffAJdu4KZuXS2cnd3x9vbG9AmWJEgTuDiAgMGaIfm6gsPhwUL4NKlp9IM4yGVhw4dYvny5QbXia4nLiEhwWCZAoAhQ4YwatQoiIig5ON5pzr/AJGkL4gz7olT60pKYvWaNU8KXrignU+YjxislyeEHhlOaSQ6OpoaNWpw5coVAG7cuEGJEiWyuVXiqbHnh4MtdaWmGv7llHZlR132rs8edSUl4ZCUBPHxas9NpuW052hcX2rqk3/1b2dkW0qKNggz96e/LykJEhLYumwZl3fsIMzJiRrvvIOPu/uT9bWMaFJScPz7b8o9vh/0eA5bUFAQNx/3Guj/gq8Lpgw4OOBYogSOLVuyaNs2bgIK0LBaNTR2WsOrRIkSnDt3jtDQUAnihJaXFwwZAsuWgV4vCzEx2qGVDRpA27ZgYwCUER4eHmqyHXiS0MTJyQlHR0dSUlLUIE63TIexpUuXsqRnT5L1hl2mArsf3/b09MxQT5x+EHcBaK9fMDISwsIy9eNKbmNrllCR/0gQZ+Ttt9/OO+ONV63C4d9/ufmHF599uxcHK0OBNJj/MhjoHc2IuifNflncdbkMB29kIMBVFHzcEhjT8IjZ3YduFGfXlWCz+8zVpc/ZMZV3mu43W/RUWAC/Xcj4WPq3mhzAxdH0i/x/4X6sPlM1Q3WmKgrtfX/F4fhxbQYzPbejvFj6d60M1QswpObfFPM2za4XEe/KD8fqWz3W0v8HgF5VzlHOP9xke1KKA98cbJz+hj7WufxFqgfcNbvv20ONSExxNLsvLS1LXaVhiVCz++aF1CUi3vKXjFQllfv34zk7Zz8OGsPrp37xW7QqfdXscctP1eBOtPmen7RULXyXTuXN/xq/4VwlLj/0y1C9Zfwe8Vzlc2b3bbtUljP3zCTysEGAZzQDa5w2u2/vtZIcvVXcwpEawPnxn/ZL28FDTYikGiTDZ+v9+eJ589khQ24F8ufVIE5f9OI29QCIi6zJqYNFCYsrwwkaaeu7+eSY1GsN8IsLwMm/AGNeiIHixSEoCFxdqVq8ODe2bQMqAx2Ahnz7bTpfCOC117QdLfqKFy/OuXOxxMZ254cfXID/AfDvv88wY4b1+jQa7d+QIdqEmMbu3YN1656U0z/GltudOoH+1D+d2FjYtCl9dWk02tGmDg7aUah6OV1UigJ79jwpp3+MLbcDAkw7sHQePdKWdXR88ufkZNjWHMXfH0aM0CY2MQ6SjhzRLhDeqhXUqWPy2WAP+vPiPD09cXZ2Vu+7u7sTHR2tBg+3bt0yW0cZgBMn1GyUACHAo8e3MzucEuA+YDLI9Pz5fBXE2bpen8h/JIjTs2PHDubMmcPo0aOZNWtWdjcn8x7/Eq6kQgpp/Whv/lMuJQWLPRCpKQrJKRn5dNRoj7PQoFRFQ1KK/Uf6piqaDAcCadWbkJKxSyk1NRXFwmuvoCE+OeOXqKXzndl6UxXL5zwu2dnivrQkp1o+57FJzhk+d2nVG5PkYnF/amoqccluxCS6mPwIYq09cUlORCdartcaa+cmLtmZqMSM/Tofl2S93siEjNXr5WI5dUF8spPN9SqKwoNoB1LRZm28eP0hiuKoLgKsLyHFiYh4Nx7EOJHA4+jGLYCIBDccPAKJ5AqxQAyo/1aq0waHgACcnYGWhvW1bdsWHx8fIiJcAF98fEobdJBkhnYkx1XAj6tXIwC/x8/X1+YpUJY66ZOSTL//p0dCguV69XNvpFe5cuaDuJQU2L3bdLutunWzvEzY3LnaZI/GjAM7c39162oDT3OOHtW+Tk5O4Oz85E9338VF22Hm6qq97eycjqDR2xuGDYP1603nesXEwObN2qi3bl1tMGfHjKb6wyl9jSJjNzc3oqOj1eDBXBDnAnRHm40y4fF/pCRgj16ZtII4jUajLllgaTglaHvjDDdcgJbai/jSpUtMmDCB9u3b8+KLL1p8rNxMeuKEJRLEPRYZGcmIESMoU6YMU6dOzRtBnBBCmKEoCvv37ycuLs5grbTsFBcXR6ryJFqJiY0hNDTqyXB2jQbc3cHDAxIDILwgVxMTiQAUJ2daNmoEbm64uLpy4fx5wsMfGNTv6We5B9PFxYXu3buzbNnfgIXlBTKoePEnPZH37t1Tb1vLEGjMUlCQ2dG0WVWvpUEf1kaMZ6ZesDzaWVGejNq1JDbW8r7Dh9O3lJtG8ySoq1ULWrc2X+7iRW3Q6e7uhkeL/rgXOYH73u24EW94XqKi4M8/tX9BQVCpknaB8KJF051oR59+EGe83IUuiNIFD/pJTXS6AT5op6DogrgdQLReGXNBXMeOHdm+fTtjx45l5syZavCmH8QZXxsmvyeEhkJ0NHh50bdvX06cOMHq1avp0aMHhQoV4vPPP2f//v3MmDGDsmXLWn8hcgEJ4oQlEsQ9NnbsWG7evMnOnTvxfEppfoUQIjucPn2anbt2AY+/sBWycTiwuTF0zs7a1Oj6Y990/4b7wSPvJ+PhrPyFXb/OBbSjBlLQzq2ZlZDA1NGjtYGbm9uTL60HIDYxmn8StV8egwID0egFaUFBQQZBnIuLKy7G4xyNfPDBB+zb9x6OjhUoU6aMba+HDfTnVOsHcbYOM7Mmq/I7ZFUQl1X1QuamrDpbGUCQ3mXJFEU7hTY+HhKt5Nffvx+ezNzQAHUgrhKay//h9ugO7s7JuDsl4eGchJdLIp4uSXjdTMQr5G8KeRykaKFk7ULzRYs++fPzs7kb0FFviKbx/0VdEGWpJ+4ZoNrj2xEREaSkpnIFOGr0GF5eXiYB2Zdffsm6devw8PBg9uzZavCmP5zSOOnKNUBxcUGj/4L++y/Uq8eJEyfUTdevX+f+/fu8//77gHYu37Fjxyy9BLmGBHHCEgnigM2bN7N48WJefvnlHPOrtF107Ehqs2YULbqXZxtUMBjzbsLCG7+TowKFzM+fahCpoWqshQ+MND5IHByAIrXN7qseraFUlNHx6ZnUEFjd7ObyMfBihEP663vMqWhVs/lcS8RrGBGesV9Ek5KSOPtPa1KfaYuj7vw8bluhRBhxz3K9aX0hKlS4Orhi8ly9kuGFOxn/BbdwoZq6KUwGHFNheJ+M11vQvxZYmEY28DmNxWGnafHzrQ0Wckj0uqmx+gt9UnIye/fto3nz2jgbJbrwKVAH/M0f1/mWxuJQtbT+73l5AYW7mN3X+o6Ghsa9Bjb+X/bwAIo+A8DrrVurX7h+v3OHX+Z3o3oUhpObzN0281guLkBQR7OPWfs+lHlkU/OYPn0jt/9crrclmTm/PmLivHm4u7uTnJzMlf/+o2zZslSu7EDVqieBnwBo2XIwAwfqtymJv//+Sb0fGFiagQPHA5ZfrvLly3PixLpMDU80lwtF2xN3G1jJw4dOgPY/3DPPtKV5c8t16a5vRbG8fJi/P/Ts+aSc/jG23LaUW8XN7cm61LbWpZ/TxlK9Go22I8lcPhxrt3X3LcW9ipJzgjh91n43MPu93MMDpVp14h4FEXflCuglwtFXtfBd+nid1Q4r1B+G6eLC2YSyRLkVxifQA58S3viU9MG9mB8aTw+D//z689iMf+DQBV664EG3bpwb0N/Li5LRT/rbwsPDSQA2mWmnucQmfn5+apDm5OSk9uLpB3HGwztTgYSgINz+++/JxtOniatq+OPTvXv3DOoJCQkx06rcxziIUxTF7DBzkf/k+yDu4cOHvPTSSwQFBTFt2rTsbo59+fuDtzfOJbwIrBVgPYjLAJ+iFr8bZ4p3AJjJI5dpno//7M0d7SiXjEhKSuJ0qDcUKmTyTcIFCArMdPNMOAEl7TdaTOUAlDIzD8YeSvlmTb1BafwHTkpK4txNhTLVvdJ1/RS339QVA4F2uDBCQkL4U+/X6cNnzhCecINKNSplvnIjhQpp/2wRGvoXoP2S1qJFC/bs2UNEBGzcuJFatWrRq1cvzp07x7hx4/jmm2+4f/8goE0A07p1CcqXf1LXc89VZ8KEJ8lhSpUqZrDfkgIF7DrtCND1xMUAFwwCjWrVnKlYMXN1e3hAzZqZq8Mcd3do0SJzdZgLflxcoF+/zNVryQcfaAM54z9dIlRLf8nJ2rXcLSlfXhtwJSU9SaSq/5eYaDmAtNbZarVzxdcXatfWDhkMDdVmsNH7tcniPNTERE6cduJiuAMQ//jvHs4OKfh4peBT0Anfws74BzgTcMePchQmiocUcHLSRsKPAwPdcMr4+Hh+37qVI1u20BJo5ODAW0OHsm7dOm4//rXjQXg4awBz4aa54ZR+ej3mTnq/eugPpzQO4gAiS5UyDOKuXePfI4bJ0e7cuUNAQID51yYXMw7i4uPjTeYNivwp3wdxo0eP5vbt22zdutVkXLitEhIS1F+TQDu/DrRfAJMy8zOeHegeP7vbIcyT85Oz5cXz891335lsW7VqFRMmTMiG1jyh+7Xf09OTDz/8kPbttYnFJ06cyO3bt4l+/Ov/jBkzGDFiBMePH1ePrVatmsE5Cg4OpmDBgmoK9SJFimTbObQ0v87DwyNP/b8ylh3Xjm50bkZ+r7TUzK5d0z42OVkbzCUkPPlLTNQmd7FUr7+/BmdnDXFx2oDO7IgAd3dtlpjgYHj0CM2DB/DoEW6O8QY9TvoexrmQajT5MCFVw91HTtx9BPyXBCSRfK8NxR9ncS10zolFvX6hQlAcjSuG0/3RI6qg/SExdMwYRj2up1H9+vj5+dGiRQt+Xr0aBdjs6sp/mOfm5mYQqAE4Ozur/ye6dOnCihUrAKhTp4663dyajncLFCD+7l1C//uPGjVq4Obmxs2tWw3K3Lp1y+THttx4jRlfO7pF1XUiIyNNXlfx9GT0vS0r/i/m2v8F77zzDr/88ku6j1uwYAHNmjUDYP369axYsYLhw4fTsaP54UC2+Pzzz5k8ebLJ9u3bt5uM7c4uO3bsyO4mCCty2/k5cOAAR48e5bnnniMoo92QuUhuOz+WREZGsnLlSkD7BUs352Xx4sXUrm1+eHNGxMTEsH//fmrXrk1hcznsjcTFxXH58mVAO/wwOjqagIAAwsLCuHjxokHZ1NRURo4cybVr1wDt3J7r169z+/Ztg3Jly5ZVg7j4+Hi2bNlij6eWbqmpqTg5OZks2BsSEqKuR5qX5ZVrJyOM/usa8PPT/ukkJ2tITHQkMdGRhAQHEhOdSEhwICHBkfh4J+I9nYh3dCK+gAdnyhZHcYvB7eFDXB89wu3RIxwfX8uXQ6uQmGppLLf+4z35/xid5M7xC0nE37tBobAQCkZGouvru3vjBgAPKYNjwXqcPneVmIhw4oF1QPLj69acU6dOmSzZtFUv8OrYsSMXLlzA09OTYsWKqdeouWyYmzZv5sgPP1AbuHjxIg0aNCDcqO5Dhw5x43F7dSZNmqQGfbmN7toxnte3efNmCppL/yqeqvS+t8Vay6CUQbk2iLt16xbnM5ADWfdr7v379xk5ciTFihXjm2++yVRbxo8fzxtvvKHej4yMJCgoiA4dOmS4d89ekpKS2LFjB+3bt7f7cEqRebnt/CiKwueff86XX34JaIevnDhxwuoahLlZbjs/aZk+fbo6F+all17i2LFjHDx4kOvXr1O6dGmqVKlil8fp3LkzO3fupEiRIoSEhKQ5xOnw4cPq7WbNmtGlSxdeffVVgx/Hnn/+eXbt2sX9+/fZt2+fOiekSpUqdO/e3aTOs2fPcuTxcKtGjRrRuXNnezy1DClRooTJl9mePXvm6SRaee3ayVkqA+2e3FUUiI4m5c49Gm2EiLB4Iu4lEv0wmdS4BLNpQfXnVLm6uuLv70+14IeUDyrPiRMn1OGSCY/fLx5492BvVFeIAueCDszEjzhu4XTzHtrZcqZrmel603/66cn8VOPrsJ+Z8bX3799n4cKFBttcXFw4BdQGLl+5wsCBA7l16xYlAN1ykIcOHaJOnToGx3322Wf07t1b7fHLDYyvnbNnzxrsb9KkSZ7IuplbZfS9TTdKz55ybRC3fPlyli9fnnZBC/bt28fdu3cpUaIEPXr0sFiuT58+uLq6MmzYMIYNG2a2jKurq9lMY87OzjnmwysntUWYyg3nJyUlhddff53Zs2er286dO8eWLVvoqcuukEflhvOTltTUVObNm6feHzVqFL///jsHDx4EtHPPatphgtW+ffvYuXMnAHfv3uW1115j06ZNVifinzv3ZBHyWrVq4ezszMiRI5k3bx4PHz7kyy+/ZPTo0UyfPp0333wTRVHU9aV05Y0NHDiQzz//nKSkJLp3756t5884iHN0dMTHxydfJCfIC9dOruDvj7O/P331fodJTYWoiFQibkYScT2SiNuxhN9OIDwsiT+PRJGECy6Ag4MDDg4OFPZMwNHR0eR8KUCiVxkcgoKgaFES3N2J2/gnUEVvGOhDIBS4AVwHwvD19TXpAbPl/4K5Xqb4+HiuPn4UP7TXUEpKCvV5EsTdvXuX33//3eTYtWvXsmrVKoOMnLmB7tpJNEpzmpycLNdUDpDe97asOGe5Noizl5s3b3Lz5k2L+w8dOgRAq1atnlKLhMh5EhISGDJkCKtXrzbZN2XKFHr06JEvvpDmZtu2beO/x4kB2rVrR8WKFfHy8mLs2LEArF69mokTJ2b6cT799FOD+7/++isLFy60uhDvqVOn1NvVq2uzywYEBHD16lXi4+PVEQ0jR47kq6++Mhg6WatWLbN1lixZklu3bpGQkJDtQ4/014oD8k0AJ7KXgwP4+Dng4+cL1X0N9h1Mms+8eYvR4MfHw76gVf2KFCsVCC5xnDt2jC1nzpAERAF38aFO+WpUeZwdyAkoUMCHyEj9dCZ+lC5dh6tXdUOEk9i+PYCzZ4sARYC7NrfbXGKTsLAwQLuMQYfH25KTk6kKbAPSGqh24cIFKleubHMbchLjxCay5IDQyZtjoGzQo0cP9ddcc386N27cQFEUJk2alH2NFSIbRUVF0aVLFzWAc3R0ZMmSJeqwlePHj7Nt27bsbKKwgX4P6qhR2lQFxYsXp2nTpoB2+OGZM2cy9RjHjh1TfwnX/yI2duxYNYA0R5fUBJ4EcaAdQqU/JN3d3d0kAYulIA60CRKyO4ADw7XiwHRxZSGeto8//piGDeswdFhnxn8+mGZ9AvFpUBFq1eJ2yZIcBU6izRcbhRvlynsaLKFh7rrq0qULDRs2okSJINq06cjt2x6cPx8IlEpX26wFcSfRLtKhKApJSUk4Ag1tqDMkJISZM2fywQcfmCQKyekkiBOW5PueOCGEZXfv3qVTp05qJkB3d3fWrFlDly5d8PLyonfv3oC29yUzyYFE1rpy5YqaNCAoKIiuein3+vbty/79+wFYs2YNVR+vvZSQkMCFCxd49OgRjx49IiIigoIFC9KhQweLw5L0e+GmTp1KSEgI8+fPJyYmhiFDhrBnzx6TYxVFUYO4YsWKpRl0vfjii3z55Zdcv34dBwcHatSokc5X4+kz1xMnRHby9/dn/PjxdO7c2eSaNE1fH8bIkY7UqqVd7eD2bTh6NJorV0KBAMAJZ2cXChYsaPI5oM3Id91sGxQFQkKgdGltJk9d57S560PX+x4H/INh9u9GwKHH+yx5/fXXCQ8PB6BUqVK89NJLVkrnLLoEVJbui/wr3/bECSGsu3z5Mk2bNlUDOD8/P3bt2kWXLtqFqHv27KkOT9m3bx979uzJtrYKy1JTU3n99dfVEQavvvqqQXrqXr16qUP7Vq9eTWhoKBMmTKB48eLUqFGDFi1a8OyzzzJ48GA6d+5sdokC0Pambdy4EdAGY8OGDeObb74hODgY0GY0/eGHH0yOu3XrlvrlSr8XzhJXV1eWL19Ow4YNGT58eK4IiIx74nJDm0X+Za6nuGjRojg6QtGi2iXs2rdPBBYAnwNzKFXqb+rU0WD8G4xGk4CloZR378Jvv8GsWfDdd7BtG1y9CgUK+JqU1R9CvQ+IiY1VM2y6AE3M1D9//nz1tu49BrSZw3MT6YkTlkgQJ4Qw8ffff9O0aVMuXdIumFyiRAn27dtH48aN1TIODg6MHz9evW88F0rkDO+//z6//voroB2mZPwLdPHixdVlV86dO0epUqX47LPP1PT8xtatW2d2+2effabefuedd3B1dcXLy4tly5ap2zds2GBynKWhlNY0b96cvXv30q1bN5vKZzfpiRO5ibkgznhbRXWl+lQgjKpVE+jeHcaMgbfeguefh8aN4aWX6uHgoP2RaNOmTQZ16K9OEB4OBw/CkiUwb54P8BxQFW2IhkHuggfAg2LFDNbdagT469Xt5uamDhU3ltuWxZEgTlgiwykt0J8XJ0R+kpiYSLdu3bjzOMV05cqV2bZtm9kPvv79+zNx4kSuXLnC9u3bOXr0KPXr13/aTRYWLFu2jC+++ALQzmVcs2aN2XXb+vbty969ewHURYSdnJx49tlnKVOmDL6+vnz//ffcvn2bo0ePkpCQYJCR98KFC/z8888AFC5c2CBQbNq0KUFBQdy4cYPDhw+TnJxs0BOoH8TlhqGRGSE9cSI3Mf7/qdFoTJbDMF6ORH9uqpcXVK6s/YMAatY8zv3792nTpo3BMZaWmEtIcACqP/5LBi6RmPgPcAHQBm5XS5UiUW+tOyegG7D08X1fX19cXFzM1p/bgiAJ4oQl0hMnhDCwefNmdcHUunXrsnfvXou/XDo5OfHuu++q9/V7Y0T2OnjwoEEwNWPGDNq1a2e2bJ8+ffD29ga0CQsmTJjAtWvXWLduHV999RUffPCBemxCQoI6xFZn8eLF6g9fb7zxBh4eHgb7mzTRDnaKiYkxCNrAfGbKvCYwMNAgG6UEcSInM+51K1CggMlaoKVKleL999+nfv36vP7662qWW3Nq1qxJ27ZtTTKy+vlB2jl+nIBKQG/g7cf/VuJmXBInjZZ2Ks2TYZU+Pj4WgzhJbCLyCgnihBAGFi9erN7+9NNP00w0MWzYMIoVKwZo1xr7559/srR9Im3Xr1+nR48e6vpCr776Kq+99prF8gEBARw9epSNGzdy48YNpkyZop5THf2hSbpEKDo7duxQb7/wwgsm9euCONDOjdOnC+ocHR1zbQrwtDg7OxsseC5BnMjJzAVx5nz66accOXKEb7/91mxGybR07gzjxsErr0CrVhAY+GTfwIGDKFu2nNERzmiHWD7Pb78VZa+TE4+MSrQDyqHtiTO3fi9AbGxaCxLkLMZBmyQ2EToSxAkhVHfu3FGzGJYoUcJiz40+V1dX3nrrLfX+559/niVt2759O5MnT+bevXtZUn9eoSgK/fv35+5dbTKB1q1bM3PmzDTXJatYsSLdu3c3k5lOy1IQ9+DBA7VnrlatWhQpUsTkWEtBXFJSkrrQd4UKFSx+6coL9OfFSRAncjLjoC0r/79qNNrgrVUrbTA3bhx06QIdO5Zj6NBBeHp6mT3Oy+smkfHx/Ip2MXK1PuB5oLKzs8WeuNwexElPnNCRIE6kKTk5mX/++YeEhITsborIYsuXL1fnRA0ZMsRiKnljL7/8MoUKFQJg1apVakIUe7l58ybdunVj0qRJtGrVSgI5K9avX68GSsHBwaxZswZnZ+dM11ulShX11/b9+/erwyf/+OMP9baloL9mzZpqcKgfxO3Zs0ftLdStO5hX6c+Lk3XiRE5mHLQ9zf+vPj5Qvz4MGqRNkFKkyEG0q9WlGpTz8LhIXFwcl4E/jOqII5AO4Y9wMxq6rZNWEBcWFsZ3331n98+xjDLueZMgTuhIECes2rVrF7Vq1aJ69eqULVuWOXPmqF+6RN6iKIrBUMphw4bZfKynp6c6JyI1NVVNpmEvGzduVP/fnT17lmeeeYZHjx7Z9THyguTkZIPFsGfMmGG3xa4dHBzU7KT37t1Tv+Ds3LlTLWMpiHN2dqZBgwYAXL16lVu3bgGwdu1atUz37t3t0s6cSnriRG7xNHvirHF3h2LFwoDlwNfAb8BV4DJJSXfVYGYfoJtZm4A3x3mRXZFDObLwPL1xxzgEtRTEnTlzhnv37jFkyBD+97//5Zjst9ITJyyRIE6Yde3aNXr37k27du04c+YMAKGhoYwcOZKKFSuyaNEidY0WkTccOXKEs2fPAtoU7uXLl0/X8aNGjVI//JcuXaomR7EH49T0J06coFOnTkRHR9vtMfKCxYsXc/78eUB7DnVr+tmLuSGVuiDOxcWF5s2b23TsgQMHSElJYf369YB2ceFOnTrZta05jf58v9KlS2dfQ4RIg61z4p4GPz+/x7digRC0+Sd/YuvWrQY/5G1EG8jdoi4KDiTgxx9Xy/GAN2hHD+pTDN14BHOJTTZt2kS1atUoWbKkuo7cv//+S2pqqknZp02COGGJBHHCQFxcHJMnT6ZSpUoG60GVLFlSvX316lVGjBhB5cqVDYbfidxNvxdu+PDh6T7e19eX0aNHA9q5Tl999ZVd2vXgwQP++usvQNuboUuRf+jQIZ599ln5QHssNjaWiRMnqve/+OKLNOfBpZdxEHf58mUuP84T3rRpU5OslPqM58Xt27dPnbfXqVMnvLzMz33JK4YPH86YMWOYMmUKjRo1yu7mCGGR8XIC2dlz7O/vb2ZrKqGhoQZbFGADDhykLsCTZUw0LjygJh68RBuGU5MKJETHcOTIEVq3bs3s2bMB7bBwMB26aC6JyPHjxxk+fLh6TFaTxCbCEgniBKAdSrd+/XoqV67MpEmT1DeJIkWKsHjxYq5cucLhw4fp2LGjesylS5cYPHgw1atXZ/Xq1TniFyuRMXFxcaxatQrQfoD36dMnQ/WMHTtW/SI/b948wsLCMt22zZs3qz8U9O/fnx07dqi/zu7evZtevXrJfE1g5syZ3L59G9AOTdRfmN1eGjRooH452r9/v01DKXX0A5cDBw4YDKXs3bu3nVua83h6ejJz5kwmTJhg9+BaCHsyXk4gZ/TE2aIAF4niH8DhcZIk/ecST0l86U+FO70Y1fx19v65l9GjRxMZGUlERITZGs312rVv354lS5bQtm3b9DyVDJOeOGGJBHGCs2fP0r59e3r16sW1a9cA7a9Yb7zxBhcuXGDYsGE4ODjQoEEDtm7dyr59+wwW7Tx37hzPP/88tWvXZuPGjbJQei60YcMG9UOsT58+Ge4VKVy4MK+88gqg/bVw+fLldmmbTo8ePahZsya///67uq7Z1q1bGTBgQL4e3hseHs7UqVMB7ZeWrFqvz8PDg9q1awPa63716tXqvrSCuIIFC1KpUiVA+0v2mjVrAG12U3sP+xRC2E/O64kzVLdu3ccjNB4B83jAQgq0LYxjiUCzP5gkJPvimfgMTRlLFZoRevWOxd4tc/PnwsPD1dtZHVAlJyebfLZJECd0JIjLxyIiIhg3bhw1atRg165d6vb27dtz6tQpvv76a7Nv3k2bNmXXrl388ccfBsOrTp06Rc+ePalfvz5btmyRYC4XWbRokXo7I0Mp9b344ovqbf3/VxkRGxvLtm3bAO1aZrrepQYNGvDbb7+pGQ/Xr1/PiBEjbP4/N2fOHAYNGsSKFStyfC/elStX0kziMnXqVDUIHzp0KFWqVMmy9uhf87rz6+vrS926ddM8VjekMikpSe2lfeaZZyRboxA5WHZen7YkZgoPD+fvv//W23KTFu0ieWNuRa75HCWSSIPyKanakR0avChMW5aNvEDq6UI44WZSty2ZLLOSueBSgjihI0FcPpSamsqiRYuoUKEC3377rTpUrXTp0mzYsIFt27bZtOhu69at2bt3L7///jv169dXt4eEhNClSxeaNm3Kzp07JZjL4a5du6aO7S9btqzV5BS2qFy5MoGPV23VTyGfEdu3b1c/sLp3724wNKZFixZs3LhRXQto2bJlBsP7LDl8+DAjR47kp59+YuDAgQQFBTF+/HiuXr2a4XZmlc8++4zg4GCqVKliMgdE5/r168ycORPQ9mpNnjw5S9ukH8TptGnTxqblKPTnxenkh6GUQuRm1ua6ZjXdHGhrQkND1c8cHRcXFzw9IcXnNCeYwTk2EMtds8fHRieRGFqOERSkCaC/IIvxcErjz7M7d+7Y9DwyylzAJnPihI4EcfnM4cOHadSoESNGjFCTCri7u/Pxxx9z9uxZevToka75GhqNhmeeeYbDhw/zyy+/UKtWLXXfwYMHad++Pa1atWLv3r32firCTpYuXaoG2sOHD8/0fB2NRqMOt42JieHo0aMZrst4KKWxDh06MHfuXPX+jBkz0qxz1qxZBvfv3bvH1KlTCQ4OpkuXLmpmsvRKSkpi6dKltGnThvHjx2f6x4tvv/1WXS7g9u3bjBkzxqSMoiiMGjVK7U0cM2YMQUFBmXrctJgL4mxZFB5MgzhnZ+cck8ZbCGGe8Ry5p0m3/qg15n4o1K2N6erqCqRyl1Mc5QfOs5xErhiUPXPmDA4RRylKKO2BsUBTwAUYP348TZs25cSJEwA8fPjQ4NjsCOKkJ07oSBCXT4SFhTF8+HAaNWpk8KW6T58+nDt3jg8//FAdmpYRGo2Gbt26ERISwtq1a6lataq6b8+ePbRo0YLhw4cTFRWVqech7Cs1NZUlS5YA2nM4ZMgQu9SrP2cyo0Mqk5KS+PXXXwHw9vY2qFPfoEGD1MBl8+bNXLhwwWKdYWFh6jwuf39/+vXrp37YK4rCli1beOaZZ9SMZbaIi4vj+++/p3z58gwbNozdu3czdepU9uzZY3MdxhYsWMC4ceMMtm3YsEFNya+zevVqfvvtNwACAwMN1ojLKoGBgZQpU8Zgm61BXMWKFQ0SFbRv315dQFwIIYzZ0hM3ffp0wHCtyerVqwOoIzV07vAfB1nGeeaRwhlAITklmdL8pZbxANoBrwPxO3dy9MABnnnmGcC2IC41NZVff/2V0xYWG08PCeKENRLE5XFJSUls2rSJqlWrql/WAapWrcquXbtYvXo1pUqVstvjOTg40KtXL/7++29WrFhBhQoV1H1LliyhVq1aHDp0yG6PJzJnz549XLmi/VWyffv2duvF0c/aldEgbu/eveoHZpcuXR7/omrKycnJoJfqu+++s1jnggUL1F9tX3zxRVauXMmNGzf49NNPDZbReOutt6wGg6DtZZw2bRplypRh1KhRalIgnYULF1p/ghasXLmSl19+Wb2vv37a6NGj1flxDx48MHjes2fPfmoBkX5vXKlSpShXrpxNx+kvGA4ylFKInMrN7cn8MFt6w7JKWo89ePBgNZnWnDlzGDduHOvWrVOHV1r63LjDbfaxln/5AWd2UgDtcHUvT0/aP/5RygNoA3SgLwXvlSA1OdUkiDM3J27BggU8++yzNG7cmJs3b6bn6ZrQT6KiExcXx4EDB1i2bFmmpiuIPEARdhcREaEASkRERLa2IyQkRKlUqZKCdgkVBVB8fX2VmTNnKklJSU+lDUlJScq8efMULy8vtQ2Ojo7KpEmTnlobcrLExERl48aNSmJiYrY8/uDBg9XzsnLlSrvWHRwcrACKs7OzEhMTk+7jR48erbZt1apVVsuGh4crHh4eCqB4enoqDx8+NCmTlJSklChRQgEUjUajXLlyxWB/cnKyMnLkSPUxGzdurMTFxZk9Pw8fPlSqV69ucG0BSqdOnRQ/Pz8FUNzd3c22w5pNmzYpjo6Oan1vvvmmkpqaqnTt2lXd9vLLLyuKoijDhg1Ttz333HPpepzM+uGHH9THHjFiRLqOXblypQIoxYsXT/froy+7rx1hnZyfnC2t8/Pnn38qXl5eSsOGDZXk5OSn3LonEhMTTd5n9f8uX75s9fhmzZpZPV73VwyU/qDM8PNTjnTurEwEZSIor1FZaclEpSUTlVl9/lSWTl5lcNyrr75q8phBQUEZfn/UPWfdudm0aZPZ9rq4uCiA8u2336a7fpE5GX1vy4rYQHri8rCCBQuqvQMajYaXXnqJCxcuMGbMmCcLYWYxJycnXnrpJU6ePKn+Ap+SksKkSZNo0aKFulCwePoiIyPVtbp8fX3NzjnLDF1vXFJSEvv27UvXsYqisHHjRkA7HEa/N8ocPz8/hg4dCmh7yPSzber88ssv6q+iXbt2pXTp0gb7HR0dmTZtmtqrdPDgQTVhiL6kpCR69+6tDpXRaDT07t2bkJAQtmzZwsCBAwHtr6UrV660+TmfPHmSPn36qImGXn75ZaZNm4ZGo+H7779Xl32YN28ekyZNUnvWfXx8rPY+ZoWePXtSqFAh9fpOj379+nHp0iXOnj0rQymFyKFatmzJvXv3OHjwoE1Ji7KKbri7JUWKFLG633g4pSW3gJXAL0WLEvt4REoqDlzmyaiS8/8+4MAKhSYMpwjanj79nrKHDx+yd+9eg97DzC4IrstdYEzXA2fLPHCRd0kQl4eVKlWKt99+m4oVK3LgwAHmzZtn0/jyrFC2bFn27NnDpEmT1A+EgwcPUrNmTZYsWWKXDJaKorB//35efvll3n77bRk3nobVq1err9GAAQMMhs/Yg/6QyvR+kB07dkwNuNq1a2dTiuv//e9/6u2ZM2earK2jn9Bk9OjRZuvw9PRk8eLFanKXjz76yGA4jKIojBw5Uh0iWrBgQU6cOMGaNWuoU6cOYLjEgq1DKhVFYdy4ceoH84ABA/j+++/VdgQFBfH555+r5fUzUE6bNo1ixYrZ9Dj2EhAQwLVr17hz5w4NGzZM9/Fly5aVZQWEyOHc3Nxy3ML0+kP+69evj6enp9XyloZTWhLr68vdtm2ZC5ygPHE8WeLg1OlTXL58GWdKUpmXaEg3om9r5/mnpKTQqFEjWrRooSZBAdTpCukVFxdHSkoK9+7ds1ouO4e6iuwnQVwe9+677/L555/btIZTVnNycmLixIns27eP4OBgAKKjoxk+fDjPP/+82bHftoiPj2fp0qXUq1ePZs2aMX/+fL766iuLX9SF1uLFi9XbmV0bzpzWrVurt9M7L07XCwfms1KaU6lSJTp27Ahol0345Zdf1H1nzpxh9+7dAFSoUMFqIo5mzZqpSUUSEhKYMWOGGhB+8cUXamDm4uLCpk2bqFmzpsHxNWvWVK+3kJAQTp48mWbbN2/ezJ9//glAcHAwixYtMvn1e+TIkTRq1MhgW8uWLRkxYkSa9WcFDw8Pm9ZwEkIIe5kwYQKVK1emU6dO6hqi1tjaE6df3sPDgzvAb5znP34khdvq/sQk3Rw0DW7UwfHv5hyYe5pL5y+lOY/aVocPH2bYsGFUr16dGzdu2KVOkTdJEJfHOTs7Z2t6YHMaNWrEyZMnDQKHNWvWUKNGjXT12ISGhvLhhx9SsmRJhg0bxvHjxw32L1q0KMPJJfK6f//9lwMHDgBQrVq1LAnyixQpomYIO378uMmEcGt0SwtoNBqeffZZm48bO3aselt/mIl+tslRo0aleU1MmTJFTcpz8eJFpk+fzurVqxk/frxaZunSpWbT7QMGgVVa/weTk5N555131PtffPGF2V+PHR0dWbBggUHq7Hnz5uW461sIIexJN5QctJmPz549y5YtWwwy3VqS3p64Bw8eGKyLd5PL7GMet1gHmH6GJSU6sH3lA1aNOUcQtiV4SkufPn1ISEjg0qVL/PDDD+r2okWLmpRNq6dO5G3y6S+yhbe3N4sWLWLt2rXqG3FoaCjt2rXj7bffVte9MqYoCgcOHKBfv36ULl2aKVOmGLyJ1a1b1yA1+6hRowgJCcnaJ5ML6WcqtcfacJbolgVITU3lr7/+SqO01vnz5zl37hygzYIYEBBg8+N16NBBXah+z549nDhxgoiICJYtWwZoh0vq5s5Z4+7uzpIlS9QAafLkyQbLL3z66af069fP4vH9+/dXl+xYvny51aG9CxcuVJ9v48aN6dWrl8WyuiyzDRs2ZPny5QbZX4UQIi/avHkzZcuWZcyYMZQvXz5dx6a3Jy4sLMzsEM2L/MNeZvOAnSg8yQiZlJQEwP27KQQzkEb0w4fMDRW3tPZciRIlTLZJEJe/SRAnslWvXr04ffq0On9KURS++uorGjVqxNmzZ9VyuiGT9evXp2nTpvz888/qEDcnJyf69evHgQMHOHr0KN988406lDIhIYHevXtneKhmXpScnKwGNU5OTgwaNCjLHisj8+IyMpRSR6PRGMyNmzFjBsuWLSMmJgaAIUOG4OPjY1NdjRs3Vnv2EhMT1R8Whg8fbtAjZ46vr6+aPv/Ro0cGi5bri4qK4qOPPlLvf/3112kG1AMGDODQoUOSnl8IkS+0aNGCS5cumU00lZb0BnH37t0z6InTl0oK/7CfY3xHLH8DkJySjKIo6nxmVypSi1FUp4Hdv2CbSwQVExMj8//zMQniRLYrXrw427dv56uvvlLfcE+ePEndunX55ptvDIZM6veqFS5cmA8++ICrV6+ycuVKGjdurH4B/vrrr9WEC1evXmXw4MGkpqY+leeTkpJCTEwMDx48IDQ0VP2lLieIj49n1KhR3L6tHePfpUuXNLN7ZUaLFi3U3ixb58XpBzw9e/ZM92MOHjxY7d1duXIl33zzjbpv1KhR6apr0qRJBr9+tmnThjlz5tjUc2nLkMovv/xSzT7Wp08fgzXUhBBCZI7xcMq0Mm22bdvWYPimObFEc5SNnGcBKYSSkpJitF6bC3Vw52WgGNpEXa+88gpHjhzJ2JN4zNvb2+x2+ZE6/5IgTuQIDg4OvPnmmxw5coQqVaoA2oDjzTffNBkyWadOHZYuXcr169f55JNPKF68uEl9Li4urFmzRs3ctGXLFj777LNMt/Phw4eMHj2aBg0aUKNGDSpUqEDJkiUpUqQI3t7eODs74+TkhJeXF4UKFaJEiRIEBAQwffr0bF+U89KlSzRp0oR58+ap27I6+YuPjw/169cH4OzZsxaHieiEhoZy+PBhAGrUqKEmwEkPT09PNe19YmIiV69eBbSJVqpWrZquutzc3HjrrbeoVKkSHTp0YN26dTb/stuiRQt1uYI//vjDZDmNmzdv8vXXXwPauav62SeFEEJknvH7tb+/v8WyVapUYfbs2TYP4b9DKPtYQIu+LijEqNvdeUBJ9hEAvAh8VL8+S+bNM8hcnBGWgjhL009E3idBnMhRatasybFjxxgzZozBdicnJ55//nn279/PsWPHGDJkSJop8YOCgli5cqVBuvgdO3ZkuG1Xr16ladOmzJ49m6NHj3L69GkuXrzIjRs3uHfvHtHR0SZp7UEb+L3xxhvUqFGDLVu2ZOixk5KSWLRoETVr1qROnTosXLiQ+Ph4m49fu3YtdevWVVMfu7m5sXDhQqtZGu0lPUMq9TNKZmbdulGjRpn84prRgLV06dKcOnWKbdu2pWtdM41GY9Abp792XXx8POPHj1eHwYwaNYqyZctmqH1CCCHMM+6JsxTEVahQgTNnzlCxYkXc3d3TlXm3cHNvkuocIJpjgEIFfsMB7XqfGqABMApIfLy2aEZZWk5Bgrj8S4I4keO4u7szc+ZMfv/9d5599ll1yOSqVato0qRJupJwtGvXjk8++QTQzrfr378/169fT3ebjh49SqNGjdQEFLp2+vn5ERgYSHBwMFWqVKFOnTo0adKENm3a0LlzZ9q3b6+29/z583Tp0oVOnToZ1GNNQkICc+bMoXz58owYMYJTp05x4sQJXnzxRUqXLs1nn31mdShFQkICY8aMoU+fPkRGRgLaD6vDhw/zwgsvpPt1yAhdchNIO4hbt26dejsjQyl1SpYsaZAgpESJEunKcmkvQ4cOVYPJ+fPn06dPHypVqoSnpyfLly8HtPMcPvjgg6feNiGEyOuMe+IsBWfG5cwlEbHk0aNHhD64SQibOc8sErlqUqYA0A+4MHMrsfdjba5bx8nJSU2WZSy7R/mI7CNBnMixnnnmGTZt2mRxyKStxo8fT9euXQFt+mBd+l5bbdq0iZYtWxIWFgZAxYoV+e+//4iNjSU8PJxbt27x33//cebMGUJCQti/fz+7du1i8+bNbN++nSNHjhikov/999+pUaMGY8eOtZh2PzY2lhkzZhAcHMzIkSO5du2aSZmwsDAmTJhAyZIlef31100WFb1y5QrNmjUzWOS6f//+HDt2jBo1atj8/DOrSZMm6q+h1ubF7dq1S91fpkwZk/XX0uvNN99UA6ixY8fi5OSUqfoyIjAwkC5dugBw9+5d1q5dy/nz5w3mZ3744Yey3poQQmQBW4M4Y2mN9NEXHx+vfkbfIZx5wE7AeDZ8LAWZ/v19Zg4+wLnf/rO5fpAgTpgnQZzI8xwcHFi2bBllypQB4MiRI7zxxhs2HTtz5kx69uypDntr0aIFBw4cSNdcrXr16rF3715WrlxJUFAQoM0QOWPGDKpUqcKWLVvUYZjR0dFMmzaNMmXKMHbsWG7duqXW06lTJ/bv369mJtQlDImJiWHmzJmUK1eOfv36cezYMTZu3Ejt2rU5duwYoB1SMmfOHH766SeL4+qziru7O02aNAG0Q1KN54aBtsfwtddeU++///77mV72oEGDBuzYsYMff/zR5vOdFcaOHWvwXFxdXalduzZDhgxh3rx5BmvbCSGEsJ8GDRqotwsUKGAxkZdx4rP0rGsaHR3NzZs3n9QF7Ae+B3ShmoKGf+nOufP/8c/pq/z81Q3WvnWImHuGvXKWpklYC+IiIiKYMGEC06ZNQ1EUm9stcr+n/9O0ENnAz8+PdevW0bhxYxISEvj+++9p3LixxfT6KSkpvPnmmwYLRg8YMIBFixale/FQ0M6P6tevH88++yxfffUVU6dOJS4ujgcPHjBv3jz2799Pt27dmDdvnsnwyB49ejBhwgTq1aunbluzZg3//fcf06dPZ9GiRcTFxZGamsrPP//Mzz//bHB8uXLlWL16NbVr1053u+2lbdu27N69G9AOqTQOgr/66isuXLgAaFP722uoZ+vWre1ST2bbcOjQIW7cuEHVqlUpV65ctvQKCiFEfvPMM8+wbds2Vq1aRY8ePdizZ4/ZcsZBXN26ddXPpLRcvnzZ7Hz4R8ByoAZQg/pEov0R92boTcqVK8fO366yeM42Or5cjDHfaJNxRUREmH0MZ2dni0Hc5MmT2bdvH6Adnq9L7CXyPumJE/lG7dq1+f7779X7L7/8MqfNTDSOjY2ld+/eBgHcBx98wPLlyzMUwOnz8PDgo48+4vz58wwYMEDdfubMGaZOnaoGcBqNhr59+/L333+zYcMGgwBOp2zZssyaNYsbN27wySefmP2FsXfv3hw7dixbAzgwTG5iPKTy8uXLTJkyBdCmf54zZ47ay5hXNGjQgF69elGpUiUJ4IQQ4inq0KEDixYt4tlnn7W4fIBxD9aUKVMIDAykQoUKada/efNmq/tPARs4SwKGQeG/5/8lJkZh3fRQNr53kISIeHVNU2PWeuJ0ARxkfcZpkbPkrW9KQqThhRdeUDMGxsXF0atXLzXhB2jnmbVq1UpdcNrR0ZEFCxbwySefZHp4n76goCB++ukn9uzZQ/ny5dXtjo6ODB48mDNnzvDzzz/bNHetYMGCfPDBB1y7do158+ZRpUoVfHx8+O6771i9erXNi1tnpXr16qnDOP/44w/1A1NRFMaMGaMOIfnf//73VOfrCSGEyD8sBXHGPXHBwcFcv36df//9N8069+7dm2aZGKI5xEpusR6IM1k/9tCfEcwZdohrB0PNHq9buigtMj8uf5EgTuQ73333ndozdfHiRYYPH46iKJw7d45GjRpx9OhRQLsmy5YtWwzSxNtbo0aN+OKLL1i+fLnaQ7ds2TIqV66c7rrc3Nx46aWXOHPmDOHh4YwePdqugWdmODk50bJlS0Cb4OPMmTMAbNy4UV12oXjx4kyePDnb2iiEECJvs5Sm3ziIA+3nlkajYfHixXh4eNjl8S9ymmPMplCg4bDJqKgoHj6E3755SC1aozH6eu7k5ISfn59Nj2FuaKfImySIE/mOu7s7a9euVdf8Wr9+PS+99BJNmjRRF4YuUaIE+/fvp0OHDlneHgcHB/r27cvkyZPttlZYThyOaLzUQHR0NK+//rq67dtvv33qSVeEEELkH7b2xOkbNmwYERERfPzxx1brrl+/vk1tiCEG385R3GIjCtpM2dHR0Tx8+JCQ48fxoQVNGYEvTzJpOjk52bxO6Z07d2wqJ3K/nPdNT4inIDg4mB9//FG9v3DhQh49egRArVq1OHz4MNWrV8+m1uVNxvPiPv74Y27cuAFoJ5/rr+smhBBC2Jutc+KMOTk58eabb1KtWjU0Gg0vvviiSZmSJUva1AZXV1duht7kIn9zkjkkc53Y2Fj+PvW3WsaRYtTkFSpRR318W4M4/UyZIm+TIE7kW127dmXChAkG2zp37syePXsoVqxYNrUq76pWrRqFCxcGYOfOnUyfPh3QfqDNmjUrxwz9FEIIkTdlNIgDbWKyY8eOERoaajaDckBAgE3JzxISEtRliyJ5xH6WcCVyA9rFCfQ5U5TOdMcfDwcHm4dTShCXf0gQJ/K1yZMnM2TIENzc3Hj99dfZtGmTDOnLIg4ODmrK/9jYWHXc/vjx4ylXrlx2Nk0IIUQ+4OzsbHa7teGU+lxdXQkMDDSbKdLPz8/m7w+G69AphCTu4hzzSeW+QblgdlKLcAZERuIXa7imnCUSxOUfEsSJfM3R0ZGlS5cSGRnJt99+K+nfs5j+kErQrmH37rvvZlNrhBBC5CfGWSF1bA3idMwFcb6+vhYTpxjTTd/Qd5c7HGQusRwBoCAXKMEhAHwUBfcVK2hkQ926aQoi75MgTggs/zon7Es/uQnA7NmzcXNzy6bWCCGEyE+aNWtGoUKFTLbbI4jz8/OzOYulYU/cE8kkc5StXGMlJdmIbpKBg4MDGkXhGaA/YH7FOC1beuJsGT4qcj4J4oQQT03ZsmXVIZUjRox4Ktk/hRBCCNAGXydPnmTXrl18+eWX6vb27dunux5jfn5+FpOPuLi48Oqrr6r3zfXE6bvKBRYSx/XH9/UzTlcAulOfQMwnUkkriNu7dy+BgYH06dPHJJjbs2cPq1evJiUlxWodImeQsWNCiKdGo9Hw22+/cfHiRVnUWwghxFNXvHhxihcvTrNmzTh06BCPHj3i66+/Tlcd5kaQ+Pr64uPjY7a8s7OzwVBLSz1x+qKAJUBrYODjIK5vnz6s23WJVKehVLgbRiF2cpqDBselFcS1bNkSRVFYu3Ythw8fplEj7SDNU6dO0aZNG1JSUli+fDkDBw5Ms40ie0lPnBDiqfLw8KBmzZqSjVIIIUS2cXFxYd26dezatcvsEEtrMtITp58ZM62eOB0F+AP4o1gx8PSkdPmaeNb7nGLFSgAO+NOBxvTBGRf1mOjoaOt16vW+3bt3T709btw4tQcuvUGtyB4SxAkhhBBCCGEjc0nQqlevbrEnzsXFxaAnztYgTueutze8+ipHUuoSmeBq8COoC1VozEsURLuET2JiIpcuXWLkyJFs3rzZar36cwFDQkLU27aueSeylwRxQgghhBBCZNDff/+Nk5OT1SBOfwhmYmJiuup3dnYGb29aTOlAqx6+ODoafn3XUIhqvERZqpGYmEivXr2YM2cOXbt2JT4+3mK9+kGcfpuKFCliUnbv3r0sXLjQan3i6ZI5cUIIIYQQQmRQpUqVAKwOp8xMJmZdz5+DkwOtxtYipUAUR0fEYZin0pkS9MIn8QgnTm1Ttz548IDixYubrVc/iNPvXTQO1G7evEmLFi0A7RDM9957L8PPRdiP9MQJIYQQQgiRDp06dQLgmWeewcVFOyfNXA8W2C+I0ynTqjgnmEsKt0zKetOAJgzHE+0cvKioKAAiIiJM1snTnx+n/xhxcXEG5davX6/eHj9+fAafhbA3CeKEEEIIIYRIh5UrV7JmzRpWrFihbuvfvz9FixY1KZveIM44e7NxEOft7U0kERxgEbGEYMyJEtTjZQIpzsOHD1m0aBH+/v40btzYoFxycrJ629HRUb0dGxtrc1tF9pEgTgghhBBCiHTw8fGhd+/e+Pv7q9s8PDw4f/48586dM8h4aWsQV7duXRYsWECvXr0MthsHcQUKFAAglRSO8ht32AQkY8ibCgznhSavMWLECFJTUw2Sl4DhsElrPXHG2aQvXbpE/fr1GTJkiCwcno0kiBNCCCGEEMIOChQoQKVKlQyCNluDuF69ejFkyBB1eKaOcRDn6upqcP88JznHQsB4/TlHAuhOfdqZ/cKvH6zp98QZB3HGBgwYwLFjx/jxxx/TzIApso4EcUIIIYQQQtiRfiBmaxCn62EzDtrMLWmgr1u3btTqUIPDzCeJyyb763KHwRimQQHDnjj9oZVp9cQdPXpUvX3x4kWrbRNZR4I4IYQQQggh7MjZ2Vm97eTklK45cfrH6o635uWXX6ZIkSLEE8cBlhPJQXVfEAcI4B9KAy8D+qlX9IM4/aQnxkGcfoBnzMFBQonsIq+8EEIIIYQQdqTfE5eSkoK7u3E/mCldsJTenjhnZ2e9x1M4wXZC2YAf/xLMTrWcLzACqPT4vn4Qp79OnHEQFxMTY/GxJYjLPvLKCyGEEEIIYUeNGjVSbwcFBVnsidPPRFmmTBkg/UGcoigm8+gucYpD/EwUholHXIDngZZA6M2b6nZrPXHWslUaD7UUT48s9i2EEEIIIYQdzZgxA39/f06cOMGbb75pMYhbtWoVvXv3pnLlynTt2pWUlJR0D6dMSEgwCeIA7gDzgb5AkNG+6pTj+KJHxHwVjYevp0FPnHHQZi2IM157Tjw9EsQJIYQQQghhR+7u7kydOlW9f//+fbPlKleuzJkzZ9T7KSkp6e6Ji4uLMxvEAUQDS4EuQG11WxHO0htnXJk95A9emt3cYKmAuLg4FEVRe9msBXHWhlqKrCXDKYUQQgghhMhC9k5sEhwcrN4uUaKExSAOIAX4BfgdiMeDf+hPCtplCsJuaVjw2gkKEaCWVxTFas+cPgniso8EcUIIIYQQQmSh9ARxtvTE/fbbb9SrV4+XXnqJpk2bmqwdZ85hYAUFidNbbCApKYk7t2OoyguUpoK6ffXq1WrvXHR0tMU6re0TWUuGUwohhBBCCJGF0hoSaa2sr6+vSZnKlSsbrNdmrSdO3w1uEM0CqjEAB/w4dfqUrgZK0Q9PdnCGgwwZMoTAwEDatWvHw4fGi4g/IT1x2Ud64oQQQgghhMghjNP2FypUKM1jbA3iAB5yn6MsIJnrRns0FKID9eiGBgfefvttAMLDwy3Wld4gLjU1NV3lhWUSxAkhhBBCCJFD2TuIA4gnloMsI46/TfZ5UodGDEaJg/fff5/Tp09brCc9Qdwrr7yCn58f69atS1dbhXkSxAkhhBBCCJFDFSxYMM0y5oK47t27M3v2bLy8vMwek0oKR9jIQ3aZ1kdpCpxvwuzPv7f6uLYGcVFRUcybN4/IyEh69+5t0zHCOgnihBBCCCGEyGKBgYEZOi6jPXFDhgzhtddeMxkO2bFjR4P7p9jHTVYDhmu+OVCY2rxIUSy329YgLiEhwaZywnYSxAkhhBBCCJHFtm3bRqtWrdJ9XEaDOF3GSuMlC/z9/U3K/sc5zrMYiDLa40VFhlOG8mYfVxfE7d69m4kTJ3Lv3j2z5YyDOP0lDETGSBAnhBBCCCFEFqtevTqzZs1K93He3t5pljG3hIGlZQf8/PzMbr/DbU6wgFTuGu1xpjmB1DdzTExMDHFxcXTv3p2PP/6YQYMGma3bOGi7efOm2XLCdhLECSGEEEII8RSUKVNGvW1tbtiAAQMAaNeuHRqNJs16PTw8TLZZWpvOx8fHYj2RRHKIRSRyRd1WlBOUZg+dgXZG5WNiYrh//z5RUdoevO3bt6vry+kzDuIePXpksQ3CNrJOnBBCCCGEEE+Bh4cHBw8e5K+//mLEiBEWy82ZM4ehQ4fSuHFjm+p1d3c32WapJy6tNP9JJHCI5dTjWYrjRQV+QxdGNgV8gI1ACtogzjhA27NnD9euXaN3795qcGk8nDIyMjLtJyWskiBOCCGEEEKIp6RRo0Y0atTIahk3Nzc6dOhgc53p6YmLj49Psz6FVI6yETeccMAw6KsGeAE/A3FxccTFxRns1837Gzp0KJMnT+a9994zCfR0QVxKSgoODg429TYKQzKcUgghhBBCiFzMXBBnqSeuUqVKNte7l2Q2AcZ9d6WBfgRQAF+rQyMnTpzI559/bhLERUVFcfHiRUqVKkWdOnWIi4vjr7/+IjQ01Oa25XcSxAkhhBBCCJGLpRXETZo0CdBmsRwwYAA//vijSfmZM2cSEBBgsv0ksALQD8Pi8SGUQdTkRa6H3LLatkmTJpkdTjlo0CBCQ0M5efIk5cqVo1WrVjRo0ECdXyeskyBOCCGEEEKIXMzcnDj94ZTvvvsuK1asICQkBG9vb5MskkuXLmX06NFcunTJbP3/gboAQRJunGIgiXjhgCf75iZSkjJmj9MxN5zy2LFj6v1bt26p/y5YsMBqXUJL5sQJIYQQQgiRi6XVE+fm5kb//v0tHt+0aVM0Go3ZYFDnDrAQaEpbYimsbo+KSqAMA3FlIxf5x+yx5oZTWkqwcvLkSYttEE9IT5wQQgghhBC5WHqyU+rs3LmTwoULM3jwYMqWLQuAo6OjxfINGjQgAtjFTpL1liDQJjZxpBi9qEZDs8caD6e0No/O3BIFwpQEcUIIIYQQQuRizs7OJtvSCuLatm1LWFgYy5Yts+kxypcvD0ACCRzkJ+I5A2CQnbIgHaljspqcdikCfffv37f4OJKp0jb5PojTaDRW//r165fdTRRCCCGEEMJmixYtwsEh7a/56QmYChQooN5OJYXDrCWSwyZLFnjTlAb0QKMXZuzbt8+gzN27d622ac+ePXz44YfqXDlrFEWhR48elC1bltOnT9v6dHI9mRP32NChQ81ub9jQfLewEEIIIYQQOdGAAQPsXqe3t7fJthP8TtXUaArR1mC7OzVphCdHWU0ySSbJSqwFcTExMbRs2RLQJjpZuHCh1XZt3ryZTZs2AdCtWzeuXr1qy9PJ9SSIe2zJkiXZ3QQhhBBCCCEyzcXFJcPHtmnThj/++MNku5eXl9nyZ9hHeaIpRjf0B/m5UI6GDCWEn4jHcEFwa0HckSNH1NuLFi1KM4jTX1vu2rVrVsvmJfl+OKUQQgghhBB5SWbmlX322Wdmt1ubY3eRk1xhFZBksN2J4tRnBN74GGy3Nifu+vXrtjcW8/MB8wMJ4oQQQgghhMjlPv/8cwBGjBiRqXosLTPg5GR9AN91LnKeZWDU6+ZAQWrxIgXxVbfZMwNlfg3iZDjlY9988w2XLl1Co9FQsmRJ2rdvT506dbK7WUIIIYQQQqTpvffe45VXXsHPzy9T9VgK4mwJlu5wk0QWUZ1BoNf7Vog7DCeSVcDNTLXOlLVlEfIyCeIee/PNNw3uv/fee3Ts2JElS5YQEBCQTa0SQgghhBDCNpkN4MD8wuFge49XOPc5zkL6lJvMf5ci8CaUqqzGkVSGAGuAi5luJURHRzNmzBg2bNhgh9pyn3wfxA0YMIC+fftSq1YtAgICuHHjBtu3b2fixIn8/vvvtG/fniNHjuDm5maxjoSEBINFDCMjIwFISkoiKSnJ0mFPhe7xs7sdwjw5PzmbnJ+cS85NzibnJ2eT85Nz5YRzY2nYpC1LFuhEEcWkLX0YXmE01dmB4+O5csUKFaLf/ftsAk7ZWJel12LixIlmExNm5WuX0fOTFW3SKLl0WfR33nmHX375Jd3HLViwgGbNmqVZ7sqVK9SuXZuIiAimT5/O2LFjLZadNGkSkydPNtm+YsUKi79mCCGEEEIIkdMkJCTw/PPPG2xzc3Nj/vz5DB482OZ6Nm7cyIfvvUe1f/+lwuNtRQMCuBMWBsBW4IjFow3rMWfEiBE8ePDA5vLZKTY2lgEDBhAREWGw3l5m5NogbtCgQfz000/pPm7r1q107NjRprLjxo3j22+/pU2bNuzatctiOXM9cUFBQdy/f99uJyqjkpKS2LFjB+3bt8+3Ez9zMjk/OZucn5xLzk3OJucnZ5Pzk3PlhHOjKIpBJsq1a9dSoUIFKlasaDVDpbHExES6dOnCrh076AbUAmpUr86pxwtyJ+PKVqpynONp1mNO2bJluXHjhtnyO3bs4KeffsLX15fBgwdTt25dm9ttTUbPT2RkJIUKFbJrEJdrh1MuX76c5cuXZ+ljVK5cGYCbN61PwXR1dTX7n9rZ2TnHvDnmpLYIU3J+cjY5PzmXnJucTc5PzibnJ+fKSeemV69eZrd/+eWXvPPOOxaPc3Z2xtvbm1RgExADNHscwKTgxGn6400p6lKYELZZrcccS8soODs7c/bsWVasWAFAq1ataNSokcX6MyK95ycrzqUsMWCFrovW3Ar1QgghhBBC5EXdunUDYOTIkRbLGE8ZGjJkiHq7d+/eAHh6eqrbdgIP69YlFQfO0ocISgHgRSMa0B3I+Np2+hRF4dGjR+p9X19fu9Sb0+TanrislpqayurVqwFo0KBBNrdGCCGEEEKIp2PdunWcPn2aWrVqWSxjnNp/9uzZtGzZEldXV/r06QMYBnEAqU2asGHmb/hTwSBkc6cWjXHjMGtJJcXgmH///ZcuXboQHBzM1q1b1cQrlnriEhMT80UQl6974n766SfOnz9vsv3u3bsMHDiQkydP4uzszJgxY7KhdUIIIYQQQjx9zs7O1KlTx2pGSicnJ+rXrw9AcHAwXl5evPDCCwwcOBAXFxcAk+lGHh4eXPEM4xbrgFSDfS5UojEDccbFYHvPnj25fPkyO3fu5Pfff1e35/cgLl/3xK1Zs4ZBgwZRvnx5qlSpgqenJ9evX+fkyZNER0fj4eHBkiVL1LlxQgghhBBCCG0QtXbtWlavXk3Pnj3NltEFczqOjo64urpyKeYfkkigNH3RD0ecKENDhnKMn4gnFtD2xOncvXs3zXYZB3H2WDsvJ8rXQdzQoUPx9vbm5MmT7N+/n0ePHuHu7k65cuVo27Yto0aNokyZMtndTCGEEEIIIXKUmJgYSpYsyVtvvWWxjHFPnJOTkxrYXeMiSfxI31rTOHHyrFrGkWLUZzgn+JFoIg2Oj4qKUm9b6olLSEgwCOJ8fHxsfk65Sb4O4nr27GnxlwMhhBBCCCGEefoBlSXGPXHGC4mXalycN79rxsstzhIb+2S7A4WozQucYhkRhKvb9XviLA31TExM5NatWwB4eXnlmCyf9pav58QJIYQQQggh0i8jQZyjoyMpKU8Sl/j4+FCibjG+2vY8ChEGZR3woSbDKUQRddvdu3dRFAVFUSz2xF2/fp0rV64AULt2bZufT24jQZwQQgghhBAiTfpBWWRkpJWSWuaGUyYnJ6v3dcsUVGlWmRMsROG+QXkNXlRlGEUpBkB0dDS9evXCzc2NS5cumX3MCxcuqLdr1qyZZhtzKwnihBBCCCGEEGkaPXq0ertt27Zpljc3nNJcEAcQRRRHWUQqt4xqcaciQylBCW7dusWGDRtITEy0+Jj6Qy7zalITyOdz4oQQQgghhBC2+fjjj0lISMDX19emvBJpBXHu7u4G++OI4zBLqc9AnCipbncjln5EcMxC75s+/SAury4vABLECSGEEEIIIWzg6enJrFmzbC5vPJzS0dHRIIgzTnQCkEgih1hOA57HhbK4EEVNluFOFM1vRXEXOGty1BP6QVxezUwJMpxSCCGEEEIIkQXS6okzF8QBpJDEIVaSxInHAdxDQBu49AaszXRbuXKlejsv98RJECeEEEIIIYSwO3NBnKIo6n1HR0eLxyqkcJBfuGiS7AR6APVseHzpiRNCCCGEEEKIdDC3xIA+/Z64PXv2mByvAJuAo2bq7gzUopzVx/f09LSxpbmPBHFCCCGEEEIIuzO3xICl+82bN2fnzp1mM0puAfbr3VeAS3TCh4HUoJXNj5+XSBAnhBBCCCGEsDtzwymt3W/bti337t1jxowZJnXtBHY/vn2FtoTSAAA/WlKbZ2x6/LxEslMKIYQQQggh7C49wyn1y3h7e5utbw8QTTG8aWawvQCNqIcLx/gNbT+dlvTECSGEEEIIIUQ6pGc4pb4CBQpYrPM4twjjV/SDNQBP6lCfnuiHN3m5J06COCGEEEIIIYTdmRtOOWDAAPV+s2bNjA8BrAdxAP9ynFA2AKkG2z2oTkP6osHR7OPnJTKcUgghhBBCCGF3pUqVMrjv6OjIt99+i6urKxUqVKBly5ZmjytevHiadV/iNKkkEkQf4MkwTTcq0oj+HGGVBHFCCCGEEEIIkR5eXl5UrlyZc+fO4efnh4eHBz4+PixatMjqccbBnyWXOU8KKyhNPzzcfYiNiwXAhbI0ZBAkZPop5FgynFIIIYQQQgiRJbZt28Ybb7zBmjVrcHZ2tumY9Kzvdo3LjP2uIX5+HgbbnSnF2ndOE/8wLl3tzS0kiBNCCCGEEEJkiaCgIL7++mvatm2bruMKFy5scL9OnToWy/YY/SyfretOAW/DIDHlYTSpP/4EMTHpeuzcQII4IYQQQgghRI4yZ84cg/uWlh3QKdUoiO//HAZoAzYP7jO05t94hN+EHTuyqJXZR4I4IYQQQgghRI7i7u5ucL9QoUJpHlO8djFOsxhXrlGTZXi6JEFgIHTsmFXNzDYSxAkhhBBCCCFyFOMgLq2eOACNRkM4DzjCEuKIgiJFYPBgcHPLqmZmGwnihBBCCCGEEDmKcRBXokQJm499BCwGbQDn4WG9cC4lQZwQQgghhBAiRzEO4po2bZqu4yMBbOi9y60kiBNCCCGEEELkKMYLddsyJw6gU6dOAPTu3dvubcpJZLFvIYQQQgghRI6i0WgM7hsHdZb8/PPP/PXXX7Ru3TormpVjSE+cEEIIIYQQIkepUKGCujbcnDlzbA7ivL296dq1a7oWDM+NpCdOCCGEEEIIkaNoNBoOHTrEzZs3KVOmDJcvX87uJuUo0hMnhBBCCCGEyHGcnZ0pU6YMYPtwyvxCgjghhBBCCCFEjiZBnCEJ4oQQQgghhBA5mgRxhiSIE0IIIYQQQuRoEsQZkiBOCCGEEEIIkaNZCuIWLVr0lFuSM0h2SiGEEEIIIUSO5ujoaHD/9OnTPHr0iKZNm2ZTi7KXBHFCCCGEEEKIHM148e/SpUvj5eWVTa3JfjKcUgghhBBCCJGr5Pc5chLECSGEEEIIIXIVZ2fn7G5CtpIgTgghhBBCCJGrGA+vzG8kiBNCCCGEEEKIXESCOCGEEEIIIYTIRSSIE0IIIYQQQuR406ZNw8nJiXfeeSe7m5LtZIkBIYQQQgghRI731ltvMXr0aNzc3LK7KdlOeuKEEEIIIYQQuYIEcFoSxAkhhBBCCCFELiJBnBBCCCGEEELkIhLECSGEEEIIIUQuIkGcEEIIIYQQQuQiEsQJIYQQQgghRC4iQZwQQgghhBBC5CISxAkhhBBCCCFELiJBnBBCCCGEEELkIhLECSGEEEIIIUQuIkGcEEIIIYQQQuQiEsQJIYQQQgghRC4iQZwQQgghhBBC5CISxAkhhBBCCCFELiJBnBBCCCGEEELkIhLECSGEEEIIIUQuIkGcEEIIIYQQQuQiEsQJIYQQQgghRC4iQZwQQgghhBBC5CISxAkhhBBCCCFELiJBnBBCCCGEEELkIhLECSGEEEIIIUQuIkGcEEIIIYQQQuQiEsQJIYQQQgghRC4iQZwQQgghhBBC5CJO2d2AvEhRFAAiIyOzuSWQlJREbGwskZGRODs7Z3dzhBE5PzmbnJ+cS85NzibnJ2eT85NzybnJ2TJ6fnQxgS5GsAcJ4rJAVFQUAEFBQdncEiGEEEIIIUROEBUVhY+Pj13q0ij2DAkFAKmpqdy6dQtvb280Gk22tiUyMpKgoCBu3LhBgQIFsrUtwpScn5xNzk/OJecmZ5Pzk7PJ+cm55NzkbBk9P4qiEBUVRbFixXBwsM9sNumJywIODg6UKFEiu5thoECBAvJmkIPJ+cnZ5PzkXHJucjY5PzmbnJ+cS85NzpaR82OvHjgdSWwihBBCCCGEELmIBHFCCCGEEEIIkYtIEJfHubq6MnHiRFxdXbO7KcIMOT85m5yfnEvOTc4m5ydnk/OTc8m5ydly0vmRxCZCCCGEEEIIkYtIT5wQQgghhBBC5CISxAkhhBBCCCFELiJBnBBCCCGEEELkIhLE5UBr1qyhVatW+Pn54enpSc2aNfnyyy9JSkrKUH0hISH06dOHgIAA3NzcKFOmDGPGjOHu3btWjwsLC2P06NGUKVMGV1dXAgIC6NOnD8ePH89QO/IKe52fEydO8Pnnn9O2bVsCAgJwdnbGz8+P5s2bM3v2bIv1/fnnn2g0Gqt/c+bMscdTzXXsdW6WLFmS5mv8+++/Wzxerh3z7HV+Spcuneb50Wg0fPzxxwbHybVj3vnz5/nuu+8YNmwY1atXx8nJCY1Gw5QpUzJV786dO+ncuTOFChXC3d2dSpUqMWHCBKKjo60ed+nSJYYNG0aJEiVwdXWlRIkSDBs2jMuXL2eqPbmRPc9NamoqBw4c4KOPPqJZs2YULFgQZ2dnChUqRPv27fnpp5+wlCYhs++JeZW9r51Jkyal+Tr/+++/Fo+Xa8eQvc+PLZ87Go2GZcuWGRyXVdePLPadw4wdO5YZM2bg5OREmzZt8PLy4o8//uDdd9/l119/Zfv27bi7u9tc39q1a+nfvz/JycnUr1+fMmXKcOzYMWbNmsWaNWvYt28f5cqVMznuwoULNG/enLt37xIcHEyPHj24cuUKa9euZePGjaxevZqePXva86nnCvY6P8nJydSpUwcALy8v6tevT0BAADdv3uTgwYPs27ePZcuWsW3bNnx9fc3WERAQQMeOHc3uq1ixYoafY25l72sHoGzZsjRr1szsvuLFi5vdLteOefY8P7179+b+/ftm94WHh/Prr78C0Lp1a7Nl5Nox9MMPPzBjxgy71jl9+nTeeOMNNBoNzZs3JyAggL179/LZZ5+xbt069u3bR6FChUyO279/Px06dCA2NpaqVavSrFkz/vnnH5YuXcratWvZuXMnjRo1smtbczJ7npvLly/TtGlTAPz9/alXrx5+fn5cvnyZnTt3snPnTlatWsW6detwcXExW0dG3hPzsqy4dgBq1qxJrVq1zO6ztGC0XDum7H1+hg4danHf9evX2b17NxqNhpYtW5otY/frRxE5xoYNGxRA8fLyUkJCQtTt9+7dU6pXr64AyptvvmlzfaGhoYqHh4cCKHPnzlW3JycnK4MGDVIApX79+kpqaqrBcampqUrt2rUVQBk8eLCSnJys7ps7d67axtu3b2fi2eY+9jw/SUlJSt26dZXVq1cr8fHxBvtOnTqlBAYGKoAyfPhwk2N3796tAErLli0z9XzyEntfO4sXL1YAZejQoelqh1w75tn7/FjzxRdfKIBSoUIFk31y7Zg3f/585a233lJ++ukn5dy5c8rgwYMVQPnkk08yVN/x48cVjUajODo6Klu2bFG3x8TEKG3btlUApVevXibHxcTEKMWKFVMAZfz48Qb7xo8frwBKUFCQEhsbm6F25Ub2PDeXLl1S2rRpo2zdutXgvUlRFOXPP/9UPD09FUCZPHmyybEZfU/M6+x97UycOFEBlIkTJ6brOLl2zLP3+bFm5MiRCqC0b9/eZF9WXT8SxOUg9evXVwBlypQpJvv27t2rAIqrq6vy6NEjm+p7++23FUBp166dyb6oqCjFx8dHAZTff//dYN/mzZsVQPH19VWioqJMjtV9CL/33ns2PrO8wd7nx5off/xRARR3d3clMTHRYJ98ETVl73OT0TdcuXbMe5rXTsWKFRVAmTp1qsk+uXZsM3To0Ex90enTp48CKC+++KLJvqtXryoODg4KoJw7d85g3+zZs9UAPCUlxWBfSkqKUqFCBQVQ5syZk6F25QWZPTfWfPLJJwqglC1b1mSfBHG2yez5yWgQJ9eObbLq+omLi1N8fX0VQFm1apXJ/qy6fmROXA4RGhrK0aNHARgwYIDJ/mbNmhEUFERCQgJbtmyxqc4NGzZYrM/Ly4tnn30WgPXr15s97tlnn8XLy8vkWF19xsflZVlxfqypXbs2AHFxcRaHjQmtp31urJFrx9TTPD/79+/n/PnzODk5WR32IrJOYmIimzdvBsyf71KlSqlD+nTXi47ufr9+/XBwMPx64uDgwPPPPw/kr+vnadJ97ty4cSObWyLSS66d7LVu3ToePXqEv78/PXr0eGqPK3PicogTJ04A2nHqZcqUMVumXr163LhxgxMnTtC/f3+r9UVFRXHp0iX1OEv1/fjjj+pjG7fF2nEAFy9eJCYmBk9PT6ttyQvsfX7ScvHiRQBcXFzw9/c3WyYsLIyPP/6Y0NBQ3NzcqFSpEl26dKFkyZKZeuzcJivPzaVLl/jggw+4e/cuXl5eVKtWjWeffdbsXB79tsi188TTvHYWLVoEQOfOnSlatKjFcnLtZJ0LFy4QGxsLWL8O9u7dm+HPHuPjhH3oPncCAwMtlknve6LImOPHj/Pee+8RHh6Oj48PtWvXplu3bnh7e5stL9dO9tJ99gwaNAhXV1eL5ex9/UgQl0NcuXIFwOqXiKCgIIOy1ly9elW9balOS/Wl1RbdcYqicPXqVapWrZpme3I7e58faxRF4csvvwSga9euFt8Q/v33XyZOnGiwzcnJiTFjxvDll1/i5JQ/Lu+sPDf79+9n//79Btvc3NyYNGkS7777brrbIteOefa4dmJiYli9ejUAI0aMsFpWrp2sozuHvr6+Fr9wmjvfUVFRPHjwAEj7+rl3716++RHkaYmNjWXmzJkA9OrVy2K59L4nioz59ddf1QRNOj4+PsycOZMhQ4YYbJdrJ3tdvXqV3bt3A2l/9tj7+pHhlDlEVFQUgNULSzc8KzIy0ub6rNVpqb602qI/TMyWtuQF9j4/1kyePJmDBw/i5eXF1KlTTfb7+PgwduxY/vrrL27fvk1MTAynTp1i3LhxaDQapk+fzmuvvZapNuQmWXFuihYtyoQJEzh8+DD37t0jMjKSo0ePMmTIEBISEnjvvff47LPP0t0WuXbMs8e1s3r1aqKjoylatCidO3c2W0aunayX0fOdns8s42NF5r322mtcuXKFYsWK8f7775vsz+h7okifsmXL8tlnn3HixAnCw8MJDw9n3759dO3alYiICIYOHcpPP/1kcIxcO9lr8eLFKIpCvXr1qFGjhtkyWXX9SBAnRA6ybNkyPv74YxwcHFi0aBHly5c3KVO7dm2mT59OixYtKFq0KB4eHlSvXp1vvvmGVatWATB//nxOnjz5lFufd3Ts2JEpU6bQoEEDChUqhLe3N/Xq1WPp0qV89dVXAHz88ceEhYVlc0uFzsKFCwEYMmSIxZ40uXaEMPXJJ5+wdOlS3NzcWL16NQULFjQpI++JT8fgwYMZP348tWrVws/PDz8/P5o2bcqvv/7KmDFjABg3bhyJiYnZ3FIB2rUXlyxZAsALL7xgsVxWXT8SxOUQumEnMTExFsvoFkgtUKCAzfVZq9NSfWm1RX+hVlvakhfY+/yYs2bNGvVNYP78+fTp0yfddTz33HPq2jLGQzHyqqdxbvS9/vrrFCpUiISEBLZv356utsi1Y15mz8+FCxfUISrWPkityY/XTlbI6PlOz2eW8bEi47755hs++ugjXF1d2bBhg5p0Jj2svScK+5k0aRKOjo7cu3ePw4cPq9vl2sk+O3fu5Pr167i7u5tN5GSLzFw/EsTlEKVLlwasZ4XS7dOVtaZUqVLq7evXr6erPt39tI7TaDQGj5OX2fv8GFu/fj0DBgwgNTWVuXPnZviLKEDlypUBuHnzZobryE2y+twYc3R0VHtIjV9juXZMPY3zo5tU3qxZs0wt1p3frp2soDuHjx49Mhjmpc/c+fb29laTOKV1/RQqVEjm9NjBd999x5tvvomLiwvr1q2jY8eOGarH2nuisB9/f3+KFCkCGL7Ocu1kH91nT69evSwuwp6WzFw/EsTlELrUvg8ePLA4uf/YsWMA1KlTJ836ChQoQLly5QyOs7U+3f20jitfvrzZNOp5kb3Pj76NGzfSr18/UlJS+OGHH3jppZcy1VbdBGdLSQXymqw8N5ZYeo3l2jGV1ecnJSWFZcuWAWlPKk9Lfrt2skLFihXx8PAAsu6zx17XcX42e/Zs/ve//6kBXJcuXTJVn1w7WS8lJYWIiAgg4589cu3YT3h4OBs3bgSy77NHgrgcokSJEtSvXx+AFStWmOzft28fN27cwNXV1eKkfWM9e/a0WF90dLQ6ZOi5554ze9wvv/xitmteV5/xcXlZVpwf0A7b6tu3L8nJyfzwww+88sormWpnaGgoe/fuBaBBgwaZqiu3yKpzY8nx48e5cOECYPoay7VjKqvPz5YtW7h9+zbe3t4ZGoKskx+vnazg4uKiBgTmzve1a9c4cOAA8OR60dHdX7VqFampqQb7UlNT+fnnn4H8df1khTlz5jB69Gg1gOvatWum6rP2nijs55dffiE2NhaNRmOylIBcO0/fTz/9REJCAmXLlqVly5YZridT149dlw4XmbJhwwYFULy8vJSQkBB1+/3795Xq1asrgPLmm28aHLN+/XqlYsWKSps2bUzqCw0NVTw8PBRAmTdvnro9OTlZGTx4sAIo9evXV1JTUw2OS01NVWrXrq0AypAhQ5Tk5GR139y5c9U23r59215PPVew9/nZvHmz4uLiomg0GmXu3Lk2t+Pbb79V7t27Z7L977//Vs9b2bJllfj4+HQ8u9zNnucmJiZGmTVrlhIZGWnyOH/99ZdSunRpBVCaNWtmsl+uHfPsfe3o69GjhwIoL730UprtkGvHNkOHDlUA5ZNPPrFY5rvvvlMqVqyoDB482GRfSEiIotFoFEdHR2Xr1q3q9piYGKVt27YKoPTq1cvkuJiYGKVYsWIKoLz//vsG+95//30FUEqUKKHExsZm4tnlbpk9N/PmzVM0Go3i4uKi/PrrrzY9ZmbeE/ObzJyfa9euKT/++KMSFxdncsyGDRsUf39/BVAGDRpksl+uHdtk9vrRV6tWLQVQPv30U6vlsvL6kSAuh/nf//6nAIqzs7PSsWNHpVevXoqvr68CKE2bNjW5ABcvXqwASqlSpczWt3r1asXR0VEBlIYNGyrPP/+8EhwcrABKQECAcvHiRbPH/fvvv0rhwoUVQAkODlaef/55pUGDBgqgODk5KevXr7f3U88V7HV+wsLCFFdXV/WNdejQoRb/jL90+vj4KI6OjkrdunWV3r17K3379lXq1q2rODg4KIBSsmRJ5ezZs1n9UuQ49jo3Dx8+VADF1dVVadSokdK3b1/lueeeU6pVq6YACqBUr15duXXrltl2yLVjnr3f2xRFex05OzsrgHLo0KE02yDXjnkhISFKw4YN1b9ChQqp70362/X/z0+cOFEBlJYtW5qt85tvvlEARaPRKK1atVL69u2rBAYGKoBSsWJFs8G0oijKvn371B8fq1WrpvTr10+99jw9PZWDBw9mxUuQY9nz3Jw4cULRaDQKoFSqVMnq546+zL4n5mX2Pj+6H7uaN2+u9OvXT+nevbtSvnx59XVu3bq1EhUVZbYtcu2Yyor3NkVRlOPHjyuA4ujoqISGhlptQ1ZePxLE5UA///yz0qJFC6VAgQKKu7u7Uq1aNWXq1KlKQkKCSVlbvugcO3ZMee6555TChQsrLi4uSqlSpZRRo0Ypd+7csdqO27dvK6NGjVJKlSqluLi4KIULF1aee+45g1/S8yN7nJ8rV66oF29af1euXDE49ssvv1S6d++ulCtXTvHx8VGcnJwUf39/pVmzZsq0adPM/tqTX9jj3CQkJCgffvih0qlTJ6VMmTKKt7e34uTkpBQuXFhp166dMnfuXLP16ZNrxzx7v7d99dVXCqBUrVrVpseXa8e83bt3p/u9yJYvOjt27FA6duyo+Pv7K66urkr58uWV8ePHp/k6X7x4URkyZIhSrFgxxdnZWSlWrJgyZMgQ5dKlS3Z6xrmHPc+NrXUZD9Kyx3tiXmXP83P//n3l3XffVdq0aaOULFlS8fT0VJydnZXAwECla9euyooVK5SUlBSr7ZFrx1BWvbeNHj1aAZTOnTun2YasvH40iqIoCCGEEEIIIYTIFSSxiRBCCCGEEELkIhLECSGEEEIIIUQuIkGcEEIIIYQQQuQiEsQJIYQQQgghRC4iQZwQQgghhBBC5CISxAkhhBBCCCFELiJBnBBCCCGEEELkIhLECSGEEEIIIUQuIkGcEELkIUuWLEGj0aDRaLh69Wp2N8cmQ4YMQaPRMHr06OxuishDjh49ikajwd/fn/Dw8OxujhBC2JUEcUIIIbLNkSNHWL58OS4uLrz33nsm+//88081KLXlb8mSJU//SYgcqX79+jzzzDM8fPiQSZMmZXdzhBDCriSIE0IIkW0++OADFEXhhRdeoESJEtndHJHHfPTRRwDMnTuXGzduZHNrhBDCfpyyuwFCCCHypyNHjrBjxw4A3nzzzTTLjxw5ktdee81qGQkEhb4mTZrQqFEjDh06xLRp05g5c2Z2N0kIIexCgjghhBDZYsaMGQA0bNiQcuXKpVm+SJEiVKtWLaubJfKYAQMGcOjQIZYsWcKUKVMoUKBAdjdJCCEyTYZTCiGEeOoiIiJYt24dAAMHDszm1oi87Pnnn8fR0ZGoqCjWrFmT3c0RQgi7kCBOCCHymXv37vHBBx9Qu3ZtfH19cXNzo3Tp0gwePJh9+/bZVMe+ffvo1asXRYsWxc3NjeDgYF599VUuXboEQKtWrdBoNLRq1crs8Zs2bSIhIQGAXr162eV56Zs0aZKa7AS0QeMnn3yiPmdLSVA2btxInz59KFmyJG5ubvj6+lKvXj0mT57Mw4cP03zcmzdvMmrUKIKDg3Fzc6NYsWI8++yz7Ny502y79F29etXmBC2lS5dGo9EwbNgwq+WOHz/Oq6++SsWKFfHy8sLT05OKFSsycuRILly4YPE44yynqampzJs3jyZNmuDn54enpyc1atTg008/JTY2Ns3XJTU1lZUrV9KrVy9KliyJu7s77u7uVKhQgYEDB7J27VqSkpIASEpKomjRomg0Gjp27Jhm3f/884/a1i+//NJkf5EiRWjevDkAK1euTLM+IYTIFRQhhBB5xuLFixVAAZQrV66Y7N+2bZtSoEABtYy5v1GjRikpKSkWH2Pq1KmKRqMxe6y3t7eybds2pWXLlgqgtGzZ0mwdw4YNUwAlKCjI6vPZvXu3WvfEiRNtfh0mTpyoHnfhwgWldOnSJm1dvHixWj48PFxp06aN1delSJEiysGDBy0+5p49e6y+tpMmTTJol7ErV66YbZs5pUqVUgBl6NChZvenpKQo48aNs3ieAMXJyUmZO3eu2eP1/x+dOXNGadu2rcV6GjRooERHR1ts65UrV5RatWpZfW0BZffu3eoxb7/9tgIoDg4Oys2bN62+FuPGjVOfz+3bt82Wee+99xRAcXFxsdpWIYTILaQnTggh8omTJ0/SrVs3IiMjcXZ2Zty4cezevZsjR44wd+5cypQpA8Ds2bMZP3682TpWr17Ne++9h6Io+Pv788UXX3DgwAEOHDjAF198gZOTE/369eP27dtW27J3715AmwY+q/Xu3ZvQ0FDGjBnDjh07OHbsGCtXrqRixYoAJCQk0K5dO/744w8cHR0ZPHgwK1eu5NChQ+zdu5dPP/2UggULcvfuXTp37sy1a9dMHuP69et07dqVyMhIHBwcePXVV9m5cydHjx5l4cKFlC9fnkmTJrF58+Ysf74AY8aMYfr06SiKQosWLVi0aBF//vknR44cYf78+VStWpXk5GReeeUVfvnlF6t1vfTSS+zevZuhQ4eyefNmQkJC2LBhA40bNwa0CWqmTJli9tiwsDCaNm3KyZMnAWjTpg1Lly7l8OHDHDlyhJ9//plXXnkFf39/g+NefPFFQNuDt2zZMottS0pKYvny5QB06tSJokWLmi3XoEEDABITEzl48KDV5yuEELlCdkeRQggh7MdaT1z9+vUVQHF0dFS2bdtmcmx4eLhSpUoVtQfkn3/+MdgfHx+vBAQEKIBSqFAh5eLFiyZ1nD9/XvH391fbYK4nLiwsTN3/ySefWH0++j1xI0eOVE6fPm3xLywsTD1Ov8fLwcHB7PPVef/99xVA8fX1VY4dO2a2zNWrV5XAwEAFUAYMGGCyv3fv3urjrVixwmR/ZGSkUrNmTYOeJ2P26onbvn27Ws+CBQvMHh8XF6f2PJYqVUpJSkoy2K///whQfvzxR5M64uPjlWrVqimAUrBgQZM6FEVRevbsqdbxxRdfWHw+UVFRSnh4uMG25s2bK4BSoUIFi8etX79erX/Dhg0Wy127dk0tN3XqVIvlhBAit5AgTggh8hBLQdzhw4fV7a+++qrF4/ft26eWe+211wz2rVq1St03a9Ysi3XMmDHDahAXEhKi7rc0nE9HP4hL609/uKV+EPfCCy9YrD8qKkrx8fFRAOW7776z2pbvv/9eARRnZ2eDIXm3b99WHB0dFUDp2rWrxeP1z0FWBnG64KxXr15W6zh79qz6eNu3bzfYp///6LnnnrNYx5w5c9Ryf//9t8G+f//9Vx3O2aNHD6ttMWfp0qVq3fv27TNbplu3bupQV3NBpE5cXJxa18svv5zutgghRE4jwymFECIf0CXWABgxYoTFck2bNqVy5comx+jfd3BwsJpRctCgQWYTd+jcu3dPve3n52e94XZgra1//fUXERERgHbYpTUtWrQAtEP4QkJC1O27d+8mJSUFgOHDh1s8vkGDBlStWtXmdmdEZGQkf/75J5D286lcuTKFChUCsDrE0NrrV7duXfX25cuXDfZt3rwZRVEAGDdunNW2mNOnTx98fHwAWLx4scn+sLAwtm7dCsDgwYNxcrK8apKbmxvu7u4A3LlzJ91tEUKIk1FadQAACnpJREFUnEaCOCGEyAf++ecfAFxcXKhVq5bVsg0bNgTg4sWLJCYmmtQRHByMr6+vxeP9/f0JDg62uD88PFy9nZ4gbuLEiSjaESRm/yZNmmT2uBo1alis89ixY+rtwMBANcuhuT/9Ner0A4HTp0+rt9Oa46ebm5VVTpw4QWpqKgD9+/e3+nw0Gg33798HrAc2lSpVsrhPfy5bVFSUSVsAnJ2dadSoUbqfi7u7OwMGDAC0czGNs2D++OOPJCcnA/DCCy+kWZ/u/1pMTEy62yKEEDmNBHFCCJEP6AInf39/qz0WgJocQlEUg7T6utuFCxdO8/GslXFzc1Nvx8XFpVlXZlkLFO/evZuhOvUDCv2gtEiRIlaPCwgIyNDj2coez8eYh4eHxX0ODk++Ruh6I3V0AaK/vz8uLi4ZapcuwUlUVBRr16412KfrnWvYsCFVqlRJsy7d/zVnZ+cMtUUIIXIS65/kQggh8hRrwxyfFv0ATz8AyiqOjo4W9+kHHsePH7f5C36JEiXMbs/u11f/+cydO5cmTZrYdNzTGNaaEXXq1KF27dqcOHGCxYsXM2TIEAAOHz7M2bNnAdt64VJTU9Vhs9Z6kYUQIreQIE4IIfIB3bC3Bw8ekJycbLU3Tje0TqPRGHy5193Wn9NmibUy+kGcLQtoZ6WCBQuqtwsXLmwxOLNG/zUKCwsjKCjIYtmwsDCL+/R7tXRDIi2xNCRQ//l4eHgYDAF92nTz7cLDw0lMTMxUb9yoUaP466+/uHLlCmXKlFF74Tw8POjXr1+adURERKivacmSJTPUDiGEyElkOKUQQuQDui/ziYmJ6ppdlhw5cgSA8uXLG3zx1iXluHz5stXgKzw83CTJhb7g4GB1iN6FCxdsan9WqV27tnp7//79GaqjevXq6u2jR49aLWttv7e3t3o7rdf3wYMHZvfVqlVL7Q3M6POxlzp16gDaRDCZWZtt4MCBuLu7oygKS5YsIS4ujlWrVgHQq1cvChQokGYd+v/Psjq5jBBCPA0SxAkhRD7Qrl079faiRYssljt48KA6TE3/GIC2bdsC2l6iFStWWKxj+fLlalZCc/QTXaQV9GS1du3aqQHlzJkzrbbbktatW6tDNpcuXWqx3NGjR9XkMOb4+fmpQ/30E64YW7VqlcV2Fi5cWH1tV6xYYVOvaVbp0qWLGlB+++23Ga7Hx8dHzbS5dOlS1q5dqw6NtGUoJRj+P9Ml7hFCiNxMgjghhMgHGjRoQL169QCYP38+u3btMikTERHBK6+8AmiH9o0cOdJgf8+ePdXEHZMmTeK///4zqePixYtMnjw5zfY0b94cgFOnTpGQkJC+J2NHvr6+jB49GoADBw4wbtw4q0MZw8LCWLBggcG2wMBAunfvDsAvv/zC6tWrTY6Ljo5WX1trdMsYbNq0yezre/78eT788EOrdXzwwQeAdrmB3r178+jRI4tlExISmD17NvHx8Wm2Lb0qVKhAz549Adi4cSPTpk2zWDYmJsZq76Muwcm1a9d45513AChbtiwtW7a0qS263uWSJUtSsWJFm44RQoicTII4IYTIJ+bPn4+LiwvJycl07tyZt956i7/++otjx44xf/586tSpo6bLf+utt0zmU7m5uak9Kvfv36dhw4ZMmzaNQ4cOcejQIb788ksaNWpEamoq5cuXBywn+tAFPYmJiezduzeLnrFtPv74Y7V3ZsaMGdSpU4fZs2ezf/9+Tp48ye7du5k1axY9evSgZMmSzJkzx6SOr7/+Wh0OOWDAAEaNGsXu3bsJCQlh8eLF1K1blxMnTqiBtCWvvfYaoM2k2KpVKxYuXMjx48fZs2cPEydOpGHDhvj7+1vN/tm5c2def/11APbs2UPlypWZPHkyu3bt4uTJk+zfv5+lS5fy4osvEhgYyOjRo9VU/fb2/fffU6xYMQDeeecd2rZty48//sjRo0c5duwYa9euZdSoUZQsWZK///7bYj0tWrSgQoUKwJM5m8OGDbMpkYyiKOzevRtADSqFECLXy44VxoUQQmSNxYsXK4ACKFeuXDHZv23bNqVAgQJqGXN/o0aNUlJSUiw+xpQpUxSNRmP2WA8PD2Xz5s1K8+bNFUDp2LGjxXrq1q2rAMrw4cMtltm9e7da98SJE21+HSZOnKgeZ4vIyEjlueees/q66P5at25tsa3e3t4Wj/voo49satf//vc/i3WULFlSOXv2rFKqVCkFUIYOHWq2jtTUVGXy5MmKk5NTms/H09NTiY2NNTg+rf9HOleuXFHLLV682GyZ//77T6lWrVqa7di9e7fFx1EURfniiy/Usg4ODsqNGzesltf5888/1eOOHj1q0zFCCJHTSU+cEELkIx06dODSpUu8//771KpViwIFCuDq6krJkiUZOHAge/fuZdasWQaZEo1NmDCBv/76ix49elCkSBFcXV0pVaoUL7zwAseOHaNz585ERkYC2vlMlrz88ssArF+/PluHVII2qci6devYu3cvL774IhUrVsTb2xsnJyf8/f2pX78+o0aNYsuWLezYscNsHa1ateLMmTOMHDmSUqVK4eLiQkBAAF26dOH333+3aZgpaHsDV6xYQYsWLShQoADu7u5UrFiR9957j+PHj1O5cuU069BoNHz00UdcuHCBd955h3r16uHv74+joyPe3t5UqVKFgQMHsnTpUm7fvo27u3u6Xq/0CA4O5uTJkyxZsoQuXboQGBiIs7Mz7u7uVKhQgSFDhrBp0yZ1iK0lgwcPVm+3b9/e5kyiuvmb9evXT7MnVAghcguNomRgFrcQQghhQVJSEj4+PsTFxfHBBx/wySefmC0XHR1NcHAw9+7dY/ny5QwcOPApt/TpmzRpkhrMycdv+uzYsYMOHToA8PPPP9O3b980j4mKiqJkyZI8evSIlStX2rQcgRBC5AbSEyeEEMKuNm7cSFxcHICaKdEcLy8vNUnHZ599lubaaCJ/02VVLViwoDqnMi2zZs3i0aNHVKlSxaagTwghcgsJ4oQQQqTLpUuXLO67evUqb7zxBgABAQE888wzVut69dVXCQ4O5uzZs6xdu9au7RR5x3///af+/xg+fDiurq5pHhMTE8M333wDwLRp06wOERZCiNzGKbsbIIQQInepVKkSnTt3pmvXrlStWhVPT0/u3r3L7t27mTNnjprS/quvvsLJyfrHjLOzM0uWLGHXrl1ZliFR5E6hoaHExsZy+fJl3n33XZKTk3Fzc2PcuHE2HX/t2jVGjRqFv78/nTt3zuLWCiHE0yVz4oQQQqRLWmndHRwcmDJlCuPHj39KLco9ZE6c7Vq1asVff/1lsG3atGm89dZb2dQiIYTIOaQnTgghRLr8+uuvbN26lQMHDhAWFsaDBw9wdXWlePHitGrVilGjRpmsMSdERnl4eFChQgXGjh3L0KFDs7s5QgiRI0hPnBBCCCGEEELkIjLLVwghhBBCCCFyEQnihBBCCCGEECIXkSBOCCGEEEIIIXIRCeKEEEIIIYQQIheRIE4IIYQQQgghchEJ4oQQQgghhBAiF5EgTgghhBBCCCFyEQnihBBCCCGEECIXkSBOCCGEEEIIIXKR/wOnrori7ZRMAQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# With FOOOF\n",
+    "fm = FOOOF(peak_width_limits=[2, 8], aperiodic_mode='knee')\n",
+    "#fm = FOOOF()\n",
+    "fm.report(X,Y , [1, 50], plt_log=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "73ce4ee3",
+   "metadata": {},
+   "source": [
+    "# Moran-David-Friston"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "6c33f325",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sigm(x):\n",
+    "  return (1/(1+math.exp(-rho_1*(x - rho_2)))) - (1/(1+math.exp(rho_1*rho_2)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "2995e9db",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameter settings\n",
+    "start = 0.0\n",
+    "stim_time = 100\n",
+    "dt = 1e-4\n",
+    "time_array = np.arange(start=start, stop=stim_time, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "H_e = 10\n",
+    "H_i = 22 \n",
+    "kappa_e = (1/4) * 1000\n",
+    "kappa_i = (1/16) * 1000 \n",
+    "gamma_1 = 128\n",
+    "gamma_2 =128\n",
+    "gamma_3 = 64\n",
+    "gamma_4 =64\n",
+    "gamma_5 = 1\n",
+    "rho_1 = 2\n",
+    "rho_2 = 1\n",
+    "a= 0    \n",
+    "\n",
+    "#Initialize input and output\n",
+    "x = np.zeros((12,vec_len))\n",
+    "noise = kappa_e*H_e*math.sqrt(dt)*np.random.normal(0, 1, vec_len)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "0ad52bc8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in range (1,vec_len):\n",
+    "  #Inhibitory cells in agranular layers\n",
+    "  x[6,i] = x[6,i-1] + dt * x[7,i-1]\n",
+    "  x[7,i] = x[7,i-1] + dt * (kappa_e*H_e*(gamma_3)*sigm(x[8,i-1]) - 2*kappa_e*x[7,i-1] - kappa_e**(2)*x[6,i-1])\n",
+    "  x[9,i] = x[9,i-1] + dt * x[10,i-1]\n",
+    "  x[10,i] = x[10,i-1] + dt * (kappa_i*H_i*gamma_5*sigm(x[11,i-1]) - 2*kappa_i*x[10,i-1] - kappa_i**(2)*x[9,i-1])\n",
+    "  x[11,i] = x[11,i-1] + dt * (x[7,i-1] - x[10,i-1])\n",
+    "\n",
+    "  #Excitatory spiny cells in granualar layer\n",
+    "  x[0,i] =  x[0,i-1] + dt * x[3,i-1]\n",
+    "  x[3,i] = x[3,i-1] + dt * (kappa_e*H_e*(gamma_1*sigm(x[8,i-1]-a)) - 2*kappa_e*x[3,i-1] - kappa_e**(2)*x[0,i-1]) + noise[i-1]\n",
+    "\n",
+    "  #Excitatory pyramidal cells in agranular layers\n",
+    "  x[1,i] = x[1,i-1] + dt * x[4,i-1]\n",
+    "  x[4,i] =  x[4,i-1] + dt * (kappa_e*H_e*(gamma_2*sigm(x[0,i-1])) - 2*kappa_e*x[4,i-1] - kappa_e**(2)*x[1,i-1])\n",
+    "  x[2,i] = x[2,i-1] + dt * x[5,i-1]\n",
+    "  x[5,i] = x[5,i-1] + dt * (kappa_i*H_i*gamma_4*sigm(x[11,i-1]) - 2*kappa_i*x[5,i-1] - kappa_i**(2)*x[2,i-1])\n",
+    "  x[8,i] = x[8,i-1] + dt * (x[4,i-1] - x[5,i-1])\n",
+    "\n",
+    "output_Moran=x[1,:]-x[2,:]\n",
+    "X_Moran = signal.resample(output_Moran, 10000)\n",
+    "freqs_Moran,ps_vPN_Moran = welch(X_Moran,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "490a736a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Power')"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "X = freqs_Moran\n",
+    "Y = ps_vPN_Moran\n",
+    "pre_X = X[4:40]\n",
+    "pre_Y = Y[4:40]\n",
+    "post_X = X[110:]\n",
+    "post_Y = Y[110:]\n",
+    "full_X = X[10:]\n",
+    "full_Y = Y[10:]\n",
+    "\n",
+    "p1=np.polyfit(np.log(pre_X),np.log(pre_Y),1);\n",
+    "pre_y =np.polyval(p1,np.log(pre_X));\n",
+    "\n",
+    "p2=np.polyfit(np.log(post_X),np.log(post_Y),1);\n",
+    "post_y =np.polyval(p2,np.log(post_X));\n",
+    "\n",
+    "p3=np.polyfit(np.log(full_X),np.log(full_Y),1);\n",
+    "full_y =np.polyval(p3,np.log(full_X));\n",
+    "\n",
+    "\n",
+    "plt.plot(X,Y)\n",
+    "plt.plot(pre_X,np.exp(pre_y), color=\"red\")\n",
+    "plt.plot(post_X,np.exp(post_y), color=\"red\")\n",
+    "plt.plot(full_X,np.exp(full_y), color=\"orange\")\n",
+    "\n",
+    "plt.xscale(\"log\")\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xlabel(\"Frequency\")\n",
+    "plt.ylabel(\"Power\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "409a7c37",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-0.0058713184697635635\n",
+      "-5.275958705214585\n",
+      "-2.479894771278701\n"
+     ]
+    }
+   ],
+   "source": [
+    "slope_pre, intercept = np.polyfit(np.log(pre_X),np.log(pre_Y),1);\n",
+    "print(slope_pre)\n",
+    "slope_post, intercept=np.polyfit(np.log(post_X),np.log(post_Y),1);\n",
+    "print(slope_post)\n",
+    "full_slope, intercept=np.polyfit(np.log(full_X),np.log(full_Y),1);\n",
+    "print(full_slope)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "b45d9970",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "==================================================================================================\n",
+      "                                                                                                  \n",
+      "                                   FOOOF - POWER SPECTRUM MODEL                                   \n",
+      "                                                                                                  \n",
+      "                        The model was run on the frequency range 1 - 50 Hz                        \n",
+      "                                 Frequency Resolution is 0.10 Hz                                  \n",
+      "                                                                                                  \n",
+      "                         Aperiodic Parameters (offset, knee, exponent):                           \n",
+      "                                 7.8943, 1399311426.1184, 7.2981                                  \n",
+      "                                                                                                  \n",
+      "                                       7 peaks were found:                                        \n",
+      "                                CF:   8.79, PW:  1.385, BW:  2.11                                 \n",
+      "                                CF:  17.60, PW:  0.798, BW:  2.13                                 \n",
+      "                                CF:  20.75, PW:  0.056, BW:  2.30                                 \n",
+      "                                CF:  26.26, PW:  0.578, BW:  2.93                                 \n",
+      "                                CF:  43.88, PW:  0.691, BW:  2.00                                 \n",
+      "                                CF:  46.25, PW:  0.693, BW:  2.00                                 \n",
+      "                                CF:  49.60, PW:  0.760, BW:  7.62                                 \n",
+      "                                                                                                  \n",
+      "                                     Goodness of fit metrics:                                     \n",
+      "                                    R^2 of model fit is 0.9865                                    \n",
+      "                                    Error of the fit is 0.1072                                    \n",
+      "                                                                                                  \n",
+      "==================================================================================================\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fm = FOOOF(peak_width_limits=[2, 8], aperiodic_mode='knee')\n",
+    "#fm = FOOOF()\n",
+    "fm.report(X,Y , [1, 50], plt_log=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "73d6a356",
+   "metadata": {},
+   "source": [
+    "# Liley-Wright"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "de7428d3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def dynamics(p,X):\n",
+    "    dX = np.zeros((18,1))\n",
+    "\n",
+    "    # Calculate synaptic reversal potentials\n",
+    "    psi_ee=(p.h_ee_eq-X[0])/abs(p.h_ee_eq-p.h_e_r)\n",
+    "    psi_ie=(p.h_ie_eq-X[0])/abs(p.h_ie_eq-p.h_e_r)\n",
+    "    psi_ei=(p.h_ei_eq-X[1])/abs(p.h_ei_eq-p.h_i_r)\n",
+    "    psi_ii=(p.h_ii_eq-X[1])/abs(p.h_ii_eq-p.h_i_r)\n",
+    "\n",
+    "    # Calculate synaptic inputs A_jk \n",
+    "    A_ee=p.N_ee_b*S_e(p,X[0])+X[10]+p.p_ee\n",
+    "    A_ei=p.N_ei_b*S_e(p,X[0])+X[12]+p.p_ei\n",
+    "    A_ie=p.N_ie_b*S_i(p,X[1])\n",
+    "    A_ii=p.N_ii_b*S_i(p,X[1])   \n",
+    "\n",
+    "    # Calculate state vector\n",
+    "    dX[0] = (1/p.tau_e)*(p.h_e_r-X[0]+psi_ee*X[2]+psi_ie*X[6]) # V_e\n",
+    "    dX[1] = (1/p.tau_i)*(p.h_i_r-X[1]+psi_ei*X[4]+psi_ii*X[8]) # V_i\n",
+    "    dX[2] = X[3] # I_ee\n",
+    "    dX[3] = -2*p.gamma_ee*X[3]-p.gamma_ee**(2)*X[2]+p.gamma_ee*math.exp(1)*p.Gamma_ee*A_ee# J_ee\n",
+    "    dX[4] = X[5] # I_ei\n",
+    "    dX[5] = -2*p.gamma_ei*X[5]-p.gamma_ei**(2)*X[4]+p.gamma_ei*math.exp(1)*p.Gamma_ei*A_ei# J_ei\n",
+    "    dX[6] = X[7] # I_ie\n",
+    "    dX[7] = -2*p.gamma_ie*X[7]-p.gamma_ie**(2)*X[6]+p.gamma_ie*math.exp(1)*p.Gamma_ie*A_ie# J_ie\n",
+    "    dX[8] = X[9] # I_ii\n",
+    "    dX[9] = -2*p.gamma_ii*X[9]-p.gamma_ii**(2)*X[8]+p.gamma_ii*math.exp(1)*p.Gamma_ii*A_ii# J_ii% J_ii\n",
+    "    return dX\n",
+    "    \n",
+    "def S_e(t,v):   \n",
+    "    p = t\n",
+    "    spikerate = p.S_e_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_e)/p.sigma_e))\n",
+    "    return spikerate\n",
+    "\n",
+    "def S_i(t,v):\n",
+    "    p=t\n",
+    "    spikerate = p.S_i_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_i)/p.sigma_i))\n",
+    "    return spikerate\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "5ef084fa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class p:\n",
+    "  S_e_max = 0.5\n",
+    "  S_i_max = 0.5\n",
+    "  h_e_r = -70\n",
+    "  h_i_r = -70\n",
+    "  mu_e = -50\n",
+    "  mu_i = -50\n",
+    "  sigma_e = 5\n",
+    "  sigma_i = 5\n",
+    "  tau_e = 94\n",
+    "  tau_i = 42\n",
+    "  h_ee_eq = 45\n",
+    "  h_ei_eq = 45\n",
+    "  h_ie_eq = -90\n",
+    "  h_ii_eq = -90\n",
+    "  Gamma_ee = 0.71\n",
+    "  Gamma_ei = 0.71\n",
+    "  Gamma_ie = 0.71\n",
+    "  Gamma_ii = 0.71\n",
+    "  gamma_ee = 0.3\n",
+    "  gamma_ei = 0.3\n",
+    "  gamma_ie = 0.065\n",
+    "  gamma_ii = 0.065\n",
+    "  p_ee = 3.460\n",
+    "  p_ee_sd = 1.000\n",
+    "  p_ei = 5.070\n",
+    "  p_ei_sd = 0\n",
+    "  p_ie = 0\n",
+    "  p_ii = 0\n",
+    "  N_ei_b = 3000 \n",
+    "  N_ee_b = 3000\n",
+    "  N_ie_b = 500 \n",
+    "  N_ii_b = 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "6dcba5dd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sim_time= 100        \n",
+    "dt = 1e-4\n",
+    "steps=  1/dt           \n",
+    "white_noise=1         \n",
+    "\n",
+    "p.v_e_equil = p.h_e_r\n",
+    "p.v_i_equil = p.h_i_r\n",
+    "h = 1000/steps        \n",
+    "T = sim_time*10**3      \n",
+    "N = T/h-1\n",
+    "\n",
+    "X = np.zeros((18,int(N)))\n",
+    "X[0,0] = p.v_e_equil\n",
+    "X[1,0] = p.v_i_equil    \n",
+    "X[2,0] = math.exp(1)/p.gamma_ee*p.Gamma_ee*(p.N_ee_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ee)   \n",
+    "X[4,0] = math.exp(1)/p.gamma_ei*p.Gamma_ei*(p.N_ei_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ei)\n",
+    "X[6,0] = math.exp(1)/p.gamma_ie*p.Gamma_ie*(p.N_ie_b*S_i(p,p.v_i_equil))\n",
+    "X[8,0] = math.exp(1)/p.gamma_ii*p.Gamma_ii*(p.N_ii_b*S_i(p,p.v_i_equil))\n",
+    " \n",
+    "for n in range (0,int(N-1)):\n",
+    "    noise = np.zeros((18,1))\n",
+    "    if (white_noise==1):\n",
+    "      noise[3]= p.gamma_ee*math.exp(p.gamma_ee/p.gamma_ee)*p.Gamma_ee*p.p_ee_sd*np.random.randn(1,1)\n",
+    "    X[:,n+1] = X[:,n] + ((h*dynamics(p,X[:,n])+math.sqrt(h)*noise).flatten())\n",
+    "EEG=-X[0,:]\n",
+    "\n",
+    "new_EEG =signal.resample(EEG,10000)\n",
+    "freqs_Liley,ps_vPN_Liley = welch(new_EEG,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "c9ec3d30",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Power')"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "X = freqs_Liley\n",
+    "Y = ps_vPN_Liley\n",
+    "pre_X = X[10:90]\n",
+    "pre_Y = Y[10:90]\n",
+    "post_X = X[140:]\n",
+    "post_Y = Y[140:]\n",
+    "full_X = X[10:]\n",
+    "full_Y = Y[10:]\n",
+    "\n",
+    "p1=np.polyfit(np.log(pre_X),np.log(pre_Y),1);\n",
+    "pre_y =np.polyval(p1,np.log(pre_X));\n",
+    "\n",
+    "p2=np.polyfit(np.log(post_X),np.log(post_Y),1);\n",
+    "post_y =np.polyval(p2,np.log(post_X));\n",
+    "\n",
+    "p3=np.polyfit(np.log(full_X),np.log(full_Y),1);\n",
+    "full_y =np.polyval(p3,np.log(full_X));\n",
+    "\n",
+    "\n",
+    "plt.plot(X,Y)\n",
+    "plt.plot(pre_X,np.exp(pre_y), color=\"red\")\n",
+    "plt.plot(post_X,np.exp(post_y), color=\"red\")\n",
+    "plt.plot(full_X,np.exp(full_y), color=\"orange\")\n",
+    "\n",
+    "plt.xscale(\"log\")\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xlabel(\"Frequency\")\n",
+    "plt.ylabel(\"Power\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "f4139359",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-0.4400558649689569\n",
+      "-2.532782000322536\n",
+      "-3.2774669855508987\n"
+     ]
+    }
+   ],
+   "source": [
+    "slope_pre, intercept = np.polyfit(np.log(pre_X),np.log(pre_Y),1);\n",
+    "print(slope_pre)\n",
+    "slope_post, intercept=np.polyfit(np.log(post_X),np.log(post_Y),1);\n",
+    "print(slope_post)\n",
+    "full_slope, intercept=np.polyfit(np.log(full_X),np.log(full_Y),1);\n",
+    "print(full_slope)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "a6f19230",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "==================================================================================================\n",
+      "                                                                                                  \n",
+      "                                   FOOOF - POWER SPECTRUM MODEL                                   \n",
+      "                                                                                                  \n",
+      "                        The model was run on the frequency range 1 - 50 Hz                        \n",
+      "                                 Frequency Resolution is 0.10 Hz                                  \n",
+      "                                                                                                  \n",
+      "                         Aperiodic Parameters (offset, knee, exponent):                           \n",
+      "                                     1.2384, 277.4299, 3.8400                                     \n",
+      "                                                                                                  \n",
+      "                                       7 peaks were found:                                        \n",
+      "                                CF:   9.07, PW:  0.826, BW:  4.06                                 \n",
+      "                                CF:  11.46, PW:  2.091, BW:  2.00                                 \n",
+      "                                CF:  13.30, PW:  0.925, BW:  2.00                                 \n",
+      "                                CF:  31.20, PW:  0.167, BW:  7.07                                 \n",
+      "                                CF:  36.93, PW:  0.359, BW:  4.52                                 \n",
+      "                                CF:  41.39, PW:  0.435, BW:  2.00                                 \n",
+      "                                CF:  46.89, PW:  0.463, BW:  8.00                                 \n",
+      "                                                                                                  \n",
+      "                                     Goodness of fit metrics:                                     \n",
+      "                                    R^2 of model fit is 0.9835                                    \n",
+      "                                    Error of the fit is 0.1294                                    \n",
+      "                                                                                                  \n",
+      "==================================================================================================\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fm = FOOOF(peak_width_limits=[2, 8], aperiodic_mode='knee')\n",
+    "#fm = FOOOF()\n",
+    "fm.report(X,Y , [1, 50], plt_log=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c55c6486",
+   "metadata": {},
+   "source": [
+    "# Robinson-Rennie-Wright"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "84ea917f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sig(v,Qmax,theta,sigma):\n",
+    " # sigmoid for voltage-rate relationship\n",
+    " firing_rate = Qmax / (1 + math.exp(-(v-theta) / sigma))\n",
+    " return firing_rate\n",
+    "\n",
+    "def sigr(v,Qmax_r,modtheta,sigma_r):\n",
+    " # sigmoid for voltage-rate relationship in reticular nucleus\n",
+    " firing_rate = Qmax_r / (1 + math.exp(-(v-modtheta) / sigma_r));\n",
+    " return firing_rate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "a1bd194d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameter settings\n",
+    "gamma = 116 \n",
+    "t0 = 80e-3 \n",
+    "Qmax = 340 \n",
+    "theta = 12.92e-3 \n",
+    "sigma = 3.8e-3\n",
+    "Qmax_r = 100 \n",
+    "sigma_r = 3.8e-3\n",
+    "phin_0 = 1.0 \n",
+    "\n",
+    "nu_ee = 0.00303 \n",
+    "nu_ei = -0.006 \n",
+    "nu_es = 0.00206\n",
+    "nu_ie = 0.00303\n",
+    "nu_ii = -0.006\n",
+    "nu_is = 0.00206\n",
+    "nu_re = 0.00033\n",
+    "nu_rs =  0.00003\n",
+    "nu_se = 0.00218\n",
+    "nu_sr = -0.00083\n",
+    "nu_sn = 0.00098\n",
+    "alpha = 83.33 \n",
+    "beta = 769.23 \n",
+    "phin = 5e-4\n",
+    "\n",
+    "start = 0.0\n",
+    "stop = 100.0 + t0/2\n",
+    "dt = 1e-4\n",
+    "k0 = int(t0/2/dt)\n",
+    "time_array = np.arange(start=start, stop=stop, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "np.random.seed(0)\n",
+    "noise = alpha*beta*nu_sn*math.sqrt(phin*dt)*np.random.randn(vec_len,1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "eef9b69c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Outputs\n",
+    "phie = np.zeros(vec_len)\n",
+    "Ve = np.zeros(vec_len)\n",
+    "Vr = np.zeros(vec_len)\n",
+    "Vs = np.zeros(vec_len)\n",
+    "phiedot = np.zeros(vec_len)\n",
+    "Vedot = np.zeros(vec_len)\n",
+    "Vrdot = np.zeros(vec_len)\n",
+    "Vsdot = np.zeros(vec_len)\n",
+    "\n",
+    "# Initialize output\n",
+    "phie[0:(k0+1)] = 3.175\n",
+    "Ve[0:(k0+1)]  = 0.0006344; \n",
+    "Vr[0:(k0+1)]  = 0.005676;\n",
+    "Vs[0:(k0+1)]  = -0.003234;\n",
+    "\n",
+    "for i in range ((k0+1),(int(stop/dt))):\n",
+    "    Ve[i] = Ve[i-1] + Vedot[i-1]*dt\n",
+    "    Vedot[i] = Vedot[i-1] + dt *( alpha*beta * ( nu_ee*phie[i-1] + nu_ei*sig(Ve[i-1],Qmax,theta,sigma) + nu_es*sig(Vs[i-1-k0],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vedot[i-1] - Ve[i-1] ) )\n",
+    "      \n",
+    "    Vr[i] = Vr[i-1] + Vrdot[i-1]*dt\n",
+    "    Vrdot[i] = Vrdot[i-1] + dt*( alpha*beta * ( nu_re*phie[i-1-k0] + nu_rs*sig(Vs[i-1],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vrdot[i-1] - Vr[i-1] ))\n",
+    "    \n",
+    "    Vs[i] = Vs[i-1] + Vsdot[i-1]*dt\n",
+    "    Vsdot[i] = Vsdot[i-1] + dt*( alpha*beta * ( nu_se*phie[i-1-k0] + nu_sr*sigr(Vr[i-1],Qmax,theta,sigma_r) - (1/alpha + 1/beta)*Vsdot[i-1] - Vs[i-1] + nu_sn*phin_0 )) + noise[i-1]\n",
+    "    \n",
+    "    phie[i] = phie[i-1] + phiedot[i-1]*dt\n",
+    "    phiedot[i] = phiedot[i-1] + dt*( gamma**(2) * ( sig(Ve[i-1],Qmax,theta,sigma) - 2/gamma*phiedot[i-1] - phie[i-1] ))\n",
+    "\n",
+    "phie = phie[(k0+1):len(phie)]\n",
+    "Ve = Ve[(k0+1):len(Ve)]\n",
+    "Vr = Vr[(k0+1):len(Vr)]\n",
+    "Vs = Vs[(k0+1):len(Vs)];\n",
+    "time_array = time_array[(k0+1):len(time_array)];\n",
+    "\n",
+    "X=signal.resample(phie,10000)\n",
+    "output_Zhao = phie;\n",
+    "freqs_Robinson,ps_vPN_Robinson = welch(X[1000:],fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "798f6c23",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "X = freqs_Robinson\n",
+    "Y = ps_vPN_Robinson\n",
+    "pre_X = X[10:60]\n",
+    "pre_Y = Y[10:60]\n",
+    "post_X = X[60:]\n",
+    "post_Y = Y[60:]\n",
+    "full_X = X[10:]\n",
+    "full_Y = Y[10:]\n",
+    "\n",
+    "p1=np.polyfit(np.log(pre_X),np.log(pre_Y),1);\n",
+    "pre_y =np.polyval(p1,np.log(pre_X));\n",
+    "\n",
+    "p2=np.polyfit(np.log(post_X),np.log(post_Y),1);\n",
+    "post_y =np.polyval(p2,np.log(post_X));\n",
+    "\n",
+    "p3=np.polyfit(np.log(full_X),np.log(full_Y),1);\n",
+    "full_y =np.polyval(p3,np.log(full_X));\n",
+    "\n",
+    "plt.plot(X,Y)\n",
+    "plt.plot(pre_X,np.exp(pre_y), color=\"red\")\n",
+    "plt.plot(post_X,np.exp(post_y), color=\"red\")\n",
+    "plt.plot(full_X,np.exp(full_y), color=\"orange\")\n",
+    "\n",
+    "plt.xlabel('Frequency')\n",
+    "plt.ylabel('Power')\n",
+    "plt.xscale(\"log\")\n",
+    "plt.yscale(\"log\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "de0e4bf0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-1.3978074561663054\n",
+      "-3.764284644231031\n",
+      "-2.614682802381492\n"
+     ]
+    }
+   ],
+   "source": [
+    "slope_pre, intercept = np.polyfit(np.log(pre_X),np.log(pre_Y),1);\n",
+    "print(slope_pre)\n",
+    "slope_post, intercept=np.polyfit(np.log(post_X),np.log(post_Y),1);\n",
+    "print(slope_post)\n",
+    "full_slope, intercept=np.polyfit(np.log(full_X),np.log(full_Y),1);\n",
+    "print(full_slope)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "5a593d0b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "==================================================================================================\n",
+      "                                                                                                  \n",
+      "                                   FOOOF - POWER SPECTRUM MODEL                                   \n",
+      "                                                                                                  \n",
+      "                        The model was run on the frequency range 1 - 50 Hz                        \n",
+      "                                 Frequency Resolution is 0.10 Hz                                  \n",
+      "                                                                                                  \n",
+      "                         Aperiodic Parameters (offset, knee, exponent):                           \n",
+      "                                    -0.1323, 4257.7924, 3.9146                                    \n",
+      "                                                                                                  \n",
+      "                                       7 peaks were found:                                        \n",
+      "                                CF:   9.23, PW:  0.745, BW:  2.18                                 \n",
+      "                                CF:  19.29, PW:  0.528, BW:  3.07                                 \n",
+      "                                CF:  25.80, PW:  0.144, BW:  4.73                                 \n",
+      "                                CF:  29.05, PW:  0.272, BW:  2.00                                 \n",
+      "                                CF:  31.69, PW:  0.311, BW:  2.00                                 \n",
+      "                                CF:  37.09, PW:  0.140, BW:  8.00                                 \n",
+      "                                CF:  43.55, PW:  0.148, BW:  2.00                                 \n",
+      "                                                                                                  \n",
+      "                                     Goodness of fit metrics:                                     \n",
+      "                                    R^2 of model fit is 0.9753                                    \n",
+      "                                    Error of the fit is 0.1236                                    \n",
+      "                                                                                                  \n",
+      "==================================================================================================\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fm = FOOOF(peak_width_limits=[2, 8], aperiodic_mode='knee')\n",
+    "#fm = FOOOF()\n",
+    "fm.report(X,Y , [1, 50], plt_log=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3afbee1b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "alpha",
+   "language": "python",
+   "name": "alpha"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/content/Eyes_closed_eyes_open.ipynb b/content/Eyes_closed_eyes_open.ipynb
new file mode 100644
index 0000000..8827752
--- /dev/null
+++ b/content/Eyes_closed_eyes_open.ipynb
@@ -0,0 +1,626 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "41a04278",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "from scipy import signal\n",
+    "from scipy.signal import welch"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dc171f2c",
+   "metadata": {},
+   "source": [
+    "# Jansen-Rit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "8e523ca2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sigm(nu_max,v0,r,v):\n",
+    "  action_potential = (2*nu_max)/(1+math.exp(r*(v0-v)))\n",
+    "  return action_potential"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "5e48d290",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameters Eyes Closed (original param)\n",
+    "A = 3.25\n",
+    "B = 22\n",
+    "C = 135\n",
+    "C1 = 1*C\n",
+    "C2 = 0.8*C \n",
+    "C3 = 0.25*C \n",
+    "C4 = 0.25*C\n",
+    "v0 = 6    \n",
+    "a = 100 \n",
+    "b = 50        \n",
+    "nu_max = 2.5 \n",
+    "r = 0.56       \n",
+    "\n",
+    "start = 0.0\n",
+    "stim_time =100\n",
+    "dt = 1e-4\n",
+    "time_array = np.arange(start=start, stop=stim_time, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "noise = np.random.uniform(120,320,vec_len)\n",
+    "y = np.zeros((6,vec_len))\n",
+    "\n",
+    "for i in range (1,vec_len):\n",
+    "  y[0,i] = y[0,i-1] + y[3,i-1]*dt\n",
+    "  y[1,i] = y[1,i-1] + y[4,i-1]*dt\n",
+    "  y[2,i] = y[2,i-1] + y[5,i-1]*dt\n",
+    "  y[3,i] = y[3,i-1] + dt * (A*a*(sigm(nu_max,v0,r,(y[1,i-1]-y[2,i-1]))) - (2*a*y[3,i-1]) - (a**(2)*y[0,i-1]))\n",
+    "  y[4,i] = y[4,i-1] + dt * (A*a*(noise[i-1] + (C2*sigm(nu_max,v0,r,(C1*y[0,i-1])))) - (2*a*y[4,i-1]) - (a**(2)*y[1,i-1]))\n",
+    "  y[5,i] = y[5,i-1] + dt * (B*b*(C4*sigm(nu_max,v0,r,(C3*y[0,i-1]))) - (2*b*y[5,i-1]) - (b**(2)*y[2,i-1]))\n",
+    "\n",
+    "output_EYES_CLOSED = y[1,:]-y[2,:]\n",
+    "X = signal.resample(output_EYES_CLOSED, 10000)\n",
+    "freqs_EC ,ps_vPN_EC = welch(X,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "f267c4e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "A = 3.25\n",
+    "B = 22\n",
+    "C = 135\n",
+    "C1 = 1*C\n",
+    "C2 = 0.8*C\n",
+    "C3 = 0.25*C \n",
+    "C4 = 0.25*C\n",
+    "v0 = 6         \n",
+    "a = 100        \n",
+    "b = 50        \n",
+    "nu_max = 2.5   \n",
+    "r = 0.56      \n",
+    "\n",
+    "start = 0.0\n",
+    "stim_time =100\n",
+    "dt = 1e-4\n",
+    "time_array = np.arange(start=start, stop=stim_time, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "noise = np.random.uniform(500,200+500,vec_len)\n",
+    "y = np.zeros((6,vec_len))\n",
+    "\n",
+    "for i in range (1,vec_len):\n",
+    "  y[0,i] = y[0,i-1] + y[3,i-1]*dt\n",
+    "  y[1,i] = y[1,i-1] + y[4,i-1]*dt\n",
+    "  y[2,i] = y[2,i-1] + y[5,i-1]*dt\n",
+    "  y[3,i] = y[3,i-1] + dt * (A*a*(sigm(nu_max,v0,r,(y[1,i-1]-y[2,i-1]))) - (2*a*y[3,i-1]) - (a**(2)*y[0,i-1]))\n",
+    "  y[4,i] = y[4,i-1] + dt * (A*a*(noise[i-1] + (C2*sigm(nu_max,v0,r,(C1*y[0,i-1])))) - (2*a*y[4,i-1]) - (a**(2)*y[1,i-1]))\n",
+    "  y[5,i] = y[5,i-1] + dt * (B*b*(C4*sigm(nu_max,v0,r,(C3*y[0,i-1]))) - (2*b*y[5,i-1]) - (b**(2)*y[2,i-1]))\n",
+    "\n",
+    "output_EYES_OPEN = y[1,:]-y[2,:]\n",
+    "X = signal.resample(output_EYES_OPEN, 10000)\n",
+    "freqs_EO,ps_vPN_EO = welch(X,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "7e6808fb",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
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+      "text/plain": [
+       "<Figure size 4000x3000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(4, 3), dpi =1000)\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xscale(\"log\")\n",
+    "plt.plot(freqs_EC,ps_vPN_EC, color= plt.cm.Dark2(6))\n",
+    "plt.plot(freqs_EO,ps_vPN_EO,color = plt.cm.Dark2(7))\n",
+    "plt.xlabel('Frequency (Hz)')\n",
+    "plt.ylabel('Power (A.U.)')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "16503651",
+   "metadata": {},
+   "source": [
+    "# Liley-Wright"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "bc470997",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def dynamics(p,X):\n",
+    "    dX = np.zeros((18,1))\n",
+    "\n",
+    "    psi_ee=(p.h_ee_eq-X[0])/abs(p.h_ee_eq-p.h_e_r)\n",
+    "    psi_ie=(p.h_ie_eq-X[0])/abs(p.h_ie_eq-p.h_e_r)\n",
+    "    psi_ei=(p.h_ei_eq-X[1])/abs(p.h_ei_eq-p.h_i_r)\n",
+    "    psi_ii=(p.h_ii_eq-X[1])/abs(p.h_ii_eq-p.h_i_r)\n",
+    "\n",
+    "    A_ee=p.N_ee_b*S_e(p,X[0])+X[10]+p.p_ee\n",
+    "    A_ei=p.N_ei_b*S_e(p,X[0])+X[12]+p.p_ei\n",
+    "    A_ie=p.N_ie_b*S_i(p,X[1])\n",
+    "    A_ii=p.N_ii_b*S_i(p,X[1])   \n",
+    "\n",
+    "\n",
+    "    dX[0] = (1/p.tau_e)*(p.h_e_r-X[0]+psi_ee*X[2]+psi_ie*X[6])\n",
+    "    dX[1] = (1/p.tau_i)*(p.h_i_r-X[1]+psi_ei*X[4]+psi_ii*X[8])\n",
+    "    dX[2] = X[3] \n",
+    "    dX[3] = -2*p.gamma_ee*X[3]-p.gamma_ee**(2)*X[2]+p.gamma_ee*math.exp(1)*p.Gamma_ee*A_ee\n",
+    "    dX[4] = X[5] \n",
+    "    dX[5] = -2*p.gamma_ei*X[5]-p.gamma_ei**(2)*X[4]+p.gamma_ei*math.exp(1)*p.Gamma_ei*A_ei\n",
+    "    dX[6] = X[7] \n",
+    "    dX[7] = -2*p.gamma_ie*X[7]-p.gamma_ie**(2)*X[6]+p.gamma_ie*math.exp(1)*p.Gamma_ie*A_ie\n",
+    "    dX[8] = X[9] \n",
+    "    dX[9] = -2*p.gamma_ii*X[9]-p.gamma_ii**(2)*X[8]+p.gamma_ii*math.exp(1)*p.Gamma_ii*A_ii\n",
+    "    return dX\n",
+    "    \n",
+    "def S_e(t,v):   \n",
+    "    p = t\n",
+    "    spikerate = p.S_e_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_e)/p.sigma_e))\n",
+    "    return spikerate\n",
+    "\n",
+    "def S_i(t,v):\n",
+    "    p=t\n",
+    "    spikerate = p.S_i_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_i)/p.sigma_i))\n",
+    "    return spikerate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "6d7b532d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameters for eyes-open with changes in p_ei\n",
+    "class p:\n",
+    "  S_e_max = 0.5\n",
+    "  S_i_max = 0.5\n",
+    "  h_e_r = -70\n",
+    "  h_i_r = -70\n",
+    "  mu_e = -50\n",
+    "  mu_i = -50\n",
+    "  sigma_e = 5\n",
+    "  sigma_i = 5\n",
+    "  tau_e = 94\n",
+    "  tau_i = 42\n",
+    "  h_ee_eq = 4\n",
+    "  h_ei_eq = 45\n",
+    "  h_ie_eq = -90\n",
+    "  h_ii_eq = -90\n",
+    "  Gamma_ee = 0.71\n",
+    "  Gamma_ei = 0.71\n",
+    "  Gamma_ie = 0.71\n",
+    "  Gamma_ii = 0.71\n",
+    "  gamma_ee = 0.3\n",
+    "  gamma_ei = 0.3\n",
+    "  gamma_ie = 0.065\n",
+    "  gamma_ii = 0.065\n",
+    "  p_ee = 3.460\n",
+    "  p_ee_sd = 1.000\n",
+    "  p_ei = 6 \n",
+    "  p_ei_sd = 0\n",
+    "  p_ie = 0\n",
+    "  p_ii = 0\n",
+    "  N_ei_b = 3000\n",
+    "  N_ee_b = 3000\n",
+    "  N_ie_b = 500\n",
+    "  N_ii_b = 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "b6500510",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sim_time= 100           \n",
+    "dt = 1e-4\n",
+    "steps=  1/dt         \n",
+    "white_noise=1        \n",
+    "\n",
+    "p.v_e_equil = p.h_e_r\n",
+    "p.v_i_equil = p.h_i_r\n",
+    "h = 1000/steps \n",
+    "T = sim_time*10**3 \n",
+    "N = T/h-1\n",
+    "\n",
+    "X = np.zeros((18,int(N)))\n",
+    "X[0,0] = p.v_e_equil\n",
+    "X[1,0] = p.v_i_equil    \n",
+    "X[2,0] = math.exp(1)/p.gamma_ee*p.Gamma_ee*(p.N_ee_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ee)    \n",
+    "X[4,0] = math.exp(1)/p.gamma_ei*p.Gamma_ei*(p.N_ei_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ei)\n",
+    "X[6,0] = math.exp(1)/p.gamma_ie*p.Gamma_ie*(p.N_ie_b*S_i(p,p.v_i_equil))\n",
+    "X[8,0] = math.exp(1)/p.gamma_ii*p.Gamma_ii*(p.N_ii_b*S_i(p,p.v_i_equil))\n",
+    " \n",
+    "for n in range (0,int(N-1)):\n",
+    "    noise = np.zeros((18,1))\n",
+    "    if (white_noise==1):\n",
+    "      noise[3]= p.gamma_ee*math.exp(p.gamma_ee/p.gamma_ee)*p.Gamma_ee*p.p_ee_sd*np.random.randn(1,1)\n",
+    "    X[:,n+1] = X[:,n] + ((h*dynamics(p,X[:,n])+math.sqrt(h)*noise).flatten())\n",
+    "EEG=-X[0,:]\n",
+    "\n",
+    "new_EEG =signal.resample(EEG,10000)\n",
+    "freqs_OPEN,ps_vPN_OPEN = welch(new_EEG,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "16e5e520",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameters for eyes-closed (original values)\n",
+    "class p:\n",
+    "  S_e_max = 0.5\n",
+    "  S_i_max = 0.5\n",
+    "  h_e_r = -70\n",
+    "  h_i_r = -70\n",
+    "  mu_e = -50\n",
+    "  mu_i = -50\n",
+    "  sigma_e = 5\n",
+    "  sigma_i = 5\n",
+    "  tau_e = 94\n",
+    "  tau_i = 42\n",
+    "  h_ee_eq = 4\n",
+    "  h_ei_eq = 45\n",
+    "  h_ie_eq = -90\n",
+    "  h_ii_eq = -90\n",
+    "  Gamma_ee = 0.71\n",
+    "  Gamma_ei = 0.71\n",
+    "  Gamma_ie = 0.71\n",
+    "  Gamma_ii = 0.71\n",
+    "  gamma_ee = 0.3\n",
+    "  gamma_ei = 0.3\n",
+    "  gamma_ie = 0.065\n",
+    "  gamma_ii = 0.065\n",
+    "  p_ee = 3.460\n",
+    "  p_ee_sd = 1.000\n",
+    "  p_ei = 5.070\n",
+    "  p_ei_sd = 0\n",
+    "  p_ie = 0\n",
+    "  p_ii = 0\n",
+    "  N_ei_b = 3000\n",
+    "  N_ee_b = 3000\n",
+    "  N_ie_b = 500\n",
+    "  N_ii_b = 500"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "eea8361f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sim_time= 100          \n",
+    "dt = 1e-4\n",
+    "steps=  1/dt            \n",
+    "white_noise=1         \n",
+    "\n",
+    "p.v_e_equil = p.h_e_r\n",
+    "p.v_i_equil = p.h_i_r\n",
+    "h = 1000/steps \n",
+    "T = sim_time*10**3 \n",
+    "N = T/h-1\n",
+    "\n",
+    "X = np.zeros((18,int(N)))\n",
+    "X[0,0] = p.v_e_equil  \n",
+    "X[1,0] = p.v_i_equil    \n",
+    "X[2,0] = math.exp(1)/p.gamma_ee*p.Gamma_ee*(p.N_ee_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ee)   \n",
+    "X[4,0] = math.exp(1)/p.gamma_ei*p.Gamma_ei*(p.N_ei_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ei)\n",
+    "X[6,0] = math.exp(1)/p.gamma_ie*p.Gamma_ie*(p.N_ie_b*S_i(p,p.v_i_equil))#\n",
+    "X[8,0] = math.exp(1)/p.gamma_ii*p.Gamma_ii*(p.N_ii_b*S_i(p,p.v_i_equil))#\n",
+    " \n",
+    "for n in range (0,int(N-1)):\n",
+    "    noise = np.zeros((18,1))\n",
+    "    if (white_noise==1):\n",
+    "      noise[3]= p.gamma_ee*math.exp(p.gamma_ee/p.gamma_ee)*p.Gamma_ee*p.p_ee_sd*np.random.randn(1,1)\n",
+    "    X[:,n+1] = X[:,n] + ((h*dynamics(p,X[:,n])+math.sqrt(h)*noise).flatten())\n",
+    "EEG=-X[0,:]\n",
+    "\n",
+    "new_EEG =signal.resample(EEG,10000)\n",
+    "freqs_CLOSED,ps_vPN_CLOSED = welch(new_EEG,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "811634b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+      "text/plain": [
+       "<Figure size 4000x3000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(4, 3), dpi =1000)\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xscale(\"log\")\n",
+    "plt.plot(freqs_CLOSED,ps_vPN_CLOSED, color= plt.cm.Dark2(6))\n",
+    "plt.plot(freqs_OPEN,ps_vPN_OPEN,color = plt.cm.Dark2(7))\n",
+    "plt.xlabel('Frequency (Hz)')\n",
+    "plt.ylabel('Power (A.U.)')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f5c94cca",
+   "metadata": {},
+   "source": [
+    "# Robinson-Rennie-Wright"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "96a1f797",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sig(v,Qmax,theta,sigma):\n",
+    " firing_rate = Qmax / (1 + math.exp(-(v-theta) / sigma))\n",
+    " return firing_rate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "aa0ade95",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameters from Abeysuriya 2015 Eyes Closed\n",
+    "gamma = 116 \n",
+    "t0 = 85e-3 \n",
+    "Qmax = 340 \n",
+    "theta = 12.9e-3 \n",
+    "sigma = 3.8e-3 \n",
+    "phin_0 = 1.0 \n",
+    "\n",
+    "nu_ee = 1.53e-3 \n",
+    "nu_ei = -3.02e-3 \n",
+    "nu_es = 0.57e-3 \n",
+    "nu_se = 3.45e-3\n",
+    "nu_sr = -1.47e-3 \n",
+    "nu_sn = 3.59e-3 \n",
+    "nu_re = 0.17e-3 \n",
+    "nu_rs = 0.05e-3\n",
+    "nu_ie = 1.53e-3 \n",
+    "nu_ii = -3.02e-3 \n",
+    "nu_is = 0.57e-3\n",
+    "alpha = 83 \n",
+    "beta = 769 \n",
+    "phin = 5e-4\n",
+    "\n",
+    "start = 0.0\n",
+    "stop = 100.0 + t0/2\n",
+    "dt = 1e-4\n",
+    "k0 = int(t0/2/dt) \n",
+    "time_array = np.arange(start=start, stop=stop, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "np.random.seed(0)\n",
+    "noise = alpha*beta*nu_sn*math.sqrt(phin*dt)*np.random.randn(vec_len,1)\n",
+    "\n",
+    "# Outputs\n",
+    "phie = np.zeros(vec_len)\n",
+    "Ve = np.zeros(vec_len)\n",
+    "Vr = np.zeros(vec_len)\n",
+    "Vs = np.zeros(vec_len)\n",
+    "phiedot = np.zeros(vec_len)\n",
+    "Vedot = np.zeros(vec_len)\n",
+    "Vrdot = np.zeros(vec_len)\n",
+    "Vsdot = np.zeros(vec_len)\n",
+    "\n",
+    "# Initialize output\n",
+    "phie[0:(k0+1)] = 3.175\n",
+    "Ve[0:(k0+1)]  = 0.0006344; \n",
+    "Vr[0:(k0+1)]  = 0.005676;\n",
+    "Vs[0:(k0+1)]  = -0.003234;\n",
+    "\n",
+    "for i in range ((k0+1),(int(stop/dt))):\n",
+    "    Ve[i] = Ve[i-1] + Vedot[i-1]*dt\n",
+    "    Vedot[i] = Vedot[i-1] + dt *( alpha*beta * ( nu_ee*phie[i-1] + nu_ei*sig(Ve[i-1],Qmax,theta,sigma) + nu_es*sig(Vs[i-1-k0],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vedot[i-1] - Ve[i-1] ) )\n",
+    "      \n",
+    "    Vr[i] = Vr[i-1] + Vrdot[i-1]*dt\n",
+    "    Vrdot[i] = Vrdot[i-1] + dt*( alpha*beta * ( nu_re*phie[i-1-k0] + nu_rs*sig(Vs[i-1],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vrdot[i-1] - Vr[i-1] ))\n",
+    "    \n",
+    "    Vs[i] = Vs[i-1] + Vsdot[i-1]*dt\n",
+    "    Vsdot[i] = Vsdot[i-1] + dt*( alpha*beta * ( nu_se*phie[i-1-k0] + nu_sr*sigr(Vr[i-1],Qmax,theta,sigma_r) - (1/alpha + 1/beta)*Vsdot[i-1] - Vs[i-1] + nu_sn*phin_0 )) + noise[i-1]\n",
+    "    \n",
+    "    phie[i] = phie[i-1] + phiedot[i-1]*dt\n",
+    "    phiedot[i] = phiedot[i-1] + dt*( gamma**(2) * ( sig(Ve[i-1],Qmax,theta,sigma) - 2/gamma*phiedot[i-1] - phie[i-1] ))\n",
+    "\n",
+    "phie = phie[(k0+1):len(phie)]\n",
+    "Ve = Ve[(k0+1):len(Ve)]\n",
+    "Vr = Vr[(k0+1):len(Vr)]\n",
+    "Vs = Vs[(k0+1):len(Vs)];\n",
+    "\n",
+    "time_array = time_array[(k0+1):len(time_array)];\n",
+    "phie_EYES_CLOSED = phie"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "a40a08c1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameters from Abeysuriya 2015 Eyes Open\n",
+    "gamma = 116\n",
+    "t0 = 85e-3 \n",
+    "Qmax = 340 \n",
+    "theta = 12.9e-3 \n",
+    "sigma = 3.8e-3 \n",
+    "phin_0 = 1.0 \n",
+    "\n",
+    "nu_ee = 7.85e-3 \n",
+    "nu_ei = -9.88e-3 \n",
+    "nu_es = 0.90e-3 \n",
+    "nu_se = 2.68e-3 \n",
+    "nu_sr = -1.31e-3 \n",
+    "nu_sn = 6.60e-3 \n",
+    "nu_re = 0.21e-3 \n",
+    "nu_rs = 0.06e-3\n",
+    "nu_ie = 7.85e-3 \n",
+    "nu_ii = -9.88e-3 \n",
+    "nu_is = 0.90e-3 \n",
+    "alpha = 83 \n",
+    "beta = 769 \n",
+    "phin = 5e-4\n",
+    "\n",
+    "start = 0.0\n",
+    "stop = 100.0 + t0/2\n",
+    "dt = 1e-4\n",
+    "k0 = int(t0/2/dt) \n",
+    "time_array = np.arange(start=start, stop=stop, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "np.random.seed(0)\n",
+    "noise = alpha*beta*nu_sn*math.sqrt(phin*dt)*np.random.randn(vec_len,1)\n",
+    "\n",
+    "# Outputs\n",
+    "phie = np.zeros(vec_len)\n",
+    "Ve = np.zeros(vec_len)\n",
+    "Vr = np.zeros(vec_len)\n",
+    "Vs = np.zeros(vec_len)\n",
+    "phiedot = np.zeros(vec_len)\n",
+    "Vedot = np.zeros(vec_len)\n",
+    "Vrdot = np.zeros(vec_len)\n",
+    "Vsdot = np.zeros(vec_len)\n",
+    "\n",
+    "# Initialize output\n",
+    "phie[0:(k0+1)] = 3.175\n",
+    "Ve[0:(k0+1)]  = 0.0006344; \n",
+    "Vr[0:(k0+1)]  = 0.005676;\n",
+    "Vs[0:(k0+1)]  = -0.003234;\n",
+    "\n",
+    "for i in range ((k0+1),(int(stop/dt))):\n",
+    "    Ve[i] = Ve[i-1] + Vedot[i-1]*dt\n",
+    "    Vedot[i] = Vedot[i-1] + dt *( alpha*beta * ( nu_ee*phie[i-1] + nu_ei*sig(Ve[i-1],Qmax,theta,sigma) + nu_es*sig(Vs[i-1-k0],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vedot[i-1] - Ve[i-1] ) )\n",
+    "      \n",
+    "    Vr[i] = Vr[i-1] + Vrdot[i-1]*dt\n",
+    "    Vrdot[i] = Vrdot[i-1] + dt*( alpha*beta * ( nu_re*phie[i-1-k0] + nu_rs*sig(Vs[i-1],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vrdot[i-1] - Vr[i-1] ))\n",
+    "    \n",
+    "    Vs[i] = Vs[i-1] + Vsdot[i-1]*dt\n",
+    "    Vsdot[i] = Vsdot[i-1] + dt*( alpha*beta * ( nu_se*phie[i-1-k0] + nu_sr*sigr(Vr[i-1],Qmax,theta,sigma_r) - (1/alpha + 1/beta)*Vsdot[i-1] - Vs[i-1] + nu_sn*phin_0 )) + noise[i-1]\n",
+    "    \n",
+    "    phie[i] = phie[i-1] + phiedot[i-1]*dt\n",
+    "    phiedot[i] = phiedot[i-1] + dt*( gamma**(2) * ( sig(Ve[i-1],Qmax,theta,sigma) - 2/gamma*phiedot[i-1] - phie[i-1] ))\n",
+    "\n",
+    "\n",
+    "phie = phie[(k0+1):len(phie)]\n",
+    "Ve = Ve[(k0+1):len(Ve)]\n",
+    "Vr = Vr[(k0+1):len(Vr)]\n",
+    "Vs = Vs[(k0+1):len(Vs)];\n",
+    "\n",
+    "time_array = time_array[(k0+1):len(time_array)];\n",
+    "phie_EYES_OPEN = phie"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "baefe3d6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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dFW1tbQVMlN373ve+qvesXbs2Ojo6CpgGAAAAqDc5RzE5x0EHHdTjmt/85jd1/YD0E088UdG6SmYHAACg/5Il+MwEAAAA+VF4BgAAavLggw9GV1dX1fuOO+64AqapTdaZZs2alfMkAAAAQApyjmJyjokTJ/a4Zv369RWXkPMwd+7citYdcsghBU8CAABAbyZL8JkJAAAA8qPwDAAA1OSuu+7KtK8RD+8mT54cw4YNq3qfwzsAAADoG+QcxeQc7e3tFa2rtISch0ruNWLEiBgzZkwdpgEAAKC3kiX4zAQAAAD5UXgGAABq8sADD1S9Z9ddd42DDz64gGlq09zcHEceeWTV+x555JHYsmVLARMBAAAA9STnKCbnmDBhQgwZMqTHdffdd1+u9631XlOnTq3DJAAAAPRmsgSfmQAAACA/Cs8AAEBNHnvssar3tLe3R6lUyn+YHEyaNKnqPRs2bIjFixcXMA0AAABQT3KOYnKOAQMGxFFHHdXjuqxPxarW0qVLY/ny5T2uO/7444sfBgAAgF5NluAzEwAAAORH4RkAAMhs+fLlsXr16qr3TZw4sYBp8tHe3p5p3y9/+cucJwEAAADqSc7xmiJyjkrKw0899VQsXLgw93u/2R133FHROoVnAAAAdkaW8BqfmQAAACAPCs8AAEBm8+bNy7Qv6wFZPWT5tuKI7O8FAAAA0BjkHK8pIuc48cQTK1p3ww035H7vN7vuuut6XLP33nvHhAkTCp8FAACA3kuW8BqfmQAAACAPCs8AAEBmWb+h96CDDsp5kvzssccesfvuu1e9z7cVAwAAQO8m53hNETnHfvvtV9ETrH74wx/Gtm3bcr//K37961/Hww8/3OO6s88+u7AZAAAA6BtkCa/xmQkAAADyoPAMAABktmjRoqr3NDc3x5gxYwqYJj/77LNP1XuyvBcAAABA45BzvKaonOPDH/5wj2uWLVsWt9xySyH3j4j42te+VtG6SmYFAACgf5MlvMZnJgAAAMiDwjMAAJDZsmXLqt6z9957x8CBAwuYJj9ZDu9efPHF6OrqKmAaAAAAoB7kHK8pKuc455xzorW1tcd1X/rSl6JcLud+/5UrV8Y111zT47r29vaYMGFC7vcHAACgb5ElvMZnJgAAAMiDwjMAAJBZlsO7fffdt4BJ8pXl8C4i2/sBAAAANAY5xxsVkXPsvvvuFT05uaOjI37wgx/kfv9LL7001q9f3+O6Sy65JPd7AwAA0PfIEt7IZyYAAAColcIzAACQydq1a2Pt2rVV7xszZkz+w+Qs64wO7wAAAKB3knN0V1TOcckll0RTU8/H1NOnT4+VK1fmdt877rgjfvjDH/a4buzYsXHmmWfmdl8AAAD6JllCdz4zAQAAQK0UngEAgEyyHlTtueeeOU+Sv6wzOrwDAACA3knO0V1ROcd+++1X0VOeX3jhhTj77LNj48aNNd9z2bJlMW3atCiXyz2uvfzyy6O5ubnmewIAANC3yRK685kJAAAAaqXwDAAAZLJixYpM+3rD4d3b3va2TPueeuqpnCcBAAAA6kHO0V2ROceVV14ZbW1tPa6777774swzz6yp9PzUU0/Fn/7pn8aLL77Y49ojjjgizj333Mz3AgAAoP+QJXTnMxMAAADUSuEZAADI5IUXXsi0rzcc3mWdsZIPzgIAAACNR87RXZE5xx577BFf/OIXK1p72223xRFHHBFPPvlk1ff52c9+FpMmTaroA9cDBgyIq666qup7AAAA0D/JErrzmQkAAABqpfAMAABksmrVqkz7esPh3ciRI2PAgAFV78v6nlA/pVIp86/zzz+/onuMGTMm8z1Gjx5d7BsAAADAdsk5uis657jwwgvj5JNPrmhtR0dHjB8/Pi699NKKnqD18MMPx2mnnRYnnnhixR+2/vKXvxwHHXRQRWsBAABAltBd0VmC834AAIC+ryX1AAAAQO+0evXqTPuGDx+e7yAFGTZsWNXfPpz1PQEAAADSknN0V3TOUSqV4r/+679i4sSJFT2BecOGDfHlL385ZsyYEVOmTIlDDz009tlnnxg+fHhs3rw5Vq9eHQsWLIhf/OIX8dvf/raqWT7wgQ/EJz7xiYyvBAAAgP5IltCdz0wAAABQK4VnAAAgk6zfzDt06NCcJynG0KFDqz6884RnAAAA6J3kHN3VI+fYdddd484774yjjjoqnnvuuYr2lMvlePjhh+Phhx/OZYajjz46rr322lyuBQAAQP8hS+jOZyYAAACoVVPqAQAAgN4p6zfztrW15TxJMbLM6duKAQAAoHeSc3RXr5xjv/32i9mzZ8cee+xRl/u93hFHHBG33nprDB48uO73BgAAoHeTJXTnMxMAAADUSuEZAADI5KWXXsq0b8iQITlPUows36q8du3a/AcBAAAACifn6K6eOccBBxwQHR0dMXny5Lrd82/+5m/irrvu6jW/hwAAADQWWUJ3PjMBAABArRSeAQCATDZu3Fj1nl122SWamnrHX0OyHDJu3bo1tm3bVsA0AAAAQJHkHN3VO+d4xzveEffff39cfPHF0dLSUth9Ro4cGf/5n/8Z3/ve96K1tbWw+wAAANC3yRK685kJAAAAatU7/tYMAAA0nE2bNlW9Z8CAAQVMUoyss2Z5XwAAAIC05BzbV++co7W1Nb7yla/EY489Fn/+53+e67UHDRoUf//3fx+/+c1v4rzzzsv12gAAAPQ/soTt85kJAAAAaqHwDAAAZLJ58+aq9xT5dJ68ObwDAACA/kPOsX2pco7x48fHT3/601i0aFH83d/9Xeyxxx6ZrzVu3Lj44he/GL/73e/iqquuil133TXHSQEAAOivZAnb5zMTAAAA1KL3/M0ZAABoKFkOqXrT4V3WWR3eNbZyuZx6BAAAABqQnGP7Uucc48aNi29/+9tx1VVXxbx58+Lee++NhQsXxuLFi+OZZ56Jzs7O6Orqiubm5hg6dGi0tbXF6NGjY9y4cXHwwQfH8ccfH6NHj076GgAAAOibZAnbV2SW4LwfAACg7+s9f3MGAAAaisO77cvyLc4AAABAWnKO7WuUnKNUKkV7e3u0t7enHgUAAAAiQpawI42SJQAAANA7NaUeAAAA6J22bNlS9R6HdwAAAEAjknNsn5wDAAAAtk+WsH2yBAAAAGqh8AwAAGSS5XBr69atBUxSjCyHkxG964ASAAAAeJmcY/vkHAAAALB9soTtkyUAAABQC4VnAAAgk4EDB1a9pzd9k2/Ww7ss7wsAAACQlpxj++QcAAAAsH2yhO2TJQAAAFALhWcAACCTAQMGVL0n64FYCg7vAAAAoP+Qc2yfnAMAAAC2T5awfbIEAAAAaqHwDAAAZJLlkKo3Hd5l/WZlh3cAAADQ+8g5tk/OAQAAANsnS9g+WQIAAAC1UHgGAAAyyXJIlfVALIWsB41ZvsUZAAAASEvOsX1yDgAAANg+WcL2yRIAAACohcIzAACQSZbDu/Xr10e5XC5gmvx1dXVVvae5uTmam5sLmAYAAAAokpyjOzkHAAAA7JgsoTtZAgAAALVSeAYAADIZNmxY1XvK5XJ0dnYWME3+1q1bV/WeLO8JAAAAkJ6cozs5BwAAAOyYLKE7WQIAAAC1UngGAAAyGTlyZKZ9veXwLsucWd8TAAAAIC05R3dyDgAAANgxWUJ3sgQAAABqpfAMAABksuuuu2bal+VbgFPIMmfW9wQAAABIS87RnZwDAAAAdkyW0J0sAQAAgFopPAMAAJlk/WbetWvX5jtIQbIc3vm2YgAAAOid5BzdyTkAAABgx2QJ3ckSAAAAqJXCMwAAkEnWb+Z9/vnnc54kf6tXr45NmzZVvc+3FQMAAEDvJOfoTs4BAAAAOyZL6E6WAAAAQK0UngEAgEx22223TPuee+65nCfJ37PPPptp31vf+tacJwEAAADqQc7RnZwDAAAAdkyW0J0sAQAAgFopPAMAAJmMGjUq077ecHiXdcZ3vvOdOU8CAAAA1IOcozs5BwAAAOyYLKE7WQIAAAC1UngGAAAyGTNmTKZ9ffnwLut7AgAAAKQl5+hOzgEAAAA7JkvoTpYAAABArRSeAQCATEaMGBHDhg2ret+yZcsKmCZfWWd0eAcAAAC9k5yjOzkHAAAA7JgsoTtZAgAAALVSeAYAADLLcli1ZMmSAibJ19KlSzPtc3gHAAAAvZec443kHAAAALBzsoQ3kiUAAABQK4VnAAAgsyyHVStWrIjNmzcXME1+shzejRw5MoYOHVrANAAAAEA9yDleI+cAAACAnskSXiNLAAAAIA8KzwAAQGYHHHBA1Xu2bt0ay5YtK2Ca/GQ5vBs3blwBkwAAAAD1Iud4jZwDAAAAeiZLeI0sAQAAgDwoPAMAAJkdcsghmfbNnz8/50ny8/vf/z6ef/75qvdNnDixgGkAAACAepFzvEbOAQAAAD2TJbxGlgAAAEAeFJ4BAIDMsh5YzZ07N+dJ8tPR0ZFpX9aDTAAAAKAxyDleI+cAAACAnskSXiNLAAAAIA8KzwAAQGZjxoyJESNGVL1v3rx5BUyTj6wHi76tGAAAAHo3Ocdr5BwAAADQM1nCa2QJAAAA5EHhGQAAqMm73/3uqvfMnTs3yuVy/sPkIMu3Fbe2tsYBBxxQwDQAAABAPck55BwAAABQDVmCLAEAAID8KDwDAAA1Ofzww6ves2rVqpg/f34B09Rm69atcd9991W9b8qUKdHS0lLARAAAAEA9yTnkHAAAAFANWYIsAQAAgPwoPAMAADU57rjjMu276667cp6kdh0dHbF27dqq9x1//PH5DwMAAADUnZxDzgEAAADVkCXIEgAAAMiPwjMAAFCTww47LN7ylrdUva8RD++yzuTwDgAAAPoGOYecAwAAAKohS5AlAAAAkB+FZwAAoCYDBw6MI488sup99957b3R2dhYwUXa33npr1XuGDRsWkydPLmAaAAAAoN7kHHIOAAAAqIYsQZYAAABAfhSeAQCAmp1wwglV79mwYUPccsst+Q+T0ZN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+      "text/plain": [
+       "<Figure size 4000x3000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "X_EC =signal.resample(phie_EYES_CLOSED,10000)\n",
+    "freqs_EC,ps_vPN_EC = welch(X_EC,fs=100, noverlap = 125, nperseg=1000)\n",
+    "\n",
+    "X_EO=signal.resample(phie_EYES_OPEN,10000)\n",
+    "freqs_EO,ps_vPN_EO = welch(X_EO,fs=100, noverlap = 125, nperseg=1000)\n",
+    "\n",
+    "plt.figure(figsize=(4, 3), dpi =1000)\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xscale(\"log\")\n",
+    "plt.plot(freqs_EC,ps_vPN_EC, color= plt.cm.Dark2(6))\n",
+    "plt.plot(freqs_EO,ps_vPN_EO,color = plt.cm.Dark2(7))\n",
+    "plt.xlabel('Frequency (Hz)')\n",
+    "plt.ylabel('Power (A.U.)')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "alpha",
+   "language": "python",
+   "name": "alpha"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/content/notebooks/Generate_analytical_power_spectrum.ipynb b/content/Generate_analytical_power_spectrum.ipynb
similarity index 100%
rename from content/notebooks/Generate_analytical_power_spectrum.ipynb
rename to content/Generate_analytical_power_spectrum.ipynb
diff --git a/content/Generate_time_series_power_spectrum.ipynb b/content/Generate_time_series_power_spectrum.ipynb
new file mode 100644
index 0000000..d4dfd93
--- /dev/null
+++ b/content/Generate_time_series_power_spectrum.ipynb
@@ -0,0 +1,671 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "id": "da02afa1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from scipy import signal\n",
+    "from scipy.signal import welch\n",
+    "from scipy.optimize import fsolve"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2122f20a",
+   "metadata": {},
+   "source": [
+    "# Jansen-Rit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "2e676673",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# JR Sigmoid function\n",
+    "def sigm(nu_max,v0,r,v):\n",
+    "  action_potential = (2*nu_max)/(1+math.exp(r*(v0-v)))\n",
+    "  return action_potential"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "02de880a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameter settings\n",
+    "A = 3.25             # mV    \n",
+    "B = 22               # mV\n",
+    "C = 135              # na\n",
+    "C1 = 1*C             # na\n",
+    "C2 = 0.8*C           # na\n",
+    "C3 = 0.25*C          # na\n",
+    "C4 = 0.25*C          # na\n",
+    "v0 = 6               # mV\n",
+    "tau_e = 10           # ms\n",
+    "tau_i = 20           # ms\n",
+    "a = (1/tau_e)*1000   # s^-1\n",
+    "b = (1/tau_i)*1000   # s^-1\n",
+    "nu_max = 2.5         # s^-1\n",
+    "r = 0.56             # mV^-1\n",
+    "\n",
+    "# Simulation setting\n",
+    "start = 0.0\n",
+    "stim_time =100\n",
+    "dt = 1e-4\n",
+    "time_array = np.arange(start=start, stop=stim_time, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "# Input\n",
+    "noise = np.random.uniform(120,320,vec_len)\n",
+    "# Output Initialization\n",
+    "y = np.zeros((6,vec_len))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "f5981074",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Solving JR differential equations\n",
+    "for i in range (1,vec_len):\n",
+    "  y[0,i] = y[0,i-1] + y[3,i-1]*dt\n",
+    "  y[1,i] = y[1,i-1] + y[4,i-1]*dt\n",
+    "  y[2,i] = y[2,i-1] + y[5,i-1]*dt\n",
+    "  y[3,i] = y[3,i-1] + dt * (A*a*(sigm(nu_max,v0,r,(y[1,i-1]-y[2,i-1]))) - (2*a*y[3,i-1]) - (a**(2)*y[0,i-1])) # Pyramidal\n",
+    "  y[4,i] = y[4,i-1] + dt * (A*a*(noise[i-1] + (C2*sigm(nu_max,v0,r,(C1*y[0,i-1])))) - (2*a*y[4,i-1]) - (a**(2)*y[1,i-1])) # Excitatory\n",
+    "  y[5,i] = y[5,i-1] + dt * (B*b*(C4*sigm(nu_max,v0,r,(C3*y[0,i-1]))) - (2*b*y[5,i-1]) - (b**(2)*y[2,i-1])) # Inhibitory\n",
+    "\n",
+    "output = y[1,:]-y[2,:]\n",
+    "X = signal.resample(output, 10000)\n",
+    "freqs_Jansen,ps_vPN_Jansen = welch(X,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "id": "adf0b52e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f8018bd32b0>]"
+      ]
+     },
+     "execution_count": 92,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Figures \n",
+    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\n",
+    "ax2.set_xscale(\"log\")\n",
+    "ax2.set_yscale(\"log\")\n",
+    "ax1.plot(time_array[20000:40000],output[20000:40000], color='black')\n",
+    "ax1.set_xlabel('Time (s)')\n",
+    "ax2.set_xlabel('Frequency (Hz)')\n",
+    "ax1.set_ylabel('Output ($y_{1}-y_{2}$)')\n",
+    "ax2.set_ylabel('Power (A.U.)')\n",
+    "ax2.plot(freqs_Jansen,ps_vPN_Jansen, color='black')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "26ed5734",
+   "metadata": {},
+   "source": [
+    "# Moran-David-Friston"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "id": "aa6e08c4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# MDF Sigmoid\n",
+    "def sigm(x):\n",
+    "  return (1/(1+math.exp(-rho_1*(x - rho_2)))) - (1/(1+math.exp(rho_1*rho_2)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "id": "3623f52c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameter settings\n",
+    "\n",
+    "start = 0.0\n",
+    "stim_time = 100\n",
+    "dt = 1e-4\n",
+    "time_array = np.arange(start=start, stop=stim_time, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "H_e = 10                 # mV\n",
+    "H_i = 22                 # mV\n",
+    "kappa_e = (1/4) * 1000   # s^-1\n",
+    "kappa_i = (1/16) * 1000  # s^-1\n",
+    "gamma_1 = 128            # na\n",
+    "gamma_2 = 128            # na\n",
+    "gamma_3 = 64             # na\n",
+    "gamma_4 = 64             # na\n",
+    "gamma_5 = 1              # na\n",
+    "rho_1 = 2                # na \n",
+    "rho_2 = 1                # na\n",
+    "a= 0                     # no adaptation in our case\n",
+    "\n",
+    "#Initialize input and output\n",
+    "x = np.zeros((12,vec_len))\n",
+    "noise = kappa_e*H_e*math.sqrt(dt)*np.random.normal(0, 1, vec_len)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "id": "5c5c7bf5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Solving MDF differential equations\n",
+    "for i in range (1,vec_len):\n",
+    "  #Inhibitory cells in agranular layers\n",
+    "  x[6,i] = x[6,i-1] + dt * x[7,i-1]\n",
+    "  x[7,i] = x[7,i-1] + dt * (kappa_e*H_e*(gamma_3)*sigm(x[8,i-1]) - 2*kappa_e*x[7,i-1] - kappa_e**(2)*x[6,i-1])\n",
+    "  x[9,i] = x[9,i-1] + dt * x[10,i-1]\n",
+    "  x[10,i] = x[10,i-1] + dt * (kappa_i*H_i*gamma_5*sigm(x[11,i-1]) - 2*kappa_i*x[10,i-1] - kappa_i**(2)*x[9,i-1])\n",
+    "  x[11,i] = x[11,i-1] + dt * (x[7,i-1] - x[10,i-1])\n",
+    "\n",
+    "  #Excitatory spiny cells in granualar layer\n",
+    "  x[0,i] =  x[0,i-1] + dt * x[3,i-1]\n",
+    "  x[3,i] = x[3,i-1] + dt * (kappa_e*H_e*(gamma_1*sigm(x[8,i-1]-a)) - 2*kappa_e*x[3,i-1] - kappa_e**(2)*x[0,i-1]) + noise[i-1]\n",
+    "\n",
+    "  #Excitatory pyramidal cells in agranular layers\n",
+    "  x[1,i] = x[1,i-1] + dt * x[4,i-1]\n",
+    "  x[4,i] =  x[4,i-1] + dt * (kappa_e*H_e*(gamma_2*sigm(x[0,i-1])) - 2*kappa_e*x[4,i-1] - kappa_e**(2)*x[1,i-1])\n",
+    "  x[2,i] = x[2,i-1] + dt * x[5,i-1]\n",
+    "  x[5,i] = x[5,i-1] + dt * (kappa_i*H_i*gamma_4*sigm(x[11,i-1]) - 2*kappa_i*x[5,i-1] - kappa_i**(2)*x[2,i-1])\n",
+    "  x[8,i] = x[8,i-1] + dt * (x[4,i-1] - x[5,i-1])\n",
+    "\n",
+    "output_Moran=x[1,:]-x[2,:]\n",
+    "X_Moran = signal.resample(output_Moran, 10000)\n",
+    "freqs_Moran,ps_vPN_Moran = welch(X_Moran,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "id": "03b5bde7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Power (A.U.)')"
+      ]
+     },
+     "execution_count": 98,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Figures\n",
+    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\n",
+    "fig.suptitle('Time Series and Power Spectrum')\n",
+    "ax1.plot(time_array[20000:40000],output_Moran[20000:40000], color = \"black\")\n",
+    "ax2.set_xscale(\"log\")\n",
+    "ax2.set_yscale(\"log\")\n",
+    "ax2.plot(freqs_Moran,ps_vPN_Moran, color=\"black\")\n",
+    "ax1.set_xlabel('Time')\n",
+    "ax1.set_ylabel('Output ($v_{6}$)')\n",
+    "ax2.set_xlabel('Frequency (Hz)')\n",
+    "ax2.set_ylabel('Power (A.U.)')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d54331b",
+   "metadata": {},
+   "source": [
+    "# Liley-Wright"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "id": "ea978533",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def dynamics(p,X):\n",
+    "    dX = np.zeros((18,1))\n",
+    "\n",
+    "    # Calculate synaptic reversal potentials\n",
+    "    psi_ee=(p.h_ee_eq-X[0])/abs(p.h_ee_eq-p.h_e_r)\n",
+    "    psi_ie=(p.h_ie_eq-X[0])/abs(p.h_ie_eq-p.h_e_r)\n",
+    "    psi_ei=(p.h_ei_eq-X[1])/abs(p.h_ei_eq-p.h_i_r)\n",
+    "    psi_ii=(p.h_ii_eq-X[1])/abs(p.h_ii_eq-p.h_i_r)\n",
+    "\n",
+    "    # Calculate synaptic inputs A_jk \n",
+    "    A_ee=p.N_ee_b*S_e(p,X[0])+X[10]+p.p_ee\n",
+    "    A_ei=p.N_ei_b*S_e(p,X[0])+X[12]+p.p_ei\n",
+    "    A_ie=p.N_ie_b*S_i(p,X[1])\n",
+    "    A_ii=p.N_ii_b*S_i(p,X[1])   \n",
+    "\n",
+    "    # Calculate state vector\n",
+    "    dX[0] = (1/p.tau_e)*(p.h_e_r-X[0]+psi_ee*X[2]+psi_ie*X[6]) # V_e\n",
+    "    dX[1] = (1/p.tau_i)*(p.h_i_r-X[1]+psi_ei*X[4]+psi_ii*X[8]) # V_i\n",
+    "    dX[2] = X[3] # I_ee\n",
+    "    dX[3] = -2*p.gamma_ee*X[3]-p.gamma_ee**(2)*X[2]+p.gamma_ee*math.exp(1)*p.Gamma_ee*A_ee# J_ee\n",
+    "    dX[4] = X[5] # I_ei\n",
+    "    dX[5] = -2*p.gamma_ei*X[5]-p.gamma_ei**(2)*X[4]+p.gamma_ei*math.exp(1)*p.Gamma_ei*A_ei# J_ei\n",
+    "    dX[6] = X[7] # I_ie\n",
+    "    dX[7] = -2*p.gamma_ie*X[7]-p.gamma_ie**(2)*X[6]+p.gamma_ie*math.exp(1)*p.Gamma_ie*A_ie# J_ie\n",
+    "    dX[8] = X[9] # I_ii\n",
+    "    dX[9] = -2*p.gamma_ii*X[9]-p.gamma_ii**(2)*X[8]+p.gamma_ii*math.exp(1)*p.Gamma_ii*A_ii# J_ii% J_ii\n",
+    "    return dX\n",
+    "\n",
+    "# LW sigmoid functions\n",
+    "def S_e(t,v):   \n",
+    "    p = t\n",
+    "    spikerate = p.S_e_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_e)/p.sigma_e))\n",
+    "    return spikerate\n",
+    "\n",
+    "def S_i(t,v):\n",
+    "    p=t\n",
+    "    spikerate = p.S_i_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_i)/p.sigma_i))\n",
+    "    return spikerate\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "id": "707f5526",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class p:\n",
+    "  S_e_max = 0.5    # ms^-1\n",
+    "  S_i_max = 0.5    # ms^-1\n",
+    "  h_e_r = -7       # mV\n",
+    "  h_i_r = -70      # mV\n",
+    "  mu_e = -50       # mV\n",
+    "  mu_i = -50       # mV\n",
+    "  sigma_e = 5      # mV\n",
+    "  sigma_i = 5      # mV\n",
+    "  tau_e = 94       # ms\n",
+    "  tau_i = 42       # ms\n",
+    "  h_ee_eq = 45     # mV\n",
+    "  h_ei_eq = 45     # mV\n",
+    "  h_ie_eq = -90    # mV\n",
+    "  h_ii_eq = -90    # mV\n",
+    "  Gamma_ee = 0.71  # mV\n",
+    "  Gamma_ei = 0.71  # mV\n",
+    "  Gamma_ie = 0.71  # mV\n",
+    "  gamma_ee = 0.3   # ms^-1\n",
+    "  gamma_ei = 0.3   # ms^-1\n",
+    "  gamma_ie = 0.065 # ms^-1\n",
+    "  gamma_ii = 0.065 # ms^-1\n",
+    "  p_ee = 3.460     # ms^-1\n",
+    "  p_ee_sd = 1.000  # std\n",
+    "  p_ei = 5.070     # ms^-1\n",
+    "  p_ei_sd = 0      # std\n",
+    "  p_ie = 0         # ms^-1\n",
+    "  p_ii = 0         # ms^-1\n",
+    "  N_ei_b = 3000    # na\n",
+    "  N_ee_b = 3000    # na\n",
+    "  N_ie_b = 500     # na\n",
+    "  N_ii_b = 500     # na"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "id": "572b9734",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Simulation settings\n",
+    "sim_time= 100            \n",
+    "dt = 1e-4\n",
+    "steps=  1/dt          \n",
+    "white_noise=1       \n",
+    "h = 1000/steps \n",
+    "T = sim_time*10**3 \n",
+    "N = T/h-1\n",
+    "\n",
+    "# Initial values\n",
+    "p.v_e_equil = p.h_e_r\n",
+    "p.v_i_equil = p.h_i_r\n",
+    "X = np.zeros((18,int(N)))\n",
+    "X[0,0] = p.v_e_equil\n",
+    "X[1,0] = p.v_i_equil    \n",
+    "X[2,0] = math.exp(1)/p.gamma_ee*p.Gamma_ee*(p.N_ee_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ee)    \n",
+    "X[4,0] = math.exp(1)/p.gamma_ei*p.Gamma_ei*(p.N_ei_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ei)\n",
+    "X[6,0] = math.exp(1)/p.gamma_ie*p.Gamma_ie*(p.N_ie_b*S_i(p,p.v_i_equil))\n",
+    "X[8,0] = math.exp(1)/p.gamma_ii*p.Gamma_ii*(p.N_ii_b*S_i(p,p.v_i_equil))\n",
+    " \n",
+    "for n in range (0,int(N-1)):\n",
+    "    noise = np.zeros((18,1))\n",
+    "    if (white_noise==1):\n",
+    "      noise[3]= p.gamma_ee*math.exp(p.gamma_ee/p.gamma_ee)*p.Gamma_ee*p.p_ee_sd*np.random.randn(1,1)\n",
+    "    X[:,n+1] = X[:,n] + ((h*dynamics(p,X[:,n])+math.sqrt(h)*noise).flatten())\n",
+    "EEG=-X[0,:]\n",
+    "\n",
+    "new_EEG =signal.resample(EEG,10000)\n",
+    "freqs_Liley,ps_vPN_Liley = welch(new_EEG,fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "id": "b7f473a7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0, 'Frequency (Hz)')"
+      ]
+     },
+     "execution_count": 103,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Figures\n",
+    "time_array = np.arange(start=0.0, stop=sim_time, step=dt)\n",
+    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\n",
+    "ax1.plot(time_array[20000:40000],EEG[20000:40000], color='black')\n",
+    "ax1.set_xlabel('Time (s)')\n",
+    "ax1.set_ylabel('Output ($V_{e}$)')\n",
+    "ax2.set_yscale(\"log\")\n",
+    "ax2.set_xscale(\"log\")\n",
+    "ax2.plot(freqs_Liley,ps_vPN_Liley, color='black')\n",
+    "ax2.set_ylabel('Power (A.U.)')\n",
+    "ax2.set_xlabel('Frequency (Hz)')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "068b03af",
+   "metadata": {},
+   "source": [
+    "# Robinson-Rennie-Wright"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "id": "2bdc9817",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# RRW Sigmoid function\n",
+    "def sig(v,Qmax,theta,sigma):\n",
+    " # sigmoid for voltage-rate relationship\n",
+    " firing_rate = Qmax / (1 + math.exp(-(v-theta) / sigma))\n",
+    " return firing_rate\n",
+    "\n",
+    "def sigr(v,Qmax_r,modtheta,sigma_r):\n",
+    " # sigmoid for voltage-rate relationship in reticular nucleus\n",
+    " firing_rate = Qmax_r / (1 + math.exp(-(v-modtheta) / sigma_r));\n",
+    " return firing_rate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "id": "74fb2611",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Parameter settings for resting state\n",
+    "gamma = 116          # s^-1\n",
+    "t0 = 80e-3           # s\n",
+    "Qmax = 340           # s^-1\n",
+    "theta = 12.92e-3     # V\n",
+    "sigma = 3.8e-3       # V\n",
+    "Qmax_r = 100         # s^-1\n",
+    "sigma_r = 3.8e-3     # V\n",
+    "phin_0 = 1.0         # s^-1\n",
+    "\n",
+    "nu_ee = 0.00303      # Vs\n",
+    "nu_ei = -0.006       # Vs\n",
+    "nu_es = 0.00206      # Vs\n",
+    "nu_ie = 0.00303      # Vs\n",
+    "nu_ii = -0.006       # Vs\n",
+    "nu_is = 0.00206      # Vs\n",
+    "nu_re = 0.00033      # Vs\n",
+    "nu_rs =  0.00003     # Vs\n",
+    "nu_se = 0.00218      # Vs\n",
+    "nu_sr = -0.00083     # Vs\n",
+    "nu_sn = 0.00098      # Vs\n",
+    "alpha = 83.33        # s^-1\n",
+    "beta = 769.23        # s^-1\n",
+    "phin = 5e-4          # s^-1\n",
+    "\n",
+    "# Simulation setting\n",
+    "start = 0.0\n",
+    "stop = 100.0 + t0/2\n",
+    "dt = 1e-4\n",
+    "k0 = int(t0/2/dt) \n",
+    "time_array = np.arange(start=start, stop=stop, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "# Noise\n",
+    "np.random.seed(0)\n",
+    "noise = alpha*beta*nu_sn*math.sqrt(phin*dt)*np.random.randn(vec_len,1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 106,
+   "id": "a8e973b0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Initializing output\n",
+    "phie = np.zeros(vec_len)\n",
+    "Ve = np.zeros(vec_len)\n",
+    "Vr = np.zeros(vec_len)\n",
+    "Vs = np.zeros(vec_len)\n",
+    "phiedot = np.zeros(vec_len)\n",
+    "Vedot = np.zeros(vec_len)\n",
+    "Vrdot = np.zeros(vec_len)\n",
+    "Vsdot = np.zeros(vec_len)\n",
+    "\n",
+    "phie[0:(k0+1)] = 3.175\n",
+    "Ve[0:(k0+1)]  = 0.0006344; \n",
+    "Vr[0:(k0+1)]  = 0.005676;\n",
+    "Vs[0:(k0+1)]  = -0.003234;\n",
+    "\n",
+    "# Solving differential equations \n",
+    "for i in range ((k0+1),(int(stop/dt))):\n",
+    "    Ve[i] = Ve[i-1] + Vedot[i-1]*dt\n",
+    "    Vedot[i] = Vedot[i-1] + dt *( alpha*beta * ( nu_ee*phie[i-1] + nu_ei*sig(Ve[i-1],Qmax,theta,sigma) + nu_es*sig(Vs[i-1-k0],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vedot[i-1] - Ve[i-1] ) )\n",
+    "      \n",
+    "    Vr[i] = Vr[i-1] + Vrdot[i-1]*dt\n",
+    "    Vrdot[i] = Vrdot[i-1] + dt*( alpha*beta * ( nu_re*phie[i-1-k0] + nu_rs*sig(Vs[i-1],Qmax,theta,sigma) - (1/alpha + 1/beta)*Vrdot[i-1] - Vr[i-1] ))\n",
+    "    \n",
+    "    Vs[i] = Vs[i-1] + Vsdot[i-1]*dt\n",
+    "    Vsdot[i] = Vsdot[i-1] + dt*( alpha*beta * ( nu_se*phie[i-1-k0] + nu_sr*sigr(Vr[i-1],Qmax,theta,sigma_r) - (1/alpha + 1/beta)*Vsdot[i-1] - Vs[i-1] + nu_sn*phin_0 )) + noise[i-1]\n",
+    "    \n",
+    "    phie[i] = phie[i-1] + phiedot[i-1]*dt\n",
+    "    phiedot[i] = phiedot[i-1] + dt*( gamma**(2) * ( sig(Ve[i-1],Qmax,theta,sigma) - 2/gamma*phiedot[i-1] - phie[i-1] ))\n",
+    "\n",
+    "\n",
+    "# Remove initial t0-length from outputs\n",
+    "phie = phie[(k0+1):len(phie)]\n",
+    "Ve = Ve[(k0+1):len(Ve)]\n",
+    "Vr = Vr[(k0+1):len(Vr)]\n",
+    "Vs = Vs[(k0+1):len(Vs)];\n",
+    "time_array = time_array[(k0+1):len(time_array)];\n",
+    "\n",
+    "X=signal.resample(phie,10000)\n",
+    "output_Zhao = phie;\n",
+    "freqs_Robinson,ps_vPN_Robinson = welch(X[1000:],fs=100, noverlap = 125, nperseg=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 107,
+   "id": "3720fe04",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Power (A.U.)')"
+      ]
+     },
+     "execution_count": 107,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Figures\n",
+    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,5))\n",
+    "fig.suptitle('Time Series and Power Spectrum')\n",
+    "ax1.plot(time_array[20000:40000],output_Zhao[20000:40000], color='black')\n",
+    "ax2.set_xscale(\"log\")\n",
+    "ax2.set_yscale(\"log\")\n",
+    "ax2.plot(freqs_Robinson,ps_vPN_Robinson, color='black')\n",
+    "ax1.set_xlabel('Time (s)')\n",
+    "ax1.set_ylabel('Output ($\\phi_{e}$)')\n",
+    "ax2.set_xlabel('Frequency (Hz)')\n",
+    "ax2.set_ylabel('Power (A.U.)')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ccd17304",
+   "metadata": {},
+   "source": [
+    "# All together"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "id": "16471f18",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(freqs_Jansen,ps_vPN_Jansen, label='Jansen-Rit',color= plt.cm.Dark2(0))\n",
+    "plt.plot(freqs_Moran,ps_vPN_Moran, label='Moran',color= plt.cm.Dark2(1))\n",
+    "plt.plot(freqs_Robinson,ps_vPN_Robinson, label='Robinson',color= plt.cm.Dark2(2))\n",
+    "plt.plot(freqs_Liley,ps_vPN_Liley, label='Liley',color= plt.cm.Dark2(3))\n",
+    "plt.title('Power Spectrum obtained with numerical expression')\n",
+    "plt.xscale(\"log\")\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xlabel('Frequency')\n",
+    "plt.ylabel('Power (A.U.)')\n",
+    "plt.legend(loc=3)\n",
+    "plt.axvspan(8, 14, color='red', alpha=0.2)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c78c3784",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "alpha",
+   "language": "python",
+   "name": "alpha"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/content/JR_fixed_points.ipynb b/content/JR_fixed_points.ipynb
new file mode 100644
index 0000000..f9b8f0b
--- /dev/null
+++ b/content/JR_fixed_points.ipynb
@@ -0,0 +1,245 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "3c85bc3b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "from scipy import signal\n",
+    "from scipy.signal import welch\n",
+    "from scipy.optimize import fsolve"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "77a50ae2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sigm(x):\n",
+    "    v0 = 6         \n",
+    "    vmax = 2.5   \n",
+    "    r = 0.56   \n",
+    "    return (2*vmax)/(1+np.exp(r*(v0-x)))\n",
+    "\n",
+    "def differentiate_sigmoid(x, vmax, v0,  r):\n",
+    "  ds_dx = (r*2*vmax*(np.exp(r*(v0-x)))) / (1+np.exp(r*(v0-x)))**2\n",
+    "  return ds_dx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "67ce6be0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7f085e4418b0>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "A = 3.25\n",
+    "B = 22\n",
+    "C = 135\n",
+    "c1 = 1*C\n",
+    "c2 = 0.8*C  \n",
+    "v0 = 6        \n",
+    "a = 100      \n",
+    "b = 50       \n",
+    "vmax = 2.5 \n",
+    "r = 0.56       \n",
+    "divA = (A/a)\n",
+    "divB = (B/b)\n",
+    "C3_all = np.arange(0.1,0.6,0.001)\n",
+    "c3 = C3_all*C\n",
+    "C4_all = np.arange(0.1,0.6,0.001)\n",
+    "c4 = C4_all*C\n",
+    "y = np.random.rand(len(C3_all))\n",
+    "p = 220 # p=150 for the lower external input fixed point schematic\n",
+    "index_values = []\n",
+    "for i in range(len(C3_all)):\n",
+    "  x = np.arange(-4,100,0.0001)\n",
+    "  y1 = x\n",
+    "  y2 = (divA*p) + (divA*c2*sigm(divA*c1*sigm(x))) - (divB*c4[i]*sigm(divA*c3[i]*sigm(x)))\n",
+    "  idx = np.argwhere(np.diff(np.sign(y1 - y2))).flatten()\n",
+    "  index_values.append(idx)\n",
+    "\n",
+    "new_values = []\n",
+    "for i in range(0,len(index_values)):\n",
+    "  new_values.append(y1[index_values[i]])\n",
+    "\n",
+    "w = [[C3_all[i]] * len(new_values[i]) for i in range(len(new_values))]\n",
+    "\n",
+    "x_to_plot = [item for sublist in w for item in sublist]\n",
+    "y_to_plot = [item for sublist in new_values for item in sublist]\n",
+    "plt.scatter(x_to_plot, y_to_plot)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "5cc8ab19",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "un = 0\n",
+    "stability_connection = []\n",
+    "for j in range(0,len(new_values)):\n",
+    "    for me in range(0,len(new_values[j])):\n",
+    "      J = np.zeros((6, 6))\n",
+    "      fix_point = new_values[j][me]\n",
+    "      first_coordinate = (A/a)*sigm(fix_point)\n",
+    "      J[0, 3] = 1\n",
+    "      J[1, 4] = 1\n",
+    "      J[2, 5] = 1\n",
+    "      J[3, 0] = -a**2\n",
+    "      J[3,1] = A*a*differentiate_sigmoid(fix_point,vmax,v0,r)\n",
+    "      J[3,2] = -A*a*differentiate_sigmoid(fix_point,vmax,v0,r)\n",
+    "      J[3,3] = -2*a\n",
+    "      J[4, 0] = (A*a*c2*c1)*differentiate_sigmoid(c1*first_coordinate,vmax,v0,r)\n",
+    "      J[4, 1] = -a**2\n",
+    "      #J[4, 3] = -2*a\n",
+    "      J[4, 4] = -2*a\n",
+    "      J[5, 0] = (b*B*c4[j]*c3[j])*differentiate_sigmoid(c3[j]*first_coordinate,vmax,v0,r)\n",
+    "      J[5, 2] = -b**2\n",
+    "      J[5, 5] = -2*b\n",
+    "      evals = np.linalg.eigvals(J)\n",
+    "      evals\n",
+    "      stability_per = np.zeros(len(evals))\n",
+    "      for i in range(0,len(evals)):\n",
+    "        real_part = np.real(evals[i])\n",
+    "        if real_part > 0:\n",
+    "          un = 1\n",
+    "          stability_per[i] =un\n",
+    "        else:\n",
+    "          un = 0\n",
+    "          stability_per[i] = un\n",
+    "      value = np.zeros(len(new_values[j]))\n",
+    "      if stability_per.any()==1:\n",
+    "        value = 1\n",
+    "      else:\n",
+    "        value = 0\n",
+    "      stability_connection.append(value)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d0cc382d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "w = [[C3_all[i]] * len(new_values[i]) for i in range(len(new_values))]\n",
+    "index_unstable = np.where(np.array(stability_connection)==1)\n",
+    "\n",
+    "x_to_plot_prev = [item for sublist in w for item in sublist]\n",
+    "y_to_plot = [item for sublist in new_values for item in sublist]\n",
+    "x_to_plot = [i * 135 for i in x_to_plot_prev] \n",
+    "x_array = np.array(x_to_plot)\n",
+    "y_array = np.array(y_to_plot)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "f91d48eb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "val = [0.15*135, 0.2*135, 0.25*135,0.35*135, 0.5*135]\n",
+    "pos = []\n",
+    "for i in val:\n",
+    "    pos.append(np.where(np.round(x_array,3)==i)[0][0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "d998dede",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f08595f5220>"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 4000x3000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax1=plt.subplots(figsize=(4, 3), dpi =1000)\n",
+    "ax1.scatter(x_to_plot, y_to_plot, color=plt.cm.Set1(1), label='stable')\n",
+    "ax1.scatter(x_array[index_unstable], y_array[index_unstable], color = plt.cm.Set1(0),label='unstable')\n",
+    "ax2=plt.twiny(ax1)\n",
+    "ax2.scatter(x_to_plot, y_to_plot, color=plt.cm.Set1(1), alpha=0)\n",
+    "ax2.set_xlabel('Connectivity C4')\n",
+    "markers = [\"s\", \"v\", \"x\", \"*\", \"+\"]\n",
+    "x = val\n",
+    "y = y_array[pos]\n",
+    "for xp, yp, m in zip(x, y, markers):\n",
+    "   ax1.scatter(xp, yp, marker=m, color=\"black\",s=100)\n",
+    "#plt.scatter([0.15, 0.2, 0.25,0.35, 0.5], y_array[res],marker=\"x\",color = \"black\", s= 100)\n",
+    "ax1.set_ylabel(\"Fixed point (y1-y2: mV)\")\n",
+    "ax1.set_xlabel(\"Connectivity C3\")\n",
+    "ax1.legend()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "alpha",
+   "language": "python",
+   "name": "alpha"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/content/LW_fixed_points.ipynb b/content/LW_fixed_points.ipynb
new file mode 100644
index 0000000..399c771
--- /dev/null
+++ b/content/LW_fixed_points.ipynb
@@ -0,0 +1,301 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "0f71151f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!pip install geopandas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "607433e0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "from scipy.optimize import fsolve\n",
+    "from shapely.geometry import LineString"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "a0322c6a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sigm(v):\n",
+    "  spikerate = S_max/(1 + np.exp(-np.sqrt(2)*(v - mu)/sigma))\n",
+    "  return spikerate\n",
+    "\n",
+    "def psi_ee(ve):\n",
+    "  return (h_ee_eq-ve)/(abs(h_ee_eq-h_e_r))\n",
+    "\n",
+    "def psi_ie(ve): \n",
+    "  return (h_ie_eq-ve)/(abs(h_ie_eq-h_e_r))\n",
+    "\n",
+    "def psi_ei(ve): \n",
+    "  return (h_ei_eq-ve)/(abs(h_ei_eq-h_i_r))\n",
+    "\n",
+    "def psi_ii(ve): \n",
+    "  return (h_ii_eq-ve)/(abs(h_ii_eq-h_i_r))\n",
+    "\n",
+    "def diff_sigm_e(h_e):\n",
+    "  #sprime = math.sqrt(2)/sigma_e*S_e_max/(1+math.exp(-math.sqrt(2)*(h_e-mu_e)/sigma_e))**(2)*math.exp(-math.sqrt(2)*(h_e-mu_e)/sigma_e)\n",
+    "  sprime = (S_max*math.sqrt(2)*math.exp((-math.sqrt(2)*(h_e-mu))/sigma)) / (sigma*(1 + math.exp((-math.sqrt(2)*(h_e-mu))/sigma)) **2)\n",
+    "  return sprime\n",
+    "\n",
+    "def diff_sigm_i(h_i):\n",
+    "  #sprime = math.sqrt(2)/sigma_i*S_i_max/(1+math.exp(-math.sqrt(2)*(h_i-mu_i)/sigma_i))**(2)*math.exp(-math.sqrt(2)*(h_i-mu_i)/sigma_i)\n",
+    "  sprime = (S_max*math.sqrt(2)*math.exp((-math.sqrt(2)*(h_i-mu))/sigma)) / (sigma*(1 + math.exp((-math.sqrt(2)*(h_i-mu))/sigma)) **2)\n",
+    "  return sprime"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "07fe3530",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h_e_r = -70\n",
+    "h_i_r = -70\n",
+    "h_ee_eq = 45\n",
+    "h_ie_eq = -90\n",
+    "h_ei_eq = 45\n",
+    "h_ii_eq = -90\n",
+    "Gamma_e = 0.71\n",
+    "Gamma_i = 0.71\n",
+    "gamma_e = 0.3\n",
+    "gamma_i = 0.065\n",
+    "N_ee_b = 3000\n",
+    "N_ie_b =  200\n",
+    "N_ei_b = 2200\n",
+    "N_ii_b = 500\n",
+    "S_max = 0.5\n",
+    "mu = -50\n",
+    "sigma = 5\n",
+    "p_ee = 3.460\n",
+    "p_ei = 5.070\n",
+    "tau_e = 94\n",
+    "tau_i = 42"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "a69f6321",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "all_fixed_y0 = []\n",
+    "all_fixed_y1 = []\n",
+    "\n",
+    "N_ie_b = np.arange(300,700, 1) \n",
+    "N_ei_b = np.arange(2000, 4000,5) \n",
+    "x = np.linspace(-100, 10, 1000)\n",
+    "x1 = np.linspace(-100, 10, 1000)\n",
+    "X, Y = np.meshgrid(x,x1)\n",
+    "\n",
+    "for i in range(0, len(N_ei_b)):\n",
+    "    F1 = -X + (h_e_r + psi_ee(X) * ((Gamma_e/gamma_e)*np.exp(1)*(N_ee_b*sigm(X)+p_ee)) + psi_ie(X) * ((Gamma_i/gamma_i)*np.exp(1)*(N_ie_b[i]*sigm(Y))))\n",
+    "    F2 = - Y + (h_i_r + psi_ei(Y) * ((Gamma_e/gamma_e)*np.exp(1)*(N_ei_b[i]*sigm(X)+p_ei)) + psi_ii(Y) * ((Gamma_i/gamma_i)*np.exp(1)*(N_ii_b*sigm(Y))))\n",
+    "    contour1 = plt.contour(X,Y,F1,[0])\n",
+    "    contour2 = plt.contour(X,Y,F2,[0])\n",
+    "\n",
+    "    v1 = contour1.collections[0].get_paths()[0].vertices\n",
+    "    v2 = contour2.collections[0].get_paths()[0].vertices\n",
+    "    ls1 = LineString(v1)\n",
+    "    ls2 = LineString(v2)\n",
+    "    points = ls1.intersection(ls2)\n",
+    "    xnew, ynew = points.x, points.y\n",
+    "    \n",
+    "    all_fixed_y0.append(xnew)\n",
+    "    all_fixed_y1.append(ynew)\n",
+    "#plt.plot(xnew, ynew, 'ro')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "bc5fb446",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "un = 0\n",
+    "stability = []\n",
+    "for i in range(0,len(all_fixed_y0)):\n",
+    "    # Jacobian matrix test\n",
+    "    J = np.zeros((10,10))\n",
+    "    ve_fixed_point = all_fixed_y0[i]\n",
+    "    vi_fixed_point = all_fixed_y1[i]\n",
+    "    # See appendix Hartoyo as the details\n",
+    "    I_ee_fixed = (Gamma_e/gamma_e)*math.exp(1)*(N_ee_b*sigm(ve_fixed_point)+p_ee)\n",
+    "    I_ei_fixed = (Gamma_e/gamma_e)*math.exp(1)*(N_ei_b[i]*sigm(ve_fixed_point)+p_ei)\n",
+    "    I_ie_fixed = (Gamma_i/gamma_i)*math.exp(1)*(N_ie_b[i]*sigm(vi_fixed_point))\n",
+    "    I_ii_fixed = (Gamma_i/gamma_i)*math.exp(1)*(N_ii_b*sigm(vi_fixed_point))\n",
+    "\n",
+    "    J[0,0] = (1/tau_e)*(-1 - (I_ee_fixed/(abs(h_ee_eq-h_e_r)))  - (I_ie_fixed/(abs(h_ie_eq-h_e_r)))  )\n",
+    "    J[0,2] = (psi_ee(ve_fixed_point))/(tau_e)  #not sure if diff or normal sigmoid (considered a constant)\n",
+    "    J[0,6] = (psi_ie(ve_fixed_point))/(tau_e)\n",
+    "    J[1,1] = (1/tau_i)*(-1 - (I_ei_fixed/(abs(h_ei_eq-h_i_r)))  - (I_ii_fixed/(abs(h_ii_eq-h_i_r)))  )\n",
+    "    J[1,4] = (psi_ei(vi_fixed_point))/(tau_i)\n",
+    "    J[1,8] = (psi_ii(vi_fixed_point))/(tau_i)\n",
+    "    J[2,3] = 1 \n",
+    "    J[3,0] = Gamma_e*gamma_e*math.exp(1)*N_ee_b*diff_sigm_e(ve_fixed_point)\n",
+    "    J[3,2] = -gamma_e**2\n",
+    "    J[3,3] = -2*gamma_e\n",
+    "    J[4,5] = 1\n",
+    "    J[5,0] = Gamma_e*gamma_e*math.exp(1)*N_ei_b[i]*diff_sigm_e(ve_fixed_point)\n",
+    "    J[5,4] = -gamma_e**2\n",
+    "    J[5,5] = -2*gamma_e\n",
+    "    J[6,7] = 1\n",
+    "    J[7,1] = Gamma_i*gamma_i*math.exp(1)*N_ie_b[i]*diff_sigm_i(vi_fixed_point)\n",
+    "    J[7,6] = -gamma_i**2\n",
+    "    J[7,7] = -2*gamma_i\n",
+    "    J[8,9] = 1\n",
+    "    J[9,1] = Gamma_i*gamma_i*math.exp(1)*N_ii_b*diff_sigm_i(vi_fixed_point)\n",
+    "    J[9,8] = -gamma_i**2\n",
+    "    J[9,9] = -2*gamma_i\n",
+    "\n",
+    "    evals = np.linalg.eigvals(J)\n",
+    "    evals\n",
+    "    stability_per = np.zeros(len(evals))\n",
+    "    for j in range(0,len(evals)):\n",
+    "      real_part = np.real(evals[j])\n",
+    "      if real_part > 0:\n",
+    "        un = 1\n",
+    "        stability_per[j] = un\n",
+    "      else:\n",
+    "        un = 0\n",
+    "        stability_per[j] = un\n",
+    "    if stability_per.any()==1:\n",
+    "      value = 1\n",
+    "    else:\n",
+    "      value = 0\n",
+    "    stability.append(value)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "3c6862ad",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "val = [2450, 2650, 2850, 3050, 3250]\n",
+    "pos = []\n",
+    "for i in val:\n",
+    "    pos.append(np.where(np.round(N_ei_b,3)==i)[0][0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "e4a291b0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f43300a4d90>"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 4000x3000 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 4000x3000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "index_unstable = np.where(np.array(stability)==1)\n",
+    "array_unstable = np.array(index_unstable).flatten()\n",
+    "plt.figure(figsize=(4, 3), dpi =1000)\n",
+    "all_fixed_array = np.array(all_fixed_y0)\n",
+    "\n",
+    "fig,ax1=plt.subplots(figsize=(4, 3), dpi =1000)\n",
+    "ax1.scatter(N_ei_b, all_fixed_y0, color=plt.cm.Set1(1), label='stable')\n",
+    "ax1.scatter(N_ei_b[array_unstable], all_fixed_array[array_unstable],color = plt.cm.Set1(0), label='unstable')\n",
+    "ax1.set_xlabel('$N_{ei}$')\n",
+    "\n",
+    "ax2=plt.twiny(ax1)\n",
+    "ax2.scatter(N_ie_b, all_fixed_y0, color=plt.cm.Set1(1), alpha=0)\n",
+    "ax2.set_xlabel('$N_{ie}$')\n",
+    "\n",
+    "markers = [\"s\", \"v\", \"x\", \"*\", \"+\"]\n",
+    "x = val\n",
+    "y = all_fixed_array[pos]\n",
+    "for xp, yp, m in zip(x, y, markers):\n",
+    "   ax1.scatter(xp, yp, marker=m, color=\"black\",s=100)\n",
+    "\n",
+    "ax1.set_ylabel(\"Fixed point ($V_{e}$: mV)\")\n",
+    "ax1.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8fa32189",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "alpha",
+   "language": "python",
+   "name": "alpha"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/content/Rate_Constant_Heatmap.ipynb b/content/Rate_Constant_Heatmap.ipynb
new file mode 100644
index 0000000..4b21846
--- /dev/null
+++ b/content/Rate_Constant_Heatmap.ipynb
@@ -0,0 +1,453 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "6934dae3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import math\n",
+    "import matplotlib.pyplot as plt\n",
+    "from scipy.signal import welch\n",
+    "from scipy.optimize import fsolve\n",
+    "from fooof import FOOOF"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3bfef51d",
+   "metadata": {},
+   "source": [
+    "# Jansen-Rit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f088dad1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sigm(nu_max,v0,r,v):\n",
+    "  action_potential = 2*nu_max/(1+math.exp(r*(v0-v)))\n",
+    "  return action_potential"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ec5148df",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Model Parameters\n",
+    "A = 3.25\n",
+    "B = 22\n",
+    "C1 = 135\n",
+    "C2 = 0.8*C1\n",
+    "C3 = 0.25*C1\n",
+    "C4 = 0.25*C1\n",
+    "v0 = 6         \n",
+    "nu_max = 2.5  \n",
+    "r = 0.56      \n",
+    "\n",
+    "# Varying tau_e and tau_i\n",
+    "tau_e = np.arange(2,60,2) \n",
+    "tau_i = np.arange(2,60,2)\n",
+    "a_val = 1/(tau_e*0.001)\n",
+    "b_val = 1/(tau_i*0.001)\n",
+    "\n",
+    "\n",
+    "# Initialization Parameters\n",
+    "start = 0.0\n",
+    "stim_time = 100\n",
+    "dt = 1e-4\n",
+    "time_array = np.arange(start=start, stop=stim_time, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "noise = np.random.uniform(120,320,vec_len)\n",
+    "y = np.zeros((6,vec_len))\n",
+    "combination_number = []\n",
+    "New_final = np.zeros((len(b_val), len(a_val)))\n",
+    "\n",
+    "for ind2, a in enumerate(a_val):\n",
+    "  for ind, b in enumerate(b_val):\n",
+    "    for i in range (1,vec_len):\n",
+    "      y[0,i] = y[0,i-1] + y[3,i-1]*dt\n",
+    "      y[1,i] = y[1,i-1] + y[4,i-1]*dt\n",
+    "      y[2,i] = y[2,i-1] + y[5,i-1]*dt\n",
+    "      y[3,i] = y[3,i-1] + dt * (A*a*(sigm(nu_max,v0,r,(y[1,i-1]-y[2,i-1]))) - (2*a*y[3,i-1]) - (a**(2)*y[0,i-1]))\n",
+    "      y[4,i] = y[4,i-1] + dt * (A*a*(noise[i-1] + (C2*sigm(nu_max,v0,r,(C1*y[0,i-1])))) - (2*a*y[4,i-1]) - (a**(2)*y[1,i-1]))\n",
+    "      y[5,i] = y[5,i-1] + dt * (B*b*(C4*sigm(nu_max,v0,r,(C3*y[0,i-1]))) - (2*b*y[5,i-1]) - (b**(2)*y[2,i-1]))\n",
+    "\n",
+    "    out = y[1,:]-y[2,:]\n",
+    "    \n",
+    "    if out[20000] == out[20005]:\n",
+    "      freqWelch = 0\n",
+    "    else:\n",
+    "      output = out[1000:] \n",
+    "      # Welch method\n",
+    "      X = signal.resample(output, 10000)\n",
+    "      freqs_new,ps_vPN_new = welch(X,fs=100, noverlap = 125, nperseg=1000)\n",
+    "      fm = FOOOF(max_n_peaks=2, min_peak_height=1, aperiodic_mode='knee')\n",
+    "      fm.fit(freqs_new, ps_vPN_new, [1,50])\n",
+    "      cfs = fm.get_params('peak_params', 'CF')\n",
+    "      if np.isnan(cfs).any():\n",
+    "        New_final[ind, ind2] = 0\n",
+    "      elif cfs.shape ==():\n",
+    "        New_final[ind, ind2] = cfs\n",
+    "      else:\n",
+    "        pws = fm.get_params('peak_params', 'PW')\n",
+    "        New_final[ind, ind2] = cfs[np.argmax(pws)]\n",
+    "    combination_number.append([ind, ind2])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b0282184",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Figure\n",
+    "data = pd.DataFrame(New_final, index = tau_i, columns=tau_e)\n",
+    "plt.figure(figsize=(8,5), dpi=300)\n",
+    "plt.rcParams['font.size'] = '14'\n",
+    "ax = sns.heatmap(data,  cmap='viridis')\n",
+    "ax.set_xlabel(r\"${\\tau}_{e}$\",fontsize=18)\n",
+    "ax.set_ylabel(r\"${\\tau}_{i}$\",fontsize=18)\n",
+    "ax.invert_yaxis()\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3a557b62",
+   "metadata": {},
+   "source": [
+    "# Moran-David-Friston"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8c9f68b2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sigm(x):\n",
+    "  return (1/(1+math.exp(-rho_1*(x - rho_2)))) - (1/(1+math.exp(rho_1*rho_2)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "192011d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "start = 0.0\n",
+    "stim_time = 10\n",
+    "dt = 0.001\n",
+    "time_array = np.arange(start=start, stop=stim_time, step=dt)\n",
+    "vec_len = len(time_array)\n",
+    "\n",
+    "#Initialize input and output\n",
+    "x = np.zeros((12,vec_len))\n",
+    "\n",
+    "H_e = 10 \n",
+    "H_i = 32 \n",
+    "gamma_1 = 128\n",
+    "gamma_2 =128\n",
+    "gamma_3 = 64\n",
+    "gamma_4 =64\n",
+    "gamma_5 = 4\n",
+    "rho_1 = 2\n",
+    "rho_2 = 1\n",
+    "a= 0   \n",
+    "\n",
+    "# Varying tau_e and tau_i\n",
+    "tau_e = np.arange(2,60,1)\n",
+    "tau_i = np.arange(2,60,1)\n",
+    "kappa_e_val = (1/tau_e) * 1000 \n",
+    "kappa_i_val = (1/tau_i) * 1000\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bd649ffa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "final_rate= np.zeros((len(kappa_e_val), len(kappa_i_val)))\n",
+    "\n",
+    "for ind2, kappa_e in enumerate(kappa_e_val):\n",
+    "  for ind, kappa_i in enumerate(kappa_i_val):\n",
+    "    \n",
+    "    noise = kappa_e*H_e*math.sqrt(dt)*np.random.normal(0, 1, vec_len)\n",
+    "    for i in range (1,vec_len):\n",
+    "\n",
+    "      #Inhibitory cells in agranular layers\n",
+    "      x[6,i] = x[6,i-1] + dt * x[7,i-1]\n",
+    "      x[7,i] = x[7,i-1] + dt * (kappa_e*H_e*(gamma_3)*sigm(x[8,i-1]) - 2*kappa_e*x[7,i-1] - kappa_e**(2)*x[6,i-1])\n",
+    "      x[9,i] = x[9,i-1] + dt * x[10,i-1]\n",
+    "      x[10,i] = x[10,i-1] + dt * (kappa_i*H_i*gamma_5*sigm(x[11,i-1]) - 2*kappa_i*x[10,i-1] - kappa_i**(2)*x[9,i-1])\n",
+    "      x[11,i] = x[11,i-1] + dt * (x[7,i-1] - x[10,i-1])\n",
+    "\n",
+    "      #Excitatory spiny cells in granualar layer\n",
+    "      x[0,i] =  x[0,i-1] + dt * x[3,i-1]\n",
+    "      x[3,i] = x[3,i-1] + dt * (kappa_e*H_e*(gamma_1*sigm(x[8,i-1]-a)) - 2*kappa_e*x[3,i-1] - kappa_e**(2)*x[0,i-1]) + noise[i-1]    \n",
+    "\n",
+    "      #Excitatory pyramidal cells in agranular layers\n",
+    "      x[1,i] = x[1,i-1] + dt * x[4,i-1]\n",
+    "      x[4,i] =  x[4,i-1] + dt * (kappa_e*H_e*(gamma_2*sigm(x[0,i-1])) - 2*kappa_e*x[4,i-1] - kappa_e**(2)*x[1,i-1])\n",
+    "      x[2,i] = x[2,i-1] + dt * x[5,i-1]\n",
+    "      x[5,i] = x[5,i-1] + dt * (kappa_i*H_i*gamma_4*sigm(x[11,i-1]) - 2*kappa_i*x[5,i-1] - kappa_i**(2)*x[2,i-1])\n",
+    "      x[8,i] = x[8,i-1] + dt * (x[4,i-1] - x[5,i-1])\n",
+    "    \n",
+    "    if out[2000] == out[2005]:\n",
+    "        final_rate[ind2, ind] = 0\n",
+    "    else: \n",
+    "        out = x[8,0:]\n",
+    "        output = out[1000:] \n",
+    "          # Welch method\n",
+    "        freqsW,ps_vPN = welch(output,fs=1000, noverlap = 125, nperseg=1000)\n",
+    "        fm = FOOOF(max_n_peaks=2, min_peak_height=1, aperiodic_mode='knee')\n",
+    "        fm.fit(freqsW, ps_vPN, [1,100])\n",
+    "        cfs = fm.get_params('peak_params', 'CF')\n",
+    "        if np.isnan(cfs).any():\n",
+    "            final_rate[ind2, ind] = 0\n",
+    "        elif cfs.shape ==():\n",
+    "            final_rate[ind2, ind] = cfs\n",
+    "        else:\n",
+    "            pws = fm.get_params('peak_params', 'PW')\n",
+    "            final_rate[ind2, ind] = cfs[np.argmax(pws)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "205011da",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Figure\n",
+    "data = pd.DataFrame(np.transpose(final_rate), index = tau_i, columns=tau_e)\n",
+    "plt.figure(figsize=(8,5), dpi=300)\n",
+    "plt.rcParams['font.size'] = '14'\n",
+    "ax = sns.heatmap(data,  cmap='viridis')\n",
+    "ax.set_xlabel(r\"${\\tau}_{e}$\",fontsize=18)\n",
+    "ax.set_ylabel(r\"${\\tau}_{i}$\",fontsize=18)\n",
+    "ax.invert_yaxis()\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4299955d",
+   "metadata": {},
+   "source": [
+    "# Liley-Wright"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1f923b81",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def dynamics(p,X):\n",
+    "    dX = np.zeros((18,1))\n",
+    "\n",
+    "    # Calculate synaptic reversal potentials\n",
+    "    psi_ee=(p.h_ee_eq-X[0])/abs(p.h_ee_eq-p.h_e_r)\n",
+    "    psi_ie=(p.h_ie_eq-X[0])/abs(p.h_ie_eq-p.h_e_r)\n",
+    "    psi_ei=(p.h_ei_eq-X[1])/abs(p.h_ei_eq-p.h_i_r)\n",
+    "    psi_ii=(p.h_ii_eq-X[1])/abs(p.h_ii_eq-p.h_i_r)\n",
+    "\n",
+    "    # Calculate synaptic inputs A_jk \n",
+    "    A_ee=p.N_ee_b*S_e(p,X[0])+X[10]+p.p_ee\n",
+    "    A_ei=p.N_ei_b*S_e(p,X[0])+X[12]+p.p_ei\n",
+    "    A_ie=p.N_ie_b*S_i(p,X[1])\n",
+    "    A_ii=p.N_ii_b*S_i(p,X[1])   \n",
+    "\n",
+    "    # Calculate state vector\n",
+    "    dX[0] = (1/p.tau_e)*(p.h_e_r-X[0]+psi_ee*X[2]+psi_ie*X[6]) # V_e\n",
+    "    dX[1] = (1/p.tau_i)*(p.h_i_r-X[1]+psi_ei*X[4]+psi_ii*X[8]) # V_i\n",
+    "    dX[2] = X[3] # I_ee\n",
+    "    dX[3] = -2*p.gamma_ee*X[3]-p.gamma_ee**(2)*X[2]+p.gamma_ee*math.exp(1)*p.Gamma_ee*A_ee# J_ee\n",
+    "    dX[4] = X[5] # I_ei\n",
+    "    dX[5] = -2*p.gamma_ei*X[5]-p.gamma_ei**(2)*X[4]+p.gamma_ei*math.exp(1)*p.Gamma_ei*A_ei# J_ei\n",
+    "    dX[6] = X[7] # I_ie\n",
+    "    dX[7] = -2*p.gamma_ie*X[7]-p.gamma_ie**(2)*X[6]+p.gamma_ie*math.exp(1)*p.Gamma_ie*A_ie# J_ie\n",
+    "    dX[8] = X[9] # I_ii\n",
+    "    dX[9] = -2*p.gamma_ii*X[9]-p.gamma_ii**(2)*X[8]+p.gamma_ii*math.exp(1)*p.Gamma_ii*A_ii# J_ii% J_ii\n",
+    "    return dX\n",
+    "    \n",
+    "def S_e(t,v):   \n",
+    "    p = t\n",
+    "    spikerate = p.S_e_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_e)/p.sigma_e))\n",
+    "    return spikerate\n",
+    "\n",
+    "def S_i(t,v):\n",
+    "    p=t\n",
+    "    spikerate = p.S_i_max/(1 + math.exp(-math.sqrt(2)*(v - p.mu_i)/p.sigma_i))\n",
+    "    return spikerate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c8eb650d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class p:\n",
+    "  S_e_max = 0.5\n",
+    "  S_i_max = 0.5\n",
+    "  h_e_r = -70\n",
+    "  h_i_r = -70\n",
+    "  mu_e = -50\n",
+    "  mu_i = -50\n",
+    "  sigma_e = 5\n",
+    "  sigma_i = 5\n",
+    "  tau_e = 94\n",
+    "  tau_i = 42\n",
+    "  h_ee_eq = 4\n",
+    "  h_ei_eq = 45\n",
+    "  h_ie_eq = -90\n",
+    "  h_ii_eq = -90\n",
+    "  Gamma_ee = 0.71\n",
+    "  Gamma_ei = 0.71\n",
+    "  Gamma_ie = 0.71\n",
+    "  Gamma_ii = 0.71\n",
+    "  gamma_ee = 0.3\n",
+    "  gamma_ei = 0.3\n",
+    "  gamma_ie = 0.065\n",
+    "  gamma_ii = 0.065\n",
+    "  p_ee = 3.460\n",
+    "  p_ee_sd = 1.000\n",
+    "  p_ei = 5.070\n",
+    "  p_ei_sd = 0\n",
+    "  p_ie = 0\n",
+    "  p_ii = 0\n",
+    "  N_ei_b = 3000\n",
+    "  N_ee_b = 3000\n",
+    "  N_ie_b = 500\n",
+    "  N_ii_b = 500\n",
+    "\n",
+    "  # Varying tau_ee and tau_ii  \n",
+    "  tau_ee = np.arange(1, 10, 0.2) \n",
+    "  tau_ii = np.arange(10, 60, 1) \n",
+    "  gamma_ee_tot = 1/tau_ee\n",
+    "  gamma_ii_tot = 1/tau_ii"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7c97e37d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sim_time=50         \n",
+    "dt = 1e-4\n",
+    "steps= 1/dt           \n",
+    "white_noise=1     \n",
+    "\n",
+    "p.v_e_equil = p.h_e_r\n",
+    "p.v_i_equil = p.h_i_r\n",
+    "\n",
+    "h = 1000/steps \n",
+    "T = sim_time*10**3 \n",
+    "N = T/h-1\n",
+    "New_final = np.zeros((len(p.gamma_ii_tot), len(p.gamma_ee_tot)))\n",
+    "for ind2, p.gamma_ee in enumerate(p.gamma_ee_tot):\n",
+    " for ind, p.gamma_ii in enumerate(p.gamma_ii_tot):\n",
+    "    p.gamma_ei = p.gamma_ee\n",
+    "    p.gamma_ie = p.gamma_ii\n",
+    "\n",
+    "    X = np.zeros((18,int(N)))\n",
+    "    X[0,0] = p.v_e_equil\n",
+    "    X[1,0] = p.v_i_equil   \n",
+    "    X[2,0] = math.exp(1)/p.gamma_ee*p.Gamma_ee*(p.N_ee_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ee) \n",
+    "    X[4,0] = math.exp(1)/p.gamma_ei*p.Gamma_ei*(p.N_ei_b*S_e(p,p.v_e_equil) + 0*S_e(p,p.v_e_equil)+p.p_ei)\n",
+    "    X[6,0] = math.exp(1)/p.gamma_ie*p.Gamma_ie*(p.N_ie_b*S_i(p,p.v_i_equil))#\n",
+    "    X[8,0] = math.exp(1)/p.gamma_ii*p.Gamma_ii*(p.N_ii_b*S_i(p,p.v_i_equil))\n",
+    "    \n",
+    "    for n in range (0,int(N-1)):\n",
+    "        noise = np.zeros((18,1))\n",
+    "        if (white_noise==1):\n",
+    "          noise[3]= p.gamma_ee*math.exp(p.gamma_ee/p.gamma_ee)*p.Gamma_ee*p.p_ee_sd*np.random.randn(1,1)\n",
+    "        X[:,n+1] = X[:,n] + ((h*dynamics(p,X[:,n])+math.sqrt(h)*noise).flatten())\n",
+    "    EEG=-X[0,:]\t\n",
+    "\n",
+    "    if np.round(EEG[2000],6) == np.round(EEG[2005],6):\n",
+    "      freqWelch = 0\n",
+    "    else:\n",
+    "      output = EEG[1000:]\n",
+    "      # Welch method\n",
+    "      X = signal.resample(output, 5000)\n",
+    "      freqs_new,ps_vPN_new = welch(X,fs=100, noverlap = 125, nperseg=1000)\n",
+    "      fm = FOOOF(max_n_peaks=2, min_peak_height=1, aperiodic_mode='knee')\n",
+    "      fm.fit(freqs_new, ps_vPN_new, [1,50])\n",
+    "      cfs = fm.get_params('peak_params', 'CF')\n",
+    "      if np.isnan(cfs).any():\n",
+    "        New_final[ind, ind2] = 0\n",
+    "      elif cfs.shape ==():\n",
+    "        New_final[ind, ind2] = cfs\n",
+    "      else:\n",
+    "        pws = fm.get_params('peak_params', 'PW')\n",
+    "        New_final[ind, ind2] = cfs[np.argmax(pws)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f58bbdd0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Figure\n",
+    "data = pd.DataFrame(New_final, index = p.tau_ii, columns=p.tau_ee)\n",
+    "plt.figure(figsize=(8,5), dpi=300)\n",
+    "plt.rcParams['font.size'] = '14'\n",
+    "ax = sns.heatmap(data,  cmap='viridis')\n",
+    "ax.set_xlabel(r\"${\\tau}_{e}$\",fontsize=18)\n",
+    "ax.set_ylabel(r\"${\\tau}_{i}$\",fontsize=18)\n",
+    "ax.invert_yaxis()\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "alpha",
+   "language": "python",
+   "name": "alpha"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}