diff --git a/tutorials/.ipynb_checkpoints/run-checkpoint.ipynb b/tutorials/.ipynb_checkpoints/run-checkpoint.ipynb
deleted file mode 100644
index a246a47..0000000
--- a/tutorials/.ipynb_checkpoints/run-checkpoint.ipynb
+++ /dev/null
@@ -1,3980 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 108,
-   "id": "b5acf92b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from scipy import optimize\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "\n",
-    "class zfactor(object):\n",
-    "    def __init__(\n",
-    "            self,\n",
-    "            mode='Sutton',\n",
-    "            Pc_H2S=1306,\n",
-    "            Tc_H2S=672.3,\n",
-    "            Pc_CO2=1071,\n",
-    "            Tc_CO2=547.5,\n",
-    "            Pc_N2=492.4,\n",
-    "            Tc_N2=227.16,\n",
-    "            A1=0.3265,\n",
-    "            A2=-1.0700,\n",
-    "            A3=-0.5339,\n",
-    "            A4=0.01569,\n",
-    "            A5=-0.05165,\n",
-    "            A6=0.5475,\n",
-    "            A7=-0.7361,\n",
-    "            A8=0.1844,\n",
-    "            A9=0.1056,\n",
-    "            A10=0.6134,\n",
-    "            A11=0.7210,\n",
-    "    ):\n",
-    "        self._check_invalid_mode(mode)\n",
-    "        self.mode = mode\n",
-    "\n",
-    "        self.T = None\n",
-    "        self.sg = None\n",
-    "        self._T = None\n",
-    "        self.P = None\n",
-    "        self.H2S = None\n",
-    "        self.CO2 = None\n",
-    "        self.N2 = None\n",
-    "\n",
-    "        self.Pc_H2S = Pc_H2S\n",
-    "        self.Tc_H2S = Tc_H2S\n",
-    "        self.Pc_CO2 = Pc_CO2\n",
-    "        self.Tc_CO2 = Tc_CO2\n",
-    "        self.Pc_N2 = Pc_N2\n",
-    "        self.Tc_N2 = Tc_N2\n",
-    "\n",
-    "        self.Tpc = None\n",
-    "        self.Ppc = None\n",
-    "        self.A = None\n",
-    "        self.B = None\n",
-    "        self.e_correction = None\n",
-    "        self.Tpc_corrected = None\n",
-    "        self.Ppc_corrected = None\n",
-    "        self.J = None\n",
-    "        self.K = None\n",
-    "        self.Tr = None\n",
-    "        self.Pr = None\n",
-    "\n",
-    "        self.A1 = A1\n",
-    "        self.A2 = A2\n",
-    "        self.A3 = A3\n",
-    "        self.A4 = A4\n",
-    "        self.A5 = A5\n",
-    "        self.A6 = A6\n",
-    "        self.A7 = A7\n",
-    "        self.A8 = A8\n",
-    "        self.A9 = A9\n",
-    "        self.A10 = A10\n",
-    "        self.A11 = A11\n",
-    "\n",
-    "        self.Z = None\n",
-    "\n",
-    "        self._calc_from = None\n",
-    "\n",
-    "    def __str__(self):\n",
-    "        return str(self.Z)\n",
-    "\n",
-    "    def __repr__(self):\n",
-    "        return '<GasCompressibilityFactor object. Mixing Rule = %s>' % self.mode\n",
-    "\n",
-    "    def calc_Fahrenheit_to_Rankine(self, _T):\n",
-    "        if _T is None:\n",
-    "            raise TypeError(\"Missing a required argument, 'T' (gas temperature, °F)\")\n",
-    "        self._T = _T  # Fahrenheit\n",
-    "        self.T = _T + 459.67  # Rankine, Rankine is used for calculation below\n",
-    "        return self.T\n",
-    "\n",
-    "    \"\"\"pseudo-critical temperature (°R)\"\"\"\n",
-    "    def calc_Tpc(self, sg=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n",
-    "        if self.mode == 'Sutton':\n",
-    "            self._initialize_sg(sg, calc_from='Tpc')\n",
-    "            self.Tpc = 169.2 + 349.5 * self.sg - 74.0 * self.sg ** 2\n",
-    "        else:  # mode == 'Piper'\n",
-    "            self._redundant_argument_check_J_or_K(sg=sg, J=J, K=K, H2S=H2S, CO2=CO2, N2=N2)\n",
-    "            self._initialize_J(J, sg=sg, H2S=H2S, CO2=CO2, N2=N2)\n",
-    "            self._initialize_K(K, sg=sg, H2S=H2S, CO2=CO2, N2=N2)\n",
-    "            self.Tpc = self.K ** 2 / self.J\n",
-    "        return self.Tpc\n",
-    "\n",
-    "    \"\"\"pseudo-critical pressure (psi)\"\"\"\n",
-    "    def calc_Ppc(self, sg=None, H2S=None, CO2=None, N2=None, J=None, K=None, Tpc=None):\n",
-    "        if self.mode == 'Sutton':\n",
-    "            self._initialize_sg(sg, calc_from='Ppc')\n",
-    "            self.Ppc = 756.8 - 131.07 * self.sg - 3.6 * self.sg ** 2\n",
-    "        else:  # mode = 'Piper'\n",
-    "            self._redundant_argument_check_J_or_K(sg=sg, J=J, K=K, H2S=H2S, CO2=CO2, N2=N2)\n",
-    "            if Tpc is not None:\n",
-    "                if K is not None:\n",
-    "                    raise TypeError(\"Redundant arguments 'Tpc' and 'K', input only one of them\")\n",
-    "            self._initialize_Tpc(Tpc, sg=sg, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n",
-    "            self._initialize_J(J, sg=sg, H2S=H2S, CO2=CO2, N2=N2)\n",
-    "            self.Ppc = self.Tpc / self.J\n",
-    "        return self.Ppc\n",
-    "\n",
-    "    \"\"\"sum of the mole fractions of CO2 and H2S in a gas mixture\"\"\"\n",
-    "    def calc_A(self, H2S=None, CO2=None):\n",
-    "        self._initialize_H2S(H2S)\n",
-    "        self._initialize_CO2(CO2)\n",
-    "        self.A = self.H2S + self.CO2\n",
-    "        return self.A\n",
-    "\n",
-    "    \"\"\"mole fraction of H2S in a gas mixture\"\"\"\n",
-    "    def calc_B(self, H2S=None):\n",
-    "        self._initialize_H2S(H2S)\n",
-    "        self.B = self.H2S\n",
-    "        return self.B\n",
-    "\n",
-    "    \"\"\"correction for CO2 and H2S (°R)\"\"\"\n",
-    "    def calc_e_correction(self, A=None, B=None, H2S=None, CO2=None):\n",
-    "\n",
-    "        if A is not None:\n",
-    "            if CO2 is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'A' and 'CO2', input only one of them\")\n",
-    "            if H2S is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'A' and 'H2S', input only one of them\")\n",
-    "        if B is not None:\n",
-    "            if H2S is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'B' and 'H2S', input only one of them\")\n",
-    "            if CO2 is not None:\n",
-    "                H2S = B\n",
-    "\n",
-    "        self._initialize_A(A, H2S=H2S, CO2=CO2)\n",
-    "        self._initialize_B(B, H2S=H2S)\n",
-    "        self.e_correction = 120 * (self.A ** 0.9 - self.A ** 1.6) + 15 * (self.B ** 0.5 - self.B ** 4)\n",
-    "        return self.e_correction\n",
-    "\n",
-    "    def calc_Tpc_corrected(self, sg=None, Tpc=None, e_correction=None, A=None, B=None, H2S=None, CO2=None):\n",
-    "        self._initialize_Tpc(Tpc, sg=sg)\n",
-    "        self._initialize_e_correction(e_correction, A=A, B=B, H2S=H2S, CO2=CO2)\n",
-    "        self.Tpc_corrected = self.Tpc - self.e_correction\n",
-    "        return self.Tpc_corrected\n",
-    "\n",
-    "    \"\"\" corrected pseudo-critical pressure (psi)\"\"\"\n",
-    "    def calc_Ppc_corrected(self, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None,\n",
-    "                           A=None, B=None, H2S=None, CO2=None):\n",
-    "\n",
-    "        if e_correction is not None:\n",
-    "            if B is None and H2S is None:\n",
-    "                raise TypeError(\"Missing a required argument, 'H2S', (mole fraction of H2S, dimensionless)\")\n",
-    "\n",
-    "        self._initialize_Ppc(Ppc, sg=sg)\n",
-    "        self._initialize_B(B, H2S=H2S)\n",
-    "        self._initialize_e_correction(e_correction, A=A, B=B, H2S=H2S, CO2=CO2)\n",
-    "        if Tpc_corrected is None:\n",
-    "            self._initialize_Tpc(Tpc, sg=sg)\n",
-    "            self._initialize_Tpc_corrected(Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, A=A, B=B, H2S=H2S, CO2=CO2)\n",
-    "        self.Ppc_corrected = (self.Ppc * self.Tpc_corrected) / (self.Tpc - self.B * (1 - self.B) * self.e_correction)\n",
-    "        return self.Ppc_corrected\n",
-    "\n",
-    "    def calc_J(self, sg=None, H2S=None, CO2=None, N2=None):\n",
-    "        self._initialize_sg(sg, calc_from='J')\n",
-    "        self._initialize_H2S(H2S)\n",
-    "        self._initialize_CO2(CO2)\n",
-    "        self._initialize_N2(N2)\n",
-    "        self.J = 0.11582 \\\n",
-    "                 - 0.45820 * self.H2S * (self.Tc_H2S / self.Pc_H2S) \\\n",
-    "                 - 0.90348 * self.CO2 * (self.Tc_CO2 / self.Pc_CO2) \\\n",
-    "                 - 0.66026 * self.N2 * (self.Tc_N2 / self.Pc_N2) \\\n",
-    "                 + 0.70729 * self.sg \\\n",
-    "                 - 0.099397 * self.sg ** 2\n",
-    "        return self.J\n",
-    "\n",
-    "    def calc_K(self, sg=None, H2S=None, CO2=None, N2=None):\n",
-    "        self._initialize_sg(sg, calc_from='K')\n",
-    "        self._initialize_H2S(H2S)\n",
-    "        self._initialize_CO2(CO2)\n",
-    "        self._initialize_N2(N2)\n",
-    "        self.K = 3.8216 \\\n",
-    "                 - 0.06534 * self.H2S * (self.Tc_H2S / np.sqrt(self.Pc_H2S)) \\\n",
-    "                 - 0.42113 * self.CO2 * (self.Tc_CO2 / np.sqrt(self.Pc_CO2)) \\\n",
-    "                 - 0.91249 * self.N2 * (self.Tc_N2 / np.sqrt(self.Pc_N2)) \\\n",
-    "                 + 17.438 * self.sg \\\n",
-    "                 - 3.2191 * self.sg ** 2\n",
-    "        return self.K\n",
-    "\n",
-    "    \"\"\"pseudo-reduced temperature (°R)\"\"\"\n",
-    "    def calc_Tr(self, T=None, Tpc_corrected=None, sg=None, Tpc=None, e_correction=None, A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n",
-    "        self._initialize_T(T)\n",
-    "        if self.mode == 'Sutton':\n",
-    "            self._redundant_argument_check_Tpc_corrected(sg=sg, Tpc=Tpc, H2S=H2S, CO2=CO2, A=A, B=B, e_correction=e_correction)\n",
-    "            self._initialize_Tpc_corrected(Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, A=A, B=B, H2S=H2S, CO2=CO2)\n",
-    "            self.Tr = self.T / self.Tpc_corrected\n",
-    "        else:  # mode == 'Piper'\n",
-    "            self._redundant_argument_check_Tpc(Tpc=Tpc, sg=sg, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n",
-    "            self._initialize_Tpc(Tpc, sg=sg, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n",
-    "            self.Tr = self.T / self.Tpc\n",
-    "        return self.Tr\n",
-    "\n",
-    "    \"\"\"pseudo-reduced pressure (psi)\"\"\"\n",
-    "    def calc_Pr(self, P=None, Ppc_corrected=None, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None, A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n",
-    "        self._initialize_P(P)\n",
-    "        if self.mode == 'Sutton':\n",
-    "            self._redundant_argument_check_Ppc_corrected(sg=sg, Ppc=Ppc, Tpc_corrected=Tpc_corrected, Tpc=Tpc, H2S=H2S, CO2=CO2, A=None, B=None, e_correction=e_correction)\n",
-    "            self._initialize_Ppc_corrected(Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction, Tpc_corrected=Tpc_corrected, A=A, B=B, H2S=H2S, CO2=CO2)\n",
-    "            self.Pr = self.P / self.Ppc_corrected\n",
-    "        else:  # mode == 'Piper'\n",
-    "            self._redundant_argument_check_Ppc(Ppc=Ppc, Tpc=Tpc, sg=sg, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n",
-    "            self._initialize_Ppc(Ppc, sg=sg, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K, Tpc=Tpc)\n",
-    "            self.Pr = self.P / self.Ppc\n",
-    "        return self.Pr\n",
-    "\n",
-    "    \"\"\"\n",
-    "    Objective function to be minimized for the Newton-Raphson non-linear solver.\n",
-    "    Wichert-Azis correlation for z-factor. \n",
-    "    \n",
-    "    Source: Wichert, E. and Aziz, K. 1972. Calculate Z's for Sour Gases. Hydrocarbon Processing 51 (May): 119–122\n",
-    "    \"\"\"\n",
-    "    def _calc_z(self, z):\n",
-    "\n",
-    "        self.A1 = 0.3265\n",
-    "        self.A2 = -1.0700\n",
-    "        self.A3 = -0.5339\n",
-    "        self.A4 = 0.01569\n",
-    "        self.A5 = -0.05165\n",
-    "        self.A6 = 0.5475\n",
-    "        self.A7 = -0.7361\n",
-    "        self.A8 = 0.1844\n",
-    "        self.A9 = 0.1056\n",
-    "        self.A10 = 0.6134\n",
-    "        self.A11 = 0.7210\n",
-    "\n",
-    "        return 1 + (\n",
-    "                self.A1 +\n",
-    "                self.A2 / self.Tr +\n",
-    "                self.A3 / self.Tr ** 3 +\n",
-    "                self.A4 / self.Tr ** 4 +\n",
-    "                self.A5 / self.Tr ** 5\n",
-    "        ) * (0.27 * self.Pr) / (z * self.Tr) + (\n",
-    "                self.A6 +\n",
-    "                self.A7 / self.Tr +\n",
-    "                self.A8 / self.Tr ** 2\n",
-    "        ) * ((0.27 * self.Pr) / (z * self.Tr)) ** 2 - self.A9 * (\n",
-    "                self.A7 / self.Tr +\n",
-    "                self.A8 / self.Tr ** 2\n",
-    "        ) * ((0.27 * self.Pr) / (z * self.Tr)) ** 5 + self.A10 * (\n",
-    "                1 +\n",
-    "                self.A11 * ((0.27 * self.Pr) / (z * self.Tr)) ** 2\n",
-    "        ) * (\n",
-    "                ((0.27 * self.Pr) / (z * self.Tr)) ** 2 /\n",
-    "                self.Tr ** 3\n",
-    "        ) * np.exp(-self.A11 * ((0.27 * self.Pr) / (z * self.Tr)) ** 2) - z\n",
-    "\n",
-    "    \"\"\"Newton-Raphson nonlinear solver\"\"\"\n",
-    "    def calc_z(self, guess=0.9, sg=None, P=None, T=None, Tpc=None, Ppc=None, Tpc_corrected=None, Ppc_corrected=None,\n",
-    "               A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None, Tr=None, Pr=None, e_correction=None, **kwargs):\n",
-    "        self._calc_from = 'calc_z'\n",
-    "        self._initialize_Pr(Pr, P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction, Tpc_corrected=Tpc_corrected, A=A, B=B, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n",
-    "        self._initialize_Tr(Tr, T, Tpc_corrected=Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, A=A, B=B, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n",
-    "        self.Z = optimize.newton(self._calc_z, guess, **kwargs)\n",
-    "        return self.Z\n",
-    "\n",
-    "    def _initialize_sg(self, sg, calc_from=None):\n",
-    "        if sg is None:\n",
-    "            if calc_from == 'Ppc' or calc_from == 'Tpc':\n",
-    "                raise TypeError(\"Missing a required argument, 'sg' (specific gravity, dimensionless)\")\n",
-    "            elif calc_from == 'J' or calc_from == 'K':\n",
-    "                raise TypeError(\"Missing a required argument, 'sg' (specific gravity, dimensionless), or 'J' \"\n",
-    "                                \"(Stewart-Burkhardt-VOO parameter, °R/psia), or \"\n",
-    "                                \"'K' (Stewart-Burkhardt-VOO parameter, °R/psia^0.5). \"\n",
-    "                                \"The calculation requires either \"\n",
-    "                                \"1) both 'J' and 'K' provided without 'sg', or \"\n",
-    "                                \"2) only 'sg' provided without both 'J' and 'K'\")\n",
-    "            else:\n",
-    "                raise TypeError(\"Missing a required arguments, 'sg' (specific gravity, dimensionless), or 'Tpc' \"\n",
-    "                                \"(pseudo-critical temperature, °R) or 'Ppc' (pseudo-critical pressure, psia). \"\n",
-    "                                \"Either both 'Tpc' and 'Ppc' must be inputted, or 'sg' needs to be inputted. \"\n",
-    "                                \"Both 'Tpc' and 'Ppc' can be computed from 'sg'\")\n",
-    "        else:\n",
-    "            self.sg = sg\n",
-    "\n",
-    "    def _initialize_P(self, P):\n",
-    "        if P is None:\n",
-    "            raise TypeError(\"Missing a required argument, 'P' (gas pressure, psia)\")\n",
-    "        else:\n",
-    "            self.P = P\n",
-    "\n",
-    "    def _initialize_T(self, T):\n",
-    "        if T is None:\n",
-    "            raise TypeError(\"Missing a required argument, 'T' (gas temperature, °F)\")\n",
-    "        else:\n",
-    "            self.T = self.calc_Fahrenheit_to_Rankine(T)\n",
-    "\n",
-    "    def _initialize_H2S(self, H2S):\n",
-    "        if H2S is None:\n",
-    "            self.H2S = 0\n",
-    "        else:\n",
-    "            self.H2S = H2S\n",
-    "\n",
-    "    def _initialize_CO2(self, CO2):\n",
-    "        if CO2 is None:\n",
-    "            self.CO2 = 0\n",
-    "        else:\n",
-    "            self.CO2 = CO2\n",
-    "\n",
-    "    def _initialize_N2(self, N2):\n",
-    "        if N2 is None:\n",
-    "            self.N2 = 0\n",
-    "        else:\n",
-    "            self.N2 = N2\n",
-    "\n",
-    "    def _initialize_Tpc(self, Tpc, sg=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n",
-    "        if Tpc is None:\n",
-    "            self.calc_Tpc(sg=sg, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n",
-    "        else:\n",
-    "            self.Tpc = Tpc\n",
-    "\n",
-    "    def _initialize_Ppc(self, Ppc, sg=None, H2S=None, CO2=None, N2=None, J=None, K=None, Tpc=None):\n",
-    "        if Ppc is None:\n",
-    "            self.calc_Ppc(sg=sg, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K, Tpc=Tpc)\n",
-    "        else:\n",
-    "            self.Ppc = Ppc\n",
-    "\n",
-    "    def _initialize_e_correction(self, e_correction, A=None, B=None, H2S=None, CO2=None):\n",
-    "        if e_correction is None:\n",
-    "            self.calc_e_correction(A, B, H2S, CO2)\n",
-    "        else:\n",
-    "            self.e_correction = e_correction\n",
-    "\n",
-    "    def _initialize_Tpc_corrected(self, Tpc_corrected, sg=None, Tpc=None, e_correction=None,\n",
-    "                                  A=None, B=None, H2S=None, CO2=None):\n",
-    "        if Tpc_corrected is None:\n",
-    "            self.calc_Tpc_corrected(sg, Tpc, e_correction, A, B, H2S, CO2)\n",
-    "        else:\n",
-    "            self.Tpc_corrected = Tpc_corrected\n",
-    "\n",
-    "    def _initialize_Ppc_corrected(self, Ppc_corrected, sg=None, Tpc=None, Ppc=None, e_correction=None,\n",
-    "                                  Tpc_corrected=None, A=None, B=None, H2S=None, CO2=None):\n",
-    "        if Ppc_corrected is None:\n",
-    "            self.calc_Ppc_corrected(sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2)\n",
-    "        else:\n",
-    "            self.Ppc_corrected = Ppc_corrected\n",
-    "\n",
-    "    def _initialize_J(self, J, sg=None, H2S=None, CO2=None, N2=None):\n",
-    "        if J is None:\n",
-    "            self.calc_J(sg, H2S, CO2, N2)\n",
-    "        else:\n",
-    "            self.J = J\n",
-    "\n",
-    "    def _initialize_K(self, K, sg=None, H2S=None, CO2=None, N2=None):\n",
-    "        if K is None:\n",
-    "            self.calc_K(sg, H2S, CO2, N2)\n",
-    "        else:\n",
-    "            self.K = K\n",
-    "\n",
-    "    def _initialize_Pr(self, Pr, P=None, Ppc_corrected=None, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None,\n",
-    "                       A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n",
-    "        if Pr is None:\n",
-    "            self.calc_Pr(P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n",
-    "                         Tpc_corrected=Tpc_corrected, A=A, B=B, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n",
-    "        else:\n",
-    "            self.Pr = Pr\n",
-    "\n",
-    "    def _initialize_Tr(self, Tr, T, Tpc_corrected=None, sg=None, Tpc=None, e_correction=None, A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n",
-    "        if Tr is None:\n",
-    "            self.calc_Tr(T, Tpc_corrected, sg, Tpc, e_correction, A, B, H2S, CO2, N2, J, K)\n",
-    "        else:\n",
-    "            self.Tr = Tr\n",
-    "\n",
-    "    def _initialize_A(self, A, H2S=None, CO2=None):\n",
-    "        if A is None:\n",
-    "            self.calc_A(H2S, CO2)\n",
-    "        else:\n",
-    "            self.A = A\n",
-    "\n",
-    "    def _initialize_B(self, B, H2S=None):\n",
-    "        if B is None:\n",
-    "            self.calc_B(H2S)\n",
-    "        else:\n",
-    "            self.B = B\n",
-    "\n",
-    "    def _check_missing_P(self, P):\n",
-    "        if P is None:\n",
-    "            raise TypeError(\"Missing a required argument, 'P' (gas pressure, psia)\")\n",
-    "        self.P = P\n",
-    "\n",
-    "    def _check_missing_T(self, _T):\n",
-    "        if _T is None:\n",
-    "            raise TypeError(\"Missing a required argument, 'T' (gas temperature, °F)\")\n",
-    "        self._T = _T\n",
-    "\n",
-    "    def _check_invalid_mode(self, mode):\n",
-    "        if mode != 'Sutton' and mode != 'Piper':\n",
-    "            raise TypeError(\"Invalid optional argument, 'mode' (calculation method), input either 'Sutton', 'Piper', or None (default='Sutton')\")\n",
-    "        self.mode = mode\n",
-    "\n",
-    "    def _redundant_argument_check_Tpc_corrected(self, Tpc_corrected=None, sg=None, Tpc=None, e_correction=None, A=None, B=None, H2S=None, CO2=None):\n",
-    "        if Tpc_corrected is not None:\n",
-    "            if sg is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'Tpc_corrected' and 'sg', input only one of them\")\n",
-    "            if Tpc is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'Tpc_corrected' and 'Tpc', input only one of them\")\n",
-    "            if H2S is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'Tpc_corrected' and 'H2S', input only one of them\")\n",
-    "            if CO2 is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'Tpc_corrected' and 'CO2', input only one of them\")\n",
-    "            if A is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'Tpc_corrected' and 'A', input only one of them\")\n",
-    "            if B is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'Tpc_corrected' and 'B', input only one of them\")\n",
-    "            if e_correction is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'Tpc_corrected' and 'e_correction', input only one of them\")\n",
-    "\n",
-    "    def _redundant_argument_check_Ppc_corrected(self, Ppc_corrected=None, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None, A=None, B=None, H2S=None, CO2=None):\n",
-    "        if Ppc_corrected is not None:\n",
-    "            if Ppc is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'Ppc_corrected' and 'Ppc', input only one of them\")\n",
-    "            if Tpc_corrected is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'Ppc_corrected' and 'Tpc_corrected', input only one of them\")\n",
-    "            self._redundant_argument_check_Tpc_corrected(sg=sg, Tpc=Tpc, H2S=H2S, CO2=CO2, A=A, B=B, e_correction=e_correction)\n",
-    "\n",
-    "    def _redundant_argument_check_J_or_K(self, sg=None, J=None, K=None, H2S=None, CO2=None, N2=None):\n",
-    "        if J is not None:\n",
-    "            if sg is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'J' and 'sg', input only one of them\")\n",
-    "            if H2S is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'J' and 'H2S', input only one of them\")\n",
-    "            if CO2 is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'J' and 'CO2', input only one of them\")\n",
-    "            if N2 is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'J' and 'N2', input only one of them\")\n",
-    "        if K is not None:\n",
-    "            if sg is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'K' and 'sg', input only one of them\")\n",
-    "            if H2S is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'K' and 'H2S', input only one of them\")\n",
-    "            if CO2 is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'K' and 'CO2', input only one of them\")\n",
-    "            if N2 is not None:\n",
-    "                raise TypeError(\"Redundant arguments 'K' and 'N2', input only one of them\")\n",
-    "\n",
-    "    def _redundant_argument_check_Tpc(self, Tpc=None, sg=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n",
-    "        if self.mode == 'Piper':\n",
-    "            if Tpc is not None:\n",
-    "                if sg is not None:\n",
-    "                    raise TypeError(\"Redundant arguments 'Tpc' and 'sg', input only one of them\")\n",
-    "                if J is not None and self._calc_from != 'calc_z':\n",
-    "                    raise TypeError(\"Redundant arguments 'Tpc' and 'J', input only one of them\")\n",
-    "                if K is not None:\n",
-    "                    raise TypeError(\"Redundant arguments 'Tpc' and 'K', input only one of them\")\n",
-    "                self._redundant_argument_check_J_or_K(J=J, K=K, H2S=H2S, CO2=CO2, N2=N2)\n",
-    "\n",
-    "    def _redundant_argument_check_Ppc(self, Ppc=None, Tpc=None, sg=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n",
-    "        if self.mode == 'Piper':\n",
-    "            if Ppc is not None:\n",
-    "                if Tpc is not None and self._calc_from != 'calc_z':\n",
-    "                    raise TypeError(\"Redundant arguments 'Ppc' and 'Tpc', input only one of them\")\n",
-    "                if sg is not None:\n",
-    "                    raise TypeError(\"Redundant arguments 'Ppc' and 'sg', input only one of them\")\n",
-    "                if J is not None:\n",
-    "                    raise TypeError(\"Redundant arguments 'Ppc' and 'J', input only one of them\")\n",
-    "                if K is not None:\n",
-    "                    raise TypeError(\"Redundant arguments 'Ppc' and 'K', input only one of them\")\n",
-    "                if H2S is not None:\n",
-    "                    raise TypeError(\"Redundant arguments 'Ppc' and 'H2S', input only one of them\")\n",
-    "                if CO2 is not None:\n",
-    "                    raise TypeError(\"Redundant arguments 'Ppc' and 'CO2', input only one of them\")\n",
-    "                if N2 is not None:\n",
-    "                    raise TypeError(\"Redundant arguments 'Ppc' and 'N2', input only one of them\")\n",
-    "\n",
-    "    def quickstart(self):\n",
-    "\n",
-    "        xmax = 8\n",
-    "        Prs = np.linspace(0, xmax, xmax * 10 + 1)\n",
-    "        Prs = np.array([round(Pr, 1) for Pr in Prs])\n",
-    "\n",
-    "        Trs = np.array([1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0])\n",
-    "\n",
-    "        results = {Tr: {\n",
-    "            'Pr': np.array([]),\n",
-    "            'Z': np.array([])\n",
-    "        } for Tr in Trs}\n",
-    "\n",
-    "        for Tr in Trs:\n",
-    "            for Pr in Prs:\n",
-    "                z_obj = zfactor()\n",
-    "                z = z_obj.calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "                results[Tr]['Z'] = np.append(results[Tr]['Z'], [z], axis=0)\n",
-    "                results[Tr]['Pr'] = np.append(results[Tr]['Pr'], [Pr], axis=0)\n",
-    "\n",
-    "        label_fontsize = 12\n",
-    "\n",
-    "        fig, ax = plt.subplots(figsize=(8, 5))\n",
-    "        for Tr in Trs:\n",
-    "\n",
-    "            Zs = results[Tr]['Z']\n",
-    "            idx_min = np.where(Zs == min(Zs))\n",
-    "\n",
-    "            p = ax.plot(Prs, Zs)\n",
-    "            if Tr == 1.05:\n",
-    "                t = ax.text(Prs[idx_min] - 0.5, min(Zs) - 0.005, '$T_{r}$ = 1.2', color=p[0].get_color())\n",
-    "                t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "            else:\n",
-    "                t = ax.text(Prs[idx_min] - 0.2, min(Zs) - 0.005, Tr, color=p[0].get_color())\n",
-    "                t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "\n",
-    "        ax.set_xlim(0, xmax)\n",
-    "        ax.minorticks_on()\n",
-    "        ax.grid(alpha=0.5)\n",
-    "        ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "        ax.spines.top.set_visible(False)\n",
-    "        ax.spines.right.set_visible(False)\n",
-    "\n",
-    "        ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "        ax.set_xlabel('Pseudo-Reduced Pressure, $P_{r}$', fontsize=label_fontsize)\n",
-    "        ax.text(0.57, 0.08, '$T_{r}$ = Pseudo-Reduced Temperature', fontsize=11, transform=ax.transAxes,\n",
-    "                bbox=dict(facecolor='white'))\n",
-    "\n",
-    "        def setbold(txt):\n",
-    "            return ' '.join([r\"$\\bf{\" + item + \"}$\" for item in txt.split(' ')])\n",
-    "\n",
-    "        ax.set_title(setbold('Real Gas Law Compressibility Factor - Z') + \", computed with GasCompressiblityFactor-py \",\n",
-    "                     fontsize=12, pad=10, x=0.445, y=1.06)\n",
-    "        ax.annotate('', xy=(-0.09, 1.05), xycoords='axes fraction', xytext=(1.05, 1.05),\n",
-    "                    arrowprops=dict(arrowstyle=\"-\", color='k'))\n",
-    "\n",
-    "        fig.tight_layout()\n",
-    "\n",
-    "        return results, fig, ax\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "efd77e30",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5483056093175225"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> import gascompressibility as gascomp\n",
-    ">>> gascomp.Piper().calc_Tr(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1, T=75)  # Temperature [F], Pressure [psia]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "7ebb29fb",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.8093081653980262"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Piper().calc_z(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1, T=75, P=2010)  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "98c5498f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5483056093175225"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Piper().calc_Tr(sg=0.7, CO2=0.1, N2=0.1, H2S=0.07, T=75)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "095ae35b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "736.2063636196116"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Piper().calc_Ppc(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "141589ac",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a6e3a3b6",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1c90f3a8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "43f74e70",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2864d67a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3b50d7a8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "id": "03828f6a",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z             = 0.77    [dimensionless]\n",
-      "Tpc           = 377.59  [°R]\n",
-      "Ppc           = 663.29  [psia]\n",
-      "e_correction  = 21.28   [°R]\n",
-      "Tpc_corrected = 356.31  [°R]\n",
-      "Ppc_corrected = 628.21  [psia]\n",
-      "Tr            = 1.5     [dimensionless]\n",
-      "Pr            = 3.2     [dimensionless]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    " \n",
-    "instance = gascomp.Sutton() \n",
-    "\n",
-    "z = instance.calc_z(sg=0.7, CO2=0.1, H2S=0.07, T=75, P=2010)   # Input: T[°F], P[psig]\n",
-    "\n",
-    "print('Z             =', round(instance.Z, 2), '   [dimensionless]')\n",
-    "print('Tpc           =', round(instance.Tpc, 2), ' [°R]')\n",
-    "print('Ppc           =', round(instance.Ppc, 2), ' [psia]')\n",
-    "print('e_correction  =', round(instance.e_correction, 2), '  [°R]')\n",
-    "print('Tpc_corrected =', round(instance.Tpc_corrected, 2), ' [°R]')\n",
-    "print('Ppc_corrected =', round(instance.Ppc_corrected, 2), ' [psia]')\n",
-    "print('Tr            =', round(instance.Tr, 2), '    [dimensionless]')\n",
-    "print('Pr            =', round(instance.Pr, 2), '    [dimensionless]')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "id": "a61f1db0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7730732979666094"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_z(sg=0.7, CO2=0.1, H2S=0.07, P=2010, T=75)  # Input: T[°F],  P[psig]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "id": "a9353b10",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "377.59"
-      ]
-     },
-     "execution_count": 35,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_Tpc(sg=0.7) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "id": "294a50d2",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "663.2869999999999"
-      ]
-     },
-     "execution_count": 36,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_Ppc(sg=0.7) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "id": "6b5d6927",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "21.277806029218723"
-      ]
-     },
-     "execution_count": 37,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_e_correction(CO2=0.1, H2S=0.07) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "id": "37a2b747",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "356.31219397078127"
-      ]
-     },
-     "execution_count": 40,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_Tpc_corrected(sg=0.7, CO2=0.1, H2S=0.07)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "id": "7ef4f6d0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "628.2143047814683"
-      ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_Ppc_corrected(sg=0.7, CO2=0.1, H2S=0.07) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "id": "e1ec3563",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5005661019949397"
-      ]
-     },
-     "execution_count": 43,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_Tr(sg=0.7, CO2=0.1, H2S=0.07, T=75)  # Input: T[°F]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "id": "43408361",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "3.1995450990234966"
-      ]
-     },
-     "execution_count": 45,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_Pr(sg=0.7, CO2=0.1, H2S=0.07, P=2010)  # Input: P[psia]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1e5b3edb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1c13ca1c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "id": "f4eeaf3b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z   = 0.81    [dimensionless]\n",
-      "J   = 0.47    [°R/psia]\n",
-      "K   = 12.73   [°R/psia^0.5]\n",
-      "Ppc = 736.21  [psia]\n",
-      "Tpc = 345.33  [°R]\n",
-      "Pr  = 2.73    [dimensionless]\n",
-      "Tr  = 1.55    [dimensionless]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    " \n",
-    "instance = gascomp.Piper() \n",
-    "\n",
-    "z = instance.calc_z(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1, T=75, P=2010)   # Input: T[°F], P[psig]\n",
-    "\n",
-    "print('Z   =', round(instance.Z, 2), '   [dimensionless]')\n",
-    "print('J   =', round(instance.J, 2), '   [°R/psia]')\n",
-    "print('K   =', round(instance.K, 2), '  [°R/psia^0.5]')\n",
-    "print('Ppc =', round(instance.Ppc, 2), ' [psia]')\n",
-    "print('Tpc =', round(instance.Tpc, 2), ' [°R]')\n",
-    "print('Pr  =', round(instance.Pr, 2), '   [dimensionless]')\n",
-    "print('Tr  =', round(instance.Tr, 2), '   [dimensionless]')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "65abaf00",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b3935a3e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f5b18791",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6bdc3b82",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e11ca904",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3bea0059",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "58cb5edb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "instance"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "14279d9b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z             = 0.8093081653980262\n",
-      "K             = 12.727096764135345\n",
-      "J             = 0.4690612564250918\n",
-      "Ppc           = 736.2063636196116\n",
-      "Tpc           = 345.325881907563\n",
-      "Pr            = 2.730212749204843\n",
-      "Tr            = 1.5483056093175225\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    " \n",
-    "instance = gascomp.Piper() \n",
-    "\n",
-    "z = instance.calc_z(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1, T=75, P=2010)\n",
-    "\n",
-    "print('Z             =', instance.Z)\n",
-    "print('K             =', instance.K)\n",
-    "print('J             =', instance.J)\n",
-    "print('Ppc           =', instance.Ppc)\n",
-    "print('Tpc           =', instance.Tpc)\n",
-    "print('Pr            =', instance.Pr)\n",
-    "print('Tr            =', instance.Tr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "43f6556b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "815d57ab",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a9382c28",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 99,
-   "id": "0222d4f3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418404080772932"
-      ]
-     },
-     "execution_count": 99,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "z_obj = gascomp.zfactor('Piper')\n",
-    "z_obj.calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1, N2=0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 114,
-   "id": "12163681",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.9876949628524373"
-      ]
-     },
-     "execution_count": 114,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "z_obj = gascomp.zfactor('Piper')\n",
-    "z_obj.calc_z(P=14.65, T=60, sg=2.025, H2S=0.07, N2=16.322/100)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dc5bd7e6",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8599a7c3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c1b08ad3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 100,
-   "id": "9550347c",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "747.9468127207383\n",
-      "373.6152741511213\n",
-      "0.4995211795770008\n",
-      "13.661213066633309\n",
-      "1.431071042838936\n",
-      "2.687356862566745\n",
-      "0.7418404080772932\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(z_obj.Ppc)\n",
-    "print(z_obj.Tpc)\n",
-    "print(z_obj.J)\n",
-    "print(z_obj.K)\n",
-    "print(z_obj.Tr)\n",
-    "print(z_obj.Pr)\n",
-    "print(z_obj.Z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 101,
-   "id": "e266ecfb",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "unexpected keyword argument 'Tpc'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_19280\\3570772943.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mz1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mz2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m663.28\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m377.59\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mz6\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPr\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m3.1995\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTr\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1.5005\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36mcalc_z\u001b[1;34m(self, guess, sg, P, T, Tpc, Ppc, Tpc_corrected, Ppc_corrected, A, B, H2S, CO2, N2, J, K, Tr, Pr, e_correction, **kwargs)\u001b[0m\n\u001b[0;32m    264\u001b[0m                A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None, Tr=None, Pr=None, e_correction=None, **kwargs):\n\u001b[0;32m    265\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_from\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'Z'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 266\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Pr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    267\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Tr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    268\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mZ\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moptimize\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnewton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_z\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mguess\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36m_initialize_Pr\u001b[1;34m(self, Pr, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    365\u001b[0m                        A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n\u001b[0;32m    366\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mPr\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 367\u001b[1;33m             self.calc_Pr(P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n\u001b[0m\u001b[0;32m    368\u001b[0m                          Tpc_corrected=Tpc_corrected, A=A, B=B, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n\u001b[0;32m    369\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36mcalc_Pr\u001b[1;34m(self, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    214\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    215\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m  \u001b[1;31m# mode == 'Piper'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 216\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_redundant_argument_check_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    217\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    218\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36m_redundant_argument_check_Ppc\u001b[1;34m(self, Ppc, Tpc, sg, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    463\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mPpc\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    464\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mTpc\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 465\u001b[1;33m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"unexpected keyword argument 'Tpc'\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    466\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0msg\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    467\u001b[0m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Redundant arguments 'Ppc' and 'sg', input only one of them\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: unexpected keyword argument 'Tpc'"
-     ]
-    }
-   ],
-   "source": [
-    "z1 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1, N2=0)\n",
-    "\n",
-    "z2 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59)\n",
-    "\n",
-    "z6 = gascomp.zfactor('Piper').calc_z(Pr=3.1995, Tr=1.5005)\n",
-    "\n",
-    "print(z1)\n",
-    "print(z2)\n",
-    "print(z3)\n",
-    "print(z4)\n",
-    "print(z5)\n",
-    "print(z6)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1692f065",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "id": "ebb5d079",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418404080772932"
-      ]
-     },
-     "execution_count": 55,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "gascomp.zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e192b0c3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "id": "83030eee",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "unexpected keyword argument 'Tpc'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
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-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36mcalc_z\u001b[1;34m(self, guess, sg, P, T, Tpc, Ppc, Tpc_corrected, Ppc_corrected, A, B, H2S, CO2, N2, J, K, Tr, Pr, e_correction, **kwargs)\u001b[0m\n\u001b[0;32m    264\u001b[0m                A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None, Tr=None, Pr=None, e_correction=None, **kwargs):\n\u001b[0;32m    265\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_from\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'Z'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 266\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Pr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    267\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Tr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    268\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mZ\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moptimize\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnewton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_z\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mguess\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36m_initialize_Pr\u001b[1;34m(self, Pr, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    365\u001b[0m                        A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n\u001b[0;32m    366\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mPr\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 367\u001b[1;33m             self.calc_Pr(P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n\u001b[0m\u001b[0;32m    368\u001b[0m                          Tpc_corrected=Tpc_corrected, A=A, B=B, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n\u001b[0;32m    369\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36mcalc_Pr\u001b[1;34m(self, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    214\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    215\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m  \u001b[1;31m# mode == 'Piper'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 216\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_redundant_argument_check_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    217\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    218\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36m_redundant_argument_check_Ppc\u001b[1;34m(self, Ppc, Tpc, sg, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    463\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mPpc\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    464\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mTpc\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 465\u001b[1;33m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"unexpected keyword argument 'Tpc'\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    466\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0msg\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    467\u001b[0m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Redundant arguments 'Ppc' and 'sg', input only one of them\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: unexpected keyword argument 'Tpc'"
-     ]
-    }
-   ],
-   "source": [
-    "z1 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)\n",
-    "z2 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59, H2S=0.07, CO2=0.1)\n",
-    "z3 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59, e_correction=21.27, H2S=0.07)\n",
-    "z4 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc_corrected=628.2, Tpc=377.59, e_correction=21.27)\n",
-    "z5 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc_corrected=628.2, Tpc_corrected=356.3)\n",
-    "z6 = gascomp.zfactor('Piper').calc_z(Pr=3.1995, Tr=1.5005)\n",
-    "\n",
-    "print(z1)\n",
-    "print(z2)\n",
-    "print(z3)\n",
-    "print(z4)\n",
-    "print(z5)\n",
-    "print(z6)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "64a99b6a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c0cf287b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "69d0cc11",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "id": "a248bc16",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z             = 0.7730732979666094\n",
-      "Ppc           = 663.2869999999999\n",
-      "Tpc           = 377.59\n",
-      "e_correction  = 21.277806029218723\n",
-      "Ppc_corrected = 628.2143047814683\n",
-      "Tpc_corrected = 356.31219397078127\n",
-      "Pr            = 3.1995450990234966\n",
-      "Tr            = 1.5005661019949397\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    " \n",
-    "z_obj = gascomp.zfactor()  # default mode = 'Sutton'\n",
-    "\n",
-    "Z = z_obj.calc_z(sg=0.7, P=2010, T=75, H2S=0.07, CO2=0.1)\n",
-    "\n",
-    "print('Z             =', z_obj.Z)\n",
-    "print('Ppc           =', z_obj.Ppc)\n",
-    "print('Tpc           =', z_obj.Tpc)\n",
-    "print('e_correction  =', z_obj.e_correction)\n",
-    "print('Ppc_corrected =', z_obj.Ppc_corrected)\n",
-    "print('Tpc_corrected =', z_obj.Tpc_corrected)\n",
-    "print('Pr            =', z_obj.Pr)\n",
-    "print('Tr            =', z_obj.Tr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "163c1a7e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3bc5e29f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a6bc9ce4",
-   "metadata": {},
-   "source": [
-    "# Testing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "id": "ff556fe7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "exec('z1 = gascomp.zfactor().calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "id": "0ba26033",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "P = 'P=2010, '\n",
-    "T = 'T=75, '\n",
-    "sg = 'sg=0.7, '\n",
-    "H2S = 'H2S=0.07, '\n",
-    "CO2 = 'CO2=0.1, '\n",
-    "N2 = 'N2=0, '\n",
-    "Ppc = 'Ppc=663.28, '\n",
-    "Tpc = 'Tpc=377.59, '\n",
-    "e_correction = 'e_correction=21.277, '\n",
-    "Ppc_corrected = 'Ppc_corrected=628.21, '\n",
-    "Tpc_corrected = 'Tpc_corrected=356.31, '\n",
-    "Pr = 'Pr=3.1995, '\n",
-    "Tr = 'Tr=1.5005, '"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 94,
-   "id": "329fa122",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "63\n"
-     ]
-    }
-   ],
-   "source": [
-    "import itertools\n",
-    "\n",
-    "lst = [P, T, sg]\n",
-    "lst = [P, T, sg, H2S, Ppc, Tpc]\n",
-    "#lst = [P, T, sg, H2S, CO2, N2, Ppc, Tpc, e_correction, Ppc_corrected, Tpc_corrected, Pr, Tr]\n",
-    "combs = []\n",
-    "\n",
-    "for i in range(1, len(lst)+1):\n",
-    "    els = [list(x) for x in itertools.combinations(lst, i)]\n",
-    "    combs.extend(els)\n",
-    "\n",
-    "s = []\n",
-    "for item in combs:\n",
-    "    c = ''.join(b for b in item).strip(', ')\n",
-    "    s.append(c)\n",
-    "print(len(s))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "982fcad9",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f57dfdd8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "98eca72e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5e2c6a10",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "45789247",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a300cd1c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d385e871",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "961aad98",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "057b4c5f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4bbb1b3a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f3e17715",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "77e41c66",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "460dbd67",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "id": "b37ed94f",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.7730732979666094\n",
-      "0.7730728821497411\n",
-      "0.7730546405630305\n",
-      "0.7730533493089499\n",
-      "0.7731021601171872\n",
-      "0.7730355427956694\n"
-     ]
-    }
-   ],
-   "source": [
-    "z1 = gascomp.zfactor().calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)\n",
-    "z2 = gascomp.zfactor().calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59, H2S=0.07, CO2=0.1)\n",
-    "z3 = gascomp.zfactor().calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59, e_correction=21.27, H2S=0.07)\n",
-    "z4 = gascomp.zfactor().calc_z(P=2010, T=75, Ppc_corrected=628.2, Tpc=377.59, e_correction=21.27)\n",
-    "z5 = gascomp.zfactor().calc_z(P=2010, T=75, Ppc_corrected=628.2, Tpc_corrected=356.3)\n",
-    "z6 = gascomp.zfactor().calc_z(Pr=3.1995, Tr=1.5005)\n",
-    "\n",
-    "print(z1)\n",
-    "print(z2)\n",
-    "print(z3)\n",
-    "print(z4)\n",
-    "print(z5)\n",
-    "print(z6)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a965c0b1",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "id": "f39c04c0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "z_obj = gascomp.zfactor()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "id": "931892c0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7730732979666094"
-      ]
-     },
-     "execution_count": 47,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "z_obj.calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "08131cb6",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "663.2869999999999\n",
-      "377.59\n",
-      "628.2143047814683\n",
-      "356.31219397078127\n",
-      "21.277806029218723\n",
-      "1.5005661019949397\n",
-      "3.1995450990234966\n",
-      "0.7730732979666094\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(z_obj.Ppc)\n",
-    "print(z_obj.Tpc)\n",
-    "print(z_obj.Ppc_corrected)\n",
-    "print(z_obj.Tpc_corrected)\n",
-    "print(z_obj.e_correction)\n",
-    "print(z_obj.Tr)\n",
-    "print(z_obj.Pr)\n",
-    "print(z_obj.Z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f5fa4f58",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2e74b902",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c964f61d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8de2403a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "1579c0c5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import gascompressibility as gascomp\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "f93bee0b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.851143760811577\n"
-     ]
-    }
-   ],
-   "source": [
-    "z = gascomp.zfactor().calc_z(Tr=1.5, Pr=1.6)\n",
-    "print(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "8df74f4e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.851143760811577"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "Z"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "00478641",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "id": "cdc31fcc",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "------------------------------------------------\n",
-      "Z = 0.77\n",
-      "Ppc = 663.3\n",
-      "Tpc = 377.6\n",
-      "e_correction = 21.28\n",
-      "Ppc_corrected = 628.21\n",
-      "Tpc_corrected = 628.21\n",
-      "Pr = 3.2\n",
-      "Tr = 1.5\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    "\n",
-    "# default mode = 'Sutton'\n",
-    "z_obj = zfactor()\n",
-    "\n",
-    "Z = z_obj.calc_z(sg=0.7, P=2010, T=75, H2S=0.07, CO2=0.1)\n",
-    "\n",
-    "print('------------------------------------------------')\n",
-    "print('Z =', round(Z, 2))\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5058371c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "f9a333f8",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z             = 0.7730732979666094\n",
-      "Ppc           = 663.2869999999999\n",
-      "Tpc           = 377.59\n",
-      "e_correction  = 21.277806029218723\n",
-      "Ppc_corrected = 628.2143047814683\n",
-      "Tpc_corrected = 628.2143047814683\n",
-      "Pr            = 3.1995450990234966\n",
-      "Tr            = 1.5005661019949397\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('Z             =', z_obj.Z)\n",
-    "print('Ppc           =', z_obj.Ppc)\n",
-    "print('Tpc           =', z_obj.Tpc)\n",
-    "print('e_correction  =', z_obj.e_correction)\n",
-    "print('Ppc_corrected =', z_obj.Ppc_corrected)\n",
-    "print('Tpc_corrected =', z_obj.Ppc_corrected)\n",
-    "print('Pr            =', z_obj.Pr)\n",
-    "print('Tr            =', z_obj.Tr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2a4ce67e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6e8c775d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1f712b14",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "id": "92d2196a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<GasCompressibilityFactor object. Mixing Rule = Sutton>"
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "z_obj"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dfdd649b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "c7638c18",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 800x500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    "\n",
-    "results, fig, ax = gascomp.zfactor().quickstart()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "fbf1bee0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fig.savefig('z-correlation chart.png', dpi=200)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "962835b9",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b39cd3fb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "30be94dc",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fbefdc7b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a0e93cbf",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 175,
-   "id": "e05ef300",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418815034924504"
-      ]
-     },
-     "execution_count": 175,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, Tpc=373.6, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2c7bf352",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1cf485fb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "aec6eef9",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e2022094",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8a293081",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 148,
-   "id": "7098fc8e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7370643378633674"
-      ]
-     },
-     "execution_count": 148,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(T=75, sg=0.7, P=2010)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "3d3ac8bf",
-   "metadata": {},
-   "source": [
-    "## Test J"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 149,
-   "id": "852a1ccd",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.4995211795770008"
-      ]
-     },
-     "execution_count": 149,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_J(sg=0.7, H2S=0.07, CO2=0.1, N2=0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 150,
-   "id": "04e6bb40",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.4690612564250918"
-      ]
-     },
-     "execution_count": 150,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_J(sg=0.7, H2S=0.07, CO2=0.1, N2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 151,
-   "id": "9c599605",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.56221847"
-      ]
-     },
-     "execution_count": 151,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_J(sg=0.7)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d38c5008",
-   "metadata": {},
-   "source": [
-    "## Test K"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 152,
-   "id": "81954a0a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "13.661213066633309"
-      ]
-     },
-     "execution_count": 152,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_K(sg=0.7, H2S=0.07, CO2=0.1, N2=0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 153,
-   "id": "b87ba767",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "12.727096764135345"
-      ]
-     },
-     "execution_count": 153,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_K(sg=0.7, H2S=0.07, CO2=0.1, N2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 154,
-   "id": "707deebd",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "14.450840999999999"
-      ]
-     },
-     "execution_count": 154,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_K(sg=0.7)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4ca78b75",
-   "metadata": {},
-   "source": [
-    "## Test Tpc"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 155,
-   "id": "fde0685d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "373.61946146146147"
-      ]
-     },
-     "execution_count": 155,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tpc(K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 156,
-   "id": "33260f25",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "373.6152741511213"
-      ]
-     },
-     "execution_count": 156,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tpc(sg=0.7, H2S=0.07, CO2=0.1, N2=0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 157,
-   "id": "6cd4068e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "232.7950339652756"
-      ]
-     },
-     "execution_count": 157,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tpc(sg=0.7, H2S=0.07, CO2=0.1, N2=0.5)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "5268f25c",
-   "metadata": {},
-   "source": [
-    "## Test Ppc"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 158,
-   "id": "00e85949",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "747.947947947948"
-      ]
-     },
-     "execution_count": 158,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Ppc(Tpc=373.6, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 159,
-   "id": "7c50c900",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "747.9869098327557"
-      ]
-     },
-     "execution_count": 159,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Ppc(K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 160,
-   "id": "29c1f62f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "747.9468127207383"
-      ]
-     },
-     "execution_count": 160,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Ppc(sg=0.7, CO2=0.1, H2S=0.07)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "34312d52",
-   "metadata": {},
-   "source": [
-    "## Test Pr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 161,
-   "id": "9cda42df",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2.687466731664271"
-      ]
-     },
-     "execution_count": 161,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(Tpc=373.6, sg=0.7, P=2010, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 162,
-   "id": "8a7367a5",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2.6875250701965503"
-      ]
-     },
-     "execution_count": 162,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(Ppc=747.9, P=2010)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 163,
-   "id": "633d61d6",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "502.5"
-      ]
-     },
-     "execution_count": 163,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(P=2010, K=4, J=2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 164,
-   "id": "5ffef93d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "3.8686451504335713"
-      ]
-     },
-     "execution_count": 164,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(P=2010, sg=2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 165,
-   "id": "bf1eb299",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2.6873527837259097"
-      ]
-     },
-     "execution_count": 165,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(P=2010, Tpc=373.6, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "43e95e28",
-   "metadata": {},
-   "source": [
-    "## Test Tr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 166,
-   "id": "2794b835",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.431071042838936"
-      ]
-     },
-     "execution_count": 166,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tr(T=75, sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 167,
-   "id": "09c1dd2a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.431055004224267"
-      ]
-     },
-     "execution_count": 167,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tr(T=75, K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 168,
-   "id": "a4827b41",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.4311295503211992"
-      ]
-     },
-     "execution_count": 168,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tr(T=75, Tpc=373.6)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1e9b2373",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a8a72002",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5b4d8907",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "85b0b136",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "id": "fb0a4111",
-   "metadata": {},
-   "source": [
-    "## Test Z"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 193,
-   "id": "8da18f52",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.8093081653980262"
-      ]
-     },
-     "execution_count": 193,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1, N2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 192,
-   "id": "4c4292df",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418404080772932"
-      ]
-     },
-     "execution_count": 192,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 177,
-   "id": "0413bdbe",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418351281782508"
-      ]
-     },
-     "execution_count": 177,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 178,
-   "id": "712ed349",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418815034924504"
-      ]
-     },
-     "execution_count": 178,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, Tpc=373.6, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 189,
-   "id": "44fa2270",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418439061899736"
-      ]
-     },
-     "execution_count": 189,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, Pr=2.687, K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b78e5043",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b0ca8381",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 122,
-   "id": "e90619b4",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2.687356862566745\n",
-      "1.431071042838936\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.Pr)\n",
-    "print(aa.Tr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "baf6ed8d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "430d0425",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 98,
-   "id": "5d82cedd",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "13.661213066633309"
-      ]
-     },
-     "execution_count": 98,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "3.8216 \\\n",
-    "                 - 0.06534 * H2S * (Tc_H2S / np.sqrt(Pc_H2S)) \\\n",
-    "                 - 0.42113 * CO2 * (Tc_CO2 / np.sqrt(Pc_CO2)) \\\n",
-    "                 - 0.91249 * N2 * (Tc_N2 / np.sqrt(Pc_N2)) \\\n",
-    "                 + 17.438 * sg \\\n",
-    "                 - 3.2191 * sg ** 2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 97,
-   "id": "e927eba8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5773589999999997"
-      ]
-     },
-     "execution_count": 97,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "3.2191 * sg ** 2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e4a7e13e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 70,
-   "id": "5a022f5e",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0\n",
-      "0.1\n",
-      "0.07\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.N2)\n",
-    "print(aa.CO2)\n",
-    "print(aa.H2S)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 65,
-   "id": "31db8d16",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "-9.986241845719988"
-      ]
-     },
-     "execution_count": 65,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.K"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 66,
-   "id": "6f90326b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "-0.4906848204229992"
-      ]
-     },
-     "execution_count": 66,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.J"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 67,
-   "id": "03d548f1",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7"
-      ]
-     },
-     "execution_count": 67,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.sg"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 68,
-   "id": "206decfd",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "672.3\n",
-      "1306\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.Tc_H2S)\n",
-    "print(aa.Pc_H2S)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 69,
-   "id": "4dafdb38",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "547.5\n",
-      "1071\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.Tc_CO2)\n",
-    "print(aa.Pc_CO2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "id": "817b49dd",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "227.16\n",
-      "492.4\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.Tc_N2)\n",
-    "print(aa.Pc_N2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ae77786d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a1091b34",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a8bffbf8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 439,
-   "id": "b5870628",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "628.2143047814683\n",
-      "356.31219397078127\n",
-      "3.1995450990234966\n",
-      "1.5005661019949397\n",
-      "0.7730732979666094\n"
-     ]
-    }
-   ],
-   "source": [
-    "aa.calc_z(P=2010, T=75, CO2=0.1, H2S=0.07, sg=0.7)\n",
-    "print(aa.Ppc_corrected)\n",
-    "print(aa.Tpc_corrected)\n",
-    "print(aa.Pr)\n",
-    "print(aa.Tr)\n",
-    "print(aa.Z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 442,
-   "id": "77849553",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2.6875250701965503\n",
-      "1.4311295503211992\n",
-      "0.7418744010634963\n"
-     ]
-    }
-   ],
-   "source": [
-    "aa.calc_z(P=2010, T=75, Ppc=747.9, Tpc=373.6)\n",
-    "print(aa.Pr)\n",
-    "print(aa.Tr)\n",
-    "print(aa.Z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8977cb87",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f5023ab8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 422,
-   "id": "3925debc",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "Missing a required argument, H2S, (mole fraction of H2S, dimensionless)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_28080\\2424930199.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0maa\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Pr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m663.29\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m377.59\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m21.278\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_28080\\3062684313.py\u001b[0m in \u001b[0;36mcalc_Pr\u001b[1;34m(self, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2)\u001b[0m\n\u001b[0;32m    159\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    160\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_P\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 161\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Ppc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    162\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    163\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_28080\\3062684313.py\u001b[0m in \u001b[0;36m_initialize_Ppc_corrected\u001b[1;34m(self, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2)\u001b[0m\n\u001b[0;32m    265\u001b[0m                                   Tpc_corrected=None, A=None, B=None, H2S=None, CO2=None):\n\u001b[0;32m    266\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mPpc_corrected\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 267\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Ppc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    268\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    269\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_28080\\3062684313.py\u001b[0m in \u001b[0;36mcalc_Ppc_corrected\u001b[1;34m(self, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2)\u001b[0m\n\u001b[0;32m    107\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0me_correction\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    108\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mB\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mH2S\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 109\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Missing a required argument, H2S, (mole fraction of H2S, dimensionless)\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    110\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    111\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: Missing a required argument, H2S, (mole fraction of H2S, dimensionless)"
-     ]
-    }
-   ],
-   "source": [
-    "aa.calc_Pr(Ppc=663.29, Tpc=377.59, P=2010, e_correction=21.278)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5611e722",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "37b247c3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 365,
-   "id": "3037b714",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "377.59"
-      ]
-     },
-     "execution_count": 365,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.Tpc"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 375,
-   "id": "3084b6e3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5005753416968373"
-      ]
-     },
-     "execution_count": 375,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Tr(sg=0.7, T=75, Tpc_corrected=356.31)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6f05b580",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 209,
-   "id": "5b021b5e",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "333333\n",
-      "0.07\n",
-      "0\n",
-      "0.07\n",
-      "44444444\n",
-      "21.278\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "628.2139838777422"
-      ]
-     },
-     "execution_count": 209,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Ppc_corrected(sg=0.7, H2S=0.07, CO2=0.1, e_correction=21.278)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 211,
-   "id": "9f32aa58",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "333333\n",
-      "0.07\n",
-      "---------\n",
-      "++++++\n",
-      "None\n",
-      "None\n",
-      "0.07\n",
-      "0.1\n",
-      "++++++\n",
-      "0.17\n",
-      "0.07\n",
-      "44444444\n",
-      "None\n",
-      "---------\n",
-      "++++++\n",
-      "None\n",
-      "None\n",
-      "0\n",
-      "0\n",
-      "++++++\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "663.2869999999999"
-      ]
-     },
-     "execution_count": 211,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Ppc_corrected(sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 198,
-   "id": "97c12aad",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.0"
-      ]
-     },
-     "execution_count": 198,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.e_correction"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 199,
-   "id": "6e83dd80",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0"
-      ]
-     },
-     "execution_count": 199,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.A"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 200,
-   "id": "aa848e3f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0"
-      ]
-     },
-     "execution_count": 200,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.B"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9c9f129c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f18ef30e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a1149e70",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8ddf4049",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 129,
-   "id": "3e7ee309",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "364.3662538443467"
-      ]
-     },
-     "execution_count": 129,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Ppc_corrected(sg=0.7, H2S=0.07)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 128,
-   "id": "e844e081",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "356.31199999999995"
-      ]
-     },
-     "execution_count": 128,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Tpc_corrected(sg=0.7, e_correction=21.278)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7df1eeab",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 130,
-   "id": "d4abbc9d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "356.31199999999995"
-      ]
-     },
-     "execution_count": 130,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Tpc_corrected(Tpc=377.59, e_correction=21.278)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0733811c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f40aa844",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2a298ef5",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "29ac9aac",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "90a1df02",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b2afba32",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6ff9b8e9",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "70d0e5e3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c963d4af",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d8c17f58",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1b9cdd52",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "da8535f9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 109,
-   "id": "b7f89bcf",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "xmax = 8\n",
-    "Prs = np.linspace(0, xmax, xmax * 10 + 1)\n",
-    "Trs = [1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0]\n",
-    "\n",
-    "results = {Tr: [] for Tr in Trs}\n",
-    "for Tr in Trs:\n",
-    "    for Pr in Prs:\n",
-    "        z = Z_factor().calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "        results[Tr].append(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 110,
-   "id": "6785584c",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EricKim\\AppData\\Local\\Temp\\ipykernel_12360\\954759431.py:20: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
-      "  ax.grid(b=True, which='minor', alpha=0.1)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 800x500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "label_fontsize = 12\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(8, 5))\n",
-    "for Tr in Trs:\n",
-    "    \n",
-    "    Zs = results[Tr]\n",
-    "    idx_min = Zs.index(min(Zs))\n",
-    "    \n",
-    "    p = ax.plot(Prs, Zs)\n",
-    "    if Tr == 1.05:\n",
-    "        t = ax.text(Prs[idx_min] - 0.5, min(Zs) - 0.005, '$T_{r}$ = 1.2', color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))       \n",
-    "    else:\n",
-    "        t = ax.text(Prs[idx_min] - 0.2, min(Zs) - 0.005, Tr, color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "\n",
-    "ax.set_xlim(0, xmax)\n",
-    "ax.minorticks_on()\n",
-    "ax.grid(alpha=0.5)\n",
-    "ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "ax.spines.top.set_visible(False)\n",
-    "ax.spines.right.set_visible(False)\n",
-    "\n",
-    "ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "ax.set_xlabel('Pseudo-Reduced Pressure, $P_{r}$', fontsize=label_fontsize)\n",
-    "ax.text(0.57, 0.08, '$T_{r}$ = Pseudo-Reduced Temperature', fontsize=11, transform=ax.transAxes, bbox=dict(facecolor='white'))\n",
-    "ax.text(7.65, 0.42, 'aegis4048.github.io', fontsize=label_fontsize, ha='right', va='top', color='grey', alpha=0.5)\n",
-    "\n",
-    "def setbold(txt):\n",
-    "    return ' '.join([r\"$\\bf{\" + item + \"}$\" for item in txt.split(' ')])\n",
-    "\n",
-    "ax.set_title(setbold('Real Gas Law Compressibility Factor - Z')  + \", computed with GasCompressiblityFactor-py \", fontsize=12, pad=10, x=0.445, y=1.06)\n",
-    "ax.annotate('', xy=(-0.09, 1.05), xycoords='axes fraction', xytext=(1.05, 1.05), arrowprops=dict(arrowstyle=\"-\", color='k'))\n",
-    "\n",
-    "fig.tight_layout()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b070bffe",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cf1c6735",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4e95ea23",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c029ebef",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "21c49886",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "dd5c2d88",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 133,
-   "id": "f99c5832",
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [],
-   "source": [
-    "Prs = np.linspace(0, 8, 81)\n",
-    "Trs = [1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0]\n",
-    "\n",
-    "results = {Tr: [] for Tr in Trs}\n",
-    "for Tr in Trs:\n",
-    "    for Pr in Prs:\n",
-    "        z = Z_factor().calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "        results[Tr].append(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 134,
-   "id": "ab3fbee1",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EricKim\\AppData\\Local\\Temp\\ipykernel_13736\\1567171423.py:18: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
-      "  ax.grid(b=True, which='minor', alpha=0.1)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 700x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "label_fontsize = 12\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(7, 8))\n",
-    "for Tr in Trs:\n",
-    "    \n",
-    "    Zs = results[Tr]\n",
-    "    idx_min = Zs.index(min(Zs))\n",
-    "    \n",
-    "    p = ax.plot(Prs, Zs)\n",
-    "    ax.set_ylim(0.25, 1.1)\n",
-    "    ax.set_xlim(0, 8)\n",
-    "    \n",
-    "    t = ax.text(Prs[idx_min] - 0.2, min(Zs) - 0.005, Tr, color=p[0].get_color())\n",
-    "    t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "    \n",
-    "    ax.minorticks_on()\n",
-    "    ax.grid(alpha=0.5)\n",
-    "    ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "    \n",
-    "    ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "    ax.set_xlabel('Pseudo-Reduced Pressure, $P_{r}$', fontsize=label_fontsize)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "000f5e65",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1ac9f964",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c949bee0",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 135,
-   "id": "1ffa5b14",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Prs = np.linspace(7, 15, 81)\n",
-    "Trs = [1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0]\n",
-    "\n",
-    "results = {Tr: [] for Tr in Trs}\n",
-    "for Tr in Trs:\n",
-    "    for Pr in Prs:\n",
-    "        z = Z_factor().calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "        results[Tr].append(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 137,
-   "id": "d4270246",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EricKim\\AppData\\Local\\Temp\\ipykernel_13736\\3204600190.py:23: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
-      "  ax.grid(b=True, which='minor', alpha=0.1)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 700x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "label_fontsize = 12\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(7, 8))\n",
-    "\n",
-    "for Tr in Trs:\n",
-    "    \n",
-    "    Zs = results[Tr]\n",
-    "    idx_min = Zs.index(min(Zs))\n",
-    "    \n",
-    "    p = ax.plot(Prs, Zs)\n",
-    "    ax.set_ylim(0.9, 1.8)\n",
-    "    ax.set_xlim(7, 15)\n",
-    "\n",
-    "    if Tr == 1.2:\n",
-    "        t = ax.text(Prs[-8] - 0.5, Zs[-7], '$T_{r}$ = 1.2', color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))        \n",
-    "    else:\n",
-    "        t = ax.text(Prs[-8], Zs[-7], Tr, color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "    \n",
-    "    ax.minorticks_on()\n",
-    "    ax.grid(alpha=0.1)\n",
-    "    ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "    \n",
-    "    ax.yaxis.tick_right()\n",
-    "    \n",
-    "    ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "    ax.yaxis.set_label_position('right') \n",
-    "    ax.set_xlabel('Pseudo-Reduced Pressure, $P_{r}$', fontsize=label_fontsize)\n",
-    "    ax.spines.top.set_visible(False)\n",
-    "    \n",
-    "    ax.text(0.43, 0.08, '$T_{r}$ = Pseudo-Reduced Temperature', fontsize=11, \n",
-    "            transform=ax.transAxes, bbox=dict(facecolor='white'))\n",
-    "    \n",
-    "fig.savefig('zplot_2.png', dpi=200)"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "id": "55cc0ba5",
-   "metadata": {},
-   "source": [
-    "Prs[-2]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4898c35f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cbeb3eda",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "bafab9ab",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 129,
-   "id": "0f58a7b3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Prs = np.linspace(0, 8, 81)\n",
-    "Trs = [1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0]\n",
-    "\n",
-    "results = {Tr: [] for Tr in Trs}\n",
-    "for Tr in Trs:\n",
-    "    for Pr in Prs:\n",
-    "        z = Z_factor().calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "        results[Tr].append(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 130,
-   "id": "501b7a3c",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EricKim\\AppData\\Local\\Temp\\ipykernel_13736\\1578593572.py:22: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
-      "  ax.grid(b=True, which='minor', alpha=0.1)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 700x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "label_fontsize = 12\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(7, 8))\n",
-    "for Tr in Trs:\n",
-    "    \n",
-    "    Zs = results[Tr]\n",
-    "    idx_min = Zs.index(min(Zs))\n",
-    "    \n",
-    "    p = ax.plot(Prs, Zs)\n",
-    "    ax.set_ylim(0.25, 1.1)\n",
-    "    ax.set_xlim(0, 8)\n",
-    "    \n",
-    "    if Tr == 1.05:\n",
-    "        t = ax.text(Prs[idx_min] - 0.75, min(Zs) - 0.005, '$T_{r}$ = 1.05', color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))        \n",
-    "    else:\n",
-    "        t = ax.text(Prs[idx_min] - 0.2, min(Zs) - 0.005, Tr, color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "    \n",
-    "    ax.minorticks_on()\n",
-    "    ax.grid(alpha=0.1)\n",
-    "    ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "    \n",
-    "    #ax.invert_yaxis()\n",
-    "    ax.xaxis.tick_top()\n",
-    "\n",
-    "    ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "    ax.set_xlabel('Pseudo-reduced Pressure, $P_{r}$', fontsize=label_fontsize)\n",
-    "    ax.xaxis.set_label_position('top') \n",
-    "    \n",
-    "fig.savefig('zplot_1.png', dpi=200)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "eb85711e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6d810187",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "066cccec",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8aa591ad",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6671084b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dd836ae7",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1a0815fb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "295d521a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d4f8a96a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ebb5b2ec",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "id": "5ad79a5d",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Attributes --------------------------------------\n",
-      "A             =  0.17\n",
-      "B             =  0.07\n",
-      "e_correction  =  21.28\n",
-      "Ppc_corrected =  628.22\n",
-      "Tpc_corrected =  356.31\n",
-      "Result ------------------------------------------\n",
-      "Tpr           =  3.1995\n"
-     ]
-    }
-   ],
-   "source": [
-    "z_obj = Z_factor()\n",
-    "z_obj.calc_Pr(H2S=0.07, CO2=0.1, P=2010, Ppc=663.29, Tpc=377.59)\n",
-    "\n",
-    "print('Attributes --------------------------------------')\n",
-    "print('A             = ', z_obj.A)\n",
-    "print('B             = ', z_obj.B)\n",
-    "print('e_correction  = ', round(z_obj.e_correction, 2))\n",
-    "print('Ppc_corrected = ', round(z_obj.Ppc_corrected, 2))\n",
-    "print('Tpc_corrected = ', round(z_obj.Tpc_corrected, 2))\n",
-    "print('Result ------------------------------------------')\n",
-    "print('Tpr           = ', round(z_obj.Pr, 4))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a938f470",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3a286c2f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8da7b6be",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/tutorials/alternative calculations.ipynb b/tutorials/alternative calculations.ipynb
deleted file mode 100644
index 3425a4f..0000000
--- a/tutorials/alternative calculations.ipynb	
+++ /dev/null
@@ -1,1872 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "4e57443c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from scipy import optimize\n",
-    "import matplotlib.pyplot as plt\n",
-    "import inspect\n",
-    "\n",
-    "\n",
-    "try:\n",
-    "    from gascompressibility.utilities.utilities import calc_Fahrenheit_to_Rankine\n",
-    "except:\n",
-    "    pass\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "class Sutton:\n",
-    "    def __init__(self):\n",
-    "        self.mode = 'Sutton'\n",
-    "        self._check_invalid_mode(self.mode)  # prevent user modification of self.mode\n",
-    "\n",
-    "        self.sg = None\n",
-    "        self.T_f = None\n",
-    "        self.T = None\n",
-    "        self.P = None\n",
-    "        self.H2S = None\n",
-    "        self.CO2 = None\n",
-    "\n",
-    "        self.Tpc = None\n",
-    "        self.Ppc = None\n",
-    "        self.A = None\n",
-    "        self.B = None\n",
-    "        self.e_correction = None\n",
-    "        self.Tpc_corrected = None\n",
-    "        self.Ppc_corrected = None\n",
-    "        self.Tr = None\n",
-    "        self.Pr = None\n",
-    "\n",
-    "        self.Z = None\n",
-    "\n",
-    "        self._first_caller_name = None\n",
-    "        self._first_caller_keys = {}\n",
-    "        self._first_caller_kwargs = {}\n",
-    "        self._first_caller_is_saved = False\n",
-    "\n",
-    "    def __str__(self):\n",
-    "        return str(self.Z)\n",
-    "\n",
-    "    def __repr__(self):\n",
-    "        return '<GasCompressibilityFactor object. Mixing Rule = %s>' % self.mode\n",
-    "\n",
-    "    \"\"\"sum of the mole fractions of CO2 and H2S in a gas mixture\"\"\"\n",
-    "    def _calc_A(self, H2S=None, CO2=None):\n",
-    "        self._initialize_H2S(H2S)\n",
-    "        self._initialize_CO2(CO2)\n",
-    "        self.A = self.H2S + self.CO2\n",
-    "        return self.A\n",
-    "\n",
-    "    \"\"\"mole fraction of H2S in a gas mixture\"\"\"\n",
-    "    def _calc_B(self, H2S=None):\n",
-    "        self._initialize_H2S(H2S)\n",
-    "        self.B = self.H2S\n",
-    "        return self.B\n",
-    "\n",
-    "    \"\"\"pseudo-critical temperature (°R)\"\"\"\n",
-    "    def calc_Tpc(self, sg=None):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_sg(sg)\n",
-    "        self.Tpc = 169.2 + 349.5 * self.sg - 74.0 * self.sg ** 2\n",
-    "        return self.Tpc\n",
-    "\n",
-    "    \"\"\"pseudo-critical pressure (psi)\"\"\"\n",
-    "    def calc_Ppc(self, sg=None):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_sg(sg)\n",
-    "        self.Ppc = 756.8 - 131.07 * self.sg - 3.6 * self.sg ** 2\n",
-    "        return self.Ppc\n",
-    "\n",
-    "    \"\"\"correction for CO2 and H2S (°R)\"\"\"\n",
-    "    def calc_e_correction(self, H2S=None, CO2=None):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_A(A=None, H2S=H2S, CO2=CO2)\n",
-    "        self._initialize_B(B=None, H2S=H2S)\n",
-    "        self.e_correction = 120 * (self.A ** 0.9 - self.A ** 1.6) + 15 * (self.B ** 0.5 - self.B ** 4)\n",
-    "        return self.e_correction\n",
-    "\n",
-    "    def calc_Tpc_corrected(self, sg=None, Tpc=None, e_correction=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_Tpc(Tpc, sg=sg)\n",
-    "\n",
-    "        # Correction is not needed if no sour gas is present\n",
-    "        if e_correction is None and H2S is None and CO2 is None:\n",
-    "            self.Tpc_corrected = self.Tpc\n",
-    "            return self.Tpc_corrected\n",
-    "\n",
-    "        self._initialize_e_correction(e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self.Tpc_corrected = self.Tpc - self.e_correction\n",
-    "        return self.Tpc_corrected\n",
-    "\n",
-    "    \"\"\" corrected pseudo-critical pressure (psi)\"\"\"\n",
-    "    def calc_Ppc_corrected(self, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_Ppc(Ppc, sg=sg)\n",
-    "\n",
-    "        # Correction is not needed if no sour gas is present\n",
-    "        if e_correction is None and H2S is None and CO2 is None and Tpc is None and Tpc_corrected is None:\n",
-    "            self.Ppc_corrected = self.Ppc\n",
-    "            return self.Ppc_corrected\n",
-    "\n",
-    "        self._initialize_Tpc(Tpc, sg=sg)\n",
-    "        self._initialize_B(B=None, H2S=H2S)\n",
-    "        self._initialize_e_correction(e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self._initialize_Tpc_corrected(Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self.Ppc_corrected = (self.Ppc * self.Tpc_corrected) / (self.Tpc - self.B * (1 - self.B) * self.e_correction)\n",
-    "        return self.Ppc_corrected\n",
-    "\n",
-    "    \"\"\"pseudo-reduced temperature (°R)\"\"\"\n",
-    "    def calc_Tr(self, T=None, Tpc_corrected=None, sg=None, Tpc=None, e_correction=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_T(T)\n",
-    "        self._initialize_Tpc_corrected(Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self.Tr = self.T / self.Tpc_corrected\n",
-    "        return self.Tr\n",
-    "\n",
-    "    \"\"\"pseudo-reduced pressure (psi)\"\"\"\n",
-    "    def calc_Pr(self, P=None, Ppc_corrected=None, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_P(P)\n",
-    "        self._initialize_Ppc_corrected(Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction, Tpc_corrected=Tpc_corrected, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self.Pr = self.P / self.Ppc_corrected\n",
-    "        return self.Pr\n",
-    "\n",
-    "    \"\"\"\n",
-    "    Objective function to miminize for Newton-Raphson nonlinear solver - Z factor calculation\n",
-    "    \"\"\"\n",
-    "    def _calc_z(self, z):\n",
-    "\n",
-    "        self.A1 = 0.3265\n",
-    "        self.A2 = -1.0700\n",
-    "        self.A3 = -0.5339\n",
-    "        self.A4 = 0.01569\n",
-    "        self.A5 = -0.05165\n",
-    "        self.A6 = 0.5475\n",
-    "        self.A7 = -0.7361\n",
-    "        self.A8 = 0.1844\n",
-    "        self.A9 = 0.1056\n",
-    "        self.A10 = 0.6134\n",
-    "        self.A11 = 0.7210\n",
-    "\n",
-    "        return 1 + (\n",
-    "                self.A1 +\n",
-    "                self.A2 / self.Tr +\n",
-    "                self.A3 / self.Tr ** 3 +\n",
-    "                self.A4 / self.Tr ** 4 +\n",
-    "                self.A5 / self.Tr ** 5\n",
-    "        ) * (0.27 * self.Pr) / (z * self.Tr) + (\n",
-    "                self.A6 +\n",
-    "                self.A7 / self.Tr +\n",
-    "                self.A8 / self.Tr ** 2\n",
-    "        ) * ((0.27 * self.Pr) / (z * self.Tr)) ** 2 - self.A9 * (\n",
-    "                self.A7 / self.Tr +\n",
-    "                self.A8 / self.Tr ** 2\n",
-    "        ) * ((0.27 * self.Pr) / (z * self.Tr)) ** 5 + self.A10 * (\n",
-    "                1 +\n",
-    "                self.A11 * ((0.27 * self.Pr) / (z * self.Tr)) ** 2\n",
-    "        ) * (\n",
-    "                ((0.27 * self.Pr) / (z * self.Tr)) ** 2 /\n",
-    "                self.Tr ** 3\n",
-    "        ) * np.exp(-self.A11 * ((0.27 * self.Pr) / (z * self.Tr)) ** 2) - z\n",
-    "\n",
-    "    \"\"\"Newton-Raphson nonlinear solver\"\"\"\n",
-    "    def calc_z(self, guess=0.9, sg=None, P=None, T=None, Tpc=None, Ppc=None, Tpc_corrected=None, Ppc_corrected=None,\n",
-    "               H2S=None, CO2=None, Tr=None, Pr=None, e_correction=None, ignore_conflict=False, newton_kwargs=None):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_Tr(Tr, T, Tpc_corrected=Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S,\n",
-    "                            CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self._initialize_Pr(Pr, P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n",
-    "                            Tpc_corrected=Tpc_corrected, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "\n",
-    "        if newton_kwargs is None:\n",
-    "            self.Z = optimize.newton(self._calc_z, guess)\n",
-    "        else:\n",
-    "            self.Z = optimize.newton(self._calc_z, guess, **newton_kwargs)\n",
-    "\n",
-    "        return self.Z\n",
-    "\n",
-    "    def _set_first_caller_attributes(self, func_name, func_kwargs):\n",
-    "        \"\"\"\n",
-    "        Helper function to set properties related to the first function called (first in the call stack).\n",
-    "        This function doesn't do anything for 'calc_...()' functions called inside the first function.\n",
-    "        For exmaple, if `calc_Ppc_corrected()' is called, this function is skipped for 'calc_Ppc()' function which is\n",
-    "        triggered inside `calc_Ppc_corrected()`.\n",
-    "        :param func_name: string\n",
-    "            ex1) func_name= \"calc_Tpc_corrected\",\n",
-    "            ex2) func_name = \"calc_Ppc_corrected\",\n",
-    "        :param func_kwargs: kwarg parameters passed to 'func_name'\n",
-    "            ex1) func_kwargs = {'self': ...some_string, 'sg': None, 'Tpc': 377.59, 'e_correction': None, 'H2S': 0.07, 'CO2': 0.1}\n",
-    "            ex2) func_kwargs = {'self': ...some_string, 'sg': 0.6, 'Tpc': None, 'e_correction': None, 'H2S': 0.07, 'CO2': 0.1}\n",
-    "        \"\"\"\n",
-    "        if not self._first_caller_is_saved:\n",
-    "            func_kwargs = {key: value for key, value in func_kwargs.items() if key != 'self'}\n",
-    "            if 'ignore_conflict' in func_kwargs:\n",
-    "\n",
-    "                if func_kwargs['ignore_conflict'] is False:\n",
-    "                    \"\"\"\n",
-    "                    This modification is needed for self._check_conflicting_arguments(). \n",
-    "                    The exception in self._check_conflicting_arguments() compares if \"kwarg is not None\"\n",
-    "                    The default 'ignore_conflict' is a boolean object, so comparing if \"ignore_conflict is not None\"\n",
-    "                    will raise type error \n",
-    "                    \"\"\"\n",
-    "                    func_kwargs['ignore_conflict'] = None\n",
-    "\n",
-    "            self._first_caller_name = func_name\n",
-    "            self._first_caller_kwargs = func_kwargs\n",
-    "            self._first_caller_is_saved = True\n",
-    "        else:\n",
-    "            pass\n",
-    "\n",
-    "    def _check_conflicting_arguments(self, func, calculated_var):\n",
-    "        \"\"\"\n",
-    "        :param func: string\n",
-    "            ex1) func_name = \"calc_Tpc\",\n",
-    "            ex2) func_name = \"calc_J\",\n",
-    "        :param calculated_var: string\n",
-    "            ex1) calculated_var = 'Tpc'\n",
-    "            ex1) calculated_var = 'J'\n",
-    "        \"\"\"\n",
-    "\n",
-    "        args = inspect.getfullargspec(func).args[1:]  # arg[0] = 'self', args = arguments defined in \"func\"\n",
-    "        for arg in args:\n",
-    "            if self._first_caller_kwargs[arg] is not None:\n",
-    "                raise TypeError('%s() has conflicting keyword arguments \"%s\" and \"%s\"' % (self._first_caller_name, calculated_var, arg))\n",
-    "\n",
-    "    def _initialize_sg(self, sg):\n",
-    "        if sg is None:\n",
-    "            if self._first_caller_name == 'calc_Ppc' or self._first_caller_name == 'calc_Tpc':\n",
-    "                raise TypeError(\"Missing a required argument, sg (specific gravity, dimensionless)\")\n",
-    "            else:\n",
-    "                raise TypeError(\"Missing a required arguments, sg (specific gravity, dimensionless), or Tpc \"\n",
-    "                                \"(pseudo-critical temperature, °R) or Ppc (pseudo-critical pressure, psia). \"\n",
-    "                                \"Either both Tpc and Ppc must be inputted, or only sg needs to be inputted. \"\n",
-    "                                \"Both Tpc and Ppc can be computed from sg\")\n",
-    "        else:\n",
-    "            self.sg = sg\n",
-    "\n",
-    "    def _initialize_P(self, P):\n",
-    "        if P is None:\n",
-    "            raise TypeError(\"Missing a required argument, P (gas pressure, psia)\")\n",
-    "        else:\n",
-    "            self.P = P\n",
-    "\n",
-    "    def _initialize_T(self, T):\n",
-    "        if T is None:\n",
-    "            raise TypeError(\"Missing a required argument, T (gas temperature, °F)\")\n",
-    "        else:\n",
-    "            self.T_f = T\n",
-    "            self.T = calc_Fahrenheit_to_Rankine(T)\n",
-    "\n",
-    "    def _initialize_H2S(self, H2S):\n",
-    "        if H2S is None:\n",
-    "            self.H2S = 0\n",
-    "        else:\n",
-    "            self.H2S = H2S\n",
-    "\n",
-    "    def _initialize_CO2(self, CO2):\n",
-    "        if CO2 is None:\n",
-    "            self.CO2 = 0\n",
-    "        else:\n",
-    "            self.CO2 = CO2\n",
-    "\n",
-    "    # The first argument A will always be None when called. However, still defining it for structural consistency\n",
-    "    def _initialize_A(self, A, H2S=None, CO2=None):\n",
-    "        if A is None:\n",
-    "            self._calc_A(H2S=H2S, CO2=CO2)\n",
-    "        else:\n",
-    "            self.A = A\n",
-    "\n",
-    "    # The first argument B will always be None when called. However, still defining it for structural consistency\n",
-    "    def _initialize_B(self, B, H2S=None):\n",
-    "        if B is None:\n",
-    "            self._calc_B(H2S=H2S)\n",
-    "        else:\n",
-    "            self.B = B\n",
-    "\n",
-    "    def _initialize_Tpc(self, Tpc, sg=None):\n",
-    "        if Tpc is None:\n",
-    "            self.calc_Tpc(sg=sg)\n",
-    "        else:\n",
-    "            self.Tpc = Tpc\n",
-    "\n",
-    "    def _initialize_Ppc(self, Ppc, sg=None):\n",
-    "        if Ppc is None:\n",
-    "            self.calc_Ppc(sg=sg)\n",
-    "        else:\n",
-    "            self.Ppc = Ppc\n",
-    "\n",
-    "    def _initialize_e_correction(self, e_correction, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if e_correction is None:\n",
-    "            self.calc_e_correction(H2S=H2S, CO2=CO2)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_e_correction, 'e_correction')\n",
-    "            self.e_correction = e_correction\n",
-    "\n",
-    "    def _initialize_Tpc_corrected(self, Tpc_corrected, sg=None, Tpc=None, e_correction=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if Tpc_corrected is None:\n",
-    "            self.calc_Tpc_corrected(sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_Tpc_corrected, 'Tpc_corrected')\n",
-    "            self.Tpc_corrected = Tpc_corrected\n",
-    "\n",
-    "    def _initialize_Ppc_corrected(self, Ppc_corrected, sg=None, Tpc=None, Ppc=None, e_correction=None,\n",
-    "                                  Tpc_corrected=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if Ppc_corrected is None:\n",
-    "            self.calc_Ppc_corrected(sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction, Tpc_corrected=Tpc_corrected, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_Ppc_corrected, 'Ppc_corrected')\n",
-    "            self.Ppc_corrected = Ppc_corrected\n",
-    "\n",
-    "    def _initialize_Pr(self, Pr, P=None, Ppc_corrected=None, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if Pr is None:\n",
-    "            self.calc_Pr(P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction, Tpc_corrected=Tpc_corrected, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_Pr, 'Pr')\n",
-    "            self.Pr = Pr\n",
-    "\n",
-    "    def _initialize_Tr(self, Tr, T, Tpc_corrected=None, sg=None, Tpc=None, e_correction=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if Tr is None:\n",
-    "            self.calc_Tr(T=T, Tpc_corrected=Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_Tr, 'Tr')\n",
-    "            self.Tr = Tr\n",
-    "\n",
-    "    def _check_invalid_mode(self, mode):\n",
-    "        if mode != 'Sutton' and mode != 'Piper':\n",
-    "            raise TypeError(\"Invalid optional argument, mode (calculation method), input either 'Sutton', 'Piper', or None (default='Sutton')\")\n",
-    "        self.mode = mode\n",
-    "\n",
-    "    def quickstart(self):\n",
-    "\n",
-    "        xmax = 8\n",
-    "        Prs = np.linspace(0, xmax, xmax * 10 + 1)\n",
-    "        Prs = np.array([round(Pr, 1) for Pr in Prs])\n",
-    "\n",
-    "        Trs = np.array([1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0])\n",
-    "\n",
-    "        results = {Tr: {\n",
-    "            'Pr': np.array([]),\n",
-    "            'Z': np.array([])\n",
-    "        } for Tr in Trs}\n",
-    "\n",
-    "        for Tr in Trs:\n",
-    "            for Pr in Prs:\n",
-    "                z_obj = Sutton()\n",
-    "                z = z_obj.calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "                results[Tr]['Z'] = np.append(results[Tr]['Z'], [z], axis=0)\n",
-    "                results[Tr]['Pr'] = np.append(results[Tr]['Pr'], [Pr], axis=0)\n",
-    "\n",
-    "        label_fontsize = 12\n",
-    "\n",
-    "        fig, ax = plt.subplots(figsize=(8, 5))\n",
-    "        for Tr in Trs:\n",
-    "\n",
-    "            Zs = results[Tr]['Z']\n",
-    "            idx_min = np.where(Zs == min(Zs))\n",
-    "\n",
-    "            p = ax.plot(Prs, Zs)\n",
-    "            if Tr == 1.05:\n",
-    "                t = ax.text(Prs[idx_min] - 0.5, min(Zs) - 0.005, '$T_{r}$ = 1.2', color=p[0].get_color())\n",
-    "                t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "            else:\n",
-    "                t = ax.text(Prs[idx_min] - 0.2, min(Zs) - 0.005, Tr, color=p[0].get_color())\n",
-    "                t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "\n",
-    "        ax.set_xlim(0, xmax)\n",
-    "        ax.minorticks_on()\n",
-    "        ax.grid(alpha=0.5)\n",
-    "        ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "        ax.spines.top.set_visible(False)\n",
-    "        ax.spines.right.set_visible(False)\n",
-    "\n",
-    "        ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "        ax.set_xlabel('Pseudo-Reduced Pressure, $P_{r}$', fontsize=label_fontsize)\n",
-    "        ax.text(0.57, 0.08, '$T_{r}$ = Pseudo-Reduced Temperature', fontsize=11, transform=ax.transAxes,\n",
-    "                bbox=dict(facecolor='white'))\n",
-    "\n",
-    "        def setbold(txt):\n",
-    "            return ' '.join([r\"$\\bf{\" + item + \"}$\" for item in txt.split(' ')])\n",
-    "\n",
-    "        ax.set_title(setbold('Real Gas Law Compressibility Factor - Z') + \", computed with GasCompressiblityFactor-py \",\n",
-    "                     fontsize=12, pad=10, x=0.445, y=1.06)\n",
-    "        ax.annotate('', xy=(-0.09, 1.05), xycoords='axes fraction', xytext=(1.05, 1.05),\n",
-    "                    arrowprops=dict(arrowstyle=\"-\", color='k'))\n",
-    "\n",
-    "        fig.tight_layout()\n",
-    "\n",
-    "        return results, fig, ax\n",
-    "\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "e1e74175",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.4995211795770008"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_J(sg=0.7, CO2=0.1, H2S=0.07)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "1fb73319",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'Piper' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_7828\\1810198164.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mPiper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_J\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mNameError\u001b[0m: name 'Piper' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_J(sg=0.7, CO2=0.1, H2S=0.07)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 75,
-   "id": "663d70a1",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "14.450840999999999"
-      ]
-     },
-     "execution_count": 75,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_K(sg=0.7)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 76,
-   "id": "86fcc840",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "371.4335560823552"
-      ]
-     },
-     "execution_count": 76,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_Tpc(sg=0.7)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 77,
-   "id": "7bb009b0",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "373.6152741511213\n",
-      "13.661213066633309\n",
-      "0.4995211795770008\n"
-     ]
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_Tpc(sg=0.7, CO2=0.1, H2S=0.07)\n",
-    "\n",
-    "print(a.Tpc)\n",
-    "print(a.K)\n",
-    "print(a.J)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 78,
-   "id": "64a330b6",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "747.947947947948\n",
-      "373.6\n",
-      "None\n",
-      "0.4995\n"
-     ]
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_Ppc(Tpc=373.6, J=0.4995)\n",
-    "\n",
-    "print(a.Ppc)\n",
-    "print(a.Tpc)\n",
-    "print(a.K)\n",
-    "print(a.J)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 79,
-   "id": "ec04435d",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "373.6152741511213\n",
-      "13.661213066633309\n",
-      "0.4995211795770008\n"
-     ]
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_Ppc(sg=0.7, CO2=0.1, H2S=0.07)\n",
-    "print(a.Tpc)\n",
-    "print(a.K)\n",
-    "print(a.J)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 80,
-   "id": "69b70729",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2.687356862566745\n",
-      "747.9468127207383\n",
-      "373.6152741511213\n",
-      "13.661213066633309\n",
-      "0.4995211795770008\n"
-     ]
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_Pr(sg=0.7, CO2=0.1, H2S=0.07, P=2010)\n",
-    "print(a.Pr)\n",
-    "print(a.Ppc)\n",
-    "print(a.Tpc)\n",
-    "print(a.K)\n",
-    "print(a.J)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 81,
-   "id": "4f327b42",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "None\n",
-      "None\n",
-      "373.6152741511213\n",
-      "13.661213066633309\n",
-      "0.4995211795770008\n"
-     ]
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_Tr(sg=0.7, CO2=0.1, H2S=0.07, T=75)\n",
-    "print(a.Pr)\n",
-    "print(a.Ppc)\n",
-    "print(a.Tpc)\n",
-    "print(a.K)\n",
-    "print(a.J)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f7524e69",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "80f90f97",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "658c5fb2",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8751d274",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "037dd492",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "id": "3dad22a1",
-   "metadata": {},
-   "source": [
-    "## Pr Check"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 82,
-   "id": "79144793",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2871.4285714285716"
-      ]
-     },
-     "execution_count": 82,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_Pr(Tpc=0.7, J=1, P=2010)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 83,
-   "id": "77e3193a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1454.66313"
-      ]
-     },
-     "execution_count": 83,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_Pr(Tpc=1, sg=1, P=2010)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 84,
-   "id": "0772dc86",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.0"
-      ]
-     },
-     "execution_count": 84,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_Pr(Ppc=2010, P=2010)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "6107a2f2",
-   "metadata": {},
-   "source": [
-    "## Z check"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "id": "f89d5d2c",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418404080772932"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_z(sg=0.7, H2S=0.07, CO2=0.1, P=2010, T=75)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7e85bd3b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5d203850",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "19ab93d8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 94,
-   "id": "d2187d76",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "calc_z() has conflicting keyword arguments \"Tpc_corrected\" and \"sg\"",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\779886230.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSutton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\879073164.py\u001b[0m in \u001b[0;36mcalc_z\u001b[1;34m(self, guess, sg, P, T, Tpc, Ppc, Tpc_corrected, Ppc_corrected, H2S, CO2, Tr, Pr, e_correction, ignore_conflict, **kwargs)\u001b[0m\n\u001b[0;32m    172\u001b[0m                H2S=None, CO2=None, Tr=None, Pr=None, e_correction=None, ignore_conflict=False, **kwargs):\n\u001b[0;32m    173\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_set_first_caller_attributes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minspect\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlocals\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 174\u001b[1;33m         self._initialize_Tr(Tr, T, Tpc_corrected=Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S,\n\u001b[0m\u001b[0;32m    175\u001b[0m                             CO2=CO2, ignore_conflict=ignore_conflict)\n\u001b[0;32m    176\u001b[0m         self._initialize_Pr(Pr, P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\879073164.py\u001b[0m in \u001b[0;36m_initialize_Tr\u001b[1;34m(self, Tr, T, Tpc_corrected, sg, Tpc, e_correction, H2S, CO2, ignore_conflict)\u001b[0m\n\u001b[0;32m    324\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_initialize_Tr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mignore_conflict\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    325\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mTr\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 326\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Tr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mT\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mignore_conflict\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mignore_conflict\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    327\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    328\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mignore_conflict\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\879073164.py\u001b[0m in \u001b[0;36mcalc_Tr\u001b[1;34m(self, T, Tpc_corrected, sg, Tpc, e_correction, H2S, CO2, ignore_conflict)\u001b[0m\n\u001b[0;32m    118\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_set_first_caller_attributes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minspect\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlocals\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    119\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_T\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mT\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 120\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Tpc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mignore_conflict\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mignore_conflict\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    121\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mT\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    122\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTr\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\879073164.py\u001b[0m in \u001b[0;36m_initialize_Tpc_corrected\u001b[1;34m(self, Tpc_corrected, sg, Tpc, e_correction, H2S, CO2, ignore_conflict)\u001b[0m\n\u001b[0;32m    302\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    303\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mignore_conflict\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 304\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_check_conflicting_arguments\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Tpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'Tpc_corrected'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    305\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc_corrected\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    306\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\879073164.py\u001b[0m in \u001b[0;36m_check_conflicting_arguments\u001b[1;34m(self, func, calculated_var)\u001b[0m\n\u001b[0;32m    224\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    225\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_caller_kwargs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0marg\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 226\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'%s() has conflicting keyword arguments \"%s\" and \"%s\"'\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_caller_name\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcalculated_var\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    227\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    228\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_initialize_sg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: calc_z() has conflicting keyword arguments \"Tpc_corrected\" and \"sg\""
-     ]
-    }
-   ],
-   "source": [
-    "a = Sutton()\n",
-    "a.calc_z(Tpc_corrected=1, sg=1, P=2010, T=75)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 71,
-   "id": "daa83938",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "calc_Tpc_corrected() has conflicting keyword arguments \"e_correction\" and \"H2S\"",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\3729029654.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSutton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Tpc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m21\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\879073164.py\u001b[0m in \u001b[0;36mcalc_Tpc_corrected\u001b[1;34m(self, sg, Tpc, e_correction, H2S, CO2, ignore_conflict)\u001b[0m\n\u001b[0;32m     93\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     94\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 95\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_e_correction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mignore_conflict\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mignore_conflict\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     96\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc_corrected\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     97\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\879073164.py\u001b[0m in \u001b[0;36m_initialize_e_correction\u001b[1;34m(self, e_correction, H2S, CO2, ignore_conflict)\u001b[0m\n\u001b[0;32m    294\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    295\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mignore_conflict\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 296\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_check_conflicting_arguments\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_e_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'e_correction'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    297\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0me_correction\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    298\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_6312\\879073164.py\u001b[0m in \u001b[0;36m_check_conflicting_arguments\u001b[1;34m(self, func, calculated_var)\u001b[0m\n\u001b[0;32m    224\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    225\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_caller_kwargs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0marg\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 226\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'%s() has conflicting keyword arguments \"%s\" and \"%s\"'\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_caller_name\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcalculated_var\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    227\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    228\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_initialize_sg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: calc_Tpc_corrected() has conflicting keyword arguments \"e_correction\" and \"H2S\""
-     ]
-    }
-   ],
-   "source": [
-    "a = Sutton()\n",
-    "a.calc_Tpc_corrected(sg=0.7, e_correction=21, H2S=0.7)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3b3742b3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "24e00ba1",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cd68ca43",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 156,
-   "id": "e2b75326",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "calc_z() has conflicting keyword arguments \"Tpc_corrected\" and \"sg\"",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_14796\\529554208.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSutton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_14796\\1784440184.py\u001b[0m in \u001b[0;36mcalc_z\u001b[1;34m(self, guess, sg, P, T, Tpc, Ppc, Tpc_corrected, Ppc_corrected, H2S, CO2, Tr, Pr, e_correction, ignore_conflict, newton_kwargs)\u001b[0m\n\u001b[0;32m    172\u001b[0m                H2S=None, CO2=None, Tr=None, Pr=None, e_correction=None, ignore_conflict=False, newton_kwargs=None):\n\u001b[0;32m    173\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_set_first_caller_attributes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minspect\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlocals\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 174\u001b[1;33m         self._initialize_Tr(Tr, T, Tpc_corrected=Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S,\n\u001b[0m\u001b[0;32m    175\u001b[0m                             CO2=CO2, ignore_conflict=ignore_conflict)\n\u001b[0;32m    176\u001b[0m         self._initialize_Pr(Pr, P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_14796\\1784440184.py\u001b[0m in \u001b[0;36m_initialize_Tr\u001b[1;34m(self, Tr, T, Tpc_corrected, sg, Tpc, e_correction, H2S, CO2, ignore_conflict)\u001b[0m\n\u001b[0;32m    329\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_initialize_Tr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mignore_conflict\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    330\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mTr\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 331\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Tr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mT\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mignore_conflict\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mignore_conflict\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    332\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    333\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mignore_conflict\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_14796\\1784440184.py\u001b[0m in \u001b[0;36mcalc_Tr\u001b[1;34m(self, T, Tpc_corrected, sg, Tpc, e_correction, H2S, CO2, ignore_conflict)\u001b[0m\n\u001b[0;32m    118\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_set_first_caller_attributes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minspect\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlocals\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    119\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_T\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mT\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 120\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Tpc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mignore_conflict\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mignore_conflict\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    121\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mT\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    122\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTr\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_14796\\1784440184.py\u001b[0m in \u001b[0;36m_initialize_Tpc_corrected\u001b[1;34m(self, Tpc_corrected, sg, Tpc, e_correction, H2S, CO2, ignore_conflict)\u001b[0m\n\u001b[0;32m    307\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    308\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mignore_conflict\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 309\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_check_conflicting_arguments\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Tpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'Tpc_corrected'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    310\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc_corrected\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    311\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_14796\\1784440184.py\u001b[0m in \u001b[0;36m_check_conflicting_arguments\u001b[1;34m(self, func, calculated_var)\u001b[0m\n\u001b[0;32m    229\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    230\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_caller_kwargs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0marg\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 231\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'%s() has conflicting keyword arguments \"%s\" and \"%s\"'\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_caller_name\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcalculated_var\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    232\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    233\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_initialize_sg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: calc_z() has conflicting keyword arguments \"Tpc_corrected\" and \"sg\""
-     ]
-    }
-   ],
-   "source": [
-    "a = Sutton()\n",
-    "#a.calc_z(Tpc_corrected=356.31, sg=0.7, P=2010, T=75, H2S=0.07, CO2=0.1)\n",
-    "\n",
-    "a = Sutton()\n",
-    "#a.calc_Tpc_corrected(sg=0.7, e_correction=21, H2S=0.7)\n",
-    "\n",
-    "a = Sutton()\n",
-    "a.calc_z(Tpc_corrected=1, sg=1, P=2010, T=75)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2962cea8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4035b30b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "id": "8eef7ffa",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<GasCompressibilityFactor object. Mixing Rule = Piper>"
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "76303295",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "id": "96c955d2",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418404080772932"
-      ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "instance = Piper()\n",
-    "kwargs = {'sg':0.7, 'P':2010, 'T':75, 'H2S':0.07, 'CO2':0.1}\n",
-    "result = instance.calc_z(**kwargs, ignore_conflict=True)\n",
-    "result"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "id": "5b3d464c",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "self.assertEqual(obj.sg, 0.7)\n",
-      "self.assertEqual(obj.P, 2010)\n",
-      "self.assertEqual(obj.T, 75)\n",
-      "self.assertEqual(obj.H2S, 0.07)\n",
-      "self.assertEqual(obj.CO2, 0.1)\n"
-     ]
-    }
-   ],
-   "source": [
-    "def temp(obj, dct):\n",
-    "    \n",
-    "    for key, val in dct.items():\n",
-    "        s = 'self.assertEqual(obj.%s, %s)' % (key, val)\n",
-    "        exec(s)\n",
-    "\n",
-    "temp(instance, kwargs)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "id": "f7896cd6",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "RuntimeError",
-     "evalue": "Failed to converge after 1 iterations, value is 0.7414685274075078.",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_7828\\339463580.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mPiper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnewton_kwargs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m{\u001b[0m\u001b[1;34m'maxiter'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_7828\\444672467.py\u001b[0m in \u001b[0;36mcalc_z\u001b[1;34m(self, guess, sg, P, T, Tpc, Ppc, H2S, CO2, N2, Tr, Pr, J, K, ignore_conflict, newton_kwargs)\u001b[0m\n\u001b[0;32m    174\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mZ\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moptimize\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnewton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_z\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mguess\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    175\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 176\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mZ\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moptimize\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnewton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_z\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mguess\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mnewton_kwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    177\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    178\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mZ\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\scipy\\optimize\\_zeros_py.py\u001b[0m in \u001b[0;36mnewton\u001b[1;34m(func, x0, fprime, args, tol, maxiter, fprime2, x1, rtol, full_output, disp)\u001b[0m\n\u001b[0;32m    366\u001b[0m         msg = (\"Failed to converge after %d iterations, value is %s.\"\n\u001b[0;32m    367\u001b[0m                % (itr + 1, p))\n\u001b[1;32m--> 368\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    369\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    370\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0m_results_select\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfull_output\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfuncalls\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mitr\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_ECONVERR\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mRuntimeError\u001b[0m: Failed to converge after 1 iterations, value is 0.7414685274075078."
-     ]
-    }
-   ],
-   "source": [
-    "a = Piper()\n",
-    "a.calc_z(sg=0.7, H2S=0.07, CO2=0.1, P=2010, T=75, newton_kwargs={'maxiter': 1,})"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "8504a696",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'{Tpc_corrected:356.31, sg:0.7, P:2010, T:75, H2S:0.07, CO2:0.1}'"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = 'Tpc_corrected=356.31, sg=0.7, P=2010, T=75, H2S=0.07, CO2=0.1'\n",
-    "a = a.replace('=', ':')\n",
-    "a = '{' + a + '}'\n",
-    "a"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6ae1fc9e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "05916f1e",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "SyntaxError",
-     "evalue": "invalid syntax (1944620624.py, line 1)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;36m  File \u001b[1;32m\"C:\\Users\\EricKim\\AppData\\Local\\Temp\\ipykernel_7828\\1944620624.py\"\u001b[1;36m, line \u001b[1;32m1\u001b[0m\n\u001b[1;33m    a = {Tpc_corrected=356.31, sg=0.7, P=2010, T=75, H2S=0.07, CO2=0.1}\u001b[0m\n\u001b[1;37m                      ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
-     ]
-    }
-   ],
-   "source": [
-    "{Tpc_corrected=356.31, sg=0.7, P=2010, T=75, H2S=0.07, CO2=0.1}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "id": "2c97a9d6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Pc_H2S=1306\n",
-    "Tc_H2S=672.3\n",
-    "Pc_CO2=1071\n",
-    "Tc_CO2=547.5\n",
-    "Pc_N2=492.4\n",
-    "Tc_N2=227.16"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 66,
-   "id": "8ccacab4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def J(sg, H2S=0, CO2=0, N2=0):\n",
-    "    return 0.11582 - 0.45820 * H2S * (Tc_H2S/Pc_H2S) - 0.90348 * (Tc_CO2/Pc_CO2) * CO2 - 0.66026 * (Tc_N2/Pc_N2) * N2 + 0.70729 * sg - 0.099397 * sg ** 2 "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 67,
-   "id": "885b9ed3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def Ppc_new(Ppc=0, Tpc_new=0, Tpc=0, B=0, e=0):\n",
-    "    return (Ppc * Tpc_new)/(Tpc - B * (1- B) * e)\n",
-    "\n",
-    "def E(H2S=0, CO2=0):\n",
-    "    A = H2S + CO2\n",
-    "    B = H2S\n",
-    "    return 120 * (A ** 0.9 - A ** 1.6) + 15 * (B ** 0.5 - B ** 4)\n",
-    "\n",
-    "def J(sg, H2S=0, CO2=0, N2=0):\n",
-    "    return 0.11582 - 0.45820 * H2S * (Tc_H2S/Pc_H2S) - 0.90348 * (Tc_CO2/Pc_CO2) * CO2 - 0.66026 * (Tc_N2/Pc_N2) * N2 + 0.70729 * sg - 0.099397 * sg ** 2 \n",
-    "\n",
-    "def K(sg, H2S=0, CO2=0, N2=0):\n",
-    "    return 3.8216 - 0.06534 * H2S * (Tc_H2S/Pc_H2S ** 0.5) - 0.42113 * (Tc_CO2/Pc_CO2 ** 0.5) * CO2 - 0.91249 * (Tc_N2/Pc_N2 ** 0.5) * N2 + 17.438 * sg - 3.2191 * sg ** 2 "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 73,
-   "id": "b1a87170",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.4690612564250918\n"
-     ]
-    }
-   ],
-   "source": [
-    "j = J(sg=0.7, H2S=0.07, CO2=0.1, N2=0.1)\n",
-    "print(j)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 74,
-   "id": "b491ee25",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "12.727096764135345\n"
-     ]
-    }
-   ],
-   "source": [
-    "k = K(sg=0.7, H2S=0.07, CO2=0.1, N2=0.1)\n",
-    "print(k)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 75,
-   "id": "a9ec4d1f",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "345.325881907563\n"
-     ]
-    }
-   ],
-   "source": [
-    "Tpc = k ** 2 / j\n",
-    "print(Tpc)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 76,
-   "id": "c9911969",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "736.2063636196116\n"
-     ]
-    }
-   ],
-   "source": [
-    "Ppc = Tpc / j\n",
-    "print(Ppc)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 133,
-   "id": "5b0a2de8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def E(H2S=0, CO2=0):\n",
-    "    A = H2S + CO2\n",
-    "    B = H2S\n",
-    "    return 120 * (A ** 0.9 - A ** 1.6) + 15 * (B ** 0.5 - B ** 4)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 134,
-   "id": "20b95639",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def Ppc_new(Ppc=0, Tpc_new=0, Tpc=0, B=0, e=0):\n",
-    "    return (Ppc * Tpc_new)/(Tpc - B * (1- B) * e)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 135,
-   "id": "c5e30c99",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "13.22374615565324"
-      ]
-     },
-     "execution_count": 135,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "E(H2S=0.07)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 137,
-   "id": "efd1660a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "625.9086837575147"
-      ]
-     },
-     "execution_count": 137,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "Ppc_new(Ppc=663.29, Tpc_new=356.31, Tpc=377.59)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0946d060",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1fb4f4c5",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b2c2978a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 97,
-   "id": "fdbaf43e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def tround(a, n):\n",
-    "    if a is not None:\n",
-    "        return round(a, n)\n",
-    "    return None  \n",
-    "n = 4"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 153,
-   "id": "20417bd7",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "self.assertAlmostEqual(instance.P, 2010, places=3)\n",
-      "self.assertAlmostEqual(instance.T, 534.67, places=3)\n",
-      "self.assertAlmostEqual(instance.e_correction, 21.2778, places=3)\n",
-      "self.assertAlmostEqual(instance.Ppc_corrected, 628.2104, places=3)\n",
-      "self.assertAlmostEqual(instance.Tpc_corrected, 356.31, places=3)\n",
-      "self.assertAlmostEqual(instance.Ppc, 663.287, places=3)\n",
-      "self.assertAlmostEqual(instance.Tpc, 377.59, places=3)\n",
-      "self.assertAlmostEqual(instance.Pr, 3.1996, places=3)\n",
-      "self.assertAlmostEqual(instance.Tr, 1.5006, places=3)\n",
-      "self.assertAlmostEqual(instance.Z, 0.7731, places=3)\n"
-     ]
-    }
-   ],
-   "source": [
-    "        instance = Sutton()\n",
-    "        result = instance.calc_z(Tpc_corrected=356.31, sg=0.7, P=2010, T=75, H2S=0.07, CO2=0.1, ignore_conflict=True)\n",
-    "        a = 'self.assertAlmostEqual(instance.P, %s, places=3)' % tround(instance.P, n)\n",
-    "        b = 'self.assertAlmostEqual(instance.T, %s, places=3)' % tround(instance.T, n)\n",
-    "        c = 'self.assertAlmostEqual(instance.e_correction, %s, places=3)' % tround(instance.e_correction, n)\n",
-    "        d = 'self.assertAlmostEqual(instance.Ppc_corrected, %s, places=3)' % tround(instance.Ppc_corrected, n)\n",
-    "        e = 'self.assertAlmostEqual(instance.Tpc_corrected, %s, places=3)' % tround(instance.Tpc_corrected, n)\n",
-    "        f = 'self.assertAlmostEqual(instance.Ppc, %s, places=3)' % tround(instance.Ppc, n)\n",
-    "        g = 'self.assertAlmostEqual(instance.Tpc, %s, places=3)' % tround(instance.Tpc, n)\n",
-    "        h = 'self.assertAlmostEqual(instance.Pr, %s, places=3)' % tround(instance.Pr, n)\n",
-    "        i = 'self.assertAlmostEqual(instance.Tr, %s, places=3)' % tround(instance.Tr, n)\n",
-    "        j = 'self.assertAlmostEqual(instance.Z, %s, places=3)' % tround(instance.Z, n)\n",
-    "        temp = [a, b, c, d, e, f, g, h, i, j]\n",
-    "        for item in temp:\n",
-    "            if 'None' in item:\n",
-    "                pass\n",
-    "            else:\n",
-    "                print(item)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 150,
-   "id": "827db540",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'self.assertAlmostEqual(instance.P, 2010, places=3)'"
-      ]
-     },
-     "execution_count": 150,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = 'self.assertAlmostEqual(instance.P, %s, places=3)' % tround(instance.P, n)\n",
-    "a"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 89,
-   "id": "322b1f9e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "21.277806029218723"
-      ]
-     },
-     "execution_count": 89,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "result"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 93,
-   "id": "92402158",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "21.277806029218723"
-      ]
-     },
-     "execution_count": 93,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "instance.e_correction"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 100,
-   "id": "b574e311",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "21.2778"
-      ]
-     },
-     "execution_count": 100,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "tround(instance.e_correction, n)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 101,
-   "id": "712f974c",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'self.assertAlmostEqual(instance.e_correction, 21.2778, places=3)'"
-      ]
-     },
-     "execution_count": 101,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "'self.assertAlmostEqual(instance.e_correction, %s, places=3)' % tround(instance.e_correction, n)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "71f42361",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "efdb753d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b9fd5fbc",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9b7828b8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b59202fe",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f426b6ad",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 178,
-   "id": "4931b0aa",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "not enough arguments for format string",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\3428000352.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mSutton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Ppc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m663.29\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m21.278\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m356.31\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m377.59\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\3113611712.py\u001b[0m in \u001b[0;36mcalc_Ppc_corrected\u001b[1;34m(self, sg, Tpc, Ppc, e_correction, Tpc_corrected, H2S, CO2)\u001b[0m\n\u001b[0;32m     96\u001b[0m                 \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     97\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 98\u001b[1;33m                 warnings.warn(\"e_correction factor computed from H2S = %s does not agree with the provided \"\n\u001b[0m\u001b[0;32m     99\u001b[0m                               \"e_correction factor within 10% tolerance. The result is likely to have minor error.\" % str(None) )\n\u001b[0;32m    100\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: not enough arguments for format string"
-     ]
-    }
-   ],
-   "source": [
-    "Sutton().calc_Ppc_corrected(Ppc=663.29, e_correction=21.278, Tpc_corrected=356.31, Tpc=377.59)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 179,
-   "id": "4eff2a9f",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "not enough arguments for format string",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\2674746062.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSutton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Ppc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m663.29\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m21.278\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m356.31\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\3113611712.py\u001b[0m in \u001b[0;36mcalc_Ppc_corrected\u001b[1;34m(self, sg, Tpc, Ppc, e_correction, Tpc_corrected, H2S, CO2)\u001b[0m\n\u001b[0;32m     96\u001b[0m                 \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     97\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 98\u001b[1;33m                 warnings.warn(\"e_correction factor computed from H2S = %s does not agree with the provided \"\n\u001b[0m\u001b[0;32m     99\u001b[0m                               \"e_correction factor within 10% tolerance. The result is likely to have minor error.\" % str(None) )\n\u001b[0;32m    100\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: not enough arguments for format string"
-     ]
-    }
-   ],
-   "source": [
-    "a = Sutton()\n",
-    "a.calc_Ppc_corrected(Ppc=663.29, e_correction=21.278, Tpc_corrected=356.31, sg=0.7)\n",
-    "\n",
-    "print(a.Ppc)\n",
-    "print(a.Tpc)\n",
-    "print(a.e_correction)\n",
-    "print(a.Tpc_corrected)\n",
-    "print(a.Ppc_corrected)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 196,
-   "id": "96997039",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "ValueError",
-     "evalue": "unsupported format character 't' (0x74) at index 108",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\1904961174.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mwarnings\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwarn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"e_correction factor computed from H2S = %%s does not agree with the provided e_correction factor within 10% tolerance. The result is likely to have minor error.\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;31mValueError\u001b[0m: unsupported format character 't' (0x74) at index 108"
-     ]
-    }
-   ],
-   "source": [
-    "warnings.warn(\"e_correction factor computed from H2S = %%s does not agree with the provided e_correction factor within 10% tolerance. The result is likely to have minor error.\" % str(None) )"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 181,
-   "id": "db1311f3",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\3949630673.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0misclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1.05\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrtol\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1e-01\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mequal_nan\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m<__array_function__ internals>\u001b[0m in \u001b[0;36misclose\u001b[1;34m(*args, **kwargs)\u001b[0m\n",
-      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\numpy\\core\\numeric.py\u001b[0m in \u001b[0;36misclose\u001b[1;34m(a, b, rtol, atol, equal_nan)\u001b[0m\n\u001b[0;32m   2354\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2355\u001b[0m     \u001b[0mxfin\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0misfinite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2356\u001b[1;33m     \u001b[0myfin\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0misfinite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2357\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mxfin\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0myfin\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2358\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mwithin_tol\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0matol\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrtol\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''"
-     ]
-    }
-   ],
-   "source": [
-    "np.isclose(1.05, None, rtol=1e-01, equal_nan=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0ca684c3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 148,
-   "id": "0b4a286b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "663.29\n",
-      "377.59\n",
-      "21.278\n",
-      "356.31\n",
-      "625.9086837575147\n"
-     ]
-    }
-   ],
-   "source": [
-    "a = Sutton()\n",
-    "a.calc_Ppc_corrected(Ppc=663.29, e_correction=21.278, Tpc_corrected=356.31, Tpc=377.59)\n",
-    "\n",
-    "print(a.Ppc)\n",
-    "print(a.Tpc)\n",
-    "print(a.e_correction)\n",
-    "print(a.Tpc_corrected)\n",
-    "print(a.Ppc_corrected)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 149,
-   "id": "b35e8aee",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "663.2869999999999\n",
-      "377.59\n",
-      "21.27\n",
-      "356.32\n",
-      "628.2272189965797\n"
-     ]
-    }
-   ],
-   "source": [
-    "a = Sutton()\n",
-    "a.calc_Ppc_corrected(sg=0.7, e_correction=21.27, H2S=0.07)\n",
-    "\n",
-    "print(a.Ppc)\n",
-    "print(a.Tpc)\n",
-    "print(a.e_correction)\n",
-    "print(a.Tpc_corrected)\n",
-    "print(a.Ppc_corrected)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6161a656",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a88ae358",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1c10b01f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9c091c21",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "99153d8e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 93,
-   "id": "a90bbfb8",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "calc_Tpc() got an unexpected keyword argument 'H2S'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\2015315914.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSutton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_e_correction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
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-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\2830035274.py\u001b[0m in \u001b[0;36mcalc_Pr\u001b[1;34m(self, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    136\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmode\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'Sutton'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    137\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_redundant_argument_check_Ppc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 138\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Ppc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    139\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    140\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m  \u001b[1;31m# mode == 'Piper'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\2830035274.py\u001b[0m in \u001b[0;36m_initialize_Ppc_corrected\u001b[1;34m(self, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2)\u001b[0m\n\u001b[0;32m    262\u001b[0m                                   Tpc_corrected=None, A=None, B=None, H2S=None, CO2=None):\n\u001b[0;32m    263\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mPpc_corrected\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 264\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Ppc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    265\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    266\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\2830035274.py\u001b[0m in \u001b[0;36mcalc_Ppc_corrected\u001b[1;34m(self, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2)\u001b[0m\n\u001b[0;32m    111\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_e_correction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    112\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mTpc_corrected\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 113\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Tpc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    114\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Tpc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    115\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m/\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mB\u001b[0m \u001b[1;33m*\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\2830035274.py\u001b[0m in \u001b[0;36m_initialize_Tpc\u001b[1;34m(self, Tpc, sg, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    236\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_initialize_Tpc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    237\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mTpc\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 238\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Tpc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    239\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    240\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: calc_Tpc() got an unexpected keyword argument 'H2S'"
-     ]
-    }
-   ],
-   "source": [
-    "a = Sutton()\n",
-    "a.calc_e_correction(H2S=0.07, CO2=0.1)\n",
-    "a.calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 87,
-   "id": "c199b5e3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'calc_e_correction'"
-      ]
-     },
-     "execution_count": 87,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a._calc_from"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 91,
-   "id": "0bd4f076",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "Missing a required argument, sg (specific gravity, dimensionless)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\3010113131.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Tpc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\3796771148.py\u001b[0m in \u001b[0;36mcalc_Tpc\u001b[1;34m(self, sg, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m     48\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_store_first_caller_name\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minspect\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     49\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmode\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'Sutton'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 50\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_sg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcalc_from\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Tpc'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     51\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTpc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m169.2\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m349.5\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msg\u001b[0m \u001b[1;33m-\u001b[0m \u001b[1;36m74.0\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msg\u001b[0m \u001b[1;33m**\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     52\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m  \u001b[1;31m# mode == 'Piper'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_16228\\3796771148.py\u001b[0m in \u001b[0;36m_initialize_sg\u001b[1;34m(self, sg, calc_from)\u001b[0m\n\u001b[0;32m    204\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0msg\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    205\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mcalc_from\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'Ppc'\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mcalc_from\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'Tpc'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 206\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Missing a required argument, sg (specific gravity, dimensionless)\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    207\u001b[0m             \u001b[1;32melif\u001b[0m \u001b[0mcalc_from\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'J'\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mcalc_from\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'K'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    208\u001b[0m                 raise TypeError(\"Missing a required argument, sg (specific gravity, dimensionless), or J \"\n",
-      "\u001b[1;31mTypeError\u001b[0m: Missing a required argument, sg (specific gravity, dimensionless)"
-     ]
-    }
-   ],
-   "source": [
-    "a = zfactor()\n",
-    "a.calc_Tpc()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a01189ea",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a0dc33a0",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cd860754",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "43d23d41",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a5135ca8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6c701f66",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6bf82dfb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/tutorials/run.ipynb b/tutorials/run.ipynb
deleted file mode 100644
index 806dc0e..0000000
--- a/tutorials/run.ipynb
+++ /dev/null
@@ -1,3867 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "efd77e30",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from scipy import optimize\n",
-    "import matplotlib.pyplot as plt\n",
-    "import inspect\n",
-    "\n",
-    "from gascompressibility.utilities.utilities import calc_Fahrenheit_to_Rankine\n",
-    "from gascompressibility.utilities.utilities import calc_psig_to_psia\n",
-    "from gascompressibility.z_correlation import z_helper\n",
-    "\n",
-    "\n",
-    "class Sutton:\n",
-    "    def __init__(self):\n",
-    "        self.mode = 'Sutton'\n",
-    "        self._check_invalid_mode(self.mode)  # prevent user modification of self.mode\n",
-    "\n",
-    "        self.sg = None\n",
-    "        self.T_f = None\n",
-    "        self.T = None\n",
-    "        self.P = None\n",
-    "        self.H2S = None\n",
-    "        self.CO2 = None\n",
-    "\n",
-    "        self.Tpc = None\n",
-    "        self.Ppc = None\n",
-    "        self.A = None\n",
-    "        self.B = None\n",
-    "        self.e_correction = None\n",
-    "        self.Tpc_corrected = None\n",
-    "        self.Ppc_corrected = None\n",
-    "        self.Tr = None\n",
-    "        self.Pr = None\n",
-    "\n",
-    "        self.Z = None\n",
-    "\n",
-    "        self._first_caller_name = None\n",
-    "        self._first_caller_keys = {}\n",
-    "        self._first_caller_kwargs = {}\n",
-    "        self._first_caller_is_saved = False\n",
-    "\n",
-    "    def __str__(self):\n",
-    "        return str(self.Z)\n",
-    "\n",
-    "    def __repr__(self):\n",
-    "        return '<GasCompressibilityFactor object. Mixing Rule = %s>' % self.mode\n",
-    "\n",
-    "    \"\"\"sum of the mole fractions of CO2 and H2S in a gas mixture\"\"\"\n",
-    "    def _calc_A(self, H2S=None, CO2=None):\n",
-    "        self._initialize_H2S(H2S)\n",
-    "        self._initialize_CO2(CO2)\n",
-    "        self.A = self.H2S + self.CO2\n",
-    "        return self.A\n",
-    "\n",
-    "    \"\"\"mole fraction of H2S in a gas mixture\"\"\"\n",
-    "    def _calc_B(self, H2S=None):\n",
-    "        self._initialize_H2S(H2S)\n",
-    "        self.B = self.H2S\n",
-    "        return self.B\n",
-    "\n",
-    "    \"\"\"pseudo-critical temperature (°R)\"\"\"\n",
-    "    def calc_Tpc(self, sg=None):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_sg(sg)\n",
-    "        self.Tpc = 169.2 + 349.5 * self.sg - 74.0 * self.sg ** 2\n",
-    "        return self.Tpc\n",
-    "\n",
-    "    \"\"\"pseudo-critical pressure (psi)\"\"\"\n",
-    "    def calc_Ppc(self, sg=None):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_sg(sg)\n",
-    "        self.Ppc = 756.8 - 131.07 * self.sg - 3.6 * self.sg ** 2\n",
-    "        return self.Ppc\n",
-    "\n",
-    "    \"\"\"correction for CO2 and H2S (°R)\"\"\"\n",
-    "    def calc_e_correction(self, H2S=None, CO2=None):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_A(A=None, H2S=H2S, CO2=CO2)\n",
-    "        self._initialize_B(B=None, H2S=H2S)\n",
-    "        self.e_correction = 120 * (self.A ** 0.9 - self.A ** 1.6) + 15 * (self.B ** 0.5 - self.B ** 4)\n",
-    "        return self.e_correction\n",
-    "\n",
-    "    def calc_Tpc_corrected(self, sg=None, Tpc=None, e_correction=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_Tpc(Tpc, sg=sg)\n",
-    "\n",
-    "        # Correction is not needed if no sour gas is present\n",
-    "        if e_correction is None and H2S is None and CO2 is None:\n",
-    "            self.Tpc_corrected = self.Tpc\n",
-    "            return self.Tpc_corrected\n",
-    "\n",
-    "        self._initialize_e_correction(e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self.Tpc_corrected = self.Tpc - self.e_correction\n",
-    "        return self.Tpc_corrected\n",
-    "\n",
-    "    \"\"\" corrected pseudo-critical pressure (psi)\"\"\"\n",
-    "    def calc_Ppc_corrected(self, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_Ppc(Ppc, sg=sg)\n",
-    "\n",
-    "        # Correction is not needed if no sour gas is present\n",
-    "        if e_correction is None and H2S is None and CO2 is None and Tpc is None and Tpc_corrected is None:\n",
-    "            self.Ppc_corrected = self.Ppc\n",
-    "            return self.Ppc_corrected\n",
-    "\n",
-    "        self._initialize_Tpc(Tpc, sg=sg)\n",
-    "        self._initialize_B(B=None, H2S=H2S)\n",
-    "        self._initialize_e_correction(e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self._initialize_Tpc_corrected(Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self.Ppc_corrected = (self.Ppc * self.Tpc_corrected) / (self.Tpc - self.B * (1 - self.B) * self.e_correction)\n",
-    "        return self.Ppc_corrected\n",
-    "\n",
-    "    \"\"\"pseudo-reduced temperature (°R)\"\"\"\n",
-    "    def calc_Tr(self, T=None, Tpc_corrected=None, sg=None, Tpc=None, e_correction=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_T(T)\n",
-    "        self._initialize_Tpc_corrected(Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self.Tr = self.T / self.Tpc_corrected\n",
-    "        return self.Tr\n",
-    "\n",
-    "    \"\"\"pseudo-reduced pressure (psi)\"\"\"\n",
-    "    def calc_Pr(self, P=None, Ppc_corrected=None, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "        self._initialize_P(P)\n",
-    "        self._initialize_Ppc_corrected(Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction, Tpc_corrected=Tpc_corrected, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self.Pr = self.P / self.Ppc_corrected\n",
-    "        return self.Pr\n",
-    "\n",
-    "    \"\"\"Newton-Raphson nonlinear solver\"\"\"\n",
-    "    def calc_z(self, sg=None, P=None, T=None, Tpc=None, Ppc=None, Tpc_corrected=None, Ppc_corrected=None,\n",
-    "               H2S=None, CO2=None, Tr=None, Pr=None, e_correction=None, ignore_conflict=False,\n",
-    "               model='DAK', guess=0.9, newton_kwargs=None):\n",
-    "        self._set_first_caller_attributes(inspect.stack()[0][3], locals())\n",
-    "\n",
-    "        print(self._first_caller_name)\n",
-    "        print(self._first_caller_keys)\n",
-    "        print(self._first_caller_kwargs)\n",
-    "\n",
-    "        self._initialize_Tr(Tr, T, Tpc_corrected=Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S,\n",
-    "                            CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        self._initialize_Pr(Pr, P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n",
-    "                            Tpc_corrected=Tpc_corrected, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        #Z = z_helper.calc_z(Pr=self.Pr, Tr=self.Tr, zmodel=model, guess=guess)\n",
-    "        #self.Z = Z\n",
-    "        #return self.Z\n",
-    "\n",
-    "\n",
-    "    def _set_first_caller_attributes(self, func_name, func_kwargs):\n",
-    "        \"\"\"\n",
-    "        Helper function to set properties related to the first function called (first in the call stack).\n",
-    "        This function doesn't do anything for 'calc_...()' functions called inside the first function.\n",
-    "        For exmaple, if `calc_Ppc_corrected()' is called, this function is skipped for 'calc_Ppc()' function which is\n",
-    "        triggered inside `calc_Ppc_corrected()`.\n",
-    "        :param func_name: string\n",
-    "            ex1) func_name= \"calc_Tpc_corrected\",\n",
-    "            ex2) func_name = \"calc_Ppc_corrected\",\n",
-    "        :param func_kwargs: kwarg parameters passed to 'func_name'\n",
-    "            ex1) func_kwargs = {'self': ...some_string, 'sg': None, 'Tpc': 377.59, 'e_correction': None, 'H2S': 0.07, 'CO2': 0.1}\n",
-    "            ex2) func_kwargs = {'self': ...some_string, 'sg': 0.6, 'Tpc': None, 'e_correction': None, 'H2S': 0.07, 'CO2': 0.1}\n",
-    "        \"\"\"\n",
-    "        if not self._first_caller_is_saved:\n",
-    "            func_kwargs = {key: value for key, value in func_kwargs.items() if key != 'self'}\n",
-    "            if 'ignore_conflict' in func_kwargs:\n",
-    "\n",
-    "                if func_kwargs['ignore_conflict'] is False:\n",
-    "                    \"\"\"\n",
-    "                    This modification is needed for self._check_conflicting_arguments(). \n",
-    "                    The exception in self._check_conflicting_arguments() compares if \"kwarg is not None\"\n",
-    "                    The default 'ignore_conflict' is a boolean object, so comparing if \"ignore_conflict is not None\"\n",
-    "                    will raise type error \n",
-    "                    \"\"\"\n",
-    "                    func_kwargs['ignore_conflict'] = None\n",
-    "\n",
-    "            self._first_caller_name = func_name\n",
-    "            self._first_caller_kwargs = func_kwargs\n",
-    "            self._first_caller_is_saved = True\n",
-    "        else:\n",
-    "            pass\n",
-    "\n",
-    "    def _check_conflicting_arguments(self, func, calculated_var):\n",
-    "        \"\"\"\n",
-    "        :param func: string\n",
-    "            ex1) func_name = \"calc_Tpc\",\n",
-    "            ex2) func_name = \"calc_J\",\n",
-    "        :param calculated_var: string\n",
-    "            ex1) calculated_var = 'Tpc'\n",
-    "            ex1) calculated_var = 'J'\n",
-    "        \"\"\"\n",
-    "\n",
-    "        args = inspect.getfullargspec(func).args[1:]  # arg[0] = 'self', args = arguments defined in \"func\"\n",
-    "        for arg in args:\n",
-    "            if self._first_caller_kwargs[arg] is not None:\n",
-    "                raise TypeError('%s() has conflicting keyword arguments \"%s\" and \"%s\"' % (self._first_caller_name, calculated_var, arg))\n",
-    "\n",
-    "    def _initialize_sg(self, sg):\n",
-    "        if sg is None:\n",
-    "            if self._first_caller_name == 'calc_Ppc' or self._first_caller_name == 'calc_Tpc':\n",
-    "                raise TypeError(\"Missing a required argument, sg (specific gravity, dimensionless)\")\n",
-    "            else:\n",
-    "                raise TypeError(\"Missing a required arguments, sg (specific gravity, dimensionless), or Tpc \"\n",
-    "                                \"(pseudo-critical temperature, °R) or Ppc (pseudo-critical pressure, psia). \"\n",
-    "                                \"Either both Tpc and Ppc must be inputted, or only sg needs to be inputted. \"\n",
-    "                                \"Both Tpc and Ppc can be computed from sg\")\n",
-    "        else:\n",
-    "            self.sg = sg\n",
-    "\n",
-    "    def _initialize_P(self, P):\n",
-    "        if P is None:\n",
-    "            raise TypeError(\"Missing a required argument, P (gas pressure, psig)\")\n",
-    "        else:\n",
-    "            self.P_a = P  # psia\n",
-    "            self.P = calc_psig_to_psia(P)\n",
-    "\n",
-    "    def _initialize_T(self, T):\n",
-    "        if T is None:\n",
-    "            raise TypeError(\"Missing a required argument, T (gas temperature, °F)\")\n",
-    "        else:\n",
-    "            self.T_f = T\n",
-    "            self.T = calc_Fahrenheit_to_Rankine(T)\n",
-    "\n",
-    "    def _initialize_H2S(self, H2S):\n",
-    "        if H2S is None:\n",
-    "            self.H2S = 0\n",
-    "        else:\n",
-    "            self.H2S = H2S\n",
-    "\n",
-    "    def _initialize_CO2(self, CO2):\n",
-    "        if CO2 is None:\n",
-    "            self.CO2 = 0\n",
-    "        else:\n",
-    "            self.CO2 = CO2\n",
-    "\n",
-    "    # The first argument A will always be None when called. However, still defining it for structural consistency\n",
-    "    def _initialize_A(self, A, H2S=None, CO2=None):\n",
-    "        if A is None:\n",
-    "            self._calc_A(H2S=H2S, CO2=CO2)\n",
-    "        else:\n",
-    "            self.A = A\n",
-    "\n",
-    "    # The first argument B will always be None when called. However, still defining it for structural consistency\n",
-    "    def _initialize_B(self, B, H2S=None):\n",
-    "        if B is None:\n",
-    "            self._calc_B(H2S=H2S)\n",
-    "        else:\n",
-    "            self.B = B\n",
-    "\n",
-    "    def _initialize_Tpc(self, Tpc, sg=None):\n",
-    "        if Tpc is None:\n",
-    "            self.calc_Tpc(sg=sg)\n",
-    "        else:\n",
-    "            self.Tpc = Tpc\n",
-    "\n",
-    "    def _initialize_Ppc(self, Ppc, sg=None):\n",
-    "        if Ppc is None:\n",
-    "            self.calc_Ppc(sg=sg)\n",
-    "        else:\n",
-    "            self.Ppc = Ppc\n",
-    "\n",
-    "    def _initialize_e_correction(self, e_correction, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if e_correction is None:\n",
-    "            self.calc_e_correction(H2S=H2S, CO2=CO2)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_e_correction, 'e_correction')\n",
-    "            self.e_correction = e_correction\n",
-    "\n",
-    "    def _initialize_Tpc_corrected(self, Tpc_corrected, sg=None, Tpc=None, e_correction=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if Tpc_corrected is None:\n",
-    "            self.calc_Tpc_corrected(sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_Tpc_corrected, 'Tpc_corrected')\n",
-    "            self.Tpc_corrected = Tpc_corrected\n",
-    "\n",
-    "    def _initialize_Ppc_corrected(self, Ppc_corrected, sg=None, Tpc=None, Ppc=None, e_correction=None,\n",
-    "                                  Tpc_corrected=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if Ppc_corrected is None:\n",
-    "            self.calc_Ppc_corrected(sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction, Tpc_corrected=Tpc_corrected, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_Ppc_corrected, 'Ppc_corrected')\n",
-    "            self.Ppc_corrected = Ppc_corrected\n",
-    "\n",
-    "    def _initialize_Pr(self, Pr, P=None, Ppc_corrected=None, sg=None, Tpc=None, Ppc=None, e_correction=None, Tpc_corrected=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if Pr is None:\n",
-    "            self.calc_Pr(P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction, Tpc_corrected=Tpc_corrected, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_Pr, 'Pr')\n",
-    "            self.Pr = Pr\n",
-    "\n",
-    "    def _initialize_Tr(self, Tr, T, Tpc_corrected=None, sg=None, Tpc=None, e_correction=None, H2S=None, CO2=None, ignore_conflict=False):\n",
-    "        if Tr is None:\n",
-    "            self.calc_Tr(T=T, Tpc_corrected=Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n",
-    "        else:\n",
-    "            if ignore_conflict is False:\n",
-    "                self._check_conflicting_arguments(self.calc_Tr, 'Tr')\n",
-    "            self.Tr = Tr\n",
-    "\n",
-    "    def _check_invalid_mode(self, mode):\n",
-    "        if mode != 'Sutton' and mode != 'Piper':\n",
-    "            raise TypeError(\"Invalid optional argument, mode (calculation method), input either 'Sutton', 'Piper', or None (default='Sutton')\")\n",
-    "        self.mode = mode\n",
-    "\n",
-    "    def quickstart(self):\n",
-    "\n",
-    "        xmax = 8\n",
-    "        Prs = np.linspace(0, xmax, xmax * 10 + 1)\n",
-    "        Prs = np.array([round(Pr, 1) for Pr in Prs])\n",
-    "\n",
-    "        Trs = np.array([1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0])\n",
-    "\n",
-    "        results = {Tr: {\n",
-    "            'Pr': np.array([]),\n",
-    "            'Z': np.array([])\n",
-    "        } for Tr in Trs}\n",
-    "\n",
-    "        for Tr in Trs:\n",
-    "            for Pr in Prs:\n",
-    "                z_obj = Sutton()\n",
-    "                z = z_obj.calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "                results[Tr]['Z'] = np.append(results[Tr]['Z'], [z], axis=0)\n",
-    "                results[Tr]['Pr'] = np.append(results[Tr]['Pr'], [Pr], axis=0)\n",
-    "\n",
-    "        label_fontsize = 12\n",
-    "\n",
-    "        fig, ax = plt.subplots(figsize=(8, 5))\n",
-    "        for Tr in Trs:\n",
-    "\n",
-    "            Zs = results[Tr]['Z']\n",
-    "            idx_min = np.where(Zs == min(Zs))\n",
-    "\n",
-    "            p = ax.plot(Prs, Zs)\n",
-    "            if Tr == 1.05:\n",
-    "                t = ax.text(Prs[idx_min] - 0.5, min(Zs) - 0.005, '$T_{r}$ = 1.2', color=p[0].get_color())\n",
-    "                t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "            else:\n",
-    "                t = ax.text(Prs[idx_min] - 0.2, min(Zs) - 0.005, Tr, color=p[0].get_color())\n",
-    "                t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "\n",
-    "        ax.set_xlim(0, xmax)\n",
-    "        ax.minorticks_on()\n",
-    "        ax.grid(alpha=0.5)\n",
-    "        ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "        ax.spines.top.set_visible(False)\n",
-    "        ax.spines.right.set_visible(False)\n",
-    "\n",
-    "        ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "        ax.set_xlabel('Pseudo-Reduced Pressure, $P_{r}$', fontsize=label_fontsize)\n",
-    "        ax.text(0.57, 0.08, '$T_{r}$ = Pseudo-Reduced Temperature', fontsize=11, transform=ax.transAxes,\n",
-    "                bbox=dict(facecolor='white'))\n",
-    "\n",
-    "        def setbold(txt):\n",
-    "            return ' '.join([r\"$\\bf{\" + item + \"}$\" for item in txt.split(' ')])\n",
-    "\n",
-    "        ax.set_title(setbold('Real Gas Law Compressibility Factor - Z') + \", computed with GasCompressiblityFactor-py \",\n",
-    "                     fontsize=12, pad=10, x=0.445, y=1.06)\n",
-    "        ax.annotate('', xy=(-0.09, 1.05), xycoords='axes fraction', xytext=(1.05, 1.05),\n",
-    "                    arrowprops=dict(arrowstyle=\"-\", color='k'))\n",
-    "\n",
-    "        fig.tight_layout()\n",
-    "\n",
-    "        return results, fig, ax\n",
-    "\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "63843a90",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calc_z\n",
-      "{}\n",
-      "{'sg': 0.7, 'P': 1995.3, 'T': 75, 'Tpc': None, 'Ppc': None, 'Tpc_corrected': None, 'Ppc_corrected': None, 'H2S': 0.07, 'CO2': 0.1, 'Tr': None, 'Pr': None, 'e_correction': None, 'ignore_conflict': None, 'model': 'DAK', 'guess': 0.9, 'newton_kwargs': None}\n"
-     ]
-    }
-   ],
-   "source": [
-    "a = Sutton()\n",
-    "a.calc_z(sg=0.7, H2S=0.07, CO2=0.1, P=2010-14.7, T=75)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "e8acb2cf",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "calc_z\n",
-      "{}\n",
-      "{'sg': 0.7, 'P': 1995.3, 'T': 75, 'Tpc': None, 'Ppc': None, 'Tpc_corrected': None, 'Ppc_corrected': None, 'H2S': 0.07, 'CO2': 0.1, 'Tr': None, 'Pr': 1.5, 'e_correction': None, 'ignore_conflict': None, 'model': 'DAK', 'guess': 0.9, 'newton_kwargs': None}\n"
-     ]
-    },
-    {
-     "ename": "TypeError",
-     "evalue": "calc_z() has conflicting keyword arguments \"Pr\" and \"P\"",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_22704\\3113971745.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSutton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m14.7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPr\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1.5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_22704\\2205029902.py\u001b[0m in \u001b[0;36mcalc_z\u001b[1;34m(self, sg, P, T, Tpc, Ppc, Tpc_corrected, Ppc_corrected, H2S, CO2, Tr, Pr, e_correction, ignore_conflict, model, guess, newton_kwargs)\u001b[0m\n\u001b[0;32m    137\u001b[0m         self._initialize_Tr(Tr, T, Tpc_corrected=Tpc_corrected, sg=sg, Tpc=Tpc, e_correction=e_correction, H2S=H2S,\n\u001b[0;32m    138\u001b[0m                             CO2=CO2, ignore_conflict=ignore_conflict)\n\u001b[1;32m--> 139\u001b[1;33m         self._initialize_Pr(Pr, P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n\u001b[0m\u001b[0;32m    140\u001b[0m                             Tpc_corrected=Tpc_corrected, H2S=H2S, CO2=CO2, ignore_conflict=ignore_conflict)\n\u001b[0;32m    141\u001b[0m         \u001b[1;31m#Z = z_helper.calc_z(Pr=self.Pr, Tr=self.Tr, zmodel=model, guess=guess)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_22704\\2205029902.py\u001b[0m in \u001b[0;36m_initialize_Pr\u001b[1;34m(self, Pr, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, H2S, CO2, ignore_conflict)\u001b[0m\n\u001b[0;32m    285\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    286\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mignore_conflict\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 287\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_check_conflicting_arguments\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Pr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'Pr'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    288\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mPr\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    289\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_22704\\2205029902.py\u001b[0m in \u001b[0;36m_check_conflicting_arguments\u001b[1;34m(self, func, calculated_var)\u001b[0m\n\u001b[0;32m    189\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    190\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_caller_kwargs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0marg\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 191\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'%s() has conflicting keyword arguments \"%s\" and \"%s\"'\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_caller_name\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcalculated_var\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    192\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    193\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_initialize_sg\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: calc_z() has conflicting keyword arguments \"Pr\" and \"P\""
-     ]
-    }
-   ],
-   "source": [
-    "a = Sutton()\n",
-    "a.calc_z(sg=0.7, H2S=0.07, CO2=0.1, P=2010-14.7, T=75, Pr=1.5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "17457519",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c03602af",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8b145044",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "795e5f7f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "bcf127cb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e0b78715",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "7ebb29fb",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.8093081653980262"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Piper().calc_z(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1, T=75, P=2010)  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "98c5498f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5483056093175225"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Piper().calc_Tr(sg=0.7, CO2=0.1, N2=0.1, H2S=0.07, T=75)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "095ae35b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "736.2063636196116"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Piper().calc_Ppc(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "141589ac",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a6e3a3b6",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1c90f3a8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "43f74e70",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2864d67a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3b50d7a8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "03828f6a",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z             = 0.77    [dimensionless]\n",
-      "Tpc           = 377.59  [°R]\n",
-      "Ppc           = 663.29  [psia]\n",
-      "e_correction  = 21.28   [°R]\n",
-      "Tpc_corrected = 356.31  [°R]\n",
-      "Ppc_corrected = 628.21  [psia]\n",
-      "Tr            = 1.5     [dimensionless]\n",
-      "Pr            = 3.22     [dimensionless]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    " \n",
-    "instance = gascomp.Sutton() \n",
-    "\n",
-    "z = instance.calc_z(sg=0.7, CO2=0.1, H2S=0.07, T=75, P=2010)   # Input: T[°F], P[psig]\n",
-    "\n",
-    "print('Z             =', round(instance.Z, 2), '   [dimensionless]')\n",
-    "print('Tpc           =', round(instance.Tpc, 2), ' [°R]')\n",
-    "print('Ppc           =', round(instance.Ppc, 2), ' [psia]')\n",
-    "print('e_correction  =', round(instance.e_correction, 2), '  [°R]')\n",
-    "print('Tpc_corrected =', round(instance.Tpc_corrected, 2), ' [°R]')\n",
-    "print('Ppc_corrected =', round(instance.Ppc_corrected, 2), ' [psia]')\n",
-    "print('Tr            =', round(instance.Tr, 2), '    [dimensionless]')\n",
-    "print('Pr            =', round(instance.Pr, 2), '    [dimensionless]')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "a61f1db0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7727976174884119"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_z(sg=0.7, CO2=0.1, H2S=0.07, P=2010, T=75)  # Input: T[°F],  P[psig]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "a9353b10",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "377.59"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_Tpc(sg=0.7) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "id": "84280172",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "356.31219397078127"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_Tpc_corrected(sg=0.7, CO2=0.1, H2S=0.07) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "id": "e9337b4b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5005661019949397"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Sutton().calc_Tr(sg=0.7, CO2=0.1, H2S=0.07, T=75) # Input: T[°F],"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1e5b3edb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1c13ca1c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "id": "f4eeaf3b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z   = 0.81    [dimensionless]\n",
-      "J   = 0.47    [°R/psia]\n",
-      "K   = 12.73   [°R/psia^0.5]\n",
-      "Ppc = 736.21  [psia]\n",
-      "Tpc = 345.33  [°R]\n",
-      "Pr  = 2.75    [dimensionless]\n",
-      "Tr  = 1.55    [dimensionless]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    " \n",
-    "instance = gascomp.Piper() \n",
-    "\n",
-    "z = instance.calc_z(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1, T=75, P=2010)   # Input: T[°F], P[psig]\n",
-    "\n",
-    "print('Z   =', round(instance.Z, 2), '   [dimensionless]')\n",
-    "print('J   =', round(instance.J, 2), '   [°R/psia]')\n",
-    "print('K   =', round(instance.K, 2), '  [°R/psia^0.5]')\n",
-    "print('Ppc =', round(instance.Ppc, 2), ' [psia]')\n",
-    "print('Tpc =', round(instance.Tpc, 2), ' [°R]')\n",
-    "print('Pr  =', round(instance.Pr, 2), '   [dimensionless]')\n",
-    "print('Tr  =', round(instance.Tr, 2), '   [dimensionless]')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "id": "65abaf00",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.8086927073843273"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Piper().calc_z(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1, P=2010, T=75)  # Input: T[°F],  P[psig]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "id": "087b6d1a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "345.325881907563"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Piper().calc_Tpc(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1)  # Input: T[°F],  P[psig]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "id": "9ae097d1",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5483056093175225"
-      ]
-     },
-     "execution_count": 35,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    ">>> gascomp.Piper().calc_Tr(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1, T=75)  # Input: T[°F],  P[psig]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "160395bb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b3935a3e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f5b18791",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6bdc3b82",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e11ca904",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3bea0059",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "58cb5edb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "instance"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "14279d9b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z             = 0.8093081653980262\n",
-      "K             = 12.727096764135345\n",
-      "J             = 0.4690612564250918\n",
-      "Ppc           = 736.2063636196116\n",
-      "Tpc           = 345.325881907563\n",
-      "Pr            = 2.730212749204843\n",
-      "Tr            = 1.5483056093175225\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    " \n",
-    "instance = gascomp.Piper() \n",
-    "\n",
-    "z = instance.calc_z(sg=0.7, CO2=0.1, H2S=0.07, N2=0.1, T=75, P=2010)\n",
-    "\n",
-    "print('Z             =', instance.Z)\n",
-    "print('K             =', instance.K)\n",
-    "print('J             =', instance.J)\n",
-    "print('Ppc           =', instance.Ppc)\n",
-    "print('Tpc           =', instance.Tpc)\n",
-    "print('Pr            =', instance.Pr)\n",
-    "print('Tr            =', instance.Tr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "43f6556b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "815d57ab",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a9382c28",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 99,
-   "id": "0222d4f3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418404080772932"
-      ]
-     },
-     "execution_count": 99,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "z_obj = gascomp.zfactor('Piper')\n",
-    "z_obj.calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1, N2=0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 114,
-   "id": "12163681",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.9876949628524373"
-      ]
-     },
-     "execution_count": 114,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "z_obj = gascomp.zfactor('Piper')\n",
-    "z_obj.calc_z(P=14.65, T=60, sg=2.025, H2S=0.07, N2=16.322/100)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dc5bd7e6",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8599a7c3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c1b08ad3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 100,
-   "id": "9550347c",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "747.9468127207383\n",
-      "373.6152741511213\n",
-      "0.4995211795770008\n",
-      "13.661213066633309\n",
-      "1.431071042838936\n",
-      "2.687356862566745\n",
-      "0.7418404080772932\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(z_obj.Ppc)\n",
-    "print(z_obj.Tpc)\n",
-    "print(z_obj.J)\n",
-    "print(z_obj.K)\n",
-    "print(z_obj.Tr)\n",
-    "print(z_obj.Pr)\n",
-    "print(z_obj.Z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 101,
-   "id": "e266ecfb",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "unexpected keyword argument 'Tpc'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_19280\\3570772943.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mz1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mz2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m663.28\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m377.59\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mz6\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPr\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m3.1995\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTr\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1.5005\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36mcalc_z\u001b[1;34m(self, guess, sg, P, T, Tpc, Ppc, Tpc_corrected, Ppc_corrected, A, B, H2S, CO2, N2, J, K, Tr, Pr, e_correction, **kwargs)\u001b[0m\n\u001b[0;32m    264\u001b[0m                A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None, Tr=None, Pr=None, e_correction=None, **kwargs):\n\u001b[0;32m    265\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_from\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'Z'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 266\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Pr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    267\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Tr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    268\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mZ\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moptimize\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnewton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_z\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mguess\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36m_initialize_Pr\u001b[1;34m(self, Pr, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    365\u001b[0m                        A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n\u001b[0;32m    366\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mPr\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 367\u001b[1;33m             self.calc_Pr(P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n\u001b[0m\u001b[0;32m    368\u001b[0m                          Tpc_corrected=Tpc_corrected, A=A, B=B, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n\u001b[0;32m    369\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36mcalc_Pr\u001b[1;34m(self, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    214\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    215\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m  \u001b[1;31m# mode == 'Piper'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 216\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_redundant_argument_check_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    217\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    218\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36m_redundant_argument_check_Ppc\u001b[1;34m(self, Ppc, Tpc, sg, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    463\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mPpc\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    464\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mTpc\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 465\u001b[1;33m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"unexpected keyword argument 'Tpc'\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    466\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0msg\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    467\u001b[0m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Redundant arguments 'Ppc' and 'sg', input only one of them\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: unexpected keyword argument 'Tpc'"
-     ]
-    }
-   ],
-   "source": [
-    "z1 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1, N2=0)\n",
-    "\n",
-    "z2 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59)\n",
-    "\n",
-    "z6 = gascomp.zfactor('Piper').calc_z(Pr=3.1995, Tr=1.5005)\n",
-    "\n",
-    "print(z1)\n",
-    "print(z2)\n",
-    "print(z3)\n",
-    "print(z4)\n",
-    "print(z5)\n",
-    "print(z6)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1692f065",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "id": "ebb5d079",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418404080772932"
-      ]
-     },
-     "execution_count": 55,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "gascomp.zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e192b0c3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "id": "83030eee",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "unexpected keyword argument 'Tpc'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_19280\\1884420974.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mz1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.7\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mz2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m663.28\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m377.59\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mz3\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m663.28\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m377.59\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m21.27\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.07\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mz4\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m628.2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m377.59\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m21.27\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mz5\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgascomp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzfactor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Piper'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_z\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m75\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m628.2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m356.3\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36mcalc_z\u001b[1;34m(self, guess, sg, P, T, Tpc, Ppc, Tpc_corrected, Ppc_corrected, A, B, H2S, CO2, N2, J, K, Tr, Pr, e_correction, **kwargs)\u001b[0m\n\u001b[0;32m    264\u001b[0m                A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None, Tr=None, Pr=None, e_correction=None, **kwargs):\n\u001b[0;32m    265\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_from\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'Z'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 266\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Pr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    267\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Tr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mTr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mT\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    268\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mZ\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moptimize\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnewton\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_calc_z\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mguess\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36m_initialize_Pr\u001b[1;34m(self, Pr, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    365\u001b[0m                        A=None, B=None, H2S=None, CO2=None, N2=None, J=None, K=None):\n\u001b[0;32m    366\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mPr\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 367\u001b[1;33m             self.calc_Pr(P=P, Ppc_corrected=Ppc_corrected, sg=sg, Tpc=Tpc, Ppc=Ppc, e_correction=e_correction,\n\u001b[0m\u001b[0;32m    368\u001b[0m                          Tpc_corrected=Tpc_corrected, A=A, B=B, H2S=H2S, CO2=CO2, N2=N2, J=J, K=K)\n\u001b[0;32m    369\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36mcalc_Pr\u001b[1;34m(self, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    214\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    215\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m  \u001b[1;31m# mode == 'Piper'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 216\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_redundant_argument_check_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    217\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mN2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mN2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mJ\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mJ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mK\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mK\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    218\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\gascompressibility\\zfactor.py\u001b[0m in \u001b[0;36m_redundant_argument_check_Ppc\u001b[1;34m(self, Ppc, Tpc, sg, H2S, CO2, N2, J, K)\u001b[0m\n\u001b[0;32m    463\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mPpc\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    464\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mTpc\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 465\u001b[1;33m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"unexpected keyword argument 'Tpc'\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    466\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0msg\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    467\u001b[0m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Redundant arguments 'Ppc' and 'sg', input only one of them\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: unexpected keyword argument 'Tpc'"
-     ]
-    }
-   ],
-   "source": [
-    "z1 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)\n",
-    "z2 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59, H2S=0.07, CO2=0.1)\n",
-    "z3 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59, e_correction=21.27, H2S=0.07)\n",
-    "z4 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc_corrected=628.2, Tpc=377.59, e_correction=21.27)\n",
-    "z5 = gascomp.zfactor('Piper').calc_z(P=2010, T=75, Ppc_corrected=628.2, Tpc_corrected=356.3)\n",
-    "z6 = gascomp.zfactor('Piper').calc_z(Pr=3.1995, Tr=1.5005)\n",
-    "\n",
-    "print(z1)\n",
-    "print(z2)\n",
-    "print(z3)\n",
-    "print(z4)\n",
-    "print(z5)\n",
-    "print(z6)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "64a99b6a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c0cf287b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "69d0cc11",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "id": "a248bc16",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z             = 0.7730732979666094\n",
-      "Ppc           = 663.2869999999999\n",
-      "Tpc           = 377.59\n",
-      "e_correction  = 21.277806029218723\n",
-      "Ppc_corrected = 628.2143047814683\n",
-      "Tpc_corrected = 356.31219397078127\n",
-      "Pr            = 3.1995450990234966\n",
-      "Tr            = 1.5005661019949397\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    " \n",
-    "z_obj = gascomp.zfactor()  # default mode = 'Sutton'\n",
-    "\n",
-    "Z = z_obj.calc_z(sg=0.7, P=2010, T=75, H2S=0.07, CO2=0.1)\n",
-    "\n",
-    "print('Z             =', z_obj.Z)\n",
-    "print('Ppc           =', z_obj.Ppc)\n",
-    "print('Tpc           =', z_obj.Tpc)\n",
-    "print('e_correction  =', z_obj.e_correction)\n",
-    "print('Ppc_corrected =', z_obj.Ppc_corrected)\n",
-    "print('Tpc_corrected =', z_obj.Tpc_corrected)\n",
-    "print('Pr            =', z_obj.Pr)\n",
-    "print('Tr            =', z_obj.Tr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "163c1a7e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3bc5e29f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a6bc9ce4",
-   "metadata": {},
-   "source": [
-    "# Testing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "id": "ff556fe7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "exec('z1 = gascomp.zfactor().calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "id": "0ba26033",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "P = 'P=2010, '\n",
-    "T = 'T=75, '\n",
-    "sg = 'sg=0.7, '\n",
-    "H2S = 'H2S=0.07, '\n",
-    "CO2 = 'CO2=0.1, '\n",
-    "N2 = 'N2=0, '\n",
-    "Ppc = 'Ppc=663.28, '\n",
-    "Tpc = 'Tpc=377.59, '\n",
-    "e_correction = 'e_correction=21.277, '\n",
-    "Ppc_corrected = 'Ppc_corrected=628.21, '\n",
-    "Tpc_corrected = 'Tpc_corrected=356.31, '\n",
-    "Pr = 'Pr=3.1995, '\n",
-    "Tr = 'Tr=1.5005, '"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 94,
-   "id": "329fa122",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "63\n"
-     ]
-    }
-   ],
-   "source": [
-    "import itertools\n",
-    "\n",
-    "lst = [P, T, sg]\n",
-    "lst = [P, T, sg, H2S, Ppc, Tpc]\n",
-    "#lst = [P, T, sg, H2S, CO2, N2, Ppc, Tpc, e_correction, Ppc_corrected, Tpc_corrected, Pr, Tr]\n",
-    "combs = []\n",
-    "\n",
-    "for i in range(1, len(lst)+1):\n",
-    "    els = [list(x) for x in itertools.combinations(lst, i)]\n",
-    "    combs.extend(els)\n",
-    "\n",
-    "s = []\n",
-    "for item in combs:\n",
-    "    c = ''.join(b for b in item).strip(', ')\n",
-    "    s.append(c)\n",
-    "print(len(s))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "982fcad9",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f57dfdd8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "98eca72e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5e2c6a10",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "45789247",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a300cd1c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d385e871",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "961aad98",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "057b4c5f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4bbb1b3a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f3e17715",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "77e41c66",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "460dbd67",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "id": "b37ed94f",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.7730732979666094\n",
-      "0.7730728821497411\n",
-      "0.7730546405630305\n",
-      "0.7730533493089499\n",
-      "0.7731021601171872\n",
-      "0.7730355427956694\n"
-     ]
-    }
-   ],
-   "source": [
-    "z1 = gascomp.zfactor().calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)\n",
-    "z2 = gascomp.zfactor().calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59, H2S=0.07, CO2=0.1)\n",
-    "z3 = gascomp.zfactor().calc_z(P=2010, T=75, Ppc=663.28, Tpc=377.59, e_correction=21.27, H2S=0.07)\n",
-    "z4 = gascomp.zfactor().calc_z(P=2010, T=75, Ppc_corrected=628.2, Tpc=377.59, e_correction=21.27)\n",
-    "z5 = gascomp.zfactor().calc_z(P=2010, T=75, Ppc_corrected=628.2, Tpc_corrected=356.3)\n",
-    "z6 = gascomp.zfactor().calc_z(Pr=3.1995, Tr=1.5005)\n",
-    "\n",
-    "print(z1)\n",
-    "print(z2)\n",
-    "print(z3)\n",
-    "print(z4)\n",
-    "print(z5)\n",
-    "print(z6)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a965c0b1",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "id": "f39c04c0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "z_obj = gascomp.zfactor()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "id": "931892c0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7730732979666094"
-      ]
-     },
-     "execution_count": 47,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "z_obj.calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "08131cb6",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "663.2869999999999\n",
-      "377.59\n",
-      "628.2143047814683\n",
-      "356.31219397078127\n",
-      "21.277806029218723\n",
-      "1.5005661019949397\n",
-      "3.1995450990234966\n",
-      "0.7730732979666094\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(z_obj.Ppc)\n",
-    "print(z_obj.Tpc)\n",
-    "print(z_obj.Ppc_corrected)\n",
-    "print(z_obj.Tpc_corrected)\n",
-    "print(z_obj.e_correction)\n",
-    "print(z_obj.Tr)\n",
-    "print(z_obj.Pr)\n",
-    "print(z_obj.Z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f5fa4f58",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2e74b902",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c964f61d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8de2403a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "1579c0c5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import gascompressibility as gascomp\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "f93bee0b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.851143760811577\n"
-     ]
-    }
-   ],
-   "source": [
-    "z = gascomp.zfactor().calc_z(Tr=1.5, Pr=1.6)\n",
-    "print(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "8df74f4e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.851143760811577"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "Z"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "00478641",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "id": "cdc31fcc",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "------------------------------------------------\n",
-      "Z = 0.77\n",
-      "Ppc = 663.3\n",
-      "Tpc = 377.6\n",
-      "e_correction = 21.28\n",
-      "Ppc_corrected = 628.21\n",
-      "Tpc_corrected = 628.21\n",
-      "Pr = 3.2\n",
-      "Tr = 1.5\n"
-     ]
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    "\n",
-    "# default mode = 'Sutton'\n",
-    "z_obj = zfactor()\n",
-    "\n",
-    "Z = z_obj.calc_z(sg=0.7, P=2010, T=75, H2S=0.07, CO2=0.1)\n",
-    "\n",
-    "print('------------------------------------------------')\n",
-    "print('Z =', round(Z, 2))\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5058371c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "f9a333f8",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Z             = 0.7730732979666094\n",
-      "Ppc           = 663.2869999999999\n",
-      "Tpc           = 377.59\n",
-      "e_correction  = 21.277806029218723\n",
-      "Ppc_corrected = 628.2143047814683\n",
-      "Tpc_corrected = 628.2143047814683\n",
-      "Pr            = 3.1995450990234966\n",
-      "Tr            = 1.5005661019949397\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('Z             =', z_obj.Z)\n",
-    "print('Ppc           =', z_obj.Ppc)\n",
-    "print('Tpc           =', z_obj.Tpc)\n",
-    "print('e_correction  =', z_obj.e_correction)\n",
-    "print('Ppc_corrected =', z_obj.Ppc_corrected)\n",
-    "print('Tpc_corrected =', z_obj.Ppc_corrected)\n",
-    "print('Pr            =', z_obj.Pr)\n",
-    "print('Tr            =', z_obj.Tr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2a4ce67e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6e8c775d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1f712b14",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "id": "92d2196a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<GasCompressibilityFactor object. Mixing Rule = Sutton>"
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "z_obj"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dfdd649b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "c7638c18",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 800x500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import gascompressibility as gascomp\n",
-    "\n",
-    "results, fig, ax = gascomp.zfactor().quickstart()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "fbf1bee0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "fig.savefig('z-correlation chart.png', dpi=200)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "962835b9",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b39cd3fb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "30be94dc",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fbefdc7b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a0e93cbf",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 175,
-   "id": "e05ef300",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418815034924504"
-      ]
-     },
-     "execution_count": 175,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, Tpc=373.6, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2c7bf352",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1cf485fb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "aec6eef9",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e2022094",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8a293081",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 148,
-   "id": "7098fc8e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7370643378633674"
-      ]
-     },
-     "execution_count": 148,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(T=75, sg=0.7, P=2010)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "3d3ac8bf",
-   "metadata": {},
-   "source": [
-    "## Test J"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 149,
-   "id": "852a1ccd",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.4995211795770008"
-      ]
-     },
-     "execution_count": 149,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_J(sg=0.7, H2S=0.07, CO2=0.1, N2=0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 150,
-   "id": "04e6bb40",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.4690612564250918"
-      ]
-     },
-     "execution_count": 150,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_J(sg=0.7, H2S=0.07, CO2=0.1, N2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 151,
-   "id": "9c599605",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.56221847"
-      ]
-     },
-     "execution_count": 151,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_J(sg=0.7)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d38c5008",
-   "metadata": {},
-   "source": [
-    "## Test K"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 152,
-   "id": "81954a0a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "13.661213066633309"
-      ]
-     },
-     "execution_count": 152,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_K(sg=0.7, H2S=0.07, CO2=0.1, N2=0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 153,
-   "id": "b87ba767",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "12.727096764135345"
-      ]
-     },
-     "execution_count": 153,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_K(sg=0.7, H2S=0.07, CO2=0.1, N2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 154,
-   "id": "707deebd",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "14.450840999999999"
-      ]
-     },
-     "execution_count": 154,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_K(sg=0.7)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4ca78b75",
-   "metadata": {},
-   "source": [
-    "## Test Tpc"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 155,
-   "id": "fde0685d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "373.61946146146147"
-      ]
-     },
-     "execution_count": 155,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tpc(K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 156,
-   "id": "33260f25",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "373.6152741511213"
-      ]
-     },
-     "execution_count": 156,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tpc(sg=0.7, H2S=0.07, CO2=0.1, N2=0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 157,
-   "id": "6cd4068e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "232.7950339652756"
-      ]
-     },
-     "execution_count": 157,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tpc(sg=0.7, H2S=0.07, CO2=0.1, N2=0.5)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "5268f25c",
-   "metadata": {},
-   "source": [
-    "## Test Ppc"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 158,
-   "id": "00e85949",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "747.947947947948"
-      ]
-     },
-     "execution_count": 158,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Ppc(Tpc=373.6, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 159,
-   "id": "7c50c900",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "747.9869098327557"
-      ]
-     },
-     "execution_count": 159,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Ppc(K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 160,
-   "id": "29c1f62f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "747.9468127207383"
-      ]
-     },
-     "execution_count": 160,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Ppc(sg=0.7, CO2=0.1, H2S=0.07)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "34312d52",
-   "metadata": {},
-   "source": [
-    "## Test Pr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 161,
-   "id": "9cda42df",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2.687466731664271"
-      ]
-     },
-     "execution_count": 161,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(Tpc=373.6, sg=0.7, P=2010, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 162,
-   "id": "8a7367a5",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2.6875250701965503"
-      ]
-     },
-     "execution_count": 162,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(Ppc=747.9, P=2010)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 163,
-   "id": "633d61d6",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "502.5"
-      ]
-     },
-     "execution_count": 163,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(P=2010, K=4, J=2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 164,
-   "id": "5ffef93d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "3.8686451504335713"
-      ]
-     },
-     "execution_count": 164,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(P=2010, sg=2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 165,
-   "id": "bf1eb299",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2.6873527837259097"
-      ]
-     },
-     "execution_count": 165,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Pr(P=2010, Tpc=373.6, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "43e95e28",
-   "metadata": {},
-   "source": [
-    "## Test Tr"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 166,
-   "id": "2794b835",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.431071042838936"
-      ]
-     },
-     "execution_count": 166,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tr(T=75, sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 167,
-   "id": "09c1dd2a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.431055004224267"
-      ]
-     },
-     "execution_count": 167,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tr(T=75, K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 168,
-   "id": "a4827b41",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.4311295503211992"
-      ]
-     },
-     "execution_count": 168,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_Tr(T=75, Tpc=373.6)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1e9b2373",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a8a72002",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5b4d8907",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "85b0b136",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "id": "fb0a4111",
-   "metadata": {},
-   "source": [
-    "## Test Z"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 193,
-   "id": "8da18f52",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.8093081653980262"
-      ]
-     },
-     "execution_count": 193,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1, N2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 192,
-   "id": "4c4292df",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418404080772932"
-      ]
-     },
-     "execution_count": 192,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 177,
-   "id": "0413bdbe",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418351281782508"
-      ]
-     },
-     "execution_count": 177,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 178,
-   "id": "712ed349",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418815034924504"
-      ]
-     },
-     "execution_count": 178,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, Tpc=373.6, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 189,
-   "id": "44fa2270",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7418439061899736"
-      ]
-     },
-     "execution_count": 189,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "zfactor('Piper').calc_z(P=2010, T=75, Pr=2.687, K=13.661, J=0.4995)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b78e5043",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b0ca8381",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 122,
-   "id": "e90619b4",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2.687356862566745\n",
-      "1.431071042838936\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.Pr)\n",
-    "print(aa.Tr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "baf6ed8d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "430d0425",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 98,
-   "id": "5d82cedd",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "13.661213066633309"
-      ]
-     },
-     "execution_count": 98,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "3.8216 \\\n",
-    "                 - 0.06534 * H2S * (Tc_H2S / np.sqrt(Pc_H2S)) \\\n",
-    "                 - 0.42113 * CO2 * (Tc_CO2 / np.sqrt(Pc_CO2)) \\\n",
-    "                 - 0.91249 * N2 * (Tc_N2 / np.sqrt(Pc_N2)) \\\n",
-    "                 + 17.438 * sg \\\n",
-    "                 - 3.2191 * sg ** 2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 97,
-   "id": "e927eba8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5773589999999997"
-      ]
-     },
-     "execution_count": 97,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "3.2191 * sg ** 2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e4a7e13e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 70,
-   "id": "5a022f5e",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0\n",
-      "0.1\n",
-      "0.07\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.N2)\n",
-    "print(aa.CO2)\n",
-    "print(aa.H2S)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 65,
-   "id": "31db8d16",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "-9.986241845719988"
-      ]
-     },
-     "execution_count": 65,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.K"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 66,
-   "id": "6f90326b",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "-0.4906848204229992"
-      ]
-     },
-     "execution_count": 66,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.J"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 67,
-   "id": "03d548f1",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7"
-      ]
-     },
-     "execution_count": 67,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.sg"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 68,
-   "id": "206decfd",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "672.3\n",
-      "1306\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.Tc_H2S)\n",
-    "print(aa.Pc_H2S)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 69,
-   "id": "4dafdb38",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "547.5\n",
-      "1071\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.Tc_CO2)\n",
-    "print(aa.Pc_CO2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "id": "817b49dd",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "227.16\n",
-      "492.4\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(aa.Tc_N2)\n",
-    "print(aa.Pc_N2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ae77786d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a1091b34",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a8bffbf8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 439,
-   "id": "b5870628",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "628.2143047814683\n",
-      "356.31219397078127\n",
-      "3.1995450990234966\n",
-      "1.5005661019949397\n",
-      "0.7730732979666094\n"
-     ]
-    }
-   ],
-   "source": [
-    "aa.calc_z(P=2010, T=75, CO2=0.1, H2S=0.07, sg=0.7)\n",
-    "print(aa.Ppc_corrected)\n",
-    "print(aa.Tpc_corrected)\n",
-    "print(aa.Pr)\n",
-    "print(aa.Tr)\n",
-    "print(aa.Z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 442,
-   "id": "77849553",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2.6875250701965503\n",
-      "1.4311295503211992\n",
-      "0.7418744010634963\n"
-     ]
-    }
-   ],
-   "source": [
-    "aa.calc_z(P=2010, T=75, Ppc=747.9, Tpc=373.6)\n",
-    "print(aa.Pr)\n",
-    "print(aa.Tr)\n",
-    "print(aa.Z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8977cb87",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f5023ab8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 422,
-   "id": "3925debc",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "Missing a required argument, H2S, (mole fraction of H2S, dimensionless)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_28080\\2424930199.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0maa\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Pr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m663.29\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m377.59\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mP\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2010\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m21.278\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_28080\\3062684313.py\u001b[0m in \u001b[0;36mcalc_Pr\u001b[1;34m(self, P, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2)\u001b[0m\n\u001b[0;32m    159\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    160\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_P\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mP\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 161\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Ppc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mCO2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    162\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mP\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    163\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPr\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_28080\\3062684313.py\u001b[0m in \u001b[0;36m_initialize_Ppc_corrected\u001b[1;34m(self, Ppc_corrected, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2)\u001b[0m\n\u001b[0;32m    265\u001b[0m                                   Tpc_corrected=None, A=None, B=None, H2S=None, CO2=None):\n\u001b[0;32m    266\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mPpc_corrected\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 267\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalc_Ppc_corrected\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me_correction\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTpc_corrected\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mH2S\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCO2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    268\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    269\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPpc_corrected\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mPpc_corrected\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_28080\\3062684313.py\u001b[0m in \u001b[0;36mcalc_Ppc_corrected\u001b[1;34m(self, sg, Tpc, Ppc, e_correction, Tpc_corrected, A, B, H2S, CO2)\u001b[0m\n\u001b[0;32m    107\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0me_correction\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    108\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mB\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mH2S\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 109\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Missing a required argument, H2S, (mole fraction of H2S, dimensionless)\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    110\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    111\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize_Ppc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPpc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msg\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mTypeError\u001b[0m: Missing a required argument, H2S, (mole fraction of H2S, dimensionless)"
-     ]
-    }
-   ],
-   "source": [
-    "aa.calc_Pr(Ppc=663.29, Tpc=377.59, P=2010, e_correction=21.278)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5611e722",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "37b247c3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 365,
-   "id": "3037b714",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "377.59"
-      ]
-     },
-     "execution_count": 365,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.Tpc"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 375,
-   "id": "3084b6e3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "1.5005753416968373"
-      ]
-     },
-     "execution_count": 375,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Tr(sg=0.7, T=75, Tpc_corrected=356.31)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6f05b580",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 209,
-   "id": "5b021b5e",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "333333\n",
-      "0.07\n",
-      "0\n",
-      "0.07\n",
-      "44444444\n",
-      "21.278\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "628.2139838777422"
-      ]
-     },
-     "execution_count": 209,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Ppc_corrected(sg=0.7, H2S=0.07, CO2=0.1, e_correction=21.278)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 211,
-   "id": "9f32aa58",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "333333\n",
-      "0.07\n",
-      "---------\n",
-      "++++++\n",
-      "None\n",
-      "None\n",
-      "0.07\n",
-      "0.1\n",
-      "++++++\n",
-      "0.17\n",
-      "0.07\n",
-      "44444444\n",
-      "None\n",
-      "---------\n",
-      "++++++\n",
-      "None\n",
-      "None\n",
-      "0\n",
-      "0\n",
-      "++++++\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "663.2869999999999"
-      ]
-     },
-     "execution_count": 211,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Ppc_corrected(sg=0.7, H2S=0.07, CO2=0.1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 198,
-   "id": "97c12aad",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.0"
-      ]
-     },
-     "execution_count": 198,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.e_correction"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 199,
-   "id": "6e83dd80",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0"
-      ]
-     },
-     "execution_count": 199,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.A"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 200,
-   "id": "aa848e3f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0"
-      ]
-     },
-     "execution_count": 200,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.B"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9c9f129c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f18ef30e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a1149e70",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8ddf4049",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 129,
-   "id": "3e7ee309",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "364.3662538443467"
-      ]
-     },
-     "execution_count": 129,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Ppc_corrected(sg=0.7, H2S=0.07)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 128,
-   "id": "e844e081",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "356.31199999999995"
-      ]
-     },
-     "execution_count": 128,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Tpc_corrected(sg=0.7, e_correction=21.278)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7df1eeab",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 130,
-   "id": "d4abbc9d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "356.31199999999995"
-      ]
-     },
-     "execution_count": 130,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "aa.calc_Tpc_corrected(Tpc=377.59, e_correction=21.278)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0733811c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f40aa844",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2a298ef5",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "29ac9aac",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "90a1df02",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b2afba32",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6ff9b8e9",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "70d0e5e3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c963d4af",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d8c17f58",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1b9cdd52",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "da8535f9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 109,
-   "id": "b7f89bcf",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "xmax = 8\n",
-    "Prs = np.linspace(0, xmax, xmax * 10 + 1)\n",
-    "Trs = [1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0]\n",
-    "\n",
-    "results = {Tr: [] for Tr in Trs}\n",
-    "for Tr in Trs:\n",
-    "    for Pr in Prs:\n",
-    "        z = Z_factor().calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "        results[Tr].append(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 110,
-   "id": "6785584c",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EricKim\\AppData\\Local\\Temp\\ipykernel_12360\\954759431.py:20: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
-      "  ax.grid(b=True, which='minor', alpha=0.1)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 800x500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "label_fontsize = 12\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(8, 5))\n",
-    "for Tr in Trs:\n",
-    "    \n",
-    "    Zs = results[Tr]\n",
-    "    idx_min = Zs.index(min(Zs))\n",
-    "    \n",
-    "    p = ax.plot(Prs, Zs)\n",
-    "    if Tr == 1.05:\n",
-    "        t = ax.text(Prs[idx_min] - 0.5, min(Zs) - 0.005, '$T_{r}$ = 1.2', color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))       \n",
-    "    else:\n",
-    "        t = ax.text(Prs[idx_min] - 0.2, min(Zs) - 0.005, Tr, color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "\n",
-    "ax.set_xlim(0, xmax)\n",
-    "ax.minorticks_on()\n",
-    "ax.grid(alpha=0.5)\n",
-    "ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "ax.spines.top.set_visible(False)\n",
-    "ax.spines.right.set_visible(False)\n",
-    "\n",
-    "ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "ax.set_xlabel('Pseudo-Reduced Pressure, $P_{r}$', fontsize=label_fontsize)\n",
-    "ax.text(0.57, 0.08, '$T_{r}$ = Pseudo-Reduced Temperature', fontsize=11, transform=ax.transAxes, bbox=dict(facecolor='white'))\n",
-    "ax.text(7.65, 0.42, 'aegis4048.github.io', fontsize=label_fontsize, ha='right', va='top', color='grey', alpha=0.5)\n",
-    "\n",
-    "def setbold(txt):\n",
-    "    return ' '.join([r\"$\\bf{\" + item + \"}$\" for item in txt.split(' ')])\n",
-    "\n",
-    "ax.set_title(setbold('Real Gas Law Compressibility Factor - Z')  + \", computed with GasCompressiblityFactor-py \", fontsize=12, pad=10, x=0.445, y=1.06)\n",
-    "ax.annotate('', xy=(-0.09, 1.05), xycoords='axes fraction', xytext=(1.05, 1.05), arrowprops=dict(arrowstyle=\"-\", color='k'))\n",
-    "\n",
-    "fig.tight_layout()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b070bffe",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cf1c6735",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4e95ea23",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c029ebef",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "21c49886",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "dd5c2d88",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 133,
-   "id": "f99c5832",
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [],
-   "source": [
-    "Prs = np.linspace(0, 8, 81)\n",
-    "Trs = [1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0]\n",
-    "\n",
-    "results = {Tr: [] for Tr in Trs}\n",
-    "for Tr in Trs:\n",
-    "    for Pr in Prs:\n",
-    "        z = Z_factor().calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "        results[Tr].append(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 134,
-   "id": "ab3fbee1",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EricKim\\AppData\\Local\\Temp\\ipykernel_13736\\1567171423.py:18: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
-      "  ax.grid(b=True, which='minor', alpha=0.1)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 700x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "label_fontsize = 12\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(7, 8))\n",
-    "for Tr in Trs:\n",
-    "    \n",
-    "    Zs = results[Tr]\n",
-    "    idx_min = Zs.index(min(Zs))\n",
-    "    \n",
-    "    p = ax.plot(Prs, Zs)\n",
-    "    ax.set_ylim(0.25, 1.1)\n",
-    "    ax.set_xlim(0, 8)\n",
-    "    \n",
-    "    t = ax.text(Prs[idx_min] - 0.2, min(Zs) - 0.005, Tr, color=p[0].get_color())\n",
-    "    t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "    \n",
-    "    ax.minorticks_on()\n",
-    "    ax.grid(alpha=0.5)\n",
-    "    ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "    \n",
-    "    ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "    ax.set_xlabel('Pseudo-Reduced Pressure, $P_{r}$', fontsize=label_fontsize)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "000f5e65",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1ac9f964",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c949bee0",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 135,
-   "id": "1ffa5b14",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Prs = np.linspace(7, 15, 81)\n",
-    "Trs = [1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0]\n",
-    "\n",
-    "results = {Tr: [] for Tr in Trs}\n",
-    "for Tr in Trs:\n",
-    "    for Pr in Prs:\n",
-    "        z = Z_factor().calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "        results[Tr].append(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 137,
-   "id": "d4270246",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EricKim\\AppData\\Local\\Temp\\ipykernel_13736\\3204600190.py:23: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
-      "  ax.grid(b=True, which='minor', alpha=0.1)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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CtTkhrLZvXkdeHocOHSr++ujRo2zbto3o6Gjq1avHc889R3JyMnPmzClRN2PGDLp160abNm184sMfSHgTBEEQBAFVVSmwOoqDW5hJVxzcaoUaScu1lLg+Pc+KTqMQGawvdTyNRqF9fMTFZ97O7HEdwJufBrXbwODvIKSmz17Ppk2b6NGjR/HXTz75JABDhgxh1qxZpKSkcOLEiRI12dnZfPPNN3zwwQc+8+EPJLwJgiAIgkCB1UH+ecEt2PB3ROhYP5Lle8+UuH7NwTTa1o1Ary19BZaqquxJyaF57bALfqZkHIZ5faHgLNRp5wpuwb5tsdW9e/dLHpcya9asC74XERFBQUGBT334A1nzJgiCIAjVjHyLnd2nstl9ynV22uG0fLYmZZGabSbUqOPD3w/x5Ffbiq8f2K0+yZmFvPK/PRw6k8vCjUks3JTEyOsbFl/z/m8HWHUgjRNnC9h9KpsJi3aw51QOA678xzlpqhPDsidQCs5C3BUw5HufB7eqjsy8CYIgCEI1Y8fJbB6avq746zd/3g/AnR3i+ODBjpzJsZCcVVj884ToYD4f2oVX/reHuX8dJybcyEt9W9Onzd9dD3IK7Ty/eCdpuRbCTDpaxYXz1air6JAQ+bewwwZ2M4olFzW+K8rARWAquRtVuDwS3gRBEAShmnFV4xoc++9t5Fvs5FnsAIQYtIQYXbHgnX7tL6i5slENlo67rsT3zn8s+WLfVrzYt9XFRe1WsOSgaA04ardFc9vbYPLfkR9VGXlsKgiCIAjVkALrecHNqCsObn7BboXCDEBF1Wix3fQGGC9cCyeUDZl5EwRBEIRqRoHVTq75vBm3ixwH4hPsFijMBFTQGEAfDE4/6lUDJLwJgiAIQjXCbHNQaHWg0yiY9JoSu0p9jt0KllzQaF3BTR6T+gSv3rGi/mnuXu9Ojad1olU9PIpW9fBYVbUCwaNoVS2PdqeKzeHEoNOg12ow6i5cPeWu3kXrnHZwmFG0BlSNDvRBF3j0avxqjFfhzWKxYDab3a5xt0ebp3WiVXF1ohVYWp7WiVbF1YlWYGl5WudLreX70vh41TGcKtzSOobR19XH4lBK1HjS5L20Os2JP9H//hKK046j/nXYerwATtchv6qqup0dinQAunTpglarJTExkcTERLfHqQp4Fd6MRiMmk6nM1xclbaPR6NYvoyd1olU9PIpW9fBYVbUCwaNoVQ2PS3emMP7rXTicKg90SWBcr2ZoNEqJGqfTicFgcFvrgro938E3w1GcdtRWd6G5+VWMWn2JGk9eV1F427hxo18b0wcCXoU3RVHc/htBUU151IlW9fAoWtXDY1XVCgSPohXYHn/encrjC7bhcKrc1yme1+9uWyK4+VKLXd/ANyNBdUDb+1HumgraC6OGp/dCcCFHhQiCIAhCFeX3fad57Ist2J0qd3WI441725Ua3HzC9q/gmxGu4Nb+Ibh7WqnBTfAeCW+CIAiCUAVZdSCN0XO3YHOo3NYulrfvb4/WX8Ft23z4dhSoTug4EO782LXDVPALEokFQRAEoYqx7mgGo7/YgdXh5ObWtXn/gQ7oLtJA3lu02+fDT08DKnQaCre9CxqZG/InEt4EQRAEoQqx/mgGj365A4vdSe+WMXz40BXo/RTc2DgDw09Puf7c9RHo8ybI2jS/I9FYEARBEKoIm49nMGzWRgptTm5oVouPB1yBoZSz3HzCuqkoP7qCm3rloxLcyhGZeRMEQRCEKsC2pCyGzNxIgdXBVY2imDrwCoy6sq87c2s357YvYMtsiGmFre0D6K4ZJ8GtHJHwJgiCIAgBzq7kbAbNWE+exc6VjaL5+MG2mPTubRgo8wG9dgu0uB1a3I6qM6LTGjxwLHiDhDdBEARBCGD2nMph4Iz15JrtdK4fxWeDO6NV7f4RsxaALd/1Z30wSHCrEGTNmyAIgiAEKAdO5zJwxnqyCmx0SIjk86FdCDH6YV5GVV0N5i3Zrp6luiAwhPheRygTMvMmCIIgCAHIoTN59J++nox8K23rRjB7WFfCTPqyNXA/9gf8ORlObYO8VHhgnutRaGmoKmQchl9fhNO7IfM4dBsNff7r09cjlB2vwltRfzJ3r3enxtM60aoeHkWrenisqlqB4FG0KqfHo+n59J++jvQ8Cy1jw5gzrAvhJl2JmktqWfOhdhvo0B9l4eBiPUVRLqyz5KIUZkJQNOq1T8DGzwDVFeouVefB67pcneDCq/BmsVgwm81u13jSn8yTOtGquDrRCiwtT+tEq+LqRCuwtDytK63mZGYhg2Zt4UyuhaYxIcwY2B6Txlni8/ifdYqilNyQ0PRG1z+XQlXBmotiK4CIeNRb3gBDMOxYeFnPlwtant4LgC5duqDVaklMTCQxMdGtMaoKXoU3o9GIyWQq8/VFSdtoNLr1pnlSJ1rVw6NoVQ+PVVUrEDyKVuXymJxVyMNztpGaY6FxrRDmj7iSWmHGy9Z5RFFwA1RjuGuDQhm43K5VT/0VhbeNGzcSHh5e5rqqiFfhTVEUt38ximrKo060qodH0aoeHquqViB4FK3K4TE120z/6etJziqkYc0Qvhx5JTHhpU+geKoFoABYcuBccMMYgWI4P7gprn8UpfiR6fn17r4ud/0JsmFBEARBECo9Z3LM9J++jhMZBdSLDuaLkd0uGty8xpINtkLXn00RZZ5xE8oPCW+CIAiCUIlJz7PQ/7P1HEnPp25kEF+M7EZsRJDvhVTVNeNmLwpukaD3g47gNRLeBEEQBKGSkllgY+jcbRw6k0edcBNfjryS+Cg/zYRZslHs5zY9SHCr1Eh4EwRBEIRKSHahjeFzt7I/NY+YMCNfPnIl9Wr4KLhZ8iDjyN9fp+1DMYSgmiJRYlrBqv9CTgrcM+3va1J2uP5tzYOCdNfXWj3UauEbT0KZkfAmCIIgCJWMHLONwTM3sDc1jxqhBr4Y2Y2GNX3Y0eDUVpj996G8yu+vuv7Q7gG451PIPQ3ZJ0vWTLvu7z+nbIOdX0NEAjy+03e+hDIh4U0QBEEQKhF5FjsPz9zAjpPZRAbpmT+8G01iwnwr0vA6eCkLCrPAYUZFcT0q1Z075uPuKRfWTMy+8HtycG6FIOFNEARBECoJBVY7w2ZtZMuJLCKC9Mwc3IHmdXwc3MAVugozwWEBFAiKkibzAYSEN0EQBEGoBJhtDkbM3sSGoxmEGXXMGdaFZjX9cByIqoI5B1QHaPRgDHetXRMCBk1FGxAEQRCE6o7Z5uCRuZv58/BZQgxaZg/vSrv4SN8LqarrDDdFAZ0JgiJBJzNugYaEN0EQBEGoQKx2J4nzt7D6QBpBei2fD+3KFfWi/CBUAN89Bp/1gjl3Qfoh0Pz9AK6o/ZS7eFoneI5Xj02L+pO5e707NZ7WiVb18Cha1cNjVdUKBI+i5d86m8PJ2C+3snzfGYw6DZ8N6USXBlElrveJliUXvuiHcuIvVEMoDFgEcR2KNxyoqorT6fRIy906b16X4MKr8GaxWDCbzW7XeNKfzJM60aq4OtEKLC1P60Sr4upEK7C0SquzO51MWLyHn3efQa9V+PjBtlxRN7TE56pPtCy5GL4egDZ5A6ohDGu/L3HGdIB/fH5X9ntfdF+6dOmCVqslMTGRxMREt8aoKngV3oxGIyZT2RdTFiVto9Ho1pvmSZ1oVQ+PolU9PFZVrUDwKFr+qXM4VZ5ftINl54Lb1IGd6NkixvdalhxY1B8leSOqKQIGfouh7hV+e13+qnE4HXyw8wMANm7cSHh4eJk9VkW8Cm+KoridnItqyqNOtKqHR9GqHh6rqlYgeBQt39apKjz/7U6+3ZqMTqPwUf8r6NWytu+1zNko8+6BU1vAFIky+DvXo9LL+Kts997isPDs6mf5+fDPbvmqyshRIYIgCIJQTqiqygvf7WbhppNoFPjgwY7c3LqO74UKM+HrByFlOwRFw+DvILad73X8TI41h/G/j2fT6U3oNXKcSRGy21QQBEEQygFVVXn5f3uZv/4EigLv9uvAbe1ifS9UcBbjgvtQUrZDcE14+H8BGdzOFJxh6E9D2XR6E6H6UN7r/l5FW6o0yMybIAiCIPgZVVV5+7fDzPrzBABv3NuOuzrW9b1QXhrMuQPNmT2oITEoQ76HmJa+1/Ezx7KPMerXUZzKP0XNoJpM6T2FWK0fgm6AIjNvgiAIguBn3v31IDPPBbf/3N2Gfp0TfC+SdwZm345yZg9qaG3XjFsABredaTsZvGwwp/JPUS+sHnP7zKVFdIuKtlWpkPAmCIIgCH5k8vKDfLTiEAAv9W3FgG71fS+SmwqzboO0fahhsVgeWgw1m/lex8/8kfwHw38ZTqYlk9Y1WjOnzxziw+Ir2lalQx6bCoIgCIKfmLrqMO/+egCACTc24eGrG/heJOcUzO4LZw9BeF0Y8gNqcJzvdfzMD4d/4MU/XsSu2rkq9ire6/EeIfqQirZVKZHwJgiCIAh+YMbao/x32T4Anr6pGUOv8sMMUvZJmHU7ZB6FiAQY8gNENbjgAN7Kzuzds3l709sA9GnYh/9c8x/0WtldejEkvAmCIAiCj5m77jiv/G8PAON6NSWxRxO3OxJdlqwTruCWdRwi658LbvWLW14FAk7VyXub32PW7lkADGw5kGe6PINGkVVdl0LCmyAIgiD4kK82nuCFJbsAGH1DY57o3dT3IpnHYFZfyD4BUQ1dwS3SD5sg/IjNaWPinxP54cgPADzR6QmGth7q9iHB1RFpTC9aAe1RtKqHx6qqFQgeRcu9usVbknl28U4Ahl3TgAk3N/O9x4yjMKcvSvZJ1OjGMOR711o3Vb10nRevy5d1qqpSYCvg/9b+H2tPrUWraJl49UTubHxn8c8vVie4kMb0ouWXOtEKLC1P60Sr4upEq/Jp/bjrNM8s3o2qwkOd6/J0r4ZYLBafelQyjmBYcB+a3FM4o5tgeXARGGr4pMl8ed37LEsW41eNZ2/WXoxaI69f9TrXxl172TxRdC+lMb00phetAPcoWtXDY1XVCgSPolW2up93pzLh2z04VXigSwKv3tUGjUa5bJ1bWukHYcG9KLkpqDWbowz5HlPohT1RK8P9uBin8k4xesVojuUcI8IQwUe9PqJ9rfZl0ioKb9KYXhrTi1YV8Cha1cNjVdUKBI+idem65XtPM/bLrTicKvdcUZfX725bIrj5xGP6AddxIHmnIaYVyuDvIbSWT1+bv+/9gcwDjPl1DGcKz1A7uDbTek+jcVRjt3QEF7KdQxAEQRA8ZPWBNMbM24LNodK3fRxv3de+1ODmFWf2ug7gzTsNtdu4NidcIrhVRjaf3szDyx7mTOEZGkc25rOen9EoslFF2wpYZLepIAiCIHjAn4fTGTlnE1aHk1ta1+Hdfu3R+ji4KWf2wFf3Q8FZqNMWBn8PwdE+1fA3v5/4nQmrJ2BxWOgY05EPe3yIQTVUtK2ARmbeBEEQBMFNNh7LYPisTVjsTnq1iGHyQx3Ra338kZq6A+OC+1AKzkJsh4AMbt8c+IYnVj6BxWGhe0J3Pr3xU8KN1Xu9mi+QmTdBEARBcIPtJ7MZMW87hTYH1zWtyccDrsCg83FwO7UN5tyJYs5CrdsJZeBiCIr0rYYfUVWVT3d8ykfbPgLgnqb38MKVL6DT6OTIDx8g4U0QBEEQysiu5GxGzttOnsXOVY1qMH1wZ0x6rW9FkrfA3LtQzNk4Y68IuODmcDp4Y+MbfLnvSwBGth3J2I5jZcOBD5HwJgiCIAhlYG9KDoNmbCDXYqdzgyhmPOyH4HZyE8y9ByzZqAndsNw7D5MpwrcafsTqsPL82uf5+djPKCj8q+u/GNByQEXbqnJIeBMEQRCEy3DwdC4DP1tPVqGNdnXDmTmkM8EGH3+EJm2AefeCJQfqXQ39vwI1cJqz51nzeHzF46xPXY9Oo+P1a1/nloa3VLStKolsWBAEQRCES3A0PZ/+n63nbL6VNnHhTB/YnjCTj0PViXUw925XcKt/LQz4GoxhvtXwI2cLzzLs52GsT11PsC6YT3p9UuHBbfXq1fTt25e4uDgURWHJkiWXrbFYLPz73/+mfv36GI1GGjduzMyZM/1v1k1k5k0QBEEQLkJSRgH9p68jLddCizphzBnWlSCt07cix/6A+feDLR8aXg8PLQBDSHGv0srOybyTjF8znqTcJKJN0XzS+xNa12hd0bbIz8+nffv2DB06lHvvvbdMNf369eP06dPMmDGDJk2acObMGex2u5+duo+EN0EQBEEoheSsQh6avo6UbDNNY0KZN6IbUSEGt3t6F1Hqgv2Tm+GX/4Oo+hDfBfq8AfqgS9d4quWHmiNZR3ht82uYtCba1WzHa9e9Rv3w+m6P4w/69OlDnz59ynz9Tz/9xKpVqzhy5AjR0a4jWRo0aOAnd97hVXgr6mnm7vXubhP2pE60qodH0aoeHquqViB4rK5ap3PM9P90HSczC2lQI5h5w7tSI8TgsUdw9QMv0gbA6YBazVAGf4eq0f0d2s4b+4IaT7X8UONQHdQOqc2HPT9Eo2gwao1oFM1l6715nwFycnIu8F3k3Ru+//57OnfuzJtvvsncuXMJCQnhjjvu4JVXXiEoKOjyA5QjXoU3i8Xi9t9ALBaLR+nekzrRqrg60QosLU/rRKvi6kTLf1rpeVaGzN7C8YwC4iNNfD64A+EGij/v3NFSFKVEKCqus1vBmouCiqoxgM5Uan2JGjfwpM6dGqvDSr4tHxUVnUZHkC4IjaLBYrGUKZR5+n4BJCQklPj+Sy+9xMSJE90aqzSOHDnC2rVrMZlMfPvtt6Snp/Poo4+SkZFR6da9eRXejEYjJlPpv3ClUZS0jUajW2+aJ3WiVT08ilb18FhVtQLBY3XTysi3MmLeNo6kFxAXaeLLR64kPirYa48lcFjBnOkKblojmAKr44DZbibXlguAUWskTB9WfC/KMgPm6T0sCm9JSUmEh/99z3wx6wbgdDpRFIX58+cTEeE6nuXdd9/lvvvu4+OPP65Us29ehTdFUdz+5S2qKY860aoeHkWrenisqlqB4LG6aGUX2Bg8cwP7T+dRO9zIFyOuJCE6xCdaRbNaa5NW8OiK8Ze89pNen3Bd/HUlZsI80bpU3abUTczaPYs9Z/eQVpjG+93fp2e9nhet+WznZ/x2/DeOZh/FoDXQqkYrxnYcW2Jjgr/f56Jrw8PDS4Q3XxEbG0vdunWLgxtAy5YtUVWVkydP0rRpU59reopsWBAEQRCqPblmG4M/38DuUznUDDUyf8SVNKh5YXDzCruFzuGNWXHrAtAawRTB3d/fw/3N7qd/y/7Fl0UaI32rWwqF9kKaRTXjriZ38cTKJy57/cbUjdzV5C4aRTTCoTqYvXs2T658km/v+JZgffBl6wOBa665hq+//pq8vDxCQ0MBOHDgABqNhvj4+Ap2VxIJb4IgCEK1Jt9iZ+jnG9melEVUsJ75I7rRJCbUtyJ2K5izCNIaCDLGgSmS0wVnyLJk0TGmIzWDavpW7zJcF38d18VfV6ZrVVXlzevfxOJwPbYMM4TRPLo5N3x1A3sy9tC5dmd/WvWYvLw8Dh06VPz10aNH2bZtG9HR0dSrV4/nnnuO5ORk5syZA0D//v155ZVXGDp0KJMmTSI9PZ1nnnmGYcOGVapHpiDhTRAEQajGFFodDJ+9kU3HMwk36Zg7vBvN6/j4cFyH7e/NCbogFFMEKAr7MvYB0KpGK7eHnL5jOtN3Tr/kNZ/0+oTOdbwLVk7VSY4lB6vTioJCuCEco85IWkEaABGGytu6a9OmTfTo0aP46yeffBKAIUOGMGvWLFJSUjhx4kTxz0NDQ/n1118ZO3YsnTt3pkaNGvTr149XX3213L1fDglvgiAIQrXEYncwduEO1h3JINSoY87wbrSp6+Mwcuh3iO98LriZ4FxwA9iTsYeY4BhqBNVwe9h+zftxc4ObS/1Z0W7PmOAYz33jajCfbc3G7rSjoBBhjMCgdR2X8tbGt7gi5gqaRlWedWD/pHv37pfc+Tpr1qwLvteiRQt+/fVXP7ryDRLeBEEQhGqH1e7k8a93sebgWYINWmYN7UKHhEjfiuz6Bta8C0OXuXaVGko+it17di+toi896+ZwOtBqtBd8P8IYQYSx9KDpyRl0/8TutJNtycahOtAoGiKMEeg1rpZg/1n/Hw5kHmB2n9le6wieIeFNEARBqFbYHE7GL9jKygNnMek1zBjShc4Non0rsnMRLB4JtVqAVl/qOW57M/ZyT5N7Lvj+6N9G0yyyGdvTtnNXk7u4q8ldF1zjz8emNqeNbEs2TtWJVtESaYwsDpCvrX+NlUkrmXXLLOqE1PFJUBTcR8KbIAiCUG1wOFWeXLidn3afRq9VmDawE1c1dv+x5SXZ/hUsGQ2qE1rcXmpwyzJnkZqfSssaLS/42aHMQ1wbdy2zbpl1UQl/PTYtCm5Fh+9GGCPQKlpUVeW19a/x+4nfmXnLTOLDKtfuy+qGhDdBEAShWuB0qkxYtIMftp9Cr1X4oF9brm9Wy7ci276EJWMAFa4YAt2fc61x+8cM1Z6zewBoGV0yvOVac1EUhYGtBl5yVsvbx6YFtgJO5P69WD85L5kdaTvQarTEBMdg0BhYenQpK06s4LObP+M/6//Dj0d+5IOeHxCiDyG9MB2AEF0Ipot0hxD8h4Q3QRAEocqjqir/XrKLb7acRKtRmPxgR7o3ifStyNZ58N1jgAqdh8Gt74BGU+qlezP2Em2KpnZI7RLfP5R1iA61OvjWVynsPrubYT8PK/76rU1vAXBT/Zt48aoXCTeEk23JJik3CYCv9n8FUKIG4JWrX+HOJnf63a9QEglvgiAIQpVGVVUm/bCHLzecQKPAew904JY2ddzuzX1JtsyB78cBKnQZCbe+VbyrtDSGtx3O8LbDL/j+wcyD5bKDs0udLuwcshNVVSmwF5BvywcgSBdEqD4URVF4tMOjPNrhUQB2DtlZ6jiy5q1i8Cq8FfUnc/d6d99sT+pEq3p4FK3q4bGqagWCx0DXUlWV15ftY9afxwB489529G0X61utzbNQ/ve46+ddR8Et/y26+IJaRVEuqXk46zDdYrsVX1OWmov5LEtdni2PQnshAMG6YEL0IcX1vtY6/3pP773gwqvwZrFY3P6bi8Vi8aiZryd1olVxdaIVWFqe1olWxdWJVtnqJq84wvQ1xwCYdHtzbmtds/hzyxda2q2zMPzyLAD2zo9g6z4RzjVQB1c/Tncapz/b9Vm3/XiCqqrk2nKLuyaE6kMxab1fu2axWMoUsjy591nLlwPQpUsXtFotiYmJJCYmeuQz0PEqvBmNRkymsr/ZRUnbaDS63WTX3TrRqh4eRat6eKyqWoHgMZC1Pl5xiCmrjwHw4u2tGHxNA99qbfwM5VxwU696DO2Nr6D1IAyWNyoq2dZsbE5bcdeEosN3vaUsQdXde6+qKhkzZpL2lmtd3saNG/3SmD6Q8Cq8KYridnIuqimPOtGqHh5Fq3p4rKpageAxELWmrz7C278cAODZPi0Ydm1D32ptmIby07lZsmvGo/SedMk1bkWPFovqy4InNZeru1TXBF9rXYqy3nvVaiV14iSyFy++4DF0dab0bTCCIAiCEKDM+esY//lxLwBP3tiM0Tc09un42o3nBbdrn4DLBLfKgt1pJ9eai6qq6DV6Ik2RGLSGirZ1UeyZmRwfNswV3DQaak14pqItVRokvAmCIAhVhgUbTvDid7sBSOzRmLE9m/hW4M8PMfz+kuvP1z0NvV4KiODmcDqwOCzoNDpMOlOJdleVEcuhQxzr9wCFmzajCQ0lYdo0ovr1q2hblQYJb4IgCEKVYPGWZJ771nWkxfBrG/L0Tc3dfiR6Sda+h/LrCwCo10+Anv/nVnCznLeRwZ81/6zbkbaDwcsGM+jHQbz050tYHVY0yoUf/77Q8gV5a9Zy7MGHsCUloU9IoMGCLwm97lqfagQ6Et4EQRCEgGfZ7tM8s2g7qgoDr6zH/93W0rfBbc078NtEAGzXPAU9nnd7xs2TDQGebiIoqvv52M88/NPD7EjfQZQpiklXTyLKFOUXLV+QMX8+SaNG4czLI6hzJxos/ApjEx/PnlYB5JBeQRAEIaD5Zc9pnvlmD04V+nWO5+U72vg2uK16C1a8CoDa/Xns3cYFxIfngn0LeH3D66io3Fj/Rl6/7nWM2rIfW1KeqHY7p197jcwvvgQg4u67qTNpIhpD5V2TV5EEwu+fIAiCIJTKyv1nGPvFVhyqyp0d4nj9nnZoND4Mbiv/Cytfd/255wtw3VPgy84MfkBVVT7d9Smf7fkMgAeaP8BzXZ9Dq9FWsLPSceTkkPz4E+T/+ScoCjFPPUn08OG+DeBVDAlvgiAIQkDyx6F0Rs3djNXh5OZWtXj7vnZofRXcVNUV2la94fq690TXztJKflyFw+ngP+v/w9cHvgbg0faPMrr96EobhKzHj5M05lGsR46gBAdT9603CevVq6JtVXokvAmCIAgBx4ajGYyYvQmL3UmvljG8dU8rdFofLeNWVVjxH1jtOhSWG1+Ga8b7Zmw/YnVYeXbNs/x6/FcUFJ7v9jwPtniwom1dlIING0keNw5Hdja6OnVImPIJppYtK9pWQCDhTRAEQQgotp7IZNisjRTaHFzfrBYf9++Iarf5ZnBVheUvw9p3XV/f9B+4+jHfjO1H8qx5jF8xng2pG9Br9EzqNonbm95e0bYuSu6SJZx97TWw2TG1a0f8Rx+ij4mpaFsBgzSmF62A9iha1cNjVdUKBI+VTWv3qWyGzNxAnsXOVY1qMHXAFRi0Gsw2H2ipKiyfhPLH+64vb34Nrny0xKPSynY/AM4WnmXM8jHsy9hHsC6Y97u/T/uo9pXyfVYdDs688y6Zn38OQFifPsS+9h80JtNlx/DlrtZARxrTi5Zf6kQrsLQ8rROtiqurjloHzuQxZNZWcsx2rkiI4MMHWqM4bVgsPtBSVXQrX0G/4RMArL1fxdFhWKmbEyrL/QBIzktm7OqxnMw7SZQxiveve5+W0S0xm82V7n125ueT9vy/KVy9GoCIR0YSOXo0VijTJpCi8+SkMb00phetAPcoWtXDY1XVCgSPlUXr8Jk8hs3dRlahjXbxEXw+rCvhJr1vtAB+fQHlXHBT+7yFvutISus/UFnuB8D+jP2MWTGG9MJ04kLjmNZ7GvXD61fK99l26hQpjyZi2b8fxWCgxqSJ1LjzTre0isKbNKaXxvSiVQU8ilb18FhVtQLBY0VrHT+bz4AZ6zmbZ6VlbDhzhnUlIshw2boyaQHKL/+Gda7gxm3voHQZ4fPX5ZXHUmo2pm5k3O/jyLPl0SyqGVN7T6VWcC2/aHlbV7htG0mPjcWRno62Zk3iP/wQpUVzj/wJLqTDgiAIglBpSc4qpP/09ZzOsdA0JpR5w7sSGeyjg1tVFX569u/gdvt7cJngVhlYfmI5o38dTZ4tj061O/H5LZ+XCG6VieylSzk+eAiO9HSMzZvTcOFXBHVoX9G2Ah7ZbSoIgiBUSk7nmOk/fR3JWYU0rBnC/JHdqBHqow4Bqor+t3+jbJnp+rrvB9DpYd+M7Ue+OfANL697GafqpEdCD968/k1MurIvXyovVFUl/aOPSf/4YwBCe/Qg7q230IaGyMYDHyDhTRAEQah0pOdZ6D99HcfPFpAQHcQXI7sRE+ajkKKqsGwCui0zUVFQ7pgMVwz2zdh+QlVVPtv5GZO3Tgbg7iZ38+JVL6LTVL6PcafZTMrzz5Pz4zIAoocNI+apJ1G0lbPDQyBS+d51QRAEoVqTmW9l4GfrOZyWT2yEiS9GXElsRJBvBnc64cenUTbNQEWBOz6EKwb5Zmw/4VSdvLXpLebvnQ/AiLYjGNdxXKVcA2ZPSyMp8THMO3aATkfsxJeIvO++irZV5ZDwJgiCIFQacsw2Rszbzr7UXGqFGfli5JUkRAf7ZnCnE5Y+CZs/R0XBduv76DsO9M3YfsLmsPHSmpdYdsw1i/WvLv9iYKvK6dm8bx9JYx7FnpKCNiKCupMnE9Kta0XbqpJIeBMEQRAqBXkWO6Pmb2dncg7RIQa+GNGNhjVDfDO40wn/exy2zAYUuGsKjuZ3lXocSGWhwFbAk2ufZP3p9egUHa9c+wq3N6qcXRNyf/+dU89MQC0owNCwIQlTp2CoX7+ibVVZJLwJgiAIFU6h1cGI2ZvYdjKHiCA984Z3o2ntMN8M7nTCD+Ng61xQNHDXVGjXr0wHw1YUmeZMHl3+KLvSd2HSmXiv+3tcW/fairZ1Aaqqkj1nDpnvfwCqSvBVVxL//vtoIyIq2lqVRsKbIAiCUKGYbQ4embuJ9UczCDVqmT20C63ifHQIq9MB34+DbfNcwe3uT6Hd/SVaXlU2UvJSeOTXRziWc4xwQzif9PqE9jH+P17D3TV0qs1G+pSpFPz2K8amTQi7+RZqPjISRV+Z5zOrBhLeBEEQhArDaneSOH8Law6mE2zQ8umADrRPiPTN4E4HfPcYbP8CFC3c8ym0rdyL5w9nHeaRXx/hTMEZagfXZvL1k2lZq2W5aBuNZT+GRXU6UW02agx9mBrDhqIYDCh6faXcRFEVkfAmCIIgVAh2h5PxC7ayfN8ZjDoNM4Z0pkOcr9a4OWDJo7BjgSu43fsZtLnHN2P7iW1ntpG4PJEcaw6NIhoxtfdUIrWRFW3rAlS7HUdeHqrDgaIoaEJCJbiVM16Ft6KeZu5e7+4BfZ7UiVb18Cha1cNjVdUKBI/+0nI4VZ5auJ1lu1IxaDVMG9SJbg2jMZvN3ms5HfDdGJQdC1EVLdw7A1rfVeJRaWV7n9ckr+GplU9hdphpW7MtH/f8mAhjhG/uRykUbNzE2ZkzsezejT0tjbofTia0Vy8URSm1rmDzZtLeeRfLkSOohYXo6tQh4s47qDlqFKpGU6zrK38XqxNceBXeLBYLZjcXfFosFo/SuSd1olVxdaIVWFqe1olWxdUFspZTVXnh+318tz0FnUbhvftb061eGBaLxXstpx390nHo9ixG1eiw3jEVZ+NbSt2cUFne52XHl/HyhpdxqA6uqnMV/736v5gw+eZ+nENRlBKPRZ2FBZiaNyfy7rtJHj/+suNpgoKIuP8+9HXrojGZMO/ew5m33kJXsyYR999/gfblgpanv4cAXbp0QavVkpiYSGJioltjVBW8Cm9GoxGTqewnXhclbaPR6Nab5kmdaFUPj6JVPTxWVa1A8OhrLVVVefH73SzeloJGgfcf7MCtbWN9o6XXoix5DOVccOO+mRha3lEur8vTurl75vLWprcAuK3hbbx8zcvoNXq/ewy9/npCr7++zGMa6tVDV8vVP1VjNBLUrh35f/5JwabNF4S3y62d8/R1FYW3jRs3Eh7uow0tAYpX4U1RFLeTc1FNedSJVvXwKFrVw2NV1QoEj77SUlWV15ftY966EygKvNOvPbe3i/ONlupA+TYRZfdi0OhQ7p8NLS99JlpFvs+qqvLBlg+YsWsGAANbDuSZLs+gUTQV5rHo2hJh2+nEkZODarUCoAkJQRMcjGXvXgq3baPWuHGl1vnTnyAbFgRBEIRy4t1fDzB9zVEAXr+7LXd3jPfNwA4b+u/HoOz/ATR66DcbWtzmm7H9gN1p5+W/XubbQ98CMP6K8QxvM7zShRPV4cCRlYXqcACgDQ/n8M234MjIQHU4qPlYIpH3V+7du1UVCW+CIAiC3/l4xSE+/P0QAJPuaM2DXev5ZmCHDRaPQLf/B1SNHuWBudC8j2/G9gNmu5l/rfkXK5JWoFE0vHjli9zb7N6KtnUBTqsNZ3Y2qupE0WjQRkSg6PXUnz8PZ34Bhdu3kfbOuxjq1SP8tsoblKsqEt4EQRAEv/LZmiO89fN+AJ7r04IhVzfwzcAOGywahrL3e1StAfrNqdTBLc+axzOrnmHz6c0YNAbevOFNetXrVdG2LsBpNuPIyQFA0elcwU2rBcAQ75otNTVvhuPsWdI/+ljCWwUg4U0QBEHwG/PWHefVpXsBeKJ3M0bd0Ng3A9utsGgo7PsfqtaA9e4ZGJrd4pux/UB6YTqjVo7iYNZBQvWhTO45mS51ulS0rRKoqopaUICzoAAAjcGIJjwMRaO56PXOc2vh/I3d5mD1ggPlohUISHgTBEEQ/MK321J44TtXcBvTvTHjejXxzcDnBTe0RnhgHs6E63wzth9IyknikV8f4WTeSWqYajD1xqm0iG5RoZ6c+flYT5wo/tp2MpnCzZtRTCb0tWtzduZMHBmZ1H3zDQAy5s9HHxuHsVFDAAo2byFj5udEDRjgd6856YX89OkuThxK9btWoCDhTRAEQfA5P2w/xf997wpuQ69pwISbm/tmQb7dCl8/DPuXuoLbg19Ak16Vtsn8vox9jP51NGfNZ6kbUpdPb/qUeuE+Wu/nBYW7dnNiyJDir8+84QppYbfcQtzrr+HMysaekvJ3gVMl7b13sZ5MRtFq0ddLIOapJ4no18+vPo/vPsuvM3djybdjCpaeqUVIeBMEQRB8yk+7Unli4XacKjzUNYEXb2/lw+A2BPb/6ApuD30BTXpX2ibzG1M3Mu73ceTZ8mge1Zz3rn2P+DAf7bD1kpBuXWm5by+qzYYjOxvV6URRFDQREWgMBuL++3qJ66MHDSR60MALxvFX1wPVqbJp2TE2/O8oqBBTP4yrHqrH2I/9IhdwSHgTBEEQfMaK/WcY++UWHE6VO9vX4dU72/gouFlg4RA4sAx0pr9n3Copy08sZ8KqCVidVjrV7sTkHpPROyvXzJHTYnFtTFBVFK0WzXkbEyoSc76N32bt4fjOswC0vr4u193flLyC3Ap2VnmQ8CYIgiD4hD8PpTN67mZsDpXb2sby6h3N0Wh8FdwGw4GfXMHtoS+hcU/vx/UTiw8uZtJfk3CqTnom9OTNG97EoDG43U7SX6iqilpYiCMvDwBFr0cbEQGV4Jy5tKRcfpq2k5x0M1q9hhseak7Lq2Mr2lalQ8KbIAiC4DWbjmUwfPYmLHYnN7aqzXsPtMdh88FORJsZFg6Cg7+cC24LoHEP78f1A6qqMmPXDD7Y8gEA9zS9hxeufAGdRldpmqqrqoozPx+nxQJaLRqjEU1ISEXbAmDfXyms/GI/DpuT8JombhnVlloJYRVtq1LiVXgr6k/m7vXu/hJ7Uida1cOjaFUPj1VVKxA8lqVme1IWD3++kUKbg+ub1uTDhzqg0yjYvdWym+GrQSiHfkXVBUH/BdDwhgvWuFWGe+hUnby96W3m7Z0HwPA2wxnXcVxxK6zK4BFVRTVbQFXRGIwoRgOK/sJHuZ4GzbLW/dOfw+ZkzdcH2bPmFAD12kTT++FWmEL0JcasLAG4MuBVeLNYLG5PA1ssFo/WP3hSJ1oVVydagaXlaZ1oVVxdZdHal5rLw7O3kmex07VBJO/f3xrVbsNi91LLbsaweCjaoytQdUFY75uLM7bbRXeVVuQ9tDvtvLLxFZYdXwbA4+0fp3/z/sWN1CuDR9vx46RPehny81BMQUSNH4epUyc4z6PFYrlsU/mLaRXVlTVgFfnLy7Tw+6z9pJ/IBwWuuCWB9r3rgsaB2ey4oAagS5cuaLVaEhMTSUxMdNtvVcCr8GY0GjGZTGW+vihpG41Gt34ZPakTrerhUbSqh8eqqhUIHi9Vc/B0LiPmbSfbbOeKepHMfLgrIUad91paFWXRcJSjK1D1wdD/KwwNLn6OW0XewwJbARP+mMDa5LVoFS0vX/0yfRv3rVQe89evJ2X8eJzZOehiY4l/801MzZtfUON0OjEYDG5ruVtX5C/taD6/ztyLOc+GMVjHjcNaUa91jYvWFYW3jRs3Eh4eXmaPVRGvwpuiKG7/jaCopjzqRKt6eBSt6uGxqmoFgsfSao6l5zNwxgbO5ltpWzeCWcO6EmrSX7buslp2M8o3w1EO/w76YJQBX0ODa8vtdblTl2PNIXF5ItvTtmPSmnin+ztcH399pfKY/c03pEycBHY7pvbtSPj4Y3Q1a/pFq8zhzamyY/kptvx4AlWFWvXCuOWRNoTXDLqsjuBCNiwIgiAIbnEys4ABn63nTK6FFnXCmDOsK+EmHxyDYSvEsPhhlGOrQB8MZQxuFcHpgtOM+W0Mh7IOEWYI45Nen9AhpkNF2ypGdTg489ZbZMz8HIDwW28l9rX/oHHjaZk/sBTaWT5rD0e3pwPQ8ppYrn+wGTp9xR9REkhIeBMEQRDKTGq2mQGfrSc5q5DGtUKYO7wbUSEG7we2FcKC/miPrULVh5ybcbvG+3H9wPGc44xbM46U/BRigmKYeuNUmkY1rWhbxTjz8znz1NMUrloFQM3ERGo+lljhM1dnk/NYNnUn2WmFaLQK1z/YjNbX1a1QT4GKhDdBEAShTKTnWRjw2TqOny2gXnQw80dcSa0w9xe4X4C1ABY8hHJkpWuNWyUObrvTdzNmxRiyLFnUD6/PtBunUTe08gQQW2oqSWPGYNm7D8VgIPa114i4/baKtsWBDamsmLcPu9VJaLSRnkOaEd+s9Me3wuWR8CYIgiBclqwCKwM/W8/htHziIkzMH9GNOhE+eARnLYAvH4Sjq1ANoVjvn4+h/tXej+sH1qWsY/zv4ymwF9CqRis+6fUJNYIuvsC+vCncuYuTjz6KPS0NTXQ0CR99RPAVHSvUk8Pu5I9vDrFzxUkAElpF03toSxSds0J9BToS3gRBEIRLkmu2M2Ledval5hITZmT+yCtJiA72fmBrAXz5ABxdDYZQGLAIZyVaN3Y+vxz7hWfXPIvNaaNzTGc+7PUhoYbQirZVTM5PP3Pq2WdRzWaMTZtS8/33CGrUqEI95WdZ+OnTXaQeyQag860N6HJ7QxSFStNtIlCR8CYIgiBclHyLnVFfbGdHcjbRIQbmj+hGw5o+OJHfmg9fPADH1riC28BvIOHi57hVJAv3L+TVda+ionJj/Rt5qfNLhOgrR1cCVVU5++l00t57D4CQ668j7p13sOkq9uM9+UAmP3+2m8IcK4YgHb2HtqJhO9djUjls13s0FW1AEARBqJyYbQ4embuZrUnZhJt0zB3elaa1fdCuqERwC4OBi6Held6P62NUVWXq9qm8su4VVFTub3Y/b173JgatDzZo+ACn1UrKs88VB7eowYNI+OQTtKEVNyOoqipbfz3Bd+9vozDHSo26odz/XOfi4FaerF69mr59+xIXF4eiKCxZsuSS169cubLEsSdF/+zbt698DLuBzLwJgiAIF2CxOxg1dzN/Hj5LiEHL7GFdaR0X4f3A/wxugxZDQlfvx/UxTtXJGxve4It9XwAwqt0oEju4TvO3YatIawDYMzM5+dhYCjdvBq2WOv/3b6IeegiouJktq9nO73P2cXjLGQCadatN9wEt0Bsq5hiQ/Px82rdvz9ChQ7n33nvLXLd///4ShwDXqlXLH/a8QsKbIAiCUAKbw8m4L7ey6kAaQXot0wa0p0NCpPcDW/Nhfj84vrZSBzebw8a///g3y4662l092/VZBrQcAFSOR36Ww4dJGj0GW1ISmtBQ6r7/PqHXVuzu3MzUfH6atovM1AI0WoVr729KmxvqVujxJH369KFPnz5u18XExBAZGel7Qz5EGtOLVkB7FK3q4bGqalVGjw6nylMLt/Hz7tMYdBqmDbqCK+JDvdey5sMX/VCO/4FqDHetcYvvUqLJfGW4hwW2Ap5a9RR/nPoDnaLjlWte4bZGtxVfV9Ee8//4k+QnnsCZm4s+Pp74KZ9gbNKkxDWeap3/b3fqTh3IZsuykygahVoJoVz3YDPqNIq46Hje3EOAnJycEt83Go0e9WS9GB07dsRsNtOqVSv+7//+jx49evhsbF8hjelFyy91ohVYWp7WiVbF1flDy6mqvPD9Pr7fnoJeo/DB/W3okhCG2Wz2Tsuaj2HRALRJ61ANYVj6LUCt2bbUzQkVeQ+zLdk8sfYJdp3dhUlr4o2r3+Cq2Ksu+JyrKI85Xy8i4403wOHA2LEDMW+/gxodVerncGlal+pFriiK2z1UAZwOlYRmNUloVhNFo6DVKVisl88Gnt4LgISEhBLff+mll5g4caJbY5VGbGwsn376KZ06dcJisTB37lx69erFypUruf76i7c9Axg+fDjDhg3jmmvKZwZUGtOLVkB7FK3q4bGqalUmj6qq8uL3u1m8LQWNAh881IFb2sR6r6XYUL4ZiJK07tyM22KM8Z3L7XWVtSY1P5UxK8dwOPswEYYIPur1Ee1rta8UHg06HWlvvU3mnDkAhN9xB3VeeRmNofSNE556dAdVda1xc9pds2F6gwadwbUH8nK5wFN/ReEtKSmpxJo0X826NW/enObNmxd/fdVVV5GUlMTbb7992fD2+eef89VXX7FkyRJ69+7tEz+XQhrTi1bAexSt6uGxqmpVBo+qqvL6sn3MW3cCRYF3+rXn1rZx3mvZClzB7cRfYIxAGfQtxHcqt9dV1ppjOccY9esoV7ur4Bg+vfFTGkc2rhQe1YICkv/9f+Sfa3VV6/HHqTHqkcuO4a6WqqrF116uxmF3YimwozpVUMAQpEOn1/j997fo2vDw8BLhzZ9ceeWVzJs3r8zX33HHHSxZsoSbbrqp1J/v3r2b1157jfnz53vlS44KEQRBqOa899tBpq85CsBrd7fl7o7x3g9qzcPw9YDi4Mbgywe3imB3+m6GLBtCSn4KDcIbMLfP3EsGt/LElpxMytCh5K9ahWI0Uvf996k5epRPZtNOHcxk6cfb+fxfa/l49O8c2ZZ22RpVVbFZHBzfdZZZz67l+w+2ERSqR6evulFi69atxMbGlunamTNnUqdOHe666y6WLVtW6jV5eXksWLDAa19V944LgiAIl+WTlYeYvPwgAC/1bcVDXet5P6glF+bfj/bkuUelg7+FupUvuG04vYHhvwwn05JJ6xqtmd1nNnGhcZcvLAcKt2/n2IMPYjt4CG3NmtSfN5fwW2722fg2i5Ma8aFc/2CzMl2vqirWQjt5mWbWLjxIXJNIFK2CoqnYZveXIi8vj23btrFt2zYAjh49yrZt2zhx4gQAzz33HIMHDy6+/v3332fJkiUcPHiQ3bt389xzz/HNN9/w2GOPlUmvQYMGrF69mri4OO655x6WLl3q89dUhBwVIgiCUE35/I+jvPnTfgD+dUsLhl7T0PtBzwU35cRfruA2aEmlDG6/HP+F59Y8h81po1tsNz7o8UGl6ZqQs2wZp559DtViQd+sGfWmTsEQ59tQWb9NDeq3KVtfVqfD9ZjU6VD5c/FhmnSOQavXcHR7uk89XY5DG9e5df2mTZtK7BR98sknARgyZAizZs0iJSWlOMgBWK1Wnn76aZKTkwkKCqJ169YsXbqUW2+9tcya8fHxrFq1ih49enDvvffy9ddf07dvX7d8lwUJb4IgCNWQBRtOMOmHPQCM69WUMd198KjQkgvz7oOkdaimCCz9vsJY9wrvx/Ux/2x39d/r/lspuiaoqkr6lCmkT/4QgJDu3anxn1fRR0dXmCe7zYGlwA4qHNp0mvwsC31GtWHTj8fKzYPNbGbFnOls/Ol/btV17979kseRzJo1q8TXEyZMYMKECZ5YLEHdunWLA9z999/PV199xZ133un1uOcjj00FQRCqGUu2JvPctzsBeOT6RjzRu6n3g54X3DBFwKDvUGM7eD+uD1FVlWnbpxW3u7q70d2Vpt2V02rl1L/+VRzcoh9+mPiPPkQTHFwhflRVxWq2Y8l3BbfcTDObfz7OTcNbo9GWX3Q4c+wI8557nJ3LfwY/7Zz1B7GxsaxatYpGjRrRr18/Fi9e7NPxJbwJgiBUI37Zc4anF+1AVWHQlfV5rk8L7xfA/zO4Df4O4jr4xK+vcKpO3tj4Bh9t+wiAR9o+wrOdnkWrqZjWTedjz8jgxMNDyfn+B1erq0mTqP3sv1C0FeNNdapY8u3YzA4ANHoNqxccoGvfRkTWLp8wqaoqW5Z9zxf/fpKMUycJjYrmzqf/r1y0fUXt2rVZuXIlTZs25aGHHmLRokU+G1semwqCIFQTft93hqe/2Y3DqXJfp3gm3dHa++BmzoH590HSejBFwuAlENexROeEisbmtPHCHy+w9IhrAfmzXZ+lf4v+bh8y7w8shw65Wl2dPIkmLIz4D94n5OqrK8yP06GWOAbEGKTDYXeSdjyX1UkHWL3gAHCu24EKUxJX0ndse+JbRPnMQ0FONj9PeZ8jWzYC0KhTV24ePR5b5fmVuoCaNWuW+v2YmBhWrlxJjx496N+/P4mJiT7Rk/AmCIJQDfjzUDpj5m/B5lS5vV0sb9zbDo23OwUvCG6Vb8atqN3V2uS1rnZX177C7Y1ud7s1kz/I++MPksc/jjMvD31CAgnTpmJs1KjC/NitDqxmB6igaBSMITq0Wg1anYYHXyjZg3bXqmRO7s/k5pGtCa8Z5DMPx3duY9nH75KfmYFWr+eGgcPocPPtKIpCdna2z3R8zZkzZ3A6naX+rGbNmqxcuZJevXoxefJkn+hJeBMEQajibDqWwfDZm7DanfRqXpN3+7VHWw2CW7Ylm8TliWxP245Ja+Ld7u9yXfx1FW0LgMwFC0h95VVwOAjq3In4Dz9EF+W72avLYTXbyU4r/NtPagF6oxZjsJ6IWkFs+fk4BdlWeg9thaJRqFE3tER9UJgerV5zwfc9xWG388fCeWz8/htQVWrE1+O2cc9Qq74PdkCXExrNxVei1ahRg99//53evXuzfft2r7UkvAmCIFRhdpzM4uHPN1Joc3B905q8e18b9N4uODfnwLx74eSGShvcTuefZvRvozmUdYgwQxif9PqEDjEdKtoWqsPBmbfeImO2q9VVxJ13XrLVlb9IO57Lkve2Fn+9/rsjADTtUpsbh7WiMMdKbkb5PFbOSk1h6eQ3ST3sOm+wXe9b6D54BHpj2dtvBgLR0dGsXbuWv/76y+uxvApvRf3J3L3e3elqT+pEq3p4FK3q4bGqavnb496UHAbN2ECexU63htFMGXAFitPmnZYlB+bdh3JyA2rRGrfY9hescavIe3885zijfh3FqfxTxATFMKX3FJpGNS0xbkW8z468PE7+3wvFra5qPj6eGo+4Wl2VNp4/PcY1i2T0h90xF9hApXh9m/Zct4SeQ1oWj1UaXW5vSJfbGxZfc7HXcDl/e9as4PeZU7AWFmIMCeWmUWNp2vXqUrUrw6NubwkODqZXr15ej+NVeLNYLG4v+LRYLB4tkPWkTrQqrk60AkvL0zrRqri6y9UcSc9n8KwtZBfaaB8fzscPtEGj2jF7o2XJxbjwQTSnNqOaIrE8sBA1qgVc5HOgIu79/sz9jFs9jkxLJgmhCXx4w4fEBcWV+llVnu+XPSWF1HHjsR86hGI0UvOVVwi5sXdxs3VfapVWpyhKcQN3VVWxW51/7ybVKhiCdT47icNisVw2aOVlZ7F8+jwO/LkagNhmLek9ahxhNWpeNFcU3asuXbqg1WpJTEz02QaAQMOr8GY0GjGZyj6tWZS0jUaje415PagTrerhUbSqh8eqquUvjycyChg+dztn8220jgtnzrBuhAfpvdNSzSiL+qOcC24MXoLxEue4VcS935G5g/Erx5Nvy6dFdAum9JpCjaDSuwiU5/tVuGMHKY8m4jh7Fm3NmsR/8jFBbdv6ReuydSpYCx04bK7F9TqDBkOQrrjOFxSFxIuRcugASye/Sc6Z0yiKhivve5Bud/dDc5ljW4rC28aNG8utMX1lxavwpiiK238jKKopjzrRqh4eRat6eKyqWr72eCqrkAGfrSc1x0yz2qHMHd6NiGDDZesuqWXNRVk0AOXkRjBFopRxjVt53vtVp1bxf3/9H1anlS51ujC5x2RCDZdeTF8e71fOTz9x6l/PulpdNW3qanVVt65ftC5X53Sq2MyuNleKVkFv1KLTa1AUpfjRZ1FtWXGnTnU62fS/b1m7YA5Oh4OwmrW4dezTxLdoXebXJLiQDQuCIAhVhDO5ZgZ+tp6TmYU0rBnCvOHdiA7xciG8ORvjwodQTm2utJsTvj34LZPWTcKpOumZ0JM3b3gTo/bSsz/+RlVVzk6bRtr7HwAQcsMNrlZXNcrWT9TXHNmeRu364a7AZlDQGbTeHxXjBnmZGfz0yXsc3+HaJNGoczduGf04QWFh5eahKiHhTRAEoQqQmW9l0GcbOJKeT93IIOaP6EZMuJe79czZMP++4jVuZZ1xK09m7prJe5vfA+DuJnfz4lUvotNU7Eeb02ol9YUXyf7uOwCihwyh1jNPY7HZyt2Lw+Hkr8WH2b48iZBIA/Va1+Dqe5qUGtwsFstlH3mWxuXqjmzdyE+fvE9hTjY6g5EeD4+kyVXXYwry3flw1Q0Jb4IgCAFOdqGNQTPXs/90LrXDjXw58kriIr38YDRnw7x7UU5u/HtXaSUKbqqq8u7md5m1exYAg1sM5qkuT13yrK3ywJ6ZycmxYynctNnV6uqF/yPqwQdd68nKObwVZFv4ZcYeTh3MAqB5t1i63dHwor1JPV3zdrE6u83Gmi9mseVHV4itVa8Bt43/F9F14ytFd4uKoGfPnsTFxfH888/TqlUrj8eR8CYIghDA5FvsDP18A7uSc6gRYmD+iCupV8PL/pPnghvngpvlgYWX3JxQ3tiddib9NYklh5YA8FSnp3ig8QMVvibKcuSIq9XViRNowsKo+/57hF5zTYV4OX00l5WzD5CfbUVv0tJ7SCsadaxVbvoZp07yvw/eJO2Y6/y4jn36cn3/oegMhipx5IenrFy5EoAFCxbw0EMPMXfuXI/GkfAmCIIQoJhtDkbM3sSWE1lEBOmZO7wbTWK8PPH+vOBW1KtUjWrhE7++wGw3M2H1BFYkrUCraJl49UTubHxnhc/k5P/1FyfHP44zJwd9fDwJU6dgbNKk3H2oqsrOlSdZ+/UhVKdKVGwIfUa1IapOSLnp71r5K79/Pg27xYIpLJxbxoyncadu5aJf2XE6neTn57Nq1ariIOcJEt4EQRACEKvdyfgvt/DXkbOEGnXMHtaVVnFeHp9wQXD7znUAbyV5xJVrzWXc7+PYdHoTBo2Bt254i571elb4TE7mwoWkvvwK2O0EdexI/McfoYuOLncfNquDlfP3cWD9aQAad4qh56AWGEzl81Fvzs/jt+kfs/+vNQDUa9OOPolPERpdMZs0KishISHceuut3HrrrR6PIeFNEAQhwLA7nDy9eDcrD6Rh0muY+XAXOiREejdoacEtrsMFnRMqivTCdMb8NoZ9GfsI1YcyuedkutTpUqGeVIeDM2+/Q8bnnwMQ3rcvsa++gsaDRf/ekp1WwLKpuzibnIeiUejStx6dbm7o1hpATx87K4rCmWNHWPPlLM6eOIGi0XDNA4Pocsc9lz27rapRWFhIkyZNmDp1Kn379vWbjoQ3QRCEAMLhVHl60Q5+3ZuGQath+uDOdG3o5SzPxYJbJeFk7klG/TqKE7kniDZFM7X3VFrWaFmhnpz5+Zya8C/yfv8dgJpjH6Pmo49WyLq7YzvS+fXzPVgL7QSF6blpRGtq1Aty24snO00BdFoNkbVj6fv4s9itVvIyMqjdqLFHYwU6QUFBFBYWEhLi38fUEt4EQRACBFVV+fe3O/lu2yl0GoWP+nfkuqZeLkIvbjJfOYPbwcyDjPp1FGmFadQNrcu0G6dRP7x+hXqynz5NyhNPYNm7D8VgIPb114i47bZy9+F0qmxcepRNS48BUKdRODePbEtIpKFc1gA6nQ6shYU47XYAdAYjwRGRhERG+V27MtOrVy9+++03evbs6TcNCW+CIAgBgKqqTPphDws2JqFR4I27W3Fjq9reDWrOgXn3VNrgtu3MNh5d/ii51lyaRDZh2o3TiAmOqVBP5t27SRk9Bkd6OtroaOI//ojgjh3L30e+jV9n7ubE7gwA2naP55r7mqDVacplDaDdasVSkI/qdIKiYAwOQWcw+G3mUVVV8rec8cvYvub555/n3nvvxWQycc899xAbG3vBfYn2ck2kV+GtqH+au9e7+4vlSZ1oVQ+PolU9PFZVLXfq3vp5P7P+PAbAf+9pS5/WNb3TsuRceI5bbPsL1rhV1L1fk7yGp1Y+hdlhpn2t9nzU8yMijBGljlde73Pur79xasIEVLMZQ5MmxJ9rdVWWMXzpMS0pl5+n7SLnrBmdXsMNA5rTvFudC2oupXVy7y42/bCY00cPk5+ZwR1PPU/jzlcWt8r6J0m7d/L1K89f8P0HX36LOo2botFqi/U9fV0Xw5FjIXPxIbJ3nCzT9RVNp06dAJg4cSKTJk0q9RqHw+GVhlfhzWKxuD01a7FYPErmntSJVsXViVZgaXlaJ1rlUzd19TE+Wek6L+uFW5vRt00tzGaz51rWPIwLHyzunGB5YKHrOJCL/P+8vO/9L0m/MHH9RByqg6vrXM3rV7+OUTVe8vPGn++zqqrkzJ5N5uQPQVUxdOtKnbfewhkW5tZnoC88Htxwhj8XHcFhUwmrYaTn0ObUqBtygY9/1imKUmJNm81splb9hrTu3psf3n29zH4eeuUtdHpXyzWdyUR4rRiUf2yKsFgslw1mZbkXqqpi3ZlB/rITqGYHaF3Xd+nSBa1WS2JiIomJiWX2Xl68+OKLfl/76FV4MxqNmExlb79SlLSNRqPbjW/drROt6uFRtKqHx6qqVZa6mWuP8sEKV3B7rk8Lhl3XyDstcw6mrwegnAtuDF5yyQN4y/veLzy4kHe2voOKyq0Nb+WVa15Br9H7RassNarVSurLr5D9zTcARD70IOFPPEFQaGi5/i467SprFx1k9+pTANRvU4NeD7fEFHLhvSmLVsOOnWnYsXOZ/TvsVgCMwSGYQsMwhoSg1emL9c7nchsfyuLPkWsla8khzHtcj4X1dUOpeXNjeAc2btxIeLiXx+L4kYkTJ/pdw6vwpiiK2+myqKY86kSrengUrerhsapqXarui/UneGXpXgAe792UUTc0vmzNJbHkYPr67ybzZe1VWh73Q1VVpmyfwtQdUwF4qMVDPNv1WTRK2Y668Mf77MjO5uS48RSsXw8aDbWffZbIgQOKZ43K63cxP8vCz9N3c/poDijQ9faGdO7TAOUSjeU91Tr/3wCq04mlIB/buZm9b15/CYfdTs34BLrd/SAJrduWWlcWrYv5K9ieRtZ3h3AW2EGrEN6rHmE3JJCTl1Pm8SsLBw4c4OzZs9SsWZOmTZv6bFzZsCAIglAJ+XbrSf69ZCcAo65vxPheXv6P/9yu0srYZN6pOnl9/ess2L8AgDHtxzCm/Ri3w5EvsR4/TtKo0ViPHUMTHEzcu+8Q1r2722v/vCXlYDYr5xykMM+GMVhH76GtaNC2ZrloO2w2zPl5qE4nwRFR9Bg6irhmLXDa7exZvYKvX/03/V58jfiWbXyjl2cl67vDFO5MB0AfG0JUv+YYYsunO4Qv+frrr3n66ac5efLvdXrx8fG888473HfffV6PL+FNEAShkrFsZwpPLdyOqsLgq+rzbJ8W3gUZcymbEypJcLM5bPz7j3+z7OgyFBSeueIZBrYZWKHBrWDTJk4mPoYjOxtdbCwJU6dgat68XD2oqsrWX0+wbslhVCfUiA+lz6i2RNQKKhdtm7kQa2EhAIpWS2zT5sS3bF18TVyzluSeTWPT/771SXgr3JVO5reHcObbQKMQ1iOB8B4JKLqyHzJcWfjxxx958MEHad26NY899hhxcXEkJyczb948HnzwQX744Qf69OnjlYaEN0EQhErEin1nGLdgK04V7usUz8S+rX0S3Di5odI1mS+wFfDkqif5I/kPdIqOV699lZ6x/jsbqyxkLVlCygsvgs2GqW1b4j/+CH1M+R5PYjXb+X3OPg6fOxqjWbfadB/QAr3B/90KVKcTS34+DrsNAJ3RiDE4GKWUx9exTVuwd80Kr/ScBTayvj9MwbY0l17tYKL7NcdQ18sevRXIf/7zH2666SaWLl1aosPFM888Q58+fXj11VclvAmCIFQV/jyUzqh5m7E5VG5vF8sb97ZDc4l1TZfFnAPz74OTG8AUUamazGdbsklcnsj2tO2YtCbe6/Ee18RdU2EN5lWnk7TJkzk7dRoAYTfdRNwb/0UT5P+ZrvPJTM1n2dSdZKYWoNEodL27AR171XerzZWn2K1WrIX5qE61+Ow2/SU2H5w5dpiQKM/PKyvcm0HWtwdx5tpAgbAbEgjvXS8gZ9vOZ9u2bSxYsOCC90xRFB599FH69+/vtYaEN0EQhErA5uOZjJizCavdSe+WtXnvgQ5ovQlullxXcEtafy64fQexHSpFk/kzBWcY9esoDmUdItwQzse9PqZDTIdyX09WhNNs5tSzz5H7008A1HjkEWo9Pv6CIzD8zeGtZ1g+ey82s4OQCAM3jWxDVF33dvmWFau5kKzUlOKvM5JPojeaMIaEEhFTm00/LCY/M4M+jz0FwOal3xEeE0PN+Ho47Hb2rlnBwfV/0vfJ59zWdprt5H13FMu2swDoagW5ZtsSwnzz4ioYrVaL1Wot9Wc2m80nQVzCmyAIQgWzOyWXobO3UmB1cF3TmnzUvyN6rRf/g7fkuh6Vnh/c4jpWiibzJ3JO8Mivj5Ccl0ytoFpMu3EaTaN8twvPXexpaZx8bCzmHTtAryd20iQi77m7XD04HU7Wf3+ELT+fACCuaSQ3jWhNcLj/2lydPnyQhS//feju2gVzAGhxzQ3cOvZpCrKzyDmbVvxzh93G6rkzycs4i85goEZCPe5+9iUadij7cSMA5gOZZH5zAEe2FRQIva4uETfWR9FXnQb2Xbp04c033+TWW28l6LyZW4vFwttvv023bt281pDwJgiCUIHsT81lxNxt5FrsdG0QzaeDOmPy5oPMkgvzzptxG7TEFdwqAXvP7mX0b6PJMGdQL6we026cRnxYfIX5sR48yMnxj2NPSUETEUH8h5MJ6dq1XD0U5ln55bPdnNyXCUD7XglcdU9jtFr/trmKb9WWcbMXYSksAFVF0WgwBoeg1etRFIVbHn2ixPVd77yPrndeuEuyrB6dFjvZS4+SvyEVAE20kej7m2NqGOH9i6lkTJo0iV69etGoUSPuv/9+6tSpQ0pKCosXL+bs2bP8/vvvXmtIeBMEQaggjqbnM2jmBrIKbbSLj2DGw50J8mZRenFwW/d3cKt7hc/8esOm1E2M/X0sebY8mkc1Z+qNU6kZVD5HXpRG3urVpDz5FGp+Pob69YmfOgVjw4bl6uH0sRx+mraTvEwLOoOGnoNa0rSLl/1qy4DqdGIuyMdx7tGeVm/AGBLitx2+5kNZZC46gCPLAkDI1bEYu9fBGBZ4R4CUhWuvvZZffvmFZ599lo8//hhVVdFoNHTr1o0vv/ySq6++2msNCW+CIAgVwMnMAgZMX0daroXmtUOZPbQLYaZLdxK4JJZcmH+/K7gZK1dwW5m0kqdXPY3FYaFT7U582PNDwgwVt74pY958Tr/2GjidBHXpQsKHk9FGRparhz1rT7FqwX6cdpWImCD6jGpLjXLYYXn+2W0oCoag4EtuSvAGp9VB9rKj5P/lWlunjTYRfV9TDA0jKmxjSnlxww038Ndff1FQUEBmZiZRUVEEBwf7bHxpTC9aAe1RtKqHx6qmdSbHzIDp6zmVbaZRzRCmD2hPRJC+zJoXaFnzYP79KCf+QjWGw6BvS13jVhH34/tD3/PSXy/hUB3cEH8Db13/FiadqdTx/H3vVbudM2+8Qea8+QCE9O1L3VdeRmM0en7v3fRos9pZ+9Uh9v7pCjQN29ek55CWGIN0F4zpy/vhdDhQVSc2s6s7hEavxxAUXNxQvqhOUUpvTH85vX/WWY5mk7noII4MV0gL6VaH8D4N0Ri1Xr2uQGD16tVcccUVhIaGEhwcXCK05eXlsWXLFq6//nqvNKQxvWj5pU60AkvL0zrRcr8uI9/K4NlbOZ5RQHykiZmDOhCmV7FYLJ5pWfMxfD0A7cl1qMZwLA98hVqjlU+bzHt6P+bumctHuz8C4Nb6t/J/Xf4P7GC2+7bBfFnqnPn5pD37HIVr1wIQOXYsxocexKqqbu/A9dRjxulc/vjiGOlJ+aBApz4JtOtVF1WxYzbbfap1fl1uehprv/icG0cmYjAFoTEY0On14IfHpKqqkvXLMQpWJgOgCTcQckd9DI0jsKo2MNsu8FdWiv4bqeyN6Xv06MFff/1F11LWT+7fv58ePXrgcDi80pDG9KIV0B5Fq3p4rCpaOYU2HvliB4fT8qkTbuKLkVcSHxWE2Wz2zKNiQ1k8COVccGPQtxjrdvLpa/O05qOtHzF993QABrYcyNOdn75sn1J/3XvbqVOkjHkUy4EDKEYjsW/8l7CbbnL7vnvjMWnvWX6ZsR9Lvh1jiI4bh7WmXqtLn5Hmi/txcP0f/PrpR1gK8ln6wVtc88CgEp0Szq+xWq0YDAa3tYrqHOmFZP98DPNuVzP54M61ibitIRqT7oIaT15X4bmOD5W9Mf2lZggrxVEhlaFxs2j5VysQPIpW9fAY6Fr5FjtDZ21k96kcaoYamD+yG/VqhBQ/cnLbo63AFdyO/wnGcJRBSyD+4sGtLB59UeNwOvjP+v/w9YGvARjbcSwj244ss56v733hzp0kjXkUR3o62po1SfjkY4LatfP4vrvrUVVVtv5yrs2VCrUSQrllVFvCa5bt8F9PPdqtFn6bO4Odv/8MQKMrunDn0/9X4jHpPzGeW/vmrpbRaAS7ijbcSNQdTUjL3E3EzQ0Ian7xcOru60pNTWXhwoVu+SpPcnJyyMrKKv46NTWVEydOlLimsLCQ2bNnU6dOHa/1ZMOCIAiCnzHbHIyYvYktJ7KICNIzd3g3GtfyYnG6NR/DogEoSevAGO7anFCG4OZvbA4bz619jp+P/YyCwoQrJjCgzQC3w4CvyPn5F07961+oZjPGZs1ImDoFfVxcuelbC+0sn72XI+daPzXtWoseA1qiN/r3ozft+FF+eP8NslKSQVHodtf9XHVf/0sGN49xqjgtDnCqoFFQgnXEjGyLJsiLzTfnYbVaWblyJX/99Vel3uTw3nvv8fLLLwOuYHr33aWfFaiqKs8//3ypP3MHCW+CIAh+xGp3MmbeZv46cpZQo445w7rSMtaLRz7WfPjyAbRJrkelyqBvK0VwK7AV8MTKJ/jz1J/oNDpev/Z1bqhzQ4V4UVWVs9M/I+3ddwEIueF66r7zDtrQ8uuXmZHianOVdboAjVbhugea0qhzNDo/9idVVZVtP/+PVfNm4rDZCImK5tbHnqJem/YXXGs5kk3u6pNYk/Nw5lqJHtiSoNY1Lj2+3UnO8hMUbD2DI9eKNtxA6NVxBLevBYqCRq9F0WvARwfuHjx4kKVLlxbPaDVr1swn4/qDm266idDQUFRVZcKECYwdO5Z69eqVuMZoNNK2bVtuuMH7/y4kvAmCIPgJu8PJ+AVbWbE/DZNew8yHu9A+IdLzAa358MUDKMfWohpCYeA3EO/eCff+INuSzaPLH2VH2g6CdEG83/19roq7qkJmSlSrlZSJk8hevBiAqEGDqP2vCSi68vu4O7T5DL/P2YvN4iAk0sgto9pQu0G4X+9HQU42P0/9gCObNwBQv30nbk18guCIyFKvd9oc6GNDCOlcm7Pz9pZJ4+z8vTjzbETe3QRNiB5nntU146bToDHpULxp53Yeubm5/PTTT+zevRuA8PBwbrvtNurUqcOwYcN8ouFrrrrqKq666ioA8vPzGTlyJHF+nOWV8CYIguAHnE6VCYt2sGxXKgathk8HdaZrQ8+beGMtgC8egGNrUA1hWPotwBjfxXeGPeR0/mlG/zaaQ1mHiDBG8HGvj2lfq32FHOvgyMoiefzjFGzYABoNtZ9/nuiBA8pN3+lwsm7JEbb+6lrrVLdZJDeNaENwuMGv9+PErh0s++ht8jIz0Op0XD9wGC1u6F2iNdM/CWoefck1af/EvD8Dy9Fsao/viFLUui3CiGLS+qyRvNPpZMuWLfz222+YzWYURaFbt2706NEDo9FIdna2T3T8zfPPP3/R3qb5+fkYDAb0eu8eK0t4EwRB8DGqqvLCd7tYvDUZrUbho/4dub5ZLc8HtBbAF/3g2BowhMHAb1BrtfOdYQ85nnOcR355hFP5p4gJimHajdNoEtWkQrzYjp/g1OOPYz12DE1wMHXfe5dQHzyeKisFOVZ+mbGb5P2uNlcdbqzHVXc1QuNNj9rL4HQ4+GvRF6z7diGoKlFx8dw+fgK16jf0+Sxf4e6z6OuEkLs6mcKd6SgGLUGtahB+U73LF5eB06dP87///Y+kpCQAYmNj6du3r19nr/zFyJEjsVgsfPnllxf87JFHHiEoKIjPPvvMKw0Jb4IgCD5EVVVeX7aP+etPoCjwbr/23NTai91l1gL48oFzwe3co9KErm6fTeZrzu9TWj+8PtNunEbd0LoV4qVg0yZSHhuLMzsbXWwsCVOnYGrevNz0Tx/N4adPz7W5MmrpOagFTTv7t81V9pnTLP3wLVIO7AOgTY+b6PnwI+hNpR+A7CmqqqJandjTC7Em5aLoNEQPaIFqdpD13WGchTai7vN8LZrNZmP16tX88ccfOJ1ODAYDPXr0oGvXrmj9scGiHFixYgX//e9/S/1Z3759ee6557zWkPAmCILgQz5YfpDpa44C8MY97bizgxeBxloAXz4IR1efC26LoV63CzonlDfn9yltGd2SKb2nUCPo0ovd/UX2d9+R8n8voNpsmNq2JeGTj9HV8mKW0012r0lm9VcHcNpVImsHc8uoNtSI8+/GiP1/rSk+u80YHMKNjzxG86uu87mO6nDiNDvA4XQFQgWi+7dAG3zukZ9D5ez8vUTe2RjFg00Khw8fZunSpWRmumYrmzdvzq233kpERGA3qz99+jSxsbGl/qxOnTqkpqZ6rSHhTRAEwUfM+OM4Hyw/DMBLfVvRr0uC54PZCmHBQ3B0FehDXDNu9br5yKnnVJY+paqqkv7hh6R/MgWA4F69iH/rTbQ+7B95Kew2B2u+OsjeP/5uc9Xr4VYYg/z3sWozm1kx+1N2/v4LALFNm3PbuAlExPh2lq9otk21OAAVUNBGGNFmW/8OboAuJhhUcGRb0ZXx3Dpwrfv68ccf2bNnDwBhYWHceuuttGzZ0qevo6KIjIzk0KFDdO/e/YKfHTp0iLAw7/97kfAmCILgA+b+dZy3f3MFt2dubs7Qaxp6PpitEL58CI6sPC+4Xekbo17ww+EfeOGPF3CoDrondC/uU1reOC0WUp57npwffwQgeuQIwkaPRnOJBfq+JC/TworZu0g7nouiQLc7G3HFTfV9ttuyNM4cO8LSD94k49TJc2e39eOq+x5C6+tdtE61eLYNAK0GTZAOY8MIzLvP4rQ40Bhds2z2tEJQQBthKNvQTifbtm3jl19+KV6TV7QhwZ1uTZWdHj168Prrr3PPPfcQHf33ppCMjAz++9//0rNnT681JLwJgiB4yaLNJ3nxe9exBo92b0xiDy8W7dsKYUF/OLLiXHBbBPWv8pFTz5m3dx5vbnwTgDsa38Gkqyeh05T/R4j97FlOJj5G4bZtoNMRO2kSEffcXW7Hkpzcl8Evn+3GfK7N1c3D25BwmTZX3qCqKlt/+oHV82bisNsJjYqmz2NPU6+NdxtWnBYH9rOFxV87Ms1Yj+egaDVoIwzkrEjCWWAn+sHmKIpCcIcYcn8/QeaiA4T3rocz3072sqMEd65dpkemaWlp/PDDD8VdB2JiYrjjjjuIj4/36nVURiZOnEiXLl1o2rQpDzzwAHXr1uXkyZN8/fXX2Gw2Jk2a5LWGV//lFfUnc/d6dxdTelInWtXDo2hVD4+VWWvpzhQmLNoOwMCu8Tx1Y1PP9exmWDAA5fDvqPoQGLAQ6l11wRq38rwfTqeTqTunMnPvTKBkn9JLjeOPe285dIiTo8dgS05GEx5O3ckfENKtW7m8z0VtrtZ/dwRVhZoJodwyqg3hNYLKNIYnHguys1k25T2Ob9sMQKNOXbl51DiCwiO8vvfWkzmkT99V/HX2Utc6zaC2NYm8qwmqxYEjx1I8nmLQUGNYG7J/OMKZj7ahCdYR1LYm4TfVL241Vpqe3W5nzZo1rF27FqfTiV6vp3v37rRv357g4GC337NAoHnz5qxZs4Ynn3yS6dOn43A40Gq13HDDDbz77rs098FmGkX14G7k5OQQERFBamqq281hzWazR9OjntSJVsXViVZgaXlaV921Vh5IZ+xXO7E7Ve7rGMvzNza45Nlal9TTgWHxULRHV6Dqg7DeNx9nvau99uhNnVN18vaWt1l0eBEAo9uMZmjLoWVud+XLe1+4bh1nnpmAmpeHLiGe2pMno2/QwC9a/8RqtrPmy8Mc3+FquN6oUzTX9mvidrcEdzwm793Fb9Mmk5+ViVan5+oHB9Gm1y0e33tFUYp7lxahqirYnKgWJ661baAYtaDXuN2c/vzrLRYLqqpy/PhxfvnlFzIyzt23Ro246aabiIiI8Oj9ysnJoU6dOjRr1gytVktiYiKJiYlujVHeFBYWkpmZSXR0tE8fDXs182Y0Gt0yU/Q3AaPR6PYvhrt1olU9PIpW9fBYGbX+PJzO+K93YXeq3NE+ltfvbY/NavHMo82M6bsRKEdXoOqDof9XGBpcfPdgedwPm8PGi3+8yE/HfkJB4fmuz/NAiwf8onW5mqyFCzn98ivgcBDU6Qrqfvghuqgov2j9k8zUfJZN201WqqvN1bX9mtKocxRBQUF+ufcOu51133zJ+iVfg6oSGVuX28dPIKZBI99qqaCai3qSAhoNilHrk3V7TqeTX375hW3btgEQGhrKLbfcQqtWrYpn6Nx9vwoKj3Po0EQANm7c6PbEUUURFBTk0V/oLodX4U1RFLcbDhfVlEedaFUPj6JVPTxWJq3NxzMZOWczVruTG1vV5p1+HdBpFOyeeLRbMC4ZjnJkOeiCUPovhIaXP/bBn/ejwFbAk6ue5I/kP9BpdEzqOom+zfqW+71XHQ7OvP0OGZ9/DkD4HX2JffVVNIYLF8j7430+vOUMy2eX3ubKH/f+grPbet7EVQ8MIiwi0mdaxQ/bFNBcZGesu6H0n9d/99137N+/H4DOnTvTu3fvCyZ6yvp+2e35HD8+heMnZpCXV3kb0/+TgwcPMm3aNPbu3UthYWGJnymKwvLly70aXzYsCIIguMGu5Gwe/nwDBVYH1zWtyUf9O6LXXnr910WxW2DhYLRHlqPqglD6f1Wm4OZPsi3ZPLb8MbalbSNIF8S7N7xLpxrl3/jeWVBA8jMTyDv3IVdz3FhqjhnjdojxSNvhZN13R9j6S/m1uSrt7LZmV17r040Yxd7PfwkKxbNhvkJRFGJiYujbty8JCZ4dl6OqKqdP/8ChQ//FYj0NQGRkN+CYz3z6i127dnHllVdSt25dDh06RLt27UhPTyc5OZmEhAQaN27stYaEN0EQhDJy8HQug2duINdsp0uDKD4d1BmjzsNT4O0WWDgE5eDPqDoTPLQAGpVfO6fSSCtIY9RvoziYeZAwQxif9PqE9rXal3uDeduZMySPeRTznj0oBgOxr71GxO23lYt2Ya6rzdXJfefaXPVO4Kq7G/utzdWlzm7zVaBSVRXL4SyMjSNd3zgv//ojDLdu3ZpWrVp53CEhN3c3+w9MIjvbtVHDZEqgWdN/o9d3Ab7yoVP/8Pzzz3PzzTfz1VdfYTAYmDFjBldccQVLly5l2LBhvPrqq15rSHgTBEEoA8fP5jPgs/Vk5FtpFx/BjIe7EOTmgvVi7Fb4+mE4sAxVZ8J67xwMFRzcknKTeOSXRziZd5JaQbWYeuNUmkU1K/cdfpb9+0kb/zj206fRRkUR//HHBF/RsVy0zxzPYdnU8mtzVR5ntznyrGR9ewhbeiExj7YHp4pi0HI86QR//vknp06dIi8vjwceeIAWLVpcdJxvv/2W7du3X/D9GjVqMGzYMAB0Oh16vZ62bdt65NVqPcvhI+9y6tRXgIpGE0TDBo+SkDAcrTZwGtNv2bKFTz75BI3GFfidTteZebfddhtPP/00zz33HKtWrfJKQ8KbIAjCZTiVVUj/6es5k2uhee0wZg/tSrhJf/nC0igKbvt/hHMzbs64ij2A90DmAUb9Oor0wnQSwhKYduM0EsK86A7hIXkrVpL61FOohYUYGjcmYeoUDB4+dnOXPX+cYvWXB3DYnUTEBNFndFu/tblSVZVtP/+PVfNm4rDZCImK5lYfnN32Twp3ppP13SGc+XZ0sSEoWg0YXOvMbDYbtWvXpkOHDixcuPCyY/Xp04fevXsX+zebzcycOZNmzZoVbz7Q6XQezeQ5nTaSk+dz5OgH2O05ANSu3Zcmjf+FyVR6m6nKTNHuUo1Gg16vL27/Ba41gC+//LLXGhLeBEEQLkFaroWBn60nOauQhjVDmDuiK1EhZTtR/gIcNlg0FPYvBa0RHvwCGnWv0Cbz285s49Hlj5JrzaVZVDOm3TiNmkE1y9WDqqpkzp3L6f++AU4nwVdeSfzkD9CWw45Ch83Jmq8PsmfNKcD/ba4Kc7L5edpkjmzeAJw7u230eILDfdfP05FvI3fJEay7XEd06OuEEP1QCxTd349+mzZtStOmTcs8pslkwmg0YrfbsVgsnDx5ErPZTIcOHQgODvZoAwdARsYfHDj4Cvn5BwEIDW1Js6YvEhXV1e2xKgt169YlPT0dgCZNmrB69WpuvPFGAHbs2EFoqPd/KZDwJgiCcBGyCqwMmrGeI+n51I0MYv6IbsSEeXhWU1Fw2/c/V3B76Ato0qtCm8yvTV7LEyuewOww0zGmIx/2/JAIY/k2BVftdk6/9jqZX3wBQOjdd1N30sRSd5T6mrxMCyvn7OLMsVxQoFvfRnS6xX9trpL37uK3Tz8kPzMDrU7H9QOH0/GW23267qxwz1kyvz2IM9cGGgjrnkB4z3olgpsnOJ1OzGYzDocDgN27d9OwYUNiYmI8Gs9sTubgoXdJS/sZAL0+ikaNnqRu3AMoiofLESoJ1157LX/++Sd33XUXAwYM4KWXXiIlJQWDwcCsWbMYOHCg1xoS3gRBEEoh12xjyMwN7EvNJSbMyPwR3YiL9PC8JocNFg2DvT+A1uCacWvS27eG3WTZ0WU8v+Z57Kqda+tey7vd3yVIVz69QYtw5OWR/OST5K9eA4pCraefIvihh1D0Hj6SdoPk/Zn8/NkuzHl2jME6bhremnqta/hFy+lw8OfXX7B+yUJQVaLj4rnNzbPbLqtRaCfrh8MUbDkDgLamieh+zTHW8272UlVVrFYrVqu1+HtWq5UjR45w7733uj2ew1HIsWNTOXFiOk7VgqJoqVt3AI0ajkevj/TKa2Xh3//+N6dOuWZy//Wvf5Gamsr8+fNRFIV+/frx9ttve60h4U0QBOEfFNocjP5yG9tPZhMVrGf+iG40qBni2WAOO3wzHPZ+/3dwa1qxwe2r/V/x2vrXUFHp07AP/7nmP+i1/g9M52M7dYqk0WOwHDiAYjIR99abhPXu7fedraqqsu3XJP769pCrzVV8KH1GtyW8pn+C6wVnt/W4kZ4Pj0Lvw9P2zfszyPzmII4cKygQel1dDNfVxhAa7NW4RY9Iixbca7VaTCYT27Ztw2QyXXKDwz9RVZUzZ5Zy8NB/sVhSAIiMvJLmzV4kNNT7dlGlsXr1at566y02b95MSkoK3377LXfddVeZav/44w9uuOEG2rRpU3zYcFlp3Lhx8XEgWq2WyZMnM3nyZDfdXxoJb4IgCOdhsTsY99VONhzNIMyoY+7wbjStHebZYA47LB4Be75zBbcH5kPTG31r2A1UVWXmnplM3TUVgAeaP8Dz3Z5Ho/jnGIyLUbhzJ0ljHsWRno62Vk0SPplCUNs2ft/ZajXb+X3OPg6fm51q0rkWPQe1RG/0z0fh/r/W8uunH2IpyMcQFMwNDz9C2xt6+ewxqdNsJ3vpUfI3pgKgqxlE1P3NMNQL8yoEq6qKxWLBZrMBf7fW0p3bBbt161bat2+PTqcr03uWm7uXAwdfJivLtc7PaIyjfv2nqRvXt3hHZlk8/Zru3m7T/Px82rdvz9ChQ92aJczOzmbw4MH06tWL06dPu6VZXkh4EwRBOIfd4WT8gm2sPZxBkF7LrGFdaFPXwzVgDjt8+wjs/hY0eug3F5rd5FvDbuBUnby96W3m7p0LwKh2o0jskFguh96eT84vv3Bqwr9QzWaMzZuTMHUK+lj/7yjMOl3Aj1N3kpmSj0bjanPVuGu02/1Jy4LNYmbF7OnsXO5azxXbtDm3jn0aY3ikzzTMh7LIXHQAR5bFNdt2dRzhNzdAY9B6HIJVVcXhcBT3JgXX8R9Go7E4ZB09epSMjAw6drz88S02WyaHj7xHcvKXgBONxkj9+qOplzACm63sGxw2Zefz8uFTrDvlXpDq06cPffr0casGYNSoUfTv3x+tVsuSJUvKVDNhwgTGjRtHfHx88fecTmeZw6m7eBXeivqTuXu9u79YntSJVvXwKFrVw2N5aDmdKk99vZ2fd5/GoNXw6aAruKJeVJk1S2g57fDtaJRd36Bq9NBvDjS7udTNCeVxP+xOOxP/msj3h78HYELnCQxsNbB4LF9qXaxOVVUyZswk7Z13AAi5/nri3n0HbUhIiWv88T4f3Z7G8ll7sZodBEcYuHlkG+o0crW58rVW2vGjLJ38FhnJSaAodL3zPq66rz8ardZtvdK0nBYHOT8dI3+d69GjNspI1P3NMDaMuKDmUlo2m6343LSYmBgsFgunTp1Cr9cTGhrK1q1bMZvNJY4HATh8+DBt2rQhJiamxPt2fpcGp9POqZQFHDnyPnZ7lkujVh8aN3mWIFPdc94ufy8OF1h47UgKP56bcTOd20iSk5NT4jqj0YjRaLzM3Swbn3/+OYcPH2bevHluHab7zjvvcN999xWHN4fDgcFgYOPGjVxxxRU+8XY+XoU3i8Xi9tSsxWLx6G96ntSJVsXViVZgaXlaV1W0VFVl0tL9fLftFDqNwlt3NaNzgvuPniwWC4rqRL90LLo9i1E1Oqx3TcdZv8cljwPx5/2wOCz8+69/s/rUarSKln91+Bd3NbrLrdfm7b1XbTbOvvY6eedmMcIefJDop57EptVi+4cPX77PTqfK1p+S2P5rMgC1G4bR4+FmBIcbsFgsPtVSVZVdy3/mzwVzcNhtBEdG0fuRscS3aovNbodz68e8eZ9tx3PJ++4YzkwLAMbOtQi5MR7VoL3g/fynVtGjzyJ0Oh1hYa7lAEWH7IJrjZZOp+PKK68sNVxdd911xY9Pzx/7fPbte4HU018DEBzclIYNniMiwnX0R5HPS92LNKudycln+fJ0Fg5AA9xXK4IRETVpDxe03HrppZeYOHFiqWO5w8GDB3n22WdZs2bNBa/xcpR2r/y5DMCr8GY0Gi9oNnspiv4mYDQa3W58626daFUPj6JVPTz6U0tVVf7z4z6+2nwKjQLv9mtP72ZRnmk57Jh+egLlXHDjvs8xtOzr89dW1po8ax5Prn6SjakbMWgMvHX9W1xZ68pyvfc6s5lTTzxBwbr1oNEQ89yzRF/kqARfvs/mfBvLZ+4haY/rrLO2PeK5+t7GaM+1ufKlVmFuDr9Mm8zhTesBaNixMzePebzE2W3evM8GjY6cX06Q/+cpUEEbaSTy3qaYmkSW2eM/KQpz/wwYRddfLLwYLnmEiwoo2B3Z6HQRNGr4OHFxD6HRlBzrYv4KHA6mJqXzSdIZ8h2uTRK9o8P4d6NYWoQGFc8UJiUlEX7eGYC+mHVzOBz079+fSZMm0axZM6/H8zdehTdPDuUrqimPOtGqHh5Fq3p49JfW+78dZMbaowD895529G0fh9lsdl/L6cCw7HGU3YtAo0O573NodYdPPHpSk2HOYMxvY9hzdg8h+hA+7PkhnWt39ui1eXrv7cnJpIx/HOuRI2iCg4l79x3Cunf3i9b5dWlJufw0bSc56WZ0eg3dB7agebc6ftFK2rOTHz98m7yMs66z2wYMpWOfO0od0xM9e3I+Od8dx55eCEBIlzpE3NYQjenSH9+X0jr/cef515f258vhGqPoH1ddjejradXyNfT6qDL5sztVFqRm8ObRFM5Y7QC0DwvixcZxXBMVVqIGIDw8vER48wW5ubls2rSJrVu38thjjwGuNWuqqqLT6fjll1/o2bOnTzW9QTYsCIJQbfl09WE+WO462X1i31b065Lg2aMOpxN+GItu9yJURYty38wyBzd/kJqfyshfRnIs5xjRpmim9J5Cqxqt/PoY558UbN1KyqOJOLOy0NWpQ8LUKZjcOFrCU/avS2HF/P04bE7Ca5roM7otNeM93C18CZwOB+sWf8X6xV+hqk6iYuty2/gJ1G7Y2CfjqzYn2b8eI29NMqigCTcQdW9TgppHez7meaEtK2sDJ5I+Izd3N1brGdq2mUKtWpfeCZ2a+h3HT3xKQcExdLowoqOvp2mTCReEtPj4h8rs59ezObxy+BQHC1yPguuZDDzfKJY7YiLRuBmqvSE8PJydO3eW+N4nn3zC77//zqJFi2jYsOFlx9i/f3/xjGXRYcb79u0r9Vpv18FJeBMEoVoyb91xXvvR9T/WZ25uzsPXXP5/zqXidML3Y1G2fYGqaOHeGdDqTh86dY+j2Ud55NdHSM1PpU5IHT698VMaRnj42jwk+39LSXn+eVSrFWOrViRMmYK+tmcn8ZcVh93J6gUH2LXKtb6tXusa3DisFaYQ359fl3s2jeWffsip/XsBaN29Nz2HjsJg8s1ZcdaTuWQsPID9TAEAQR1jiOrbCE2w568lLy+PkJC/zyp0OAoJDW1JXOz97Nz16GXrs7I2sXvP0zRr+m9q1OiJxZLK/gMvsnff/9Gu7ScUzbqVddZuW14hb+w9ybrsfACidFqebFCHwXVrYPTRDs28vDwOHTpU/PXRo0fZtm0b0dHR1KtXj+eee47k5GTmzJmDRqOhTZs2JepjYmIwmUwXfP9iPPzwwxd8b9CgQSW+LtrcURTuPEXCmyAI1Y5vt57khe92AfBo98Yk9mji2UBOJ/xvPGybh6posfX9GH3ru3xn1E32nN3DmN/GkGHOoGFEQz698VPqhFz4uNBfqKpK+pQppE/+EICg7t1JeOdttCEeHnBcRvKzLCybtsfV5grofFsDut7W0C9trg5u+JNfpk4+d3ZbEL1HPkbLa27wydiq3UnO7yfIXZkETtCE6gm5rR7hHWLdfrRbhMPhYP369Rw9epT+/fsDroBVs2Z3atXqUeZxsnO2YjLVJT5+CKASFBRPXNyDnDgxHXeC29ECC68dOcUPaX/vIB0ZX4vH6sUQob90JMkqsF7y5/9k06ZN9Ojx92t88sknARgyZAizZs0iJSWFEydOuDXmxfj88899Mk5ZkfAmCEK14qddKTz99Q5UFYZcVZ9nbvbwdHenE/73OGyZA4oG7vkUR5PbKN8+BX+zMXUjY38fS74tn1Y1WjGl9xSiTZ4/YnMXp9VK6gsvkP2d6ziS6KEPE5aYiCbYu1P+L8epQ1n8/OkuCnKsGIJ03Di0FQ3a1fS5js1qYeXs6ez47ScA6jRuxm3jJxBZ2zfh2Hoqj8yvD2BLcc1EBbWvRUTfRti0ns/QnDp1ih9++IHU1FRiYmKw2+1otVq3zx5TVZWw0DZYLKmcPv0DUVFX43DkkXbmJ2rUKFsATLfaee9YKrNPpWNXXXGvX50oJjSMpa7p0n1sc8w2Zq49yqe/7XLLd/fu3S+5VGDWrFmXrJ84cWKZd7EOGTLEDWfeI+FNEIRqw8r9Zxj75VYcTpX7OsXzUt/Wns1oqCr8+BRsme0Kbnd/Cm3uveRxIP5kxYkVPL3qaaxOK13qdGFyj8mEGkLLTd+emUny2HEUbNoEWi11XniByAf6+bXVlaqq7Fx5kj++PoTTqRIVG8Sto9sRWdv3s3zpJ47xvw/e5OxJ1yxNx1vv5Pr+D6PzQQ9W1eEkd+VJcpafAKeKJkRH5J1NCG5XC1VVsZndD28Wi4XffvuNLVu2oKoqJpOJG264AZ1OV+rve0hIM7Ta0n9fnE4bDkc+oaHNaN3qXU4kfcbxE9NRVTtRUVfSpPHzl/RS4HDyadIZPjpxhrxzO0h7RofxdN1oOtaIvOR/f/kWO7P+PManq4+QXWjDafHuUWNVQsKbIAjVgvVHzjJq7mZsDpXb2sXyxr3t0HjyWE1V4cenYdNMQIG7pkK7+0s9gLc8+OHwD7zwxws4VAfdE7rz9g1vY9T65sDSsmA9doykUaOxHj+OJjSUuu+/T+i11/h1c4TN6mDl/H0cWO86cb9J5xiuuq8BYRG+neVTVZUdvy1j5ezPsNushERGccujT1C7WUu0bp4DVhq20/lkLDyALTkPAFPrGkTd1QRt2KVnoi7Fvn37+PHHH4sPsm3bti0333wzoaEXD/OdOy1Eoym5Xq/o/VMULTpdOKrqpEaN66lVqzeK4uri4HRaAAelRQm7U2VhagZvHk0l1epqs9UuNIgXGsdxbVToJYO92eZg7l/HmbrqMGfzXY9Km8SEMrJbEx58342bUYWR8CYIQpVne1IWw2dvwmJ30rNFDO/164DW0+C2bAJs/AxXcJsC7R/wud+yMn/vfN7Y+AYAdzS+g0lXT0KnKb//rRds3MjJx8biyM5GHxdH/NQpmPx8RlZ2WiHLpu3k7Mk8FI3C1fc0pl3PeCwWi091CvNy+XXahxzc8CcADTp0os+jTxAUHuH1jKLqVMlbc5LsX46DQ0UJ0hF1R2OCOtTyeG1bdnY2y5YtK97dGBERwe23307Tpk0vW+t0WlEUA4riahWmqk5cR38UoeBwuI4q0WhcwdJlU8Vuz0Gj0eM6StcV+rbnFDBuXxIHClz3Kd6k5/lGcdx1bgfpxYK9xe5gwYYkPlpxiLRc1/vZoEYw43s35Y72dcnLzSm1rjoi4U0QhCrNgdN5DJm9lTyLnasa1eCTAVdg0Hmwm01V4adnYcOnuILbJ9ChbEci+BpVVfl016d8tuczAAb+P3tnHR7VlYbx3x2Pu7viDsGKBpdCaaHuLVJKvVvZyla2W9sa0AJ1X7zFrbgHd+LurqP37h83mRAIkISE2rzPs1syc8/5zj2TzLzzne973w538WyfZ6+rwXzZr7+S/dLLYDKh69qVoE/no/Js/VqzC5F2uojNX57GUG3GzknN6Ic6E9Cu6RZmTUXmudOs++R9KooKUChVDLrjXnqNm4SgUFxzLFNBDaXL4jGmy80VuvbuuE2JROncsmypKIocPHiQrVu3YjQaUSgUDBgwgJiYGKuDwtUgSWbqyZp4wTMCUKcVZ6GuMeGCkbVj6+aR5/g4PZ/4aj2uKiWPh/jwQKDnFTtITRaRpYcymbc1gewymfAFuNrxeGwUU3oGoFJev9/rPwts5M0GG2z4yyK5oJIHvz9GWY2JHsGufHFvb3TqFhiRSxJsfBEOLJB/vnEudL+jdRfbRIiSyDtx7/DTuZ8AeLT7o0zvOr3FGZvmQpIkCufOpfDTzwBwGj0a/7f/g8KudWQyGo0pShzekMaB1ckggU+YM2Omd8bRrekOP02BKFo4sGIJ+5b9jCSJuPr6MeHx5/AJb2E38gWQRIma/XlU/5YFZhFBq8R1Yjj2vXxa/NrVNSTk5Mg+p0FBQUyYMAFvb++rZgf3lpTzaXo+Jyv15BnNfNEBxnm7AgoEQYHFUo0kiajVskuEQqHly4xcvsvNItNgwl+r5tFAR27xdgQUVpleBaBWwOxgb+YEe+N6hQ5Ss0Xkl2PZfLI1gYxiObPn66xj9vBIbu0d1LIvWX8T2IzpbbH+1Gu0xfp7rLElYzJLarjry4MUVhnp6OfE1/f1wV6jvOocl8SSJNj0EsL+T+UfJ34CPe66pMbteuyHSTTx6t5XWZO8BgGBF2Je4Lb2t1nnac1YjY0RDQZy//kS5WvXAuD+8EN4PfFEoxmp1nqdDTVmtn57lpTjhQB0HOTPoKlRKNX1MVsjVkVRIevmvU/W2dMAdBg0jNgHZqKxs28wb0timYv1lCyNx5gqH/tpI11xvTkKlavWOmdT1lgHo9HItm3bOHDgAJIk20yNGDGCXr16IdQeS15tjdVmE+3t4RYvR2aeL0UU9ZhMpSgUOmuNm/w/eY7vcyp5N72CtyPc6Oao5FilieeTSnDTODHKq+Hcb0UG4qFRXfbezBaR1Sdy+WxXGimFcnetp6OGR4ZGcEdMMFq1stGxbVlH2Zo4fPgwvXr1atMYNmN6W6w2GWeL9eeK1dJxf9RY+RUG7v7mCDllesLc7fj8zm5oBQv6JnbuWWNJEqrtb6A+KBM34+j3sHScdtmu0rbcD71Zz4v7XmR3zm6UgpIXe7zIxNCJ1+U92GAwIJaUkv/00xiOHQOVCo8XX8TppskYjJfX3rrW17kkt5rfvjpPeYEehVKg/y1htOvng8lixGS5/Ljmxko5EsfWLz/FUFWJWqdj8D0P027AYERodH+bGkuSJAyHCqjanAkmEdQKHEYFoe3liVmQMDfhtbs4VmJiIps2baKiQj52bd++PbGxsTg6Ojao+7t4nEKhaOBLGuvpRqynKwAzz5eiUjmj0bhan1epGtpPLcsr4W5/D2729wcgwhmOVSn5NKOAUV6utQesMpwQG903UZLYfLaAudtTSCqQSZurnZoHBwZzR59A+cuVxYTeYrrsXgD06dMHpVLJ7NmzmT179hV27/dBnz596Nu3L48++ijTpk1D3QpdyRfDZkxvi/WnXqMt1t9jjc0ZU1Jl5OEfj5NeXEOQmx1f3dMDP3en5sfSaBC2vo5QS9yk8R+g7v3AZXXc2nI/KowVPLnnSQ7nHUar1PL+4PeJ8Yy5bntvTEkh9/EnMGVkoHByIuDjj3Do379NYtWNSTpSwNbvz2E2WHB00zJ6emd8Qhv3s2xpLJPRwN6fvuHYJjmT6BMeybjHnsXN1/+a78tcoqd0eSKGJFmMVhPmjN2EYBz8XFq0HxUVFWzYsIGzZ2VXB1dXV8aNG9doQ8LV11h3yAkg0N5Bh5PyyuUEflo1gVp1g5HBdhoOllUhihKqCxqALjavlySJLWfz+XBLPGdzZNLppFXx8KAw7r8hDEdt06hIHXmLi4trdW/T1sQ333zD/Pnzufvuu3n66ad5+OGHmTFjBoGBga0Ww2ZMb4v1p1+jLdbfY41NGVOhN3HfN3HE51Xi46zlh4f64m2vaH4sQNj2JsKej+QHxr2P0OfBVlljc8cV1RQxa8sszhafxVHtyLzYefT07tkig/mWrLHq4EFy5zyGWF6OOjCQoIUL0EY0zb+zJfshibBvZRLHNmcAENDOjdEPdcLuKvIZzY1VlJXBmo/eoSgjDYDeE6dww213o1RdPUtypViSJFEdl0fp2mQkgwVBrcB5TCgO/fwwGA3N3w9JIi4ujt9++w2j0YggCAwYMIAhQ4ZcQpKutEajsQS12rXuWS5sPljdMwrdBQ0FF69PkiTmdQjBJEnWujYRuNPPgzv8PKyd242N2xFfwIeb4zmeKZNYR62K+weGclcfP7xdm/6lqrH5/6i45557uOeee4iLi2Pu3Lm8//77vPPOO0ycOJE5c+YwdOjQa45ha1iwwQYb/hKoMVp48JtDnMgsw91Bw48P9SXY3b75sg6ShGrXuwj7PpR/HvsuxDzc+gtuAnIqc5i+ebrVYH7BiAV08Ohw3Wp/SlesJOeVV8Bsxq57dwI/nY/Kve1cG2oqjGz8/Aw5CXJtWI+RwfSbHI6iFbsNJUni5NZNbPtmIWajEXsXV8Y88iRh3a+9RslSZqBkRQL68yUAaEKccZsajdrTrkWvWW5uLqtWrbI2JAQEBDBx4kR8fZvu6mCx6ElP/wK9IZ/27V5r8FwdGTKIIhpBqNP/aIC6dasVAkazSInJXDsWdIICvShir1Rc0oe6N7GQDzbHcyhN3gs7tZL7BoYyfVA4rvbqNhVw/qOgT58+fPfdd3zwwQcsWrSIhQsXEhsbS4cOHZgzZw733ntvs04vL4SNvNlggw1/ehjMFqZ/f4iDqcU46VR890AMkd5OLSM5O95GXUfcRv8H+s5o3cU2EcllyUzfNJ286jz8HPxYNHIRoS6h1yW2JIoUfPwJRQsXAmA/ahSB776DsoUfNE1Bflo56xecpLLEgEqrJPaeDkT2al0ze31VJZs/n0/8vl0ABHbqyvg5z+Dodm2EVJIkqo/mU7oqGUlvBpWAy6hQHG8IaJG/qtFoZPv27ezbt896/BkbG0vv3r2bbG0lSRL5BRtJTPwPen0mnp6jrM9dnMEySw1V3erGNzxcBQeVEkfkrJsCqBFFLFKdwlv9uA82xTN3m2wIr1UpuLtfCDOHRuDpeOUGjb8qNBoN9vb2aDQa+XeluppZs2bx5ptvsnTpUvr169fsOW3kzQYbbPhTw2wReezno+xKKMROreSb+/vQOcClZZNtfwdhhyx6K418A6H/I6240qbjdNFpZm2eRYmh5LobzIt6PTkvvkj5uvUAeMyciePDD6HQtp1rw5k92ez8OR6LWcTZS8e4mV3xCGhde6/s+LOs/eQ9ygvyUSiVDLz1bjqPGIvdNXqvWiqMlKxMRH+mCAB1oCPu09qh9m7ZvPHx8axdu5ayMvmYMTo6mgkTJjSrxquyMp7z51+jrPwAAFqtL8HBDwAycZu/LZGNp3NJyq9Ep1bSKciF58e0p4OPrAsn1hK3OtQdsh5IKebNtWesZQl3DwxjWkyQ9TpRlBAEiM+rQKNUcHtMEI8Mi8THuRVIf8F52PLfa5/nOuLEiRPMnz+fn376CaPRyNSpU/npp5/o06cPJ06cYPr06cyYMYPjx483e24bebPBBhv+tBBFiWeXnWDj6Tw0SgWf39ObXiEtzKLsfA+2vwWAaejLqAbMacWVNh2/p8G8uaiIzNmPUnPsGKjV+L3+Oi6TJ7XZEZfFJLJrSTynd2UDENrVkxtuC8PZrfX8SUXRQtyvy9mz5AckUcTFx5fxjz2Lb0T0Nd9X9fECSn9NRKw2g1LAeUQwToODEJTNz7ZVVFSwfv16zpw5A8gOCePGjSM4OLjJR2smUxnJKR+RlfUjkmRBodAQHDyd0JAZKJX1ZPJASjF39Quhc4AzZlHinY3nefDrONY/OQgHjQqFIFBlERElCReVEkEQSCms4v6v47i1TxDvTu3G/pRi3lpzBn8nLeM6+yFRX0V3Q5Qnr9zYiQDXa9T+kyRI2wN750L8BgTDnyNjt3jxYubPn8+ePXvw8vLiqaeeYtasWQ2Ou7t27cpbb73F6NGjWxTDRt5ssMGGPyUkSeLlX0+x8mgWSoXA/Dt7ckNUCxX+d30AW9+U5419FXPvWb/Lm+PvaTBvSEoiY8ZMTJmZKFxcCPzkExz6xrTZEVdliZ4Ni06Rl1IOAvSdGE7P0cEYjK1nc1VZXMT6+f8l/dQJANoPHMKIh2ajtbe/pvsSq0wUr0il5qSsPaf2d5Czbb7NJ52iKHL48GG2bNlilffo168fQ4cORaPRNIlgSpKFrOzFJCd/gMkk15i5u8fSLvol7O2DL7n+uwdiMIoixbV6Ky9N7szYd7ezL62E/uEeOKtqvUupP2L9+WA6Pi46Zo2W7c9u8ggkPqecL3elMLaznzxxLXu7u39os/ehASxmOLtKJm3ZR6ibXIoaDSy9trmvA26//XZ69OjBV199xe23337ZxpLQ0FDuuuuuFsWwkTcbbLDhTwdJkvjP+nP8eCAdQYAPpnVjZEeflk22+yP4rbaQe/jLcMOTl9Vxa0usTlrNK3tf+V0M5qv27SPzsccRKypQBwcTtGAB2vCwNouXFV/Cxs9PUVNhQmuvYuSDnQjp5NGqRDH5SBwbPv2QmopyVFotsQ/MotOQ2GvuWKw5XUjpikSkajMoBJyGBeE8PAihBU0VeXl5rF69mszMTAD8/f2ZOHEifn4yGWrKfpSUxhEf/zqVlXLGzsEhiqjIl7G373nFjJ1aEPDRqBCBqnKZMIc42+GikiVDXC5yRjiWXsrQaC+8NSqk2hq5wVFeLDuUidkiolEprr0b1FgFR3+EffOgVO4CRqWT3Uz6zQa1Fzz4xydvr7/+Oo8//nij9mSVlZUcOXKEwYMHEx4eztdff92iGDbyZoMNNvzpMHdrIot2JgPw1k1dmNQ9oGUT7Z0LW16V/z3snzD4mUucE64HFscv5r/H5Hqe620wX7psGTn/ek3uKO3Vi8B5c1G5ubVJLEmSOLE1kz3LE5FECY9AR8bO6IKLV+tZa5lNJnb9+DVH1q8CwCs0nAmP/wN3/2vT2BKrTZSuSqL6WAEAKh973Ke1Q9OC2jyj0ciOHTvYt28foiii0WiIjY2lT58+TW5I0OuzSUh8m/x8WaNOpXImPOwJAgLuRBCUV8zYXdiMIEkSb607S+9QNzr4ymSjMRKWX6FnkKMn4gV/Hl6OWsyiRGm1Ee9rqWurzJc9g+O+gBo5c4idu9zl3edhcKy1cKitA/yj49VXX2XUqFHExMRc8tz58+cZNmwYFkvTBMMvBxt5s8EGG/5U+HJ3Ch9sjgfgpfEduD3m0mOhJmHffNj0kvzvIc/DkH+00gqbDkmS+Oz4Z3x2XPYJvbPDnfyjzz+ui8G8JIoUfPgRRZ9/DoDzhAn4/fvNNmtMMBksbPvhHAlxeQBEx/gw9K72qDUt8Jq9DEqys1j7yXvkpyYB0HPsjQy6835U16hwX3OumJLlCYgVRhDAbqAvbqPDUbTAJzcxMZG1a9dSWloKQIcOHRgzZgwuLk1rspGlPz4nNW0BoqgHFAQE3EZ42JNoNHJt5BXttmjYWfqvVac5l1PB0pmNdzxKFzQvCBf890JlkRZn3AoT5Czb8f+Bpfa43C0M+s+G7neC5tqaSX4vXCljajKZmkzQrwQbebPBBhv+NFgcl8Eba+TjoSdHRPPQoPCWTbR/gWw0DzD4WRj6fCutsOkQJZF3497lx7M/AvBIt0eY2W3mdREiFfV6cl54kYoNGwDwnD0bz0dnt1nssoJq1i84RVFWJQqFwMCpkXQZGthq8SRJ4tyubez64StMBj12Ts6MnvUEEb0uzXw0B6LeTOnqZKoPy4RT5WWH2y3RiN5qhGaapldWVrJu3TqrQ4KzszPjxo2jffv2TRovS39sqJX+yALA1TWG6KiXcXLqeMWxBUYT6wvKuNvfw/qYAHy6LZHUwiqWz+p/SUeolbTV8pBeIW4oBAGFUE/W9CaRjn7OuNk3gxxLEqTvQ7PrI4TEjfWPB/SGgY9B+wmgaD1Cf71QXl5uJeQga/Slp6c3uKampoZvv/22WTp9l4ONvNlggw1/Cqw9lccLK2XT8IcHhfFYbGTLJjr4OWx4Tv73DU/Jx6XXWbndJJp4dc+rrE5eDcDTPZ7m3i73XhfiZikqIv2pp9GfOAFqNf5vvoHLpEltFi/tVBFbvj6DodqMnbOGMQ93xj/KtdXmN1RXs+XLTzm3ezsAQZ26Mu7Rp3F097jywKtAH19CyfJ4LGVyts3xhgBcRoWAStGsLlVRFDly5AhbtmyxumLUNSRom5jlrKw8T0LCG5SU7gdAq/UjKvIFvL3HXfF3pspsYWFmIZ9m5BPr7sTd/h5W2Q+DWeS+gWE8MjQShUJokC2q+7dg/T+5PMEsSg3i9Q51Y9ms/qiaUu8nWuDcGtjzCULWIZSAhIDQbhwMmAPB/a7732Fr4sMPP+T1118HZHJ70003NXqdJEm8+OKL1xzvmshbnX9ac69vblFqS8bZYv091miL9fdY45azeTy/8gySBLfHBPHC2PbWuZoV69BXCOuekZ8b+ITcoCBfeE3ra844g8XAszueZXvmdpSCktcHvM4I/xHXZe/1CQlkz5yFJTtb7iidOxf7Pr2vOE9LY4kWkaMbMzi6MRMk8Al3ZszDnXFw1V75WK8ZsXKT4ln78XuU5eciKBQMmHoHfSbdgkKhbP7vRt26DWbK16dSdSAXAKW7DrepUWhDXZq9xvz8fNasWUNGhmz15evry8SJE/GvNXe/2hxGYwlJyf8lL28JIKJQaAkOfpiQ4BkolXaXncNoEfkht4RPsoopqHVECNTVZ8eqDGYMFhFnrQoJsIgXkLVa1JjMiCI46mSaoFQKVBrMgIRWpcQsilQZLA18SRu9H1O13ISwfz5CSap8nVKLpdMtKG54HLyiuWCCK+7HH1ncd9SoUTg6OiJJEv/4xz+YM2cOwcENSzq0Wi1dunRhyJAh1xzvmsibwWBotk5OXSt0S2I1d5wt1u83zhbrzxWrpeOuR6z9KcXM/vEEZlFiQhcf/jk60mpQ3ZxYymPfo9n4LACmPjMxD3wOLjNPW91XpamSZ3c/y+EC2WD+rf5vMch/kDUj05qxLkbNgQPkP/MsUmUlqqAgfOZ+giIkpEnv4c2NZawxs/OnRNJPycXn7Qf60HdyKEqVdNV4TYkliSLHNqzmwPKfES0WnDy8GPzATEI6dcVoNAGmJq3z4lim1HIqf01FLDUCoOvjjf2IACRNwwaAq63RZDKxd+9eDh48aG1IGDRoEB07dsTe/uqWbZJkJjdvGRkZczGb5SJ9D/dRhIQ8jU4XgMkEJtOlc0iSxKaSSt5NLyRZL99DiFbNM8GeTPSsr6mrMsrF8sXVDffJUatCp1YiAGaxntQBKAUBJ52KCr2ZSoMFpSBgr1WiaeT42Gg0IlbkoTryFaqj3yLUFMvr07lh7nkf5p4PoFc6yd2wTeQQ+dX5/O/E/wDZdkqpVDJ79mxmz57dpPFtjf79+9O/f38AqqqqePjhh60kvS1wTeRNq9U2y5er7tuKVqtttjFvc8fZYv091miL9dde45G0Emb/7yRGi8jwdp78d1p3NKqm18NYY51ZgqKWuEl9Z6Ea/Raqy8Ruq/sq0ZcwZ+ccThedxkHtwNxhc+nt2/u67H3p0mXkvf46mM1ou3cncP481E30KG1urOLsKtYvPEVZfg1KlcDg26PpMKBpH2JNiVVVWsKGzz4i7bis/xXVdyAjHp4NSlWL91AyiZRvSKVqn+whqnTV4nZLFNoI12avMSkpibVr11JSUktc27dn7NixODk5odfrr7rGkpL9JCS8SWXVOQDs7CJpF/0q7u79r3g/B8uqeDMpm7jyagDcVUqeCvXhbn8PNBcVyHsfmw/nVssNAyodBMUgxr6G4BhlPbl01l1ED86uQn3oK9xzT4LZCN7t5UafyNhL1qI5/gNsfAGhtglBcguVpT6634FK44BSkpCasBeiJHIw5yCL4xezPWM7xmqZkMbFxTXLceJ649VXX23zGNdE3gRBaPa3xbox12OcLdbfY422WH/NNZ7OLuP+b+KoNloYGOnBB7d0QlOr9t4cqE4tRlj3pPxD35kIY/5z1dqa1r6v3Kpcpm+eTkpZCm5aNz4b+RmdPDpdU7ymjJE7Sj+k6PMvAHCeOAG3l15C7ezcJq9z4uF8fvvuLGaDBUd3LcPviyYwyrPVYqUeP8L6+R9QXVaKSqNl2H0P02W4rFBfl71sbixjWgWly+IxF8kZIIcYX1zGh6HQXv7jsbE1VlZWsnHjRk6ePAlc2pAgSdIV762mJovExP+QXyDbkqlULoSHPYGHx03Y2Tle9r4SqvS8lZzD+kI5Q2enUDAjyJMHvJzxcnS4ZJwkya4FUu+HkPx7gmhGse1NFD/eBI8cAM2lYwBI2wfhwyD2FdC5wtEf4OfbkB7aAn7d5H2p81lI3iZ3jwb0ggGPIXSYeEkTwpX2osxQxq+Jv7Ikfglp5WnWx7t5deMsZxvdh98b6enp+Pn5oVarL2lUaAwXH6k2F7aGBRtssOEPh6SCSu758iDlejO9QtxYdHcvFKK5+RMd/xn1uiflD5U+D8OYt697UXRaeRrTN00nuyobH3sfFo1aRLhLC7tkmwFRryf7ueep2Ch39Hk++igej8xq1pFzk2NZRPb/kszRzfKHVmB7N0Y+2BFBJbbK/Bazid3/+55Dq1cA4BkUwoQnnsMjUP4AbEktlGQSqdqUgX5/HkigdNbgdks0umi3Zs0jiiJHjx5l8+bNVgLZt29fhg0b1qSGBIulhrS0RaSlL0QUDcjSH3cQEf4EKpXrZY9Y8wwm3k/N5aecIiwSKAW4w8+DZ0J98daoLhlXYzKjUymRJJDuXA7US34waT7C+5FIOccgZGDjCx37dsOfR7wK59dB/Abw7VJfLycIENAT+j8Cwf2b9fd2qvAUi88vZn3Kegy1WTsHtQMTwycyrd00vBXe/I//NXm+64mwsDD27dtHTEwMoaGhV/0SYdN5s8EGG/5SyCiu5q4vDlBUZaSTvzNf3dcHe40Kvb6Z5O3EUvh1NgISUq8HEMa9d92J27nic8zYPINifTEhziEsGrkIf8e2q4Opg7mwkIxHZtd3lP77TVxuvLFNCr5rKoxs/OI0WeflY8Keo4Ppe2M4gkJoFU/U0twc1n7yLrlJCQB0GzWeIXc/gFrTcj06Y0YFxUvOYy6oAcC+lw+uE8JR2DXvI7GuIaEu0+Ln58eECRMICLi6aLQkSeTnryMh8T8YDPJxratrX6KjX8HJ8fINORVmC5+m57Mgo4AaUSbHYz1deDHcjygH3SXjaowWvt+fyvm8St6/pStwAWmjVvbDUC7/YNdE4ipJIFnAUIGgc5UfqpsLYNBTTZsHqDHXsD5lPYvPL+ZM0Rnr4+3c2nFr+1sZHzYee7Ws91b2Bxbp/eqrr4iIiLD+u7lZ++bCRt5ssMGGPwzyyvXc+cUBcsr0RHo78t0DMbjYqZtPOk4ug5XTESQRc7e7UI5//7oTtyN5R3j0t0epMFXQ3r09C0YswMPu2uQrmgJDYiIZ02dgys5G6eJC4Ly52Pfp0yax8tPKWb/wJJXFBlRaJbH3dCCylzfQOp2BZ3dvZ8sX8zHW1KBzcGTUzMeIihnQ4vkks0j5b+lUbM8ACQRHNW5TIrHv2DxP3LqGhD179iCKImq1muHDhxMTE4NSefWazIqKM8QnvEFp6UEAdFp/IqNexNtrzGU/9I2iyHfZRXyYmkdRbQdpb2d7XonwJ8b1UpcHg9nCz3tS+HR7MoWVBgZEuNcSLPl5axxJgv0LkLrdDt5X1our7waV4NjP4BKE1HUq1IlKN+NvLLU8lV9P/sqqpFVUGCsAUCvUjAkdw7R20+jm1a3NCVBr4t5777X++7777mvzeDbyZoMNNvwhUFxl5K4vDpBeXE2Qux0/PNgXD8cWZFdOr4QV00ESkXrcjWnkOyivg2PBhdiVuYuntj+F3qKnp3dP5sXOw0lzqc9ha6Nq717Zo7SyEnVIMMELF6IJDW2TWGf3ZrPjp3gsZhFXH3vGzuiCu3/zjdkbg1Ffw7avF3F6xxYAAtp3ZNycZ3D29G75nFmVlCw9jylXLui36+aFbnQAdm7Ns7dKTk5m9erVVkHWdu3aMW7cuCY5JJhMJaSmfUp29mJk6Q8dISEzCQl+GKWy8eY/SZJYlV/Kf1JySK2RC/Yj7bW8GO7HWE+XSwiOwWxh8cEM5m1LIL9Cvj7QzY7pgyNqM24XESKzQT4CvZKbwYWkDUA0Q6fJ0O02aIaNm0k0sS19G4vPL+Zg7kHr44GOgUxrN43JkZNx0zXv2PrvCht5s8EGG353VOhN3PvVQRLyK/Fx1vLjg/3wdWmBV+KZX2HZg/KRTvc7YeLHYDC2/oKvgA0pG3hx94uYJTM3BNzAB0M/wE7Vet6dl0PJ0qXkvvZ6m3uUWswiu5YkcHqnrPIf2tWTEfd3RNvMI8fLoSAthS0LPqYkJwtBUNDv5lvpN+U2FE3IaDUGySJSsS2D8q0ZIEooHNS43RSJrpNHs451L25IcHJyYty4cXTo0OGqY0XRRGbWjyQnf4zFIh9RenuPJyryeXS6yx+j7y2p5LXELE5Uyev01qh4JtSXO/w8UCkakjCTRWTZ4UzmbU0kq1Q+DvZ30fHo8Chu6RXYqKQHhgqwGEHnQkOVN+oJm3SRoZbFKBvIa51AqW6SF3BuVS7L4pexImEFBTWyN6xCUDA4YDC3tb+N/v79m2QJJ1ZXX/Wa3wtNaVK4ELaGBRtssOFPjRqjhQe/OcTJrDLcHTT88GBfgj1a4Gl4dg0se0Ambl1vgxvn1h/nXCesSFrBO4ffQUJibOhY/n3Dv1Err81X82q4tKN0ouxRqtG0eqzKEgMbFp0kL6UcBOg7MYxeY0IRFNd+vCVJEkfWrWLnT18jms04unswbs4zBHXs0uI5TblVFC85jym7CgC7Lp64TopA6ahp8rFuYw0JPXv2ZOTIkU2Syiou3kN8whtUVck1e46OHYiOegU3t8tbd52trOGNpGy2FsvHiQ5KBbODvZkR6IXDRVI5ZovIiqNZzN2aQEaxTNq8nbRMvyGEuwaEoVM38jEvSXKdm9kA9u5y9uzC/ZAkkC5uNhHkDlJ9mdxtqrpyVlyURPZl72Px+cXsyNyBWDufh86Dm6NuZkLwBEI9rl7YL0kSNYcPU7piJTlr117x2t8TTWlSuBC2hgUbbLDhTwuD2cKMHw5zMLUYJ62K7x6IIcqnBceL59fD0vvk45wuU2Hyp7I0wXVUZP/q1Fd8dOQjAKZFT+PFvi+ibGOPRlGvJ+f5F+o7StvQozQ7oZSNX5ymptyI1l7FyAc6EdK5dWr4qsvL2PjZRyQfiQMgondfRs98HDunlml5SRaJip2ZlG9JA4uEwl6F66QI7Lp6NWtvLm5IqHNIcHd3v2onaU1NOvEJ/6awUD76VavdCAqaQ0jwnSguc9SYpTfyTkoOS3NLkACVALd7u/KPCH+8tA3JuEWUWHU8i4+3JJBaJGekPB01zBoayR0xQWAxob2MJuIXR+ezJWMbKZWZ6JRaunl144meTxDmElp/kbFSJnB1WTmzXiZuWieOFp3i/k0PEekawdKJS7kwaydJEtvSt/H+4ffJqMiwPt7Htw/T2k0jNigWleLSbtiLYcrOpuzXXyld+Qum2v0Xr5HwtCWuR5PChbCRNxtssOF3gdki8sT/jrEzvgA7tZKv7+9D54Cr1w1dgviNsPhuEE3Q+WaYvOC6GltLksSHRz7k61NfA/BQl4d4rMdjbf5Gfr08SiVJ4vTOHOJ+TUMUJTwCHBg7swsuXi3IjjaC9FMnWDfvfapKilGq1Qy49W56j5+MQtGyrKkpv5ripfGYMuSsla6DO243RaF0bnom0mQysWvXLnbv3n1JQ4JCcWVvU7O5itS0z0hP/xJJMiIISgID7iY0dA4WixZBuPR3s9Rk5pO0fL7MKsBQ62ow0cuVF8J88VNI6DT12VtRlFh7MoePtsSTVCBnFN0dNMwcEs5d/UKw16iQJAm95fIuE4fyDnNbxI10dovGIlr45Mw3zNw8nV8mLMa+ruasLvtWl702VQMSFZU5vLj7Rfp6dafIUAL68lqCJ2fbBARWJa0ioyIDR7UjN0bcyLR204hwjbDGv1zWU9Trqdi8hbKVK6jat9/65Uthb4/T2DG4jhwJw4Zd9r5+T1yPJoULYSNvNthgw3WHKEk8t/wk60/lolEqWHRPL3qHNk3xvwEStsDiu2Ti1nEy3LQIlNfvbc0iWnjzwJssi18GwJyuc3i4+8NtTtwMiYnkzJiJuY07Sk1GC9t/OEf8wTwAovr4MOyu9qi1106ORYuFvUt/4sAvS0CScPcPZPzj/8DJx69F+yeJEhW7MinflAZmCUGnxHViBPY9vZs1X51DQnGxbOkUHR3NuHHjcHV1leNcwZc1N+9XkhLfxWCU98vd7Qaiol/C0SEKSZKwWBqSPr1F5KusQj5Jy6PULGeV+rs68HKEPz2dHWQSVksURVFi4+lcPtqSwPk8mZi62quZPjice/uH4nAFUeGLsWDs1/W1bJLEW54duX/TQyRX5dDJzh0BAexcGw6yl7Osiw79l7s73YdCUHAw5yDoXJCQrCLEAAFOAfyr/78YGzbWKvNxOUiShP74cUpXrKR83TrEysr6kDExuEy5CedRo1DY2/+hpUJsIr022GDDXxqSJPHv9fGsOJqFUiEw944eDIryav5ESVvhf3fIBdQdJsLNX1xX4maymHhh9wtsTN2IQlDwcr+XGR80vs3jVu3dS+bjTyBWVKAODiZo4QK0YWGtHqe8sIb1C09SmFGJoIABUyLpFhvUKsS0LD+PtXPfIydetoDqMnwUw+6djkqrbZE2nLmwhvIl5zFnyB/82mg33G6OQuXS9G7lyspKNm3axIkTJwC5IWHs2LF06NDhqvdcXn6C+PjXKSs/CoCdLpioqBfx9BzR6FiLJLE8r4R3knPIMsgZsnYOOl4K92OER0P3C0mS2HQmj4+2JHA2R252cNKpeHhQOPcPDMVJ14yaykuIpwCCgJPOle/GflfbWCNcVvLDZDExq9ss7FR2mEQTN0bcWDtLQ6eEZ3o/c9U9M+cXULRxI2W//IIxOdn6uNrfH5ebbsLlpsloAgObfm+/M/5UIr11Hm/Nvb65+j8tGWeL9fdYoy3Wn2+N7208z09xWQgCvHdLV0Z19LnqHJfEStkBP9+OYDEgtRsHN395adF1G95XjbmGp7Y/xZ7sPagUKt4e9DYjg0ei1+vbdO9Lly0n97XXLvEobWrMpsZKP1PE5i/PYKg2Y+ekZujdUYR2bp5+2+Vixe/fw+ZFczFUV6Gxs2fkw4/SbsCgZq3PGkOUqNqfQ/mGVCSTiKBV4jI+DPvePgiCcMV56uKIosixY8esDQkAMTExDB8+3FrXduE8F67RYCggOfm/5OTKmVel0p6QkFkEBT6AUtlwbF2srUXl/Ds5hzO1HaT+WjXPhvoy1dcNZe0Hft38287n88GmeE7nyJk2R62KBwaG8uANYTjbqS9Z22X33mKC3FMQ0MNanXbhqCpTFaIkWjs+G5vTIlmoNFVaJW/MohmTaMKOxjupG5tDNBio3LaNshUrqdqzB2pFhgWdDqdRo3CZchP2ffogKBpfR1uITLcW/lQivQaDodnfkgwGQ4tuqiXjbLF+v3G2WH+uWC0d19wxn+9O5bMd8rfsV8a1Y2yHpss11MVSpO9Bs/QuBLMeS+QojBMXgEkEU+PztPZ9VRgreGr3UxwvPI5OqeOdge/Q36c/BoOhzfZeEkVK582n7Gu5rs5h7Fgcn38Oi709llZ8D5YkiRNbsji8Xhax9Qx2JPb+aJQ6qUW2WhfGMhkM7Pn5G85slwv4fSKiGDnzcZy9fBr8DjR1Dy0lBipXpWJOlYmNIsQB58nhKF21TV5rdnY227dvJzMzU16Tjw+jR4/Gz8+vwZHlxaipqSQ75xsyMxdgsch1Z16eEwkJeRKNxhuTScJ00e/jyUo9b6Xmsb9SftxJqeARf3fu83NDp1BgMhgwIb8Ge5OL+WRbCiey5EybvVrJXX0Dua9/MG72asCCXn/lzI3BYEAwVqI6/gPKQ5+j6DgJAnpwMf2pNFVitBhx1bpecb5yYzl2SjuUtTV7EhIWqfE1mEwma2ZJkiSMZ85SuepXqjZsRCwvt16n7dEdx4k34jByBApHWW/PYGxc2keSJDLiiwDo06cPSqWS2bNnM3v27Cuu+3rhTyXSq9Vqm9QqXYe6bwJarbZZb3AtGWeL9fdYoy3Wn2eN3+9L44PfZOL2dGw49w4Mb36s3MMIy+5GMNcgRY1CMe17dFeQLGjt+yqqKWL2jtmcKzmHk9qJ+bHz6e7dvcWxmjJO1OvJ+ec/qdggd5R6PDILj9mzMRgMrRrLWGPmt+/OknKsEICON/gxaFo0CpVsc3UtsQoz0lj3ybsUZWaAIBBz4y30n3oHSpXqsmOuRDCrD+ZSti4VyWhBUCtwHhuKopsrdnZ2TVpjXUPChQ4Jw4YNo2/fvldtlCgs3EZ8wr/R61MBcHLqSnTUS7i49Gz0+tQaA++k5PJLfikAGkHggQBP5oR4436RjMfepEI+3JzAoTTZakynVnB77wAeGRaFp1MzPmtLM1Dt/RTViR8QDDK5lS6QzSlatIiKzVswJCeDVoN9j544PPP0ZY/fJSTMoplyfRF5i77FsG4zYlExCh8vKh+4C99b70StqD++VavVCKWllK1ZQ9mKlRgTE63PqXx9cZ50I7qxY3GKjr7q61WUVUl8XB6Jh/LJz5HJW1xcHM7OLetE/qvgmsibIAjN+mO+cMz1GGeL9fdYoy3WH3+Nyw9n8sqq0wDMHhbBQzeENDuWMisOYcntCKZqiIhFmPY9qK/+gdZa95Vdmc30zdNJK0/DQ+fBwpELaefe7ppjXWmcuaiIzEdmU3P8OKjV+L3xOq6TJyNJUqvGKsmtYv2Ck5TkVqNQCQy+NZpOg2R/zmuJBXBi83p2fP8lZpMRB1c3xj76NCFdujdrfXUwlxooWR6PIaEUAE2oM+5To1G666wabFdb49UaEi6HqqpkEhLfpKhohxxb40lE+LP4+U1BaERPsMBo4qPUPL7LLsIkSQjAJE9nXowMINiu4ReOA8lFfLglnv3J8pq0KgV39QthxuBwnNQSOp2uaXufcxz2zoPTK1CLtV7Anu1gwKMIXW6z1rJVxx3C7tYp2HWIxElhT/HHc8l48CHC16xGYW+PdEl+Dtx0buQ8/RhSUTF+b76BJcAbQ2E+Dgo7VBdJnxQtWkTBJ3OhNvsmaLU4jRiBy5SbcOjXD2o7di/3epUX1hAfl0dCXB7FtRp9AGrN9esiv1ZYLBaWLFnCtm3bKCoqwsPDg2HDhjF16lRUqmuvzbU1LNhggw1tig2ncnl22XEA7hsQytMjo5t/BJcZh2bp7QimKggfCrf92CTi1lpILktm+qbp5FXn4e/gz6JRiwhxDmnTmIakJDJmzMSUmYnCxYXAuZ/gEHN5YdeWIvlYAVu+OYNJb8HRTcuY6V3wCbv2rEZNZQUbP/uY5MMHAAjr0ZsxjzyJvXPz5WAkSaL6cB6lq5ORDBZQKXAZE4rjAH8ExZVr2+rQWENCbGwsXbt2vWK2zWyuICVlLhmZ3yJJZgRBjZ/vnURGPo5afek+VZktLMwsYH56PlUWuaZrmLsT/wz3I0IloNPVS5YcTivmg83x7EmUM0oapYI7+gYza2gEPs66Kx7dXrA5kLgF9n4CKTsBWXXNEjwAxQ1PIESOhIvuz+OzjzCYDThpnFAICnzefovMe+9Dn5yErlMnAPQWPaIk4qh2RBAE9EeOYikpJfiLz1E6O1Ntqkbh74ujxrl+HQCCQM2pU2CxoOvWFdebpuA8bizKCzJljb1e1eVGEg/nEX8wTxaBroVCJRDSyYPoGF9cg1U8sfDK2/FHQGFhIWPGjOHIkSOoVCo8PDwoKiriiy++4P3332fjxo14ejbPT/di2MibDTbY0GbYGV/AYz8fRZTgll6BvDKhI81O3mQehh9uRjBWIYUNRrjtZ1C3vd1UHc4UnWHm5pmUGEoIcwlj0chF+Dr4tmnMqv37yZzzmNxRGhRE0MKFaMNbt6NUFCUOrkrm8IY0APyjXBn9cGfsm6GHdjlknjvNuk/eo6KoEIVSxeA776Pn2ButhejNgaXcQMmKRPTn5KyUJtgJt6nRqJuoM1fXkLBp0yYrEerbty/Dhg2zZhUbgyRZyMlZTmLS+5hMMrny8BhGVOSLKBR+qFQNvzyYRImfcop4PzWXAqOc9erqZMfL4f4McndqQMSOppfw4ZYEdsbLVlFqpcC03kHMHhaJv2sTf7fNBjixBPbNgwK5axdBCZ2nIPWfjdGtvVzW1Mj92ansGli2qZxdCPnxRxT29lZdN3uVnIGr2x9dp06EfP0VKBRYqqrQQsOShQviOE+YiPeTT6IND7/iLRhqzKQcKyQhLpfMcyUX8j8C2rkR1ceHiB5eaO3lI9k/slTIhXjyySc5f/48P/74I9OmTUOpVGKxWFi8eDEzZ87kySef5Pvvv7+mGDbyZoMNNrQJ4lKLmf79IYwWkXFdfHl7ShcUTcySWJF9FL6/CcFQjiWoH4rbfr6ygXYr41DuIR7d+ihVpio6enRkwYgFbW6cXbp8BTmvvip7lPboQeD8eajcW6CBdwXoq0xs+eoM6WdkQtQtNogBUyJQKK/NTkwULRxYsYR9y35GkkRcfHyZ8Phz+EZENXsuSZKoOVZAyaokpBozKAVcRoXgOCiwyXZcl3NICAgIuGJWq7T0EPEJr1NRIR/129uHExX1Tzw9hl4yTpIk1haU8Z/kHJJq5IxyiE7DC+F+3OjtiuICUnMqu5xPd55k23mZtKkUAlN7BzJ7WCSBbk38va4uhkNfwsHPoVLWk0PjBL3uhb4zwTVIzoI1cm91f3vCRT6mlqpKeUwtua4jbBdeJxqNSCYTglqNws4OJAmxqgrBZEbh4NBgPpfRoy67fLPRQurJQs4dyCHzTCkWc70Nl3eoM9F9fIjs7Y1DM2Re/mhYvXo1b775Jrfffrv1MaVSyR133EF+fj7/+te/rjmGjbzZYIMNrY5TWWU88HUcepPIkGgvPrq1B6rmEoOc4/DdZDCUIQX3x3jzD+g0Dlcd1lrYmbmTp3c8jcFioLdPb+YOn4ujxrHN4kmiSMHcuRQtkM+FnMeNw+8/b6G4ig1Tc1GUVcW2r+MpL9KjUisYdk97ovtceyaxoqiQdfPeJ/PMKQA6DBrGwDvux9mt+WTXUmGk9Nck9KfljJc60BH3qdGofZr2+jfmkFDXkKC8gsG9Xp9DYtI75OWtBkCpdCQ87DECA+9Gobg0I7m/tJI3krI5XC7bU7mrlTwV6ss9/h5oLsgynsoq46Mt8Ww5my/PqxCY0iOAOcOjmu7jW5wM+z6FYz/Wuh0AzgEyYet1r9XloDFUm6qJL46nm3c3AA5vSCP5WAGludUoVQK+wfb0n9oOt8uclkuSBKJIwpEiTuwvoSy/Bo2diqD2LvQd7oFjLXm7XBZTtIhknishIS6PpGMFmC7olHXztSc6xoeoPj6t5trxe0OSJDrVHj9fjM6dO7eK5ImNvNlggw2tisT8Cu756iAVBjMxoe4suKsXGlUziVvuSfhuEuhLITAG7lgCUtsavF+Ijekbee3Aa5glM0MCh/D+kPfRqdquxk40GMj+50tUrFsHgMfMGXg99liLjhmvhPiDuWz74TwWk4izp46xM7viGXjthDTx0AE2fvYR+soK1Do7Rjw4iw6DhrVIcNdwupiS9emIVXK2zXl4ME5DAxGaSP5b0pBgsehJT/+C1LQFiGINIODvN5XwiKfRai6tTYqvNvB+Qg6bi+TaLDuFgplBXjwS7I3TBX6i53LL+WhzAhtO5wKgEGBS9wAei40izLNpRFSRdQgOL4Sza7Cqs/l2gQGPQaebQHn5v4uEkgSWxi9lTfIaJkdMtpK37IRSugwJwNNLhag3ELejiNXzTnD7K32t7hkXE4zctCq2r8hk4C1RhHb1oKrUwI6fzrPzVz3jZnvDRaRYkiRyk8tJOJhL4pF8airq7boc3bWEdfegQ/8APAMdr9qMUZydSfz+PRzfua1Je/Z7Y8SIEWzZsoURI0Zc8tzmzZsZOnToNcewkTcbbLCh1ZBRXM2dXxyguMpIlwAXvryvN3bN7RDLOyMTt5oSCOgNdy0HrVOjx0BtgSXnl/DvA/9GQmJ8+HjeGPhGAxmE1oa5uJi8R2ZjOH4cVCr8XnsN15untGoMi0Vk3/Ikjm+VjcKDO7kz8oFO6Byu7b7MRiM7f/yaoxvkTJV3WAQTHv8Hbn4Bzc4uWKpMlP6aSM0JWapE7eeA29RoNP5NI5dVVVWsW7eOkydPAnJDwrhx42jfvv0VZUfy8zeQmPQ2er2s9ebi0ovoqJdxdu5yyfXZeiPvpeSyOLcYEVAKcKefB8+E+uKtrd/L+LwKPt6SwNqTOYBcwzWxqx8zbgimY6DH1TtHRQucWwv75qHNOFD/eORIGPAohA25rAuC0WJkU+om/nfufxwvPG593FXnav33xDndEKurkYxGlE7ujAj3ZeV/j1CSW4V3iHOjr115uUhgO1e6DgtAUChw8bKn56hAzu7LtRK3unGpJwrZtTiBiuL6v1mdo5rIXt5E9/HBJ8wZg9Fw2S5aSZIoykwnfv8eEg7soTBDrsvUmy7v1/p7o+7LAsDLL7/MlClTsFgs3HHHHfj6+pKbm8uPP/7IihUrWLFixTXHs5E3G2ywoVWQV67nzi8OkFduINrHke8eiGmedQ9A/jn4diJUF4F/D5m46ZwbsfVpG3xx8gs+PvIxALe2u5UX+75oVZ1vCxiSU8iYOQNTegYKJye5o7Rfv1aNUV1uZOPnp8iuldfoNjKA/pOjUF5jfVtRVgZrP36XgrQUAHqNn8wNt9+LSt18QlhzuoiSlQmIlSYQwGlYEM7DgxGakLEVRZGjR482cEioa0i4kg5pZeV5zp1/jfLygwBotb5ERjyHj8/ESwhFqcnM3PR8vswsQF9rHD/e04UXIvyItK+PkZhfySe/JbD6RLb1V3Z8Vz8ej40iytvx6plIYxUc/RH2fwolKQiApNRAl2kIAx4F7w6XHZpRnsHS+KX8kvgLJQZZJ04pKBkWNIxp7abR16+v9b4kSZLr1uzlY0qtHdz8bC9UV/CsbT8ggMjefkgiIEggQXhPXyJ6+V1ybVZ8CRXFetRaJeE9vIjq40Ngezfr79zlXCEK0lJIOLCH+P17KM7OtD6nUCoJ6dId307dYOWmK+/h7wRPT88GvzeSJPHf//6XDz74oMFjAL169fp97bFssMEGGwCKq4zc9cUB0ourCXa354cH++Lm0MyuxcKEWuJWCL5d4e6Vl5pjtxEkSeLDIx/y9SnZweD+DvfzRO8n2pS4VR08KHeUlpWh8vcnaNFCdJGRrRojN7mMDQtPUlVmRK1TEntvB/zbO6FoYsF/Y5AkidPbt/Db1wswGwzYOTkzZvaThPfo0+y5xGoTpauTqT4q14KpvO1xmBSCY3gTslNcuSHhcjCZSkhK/oisrJ8AEYVCS3Dww4SGzECpbFhz1ZhxfF8XB54L9KC/l5t1jSmFVXzyWwK/HsuiltsxppMvj4+IooOfXEh2xUxkRS4cXARxX8qlAgA6V6Q+D6Hvejc6z5BGM21m0cyOjB0siV/C3uy91se97b2ZHDaZaR2m4ePgc2m8WluqOoZpNIhIEghIUNekUNfcUNfEoBRQqCT0NWbr6a1SJaCxu5Twufk7MPrhzoR28UB1hcy7JEnkpyQRv3838Qf2UJqbY31OqVIR0rUH0f1uIKJXX3SOjn/obtNXXnmlRTqILYWNvNlggw3XhAq9iXu/OkhCfiW+zjp+fKgv3s7NrA8rSoJvJkBVPvh0gXt+Bbu27eqsg0W08OaBN1kWL/tTPt3raW6NuLVN34jLfv2V7JdeBpMJXdeueH34AVp//1aNcXpXFjsXxyOaJdx87Rk7swuuPvYtqkOrg6G6mi1fzOfcHlmoNrhzN8Y++jSObs3vhq05V0zJigTEcqOcbRsciFNsMAZL4/ZIF8JkMrFz584GDgmDBg1i4MCBl21IEEUzWdk/kZz8EWazTALc3UfSLvqf2NsHNbjWIkksyy3h3ZSGxvH/DPdjhLuTVacwraiKT35LZOXRTCtpG9HBhydGRNE5oAl6dnlnYN98OLkE6u7bLQz6z4bud4DavtFygbyqPJYnLGd5/HLya2TiKyAwIGAA06KnMShgEGaj+ZLMo5VAXlBLaawxYzFL6BxVVoIoCMIlZFG0iBhrzKg0SpQqhWx7pbdgrDGjsWtIJToNvDx5liSJnITznN27k5TDByjLz7M+p1SrCevei6i+A4noFYPW/vo1KF0rWqODtDmwkTcbbLChxagxWZj58zFOZpXh7qDhh4f6EuTezI6x4mSZuFXmgncnmbjZt640xuVgsph4cfeLbEjdgEJQ8Gr/V7kp8qZrIjhXgiRJFM6bT+H8+QA4jRmD33/e4up0pekwmyzs+l88Z/bIWYzwHl7E3tsBjU51TV1uOYnxrJv7HmV5uQgKBQOn3UXMpFua3VQh6s2Urkmm+pD8oa3ytMNtWjTa4Npaq6ucJiUlJbFmzRpKSuSjwXbt2jF27Fi0Wu1lxXaLi/cQn/AGVVUJADg6ticq8iXs7Lo3IDiSJPFbcQX/Tsrm7IXG8WG+TPN1RynIUjdZpTUs2hPP8iNZWGpZ2/D23jwxIoquga5XvgFJguRtshNC0m/1jwf1hQFzoN04UCjrr63bN0lkf/Z+Fp9fzI7MHVZfUXedO5MjJ3NL9C0EOQVZ78OM2TpWf/48xvQMnEbEWh87vmkdxzato7wwH0EAj8Bg+k25jbAevS9arrwGk8FCTuIZ9i75hqLMdBzd3Ok1fgrR/UagrpWTu2xtoSiSFX+WhAN7STiwl4qiAutzKo2W8B69ieo3kPAevdHY/Tk7TtPT0/Hz80OtVlszwVdCcHDwNcW7JvJW50PX3Oub+wbSknG2WH+PNdpi/X7jDCYLjy0+ycGUYpx0Kr57oA8RXg5XnaNBrJJU+GYiQkU2kld7uOcXmbhdNEdb3FeNuYandzzN7qzdqBQq3h70NqNCRrXZHopGI7kvvUz5arm43/2hh/B68gkQBCS9vlV+PyqK9Wz8/BT5qRUgQL9J4fQYFYxQSzpacm+ixcKRdb9ycPnPiBYLzp7ejHvsWfyj21vX0tQ16hNKKF2eiKXMAAI4DPDHZXQIglp51fXVOSQ01pBQp7128bjqmjQSE/9DYeEWANRqN8LDnsTPbxqCoGww5mh5NW8mZ7O3VLZjclEpmRPszQMBntjV1mplllQzf2siSw9nYq4lbUOivXhiRBTdg1yvvB9mA4qTi+HwIsiT9eMkQQEdJkK/2RB0gXtG7RySJFGsL2ZD4gaWxS8js7K+DqyXTy+mRk9lRPAINEpNg9iSJGEuLqZ4y2+U/fILhrNncbvn7gbkTefkRt8pd+IdEoQgCJze+Ru/vv9v7nr7IzyDLnUPKcvPY82Hb9IldjRjH32a7PNn+O3LBag0DnQaOuSSexdFC1lnzxB/YA+JcfuoKqkv6Ffr7Ajp2oP2AwYT1r0X6osI9OXQGhIbbYWwsDD27dtHTEwMoaGhV83c/641bwaDodnfUA0GQ4uOI1oyzhbr9xtni/XnitXccWZR5NnlZ9idVIydWsGC27sS4a5t8vuBwWBAUZ6J5qebUJRnIrpHYbh1KSgv31XamvdVaazkyd1PcrzwOFqllncHvkt/n/7W9bf2HlrKysh/6mkMR46AUonHiy/gNGUKBqOxxfEuHpOTWMa2b+PRV5rR2CsZdnc0Ae1dL7Eia06s6rJSfvt8Hhmn5K7FiJj+DL13BloHhya91nWxJKOFqk2ZGA7LGReFmxbHSaGoQ5wwWExgMV0ypg6SJHH8+HG2b99ufa5nz54MGjQIrVbb6GtmsVSRmbmI7JzvkCQToMTX91aCAmejVrtgNJoBMwaDgVS9ifcyClhfXAnIxvH3+boyK8ADV5USTEZSi/Qs3JXG8iPZmGpJ24BwNx4dGk6PIPl49LL7oS9Fdex7VIe/RFspS4ZIanssXW/H3Hs6kmstUbpI+PdY4TFWJK1ga+ZWTKK8Pw5qB8aHjOemiJuIcIkAQDSJ6E3yWMlkomb3HirXrKZ65y4w12bf1GrU0dHW+Y01ZoI69ULnoLYKHg+89R6Ob15PTsJ5PINCMOktSJJkPRI9s3MTju6eDLr9QZQqATffQLLOx3N88yo6DxvS4JbP7NnJjm8XUVNeX6OmsbMjtEcfInr3I6hzV8yi7NlqASzNeN8A6NOnD0qlktmzZzN79uwmjW1rfPXVV0RERFj/3db1b9dE3rRa7RW7eS5G3TcqrVbbrBtryThbrL/HGm2xrv84UZR4ZcVJNpzJR60UWHBXTwZEezcrFmWZaP93C0J5JpJ7BMJ9q9E5XV4otjXvq6imiEd2PsK54nM4qZ2YFzuPHt492iQWgDEtjeyZszCmpqJwdCTgo49wGDjgmuJdOAbgxNZM9q5IQhIlPAMdGTOjM86el9osNSdW6vEjbPj0Q6rLSlFpNAy9dzpdho9q9hrJ0lO2PAFLifzB69DPD+exoSgaKWS/eH11DQkZGbLEiZ+fHxMmTMD/ovrAunEajZq8/FUkJb2H0SjXgrm5DSQq6p84OkQ3GJNnMPJedin/yy/DglymP83XjWdCfQms9R/NK9fz6fYk/ncwA2OtT2n/cA8eGRzMwGjfK+9FSarcNXr0R9mTFxAdfSFmOkLvB1DauXLxDlQYK1iTvIYl8UtIKk2yPt7JoxNTo6cyJnQM9upLjxX1Z89S9suvlK9Zg+UCyQpdl864TJqM87hxKN1crY+bjfK96CtlUiiKFpIP78Nk0DfIqIpifaYrN+k8IV17YDJaMOolBAFCuvTg3O7fsJjNKC8wW888dZya8jK0Do5E9ulHVN+BBHfuZu1ErsuUNvdvrI68xcXF4ex87f67rYl7773X+u/77ruvzeNdE3kTBKHZ7LJuzPUYZ4v191ijLdb1GydJEm+uO8vSw5koFQL/vbkzg6O9mxerPBvt4qkIpWngFoZw3xpwvlRuoCXru9q4nMocpm+eTmp5Ku46dxaOXEh79/ZtEgug+sgRMh+ZjaW0FJW/H0ELFqCLjr7quKbGMptEtv9wnoQ4uX4suq8PQ+9sj/oKHX5Xi2Uxm9j9v+85tFrWovIMDmXEjMfwj4hq1vpEo4XqDRnoD9a6CrhqcbslGl2k69Xvy2xm586d7N27F1EU0Wg0DB8+3JpxaQyVlSc5feYdysvlLKGdXTBRkf/E0zO2wborzBY+Tc9nQUYBNbVdlyM9nHkx3I8OjjLhza/Q89n2JH48kI6x1r4pJsydp0ZG0zfMHb1ef/k9zDgIe+fCuTXIuhqAT2ek/rMxRI5H5+B8ybjThadZEr+E9SnrqTHXyOtX2TEmdAyTQifR07/nJWPMRUWUr1lD6cpfMJw7Z31c6eWJy8Qb0Y0bi3OnTo2u0d5FJqcFaan875VnMZuMaHR23PjUP/EIlGuxNHaqBmOry0pwcu+FvZPGenzp4uWOaLFQXV6Go5u73KcqCPiGRdJuwCCCOnZpQOouREt/522QYWtYsMEGG5qMD7ck8PWeVADeubkLIztcqj5/RVTkwnc3oihJQXINqSVurdtleTmklqXy8OaHya3Kxc/Bj0UjFxHqEtpm8crWriXn+ReQTCZ0nTsT9NmnqLy8Wm3+8kI92745QVFWFYJCYOAtkXQdFnhNH3Clebms/fgdcpPkwv5uo8Yz+K77rUX5TYUhtYzipfFYiuTjMIcYX1zGhaHQXf0jJzk5mc2bN1NaWgpA+/btGTt2LC4ujXdvGgx5JCa9R27uSgCUSgdCQ2cTHHQfCkW9tZhRFPkuu4gPU/MoMsnHid0ddbwcGcBANycACioMLNyRxPf70zDUkrY+oW48OSKa/hGyfEmjdVeiRSZre+dB5sH6xyNHQP9HIXyo/PMFx4PVpmrWp6xnafxSThedrh/iGsnU6KlMiJiAk9qpoY+q0UjFjh2UrfyFyp07rceiglqNY2wsrjdNxmHgQFAqLznGrS43YOekAcmq9IGbfwB3vf0xhqoqEuL2svGzD5n26n8arXmru21JFK3jxdoHBUGwEjeAbqPHXbpHfyNs3bqVoqIipk6dCkBeXh73338/R44cYdSoUSxatKhZp5aNwUbebLDBhibh853JfPKb/KH++qRO3NwzsHk1r5X58O1EhKJEROdAhHtXg0tgG622Ic4WnWXWb7Mo1hcT6hzK56M+x9fh2v08G4MkSRQtXEjBRx8D4DgiloD33pNFUVsJ6aeL2PTlaYw1Fuyc1IyZ3hn/qGuTVjm7ZwdbPp+HsaYGnYMjo2Y+RlTMACRJanJNkmSyULYpjcrdWSCBwkmN2y3R2LW7evdwRUUFGzdu5NQp2RvV2dnZ2pDQGCwWAxkZX5Ga9ikWi+z16es7hciIZ9Bq67XNREni1/xS3k7OIU0v1xhG2Gl5IdyX4Y5a7OzsKKo0sHBnMt/tS0Vvkklbz2BXnhwZzQ2RnpcnxIZK2Wt0/6fyMSlAragu/WeDT8cLNkcmOhdaVlWa5Do7tULNqNBRTIueRg/vHtZ4dcfB+tNnKPvlF/lYtJbUAui6dMHlpsm4jBuH8gL7rzqCWV1uJOlIAQlxedg5qxk7o4uVeAmASq3Gzc8fQRDwjYwiLymBI+tXMWr6nAbzIEk4uLpSWVrChdS1prwMhVKJnZMztCBT/VfFK6+8wsiRI60//+Mf/2DXrl2MHDmSZcuWERUVxcsvv3xNMWzkzQYbbLgqfj6Yzr/XnQXg2dHtuKd/aPM6v6oK4dsboTAeyTkA4+3L0bpeW6t8U3Gs4BhP7X6KSlMlHdw7sGDkAtx1bSNFIplM5L7+OmUrfwHA/b778H72GYQrmKE3a35R4vCGNA6sTgYJfEKdGTOjM45uLf8Wb9TXsPXrhZzeLndkBrTvyLg5z+Ds2fQ6RgBjRgXFS85jLpCP/ex7eaMd4Y/O9cr2VqIocvjwYbZs2WJtOqhzSKir6bsQkiRRWLiZhIT/UKOXJRmcnbsREvwcXl4xDQjEzuIK3kzK5kSlvCZvjYpnQn253c8DlQA5xeV8siON7/alUW2Uu/+6B8mkbXDUFUhbRQ7s/g4OfwX62qJ8Ozfo/SDEPAwX1W8aLAY2pW5i8bnFDSyrgp2CmRo9lUmRk3DTNSTf5oICSlevpnTlSkwJidbHVV5euEy6EZfJk9E2IupsqDaRdLSA8wdyyEkos2bMwnrIWfK6W2rs3iRJwmIyyX/bktSAqPlFtSf5SFyDceknj+ETHnnZo9G/K+Lj43nuuecAMJvNrFy5knfeeYdHHnmE999/n6+++spG3mywwYa2xarj2by4UpZnmDEknEeGRjRvgupi2au04Cw4+cG9q5Hsr89R6e6s3Ty580kMFgM9vXsyL3YeThqnNollKS8nb84c9AfjQKHA56V/4n7HHa02v7HGzJZvzpByXPb+jO7nzbA7OlxRwf5qyE9NZs3H71KSnYkgKOg75Vb633wbimaQTcksUv5bOhXbM+qzbVOi0LV3v2pmNjc3lzVr1pCZKUtg+Pv7M3LkyMtKLVRWnic+4U1KSmQ3AY3Gm8iIf+DjcyMGQ71a3omKav6dlMOOkgoAHJUKHg325uEgLxyUSkqqjHy+K5lv9qZaSVvXQBeeHBHN0HZelydtuSdh3zx0J5cj1HaA4h4O/R6RRXU1DUVl08rTWHp+Kb8k/UKZQSZ5KkHFsOBhTI2eSl+/vg1cPESjkcqt2yhbuZLK3buhVk5C0GhwGhGLy0034dC/P8JFZMlktJB6opCEuDzSThchmutpl3eIE1F9fIiOadhgsevnbwnr3gsnDy8MNdWc37uTzDOnmPL8qyBJ7Pr5WypLihk7+ykAuo0cy7FNa9nx/Rd0GT6G7ISznNy6mXGPPdP4Xv2NUV5ejmttJvTw4cNUVVVx4403AhATE9Mqgr428maDDTZcFlvP5fHU4mNIEtzZN5jnx1ze5LtRVBfDdzdC3ilw9IF718gfdtfBZH5j6kae3/U8ZtHMDQE38MHQD7BTtd7R5YUwZmaSMWMGxqRkFPb2BHz4AY5Dhlx9YBNRnFPF+gUnKc2rRqESGHxrNOG93VGqW2bfJUkSRzesZucPX2Exm3F092DcnGcI6nipGfuVYMyqpGTpeUy58rGlXXcv3G6MQGGvvmJm1mg0smPHDvbu3VvbJaohNjaW3r17YzReKllsMpWSnCJbWkmSBYVCQ3DQg4SEzEKlqtcWTKsx8E5KLivzSwFQCwL3BXjweIgvnhoVZdUm/rs7ka/3pFJpkOvFOvk78+SIaGI7XKbxRhQhcQvsmwcpO+rMo5CC+yMMmAPRY+pFdQGTaGJb+jaWxC/hQE69qbyvvS+Twicxrf00vB3qs5qSJKE/dYqylSspW7sO8QILKF23btiPH4/HjRNRXXAsCmAxi2ScLSYhLo+U44WYDPW6YW5+9oR196BDP39cfRp3KagqLWHdvP9SVVqCxs4ej4Agxj/+LN5hEeirq6gsLqKiSP6iIAgCrj5+THn+X2z/9guObVyLg5sHw++fTnTfgY3O/3eGt7c3CQkJDBo0iC1bthASEkJgoFwiUlFRgboF/r8Xw0bebLDBhkaxL6mIWT8cwSxKTO7uzxuTOjePuNWUwvc3ydkKBy+4dzV4Rl4Xk/kVCSt4bd9riJLIyKCRvD34bTSqZnqtNhE1x4+TMesRLMXFKL29CVrwGXYdO159YBORfLSALd+cwWSw4OCqZcyMzviEOrfYBaKmopwNcxeSfFgurA/vFcOYWU/IdUtNhGQWKd+WQcW2DBAlFA5q3G6KxK7z1RtY4uPjWbt2rdWnskOHDowdOxZnZ+dLCJ9safVzraVVKQBeXqOJinweO7v6Y/dCo4n3U/P4Ka8MkyQhADf7uPFsmC8hdlrKakx8sDmer3enUFFL2jr4OfHI4FDGdwts3JnBpIcTi2X7qsLz8mOCEqnjJAw9H0IbPqCBhVR2ZTbL4pexMnElhTW1pAeBwYGDmdZuGgP8BmAymqyF6qa8PMpWraLsl18xJtXLgqh8fHCZNAmXyZPRhIWi1+tR1o4RRYnshFISDuWRdCQfQ1W9i4KTh46o3j5E9fHB3d8eg8FwqT2WKGI2mTAbDdxw691w693W5xQqFUq1GpVGg1KpYtycSzNqQR27cPc7Hzec8w8snPt7YcyYMbz44oucPn2ab775poGMyLlz5wgNDb3mGDbyZoMNNlyCYxmlPPRtHAazyIgOPrw3tVvzzMz1ZfDDFMg5BvYeMnHzatdm670Q357+lvcPvQ/ALVG38HS3p1Err/2bbmMo37iJ7H/8A8lgQNuhPV4ffYTuGm1v6iCKEgdXJXN4QxoA/lGujH64M/bOmhZ/YGacPsm6ee9TVVKMUqVi8F0P0mPMhGaRcmNOFSVLzmPKkbXL7Lp44jopAqXjlclxeXk5GzZs4MyZMwC4uLgwbtw42rVr/PfiYksrB4dooqNewt29PtNTZbawIKOATzPyqarVYRvm7sQ/w/3o7GRPud7Ex1sS+GJ3MhV6mei093XiiRFRjOzgg9HYiGBxVaFsEB/3OVTV2jhpnKDXvdB3BrgEIdUSZ4toYVfWLpacX8LurN3UVYl52nkyJWoKN0fdjL+jXCIgSRIGfQXlv22l7JdfqNq712oQL2i1OI0cictNk3Ho189aI1nXsJCXWk5iXD4Jh/OoLqvPTNo5a4jq5U1UHx98wpwbNDpY970gn/gDe8hLTWLEA7OwmEyItcexCpUKlUaDSq1pts3ZnwE7d+7kvffe4/Dhw+Tk5LBy5UomT5582et3797Nc889x7lz56iuriYkJIQZM2bw5JNPNivuW2+9RXp6Op9//jkxMTG89NJL1ud++uknBgwYcIXRTYONvNlggw0NcD63gnu/OkiV0cKACA/m3dEDtbIZb+yGCvhxKmQdlou471kF3h3absG1kCSJecfmsejEIgDu73w/T/R44hKHgdaKVfzVV+S//1+QJByHDMHvv+9jaqXGBH2Vic1fnSb9tCy42m14EP1vjkDZnNfhAogWC/uW/48DKxYjSSJu/gFMePw5vEPDmzyHZJGo2JlB+W/pYJFQ2KtwnRSJfbcry5+IosihQ4f47bffMBqNCIJAv379GDp0aKMNCXp9OvEJH1JYuBkAlcqViPCn8Pe/FYVC/sgyiRI/5BTx35RcCmtlP7o66Hg50p9B7s5U6E188lsCX+xKpryWtEX7OPLEiGjGdPJFoWhE8qMgHvbPh+P/A3NtVtM5EPrNhJ73gK5WqkSSyK/OZ935dSxPWE5edb2xej+/fkyNnsqw4GGoFfWCtDVHj1K68hfK169Hqqy0Xm/XqxcukyfhPGYMSqeGtZhFWZXEx+WREJdLRVH977DWXkV4Dy+i+vgQEO3W6Jeqktxszu7eQcqRg+Qly80OdfIfglKJRqtFpdY0qG38K2bQqqqq6NatG/fffz8333zzVa93cHDg0UcfpWvXrjg4OLB7925mzJiBg4MD06dPb3JcT09PNmzY0Ohz27Ztu2aZELCRNxtssOECpBZWcdeXByirMdE9yJXP7+mNTt0MQmKsgh+nQcYB+cPunl/Bt3PbLbgWoiTy9sG3+fnczwA83vNxHuryUJt8IElmM7lvvEnp4sUAuN1xBz4vvgBKJaZWqOUrzKxg/YKTlBfqUakVDL2rPe36tlzWpLwwn3Vz3yfrnJzxaj9oGCMffARNM6RLzAU1lK86hylTJh66jh643RSJ0unK2ba8vDw2bdpEdnY2AAEBAUycOBFf30vvx2yuJDX1M9IzvkSSTAiCkoCAOwkPexy12hWQZT9W5ZfyTkoOKTVyBirMTsMLYX6McNJiUaiZtzWBz3elUFYjNxREejvyeGwU47v4XUp0JAlSdsC+TyFhY/3j/j1kfbaOk6A2aytKIvuy97E0finbM7ZbjeFdta5WY/gQ53p9NFNWVv2xaFqa9XGVvz+ukyfhMmkSmpCGemplBTUkHMojIS6P4uyq+jEaBWHdZMIW3NEdpepSEl+UmU78/j0kHNhDQXqq9XFBUBDQoSNdY8eg0dn9JTNsl8PYsWMZO3Zsk6/v0aMHPXrUu62EhoayYsUKdu3a1SzydiW0ljOEzZjeFutPvUZbrNYbl1NWw93fHKOgwkA7Xye+vq839hrlZee6JJapGn6ahpC+F0nrDHf/Ar5dW8Vk/kpjzKKZV/a+wprkNQgIvNj3RW5td2uDMa0Vy1JZSfaTT1G1ezcIAt7PP4/b3XfJ5vKt8JrFH8xj+w/nMJtEnD10jJnZBc9Ax0vmbGqshIP72LTwEwxVlWjs7Ih98BFCe/VFpdU2aZ2SKFG5K5PyzXK2TdApcb0xArvuXpcXrEVuSNi2bRsHDhygzu4qNjaWXr16oVAoGoyTJJHc3F9ISn4Po1E+przY0kqSJHaVVPBmUo5V9sNLreLpUB/u8PNAbzSzaFcS3+zLoLSWtEV4OfB4bBTjuvihVFx0nGgxIp1agXbvPIR8WVdOQoB2Y2XSFtzfWs9WVF3IL4m/sCxhGVmVWdZ19/LuxS3RtzAiZARapZxBtFRWUrF5C2W//EL1gfpmBcHeDqeRI7EbNw6XgQOtGS9JkqgqNZB4OJ+EQ3nkp1ZYxyhUAsEd3Qnp5kZUTz80Fwgc1732BWkpJBzYQ8KBvRRn15vWCwoFAR06067/DUT16Y+9i2uDsVdDS7/0NHXctfytgHwEfyG0Wm2jWdxrxdGjR9m7dy9vvvlms8b94UV6bcb0f/1YLR1ni/XnilVcZeTB746RVVpDsLsdn9/ZFZ1CvOrftzWWqQbN8ntRpu1G0jhimPY/JPcOrWoy39gYg8XAS/tfYkfWDpSCkldjXmVMyJgG626tWObcXPIeexxTQgKCTofXW29hP2xog2PZlr5mNdV6Dv6axukdOQAEtHNh6N1RaB1Ul30NrhTLbDSw53/fcXrrJgC8wyIYOesJXLx9rdZOV4OlSE/lLymYM+UMkDrSGYeJoSicNVc8ik5ISGDz5s1UVMhEpH379gwfPhwnJ6dLOkkrKo6TkvIfKqtkAqXTBuHv/zg+PqMRBAG9Xs/pKj3vpBewq0zuaHVUKpju584Dfm5gEVmwNZ6v9qZbSVuYhz2PDAllbCcflAoBk9GA1fb+ApN4RZ1JvMoOS5dbZZN4d/kYWdLrOVxwmBVJK9ietR2zKB+9OqmdGBc6jvGB42nvJYsHiwYLJYd3Ubl6DdVbtiDV1FjvT9enN44TJmI/IhaFvT16vR6jyYS+tJrU48UkHy0kN6ncankgCOAX5UJ4T09CurijtZdffxEzer0ZSZLIT04k6dB+kg8doLyg/shWoVIR1Kkr4b37EdajN6jUVoJw4e/QlV57g8HQIhJ04bimErKW/l0CBAUFNXj81VdfbRX5jToEBgZSUFCA2WzmX//6Fw899FCzxv/hRXptxvR/7Vh/hjXaYl37uHK9iek/nSCluAY/Fx0/PtSPQLerH6lZYyklhOUPI6TtRNI4wl3L0Qb1bdU1Njam2lTN0zuf5mDuQTQKDe8PeZ+hQUPbJJb+9BlyZ83CXFCA0tOTwM8+xa5z56uOawqqyg1s/zpZ/hAHeo4OJubG8Cs2iFwpVlFmOms/eY/C2qOz3hNvZuCtd6JUqZu0RkmUqNqbTdnGNDCLCFol9qMCce4X0HhXZi3KysrYsGED52p9Nl1dXYmNjaVTI/6aBkMuiUnvkZf3K1BnafUogQF3YzRK6HQ60vXGS2Q/7vH34IkQH+yB7/al8fmuFIqrZEIY4m7H47FR3Ng9wJpps6I4RXZBOPYjgkkmgZKjD6Ye96HqOx2lgwdKoFRfyqrkVSyNX0paef1RZxfPLkyLnsao0FHolDqZAOfmUv7rKspWrcJceywMoA4Oks3gJ92IJiCg/p5rTGSeLCf1eBqZZ0samL77hjsT1ceHiJ7e2DvXH0VLkoTFYqEgJZHEg/tIOLCXyuJC6/NKtYaw7r2I6juA8J590No7WMc11/hdkiSrj2xz33OaO66lfyt15C0jI6PB8WNrZ9127dpFZWUl+/fv5/nnnycyMpLbb7+9yeP/8CK9fzTTbFusP844W6w/R6wao4WHvj3E6exy3O3VfP9gDEHu9k2PZTEirJyOkLgF1PYIdy6F4H6tusbGxpQZynhkyyOcKDyBvcqeebHz6OPbp01iVWzbRtbTzyBVV6ONiiJo4QLU/o2LDDc3Vn5aOesWnKSqxIBaqyT2vg5E9Gias8HFsSRJ4uTWjWz75nPMRgP2Lq6Mnf0Uod16NnmN5qIaipfGY0yViaQ2yhXXKZGYdaBQKBodY7FYOHjwINu2bcNoNKJQKOjfvz9DhgzBYrE0iGWx6EnP+JK0tAW1llYCfn63EBH+NFqtF5IkUWSuZEFiNt9lF1llP6b4uPGPMF+8lEq+35fGop3JFNWStlAPe+YMj2JUezcc7e3r1yhJcu3l3rlwbi3W9JZPZ9m6qtMULGYJlVbL0fyjLI1fyqbUTRhFeV57lT0Twicwtd1U2rvLWTZLRQVl65ZRsnIlhmPHrHugcHTEeexYXG6ajF2Pensrs9FC2ukiEuLySD1ZhKXWegvAM8iRqN4+RPb2xtmj4Zcl0WIh48xJuYbt4F5qyuu139Q6O8J79Caq70DCevRCo2v8i9Yf9T3nWseAXDfWWrVjjSEsLAyALl26kJeXx7/+9a9mkTebSK8NNtjQZjCaRWb8cJi41BKcdCq+uLs7EV5XtjJqAIsJzaoZCAkbQWUHdyyBkGtvgb8aCmsKmb55OgklCbhoXVgwYgGdPdumKaL4+x/I+89/QBRxGDCAgI8/uqQrsKU4syebnT/HYzGLOHvpGDerKx7+zdj/C6CvqmTzonnE798NQEjXHoyd/RQOrm5NGi+JElUHcihbl4JkEhE0ClzGh+MQIzcWmC9zdJuVlcXq1avJzZWPIIOCgpgwYQI+Pj7WrBHIxDK/YAOJif9Br5frxlxcehId9TLOzl0BqDRbWJCRz2fp+VTVZqXqZD8itFp+2J/Gwp1JFFbWZtpqSdvk7v4oFUL90aDFDGd/lfXZsg7XLzZypEzawoeCIFBuKGNlwkp+SfmFpNJ6nbUO7h2Y2m4q48LG4aB2QLJYqNy1i7KVv1Dx229IdUfGCgUOAwfiMnkSTrGxKGpPoSwWkcxa8dzk4wWY9PXiuc5eOqJjfInu44Obb0PxXLPJRPqpYyQc2EvioQPoK+rrurT2DkT0iiGq3w2Edu2BStM2moU2XApJkprdsW4T6bXBBhvaBGaLyBOLj7IzvgA7tZKv7+tDB59muA9YTLD8QZQJG5BUOoTbf4awQW234FpkVWYxffN0Mioy8LLzYtHIRUS6XerveK2QLBby3nqLku9/AMB16lR8X3kZoRXedC1mkV1LEji9UyYxoV09ueG2MJzdGlfCvxqy48+y9pP3KC/IR6FUcsNt99B7wk1N7io0l+gpWRaPIUnO7mjDXXC7JRqVu0xGGqth0uv1bN26lbi4OCRJPuYcMWIEPXv2vORotaLiDAmJ/6a0VC7g12p9iYx4Dh+fiQiCgFEU+T67iA9S8yiqlf3o7mTHSxH+9HKw58cDady3o560BbnbMWd4FDf1CLBK2EiSBIZyOPI5HFwEZRlycKUWut0q21d5d5Czk4UnWXJ+CRtTN6K3yITPTmXH2LCxTI2eSicP+ZjXkJBA3i+/UL5qNeaCAuv9aCIicJgwHvcpU9D4+ACyJl/W+ZJa8dwC9FXWKjsc3bTWDJujlwo7OztrBslkNJB6/AgJ+/eQdPggxppq6zidkzORvfsS0qMPkT17o1LbCFtzUVlZSWJivS9sSkoKx44dw93dneDgYF544QWysrL47rvvAJg/fz7BwcG0by9nWnfv3s3777/PnDlzmhXXJtJrgw02tDpEUeKFFSdZdzIXjVLBont60SvErenNRxYzrJiOcHYVklIDt/4AEcPadtFASnkKc3bOIb86nwDHAD4f9TlBTkFXH9hMiNXV5D/9DDU7dgDg9fRTeDz0ULOPkhpDVamBDYtOkptcDgLETAij15gQDMbma9FJosjBX5ayZ8kPSKKIi48v4x97Fr/IpokhS5JEVVwuZWtSkIwWBLUCl7FhOPTzQ7hMvZ0kSZw9e5b169dbGxK6dOnC6NGjcXRsmDU0GotISnqfvPzlgIhCoSUkeAYhIQ+jVNojShK/5JXwdnIOaXqZmIXbaXgq0JNxXm78dDCDJ3YkU1gp702gmx1zhkcypWdgQ93BkjQ4sADdke8QjLUaavaeskF87wfB0YtKYyVrzy1mafxSzpectw6NcIng1na3MiFiAk4aJ8wlJZT88CNlv/yC/vRp63VKV1ecx4+XzeA7dcRgMKDSaslNKSMxLp/Ew3lUXSie66QmspcPUb298Q13QajVldPr9Rhrqkk5dpiEA3tJOXoIk6H+787B1Y3ImAFE9x1AYIfOCAqF7LCgahuR6b86Dh06xLBh9e9NTz0l+7Tee++9fPPNN+Tk5JCenm59XhRFXnjhBVJSUlCpVERERPD2228zY8aMZsW1ifTaYIMNrQpJknhz7VmWHs5EIcAnt/dgUJRX01v2RQv8MgtOr0BSqDHe9CWayBFtu2jgTNEZZm6bSamhlAiXCBaNWoS3fdNqw5oDU34+GTNnYThzBkGjwf/dd3AeM6ZV5s5JLGXDolNUlxvR2KkY+UBHQrt4tkiWobK4iHXz/kvmmZMAtB84hBEPzUZr37R6RXOpgdKViRjiSwDQhDjjPjUalefls6+lpaWsW7eOhATZ8cDd3Z3x48cTERHR4DpRNJKZ+QMpqZ9gNssEz9t7PFGRz6PT+SNJEtuLy/l3Ug4na2U/vDUqngn1ZbKHCz/vS2HItycoqJBJW4CrTNpu7nURacuIg31z4exqBEmuJZO82iP0nw1dpoFax+mi0yw9MZ91KeuoMcuxtEoto0NHc0vULbRzaodOqaRyx04yfvmVyh07wFxrOaVS4Th0CC6TJuE0ZAiCRna2KMys5NyBbFKPFlFeVE+8rOK5vXwIaOeK4oK16qsqSTp0gHP7dpFx6jgWU31mzsnTi6iYAUT3HYh/dPsGGdOWSnbYIGPo0KFX3MNvvvmmwc9z5sxpdpatMdhEem2wwYZWxce/JfDVnhQA3r2lG2M6N0P8VRRh1Rw4uQQUKpj6DWJobButtB6H8w7z6G+PUmmqpLNHZz4b8RmuOtdWj6M/H0/GzJmYc3JQuLoS+Ol8HHr2vPrAq0CSJE7tyGL3kgREUcLd34GxM7vg6t30xpALkXw0jg3zP6SmohyVVkvsA7PoNCS2SZlBSZLQHyukekMGksECKgUuo0NwHBhw2WybxWLhwIED7NmzB5PJhEKh4IYbbmDQoEGX1O4UFm4jIfHfVFfLv2MODh1oF/0Kbm4xABwtr+bfSdnsLpUzZI5KBY8Ge3O3rzurDmcx4ptj5F9A2h4dHsnNPQPR1InSWsxwbo1cz5Z5sP6+wodh7PkQmo7jqLboWZeyhqXxSzlTdMZ6TZhLGFOjp3JjxI04a5ypOXWK4k/fpXrjRiylpdbrdJ064TJ5Ms7jx6FydwegNK+ahENZJMTlUZJbf7Sp0ioJ6+opi+d2cEepride1eVlJMbJHaLpp45bLakAXH39iOo7kOiYAfhERLVKVteGPx7KysrYv38/hYWFjBs3Djc3tz+GSK8NNtjw58GXu1P4aIucNXntxk7c0iuw6YNFEdY8Dsd+BEEJt3wF7cdfVsettbArcxdPbn8Sg8VAL69ezBsxD0dNy4r6r4TK3XvIeuIJxMpKNGFheH38EfZRUdc8r9loYcfP5zm3Ty7oj+zlzbC72zcQXG3yXCYTu3/+hsNrZXkNj6AQJj7xHB6BTfNStZQbKFmRgP5cbbYtyAm3qdGor0AiMzIyWLNmDXl5sp5YSEgIEyZMwMuroSVWVVUSCYn/pqhIPmpWqz2ICH8aN7fx2Nk5kFSt5+3kXFYXlMqxBYH7AjyZ6e/JpmPZjP1xp5W0+bloeXR4FFN7BdWTNn05HP0BDnwGpbXHXEqNnGHr/wh4d+Rczgl+PfAm61LWUWWq1aZTqBkZMpKp0VPp5dMLc34+Zd8tIfliM3gvL5xvnIjr5Mloa1/3imI9CZvSSDyUT0F6vXiuUqUgoIML7fv6E9rFE7W23oGkorjQKumRefY0klTfXeoRGExYrxg6DBiMV0iYjbD9xfHGG2/w9ttvU1NTgyAIxMXF4ebmRmxsLCNHjuT555+/pvlt5M0GG/4GWBKXwRtr5CzEM6OiuXdAaNMHSxKsewaOfAeCAqYskm2D2vhIZ0PqBl7Y+QJmycyQwCG8EfMGDuqWFfVfCSVLl5L7r9fAYsG+Tx8CPvkYUysca5QX1bBh4SkK0isQBOh/UyTdRwa16EO7JCeLNR+/S36KTDh6jJlInym34diEb/GSJFFzrICSVUlINWZQCjiPCMZpcBCCsvG11NTU8Ntvv3Ho0CEAdDodo0aNoscFMhgAJlMZKalzycz8HkkyIwhqgoLuIyx0NkqlI+nllcxLz+Sn3CIsEgjALb5uPB7ozZ6Tedy0dBd55TJp83fRMXtYJBM6e+LsUCv5UZoOBxbKv3uG2u5LO3fo8xD0eYhqnRMbUzey5NCbnCo8ZV1XiHOINcvmIumo2LKFjJUPUbVvn/X3VtBqsR86FLebp+A4YACCSkV1uZET2zJJPJRHTlK9PIegEAjq4EZUbx9Cu3kiCWZ0Op0sW5OfS8KBvcQf3EtO/LkG++gdFkF034FE9R2Am18Aer3eOs6Gvy4+/fRTXnvtNR555BHGjh3L+PHjrc9NmDCBFStW2MibDTbYcGWsO5nD8ytOADB9cDizhzWjO1OSYP1zcOhLQIDJC6DLLW2z0AuwPH45r+17DQmJcWHjeGPgG1iMlqsPbAYkUaTgw48o+vxzAFwm3YjvG28gqNXX7FGaea6YjV+cRl9pQuegZtTDnQhq796iuc7s3MqWLz/DpK9B5+TMmFmPE94zpkkNJpYKIyW/JKI/XQSAOsAR+xtDcAx2a5RASJLEqVOn2LBhA1VVcvaqW7duDB48GHd39ws05SxkZS8mOflDTKZiADw9RxAV+Tz29mGUmy3MS85hUWYB+lrZj5EezjwT7M3xs4XctXIvueXy+v1ddDwyLJKpvQPRKOUCfTIPySbxZ1ZBrYcontHQbxZ0u534ygyWnv6CNclrqDTJR7AqhYrYoFimtptKH+/e1Bw+TNkb75O/YSNiVb1PqF3vXnId2+jRmNRqsCg5eyCfhLg8ss6X1H8nEcA/0rVWPNcLO0eNdY9yktNIP36IhAP7yE+tz+AB+EW3JzpmAFF9B+DiXV+WYKtf+/tg3rx5PPXUU7z77rtWuZw6REVFWetGrwU28maDDX9hbD+fz+P/O4oowe0xQbwwtn3Tv/VLEmx6CQ4ulH+eNE+WXWhjfHv6W94/9D4A06Kn8c9+/0RAwELrkTfRYCD7+eepWC8XFXvOno3no7MRhMv7dTYFkiRxbEs6+1YkIUngFezEmBmdLxFhbQqMNdX89uVnnNm1DYDAjp0ZN+cZnNyb1uRQfaKA0l8SEatrs23Dg3EcEoDBZGz0+qKiItauXUtycjIAHh4eTJgwgdDQ0AZEsbh4LwkJb1JZJXdtOjhEERX5Tzw8BqG3iHyWns8naXmUmOXXq7ezPf8I8SU1oZgZnx6wkja/2kzb1N6BaFVKEC1IZ35Fs3ceQlZc/cLChkD/R6kJHcjG9M0s3fwQJwpOWJ8OdAzkluhbGBM4Bs8yE+VLV5H86z8xZdX7kKoDA3GZNAmXSTeiCQ7GqDeTdLyA8wdyyTpfimip30+fMGeiestuB45u9ZZP+anJJBzcS8KBPRRlZlivFwQFgR07E9V3AFF9+uPo7nHV18aGvzaSk5MZPXp0o885OTlRekGNZUthI2822PAXRVxqMTN/OIzJIjGhqx9vTu7SPOK25V+wb57884SPoMddbbXU2pAS847NY9GJRQA82PlBHu/5+DUTqothLi4m85HZ1Bw7Bmo1fm+8juvkydc8r8lgYfv3CaQclbNc7fr5MvSOdqg0yquMvBR5yYms/eRdSnKyEQQF/afeTt+bpqFQXH0uS5WJ0l8SqTkp2yip/RxwmxqNxr/W4N7U8Hqz2czevXvZsWMHFosFpVLJ4MGDGThwICqVyrr3NTXpJCa9TUGB7JeqUrkQHv4EAf53IAlKfs4p4v2UXLIMcoAoey1P+LlRmVnDPxbFNSBtjwyNYFqfIJm06cshTq5nE0rTUQKSQo3QdRr0m0Wi1o6l8UtZffhfVBjl2jOVoGJY8DCmRk+lt0MHKjdsouTfz5B8oeuBgwNOY8fgOnkydj17YjFLpJ4sInHDyUvcDjwCHYnq7U1Ubx+caztuJVEkJ+E88Qdkl4OyvNz6uZVKgrt0J7rvQCJ698Xe2aUZr64Nf3W4uLhY60QvRmpqKt7e194pf03krc6frLnXN/eNuCXjbLH+Hmu0xWp83MnMUh74Og69SWRYOy/+O7UbCuHyRzeXxNv2b4Q9H8nPjX0Pet13SY1ba+6HKIm8c/Adfj7/MwCP93icB7s8eMn11xrLkJJC5syZmNIzUDg7E/DJxzj07dtg3pbEKiuoYf2CkxRnV6FQCAycGknnIQFNIp4X39+Rdb+y66dvES1mHN09GTfnGQI7dLJee6U11pwupPSXJMRKEyjAaWgQTsOCEFSKRvcxLS2NNWvWUFgoE73w8HDGjRuHh4eHNY7JVEFa2nyyc75FkkwIgpIA/zsIC3sMlcqVjUXl/Cc5h/jq2to1rZonAr2wZFTx7venyLM2IsikzZppK01HOrAQjn6PUFvPJtm5Y+5+N6Y+97O5+ATLj7zH0YKj1vsLcAzg5qibmRQ6Absj5yl7dwlJW7ci1RneKxQ4DByAy6RJOA4fjqTWknG2mIRvzpJ6vBCToT576+JtR2g3d9r387c6W4iihfTTJ0g4uJfEg/uoLC6yXq9Uawjt3pOoPv3x79QVF3ePBtZkV8Nf/T3nesX6MyA2NpZ3332XSZMmWWVBBEHAbDbz2WefXTYr1xxcE3kzGAxNF/a8YExLijVbMs4W6/cbZ4v1+8U6l13Cgz+dpsJgpneIKx/c3BHRbERvblo81Z4PUO9+DwDj8NexdL37sl2lrbEfZtHMG3FvsD5tPQICz/Z8llsib7nkveVaY+kPHyb/qacRy8tRBQTgPfcTlGFhjb6HNSdWxtkSdnyfgLHGgs5RxfD72uEb4dwsSx2DwYC+opzfvphP+gmZrIT1imHY/TPROTpddY1ijZmq9ekYT8r1Z0ovHY6Tw1D5O2AwG8HccFxNTQ3bt2/n5ElZJ87e3p7hw4fTsWNHea/0eiRJpKBgFWnpH2EyyeTOxaUfoaHP4WAfxf6Sat5Jj+dwpbw2F6WC6b5uOObU8OkPJ8itbUTwcdIyfVAIt/Twl7tH0/ZjObQQ5fm1CLX1bKJ7FOY+00kM6s3SlNVs2ngX5UaZ0CkFJYP9B3NTxE10L3Ol+te1lGyYSlFRPbFSR0SgGzMGlxtvROHhSU5iGQcXJ5N6sghjdT1hc3DTEN7Dk/AenrgH2GMwGFCrJOIP7iP58AFSjsRRc4EtlVqnI6RbLyJ69yW4S3fUtT6ier2+2ZZJF79mbTnmrxqrbs/79OmDUqlk9uzZzJ49u1lzXA+8/vrr9OnTh44dO3LTTTchCALz5s3j6NGjpKens2TJkmuOcU3kTavVNktsro5pa7XaZr1oLRlni/X3WKMtVkNkFFcxa/FZSqpNdA1w4av7+uCku7o6uzXeoc9Q7H5XfmzE66gHPsblRrfGfhhFIy/tfImtGVtRCkreHPgm48PHX3FMS2IZNm0m76WXkEwmdF27EvjpfFQejdcmNTWWJEoc3pjGwdUpIMm1UkPujsTD17nZa8w4fZKtn8+jqrQYpVrN0LsfouvIsZed58I16s+VULYyAbHCBAI4DgnEOTYYQaW4ZJwoipw4cYLt27dTUyOL1vbs2ZMRI0ZgZ1dfl1dWdoT4hDeoqJDJnVYbRHTUP/H0jOVclZ7/JOSwuUgmOTqFwP1+HvjmG/lmeTw5ZTKZ83XW8tDAYO7sH4ZOCZxdA/s/RWigzzYUfZ/pbFFbWJqwjKPxc63P+Tv4MyVqCpNcB6Peup+yuR+Te77eHUHp7l7rejAJdXQ70s8XcmRvKUlHDlNTUX82bO+sIaKXN1G9vfEJk18bk9FA6rEjnN+3i7TjRzBU1zc0aB0ciezdl8iYAYR06X6Jj+if4X3grxqrjrzFxcW1qTH9tSIyMpI9e/bw1FNP8emnnyJJEt999x3Dhg3jxx9/JDi4afI+V8I1kTdBEJrNnOvGXI9xtlh/jzXaYsnIr9Bzz1dx5FUYiPJ25JsHYnC2a7ofojpuIYptr8k/DH8Z4YbHW32NF46rMdfw+PbHOZBzAI1Cw3+H/pehQUNbNZYkSZR98SWln34KgNOoUfi/+47VRLylsYw1ZrZ8c4aU43JGqtMgf26YGoXJYmzWGkWLhT1LfuDgr8tAknAPCGLCE8/hFRx69XszWChdk0D1kXwAVF52uE9rhybIqdHrCwoKWLNmDWlpaYBsnj1hwoQGHyR6fTaJSe+Sl7caAKXSkdDQ2Xh53kqRoOOxcxkszytBApQC3OrtRniRmR+Xn7+AtOmYPUw+HpWqitAdWoBwYBGUXajPNpXkzpNYWnyMVcfeapBlG+g3kFvDb6LL2Roq5q+mZPcnss4gIKjVOA4fjsvkSTgMHEhBtp7Dh/JI/OEAVSX1mTCtg4qInnINm3+UKwqFgKG6mvh9u0g4sJfkY4cwX5A5s3dxJSqmP5ExAwjq2AWl6sofjX/k94G/cqyWZAV/L3Ts2JENGzZgMBgoKirCzc2twReka4WtYcEGG/4CKKs2cc+XB0ktqibQVcd3D8Tg7tAMI+sDC1Fv+5f876EvwOBn2mSddSg3lvPU7qc4UXgCO5Udc4fPpa9f31aNIRmN5P7rX5StWAmA+4MP4P300002bL8cSnKrWL/gJCW51ShUAkNua0fHG2TbJ1MzGmLL8vNYO/c9qzZYl+GjGXbfw6i1Vz/N0J8voWx5fH22bVAALiNDENSXNjSYTCZ27drF7t27EUURlUrF0KFD6d+/P0qlfL3FUkNa+uekpS1EFPWAgL/fVMIjnqZCcuHfydn8kFeKsbbmaJy7E51KJZb9msiKi0jbtD5BaCsykLa8JNezWf1GPTD0vp9NPuEsS9/EkT31v2N+Dn7cHDGF8VURSGu3Uf3CC+RWVlqft+vRQ5b3GDOa0koVpw7lkfj6IcoL64+T1Tol4d28iOrjQ2AHN5RKBTUV5ZzZ+RsJB/aQduIoFnP9+bGTpxdhPWPoMGAQ/u06NKkZxAYbroaamhoiIyNZsGABEydORKvV4u/v3+pxbOTNBhv+5KgymLnvm4Ocy63A20nLV/f0wNelGSKzh75C2PAcANINTyMMea6NViqjsKaQmdtmkliWiLPGmc9GfEZXr66tGsNSXk7mY49TvX8/KJX4vPwS7rfdds3zJh8rYMs3ZzDpLTi4ahkzozO+Yc3vNIzfv5tNC+diqK5CY2fP0Ptn0Hnw8KtmFkS9mbK1KVTFyZ2PSg8d7lOj0YY2voakpCTWrFlDSYnsqhAVFUVsbCw+Pj4IgtxMkZe3msSkdzEYcgBwcelNdPTLKO06MD+zgE/Tz1JpkTNfA5zs6VUOq9emsrX8ItLWOxBtdhwsfwnOrW3gN5rcfRrLlHpWpayjPKM+yzYkcAjTHAYTuT+TigXLqcjMtK5d7e+Py+RJuNx4I1U6LxIP55Pw0bmG9lQaBaFdPYns5Y13hAOOTvZUlZZw8rcNJBzcS8bpE0hifVepm58/UTEDiOo7EO+wCAwGg00014ZWhZ2dHTU1NTg4tL6g+IWwkTcbbPgTQ2+yMP37QxxNL8XVXs13D8QQ5Hr1GjcrjnwHa54EwBQzC9Xwl6ANP8iyK7N5eNPDpFek42nnycKRC4l2i27VGMbMLDJmzMCYlITC3h7Pd97BbcS1ebCKokTcmhQOrUsFwD/KldEPd8beuRnZTcBk0LP92y848ZusL+cX1Y5xc55F2wSpCX1CCSXLErCUycd9uhhv3MZHoNRe+jZeUVHBxo0bOXVKdh1wcnJi7NixtG/f3lo3VF5+gviENEUEfQABAABJREFUNygrOyLPp/UnMvJ5XD3H8ENOMR8eP0uhSc5UddCqGVilZMumDI5cTNp6+qKNXwNf3wfZ9Z2hNeFD2RDah5VV8RxN/Mb6uJ+DH9P8xjEyyQHp823UHH2J4trnFA4O2I+IxX3KzZjDOpF0tJCtP+ZRmJFsHa9UKQjp7EFkb2+rPVVpXi6nfltL6tE4suPPNeiM9gwOrTV+H4BHUIiVqP1ZOhdt+PMhNjaWLVu2MHz48DaLYSNvNtjwJ4XZIjLn56PsSSzCQaPkm/tjaOfbeGdiozj2M6x6DACp70zMQ15B1YbELaUshYc3PUxedR5+9n58PupzQlxCWjVGzYkTZMx6BEtRESofHwIXfAahodc0p77KxOavzpBe61LQdVggA26JRKls3vFrYXoqaz5+l6LMdBAEYibdwoCpd6JQKq/4mokGC2XrU6jaL2fGlO463G6OQvLXorhIQ04URQ4fPsyWLVus3XwxMTEMGzYMnU6HJEkYjQUkp8wlN3cFAAqFHaEhMwkMepDVRXreOXieNL0svRGiUXFDpYLde7P54ULJj2GRTOvkiPb4dzD/cyivFcRVaknqPIFl7l6syt5Necpi+WFByVC/G7itrAMBuxKo2vY11Q3kPQbiMmkS9BxI/PEiDmwrIe/rA9b7UigEgjq6E9nbm7BuXmjtVBRlZXB47TISDu612obVwS+yHZEx/WVbKt/WP7KywYYr4cUXX+Tmm29Gp9MxZcoU/Pz8Lsnuuru3zHGlDjbyZoMNf0KIosQ/lp1g85k8NCoFn9/bm+5Brk3PJpxYCr8+AkiyT+To/0ALpA+ainPF55ixeQbF+mLCXML4ZNAnBDtfe8fVhSjfvJnsZ/+BpNej7dCBoAWfofL2brac0YUoyqpk3YKTlBfUoFQrGHZXe9r19b36wAsgSRIntqxn+7dfYDYZcXB1Y+yjTxPSpbv1+ctBn1RKybJ4LLXF+A79/HAZG4agUVxyX7m5uaxZs4bM2qNHPz8/Jk6caK23sVgMpGd8SWrqZ4iifPTo6zuZ8PBn2FflwMNH0zlVKXegeiqVDKoUOLIvl+XlDUnbrWF6NIc+gU9+ApM8j97Bm80dY1kmlXOkKA5q1TZ87Xy4Vz2IAcdNmBdsw1L8G3WVbNroaFwmT0Y9dDRp6SKHDuWRs/YI1G6HIEBAO9lPNLy7F1oHFfkpScT9uoWEg3spzmrocuAX3Z52/W8gsk9/nD29mvUa2WBDa6JXr14A/Otf/+K1115r9JqLbbOaCxt5s8GGPxkkSeK11adZcTQLpUJg/h09GRDh2fQJTq+ElTNAEqHnvTD2vTY9Kj2af5TZW2ZTYaqgg3sHPhvxGfbYt9r8kiRR/O235L/zLkgSDkMGE/DfD1A6OlzT0Vji4Xy2fncWs1HEyV3H2Jld8ApuvJPzctBXVrJp0SckHNgLQFj3Xox55EnsXVyvOE40WijfkErl3mwAlK5a3G6JQhfpBjQkfAaDge3bt7N//34kSUKj0TB8+HBiYmJQKGRx3vyCDSQmvo1eLxM7Z+fuREe9TCJR3HE2m32lshq8IwI3VAqcOZHH+gsybQ8NCOJu/0w0cf+ADRupY1iJvh1YHtSBVeXxlBfukdcqKBnrEMOUZE9ctx3DnPw/6r4WKD09cZkwAd3oCWRVuXHyUB5Z75278JQTnzAnomN8iezlg52jiuz4c+xfsY6Eg/soL6hXrVcoVYR06UZkzAAiesWg0Ops9Ws2/CHwyiuvtPnvoY282WDDnwwfbI7n231pCAL8d2o3Rnb0afrgs2tg+UOy2Xf3O2XbK4XiEveE1sLerL08sf0Jasw19PTuybzYeTiqHa8pG3YhJLOZvLf+Q8lPPwHgevtt+P7znwhXkXq4EkSLSNyqNE5uk4lTYHs3Rj/UGZ1jM2oJgaxzZ1g79z0qCgtQKFUMuv0eeo2ffNVuV0NqGcVL47EUyXvkEOOLy7gwFLpL7+n8+fOsW7eO8nI51dWhQwfGjh1r1cCqqDhDfMKblJbKR5BarQ/BQU9Q4zaeJ1LzWV8oG2RrJehbDsmnC9heS9r8XXQ8OiSYqZp9KA+8hGLbGQD0gsCmiH4sc9BxtDwZCg8BEKLy4cGiTnQ+VIg5bjdIEmZA0Gpxio3FbtyN5NlFEne0kIzP8xH/z955h0dxXX34ne276r33QhMgimimV4licO+4g2PcHdtxEif+kthJHNtx770Bxg3TO6Z3BKIIUO+97q62zcz3xwoJmSrAsQXzPs/3fGFnzj1nZmfWP917zzlSuxALjvUmaWAwCf2DELQuavJz2PL1j+Ts3Ialob7tPI1OT1zqAJIGDSWufxoGD3dnBFmWL9ozpaBwoTz77LO/uA9FvCkodCHe35DH62tzAPjblb2Y0S/i3I2PLIcFd4Dkgt7Xw5Wvu4XbL8TqwtU8ueFJnJKTK8Kv4L9j/otRY7xoG8Uli4XSx3+Pef16EASCn3gC/zvvuKC/eFvMDla+f5CSI27B0H9SNIOnJ6BSnfuYkiSy84dv2PLNV8iShG9oGFMeepLQhKQz2slOkcaVRZg3l4IMah8dftckY0j2O+ncxsZGlixZwrFjbvHl6+vL5MmTSU52J3/YHTXk5b5EWfkCQEal0hMTPQtNyB38J7+Ob3OPIQEqUWZAk0zZoVp2mN170MJ9DDw6zI+rxBVoNt8HFncduaNGL76N7csiVy3NrjJoAo2s4iZLChMOazFu3o/csrKtmYNx4EB0EyfTFDuUfQebKPqhDtHVXmQ3MMqTxAHBJA4IweSjonB/JpvmfkPu7u3YLe1Fc3VGEwkDBpE0aBixffuj7URheAWFXwtRFPn6669Zt24dtbW1BAQEMGbMGK677jo0F/DH5XEU8aag0EWYt6OI55YeBuCJSd24bWjsuRvnrIavbwPJCb2ughlvwy9Y12phzkL+suUvSLLEhJgJ/HvEv9GqOzdzdSaclVUU/+4+7IcOI+j1hL/wAt6TJl7QmNVFzSx7J4vmOhsanYqxM3uQNLATs5qAub6Wte+/Sckhd2eCHiPGMP7u36EznnmZ2FlipnFhIa4a954z08AQfKfGnzTbJooi27dvZ926dTidTlQqFUOHDmXUqFHodDokyU5x8afkF7yJKLp3lwUHTyEg+gneq1Lx8c5C7LIMokRKnUTd0XqyThBtf0yTyWj+FvWGb0C00yIIrAiMYEFAKPsd1WBzF9odYAni5oJworcWIle7s1VlQBcTg8eVM2jsNprsfBcFO2sQt7RnivqFmkhKCyFxQDAmb4H8vTvZ8MU88vfuwmlvnzkzevuQmDaEpEHDiE7pg1pz8Z4dBYVfmpqaGtLT09mzZw8ajYaAgABqa2v54IMPePHFF1mxYgWBgZ3Y6nIKFPGmoNAFWLy/jKe/dwuC2SPjuX90wrkb562HebeA6IDuU+Hq90H9y736Xx7+kn/t+BcAMxJn8Nehf0Wjunj+bEeOUjx7Nq6KCtT+/kS99SbG1NQLGvPItnLWfXkE0SnhE2Rk7J3JhMV1Lhssb/cOlr/9CjZzM1q9gXF3/45eo85cokR2SjSuKsC80T3bpvLW4Xd1EsbuJ/suKSlh8eLFVFS4a7xFREQwbdo0QkNDkWWZ6uqVHMv5Jy0tboHl5ZVCRPwzfN0cyVuZVTSLEogS8dUOrDlN5FjcLaQiffT8I6WCkXULUG1a774fOi3fRCSzRCfTLNrBUY2/Rc3tZXGkZVrR5BQB5ciAyscHz8lTMPedRG6dh7sBfFZZW9w+QUYSB7q7HRg9XeTu2cH6Tz87uWhuQBCJg4YS3bc/cX1SUf+Cz6iCwi/Jo48+ypEjR/jyyy+5/vrrUavViKLI/Pnzue+++3j00Uf5/PPPL8jHBb0dx/uTdfb8zi6bnI+d4uvyiPFy8PXTkWoenZ+JLMONaVE8ld6t7Zyz+irYBF/diOCyISenw7UfgUpz0h63i3E/ZFnm/az3eSPzDQBu6XELTwx8ApWg6jDuhfgyb9pE2SOPIlks6OLjiXznbXRRUacd62y+RFFiy7e5ZK1zb+SPTvFn/B09kFXiOcfncjrZ+NUn7F32IwDBsfFMeehJ/MIjzjiGo7iZ+m+O4qpyz7YZ+wXhOy0BlVHTwc5ms7FmzRp27XLvLTMYDIwfP54ePXpgNBppbs7mWM5z1Ne7kyJ0uiCi4h5njTSKuw9XUe2sAJdERJUDZ24TZVa3aEv0FXg+/gADK79GtfsYVkFgmZcn3wRFckC2Aja0NpmpxX5MOeJBQFYJiO5uEGg1mEaMpmXolRQ7w8jPqsOx3AytuaSe/noS+wcT1dsHbz+ZvN07WPPhh5QcOoAsn1g0N4KkQcNIHDSUkPjEtusVfvbMnI3f+vvcFWLsKr66AosWLeIf//gHN910U9tnarWam2++maqqqouyJ+6CxJvdbu/0JtHjtYfOx1dn7RRfv56d4uvi+NpT3Mh9X2TiFGUyegXz5/TEtiKrZ/OlKtmB7usbEVwtiHFjcEx7F5wSOE/9zl7I/ZBlmdf3v84XR74A4J6e93Bvr3tx2B0XzVf911/T9J8XQRQxDBxI0EsvInl7n/U36HS+WpodrPv0KBW5zQCkToyk36RIUEnYbecWX0NFGSvffoWawnwAeo2dxPCbbket1Z42Ltkl0fJTGS2bK0AGwUODblI4pt7BOHCBzT0bJcsyhw8fZu3atVha94D16tWLMWPG4OHhQXNzOfkF71NZ+Q0gIQg6QsNmkmm8hccLmymyl4FLIrDchpzfTG2Le9xU72b+Eb6VXhU/IBxq4JBOyzfBISz1NGGRRQTJQu8SFdflBpO8rxaVtQZw93DV9u6DdcRVVBiSKTpixr7ZBbj3xJl8tMT2DSC+XyBafTMFe3ey/uOtVP+sBltgTBzx/QcRP3AwfuGRbff5+HN9qb7P52un+OpoA5CWloZarWbOnDnMmTOnU2P8L5BlmV69ep3yWEpKykURoRck3vR6PYZObB49rrT1en2nm0t31k7xdXnEeCn7OljWxH1f7cfmkhidHMQrN/ZHpzlzgkGbr5oDCAtuQXBakeNHo7rxKwza0zdFvpD7odFqeH7H83xz7BsAnhj4BLf1vO2i+ZIliepXXqXp/fcB8L7ySsL+/jcE3dm7G5zOV2V+I8vfO4ilwY7WoGb8HT2J6xt4zvHJssyhDWtZ+9E7OO02jF7eTLzvYcJ79j5juQpHqZn6BUdxVbrroxn7BuEzLQ6HSuzgr66ujqVLl5Kb6xY+AQEBTJkyhbi4OCTJQXHJ5xQUvIEouoVnYOAkSgIf44ESF4fK68Al4VPWgjrfjLlVDE7yKeGP/muJrliFpVBigacH3wRFc7j1vwLhNS5uPerF8AMS+pomwF14VxMRQcvoa6kJHkBBjo2WQ06gwR2/p5b4/kEkDghGo6kjd/c21n24ldriwvaLFgTCk7u7Z9jShuATfPo6eZfq+9wVYuwKvo6Lt507d7ZlVP8WGT9+PKtXr2b8+PEnHVu1ahWjR4++YB8XJN4EQei0cj5u87+wU3xdHjFeir5yq83M+nIfZruLQbH+vH3rAPSnaDp+KlSVWQjzrkVwNEPsCIQb54Lu7HXVzufaRFnkr5v/yvKC5QgIPDvsWa5Ouvqi+ZLsdsqffpqmpcsACHxgDoFz5lzQd3ZoUxk/zTuC5JLxCzWRcV9v/EI9zmhzInarlTUfvsXh1v1hUb36MPmBx/Hw829d8jvZTnZJNK0tonl9MUig8tDid1UixpRAZFlGaLUTRZHNmzezceNGXC4XarWaESNGMHz4cNRqNbW16ziW8zxWq3umz9OzB+awv/DXaj+2HTGDS8JUYkVXaMFmc6FG5A6ffTxgWkVA/T6y6nQ8G+DDUk8vbIKMl1Vmyj4Vk4+YCCps5LgoE7y8cY27lqqIoRSWgLXUAaVuoaj30JCQGkRC/yBUqkpydm1m+RtbaKw6sQabmqievYnpN5DuQ0fg5R9w3t/XL2mn/JZ2LV/nMyv4a/DMM89w9dVXI4oiN998M6GhoVRUVPDll1/y3Xff8d1331FXV9d2/vl0W1B2hCoo/MYobWhh5oc7qLM6SQn35oM7BmLUnWNmaEUW+vk3INibIGoI3DTvnITb+WBz2Xhi8xNsLt+MRtDwz5H/JD02/aKN76qvp2TOA7Ts2QNaDYHP/IXA66497x9w0Smx4eujHNro3kwfnxrEuNt7oDOe+89gRe4xlrz6Ag2V5QgqFcOuu4VBM65FpVKfdinEUeaebXOWu5c+jb0D8Z2egNqz48xhQUEBS5YsoabGvUQZHx/PlClTCAgIwGw+yrFjz1FXvwkArTYAR8jvecM2gFU5zeBqxlBkQV9kwW4X0WHmEe/NzFStwOWoZLHLg28iwjim06J1ygzMFknPNtLtWAsq0Qk0IqvVuEZcSW3CaIpqTZgbHNDgXvbWGtTEpwaR0C8AWS4hb9dalr72sxpsWh2xqf1JTBtK/IBBGDzc9fw6szqjoHAp0L9/fwBeeuklXn755bbPj/9GHO/AcJzz6bagiDcFhd8Q1c12bvtgO2WNNuIDTXxyZxrehnMsk1B1GD6fgWCrR44YiHDLAtB7/iJxWpwWHlz7IDsrdqJX63l59MuMjBx50cZ3FBRQNHs2zsIiVN7eRLz+Guo+fc57PHODnRXvHaAyvwkEGHxlPAMmxSCcY/02WZLYveQHNs79DEl04RUYxJSHniSiW4/T24gSzetLaFpTBJKMyqTBd0Yipj4dWzdZLBaWL1/e1kTew8ODSZMm0bt3b5zOerKP/JWysrnIsogg6NCG3cc81xS+KzUjOxvRFpkxFFlxOkTChXIe9lrDFGkdWYLEc54erPCMxAF0L4bfHYQrsgV0NhGwIAP2vqOpS0mntCWApjoH5AI40OrVxPUNJLaPDzZrDsX7l7Hk1R0n1WCL759G0uBhxPUd0KEGW1fZXK6gcLFROiwoKFxGNLY4mfnRDvJqLET4GvnwtlQCPPXnZlxzDD69EsFaixTaB+HWb8Dwy+wJabQ38rvVvyOrJgsPjQevj32dtLC0iza+dc8eSu6fg9jQgDYigqj33kUXH3/eFfQr8ppY9+kxWpoc6E0aJtzVi5iUc1/GszY2sOyt/1KQuRuApMHDmDjrIQyepxfGzgoLdQuO4ix1Z18aegXgNyMRtVf7bJskSWRmZrJq1SpaWtwZpwMHDmTcuHHo9RqKSz4hP/81XC539wRNwAyWau/hqwoHTkcT6kIzxmILLofIINUBHvRYRXd5Dz8aPbjWy5c8nZawWpkZGyTGHtbgV+/OMpWBlpg+NAycQakUQVO9q3V7mwONTkVsn0BiennhsuWQt2chS1/bjeuEJBmTjy8JAwcrNdgUFE6D0mFBQeEywepwcfcnOzlc3kSgp57P7x5EqOc5LpXW5sKn08BShRySgv36+RgMvr9InNXWamatmkVOQw4+Oh9eHfkq/UP7X7Txm5YupewPTyM7HBh69ybq7bfQBAae1yyOLMtkrS9h04IcZEkmIMKDjPt64xN07svIhfszWfbmS1ga6tFodYy+/V76jE8/fSKDJNO8vpim1UUgyghGDX7TEzD2DeqYMFFZyZIlSygqctdkCw4OZtq0aURGRlJbu57Mfc9jtbqL26o8Utng9Qc+rdFjbWlBU2jGo9iCxmljhnozs0wrqNFV8q2XJ6s9IjC0wBX7ZWYdlIgvO16Ww0lLQCz1g66mTJtAUxNQC+BCrVURmxJARDc9zpZj5O9dy7K1+5BOWMrxCggiafAwkgYNJbxbD1S/YIFnBQWFs6OINwWFXxmHS+K+L/awq7Aeb4OGz+8eRFygx7nNNNUXwqdXQnM5BPWAmQtB5XF2u/Og1FzKvSvvpbi5mCBjEO9OeJdIQ+RFGVuWZWrf/4Dq1v0hXhPGE/7CC6iMp8+QPRMuh8hPXx0he5u7oG3igGDGzuyBVn9uokN0udg491N2/vgtyDIBkdFMffhJAqNjT2vjrLTS+HU2Ypk7k9TQwx+/q5JQe7fPtjkcDn766Se2bt2KJElotVrGjBlD3759keVSMvfdSV3dRgBkTTC7/Z/lk/pw6osdaAobMBVZCHTVcptmFZM917HOQ+ZBLw8qCGZgjsxjByRS82TUrZrN6hFK/cDpVHqn0NCsghagBVQagZheAYQlCNgtR8jfu5SD6w53qP8XEBlN0qChJKYNxSs0HKPR2GU2jCsoXOoo4k1B4VdElGQemb+XDUerMWrVfHznIHqEeZ/bTFNjCXw6FZpKIDAZbv8RTAHwCzTozmvMY9bKWVRaK4nwjOD9Ce8T6RV5UZqBy04nFX/7Gw0L3KVG/G+/neAnn0BQn9/sTnOdjWXvZFFd1IwgwMBpMQxMj0N1jn1cG6sqWPzqC1TmuvuG9hmfzuiZ96DVn3rjvSzJmDeW0LiqEFwygkGN77QETP2DO4ido0ePsmTJEhobGwHo3r07GRkZGI0ix3L+RWXlfGRZRBL0HPB7ms8sqZSXOtAU1GEstpAi5nKHZikBfpn84GXiOqMXScUweZvM0GwRU+vKZoshgLqUDKpCBlBvaRWOzaBSC0R09yUg0oZkyyV/73ccXp/f4VpCE5NJTBtK0qCh+Ie7hbksK03fFRQ6yw8//MCXX35JYWHhSe+PIAjs27fvgsZXxJuCwq+ELMv88bsslmZVoFOreG/mAAbEnNyE/JQ0lcEnU6GhCPzjYeaP4Bl8UueEi8Hh2sPct/o+6mx1xPvE896E9wjxCLkoG9JFs5nShx/BsnkzqFSE/OmP+N9yy3mPV3KknhXvH8BmdmLw0DLxnp4ExprOecYoe8sGVr33Bo4WK3oPDybOepDkIcNPe76z2kr9gqM4itxlNLSJ3gRc2w2Nb7vQa2xsZPny5Rw+7O5L6+PjQ0ZGBsnJCZSWfknmvtdwuRqRgWyv2XzlSievwommoA6P4iYmyTuYrl9GXmAl73p5omoIYOROiVcOSgS5t8PRovenpNcoqqOGUW9rXRa2gKASiOzmQ2CkBVvTEfIzt3NsU3lbbIJKRWSPlPYZtoAL67eooKAA//nPf3jqqacICgoiMTERD4+LvxqiiDcFhV8BWZZ5fulh5u8qRiXAazelMiIp6OyGAM2V7qXS+nzwjYHbF4F32C8SZ2ZVJvevvp9mZzM9/HvwzoR38Dd0vibRqXCWl1Ny3++wHz2KYDQS8fJLeI0Zc15jybLMvjXFbPkuF1mSCYzyJOO+3nj5G85p1shps7Hu0/fIWrsSgNDEbkx9+El8gk/dmF6WZMybSmlcWQguCUGvxmdqHKpePqiN7iQTURTZsWMH69atw+FwIAhCWxP55uYtbN/xYNu+tmP6DBao7+RgLWjy6wkuruR6YTXdvNexzlvmOUnP0EPePHxQIr7CvRfNpvelOGEINXEjqXf5uAOzgSBAeJIXfiENtDRlU7BvJ8e2tNeUUmu0xPTtR9KgYSQMGITR67db7FRBoSvy1ltvcdddd/Huu++iPs8VhLOhiDcFhV+BN9fl8P5G95LVv67pQ3rKOYovSw18Nh1qj4F3pFu4+VycfWc/Z0vZFh5Z9wgtrhb6B/fnjXFv4KXzuihj2w8fpvrhR3BVV6MOCiTq7Xcwppy6nczZcNpF1n2RzbGd7iKx3YaEMvrmbmh0p6+9diLVhfksfuXf1JWVgCAweMZ19Jt6NabT/LXsrGlxz7YVuqe99Em++F2TjNpH1yYUf95EPioqiilTpuDp2cShw7Pb9rUVavrzve4RdtYb0OQ306vkGNP1P+IIPshKg56SPB0jf5K5P19CLYNd50Nx1ABqEkZRT+ssmQsQICzehHdgNdb6wxRl7SZ3+8klPRLThhDWvRdevn7K/jUFhV+I2tpabr755l9MuIHSmF7x1cVj7Iq+PttawIsrjwLw5yk9uG5A5EljntJXSz18Nh2h+jCyV5hbuPlGd1gqvVgxrilaw5MbnsQpORkWNoyXR7+MSWvqMO75+mpev56Kxx5HbmlBl5hI1LvvoA0PP+M4p/PVWN3C8nezqC21oFIJDLs2kd6jIxAEoYPNqcaWZZl9K5fy0xcfIjqdePj5kzHnMaJ69cFms538nUgylq1lNK0oRHa2zrZNjsOUFtLmr6Wl5aQm8hMmTKBXrxgKCl/n0GF3vbZSIZbFhifY0BCEJquJceVr6ee1hCORtWyr0jFyk4F/HZUxOiTsOm/Kw/tRHTuCem0o0Cq6BAiO0eLlW46l7jBF+/YhOtt7yZp8fEkYMJjEQUOJ6tUHjVbbtn/tUn/Hfmu+ukKMXcVXV+CKK67g8OHDjB079hfzoTSmV3z9InaKr1PbLdpfwV9/PATA70bGcsvAsNO+Qx182RrRz78OVeUBZI8g7DcsQDaFnTI54UJjXFqwlL/v/DuiLDI2cix/G/w3VKIKm3jhvpq+/pq6f78AkoRh8GCC//MCopcX4jn8jvzcV2l2A+s+P4rDKmLw1DL2jmRCE7zb+h+eKUabuZl1H75N/t6dAMT0HcDYe+7H6OW2/7mNWGfDvLAAV5G7bps2zguPK2NR++qx2+3IsruJ/Jo1a7Ba3dmmKSkpjBx5Bc3mRWzbfg+i2EQ1QSzRP8yaxiQ8DtZwXe07ePpuId9TQjoocMchDf5mCYfWi6qgVKojh1BviqFNsAH+4TImz2Kaag5QvO8osiS1HfMOCiau/yDiBwwiJDG5raSHSxRxtZb+uNTfsd+qr/O1U3x1tIHffmP6V155hauuuoqoqCjS09PRnUMf5s6iNKZXfHXpGLuSr015DTy90L1p/fahMTyR3uP09cJO9OVohm9vRajYj2wKgJk/og8+dWX/C43xh4IfeH7H8wBcmXAlzw59Fo3q1D8TnfElSxLVL75I3cefAOBx5ZVE/P1vqM7xR+1EXwB7VxaxbWEeyBAc60X6rBQ8/U7+LTpVjCWHD7D09Zcw19Wg1mgYcfOd9MuY1na8gy8ZLNvKaVpe4J5t06nwzojDY3Bo2/m1tbUsXbqUvDz3/rXjTeS9vPLJybkNa0s+jXizTPsYy5sHEbr/CNc6nsGmyse7Qs2I1RIzq8Gh9aA6MJW9yWnUeyfQQbCF2TF6FNNUdZCyg7kdrjEwOrYtQzQwOvaM38Wl/o79Vn11hRi7gq+u0pg+MTGR8ePHc9VVVyEIAiZTx9qSgiC0ZZ2fL0pjesVXl4+xK/jaWdjAnLn7ECWZq/tF8NdpvVCdpTWTIAgITgvCVzdAyU4w+iHMXAghPX+RGD/L/ow3s94E4ObuN/PUoKdQCWcur3EuvqSWFsqefIrmVasACHz4ITxuvx2VTtfpe++0i6z7PJvcPdUA9LwijJE3dkOtPX2cx+OTZYlt385n27fzkGUJv7Bwpjz0JCHxiae0EevtNHx7DHue+0dWH++D37XJaPzdItHpdLY1kRdFEY1Gw9ChQxkwIJT8/P8jv2ATVoysUN3BkuYJdMtbzlTHHDzKzAw+BD0LBVxaI9WBfdmbOpB632SOCzZZlvENbsZgLKKx4gBlh0pPDI7wpO7E9BtIj6Ej8AsLP+d7eOL9uNTesd+6r64Q42/dV2fj+rV48skneeONN0hNTaVHjx6/vZk3BQWFs7O/pIHfzd2PwyUxoWcIL1zb56zCDQCnFb67HYq2gt4HbvsBQntf9PhkWebVPa/y4YEPAZjVZxYPpD5wUX4oXbW1FN9/P7Z9+xG0WsKefx7vqVPOq25YY3ULaz8+Sn25FZVaYOSNyfQaEXFOts011Sx782VKDrv7h/YaNY6xd92HznByEWBZkrHtrMK6ugTZISFoVfhkxOExJKytF2pubi5Lliyhrs6dxZmYmMiECUOorvmI3XsW4EDDauEqljeNpVf+F1xbPo/uR2UGHpMR8KA6qC/7+vSnwa8bcqtAlmURn4A6tLpCGsoPUHm0PUNUpdYQ3bsvSWlDSRg4GJOPr9L0XUHhN8onn3zCU089xT//+c9fzIci3hQUfkGOVTZzx8c7sTpEhiUE8PpN/dCoz6FYrMuG7rs7EQo2gs4LbvsOwlMvenySLPH89ueZf2Q+AI/2f5S7et91Uca25+VRPGs2zpISVD4+RL3xOqa0tPPadFyQVcPqjw7hsImYfHRkzO5NaLzPOdnm79nJuo/exmZuRmc0Mv7u++kx4tQlSVz1Nuq/OYo91z3bpov1xv+6ZDQBbpHX3NzMypUrycrKAsDT05P09PF4ee0k+8i12F0W1stjWFvbnbQD3zH72FIGZ8sYnSaqA/tyqGd/6vy6Q5tgc+LpXYZKnUdjxWGqctszRLUGI3GpA0gcNJT4fgPRm9qzX7vKxm0FhcsRURSZMGHCL+pDEW8KCr8QxXVWbvtwB/VWJ73DvXj3tgEYtOeQOu5ywNe3oy74CVnr4W4yHznwosfnklz8ZfNfWJS3CAGBpwY8xc29br4oY1t37qT4gQeRGhvRRkUR9e676OPjOj2OLMnsWlbAjsX5IENogg/ps1Lw8NGf1dblcPDTFx+RuWIxACHxSUx9+El8Q08uyyLLMpadFTQuzkd2iKBR4ZMeg+ewCASVgCRJ7Nq1izVr1rRttB40KI0+fWQKix6jvKqIDeJAcg5p6J+5lX8e3kiA2UR14BDyEvtR79cduTV5QJZaMHmWoVLl01CeTW1De4ao0duHhAGDSRo0lOiUvmh+geUWBQWFX5aJEyeybdu23262qYKCwqmparZx64fbqWiykRTsybu3pOKpP4fXTXTCN3ciHFuBrDHCzfMgeshFj88hOnhyw5OsKVqDWlDzjyv+wbjwcRdl7MZFiyj/45+QnU6MffsS+fZbaPw7X9jX3uJi9ceHKNhfA0D3K0IYdWN3NOcggGtLilny6r+pLioAYMDUqxhx00zUGu1J57oa7NR/exT7sQYAdDHemKZF4xHhiyAIlJWVsXjxYsrKygAICwtjwoQeNDS8y8HsbayrisO4OYhBB/dxXbWR6sCBVET153AHwdaMwVCMIOfRWJWDvfHnGaJpdBsynIjuPZWm7woKXZxnnnmGG264AQ8PD6ZMmYL/KX7/TvVZZ1DEm4LCRabR6mTmhzsorLUS6Wfks7sG4Xv2iSIQXfDdvZC9GFmtx3H1J+hiR1z0+KxOK4+se4St5VvRqXS8OOpFRkeNvuD+lbIsU/vOO1S/+hoAXhMnEv7Cv1Gdx76sunILy97JoqHSilqjYtTNycT280OtOfOSsyzLHFi3irWfvIvLbsfk48vYu+8nedDQk/bwybKMdVclDYvzkO2ts22TYvAYFo7d4S4Xsm7dOnbs2NGWGTdmzAC8fdax+9CLFG73InKPgeuL6qgP6EtVUH82JXVDVmnc2XRSLQZtMZKYg7m+GPsJyWVB0bEktrakCoyOxW63YzAYusyGbAUFhdPTt29fAB577DEee+yxU54jtpbuOV8U8aagcBGxOlzc+ckOsiuaCfLS8+U9gwn1OYcWTZIIC++Hg9+DSgs3fI4UNfKix9fkaOKBNQ+wt2ovRo2R18a+xpCwIRe8h0p2Oil/9lkav/0OAP+77iL4948jnGMz+BPJ21vN6k8O4bSLePrpybivN0HRXme9h3arhVXvvcGRre7uBdG9U8mY8xjqUyQluBrtNHx3DNuRegB00V74XZeMNsiEJElkZ2ezdu1ampvdPUtTUrrRvUcpe1Y+imorJB/zIsDHLdi2Dj1BsInlaLWFSI4cWpqqcbT2HkUQiOjWg8Q0t2DzDQltv3fK/jUFhUuKv/zlL7/4H2KKeFNQuEjYXSKzP9/NnqIGfIxaPr97EDEBHmf/j7MkwaKHYP98UGng+k8haeIpC/BeCHW2Ou5bdR+H6w7jpfPirXFvkRqcesHjis3NlD3yCJYtW93N5f/8J/xv7vzeOUmS2bk4n11LCwAIT/Jl0r0pmLx1Z72H5ceOsOS1F2isqkSlVnPFDbeRNu1qEIQOok+WZay7q2hYnItsE0Ej4DMxFs/h7r1tdXV1LF26lJycHAD8/XzpEVJO3bLnqX9BS6RpEFVB/diV1r1VsLmQXMWoKUBy5OJsacLh1nuoNRpi+vQjYeAQElszRBUUFC59nn322V/chyLeFBQuAqIk8+j8TDYeq8GkU/PxnWl0Dz2HIpKyDEsfh71fuDMQr/kAuk/p0PLqYlBpqWTWqlnkNebhb/Dn3Qnv0t2/+wWP6yovp+yhh3Hk5CCYTO7m8qNHd3ocm8XJqo8OUXSwFoC+Y6MYek0C6rNk5sqSxM5F37F5/udIooh3UAhTH36SsKRu7uMn3Eex0U799znYst0lOHRRrbNtwSZcLhebN7prtrlcLowtTSTYcvBfWwqqPshBs8hKPT7DZkdy5iCKx8BVhOSy42z10d5DdChxqf3RGU0/D1lBQeEy4ujRo9TW1hIYGEhSUtJFG1cRbwoKF4gsy/zxuyyWZlWgU6t477aB9I/2OxdDWP4H2PURIMBV70Gvqy56fMXNxdy78l5KzaWEmEJ4f+L7xPl0PvPz59gOHqL8vvsQa2rQBAUR+c7bGHt1vrl8bamZpe9k0VTdgkarYvSt3ek2OPSsdpaGepa+8RJFWZkAdBs6ggmzHuhQUgNaZ9v2VNKwKB/Z5gK1gM/EGDyHRyKoBfLz81m8eDFNZaUElmUTU16DzpFEddAEsru3CjbJjOg8hOQ8jOgqR5DbEw48/PxJHDiEhIGDCUpIwsPTS9m7pqBwmbNgwQJ+//vfU1JS0vZZZGQkL730Etdee+0Fj6+INwWFC0CWZZ5fepj5u4pRCfDaTakMTwo8F0NY9RfY/o7739PfgD7XXfT4chtyuXflvVS3VBPlFcX7E98nwvPcCtueieZ16yh9/HFkawv6pKS25vKd5diuStZ+dhiXQ8LL39C2v+1s5GfuZtmbL9PS1IhGr2fsHbNJGTPhJNEkNjlo/jYH51F3toA20hP/65LRhnhgNptZtXgxVSuXEFlWjKc9jtrAceTHurNEJbEOybEH2XkY0VXbNqYA+IVHkpQ2hMS0oYQmJCGoVMiyfMFJHwoKCl2fpUuXcuONN9KrVy8eeOABwsPDKS0t5YsvvuDGG29k0aJFZGRkXJCPCxJvx/uTdfb8zm7QPR87xdflEeOv7evNdTm8vzEfgH9d3ZtJvUJPGvOUvtY9h7DFnZUpT/kvpN7SYan0YlzXodpD3Lf6PhrsDST6JvLu+HcJMgWdcszO+Kv/ai6Vzz3X1lw+8rVX0Xh7n3OssiwjuiS2fJdD5qpiACK7+zHh7p4YPU+9v+14bC6ng83zPmf3kh8Ad1/PKQ8/SUBEVNt5x/9/S2Y1DYvykFvcs23e46PxHBGJLLnY9eGHFP34LSZzKN7+gyiPnokkqJDFCkT7FmRnNpLY3CGG0MRuJKYNJmHgkDZ/p7p/l8Nzr/i69GLsKr66As899xwTJ05kyZIlqE5I2nriiSfIyMjgH//4x68r3ux2e6f/0jxe4PJ8fHXWTvH169ldDr7m7izhxZVHAXhqYiLTUoJO+z6caKfZ8grajf8BwDH+H4gpN50yOeFCrmtfzT4e3fQoFqeFnv49eWXEK3ipzpyxeTZ/siRR/+qrNH32OQCe06fj8fvHcel0uDrxO2CzOFn7yREqctziqPfYcAZMjkZQS2eMr7q4iJ8+eovqAncD+N7jMxh6/a1odLoOdpLZiXlxIc4jDQCoQg14zohHqsln91OvUp3VRKNvX+pDHkUKBclVjNSyDsl1FFk6IblBUBPWvSfJaUOI6zcQD7/2ukzn8j13hq703Cu+Lt0Yf+u+jjemT0tLQ61WM2fOHObMmdOpMf4XZGZmMm/evA7CDdy9We+//35uPo+Erp9zQeJNr9d3qrfecaWt1+s79aWdj53i6/KI8dfytWhfOX9f5hZuD4xJ5L4xyefma+sbCBv/5f58wt/RDnuAk8vGXth1bS3fylNbnsIm2hgQMoDXx7yOp87znK/tVP4km43yp/9I88qVgLu5vP+sWdjt9k7FWFPczLJ3D9Bca0OjUzF2Zg8SBwSf1e7QxnWs+fAtnDYbBk8vJt33MAkDB590DS37amj4Mbdtts2YoqaueBNZj35JrTaJBr90pDgXkrMA0bocyZULsqttDIdKS0tkdyaNG0H/4SMweJz5vv3c/6X+3Cu+Lt0Yu4Kv4+Jt586deHufQ0LYr4RarcbhcJzymNPpPEnUnQ8XJN4EQei0cj5u87+wU3xdHjH+r32tO1LN4wv2Icswc2gMj09MPusYgiAg7HgPYdUz7g/G/hnhiocuenxritbw5OYncUpOhkcM5+XRL2PUnFznrDP+XHV1lPzuflr27WttLv8cPtOmIctyp2I8sr2C9V9k43JKeAXomfy7PgRGnnl/m6PFypqP3uHQhrUARPZIYfKDv8croOO+QrHZQf0POdgO1iLZmrCZD1JobqD6WAQNfilIQQmIzlwk8w9IriKgffnFqdZyxDMJz9Q0/nxzBsE+Hm1N35V3TPH1a9spvjradAXS0tJ44YUXmDx5MkZj+++v3W7nxRdfZPDgwWewPjeUhAUFhU6wq7CB+7/MxCXJzEgN59lpvc7pB0Wd+TnCiqfc/xj5hPv/LjKLchfxzOZnEGWRiTET+deIf6FVn2pe79yx5+dTPPs+nEVFqHx8iHz9NTwGDerUGJIoseXbXPatde9vi+7pz4hbEvDxP/OsVmVeDktee4H68jIEQcXAGddyxXU3o1a3/2zJskzL/hrqv8miOS+TYnM9VYZw6n36IXs1IDlzEZvnI4sVHcZWaQWOmhLZ49uHbsNSeWliT4JM+rYxFRQUFM6X//u//2PcuHHEx8dz3XXXERoaSnl5Od999x21tbWsXbv2gn0o4k1B4Rw5WNbI7+buw+6SGN8jmP9c1xeV6hz+Esz8Et2KVrE27CEY86eLHtu87Hk8t/05AKbFTuNvw/+GRn1hr7d1925K7p+D2NiINjKSqPfeRR8f37kxmhys/OAApUcbABiQHkPatDgcDvtpbWRZZs/ShWz48hMk0YVXQBCTH3ycgNiEDn0/XfUWil78jvzDRVToAqn3TkE2ViI6cpGaNyNLDR3G9Te0UO4RzhLDKEq9IxnWP5QfxvcgzHQuvcsUFBQUzo3hw4ezcuVK/vCHP/Dmm28iyzIqlYrBgwczd+5chg0bdsE+FPGmoHAO5Fabuf2jnZjtIoPj/Hnj5v5oz1JAFoD9C2DhAwDIg+9DmPA3uMhT/x9mfcgre14B4ObuN/NQ74dQX2Bz86alSyl76g/ITieGPn2IeutNNIHnUALlBKoKm1j2ThbmejtavZpxd/QgoV/wGWe2rI0NLH/7FfL37gIgMW0oE+97CIOHJzabDVmSqNm0m0Pzd1Fcr6PBKxLJt7VobtMakK1tY6kEiRhTA5KngeWG4axRpSEZtQzqF8L8cT2J9FBEm4KCwi/DqFGj2Lp1K1arlfr6evz8/DCZLl7RbkW8KSichbKGFm77YDu1Fgc9w7x4f+YADNpzEEeHFsL3sxGQcaXORD3pnxdVuMmyzOt7X+f9rPcBmNVnFnP6zmnb1Hu+Y9Z+8AHVL70MgNeE8YS/8AIq47ntmztO9tZy1n95BNEl4RtiImN2b/zDPc5oU5iVybI3XsLSUI9aq2X0zHvpOyEDQRCo2XWIQ9/toKhEoMEQiOSUENUHkBoXA+0JBxqVi0TPOqK9GtllSuEN8Sry5HBkk5rU1EBeHtuLBM/OXYuCgoLC2aivr+eee+7hzjvvZOrUqW2fm0ymNtG2ePFiPv74Y9577z0CAgIuyJ8i3hQUzkCt2c6tH26nrNFGfJAH79/SFy/DOewjO7IMvrkLZBE59RacE/+F+iIKN0mW+PeOf/NV9lcAPDrgUe5KueuC9mvJLheV//wnDV8vAMD/9tsJfvIJBPW5z+KJLonNC46R9VMpALF9Ahl/Z0/0xtP/1IguF1sWfMmOhd+ALBMQGc2Uh59E3Qyb/7GAgnwn9WoTkrMGUcxBbizlxIQDjc5Bd48aunvVovZQ8aFrCn9wjaLZZULy1NAjxZuXx/all7fSqkpBQeGX4YMPPmDfvn2kp6ef9pz09HQee+wx3nzzTf7yl79ckD9FvCkonIZmm5PbP95BXrWFCF8jn981CH/DOQiwnNXw9UyQXND7Opj2GjicZ7c7R1ySi2e3PMvC3IUICPx5yJ+5vtv1FzSmaLFQ9fAjtGzZ4m4u//TT+N92a6fGsDTaWfH+Acpz3N0M0qbGkTY5FuEM+wIbqypY8tp/KD92BICeAyfg6Ypm+d+20YDkzhB15iKLNR0NPRz08KhkgKmaYIOFPaok/uq4l59sfZFRIXlrSepl4oVRqfTUqztV0khBQUGhs8ybN497770Xjeb0skqj0XDvvfcyf/58RbwpKPwS2Jwid3+6iwOlTQR46Pj87kGE+xrPXpQ67yeYdwuIDug5HWa8Ayo1cHHEm1N08tTGp1hVuAq1oObvV/ydaQnTLmzMykqKZ8/Gnn0EwWgk4qUX8Ro7tlNjVOQ1svzdLCyNDnQGNePv6kVcnzPvkTuydSOr3nsD0aolQD0ATN05lt2C5NyF6MgF2dx2royMzUck2buacbpiAnR2bLKO5cIgXndcSa4UCYDkqyO6h45/j0jlCn8fZFlpWaWgoPDLc/ToUQYOHHjW8/r378/f//73C/aniDcFhZ/hFCXmfLmHHfl1eOk1fHrXIOKDPM++JFm4FebeCC4bdJsM13wIak2HtlcXQourhcfWP8am0k1oVVr+M+o/jIsed0Fj2rKzKZ59H67KSlQBAUS98zam3r07NcahTWVsmH8UySXjF2pi8u/64Bty+iVKp83Gijc+pGZ3FQZdBi2eLdQ7cpHMC4D2wpYulUxdgIsYLxvTtYeIULmPVQmBvCZO5T1HOmbc++hEfx1hyWr+PrQHE4NDu0w9KAUFhV+ODRs28J///Ifdu3dTXl7O999/z4wZM057/nfffcfbb79NZmYmdrudXr168eyzzzJp0qSz+nK5XGi1Z99So9VqcTov/I95RbwpKJyAJMk8sWAfa7Kr0GtUfHhHGikRPmc3LNkFX14HTiskjofrPoELrLF2ImaHmQfWPsDuyt0YNUZeGfMKw8IvLN3cvHETpY88gmSxoEuIJ+i11zB2ohSI6JTY/HUuR7ZWARDfL4hxt/dAZzj5Z0WWZWqKm9m3YAt5WWW0YEdS1yDZM8EutZ3n0EgUh9sJ9tIzRShgoFiKAMgI5Oh68Y51FN+6hiLj3ocnBuoJTBL404BYro6IR6WINgUFhVYsFgt9+/blzjvv5Jprrjnr+Rs2bGDChAk8//zz+Pr68vHHHzNt2jS2b99Ov379zmgbFhbGoUOHGDly5BnPO3jwIKGhoZ26jlOhiDcFhVZkWeb/Fh3kh8wyNCqBt2/tz6A4/7MblmXC51eDoxniRsINX4Dm4pWhaLQ3ct+q+zhQewBPrSdvjnuT/iH9L2jM+gULqHj2/0AUMQ0eTMRrr+LU6c7Z3tJgZ9l7WVTmNYEAQ6bH039STIcZL1mWqSps4sjKwxzbfYRmW3Hr/rXqDmNZ9S5yIsyYEkMYa3PwYPVBPKUW9xhaL/Z7j+K58oFst7W3IBODDXgnwBO9/bgtrt9FTQZRUFC4NMjIyOhUA/hXXnmlw7+ff/55Fi5cyKJFi84q3kaNGsVbb73F3XfffdoZOKfTydtvv82YMWPOOabTcUHi7Xh/ss6e39mMuPOxU3xdHjFeTF//XXWUT7cWIgjw4nV9GNOtY02yU/qqPAifz0CwNyJHD4Ub54LG0GGp9EKuq9pazezVs8lpyMFX78s749+hZ0DP0451Nl+yJFHz2mvUvvseAN5XXknY3/8GWi2yzXZOMZbnNrDivYNYmxzojGom3NWTmBT3/jZJlKgsaCJ73RGO7dyPtaUA0ZEHcnOHMcxGB9nRZsyxJiZE9eTZnMPEFa9uOy4aE8iMvJKnjyRwtNQtoGVACjViiof7EwVmJ49A35oJe77342LZ/K/tFF9dy1dXiLGr+AJoamrq8Ller0evv/h1GyVJorm5GX//s/8R/+ijjzJw4ECuuuoq3nvvPcLDwzscLysr49577+XIkSN8+eWXFxzbBYk3u93e6c3Adrv9vPajnI+d4uvXs+tqvj7bVsxra3MAeCYjmUndA075bJ9oI9QcRT/3KoSWeqSw/tiv/gwkNZzF7lwprC/k8W2PU2wuJtAQyBuj3iDeI/6s79zpfMkOBzV/fRbL8uUA+Myehe/s2dglCez2s8YoyzLZmyvZ9n0BsiTjF2Zi+C2xBIR5kH+gkmMbc8jbuxdbSwGSM58T968BNJtaOBBnoSTMSVrkQGZj5IpDq9AW7WwdX4VNM5TtSdfxlyN+FGW5/3qVBRDDTejjBG4Pr+N3CaPw1JmQnU5s57B35Lf+/J6vneKra/k6XzvFV0cbgKioqA6f//Wvf+XZZ5/t1FjnwksvvYTFYuH668+ezd+nTx/efPNN7r//fuLi4hgwYABxcXEA5Ofns3v3biRJ4u2336Z3J/cVn4oLEm96vb5TKfjHlbZer+/Ul3Y+doqvyyPGi+Hru72l/HPFMQAen5jMnSMSz+6rLg/mX49grUUO64sw8zsMBt+LFmNBYwEPbn6QypZKwj3D+WDCB0R6RXbquk70JTY0UPLgQ7Ts2gUaDaF/+z98r7rqnGN0OUU2zD1K9lZ3j9D4/kEkDwoha+lBCvbtxmHLQ3KVAO3711SyQKNHM5mJFgrC7MR6x3Bt5EQml+Xit/sHBJdbhIqyF2ZxIhtjr+PFKijIdI8hq0CM8EATq+bW4EIeiB9BuN/ILvFMXUoxKr4ujxi7gq/j4q24uBhvb++2z3+JWbe5c+fy7LPPsnDhQoKDg8/J5t577yUlJYXnn3+edevWsW3bNsBdqDc9PZ2nn36aIUOGXJT4Lki8CYLQaeV83OZ/Yaf4ujxivBBfqw5X8dS3WQDcMzyOB8YknnEcQRAQGgoRPrsSzBUQ3Avhth/A6HfRYjxSd4TZq2ZTa6slzieO9ye8T4hHSKeu60RfjuJiimfNxpGfj8rT091cfujQc46xuc7G8nezqCpsRpZlfAObyNm6mcPr807av6aVVdSbGtjdzUJ+mAOdU0WakMw/ug0jJXs5HHi+7VyHlECTOJWlplF8iEhhjnsWTVYLiFEeqGJ0zPA5wFM9RxDpMxybzdYlnqlLMUbF1+UR42/d1/Fzvb29O4i3i838+fO5++67WbBgAePHj++U7dChQ1m0aBGSJFFT465PGRgYiEp1Du0UO4GSsKBw2bI9v54H5+5DlGSuHRDJn6b0OOsPidBUCnOvhqZSCEyGmT+A6RySGs6RrOos7lt9H02OJpJ9k3l3wrsEmjrXU/REWvbto/h39yPW1aEJCyPq3XcwJCef3bCVooO1LH8vE1tzPpIzF9GZT2VDe/01ZDBJauo969jSvZnCMBFkCK8xkJEdxMM9Eomo/glWrXSfLmhoYTj1tgwWyol8aRApbXbPwMkaATHaE6L1TDLt5Ink3nQLuQdBEDq9N0ZBQUHhfJg7dy533XUXc+fOZcqUKec9jkqlOucZu/NBEW8KlyX7Sxq4f95+HC6JiT1D+NfVvc/+F2BzBbp51yE0FIJfHMz8ETwv3su5s2InD6x5AKvLSt+gvrx8xcsEGM+//13TqlWU/f4JZLsdQ8+eRL79NtqQs8frsLk4ur2AHQvX0Vh1CMlZwIlFhgVZhY9TwOzbyNrkOvLC3cIqUPam3xGBK2plJoVYiTHtQ8jfDYDsEUyLYTqVpcP5Hk/mqpxUy3awgaxV4Yr1RI40MEq/jcdighkQcx8qlfLzpKCgcP6YzWZycnLa/p2fn09mZib+/v5ER0fz9NNPU1paymeffQa4hdvMmTN59dVXGTJkCBUV7m0iRqMRH59zKBn1P0T5dVS47MipMnPHxzuxOkSGJQTw2k390KjPMqVtrobPpqOqz0P2iUK4fRF4h120mDaWbOTR9Y9iF+0MDh3Mq2NeRSWe/zR73aefUfXvf4Ms4zFqJJEvv4zK4/SN4W0WJ5lrDnBs2w5qi/Yjuco4sX+oWtIQYJdxBrWwNL6cIxEyCAJGjZFJgcPw31RB/8pj9PcvJzjM4jaSgKjBOMJvonBnPN/UOpmPgwbsIIGsV+GK9UKKMDBUu50HQiVGJt2BRuN13tetoKCgcJxdu3Z1KMvx2GOPAXD77bfzySefUF5eTlFRUdvxd999F5fLxZw5c5gzZ07b58fP/y2hiDeFy4qSeiu3fbidequT3uFevHvbAAzaszRet9a5y4HUHEH2DIPbF4Fv1JltOsGKghX8YeMfcEkuRkeO5sXRL6JT6bCJnW/rJIsitS/8h+a5cwHwvfEGQv/8Z4RT9NszN7Swd8UOjm3fRkPFQWSxrsNxvWggyGJDGwbL4svYEWFFau1T2j94AFcmXEnk/grUS9+hl3cZxnCX21BjgN7XIva+k/zNRj7/qYxvMXN8sVU2qHHFeyFGmBgo7OBevxImdp+F0Xjx7qmCgoLC6NGjz7jl4ueCbP369b9sQBcRRbwpXDbUmO3c9uEOyhttJAZ78u4tqXjqz/IK2Brh86ug8gCyRzD2m75B7xd70WL6IecH/rrlr0iyRHpsOs+PeB6tSntee7wkq5XSJ57AvGYtAMFP/B7/u+7qsBxcV1bP7qWbyNu7HXPtEZBbThhBwMNpJKShCVEvsWtICx9GVuLSuO2DTSFMT5jO9PhphBUfoG7+Xwlx5SK05mpI3pGoBs+CfrdReNDGOx8f5gdnJcc9yB5qnPHeSKFGegv7mGnYzrRe9+DrM/t8bp2CgoLCZYsi3hQuC5psTm7/aAf5NRYifI18dlcafvqz7HGzN8MX10J5JpgCYOZCZO+4ixbTV4e/4p87/gnA1UlX85chf0GtOsss4Glw1dRQ/Lv7sWVlgU5H+L/+ic/kyQCUHilmz/KfKDqwC1tTPiC22Qlo8bLriaivAZWabT2cfJReToveXa5Dp9KTHj2WGYkzGOLbHfX+eTg/mIrWXEKoewAavVPwzvgjqm7pFJSZef3N/SyqbWqr8iZ7adyiLcRANw5zo2o5UxOmExHx5kXPwFJQUFC4HFDEm8Ilj80pcs8nuzhY1kSgp44v7hlMmI/xzMVuHVb46gYo2QEGX5i5EIJ7nLIA7/nwQdYHvLrnVQBu7XErT6Y92en0/OPYc3MpnjUbZ2kpKh8fAl96kQqNNyufe5Pyo5k4beUdzldjwrdFTVR1GaExwfwUA/8Z20yNj7XtnJSAFKYnTicjLgOf+iLY8T5y1gJwWtECdlHNMWc8fjP+j/DBk8mtNvPa+7tYkl/TLg19tTjivZEC9cSTw3V8y5WxI4mJfg+nUz7v61VQUFC43FHEm8IljVOUuP/LPewoqMNLr+HTuwYRF+hx5mVJpw3m3QSFm0HvDbd9B6G9O7S8Ol9kWea1va/xQdYHAMzuM5s5qXPOW8hYduyg5IEHcTQ3U94tlcrk7tS8/SaSq2M7Kq3sS4BFJKaykJB4AwXDw/g8pIXdZLed463yYUb36cxInEGSVwwc/hG+vAGKtgIgANU2E5n14cgp1zLq7ofIKjfzt093sTK7qi29QfDXYUvwRvbTEU0h18jzmRQYTc8eb6LTBSDLMk7nxRHBCgoKCpcjinhTuGSRJJknFuxjbXYVeo2KD+9Io1f4WdK9XQ74+jbIWw9aD7jlG4gYcHHikSVe2PkCX2V/BcBjAx7jzpQ7z3u8sq+/Zsf7X1ARlYhFYwGaobXVFGgwyH4EN7UQV56LX6yaulE9WRznwyLbDpzSEQBUkor45t7cMugGJvUejaerCWHPp7D7EzBXAiALKnItweyqCqZKDmH83fdjjkpl1ryD/HS0vUivKlBPS6I3so+OMLmUa5jPSJ2D/ql/x9Mz6byvU0FBQUGhI0pjesVXl47xdDayLPPsokP8kFmGRiXw1i39SYv1azvvlHaiE765E+HYSmSNAW6eB1GD2mbcLuS6XJKLf2z5Bz/m/gjAnwb/iRu63XDasU7lS5ZlqgoKyFz5E3lbNtJirwJ/gEYABMEDD5c3oQ2NxFQcxTO8BXHcUNZ3T2SefTM1LYuhdWU00BJBt6rBDDGN5Jq7h+LRuBvpx/vg6DKQ3Qufskcw+eo+rNzdhMWlJzgukbgrZ/OX/fXsWto+G6cJNmJO8kL21BIkV3K1/DXD5FxSU/5KcPDottjP9p2d7R7+2s/Ub8lO8dW1fHWFGLuKLwU3SmN6xdcvYvdr+3p9XR6fbS1EAP45owfDYr1PelY72Eki2sVz0GQvRlbrcFz9CVJo2kl73M4nPqfo5M9b/8y6snWoBBV/SfsLk2Mmn1ODeUl0UXzgIAfXb6HsSCbOlvoO56hUgXg5DETWVhNRdRh9kD/C6OHs7zeQr1W7OFT/LTS4z/XV+dLLMpiwQ30ItEbSI82DYcm70M19GlXNEY6nDoiRQ2iMu5LFy7KoLi5BwoB4xXV8KUaT/WMeAGpAE2qiKckL2aTBT67lKnkBV7h2EB0+m4T4VxEE9WmvsSs+U781O8VX1/J1vnaKr442AGlpaajV6pPqsV1OKI3pFV9dOsZT2Xy8uYC3NhQA8OyVPbk2LfbMdsiwcA7C4R+QVRq4/jN0yekXJT6by8YfNv+BjWUb0ag0vDDiBcbHnLlXXktzE0e3bePA+k1UFxxCEu0nHFWjUYXha1MTVV1CSO1OtP5+eE6cQMGgKXyiP8C60qU4G90dETSChhGRIxgfmE7T9z40ltsJ0JUwYcDX+FcuRih2742TtSZcPa9BNXgWBw+Xse6T97A7XOQH9eNA2BUUl4mABZ1KQBNqpC7JGwxqvOUGpsvfMUpci7/nlaQN3IBGc/piwOd7H3/tZ+q3Zqf46lq+ukKMXcHXcfG2c+fOX7S3aVdAaUyv+OryMZ5o892eEv62+BAAj01I5vZhpy/tIQgCAiAseRz2zQVBjXDtR9At46LEZ3FaeGjtQ+yo2IFeree/o//LiMgRJ50nyzJ1pSUc3ryFI1u30lCey4ndDRBM6NQRBDQ7iKnMx69xAyqjAe/JGZhH3sZi33wWFS6lpqqmzSTZL5kZiTOYHDeZ5hyZ1R/tJ1Jax7ig5YSps6C09cSAJEi7B/reiMXiYuPn73Nw+3YOeXVnf+QgGmQ9NIsYtSo0oSaqEz1Bp8ZTbmaq/D3j5eVoxVSGDF6Cj0/MWe/J+dzHC7HpCr66QoyKr8sjxt+6r87GdSmjJCwoXDKsPlTJE9/sB+DOK2J5cGzimQ1kGVY8Dbs/BgS46l3oOf2ixNJob+T+Nfezv3o/HloPXrriJYZFDGs7LrpclGYf5PCmLeTu3kFLU3UHe0EdiEEVSnB9M1GVR/EyZ7mFpl6P6YkH2TLIix8KF3Ow4kdwt9/DT+9HRlwG6VHp9A3ti4DA/h93Yt/0ITd6rsRT3dpBQVBBt8lu0RY/GgSBsuxDfPvaf9nqCiUz6lZa1EaQwdukRRNqoizOBBoVRtnKZPlH0lkM1mASEl6he/cJyo+qgoKCwv8QRbwpXBJsy6vl/q/2IEoyV/eL4JkpPc8sKGQZzU/PIWx/x/3v6W9An+suSiy1LbXMXjWbI/VH8NZ58874d0j0TKSluYn8vbvI3rKV4oOZiB3KZahRaaLwUAUSWlVJRNUhTC3bEbRaZElCFODAkFC2XteNDbXv4drjbkWlETSMjBzJlYlXMjJiJBqVBltLC66jG6j9/hVSbBtQe7YmIJgCEQbcDgPubGvvJUkiq77+lvfXH2G/VwYOlR6AIB896ihPCkL1oBbQyzbS5cVM4UdULVr8/R9i0Mi7cDqdKCgoKCj8b1HEm0KX52B5M/d+theHS2J8j2D+fW0fVKqzzAT99G+0299w/+8pL0G/Wy9KLBWWCmatmkV+Yz4B+gBe6v03rJuymb/lI2qLcvj5cqhaG4eP4ENYaQEhNbsx2BtAq8Vz+HDwvYKDmxeyvjdsTjXQoKuBavfSaHf/7kxPmM7k+Mn4G/zd49makPfPR7PlPbQNRwkDEMDqOwDTuPsRekwDjb7N/ZH8Uv7vg6VsdwYj+vQHICLAiCbBmyM+alAJaGUnE+SlTOMHDA47kjiVUaP+hKenD7IsK+JNQUFB4VdAEW8KXZrcajOzvsjEbHcxKM6fN27uj1Z9lpZLm/6L8NO/AJAnPoeQds9FiaW4uZhZy+5FLKplTF0k3WqCWP/9Cx3OEdRBqLVxBOBBWGEWQTVr0LosoFbjMXQo3hkZOK7ox7ffP8/Sph8puPv4tbjwN/gzNX4qVyZcSTf/bu2DVh6EnR/C/vkIDjNawCkZyJPGEHjVIwQMGNIhhpyqZv797XbWFLQgCeGggigfFfpeIRzwFEAQ0MguxsoruJLv8BabaagfSGran4mL63lR7pWCgoKCwvmjiDeFLktZQwszP9pBndVJr3BvPrh9IAbtWXqDbnsbVj8LgHPkH9EMvfA0c2tjA9s3L2Ppqs8ZXaFBI4UAYKOO48uhWn0cIbKG4Jwd+Nd9h0a0gyBgSkvDe/JkDONGsdGyn4XHfmDT8meRTDKYBLSyilEx7t6iwyKGoVVp3U5dDncHhJ0ftHVAAKhzRXDQmk592HTGzx6KyVvXdmxfcQNvrj3GqsOVyAggqIhQN+E9NJm9JhUIAmpZYqS0mquEBQRQS3V1Ih6RzzJu7GTU6vPru6qgoKCgcHFRxJtCl6TO4uC2D7dT1mAjNsDEJ3em4W3Qntlo18ew/A8AyCOfwDX0ofN6AWRZprown7zdO8jZtYPKvGOATOjxSmmCB2ptHAZjHGGii4Ds9fjV/YRKdu9TM/bvj3dGBl4TJ3JIVc5nOT+yfPVrNDmaWu0hsQwyoiZy/bXP4GvwbXfeUOTufrDnM7C4kxxkQU2FdgTbK8ZS6kihx/AwJt/YDY1GjSzLbMmt5a31OWzOqeW4g0hnKfq0eA6G9ABAJcsMFzdwlWoewUIlDQ0hNAkPMTnjzss+JV9BQUHht4Yi3hS6HGa7izs+3kFutYUwHwMf3pZKoKf+zEaZc2Hxo+7/PexBGP1HsNvPbHMCTruNoqx9HN25jcLMPVgaajscF9QhqLRxeHrEEO5oxO/gCnzqf3TXkAN0vXrhO3UK3unp1HoLfJu7iB+33E1BU0HbGAFWNSMynYzO1TP42ddQDxiAQW8ASYLcte5ZtmMrQJbcBl5hWJNvZtnO/lSUm1BrVYy9vRuxqb4IgsDyAxW8vT6HfSXuDgwqWSLGUYSreyA5yWnICAiyzBWuHczQfE6Yqhyr1Zui6isZOfIBEhISzvn+KCgoKCj871DEm0KXwuYUmfXZLvaXNOJn0vLZXYMI9z7LY3zgW1h4PyDDoFkw4e/n5Kupppr8vTvJ3b2DogP7EDtszteg0sag0sbh0hkIthTR7fBGPJq+5HiqhL5nD/cMW3o6Zh8Tm6o2sWj/M+yo2IHcKuoMagOjvQcw6MtMeu5vRBccQtR776JPTsZWVwq7v4XdH0F9QbvruJEw8G5ybWms+SwHp13E019Pxuze+EZ48O3OQj7cWkxOlRkALRLxLblYk/zI7jkMuTULd6gjixnaD4jUlOBw6MkrHkpy8t1kpI9Ao1F+GhQUFBR+qyi/0ApdBpco8fC8vWzJrcVDp+bTuwaRGOx55jZThxfDt/e6Z6v6z4T0f4MgtPUrPRFJEqnIOUbenp3k7dlBdWF+xxMEL9TaOFS6eLx9/RDL1pNy+Bu8Le2zcPrkZLwz0vFKT0cbG8POip0szHmb1UWraXG1tJ03MGQgVyZcydBCPQ1P/Bm5pQV99+5EvfM2WmcR8vezMRz8AeF4dwW9D6TeDAPvQgpIYsePeexe7m4uH9HNl5G392Dh4Qren7uTsgb3/fDUqUi251Af6cn+niOQVe49a0NcuVypfpMYbSGiqKaoNAWjYQbTpmUQEhKi1GxTUFBQ+I2jiDeFLoEsy/zx+yxWHKxEp1bx/syB9In0PXOj4mOrYMEd7kbrfW6Aqa+AqmMmqt1qoXD/XvL27CR/7y5amps6HBfU4ai18WgM8YQH+xJYk4nX9g/RWxvaztHGx+GTMRnvjHT0iYnkNebxZe6PLN69mApLRdt50V7RXJlwJVMTphLhGUHdl19S+dyfQZLwHDGYiDsGo/r+WqjMapu9k8P6urNhU64BnQc2i5NVb+6n6KBbMCaODic7QMX4NzdRZ3EAEOCh5Qp/K4fkGrZ1H4bUmmgwWKhgqutV4tVHkWWorIynvn4kEybcQFJSUqf7FCsoKCgo/DpckHg73p+ss+d3xuZ87RRfl06Msizzz2XZfL2rBJUAr9+UytCEgA7nn+Qr/yeYfyuC5ETuOQOmvwmCClmSqC8rIW/PTnJ276DiWDaSKLbbCXpUmhjU2nj0XglEBmkIrNyDx5aXUVsb204r84PqYclMufd5PJJ70GBv4NuC5Sxa/AwHag+0neel82JSzCQmRU4iLSINlcodQ+W//03dx5+g83YSmh6GybAKYdX37uvVGKDX1dj73Ioudkib4KwtaWbZuwdoqm6hRQflfbx561ABFoc7/ig/I1elBrGp8jDfhscjqmMBGKSrZ5r1deLV+0AFDfWhFBamkZp6JddeOxytVvub+J4vR19dIUbF1+URY1fxpeDmgsSb3W7v9F/rdrv9vJZlzsdO8fXr2V1MX+9vKuD9je4lzL9P687IBN8Oz93PbVQlO9B9fSOCy4aYOJGWCS9Rumc3hZm7Kdy3h6bqyg7jCyp/VNo41Np4TH7RRPg7CCjbicfGZxBaLG3n2UJ8WRbfyJYeKlIHT+exfo+zsXIbS9a8xebyzYiyW0SpBTXDwoYxOWYyw8OHo1frsdlsOBwOJJuNmmf+hObYEmLGWjEFO4BqcIDkn4ArdSZiyvVg9MNmsyE73LNpeXtr2DQvl2qXi72+MvtVTpw57mXYbiGe3DA4kp2OGl5y2RGjkgHoLdVwnfAFCfaNoAaLxYf8/P74+gznxhsn4ufnhyiKiK3i9df+ni9XX+drp/jqWr7O107x1dEGIC0tDbVazZw5c5gz58LLPXVFLki86fV6DAbDOZ9/XGnr9fpOfWnnY6f4ujRinLujiJfX5AHwx8nduXlo/JltSvfAglswW0XyjKPJL0uh6OH7cNp/3ooqEpU2DpU2Hv+wMCJ8LfgXbkW79jWwWtvO1EZG4pWeztpEG883uJvXT4qZhE6nZ9qSae3lPXB3Pbgy4UoyYjMIMAacFKO6PBvHf+8mwjMfzVB3xqgsqKH7ZBh4D0LcSLSCgPYEG61Wx44f81m2poAdehdHTaI71UGCgbF+3HpFDLu1Lp4trXG3tlJDXFMJd/quJEFeAoDDYaCwIBWrOZX0yVPo3r37Sd/Lr/09X66+ukKMiq/LI8au4Ou4eNu5c+dlX8LogsSbIAidVs7Hbf4Xdoqvrh3j0qxy/vyDewny/tEJzBp56tIVgiAgyxIV25eTN/dv5DUkUm33BERgZ+tJ7tprKm08Km00obH+hJjqCSrYgrD4OaQTBJsmPAzv9Ay8MzLQ9+rJG5lv8H7WJyAIeOu8WVG4ou3cYFMwU+KnMC1+Gkl+SScHJ7rg2Ap0P72OumwrulZNJxkCUQ2ZhdB/JniHnfK6bBYnb76xn8WV9RR6SW2fj+sezE1XxLJN5eTR4ipaZEClJqKmkNs81pDitQRBBFHUUFLSk7KSFAYPGcmoUaPQ6XSn9PXze3+udLVn6rfoqyvEqPi6PGL8rfvqbFyXMkrCgsJvko3Hqnl43l4kGW4aFM0Tk7qddE6LuZmCfXvI2bmN4qw9tJgtQHDbcUEdilobj0obj1ofTFSyH+HGWnyz1+NasAzJakXG3W1UEx6G96R0vDPSMfTujSAINNobeXDVLLZXbG8bs8nRhEFjYEL0BKYlTGNQ6CDUqlN0HmgqdxfS3fMpQlOp+0UTwFLnje6qv6IdeQeoT/36iZLMNxvyeW35UUoRQQsqAaanRnDTsBjWOG3MLinHIroFXVh1MVfZfmRY5E8IiMiyQEVFAoWFfQkP6s7s+6YRFBR03t+FgoKCgsJvC0W8Kfzm2FvUwOzPd+MUZSb3DuUfM1JaZ9dkaooK3JmhmbsoO5KNLLfPSCHoUGliWwVbLHqTF9E9/AjXVeGVtRL7p6uQrFYcraerQ0PxTp+ET0YGhj59EAQBp+Tkp5KfWJizkLXFa5FOGH9I2BAmRU0iIyEDD53HyYFLEuSvh10fQfZSd5Yr4LKraMwzYlX3I+zVT9CcRkjZXSLf7ynljZVHKTG7lwc0wDV9wpk5PpHFZjM35xdjbhVtwTWlTKn+gbGJG1Fp3DXo6urCyc/rj+CKYNq0DFJSUpS/VhUUFBQuMRTxpvCbIqfawl2f7MHqEBmRFMi/p3cjf88O8vfsJC9zF+bamg7nC+oAVJo41No4BE04nr4G4noHEEIpHnsWY313LZLVyvEKa5qwMLwnTcJr0iRITsJoMgGQVZPF4rzFLM9fTr29voOPSTGT+H3a7wkxhWCz2TBof7bP01IDmV+621bV5bV97NTHU7W+nuZiA4bho4j678uoPU4Wfc02J19tL+LDTflUNbtFm0GCkV6ePHpXKosdVq46kk+Tyy3aQhuqGV/4A2Pj16Dv7hZt5mZ/8vP709gQTv+UVCZMndSp/agKCgoKCl0HRbwp/GYoqW/hns8zkZuqydBXM7psCx/O/ieiy9V+kqBBpYlCpYlzJxyoffDXFBLrc4TQbl5o9y7H8vJ6JKsVc6vJccHmnT7JPcOmUiHLMrk1uazOWc2SvCUd2lRpVVqckhM1av418l+kx6UDP0tTl2V3Q/hdH8GhhSC2zufpvZH73EDtHhfVn64AjPjefDM+jz2KqlUoHqe62c7Hm/P5fFshzTb3NXpKMNCu4dqRcRzobWRGXhGNLvcMXrTLxtDMeYyNXoVnH3cChsPmQX5BX6qq4on0C+fG2dPx8fVBrz9LuzAFBQUFhS6LIt4UfnVcDgcH9+zlvS+XMKEuFz+Xu55aSetxlcYHQR3rFmuaKFQqLWFxJmKb5xFctga5WMRcpsf27fcczynVhIfhPbFVsPXt27Z02GhvZGXhShblLmJv1d62GIwaI6MiR1HQWEB2fTY6lY7/jvkvIyNHdgzW1gj7PnE3ua850v55WCoMvBMpcSqlf3wW85o1AAQ/+SR+d9zeliUFUFBj4b2NeXyzuwRH62xaICrSrGq6aXXU3RjF711WGkrdSRSJeg0jDy1jgOYLfAe4Jank0lFY3Iuy0u4Y8GD6xAmkDh3gDlEptqugoKBwSaOIN4VfhaaaKvL37iJv7y6KsvbhcthpKwIiqFBrI9sEm6DyR2vQEN3Tn9ju3gRW7sT+2SOY8+00icc7JtjQhofjlZ7uFmytSQcADtHBxpKNLM5bzE8lP+GU3EuNAgKDwwa3JR48ueFJsuuzMWqMvD72dQaHDXYPLctQuht2fYThwHcIx9tcaU3Q+1oYcCdE9MdVU0PxPfdjy8pC0OkIf+HfeKent83YZZU28u5PeSw7UI7UOonXw8+DHuUuIl0CWanevJ2kp9HWDEC8QcfNYjkhB/6EX3w1ggpkWUVFaTcKi1NwOYz0j+3F+BumYDQZW0NVilgqKCgoXOoo4k3hf4LoclF25BB5e3eRv3cXtSVFHY+rPNC2JRtEIwh6TN46YvsGEpPshW95JtZV32J+ewM1tuOzWCq0YSEYJ07Cb8oUjCcINlmW2Vu1l0W5i1hRsKJDPbZkv2SmxE1hXPg4ov2jabQ3Mnv1bA7VHsJL68Vb498iNTgVbE2Q9TXs+qRjy6rgnggD74I+14PBBwB7Xj7Fs2bhLClB7etL5FtvYurfH1mW2ZRTw5trj7Etv30v3ejkIK6Q9TTvqWF3kokfe5kwawBJIsGoZ06YBwE7/oDKeweqRLcga6iJ51heb2w2b8J0AUy9ZToRydG/wLeloKCgoPBbRhFvCr8Y5rpaCvbtIX/vLgqzMnG0tNdSQxDQGSORpGj37Jo6CEEQ8A01Ep8aTEySCVPOTppXzsPy741UOhxtploPF97xAl4P/xf9sAzsdjsGgwFBEMhrzGNJ3hKW5C2h1FzaZhNsdNdjmxI/hW7+3ZBlGZvNRk1LDbNWzSKnIQc/vR/vTniXHnYb/PgQZH0DztYOCxoDcq8ZOFJuQZcwvEOPVOuuXRTPeQCpsRFtdDTR772LKiqaRfvKeHdDLgdK3cJRrRK4sm84tw+IIntRIYuxsGWqH1aDe6w4o45HY4LoWfUVZYfeQR3gvmZbUxjZuX1pbg7CKOvISL2CtOkjUP2sT6uCgoKCwuWBIt4ULhqSKFJ29DD5e3eTt3cnNUUFHY5rdB6otLHIxKDSxCCojIBMqVZm6PAIhg/0Q9y1HtuyT2l6ZguNTmebrTY6Cu/wZrx9jqIP9US4czGE9kaWZWpttazLX8eSvCUcrD3YZmPSmBgfM56p8VNPWY+twlLBgxsepLC5kCi9P59ETCX4m/ugPLP9pMBk97Jo3xvB6Idks8EJpTcalyyh/A9PIzudGPv2JeC115mfZ+H9r3+iqM4tVo1aNdf0C2P26ERcDU7+vvII67trsRrcCQyxRh2PxoQwXLWTowfuolKoRq0Hu9mTgsI0qmojEGSBPl6JTLx1Gp6hPhfnC1NQUFBQ6JIo4k3hgjDX11GQuZv8zN0UZu3FbrGccFTA4BWJJEWBKhZBHYIgCGgNaix+WlY2NlFPMy/FNBG1aj5Vf98GJ2SW6uLj8U6fhNfY0ej3/AUhbzvovWHm91gDEliTu4gleUvYVr6tQ1/RKyKuYGr8VEZHjcaoMZ4y7qKmImatm4VvfRH/apHIMB9Flf0P90G1DnpcCQPvgphh7WLthP1ksixT+8EHVL/0svvfEyazcOo9fPpeJnUW94yZn0nLHcPiuG1INODitT3lfG5pwtLNnQkapdXyeEIo4w355B27h2zzfhDA2aKlvHggRZXxyLKKEHxJHzWB2DE9lZptCgoKCgoXJt6O9yfr7Pmd3VR9PnaKr1/GThJFyo9lk5+5m4LM3VQV5HU4X6M3oTMl4HREoNLEgsqECvD00xPbJ5DYPoGsOJJDzvwfmVm6n751eQiSxHHJp01MxDt9Et6TJqFPTATRCQtmIuStw6H1YNukZ1iSO5+169dic7VnVfYO7M3U+KlMjJl4Ul/Rn5NXfYDvvr+Fl2vL6X3CcqzsnwAD7oC+N4FH4Ik3ocO9kJxOqp57job5X1Np9GPZtNn8KIfQss59LyL9jNwzPI7rB0YhqwU+La7m1dwKGtWAQUWQA57sHs5U/yaK8//MvpqVAIhOgcqCbhRUpSKKWgyyliuCUhly61g0PobTXs+Zvq9z5bf+LF6qvrpCjIqvyyPGruJLwc0FiTe73d7psgR2u/28Zg/Ox07xdXHs6qsqqTx6mKL9eyk5uB+71dLhuMk3EoQYXK4oBHUoEirUOgiI9CA6xY/oFH+81c20rF1HwdNLueLoIUbQ/hLqunfHNH4cHuPGIYaGYjAYkAGb1Yxm4X0cLlzD4sBAlvsFU5/1eptdlGcUk6InMSZ0DEmB7X1FT/dMCpUHaN7xOqHZi3hCam0Mr9IgJk9BTL0NKfqK9lm204zRUl9P1V+f5eD+XL4ZcDMbovohOgRApHuIJ/dcEc2kXsE4ZfiotJK3S+qoFUVQg69Z5Ba1kfuGelBZ9gp7cr8BRGQJqgvCKawcis1pQpChlxDN0NFX4D84CpcArk68Z5fqs3ip+jpfO8VX1/J1vnaKr442AGlpaajVaubMmcOcOXM6NcalwgWJN71e36kq7seVtl6v79SXdj52iq/ztxNdLsqPHWldDt1FdWF+h+Nagwcmn0Ts9ghkOQpJ8Gj9XEVEN19iewcQmuyJl7MJ86pVNP9xFaX79wPg3TpGfXQSyddfidfEieiiotpitNls6PV6CpsKWLJsDkut+RSHh7qNXGb8DH5kxGYwOW4yvQN7A7TZnPK6HGY48B3s/gShbA/Hn9ZyvQmPgffjOWQWas9gTtGd9OShKitZ98RzzNV3Z/fYGW2fX5EYwOyR8QxPDKRFkvmsrJa3iqqodrqXgH3NIqOO2XlsTDhan4Uc3P8BoujeD9dQ7EtByVCane6ZvhDJhzHRg0m4rj9OrdSWiHGuXGrP4qXuqyvEqPi6PGLsCr6Oi7edO3fi7e19lrMvbS5IvAmC0GnlfNzmf2Gn+Dp3u+a6Ggoy95Cf6a679vPZNa/AaNS6OKzmcARVCHaHCgQweWuJSQkgrk8QkT38kMuKaFqxmKZXVlKTnd1mLwsCh/1j2BjWh8CMSfzprjEnxVHTUsOiY4tYWbyyPfFAq8Wo0jImZgJT46cyJHwIWpW2fVxZPvV1lWXCnk9h/wJwuOumOYHVHib2RfVjzoy5aGQdwjmII5cosWh1Jm8t2sux6CmAu1H8lD7hzB4ZT0qED1ZR4r2SGt4oqqLmuGiziAw/2MIou8CAqw5T1fgojnp3ey9rrQf5R/pQ50oEwCBrGaLqTto1I/DoG4wsy7hsNuUduwx8dYUYFV+XR4y/dV+djetSRklYuEwRXU5Ksw9TsM+dbPDzzFCdyROvwG64nBHYrOE4RRPOFlCpwT/cg9je7v1rwbFeOI8eoXnVXIqfWYkjJ7d9EJUKU1oajYNGcF+BJ2VqTyb3DuXpm/q3vYRmh5k1RWtYmr+UbeXb2hrBq2WZIS02pva8mbHD/oBJ27G11CmxN7vLe+z+pEPGaIt3GO9qHHzvaaB71AheGfMKBrXhrEv+VoeLr3cW88GabEqsEniGopecXNcnhNmT+xLlb8IiirxdVMWbJ4i2IJfA4D3N9Cmw0+2KPLwSvqa82r0fTnb4kLM7kkp7X2SVGkGGHmIkw7sPImRGd9SeurNfp4KCgoLCZY0i3i4jmqqrOJJ9kIJ9eyg6sA+nraX9oCDgFxqH1hSPpSkUlzMQS7O7jphKIxCR5NuWcOAdoMeWlUXTd9+Rv2o1zqITCu5qtXgMGYxh9Bj80idRKOqY+c5WGtROhicG8t8bUhFlJz8VbWJJ3hJ+KvkJu9jeOipF68fUilzSzVYCpr0O/W4980XJMkL5Xjgwr2NdNpUWekxjV2QKs459jlPWMiZqDC+OehGdWnfGja81ZjufbSngs22FNFjd5Uq87WauseVx1xO3EhkXiVWSeKtVtNW2irZInZaR2TZidzXiGZBD/DWLEVUHaWkBtcqbsgOR5Jb3QNSaQOVeIh2u60Xi9f0x9go8bTwKCgoKCgonooi3Sxinw07JoQMUZO6mYN8e6spKOhw3ePngG9odSY6iuTaIFpuRltbJKIOnhpiUAGJ7BxIcb8LLy0DLnr00v/sZVatW4aqsbBtH0OvxGDEc74kT8Rw9GpWXFzabjUqbzG3vbaXB6qRPlDezJsr8c8ffWVW4qkPHg1jvWKbET2FydRnRm151fzj5xTMLN1sj7P8a9nyKoSKr/fOAxLaM0R8rtvDM5meQZImMuAyeG/5chyXXn5NfY+GD1p6j9taeo6GWGq459hNX9fAj7r/PUe8SebOoireLq9tEW7RBxx1GL7RzC0EqImT493iE7UEEVCoDWIeydYMeuyEItGCUdQxyJtKnbx/8piWgMp0+JgUFBQUFhZ+jiLdLCFmWqSstoWDfHgr27abk0AFczvZSGIJKRWBUEgavBKzmcMwNXjTUtO8h8As1tc2uhcb7ILicmLdupeE/K6hcvx6xvr29k8pkwnP0KLwmTsRzxAhUHh4d47A4uO3TPVTacwmJPYjZ/wBz1lW1nRNsDCYjLoPJ8ZPp4d8DYeub0Crc5Al/Rxh076kuEIq3w+5P4eD34GpBAGS1HnpORxhwR1tdtvnZ8/nHdnfdtmuSruGZIc+cVKT3OLsL63l/Qx4rDlVwfEKuh2Dmqu3fMawsi6C778TjkUd4q6yOt4uqqHO5a8rFGHQ8EhNC9yNWdn69G7+eC/GN34QgSICKQP9p7FipodRsAIMKQRboJUYy0NSNkJt7Yuzm35mvV0FBQUFBAVDEW5fHbrVQlLXP3YZq326aa6o7HPf0D8Q/oieyEE1DlR/NTVqaWye91BqB8CTf1v1rAfgEmZCsVswbN1H+zirM69cjmc1tY6l9fPAcNw6vCePxGDYMlV5/ypiya/K499sPqPPajkdgNVbA2gJeWi8mxE5gctxkBoYMbBdTOz+AlX8CwDn8STTDHuw4oLUO9s1zJyBUtydBENQDuf9MbN2mY/ALbyvz8enBT3lx14sA3NLjFp5Ke+qkja6SJLMmu5pPtpWwq7BdlI5J9OeqXQtJXL8QQaXC869/Yf6wMbyzPZs6p1u0xRp0PBIbwnR/H7Z8vY+jDZ8Rl7ESlcYtlAMDx9FYMZQfv8lB1GhBBaGSL8Oc3YhKS8Rnchwqg/LqKSgoKCicH8p/QboYsiRRlZ9LefYBCvbtoexoNnJrzTIAtUZDSHwPjL5J2Kxh1JbqqCppFy4GT23bcmh0T390Rg1iYyPm9asoXrUKy8ZNyPb2PWjqwEBMY8fgm56OR1oagvbUS3zV1mqWFyxnce4SDtUdBCOoAZ1Kx+io0UyOn8yIiBHo1D/bkJ/5FSx53H1twx/DNexR90MpSVCw0S3YDi8CsXUGUWuCXlfDgNshMs39WWvigSzLvLPvHd7a9xYA9/a+lwf7PdhBuNmcIt/vLeX9jXnkVbv3x2nVAjNSI7izpy+GPz+K/fBhrL5+rHr+JT7VelKfVw64e4/OCffnhohgrPVmVn35T/Sh3xIY4c5m9fbuS1DgfSxesJcaSyFotJhkHYOdSSR6ReF/WzeMSX7n/mUrKCgoKCicAkW8dQHM9XUU7t9Lwb49FO7fS0tzU4fjvqHhBEb3QlDFUF/lS121BCdMwAVEeBLTO4CwZC+iugWiVqtwVlVh/mEBFatWYdmxs0NbKm1UFF4TJuA1YTyGPn2wOxynrDfWaG9kdeFqluUvY0fFDmSOdyJQQUsivxt4Hbf3nYqnzvPUF3bgW1jYWmBx8O9g7DNQWwy7v4U9n0H9CfXlQnu797L1vg4MJ/T2lNu7H/x3z3/55OAnADzU7yHu7dO+9FpvcfDFtkI+3VpAjdktBL30Gm4ZEs2dV8ThU1FE8ew7qW1o5Ptrb+Gb8VNpkgGXSIJRz6OxIUwP8sVpb+HY/q8pKnkVj1j3MrBWHU1i8uNk7hJZumgzsiAgyAIpYhT9XHH4DY1CPzoUg3f70rKCgoKCgsL5ooi33yAup5OyI4da967tOUWRXCMR3Xpj8kvEZg2nqhBKjh2ffZNQa1REdvcjtncAMb0D8fI3IMsyzUePUv/xj5hXr6ElM7PDmPqkJLdgmzgBfbdubULt51mZVqeVn0p+Ymn+UjaVbsIltYs+P1US5WU9ECx9ee/G4YzqEXb6ujzZS+G7WSBL0O82SBgDX9+K4chyhNY+pei8oM910H8mhPc77f2SZInntj/H10e/BuCptKe4tac72aGo1sqHm/L4elcJLa3LnuE+Bu4aHsf03kEE+nhi3baNA0/+gQWDRvDt+CmYDUaQIcmk59HYUKYH+6IWBGprN5O19++IqmNoPUBy+BAb+xAueSBffroIi80OgkC46MdQVzeCAgLxuyYJXax3pzuRKCgoKCgonA5FvP0GkGWZ+vLSNrFWfCgL1wlLlwDBcYkExfRC0ERTV+5FRZENigDcos3DV09M7wBiUwKI7O6PVq9GlmXs2dlUf7Ga5tWrsR892mFMY9++eE0Yj9f48ehiY08bn1N0sr1kO0vzl7K+eD0trvYSI0l+SUyOm0xhUTKfb2xGJcBbt/RncJzv6S84Zw0suB0kFwT3hNw1sPdzjss8OWowQv/bodcM0J15tsolufjbjr+xtHApAgJ/HfpXrkm+hr1F9XywMZ9lB8qRWvVnzzBvZo+KZ3LvMDQqAZvNRsHCRby5dS/fPf1PrEZ3Lblkk4HHYkOY1irampsPc+zYv6lv2AgqEJ16BMs19Bx8N2tW/0Re/jcAmCQdQ13JxMrBeI2IxHt8DCqdWunHp6CgoKBwUVEa0/9KvmwWM0UH9pG3ZxclB/fTVFPV4bjJx5eoXqmY/JKwt4RSdsxB7j7ncWsQICTWu02wBUR6IggCsijSsncPtavXYF69GmdpafugajWmtDS8JkzAc9xYtCEhHa7hRERJZHfVbpblLXOX9nC2L9VGeEaQEZdBRmwGSX5JvLchj883uhMJnr+qNxN7hmCz2U59P3LXwVc3IEhOZECoOuT2b/SHPjdi63U9+si+7T1Gz3BPnaKTpzc9zcrClagFNX8b9g/09oFc+84WdhW0JyGMSg7i3hFxDEsIaJsJrLY5+O/ClczzCaYlfToAPUx6HosNZXKQDypBoKWlhLz8/1JZ+SMgI0tqGvJGEh1zH41e9Xz44WdIkoQgQx8xllRXLMZgT/yuSUYX7dV2X3/rz+/52im+Lo8YFV+XR4xdxZeCG6Ux/f/IlySKVOXnUJS1j+KD+6jKPdbhQVRpNIQl9yAwugeCOob6CiNFR8y4Gw60bqw3qIno5ktokgdxfYMxerqTByS7nfrVq7GuW491/XqkE0p6CAYDxqFDMY0ejWrwIEytgk0ExJ99d7Isk1WbxariVawuXk2trbbtWIAhgAlRE5gYPZFe/r3arnXutnz+ucwt3B4fn8D03kHY7faT7odQfRjNlldQZy9sm2ETADF2FGKfmxGT0kGjdz9PP5t1POX9Fu38Ycsf2Fy+GbVsIN3vWV7+3kRB7W73vVIJTOkdwp1Do0kO8Wz7jqodLt4vreGL0hpaQmIA6GZp4pG+3ZgY4IVKELCYKygpfZ+KirnIslswNxWl0Zh3NeFpwWw88BPNze4khXCXL1eIPfDGhGlEGMaRYUga1UnvxW/9+T1fO8XXr2en+Opavs7XTvHV0QaUxvSgNKb/RX01VlW4Ew3276X4wP6T+oX6h0cS1j0Fn8DuWC1BlGZbOLLdhltauUt0+IWaiEkJIKZ3AKEJPqhal/u0TieW1asxr1mDZcNGJKu1bVyVjzeeo0bjNX48HlcMQ2UyIcvyKRu4y7LM0fqjLMtfxvKC5ZRZytqOeeu8GR89nnER4xgaORSNuuPjsvJQJc8scgu3WSPjeWBct473AwfCwe/dS6Klu9p9qnUwdA70vx2VXywqQNuJe291Wvn9ht+zteQAUsMk5OYxzMsGsOJt0HDL4GhuHxZLiHf7s1lhd/JWcRWfl9Vik2TQaEkuzOMhbx1Xz5iMIAiIopXi4o8pLHoPUXTff0tlD6r2X4POMwYxqoAtu90zhUZRw3CxJ9FSIJpQE/7XdUMXfurEjN/689sVYrxUfXWFGBVfl0eMXcGX0pi+HaUx/UX05WhpoeRQFgX791K4fw8NFeUdzjF4eBLdO5Xg+BQQoqkqlCg4UI/olAH3LJdaqyIi2a+1nEcA3oHGNntnZSUNa9bSuGoltl27wNmeLKAJCcGrtQabaeDAU5b0OPG68hvzWZ6/nGUFy8hvbE+IMGqMjI0eS0ZsBsPCh6FRabDZbGjUmg73Y1teLQ/O3YsoyVw3IJKnM7q7j8sylOxAt/NjhOxFCM6OgpWg7gh3r+yYMdqJe9/saObORX9g37FwnI3TQHY/wpF+Ru4eHsf1A6Pw0Lc/1qU2B28UVfFVeS321s1vPfKPcfvqxUy941YCJoxHll2Uli0gP/91HA738rVsj6d423TMVcnok6rJb96IXCq7l0id0fST4lELKnwmxuI1KhJBrTplvOd6XRfL5n9tp/i6PGJUfF0eMf7WfXU2rksZJWHhApBEkYrcYxTsdycaVOQc7VBzTVCpCE/uTlSvVDz8kmiu96boYD1Fy6xATdt5nv56YlMCiekdQEQ3P7Q6d/FaWZax5+bSvHoNzWvWYNu/v4N/XUICXuPH4zV+HIaUlLM+2GWWMtbnrGd5wXKy69qL3epUOkZEjiAjLoORkSMxatoF46n2GBwobeTeT3fhcElM6BnCP6/ujWCphn1zYe8XCDVH2x8s31iw1oDDDOH9YeZCMHT+LyZZllmdXcgTP66goX5y2+d9I324fUgk01Kj0GraOygUtth5o6iKeeV1OFuvoU9hLrf9MJ9BteVEv/0OcnwcVVXLyct/CavVLWB12ghqDsygdF9vHKYa7JF7qG1yL4GGOjwYJffFSzaiCtUTdFMvtCFK+Q8FBQUFhf8tinjrJA2VFRTu30Ph/kyKDuw7aSnULyycmD79CI5LQZLCKD1q5cDmelz2ZsC9T0qlEghL9CG6VwChSZ6ExvqhUrlnbmRRxLpnD81r1mBevQZHYWGH8Y2pqRhGjsQ3fRKG+PizxltpqWRl4UqW5y9nf027+NMIGoaGDyUjLoMxUWNOX4vtZ+TXWLjj4x00210MjfXhzYFVaBbcBkeXu7NHAVlrQuw2FXX3DIQVf3YLt5AUuPXbTgs3pyixZH85b/90lCMVViASkBmW5Mmj4/owINoXu92OpnXmK89q59XCSr6prENs1Z1DBJEb33qZPvv3oE9MIHrePJqNRRw7cDNms7svqlbrj4/hTnbO647Z3ow16AAOdSM4wSipGO7oSQwhSIKEZ3o0PiOjEVTKX4EKCgoKCv97FPF2FmxmM0UH91G4fy+FWZk0VlZ0OK738CC6V1/CuvXEK7AHdWVqCg/Ukr3DQmstDwBM3jqiUwKI6RVAVE9/9EZN2z402W6nees2mteuwbxuPWJte6KAoNViGjoEr3Hj8RwzGk1QkHvv2hn2Gta21LKqcBXLC5azp3JPW/FclaBiYMhAMuIyGB89Hl+Db6fuRWWTjds+3I6npZAnfLdxnXkjqq9PuB8RA6H/bdDrKpxNtajnXgXNpRCYDLf9AKZz7+XZ2OJk7o4iPtlcQEXrzBeCA++AQ7xx9TWMjO8OtM8MHrHYeK2oih8q6zk+9znKz4t7C48Q8aenwOXCNGgQPv+ew4HKP1FXtxEAtdpEVNTd1B2ZyIa5xVg8j2ILdF+TRqWimyWQQUIv1KiQglX435CCR7ivMn2voKCgoPCroYi3nyG6nJRmH6TiyCEKszKpzM1BltuXQlVqNWFJ3Ynt04+guF7YLH4UHapn7+o6nLb2shyCACFx3sSkBBDdK4CgKK8OMzWu+nrM69fTuGoVLVu3Ibe0105TeXnhOXIkXuPH4TFiBGrP9lmx06VKN9gaWFO0huUFy9lRsQPphJj7BfcjPTadESEjiPSLPC/h0djYwGfvvsJLluUM1mfD8WRKUwD0udEt2oJ7uD9rrkQ/7zqE+gLwi3UvlXoGnZOfkvoWvtqVx9e7irE43EV11RoLar/NRIUX8MmUN4jyjmo7/5C5hZfyyllW18zxOzM+wJtHY4KJ/vRjat5yt8oyXDeG5uu15By+CQBB0BASfC3RkQ+wcW4Vh47uwRJYgKxyzx6G4cFIS2+8BA9EXJgmReI7Mg674+yZsAoKCgoKCr8kl714k2WZ2uJCCrP2UZi1l5JDB3DaO5Z58A+PJKZPP6J69UVniqbsmJWCA3XsXlXNiX2oDJ5aYnoFEJ3iT3SPAAyeHZMGHEVFNK9Zi3nNGqx79rj7d7aiCQ3Fa+xYvMaPcycc6H7WA/QUNDmaWFu0luUFy9leth2X3J7AkBKQQnpcOpNiJxHqEdo2y9fJmwMlOxF2fILuwHc8IbeACmRBhZA4HlJvgW6TQXNCrNY6+OIqVHU5yN4RCDN/BO/ws7raXVjPBxvzWHGwoq2oblyQHrPpR1oMG4j1jeSDiR8Q6hEKwN4mK68UVrCipr3+3ORAHx6JDaG3XkP5M3+hZuFCRC8Z1xM9KA9ai1ztLvsREjyVuLhHaK7xYf5/t1HuPIjo7V7+9vf0pk9VEImqWBDA7ucg+t5haP2NSo0hBQUFBYXfBJeleDPX1VKYlUlhViZFWZlYGuo7HDd6+xDTO5WYPv0IjO5BXZlA0cFa1n9Vh8PWvtH/eKHc6J7+hCZ5EpkUiOqErENZkrAdOOAWbGvXYD+W08GPvls3DCNH4jdpEoZePc9pRszsMLOqcBVrStewpWxLh/ZU3fy6uQVbzKQOs1OdprkS9s+DvV8i1Bzh+AJtESEYB91B0PA7Ti3IbE3wxTUIlQeRPYLcM25+Mad14xIlVhys5INNeewtamj7fERSIBmpOt459gg2ex1Jvom8P/F9Ao2B7Ggw89/CStbVufcPCsBkfy8ejw+jp5cJsbmZotlzMO/dinmajDVdhSTsBxn8/UeQkPB7vL1SOLi9gMUL59OiqwQt6HV6eqiCSa2OQ6PS4pTtGMaGED/x7IkgCgoKCgoK/0suC/Fmt1opOZzVKtb2UVtS1OG4RqcnskcvonunEtmjNxaLB5U5FrI21FFXdqTDuQZPLdE9/YnuFUB0L3+Mnrq2WS1BJSDZbFi2bsW8dh3N69chVrdnlbZ1OBg7Bs+xY9FGRGCz2U7Z9P1ELE4LPxX/xIqCFWwq3YRDcrQdS/RNZFLsJCbFTiLOJ+78b5LohKMrYO8XcGwltPYXdQh6FrkG8T1jefTu2xkQG3Bqe4cFvroeyvYgG/2x3/A1+oDEU57abHMyf2cxH28uoLTBvVysU6uY0S+cWwaGg6mM3635Hc2OZnoG9OSdce9w0Kbh5ewctjS466+pBbg6xI8Ho4KJUoPBYMBZXk7R7+6lLuwo5r9JSJ7umTIvr94kJjyJv/8wnA4n8z5YxJGiTGSd+xq7RyTSM9cTfwJAgCZTPfG/G4MhyOv876eCgoKCgsIvxCUp3kSXk7KjR8jL3EXZ4YOU5xzpUMIDQSAkLpGYPqnE9O6HZ0AMZcfMFB6oZe/qMpx28YRzW2fXWsVacIw3qp9lGbpqa2levZqajZuwbNnScf+ahwceI0bgNW4sniNHovZpr292pmU4q9PKhtINrCxYyYaSDdjF9r1WMV4xpMelkx6bTqLfqQXSOVN5CDK/hP3zwdK+BCxHDmKxehxPH0nApvLgvdsGnF64OW0w72Yo2gp6b7j1O2T/7iedVlxn5ZMtBczfWYzZ7p4x9PfQceuQGG4bEkOgp44txVt4bNVjWF1W+galckP//zDzUA07m1q7TAgCN4T680BMMLFGfZtwbjl0gCPv3EnjLfWIrWGaTHHExz9GcFAGgiBw6EA2C79fjF00gwq89f5c4RFHeI4PgiBgEy0IQzzoec2VF3ZPFRQUFBR+dTZs2MB//vMfdu/eTXl5Od9//z0zZsw47fnl5eU8/vjj7N69m2PHjvHQQw/xyiuv/M/i7QyXhHiTJYnqogKKDuyjKCuTksMHT9q35hsa5l4K7d2PsKSe1JaLFB2sZeOCOhoqd3c41+CpJbqXvzvZ4BR712RZxpGbS/PadZjXraMlM7NDD073/rUxeI4dh2lQGqpz2L8GbsG2sXQjKwpWsLFkIzax/RpivGOYFDuJiTETiTJEYTQaz385r6Uesr5xi7ayve2fe4ZA3xsh9RbeOqDmPyvcs44vTO/BmO7Bpx5LdMKCOyBvPWg94JZvIDwVWvfXybLM7sJ6PtyU32E/W2KwJ/cMj2NGvwgMWnd9ts2lm3l4w8PYRAcxYTdR7nsV9x52Z37qVQK3hAVwf3QwkYb2+ynLMhVb3qKo8h1cV7kFuk4TSPz/s3fWYVZW2x//vKenu3vozqG7QVFMUEn7iu39WVevXm9Z10QMBBQwMBELJWboGLqb6e48vX9/HObAIacYGNif55lH5p13vWvtfc6c+br3Xmu1eIKwsFtRqTQUFhby80+/kZJ2DACVXUuPqG60SdFgKHUDBXJV6bScORSfqLD6zalEIpFIrigqKyvp0qULM2bM4JZbbrno/SaTiaCgIP72t7/x9ttvN0GE9afZirfSvBxS9+xyCLa9u6guK3X5uZu3DxFtOxDXtQfRHbtgt3uRtq+Qg5uLWLloJzbL6cV0FULjvYluH0BUez+8grS4ubuKI2GxULVtOxWJiZQnJmJJc9161bVti9fwYXgPH46+XbtaC6tqazVrUtbwR+rZgi3KK8q5JdrGrw2KotQv8QDAbkN1PBH2fwsHf4WalTyVBlqPgW6ToeVIUGv4YnMqb/yxF4C/X9+e8Z1Dz/1MmxW+vxcO/w4aA9z5NUT3BiGw2Ows35XF3HUn2JVx6rUZ2CqQuwfEMaR1kMscJaYl8uTq/6PC0B0C7mCb4geVJtzVKqaFB/BgVDAhelcRXVySzKHNz1CpTYVQUJnUxMY/THTL+1Cr3TCZTKxbt5r169djt9tBKPjaohkT0hJPh46jylpGZTsz3WZMRKVSI5FIJJKrg7FjxzJ27Nha3x8bG8u7774LwLx58y5VWI1Cg8RbTX+yut5f16w9IQSVpSWkbDtE2r7dpO/dRWlerss9Gr2eyHYdienUleiOXfAMCCdlXwG5R8vZsfIYFUWuJR48/PSOs2vt/Yls64feXev0ZTQaEUJgKy2lct06KhKTqFi7FnvZqcxGRavFvU8fPIcOxWPwIGx+fi5n1y62Jboucx1/pjq2RE8XbJGekYyKGcWo2FG083cVgafPX63nsOCIo/PBrq/Rl5/qWypCOjiyRTvdDh6Bzuu/7c7ihSUO4fbw0JZM7xfjnA8XhB2WzkTZvwSh0sLtCyF2IKVVZr7aksbnG1LIKXPMuU6jYkLXcO7uH0eb0FPnyGqe+fPx3/nrzmVUhvwLm9YhFL3VKu6ODOTeiCACdBqX+8srDnDs2JsUFa0GLShm8EtvTbs7P0fvHoQQgj179vDnn386G8hrTX508ehIR7sazcmKLqnmA8RM70erTh1cnn8+GvL+bcrflasxxqvVV3OIUfq6NmJsLr4Ayk77WwyOPut6vb5Oz2ruNEi8mUymOq8CmUymWq1KmauryDp0gIz9e8g8sJfCdNdOAyq1muD4lkS270Rk+84Ex7WkOMdE5sES1iwuJC81hdNKnaFSK4S28CaynS8RbXzxDT21siawYTQ6zrlZUtMoW7USy4aNGHfsANup828qX1/cBw3EbdAg3Pr2ReXuDoAdMBmNFxxXlaWK9dnrWZmxkvXZ613OsEV4RDA8ajjDI4fT1q+t8zk1TXjrPIemMtQHlqLe8zXqrFMN4e0GX+ztb8baaRIipJOjGB04tzg3Hi/i8cW7EAIm9gjnoYFRmEyms/0JgXb5s2h2fY1Q1Jhv+Ihj7j1Y+P0uluzKpvrkqmaAh5Y7EiKZ1DOCAA/dSVen3i9Gu50XDqznx2I9dv+7AfBVq7g33J8pIb54a9Rgt2I0Wk/appGW/gEFBb86HmAD9/UqQjwnEvrQ8whFITU1lRUrVpCRkeF4zawGfCviGRYQhq8j14FySxFZgRl0mHojPv4BdXoP1/b92xh2TemrvnbS1+Wzk76al6/62klfrjYAUVGu1RReeuklXn755To9q7nTIPGm1+sxXKDS/5nUKG29Xn/Wi2Y1m8k6fIC0vbtI37ebnGNHXJMMgMDoWGI6dSWqYxci27bHYlKTfqCIo1uLSFq4C2OlxeV+7yCDo+5ahwDCW/mi1Z+9LSasVqq376AiKZGKpNWYT5xw+bmuZUs8hw7Bc+hQ3Dp3RlGf4xnnGVelpZI1GWv4M/VP1meuP2uFbWTMSAaHDaZraFdne6x6z6HdBifWwK4v4cDPKNaTZ84UFbQciehyB8boIRg8fdCf4xdmd0YJjyzeg8UmGNsxlH/f3AW1SjnbnxCw/EWUHZ9jFwob+n7CvB3RrDq0yfmstqFeTO4VwS09ojHozn6LVVhtfJ5VyDsp6VTYg0ED7hj5a3wst/l7EuDh7jI2kymPlJRZZGV/gzhZy84tWYXX71oi/vIShvHjsdvtJCUlsW3bNoQQKEKFW0UUbWwxdPVQo64Eu7BzpGI7ITd3YsiQBzGZTOd8L9Z57i+BXVP6ag4xXq2+mkOM0te1EWNz8FUj3tLT0/H2PtVq8VpbdYMGijdFUeqsnGts7DYbucePkLZ3N+n7dpF56AA2i6v48g0JI7pjF6I6dCaoZWu8fQPJPlZK+v4ikn/dS2Gma19RnUFNZFt/otr7E9XeD52Hcs4yHLbSUirWrKUi6eztUDQaDD164D18GF5Dh6KLql29tJpxVVoqScpIYnnKctZnua6wRXlFuWyJgmMlSqVS1Wkea3wpiuLYFt35Jez6Gk7bFiWwDXS7C6XzRPAKBSFQTq4OnunraF4FMz7bSqXZRv+WAbwzqauzV+hZ/pL+i3HDxyy1DWaexz0cTNQA+SgKDG8bzN394+gT74/JZMKg07j4KrZY+TQjn7kZBZRYbYAGlTWfoR75fNprIga1ylFy5aQvi6WU1LRPSE//DLvdIUbdTnji+ZURfZEnEe+8jVv//mzatIm1a9c6V9AMpiD8yuLo5eVJkFYBG5SY8zim28ugF+7FLyzCIfBOH1d95r4OXOm+mkOMV6uv5hCj9HVtxHil+6q519vb20W8XYs0WcKCsNvJSz3B8Z3byD60n8yD+zCfVlIDwMPPn+gOnYnu2IXojl3wCgyiKKuStP2FrP0yk5zjB10SDVAgONqLqJN110LivFGfFB1CnDrYL4QjO7QiKYnypCSqd+x02Q5V+/nhOWgQnkOH4t6/HxaN5qK1106nzFzG8pTlJGUlsSFrAxb7KREa7RXNqNhRjIoZRVv/ti7PrOt+vxNjKez9yrHKlpF86rrBBzre6jjLFtH91LboBcgurWbq3M0UVZrpFOHDx1N6otec++B+3or3WZR4jC9s71GID5SCu07NbT0imd4/jrhAj3OOK9dk4aP0PD7PKqTK5nj91JYs3Mt+ZmZ8Bx7rNhNFUZx2NlsVGRkLSE37BKvVIay9tG1x+6QQTXIpmqAQohZ9RI67O79/8gm5uY7zj54GX9SZ0bRS/OjopUaDgk3Y2F+yAY8BYVx/x/OoNa5JDxKJRCKRNDcumXgTQlCUmX5yG3QP6fv3YKwod7nH4OlFVIdORHfoQlTHzviHR1JdbiHjYBHJvxaQduAwVaVmFxsPX71DrJ1MNHDzPHcZDrvZTPXGjZRu2EBF0mosJ89A1aBv1RLPIUMd26FdTm2HCiGw1OIMVLGxmMT0RP5M/ZPN2ZtdOh3E+cQxKmYUI2NG0tqvdZ3/L+ac2KxwbBXs+grDwV9Ralb0FDW0HAFd74DWY0Fb+23s4kozU+ZuIavUSHygB5/NSMBTf/ZbYl9WGYuW/cyv6dFYiAcgwteNqX1jmNQrGh+3cwuitGoTs9Pz+TqnCNPJGiFBqnKMeZ+hr0rm8e6Pcm+ne5332+1msnO+JjPzY8xmR805T482hBvHUvnYfERVNfpWLfH+3//4edcu9u3bBziWzINUrVGn+tLVTUOQ1iHgC4yZ7DVtYODMu4np3LXW8yKRSCSS5k9FRQVHj57qbHTixAl27tyJv78/0dHRPPfcc2RmZrJgwQLnPTt37nTa5ufns3PnTnQ6He3bt2/q8C9Io4k3IQQlOVmk79vjyAjdt5uq0hKXe7QGN8JatyWuS3eiO3YhKDoWm02QfayUw1uKSNufTEF6hWuAWhVhrXwJa+VFfOcQ/MM9ziuGLLm5VKxeTcXqNVRu3ICoOrWyp+h0uPfujeeQwXgOHoIuMqLOYyyoLmBl6kqWpy1na85WbOLU6l28dzyjYkcxOnY0LXxbNI5gA8jd59gW3fMtVORS81QR3B6l652ObFGvkDo/tspsZcZnyRzNqyDU28CCe3oR4Hnq3IDVZufP/bnMW3+CrSnFgGNVLcG3gruvG8TI9iEuW6unc7jSyLsnsvmpoIyaGerp7U6oMYlNR9/HADyT8AyT2092jEXYyMn9mePH38FoTAfAzRBNfPzj6NeZyHnpFbDZ0PXpQ+odk1j/zTdYrVYURaFDm86U7/IhrEpFOy8VakXBajezu3gNtpZqbv7LP3H39jlnnBKJRCK5etm6dStDhw51fv/kk08CMG3aND777DOys7NJO6PsV7du3Zz/3rZtG19++SUxMTGkpKQ0Scy1pUHirTQ/l7Ttmx0ra/t2U1FU6PpwrY7wtu2J7tCZqA6dCY5rgdliobLQRsbBYjYv3U3WkRKsljMSE6I8iWrnOLsW1sIHtUZ1zjZSwmbDuGcP5atXU7F6Nab9B1yeow4MxHPoULyGDsGjTx9ndmhdyKnMYUXqCpanLmdH3g4Ep7YE2/m3Y0TMCEZEjyBMH1anrdYLUpEPe79ziLac3aeuuwcgOt6Kqd3N6GN6QS2THM7EbLXz4KLt7EwvwcdNy4J7ehHp55ibkiozXyens3BjqrN1lRYr16s2MqOrF51ve/6827E7y6p4Py2X3/JLnbM02M+LR6ID+X3fGyw9/hMqFP7e9+/c2vpWhBAUFKzg2PG3qKw87PClDSQu7mHCw26n6IOPyZn9IQIomjCB5JBgSjduBCAmJoZ2kQkc/7mAnjoFPzfHXORUp7CzZBU977yVLqPGNZ6IlkgkEkmzYsiQIRc8nvTZZ5+dda3ex5mamAaJt4VPP4JBe2rLTK3RENaqLVEdOhHVoTNhrdqi0WqpLDGRfrCIfesOk36giOpy18QEdx8d0e38iWznT1Q7f9y9XbdCT59MW2kpFevWUblmDRVr1mIrPq2pvKJg6NwJz8GD8Rw0GBEfV69OBOnl6aw9upYVqSvYW7jX5WedAzs7BFvMCKK8opzx1atw7ulYjHB4maMm25Hlzt6iqLTQZgx0ueNkEV0twmis1Xm2c2G3C/767S7WHM7HTatm3vQEWod4cTi3nPnrU/hxRwbGmlIfBrjDuoQp6j8J7jEBZfx/z/IrhGBjSSXvpeaSVHxqW3yknydPxoXR0UvH82ufZ1nKMtSKmn/2/yfjW4ynqGgDx47/j7KynQBoNN5ER99PUODtuGs9yXn+JUp/+okSHx/2jr+eTKsVSkvx9vZmxIiRlO7TUfFrNgPcVKgUBbPNyM6iVZT7lTHhny8RGB1br/mRSCQSieRKp0HiTaVWE966HVEdOhPVoRPhrdui1RswG61kHS5h448nSD9QTHG2a1aoRqcivJWf49xaOz/8w86/FSqEwHj4MKUrV5G7fr2jFdXptdc8PfEYMOCkYBuIJiDglF0tBZUQgqMlR1mRtoIVqSs4XHzY+TMFhe4h3RkR7RBsoR7n6TZQH4RAlZEMB3+AfT84EhFqCO8OXe+EjreAu7+LTf3dCV75ZT9Ld2WhUSl8cFc3SqrMTP50M+uOFjjvaxfmzYxWVdywdQYGTSXWDrfC9W+5CDchBMsLy3gvNZetZVWAo1n8TcF+PBwdTIwaVFoVTyU9RWJ6IhqVhtcHvU4vv2B27JhKUfF6AFQqN6KjphMdfT8ajRdV+fmkP/0gxdu3s7dnD461bImwWlGr1fTv35/uXXqxZc4BogqL8TI4zilmVB5mW+Fy2o0cyvi7pqPVXXtp4xKJRCK5dmiQeLt31jyCQkKx2ezkpZSzc0U26QeKyD1eht1+msg4mRUa2daPkBaeRLcNQqM7fysie2UllZs2UbF6DRVr1mDNyXH5ua5lC4dYGzwY927dULR1zyC0Czv7CvaxIm0FK9NWklp2qgiwWlHTK7QXI2JGMCx6GIFugRd4Uj0oOg67v3F0PSg+ra6cdyR0mQidJ0FQ68b1CXy0NoXPNzrGOb5LOP/4eT+phQ7hpVJgZPsQZvSPo7fqIMqiaWCvRrQbj2XcO6gVx7ak1S5Yml/C+6m5HKh0iGO9SuGOsAD+EhVEzMlm8SUVJTy79lk2ZG9Ap9LxVr+n8Cv9nq3HlgOgKFoiIu4gNnYmep1jfs1ZWWTe/wAHgb3XX4f5ZE/Ydu3aMWrUKEwFsP+NHbQTAkXtaCS/rWA5Beosxjz5BC169m70OZNIJBKJ5EqjQeLt8OYitmTkkXm4GIvR5vIz70CDYxu0rSMr1OChda6GqbWuZ7WEEJhPpFCxZjWVa9ZQlbwVcVrNN0Wvx9ArAe8hQ/EcPLheyQYAVruV7bnbWZm2kpVpK8mtOtViS6fS0S+iH8Ojh9MnsA8hPiGNe16qqgj2/Qi7F0P6ZgAUQGjdof2NKF3ugNiB9T7HdjG+3JzGe4kOoahTq/hxh6NHlLdBw6Re0UzpE0OUvztkbIMFE8Fa7dimvWUuWOwYbXa+yS1mdloeqUZHBrCnWsW0iEAeiAwi+LS+o5WWSh5b+xg78ncQodfxbMsOWFP/Tj4CUBEWOoG4uMdwc4t02hgPHmTr08+Q3KIFpX6+AAQFBTF27Fji4+M5vOQobMgiWqWAonCifA87i1YR1qEtE+/5HwGhsqG8RCKRSK4NGiTeNi45hpvOkYWo99AQ2cafqHZ+RLb1wyfowskB9qoqKjdvpnLtWirWrD2rlIc2Kurk6tog3Hr2xAz1Sggw2Uxsyt7EyrSVJKUnUWIqcf7MXePO4MjBDI8ZzoCIAXhoPRrn/FoNVjMc+RN2fw2H/wDbybInigriBiM6T8QYNxKDd0C9z7BdDLtd8L8/D/FB0jHnNbPNTstgT6b3i+Xm7hG413RByNkLi24Gc7lDSE5cSLlQMzcrn/k5JeSZHeVQ/LVq7o8MYnpEIL5a17dQqamUv6z4C2nFu7gjAHq7l2Mrc2yRBgeNJT7+cTw8WrrYZC5fwbJvvyG9uyPLx6DXM3TYMHr27Im90sr+15LxLjaCSqHSWsbWgmXkmdMZeNc0uo+9AZPZtZyMRCKRSCRXMw0SbxFtfGnTNZqodv4ERnqiqM4vQIQQmE6coHTVKvI2bKR661bEaX90Fa0Wt549nMkGurhYp1ATQjj7b9aGcnM5azLWsPzEcjbmbKTKWuX8ma/elyFRQxgePZy+4X3Rqxv5fJQQkL7FscK27weoPi2hIrgDdJkEnW4D7zDHvY0lFM+g3Gjhu20ZfLz6ODllp3wMaxvE3f3j6d8ywFUI5x+GhRPAWAKRCeTfspC56SXMzyyg1OpYVY3Qa/lLdDB3hgXgfo4yIUXGIh5bfg9xtv1MDbOiPfn4gIDBxMc/ibdXR5f7zWYzKz/9lK3Z2djCw1GEoHPHjowaNw53d3dKNudQ8tNRvIXjPXCkbBt7itfgFRbCnY/+j5C4Fs0mM0gikUgkksaiQeJt7AOd8PE5VUPrzD+k9srKk6tr66hcuxZLZqar8/BwPAcOxGPQQDx690bl4eHy85rn1fRBu9Af6oLqAhLTE1mVtorNOa5Fc0PcQxgePZzh0cPpFtwNjerUsM98Zm18nYkQwnGO7dBPiD3foJx2jk14hkKnW6HzRAjtdLpRvX1dyOZYfgULNqby/bYMKs2ntrJj/N2ZPakj7SIDXEUxQHEKLLgRpTKftMjBfNjvbb7anobx5LnFFgYdD8cEc3OIHzqVytX2JDllJ/hsw11McsvDcFLX+fj0pEX8U/j6JrjYCCHYu3cvfyxZQqXdDmo1YTYb1993H36BgWhNCpkLdkNqGVqgzFLClvyfKTRl0WnYaIZMvRetweAyF3UVcZdi7purr+YQ49XqqznEKH1dGzE2F18SBw0SbyaTyWWLUQiB5fhxqtevp3r9Bow7dsDp/Uq1WnRdu+IxcCBu/fuhjYtzCgkzXHAVymQynbVlmlaexurM1SRlJrG3cK9LDbY47zj6h/RnRMwI2vm1c9pazVasWLkQ5/J1TqoKUB9cimbf97hlbTs1D1p3bK3HYetwG/aYAaA6mZxxjvHV2tcFbOxCsOZIIV9syWDdsSLndZUCdgEJMb58OrkrdqvZ2djXSXk2+i9u5JBNz6wur7LEty+2XEfJj84eBv4S4c8gNw3ubm7YzWbOHIHNVsWRtE/IzJpHL72jxIjW0ILo8EcJDh6Goigu75GcnBxWLF9OZpajD6t7ZSX9AgLo9sgjKIpCxaYsjCtzUNkEdmHnQOlm9hevR+thYPS9T9EioQ82wHbaM+szh/W1u1p91ddO+rp8dtJX8/JVXzvpy9UGICEhAbVazcyZM5k5c2adnnG10CDxptfr0ZrNVG7c6FhdW7/+rMxQbWQkHgMH4jlwIG69EjCrVHU+u1aj0LU6LQeKDrAqfRWJaYkcKz3mcl+nwE4MixrGsOhhxHrHnrOwb2196fX6c9tZquDQ745s0WMrUU6u8AlFBfFDHStsba9DrfPg/Pm0tfR1EZsyo5Vvt6azcFMaaUWOrWFFgf4tAjmQXUZhpZlOEd7Mm9ELD50ao1Fx9VWZz5afn2dW1F9YHtDP6WOQnyePRofQz9exEmo0Gs+K0W43kZm1mOMn3sdmLcZNBQU2LZ1av0CbyDscjelPm/uKigpWrlzpbD2itlppd/Agg2+5hcBJk7AWVFP0/REsKWWogEJzEcl5P1JqKSCyfSfGznwSr4Czs37rM4eNMfdXk6/mEOPV6qs5xCh9XRsxNgdfNeItOTlZNqZviHH6ffej2b/fpe6aotfj3quXYzt04AB0sa5n1xSjEUVRav2CWWwWknOSWX5iOWuy15BXlXcqeEVDz9CeDI8eztCooYR4nGoTJYRw+qmruj/LzmaFE6sdLaoO/Azm01p4hXdDdLoNY8vrMQRGN9xXLTiSX8nX246yZEcW1RbH3HsbNExMiOKGLuE89e0uCivNxAV6MH9GL7wMWpf5EMCKrCxm7dzElvhnHXEA1wf58nBMMF28TiWbnDmPdruFnJwfOXHifYwmx+pZgVVhqzmUJ4csJswzwsXGZrOxefNmVq9ejfnkGcfolFS6Hj5M6//+B48BgyhfnUHZilSwCqzCzp7iDRwp3YCiVjHgjmkk3HAzKtX5pXCjvc6XyKY5+GoOMV6tvppDjNLXtRHjle6rrnFdzTRIvBl37sRTrUbXogWeAwbgMXAg7j17oDLUvjn6uSg3l7Mucx2JaYmszVxLheWUWHLXuDMgYgDDoocxMHIg3rpLpL6FgKztsPtb2Ps9VJ4SjfjGQOfbHX1Fg1pf0sSDGiw2O8v357JgYwqbjp/aGm0T4sW0frFM6BaOgsJdn27icG4FwV56Ftzdi8DT+pVa7IKlOUXMTs3hULUF3Fugs1u4LdCdh1q1oIX7+V83IWzk5v7K8RPvUl3tqBVXZlOxrFRNgbYNH4+a61IPTwjBoUOH+PPPPykqcsTrX1ZGt81bCFEpRM35BLVvDHkf7MCS5SjinGsqIjnvWyqtJfiGhnHdI/9HaMvGr3cnkUgkEklzpkHiLfj55wgfNQptRP3qrp1OTmUOiemJJKYlkpyb7JJwEGAIYFD4IEbEjaBPWB90at0FntRACo+h2fElHFgCRadty7r5Q4ebHNuiUb0uWWmPM8kvN/H1ljS+2JzmzBpVKwojO4QwvV8sveP8URQFi83O/Qu2sj2tBG+DhoX39HbUbQMqbTa+yCrko7Q8sk6W+/C0VjIt7w/uGzyR0MgO5/UvhKCwcDkZmbOprDwCgKL24bcSO6tKrbT0a8+nIz/Gz+B3Kub8fH777TdnI18PnY6Om7cQc+gQ+hYtiJr9IVX7rVR8sQPsYLbb2VG8gZSTJUU6DB7OsBkPoHOrey9aiUQikUiudhok3nxvvhntadmmdUEIwcGigySlJ5GYnsiBItem8vE+8QyNGsrQ6KF0DOiI2WRuvMbvZ1KeA3t/gD3fomRtx1luVuMGbcc5VthaDgd13Ts51AchBDvSS1iwIYVf92RjsTkSMQI9dUxMiOKWLiHEhfg658JuFzz93W4SD+Vj0KqYNz2BNqFeFJitzM3I57PMAopPlvsIslVwf+oXTC1MxGfyVxB+buEmhKCwaDXHj79Nebmjv6tG443G/zqe27OcYnMVnYO68OGID52rn1VVVSQlJZGcnIwQArVaTTf/AKLnzEFrNOKekEDQ//2Xom+ysBY6hGi6sZhtud9gspegc3dn8NT76TRkuFwel0gkEonkPDRIvNUVs83MxpyNbMjdQFJ6kkuHAwWFrsFdHYItaiixPrHOn12S9ODqEsf5tT3fQspaEI5MSaGosccOQtVlIkq760Hv1fi+zxeS2cbPu7JYsCmFvZllzuvdon2Z1jeWsZ1C0alVZ2X4/vu3A/y4IxO1SmH2Xd0JCvHg2cMZfJ1d6Cz3EWfQ8UDOUibt/h8GjQam/Ajh3c4ZR1HRBo4ff4vSsh0AqFTuREfNIFfXmcfXPE+1tZqE0ATeH/Y+HloPbDYbW7duJTEx0Rlbq1at6F1QgOX99wHwum4C7n2mUfTlcQBMiiC5YDOZZasBiGjTnrEPP4XO69o+hCqRSCQSycW45OKt2FjM2sy1JKUnsT5zvUvBXDeNG33D+jI0eigDIwYS4BZwaYOxVMPhZbDnO0fnA9tplfmjejuK57a/EbPaC4PB0GRbo6mFlXyxOY1vtmZQWu0oraLTqLihSzhT+8bQOdLXee+ZQvaj1ceZu85RV+6RCe1ZbKvm503Z2E/+vIuXGw9HBTF23TNo9nyDUOvhjq8gus9ZcZSUbOX48bcpLtkEgEqlJyJiMqEh09hRepQnk57EbDfTP7w/bw99GzeNG0ePHmXZsmUUFDga2wcHBzN6xAh0n35KxdKfAfCb+jR20Y6qbfkApFgq2J79NRZbIYpKRd9b76D3hNtRVKrG624hkUgkEslVSqOLNyEEJ8pOkJSexOr01ezM34ld2J0/DzAEOLdDe4X2wqBpWHLDRbFZTmWKHvzVNVM0qK1DsHW6FfxiawZwyZMPAGx2QdKhPD5bf4J1xwqp0WSRfm5M7hPD7T2j8Pe48Nm+b5LTeXXZQewBeqITQni1sgQcZ/8Z6u/FzOhg+vt4oPzyGOz5BqHSwO2fQ/wQl+eUle3m+PG3KSxaA4Ci6IiImEhszEPodEH8dvQ3Xtj0Ala7laFRQ3lz8JuUFZfxwx8/cOSI4xycm5sbw4YNo2ubNmQ9/gQVGzaguPvjc9tLWEvdAAtWNw3rMraSW/YnIPAKCOb6x/+P8NbtAFmAUSKRSCSS2tAo4s1it7A9dzurM1azOn01aeVpLj9v49eGIVFDGBw5mHiPeNzd3C/tmSa7HdI2oN25GA79AtWnsjPxiYaONzsEW0jHJltdq6GwwsQ3WzP4YnMqGcXVgCOEIW2CmNo3hsGtg1FfoM1YDb/vy+GvG45g6RuE8NZxTNhQK3BDkC8zo4Pp6OXuEKJ/PA/bFyAUFZbrP0DbeozzGeXlBzh+4h0KClacjENNWNitxMU+jMEQDsAvx37hhY0vYBM2xsSO4cWeL7Jq+Sq2bNmC3W5HpVLRq1cvBg8ejKasjPQpUzEdOoy21TAMXSZiK1VApZDtbmf9/s+x2Rw9bNv2H8KIex9C7y6TEiQSiUQiqQsNEm/LTiwjuTSZ9ZnrXcp5aFQaeoX2cgq2cE+HEBCiEZu+n0lNaY+9P8DeH1DKs04NziPIkSna8dYmzRQ9FZpge1oJizal8uvubMw2x0qkj5uWm7uGMq1/PLGBnrV6VqXVxr/2Z/J5bgmisz8AbioVd4X7c39kENFup/VqTfwPbJrt+PcN72NreyNaoKLiMCdOvEde/u8nb1QRGnoDcbGP4u4e4zT//vD3/GPjPxAIboy7kfH68Xw460Oqqx2is1WrVowaNYqgoCCMhw6T8sAD2CoE7kOfRe0TB1ZQhbqzNn0fGceWAGY0OgMj759J+4FDGzCjEolEIpFcuzRIvP1j0z9QuzmKp/ob/BkYMZDBUYPpF94PD63HRawbidz9sPc7Ry224hTnZaH3xtZ6HOouE1HiBoG6SXMzAKgyW/lpZxYLN6ayP/tUAkKXSB8m94nh+s5hYLM4ztddhDyThbmZBcxLz6fcbgc3DTqb4LH4UGZEBeGvPWN8696GNa87/j3uTeh6F9XFBzl2/BNyc38GBKAQEnwdcXGP4uHRwsX8iwNf8OqWVwG4xfcWgvYE8ftJsRcYGMiYMWNo2bIlAJUbN5Lx6BNowvpj6HU9ikoDWhXmdt788udCLNX7HXbRrZjwf8/gExxaj9mUSCQSiUQCDRRvLX1bMqL1CAZHDaZTYCdUiqqx4rowBUccK2z7foD8g6eua92hzTjoeAu0GIbFKlA3YeJBDUdyy1m0KZUftmdSbnLUVdNrVIzvEs6UPjF0ifIFTq5E2iwXeBIcrTLyYVoe3+UWYzqZOapUWokvt/PrTd3wNZyjfMmWObDiZce/R/yD6k6jOX7gaXJylsDJVIagoNHExz2Gp2ebs8zn7Z3H29vextPiyTjzOGwnbOSTj5ubG0OHDqVHjx6o1Q7RXrJkCblvzsXQ83HUPo56f/pWvuwxZbPz5w8Q9jJAoef42xl4x52o1BdrGiaRSCQSieRCNEi8LRizAJ/T6rxd7MB5TT+zuh5MF0JAcSri6K+w/0eUnD2nfqbWQcsRji3R1qNB53HKl8VYL191jVEIgclq48+dmXyxJZ0tJ06dsYvxd+fO3tHc1iMSv5MJCDXPPp8vIQTJZVXMTsvjj8JTK3aGCiu2I6W0Rc23D/TFR685O86dX6L89lcAqgY+QEpALjmbRiCEo85bQMAw4uMew8urg0ssNf/+cNeHzN0xl84lnWlV3gqbsKFSqUhISGDw4MG4ubkBYLfbKZg9h4rVWbj3/yuKokLlrsFtZDQ//biYwtREQKBz9+fGvz5NVPuz/TXW3Nf3PSV9NZ8Yr1ZfzSFG6evaiLG5+JI4aJB4M5lMdT7DZjKZap2soJRloj74M+qDP+GWvcN5Xag02GMHYWt7I7ZWY8BwUkDacckUrYuv+saYWVLNN9uy+G57FkVVjlU0lQJD2wRyR89I+sb7oVIUwH7OuTrdl00I/iyqYE52ETsqHPcqwBAfdzK25pF+vJRoXwMf3NUOvers56kOLkW39GGMehXHu/cgR/UTItux8ufrO4CQ4HsJCOgJcJatEIL3dr7Hpm2bGF08Gr3dcXauRYsW9OvXj/DwcKedsFgo/M+niKp4dC3aA6Dr5E9JnMJ3H/0Ti9GRlBDaKoHrnpiJ3t2j1u+T+rxmTfE6X+2+6msnfV0+O+mrefmqr5305WoDkJCQgFqtZubMmcycObNOz7haaJB40+v1tTqvVUON0tbr9ed/0cqyYP9PsH8JSvrmU7aKCmIGOLZE241H5e6PCjhfz4Na+aqnnc0uSDyUx5eb00g6nO8s8xHspWdSQhSTekUR5uNWa182jZbFOcV8kpFPqtFRe06vKNwa6sfdoQH865s9pB8vJcBDx4K7exHmqT47vsN/YPpjJofj3cgM90AoJ0CAn19/4uMew9u7G0aj8Zzjsgs7//n1PxTvLqarpSsAQUFBjB49mvj4eBc7c14Jef/9GcWQgOIOitaK/+QubNq8hu3vLQBhRlH0JNw8lf63jm/0uW8MG+mr+cV4tfpqDjFKX9dGjM3BV414S05Oxtv72i7o3iDxpihKnZVzjY2LXXkO7F/qOMOWtvH0uyGmH6L9jRjjx2AIjK6Tv3P6aoBdbpmRxcnpfL0ljazSUytJ/VsGcHu3MMZ2iUSnqf2ZrjyThU8yCvgit5SSk+2r/DRqpkcEcndkIP4aDQ9/uZ2Nxwvx1Gv4/O5exAd5YjQaXeIzHf6JlOSHyerpjV3lWOXz9e1NfPwT+PkmAI5flnONKyc3hw+/+RClUMEbb9R6NWNGjKF79+6o1WqnHUB54lFKfz+BYohDCDv6WPCc2J1vXn2LgtRtABg8o7jl+efwCQ9q1LlvbBvpq/nFeLX6ag4xSl/XRoxXuq+6xnU10/QpmDXUCLb9SyB1A47sx5NE9XGU9mh/A3iHN1nh3HNhtwvWHS3gy81pLD+Qi+1k0oCfu5bbekZxR69oYgPcMRqNaNW1S9g4WFnNx+n5fJ9TjPnksl2sm44HooK5PdQPj5Oi6W9L9vL73hx0ahWfTOlBxwgflz1/kymf1H3/ILPoN+zhjvN0Pt49iG/xBP5+fS8YQ2VlJasSV7F121YUoWDHTmj7UGaMn+E811aDrchI/ne7sWSbUdRu2Csy8bu1Dfk+Kr56fCZWUwmgENlhNLc8+wBqrUZ2SpBIJBKJ5BLRtOKtPAf17u/hyK+QuhEXwRaZAO0nQIcJ4BPZpGGdi/xyE99tz+DrLemkFZ1q6dUzxo+7+kQztmMYBq1jla02hyiFEKwtruDD9DwSi8qd17t5GngoJoRxQb6oT/u/irdXHOHLzWkoCrwzqSv9WgY6f2Y2F5CesYDMjEXYhRlUCj4md+J7vodf4JAL/t+J1Wply5YtrFmzxnHmAIVs92zGjBnDTZ1vco3ZZqd8bSZlf54Au4KwmrHlriX4H9NYvzKR3St+BASKyod+kx6iz439az0fEolEIpFI6selF2+lmY4G8Pt/grSN6M4l2NrfCL5RlzyUiyGEYMOxAhZuTGHlwXwsNkesXgYNN3eL4I7e0bQNrds+u9luZ0leCR+l5bG/8lQSwrggHx6IDKKTXo3BYHARXAs2pvDeSkfbqX/e2JFxncIczzIXkJo6h4zMRdjtjmd5l1mIr4rB/5ZlKPrz19YTQnDo0CFWr15NcXExACW6EvYF7uP5Mc8zNNq1aK45vZziH45gya4EFKx5+8G6C88XH+Wrd9+mJMfRYN7g1ZGbnn2S8JbBdZoXiUQikUgk9ePSiLeSdDiw1CHYTks6UAB7eA+UjjehtJ9wRQg2gIIKE99vy+Dr5HROFFQ6r3eN8uXO3tFc3zkMd13dpqrYYmVhViHzMgrIMTuyUN1UKu4I8+f+qCBi3fQIcXbHiV92Z/HS0n0APDGiNZP7xDhEW9qnZGQswm53dDfwroT446X4u3VAmboULiDcsrKy+OOPP0hNTQXAprWxw2cHuT65vDvsXfpF9HPeazdZKfszlYoNWSBAmCsw7vkWQ3tviq8bz4//+Bt2qwkUPaGtb+CWZ+7E4HG+tBGJRCKRSCSNTeOJt6LjjjNsB5ZC5jbXn0X1gfY3ItqNx6QPdGSoXuaDh3a7YOPxQr7cksaf+3Kcq2yeeg3XdQxhar84OkT4XOQpZ3OsysicjAIWZxdRbXcUxA3RabgnMogp4QH4ndkJ4TTWHSngicU7EQKm9o3hwYF+HDn6qoto83JvS9yeYwRmZqMEt4fJP54qlXIGZWVlrFy5kl27dgGgVqspCC1gtWY1Op2O2cNnkxCa4Ly/+mARJT8exVbqyOixpG/CtOcb9LeMZ6ubmuNzPwBA0UTQ/bp7GTSpJ6pa9GGVSCQSiUTSeDRMvBUehZ2r4MBPcFrh3JosUdrfCO3GO5IO4LImHtSQX27iu20ZLE5OI6Xw1Fm2LlG+3Nkrius6haEW1jqXQNlUVsVnR7L5s7DMuTHcwdPAg1HB3Bjsi0514WSG3RklPLBwKxab4KYu7kxu/ysbNi48tdLm1Zm4sGn4//gKqsJshH88TFkC7v5nPctsNrN+/XrWr1+P1eqo89a2Q1t+Uf3CropdeGm9mD1iNl2DuwJgKzdT8vMxqncXOMZjq6B686fY8g8gHriX3/ftoLqsGFCh8+rPuIem06J7SK3nRyKRSCQSSePRsFIhc4aC/uTKi6KG2AGODNG248HryvnjbrcL1h4t4OstaSzfn4v1ZMaol17DhG4RTOoVRYdwx+qVYyvTWqvnmu12fsor4eP0fPZWVDuvjwzw5oGoIPr7etYqtfl4fgXT5yejooTHe22gi/8q0tNPrrR5dSI+7jEC3DqjLLgBCo9h945AmfrTWXNst9vZtWsXK1eupKKiAoDo6Gj6Du3L3/f8nYPFB/HR+fDJqE9oH9AeYRdUbs2h9LcUhNEKCtgKt1K1/jOEVkX21Ins3OjolKCofPGPvokbnxiDX2gT9a2VSCQSiURyFg0Sb0LRQMthjhW2NuPAI6Cx4moUcstM/LQ+nW+2ZpBZckpcdY3y5Y5eUYzvEl7ns2wAhWYrC7MKmJ9ZQK75ZO9SRWHiyfNsLd1rv2qXV27ioYWJjIj4lWHR69GqzNjtNaLtUQIChqKYK2DBjZC7F+EZgnnit+h9XM8LHj9+nD///JOcnBwA/Pz8GDlyJIExgdy//H6OlR7DX+/PJ6M+oY1/Gyx5VRT/cARziqP9liZQS2XS+5iPbqc6OJA93dpRsDMZALWuAy1738qoe7qhc7t81WUkEolEIpE0dNv0sR0QEtNIoTQOVpudxEP5fLUljaRDeZxcZMPboOHm7pFM6hVV54zRGg5XGpmTkc+3OUUYTz44RKdhRkQgt/t7EublUacigoWlWXy16p881jkJvdqR1ODt3YW42EcICDhZ8sNSDV/d4ThH6OYHU35EeMc7n5Gfn8/y5cs5fPgw4Oh6MXjwYHr16kWBqYC7/7yb1LJUgt2D+WDQB7Tyaknp8lTKk9LBJlC0Ktzaqch/9wlspSVkt4plr48b1pwsUAxoPUaScOMwel/XAlUt69hJJBKJRCK5dDRs5U3vU6eaXpey8W1KQSXfbsvgu20Z5JWbnNcTYv24o1c0YzuG1qou25m+hBAkFZczJ6PApT5bJ0837o8M4oZgH7SK4uj5WctxmUy5HE/5mPSMr0gIdog2g3tn2rR8DH//QU4BKKwmWDwFJWUtQucFk39ABLVDGI1UVFSwZs0atm7d6uyC0LNnT4YMGYK7uzsZ5Rncu/xesiqyCPcMZ86IOfhk6clbtANrvmMVUt/GD41XGrn/eBaj3cb+Lm3IxgoWMypNNB6B1zHqvt4Ex7uDUvv6bc2lwbH01XxivFp9NYcYpa9rI8bm4kvi4IpuTH8xO5PVxvID+Xy3PYvNKSXO6/7uWiZ0DeP69v60izh5oN9mwWiz1NpXtV3wY0EZ87OLOXay36gCjPTz5O4wP3p5uaEoCnazGVMtx2UyZZOZOY/cvO8RwoxGBSdK4+jc5nE6xg5DURRn7zbsVnRLH0R9dDlC44b51oXY/dthraxk06ZNJCcnYzY74mrZsiVDhgwhIMCxbX0o/xAzk2aSV51HlGcUs/vMwu2PSsq3O0qFKB4a3MdEYUz+mYLX3iPfy409LeIwCiugRuPWn6C4gQy/uy3egQZnO666cKU3OJa+GsdO+rp8dtJX8/JVXzvpy9UGZGN6uBIb09fCbm9mKd9szeCnnZmUnUwuUBQY3CqIiQlRDGsbjFatnLcR+4XIqDbxaW4Zi/PLnP1GPdUq7gzz5+6IQGLc9HUeV7Uxk9TUj8jO/g4hHALycHE8v6eM46mxt9OzbZirnbDDT0+gHPoFodbBpC/Qxg9m3759rFy5kpKSEgBCQ0MZNWoUcXFxTtMjxUd4MPFBCo2FtPBuwYfhbyLm52GqcPh1TwjBe2QU+W+9TuHixRwKDyAlyBeEDUXlj9ZjHG36dmLI5DZodep6vWaN9TpLX7Jp9tXuqznEKH1dGzE2B1+yMf0prozG9LWgzGjlmx2pfLM1g/3ZZc7rEb5u3NYzktt6RhHhe6onpxDnbsR+LoQQbC2rYk5GPr/mlWA7eT3WTce9kUFMDPXH6yIN58/lq7o6jZSUD8nO+QEhHCKz3N6JD7cN5khJKz6c3JNecT6udkLA78/Arq9AUaPc9hmp2pb8OXcumZmZAHh6ejJ8+HC6dOmC6rQSJAcKD3D/8vspMZXQ1y2BlwsfwbY5GwBNkBvu10XjEeVB1l+fImvjena2iqTCzdETVa3vgtZjMANubUfnYZEu47gaGxxLX80vxqvVV3OIUfq6NmK80n3VNa6rmSs6ddBuF2w4Vsg3W9NYtjcXs81R9FanVjGyQwgTe0bRv2Ug6noWijXZ7SzNK2FORj67y09lo/bxduPB6BBGBvq49ButLZWVx0lJnU1u7lKEcEhBP79+HCi/hb/95uhG8OrNnRjVPuTsbeeV/4DkOYBC4ch3WbGrggMH5gOg1WoZMGAA3bp1w8vLy+WNvDt/Nw8uf5AqcyUPGydz3dH+2C0VoFbwHhqF5+BIqnKzSZ0+k4PZ6RxqFYldpaCo3NG4j8LTvw2j7+tIRGu/Oo9XIpFIJBJJ03FFirf0oiq+O5l8cHqJj7ahXkxMiGJC1wj8PHT1fn6+2cLnmYV8nlVAfk2pD5XCLSF+3BMRSLxGOavfaG2oqDxMauqH5Ob+CjiEpr//QOJiH2Z1Shh/+20nAP83ug2TekWfffhyzZuw7m2qMLA67mmSV5zAbrejKArdu3dnyJAheHp6niX4tuZsZebKmUSWB/Fs/tOEVQYAAn28D743tUQb5I7x+HFOPHA/27V2CiIcTe5V2ji07qMJbRHKmPs74ulX+y1wiUQikUgkl4crRrxVm238sS+Hb7ams+FYofO6l0HDDV3CmdA5mB5xQS7bhHVlR1kVczPyWZpXgvmkcArTa5keHsjk8AACdBqEOLvf6MUorzjA8WPvU1j0p/NaYOBwYmNn4uPdhdWH83nqG0fNtOn9YnloSIuzH7LpIyyr/sMWerBGMxjTCUdma6tWrRg5ciTBwY7G72cKvo1ZG3lm+f8xLed6xhcPRkFB5a7BZ1wc7j1CUBSFqu3b2fLU4+z298CiUaOoNKgNg1HrOtNhUASDbm+NWivLgEgkEolE0hy4rOJNCMGO9BK+3ZrBL7uyKDed6mwwoGUgt/WMZHSHUPQaVb0yHsHRBeG3gjI+zchnW9mpdlg9vN25LzKI64J80dZz27W0dCcpqbMpKFjpvBYUNIa42Jl4ebUHYGd6CX9ZtA2rXXBDl3D+fn37s8Yhti9gz7L5rGQapfiAVRAaGsrIkSNp0eIcQu8ka9LX8M3S+byX/QyBVl8A3LsF43NdHGpPx8pk4c8/s3LW/0gPdhzu1OhDUenHoNEHMHhSG9oPCK/X2CUSiUQikVweLot4yy0z8uOOLL7bls6x/Ern9Ug/N27tEckt3SOJ8nd3Xq9PbZd8s4X5GQV8kVdK3smtUZ2icEOwL/dEBtHN2/0iTzg/xcVbSEn5gKLidSevqAgMGE18/CN4ebVx3ncsv4IZ87dQZbYxsFUgb97W5axG7ulrvyRxw1ayGQuAt7c3w4YNo3PnzhdcZUzau4KipUd4tvxuANQBevwmtMLQynFmTQjBoXfeInH1n1T5egKgde+FStcXL393xtzfiZC4aztbRyKRSCSS5kiTiTejxcaKA7ks3pLG+mOFzs4HBq2KcR3DuLVHJH3iA84SN3VBCMH2sirmZRawNK8EizjVBWFaRCBTwgMI0mnr/eyionWkpHxASaljC1RR1ISGTCAm5kFUqjCXsik5pUamzt1CcZWFLpE+fDS5BzrNKTGWl5fHiiVfcjirBAhBpxIMHDKcPn37otWeP0ZhE+z4LYnIrVpaiU7YFDveQ6LwHRaLcnLr02Y2s+qvj7EnJw2h16JVu6G4XY9KG0V4a19G39sRd+/6nxmUSCQSiURy+bik4q1mW/T7bRn8vCvLWZMNoGeMH7f1jGRcpzC8DPUTVDUYbY4G8fMy89l1WtZoN08D90UFc32wL7p6npUTwk5BwQpSUj6krHw3AIqiIzz8VmKiH8DNLfKsc3KlVRamzdtCZkk18YEezJuegIfeMdXl5eUkJiayY8d2hAAFOz39qxg84+94el14JcycXs6Jr7cSXehYScv2L6bTlKEYwryc9xSlnmDp83+l0GoCRcHdvSU27SgUlYEOg8MYeFtr1BcpeyKRSCQSieTK5ZKIt+zSan7Ynsn32zM4ftq2aJiPgRs6hTCxdyzxQZ4N9pNpNPN5ZgGLsgspsjhKcuhVCjcG+zIjPJC2OlW9skYBhLCRm/sbKakfUlnp6BuqUhmICJ9EdPS9GAxh57QzWmzcuyCZQ7nlhHjr+fzuXgR46jGZTGzYsIENGzZgsTgK5rblCEOjFYKnzkPRnH8lzG60UvpHChUbs/BAQ7mqkl2d07nttrtRq0+1/Nrz21ISF8zBCqjtAreAsVhpj1anYujktkR18pH9SSUSiUQiaeY0mnirNFn5Y18OP2zPZP2xAsRp26JjO4ZxS/dI+sT7YzGb6tSV4UyEEKwrrmBeZgF/FJSeLMgBEXot0yICuTMsgMB6Zo0C2O1mcnO/Jyt7HtXVjnZSarUnkZGTiY6agU4XeF5bq83Ow1/uIDmlGC+Dhs/v7kW4j57k5GSSkpKorHQI2Uglj5Eikej41hhv+gzU5155FEJQvbeAkp+PYy8zo6Cw0nszhf0Ejw96ynkmrrq8jD/efZ1je3YC4GnVYQuaghUfvIPcGPtAJwIiPOo1HxKJRCKRSK4sGiTebHbB+qMFfL89g2V7c6gy25w/6xXnz609HNuinie3DIUQ1K676NmUW218kZHP51mFHKk61Xi+n68n90QGMjrAB00DzsvZbNVkZS0mNe1TTKaTXQk0vkRHTScyciparc8F7YUQ/G3JXlYcyEWvUfHp1J6I4kxmf7uCwkJH6RN/H0+GV/9Ke/N2lKjeiIlfgP3cW5jWIiMlS49hPFgEQKY2j1lhX9Gzz0AebHufczUxZfcOlr37OpUV5ShC4K/EURE4AQUVMR0DGDGjPQYPrWzoK5FIJBLJVUKDxNvod9aQbzolPmL83bm5ewQTukUQfY5s0Zp+ZnUREgcrqvksq5Bvc4qoOpnl4KFWcVuIH9MjAmnjcWoV7/Tn1taXxVJGZuYi0jM+w2JxCCWtNpDo6HuJCL8DjcbjrGefiRCCd1Yd55utGagU+PfIMPYmLiE9PR0Ad3d3BiV0oue2v6IxZyBCOyPuXIzQuiOMRte4bXYq1mVRvjINYbFjV9n5yv93Fgf8wQPdH+S+TvdhNBqxmEys/3oB239f6vBhsuLuO44KQ0cUoOd1sSSMi0VRKS5zUVcRVx876at5+WoOMV6tvppDjNLXtRFjc/ElcdAg8ZZbZsLXx5uxHYK5sUsYXSO9nStC59uiM5lMFz2DZrYL/igqZ2FuCcmnJSC0dNMxJcSXmwK9nb1GL7QVeCFfZksh2dkLycn5GputAgC9PoKI8Lvx9h6Du7sPVitYrRffaly4OZ1P1qXirVQzOaqUvYmObFSNRkNCQgK9O8Ti/d1tqCoysAe0wnTbl4ABTCaXGC3pFVT+kootzzHm3IBSXvR5l3R9Do92fpTJrSdjMpnIOnaYtfM/pijTIQ5DywRVUQ9QofJBa1Az+K6WRHf0x2Q2ucRZm7mv6zw2po30dfl81ddO+rp8dtJX8/JVXzvpy9UGICEhAbVazcyZM5k5c2adnnG10CDx9uatnbghoSV6be2yF2uUtl6vP+eLlmE0syirkC+yiyiwODJT1cDoQG/uCvRmSLBfrTssnM+X0ZhFWtqnZGV/g93uEGYe7i2JiXmQ4ODrURQ1RqPxvDGeyc+7snj7j/300WTSVlNAVZ5AURS6du3KkCFD8NZY4LPrUEpSEb4xKFN/wuAd7hKj1qai7I9UqpJzAVDcNaxts49/V78LCjzX6znuaHsHwm5n269LWLd4IXarFZ3FSnhVCLmxUxCo8A/zYMyDHfENPruG3cXmvq7z2Ng20tfl89UcYrxafTWHGKWvayPG5uCrRrwlJyfj7X1t1ylt2LZpxzAMuro9QlEU5xeAXQhWF5XzeVYBfxaUORMQQnQaJocHMDk8gFCdFqPRiEqlqtMLfbqvisojpKV+Qk7uUoRwCENvr87Exv6FwMARKIpDFAohzorxfCTuz+Tz73/lZl0OWsUReevWrRkxYoSjnZWxFD6/BfIPglcYyrSl4BPhtBdCYN5TRMmfGdgrHacB3XoE83Hgt3yVthhFUXip70vc0voWygryWTb7bdL3OcqVBJVVYdAPIid2EAAtewQzdEpbdIbzvx61HVdj2ElfzctXc4jxavXVHGKUvq6NGK90X3WN62rmsrXHKjRb+Sq7kIVZhaQazc7r/X09mR4RyJhAH2fbqobsc5eV7SI19SPyC5Y7r/n59SM25kH8/PrV681gtVr5eeU6Nm9YRye1QwiGhYUxevRoYmNjHTeZK+GL2yF7J7gHwNSfwC/W+QxLfhUlS45iOlYKgCbYDe8b43kl63V+Pf4rKkXFv/r/i/EtxnNw/WpWzJ2NqbISNdAyp5KCyGnke0WjKND35pZ0HREl39gSiUQikVwDNKl4E0KwtbyKr47n8kt+qbM5vLdGxe2h/kwJd01AaIifoqJ1nDjxIaVlm53Xg4JGERPzID7eXer1XLvdzr59+/hj+QoqykoxKGDWuHP7jWNp3aIFbm5ujhutJlg8GdI3gd4HpvwIQY62WcJipywpnfKkdLAJ0Ch4D4/G0C+EZzc+x/LU5WgUDa8OepXBQf359b03OLh+NQB+VkF0npZjbZ7EqvHA4Kll9L0diGzr37AJk0gkEolE0mxoEvFWZrXxXU4RC7MKOVB5KgGgi5cb08IDuTHEFw91w6v+C2EjL28ZqWkfU16+DwBF0RAaciMxMffj4dGy3s8+fvw4y5cvJzvbUUakWmjI82zB2w/dhI+7/lTihM0K390Nx1aB1h3u+hbCHGLReLiY4p+OYit03Ktv7YfbmEg0wQaeWv1XkjKS0Kq0vDn4TVqVB7Lg9UcoL8xHUVS0LK1CY2vPofY3gqIQHOPFmAc64eXfcLErkUgkEomk+XDJxJsQgh3lVSzMKmRJbgnVdseZMINK4eZgP6ZGBNK1Ac3hT8dmM5Gd8z1paXOork4DQKVyIyT4ZuLiHsDNLeIiTzg/WVlZrFixguPHjwNgRc1uSygVPnEsfnAgvh76U9u6wg4/zYSDv4BaB5O+hOje2MpMlPxynOrdBY7YvHX4jo/H0CGA0spSnlr1GBuyN6BX63lr4JuINcf55pe3QQi8vX1ptz+VzNCbKAjqCkDrPsEMubMt2jqeN5RIJBKJRNL8afS//hVWGz/kFrMwq5A9FafKfLTxMDAlzJ/xvu4Ee3o0yvksq7WcjIwvSM+Yj9nsEEZarR+RkVOJjJiMzeZW724OhYWFJCYmsm+fYwVPpVJRYIjkjyJ/vDw9+f6evgR56U8ZCAG/PQ27vwZFDbd9hogbQuWGLEr/SEGYbKCAZ79wvEfGoDJoqDRX8sTaJ9iWvw03jRuvtn2BlFnfkZ+WAkDrmBYEJ+5lf7u/UOUeikqtMGhSa+J7+qOpZYavRCKRSCSSq4tGEW9CCHaVV7Moq5Af8oqpsjlW2fQqhfFBvkwNDyDBx1HstjFaNBlNOaSnf0Zm5lfOGm0GfTjR0fcQHn47arU7Qghstrr7qqioYNWqVezatQv7ydXCTp06s6o0iF8Pl+Gp1/DZjARiAjxc7DRr/oOy9VNAgZs+xuwxiOIPdmLJdMSnjfTE76ZW6CIcPV3LzeU8tOIhdubvxEPjwXPqyex+ax42qxU3L296h0RTsTqVHV2ewqYx4OGrY+wDnQmO9ZJtriQSiUQiuYZpkHgrt9pYklnAojNW2Vq665kSHsBtof74a0+5aGh15MrKI6SlzyUn5yeEcJTW8PBoRUz0A4SEXI9Kde4eobXBaDSyfv16Nm3a5Gwc37JlS4YPH877mwr49XAaOrWKT6b0oGPEGa2y1r6FdtP7ANhHvUvp8W5Ubt4JAhSDGp/RsXj0DkM5mT1bairlgeUPsK9wH8FWHyYf7c7Rw8sAiOvag07ZpRzcAWkd7wMgorUvo+7tiLu3TlaYlkgkEonkGqdB4q3/5oOY3Bzn1vQqheuDfJkcHkAfn8bZFq2hpGQbJ1I+pLg4yXnN17c3MdH3ERAwpEG+LBYLW7ZsYd26dVRXOwRoWFgYo0aNIi4ujndWHObLzWkoCrw9sSv9Wp7RmH7zJyirXkEIqGo/i9JVrbBXOJIa3LsF4zMuDrWXznl7kbGI+/+8n0PFh+iQH0Tfvf4UVR9Ho9cz6Na7cF/8K8nWnhRHO7JTu46Mpu+EeFTq2hUnlkgkEolEAmvWrOGNN95g27ZtZGdn8+OPPzJhwoQL2qxevZonn3ySffv2ER4eztNPP82DDz7YNAHXgQaJt2q7nTYnV9luPWOVraEIYSM/fwVpaXMoLdtx8qpCUNBoYqLvw8ena4Oeb7PZ2LlzJ0lJSZSXlwMQGBjIsGHDiI2Nxc3NjUWbUnlnxREAXrmhA9d1DnN9yM4v4ff/w2KPpMj9v1h2+AEWNEFu+E5oiaGFr8vt+VX53PfnfaQXnGDEwXAi07VYMRLSohWjbptCxisfsNZnLCYvfzQaGDa9A616hjRonBKJRCKRXItUVlbSpUsXZsyYwS233HLR+0+cOMG4ceO47777WLRoEevXr+ehhx4iKCioVvZNSYPU1led4hgWHd6oq2w2m5HsnB9IS5tLdXUKACqVjqDAG4mLux8Pj/gGPV8IwYEDB1i5ciWFhYUAeHt7M3ToUDp37oxKpcJoNLJsbw5//2kvAI8Oa8mUvrGuD9r/E/YlT1BumUK5/TYoUYFGhffwKLwGRqJoXFfKcipzuPfPezEfz+WmPRG4VatQVCp6jL+ZHh26k/zCXA6E3Y5QafH2VTPu0R4EhHs2aKySa4fY2FiysrIudxgSieQqJTw8nJSUlMsdRp0YO3YsY8eOrfX9H330EdHR0bzzzjsAtGvXjq1bt/Lmm29eXeKtx8kkhNqew6rpZ3au+83mIjIzvyAjcyEWS5EjOI0PERF3ERkxBbvdE4PBUG9fQgiOHz/OqlWrnH/k3NzcGDhwIAkJCWg0Gud9W04U8dji3dgFTEqI4vERrVz9Hl1J9dcfUmr+ABuOlTFtKx/8bmyJNsDtrDnJrMjk/t/vJXRbFR1SHPf7hoYxZuaTaI9nsPwfv5AVcSMAMW08GfFAN/RumnOO9UJzWJf5uJR20lfT+oqNjSUjI8OZYCORSCSNTXp6OjExMWcJuKb+LAUoKytzua7X69Hr9ecyqRMbN25k1KhRLtdGjx7N3LlzsVgsaLX1P1ff2DRIvJlMpjpnPppMJpeVuurqVLKyF5Cf/5OzUbxeH0F42FSCg286mTkKJpOxzit8Nb4yMzNZs2YNaWmOGnBarZaePXvSu3dv9Ho9VqsVq9XR5upQbgUzv96D2WpneJtA/jamhbMZLoDYv4mqH3ZjtP0NAJWPFo8x0dhiDNjcFGxnzEdaeRrP/vQw3Tcp+FU4Gul2GDqSfpOmUvTDMlauNFIe3AeEoNuIELqOi0coVoxGa63nsK7z0RR20lfT+crOzsZut7No0SLatWtX59gkEonkQhw4cIDJkyeTnZ19zr/5TfVZWvO3OCoqyuX6Sy+9xMsvv1ynZ52LnJwcQkJcjyqFhIRgtVopKCggLCzsPJZNT4PEm16vr1MdtRqlrdPpKCvbQVr6pxQUrAAcatrLqyPRUfcRFDQalUpzlp1er6/1iy2EIC8vj2XLlnHo0CEA1Go1PXv2ZODAgXh4eJxlk1Fcxf1f7KLCbKNnjB+z7uqB4WQ9NWG1U/FbMuUbbQgSABuegyLxGh6LonVstZ4Z37Gio7zx8SP03adDLRQM3t6MefBx4rr1ZP9/5rLheDAWrxC0iplRD3YlpsvFz7fVZy6a2k76ujy+2rVrR/fu3Wsdl0QikdSVM//mN+VnaY14S09Px9vb23m9MVbdajgznprVviutd3iDxJuiKHUakN1upbDoT3JyFlBWtst5PTBgGNHR9+Dr2/u8z6vxVRt/RUVFJCUlsXv3bqdtly5dGDJkCL6+vue0KawwMW1eMnnlJloFe/DptJ64nexgYDxaTMn3B7AW2wA9erdUfO8dhzbC0VNUCHFWfNsPbeC7d1+hXaEj0zS6e3eu+8tTGPQG1jzxEfuMrUGnwkdfxfV/G4pv8Nli8nzUZS4ul530dfl8SSQSyaXiXJ9HTfX5VnOvt7e3i3hrLEJDQ8nJyXG5lpeXh0ajISAgoNH9NYQm6a9ktVaQlf0t6emfYzSmA44khNDQm4iOurtBPUdPp6ysjDVr1rB9+3bn+Z927doxbNgwgoKCzmtXabJy92fJHC+oJNzXwJy7uuLjpsVWaqLk19PaWlGMT/Aq3B96BcVw7jeOEII/f/6MHYu/I8CqwaaFIVPvI2HkDRjzS1jy1Bdkq9uCAnFhJgY+PgTPRmoTJpFIJBKJpH707duXn3/+2eXan3/+Sc+ePa+o825wicWb0ZhFesbnZGZ+7eyEoNH4Ehk5mcjIKeh1gRd5Qu2orKxk/fr1bNmyxXl2rUWLFvTv35+4uLgLKnuLzc5fvtjOroxSfN21LJjRi2APFeVrMylfkYYw2wA7nupf8A7biuru7+E8wq2qtITvZv2bgj0H0aJQHqzm3mf+R2RkS/L3pPDrO8lUamNR7FZ69dbTfcZol/N0EolEIpFIGoeKigqOHj3q/P7EiRPs3LkTf39/oqOjee6558jMzGTBggUAPPjgg8yaNYsnn3yS++67j40bNzJ37ly++uqryzWE83JJxFtZ2W7S0uaSl/87QtgAcHePJypyBr6+Y/Dw8GuUrSCj0cjGjRvZuHEjZrMZgOjoaIYNG0ZMTMxFkynsdsHT3+1mzeF8DFoV86YnEFlpo/iLQ9jyHAV7dboUfHkLXSAw7Xdw9z/ns07sSGbF3FlYKqqwKYK87h689NhcvPReHPx5O0lLc7FpA9Bbyhh5Zywxw7vKbgkSiUQikVwitm7dytChQ53fP/nkkwBMmzaNzz77jOzsbGciI0BcXBy//fYbTzzxBB988AHh4eG89957V1yZEGhE8Wa3WykoWEFa+nxKS7c6r/v59SU66h4CAgYDSqP05TSbzWzZsoX169c7uyKEhoYyfPhwWrZsiaIotRJGry47yI87MlGrFD65qQuxG/Mo2JEHgMpNjY/7N7hXfIbiEw5Tl4FX6NmxVFeR+Pkc9iYuB6DIy0zJ8DDeuPVDDCoDq99fzd59NlDr8TNlcN1zQ/BpHd3gOZBIJBKJRHJ+hgwZckEt8Nlnn511bfDgwWzfvv0SRtU4NLjnktVaTlraXDZuGsaevTMpLd2KomgJC72ZXgm/0L3bIgIDh6IoDW/vZLVa2bRpE++++y4rVqygurqawMBAbrvtNu6//35atWpV6xW9OWuO88ma46iBzzvH0OKnFKp25IEC+q6+BIe9jkflfBSPAJj6E/ieLbgyDuxlwdOPsDdxOQLB3rhSSm5twf9u+xjFqOHHF5c7hBsQZ9nHrW/dIIWbpMnZtm2by+Hg831t2LChyWJ6+eWXXXwHBQUxfPhw1q5d22QxXIyCggIURTnnB3x9OHPMgYGBDBgwgN9++61Rng+NH3NjUJuYavP+vJLG1BQsWbKE2bNnX+4wJFcoDVp5O3r0VcorfsVmqwRAq/UnIuIOIiPuQq9vvLZONa2sNm7c6CzO5+vry5AhQ5xdEerCjzsy+PdvB+iEmte8fPDeWYQAtJGe+F4XhWb1PaizkkDvA1N+hMBWLvZWi4UN3ywi+ecfQAgq3Kys7VxAh679eWPwGxSlVfP7W5uosmhR2Ux09zhAwnsPo9LpzhmPRHIpiYuLY+PGjc7vP//8cz766CMSExNd0v6busyIm5sbq1atAiAjI4N//etfDB8+nG3bttGpU6cmjaWpOH3MWVlZvPrqq4wfP561a9fSr1+/yxzd5eP09yc4Do4/8sgj3Hnnnc5rLVq0aOqwLitLlixh69atPPTQQ5c7FMkVSIPEW2bW13h4qPDwaEVU1AxCQ25Era593beLYbfb2bNnD0lJSRQXFwOOFOFBgwbRrVs31Gp1nZ+5+nA+//lmD89jYBw6KLeiuGnwGROLR/dA+H46SkoSQuuBMvk7COvsYp+feoLfZ/2P/LQUAI5GVrK5XSGD44fz2uDXOLI2hzVfH8aOFreqXAa2L6HlM0/Icg+Sy4a/vz99+vRxfj979myio6MZMmTI5QsKUKlULnH16tWL2NhYPv74Y2bNmnUZI7t0nDnmvn37EhERweeff35Ni7fT56SG6Ojoc15vrgghMJvNjVqTrDn5lzQuDdrL9PfrT9eun9O71+9EhE9sNOFmt9vZu3cvH3zwAT/++CPFxcW4u7szevRoHnnkEXr27Fkv4bYrtZhln+9igfBwCDfAIyGU0L/2xDMhBOWXR1AO/oJQ62DSFxDV67SYbGz56Tu+eP4J8tNSUHsYSOyRz7rOBYxucx0vdX+ZtZ8fJOnro9hREViwm+tGa2j17F+kcJNcUezZs+eKXNmKjo4mMDCQEydOALBv3z7GjRtHQEAA7u7utGnThtdff93FZuPGjQwbNgwPDw98fHy48847ycvLc7lnyJAhXH/99S7Xtm7diqIoJCUlOa/NmTOH2NhY3N3dGT58uEuW2uksWbKEbt26YTAYCA0NZebMmVRUVNRrzGFhYQQFBbkcmq7L2GoTc23HX9MayNvbGy8vL3r37s3y5csvSUwN4WIxTJ8+nY4dO/LHH3/QqVMnZxvEEydOUFRUxMSJE/H29qZFixYsXrzY5dk1tr///jsdO3bEYDDQo0cPNm3aVO84fvvtN7p06YJer2fp0qVO2xtuuIHw8HA8PDzo2rUrCxcudLH9/PPP2bdvn3PbePr06UDtX8+L+b/Y6yi5smnQylunTh/g4+PTWLEghODgwYMkJiY630hubm7069ePzp074+3tXW8hlLIzl7JvDjLT7vi/Dk24B34TWqKP9gYh4PenYddXCEWN+cZP0MUPcdqW5OawbPZbZB7c74ipbRSfRWykWm/jlla38Firv7LsnV0U5phA2GmRsYz+/3c9Xpd5ZUMiOROr1cqBAwcYM2ZMvZ8hhMBms130PrVaXaff17KyMoqKiggPDwfghhtuIDg4mLlz5+Lj48PRo0fJyMhw3r9x40aGDBnCuHHjWLx4MZWVlbzwwgvccMMN5/xjeyF++eUX7r//fqZPn86kSZPYunUrkyZNOuu+pUuXcvPNN3Pbbbfxn//8h+PHj/Pcc89x6NAhVqxYUSef4ChlUFRUdNaWYG3GVtuYa8P69esZNmwYffr04dNPP8XX15etW7e6iMqmjulc1PY1z87O5plnnuHFF19Eo9Hw6KOPctddd+Hp6cnAgQO59957mTNnDpMnT6ZPnz7ExMS42D700EO8/PLL+Pn58eqrrzJ69GiOHDlCcHBwneLIysriscce44UXXiAqKsrZ1ik1NZX+/fvz4IMPYjAYWL9+Pffccw9CCKZOncqLL75Ifn4+Bw8e5IsvvgC4YK3S83Eu/435eyO5jIh6UFpaKgBRXFws7HZ7rb9sNpuorKwUNpvtrOsHDx4UH330kXjppZfESy+9JP7zn/+IxMREUV1dfV672vgyF1eLzIX7RPoza0T6M2vEwWfXiPy16cJmPe1ZK14R4iVvYX/JR9h2fuX0ZbPZxM7lv4t3p9wi3rz9OvHu1FvFnEWviI7zO4qOn3UU/9r4L3Fib56Y81iimPXASvHx3T+JDaOmisrduxs0H41t09R20lfT+tJqtQIQ27Ztu+jv7r59+wQgvvzyy/r86gshhJg/f77A0dPugl+JiYnnfcZLL70kPDw8hMViERaLRZw4cULcfPPNAhDLli0T+fn5AhBLly497zMGDRok+vXrJ+x2u/Pa3r17haIo4tdff3VeGzx4sLjuuutcbJOTk11i7N27txg4cKDLPc8995wAxPz5853XunXrJnr16uVy35dffnnR8Z5rzGlpaeLOO+8U/v7+4vDhw3UeW21jrs34+/XrJ9q3by+sVut542/MmC4GIN544416xTBt2jShKIrYv3+/8573339fAOKZZ55xXisuLhZqtVq88847zmvTpk0TgFi5cqXLfZ6enuK5556rcxyA2Lx58wXHarfbhcViEffff7/o27evSywdOnQ46/7avJ4X8l/b35vT2bZtmwCEVqu9rJ+lxcXFAhClpaUXnNNrgcvamF4IwYkTJ1i3bh3Z2dkA6HQ6evToQa9evTAYDAghMJlMdW5iK2x2KjZkYV6XB2Y7dgSJOjvD7+2ER5A7JrOjOK5m8yy0a98EwDLqVWytb8RkNFJVWkLivA9J270DgPA27SkfFsG7qZ+CAne2upMhebfy2+d7EAK8ylPpVrqMmA/+jRIRUet5udKbo9fXTvq6fL4uxJ49ewAatG06fvx4kpOTL3pfmzZtLvjzyspKl6rlfn5+zJo1i9GjRyOEICYmhueee46ioiKGDx9OZGSk896qqirWr1/Pm2++6bIK2KZNG8LCwkhOTmbcuHG1Go/NZmPbtm1nbcneeuut/Pe//3V+X1FRwc6dO3njjTdc7rvtttuYOnUqa9euZfDgwS7xKIricsTjzDGr1WqWLl1Kq1ankqJqM7bRo0fXKubaUFVVxaZNm/jvf/973uMoTR1TfWOoec3Dw8Np166d857WrVsDMGLECOc1X19fgoODSU9Pd/Hj4+PDsGHDXO4bNmyYc1WqLnEEBgbSq1cvzqS4uJiXXnqJn376iczMTOdzGrsF05n+G+P35kpoTJ+QkIBarWbmzJnMnDmzTs+4WrhsjelPnDhBUlKScxtEq9WSkJBA//79cXd3P6ddbZvYmo6VULr0ONa8KgD2Y2Oum5XXZvYhIuC0HqJb56Ek/cvhY/jLaPs+gEYIjm7ZwJoFn2KsKEet1TJg0lS2Rubywa4PALi3zf203D6I7bsdv/RhWevp5HGY2AUfovHzq/N8XKnN0ZtDjNJX3dizZw9arfaiwspqtaLRnPvjwd/fv1bHJS52LtXNzY01a9Y4y2ZERUU5M8cVReGPP/7ghRdeYObMmVRWVtK9e3fefvttBg0aRHFxMTabjSeeeIInnnjirGef+Qf5QuTn52O1Wp1bYjWEhLhmzJeUlCCEIDTUtd5jTd/DoqIiVq9e7VIUdPDgwS7nkGrGbLfbOXLkCM8++yxTpkxh7969hIWFAdRqbLWNuTYUFxdjt9ud29Xnu6cpY6pvDDWc2cNadzLT/1zXzxQj59qeDA4O5vDhw3WO48y5qGH69Ols2LCBv//973To0AFvb28+/PDDs87gNZQz/TfG782V0Jg+OTn5kvQ2bU40aWN6gLS0NDZs2OA8S6HRaJyizdPT86K+LuTPWmKi9LdTvUir1PCerZokrZ2v7+1LbOBpz9/9Lfz6lOPfA55EGfgExooKVs77kIPrVwMQHNuCMTOf4OvCn/lk1ycAPBT1BF6/tiMlvxCV3ULrI9/QpqsPfi+9j8bH54puWN4cmqpLXw33dSF2795N27Ztz9mnb+bMmQghOHDgAGq1+rxnuD7//HNmzJhxUV+JiYkXzGhVqVT07NnzvD9v06YN3377LRaLhQ0bNvD8888zfvx4MjMz8fX1RVEUnn/+eSZMmHCWbWDgqdZ7BoPB2YGlhqKiIue/g4KC0Gg0Zx3Yzs3Ndfm+xueZ161WK4WFhfj7+9OjRw+XVUkvL6/zjrlXr160bduWXr168corr/Dhhx+6+LnQ2Gobc23G7+vri0qlIisr6yzbM8feWDHVh7q85g0hPz//rGt5eXlOcV2XOM71u2s0Gvn111/53//+xyOPPOK8bj/Zj/tiXOz1PJ0z/TfGHJ5rTE31+SaT/07RJI3pAedKW2pqKuD4v/KePXsyYMCAsz7g6oqw2ilfm0H5qnSExQ4K7AvW89fcfIxqhflTe9Ex4rSVgoO/wY8PAAIS7oPhfydl5zb++Pg9KooKURSFXhNup88tE3lv1yzm75sPwCNeLyCWhFBqrkZvLKLTvjnETRxJ4BNPYDrjl0kiuRLZs2cP/fv3P+fPdu7cSVRUFH/88YdzpeJcNNa2aW3RarUMHjyYZ599lhtuuIGsrCxat25N3759OXDgAP/6178uaB8ZGcny5csRQjg//E/PolSr1XTv3p0ff/zRZTXiu+++c3mOp6cnXbt25ZtvvnG22QH4/vvvsVqtDBw4EC8vrwsK0jPp0aMHd9xxB/Pnz+ell14iNDQUDw+PWo2tNjHXZvw1/hYsWMBTTz11zhXTxo6pPtQ2hoZSWlrKqlWrnFunNd8//PDDjRKHyWTCZrO5/I6Vl5c7M0FrONeqIFz89bwQTTWHkkvPJRdvJ06cYPXq1aSkpACnPigHDhzYKMue1QeLKP35GNZCx5tcF+PNH+E6Xtx4HID3buvCgFan/d/E8dXw7XQQNug8CcvQV1g990N2LXdUOfcLi2DoPQ8R06ETryW/xpcHv0RlV/Gw6V+YN3oAdvyKDtDh4OdEPfMY/nfdJXuUSpoF5eXlpKam8uCDD571M/vJ8jw//PDDBYUbOM7lNPbZnDPZvXs3Tz31FBMnTqRFixaUlpby3//+l9jYWGdm5htvvMGwYcOYOHEikyZNws/Pj4yMDJYvX86MGTOcq3633norc+fO5ZFHHmHChAmsX7+eH374wcXf3/72N2688UZmzJjhzJL88ssvz4rr5ZdfZsKECdxxxx1MmzbNmW06fPjwetfNe/HFF/nqq6945513ePXVV2s9ttrGXJvxv/rqqwwbNowRI0bw0EMP4efnx/bt2wkMDOTuu+9u9JjqS21f84bg7+/PPffcwz/+8Q98fX2dr8njjz/eKHH4+PiQkJDAq6++6lytfPXVV/Hx8XFZtWzXrh3z5s3jq6++olWrVgQGBhIbG1ur1/NCNMUcSpqA+mQ51GSblpSUnPee48ePi/nz5zuzR1955RXx888/i5ycHJcsl9pgt9tFVVWVi50lv0rkz9/rzCLN/NdGUbE9VyzekipinvlFxDzzi/ho1SFXX2lbhPhXmBAveQvx1Z0iY99u8ekj94o3b79OvHn7dWLlvI+EqbpKVFRWiJfXvyw6ftZR9Pqkn/joH8vErAdWilkPrBQ/j/k/sb9LN1F2WjbSueKr77guhc3VHKP0JWqdbbphwwYBnDOj7ODBg6Jz5861jq+h1GReno/c3FwxefJkER8fL/R6vQgODha33HLLWVmZycnJYty4ccLHx0e4ubmJVq1aiQcffFCkp6e73Pf666+LqKgo4eHhIW6//Xbxxx9/nJWd99FHH4moqChhMBjE4MGDnfN1ZpbkDz/8ILp27Sp0Op0IDg4WDz30kCgvL2/QmO+66y7h7e3t8plam7HVNubajH/9+vVi6NChwt3dXXh5eYk+ffqIFStW1Hm+axvTheA82aa1ieFcWZqJiYkCEMnJyS7XY2JixMyZM53f19j+8ssvol27dkKn04lu3bqJ9evXN0ocNRw5csQ511FRUeKNN9446/1RWloqJk2aJAICAgQgpk2b5vxZbV7PC/mv7e9NDadnm55JU36WlpSUyGzTkyhC1H3ZqKysDB8fH0pKSs46uHy+lbYBAwbg7e2N0WjEYDDU+cB3jZ0w2ylPTKd8bQbYBKgUPPuH4z08mqSUQu5bsA2bXfDg4HgeGxJ7ylfOXvhsHBhLscYMZoP2Brb+shQh7HgFBDH6L48R06krVpuVF9a9wK8pvxJe1oIJJx7GXqVCYzPSbv9nhIpMoj76ELfOnc8ZX33HVZeDnk3lqznEKH05tlcsFgvbtm2rd4urxYsXs2zZMubPn18ve4nkamD69Ols3bqVvXv3Xu5Qrii2b99Ojx490Gq1Z523a8rP0tLSUnx9fSktLZUJC43xEHGy5Mfq1atdzrTViLYagVcPnejio2pnPmW/n8BW5njz6Fv54ju+Bdpgd7anFfPQF9ux2QU3d4/g6dFtnJkpFB6DhTeBsZQ8n978vi+SgvQlAHQYPIKh0+9D7+6B1W7l+XXP8/uJ3+mSM5S+qTdiFwqeVdl03PMxviEeRH3yFbpo2VxecnWxY8eOJu9tKpFIJJL60SDxJoTg2LFjJCUlOVOM1Wo13bp1Y+DAgY3WfcGSXUHZkqNY0xwtaNR+enyvj8fQPgBFUTiaV8HdnyVjtNgZ0iaI127pfErNl2bAghuxV+SxxdiTjYfdsNvScPP2YdT9j9AywdE7z2Kz8PSap0k6sYaRx6bTorAbACH5W2l74As8u3QgcvYHdSoFIpE0F2rO9UgkEonkyqdB4m3hwoUUFhYCDtHWo0cP+vfv32iizVZpoWx5KpWbs0GAolXhNSQKr0ERKFpHRlROqZFp87ZQUmWhS5Qvs+/qjlatcqzyVebDVzdRmFfAsrze5FToAButevVjxH0zcfd2xGmymXgq6Sl2HTnALYeewq86FAVBqyPfEpG5Gu/Rowl/7VVUdahpJ5FIJJLmxWeffXa5Q5BIakWDxFtWVhYeHh5O0dZYe9DCJqjcnE3p8lREtRUAXXs//Ma3QOvn5ryvtNrC9PlbyCypJj7Qg/nTE3DXnRySsQTd4jvYfqSKdXndsQoVeg8Phs94kLYDhjhX5oxWI48lPkb2nkpuOfZXtDY9BsVEh23v41N2Av/p0wl++v9QThYPlUgkEolEIrmcNEi89ezZk1GjRjW4TtvpGI+WUPLzMay5ju4I2lAPfMbHIcINaE5b+TJabNy3YCsHc8oJ8tLz+d298Pc4WeLAXEnp3In8sU0ho8pRViC2S3dGPfAoXgGnyoZUWap4ZMWjqLaEMDp7IgABIo+2G95Gbykn5Pnn8Z86pdHGJpFIJBKJRNJQGiTeRowY0WjCzVpkdHRH2OvYhlW5a/AeFYNHQhioXPup2eyCJxbvZMuJIrz0Gj6f0Ysof0dLLWExsuf1O0nap8Ji90Wr0zF46n10HjHGJaulwlzB478+RejGBMLLHH0F4yp3ELN1HmqdlvB338V71MhGGZtEIpFIJBJJY9HghIW6ZJDW3H+6jd1soyIpg/K1mWC1gwo8eofhPSIalbv2LDshBC8v3c/ve3PQqVV8PKUH7cK8EEJQnp/Dn//8C6l5NkBDWEwkY554Eb/QcOdzAMrMZTz9zcu03jIGD4sPao2gQ9oPBB5ehdrPj6C33sKzd69aj+1c47pUdk3pqznEKH1JJBJJ03HmZ1JTf5ZKHDRIvJlMpnO277iYjaIoCCEw7ymiakUG9nKLI5hYLzzGRKEJcceMDYy2s+w+XpvCwk2pKMBrN7WnW4QH1dXVHN6wmrWfzcZsEagVO31GDqLVhPtwc3d3ibHYWMzrCz+lw4FxqIUaN08LXTe9h1vBcTRRUYTMeh9bcPCpMiN1HFddqY9dU/qqr530dfl8SSQSyaXiXH/zm+rzrebvckJCAmq1mpkzZzJz5sw6PeNqoUHiTa/XY6hDBmaN0lbyzZT/cgJzWjngKP3hc12cs/TH+ex+2pPHO6scba/+Pr49E3pEU1lSzIpPP+DY1s0AhBrKGXPPPfgNmIzRaESv1zufmVOSx4fvLaVV9gAAgoPLaffTP1GbKjF06ULk7A9Q+/mdZVfbcdXFpr52TemrOcQofZ3iwIEDtY5JIpFIasvpny1n/s1vys/SGvGWnJwsi/Q2xFhRlDpNvK3MTOXvKZh2Os61KToVXkOj8RoQgaK9cDZn0pFC/rZkHwAPDWnBjP5xHNq4jhVzZ2MsL0OFnX5BaSTc8zyqbnc6m/bWfB1LyeC7WRsJrWiNXbHRNiSTiK9fQwG8Ro4g/I03UBkMZ9nVdS7q+n8SV7qv5hDjte4rPDyc9PR0Jk+eXKeYJBKJpLaoVCrCw8PP+XnUVJ+lcifiFJe8MT2AsNgpX5dJeWI6wuzYCnXvHozPmFjU3vqL2u9IK+bJb/diswtu7RHJw31D+eWd1zi0cS0AQfoKxoYfIujmV6DbnWfZb9t4mHWLjuFpC6BaV85Aw168v14EgN/UKYQ88wyKWt2II5ZImo6UlBRiY2PJysq63KFIJJKrlPDwcGfbS8nl55KKNyEE1XsKKP39BLZix3KnJsIDvxtboo+u3ZKno3vCVoxWO0PbBHFvVCWf/9/DVJWWoCgKvf1T6ROUhnr4C9DrPhdbu03w59c7Obq6GA16inxSmVC4Gc2fq0FRCHn2GfynTWv0cUskTU3Nh+qV2n9V+mq+MUpf10aM9fUluTxcMvFmzqyg5OdjmFPKAFB76/AeE4vS1gudm9tFrB3klp3snlBtoXuIjpvKVvPr26sBCAjyZYznakINZdDvURj4lIttVamJJR9upyTV0Qc1PWwz03dtQew/iKLTEf7663iPGd2II5ZIJBKJRCK59DS6eLOVmyldlkLV9lxnSyvPQZF4DY5E0apqnZ1aZrQwbZ6je0JvTS6DDyRypLQYRVHRc0B3+hV8gAYz9JgOI1+B0/5PIetoCb99vAtTuQ2z2kh69O888Mde7Fk5qH19iZw9G/fu3Rp76BKJRCKRSCSXnEYTb8Jio3xtJuVJ6QizHQC3rkH4jIlD4+s411bbGi0mq437F2zleFYB15VtJr54H9WAX1gEY24eSfiahwEzdLwFrnvLKdyEEOxamc6GH44i7FDklk1Z6M/c//1x7GXlaKOjif7kY3SxsY01bIlEIpFIJJImpcHiTQhB9a58SpelYCtxnGvTRnnhe308+pi6p/La7YInF+8ia+9OJheuxsNaAYpC55HjGDy8O7qvbgVrNbQaDTd9DCpHooHZaGXVggMc254PwJHArfhoErl7USbCYsHQpTNRs2ejCQho6JAlEolEIpFILhsNEm/m9DLy15xWr81Hj8/YWNw6B6Go6n7gUQjBKz9up3rV19xY4agr4xsaxqgHHiPI2472ywlgKoOY/nD756B2dGAoyqrk94/3UJJbhU2xsiHmR/rlHWLkb9kAeI4YTsQbb6Cq5Vk7iUQikUgkkiuVBom3grn78NJ7OOq1DY7Cc2AEKl39S258sOg3+H0hHWwVAHQfewMD7piKpioH5o5BqSqEsK5wx9egdQixw8k5JC46hNVko1JXwp8t5zFtVyk91xcA4Df5LkKee06WApFIJBKJRHJV0LBtUwXce4TgMzqmVvXazoe5uor5b7+PaddavACVdyC3PvEUUe07QXkuYuFNKBXZiMA2KJN/AIM3Nqud9d8fZU9iBgDZvkdJjJ7HMysVWu0rAUXB74knCL73HhTVhQsASyQSiUQikTQXGiTeAu/rhH+7iAYFkLp7J0tnvY251NF1wda2P48+9wRagwGqi2HhTShFx7H7RKFM+RE8AqgoNrLsk73knnCUIdkdtYr9vj/xzyUGwtIqUHQ6wl5/Dd3gwbJejUQikUgkkquKBok3bZhHrTNI4VQ/MyEEpqoq1nwxjz0r/wCgVOOFqc+t/Oehm1CpFISpHL64DSVvH8IzBNPt36D3CiN9fyHL5+3HWGFBbYA/4uZTadvBG19q8SmsQO3rS8QHs3Dr1g2j0Vin+M6M8VLaNAdfzSFG6evaiPFq9dUcYpS+ro0Ym4sviYMGiTeTyVTrum2n22Ts203i/I+oKHScS9vl3RHRfSwfTOmJ2WwCqwndd1NQZyQjDL6Ybv+aakMoO385xvbf00GAPliwMOq/BOXm8NoPCoYqI5rISEJmvY8qJgaTyYTJZKrXylt97K5WX/W1k76al6/62klfl89O+mpevuprJ3252gAkJCSgVquZOXMmM2fOrNMzrhYaJN70ej0Gg6HW9xsrK9n41WccWL0SgEqdD3/4D8a/ZTu+nNEHT70G7Fb46V6U1DUIrQfc9R3CrwNr5+0jY38JAN6d7bzr9hzdD1XxyC+gsdowdO5M5OwPnKVAalS9Xq+vc1uRutpdrb6aQ4zS17UR49XqqznEKH1dGzE2B1814i05ORlv77qXIruaaJB4UxSl1hOfsnMbf37yPuUnV9sywrrzs647EUE+zJveCy+DFux2WPooHPwF1HqUO74iX7Tl9/9uo7zQiFqrwm+Eif+WPM24zVamrHIUAz5fKZCa+Oqq7utjd7X6ag4xSl/XRoxXq6/mEKP0dW3EeKX7qmtcVzOXtDE9gLGygqQFn7IvaQUAXkEhbI8ezbIiDwI8dHw+oxdBXnoQAv54DnZ9CYoacet89me2ZO3ibdisdrwC9LiNK+LfR/7GtD+tjNnu2Pv2mzyZkOeelaVAJBKJRCKRXBNcUvF2fHsyyz95n4riIlAUuo6+np9UnVh2oBh3nZp50xOIDfRw3Jz0Kmz+CADLdbNZszmOg5sOARDbKYDSPgd5ffu/eOonGz2PClAUgp95Gv9p06Qal0gkEolEcs1wScRbdUU5SZ99wv61iQD4hYUz6sHH+PyYwtK1J9CoFGbf1Z0uUb4Og42zYfWrAJT0e4dlv8dTmJmDokCfCS04GLWB2Un/5u/f2GiZA4pOR/jrr+M9ZvSlCF8ikUgkEonkiqXRxduR5I2s/HQ2lSXFoCj0uG4C/W+/iwXJ2cxZux+AV2/pxJA2wQ6DHYsc26XAsZZvsvK3eCzGCty8dYy+pwOrbL+waNlr/HuxjeBSUPv6Ejl7Nu7duzV26BKJRCKRSCRXPI0m3qrKSlk17yMObVwLgH94JKP/8hjhrduxdFcW//zFIdyeHB7PLd0jHUb7l8LSR7AJNZu8/sfOdTGAjbCWPoy+ryOL07/g9yVv8a/vbHgaQRsVRfScT9DFxjZW2BKJRCKRSCTNigaLNyEEhzasYdX8j6kuL0NRVPS84Wb63XonGp2ODUcLeOqbnQBM7RvDvf1jHIbHVsH391Bh9eVP62tkHw0EoOvIaPpMiGfO3k/Y/uX7vPiLHa0NdB07Ev3xR2hPlgKRSCQSiUQiuRZpkHirKC4m8ZP3ObZ1EwCB0bGMfvAxQlu0AmB/Vhn3L9yGxSYY1ymUv1/fHovZBOlb4Ou7SK9qw/KK56i2uKEzqBk+rT1xXQOZteN9cuZ8zBOJNaVARuD/yj/Q+Pk1cLgSiUQikUgkzZsGibcvX3gSlcWMSq2m900T6X3Tbag1WgDSi6qYPn8LFSYrveL8eev2rqhVCta8/Ygvb2db8Ti2VNyBQEVApCdj7u+IT5Ab72z5H8o785i842QpkKlTCH76aUwWS8NHK5FIJBKJRNLMaZB4M1dVEtOmHaMffIygmDjn9eJKM9PmbyGv3ESbEC/mTO2JQatGFBxFfDWD33JmkmrqCUC7fmEMmtQatVbF/9b9m9DXvqTHUYFQIPS55/CfOtXRz0yKN4lEIpFIJJKGibe+t97J4NvvQqVWOxvGVptt3PN5MsfzKwnzMTB/Rk+8DRpEaQa5nzzKnxnPU24PRq1VGDSpDe36hWEXdt7442+0f/VHWuSAXach6s238Bo5wqWB7dXYZPdK9tUcYpS+ro0Yr1ZfzSFG6evaiLG5+JI4aJB46zB8DGaLxbkqZrXbeeybvWxPK8HboOHjOzvjp1eoLszg6KzXWZ/zGHa0ePlrGXZ3OwIiPKisqmTWL8/S962VBJeC1dudyPdno+3c2aXp/dXYZLc5+KqvnfTVvHzV1076unx20lfz8lVfO+nL1QZkY3poxMb0Qgj+8eNeVh0qQKdR8em0nnSK9sdcWkzSmz9wtOQmAGLaGhh+X08M7lqsdisfz3+U4bPW4WkEc3gAbectQhcT4+Lnam2ye6X7ag4xSl/XRoxXq6/mEKP0dW3E2Bx8ycb0p2i0xvTvrTzK18npKAq8N6krveICKEwrZNlbiZQYO6HCSp8x/rQZ1R6DmxarsDL3rWkM+2wHWhsY28fSae6X580ovRqb7DYHX80hRunr2ojxavXVHGKUvq6NGK90X3WN62qmUYr0fr0ljbdXHAbglRs6MKZjGIc2ZJC0aB9Wuz8e6iJGT4khtHcPjEYjZquZr1+4jcE/HQGgekBXus6aj+rkKp5EIpFIJBKJ5Nw0WLytPJDL35bsBWDm0Bbc0TOKxEUH2L8uG9ASpd/NyAd64tY+ASEEJlMVKx6+nV7rswCounUE3V95F0WlamgoEolEIpFIJFc9DRJvu9KLmbn4ADa74NYekdzXLZofXt9GfnoFYCfB8zt63nsTqrYDAKgqLWTDjBvocKAYuwLGh++kx8wXG2McEolEIpFIJNcEDRJvD3+5A6Ndx+DWQdwfH8q3/92KudqKQSljpO/bRN/5CLQdDUBZZirbp91CXEYlJg3YXn6MHrc+2CiDkEgkEolEIrlWaJB4K6m20i0+kBnuPiyfsw+AUO0BRvv+D88bnodOtwJQvH8Xh++eSkiJmTJ3Be3/XqLH0IkNj14ikUgkEonkGqNB4q21l4E7Kgzs25cJQFf3JfTxWoR6xN8g4V4A8tesJOPRx/A22sgOUOH59qt0S7i+4ZFLJBKJRCKRXIM0SLyNL9RQaCtHpxMM93ideP0m6PcIDHgSgOxvv6TwpX9isMPhaA3xH35Cy/CujRG3RCKRSCQSyTVJg1I8LdVWAoPhdr9HHcKt+1QY+U8EkP7u/yh58Z+o7bClo47Wny2iY3yfRgpbIpFIJBKJ5OLMnj2buLg4DAYDPXr0YO3atRe8/4MPPqBdu3a4ubnRpk0bFixY0ESR1p4Grby166xhdMV0NNZSaD8Brn8HYbGQ8sJzGJf+BsCyAe6Me+0L2gS0lX3JJBKJRCKRNBmLFy/m8ccfZ/bs2fTv35+PP/6YsWPHsn//fqKjo8+6/8MPP+S5555jzpw5JCQksGXLFu677z78/PwYP378ZRjBuWnQytuAkvscwq3FMLj5E2yVVRy77x6MS3/DpsAXN3hz45vf0iagbWPFK5FIJBKJRFIr3nrrLe655x7uvfde2rVrxzvvvENUVBQffvjhOe9fuHAhDzzwABMnTiQ+Pp5JkyZxzz338NprrzVx5BemXitvNSto5WWlENcTxnyA5VgKqY88jP1EKkYtLLrFj5n3zyFACaC0tNRpZzQa69yQtj520te1EaP0dW3EeLX6ag4xSl/XRozNwVeNlqj5bw16vR69Xn/W/WazmW3btvHss8+6XB81ahQbNmw4pw+TyeTs2V6Dm5sbW7ZswWKxoNVqax3vJUXUg2PHjglAfskv+SW/5Jf8kl/y67J+vfTSS+fUKpmZmQIQ69evd7n+73//W7Ru3fqcNs8995wIDQ0VW7duFXa7XSQnJ4vg4GABiKysrPpIpktCvVbe/P39AUhLS8PHx6dOtgkJCSQnJ9fZZ33smspXWVkZUVFRpKen4+3tfUl91demKe2u5vmoj0195+NKf53ra9Mc5qMpfcn5OMXV/NlRH7ureT7qY1NaWkp0dDSpqan4+vo6r59r1e10zlzdE0Kcd8XvxRdfJCcnhz59+iCEICQkhOnTp/P666+jVqvrFO+lpF7iTXWyD6mPj0+d31BqtbrONvW1a0pfAN7e3k0SY1OPS85Hw31B3eejObzOV+t8NPXcg5yP07kaPzsaYnc1zkdDfld8fX1rZRsYGIharSYnJ8flel5eHiEhIee0cXNzY968eXz88cfk5uYSFhbGJ598gpeXF4GBgfWK91LQ5N3gZ86c2WR2TemrvjSHccn5aLiv+tAcXuerdT6u1t+V+tpdrfPRHH7H6suVPh9NMRc6nY4ePXqwfPlyl+vLly+nX79+F7TVarVERkaiVqv5+uuvuf76650LV1cCihB1r99RVlaGj48PpaWl9VbOVxNyPlyR8+GKnA9X5Hy4IufjFHIuXJHz4Up95mPx4sVMmTKFjz76iL59+/LJJ58wZ84c9u3bR0xMDM899xyZmZnOWm6HDx9my5Yt9O7dm+LiYt566y2WL1/Otm3biI2NvYSjqxv12jbV6/W89NJLF91nvlaQ8+GKnA9X5Hy4IufDFTkfp5Bz4YqcD1fqMx8TJ06ksLCQV155hezsbDp27Mhvv/1GTEwMANnZ2aSlpTnvt9ls/O9//+PQoUNotVqGDh3Khg0brijhBvVceZNIJBKJRCKRXB6unA1ciUQikUgkEslFkeJNIpFIJBKJpBkhxZtEIpFIJBJJM0KKN4lEIpFIJJJmRJ3EW2xsLIqinPXVlLVrriSsVisvvPACcXFxuLm5ER8fzyuvvILdbr/coV0WysvLefzxx4mJicHNzY1+/frVq1p3c2XNmjWMHz+e8PBwFEVhyZIlLj8XQvDyyy8THh6Om5sbQ4YMYd++fZcn2EvMxebihx9+YPTo0QQGBqIoCjt37rwscTYVF5oPi8XCM888Q6dOnfDw8CA8PJypU6eSlZV1+QK+xFzs/fHyyy/Ttm1bPDw88PPzY8SIEWzevPnyBNsEXGw+TueBBx5AURTeeeedJouvqbnYfEyfPv0sHdKnT5/LE+xlok7iLTk5mezsbOdXTeG722677ZIEd6Xz2muv8dFHHzFr1iwOHDjA66+/zhtvvMH7779/uUO7LNx7770sX76chQsXsmfPHkaNGsWIESPIzMy83KE1CZWVlXTp0oVZs2ad8+evv/46b731FrNmzSI5OZnQ0FBGjhxJeXl5E0d66bnYXFRWVtK/f39effXVJo7s8nCh+aiqqmL79u28+OKLbN++nR9++IHDhw9zww03XIZIm4aLvT9at27NrFmz2LNnD+vWrSM2NpZRo0aRn5/fxJE2DRebjxqWLFnC5s2bCQ8Pb6LILg+1mY8xY8a46JHffvutCSO8AmhIY9THHntMtGjRQtjt9gY3WW2OXHfddeLuu+92uXbzzTeLyZMnX6aILh9VVVVCrVaLX375xeV6ly5dxN/+9rfLFNXlAxA//vij83u73S5CQ0PFq6++6rxmNBqFj4+P+Oijjy5DhE3HmXNxOidOnBCA2LFjR5PGdDm50HzUsGXLFgGI1NTUpgnqMlKb+SgtLRWAWLFiRdMEdRk533xkZGSIiIgIsXfvXhETEyPefvvtJo/tcnCu+Zg2bZq48cYbL0s8Vwr1PvNmNptZtGgRd99993kbvF7tDBgwgJUrV3L48GEAdu3axbp16xg3btxljqzpsVqt2Gw2DAaDy3U3NzfWrVt3maK6cjhx4gQ5OTmMGjXKeU2v1zN48GA2bNhwGSOTXImUlpaiKIpL8+1rFbPZzCeffIKPjw9dunS53OFcFux2O1OmTOH//u//6NChw+UO54ogKSmJ4OBgWrduzX333UdeXt7lDqlJqVeHBXAs35aUlDB9+vRGDKd58cwzz1BaWkrbtm1Rq9XYbDb+/e9/c8cdd1zu0JocLy8v+vbtyz//+U/atWtHSEgIX331FZs3b6ZVq1aXO7zLTk1j5DObIYeEhJCamno5QpJcoRiNRp599lnuvPPOa7ol0i+//MKkSZOoqqoiLCyM5cuXX1GNwZuS1157DY1Gw6OPPnq5Q7kiGDt2LLfddhsxMTGcOHGCF198kWHDhrFt27ZrphtFvcXb3LlzGTt27FW/934hFi9ezKJFi/jyyy/p0KEDO3fu5PHHHyc8PJxp06Zd7vCanIULF3L33XcTERGBWq2me/fu3HnnnWzfvv1yh3bFcOYqtRDiml25lpyNxWJh0qRJ2O12Zs+efbnDuawMHTqUnTt3UlBQwJw5c7j99tvZvHkzwcHBlzu0JmXbtm28++67bN++XX5WnGTixInOf3fs2JH/b+9uY5o62ziA/4FCEcSshUrbsTJQZGTCzOZmxc0gDmeY+MoUWRA1y+aicS4LiduS1UyRZWFOt+kXJZBl2TRDw0CZ3VDWuSVMYhUwKIEERacMqCDvWMr1fDDtI+/nQOFQvX5JP3B695z/fXETrpxz2s6fPx/BwcE4c+YM1q5dK2GyyTOmy6Y3b95EUVER3nnnHWfncSlpaWnYvXs3kpKSEBkZiZSUFHz44YfIyMiQOpokZs2aBZPJhPb2dty6dQsXL16E1WpFSEiI1NEkp1arAfz/DJxdQ0PDoLNx7MlktVqxfv161NbW4vfff3+iz7oBgK+vL2bPng29Xq3TTyMAAAzkSURBVI+srCzIZDJkZWVJHWvSXbhwAQ0NDdDpdJDJZJDJZLh58yY++uijKfd9m1LRaDQIDg5GdXW11FEmzZiat+zsbMycORNvvvmms/O4lM7OTri79y+hh4fHE/tRIXa+vr7QaDRobm6G0WjEqlWrpI4kuZCQEKjVasc7tIGH9/KYTCZER0dLmIxNBfbGrbq6GkVFRfD395c60pRDROjp6ZE6xqRLSUlBeXk5rly54nhotVqkpaXBaDRKHW9KsFgsuHXrFjQajdRRJo3oy6Z9fX3Izs5GamoqZLIxX3V9LCQkJCA9PR06nQ7PP/88Ll++jAMHDmDr1q1SR5OE0WgEESE8PBw1NTVIS0tDeHg4tmzZInW0SdHe3o6amhrHz7W1tbhy5QqUSiV0Oh127dqF/fv3IywsDGFhYdi/fz98fHyQnJwsYeqJMVot7t27h7q6OsdnmVVVVQF4eIbSfpbycTJSPbRaLRITE2E2m3H69GnYbDbHGVqlUgkvLy+pYk+Ykerh7++P9PR0rFy5EhqNBhaLBUeOHMHt27cf24+lGu3vZWAz7+npCbVajfDw8MmOOilGqodSqcSePXuwbt06aDQa3LhxA5988gkCAgKwZs0aCVNPMrFvTzUajQSAqqqqnP7WV1fT2tpKH3zwAel0OvL29qbQ0FD69NNPqaenR+pokjhx4gSFhoaSl5cXqdVq2r59O7W0tEgda9IUFxcTgEGP1NRUInr4cSEGg4HUajXJ5XJavHgxVVRUSBt6goxWi+zs7CGfNxgMkuaeKCPVw/5xKUM9iouLpY4+IUaqR1dXF61Zs4a0Wi15eXmRRqOhlStX0sWLF6WOPWFG+3sZ6HH/qJCR6tHZ2UnLli0jlUpFnp6epNPpKDU1lerq6qSOPanciIgmqjFkjDHGGGPOxd9tyhhjjDHmQrh5Y4wxxhhzIdy8McYYY4y5EG7eGGOMMcZcCDdvjDHGGGMuhJs3xhhjjDEXws0bY4wxxpgL4eaNMcYYY8yFcPPGGGOMMeZCuHljU05OTg7c3NwcD5lMhqCgIGzZsgX//vuv1PGGtGfPHri5uTl1n0PVQaPRICkpCdXV1U49FjAxc3Amoflccf1MZYWFhf3q6eHhgeDgYOzYsQOtra1Sx2PsifRkf7M8m9Kys7Px3HPPoaurC3/++ScyMjJgMplQUVEBX19fqeNNGnsduru78ffffyM9PR3FxcW4fv06FAqF1PGmLF4/zmE2mwEAJ0+ehFarRXd3N37++WccPnwY7e3tyMnJkTYgY08gbt7YlDV37lzMnz8fALBkyRLYbDbs3bsXeXl5ePvttyVON3kerUNMTAxsNhsMBgPy8vKwZcsWidNNXWNZP52dnfDx8ZnMmOM20ZnNZjN8fHywevVquLs/vFgTExOD4uJiFBQUTNhxGWPD48umzGXo9XoAwM2bNwEAjY2NePfdd/HMM89ALpdDpVJh0aJFKCoqcrymuroaycnJmDlzJuRyOSIiInD48OF++928eTOeffbZQccb7jLdmTNnMG/ePMjlcoSEhCAzM3PYzH/99ReWLl0KPz8/+Pj4IDo6GmfOnBnL9B3sDcl///3Xb7uQuYqZg9i6XL9+HRs3bkRgYCDkcjl0Oh02bdqEnp4e0RnF1FiogevHPg+z2YzExEQoFArMmjVLVFYha1DIGKG1dkZmsS5duoTIyEhH42Y3Y8YMdHR0jGvfjLGx4TNvzGXU1NQAAFQqFQAgJSUFZrMZ6enpmDNnDlpaWmA2m2GxWAAAlZWViI6Ohk6nw1dffQW1Wg2j0YidO3eiqakJBoNBdIZz585h1apVWLhwIY4fPw6bzYYvv/xyUCMFACaTCXFxcYiKikJWVhbkcjmOHDmChIQE/PTTT9iwYcOY6lBbWwsAmDNnjmObmLmKmYNQZWVlePXVVxEQEIDPP/8cYWFhuHv3LvLz8/HgwQPI5XLBGSciHzB4/ditXbsWSUlJ2LZtm6MZEZp1tDUodIxY48kshsViQV1dHZYvX95ve2NjI65evYqXX355zHNgjI0DMTbFZGdnEwAqKSkhq9VKbW1tdPr0aVKpVOTn50f19fVERDR9+nTatWvXsPt54403KCgoiO7fv99v+44dO8jb25vu3btHRESpqakUHBw86PUGg4EG/oksWLCAtFotdXV1Oba1traSUqkcNFav19PMmTOpra3Nsa23t5fmzp1LQUFB1NfXJ7oOZ8+eJbVaTYsXLyar1Sp6rmLmIKYusbGx9NRTT1FDQ8Ow8xGaUUyNhyJ0/djn8dlnn40562hrUOgYobV2RmYxfvvtNwJA33zzDVmtVmpvb6eSkhKKjo4mmUxG58+fF71Pxtj48WVTNmXp9Xp4enrCz88PK1asgFqtxq+//orAwEAAwCuvvIKcnBzs27cPJSUlsFqtjtd2d3fj3LlzWLNmDXx8fNDb2+t4xMfHo7u7GyUlJaLydHR0oLS0FGvXroW3t7dju5+fHxISEgaN/eeff5CYmIjp06c7tnt4eCAlJQW3b99GVVUVAPTL1tvbCyIatg7Lly+HQqHAL7/8AplMJnquYuYgVGdnJ0wmE9avXz/orJad0IzOzDfa+rFbt27dmLICI69BOyFjxBpPZjEuXboEANi5cyc8PT0xffp06PV6PHjwAEajEUuWLBnydb29veInxRgTjJs3NmV9//33KC0txeXLl3Hnzh2Ul5dj0aJFjudPnDiB1NRUHDt2DAsXLoRSqcSmTZtQX18Pi8WC3t5efPvtt/D09Oz3iI+PBwA0NTWJytPc3Iy+vj6o1epBzw3c1tzcDCKCRqMZNFar1QJ4eEnqxo0bg/KZTKYh63D+/Hm89957uHbtGjZu3Oh4XsxcxcxBqObmZthsNgQFBQ07RmhGZ+Ybbf3YDfwdiannSGvQTsgYscaTWQyz2Qxvb29cvHgRpaWlKCsrQ1NTE0pLSxEbG+sYd+jQIaxbtw7Jycnw8/PD2bNnxzw3xtjo+J43NmVFREQ4bs4fSkBAAA4ePIiDBw+irq4O+fn52L17NxoaGnDq1CnHWa7t27cP+fqQkBAAgLe3d7+b6u0G/rNTKBRwc3Mb8p/uwG0KhQLu7u64e/fuoLF37txx5NdqtSgtLe33fHh4eL+fH62D/V2Tx44dQ25uruOmdaFzFTMHoXVRKpXw8PDA7du3hzy2/bhCMnp7ewvON5rR1o/dwDdfiKnnSGvQ3sAIGSO01s7ILIbZbEZUVNSo97aVl5fDZDIhNzcXP/zwA2w2m+hjMcZEkPq6LWMD2e9ZKi0tFf3a1atXk0qlIiKi119/nV544QXq6ekZ8TUZGRnk7u7uuBeKiKinp4dmz549rnveFi5cSGq1mjo7Ox3bbDYbRUZGirrnbWAd7t27RwqFgiIiIshms4maq5g5iKlLbGwsKRQKamxsHPa4QjM665630daP/f6xoTKLqedAj65BoWOE1nqiMg+lpaWF3Nzc6P333x917Pz58+nQoUNOOS5jbHR82ZS5pPv37+PFF19EZmYmTp8+DZPJhMzMTJw9exZxcXEAHl7Kqaurw2uvvYacnBz88ccfKCgowNdff93vks+GDRvg4eGBpKQkFBYW4tSpU1i2bNmQZw/27t2L+vp6xMXFIS8vDydPnsTSpUuH/NDXjIwMWCwWLFmyBLm5ucjPz0d8fDyuXr2KzMzMMX+bgUKhwMcff4xr167hxx9/FDVXMXMQU5cDBw7AarViwYIFOHr0KIqLi3H8+HEkJyejra1NVEYxNZ4oQrIKWYNCxgDiaj2ezHZubm6IiYkZcX9msxlEhJdeemnEcX19faisrBx0Hx5jbAJJ3T0yNpCQMyfd3d20bds2ioqKohkzZtC0adMoPDycDAYDdXR0OMbV1tbS1q1b6emnnyZPT09SqVQUHR1N+/bt67e/wsJCmjdvHk2bNo1CQ0Ppu+++G/JdlURE+fn5FBUVRV5eXqTT6eiLL74YduyFCxcoNjaWfH19adq0aaTX66mgoGDcdejq6iKdTkdhYWHU29sraq5i5iCmLpWVlfTWW2+Rv7+/Y7+bN2+m7u5uxxihGcXUWEzdHjXSWSwhWYWsQaHrVGitx5uZiKitrY0AUFJS0oj1yczMJABkNptHHFdVVUWBgYEjjmGMOZcb0YC3tjHGGHtsFRYWYsWKFSgrK0NkZOS495ebm4ujR4/CaDQ6IR1jTAi+bMoYY0+Q4uJiJCUlOaVxA4CKigpERUU5ZV+MMWH4zBtjjDHGmAvhM2+MMcYYYy6EmzfGGGOMMRfCzRtjjDHGmAvh5o0xxhhjzIVw88YYY4wx5kK4eWOMMcYYcyHcvDHGGGOMuRBu3hhjjDHGXAg3b4wxxhhjLoSbN8YYY4wxF8LNG2OMMcaYC+HmjTHGGGPMhfwPXo8lxkTkIUYAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<Figure size 700x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "label_fontsize = 12\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(7, 8))\n",
-    "\n",
-    "for Tr in Trs:\n",
-    "    \n",
-    "    Zs = results[Tr]\n",
-    "    idx_min = Zs.index(min(Zs))\n",
-    "    \n",
-    "    p = ax.plot(Prs, Zs)\n",
-    "    ax.set_ylim(0.9, 1.8)\n",
-    "    ax.set_xlim(7, 15)\n",
-    "\n",
-    "    if Tr == 1.2:\n",
-    "        t = ax.text(Prs[-8] - 0.5, Zs[-7], '$T_{r}$ = 1.2', color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))        \n",
-    "    else:\n",
-    "        t = ax.text(Prs[-8], Zs[-7], Tr, color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "    \n",
-    "    ax.minorticks_on()\n",
-    "    ax.grid(alpha=0.1)\n",
-    "    ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "    \n",
-    "    ax.yaxis.tick_right()\n",
-    "    \n",
-    "    ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "    ax.yaxis.set_label_position('right') \n",
-    "    ax.set_xlabel('Pseudo-Reduced Pressure, $P_{r}$', fontsize=label_fontsize)\n",
-    "    ax.spines.top.set_visible(False)\n",
-    "    \n",
-    "    ax.text(0.43, 0.08, '$T_{r}$ = Pseudo-Reduced Temperature', fontsize=11, \n",
-    "            transform=ax.transAxes, bbox=dict(facecolor='white'))\n",
-    "    \n",
-    "fig.savefig('zplot_2.png', dpi=200)"
-   ]
-  },
-  {
-   "cell_type": "raw",
-   "id": "55cc0ba5",
-   "metadata": {},
-   "source": [
-    "Prs[-2]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4898c35f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cbeb3eda",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "bafab9ab",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 129,
-   "id": "0f58a7b3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Prs = np.linspace(0, 8, 81)\n",
-    "Trs = [1.05, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0]\n",
-    "\n",
-    "results = {Tr: [] for Tr in Trs}\n",
-    "for Tr in Trs:\n",
-    "    for Pr in Prs:\n",
-    "        z = Z_factor().calc_z(Tr=Tr, Pr=Pr, **{'maxiter': 1000})\n",
-    "        results[Tr].append(z)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 130,
-   "id": "501b7a3c",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EricKim\\AppData\\Local\\Temp\\ipykernel_13736\\1578593572.py:22: MatplotlibDeprecationWarning: The 'b' parameter of grid() has been renamed 'visible' since Matplotlib 3.5; support for the old name will be dropped two minor releases later.\n",
-      "  ax.grid(b=True, which='minor', alpha=0.1)\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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3v8snPvGJSV3nmhZvQ5yv/kVRvCa/EciMzxe/+EVOnDjB7t27Z9qUGWP+/PkcO3aMgYEB/vjHP3L//fezc+fOa1LAtba28qUvfYm33noLnU430+bMOLfeemvy/1VVVaxZs4Y5c+bw61//mkceeWQGLZsZEokEK1as4Hvf+x4AS5cu5dSpU/zsZz+75sXbr371K2699VZyc3Nn2pQZ4fe//z3PPPMMzz77LJWVlRw7dowvf/nL5Obmcv/990/4Ote0eEtPT0epVI7ysvX09Izyxslcu/zt3/4tL7/8Mrt27SI/P3+mzZkxNBoNc+fOBWDFihUcPHiQH//4x/zP//zPDFt25Tl8+DA9PT0sX748uS8ej7Nr1y4ee+wxwuEwSqVyBi2cWYxGI1VVVdTV1c20KTNCTk7OqC81CxYs4I9//OMMWXR10NzczNtvv80LL7ww06bMGP/wD//AV7/6Ve69915A+rLT3NzMo48+Oinxdk3HvGk0GpYvX55c+TLE1q1bWbt27QxZJXO1IIoiX/ziF3nhhRd45513KCkpmWmTripEUSQcDs+0GTPCTTfdRHV1NceOHUtuK1as4JOf/CTHjh27poUbQDgcpqamhpycnJk2ZUZYt27dqLRCZ8+epaioaIYsujp48sknyczM5Pbbb59pU2aMQCCAQpEqvZRK5aRThVzTnjeARx55hE9/+tOsWLGCNWvW8MQTT9DS0sKDDz4406ZdcXw+H/X19cmfGxsbOXbsGA6Hg8LCwhm0bGZ46KGHePbZZ/nTn/6E2WxOemitVit6vX6GrbuyfP3rX+fWW2+loKAAr9fLc889x44dO3jjjTdm2rQZwWw2j4p9NBqNpKWlXZMxkX//93/PHXfcQWFhIT09PXznO9/B4/FMypPwfuIrX/kKa9eu5Xvf+x4f+9jHOHDgAE888QRPPPHETJs2YyQSCZ588knuv/9+VKprV3rccccdfPe736WwsJDKykqOHj3Kf/7nf/LAAw9M7kLTtfx1NvP444+LRUVFokajEZctW3bNpoLYvn27CIza7r///pk2bUYYaywA8cknn5xp0644DzzwQPI9kpGRId50003iW2+9NdNmXVVcy6lCPv7xj4s5OTmiWq0Wc3Nzxbvuuks8derUTJs1o7zyyiviwoULRa1WK5aXl4tPPPHETJs0o7z55psiIJ45c2amTZlRPB6P+KUvfUksLCwUdTqdWFpaKn7jG98Qw+HwpK4jiKIoTp+mlJGRkZGRkZGRuZxc0zFvMjIyMjIyMjKzDVm8ycjIyMjIyMjMImTxJiMjIyMjIyMzi5DFm4yMjIyMjIzMLEIWbzIyMjIyMjIyswhZvMnIyMjIyMjIzCJk8YaUDfxb3/rWNZst/nzk8UhFHo9U5PFIRR6PYeSxSEUej1Tk8UjlUsbjqsvztmvXLn7wgx9w+PBhOjs7efHFF7nzzjvHPb+zs5O/+7u/4/Dhw9TV1fHwww/zox/9aFJ9ejwerFYrbrcbi8VyaTfwPkAej1Tk8UhFHo9U5PEYRh6LVOTxSEUej1QuZTyuOs+b3+9n8eLFPPbYYxM6PxwOk5GRwTe+8Q0WL158ma0bzeOPP37F2l3JvqbK1X5fV3Isptrf+3U8rvTzK4/HzPQ1VeTxuPS+ZsN7bKpc7eNxpf+2XNXlsQDxxRdfnPD5Uy1P43a7RUB0u92TbrtgwYJJt5lquyvV15Uej6t9DOXxSGWq43El72uq7d6v4/F+/eyYarv363hc7e+x9/N4XOm/LddkddhwOJwyxzwwMACA2+2e9LXi8Tgej+eKtLtSfQ2d+367r6m2kccjlamOx5W8r6m2e7+Ox/v1s2Oq7d6v43G1v8fez+MxlTZDmiORSEyqHXBtet6++c1vjlt0XN7kTd7kTd7kTd7k7UptDQ0Nk9ZH16Tn7Wtf+xqPPPJI8me3201hYSHNzc1YrdYJX0cURUKhEDqdDkEQLms7ua/Z1ddssPH92tdssFHu69qw8f3a19VkY8jno62mmuaTJ2g9eQyfy5ly3GC1U7hwMYVViylYsBCd2UJ/p5+W0y5aa1x0N3kRE2LyfI1ORW6ZheJFGRSUO9CZ1GPaFPf78b+3B9/27QT27CHh9yePKawWjNffgOnGDRhXr0ah0415DbfbTVFREWlpaRMeiyGuSfGm1WrRarWj9lut1kmLN61WO6UHcbLt5L5mV1+zwcb3a1+zwUa5r2vDxvdrXzNpYyIep7P+DM0njtJ84ihd9XWI4vC0o9FgIH/BQoqqlpBTXknu3HnEYyLttf2ceddJ08lWfK7hsCmdyoAj10jRwjSKq9LIKrEQiUbGtDHmdOJ95x28b79NYM9exGgUAAOgzM7GfPPNWLZsxrBiBYJ6bNE3FpMZiyGuSfEmIyMjIyMjc/UjiiL9XR00HD5Ie001radOEAkGU85Jyy+kePFSihYtI39BJWqtDndvgPqjXRx98wTtZweIR4cFnlKtIG+eneKqNIoWpmFJ16f0R3T42pG2Nrxvv4337bcJHjkKI+LTNEVFmDffjOnmm6GsDL3BMCkh5o/6L37SOFx14s3n81FfX5/8ubGxkWPHjuFwOCgsLORrX/sa7e3tPP3008lzjh07lmzb29vLsWPH0Gg0VFRUXGnzZWRkZGRkZC6BoM9L68njNJ84RtOJo3h6u1OO68wWiqqWULxoKUWLlmJOSyceS9BRP8D+V1ppOemkvyuQ0sbk0FK8MJ2iqjTy5ttRa5Rj9i2KIuEzZ/C++y6+t7cRPnMmte+KCsybb8Z8881o5s5FEITktO5ECMfDvNv2Lq83vs72uu2TGJVUrjrxdujQITZu3Jj8eSg27f777+epp56is7OTlpaWlDZLly5N/v/w4cM8++yzFBUV0dTUdEVslpGRkZGRkZka8ViUzrNnaK4+StOJo3Q31KdMhSqUKrLL5lO6ZDnFi5eRWVyKoFDg6w/RfNJJ88kTtNX2Ew3Hk20EhUBWiZmSRRkUVaXhyDGO6xUTYzECh4/g3fY2vm3vEG1vHz6oVGJYsQLzTTdhvmkT6ry8Sd9fNBFlX8c+3mh6g20t25Iet3g8fpGW43PVibcbb7xRcluOw1NPPTVq34XOl5GRkZGRkbl6EEURZ1sLLdXHaK4+RuupaqLhVM9VWn4hRVVLKFq0lLwFlSQQUKs1dJ/zsPelc7SccuJsT5121Fs0FC1Mo6gyjfxyG6IiPm58XSIQwPfee/je3oZvxw7iI1KFCTodxnXrMN98M6YbN6Cy2yd9j/FEnCM9R3i98XW2Nm9lIDyQPJZtzObW4ltZl7aO1aye9LXhKhRvMjIyMjIyMu8vfP0umquP0XjsMG2nq/H3u1KO6y3WpFgrqlqCOS19sF2Y+sN9NJ3opeOsm0hohLdKgKxiiyTYFqaRUWBGUEhCTZrKTPVsxfr68O3YgXfbO/j37EEcke9VabNh2rgR06aNKJcvx2C3T3ohgSiKHO89zhtNb/Bm05v0BfuSxxw6B7cU38KtJbeyOGMxCkExpdyyQ8jiTUZGRkZGRmZaiYSCtJ0+SXP1MVqqj9HX2pxyXKXWkLegMinYMgqLERQK4vEEXfVuTu6qp/mkC2e7L6WdzqSmsNJBUWUaBRUO9CbNBe0InzuHf/t2vNveIXjsGIyYqVPn50vToTffhH7pUgSValLxayAJttPO07xa/yrb2rbR4e9IHrNoLNxcdDO3FN/CyuyVqBTTJ7lk8SYjIyMjIyNzScRjMboa6pJToZ11tSRGxnQJAlklc8gtr2TO0uvIK69ApZGEl9cV4vR7nbScctFa6yJ6nncts8hM3nwrpUuyyCyyoFCM7xET43GCx4/jfXsbnm3biDWnikZdZSWmmzZhvukmtPPmTSlNhyiKnO0/y5tNb/Jm05u0eIfj8A0qA5sKN3Frya2syVmDWjnxlCGTQRZvMjIyMjIyMpNCFEVc7a10namh5eQxWk+fJBpKTeFhzcqmaOESCquWULhwETqTmVAohEqpprPeQ/NpJy2nXPR3nhe7ZlZTUDHsXdMZ1RdM7psIBPDv2YN32ztS/Fp///BBtQrjqtWYb9qEaeNG1NnZU77ncwPneKPpDd5oeoNGd2Nyv06pY13OOm6fczvX51+PTjV2Ut7pRBZvMjIyMjIyMhfF09tD88ljtFQfp/XUCfwD/SnHdWYLhZWLKFy4mKJFS7FlSUJJFEXcPUHOHmyj+WQvnfUeYpHh1aSCAFklVmk69LzYtaH25xPt7sG3Ywe+d97Bv3cvYiSSPKawWDBtuAHtunXYbroJldk85XtucjdJHrbmN6nrr0vu1yg0rM9bzwdKPsANeTegiCsmnXz4UpDFm4yMjIyMjMwoAh43raeqaTl5jJaTxxno6kw5rtJoyCuX4tYKq5aQWVSCoFAAEAnFaDzeS8spFy2nnXj6UuPIjFYNhZVpFFamkV9uR2e88PSiKIqEamrwbd+Ob/sOQidPphyX4tc2Ydq4CcPyZaBSEQqFUI5TmupCtHpb2VG3g7ea3uJM/3CeN5VCxdrctXyg+ANsLNiISWMati0+8Ti56UAWbyMQRXFSaUeGzp9sqpKptJP7ml19zQYb3699zQYb5b6uDRtnW1+RYIC2mlO0njpBy6kT9DadSzlXUCjInlNG4cLFFFQuwlFYgtFslhLVJkR6W3201rhoOe2iq8FNIj5si0IpkD3HSk6ZmTmLs0jLN6V4qcayOxEOE9i/X1ohun078a4RyXoFAV1VFaaNN2LedBOasrmjrjeZ8Wj1tvJW01u81fwWNa6a5H6VoGJVzipuKb6FTQWbsGgto2y+lLGfKte0eHv88cd5/PHHk4nywuHwpFaZDLWZipt0Ku3kvmZXX1NtJ/c1c+3kvmZXX1NtJ/clEYtE6G44S9OJo3TV1dJzrh5xRPknAEd+AfkLqsivqCK3vAKN3pA81t/rpfG4m/baATrODhDyxVLamtO15JfbyJtvI6fMilqrHIxdUxMekaZjJHGnk8C77xLc9S7BffsQR5TCEnQ6dKtXY7jhBvTXr0eVLqUTEQfvfbLj0eZrY1vrNra1baO2vza5XykoWZG5gpsLbmZD3gZsWhtDHY2nEaby+4p0np7U+SO5psXbQw89xEMPPYTH48FqtSYL306UIaWt1WonXWR3su3kvmZXX7PBxvdrX7PBRrmva8PGq62veCxGd0MdLadO0HrqBB1na4hHoynnWLNyKKxcRMHCRRRUVGG0DSeojUXjdNa7aa1x0XraNSpJrlqrJG+ejYIKB4UVDqyZhpTjY9koilI5Kt+OHdJ0aHV1SjoPVWYmxg0b0Kxfh+3661Hq9UyE8cZjPA+bQlCwMnslmws3sy5rHTnWnMvzew654dSLcOy3RBsOTOj6Y3FNi7fzEQRh0sp5qM2VaCf3Nbv6mg02vl/7mg02yn1dGzbOZF+JRJyexnO0Doq1tppToyoZGO0OcssrKVm8jKKFi7FkZCaPiaKIq8OfFGvtdakF3gEyCkwUVKZRWOEgu9SKUqW4qI1iOIx/cDrUt2Mnsa6ulHN0lZVSwtyNN6IbrFE+FL82lfFo8bYkBVuta9jDNiTYthRv4abCm3DoHIiilOdtWn/PiQQ07YKjv4WaVyAmeRNFxq6vOhFk8SYjIyMjI/M+QEwk6G1ulBYZnDpOe80pwoFU75jObKGwooqChYspXLgIW3Yu4XA4uVIy4InQWuOircZFa40LvzuS0t5g1VC4wEH+AjsZJUbsGeYJiZxoZyfeHTvwbN9O6MBBxBHTj4JOh3HtWkwbNmC68UbUWZkpbacSG9bobuS1htfY3r6ds/1nk/uVglLysBVvTgq2y4arEY4/B8eeBfeImuwZ5bD0U1B0K3y/bEqXlsWbjIyMjIzMLERMJKQaoaeqaT19grbTJwn5vCnnaPQG8isWSlOhlYuSlQyGiIZjtJ8ZoLvBR2tNP8621IoGSrWCvDJpKrRggQNHrlTgfchDNa5tg8lyfTt24tu5k/CZMynHVTk5mDfeiOnGGzGsXIliCqtCU/oTReoH6tnavJWtzVupH6gf7mtw0cHmos1sKtyEXTf5WqUTJuyD03+SBFvz7uH9WitU3Q1LPgV5y6T8KHJ5LBkZGRkZmfc3oiglxm05dYK2U9W0nq4m6PWknKPW6shbUElBRRWFlYvILJmDQjk8PScmRHpbvNJUaI2Lzgb3qKnQ9AITBQsksZYz14pKPbHpvfjAAL7d7+HbuRP/rl0pxd4RBPSLF6Ndtxbb5s3o5s+f9FTy+YiiSK2rNinYmjxNyWMqhYqVmSv5QOkH2FS4CavWekl9XdiQBIqWPVDzPJz6E0SHvJ0CzNkIi++DBR8E9cTi9SaCLN5kZGRkZGSuQkRRxNnWQuvpatpOn5TEmifVW6PSasmbX0FBRRWZc+dRUF6JSp2aM83TF6Sttl+aDq3tJ+RPXaRgtGkksVbhIH++A4PlwvVCR9oXqq3Fv3MXvl27pNqhI1arKiwWTOvXY7pxA8brr0dps12wUsJESIgJTvSe4O3mt3m75W3afe3JYxqFhrV5a9lStIUb8m9Ak9Bc3sS5Q9Oix59FOzBiWtQxB5bcB4vvBWv+ZelaFm8yMjIyMjJXAUPToK2DBd07ztaMFmsaLbnzF1BQUUVBRRXZc8tQqtTJaUylSkXIF6XtTD9ttS5aa/vx9KaWrVLrlOTNs1OwwC4lyLUq0Ov1ExI5cZ+fwL69eHfuwrdzJ/GenpTj2rIyTBtuwHTjjeiXLEFQDcuMqeY1iyViHOo5xLud77KtdRs9geE+dUod1+dfz82FN3ND/g2piXMnmfprQoQ8cPolOPY7aNkDgACIGhMsvBthySehYKU0LXoZkcWbjIyMjIzMDJBIxOlraab1VDVtNdW01Z4mdN406HhibSTRSJzO+gGaTvbSVe+lt9UrJT8bRFAIZBVbKFhgp2CBg8wSC0qlFPd20dg1USTS0IBv5y58775L4PBhGJFeRNDrMa5eLS02uOF61Lm50zAyEIlH2N+5n20t23in9R36Q8OluIxqIzfk38Dmos2sy12HQW24wJWmgUQcGndKgm3EatGhaVFx8ScIFd+Ezuy47KJtCFm8ycjIyMjIXAES8TjdjfW01ZyireYk7bWnCPtTV4OqtFry5i0gq6yc0sXLxhRr8XiCniYvbbXSNGhXo5tELNWr5cg1kl9up6DcQW6ZDY1+4n/uE36/lMpj1y78u94l2tGRclxTVITxhuvRrF6Ndd26KZWgGotANMB7He/xdvPb7GrbhS86vHjCorGwqWATm4s3szpnNRrlxKZ2L4meWjj+Ozjxf+AdMQbp82DxJ2DRx8GaJ+WluxxevgsgizcZGRkZGZnLQCwapfNsDT0NdbTVnKTjbC3R0PlTmHryyqWYtfwFC8kqnYtCqUyJDRMTIs4OP221LtrP9NNeN0A0FE+5jsmuJafMQlFlOvnlDoxW7YTtFEWRcF0d/nd3j+1d02gwrFqF6YYbMN1wPZqioqTHTqGdeD9j4Q672dG6g20t29jTsYdwfLhSQoY+g02Fm7ip4CYW2hZiMpguX/zaEAEnyqO/g1PPQ+ex4f06Gyy8W4ply1t+xTxs4yGLNxkZGRkZmWkgEgrScbaW9pqTtNWeorPuzKgKBlqjkbzySgoWLCR/wcJRq0EBEokE7t4gDU1O2moHaD/bT8h3/nVU5M+TYtbyyx1YMnQp+douRtzrxb93L75BwRY/L1GuuqAA0/XXY7zheoyrVqGYYGWDidDl72J763beaXmHQ92HiIvDQjTflM/NRTdzU+FNLMpYhEJQXL74tSFiYTj7hrT4oO4tNInBMl8KFZRtkbxs824B1aUJ1elEFm8yMjIyMjJTIOj10F57mrbaU7TXnKS7sWFUbVC92UL+goXkV1SRv6ByVJ61IbyuEG21/bSf7af9TD++/tRanSqNgtwy2+BCAwfp+SYExbBIu9hiADGRIHS6Bv/u3fh2v0vw6DGID4smQavFsHIlpuuvl7xrxcWTH5ALcM59jm3N23i7+W1Ou1JrepbZy7ip8CZuKryJ+fZLTyEyIUQRWvdLgu3UC1LZKqTFB4msRQhL70OougeM6ZfflikgizcZGRkZGZkJ4HX20tjYQHvtKdprT+Nsaxl1jiUjk7zySvIXVJI3vwK9I33MlZx+d1iaAj3TT9uZfjx9qZ4lhVIgu9Qqedbm28kstly09NT5xJxO/O+9h2/3bvy73yPucqUc15SUYFy/HvXKldjWr5tw3dCJkBATVPdV807LO7zT8k5KDjYBgcUZi5OCrcBSMG39XhRngxTDduL30N84vN+SB1X3IC76OGFLiVTnfIanRi+ELN5GMFRcdrLnT3b581TayX3Nrr5mg43v175mg41yX1e/jWIiQV9bCx21p2k/I23evt5R5znyCsibX0HegkryyytH1QYNhUKIokjAE6H9bD8dZwdoPzvAQHcg5TqCQiCzyEzePBt5823YcrWYLMYU0Xchm0VRJBGJ4D9+HP977+Hf/R7hmpqUcxQGA4Y1qzGuX49x/Xo0+fnDtTy12ksex0g8woGuA2xv3c721u30BfuSx1QKFauyV7E+ez1bSreQYciY0H2N19ek7As44eQLUP1/CG0Hh8/RmGDBHbDoXiheDwql1GbwdzalvibBVFOnwDUu3h5//HEef/xx4oOu43A4POl59XA4PCUX71TayX3Nrr6m2k7ua+bayX3Nrr6m2m6sNrFIhJ7GBjrrauk8W0N3/dlRdUEFhYKMohJy5i0Y3MrRmy0p5wz9DQl6o3Q1eGg746K30c9Ad+pCBQRIyzWSU2Yhp8xKVqkZjU6Vcp1wOHXq9HxEUSTW0kJw716Ce/cROnQIMZAqCjXl5ejXrEG3ZjW6JUsQBhP4JkbYeilj74162dO5h53tO9nXtQ9/bHjMjCoj63LWsSFvA2ty1mBSm6SFGArd5f9bGw2SqHkVse5lhHPvIAzGsYmCgkTxBuKVHyVe9gHQGKXzI1EgOrW+ptimzem5+EnjcE2Lt4ceeoiHHnoIj8eD1WpFq9VKrtIJMqS0tVrtpH5pU2kn9zW7+poNNr5f+5oNNsp9zbyN8XCIzrpa2mtP03Gmhu5z9STisZRz1VodOfPKyZtfQc68chwFxZhttjH7CngidNQNSJ61un76OwOjzknLN5FXJnnWcuba0BnVo8652H3F3W78+/fj3/0e/vfeI3ZeGg+lw4Fx3VrJu7Z2Lar0C8dsTWUMO3wd0oKD5nc42nuUmDg8bpn6TDYUbGBTwSauy74uJaXHZf89J+LQtBuq/w9qXkYID9d5FXOWwKKPwcK7UZiyUABjjf7lfu5FUeRY6wBPvtfEq4fPTej6Y3FNi7fzEQRh0sp5qM2VaCf3Nbv6mg02vl/7mg02yn1duXZiIoGro52OszW0n6mhvfYUA10do84zWG3SFOhgzFpGUUlyJWhyenGwL787PCjUBug4209/1xhiLc9IVqmZwop08srs6Exji7UL3RfRqFTgfc8e/Hv2EKo+mVKCSlCr0S9fLgm1FcuxLF48avXqRPsabwwTYoIaZw3bW7ezo3UHZ/pTi8zPtc1lY8FGNhVuoiKtAoUwfmzetP+eRRG6qqUYtpN/BG/nsN2WPIRF9yIs+hhCZvml93UJbSKxBK9Wd/DUe00cb5MWRyQS8rSpjIyMjIwMANFwiK6GOjrO1NBxtoaOs7WEfN5R56XlF5I3v4Lc+QvIm1+BNSt73D++XleI5tO99Db56agbwN0THHVO0rM2z05umQ2tUTXpWp6iKBJuaMCzcxe9Bw4QOHhw9FTonDkY163FtG4dhuuuQ2EwDIvLMVayToVwPMz+zv3saN3Bztad9ASHS1IpBAVLM5cm49cKLYXT0uek6G+G6j9A9fPQOyK2T2eDyjsRqz5GOHMJOr1hRhce9HrD/HZ/M7/d30KvV5oG1ygVfGhJLncvtLP2R1O7rizeZGRkZGRmNd6+XjrqaiWhdqaW3uZzJOKpSWxVGi3Zc8vILVtAeskcihYuwnBevNoQoiji7g3SUTdAZ53kXfM6z4vREiA930RemSTUcstsozxrEw1Ij/b0ENi3D/+evfj37iXW3Z1yXOlwYFyzBuPatRjXrkGdkzOh606WvmAfu9p2saN1B/s69xGMDQtUvUrP+rz1bCzYyPV512PVWpPC9Irh75Pqilb/QUrzMYRSC/M/AFUfg7LNUj428cpXPRjJsdYBnnqvkVerO4nGpecgy6Ll06uLuHdlIekmLW63+yJXGR9ZvMnIyMjIzBpi0WhyYUHH2Rraz9bidzlHnWe0O8ibt4Dc+RXkzi8ns7g0pYD7SNEhJkRcnZJHraN+gI66AQLuSMr1BIVAWr6B/HkO8ubZyZlrRWuY+DToSOI+H4GDB/Hv3Utg717CdfWpfWk0aJcuxbx+PaZ1a9GWl0+bR20koihytv8sbze+zXtd71HdV51yPNOQyY35N7KxcCPXZV+HVqlNaXtFCPug9lU0x5+T6osmE/oKUHIDVH0UFnwI9LYrY88FCMfivH6yi6f2NHO8dSC5f2mhjc+tK+HWhdmoldPze5TFm4yMjIzMVYvX2UfH2Vo666Tpz57GBuKx1IUFgkJBZnEpuYMrQPPmLcCcnjHuVGU8lqDrnJvOejed9QN0NrgJB1KvqVBJxdyHvGpZJRYSxCY1BTpEIhIhdPx40rsWrK5OSZCLIKCrqMC4VvKu6ZYsIQJT6utiDE2H7mrbxc62nXT5UysrVKRVcGPBjdyYfyPljvJp739CxMJQ/7bkYTvzBkIsSDKKL3cpVN0DlXeB5fJ4ICdLjyfEr987x/8d6aDPJ4l+jVLBBxfn8Nm1xSzKt017n7J4k5GRkZG5KohGwoNetTNSyo66M/jG8KrpzRZy5pWTW1ZOWnEpheWVaC6QYDYSjNHVKIm1jvoBuhs9xKOplRBUWiU5pRZy5trIm2cjs9iCSj0c+C957GLnX3pMxHicUE0t/n178e7ZQ/jIUcTzpvDUhYUYV6/GuHYthlUrUdntKX1N55RfT6AnKdb2d+5PmQ7VKrVcl3kdm4o2saFgA5mGzAtc6TKSiEPTu5Jgq3klWfEAQHTMIbbgTlRL7kXImDcz9p2HKIocau7n13uaeONkF7HE2FOjlwtZvMnIyMjIXHFEUaS/s4Ou+jN01J2ho64WZ0vTqFg1QaEgvbCY3LJycueVkzOvHFtWDoIgJKdA1efFXfkHwnQMetQ66wdwtvk4f5ZPZ1KTM8ea9Kyl55tQTHFKSxRFIg0N+Pfuw79/H4EDB0l4UnN4KdPSJLG2ZjWG1WvQ5OdNqa+JEE/EOek8yc7Wnbzb/i61rtqU41mGLDbkb2BDwQZWZK1AiAmXxct3UUQR2g5Kiw5OvwS+EbF+5lxYeJc0LZq9mFg4jOpKxteNQzAS5+Xj7fx6TzOnO4d/x8sKrHxufSkfmMap0QshizcZGRkZmctO0Ouhq/4snfVn6Kw/S1fdGUJ+36jzjDY7OWXl5JTNJ7esnKzSuaPE2UjEhIiz3UfXOU9yCnTU4gLAkq4jZ46N7DlWHAU6sovsKKYYRyaKItHmZvz7DxDYvx//wQPEe/tSzlGYTBhWXod62TJs19+Adl7ZZRVHnrCHnS072duzl/fa36M/3J88JiCwMH1hUrCNrB8qiiKh2BUM7BdF6Dwu1RM9+SK4R5QY09uh4sPStGjhWhj6/Vyp+LoL0OIM8Mz+Zn5/sBV3UErmq1MruHNJHp9eXUSpQzNpARyXKyzIyMjIyFwtRCNh+pobB8XaWbrqzzLQ3TnqPKVaTVbJXLLnziOtqISiyios6ZkX/AMYCcXoafIkY9a6zrmJhM7z1gngyDORO9dGzlwrOXNsmOzSFNbIfG2Tuqf2dry7d+M6cpTAgQPEulJjxQStFsPyZRhWr8G4ehW6igpQKgmFQmgvg1draLHBu+3v8m7buxzvPU5cHB4Hk9rEurx13JB/A+ty15GmT5vW/idNTy2c/CPaky8guEYs0NCYoPyDsPBuKL0RVJpxL3GlSSREdp7t5em9Tew425vUkAUOPZ9eXcTHVhRgM2iSz9RECScS/KGrnx/XNEzZNlm8ycjIyMhMmUQijrOtla6Gs3TV19FZfwZna/Oo6U8Ae04eOXPnkV02n5y588koKh61AnSkyBFFEa8rRPc5D50NklDra/MhnpfcVKVVkl1iIXuOlZw5VrJLrGj0l/bnLdrRIXnWDkhbtL099QS1Gv3iRRhXrsKwahX6pUtQaFKFx3SvyPRFfOzv3C8JtvZ36Qn0pBwvsZRwQ/4NbCjYwJLMJagVU1sNO204G6SaoqdegJ7TCIAAiCodwrxbYOFHpdQe6vHjFWeCgWCUVw528My+Flpcwzn2bpiXwf1rirhxfiZKxeTFuDcW59ftfTzR1ktPJEYiGLl4o3GQxZuMjIyMzIQQRRF3dxdd5+roqj9LV0MdPY0NRMOjvQ4Gq43sufPImSOJtezSMnQm0wWvH48m6Gvz0dngpvucJNb87tF/4Ex2LdmDIs1RoCO31IFSNbmqAucTbW/Hf/AggQMHJbHW1pZ6glKJtrIS05rVGFetQr90KYoLLJKYDoa8a7vbd7O7fTfHeo6llKLSKXWsylnF9XnXsy5vHWmqtJmJXRtJf/PglOgL0HVieL9CjTh3E9F5d6Be+GHQjZ1jbyapbnPzm31N/OlYB+GYtKDFolNxz4oCPrW6iJJ045Su2xuJ8ovWXp7q6MMzeN1crZpPZ+bwyBRtlcXbCIbqk032/Ml+u5pKO7mv2dXXbLDx/drXbLBxNvSVSCTwOvtobW+h+1w93Q11dJ2rJzxGnJpapyerZA5Zc8pwFBRRuGAhlozR058jbRBFEV9/mO7GwSnQhgGc7X4SsVQ7FQqBtHxT0quWVWLB7NAlryFVFRAmfH+iKJJIJAg3NxM8dIjAwUMEDh4cVSMUpRLdwoUYVl6HYeVK9EuWEFEqU8TRxfqcyth7Ih72dexjV+su9nXvG+VdKzQXsj5vPdfnXc+K7BXJ3GtDYzEj77GBFjj9Jzj1IkLHkeFzBKU0FVr5ESj/IKLOSiwUQqXRTSqO7XI+96FonFdPdPKbfc3JslUAFTlmPr2mmA8tzsGgUSWvOZm+GgNhft7Wy+87XYQHj5UZtHyxMJM7M20EvV5ZvE2Fxx9/nMcff5z4oHs/HA5Pat56qM1UvuVMpZ3c1+zqa6rt5L5mrt213Je/30VPUwO9TefobTpHT2MDQc/oDPAKlYq0giIyS+aQVTKXzNK52HJyUSgkz9dQjFc4HE5pF4vE6Wvz09vso7fJS0+zl4A7Our6OpOKzGJzcksvMKLSpHrVRn5OT+TeRFEk2tRE+MgRQkeOEDx0mERPqihCqURTsQDd8uXoVqxAt2QJCuOwpyUKhKcQK3cx+xJigtr+WvZ27WVf1z5OOk+mxK5plVpWZK5gTfYa1mSvocBcMHxfUZFQdHJjMRUbx0LwtMHJl6D+NYTOkYJNQaJwLfHyDxOfdxsYRsTahcNXzXPf7Arw+0PtvHCsE3dQ8maqlQK3VGRy96IMVs0ZzBOYiE0oRczIvk74QvxPh4s3XF6GEtIsNel4MNfBzXYTCkEgEYmMeo9MhmtavD300EM89NBDeDwerFYrWq12UqU+hpS2Vqud1EM1lXZyX7Orr9lg4/u1r9lg40z2JXm8XPScq6e7sZ7uc/X0NDbgH+gf1VZQKEgvKCJrThnZpXPJKi0jvbAIpWrsWKqhvjRqDe7eEN2NbrqbPPQ0eiSv2nmxaoJCID3PSGaJBUe+noL56Vgz9Jc8jmI8TvjMGQKHDxM8dJjAoUPEXa7UxioV+kWLMFy3AsN116E/T6xNtK+p2Ncb6GVv5172dOxhb8felJWhIMWurcxayYZCKZWHTnXxv0tX5Jka8rCd/hNC+6HhawgKKFonedgW3IHCmIECOP8pmen3WCye4J3aHn67v4VddcOrg/Nsej65qpB7VuSTZtRMqR5tIpFgrz/CT1t72T0w7J2+2WHmbwozWW01jrqeLN6mCUEQJv/tY7DNlWgn9zW7+poNNr5f+5oNNl6JvkRRxNvXS9vZGvrbWuhpbKC7sYGAe2CM6ypIKygkq2QuWaVzyCydiyUrB5PFetG+Ap4IPU0eupuk6c++Fj/h4Ghvhd6ikRYWlFrJLrWQUWhBrVUmp/ymEq8lCAJiJELo5EkChw5Lgu3oURK+1OldQatFv2QJ+hXLUVVVYV25EqXBMOm+pvJ7jiQiHO05yp6OPezp2MPZ/rMp5xjVRlbnrGZt7lrW5a0j15g7pfG4LM9Uf9PglOhLMHJKFIFEwWoUVXcjLPgQmLNmzsaLtOnxhnnuQCvPHWyh0x0aPAYb5mXw6dWpCxBEUZxUX9GEyMs9AzzW3E1NQBJjKgE+kmXnbwoyWWAaPy5ysmMwElm8ycjIyLwPSCTi9Hd20DM45Tm0jZVLTVAoSMuXhFpmyRyy58wlo6gEtXZEvU9x7PQH0XCc3hav5FFr8tDd5Bkzr5pSrSCz0ExmiYWsYkmwmeyT87iMR9ztJnD0KIHDh/EfPETk1CnEaOoUrMJoRL98GYYV12FYsQL9wkoEzXBaB8VlTPgqiiL1A/Xs7djL7rbdHO09Sig+PEYCAhVpFUmxtihjUcrK0MnGn007zoakh43OY8P7hzxsFR+G8g8SUduk2app+J1ON4mEyJ5zLv5wpJOtNT3EB72+DqOGe1bkc9/KQorSprYAAcAfi/PbTif/09pLe1h69gwKBZ/OTePzBRnk6y5vyhNZvMnIyMjMMmKRCM62FnqaGuhpaqSnqYG+5qYxV30qlCoceflkzykb9KrNJb2oGLXm4qV74rEEPc1eelu89DR56Gn24Orwj441F8CeZSCz2IIjT09eWRrpBSaU05BpXhRFou0dBI8cJnD4CMEjRwjX1Y06T5mRjmH5CgzLlmFYsRzt/PkIyktbgToZ+oJ97O3Yy77Ofezt2EtvsDfleKY+kzW5a1iXt45VOatw6BxXzLYJ0VsLp1+Gmpeh++TwfkEBxeuh4k5YcAeYBstnidNbwmu6cPkjPH+4lWf3t9DkHE7zcV2xnU+uKuLWqmy0l7AyuScc5Zdtvfy6w4k7JsUmpqtV3J9t4y8Ks3Borkx6Flm8ycjIyFzFBDxuepsa6W0+R0/TObqbGujvaEdMJEadq9JoySguIbN4Dlklc8gsLsWRX0gsHr/oFFwinqC/K0BPs4eeZi89zR6cbT7isdFeIKNVQ2axhaxBr1pGkQWtXnVJ059DiNEoodpagkePEjhylODRo8S6u0edpykuRr9sKapFi7CuXo2mqGhavHoTJRANcLj7sCTWOvdS158qKHVKHcuylnFdxnXcUHgDZfbLW2Fh0oiDlQ5qXkF76k8IrhH2K1RQcoPkYZt/O5gyZs7OCSCKIgcaXTx7oIXXq7uIxKX3hlGj5CPL8vjU6iLKsy8tNUmdP8TPW3v4Q1c/kcFvL3P0Wh4szOCjmXaIRtCpr5ykksWbjIyMzFXA0LRnX0sTPU3n6G1upLfpHL5+15jn680WMkvmkFFUQmZxKZnFc7DnDq/6HEIURWLnJcxNJET6u/z0tnjpbZZWfva1eolFRwtCrUFFZrGFzCIzmUWSWDPapq/gdqy/n+Cx43gPHSRyoppQdfWoIu6oVOgqKzAsW45+2VIMy5ahSktLikXNFchtFkvEqHZWc9R5lL2deznee5xYIjWub4FjAWty17Amdw1LM5eiUUw++P2ykkhA2wGp8HvNyzDQMpw4V6lBmLMJFnwI5t8KhqvMMzgG7kCUPx5p49kDLdT3DIcHVOVZuW9VIZvn20mzmKb+RUIU2ef287OWHt5yDtcxXWEx8FBhJrekW1EMLgIKjV44fUG83hpOnvq3KdkFsniTkZGRueIEvR466utwd7bT19pEb3MTztZmYtGxM67bsnPILColvagEW24+efPKMTvSJvRHKRFP0N8ZwN3VT2+rj95mL31tXmKR0UJNrVOSWWgmo8hCRqEJa5aGjHzblGuAno8YjxOubyB47FhyizQ2jjpPYbViWLIE/dKl6JctRV9VddkT4o6ydTBubX/nfvZ37udQ9yF80dT4wVxjLqtzV7M6Z/WYU6EzHrsGEItA825JsNW+mlr8XaVHLLuZ6JwPoK78IOhtM2bmRBFFkcPN/Ty7v4VXqzuTyXT1aiUfXpLLfasKWZRvGzdmcyLERGkRws9aeznmlaZeBWBLuoWHCjJZabtwsukL4fPX0Xjux/T0vo7fP/o9OFFk8SYjIyNzmYhFo7jaW+lraaK3pYm+wW08b5paqyO9sIiMwhIyikvJKCoho7AIjV5aFXmxacl4NIGzw0dvi5e+Vh+9rV762nzEx/CoqbRKMgpMZBRKHrXMIjO2TAPCiFV3U6kBmnL//f2ETpwgePw4wWPHCZ44MWoVKICmpARN1UJMK67DsHwZmpIShGkSjJOhzduWFGv7u/bjCqX+niwaC6tyVrE6ZzVrctaQb86/Ojxq5xPxQ/3bUPNnOPsmhEfk69NaYf4HpPi1OTeBWk88FEJ9GRdwTAcDwSivH+7kdwdaqRvhZSvPNvPJVYV8eGkeFt2lxZv5Y3Ge7XTyRGsvrYOLEHQKgY9lO/irggzmGqY+RoFAI42NP6Gr+2VABAQyMm4B/mdK15PFm4yMjMwlkkjE6e/qwNnWIgm01hacrc30d7aPWeMTwJyeQWZxKRlFpWQUFZNRVIItM3vCoiUcjOFs89Lb6qOvVXrt7xidSw1ApZVWfmYUWsgoNJNRaMaWZUAxhfqM4yFGo4TOnMVz+DCu06cJHTtGpLl51HmCwYC+qgr90iVS6o7Fi1HabDMyvdjl7+Jg10EOdB3gQOcBOvypVRb0Kj3LMpexMmclq7JXUaQvwmgYna/rqiDgRHnqFWh4Exq2Q2yE18mYAfNvg4oPQfENqcXfrwbv4DiIosjBpn5+d6CF187zst2xOIdPrCxkSYHtkn8fneEIv2rr4zcjFiHYVUoeyE/ns3npZFzCIoRgsI3Gpsfo6noBcTD5ckbGLZSWfIl4PBtZvMnIyMhcZobypvW1NdPX0oyzrSW5xSJjT3nqjCbSC4uTHrX0wiLS8gtJCIoJiZWhMlLONsmT1tPsxtURwNM39pSQ1qgio8CcFGnp+Sa0ZgG9YeLJby/G0ArQ0InjBI+fIHjiBKHTpxHHSDqqKSlBv3gx+iWL0S9ejLasDEGlGnW9K0FfsI+DnQfZ276XI71HaPamikuVoKIqo4pVOatYlb2KRRmL0Cg1SRunOg132XA1wpnXpOnQlr1oxBEeVluR5F0r/yAUrATFlVt5e6k4fWH+eKSN5w62cq7Xn9y/IMfMfauK+PCS3Ev2sgGc9Ab4eWsvL/X0M7Qup1Sv4XNZNu4ryMJ4CatSQ6EOmpp/RkfHHxBFyYuXlraR0tIvYzEvBMDtHl3BZKLI4k1GRkbmPMTBup5JcdbeSl9rM862VqKh4JhtlGoNafkFpBcUSWKtoIj0giJMY8SmjScE4tEEri4/fa0+nG0++tql6c9wYOzyPCaHlvR8M+kFpqRgOz+X2nSIjlh/P6GTJyWRdqKa4MmTxJ3OUecpLBY0lRUYly7FsGQJuqoqVHb7JfV9KfQF+zjUdYiDXQc52H2QRndqfJ1CUFDhqGBlzkpWZq9kaeZSDOrJJe69oogidBwdFGyvQc+p5CEBSGRWIiy4A2HBHZBVeVXmXxuPRELkvYY+njvQylunu4jGJTVl0Cj54KIc7lqcxco5mZccf5kQRd5xefl5S09KJYTVViMPFmSyOc1MJBxGN8U0N+FwD03NP6O9/TlEUfpCZ7evZU7pV7Bal12S7SORxZuMjMw1SyIeZ6C7C1d7K872FnpbmhnobMfV3jZmzjSQ8qbZc3JJLygiraCQtPxCzJnZZBYWoVRO7CNVFEX8A2G6+/w4230426XX/q4A4hjTngqFgD3HQFqeCWu2jpwSOxkFZnSm6c8plfD7CdXUEKyuxn/sOJHTp4m2to4+Ua1GN38++kWL0C9ehK5qEeqiQsKRyIytruz2d3O4+zCHug9xqPvQKLEmIDDfPp8l6UtYm7+WFdkrMGvMV9zOSRELQ+O7cOZVOPMGeEdM7QpKKFoL5bcjzr+VsC7rqk2aOx6d7iDPH2rj/w630uoa/mK0KN/KvdcV8qEluRg1ykuOvwzEEzzf5eIXbb3UDVZCUApwR4aNLxRkstQyHFc6FSJRJ62tT9He8SyJhHR9m20VpSVfxm5fOWW7x0MWbzIyMu97IqEg/R3tuDrapK2tFWd7KwNdHcRjY3u1FEoVjtw8HPmFpOUVkJZfSHpBIbbsXJQjpv2SGfvHmZYKB2O42n04O/zJV2f7+N40rUFFWp6J9AIT6fkm0vPNOHKMKNWKacmjNpJEKES4tpbgyVOEqqsJnjpJpOHcmHFQmuJidIuq0C+sQle1EF1FBQptasqQK726st3Xzr62fZxwneBQ9yFavakiU0BgvmM+K7JWcF32dSzPWo5FY7m60neMRcCF8vSf4dzb0PAOREYs8lAbYe5NUH47lG0ZTulxlSbNHYtoPME7tb38/mALO8/2MvR9xaxTceeSPO5dWUBlrjV5/qU8V93hKE91OHm6ow9XVIo5MysV3Jebxl/mZ1BwiZUQIhEXzS2/oK3tNyQSkvi0WpdRWvIV7PY1l+0Zk8XbCIYK2U72/Mk+WFNpJ/c1u/qaDTa+3/oamurs75REWm9rC57uTlwd7fhcfeO2U2k0OHLzceQVYMnMJquklLT8QqyZ2Ski7Xy7zrcxGo4x0B3E1enH1eHH2eHD1eHH5xq7+LSgAFuW5E1LzzeRlmciLc+I0TZ2CamRYzGVsY8HAkTOnCV0+hShU6cInTpNuKEBxlhQocrORldZiWr+fEzLlqGvWojSMjrJ6fl2XM7fsyiKnHOf40jPEQ53H+ZI9xG6Al0p5ygEBfPtklhbnrWc5VnLsWqto65z1T33ogh9ZyTPWt2b0Lo/JX5NNOfAvFul/Gsl18PIQvWD154Nn28NPV6e3dfEn0504/QPx4iuLHHw8RUF3LowG71Gmbz+pfR10hvg583dvOz0Eh1sV6DT8Jd56Xwix4FZNbqfyfQVjfbT0vJL2tp/QzwupRMxmxdRWvoVHPb1yffwxZ7pqXJNi7fHH3+cxx9/nPjgh1c4HJ50bEg4HJ6Ssp5KO7mv2dXXVNvJfV24XcjnZaCrE3d3JwNdHQx0djDQLf083qIBkJLa2nLysGXnYs/Nw56bjz0nD3NaenKF55BHBiAaixEdwysXiyZw9wQZ6Aow0B2kvytAf0cAnys87sI9g1WDPceAI8eAPceAPdeAziJgNI+OrwqPEfR/ofEYi4TPR+TMGSJnzhCuqSV8+jSxpiYpSet5KNLS0FZWoK2oQFNRgWbBAlTp6cnxUOl0RIHoBD8bp+v3HEvEODtwlqO9RznWd4zjfccZCA+ktFEKSubb5rM8czlLM5ayJH0JJs2IHFwiY36mXxXPfTyConUfyvq3UDRsRTGQungilr4Acd6txMtuQcxaNDwVGiN1Jekl2ne52/nDMd443cMLRzs50jocoJ9u0nDn4mzuWppLSdrg+yARJTROttuJ9BUXRd7p9/O/XS72eYanYJebdPxFjoPNDhMqQYBYlFBs/Ky6F+orGnXT0fkUnZ2/JZGQRJvRWEF21l+RmXkTgiBc9D0MknD7xgsnLnreeFzT4u2hhx7ioYcewuPxYLVa0Wq1yQ/uiTCkzrXayRVbnko7ua/Z1ddssPFq7ivk9zHQJYmz3rYWvL09yZ9DPu+47RRKFbasbGw5uVgys8ksLMaRm489Nw+9+cLlcc63MRKKScKsK0B/l5+BrgCuDj+evuC4Ik1nVOPINeLIMUqvg5vOqB7VVygUmpaxj/X1EaqtJVxTQ+h0DaHTp4m2tIzZXpmejq6yEl1lxeBrJarMzAt6+q7UM+WNeDnlPMWx3mMc6TlCdV81ofNEilapZVHGIpZlLmN55nKq0qtQxCe2anc6bLzk8fB1Q91b0tawAyEy/CyLSq1UkmreLYhlW4hoM9DpdJLYuMru62LtRFHkUHM/fzjUxqvVnQQikoNEqRC4fo6DT6wqYmN5JuoJLgq4mI2+WJznulz8qq2PppD0BU4J3Oow82BRFsutEy9AP15f0aib1tYnaW17knhcWgFrMlVQWvIlHI6NhMPhST2H/72tjjeq2yds1/lc0+LtfARBmPS3j6E2V6Kd3Nfs6ms22DhTfYmiSNDjZqC7k4HuLkmYdXcy0NlBf3cnIa/ngtcypaVjz87FnpMribOcPOy5eVgzslAolUlxdLEPU1EUCXgikjDr8tPX7sHbG6a/K4Cvf/xvz1qDCkeuEXuOEXu2AXO6huwiGwbrxP8ATnYMxXicSHMzgepqvPX1hGvPEKqtId479pSwKjcH3YIKdAsWoJg7B/PSpWiysibU11RtnGgbURTp9HdytOcox3qOcaznGGcHzpIQUz2DFo2FpZlLWZq5lOVZy6lMq0StVKdcZyiQ/ap87sUEiq7jCM3bEereklaKjsSYCfO2wLxbEUpvBO2g11AUEa7m+xqnXZc7xB+PtPH84TYa+4ZTfJSmG/nYdQV8ZEkuFg1Tijccy8aWYJhftffxbIcT72A9U5tKyady0/hsbhppJC65r2h0gJbWJ2ltfYp4XIo9NJkWUFryMOnpm5OfZ5MZwxcPt/La9vf4kLaBH03KsmFk8SYjI3NZiMeieHp7cPd0M9DdhbOjDZ+zF3d3FwPdXeOm3BjCaLNjy8rBnJFJen6hNNWZnYstOwe1dnKZzmPROO7eIAPdAWnrCtDfLXnVIsGxFw4A6M1q7NnDIm3Iq2awaJIf0sNCcXKeiwsR93oJnzlDqPaM9HrmDOG6OsTgGGMmCGhKStCVl6OrWICuogLtggXJFB1D9s1kBv1oPEqNq4bjvcc52nOU4z3H6Qn2jDovz5THssxlLM1ayrLMZZRYS1AIV77SwiUR7JcWGdS9DfVb0fl7U4/nLoWyWyTRlrMUZqCSxHQSjsbZWtPD84fbeLduePHBUIqPj60oYHmRPSlyLjVtjSiK7Bnw8cu2Pt7sczMk9+fotXy+IIN7su0YR3yBmyrR6ACtbU/S2vrrEaKtnJLih8nI2IwwxefytfeOsfOtN1mjDhJOjJ3AeyLI4k1GRmZKJBJx/P39eHq7kyLN3duNu6cLd083PqcTUbxA7T5BwOxIx5aVjTUrB3uOJMxsWTnYsnPQ6PQT9qBJ9oh4nSHcPQEGegI4O7x4nREGugN4XSGpIs3YZmBO12PL0mNO15KRZ8GRIwm286c7pxsxGiXS3Ezo7FnCZ+sInz1L+MwZoh0dY54v6HSoy+ZiqJA8aroFC9CWlaEwXF25yXoCPZzoO8HxnuMc7z3OaedpIonUeESVoKLcUc6SzCUsyVhCuaWcQkfhtAngK4YoQle1NBVa/za07ofB514ARI0R5mxCKLsFyjaDOXtm7Z0GRFHkRNsAz+1v5rVTPbiDw/FjK4sdfHRFPrdX5WDUTp/ECCUSvNjp5JdtfZz2D4uyDXYzny/IYJPDjGIanp1odICWll/Q2fXMiOnRckpKHiYjfeqizel08tKfX6e1sR6bAAmFmptvvp7vf//7U7qeLN5kZGTGJB6L4XP14entwdPXO/jag6e3h4GeLnxOJ4n4+F4rAJVWizUjC2tWNkZHGmm5+dizc7FmZWPNyEKlmdwy/UQ8gdcVxtMbxN0bYKAnOCjWgnj6giTi46/e0uiU2LIM2LIM2LONg68GrJl6VOqJT7VOBTGRINrRSbjuLOG6esJ1dQTPnCHW2IgYHTtwWpWTg27+fLTl89GVl6OdNx91YQHhaPSqSnMRjoepcdZwovcEJ3pPcLz3+KhVoABWrZVF6YtYmrmUJZlLWJi+EL1KKjY/HR6ZK0rABee2Q/02SbCNLPYOkFEOZZsR524mlLkEndEyq3KvjUe3J8SLR9v54+G2lPqiuVYddy/P5+5l+RSnTzy+bCJ0hiM82dbHMx1OXIOlq/QKBfdk2/mL/AzmG6fHoxyJuGht/V9a254eIdoWUFLyt5ck2kKhEDt37mT//v0kEgkSIvTpC/jOX38cJbLn7Zpgqh/WV8uHvMzVw1DMWV9nBxGvB6+zF09fL15nH96+XjzOXvwu14U9Z4BCqcScnoE1IwtLRhbWjExJmGVmYc3MxmC1pUyXTER0RCNxPH1BPH2SF83V5cPviuDuC+LtC41Zu3MIpUqBJUOPLVOPKU1DWq4Ze5Yk1PRm9WV/L4iiSKyzk3BDA+H6BsL1dZJYq69HDATGbKMwGNDOmzdiK0M3bx5Km23M6zOO2LsSJMQELZ4Wqvuqqe6r5kTvCc70nyGWSBXxCkHBXNtcFmcsTm5FlqLZ+1mUiEPHUVS1b0DTDmg/nPSuAaA2QMkGybNWthlshdJ+cfbkXhuPUDTOW6e7+eN506JalYLNCzL42HWFrJubgXI66+SKIgfcfn7V3servQMMfSfL06p5ID+DT+Y4sKmnR75EIk5aWn6VkvLDYJjPnNIvXdL0aDwe58iRI2zfvp3A4Hu/NW6lVV/GMw/djMOsk8tjXStoz0uIebnbycxOxESCgMeNz+XE63JKr85efM4+SZy5+vA5ncSi46fVGEKpVmNJz8CcnoklPRNLRgaW9Ex0VjsZefmY0tLGTU47Hol4Al9/GK8zhMcpiTSPM4inN4SnL0jAc2G7hgSadXCzZeqxZkoeNLNdh6CYnFicCmI8TrS9XRJpDQ0Ez54l1tREpL6BxDgiTVCr0ZSWoi0rQzN3DoqiYkwLK9Hk5U24GP2Vpi/YR11vHSf7Tkqb8yTeyOjVvg6dg0UZi6hKr2K+ZT7Lc5enpuyYjbjbpNi1hnfg3A6EYD8pk+iZFVKy3Lk3Q+EaUL1/PmeHVou+cKSNP5/oxBsaFucriux8dHk+t1ZloyE+re+xUDzBiz39/G9bH9W+4fjO1VYjn8m0ckdO+oRXqF6McKSPluYnaGt/Nplc12yqpLj4i5hM69DrDVO+r/r6et588016e6V4x7jGxDu+XDzqNJ5/YC2Z5kv3FsriTWZMZC/f1YcoioT9fnz9Tvz9/fj6nfj6XfgHXPhcLjzOXgID/fj7XSTGSLw6FnqLFUu6JMjM6RmSUEtLH/x/JgaLdZSwuJgwiscT+AfFmdclbZ6+IO6+AH5XBF9/+ILeM5BWc1rS9VjSdRhsatJyzNgyDVgy9JhsWoRp/JZ/IRLBIJGmJiKNjYTPNRI510C44RyRpqYxi7ADoFKhKS5CO2cu2jlzJG9a2Vw0hYUIaunP/9AYaq6i6c+B0ACnnac55TzFKecpTvadpDvQPeo8rVJLuaOcqvQqFmcspiqjilxjbqqHVT1ziyOmTMQPzXsksVa/TUqaOwJRayFRdD2K+bcgzL0JrPkzZOjlo9np54Uj7bx4tJ0W1/CXkDybnruX5XHXiGlR6Xc99Wm/kbSFIjzd3scznc5kFQSdQuDuLDsP5GdQYdRJOQen4X0fDnfT3PIL2tt/RyIheUXN5ipKSv6W9LRNwNi5ASdCX18fb731FnV1dQDo9XqE3Ep+dkpEoVDy5CeXMT97esqxyeJNZkxkL9+VIxoJExgYIOAewD/Qj7uvl7DfS2BgAP+AC/9AP/6BAQID/RPylgEgCBhtdkz2NEyONEmQpaVjdqRhTsvAlJaO0e4gFp/cN2dRFAn5ozi7/ET9Pnz9YXz9IbyuML5BoeYfGD9Z7RAKlYDZocOSrsecpsOSpsOaYcCSLu0bWihwuT1oMOhF6+wi0tSEv+4sA21tRBubCDc1EuvoHLedoNGgKSlBU1KCsrgIQ3k5urlz0RQVJUXa1Yo77KbGVcNp52lJsPWdos3XNuo8AYE5tjlUpVexMH0hVelVzLXPRa24uu9vQiTi0HUcGrbDuR3SQoP4iPeXoIC85TBnE8y5CfKWEYnEZl3t0IvhDkZ56XA7r5zs4XBzf3K/UaPktqocPrIsj9UlaSim+QuTKIq8N+Djf9v6eGPEqtE8rZrP5aVzX24ajsGp0UupRDBEKNRBU/P/0Nn5fyQGF89YLIspKf5b0tJuTFk9PlmCwSDbtm3j6NGjJBIJFAoFK1euxO+Yx9+9UAMIfPvDldwwLyO1YefxKd/PVSfedu3axQ9+8AMOHz5MZ2cnL774InfeeecF2+zcuZNHHnmEU6dOkZubyz/+4z/y4IMPXhmDrzDH33qN42+/jqdX+kacll/Imrs/QcnSFeO2aT1dzc7f/ApnWwsmu4PrPnQ3izffdqVMvuaIx2KEfF787gHcfb3EQkGCHg9BzwABj5uA2z342k/APUBkrPQPF0BnNGG0OzA50jDZHRhtdgw2O1qTBUd2Dua0dIw2OwrlhaczRVEkNsJDJyZEgr4o/oEw/oEwvgFJmPn7h/4v/RyLXDgODobFmdmhw5wmverMStJyzFjSDRitmivmPQNpKjnW20ukuZlIczPR5mbCTU1Em5uJNLcgXqAyg9Jmk0RaaQna0jlo5pSiLS1FnZeHMImccjOFM+jkRPcJGrwNScHW7hs7OWiRpYiKtAoq0yqpSKugxFBCmjntqryvSSOK4DoH53aiqd8GzbshNJB6jrUASm+UpkNLNgzXDR1qz4UX6MwWwrE422t7eeloO+/U9hAZzJGmEOD6sgzuWpbHlorhUlXTiS+e4Ln2Pv63vS9ZIB5gvc3E5/LTuSXNOi0etiGCwVaaW35OZ+cLiKIUL2q1LqOk+Is4HDdc0rMdi8U4ePAgO3fuTHrr5s+fz+bNm2nyKXj4F/sB+Pz1JXxyVVFq455aeO6+Kfd91Yk3v9/P4sWL+dznPsfdd9990fMbGxu57bbb+PznP88zzzzDe++9x9/8zd+QkZExofazDVNaOtffdz+2rFwATu/axks/+A6f/rcfk15QNOp8d08XL/7bv1C16RZu++Lf037mNNt+9TP0FivzVq270ubPKkRRJBoOEfJ6cbucJCJhQj4fIZ+XkM9L0OtJvga9HkmgeT2EA/6LX/w8lGo1BqsNg9WGzmTBkpaO0W7HaLVLrzZ7UqSpNaO9mxcSEEPesoA7gt8dTr76B8J4XUGCvhj+AWn/hVZrjkRnUmG26zANCjSTQ4fJrk2KNYM5VZxdEQ9aLEa0s5NoayvhlhaC586RaO8g2tJCpLUV8UJTIWo1moIClAUF6OfORVtakvSqDeVLu9oRRZF2Xzu1rlpqXDXUumqpddaOmU8NoMBcwALHAirSKliYvpAFaQuwaCwp15tVK0DHwtsNjbugcQec2wnuVgSk7PsAaC1SVYPSG6F0I6TNeV951UaSSEhxbC8ebefVEx14RsSxzc8ycffyfO5ckkem5fJMeZ/1h3iqvZf/6+rHNygWDUoFH8t28Nm8NMqN+mntLxBoouHcY/T1vYIoSl9SbbZVlJT8LXbb6kv6HBJFkdraWrZu3YrL5QIgIyODD3zgA8yZM4dmp5+/+s0eIvEEWyqy+OqtC1Iv4OmAZ+5GCF84GfmFuOrE26233sqtt9464fN//vOfU1hYyI9+9CMAFixYwKFDh/jhD3/4vhRvc5avTHno1t/7GY6/9RqddWfGFG/Ht76BJS2Djfd/HkEQSMsvoPtcHYdeeeGi4u3wG800HuulvyuASqMgu9TKmo/MwZ594aXgZw90cfStVtw9ATR6FYWVDtbdXYbONL1TLRd784miSCwcIhIOEQ2GCYcCBHxeiEWJBkOEgwGCXjeevj7Cfh/hgF8SZn4/Yb+PkM930VQYFzAOncmE3mzBaLVjsNrQW6wYLFZJpFksg2LNjtFmQzMYHDvhygAJkXAwRsATIeiNEPBE8Lj8RAMiAW+EoEfaN7RNVJQhgN6swWTTYrRpMdmHNp20z67FaNUQS1z5dBWiKBIfGCDa1iZt7e1EWtuItrZIrx0dYxZZT6JUos7LQ1NYiKaoCE1x8eBWhDonB5TKq9qDNpJwPMw59znOuM5wpv9M8nWsxQQABaYCKtMrqUyrZEHaAsod5aMKtr8vCPZLcWuNu6St53TqcYUaMX8FsYJ1qOZvQchbDsqr7s/gtHK228ufjrXz0tEO2geGvfzZFh0fXprLhxfnUmLXXJbnPpoQeaPPzVPtfbw3MJxaZI5ey+fy0/lYtgOLanq9ez7fGZqafkp3z2swOBnrcFxPSfEXsdnGn6GaKB0dHbz55ps0NzcDYDQa2bRpE+Xl5RgMBtyBKJ976iAuf4SqPCs/undJ6krckBue+Siiuwu36gvAD6dkx6x/avfu3cuWLVtS9t1yyy386le/IhqNoh4j9iQcDqcUjvV4JPX7P1/4Irl5BVjTszFnZWBIt2O0mjDYjGj0OtQaLSqtNvmq0mhIJBKTniMfqp02lXZDf+BBSpJ6dt97RMMhcsrmj3m9zrpaChctTbYHKFq0jJPbtxKLRlGqxn4ERFGko26AhRvyyCyykEiI7P/TOV7+72N84p9XodaO/YbrqOtn21M1rPtoGcWL0vAPhNn57Fne+U0Ntz5YNWY/iUSCaDhMLBohFg4TC4eJx2M4cqRVeMP3JQ79A1FEqRBGFCIXB+Oshs4RGQq8Uqk1qNQa9BYztszU8kCRUJBnv/53+Pqd4467QqlCazSiN1vQm8zozGZ0JmnTm83S/pGbxYrWaEQQFBMWA/FYgpA/StAXwesKEI+4Cfli0j5vhJAvSnBo80YIeaMXDfo/H51RjcGqwWjVYLBqMVg0aAwC1gxTUqwZrBqUF1nNJYoi0dDknt+JPPOiKBLv7yfa0UG0o4NYRweR9g7CLS3EOzuJtbePu5JzCEGjQZ2fjzo/H0VeLvrSUkmoFRaizs29YCzapbwvJ9tuom1EUaQ70E1dfx11A3WcdZ2l1lVLs7eZuDhaqKoUKuba5rLAIQm0+fb5zLPPQxlXjnoOJ9L35bqvaWsX8iA07IL2fYhNu6HzOMJ52ZjF7EXSFGjpBihcg6g2EA2FUA7Frk2wz6t9PEa2aR8I8srxDv50rIParmFBb9aquLUqmzuX5LGyxIFyxMrs6bSxKxzlt51Onulw0hWRvgArgC1pFj6RYeamTAfKwYVQE+l3IuPh8VTT1PxT+vq2JvfZbRsoKf0iNmvq38Cp9OXxeHjnnXc4flyKU1OpVKxZs4Z169ah0WgIhUKEo3G+8MwhzvX6ybXq+OVnlqMfzCEJQCwMz91HpCtOf/yn+AJWrlnx1tXVRdZ59fqysrKIxWL09fWRk5Mzqs2jjz7Kv/zLv4zaH4300N3WT3fbiUlYIKBQqVGqNChVapQaDSq1GrVWi0qjRqVRo1SrpWNqFUqVGoVKjQhotBoUSpW0qZQoB/8vKBUoFEoUSiWCQoHBamXedWuSKwj7Wpv5w7e/TiwaQa3TcfuX/glbVg7xMfI/+QdcFJoXpxzTGU0k4nF8/U6MtsEpIUFAIShoO3Oa/PkVJOJxbv1C+bBYAq6/t4Rn/t8hOuudZM8xD6ko6eCgYOo468Tk0DJvlQ3EOJpsJfNWOjixo4ug1yN9UCoUqFQq/vi9f6an6RyxaHTUB2h6QRH3fvvfScQTiJdQQmTod4Qg3aMAICgQBAGFQoHeZGH5HR8hFo2i0RvQGk1ojUbp1WBEZzKh0miTRYcvRCIuEg3F8LrjOLv6iYTi+NxBxJhAJBAjHIgRDsSJBAf/748RCkQJB2LEwhePIxsLjV6JzqRGZ1KjNSoxDooyvVk9vA3+rFSNFmVD4nKIaDQyoTRi4XB40t/SQ24PsZYWYp1dxLq7iHd1E+vulv7f2Umss+vCU5uDKNPTUeXlocrNRZWfjyo/D3VeHqqCApTp6cnVsSPvLQGE4/ELe+ameF9TbXd+G2/EyznPORrcDTS4G6h311M/UI83OrY3zaKxUGYrY55tnvRqnUeJpSSl9icACQiFQzN2X9PaLuxD0X4ARcselK17ETqPoTtPxCYcZSSK1hIvXEeicB0Y0kYcBAa/vL8vxmME/YEofz7ezpu1Tg63DOcPUysEbihL4/aqLDbOS0enlr54RyNhht7q02GjKIrs9QR4pnuArf0+YoMf6WlqJfdmWrkv00auVk0oFCIaiTDZbIXj2ejxHKGt/QkGBnYP7hFIS9tCft7nUSqL0Wl1k57+H9lXJBJh//79HDhwgFhMEqIVFRVs2LABi8UiZQEIhwmFQvzrWzXsO+fCqFHy008swqIZsXJVTKB88WH8dZX447cDCgTD+PWTL8asF28wevpsSOWO9zB+7Wtf45FHHkn+7PF4KCgoQKPIRCPoAAUikBASJIQEiDEgJgU7ijEgyrCkEUnEIiRik38YJ0p6QRGli5cRj0ZJxOMYLFbu/vq3iQQDnDt6kLf+57/50CNfw56TN6qtmEgQj0QI+Yb/AESCUkxWxO9HpZI+6BVKJUq1mmOvv0J2yZxkXyPxDxbqViiiRMcJsk/L0+IfiNBc3UfePDMhX4zG4y7y51tIxIa/gYmiSCQYHOE5Y9AOFWqtFr3FOpgcMSGJLkEYFF+SEJN+twKCYmjfiHPO+3/KeAx6L0dSeeNtRENxouHBLRQnGogR6I8TDfuJBN0E/WESMYFIKE40FCMSihMJxYgG44RDMSKBGNHwpYlMQZBSZGgMKkmAmTToTGr0g+JMb9ZI3rMhcWbSoFQPf3ud7JTf0LdLrXZyNTnPbzc0nRnr7R0UYz3EuruIdvcQ6+oi1tNDtKuLxAQTUqoyMlDl5qLOzUWdmwMZGeiLS9AU5KPOzUUxgRqdU7m36RqPi+GP+mkYaKC2t5aWQAv1A5JI6wmMHZumFJQUW4ops5dRZiuj2FRMVWYVWcasCfV3pe7rsvQV9kDLfmh+D5p2Q8dRhPPFmrUQoXSDFLtWvB7BnIOSEXFtl9vGaW4zmXa+cIy3TnXzyvEOdtf3EUsM/e2DVSUOPrQ4l1sXZmMzjF/J5FJtDCqU/F/3AL/pcNIQHBYjK61GPpubxu0ZVjQjvGzT9Znj6t9Nc/PPGBg4MHjPSrKyPkRR4RcwGucmPxOn2pdareb48eNs374dn0+a8i0oKGDLli3k5+ePavPzXY28eKwLhQCP3beUxUXpKeeEnv0vnNW3EScTAMOKLAzrHPC9CZuWwqwXb9nZ2XR1pZZi6enpQaVSkZaWNmYbrVY7ZkqLyMoC9tnSye9roih+FHOsA29QQdBvQRE0YwsYsIQMGCJ2tDEjMaWeiEZLVKklptISVaqJqVTElGriCiWiAIhxROJAHMQ4EBvclxj8OTF4LAEkpHNFcXB/AhARVNlIkkcBAijVSqyDCxYyiufS29xE9fatbPjUX4y6J4PFRsDrQRiRSDXk86FQKNFZrAhKleSUUigQFErMmbkICiWCMpEsCD00s3Do9WaySkykF1oZ9GElg3uFwf/nzdez8VMKdj1XTywqIiZEihY6uOHj81CoFNKZCsnLt+mBvycWFYnGEuiNJpRKDaAgkRBRqRWoNFoUKg2uX/4C39tvE2lsRKHVoVuyhLQvfwV1UTEwKKMTg9ENoog0hSoiRiL0P/FzfK+/StzZhyozC+vn/hLTHXciIglAlVrBS/9xFFfH5BcZjIdKq0SrU6LRq1DrlZIIM6jRGlRojdKrbvD/OpManVHatHoVCEw57koYKVynoY0YjRJz9UuirK+XeF8fsb4+or29RLq6EZ1OYj09xHp7xy3xdD4KgwFVTg7qnBzUOdmosrNR5+SizslGnZuLKicHxYiSWZey0GG6x2Oy7dxhN43uRhoGJE/auQHJq9blH106aohsYzZzbXMps5VRZi9jnn0eJdYSNEppTKY6HtN5X5e1r6ALoWWvFLfW/J5UM/T8Kh+2Iii+HorXIxatJazLfP+OxxjtQtE4O8708PLxDrbV9BCODY/PgmwTH16az4cW55Jrm/gCgMnaKIoix7xB/re1mz87vYQGRaNRqeCjWXbuz0unwjR2/5cyHiDS27uVpuaf4vWeHNyvJifnboqLvoBeXzgtfTU2NrJz5056eqQvVHa7nc2bN7NgwYIxr/XnE538eHsjAP/yoUo2lg/PBsb9Udz/+zqB9usAUJpi2O9dgm6u/dqusLBmzRpeeeWVlH1vvfUWK1asGDPe7UJkvBfic6UCDVVhttvu5nh7BQu7z3C9upoVadXYtWdo0gqc1aipV2nojqpQ+pWkeUUcXkjziqR5IGfwZ2tADYKemEpPTKknptIRVw39rCOu1BFTaaVXpY64zkRCayKh1knnCmriqNAYzAiCGgQlgjDGnL2oIB4TgdFvlqzSBTRXH0o51nq6hoyiOSiV5hExZAKICkKB5SCqEBMKxME3pAjse6kBV0eQ2/66ikRs/G9xA90B9rzQyOJNBeTOsxP0Rjj0WhM7f9fAuo+WASKCAlRqkd3P94wrmhy5Ru7+h+XEogn8+w9i/MjHsFdUQjzOwM8fo/0Lf0XO715AoR//A6r3H/+euMtJ2te/iSq/gHi/C+Lx4RnaEe9BpUqBSqNArVOi0alQa5Upm0IFepMWjV6FRqdCox88T6dEq1dJHjO9tA3FjE3VG3a5EBMJ4m438f5+4v39xJwuQj3d+Dxe4i4XcZeTWJ+TmMtJ3OkiPjAw4XggAKXdLnnNsrNQZ2WhyspGnZ2FKisLVWYWMZsVQ0YGiqu0msBUiCfidPg6ONN3hvZgO43uRhrdjTR5mnCFXOO2S9enU2wuZp5jHmX2Muba5jLHNgezZnoSeM4KRBHcrdCyD5r3oG16D8F5dvR59hIoWgfF66F43XDpqaFrzPYVsRMgEkuwu76XPx/vZOvpbrzh4YVUpelG7licyx2LcsizqC7rghtfLM4L3f083eHk5IgKCBVGHffnpXN3lh3TNC9AAEgkovT0/omOjv8lEGgAQKHQk5f3CQoL/wKdNnta+unu7mbr1q3U19cDoNPp2LBhA9dddx2qceLDj7T083d/kOLgHlhXzKfXFAPSZ3nweC8DL9aQCNuBOKZSJ5bP3oliGlKwXHXizefzJQcOJAV87NgxHA4HhYWFfO1rX6O9vZ2nn34agAcffJDHHnuMRx55hM9//vPs3buXX/3qV/zud7+bdN+NWW8idH+OOcEisnJEbpn3cw7Or+Jn3fcSb78H/YCP5f6zrFOc5GHVaSo4R78CGqxq6jPU1KvV7DRaaVAp8IoxBDGBKejH4fVj94nYfeDwQn7IQFZIgyOgwOSJoh7wI0THX9WomVeGMv4sQjTCnhd/T2HlIsz2NCKRCHWH99Fx9iQfevirqIUYe178Hb4BF5v/8mFAYNFNWzi543X2/vEpKjdsprP+DLXvvcOWLzySjIESEaXpRwWY03TStOSI1TH7XmqgpcbFbX9dhdF24SS8J3a0kVlsYeGNQ25lIyqNktd/Xs3SW4owWDSD8WegM0kB9CCiVCoRlAIKhTQVassyIChAoRTIfuxnAMkpU82//CstN99IrL4Gw/IVw7Fs0kkABPa8R/jYYYpfewOl1ToY9lY8fK8wOK0KH//GdSguEKR/teXxEhMJEl4vcY+HuNtDwuMm5nYT7uvDHwgQd3uIDwxIQm1gQNr6+yUxlphkbJ1CgSotDWVGOqr0dEmcpaUh2u3oc/NQZWagzsxEmZGR4jEbZbMoIoamFnc104iiiDPkpMXTQpOniSZPE83uZpo9zbR4W4gmxvc6ZhuzmWOdQ6mtlDnWOcyxzaHEWoJFY7mqnqkrQiIurf5s2Qcte6VXj5RvbvAjQSKzQio3VbRW2iy5M2XxjBJLJNh1tpdXqzt581Q37uDwc5Zr1UmCbXEulbmW5FTi5UrtcsIb4DcdTl7o7sc/mOZDIwjclmbmgYJMrrMaL8tzHI+H6Oj8Ay0tvyQUkpJIq1Rm8vM/Q0H+Z9FoHBe5wsTweDxs376dY8eOIYpiMsnuDTfcgMFgGLddqyvA5399iEgswcZ56Xz9NiklSKw/xMBL9YTO9AMK1EIj9iXtaD721WlLRXPVibdDhw6xcePG5M9DsWn3338/Tz31FJ2dnbS0tCSPl5SU8Nprr/GVr3yFxx9/nNzcXP77v/97SmlC8gr8pO16mSbNvWQ1N7Ew9Aki9r1smvsdjqxczKv+29jVsZr3Ohbxg1ACC35WKmq5Q1PPrWItDucZcPYjAt1KJefUahodeTQUZnJOreJYZID+iBsIDW6DiCLGkJLskI75YibFcTs5UQMZIQ1WP2gsmYPTmgoCPg9bn34Cv8eNVqcnPTefD//NIxTOLYOwn4CzF5+rD0VAWkFrM+j40INf5t0Xfkf1O69jstjY8NH7mL+wEiJeUCgG33RKBKWaRYY6VIpilMo4KGH3C420nHJx58OLsGUZpAfvAvFkiKDSSIHzQxgs0h91g1mTsv8jjyy7qDBSj6EVI33S2Okz09DoVWO2c767A93CStxPP4n7Ty+j0OsxbdpI+sMPozivL0F58TfTVD+YRgbziuEwiXAYMRhCDIdIBIPJLe72EHc6Sfh9RAbcCMEgCb9fEmk+Lwmvj4TPR9zjIeHzTcojdj4Ksxml3Y7SbkewWtBkZKJKS0OV5kDpSEOVnia9pjmkc85L9nu1idnpICEm6A30Uu+spzvUTauvlRZPC63eVlq8Lfij40+raxQaCs2FlNpKKbGWUGItodRaSpGlCIN67A/+y+lhvWoIeaD9kBSz1rof2g5JnzkjUaggZwli4Woi2cvRzN2AYBw73OVaIBZPsL/RxasnOnj9ZBf9gWHBlmHWcntVDh9clMOyQvu0Vzw4H38szp96Bvh1Rx/HvcNetjl6LZ/OTeOebDuGeOzypBiJemhvf4aW1ieJRiUPtlrtoLDgL8jP/yQq1fR4qMPhMHv27GHPnj1EB0M/KioqWL9+PTk5ORe8L3dQSgni9EeozLXwg7srUADe99rxvNmEGEkAUSyq32FeGEW453+nNYegIF4TnyIXxuPxYLVaefIbH2a7/gyffWMp1WU3YI0dY3nWBzmoa8SbcYz80uMcNSzllcSd9DgdKNsDKHpDDM1kZir9/GVhO7ea6skfOITQWzuqr/70OTTkVNJgzqRFb6A54qLJ00ybt23Mpf8AZbYynr7taeKDqy6VghIVChSigBJB6n8oZUkiAaKImEgk/89E0pkolSg0Gjq+/nVyv/c9EpEIu19qpb56gC2fKMKWPuxV0eiUqAYD5Q9s7cbvjbLpniIQBM4cdrHrxRbWfaiAgnlW/L4oe15uRRAE7vpSpXQBhQJBpcL7xhvEfX5iAmh0egS1GkGlQlApUVitGJYuHRSEqba3P/wwcY+Hwl//mpS3wog3RusXHiRw8CCG1atJf/ALxPsH6PrudzGsvI6cb/8rICYFaPBENQmvBzGeQIxGEWNRiMWkOC61GvPmzQhDLvORtoz1/xGvw4txRVJW5o5BIhCg6Z6PEesZO2h9LAS9HqXZjNJqQWG2gNmMxmFHabOjtNlQWq3Sq802KNZsqGw2BM2lxU9NdTr4SvU1XrtANECHr4N2XzttvjZava20eaXXdl874fj4K78EBHJNuRRbiimyFFFkKaLYUkyxtZhMfSbRyOTy3r3vxl4UwdmA2HaAeNNelJ2HEbpPM+qZ15igYKXkWStcDXkrQGN4/43HJNrE4gn2nXPxanUnb53qwukfXsSVZtRwa1U2H1yUy3XFjtR8YZfpvk54Azwz6GUbSqarFgRuy7Dymdw01tpMKZ6+6RyPcLiX1tYnaWv/LfG4tEhAp8ujsOAvsdvvwGi0TUtf8Xico0ePsn37dvx+6YtZfn4+W7ZsoaCg4KL3FY0n+NyTB9ld30eWRctLf7MOkztI4M8tRFulLyga1Vnsiv9EXVIMn/ojjFHv1+12Y7PZcLvdWCyWUccvxFXneZtJ/MUfZK3vMCfzjlHUM5emjEp2d/yO9Vl305PIZJ+rgILcGh4t/gdOZCzmlYw7qY/ORdkZRNkeoMdr5HuN8/ge88gwf4T7lui5J7ONfPdRqRRL10nsfQ2s6GsgmSrQnAOFq4nOu43W9FKa1CpavG00e5tp8bTQ7GmWzhMhloiNKfAEpAUASqUSpaBEKaiknwUlSoVyUKcMrjoY3MQhYTck7gBBqcS4bp0kokSR0welbzx/frIxpb8NH8lj/lI7AAFvFN9ABHFwZeq8xRYiwRxOvtfDnlfb0OqU5JYYWbUlezhH16BQdP7yl4TP1o35u9DOK6Pot78lEYmkpHfo/c//IlR7hvzHfkK8v3/MtgCJwTx+mV/9J5QmE+r8fNL/+q/p+ud/Jv2hh1BotUk7ur71zQvaYd60iUQ0ihibvtI4Q6thERQIKiVKiwXzbbeR8LhJaHVobDaUZjMKs0l6NZlRmk2S18xiQWGxTFtg//sFX8RHp7+TTn8nHb4OWgZa6A510+HroMPfccEYNACFoCDLkEWxpZhCSyGF5kKKLEUUWArIN+UnFw2cjyiKRC/bWvOrlJAb2g9L3rS2g9IW7EfgvD8qtiIoWCUJtoJVkFUJiumPiZptROMJ9g8KtjdPdeEaIdjsBjW3VGazuTyNG+Zno74MMWTn443F+b8OJ7/tcHJiRCxbiV7DJ3PS+HiOgwzN5atnGwg009L6Szo7n0/WHTUayygqepCszNsRBNW0TAmLosjZs2d5++236e3tBaTFCDfffDMVFRVJUXqxa/zzn06yu74Pg0bJrz65HMOBbtw72iAhImgUWA3/hzH4a4TMcrj3t2MKt3gsxt7nJx/eNYQs3kYwd9mNFL7yKA9dD9/75Qt4LI/g0izjnc7fsjbzTj5iWMvONhuHe0opLDrBN3P/H3XqebxadCeHi65D8ERQdgTQdobo9Yb58b4wP8ZEefZt3L3sr7jzLiMZ/UcRm98j0bQHRddxBG8nnHoR9akXKQVKNWbIXyF90M25D/JXEFJpUSvUqBVq4mJc2hLx5P9FROn/4+SwEhBQCkoUCknQKQQFSsXg66DQUwz+wXfcey+iKKLUavmbn20ce2pU+g+IIjf/pUMSg0OiUBRZvMXC4s3Fg+cwnDB3yPskCAgqFcbrr0ddVEw8FEQhghiLSV6vaAzVYN3IkVN2Pf/5X/j37CH/sZ+gzr5wgGoyPmvEtxltiWRT3OlEWVAASiWCQom6pARBrZF+Tnr/VAhqNerCAgSVGjEWRaFWD3v3hsQXI4TYyP3CYBSPMFKojT3dPET2V/9JFmHjEI6H6Qn00B3opsvflXzt8ndJgs3XOW4+tJGYNWbyTHkUmCVBlm+WtgJTAVnGLOKRuDz25xOPSLFqbYeg/Ygk2vrOMsqrptQi5i4hlr0EVfFahMLVYJ6eQPL3A+FYnPfq+3i9uoutNd0MjJgStRvUfGBhNrdV5bCmNA2lQiAUCqG6SMLsS0EURQ57Ajzb4eTFnn6CgwvUNINetk8NetkUl/G94PWeoqn5f+jpeZ2haggWy1KKix4kPX0TgjDxRL4Xo729nbfeeitZGUGv17NhwwZWrFgx7mKEsfjFu+f43YFWFAL8YuN80p9vwNsrCV5duRV7+NsoO7eCNU/yuOlto67h7unm1Z/8gMZT1VO+H1m8jWBZURovJ9ZxS3wnv99g4tM7fsXBFV8jJEbZ1fUHlqdt5nbLMqrjLRw+p6ezYx5z5h7nEfv36SCP1y13sdt6A/55VhR9IczdIWJdQWq7vHz3tRoefR3WzU3nrqVf4IZV/4RDL0DHUSl4t3kvtB6QYkLObZc2AAR05R9EvPsXaFCAQiOl/RgRS5UQEyTEBHExPub/QRJQ8UScOGMLPLVCjUqh4tmaZ/l0xaeJi/FBUTe8CYwQHue9oYVBW4b2TuSPX9Y//MNFxYrCIE2pdP/rd/C/+y5FT/8aTXFxypt5rHbGNWvw7diBQq9HYZTKeQWOHQOFAu38+ShHrFIt+PGPL2inKIoo0fLL6l+yrWUbje5GdCodizMW85XlX6HEWjJuu5E2Hu05yufe+BxzbXN5/kPPX7DPa4VYIkZ/qJ/eYC+9gV56gj3Sa6CHnoD0/65AFwPhgQldz6q1kmPMIduQTbY+mwJrAXnmPPJMeeSaclNqd56PKIrjvj+uGRIJcNZLn0vth9G2HYLukzDWlLKtCPKvk7xq+SsgqwqUamKhEKqh6gXXOMFInLdretl21sk7NT0pq0TTjBq2VGYlBdtIoXY5o5n6IjGe73LxbKeLs4Fhb9ZcgxTL9tEsB2mayycNRFHE5dpDS8sTuPp3J/enOW6gqOhBbLaV0/rlqb+/n23btnHq1CkAlEolq1evZv369egvkK1gLN442cWjr9diAn5ZkEP+m23EAIVZjWFLHpaGr6Fo2gpaK3zyeUnAncfZfbt5639+QjjgJ6KaWnJ2kMVbChqVgq7iO/iLtj9z2yITNx1zUVHza05U/TUiEQ4538QTdbEkbSP5oTR2qWo5WW3Fau2movIUf6H6CR8Vn2ab6h62Zm/BnamHciumnhCO3gg93X7erevj3bo+9GoFWyqyuXPpPNavW4v6BoW0Gqv7FLQdkIRc637ob4L2QwjBfileJM6gB0cJCiXCoBdNqVCjZrRbe0jciUO5zxj8WRRJkBoL54142de5j3vL7yUcD4+aoh2anh1zY1jgKRQKBKbvzdf17W/j+fOr5D/+GAqjUcorJooozOZkwtae//hPYj3d5P7bvwFg/eDt9P3sZ3R8/Rtk/O0Xiff30/ODH2K9664JJXkdi0Pdh7i3/F4Wpi0kLsb576P/zRe2foGXPvzSuIHpQ3gjXr7+7tdZlbMKZ3D8UlzvB6KJKP2hflwhF66gC2fIiSvkosfXw0B0AGfQSV+wj75gH/3h/uQXjIuhU+rINmaTZcwiyyBtOaYccozD29DvQfZgToBEAvobofPYoFg7Cp3Hk4sKUlaA6myQtzx1M2WMvqYcQo07GOWd2m7ePNnNzrO9BKPDn6OZZi0fWJjNBxZms7LYcVk9ayOJiyK7XF6e7XTxRp+b6ODvSa8QuCPDxt1pJq7PsF/WND6iGKen5w0am36O3y/VnBUEJZmZt1NU+FeYzQsucoXJEQgE2L59O0eOHCExuMp+8eLFbNy4EZvNNunrnWgb4MvPHWWDqOJraiPGFilWzrgyG8stRYjb/hFF7Sug1MAnnoWsipT20UiYHb/+BSfefgMApz3K1nnd8Iep3Z+8YIHhBQsDAwNsb/Cy4KVbeDozwGmPke89Hae+9MM0F2xGjOwkEjhCnqGMdbl3kYgnOG5u5WisAVFMUFDQyZy5J4jHewmh5aD2E7zG7bREpDeEKhBjgTuBt9VLV//wN540o4bbF+Xw4SV5LCs8LyDT1wOtBxC7T5FwNqDoO4sw1rdgSy5kVEDWAshYABnzk4HA4XB43CzToijiiXhwBp10BbrwhD1sLNxIPBEnlohJYi+RIMHkviEMCb2hBIlD4g6QxKagpMZZg0apQStqyTBnYFAbxrSxpnzsN3X2976L7SMfQRAEOr76NaLt7RT95unk8fC5c3R/5zsEjhxFabNh/sAtZHzpS6NWm16M8bx8rpCLDb/fwJO3PMmK7NEFj0e2+8dd/0ihpRCloOSdlnfG9bxdTcHUoigSiodwh924w248EQ+esIeB8AB9/j58cR8D4QEGQgP0h/sZCA/QH+rHE/FM2G6QYs0cOgeZhkwy9ZlkGjLJMGSQacgkXZ+OTWmjyF6ERWu5rEHpV9PYT3tfAT86fxtC1wnoOCaJtK4TUgWD81HpIWcxYu4SohlVqEvWIDhKJ+RJuxoWpsxEXz3eEFtPd/PGyS72NjiTlQ4AcqxabluYw22LclhaMLFVotN1X83BMM91uvi/Lhft4eFp2sVmPZ/MSePOLDtm5cRrME/Fxng8SGfnH2lp+RXBkJQpQqHQkZt7D4UFf4lenz9u28n2BcPlrHbv3p2sYT5nzhxuvvnmMctlTqSvjoEgD/zkPT7jV3DDoJNEla7HftdctKU2xHf/C2HbtxARED76v7DwrpRr9rU28+qP/52+1mYQBGrnBtg/p4dF1sX89u7fTmnBgizeSBVvolrPL7/3Re7Uv8BH8nN48LU4N54QOL7ma7jUOSiFdwj0H8ehy+Xm0k8jBKFP7+NdSx1OtwuFIsZ113nQG3YQj/tJIFBv+gyvKz7MAe9wvNjCqIK8/hjVda6UYNUCh547FuXyoSW5zM8yp6SaCIVC6NRKhJ7T0hL8tsNSoLBzrGB7ATLmI+YuJZqxEHXhCoTsKtAYLzoeY4mVIa9divduxM8jXyeCP+rnvtfuSykJpFKosGgsWDQWKtMq+ebabxJPSDF9Q1O2Q68KJCGYFIgjjo+0+2L3NRHGa9fiaeH2F2/nhQ+9QJm9bNx2L9W/xO/P/J5nbnuGJ048cdnFm4hIKBYiEAsQjAUJRAMEYgH8Uf+ozR10E4gH8EV9eCPe5Ks34sUT8Vwwh9mFUAgK7Fo7Dr0Dh86BQ+vAqraSbc4mXZ+e3NL0adi1dmlhzWUaj6tWUF2uviIBKUat6wR0VSN2VUP3SYToGCXtlFppEUHeMshdKm3p80Gpuvrua5raTVdfDb0+tp7uZuvpbo609Kc4HcsyTXxgYTZbKrKY49Cg1+uv2H0l1Bpe73Pzu04X7w34ksetKiV3Z9m5L8fBQrNhVLvpHvtIxEVb+zO0tf0mme5DpbKRnX0vxUWfQ6tNH9Vmqn2BtIJ0qJyV1yt5jzMzM9myZQtz586dcl/eYJSf/ude7vSCcbBCkPnGfCwbCxHUCjj+HLz4BantLd9DWPNQyrWqt73J9l//glgkjNZiZtvCDuptLpZlLuPRFY+Sl5knrzadDmwGDY05tzK39/fcEAjy2xt1rK9TsODw4xy+4V8JRTZizwVXx3FebXiC2xY+SLrLxB2RxZyc7+LQuePs3+/A4biXNWudeL1/Zp7v18zjabxpf8Ebijv5szPMSY3IySwl+QW53CNqCLR62V7TQ6sryE93NPDTHQ2UZZqSiRiL0wbfbEo15C6Rtuv+UtoX7JemPTqOSgHFHUel5Je9tQi9tSTXyAkKSJ8HOYsHtyWQvRB01lHjMOStSzYdEkYXeG8PPfSiSsQT9uCODHtr3GE3vqgPT8SDN+Kl29+NSW0ipovhDruJi5KnzxVy4Qq5pMUZifiY07cTIUXsDS0cYFjkwWDKFYWKp089jSfiQa2U4v5Ugkp6VahI16ezpWgLsUQseY2he/3+ge+zJGMJheZCwrGx00w0e5r50ZEf8cTmJ4glYsQSMRIkCMVCDCYTQRClqebXG1+nL9hHMBJEFESiiSjRRJRIPEIkEUn+PxQLSa/xEOF4OPlzIBYgFAsRik9vok6VoMKitWDVWpPi2qwyk25Mx66zY9PasGvtWLVW7Do7Dp0Dq9aa9LQOjZc8jTnNiKL0Pu8+JcWldZ+Sykk56xlZUmpotEW1UfoCl3z/L5Y89OcXspcZk0RC5Girm10NTWw93U1Db2ruv8UFNm6pzOKWymzmZJiA4ef+ciOKIkc8fn7b1ssrTi/ewRQfAnCD3cwnchx8IN2K7gpM0waDLbS0/C8dnX8gkZDuXacroLDwAXKy7yYaVaDRTC10ZSzGWkFqtVrZtGkTZWVlk45rG0mw3cvJXxznk6HBd1GukayPzUedPegEaXgH/iSJtejKv0a1+m+SbUM+H1uf+Aln978HQGZFOU//f/bOO7yO6vj7n729X+mqd0ty793GDePeANN7DyGQEPoLBFIIBBIIhISYEnoNptmAG+69914lWb3e3tu+f6x8bVmSLUsuIj+Pn332erWzM+fs2d3vmTMlZxOVgpXeSb3516g3WPLe7lbrdtHyxnHLm81mw2w28+6qAgYsvgFBW8wd6SlM2SJw58IQtsyBbOt0F2I0gtmyjOqCnWg0Bq685BEokqxn9n4KFldswG63AzB4SC4Z6RuprZPWuWUyNerUX7JQnMrMWj+2sARMdDIZ1ySY6eyFTftrWH6ghmDk+Au4Z4aJid2SuLJfJlmW01vPcFfVR4ZtJVq2DVn1bgR30zUVxbgcCcSl9ILUXogpPfGrk9Ccp9miz+dDVIi4QpK1xxl0Eo1G6Z/SPwZ2mrT4HbP2nWD5OxOSC3LUcjW3z7+dQ/amU4V0iuvEJ5M/aQQi/7n1n2yo2MA/L/snSbomfH+AiBjhwSUPMjl3MpfnXw7Ax3s+Zk3ZGv4z4T9npEdrSaPQoFVoMSgN6BV69Cq9tFfq0Sl1qAU18dp4TGoTBqUBo8qIQWXApJL+H6eOQ6toOA4uWmQugCy/A2r2I1btJVKxC0Xtfqjeg+B3NH19fRKk9o49z4H4TqjTeiDIWz5fb+99eD509AUjrD5cy5L91SzdX02N6/gkTSkXGJqXwPhuKYzrnkyauTFIONftqgiE+KbSyldVNg57j+uWpVFxY2o816VayNI0X/nkbOrocGyjuOR9amoWcixy1GjoQXb2L0lKmohM1jpr7ql0LCkpYfHixbHE/VqtlpEjRzJo0CDkcnmrZflcXkJrq3GuLEMmggcRcVQ6nSfmHa8+VLEDPpqKEHQj9rwG3+R/odFKrj/lB/Yx941XcNXWIJPL6XblNP4qfk5doI7uCd15fdC/WfVuAcUF1Tzx4RUXl03PlGbMmMGMGTOIRCIcPHiQyspKTCYThXVevnzrOf6s/Jhbs/PYJYT4zxdmTCVWSic/zkFfLnJlBINxIVVH9qHW67ly/P9D2FGfx6yznk3mo+zYtQOQ8siMHZuHz/cZTtdmAORyE0np97FBMZWPq1wc8B1fOr3UrOe6eAP+Ci8L9lSzrsBG5ITb1DvDxMTuyUzsnkRGC4oPHxvAuKuQVe2StsqdCFU7kdWXpzmZoiojYnJ3xKSuRJO6ISZ1I5rYtUkrXZOyzoCa4hEEoYHlrykSRbERqDj2L5aihOPLl8fA34kyBEFg5t6ZVHgqCEVDMetYWJT2Sdokfjvwt4QioRjvP7b8g1Vlq3hjzBukG5ov3eMKupg6aypy4fiS4DHwKRfkvHrpqwxIHYBckKOUKXlz25vUeGsQRAGNUoNSpkQlU6GQKVDJVbH/q+VqyVdQrkYj16CWq1HL1QgRAbPOjFahRavQoparG1i/Wtr3LaGzdZ/bG98FlxVwI1gPIas9gFCzX9rXHkDmKm/yGqJMgWjpePwZTelJNLknGJLbrF9r+X7u97naFWD5wVqWHaxlXYGtQeF3g0rOqM4JjOmSxKiOCRg1pwfDZ7td/miURVY339Q4WO3wxryRNTKB8WYdN6VaGGLSnlGKj9bq6PN58PrWU17+ES7XttjxOPNwMjLuxmRqHDl6NvqjtraWlStXcuiQNNlVKBQMHDiQIUOGNLh2a2QFC5y4fyxCtEvf5OWEsEzL4bIBx9/1gqMY9afTEDzVRLKHE7zuC/xhEZVKydY5s9k0+yvEaBRTcgp9br+JpwpfpMZXQ6e4TryQ9yrrPynB5woT9lTz8Gc3XQRvraWTLW8A17zyPV977mS5XsPDKUkMqNDy5EcuREHGvpvfprIsRFyKkmjwO6oLDqEzx3H1Dc8QWloHERFluh77pVrmLpmP0yk5BQ8dOoQ+fWQUHX0Nr1eq36pWp9Khw0McVo/n/XIbi+ucMftRrlbFnemJTDAZWLW3ijk7ytlcbOcEX1j6ZJqZ0iuNKb1SyYxvHPF42pmOzw5Vu6Byd/1+F1TvR2jG10k0ZUJyN0jqKi25HNurjed1pn6+6dhj8tLGl1havJT3J75PjinnlDxRMcph2+EG7Zp5YCYbKzfy6qWvkmHIaBSl2l4tED8nWe1eR1FE9NQSLN+NylmIUHtQyptWcwChmckUgGjKgKSuhC2dkWf0RkjpKblBKE4/yfmf68OzqGM0KrKrzMGyA5J1bVdZwyCOjDgt47olM6ZrMn3SdZj0TQdWnct2iaLIJqeXryut/FBtx3nCqsxgs54bUuOZlmhGGT6zSh+t1TEWhFDyIX7/UQAEQUlKyhVkZ92NwdDlrMk6kS8QCLBixQp27NgRm7z37duX0aNHNwI/Zyor4g7hmFeAb5u09FpNlH/gZ9ikfH51af7xE71W+GAiQt0hxOTucNd8RLWJ2opylr83g5K9Uu62riNG0/2GK/nligeo9FaSH5fPHxJfZeN/i4mERfSecjoe+ICRm5ZdBG+tpRMDFo6Btxfn7WPEunsZLt/FlZ16cDTs4u01XbCs3IPQdyhrs+/G5wyR189ATcFn1BQVYLAkcO0v/0RgThVRTwiZUYXhxnyW7V7Dtm3SrCQhIYErr7ycqLiW0tI3CQQqANDpOtIx/zHc+lF8VFbHfyvrcNbP+HRyGdemxHNLopE0pYaf9lQyd1cFGwutDYBczwwTk3umMbFHKh2TG/pcnNHLLRwgUL4Htf0wQtUeyfm5ai84S5tnMmUiJnclEpePPKUrQlJn6cOiTzpllFpbHuZTRdGeLZ5jfAAvrH+B+YXz+eeYfzbI7WZQGtAopNnd61tep9pbzYsjX2wy0OHN7W+es4CF89kf/xc+6m2WFfJLqThqD0lBRbWH6/eHwG9v/oKGFOnZSe4uTZSSu0sTJG1c+2hXO5HVFh1rHW42lbhYWu+iUus+vuQoCNAnM47x3VMY2y05Fjh2IfqjShT4psrO15VWjvqPr85kqJVcn2rh+lQLuTr1WZHVEr5AoJrS0k8pLfuCcNgOgEJhIiPjFrIyb0OtTjlrsk4kr9fL8uXL2bJlSywZfdeuXRk7dixJSU27rbRUliiKeLdU4ZhXSNQbRgR+kIWYEfVx+cAs/npNr+P8IR98fIWUzsuUCb9YBKZ0Dm/ewE9vvY7f7UKp1jD2nvuxDOjOXT/dRZm7jA7GDjwqvsTeRVKAXkLtLnpXfk/Cqy+ROnToRfDWWmoKvG0oqOOr917mVdXbfJWax/PaMN2iKfz5DRui14vw2N9YutWAKMLwazPYNu91rGUlmFNSue6RP+ObXUG4ygsKGZbrOlOqtfHjjz/icrkQBIFBgwYxZsxIqqpnUlT0JuGw5LtiNvUjP/8JVKaBfFtp4/2yWg54jju8XmLWc2dmIpMTzdg9QX7a3TSQ65RsYHLPVCb2SCU3XnlG0U7NDnqfXQJyNfuher+0rzkAzfjSAVKywsRO0scoIQ8s+ZCQD5a8VlvrTqnjWeY5xgfQ+5PeTf79+eHPM73jdACeWf0M5e5yPpz04XkHbyfLOhc8rdXx5/JRP2NZIR+irYhg5QFUrmIEWyHUHQFrAThKoRk/TBEB0ZSBkNwNIamL9HwkdYWkzqCNv/Dt+hnIOhM+URQ5VO1m+YFqlh+oYVOhldAJL0yDWsHITolc1jWZ0V2SSDY2Xmo7X/1hD4X5sdrOzIo6Np9QEF4nlzEtycx1KRaGxzeufHAu+9Dl2ktxyQdUVc1BFKVVGY0mi7TUW8nKuhGl0nDWZJ1IwWCQ9evXs2bNmljaj5ycHMaNG0dWVlabZYVqvNi+O0ywUPr+CslanvY4WenxMSw/gY/uGoxKUe96Eo3AV7fD/jmS+9DdCwnH5bHy8w/ZtuBHAJI75DH1oScJxym5a8FdFLuKydXmc1f1M5TvliJgs4sX0sW/iZz338NvsbS6tulF8EbT4C0ciTLq+R9YJv4CURZmYqceWENO3qmeTPz7PyJPSMD26HtsXlSOQiljygN5/PTWn3FUVWJJz+T6372Ib24F/v1SiLRxbDbK4UksWLCAnTt3ApIVbvr06aSmmjla/B9KSj6MRedYLCPJz3sMo7Ena+xu3i+t5adaR8y/IVml4Ja0BG5LTyBdo6LWHWDx3irm765k7ZFaQpHjtzUzTsOEHqlM6JHKwJz40yaGPOOXgM8GNQcQq/cTrtqLwl6IUHsI7EcbRL01IkMKoiWPiLkD8sR8BEsuxHeA+FzQWc66xe58AqPW8l0EbxeOr0meaFQK/rEXSwmzY1uhtHdVnPqiahMkdJQmMAmdILEjJHRCtOThjwj/c4CqPd1ndyDMmsO1LD9Qw4oD1ZQ7GkZ95ibqGdNVWg4d1MFy/CN9FnVsKU8gGmVJnZNvq2wsqnUSrH82BaRo0etS45mcZEYvb77O6dnuQ1GMUle3guKS97HZ1sWOm80DyM66h8TEsQQCZ7ZM21Idw+EwW7duZcWKFbHC8UlJSYwfP55OnTq1SN6pZInhKK7lJTiXlUBERFDK0F6Wxd17jrK9zElugo5Zvx5OnE517GIw73HY9J6UXuf22dTJM5n7z5epKS4CoM/EqVx66z04Ik7u/uluCh2FdJR345ojD+GoCCBEw3Q98Dk5+lqyP3gfZWpqmwrTXwRvNA3eAB6ZuZ3xu59ginwjb/WeyJuuffQyd+X5dzwECwuJu+121msnUH7QQXyqjgn3ZPHtS8/grqslqUMe1z37FwKranCvlPxYtL0Tib+2MwcLDjFnzhzcbikHzyWXXMJll12GKNooLJpBeflMRFEqo5KUNIn8vEfQ6fIpcLj4xurh84o6qoPS3+UCTEgwc0dGAqPijcgEIZbhe8HuSpYfqGngcBuvUzKmawoTeqQwqlMSWlXjl8FZewmE/JIFovagtFxUVwDWI5Jlwlt76oupjPVALgfMWRCXDXH1e3MWoiYOfyDwfxO8rXoV9v0oLb8pNJA1BHHcnySA0JysvT/A5vcln8ZwEJK7Il76FHQc26p2/Zw/6g0oHJTSbTjLEB2lhGsLUbjLERwlEmBzlEi1PU8lS21CjOuAkNhRSmabkC9ZmC15oE9schLyvwqoLuR9FkXYW+Fk5aEaVh6sYctRW4NJrFohY2heApd2TuKSDia6ZlguaH9ERZGNDg/fVtn4odqOI3w8mr2rXsOVFgM3ZCaTfppo0bbo1xRfOOyhsnIWJaUf4fUWAlIlhKSkSWRn3Y3Z3LfV8k7HE41G2b17N0uXLo1lbIiPj2f06NF07NgRna7t/oaBAju2WYcJ19cjVXeOx3xFPr+dv5cFeyqJ1yn58p4BdE4/YXysehWW/BkQEK/9kF1VWpZ9JOVu05rMTLr/YdK69cSHj3sW3sNh+2G6hwYybt+dBD0RVCEXvXa9Q0q2nqx3/4MiXrKuXwRvbaTmwNucneXM+/It3lT9C1t8NhMSNPgjfj62PIL2iVdALsfywefM/86FxxGky5BU+k8wMfO5p/A67KR16sK1zzxPaLcT2+zDUiBDpoGEW7vhEn0sX76cHTt2AGCxWLjyyivJycnB6z1KYeG/qKz6HmnZRUZq6lWkp99HnDmPkCgyv9bBx2V1rD0hCWOORsWt6QncmGYhSSXlbvIEQizdW8HyQ1aW7K9uUAxZrZAxomMiY7ulMKZrMqlmaangvLyAfXawFiDWHSFcfQCFuwzBdhSshdBMZF0DWSojoikdwZyJYM4A07EtHcyZYEwDtbHBh/N/Brx9ejX0vEZKrBoNw5LnEav3wAMbQKVvmm/+U1KR8NyRUqmjbZ8hrn0DfrEY0vr8b37UnXVoQjYEVwU4KyQrmatCAmsOCbDhrjr9xQS5NLbic+onFPWbJRfic8/7RKI99/35vs/VTj9L95azrsjBmsO11LobAu0OCTpGd0nm0i5JXJKXgEYpv6D9IYoi+zx+vquyMavK1qDqQapKydUp8VybGk83vea89z1YKS37lPLymYTDUtCGXG4gI/0GsrLuRKNJb5LvbOgoilKutiVLllBdLfmFGQwGRo0aRf/+/VuV9uNkWRFPCMe8QrxbpGdeZlASd3k+2t6J/G3BAd5ecQSVXMZnvxhMr1TdcVknJOH1j36ehVvdHNqwFoCc3v2Y/OtH0ZnjqHJU8eDKB9lv288g23gGHpqGGAGju5Reu97C0rcLmTNmIDccT/V1Eby1kZoDb05/iGF/nsMG5X3ohQAvjLiTmWVLGZkxkt99L8e1aDGagQNR/v6f/PD6dkQRLrutK0lZQb7601P4PW6yuvfiqqf/RLTUT91ne4l6w8hMKow35GPIS+DQoUMxXziAIUOGMHbsWFQqFW73AQoK/kFN7SIABEFBevqN5HZ4IOYYut/j45OyOr6pssYCHJSCwKREM7enJzAsTk+w/sMSiYpsPmpj4Z4qFu6tpNTWMON6zwwTY7tKTrodz3NW8AY8IX/9MlWhtD+2HbOGeGpappBSD8YUCcgZUxENqYQ1CSjiMxD0SVI6BX2yZB1pJsP/MR2PUbsAbyeTpxZeyUe8cy7kDG+5rBlDoMdVcOmTP5+PejgoWW09NVK73dUSAItt0v9FVyVCU6WfmiK5GsyZiOYMIvo05Am5CPE59dbebDCmwynyo7V3kPO/JMsXjLChsI41h6Ua0fsrXQ3+rlPJGZafwKjOSYzqlESHxMY5MS9Ef1SLArOrHXxXbWvgw2yQy5iWFMe1qfFcEmdAXn/d89X3oijicGyl6Oj7WK2LEetzWWq1OWRl3Ula6tUoFE37s50tHQsLC1myZAmlpVJAnFqtZsSIEQwZMgSVStVmWWq1Gt/W6lhAAoJUj9Q8KReZVsHMTcU8+a0UIfr6DX25sm/6cVkFy+Dz6yAapjTvLuatd+Cqk3K3jbjpDgZOnY4gk+EMOPnFT79gv/UAl5XeQOfSoQAk1W6n+96PMV82kozXXkV2Uvqri+CtjdQceAO45b313HD0T1whX0fxoDuZVrsMEZHvBr1N5KZfIwYCpP/jNQ4L3Vg/uwC5Usa1Tw4k7C/n6xeeIejz0aHvAK58/Flwhqn9eC/hai8oBOKv64y+TzI+n4+FCxfGIlLj4uK44ooryMvLA8Dh2M6Rglex2SS0L5Opycy4lZycX6JSSSVGPJEIP1Tb+bS8jq1Ob0z/XK2K65NM3JKZTLL6uPldFEX2V7pYur+axfuq2F5i58SRkGRQcVnXZC7rkszwTomYNKfPwn7eXvZBL6KjhGBNISp/NYKzQoqEdZSBs1yyqLT0ww2AALoECczpEiR/O10C6BLBnI3Y+xqQKUGQSdnqBUHiOY2+5w281R2BN/oj3r8Wkru3jC8aRXy9Fwz/LQz+5fn/qIsihLxS8lmfXYq+9FrBZwVvXey36LUSddci89UheGul88+ARKUewZQmAXhTumR9NNZbZ80Z0pK8LgGE1kUTnrX+uCirSb5wJMrucmc9WKth61F7g+TlAN1SDYzuksyozskMyIk/J75rreGrCoT4sdrGd5VWtrqPAzaVIDAuwcRVKfGMSzChbcIH+Vz3fTQaoKpqHiWlH+Ny7Yodj4+/hKysu0hMuAzhNDki26pjeXk5S5YsoaCgAJBytQ0ZMoThw4ej07U9hZIoinhKbXjnlRAslL4HylQ9cVd3RJ0tAaW1h2u5/YONhKMiD43txCPjOx+XZTuA8NFUogE362WTWL/PhyhGiUtJY+pvnyC1Y2dAKvV436L72FdxkMmH7yHNJrmvdCiaS27RfOKumk7a839GUDSeAF4Eb22kU4G391YVsHH+J/xH9Q8wZfBov4ksKl7M9I7TeXBrMnUz3kSRlkrej3OY9+FhivfUEZei47qnB1JddIBvX/wD4UCAjoMu4fJHnoKQSN1/9xM4YAPAOCYL07gcBJkQs8IdywvXv39/JkyYUO/PIVJVtZLSshk4HFsAkMt1ZGbeQU72L1Aq42I673H7+KSslm+rbLjrX3SKet+4m9IsXGYxoTipOHKtO8Cy/dUs2VfNqkM1eILH/S8UMoEBOfGxSKwTa66eSO3hZR+joAdclfVbBbgqEV2VRBxlyH11CJ4ayUrjrYPTVWYwpjUdAagySL55an39b139Xg8qPaJST1hQodAaEJRaUOokHzWlVtrkailHl0Il/ZYrEeHM+kMU4b83IfrtcNd8oIVAcc0/EVf/A369EfRJp+YRRWl5NuyHcAAx5CPgtqEWIgghrwTCgp7j+6AbAq76zQ0BJ2LQjehzIAScUlUAvwNaWTcVQS4BLn2iBLgNqfX7FAmcGZIR9cn4VfFoTEkIspaVBPo5g5z/FVlqtZqD1W7WHq5j7ZE6NhTU4QqEG5ybEadlRMdEhndK5JI8CwaF2G76oy4YZl6tndlVdtba3bE3iwwYEW/gqpR4piSaMStPndz3XPV9IFBNWdkXlJZ9QShUJ+kmU5GYMIUOHX6B0ditRbLaomNJSQlr165l//799fJlDBgwgFGjRmE0Gs+KLDEUwbmsBNfyUohKAQmmcTkYRqQj1IPlw9Vurn5zDU5/mCv6pPPPG/vGlrYDVQdRf3Y5LpuduXWDKZc+13QfNYaxd/8KlVYCl96QlweWPMDhomKmHLgPsy8JuRCl2+4PSK7ZhuWOO0h+8v81+w66CN7aSKcCb0dq3Ex5dRGb1fdjFHzsuOZNbt36VxQyBfOnfI/z2juJVFSQ+MD9GO7+FV/9ZRNuW4BOg1IYf3d3inftYNbLzxEJheg6/FIm/+ZREAWscw/jXyutvWt6JGC5vgsytZxAIMDixYvZtGkTAEajkWnTptG5c+fYy81mW82RgtdiMya53EB21t1kZd2FUnl8AHjCEWZX2/isrJZtJ8z80tRKbky1cGOahRxt4wSf/lCYNQerWFtgZ9nBGgpOquGXatIwslMiozonMaJjIvH6tpu2L9iHJRKWAJynWlqK81rrt7rYJnprET1WhIAdweeAoOvUglpLggxRoakHdSoEuQpkCpCrpDQSV70F4RBwQq3XRX+AI8sQb/laApmcsvysRHu/h5+eRrzqHcgZLvEIclAo4eu7pDQwkaC0hQMQ9nHKqOG2kCAHbZzkh6ezgNZywj4eUWshqDCiik+Xlrr1SdK5pwFkP8ux+H9QliiKFNR6WF9Qx+qD1WwsslPnaei3ZtIoGJqXwMhOiQzvmEhu4nG/zvbQH45QmAW1TmZX21hpc3FCjAQDTDqmxhu4Oj2R1BYGHpyLdjkc2ykt/YSq6nkcS/WhVqeSmXELaWk3EI3qzvn4sFqtLF++PJZtQRAEevfuzejRo4mPb2Jy3EpZ/oM2bN8fJlInffPUXeKJn94RRfzx9C9WT5DpM9ZQbPUyICeez38xBI1Scp0RvVbE9yZwqMjGosouBCIyVFot437xa7qNGH1cTtjPb5b+hrJ9dsYfugt1WItWHqDnhn9gdJeQ9PBDJNx33yn1vQje2kinAm+iKHLpK8t5yPV3rpGvhsH3cYdQxdbqrdzT8x5uLe9IzRNPIKhU5M2bS53fwKzXtiFGRS69uQs9R2VwZMsGfnj1RaKRCL3GTGDcvb8hEAgQ3evA9l19IEOqnoQ7uscGWFFRET/88ANWq5RqpFevXowePRqLxRKbHdTWLqGg8B+43dIMRqEwkpV1N9lZd6FQGGP6+/1+jkbgvxVWvq6yYg0d//gPjzNwY5qFKSeEoZ/8oBTXeVl+sJpl+6tZe6SuQfSqIEDvDDMjOyUxslMi3ZI1GC9ABvLzKisSOr7c57NJS7QB53Frk1/6LQacRHxO5FE/QtArWaSCJ1injgGjllByd7j7J4gEJCsYwJLn4fASuPEzaRmwJbR/Hvz0O7j8dcgbffy4TCGBxg8mSrn8TtUfchUotFJwhEonWRRV+vq9TkqPoTJIASNqI6gNiCojQZkGlTERQRsv5UnSmCW+U9yLn+X4uCirWZ4Twdr6AivrC+oa1AsF0CrlDMq1MCw/gWH5CfRINyOXNS3/QvWHMxzhpzonP1TbWWF1ETrhM9rLoOXK5DiuSI4jS6O6YH0fiQSorp5LaemnOF07Y+eZzQPIyryDpKQJyGTKcz4+7HY7K1euZNu2bTFXkm7dunHZZZeRnJzcLN+Zyoo4A9jnFODbKWUykJlU6CZmYeqXiuyEyV4gHOHW9zawqchGlkXL7AeGk2CoN2KEfAQ+mM7yLXXsdqQCkNaxC1N++wRxKamxawQjQX679Lc4tsgZVjQdGXLiZTa6r34ZdchF6h9+T/xNN522XRfBWxvpVOAN4I/f76Z4w2w+VL0ChhSWXvcmDy1/BKPSyPdTv8f70BN412/AOH4cmW+8wbaFxaz97jByhYxr/t8AkrKNHFi3irn/fAVRjNJv8hUMvf5WtFotwWIXdZ/uJeoOIdMrSbitG+oOkg7BYJDly5ezbt06RFFEp9MxadIkevU6nvFZFKNU1yygsPBfeDzH6ryZ6kHcncjlhgaDPhCNsqDWwRflVlbaXDGzvkEu44rkOG5MtTDQpCPQTPScPxRhY6GVVYdqWHmwlgNVjR2Gh+RaGN5RmiV3STEia+bFK+nffj4sF4RPFCULV8gHYb+0JOlxoFbIpBJlkbD0d7kSMgZIecfEiATADsyH274DS269v6IICE1b3gRgzyyY8yhMfwu6TD6+WCwICMgka1bVHgkcypSSxU+pkZZ6FWppL1cjCsL/Rt9flHXOZUWjkm/tpiIrG4usbCy0NgJrKoWMfllxDMw2MapLKv2yT++3djZ1bCnZg2HmVNbyk93L8pMAWyedmunJ8VyZEkdH3XELz4Xoe7BSVv5fystnEgpJk39BUJGSMpWszDswmXq1WVZL+FwuF6tWrWpQFaFjx44MGzaM3NzcsyZLjIp41pXjWHgUMRABAQzDMzCOyyIohhvwiKLIo1/tYNa2MowaBd/dP4xOKfVLtdEIVe/cwty11diCOhAEhky/nkuuvQn5Cf5qoUiIR5c+RnRVMt2rhwGQKRaRv+ofyGWQ/te/Yp42tUXtugje2khN1TY9kVYcqOHej9axWfMAZtxEbpvN9J2vUeQs4uE+D3OzdiRFV18NkQhZ772HbtglzH9rF0W76jAnabnu6YGotAr2rFjCT2+9DkC/qdMZfevdCIJA2B7A+uleQuUekAvEXZmPftBxlF9WVsYPP/wQC6Hu1KkTU6dObaCrBOLmU1T4Bp76uqkKhYmszLtITLwBg6GxX1OJP8jXlTa+Oqn0Sp5WxVUJRm7ISCKriWXVE6nK6Wf1oVpWHqph9aFarN6GfkwJepU0g+4o+adkWxpa5f5XP2LnVMe5j8Gur+HGL2K53QBElVGyhAEsfk5KuXLVO9L/d30Ds38Fk/4K3S4/ziNXI2jjWtymc9quC8x3UVbb+fyhMFsLa9lR7mZzkY1NR224/A191lQKGf2z4xiam8CQPAv9suJQKWTtsj+soTA/1TqYW+Nglc0dS54LEmC7IimOy5Pj6KJvuvj5+ep7URSx2tZSUvwJVtsyqE/nrlankZFxM+lp16NSJZwXHb1eL2vWrGHjxo2Ew9K9z8nJYcyYMWRlZZ1VWcFSF/bZRwiVSSmzlJkG4q7qiCrd0CTPv5Yc4h+LDyGXCXx01yBGdJQC/sRIhM2v3suarVVEkaE3GZj80NNk92hYVSccDfPUwmfRLM0n3dUREOnq30Ta+o+RadSk/+N1jKMvbXG7HA4H8fHxF8HbmdKMGTOYMWMGkUiEgwcPUllZ2WQH+kMRLnl5Fc/xNjcolhPueztfdxzGi1teJEWbwqyps3C8+g9cX/wXZW4u6TO/JBiE2a/uxGMLkts3gdG3S1mhdy/9iZWfvAfA4KtvZOAV1wAgBiO4vy8iuFfyjNQMTkY3ITPmXBmJRFi9ejWbNm0iEomgUqkYNWoU/fr1a2ASlrJiL6Sk9C18viOA5BOXlnYraam3oVQ2BqeiKLLR5eObGgfz6lx4TygbM8So5eokM5MtBoyK5tNpgJR0clexla1lHtYV2th81IYv1NBXKtWkZlCHOAbnxDO4QxxZ8dqYle9M6diDea55zjdfUzyCIKCuDzMXnotrki96xQyEfrdI/5l9v5RW5c650v8/mopwdE0jHrHPTZIlrp4CgQAteSX8X+r7i7Ka57N6gmwvdbC12MG2Ege7y12NokF1Kjn9sswMyDYzIDuOPpkm1E28S9pLf9QEw/xkdbHA6ma903uihyn5aiXTEk1MSTDSWXfqiW1b9GspXzjspLrme6oqv8LnL4wdN5uGkJp6ExbLaATh1MERZ0tHv9/Pxo0b2bJlC8GgZAxIS0tj1KhR5OTkxADU2ZAV9YfxLikjsFlKGyWo5ejGZaDun4RwwkrPiTxzd1fx+Ld7AHhuWheuH5ABgMdmZenfn6SkzA5AfucshvzyaeISG9ZMjUQjvLDw75iX98AUSECmFOlX9QPmnQsRDAbi//4KpiFDzqhNTqeT1PpKCxfBWyvodJY3gHs+2kTo0BI+Vf0VUZdA4OGdTPhuCraAjb+N/BsTEoZTMHkKEauV5CefxHLnHVQWOJj96jaiUZFRN3am56XSYNn843es/PxDAC697R4GTJ0OSCDKtawE16JiANT5ZuJv6opcf9wvweVyMWfOHEpKSgDIzMzk8ssvb+Q7IIoRqqsXUFj0Bt56S5xcricz41aysu5udhbmCUf4scbOVxV1rHMe98fSyAQmJpi5NjWeS+ONKJtYCj15phMMR9leYmftkVrWHKljR4m9QcZzgDSzhoHZZobmJzKog4WOyYYWzzTbswXifOt4jPd88Vzs+/97siJRkYNVLraV2NlebGfzURuFtZ5GfPE6JYM6WBicK23dUo1nvyRfG/ia4in2BZhX62R+rYNNDk+D+PMeeg1TkuKYmmgiW067uM8u1x5Kyz6nqupHolHpPS2X60lMnEZO9h0YDJ3PmqzT8QFs3LiRdevWxeqPpqamctlllzUqZdVWWWq1Gv+OWilnm1ta5dH2TcI8JRe5UdUkj0ajYVuxnZve20AwHOUXI3N5ZooUVXtk8wZ+mvEKfl8AhRBh9Jje9LznxUZuQ1Exyosz38CwqjOqqAaVMcKgfR+iPrwNeUICme/+Bzp0OON2XbS8tZFO5/MG8On6o/xp9g62aX+NSXTCrd/xpvsAb+14i54JPfli6hc4vv2Wimd/j8xgIH/BfBSJiWxfXMyabw4jUwhc88QAknNMiKLI6pmfsXHWTADG3vMAfSdMicny7anFOvMgYjCC3KIh8fbuKFJ0sYEoiiJbtmxh0aJFBINBZDIZI0aMYOTIkSiVDfOxRaMRysrnUF7+Lm73PgBkMi2ZGTeTnX0vanXD2QUcH/S1yJhVbefrSiuHvMf9VBKUCq5IjuPqlHgGmo4vg57uwfQFI2wtttU7K9exvQkwF69TMiDHwuDceAZ2sNAz3dyk/0t7/2BeCB2P0ZnIOlOe1ur4v973/4uyalx+Nh2pYXelh23FdnaW2hukEDpGHZMNDMyJZ0D9lqqXnZcE363lE0URn89HQQTm1zpYUOtgzwnR+AD9jDqmJpmZmhRHbr2F7ULf50jET3X1PErLvsDp3BY7V6/vTGbGraSkXEE4rDhvz1ggEIgtjx4DccnJyYwePZquXbs2WBFqqyxRFHGX2PAtKCVY4ABAkaQlbnpHNPlxp2xXjTfKVW+upc4TZFy3FN65bQDRUIAVn37AjkXzJL3VbqZM6U/Cja814bcZ5e/vfoR+WwcA9Cl+Bq/8F0LFUZTp6VKd0pycVrXros9bG6kl4K3E6mXky8v4i/J9bpEvgX63Ujv+OSZ+O5FgNMgnkz+hb2Ifiq6/Af/u3ZivuZr0v/wFURSZ//YuCnfUYkrUcP0zg1Fp5Ph8PjbP/opN338DwKQHHqHHpWNj8kKVHmo/2UvE6kdQyYm/oTNCnr7B4HA4HMydO5eDBw8CUqH7adOmkZubG7vOiTOWurqlFBb9O5ZiRCZTk552PdnZ96LVZjTiOSZLFEV2uHx8U2VlVpWdutBxH5YsjYqrkuO4KiWermdY0sUXjLDlqJU1h6rZXupiW4kN/0nLrGqFjD6ZcfTLiaN/djz9s+NJMqov+Iv0XPFdBG8Xju//siyXP8SuMgc7Sx3sLLWzo8RBmb1xJLReJadvdhx9s+IYkCM9j7Hi3ee5XWfKF46KbHC4+anWwfwaByUnlKaSCzDUbGBykplJiWYym0jrcaHus9dbSFn5f6mo+JZwWAIugqAkOXkSmRm3YjYPiL2nz0ffB4NBNm3axJo1a/B6pYTwiYmJjB49mu7duzcJ2lorCyAajOBcWizVCK/P2WYck41xZAbCKQJbRFGkxu7mlg+3cqjaTY90E1/ddwmeimLmvfF36kqlFa4BllJGXNoHxfUfgkzWQMdQMMKbr89CWSitVMXl2Rjw3WuIdiuqjvlkv/8+ypSUVvf9RfDWRmoJeAMY/9oKEmo38qXqBdCYER8/xB/WvcDsgtmMzR7L65e9jnfbNo7edDMAHb6aibZ3b/yeEF/9ZRMuq5/8fklMuLcHgUAAtVrN8k/eZdv8HxEEGVN++zhdh42KyYt4Qli/2EfgiPTAakenEz8+F5n8RB83kb179zJ//vxYofu+ffsyYcIEdDpdk0CszrqCosJ/46ifvQmCgtSUK8jJuQ+9vuMpB2IoKrLS5mJWlY35tQ48J/i3dNNrmGoxcHVaInnNOPCeTA0elIjI7nIHm4usbCy0sfmotUEt1mOUZdHSPyueXukG+ndIpHu6KZajp6Wy2tuH5WzIOkYXwVv71/FCynIHwuwtd7K7zMHuMgc7yxwcqXFz8pdAECAvUR8Daf2y4+mYbGg2bcf5bldL+FzhCMusLhbWOlhc58R+QvF3jUxgtMXI5MQ4xieasFygxLlNUSQSoLx8LtU132K3rz+usyaTjPQbSUu/DnV9dZ22ymopX1Og7VjR+F69ep0StLVGR1EU8e+tw/5jARG7tPKj6RpP3BUdUVhO/30JhSPc+eFG1hyxkmJSM/v+YZSvXciqLz4iEg6jV4aZlLqPDj16wK3fSZH1J+gY8op8/I+lyGp1RIQIaV3L6P3xG0S9XjS9e5P1ztuxAvMXwdsFopaCt5fm7ePdlYfZbvgtprAV8aaZ7DVnceNPNyIgMPequWSZsih/8ikc33+PpndvOnz5XwSZjKpCJ9/9fQvRiMiI6zvR+ZLEmCPlonf/za4lPyGTy7n8kafpOGhoTKYYieKYW4h7rVSsXUro2xmZuuGLxufzsXjxYrZskaov6HQ6Jk6cSK9evZpM+yGKIjb7eo4WvYXVdsyRXSApaQI52b9Cpep02oHojURZVOdgVpWNpXWuBpFYvQ1aLq/PddRUIuAT9Whu0EejUk6orcU2th61sbXYxqHqxh8ZpVygW5qJPplx9MmKo0+mmbykxh+Z9vZhOduyjtFF8Nb+dTxfsmyeIHsrHOw4auVAtZdd5Q4Kaz2NniGQKhf0yTLTOzOOPplx9Eg3oiTSLtt1Kr5iX4BFdU4W1zlZbXM3SOlhUcoZZzFxmVnLhBQL+iZKFp1NHc+Ux+stpLz8K8orvo1VQAAZiYljyMi4iQTLSASh6Ynquer7YDDI5s2bWbNmDR6P5OMYHx/PqFGj6Ny5Mzrd2c/rGa7zYf/hCP76SkTyODW6iZmY+qa1SJYoivx+9m4+21CMVinns5u7UjTrA4p2bAUgzxJgYsI2dGkd4e75DSroiKJI8f4afvzPNgSfEp/CTX6XArr95wPEUAjd0KFk/vvfDQrMXwRvF4haCt7WHanjpnfX81ftp9wozkfsfQP+yf/k0TWPsrpsNTd3vZmnhzxNuKaGIxMnEfV6SfvrS8RNnw7AjiUlrP76EDK5wNTf9iSrc2L9mnqEBW++zr5Vy5ArFEx/4vd06DuggWz3xgrs3x+BiIgiRSf5wSVoG+lYXFzMjz/+SE2NFIWTl5fHuHHjSEtrftA7nTspOvoWNTULY8fM5kvI7XA/FsuwFg1GeyjM3Bo7syqtrHM0jNDqa9RxRXIc05LMZJ8E5M500Dv9IbYX29ly1MrWozb2VLiwnpSRHaQIt+5pJnpmmOs3E/mJesKh4P8sgDhmzT0TWWfK01od28NH/X9ZVjQqUmz1sq/Cyd4KJ3vLpX2Fw9/kdVJNmthz0StDAmxJxrY9m+eiXS3hc/t87A5EWGx1sbjO2aDwO0CeVs3ERBMTE80MMuuRcYYl6NqgY0t4otEA1TULKS/7EtsJVjaVMpn0jBvISL8ejSb9nOh3Kr5gMMiWLVtYvXp1I9DWu3dvZLIzT+9yOh3FUBTXihKcy0sgLIJcwDgyE8NlmQSjoRbL+mB1IX+esxcBeHmIgpq5H+NzOVEoVVzayU+f6Bqp5vEvFjdKcL5vbTlLPtuLEJVRqyujf+ZhOr73DUSjGMePJ/3VvyNTNR8ccRG8nUdqKXgLRaL0//MiOgf38K36OUSVEf+Du9ju3M8vF/8SrULLomsXYVabqXvvPar//irypETy5y9AbtAjiiIL/rObgm01GCxqbnhmEJr60lLRSIQ5//wbhzasRaFUcdVTfyK75/EcM6Io4jpUi/vrAqKuIIJWQcLNXdF0im+kZzgcZu3ataxYsYJIJIJcLmfkyJGMGDECxSlmmm73QY4Wv0NV1Y+IogS/jMae5GT/kqSkichkLVtWcMsUzK918EO1VN/vRC+23gYtU5PimJJkppNe0+YXjlqtpszuZ3uJPears6vMgS/U2LFarZDRJcVA93Qz3dNNdEsz0TXViFGjbEJCY1nt5WXfHmS1Z6DYWr6fi6yyOidFtiAHqtwcqHRyoNLFwSp3k2MeINuio3Oynj7Z8RJgSzc3AmrtoV1nwlcTDLHc6mJpnZOldU4cJ7hvyAUYZNIzLkECbJ1OcuFoL/fZ4zlMeflXVFR+RyhUXzwTGQkJl5Kedj0GwyVotS2Lvj+b7WrK0hYXF8eoUaPo06cP8mYq8bRVR/8BK7Yfjhwva9Uxjrgr8lEmN3b/ORUt3V/FLz7ejCwS4jf6vUT2rgUgKSeXqV1sJJT8KFWBuWs+pPaM8UWjIuu+O8z2xVImhwLLDsbpC+nw6SIAzNdcTdpzzzVZYP4ieLtA1FLwBvDA51uYv6ucnaZHMQarCVz1Icpe07luznUctB3k4f4Pc0+ve4gGgxRcfjmho8Uk3PsLkh97DICAV/J/c9b5ye2byOT7jldLiIRD/PDqixRs3YRSreGa3/2ZjK7dgeODQxkUsH62n2CJCwQwT87FMDKjyQFTV1fH3LlzKSgoAKSAhqlTp5KXl3fKNnq9xRQWvUt19XdEo9KDpNVkk539C9LSrkEub3lCyppgiDk1Dn6strP+JCDXWadhapKZcSYN/SzmFvlMnErWMYpERQpq3Owud7C7zMmuMgd7y524TypwfYwy47V0SzPRLdVIpxQjXVKNdEjQx6Jc28vLvj3JOkbtcYm2tXztSZYoitS4AxyucnOo2s2haheHq6Xfde7GlmaQkt92STHSPc1E93Rp65pqxKBWtJt2tZYvIopsd3pZYnWytM7FDpe3QTqPeIWcMQkmxiWYGG0xEn8K/7ULeZ/DYQ/V1fMor/gKh2Nr7Dy1OpX09BtIT7sWjSb9gvS9TCZj06ZNrF27NubTFhcXx8iRI+nbt28MtLVFXlM8Yasf+5wC/HulZWKZSUXc1Dy0vRNj57RU1t5yJ9e9vRatq4rr3CtQOKXE9gOmXsmIxAIUG9+Uqsfc+i3kHU+mG/CGWPj+Hor3SBUpNmcs4AZvFTmzNgJguftukp94vFnZF8HbBaIzAW9fbS7h/32zk9fjvma6fxbhbtORX/8RPxz5gWfXPEuyNpkF1yxAKVfiWrqM0gceQFAqyZvzI6qcHACqihx898rWmP9bnzFZseuHg0Fmv/I8R3duQ6XVcd2zL5DasXODwUFExDb7MN7NUmF7bd8k4q/uhEzV2BciGo2ybds2li1bFgto6NWrFxMnTsRgMDTZxuMPs5ey8s8pLf0kNjNUKi1kZt5OZsYtqFSWJvmaG8A1wRA/1TqZW2Nv5IuSpVExMdHEpEQzQ8yGJvPInYmsxv0gUlTnYVtRLUfq/OyvdLG/wkl5M8tKCplAbqKezilGOiUbyIlX0zUjjtxEQ4uCI1qjY2t5LoSsY3QRvLVNlqBQUmz1UVDjpqDWQ0GNh4IaN0dqPDh8jYN1QKp0lpOgo3OKka6pRrqkmuonHLom86n9XPuwMhBihdXFcquTFTZXg5rMAD0MGi6zmBhlUHNJYjzK0+SSOxc6toTH5/MRDO6nouJrqqrnEolI1ixBkJOQcBkZ6TeSkDCqgS/b+ex7v9/P2rVr2bRpEz6fFGF84vLoyaDtbOlIWMS1shTnshIIR0EGhmEZmMZnN/LpbomsaqefK/+9mtSSDQyzbUAmRtGZ45j0wCPk+jbAT09LJ179HvS+LsZnq/Qw761d2Ku8hGRBlud9xgMFPrKWSjWekx59lIR7f3HKNl4EbxeIzgS8Vbv8DP7LEvoIh/le/QdEpRaeOEJIrmTitxOp9dXy0siXmJY3DVEUKbn3l3hWr8Zw2WVkvfUmIN3orQsLWT+rCJlc4OonBpDS4fiNCwX8zPrrc5Ts3YVGb+C6P7xIUk5ug8EhiiKe9RXYfyyAqIgyXU/Crd0bReEcG1QAy5YtY+NGaSahVqsZN24cAwYMaGTxOnkgRiI+yiu+obj4Pfz+UkBKM5KWejVZWXej1+c1yXcqcoTCLKyTgNyyOheBE4ZhnELO2PoljzEWI4YmsrGfrZeb3RtkX4WL/ZVO9le4OFjt4lCVu1krnSBIlrq8RAP5SQbykvTkJerJTtCRZtY2CJK40B+/cynrGF0Eb6fn84cilNq8FNV6KarzcLTOy9E6CaSVO/xEm3kDywRpybNjspFOKQY6JRvIT9KTaVJiMekveLvOtiy718t2f4TlNhcrrC72n+S7ZlLIGBVvZEyCiTEWE6nq1hVVP1/9EQjWUlkxi7Lyr2PVbgC02g6kp19PWupVqNVNF2Y/H+3y+Xxs2LCB9evXx74RFouFUaNG0atXr2ZB29nQkSIv9jkFx5dI88zEXZmPMkV/Sr7mZPmCEW57YyGZO2eT5S8DIH/gEEbdfi/xNesQvrkLEGHcczDi4Rjf0T11LHxvD0FfGJfKxqJO7/LMFjlp6wtAEEj94x+Jv/GGFrfrIng7z3Qm4A3g8jdWs6vMzp74J9D7yhGv/wSh+5X8Z+d/eGPbG3SzdGPmtJkIgkCgoICCK66EcJisd9/FMHJEbDa24tMjFGyrwZig4frfDUKjP+57FfT7+PYvf6D84D60RhPX//El9InJjQZHoMBO3ef7iXpCyHQKLDc19IM7eVCVlZUxZ84cKioqAEhPT2fq1KlkZDSf5+0YRaNhqmvmU1z8fixXHEBiwhiysu8mzjyk2YL2zZEoilg9XjZ4Q/xU52RRnaPBDFspCFwSp2d8gplxCabzkjBTFEUqHH4OVklA7mCVi4NVTgprvTj9TYM6AJVcRpZFS4cEPTkJerItWlIMCvJSzGRZdOhUp49sa28f2hnLDvPTnkqOVLvRKOX0z4nnyUldyE+SrLbN8a0vqOOFuXs5WOUmxaTmvlF53DIk55Q8Z6tdreVrraxQOMLRGgc13iilNh+lNh8lNq/02+qlwunnVG9Zo1pBXpKe3EQ9ebEJgbQ/2crbnsHKmfJERJHdbh8rrS5W2Vyst3saRKwLQB+jjtEWI6MtRgaa9CjOQgT5ueyPaDRIXd1yyiu+pa5uOaIovS9kMg3JyZNJT7ueuLhBp5V7Ltvl8XhYv349GzdujFVEsFgsXHrppfTs2fO0oK0tOoasPqzfHyZ0wA6AzKgiblou2t6Na2+3VFY0KvL//v4Z8dtmo4kGkKvUjLnzXnpeNoHQ4eWoZt6AEAnCoHthyitQb/zYvriEdd8dRhShwljA8tz3eWG5npSdZaBQkP63v2GeOqUZjdreF3ARvLWZzhS8vbbwAP9aepj3Umczzv4VYs9rEa59H7vfzvhvxuOP+Plg4gcMSh0EQNVLf8X68ceo8vPJmz0LFJIPiiAq+PrFTThr/eT2SWTyr3o1BGZeD18//yxVBYfQx8Vz5VPPkdoht9HgCNv91H22j1Cpu5EfXFODKhqNsmnTJpYuXRp7eAcMGMDYsWObzA13MomiiN2+ieKS96mtXQL13icGQ3dSU28lM+PKZv3imrpWAyufKLLJ4WFBrYOfah0U+hr69+Rr1YxLMDE2wUgftQKTruWZ3Nv60lar1Vi9IQpqPBypcceWt4rqPJRYvY2qRZxMCXoVmfFaMuN1ZMRrSTNr6jfpd6JBjSC0r0i42z/YyOW90+iTFUc4IvL3hQfYX+lk0SOj0KkUTfKVWL1M+MdKbhycxS1DstlcZOP33+/mnzf2ZXLPloX6t6VdreVriicSFalzB6hyBqhw+Ci3+6hw+Cl3+KXfdh9VrgCR5sxn9WRUK8hJ1JFj0ZOToCMnQUeqQUG3DAtJxjML/GhPYOVMeERRpNAXZKVNAmtrbO4GedcA0tVKLrUYuTTeyCiLsV3lXjsVn8u9n4qKb6is/J5QyBo7bjL1ITHxSjIzrkKpbPnH+Vy0y+VysXbtWjZv3kwoJC3JJycnM3LkSPLy8s4o5ceZ6iiGIrhWlOJcXlq/RCpgGJGOaWzjJdIzkRX0+/jnC68gOyStKBkyOnDd409jSc9ArNoLH0xCCDig6zS4/hOQyQmHIqz4/AD711cCsD95PVtSZ/K3eSYSD9ciaLUkvfIylrFjz/mYugje2khnCt62Ftu4+s21DNcU8DnPIqoMCE8cAaWGF9a/wMwDMxmdOZo3xr4BQMTp5MikyUSsVlKefor422+P3eiaYhffvrKFaFhkxHWd6DM2q4Esn9vF1889TU1xEXpLAjf+6a/EpaQ10kkMRSU/uC31fnC9E4m/tjOCsvlwbpfLxaJFi9i5c6fEo9Uybtw4+vXr12ILmtdbSHHJR1RUfBMLblCpEslIv5mMjJubLL/VQO/TvOyP+AIsrnWyqM7JBoeb8AmjVS8TGBFvZHSCiTEW4ynzyZ1OVlv5IlGRCoePo3UNl8aK6zyUOwLN+i+dSAqZQIpJQ7JRRYpZS7JRTbJRTZJRTbJRQ5JRTaJBjUWvalQy7Hx9xOrcAQa8sJgvfzmUIbmWJvlemr+PxXurWPLY6Nix3323k30VLr57oGWpZ9qi4+n4RFHEHQhT6w5S5w5Q6w5Q6w5S6wpQYfdS5w1R7QpQ5fRT4wo0u6x5IillAhnxWrIsuhhAz6z/f45Fh0WvaqBHewFU51IWQLE/yBq7m7U2N2vtbsoDDZ8Do1zGsHgDI+IMDNGp6BlvOmuBS2eTpym+QLCWqqofqayYhcu9J3aeSpVEaup00tKuQa/reMHvs91uZ82aNWzdupVIRALLxwrGd+nSBUEQzpmOoiji32vFPucIEZtkKFB0MGKZ3glVatNLpC2VVX5wP1+/+jfC9hpEIG7oJO568D7kCiU4KxDfH4fgKEXMGoJw+/eg1OJxBJj/9i6qCp0gwNoOsyjWL+Pl2QbiSh3ITCYy334LWbdu52VMXQRvbaSWFKY/kSJRkcEvLsHqCbDf8jgabwXijV9AlykUOYu4YvYVAPww/Qc6mDoAYP/qayr/+EdkRiO58+cR1uliN3rX8lJWzZTyv131eP8G/m8AXqeDr557GmtZCabEZK7/00uYEhv7SoiiiGdDJY56PzhFqg7LLV0J64VTDqqjR48yb948qqulyJyMjAzGjh1Lhw4dWm4OD9koLfsvZWWfEQxK1xEEJSnJU8nMvAOTqVeTfGcy6J3hCCutLhZbnSypc1EbariEmatVMTreyGUWE5fE6Rv5yp3Pj9jJfK5AmLL6JbVSm48ym7ScVmH3U+n0U+Vs3vepKTKqFVj0KmkzqLDoVBhUAhajljitkjidEpNGiVkrbQaNAoNagVohi7WhNe0qqvVw2asrmP/bEXRNa/plc/076+iRbuaPl3ePHftpTyW/+WIbe/88scWO5afTMRyJ4g6EcfrDOH0hXP4wTn8Ipy+Ewxei1unDFYxi94WweULYvEHs3hBWb5BgONqMxMYkEyDRoCbVrCG93lKaHqchLU5LullDqkmDSSWiO4N6nv+L4E0URY76AqyqtbPJE2St3U3ZSWBNJQgMNOsYGW9kZJyBPkYdCtn5K+3UWp5jfF6vA7d7DZVVs7FaV3IspZIgKElMHENa6jVYLKNiaZUuZLtqa2tZs2YNO3fuJBqVxntmZiajRo2iY8eObXoPtIQvVOPF8WMBgUN2AORmFaYpudBR36bat2I0yoZZX7Huuy8hGsUpN2CYcBuP31G/xBlwwodTEKp2E43Ph3sWIugTqCpysuDtXXgcQeQa+DH/bfyRvbz0jRpjrRd5YiJZ77+HulOn8zamLhambyXNmDGDGTNmEIlEOHjwIJWVlS3uwP83aw8/7qziv5mzuKT2a8I9riU07d8APLb6MVaVr+Lq/Kt5asBTAIiRCBW33kZw/34MV1+F4YknYrNTURRZ9vFBinZYMcSrufLx3qh1DU3JHruNWS/+AWd1JaakFKb/7jkM8QlN6hYqduH6ugDRHULQyFFNy8TQ49QWsEgkwtatW1m9ejXBoLRU2bdvX0aOHIlOp2tRnwD4fG48nlVUVHyGy70jdtxo7Etq6s0kWMYjkzXMq3biTL2lFBVFttmcbPCFWWn3sMXta2CVUwjQ16BlmEnHMLOOfgYtKpnQKlmt1fFM+MLRKLXuIJXOAKV1bhwBkRpXgBp3kBp3kFp3gBpXEKs3eEYg72RSyAT0Kjl6tQK9Wo5WIUOnVqBRytAo5WgUMnIS9Nx/WSci0ajkqyWAgPSBffC/23D4Qnx2zxBOfEcJJ/yY+Poqruqbwa8uzYulc9hWbOPm9zay4onR0jIhIJcJzNpSTJUzQCgSJRiO4g9HCYSjBMIR/CHpmNsfwh8R8QYjDbbAGQCwpkinkpOgV5KgV8U2s0ZGRry+3uqpIsmoJkGvOmVJKGjd+DifY/FcyIqKIod9QTY6vWx0+djk8lEZbDihOvYcDjXpGGrS0t+gRdsMeG+v/SGKUVyubdTUzKG2bj6RiDv2N4OhF0lJV5KYMAmlMu6s6ddaPr/fj8PhYN26dRw4cCB2PCcnh0suuYTs7OwmwcXZ1FEMRvCurMC/rgqiUqJd7bBUtCNSEVTyNskKOO0sfudfVB05BMB+fSeUw6/mlZsGIBMEiARRfX0r8qMrEfVJOK/7DlVKJw5vrmHNzCNEwiLqRPgs+6/oHOX8+RsFekcARWYmKW+9iTIzs9X90Roep9NJamrqRfDWWjpTyxvAD9vLeWjmdqZbinnd+xSi2gSPHwKFmk2Vm7hn4T1o5JpY0l4A75YtFN96mxTF8tmnmPv1iz1IAV+Yr1/ajLPGR26fRCbd17PRMktteRk//O05HNWVxKdlSEEMcfFN6hdxBrB+vp9gsQsA49gsjGOyEU7zEXK5XCxcuJDdu3cDoNFouOyyyxg4cOBplzNOnn04nTspKf2Y6up5iKI0A1epEklPu4H09BtobT6jpmS5whHW2N0st7pYbnVx1N/QV04rkzHUrGeoUc2oxDh6GnSNnJ9bKqu1Op4NnmhUxOELYfVIQM7qCVLnCWJ1B6h1+fGEojh9YRz11qdjVihPsOkErk1RlxQj39x/CcFwlPAJSPHlBftZe6SOd24bQIqp+ZfUtW+vZVrvdO4c1iF2bEeJnV9+uoV5vx1BgkGNQiagUsi49q11HKhytVi3pkinkmPUKDBplJi0SoxqBQaNApNaRoJRi0WvIl6nJE4n7eN1KhINarSqC2eZ/TnK8kei7HT72OzwsLF+s53ks6YUBHrp1QyPNzI83sggsw5dCxzg22N/eDyHqKz8nqrqH/HXRzACqNVppKZOJzVlOnp9/lnXr7V8R48eZeXKlbG8ngBdunRhxIgRZGZmNst3tnQURRHf9hocC4qIOqX3r7pLPHHT8lAkatskKxqNsn3RfNZ88RGhgJ+QXM0Sy0h0XQfy5S+HSoE9ogizf4WwcyaiUo94xxy8cV3YsaA8lng3rrOcGZZnSC2z8/tvBDS+MOrOncl6910UyUmt1vGi5e0C0Zn6vIGUYqL/84sQxSiHEx5D7qmCm7+CzhMRRZHr51zPfuv+WNLeY1T26GM4581D3a8fHT7/rAEgqil28c3Lm4mGRYZf25G+47Jjfzs2OIIuJzOfewpXbQ0Jmdlc/8eX0Jma1lkMR7H/eATPBskxU9MlHssNXZDpTl9R4NChQyxZsoSqKsmHLjk5mcmTJ5Obm3tKvqYGcCBQTVn5l5SV/feEJVU5iYljyUi/Fa22X5vM6E3xHfUFWG1zs8rmYpXNTd1JS6xGuYzBZgOXxOkZFm+g9ynAXHv8sJwpXzQq4gmG8QQiuAMh3IEILn8Im8tHVJARCEfxBSP4QlH0ajk3DMwiHI1yLHH9i/P2sexANR/cMYj0eC0nZkg9+QVyz8eb6Jpq5ImJXWPHlu6v5qlvd7L2qTEoFTLkgoBSLuP1xQepcQdQySXLn1opQ6NouFcQJc6gxaBWoKu3GupUcvQqCaQ1tQzbnvr+5yqrOhBkba2dHb4Qmxwedrp8DaJBQZoUDTTrGGo2MCROTz+jDtnPuARdIFBFVdUcKiu/b+DHJpcbSEqaiMUymZTkUchk5y4i80z4RFHk4MGDrF69mpISCaAIgkDPnj0ZMWIEKSkp50XHULkH+w9HCB51AiC3aIi7PA9tt4RmeVoqy+t0sOjdf3N44zoAXHHZfGMchSkhidm/GU6ysX4iueTPsOpVEORw80z86Zfy03u7Kd1nByDrUi1/iTxCp0Mu/t8sUAajaPv2Jeudt5Gf8N0/3+Dtos9bG6g14A1g+ow1bC+xs7DLj3Q++l/oewtMl3K5fX/4e55d8ywpuhTmXzMfZf1SYaiigiOTpyD6/aS/9irmKQ1DkXctL2XllweRyQSueqI/qbmSPicODkd1FTP/9CRuax1J2R247g8vojU2feNFUcS+vhTP3GIIR5FbNCTc2g1VetMJek+UpVKp2Lp1K0uXLo0lb+zRowcTJkxosp9ODyBC1NQuprT0U+z2DbHjWk0uGZk3kZ52NUpl05bEM5XVQK4ost/jZ6XVxco6B5tcPlyRhktuermMwWY9g8x6Bpv19DPp0LehDExr+dqbLFEU+eMPe/hpTyVf/vISchOlMm/HqLmAhSX7qln86PEM5s/M2sXecme7CFi4KKsx+SJRdrt9bHF42OrystXpodTfOMgmUalgsFnPQLOeoWY9vYy6Bgm1L6RfaWv7IxSyU129gKqqH7HZN3BsOiIIChISLiU15UoSE8cik6nbzX2ORCLs2bOH1atXx3yV5XI5PXv2ZNSoUSQkNO1Sc7Z19Na5CKyswrupEkQQlDKMY7IxjshAULZ9UlW4fQs/vfU6HrsNmVyOo/s4PnZ1QKdW8s39w+h2zO920/sw91Hp9xX/xpZ+dSzxrkIpo9PVRp6teJCeOx389kcReUREP2IEmf/6J7KT3IIugrefEbUWvB1LGfJQfhWPlD0CGjM8fhgUKoKRIOO/GY/Vb+WVUa8wKXdSjK/m3/+m9t8zUKSlkT9/HrIT1slFUeSnd/dwZGs1RouG65+R8r+dPDis5WV89dxTeOw2knPzue73f0GjbwzIjvHJrGGsn+8nYvWDQkb8VR3RD2h6VnayLK/Xy7Jly9i8eTOiKKJQKBg+fDjDhw9HdUKB3jMZwG7PIcpKP6ei8rtYxnGZTEVy0mTS0288bS6ktjxgSrWavR4/6+xSBNwGu6dRygK5AD0MWgab9Qw26emlkdPBZGwXH9rzKevZ2bv4fns5794+kLyk+ugwEYwaBRqlHEEQ+NuC/VQ5/Lx2Q1/geKqQm4dkc9PgLLYetfPM7F0/y1Qh/4uywlGRQ14/211edrh8bHV62HuSzyhIfoydtSoGxxkZFCdNanI0qrP+XJ5vPlEU8XisuNyrqa6aQ511VcytA8Bs7k9qynSSkyc3qCLTHu5zMBhk+/btrF27FrvdDoBKpWLgwIEMHToUpVJ5fvowIuJeX45z0VFEv/Tu1PZNwjw5F4W5+aj/lsoKBfys/PxDtv80FwBLRhbuIdfy6jY/MgHeu2MgY7rWf78OzIcvbwYxCqOf5mjivSx8X0q8q49T0f1mE4/suZ/BG+zc+1MUQQTTlMmk//WvCCcVmG91f1wEbxeGWgveNhdZufbtdcRrZGzVP4jgqZFqpnUcB8Cb29/krR1v0TupN59P+TzGF/F6OTJlKpHKSpIe+i2J99/f4LpBX5iZL27CWeOjQ+9EptwvRWqePDjqSouZ+dzT+JwOUjt25tpnnketaxh+3SBKxxfGOvMA/gNSqSv90DTipuUhtDDtREVFBfPnz6e4uBgAk8nEuHHj6NmzJzKZrFUDOBRyUVr2HdXV3+B2740d1+nyyUi/kbS0q5q0xp3NBywqiuzz+Flvd7Op3pfn5JQGAGkqJf3NOvoZdfQ36elj1KJvovrDudDxXPC1hKfDU3ObPP7Ktb25dkAmgiDw2Fc7KLV5mXnfJbG/ry+o4/k5ezlU5SbZpOZXl/7vJultz7LCUZHDXj9brQ72+MPsdPnY7fbiayLqJUmloL9JR3+jnv4mHX2MWpThULtsV2v4IhE/dXUrqKqeS23tUqJRX+xvBkM3UlIuJyV5Klpt0/5hF/I+ezweNm3axMaNG2N1R3U6HUOHDmXQoEFotdrz1vf+QzbscwoIV0l6KNP0xF2Zj7rD6b+dLZFVVXCYeW/8HWu5VM2n3+TLCfSZxAMzdyMCf5jWnbtH1LvvlG6Gj6ZB2IfY9za2aR9n3ewCECE130zeVUoe2vxrLl1m5eYV0mpL3I03kPr73yOco7JfF8HbeaTWgrdQOEL/5xfjCoTZ1HcuSfs/h/63wxVSfrdaXy0TvplAKBrisymf0SepDyDd6NrZ31P79NMIWi35C+ajPMk34WT/tz5js5ocHDVHC/nqz7/D73aR1rkr1/7uz6i0x83AjZxKoyKupcU4lxSDCMosIwm3dEURp2mW50QSRZG9e/eycOFCHA4HIKUWmTRpEpmZmW0a9C7XLsrKv6Sq6kciEenFIAgqkpLGk552HRbLMI7V/zvXD1ipPxgDcpscbva6/Zwc2ygDuug19DPp6GXU0cegpdsJ0XTt+aPeVlnH6ExknSnPMb5AIIBa3fJEtsf4/lf7vjk+byTKPreP3fXbLpeP/R4f/iaAmkEuo7dRAmh9jDr6m3Rkadqei669gbdIJIDVuoKq6nnU1i6JvVcAtNocUlIuJzXlcvT6judEx7a2y+fzsX79erZu3Uo4LPntxsXFMWzYMPr164dSqWzEc676Plznwz638HgBeZ0C7WXpmIdlITsLdWWj0Qibvv+WtV9/TjQSQR9vYdL9D+NOzOe6t9fhC0W4dUg2z0+vD+arOwLvjwdvHeHcSSwNPcuhzTUAdB+RTvZkFfcsuosp82q4fKP0DCT86j6SHnronK3qXARv55laC95EUeS+TzaxcF8Nfx9o59rdD4DWIkWdyqVUH8+sfoYfjvzA5A6TefnSl2N8Pp+P6l/ci2/rVkxXXE7Gyy83uv7uFaWs+K/k/zb9sX7EpaubHBxVhUf4+vnfEfB4yOjanauffg6V5tTRPb79VqwzDyD6wlJZrRu7oukcf0qeEykUCrF+/XpWrlwZy9bdq1cvRowYQXJycpsGfTjsorLqR8rLvmzgNKxWp5GWdg3padeg0TQNZs9UVkv5rB4vB0JRttUvM21zepu0zskF6KzT0MuopbdBS0eVnL7xZuJaUBqrrTr+r4K31vK1Z+DRFlken48qUcZ+r599bj/7PD72uf0U+gKNgkdA8ufsplPT16Snr0lHX5OOPK1aSq3Qjtp1tvgiET9W60qqqxdQU7ukQWoPjSaD5KQpxMWNJSGhcV3ns61ja9tVXl7OqlWr2L9/f+wZSEtLY/jw4XTr1q3JElbnqu+jgTCupSW4VpdBRJQKyF+SjnFsNkEhfFb6w15VyfwZr1F+QFp96TxkOOPu/TWOqIorZ6ymyhlgWF48H989BKVCDp5aeG8c2ApxJ4xknvNZakq8yGQCI67vRFx/kXvm3cn07yq4bKfUf8lPPUnCnXe2uT/OFg9cBG9tpraAt0/WHOGPcw4wMMvIN547wVsHt82G/MsA2Fe3j+vnXI9ckLPgmgWk6lNjN5ojRyi67noQRTp8+V+0ffs2uv7C9/dweHO1lP/tsV6YE5r2u6o8cohvXniWgNdDZveeXP3kn1BqNKccVGGrn7rP9xEqk8pqGcdkYxqbDULLSzS5XC6WLFnC9u3bAVAoFFxyySWMGDECtfrUFQ+OtfFUslyuPZRXfE1l5Q+Ew47Y8bi4oSQmXkF62lSUyuaDL85E1pnyVQZCbHVKUXg7XV52unyNEgcfowy1kh4GLd1jm4YOGvVZqdXYWr6L4K3tPOdSVkQUKfEHOejxc8Dj56DXH/vdlDUNpKXPngattBm19DLoyNEoCZ5hzeFz2a5zwadQRLBaV1Bds4C6uuUNLGxqdRopyVNITpmKydgbaF8l6I5RNBrl8OHDrF27lqKiotjx/Px8hg8fTm5u49KIbdXvVHxiVMS7rRrHgkKiLmmiqu4UR9y0PJQp+rPSH6IosnvZIpZ9/C4hvw+VVsuYu35F91Fj8IUiXP/OOnaXOemYbODzu/qRHGdECPng42lQtoUK1SjmW5/A5w6j0SuZ9MueyDL83DvnTq77ooTBB0WQy0l7/nnirr6qTf1xtnngInhrM7UFvBVU2Rn7+lpkAuwfNB/Vzk9hwF1w+eux8+5acBebqzZzT897eHjAww1udMUzz+L47js0vXvT4cv/Ipw0Ewz6wnz14iYcNT6yuscz7Td9mp0tVhw6wDd/eZagz0d2z95Mf/KPKJSqUw4qMRTFPud4OhF1pzjir+9CSBE5o4FYXl7OggULYv5wer2e0aNH079//1MWOm7poI9EAtTULqSi/BustjVQb2OQy3UkJU0kLfUq4uOHxpZV2yKrtXyiKFIZDLHT5WOHy8sul489Li/lwaYBnUoQyNep6azX0EmnobNeQ2edmjRBPKOara1t20Xw1naesyHLFYlyxBugwOvniC9AgTfAYW+Aw97mQZpGJtBZp6GrQUN3vbRc302vIVndOA1QewOlZ4svFHJQU7uEqsr52B1riEYDsb9p1OkkJU8kJXkKJlNfBOH4O7O99UcoFGLnzp2sW7eO2tpaQBrr3bp1Y+TIkaSlNS6HeLb0a44vUOTAPqdAqpcNKBI0mKfloel6vCReW/vD67Cz8D9vULBFqkua2a0nkx54BHNyCtGoyP2fb+GnPVVY9CpmPTCMZJ0MjUqBMPM2ODifveErWGG7i2gEEjIMTLm/F36di1/NvoObPj5Kz6MiqJRkvPoqpvHj29Qf54IHLoK3NlNbwJvf72famxs4UuPhq3FeBq/+BegS4fGDUJ8LaEnxEh5e9jBmtZlF1y5CI9fEbnSktpYjEycR9XpJ/9tfMV95ZSM5NcUuvn15C5FwlEuuzqf/hJxmdSo7sI9vX/wDIb+PnN79uPLxZwlHo6cdVJ6tVdhnHUYMRZGbVeivycPYKfGMBmI0GmXXrl2sWLECq1UqzpyYmMiECRPo1KlT0+CxFYPe5yujouJbKiq+wx8oiR1Xq1NJTbmS1LSrMOg7nRVZZ4MvIFeyz+tnr1ta3tpbv8zlizZdIUAOZGlU5OrU5OvU5GnV5NXvMzQq5GepH88leAuLIsGoSFQUEQGNTIZCODXPB6U1fFhWS4k/SIZaxUMdUrguJf60sprTsb0AD1EUqQtFOOoLcNQfpMgX4KgvwBGPnyJ/qFlrLYBaJtBRp6ZzPbjvqFOTq5DRNc6IooVLfu0NrLSFz+8vp6Z2MTU1i7DbNyKKx/tOq80hOWkSycmTMBp7NXud9tIfHo+HzZs3s3HjRjweKeL+WOTo4MGDUaubdpM5m/qdzBexB3DML8S3sx5EquWYxmRjGJ7e4sC2lsgq3b2dRf/5Nz6nA7lCwfAbb2fA1Ctj+fP+On8/b684gkou44t7hzAgJx6/z4dm6bNEN33EGve97PJMBCC/XxJj7uiGU7Tz4Le3c8t7heRXAnodKf/4B/EjR7bbcX8RvLWR2greXl5UwIdri7h5YBovHr4K/Ha4Yw7kjgQgEo0wddZUytxl/OGSP3Btp2sb3Ojad9+l5tXXUCQnS6lD9I0L9u5aUcrK/x5EkAlc9Vh/0vKb17N0326+femPhAMBOvQdwMRfP4beePo0F6FKD3Wf7SNc6wOZgHlyBwwjMs54ACuVSrZs2cLy5ctj+eFyc3MZP3486enpTfK05oXj8/kIBvdRWTmLquq5hMPO2N+Nhh6kpEwjJWUaGk16m2Wdbb6oKFLqD3LQG+CgR1oOO7Ys5o40X/ZJKQhkapRka9Rka1Vka1TSXq0igSgZRj3y8/BRP10QwXq7mz0uH530av5wuJzn89MZYTECTYOwj8pqeeFIOX/vkkU/k45tTi+PHSjhzW7ZTEg0N8t3NtvW2v6IRKOUuTzUIFAWCFPqD1LqD1IWkPZFviCeU9xTgBSVgjydmnytRtrr1HTRa8g6Cay3R0B1LmWJoojHczAG2FyuXQ349PpOxMePJT1tGgZD1xbJvND9UV1dzfr169m5c2csCMFkMjF06FD69++P5jTuLueiXT6nh9D6WlyrSiEsggD6QamYxucgNzZOp9FaeQGvhyUfvsO+lUsBSMzuwJTfPEZSTm7snK82l/D/vtkJwD9u6MNV/TIRRZHw8lcIL3uDn+yPUxaUMjAMuSKXAZM7YA/YeWTmbdz6zhEyrCDEmcl57z3Iz2/X4/4ieGsjtRW8rT/q5K6PNpNu1rCm27cI2z+HQffC1L/Hzv1076e8vOll8sx5zLpiFoETfFCiwSAFU6cRKikh4f5fkfzQQ41kRaNRFry7i8JtdRji1dzwzGA0huYrJZTs2cl3f32OcDBATp8BXPn4MyibyGnTSI4/jO3bQ/h2STMvTfcELNd2Om1VhhP741i7fD4fq1evZv369UQiUi6gnj17MmbMGCwWS5M8LaWT+SKRAHV1y6ionEVd3fIGM3KzeSCpKZeTlDSJaFTfLsBbcxSNRil2eSiLQqEvyBGv5Ih+xBugyBckdJrHVSUIpKmVpGuUpKtVpKuVpGtUpKgUJKuUJKsUJKmUaOWtS+3SmnalLtvOBz06MDmpeRA2bctBBpn1/LFjRuzY7w+Vst3p5Yf+nZrlO1s6NsUjiiL2cISaYJiaYIjqYJiKQIjKQIiKQIiqYP0+EGpUeeBkEoA0tZIcrYocjZocrYp0uUBXs4F8nQbDKVLOnO12tZQulCxRDGGzb6S2dgm1tUvx+0tPOFPAbB5AUtJ4khLHodXm/Cz6Q61WU1BQwLp16zhy5Ejs72lpaQwbNozu3bs3cC85X30vRkU8W6twLChCdNf7teWZMU/LO2Ui99bIK923mwVv/gNHdRUIAgOnXcXwG25DcULE7Lojddz2/gbCUZEHx3TksQldJFk7vqT2q5eYb3saVzQZpUbO+Lu6k9snCWfQyVOf3spN7xwi0QlCShK5H36EKje33Y/7i+CtjdSa2qZw/IaJMiX9XlhMMBxlzdUhMubdgWhIgUf3Qb2vhTvoZvy34/GEPLw19i36W/o3uNGuxYspe/C3CCoVufPmosrIaCTLaXcz5/U9OKp95PRMYMr9vU5Zq7R41w5mvfxnIqEgeQMGc/kjTyFXnB6ERaNRHKtK8C4qhYiIPF6N5eauqDKNLeqPRpFEdjtLly5l1y5p1iyTyRgwYACjRo1Cr9ef9QcsGLRSU/MTVdU/Yrdv4ph/nIAck3koaalTSUqa0Gwh6TORdbb5TsUTEUUqAiGK/UGKfUFp7w9S7AtQ4g9SFQw3GW3YFJnkMpJUShIVMhLVKixKBRalvH4v/Y5XKjAqZJgVcoxyOZpWpkBJW76DD3p0YFKiqdnzJ2w+yNgEI0/mHvfv+UtBBe+U1HB4RE9ULUxFcIxO1jEYjeIKR3FFIjjCEeyhCLZQGHs4gjX2O0yNP0hdJEptMExtKNwocW1zJANS1Eoy1UoyNSoyNKrY72yNiiyNKtZ/TenX2nadK57zLSsQqKOqajEO5yqs1lWxxN0gJe+Ojx9OUuJ4EhPHoFIlXhAdW8MXDAbZsmULW7dujfmzAXTt2pWhQ4c2Wyj+fLQrUGDHMbeQULnU13KLBvOUXDTdLS3ib6m8cCjE2q8+Y/OcWSCKGBISmfzAo2T16NXgvMJaD1e/uRa7L8TUXmn868a+yGQCFKzg8HuvstR+P2FRgzlJy+T7e2FJ0+MOuvnTh7dx/TsHMPmA7EzyP/wIZfrZq5t9rnjgYm3TVtOMGTOYMWMGkUiEgwcPUllZecYdeOyG3f3pNtYV2Pjd+A7cu3ESQsBJ4JbviWYOiZ372rbX+PLQlwxLHcZfB/8VjaZhbrWqX/0K/8ZN6CaMJ/lvf2tSlqcuwpzXdxEJiwyclk3vsRmNzjuRSnbvYN7rfyMSDpHbbxATfv1IiwCc3+9HYY3g+voIUXsQ5AK6CVloBiWdxifF36BdJ1JVVRUrVqygsLAQAKVSyeDBg+ndu/cZ9/vpZB2jQKCS2roF1NbOw+M5ngRYEBSYTUNISBiPxTL2tGW5WiLrbPG1VpbL58MhU1ARCFERDNdvISoDYapDYWpCEaqD4dNaiZojlSBgVMgwymXoBAG9Qo5OJkMrF+ioVfN4fgbhaBSxfnwI9Vv+ql28Xb/8efLQOfbflwsr+brKxgc9OtDDoGGX28fdu49SFwqzfkhXklXSmFXIBL4sq6bSL7XDH43ii0TxRUW80Sj+qBj7vyMcxhMVcYWjBNrwmjPLZSQoFSSr5KSoFKQoFaSqlNLv+s0cDWPUas/ouj+HMXWuZIliFI9nLzbbKmz2Vbjdu+CEqYdSmUB8/KVY4kdjNg9FLtc1e6322B9Op5OtW7eyY8cO/H4/IPmz9erVi4EDBxIXF3dOdGwJT6TOj2dxKaH9dkDya1NckohxeEYjv7a2yqs9Wsjid9/AWir5JncdeRkDr74JU3zD963dF+Km97dQVOeld4aJj+/oh0YpR6zay443P2Wr8woAMrqYGX17Z9Q6Bb6wj79/cBfXvn8QbRCiXfLIefNd5Jbj125v4/5kcjqdpKamXgRvraW2Wt40Gg3vrirkpfn7ubRzEh/Fv4+w40vEwffB5OMgrMRVwrRZ0xARmTlxJl2TG/po+A8coOjqayAaJfuzT9ENGNCkrL2rK1jxxQEEmcD0R/uSlh93Sh0PblrPgjdeIRIKkT9oKNMeehK5ovm8Yw2WMPwRbN8ewr9HSsyo7ZVI3NUdkWka87d09lFYWMjixYspLy8HpEzhI0aMYNCgQShOoVdrZJ1IHk8B5eU/YLMtxu3ZHzsuCHLi4oaSnDSRxMRxqNXJbZbVWr5zLUsURZzhKFXBENWBEGUeL25BVm+BCmMNSfu6oGSVcoUjuCLR01r0uuo1/Ni/E4FotJG1qu/aPbzWJYsxCc2/nPyRKC8VVjC3xo4ogkWlYGqimY/K61g6sAsWlQKFAGqZjMu3HmK/x9/ivjmRdDIZJoWMeKWCeKWceIWCuHorY7xCjoEo6TotSWolSUoFiSoFqtP4ELbH+9weZYVCdqzWNdRZl1NXt5JQqK7B33W6LiQljSUpcWx9wMHpgUR76g9RFCkuLmbjxo3s27cvFthjNpsZMmQI/fr1a/HH/Vy0K+oN4VxagmddBUSlfG36wWkYxmSdcXaB08mLRiJs/vE71n79BdFIGK3JzPhf/ob8AUMa8YQiUe74YBPrCupIN2uY/evhJBnVBKqKWfzybI56JQtdj1FJjLiuG3KFHH/Yz+uv38SUjw6gioDYvyed//Mh8hP8xdvLuD8VXbS8tZHa6vOm0Wg4UOVi0uur0Chl7LwxgurrW8CUAY/s4URzw4NLH2R5yXKuyb+GPw7/Y6MbXfHHP2GfORNNjx50+PqrWOqQE2UBLPpgL4c2VaGPU3PDs4PQGk7tVFqxfw8/vPoXIqEQnQYPY+pD/69ZANeU7497TTmO+YXSMmqChoSbGi+jnskAFkWpUsOSJUtikakmk4lRo0bRr1+/U6YXOVNZTfH4fEVUVy+gunp+g0TAkh59SUocT1LSePT6/J/FS+BcyoqKIu5IFGc4gjMcwR4KY/f5CcsVeKNRvJEoWpmMq1PjCUdFIoD0VpEiTbuu3s0b3bIZazEdN7WJNAkIQ1ERayhMkkrB11VWXi2qYsOQbshlAnJAKZPx+tFK6oIRlDIBbb3lTyeXo5UJ6OQytHIZWkGGOhomQafFpJBjUsgxyOWN8uq1tQ9by/d/QZYohnE6d1BnXYnVuhqncycn3nW53IDFMpzEhNFYLCMRxbifZX+EQiF2797Nhg0bqKysjB3Pzc1l8ODBZGdno9PpLli7xHAU9/oKnEuKEX2SL7CmSzzmKbmtztd2Knm2ynLmz3iNioPSBLnjoKGMv/c36MxxTX5bnv5uF19uKkGvkseKzduOVjHvteXYA0nIhRCjb+pIzqB0NBoNoWiIt166nnGfH0AmQnTkILr9+11kJ+UV/Tk8Y23xeWuZmeMinZa6pBhJMampcgbYKO/LCKUenGVQvhUyjlvQbu12K8tLljPv6DweGfQIZnVDsJj02wdxzp2Lf88eHN//QNxV0xvJEgSB0bd0oabYhb3Ky+IP9zHt171P6f+W23cAVz72DN///QUObVzL3H+9zNTfNg/gTpZnHJGBOsdE3ef7iNT5qX5rB+bJuVII+RkM1hOv2aNHD7p06cLmzZtZu3YtTqeTOXPmsGbNGkaPHk2vXr3OKAP6mZBOl0uHDvfTocP9eL1Hqa5ZQE3NQpzO7bHtSMEr6HS5JCaMw2QaiVo9BEH4v/fIyAQhBoCg/kWlUTT5olI3c7v0MhnxSon/dOMlVSMtkS6sdTIhwURCfXWKY3xP56U3y3uMWvsyvUitJ1EU8XqLqK5ejtO1HpttfYPqBiBFhyYkjCYxYTRmc39kMlWM99jy4s+FbDYbmzdvZuvWrbGoeoVCQZ8+fRg8eDApKSkXtF2iKOLbXYtjQRGROkkHRYqOuKl5sWo6Z1vejoXzWPH5B4QDgQYJd5t7Bt9fXciXm0oQBPjXTf3olmaiaHsli97dRjCShEFhZfKvepPUIw+/308oGuKTP1zLhG8PARCePIqer8xAaOGKzf8S/d9r8TkiQRAY2SmJb7aUsuKIkxGdxsHe72HfnAbgbXDqYPLj8jliP8L3h7/n9h63N7iOIiGBxPvvp/qVV6h57TVME8Y3mTpEpVEw8d6efPO3zRTvqWPrwqMMmNThlDrm9hvIFY8/ww9//wuHNqxl3ht/Z8qDj7cIwAGosoyk/LYf1vplVMecAgKH7cRf1xm5/vR+dE2RXC6nT58+DBgwgC1btrBq1SpsNhuzZs1i9erVXHbZZXTt2vWcgTgAnS6HDjn30SHnPgKBKmpql1BbswirbR1ebyHF3neBd1Eo4khIGEViwmgSEkad1k/u/zJ5whEKfceTphb7g+x2+YhTysnSqvnLkXIqAiH+3V3KWXjE62eb00t/kx57OMw7JTUc8Pj5V9fsC9WEi9QCCgSqsFrXYrOtxWpbSyBQ2eDvSmU8lvjhWBJGYrGMQKNOvUCanh0SRZHDhw+zadMmDh48GDtuNpsZNGgQ/fv3R6dr3j/vfFHgqBPH3AKCxS4AZEYlpvE56AemnnKS31py1taw8J1/cXTnNgCyevRm0v0PY0pKbpZn8d4q/jJvHwDPTOnGmK7JbJ5XyIYfCgA1aeoDTPrNUHSdOiOKIqFIiNmPXcfwBVK0buD6ifR57h//ZydnF5dNOTvLpoIg8MOOcn773210STHy09gq+O4XkNgZfrOpAd/XB77mz+v/TKYhkzlXzUEua7hEGA0GKZh2OaHiYhJ+dR/JDz/crCVh7+pyln22X/J/e6Qf6Z3iTqkjwJEtG/nh1ReJRsJ0HjqiEYBriW+HZ30F9rkFEBaRm1RYbuyKKtfUZnNzMBhkw4YNrFmzJjZjTUlJYfTo0XTp0iUG4s6HaTscdlFXt5KamkXU1q0gEnGe8FcZZnNfEhJGk5BwKUZD90Y+Ou1hSedCyVpjc3HN9iONjl+fEs+/uufw231HKfEHmdVPSgNy0OPngb1HOeL1oxAEhscbeDY/nXzt8aWQn3N//K/ICgRrsds3YrNtwGZbh9fb8B4LghKjsQ+JCaNISBiF0djjnPmutZavNTw+n49t27axadMmbDZb7HheXh6DBw+mc+fOTU4wz3e7POV2AssrY6meBKUMw6hMjKMykambdkVpi44+n4/CTetY9tF/CHg9KJQqRt5yJ/0mTmtULehEWQW2INe9vQ5vMMLNQ7L50+RuLPt0P4e3VAPQQ7eQkfeNR95lLAChYIA5D1xB19VSBR/PL65mwGMvnNa/tz2PKbiYKqTNdLbAm80TpP8LixBF2PDoIFLe7g7REPx6EyR1jvF5gh7GfzMeV8jFv8f8m0uzLm10bdfixZT+5kEElYr8+fNQpKc37c8giiz+aC8HN1ShN6u4/pnB6EyqBn9viu/Ilg388OpLEoAbMpwpv30iBuBaOhCD5W6sX+yXkvoKYBybjfKSJLRnUNqpOVk+n49169axfv16gsEg0BDECYJwXj9iPp+bQGB/vbP1ctzu/Q3OUSotWOKHYbGMwGIZjkbTulD1n8MLp7WyjtGZymotX3vvj5+DLKezGK9vBw77Rmz2jY3AGggYjT2xxA8j3jIMs6k/oZBwXtrVWr4zCe4pKytj8+bN7N69O5ZQV61W07dvXwYNGkRiYmKz/OezXRFPCOfS4uPBCALoBqRgnpCD3HTqGtOt1dFjt/HTO/+icKtknEjr2IVJv34ES3rmKWUV1zi46f0tlDv8DO+YwL8u78Wi/+yhrsyNjBCjTO/S46aroN8tUtsCfhbfcznZm0uJCuB86GYu+dXvT6tfexxTJ9NFn7d2QvF6Fb0zzOwodbCiOMD1uaPgyBLY/yMkPRY7T6fUcWXelXx24DM+3/d5k+DNMHYsuiFD8G7YQPWrr5L+6qtNyhQEgUtv6kLNURe2Si+LP9rL5b/pc1rTeP6AIVzx2O/48bUXObhhDeK/xBb7wB0jVbqB5Af7Yf/+MN6t1bgWF6M4bEN1Y1cUcWcenn0iabVaxowZw9ChQ1m/fj3r16+nqqqKmTNnkpKSwqWXXkqHDh3aJONMSBAUxMUNJD5+EB3zn8DvL6eubgW1dcux2dYTClmpqp5DVfUcAHS6fCzxwzEYBpKUNByVKu686XqRLlJrSPJZO4LdvhmHYwt2xxZ8vqONzjMYuhIXN5j4+KHExw1FqTQ3uEYo9PPyXTuZAoEAu3btYvPmzQ0CEFJSUmIuHmr1qQHR+SIxFMG1phzX8hJEv5QIXd0pDvOUPFRpjd1tzhYd2riWRe/OwOd0IJMrGHbdzQy64hpkpwk08wUj/ObLnZQ7/OQl6fn9wDxmvbyFgCeMVmZjUtwrpE84Abi53ay643Ky91QSkoP9yTsZdfuT56xdPye6aHnj7FneAF5deIA3lh5mWu80/t15O8x5BNL7wy+XNeA7UnuEq+ddjYjI91d+T15cXqPr+/fvp/Cqq0EUyf78M2TduzeL7OvK3Hzz182EQ1GGXJHLwCm5zep4IhVs3SRFoYbDsShUmVx+5mk4tlZhn30YMRhF0CqwXNMJbc9Tz0pbot8x8nq9MRB3zBKXlJTEqFGj6NGjR4t84s7VTCwaDdVH1a3Cal2D07kDOLEckoDR0J24+CHExw8lzjwIpbLpWdbPYbZ40fL2vyErEvHhdO3G4dgqgTX7FsJh+0ncMoyGbtLYjRtMXNygUya3Pp/tai1fczwVFRWx3GzH3jFyuZyePXsycOBAMjIyGlTGuZDtEqMi3q1VOBcdJeKQdFWm6dGMTcfUI+Wc9aHP7WLpB2+zf80KACyZ2Ux98HGSOzT+fp1M0ajIb/67lXm7KonTKHmtXx77FxQjipCsOsJk80sYBk6BK94AQSBstbHxtiuJP1KDXwnVz9zFhBueuOB9fzZlXVw2bSOdTfC2qcjKdW+vI06nZMvDvZG/1hUQ4ZG9YM5owPfkuidZVrKMG7rcwLNDn21SRsXv/4D966/R9OxJyscfoT1FyPm+tRUs/WQfggBXPNyPzC7xLRpUBds28cPfJQDXcdAlTH3oCULhM8/7E6rxUvvffUTKvQDoB6dinpaHTNX8bOxMB73X62XdunVs2LAh9oJNSEhgxIgR9O7d+5QpRs7XwxwKObDZ1mO1rsZqW4fPV3jSGTKMxm6YzQOJMw/AHDcg5sj9c3jhXARvPz9ZPp+XqFiJy7kdh3MHTsd23J79iGKkwbkymQaTqY80Ls0DUKu7YTAkt8t2tZbvRJ5gMMju3bvZsmVLLO8kgMViYeDAgfTt2zcWgNAe7rMoivgP2nDMKyRcJb1n5XFqTBM7oO2dSCB4ZuDyTHQs2LaJhe+8gcdmRRBkDLriGvpNu6pFdbMBXlt4gH8tPYxGEPhjWirWvXYAuhrWcqn+dRSdLoWbvgS5kmBlJTtuuRpDmQ2XBmpe+BVjxv6yXT9jF8HbBaCzCd5CkSj9/7wIVyDM7F8Pp+/C66FkA0x+BYb8sgHfDtsO7l10L1qFliXXLcGoalx+Klxby5GJk4h6PCT++c8kXnftKQfHko/3sn9dJTqTihueHYzWqGzRoCrctpnv6/PA5Q8ayrj7fove0LKH8sT+8Hm8BFdV415ZCiIokrRYburabJ281g56r9fLmjVr2LJlSyywwWw2M3z4cPr164dS2Tj69UJ9WATBid2+AZt9Azbbeny+okbnajSZxJkHYDL3R6vpQXx8T+TylkfwtocPy+l4jtH5Am+BQAC1Wt1u++NcyZLOKcPp2oXLtRuncxcu5y7CDQJuJFKpkjGb+9VPIgZiNHRrlL6jvbTrbPFFo1GKiorYtWsXu3fvJhSSanrKZDK6detG//79yc3NbWTNv9D9ESh24lxQRKDAAYCgUWAak4XhknQE5bmrVRzwelj+yXvsXrYIgPj0TCY/8AipHTu3WN7sbWU8PHM7xqjArxUmItYgggyGJ82mNx8jpPWGu+aB2kigsJC9t9+ApsZFnRFqXnyA6eN+067H4kWft3p68803eeWVV6ioqKBHjx68/vrrjBw5stnzZ8yYwb///W+KiorIzs7mmWee4fbbb2/2/HNJSrmMYR0T+GlPFSsP1tC36zQJvO3/MQbejtHg1MF0jOvIYfthZh+ezW3db2t0PUViIon3/4rqv7+K7V//wjJlMnJD8wWDR93UheqjLqzlHhZ9sIdpD/Zpkd65/QZy5ePP8v3fX+DIpvVEwxGueOxpFMrTF7M/kQS5DPOkDmg6xWH96iDhGh/VM7ZjnlSfE+4shalrtVpGjBjByJEj2bJlC+vWrcPhcDBv3jxWrFjBJZdcwsCBA9Fo2uZ7dzZIrU4mNfUKUlOlEi/+QCV220Ycjq3YHVtwu/fj95dS6S+lsup7AGQyLSZjT0ym3phMfTCZ+qDRZJzRi6G90TEwdb6ovfglnUsSxQg+XzEu115c7n24XLtxuXYTCtkanSuTqTEae2E29cFk7ofZ1Ae1Ou1nPabOhLxeLzt37mTbtm1UVVXFjickJNC/f3/69u2Lvom0TBeaQjVenAuK8NVXuUEhYLgkHdNlWch0rUvR1FI6unM7P739T1x1NSAIDJhyBcNvvB2lSk1L7T6bi6z8v292khmWcUNQSyQYRKNXMDHjYzKd34A5G275GtRG/Hv3cvDO29A4vZRboOYvD3DjZQ+2WNb/JWp3lreZM2dy22238eabbzJ8+HDeeecd3nvvPfbu3Ut2duOcT2+99RZPPvkk7777LoMGDWLjxo3ce++9fPHFF1x++eUtknk2LW8AX2wo5nezdjEwJ55vbkiFf/UDQQ5PHAadpQHf1we/5vn1z5NlzGLOVXOQNRFWHw0GKZgylVBpKQn330/yQ789pV7WCg9fv7SJcDDKoKkd6DUurcUzgqLtW5j99xeIhELk9R/E5Y/+DkUTVqyW9EfEE5JKa+2VXjrqTnFYruvcIPrpbM2OQqEQ27ZtY82aNTgc0sxUpVIxcOBAhgwZgtlsbrdWgXDYhcO5A4d9M3bHFpzOHQ0Kcx8jpdKCydQLg6E7RmN3jIZuaLU5CELrZt0/h5np+bTYtff+CIdduN0Hsdl24g8cwe3ej9u9n2jU1+hcQVBiMHTGaOyF0dgTtaoTFktv5PKWT8ba+5hqCV80GuXIkSNs27aNAwcOEIlIy8RyuZzu3bszYMAAcnJyWiTzfPeHp9pJcHUV3i1VkgutALr+KZjGZzcZEHY2+zDo97Hysw/ZsWgeAOaUVCbd/zCZ3XqekbwSq5fp/15Dti3CWL8KQQRLuo4pWR9iPvolaOLgnoWQ1AXPxo0U3ncvcl+QglSoef5X3DnyoVa3rb0/z/A/tmw6ZMgQ+vfvz1tvvRU71q1bN6ZPn85LL73U6Pxhw4YxfPhwXnnlldixhx9+mM2bN7N69eoWyTzb4K3E6mXky8tQyAS2/3EChvdHQfUemP4W9L25AZ8v7GPcN+NwBV3MGDuDUZmjmpTlWLCA8ocfQdBoyJ8/D2Va2il1O7C+gsUf7QMBJv2qO3m9W+7EWrRjK7NfeZ5IKESHvgO44rHfoVSd3orRVH+IoohnQyWOuQWIoSgynYK4qzqi65V0yj5sjSyASCTCrl27WLNmDTU1NYC0HNKrVy+GDRuGyWRqNx+W5nh8Pi/RaDku104czp04nTtwu/cjiqFG58vlegyGrhgN3VGp84gzd8dg6NxsQMSFbNdF8NYynnDYjcdzGI/nEB7PIdyeg3g8hxolwD1GMpkGg6GLNA6MPTEZe2IwdEEmU7erdp1Pvrq6Onbs2MH27dtxOo8vF6elpdG3b186depEfHx8u+yPqDeEc0Up7jVlHCsUrOlmwTypA8qU5i2DZ6sPi3fv5Ke3/4mzRrJO9hk/hVG33oVKoz0jeS5/iOtmrKHD0SC9gtIiX6eByYxM/Bjt9v+AXAW3fw85w3AtXUrxQw8hC4XZkw01f7yX+4c/2qa2/RzG/f/MsmkwGGTLli089dRTDY5PmDCBtWvXNslzLPrnRNJqtWzcuJFQKNSk71MgECAQOJ79/djDLYriGZlnj51/Mk9mvJZsi45iq5cNBXWM6ToVoXoP4r4foc9NDfi0Ci1XdbyKT/Z+wud7P2dkRtPLw4bx41H360dg2zaqX3uN9JdfPqVunYekUnbQzr61FSz/9BDJz5gxtDB9R3avvkx5+Gnm/+tvkiXu5ee58vFnUKpPzd9cf+iHpKLKNWH76iChMjfWz/fj62cl7oo8BLX8jPv9VLJkMhl9+vShd+/eHD58mLVr11JUVMSOHTvYsWMHeXl5DBs2jLy8vDN6MM+mjqfjAQGdLh+9viOpqVcDEIkEcLv34nLvxV2/RObxHCAS8eBwbMHh2NLgOmp1CnpdJ/R6adPp8tDpclEqLQ2A9flsV0t4bPaNFBe/i8u1h2Cwml493yIxcRyCIDTLW1n5PcXF7+L1FaFQGLFYRtGp41MoFHGn5Dsb7WotXyQSxOstwuUux+ctxOsrxOstwOstIhisbpZPrUpBq+uEydQDo6E7BkNXdLoOCELjQJ1j+rTH+3wu+Px+P3v27GHHjh2UlJTEztFqtfTq1Yt+/fqRmpoaO7e99Uc0GMGzphzXytJY2g9VjhHTpFzUHUyx651N/U7kC/p8rP7yE7b/JKU7MiYmMfG+h8ju1adJ2aeSF45EefSjLQwsCJMWUYAAw67Op7f2B+SL/yPxX/UOZF+C/bvvqHj298iiUTZ1Eqh7+g4eGvpwg+u297HYFlmtpXYF3mpra4lEIqSkpDQ4npKS0iDfzok0ceJE3nvvPaZPn07//v3ZsmULH3zwAaFQiNraWtKasFC99NJLPPfcc42OBwKBmPN7SykQCDQJAoZ0iKPY6mXlgSqG952AZuXLcGQpfmcdqPQN+K7qcBWf7v2UtRVr2V+9nw6mDk3KMjz4GwJ334Pzxznor78edc+eTZ53jAZdmUVlkQNbuZeF7+1h0v3dkclbBliS8jsx7dHfMee1FynetZ1vX/oTUx9+EuVJs6+W9gcmGca7OuNbUYFvdQW+bdUECuwYrsolkqJsld9Ns7LqKSsrixtuuIHy8nI2btzIwYMHKSgooKCggMTERAYOHEj37t2bBPhnKuts8jXHo1Z3Q63uRmLCNQCIYhifrwiPZx8ez37c7oP4AwUEg1UEAtJmtTW0PsvlRjSabLTaDmg1OcjlaRiMHdCoM1EqE2hJNvyz2S5BEBr4pkUjPgyGbqSlXcvu3b8+7TXt9s3s3fcEnTo9Q2LCGAKBKg4c/D379v+OXj3fbCT/dC/Ls3WfRVEkHLYTCFTgD5Tg95cS8Jce/x2oACLNXk+pTESn64hOm49O1wmtLh+dNh+F4ngVk+OyQ0Bjq+y5aNe54mktXzQa5eDBgxw4cIBDhw7FlkUFQaBDhw706tWLTp06oajPX3ns/d6e+kOMRPFvqcW3shzRIyUClidrUYxMQt8jCVEQWvxdam27ju7ewepP3otZ27qPHs+wG25DpdWeUnZz8l75Yg+ddnjQizLkGjnj7uxMdnQF8h+krAqhy/5IOH8yjv+8i+0f/0AAlvcSqHvwBh7t+2AD40pb2tae7nNzPK2ldgXejtHJHSCKYrOd8vvf/57KykqGDh2KKIqkpKRw55138vLLLzebNuLpp5/m0UePm2SdTidZWVmoErQqYwABAABJREFU1eozcnA/hrSbimgb1SWFr7eWs77IjvqKEYhx2Qj2YjRlaxC7Xt6AL1+Tz6WZl7K8dDnfFX7H74b8rmlZffsSuvIKnN//gP0fr5P92aenHiwamHRvT77+62YqjzjZubiCoVeePh/PsXbl9u7Htb97nu/++kfK9+9h3j/+ylVP/RGVtunafafqj2OknZJPoHsStq8OELEFcH58AM0lKagm5SFTnjrB45nKOkZ5eXnk/X/2zjI8qqsJwO9dl7i7QUICwbVQimuLtFjdqAt19351N1oKbSm0tBQp0BaKFnd34u6+sfX7/ViSkpKEOAH2fZ59FnbvnJl7drN37pw5M2FhFBQUsHPnTk6cOEF+fj5r165l27Zt9O7dm759++LoeP5u38bqaq5cY2XU6mjc3KJrhO0tlrJzlttsy2+Vlcno9ZlYLKWUl5+kvPzkeWNJJApUSn9UKn9U6gBUSj+USh+USu/qh1TqUG1na5yXu/sQ3N3PL1pdFzrdEVQqfwID7jg7H4H4+d1Eaurc84690AaGhtooilZMpkIMhlyMxjwMhhzKytOxmHPRG7JsDps+E6u1/guuRKJCrQ5BqwlFowlDrQlBqwlDrQ6ttw5ga3+n2rsuURTJzs7m2LFjnDhxgrKysur3PD09qyPv7f3vWbSKVB7JRbcxFUuR7SIudVPhNDIIVRPKfjTFPpNez47FCzm89k8AHN09GH3/LIK79WySPlEUmb/gOC77S5AiIHdXMuPxnjiVH4afHrXp7DUTyaBZ6D7/nKJ53wHwZz+Bivum8erAV2q1vb1+F5ur67Jx3jw8PJBKpedF2XJzc8+LxlWhVqv54Ycf+Pbbb8nJycHX15e5c+fi6OhYZ+sSpVJZ6w+5IAiN9pyrZP4rN7CDOwAx2aXkl5vwjJwAe2YjnFkNURPPk7ul8y1sSd/CqoRVzOo1q9ayIYIg4PnEE5Su30DloUOUrVuH07hx9drn6qPl6hkd2LIwjkNrU/Dr6EJwtHuDz8s/sjNTX3qL5e+8SkbMKZa/+xpTXngDpab23Iu65uNcVKHOeD/Wi+I/E6k4mIN+Vw55iaW4Te9UZ0mRpuo6F3d3d0aPHs3o0aM5fPgwe/fupaSkhO3bt7Nz5066dOlCv379CAgIqDVC1JLfj5aWOVdOLnfCxaU3Li69a7xvsRiorEw5u0SXTEVFIuVlyRiMmRgM2VitRtt7lUlw/mZFAKRSDUqFNzKZO0qVBwqFOwq5O3KF29l/uyGTOSOTOSGXOyGVaqujec05r3Ofz8XZpRcJiZ9QULAFd/ehGE0F5OWtxd19WL1yVYiiiMVSgdlSitmko7w8j7KycszmYozGQkymQkymIoymIozGPIyGPIymfP5bH60uFAoP1KpA1OogVOpANOogVOog1KpArFZH1Oq66zbWNx9t/Z1qD7qKioo4duwYx48fJz8/v/r1qmXRHj164OvbsN2zF3M+RKtI5ckCdBtSMOfaarVJHBU4jQi0NY6XSaoDFq0592mnjrNuzueU5Niut9HDRzP0tntQamq/Ob+QPrPJwpI5x9CfLEKKgBio5q6n+yHXxcPim8FiRIy8DtPQ1yh+401Kli4FYNFQCdabJ/LWoNdq3bDXlHNrjkxb6mpKVLCKduW8KRQKevfuzYYNG7j++uurX9+wYQOTJk2qV1YulxMQYOuptnjxYq677roGVd1vLdwdlHT2deJUlo5dCflMirI5b8SuBYvxvOP7+/Sng3MHEkoSWBW/ils731rruHJvb9xnziT/q6/I/ehjHIYPR3KBiEJYTw/ykys4sS2DDfNPMuOlfji6NTzC6Bveiakvv8Xyt18hK/YMy956mRtefBO1Q+13tg1BopLhNi0CVaQrRSviMWdXkDv7CE4jgnAcEojQwOXdpqBSqRg4cCD9+/cnJiaGPXv2kJqayvHjxzl+/Dg+Pj707duXrl27olA0rlRKe0YqVeLgEIGDg63P7rnROlE0YzBkU6lPR1+ZQaU+DYM+y7b8aszBYMjGbC7FYqmwOXckQWlDtArIZI7IZE5IJFrkMi1SqQapVI1EqkajCSE46IGzztDZLXVn5QCsogGLpbLOHzlHhyiiot7lxMlZWK1GRNGMu/tQOoQ9hdlcBthyCCUSGbFxb1NeHmdz1sylZ8+ntMGO2H/PSy53Q6n0QqHwRC7zQqMNRK3yRanyQ6X0Ran0RSqt/W+zau7t1E95eTknT57k+PHjNfLYZDIZnTp1omvXrgQEBKDVapt1IWwLRFFEH1OEbn0ypkzbbnJBLcNpaADaq/zqLWbekhj1lWz/5UeOrFsN2KJtQ+68n4i+A5o8h6WFelZ+dRRdZjlWRIo6aHj5qf5IyvPg56mgL4aAvlivm03ecy9RsWkTVgHmjZUgnzyed6/+X72Om53zaVfOG8CTTz7JbbfdRp8+fbjqqquYO3cuqampPPDAA4BtyTMjI4OFCxcCEBsby759++jfvz9FRUV88sknnDhxggULFlzM0wBgUEd3m/MWX8CkG/qB1hPK8yB5B/gPrHGsIAjcFHkTb+19i99ifuPmqJvr/DK7330XxUuXYsrIoHDBQjzuu/fCtkztSE6yjrzUUtZ/d4LJT/VCKm34H4tPh3CmvvI2y95+heyEOJa++SJTX34LjVPDd+fWhjraA9FXSeWaNPSnCtGtT6HyVAFu0zsh92r4HWBTqCoX0LlzZzIyMti/fz8nTpwgOzubP//8k/Xr19OjRw/69OmDQz219S4HJBI5anUganUguNZ+jMVSgcGQg16fRXl5NlCK0WSLThmNBZiMhRhNBZjNOkwmHaJoBETMZh1m8/kFYgG02giCAu+udrz+i9VSicVSt5dYUZFEfNy7BAbchatrf4zGfJKSZxMb+zrh4bb0A0GQIYpQUnKQ8vLYumYAmcwRqdQRpeJsJFHuilzuilzhjlzugkLhgVLhiULphULugURi+/k81wlu7w7EpUBlZSWnT5/m5MmTJCYmVucpCoJAaGgo3bp1IzIy8uxNx6XhBOvjiyndkIIx1fZdFpRSHK72x3GwPxJV212GU08cZd2cL6pz27qNGMvgW+5CbEagIyO2iLXzTmIoM1EpiMSEKvjqiX5ITBXwyzQoSQW3MCwTfyD9kSeo2LMHkxS+mChBO2ok7wx+B5mk3bki7Z52N2MzZsygoKCAN998k6ysLKKjo1mzZg3BwcGArf9campq9fEWi4WPP/6YmJgY5HI5w4YNY9euXW3atLwuBnX0YN72JHbE5yMKEoRO4+HQAjj913nOG8B1Ha7j00OfkqxLZk/WHgb6nX8MgESjwevJJ8h87nkKvv0WlxuuR1bHEnEVUrmEMfdGs+Sd/WQn6tizIoFBU8MbdT7eoR2Y8eo7LH3rZfJSkljyxgtMffktHFzdGjXOf5Fo5bjdGkXl0XyKV8VjSi8j54tDOI8JwWGQf4sV9q0Pf39//P39GT16NEeOHGH//v0UFRWxd+9e9u7dS3BwMH369CEyMrJBGxwuR6RSDRpNqG2zg/rCzorFYqh23EymEioqC5FKzTaHzFqJ1VKJRKJBEBRIJBJELLZAGeeW+ZAjSJTUpSU9YxFOzj0ICppZJYFM7sLRo3cTEvoYKqUXIEEikdEh7ClE0YxEqrJFA6WOyOROyKSOSKW2GwW7E3ZxMBgMnDp1ipiYGOLj47Fa/+0N7OfnR3R0NNHR0Y0up3CxMSSXULIuGXPyWadNLkE70A/HawKQatvud8RYWcG2RfM5uuFvAJw8vRh93yyCu/VosgMsiiInt2Wxb1UyohVypFb2+kr45aF+KAURlt0FWUdB44752u9Je+gp9CdOoJfDh1MkOF99DR8O+RC55Mr8PW0u7c55A3jooYd46KGHan3vxx9/rPH/qKgoDh8+3AZWNZ5+oW7IpQIZxZWkFlYQHDXB5rzFrIERb513vFauZWKHifx65lcWn1lcp/MG4DRhAoU//Yz+xAnyPv8C3/+9eUF7nD3VjLgjir/nHOfIxjR8O7oQ1sOzUefkERTCjNffY+n/XqIgPZXfXn+Oaa+8g5NH48b5L4IgoO3phTLMmaLlcRhiiyhZnUTlyQJcp0Yg96h/l2tLodFoGDhwIAMGDCAhIYH9+/cTGxtLSkoKKSkpqNVqunXrRq9everMw7RjQypVIpV6olR6nk3mrc8xqn15USrVIpfZoru1JzJbkEgUyOX/RoDlMttyvkyqOZtzZ5Pz9BxZr73N2bZvp/Ho9XpiY2M5deoU8fHxmM3/Rl69vLyIjo6mS5cuuLtfOEe3vWFI0aHbkIIhvtj2glTAob8vjsMCkTq2bSpG8tFDrJ/7JaX5trqX3UeN55pb7qxz41lDMBstbFkUQ8xeW77cKbmZna4iS+7tj7tWAX8+BnHrQabGNOJrUh95GWNSEqVqgXemS3Dv1Z9Ph36KohFFo+3UpF06b5cLGoWMnkGu7EsqZEd8PsG9rwGFI0JZNpLMQ9Dh6vNkbux0I7+e+ZWt6VvJKsvC16H2YryCRIL3C8+TcsutFC9fjuutt6Dq1OmCNoX18KT7iECObkrjn4Wn8QhwwKmRjpGbXwAzXn+fpf97ieLsLH57/XmmvfI2zl7Nd2Zkzko87upC+f5sSv5KwpisI+ezQziPDsbh6raJwoGtXlx4eDjh4eEUFRVVL6nqdLrqaFxAQAC9evWiS5cuV0QrprbAbC6nsjKl+v+V+jRKS08hl7ugVvsTn/AhBkM2XTp/DICHx3DOnHmJ9PRFuLsPxmDIJTbuLZwcu6NU2p3r9kZlZSUxMTGcOnWKhISE6tIeAK6urnTt2pXo6Gi8vLwuopVNx5CqQ7cxFUPs2R0/EgFlD3dcRoUid23bVn36sjK2/PQdJ7dsBMDJ05sxD8wiKLphLRPrQldQydpvT5CXWooowGalkcMqCz/c0pcIb0fY9qEtSCFIMPR/h9Sn3secnU2hk4T/zRDwiOzBF8O+QCW7+K0LL2XszlsrM6iDB/uSCtkVX8At/YMhYjScWI4kdk2tzluYSxj9ffuzN2svS2KX8Fivx+ocW9O7N45jx1K6di05771H0A8/NGi556rrO5CdWEJOko51805ww9O9kcobl/Pg4u1zNgL34lkH7jlbDpxb/cu3DUEQBBz6+aLq6ErR73EY4ospWZNE5fF8XKeG11tlvDVwcXFh8ODBjBgxgsTERA4dOkRMTAzp6emkp6fz999/ExUVRffu3WttaG2n4ZSWHufQ4Vuq/x8f/w4APj430KXzhxgNuej1WdXv+/lOxWIuJz3jJ+Li30Emc8LN9So6dHimzW23Uzs6nY6YmBjOnDlDUlJSjSVRDw+P6rxTJycn1Gr1JblkbUwrRbcxBX1MldMG2t4+OAwLwKwGmaptb+7iD+xl43ezKS8qBEGg59jruPrG28/rktBY0s4Usn7eSfTlJqQqKb9IK0iVW3l9QmeGdvKCo7/BP7ZVpcpOT5L2yjwsxcVke0h5Yzr4dejGp4M/RSNv3XzmK4F21x7rYtDS7bHO5WBKIVO+2Y2rRs7Bl0chOfU7LLsbq1s4wqP7a5XblLKJx7c8jqvSlQ3TNqCUKuvUZUxPJ3H8tYhGIwFzvsFx6NAG2VhaqOe3t/dhKDcTPcSfITd1uqBMbZQVFbLsrZcpSE9F4+zChKdfxj+8U6Pq49SnSxRFKvbnULw6EdFgAamA08ggHAb7YzAZL1q7lLKyMo4ePcqhQ4coKCioPtbR0ZFu3brRvXt3PD09L8uWLm2tq4rWlrtU5uNS0FVWVsaZM2c4c+YMGRkZNY7x8vKqdtiqImyX6nwYUnWUbkqt4bRpenrjNDwQmbu6zc+rKDeHXYsXErNrGwCuvv6MfmAWAZFdmqVLFEUOb0hlz4oERBEcfDXMNhaTa7Fwa/8g/jc5GiFpG/w8Bawmyt1nkDb/IGJFBSl+ct6cZiUgoDPzRs9DYVVccp9za+m6bNpjXY50C3DBQSmjqMLEqSwd0R1HIkpkSArjEAviweP8TQNDAofgo/Uhuzyb9cnrmdBhQp3jKwICcLvjdgrmfUfuBx/iMGgQQgMS6h3dVIy6qwt/fXWUE1sz8OvoQnjfxi8zObi6Mf21d1n29ivkJSey8r3XmfLiG/h2vPASbkMQBAFtPx+UnVwpXhGP/kwhunUpVB7PRzMhGEIuTujdwcGBQYMGMXDgQDIyMjh69CjHjx+ntLSUnTt3snPnTnx9fYmMjKRHjx6NuimwY+dSw2KxkJaWRmxsLGfOnKGwsLDG+wEBAURGRhIZGVln/c1LCUOKDt2mc5ZHBdD09MJpeBCyNsrPPRdRFInZtZ1/5s+hslSHIEjoM+F6rpp2c4P6UteHUW9m809niD9oa9sW0seTd3Nyya20cFWYK69O6IyQexp+uxWsJnTCUDLn7kE0mYgJU/L2ZDMB3uF8O+pbnBROl8Tu4EsBu/PWysilEvqHurHpTC474/OJ9u8AIVdD4haI+btW500mkTEtYhpfHv6SxWcW1+u8Abjfdx/Fy3/HmJhI0ZIluN1yS73HVxEc7U7vccEc/DuFf34+g0egA64+jV+S1Dg5M/2Vd1j+7mtkx8ew7K2Xuf7Z1wjoXH/7rsYgc1bifkdnKo/kUfxnAqbMckrmnsJyTQBOI4LarEbSfxEEgYCAAAICAhgzZgxxcXEcPXqU2NhYsrKyyMrKYvPmzQQFBdGlSxc6d+5cZ+V3O3YuJSoqKoiPjyc2Npb4+PgaF2WJREJYWBiRkZF06tTpsvnOm1JKKdsR/+9GhKpI27DAi+K0AZQW5LPx+69JPLgPAPfAYMY+8Bg+HSOaPXZxbgV/zzlOYWY5EolA/ykdeON0Kumlejp4avlsWjTy8mxYNBUMOoqKupK9Pg5EkaNdNLw/3kCAWyjzRs/DVeVq3xTUgtidtzZgUEcPm/OWUMD9QzpAxFib8xb7NwyaVavMlPApzDk6h2P5xzhZcJLObp3rHF/q6IjnrEfJfv0N8r/8CucJE5A2MATb77pQshNKyIgtZu3cE0x9vg+yRua/AagcHJj60pus+OBNMk6fZPk7rzLxqRcJ7dmn0WPVhSAIaHp6oezoQtGqePQnCijbmm7Lhbu+I6rwOgqUtREymYyoqCiioqLOKy6amppKamoqa9euJSQkhC5duhAZGXnZ14+zc/lgtVrJzs4mPj6e+Ph40tLSalyM1Wo14eHhhISE0Llz50a1GmzPiKKIIaEY3T9pGBNLbC9KBLS9vXEcGoDM/eI4baLVyrFN69i2aD7GygokUhm9J9zAwKk3IpM3fxdn8vF8Ns4/haHCjMZJwZj7uvDu/mSOppfgopHz3e19cBIq4JfpiCUZFKSEkLfHlkKyt68Tnwwvx98pkO9Gf4eH+tKPtrY37Dlv/JvzVlRU1OI5b2BrkTX28+2o5BKOvDoKhS4NyZc9EAUpPB0HmtrrpL2w/QVWJ61mcofJvDHwjfpzw8xmkiZfjzEhAbe778LrmWcabGNFiYEl7xygQmek0wAfht3WCYOhcX31qnSV6XRsnPMZSYcPIJHKGP/oU0QMOH9jxrkyTc1L0B3NpmJtGtYSW8cKdU9PnMeHIXWofdm4LXMgzpUzGo2cPn2aEydO1Mj/EQSBwMBAIiMjiYqKwsXF5ZLI02hLXW3JpTAfba2roKCAjIwMEhISSEhIoKKiosYxXl5eREREEBERgb+/P4IgXJS/sdaYD1EU0Z8ponRzGqa0s4WiJQKaPl44Dg1E1oDdo611XkVZmWyY+yXpp08A4NOxE6PuexQHT69m6xKtIgfWJLN/TTKI4B3mxNh7o/nuQCqfbYpDLhVYeHc/+gc5Ii6aiiRpGzknfCg6abvp3zzMjW/6l+Dr4Mf8MfPxc/Br9floKZm21lVSUoKrq2uTct6uaOdt9uzZzJ49G4vFQmxsLNnZ2Y2ewKoPrD5EUeSaj3eSX25kwR096Rfiivy7ocgKzmC87issXabWKncs/xj3/HMPSqmSP6/7E5WoqldXxY6d5D76KMjl+C9fhjwwsME2ZsWXsPbrU4giXD0jjKAezk26c9br9chlMjbN/ZL4fbsQBIGhdz9I1OBh9co0VZdSkFPxTwb6fbZ8DEEtQzsmAEU391r/iJqjqyXkiouLOXPmDDExMef18K26EAYHB1dfCFvbxracj/pk6jtXg8HQpFIs58o19GeuvczHxdJlMplIS0urrmuYk5NT432FQkFwcDChoaF06NCh1t/Li/031lwZ0SpiPF1E5fYsLDmVthdlAqqengh9XNB4tfw1oqFyVouFo+v+Yt+K37CYTMgUSvpPuYmuo8YikUibrctQaWbbz/GknbLl8kUO8qb/5BDWncnjqeUnAXhrYiRTevgiX/M40mO/kXnAA12iLdK3+jpvFnQtwFPtyZyhcwh0DGzQeTXGxtaWaUtdOp0OHx8fu/PWVFo78gbw+OIjrDqaySPDOvLkqHAsG15HvvtzxM6TYdqPdY4/Y/UMzhSe4YleT3BjhxsvuCMo/d77KN+5E8cxo/H/7LNG2XhwbQp7VyUilUu4blYX/DrU7gDVRc1emVY2fvc1J/5ZD8DQO+6l17iJ9co05+7ImFZK0e9xmLNtkQFFmDMukzrUaLF1sSJvdcmVlJRU78hLSUmp4WA4OzvTsWNHwsPDCQ0NvWCP1cv1zvRytbG96LJarWRkZJCUlERiYiLp6ek1aq8B+Pj40KFDBzp27EhgYCBSad35pZfy5yyarVQczaNsazrmPJvTJiikaAf44HC1PxIH+UX9nHOS4tnw7ZfkJicCENS1B6PufRhnL58W0VVeYGbt3JPo8iqRyiUMuSmCyKt8OZJWzI1z92AwW7l3cCgvjo+CLe8hbnqf9F2ulGeqQCplxXR/fg3JxE3lxvwx8wl1Dm3V+WgNmbbW1ZzImz3n7RwEQWh0tKNK5kJyg8I9WHU0k50J+Tw1OgJLxzHId3+OEL/J1qhedn5koarf6Wu7XmNJ7BKmh02vV5cgCHg9+yxJ119P6br1VB46hLpXrwbb2HtMMNkJJaScKGDzgjimveiCStO41iVVeiQSGaPvexSlWs3B1avYsmAexsoKBtxw43l2NNS+unQJgoAyyAnvR3tStiODkg2pGBNLyP3iMI6D/XEc/u+GhpbQ1VJyLi4uDBgwgAEDBlBeXk5sbCynT58mMTGRkpISDh48yMGDB5FKpYSEhFQXDXZzc6t1vKbY2Jbz0Z7m/krVZbFYyMzMJDk5mZSUFNLS0jAajTWOdXJyIiwsjNDQUPz8/PDw8Gi359VUuXNlrEYL5fuyKduegaXEYHtfLcNhoB+Og/yQnP0NFEXxonzOZqOBXUt/4eDqlYhWKyqtA0Num0mXoSNb7Lc08XABO39LwGy04uimYtwDXfEMciSzuJJ7Fx7EYLYyMsqb58dFIRxZhGXD+6Rtc6MyX4mgUrLk1mCWeibirHRm3uh5hLmEtdp8tNfvYlNlmordeWsjBnW0JWweSy9Bpzeh8O2B6OCNUJZja1TfcUStcuNCx/HxgY/JKMtgd/ZuRobV3+JH1SkCl6lTKV6yhJz33id48a8NtlGQCIy8szO/vbMPXb6ezQvPMPb+6CZ/wQRBYMht96BQa9m97Bd2LVmEvrSUobffg9AKhWwFqQTHIYGou3pS/EcC+jOFlG5Jp+JIHi4TwlBGNa8Ha2ui1Wrp2bMnPXr0oLS0lOzsbOLi4oiLi6O4uLg652jt2rU4OzsTGhpafYG9XHby2Wl5DAYD6enpJCYmkpGRQXp6eo02VAAqlar6+xQWFlZ9c3CpNH1vKpZyExV7sijblYm1wjYnEkc5jlf7ox3gi0R58S+PKcePsPG72ZTk2FIsOl01mGF33ofWpWU2Z1ksVnb/Hs/RTekABEa5MnpmNCoHOeUGMzMXHCC/zECkjyOf39gDaeI/mJY8QdpmDwzFcgRHRxbdHcxKzRkc5Y7MHTWXCNfm73K1c2Eu/rfzCsHfRU2oh5ak/HL2JhYyOMzZtuv00AKIXVun86aWqbm+4/UsOLWAZfHLLui8AXjOehTdX3+hP34c3erVKEeNarCdKgc5Y+6NZsVHh0g8ksfRTWn0GBnUYPn/IggCA6fdjMrBgc0/zuXQ339QWVbKmAceQyprna+fzE2Fx51dqDxVQPEfCViKDRT8dBplJ1fUYwLAt33vgpPL5YSHhxMREYEoiuTn5xMbG0tcXBxpaWmUlJRw5MgRjhw5Athy5UJDQ/H396dDhw5otW3bgaK1ac7Nw5WEKIoUFxeTlpZW/cjJyTkv30+j0RAcHExISAjBwcF4eXldUV1BzMUGyrekYjiUj2iydXuQuqtwvCYAbS9vhCbstm9pKkt1/PPjXGJ2bgXAwd2DkTMfokPvfi2mo7zEwPrvTpIZVwxArzFB9J/UAYlEwGoVefy3I5zO0uHhoOT7O/uiLTqN8bs7Sd3ggqlchtTDgx/vDuJP6TE0Mg3fjPqGzu51V0Ww07LYnbc2ZGAHd5Lyy9mVUFDTeYv5G8Z9AHVcbGZ0msHCUwvZlb2LtNI0gpzqd6ZkHh64338/eZ9+St4nn+J39dXQiERK7xAn+k0OYc/yJHb/noB3iBO+HV0ac6rn0WvcRFQOjqz9+lNOb9+MobyM6554vkW2tNeFurM7yo4ulG5Oo3RbOoaYIgwJxViuCcBxaOBFqw3XGARBwNPTE09PTwYNGoTRaCQ1NZXExEQSExPJzs4mNzeX3NzcahlPT0+CgoIIDg4mKCgIFxeXi3cCLUBT+8Ze7v1mKyoqyMjIIDMzs/q5rKzsvOOcnZ3x8/MjLCyMkJCQRi+DXi4YM8so255BxdE8sNocWrmfFsehgaijPdqsb3J9iKLImR1b2LzwOyp1JbbWVmOu4+obb2tWI/n/kpVQwrq5xykvMSJXSRl8Uwci+/27SeqDdTFsOJWDQiZh7u298RcK0H8xjdS1aix6KfLAAObfG8KflXtQSVXMHjGb7p7N65lqp3HYnbc25OqOHizam8rO+HwYFQZhQ0CmhpI0yDkBPl1rlQt0CmSg30B2Zu5kaexSnurz1AV1ud1xO0W/LcacmYVu0SI0jzzSKFujBnmTn1JO/IFc1s07wfSX+qFxap6j1XnwMFRaB/785F0SD+1n+duvMumZl0Hael9DiUKK85gQND29KF4VjyGhhNJ/0qg4mIvz+BDU3TwvqQuZQqGgY8eOdOzYEYDy8vLqZPOUlBQKCgrIy8sjLy+PgwcPArYcpoCAAPz9/QkICMDX1/eCGyDstC/Ky8vJzs4mKyuL9PR0srOzKS4uPu84iUSCr68vgYGB1Q9HR8d2X6altRBFEUNcMaXb0zGcjTAByEIccR4WhCrCtd3MSXF2Fhu//5qUY4cBcPMPZPQDs/CPiGoxHaIocnxLBjuXxmG1irj6ahl7XzRql3+jjcsOpjNnawIAH07tRi8vCeVvXk/6nyJWkxRlp3B+uCeYPwq3oJAo+GLYF/Txabl6nnYaht15a0Ou6uCOIEBcbhm5pQaCPJ2hwzCIWWOLvtXhvAFM7zSdnZk7WRm/kkd6PoJSWn9UQaJS4fXkU2Q+/TQl83/EY8YM5Gf7CDYEQRAYdksnCtLLKMquYMMPJ5kwqweSZt6dhvXqy5SX3mTF+2+SceYkS998kWufeAGVj2+zxr0Qci8N7jOj0R3OonJDBpZiA4W/xqDYnYXLhA4o/C/NYrlarZbo6Gi6dOmCXq/HarVWFwROTU0lMzMTnU7HqVOnOHXqFHB2Y4uXF35+fnh5eREQEIC3t3e7cOiSk5PZtWtXdRRpxowZREZG1nn8ihUrOHr06Hmve3p68tBDD7Wmqa2CxWKhqKiInJwcsrOzqx+lpaW1Hu/m5oa/vz9+fn74+/vj6+uL/D/t8a7EggKi5ezO0W0ZmLLLbS9KQN3VE4fB/ljdZe3GmbWYzRz4awV7lv2K2WREKpcz4IYZRI8aj9ah5fJZTUYLWxadIXavrfxLx95eDLstErlSWp3buD+5kBd+PwbArOEdmRTtSelrY8lYWYpolaDu2ZX5dwazKnstMomM9wa+xwC/AS1mo52GY3fe2hAXjYJoP2eOZ5SwJ6nI5rx1GnfWeVsDQ56tU/Ya/2vw1niTU5FzwX6nVThdO57ChQvQHztO3pdf4fe/Nxtlr1wlY+x9XVn63n7SzxSx/68k+k+sexdRQwmIimbG6++x/J1XyUtJ4vd3XmHqS2/h2soOnCAIKDu74dTVm7LtmZRuScOYrCP3q8No+/rgNDoYqcPFd2Cag0ajqe7yAGA0GsnIyKjx0Ol05OTknFfDy93dHW9vb3x8fPD29sbb2xsnJ6c2zYcymUx4e3vTo0cPlixZcsHjx40bx8iR/+aBWq1W5syZQ+fO7Tv3xmKxUFBQgE6nq46U5uXlkZ+ff16pjirc3Nzw9vbG09OT4OBg/Pz8UKsvTnX/9oq1wkTZ3mzKdmdi1dl20QoKCdq+PjgM8kfmpmpXGzEyY8+wYd5X5KcmAxAU3Y2R9zyMi49fi9pYklfB39+eoCC9DEEiMPCGDnQfEVi9MQUgtbCC+386iMkiMr6rD4+PCKf41evJ+j0TRAGHQX348Y5Qfk9agVSQ8uE1HzLIa1CL2WincdidtzZmYEf3s85bIdP7hdjy3hAg8zDossCpdgdGKpEyOWwy3574liUxSxrkvAmCgNdzz5F6y62ULF+O2223oopo3E4gNz8tw26NZMMPpziwJhmfMGeCo90bNUZteIWEceObH7DsrZfR5eaw+NVnuOGFN/AO7dDssS+EIJfiNCIITW9vSv5OovJoHuX7sqk4mofT8EAcBvq3i6TllkChUBAaGkpo6L81l3Q6HZmZmaSnp5Oenk5eXh7l5eUUFBRQUFBQHaEDW8svDw+P8x4ajaZV2h9VlUNpKCpVzcLVp0+fprKykh49erS4bY3FYrFQUlJCYWEhBQUFNZ6LiorqjIjJ5XI8PT3x8fGpfnh7e6NUKi+JThUXA1NuBeW7Mqk4lFu9CUHiKMdhoD8O/X2qy320FwwV5Wz/dSFHN6wBUUTl6MTQ22bS+ZrhNRyqliD5WD4b5p/CWGlG7WjbkOYfUXO3apnBzD0LDlFYbqSrvzMfT+tB0cu3krsiFhBwHtmfn26JYEnsr0gECe8OfpcRQSPajRN8JWJ33tqYq8Lc+XZrIvuTi20vOHhBQB9I32/bddrnrjplJ4VO4vuT33Mk7wgxhTF0cut0QX2aXr3QjBhBxaZN5H7wIUHfzWu0zRH9fMhKKOHE1gw2zD/J9Bf74tQC/fxcffy48Y0PWP7uaxSkpbDkjeeZ+NRLBHft0eyxG4LMRYn7TZEYrvKl+I+zze7/TqZsdxbOY0JQd/dsF0nMLY2TkxNOTk506tSp2hGoyqmqWq7LyckhPz8fs9lcvXT3X7RaLa6urri4uODq6lr976rxL8Yy7OHDhwkLC2v1TRqiKFJZWUlZWRk6nY78/HzKy8spKSmhuLiY4uJiSktL670IVzlpVQ8vLy88PT1xdna+onZ/NhVRFNHHFaHbloYpXlf9utxPi8PV/mi6eSLI2tc8iqJIzK5tbFn4HeXFti4GXYaM4Jpb70bj1PAC8Q3BahXZ92ciB/9OAcAnzIkx93bFwbVmyo3ZYuXJZSeJyy3D20nJ3Ft7oXthJoWrz+beXdePRTd25eeTPwLw5sA3GRc67opcjm9P2J23NqZPiBtSiUB6sZ6M4koCXDW2pdP0/ba8t3qcNw+1B8ODhrM+ZT1LYpbwylWvNEin62OzqNi2lfIdOyjbvgOHwXX3Gq2Lq6eGk5usIzellHVzT3DD072RtkB0ysHNnckvvMG6rz4m/dRxfn/3dcY9/ASRg4Y0e+yGogxxxuuRnlQczkW3PtmWD/dbDPIdGTiPD0UZ1rI/qu0RBweHGhshwBY5Ki4url7OO/eh1+spLy+nvLyc9PT0WsdUKpU4OjpWP9RqNY6Ojmg0muqHg4MDrq62KEBzI0mlpaXExcUxZcqURstarVYMBkN1pKyyspKKiorq54qKCsrKyigtLa1+rmt581ykUilubm64u7vXeHZzc0Mul6NWq+0RtEZiNVioOJxD2a4szLlne60KoIp0w+Fqf5Rhzu1yTv+7IcHV15+R9zxEUHTL79KsLDOy4fuTpJ22OYhdhwUwaEpHpLU4s+/+fYbt8QWo5BK+u7kn4ssPUrhpHwBe1/fktxn9mX/0GwBeGfAKkzpOanF77TQeu/PWxjgoZXT1d+ZIWjF7EwsJ6K2BiHGw6U1I3ALGclDUXadreqfprE9Zz1+Jf/FknyfRyi9c00seGIjrzbdQtGABuR98gHbgVQj1tLipDalcwpj7olnyzn5yU0rZvjSOoTdfOPLXEJQaLTe88AZrZ39C7J4drP7iQypKiuk1vu1+JASJgLa3N5puHpTusOXDmTLKyJ93HFWkK8rhfhDYvuvDtTRSqRR3d3fc3Wsuk1fVE6usrKS4uJiioiKKioqqI046nQ6j0YjBYMBgMJCfn1+nDi8vL+6++24sFgtWq7X6olv1bDQaqaysPO/1Ks79/4EDB6oLzhoMhvPOZePGjRQUFGA2m2vYZzAYMJlMTZojtVqNg4MDjo6OuLm54eLigouLC87Ozri4uKDVamuNorWnvKtLBXN+JWW7Myk/mIOotznOgkKCsrsHztcEIvdsuVIaLYnFZGLPmlXsW7GkekNC/8nT6TtpKjJ5yy/n5iTrWDfvBGWFBmQKCcNujSSin0+tx/6yN5UfdiYD8MnETri8MYuS3YdAEPGd0onlM0bwzaHPAHi277NM7zS9xe210zTszttFYECYm815SypgSu8A8IoCl2AoToGEzRB1XZ2yfb37EuocSlJJEn8l/MWMyBkN0unxwP2UrFyJIS6O4uXLcZ3e+D9CJ3c1o+7uwl9fHeXktgx8wpyIHNAymwxkcjnXPvYMGmcXjqz7i80L5lFWVMjgm+9s07toQS7FaVgg2r7e6DalUr43C/2ZIvQxRZh6eeE0IhiZ25XlxNWGSqXCxcUFPz+/Wt83GAyUlpZWP3Q6HcXFxRiNxhoRrf8urVYtxVQ9WyyWBkW4RFHk6NGjREVFYbVasVqt1e9VOU9JSUk16uHVhlQqRaPRoFara0QIz3XSzn2Wy+X2PLRWRLSKGOKLKduViT6mEM6u1MncVWiv8kPT2wsjZmStkH/ZEqSdOs6GebMpzsoAbP1IR858EFdf/xbXJYoiZ3blsGdFElaziLOXmnH3d8W9jp30u+LzeXXVCQCe7O9J5w+fpezYSQSpiP9kX/648QY+O/gRAI/1eozbOt/W4jbbaTp25+0cRFFs1Dp+1fGNXfvvH+rGnK2J7Eks+Fe20ziEvXMQY9ZA5LX12jYtYhof7P+A32J+Y1rEtHovGFVyEmdnPB56iNx33yXv8y9wHD8eaR2V+Os7r6DObvQdH8L+1clsWRSDu78DHgEOTZ6Pc2UEQcKwO+/DwdWNHYsXsv+P5ZQVFTL6/keRys4vf9Can5dEK8dlYge0V/miW5uM/lQhFQdzqTiSh7avD47DApFeoO5da9vYnnUpFIoaUbsLOTjnOm3njiuXy6uL7f5X37n/T0lJobi4mJ49e9YolfFvr10J11xzDUajEZlMhlKpRKlUolAoqv8tl8sxm82NWso8dy7ay9xfDros5SYqDuZQvjcbS+G/EUplhCsOA31RhrsiSGyJ/aLe1O7mo7y4iG0//8DpHVsA0Dg5M+T2e4gcNKRBGxIaa6PJaGHbrzHE7LHtIA/t4cHw26NQqmW1jpGUX86Diw5htorcGKZi/LzXqUxMQiK3EjDRgdU33cF7Zx23+7vdz8zombX+/V0J38XW1tVUrmjnbfbs2cyePbv6zt5gMDR6KcNgMDT6brurjwapAKmFlSTmFOPnrEISOhLl3jkQuxZ9RTlIzl/WrNI12n80nx/6nLjiOPZl7KO7R/05E1Vy6usnI/v5Z8xpaeTOmYPrww836byih/uQmVBMxpli/v72GBOf7IZSLbugXEN1dRs7AYXWgc3z53B6+2ZKC/IZ88hTKDXaeuWaouuCOErQTguDRBcsO/MwJZZSvieL8gM5qPp7oR7kg0Rd959Rm9h4CesSBAGlUln9uslkorCwsPr90tJS8vPz0Wg0ODs7s3HjRkpLS7n++utrjHPy5MnqIsRVVDUSr6Jjx471/lharVaMRmOTNgtcinPf3nTp9XrM6eXoD+RiPFkEFttnJSilKHu4o+rrhdTdFmEzGP9dFm9P82G1Wjj5zwb2Lv8VY2UFCAKRg4cxcMZtqLQO5y3nt4SNurxKNv0YS1FmBYIAva8NoutwP0TBjF5vPu/4kkoTd/94kJJKE8O1ldz968eYsrKQqSwEjIPVU+7nfwc/BuDWTrdyd6e767wutqe5vxR1Neb78F+uaOft4Ycf5uGHH0an0+Hs7IxSqWxU+YMqT/vci09DUCpFOvs6cjyzlCMZ5YR5u0DHIYhKJ4SKAlQFJyCwf526vFRejAsZx8qElaxMWkn/gP61K/qvjSoV3s88Q8asWeh++hmPm29G7nv+smdDzmvMzGiWvnuA0nw9OxcnMe7+aBBo9HzUpavHqHE4e3jy12fvk37qOCvffY0bnnsNRw/PBtvYlPOqUy7UFVWUL8bEEnTrUzCmlqLfmY3hQB4OV/vjMMjvPCeuzW28DHRlZmayYMGC6v+vX78egO7duzN58mTKysooKSmpIaPX6zl16hRjx46t14YLtctqj/NxJeiy6s1UHMnFsCeLipzK6tflflq0A3xRd/ess5Vde5qPrPhYNn3/NblJtu4E3mEdGX73g7j4BzZ6Sb2hNiYeyeOfBacx6i2oHeUMua0jodHedcqYLFaeWnSU5IIKrjLn8uyaeViKipA7mAkcWcE/017hfydmA3Bz5M080/eZOsdqT3N/qepqjvMmiM2J210mVDlvxcXFODs3fGfhhZaC6pN7688TfL8rlel9Avhg6tnI2bK74cRyGPwUjHi1Xl0n8k9w0+qbkEvkbJq2CVeVay2azpcTRZGU226j8sBBnCdNxO/995t8XrkpOpZ/eBCrWWTA5DB6jQlu9HxcSFdOYjwr3n+D8uIiHFzduP751/EKCWvS3Dfn8/rvHOrPFKJbl1JdvV1QSnEY5IfDIH+kWnmT9bWUjZeTripaW+5SmY/LQZcoihhTSynfl03lsbzq2mzIJGi6e+IwwBd5gMMF9baH+agsK2Xn4oUc3bgWRBGlRsvVN95Ot1FjEQRJq8y91WJlz6pEDq9PBcC3gzOj7+mCVCXWq+uVlSf4aU8K/YsSeG3fAoTKClSuRgKGFrN14os8HfcTFtHClPApvHrVq0iEuqPQ7WHuL3VdJSUluLi4UFJSgpOTU4PlANpXEZwriH4hNmdrb9K/S0SEj7E9x62/oHy0RzSd3TtjsppYGb+ywXoFQcD7uecBKFn1B5UnTjZY9r94BTtxzQxb0d+9qxJJP1N4AYnG4x3WkZvf/hj3gCDKigpZ/NpzJB852OJ6GoMgCKij3PGa1RO3myOReWsQDRZK/0kj+/39lKxNwlJmvKg22rHTHrFWmCjdkUHOZ4fI++YoFQdzEE1WZJ5qNKMD8H2hL27TIlAEOrb7zR+i1cqxTev44fH7ObrhbxBFOg8exl2fzqHHmGuR1JL60hKUlxhY9dmRaset+8hAJj3ZE61L/ZHlhbuT+WlPCoMzj/Lazu8QKivQeBkIGl7A9uEP8Ez8z1hECxPCJlzQcbNz8bF/OheJXkHOSCUCKQUVZBafXSroOAIQIPs46DIvOMaMTradpktjl2IVrRc4+l/UXaNxmmDr0JD7/vvNSprsfLUfkQN9EUXY8P0pyoubHgauCycPL2588wMCu3TDpK/k9/ff4Pg/F3ZwWxtBIqDp5on3Y71wvzUKua8W0WihdEu6zYlbk4S11O7E2bmyEa0i+tgiCn49Q+Y7eyn5KxFzTgWCXIKmlxeeD3TD64leqK9qf50Q6iI7IY5fXnmaDXO/RF+qwz0giOmvvsO4R55C61L7KkhLkBlXzJK395MZV4xcJWXMvdFcPTUcqbT+S/m22Dze+PMU1ybt4oX9PyOYTTgG6gkcUsC+gbfyTPZazFYzo4NH8+agN+2O2yWA/RO6SDgoZUT72cKke5MKbC9qPcC/t+3fcRsuOMbYkLE4yh1JK01jd+buRun3euJxBKWSiv37Kfvnn0bJnosgCAy5MQKPQAcqy0z882MsFlPDHcmGotI6MOXFN+g8eBii1cqGuV+yZ9kviNaW19VYBImAOtoDr1k9cb+9M/IAB0STlbLtGRR9fpyi5XGYqoqJ2rFzhWDKq6BkXTLZ7+8j/4cTVB7NA7OI3FeLy6QO+L7YH7fpnVCGtM+iurWhLytlw7yvWPTSk2THx6JQqxly20xue/8LArt0azW9oihyaH0KKz89TIXOiJuflmnP96Fjb68LysbnlvHwooPMOLWOR47+jiCKuEQY8b+qkMNdxzKraC9Gq5GhAUN575r3kEmu6FT4Swa783YR6R9mK6OwJ+Gc5caIhi+dauQaJnacCMBvMb81Srfczw+3O+4AIPfDjxCbWKQUQKaQMva+rijVMvJSytixLK7JY9WHVCZn7MNPMmDKjQAc+msFq7/4AJOhfRQ7FQQBdWd3vB7ugftdXVAEO4FFpOJADjmfHCR/wUkMySUXHsiOnUsUq96M/lAeeXOOkfPxQUo3p2EpMSKoZWiv8sXrkR54zeqJw1Xnb/Bpz1itFo5tXMui52ZxfNM6EEWirh7KXZ9+S5/rrkcqa71zMVSY+HvOcXb/noBoFYno583U5/rg6nPhAu1F5Ubumb+XW/ct5bYztmuKRy/w6ZnPibB+PGxKQW/RM8BnAB8N+Qi55NKIfNq5wnebXmwGhLoxd1sie6oibwDho2Dz27ZuC2YDyOrPY5geMZ1FpxexNX0r2eXZ+Ghrr6RdG+733UvxsmUYk5Mp+m0Jbrfe0sQzAWdPNSPv7szqr49xclsm3iHORA1smQK+5yIIAoOm34qzpzcb5n1F7J6d6PJymfTMKzi4urW4vqYgCALqTm6oIlwpjcvHuCcX/enC6ociyBHHIQGootwvy96pdq4sRLMVfWwRFYdzqTxdAOazaRgCqCJc0fT2Rt3Zvd31GW0oGTGn+Wf+nOpdpB5BIYy46wECOke3uu681FLWzTuBLl+PRCYweHoEXQb7NShSaTRbeWTBHm5aN5drMo+BIOB9jQo33wROe0dwv6KMclM5fX368sHAD1BI274XsZ2mY3feLiJ9QlyRCJBSUEFWSSW+zmrw6Q4O3lCWA6m7IWxovWOEuYTR27s3B3MOsiJ+BQ92f7DB+qUODng++gjZb7xJ/ldf4TxxAtJG7ng5l+Bod3qOCeDw2nS2/hKDR4ADnkGOTR6vProMHYna1Y21X35kyz956SkmP/sKXiFhraKvqcgDHXAM98CcV0nZ9gzKD+VgTC2l4KfTSN1UOAzwRdvH+5LJ9bkYGAyGC5b5aEk5OxemardoxeFcKo/lYa34t56Y1EOFto8P2l5eSJ0u3fkvKyxg2y8/cnr7ZsDWxq/P5Gn0vXZyq0ba4N9uCXtXJGMxW3F0VzH2vmi8ghv2+yyKIv9bup9rf/2InnlxIJPhf50nTqqDxDv7cJ+LglKjjp5ePfly2JdILJemY30lY//ELiKOKjld/W2lSfYmnl06lUig4yjbv2MblpQ/LWIaAL/H/Y7FeuFWQufiMm0aig4dsBQXUzB3bqNka6PHqACCu7pjMVv5e85x9GVNX469EH6dOnPTWx/h6hdAaUEei199loSDe1tNX3OQe2lwnRKO73P9cBwaiKCWYSnUU7Imiax391H0e1x12RE7NWnqhhp7FaSWRRRFjJlllKxNIvvDA+R9c5TyPVlYK8xIHOU4XO2P56M9cH6oC45DAi5Zx81sMrFv1TJ+ePx+m+MmCHQdPpq7Pp1D99HXImlkX+jGYjJY+GfBGXYtTcRithLS1Z3pL/ZtsOMG8NPfR+j72Uv0zIvDqlITdEc0TqqDJKsducfHk2Kjji7uXZg9YjYaefvsCWunfuzO20VmQFXeW+I5S6cRo23PDch7AxgZPBIXpQvZ5dnsyNjRKP2CTIbXM08DULhgIcb0jEbJnzeeRGDknVE4e6opLdSz/vsTWK2tdxF19fHj5v99RFDXHpgMelZ++BYH/lrRbi/cUicFzmND8H2hH643hCP30SKarJTvy7aVT5h7DMOpQkTLxd+IYccOgCmnnJL1yeR8fJDcLw5TuiUdS6EeQSFF08sLj5nR+L7QH5frwlD4Xbg2W3sm8fB+Fj7zMNt/+RGTQY9veCduefsTRt8/C42zS6vrL8wqZ9n7B4jZm40gwIDJYYx/sBsqbcMj89u3HcXvlVmEl2RgdHQm7IkRaMvXkC6Xc09QCAXGEjq5duLbUd/iqGidlRE7rY992fQiMyDMnW+3JdZ03sKGgkQGBXFQmAhu9S8FKqVKJnaYyMJTC1kWu4whgUMaZYPDkCFoBgygYs8e8j75BL+PP2rCmZxjj0bOuAe6suz9A6SdLmLvH4lcNblDs8asD5WDAzc8/zr/zJ/DsY1r2frT9xSkpzFi5oPI5O1zOVKikKLt54OmrzfGJB1luzOpPJmPMUmHMUlHxd9paHp5o+3rjdzTfmdsp+0QRRFzbgUVx/OpOJqLJe+cDUEyCepOrqi7e6KKdKuz88GlRkF6Glt++q66hqTWxZXBN99J58HDEJrQLq0pxO7LZvOiGMwGCxonxQW7JdRG3J6jyJ54DE+9jlIXD7q/Oh3lvpfJlkq5J7QTOcYSwpzDmDt6Ls7Khhekt9P+sDtvF5mqvLfkc/PeVM4QdBUkb7eVDOl//wXHmRoxlYWnFrItY1ujNy7YCvc+S9INU9CtWYPr7bchdOrUnNPC3d+BYbdFsuH7Uxxam4J3sBNhPT2bNWZ9SGUyRt7zMO7+gWxZ+D0nNq+nICOViU++2G42MtSGIAgow5xRhjljLjZQtieT8v3ZWMtMlG1Lp2xbOopQJ7R9fVBHe1w2F0s77QtRFDGll1F5Ip/KkwWY8/9tU4VUsG086OaJqrMbEuXlc9moLCtl99JfOLJ+NaLVikQqo9f4iQy44UaUmra5aTKbLOxYEsfJ7bbanv6dXBl1d2ckisZF37O378Y06xFcTZVkewQw4KOHUK6/hzyphHtCO5Fh0hHkGMR3o7/DTdV+fxPtNIzL56+wBajqT9bY4xu7RHeunK3emzPHMkrYk1DA5J7+toPCRyMkb0eMXQf97rugrhCnEPp49+FAzgGWxy7noR4PNcpGZWQkzpMnUbJiJbkffIDnvHnNOi+A8D7e5CTpOPZPOhsXnGKqT+/ztre3xByeS89xE3H1C2D1Fx+QFXuGRS8+wcSnXsSnQ0SL62ppOamzAqfRwcgHeUFKBRX7czDEFlVH44r/SEDT3RN1Dy8UwTUr0DfFxracj/Y+91eiLtFixZiso/JkAfpTBVhKzikoLRVQhrsgi3DCsbsP0nM21NSn+1L5nC1mM4fX/snuZb+iLysFoEOf/lxz6924+vhVH9cSuuqTKcmrZN3cE+Snl4EAfcYF0+faUATB1rO3obqK1m0g76mn0FjMxHp3YPBXL6D660YKsXJvcEdSLGX4af2YN2oeHmqPGuO2h+/ilayrqVzRztvs2bOZPXs2Fostyd9gMKDXN65mmMFgaFKOx7lyfYJsztvOuFzGRtly4ISga1ABJO9ArysAhfaCuiaFTuJAzgF+j/ud2yNury622FAbHR94AN3fa6k8dBjdunVIxo1r1nkB9BrvT25KCdkJpaz55jgTnohGoZLVK9NUXVX4dOrMlFfe5e8v3qcoM4PfXnueIXfdT+SgIS2uqzXkjGYjqg4OOHRwQK0zYjiSj+FwPtZiI+V7synfm43ERYGyqzuKrm7IPNVN1tWW53UpzP3lrstaYcYUV4IxrhhTvA7RcM4GJ7kERYQzikhX5OHOSJRS9Ho9JokFk77hG6Ha++eceuIoO36ZT3GmLb/XLSCQq2++i4DOXQHqvQa05OecfKyA7b8mYNJbUGllXHNrOAGRLhiNhkbp0i1fTv7b7yAXRfb7RdPnk+dxWX8bOlMZ9waFkCDq8VJ7MXvIbFxlrrWe3+X+vW+vuuyN6ZtJVWP6oqKiNmtMf67cP2dymbngACHuGjY/PbTqIPiiO0JxKuKNvyJGjL2gLqPFyMhlIyk2FPPFsC8YGji00TbmffElBd98gywggLC//kTSiFILdemq0BlZ+u4ByosNhHTzYNz90dX1zVqzebChooK1sz+p3oHaa/wk+t5wIxqtttUbFTdVri4Z0SpiSCim4nAe+pMFiMZ/L6ZyPy3qHp5IIhzReDldVo2bL1cb20qXKIqYssopO5WHJV6HMbUUzvnFl2jlqCJdUXVxR9XRFUEuqSHbXs+rKXL5aSlsWzS/Oq9N5eDIwOm30G3E2AbtIG2p+bCYrOxakcDxzekA+HRwZvTMzji4qhqlSxRFCuZ8S/4XXwCwLrgfXd58lpGHH6As5zj3BQZxQirirnJn/tj5hDiFtNh5NVXOrqsmJSUluLq6Nqkx/RUdefsvgiA02nOukmmOXN9Qt+q8txydAR9nFQgChI+G/d8hxG+ATuMuqEspUzKpwyQWnFrAsrhlDAsa1mgbPe6ZSfHSpZjT0yle/Bvud97R5POqQuusZNz9XVnx8SGSj+Vz4O8U+l0XWq9MU3Wdi0qrZdLTL7Fr2S/sWb6YQ2tWkZuSxIQnnkfj2Lg/lNaysaEyglRAHeGGOsINq9GC/nSBzZGLLcKUWY4psxzWQHmgI5pod9RdPJB5qNv9ebU3uctBl6XchCGuCH1sEfq44vP668p9tKii3FBFuaEIcKy3UHR7Oq+mylWUFLNr6SKObVyHKNry2qJHjOHq6beidmzcbsvmzocuv5J1806Qm2Jbqu0xKogBk8Nq7U1any7RYiH37Xco+uUXAH6NGEHIk48y/MxzVOYc52E/P05IRVyULswbPY9Q59DzxmjueTVVzq6rpkxTsTtv7QAnlZxof2eOpZewN6mAST2q8t7GwP7vbPXexjcsQDo1YioLTi1gR8YOssqyGrVxAUCi1eL56KNkv/Ya+d98jcvkSUhdXBp5RufjHerEkJsj+GfhGfb/lYRnoAOh3VtvA0MVgkTCoOm34hkUwt9ff0r6yWMsev5xJj71It5hHVtdf2sgUUjRdPdC090LS7mJyuN5VBzJw5isw5RWSklaKSV/JyP30aDq4oE62gO5j6ZZPxR22i+iyYIhpRRDQjH6uCJMGWU1omuCXIIs2AFNZ0/UUW7IzonwXM6YjUYOrlnFvpVLMFbaNmCE9xvI1TffgdrFDZWqbech8XAemxaexlhpRqmRMeLOzoR282j0OFajkcznnqP077VYEfi26yQ0M27kLt1sDMlbeMTHm8MKKY4KR+aOmku4a3grnI2di43deWsn9A9141h6CXsSz3HeQq4GmQp06ZB3Gpwu3D0gxDmEfj792Je9j9/jf+eh7g812hbnKTdQ8NNPmOLjyZ/zLd7PP9foMWojaqAfeallHN+Szob5p5j2fB9cvNtmR1fEgKtx8fFj1Udvo8vL4ddXn2H4XQ/QbcSYNtHfWki1chwG+KHt70tFfiliQhmVJwswJJRgyq7AlJ1K6aZUpM5KVJ1cUUW4ouzogkR16fzpN9XpvFydVdFsxZBUgjGxBH1CCcY03b8tqc4i99GijHBBFe6KItgJg8XY6CWdSxXRauXMzq1sX7yQ0vw8ALzDwhl620wCOkdXL3G1FRazlR1L4jh2dpnUO9SJMfdG4+jWeOfRUlZO+qOPULF7D2aJlI963Yh+8AgWeW7EtHkBj3t7sl+lQCvXMmfkHKLco1r6dOy0Ey6dX/DLnAFh7szbnsSexHOa1Cs0EHqNrVhv3AbofeGSIWCLvu3L3sfvsb9zX9f7Gm2LIJXi+vhj5D7yKIWLFuF6800ogoIaPU5tDJrWkYKMMjLjilnzzXGmPNcb2uh64hkcyrTX32fzD1+TeHAfG+Z+SVbcGYbf/QByxaVZDf5cJA5yVP19cRjgh7XCROXpQttOwtgiLCUGyvdlU74vGyQCyhAnlBGuCCEaxEAlgrT9XtSb2uLqcmmNZdWbMaaWYkjRYUwuwZBSCuaaZSQkTgpUYc4ow11Rhbsidfq3T6UoitC4xiuXLCnHj7Dt5/nkJtv6kDq4ezD4pjuIGjSkzeq1nYuuoJK1c0+Qn2rrnlLfMumFMOfnk3rffRhOncYgV/J63zsojOzBmt4piH+9ydNeHuzUqFHJVMweMZtunt1a+nTstCPszls7oU+ILe8tKb+c7BK9Le8NbHlvceshbl2DnbcRQSNwVbqSW5nL9oztXOV5VaPt0QwahHbQIMp37iT3k08J+OzTRo9RG1KphDH3RrP03f0U51Swaf4pht3ZdmF9pVbLpKdeYv8fy9n528+c2LyB3KREJj71As5ejVtibs9INHK0vb3R9vbGarRgSCrBEFOEPqYQc4EeQ2IJhsQSAEo1MpShtlpzyg4uyLw09eZB2Wk9RFHEUqg/x1nTYcopr7EMCjZHverzUoY5I/NQXxFRtbrIS0li+68LqjcjKNQa+k2aSq/xE5ErL84yccLhXP5ZeKbZy6QAxtRUUu+5F1NqKpVaJ57rcxfZPqGsGWVG9dejPO/pzmatBoVEwRdDv6C3d+8WPhs77Q2789ZOcFbL6eLnzPGM/+a9ne1zmroX9CXQgDwNhVTB5I6TmX9yPstilzXJeQPwfOZpynftonTtWioO3Y6mV88mjfNfNE4Kxj3Qld8/PETy8QIOr1czcHLbOXCCREL/66fj0yGC1V98QG5yAj8//zjjHn2KsJ5928yOtkKikKLu5Ia6kxvQAXN+JfqYQipjijAklmCtMFN5soDKk7YuHxKNDEWoM8oQZxRBjij8tAjyi18c2JBYQum2dIwZZVhLjbjfFoW6S/0XQ9FsRfdPGhWHc7GUGpE6K3EaFoi278V31EVRxFJiwJRRhjG9DGNGGab00hpN3quQuqlQBjuhCHZE9FOhDXBBchEiSe2N0vw8ti9eyJmdW0EUkUhl9Bg9nv43zEDjdHE6CJhNFnYtT+D4FtsyqWewA2Pv7YpTAzYQ1UblyZOk3Xc/loIC9B7ePNLjTrIdPfn1Omf8183gZVdH1jlokUlkvD/ofQb4DWjJ07HTTrE7b+2IviFuHM8o4UBy0b/Om2sIeHRCyI9BmrQFes5o0FhTIqYw/+R828aF8ixCVfXvNqoNVadOOE+5gZJly8l9/32CF//aYnf3XsFODL21E5t+PM2Rden4hLjQoadXi4zdUIK79eDW9z7jz0/fIzs+lhXvvUG/SVMZOP1WpLLL909D5qHGwcMf7UA/KssrkOSbMSbpMCQWY0zWYa0woz9ZgP6sM4dEQO6jQRHoiCLQEXmAA6Jj2zsOVpMFua8WbR9vCn4+3SCZwl/OYC0z4TolHJm7Gmu5CbEVe+3WhWi2Ys6vxJRVjim7HGNWOcbMMsQy0/kHSwXkfg7Vzpoy2Ll6GbQqX+tKjrKBrTPC/lXLOPT3n1hMtt20EVcNZvCNt+Pi43vR7CrOrWDdvBPkp5UB0HN0EN1H+6LRNi36V757NxmPPIq1ogJTaEfuibyZAqUTb4/yod/OO3lTK/CnoxapIOXDaz5kkNegljwdO+2Yy/cKdQnSN8SVH3YmsT+5sOYb4aMgPwZJ4qYGO2/BTsH09+nP3uy9rEpcxePujzfJJs9Zs9CtXkPl0aOUrl2LUxMK99ZF5ABf8lJKObY5nY0/nsbFS4O7v0OLjd8QnDy8mPH6+2xZ+B1H169m36plpJ0+wXWznsXJs22dyYuBIJWgDHZCFeIMwwJtVfczyjAklmBM0WFMK8VaZqouR1K+N9smKJMg99Yg99Ei96l61iJxkLeaY/Fv9LBh6GOKMCSV4PtsXyRVHQKakCTeGKxGC+b8StsjrxJTXgXm7HJMeZVgqcVplIDcW4vc3wFFgCOKAAfkPloEmT2qVhsmvZ5Df//B/j+WY6iw5ZH5dYpiyK0z8YuIvKi2xe3PYfOiM7aiuw5yRt7ZmaAubk3eHFG+bh15r7wCJjP07M3M0GkUWGXc3seTmxKe5n1JKcucHBEQeOfqdxgRNKJNN2LYubjYnbd2RO8QVwBickopqTThrD57wYkYA7u/Qpr4D4hWEBq2hDW101T2Zu/lr+S/eKT3I8iljW/SLvfywn3mTPK/+orcjz/BYcQIJArFhQUbyMApHchLLyUrroQ13xxj6vN9UDu03PgNQSaXM3LmgwR27sr6b78gK/YMC597lDEPPk5436YtOV+qCFIJyiAnlEG2OnhVS3vGtFKMaWUY03SY0ssQTVZMGWW2shTnINHKkHlokLmrkLmrkXnYnqVuqjbbmFKF/nQBCn8HSremU344F4lCiirKDefRwU1eBhZFEWuZCUuxAXORHkuR7dmYW0ZxgRFLSd0V0wWVtNrJlftosLrJ0Qa7Ir2MeoW2FhazieOb1rN7+a9UlBQD4BkUwqCb7sA3sgtqddOWJFsCs9HC9iVxnNph603q29GZ0TOjcXBVNrn9UeHPP5P3zrsgiihHjmam/3jySswMCHHmNeOnfF6RwCIX27Lwm4PeZHzY+Ga1WrJz6WH/1WhHeDmqCHHXkFxQweHUIoZ2Ohv5CRyAqHBEqMhHzDoK/r0aNN7wwOG4KF3IrcxlZ+ZOhgYObZJd7nffRfFvv2FKT6fo50W4331Xk8apDYlUwrA7wvnr85Pozvb5m/BYjybtxmouna66Gu+wjqz+/H2yE+L446O36Tl2AoNvabnzvdQQBAGZiwqZiwpNV1tdPqvFSkVWCZIiM6bss5GlnArMBZVYy80Yy3UYU3Tnj6WSInVRInVSInVSIHU+++ykQOqoQKKRI9HIEJTSFonemQv1GFJ0CHIpHrd1xlJuonhlPNYKM27TImocK5qtWCpMmIsq0Rv1iGUmLKVGLGVGrKVn/11iwFxkOG+n53+RaGTIPNS2h6fGFpn01SJ1VlafV9Xyp0Rx8XMJ2zNWq4WYndvYuXQRJTm2qK+ztw+Dpt9K5MBrQBAuarSpILOM9d+dpDCz/Gxv0hD6XhuCpIm/X6IokvfpZxTMnQuA04038aT3CJJSigly0/Cj/yrmJuzgB1cXAF7u/zKTO05uobOxcylhd97aGX1C3EguqOBA8jnOm0wBoYMhZg3Eb2qw86aQKpjYYSILTy3k97jfm+y8STQaPB9/jKyXXiZ/zhycr5+MzNW1SWPVhkorZ/wDXVn+4UEyYovZsSSOITd1arHxG4OLtw83vvkB239dyMG/VnB47Z9kxJxi5P2P4RPS+LzByxFBIiB1V6HyV6Hp+q+TZTVaMOdWYC7QYy6oPOe5EmupCVFvwZxdgTm7on4FEpCoZSgCnXC7ORLxrLMkgK3zSLU+K1bD+cn91ZxdpnSZ1AGJSobMXYXjqGCKl8biNCoYQSFBkArkzj2O+T8RxPonAKSOCqSuKqSuSqQuSkQnGWpfJ+ReGqTaxke47dREFEXi9+1m55KfKUhPBUDj7MJVU26i64jRSGXy6uMuln2ndmSyY0kcZpMVtZOCUXd1JjCq4cv6541pMpH16muUrFgBgPNDD/KZ7zXsPZiBo1LG8p5H+OXEr3ztZvvtfabPM8yIbFgajZ3LD7vz1s7oG+LKsoPp5+e9dRhhc94SNsGQZxo83g0db2DhqYVsS99GXkUenpqmdTVwnjyZwoU/YYiJIf+bb/B58cUmjVMXbn5aRt3dhTXfHOPE1gzc/R2Ivsa/RXU0FKlMztDbZhLUpRt/f/0puUkJLHntGYbdcS9dh4+54pPF60KikJ7N2zq/5ZBFb6YiuwSZQcCqM2LRGbHoDGefjVhKjYiVZkSTFaxgLTdjLtKDVax+nHeZNltrNlb/rz1aGVJHBYJUQDTZjpO52mq/WYr1tvZhEuHfSJpwNjroqETqKEfiqEDqcDYq6CBH6qxE5qq0RdBk5/cAVV4hRXBbE1EUSTpygJ2//Uxukq1Wm1Kjpc+EG+g9fhLyNu6KUBuGSjNbF8UQfzAXgKDOboy4szMap6ane1grKkh/4gnKt24DiQSfN95gsXtXlqyPRyLAL9fks/7ox3zqbnPcZvWcxe1dbm+R87FzaWJ33s5BFMVG3clVHd/Yu7/65HoH2f44j6QVYzBZUJy9SIgdhtsiD+n7EfUloGxYb85Q51C6uXfjWMExVsSv4N6u9zbNPokEr2efIW3mPRT98iuuN92EIiSkwefVEF0hXd3pPzGMvasS2b44FlcfDX7hLg23sSnnVQ+hPftw23uf8/dXH5N++gQb5n5F4qH9jLrv0QaVIWgLGy8VXYJCgtRLfUEHRzRZsVaasVaaEE1WW6N0qWCrc1at7uw/ZJJ6c9cUwc7oTxchApKzeWWWUhMIIPNSI1HIQCLgfncX2/KlXILBaGhQJ4Jzz729z/2loivt5HEOrFxCVtwZAOQqNb3GTaT3tZNROThUH3cxbcxN1rH15wRKC/RIJAL9J4XRY2QggkSodbyG6LIUFZP2wAPojx1DUCrx+/QTDvh24cOFBwD4dJCFM8de4r2zjtt9Xe/lnq73tMhctLWcXdf5ck3linbeZs+ezezZs7FYbHflBoOh0fkTBoOhSXfbdcn5OUpxUcsprjRxKDmPHgFnnQSNLwrnEKQlyRhiNmGNaPiuz2sDr+VYwTF+j/2dWzregkS4cD5GbfZJe/VCPWgQlTt3kv3hh3h9/HGDz6uhujoP8SI3tYSkwwWs/fY4E57sWmcbmebqaghyrQPXPfMyB/5cwaE/lpFwYC+ZsWcYdveDhPS4cCHMtrDxstOlABRSBMHmXCHYcu+sBgvmgsrqw6xlRkyFlbYcMxcVJWuTsegMuE23Lbmre3tRtj2d4j8ScBoZjLXChG59Mpo+3kjU/y5tWpRgFs1gaqfzcZnryjhzkv0rl5J55iQAUrmcriPG0nP8JNRnb5Lq+11uCxtFq8iJLZkcWJ2KaAUHNyVDbw/HK9gRg7HuTSoX0mXOzCT74UcwJycjcXLC6/PPSfHvyKzvD2AV4d4uICQ+zf9cbc7rLeE3MTPynjrnoy0/56bK2XXVlGkqgmjfooJOp8PZ2ZmioiKcnRte2LFquaSxPQMvJHffTwfZcCqHF8ZFct81YdUylj+fRH54PmLvu+G6Txqsq6isiOv+uo4yUxlzR81lgG/9RRzrs88QF0fS5OvBaiVo4UI0ffs0+LwaqstktLDyo0PkpZXh7q/lhqd7If9PL86W0tUYudKcLP7+6uPqHJxuI8cy5NaZdS7lXAwbLzddVbKCIGBILCZ/3onz3tf08sJ1WgRFS2MxF+nxvK9btZw5r5KSPxMxpuiQaGSou3rgVMdu00thPi4nXWknj7N72S+kn7Z9phKZjG4jxtJv8jQcXBuWO9YW81FRYmDTgtOknS4CoEMvT4be0gml5sK5jfXp0sfGkn7vfZhzc5H5+hA4bx4VPoFM/noXqYUVDAmQcKP0BZ5Xm7EKAjeGT+GFAa/WaXNbfs5NlbPrqklJSQmurq6UlJTg5NSw1bQqGhV5mzlzJnfffTeDBl2ehQAFQWj0haVKpiXl+oa4suFUDgdSirj/3ATtsGFweD5C4j81ErcvhEauYXzoeJbELmFF3Aqu8rtw+Yu67FNFROAybRrFv/1G7gcfELLktxo9A5syH/+VUShljHuwG0vfO0BBRjkb5p9m3ANdkfynZVNL6GqMnFdIGLe++xk7Fi/g4OpVHNu4ltQTRxn38FN11phqaxsvN11VjhuAqoMrAe8NrvPYqojbuXJyLw2e93RtVRubKncl6qpaHt29/BfST5112qQyug4fRbexE/D0D7zoNp5LyokCNi04RWWpCZlcQr/JIXQfFtSo7ha16Srft4/0hx/BWlqKMjycwO/mIbp78tAPe0ktrCDMRcbNqrd5XmZz3G4IHssLV716wVWTtvycmypn11VTpqk0aj/z/PnzGTNmDBs3bmyyQjsXpk+I7a7zYEpRjTVxa9AgRIkcipKhIKFRY94QfgMAG1M3UqQvapZ9no8+gkSjQX/iBLrVq5s1Vl04uqkY/0BXpDIJycfy2b2icefbWsgUCobefi9TX34LB3cPirOzWPzqs2z56XtMBnuBTDt2akMURVKOH2HJGy+w9H8vkn7qBFKZjO6jr2XmF/MYMfMhHN2btpmqNbCYrOxYFsdfXx2lstSEu7+WqS/0IXKgd7MuuAC6tetIm3kP1tJS1H16E/zzT8i8vHjtj5PsSSxEq5Dwgv8cXpAVYhYExvsO4tVr3mtQuoudK4cmfRsmTpzI+vXr63z/5MmT3HLLLU026kon2s8ZpUxCYbmRxPzyf99QaCGov+3fCf80aszO7p2JcovCZDXxV+JfzbJP5uGB+333AZD7yadYW6nOkk+YM8PvsEW0jmxI5dTOzFbR0xSCu/bgjg++ImrwMETRysG/VrDw2Uerowl27Ng5W/LjwF5+efkplr31MumnbU5bjzHXMvOL7xg580GcPNqP0wZQnFPBsg8OcHRjGgBdhwUw9fk+uPlqmz124c+LyHjiCUSTCcdRIwn67jukzs4s2JXMr/tSEQR4J2o5L5hjMQkCI9278/bIr5BK7PUA7dSk0c7bDz/8gI+PD5MnT+bvv/+u9ZiysjIWL17cbOOuVBQyCT0CXQA4UFvJELDVe2skU8KnALA8dnmzdrkAuN15BzIfH8xZWRQuWNisseojoq8Pfa8NAWDrohgyYpoXNWxJVA4OjH/kKSY/+yoObu4UZ2fx2xvPs+mHbzBWXqCWmR07lzFWq4UzO7ey8NlHWfXh/8iOj0UmV9BjzHXM/OI7Rtz9II7uHhfbzBqIosjpXZn89s5+8tPKbPUnH+rGNTMikDWxI8e5Y+d+8ik5b70FoojLTTfi/9lnSFQqtsXm8eZfpwB4petW3tbvxiCRMFgbyvtjf0AmuaL3Fdqpg0Y7byEhIWzbtg0/Pz9uuOEGVrfSstmVTp+zrbL2J//HWekw3PacvB3MxkaNOT5sPCqpioSSBI7mHW2WfRKVCq8nHgegYO5czAUFzRqvPvpeF0rHPl5YrSJ/zz1OcU77cow69O7HnR9/TdcRYwA4sm41C555hJRjhy+yZXbstC0Ws4nT2/7hxycfYvUXH5KfmoxcpabvpKnc89X3jLj7gXbntAHoy02sm3eSfxaewWyw4N/JlRkv9yO0W/NtFU0msl58qbprgufjj+Hz6qsIUikJeWU8/MshrCLcHXGYeYbVVEokXKX05p2xC5vU0tDOlUGTlk0DAgLYunUrgYGBTJkyhT///LOl7briqcp7Oy/y5tMVtJ5gLIO0vY0a01HhyOiQ0QAsj1vebBudJkxA1aUL1vJy8r76qtnj1YUgCIy4PQqvECcM5WZWf30Mfbmp1fQ1BaVGy+j7HmXqS2/h5OmNLi+X5e+8yqZ5X1X3YrRj53LFUFHBgT9/5/tZ97L5h28ozs5E5eDIwGm3cN/s+Vxz851oXVwvtpm1khlXxG9v7SPhUC4SicCAyWFMfKwHDmcLOjcHa3k5uU88iW7lSpBK8X3rf3g88ACCIFBcYeSeBQco1ZsZFRDDOuFXyiQSeksd+eyGVSilzddv5/KlyRmQ/v7+bN26lZCQEKZNm8aqVata0q4rnl5BrggCJBdUkFd6Ti0YQfJv9C2h8UunUyOmArAueR1lxka0BKoFQSLB67lnASheshRDQuttKpAppIx/sCsOrkqKcypYP+8kVkv9PSYvBsHdenDHR1/Rc+wEAGJ2bmX+kw9wdMMarNa6uwHYqZum1kJqTg0lOw2jrKiQ7b/8yLyH72Lrzz9QVliAxtmFa265i3u/+p6rpt5UXWC3vWGxWNmzMoEVnxymrMiAs6eaG57tTe+xIeftbG8K5oICUu+6m8qdOxFUKgK++hKXqbbfX5PFysO/HCIpv5wo91RitD+gk0joJiqYPeUv1HJNs/Xbubxp1vYVX19ftm7dSlhYGNOnT+f3339vKbuueJzVcjp529oMHUxpuby3Hp49CHMOo9JcyZqkNc01E22/fjiMGAEWC7kfftTs8erV5azk2oe7IVNKSY8pYvfypGbn7rUGCpWa4Xfdz43/+xCPoBAM5eVs/O5rfn3lGXIS4y+2eZccTf2M2+N343KhMDOd9d9+wXeP3M2+VcswVJTj5hfAqPse5baPvqbPhBtQqNuvA6LLq2TFR4c4uDYFRIga6Mv0l/riHdK4Wlt1YUxNJfnmm9EfP47E2Zmg+fNxHDas+v3//XWKnfEFuGuy0Ht8Q5FEIMoi8M31K9Cqm94f1c6VQ7P3Hnt7e7NlyxbCw8O56aabWLZsWbON+vrrrwkNDUWlUtG7d2+2b99e7/GLFi2ie/fuaDQafH19ueuuuyhoxRystqLv2aXT8/Pezv4IZB+DstxGjSkIQnXZkN/jWsbZ9nr6KZDJKN+6lcq9jVvKbSweAY6MvrszCBCzO5cjG1JbVV9z8AuPZOpr7zHszvtQqDVkx8ey6MUn2fTDHPTlzYt62rHT1lSV+1jx/hvMf+IBjv+zHovZjF+nzkx65hVb3ufw0Ujl7TdPSxRFzuzOYuXHx8hNLkWpkTHm3miG3x6FQtUyGwMqj58g+aabMaWkIvf3x/fH+ah7dK9+/6c9KSzcnYJckY9L4FfkS0Q6mq3MvfZnnJyDWsQGO5c/jXLePDxqT9708vJiy5YtREREcPPNNzdrp+lvv/3G448/zksvvcThw4cZPHgw48aNIzW19ov0jh07uP3225k5cyYnT55k6dKl7N+/n3vuuafJNrQXqjYtnJf35uBly30DSNjc6HEndpiITCLjZMFJzhSeaa6ZKENDcb3xRgAKP/kU0dK6y4Oh3T0ZNKUjALtXJBJ3IKdV9TUHiVRKz7ETuOvTOUQOGoIoWjmy7i/bxW/zevtSqp12j9lo5Pjm9Sx89lGWvfUyiYf2gyDQoU9/bnzjA2568wM69ulfo1h3e0RfZmLdvBNnNyVY8Qt3YcbL/ejY26vFdJRt30HKHXdgKShAGRVF8C+/ID+nB/Su+Hxe/+MkgqyYoNAvyZVYCDGZmTf0S1y8u7WYHXYufxr115abm0ufPn1qfc/Dw4MtW7bQuXNnvvjiiyYb9MknnzBz5kzuueceoqKi+OyzzwgMDOSbb76p9fg9e/YQEhLCrFmzCA0N5eqrr+b+++/nwIEDTbahvVC1aeFEpo4Ko7nmm1VLp03Ie3NVuTIiyCa/PLb5GxcAPB5+CImjI6bYWEpWrmyRMeuj+4hAOg/2AWDTj6fJii9udZ3NwcHVjWtnPcPUl9/C1S+AipJi1s/5gp9feILUE83b+WvHTmtQXlzEvhVL+O7Rmayf84Vt56hSRY8x13H3p3OY/Mwr+Ed2vthmNoi0U4Us/t9eEg7lIZEI9L42iImP96izb3JTKF65krQHH0SsqEA78CqCf1qIzOvfGnbJ+eU8uOgQVkFHSIcvyZUYCDCZ+a7vS3hU5THbsdNAGh0nrq8tiLu7O//88w8jR47k6NHGX5CMRiMHDx7k+eefr/H66NGj2bVrV60yAwcO5KWXXmLNmjWMGzeO3Nxcli1bxrXXXlunHoPBUCOZWafTAbaQemPyZKqOb2xuTUPl/JxV+DmryCzRczi1mF7+2n9lOgxH2PkZYsI/YLXYNjI0Qtf1Ha9nXfI6Viet5qk+T9XY2dSU85K6uOD+wAPkffgheZ99jtPYsUi0Fy5q2Zw57DspmIoSE8nHClj9zTGmPNMbF++682xa+/NqiFxQdHdue/8Ljqz7i72//0ZeciJL//cSHXr3Z/Atd+Lq699mNrblfLSHubfrurCMKIpkxZ7hyPrVxO7ZidViu2l0dPegx9gJdB02unoDQm3jtbfP2WyysGdlIsf+SQfAxVvDyLuicPSSIwiNy4usS5coihR+9x15n3wKgNN11+L79tsICkX18SWVRu5ZeACdsZiAsK/Il5TjazbzXfjteHW7pdYx2/N36lKw8VLR1VRavPqfm5sbO3bsYPfu3Y2Wzc/Px2Kx4O3tXeN1b29vsrOza5UZOHAgixYtYsaMGej1esxmMxMnTuTLL7+sU8+7777LG2+8cd7rBoMBfSO7BRgMhia1S2moXM9AZzJL9OxJyKOLh+xfGa8eqOQahPI89KkHEb3r7t9Ym67uLt3x0fiQXZHN2oS1jAka0+zz0kydgvSXRVgyMsmZOxfXBx9skFxT59BkMnLNLR0oK9aTn1rOn18d4brHuqJ2qDvnprU/r4bKRY8cR4f+gziwciknNq8n4eBeko4coMvw0XQdMwGhCVXnm2JjW85He5l7u67zMRkMxO3ZwYlNa8lPTa5+3TO0Iz3HTSCsd38kUluh2gv9RraXz7kgo5ytP8dRnF0JQOQgb/pNDEamkKLX61tEl2ixUPjhh5T+tgQApztux3XWLAxWK5ydp4pKPU+siCE+Pxfv0G8olpXgaTYzx30Ibn0fq3M+2/t3qqlydl01ZZpKq5Ru1mg0jBgxosny/52Ac5tT/5dTp04xa9YsXn31VcaMGUNWVhbPPPMMDzzwAN9//32tMi+88AJPPvlk9f91Oh2BgYEolUpUqoaH0as8baVS2ehm2w2V6x/mweoTORxJ16G8JuQcGRWEDobYdSjTdkJw30brmtRxEt8e+5bVKauZFDGp+eelVOL6+OPkP/MsuoU/4XHTTch9fOqXaeYcqlQqrnu4B79/cBBdvp5/fohl0uM9kCnOr4jeFp9XY+RUKhWj7n2Y3uMnsvXnH0g6fIDjG/4mZuc2+lx3Pb3GTWjwjr2m2NiW89He5t6uy0ZRVibHNv7NiS0bMJTbWvFJ5QoiB11D91HjcfYLQKVStcvzqkvOahU5uimNvX8kYjWLqB3lDL89iuBo9xbVZdXryXz+Bco2bgRBwOu553C74/bzZN5bF8f2xCzcgudSocjHzWJhnqoToRO+gjraXrX379SlYOOloKvdOW9NxcPDA6lUel6ULTc397xoXBXvvvsugwYN4plnngGgW7duaLVaBg8ezFtvvYWvr+95MkqlEqXy/AKIgiA02nOukmktub6htry3w6nFWM46sdUyHUZC7DqEhE0w+IlG67o+/Hq+PfYte7L2kFmeib+Df7PPSztiBOW9e1F58BD5n32O3/vvXVCmuXOodVZy3aPdWf7BQXKSdGz68TRj7o1GqKVWU2t/Xk2Rcw8I4obnXyfl2BG2/PQd+anJ7FryM4f//oO+k6bSY/R45MoL31Q0xca2nI/2OPdXoi6z0Ujc/t0c37iWtFPHq49x9vKm+6jxRA8bhdrRCVEUqyNU7fW8/iuny69k04LTZMYVAxDSzYNht0aicVK0qC5LcTHpDz1M5eHDCHI5fh9+gNPYsecdv+RAGgv2JuAY9B0mVTbOFgtzza50uHURSOu//Lb379SlYGN719VYu86lXW0PUigU9O7dmw0bNtR4fcOGDQwcOLBWmYqKivPy8KRnw/vNWU9uL0R4O+KoklFutBCbU17zzY5no5upe8DQ+NIT/g7+9Pe1NbpfFd8yRZaFs3egACWrVlF5vG0atbv6aBn/YFckMoGEw3nsXBZ/yX3+wd16cOt7nzHy/lm4+PhRWapj288/8P2sezm89k/MpvbVVcLOpUVBeiqbF8zj2wfvYM0XH9ocN0EgtEdvrn/uNe7+fC59J05B7dgytc7aElG09SVd/NY+MuOKkSmlDL2lE+Mf7Hqe49ZcjBkZpNx8C5WHDyNxciLw++9qddz2Jxfy8qrDaAN+BE0aDlYr35ZJ6XTT76BofpN7O1c27SryBvDkk09y22230adPH6666irmzp1LamoqDzzwAGBb8szIyGDhQlsz9AkTJnDvvffyzTffVC+bPv744/Tr1w8/P7+LeSotglQi0DvYlS0xeRxKLaZX6Dm5UG5h4BIMxSmQvAM6nf8DciFu6HgDe7P2sjJ+Jfd3ux9pHWH8xqDu2hWniRPQ/fEnue+/T9BPC5t1h9FQ/MJdGXFHFBu+P8XRf9LQuCjoNTq41fW2JBKJlIirBhN9zXBOb9/M7uWL0eXl8M/8b9n/x+/0v34aXYaMRKZo2QuSncsTQ0UFsXt2cGzTOrLjY6pfd3D3IHroKLoOG4WTZ8uVyrgYVJaa2PxjHElH8wHw7eDMiDujcPZs+SLBhjNnyH10Fpb8fGQ+PgTNm4syPPy849IKK7j/p73IfH5C4pCI2mrlm4IKuty+BhxrX0WyY6cxtDvnbcaMGRQUFPDmm2+SlZVFdHQ0a9asITjYdhHOysqqUfPtzjvvpLS0lK+++oqnnnoKFxcXhg8fzvvvv3+xTqHF6XPWeTuYVkKN6nWCYIu+HfjBVjKkCc7b8KDhOCocySrPYm/2Xgb61R7hbCxeTzxB6br1VBw4QOnGjTiNGtUi416IiL4+lBcb2bU8nt2/J6BxUhA54Pyl8/aORColetgoogYP5cTmDez5/TdKC/LY+N3X7Fr6C73GTaT76PGotO2z9ZCdi4fVaiH1+FFObt1E/P49mI22vBpBIiGsVz+6jRhDSI9eSFrgRu1ik3Q0n80/n0FfZkIiFeg3IZSeo4NbpL3VfynfuYvsWbMQKypQRkQQOG8u8lrSecoNZu5ZuJcKlwXIHWNQWa18lVtIj2mLwSuqxe2yc2XS7pw3gIceeoiHHnqo1vd+/PHH81579NFHefTRR1vZqotHVb23Q6nF52/e6HDWeWtCqywAlUzFtaHXsjhmMSviVrSY8yb39cXtrjspmPMtuR99hOOQIQhtFC3qOSqIihIDRzam8c/CM6gdFNXJypcaUpmc7qPG02XISI5tWsuBv1ZQmp/HjsUL2btyKd1GjqX3tZNwcL00z89Oy1GQnsbJbZs4vX0zZYX/dphx9fMnYuAQug8fjaN77YXWLzUMlWZ2LI3jzK4sANz8tIy8qzOegY6toq9k1SoyX3oZzGY0/fsT8NWXSB3P12W1ijy2+BApku+RO51ELop8nptP39EfQ9iQVrHNzpVJqzhvw4cPx8/PjxdffJHOnS+NIo7tmR6BLsilArmlRtKLKglyPydfInSwrcZbYQIUp4FLYKPHvz78ehbHLGZT6iZKDCU4KVom58X9nnspXrYcU0oqRb/+itsdd7TIuA1h4A0dqSg1Ers3h7VzjzPpiZ4t1rfwYiBTKGzRtlHjidm9nf2rlpGflsLBv1Zw+O8/ibp6CNEjx+Ef3ulim2qnDSnJzSFm93Zidm0nNzmh+nWV1oFOg4bQZchwvMPCMRgMjdpJ355JO13IPwtPU1ZkAAGih/oy8Ppw5IqWv5yJokjBt3PJ++wzALRjx+L//ntIa9nwBvDx+jPsKP4auctRZKLIJzn59O35EPS4pcVts3Nl0yrO25YtWwBYvHgxN910Ez/99FNrqLliUMmlRPk6cSy9hCNpxTWdN5Uz+PWCjAOQtBV63tro8Tu7dybSLZIzhWf4K/Evbo68uUXsljpo8XxsFtmvvEre19/gPGkSUheXFhn7QggSgeG3R6EvNZF6qpDVXx3j+qd7ona5tJeKpDIZnQcPI+rqoSQdOcD+VctJP32Ck1s3cXLrJvw7dab7mGsJ7zcQWTvuMWmn6ZQXF3Hq8H5idm8nK/bf9nYSqZSQHr3pMmQEYb36VX/+l9rGnbowGSzs+j2eE1szAHDyUDHijihcA1TI5C3/dy2azWT/7y2Kf/sNALeZM3F86EEkdawgrDyczndnPkHhehCJKPJ+bj5Dwiegv/qZ9rnEZeeSplW+U1arlfLycrZu3VrtyNlpHj0DXaqdt4k9/Gu+GTbU5rwlNs15A5jccTLv7XuPlfErW8x5A3C54QaKfvoZQ2wsebO/xuelF1ts7AshlUoYc180qz49TG5KKX9+eZRrH+2CyufSj0AIgkBYz76E9exLZuwZDvy1gvj9u8mIOUVGzCnUTs50HT6a7iPHXfIJ6XZAl59H/P49xO3bRfrpE1DlkAkCgZ27EjnwGjr2uwqNk/PFNbSVyIwvZtOC0+jybAV3o4f4c9X1HZArpY0urN4QrBUVZDz1NGWbN4Mg4P3SS7jecnOdug6nFvHC1ndQuO5BEEXezitgtGdvxAlfgvnycJ7ttC9a7YZAq9Uyfvx4xo8f31oqrih6BLqwYHcKh1OLz38zbAhs/8gWeRNF20aGRnJd2HV8fOBjzhSe4VTBKcK0Yc03GhCkUryff47Uu2dS9OuvuN50E8qw0BYZuyEoVDKue6Q7yz88SEluJevnnub6p3qjdrh8dmv6RUQy4YnnKcjKJHbXVo5vXEtZUSH7Vi5l36plhPXsQ/TQUYT26muPxl1CFKSnEb9/N3H7dpOTGFfjPd/wSCIHXUPEgKtxcHW7SBa2Pmajhb1/JnFkYyqI4OCqZPjtUQRG2c65NaKK5oIC0h58CP2xYwhKJX4ffYjTqFF16sou0XP3qjeRuW4H4PX8Qq5TB8CNP4NMCeaWdy7t2GmS81ZZWUnHjh2ZM2cOEyZMaGmb7NRCzyAXAE5m6TCYLShl5ywTBPQDmQrKciAvBrwiGz2+s9KZEUEjWJu8lpXxK3my+5MXFmog2oEDcRg6lLItW8j94AMC53zTYmM3BLWjgomzerD8w4MUZVWy+utjTJzVA4Xq8lrM0Lq6cdWUmxhw/QwSDu7lyPo1pB4/QuKh/SQe2o9Sq6XTgMFEDR6Kf6fOTXLy7bQeFrOZrNgzJB45QML+PRRmpv/7piDgFxFFx74DCOreC6/A4DYpv3MxyU4sYdOC0xTnVAAQOdCXq6eFo1S33t+tMSWF1Hvvw5SaitTZmYBvvkHTq2edx+tNFqb99iZmp40AvJhfyA1WNdy8BNSu/0ZI7dhpYZr0V6BWq6msrETbgMbjdlqGIDcNrho5RRUmTmeV0iPQ5d835SoIGgCJW2yPJjhvYNu4sDZ5LauTVvNQl4dQ0XLLi17PPkvZjh2UbdlC2c6dOAwa1GJjNwQnDzXXPdKdlZ8cIidRx99zjnPtw91aJVfmYiORSgnvN5DwfgMpzMzgxOb1nN6xhbLCAo5tWsuxTWtx8vQm6uohhPa9Cr+wjhfb5HppqpNyKTg3ZUWFpBw9RNLhA6QcP4Kh4t9C3BKpjKCu3QnvexUd+vRH6+Ja3fXgcsZstLD3j0SObEoDETTOCobdEklIt9bdKVt59ChpDzyIpagIeUAAgXPn1rtKIIoiM357j2LlnwA8XVDETZVmuPM3cGu71QU7VyZNvoUZMWIEGzduZPjw4S1pj506EASBbv5ObI0r4HBqUU3nDWx5b4lbbEunAx5oko4BvgPw1fqSVZ7F1sytNfqdNhdlWChut9xM4YKF5L73PtoVvyPI2jby5RHgwOj7o1j3zWnSzxSxbt5Jxt4fjVTarhqNtChufv5cc8tdXH3T7aSfOsGp7ZuJ27sTXV4Oe1csYe+KJbj5BdCh7wA69umPb8dOCJL2NR+1tbJrTbnWxKTXk3HmJKknj5F09BD5KUk13lc5OhHavRehvfoS1rMPSs2VdYOclVDM5p9iqqNtnQb4cPW0cFTa1l3uL924kYynn0HU61F16ULgt3OQedTvLD74xxckWhYD8EhRMXfoymD6Qgjo06q22rEDzXDeXnzxRaZMmYJKpeKGG27A19f3vDtdN7dLKxejqrlsY49vbN5FU+REUax23o6kFiMO/I9s6BAEQEzeARYTSGSN1iUgMKnDJOYcm8MfiX8wMXxiY07rgrrcH3yQ4pWrMMTFUbR0Ka433tjmc+gZ5MC4B6NZPfs4ycfy2TT/FCPu6lxvUc+2trE1dAmChMAu3Qjs0o3hd91P4sH9nNr+DynHDlOYmU7hqmXsX7UMjbMLYb360qHPAIK6dkeuON8BasvzqpIVBKFJc9IYudaYe7PRSFZcDKknj5J28hjZ8XFYLeZ/DxAEvMM6EtqjN6E9+uDdoWON4rn/HbM9fadaUpfRYGbvyiRObssGEbTOCobc0omQrh7V47aWjUWLFpHz9jsgimivuQb/Tz5GotXWO/dvbp3PzuLvALi3uIT7i3WIo/4HURNqLJVeCnN/udp4qehqKoLYROlz+4nWtTxhsViaZlUbMXv2bGbPno3FYiE2Npbs7GycnBpXC0yv1zepflJT5LaczubBJacIdFWxftZ/iulaLai+6IxgKEF/2xpEv15N0pVZnsn1q69HRGTF+BU1mtU3hAvp0i1eTOH7HyBxccH/j1VIHR3bdA6rZNJOFrHxhxhEq0jEAC8GTQ+rd5ntYtjYFrp0RYXkxJwm6fB+Uo8dwlhZWf2eVCbHJ7wT/lHR+EdF4xXaAenZaGlLnZcgCDUiZOmnT3Dgz9/JSUqgvKiQiU+9SIc+A+r8bNJOHmfp/87fwXznx1/j6hdQQ85gMFzwx7K5c19RXER2QizZ8bHkJMSSm5iAxVyzJ62DuwcBnbvi1bETYT37NHqHaHv/TjVWJiu+hJ1LEtHl2ZaDw/t50m9SCEpNw2ILTbVRqVBQ9Pnn6BbaSlk5TLkB9+efr3dFQK/XsyhmDXPOvI8giNxaUs6zhQVYet6JadS7teaRtue5vxhydl3/otPp8PHxoaSkpNG+R5Mjb6+++uolkVNSHw8//DAPP/wwOp0OZ2dnlEploya/ytNWKpWNmoumyImiSM+znRbSivSUmwXcHf4TFQkdDGf+Qpm+C8IGNklXmCqM/j792ZO9h/Xp63mwx4Mtel7KW26hbOkyjImJlP/4I55PP92mc1glE97bFwEpG74/SeyeXNRaBQOndKx1rLb+nNtSl6OLK55DhtN16AgsZhPpp04Qf2AvCQf2UlaYT8bpE2ScPgGAXKnCP6oLgV264RHagYDwSOQNXJpsqH0mvR7P4FC6DB3Jn5+826CxAe76ZA4Kzb+9LNW1/BBeaBm1sXNorKwgLzWZnMQEMmJOkZMQiy4v97zjtC6u1VHPwC7dcPaytVSq+rG/3L5TDZUxVprZvSKBk9szAdA4yRnayNy2ptpo1espfOllSteuBcDzicdxu/feescQRZEVcWv59qzjdn2pgWcLCyB8NNLrPkIqOf9y2l7n/kqw8VLQZTAYGnzsf2my8/b66683WWl7RRCERjukVTJtIeesVtDRy4H43DKOppcwIuo/ffXChsKZvxCStsKQZ5qsa1LHSezJ3sOqxFU80OMBJELDc6AupEtQKPB+/jnS7rufwp9+xmX6dARv7zabw3Nlwvt4YzZa+GfhGY5uSkehktFvQu0lUtryc75YumRyBSHdexHSvRcj7n6Awsx00k4cO7vkdxx9WSnJRw6SfOQgYNsY4R4YjE+H8LOPCNwDgqqjc02xL6xXX8J69T1P7tznmu/ZnjUuLjX6vJ4bYWvu3IuiSGlBPvlpyeQmJZKXnEhuSiLF2Vm1DYBHYDB+4ZH4RkTiFxGJq6//eTZULele7t+pukg+ns/WX2JsXRKAzlf70mt8AE6uDq1uo6W4mJyHHsJw+AjI5fi9/RbOEy+cIrI+eRPvHnodBJFRpSKv5+cg+HSFqfNBWndOXnub+4stZ9dVU6aptEjGeGxsLAUFBXh4eBAeHt4SQ9qpgx6BzsTnlnEkrbh25w0gbR+YKkGubpKO4UHD0cq1ZJZlciD7AP18+zXP6P/gcM01aK++mvIdO8j96GM8PvygRcdvDFED/TAZLGz/LY79q5ORyCT0GRdy0expLwiCgLt/IO7+gfQYcy2i1UpeajJpJ4+RevIYWXExVOpKyEu2OTPHN60DQCZX4OofgJtf1cMfN/9AXHx8W9Xen557DIvJiHtAIP2vv5HALl0bJS+KIvqyMnLTUyjPz6MoK5OizHQKszIoysrAXMcdsoO7B55BIXiEhBHUuSu+HTuhPCcCaKcmlWVGdiyJI3ZfDmDrkjDs1kj8O7m2yS5aY3o6affdjzExEYmDAwFffYl2wIALyu1I38Ez254BwUr/Mhkf5icicfSzlQRROlxQ3o6dlqZZztvSpUt5+umnSU//tx5RQEAAH3/8MVOnTm22cXbOp2egK8sOZtRerNe9Izj6QWkmpO6BDsOapEMtUzM6cDQrElewMn5liztvAN7PPUvi7t2UbdyIdv9+VIMHt7iOhtJtWCAmg4U9KxPZuyoRwO7A/QdBIsErJAyvkDB6jZ9EZWUlpvJSchLjyU6IIychluyEeNtS4lmH7r84uLnj5OmFg5sHjm7uOLi54x4YRHB0D5sOQYBG3rlqXd0Ydd8jeId2xGI2cWrbZpa+9RLTX32HgKhowNbxBSAvJZmywjwqdCWU5udTWpBHaUE+pfm2Z5OhbudBkEhw8wvAKyQMz5AwvILD8AwJRePkbHP8mrAEeiUhiiLxB3LZviSWylITggDdRwTSb2IYcoW0WYnbDaXy+HFbKZCCAqTe3gTNnYuqU8QF5fZl7eORfx5DxEznMjVz8mKQKhzhlqXg5NfqdtuxUxtNdt7WrFnDjTfeSJcuXXjkkUfw8/MjIyODn3/+mRtvvJE///yTcePGtaStdqC6RMjRtGKsVrHmLklBsHVbOPqrrWRIE503gOtCr2NF4go2pGzgxf4v4qBo2btLZXg4rjOmU/TLrxR9/AkuAwe2eemQc+k9NgRRhL2rzjpwIvQZH3LR7GnvCIKAk4cXzp7eRPS31ewTrVaKc7MpzEijMCPdtos1M4PCjDT0ZaWUFRZQVlhQYxyPwGBufPMDLCYT1qoNTuc4cMbKSvRlpedq5lz/SOPkTHi/QYAt52Tg9FsozsmylUDx9UcURSRSKVK5nLWzPyY/LaXe81I7OePmF4Crrz9ufv64no0eOnv51LkcbKd+dPmVbP01ltSTts/ezU/L8Nui8A5tXIJ2cyjdtImMp55G1OtRRkXi+dnnKIMCLyh3OPcwD258GItoJLDMmZ/zjiMVpDD9R/CJbn3D7dipgyb/Gr399tuMHj2a1atX19h5+swzzzBu3Djeeustu/PWCkR4O6CWSyk1mEnIKyPc27HmAaFnnbfELc3SE+0WTahzKEklSaxLXseUiCnNGq82PB59lJI//8IYE0PJ7ytwnT6txXU0hj7jQhAEbBG4P85G4OwOXIMRJBJcffxw9fGjQ+/+Nd6rKCkmJzUZY1kpZYWFlBbmU1ZYgFQmQxAkwDke2Tlb7q0WCxZTzd2aF8IrJIy4fbtqRnMEAQd3D6RyBWonJxzdPc4+PKufHdzcsIjYI2gthNVi5djmdPb+kYjZaEUiE+gzLoReY4KRytqulmDhTz+T887ZUiCDB+P36SeYpBcuzn087zj3b3gAo1WPW7kHK/IPIQfEaz+GjiNb33A7duqhyc7bkSNHWLx4cQ3HDWx35A899BA339xyzc3t/ItMKqFrgDP7kgo5nFZ8vvMWNsT2nHkEKotA5dIkPYJgq/n22aHPWBm/slWcN5mrKx4PPUTu+++T9/nnOI0bi9TR8cKCrUjvsSHAuQ6cSG/7EmqzUTs549OxU52OkUKt/rdO0jnOm0KlRqk9N+orVj+JnHX5BAEEW51CBCjKysTBzR21kzOCRFKdRDzlhTfqtVEURSyXefeCtiIvtZQti2LIS7VFTf3CXRh6Sydcfdqu6LBotZL7/gcULlgAgMv06fi8+gpIpZgu8DmfKTzDfRvup9JcgabCmz/zjqAUwdT/YWS972wD6+3YqZ8m3/5IpVKMRmOt75lMpvOcOjstR1Wf01rz3pz8wCMCECF5R7P0XBd2HRJBwpG8IySXJDdrrLpwvfkmZCEhWAoKyP+6bXue1kXvsSEMmGzbdbr3jyQOrEm+uAZdIQiCgNloID8thYL0VABKC/MpzEynQleMXKlkz/LFbJw3G7lKhUKl4timdSQfO0RZQT7FOVnsXvoL8ft303PsBCRSaZN2mtlpOiaDhX2rkln23gHyUktRamQMuzWSyU/0bFPHzarXk/HY49WOm+eTT+LzxusNSs2IL4rn3vX3UWYqRVbhw6rcUziJJsTOkzEPeam1Tbdjp0E0OfLWt29fPvjgA8aPH49a/e+uRoPBwEcffUT//7N33vFNlV0c/94kTbr3HrSl7L33lOFWENkgIEOhogIOtoALFBGViggiDkBEkaEoQ0Q2yt6jFOjee6Vpct8/Qiu8lNKkaZOU+/2QD2lzz3N+96ZJTp7nOee0b1+OtURlaHlr39upmMyyDwjtDqlXIOpvaPCE0X687b3p7N+Z/XH72XJtC6+0esXose6FoFTi/to0kl+aTPp33+E6cGC5/QSri9tn4P7Zdp3i4mI6PGXZPUBrAknXrvLjgv+K7v793VcANOr2EI+GTyUvM4PstJTSx7XFGvZ9t5rc9DQUSiUeQbXoP/0tQltILYqqm+unU9i34Qq56frM3DptvOkysC4OLtXbpqw4PZ3YiZMoOH0awcYGv/ffx+WJxytkeyPrBuN2jiNTnYFQ4Mv6pBv4kgeB7aDfctBKXwQkLAOjg7f58+fTq1cvateuzcCBA/H19SUhIYFNmzaRlpbGnj17TKlT4jZa1nID4HJiNnnqYhxU//c01u4O/66s9L43gH51+rE/bj9br23lpRYvIZeZvpG7fefOOHTvTt7ff5O8aBFBK74wuQ9juD2AO/F7DKJWoGP/MGkmpwoJatyMaRt+Lf35/7MQH5k05Y6f2z39LO2evjuzvTqyFyX0ZKcVsH/DVW6cSQXA0U1Ft6H1CG3mVe1a1FHXiXnhBTQxMchcXAha9hn2bdve3xCIzYll3M5xpBWmoSv0YXliGg1IBrcQGLpeX3pJKy2rS1gGRgdvXbp0YefOnUyfPp2IiAh9VpdMRvv27Vm/fj2dOnW6/yASRuHjbIufiy0JWYWcjcuiQ22POw8I6QKCDNKuQnY8KI3vMdsjqAcuKheS85M5nHCYLgFdKqm+bHzefJOogwfJ/ftvcvftw7FbtyrxYyitHwlBJhc49PM1Tu6MpqigmG5D65fbC1VC4kFAq9Vx+s8Y/v31uj4hQSbQvE8QTXr64uRSfUukJeT98w+xk19Gl5WFTVAQQStWVHgWPzEvkXE7x5GUn4RO7c3cBB3duKbfMzz8J3DwvKNnqYSEuanUxrTu3btz+PBhcnJyiImJITs7m4MHD9LNQj54azLl7nuzcwO/Fvr71/+ulB+lXMljoY8BsDlyc6XGKtdPaAjuI0cCkPT+QkQDMwyrkha9a9F5UG0Q4Pz+eHavPo9WqzO3LAkJs5EQmcmP7/7L4U3XKC7S4VfHhUGz29KxXxg2KtPPzt+PrK1biR47Dl1WFnbNmxOy4YcKB24p+SmM3TGWuNw40HjyfJwngzmOKLOBIWvBUyo8L2F5GD3ztm/fPlq1aoWjoyP29vbY31ZVPDc3lxMnTlhdECfeluVmyPGGLtEYY/f/Ns0DXdl+NpFTMRlljxPaHSH+BET9jVivX6V8PR32NOsvrWdP9B4yCzNxUZXdSLuy5+Ux8UWytmyh6Pp10r9fi/voURXWaMx5GWJXr4M39k62/LnmIlePJVNUqOXh8Y1RKO/9QVXdGmuirxJbQRCM0mmInTVcD3P7ys8u4vAv17h8JBEAW0cbOj0TRv0OvqXXurrOC/QFmDO+/JKs5fqtFk4P98Vv4UJktrb3HOt2X2kFaYzbOY7onGjkWg96xDRkmrBWf+DTyxCDO5fOuJn72luSL2vQaC2+jMXo4K1nz54cPnyYdu3urr5/+fJlevbsibak6KaFEhERQURERKlOtVptcIsWtVpt1B4oY+xut2nsqw+WT9zMoKCg4K6xZIEdUfExRP2NurCwUr5C7UOp41KHyKxItl7ZysC6967HVqnzsrHBNTyctLffJiUiAlXfPsjd773kW9lraKhdUBMXeo2tz56vr3DzXBpbPz1J73ENUNre+2VU3Rqt0Zetra3B/o2hIq9tS7geluhLpxW5eCCRE3/EoCnUv1/W6+BNmydqYetgc0eD7eo6L1GjIe2dd8jdug0A59GjcJs8mSKA+zzXarWa7KJsJu6dSFRWFErRjTo3O7FY0Ge8azq/RnG9p+8ap6Y/z9VhJ/m608ZYjA7eyosYraVUSHh4OOHh4WRnZ+Pi4oJKpTLog6Qk0lapVIa96Rhh9/82rUK8kMsEUnKLyFCDv+v/6Q7riihXIeQmYJsXg8q1qdG+APrX7c+Hxz5ke/R2RjYdWWXnpRo8iNyff0Z94QI5K1bgO7/s2lym8FVRbrer29IPB0c7tn9+hsRrOexYfoknJjfDzlFpMRprmi+1Wm0Su/u9tq3lelS3r7SbBez/8Srp8XkAeNVyotuQuviE3j0DX13npc3KIu6VV8k/ehTkcnxmz8ZtyOAK+8opyuGVfa8QmRWJncwVp6uP8pXwCQp0iM2HoOg1C8X/6ajpz3NN02gNvqoteMvOziYzM7P058TERKKjo+84pqCggG+++QZfX1+jRZkLY2pCldhUh93tNvYqBQ39nDgXl82pmCwC3P6vGbbSHoLawY39yKMPIAQ2M9oXwBNhT/Dx8Y85n3aeyMxI6rqVvQ+ksuclKBT4zprJzeEjyNz4E25Dh2LbsGGV+DKE2+0C6rnRb2ortn56ipToHH5ZfJInXmqOi5dduXbVqbEm+brdtqrtrOF6VJevvEw1+zdeJeqEvq2VykFBx35hNOzsX27CTlWfV1FMDDEvvKhvLm9vj+eiRbj17lVhf3maPF7d/yoX0i/goHCh+PIzfCd8iqNQACFdEZ78DO4x+VATn+earNHSfRnznlaCQdNjH3/8MaGhoYSGhiIIAv379y/9ueTWqFEjVqxYwahR996vJGEaWgbpS4acisko+4DaPQCQ36xcsV4Ad1t3ugXq9zBWZeICgH3r1jg/9hiIIonvvlupfQFVhVctJ555rRWObioyk/L5+YNjJF7PMrcsCYlKU6zRcvyPG6ybd1QfuAnQuFsAI+Z3pHHXALNmWuefOMmNQYMpiopC4etLrbXfY9+lc4XtC4oLmLxnMmfTzuKgcEIdNZyvWYO/kA4edWHwd6C4exZdQsLSMGjmrW/fvjg6OiKKIm+88QaTJ0+mVq1adxyjUqlo2rQp3bt3N6lQibtpEeTKd0dulp1xChCqD7ZkMUdA1IFQuSywfnX6sSdmD79G/cqrrV/FRmZTqfHKw/u1aeTs2UPBseNkb9+Oy+MVK7JZnbj5OvDsm234NeI0qTG5bFlykj7PN6Z2y+qvbyUhUVlEUSTqZAqHNkWSnarf6+UV7Ej3oQ3wCam+JvL3Inv7duKnz0AsKsK2USMCly9H4e1V4X3Kaq2aV/a8wrGkY9grHCD+eT4oWktT+Q1Ee0+E4Rv1mfoSElaAQcFbx44d6dixIwB5eXmMHz8ef3//KhEmcX9KyoWcjctCo9VhI/+/iVT/log29ggF6Ygpl8CncaX8dQnsgrutO+mF6RyMO0iPoB6VGq88bPz98ZgwntRPPyN50Qc49eiBzKH6a0fdDwdXFf2ntWLnqvPcPJfG71+epcuzdWneK8jc0iQkKkxqbA4HfrxK3JVMABxclHToH0atpi7Y2d+9HaA6EUWRtBVfkrJ0KQCODz1EwOIPkdnbV3hWXqPVMHXvVA4nHMZOYYdb9kQGZW2nj+KEfm/w0PXgbv7OLhISFcXorIKZM2fi4lJ2yYi8vDw0FlSnq6YS6umAi50N6mIdlxJy7j5AbgNBt9qUVbLPKYCNzIbHa+tnwLZEbqn0ePfDY+xYbIKCKE5OJvULy+i6UBZKWwWPTWxK424BIMKBjVfZv+EKOp3lLfdKSNxOQU4Re9de4sd3/yXuSiZyGxltHgth2PwO1G/vi2DmYtRiUREJs2aXBm7uo0YR+NmnyOztyze8DY1Ow+v7Xmdf7D5s5bY0lU+lfexxnlf8AYDwzAr9/mAJCSvC6OBt/PjxjBs3rszHJkyYwMSJE40WJVExBEGgxa0+pyfvte8t+NZ+kJsHTeLz6bCnAdgbu5fMwkyTjHkvZCoVPjNnAJC25hvUUder1F9lkMlldB9aj479wwA481csO748h0Zt2eVyJB5Miov0+9q+n3OY8/vjEUUIa+XNsLfa0/6p2uWWv6kutJmZRI8bT9amTSCT4TN3Dj4zpiPIK779Q6vTMmv/LP6M/hOlTMmj3jPgzBXmKr7VH9B7HjTuXzUnICFRhRgdvP3111889dRTZT725JNP8ueffxotSqLilARvp+617y3kVvB246BJ2rvUd69PA/cGFOuK2X59e6XHux9OPXvi2L07aDQkWWjyQgmCINDq4WD6jmuMXCHj+ulUfvvsHNmpBeaWJiEBgKgTuXwkgbVvHeHI5iiKCrV4BjnSf1pLHpnQBGdP8y6RllB04wY3Bg8h/59/kDk4EPTFctyHDTNoDJ2oY+6hufx+43cUMgXP13uLk3vj+cxmGXJBRGw1Cjq/WjUnICFRxRgdvCUlJeHn51fmY76+viQmJhotSqLilLbJisks+wD/VogKO4T8VEi5bBKfJbNvW69tNcl498Nn5gwEGxvyDh4k1wq+FNRt48PTr7bAztGG9Lh8Ni48RsyFdHPLknjAib2Uzo/v/8vuNRfJzVDj6Kai9+iGDJrRFv+6lrNRP++ff7gxeAhFN2+i8PcjeN06g3sdi6LIgsML2HptK3JBzmst3mbz7zmssvkQe0GNNqQbPLYYKlGqQULCnBgdvLm6uhIZGVnmY5GRkTg5ORktSqLiNA90BeB6ah7ZhWXsM1So0AW01t83QckQgMdqP4ZCUOhrvmWU/TdgSpTBwbiPfR6ApPfeR2dgFwxz4FfHlWdntMEzyAF1XjHbPjvFiZ03LXrmUKJmkhaXy84vL7L1E31WtNJWTod+tRk+vwP1O/iZfV/b7WT+8gvRY8ehzcrCtnkzQjdswLZ+PYPGEEWRhf8s5OerPyMTZMxp/w7rd8j4VPc+PkImOq+GFPVbpd8TLCFhpRgdvPXs2ZP333+f9PQ7ZxTS09NZuHAhDz30UKXFSdwfNwclAa76pY7zcdllHqML6qS/Y4KkBdDXfOsa2BWovtk3zwkTUPj5oYmPJ23lqmrxWVmc3G15bHITGnT0RRTh8KZr7Fx1XtoHJ1EtZKcWsPvrC2x4919iL2Yikwk07RnIiLc70vqRkHL78lY3ok5HxqefkThzFmg0OD36CMHffIPCy7CyO6IosuT4EtZdWgfAWx3n8+sBD17LWkhDWQxaB2+E4T+CyvylTyQkKoPRwdu8efNISUmhbt26TJo0iXfffZeJEydSr149UlJSmH+PtkYSpqdpgD7r91xc2UVidbX05V1Mte8N/ls63Ra1jWJdsUnGLA+ZvT0+b74JQNrKlRTFxFS5T1OgsJHRc2QDug+th0wmEHk8mZ8/OEZWSr65pUnUUPKy1Oxbf5m1bx3h8tFEECGkuTtD5raj2+B62DlZVhFaXX4+8VOmkvX11wB4THyRgI8+QmZEz9tlp5ax5vwaAOZ2nMulK/Xodf1DeshPo5PbIh+2AVykMj4S1o/RwVv9+vXZv38/LVq0YOXKlcyZM4dVq1bRokUL9u/fT/369U2pU6IcmgTov0WevVfw5tcSUa6CvGRIM80yZ7fAbriqXEktSOVw/GGTjHk/nB7ui33HDohFRSQvWlQtPk2BIAg06R7I01NbYuesJC0uj43vHyPqVIq5pUnUINT5Go5svsb3cw5z9u84dFqRoEbuPDu9DQ+Nro+rT8XLa1QXmqQkbo4YSc7OnWBjg9/ChXi/8gqCEb2xV5xewZdnvgRgervpyHI6oju0jBGKPxERkD37FQS0MvUpSEiYhUrlgzdv3pw///yTgoICMjIycHd3N6ixu6VR0lzW0OMN3cdkjF15Nk38b828xWfd9bgoivrALbAt3DyAeH0/eNSptD6FTMFjoY+x7tI6tkRuoUtAF5OfV1n4zJzJ9f7PkPvnHuwPHEDVq1eV+TK1nV+YCwNntGHHl+dIup7N71+cpXFXfzo9WwebW0tYlvI3Zc2+rEGjKX0VFRZz9q9YTu2OQZ2vnwX3CXGmQ7/aBNR3QxRFCgsLLe68Cs+fJ3ZSOMXJycjd3PBc/CHOHTsa5W/NuTUsO7UMgKmtp9LQ/lFWr/2MTxX65VP6voPY4HG4TZ+lXQ9r8mUNGq3Fl7GYpJiPnZ0ddnaWkWJuCBEREURERKDV6vcgqdXqCrdaKUGtVhvVXNYYu3vZ1PVUAXA9JY+0rFwcVIq77GwC22Nz8wDaqH1omgw1ib5Hgh5h3aV1/BXzF8nZyTgrnU16XmUSGIjz0KFkf/cdaYs+wLZtW2QqVdX4qgI7hS08MqkhJ7bHcPaveM7vjyfuSgY9nquLu79DtWusqb6MtbMmX5pCLRcOJHLur/jSoM3Vx47Wj9eiVhM3BEEofT+ztPPK27Wb1LlzEQsLsQkLw/uTpWg9PFCr1QZrXHdxHZ+c+wSAF5q8QE+v/rz15Tq+kC9DJohoWo6muMXzcNt7u6VdD2v0Zayd5OtOG2OpVPB29epVVqxYwcWLFykouLOWlSAIFl/rLTw8nPDwcLKzs3FxcUGlUhk0c1gSaatUKoOeNGPsyrPxt7XF38WW+KxCItOLaB/qeJedPKwHHPwIeewR5CpVuSnyFdXX3Lc5dVzrEJkZyd6EvQysN9Ck53UvfF55mbw//kAbG0ved9/j9VJ4lfmqKruug+oT0tSLP9dcJDOpgG0fn6PjM2E06e5vEX9T1uzLGjRWxldRQTHn/0rk1J8xqPNKgjZ72jwWQp023nc1jrek8xJFkbQvVpD66acAOHTtiv+Sj5A5OFBYWGiwxo2XN5YGbhOaTmBskxeZ/PkWFhe/j51QRHFYbxRPLEYh+++jzpKuh7X6sgaN1uDLLMHbuXPn6NChAwEBAURGRtKsWTNSU1OJi4sjKCiIsLAwo0WZC0EQDI6cS2yqw648myYBLsRnFXIuLosOtT3utgtsA3IlQk4CZFwHj/Kfn4roEwSBfnX6sfjYYrZGbWVQ/UEmP6+yUDg64jNjOvFTp5H+5Ze4PvkEypCQKvFVlXa1GnkwZE47/vz2IjfPpnHgx6vEXEin0+BQ7OzM/zdlzb6sQaOhNkUFxZz9O5aTu6LvCtrqtvW5K2irrD5j7e5lo1OrSZg1m+xffwXAfdRzeL/+OoJCgSiKBvvaErmFt4++DcCoRqMIbxHOzPUHeCN9Dl6ybIo8G6MctKbMkiCWcD2s3Zc1aLR0X4bqup1K9TZ9+OGHOX/+PKIo8tVXXxETE8O2bdsoLCzknXfeMVqUhOE0uU/GKTZ2ENBGf99EJUMAHq/9OHJBzpmUM1zPqr72VU6PPIJtp46IGg2JCxZUau+AObFzUvL4pGZ0HVwXuULGzXNpbP7gNNdOSskMEnoKcoo4suUa38w8xJHNUajzinHxtqP3mEYMnduO+u19yw3cLIHilBSinxulD9wUCnznzcNnxgwEhXHzB9ujtjP30FwABtUZxNTWU1m59wqPX5pBPVkcRXY+KEduBJVUb1SiZmJ08HbixAlGjRqF7FZWkE6nA+Dxxx/ntddeY8aMGaZRKFEhSsuFxJdd6w2AkC76/03U5xTA086TzgH6FlzVVfMN9N9YPKZPR1AqyTt0mOztVd+qq6oQBIFmPYN4dnob3PzsKcjRsOPLc/z+xVnyMo2fVpewbnLSC9m34QrfzjzE8d9vUlRQjKuvPV2H1fkvaJMb/RZebRReuMD1gYMoOH0amYsLtVatxG3IYKPH23VzFzMPzEQn6hhYbyDTWk7jr0vJuPw1na7yc2jkdiif2wguASY8CwkJy8LoV35JdqlMJsPGxoaMjP8ao7dp04YTJ06YRKBExSiZebuWkkue+h5110r7nB4wWb03gKfC9D1uf436Fa2u+grQ2gQF4fHCCwAkLVyINrucwNUK8Ax0ZOCMNjTvE4BMJhB1KoV1849yfn8cos46ZxYlDCc9IY8/11zg+9mHOftXLMUaHd7BTjzyQhOGzmlH3bZeVhG0AWTv2MmN4SMoTkxEGRpK6IYfcOjQwejx/or+izf+fgOtqOXpsKeZ1X4WUan5nNqwgCHyv9Ahw2bQGvBrbrqTkJCwQIx+BwgICCA1NRWAOnXqsG/fvtLHzpw5g6Oj471MJaoALycVvs62iCJcSLhHEBPYDmQ2kB0HGTdM5rtHUA+clc4k5SdxLPmYycatCO7jxqIMCUGbkkrK0k+q1XdVoLCR0/qxWjw7ow3ewU4UFRSzd+1ltiw9SWaSVNi3piKKIjEX0tn22WnWzz/KpSOJ6HQiAfXdeOqVFjw7vQ1hLb0tqpVVeYiiSEpEBHGvvIJYUIBDly6EbPihwntTy+JA3AGm/T2NYrGYx0IfY36n+WQXFLPh+y+YJqwFQPfw+1D/EROdhYSE5WJ08NalSxcOHToEwPDhw1m4cCHjxo1j0qRJzJgxgyeffNJkIiUqRmmx3th77HtT2kNpn1PTLZ2q5CoeDX0UgF9v/GqycSuCTKnEd95bAGSsX0/B2XPV6r+q8Ax0ZMCbbej8bB0UShlxVzL54e1/OLb9BsUaqb1WTaFYo+XCwXg2vPMPWz89RfT5NBAgtLknz77Zhn5TWhLU0L1SG5urG11BAfFTp5H6mb7umvuoUQR9sRy5s/EtqY4kHOGVPa+g0WnoE9yHd7u8iygKLF2zjlnqpQAUtBqPouOLpjgFCQmLx+hs01mzZhEfHw/Am2++SWJiImvXrkUQBAYNGsTixYtNJlKiYjQJcGH3xWTOxd8jeAP90mnMEf3SacsRJvP9dNjTbLi8gb1xe8ktysWpGjcKO3TogPOTT5K9bRuJb71FyMYfEeSW07fRWGQygRa9a1G7hRd7110m5kI6R7dGceFAPB3616ZuGx+r+lCX+I/87CJO74nh0qEkCnI0AChUchp28qNZz0BcvS2vG0JF0CQlkThxEkUXL+o7Jsx7C9cBAyo15rHEY0z+czJFuiJ6BPVgUbdFKGQKPv1pN5OT52IraMip1RunJ6yn64qERGUxOngLCwsrLQcil8v59NNP+fRW7R4J83C/HqeAPmlh/0f6PqcmpIlnE0JdQrmedZ1dN3fxTL1nTDr+/fB58w1y9+6l8MIFMtatx32k6QJTc+PsaceTk5tz9d8kDv9yjZz0QnZ9dYEze2Lp/Gxd/MJczC1RogKIokj81UzO7Ysj6mQKOq1+H6Ojm4qmPQNp3MUflf3dZS2shfyTJ4md/DLa1FTkbm4ELvsM+9atKzXmqeRThP8ZTqG2kC4BXfio+0fYyGz45fB5Hj3zMp6ybDJdGuAyfA3IrP8Lm4RERbGOXa8SFaIkeItMziW/6B5JC0HtQaaArGjIuGky34Ig8GRt/VL51qjqyzotQeHpife0qQCkLF2KJim52jVUJYIgUK+dL8Pmd6D9U7VRqOQkXc9m04fH2bHyHNmpBfcfRMIsqPM1nN4Tw/r5R9m85CSRx5LRaUW8gh3p83wjRrzTkVZ9g606cMv8eRPRz41Cm5qKTd26BG/8sdKB27nUc0zcPZH84nza+7Xn4x4fo5QrOX49CZ/fJ1BXFkeO0hvV8B9AKe2xlniwMCh4e+ONN4iNjb3jdyUlQiTMj7ezLd5OKnQiXLxX0oLSAfxb6u+bcN8bwBO1n0BA4HjScWJzYu9vYGJcBw3CtlkzdHl5JL3/frX7rw5slHLaPBbCiAUdaNTZD0GAyOPJrJt/lCO/XCc3w7D2bhJVgyiKJEZlsefbi6x58yAHfrxKRmI+CpWcxl39GTizDU++2pS6bX2QW0nmaFmIxcUkvvceCbNmIWo0OPXti9+ar1EGVK5Mx6X0S0zYNYFcTS6tfVrz2UOfYauwJT4jn5hvJ9JJdo5CwQ77UT+Bk6+JzkZCwnow6F3jo48+Kt3nBqDVarGxsZHKglgQJSVD7pm0AP/VezPx0qmvgy9tfdoCsO3aNpOOXREEmQy/+fNALifnjz/IsfD2bJXBwUVFz5ENGTSrHYEN3NAVi1zYl8j3c47w1/eXyEqRMlPNQU56Icd+v8G6eUf5+YPjXDyUQLFGh7u/A92G1GPMws70GN4AryDrLx6rzcwkZsIEMr79DgDPl17C/+MlyOwrt1/vasZVxu8cT05RDs29mhPRKwI7hR2FGi27Vk6nn/gnWmTw7NfI/JuZ4lQkJKwOg/a8lVXF3lor25dFSX8yQ4839BoYY1dRmyb+zuy5pE9auN3mDrvgzggHPka8sb/Mem+VOa/Hgh/jn6R/2HptKy80e+G+G+pNfQ1VDRrgPmYM6atWkTh/AXZt2yJ3cqoSX1VhZ6iNR4ADT77cnNhL6fz723USr+Vw4UA8Fw/GU6etD60fCcbdz8Fk+oy1q4nXvoSiwmIi/00m6kQ6sZcz4Ja5QikjrKU3jbr64VvbpfS1cM/XZRVprApf6qtXiX3pJTTRMQj2dvi/vxCnvn0q7SsqM4pxO8eRqc6kiUcTPu/1OfYKe3Q6Heu+/oTn878BILv727g2esRirseD5ssaNFqLL2OpVGN6ayciIoKIiAi0Wn3pBbVaTWGhYctOarXaqIw/Y+wqYlPf2w6AMzGZpedyl51XC2wFOULmTQqTryE6373EYex5dfTsiL3CntjcWI7GHqWFV4v72pj6GjqOfZ7snTspjo4mYdEiPGfPrjJfVWFnjI1XqAMPjatDVnwRp3fHEXsxk6v/JHH1nySCm7nTuJsfPrWd7hrX1OdV3lgajaa0I4sh3G5nyJtdVV77Yo2OuEuZXD+VRvT5dIrV/20f8a3jTN22XoQ088DGVl46rin0GWtnSl/5f+0lZfZsxPx8FP7+eC/9GJu6de/9flNBItMieeXQK6QXplPPtR5Luy7FRmdDYWEh237/leFx74EAsXVH4tFhbKX8Weu1tyRfxtpJvu60MZYHOngLDw8nPDyc7OxsXFxcUKlU2NraVti+JNJWqVQGPWnG2FXUplWIFwDXUvNBboNKIbvbztYW/FtA3HFUCf+C951N6itzXq6iK72De7P12lb+iPmDDkHlV1Ovkmtoa4v/228TPWoUuT9vwv2pp7Fv17Zany9j7Srrq1ZDF4IbeZN8M4cTf9wk6lQKN8+kc/NMOq6+9jTu4k/9Dr7YOthU+/VQqVQVPraydlVx7Ys1WqLPp3PtRAo3zqaiKfyv3p6Th4oGHf2o394XZ0+7KtFXVedVUTtRpyP1889Ji/gcAPt27fBf+jEKN7dK+4rJjmHK4SmkFqZS17UuK/uuxM1WP+7Bf4/x0OmpqAQNMV7dCRyytDSz1JzX40H2ZQ0arcFXtQZvly9fRnGrmXDJjNWlS5fKPLZVq1ZGCzMHgiAYHDmX2FSHXUVsfF1s8XRUkppbxMXEHFoGuZZtF9wZ4o4jxByBFkNNel5Phz3N1mtb2XlzJzPaz8BWUX5AXBXX0KF9O1wHDyZzwwYS5s6h9pYtCLdeWDXheb6fnU+IM4++2JT0+DxO74nhyr9JZCbmc/CnSI5sjiKstReNOvvjFqiqlvO6fcbM0DdSY+xKjq/stS/M1XDzfBo3z6XdFbA5uqkIa+VNWCsvXHyV2NnbVfvzXF2+dHl5xL/xJrl79gDgNnIkPm+8jmBzd4asob4SchMYv3s8yQXJhLqEsrLvStzt3AGIionF77dReArZxNvVI2jcOpDf+bFlrtfYg+7LGjRaui9Ddd2OwcHb6NGj7/rdyJEj7/hZFEUEQSgN7iSqD0EQaBLgwt7LKZyPy6JlkGvZB9bqAIc+heijJtfQ2qc1/g7+xOfF81fMX6XdF6ob79emkfvXX2huRpMaEYHX1Klm0WFO3P0d6DmiAZ0H1OHKv0mc3x9HakwuV44mceVoEi7edtRt40NYKy88Ahwr9WZSExBFkdSYHG6eS+fmuTSSrmdx+0ptScBWp7U3PiHOCDIBURQN3m5hTRRdv0HsSy9RFBWFoFTiO28ers/0N8nYSXlJjN05lvjceIIcg1jZZyUedh4AZOXkk/H1UFoLcaTJPPEc/wuopJIgEhJgYPD29ddfV5UOCRPS9Fbwdra8Yr1B7fX/p1yE/HSwdzeZf5kg48mwJ1lxZgVbrm0xW/Amd3LCd95bxE4KJ2311zg9/AiE1TaLFnOjtFPQpFsAjbv6k3wzh/P747j6bxJZyQUc236DY9tv4OxlR1hLL2q39MIn2LlSfTTjr2Zwcmc0ydE55GcV8cgLTajdwqtCtgmRmfyy5CTu/g4MntXWaA0VQRRFctIKibuSSfzVDKIvpJGfpbnjGI8AR4KbeBDa3LM0YHtQyN+/n9SZs9Dl5qLw8SFw2WfYNW1qkrFTC1IZt3McMTkxBDoG8nmPz/G29waguFjLyS/G0EN3hnxskY/YgNI90CR+JSRqAgYFb6NGjaoqHRImpLRcSNw9ar0BOHiCR11Iuwqx/0K9h02qoSR4Oxx/mOT85NI35erG6aGHcHr0EXJ+/4OEObPx/eYb/Z6/B5SSJVWfEGf9bNyxBGLOZxJ9IZ3slAJO7ozm5M5oHN1UhDT1xL+eK/51XXFwMWzfmUatwyPQkQad/PhjRcX7zaoLitm95gKBDdzIzy4y9PTuiyiKZKUUEH81k7grGcRfySQ34859JwqljMAG7oQ09aBWYw+c3B+8vxdRFEldsYLUTz4FUcSudWsCP1mKwtPTJOOnFaQxbsc4bmTfwM/Bj1V9V+Gu+O8L5N9fz6JX3h9oRYHUR7+gVu02JvErIVFTeKATFmoqJZ0WribloC6viXmt9vrgLfqwyYO3YOdgWni14FTKKX6L+o0xTcaYdHxD8J01i7xDh1FfvETWd99jN2mi2bRYEko7BXXaetGkaxAatX4zftTJZG6cTSM3Q825fXGc2xcHgKuPPf51XW/dXFDcZ09+cBMPgpt4GKxp79pL1GvniyBA1OlUY06rlJJALTUml5ToHFKis0mJzqUw786ZNZlMwDvECb+6rniHOBDc2Asb5YP71qjNzSV++nRyd+vrJLoOGYLvzBkISqVJxs8szGT8rvFcy7qGt703X/X9Cn9H/9Kl58PbvqJX3HIALrWYReMOplmilZCoSTy471A1GD8XW9wdlKTn6ZMWGnjdY+agVkc4+X2V7HsDeKrOU5xKOcXWa1sZ3Xi02fZTKTw98ZkxnYTpM8hcsQL3Rx9FVTvULFosFaWtgjqt9Xu5ijVaYi9mEHMxnfjITFJjc8lMyiczKZ8LB/RFuu2cbfAIcMTD3xF3fwe8g50qvWfu4qF4slMK6DOmEce236iwnVarIye1kMzkfLKSC8hMzicjMY+UmByK8u/+8iKTC/iEOuNf15WAum74hrlgo5KX7l1T2Dy4PTLV164R+9Jkiq5fR7CxwX36dLyGDTXZazdLncWEXRO4mnEVTztPvur7FUHOQaWJKZeP7aHlsTdBgBN+g2nV/3WT+JWQqGlIwVsNpCRpYd+VFM7HZ907eCsp4xF3HIrVoDCulMO9eDjkYRYeXUhkZiQX0y/SyKORScc3BJennyb719/IO3CAhJkzCV77PYL8wf2QLg+FjZyQZp6ENNMvkRXmaUi4lkX81Uzir2SQEpNLQbaG2OwMYi9mAPrEiAGvt0arFQF9wpIgEygp6ybqRHRaUb9fTBThVixQEhRkJuVz+Jdr9J/WSp8EcEuLKIKo0yGKAqBDEATO/hVLalwu+dlFZKcUkJ1WiKgru/6bTCHg4e+IV7ATXkFOeAc74e7v8EAHaPcie8dOEmbMQJefj8LXl4BPliLUq2ey8XOKcnhx14tcTL+Iu607X/X9ihCXkNLH02Kv4v3baGwFDaftO9Bi7Ocm8y0hUdOQgrcaStMAZ/ZdSeFsXDYDmvuUfZBHGNh7Qn4qJJyGoHYm1eCsdOahWg/xx40/2Hptq1mDN0EQ8J0/j6in+1Fw6hRpX63Gc8J4s+mxJmwdbAht5knorWCuqEBDws0MclM1ZMTnkxafWxo8iTrx1v07g6miQi2FuZr/HxoAnSjyx8pzNO8dhNJWQX5WEZpCLTqtSMFt+94EmYDCRsbFwwmkx+fdMYZCKcPFyx5XbztcvO1x8bbD2VuJb4ibFKjdB1GrJWXpUtJWrgLAvn17ApZ8hNzd3WRZtHmaPCbunsi5tHO4qlxZ2XcltV3/Sx4qzElHt34Y7mQTKQslbOIGZArp40lC4l5Ir44aSsm+t3PlZZwKgr5kyKVf9fveTBy8gT5x4Y8bf7A9ajvTWk/DRn53XajqwsbfH4/XXyf1rbdI+ewzHLt3w7Z+fbPpsVZsbBV4BztRq77tHctpoigit5HpAzhRRNSB7lZQJwhC6Wzb/8V1aAq1pMXmkh6fy9EtUbfG0h/3zcyD9B3bGP96bsjlAjK5QP32+kbkdk5KnD1scfG2x8FVeZeWwsJC5ArrbfpeHRRnZBA/bRp5hw4D4P7883hPnYKgUFSqdc/t5GvymbR7EqdTTuOsdGZl35XUc/tvRk8sLiL6i2epr4shCXfsRv2Mo5OrSXxLSNRUjH5nO378uCl13MHnn39OaGgotra2tG7dmv3799/z2NGjR99RHK/k1rhx4yrTZw2UZJxeScqhqFh37wNr3Vo6raJ9b538O+Fp50mGOoMDcQeqxIchODz5BI69HgKNhvg33kRXZPqMxgcVQRCQK2QolHJsVAqUdgpsHfTButJOjr2zUn9zuXVzVmLnrMTF05ZBs9owcGZbBs5sy6CZbWnc1R9XH3sGzWxLrcYe2DnaoLK3QaGU0+rhYFo9HEzDTn4E1HfD0c2wquYSegrOnuX6gAHkHTqMYG9PwMdL9IV3TTjjVVBcwOQ9kzmRfAInGye+7PslDdwb/HeAKHL5q/HUzz9Bnqgi4bGvCQgOu/eAEhISQCWCt7Zt29KxY0fWrl2LRlP2cogxbNiwgVdffZVZs2Zx8uRJunbtyqOPPkp0dHSZx3/yySckJCSU3mJiYnB3d2fgwIEm02SNBLja4Wpvg0YrcjU5994Hlux7izlSZpP6yqKQKXg89HEAtl7bavLxDUW/fDofubs76suXSV0WYW5JNZKiwmJSYnJIickBICetkNSYHHLSCxEEgSObo/jzm4vIZAJyGzleQc54BTrhFeiEZ6AT9k5K5DYyPAIcsVFJy56mRBRFMn74gZvDhlMcn4BNcC1CfliP86Omrceo1qp5Zc8r/JP4Dw42DnzR5wsae9z5pfra5ndpkLAZrShwoOn7NG/b3aQaJCRqKkYHb2vWrEGn0zFy5EiCgoKYM2cOsbGxlRa0ZMkSxo4dy7hx42jYsCFLly4lKCiI5cuXl3m8i4sLvr6+pbdjx46RkZHBmDHmK01hCQiCULp0ej4h594H+jUHhS3kp0FaZJVoearOUwDsjd1LZmFmlfgwBIWHB77z5wGQtmoV+SdOmldQDSTlZg4/vvsvP777LwAHf4rkx/eO8c+26wDkZ6nJSa+5XQksFV1BAQnTp5M4bz6iRoNTn96E/vQTtiZMTAAo0hbxyl+vcDjhMHYKO5b3Xk4zr2Z3HJN0ZANhpz8E4Ff/yXR97O42fRISEmVj9Pz4c889x3PPPce///7LZ599xuLFi1m0aBFPPvkkkydPpkePHgaPWVRUxPHjx5k+ffodv+/bty+HDh2q0BhfffUVvXv3Jjg4+J7HqNXqOxrCZmfri9mWNJetKCXHG7o3xBg7Y2ya+Duz/2oq5+Jz7m0nt4GAVgg3DyHePAQedUx+XnVd69LAvQGX0i/x+/XfGdJgSKXOy1i7222cevfG+emnyd6yhfjp0wn9ZRMye3uT+TKFRmv25V/PlUnLe95lJwj6dlIPjWpY+ruyaPtEKG2fCL3LzpQaTWFjTb7U168T/8qrqK9eBbkcr6lTcB8z5p7X1lhfRdoiZh2axcG4g9jKbYnoFUELrxZ3jJMXdRTXP14CYLvdk/QdMxexWFNjr31N82UNGq3Fl7FUenND27Zt+fbbb1myZAlffvklK1asoFevXjRs2JDJkyczatQobCtY0T41NRWtVouPz53ZkT4+PiQmJt7XPiEhgd9//51169aVe9z777/P/Pnz7/q9Wq02OLtKrVYbtd/GGDtDbep56YORSwnZdwSr/4/Cvy02Nw+hvXEITaNBRusrz+6xWo9xKf0SmyM30y+kX4VsjPVVURuXaVPJO3IETXQ0CYsW4TFjhkl9mUKjtfgSBAGVyrSlZsrzXZE3vQfl2leErB07yHrnXcS8PGQeHngvXIhtm9blvi8Y46tYV8yMgzPYn7gflVzFR10+oolLkzveV3UZ0RSvHYIjRRwUWtFk9FLQFtfYa19TfRlrJ/m608ZYTLYzValUYm9vj1KpRBRF8vPzmThxIu+88w4bN26kQ4cOFR7r/y9AyTfv+7FmzRpcXV3p169fucfNmDGDqbc1Kc/OziYoKAiVSlXhQLNElyiKqFSGbZg2xs4Ym6ZB+nYzkan52NgokcvvsUoe2hkOf4I87l/ktrZVcl5P1n2ST09/yoX0C8QXxpeWCTDrNbS1xf+9d4kZO46cHzfi2vdhHDp3Mokvk2msIb5MSUWCREu/HtXlS9RoSF7yMZlr1gBg17o1AUuWoPC+f59ZQ30V64qZvX82+xP3YyOz4ZOen9DJ//9eT4VZpH43BC9dBpfEWjiP/JYgb48aee1rsi9r0GgNvioTvFU6j/7MmTO88MILBAQE8Oabb9K+fXuOHj1KVFQUp06dIiAggBdeeKFCY3l6eiKXy++aZUtOTr5rNu7/EUWR1atXM3LkSJT3aeOiUqlwdna+4waUmbVqzbcQTwdUChkFGh0xGQX3PvZWiRAh/RpCXmqVaPG096RLQBcAtkZtNfu1Kbk5du6M2/DhACTMmoUuO9vsmmrireT1ZejrzFg76SZQnJhI9HOjyLgVuLmPGU3wmq+x8fE2uS+dqGPWwVnsvLkThUzBxz0+pnNA5zuP02lJ+XoYXgVRJImu3Hz4a5qGBZn9Okk36WbOm7EYHbxt2LCBbt260bJlS7Zs2cLUqVO5efMm33//PW3btgWgWbNmvPfee1y4cKFCYyqVSlq3bs2uXbvu+P2uXbvo1OnuGZHb+fvvv4mMjGTs2LHGnVANRCGXUdfbEYDLSeUkLdi5gfetAroxVVMyBP5LXPj12q9odeX0XK1mvF+bhjIkhOKkJBJmz67UPgQJCUsgd98+rvd/hoJTp5A5OeH10WK833gDwcb0dRa1Oi1zDs7h9+u/oxAULOq0iG6B3e48SBRJ++kVvJMPki+q2N50KQ93kprNS0gYi9HB29ChQ8nLy2P16tVER0czf/58fH197zouJCSEESNGVHjcqVOnsmrVKlavXs3FixeZMmUK0dHRvPjii4B+yfO55567y+6rr76iffv2NGnSxNhTqpE08HMC4FJ5GacAQe31/0cfrjIt3QO746x0JrkgmaMJVRckGorMzg7/xYvBxoacXbvJuM+eSQnjMHaJoDJLCw8aYnExyUs+JmbCC2gzM7Ft3JiQn3/C4aGHqsSfTtQx7/A8tkVtQy7I+bD7h3T173rXcbl7P8Hj4vfoRIFV3jN47pl+VaJHQuJBwejgbcGCBezdu5dRo0bdtUyZm5vLvn37AKhduzZff/11hccdPHgwS5cuZcGCBbRo0YJ9+/axffv20uzRhISEu2q+ZWVl8fPPP0uzbmVQ3+dW8FbezBvom9RDlc68KeVKHg3V15Lacm1LlfkxBrsmjfF5/TUAkhcuorCCs8USFcfYGU1pJrRiaJKSiR49hrQvvwTAbdgwgtevQxkUVCX+dKKOBYcXsDlyM3JBzqJui+hVq9fdus7/iv3f8wD4QjWGUc+/hFwmFVWWkKgMRgdvb731FhcvXizzscuXL9OzZ88yH6sIkyZN4saNG6jVao4fP063bv9Nwa9Zs4a9e/fecbyLiwv5+fmMHy/1qvx/Gvjp9/NdSsgu/8Bat2be4k+BpqDK9Dwd9jQAe6L3kFtUTvFgM+A2ciSODz2EqNEQN2Uq2ty8+xtJSFgAuQcPcr1/f/KPHUPm4EDAx0vwnTsH2X32/xqLKIq8d/Q9fr76MzJBxntd3uPhkIfvPjD+JOLPY5EhskHsQ9+xC3CxM1+LPAmJmoLRwVt534Y1Gg0ymdRT0BIomXm7mZ5PQVE5+8xcg8HJD3QaiD9RZXqaeDYh1CWUQm0hO2/urDI/xiAIAv7vvYvCz4+imzdJnD9fmvWRsGhEjYbkj5YQM3Yc2vR0VA0aEPrzTybvlnCHT1Fk4T8L2XB5AwIC73R+h8dqP3b3gVlx5H8zEKWukH26pngPXkqdW+9HEhISlcOgCCs7O5vo6OjSZcvExMTSn0tuly9f5ptvvilz/5tE9ePlpMLDwQZR1Pc5vSeCcNu+tyNVpkcQBJ4K0ycubIm0rKVTALmrKwEfLQa5nOxt28ja9Iu5JUlIlElRbBw3R4wkbeVKAFyHDiHkh/UoQ0KqzKcoinx47EPWXVqHgMCCzgt4MuzJuw9U55C3ZgD26hQu6wK50u0zejYKrDJdEhIPGgYFbx9//DGhoaGEhoYiCAL9+/cv/bnk1qhRI1asWMGoUaOqSrOEgZRmnCaaf98bwBO1n0BA4ETyCWJzKt9SzdTYt2qF1+TJACS+8w7qa9fMrEhC4k6yd+7kev/+FJw+jczJiYBPPsHvrbeQGVCn0lBEUWTJ8SV8d+E7AN7q+Bb96vS7+0BdMYU/jMEh4yIpojNr6yxmbK8WVaZLQuJBxKAivX379sXR0RFRFHnjjTeYPHkytWrVuuMYlUpF06ZN6d5dajBsKdT3ceTI9QwuJlZw31vMURB1VabH18GXDn4dOJxwmK3XtvJ8g+erzJexeEwYT/4/R8k7dJj4KVPx+fYbqMIPRgmJiqArLCTt3ffI+eknAOyaN8f/o49QBgZUqV9RFFl6Yilrzq8BYE6HOQyoN6DMY4Xdb2F7YzeFog3vu7zFu0P6VqqelYSExN0YFLx17NiRjh31szN5eXmMHz8ef3//KhEmYTrqeTsAFZh582kKNg4IhVkIqZchqGWVaXqqzlMcTjjMtqhtjKk/psr8GIsgk+G/aBFR/fqjvnqV9MWLsX/nHXPLkniAUV+9Sty011BfuQKAx/jxeL08uUpqt92OKIosO7WM1edWAzCz/UwG1R9U9rFHV2B78isA5spfZtrzw7FTyqtUn4TEg0ilsk2lwM06qO+jXza9lFhOg3oAuQIC9YUzZbH/VKmmXrV64WDjQFxuHKdST1WpL2NReHkR8OEHIAjk/ryJzJ9+NrckiQcQURRJ/34t158diPrKFWTu7gStWon3tKlVHrgBfH76c1ae1e+rm95uOkMbDC37wCs74Q99f+APi4fw7MiXCHC1q3J9EhIPIgbNvEVHR+Pn54eNjc1dtdbK4v+XVC2dkv5khh5vaEaiMXaV8VXb0x6ZAOl5RaTkqPFyKqc3ZFB7hOt/I4v9B1GcYLCvimq0ldvSN7gvv0T+wm83fqNDYMV73xrqqzI29h074hE+ibRlESTOn48qLAy7li0sSqPky/o0VtSmOC2NhJmzyLtVN9OhSxfc5s7BPjCwwv4qc14rz69k5Xl94PZ6m9cZ1mBY2eMknUP742gU6NhQ3APfx6bTNsStWjTWhOfZ2nxZg0Zr8WUsBgVvoaGhHD58mHbt2hESEnLffQxareW0QCqLiIgIIiIiSnWq1WoKCwsNGkOtVhu1n8MYO2N9Cbpigt3tuZ6Wz5noVDqHedzzWJlva1SAEHvUqMr2hmh8OPBhfon8hd0xu3kt7zVsFYbtKauua+g4Zgy5586j3ruX2Jdfxm/t9yi8vS1Ko+TLNHaW5Cv/wEFS33oLXXo6KJW4v/IKTkOHoFarDX5tGqPv6wtflwZuLzd7mYG1B5b9/pibhPy7gSiL8zikbcSJxtOZ19K3Rr6XSr4qbyf5utPGWAwK3lavXk1YWFjpfWvfhBoeHk54eDjZ2dm4uLigUqmwNWBTekmkrVKpDLoWxthV1lcDP2eup+UTla6mV+NyzrF2J0RBhjw7FlVROoJzxZfGDdXYIagD/g7+xOfFcyDpAE+EPVFlvoy1KbHzfudtksY8T9HVq6S+9jq1vvsWmaqcGUwzaJR8WY/G8mx0ajUpixeT8f1aAFR16+K3+ENs69Ur/aZe1ef11dmvWH5uOQAvt3yZcU3HlX1gUR7an0ehyEvgms6PFb7z+OSJptLzXMN9WYNGa/BVbcHb7eU/Ro8ebbRTS0UQBIMD0hKb6rCrjK8Gvk78fi6RS4k55dvbOiP6NIbEswix/yI07mewr4pqlAtyngp7ii/OfMHWqK08WaeMelEm8lUZGwC5gwOBEcu4OXAQhWfPkvTWW/gtXHjfcar7eZZ8WY/GsmwKL14k/o03UV+9Cui7fni/Nu2OLwpVfV5fn/uaT05+AsCLTV5kXNNxZdvpdIi/vIAi8RTpoiPTbecQMbI7KoUoPc8PgC9r0GjpvgzVdTtSG4QHhAa++srm9804BQhoq/8/9lgVKtJTUrD3aMJREnITqtxfZVAGBRGw9GOQy8naspX0b74xtySJGoJYXEzqFyu4Pmgw6qtXkXt4EPTlCnxnzbzvDK8p+eb8Nyw5vgSA8BbhPN+onDI+f85DuPQralHBS9rXeGvUE+Xvp5WQkDAZBicsGIK1JSzUZEp6nF5NyqVYq0MhLyduD2wDx1dDXNUHb4FOgbT2as3xlONsi9rGhGaGJUlUNw4dO+Lz5pskvfceyR98iKpuXRw7dza3LAkrpujGDeKnz6Dg1CkAnPr0xnf+fBTu7tWq49vz37L42GIAJjafyAvNXrj3vrXja+CgfnbuDc0EBg8aRJMAl0ptwJaQkKg4BgVvFUlSuB1LT1h4kAh0tcNeKSe/SMv11Dzqltdj8Fa5EOJPgVYD8qotR/B46OMcTznOlsgtjG86vlJTydWB28gRFF68SNYvvxA3dRqhG39EKX1RkTAQURTJWP8DyR9+iFhQgMzREd85s3F+6qlqfw2svbiWD499CMALzV5gYvOJ9z44ai/ir9MQgI81A/Dt+hxPt6jaIsESEhJ3YnDCgqV/sEqUjUwmUN/XiZPRmVxKzCk/ePOog6hyQVBnQdJ58G9Rpdp6BfZi8YnFROdEczL5JK18WlWpv8oiCAK+895CHXWNwtNniHlxIsFrv0fh5mZuaRJWgiYpiaSZMyk8dBgA+w4d8H/vXWzMUDtz3cV1LPxnIQDjm44nvEU4giCUPYuWchndhpHIxGI2aztxqvYLrH64QTUrlpCQMCh4q4lJCg8SDXydbwVv2TzZvJwPCUGGzq8l8ht79UunVRy82Sns6Bvcl83XNrM5crPFB28AMpWKwE8/48bgwRRFRRHz4osEf/01Mnt7c0uTsGBEUSRr0y8kLVyILicHQaXCe9o03EYMR5BV/xbkDZc28P4/7wMwtslYJrecfO8v6HmpiGsHIlNn86+uHp87T2HjsFbIZdIXegmJ6sagd4vo6Gg0Gk3p/fvdJCwLQ5IWdP63AqhqSFoAeLrO0wDsuLGDfE1+tfisLDY+3tRatRK5iwuFp88Q++qriLdeHxIS/48mIYGYCS+QMGsWupwclI0bE/LzT7g/N9IsgduPl3/knaP6lm9jmozhlVav3Dtw0xTCD8MQMm9yU+fNVOENPh/VERe7qu/wICEhcTcPdJHeB42S4O1iQkWCt9b6O9UUvLXybkWQUxAxOTHsjt5dmoVq6ajq1CHwi+VEj3mevH37SZg9G7/33zfLh7GEZSKKIpkbN5K86AN0eXkISiWekydjP2QwKkdHs2j68fKPvH3kbQBGNx7NlFZT7v1+LoqwJRxijpIt2vN88eu8NaIbdbzL2XohISFRpTzQRXofNBr46jNO4zILyC7U4Gx772/NOv9bTenTrkJBBthV7X4uQRB4Ouxplp1axpbILVYTvAHYt2xJwNKPiQ1/iawtW5F7eOLzxuvmliVhARTFxpE4dw55t/a22bVogd9776IMDTW4A4Gp2HhlY2ngNqrRKKa2nlr+e/nfC+HcT2hEOS9qXqVfr570buRTTWolJCTKQirS+wDhYm+Dn4stCVmFXEnMoU1IOaUI7NwR3cMQ0q9B3HGo07vK9T0V9hQRpyL4J/Ef4nLjCHC0ngw2px498Hv3HRKmzyB99WoUHh64Pz/G3LIkzISo1ZKx/gdSlixBl5+PoFLh9eqr+iVSudxsJTU2XtnIgsMLAHiu0XNMazOt3MBNfv5nhL8XATC7+HlcG/fmpYfqVItWCQmJeyOt7Txg1L+1dHqpIsV6A6t36dTP0Y92fu0A2Bq5tVp8mhLXfv3wfv01AJI//JCszVvMrEjCHBRevsyNocNIeucddPn52LVpTe0tm/EYMxpBLjebrp+u/FQauI1sNJLX2rxW/oxb9BFsfp8CwBfFT3La6yk+fLa5tOIiIWEBVCp402q1rF+/ngkTJjBgwAAmTJjA+vXrKS4uNpU+CRNTsnR6KTH7/geXdlr4twoV3Um/Ov0A2HJtCzpRV21+TYXH2LG4j9HPuCXMnk3+33+bWZFEdaErKCB58WKuPzOAwjNnkDk64jN3DsHffosyJMSs2jZHbWbBEX3gNqLhCF5v83r5QVh6FGwYjqAt4ndtW1bYjGDlc21wUBm0WCMhIVFFGP1KTE1N5ZFHHuHEiRMoFAo8PDxIS0tj1apVLF68mB07duDp6WlKrVVOSXNZQ483dAnEGDtT+arvo98gfSkx555jldoEtEYAxNhjoNPBfb5xm+K8Hgp6CEcbR+Jy4ziWeIy2vm2rzFdV2Xm9No3itDSyt24l+bXXUQDODz9sURprsi9zaMw/eJC4hYvQxMYC4NS3L96zZmLj7V16jKl8GWr385Wfee/YewAMbzic19u8XqamUgoyYd1ghPw0Tutq85o2nBXPtSbQze6+fmv68yz5sh6N1uLLWIwO3qZMmcLly5dZu3YtgwYNQi6Xo9Vq2bBhAy+++CJTpkzhu+++M1pYdRAREUFERERpVqxarTZ4E7FarTZqGcEYO1P4qu2u7z14OSGHgoKCe46nVqsRXOtgq7BFKMykMOEContYlWi83UZAoHdQbzZHbWbTlU00dW1aZb6q0s5t9iy0ajV5O3YQP+01ivLycHzsMYvSWJN9GWtnqE1xaioZSz4m7/ffAZD7+uIx/U3su3dHC2jLeT+pjvPaHLW5NHAbXHcwLzd5GbVafW8DrQblxhHIU6+QILozrmgaLz/cmNaBjhV+b6yJz7Pky3R2kq87bYzF6OBt27ZtvPPOOwwdOrT0d3K5nGHDhpGcnMy8efOMFlVdhIeHEx4eTnZ2Ni4uLqhUKmxtbStsXxJpq1Qqg540Y+xM5atBgBKFTCBHXUy6GgJc7z7fUhtbW/BrDjFHUaWcBf/G1XJez9R7hs1Rm/kz9k9md5yNg41DlfmqMjtbWwIWf0icSkXe1q2kzp6DQifi+uwAi9FYU31Vh0ZRoyFj7TpSly1Dl5cHMhluI4bj+fLLyB3u/ns1hT5D7X668lNp4DaoziBmtJ+BrLwSNqII215HuHmAPGx5vuh1OjdvyLhuYeXbVfN5VdZO8vVgaLQGX2YJ3kRRpHHjsj/MmzRpUqnpQHMhCILBkXOJTXXYmcKXykZOHW9HLiXmcDkxh0C3sjsClNoEtoWYowhxx6DF0DKPrazG/7dp4d2CEOcQbmTfYNfNXfSv27/KfFWlnUyhwPOtudg4OJC5fj2Jc+YgFhbiPnKExWisqb6qUmPe0X9Ieudt1FcjAbBt2hS3N9/EpXUri7keG69sLN3jNrzhcF5u8jIymax8X4c+hZPfoUXGS0WTsQloxrwn6t/fzgh95raTfD0YGi3dl6G6bsfohIXevXuze/fuMh/btWsXPXr0MHZoiSrGoIzTgOrNOIVbNd9udVzYcs26MzYFmQyfObNLkxiS3n2XtFWrzKxKwhg0iYnETZ1G9KhRqK9GInd1xfftBQT/sB5V40bmllfK7eVARjQcwRtt3rj/h8SFrYi73gLgbc0Iztp34IsRrVApzJcdKyEhcW8MmnlLT08vvT9nzhyeeeYZtFotw4YNw9fXl8TERNauXcumTZvYtGmTycVKmIYGvs5sIb6C5UJuJQwknQNNAdjYVa24WzxZ+0k+O/kZx5OOE50dTS3nWtXityoQBAHvN15HZmdL6ufLSV78EbqCQjxfCq/UNy+J6kGnVpP+7bekLv8CMT9fv0Q6ZDBeL7+M3NXVolYZbu+cMKLhCN5o+8b9jeJOwKYJCIh8U9yHtTzCDyNb4ediZ7ZCwhISEuVjUPDm6el5x4eNKIp89NFHLFmy5I7fAbRu3Vpqj2Wh/NfjtALlQlwCwdEHcpMg4TTU6lDF6vT4OPjQ0b8jB+MO8kvkL7zS6pVq8VtVCIKA18svI6hsSfn4Y1IjIihOTsZ3zmwEpdLc8iTKQBRFsrdvJ2XJx2ji4gB9hwTfuXOwbWQ5M20l3B64jWw0srQcSLnBZVYsrB8KxQXs1TVnQfFzvPNMU1oHu1tUUCohIXEnBgVvc+fOlWYKagAN/PTB27WUPNTF2vKXRgRBP/t26Vd9vbdqCt4ABtQdwMG4g2yO3Ex4i3AUMuuvMeX5wgRk9vYkvfcemRs3oo6KIvDTT1B4eJhbmsRt5J84QdLCRRSeOQOAwtsbrylTcHn6KYvsW7vh0obSJvPPNXru/gV4AdQ5sG4I5CZyVQzipaLJDGkfytB21jvLLSHxoGDQp6E1ZJBK3B9fZ1ucbRVkFxZzLTmPRv7O5RsEtL4VvFXfvjeAHoE9cLd1J7Uglf2x++lZq2e1+q8q3EeOQFkriLhpr1Fw/DjXBw4kKCIC24YNzS3tgUcTHU1axOfk7NwJgGBvj8e4sXiMHo3MvuzkHnOz/tJ63juqzyqtcOCm08JPYyHpLOmCC6MLX6NhSABvPVl+RrmEhIRlYNBXyOjoaDQaTen9+90kLBNBEGjgZ0CnhZJ9b9UcvNnIbUob1G+6WrP2UDp2707IjxtQBgdTHJ/AjWHDyf5jh7llPbAUp6SQ9N57xA14Vh+4yWS4DhxI2B+/4zVpksUGbmsvri0N3MY0HlOxwA1g52y4uoMiQcnzhdPQuQTx+fDWKBWWN6soISFxNwbNvIWGhnL48GHatWtHSEjIfd8kpD1vlkt9Hyf+uZ7OlaTc+x/s3xIEGWTHQnYCOPtVvcBb9K/bnzXn17A/bj/J+cl423tXm++qRlW7NiE/biBu6jTyDh4k7tVX8Zg0EcexY80t7YGhOCOD9K++In3tOsSCAgAcunbB+7XXsa1fz8zqyue7C9/xwb8fADC2yVheafVKxQK3f1fBkc8BeFX9Ihfk9fhpZGu8nFRVKVdCQsKEGBS8rV69mrCwsNL70v436yXMS19INCqlAsGbyhG8G+kzTuOOgfOTVazuP2q71KaVdytOJJ9g67WtjGs6rtp8VwdyFxeCVnxB8uKPSF+zhrTPl1Nw8RIB772Lws3N3PJqLNqcHNK/XkP6N9/oi+wCts2a4jJxIm49elj8e9u3F75l8bHFAIxvOp7JLSdXTHPkbtiuz0D9QDOI7boOLHm2Kc0CXatQrYSEhKkxKHgbNWpU6f3Ro0ebWotENRLmre9xeq0iwRvo970lndMnLTSsvuAN4Jm6z3Ai+QSbrm7i+SbPIxNq1tKOoFDgM/1NVPXqkfjWW+T/9RfXn3oa37cX4CTVSzQpurw80r9fS9rq1eiysgBQNWyI18uTcejevVIVz6uL7y59x2dnPgPghWYvEN6igiVnki/CxjEgavlF7M7n2qcZ2yWUZ1oFVrFiCQkJU1OzPgUlKkyYlz54u5mWj0aru79B6b6341Woqmz6BPfBwcaBmJwYjiVW77676sT1mf7UWvs9NqEhFKekEPviROJnzkKbU4F6fBLlUpyeTvInn3D1oV6kfPwxuqwslHXCCPjkE0J//gmnnj0tfrYNYPW51aWB26Tmk3ip5UsV052XAusHgzqbU7LGvKl+ns51PJnxaIMqViwhIVEVGF17Yc+ePaSlpTFw4EAAkpKSGDNmDCdOnKBv3758+eWXBvUJtQRK+pMZeryh9ZCMsTO1Lx8nFXY2cgo0WqLT8qh9K5i7p01gGwRAjD8BWg2UUbajqs7LTmHHY6GPsfHKRn6++jNtfdtaxDWsCjvbJk3wXbuW3BVfkvHtt2Rt2kTe4UP4vfMODp06mdSXNf/9VtROHRNDxppvyPr5Z8Rbs2o2wcF4hk/C+bHHEOTyu/xY6vX48syXLDu1DICJzSfyYvMXK2QvFuWj3DQaITOaRIU/o3NfxsfNmc+GtEQuu3cdOGt6ni1VY031ZQ0arcWXsRgdvM2dO5c+ffqU/vzGG2+wf/9++vTpw08//UTdunWZM2eO0cKqg4iICCIiIkoTK9RqtcEVxdVqtVHf2I2xM7WvEA87Libmcik+A38nRfk2jrWwVTohFOVQGHsa0bvskgJVdV6P13qcjVc2svvmbpKaJeGicrGIa1gVdhpBwOXVV1B160rqvHkUx8QSM3YcTgMH4vbqK/fMfLT061GdvoouXyH9q68o3LMHbr2+lY0b4zJ6NPY9eyDI5ag1GriVPW8OjRW1EUWRVRdWsfL8SgDGNRjHmPpjKvZeJYrYbJuEIv44BXInhuZNQ23jwprBTbGT6+47hqU/z8baSb7MZyf5utPGWIwO3q5cucKbb74JQHFxMb/88guLFi1i0qRJLF68mNWrV1t88BYeHk54eDjZ2dm4uLigUqkMmi0sibRVKpVBT5oxdlXhq66PExcTc4nOLLrjvO9pE9gaovaiSj4DtVpX63m19GtJfbf6XM64zJ/xfzK0wVCLuIamtrvdxrZTJ5w3byb5oyVkrltHzsaNFBzYj+fkybg89VTprJEpfFnj3+9dxxYVkfPnn2T+sIH8f/4p/b1D5864jxuLffv25Y5hiddDFEWWnVpWGri92upVhoYNrbivv95DuLgZnaDg+YKXuS76sWxgc5oHe5r1vMxpJ/l6MDRagy+zBG/Z2dm4uroCcPz4cfLy8njqKX1Nrnbt2lllQV9BEAyOnEtsqsPO1L5Klkqvp+bd9ViZNgFtIGovQtxxaPu8yTRWxEYQBJ6p+wzv//M+P0f+zNAGQy3iGlaF3e02cgcH/ObOwblPbxJmzUYTH0/izFlkfP01XlOn4nhbZqQxvmQymVHnZYxdVV1DTWIimT/+SMbGjWhTUksE4tCnD14TxmPXuOKFZy3p9SyKIktPLuXrc18D8Hqb1xnZaCSFhYUV83XmR9inLyUyq3gch3WNCe8ZxhPN/E2m0VQ21W0n+XowNFq6L0N13Y7RCQve3t5cvXoVgN27dxMcHExgoD5rKScnBxsbG6NFSVQPJUkL11LyKmZQmrTwbxUpKp/Haz+OUqbkasZVzqedN4sGc+HQsSO1t/+G9+uvIXN2Rn01ktiJk7g5YiT5J04aPa5KZVxtL2PtTIWo1ZJ74CAxL71E5EO9SP18OdqUVORennhOmkjY7l14LXzfInuQVgRRFPnw2Ielgdv0dtN5rvFzFR/g5mHYEg7Ad/L+rNd0o2d9L6b2qV8VciUkJKoZo2feHnnkEWbOnMn58+dZs2bNHWVELl26REhIiCn0SVQh/wVvFSwXEthG/3/qZSjMAluXKlJWNi4qF/qE9OG3qN/4JfIXXm/xerX6NzcyW1s8xo7F9dlnSVu1ivRvv6Pg+HFuDhuGY6+HcBo7FtuWLc0ts8oQRZHCc+fJ/vVXsrdvpzglpfQx+3btcBs6BKdevRCUSkRRRGvg/lVLQRRFFv6zkHWX1gEwu/1sBjcYXPEB0q/DhuGgLeKobWfmZg4g2N2OpYNbIJdZfkathITE/TE6eHvvvfeIjo5m5cqVtGvXjtmzZ5c+tm7dOjqVkxknYRmEeuoL9Wbma0jPK8LdQVm+gYMnuNSCrGhIOAOhXatB5Z0MqDuA36J+Y/v17bzU5CVssa6MZlMgd3HBe9o03IYPJ2XZMrI2/ULun3vI/XMPGU2b4jZkMM6PPmqxLZ0MRXMzmtzdu8j+9TeKbtwo/b3MxQWXxx/HbegQVHXrmk+gCdGJOt47+h4bLm9AQGBux7k8W+/Zig9QkAnrBkF+GnH2DRiVPg4HlZKIIc1wtpNWQyQkagpGB2+enp788ccfZT72119/WV2ZkAcRO6WcAFc74jILuJaSi7uD+/2N/Fvog7f4k2YJ3tr4tCHIKYiYnBj+jPmTZxsa8MFWw7Dx9cX/nXfwGDOG1M+Xk71jB4Vnz5Jw9ixJCxfh8vTTuA0eVKHAJv/ff0n7ajWF589TnJJC4LLPcOrd+97HHz9OykdLKIqKQldYiI2/P66DB+FhguLdolZLwZkz5O3fT87ev1FfuFD6mGBri9NDPXF+4gkcu3RBUN7nC4cVodVpWXBkAZuubkJAYEHnBfSr08+AATTw43OQeoV8Wx/6pU+mEBUrBjUv7agiISFRMzA6eCsPZ2fnqhhWogqo7eVAXGYBUSm5tA2pSPDWEi5u1QdvZqAkceGTE5+wOWrzAx28laAKC8N/8Ye4TJ1C4fbfyfzxRzQxMWR8/z0Z33+PXatWOPXtg2PXrihr1y5zk6yuoABVg/q4PNOfuJdfua9PmZ0dbsOHYVu/PoKdPQUnjpPw1jxkdva4DR5k8DkUp6eTd+AAuX/vI+/AAbS3uh8AIJfj0KkjLk88gWOv3sgda14gUqwrZs7BOfwa9SsyQcY7nd/hyTADOpmIImx/Da7/jVZhz5CcqaTgxqu969K3kY/BJZAkJCQsG6lI7wNOmJcj+6+mVjxpwf/WniozBW8AT4c9zbKTyziTdoYrGVeo7y5twgaQu7vjMW4sHmOfJ+/QYTI3bCBnzx4KTpyg4MQJkhcuQuHvh2PnLjg9+ggOHTuW2jp264Zjt24AxFXAl22jRtg2alQaCCoDA8jZtYv848fuG7yJWi3qyGsUnDlN4ZkzFJw5i/rKFX0AcguZszMOnTvh2K0binbtcPD3r1RmliWj0WmYsX8GO27sQC7IWdhtIY+EPGLYIIcj4PgaREHG67zCGW0QfRr58PJDNWM5WUJC4k4e6CK9Erf1OE2uYNKCfwv9/xnXoSAD7NyqRlg5eNl78VCth9h1cxc/Xv6ROR2lv7PbEWQyHLt0xrFLZzRJyWRv307e/v3kHztGcXwCmRs3UnD6FMHr1iFqtfr0doUC5AoEhfz+Dsqg8MIF8k+ewuuVl0t/J4oiiCIF58+jvnKF/KtX0Zy/QOH584j5+XeNoWrYUB9Edu+GXbNmCAqFPkmhBs8aFWmLeGPfG+yJ2YNCpmBx98X0qtXLsEEubYed+j3HXzuMY1NqU+p4O7JkUHNk5XRQkJCQsF4e6CK9EhB2K2khKrWCM292buAWqg/e4k9BWM+qE1cOg+sPZtfNXfwa9StTWk/BUel4f6MHEBsfbzzGjMZjzGh0BQXk//svufsPoImJAVFELC5GvNWB4Ha0Obn6pUtBAJkMSuoX3bqJgCCKRD78CNqMDEStFo/x43F++GGKMzNBq0UEZEolibNmob5y9Y7xZfb22DZtil2zZtg1b4Zd8+YovLyq5ZpYCmqtmpkHZ7I/bj9KmZKPe35Mt8Buhg2ScBp+HguIHPXox4K47jjZKvhyZGucbKUEBQmJmopUpPcBp2TmLTo9H3WxFlVFZl78W94K3k6aLXhr69OWEKcQbuTcYFvUNoY2GGoWHdaEzM7ujuVRUacDGxsoLtYHW7cFcqJOi64C1b8DPv0UXUE+hRcukLbiSxQ+3v8lOsjlIAgo/PxQeHkj8/fH4VawpgoLu6NDxINGQXEBrx14jaNJR7GV2/LJQ5/Qyd/ADP3seFg3BDT5JHh0ZHjcMwiCwKdDWt7Rq1hCQqLmYXTwVlKkt2vXrlKRXivG20mFo0pBrrqY6LR86vo43d/IvwWc32TWfW+CIDCgzgA+OvkRGy5tYEj9ITV2T1SVIQjIVCq4raVLyRKbzM4euaNj6dInOp1+pq7k51v2qtAQEATsmjRBl5NL+jff4Nq/P8jl+uBMJqPWihWly5+2trYP/POUp8njpT9f4ljSMewUdkT0iqCtb1vDBinKg/VDICeeApc6PJ44lmIUvN63Pj0beFeNcAkJCYtBKtL7gCMIArW9HDgTm8W1lLwKBm8lSQunqlTb/Xg8+HEizkZwLesax5KOGf4BKHEXJYGVTGlzzzpxt++huj0QE5Q2oClGZmdXtSKtmOyibCbunsiZlDM4KBz4vPfntPJpZdggog5+mQAJp9HZeTA0bwrpWnsea+rLpB5hVSNcQkLCopCK9N5GSXNZQ483dEOwMXZV6au2Z0nwloMo+tzfxrcZAkBWNGJuir54r5EaK3NeDjYOPB76OD9f/ZkNlzbQxqdNlfmqCc/zvewEQUCbm0tRdHTp74tiYim4cAG5iws2/v4kL1lCcVIy/osWApC+di02/v6oQkMByD9xgvTVX+M2fHiZGqRrDxmFGbyw+wUupV/CWenMJ10/oYVXC4M1Kva+i3DpN0S5kpmq6ZzKcKO+jyMfDGhWekx1npe5fFmDxprqyxo0WosvY3mgi/RGREQQERGB9tY+H7VabXBmm1qtNmoZyBi7qvIV7KZ/rq4kZpeef/k2KlTuYcjSr1F08x90tR+qlMbKnFf/kP78fPVndkfvJjYjFk87zyrzZe3P8+0IgnBHf9KC8+eJGTW69OfkRYsAcO7XD//336M4JRVNQsJ/A+hEUpZ8jCYuDkEuxyYoCK+pU3Eto0yIWq1GFMUH+tqnFqTy0t8vEZUdhbvKnc+6f0aQbRDqCuwrvB356XUo/4kAYK3P6/wQFYCLrYJPBzVBLhZTWFhslL57YUnX0JR2ki/z2Um+7rQxlkoX6c3KyuLIkSOkpqby2GOP4ebmZjVFesPDwwkPDyc7OxsXFxdUKpVBQWdJpK26bc9QVdlVpa96fvoepTfT9XuSKuQroBWkX0OZeh4aPWa282rq0pQWXi04lXKK32J+44VmL1SZL2t/nsvDoV07Gly8cM/H/d9/746f3UYMx33kiAqNrVKpHuhrn5iXyMS9E7mZcxNvO29W9l1JiHMIhYWFhvm6vg92vgHA6dovMPtCY2QCfDK0JfX8711guyZcQ2vVWFN9WYNGa/BltuDt7bffZuHChRQUFCAIAv/++y9ubm706tWLPn36MH369MoMX+0IJeUQjLCpDruq8lXHW7/PraRB/e3H39OXf0s4uxEh4bS+fEQlNFb2vAY3GMyplFNsvLKRcU3HoZDd+8+6Op8vY+2qy5coiqXHGvrmZozdg3jtY3JiGLdjHPF58fg7+LOq7yqCnINKr2GFfaVG6ltf6YpJrvU4Ay51B+DNRxrQo/79ExSs+Rpau8aa6ssaNFq6L0N13Y7MWMPPP/+c+fPnM3bsWH777bc71m6feOIJfvvtN6NFSVQvwR72yATIKSwmNbeoYkYW0GmhhL7BfXFTuZGcn8zfMX+bW46EBABRWVGM/n008Xnx1HKqxTePfkOQc5DhA+Wnw7qBUJhJkV8bno4dRrEOnmzuz4RutU0vXEJCwuIxOnhbtmwZU6dO5dNPP6Vv3753PFa3bl2uXr16D0sJS8PWRk6gmz6zsGT27b74NgMEyI6DnKSqE1cBlHIlz9R9BoAfLv9gVi0SEgCX0y8z5o8xJBckE+YSxppH1uDr4Gv4QMVFsGEkpEehc6nFWPUUEvIFGvo5sWhA00p9c5eQkLBejA7eoqKiePjhh8t8zMnJiczMTGOHljADYV76TgsVDt5UjuB1q6dowqmqEWUAA+sPREDgSMIRrmddN7cciQeYU8mnGLNjDOmF6TR0b8jXj3yNl70R3SNEEX59FW4eQFQ6scRzAfvjBVzsFKwY0Rp7ZaW3LEtISFgpRgdvLi4uJCWVPeNy48YNvL2lQpHWRElF9qiKNqgH8Guh/98Clk4DHANKWwv9ePlHM6uxHozdMFuZjbY1maMJR5mwawI5RTm09G7JVw9/hZutm3GDHfgYTq0FQcbuJotYdl6JTIAlzzYhyL3sGnwSEhIPBkYHb7169eKDDz4gL++/D3tBECguLmb58uX3nJWTsEzCbgVvFZ55A4va9wb6fqcAWyK3kK+5u/G5xN0YW2eoMvWJaip/x/7NpN2TKCguoKNfR77o/QVOygoUvS6LC1vgz/kA3Gg7l4lH9AHg9Ecb0Kn2vTNLJSQkHgyMDt4WLFjAzZs3adSoEdOmTUMQBJYtW0a7du2IjIyUmtJbGQYvm8KdwZsFfJh3DuhMgGMAOZoc/rhRdg1CCYmqYFf0Lqb8NYUiXREPBT3Esl7LsLcxcnYs7gRs0pe8yW0xlgHHm1CsE3m6hT/juoSaULWEhIS1YnTwVqdOHQ4ePEjDhg35/PPPEUWRb7/9Fk9PT/bv30+tWrVMqVOiiilZNo3NKECt0VbMyLcpCDLITYKchPsfX8XIBFnp7Nv3F7+XZockqoVNVzcx+8hsisViHq/9OIt7LEYpVxo3WFasvmdpcQHasN6MiHmatLwiGvk5s/CZZlKCgoSEBFCJ4A2gUaNG/PHHH+Tk5BAbG0t2djY7d+6kYcOGlRL1+eefExoaiq2tLa1bt2b//v3lHq9Wq5k1axbBwcGoVCrCwsJYvXp1pTQ8aHg6KnG2VSCKcD2tgvvelPbgdeu5tpCl02fqPoOdwo6rGVc5HH/Y3HIkajjfnv+WeYfnISIysN5A3uvyHjYyG+MGU+fCuiGQm4To3Yg5immcisvFzd6GFSNbY6eUm1a8hISE1WJU8FZQUEBAQADbtm0D9BXU/f39sTNBQ+oNGzbw6quvMmvWLE6ePEnXrl159NFHib6t7+L/M2jQIP7880+++uorLl++zPr162nQoEGltTxICIJAmHfJvjcDkhYsbN+bi8qltGzImvNrzCtGosYiiiKfnfyMD499CMCI+iOY3X42MsHI78M6Lfw8FpLOgoM3P9VbzLrTGchlAhHDWkkJChISEndg1DuNnZ0dBQUFODg4mFoPS5YsYezYsYwbN46GDRuydOlSgoKCWL58eZnH//HHH/z9999s376d3r17ExISQrt27ejUqZPJtdV0ansakXHq30L/v4UEbwAjGo5AJsg4nHCYy+mXzS1HooahE3W8d/Q9vjzzJQAvt3yZyc0mV25Jc9dcuPIHKGw52/ULpu/JAmDGow3oVKf8fr0SEhIPHkYXCurVqxe7d+/moYceuv/BFaSoqIjjx4/f1Varb9++HDp0qEybrVu30qZNGz744AO+++47HBwceOqpp3j77bfvOROoVqvvKHWQnZ0N/NefrKKUHG/o3ipj7KrD1+1JCxX25d8SARDjTyLqdBZxXgGOAfQN7ssfN/5gzfk1vNflvSrzZWo7yZdla9ToNMw5OIft17cjIDCz/UwG1RtEYWGh8b6Or0E4vAyAtD6fMHqnDu2tBIXnO4fcMa6lX/ua8jxLvqxfo7X4Mhajg7eZM2cyYMAAbG1teeaZZ/Dz87vrm6e7u2Ep7ampqWi1Wnx8fO74vY+PD4mJiWXaREVFceDAAWxtbfnll19ITU1l0qRJpKen33Pf2/vvv8/8+fPv+r1araawsNAgzWq12qhv3MbYVbWvIFf9JuvIpJyK+3IJw1amQMhPQ51yDbXKyyLOa0idIfxx4w9+v/47LzR6AR97nyrzZWo7yZf57MqzKSwuZMbhGRxMOIhckDOv/TwervVw6ZdBY3zJb+5H+ds0AAo6vcZzR/xJy8uhoa8jbz1Wt8x6epZ+7a39eZZ8Va2d5OtOG2MxOnhr3bo1APPmzSszEALQaiuYtfh//P8FuL0R9v+j0+kQBIG1a9fi4uIC6Jden332WSIiIsqcfZsxYwZTp04t/Tk7O5ugoCBUKhW2trYV1lkSaatUKoMbextqVx2+Gvjra0ndSMtHqVRW0JcteDeCxDMo0y6iCw20iPNq5d+KNj5tOJZ0jJ+ifmJam2nV+nwZayf5skyNOUU5TDk4heNJx1HJVXzU/aPSotDG+iL1MsrN4xBELWLTQcxKf4LzCfG42dvw5XNtcXO6+73L0q+9tT/Pkq+ao9EafJkleJs7d67J09Y9PT2Ry+V3zbIlJyffNRtXgp+fHwEBAaWBG0DDhg0RRZHY2Fjq1q17l41KpUKlUt31e0EQDD6nEpvqsKtqX8EeDshlAnlFWlJyNQTb21fMl38LSDyDkHAKoXZfizmvMU3G6IO3qz/xQvMXcLRxrNbny1g7yZdlaUwrSGPi7olcTL+Io40jy3oto7VP68r5yk9D9fNzCOpsCOrAd96vsem3yAolKFj6tbfW51nyVfM0WrqvysRQRgdv8+bNM9rpvVAqlbRu3Zpdu3bRv3//0t/v2rWLp59+ukybzp07s3HjRnJzc3F01G+4v3LlCjKZjMDAQJNrrMkoFTJqudtzPTWP62l5BHu73N8I9BmnJ761qKQFgC4BXajtUpuorCh+vvIzoxqPMrckCSsjNieWF3a9QHRONO627izvvZxGHo0qN2ixGjaMQJZ5E9EthOMdP2P+95GAlKAgISFRMSpV502r1bJ+/XomTJjAgAEDmDBhAuvXr6e4uNjoMadOncqqVatYvXo1Fy9eZMqUKURHR/Piiy8C+iXP5557rvT4YcOG4eHhwZgxY7hw4QL79u3j9ddf5/nnnzdJ6ZIHjZKkhahUA9pLWVinhRJkgqw0YPvu4ndotBozK5KwJq5kXOG5358jOicafwd/vnnkm8oHbqIIW19GiD6MqHIm+YlveOHnm2h1Iv1a+DNW6qAgISFRAYwO3lJTU2nfvj3Dhw9nzZo1HDp0iDVr1jB8+HDat29PamqqUeMOHjyYpUuXsmDBAlq0aMG+ffvYvn07wcHBACQkJNxR883R0ZFdu3aRmZlJmzZtGD58OE8++SSffvqpsaf2QFPS4/S6IcGbdyOQKxEKMxGy7l2Pzxw8UfsJPGw9SM5PZsfNHeaWI2ElnEg6weg/RpNSkEId1zp899h3hLiEVH7g/YvhzA+IgpzcJ1YwfntuaQeF96UOChISEhXE6OBtypQpXL58mbVr11JQUEBCQgIFBQV8//33XL16lSlTphgtatKkSdy4cQO1Ws3x48fp1q1b6WNr1qxh7969dxzfoEEDdu3aRX5+PjExMXz00UfSrJuR1L4183Y9zYDgTaECn8YAyBJOVYEq41HKlQxvOBzQF+2tTGq2xIPB3pi9TNg1gZyiHFp6t2TNI2vwtveu/MDnNsGedwAQH/2AOed8OBOXJXVQkJCQMBijg7dt27bxzjvvMHToUORy/ZuOXC5n2LBhLFiwoLT7goR1UTLzFpVqQKFeKF06FRJPm1pSpRlUfxB2CjuuZFzhn6R/zC1HwoL59fqvTNk7BbVWTbfAbqzoswIXVQX3fpZH7DHYPFF/v8MkvtX0YvPpRGQCLJM6KEhISBiI0cGbKIo0bty4zMeaNGkizXBYKSXBW0KWmvwiA/Yu3greZImnqkBV5bi9Zdb3l783sxoJS0QURb4+9zUL/l2AVtTyVNhTLO25FDuFCWbwM2Ng/VAoLoR6j3C0zhTe+e0ioE9Q6CwlKEhISBiI0cFb79692b17d5mP7dq1ix49ehg7tIQZcXNQ4mavb6x93ZDZN78WAMiSzllU0kIJJS2zjiYdlVpmSdyBTtTxwb8f8PGJjwEY1WgU73R+x/gG87ejzoF1gyEvGXyakNhnGeE/nKZYJ/JEUx8pQUFCQsIojC4VMmfOHJ555hm0Wi3Dhg3D19eXxMRE1q5dy6ZNm9i0aRPp6emlxxvabUHCfIR4OJCRn8nNtHyaBLhWzMirAaLMBkGdjZh5E9wt60Mp0CmwtGXWyrMr+ajHR+aWJGEBqLVqZh2YxY4b+mSWl5u9zLgW40yTOKDTwk9jIfk8OHhTOHAdL/xwmdTcIhr6ObHgyQZSgoKEhIRRGB28tWrVCoCPPvqIJUuWlP6+ZLm0pANDCcZ2W5CofoLc7TgZk0lMRkHFjRRK8G4IiWcg4bTFBW8A45qOY8eNHey8uZNL6Zdo4N7A3JIkzEh2UTav7HmFY0nHUMgUvN3pbXr59zKdgx2z4OoOUNgiDl3PnL8yOR2bhau9DStGtMbOplKVmiQkJB5gLKrDgoRlEOim3zwdm25AximAbzN98JZ4Fhr3M72wSlLPrR59avVhZ/ROlp1cxrJey8wtScJMJOYlMnH3RCIzI3GwcWBpz6W0921vcG/je/LvKji6XH+//xd8H+vFxuPnkAnw2dCWBLnbm86XhITEA4dFdViQsAxq3cp8M2jmDcCvOZz6Xh/AWSjjG4/nz5g/+Tv2b06nnKa5V3NzS5KoZiIzInlx94sk5SfhZefF8t7Lqe9e33RJVpF/wvY39Pcfms2/Dt2Zv/YIAG8+0oCudb2khC4JCYlKYXTwVhMpaS5r6PGGvhEbY1edvgLd9Bl2Men5hmn0bYoAkHCmwnbVfQ1rOdbiydpPsvnaZj478Rkr+660OI2Sr6qzO5Z0jFf+eoWcohxCXUJZ3ms5/o7+dxxfKV8pl2DjaH2z+eZDSGwazsSIgxTrRB5v6sf4rqGm81WFNtbgyxo01lRf1qDRWnwZywMdvEVERBAREVG6H0+tVhu8lKFWq41aPjbGrrp8+Tjo6/bFZhSQX1CArKK2rnWxRUDITaQgNRocK1bYtLqv4egGo/n1+q8cTTzKgegDtPFuY3EaJV+mt/vj5h+8/e/baHQamnk046MuH+GicLnjNV8pXwVpqNYOQqbORhvYgdwe7/Pi2uOk5hZRz9uBBU/UQ61Wm/y8qsrGGnwZayf5Mp+d5OtOG2OpVPC2efNm1q5dy82bN+8KegRB4PRpyyvYejvh4eGEh4eTnZ2Ni4sLKpUKW1vbCtuXRNoqlcqgJ80Yu+r0Fexlg1wQKNLqyNEI+DhX7JqIKhWie22E9GvYZlwGz1pVos9YuxKbUNtQnq37LD9c/oGV51fSOahzuWPU1Oe5pvr6fzuAVedW8dnJzwDoVasX73d5H1uF7T1tDPalKcR201iErGhEtxBkQ9eycEcsp2OzcbGz4cvn2uDu7GDS87LEa2/O59kSNdZUX9ag0Rp8mSV4+/DDD3nzzTfx8vKiTp06ODg43N/IwhEEweDIucSmOuyqy5eNQo6vi4q4zEJiMwrwdal4oVKtTzNk6dcQEs9Avb5Voq8ydiXHj282nl8if+FkykkOxh+ka2BXi9Mo+aq8XbFYzLtH32XT1U2Avobb1DZTkQllZ3oa5UsUUe54DSHmKKhcEIZtZN25fNb/E4MgwCdDWhDi6WjS87Lka2+O59mSNdZUX9ag0dJ9GarrdowO3j7//HOef/55VqxYUdoeS6LmEOhqS1xmITEZ+bQJqXiNPtGnCVz8xaKTFgC87b0Z2mAoa86v4bOTn9EloEulXkgSlkeuJpdZ+2dxOOEwMkHG9HbTGdpgqOkd7V+M4vxPiIIcYdA3HM/34q2thwF4rW99etQ3QV9UCQkJidswutBQWloaw4YNkwK3GkqAa0nSgmEZpzqfpvo7CZa9ZA4wpskY7BX2XEy/yJ/Rf5pbjoQJScxLZMKeCRxOOIydwo5Pe35aNYHbuU0If72rv//4RyR7dWTi98fRaEUebeLLpB5hpvcpISHxwGN08Na5c2cuXrxoSi0SFkSgm34/ULSBtd50Pk30dzJuQGGWiVWZFndbd0Y0GgFAxKkItDqpkHRN4ELaBYZvH05kViSedp58/cjXdA/qbnpHtzWb17R9gaLmzzFp7QmSc9TU9Xbkw4HNpdlcCQmJKsHo4G3p0qVERESwdetWioqKTKlJwgIIdP2vXIhB2LkjugTq7yeeNbEq0zOq8SiclE5EZkbyx40/zC1HopLsvrmb0X+MJqUghdrOtVn76FoaezQ2vaPMaFg/BIoLEes9QnGPubz92wWO3czAyVbBl8+1wVH1QCfzS0hIVCFGB2916tShd+/e9O/fH3t7e5ydne+4ubi4mFKnRDVTUust1tBCvaDvtACQYNn73gCclc6MaTwGgM9PfY5GpzGzIgljEEWRlWdWMmXvFAqKC+jk34lVD63Cz9HP9M4Ks281m08Bn6YwYBWbTifx/ZFoAJYObkGop/UncElISFguRn81fOONN1i2bBktWrSgYcOGKJVKU+qSMDMBrvpl04SsAjRaHTZyA+J832ZwebtV7HsDGN5wON9f/J7onGg2XNpQupQqYR0UaYuYd2ge26K2ATCswTBea/MaxUXFpnemLYafnofkC+DoC8N+4HRSMfN/uwLAlN716NXQx/R+JSQkJG7D6OBtzZo1vPnmm7z//vum1CNhIXg5KlEpZKiLdcRnFhDsYcBMgt+tmTcLzzgtwd7GnpdavsSCwwtYdmoZfUP64m0vZQhaA2kFabz616ucSjmFXJAzo90MBjcYjCiKFFMFwdvOWRC5CxR2MHQ9qXIvJq49QJFWR++G3kx+qI7pfUpISEj8H0Yvm2q1Wvr06WNKLRIWhCAIt7XJMqLHKUDKZdAYsexqBgbUHUAzr2bkafL44N8PzC1HogJcybjCsN+GcSrlFE5KJ5b3Xs7gBoOrzuE/K+HoF/r7z3yJxrcF4WtPkJBVSKiHPR8Nao5MJiUoSEhIVD1GB299+/blyJEjptQiYWEEuZU0qDcwacHJH+w9QNTql5esAJkgY06HOcgEGTtu7OBQ3CFzS5Iohz3Rexi5fSTxefEEOwez9rG1dPTvWHUOI3fD72/q7/d6Cxo9xfvbL3H0ejoOSjmfDW6Ks61N1fmXkJCQuA2jg7c5c+bw/fff88knnxAZGUl6evpdNwnrJtDdyIxTQbgtacE69r0BNHBvwLAGwwB49+i7qLXGty6RqBp0oo7PT33OK3+9Qn5xPu1827H2sbWEuoRWndPki7BxjP7LSPNh0GUKv5yMZfXB6wB8NKg5YV5SgoKEhET1YfSet+bN9UtjU6dOZerUqWUeU9Lw3Voo6U9m6PGG2BhrZw5fQW7/BW8Vsb/Dl28zhKi/EBPOQDm2lnYNw1uEs/PGTqJzoll1ZhWTWkyyOI0Pqq/colxmHpjJ3ti9gD7RZGrrqdjIbO4a12Qa81Jg3SAEdTZicCd4cikX4rOZsUlfBie8Zxh9G/lQWFhYo6+9JfqyBo011Zc1aLQWX8ZidPA2d+5cqy9AGRERQURERGmQqVarKSwsNGgMtVpt1HUwxq66ffk66peBbqblVfi6lPiSezZECYjxp1Dfx9aSrqEcOa+2eJWZh2fy1bmv6B3Qm1pOtSxK44PoKzo3mtcPvM6NnBsoZUqmt5nOEyFPoC3SoqXsL4mV1lhciHL9UOSZ0ejcQlE/vYqMLDUTvjtGoUZH1zruTOyi/9uoydfekn0Zayf5Mp+d5OtOG2MxOnibN2+e0U4thfDwcMLDw8nOzsbFxQWVSoWtrW2F7UsibZVKZdCTZoydOXyFejsDEJdVWKHrcoevWm0AEFIuYqtUgKzsPzVLvIaP13mcX2/+yqH4Qyw+tZgven1hcRofJF/74/fz1tG3yNXk4m3vzdIeS2ni2aRqNQL89hJC/DFEWxeEYT9i4+LHG1//S1xmIbXc7flsWGsc7Gxq9LW3ZF/WoLGm+rIGjdbgyyzB2+1cuXKFtLQ0PD09qVu3rimGNAuCIBgcOZfYVIdddfuqdas8SFpuEQUaLfbK+/+5lPpyDwOlI0JRLqRFgndDk+oz1q4iNoIgMKv9LPpv6c+RhCPsuLmDnn49LUrjg+BLJ+pYeXYlEaciEBFp5d2Kj3p8hKedZ9Vr/HsRnPsJZAqEQd+BVz0W/36JA5Gp2NnIWTGyNa72yrvtasi1txZf1qCxpvqyBo2W7stQXbdjdMICwMaNGwkODqZhw4Z06dKFBg0aEBwczE8//VSZYSUsBBc7G5xs9QGbwZ0WZDIo6XNqRUkLJdRyrsW4ZuMA+PDYh+QW5ZpZ0YNFZmEmL/35EstOLUNEZHD9wazqu6rCgVulOPsT7L1Vv/LxJVC7O7+dSeCLv68BsOjZZjT0c656HRISEhL3wOjgbfv27QwZMgQXFxcWLlzIt99+y/vvv4+LiwtDhgzh999/N6VOCTNRWi7E0IxT+K/emxW0ySqLsU3GEuwcTGpBKl+c+8Lcch4YzqacZdCvg9gftx+VXMXsNrOZ1X4WNvKqL8Uhi/0XtoTrf+g0GVqP4kpSDq//pP8CMr5rKE81969yHRISEhLlYfSy6bvvvkvfvn357bffkMn+iwFff/11Hn30Ud555x0effRRk4iUMB9B7nZcSMg2Mnizrk4L/49SrmRW+1lM2DWBjZEb6RXSi04Bncwtq8YiiiLrLq1j8bHFFOuKqeVUi4+6f0SwfXD1CMi4gfKX0QhaNdR/HHrPJ6tAwwvfHSe/SEunMA/efKRB9WiRkJCQKAejZ95OnTrFpEmT7gjcQL+GO2nSJE6ftr6lMom7qeVeUqi3kg3qK5ESbU46+ndkQN0BiIhMPzCdpLwkc0uqkeQW5fLa36+x8J+FFOuK6RPchw1PbKC+e/3qEVCYBeuHIuSnIfo2gwEr0SFj6oZTXE/NI8DVjs+GtkRhSI9fCQkJiSrC6HciuVxOUVFRmY9pNJq7gjoJ6yTIvRLLpl4NQGYD6izIuGFaYdXIm23fpJ5rPTIKM3h93+todBpzS6pRXMm4wtDfhrLz5k4UgoLp7abzUfePcFQ6Vo8AbTFsHI2QchHR0QeGrgelA5/uucqfl5JRKmR8MaI1Ho6q6tEjISEhcR+MjrDatm3LBx98QEHBnTMyarWaxYsX0759+0qLkzA//7XIMmLmTaEEn0b6+1a6dApgq7Dl/Y7v42jjyMnkk3x64lNzS6oRiKLI2otrGfrrUG5k38DXwZc1j65heMPhlcrCMlAE/PEmXNuDaGOPesC34BzAnxeTWLr7KgDv9mtC00CX6tEjISEhUQGM3vM2f/58evXqRe3atRk4cCC+vr4kJCSwadMm0tLS2LNnjyl1SpiJoFstsmJvdVkw+EPVt5k+2zThDDR6ugoUVg9BTkEs6LSAqX9PZc35NbT0bslDtR4ytyyrJbUglTkH53Ag7gAA3QK78U7nd3CzdateIUdXwL+rAAGe+RLRtznXU/N4dcMpAEZ2CGZgm6Dq1SQhISFxH4yeeevSpQs7d+4kJCSEiIgIZs+ezfLlywkJCWHnzp106iRt7K4JBN6aectRF5NVYMRyYUnGqRXPvJXQO7g3IxuNBGD2gdnE5MSYWZF1si92HwO2DuBA3AFUchUz289k2UPLqj9wu7IDdszQ3+8zHxo8QV5RMS98d5ycwmLaBLsx54lG1atJQkJCogJUqkhv9+7dOXz4MPn5+WRkZODm5oa9vb2ptElYALY2crycVKTkqIlJL7ijMGmFsMIG9eUxpfUUzqSc4XTKaabtncZ3j32HSi7thaoIhcWFfHz0Y9ZfXg9AXbe6fND1A+q41al+MYnn4KfnQdRBy5HQ6WVEUWT2lktcTc7F20nF58NboVRIe3clJCQsD4PemTIyMhgwYAC//vrrHb+3t7cnICAAe3t7fv31VwYMGEBaWppJhUqYj5IG9dHGJC34NgEEyE2CHOvP1LSR2bC4+2JcVa5cTL/IB/98YG5JVsHl9MuM+XNMaeA2ouEI1j++3jyBW04SrBsMRbkQ2k1fiFcQ+HL/df64kIyNXGD5iFZ4O1e8VZ6EhIREdWJQ8LZq1SpOnz7NI488cs9jHnnkEc6ePUtERESlxUlYBqUZpxlGBG9KB/C81TKtBiydAvg6+LKw60IEBH688iPbrm0ztySLpUhbxLKTyxj621CuZV3Dw9aD5b2X82a7N80zY1mUDz8MhexY8KgLg74FhZIDV1P54I9LAMx9ohGtg92rX5uEhIREBTFo2fSHH35g/PjxKBT3NlMoFIwfP54NGzYwd+7cSgusTkqayxp6vCE2xtqZ01fgrZm3mFtJCwb78m2GkHoFMeE01OldaX3G2pnSVyf/TkxoNoEVZ1Yw99BcHG0c6RHUw6I0mtvX2dSzzD00l2uZ+rZSPQJ6MLfjXDztPSvs06QaRR1snogQdxzRzg2GbQBbV2LT85m8/gQ6Efo192VYu6Aqv4416Xk2ly9r0FhTfVmDRmvxZSwGBW9XrlyhTZs29z2uVatWvP3220aLqi4iIiKIiIhAq9UC+jInhYWFBo2hVquNKmtgjJ25fPk66tsS3UzNve/1KcuXwrMhNoAu9gRFZdhb6zUcXW80URlR7IrZxdS/p7Ko0yK6+ne1KI3m8FVYXMiX579k3ZV16EQd7ip3Xm/1Op29OmMrszXba0yx731sLmxGlNlQ1H81Ont/CnPyeOG7E2Tka2js58T03iH3rF9pao3W/jxbgi9j7SRf5rOTfN1pYywGBW/FxcXY2Ny/v6CNjQ0ajeUXMg0PDyc8PJzs7GxcXFxQqVTY2lZ8n0tJpK1SqQx60oyxM6ev2j76JtxxWepyr889fQW1BkCWcv4ue2u/hou6L0K2X8aOmzt489CbLOm+pHQGzlI0Vqev40nHmXdoHjdzbgLweOjjvNH2DVxVrhQWFlbLeZVpd2odwuFP9A8+9SnKuj0RRZHZ285wISEHdwclX4xsjbOtYLXX/kHzZQ0aa6ova9BoDb6qLXjz8/PjwoULdOvWrdzjzp8/j6+vr9GizIUgCAZHziU21WFnLl+13B0AiMsoQBRBJrv3OGX6ulUuRMi4AepssHW5v42BGqvSpjw7G7kNC7sthP2w48YOpv49laU9ltI9qLvFaKwOX6kFqXx64lN+ifwFAG87b+Z2nFt6HURRrNbzusPu5iHY9or+l11fQ2gxDIDvj9zk5xNxyARYNrQlgW72FBYWWt21f5B9WYPGmurLGjRaui9Ddd2OQQkL3bt35/PPPy93Vk2j0bB8+XJ69uxptCgJy8LPxRa5TKBIqyM5x4hvCvbu4Byov5941rTiLACFTMHCrgvpG9yXYl0xr+59lb9j/ja3rGpBo9XwzflvePKXJ0sDt2fqPsMv/X4pDdzMSto12DAcdBpo1A96zgLg2I105m+7AMD0RxvQqY6nGUVKSEhIGIZBwduUKVO4dOkS/fv3Jz4+/q7H4+Pj6devH5cvX2bKlCkmEylhXhRyGX4u+uVOozJOAfxua1JfA1HIFCzqtqg0gJuydwp/x9bsAO5Q/CEGbBvA4mOLydXk0sijEd89+h3zO83HWelsbnlQkAHrB+v/D2gD/b8AmYzk7EImrj1BsU7k8WZ+jO9a29xKJSQkJAzCoGXTZs2aERERwaRJkwgNDaV169aEhoYCcP36dY4fP45Op2P58uU0bdq0SgRLmIcgN3tiMwqISc+nbYgRZRR8m8Hl7TWmXEhZKGQK/coDaBEAAELOSURBVBLqPth5cydT907lrXZv8VS9p8wtzaTE5sSy8OhC9sXvA8Dd1p1XWr1Cvzr9kAkWUtRWW4Ry8ziEtEhwCdI3m7exo6hYx8S1J0jJUVPfx4kPBjSr1NKFhISEhDkwuMPC+PHjadKkCe+99x5//fUXR44cAfSFeh955BFmzJhBhw4dTC5UwrwEudtxOApi0o1oUA//tcmqoTNvJdjIbO4I4GYfmc2/Kf8yo/0MHGwcKjSGscFEVQchiXmJrDq7ip+v/kyxrhiFoGBow6G82PxFy5hpK0EU4depyKMPIiqdEIZtAEdvAN757QLHb2bgZKvgi5GtcVBVqsmMhISEhFkw6p2rY8eObNu2DZ1OR2pqKgCenp7IZBbyrVvC5AS5VaJQL/y3bJpyCTSFYFNzq9fbyGxY1G0RIadCWHVuFVuubeFE8gkWdl1IM69m97VXqYwrXmus3f0oCdo2Xd2ERqff79repz3T2083T4eE+3HwE4RT3yMKMnh2Nfg0BuCn47F8e1ifBbt0cAtCPSsWTEtISEhYGpX62imTyfD29jaVFgkLprTLgjEtsgCcA8DOHQrSIfkCBLQyoTrLQyFT8FLLl2jt2Zp5/8wjJieG535/jkktJjG2yVjkMrm5Jd6XxLxEvjr7FT9f/bk0aGvr25aJzSbSxLWJQWV1qo0LW2H3WwBoer2NTd0+AJyLy2LWL/pkmVd716VXQx+zSZSQkJCoLNJUmUSFCHLXd1mIzTBy2VQQ/pt9q8H73v6fll4t2fjkRh4NeRStqOWzk5/x/I7nic+9O+HHUriUfokFhxfw2KbH+OHyD2h0Glr7tGb1w6tZ/fBq2vjev1C3WYg7AZsmACC2m4C29VgAMvKKeOG746iLdfRq4M3LD9U1p0oJCQmJSiNt+JCoECXLpglZBWi0OmzkRsT9vs0gam+N3/f2/zgrnVnUbRFdA7vy7tF3OZF8gme3PsuIRiMYXH8wHnYeZdodSzzGmvNruJB2gZSCFJb2XEqvWr3u6Wf3zd38eOVHLqdfpkhXRJhrGJOaT6JzQOf7aszX5LPjxg42XtnI2dT/yrm08m5FeItw2vm1M/zEq5OsWFg/BIoLoE4fePg9KCpGqxN5+YeTxGUWEOxhz5LBLcqtUyghISFhDUjBm0SF8HJSoVLIUBfriM8sINjDiP1CJUkLD9DMWwmCIPBk2JO08G7B9P3TOZNyhuWnl7P63GqeCnuKkY1GEuoSeodNQXEB9dzq0a9OP6bsvX/pnePJx+ng14FXWr2Ck9KJzZGbeWnPS6x7bB0NPRqWaROZGcnWm1v5NepXcjW5ACgEBQ/VeoghDYbQxqeN5WdjqnNg3WDITQLvxvp9bjIFUMySXVfYfzUVOxs5K0a2xsXu/h1iJCQkJCwdKXiTqBCCIBDoZse1lDxi0o0M3nxvLZsmnQedFqxg35epCXIK4ttHvmV39G7WnFvDubRzbLyykZ+u/MTQBkN5o+0bCOirdHcN7ErXwK73H/QWb7Z9E/gv6/SVVq/wV/Rf7I3dWxq8iaKIVtSy7uI6fon8hcjMyFL7QMdAnq33LE/XeRpPOyspWqsthp+eh6Rz4OB9q9m8M4giOy8m8/neawAserYZDXwtKCNWQkJCohJIwdttlPQnM/R4Q2yMtbMEX7Xc7bmWkkd0eh6iePdS3319udcGG3sETT5i6lXwqm8R51XddjJBRt/gvvSp1YcTySf45vw37I3dy7+J/1JQXIBWp0Umk2Ejs8FGZvNf7TSRcjWUtKAqOUYn6sjT5OFs40yBpoAiXRFanRalXMnmyM1EZkYiF+T0DOrJwHoDae/XvtTX/fxYzLXfMRPh6k5EhR0M/QFcAkEUiUzKYcbmiwCM7RLKk8387uu7pv4t1lRf1qCxpvqyBo3W4stYHujgLSIigoiICLRaLaBvEltYWGjQGGq12qhlJWPszO3Lz1kJwI2UnHtep/v5Uno1Qh5/DE3McbROwUbrM9auOn1VxK6xS2M+6PQBN7Jv8GfsnwAUi8Voi7UUoE8OKQmoirRFqLVq/cwcAvp/+rEFBLSiFq2oRSfq0Ipavr/4PfnF+bTxbUOOJgcAuSDXz+r5d+W5Bs/RwrUFPs76zMsidVGVXg9TX0P58a9Q/rMCgKLHP0Xn0QgKC8lVF/PC98fJL9LSLsSVV3sGV/h1XVP/FmuqL2PtJF/ms5N83WljLA908BYeHk54eDjZ2dm4uLigUqkMKn9QEmmrVCqDnjRj7CzBV4iXEwAJ2UVlXqcK+fJvAfHHsEm9iI2trUWclyXYNbBtQAPvBoiIKAQFGlGDRqehWFeMTtQBUKAtILsou0K+90TvYc25NSzovAA3WzdsZDYo5UqUMiUKmYJX27yKKIoUFhZa57W/ugv+nKM/ptdbKFsMLD3+1Z/OE5Waj6+zimXDWuFoX7HXdE39W6ypvqxBY031ZQ0arcGXFLyZCEEQDI6cS2yqw87cvmqV1HrLKLjnWPf1datciJB4Rl8+xEh9xtpVpy+j7ERQKVSo0L8J6EQdxf9r787DoyrPPo5/z8xkZrKzhIQtLLLvSxBFxaXWfbduIGitVCnRaqm1WHn7qtVq694aVNq3KoKKS2u1YhUXFMWNEBAQUNmCIXsgk2328/5xmJCYBDNn1jNzf66Li4Sce373TILenDPnefxegNbLqCqHT8+rHPpdVTEpJswmM++Xvs8D6x/gTzP/xEn5J7WebYvp8wpnVsUWePkaUP0weQ7KCb9q/Vl6/IOdvLW1EqvZxKOXTaBPpj1ufz4kKzl6TNQsI/QY71nB9tWWDG+i2wb2DHGhXmi/1lsI1/uThUkxYTVrl6vTUtLoae/Z6XGBYW7V7lXc89k9/OnEPx1xWRHDaqjQ7ix1N8KQmXDuw62D29pvqnngrR0A3HH+WCYOkBsUhBCJSRbpFd0W2GWhtslNi9un70Fyx2rLOLQc0NbmEl1q9jSzvW472+u2A1DWUMb2uu2UN5YD8EjxI/xu7e9aj1+1exWLP1rMLdNuYVKfSdS01FDTUkODuyEm/Yedu1lby83xHfQeAZc/CxZtsN1X18wvny/Br8Ll0/KZNX1QjJsVQojIkTNvotuy7BZSU8y0eHxUOpwM0bM3pMUGfUZrSztUfKndHSg6tbV2Kz9762etn9+//n4Azh92PveccA/VLdWUN5W3fv3lr1/Gq3q557N7uOeze1r/PHC8oal++Nd1sL9E22Zt9kpI1c5COj0+frGimAPNHiYOzObOC8bFuFkhhIgsGd5EtymKQt9sO7trmvQPb6Ct91a5RdtpYdTZ4W0ygRzd92g2X725y69/fyD7xxn/AEJ7H0XceudO2PY6mK1wxXPQexigXS5e/OoWtpQ56JVu5fE5BdhTzCHdgi+EEPFOLpuKoORm2gCocAS3pEo7SbjHqdDPvGkFyrpHtU8uKILBM1q/tuKzUl4u/g6TAo/NmsKAHqkx6lIIIaJHhjcRlLwsbdmFKof+W5xbd1pIsj1OhQ67PiDlbW3nCE5aBBMva/1S8d4D3Pn6VgB+e+ZojhtukF0hhBAiRDK8iaD0zdaGt8pQzrz1naD97vgOmuvC0JVISNU74MW5KH4v6oRL4eRFh7/U4GLBimI8PpWzJ/TluhOPimGjQggRXTK8iaAELptWNoRw5s2eBT2Hah/LpVPRmcZqWHEJisuBb8B0OP+vrUuCeHx+Cp/bQKXDxfDcDP58yaTEfJ+fEEJ0IS6HtyVLljB06FDsdjsFBQWsXbu2y2PXrFnTbnG8wK/t27dHsePkEbhsWlkfwpk3OPy+N7l02oHeVbdDWa07rnha4IVZcLAUtedQ3Bc/BZbDuyTcu2o7n++uI8Nm4cm5BWTY5L4rIURyibvhbeXKldx8883cfvvtlJSUMHPmTM466yxKS0uPWLdjxw7Ky8tbf40YMSJKHSeX1sumDSEOb4H3vVVsCrGjxKP3TsmEuMPS74dXfwHffQH2HjD7RUjr3frlf28s4x8f7wbgwcsmMaxPRowaFUKI2Im74e2hhx7i2muvZd68eYwZM4ZHHnmE/Px8Hn/88SPW5ebm0rdv39ZfZrM5Sh0nl7zMw+95C2lY6DdJ+13OvIm23r8btv4LTClw+XLIOfyPsO0VDha9oi2dsuDkYZwxrm+suhRCiJiKq+sNbreb4uJiFi1a1O7PTz/9dNatW3fE2ilTpuB0Ohk7diyLFy/mlFNO6fJYl8vV7hKTw6Ft9h3YXLa7AscHO8ToqYuXrD6Z2or2To+f+hYP2akp+rL6TkABqP0W1dWIarN1u7+gs0KoiXZdUmeVLEdZ+6B2/Pl/gSEntNbUN7u5flkxLR4fJwzPYeFpI4/4WAnxekiW4XtM1Cwj9GiULL3ianirqanB5/ORl5fX7s/z8vKoqKjotKZfv34sXbqUgoICXC4Xzz77LKeeeipr1qzhxBNP7LTm3nvv5c477+zw5y6XC6czuMuBLpdL15ul9dTFS1Z2qoX6Fi+l1fWMyM3odl07lmzsGXkojZV4yzbhsh0fVH9BZYVYE+26ZMwy7f0I639uBsAz41d4R10Eh/4utjid/PrVr9lb10z/bDt/vmgMHrcLT5R7lKz4y9JbJ1mxq5Os9jV6xdXwFvD9F0BV1S5flFGjRjFq1KjWz2fMmMG+fft44IEHuhzebrvtNhYuXNj6ucPhID8/H5vNht1u77SmM4FJ22azBfVN01MXT1l9s+zUtzRy0KW2e72Czuo3Cb55G/uBHVhsP4r584qHuqTMqvkaXr1WWxJk/E+wnPZ7LIeOUVWVojW7WPN1LVaLiSfnFtCvV2b0e5SsuMsyQo+JmmWEHo2QlTDDW05ODmazucNZtqqqqg5n447k2GOPZfny5V1+3WazYevkMl3gTtVgtL3DNdJ18ZKVm2VnR2UjlY6O/9IIKqvvRPjmbUxVW+LiecVLXVJlNdXAc5eBsx7yj0G5YAmYDr8V9/3tVRR9sAeAey4cz4SBPaLfo2TFbZYRekzULCP0GO9ZwfbVVlzdsGC1WikoKGD16tXt/nz16tUcd9xx3X6ckpIS+vXrF+72xCGtuyyEstYbtC4XYqrcEmpLwog8LfD8LDiwB3oO0fYsTTl8JndvbRM3r9yIClx5zCAunZYfq06FECKuxNWZN4CFCxcyd+5cpk2bxowZM1i6dCmlpaXMnz8f0C55lpWVsWzZMgAeeeQRhgwZwrhx43C73SxfvpxXXnmFV155JZZPI6H1zQrDLgvQulyIUrMdfB6wWENtTRhF65Ign2tLglz5MqQf3t6qxe1j/vINOJxeJg7I4n/OHRO7XoUQIs7E3fB2+eWXU1tby1133UV5eTnjx49n1apVDB48GIDy8vJ2a7653W5uueUWysrKSE1NZdy4cbzxxhucffbZsXoKCS8v69AuC6EObz2HoNqyUFwO1OrthxfuFYnvvbsOLwlyxYp2S4Koqsrv/rWZbeUOemdYefSy8dgssvSPEEIExN3wBrBgwQIWLFjQ6deefvrpdp/feuut3HrrrVHoSgTkHjrzVhHK5vSgbXfUdwLs/RjKN8nwliyKn4GPHtY+vuAxGHJCuy8v+2Qv/yopw2xSeGzWlNYzvUIIITRx9Z43YQyB/5lWhXrmDaD/VO33/SWhP5aIfzvfh//8Svv4pEUw6Yp2X16/p44//OcrABadOZpjj+r9/UcQQoikJ8ObCFrbGxb8/hC3ZBpQoP1eVhxiVyLeKdXb4KWrQfXBxMvh5PaLcVc1OFmwYgNev8o5E/sxb+bQGHUqhBDxTYY3EbScDCsmBXx+lZqmEC+dDjh05q1yC3jCcCZPxKfGSqwvz0FxOWDQcXD+X7XL5od4fH5uWFFCVYOLEbkZ/PknE0O6jV4IIRKZDG8iaBaziZwM7aaFqlDf95adj5qWg+L3QoXsc5qQ3E3w/BWYHGWovYZpNyhY2q+z+MdV2/h8Tx0ZNgtPzC0g3RaXb8cVQoi4IMOb0CUvXMuFKAr+flO0j+XSaeLx++CVeSj7S1BTe8HsFyGtV7tD/r2xjKc+3gPAg5dNYlifjE4eSAghRIAMb0KXw8uFhHjmDfAHblqQ4S3xvHU77FiFarbhvvhp6D2s3Ze3VzhY9MpmABacPIwzxvWNQZNCCGEscm2ijcD+ZMEeH0yN3rp4y8rN1Ia3ivqW1uP0Zvn6TiYFUMuKoZu18f4aGqHHiGd9+jjKZ49rNRc+jm/A0e1qHC0erl9WTIvHxwnDc1h42sgOj5lQr4dkxUWdZCVHj0bJ0iuph7eioiKKiorw+XyAtkms0xncZUCXq+P+npGqi6es3mnaj87+A03tXjNdWb3GYAeUul20HCiH1J5h6TFcNdGuS4Qs0zf/xfrW7wDwnLwY7/CzcTmdrTV+VeXmFzazt66Zftk2/nzRaDxuF54o9hiuGsmKXZbeOsmKXZ1kta/RK6mHt8LCQgoLC3E4HGRnZ2Oz2bDbu78gaGDSttlsQX3T9NTFW9aAXtr7kmqbva2vme6s7DzUXsNQ6nZir/0Khp8as+cV67qEyCrbAK/9AgUVdepPsZz4a8yH6gI1f33vW97/ugarxcSTc6fRr1dWdHuULMNnGaHHRM0yQo9GyJLhLUwURQl6cg7URKMunrLysg/vstD2GL1ZDCiAup0oZcUw4sdh6TFcNdGuM3TWgb3w/BXgbYHhP0Y550EwmUBVW4//4OtqHn7nawDuvmA8Ewf2iG6PkpUwWUboMVGzjNBjvGcF21dbcsOC0CWsuyyALNabCFoOwnOXQVMV5E2AS58Gc/t/H+6ra+amFzaiqjBrej6XHZ0fk1aFEMLIZHgTugSWCqltcuP2+kN/wLbDWwhv4hQx4nXDyjlQvR0y+8PslWDLbHeI0+PjFys2UN/iYdLAbO44f1yMmhVCCGOT4U3o0jMtBatZ+/GpagjD2be+48GUAs01cLA09McT0aOq8NqNsGctWDPhyhche8D3DlG5a9UOtu530CvdypI5Bdgs5hg1LIQQxibDm9BFURRyw7jWGxa7NsCBXDo1mvf/CF++AIoZLnsa+k7ocMjzn+/jXxsrMCnw11lTGNAjNfp9CiFEgpDhTeiWJ+97ExuehQ//rH183iMwvOPNJiWlB7jj9a0A/OaMURw/PCeKDQohROKR4U3odniXhXANb9O032V4M4Zv34XXb9I+PvE3MPWqDofUNLpYsGIDHp/Kj0f34foTj4pyk0IIkXhkeBO6Bc68VYTjsikcPvO2fyP4vOF5TBERStVWeOlqUH0w8XI45fYOx3h9fm58roTyeidH9Unn3gvHhHRrvBBCCI0Mb0K3sF827T0cbFnaGmHV28LzmCL8HGXYXpqD4m6EITPh/Megk6Hs/rd38MmuWtKsZp64cioZNllWUgghwkGGN6Fb62XTcNxtCtpirv2naB/LpdP45KyH5y5DaSxH7TMaLn8WLNYOh725uZwnP9gFwP2XTGJEXmaHY4QQQugjw5vQLS/z0GXT+jANb3D40ul368P3mCI8vG5YORelcitqei7MfrHTfWi/rWrklpc2AfDzmUM5Z2K/aHcqhBAJTYY3oVtgi6yqcL3nDWBg4KaFDeF7TBE6VYXXboDdH6CmpOO6ZDn0GNThsEaXl/nLi2ly+zhmaC9+e+boGDQrhBCJTd6E0kZgc9lgjw+mRm9dPGblZmqXTRtcXhqdHtKs5tCz+k9FAdTqbeBqAGtGSD2GWhPturjNevcPKF+uRFXMqJc+jT9vQoc6VVX5zUub+LaqkbwsG3+dNQWzSWmXI6+9ZMW6TrKSo0ejZOmV1MNbUVERRUVF+Hw+AFwuF05ncJcAXS6Xrjvo9NTFW5YFSLOaaXb72FfjYEjvtNCzUnpgy+yPqWE/rr1f4M+fEVKP4aiJdl28ZZlLnsH60YMAeM68H1/+TFxOZ4e6p9aV8uaWClJMCg9fMp7MFLXd3yd57SUrXuokK3Z1ktW+Rq+kHt4KCwspLCzE4XCQnZ2NzWbDbrd3uz4wadtstqC+aXrq4jWrb7adXdVNHHRpx4cla2ABbNuPtXoLjDglJs8rVnVxl7XjTVh9m3b8SYtImf4zLJ3Ufbqrlgff3QnA4nPHMGNEXsyel946yTJWlhF6TNQsI/RohCwZ3sJEUZSgJ+dATTTq4jErL1Mb3qoaXO1qQsoaMA22vY5Str7TJSiC7THUmmjXxU3Wd8Xw8s9A9cOUuSgnL2r9frStK69v4cbnS/D5VS6eMoCrZgzp9PHktZeseKmTrOToMd6zgu2rLblhQYQk7LssQJttsuSmhZip2wXPXaatuTf8NDj34U4HabfXz4IVG6hpdDO6byb3XDQhpP8gCSGE+GEyvImQBO44ragP4x2n/ScDCtTvg4bK8D2u6J6mGlj+E2iugX6T4NKnwZzS6aF3v/EVJaUHybJbeHJuAalWc3R7FUKIJCTDmwhJYK23sC3UC2DLhD6HlpjYL2ffosrVCCsu1c689RgEs18CW+d3/P5zQxnLPtkLwCNXTGZw7/RodiqEEElLhjcRkrBvkRXQeulUdlqIGp8HXvqpNjCn9oI5/4LMvE4P3V7RwO2vbgbgl6eO4EejOz9OCCFE+MnwJkLSN1t7z1tFuIe3gTK8RZWqwus3wberwZIKV74EOcM7PbS+xcMvX9yM0+PnpJF9uOnUEVFuVgghkpsMbyIkuYHLpg5XSAsOdtD2zJvfH77HFZ17727YuAIUs/Yet8BOF9/j96ssXLmRfQecDOyZyqNXTMZskhsUhBAimmR4EyHJPXS3qdvrp77FE8YHHgsWu7YReu034Xtc0dEXf4e1D2gfn/swjDqzy0Mfe/9b3ttRjc1i4ok5U+mR1nFTeiGEEJElw5sIic1ipmeadidiZTj3ODWnwKBjtY93rQnf44p2TDvegFW/0T45+XdQcHWXx67ZUcXD73wNwP+eM4px/bOj0aIQQojvkeFNhCxw00LY3/c27Efa7zvfC+/jCs3edVhfX4CCCgXXwEm3dnnovrpmbnphI6oKs6fnc9HkflFsVAghRFsyvImQReyO08DwtnsteN3hfexkV7kVnr8CxedCHXU2nPNgl7tZOD0+frGimPoWD5MGZvP788ZGuVkhhBBtyfZYbQT2Jwv2+GDfqK+nLp6z2u6yENas3LGQnovSVIW671MYMlN3j3prol0XlayDe+HZi1FcDnwDjka5+G+gmLQ7Tjt53P95dQtbyhz0Srey5MqpWM0mnJ44fF4h1kmWsbKM0GOiZhmhR6Nk6ZXUw1tRURFFRUX4fD5A2yTW6Qzu7JHL5dK1HZCeunjN6p2m/RiVHWgOe1bKkBOxbH0Z747VePserbvHUGqiXRfRrKZqbCsuwtRYgT9nNA3n/h2b3wxd/Ny/WFzGS8XfYVLggYvH0suu4HK54u95halOsoyVpbdOsmJXJ1nta/RK6uGtsLCQwsJCHA4H2dnZ2Gw27HZ7t+sDk7bNZgvqm6anLp6zBvTSVtavbfJgs9nCmzXix7D1ZSx7P8RivyuqzysWdRHNcjXAK3NRDuxCzc6HOa9gtfbqsmbTvoPc86Z2p+9vzhjFKWP7x+fzClOdZBkrywg9JmqWEXo0QpYMb2GiKErQk3OgJhp18ZqVl5UKQGWDK/xZw07RjinfBM21kJ6jq8dQaqJdF5EsrwtWzoHyjZDWG2Xuq5A9AMXp7LSmrsnNghUbcPv8nDEuj/knDWt3TNw8rzDXSZaxsozQY6JmGaHHeM8Ktq+25IYFEbK+rTcshHGpkIDMvpA3HlBlyRC9/D7453Ww+wOwZsCVL3e5ewKAz6/yy+dL2F/v5KicdO6/dFJI/5ERQggRXjK8iZAFbliobnTh84dxl4WAQ2ff2Pl++B870akqvHkrfPUqmFLg8uUwYOoRSx5avYOPvq0hNcXME3MLyLKnRKdXIYQQ3SLDmwhZ7wwbZpOCz69S2xSBJT2Gnar9vvO9Tu+IFEew5j5tBwUUuHjp4UG4C29vraDo/Z0A/OmSiYzMy4xCk0IIIYIhw5sImdmk0Cfj0Nm3hghcOh00Q9sqq2E/VG8P/+Mnqk+WwAf3aR+ffT+Mv/iIh++qbuTXL24C4GfHD+X8Sf0j3aEQQggdZHgTYdG61lskhrcUOww+XvtYdlvonpLl8NZt2senLIbpPz/i4c1uL/OXF9Pg8nL0kJ7cdvboKDQphBBCDxneRFjkBm5aaIjQTgiyVVb3ffUavHaj9vGMG+DEW454uKqqLHplM19XNtIn00bR7KmkmOU/DUIIEa/kv9AiLAJn3qoiceYNDg9vez4GT5i34UokO9+HV64F1Q9T5sLpd3e57VXA0+v28tqm/VhMCkuunNo6iAshhIhPMryJsGhdLiRSw1vuGMjoC94W2PdpZDIMzlS2HlZeCT43jL0Aznv0Bwe34tKD/HHVNgB+d/YYjh7SKxqtCiGECIEMbyIsciM9vCmKXDo9ksotWF+6EsXTrL1OF/8NTOYjllQ5nNz80ha8fpXzJvXnmuOHRKdXIYQQIZHhTYRFXqTf8wYyvHWlduehjebrUfOP0dZys9iOWOLx+bnh+RJqGt2MzMvgvosnyEK8QghhEDK8ibDIzYzgUiEBR52s/V6xGRqrIpdjJAf2wDPnoTRV4c8dB7NXgjX9B8vue3M7X+w5QLrVzONXTiXdJjvlCSGEUch/sdsIbC4b7PHB1Oiti/esPhlWAA40e3B7fVgtR75kpysrPQf6TUIp34S68z3UkRfE7Wuoty6omvrvtMHNUYaaMwrnpS9gt2X/4ELG//lyP//30W4A7r1wDENz0iP+Oibcay9ZMc8yQo+JmmWEHo2SpVdSD29FRUUUFRXh8/kAcLlcOJ3B3cnocrl0XW7SUxfPWalmFYtJwetXKa9rbL37NNxZlsEnklK+Cf837+AafGZcv4Z667pV01iJ7bkLMR0sxd9zKK7LX8RlyURxHfnM5zdVjfz25c0A/Pz4wcwcmoXrB2p09xiGmmjXSZaxsvTWSVbs6iSrfY1eST28FRYWUlhYiMPhIDs7G5vNht3e/WUSApO2zWYL6pump84IWTkZViocLg66VAZ383UMOmvkafDpXzHv+RCb1Rq3r6Heum7VNFXDystQDuxG7TEI5erXsWUNQHU6j1jncHq46aWtNHt8HD+sN785czRejzt+nleM6yTLWFlG6DFRs4zQoxGyZHgLE0VRgp6cAzXRqIv3rNxMOxUOFzWNwf0LJKisQcdCShpKUxWmmu0og6bG7Wuot+6INc118OxFULMDsgagXP069MgHVT1inaqq/OalL9ld00T/bDt/mTWFFIsZnzdOnlec1EmWsbKM0GOiZhmhx3jPCravtuSGBRE2OZkRXqgXtLsoh5wAgHn3msjlxCNnvTa4VW6BjDy46jXoOaRbpU98sIu3v6rEajaxZE4BvTO6f1lbCCFEfJHhTYRNVO44hdYlQ0x7PohsTjxxOmD5JVC+EdJ6a4NbzvBulX78bQ33v7UdgDvOH8fk/B6R61MIIUTEyfAmwqZP1Ia3UwEwla6DxsrIZsWDwBm37z4Hew+46t+Q272N4/cfbOHG50vwq3BpwUBmTc+PbK9CCCEiToY3ETa50bhsCtBnJOrAo1H8Hih+JrJZsdZyAJZdCGXrIbUnXP0a9J3QrVKX18cvVmygrsnNuP5Z/OHC8SG9x0IIIUR8kOFNhE3ULpsCTL9O+734KfB5Ip8XC811sOwC2L9Bu1R69evQb1K3y+98/Ss27TtIdmoKT8wpwJ7SvbX3hBBCxDcZ3kTY9InWmTeAsRegpvdBaSiHba9FPi/ammvhmfOhfBOk5cDV/+n2GTeAF9fv47nPSlEUePSKyeT3Sotgs0IIIaJJhjcRNn0ytbXdqhtcIa0c3S1mK95Jc7WPP/9bZLOirakanjkPKjdDei789A3IG9vt8i1l9Sx+dQsAv/rxSE4elRupToUQQsRAXA5vS5YsYejQodjtdgoKCli7dm236j7++GMsFguTJ0+ObIOiU4Etstw+P44Wb8TzvJOvQjVZoPQTKP8y4nlR0ViJ7fmfoFR9BRl9tcGtmzcnABxsdjN/eTFur58fjc7lhlO6d0eqEEII44i74W3lypXcfPPN3H777ZSUlDBz5kzOOussSktLj1hXX1/PVVddxamnnhqlTsX32VLMZNu1dZ+rGoLbZkyXzL4w5nzt48+XRj4v0g6WwtPnYKr9GjWzP1yzCvqM7Ha5z69y88pNfHeghUG90nj4ssmYTHKDghBCJJq4G94eeughrr32WubNm8eYMWN45JFHyM/P5/HHHz9i3fXXX8/s2bOZMWNGlDoVnYnKQr1tBW5c2PyS9gZ/o6raBv93Okrtt/izBsBP/wO9hwX1EEs+2M0HX1djTzHxxJwCstNSItSsEEKIWIqr7bHcbjfFxcUsWrSo3Z+ffvrprFu3rsu6p556ip07d7J8+XLuvvvuH8xxuVzt9hRzOBzA4f3JuitwfLDv79JTZ5SsnPQUdlZDlcPZrfqQn9fA6dB3AkrFZtQNz8Lxv4xcVqTq9n0Oz12G4jyI2mc0rktWYOs5FILIe2dbJUs+3APAHy+awJh+mT+Ya5SfqUTsUbKSo8dEzTJCj0bJ0iuuhreamhp8Ph95eXnt/jwvL4+KiopOa7755hsWLVrE2rVrsVi693Tuvfde7rzzzg5/7nK5cDqDu9zncgW3j2codUbI6p2mfQ/2H2jq9msZ6vMyT7kG65sLUb/4G64p14Kp6yUxovkadqfOtPNdrK/OQ/G24O9fgOuSZ3EqaRDEhsWldc38+sVNAMw+egBnjekdtdc+0jXRrpMsY2XprZOs2NVJVvsaveJqeAv4/gugHtp0+/t8Ph+zZ8/mzjvvZOTI7r836LbbbmPhwoWtnzscDvLz87HZbNjt9m4/TmDSttlsQX3T9NQZJSsvOxWAA05ft17LsDyvKbNQ1/wBU/0+7KVrYPQ5kcsKZ92XL8K/F6D4vajDTkW5bBm2lDRUp7PbWS1uHze9tBWH08vkgVn8/rzx2Lq5nptRfqYSsUfJSo4eEzXLCD0aISthhrecnBzMZnOHs2xVVVUdzsYBNDQ0sH79ekpKSrjhhhsA8Pv9qKqKxWLh7bff5kc/+lGHOpvNhs3WcWNuRVGCnpwDNdGoM0JWn4zDC/V2tzbk52VNg6lXwcePonzxNxhzbuSywlX36ePw30NvDxh/CcqFj4PFCof+odKdLFVVuf3VLWyvaKB3hpVHLp2ALcWccD9TidqjZCVHj4maZYQe4z0r2L7aiqsbFqxWKwUFBaxevbrdn69evZrjjjuuw/FZWVls3ryZjRs3tv6aP38+o0aNYuPGjRxzzDHRal0c0idTWy6kyhGlGxYCpl0Ligl2rYHqHdHNDobfB2//z+HBbfr1cPHftMEtSMs+2cu/SsowmxQemzWFvKyO/yARQgiReOLqzBvAwoULmTt3LtOmTWPGjBksXbqU0tJS5s+fD2iXPMvKyli2bBkmk4nx48e3q8/NzcVut3f4cxEdOYfWeqtujPLw1nMwjDwLdryhLdp7zgPRze8OZz28Mg++eVv7/JTFcOItoONfX+v31PGH/3wFwG1njebYo7r/PjchhBDGFnfD2+WXX05tbS133XUX5eXljB8/nlWrVjF48GAAysvLf3DNNxE7gcumVY4YDBLHXKcNb5ueh1N/D/as6PfQldqd8PwVUPM1WOxw/mMw8VJdD1XV4GTBig14/SrnTuzHtScMDXOzQggh4llcXTYNWLBgAXv27MHlclFcXMyJJ57Y+rWnn36aNWvWdFl7xx13sHHjxsg3KToVuGzqcHpxenzRDR96EuSMAncjbFwR3ewj2fk+/O0UbXDL7A/XvKl7cPP4/NywooSqBhcjcjP4008mhvS+CSGEEMYTl8ObMK5MmwWrRfuxqo7WQr0BiqKdfQN4757Yv/dNVTGv/zusuES7ZDpgGlz3PgyYqvsh7121nc/31JFhs/DE3ALSbXF38lwIIUSEyfAmwkpRFHKjvctCW1OugkHHgbtBu0wZq10XPE54/ZdY312Movpg0mxtn9LMvrof8t8by/jHx7sBePCySQzrkxGuboUQQhiIDG8i7NouFxJ1Fitc8Rwcdar23rJ37gCft/XLei8xBlW3fyMsPRml5FlUxYR6+t1w4RJI6f4agt+3vcLBolc2A7Dg5GGcMU7/ECiEEMLY5JqLCLvcrMDwFqO7H9N6wpyXwNOsbTHl94JZ+1HvbH2/7uhWnc8Dax+ED+8Hvxc1vQ/us/+CdexZuu4oDahv8XD9s8W0eHycMDyHX58+SvdjCSGEMD4Z3kTY9YnlZdMAkxlMVnA7wOcCVO1MXKRUbYN/XQ/l2jZVjL0AznkIvyk9pIf1+1UWrtzI3tpmBvRI5S+zpmA2yQ0KQgiRzGR4E2EX08umbZWth48e0gaqpmq49BltqOpKQwW8dTuUb9SW9jhmPpx135Ez/D745DF4727wucHeA855EMb/RPt6iGuvPfb+t7y7vQqrxcQTcwrolR78Yr5CCCESi7znTYRdbpZ2hiumZ95Au2zabzKc9gftc3ejNmx1xeuC9ByYeQv0/YFFnlVVWwLkH2fC6t9rg9uIM6DwM5hwSUiXSQPe31HFw+98DcDdF45nwsDskB9TCCGE8cmZtzYCm8sGe3wwNXrrjJTVJyOwRZbzBx8jos9r+I+1X6gor85HUVVU50FI7Yna2b9begyCMw+daSt5FlC1Ie1QnqIoWp7fC/+8DmXrP7WvWTPhzD/C5Dna0NamRu9rv7e2iZueL0FVYfb0fC4tGHjEx0n0n6lE61GykqPHRM0yQo9GydIrqYe3oqIiioqK8Pm0szEulyvoLYZcru5vwB5qnVGyeti0uqoGZ7dez3A9L0VRurixQDtGVRQUvwe1qRosNkhJA1NK986SqSp4W8DrRDGlQPV2VEsqvklX4pm+ALL6g6vjmUY9z+1gYzPzV2zF4fQycUAWvz1tWMReR6P8TCVij5IVuzrJil2dZLWv0Suph7fCwkIKCwtxOBxkZ2djs9mw27v/pvbApG2z2YL6pumpM1LWgN7aAFXb5CHFajviG+yj+bywZqCaUlD8HvA6wetEVSyQkqr9Ur53Nk71g6cF/F4UbwuK6geTBVVRYNrPYNxFmNN6Yw5jj36/n3tXb2V7ZSO9M6w8MbeArIzUH6xL9J+pROtRspKjx0TNMkKPRsiS4S1MFEUJenIO1ESjzihZORlWFAV8fpWDLR5yMo68zEbUnpfJDKm9UFUviqcFPC0oqldb0NfdqJ2FU33aL59bG/Bc9a3lqmJGsaajWFJh+s8j0uOzn5by+uZKzCaFx2ZNpX+PtO49Nx1ZemuMkGWEHiUrOXpM1Cwj9BjvWcH21ZYMbyLsLGYTvdOt1DS6qXK4fnB4iypFASUF7FawZWo7IXiawe8Bv7vtgdqZOLMN1WQB06EzdCH8ZfshX+yp4+43tgGw6MxRzBjWO2JZQgghjEuGNxERfTLt2vDW4GQsWbFup3OKCaxp2i+fR7sRQTFrZ+jMKWBJhbRerTcgRFKlw8mCFRvw+lXOGpfLtScMjXimEEIIY5LhTUREn0wb28pjvNabqxHqdh3+/MBeqPgSUntqd5a+cwc4yuHiJ7VhzZwC5V9qx7qboLlG+9ycAn1GR6xNt9fPL5YXU93gYlReBnefPyak0+lCCCESmwxvIiJiujl9wP4SeObc1k+Vt28HQJ00Cy56Ahoqof679jVPzjz8cflG2PwSZOfDzZsj1uZd/9nKhtKDZNktPDGngDRrV7dACCGEEDK8iQgJbJEV0zNvQ2fCHW1uOPj+5c+LHu9Y0+b4NoVhbuywF9fvY/mnpSgKPHrFFIbkpAe9XI0QQojkIjssiIjIjYfhLc59+d1BFr+6BYCbTx3JKaNzY9yREEIII5DhTUREbmZgiyw5i9SZ2kYX858txu318+Mxudz4o+GxbkkIIYRByPAmIiIuLpvGKa/Pz43Pl7C/3snQnHQeunwypiMsZCyEEEK0JcObiIi4uGEhTv35rR2s21lLmtXMk3MLyLKnxLolIYQQBiLDm4iIwJm3ZrePRpc3xt0cpnc7klC2MWnrtU37WfqhtnzJ/ZdMYmReZlgeVwghRPKQu03bCOxPFuzxwdTorTNaVprVTLrVTJPbR5XDSXpOesSygqnx+/26svTWte3xq3IHt768CYD5Jx3F2RP6dnhMo32f4zHLCD1KVnL0mKhZRujRKFl6JfXwVlRURFFRET6fD9DOrgS7TIPL5dK1oKqeOqNl5WRYaapr4btaB/0yul67zGjPS0/dwRYP1y9bj9Pj5/hhvbjhxMFd/qwl6usRq9deshI3S2+dZMWuTrLa1+iV1MNbYWEhhYWFOBwOsrOzsdls2O32btcHJm2bzRbUN01PnRGzcrPs7K1rod6ldvm6GvF5BVtnSbFy63Nf8t1BJ/k9U3ls9lTS06wx7zFRs4zQo2QlR4+JmmWEHo2QJcNbmCiKEvTkHKiJRp3RsnKztIGtusF9xMcx2vMKtu6h1V+z9psa7Ckmnpw7jZ7ptrjpMVGzjNCjZCVHj4maZYQe4z0r2L7akhsWRMTIHafw361VPP6BdoPCny+ZxNj+WTHuSAghhNHJ8CYiJtnXettR0cDt/94GwHUnHsX5k/rHuCMhhBCJQIY3ETHJvMtCfbOH658tptnj4/hhvbn1jFGxbkkIIUSCkOFNREyynnnz+VV++UIJe+ua6Z9t5y+zpmAxy181IYQQ4SH/RxERk6yb09//1g4++Loae4qJv14+gV7pnd9ZKoQQQughw5uImMDwVtvkxuPzx7ib6Hht036e+GAnAH+6eCJj+8kOCkIIIcJLhjcRMT3TrFgObbhe05j4Z9+27q9v3UHh+pOO4vzJcoOCEEKI8JPhTUSMyaSQk5Ecl05rG11ct6wYp8fPSSP7cOsZo2PdkhBCiAQlw5uIqNysQ2u9ORJ3ePP4/BQ+t4Gygy0M6Z3GX66Ygtmkf/FFIYQQ4khkeBMR1Sdw5i2BL5ve88Y2Pt1VR7rVzNKrppGdlhLrloQQQiQwGd5ERCX6mbcX1+/j6XV7AHj48smMzJMbFIQQQkSW7G3aRmBz2WCPD6ZGb51RswLveatqcHb6eEZ9XgAlpQdY/K8tANx86ghOG5vX7ph46DEZs4zQo2QlR4+JmmWEHo2SpVdSD29FRUUUFRXh8/kAcLlcOJ3B7Qbgcrl0bS6rp86IWT3t2sndivrmLl9bIz6vCoeT654txu3zc+roHH5+/MBOn1+yfJ/jLUtvnWQZK0tvnWTFrk6y2tfoldTDW2FhIYWFhTgcDrKzs7HZbNjt9m7XByZtm80W1DdNT51Rswb0ygCgtsnb6WtrxOfV4vbxyxfXU9PoZlTfTB69Yippto5/lWL92idrlhF6lKzk6DFRs4zQoxGyZHgLE0VRgp6cAzXRqDNiVp8sbWCrbuj6XyVGel4Av/3nZjaXOeiVbuXvV00jw971DQrJ8n2Otywj9ChZydFjomYZocd4zwq2r7bkhgURUW23yArl+n68WLJmJ69v2o/FpLDkyqnk90qLdUtCCCGSjAxvIqICNyy4fX7qWzwx7iY0b39Vyf1v7QDgzgvGcexRvWPckRBCiGQkw5uIKHuKmexU7bKikXdZ+LqykYUrNwJw1YzBXHnM4Ng2JIQQImnJ8CYiLnDptMqgw1tdk5sFL3xJk9vHjKN68z/njo11S0IIIZKYDG8i4vpkHl7rzWjcXj8LVmyg7KCTQb3SWHLlVFLM8tdGCCFE7Mj/hUTEtb1pwUhUVWXxq5v5bHcdaVYzf7uqgJ7p1li3JYQQIsnJ8CYiLvfQciFG2yJr6Ye7eHH9d5gUeOiScbL1lRBCiLggw5uIuEGHltPYVuGIcSfd99bWCu7773YAFp8zlpNG5MS4IyGEEEIjw5uIuOlDewFQvPcAbq8/xt38sC1l9dz8wkZUFeYeO5ifHid3lgohhIgfMryJiBveJ4OeaSk4PX627K+PdTtHVFHv5NpnvqDF42PmiBz+97yxIa2CLYQQQoSbbI/VRmB/smCPD3bnAD11Rs5SFDh6SC/e/qqSz3bVMiW/R8SyQqlpdnuZ98wXVDpcjMjN4LHZUzCblLjqUbISo0fJSo4eEzXLCD0aJUuvpB7eioqKKCoqwufzAdomsU5ncMtZuFxd79kZ7jojZ00ZmMnbX1Xy6c4afnrMgIhm6anxqyq/fHEzW/Y76JmWwpIrJmDFh9PpO2JdNHuUrMjXSZaxsvTWSVbs6iSrfY1eST28FRYWUlhYiMPhIDs7G5vNht1u73Z9YNK22WxBfdP01Bk96/iRefD2t2zYV0+K1YbZpMTV87rvze28u70Gq9nE0rkFDO/XM6SsSPQoWYnTo2QlR4+JmmWEHo2QJcNbmCiKEvTkHKiJRp2Rs8b2yyLDZqHB6WVHZQPj+mdHLCvYmmWf7OHJD3cB8OdLJnL00I57lsa6R8lKvB4lKzl6TNQsI/QY71nB9tWW3LAgosJiNlEwWDub9fnuuhh3c9h/t1Twv69tBeCW00dy4ZQBP1AhhBBCxJYMbyJqAkuGxMvwVry3jpteKEFVYfYxgyg8ZXisWxJCCCF+kAxvImqOaTO8hXKXTTjsrG7k2mfW4/L6+fGYXO46f1xIp7CFEEKIaJHhTUTNhIHZ2Cwmapvc7Kxuilkf1Q0urv7H5xxs9jA5vwd/nTUVi2w2L4QQwiDk/1giamwWM1MG9QBid+m0yeXlmqe/4LsDLQzpncb/XT2NVKs5Jr0IIYQQesjwJqLqmEN3cn6+uzbq2R6fn5tf2sLW/Q5yMqw887Pp9M6wRb0PIYQQIhQyvImoCrzv7bMov+/N51f5zUtf8tHOOlJTzPzf1UczuHd61PKFEEKIcJHhTUTVlEE9sZgUyuudfHegJSqZfr/K7/65mX9v2o/FpFA0ewqT2mzRJYQQQhhJXA5vS5YsYejQodjtdgoKCli7dm2Xx3700Uccf/zx9O7dm9TUVEaPHs3DDz8cxW5FMFKtZiYO1Bbo/SwK73tTVZU7X9/KyvX7MClw/8XjOGV0bsRzhRBCiEiJu+Ft5cqV3Hzzzdx+++2UlJQwc+ZMzjrrLEpLSzs9Pj09nRtuuIEPP/yQbdu2sXjxYhYvXszSpUuj3LnorulRet+bqqrc9+Z2nvlkL4oC918yiTPHyeAmhBDC2OJueHvooYe49tprmTdvHmPGjOGRRx4hPz+fxx9/vNPjp0yZwqxZsxg3bhxDhgxhzpw5nHHGGUc8Wydi65goLdb7yDvftG57dc+FE7h4quyeIIQQwvjiam9Tt9tNcXExixYtavfnp59+OuvWrevWY5SUlLBu3TruvvvuLo9xuVztNoR1OBzA4c1luytwfLBvvNdTl0hZUwf3QFFgT20zFfUtZFsJe9YTH+zk0Xe/AeD3545h1vT8qL6GeuskKzl6lKzk6DFRs4zQo1Gy9Iqr4a2mpgafz0deXl67P8/Ly6OiouKItQMHDqS6uhqv18sdd9zBvHnzujz23nvv5c477+zw5y6XC6fTGVTPLpdL18r8euoSJcsKjM7LYFtFI+u+qeJHw7PDmrX8s3386b/a4Lbw1KOYVdCv9fsazddQb51kxa5OsoyVpbdOsmJXJ1nta/SKq+Et4PsvgKqqP/iirF27lsbGRj799FMWLVrE8OHDmTVrVqfH3nbbbSxcuLD1c4fDQX5+PjabDbvd3u0+A5O2zWYL6pumpy6ULCDorGBrgq07f9IA/Op+9jvc2O32sGSpqsorG8p4uaSCUXmZzD4mn6tmDGlXE63vl946yUqOHiUrOXpM1Cwj9GiErIQZ3nJycjCbzR3OslVVVXU4G/d9Q4cOBWDChAlUVlZyxx13dDm82Ww2bLaOi7MqihL05ByoiUad3qzAQBpMnZ6aYOrmnXgUc2YMxqQo2A/tcBBKlqqquH0qZ47vy5nj+2I1m7BaTB0eM5rfL711kpUcPUpWcvSYqFlG6DHes4Ltq624umHBarVSUFDA6tWr2/356tWrOe6447r9OKqqhjTRisgzKwpurx+nx4c/hOv+oH2/G5xemlxe3F4/ZpOCLcUc0l8MIYQQIl7F1Zk3gIULFzJ37lymTZvGjBkzWLp0KaWlpcyfPx/QLnmWlZWxbNkyAIqKihg0aBCjR48GtHXfHnjgAW688caYPQfxw0wmBRVt5wOPz4/Nom9/Ub8K9S0ePD4/ANmpKdhTZK9SIYQQiSvuhrfLL7+c2tpa7rrrLsrLyxk/fjyrVq1i8ODBAJSXl7db883v93Pbbbexe/duLBYLw4YN47777uP666+P1VOIC2t2VPHTp7444jFPXXM0p4yK7Lpnn+2qZemHu9hcVk9Vg4sn5xZwxri+AFjNJlr8PjxeFdv3fhKf/WQPT364i6oGFyPzMvj9ueOYfmiJEYBH3vmaR9/9tl1NToaV9YtPi+jzEUIIIWIt7oY3gAULFrBgwYJOv/b000+3+/zGG2+Us2ydOPao3nx++6lw6IrkGY98yOxjBnH1cUNaj+mVZo14H80eH2P6ZXHptIHMX76h3desFhMtHh/uQ2fNAl7ftJ+7/vMVf7hgPNOG9GTFZ6X89KnPWb3wJAb0SAXA54ej+qTz2KwpmBSF7NQUrJa4eheAEEIIERFxObyJ0NlTzNhTzKiqSkW9kwPNHqYN6UVuZvfvpg2HU0bldnl2L8WsDVtev4oKBN6h9vePdnPZtHyumD4IgP89bxwffl3N8k/38pvTR9Hk9uL0+DArCnlZdnqkWTGb5P1tQgghkoMMb0lg6/56ACYMyA66tuj9byl6/9sjHvP0NdPbXdLsLrNJwWxS8PlVHC0eUq1mUGFLWT2/OGlYu2NnjujDF7vrqGl0BU4msu9AM2c9uharxcTk/B7cesZoBvVOC7oPIYQQwkhkeEsCW/c76JtlJyej4/IoP+TKYwZxzoR+Rzymb7b+s3l2i4kmtw+X14/L66e20Y3Pr9IrLQXQ7iR1enykWc1UNWiDm8WkMP2oXkwd3IOhOenUNnr463vfcPHj61j9qxPpmR75y8FCCCFErMjwlgS27HcwbkDWEY/x+dVOLz32SLPSI4LvjUu3WbBaTDg9fpzew8uGOJxe6ppcqKp2WdWvqiiKdjepzWLitDGH1/1TFIWpg3tw4p/X8MqG75g386iI9SuEEELEmgxvSWBrWT2XTcvv8OdX/+NzRvfNpKT0IJdMG9jpMZG8bBqQYjaRYjaRiQW7xYxZUahtcuHxaYOcokCj00telr11GZDv7wmXZrUwum8mu2uadPchhBBCGIEMbwnuQJOb/fXOTs+8fV3ZwEkj+/Di/Bld1kf6smlbiqKQlZrC+IHZfPldPedN6o+qQmqKmU9313Ha2K532XB5fXxb1cjRQ/QPkUIIIYQRyPDWRmB/smCPD6ZGb53erM1l2s0K4/tnt6t1OD0owDXHD+n0MQP7yWanppCdmtKt/trWBT5vcnnZW9vcety+uma2ltWTnZbSuuzHM+v28PZXlayYdwwA804YwsIXNzFxYDZTB/Xk+c9L2X+whdnTB7U+7j2rtnHqqD4M6JlGTaObx97/lkaXl4unDujyNYrm90tvnWQlR4+SlRw9JmqWEXo0SpZeST28FRUVUVRUhM/nA7RNYp1OZ1CP4XK5dG3DpKfuh2oURemwZ+tX5Q56p1s7nB37uqKBqYN7BpWvx+ayemb97bPWz+9+YxsAP5k6gAcunQRAXZO73YB37sT+HGjy8Jd3v6X60CK9//jp0Qzsmdp6TEW9k5tWbuJAs5te6Vam5Pfgn7+Y0e6YAJfL1fqXJJrfL711khW7OskyVpbeOsmKXZ1kta/RS1FDGf0ShMPhIDs7mwMHDpCd3f3lNFRVxel0Yrfbg/qm6anTmxWo/X7Nc5+VUtfs5oZThne7Rm9WJGr01EXz+6W3TrKSo0fJSo4eEzXLCD0aIau+vp6ePXtSX19PVtaRbyr8vqQ+8/Z9iqIEPUQEaqJRp6em7YDTtu6bqkaOH57T6WN1VaM3K9w1odRF8/ult06ykqNHyUqOHhM1ywg9xntWsH21JcNbkrrj/HGxbkEIIYQQOshmkEIIIYQQBiLDmxBCCCGEgcjwJoQQQghhIDK8CSGEEEIYiAxvSUDPWjJ615+J9ywhhBDC6GR4SwJ6lvLTu/xfvGcJIYQQRifDmxBCCCGEgcjwJoQQQghhIDK8CSGEEEIYiAxvQgghhBAGIttjtaGqalBvgg8cH+wb5/XUSZaxsozQY6JmGaFHyUqOHhM1ywg9GiVLr6Qe3oqKiigqKsLn8wHa0hNOpzOox3C5XLo2l9VTJ1nGytJbJ1mxq5MsY2XprZOs2NVJVvsavZJ6eCssLKSwsBCHw0F2djY2mw273d7t+sCkbbPZgvqm6amTLGNlGaHHRM0yQo+SlRw9JmqWEXo0QpYMb2GiKErQk3OgJhp1kmWsLCP0mKhZRuhRspKjx0TNMkKP8Z4VbF9tyQ0LQgghhBAGIsObEEIIIYSByPAmhBBCCGEg8p43Dt+u63A4gn5jo9PpxO12R7xOsoyVZYQeEzXLCD1KVnL0mKhZRujRCFkOh6O1PlgyvAENDQ0ADBo0KMadCCGEECKZNDQ0kJ2dHVSNooaySlyC8Pv97N+/n8zMzJDu/hBCCCGE6A5VVWloaKB///6YTMG9i02GNyGEEEIIA5EbFoQQQgghDESGNyGEEEIIA5HhTQghhBDCQGR4E0IIIYQwEBnehBBCCCEMRIY3IYQQQggDkeFNCCGEEMJA/h8d7zjA7V94sAAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 700x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "label_fontsize = 12\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(7, 8))\n",
-    "for Tr in Trs:\n",
-    "    \n",
-    "    Zs = results[Tr]\n",
-    "    idx_min = Zs.index(min(Zs))\n",
-    "    \n",
-    "    p = ax.plot(Prs, Zs)\n",
-    "    ax.set_ylim(0.25, 1.1)\n",
-    "    ax.set_xlim(0, 8)\n",
-    "    \n",
-    "    if Tr == 1.05:\n",
-    "        t = ax.text(Prs[idx_min] - 0.75, min(Zs) - 0.005, '$T_{r}$ = 1.05', color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))        \n",
-    "    else:\n",
-    "        t = ax.text(Prs[idx_min] - 0.2, min(Zs) - 0.005, Tr, color=p[0].get_color())\n",
-    "        t.set_bbox(dict(facecolor='white', alpha=0.9, edgecolor='white', pad=1))\n",
-    "    \n",
-    "    ax.minorticks_on()\n",
-    "    ax.grid(alpha=0.1)\n",
-    "    ax.grid(b=True, which='minor', alpha=0.1)\n",
-    "    \n",
-    "    #ax.invert_yaxis()\n",
-    "    ax.xaxis.tick_top()\n",
-    "\n",
-    "    ax.set_ylabel('Compressibility Factor, $Z$', fontsize=label_fontsize)\n",
-    "    ax.set_xlabel('Pseudo-reduced Pressure, $P_{r}$', fontsize=label_fontsize)\n",
-    "    ax.xaxis.set_label_position('top') \n",
-    "    \n",
-    "fig.savefig('zplot_1.png', dpi=200)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "eb85711e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6d810187",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "066cccec",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8aa591ad",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6671084b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dd836ae7",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1a0815fb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "295d521a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d4f8a96a",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ebb5b2ec",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "id": "5ad79a5d",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Attributes --------------------------------------\n",
-      "A             =  0.17\n",
-      "B             =  0.07\n",
-      "e_correction  =  21.28\n",
-      "Ppc_corrected =  628.22\n",
-      "Tpc_corrected =  356.31\n",
-      "Result ------------------------------------------\n",
-      "Tpr           =  3.1995\n"
-     ]
-    }
-   ],
-   "source": [
-    "z_obj = Z_factor()\n",
-    "z_obj.calc_Pr(H2S=0.07, CO2=0.1, P=2010, Ppc=663.29, Tpc=377.59)\n",
-    "\n",
-    "print('Attributes --------------------------------------')\n",
-    "print('A             = ', z_obj.A)\n",
-    "print('B             = ', z_obj.B)\n",
-    "print('e_correction  = ', round(z_obj.e_correction, 2))\n",
-    "print('Ppc_corrected = ', round(z_obj.Ppc_corrected, 2))\n",
-    "print('Tpc_corrected = ', round(z_obj.Tpc_corrected, 2))\n",
-    "print('Result ------------------------------------------')\n",
-    "print('Tpr           = ', round(z_obj.Pr, 4))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a938f470",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3a286c2f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8da7b6be",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/tutorials/utilities.py b/tutorials/utilities.py
deleted file mode 100644
index 68568ab..0000000
--- a/tutorials/utilities.py
+++ /dev/null
@@ -1,4 +0,0 @@
-def calc_Fahrenheit_to_Rankine(T):
-    if T is None:
-        raise TypeError("Missing a required argument, 'T' (gas temperature, °F)")
-    return T + 459.67
\ No newline at end of file