diff --git a/bmcs_course/4_1_PO_multilinear_unloading.ipynb b/bmcs_course/4_1_PO_multilinear_unloading.ipynb
index fc946a696e78b84ef7c94047c06174f494dc1033..eb7c7f67ae8eb468bb219be6a70f1e15d349c9c3 100644
--- a/bmcs_course/4_1_PO_multilinear_unloading.ipynb
+++ b/bmcs_course/4_1_PO_multilinear_unloading.ipynb
@@ -18,27 +18,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/rch/miniconda3/lib/python3.9/site-packages/traits/observation/_has_traits_helpers.py:70: RuntimeWarning: Trait '_wrappers' (trait type: List) on class ActionItem is defined with comparison_mode=<ComparisonMode.equality: 2>. Mutations and extended traits cannot be observed if a new container compared equally to the old one is set. Redefine the trait with List(..., comparison_mode=<ComparisonMode.identity: 1>) to avoid this.\n",
-      "  warnings.warn(\n",
-      "/home/rch/miniconda3/lib/python3.9/site-packages/traits/observation/_has_traits_helpers.py:70: RuntimeWarning: Trait '_wrappers' (trait type: List) on class ActionItem is defined with comparison_mode=<ComparisonMode.equality: 2>. Mutations and extended traits cannot be observed if a new container compared equally to the old one is set. Redefine the trait with List(..., comparison_mode=<ComparisonMode.identity: 1>) to avoid this.\n",
-      "  warnings.warn(\n",
-      "/home/rch/miniconda3/lib/python3.9/site-packages/traits/observation/_has_traits_helpers.py:70: RuntimeWarning: Trait '_wrappers' (trait type: List) on class ActionItem is defined with comparison_mode=<ComparisonMode.equality: 2>. Mutations and extended traits cannot be observed if a new container compared equally to the old one is set. Redefine the trait with List(..., comparison_mode=<ComparisonMode.identity: 1>) to avoid this.\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%matplotlib widget\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
-    "from bmcs_cross_section.api import PullOutModel"
+    "from bmcs_cross_section.pullout import PullOutModel1D"
    ]
   },
   {
@@ -51,13 +38,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
     "A_f = 16.67 # [mm^2]\n",
     "A_m = 1540.0 # [mm^2]\n",
-    "p = 1.0 #\n",
+    "p_b = 100.0 #\n",
     "E_f = 170000 # [MPa]\n",
     "E_m = 28000 # [MPa]"
    ]
@@ -73,25 +60,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 29,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "REGENERATE DOMAIN\n",
-      "REGENERATE DOMAIN\n",
-      "REGENERATE DOMAIN\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "pm = PullOutModel()\n",
-    "pm.mat_mod_.s_data = \"0, 0.1, 0.4, 4\"\n",
-    "pm.mat_mod_.tau_data = \"0, 800, 0, 0\"\n",
+    "pm = PullOutModel1D()\n",
+    "pm.material_model = 'multilinear'\n",
+    "pm.material_model_.s_data = \"0, 0.1, 0.4, 4\"\n",
+    "pm.material_model_.tau_data = \"0, 8, 0, 0\"\n",
     "pm.sim.tline.step = 0.01\n",
-    "pm.cross_section.trait_set(A_f=A_f, P_b=p, A_m=A_m)\n",
+    "pm.cross_section.trait_set(A_f=A_f, P_b=p_b, A_m=A_m)\n",
     "pm.geometry.L_x = 100\n",
     "pm.w_max = 2\n",
     "pm.n_e_x = 100"
@@ -99,13 +77,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8ff5aa5a95fc4543b9b09e65793c2014",
+       "model_id": "374902ae146a4c22876b0e305cc4334a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -123,13 +101,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e63e64be77934e39a3bb239662a1d0d8",
+       "model_id": "758c8168ddc54d69a81fe502e229786c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -145,22 +123,17 @@
       "text/latex": [
        "\n",
        "        \\begin{array}{lrrl}\\hline\n",
-       "        \\textrm{number_of_cycles} & n_\\mathrm{cycles} = 1 & \\textrm{[-]} & \\textrm{for cyclic loading}  \\\\\n",
-       "                \\textrm{maximum_loading} & \\phi_{\\max} = 1.0 & \\textrm{[-]} & \\textrm{load factor at maximum load level}  \\\\\n",
-       "                \\textrm{number_of_increments} & n_{\\mathrm{incr}} = 20 & \\textrm{[-]} & \\textrm{number of values within a monotonic load branch}  \\\\\n",
-       "                \\textrm{unloading_ratio} & \\phi_{\\mathrm{unload}} = 0.5 & \\textrm{[-]} & \\textrm{fraction of maximum load at lowest load level}  \\\\\n",
-       "                \\textrm{amplitude_type} & option = increasing & \\textrm{[-]} & \\textrm{possible values: [increasing, constant]}  \\\\\n",
-       "                \\textrm{loading_range} & option = non-symmetric & \\textrm{[-]} & \\textrm{possible values: [non-symmetric, symmetric]}  \\\\\n",
+       "        \\textrm{n_incr} & \\textrm{10} & & \\textrm{None}  \\\\\n",
        "                \\hline\n",
        "        \\hline\n",
        "        \\end{array}\n",
        "        "
       ],
       "text/plain": [
-       "<ibvpy.tfunction.loading_scenario.CyclicLoadingScenario at 0x7fdbc3ba7f40>"
+       "<ibvpy.tfunction.loading_scenario.MonotonicLoadingScenario at 0x7f172c444ae0>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -173,38 +146,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "text/latex": [
-       "\n",
-       "        \\begin{array}{lrrl}\\hline\n",
-       "        \\textrm{loading_type} & option = cyclic & \\textrm{[-]} & \\textrm{possible values: [monotonic, cyclic]}  \\\\\n",
-       "                \\textrm{number_of_cycles} & n_\\mathrm{cycles} = 2 & \\textrm{[-]} & \\textrm{for cyclic loading}  \\\\\n",
-       "                \\textrm{maximum_loading} & \\phi_{\\max} = 1.0 & \\textrm{[-]} & \\textrm{load factor at maximum load level}  \\\\\n",
-       "                \\textrm{unloading_ratio} & \\phi_{\\mathrm{unload}} = 0.0 & \\textrm{[-]} & \\textrm{fraction of maximum load at lowest load level}  \\\\\n",
-       "                \\textrm{number_of_increments} & n_{\\mathrm{incr}} = 20 & \\textrm{[-]} & \\textrm{number of values within a monotonic load branch}  \\\\\n",
-       "                \\textrm{amplitude_type} & option = constant & \\textrm{[-]} & \\textrm{possible values: [increasing, constant]}  \\\\\n",
-       "                \\textrm{loading_range} & option = non-symmetric & \\textrm{[-]} & \\textrm{possible values: [non-symmetric, symmetric]}  \\\\\n",
-       "                \\hline\n",
-       "        \\hline\n",
-       "        \\end{array}\n",
-       "        "
-      ],
       "text/plain": [
-       "<ibvpy.tfunction.loading_scenario.LoadingScenario at 0x7f4d73abd0e0>"
+       "'cyclic'"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "pm.loading_scenario.loading_type='cyclic'\n",
-    "pm.loading_scenario.trait_set(number_of_cycles=2,\n",
+    "pm.loading_scenario = 'cyclic'\n",
+    "pm.loading_scenario_.trait_set(number_of_cycles=2,\n",
     "                              unloading_ratio=0.0,\n",
     "                              amplitude_type='constant',\n",
     "                              loading_range='non-symmetric')\n",
@@ -213,25 +171,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "<ipython-input-7-a80ba1790c48>:1: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
-      "  pm.loading_scenario.plot(plt.axes())\n"
-     ]
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6edd2a79034b426fae337ea32d7ae37b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "pm.loading_scenario.plot(plt.axes())"
+    "fig, ax = plt.subplots(1,1)\n",
+    "fig.canvas.header_visible = False\n",
+    "pm.loading_scenario_.plot(ax)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -241,29 +207,29 @@
        "        \\begin{array}{lrrl}\\hline\n",
        "        \\textrm{A_m} & A_\\mathrm{m} = 1540.0 & \\textrm{[$\\mathrm{mm}^2$]} & \\textrm{matrix area}  \\\\\n",
        "                \\textrm{A_f} & A_\\mathrm{f} = 16.67 & \\textrm{[$\\mathrm{mm}^2$]} & \\textrm{reinforcement area}  \\\\\n",
-       "                \\textrm{P_b} & p_\\mathrm{b} = 1.0 & \\textrm{[$\\mathrm{mm}$]} & \\textrm{perimeter of the bond interface}  \\\\\n",
+       "                \\textrm{P_b} & p_\\mathrm{b} = 100.0 & \\textrm{[$\\mathrm{mm}$]} & \\textrm{perimeter of the bond interface}  \\\\\n",
        "                \\hline\n",
        "        \\hline\n",
        "        \\end{array}\n",
        "        "
       ],
       "text/plain": [
-       "<bmcs.pullout.pullout_sim.CrossSection at 0x7f8eacdf6530>"
+       "<bmcs_cross_section.pullout.pullout_sim.CrossSection at 0x7f172c3c3ef0>"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "pm.cross_section.trait_set(A_f=A_f, P_b=p, A_m=A_m)\n",
+    "pm.cross_section.trait_set(A_f=A_f, P_b=p_b, A_m=A_m)\n",
     "pm.cross_section # display the cross section parameters"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -271,17 +237,17 @@
       "text/latex": [
        "\n",
        "        \\begin{array}{lrrl}\\hline\n",
-       "        \\textrm{L_x} & L = 45 & \\textrm{[$\\mathrm{mm}$]} & \\textrm{embedded length}  \\\\\n",
+       "        \\textrm{L_x} & L = 100.0 & \\textrm{[$\\mathrm{mm}$]} & \\textrm{embedded length}  \\\\\n",
        "                \\hline\n",
        "        \\hline\n",
        "        \\end{array}\n",
        "        "
       ],
       "text/plain": [
-       "<bmcs.pullout.pullout_sim.Geometry at 0x7f8eacdf6470>"
+       "<bmcs_cross_section.pullout.pullout_sim.Geometry at 0x7f1720a92130>"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -299,7 +265,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
@@ -310,34 +276,34 @@
        "        \\textrm{E_m} & E_\\mathrm{m} = 28000.0 & \\textrm{[MPa]} & \\textrm{E-modulus of the matrix}  \\\\\n",
        "                \\textrm{E_f} & E_\\mathrm{f} = 170000.0 & \\textrm{[MPa]} & \\textrm{E-modulus of the reinforcement}  \\\\\n",
        "                \\textrm{s_data} & s = 0, 0.1, 0.4, 4 & \\textrm{[mm]} & \\textrm{slip values}  \\\\\n",
-       "                \\textrm{tau_data} & \\tau = 0, 800, 0, 0 & \\textrm{[MPa]} & \\textrm{shear stress values}  \\\\\n",
+       "                \\textrm{tau_data} & \\tau = 0, 8, 0, 0 & \\textrm{[MPa]} & \\textrm{shear stress values}  \\\\\n",
        "                \\hline\n",
        "        \\hline\n",
        "        \\end{array}\n",
        "        "
       ],
       "text/plain": [
-       "<ibvpy.tmodel.mats1D5.vmats1D5_bondslip1D.MATSBondSlipMultiLinear at 0x7f1f25718810>"
+       "<ibvpy.tmodel.mats1D5.vmats1D5_bondslip1D.MATSBondSlipMultiLinear at 0x7f1720d3c590>"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 38,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "pm.mat_mod_ # configuration of the material model"
+    "pm.material_model_ # configuration of the material model"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f184fee970b4427b91685ce451f3669a",
+       "model_id": "8f0a1b5efd8d4b94bfa3aa166d48fd75",
        "version_major": 2,
        "version_minor": 0
       },
@@ -350,30 +316,48 @@
     }
    ],
    "source": [
-    "_, ax = plt.subplots(1,1,figsize=(7,4))\n",
-    "pm.mat_mod_.plot(ax, color='green')"
+    "fig, ax = plt.subplots(1,1,figsize=(7,4))\n",
+    "fig.canvas.header_visible = False\n",
+    "pm.material_model_.plot(ax, color='green')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 45,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6872512485f74e85ac8f6c2f1ac0dca5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "c='red'\n",
     "pm.geometry.L_x = 200\n",
-    "pm.sim.run()"
+    "pm.reset()\n",
+    "pm.run()\n",
+    "pm.interact()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3399b8c10dc540369e2282ed2a5dad7c",
+       "model_id": "bd5b8702155d43d09659d82ce34e9222",
        "version_major": 2,
        "version_minor": 0
       },
@@ -386,8 +370,9 @@
     }
    ],
    "source": [
-    "_, ax = plt.subplots(1,1,figsize=(7,4))\n",
-    "pm.hist.plot_Pw(ax,0.68)"
+    "fig, ax = plt.subplots(1,1,figsize=(7,4))\n",
+    "fig.canvas.header_visible = False\n",
+    "pm.history.plot_Pw(ax,0.68)"
    ]
   },
   {
@@ -398,7 +383,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0aaabc9a67844b0b801d026243f8fb32",
+       "model_id": "7f35876c24b6445cb2053697ef53d55a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -413,8 +398,8 @@
    "source": [
     "_, ax = plt.subplots(1,1,figsize=(7,4))\n",
     "for t in np.linspace(0.,0.62,4):\n",
-    "    pm.hist.t_slider = t\n",
-    "    pm.hist.plot_sf(ax)\n",
+    "    pm.history.t_slider = t\n",
+    "    pm.history.plot_sf(ax)\n",
     "plt.show()"
    ]
   },
@@ -426,7 +411,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f8316fff884f47d4b59a27f8879206fc",
+       "model_id": "03f8aa88c1444458a747e1156b640a86",
        "version_major": 2,
        "version_minor": 0
       },
@@ -441,20 +426,20 @@
    "source": [
     "_, ax = plt.subplots(1,1,figsize=(7,4))\n",
     "for t in np.linspace(0.,0.62,4):\n",
-    "    pm.hist.t_slider = t\n",
-    "    pm.hist.plot_s(ax)\n",
+    "    pm.history.t_slider = t\n",
+    "    pm.history.plot_s(ax)\n",
     "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "cafa3ab8f561421e899e6f2b0ba7eff9",
+       "model_id": "a5d966e4f2c248f698b9b838cdd40746",
        "version_major": 2,
        "version_minor": 0
       },
@@ -469,20 +454,20 @@
    "source": [
     "_, ax = plt.subplots(1,1,figsize=(7,4))\n",
     "for t in np.linspace(0.,.99,5):\n",
-    "    pm.hist.t_slider = t\n",
-    "    pm.hist.plot_eps_p(ax)\n",
+    "    pm.history.t_slider = t\n",
+    "    pm.history.plot_eps_p(ax)\n",
     "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8b62d46e22af412cb0926afbb213a01e",
+       "model_id": "f372aca57f194f80982786ae22c298a5",
        "version_major": 2,
        "version_minor": 0
       },
@@ -497,8 +482,8 @@
    "source": [
     "_, ax = plt.subplots(1,1,figsize=(7,4))\n",
     "for t in np.linspace(0.,.99,5):\n",
-    "    pm.hist.t_slider = t\n",
-    "    pm.hist.plot_sig_p(ax)\n",
+    "    pm.history.t_slider = t\n",
+    "    pm.history.plot_sig_p(ax)\n",
     "plt.show()"
    ]
   },
diff --git a/bmcs_course/4_2_BS_EP_SH_I_A.ipynb b/bmcs_course/4_2_BS_EP_SH_I_A.ipynb
index 726710c52a8e5623bac409fc41752963a548d0e7..7113cec4d7cbda52f9ba98b6af72888aec79c078 100644
--- a/bmcs_course/4_2_BS_EP_SH_I_A.ipynb
+++ b/bmcs_course/4_2_BS_EP_SH_I_A.ipynb
@@ -1352,7 +1352,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 720x288 with 2 Axes>"
       ]
@@ -1427,7 +1427,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.2"
+   "version": "3.9.1"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/bmcs_course/4_3_BS_EP_SH_IK_A.ipynb b/bmcs_course/4_3_BS_EP_SH_IK_A.ipynb
index a30bf15531b9157888c5d4742dcc7561b23d3f49..dafd3186092b463fdc4a517dcd2f3e8986122118 100644
--- a/bmcs_course/4_3_BS_EP_SH_IK_A.ipynb
+++ b/bmcs_course/4_3_BS_EP_SH_IK_A.ipynb
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {
     "slideshow": {
      "slide_type": "skip"
@@ -97,7 +97,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {
     "slideshow": {
      "slide_type": "fragment"
@@ -106,7 +106,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle - Z - \\tau_{Y} + \\sqrt{\\left(- X + \\tau\\right)^{2}}$"
       ],
@@ -116,7 +116,7 @@
        "-Z - τ_Y + ╲╱  (-X + τ)  "
       ]
      },
-     "execution_count": 3,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -151,7 +151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {
     "slideshow": {
      "slide_type": "fragment"
@@ -160,7 +160,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle E_{b} \\left(s - s_{pl}\\right)$"
       ],
@@ -168,7 +168,7 @@
        "E_bâ‹…(s - sâ‚šâ‚—)"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -197,7 +197,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {
     "slideshow": {
      "slide_type": "fragment"
@@ -206,7 +206,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle E_{b} \\left(\\dot{s} - \\dot{s}^\\mathrm{pl}\\right)$"
       ],
@@ -214,7 +214,7 @@
        "E_bâ‹…(\\dot{s} - \\dot{s}__\\mathrm{pl})"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -245,7 +245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {
     "slideshow": {
      "slide_type": "fragment"
@@ -254,7 +254,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAM8AAAAaCAYAAAAQcgjDAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAIgElEQVR4Ae2c7XEUORCG1y4H4DMZmAzARIDJwEAEQAZQ/mX/oyADIALOZACOAEwGcBEAm4HvfWS1bmZWX7s7M7u33q6S9dVqtbrVrZZmYef6+nqyha0ENlUC5+fn+1rbhdKxyjt9rnO3S0wTnCgdd9u39c2UwKbrW+ubSnMvYtpT35tYe7cthdcyHgSpgY+Uf+kS2NY3TwK3SN+/E9r7KBl8TvQ1m6N4Oxa2iQjH26Xy+81R2/JmSmAT9K01HEo7hGTsXU4R8js+f6V+Tp2JX+sf5TNhm9qeg6/8LbgpiOE1Tx6YeJcavG3fOAn87/WtDf1TWnmmhBF9wQCUXqn8Q+lSqQjCfy+kF8oxvCTE8PbAVgeTHyl/lBx9g/dS2QMlwjvgu9JPjXvsav6P6igGHCz/mxJeANwWqI1FsuhoTNpC7qEy9nzzsCzekC3yP/LjkJvznL6OctHTgdI34Wd15cdEM42t1feo+oky22jM6G+qPgzJgcoY0RslHglqriAcGh+UWvv4hlrrbwvPGY+6sVYsMAswBYJynugwmlSI91H9KBuLDotSPYDabTPYZgl9QxTGnm/eNYg/ZIvSke135VHjULsZ2bxTNPGL+tY8o+qnyVysvAA/U9HBSdQAex9jI3xjXApaeLsei7iv5uI0EfF7fsyn2AzqhxZ4PDxEDcf3w+RfwkkZIGi9geYZdb5FGBeP9sqZ85YoMCnXynmL+l43eS3Az36tnDxtIqMnOfl18XbVYMZAmFADpuCWsYkOVsuljTAsalhd4sLLWXkXfen62PMtwLCdNi3ZRugQTi0EkkG1vtdNXhl+2HvhlFGZ05l9mHNCXfmx/0thG2MCHicPxkAIVruRn0KhyZjKKORUOXebZb0i5G8rOMfUlC2CUJ3N4EBl9DTPpvAjQzavvsPANS8cSzZ8o0RWd5U7R6ScE4j7zETl3IMYDqnmChHw9jSAB4BawxHqBEMJl38xRAhwX3n1pV+40OBRAXisOjE+ngMBFO9eblTlH9GzD2G/NOSu0jvmSw1XHw8djIEfNin8BfmozObjwh7aVO8LkEvLMPx8rbnUluS/gpEqfWsOZIDMAJ5/Xw+0ZjdB7k8FLzwYRPeN57nmREGmnGCklrw7vAU8jGdf6XcHIVoVUTYO4BSsOlaOkOc9bfAEeAGUwkWNMAVvUW2Aws+CaLH5ocujhfHLWv9RHWPntAXnnnIXZirHEbAe8GnDkOC1KfxBPiJrbpPtocrmWOCXdoy+LyjqW/Mjt/BC6nlDLr3pp3YxlbywpmXBbIA9gYGkIODtCuNAaZrC7LRbTP5Li2LT80KExaNwNloRhAdzDxmrhIKgeUd534q5Et1Pohs8ucqsk5iV1yYAns2w4ItThkcMcnhj0+KJOBEmPv9KeQAw2TK3S5oDPjHyGecEL0pXSmz0eSCrb9FDDkQAzQ0EH8hzVCjx4vsx6onKuZCshm+zAeSTg4A318kjiuYdOSbtiyzM47FPlZwHV54EjQsbQeV9ITLeNnNy3DwdXpDQfh0Zx/xHvh2jNWFgSM0TxobSxvrYTE+F3yuvNolyJ1vRD5uWslIwfnBVd2GF72MtQZ70VwByMe+ZRBd9jJITkIu3GXYOH7qXSuS1gJMI600NSvGidtZe5C1Ft9NelInHD3gYD5unZG02Dx4YYYb4kgUooWC8Fd6wKAyICQ8PR0jV94kD+SdK8MnaukAbJyVGG4xLdXMGLXxoKGFk8Gt3gBZOTxUn2wgt51lpFw9sTAzZeMXgHirNA1l9aw70CX1CcjNo+3KfnEdjoNvrZ4dFeUkyme8wGwjGkUAPeLsJhJlmLcQJUh2xMMEUzOlTBE+Ll5HgxVVmYywNng60ckZM/1fhovBawMiD06gdVIMnPpKyVV/zZMFwHA9qx9hYB07rpdKFEvWlQXQIWfkdGF4dxwj9XmjPy9yIvNj6pgUeAx7Gg3KsITfOjsdWGMEALZA26GAQWVrqZ6Pg+c17qurggxXIS3SauM2yxtnic99COE2KIWaTrsouXOq0Lcxnh05StoYnfjn5HjTWhxyR+Xu1IUvuYubEVExCUt+iwz02yE3lqpAtOdMSHSvgJZwoBbYDHsaD0O0OkBvHnWCiRaU8ul3YkqePxuItOW14WfushEczhTVDKAyQX8EueknFO9uGVPEGRA/PDTgDVx1+agB8W1/A1/hl+TRaWdlqHgwFWTR5YH08u089EfIaPeb0zTzNOSaiD28YqM3jpxs8G5sXnBNOtbTOgLenARgDXnXGs9KmPk4EBpAmauMSScgTTg6V8XhuAyjHINiUsd+1ceF2m1o5+NDGE4IbjFJlFuE8pPIZvoSfBY2BHkYJX9xTnEBUt5AHmtYX5s0QPRD+DJ7aFuZTY1OybbIBDgZB3n08oL150nDfQGYlSOpbA58pHYs37jsGrHGIe6nRT+Vj84L8ZqKqCHP/4fHvec7Ozv4oHVNepySeTpT2V82TeLjI8bAKPjXntVKQjcro8CTHp/V53LXTt/G3ilwyuVJ6Xpq7ibfrLetv5e5EiFjaKpuaMf5K+JDX5RQl1MnBKvgMp4x4JBzlVw+197h11XdOxoP1SW6c7OgZuSShi2fGQ5xr94Hk4DE7PKNDPg3XLofYeyZks8Er5JPvT4SmhFjht1zGVyFfO30X+B26m08bfFCfFiZq49kxpePoQqnq2LcxQ+Y1R+iQ8xtt5GLlWL4ufMZ4y7WxLqW10XeO16H7JIcfSoelebp4dvJgcFzQTguWN1q3vMAg31QWWED4FhUbu0Z8xtjLta2VvnOMDtkn/RFx8WoZwuDYfDG88B+AMEAIvIDxw8dVvK7EeN62DSiB265vrf9Q4sVwsvf9FF7z5JkIiQsn31+I87ew4RLY6nvCIRH7PWNX81G8fwGMo2/ySLy55AAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle \\left( K \\dot{z}, \\  \\dot{\\alpha} \\gamma, \\  E_{b} \\left(\\dot{s} - \\dot{s}^\\mathrm{pl}\\right)\\right)$"
       ],
@@ -262,7 +262,7 @@
        "(Kâ‹…\\dot{z}, \\dot{\\alpha}â‹…\\gamma, E_bâ‹…(\\dot{s} - \\dot{s}__\\mathrm{pl}))"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -314,7 +314,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {
     "slideshow": {
      "slide_type": "fragment"
@@ -323,7 +323,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle \\left( \\lambda, \\  - \\frac{\\lambda \\left(X - \\tau\\right) \\sqrt{\\left(- X + \\tau\\right)^{2}}}{\\left(- X + \\tau\\right)^{2}}, \\  \\frac{\\lambda \\sqrt{\\left(- X + \\tau\\right)^{2}}}{- X + \\tau}\\right)$"
       ],
@@ -336,7 +336,7 @@
        "⎝                    (-X + τ)                                     ⎠"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -433,7 +433,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {
     "slideshow": {
      "slide_type": "fragment"
@@ -442,7 +442,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/latex": [
        "$\\displaystyle \\frac{E_{b} \\left(\\dot{s} - \\dot{s}^\\mathrm{pl}\\right) \\sqrt{\\left(- X + \\tau\\right)^{2}}}{- X + \\tau} - K \\dot{z} + \\frac{\\dot{\\alpha} \\gamma \\left(X - \\tau\\right) \\sqrt{\\left(- X + \\tau\\right)^{2}}}{\\left(- X + \\tau\\right)^{2}}$"
       ],
@@ -462,7 +462,7 @@
        "    (-X + Ï„)                  "
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -485,7 +485,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
@@ -494,7 +494,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/latex": [
        "$\\displaystyle \\frac{E_{b} \\left(\\dot{s} - \\frac{\\lambda \\sqrt{\\left(- X + \\tau\\right)^{2}}}{- X + \\tau}\\right) \\sqrt{\\left(- X + \\tau\\right)^{2}}}{- X + \\tau} - K \\lambda - \\frac{\\gamma \\lambda \\left(- X + \\tau\\right)^{2} \\left(X - \\tau\\right)^{2}}{\\left(- X + \\tau\\right)^{4}}$"
       ],
@@ -518,7 +518,7 @@
        "  (-X + Ï„)             "
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -541,7 +541,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {
     "slideshow": {
      "slide_type": "fragment"
@@ -550,7 +550,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle - \\frac{E_{b} \\dot{s} \\sqrt{\\left(X - \\tau\\right)^{2}}}{\\left(X - \\tau\\right) \\left(E_{b} + K + \\gamma\\right)}$"
       ],
@@ -562,7 +562,7 @@
        " (X - Ï„)â‹…(E_b + K + \\gamma)"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -585,7 +585,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {
     "slideshow": {
      "slide_type": "fragment"
@@ -594,7 +594,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/latex": [
        "$\\displaystyle \\left( - \\frac{E_{b} \\dot{s} \\sqrt{\\left(- X + \\tau\\right)^{2}} \\sqrt{\\left(X - \\tau\\right)^{2}}}{\\left(- X + \\tau\\right) \\left(X - \\tau\\right) \\left(E_{b} + K + \\gamma\\right)}, \\  \\frac{E_{b} \\dot{s}}{E_{b} + K + \\gamma}, \\  E_{b} \\left(\\frac{E_{b} \\dot{s} \\sqrt{\\left(- X + \\tau\\right)^{2}} \\sqrt{\\left(X - \\tau\\right)^{2}}}{\\left(- X + \\tau\\right) \\left(X - \\tau\\right) \\left(E_{b} + K + \\gamma\\right)} + \\dot{s}\\right), \\  \\frac{E_{b} \\dot{s} \\left(K + \\gamma\\right)}{E_{b} + K + \\gamma}\\right)$"
       ],
@@ -612,7 +612,7 @@
        "⋅(X - τ)⋅(E_b + K + \\gamma)             ⎠      E_b + K + \\gamma    ⎠"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -855,7 +855,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {
     "slideshow": {
      "slide_type": "slide"
@@ -864,7 +864,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 720x288 with 2 Axes>"
       ]
@@ -934,7 +934,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.9.1"
   },
   "toc": {
    "base_numbering": 1,
@@ -956,5 +956,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/bmcs_course/4_4_BS_EP_SH_IK_N.ipynb b/bmcs_course/4_4_BS_EP_SH_IK_N.ipynb
index 2c13bd5acc281e4efa21d79daf521bf80b9df7ec..fe67d9e4107d4bbf2af172bf9b9bdc2c50806a31 100644
--- a/bmcs_course/4_4_BS_EP_SH_IK_N.ipynb
+++ b/bmcs_course/4_4_BS_EP_SH_IK_N.ipynb
@@ -31,7 +31,7 @@
    },
    "outputs": [],
    "source": [
-    "%matplotlib notebook\n",
+    "%matplotlib widget\n",
     "import sympy as sp\n",
     "sp.init_printing()\n",
     "import matplotlib.pyplot as plt\n",
@@ -140,7 +140,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAGAAAAAZCAYAAADOtSsxAAAACXBIWXMAAA7EAAAOxAGVKw4bAAADEklEQVRoBe2a7VHbQBCGZU8KYEIH0IGhg0AHkFQQ0wGe/LL/MdCBoQToADpISAeQCpKhA+d5NHca4ciyZmQJT7idWa/ua3f17t3e2jCYTqe3WZaN4EjHs9nsOTaS3BwC4HqOtrOSxsmAADwycFDqTI89IADmY80Me7CVTNQgkAJQA04fQykAfaBcYyMFoAacPoZSAPpAucZGCkANOH0MfWhihJLpknm/w9x95IS+lyZr+5iDL36P8fuMdEr7J7zH8xHyOu/t+AM7YhRJ2xf6ETtWybUBQMk9iwU8V4Y8oq2x8heKVfo778efHYzcwHN4F74Mvu4hT2l3StgQbDE64/lBY0h9+oU8gJ9h54yQd46XaVhuLD+Hhe6iciQnzHtcnvuG7Y/Y/oSPV7Ab5Tj48rUnn8Rijt0cfG3ybHb4AYuVdAIX43lP+Fh7ApyHQiPsEX/gOb6gQ29O+FP8bMKzO+8b7PEXhE4JG566HeRVhSH9Ogz9u6v8WXcCVKJy047GnlBUznV0bQfhl8d8jOzzfvqMzcqdTb8bwDQoXhdwJdUGwBXhhQY8uvM1dk6fO21rCH/cIKbKYid27WPQLw5mh1Xk+HfmGoxKWpmCWGTkTpBWPRlS8E1BC9uRaLvzdEJZRfvMKdJE1YQ2feg2v2bI5Wrnhu7OLmHsvcCariPn/HPxlhesDACT3FWmnYJQ5stea9xOpBH2ovHXVC9Dd6HjViLxAqK7G8KG5afVmGWn0o1gJaSfnYGP7kgG3cxQnDwH8MVfOsVGtm0FVC5k7M6pLgBWEQIalbnAiL4qP2M7zLtD5kZz7d1/fMFeXhQgBd1d72mzJKx84U26hA3tuNnMFk9Bt+/vJpSzMOZ3qGp//HvAYrHI2jJ67tWBHMHztvr+9/VgNJaHIWqtBFEu539TkZyoAQIbCQB2zPfm30jeH4kaILCpABxiK69COA1WS3+Qfd4FDV51O6fUXcKNPQbsV39Tpp2Xro0VvOOJmzoB7xjCdq+eAtAOv9ar8xREyog1rArT/wW1hrVaATiX/y/ISnHyF1j2E110yN5NAAAAAElFTkSuQmCC\n",
       "text/latex": [
        "$\\displaystyle \\left[\\begin{matrix}s_{\\pi} & z & \\alpha\\end{matrix}\\right]$"
       ],
@@ -195,7 +195,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle \\left[\\begin{matrix}\\tau & Z & X\\end{matrix}\\right]$"
       ],
@@ -227,7 +227,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHMAAABLCAYAAABDargmAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAI4ElEQVR4Ae2d7XEUORCGd13+fcXhqgtgyQBwBJgMwETAkQEUv+x/FGQARMBBBkAEBmfABXBVuFyXwN37CLVKs6v53NldaT1dJetb0+pX3ZJGmvX87Ozs7mw2+y6Xok/n5+ePUxlT2vYlICx+6KmL1JOVNz+IMt4o/GzJvY3ydxYUo8kO7IyhDT64pa+v9ehljD4ZO4cWkP9WDf0dxbMIiqfnYgS+suNtQwJaqM+P5FCuCintXSVBEaWR9Ig/MZjEW0mVEe5Dufu+8Df51z6Md0sOTbot903lKTuIVBcmj+SvdGxQgwVUUl+/yN2l73JB67qwPgRMBPtGD/pP/qX8JFhKN9C78LFSRvUZFC/l31vJ3PME9Rn5fpcD2FhRGnsez5mNBeNMPeDEx7/E6UthTMI6ppH5IYs5e6lf24rSd2TQmQaBqdZNGz+3PInV11A61aBZmSOGNlZaPd93ZICF6kRDwXSaqQdVNFNxTKsjhTEPlXyf1eqpLu2vo9WtzyikADI47cpr7znTN8zetAKUB6Bi35V22ZWRpXLsbSvtL+W7qNrHDP30eUfyXymtwoPP27i3IV6QAVawk4XqDaaYdlqpB7CE/uilhCkg/Y6Pr+uxUm6cL/VsTPwL+W7AeL5sH7bu83vV3yAvTFMm71aeeoOpFm2+fBwJEk39qPhYppHBcVXHvZ7D1ufEnu/LvZBvg6uu6ujpG+YFGSCLTjQETDdSYkESlquYRcVvyV3LAfR7uSuFbSC0MccetdVcqj20EwBZwje2rXyE8lWus3BUNgxYhRupDy+NDVUzUQ4GbicaAubKfOmfFJbRXnB/Kp39EkDD1FhaO6M9Ofa7LLhscPEstDNJymNwjL5nHcJLksF0YqdBbVV7rWbFuBOcKq9sSeiUNSofIONJm3ofovy2IG01apCex3w5Vzk0EqvwXPHGOiqzEdogL/SndrpZ7kxfzTRTVjGpcaPqGGbhWL57BScfTYYp5jhAPZZ7qvC1/DqiA0nzonpYAF51ucWWfHjBzPJGaqvUlReVoy8oQLJPSr+jMrEyWD/QzFS65Vf8g0qsPeJe6OrBl6miSgcsjtPilShpMPRO+QB8IRdMssIpon1ATxHtxe3P1C580X7TAEm1tW5aV14w/5h4BuAz8YlFYVqYe1cHGHVWrKDSknSYTI0S9TC06r0co8qNLKUtrxopw3YCf3kxhDZzImOCxqdsE9GBCmBR4acKo+XhBYXiLLQ4Gto2tfIivlgIOt7kvxSDyAI54dqIwdI28EMbXcBE+OscUANczBCjrW4kOsbUWczmTI7Tg4oV8PFKmqu0gz9deFEZ5GfEIGSuZ+ppJJUxxWmUVdzIQRzZUJgRyDGZEa+nPlikwWcA7ELbGlganiVw0LIr3wJzIa6JMM2xEjSVdXnbADOMLHWIVS5nnK3ndCrDapi3TG6EtvYk/wJYN5ueABVwk+T7TN/jHUGybJy4DTDpxGsxxhzHqs1WxDEfdWHq1s2ddXVyTQe8v2BOMmCa4CVK3bxJn3tPbfPoQlfd8pjn74zUYTSTuabXKN0Zw2s+WP3EerFmCBatqUlfnkXV/LCpYA55vlM3Akjkrf4O7us2zGwOY+JG8DCBuUcwT2BOYO6RBPaoK5Nm7hGY2a9mm2StlR9712M5XrRD7N8466zs0RRns04ZXq3xNipcN1F4b6h0MO2YjeMvQKw7fOb1IRt0Tiw67d9KRLhoMBG4wLGX1slXhMpnE97nykqJODqeiwdTvTjx0q+c+wlENNGOnPZWG33fnbcPYD6hJwIv3H5QGG19Ir/2TpDr/Z792QcwAY6FjyMBiFm9J7/z8ZkH30403I08pS3UTlHvhIsGUwI3E+u0UnFWt5wB9jWr3KTgpOKI+moHk83BQ+cBofI7p9L3mXac9lOCBwRWt7yodh+sdpGu6qCBD6grx5aFNvkmtCgg6WvRmin+TTO5A+S2KUpDMzG1LH6SK1ylB1K9oMUKs2iifpFzLZr5m++Z+T5ahMd8ydlfODby4GB2uT9k25bWzqgsGsrHvexFeblQCv1hjALmvz5ivuVl7UvgppWVLYlnGu2C0M5W8m1xFzdopMJoaQn0jzEJmKWSzZdhS2IdERCkYT4BqBEU5TMomGPNTFszLIqKopLnTPc+ViCEbcmS5FmdoqFoZ9C4uIzqYobJ464vGo5jRUvblfe7imdPRYEpgaNlaAzzG26mNPaHF/KDZikMiPbynW9QAC31XpYXC07D5VOettFoytYNEmXnSdlf6MpTbPlwpUHHyt1d6Cp5zsxHoplwMoGZCRBjsDGBOYYUM2ljAjMTIMZgYwJzDClm0sYEZiZAjMHGBOYYUsykjQnMTIAYg40JzDGkmEkbE5iZADEGGxOYY0gxkzYmMDMBYgw2JjDHkGImbUxgZgLEGGxMYI4hxUzaKOpwuk5mOtOzOz/8KjQ/acb5XvJwWekcQlN+Icf1Ei49hwtcCnONhJ+3CWmKF0FFa6YEzt0dfi35s3zuvHLbgGsgX8kDAXw5d+tAPge53CYAaMpShnhMD1WuOCDpQNFgin9+dJH/VxYudXkg3DeYdFAEkFzHBDi08Hc5fMBHi/ltO66VzLx/QbhEKhZMCZ4LW9wJepUQPPd47vt0bqejaYCauqRFGqYV4k5Q68XpX0Xz+1vynHkqcaJxKZNIGuaVudGBrXC48BXDQH05AEdz7T8xxEWKCRepmRI8GolLLnK89Mnn1h7AdiG+LQk347tUyK1MqWAaQE3/0QiN62MymTut3dxw6sRPkWD6nqFFdqs9dFaAsGKF0MyZ4m5xQ7iBKMscXDQVO2cKJC4q8xkf8yJzndMqxZ2plI+mWV6TOQbA2yrbVoZyWVOxYCJVAZD87MDnFfd95bojpWQzu27fXX0NCMxwsXvLWAg3HkwJgz1m8SYWUCcwf/0PlvAGCaGUShOYNZ/7lQjojQdTc2b4TYMSAYx5jlezP9SxOI8wL7FT7zOXy03xLUhAWPCSZFH3KMB0H5fWFNibUVvTv9KS2TfX0v+Od/4AFfjjywAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle \\left[\\begin{matrix}E_{b} \\left(s - s_{\\pi}\\right)\\\\K z\\\\\\alpha \\gamma\\end{matrix}\\right]$"
       ],
@@ -296,7 +296,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle \\left[\\begin{matrix}- E_{b} & 0 & 0\\\\0 & K & 0\\\\0 & 0 & \\gamma\\end{matrix}\\right]$"
       ],
@@ -378,7 +378,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAKoAAAAVCAYAAADW6nUiAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAEWElEQVRoBe2a61HcMBCAPQwFMJRAOgBSAUcHZKiA0AFMfsG/G+gA0kGgA0gFCZQAFYTQAfk+n23kO99bd2cH78yeVrIs7XslQ/L29pa0WH8dnJ2dbX1EO+VyryUtNEUDx+fn552mMBuRz1Tu9YgLpkuhzL8QG+Ar+JQhTQpb/G6DT8z71Btqf2NoAH2esM4+mDuz+r9m/NT1abXJA6gNctt0Gb+lX3uI6qgIrZJUiFFwHUofKEol7YTPWnp+DaDfS1a5pL2hPQCPoAsnhH4FddpjEdok0hiI6qhI/UUMFRRo4if0Jrij0oLxD0Mit4G8RVsK4sgK6LKejqpDho5qJj1kb7Nu4yD2GXUTRRTKybXB2B20JX8PulGRnMsQqbXaiAsD9PvI4mIHWudMaN3zgtZE0kiI7ahGcwlQzhUDZpJ9aBXYwuI1oM6F08xJvzfZSRUkaunvd0T6F+zxFfRMdO+GqwL297LxDRyW0TSq57zGA3J4icp173HrqC5CzWqHqI4aKgOGdFCdQwdY5Jks3LaSzozmM0vfC6gR09swbQrM+d+yvTpX/7+Q7bUn5Wp/57HDQhwVhjzMW36M7JVmKfb3bKyxirMzdAIWjgl9AJpt5dszdKkC8Myznuds4Yr+SmXqsTH2Nz2fMstL1cr5RWdj7TBKonUWsBR6Ix9WEqve92ZfGDqcwHiHvp9IbqFVUgH0vfGOvEzxPDY/8lnwyvoqrJRhGNOJ5Ve+O7SlYwp9v/u6hp98Su8yNgDMMUjVQz9YhhOel/SSTXpkPMplJ9s/rxgG4YBM/Yz193ln6Xbo5yHs66gqPsp3TdbSCcw899BVSs+/44U8lOiY/JQWfu8cQubZ8X20R3mWe4aHm5B/aI8x3Yy3/ncG+syrcsSEcTO2wbqwDMfaBolZ3+DqQrunei8FH/2RwLvR/GLIRqPsMPDK2sDIjAMIZqkxM5sZBr7VMWaG8S8jqwYN97uKicw4BphZyHkJrXJt0BZZ2fE6Ajx69tZJU16z1gpmRlWOOsFQO1QxuVY1OO0YSrBMmKVewL0h7xvpP4Y8W8pwZiwz2lCn45mZx4uIn3SUqxFfA+BVJ72rkM1xoTLL9x4t9xceDZqRdujnKIqjsmj+Vye/lVoyCqC/DZpJLUWlZ8Wk5RFG8cgzsqzAp0Y16J7B3NCQ9QN4NdubJGwHyjtj+ReXE+fWRIKJ7BDyuh52ZqER3kzp2VQHsOzQpODFwcjJlVOHiP4MP/I7CWj0XeQZ69iTLBZ7Dnypc4NoF1TH/i2/KPv0E/oet8JAe2As2qXNPWaEaeyQbhHDUXXAOjjhWJ1hpKoL3rD3zP5m1VqCDgdjA3eBkFnmGGxRLsrhuvPSU9oh3S5W6Z+X9zq+b5ayKsQEnV9sYUoNzJ1Rp9yvEdOJeMulZdN/spFOP/fMy3yW4eZd5kO+3zpqhdlxKL87ii3URANt6a+JISZg4w9zantmnoD/Waekcv8DIcSZoLLaK5gAAAAASUVORK5CYII=\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAKoAAAAVCAYAAADW6nUiAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAEW0lEQVRoBe2a61HcMBCAbxgKYEgHpAMgFXB0AJMKCB3A5Bf8uyEdABUk0AGkggRKgApC6IB8n8/2yGffC+uwL3hn9rSSZXnfWgl6Ly8vvQ7br4OTk5ON92inTO6VXgfLooHD09PT/rIwG5HPRO7ViAsmS6HMvxBr4DP4kCJNAhv8boIPzPs4HOp+Y2gAfX5hnX0wc2b1P2D8m+vTapM7UBtktvH5Nf3WQ1RHRWiVpEKMgotQ+kBRKmkrfNbR9TWQ6vuC9orV9sAD6NwJoZ/BY8YPRWiTyNJAVEdFaiN6P1RQoImf0OvglkoLxt8NidwG8gZtIYgjK2DAejqqDhk6qpl0l2/v0i4dxK5R11FErpxMG4zdQLvl70AvVSRnMkRq3W3EhQH6vWdxsQ+tc/Zo/eYZrc67lBDbUY3mAqCccwbMJEazCuxg8RpQ58Jx6qSXtO52SwtRt/5RR6R/hmYs8q2JbpvUUsDLuIxWqqub5LfOt5HVWjXTveXWQZ31Yr4b8DWXHaI6aigQDOmgR6BRvciaLPxsJc33zTDPoFnlCdSIHixyYM7/lu3Vufr/hWzK3jjUscNCHBWGLOZ1DiM7uR5pSkt839r4hjavnaF7YO6Y0HvgV+bJtzV0YQfgmbWedbZwTr9RmYZsTP1N6lNmWZc2zi86m2qHSRKtsoAp2BP5uFRc9b4n+9zQ4QTG+/S9IrmGLhTv9DfHvZetwfPY/Mhnzqs80C9kGMZ0YvmVbw8hhTKFvve+ruGVT+FdxkrAHINUPYyC23CP5wW9pJPuGY9SR6bfz3YMg7Ak0yhjo33eeXM7jPIQ9nVUFR/lXpO1kqhhvVvoKqVroCoj5TzF5CdftEh8pptlx+KTYS33CA9XIf/QljGDlLfRd0p95lXKyLgZ2+uphWU41jZIzPoG1wDab+q0heCjPxF4N5pfjPnQJDuUXlkpjbxyAMHcaszMZobSXR1jZhj/MtI0aLjfVUykxjHAzELO69Eq1xptnpUdbyPAo7W3TprwmraWMmZU5WgTjLVDFZMrVYPzjqEEtwmz1BO4M+Z9I/3HmGdvMpway4w21ul4ZubxIOKVjnJ5GFxYBowlODx6cLIWH5VN5xUqs/zw0dv+wqNBM9EOoxxFcVQWzf7q5F2pW0YO9K1LzaRuRYVn+aS3I4ziqX9wgE+NatA9gpmhIdsH8Gq2N0l8oC1t74xlNy5Hzm2JBDPZIeR1Ney8hkZ4DyDWpjqA2w5NAh4cjJxMOW2I6E/wY2afBTT6NvJMdexZFos9B77UuUG0Dapjef0O5hk1nXPJswzuGPP80LQt5rFDwnsMR606NGWKaVWLgebh1exvVm0lIIsOWToLhMymc6IclMN169Jz2iH5XKytvy7vbXzfLOWuEBN0frGDOTVQO6PO+b2lmE7Eu6X2Qf/JRjq57qnLPGuVasi6a76X9ztHrbA0DuW9o9hBSzTQbf0tMcQMbPxhTmtr5hn4f+2URO5/EtGaf87G+rwAAAAASUVORK5CYII=\n",
       "text/latex": [
        "$\\displaystyle - Z - \\tau_{\\mathrm{Y}} + \\left|{X - \\tau}\\right|$"
       ],
@@ -446,12 +446,16 @@
    "outputs": [
     {
      "data": {
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+      "image/png": "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\n",
       "text/latex": [
-       "$\\displaystyle \\left[\\begin{matrix}- \\operatorname{sign}{\\left(X - \\tau \\right)} & -1 & \\operatorname{sign}{\\left(X - \\tau \\right)}\\end{matrix}\\right]$"
+       "$\\displaystyle \\left[\\begin{matrix}\\begin{cases} 0 & \\text{for}\\: X = \\tau \\\\\\frac{- X + \\tau}{\\left|{X - \\tau}\\right|} & \\text{otherwise} \\end{cases} & -1 & \\operatorname{sign}{\\left(X - \\tau \\right)}\\end{matrix}\\right]$"
       ],
       "text/plain": [
-       "[-sign(X - Ï„)  -1  sign(X - Ï„)]"
+       "⎡⎧   0     for X = τ                 ⎤\n",
+       "⎢⎪                                   ⎥\n",
+       "⎢⎨ -X + τ             -1  sign(X - τ)⎥\n",
+       "⎢⎪───────  otherwise                 ⎥\n",
+       "⎣⎩│X - τ│                            ⎦"
       ]
      },
      "execution_count": 14,
@@ -516,7 +520,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/latex": [
        "$\\displaystyle \\left[\\begin{matrix}- \\operatorname{sign}{\\left(X - \\tau \\right)}\\\\1\\\\- \\operatorname{sign}{\\left(X - \\tau \\right)}\\end{matrix}\\right]$"
       ],
@@ -885,788 +889,13 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        // select the cell after this one\n",
-       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
-       "        IPython.notebook.select(index + 1);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\" width=\"852.75\">"
-      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d23f8cf21a2441bd924b9cec4a071f2a",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -1830,7 +1059,6 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
-    "scrolled": false,
     "slideshow": {
      "slide_type": "fragment"
     }
@@ -1838,788 +1066,13 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        // select the cell after this one\n",
-       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
-       "        IPython.notebook.select(index + 1);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\" width=\"1399.5\">"
-      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8301393bd55b4fa19ace99d99e81777d",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -2647,7 +1100,6 @@
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {
-    "scrolled": false,
     "slideshow": {
      "slide_type": "subslide"
     }
@@ -2655,788 +1107,13 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        // select the cell after this one\n",
-       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
-       "        IPython.notebook.select(index + 1);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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width=\"1198.5\">"
-      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3d298777fa8b4c0d9eff04e9a47d3dd0",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -3464,7 +1141,6 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {
-    "scrolled": false,
     "slideshow": {
      "slide_type": "fragment"
     }
@@ -3472,788 +1148,13 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        // select the cell after this one\n",
-       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
-       "        IPython.notebook.select(index + 1);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\" width=\"1399.5\">"
-      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "468cb665b1d942e79371e4bc521b64d2",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -4273,7 +1174,6 @@
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {
-    "scrolled": false,
     "slideshow": {
      "slide_type": "subslide"
     }
@@ -4281,788 +1181,13 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        // select the cell after this one\n",
-       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
-       "        IPython.notebook.select(index + 1);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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width=\"1198.5\">"
-      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "444c48f15ee04dc8a9036d61550f0d09",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -5092,7 +1217,6 @@
    "execution_count": 30,
    "metadata": {
     "hide_input": false,
-    "scrolled": false,
     "slideshow": {
      "slide_type": "fragment"
     }
@@ -5100,788 +1224,13 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support. ' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option);\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>');\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        // select the cell after this one\n",
-       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
-       "        IPython.notebook.select(index + 1);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\" width=\"1399.5\">"
-      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "73f24863d41e4213a2b02c4ab067bcfe",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
       ]
      },
      "metadata": {},
@@ -5890,7 +1239,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f675768cad8b4fc098f6283d51c57f86",
+       "model_id": "c47f56d4a7644b5bb09189db5ef2d4db",
        "version_major": 2,
        "version_minor": 0
       },
@@ -5904,7 +1253,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2366f3f7ac044b8da2fdb0ddfb02fe2b",
+       "model_id": "ad607147d29a490f84f43135f4099079",
        "version_major": 2,
        "version_minor": 0
       },
@@ -6006,6 +1355,20 @@
     "\n",
     "ipw.interact(reset, **margs_sliders);"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -6025,7 +1388,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.9.1"
   },
   "toc": {
    "base_numbering": 1,
@@ -6047,5 +1410,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/bmcs_course/5_1_Introspect_Damage_Evolution_Damage_initiation.ipynb b/bmcs_course/5_1_Introspect_Damage_Evolution_Damage_initiation.ipynb
index d66efcfb822506b30477a53df05b737480551aba..d274a269d26b6832e3cb140f2a743d03f6fd0048 100644
--- a/bmcs_course/5_1_Introspect_Damage_Evolution_Damage_initiation.ipynb
+++ b/bmcs_course/5_1_Introspect_Damage_Evolution_Damage_initiation.ipynb
@@ -176,7 +176,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2004fb9ee4454265be32c0c74357d6d7",
+       "model_id": "2a713770d0b7435b948b1bb12ac6668c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -376,7 +376,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8fc1979655a546acbc7f187c9dc7d8c6",
+       "model_id": "be58a61943c8465cb854ec0965d6836c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -441,7 +441,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "51661c02fd424763b26f583792bac4bd",
+       "model_id": "9e9807ec130d4299827d707009d99a81",
        "version_major": 2,
        "version_minor": 0
       },
@@ -520,7 +520,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e00a9dcc733a43459c88f65451e1bd8b",
+       "model_id": "8239f242d4c340cd96165b31b049ee15",
        "version_major": 2,
        "version_minor": 0
       },
@@ -652,7 +652,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "530e5a118fb94054a4e12f8ed9557685",
+       "model_id": "0df2e25fcdfb4e85bb630717a1cb7456",
        "version_major": 2,
        "version_minor": 0
       },
@@ -790,7 +790,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "efd84d709518404eae14b944cb85e844",
+       "model_id": "a6af834a1d9e4eba9fbbf8dd4976a7ff",
        "version_major": 2,
        "version_minor": 0
       },
@@ -823,7 +823,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "64f7400bfa8846308f5c40bc633f386b",
+       "model_id": "7279f19c3c8b475c8e55286b0cc2287a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -874,7 +874,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5d7119dbd3f34a7bbd379871ac4f67a4",
+       "model_id": "fca82a14fcce40c2bc7e9bfc0aa5b40d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -888,7 +888,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b8f7803025304299ac63ad7c027c24de",
+       "model_id": "586c5b29d90747f9af63d9e47f2953fb",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1073,7 +1073,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.2"
+   "version": "3.9.1"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/extras/pullout1d.ipynb b/extras/pullout1d.ipynb
index f2df84cc57dd8399c8fddd4fec52ae1eebe5f1be..301461e861853efc87c8d13fc6e420898b5635c5 100644
--- a/extras/pullout1d.ipynb
+++ b/extras/pullout1d.ipynb
@@ -365,7 +365,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
diff --git a/index.ipynb b/index.ipynb
index 8753e533b076aa4d2f0985edae1cdf02de767bf8..fb1baa1da1835f052b85b41b2e82a19ec4d8afb1 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -141,7 +141,7 @@
     "### 1.3 Interactive computational environment\n",
     "\n",
     "To demonstrate the theory on examples that can be interactively modified, let us consider an elementary case of mixture rule to determine the effective stiffness of an elastic composite </br>\n",
-    "[**Mixture rule**: example elastic mixture rule](pull_out/1_1_elastic_stiffness_of_the_composite.ipynb)"
+    "[**Mixture rule**: example elastic mixture rule](tour1_intro/1_1_elastic_stiffness_of_the_composite.ipynb)"
    ]
   },
   {
@@ -158,7 +158,7 @@
     "### 2.1 - Pull-out from rigid matrix - test setup and theory\n",
     "\n",
     "Using the analytical solution of the pullout problem assuming constant bond-slip law, elastic fiber and rigid matrix, we first explore the fundamental relations between the measured pull-out curve of a steel-rebar from the concrete matrix:</br> \n",
-    "[**Pull-out:** analytical constant-bond model](pull_out/2_1_1_PO_observation.ipynb)"
+    "[**Pull-out:** analytical constant-bond model](tour2_constant_bond/2_1_1_PO_observation.ipynb)"
    ]
   },
   {
@@ -168,7 +168,7 @@
     "### 2.2 - Classification of pullout configurations with constant bond stress\n",
     "\n",
     "Include further configurations of a pull-out to show the differences in their behavior, learning the correspondence between the shape of the pull-out curve and the distribution of slip, shear, fiber and matrix strain and stresses depending on a particular configuration, i.e. elastic matrix, short fiber, short matrix and  clamped fiber:</br> \n",
-    "[**Pull-out:** extended analytical constant-bond models - short / long / elastic / clamped](pull_out/2_2_1_PO_configuration_explorer.ipynb)"
+    "[**Pull-out:** extended analytical constant-bond models - short / long / elastic / clamped](tour2_constant_bond/2_2_1_PO_configuration_explorer.ipynb)"
    ]
   },
   {
@@ -179,7 +179,7 @@
     "\n",
     "The crack-bridging action of a fiber within a composite loaded in tension is a key to understanding the behavior of brittle-matrix composites. By putting crack bridges in a series, we can directly simulate a tensile test and predict the test response in terms of the stress-strain and crack spacing curves. This helps us to study and understand the relation between reinforcement ratio, bond strength, matrix strenth and the tensile response of the composite:\n",
     "</br>\n",
-    "[**Multiple cracking:** tensile response of a composite](pull_out/fragmentation.ipynb)"
+    "[**Multiple cracking:** tensile response of a composite](tour2_constant_bond/fragmentation.ipynb)"
    ]
   },
   {
@@ -191,14 +191,14 @@
     "### 3.1 - Pull-out with softening and hardening bond behavior\n",
     "\n",
     "The shape of the bond-slip law is distinguished into hardening and softening leading to a completely different pull-out behavior. A numerical model of the pull-out test is used to visualize the debonding process</br>\n",
-    "[**Pull-out**: with softening and hardening](tour3-nonlinear-bond/3_1_nonlinear_bond.ipynb)\n",
+    "[**Pull-out**: with softening and hardening](tour3_nonlinear_bond/3_1_nonlinear_bond.ipynb)\n",
     "\n",
     "### 3.2 - Anchorage failure mechanisms\n",
     "\n",
     "With the developed understanding, we address the questions related to design rules: What is the necessary bond length to avoid (or to guarantee)  a fiber pull-out (fiber rupture). At which distance can we expect a matrix crack to appear?</br>\n",
-    "[**Anchorage**: pull-out, fiber rupture, matrix crack](tour3-nonlinear-bond/3_2_anchorage_length.ipynb)\n",
+    "[**Anchorage**: pull-out, fiber rupture, matrix crack](tour3_nonlinear_bond/3_2_anchorage_length.ipynb)\n",
     "\n",
-    "Related optional supportive material</br>\n",
+    "### Related optional supportive material\n",
     "[**Appendix 2**: Newton iterative scheme](extras/newton_method.ipynb)</br>\n",
     "[**Appendix 3**: Nonlinear finite-element solver for 1d pullout](extras/pullout1d.ipynb)"
    ]
@@ -207,34 +207,43 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## **Tour 4:** Unloading and reloading\n",
+    "## **Tour 4:** Irreversibility due to yielding\n",
     "\n",
-    "### 4.1 - Reversible and irreversible behavior\n",
+    "### 4.1 - Unloading and reloading\n",
     "\n",
     "Non-linear behavior can be described by nonlinear functions as we did so far. However,\n",
     "this description cannot capture the irreversible changes within the material structure.\n",
     "To demonstrate this, let us revisit the pull-out test and unload.</br>\n",
+    "[Unloading with multi-linear bond-slip law](bmcs_course/4_1_PO_multilinear_unloading.ipynb)\n",
     "\n",
-    "- 4.1 [Unloading with multi-linear bond-slip law](bmcs_course/4_1_PO_multilinear_unloading.ipynb)\n",
-    "- 4.2 [Basic concept of plasticity, ideal and isotropic hardening](bmcs_course/4_2_BS_EP_SH_I_A.ipynb) \n",
-    "- 4.3 [Basic concept of plasticity, kinematic hardening](bmcs_course/4_3_BS_EP_SH_IK_A.ipynb)\n",
-    "- 4.4 [EXTRA - Generalization of the algorithm using vectors](bmcs_course/4_4_BS_EP_SH_IK_N.ipynb) "
+    "### 4.2 - Basic concept of plasticity, ideal and isotropic hardening\n",
+    "\n",
+    "[Basic concept of plasticity, ideal and isotropic hardening](bmcs_course/4_2_BS_EP_SH_I_A.ipynb) \n",
+    "\n",
+    "### 4.3 - Basic concept of plasticity, kinematic hardening\n",
+    "\n",
+    "[Basic concept of plasticity, kinematic hardening](bmcs_course/4_3_BS_EP_SH_IK_A.ipynb)\n",
+    "\n",
+    "### Related optional supportive material\n",
+    "[**Appendix 4**: Generalization of the algorithm using vectors](bmcs_course/4_4_BS_EP_SH_IK_N.ipynb) "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## **Tour 5**\n",
-    "- 5.1 [Damage initiation, damage evolution, 2D bond behavior](bmcs_course/5_1_Introspect_Damage_Evolution_Damage_initiation.ipynb)\n",
-    "- 5.2 [Pull out simulation using damage model](bmcs_course/5_2_PO_DM_FRP_N.ipynb)"
+    "## **Tour 5:** Irreversibility due to damage\n",
+    "\n",
+    "### 5.1 [Damage initiation, damage evolution, 2D bond behavior](bmcs_course/5_1_Introspect_Damage_Evolution_Damage_initiation.ipynb)\n",
+    "\n",
+    "### 5.2 [Pull out simulation using damage model](bmcs_course/5_2_PO_DM_FRP_N.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## **Tour 6**\n",
+    "## **Tour 6:** From debonding to cracking \n",
     "\n",
     "- 6.1 Crack propagation"
    ]
@@ -243,7 +252,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## **Tour 7**\n",
+    "## **Tour 7:** Reinforced bended cross section\n",
     "\n",
     "- 7.1 Beam bending "
    ]
diff --git a/tour1_intro/1_1_elastic_stiffness_of_the_composite.ipynb b/tour1_intro/1_1_elastic_stiffness_of_the_composite.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..8c23489eb65bbbb8796eb0ac4a75d53b6a1b306e
--- /dev/null
+++ b/tour1_intro/1_1_elastic_stiffness_of_the_composite.ipynb
@@ -0,0 +1,396 @@
+{
+ "cells": [
+  {
+   "attachments": {
+    "image.png": {
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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    },
+    "tags": []
+   },
+   "source": [
+    "# Example: Calculate elastic stiffness of a given composite\n",
+    "\n",
+    "[Video explaining the theory](https://moodle.rwth-aachen.de/mod/page/view.php?id=551801)\n",
+    "\n",
+    "## Task\n",
+    "Predict the tensile stiffness of a reinforced concrete cross section shown in the Figure with the thickness of 10~mm and width of 100 mm.\n",
+    "The cross-section is reinforced with 6 layers of textile fabrics made of CAR-EP3300 specified in the table below\n",
+    "\n",
+    "![image.png](../fig/mixture_rule_elastic.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Theory\n",
+    "The derived mixture rule will be used to solve the task"
+   ]
+  },
+  {
+   "attachments": {
+    "image.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    },
+    "tags": []
+   },
+   "source": [
+    "![image.png](attachment:image.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    },
+    "tags": []
+   },
+   "source": [
+    "\\begin{array}{|c|c|c|c|c|c|}\n",
+    "    \\mathrm{Label}\n",
+    "    & \\mathrm{Material}\n",
+    "    & \\mathrm{Area }\n",
+    "    & \\mathrm{Grid\\; spacing}\n",
+    "    & \\mathrm{Stiffness}\n",
+    "    & \\mathrm{Strength\\; (characteristic)}\n",
+    "    \\\\ \n",
+    "  \\hline \n",
+    "    &     \n",
+    "    & [\\mathrm{mm}^2]\n",
+    "    & [\\mathrm{mm}]\n",
+    "    & [\\mathrm{MPa}]\n",
+    "    & [\\mathrm{Mpa}]\n",
+    "    \\\\ \n",
+    "   \\hline\n",
+    "    \\mathrm{CAR-EP3300}\n",
+    "    & \\mathrm{carbon/proxy}\n",
+    "    & 1.84\n",
+    "    & 25.77\n",
+    "    & 240000\n",
+    "    & 3500\n",
+    "    \\\\\n",
+    "   \\hline\n",
+    "    \\mathrm{solidian\\; GRID \\; Q95}\n",
+    "    & \\mathrm{carbon/proxy}\n",
+    "    & 3.62\n",
+    "    & 36.0\n",
+    "    & 240000\n",
+    "    & 3200\n",
+    "    \\\\ \n",
+    "\\end{array}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# How to evaluate an expression?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Calculator:** Let us use Python language as a calculator and evalute the mixture rule for the exemplified cross-section.m"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "A_roving = 1.84 # [mm**2] \n",
+    "n_layers = 6 # - \n",
+    "spacing = 25.77 # [mm] \n",
+    "thickness = 10 # [mm] \n",
+    "width = 100 # [mm] \n",
+    "E_carbon = 240000 # [MPa] \n",
+    "E_concrete = 28000 # [MPa]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "37082.18859138533"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A_composite = width * thickness\n",
+    "n_rovings = width / spacing\n",
+    "A_layer = n_rovings * A_roving\n",
+    "A_carbon = n_layers * A_layer \n",
+    "A_concrete = A_composite - A_carbon \n",
+    "E_composite = (E_carbon * A_carbon + E_concrete * A_concrete) / A_composite\n",
+    "E_composite"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Thus, the composite has an effective stiffness of 37 GPa."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# How to construct a model?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Once we have derived the formula capturing the design question, i.e. \"what is the stiffness of the new composite?\" we want to learn from the model and develop a new intuition. To explore the possible composite designs let us rewrite the above equations as symbolic expressions. Then, we can construct a model which can be interactively used to study the available design options."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In contrast to the previously performed numerical evaluation, we now express the derived equations as mathematical symbols instead of numbers. To do this, let us use a Python package `sympy` to do symbolic algebra."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sympy as sp"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The parameters of the model are now introduced as `sympy.symbols`. To distinguish the symbols from numbers introduced above, let us name the Python variables referring to the mathematical symbols with a trailing underscore `_`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "A_roving_ = sp.Symbol('A_r')\n",
+    "n_layers_ = sp.Symbol('n_l')\n",
+    "spacing_ = sp.Symbol('d')\n",
+    "thickness_ = sp.Symbol('h')\n",
+    "width_ = sp.Symbol('b')\n",
+    "E_carbon_ = sp.Symbol('E_car')\n",
+    "E_concrete_ = sp.Symbol('E_c')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To see the difference between a variable referring to a number and to a symbol, let us display the variables `A_roving` and `A_roving_`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.84"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/latex": [
+       "$\\displaystyle A_{r}$"
+      ],
+      "text/plain": [
+       "A_r"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "display(A_roving, A_roving_)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us now rephrase the the above derived equations in the symbolic form, i.e. using the symbols with the trailing underscore `_`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$\\displaystyle \\frac{A_{r} E_{car} n_{l} - E_{c} \\left(A_{r} n_{l} - d h\\right)}{d h}$"
+      ],
+      "text/plain": [
+       "(A_r*E_car*n_l - E_c*(A_r*n_l - d*h))/(d*h)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A_composite_ = width_ * thickness_\n",
+    "n_rovings_ = width_ / spacing_\n",
+    "A_layer_ = n_rovings_ * A_roving_\n",
+    "A_carbon_ = n_layers_ * A_layer_ \n",
+    "A_concrete_ = A_composite_ - A_carbon_ \n",
+    "E_composite_ = (E_carbon_ * A_carbon_ + E_concrete_ * A_concrete_) / A_composite_\n",
+    "sp.simplify(E_composite_)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**The power of modeling**\n",
+    "\n",
+    " - Instead of a number, we have now a symbolic expression showing the influence of the individual parameters on a design property, i.e. on the material stiffness $\\bar{E}$. \n",
+    "\n",
+    " - This expression represents the first model that we constructuted in the course using the conditions of compatibility, equilibrium and constitutive laws.\n",
+    "\n",
+    " - Using a model, we can explore the behavior of the composite, develop a design intuition, optimize the design.\n",
+    "   We learn how to construct simple models describing the mechanisms governing the behavior of a composite.\n",
+    "   \n",
+    " - We will construct simplified analytical models for pull-out, that will help us to understand elementary types of\n",
+    "   material behavior.\n",
+    " "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Next steps"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " - Login to jupyter.rwth-aachen.de\n",
+    " - Navigate to this mixture rule example\n",
+    " - Evaluate the cells by issueing the [Shift+Return] key combination"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Why Jupyter Lab? Why Python?\n",
+    " - [Jupyterlab introduction](https://youtu.be/A5YyoCKxEOU) [7 mins] video explaining the basic features of jupyter notebook within jupyter lab \n",
+    " - [Most Popular Programming Languages 1965 - 2019](https://www.youtube.com/watch?v=Og847HVwRSI) Check this race of programming languages over the last 50 years and wait till the end of it ;-)\n",
+    " - Useful packages\n",
+    "   - `matplotlib` - how to plot fancy diagrams  \n",
+    "   - `sympy` - how to perform algebraic manipulations\n",
+    "   - `numpy` - how to manipulate data - beyond `Excel`\n",
+    "   will be shortly explained."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.9.1"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {
+    "height": "calc(100% - 180px)",
+    "left": "10px",
+    "top": "150px",
+    "width": "184.567px"
+   },
+   "toc_section_display": true,
+   "toc_window_display": true
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/tour2_constant_bond/2_1_1_PO_observation.ipynb b/tour2_constant_bond/2_1_1_PO_observation.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..0d8f548abdb6e52ecd55900ea0b16b859696b3cf
--- /dev/null
+++ b/tour2_constant_bond/2_1_1_PO_observation.ipynb
@@ -0,0 +1,268 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "<a id=\"top\"></a>\n",
+    "# 2.1 Pull-out of elastic fiber from rigid matrix "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "[![title](../fig/bmcs_video.png)](https://moodle.rwth-aachen.de/mod/page/view.php?id=551807)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# The simplest possible pull-out model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An analytical solution of the pull-out problem is obtained by \n",
+    "\n",
+    "1. Integrate the differential equilibrium equation relating the shear flow with the change of the normal force \n",
+    "$A_\\mathrm{f} \\mathrm{d}\\sigma_\\mathrm{f}$ in the fiber on an infinitesimal element $\\mathrm{d}x$\n",
+    "\\begin{align}\\dfrac{\\mathrm{d}\\sigma_\\mathrm{f}}{\\mathrm{d}x} = \\dfrac{p\\bar{\\tau}}{A_\\mathrm{f}}\\end{align}\n",
+    "2. Substitute the result into the elastic constitutive law of the reinforcement\n",
+    "\\begin{align}\\varepsilon_\\mathrm{f} = \\dfrac{\\sigma_\\mathrm{f}}{E_\\mathrm{f}}\\end{align}\n",
+    "3. Substitute the result into the kinematic relation stating that the pull-out displacement is equal to the integral of fiber strain along the debonded length\n",
+    "\\begin{align}u_\\mathrm{f} = \\int_{a}^0 \\varepsilon_\\mathrm{f} \\, \\mathrm{d}x\\end{align}\n",
+    "4. Identify the integration constants by applying boundary conditions: equilibrium at loaded end and compatibility and smoothness at the end of the debonded zone $x = a$\n",
+    "\n",
+    "These step deliver the pull-out curve as a square root function\n",
+    "\\begin{align}\n",
+    "P = \\sqrt{p \\bar{\\tau} E_\\mathrm{f} A_\\mathrm{f} w}\n",
+    "\\end{align}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Graphical summary of the model derivation"
+   ]
+  },
+  {
+   "attachments": {
+    "6ef958fc-7d8f-4dc2-848a-36d05b0e32b8.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:6ef958fc-7d8f-4dc2-848a-36d05b0e32b8.png)"
+   ]
+  },
+  {
+   "attachments": {
+    "image.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {
+    "hide_input": true,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Model application\n",
+    "Let us utilize the the derived model to simulate the test results of the RILEM pull-out test\n",
+    "![image.png](attachment:image.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "| Symbol | Unit |Description  |\n",
+    "|:- |:- |:- |\n",
+    "| $E_\\mathrm{f}$ | MPa | Young's modulus of reinforcement |\n",
+    "| $\\bar{\\tau}$ | MPa | Bond stress |\n",
+    "| $A_\\mathrm{f}$ | mm$^2$ | Cross-sectional area of reinforcement |\n",
+    "| $p$ | mm | Perimeter of contact between concrete and reinforcement |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Observation**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " - The measured displament at the loaded and unloaded end are different\n",
+    " - Their difference increases with increasing bond length $L_\\mathrm{b}$\n",
+    " - The shape of the pull-out curve has a shape of a square root function"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Question**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " - Can the above derived model describe the debonding process correctly?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Look inside the specimen using the model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The parameters of the above experiment are specified as follows"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = 16\n",
+    "A_f = (ds/2)**2 * 3.14 # mm^2 - reinforcement area\n",
+    "L_b = 5 * ds # mm - bond length\n",
+    "E_f = 210000 # MPa - reinforcement stiffness\n",
+    "p_b = 3.14 * ds # mm - bond perimeter\n",
+    "w_max = 0.12 # mm - maximum displacement"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Construct the model:** To study the model behavior import the class `PO_ELF_RLM`, construct it with the defined parameters  and run the `interact` method"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib widget\n",
+    "from pull_out import PO_ELF_RLM\n",
+    "po = PO_ELF_RLM(E_f=E_f, L_b=L_b, p=p_b, A_f=A_f, w_max=w_max)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Remark:** that the length $L_b$ is not the end of the bond zone. It only measures the slip at the position $x = L_\\mathrm{b}$ from the loadedend. However, the debonding process can continue beyond this length."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "54c0ab9fb44c4ca791d5f31a423d2f92",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "po.interact()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Let's learn from the model\n",
+    "\n",
+    "Exercise the relation between $P$ and $\\tau(x)$ and between $w$ and $\\varepsilon(x)$.\n",
+    "\n",
+    " 1. What is the meaning of the green area?\n",
+    " 2. What is the meaning of the red area?\n",
+    " 3. What is the meaning of the slope of the green curve?\n",
+    " 4. Is it possible to reproduce the shown RILEM test response using this \"frictional\" model?\n",
+    " 4. What is the role of debonded length $a$ in view of general non-linear simulation?\n",
+    " 5. When does the pull-out fail?\n",
+    " 5. What happends with $a$ upon unloading?"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.9.1"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": true,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {
+    "height": "calc(100% - 180px)",
+    "left": "10px",
+    "top": "150px",
+    "width": "165px"
+   },
+   "toc_section_display": true,
+   "toc_window_display": true
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/tour2_constant_bond/2_2_1_PO_configuration_explorer.ipynb b/tour2_constant_bond/2_2_1_PO_configuration_explorer.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..6c5bc823ee3fb0c334a2c8f6aaae7b06d15e97ed
--- /dev/null
+++ b/tour2_constant_bond/2_2_1_PO_configuration_explorer.ipynb
@@ -0,0 +1,316 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "<a id=\"top\"></a>\n",
+    "# 2.2: Classification of pull-out configurations\n",
+    "\n",
+    "[![Classification](../fig/bmcs_video.png)](https://moodle.rwth-aachen.de/mod/page/view.php?id=551810)\n",
+    "\n",
+    "The analytical solution of the pull-out from rigid matrix for constant bond-slip law \n",
+    "explained in the notebook [2.1 Pull-out of elastic fiber from rigid matrix](2_1_1_PO_observation.ipynb) can be adapted to \n",
+    "several practically relevant configurations that occur in brittle-matrix compostes. The notebook \n",
+    "addresses the following four configuration of pull-out\n",
+    "\n",
+    " - Rigid matrix\n",
+    " - Elastic matrix \n",
+    " - Short fiber\n",
+    " - Clamped fiber\n",
+    " \n",
+    " This notebook summarizes these four configurations using interactive web-apps to show their qualitatively different behavior. Using the prepared models,the  correspondence between the pull-out curve $P(w)$ and the debonding process is visualized in terms of the stress and strain profiles along the bond length. In all models, the following material parameters are be used."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "| Symbol | Unit |Description  |\n",
+    "|:- |:- |:- |\n",
+    "| $E_\\mathrm{m}$ | MPa | Young's modulus of concrete matrix |\n",
+    "| $E_\\mathrm{f}$ | MPa | Young's modulus of reinforcement |\n",
+    "| $\\bar{\\tau}$ | MPa | Bond stress |\n",
+    "| $A_\\mathrm{m}$ | mm$^2$ | Cross-sectional area of concrete matrix |\n",
+    "| $A_\\mathrm{f}$ | mm$^2$ | Cross-sectional area of reinforcement |\n",
+    "| $p$ | mm | Perimeter of contact between concrete and reinforcement |\n",
+    "| $L_\\mathrm{b}$ | mm | Length of the bond zone |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **1 Ridig Matrix**\n",
+    "**PO-ELF-RLM:** Pull-Out of Elastic Long Fiber from Rigid Long Matrix"
+   ]
+  },
+  {
+   "attachments": {
+    "9993286b-4057-4b22-b695-3e395e3ffeef.png": {
+     "image/png": "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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:9993286b-4057-4b22-b695-3e395e3ffeef.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**For comparison** let us import again the simplest version of the pull-out model assuming rigid matrix, elastic fiber and infinite bond length."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "aa679c9a134f4afa9e5e06a6d61c16b9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib widget\n",
+    "from pull_out import PO_ELF_RLM\n",
+    "po_explorer = PO_ELF_RLM(E_f=1, E_m=1, tau=1, p=1, A_m=1, A_f=1, w_max=0.5, L_b=1, t=0.5)\n",
+    "po_explorer.interact()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **2 Elastic Matrix**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**PO-ELF-ELM:** Pull-Out of Elastic Long Fiber from Elastic Long Matrix "
+   ]
+  },
+  {
+   "attachments": {
+    "19c4f327-1799-4e88-b100-96d66ebf2dff.png": {
+     "image/png": "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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:19c4f327-1799-4e88-b100-96d66ebf2dff.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a20f4260c8f54ab59d4d9ad7c2474cca",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib widget\n",
+    "from pull_out import PO_ELF_ELM\n",
+    "po_explorer = PO_ELF_ELM(E_f=1, E_m=1, tau=1, p=1, A_m=1, A_f=1, w_max=0.5, L_b=1, t=0.5)\n",
+    "po_explorer.interact()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **3 Short Fiber**\n",
+    "**PO-ESF-RLM:** Pull-Out of Elastic Short Fiber from Rigid Long Matrix "
+   ]
+  },
+  {
+   "attachments": {
+    "95a04ae4-2cb4-46a8-8581-9de442b93ee4.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:95a04ae4-2cb4-46a8-8581-9de442b93ee4.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "291aa713915840b5a850713f697d8a43",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib widget\n",
+    "from pull_out import PO_ESF_RLM\n",
+    "po_explorer = PO_ESF_RLM(E_f=2, E_m=1, tau=1, A_f=1, A_m=1, p=1, L_b=1, w_max=1.3, t=0.26)\n",
+    "po_explorer.interact()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **4 Clamped Fiber**\n",
+    "**PO-ECF-ECM:** Pull-out of Elastic Clamped Fiber from Elastic Clamped Matrix"
+   ]
+  },
+  {
+   "attachments": {
+    "9de172b7-49d2-43f9-8aa3-90031c3b9197.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:9de172b7-49d2-43f9-8aa3-90031c3b9197.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d478b79994f341aeb762889f895f17c6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib widget\n",
+    "from pull_out import CB_ELF_ELM\n",
+    "po_explorer = CB_ELF_ELM(E_f=2, E_m=1, tau=1, A_f=1, A_m=1, p=1, L_b=1, w_max=1.3, t=0.7)\n",
+    "po_explorer.interact()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Summary\n",
+    "\n",
+    " - The four configurations of the pull-out show that the pull-out curves have qualitatively different shape and explain the externally observered by visualizing the stress field development during the loading history. \n",
+    " - The pull-out curves calculated using the models 1 Rigid Matrix (PO-ELF-RLM)  and 2 Elastic Matrix (PO-ELF-ELM) are not affected by the bond length $L_\\mathrm{b}$. \n",
+    " - On the other hand, bond length strongly affects the maximum force and descending branch in in model 3 Short Fiber (PO-ESF-RLM). Bond length also affects the value of the final stiffness in the model 4 Clamped Fiber (PO-ECF-ECM)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/exercise.png\" alt=\"Run\" width=\"40\" height=\"40\">\n",
+    "    &nbsp; &nbsp; <a href=\"../exercises/X0201-X0203.pdf\"><b>Exercises X0201-X0203:</b></a> <b>Pull-out with constant bond-slip</b>  \n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next notebook: [2.3 Tensile behavior of brittle-matrix composite](fragmentation.ipynb)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.9.1"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": true,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {
+    "height": "calc(100% - 180px)",
+    "left": "10px",
+    "top": "150px",
+    "width": "165px"
+   },
+   "toc_section_display": true,
+   "toc_window_display": true
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/tour2_constant_bond/fragmentation.ipynb b/tour2_constant_bond/fragmentation.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..c8394ba14b6ef497d3d19b341354b25282ff78db
--- /dev/null
+++ b/tour2_constant_bond/fragmentation.ipynb
@@ -0,0 +1,821 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "internal-collect",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 2.3 Tensile behavior of brittle-matrix composite"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "trained-sculpture",
+   "metadata": {},
+   "source": [
+    "[![title](../fig/bmcs_video.png)](https://moodle.rwth-aachen.de/mod/page/view.php?id=602450)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "computational-mozambique",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    },
+    "tags": []
+   },
+   "source": [
+    "With a basic understanding of the debonding process in the vicinity of a crack bridge studied for various configurations of a pull-out problem ([2.2 Classification of pull-out configurations](2_2_1_PO_configuration_explorer.ipynb)) we describe and visualize the process of fragmentation (multiple cracking) in a reinforced composite."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "subsequent-danish",
+   "metadata": {},
+   "source": [
+    "Consider an example the textile reinforced concrete cross section loaded in tension. The cross-sectional parameters are as follows"
+   ]
+  },
+  {
+   "attachments": {
+    "cbf04e3f-0f4a-465c-a5d9-eca0fed2c315.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "fundamental-russian",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:cbf04e3f-0f4a-465c-a5d9-eca0fed2c315.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "inside-motivation",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    },
+    "tags": []
+   },
+   "source": [
+    "# Crack bridge as a key to understanding the behavior of a composite"
+   ]
+  },
+  {
+   "attachments": {
+    "ead9214a-a8c5-4f41-9aff-afe673ecd6d8.png": {
+     "image/png": 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+    }
+   },
+   "cell_type": "markdown",
+   "id": "attractive-nebraska",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    },
+    "tags": []
+   },
+   "source": [
+    "Matrix cracks develop along a tensile zone of a composite, e.g. in a tensile specimen.\n",
+    "The stress, strain and displacement fields exhibit a periodic structure with symmetry points\n",
+    "at \n",
+    " - crack positions, and at\n",
+    " - midpoints between cracks.\n",
+    "\n",
+    "![image.png](attachment:ead9214a-a8c5-4f41-9aff-afe673ecd6d8.png)\n",
+    "Therefore, it the crack bridge model derived for the assumption of a constant bond-slip law can be \n",
+    "conveniently used to describe the tensile response during the multiple cracking process."
+   ]
+  },
+  {
+   "attachments": {
+    "a3564c30-b942-40f5-8b44-25277e739aa2.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "saving-gamma",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    },
+    "tags": []
+   },
+   "source": [
+    "![image.png](attachment:a3564c30-b942-40f5-8b44-25277e739aa2.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "recognized-anime",
+   "metadata": {},
+   "source": [
+    "## What do we need from a crack bridge model?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "third-excess",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "db6f8daf02364fe1be9db16e48f5299f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib widget\n",
+    "from pull_out import CB_ELF_ELM\n",
+    "po = CB_ELF_ELM(E_f=1, E_m=1, A_f=1, A_m=1, p=1, tau=3, L_b=1, w_max=3,t=0.4)\n",
+    "po.interact()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "sufficient-lincoln",
+   "metadata": {},
+   "source": [
+    "Knowing the matrix stress profile ahead of an existing crack, we know the distance at which no crack will appear. This length is referred to as shielded length."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "novel-eligibility",
+   "metadata": {},
+   "source": [
+    "### **Question:** How long is the shielded length?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "sweet-injury",
+   "metadata": {},
+   "source": [
+    "Use the crack bridge model to find out the distance $l_\\mathrm{shielded}$ at which the matrix normal force attains the level \n",
+    "\\begin{align}\n",
+    "N_\\mathrm{mu} & = \\sigma_\\mathrm{mu} A_\\mathrm{m}\n",
+    "\\end{align}\n",
+    "Realizing that the slope at which the matrix stress grows is \n",
+    "\\begin{align}\n",
+    "T &= p \\bar{\\tau}\n",
+    "\\end{align}\n",
+    "As a result, the distance can be evaluated as\n",
+    "\\begin{align}\n",
+    "l_\\mathrm{shielded} = \\dfrac{N_\\mathrm{mu}}{T}\n",
+    "\\end{align}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "distinct-soldier",
+   "metadata": {},
+   "source": [
+    "### **Question:** What is the elongation and average strain of a crack segment?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "regional-processing",
+   "metadata": {},
+   "source": [
+    "A simple way how to find out the total elongation of the fiber with a nonlinear strain profile is to integrate the strains, i.e.\n",
+    "\\begin{align}\n",
+    "\\Delta u_\\mathrm{f} = \\int_{-L_\\mathrm{b}}^0 \\varepsilon_\\mathrm{f} \\, \\mathrm{d}x\n",
+    "\\end{align}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "animal-blank",
+   "metadata": {},
+   "source": [
+    "so that the average, or **composite** strain is obtained as"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "collaborative-mexican",
+   "metadata": {},
+   "source": [
+    "\\begin{align}\n",
+    "\\varepsilon_\\mathrm{c} = \\dfrac{1}{L_\\mathrm{b}} \\int_{-L_\\mathrm{b}}^0 \\varepsilon_\\mathrm{f} \\, \\mathrm{d}x\n",
+    "\\end{align}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dressed-radical",
+   "metadata": {},
+   "source": [
+    "**Remark:** This expression is important in view of homogenization of non-uniform strain profiles in a heterogenous material structure. It is one of the fundamental concepts of micromechanics. We will use it later on to derive the effective stress-strain curve of a multiply cracked composite."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "unusual-float",
+   "metadata": {},
+   "source": [
+    "# **Model 1:** Deterministic matrix strength (ACK model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "flying-theory",
+   "metadata": {},
+   "source": [
+    "The typical shape of the stress-strain curve of the composite involves three stages:\n",
+    "- elastic stage which is governed by the mixture rule\n",
+    "- stage of matrix fragmentation\n",
+    "- saturated crack pattern with a linear branch"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "spectacular-bread",
+   "metadata": {},
+   "source": [
+    "How to interpret and characterize these three distinguished phases of composite material behavior?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "manual-dollar",
+   "metadata": {},
+   "source": [
+    "The ACK model developed by Aveston, Cooper and Kelly is an analytical model that represents the composite tensile response by a trilinear law as shown in the following figure. This model is based on the following assumptions:\n",
+    "- The bond behavior is governed by a constant frictional bond in the debonded interface\n",
+    "- The constitutive law for both reinforcement and matrix is assumed to be linear-elastic with brittle failure upon reaching their strengths\n",
+    "- Multiple cracking occurs at a constant level of applied stress, inducing a horizontal branch in the stress-strain behavior"
+   ]
+  },
+  {
+   "attachments": {
+    "e49027f3-9a05-42fd-bb36-8b4c8c4af4d2.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "molecular-quarterly",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:e49027f3-9a05-42fd-bb36-8b4c8c4af4d2.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "equivalent-nevada",
+   "metadata": {},
+   "source": [
+    "## Stress-strain curve\n",
+    "\n",
+    "The trilinear curve of ACK model represents the composite tensile response by identifying the following characteristic points:\n",
+    "- [$\\sigma_{1}, \\varepsilon_{1}$]: The inital values of stress and strain are set to zero. \n",
+    "- [$\\sigma_{2}, \\varepsilon_{2}$]: In the first stage, the matrix is uncracked and perfect bond between matrix and fabric is assumed up to the first cracking stress $\\sigma_{2}$ , which is defined as \n",
+    "\\begin{align}\n",
+    "\\sigma_{2} = E_\\mathrm{c} \\varepsilon_{2}\n",
+    "\\end{align}\n",
+    "where $\\varepsilon_{2}$ is the composite strain value at which the matrix cracks and $E_\\mathrm{c}$ is the composite stiffness. \n",
+    "The strain $\\varepsilon_{2}$ is given as\n",
+    "\\begin{align}\n",
+    "\\varepsilon_{2} = \\dfrac{\\sigma_\\mathrm{mu}}{E_\\mathrm{m}}\n",
+    "\\end{align}\n",
+    "where $\\sigma_\\mathrm{mu}$ and $E_\\mathrm{m}$ are the matrix tensile strength and stiffness, respectively.\n",
+    "The composite stiffness has been obtained using the\n",
+    "[**mixture rule**](../bmcs_course/1_1_elastic_stiffness_of_the_composite.ipynb) \n",
+    "and can be expressed here as:\n",
+    "\\begin{align}\n",
+    "E_\\mathrm{c} = E_\\mathrm{f} \\; V_\\mathrm{f} + E_\\mathrm{m} \\; (1 - V_\\mathrm{f})\n",
+    "\\end{align} \n",
+    "where $E_\\mathrm{f}$ is the fiber stiffness, and $V_\\mathrm{f}$ is denoting the fiber volume fraction (reinforcement ratio).\n",
+    "\n",
+    "- [$\\sigma_{3}, \\varepsilon_{3}$]: The second stage is characterized by the crack propagation. In this phase, the load is\n",
+    "assumed to be constant up to the strain value $\\varepsilon_{3}$ calculated as follows:\n",
+    "\\begin{align}\n",
+    "\\varepsilon_{3} = \\dfrac{\\sigma_\\mathrm{mu}}{E_\\mathrm{m}} \\; (1 + 0.666  \\alpha_\\mathrm{e})\n",
+    "\\end{align}\n",
+    "where where $\\alpha_\\mathrm{e}$ is an homogenization coefficient given as\n",
+    "\\begin{align}\n",
+    "\\alpha_\\mathrm{e} = \\dfrac{E_\\mathrm{m} \\; (1 - V_\\mathrm{f}) }{E_\\mathrm{f} \\; V_\\mathrm{f}}\n",
+    "\\end{align}\n",
+    "\n",
+    "- [$\\sigma_{4}, \\varepsilon_{4}$]: Finally, in the third stage, when the crack pattern is stabilized the load increases linearly up to the ultimate tensile stress $\\sigma_4$  with a slope equal to $E_\\mathrm{r}$\n",
+    "The ultimate tensile stress is given as\n",
+    "\\begin{align}\n",
+    "\\sigma_4 = \\sigma_\\mathrm{fu} \\; V_\\mathrm{f}\n",
+    "\\end{align}\n",
+    "where $\\sigma_\\mathrm{fu}$ is the tensile strength of the fiber.\n",
+    "The slope $E_\\mathrm{r}$ represents the effective stiffness of the reinforcement with respect to the whole cross section and is given as\n",
+    "\\begin{align}\n",
+    "E_\\mathrm{r} = E_\\mathrm{f} \\; V_\\mathrm{f} \n",
+    "\\end{align}\n",
+    "The composilte strain at failure $\\varepsilon_{4}$ is given as\n",
+    "\\begin{align}\n",
+    "\\varepsilon_{4} = \\varepsilon_{3} + \\dfrac{\\sigma_\\mathrm{4} - \\sigma_\\mathrm{2}}{E_\\mathrm{r}}\n",
+    "\\end{align}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "forward-worthy",
+   "metadata": {},
+   "source": [
+    "## Crack spacing"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "japanese-exception",
+   "metadata": {},
+   "source": [
+    "### Matrix cracking is like car parking ?!\n",
+    "\n",
+    "![SegmentLocal](../fig/Cars.gif \"segment\")\n",
+    "\n",
+    "Consider a process where particles (cars) are randomly introduced in a system (along the street). \n",
+    "They must not overlap any previously parked car. What is the average distance between two neighbouring cars?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "radio-pontiac",
+   "metadata": {},
+   "source": [
+    "Probabilistic analysis of the car parking problem delivers the result that the average spacing is 1.337 larger than the car length ([Wikipedia: Random sequential adsorption](https://en.wikipedia.org/wiki/Random_sequential_adsorption))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "communist-accessory",
+   "metadata": {},
+   "source": [
+    "### How long is the car in a concrete tensile specimen?\n",
+    "\n",
+    "The final average crack spacing $l_\\mathrm{cs}$ is given as\n",
+    "<!-- 1.337 \\; \\dfrac{(1 -  V_\\mathrm{f}) \\; \\sigma_\\mathrm{mu}}{  V_\\mathrm{f} \\; T} \\\\ -->\n",
+    "\\begin{align}\n",
+    "l_\\mathrm{cs} &= 1.337 \\; l_\\mathrm{shielded} =  1.337 \\; \\dfrac{A_\\mathrm{m} \\sigma_\\mathrm{mu}}{\\bar{\\tau}p} \n",
+    "\\end{align}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "peaceful-number",
+   "metadata": {},
+   "source": [
+    "## Examples"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "finnish-alexandria",
+   "metadata": {},
+   "source": [
+    "### **Task 1:** Evaluate the tensile stress-strain curve\n",
+    "Consider a steel reinforced cross section of $100 \\times 100$ mm \n",
+    "reinforced with a rebar ($d = 16$ mm) diameter. \n",
+    "Plot the stress-strain curve using the ACK model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "suffering-arkansas",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "E_m = 28000 # concrete stiffness [MPa]\n",
+    "E_f = 210000 # reinforcement stiffnes [MPa]\n",
+    "A_c = 100 * 100 # dimensions [mm]\n",
+    "d = 16 # diameter [mm]\n",
+    "sig_mu = 3 # concrete tensile strength [MPa]\n",
+    "sig_fu = 500 # reinforcement strength [MPa]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "pediatric-radius",
+   "metadata": {},
+   "source": [
+    "Derived parameters of the cross composite section"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "chemical-rotation",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p = 3.14 * d # bond perimeter\n",
+    "A_f = 3.14 * (d/2)**2 # reinforcement cross section\n",
+    "A_m = A_c - A_f # concrete cross section\n",
+    "V_f = A_f / A_c # reinforcement ratio / fiber volume fraction\n",
+    "E_c = E_m * (1 - V_f) + E_f * V_f # composite stiffness\n",
+    "alpha_e = E_m * (1 - V_f) / (E_f * V_f) # homogenization coefficient"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "julian-registration",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "31657.472"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "E_c"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "diagnostic-blood",
+   "metadata": {},
+   "source": [
+    "Characteristic points of the ACK model deliver the values "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "southern-implementation",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "eps_1, sig_1 = 0, 0\n",
+    "eps_2, sig_2 = sig_mu / E_m, sig_mu\n",
+    "eps_3, sig_3 = sig_mu / E_m * (1 + 0.6666 * alpha_e), sig_mu\n",
+    "sig_4 = sig_fu * V_f\n",
+    "E_r = E_f * V_f # effective reinforcement stiffness related to the composite cross section \n",
+    "eps_4 = eps_3 + (sig_4 - sig_3) / E_r"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "breeding-roller",
+   "metadata": {},
+   "source": [
+    "Plot the composite stress-strain curve"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "qualified-bulletin",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a0e83aa441c64c3c92cafa235e839512",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib widget\n",
+    "import matplotlib.pylab as plt\n",
+    "fig, ax = plt.subplots(1,1,figsize=(7,3))\n",
+    "fig.canvas.toolbar_position = 'top'\n",
+    "fig.canvas.header_visible = False\n",
+    "ax.plot([eps_1, eps_2, eps_3, eps_4], [sig_1, sig_2, sig_3, sig_4]);\n",
+    "ax.set_xlabel(r'$\\varepsilon$ [-]'); ax.set_ylabel(r'$\\sigma$ [MPa]')\n",
+    "ax.plot([0,eps_4],[0,E_r*eps_4], color='black', linewidth=1, linestyle='dashed');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fantastic-class",
+   "metadata": {},
+   "source": [
+    "**Note** that the curve does not depend on the bond $\\tau p$."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "beginning-residence",
+   "metadata": {},
+   "source": [
+    "### **Task 2:** Evaluate the crack spacing\n",
+    "\n",
+    "What does ACK model predict for a specimen with the dimensions $100 \\times 100$ mm reinforced with 1% ratio."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "casual-steel",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "97.79047929936306"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A_c = 100 * 100\n",
+    "d = 16\n",
+    "p = 3.14 * d\n",
+    "A_f = 3.14 * (d/2)**2\n",
+    "A_m = A_c - A_f\n",
+    "tau = 8\n",
+    "1.337 * A_m * sig_mu / (p * tau)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "intellectual-needle",
+   "metadata": {},
+   "source": [
+    "which corresponds to reinforcement ratio $V_f$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "south-supervisor",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.020096"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A_f / A_c"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "breeding-developer",
+   "metadata": {},
+   "source": [
+    "# **Model 2:** Random matrix strength\n",
+    "\n",
+    "In reality, the matrix strength $\\sigma_\\mathrm{mu}$ is random. Its profile along the tensile specimen can be described by the probability distribution function.\n",
+    "Weibull probability distribution is used to describe the strength of materials."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "distant-anderson",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "10aca4be480b4c75b238bb24d99c48ce",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib widget\n",
+    "from pmcm import PMCM\n",
+    "pm = PMCM()\n",
+    "pm.interact()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cosmetic-attachment",
+   "metadata": {},
+   "source": [
+    "The probabilistic multiple cracking model uses the crack bridge model which is inserted at any newly emerging crack position. By assembling the profile along the specimen we obtain the \n",
+    " - matrix stress field  $\\sigma_\\mathrm{m}(x, \\sigma_\\mathrm{c})$, and\n",
+    " - reinforcement strain field $\\varepsilon_\\mathrm{f}(x, \\sigma_\\mathrm{c})$. \n",
+    "for any state of loading $\\sigma_\\mathrm{c}$. No finite element calculation is needed.\n",
+    "\n",
+    "The algorithm used in the above web-app can identify the individual cracks exactly. For a given load level $\\sigma_\\mathrm{c}$ and crack distribution along the specimen, the composite strain of a specimen with a length $L$ is obtained using the averaging formula introduced above\n",
+    "\\begin{align}\n",
+    "\\varepsilon_\\mathrm{c} = \\dfrac{1}{L} \\int_{0}^L \\varepsilon_\\mathrm{f} \\, \\mathrm{d}x\n",
+    "\\end{align}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "distinguished-sensitivity",
+   "metadata": {},
+   "source": [
+    "**Further reading:** [Paper describing the general probabilistic multiple cracking model](../papers/pmcm_fragmentation.pdf), Journal of Mathematical Modeling (2021)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "designed-newark",
+   "metadata": {},
+   "source": [
+    "## PMCM application"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "contained-corruption",
+   "metadata": {},
+   "source": [
+    "Apply the model to a composite cross section using carbon textile fabrics as specified in the notebook [**Mixture rule**](1_1_elastic_stiffness_of_the_composite.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "annoying-extra",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "A_roving = 0.5 # [mm**2] \n",
+    "n_layers = 6 # - \n",
+    "spacing = 8.3 # [mm] \n",
+    "thickness = 10 # [mm] \n",
+    "width = 100 # [mm] \n",
+    "E_carbon = 160000 # [MPa] \n",
+    "E_concrete = 28000 # [MPa]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "inappropriate-panic",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "32771.0843373494"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A_composite = width * thickness\n",
+    "n_rovings = width / spacing\n",
+    "A_layer = n_rovings * A_roving\n",
+    "A_carbon = n_layers * A_layer \n",
+    "A_concrete = A_composite - A_carbon \n",
+    "E_composite = (E_carbon * A_carbon + E_concrete * A_concrete) / A_composite\n",
+    "E_composite"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "moderate-stretch",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a7a532b8294641fc87136d71a774e59c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pm2 = PMCM(sig_cu=20, sig_mu=4, m=8)\n",
+    "pm2.crack_bridge.trait_set(E_m=E_concrete, E_f=E_carbon, tau=8,\n",
+    "                          A_c=A_composite, A_f=A_carbon, p=n_rovings*n_layers*3.14)\n",
+    "pm2.interact()"
+   ]
+  },
+  {
+   "attachments": {
+    "192b4a48-d1b5-44a1-9736-0fa01372f454.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "id": "choice-deployment",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:192b4a48-d1b5-44a1-9736-0fa01372f454.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "statewide-publicity",
+   "metadata": {},
+   "source": [
+    "## Examples"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "coastal-tuner",
+   "metadata": {},
+   "source": [
+    "### Task 3: Use the model to validate its prediction\n",
+    "Given the cross sectional areas $A_\\mathrm{m}, A_\\mathrm{f}$, concrete and reinforcement stiffness $E_\\mathrm{m}, E_\\mathrm{f}$ and strength $\\sigma_\\mathrm{mu}, \\sigma_\\mathrm{fu}$, reinforcement ratio $V_\\mathrm{f}$, bond stress $\\tau$, and perimeter $p$ calculate the average crack width at failure of a tensile specimen.\n",
+    "### Task 4: Evaluate the average crack width\n",
+    "Compare the crack width obtained using the ACK model and the PMCM model for a given reinforced cross section design "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aware-throw",
+   "metadata": {},
+   "source": [
+    "# Execrises"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "rational-prototype",
+   "metadata": {},
+   "source": [
+    "[Exercise X0203 - Tensile behavior of acompositewith constant bond-slip law ](../exercises/X0204.pdf)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "norman-terry",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "base"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tour2_constant_bond/po_symb/CB_ELF_ELM_Symb.py b/tour2_constant_bond/po_symb/CB_ELF_ELM_Symb.py
new file mode 100644
index 0000000000000000000000000000000000000000..6a205fc2d8f741d672c549b97a316212c048e9bd
--- /dev/null
+++ b/tour2_constant_bond/po_symb/CB_ELF_ELM_Symb.py
@@ -0,0 +1,131 @@
+
+import bmcs_utils.api as bu
+import sympy as sp
+
+
+class CB_ELF_ELM_Symb(bu.SymbExpr):
+
+    E_m, A_m = sp.symbols(r'E_\mathrm{m}, A_\mathrm{m}', nonnegative=True)
+    E_f, A_f = sp.symbols(r'E_\mathrm{f}, A_\mathrm{f}', nonnegative=True)
+    tau, p = sp.symbols(r'\bar{\tau}, p', nonnegative=True)
+    C, D, E, F = sp.symbols('C, D, E, F')
+    P, w = sp.symbols('P, w')
+    x, a, L_b = sp.symbols('x, a, L_b')
+
+    d_sig_f = p * tau / A_f
+    d_sig_m = -p * tau / A_m
+
+    sig_f = sp.integrate(d_sig_f, x) + C
+    sig_m = sp.integrate(d_sig_m, x) + D
+
+    eps_f = sig_f / E_f
+    eps_m = sig_m / E_m
+
+    u_f = sp.integrate(eps_f, x) + E
+    u_m = sp.integrate(eps_m, x) + F
+
+    eq_C = {P - sig_f.subs({x:0}) * A_f}
+    C_subs = sp.solve(eq_C,C)
+    eq_D = {sig_m.subs({x:0}) * A_m}
+    D_subs = sp.solve(eq_D,D)
+
+    eqns_u_equal = {u_f.subs(C_subs).subs(x,a) - u_m.subs(D_subs).subs(x,a)}
+    E_subs = sp.solve(eqns_u_equal,E)
+
+    eqns_eps_equal = {eps_f.subs(C_subs).subs(x,a) - eps_m.subs(D_subs).subs(x,a)}
+
+    a_subs = sp.solve(eqns_eps_equal,a)
+
+    var_subs = {**C_subs,**D_subs,**E_subs,**a_subs}
+
+    u_f_x = sp.simplify( u_f.subs(var_subs) )
+    u_m_x = sp.simplify( u_m.subs(var_subs) )
+
+    A_c = A_m + A_f
+    E_c = (E_m * A_m + E_f * A_f) / (A_c)
+    G = sp.symbols('G')
+    u_c_x_ = P / A_c / E_c * x + G
+    G_subs = sp.solve( u_c_x_.subs(x, -L_b), G)[0]
+
+    u_P_c_x = sp.simplify(u_c_x_.subs(G, G_subs).subs(var_subs))
+    u_c_a = sp.simplify(u_P_c_x.subs(x,var_subs[a]) )
+
+    F_sol = sp.simplify( sp.solve( u_m_x.subs(x, a_subs[a]) - u_c_a, F)[0] )
+    u_P_mc_x = u_m_x.subs(F, F_sol)
+    u_P_fc_x = u_f_x.subs(F, F_sol)
+
+    u_P_f_x = sp.Piecewise((u_P_c_x, x <= var_subs[a]),
+                           (u_P_fc_x, x > var_subs[a])
+                        )
+    u_P_m_x = sp.Piecewise((u_P_c_x, x <= var_subs[a]),
+                           (u_P_mc_x, x > var_subs[a]),
+                         )
+    eps_P_f_x = sp.diff(u_P_f_x,x)
+    eps_P_m_x = sp.diff(u_P_m_x,x)
+    sig_P_f_x = E_f * eps_P_f_x
+    sig_P_m_x = E_m * eps_P_m_x
+    tau_P_x = sig_P_f_x.diff(x) * A_f / p
+
+    w_P_pull_ = u_P_fc_x.subs(x,0)
+
+    P_w_pull_min, P_w_pull_pls = sp.solve(w_P_pull_ - w, P)
+    P_w_pull_ = P_w_pull_min
+
+    a_w_pull = a_subs[a].subs(P, P_w_pull_)
+    w_argmax1 = sp.solve(sp.Eq(a_w_pull, -L_b), w)[0]
+
+    d_Pw_pull_dw = sp.diff(P_w_pull_, w)
+
+    w_argmax = w_argmax1
+    K_c = sp.simplify(d_Pw_pull_dw.subs({w: w_argmax}))
+
+    P_c = P_w_pull_.subs(w, w_argmax)
+    P_w_clamped = sp.Piecewise(
+        (P_w_pull_, w < w_argmax),
+        (P_c + K_c * (w - w_argmax), w >= w_argmax)
+    )
+
+
+    P_w_pull = P_w_clamped
+    w_L_b = P_w_pull * 1e-9
+
+    u_w_c_x = u_P_c_x.subs(P, P_w_pull_)
+    u_w_fc_x = u_P_fc_x.subs(P, P_w_pull_)
+    u_w_mc_x = u_P_mc_x.subs(P, P_w_pull_)
+
+    P_d = P_w_pull_ - P_c
+    u_d = P_d / A_f / E_f * (x + L_b)
+
+    u_w_f_x = sp.Piecewise((u_w_c_x, ((w <= w_argmax) & (x <= a_w_pull))),
+                           (u_w_fc_x, ((w <= w_argmax) & (x > a_w_pull))),
+                           (u_d + u_w_fc_x.subs(w, w_argmax), (w > w_argmax))
+                        )
+    u_w_m_x = sp.Piecewise((u_w_c_x, ((w <= w_argmax) & (x <= a_w_pull))),
+                            (u_w_mc_x, ((w <= w_argmax) & (x > a_w_pull))),
+                           (u_w_mc_x.subs(w, w_argmax), (w > w_argmax))
+                         )
+    eps_w_f_x = u_w_f_x.diff(x)
+    sig_w_f_x = E_f * eps_w_f_x
+    eps_w_m_x = u_w_m_x.diff(x)
+    sig_w_m_x = E_m * eps_w_m_x
+    tau_w_x = A_f / p * sig_w_f_x.diff(x)
+    tau_w_x = -A_m / p * sig_w_m_x.diff(x)
+
+    #-------------------------------------------------------------------------
+    # Declaration of the lambdified methods
+    #-------------------------------------------------------------------------
+
+    symb_model_params = ['E_f', 'A_f', 'E_m', 'A_m', 'tau', 'p', 'L_b']
+
+    symb_expressions = [
+        ('eps_w_f_x', ('x','w',)),
+        ('eps_w_m_x', ('x','w',)),
+        ('sig_w_f_x', ('x','w',)),
+        ('sig_w_m_x', ('x','w',)),
+        ('tau_w_x', ('x','w',)),
+        ('u_w_f_x', ('x','w',)),
+        ('u_w_m_x', ('x','w',)),
+        ('w_L_b', ('w',)),
+        ('a_w_pull', ('w',)),
+        ('P_w_pull', ('w',)),
+    ]
diff --git a/tour2_constant_bond/po_symb/PO_ELF_ELM_Symb.py b/tour2_constant_bond/po_symb/PO_ELF_ELM_Symb.py
new file mode 100644
index 0000000000000000000000000000000000000000..a6c7a713067dad2bee566458085a33dada3d8a73
--- /dev/null
+++ b/tour2_constant_bond/po_symb/PO_ELF_ELM_Symb.py
@@ -0,0 +1,89 @@
+
+import bmcs_utils.api as bu
+import sympy as sp
+
+
+class PO_ELF_ELM_Symb(bu.SymbExpr):
+    """Pullout of elastic Long fiber, fromm elastic long matrix
+    """
+    E_m, A_m = sp.symbols(r'E_\mathrm{m}, A_\mathrm{m}', nonnegative=True)
+    E_f, A_f = sp.symbols(r'E_\mathrm{f}, A_\mathrm{f}', nonnegative=True)
+    tau, p = sp.symbols(r'\bar{\tau}, p', nonnegative=True)
+    C, D, E, F = sp.symbols('C, D, E, F')
+    P, w = sp.symbols('P, w')
+    x, a, L_b = sp.symbols('x, a, L_b')
+
+    d_sig_f = p * tau / A_f
+    d_sig_m = -p * tau / A_m
+
+    sig_f = sp.integrate(d_sig_f, x) + C
+    sig_m = sp.integrate(d_sig_m, x) + D
+
+    eps_f = sig_f / E_f
+    eps_m = sig_m / E_m
+
+    u_f = sp.integrate(eps_f, x) + E
+    u_m = sp.integrate(eps_m, x) + F
+
+    eq_C = {P - sig_f.subs({x: 0}) * A_f}
+    C_subs = sp.solve(eq_C, C)
+    eq_D = {P + sig_m.subs({x: 0}) * A_m}
+    D_subs = sp.solve(eq_D, D)
+
+    F_subs = sp.solve({u_m.subs(x, 0) - 0}, F)
+
+    eqns_u_equal = {u_f.subs(C_subs).subs(x, a) - u_m.subs(D_subs).subs(F_subs).subs(x, a)}
+    E_subs = sp.solve(eqns_u_equal, E)
+
+    eqns_eps_equal = {eps_f.subs(C_subs).subs(x, a) - eps_m.subs(D_subs).subs(x, a)}
+    a_subs = sp.solve(eqns_eps_equal, a)
+    var_subs = {**C_subs, **D_subs, **F_subs, **E_subs, **a_subs}
+
+    u_f_x = u_f.subs(var_subs)
+    u_m_x = u_m.subs(var_subs)
+
+    u_P_f_x = sp.Piecewise((u_f_x.subs(x, var_subs[a]), x <= var_subs[a]),
+                          (u_f_x, x > var_subs[a]))
+    u_P_m_x = sp.Piecewise((u_m_x.subs(x, var_subs[a]), x <= var_subs[a]),
+                          (u_m_x, x > var_subs[a]))
+
+    eps_P_f_x = sp.diff(u_P_f_x, x)
+    eps_P_m_x = sp.diff(u_P_m_x, x)
+
+    sig_P_f_x = E_f * eps_P_f_x
+    sig_P_m_x = E_m * eps_P_m_x
+
+    tau_P_x = sig_P_f_x.diff(x) * A_f / p
+
+    Pw_push, P_w_pull = sp.solve(u_f_x.subs({x: 0}) - w, P)
+
+    w_L_b = u_P_f_x.subs(x, -L_b).subs(P, P_w_pull)
+
+    a_w_pull = a_subs[a].subs(P, P_w_pull)
+
+    eps_w_f_x = eps_P_f_x.subs(P, P_w_pull)
+    eps_w_m_x = eps_P_m_x.subs(P, P_w_pull)
+    sig_w_f_x = sig_P_f_x.subs(P, P_w_pull)
+    sig_w_m_x = sig_P_m_x.subs(P, P_w_pull)
+    u_w_f_x = u_P_f_x.subs(P, P_w_pull)
+    u_w_m_x = u_P_m_x.subs(P, P_w_pull)
+    tau_w_x = tau_P_x.subs(P, P_w_pull)
+
+    #-------------------------------------------------------------------------
+    # Declaration of the lambdified methods
+    #-------------------------------------------------------------------------
+
+    symb_model_params = ['E_f', 'A_f', 'E_m', 'A_m', 'tau', 'p', 'L_b']
+
+    symb_expressions = [
+        ('eps_w_f_x', ('x','w',)),
+        ('eps_w_m_x', ('x','w',)),
+        ('sig_w_f_x', ('x','w',)),
+        ('sig_w_m_x', ('x','w',)),
+        ('tau_w_x', ('x','w',)),
+        ('u_w_f_x', ('x','w',)),
+        ('u_w_m_x', ('x','w',)),
+        ('w_L_b', ('w',)),
+        ('a_w_pull', ('w',)),
+        ('P_w_pull', ('w',)),
+    ]
diff --git a/tour2_constant_bond/po_symb/PO_ELF_RLM_Symb.py b/tour2_constant_bond/po_symb/PO_ELF_RLM_Symb.py
new file mode 100644
index 0000000000000000000000000000000000000000..a4167f16a777b4768eb70d077c369f609d38241a
--- /dev/null
+++ b/tour2_constant_bond/po_symb/PO_ELF_RLM_Symb.py
@@ -0,0 +1,84 @@
+
+import bmcs_utils.api as bu
+import sympy as sp
+
+
+class PO_ELF_RLM_Symb(bu.SymbExpr):
+    """Pullout of elastic Long fiber, fromm rigid long matrix
+    """
+    E_f, A_f = sp.symbols(r'E_\mathrm{f}, A_\mathrm{f}', positive=True)
+    E_m, A_m = sp.symbols(r'E_\mathrm{m}, A_\mathrm{m}', positive=True)
+    tau, p = sp.symbols(r'\bar{\tau}, p', positive=True)
+    C, D = sp.symbols(r'C, D')
+    P, w = sp.symbols(r'P, w', positive=True)
+    x, a, L_b = sp.symbols(r'x, a, L_b')
+
+    d_sig_f = p * tau / A_f
+
+    sig_f = sp.integrate(d_sig_f, x) + C
+    eps_f = sig_f / E_f
+
+    u_f = sp.integrate(eps_f, x) + D
+
+    eq_C = {P - sig_f.subs({x:0}) * A_f}
+    C_subs = sp.solve(eq_C,C)
+
+    eqns_D = {u_f.subs(C_subs).subs(x, a)}
+    D_subs = sp.solve(eqns_D, D)
+
+    u_f.subs(C_subs).subs(D_subs)
+    eqns_a = {eps_f.subs(C_subs).subs(D_subs).subs(x, a)}
+    a_subs = sp.solve(eqns_a, a)
+
+    var_subs = {**C_subs,**D_subs,**a_subs}
+
+    u_f_x = u_f.subs(var_subs)
+
+    u_P_f_x = sp.Piecewise((u_f_x, x > var_subs[a]),
+                           (0, x <= var_subs[a]))
+
+    eps_P_f_x = sp.diff(u_P_f_x,x)
+
+    sig_P_f_x = E_f * eps_P_f_x
+
+    tau_P_x = sp.simplify(sig_P_f_x.diff(x) * A_f / p)
+
+    P_w_pull = sp.solve(u_f_x.subs({x: 0}) - w, P)[0]
+
+    w_L_b = u_P_f_x.subs(x, -L_b).subs(P, P_w_pull)
+
+    a_w_pull = a_subs[a].subs(P, P_w_pull)
+
+    sig_w_f_x = sp.Piecewise(
+        (0, (x < a_w_pull)),
+        (P_w_pull / A_f * (x - a_w_pull), True)
+    )
+
+    sig_w_f_x = sig_P_f_x.subs(P,P_w_pull)
+    eps_w_f_x = eps_P_f_x.subs(P,P_w_pull)
+    u_w_f_x = u_P_f_x.subs(P,P_w_pull)
+    tau_w_x = tau_P_x.subs(P,P_w_pull)
+
+    eps_w_m_x = eps_w_f_x * 1e-8
+    sig_w_m_x = sig_w_f_x * 1e-8
+    u_w_m_x = u_w_f_x * 1e-8
+
+    #-------------------------------------------------------------------------
+    # Declaration of the lambdified methods
+    #-------------------------------------------------------------------------
+
+    symb_model_params = ['E_f', 'A_f', 'tau', 'p', 'L_b']
+
+    symb_expressions = [
+        ('eps_w_f_x', ('x','w',)),
+        ('eps_w_m_x', ('x','w',)),
+        ('sig_w_f_x', ('x','w',)),
+        ('sig_w_f_x', ('x','w',)),
+        ('sig_w_m_x', ('x','w',)),
+        ('tau_w_x', ('x','w',)),
+        ('u_w_f_x', ('x','w',)),
+        ('u_w_m_x', ('x','w',)),
+        ('w_L_b', ('w',)),
+        ('a_w_pull', ('w',)),
+        ('P_w_pull', ('w',)),
+    ]
diff --git a/tour2_constant_bond/po_symb/PO_ELF_RSM_Symb.py b/tour2_constant_bond/po_symb/PO_ELF_RSM_Symb.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee96495e3c5a22b4cf36e1af7149ae35cb8c23e4
--- /dev/null
+++ b/tour2_constant_bond/po_symb/PO_ELF_RSM_Symb.py
@@ -0,0 +1,80 @@
+
+import bmcs_utils.api as bu
+import sympy as sp
+
+
+class PO_ELF_RLM_Symb(bu.SymbExpr):
+    """Pullout of elastic Long fiber, fromm rigid long matrix
+    """
+    E_f, A_f = sp.symbols(r'E_\mathrm{f}, A_\mathrm{f}', positive=True)
+    E_m, A_m = sp.symbols(r'E_\mathrm{m}, A_\mathrm{m}', positive=True)
+    tau, p = sp.symbols(r'\bar{\tau}, p', positive=True)
+    C, D = sp.symbols(r'C, D')
+    P, w = sp.symbols(r'P, w', positive=True)
+    x, a, L_b = sp.symbols(r'x, a, L_b')
+
+    d_sig_f = p * tau / A_f
+
+    sig_f = sp.integrate(d_sig_f, x) + C
+    eps_f = sig_f / E_f
+
+    u_f = sp.integrate(eps_f, x) + D
+
+    eq_C = {P - sig_f.subs({x:0}) * A_f}
+    C_subs = sp.solve(eq_C,C)
+
+    eqns_D = {u_f.subs(C_subs).subs(x, a)}
+    D_subs = sp.solve(eqns_D, D)
+
+    u_f.subs(C_subs).subs(D_subs)
+    eqns_a = {eps_f.subs(C_subs).subs(D_subs).subs(x, a)}
+    a_subs = sp.solve(eqns_a, a)
+
+    var_subs = {**C_subs,**D_subs,**a_subs}
+
+    u_f_x = u_f.subs(var_subs)
+
+    u_fa_x = sp.Piecewise((u_f_x, x > var_subs[a]),
+                          (0, x <= var_subs[a]))
+
+    eps_f_x = sp.diff(u_fa_x,x)
+
+    sig_f_x = E_f * eps_f_x
+
+    tau_x = sp.simplify(sig_f_x.diff(x) * A_f / p)
+
+    u_f_x.subs(x, 0) - w
+
+    Pw_pull = sp.solve(u_f_x.subs({x: 0}) - w, P)[0]
+
+    P_max = p * tau * L_b
+    w_argmax = sp.solve(P_max - Pw_pull, w)[0]
+
+    Pw_pull_Lb = sp.Piecewise((Pw_pull, w < w_argmax),
+                              (P_max, w >= w_argmax))
+
+    w_L_b = u_fa_x.subs(x, -L_b).subs(P, Pw_pull)
+
+    aw_pull = a_subs[a].subs(P, Pw_pull)
+
+    eps_m_x = eps_f_x * 1e-8
+    sig_m_x = sig_f_x * 1e-8
+    u_ma_x = u_fa_x * 1e-8
+    #-------------------------------------------------------------------------
+    # Declaration of the lambdified methods
+    #-------------------------------------------------------------------------
+
+    symb_model_params = ['E_f', 'A_f', 'tau', 'p', 'L_b']
+
+    symb_expressions = [
+        ('eps_f_x', ('x','P',)),
+        ('eps_m_x', ('x','P',)),
+        ('sig_f_x', ('x','P',)),
+        ('sig_m_x', ('x','P',)),
+        ('tau_x', ('x','P',)),
+        ('u_fa_x', ('x','P',)),
+        ('u_ma_x', ('x','P',)),
+        ('w_L_b', ('w',)),
+        ('aw_pull', ('w',)),
+        ('Pw_pull', ('w',)),
+    ]
diff --git a/tour2_constant_bond/po_symb/PO_ESF_RLM_Symb.py b/tour2_constant_bond/po_symb/PO_ESF_RLM_Symb.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6b4ecb7cd0bda56200f5d53ca982b5dd3ad61ce
--- /dev/null
+++ b/tour2_constant_bond/po_symb/PO_ESF_RLM_Symb.py
@@ -0,0 +1,117 @@
+
+import bmcs_utils.api as bu
+import sympy as sp
+import numpy as np
+np.warnings.filterwarnings('ignore', category=np.VisibleDeprecationWarning)
+
+
+class PO_ESF_RLM_Symb(bu.SymbExpr):
+
+    E_f, A_f = sp.symbols(r'E_\mathrm{f}, A_\mathrm{f}', positive=True)
+    E_m, A_m = sp.symbols(r'E_\mathrm{m}, A_\mathrm{m}', positive=True)
+    tau, p = sp.symbols(r'\bar{\tau}, p', positive=True)
+    C, D = sp.symbols(r'C, D')
+    P, w = sp.symbols(r'P, w', positive=True)
+    x, a, L_b = sp.symbols(r'x, a, L_b')
+
+    d_sig_f = p * tau / A_f
+
+    sig_f = sp.integrate(d_sig_f, x) + C
+    eps_f = sig_f / E_f
+
+    u_f = sp.integrate(eps_f, x) + D
+
+    eq_C = {P - sig_f.subs({x:0}) * A_f}
+    C_subs = sp.solve(eq_C,C)
+
+    eqns_D = {u_f.subs(C_subs).subs(x, a)}
+    D_subs = sp.solve(eqns_D, D)
+
+    u_f.subs(C_subs).subs(D_subs)
+    eqns_a = {eps_f.subs(C_subs).subs(D_subs).subs(x, a)}
+    a_subs = sp.solve(eqns_a, a)
+
+    var_subs = {**C_subs,**D_subs,**a_subs}
+
+    u_f_x = u_f.subs(var_subs)
+
+    u_P_f_x = sp.Piecewise((u_f_x, x > var_subs[a]),
+                          (0, x <= var_subs[a]))
+
+    eps_P_f_x = sp.diff(u_P_f_x,x)
+
+    sig_P_f_x = E_f * eps_P_f_x
+
+    tau_P_x = sp.simplify(sig_P_f_x.diff(x) * A_f / p)
+
+    P_w_pull = sp.solve(u_f_x.subs({x: 0}) - w, P)[0]
+
+    w_L_b = u_P_f_x.subs(x, -L_b).subs(P, P_w_pull)
+
+    a_w_pull = a_subs[a].subs(P, P_w_pull)
+
+    P_max = p * tau * L_b
+    w_argmax = sp.solve(P_max - P_w_pull, w)[0]
+    P_w_up_pull = P_w_pull
+    b, P_down = sp.symbols(r'b, P_\mathrm{down}')
+    sig_down = P_down / A_f
+    eps_down = 1 / E_f * sig_down
+    w_down = (L_b + b) - sp.Rational(1, 2) * eps_down * b
+    P_w_down_pull, P_w_down_push = sp.solve(
+        w_down.subs(b, -P_down / p / tau) - w,
+        P_down
+    )
+
+    P_w_short = sp.Piecewise((0, w <= 0),
+                            (P_w_up_pull, w <= w_argmax),
+                            (P_w_down_pull, w < L_b),
+                            (0, True)
+                            )
+
+    w_L_b_a = L_b - P_w_down_pull / p / tau
+    w_L_b = sp.Piecewise((0, w <= w_argmax),
+                         (w_L_b_a, (w > w_argmax) & (w <= L_b)),
+                         (w, True))
+    a_w_pull = - (P_w_short / p / tau)
+    P_w_pull = P_w_short
+
+    a_w_up = -P_w_up_pull / p / tau
+    b_w_down = -P_w_down_pull / p / tau
+
+    u_w_f_up = sp.integrate(-P_w_up_pull / E_f/ A_f / a_w_up * (x - a_w_up),(x, a_w_up, x))
+    u_w_f_do = sp.integrate(-P_w_down_pull / E_f/ A_f / b_w_down * (x - b_w_down),(x, b_w_down, x))
+    u_w_f_x = sp.Piecewise(
+        (0, ((w <= w_argmax) & (x <= a_w_up))),
+        (u_w_f_up, ((w <= w_argmax) & (x > a_w_up))),
+        (0, ((w > w_argmax) & (x <= b_w_down))),
+        (u_w_f_do + w_L_b, ((w > w_argmax) & (x > b_w_down))),
+    )
+    eps_w_f_x = u_w_f_x.diff(x)
+    sig_w_f_x = E_f * eps_w_f_x
+    tau_w_x = sig_w_f_x.diff(x)
+
+    eps_w_m_x = x * 1e-9
+    sig_w_m_x = x * 1e-9
+    u_w_m_x = x * 1e-9 # u_w_f_x * 1e-8
+
+    #-------------------------------------------------------------------------
+    # Declaration of the lambdified methods
+    #-------------------------------------------------------------------------
+
+    symb_model_params = ['E_f', 'A_f', 'E_m', 'A_m', 'tau', 'p', 'L_b']
+
+    symb_expressions = [
+        ('u_w_f_x', ('x','w',)),
+        ('u_w_m_x', ('x','w',)),
+        ('eps_w_f_x', ('x','w',)),
+        ('eps_w_m_x', ('x','w',)),
+        ('sig_w_f_x', ('x','w',)),
+        ('sig_w_f_x', ('x','w',)),
+        ('sig_w_m_x', ('x','w',)),
+        ('sig_w_m_x', ('x','w',)),
+        ('tau_w_x', ('x','w',)),
+        ('w_L_b', ('w',)),
+        ('a_w_pull', ('w',)),
+        ('P_w_pull', ('w',)),
+    ]
+
diff --git a/tour2_constant_bond/po_symb/__init__.py b/tour2_constant_bond/po_symb/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..0367f989c2a90b84925377ba987c842c0e442960
--- /dev/null
+++ b/tour2_constant_bond/po_symb/__init__.py
@@ -0,0 +1,5 @@
+
+from .CB_ELF_ELM_Symb import CB_ELF_ELM_Symb
+from .PO_ELF_RLM_Symb import PO_ELF_RLM_Symb
+from .PO_ELF_ELM_Symb import PO_ELF_ELM_Symb
+from .PO_ESF_RLM_Symb import PO_ESF_RLM_Symb
\ No newline at end of file
diff --git a/tour2_constant_bond/pull_out.py b/tour2_constant_bond/pull_out.py
new file mode 100644
index 0000000000000000000000000000000000000000..8beec3205c4d9494de825498f8ed72b9ebb5fb99
--- /dev/null
+++ b/tour2_constant_bond/pull_out.py
@@ -0,0 +1,212 @@
+
+
+import bmcs_utils.api as bu
+import numpy as np
+import sympy as sp
+import traits.api as tr
+
+from po_symb import \
+    CB_ELF_ELM_Symb, PO_ELF_RLM_Symb, PO_ESF_RLM_Symb, PO_ELF_ELM_Symb
+
+class PullOutAModel(bu.Model, bu.InjectSymbExpr):
+    """
+    General pullout elastic long fiber and rigid long matrix
+    """
+    symb_class = PO_ELF_RLM_Symb
+
+    name = "Pull-Out"
+
+    E_f = bu.Float(210000, MAT=True)
+    E_m = bu.Float(28000, MAT=True)
+    tau = bu.Float(8, MAT=True)
+    A_f = bu.Float(100, CS=True)
+    A_m = bu.Float(100*100, CS=True)
+    p = bu.Float(20, CS=True)
+    L_b = bu.Float(300, GEO=True)
+    w_max = bu.Float(3, BC=True)
+
+    t = bu.Float(0.0)
+    t_max = bu.Float(1.0)
+
+    ipw_view = bu.View(
+        bu.Item('E_f', latex=r'E_\mathrm{f}~[\mathrm{MPa}]'),
+        bu.Item('E_m', latex=r'E_\mathrm{m}~[\mathrm{MPa}]'),
+        bu.Item('tau', latex=r'\tau~[\mathrm{MPa}]'),
+        bu.Item('A_f', latex=r'A_\mathrm{f}~[\mathrm{mm}^2]'),
+        bu.Item('A_m', latex=r'A_\mathrm{m}~[\mathrm{mm}^2]'),
+        bu.Item('p', latex=r'p~[\mathrm{mm}]'),
+        bu.Item('L_b', latex=r'L_\mathrm{b}~[\mathrm{mm}]'),
+        bu.Item('w_max', latex=r'w_\max~[\mathrm{mm}]'),
+        time_editor = bu.HistoryEditor(
+            var='t',
+            var_max='t_max'
+        )
+    )
+
+    w_range = tr.Property(depends_on='state_changed')
+    """Pull-out range w"""
+    @tr.cached_property
+    def _get_w_range(self):
+        return np.linspace(0, self.w_max, 100)
+
+    def plot_Pw(self, ax):
+        w = self.t * self.w_max
+        P = 0.001*self.symb.get_P_w_pull(w)
+        w_L_b = self.symb.get_w_L_b(w)
+        ax.plot(w,P,marker='o', color='blue')
+        ax.plot(w_L_b,P,marker='o', color='blue')
+
+        P_range = self.symb.get_P_w_pull(self.w_range)
+        w_L_b_range = self.symb.get_w_L_b(self.w_range)
+        ax.plot(self.w_range, P_range * 0.001, color='blue', label=r'$w(0)$')
+        ax.plot(w_L_b_range, P_range * 0.001, color='blue', linestyle='dashed',
+                label=r'$w(L_\mathrm{b})$')
+        ax.set_ylabel(r'$P$ [kN]')
+        ax.set_xlabel(r'$w$ [mm]')
+        ax.legend()
+
+    def subplots(self, fig):
+        gs = fig.add_gridspec(2,2, width_ratios=[1., 1.])
+        ax1 = fig.add_subplot(gs[0,0])
+        ax2 = fig.add_subplot(gs[0,1])
+        ax3 = fig.add_subplot(gs[1,0])
+        ax4 = fig.add_subplot(gs[1,1])
+        ax44 = ax4.twinx()
+        return ax1, ax2, ax3, ax4, ax44
+
+    def plot_fields(self, ax_u, ax_eps, ax_sig, ax_tau):
+        L_b = self.L_b
+        x_range = np.linspace(-L_b, 0, 100)
+        w_max = self.w_max
+        w_range = self.w_range
+        P_range = self.symb.get_P_w_pull(self.w_range)
+        w_argmax = w_range[np.argmax(P_range)]
+        w = self.t * w_max
+        eps_f_range = self.symb.get_eps_w_f_x(x_range, w)
+        sig_f_range = self.symb.get_sig_w_f_x(x_range, w)
+        N_f_range = self.A_f * sig_f_range
+        u_f_range = self.symb.get_u_w_f_x(x_range, w)
+        eps_m_range = self.symb.get_eps_w_m_x(x_range, w)
+        sig_m_range = self.symb.get_sig_w_m_x(x_range, w)
+        N_m_range = self.A_m * sig_m_range
+        u_m_range = self.symb.get_u_w_m_x(x_range, w)
+        tau_range = self.symb.get_tau_w_x(x_range, w) * np.ones_like(x_range)
+        T_range = self.p * tau_range
+
+        eps_max = np.max(self.symb.get_eps_w_f_x(x_range, w_argmax))
+        sig_max = np.max(self.symb.get_sig_w_f_x(x_range, w_argmax))
+        N_max = self.A_f * sig_max
+        u_max = w_max
+        eps_min = np.min(self.symb.get_eps_w_m_x(x_range, w_argmax))
+        sig_min = np.min(self.symb.get_sig_w_m_x(x_range, w_argmax))
+        N_min = self.A_m * sig_min
+        u_min = np.min(self.symb.get_u_w_m_x(x_range, w_argmax))
+        tau_max = self.tau
+        T_max = self.p * tau_max
+        x_min = -L_b
+        x_max = 0
+
+
+        self.plot_filled_var(
+            ax_u, x_range, u_f_range,
+            color='brown', alpha=0.2,
+            ylim=(u_min, u_max), xlim=(x_min,x_max)
+            )
+
+        self.plot_filled_var(
+            ax_u, x_range, u_m_range,
+            xlabel='$x$ [mm]', ylabel='$u$ [mm]',
+            color='black', alpha=0.2,
+            ylim=(u_min, u_max), xlim=(x_min,x_max)
+            )
+
+        self.plot_filled_var(
+            ax_eps, x_range, eps_f_range,
+            xlabel='$x$ [mm]', ylabel=r'$\varepsilon$ [mm]', color='green',
+            ylim=(eps_min, eps_max), xlim=(x_min,x_max)
+            )
+
+        self.plot_filled_var(
+            ax_eps, x_range, eps_m_range,
+            xlabel='$x$ [mm]', ylabel=r'$\varepsilon$ [mm]', color='green',
+            ylim=(eps_min, eps_max), xlim=(x_min,x_max)
+            )
+
+        self.plot_filled_var(
+            ax_sig, x_range, N_f_range,
+            xlabel='$x$ [mm]', ylabel=r'$N$ [N]', color='blue',
+            ylim=(sig_min, sig_max), xlim=(x_min,x_max)
+            )
+
+        self.plot_filled_var(
+            ax_sig, x_range, N_m_range,
+            xlabel='$x$ [mm]', ylabel=r'$N$ [N]', color='blue',
+            ylim=(N_min, N_max), xlim=(x_min,x_max)
+            )
+
+        self.plot_filled_var(
+            ax_tau, x_range, T_range,
+            xlabel='$x$ [mm]', ylabel=r'$T$ [N/mm]', color='red',
+            ylim=(0, T_max), xlim=(x_min,x_max)
+            )
+
+    def update_plot(self, axes):
+        ax_Pw, ax_u, ax_eps, ax_sig, ax_tau = axes
+        self.plot_Pw(ax_Pw)
+        self.plot_fields(ax_u, ax_eps, ax_sig, ax_tau)
+
+    def plot_filled_var(self, ax, xdata, ydata, xlabel='', ylabel='',
+                        color='black', alpha=0.1, ylim=None, xlim=None):
+        line, = ax.plot(xdata, ydata, color=color);
+        if xlabel:
+            ax.set_xlabel(xlabel);
+        if ylabel:
+            ax.set_ylabel(ylabel)
+        if ylim:
+            y_min, y_max = ylim
+            dy = y_max - y_min
+            ax.set_ylim(y_min-0.05*dy, y_max+0.05*dy)
+        if xlim:
+            x_min, x_max = xlim
+            dx = x_max - x_min
+            ax.set_xlim(x_min-0.05*dx, x_max+0.05*dx)
+        ax.fill_between(xdata, ydata, 0, color=color, alpha=alpha);
+        return line
+
+class PO_ELF_RLM(PullOutAModel):
+    name='PO_ELF_RLM'
+    symb_class = PO_ELF_RLM_Symb
+
+class PO_ESF_RLM(PullOutAModel):
+    name='PO_ESF_RLM'
+    symb_class = PO_ESF_RLM_Symb
+
+class PO_ELF_ELM(PullOutAModel):
+    name='PO_ELF_ELM'
+    symb_class = PO_ELF_ELM_Symb
+
+class CB_ELF_ELM(PullOutAModel):
+    name='CB_ELF_ELM'
+    symb_class = CB_ELF_ELM_Symb
+
+
+class PullOutAModelExplorer(bu.Model):
+    """fix the update behavior"""
+    name = 'Pullout Explorer'
+    PO_ELF_RLM = bu.Instance(PullOutAModel, ())
+    def _PO_ELF_RLM_default(self):
+        return PullOutAModel(symb_class=PO_ELF_RLM_Symb)
+
+    PO_ELF_ELM = bu.Instance(PullOutAModel, ())
+    def _PO_ELF_ELM_default(self):
+        return PullOutAModel(symb_class=PO_ELF_ELM_Symb)
+
+    PO_ESF_RLM = bu.Instance(PullOutAModel, ())
+    def _PO_ESF_RLM_default(self):
+        return PullOutAModel(symb_class=PO_ESF_RLM_Symb)
+
+    CB_ECF_ECM = bu.Instance(PullOutAModel, ())
+    def _CB_ECF_ECM_default(self):
+        return PullOutAModel(symb_class=CB_ELF_ELM_Symb)
+
+    tree = ['PO_ELF_RLM', 'PO_ELF_ELM', 'PO_ESF_RLM', 'CB_ECF_ECM']
diff --git a/tour3-nonlinear-bond/3_2_anchorage_length.ipynb b/tour3-nonlinear-bond/3_2_anchorage_length.ipynb
deleted file mode 100644
index cc4e16ca6ebf87564f1b32902ec85c37c023442f..0000000000000000000000000000000000000000
--- a/tour3-nonlinear-bond/3_2_anchorage_length.ipynb
+++ /dev/null
@@ -1,101 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "# **3.2 Failure modes: pullout, fiber rupture, matrix crack**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/start_flag.png\" alt=\"Previous trip\" width=\"60\" height=\"60\">\n",
-    "    &nbsp; &nbsp; <b>Starting point</b> </div> "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To enforce the conclusions made in [3.1 Hardening and softening](3_1_nonlinear_bond.ipynb) let us classify the failure modes in view of the type of the bond-slip law."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/destination.png\" alt=\"Previous trip\" width=\"60\" height=\"60\">\n",
-    "    &nbsp; &nbsp; <b>Where are we heading</b> </div> "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To be completed"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/exercise.png\" alt=\"Run\" width=\"40\" height=\"40\">\n",
-    "    &nbsp; &nbsp; <a href=\"../exercises/X0303 - Anchorage length.pdf\"><b>Exercise X0303:</b></a> <b>Anchorage length</b> \n",
-    "<a href=\"https://moodle.rwth-aachen.de/mod/page/view.php?id=551825\"><img src=\"../icons/bmcs_video.png\" alt=\"Run\"></a>\n",
-    "</div>"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "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": "3.9.1"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": true,
-   "sideBar": true,
-   "skip_h1_title": true,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {
-    "height": "calc(100% - 180px)",
-    "left": "10px",
-    "top": "150px",
-    "width": "203.5px"
-   },
-   "toc_section_display": true,
-   "toc_window_display": false
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/tour3-nonlinear-bond/3_1_nonlinear_bond.ipynb b/tour3_nonlinear_bond/3_1_nonlinear_bond.ipynb
similarity index 99%
rename from tour3-nonlinear-bond/3_1_nonlinear_bond.ipynb
rename to tour3_nonlinear_bond/3_1_nonlinear_bond.ipynb
index b8f9ba906ac232dbb2acf1b7d35a02126d8bcba5..e701df35f488e225bf38f780eb59bc4a9b3f269d 100644
--- a/tour3-nonlinear-bond/3_1_nonlinear_bond.ipynb
+++ b/tour3_nonlinear_bond/3_1_nonlinear_bond.ipynb
@@ -8,6 +8,7 @@
     }
    },
    "source": [
+    "<a id=\"top\"></a>\n",
     "# **3.1 Nonlinear bond - softening and hardening**"
    ]
   },
@@ -15,7 +16,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/start_flag.png\" alt=\"Previous trip\" width=\"60\" height=\"60\">\n",
+    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/start_flag.png\" alt=\"Previous trip\" width=\"40\" height=\"40\">\n",
     "    &nbsp; &nbsp; <b>Starting point</b> </div> "
    ]
   },
@@ -37,7 +38,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/destination.png\" alt=\"Previous trip\" width=\"60\" height=\"60\">\n",
+    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/destination.png\" alt=\"Previous trip\" width=\"40\" height=\"40\">\n",
     "    &nbsp; &nbsp; <b>Where are we heading</b> </div> "
    ]
   },
@@ -2308,7 +2309,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a231a6dcdba44f3ba3e463ae8c688fcc",
+       "model_id": "2dba3869e34146709cdc6c77a21e6d7e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -2346,20 +2347,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/rch/miniconda3/lib/python3.9/site-packages/traits/observation/_has_traits_helpers.py:70: RuntimeWarning: Trait '_wrappers' (trait type: List) on class ActionItem is defined with comparison_mode=<ComparisonMode.equality: 2>. Mutations and extended traits cannot be observed if a new container compared equally to the old one is set. Redefine the trait with List(..., comparison_mode=<ComparisonMode.identity: 1>) to avoid this.\n",
-      "  warnings.warn(\n",
-      "/home/rch/miniconda3/lib/python3.9/site-packages/traits/observation/_has_traits_helpers.py:70: RuntimeWarning: Trait '_wrappers' (trait type: List) on class ActionItem is defined with comparison_mode=<ComparisonMode.equality: 2>. Mutations and extended traits cannot be observed if a new container compared equally to the old one is set. Redefine the trait with List(..., comparison_mode=<ComparisonMode.identity: 1>) to avoid this.\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from bmcs_cross_section.pullout import PullOutModel1D"
    ]
@@ -2773,6 +2763,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "<a id=\"cfrp_sheet_test\"></a>\n",
     "# **Studies 2: Softening bond-slip law**"
    ]
   },
@@ -3004,7 +2995,8 @@
    "source": [
     "Note that a list in python is defined by the brackets\n",
     "```[1,2,3,4]```. Two lists can be \"zipped\" together so that we can run\n",
-    "a loop over the lengths and colors as shown in the third line of the cell"
+    "a loop over the lengths and colors as shown in the third line of the cell\n",
+    "<a id=\"crfp_study\"></a>"
    ]
   },
   {
diff --git a/tour3_nonlinear_bond/3_2_anchorage_length.ipynb b/tour3_nonlinear_bond/3_2_anchorage_length.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..1ae4aedfbe5bcb196c34c192a665b67249c2f7c8
--- /dev/null
+++ b/tour3_nonlinear_bond/3_2_anchorage_length.ipynb
@@ -0,0 +1,621 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "<a id=\"top\"></a>\n",
+    "# **3.2 Pullout curve versus bond length**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/start_flag.png\" alt=\"Previous trip\" width=\"40\" height=\"40\">\n",
+    "    &nbsp; &nbsp; <b>Starting point</b> </div> "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the previous notebook [3.1 Hardening and softening](3_1_nonlinear_bond.ipynb#top) we have seen that the effect of the softening \n",
+    "in the bond-slip law affects the pullout response in a qualitatively different way than a constant or increasing shear stress for a growing slip."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/destination.png\" alt=\"Previous trip\" width=\"40\" height=\"40\">\n",
+    "    &nbsp; &nbsp; <b>Where are we heading</b> </div> "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To deepen our understanding of the correspondence between the bond length and maximum achievable pullout force we will \n",
+    "study the response of three types of composites. With the pullout model introduced in notebook [3.1](3_1_nonlinear_bond.ipynb#model)\n",
+    "we will simulate the pullout curve for a changing bond length and extract characteristic points of the structural response.\n",
+    "In particular, we are interested in the trend of the maximum pullout force versus the bond length."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**More observation perspectives:** We can establish a direct relation between the level of our understanding of the observed phenomena, e.g. pull-out behavior, and the quality of the models we are able to formulate. The better the model, the more general the design rules can be formulated. Thus, the validity of the model is a central issue.\n",
+    "When designing experimental setups, it is therefore crucial \n",
+    " - to formulate a hypothesis how the phenomenology works\n",
+    " - to provide several perspective of observation by changing some parameters\n",
+    " \n",
+    "Indeed, the change of the bond length is an easy way how to extract much more information from the test then if only single geometrical configuration is used. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Parametric studies:** The notebook demonstrates an important discipline of engineering research, namely capturing the correspondence between the material behavior, geometrical configuration using design formulas and rules directly applicable in engineering practice. Many design formulas are derived solely based on \n",
+    "thorough experimental studies. With an increasing quality, or more precisely, validity of the models, some design configurations can be also covered based on the simulation results. In the subsequent studies, we will use a model and as a virtual experiment to demonstrate the derivation of a formula for **anchorage length**, i.e. the minimum necessary bond length that guarantees the full utilization of the reinforcement."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **Case study: textile reinforced concrete**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To characterize the bond behavior between carbon fabrics penetrated with rubber-like material the test setup with a variable bond length has been. This symmetric, double-sided pullout-test was chosen to appropriately reflect the condition of a typical crack bridge as it occurs in structural TRC members under tensional or bending loads."
+   ]
+  },
+  {
+   "attachments": {
+    "0ebcbb43-c944-42e1-bf82-26894ad4513f.png": {
+     "image/png": 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L5bLHcpPsiV4DpQKY0nrUEwo0hk1qEyZ1H9alCvCB9UnSOoJZP735bm5Fj3wS/g72y8iPYZ0JHS2eLsoJvho3qPAQehrQ4f3A2y7ZFWP9alJOBLU+8ANlhfMl/oj9L3wqjYlUgwDbcvzn3i+nSJTmqSC3UkWjbJTAWJ6U8kPoZxEKL+5aUj5ZAQCm3DN9EjzC4Bh6zLl9PyYd6/WcC/HmQH42ZOPp4I+LHRre2wkQDda5EhYpFYqw0B5BiloX8vfkCdAynHgV50tMz0/6NqmztBiBw3PK/OTbEQQfR0XA4UfT90EvcgaoHsuLj23rD3suB6Tq4Nkf6s0uvj8znz/HEOvj6FDpHm8WzJECvUCh7LIieMzQEWDFN8X/ue4IVI4vM8zd9Iy/WX6ZHRI/8/9SXQ/TlN3GY6NKzSnvYp5VSkfSdIwVAO/CWY9BHrsE+PIueZR1mdZa9F/OHQ3oUY4rRdApHC7y38xBIel+x4x8kGUf5ovOz1POJwTK49853EqSaeaoK+VHvuW4Tc9HCVR6XTpoOBelo57maE4/HRgw94z1seX+XGTkjw4s5wbu0EocHf0Ph4UJLo+tXyrIwyvpxroSu4nnj6PRtf0wuRmrn2XItpSGQJ6l532+4CVo08kDI8OWk6MH4o+eOZvyMYxbCu8/JKSOBWFTz55L/+M4lZupD6y3uTQEPVGu91NJyNA6HufkIWE0ekz4fs5/pfMNP2Q+5uiQh+6va+zb6HU+vk3RwFFCsavyfTTFthZjX6UH/SMx3E9vbH5M+lA+kTLiELwcUf/Mo4+NNM3JEPncY/sqZUDR4fWJlHWpT3I8jDGTZx5b5tz3eVRnMmbKISQN++TFKi+F0Xg+qL/wvNQteVsfolw3PHY+HmO83wfscoD52Pofqucx7z+2jB+bfgJgCZQkTBGEYLrY5sLr4fPjgKW1Y5ljWaq0RsDcpR/ijfH++EOi7/O4jaHk+XbQihq/L4coAQ3vVbpj13uHkP/Cg1IB+PHKKhnGZuj5+HGQIJB/l0JYozeEzx0PLlmLE96HeeGhlIE/CBOGxPJQtQiHTdp2Ty9n5wSTORsjG4eeZGlAsKwQgsjHvHwg8XECJsz/cVReD/cZBaEP5ffuo7HMcQySQvuANh1+iCPddtKg/JgkDYVPVe5D/XusIpp6vMjT421RDnMe0inNK8aSJ64MTOQ7jwO1czTWL1JrCmvU+/Itbh9KdCiMHr0Ypp0Qjc3DvpYcEiPv+4PvvXepf6VNd+H9UGfucCiRLsiT8m13jwFBBZPSj9+Nc1ZOh3gIhN0X1aPTZa5Nsu7HUDEi+wgD6EPf/ynoZxEKBwqDp8rflRnn+EGWeTUPuZiVcpPnHgcup3ma94W65wREXvfDAHf0TpaBZUh8TkypdchViRugkoADABcOo6U3KpWRwJwAYH4USOz7FFgS9ZX1e8hPOWKcoy6btsUnj+Xc+IzlHhrZkzQCjzROYz+mZcylGMyDy/vzY6fAbCynxKfHAqs5Uuq4mzLmvO0Ptf8xXvq8zAkAxyGwDN9rHCqIqQdEeqBK3pkjWoRggD1eeTwsHz6VIqAZRABSqsc9Ym44Azmo5MYXPuNm6josjx7tyaezXrWZUo7xWioUc8qkAUua3lt9v0fs0wBLJ+oLYxxy/Ap3zXvO6/08lgOntBbgUz6sc2Euped5fHbk//uAZdBbx1xHOl2fj/dYjn0+Cuzec+tTHqWbuxd97l3O0SiDjpMTj6nnQ99/rAMsezmV/UHl4CMCSzaG92lOwyUjTQEIPyt1QoVrIWOIm0n+ZIr82riSUFBKoWkaWGvRdR2cc+OF8oKxpDJXSqGqqoMFKhlSls8T6nOS1wNKcMArL/luVVXp2Xw8c6XL90cl7FOf8rGQ7R3LdhgGi7quY/jcCytWAhcfz20brVgqE6nQ2RcghG14v7e14tpOgebkFVGT/sVUhqqqMQwDtDaJf+S48JpQ5+xocQtBw/I5r8651K7wmYf3Nhur3Esw5uwyFEW+MMag7/uD6x/5XX4lJD/nfdZyPnP+zYEk6+BzwzCkz/u+T3xsrZ3cWyvHVpbF77iOeP2qXKcy9FZVVVGBS17l88MwoGkaOOdS24wxiT/quk58K4lzxr5xDJXWYG4Wx5Lv52Mo+8G54Rruug6r1SrJJHnNrLU2rd38KlrvPIYhfN91Hbz3SY7kQHru6lD2i/M02D7x2fROejeZL7YlX8+SPySfO++hlYe14x3G1h3eV5zARYE38vXohmHCz+zDCIQQjDCMO2pzvsvlpPfTMeG6kryZ7mIW0YeJ0RLl0WBDGbn8Se3AVE9IHpOGoHVD7P+4joyu0ljKNrAs1mGthfNhXZO/yT9936dxk3PHMtPci/mQd1DPGa9sI4AkUyjfpD6jTuB4cv76YR/GySPp1onu8UgGgFxzcswk7yR+s3ZSH/seZLlG31tUlUl9SOMv1qC1FtZa1I2Z8LqUe3QmuLjDJkSgpnqy7/tJm2X/chkpxzaspeCBl+CU7yfd5mwc6+CQoZymzJFjIOW41HuyHfK3bKMcR64TjpGUPbIvxpiDssn/cn2W5Ho+Xhz7H3o96yfzWMrJlRRw4sNoXe6a4mSQCff7Pfb7/cjcZmR0Pg+EQd11W/T9HnawUDqEfUPRo/UxMtlY3wi21AGjIgovrRW0NukzpWPonBYW2+KDS4+gerLbT/F2lfCe0iEp2UXprRW9iQEAVvndyN6jquuDzyBAPmJbw92uo4Bv23YirKQA5PVWpTHIf1NY8DMyswRBZNJ8sWmt0XVdKottya8HJEDh/ym0vXfwbhCL32PoA9BBGkegMhWsnVpjUkDKxRpADpKC5vMES8ZoOOfhrIU2Js0dnzc6gtnEjw52sGjadiKEOKdpXAjCvcdgh1SWEkBWKwVTVUD0QDjnYCoDo0eBDBV4TFgK0ErBuhHwJx7MBIrWPHpKCCrvx3Fk3d4n3rfWom0baKXRDz2MqVDXFfp+gHcu8Wff7yOPKzDNZBgsAA9jKpgEihSatgEQ1nr43iSwx3Hj/wMPuokQZdnb7QbOOTRNHZ9RGAYLpdg/k/hIKY22baF1PYKHKNSHYZgAfdYz58nid33fo2maCLztOMYFwCGBfw4mpJzKAcicsshJ8v2ckZe3ra7rYj+TklQeWoc5Dc+NskzUjGE/gkC59uXfCYiJ0CPbIsdByhu+Q2BXGisaFaUxkIqTwEWWkYMMkjEGBgr90Kf2SDAuxzcH0BJ4UhZKw0nKpbw8kvybIFOOKf+W4EyO6RCNh5yHtKqi7mOdkr/CXNJzN+oiD+fsBMSFdTl60CVv5vyeg1R+TpkunVWprWlfQQYOhVOLP5Tb0vAsGQ50jub6DBgdOpKnpFHFeXBSxma8KvlI1puvWznvlEGyPeyD5BH+5LJpzvj91PQThMIP3fklgejg4K2HNnpigW02G/zxj3/Ezc0NFosFvPdYr29h3YC6rpPnhAuHExPqCApEax29KtUIRobAeH2/xzBYLBYLXF5ewNrgIQteOODy8jIy6ZAUBSAnXE88E03TwHuP3W6XQFbXddjvewBAVY2AYPRkaFSVgTGj4BmGHsNg4b1D13UAgLOzM5ydnaU+DsOQrBqtNdp2gcWiTdZ91/UY+pFhF4tFfNZEkDy2f7AW1o19D8I5MDSVDftGYBgYPQiV3W4HpRS6rsPl5RW0VlgsFqmvm80G1lo0TYvVagmlNIahj2A39FcumtBmB2uHBDK1NvB+gLN9sn4JPjmW+/0+9nUJBY1oA2D0xk6BlXMOy+UC+36H3W4LAGjbFnVdY73ewNoBi8UiA8AqzSN/aPg0TYM2AkoAyaKu6yb1BSCgDcKaHr+2bZNg7fsBm80a3gNnZ6s0z1QOfd+j67r0XvKURZ4I/NBiGAZstzt477BcLrNVp7BYtGiaNoCDKJS6rotC00dQHQQW29d1+zRf7N9yuRRCOQC78H878TSFMqpU7jAMGGK/jDGwzqLf98EwMToBhKZusFwusd6sAQDru3VSTHVdB+OgCutfIbR1s90EmeE8FosFqqrCvu9hqIgQDJC6XsLoGs+fP8f19TUWiwU2m00CArmHOCeu8bZtAQDb7Ra7bov1+ha3t3dRSY0Ke1SiVZx/M/FIBD4Lcirw12gIE/zzc2N0BONTGoHImKsqjXW2g3NFzxtBW8njpzVgIo6R4LNpmkzxeRhdg5vPJkZ1XIsJbADQJswHvZslzya9apTBsl2j3B/BB5/JDQN+N4IAHeXE1EMsI1MjILCwjt5dj7qu0rqX40pwQ+BBg2a/7+I6DXpJeoanYIJzVwL/KvKFT7oNyTRk/SOQofxmGykfwt8VvKNfYuo0KDmJpDOA45T3nyQBLd+VcoDvWxc8+967pHPlnI9FBoN3Agwz3uLfUubINVUysIIXWqRHQU14zHvAOQutK1TCkJjy9DQqkFqcGVL8kd52CUTZNrZfPpPzohxnYHSCPGRsfir6ZMBy1pqf2Rl7gNqVh/MOHiO4uLu7w+9+9zvc3NygaZoEIurmGjzLUKng5QhArI/grk5KCwCM0WjbBovFAk3TJI9E3/dJCVPBSyITOOfQtqPLuBQik8onCMYlnGujwLNpsdd1jeVyKUClStY7FyctWgol1ps/0/dBAdMbKduvlML5mYL3Y8iQPzKEwkVR+8PNUxTybdui67rkkWzbJildKqG6rtC2LZQKgJKKlm06O1slg0EKYYbJOHZcVDIcwLaE+jts1rfJkGiaBsYYXFxcJME5DEMEFBp9PyQQRs+B1joBofV6jaapcH6xhDHPJvzx2WdjeH0YBuz3+4lS67oOXdehqgyurz+L/TybhKpkCMtai91uh2EYwTJ5Uir7qjJYrZYw0TNP44nj1fc9djuVeDp43bRYC2Noc7lc4OrqMvHe1PDChJ8CHysADeq6Ql3XaY3UdY22bdH3PVarBaytU2pH3/eTFIR3794BqKLhV6OqqrR+pYeBZW93WwzWYrFscXFxkQzK/X6Pvu/DOyaEMne7Ldq2xepsmdYSgMTj2+02jLsNfHpxcT7xErVtkCHDMGDoe1g7oOss4DW+//57OOfwl3/5l1itVonn2bdcqJO4nrbbLX7729/i2+++hbUDwnl+U3lCcE4Dres6nJ+fJz6Rsol100tHOTUCy1E+5LTb7dKcee+x2WySIVLX9ST1gYYT32GoUyppay3gLZwbDry5XFOyXYv2DMNgJ6BIjqNU/s2ixX6/x263S0ZZ0zQT41x6tNhnto/REcoDypgcZBAsT7/38G6aesAxmoIXj33fwZjw/n6/T22UAIZ6hB4zrnOWJ38o17z32O/3AoROzxOsqrCWNpvNZJ2RR2jwS0/tbrdLMpVjyPXL8Qrr24Wce+9h7YAE4L1DZQx8jLAEHiRgHNM3OO6BB1Sac847ZR37NQX3DnVjJkZXHuofAZyBwhQ8SU+sBLYsh2OUjFYB0JxzcN6Cp1NIgMj3qY+8D4YSN0PmfJ+TNHZlKpzECuQzRvdyI056I3OvKMtjH+u6xsXFxaQPLIe/PzXg/KQey2LjC5+VnosOdDg7unjfvn0L7z1evnwJpRS22230xDTYdVvs9/ugZFbBk0fGlV4dY0wKOWtaOy6EGClg83aFSSbzIP3Q8yqZSTKj9IKxnNVqheVy+eDESk+dZB4ghKeklRMWcwWtDdpW7ppjG2LEUykMfQBEi8UC2+0WZ2dnCahIoVtVJob2RwYfhgGbTfD68EeCK451VVVYrVYT4UHhQqXIhQaMVjEXO4UrMApRjrME2KEcg7PVEkohejCDd4/zQ6VhTAULj7qp0bRNXHhhTKy1qKsagEfbNjg/P8Nge9R1lYSVbC8FNwU5FQE9yU3TJJB0fn6O/X6fnuO7VDosVwrf3MvBH/I020MKnt8mgRSOEZUqgRyFOoW/FFDSiyMFJJ+lx3O73SZwS+V8dnaWeFY+z3nsui55/iQIkQBJApOz83OYykzyoVerVTJkuJ653lnPdrtFVVU4Pz9P/Mz5W6/XuL6+TmvRGIOzs7NkIHAsFosl2mYFhQr/9s03+Nc//AG/+MXXKf2B7WZ7S4pkv9+nddDtO/T7PazrYYxGXVexjRe4vLwUCpCgyOL9+/cJnpz34gAAIABJREFUCDRNnfhntVpiuVxhsWhBrxTbwLxAY3T0bk5J5nJS0fV9j/2+EyBEo6pqPHnyBG/fvoXWCi9evIgGOsEbvfIe/X6H3W4z8VIzBUXmF1prcXuzxt3dBotFi3axgB0slqsl2qaFzPPuhx7rzTqt/+fPn8U1ovHq1Svc3t6ktr9//x5fffUlnjx5iu+//x593+Py8gIh6qKj975JnuASkCMvcF113R52yPLbo67YbLbRuAipGotlg7YNRuDd3R2urq5i1KvHZrNJa+Pi4iKVlddNmUEPsczp5ZqmsdZ1HdbrtYggTPUL1+j19XWST23bYrfb4bvvvktrcL1epzUs5VFYqxsMQ5cMj8vLS5yfnyd9c3t7i37XH+SVEpyyzKqq0C6WaLxHXTfQKgBGpr5477HbdUnmhEhFj24fdEzf9xOnCw2GUVdUUMqg23XohyGkCMW1VFUV6qZBFSN+u90WUAr7rsNms8Xl5UUcoxFjDMMA63r0fZd0hgSiq9UqyZiwti2GwWGIxoK1Ft1+DxejYyEaske328GYCmdnKwAqrmuFqqonANp7n9LgtrsdrB1gB4t+GNA0NbwPeqWN68sYg34Y0O26OPYxrWy/x/XVNX7961/j8vIy8bWU8z8GfURgqWJCbchlqxgjSW758H/3wDVgadFpBVPVcNETaW2PrttguWqhjcK+20NrE5lWo60XMCpMFlx0mXtAKQ8fFUxtDLRqQs6YjR5RTwgbQ0s65LhZyI0tKu6oY26cgvPhMw+Hqorh48j4pY0VFCpUEtJiyd3pwJiUPYawRjf4druFtRZPnz4NYdc+ekzF0UAA4GO2kgfgfLR6tML5xQWggDoKxf3Qg9u7ldEwWsNUo4XPdmmtkzKmFU7Kc0HkJhepjF0MURmt4RHC2wDC3yqcM2kHm7ylVIJsSx76ADTCuYdxTryC0gZKGww2eAe8s7DWh7Bqv4c2Gm2zgI/5mMYY9LYDPOCVQ9d30GrMq5l6KjDxiJB7qqYOY4bo5aiqUL6zUCaEp7Sahn+Awxw2a20KZYZw/wgCJW/kViy9IDRI+H+CfraZxliuUKSHlKBXWsLst6ybz+U5XKM3uU99kO3NvX23t7cpjYV8k1v2rJ9tlPwYwvEdnjx5kgQpx+T8/By73W4y3m3bJo+p9N7f3t5CKeD161e4uLiENhYXlytAOQx2D2d9mNfewbkKdd0cKIeoqqA80A8O3g/o9jtUVQip3dzc4eXLL3F5eYaqVgBckCMRFFZVDe/PsVjUqS+LRQj77/t9SH0ZRkBhnYVSdZBz3gaZ5kJOL73M1jnwTC3bD6iqALisrWFtm/ijquuYFjBgtVpAqQWc62EqDWeHmH8YNp2crZbYbCyq5mICbJRScNYGvo+yxytgcbbAYrVIc5B4fdjF/4ecNVMZXFycYbAWzlrUtYE2oczz8yW8H+C8w7Nn13j+2VO0TYPFssbTp1fY7Tq0izadPOHhMdg+5isvJnxLgy43qIPRzlCljikeQNdtUTcGi+UFum4HpfwksrBcLpOsI7CiAZ3n+JGHpWEinyXf81kpQy8vL9P7u90u6Qjyu0wZ4PuLxQK//OUvk0x4+fJlkiMyZSa0ocEw9FguF6lf7E9InwnpTLvdDv1+gKlqVFFX1XWDdtHGHHELow2qysAjpDBBaZgqOGeGYcB6c4PlcoWL83P0QwVgCa2B58+fp3khr4zpUHYi96yd7pEYBpv4yHuPbtfh4jIY994NePrsGpeXlzHnOrSRzgXvLJS+TLJCruvFYoHdbpcAZpCJ44HpMhXNaB33OAS+Wq0CqIzZqaG9KZ/TibFn/vh5KjM5mODRpAiPgVLB0A18y/Y6bLfBwfb6zSs8e3498VpLUCnlNX9/TND58YBlHCgFFfM0ZH6BmjyYe+tyq58D7x1Snl+AevTikZFreB/d7apCXZtYvgs39yRMGzYfKMTNzkojpIiHfY2DDXlWgEe/D9a3qavYIQ14HTccKIQjW3y4BlE5eBD4jp60MRRwmHAtF36u1IExmZiAQgoYAMn7RPDgvcdg95DnktnkleGYCMCikPJWKVil94vU932qj+2TYUvp/crnT4K/iXAk+GWIPYItAgkbczWNMVD6MBFdjtGUOKbh/9KzGRZgyNVRKlzVGJSjjYp5gKni+CoAysO6IARz3pyETZg+EK/RS4o+KijuRubzWmsM/bjDkZ/L8vK6KEypVKRQlYZIKcxXUk4MDcp2sn4JJiUglQJI7riUxlG+eUAqXO891uuQ/3h1dXXAZxI8A8Hb1y7agxs0JNCUAJjeUipYEr06rGOxWKTn5Brtui55hhgirGqNfthhv99hGPb47rtvY16rgx4MtKrQtmF9hd3O0819xmgwfzZ8F9cLHFZnS6zOFqibcQepUmHTiPMW3nlUtYZHlcYxGKMKjaph7YCqpuE6bhjZ72OeMQy0DmWYSmO72+DVq1fJc2aqsCHD+QH7PnjL2rbFruvhfMi73vcBRDZti33f4f379zDG4MmTJ+i6LoZh75KhIXkskadpGFeoVskI4W7sYBCy/zSCY4hfaXijgnHsw7o8O1+hXTTJYKFHqet2gPIwlYJzNH4QLzk4zHujwZvzOOUEc+SdC56gkD4QgNx226d0Aq6L0L/DvEy2j9623W4Hay2ePHmSZChJygLOKT9jSoLUm1xPDK9SHpPyFAGuM8oTpsgQJBHYAoiGRzsZF6aVtW0wSI3W0OfNRD4oRYePTmt5vw/XA/N4I85FVRk8e/Y0rP1KQ+kq9VdGNeSucOmg4Dgf7ludgnbmdte1wWq1mEQIQhQirrmqgjGjYS51TchL36Z5v7u7w2KxEKCe+rqGMYsJb3BdUGUZrbHZbLDdbrFcLrFarbBYMJpkYUxwkIS6q6QP2a7dbgfrLOpqgaoyabe9XGfW3mCzuUPIBTWpvAcpw2UfQj/JOZY5MJBAJIGYSSg3MKdUyPt+QF1p1HULREHOHaRMgPc+bFHksQqAgsaQbAfEHY2VokclJnszYdireBcv2zltf7oJRY3eNHn0T+7t4iKWAiAH2XxPWrIy5CEFwd3dXagDVWqb9Ow5N270yQUof0sPkCSppAlEZM6PzHWUIIf11HWdPEdcFKZuArgX4LpUflVVcde9zFGd7ubLeScnCuJRKClYO1WEyOqYWHHq8MiovO7AlyoaJdMypMXNhHaIeZX5PbJc6SGUynDOmuTGKc6D9EKwLrmBh32n4SBD5zKfKzca5Ge58cMy5WcEoavVChcXFyk8nRO9szLUlQNiOUYyhL7b7SabBZgvJp+VQJL1JH40Jm3iYfiNY3l3d4f9fo/lcpk2cVk7QCmNqjbRuxQuHAhjQ2WHtKMfGHc1e+/QLmq8ePFikirBtnPcyTP0cNGzul6vcXFxkfL0ZCiUfZXpB3JdLxaLiTeLoJuh0zyHkOVxLFer1UQ+80emrOTrIie+Q37LPSQPeVX2+/2kPpmDKkOyXIOSRwHA2dEIY+hW1sP2SLAvw/kE+Rxnjg35SK5VtlmehAGMxxLtdruJrMjHjrxPQEiDkTzu3LiZVUY4mF+cG+AERjQs6d2URqo0NqWhR7khoxJ93ydlKGUz28X3ON7WhY2ukg+k7uHcMmWF6VlSRsrxuc+7JnPG2Re2U6bW8Df7Kfuay3qlVErjsdamfPxSW+QmG2n4ExTSK829AOTD8J5PJ4BIeUy5JGWyQjlPUimVTnsJqRDczPXj0o8OLB9yt05AFwQIiZ8FYasPhLH3LuZdTEFZKE8oKnH1owoVRvf/AOeBqg47Oa0LR2d45QGMR/LwHtMRPCJ4GPzIkDJUl5NUrvkik59NrZ1R8EnQkICZOPRcliOFMAUABZUEuCVgKYUs6yazMueHYyDbIgV67v2Sd7rLPktwwP6x/twiPpak9RuAeATD6lDxcM6SNVsYd/Zfvqe1Ho+F0jxpYBTIeXsXcSMCd6rnm6vmeID9n6PUFjfmD+ZzaK1NmzVyD2kOnB8zznk7KUDX63USjveBELaXQv7s7AxVVHrst3xP8oTM4ZQ8ROEtlYRca3LMqIi6rpso/RAZqLG+26YNX0G5hmOkArAA6rqFtcNkY2A/7FFVJq23uq7RdWED2cXFxWRdsI9yrUmwzZy79+/fp3w7ma5A8CnngWNBgHB9fY39fp/SIAhYmA/JXFXJF9JQJhi8vb3FxcVFapOUtZLm5pmhYEmcTwnA8rVOcCuNZgmapAImP80Ry5DRF8q/3Kjj7v43b97gyZMnyaP3/v37STh/YjwLuSrD1OQxhpXzqAGJqU5y7cicZbnGOfcEErmhDozGlcxv5kYj+bxcbwSycsykdzMAbg14czCGpHETUhc91JnjyI352HL+aeiw3znIk+NWmud8Z70EzVrrtEGOmyTlOElAL+us6xp3d3cpLYDgPpcxHKsJhhEAl+uUee9SDoR3wnWaeRukh56GkR3tosnY0Ahi3nhIMflhZ1F+CP0sgGWuQL0PHksXvYqIuTL0UNR1g6ZpoVWFrhsQwlFtfNcF168NZ6sFpQ8E7wFQxeqdC4eseg/sOwelKsBrdDuLqqpRNTU4e94H4BraAsQgblhc8Oj7AUpNw4oSGOVghM/lynMEq9PFJxU/Fbf3Ph01pHmuonMT4SgXLhVfDj4kKJSUe+tK/ZBAVVpUSo0H1co+WGuh1fh/9jUfmzDCSLmcbE9Jic3xFPsb+KUGEHMDvU+gjnNwcKSJqE96GDlX/G2tTTmWct7kOLB8pVTyggLjrnYKSM6t7JPs75yypicq9zBL4jzln7HfMs9Ttl3yYD72UpnkRpAxBsvlsuhJyqnkGcFw+Bz5pO97bLfb1AdefOCcw/n5eapPKp1k5QsvC3/Tcyg9hVQYu11QQl9/fRXfDWFpo+u02Wuz2SDsJB2Ba2UM1us16rqabDpaLlcH3mA575zjuq5THjVTKp4/f57mLO2MF/PKPsh1SkDAcZa7TQkyCFQ5RxJscO2NG4karNfrg/HN+aLEqwS8BMdS6UtgIfkkB8vyeb7DMo0x2Gw2CcRJuRmMxdF7n/OibLMEggSqEuxIQMFxl7nNcpw5trvdLqUwSUAsATKJZdErFk6ZqFJ9eXQgnAgR8lTpBcsBYy7LeUoG1+cU3BzOG8eTAC3w4IBdDOdyAxz5kakvl5eXWCyX6PsO8mIKqe8I8ilLKDdkpO1AN9xj+HJtkF/kiQcckwPvK8YNsTKiwbrW6zVev36Nly9fJqMrl5HSQyuJ401+CPJiPNkDGEG4tX1ypiVdJOQZ67DWBoyThbglwB3ltoI/DBR9cvoJ7gqfekVyQJkDSxVBobXjcQoJsJgwyH/812+x3oQQUdu2ODvnzknm9mjUTY3KaLR1lXaDK6WhjcbQdah0jd1ujVev3uH8/AKffX4ez6mysN5FUDDEELsPrkoVckEDo439yy1vKTilZ0kKSjk+kqkfsoYCBQA9EaSYnhmYW2SScuHDZ2nRcbHm4Jd1sFwpzAEcKEHvPHx25ArDcWwXwaRW+mB8OHb0JuTjLYkWvQReSikMdtwkIwWMBPxKqQSAJWjKQ6oARO7tNHdLWudJCQ2jpyQHkyVwxnGmsJPjLseP9cuQnJxjCZy9n4bBueuxqqqJt04KRJ7HmPOM5BWuSQJOCXqobMf8JqS+MLRLPt1ut2gXLRrBE1L5cYc8eYC5Tuz/mzdv0DQNzs/P0/gQmDA9QxoTq9UKm80Gt7e3qc3ehzwqGnC///2/4J/+6X/EOhtcXT7Br371q3gqQjiiJCjqIe4E3+IPf/gD3r17h7OzZQKEZ9HrJvsjx00e6fPq1asEWrg7liFsufFE8pA0JJVSCRDK1ASCFCp/Hk3FdnFdycsI5PFW7969i3lhiwMvdL6Wcjkj5SBpzmDKZaD0wkoQLze8yPGjQs7rIwggkC7JRaUUbm9vYa3F8+fPcXFxMQmdMx+X7+f5jRwDrp83b95AKYVf/epX6egoublOEv9maJhHCl1dXU2el2di5qkvUn7I8uX7PBlE6og8dM/3pXd/3EA3ygkZJTDGJK+81jrsWrZ7VNXUSM5BGUH4t99+i2fPnqXNMnKuSzyUy1quD3q4ueY5ZsMwYLVaJSNSGgjS4JRee54XTSAv1wP7wFNBzs7ODtpG3qRRzDUn25TzIcdDtkvOsbM813OKo7QOGzRlRPGnoB/9uKGJZ6gAlDhRDj7c/oLRsrDWhlBZVcHawERv3rzFH//4LZxv0LQ1NluL129v4b2D4sGxCDduaK3ghz0qY1BVdQyd67BJyDpstztstjtUpsb1k3N89dVzvHj5GYw28Cqc1zVacAw1hjxNoAyYZd/kAuGzc56gfPFIRcTEasm48lm5+1DWBSAtNCmAS3OwXq+TcJC/JXhlG6T3kc8R0FFwtG2bbucApoBILoCUO4UxDCLLJQ/Rks93p7MdBGS0qPt+gDFqsmhlbpkcQ+dcSlKX4/79999juVzi7OxsCgqyuimUpJKXSkuGc+Qc5OCdgk3mWEkw4ZxLwEoCDCmEpSIiUGH7pGVeArpyrUpPUa4Y8vbn3kHpbZHtk89RKQXAN45L3l+CIRkmY7+89+ncS/Iew/9y7ck8YZ5NycP7+cxqtQobLrYdPvvsEn/xF38BYwx+85t/wj/8wz/gH//xH+E98F//6/+F//bf/u/kLbu6ukRVB0/qn//5n0NrjdvbG1SVwa7rUNVV4kECA44351xrjS+//BLb7TaFr5NhFMEK20pQIXmNIJrKc7vdpnknqKHXRMoQWUY+3xzP6+vrg/WYk5QTbKc0fLbbbQpH5h421pWDw1yZy/Um80UJLqayScHoJoFThoVzmSZ5VPK4zAHkWmI9ch5psHG+6BnkmBEMSmNfzr1sD+u4vLw8kCGkkrc31wUSOPE7bniT8+5ciIQxT5NlcX4oi1he2zTwfox6STmqtcbNzU08u7iZACYp6/Oo1t3dHX7zm9/gz/7sz/D1119PvIKca9luGf5PQLYbjwviBiU5J5K/JL/KOeB4SQNOjrfcrMi5l6kGUr5I2cT0IOokOSeh/nB2qFJIckm2lTwWjHGdQtxyPNg+HmXnrEPYcPzj0k+yeScnyRyJAeOxFhzoYRhSeIC5TlVVpXMrm/YaL15+gaqqsN1usN2usdms0XV77Pcdui7syIMlkg9Jrd4r1FUDaz2cU6jMOQCF169vcXd3g9VqifNLHnPRQxtCyLC7UmvNZM1in/h/uUBy4Xgf5aGhXGk75wA1fzUc38vbVgqTSHAhlZj349EaUuHwO3lki1RCsr1J6KhDIC0t5eTRjakM/FuGIKy16TzNi4uLA2AJIOWBUeipuAnLummYWs6LVNZSoLBvq9UqhZuSwtRTgC1D3Dlo5lwwHJML7dLzkuhBlhs3cgGbt4WKjEKX5XBTUX7cSL4BguNSolzoEyRxDKQnRyk1niMrBDLLlwDT+vEgeRLngB44Cm+eGSm9fhIwsu0EJlQ6MtQGBC/UZrPBbrebHBAOhI1ot7e3qKqQa2VtGP/1eoPvv/8ef/rTn+K5rcFbsHu3RdPUuL6+wj/8w/8Tb+sasN1ucH5+NgHwBHg0nCVQPjs7S2MjDZCSbJF/88pbHtj97t27pKgZIuQ5syVPuAQUcj1Lj/198ovvy+ekV4t8Qz7JjQc+z/clyJSeV2NMCgPnhkM+VpVRB9556YGiHGLeKc+CzNeWlGk08F+/fo3VapXGVL6z2WzSkVhsq9w4Iyl3JHC8JZhh/6SBV5LJ0sDNjej8ef7Ig9U575JXJxEb5+Ds4UHflGvUF1bIUDkf8v/sd13X+Ju/+ZskH3NDkCT5xfuQY317e4u2bXF5GY4L4g58+a73fuJpl0Y0fzMX+fb2Fi9fvpykekki3+aXqkiZLC88oB6S6RDSOAtjqFFVDfb9eK4uUz2Y8sMyNpsOQ79P5bBuyvHlMlwY0bnDW7h+DPpZAEtgOrnhP4g5khpajwI0LHwFgAn/GqbRWG/v8P6mxfWTK1xcnePFl58jHPkRw3Ouh3ce3WaNbtfh7m6DrhtgBwdrPQCDoXfYbHaAV6hMA+/2gIrHNsAAVoGbdxKQVPfnfORWlvz7MWNyXwhJCmF+noMtKVAkM0vBLgEOc7tkDgyBSgkElfojQWuot9xHWR4T0fP7giX4A5C8HTkAIckFTDBW12GHIsvMPa18thWJ7bJt9FTKu36V1nB+umu9pOydC2cb5sqDAucYkmVLq5hgi+MjvQvkHQDprL18rcm2SKErlZNU1rJvJSUlAYIcf5ZP0EawIA8o11rH+9cPjzWS88F2M0yf77KezJGYX9nOYIRuk6Km15I5Y8vFAm27xNOnTwAAr1+/Djs7mwbdrsNqtcLl5WUCgF0XPGJVHcKBdd3gt7/9Lf7Lf/k/UdehLrap7/t0BNJ2u8Xd3R3atj3wGOVeYAkc5kCeTF2Qh9ezbgLsXB5JgyTnuVwG5XMsifxMw0ICZ5leMTE49WFIWnouJcijsueh5FTwMvWGc02iAQIg8R55U4Ja1iPlQTomyU7PtbXWpgPB6d1iPiXXpAS8csx5vWq+nthvtlV63EjS4M0NjXxM2S8pL/KxyeUJMJ5xmc/ztPxDvUPATx70PhzrB4xlsM9hU1uX+IJGobwOV/KbPOKOIIpjnDsLpPHBNnMccoNX9o3X956fn+Ps7CwZoHMkT1sIxuZ6cjGFnH+OjzQ8JM8BDrtuC2N0qpuy8v3791BK4fz8PJSLaTSBhsN+v8fd3Z3Y0Ijc5/Wj0M8CWErhxZ9w0C9QNcEz6L3H27dv8ezZM2hdQWugH8IiePHic/zhX7/FN3/6A969X+H6yRW++vJLNG0NnjHn0cB7h8uL52Hrja5QVQ3qaoF+P+D779/hm2++xfDtq2DtdHtcXS/CjvE+eCtNDfBg0tBuB+90OKM7w5a5sJgDklJQlYgLRYYUc0VbKi9X/lKxSKUtvTqyDCp7GTot1QeUw9oU8gzLNU0DZ208aH6+n/QY6KyaHEjnuzJL5clNAip6vfd9l9ojk6LpEe/7Hv0wQFVToCTze6Ulr+IREaV28u/UBj+Ol7SEJWgrlUHirTc5OJV/09KnV4Qkc2Gl4pV8lQu7fGNN7sks8YIsPw8rSu/o3d1dUshUKhyLqq7SQfMlQMkyc6+H5FV5qL70UFKws6yLi4twoPDr15PrFcORKsDNzU38boHPPnuOFy9eom2XWC1XsU8t/vZv/xZnZ2fRAxwOhP7mm3/D3//938fcrKCk37+/wfn5W1xdXU1OalitVgloMUdM5vCRuLblrlQJAuVzVF5VFTYQybXA61WlUZfzKtd7DrpyIFoiviv7QF7Koxs5kMx5SfaH/edGnffv3ycgznErEfsgN9nISIjsGw0SyXO5YSXz3ji+cocxjYa8HnmM1Nxal0BI/k1+yedBzp80Gvk328h2ye/yHfWMAuWOB+mJGyMl8bD8TG+zrASeFAA4KDUFv/KHY8uxIkhnv2Vkh3zP9nNcnj17loBVHs2h7JFewFK+d94m5jTnz0q+Yhu5eYm53flaIm/J7/KIWFXpeNRSuK7zd7/7HZbLJb766it89tlnE9kaNjlNz0nluDB9ZhgGVOangXgfp9bHIGKl0i5arwDvgXhpT2AGIH0PTYvNhxP6Ly4jqDRhwLzDYtHg8voSvQVev36D9XqNP/7rHV5//xqmqbBYtOEasbYOFpYzcNZj33Uhp3K9Rd9b9H24nglQaJoKX3zxHP/hP3yJxaKGdVtoE3aFhoRZz/0ycN5CFw4gnQOWOUC8d1gzxZn/nUCOG6JVGBb8oTXmEQ5LVagqg2EIQMs5eiPH+1W9dxgGi7ZtwHteWVZ+PA7LzxWCcy5ZnXIXaDjIXkUvb1Qs8fB6nwnBObBDcCfvTi7lWEoPYliMoe/OVwdKjV4QYMytSeOnxqTwpm0OBIIx4Yad6WdjOEz+RO5JwlwqgVxwT0BU1idpnbMs58ItLM6LXN7Io9aNXoASf6X34zjm4Uj2WQJSyX98Jgec0vtBwDdYGyIJwATch7H1AMcLh2FeWbfkSwnQ2UYqcAI2hsokmKa3hHmI3sebsZTGanWG5WKDfn+L5XIV6jAVoA32w4ClUtDGIGxiqLHd7oSHKGz6+Ou//mv8x//4v+DNmzdwbsCu2+Du7i55Oal0pHc1zy2lx2rO81oyCrk+5FmyIfRr0NQNjKlRmTqF3Ey8qQpwMHpMpZCGp/wsl0H8v+Sn/DxD8uooZ6YGDp+RHilZz7t37/Ds2TMASHeIP3v2HFoFmVWZGsMQ1rkxFXw8JYMOCqXEhjs1TXORkRquX3lepORvGjDyXdn229tbvHnzJt10IwGk3DQ3BWmHedX5usvHXUYr8nQCaUDSczYMFtZyrwEjGSY6ScJRfavVmVgXA3hNsDGU34wOhVvnHKa53GyXBNThTOjpeIcUNHr4wzWnHF+5e5ze4pxXWFfbtri5ucFms5nwHceZc8W/pe6VDhVpLMnUmhxsSpJjTdkjN7xxzQYecKjib8pUrTWsyx0t0818T58+TbvaD7y1/T7yuob3QYfv9108TSJsMtZaIV1D9QPOspQGzmPpowDLoAS4eMecINnANDEKcCrcWAIuFB2QpfUIzKoiuPThFgtAod8OgNeoqxBCcPGy+HbRwMPh5csXuLi4wr/+8U949/YWm62F2nvcbbaw9jaepWWgbAtvHZwLh6lrpTD04TqnxbLG1199hq+//hyXVy3s0MH5OygdQu5KGfDeXIWQW6kL3koA2UIaGXEYhkkYqASM+L4Mp5S8U3xG61Fw82rJ/Z5CTKMyGkbH3LN9UKAGUSDXTTyZPx7yrBSqWk0E5py3iP2T/+fCyBUh57kfBtQ6eJL7njdwhOslAWBw0TtmpxuYJHCQ+TelMZOeAb5jjIE2GmoYhRbHn+MrQWUVr/xyzsKr8DeUgoODrhg56WFNAAAgAElEQVROcWjMeIWg9Hjwh7svq6qCix52mSMpjxJh+61zGNyYG+XjVZu0juHCpqT9jvnC0bMSFakxBtY5NHU80kKFm6QC30+PxpD8J+eS48yxkWdgAkgKSypIKjnp4WGIUimFqomKVimcnZ+FdAcf+Ksfxhs2rBuPemFeXgm40vvA9uRKmH3TWuP6+jp5ODjnDIs1TYMnT57g3bt3ITTfDbi8PEPdLFAvLN68v8Hl5RUGB9hhj6qqse52WLRLaOthh8iLKoSzghwcUNcNFu0KVbXGfj8m9stdoRz7pmmSR5pzwFDh7e0tnj59mtZevuZywEHvHUHzfr8PqT1Q2O32sNZj5+m1CYofDlDKAMpjGPbJGEjGawRNFxcXIx9iND4kkKT8Z385B3LjEdcn+ynlWok+//zztLYICipTw8Vb3rxX8NbDex2vzQOcYy79lGckmCOfkMhr0jAlH69Wqwk/c72Tr+q6xtXVFa6vr4syhgYMQ6X5hpi8XZxfKVOl15J/SyAlAfII0By8U6iqBs462CECrKi4naUHsga8R9usAHg4G6/gDd6KCDQjv+lRXkr5KY9Roiyw1qVjdJyNjiUPeIQNKM4G3gtGtwdPV5CeYebMy8PJnXPpLvObm5t4pNcyeV67rsPV1dWBs4JpVOv1eiKfAeD777/Hs2fPUtqQ5OmcJyjj5GauQwDq4NwA5wdUdXBKOReuFwZ8cljJOfc+pI988cUXib/YFtZ9e3eD8/MLrFZLvHu/w+3dDawdYK1D01ZYLhtA2YjL0saQe8ljvK0q58PH0o/qJ6Vjj02dYvX8syl6Dx6qMUmfzGudw936Dg4L1FWDP//1f4K1GnfrLW7XG/RDj+1uE28oAbSygIs3aFQabdPg8vwSFxcXWCwr1FUPXQ3wGIJCT3xCwRSA7kPeRvm9XGjpTEMchjIfKo/KsOzF9JGxuBDCe4EhqWwd+n0fvYgG1gavpRc5gmO5CspPLdE0M1n9sg8yhJaTBH0yXFkCiWx70zQpjJlbmew7c2lKgJfjFqy6cczlUSkU+gRG7IcU4uwT62EOES1cCta8Hbzpouu6cIQRRu8Gf6R30wVNGQ9eR7F+goXcq+Ozd2T+qXPBI5/vpM/Ll2Xmcyg9O1KQyrmXYJRJ/AQYpbbKOZKeJPlMnu4g2whMbzSZW2NyLlmHcy7lIsl2Kq2htcFmvU5Xr53FEJdScYd2sijHqED0Laf19PbtW7x9+w4q3iJ2cXGBZ8+epbGXxhcBEzC9KamqqnR1331CXvZtvV6n8zPT+tAGvFd5BDpct5wDKkKPcLf5mJ/HECXHm6CBYE8CSOkZTHJaGIrkd+mFAaY7cnMqefgdPNQDPEu3vQzF39zcpONjWHa+01fymVIqhbo5DjRq+J33Pt2EJsEPyyTJA9JlxIHtI4Ci500abJKHOddyM5NcL1PyMLqGd9wRHc5enshAsm/UbXd362RI8LzkwNuIoN2lW7+UUilsHO7FPrwIBB4pLzDiSgFi4rwpFx041eQIHjoIyIfUC6yH+wHIU8tlOOKLAFIaCjzuyfuQWrfdbvH555+nXd3Pnj2bnJaQO1bkHOQeTSnj5NhrreG8BUBvPXltalDQ4OI64/WpUlZTx5yfn6OuK3T7Dn3PCxkUnOuCV9qMzgrz428K/3nkWJZJQetgbUkmZg4FFfs33/wb/vn3/x+GoYbzHm2zwNnFJS4ur3B5eY3l8hx1Gw5Ub5oKy4XHMGzR91sADkbp4HHwDs7v4ewOznUxtBzuC8+t6ZJrfLYXmZclDyeTQUvvyR8pOMns0tsmmZMCC8BESFZVBR2ZW+bByBwSCjIFnUB+SfHnXhJSyXqWixIYLXkp0CUYAKa3Be12uyRYJADOgYr0vMmwXRCgDt4dgph0bubEwrcTIcY6JNCloL+5uUk5bFrr9L334yYDPu+dSyFeUq7EAEzGXfaPliwFjFQ2JZ6U+UmSz+TfUglJ0FUKeeaKveRVkSAwV8DWuYP5c4XP5HiTp2Tul1wDHF8aCzK3UvKdBHCcd/I+Q6tUGOdnIXGfN+wsl0tcXl5ivx/zA7UmLwIKzCULnv/Az+Gg6Hfv3kavhMX52Sqdr8d+SV7kfC4Wi0n4js9yneZzLcEG15I891HylJxbyTcjf7ik6KXX2jmX8hnZbu463+126dpHru28XBmGlJsX5K7d+4xsWW7iwXiUXM6PJeKtN0qNlzfI8kqGc16mBMwcF67HrusmG69yY4HlyHBpLtPIt/Jvjok0AKVhx3qY+pCHTSXAy/siPbXsq2y39OTl61PrkA8oz+OUu8pZL+uQ81aSa3FC4aKBw9x8jt/5+Xk6aqdpwk153333Hfb7PX7xi1+kdd80TQKM5+fnKR+XY8PzJpVSuL6+xmeffZZ0DDdjSVArwaLUsbykYTz+cHre5EhBD2y2+yTHqFtKxhDnjHnoi8ViIps4bnRYsM/kO8pgRnJCmkGhWZ+YfsbA0sMLj5m8RowKaxgGXFxc4OUXQD9o7Ps91tsN7u5e4279DvaP/wJtWjgfrlw02sBUFpUG2oVB29ZYNC3ubu4AAM+eXeHFF+Fw167bom0qcPMPMPWuAIeLLaeSsmf4rVRO6V35XK5QCbClByZX1BMwgZCCQKuNiliGr5LwjBmBOfNLEEvBkJ8xWhoTKjla1xKw5Z4LgkE+kx9TwrpzMMhx5eLk8wSaw9CjacedermVmCfV58BK5t/IpHA5zl3XpfxPhsgYRuMJBXP8w7+NUrB+eqUkMCp0ABMQmwMnviN3wspxl8peKrCcv9m2CUAR45PzJp+THhY+71wI09MgkoaA5GvJL/xuv98nr4RsF/mEfZObXlgny5IJ7sC4e5X8K3elBqC5QC142YrduUyr0FpDVwoq7XgdPZbGGNSNgak0jNGwdnr4sgTh9PZJY0de4ca5lGsqN9Ykny4WC2w2m7R2nHPpQOV8Hg9pXE+UMWybNPa4pqj8yYdyt3PuvZT1cp7kjScc31LbpMGcy8s5g0euM8rdxWKBL7744gBgyrBmqfySAfanP/0Jz549S8fJyLHJjbESQJUyTabHyGfk+uT4cPy4eYse7jSDYl2G5w9veMojK7Jf3oeQ8/n5+USnSBnB5wnISsA+N0ZLukx+B9FX8oHkQXnHvVIqnQjA9cGx4PFOwzCkEwD2+z12u91kw5Jcg/IGoTyvNgf0ABKYk/MmgbrgHlgb2kCjgms5XxMStDNSwaOG+HmeOmeMSR5aeepEOpnBWmj148O8ny2wDIw6MiOFlbSQtA7XRl1ff47extCICsz+/vYO280eNzc7vHu/wW7nYHQNRF+c8z3s0GPoB1S6wn7f4f27Na4v/1dcXF7DWyDkSx16a4AyGMwpf6YEjHIr/KGyKLi48YCCRrZRWrz5jrrBjrsnyahyAXGcq0pDXhlV8iZIcLnf71N4iYtftl0CPtYtD3IvjS/nXYbQ2A+CidyypCAk4GB/wvV8W1T1RQJYMvfJOYfNZoOqqpLnIW8765M7DAnsZV8I+Ha7XTqoehiGdJuPnM8SWAgAw0+UVQ7oKDxomQKYzLUEpakPanp+JHOROL8sI/eEkii4JZDNgWXKUY0gjQbMYO0YNc7mmW2W5ckypfdRjhnf43wwRzHnKbmGZTnk1cVige12i7OzM9ze3qLve9zd3SXDoGmakAfuBHhWNJJ0NMJSLBHea1jXx/53GAYFa3u0izoBR3q/Ob/SS87cMAmc545IkeMoQ4cyMqK1hh3Gw8ZlxCDnOyCEKOVRONaGCw5evXoFYwyeP3+elLK8nYt8JNsnDTA5JwTzuQyak4XSSBg7PYZXJU+UyiKfyNC93LDHMc6949I4lfKxaRr88pe/TIaJ1uMh4ZJP+SONHXnzTg60uDZl2gnnUBq42+0Wz549mxz6znmQEYTAq6Pe4TqjQyHnqXxtST6R30vjkf3mOZ0SXOdrUH4m13z4AbQJoXpe7QgE44heR611yotcLBbJaJA7ybUOh+XLNZx7h/l/6UwgCOWGU7aPMpbvyt+SJySfjuTh3AClp2F0ySccX84LZQQ9wASX1D+U29Rb1FnkDekxzs+N/rHoowDLFAUC4i6l8TR/UmJYABALRg60tNhSA6sqHY8hyxmVp0M/BOs8HFYNLJcai9UTOKeh0OK7797iv//3/4Gz5TlW59doaoN3795gGDoM+yFuqgi5Sb/73e/wv/8fv455VofhEAnAuID4DBmhpCRzy5OLnpYVn5ELsiQkOUbSPU7mkp46KexTqBdh4VJYOOfSopHAwhgDrXTK85NhdTkebCvDDNLKlqCZyozhtNw7IRVcyZKWlqD0ZJIfZBiC4yTnBwhn+y0WDby3qR+0TtkOXsfF8ZPeSWC8tYjAnuCOQlwCbellJTXVGKaV/aPgI3BjP+gR4pzSquZnciOBnEP5bp6jQ4vXGJOOROF6lcKfgleCU/KZ5JXcUJIea/6/aRqsN2vU8XihEtiQuVAyWZ4hTAr9PEwo1xvrzb1q5BsaY1yr9PTkhoVSozGwWq3CWZB+GgpLJ1tkdyA751A3FZTTaJoq8pdCVQHb7SadvSgNBK4FKmkqPPKG5HVZD9/b7/eT9ZXLHs6btWOOFtcrARfrsraPCn6aatP3Pa6urgAgbeSShg89lfLYE9ZLvpZyjPO73W4PPFQSKJGPJFiidzmEwr0I+9UTXqaivrm5mRhiuUxluTQU5XxKWcQ11zRNutWF4CYHkCT2S26U4/jzuka2Sxo6HGO2g+VwTHltItcq681zx51z6PZ7DINPKTsSxPLvb7/9FqvVKp2TKNcNvcs5OJQ5tZxfKcuk7Cg5DuSmrcjhk7UgeZ7PSvAl14LUUYwaSV4iD/EzzgcweucZXuZaIDBljnPJWJdjLvUi16PW8aYne3gigASaMjLB8cydM+wfZUQO+BeLBZ48eZIcGuNY4oByA8g5FyBcbN+cgXcsfRyPJQ32B0g+kjObtDbkGxIEyWfGxexg7R5VXaGqwmHLUBp1G5KItQJWywbLRQPn9hjsHl+++Br/+T//GsZobO7u8Pt//j2++dM30Nrh7u4GNzfvcHW1grX7YsfyRSJDEdK7dGi9HF7DlXtWcguP9eWWJcvIF2DJMzOWFUJ1pf4QpFABAxZGVwfl5H2XC00+J0GjXBTjghu9jKXNFlKoS+tdfs96pjwzNT7YnhCODBuyJAiRP7KdBGecU/lZvqBzIM1+5jmh/TAAfuRpKcSo4JVScD6e45rxAt+THklgCrzZJhlaTQpam5RjROEk+50rWzmfHBfpmZGh7NxwYhjemFDnzc0Nrp88SfNP40zusJVeEFl+zueyjXlurswdk94wGmMcP/ZdpoOkW2mWYTf2u/fvcXF1nTYkqNi+uq5RVwF81gDsQCUGVJUGj/ba7zsAPt6UsUfTjjdvSACQ85gE+bKfku9k1EYqSQLiXF7wtABZrjSMR0/WMlwm4acH7RNgSOBA8EugRR6mopQeHblGjDHpzFDOF71w2+02ySE5d1xH5GXnHOBNBO3jWErjSeuQO/fq1Su8fPlysla5NuSakTyUf8ajq2iQ3N7e4vXr13jx4kW6S5z9lJ5hjhHPS5Vn0X777bcwxuDFixcHxhrHQKbfyPUo9UyuN/J1EozqMWWnBPaYHpCXJ+V1Pla5fiKfltIVHtIdNNa8daDeP1bXyHZKY1G2LYGnTGfwt9QxNN6Z4pAbGLLenKQsY3ulTJL6i55rGof0lPJHyln27RAjTQ1ehvy5plCHfPAS5TjBF77L5+BY+lmEwnPQED+NiH68ncN7nw4glVRVGkpZ2MGGwXEKtveA0nBQWC7O8PzZM7x5e4Pb21v85h//Ef/8zxqLRYvzszM0bYu2abDfb2Ctw93dBstVBTPjRZ5MhlD2uTIsTQqVgLRcZFmlMcm/Kz2fh1VYF9uilEoWvixfMikFQvBgjApOemBzS4fll0gCOKnEgNFLB4weVbnoKMwIjKRiLYFmWbYc13F+KFRGb4pUVrkVKseU7cgtzBzQ5eMv2+VcOLojHzvWKQW4E8BRAloqTQIytqck5KRSZ5u7PgCO5XKZ3pce0jlQmXsJ85Aq+0MFIYGIUiHR/OmTp+lIKQmi5DzI+uhxoKKSYyafkzwmeY4eIAIYuVtdRka4I5xgqWka7Lse2+0ObdOgbVvc3t4CUOEcS4R8p36wqKsKlfcAAYtRMEZBaxWvk92hbRt03Q673Raff/EZLi4uDg5KlsA5Bwz8Yf4UdxVLQChljszDleSdBwwST8g1K3PWnbNJw8j6aYwYYxLAZJ2cb84Vx57jzVA6ic8CSB5Aelik8ZmHLuUch/+PRhr7LA0N1vvVV18d8LXMU5uMUwFAkE+5mUIphadPn6Z7vCkfpXyS5XjvJzvIacT84he/SOMvQbZ85+bmBsvlMuX0zbW3JItH4DBGsORYyqssF4vFJI83B2ESYOX1yzKld1k+XwKa8ifxswunmOQGf/6+9FyTd7kWlFKTw/BzvcX1L3WKjCRKb20eXSqB2rm/Q9ke290ObTuuMa4Tgko5fjKVIT9mqNR+Kb+3220ClWx33dSw5cvpDskfOll+KP0sgCWAg4Uo+0UBzJ13uZeqMhrODrBeoalWcFZju3XY7bZY373FYBHO8TLBc+CUg7PhpoHvvn0Fbx3qugIU0NRLrFbnqOsGzh7esykZnQxLwSxDQHOTQwUmPTMll3dOcqHK/0tBkIO3XNA5nhQcSQoNmQTeti2cnS56qcAfEhp5m7m4pZdM5iSWrDmWKfsgwx35eOWggUJ6fCccq7RYNkkZEGzIkAx/yxwzOcYUOjJMKN+ToF62KYCkcJ6YbKMUqqksAFqEaSRgkHNBXiuR9IaOgn607KXyZ/tL85gbIBTeMrQnn6Oikt5B/g2tJqcRyDxACdilsiK4kHMs+UMCBHrvpKco3/hFzzzHUa5l6W19+/YtgHDb0XfffQdtKhhT4eIybBj45ptv8P7dW9hdh/XdHe7ubrHvOwAOZ2dnePfuLb788gV++atfYN/vMNjx/Ewab96HsyEJNqRcyOeEgEb2Q2s9ASosV46rHBsJRLkuZMgwlB1vZKnGq0Y5V6xbensol2VKiJRtnEe+Kw2V/GQKAnz2XUY2JEhI685PjV4Ct/1+f7DjnsCMa6yUrsR6S0Q+YtiauXkSFEjjivVwLlhfaYPHmzdv0u09Uq7TO16aT9mXEhiWz4Q2jrnobKMMh7M/Mhoix/6+8ZG6TxrSeRskERhKveLBc6undcl1IOcvP9eU4y0jHxx3OSd5JCQHbbJNEliWHBs5SaM5jLPFom1hKj3JKybPM8VHngQBjJt82Sb2jW2Saw9ASuHgBlqm/Tzm8hqPQxyWGxLH0o8KLJWf7AcZT4ATHRkRejhoOCD3PlnNzIszlYGhgNoPqCsDo2u8evUe3333Du/e7dDvHXb9ABvzEvb9gGGIzKsGXF9f4frqAt1uh7ap0C4q/OLrz3D95AzDsIa8hgqirbkSJvPl1k+JAaVFLkOm+cKZA265Yi0BPfkZn0teOiG4peCVHohhGGD0KIjlLjnZ1tyay8eJ8ym9D2Gc6F0IN5dM+xU4Q27SkuFSpQAvmGgKLB2cC7wzBcLs13h+ngxDyHHOgTqAiTCQniUCJ9mOEvinwtfhRMNJmISeW9lfHxL6DtpBYSIT73NrXPIQ25SUCcbwOEMvuWe9pGilZ1cCDLaJv3OelWkDYdzUROBLzyf5RO6GJhiQbZAeWAnK09jF+hlyzsdut9slkCZBEBU4lcLbt2/x5s1brGKY8/lnn+Hp06dQesyFWq83WL9/D/hxY1Lf93jz5jXev3+P6ydXscxgfHKjFIB0BBXzYHMeKpH07obw+gbfffcdvvjiC6xWqwTiSxTAz/h/jgl5SWsdw2hbnJ2vEA5ynt67PCo1Hqw+zkG4pevwZAJ+79zoLBhlA28eGqDUmD8md/fLuc3Dxd6Fs3mlt4e8zju8OVcyPUDKsDmQIAEeQQB5RYZ7CcSkpzj3wgOj90tGGKTBTU8v/2YZcofzXBunNKY8yfHm5MtwKvmAfeExPBIcpfdZutAbUgZJeSfzGOeI0YQJsPQuHh811We5IU0+kF5cuc5zIyaX8ayPek/Ww3HhfNZ1nTYlyXrmAHY+Ti6c/p7GWeaKUsblTiGpx2U6SO5ld85NTn/geN7d3U3WtDELPJYk7/8Q+mjA0nskYSMH5oCUgnIhjAHvoR3StX6wDsq5uMHHwaqo0OFQ1xr7fod+6FDXBt7bdC5eVTWoTIPXb27x2//3X3B718E7jSfPnuGrp1fQlYLze+z7Hm9e38I7j81mh8+en+N/+09/DjvsUdcGSnvA91DKAl7FG2mmJBlAutnJ0Lk3dbpwphbT4dBMwZ4Ehrl1NbGW4aFVFJbxxwNhJytCzl44PWgqTGU4XiYvd10H74akENlHLjj5rhwTuRlALmT5AxVuVmraOljRJoTorXXJmNBGY7A9jNaA8lDaQ0HBI6Q7AICPwqcyHF+O0xj+CU0IXlqtNJp2VI4cO+l1k/zK/sr5AMYNAjlwnwN3VJZKKcDH8UgbP4CqrlFVcSzDGcQI99FPvTP55izpeZDjLHlNPqeUgvMOVR1BulYJ9HieWCxycPm+9Q7ehuvfEg+pUXkZE0GD0XBDWJNNU4fbc+IZkItFPEw+egspYKVylse8SEDJ9SLHgOMgFY4MpXKe+K5USNLiP4h8RL5dLBbgVWzGGGy3W7x5/QYvXnyJwVrc3t5CaYWzs3N4a7HbbrDfdVjvdth3XVCO2uDmbg0HhaZdpruYLy8v0/qht0gq5VwBWmsT+GMf5Kao58+fJ++NMSbdGCKNF2NMvDpuel871wH/vr29jVdOXqQxUQDgFYY+bsQhyPFh97jWGkqrsC69wjA4vPrudThY+/w8vh8VuQAhwXiocbYyYA5YZRpA+bQxToIXCfqlMUJelYAj5SoLL7iUp9LgKK1dSfmz8p0xElGhbdtJOosEj/zNuZCGFYC0o5deaJlWxefJIzS6wmfhMPFQhY7yTiGBSx9lgvdFxxWdCCyTa1Bu0Cs5MuTY5J5ClltyfMj35O80d8pD6yD/cuOExvB6vUZd12kT6JSfDs/lZPk5SJIANG8j9Ri/k7v+5Ttyfuf6FnJv92gX4/W10hBiW+QxaTSgOd/jvoeRjA5RxmdPn8E5i7puMAw9hr7H+m6NpqlRmShb3OHszwHH/5+5N1uSJTmuBI+Ze+yRe96lWKhbBAk0OWzpETYpMi3C95GZb+A/8olv/TCfMBwZTKMHJIBCF4DC3XON1d3N5sH8mB/X8MiqwhQLZSL3ZmaEL2ZqaqpHF1MbWguR6uFbtO/UYxnj04sUaL2WVGStJeUAuBDTdy0GSqUkIoCA0ahogYgDt+4DobWCC9SNR+lL/O73b7Beb/HixSf4j//xPwFFBFwF+BrR7RFjAJpXKFBgvV6hKAt4vwV8hcK3Gx2qCkXp4AHEJ6wSTroqKBVaamE/ZR1zUVDo8Dk2PKyeMtsXL6GiEEOuup9BaEI0vXw1FV5M+Gei+GQygUPZ0rfbxHIspDXEpDZsnRZUOh+1rtOZ7E1I53dHh6R0YoTzqTD+frfDaDZrC9WHdHJBTOdeJ49JRAgNomFh55HP42570grcCCB9pvleKjS12fAW6W6F19B8MkRJYUjBpsZHZ6FHVCbs7rxDgf6512pYqKfNhqKtsOzNg3NtDhPgfNr17wuPu5s7VFWFi4sLlEVX/9I5l46AixFl2YLqfEpL34M48iP4wmNcMG+rwmQ6Sbt2W8EMoOcZJw35rs6j3QcOVnirUUMQoTmjFmDzmQwTq8Ki0thut9mLGwJyLuSrH/9FCxrSeb8Pj7fYbrdwRYHT8zO8fP4CvmDeYNF6CbYIIeCXv/ol3rz7gLIsMBpP8jxZg5Q0oaKcTCYHJYPU20YPXFmWuRA0ve/cRBJCyDuri6JA1QQUvux5xfg+8tP5+XlbGxBI9Xs1VYKHVXTzn+YGQIggsAkNMJnMMBpNUBasSJBAbYyUh60Miw7ej2SeHJq6bo2TfkoAd0k75xL9XbpXTwfT0L2uRbtuj0WU1Gi3Ms7yIK9TPrZOBJUPaiiqwadgxoY6LTjT30MIcChSDCREIPoEIAOvS+/1LjkWNEJgacRnawTHgjBLG33GkL7TsX0dJqDuch6o69CCy25ebQkdBZNc+/zc9onP17+VDkN9AboUBp1Xfk+ZZQ1B5Sf2z+bfKmZQ+lrjWj2j3OR1fn6eeWQ8GmG33bXVEQJiCPDOo2qqVHN3lI7nLNryTRYZDoFKqwW777+91/JPk2P5Dfvpnc+bTTRHpTXCQM8UkBTkZpOObnz//j3W6zUWJwsAHlWdFHg5KlKeoQfmiwliCFivH7DfbnB6ukyCL0aE4PJxjrarQ5aXfmcnS/M5jjGzLnpVrlYwcfzWWip8/4QFe+9QUxCrdb6yZe+7UhMU2vQcKEiyY7BWXZ8mCQx2Ci39y/SUYvS+8O3U9q3OtIA7+h8DhqSBenqeEihD99NyJSg5WIjGetU5VmGoysn21YJObTYXSN+r31uhdqzRSFAPM/unpTZUAarny34PdMcpqjLWTQIhhF6YUHlcQ5eaKqEpFlYJk1akJWmgc0wlp/1UD4EF4AyRd+HGdGTaar3G2dkZLi8vsdnuULbCfT6fYzKbYbFYAnUyekLgbveAojhHURQ4OzvFf/v5/wPAYbGY9zxBdh5j7MrmqAF4d3eHyWSCs7OzDK6YmzUajfD4+NjjQYJrRiCyInNdXiOfryk8qlATX0QA/dJEZH8aatYTxfnlphbNQ7TyT71V9n7vyx4/MWxK4F9VFTabDeazsgcYOc9PgSC7Ho5da+87Jk8JHhSEWkeCGjLW6OnGfHhkqdU11ssemsPi+PqM9PNwU6LVHzEmL/Hj42OvNqZ6IO/H+qYAACAASURBVIfkOb14/J4pRk+N1dJf5YJzEdF5NE3HN8xn5btoPFRVhe1229sspPOp/dcxW4fIUJ+GGj2IlBFD+kD/Vlnli/7mUo0UWFoMydjLy8sDTLDf7/Hw8IDT09MsZ7nZi2D7WGT0+2g/mM07tiUCxiwkb25uejleGgqLiNhu13j27Aqrxx22uz1+9rOf4fT8DJ/+6FMsT6bw5QQOAQEb+AKo9zVG4zFWj3e4+fABs1lyVY9HBZrQKrYBJlOhoVaNWmzftg0tRC5SBSW6G1QZzVpBuojsezKzi9Dg8Vm6gaepKxRF7O3e1oVjmdaCIAuEE2BIyp65T8DxjThMZNeyNZpYzncdA5adV6PLm1EPn6W9bdYath4HS1/9ju/lBhkNfVlAo0JeLXJ+T8VOemqBcg0ZWyPEAis7VrX6GZ5lfzUPiM/WkBx5gcBOAb5zyeNGgGhBjIJ18iABiBY5ZiO/Kh+pglWvLseltNSx6tohyFwsFliv19jv95jNZikMW4xwenqK7XabT/wiEOe87Hd7OLeGa2JK78j9DYjRpSLG7UbDHNJsQs4RV/5XHuWYtDZejBGbzSafcb1YLHJpksVikQ0+3XmsMiP1P80feYahNe0H175uoFI+VYBgjSqdL+V1Nags7wyBp+TNPNyktVqtcH9/j+vr61wzM4Q2d0SaBRhPta8DoF8HTIeuG1pzQ88FunxHBRRDAJfz+02b0m6oX/p8BUrn5+d5jWj+s+2LNt3kaOf3qTYEoiICmnp/sJYVPHJ90BhWg/TYe5SPAQzKRtsn+7luNGJ+9NCc2LlL/evzg9Kd11Iu2n4DHYjluMuyRKjV0dZd2zRNrnd8c3ODyWQGuO//sPAfLLAEOuLWdY3dbpcLvAIKnoAYG0TX4M8+fYn1eo83bz7i3ft3+HBzg9evX+Pq+gqvPn+Fi8tTTCcl0ALHpgbu79fY76u0CzykJPxodk9rs6BJw1p2EVMhHQMvbAqWdWysp6VWnYIqtib2QzvHgKX1inGxsNi6biiIIeXOkanVm0JAoe59Lg5V/v3WtxgVFB8DbVrfUUGk7vg91mazWU8pHgt/HWsWjFhhpP1VQcrx0zBguRstVM7nUZgoDQgkVWjoWG3CvPZBFYp6pPWdun5UeSitFUA+BcT5Uz3d3BTFen9s7IueyaubK9g3roPOGOlvbmPf2Zj3S8CmuWtDwMXW2eM7eOLKbrfD6dkZppMpFssl3n342F5Tw7kSaPs7ggN2O0yKlIvZ9izTeTQaYb9LQH29XmG/n8EhYLrrzl8mgKPBQH5Q2rGY+mg0wsXFBbz3+ZxiGoIM8ROgL5fLvEY5h74FbAquLfDjzlKdf5V3SvtjgEtlHnmMPK7e5GPrqqVijlRwfhaLRS50TRolGXWY43Zs/o+1YwBTgdlTz1FaAYcbPOyYlbd5Hf+pgT7Ut/wvxAO5afXQMVDJz+n51pJPGkWwqSi2L+RXAmRuHrHg/in9p/qzCTXqun/ikJbkUR3DzSpsuqN6aC7186/rk22bzQZ3d3e4vLzEbDbL+eFPOZL6vNDXP0+tIatf+DurP3Bc4/E4H/m43W7hvc/1dvf7PdbrNdbrdcvH32iY32n7boDlwJr7ugX9dd8751C0GwbItOfn51lo9MGbQwgVirLAX/3VT/DixRpf/eE9bu8eUFUN3r+/xYeP95jPp3h2fYH5dILr6wvsNjt8fH+P87MFRuUEm+0j6roVAkUxGLHX3C+OQwWZAg0CE13wdsEBh0KEn+lmBasMtdmw5jELjguTClafq+FKKiJayppXokKTY1Pvim39vBigCe0RV66fv2SBOi3hp8LXuvDsux8fH3vJ0gwLWiFv6WkBLj9TL47tgwV2QP/IOhs+4VypkUB6sE4h36W7oJWHSFta8FZ4WiOCzyeAU0+fGhfKJ+oRtGCWz9TwcramJSytddZ0BzyAfKIW50jnmbzAe3i/8ij7tN1uM5izSl1pwufp3HMd6LFttzc3WC5PMB6Psdls2jXjMRqVcL6t1zcqu0T83gkRSZBvtxtMpxOcnJzk+9frdQZ9HMN6vc5r1h4xyN2odl7UC8z5YD1OVcCkfwgBEQ2Kosz0ZGhZS25VVZWNIaWbGhdqNA6ldhBskB9UAbNvVn72W7uZTKSvplNwrofmmetj6H12Lej3+vkQuHyqDQE6fb/KdvaD61UjN3yXylSmaFjvdYyxTdU6DJ/b37X/6gyIMeYyUTzCljKXhg3l7xAwA/rHTCqgP9YsrW1eYTr2dAzvXc4VZrPewabpSmwNvfcYLTSfe8hYHZpzRgfUAaA0YNksRmq0ed8aC7F7/zGDQI1e1Q0cKwHkeDzO64GbAqfTadYdTdNkI+ypOTjWlAbf5Pqh9p15LJ2j97BzYQ8tyqEFYJWVcw7widGiS94yhuvU2gLaRRwCYgSqeo/Ce5xfLHFxeYX7hy1+85svsd1VuL9/wHq1w+837+AQ8fqrd9hXG4xK4OrqBTabPWIEoge8J6hUhdESTBKFLfGt8FLBpoKD/baC11p7GjIjw9BLoaC0FitOwxdKc/bJhnYtE2U3f7vbV489tLseKXg0pKPCnUAjfd6ekRwbsKaavp/Kle8nnSjYKISAzopVwKsKJcaYS7uwXwoq6VWzSfI6B0PWqIIzBej6Pdt4PM4WJIU08/h0JynpROHOedF+hJDOwZ7P5711okCVtOL1FugSuLHcTghdySHSTBWjAgirOJWPtbiz0oDAz9ZsVR5SAErQp7xDUD6fzzNdtBSLBfScT5ZNGcq/svTguiGwms1muL15wLNnzzGbzXB+fp5owftbAFsUBcrRCB7eRGMjgJA3/Hz55ZeYTCbYPD5gOhn1xlUUBRaLRQYPVF5a39F731MSVD7WKFEe53daSiXG2APPHLfmsJG+dg7YFMzzGq5v3dXKz7hOV6tVnkPlJ+13N5bYoyeVsfV+py+7PEM1gjRcqkaY8gF/V28q+dqCOPZjSI6TtkpXuyat0cQ+kQdISw1rcq2+f/8e19fXeY2pY8XLvXbN6ryT37jeVXdQDqguUu+fGi9WX2tf2bQveg0NDqvv+fyiKOALlvnp5Juls4LDYzpM59HOHa+hp596bWhetV1eXubncC2SZuv1GqvVqmeQ9UFr2kRFfrA55wTRWj6J8pD3OOf6z/dpt7fSSHXCer3G+/fv8ezZC8zmfRlPnrD4LMZ4UAIyz+UgVY63P0koXBH5UxZhiF2emxV4ytSJKQD4VCkwhAq+8FiejPFXf/2XGI2nePv2PUIT8Hi/xurxAYgNJpMpLi+WGI/GSaBJbk90QK7cYPr+bceqY9bD5IcAuJ18Ch4CEmsleu9RAHmTk+3jEIgfCh9ZoJdKHOyzhbRarbBarTCdTg/OnOUzdHFTKXWft0fPOZ8Fh72fgk+BszbNk1RBMAQCj1laTdNkXqJQUU+PFdDa7HvYF91tTC8QFQP7omkNPEmDQlxDohRaugGmKIoMuO2cUSGR3nquryor0osbKxQUWI+ECh3rZeBPBRj8ZxXokHXvXJevpN4tlQe8pyiKDLh5nfX2Asj5uHyOloS6u7tD0zQ4Pz/v9YW/Mwx4eXmJu7s7AMD5+Tk2mw0eHx/x+vXrVLx6Ms1j6gEhCgoHIJdrcm1oOq2fk5Ml9psNfFtKh+POOzxbDxH5nx4JNdi0/iCBp6YycG3wXHXmTbPwctot3M/n5fzoJh8FtBZIKiCibCIdmqZJaQStA0B5m4dakJ/s2rY8+E2byjQ2emg10mJBhvK2yhOOhzz2FNBQutj+6DvJK+RJvd6uZ72XYI95j5pbzevtCUn6HKsD1ONGfuPzek4aDOs4OybSS+WLlY9Dc83rjoHTBJa7Gs8EgJauXB/T6bTHB0NjB/qF6jlWTU3SKgn8Xt+p60UrWzBSwPkdainS0Xn/STOOj9EKzg3rUJ6envZOQ9Kxee/btL144JRgXjhxk3WPHcMwDn1e0nXzbdv3DiyHGO2b3qf/ABGQdQ3vPLyP8D6kGoeoEF3AfD7Dar3GZvuA05NT/OhHf4662qPwDjE2GI88mmqHptkh1c+qkXKlgOgDHA5zHr5JUybQn5qfoRao0kIXydCOQxXSTdO0O6iHSxzp81SgUjCocFRlwb4ShBBgqhCywlrHaWmVEphTmSCCYPaBdbrUgmYRa20UjjbcZtsxRcXPqQg5NlXSKviGmtJegTqFBIElBQU9kwSvepyfemFUuanBxHdagcw5sIBYx6khQ/ZFPY3q0bIAUL2Q2gel5RB91QOv3kqCXI51aJ56QhP9c5+H3qnAWmlIMKXKQ2vBKR/wmQzJO+cwny3RNF34tSzL5LFEd3JWURQofIGRLwCnoduIGNsNMO3O6dVqjdIlL8P9/T3Oz8/z+Njn1WqFzWaDs7OzrCjUa6DzpyBI69sRfOr3eWe2d3Chv7GJXhJ6Udh0TkhfPpP3qyHKPrC2oMqxIU+hzoHKpnTfcE7Y4HqM/e9pzG23Wzx//jxHd4ZkFXlCo0IEcMxh1UoJHI9dY9Zw13dQPnNeKGP0gIbecER+08hcLpcZKFhgakGq0teuaz5Pd+rzeVauHJB5QEbQcNDjOJUO+g7yjBqF6njIHrcBb7GVbXyHPRlNZaHOiR2D9sV6p0kDzgGfSz6w8pDzQllKEGyba3e6qyzj++x63mw2+PDhA0JIJ3hpf7Q1dZdvSVBMg5ORiTynzmUc81TLZrGs0WOG1de1PwmwPGZVDF1LC4FMbEOEKX8hIrok0CN8AjE+IiLg/uEjfv7ff4E3b9/jxYvnePb8fwbcHk1MxVir2qGqdvCuBT8heR+8d2jMhpNjk/xNxqz/mqbB+/fvsdvt8OzZs154YggA6gRvNpscYsq5nS0pVYHr8yg87XP5vQ0hcUGp94xhOzYLhOx4h/rvXN+zymv4fO89bm5u8nssXygNrUWp79XfrcBUATEkYJWutvE9BLYKgID+Gcj0jFK57Xa7nqLy3ufQhip7jqsr+9L9bb0DKsg4F+q9tOOn9aseAH2mAlkFszYkqsKY36mHJxs8xhiyoHaI1pwT8iy9tZq8PuQ5Zr9DCLi/v8d6vcZ8PseLFy8yuNAcKGsIaaFovuP29jbPa1GymHxqhS9QlgUwIA6o+IrW41TXNbarR7hxmXd0s9+73Q5v377F3d0diqLoRQMUvNnfyWNqZFDBE0SQR7z38EYGAf0DEvg8Vfj6LuV/nUvezw1bLInE55N/rAGhRsWBvBhQgoOgx6Vz2cknzjnM53PMZrNeHjEBlZUP9rQcro3FYpHXFuX114EW/m1D4Fz/m80Gk8mkdzCAyl79nfS04MPSytLmmPzj9SoHbM1PHcuxpuNUb6VuPNP9BnpfDqm6vpOktxk3pqN3gf7hIAr6+LfKXpWfQ2DfOYcPHz6grmtcXV3lqBjp45zr8a3tr3oZNeeboI68ZvNR2eq6wmab8qu1/woAt9ttdkA8e/asF0Gw69Y5l9cz+805YO40kLDCarXC+cUCNvQ61M8Y01ntFp/9Me0HEQo/xsx099ITxJCNRdTeF3BwCAEIaBe2L+B8gf1+i+1mg+lkghgauGIPX24RQ4TzBUIdUddblEUB78ftBKb3uhjkHX8ccregkp9dXV3l34dCAzo+Mrp6A1QIFaMupKmCXPtuQZD2T4FWtzCpcPoCMxWB5gJMJ+V04+yeG0JEKr2SksxdGyqMZge7Clha93qOuDbtuwVZFkAO0ZK0IS/Rs6iAWpW4bRRg3MWsOxZVIWv/6DmjZa9nFvNdqoCHQCu9ngTgFGaaZK/pIno6knoImF/pfdpIQrDKpoKYjf1TRa1CfMiq5bzQO8K+si88Jo3J5nwm388ajWnnL7BarZGPBIwtLzqHGNM6r6p0StNoPEKMwKgc4erqCmWRwGA6NrQD61ZBKrCMMWK1XuH05Ayj0QjL5RJVVeHhYYXdvsK2BbnnFxc4PT/HpBi1a6TzWALpqLXsDW9DXWenp3j+/Hn2YBHw0FvPXErOl3o/NA+V9OXmhbpOXoq0gzygKMpMk8lkiro6PLaO88Y+Ug7Qs65efCtz+TnXF0/7YZqP5kPb9WRBwvHG7+Pw3zHJae/7hr/mDKtXS4/N5LvVoNVrlY+5JocA2BDYtEXGSbvFYtGjNftrvfekn4KGY3ncPWoZwGnHobJTKyhozu7QOIF+3rnOn8pN8oX2Qd+vQFQNI9Vv6ZC0lDYVY9PqkLTuR6OkdxK9ulxr7bMaWrYPTAGi119Trrz3Oc3L9tu5bmMc0z14Hj1BJkviHWu57mqbI0+Hwbt371CWJV68eJG9jZT3XN+6dpR3myagzClUBSaTAnVdtcbpAs6lut401PIqegJvJXB/WMHgj2nfDbCUID4PkdeQ2FDThcef6vL2rgv1siahtVqccyiLEkUsURYTwKWSBQBQuBJV1aDEGCUmqGOJablMJ4mEBg4Ozqf+zmbTNgepBSqt9QTft16AwxCz9gXoQkdcdLxHE47V4rKCQsGdte5IV12cRVG0JxYFFM6jHBUdWIkBTd2giTV80Qqy0G2c0I0ktu913cC1p/gUJeCjA2IEXEAI+7QT1rXgEQ5NlXbKep+O9nPewfespJBOlPF9EKy0K4oC19fXBzvUeY3urtb8QAXbFuRYD6xvlXyMMYcBh8AkhR7pxEawOJvN8vnMFhAWRZGPeOO7WZia3jpuMNHajewHQRW907vdDtvtFicnJ9nbQADOHCPmHLGMDxWWgoflcomyTKe1FEUqNcLxK9ACkK1e/s5j56ywUYWoYId0t2WMSFt6bwj0p9Mp7u/vEWPEyckZQhNRVzVGI4/zs8s07jLNW1F07x+NxijLCeq6gncFAgK8d/CuhHMFCgfEIqW46HrkOG5vb1EUBT58+ID5fN7StkmKLQb8/Oc/x7/+4pf40Wev8OLFJ/jpTz/H+/fvcHd/i9/+/rfYrLbYbTepxMdqhdev/wDEBv/4j/+It2/fYHX/gLPTU9T7Ci9evOiBW+dcLhninOulmpBOZVn2NtioEp/N5ojRYTJxmM9aYB6AJkaMyil2uy3KssB4nPhlMknpAIz+kO8IItXosYYo+b4oihwq5jnWCpC4jnqbTMTzoiBmvV7njVPdGlajMXmwkjHKM93T0XVNE1GWyWNJPtP3Zk+tRnZETigwtF5VNciUFpoKoClBVqaTp+lJ0vxKenUtYAeQ1y3XkgJKjSJ0PFD2ZBPnSvPydZxFUWTw9PDwkH9nNQD10Ka11ZW603WvoLIPdpocqaFxyxQUGsSaH6y8lvVBe/So8yXKMoVw6WAKISA0yWnhfMze6iH5ZXUoeU6BqOqU+XzeW1/qeabscs7lFC2Oh/22hgnnLslDn0uFqex8+fJlj3etTlSMwPd3daU9Pny8Sxsxo8N+X6EsCjTB4XG1SevQj7DZ7tOhMPFwA6bSKQHQFvYIr/2xTrU/icdSAdlQS0QOQOzCGNvtFvP5vLfogXZ3Z/QIoUY6azR5zkJdoaljPhsZMWI2nyFGB0SeFNAATUqRag9xzEcCwiEd6ei+fX6ljkNBAwWYAm77tzZ6x/gMdbUfeOkMKTWXxrm0gwy+s8BYQkELvyrY74q6qodBrOD2/3RPOtkoJV1HhNjWzXPdM9Lz+x6LoRAPf1drnf3TDUNWaFihp+NRYErL2QoZC/Q1LK7v4SLX/EFrrXPe+FwCB2uk8Pqhxr6xnxrW4zi4aQXolDH7zndTqdPDyrwggoghy5TPUa8KwStpYRWdjkcVsgKUx8fHvHGpruveDvUEKE/Se/YNYnQYjVLqQKpTWeW/dV2l/nDXKd+bvBsx6q7TEdJxsH2PxrNnz7DdbvHx48ecKsBNKLvtBiEELM6W+OTlJ/js1ef45NNPcHl5gTfvXmO92aBqarx//z6D/GQIr/HP//zP+PzVK1xfXmDXbuJqQt8bTTotFgtsNpscLiUgYbu7u0NZlphOp3lNJPkVEAONz1Z+OeB3v/sdPvvsM0ynswzOSGN6W9gPe1KK5U+dV64dTVUhINFqGeQ/rb6gsoq/01jRXbFpbOTBBDJiVoo8VrIPHHTtqQdwKE1Hm64p67TQNAH7DAVSNA71/TQkCRLpEXt4eMDV1VXmeS3vo3njCl7V4FSQyPdr07Cy9ovGHT+fTCbZ8KU84fNocDBKaD3cVp+pzCHdLP1VjisQVH3TyYx+OUF9nwM91B5w6ehHSxOrRwjcSB++T9/BsTP9gd/TiFdjz8pYoJ93z2dobjdPElJ9o9Enlde69jRCVFUVlstlBuWP6zUeHh4BJAOjaRoUsxkKT4Mz4RvnfJcr93WtxUkc5xDvf9P2gymQbgVPiKm0B70/NociK67Cw4WAOlRAjCj9CIBHEwOKskDdRJyczTBbzHF2cYK0O3nUEbCIiE0DILnYfcZPBYIRhHz/tx0TJ8l6br4pPfQzghkCn2MTbxcYrb6qbrJLX60yXpfDd7IhgsLhmOVCBuSifYohbdgf6HsSAOSwoAoh9kvHZoWatmOAU++1wk37QjrruPm7JnPrDkEK5BBCb7einW/S4Bg9eY+G2jVkrzSmsNR7OV9W4arwZ3jeghz2j+Cb3i1V5FYhPDXHCkBPT0/zvVQ2zCvUZ43GYzh0XmCCGcs3Oh7Oh4aSge40oaIoMqhU3uRcvXjxIp+0MxqNMBlPECPw4sULPLt+gdV6jZ///Of48ndfYr1e4cPNe3y4ucHF+RVevHyJh/t7hNCkHL/pJIdXaQSE0N+EpJ4KjlOVvyqcq6ur7Llk3+u6Rsoq6RubIYSct01AoeF+7z0eHx+xWq1wdnaG5XKZ7+ducpbJ0kZDj3UuLY8SZCbP6CTX1zs7OxuUeWooW6PIAgUFVcBh1EY9iOQPW6pliE+tjNU1QHCvoM6ClyGQQbnMAxrUI6/RBHrydNezlZkMWZMXdBwxRnz8+BEnJyc5FYF9tICXv5PXNNyqEQVNTeFcqgFNOvAeS1eVRyo31RNvve523oZkotI9gzwXwFxMlUtPzTXnR3mK3/G9dV1nvtWSdfaZlm84tul02sud3O/3KEdpp7sa5uqlH4/HuL+/T/mQUr1Cf5IH6LSYzef40Y/mvfEzPE8gGmN88hCRf8/2gwCWlpDpd4/okBelhmv12qZp4AE4F1KmU2zQIOVVNaHBbHaCn/6Hn8A5Jpc/oPRtgZ7YwEW0ibB8c5sv5ZJnE0cY9Zu0IWuKzKHtGMCwYGhIuB1rXOAKDJ13QPs7c/+G6jnqfRb0Db1XlYQFOfY6e7+lDYWxhp1IIytEdrvdQRhLaarX85kcN8dL740CHX2ehm/1Gnoc+BmFNmmnHqehObP01kbBQGWgOW0MNWk4ksLeevOoRKgI6rrOXqKhupg2bWC/32O322UlaT0zdkzWOLRjZ/SBYySY4vO7DU4O1b7q0UU9ynw/Q+qqlNkvNW4SL7fRCMkJBpBDzBqOOzk5AZD48NWrV3jx/BNstntsdztMphM4ByzPFvjrv/kbjMoJZpMJQpPqszZ1jdXjPb766itMJxOsHu5bnvF57NZT7lyXg0fFQeCvwHOz2fR2hk8mM4Sm4xn+m0wmWK/XeV3TE0sPCTcQMR9xCCDYRiOE64fzN7QJhOCcG5HUs6bX6aYD9YppRIJ9UZnA8RK8Ky9awPlUGM+uQfte/U6BCz9jXzUMqkBJP4sxZmOZ9OMmIb2OMjnGiPv7+15Eie8lDS8uLnpyl8YV/6YMUjClcpXyT73WOkaNOCgwI80VHKlnk3PLeaV81DU5ZORbOa7ymy3/7pInm3/yOuuA4rvUuOYasoac9x5v3rzB4+NjLhyvm3W0Wb5RY3q73ebITNPUOcfRjhdAPjWM/EGeVXoyx1MPo2jqBuPxJH/G70MIWK1WuQ+LxaGR+H20HwSwtM05l3L0fIl9tc/om8ygC6SqKozKAqNijICIfd0ghgDnkwt7s22w3VbY79eAdxiXJabjMYrCwbkAXwCFD0geywaI3cIMCG2S+ABjf4NGZrahQ7XanrKwVDio10Etvaferf3NAqrNXWV4lkpL30EhZPMrLHBkGxJYQ80CZQ356POd65/owus1lEEBYj2pqlgssKRyBlJpFAKnxWKRx6DeL/V8WW8G54eeGt5H4WCVndJa6XDMaFElRZrqTlUqFFsmRuvTWaCufEer2dYMZb/JI/Q2KaBRMK8CVfmB/VUDRT2Q2fLm+dytx6QoCjh0gE+jFfpsBSH0omlOGoE0+5cM0KSI9BkaquXYV6sVqn2NJnShQi/KZz6fo5wUOD09QwgOUcDxdDLBfDbBp59+ijevX+NXd7eIMWKzWWOz2fRoprUFlbc4t0rTsizzbufNZtPmx47aXFKpAygATb1UfC83RrE0kK59rbphG+ebvG/rAlLOzefzLKPUy6LrRfvJsTnnctki9bQpb3MtKFDQ3b18Fz2DBEEMs9tmIwdqjFIu8RnqVeRYVAZpPx8eHrJMIVBkTjTnl3nW3MjGaxTszOfzHs3sz+l0lo9kJL2Vfpr3SlClcoB0H0pjICCkTLF6y4ItfqapHkyT4Fxof0h/a9AoYBtypGRZ4NKGPG4GtY4Ay2v8nGPWSBNpFULA+fl53ugDdHmv1hl0zIHCElFN0+Dx8RFVtcdi0dVxZdN5oPyz3luOQT37dKYs5ifY76uerKURt1gs8vPqugYm+N7b9w4shyxjyzzOtQi/Tczm5h0K9kMrtEAdPGIEHEpE51EWU1RNxBdf/A+8efMO94+PGI/GGBUjzKcznJzMcHIyx+XlKWaTdN7vcjnFfr9FWY5QNW29wcGDHZ8ekwVgQ1YYr7VhFnudght9vrXuh6w7BRYxxlRXzw/ncXydYuM1QyEtDccqoFHQR6HP+bOeW46HAteGh1QJcDzkB1UuFkCxzwQZ6smlpagnGnCcFJIKzPgOOz8KRtX7MuRJsHTX69Tat9a3VX700sfbWwAAIABJREFUFqjhoopHhSHppiWMNPFcx6VAWP8B6NHZe583Aem9KsRtyNIqTvX+an6Zc763uUQBNpWjghbSW5Wi7pZP36fyY5rwr543hgPzhiZEFHndAHAO3vFITA9EYLvdYTTqztdu6hqNAxxSn1arVR7HdDrFcnmS50t3pFKxKxDmXGkBfQViKd/cIzT9z/l8NWI4F5ZHrKwgb+ha5NxxMwr/Zl6lnrhDEDIkg3TN8Hvd4EH+GaoFqEa2BcMEcVwT6oGznmjlZwWJPb0TD1M8FKzbcVijioqfvKd9tXQgyOEZ25xrGjPc7KLynkDZOYfd9qHXD+V/0l7/tiCVwJYARA1w21dLF7vWlVZ8hpbVUk/qUG6oGh/Kn9ax0X+XQ4xdHyyv8ac6L9QrPUQTNq2sMWRoHdPZegRnmssEKn3helEu1Wta/1X7ZvlV5UFdN3h4eMjpRVzr9IAyhcnOz9c16+xIfTrYwvG17U+6eUf/tuAyxpRjSQ9QaH/XlhR+iRA8Cp/yspwv4THC7d0Kv/nNb/GH12/hfIHTk1QbygVgvw949/YGX331GnW1hYs1lssJ/v7v/xbT6QgOEc4ViENF6p4Y05CFzZ+6WO0CtffZxWvHbK8ZAq4ahsiLKkbUTd1jXM1/UiBk3ftsQ4tMd2BaRUSvCRe4eofU28Fn24Rm2zdVbjakaAWq9pn3auhfy/XocyyoUuCiNFEvDoGozgMXOEv88HP1UlGwq/JTOqmgVwHCvqo3Su9RhcP38m9ep2FEHTevZT+pIDmn5BsN11DxD/Guhqc1Z4uC0hoCMXZeKeYr6fGAFMZMCbBeTOe6c7bPzs7ad9XwxaFRQMNiMpn0CmMzfFXXddpt2ea1R5fSZHhWOIC21FmA8+nkL+8SL9ze3rZ5cum6+XyeN/jo2lMwprRXugHoAYCiKBBD2uxA2qvRpJEO71OpKfKbFlTms9Qo03xPXqvlXZhSYsEF+VA3hCggUvli5QfXEYBeugqbhsHJr9QJrN2naRbqnbNyjDQaMkLp6SUNuE6HPGH8Wxu9vna9D8lp/lTQyb5bGUE+4djTfE8PZJUaB0pfXbvWsOI8qbGpPES62LxM3nfMWLF0VPpzHGo4al7rMf2o77Gg186HykL7XvI5aa58FmO3uZFr0c7zkB7ks/vGeqoys9t053z3AWJ9oDs4Zk054LNZuWJUTnJ+tM6Pjeiu1xucngx29cnWB7nfPhXwBxkKZ+OiU6ubigjoGKfaB4xHE1R1wHZdoW5qfPX79/jw4RFlOcP5+QVefvIJ9vsd3r35A+r9Fk2d6juVRYH1aoXFYgxfeIxGJZqmRkrc/OZ9tVYG0LeOFAzo5xoS0kViQ1I60XaB6uLWfijIA9JxWbrQ1OPDxr6p4FBBObTIh6xMzQu0/+xCpSLSUKkKQFVSKhw0vKN5jrpI1dugApXf6XwMzammIOiY7diG7lcFoU37qwqIP+28KKDl/ZbfdM7YN4KxY31RoK58pQqV93rvsVwuM40B5PxG/cf50zm0hozyAD0zfa9jRFWl3FctCUVeaZpUgmyz2eDy8rLnnSUf6TGdpFmMDWLsG69U0uv1Oh/pmO6fYCJF2WNs1y5COuXLpYMYvPfwEaDwdYhwCL2NEEVRIsYG280Gk0mnsKxCVGNKa4CSNgpInXOIbd0/9lENEMvTWnCb16mnUA1WG0Iln6hHXudDowZUaLrW1WOkMkL5TOWjglw2CxL47tPT08yf3LygYXqlg/KlLfukhomuq2MAgmMZamqY67g5fxoOJ29r5MGub9Kd1xOgeFf2+mF5ydLVGt8qE7kW1VjQ9yl9jo2bz1VAr7KBz9C8UN7TBzL9MQx5DWmAslay3qPyXteOzsPQfMUYM77Q9XnMa/mULtSWInCJbpvN5mBjqu030KXyUD4qr1ZVhcfHDSbjac+gVPlOD/hqtTo6V/+e7QcLLJ3zcD4VclakP9SmsxnW6w1+9cvf4A9vblD4CfZVRFkmxXd/v8Jsfo/FYoa/+/v/hNIDdbXDavWIx8dbjAqHs7M55vNp69nwaEL1jYHlEKjUpqDAWs3AYZjk696lwHVIeVurlAIj5a0e5jOy2YVux3JscekiIWMrgOAzNU+P99ETplaW5hJqo8BSQXeMJyg4hzyZGqIZCv0A3ekw/LfdbrFcLntC1wJTG5KhN4UeoyFAqHNh+8D5Ve8Rv+e96gHUOVUaq+eRIJk5X3bHtyoWoPOQEzxYK58ecfWWKQ/ruBRQhtCF45W3qHwJWlkeiTuN+T72U0vnaO4x56YT2ikVJNfXFgOlruu8mYn3jcrk2btfbXv9c3B5LTnXgoAYW1HR1oILicfK1qM6n6eyP1/+9ktcPF7gk08+OdiUoaBA182Q0uzWGhBD53XUdA8+g94/3bi1Wq1QFEXeTTy0rilv1+t1znMl7Zk2wPlS8GE9QWoos+najTEebFJSw4rjtSW7hoCzesiUhkDa8a4GrzYrU+x32o6BB/u9ygg16tRQUN7lHDLvW0sgkZ48qjSH/9GnM0GYGqJ8tm5+Vfpp6pNuZFMArOBX6WUNZqUB0OVYqrxSY0899eyPhsV5/VN0ZhvSf2qssnSQVo3g/Ogas3L42Hw/ZXDYlrzYwMePH/H4+Ihnz57h5OSkx+uUofQWUz5ybVg5XFUVppNZT3bregLSmjhpT/v5vtsPFlgCEd75nNBtQxp9hqyx3e1QjEc4Oz9DXQF1U7V14yL21R6//PWv4F3AdvsJXlxf4uLiFBfTJa6vF0CoATSo6j1cW4wX+eTMr292EaiVaD1EuuBpJdpx6eIbWjCqXPQ77Y8CA83HCzH2lC+9wHrvkOX+lDBVb4f+bRWA5tOpd0RrVTJso2VQVDjxHpswr4ragldew3Cg7s60AJbv4MkpDJ8rgBvaMKD01nka4lmGQihIrRebioDXKEgeUn6cLxU+Shs+g0aa9z4DXp0jfY4+i8qPY1GAay1tzqFV/HbNAl2oTPm5aRo4ANNJB4J4DTda2VzRofp0ulEijbFGUbbHipq1Q2HNovWnp6dgPUUCklT+qPVWet/99P4AWDqPfPJNmu+Aqtpht0/1Mq+urnrGjq4vXSs6h9q6jW0FYugbAzpPSnuOjaHaGLti9rxG54nrSXPTFFAomCefkK6sKECgovnKvNZ6lPT9TA9RnrI1FXk9eYLjAzqjljzivc/lqkhP9XIrELO8bNeRnY8hgGFzYm3FBpV7fJ4CoP1+n2uFWq+yzuVsenLQNwXoNsSuY+b7VJapnFVDX9foU+Pm5+yPbppS+a1/qy7UZ6r+Ofae9rfevOpztR80om2VAvsOC4QJ9uwa/DbAcr/boxx5XF5e4urqqmeAq+6wzye/U5YByGtjPJrlsZOXuPa4fp1zmJj0we+rfTfAUmhuGeigtfMRYuxwm3MIiCmJCW3OUkyu7iQ8gXTSQmvttYW50/UOZekwnZZ49eoTTGenCE2B3S7g9vYBv/7iN3h4fMRkXCKGPX7xb/83yvF/wNWzGeAC6qZGUQBNVaMoHcpihLqq0yYXh96h7DpG4DAEPWSVWcFNgczncNHq4tDrgQ6skBFVYDjnsN3t4BwwHo1ToXK0lhYA11632+8RQoPFcpktYw0bWSCmfVDhBPSVHsek/dT7LcjRPDy6+9WSZ922p3iI9wxZm6r8lM4AerXlVJHo2NlnFUB8NoGevke/VzrSm8ZQhoJ7tU7VE6DvV9ozVUCVu753iE4agmOfNF+Z4JZ9U15Lc00joUBoYjoxCenkC+cKVPs96qZBWZRp/YbWyAuAd0W78Q4AOmu6qRsURZmK5yMiRgeHdBxrVTF3tEAIMZ+drXnV0+k0e485f9xApEAFQC40nq5LAjnEGqqI0jhD5o26rnF+fo50lFyKmqS1Ftrc5FSmLPFuwMQX8GhPfwnpBKr0e5rTq+trPKzuUe32WK1WOD1bZp7nuMgfOochRBSFeJiaNI+jUeKZzWbbpgj0x8DxK6Djd0xjCCFkL7XNV1avGvvInFDrxSYotVUQ1FjjuChn2B87Vwp49D26xm3Ymn3gyUk0FumIIO+TLpZG1njW6yln9acay0pz0lH5ifJZU17UoKbnn7Rla5qmPS960hqWNUIA6jrlCFdV03qa5y0vHqYx8DM7JgVv1kjWjVld+kZ3Apf1SrOvSjt+psajykr9W/uh86DzwftU7x22lP+nQF6vV31FeaAG1RA4tLz8lKEBF1px4OAcxA9FnZ/+Kkqf64LqGrDjU95SUK/gv67rZGzXDYpihOlk2kZiApq6gi8K7PcVHu4f4LzDen2B87MLxG9UJD0C4G57wLmIGIcjgl/XvhNgGYG2I51COgYKonNo2oRWAHA+gcrQdKUDGAZHTHlEVdWgKMdwKNJn6SoA6ejHJtTwRcS4KOBcDeeB5XKK5XKOze4R7nXA+cUZqmaLau9wcjZD8HsADRrX5l0VbbJ+BHw5BtCWGzKJq+qlOQYshzwibLrAVGhpGFgXvxVaGj7gs9frFZz3GE8mCE2AA+BLARaIGLe5XTaUqX2xgsOCHPVsqWdFaZLzv+Ih3Xiv5t+pd4xjArpTOygINITx1PPt7xpqUG8B3z3kUeQ7FcQpzbTPHI+lpXpLqGQITofqqFkwqbsHi6LAarWC976XO6hluHQjAvtqvY8sik+FR+Wsnr00B0VbxgYoixH2Oyq1dMxatW9QFGM4110fY9psl35Pp6OgPRc1zV0qH5bO7e6P0fsCTb3HeDyBL5H7yfxKjqVX7NwYcaSTndtuvQUURd/jpQpMT78pijE2mx1ubm4xGo9RjgrAAXUTsN9XaUd2WcL7AgU86mqPoiwwnYzbDUCtZ3c8wna3w3azAVoQxhA0vUocZ89jEz1Ck3a9OhQt/5YYjaao6wp1vcJi0dXvVFpoDiRBAk+BIbi0Bi0VlvIPw99qNKqxpeCS89E0TQ7jWiCna1vlENeBekA5RwrSbH+cS97Xy8vL/D6W7SF/6Vq1soLfsd9DwFPnROWcAgHKZNZgZb9D6GrRUj5oTrhGAviu9M8hNBHbzR4xAt4DhS8BeIQmIDQNJpM5vDuMyqg+6T8z9oC9cy7LDpVtShelh0Z1enwqc6q04WdMJ1I5S9qw7iLpT57U4y9181Cff/gO1+NjNQAI3vlu3SCjQFR1hZUrjHBp6g1/Nk2N0LSAz7skM71DQ/3reQxlTOl17fpRp4D3vrdRlf3bbDa5tJjOB+9frVYITYPrq+vkFGuS8Vy2EZlNtcNut07lqgLTQp5O4Uh9CkDOW9VTAomDvrmX9nsNhUd3CAB637c/neuYaLvdoapqjMcBsTzM+wOAGApMxlPc3jzg93/4Le7v16grYDyZYbZY4JOXn+Ly+gKTWYnZ5KcoRxHr9T28i7mk0ZFMjqNjsRaPgiu7+IbGay12fm/BkVqByuS6+M7Oz/NCIgOqULHvoweBwk0tVn2/gj8+wwI2Kn2+m8DF1v9ST6LubNXcPPaNQFIT1akwGJpUJWdDFZ3X7bCYvuYMqRWswHeIx+x1Gm60QlmVEe8hoGSumNaGG7K06b3gmFOx20V+n8130vHyp+Zz6Zwq3+m82BQDLaLfzb/reWLVSKCgt16p5H1Lv3O3NuAxGvmcakDlx3HRK8ljHnVjAWnH+1Rx6/gVhHqfQtTAofypqiqffLFcLlEWrg2xF7h/eMCvfvUreF+gHI1R1Q0+fPiA2WKB8XiK+XiCcpQUxPv371rPWcxFjb33mM1nKL3H9fUzFEV/J6wCjOx5gm58QqY9Uxkmk2kOfzF8qikBBA4Moc1mM1RVlcvLULHrbmzyhDXA+H0I6UhOplCQdlT+jDQwf1d5n/2inKFM012sms5gjQbSSdeZhgY553d3d7i+vs48wufYfFY25p0y/GxrXeo88VkKVAi41us11us1yrKr2cixa8qLblJTma+RC5fnnulYAOBQ+KIHJtkngnLt4xDws7/z3XpeOOmoBrHqD/ZTDV6VsTbSxPvpRWakTI0ea1zburwqIxW4OkR4j8z/RVHktAjOk/5UHXNMxiuvsb82jaGT+a2RUDLvv6toEYE8V7vdtqdbFfCSV2ig2Q2H7LPK96ZpUlSl7uoBq2xUnuJBC39ci/Lv27fvP8fSMB1/H7ostGh7Op32drj2m8OonGK9rvHFr3+H9x/vERoH50us1xXu7lfw3uF3X/0Oi5MZ/uavPsdiOQHiGDFWGI0KxKbKYXUMeCm1qacK6C/WY94vO169zy5gfkfmsGNWaysL2tj3vinA1eeqElAQqoWRFbR0c9HvG/tlPY8USlofDUAGr7rxQoGzuvwpSIZAkdLEWqjWQ6ECy84Nc26o3OycHGtDc6rAjOPoAFVXCkbBkL1X6aygUL2LNtfHhtn0nypEVVx2vSkos+DYu85DyCP+CI6n0ynevn2bQJiUllGAMGRYAcjP4vdUvBryYV1C9Tjy+co76sVUIGvfmZ6VjMcQDncCaxiQnq/xeIK6SbXiJpMJPv/8z/Hh5ha/+MUvUvi1HOH9h49odnv8b//7/4q//uu/xj/90z+1/Urz91/+y/+C6SydgjMueHRl8urxNDHyhvIRZE0pn5C36PEsy7JXN5FtCFhzXdqmBhV5h7lx9KSSzpwjVZQM6ZKPbM4l55rzqUDt2EYTC2YA9MCo8sZ0Os0nEi0Wi8HafUP6hc/UvvD8bH3/0DM4NsoinmBl17Z9Do1azpEa/309cTg/2gc1KlXm6JrX96rRyLkuilQDlM8hD6p3Ug3esiyxXq9RVRXOzs56qTlD+kqNBN0FrRsnVXZZHh/6Tvncub6jhafN0BBVnWTzlZ+S86o71YPOezv+iLnKCgG+riNbbkvvVycKvfzcqKMGoxpICi6LooB3/Y2rXBvOdWfBW779PtufrI7l1w84MaY9eWOoVVXEzcdHvH9/i3I8xdnVJT55+SnqEHF3f4e7+xusN4+4vd3h//o/V3j58jk+e/USZTlGU+/bPC8FU0/3zS48jkm/t+PjtdZqUksKeHqHohW6ZLy6qbMngl4DmwepfaRlSIGhgkVDBsDwblXWDmQtQV7HxWiPn2LjorKKL4SQi0nP5/O8uLTPzAnUsK0CT0tn3qMAT4WZlvrQMIMK6qF5P/a+IYFlLX6bUK/K3F4PdIn76tVSYKWgkddpKsKQUaJgjf05ZgjRm7jb7XpnRDvnsmdI+UV5SfupNOL3alAQLJCPcnks38/lU1CtIFwVLYCegdKtJaTwVehK7di5m81maRzFJAPM0WiE58+f4z//3d/hiy9+g48fb5Jcms3giwJ/+O3v8cUXX+Dzzz9HXTdIYTqPh4cH3Nzc4uX0ObxvS4Q8PGC+mPfqSCqoJU0c+ms3xtjzKBVFv+wa1zqVvfIl6T0ajXqnbeVKEQPrhTS3m6J4EgzXHk8YYQkV8gI9f/xbPTRD88R1wLVNJW15ibQKoSvHpP3hiSkKDvR9tvFZQxvohkCfbSzI7r3P49dojDV4h3SErpE0j2lPgYIRvUbXyZBhNARECXqdcznXzzmHq6urA0eBBXDqsLDeWzUI2KxTQj8nHwJdFEbXKJ9tZZLSNNE1oKor7HYbjMdjzGYzFEXRS/VQ8M9xcKxKT21cZ7yO+efKF51eDYDr5+HyvWoQ2TQC/tTIHoGkbtYkSFZA2QPecGiaWmjSRRCKosDZ2RlijAe1v7+v9v0Cy4jeSTZPg8uOkUh0hhMOHhvTiRqTyQTr7Q7v373F1dUlrp+9wMs/u8Z6vcLb96/x+u1b7FY1vvzyKywWc1xenSQmbpNf4VrXLxluoHu6AA770R+b9YxYhrYAVRf5MfBqhROFhoYRjwEgDT+ot4vlVrhIs+dE3qmWJD3IAA7C1lVVYbPZ5BMBCCL4HE1iZh4Jlbo+x9IP6EJXCoQtuLLzoJ9RGdt8TRXSQKe8bbPeMKt4rHWqSl7zm0hLDUXqfBP4xBjx8eNHTKfT7CWw71C+OsYjqsjVM0Flc8CjIWBf1TnE6lx3vBxpeH9/n3facpwMvwLIIIYKi3RlKAxA9rjRWh+Px9hut3nXK4uWK1ghvUhfBcvki2FaHHopuR4YyqSg52aZ6WSCzW6Pn/3sZ9jvK7x99x7v3n/AdDrFbDbH/f0DLi4u2g0/AVdXl236QIOTkxOcnp50R/VVe9w/3MMXKZ9TwR2Va0ebfskhrlka2WpskY78m7xDkKqedAXnLNyvjfRk2SVVlkwT0PQD5XvyhUaWFNg653L4nWNjPqaWWbHrTgGnjpHvIo9yTMr3CoiGnBNM6dCjSxUAknbaVK7e399nXie/qaFo79HvFeQAYhSiQKpKcpizzfWpuYeU66orrTdUDWz2R8Oo1AcKhq2Bogc9cH2q7OVcD1UYAZDzpdUjrGFmpbXOg86hcykNZ7vdwhfA2dk5mqbOqV30qpM/1Xuu8lX7oI20Ip9Rr6peSOMNiDHlT3JfCPvLTW+csyGDgp8x91nlUlmWWK1WeHh4yFENzhN/H41G8K0rTI1CBdE8NIC8MtSexl///5qL39HTU7I58F//6/+Bf/mXfxk8mzW61i2PvuC3wKB9IorC4ePHj/j973+Pi4uLnqeqYxYHYISqcri5ucMv/vXXiNFhX1WYLxZ49eevcHV1gcXJDOtNhf/xr1/h7ds3qJs1PvvsJX7y088QwhaFa+Bc2gnlyUgDlNHFp31mn4B+KMoqfWvlqRA6BgitZ0HDUCEEFKPy4Dp9DxkzhK5ws+bPcUGox0uBm83z5DvsoqFFykWlzE7AyAWvdFQhotYzBYl6dPhetd7V+FDPrYLj3W6XPXAKQLocvMO8TH2XnVMuWh3Xx48fsVgs8vv1fvbDe5+P/WLog5YovSfqcabCVoWqQFTBidLEXqcgTBVBjLEXQooxoq4aeH9YY3LoJ/vEObq5SR6909PTA56m4uFPGkXqYWT/yB+6QYnzFkLIO8SprDT1YjweY71eo65rzOfzdu4dYmzgi8Oc06Io8Pr1azw8PLTG1RLj0QQ3N7f44ssvcX19jc8+e4WiHCEiAd7F8gTT+RxjV2C/36Ju6nZORwASaPrDH77Cr7/4FXa7HSZlgbPTJS4uLrInQucCQAZJTd2vO2h5U/OSqWzoLSOduZY4z+PxOOdcaZ4vQYMCVyvn6CGlsiKtaRQwx01zGRX0lGWJ3/3ud7i4uMihat3gQz5VYMyj6QhI+Uz9x5w9fSf7SsNBaael3TRvmN+p144yUek/ZDhavcU+KGDY7/eZtuRjAhjSNQPN4FDXnfyiLCFgU0CihqG+nznpt7e3OW9PPdSkD+fHOg6GDDNer2CIvGbnXI9DVJlJPrXGvK552w/ex/eEkMqmRTRYLue9vup8qhwHkOvh2nQFO3dMLSGPUD+q0yT1LyKiyfKahhvXIA0WoAOpHJsaCmpYKh8O6bie0RVij87kV17nXMr9XSxO8JOf/E9omm68lL1K47SzvGmxTz/K9g//8A/481efY9jvP9x+wHUsgbpOypaFqTmJupjSotgDrsD19Tm2+0/x7t1H7G9SAfRf//qXeHi4xl/+9C+wPDnB8xfP8eHDe6w2ezw8PCSFUHjgG26rt8CDfbBNv7cK/49punD0dwtSrfLn7yosgc7CIROTOTVcq4n1CvisVUuPBgWxeiLs+e5qffL+/X6Pjx8/Yj6f4/z8PHtz6MUaClvqmFRB83PdBOR9KrRPq3kIGBMIU0FS2HPO1XOhHjeOn8+cTCbY7Xa9z/Q5TZu3N5/Pc66czqFt6mnQnZx8rs6Hfd+Q0rN/M7eMCsE5h3I0AqLvARUb2uN4VDEDXUkgawQAyECEzynLMm/GogLkTkxrtGg/NB+TipTPJ99qOa2k2Edpd7dZEzSwiqLI4cz9bo9ROUbTHn+6bEt07XY77gACvMe+quGa0B79qrlfKYLCvoUQUFd7LBdLLJfL3o5/VbDdmjr0lts1o/xC/ldvmZULVtmrYlUjhXNJL57SmEqd+Yy8Vk/10X6S30MIeP78Ocbj8UFOqJVZNBCd60oZ8R0KQni9PTKWYIl00fHxM6WBGrS8Vg0Zjska1zpv2jSfnPyleXX6O0EAo3HOOTjv4X0/T5OyV2W/lgVS7xiNNDVY6N3l50xpUScAr9dxWVBuHSRcs0pLvs/KCX5OAKVpOGxqXKrRofmKzjmcnJxgNC5QVft8Qhf7q2tB77E65FjTyB/7pJGBlP+dvJZwfc8q+0uZQvnKfmhUwuayal95L3WfpoOQh+j8Uh3Nd5GvHh8fcXt7Cztcy7fOOcjZEd9J+0EDS7WQ1JvVR9sBo/EYdR0xnozw+eevsFye4fz8Hu/ef8Bqvcbr1+9Q1QHLk1PUmwbON1gspvjs1Z9hNptgv10h0fnrSasL9gD1mxnUkISO6ds2XdAaggIOi7BrvyyYIwMqUFALX8MoXDC8lmFODWuzHxQU/H0+n/c8n9w0wFCKFRTee1xdXfVCYvpcei9oidtkdfs3LS0Fzcy/0rCsCjh+Tg+XVSI6l1a48zuebKK7P7XRA8MzowkUdXOPDVnxHTZ8b5WbzpsKWOXXIWBJ7wnzCWNsKyQIaFUet88iTW3Kg3pdOcdFUWSAT0BA+pE25Fn1gvAZ6oEGcOB91pxAftdtJurnIHI9kH9UyfL92+0Wj4+POce0LEugLYyOmDYCFW3tSrBEegzgtJMmVVWh3u8xmU4yTVRhqCfnmNIjj3ONsHD82dlZnm9roCj/WS+5Ppf3Uh4wRE5aao6bhjTVe89n7ff7XC/W8g2P4VRPooaplb/U+2J5VvumIJYgwAIc9RByPakM0rWiHko2BewqDyww4rU2rYj1KjUUrF7a+/v7XPXB4TAlyjpT2L+Hh4ecF8zrNcVJIxQqKzUPXw0ClS+2kT76HKWTykU1cJUPLG1t3rjOr9KbXnGNiO2rbTbe9H1WHyotVMcNrTU1jBRoxxhz4zW7AAAgAElEQVSzs6CXd+z63n3KIuoA9kM9kayKoREWHTvvZV/5Xr3Oe4+6quDd4W55yuKHhwc8Pj5iOk0bBln3VOmlc5fG/O2xybH2gwaW3nfARD1f1ip3SJOx3Wxx97DBw8MG08kMz599go83d9jtd3j/7h5v3t7ANQ0mkxI//vErXF6eY7ffIsYa3pPJniaufb/+tN4HZRideH7Gn0MLecgStIKa/xpzXiqAnlLXflprbggoq1dAhb71RCnDU2Exx0StJ1q3DOkoENBFybHp76pQARwoRcsLVkmSf7LnqO6f0EPAo0JY51LbMeFJYTKZTLKXTO9RGikvkz6aG6TWrFrwznUhQQKgIatf36lj0OcoH7EMDdCdhBMc4I1yUAXFNaAGn4ajNR9M6abhU84NryeYp/GhioLPIjDkszTUxn8PDw/ZuOG7Ew3SSV6uOAzhAcje07qu4V2iA1yXv+wyT7Z5izGkbDjvEWODiARelXf3rZdwPB7BtRUueAKIrh1VuCEE+AERZENl9DpZDxPnhTyqPGuVuAJ6lResI6qKkffrfHK9p6LeiTfp0dQ54T30nKnyH+JdAgFepyePWIMW6Dz5KktUV7Cvus41FKnvtv/U0DgGuLTpJh4a4kzB4Rzpuh6Px7i6uhLjbA/v+ikrFgix3zyak7uu2R/eQ5nMtUPa0qNGzzBpqzmPlg661qxOsbyhv3PM5Cd9h8111LVAOnGeaLQ3TYMQA3z0qOsKReEPdN2xebWeyGPNykhuRu3mxMP7iBD7OcxqENAZowaS9ym/mrxgedDueyBdh8LmTdOgHHfrjHqEkT6W0JpO5+m0PWFdazi1FMEAe//R7bsHlvT8daH6tkV8HWizrW4Tc+fzOZx3KMsCTUPPjAOcg4uJST/e3uDf/vULrDcNQuMBjLFYnOCzV5/De4cvf/sl1tsVpsuAv/jxK1xengKuRumB6EwoPHIgwxbNMeuKn1kAqUysiufbNHu9ClDn/IEg0Hf3QKgoHR2XLmgNexB4ULiox9MqstFojLquWgVamzC4Q1O3Z16XI7gsqA8FUVq4DjF2gGU+n/e8ehwz2l24Dukc9CQsfbtDt/NkhiYgxFQKJr2L89GGASJQFK0XCQ51U+f3AK59X0jvKTxCiIgh5aYknkB7SlN6d8nQMdrrYsxFtZkbB7i2qLhr83Ec6rrbTR9bPqzrBt47FEWZT4LyziO4iKZJYVfORaewO54oiqIdY4SDy8swRiCGiMWiPT6zTUifTkZoms77w2erIiL/aC4tr6HHUHmVwnI+n2ehaw0HeryUtxTU2LCYepw3m00GbVZgJ1q2YLDoA1X1bPNd+2qP6q7OeYfj8RhlUaBu+iWdyrJE6QpATuRJ/NzmPXqCo/5JI03TpHD7eJQN47Ic5TkPA1k5Go5UAM+zvLl2dC4oazguVeRDMkhlA1MkgM67x3lQ+cPd5tvtNgOAIUOY/dZyVFbZ8x7OGz35QOft138qo5zrTvpR4Lnb7TLfKQDQaI7+I53tHgHlEx2bbZqrSdCnhiPfQ/5nXjgjQjE6TMbTdPJcE1qZkeRPAjb0xjm8fPmyBxStEUawoXOmoXcN2yrQGwJmargrMFaa8HlW1+iaIU8OheyVvxTQ6zol7RPvlT3vMfvEfzq/tn6mAmAdZ+KPRF/nkoykR55yJMYIuP5+CQ1Fk0ZqMMYYc9qPVkxRg1DllQXL+kznHObzBbxLe1BCCDg/P8+eaKCrKxtCQAwhZ9fE1sBmn6gOkrdSMU8Xhfm2uA34ToFlAJyHQ4DzEc6Ftj99gOZ9qkhvQZC6r4FE0Lqq0ISq3R1VwHmggANcRESAi0jHqJUON3c3eFyvsZhdw2GMx8c1dts10Kzxo8/+DKfLz7DdPWI2H2GxnCKGGk2o4WJEjE2LexMxo3MZH+tCU08X+9yBhOEw99BnKsBVIPDa5GZP4MA5PqP9rmWGGCJiU6P0o9xPFXSqkHUBKyjg5xqCVuHKxU8vHHdus7/JcgoofAkeuengAXiURTpf2TmPskgnKCVPWAJXzrkWdAV4N5LdbxWiA0ZlmbxAqNpyUAWcSyctJaHVeuNoFLgCdRXgHcFhAoRl0Sn30idJERrAoWiBK9pNmGnTVmzBlUM6faZp6ha8lCjaDS0xpILFPEUm0aGG9wWKwiPEiCZEILqeUAyhQTpNymG/a+A9BXYB59LRhmWRaNrUPHov/R6cg0Oqxxhimp9p6yFtmoimblJ+lvMoivSzZuqf93C+SNeUDk2dxhqaAMSIkU9Avq4DYnQZVCogGY1GuL+/z+dcUyHR+/bw8JDXheYzWe+ZCn/yqfW6qqdVw52kNXmV35FX+VxNl2Crqgrb3QbTaVfjTdfHbrfLO8NjcJjNp1i1G4BijHDep7B34XI4uCxLoEmpA0X2NjSIsQs3dmB8BKAAoodD2uTD7wCPpg5oQkzrJPQ3OaiSpGFLvuL8qFJTZcWfGh0Y8miqAaH3AV30g2CWm2sUBGheJGULf/I99DzSGCGgoldIva86Ppv+w+dy7shvagAR4Ckfa3849wp2SG8F7qST9TArPw4BOi3Dxp8EnNp/HSM9wM5H1Ltdq5Ni0n0uwLVGaogNEBz2+87Y57zWdZ3BPb1WzKFWPcX+csyk/+PjY/aqWdCvANM25ZUhh4tGccivrJNK0ETga9e6zn0GwE2D0agfZSKPUT7t9/tcY1R5nfOhOpE6ryhdK0tdPnq2CX3PajLOu1xkoNtkqXIvg8JW/hc+6bAYAmKI7Yk9PhWj8T7hmtDP13SFT7uIE5ZNKCBEVPW+l+LFeST9qa8nkxmci3AxpPeFJuWER3QVetrneuKfSLkYUBSjVpd+u/adAcvcSZbsEQs+NxdzjTZlOmshdd8n0Nc0FZxLXkqX40Rd4aI6BLz89Bqfff4XKOMZPn54wC/+35/j8eEGX/3+33B9XeD0ZIKrixPs6g0QNkkZuHYBpCXbe38wHkC1tI4tLLVij3kkVSHyOqtw07N826fWmpZRd/09DGUD6AksqySsdc7FqGFGrRdZFEX2MlEwWisRsUBd79vNVkDhXBs6pGcwLdDkuUEGy2mBujYkxzIVvq3RFVrhM229WQmodSHJFnjznFa47NVomn79LqU5x5iUkUcMAXUIKEuPEDol2ZVdSrzsvR7Llme9FYxAUXR5MXXVhTEA33ob6YVLYRR+H0LAZrPLZ9nu95WAhPTeyWQmcxdROofCJ4DuPYAQ2l197cqL6exuBxpx6e9EswKxqREc58UjRoftNnml6f3SsAwF/rNnz7ryOQIMgJSbqjuEbTqAPgvoNqPYIyUJwociA1TOVALcaUtAo4aehtLofQuhK9mhvMzdngQ4RTHGyfIUb96+7UKITYN93SRDKSvodHpQ3ewFQHZghXO62+1QOA/vChRFV/uwLKm8kzB3SMaz9/18L/UkqbwZysvUkKU2yhmGvzUszfvVc0vllj3e6MtpGzLlRg56mNQ4JRDXUjRAd8qWgjsFdJpfaT1S+m5LB/W0cxOhDbsqXTgedSLoWK1nbQiI67wore28kUfJl7yOaybxpsNoVOY12NGE66hN9UHRmyvSR+dB+8W+sw/qVOBnzP9WHTWkn4do+NRnPaeJXKMeUOVZBYEKQLMjxvdzY3VONDzMNW7XE+WEOk7KsnUQFElHhch82KSPmPKUjLTOGbPZbHB7e4vZbIZzOQUv98O3uaxAjl7p+gkhIIinUWnFMdL7yPGoTie9NI+4q7aRBL9zVMbp59CcpSgXHYEp53I4bP717QebY5kciK4n/OwiZXPOYTIZw7sCvgm4uj7D2fkSDw9vEGKJECtUdUBogEAwKYvGPtcyq/1MLWu1ZK3XcKhZC0t/UsklL5BDI4Jp6D1U1kMCgELL0k1zbXRzAWnNmoJcQLTg1RrURR5DBHBo+Sst+J0VBByzhqd471BuJYWBbtqgh4C0ozJRQap00zC/giddxLzeKgadW+UFCjF9FueC82D/Jl22220OkdDTQW+Hhn07r2f3bHp7dN5VWNmQteUj9cAP5fSo0KWxQXDA6zRXkrQY2vGonh3tBwEda6OS55SPlIcY3tO8UH7Hf3rEYQihzd9MqQg2nM73aA4eWosdLWCq6xoRSOkNcD1e8r7I703jTH1huaOiSPVaVw+PuLu7w+XlZe8AARuyc67z1hFM6dxYL5vyqgJDuw4JsLIH1vU3svH5VoYoGFRlxrlg+gLX8W63y14iDdGSBwlC+Znd6KZzoXKffEgwqmk5er/KFaXJELC08vfYug8Dctga7DqHXLsW0Fg5bUEW6cq/rbzS9wDJS04ZyM9s9Eyfx89JW4280TiLsSu5o3Og80gwr8D165qOwcokpSXn30bcqAs63ZMiA/o8oL+Rht5Elc1VVWG9XqNpmlwSrdt8ViOiwag4LMGk80beZkpBWZZYLpe9lBT9513/4A2uaTWgVR5b44TrkOtCPfRDxgsdRelnVwfYRn++6bxZp9s3aT9YYMk8R80VONb2+z1cMcLj6hbrhw84Pb3Cy0+uMZk0uLyYYT4fo2l2KMoR6qq/4QPAgZB+qj1loX7dMxSUsum7tU9sFsTaZ1D49BjZCA3dfUqAosqDidE6DgV0Coh04SRQWsOhX4qI3iwdo3o62S9dbFpOhHSwoRgCBdYS4xj1tATyC70yKrSUh6yCtF5YfSbpYJW3Po9jYT/Vs02hYBU3Q1Dz+TyHbrhbnIJbN/JozTRVumoBKxiz/KmgVkF8WZbZS6Fgk3lJaukrf+kzCfiA/iYA3ahF4UYeiTFmb7jSn3ytPynIl8tlphEBioJ58oiO23umd1RpI40AOApqjn+z2aCpAbRe82yEFAX2dbcRYhRiUkTOo6nVQ53m9u7uLufL1nWNal/h8fER4/EYp6eneX6HDAHKO13HpJdVdkonGl7qtWLjznalkwKuIWOVfKV/cy7UeOjG3s8vs3JRZZ3KH+3/sWaNBwvq7HXad/tuvm9I7qpBpXxulbfeY+UKaWifr/KZHiWlF+dcgRXfPbTxJMSu3qKucdUZmisaY+zVvqRTgXSivOFz6OmlzNF6mzS4vmlTeisd2EgH8qXSA+jSxzJPgfL30JOsYEvHx/fQALq/v8dkMul9X/h+dRTSgHpC51vP9mZ0gjSml1X1pfLgZDLB7e0tVqsVzs/P8xnnnBdrUJP+1hDW9c9Nd9pfyjn20/L5v1f74QJL1xELwIEg0zYajXB7v8F//2+/xm4d8ez6Jf7yLz/H1U/+Et7vUdfJK7LfV22o8LCsghJamYHfWW+aCks7wV83acpgmlOiHqYQhr2aVgkNWbMq2Ozf9CjlMDb6u6u1f5rDRTprH7rfuxIaqlCscLBNFw+tSRVgdvHQc8Zi57aOmg2p8jOdFz055JiiYBvy5LBfmkyuQo/KiKUxlG/0PfxbvVr8nDukle8UBB7jUzUyrNdQPUxWAZHOfId+R/BmPcfkB6WDCmIr7K0iZ1OvCN+jCpeNHkjllwNl0/7jmc8EB6PRGEDIJSg5p1q+RIuqV/v07j/7s0/w8e4Ov/nNb3D/8AhflEibpTzmiyWKssSkGKEJNcbjlAqx3W6w3W5we3uDi4vzLpxZFlgsFvDe5zqvHD8VNPvPOdR0FjtOy/fkV46b86nzrqVQFECyWdDHjUEKtgDk9cc56tI8ulxKNUIoA7TUEcdBj6iWn9KcQX7GtaRlWjhmBdJ6n/WQK8/oeNlUVpKGCmLtPPB369G0a17BoT6HfMhrVCdRRpMntaA7r2nqDkAqcFD9wPWoURnywXg8zsdxTqfTvAHLub4jQQ0Qeqi1soW2pxxAqjOPeZk1hKz8xX5TxgDcn3BoZClQBPqpEXqsKPmYp4ol3dAgxMMySJZPbFRAUzXsOqIBYJ0BDw8PePfuHYqi6NXKtSCUfdtsNhkIk1739/fw3uPs7Cw7KDjf3DSmhqEFmN+o/RH48zsDlnZyB68BN58chp2Hrk1n+/ZLQyjz5AluSrx7c4e72xUW0wu8e/cB6/UKr370HBeXczgXMJ/PUO8rRHRCXC27oaZueAvQjgl5HZP2WUGK0kvpoAIwWWXDoRv7PhUG+p0VErxWgR/Qz11TxTabzXqeRQVNHdgrEBrfoxUFEd9nw1CqCPR6erx4nyqDokgFXylYVNhR8FDhsK9D4I/gxQoNXfR6rTb1yFJQqadNc6Z03Ao4OR98BwGlFvTWI+YUALDwMp8dQuiFzTUXTmts8p2WLxQo8z7yhHp8VTGpF0eBCcOhWrCa41bAZNeHbpSg11Yb8x/Pz8/hXHcilBoRuj6GgFWim2/zLJvefHBs7FNRFFhenOXi9be3t7i9vcXrN28Ro8Oi9ZienJ5hNl/g4uQUq/UjttsNNpsN3r59g3fv3uD+/h5/+5//FldXF2nNtADq5OQkh3J1Heg4VGnzGoJtaxDwfl47BLadc7lwPZWUcy5Xe6AnhJ56rjdu/NAagtpfzjPnWPNl1bNIQGmNWb2GAN8aDSpDNeSrckLnn3xJflfQy/damZ0BQDjM/1P5YO+x1+vvKnf5u0Y5lHbkQxslYspHWZYZ/Ki+tPJJaac60wJmgvn9fo+7uzvsdjucnJxkI8emYqhsZ1N5Y/U3owssHTbUhoxNTRmggan06AyTQ2+zjbao3rDzTJmjVUuSNx+IMaAJ3RGXeuKR6n96JPUUI86p6o+iSBVJirKLUPAZn376KT799NO8lhlRsJsfqXM/fvyIi4sLLJfLrAu0DJMajqQPn6l8921AZYwR+BYYlO3fxWNpAVD+3LWbYjAcQu5di3Tyjp6XaRcLADRNQDke4/TkGpcXO+w3AWUB3NzcITRbXF79TXtMWtpkkYrEHYatjxHcWqmqpNl00vhTvTpqVfN6Xez6/B4NXX+xWQ+avt9aQ6mMwLBlrN5LBXeqsPb7PRaLRQY7HJdaZ+ldqY+s4ajPSfPTB2lcQM657Fli8XOGA1TRs6AsFb16iNXSVQHIzzebTc8ACSFki88CeedcPl5Nc8F00aoXQOdpSLlRkdsSPUp/PlsVrvbXrhGdB+b2KChVr4+GP6xnWoGMNdRITz7bpllYA8ECa7tBwwpcFfpqlesaUiG52+1we3uLxWLRA87q5VSe0c/JjwlQOThXpt2evtu9rocDkLezUm93ld7f37efF9nTMan2OCnP8OMf/xi//+q3+O1vH/KGIgr+87Pz3Lfz8/P8fFUcFvhzLpQflObWS6zygc+zvKa/K50eHx9R1zUuLy8P1oL3Psve9Xqdy+J4nwA6AShprCFUbWqAWRnC/lsgYBXzMX2iypfricCZ/MbPuh34h/mMSjsdP9fMUFM+03nkfPN36/lSmWtzqMmT+t7z8/OeManyTUGTlRMc75D3X2l+fX19wIs0NIZ0HqMr+l79nf3c7Xa5vqYaszp3HCfpaA1zPovyrhsDve4JCLJ/TIHiM7hxTPcVaNNQdnp+55XVcen88TumMjw+PuZqKSqfLJDV3HE2O1Y1tNhXdRadn5/3jDQ+m89SED+EOaxTS8eVfiZ9rgbatwGh2r7fUPi3dKmqMgL6eTZ54N4jBo/l4hxl+R6raoW6rlAWBc7PTjEZTwAXEJoa3pcI7psdyTjEiLzvqWaVsAK4p951+KC0S8sy2tC1dhwxRiACwfU9gyGEnB9FK5mLT4VVURQZGKlS4sLvg9SI8ag715ljJ8iwViPQeQ2th01zhfhuhuK891mgqdDh8zUPUN8BdB4gu1DIRwTPHB89L3qNBZBsKvAsOOLvdv55yo16KkgDFQTqgf3/qHuzLkmO7EzsMzN3j4iM3CqrADSARlNsctgaipLmRW9aHqg/q3OkZ83vkIZnRB2SLS5oFIDaconV3c30YP65f37DIgtoNsAeq1MnMyN8Mbt27d7vLnaN82QbgTrnkJ4mBSYK3m07Jzys0cOx2tZ13bhhg3OuQNk2/U4VET2HBMyc9+VyiYuLi7FWogItSz8+jzmYmicXY4+YEhbVPJeXa4H9yuHsPeo6C/Db21u8fv16MJ6WqIfUgJcvX2K9XuO7775D0yxwfX09jGGFvr/CV199hc8//xyH4w5v377F1cUaq9VqNFCey09TftPfJ5D8fNmXkozgOqEnqOu6EaxTPnAzGHlayzYxVKcgT0/icm4qJm9ThbSGIHeBjzX25HkKLmx6TqnRcKT3hsdlWkMvxryBi3lwpIfKDvaVY1fQxGa99ufmzgILyl0afwTP5F82lZ8WJKg+GnVXmuacTeeT88D7dZc5DSSVw/oeBfjn5sECWj6DRxGSlpYeqq8UTKpRqnpHDebJqZBr0rJmbIxxPImIY1QjQcGS8pyuL+dyyR/yJnlJvc22z+QpBebquCC43+/34/pX2ax8xc8svckrrFSiBomdD/Izvc5VqGaG5s/VfjJgWQRQAH6oX5VXKcE1bEBi1/UCCQ7v3r3FbrdD17dwLuIvfvNrfPH5HRI6dO0RdRWGUPwc/P2Y/p/tqywY/q6Lis/7MRYAC1xT2NiQhF2kfIcKJgV5akHr3/yMApMAhwq2FLKzikOBvrXG9ZQVLmL12tR1jfV6PQpe9ldBkFpfyg8a7iQwIU2omMaj+HAKwHX81ltD4cFx8Bn2XgW5akSowtW5UlClNNHxqEIC5nmItnEtEFjyfruJ5TnPi/KLpbfyUen9BCpKBz631Cz/c051begGJf7k0WY6L9aAY3+poGgcWa81x2hBP+elbmpcrC7w8PiIpmnw6aef4je/+a8R6gaLRd45WzUNmmaJ9WKJrm+x3W7w4sUL5I1CGTz+0z/9ExKmfCd7Jvs5mlpQw7GpslcPhF5/7pnWE0dacpe1HoGpITU1Dkk79Xzzen6vRhn7TSVNEM/+AJgpPfWmaqH9c2PiMZV9P20WVLqwD/ocyi/ymaXZPBozj2qpAVMCnvpO+7f1VtGI0u81H+7c81TGeTf3DrNvOi7lfZ1DXQsqc7z32Gw242Y7fbbt0zkacN65ccbOh9Kb72Z/1HhVfrXe2hjzoRF6/263GysSqGNB5b7lpTmwBJAcvBg3unlH9TllN09aUh5XetJRwfWv/bHX0QHQ9z0uLy/HnEmliUYnbVP+ztho2gSowPecHvxDtp/UY3mywBzwgwP2LteE42TqolbldTjs8fq77/AvX3/A8djieNzhiy9/gV98/glcaHE4PqGqPeATumMPhFwzjv2z1tT0+h/nArYAwipMZWDbSkrYD4W2Vdiqh8++0ypXCx7Vq8C/rSdN3fX8vqqq0bK1iwvAUFR8nrhuFbnmDylQpoLabDYndFMhSICt4E8XDIATOvEn77NgWMdKGtCrxw0rCmR1nrWp0lCwUBIa/Ezrsimop6IvKVLr3WDT0FSMEdvtdkZLAhLmaJWaXltSFiUjRsfPs5BJS1VatvE7K+QsvwJTGgnnURU9wYQCSfVak86ThyDnTtFbrEpV+5RSAtKkKLhT/9WrV+hjGjbw9HAhwHuHx8dHHI97XF5e4urqCtvtBnd3v0BdV/jii8/x7Xev8Xd/93fo+3xKjs1TPNdUNul6JIjTSI5e/5zcIs019K/eGRbWZtoJacwd87yfmx5SmsoxsSng5+9cS7vdbpYTprzPOeW1nGvyvA2xAxjzAjnfmi+rz6FsIw1o3LIvJS+RBSPAPKz9Q+eOTWWjyjUrM84ZFdp3tj7O81CpJ2mEee/HY0oVAPF56/V6plPtnOg8nQMyOk41CtRAUZ2igNI+S+dB9ZMa4fw7XzsZF4vFAi9fvjx5R0nWqOGgn7POshpyKnct8CfN9vv97Lhda/Atl8uR16x+UL5W+WlpwXsUvJbmQ/FR9gJ3M9n6U4JJbT9rKNwBUoo8TyJmxdTNtU6P0PKzSSfQuX94xPfffYvuGNHUNa4+vcW//82fAalF6ltUlc/vTD2q2qPtY+7FDCA5+c92CgLPWWh6nYIjDe+d8+DoPfaz4PMJKnBzz9J4jxzPp8+xQtWCTl2k6lnVBUPhq4pfvQwAQUKCi3EG5vhuzY0FThPgdS4VNFl6WqsVmDaX0Ltqc80IZun90k0hGvbWvC7uyCPwU3BZUnr2O47LgrTJys4Cg0CMtFTvJq9TOmgyveUTfq41RtUTwtBjKQzOaxQY2/4S1PMZ9v30dmlRfd0VrO/hWPV9lm8prFNKswLoFKqajmG94xS4PJNdT4fpug4x9ej7+aYDVZxTTl6L4/EwnNqUeelps8FydTHQJSF4h6enDfrDEev1BV598gr7/W441rRHPsc4YLPZwvsKXd/jH//xH/Hll1/OFOBzQFDnQvlRDSUqoo89S2lM5U8wqSBQ+dnyEj8jcOHa3e12ADDLX2YfNST6+Pg4q9NKmqts0jnh33pWuDY9HUbvU3lDGuozgXltQ/KY5vNZ+itw/RgQ5U+9xhrcCtqUvvoMNutd5LO6tgOch6dmTQCQ0LZHhCqgP/R48+Yt+r7H559/PqMzn2vlME+f0qMoVfbrWM+BG9KXre97wA20TMgGmsOQxpZ3TSOl4fALgufhQA2fPYk+5NA/5zSfPtaOPGY3flo9Y3WcGmukBfde8NhMzUUlHyrv0Cuo5eF0nihbuz5i0TSjUat6irzBeyhjY4yjPtIoXYm32Chjvc91dPNc8n1TKbSyc8/in39d+0mB5Qkwc0Co3FBUmxMdAagnhsoVOB46VKFBjBgmlRsqACDXp1suanz2yR3e4gO++OKX+PzzL+Cdx7E9IIQlnKtxPG4R+4jksscBKZ8Ew04578YjHMEtL64fGUwtRa3PWBqvLjqbkzblh8zzikqta0/Di2qp6J7xPs13ko2Lz4Q66JngItB8JN5DgUBQuN/vRybXvtr7uCuYi9VaSeop4KYWFuTlcxRIkV6Pj4+z0DnDieyXKidVvmoZMr9KlY4Fh87lPDJ+pwASmMJ/pCHnl33jGJXmGtLVMaiHhygYI3EAACAASURBVB45K5CtccJrLf1pzZfAfLZY27GuGlsJPCrvas4tkMvONE0zO8ebz+BGAQU5mksGYBTIHJN6biwwSCmN4EPrLvI+9YIRNCvoSSlhs9mM4U8CXee4c30ymghi+TzW2VwsGqTYYbmsAUQslwukcZ7yaUebzQ51XePuk8/yO44RVVigCnWulBDziTqxB7q2R+WA/+rf/XqWu2znUvnSGiWcZ03aJ78x95QbCqwBp3NMo1L5loYvN8pxE4R6E/kMnr3NeaGHn1GH/X4/O71Jczq5bjX6oaFGXYsqy3Ss1tgjfTT/UxW1NVJUZqg8VhChoX1u6FMdYA0/lRcWNOjcWi+nbqzRe3T++Vw1vMexDqfReQ+klI38vktI6OF9QJtaXN+s0R67mQxXeak5zzHGUU6wzB+NEAWX3EDCNUbDApjyAQmiMhEi3AAsY4r5KFmkIeIQsHnKG9+uri4RQjXsL8jYIKUWXc9ayhWAiBin6gacM9Jvs9mM3lnyrc4Nx6lyV2VS33foumlDpeZ96mlufK4aZCqDVL9UIcxklfIfn0OsoDzIMeqzuQ/B6nY1vqlvco3kS6TkkE/UySfJ+eFoSedOnWWUj9Y7/mPbz17Hkt7KPNHzBTS7IkW07RFwU4L9RPDsNYgxC4yvfvUFvvrqSzT1alg8FVICHh832O22uLhcYbFYwnuXz1l1cdajlNyJz1Q/ec4TAJRD2RaYPEsTM7mlZ/G6UggmYp6/qVbtuefkhVo+XlPBmXr2rAdj6D1SnINZ9UxZITz2eRDaCgq037xec1O07/oZn8f3qOIBppqFHIudG+spUICtfS+BP323LkYFwXym7hA/553gZzrPqijt9yUBwDESoFHBlrw+1shRC5mgEZjAJnlBjSJNYAcwnjVMcEIATgGpfT4HpGh8kJ80v1Abgct+vx9zTTlW3aTmHLBeX8wUAud5t9uNynH0aA3gMITMO/vDARd9Pxz1mjcIXV5eYrVYgmE5yrWqDjge90Olg7zpJXicVCRQr4bSX88dLvGV/idfLRaLcbe29ZoA2ThYrVao63rmlSrJntLGopTypjNNSSF4uLq6moXPed40n0U6s/yMrk023ss5VANGDTkCU42aqDGtBo5GXhSEWuBnQR0bx6ue0ZIRwM81GmRlWen5rKShhpcFH2y6bkgnro1pAxp5q0YIGZAvFgt0i4jsFJzXH545KsRQVDBrvbi8lrqYIIZzyPVDwy8hoaroyKFDCQAIgiJub2+QUppV8RioOsMGfX96RKWdD+2L6kR9LuUJyzmxvNvhsEdVhxkNzjl+PoYJbFM9yvuVLzSSw+tJd3ouAczobvU51wDrXV5eXsL7ClVVI8a845tHE6dkxzDP0f6x47Pt5y+QbqzwZwGVn9ffy6HPgBCY/5Q9ETFmhtwfexyOEavFGt+8/hZ/8zf/GfvdHl999Uv81X/7V4OiAE5D7yXlDpC25yxQNm5ysTX8fujklGigTKPXlZ4ZRICp8OQ99vm64MjsWoCa+WAEQRYIzfuUfczWO6XX6mLisxjGVosSmDYVEHRSsKl3geEPglMuQAIo3XnH/lueOycwLK1VMGnoSOmo/ef36l3h91RQ7N9zGxMs4OPv1go/Nw4NnzzHhxqWtLRhPwlA1ONraaN8RNBB2lPJWz5SMKBjVvpxjhVo6LXqJedYlY+pbGKkJ2LycLBvmr5Br996vcZxeO/FxQUuLi5kPgL84BGYIiiD1yjlOnthCKOPmwww37DBRvBOI0zDrdqvkkEEZP6+u7vDdrvF/f39WOLFghnm2Gq4zq5lnU+CJNKXhbr1fhp3zE12Lnv9t9vtzNtDYGfztO37OWblJzbOo4JMm1ah/EvjgeMqGeQqT1Wh9/10Io09QUx51j5TgT7HwneU3s/Pda5IXx0XUDYu+Lk1oDn2kZdcQCzQW+WZfsdxcv3qO7UflAcqn9SYpEHn3PzUNuU10jrGvPmmVHlC5R7fawEQnz9P04qzaJI+w0bUJrl3euxtSYda7+RzOIZ8wPSTUmkiziMrfPB75njzO5VvVnbq/Iyb36rTtVHiRaW1/f/7tJ/fYynEeLbTrpzMGyNBHw949/BVh5jy0YKLhYfzCW17wHK5gHcBXdfDIVsiMXUoAcnT15+Gqs4RWkPVyrz/GtSvwsjS4ORaX673pkxvBZM+2yo1PYIQwImgmzOdmwFwLggLRKksgbk1pqFQvkOtO5au0JAoaU7rje/lAtKajqowSgJAgdq5+S15F89ZdnwGQYt63Mgf9ASUcib1OfZ3Vfxs9JCc6zPpXhLY/J7X63+CiMViMYalLX0U3LEfFJrWmLDA6JyhpoKS8878Kbu+Ukrjd4vFYgQ3qthnxkZwMx4jjzdNg7qux5NH6rrG4XDAYcjjbdssM7LMCQAGT9roFclnhMOlAUBOOYptm0vtJIcZTVSZKLhVo0jzVK0M4jMOh8PoibTAyno0qKSur69Hw80CG76XvEWgo8XP2V89lYcgvu/72ecMh1tDVsOPbMo76nFSz6V61VUusc8qZ8jXFqSpPNJ1ojKJskefo4BG81AtDUvrpCS3tdKB9svKaguqLN2U/lxvmvLkJeKnz7X1HTl+5R8bCVJ+olwg/fg5+zYHQKfHXiofe59PjzkXgiVdSsaVNb6U9jHG0aDn7wpCLy4uxjHWdYM+drP5/EFYBWXnkPZP+0/6cn3ze8ohrjmtf3kuAqnyks/jwSaHwwFhyD9dLJYndHquv/z5Xw6wxKkXrtRi7NG2XHjVBCz7nH/pXIUQBqGQWvSxQ1V59F1Eikesry+wvlqi7R6wvGgQ6oQ2HhD8+d1ts34aEPEcgenNOCeoP9ae856pUCqFkAAg+ElhWmtEBZUKT83hoACyp57Ye4F5mJ3eBS4MBWD6typ5FZS6KUXBiVpW19fXAICnp6dR6PGd3vsxn4v9dW7aqOKcG3PCaAXqYtZ77Hhs6EvnSAUs/9Y+8HoFU1zowOlpIKVWAnDaFKSXLFD1CFPBl0KcJeuUQpfzqtaw9lu9hfReKVjSeU4pYb1ez9aHPs/S0gIL3ThkBar1GpA2zD0kYHEu53iRblS+PCmEoJTKh0ZN17UIQ15SfkcOZ+T+RDjn4TzyRjs49H0O29V1g+Uq19H1PszyfEkD9TYRwK3X6xHcsK8l4EIDgEBaC1KXeInzwfFyzlQhk/Zq9Hjvx1A3Q9r6HUEfIx1MjSAP0KNpAaUCEYJ/VXz6bIYumVenu8/1Wh0/38OqFsq3GhrnZ6rs9WQV3VEOTCfLqNxXGtoyN7zGNqW/BWVWZmslA50zXTcqi5nr6lzO8UtpXuZJ17bSykZZLA8pvTg3TFE4HA64vr4e58p7jz726Nt+CIdPjWPWdBUrc88Zo9qvc7rTGjLMH2YePTcm6TvyOpo2CWopredktcqi0nV6oo6OlV585WNdHzyJTPci0LjT8Vk8Rb19OBxwPHYDL0xpKOeapfu/pv0kRzqWPDxjM9+TmPZ+7vgKAYO149B3CSFUyLQZPAcxAr6Cr4A+ecA7JOdwdXuJu+0tQuPw5a8+hatbuK4DUjxZMFko8T30hp4HmnZcanHymXbCS029J3q/va/k1dO+c4FQYJIxCSyA+QkeLFgMYCbM7QJWBcBnW+bzPswWiSpO3XiiIEMFIN9pPTcU0Px+tVqNykpr66mnln3nuym4tNQRw1sKMjUswf4SjLLfWifSzpWdF45HlQ0FBQUW55/v1Q0M+jfbJPjmG6NIJ/UqEVjrfDE0zXlVQWZpyTWoa1PLh+j4KKzUO6uK0oZ97EYn0p8KQAUoP1Nlaz3zauSo0OTzp3qqORzOZ2tKgnPzJHy+Z8onHHKHqwoxOjABPh85G1A3BFEAEJFSjxByPcvr6yuE4NDKkZ3KqzTuCGoVaFoesyCK/K3rV/PeSCsqR24+4LXMkdRNZTHGk3A6v9O+lbwnmo+o16oHm4rT7ujm+rH8p2u6xANcV+yjNR5JIwuWVfaqAaMbd3iPriP2R8/utjxf8pJyzSj/q3wjHZxz47ywuoEaIOp9I1hX/qd8tBESjtnKJTU+ORauDRrAfKbKajb1YHPTDOe36zo4YDhFr5vJHdKQDo3JiOuKY6KhR35mX3ST4P39PZqmGQuRq8zWPEWVD+wH39l18zx4XUeqy6zso95jaouOoZcNMbrulR+5Bm3oXp0o3ACk60LXD+nO+0II2G52sxA6ecPq+xKo1M9/bPtZPZYnmY0GQOlgU4zIO90cgB7OeaTokFIP7ys454HkEBMQ0hLO9YjJwQ1lCuqqxq//7M8QYwugR9vvUNUV0HpD1IC+zx5S54AQKiDlEggWXAKnoUMrcJ4bX5EmOuYzwJKfqRBjH5xzSO75UgQqcBQ8Pcc4ZE4qMfUocCFnAZfg3XSKDJ+twor9nt83L6Gglhswr4en47CM/xxdWWNPPR1Kc1XUtr+kk/WQ6Jxby1n/VpBjF65ayVQwFOg/xlrk/Zq3ahVzSmlMUr+5uZndqzQlj+hnqij5s2ka7Ha78Xzhc95S9TZRqOmY2UdeQ1Cj3lzl9+PxiN1uh6urq9EjRg875/VwOGC73Y7XqMETgkdCROomr5luTmJu4OPj46gUdrsddvv8jofHR8B5wOWNgc4HtN0BLh4R02qsUlBV2Sh1Pm8WoqckppxUr4qQoFfTOVjgWcelPKVzrAafKinN6eLfOudVVc1CbmowOOdmCoyf81k6ZwpIyR+sjchxAznawFQFa8CQJ5Qvle8U5FAOWZmr/xUIUbmSxgSZVMDqPWc/LKjt++l4QvtO9kXXmjVySTPOD0GUPXmIbbfb4fHxERcXFyOvKK/rfGtUyIbCOW7S1Lkp1UBBldJMr+dP6xku6Rb2h2uOn4198qfGCOeIa1+bvVbTIziPrODAz51zs7PJVZaFEPDixQt0XT6CkfSxvAQ4hGqKTPBdmqtr6UP68XumYbGSAPvMHOfD4TDWSdb5VyObz9JNywpES/qP/KcAPoQAiFGoRtRP3f6NdoXL36JIOdF2gef/Hs57VNUCznnstgfEmFDVDfaHHukwJNX7Cs4BsY849DlxHt7B+xpt28H3NfzgkUwpIcU0KB2H2CcEHwA44Ewupl1kz02SLm6O9WNgUwVr6TtlRtKoaurxfWRyWpgqBJk3RBrzOxsC13lRMKAeBv3pHUZ3veY3WlCi47dhdNtsyEyB37lwjaW9vc7mMqlCsMqF3gA9PcKCQwuS9HmlRk8ilT5pRa8LQ3YMOwKnwsPyhX5WEtwUrHmH4Cn4tWWq+BwVQGqpU9FS2drwmT5Hvdx6MooaNmzWe8PvNccohDDWpyRQ4TwQDPJoSfXOZAWRcyCVH/l8KjctLbNc5uMbIx7Rde/w//7t36KqF1gsL+B9QILD6mKJZT09Z7Va4njc43A84OXLF6iqgHfv3qHve6xWK1xfX4/8zj6UNqHY+bQ8pYaZ8jO986QFaUceUKVF2uhxedaLp3KYfGKNM72enhoN2+qaVaCiYWCO1XpQOC5ep/maXB86x3ovga8FTbxGZaXKGCph5hbbnGFtjBCo0apj5rNVv93f3+Pm5mY81MC2y8vLGQDnM5jyY+dIQRfnUuc9pYSYgNi1J2u0xGvqxSOwJw/YZmlS0l15A66H9+UUIo1oqKGs64TfabqW3b1eVflIT1sVgbxgDWdrEOT3DeN0UyqOHlNqaaHVG5gyQbmj64dVGDS6UGrax5F+wjsE09oHnT/lYQBjeoJWY3gOX/wh27/NrvDx11Mij4SMOS9JF4J32VP59LjFP/zD/4enxw0Ah+gq+KpBXTVZIDQNFk2N5apBs/BYXtRoGo/gewRMNRy992jqevBSdkipR9+7weMQkOtrnu4GY7M5UHYc58ZmmzL3c80CixK4Ug9gjDnXJqU0CkqbW3QOCKni0Hmy4CkN3l37TKsUrUWtn1G5K4A4RyNLx3N005xClvWw/VIgSaGsuynZDxXm+l4AJ9fqdyWa8nlqnVrlaz0pvMZarADG0IfyIoWIbnqyKQOkAb9XEKFeJY5PhRLP72byvuUTVTgEnurR1jljLhaBp/VC6jx572deCQpzjk+VhX1P3/dwHqjr+TF69LRst1vEGLFarbDb7cbnsdzHu/f3qJsFrq4SmmYJP4T+/uSXnwMAbm6ucXt7g6fNI/7jf/w/EWOHX/3ql2iaCh8+HNCEKXRKemqOlYbbSmvpcDjMwKPufFc6a1PjRD3HQPbgMQd1uVzONrsRuNFzyfcpMLRg4Hg8jl7NxWKB1SqXfksp4ebmZhait/LOGnZ8P3lTU1n4jtVqhYeHBwDA9fX1LOxbAsClCgxqcFKhK+DV0kElGaO8bo0r5V3Se7FY4ObmZvTslZoCZetEIN/YDYvWWLMyMYRcQl2NidJGUwXxfD+NXeaT6thtH7R6w3RNdvTnXOT5fCvAK+3g53UEuYyYMPJGmTAHh6chZBrumoZE40t1So6Qsr/Tmrq/vx/fTdmqhivfzzVFjzQ/v7m5GWm1Wq1ONscq75SMbuVj5TnlM+U3PiN72T2uri7HCEXp2T9F+7fZFa6/F4RoSkksjwTAIwQHeI/YHxFC3kF2ub5G2/bY7Drsjw5PT0e8f7cDkL0TMXa4fXGB65srLBYVbm4usawjKh9Q10ukmHA4dOg2U65RjH0Or7v8GNtsiLM0judaaVKtEOR7ngMoKrTI6HaRaZ9VqesYSgqp9P55v102EEYwMi1y64VURWJDRgqodIe4vU/7qTR6DoxrmENDrEpvjouKTN+dUi60HUIYzzK3VqIKJTu2Ur9UINDTQUuYgouCw+ZR2t9LIJFj1KRv9QRawKr/VSlbAccxKdC2eXSq3DhPqnhK6Q8EqaowWYyd/GB3FOtcWWDMfmkoaMpn7ZDzHyeDRgGbKiDSbLfLdQyfnp7gAFQjT+YUnZgi3r9/j6urS2w2G9R1haurS9zcXKOua7x4cQcAeP369RjK12P0OBb1alke5+ea02cBqM4ZPRuaq6alxMiHWvpEQbh6wuhVU8+VrintH9/Da61HjHPBd9gwpI1MqIyzcpZzrjmGFiBqGS3Lc9pUNvAZVgGH6tQoAzCWgSHdrYNB1xY3izBqYfNt2SYPaUROz3IndAIwlqXJ/ZqvZc3HzPyeo3IcP6+zwMpGhZqmOSkOP2/z+XB+AmeRPOwcUpwcNKU51fVK3uRY+Rm9w+QhBZ9ct+QpaxTrXOrcqhcv0yKD8JwGl+nFc751/fG90/w5LBZT2TDl077vsaibMSQO4GTNqz6b/04+mtZg5rEpojQH8XN9l3Ne65ks0GjUTwkwfxJgab0FbA4DYwFFhiaxc7jtOFgZDFv36PqIpl6gbmp8+eVn8CGg64Dk1nj3cMTvvv4dvn/zfV7EXYcEoH27xfv7wX0e3sDFI5omoK5z8v1+f8DF6gKvXt3hl1/9At71iOmIMCgQYD7xJavUKgHbStfyb3vPqCiRPYHcOMCFqUo+IC+yuqpnzOzcVMONi4wK1OYakglPhflU7LcKk5fHOYcUE1JyQPJAmooRUxBYS1hBor7HCnTOvb3O0p5NLTiGvfg5w8ykt7XutRSG5UENC/EaLVNxDvCrki2BdaWDBWFKP+WTCbxPAsHyEOmnwoehMz2bXedGBavyXmk8msOpYTZ682zoydKCz1beVQ+mht+Yt2nXnIJ6C1L5Oz1rupOTtAshjJsI9DPvcy4lBX9VVahCDSQP72uklHdU1nXC1fUNrm9uUVU14AOurq5wfXON/W4PuBab7R739494efcp7u5e4NvXb3B//x4Vaji4k9OfbD065VUdu+UXBSwaLiTdFARaUMbnL5fL2WYLDRNSsStQ1Her0tRQML1czmUvo57gpGMhD5SMI+W5sRbfoNQXiwWWy+UsL5ZKk+FrrifdIKfA29JYgfxIywGEwbmcb+8AV4VB7kVg0GFVqGc5iyqzNPLinBs3lPBzbsxRGkx9cXBwcC7zcPA+67o2y/S04FiGFDHn0TT5FBsgh53zc30OKWEuQygf7U55Glh6rc2xnMlmn+AD0PU9qooHMSQkZH3lfC6/1Q/6i3RRkKe8pPL+4eEBVVXh9vZ2pkPIW+yvNYBJX/Xq2nkBJnBHMMq6zd6HrNP6DnD55KwXty8HHs6F5oOvx7lJKQEph/uDr7G+uBprecIBdb1A7CN8mPTBsuLhHpLeEiN65ptShpIvQoB3DjE5eOQ5b9sjgDSTc+P6cQ5t12G/38G5CtvdHsvlxQT0Va+yA2d02u/b/mDA0iLmErBMGBSOUYzaxlCG4/Fp+UQB5/Ouy5iO8C4OHsmAUNXYHPb4+vXv8PrNa/Rdi1AHLC8vADi4WKPvHYBqmLyAfdshpeOwQcjh6WmLD/cHOF/hs8+vsFwCfWyH8iFzhWtDnnacFviwlbxkvEYXtN4T03AEVpor/ATk2pXV/EgqPk/DKbqbU+lr506Fa+5jPvrSIcF7KsA8B84BVRVmJXys0tE8txLgVotSBQVppfcpXSx4UaGujQCEwsWOUz0dlj7sBzdSWPra91gg7OziTadeSJ13Pqc0H9aKLY2Rx5jxtBuby3NOMeh7KbAtMLS/69+adF8C0vYeGjwcu4Ii9uecJa/zrpa3BasWSExhqxZ1PYEJDZ2v1+sxrAoAfZ9Q1x5VqHA8dvjTP/1TXFyscXF5hdUq172LCajqBk2zxGp5Ce/zOxdNjX/3Z7+B8w7ffP01Ht9vkKLDYT+dXa45iZrzrLlyCgDOeRuUH5R+upY1gqDgjp/xZCv2p+u60Yusz7cGI7+zIFa9TxZs8b5zMpPzqPRIKc3Kh+kYdN2S5xVgnJM71ljluFJK6FKE51jdcFKJc0CuJAVEPx2mmyZDlJ62kjeIz9Z0AvUWzo0+wMHD+YDgHAZpj9jn72KM8K5CqLIadQjwLiH4CkjD+nD5WMQYB9DjPfo0hV7Vo2dpoRs8SEcrdwAgIYLQxDngcNih6zrxyAP5fOqEBP5d9r6mlGYeZq3akVKabSaz+kQNEfI086XVccFn29xcNXLyWgzwSOhTj+CrQWbwfZSfeWxZLQ/96ijTgK6jI4iy1Oy1MGMnnVFl8MhxTfQazk13ATFyXqoM7Cl3Zb3EOJW2qytgf9hnkCzyVnXBOP9mjZTm/Ye2nzQUbj0gyAbgidK0yrZpGiyXC+z2G+RzLtO4iHOuSjUwhMfT5gl//9vXePvuEa/urvHFF59htVphuVzhzZt3+Od//BYOFUJYIbiAulmgaw847DfZs9lmN7tHwjfffIuLVcL68xu0/XG0MkoCSts5sKH3WoFDYUPhb70+1uNnPT/qFdNEdRVw2gerEADMlJyOJVt7CW6QpvaIOW6coKdCFYvNOVRQRSWviekppXFDhnNTvTYFXM8xOb1oU7/nG0j4DjsfpdI99rkWbNv55ri1qLDeU/IGWKOrtA70Pjsv9BDxe863FnNW2nIsnJvSe2yzCsCOmddYwFcCOxZw2/xaBYuW9vo+0k092/RUK6049/SekZ/atoXz2SBSD4l65NTDFGMux3M8HvHJJ5/g6voGWQzl/jRNg8VyhRBqeOfgHfGHg3PAfrfD559/gfZwxLv3b/H09DAeG7ler4vrjmNkOTANKyu/KW1tvpXOoW5eoUJW/tR5YChb85EtuNQoiNKazyYgcC7LjM1mg8vLnN/1+Pg45nlrf62yU9Coa0rXozU8lB7neM+uf71evdcxh9Mm/nMJSGLcSJH9DJnmz+bzNUfUzpfKR66JkR+y10DGMT+AQOXb9N5cEsuGmy1NSzTi+DnfrFwAZLDOEP5qtZqBcO/yqVIpRTRNjeOxHCrXPlgwQzoRdNPTmFLCixcvZmXllIZqvOiccizk0Y/pDZUnq9XKgP1wIjfViaFrkmk7PB4yv99E+c70Q3WF9wEhlPWALm/nhjXo5nNJPqLsA4DD/ojD/jDrsxp8Sle4yeln5e+Pbf8mOZaln/ydf3dd9sRcXa3BM1Dp3crCNDPWu7fv8O7dt/jll1/hy19+gfXFoHTTATfXNT6sPXbbI477FnVYYrlcYH19hfruBY6HAx4fn/D09IDuuMP28Qlt+xIp+QFU5VZStHZMlnnUep+8JlkA60aVc0nUfZw8lap8yejayMwM52n+m/aH9GWYlP1Vj8g4zhTAwvRc3Fz8zIEjSFBQwIWqYR++Q4UC6Ua6sA+kgx6lxrFbocRxqXWr9CrNk773OWBVananvQp5OyblGWudPvcO7avS68RIk75eXV2Nz2N+nfWQKwD4sYaSPkfHPwnEcn6p9tvSRPnCvlPBt/ZVjSMV9BakqJDl8xeLBWKa55DqM3TsfjgffLvdYrPZ4NWrV7lerpsUmkYLgOwscoMfJ7r8/uPxiPv7e+z3uxG4WVrYVAU+U0uUaO1C9lGVvFVE5BtVJPod15tzU56iBXCW5ro2LShSMEjHgNJV50uNQB2LzjWvt3nGNuxp15L2tQRCS3RS3oZzwxyWc96UF/N3DglzgGqVtfXk2/VCWclNa26oz2yNNZUFth/qydZx2b8VXOrzODcppdHTpyFkuxbzPROoAuZHhtp2bn5LtKEOW61Wo663ILkE1Pg3eUDzV89FtPgcPRxBn12qvUk+V/rqe6jX1YlgdTGvVR3K+2xEdKL3HKRnGs5rv7LPdV3j9vY21+5EGHlU6XACKvMfz/L8j2k/KbC0jJMAIPUnxADmocFs7T7NBGSU4uV9n+AGRVnXFX7x2St8/tkLrBqga59QVQ6x73F5scBf/vs/wbu3W/zu67fYbrb47tsHOO/hwRySHqlvsds+4Pp6gZcvb+Fd3g/O9kOVsWUAjpGCQ0sh2ERkjnX0wKT5MYqlxWiBEkNZKsh5Py1yeryovEoeuxACqrAYrS71MuqzlD7aH7vwdcxWCVG5MYexBFT0HaXGe+xcWUGqtNYwSQmE66YXPpN9wF+0CAAAIABJREFUVFBSemfpMxXg5OnStSo4bNhTgYe+S71SKaUx0d3S0wrIUtjOzpk23WWuoNner+/QnxyzesotD1tlr3SxoIeeSQ2dkVd5HWmyWOQyY+y/Kk71ggJAFXLoqev6UdFmmiTkU3R8TpNxDk3dDCZojqo4ALHPfXr79o0c2zffVap0trxQVdXo3bRA0MoDC5h0bvU9uimFvK0hxpRyWRQggwRV6BrK1Tm33ncFv3yOc7k49eXl5XASyHHsK8dneZQ8ot9Z/ip5/q2RodeXwJalJQBEJCQ3X7M6vrlifn4e9D3UA8wDjjHiw4cPWK/XYy5qNiByqTyVs6V1y7HSK18CnFYeW76xxnVKaQR0XA88vWcaM6+d7jkej+NuaKXxc03lB/ujkQNNmWFOrUYnuG5LwAqYCsmf6w/XndY41nkmbZXWvObECYOpJJQCRZUvtqmjxfKP0pqfK28BuXJNwjxfntiJ/3Pkw80cIiUv+unc/hGHwn8IGAPmFhfvyzX98tFmmnvhfT4iihZd13V49eoVPv30U/gqb/DxLiH1R6DP4dy6WuPTV9dYNg2+ef0GD5sNurZDe2yR+ojgElwdsby7wK/+5Bd4cXuBY7sZNveUvQGlMbBRCGouR9u2Y1iNOUwcM8NeFCx8VxIPJ5nbblAhk1Ah6EKw1xDI2jIl/NzuoMvCZQorlMLGnGO1zqyyVtCswkM9OHqMHgGSDf/pIig1GzYrASNdLHZzh86z9lOFOpsK/HOeUvWe2b81FMa+27GV/p4AzmnYl4Kl76edpyqUVFHzO/bDrtNzytIKO6Vridb2JzfWqABXwarA2865BYO8znphqcC32y2qqpod+Zl5au5x5fxrf2KMeHh4xP39h3F9wDH0NoX0xxqgILjv4eHgXa4usRv60PW5QsXUh1MPviojygVN7bAgwc5vCVioEaBRAeU95uVy3dnNAKSx5gWWcvP4N5U0c7w471qpQKshWI8Uf9oxW6OB/dU6nFZJloCV5XEdQ4xxSFM8NQiBeZ3BEAJcKgM4zrPyqpWv5FPvp2oQMUYsmiVSmnb4l0oL8VkqI3XdWZCgTWlAx4KCV84JIx/US6cyLudWUi7t9/vxjOrSuy0AUr5RYEkHBsEk0114T9d14yk66/X65F2kpY0E2uZcdmjY02zUQcH1udvt4NyU6qH52UoXjUgoX6iRr30lvbUUnvXy2+tJ+76PSJjX1eT66Pt+NOC6tsN+tx8jCaqzzgHL0t8/tv3BgaUi+5POubkSVU+RDRtXdYXFgqcjAN4N3g7ncDgeUdcO+fxTh9hHtG2Hw2ELuBbLZY2u79G1OzS1g3cLXK0bXP/Fr3CMLbq2R3tM6LuERd3AuYjFwqFpgL7fwLsWPXc+D00tRAUi/FsXDpmfpQo050FPq+BC0tp8/Hy33w80mGqelcCBLky+CzgNV1GA6LnIdoONzl2+ftoNXFKAvIdCQBWDeo0AjMJAi1pr4VoqiLqux9qbaiGWQI0KJi4qerC0P7yPdLECmvOiQkV5Ut+rtfqU50vgivyhz+azdP61WUWl4zuJAKR0Ili0v9aqVoWu86feLOsp0rqH1lNqQQ7nXMvY6Dj4DvUCKA3tuuK86HjZ6GnQndZKI/LsZDT1CIMS56Y2BepKi5QSLi5yIfQQpjns+7wjGMCwgSPJu4Y8y+FfSg5HFk1OXY6yiLKy3hb9730up0YaKL1saokN+bE/yh8MyzP0pmfWKw+qotZUFK5Zenh0rkhznW8FgOTdGOPo/VJeU0NDQ4/KgwDGPmvN28PhMAJ8lcOcW/VsWf5Ruk7Gw8CL3nFqZzS1xlHXdcjHxk9rlPUq7cY2XqMbkj799NPR8TCmLyUPwJ+8V1NGJvk8eak4drvmLC01bYj8oMCd9NZDM9TQV6Msg5XMJ1dXV6Pe45pUntUIVQkb6HPVoLJylkdd2mZBtnrpzjWOa7/fjxUGbIoG58rKJ/1JXUJes9eoY0hzZa1hq2tBdYoF3fl43nxKkKUBjdJxn0V06GM/0tU6XWZyx+iOyRkyLocf3H7SUPgpCsa4eO11tEzGBeDN+dkYwkxpUtR5B5VH3Szwd3//D/j2299huarx53/2azQLSZB3PbxvkVILHyJWTYXlokYdlkgpwqFHjHt03Q7OZU9nSrleVAmcAPOFy4VDq5weSmXuktdPvXZkPrXi1TLiO3kff+/7nIuqi5iKls+3Gxws7VXw8D+/UzChzF4SDvp3qdyDDXdRuLF4KwGJLUSr+ZqqvCzA0e8UKKvHQcdZ6jf/5vtpiatXl0JBx6IeKPWk6VwxRM1xWCVqhYkqlFI4RedP2zlhyv7rPbpJgopGN48oH1hga/tQAowfa8qTFhDZdyiQUYVjr+OzeD3fE9u82UDpwOsIXIA8T6vVBbJnYBLoznl0/RQViDEheAxFm49wGHatIqGuA6pQjd4Dli6jciF/WM+KGm7a7HieM2YUuClf2fV/zitx7vOu62aGoSp+8pEaqapYeQ8LXBMQ2dNxLI/xXhaWJn9dXl7OjB5db5Z/OM8WwPO7sbahd0jOjXFeHSdprsbTcbdHNeSc07A/17iW+Sw90Yugo67r4dji03tTSpJWMckPykyNsNixl35X2aSgU2Wp6hPyPGUdv7dGKqNPqtc4rypzOOYSnWz7GJ9aY/yH3s/1pzpBgSINGKWLyng+w8ps29q2HSstkA6Hw2FMSaPn/dz9OqfPrXs+i78751A1NVKc8JXl6Z+q/bzAUsIM9jolXAhhVvcpfz5/Ztd18C6Dps3TAd99+4APHw5Y7BK2XzjUzQopATENCbm+Q993qKsaLkU474Y8zojLiwVy7mc+AjJnMQwWy5mx6Ge0OJlrwtCSZVj+H0NoImSUDgoqLXhSQMn36u459RRq2Isg126KUUAxyzUZgDWvOTunAtqsl4Gfe+9Hb0iJsQkquTAoKHkd+07L0faJTUOrBKsU4BryU4NAwZuOra7r0evMHZHnwjwloMr/CgjVI1MC8RagEWCrYvwh7ZzgsKDSzpUVnurFUI9U6X2k/48VWtbToDykz7KAgN5X22cFwbrevAdSmkdIdK1M1vlEmxjTWGS+PR7h/Px0H6TJ804Q6l0u0RVChapmCC+/U8sLqVxQ2p/jb0snCxgVJKvs4XP0RBn9f45PbFNQT3ABzM875zpTEKI8ppGc5XI5RhdoPOo8sHE+eUoQ15PWTyV9LJAtgdvJKJhCgwoW4oArueHBrjmNsjVNAwgIW6/XMyNBaafzqnPEndcTcKxRV82JUWfXFuWkBWg27GqNbh2PGjBq0Cj9lV5Kp4AA7x3oy+I839zcAMAYPVP5pzL0nJF6DlixKd/+a4ElDZIY46hjrDy0xkpp3XI859YTZdV2u8XFxcWol1QW6EbDUv+5IS47Jzyy+DnlM8pq3c+RkMYUPCtnf6r2kwJL23E3RRhOristPudkUbpB4KS8eafve/gqHyl3/7hDn2o0zS28D9huHK6uVmgWAanfDOAyomo8+u6Iyi/x5rvv8bf/z9/j5ctX+PNff4W6BoKv4JFrNXoM1ivmjGsXPIVs3+dyA9vtduYxIFgjmGSehrqsNVQzKjw3eXLZyCi0pggoGTqmgKH1q5uDzoECXs//E4CZ74xn/3RereWvC5jgkGCOO8n1OfpTvbcarlNFpV4zK5hUQaSUziZ8l0CytTr5c7FY4NWrV2iaZiygqx4mtVo1ZKXhOAVkDBHx+ZqfyXlXsEtgyvf9UEHwsetUGFovBflJS8OoN7bUSAvS+Jx3tdTUo63K04Zs1CBQQMnvOC72k/zHDW3H4x5wCcvlYvTKHo/H2c7r6fSOvD7rusJyfTmmCsTUISGv4apu4LzmpXUIgxfOOyCEFmkE5QEhTAX2adTo+lYgVAI0bBZglubWGisKRuz7Sl6j5+ZK5RFBtV3PnBN6e3RuCDh0c4auJ91QqHysR+SRxzgerrNz9FRgVJJZ/N/1fd7dH+ZeT/UqaT4cPMbwYYxxPDXqOfqpjtNcOOulVnmk60pBTil6omum5Jiw3yngJP0UwOu75sCqQh87OIdZJEnlmY2U6TieM1RtK8lm/fyH3m8/Kxl2umZ0A6feo33g58/1paoq7Pf72cZa0oY8YdOH7P16RjrLPJXQlOrRruuQosPjwwMeHx/HlLsf46T4fdvPvivcouzStSklICXwrHAgZW8BHHwIACv7u1yh//vv77HbdkipwmK5wutv3+Fxs8Xd3SVe3F1gsaqRXBo8lkscdxGvX7/Bu3f3+e82DrUx8y5x53L+goZF2C+1gCnYmLdIgHd5eTkuNnoD2VSQEmjq5+Nidw4Rc8ubgIXAUi03AsmqqrBarU48k+qxABzdx8Nn0/++j/mkAJ+B/WxOcJq7Y2liQTIVfMkzp/3n9fRcat6Uczk3k1abvV9DSgpIFIxqeN0CYysUOAdc7DQAbIie93I+SB8KaCu8VTHbXDm9zjmHZrHIG7jEmKiqCpOPANNJVj/QStfrrCXOubOKV5XBOWF0DuD9kKYKSYG65XudawpZFdA6Po6F85Sf41HVflrfPucQA3mj3HK5wm63nx0/Bzi8f/8BKQGLxRKr9RohZH749vvvsdsfsNvs8eL2Fr/5zV/g//qbv8E//9M/4n/+n/5HXF5eYn84IA6Rj9VqNXooOGbNTdb/pZItwLRpDCjvKmXjmtN0FKX1x8Dkc4pYcyw1hMf+bbfbEQQqj1PhaZ85Hq4zm/9pdYLmTWpuqPIp+cRGF6zzYg6SpvH0QwmXqQZ6QuxzPueiaeAwADnkmukWaFiDSL/TUKRuUpnpCl82yvhcyo9MyyGvvO9QD06E47EVWZ09W8yVV1rwmco7E9DK+cNZDw7pBoPRBUzeXK0F3HXM22T/aRzOc6/tHoASn/3Qpl7C54yxkoykfNf1BJw6IvidDZVbvVEyrtiYC8wjUjV1go6Tw+Ewy3G2fdX9ELnPSWDlwNMxoYsdvPO4uFhn59WhRd/5k/SEc97RP1T7WUPhcIDzHk5CNbxOGa3vezifd1ly7lyilTehfh8qbDYf8OH9W1ysrvHixR26vsXDwz0+3D/h/ul73D/d4PbFDS6vV2iqNdBf4v7DA95/aAG/RIJHch5ddEgIcJ51MHN/lYlUUJIx6UIngKnrGsvlclQQKuS4uEogS71HI/hM82O2qCg1DERQ2TTNCCgpJE/on4B8DFgG6FVoUFUhfzZ4KJ1zgOdJBFPuow0bqjBXT6lar8A8TKzAkwqKpVW4SAkeyfgaMrChG6UdaW+T0HmNCrQS4ON8aZhOlRA3UVE5TAJ1eq4qt3x2dI2Li4vxdBP1ZAOTsrbeTh9CLswcXF4zziGErKzbrkNKMYOilOASEMTyVsX1XFNLnf3mpq7VajUCE+bEaQ6XVdK8j7TjRhEreK2lTIBgm4LH5XIJYH7Oulr79Ijz9BjyoQKfPJceVWjmQNYNp5QE4HjcIvYJIdSDhzHA+YB3777Hn/7Jn+OzX3yRjVoPPD7e4/W33+Hdh3f459/+M169vMP/+tf/C/6P//1/w29/+1v8d//9X2F/3OLdh7dYrZZIPqFu6plHIq+vqYakNgXZnEsFzTp/6q3i9fybPFAyqEq/87nnjBLN3+J9WsKoZEhrU4DLNarRHMoyPt9u7GHo3K59lUUlAGnHx5/az9FwSdno9iEfh9gNcrQOAamLqEM+/cQh52QSGHI+aTyq8a25dBYIEYRPHv8px0+9avrMsb8+IaYe3ifElAFF3YRRP4xgxZ2uOwAjOCeP5XckwCUknvjGeQoAnENKHfo+OyA2T1ssVyt4H+F9hdhHxN5NtT1HfJ4dQSrX1aOp7WMA0ea6c+6V3qX7Skaq8oXqqJJxzeeoHqb8p+w5B4r5bNWN6rEPIYyluZS3LUZSBwoQxpMBbXqhcw4pJsQecC6grvPxp7rulE4jLdLcScR+IqXS1phn289aIP2cD8MyRf7JieJnGC20/HeHlHo0TYVPP7nBixdf4O7lS/Sxx5u3b/Hm7Tvs9nu8e/uAN9/fI1Qhn+2KJQ6HPd69/4CqcvjyV1/mxFp0eTfn4BNy0jdtzJVQAAFkj2DeSTo/W9eCMA0pcMzWEho9lmmejKu/a6ib79XFwb4rowIODrnweb5/OjmH58xmSzPfa8PRSgP+rSDpnDBno7AjUCNIY5kKfUZJ2VKwzMc0rwXI/9ZLonOiAtsKDgUlNt+G3hWlA8ejJaS897i7u5s9kwCcHlmdbxUi3jPPKxl5kdCnXLx7PI3KTaE4bSUBW15jGDcE6ClK/I5hS5sTrHNCBWHpb702HK8FpiXvnI10PDw84MOHD/jkk09GQKDC0Qp89YjxvRn4DNYilF8d7u/v8f79+4HPp9BqU9dYLVdo23wgQ9v22B22eHh4RNu1CD4gxYjv33yHd+/eDQC3Qd+3uLn5BG/evMF2t0Efe1QNz1I+LdVTmj/rYTo3p6OnTYC3bvpTo9cafcoHOicfU+xW+SsPKwjWpsCIa49gUdeiPtMCQk0fUNCs77cGFq+hzNzv9zPvkJUlGDgkH2qSze3gPOqmymst467ZhkKdB64n9kONfPWw6nzZtQPMc0P5k+POnqeIrk/wXvVH/r5p6vFnBmKn88k+zIzzkKsZ9D2NhclJoUZ95oOAq6sbsxapY7IOpU+t7yO8n589Xwr5kk+UH0g3lSkqw9Tw0HWjjXJHw8DPAViOUcern9PbXFUVttvtWPFEHSfnnsWmlUJUt58D2zYdKf88HescFPPvOWB+btyl5/w+7Wc/eedcOwVBFBpzgqjC8N7jxd0LXF8Di2aJPj6hrip8/tkLNHWFd+/vsXnaY7s7oN33aNMBu/1bAAlX1w1e3t3i08/uEKqUvaOIgEtwKeWEUMyZgh5K51hr84Cu68Z6m2RcC/Ao+NV6pUIuAU8A03m18gytK7ZcLkcrhx4l9QJQybIfKSV4F1A31ZjvqExsLaMY40nRWyoDBXR8p/WglJhSrUtriet3Spdzi0FBinXtW69F6TMrNNR7qXla9r2kCa+jR43WK8ObpOFutxvpzPxFALOwoNKdCgJ+3k/+rjth08CndqznaF+6RgW8zoMqf4Zuzr2Dgt+Gpkrvt9+VBDHHRhoyjERvhT6Hnm/rwSeYVEBbArZcB3MF1o8RgL/8y79EFRZ4eHiEDwEPTw94fHxA7HMO5nq9xnK1GHOYrq6uxmhGPu4ue3wdJgXxXJUG0qQU4i41lR2cHz09xc6tGm4W1KjRa5sq/JLSVePoHFjWa633SmVW6X6ORz3p+i7bJ2vA0wNOOVwyRtk3YL6JiLJaQ6J8D1NlOL62bceySuQpPbDAzofSPXdgbgQqAJ3NcdchO1/mvKKgbfTu9akIWNTw6LpuAJZxdryuGmx6n/cBdVXPvlNZNvJGIniejI6SkarzzOdo+aLSmlBZo3Nkm/Llx4w6Nh2D1gVWLKB4YLlcDmWAfliIX4HiuTWjzZZdK12vOpTzwv/cma5j+ynbHwWw1AkbLQt3KljVIiYoCd7D+Q6x2yIlB+8X8B64uV7h7u4Wh32P/f6I3f6Iru/gQosYW1ysV7i+XKNuEvruCO/SACzHjIUR8QOYAcPHx8exXMDFxcW4IUcXllqDbAomFRzT66U0aNsjun5e3gYYziheLMawt1UsasFpOCW/uz7pq9JcwakuKIIhejw0pGUFnzJ9iYH1dAINsfNvKkUuJF1ACh6Ox+PoadN3KbgnoFfPghXk/I40U0FllY0mX5Metm8cn1qx9h4Kbcv/oyHAULd8p0J09l88A3r9c02fp6DXgkyG/88BRu238sU5xaECj+uDO+5t/9ivtm2xWq1wfX099tF6e0oeOvUO6fvtu47HfBDD9fU1drvdUDKsR9Ms8f333+PLr9ZoVs1I5+vra9zdvcCvK49Qebj/wYHRlb/+679GVQUsl82wjgLg3Fh67Jy38IfMVamVPN7AtNEFmObVKjxr3OmcnPP6WENI+6iGWQkwq7GtuXYMnStYK92vIE8Vsa5RC5ytARNjxHK5HL2VJaPKjk11Dd9BuWMNYpUl+iyVR/q3lQ3OOcDT41dOO6H+yGV9ymARmNdEDCYtxY5r4gEAbhqPRsg4lml+XN7MZvjP8oVzjBLNHRHnAJiC1Ox1bWb3UE+wsf/UGSVgqfzFPpzj8xJo04iW8h5l/bt371BV2cg8B2ztO5TfP9a22+24mbLkzCmNgT9TmtacfvdTtz8aYKmbGrz3Q45l3nUGzC1s9cTFGLGoKvRdQnBAih26yKTyHRYLoFk43NwukZyHr8nkPaqQPaLO9UPsY/g/hCKjKE4CNf69XC6xWq1GgaXCgh5EFURqhVLI0Nqx3rfj8Zj7gMliIiOy/Am9SASlGvbTZ4cQRqasQg3vJyCmVrl6EdTbwQRj59xsx6YCWQVi/L2kHEqCX72UfJ8uHFWY6g213ic2FeIcP9+tgJ/X6tyx79ZrqeNl2F49Zwq01dum/Mo+qxeNfVJrnLQgXFQhwWR/pWPss5fdesnPATulhSo0/V3nlJ5Y8pu9n/weYzxzQsf8/Tqfth9sGvKkIiG91ZgCMBpK7APvuby8nNU9tP2zXh2Wo2J+2na7weXlJa6vr+EQ8oEJcSqQPq6RlOC8G5QM64F6/P3f/z3evXuLTz59Na5TphWQP8+tE6UN+eRciJnfAVNkhDXz1JhRhafP0ry/kqJl0zkjzytfKyA4t/b5k9drCoWut1Ljuyj7VG5aHtL1pzQkgLa1C0v3q4xQGvB5HCfnlPdoGSzKTH6v4Ivzpl5a7z2QPJR8ajir7MybMSeZps+2B0RUIaDEZhzj+A5w0+b85C7r1c50BZBOS63pe6cXnfbfAn82rZPKedT0IV0LmmLAFLVSfduS8XWOz1TW8zobkaNTg/rQ+6km63PPVNrYZ1qvrzY6W/jdc/nzSnuls4LxnwNc/uTlhix6zonBp0WALeHzJp186g7DR+pV0wmKfULwATHFYadsQkqHrJrdQGAPOB/Q9znHMCXumgRC5ZFSj9QPYbA6oOsigEkBpJTGMOjl5eXofQQmQa2gKI9hEmTqmaMwUPCjSrGua9RNg1CFmXXMd3KTid7D56SUxu8YnqcSzAzpZtasKiadK/bfez9uMuC1KhjJ8Oo1tYnmOq96HZuGwUhLKvjLy0sj0CbwVQpvAKe7bdlfDUlRMFgBoQC/7/sZqC95JBTIqRAmDVT5KkhVYafrwLlcOzXGnE+pNT3tmgGGTKY0977o+7VvJfor75QEoAIQbUpbS4MSWLR8oN5NqxjVe8pQ8vv379E0DW5vb2djsBuLuP622+24BpbL5dkUB75P67xW1QKbzQ5XV9f5pJ5W+ZUG6DAWB6SU00ZYCqRtIy4uLrBcLsedsxjkg1ZnIL+VIg762TnvhDWcVAZYY5VNDRDS2Z6VrHzEdVkCOGwEWHwX3x1CGL213BDHuVfPkR2TenOUv/T95BmCDu2/lSecV5W7doe+AmKdB3pXtaYsx1xaS5a3eK3lOwC4v7+H9x5XV1ejIwApwTk/W28KNkZAnjCU+5kfNsFUAX1/HyOQ5iF8W0Q/G7MReWPg1MfHx0e0bYvb29uZnqrr7MwpzRP73rYtlqslXMrpPbzOyib9qdU1zsl3nSOluRpMJVlm15jOiX5OoEiD0266VJ0XQsDd3d1sXHb+7fv0vYoBRlkh18YYcXt7O9NJpTWoTccBlkczXutzwN72+7n3PNd+5s07CcC5XMq5os0ofW5RFgELgD728NUgMFmCYTjGKANKP3gaErzLpxs454DYDxtkOsS+RVNXuX8R6LoeoZo8Nn3fzzboqNBSxlQrmPeqV0W9mToWWuIsC+CCLy4sAiQW1XXOjeFEVcralxEcxIjgw8xzMx79JP2h8OUC2u12SCmZkkUT46l7Xr2A2ufSImfT0kkMafAZTIa3gp9ChHMD5I0oy+USi8ViBArWeOFz2G+bh6aghvdTaequc2DuWbOtBKpVaJS+nwBBQM4tPlX0pYVeErg67zqvz73fzo3liXPhGyu4zwks0lsBpPUs8X2cW4J5RgjsRgitSMC5uri4wHa7neXEFQG88AfrXdJYqusal1eXw1yLzDHkDyEgprlXg/1Yry9RNznHbrPZYHOxGUGurm3bF+3nOU8lr7NjsoppkqWTEci54POBeci8xDt23nXN6/uB+dGh2+0Wu91uPEoTmHv+rPxUOaFAhTtvbQklfS/fSaDMfloaK0C04K9EX6UB5eI5QKrj4zMIBjWa4b3HZrNB0zS4vr4enSbZCzg32tTgHulv5Jo2na9sOMehvNbkKNGcz3GM8OjTPOyta34m7/seXTd/L/tJPXc8HrG6WA16MOe4Wi/tx0DSczLPepDtJtMSyFTZXpJVyicqS+3zyLu658Dyr9Kr1H8F4+oss/qe39t1Uuq7XbfOTeemA+cjCrZfpO9/EcDyXLNChQIECAjBn4QKCw/IhW19gEsOLlSoQ4OuHybLZS8QUkAIK8SYkGIPhwDvE5yr0SVOSPYAVaEaQ9FUcBcXFzNPi04CJ0LHQ4ZXL8JJyN+5cTMNBWKMET7kdABg7lXZ7XajcqUnlMWd9/v9KDgIUGmt5DDLZI1tt1us1+tZYWH2lfTXs32td0UXNu+n4qAisALWKj79XBvvDyHg8fFx9BaoJa7AUheB9WhrszmAWuZEFzoVl9KC1+s1dv7ZN33HDxEwSlvvPbyAuZLSNQ+gA228RsNTKmxoEfNdBPBWyKuwtvx9brw6nlKzxoV6cq2HidcA0zGC63U+opXhamB+hjWVps4Z51wFuD5bf2rx65QmT6dzTpS4CG0/bEhAgBMezgCixTfffDN4gYai/96PdeyYXlLy3ACY8SD/ttfwcws6NKxWeradn5KXWHlWwajOOZVqVVVjqk1KOeTP3Gx649br9Yl81/5yR4crAAAgAElEQVRag4Y8yuMBS2PX9aTgmGPh+uXv9AhSpmnBad6r64z8ySgR6aMRqOc2iqicLMkEAPjkk08Q43TqC3WVzos+x447P+e0trJ62ZzL0Z+mnoNxladT50/BCj3vKss5N31/anRQn416xzkk2S9hN9Sp3PkYwPxYOweYzsmokswm/+j6U/A4kspNIWaVQdZg/Fh/OQ8xxpmDSPWLgmF9f+n5J+skH4Q9S5krOehKdPrXtD8qYMmFm3dcHxFjQFVNZ2yXB+4QmiWOx4i26xH7iD526FMuHZT6XKYl50gBffeIlCIw1P8KAagrh5vrNarg83mxMYfej1I7TTe96ARpK4UTrdAjSFKBrQxFQdL3EU7AKEMyqjC5o1W/B6aTd7h7efTYGG8x+6cKjn3QflMYn1u4yqR8NsPO50rV6L32d6UDlTHHrGFPYMoP4ikqBGSl9xFIkdZVVZ3kLHIOqSAYVictSuFwBQDnABfbuc+VtjHlXL5UsFJPHzh/rhXa/M4KcDuXFow8B6BL/1W5qZHFpu/V0HepWTqrstYcy6qqRoHJKg2si9p1+QgzKlnrEVDgSo8o0y9yUecKdVUhwgPDiTtjWo1z+ehG7+FzQZpZlGC73eDt27d49ckrxJh5drW6wNXV1ahIFCywT5aeH+OlE1YQRaRgsOSxVTBJ2cbPbU5X6R3ABAC5JlW5khf0Gh2jXlfiE8pYBXbAqYdVFS/lHt+t71eet/Qo8bDSXQ1r1VPPAQdLb11L/DulNObDHo/HAQQ3qMIpXXR95kjc9GyltwJg0nm/3yP2mNHmOVlCOqthq2HavKb6bNOKnOC8kE5jdQ+UK3x8DHiN3UqngFfni38/90z7bvu5nRsbfdM8b80N1p+q/60xa5uVRc/R4pxh+YOay/fv9/ui59t0Kjsq/gDtjwJYAvOJz2GpFovF/BgvthlhksNm0+Lrf3mL+8dHdF3E4XjM3kpfIcVc7LxPCYiAhwcQkVIHpB4JRyxqj//wH/4bNM0VQsinBfAkAXoE1QrlBJEhbWhcGZNj896fAD07bo7Ne4+u79F30+YFKke1OtVCV8FLwGlD4RiSvReLxdgX642zAlbDY6qwdDFoeJKKQPMc1dNVWmwECdpXCknuTFYgbBclQy96/zmlpUdo6rUWhOnvduOKNlVS9j79W+fa3m89T1lxzM/LPgsshyrE1qDR9/I7fZ6GxRTwlUKbbDaU7tzcY1yiz6ynBtgA88LypbCbAkCeYMG+HI/HMf+37/vxe/Kilq06x78KOHRDzej5DhWc90gxp/K4ISzuvJvqGoK0T/C+xm6Xj/9cLhaoqmljwf39Pa6urkZjS8snKX+okVmaT50DTWvR+bZpOvy+9C5do5xTXaf2ObyHO3Z3ux2AbCATyHBsariStvxdjQudj5TSmI9aAn+WDpxjyuoYIx4eHnA8HnF7ezsauX3fjyVh+GwFxeQBAkkaJfv9fvSYc17odS5FYCwwtXLPAtbdbof9fo+XL18CKSCluaFpvYV9P1RDcfM5pRzldXzvYrFAZY4ULRvfdJhMc0RnBeUT9zuEEITvJ+BMeaBevlDNQ8iqU3TulTa2lT4vycYSaLJyV/lI50jXgtKPurskXzXMTDrYd54zoCn7VFbZ9am0te8uyYPTsc83lar8P6FpSmdrjf/Y9rMCSwc3HZZWsMg5cIZYuGmFgh7AyUQiAQ8PT/jm9ffYbPdYrdaAq1FXFZrFAj44RDckJDvAdXHIy+zQHvc4tj1WywbLVS5TlGKPEHwGppjXsNI+nghlYFBAPQcIz1qEcVCabqBCjmDk53CD0eAR6boOXduhj3E8wYCLUT1RykRt2yEl7lStEXwN7yt4l4ue55N13FjCiSejaG4j6UwlrBsNKAA1AdgqKd7L51jP3hTSwQiEmK9W19zJ54aFkD1GzqVhbDmhnWPMvJPvyAvZ4/LyGiklbDZPAID1+nJiEGEWFcIKhgm0VJhwPAxbsikY57OsQCmFD89ZsBpiAwD0EfABwfmpnFBKQ9FmARADb2nju61XhmBDQboFC8pjKvT12aXPSsrfNipxNVKsx0n7pIKfffHejyf7sAyR3sc8ZZ2P/X4/Mw5s/zhubvYJIQAO2B32aGOP2mfae+/RR947nlMF5x1imocoGWbNx+v1SH3Ese3w5s0bLJfLMd/wnOdA89CUD21TsKbzqt41nR/tI99j54L3W2VojWVgXoJNjUy9Tvuva83yl/5N4KanKVEm6XOtIUoFqsYmI2B6JCvTinSNWn5TmUh5qZshzxl6VuHP5OVQ0HpYLVlG+wp5MynySSk+l7xLKSHFXK7HeY/Ux5ySERMSethX8730SqrBuF5fwPuAvovoYw/nAvIJO7MnAOBG0vx85wKqijTKXJ9irosJ5+ADECPlQgJcQjsA7uWyyTosRsR46iUugUqOo0TTc3LonKGhc2tlVGlu9Fr1AOs6tNFHC4itg0efpTjGFkfnszU69hw99HkaLVMenmg0bQRjH89FIuzzx5+/h6P0ZzvSceygmRASxIYXX7x4ARZHV0JYazAvBmC5qnBoHdr2AOdrrC5WeHH3Ar/4xR18neBCh64/YlnR+9ijb1sk9LhYLBGCA9AjezNziYbk5ju5VeiqFRGRS470A6j0w3mp4+i9yWXI3YbzHpXLte4Ow2acw+Ews/S52YdAhkB3pCmAKrCAtUfwNeo6W6hABh5pOGNdmd0qHF0Q6j3jeylcS5aSHleonhILGryvBuEWEcZ6bQ6AR+x7IOWzaYMfiJTSWNMtxYQQPPou4ng8DEC3HgVg3nAVUVcLeB+QImnuxpmIqZ9tLKCy0TQCzi/DqrQkgSlxXwUa50YV6rlQmSr1kiJWWrkBMMauQxxAk4vKixjAdhpzcalUVcCoN9nm0xLIqrDXOdN8KArEkYeFd9QgJA+ca9ZAUkvaGk70qLOUh9aA5UYe9o2FqQkkuH4Y6lajQeeAa/rp6Snv4u46HNoD7h8f8aUPcMEjuUEYxx4eDqnPCrM9toCPcBiMgoFWXduhqWs0VYXKO1TOA8GP80Pa6/xYvuA65XpUecm5IpBSr68qP32mXbdqBOrckDdKG73Uq8d5VhBGAK8g1QI17YPleT6bijfGaTc6+VsrbJS8euTBm5ubcZzqGbaggQY2+VAjT3yf7srVzUMlWahjkU/gkCty5L8GEFcBKTosFxdo6hX62CP1HarKw3uHLnZIKcNRH4C+7dH2x2GsGezZCEPJYImxR9e1Ixjt+jg4PU49lm2bgOQFuA5zlDy6LsG5CjECcBEYzxTnWgISYj5mEoBzCS6wmkZTpJeue/u5BZBslN/UTeRH9XDrs8/NkfX+6ZxrZIxzrd5txQSU/+Qv7k9gLWOVZfSe53mJJ7/zufxdry+NIYSAp6cn9H0/q/U73efGmtu6NpVG/OnkuZQBNKR/rCfzjyoUrkI3prwggNMEZgAirDxevnyBmALev7vHw9Me+12H42GLd28igBbryxVevLzC9eUl+nYDYDgnuAlYLJaDwj4tXpxwas2oJctE6RLRrYJXhaA/aV0zL4yClaE+CjxVRJrrGWNE2+VzYpsmjAykC9F6z9Qa4WeqiPmdKhd6DLiYdWwla9KC1/y3R1UFBBEm3nvEPheTTinheMjeHgoJ5/I92fuQUFX1zAqb+jGBflVYMqNwzqPr2tmOcc2xpMAirUk3W7/TjpXjU2ClCswaJzoHmq8zAz2YvHc+v2wOvnDqVSTw03cTuPBZ9LyooNRnKDDmu84JZ23W+i99r3nSyhf2PqWz9UgBUwFw8iMFseZT8rncxMHr1FvAd9zf30/nm3uH7XaLp6cNfvfN7+B9jeMx4nho8y7vOmC1WiDGDn2K8KHC4bBDHGRBezyg77t8Ak9K6Lvc78PhgKurqzF0f27zBzD3iHAMpbWmMkYVpXoxbeTAejTU60c62zkkH2h/SVOr5J8zKtgUdGq/9Hu73rLnbY37+3usVissFotZZQzKErvWLMjVeedzbTkZ8o+uAx0bIzjnQpynA3aYV3igDOA7Bhk8RL5YmscaBM6p3pvrFg3XlsAbxzN95050HgCkqKASoFHu3HysCQT6c1m3Xl/M+qR6rzTPmuL1XB1Iq8/01Bu+m2BKZdE5uWTDy+Qfmy+vnl+V5ed0Hq+nPAIwWx9qzJ0aINN4LV4oXUM5qHTw3o+e+qZpsHnaIKU0ng7I3fp23f+h2x8VsOTktYMnMY97Ehzq5ZhATo2mXuDzX3yCly/v8PS0x4cPT3j3/gFPT1t8/S//jFAFvPzwEi9f3eLVqzWqKp/x23W5bE/lg3Uqjn3iTxVwVoBaJagK3wpyfs/vOF6CSi40emgYjiaz6L1cXN7VIyNr7qf26ZxlqF4Fjk8tezK5tRh1PtSLbL0rM8AAB++n3dy8X3eS6hgJqgmE6Lna7/c4Ho+4vLwcvRqqPIoK22W7i9dpWE7Hy3lgDqoNo31MWFklpnRSMGwtZuWLEl+psuV7qODYLE/yHlVGdu6tkKMA5Hg4HycpKOY5+vNcKwFofUaJLrqGaEUTNG02G7RtO+a/KcjRdcfPtWyUgrb1ej2uu2bRYLvd4T/9p/8bv/3tP6Kul/C+weX6Cl9++UsAES9fvsDd3QtcXl3CVzVef/M1vnnzBofDAfcf3uOzzz6ZNpL0U4FsTe2xQE2bblDieG1uttLH0l49zqrkT8HF6Q5t6znhtfosvlvXkoKdUqPSVx7mc5TPlNd1LDTil8vleI+OzY7fgkwbZSI/WjBgnRgEA9YTaMHFs20KmhTbCI59rghxPLZFOql+4Tq181F8fWFuzl2f19g89Uz7oYPS9UwZStBX6p99t03L4UbZ55rKNUsjIMvvzWYz8zKX5snqKu2D6gNruFhQf46OatCr96/s9BCqGmPqOfDJUny3t7ezPqizwvlcjrBpmvEEPRup+inaHwWwtKCg73sk5FxH504VsSqelCIOxx2q0CAEh9vbBW5frPHJZy/w9u173D88Yrs94u3bt7i/f4/2+BJX12tcXV0OTByRN9gZIjPvsdBoIUzCazqRw4btOTbrXSITd103HiWnVjB/0qMGYAYcCSq7rsNquURdNyPgVWtrotMcvJQWlAovVUD7/X48q5kK8RwA5aK3iy4/e+7B00WkC885h91uN1rhAEYri5ZpSvPzb1WA0SNkmAz7wwHeY5aHRHrpGd60+iw44/NVaalwtXNPulirUwXVRJtTUFUClnx2CcSWPFPqCVCvH5vtm1rKOt/ncnO03zqOktCyYJvvUVpZwV3y/CrY4pneLMRNQ4ygrARSda7oCTscDthut6PB8urVK6zX1+h7wKEaywh98cXn+NWvvsKXv/wcoQq4f3zCer3Ger3G+/fv8ebNG1SBp2U5YFDQLPTOzSO6BmyzBoPyuTVGuO6sZ0XB1omB59zMALWGkPK05UE1Jvkc9uc5T8y5z0gHVaK6trXfDDFaI9saTed+181qJWCsXlIFR+pdLsnU37fZZyIh5+zGhFyxJMxKrFnjyxpeYzTD0LqkeyxtlF4lXXt6HXfrd7P32lQByg+rDzQiwr+Bct1WXSc6VgWmBFNal9mO61zTflF3WCCsz+H6sNEgfRb16RjVlPn5GLBTmlE/2VYyCIFJbgMYNjNWCL4eK7uQRj/Y2/57tj8KYAlMRB4VofPwfs5IbN5PNeEyEwEhJHR9zkmpArBeeyyXr/Dqk1vs9y2+ef0dtrsdvv7dv+Bun/M3L1ZLNE3OjTrFlTkx3yrvlBK22y0AjEc6Zlw69x5YwWOFAkMw3IhArxjHT8tPF46Gw+f5HhhpZwWfKlOr2EtCSRmZ/WzbFhcXF+P7+Tlz29QDZAGsCh0HN1rDqly1hqDu6lXlT5rs9/uxjAyfo+HP88CGJydVM+8LhaH3fgwVPDw8jLX3mIO13+/HHD4LDAh01Cuk9CiFUEoKQA0C9Y6q0VUCrCXLltfrs9U7owDL8jf/1jSB50Iy+vtzynbGC6a/9jlWmGo/OC/kAQIRC1KppJ7ruxppKSVsNlt88/obVENKyXZ7wGq1RFU12O322G63+Prrr/H27fc4dkds9wfstxtsNhu8efP9CB6vrq7Q9xGVmzZ/7XY7bLdb3NzczIwa26yBp/Q5r+gnmpZywvhc/Zu/WxlB3tN5I52puBS06yEF9CTZtlwuR68x13fJiLJzw+9JKzVArfLXNaZyVp/H9ct+Kz35fI5B1xzvV7n2Y4BladZ0TeYx5GL8+We5LIzOM/PALb1tv7Tf+l1pXfRdD+f8rDQR3zvvyKSvVSfFGMdULJs/zb5YY4H9ey5v1fKjc258jxpCIQS8fPnyxPlToqP2h3xDPlU8QuBm+a/0TMtz2l977bl+KQ0+tt51XeraojczpanEIUuwPQey/1DtDw4sOcFnXdByDTA/r5mtrmtsd0/Z4pdQOJ8PTNZejBF1qICYywfFBPR9zGeNp4jVxRLLVUC9+AT7/R5v3uSNGcfjEZfrXB4j9hF+2IAD5PqBOQ9zXrGei0XDbX3f43A8oBoKwqq1QybjvWoxcwysnUfgyDyZUuFV/ucCJo3rusJyuRzpp7u42Xeb1K9CU5PhCdK0bufd3d04dj4PyJ7Mw+GATz/9FABGZlYBrTSI/z977xZrW1LVjf+q5pzrti/n0qdPN9AfyIEgyqWNQrwFMRpM8BaDAcWQGIk+fOCDJiQ++GB8NL6QiASJaPTBaCRpEwWJLyLEK8YoRsMfofkD0tKn+/Q5ffZlXeacNb6HqlFzzDFrrr129z50IzXSu8/ea81Z9xrjNy41ilo4h55LkNeBtj7K76WQ1O5eGWcnBbIcCxaEBwcHMGZoWWGgyRZgTvDL89wlzu5rkNLFoRP/cj/kWpBCmd3/8kCU1OYZLPHfslxtzVoul3Gu+GQhvy/fkQBcn/DXJPtIRFGIyXHjMZFjJNeSBsHSmi6fletSCu3UD4+XzC3I4yDd3XrPSCVJCjFer9PpFKvVKvCDFiDClStX8eCDc8ymeyiKKuxf74IitChKrwQuFnuYz+e4cuUy1qsV7j59x1u5gmtPuqB4DjimU+4Tngt52Ig/k7xHK5k8fhqc670g96MUghKMyfe190QrMjx+vJ95Py4Wiwg0+CpHPlDF+0qWKRUA5kHMf+ShQb3ueKw0KJahOlLZkxk+eP3J8rQFStajFb6xfaPBe7evu7bxdynLFY8ZP8PyIAXCpVKr26vbpEMqOIZ/uFe8DGSS3hm5RrzRxaBtvUyQ8eXymtWjo6PYH7mmpdVPyye5TlPGDLlmZF+5fdLKqxVSuWfYsDOdTlGWPicux9NrT4lcL1yXBJxSQZBGATZGaA8Tp6viPrFVk72YHPIhjQMp5UnKTf6deYSXzyss5gdx/fOcJxUj0zc0xXXu3LkPhn+Nr3REPITgf01rfM45cEoayUx4Iw2fbwHjg58N+XQ1rmlgjEVb1zDWYn9vjoP9PSwWi+Aym8Bab+2yMCDD7fE/BDMQjlw/M3Y+LX1ycopq0uU00wHtKUsCCwle8Axm+Hu5kKUVUy6+yWSC2WyGy5euAkB0EbM7VzKFMYbH5UmhIl2ukqHJNjHzXywW4/OtgJ4fw36MpnT3sACQ70mBIS0RUtDKuBzupwzkNsb4pOPOwJjOAszzwL8zg5BWUFnf2JplUMrARwK/bUKBP5NWKzleZ+0THh+2sGgBo8tJKXoS0G2zeKf6lALy2nIs69VgSZcrP5dB/VyWdCkxONbAtKoqLJfLnjuIY5W19Uq2Sc7D4eElFOUEL37xi3F4eBmrVYOyKOFC+peytKiqEra0sGUFartDhm1T49/+9V/83i76CsALXvACHB4exnlKAbWUQs6KCPdP8sHUSf0UsTAZe3bsb6lQcVt5T2reKAUdrycWnPo5bZHnOnkNnp6exutZt1kHU8qH5ntjfZNrKQXE5dhx33XfUu1KgfS2cXENszVtrL5UHztZc4KrV6/23Jl6n6XKTbVTe3h8/4bW5uEzAMihCJkO1ut1PGwpx4SVBJ25QCo3PD/SrS2/AxAPvLHMlYdVuG/b1r7sv1zXvFaZxzDQkwrrWPlS8Zb94LhSuddS64TlBMsaNjTw2pKgUs/n2NqRBh1eG0VRxtvKZEaZkUHa/v056GuWbih+NvKdtMrUde1TrAQgsm3DAIAB+aujyADOorQTmMkETdNGFN7WDs55bXA2m4VBbMGRlEQUrm5z4BRfKWDJC1DmNDs4OEBRdhYjdm9LJisXDGvwAOIpbmk1k8KCBSgvFE5hwKCO7y43xsRbHKTbIY5RYgz1ApWbT3/Of3O7pTtZbtYI5JTro9McOyYtgUYKvMk1IX+kAGaBJwERA3V+tixLf0WmIazXy5hnkC1D0m0iGUW3Oc8+6bqLkJBKgwZbKWah5zG1n5jhSktNSrCmhLj8XJavx5rHV1ol5ZjL/mmGK7+Tdcl5lECVx13GvbFQ0qcf5TqQ8y+tWDr2SgNnmcJoMpmgqErs7+9huV7j7t2nsVj4A2INsVvZh3MANYwzMI0D0Gn0xhhMpzMf2lJVqF3XZnkzlHMupgGR7eHfpWIorfqsBEmwlwJWmqTFSMYM6niylOuQebKcV65DWngk+JdKMK9RbSnlsuUakVZnXhNynMbWm+bT0uothbx+VwJcqdimiL9LHaTS4yWVBud8iEVVVfHAYdpFS0mfuQbxcq3IvbqNUnMq5z4q8GbI69L8x/ROZktFU54X4BQ4bDyQ5UheK7ORaD61Wq1wcnKC/f396JmTcyzLTY2DVAw039MZMuTv20jOg2wDyywJCvVc8VyyUYPlvryVj41TqZhT3S8m6THlQ0x1XQPkr0be39+PPC8JxndUdHahrzmw5M/15pCL1zPAYcD5WHnGAE3ToihKzKcHOD2pcev2HbTOf1lVJeZ7c0xnMzhaoyh8HIvPLeZ8ltfYXs6dSEjtch1IX1UVJrPuwACDGs3cJZCQDL4oimj2ZjO1PiEtXXkAomuB7+MGCJtNd9ON1Jr0RpWfadO9tEbINsv3mfkul0sY40+cpbRB+XfcyCHlD88lj4XWdrkOWbcsU46fjPfSAIpBo2+3gUMnGHg82aWqrXXSNaP7I4k/S10lt424fSlAzd/rzT9Wv4wDkq56XZ5mRLpsCdLkevHj1897yWPHFnkNELS1W7ZBjrO20KUYMz+rhQ0nSee5Y4ZqrY1XPc5msxjDzJZLzdy5L/zZJoDQk5NTP77W38ZlbYGisOHHgAyBDGAFnyiLAnt7ixgL3GzWODk5ieuJY5JlHJRUZCTQlj8yhlQLMs1Pt61TCQDkdxIMyjkZU/h4Tci51AcQgW7/pOKSU65l2Ve+WYnj3lKk+5MCUPpzzSf0GI3VowHKGA3ARutDH5xzcf0l6zPpWEwez6qq4glgHS6h69dtH+sTP79Nvso1EcchyFwAMacskT9/wPvOORdT5qWUVeZXKT4g5Q0rhTLfsOxnEiQlxkPvEe635DdSGeE2pAwL0jvJe4dBtd7D3B+5L6Ts5TMDbL3kfT5mSU+tXa5DjgPvMT4jIN9PjdlZysl56J4BS0rkVyAATk2uFmBAmCwMn/PPyh9PTdtiWk0AVPif/3kKj33lKTx56whNDdiiwGRaYf9ggcmswP4Vg+m0QlWV2NubwZpgsyQKt5gQjAX87QRDcMUCln8nIrRKIBNRNKvzaWYJVCQoknER1nbXPvKmi5pv62K5VVmhKAtxk1EXZyaZPo8dj68UIBJMSUDBffJ9sWIMDPyNDBT/9mPCm6A/TkRpy6dz3Qbm+rVAlW3SMZXaVc0kgZi2BnjG4e+slaCTy+d35Wbm07vS1Z5iXhqIbwOWmkGxtUcDNmN8QvseQ7c26apw5BPOx3kH0DZNTF0CAMb6eYxXPwLxRh/X+owGhe3fiMJjmToskWJeEqzrMZBMXH8m548/lwdyJGhmIcNzqAElCwjeo2zl5M9TIEICWSKCsRbTyQRlUaAsfUzghhyqokDT8Jrx4JIMAaaANd04lWWJvf193L17N1rNZRJ+ud+lIJF8RipZUoBwX7TSk1IeNcmwG7m3pDKpQaT+W8+/dL3xD7sqZV/kbUiSj2qgIevgOD1p6dQk+y0VUa2UynXT1QMUhVzv3UHQflUaGHg+6GNGS+hm8fucm5JzRU6nEwAmZi7wc9eV3708HmrD+1MCNV3vOMAayk3+nNvBPGLwploHzjnA+Dlho4j8Xt56JOdXzrnc43IetYufQSobMHjNS74r183YOvHrz98o5MdRygsD50xcy1qxGuP73Cf+ng0l/B7vCalEyfYaY2LIFsdiS88C7xvZBtkuTTw+0qvgc+t264fPbiRpCzg/L10YsHRB26LwO8F4KZcw/OnBkRptxzx5cclTi0BhKzgiuNYLgbKcwBGhNhMcH9f4/x79Ck5PWjhMUM0rlKU/NHLn+C7c0Qa42WJS+usCJ9MSh5cWuH7/NRweLkAAirKEc008wKMZodRo4oYyiEJC3kXLi0K7ZXTMpASenZvFXxrnnwEMHIx1sMagKMq4MZzrQBq3VacrAYauSaAvPBgAMyAGDEABhBAzDb8hrbWYTQsQHMj5OI6maVHXbbie0cLaMoYYeMuwhTEFJOfi8eQAfdlGyaxkvyTgZi0WQI9BSaDcnVj3OTQ3G6+5ScuV1v4lkJLzJ4GotK5qBUgCZWYo/CMt1tq60wMR4XIAWFYeKGYp6O8jG920xhi05EDWX/bUkAMCWIpz7zUpOP9CuFnG/+1cC0MOcD60RIOVFLiU86XXlRQo3Gd2A+v1J/svmTGTVLZSCgfQz0EqFRcZQ8x7g99h5s/WQwBYzBag9klsVmuslysYU4FMd90jAvC3hQE5A2sRQTwfwAOA1rVo2hpN6MsTTzyBBx54IAIyPsyj51S2VwohOd7y9xSwlKAtggH0LXy8RlmoSfEclb8AACAASURBVOCv51UqXdp6Jedazq/cj1L4s/DlfZKyALIFR7ZZk6xbzqkxJt4GxjzCJ/hmII3Aiyx8U8n/R4JnUqccO3L+fTIgOBS29KDUGDAaI6+tRVWf/yby+202n6BtHcrKwlENYwEYi8Iyj3X+ykR417ncI9w//rtb+142tOGwmbUWtii9kQQEF27qsgawhfVnEKRBpg5zav0Vj57Ppy3fcj3ENRKuSJNubE5LJ4Gl3MdSwZDzyyTXH/MNCa6M6Z9bkPuY15qWCW3boG35BjsLY8KhSO4fGRhLsNRZKKWFXQNXvR5l+3XIhuSFEvTJMrWskEqf9N6NzYn8jseBAfhqtUJhO48gj3FKWWN5rclEGbQ7XQiwDHvICycT/uY2bwGVksHJ7z1zLgFDcZNZY+Pd14X1h23qusXpySlWDaF2G5ycNDhZGZCdYj7bx4te9BDKCthsTnF8chtNvcbmpMFmtcJydQxHDW49+RRufvUJfOurvhn7+zN/UxUKWNtZ1/qaYbfQ4sYpO80f6OfiGtsAsr9a4yMigCw89/FgzhgLS/1DLB74poOEtfCWbi4N4ICOkTNAJue1c7mijE9xHu68bSNgdC38VY0NgZxBSxTvxWUtyGD8zmOg71aTACJlKZEnf+X3/K5z3b3bkQmE8eI6ZHxaqqyUZU22X1rqtIVIa5hayMvPpRYemY4Jhgsr36FwF70AGh779/52fH0lx2sZ470HfM8131/fNTb+7dcdoUgIkZTbTa4h7arU/ZWkQaheF3JsJNOVderT0JoBp6xy/LkkXmvSNU7OYVJWWC+XWC6X2N+boG4aGFsA1qIEwRQWtixAtQNR/6aU/f19zBeLTmkpW1BLODk5iaEfMsWWHg/tAktZ5uX3epzH9pkUJlJYp1x9es+l6hybT90OCURlf+S8yn7IudzGM7isFADgOGpfr4VrTQBa8LwVxt95DeF2Nak1ZlAWXlHwlk+v3FelvB7PRD7HgLLrD0DwisRqtYS1izjuVVWhlaABLjnumqJsgVfUJ+IGFi94Q3vIH4J1kocHD5RBgdYFy2d4h+I8pee0p8CE57RFTSuVQAfw2GrMa18bP6TRQK4VCUAlX9b1yvXQPefQtg0ctTAWsBYwNrwTbjiiMC62gAAufYu35CFsRU/xvBRolJ9J8KfXvzGmF7OsvY56rDRA1wpovInJDdfS6J5K1DW0cp9Nz6s8ltJFWxQFHDUIthV4OetjI50Dlss1bt++g5s3n8CqJrQ0QVNbrFeEsphjvVzj8a/+DxaLKaazEpcPr+DgYIHVyQmWJ0e4fbvA3eM7ODo6xnRqMJtNvIvC1b5OY3qgjdsoN5n8XKZzkFq61tg06JCARjNVQ303jK5Tt0OTbENKQMj+yBRA1loQArAcmSu9WXiBb2uXfFa2QcfpaZCX2hDyeVm2FjDdO57jc13cDpmSaQwEaUYpXa76O0laCEtLDZcjgWwHEL1r2tHwAJQs76y5lxamMQChrUvGGFhjYVyXaJ7Xt2Z0u/Y7ZZE6i1IMWltx5Pca4EvmLfvH70vwYIzpAdWqqnD16lXcvv10uBzgAOR8iExoHWB83K4pS7Sttyb7OXTxUN2dO3dQTbz1dX26wlxYyflffQAHGB6KSiklejw1D0mBev0+/8i1zGOdmg9t5TjPnG7bW6lTsLx+x/al7rMkthoVRYGTkxOfO/Twvt5BOd0m7j8feLh06VK0nMtk6dvGXpbZ+0xYAWUaOZnVYNte3kYcO9fF23dt0m3U7ZXKG38u+av8bGz+dF/lu3qPrVarGP4l47P12pfrULZVk1aspKIky/AWZ9MDrXKfMFnrPRBadvOzMh40tUdS4yz7oZU6TSlrLaclSpEElimQzWc9Vssmtpv31r2m5wWw1BuibVs0rXfN+dt3wsmxdgODIoBqwmRS4tKlA0xrg+XaYG0bVGWJzdqhdRvcunWKW7daWEuophYPPnAfXvnNL0ZZHOLo7gHu3LmNulnj8uVLuHz5AOvNOiwewFsh2Jc/1Nxle0HD061SYMuYB1mWdI/ys0wG/bi/VNn8zjYQJ9vBLnhZDpfPwJiou3puTG5IFwdvOtnHMcGWIgnu5NjoU4KyXn0jDLdB1997P4LJcSYuN90Y80kxiRRJdzg/JxlBilnG+TLpE6dagG0TuPr3cwE7sZ4lc5cgSAojTVoQ6XRW256XoF8zw1Tf5SlpaR2QJx95DWhgLeuQue+qqsKlS5dw586R77e1QMluT8RDYUSEEgWatoVxPOctytJif3/fW6gKL1A39SYCye462mEeQznmup3bxkn+jIEf+a8EigwsU3Uzye81cHimpNuslUatDIy9r8dJhl2cnPjk9ZcO7+spEJLn6H5KHilP8Mux1odItu8v75qfzfz95kdHR5jP59E6pcM6zrNXU0Aw9Z3m+UD/6lA5fhrsbeMzek/qeUv1SbZH1yfXmewDMDwsdlbZvowQ1mOH4WxA/6T/mCElJWvGKNWuMS/hs9k/MsxLe3OATrEuihKu7S5hkSF695KeF8CSSYIh5zioWAI6+NRCtsD+/gL7+3t44IEHsWkNNo3BZt1iedrgf/7nJtarOsRXElxbY7NeYrmawtEKtqhweGmGxd412LCx62aDut6EwGpCWXh3LzB0VcnFGz4cxAtJZiGBF7+vTfpMEYjCgmiYS1NvupTAlN/JdkpBIhe7ZPBxHpwbAEvZZu0qlmlhxhiRFhT8nIyp04JTb1Buf0rI6rWkxxUh8F5v8pSATlm85NhrK8tZYy/r0bFHuv3O+dhIwlBIbAMP8lnZVvm+ppQr0jkC2vR91hpsaku67g8/v40Z6/7pPsh4I90XOY68Btm6kIqb1YoArzm2oPDfbeuw2fiLFE5PT1GWExQTVl5Eaipid3sXCxbTWZUl6trnn5yFmD+2QGgBJdeeFp4pISzf42dSwlzvOf0+jwkrl3rfyHHWaY70XGyj1FrVyoNsq+Y121LAyHcZ9HOc6+HhIfb2+il+2CqtxwvwJ5zlc1JR1bw4pRjqvd/n915pYWWIb2hiC955xpNpOp3G+ZBgV44Nt43bIl3Lsk+ap6dAqib57Biw5N9l4vfUgUhdL7c1tXYkH+JnZb3Sg2gLjiEd/vStkwDRUKGRPILr2sWSzr9zedtc20D/MByvV1ZAUnXIVEXA8OpO9qBMJhMslz7N3nw+HxhH7gU9L4ClPN0o3cn+lpSQa9LYcKBHx+m0IACz6QyLxQyHBwZte4rbt+9gvSbM5wscHvobVw4vLVCVLepmA2uMD6R2DTi1UVX5QzHwl7aCOLAbQ2HWE54YLmw5cXJhSQGZEv7xffFZakOcpTnJxS9/5GlqqS3zQuXffd+G8VzA8CCQBr6sicvPUpaOVHyU3BS80XR/JSjmeBfZTn3wA2HVsGtZtlsyJj1+sj0a3ErgokMdUhtWM5OUGyP+OOcPwyXG66xydfvH/tZtHYCV8Ld2T8o5O6u/KeEy1n4tlHj+x+KHeP5lvC2vB6B/s0cKdMk9LPeKB6Ul1utTrNdrfPWrX8XNx2/5JGTWwpbWZ5WY+ly202KCovRrzt+AZHHt2n24efNxWGtwfHIEwAMWTlS8WCxi+hlrbe+mLG09lG1LWXHkGI6BnV0oFZah527oOhzPY5qi1B6T6zIFgCUg1M+kyqzrGicnJzg8POyedQ5k+oBdgygJSHQMN9Cl1JEu+lRfUu0zlg+mesPFfD7v3ZAlwZ32ZmyzEPOc6RCbFGiQ4F2GyOj3dJ3SCzDWRya5lzUwlae59V3Vet3JHM+6D9tCkFI8xviolR6QlP2W69Ur9P1sBdweBnnchpSyrPu9S/v09/IGN4mF9HjymKYwRN9j2IW7SAXyLEX/2dLzAljyRucBZZeSsW1YGGy9BGR+S4MigE0Hwhqu3aAoJ7jvvjmWq9tYrU6xWCzw0EPXUFYcs7mCDSkdHPkE6j41BIOSJlogArLsASnt5jXGxIMPUhvU/WKS4Chl+YkCxT+dFIqyTQykuC38w+1gbVimQpAnyFPArosnQVKYyfe4Lpk8W7p9JYOSDJndj0TUy/upGbx0f3O/5Zhyvxgk643V/Q4YY1GWw1QtetPKzzT45e80M5fvSje4FoBcZ8qyzfNLqjz5jl4PY4JW76mUgE6BT8Bb2owdpryRdcvQg9huxVD5X+12lOVwug3JULmdrGED3dV2eq7kupHrQgJ3fi41Rsy8p9NpzM1a1xsslz4P5a3bt3Hn9pE/uGMsHFoY42MqjTUoUeDylUPs7+/j8ccfx3J5ine/+//i85//HGbzmQjbGF7Tyadn+eYSzsigBaDc87L9ctxTfEEDtRSw43Ui0yXJOmV9/J22oBB11pyUN0CWsw0k63XDbZZXkabAj3ynLEtcunSpz3OLLpRIXlWr17deJylgpNPH8BiyNbosy2iR7vrQeUGIKF6Ksbe3F8uXhw2lMi3f032VPEjvZ71HUlfH8u1t3H7uk1ZsNKDxn/fXZGpvMvF4S/kj/9bjz59JnsD18hjLfKCyXUz8PvPqeGBH8HU5bv59f4J+mzzgNjLA1GMtSfephxlGxkrLDDkHUgZ5PtUdhgKGQJOf53yw8ka+1LxeJD0vgKXcFHHCTIuyYM2LAHjXrP8J6XAM+PJFmDKc+jMtFvsWD/2f+3Dt/gPM5wtMZkBdr+Nm6BN5tSage86R5D+SgHZ4CCZOzIgmooX+Li7B2CriNgxPjGuGKi0bknnz76n8lhLoyA3Ci7kMMSdyI0qBJRc/lykZh35Pu5ZlWyQD0ICby5egVK4V7pe8llHfwRoD5gsbXZYsUKX7Xv5oAS+BmgZVKStNCrTpE49ybWiGYgx660rPu37/rPp1vRp8SCrg3b3aovtsGJFmivyTYnIy5ySvqclkEuMadR+AofVZrm/Zfjm3QHfoRx6qoKBQTaczNM1TWG/WmM/3ELKxxHIsWdjCom1duN93ihe/+P+AmzidTEBw8Q76WbiTmC0gzA/YRcjAU+enlPOXEno8vnJvpoB2av50PXq89N/yGXmylxUETvOjgZD2nshydqHU4ayx/nCd3P6iKFBv+pcjAENglop1T5UvgQXzEL2m+8C5U3K1x0rTZrPBbDaDMf5Oeh0GIkke/pG8dlfS7ZB7gr1OEoTJcSX05ZNUYrXcA/px+fKAq+ZJrHBxyIC8z5zBojQgaJJ5bv0zBs51a1DKGjmGm80Gs+kMROM8VhuC5Phs443aE7gNhJ/F46V81xZqvUeJKN4EyAnrU9k97gU9b4Al0HcL2FIOMltxAqAEW6C6vy0MnGvQtuG6w/kUi/kU5AyazRou5I0D5GIUDC6xH43tb5BRBknp9+W7z4T0u5oBMI0JEK0hpsCdLK/n0nY1jOkAHW96BmvswmMGJBe81rLkopeggTfGarUaACypTaaYlmQszBi4j/Ig0lhf+V0pBM8CzkMNd5yRa2GtGSgLDJ3T0tcBtMJtf5Yg1n3UCtBY+8aIyF9vOgbWnglpAMNzU1VVtE5LZs0ghQ+7sHssts+5wRrQyogGSynrs/ycyynLErPZDE8/fQTnHO6//zqm0xnIGNjCoCgMyokXcNYZVJMSDB4efPBBfPGL/z+WyyUODg/Q8RgPIBk4AsMDaixE9bpPjb0WIPKZscMgqTJ4HKVVSI+d3BNcl1Z02LIs93dKgG5zlW+j1L7c9qxO4VWWXY5DqWBoheusslM5FBnw6IwTsSxjYS0bLvSBkT7JW5nYYq9dtkxO5BE67/5kHpTKKcoeoNVqBedcLwl6nAf4ND76hrwx4CTXdMq4ocG+vPBAjrn8PUVyTP2Y+QToPlfnUAmT/fZIOT1WPEayX2MGBU3agrgNVI4BS72m9BrU+5Hr5UM78/k8vsdemntJzwtgKYkXfFEAxvgk0SStlOQtCt3n/uYbAsG1gDEhRs0RClsGN6tP4N00DYz1QsATL4zOMumJ4udaQKeAihm5/lE+I7XnXch3cTxYX1LqGQkiU+5W2a5U2Q4OhemStaaESXxWLFTpdpWMSIJWnURZa/z8DH+fApVM0m0qy+fvlsulv82oLMIc2zgmRNRzt8uypdVIWjm2zUNqXmQf5JhLUJP63JouxGJbXduAoxzjFLjVzInJEWDcEFg+W2Yk65fM2Zjhnb36HmKgS7Qu3x8TXpIkkEgpOxKkOudwerqK1o0XvvCFeMlLXgZrSxRlGRKlGxRlAVtYWGcA44WXd6UDi8Uebty4gbqucbo89gqt6wtmub40OJYCWLYxpUDIfug5lkJszFOihXzKgiz3oFSuZX2ynWOuW7mWd/XcpPp71jNAH2AYmEEyeqnM8XvbrKDcP6mQptaPBh++rx4E1vUGi8UieXOOJAZ2fNXttv2/C5gcAyuA9wSs1+t44In7UVUVbt++DedcjC1UJYQ1oQ/ADMO3NL/m+lP8kV3z/DkbRfhvaWTY1tdu3Ig7PHhWZpTwvzcADSGRdrHzvGuAqp/V7+s9laKzDAFclxw/GYbCZXAb9W1fbKF9pgrervS8BZbWAsbDRfDiIEIvO7wfvHBVU4hHZGta29ZwjrBarVEULayV6QT4X04n1FlGu++Fm1syydCQsza8pL6WHbQiTmTL9RFrS90zWjvX4INJCynJ8Pj7zWaDtm2jZaEHYmw/KN8Dry6fKH8mXUb892QyiX/zAucTlxI8SZcyA08pPHU/U0KSLVpcpjz5xy5v6QpnrXsymaCwJZp2g9VqjaapUZYV+Eo2a4s43tzGum5Q2AJFyUytHxNkhQbcuBacjzyqGcbEpcWfASZeaVoYC0fwN2WEbjoitE0LWH+zC4i6wHMA4n+CeK3yGjKIWhKZ6LIyIbm9t/6Tb2+4jrNXIoW229goX5zp+hB3iel+9x4kAUjEFmJyjm++MPHKSWPC+mxqGAhLrnOA9beCLE9O0boWly9d9rkkgyJJxvitGQEWM/7QT0IcbxIhENz2FPh2zmEymWGzqdHULWAsFosZiqLy3bH+SseyKv3NI7VXfh21ODg4gLU+JvDg4ABHR0cwK3/PeFPXaKoWbetQFKXnZQOB69edtMpIq7bcr70VoPiBtoSOgRgNrJj3jilxmiTI5PjU6XQ6eEbzFg1c9fNjn0uh2nc1D2noum1hC4tJSHYe17nxOwIG3kNFgs9yuJUhWGPhGofG+Xj1zWoTQxj0lay6H0SIMZgHBwexL2MWr6ZpQxxmEdIcUVjTsUQApgcSNNDZRnJNMNiO824N6vUGbdvg0uVDf+UrKNwyFTyK5GAMUFXdTWo65In7NzbXWrbx71rp0wrkmDLMJEO22PtT1xsgyDTmP9b4fL2Na0FkUFUT1JsGOnc10E+2z0CXzy1IhSJl/ZYkv0/hhxTg0+VpRfIsIMqXAhwfH+POnTu9Q2270HmelXThwFIO9FlaBZN0f3XWMZ8IPQItIF5HZW1/cqqySx1Brb8X2t8eEhgkNSDX+sDcdqgpG2uDMBZAhhkOAFjTuwqLxA//rYdfb3QWeOS8MCSyEYx4cNNpumVZgUx/kUlNP+X+Y9KnYPlfqbVoYcNz1WPerps/qYVq6wfXzdYlZlDa1WuM6cWPyaDxVALY1P3Z3H5uU6o/3H4GoAcHB6J9Fv7WjRLWVgA8E5dqhQnrrSwmMMb62zjIgJxBYas43q71gsiWnFc1pJdpapiW12iw8oBQMng1ft7b1gGw6N0NHASdAQEtUJhgdaEWrnUdeCaHwhbeXR1WqQd5/s7bkN8fQOHBG4JSZtjtQ2hBsNbFdopG+KvOCD5JvkH3d+FjCl3bgByhtNYrf9yHAC7BQHjAk2y4Rs2n3ydjw4ldwPChKhBg/VV7xhpsWkJRTYG2ReuTjQG8V0KEtQ/ZMKrtYX84PgxHMD2FdMjYJd8ypoC1BQiEk5MjXLp0JZbtvytRFiWIwtWbghuUpY+Pe/rpI9R1A2OAzabF4QOX/f43fp6qsgxlEsj59hdFNUg9M2bdk32Qyloqdk3+q8uQdfCeTSmqEtTFfRDq4vQ+QHegTgJB5gEyLk16QlKxzLINsp9jfZHzyO2YTCZoXYuW/NWMYbd4cNCyBZNYM/JGCddgvd5gEg7ZEBFgCFR4hceZFnbq4/f0OKcVFn9AcTKpIkhJ9cX3tURVVuGGLaAsp518cHKcAGuHqY/G3Ow8B/LgklTMPcisQeRQTQoAHnAZCziqw/t+T5Zhv8k1J/skAZhsk2xHCgBL2SLXJb8j3eIykwL3RYN8brO/ZpgVTIr8erNpAYSrOYlQlpNkKAeXy6msqqrq5QBl3CKVP7k39ZkDuZckQJTyVsbvpiySPB5yDHgtyH05m02xPPWy+dKlS70YU83/orlNzSmIzn33zj21WI5tfskwgL72wZpAWbHrcojqdfljWlpkGju0adBGr8Im65dl7Gq15Gc9oOje4/Kapjt1yDTm0tOkx1FrMzGGJPFM7O/IfOhnU+MnT/0yU5VAVQoobhcfYBhzP0mSgo3jpLg8aSGR/U2V6S2bE1jrgRqPCY95ITTKLlemsDQPtpd3Ba1XGzhyODg48JpvXUdLmTFeKWmaNjBwPafD/hIZuNZFwBYFufM/HjiFtcCaSaJtw9+H1quuf/13vfWGzbAUn3WsRhkBpXbcA9oCQUTdfb292mWsLoV7uQOAZ1AY2mMLG+eH40L7hXnrKAIoTJHMmODXL7DZhITYzoX43XAFYKjLhHLLiuez4zWta2KsXF0bbDZrkCMURQnAnxAHAev1pndK3I+NC1bydHqXlIAeS0ki911qnsZ44TBOTQ/peGiHVqaB4Ul13QcNOlN1SEuULEf3SfIdntsmWOI6KzqF8Y09Eu/7dTCfz3oZLuJ+g88IYA0bI84mAxPWb99zo63FzCu69vCaNf52xqitJdwBgbTMSAHxMTnSEfX+lbLBg7gGde2SBgEJmCSQ0u07j9xkj9t8PsdyuURd17h69WrPaDF2O01Hcq5SpiA/pgyqGLRxWILMcdsZgMpoMGG5l+pXat9pIJky8mj5JPcNlyPL5LXFa4k9eWvrAfl8PsdkMsHJyclA/l80PSeucGnZkloBIJgIinCP6riptxuYlGDtPb31mW0AOEV6Yk2ibA9MQ9uJ3zHBtT8sT6azkItqF0oxa9l2KTT19/yZFk4dmOr3OdV2fbOKtqpKYMvzxod+JpPJaFyK3jhaw5PxNlIDY0061VbWLnWyZ+nOOKvPukxbWBSm00pZy2TmA6CX2/MsYgtFLF+5/3i9wJidhRswzDc6xly2gQAtqCK43YGkQNPzK8nPzdASpNui26HXWfd+wJURVAzrYwECIMSaWTyFOyr8wfowBV4rxl+9GXoXyzaWMJvNMJ/PUZYllksDV7Qx16VzLqaa4bXK/fHJnIdWRmkJ0/1MuYfljxRWmsYV8iG4Y9IWKrba8FimlMkxgCvjE2X9QwWo3ya5HiSxssqKa9M0PshxR5JAXZ4climWYtt2xEaEoBBCyQ3Rx74sO7uN/XfS38u9Jut7JoBCA6dtMbtj8is1z5pSn3F4W1mW0TLOPFzerX0esDpG3EYuV2Yq4dAvHgu5Vsb2l+5TSkmU9ab6IT/TvG9M7rIBhgEyH8BaLpc9gHyv6DmzWDLz0Iw7bmrHVoQ0M+wvUoJOE2DYLafiKs+3qcZBLSAteQYYpCkwg5xY/vn+YpJjAfSvv0tpOqkNrV0NTNIlpBettijoejRYTpXPf/NtIlwOa3rcXplni8uXwHAMBOpxkrn2pHCVSY257NSVbfpAELdZhxwww5D55MYYKQBMKn84iDezv72p7c3t2GZOAjv4OD7ZLm6nLMda71alHSWcFthjyotsowaDsj/+e2Bsj6ZIC8UUc3OO4N3Nw2D0VJt0XbpsYvMmpT0YPL88xj6+eBZXP18r68cb0QWqrc+Iz3s3Oguluq7R1i2Ojo5izlYGs1oYRMss+ut/bN1o5SvlmjyvAEnFjqViB2Wdqd/l3ylgOVDQRwCjXrfb+iMFflEUePLJJ7GuN7j+wAODZ1NrlMeL48Q584VWws4DLLt2+d/lfA/bM7SmpUDIGEDUY8rzJ8GPvN5vV5IHLseyi2iSfC+1Xnddl/w+X6s5mUywWq1660VbgZ8pSYODBJNSOZOu6V3iW1PrPDUWUtboK2n1e2OKNb/f7Xv//f7+PhaLRWyjTgl20fQ1B5ZyAqRQ4EXIKUbalrPz9zuv4w049mRQDyRg6kASpxA6iwjoaZlMyYVLBv00RrLvvoyUFiLHh4EMa9pset+FxhLNyk3N46vHXG/O2EdxuGgMVPJnnHdMzqmsUwIsXvjySq9tYFn2SQoq+b3cZNssvlKblmWntEiZrHqX8W9d27NOcr+ZUXFanRTpfUIYWuB0KEEErme2Ll3fWf2SjE73tTslr05ejvSHqWeZE4AlvTe6m3PGXL38vXa16vkkIoAcUruJ1wHnx2saH19Hzq+BhrrQC+dIgEoPNAvTKbfdOHgQwXuhLEsYMjg9PcXly5cBAOv1urdH+VaesiqwWMzhD2ykhbDe57xW9H6TQk8qfmeRTlckrbnaTcd7Tlp1tDW1m9Pd+Emq39rStW398vc+rnGCaguA0muV+8kHAbUA1+3ajZgvud68cDlDxegcRSuS7ZVrQ99QdR4ApudAAx79rFamuT1y3s6aQ0lyPWlDFJ+c15b/Z0qML/h2LMnHNbDm/ktvY0ruaHCYAsSSl8lrP3X/5RxI0vyPsYQv3x/eWa1WMZ/lvQSVwD0GlqnGa+bCzJXdFxws7ZOjruPpZAYtelKJCNYUURBxHRqQ8ORqqw8zErlIfLsMWuq3WZYjF4avv7/JdKyPtiKwqV32h8dBW6q4n/Jzrano/sq8gPIgjRYaUhgwyPPtBpq6u/GC26fBgBSODIhTudHkSVfNoPh6O95QMpUHt5EBI59u57njfssccprJcNv5mfV63RtDmc9NAzdZECy7wAAAIABJREFUjuxXtAIYoBSHyVLzQuRdEBzwLRUrrl9asQrjrxWUwFK2jd9xjvzpbfLXVcrAfB5PbndnjStUGW6w5ni+pMVbCwj2JpSljzXTCp+2bvKa1Oku9Fpo29YfDCr7IQty/LmsVCJ8abFilxYAWGNh4HprVypCUkBNJlPcvXssGL8/mIXWwYFgbdEpU1Gp7YClLSzmdg7OR2htgdliinpd4+7du7h8+XIcl7quo3vKJzNe4fT0BLPZBPP5vMefpNIjLYM6DCQFspmqqooxVgcHB730TSnBz2tdp3ni3+X+kCfKtWIswadcZxLISVDKVn9ZD887H+KQcyiVOunJ2NvbA1mD9WbjHUtxjifxfT1GrNxz35jPsHyKLlhT9ta45ouxbYU/Pc3x9W3bYr1e9+7Ojn1E3zooeY0MM5BAXvI9+b2cUx6zpmlwenoar6jU1lPm/ZKPyjAHrcDwu1Lh0Pk8JcDl97WXSN4ioxUXXies/Ml1oY0qLON43uTe4JuGWL7I9cj8gl3dkk/LQ07MT+ThJK5fHoxhi2BVVajrurfOdXo9uX9kmWOWbTlukpexZfXo6CgeXFsuVyiKAsvlEqenp73LGGTdmiduU/52oeckxlI3VsYxsJuzbmoURf96KRkfJ029ZAmg7jM5adb61DCdFaR/u4IEKZKJrtcb2NJfAagXq1yQZeGTrmtXvE8pwpvTHwLp3GxFb1Pyc3VdY7VaYb1eYz6fx9QAksnLxcg3esgxkiCQqB//yIyZgRxr9PIEWgQOTQOgS/zLAlwGTOu6emA/CEqgs/6t1+sILnicV6tV3ITz+Tya6yWz4nmSYE8zcbmurLW969WYOfDtIJJBcn/11YJcFzMu/k4KcMCfYnYYxqxKxi+Z81g8kIyH6QEi0TfJ4Mqy9Lkug2tWChBum4zzlEJErz3+YUDG9cm+8tpnxsh53zabDRy1USFM1SPboYWfBILxHbF/ZTaD9Xod1wG78haLBVarVe8wmBRsTMYaGNd3ZXK9x8fHABCvPQP8Qa6yLLEoFtjf3w9r1s+15BUi4RIisLSAD4FlhaZAU/uxIqLoleF2yrXXtj510Wq1AtAlHucx4HnRiaKloJf7sm3bKFAkj+A5krHuKUVCCngNwjSw4fpYqeH5ZYDdnT7uXMv8N7eF28/8RgJGfl56O+T+1cKay6Bw8wq3SVuh5PpjcNGXMZ6YlwAe+JbOp43SCmxKGazrdZRf7F7Xhz6apkEh5JUkbqfs93Q6xWq1SgJtnkeOY+dk5zy3fLpZgjj/fj8cSCqScm9LJVv2W64H7W7lttV1HZVB3uM6j60EupIns4FAK6dyXWnDA+8ZrezyM/J7aTzRyoWul5/h3xkcSwMR18djr4G5lgW7Wl1lvfwjzy3wHPurqQ1ms1ncN3ofRxCJLghDG2fOS89JjGXqOT3Yy9UGk0kJIhuBEF8XxtcUxYmlAs71DyTwougEewmfY86bt2ezWWQgZVni+PgYp6encdHb0uD++++DtQar1SoyBDZVM0BZblYo7ATG9A9mNE0TQFOLqvLD7E3rHUiRGthqtcLp6WlkoLyReZHw/bJ8CwnfMczMYz6fY39/H865eJONjBOSAI4PEMxms7jgeHPzZiyLKdq2u45OCjItZDabTY/BMXNeLpdYrVZxo3Gbi6JL/stxM/zdyclJD0DzGDEoYYa1Xq/9DUuLxUBrZ0FzenoKwAOGxWLRA/Q83pPJJDJlWY5kltw/edeqtRZFWaIqLFrqUrTwBpcMTq9FqdmzUJ3NZpHJWWNRFiXW6zVWq1Wcu+PjY0wmE1y6dMlbHJxDSw6T2TQegpLCRCYZl4Kd+6xdONJ9IveQ1Lb5ez/va9T1Bq2r47xLq4OcEx7f5XLZE1A8pjyvHnxZ1LXvBzPD9XqN5XIJoH+KWyovZVlitVpF6/BkMon7a71eo92sB0Kf9wsftPF7vMB8vsB6XWNvNsW1a/dhPpuhblq05GBtsMYZA757vucKN4S9vT0sFgssl0uUZQHXdABN3yqyv78fXeHr9RrVxB/g4bmXgM1a7/5jcCr5kQR4PC68FngvSeGvD90BfZAkwWWKl0uBKd9hISuFn7Sa854HEPc3r8Hj42NYa2NqFKkAcHt5PbLngdcmr+m7d+/GdVhVFYqqjMqKBCqsyLNSy2uDx4vHT4LFnicjLCWpIMk+R+XM+DAKwL87m80wnU57oCACj8KgKvtJwOVYSSWAjRA8Nnfu3Im8ZH9/P8oR6RGx1mJ/fz/KUGkRNcagdQTnOm+aVDx5n/HYMZ+VfIEVIVmmBD2s4LetP8jGnge2tkmrnVRUpcyRRg7eQwz6eK7kfpBzyfxW90sr0fyvNCqxYsjPy/0mFZwU8JXgVM6pBL5cn/xujHRIgOyL3IdlWWJ5WuPKlSuYzWa9vt5LumfAcldQyc9KUHj16lXM5hO0bQNru/yHzChkHimfqLoCqMsjxQPNQrVbBH3zOy9Mvj6LNe2qKtE47zIoNkVkdnyZu9x0TdOiKhewpj+UzLScc3Btp80DXfwDW0hk3dJ8z8KUN99sNsNms4nPd1YOv1mPj4/je9LNzhtbWyvYLcKfTSaTCDbX7RrkuoMxcoPy+EmGKN00csNHTTwION74DHCkFYEBM29CHjMJYrn809PTyOCky1DW7ZzDcrnE8fExjo+PvVssrIvlchmZAJ82ZPcYC2XJBMuy9FaKAKAisysLkOlrr3VdRyVFWuuuX78OAJFBcbwLg9doDSbA1d2hAbbMcd/u3r3r3ZkANk2N+Z63qvEYssDhMbt06VJcH5x2gsfs6aefjnuLFRy+0lACS2n9AhCsUCtYayKwZJDAFldmYLwWuQ2sqElwK9eNcwbWFLHf1toIIhgwMyBkwLRer+N867qNMQC1MK6ri79nocgHGXhe9/b2MJlMMd/fw97evi+rLGBRwJhub3WWpT6w5PRSXoHy7v3FYhEFs7SSVFUVAc7+/j7uPH0be3vz2B+eK17jvE94blhRkOVJAM2gdH9/H7PZrLeftRDmPaatKWPB/qwQsoCdTqcwxseTMp9mPiyVNK6T+8XtZ6XXGBPHZDqdYm9vL65ruf+YnzDv4/p5rRVFAVMUmM6n2KP9aLk9OTnB6ekpjo+P0bZtBJZEhMPDw+g56fh2J6ui12PTwKdd7ZQvbdzw69tiMqmizJCgU3oo5Htcltwbkt9yO6RHBgCeeuopFEURwXVRFFgsFj2lgpU1BtjczrquQ5q/4Z3fzJukJ4dlDRs4+FmpPHMbeX+yUWA6nfYUHAn25fwCiPuAXcpstZzNZpFn8BqSd4uzZZjlMCsMPGZjFjltiZQWSq4/ZfXj7/lZHn9pXJFrRPdRW3flvymS7zJg5nHsQjbawRo4DzZ7pvScHN7RabikyZiIsH9wgMXeHNZ2GshgQIwJN3dYNA3Q1H03oEby/sfBivRjnEOvbdrooiYKucyMQxFuFuBJ67TLzuVa2AJABZ94e9j3nkYDfx2cc61gGhbOSa3SCaHBG74BwCC6K19q+vzDi9MzaqBt2aVdiPcNjOnGncGc1HraBpjMpr04Ns34uE5mBKyNsRbLgoWflSS1TAYKzoUExtRtYmmNkUnYmWk0TYNNXcNJN3FVoQxW3Pvuuy8cxPL1L1crzIOVqK7raP43geFaY9A6h0lVhZtwvJV6OpvBtd3JzqZpsN5ssKnr4I7u4kw5jIH7xsCyrzF388iAsAPgU6AoUTQ1AIPpZILJdILLVy7j9OQUJycnIU+mA2ynKbPSwxYRVgrYrcrjyEmap1Nv6azrDhjGk/Lkr0rlMgBEq0Q1qUI6nRlOT09gSYJCjitF3OSd9bOIQJC3f7dP/JqYTqbwU2WjMifvu5Uuc2ndYEtoURRY7O0BwtpBRHBtDUt8+4aI8zYGbdNgf38fV65cQVWFxPjhpi4yBpu6RlM3sEUJE27esZZvDkpY8ixQVRPcuHEDxhg89dST+OIXvoiq8EnV5V7a1DVu3brl21oUKKtyYH22tohj4Pcsu+1LrIJgh/E5N/3NPhaT6RQgwmq9RhvW4FNP3cb+/j5ggDphWSmC0rRcLmMoAM9lVQ3vaGZwz/1h4S0trGFE4vt+nfh9RACmk0nkR0VRxmT/t249hU3tk5Qfn5wEvriJ8+yFJFvRSqE4F95C7Cgkp7coCm/93dQ1Ll26FMfSBM9Ap3hTBEAnJycRMAPA5cuXo2XZW04tNicbuNZhsVhExY/bN5/Po7JS1w4nJ0eo60206jH/YQBwcnLi+ZetgIXp8V0ed2mlr+sa680GLYc2kcOkmuD69evRA8cgfL1eR4VMlsFgZzqdhvZOUNcbNE231hiMMHiUlsOiKOI+ttaCwj6UQIc9MfwZW0oBYFPXmFT+Rqv29BRG8CiWJ9LKJ0NBOGaQeR8rVNx/5xxu376Nk5OTuBYnkymsNTg8vBTXo1cSHNbrVWeIgr90hWUXZz1hfMLKMXvCWDE8OjrqxQrLWE7mUywf2FMowaa0cEremCIJYKVyJ63hPsSmjHye65CA9l7R1z7G0nghwiGJBHg3BXxsVeP4tGu4SYQMjA3xTY4ABjdBQBhYVJWPpWzbFnVTh2uoRNmM/lHAGAr3MJMXNLZAUbgYXGAI/iafwgYACFSVNyF7MMZapongwINKfbLPxM3WnS73yXX9xgyD4e8OiQl4J1OLPevL88IH4XcHPpXK37lwTV0ZAKq8CcKFOv3fPNg+IbUN11p57h6CvmPSX+mCKOKd1SY82wfKiAip9UFlKKzFfgAPTduCwkJmcGdYsFM3/1M1Bob62jrXM5lOo1Yw4wkJIxgPGhUWZWAW1hgY273vgUoNY/2tJ224rozbxiETTGVRAAb+Lnrn76rnrAIuaPhkgLKsfD3OK00MZqIViPyBDsCX5YhikD5MYKY839aPoaEuebjvh0/yvX/5clxp/H6nTFSwIuuBZ24tnGujUhEVpyDspTueBXVZFnDw10tGZYX3EREMWzGNQdvUcU0yCNVWsKg4Fn2tnReAo05ZK6xPBs1Mn9e+V64grA5+nurAvOvA0G0YJ8OCyVo/Bm0DWwSAK9IE+RtECEUZrD8wIGfQtG0IOgr8J4yJCXwJYf8QHOdOENvMH9SwtkBVlbh+/UFMJ/O4D5oQbiMtUTLU5L4HrqOta98n42PunHNo2gYNg/uyQjUNB1ACH6GwZsg5zKYzwADrzQZN3aCoSqw36xCb6wG7LfxY1Y23vJVV6flhNUVhrM+paXnfI+4VXmGFsZjP9+N+btoQBwkPEuu6RtM2KIvSX3tqhlaWsqpQlWXk/xN4/rzZ1CiLAuWkwnK5xGQ2w2Q6x2S+53kTTOw3g0POzGCNRVVOMZnMoodhEyz5R3dOQCBMJxMURQkzt5hNRB7OeROUCsBSB7xPj1ao7BSnp6dYLpeYTqY4PT4FYIKHYgkih+VyFYR6jdlsCn+Xdov1Zhn2H2G93uD4+CSApgKbTY3T0xP4NFsW0+ndCA6apo08lsL6a12Lpm5Qty1MAPFEgAPgTj2fbMiBjEFLDq5pYUywzgvQyIDv6MjP/aTyN77ZwqJpW6xXa1QVK8RtkDd9+VtxvLxzaAIwgzEw7C0DULcOLYDaOdStvwVpHQwCpvA3krm6ATmHSdWl2WFPkgRnHFLFVm8GTGzNZqs1gBhWRQSs1zXW6zpYSDsA58eAsF6H942LVs3JdIoyeFqqoLQ753ByfIyTo2NMqwkuX76E+dyfID89PsGm3mAxm8MWFvWmxma99pdKxD4YrOsNDokwN8CEDTUBT1jjf9/UdTjEWMa1yTwHgJetbAyCly+MMk6CJX69XmNv78CDaFt6PAUA5I1ygWsxMoFFZ7yTFtld09lJ+ppbLB1RvBY74rIwOAhAygUARmwZ86UBFv0BYWYX7kQm4y1PBl5IekGA+DwAfxVebCDQAjBFOcjL769Yq/zn5BmYIxYaPji/66eGld5q4QGlET8EOJ0ihsEKa6VA28pbIQBOUwH4W0HYpU9kQNRZWmWbiLjdovfGXxnmKGSpJN9wRw7GIQpMv34tCA4BTkWQDsOLk0RdFJMQt+TBv6ub0G3jPwP8VXzq3f6oIwhr8Yl0D8i8mvwdWZAxsGUV08k4ACZo09S9jJYAG65LqxuCCRY0awAUAuwbv/FaIFwBZsG3MMXm2BLVtL99ZOYZA9NhDQMfj2UNjC3AUXn+lsdQpoEXlsaE7FUuHgyJ/QhKgrQSCLUB3XD5vlhbYDLZnpTdGItqMo1Kg8fBvkZb2UGKHhPKhjGwMMFi76ksgbHMLoQA0FOKsqgboAAa+lRVfIpXKFDGoLI+FKGcTMPyNBGk+vSyBkVVoZx0geusyJqgBBThcxfKh7UobAUXYmfbwLOMsT1niwXAeWm5bq6Ywzmc8+vsyn33+WsFnXdPdVbL4UAZIph5UEBhesqDGjaw8sjPMVj1yp/FoenuS3foeAfzSd0AQxisqSQFBmx0s8I8MvAg5+OA/X5UPEPMAbcXGE+uPSBHsDR8zhaFbwfXE6zvgy4EBY+NAD1BKsqNimdRoA1eEgZbRehXUzcoWLgThcT5Jir/xlJ/TJzzV3o6Qts20RAgvXeGreLh3/7wG5Ad7m1v5fbnCdqmBcFfvVpa35a29QCcXKf4stGC4NfIdDaDMV1KLHbhD4bfuViX9GrFUDFHqJu65+buAGIZ5kikVSNCvVmjCR4CYzrP1oY9OjGMS4aaBIszdTH7Td2EWPQFClthU9dAsPQ757AJ1mMXxqMsKswWeyDjwZ8tujW5bryS5+Bz2u4fHmI2maJZb7BarrBZb7yHbDrFbDLBdDZDWRSYTaZYbTZYN7UH6ps1NnWNkydv4emn72IyncT+scLgWoeiLHqhWlVVBWxkUZTd+QzAyydH3vDh15kPR5lMJ5jNZzC2xH1XrmFvfx9FWYGazhhDQbB0UqYDlb19d35c+RzdvBOYV9jz0VoTvw8/tpMPkfQGAwLA4ieNDcwqPRrSWhHrS5qFjao8TEii2KQ7zCNS6FmRFqVtn0l3XQcqAHZNyc+T2QyT0sHEe6RZdHsBO7xazAOA/ufcHk2OEoIAiQXJsUPD1g6aHhdH73U7eJkU2DqbuoTiEXYTD6+J2ysJfVMfJro55mZITkkU5CY+I5Dkto7w6yP1p/ZJogNkwv7r+scMZ6AsGbFmop3u7DbGuskMgUgosWuA6a33wZPGersN72NysOi3q+CtK/bMoP1hTRe2O6DgiyME1SQCJwYf/L41BgXvE9mHnuJDYp15q4kNfM6GwfUCIQEYw3xwO3kt6PljMM68xrcvXBYRrBLdvBp/V3oI2TFuaL3lboyGMOm5IIzMpxhr64GyCw9KN5+O6ezGN1FXaj2YIbBlxaEDsX6si0TaRhnLSAF8ylCfWCYAU/r2VtMK1dS/M533s2HIfjFALIoCxgJtWyfHiefQWh26tUv/h56ynqcnrmsHUJeNgfsn4xH5O384zQMqD/DTE9y5Vdkz4cMwZP3cZB6L2Yzn2nbGC5Xbky8V4dAmCn0vCr9W2whgfd364AoFi70H5mFPEkJYRP9yDbaERlCMcIuaykbDcbL+8+DFaxu0wfMAklZcG/kFy2hWUDmsh0O4ZEiMDOuRWVjYQ8jtlPHI/COVkclkgr29vRjD6k+E7/uwunoTPCDhnANYieosn5rPJGXGDvScAMsU6Y0jGc225/yH/n9yk4wNyFiZW8GloDFteteYhWjW3qFNTHLj9AAnda7pXYgBAwwJCwtF603PQuIKSMtOBNYDRuPdjkNKzVPnSj67rYkE54lxJiDeqS0pNU/++Q4xWYZFJjo4BQiB33As1ymBtAAEGT5sa6qfjlvcf5+liOX5MBa7bs2kBRDpNZUa02B3C/V2QGXbipLrJHXXd/odEsnEe63y4MdQZynyEzFWUuibt1wyMIZcv/6xDphJRcr0n7WwcQ1R2CB+nAisBvEYW/Ev/1AcKaP+lZA/CDjnHU429M/Y9OUOLTmx5xgkOOgFaAwJPsfPct0WnWIoQk3QrTUDi8ENsyatLCR1EiJAt994QOuI59IgWpEN36rE5ffHjlO2pZX3kbWj9pMJLnwisZ5oyLWAbu8Qr/8QGjCYkrBWWteisP7eehfcz5ybksEA4GCN9QESxudCNo7YPYG4JoyBC0DMEcG1BOMY7Bq/Hl23JvvKIgXGk1gT1kSwwEPLY8Fgz0WrdQkj5pvIAM6EOXIw8POoD5ZI6mKqKWB4E6xgnpFYW3iFiu1iLaGlDjB5xac7H2CKsDetz03dgR6LluDd2MagLEOoQBt8aiwbwngyOG5CGACHRDlyncc0xKgXRYlyEg70wPefiA/fAKWlzurfuOCB85bFycy7aNq29YpJCCkzgTcaRyhMEQ/fajk+psRJBUD+LmMxx3BOv2wbLLqdJVnOZw+Uow/Qt+Gos+hrDizj1iD5txkI7SgURt6XxF33ef3MKCMZez8NjMbeT1g8RyyOA4feiDVgmxWVAhORCzK6T/nzJDBNNJ4Mw0ihUTKo6IRYx2yM+DwYlRJ3nbvEaCcty9ZsAQzq/RAr1+9T6n2XnNQUgAfChhFB0nITpn6XG4//7hoUjUm9EUhZPfwXlDAAMJjr5oMZwi5EZlhkcu0B8IEffYqubEMx9hPoQJQqud9GAy/cduQ9JuFFIPE/bZ3vP9edtjWwcV0W1vaUn74lbKj0dX+HNe3EnItxiO8Hl3GMM4Vf2xYhXIIXAIKGIXFlbHznQjfE4QUGMORz8Oq+Un8dGhiQSZxgJcAUNADWMWZaCCO26kZgGZP6D6pPKgtpvofBQvFW4C7PrAnx6AV1dcv2R8DR+yrJpQefpJadI/h4aFIKeWI/upY5F2szHpgOjBzhfd6+znnwyYdHwaDPWO/mFu2lAGy7m5SCu7+laHkyLfMwr3h7HZa8y06CUT0W4na07pvuhHkR4hcJBrDWA2Y+IAkfKtOV78fAMPAPADSGLAyUGrHXCDE+v6fQkx9jaSHk/cvhLAHyAlGuUdS/Wd33IM3AtS1aCjzL+DRvzvFaNuFQmH+ndSHNlXOQYqMLy2KvR1BsOYbe+PAVcn59e+WPT/H79VEUFkALRw02TR3G0rup/aGofqq1kkNoqBuYxvkzAEXhwT0fCi4K2/FB8gd2/an5cIiJ8Y1H5B1+AmLYBZfZNF75WcwPguXcnwPg+G6ug3kv8zkJLp8pXRywDBadsyx3JjLicEiDhyaxd1JuliQwQ+c+I35Z/HMW7WptBKAPf8f3dQmdKX7w9OCTpCs8/I9CfCeZbgkFHdb/Ntb2RJsQGJsJG9l0lXTvhPfI2igQ+fOhfSA0IQks7aBtbN3rgbD4P/EZd2uIywefkUGIBE31dUheE2VN0HZzF8ajNzZsGIimjeF4kwmAWbUzJcgMEjFpEljGdot5QjdeqR65BLDk+UrVM3yU6wu2t+BetInaBla/UNeY1bT/LqV1gMA3KFiH45jreSYfSxTBG7HbOwC10F9rTFR0DLdZAD4DE2OLWZ5KUGoAtKYfQG1td7CJy7QI67QHKtVkyIkjwLggLDn8ACqWOv7bHZiLazO197hPov1ds01UWAlAwUBaKKjGD1ivnQRCk1goLLwlUTiI1icCH7xkzBKBMrzllQLoK4rCH9YSArfXsV79w/3kPRUjoCugQLPFyFCGuN2o1FC6fmMQYgnZPUrRdW3iYT/yY1z6JkWroLGAcWjbTQTZzjnfLraqWvYYeetSb0wNgzjlnicg5QrncKEIMAAQWpDtuHfsp19kfgUzLyR/aJHdxDxX/sCfHHy11IPS5w88mghSnHOwZQGg6GKf0XmfYnYLhLCCggGjGAfeV+yONiZYlf0atzHWlGI2B267tYXnaWEsI4BCOFvA5Ye+13UbD8wBgGt8bK0/G8Hj5t3eRZjsDqCZGA9JoY9lUfiDSdSNO8fgytRFRTigByKU4aS8c/4a2iJk0WjrJlq4wTMfeAPCfi/KIoL9MqTAaeo1gArW+WwfJm6RzqpvlGzrGVN2tRwIujBgSdSlreHg5iTiHXFR7kppS1QxlETYHTCmhy3FtEYoYUkbezPZpsTx/9T7XRzEjjSoK4DUM9roRUDRaTVbSG6Y3ufO9Krn0dTTxPElmtqmHQBWH1PTL8CRg6N2a2+6tvaficJbWyhMd+OLFKepWFLPPM+sGgBQIoUChyvNwMLYYvBoIYQYP9m6diDcOd6nazl1VhD1vmsS65yGzTQALNdPiIy0W/ok6hv+TY6Att06S3GcWxLKQteHaGknw9ArOvIZnRDCicfuNV9KEKK6bzFul8Q8uHbATHti3fm74WEMbDXp2hjGJIK30EZqPQjrrn9kONoHMp1aHAShmq5Rbka9f8IBBwJc09XmeHS6kkjVz5/0FeKuD/JvxDfV3wSQawJYAQDX4/mxb8bAUCuUDTVh6m9DxeD7PjfjOXBhn8p1ky6fs4ectXa9TiRBEQthttZ3zxNxndyeFiB/EI9cA67Sg3xh2ySAQ1WS9gjSwC6k24v1hz41NQw5H2fcNh6gGIeUp4n7xtvZAChtAWrVqFKIC5ZkPMA2qqy2HWeGist6MOuvRYIhb13z2R/6MwYJpMB8PFjhvTkTgM9S4JpwIxA6HkDCq8JlRKUztJupLNTRweA5K3oynkKd8Vhx+JSzh/SLLYJrfEBEIMUTrbVwbbcuUjLfAjH+VDV/QAYGZWnRbjY9f1XSBW8M2raLzSWikC/cn+yfpgKVx+qlZ2PvDOSIUIeca48//jjuHt0dJOkVFT6rutLxhN66drF0DmB5nlKT1oBzTNiuYHl0nHetS1soWM9L/B0/Fuxo0Mzu5L58n7Vl0XL/ndPbRoKYDqCRoWSMZYrSQfFakIZnU4cqUi7ChFKRImbQQ6g/BLZ8kECjcAa73HkaA5bRDdoXpinLEGvJuk0Fj7OgfjJwX38Qzlx2AAAgAElEQVSnLKSEc1eGIR8zZnrfp4V55+GTT3d3Ice1AMAKJ6+sb0BxSfbrHBipCDC7rid4ZtzPPdFZPnvVR2C/BcDAW/s6Z2UaZJ0JwtR+8lZaiHHaogCAQp/G29h73oQ+U38d9EZkBBgbqQBIcDu2zxRJDi3rI6LBCMVwI24M7y31dwy52FL/2bOo+0pdPc+AYpu4jYZgyV8iEM38vpWdFVSV4KyL3kKOM0/9bSENAtv4Wkj/N5ALu1HnSgf4AA+RgGrnW/Jdq9gi2ZuQfrDWmCSLHoizuhMUJiOCHhj68pKWzSSX9PUNix3zsiUP+KX3SDqsbmi4YXDef9AGIM1rzltdr169gsV8hnLH8xHABQHLDrv3s9anOs8upGdMKRcvN2L8z2dY147P7ViZVy4TD4/1KUXPok008vnXitzu69LDX93WBF7tgM3ZNLbS9X4+zzgNnVHnqz+B35Jt4vcTQzJs/8hzSUqNaeL9rymNVZ6a/NEiFLD1iHFrcb33n+UAaGB4jqW/+4LaXvk9p9Te63hcJ/mDKqAaNzImKZ1UvdmrP1XEs9jPF/F+mp6Fp86kRmsEhJBUgKW21LfiDr6HqCMJ9pO1bSlzOxn5P5K79dkZiNKWwYvfEvHgp64qodTsYngYI8/fd3uflaqdylWYg/dSD8OGBzwGJVTnAJYX6Arvx4a0rt0yIM+CcybdwTtoGeclg52ly7km8xyTk6znXAxyd0E6qEv8/7z1AOkxsUA6xhLDdhr2zehnx7S6ndq5G+AaA3vJMrmZO89LogUpJWDEatNrG4UlOjiZGw5PjanpkvMlTqrH95F4PvV3ynCR+huJv1Nlju29gQYxBIuyCF2+SY1BitLFbn2+9ycxkJX10c4CIpa565jutPh3r3rXMntnR0R7SQ1+3B+UGBPdMN1viY3U3zC7K5WRzlrL90BkjUPgZ1cmx7L2yMi16wepC62QG1a3r3ufep/7yUgqur1yxFyfl0ynfDxbnepZkdl9pgyl22rU74TdgeEY7ZzXFenxH5PPOpaXZ2FQXlKx2U4XZrFsQ1CogQkBopoL+kamDgVcCCWF87Mo73xo4euGzudKH8a5pf5OL1z0ngmiFp25uisjuWgT7/u69GO7a7jPfqX3KW7DHctNn7ZFEsUYcw4Lxz1QqkhZI1IKwHnrZ7dp/6Xh3zpubFiQSCVT9N3zW1ngAJkg4WYaHpTYSvpQA5BGpedie7uin5G/U/PxLIDyKD1bsGpSf4woz6k47hHJnlwB5hxjuKOitzMZvSSewbwOqjfxQGeqZFE1fAjODu03IZn+4GNx0FPU9OyBQ6fB+f/b6O6/UKKdeh8e3dGYMrR7bKv+WdF5ZPauYSSpMx1EFLNcxK9NJ+fOY0u+EGDJDTuzsouoKFOm5xOdZ/fciw1wr3SfJIPdpgA80zITtJUTU//XUW63M9sf/nkuy+I5UNwzbNKF0L0Alucp90LMF7vW//W00c5TvwSe53UZ65yXNPp3HzLuaqsaL2/8b6jPvs4QwtjW38Ur8jwl2fSUc2RXujBgmSlTpkyZMmXKlOkbmy76KHWmTJkyZcqUKVOmb1DKwDJTpkyZMmXKlCnThVAGlpkyZcqUKVOmTJkuhDKwzJQpU6ZMmTJlynQhlIFlpkyZMmXKlClTpguhDCwzZcqUKVOmTJkyXQhlYJkpU6ZMmTJlypTpQigDy0yZMmXKlClTpkwXQhlYZsqUKVOmTJkyZboQysAyU6ZMmTJlypQp04VQBpaZMmXKlClTpkyZLoQysMyUKVOmTJkyZcp0IZSBZaZMmTJlypQpU6YLoQwsM2XKlClTpkyZMl0IZWCZKVOmTJkyZcqU6UIoA8tMmTJlypQpU6ZMF0IZWGbKlClTpkyZMmW6EMrAMlOmTJkyZcqUKdOFUAaWmTJlypQpU6ZMmS6EMrDMlClTpkyZMmXKdCGUgWWmTJkyZcqUKVOmC6EMLDNlypQpU6ZMmTJdCGVgmSlTpkyZMmXKlOlCKAPLTJkyZcqUKVOmTBdCGVhmypQpU6ZMmTJluhD6hgWWRPRcNyFTpkyZMmXKlOl/FX3DAUvnXA9UZoCZKVOmTJkyZcp0MfQNByyZjDFwzqFpGjjnnuvmZMqUKVOmTJkyfd2ToW9Ak13btrDWwhgTLZbGmOe4VZkyZcqUKVOmTF/f9A1psTTGwBiDuq7x5S9/GUdHR891kzJlypQpU6ZMmb7uaSuwbNsWRISmadC2LZbLJZqmGTxHRGjbFs65+MPv8N/8HFsIOdaRiHrP6Ocumtq2jaDyk5/8JF7xilfg277t2/Df//3fWK1WsW365xvQsJspU6ZMmTJlynQu2gos2bJnjMFyucQf/uEf4tFHH00+VxRFdCfLvyVg5LJ02eySlkDzXhIRwRiDzWaD2WyGsiyxXC5RVVUEntxOfhbwoDRTpkyZMmXKlClTmsqxL9gKyeDQGIN//Md/xOte97rBs2zR03GLAOJnQBfbyOUbY2Id8jPg3sU8GmNgrYVzDm9605vwyU9+EsYYvPzlL4/WSf5etp37kilTpkyZMmXKlClNo8BSWhKNMbh58yY+97nPjT4L9IFjioqiAIAIQoEOrGkAJ0HmRRJbQ7lvr371q+PnxhhUVTV4VoPhTJkyZcqUKVOmTEMaBZZABwRXqxV++7d/G5///OfjZ5KkSxsATk9Pcfv2bRhjcPXqVcxms0HcJBFhtVqBiDCbzQAAR0dHaJoGly9fTtZzEWStxXq9xnQ6hbUWdV1js9lgPp/DWttzhVtrsVwu8dRTT8Fai2vXrmWrZaZMmTJlypQp0whtTTdERPjbv/1bfPCDH8Rf//Vf4+mnn8aP/MiP4PDwEIvFAm9961vxnd/5nSiKAs451HWNP//zP8cnPvEJvPrVrwYR4dOf/jS+67u+Cz/+4z8eAeQf//Ef4+Mf/zhu376Nhx56CO9617vw4Q9/GLdv38bR0RGcc/jZn/1ZfPd3f3cEckVR9Cydkm7evInf+I3fwOnpKZxzKIoCDz/8MH7u534OZVniYx/7GD7ykY9EIPm2t70NV69exQc/+EF89atfRdM0eP/7348XvvCFERyvViv80R/9Ef7hH/4BDz/8MI6Pj/GVr3wFb3/72/H6178eq9UKH/rQh/DZz342xmtev34dP/qjP4q/+Iu/iP1o2xbvfOc78e3f/u34wAc+gM985jOo6xrXr1/Hu971Ltx///33DERnypQpU6ZMmTJ9TYm2kHOObt26Rf/1X/9F73rXu+j69ev0kY98hD7/+c/TZz/7Wbpz5w61bUtN09DJyQm95z3voe/7vu+jr3zlK7RarahtW/rMZz5Db3jDG+gXf/EX6fj4mDabDd28eZM++clP0ute9zq677776B3veAf9y7/8C63Xa1qtVvShD32IXvjCF9J73/teWq1W1DQNLZdLcs6NtvPf//3f6dd+7deoKAp6+9vfTl/84heprmtqmoYee+wxeve7300vetGL6MMf/jDdvn2bjo6O6N/+7d/oO77jO+jKlSv06KOPEhFRXde0Wq3ol3/5l+lVr3oVffrTn6amaWi9XtP73/9+unHjBn3sYx+jpmnoC1/4Av36r/867e/v01vf+lb69Kc/TXfv3qV//dd/pbe85S30wAMP0J/8yZ/Q3bt3qW1b+s///E9685vfTK997Wvpox/9KK3Xa6rrerRfmTJlypQpU6ZMX0905qnwg4MDvOxlL8N8PocxBg8++CAeeugh3LhxA4eHh9F1/Gd/9mf4y7/8S/zKr/wKrl+/Hq2YN27cwC/90i/h4x//OD72sY8BAK5cuYJXvvKVuHbtGvb39/HTP/3TeNWrXhVd0G95y1vwmte8Bu973/vwqU99CkQUT2ynaLPZ4FWvehV+6qd+Ci960Yvw2GOP4dq1ayiKApvNBi94wQvw2te+Fr/6q7+KH/uxH8Ph4SHm8zm+5Vu+Ba985St7J9KNMfjEJz6BP/3TP8XP//zP4xWveEWs/4d/+IexWCzwyCOPwDmHhx56CD/zMz+DGzduxHpmsxle/epX4yd+4idweHiIy5cvYzaboW1bfNM3fRNe85rX4D3veQ9+8Ad/EFVV9UIIMmXKlClTpkyZvp5pK7Akouim5cMtxhiUZRlPTFdVhaOjI/z+7/8+HnjggegCZzLG4Hu+53uw2Wzwm7/5m7h161Z8d29vDwcHB3j44YdRVRWKokBRFLh06RLe/e5340tf+hJ+7/d+LwKvMZfxZDJB27b45m/+ZrzhDW/A3//93+PRRx+N6YScc/i7v/s7vPGNb+yVsdlsUBRFdK+3bYu7d+/it37rt7BYLPDGN74RZVnG/l+/fh3f//3fj7/5m7/Bk08+CWMMXvayl+HNb34z/vmf/xmPPfZYjOFcr9d44okn8Mgjj8R6nnzySazXa/zQD/0QyrKMY5opU6ZMmTJlyvS/gc48icIgkWMXde7Jtm3xxS9+EY8++iguXbqE/f393ulpay2m0ymKosBjjz2Gu3fvxjRDfHinaRpsNpteDOVLXvISPPTQQ/iP//gP3L59eysIk+mK3va2t+H+++/HI488grqu0TQN/umf/gkvf/nL8dKXvrTXp6qqelZDay1u374db+N55JFH8IEPfADve9/78N73vhe/8zu/g5s3b6JtWzz99NOx/29605twfHyMv/qrvwLgDy997nOfww/8wA/gU5/6VIzj/PKXv4wHH3wQe3t7GVBmypQpU6ZMmf7X0dZT4Qzm2rZFWZa9m3Q4v6W1Fl/4whdw584dXL58GZPJJL4rUwodHBzgS1/6Eh5//HHcuHEDZVmiqqoIQieTSe82nmvXruElL3kJnnjiCdy8eRNXr15F27ZJqyW3h4jwhje8Aa9//evx0Y9+FO94xztw/fp1/O7v/i5+4Rd+AZPJZJAaqWmaXlL2zWaDtm1xeHiI7/3e78VLX/rSHgj8yZ/8SRARXvCCF8T+Pfzww/jWb/1W/MEf/AHe+c534v+xd+dRUlZn/sC/b9X71tJ709A2S7NvASQiIAooRkkgcZ9M4hjNZJJMxslvxpyJ888kzmSZJJOcbGdy4pwkE2PMGUcnMS6JhiguCaIIomgERaSbZqehN3qt5d1+f5Dncquobrqt6oaq9/s5h0PTS1U1VXXf5z73uc/dvXs3amtrcccdd2DdunXYvXs3pk2bhq1bt+Kiiy5CWVmZWtZ3XVf9nxGVCn0iqI8FgAH4PnwAvucjbA42ty3sSVenJpPGGS3DRnOCJ7+3XmYzFmzbVitLegJAEgMysebklohGw5AZS1mydl03ow2PYRjo7u7GL37xC3R0dKChoQG1tbXo6OhAKpXKOIXH932kUin09PSgqqpKteyR4yIlmEylUgBODcbpdBrt7e04dOiQ+hkZLAd7nDJwV1dX46abbkJTUxOefvppNDU1IR6PY8GCBer79J+RjKUErKZpqsc/depUzJ49GzNnzsSsWbMwbdo0TJw4EQ0NDfB9H+l0WgXNa9aswcmTJ7F582Zs2rQJ73nPezBt2jQsWrQIGzZsQHd3N44fP44LL7wQwOlG7bLUTlRKsoM33wdcx4dju+ju7sWTTz6NN998G77nn4oh9T+nfmqQP8j6e7hfOz0eyd+jdcKXjG3yMTC2QVxzczN+8pOfYO/evWqibBiGOmaXiGg0nXUp3PM81fNRgkzg1Kz45ZdfRiKRwIIFCzB79mwcPHgQfX19GafwpNNpOI4Dz/MwZ84c1NXVZQSdUuMYjUZVcBgOh7F7924cPHgQS5YsQU1NDUzTHPS8bskISLB43XXXwTAM/PrXv8bLL7+Mq666Si0/y/3pp+qkUim1FN/Q0ICVK1eiq6sLx48fV/fhOI5qebRp0yacOHFCBcihUAjr1q0DADz66KM4duwYPvCBD6CxsRG33HILXnzxRWzYsAHjxo3DpEmTMupV2ReTSo0EbfphBI5jw/M8NDU14Yc//C88+sij6OzsHOQGhrr17AByuF/DGYHkaPbK1d/jejA7Fn/S6TR2796N//qv/8KGDRuQTqczauMBqNUnIqJCG1aNpeu6aGhoUINRIpFQGcaKigrEYjF8+tOfRkdHB5566qkzZsUbNmyAYRj47Gc/i9ra2lN3/Odl6J6eHuzevTtjli/nkk+fPh0f+9jHzhqESf2nBJc1NTW44YYb8NJLL+HFF1/ERRddlPGY5L5c10U6nUYkElHLRuXl5fjrv/5rXHDBBfjd736Hvr6+jBOF9u7di40bN6ozxkOhkOqbOXv2bDz99NNYtGiR2oy0atUqJJNJ/PznP8dll12mgmkpJeDgTqVIJm+u68JxHPT29uHpp5/Bgw/+Em1tbYjFYnAcB4lEMvefgcL+SSZTsG0biUQCjuOM6u8u41UqlUJXVxf6+vrQ29uLvr6+MfmTTqfV5sDnnnsO9913H5qamtTvLeMlJ7VENBqGXIeVWS4ArF+/Hj/84Q+xYcMGzJw5E8899xzmzZuH6upqeJ6H6667DgcOHMB3v/tdTJkyBStXroRhGNi4cSN+8IMf4POf/zxuuummjGVwy7KQSqXw4IMPYvLkyZg5cyYGBgbwzW9+E++88w6+/OUv45JLLjlrXZBkHvTg9KMf/SieeOIJTJw4EdOnTwdwOmMQDofR1taG119/HU1NTUgkEvjtb3+Lq6++GnPnzsXSpUvxr//6r/jCF76A8vJy3H777aipqUFzczO+9a1vqQbrUkPlui6qq6tx44034lvf+hZWrVqlHseSJUvUpqFFixZlPH4JholKiV42AwB79uzBr371ENpOdMKyLHieB9M0sWXLFuzcuTPHLRgYxpx3ZAwXnmfD81xcf/31qo3YaC1Ru66LV199Fffff3/GuDMW9I2TALBz507s2rULN954I1auXKlWh1iGQ0SjYciTdyRwchwHtm1j8+bNeOyxx1BdXY3Jkyfjlltuwbhx41Rw1N7ejj179uCPf/wj+vv7AQDV1dVYtmwZVqxYgXg8rgazzs5O/M3f/A0OHDiA733ve9i3bx9OnjyJjo4OVFZW4pprrsGcOXNQUVEB4PRmm1yzbMk+SpAXDofR0dGB733ve7jtttuwcOFC9XUZdN98801s3rwZHR0d6hjJKVOm4MYbb1SZ2R07dmDLli04duwYysrKUFNTg5UrV2Lx4sWqPED+j0KhEHbv3o2HH34Y//AP/6Ays67r4le/+hUMw8BHPvKRjMcgJ/Nw8w6VGtd10d7ejhdffBFbtmxBOm0Dflhly2SlQIKu0WaEANM8VZrz6U9/Gu9973sBYFSydvI7bdmyBffeey8qKyvVCs9YkISAbdsoKyvLyNAuXrwY69atQ0NDAyzLynjM3MxDRIUwZGA5GiTA6+jowCc/+Uk0NTXhySefxNSpUwEgIzPJgY7o/JY9fEh5x1tvvYX/+7//w8mTJ/88mTTge6e7ROh11mcwPBR6V7jcnud5+PSnP40lS5aMWjAlk80tW7bg/vvvVwHcuVydkCyxbdsIh8O4/vrrsXr1arV5UTKqmTv4iYhGbszXQmTQkgFdNtRwQCMqTo7jqFrjVCqFzZs34w9/+AP6+/tVLZ/juDCQGVDmDOoM4FQQWOjaYyPn2DMasu/nfCElCul0Gk888QTa2tqwfv161NbWsgURERXMmEdysvwrbYYcx1GN0uXrHNyIioNsqpNgyjRNLFy4EPX19bBtW7XUyrUCkTOD5/tZyUq9ldC7/7fneardzlhvmBur3eBDlRVIgC/ZyYaGBqxYsQKVlZUAoFrKERHla8wzllKr+eKLL8IwDNTX1+Pee+/FkiVLsG7dOlVTKbVYRHT+0jeleJ4Hy7IwefJk3Hrrrdi+fTuef/559PX1IWSEEAqHMoKf3BtajFMFkQVmmh5CISOjw8No1xVmt10aK7l+J9nYGIvFcPXVV2PFihVoaGhQE32OtURUKGMeWIbDYVxxxRVYs2YNgNP1VslkEuXl5arBOhGd/7I7Nsi/6+vrcc0112Dx4sX41a9+hebmfQibPgz8uQ/6n4OtRGIAp35cMm3ZGcfC8H1X1W6mUqkxqXeUoE3+T8Zkk9KfTzHLlk6nsXDhQlx//fWYNm1axs5xeXzSAo0rRkSUjzHfvAPkzhTox5/pAx0RFSfJ1LW1teGNN97AH/7wB5w82YNwKAQfPlauXIlZs2b/+bv1wLLwTgV2p46mnT59OiZMmDAq96Pr7u5GW1tbRrP0sdDS0oLf/va3ME0TiUQCF1xwAVauXImLL74YdXV1qt8vwJpKIiq8c9LILNdgNlaF9UQ0NiSAqa+vx5o1azB37lzcf//9OHz4MGKxGCZPnoTly5eOyXtdzxqO1VJ4VVUVKisr1f2M1Zgmp5/19/dj3rx5uO222zBu3Di1O91xHE7ciWjUsEMuEY0KfbJomiYmTpyIT33qU9ixYwdeeumlMQ24pNZROlCMxf2eq5Zp4XAYdXV1uOqqq7Bw4ULU1taq1SD5OoNKIhot52QpnIhKl3R8yM4MykEG4XAY+/fvh+M4mDVr1pi1GdNbHemPb7TodZVjGch1dXUhmUyqY3j1zVX6cbLsFUxEo4GBJREVlH4Slp4pk69JYCNNu8fqMWUv/452YKXvfh/LIE6CRv20Mfk/l+fDdV0e6UhEoyJwgaU+2OtHMhJR4eiZuuz33PlQ36dnE+X9L5uNCjUenOuNiHoQz42RROdG9qoBMDpHyZ5PAhdYymxeBlfO3ImCKzubCuQ/6Ge37uEYQxRc2SHWWK9gnAuBG+2yA8vspToiChbJKOjL5fkO+vrtmKbJMYYowIJWhhK4jCVw+sxcPags5dkDEeWmLwsXcpkquxRgLDYLEdH5SV/FAEp/Kby0w+Yc5AlOp9NIJpNq5hDA+Joo8PQl63g8XrABX5bA+/r6AJT+hYSIctMDyng8rlZHSjmZFbjAEjj1RLe0tGDXrl0lX+tARIOTQb+urg7Lly9HeXl53oO+TFKPHz+O7du3w7ZtjjFEASVjTGVlJZYtW4Zx48ad64c06gIXWOoZCn1nOBEFj2QSbdsuWONwyVYahoFUKpWxM56IgkWSV7JCGoRJJtdniIiIiKggGFgSERERUUEwsCQiIiKigmBgSUREREQFEbjNO57nwfd92LadcaZxLrkK7qUnXTgcRigUguu6ANgHk6gY+b6vmhe7rptx/Fo+twlA9coFwE2CRCVEemA7jqM25wzWq1bGA8uyAjMGBC6wlFYisgNUXgi5jl3KxTRNeJ6HcDic0UaEuz6Jio++YzscDqsec/mQC4xhGGq3uXyeiEqHBJX6QQjZcp3uxz6WJUyyl4Md65jrc7Ztw/M8FVxKWxEiKj6SQXAcR40HQGFWIAzDgGVZGQ2Siaj4yUqlkHEjV8zguq6KGQb7nlITuMBSzzBKVmEkTdI9z0M0GlUvrEgkAsdxAvFiISo1svIgAWAhAkspr5ExQrITHCOISoO+8nm2I1slCSVfD0IiKnCBJQDVIL2iogKmaQ6aws5mGAb6+vrQ0tKilsR5BjBR8ZKgsq2tDfv37y9I8CcrILZtI5VKqQCT4wRRaairq8OECRMy4oChViZM0wxMc3QgoIFlKBRCNBrFpEmTEIvFAJx9FiEvmq1bt2Lbtm0qKyGnbBBR8ZFMwokTJ7B9+3b09/cXJLg0DAMNDQ1YsWKFWtUgouKjr2JIEmrNmjVYtmzZGdnKoTbvBKlsLnCBpTyxsvHmbNlKvbBfvteyLITDYZX5LNRRcEQ0tqQzRFlZGYBT7/NCBIGmaSIcDqvblUkoERUXuc5LvCA1kzo9eMymL4FL2VypjwWBDCylUN91XTiOM+igrwec2QGm/jN6YS4RFQe9RYgsXxciqyBtSACoDX4cH4iKlx4LyPVe3/grLctyJamkJZEElKUeVAIBDCzlyY1EIvA8D7FYbNCBP7uYX3/RJBIJmKaparRYP3VuDGf2F4QZYlAU8vmWADASiSCVShXqIar7DoVCSKVSqowm3/6YlFupvr9L9ffK11j/v0jGUu4bOLUioW/+lSAzVxwRi8VUzbVlWYF4XgMXWMoLIZlM4ujRoypbkYssfUu/S2kfsnjxYriuqxqelvqLhKgUZWcaVq1apUpb8r1dGR8AqB3iDCyJik92YOl5HqqqqtDa2grHcWCaJhzHGbQHrmQ4Y7EYJk+ePNYP/5wIXGAJnM4+9vb2quDxbH0s9ZnJ/Pnz4XmeqpdgtpKoOEm7obq6OqxYsULVRObL9320tbVhy5Yt6t9sN0RUfLJXLSXQ7OjoQDqdhmmaQ57gp5/SE5QxIJCBpWzAkSzCYKnpXJ+zLAu2bauvM1tJVLzkeFbP89SGm0KQIv4g7QQlKkX6+1df0ZAxA8BZx41QKKQ2DAdhPGCqjYiIiIgKgoElERERERUEA0siIiIiKggGlkRERERUEIELLKWYXnZpSv86fXe4voMzu+WQsG2b7UOISoS0BClEI3O9PYmMGzz2lag46Rtu9PhAPh8KhVQskCuOkGOfh2ptWGoCtytcdoHbtq0amuZqkK63FwKQ0WU/FAqhsrISnuexOTpREZP3f21tLUzTLFg7ELmIVFRUwLZtRKPRQOwGJSpVeiyQSCTOaDcop/Fkk1jDdV2kUimUl5eXfMwQuMASOPXCKCsrw4wZM9SAn/2CyA4sJajcvn07Nm3apL5m23ZgelMRlRoJJnt6etDS0oJkMplzPBgJOWWnqqoKc+bMyZiUElHx0YNKAFi5ciWuuuqqjJaFg72/ZULpui7i8XjJB5VAAANL13XVH9M01ekY2bKPcJIXg2ma6O7uVulvvXkqERWXdDqNUCiEgYEBNDU1IZlMAkDeQaBhGLjgggswa9YspNNphMNhjhFERSi7LA6AOlnLMAyYpjmsEhrJWgbhFK7ABZZyNKMsVYVCoWF1xJcXleu66uxPOcaJFwyi4v1y1RQAACAASURBVCPNjn3fRzQazWh8nO/tSuP1cDgM0zSHffEhovNLdmCpn6IjtZPy3s4VR8gYI83UmbEsYXI0EzCyE3T0A+eDVIxLVIpkcqgHfYV4T2cvnQ12uhcRFQf9/SsTRdM0VZnLUCU0ksASpT4eBDKwNAwDjuOgu7sbAwMDww4Q5UUzfvx4eJ6ninJL+QVCVMpkeSoSiWD58uUYGBjIewe3YRjwPA8TJkxARUWFWiFhjSVRabAsC729vRklc3rmUqfvIAeCUTYXuMBSZhWu66KzsxPA8OupDMNAPB7HxRdfjEgkktFKgIiKj4wHNTU1mDp1qqq5zjdr6bou+vr6sH//fqTT6UI8VCI6T5imiSNHjgCAuv7rey5yicfjmDVrllpOL+XVzsAFlsIwDLWjeyRPsGEYqKqqUm1KDMNANBodxUdKRKPJtm2Ul5dj3rx5iMViBblNwzDQ1taGw4cPsw6bqMTISkd2ljJXYCkrGJ7nqRXOUh8PAhdY6ru4380THA6HVeGuYRiwLCujXpOIiodssNHlO+jLrk/HcTguEJUg2cATiUTOGke4rqu+H0AgNv0GLrAETm/c0WsfhrMc7vs+kskkwuEwLMuCbdtIpVJqtxcRFRdZxpIxoRCtQPSTvQaruyKi4iYldRIgDvY+l8mrBJNB2JcRuIgouy+lyH6iB0tpSw2W9MEMQlqbqFRJECjHMEpQme97Wi4y+qYdjhNEpUFfrTxbDCBL4EEaBwIXWAKnax4kRS0B4nBJFkL+MLgkKj76yoWMBfL5fHZw62OBBJhycSGi4qeXuWSfC54tV/9KthsqMfqW/3g8rloPDedCImls27bVUXCxWEwFl0RUPPT3fFlZGRKJhFrayvf9LMe9RqPRjAkoERW/7HPCRa73uLQljEQiGb0sS1ngAksRjUYxefJkdXZnrmxC9ovEdV288sor+OMf/5gxSyn12QdRKdLftydPnlRHOkoWM5/bDYVCqKurw9y5cxGNRjNqsYiouK1evRqXXnqpapSuH7aSTcYSaagehHEgkIFl9lnhruueUXib68mXjGVPT4/avCOZSyIqLrIELju4Dx48iP7+/rzfz7L0Zds2Zs+ejYGBAU4+iUqIjBsSPziOM+hKh9Ru27ad0XaolAUusNQ75QMYtLl5rjor+bdlWapwV46DY3BJVFxkLJAsQqF2cTuOo3Z+mqaJdDpd8hcSolKV69quf07fqJdr7JAY4922OCxGgQssgdMzCP3fwyUF/3Kahixx8cJBVHwk+PM8D+FwWJXF5DP4y0VHJp1sR0ZUvAZLGkmmUl8Kz/W9Mq5IrWUQdocHcsSTIDCRSMC27WH3rfN9H/F4HAsXLlQvkCC8SIhKkf7+nT59Oi688EJVXJ9vYCnF+pFIRN0exwii0jBu3Di1gUfv/JArsJRlctu2AzMGBDKwBIBkMoljx46pWsvh7goHgDlz5sCyrDPaDRBR8ZBspeM4qKurw3vf+15Eo9GC7AgHgI6ODrz22msZrcmIqLjkGg9CoRBaWloyViqljWEupmkiHA5j1qxZgVjdDGRgKUvXjuOo8z6HczGRAFKWuMLhcEb9BBEVF2kD5HkeysvLEYvF8n4vy8/rKyLcvENUnAbb6W3btvp69t4Nned5cBwnUCUxwflNNdIUPRQKqfqqd5NxlCUvZiuJipdMLAtZXC8N12VTEJfCiUrLYDvAs1mWpZJZQchWAgEOLPW/R2qo2QkRFY/sC0Ehgz99fGBQSRRMQYwTghE+ExEREdGoY2BJRERERAXBwJKIiIiICiJwNZZSSC+Nzc/WBkTvU6kX4MqmnSAcz0RUqqQ7RDQaVZv4ClEPKeNFLBZTfeyIqDhl76uQ07WG05tSxgLZKBwEgQssgdP968aPH49QKDRog3RpL6SfrNPc3Ix33nkHruvCsiwkk8nAHCxPVGpkcplKpfCzn/0MqVQq79uUi09VVRVqamrUGMMxgqj46F0dZPI5a9YsLFq0CKlUSiWZBuv8IMmrWCym4ohSbz8WuMBS2n+Ypom6ujpEo9Gc35e9c1xeEPv27UNzczPS6TQikYiauRBR8fF9H9FoFJ2dndi0aRMGBgbyHvTlAtTY2IgrrrhCndBBRMVHX7WUILG+vh5VVVVntBzMlaSSmENWN0s9qAQCGFgCp2YQtm3Ddd2MfnO56BcEaYoqx7X5vq/+5oWDqLjIgJ9OpzMmkvlOFPXb8n0fjuPAsqy8Hy8RnRsSH4RCoYwT96QsTkrr5MCUbHrpXBAELrDULxzhcBjhcHjIjEJ25lKancqJHVI/VeozEKJSIxNKOSxBX+7KR/ZJO1Iqw8knUfHJTi7pq5j6eDHY2CFZzCDFCYELLPV0dCKROGvBvv4ikqC0vr4ejuNkpL2D8oIhKiWu68LzPFRWVuLqq69W/86HZDUqKytRX1+vjoFlYElUfPRjmyXrWFZWhnQ6DQDqc4NtzkmlUhkxRhBiBcMP2GgnL4I9e/Zg586dI6p5MAwDkUhkDB4lEY0V3/dRWVmJlStXIhqNFmTg930fHR0deOGFF1iDTVRiHMcZdNk7m4RYkUgEV155JWpqakbzoZ0XApexzIfv+0gmk+f6YRBRgUgQ6TiOWr3QP/9uyOTVdV3Yts1MJVGJCULWMR8MLEeI2Qei0iFF9wAy2orlQ6+l0neDcuwgKg2cLA6NgeUIBWVXF1EQSDBZ6MJ6/SAFwbGDqDQwYzk0BpYjxKwDUWmQHZ7Zfwpx0ZB+d9kndxFR8WPGcmiBDCz1hqa5/j0YfXnLNM2M4l2+0IiKjwSAhW4HJK3I9PZmHCOISoM+Xpxtx7dMWIO0YhHIwBI4fazjcHd2Ach4cUhTZVnuYjaCqLgYhgHLstShBwAKunlHWpAAmbWcRFQ8BgsWJbjUv54rnpA+tjIWBEFwflONzCBisdiIGiLru8L1C9FIglMiOn/Irm3f99Hf368+n28QqO8Ml48ZWBIVn1zlb3IUbPZqR65YQBJQg/W5LEWB7GPp+z6am5vR09ODysrKYS9Rua6LPXv2oLm5GY7jAAAbHxMVMTmGTT+Bq1Dv50gkom6bgSVRccr1vp06dSoWLVoEx3EyemEPNXa4rotZs2ahoqICQGnv1whkxlIyCfLxcAd93/fR09OD1157LaPQPyizEKJSYhiGmhj29/djy5Yt6Ovry/t25eLS2NiI5cuXq7OEOU4QlYZIJIIlS5YAgJo4DrZXQz4XpCRUIANL/YzgcDislqt0g+3ilOPa5GLB/nRExSudTqv38sDAgDp+LR/y8/39/fA8D7Ztw7IsjhNERUrfqCN/S6syPaDMFTNIVlP/+VJfvQhkYClPsm3bqsYq+4nOFVjq2Un5O2i7vYhKSTgczqh9kiAzn+BSXxKTcSTf2ySic0tvSSanasn7Wjbn5XqPR6NRAFCJqCAIbGDpui7a29sHLagdLGOZSqUQDoeRSqUyWgyU+gyEqNTIRcJxHNi2jZqaGiQSibzfyzKeVFVVIZVKqd2gQbmoEJUafaIo40YikVDB4lDJpYGBgYxWhcNtb1jMAhlYAqcG/56enow+c9lyZSzr6uqwbt06WJalboeIipe8r2fOnImysrKCTBJl4trc3KyW1zn5JCpO+hK4vJf379+fsWlnsGBR2o7FYjHMmTMHAJfCS5bUV8ry9lBFt/q/fd9HWVmZSn1LgElExcf3fdXHctKkSYjH4wW5XdkYtGfPHtXHjhlLouKUHVjqLcT0z+UiMYZt2yUfUIpABpZ6jQRwqs5quGRZy/M8WJY1aFBKROe/UCik3sdS0pLv+1mvxZYVEY4TRMVNDy6zJ4m5mqXrX5OfY2BZorJfAFLvMNxsgvSvlDpNIipeMhaMxuAvWUvJVjKwJCpe2XsqsseJwWIImWSaphmYMSBwgWUu3NlNFEzZS1yjcbv630REpY6BJTCis74ZgBKVDv19X8hlqqAseRERZWNgOUK8YBCVDlnSksllIZfBpXny2XaNElHx4ft5cAwskfvg+Fy4C5yo9IxGH1o9YJV/E1FpcF13RHFD0N7/gQssHcdRp21Mnz4dkUhkyJmHfE0uEHv37sWbb76ZseuTiIqXZBWfeOIJde5vPmRXuPSuk9ZkRFQa5syZg0WLFmW8twfrKCEnb8lGviAIXGCpL0tZloVIJDLkjvDswDKdTmPv3r1wHAemaWacA0pExUN6WEYiEXR2dmLr1q0YGBjIe7Io7YUaGxtxySWXAAhm1oKoVE2aNAnl5eUZvSwHCyylnVmQJpiBCyzD4XBGc/OR9KLUXxSRSERlJQrR+46Ixp5pmnBdV/WnBQbPPAyXvkQWiURg2/aIeuUS0flN3/B7tmDRcZzA1VkHLrB0XVfNHmRZfDjZBMlKSjbC8zyEw+GMM0SJqHhImzGZHMrn8qX3xtUDyqBcVIhKXfamP/lcrve4xAlskF7i5DhHmUlIsJmLvhQutVPjxo1TxzPJbRBR8ZELhOM4mDlzJmzbLsjJO77vY9y4cQCgym0YWBKVBt/3kUql1OrnUEvh+ippUAQusJQBPpVK4cCBAwCGPm1Dz0gahoFYLIbly5eP2eMlotEjF4N4PI6ZM2eedTPfcG/T8zz09/ejqampoNlQIjr3IpEImpqazogdBtu8AwCxWAzTpk0bs8d4LgUusAROPfmy+3O4mQQ9lV1ZWTkGj5KIRpu896uqqrBw4ULEYrG8N+P5vg/XddHe3o7W1taCnUFOROcH3/fV8c7DlU6nA5O1DGRgmW0kJ+/w4kBUOmRyKfWQ+iaefMhtAhwziErNSLo8BPG0PgaWGP6LhBcIotIigeTZlrNGQq+54sk7RKWH7cOGxsASDBiJgipXjVQhLhh6IMnxhaj08H09uMAFltkXDlkKG+x7hf4z2fVSQWojQFQq9Lpp6T1ZiFpIyVRKOyP980RU3LKv/UDmKsVgP6NPNEt9LAhkYKlv3Bns5Bx5IegvArkAWZalLhymaSKdTo/1r0FEeTIMA6ZpZvSkdV13RDXXucjYIo3Xh3sAAxGdv/SSFj2OyE465fo5GWNKPaAUgQsspWGxaZqYMGGCetJzDfx6YCkXm9bWVrz11lsAMgv/g/KCISolcmEIhUJ49dVXz7hQvBsyUZXAcqS7R4no/KK3DPN9H+PHj0djYyMMw1CT0sHGDok5pJ9l9klfpai0f7shmKaJcePGIRqNAsg909DT13KxOHDgAHbu3KlO1gBOXUCYkSAqLpKBME0T7e3tePnllzEwMAAgv/op+dlJkyZh9erVAKBO6yKi4pJ9so7nebj88ssxY8YMAKfPAh/s/S0/7zgOIpFIII53DWRg6fs+bNtWxzoOp0G6LH3LUrh8HA6H8+57R0RjT+8vWVZWppa28iWrGHLiThAyFESlTG8dpq9w6qf3DSa7lE6WxUtZ4EY7vYZKL7LPpqe+9dYCcvHRN/0EoRiXqNTI+9ayLADIODAh34ylXHxCoZD6mGMEUXHKtVnXsqyMTX9DJac8z4NpmoFpUxS4wFKCwVAohGQyqWYRw3mypYaivLwcwOmNQOxRR1ScJPirrKzE7NmzkU6nC7Ir3DAM1NTUIBaLcYwgKmK53rexWAx9fX2IRCIqLhiqJC4UCiGVSqmPS13gAktZ+hoYGMDRo0fV5p3h/mwkEsEll1yCSCQC27ZV8S4RFR/DMOA4DqqrqzF+/PiCnL4jGY3e3l4cO3ZMTVyDkKkgKjW5gsXy8nIcP35crXDoKxO5SIazsbExo0VRqQpcYKmnsfX6yuE+yaZpoq6uTl0sZKcXERUfwzCQTqdRW1uLSy+9FNFotCAZBd/30dbWhu7u7rP2uCOi4tPT03NGr+tcgaUEnBUVFWP58M6p0s/J5qDv6B5pJsHzPFWAK30wucRFVHxkA55pmuo9XYjNO3K7Mi5IbRURlQZ98ql/LPGE/kc2+OptC0t9PAhcxlLo6ejhPslSJxUKhTLqpgpxWgcRjT1Zyso+jSuf97N+Prhev80xgqj4DBYjSHJJYoGhNu/om4QLcQjD+S7wgaW8OIbzJMuMQ4p19T9EVHx831cNzOX9ne9SePYFRNqScZwgKj5n23inxwO5VjxydZAp9bEgcIGl3h1fbxkwnDpJvT1R9gWD2Qii4iPvaVGIk3fkQiKbgOQIWNZiExWn7Ou73gP3bF1lJEbIXhUp5d3hgQssZcbgeR5s2844lnG49MwGd3wSFSe9v5z8uxCDvd4LU8YZdo8gKl7Z13cZJ/QNwIP1xJYspmVZgYkVAhdYyrK3aZowTXPEBfumaSIajcJxHITDYVVfQUTFR/rPSXBZiEFfbiMUCqGsrAzA2ZfTiOj8NNT7Vr/+Z69+iHeTvCp2gQssJVvpeR4ikciILySpVApdXV2qMao0SQ/CLISolPi+j3Q6reqmX3vttYydm/nq7e1Fb28vbNsO3IWFqFTkSjxJYkovhRuqjEY6Q6TT6ZJfBgcCGFhK2joSiaCxsREVFRXD3rjjeR62bduGjRs3qhQ4l7eIilsoFEJbWxtef/111ZuuENnFyZMnY+nSpTBNs2DL7EQ0trIDS9/3sWbNGrz//e9XMcBQx7bq54oXqk/u+S5wgaU88Y7jqFmE7ArN9b3yotB3dYVCIcRiMbXrk82PiYqPXhdVXV2t6qXzfT/r/SvLy8vZkoyoBOirnbLimU6nM/pV5spuyiEqlmUVpE9uMSj90DmLvDgkdT3UEy2ZC/2P53lwHCdjAw+DSqLiozcylwbphXgvy5gg4wwPUSAqbnonGX03uJ5wGkr2gSylHjMELmMJnHqSLctSh8IPN5sgae94PK6CUmYiiIqTnrH0fR+xWGzQXnQjvV3f9xGPx9VGQYAN0omKUa5VDDl1T7KUQ/XD1ieu2X2wS1XgAksZ3BOJBA4ePAhg8CPX9ForedFEIhEsWbIE0Wg0o2C3lF8kRKVKgsjy8nLcfPPNqh4yH6FQCMlkEuFwGAMDA0ilUhwjiIqUnmWUa35dXR3a29vPSCwNNnZIfaW+g7yUBTKwlHqIVCqlspC5XhC5AkvTNNHY2JhxpGOhltCIaGxJjXVDQwMuueQSlJWVFSSz6Hkeurq6sGnTJnWQQlDqq4hKSa7m5r7v4/jx4xl9rAfbzCtjTFVVlRpbSn1fRuACS0lFywtAelnmkv2C0i84+ikapfwCISplMlmUInz5XCHYtq0uPAwqiYpTri4REhsMZ4e3rHTqezNKXen/hkREREQ0JhhYEhEREVFBMLAkIiIiooJgYElEREREBRG4zTuyG0vOCJYdm4N9r3y/FN3KiT2yMwxAIIpxiUqRtAaKRCIACtNrUjbs6OcISy9LIio+sqFP7wQjnWUsy8polp5NelhGo9Ehj34sJYEc7Xzfh2VZmDBhwpAn5+gXGfm+Y8eO4cCBAwiHw4hEInBdN2OHOBEVl1AohN7eXjQ3N6uG6fmQXeChUAiJREKd7lPqFxOiUqUHlp7noba2FpMmTVJN0odKUElrwkgkEpgkVOACS8Mw1IuguroasVhsyO/Vs5K+76OpqQkvv/wyUqmUesEE5cVCVIpCoRB6enqwbds2JBKJvG8vHA7DcRxMnjwZS5cuzVj5IKLiI6uWcsrO6tWrsWLFCnXtH6pXrcQO8j1BGAcCF1gCmRkFCTQHIxcEvWO+aZpqWVyfyRBR8ZDyFs/zVC/LdDoNx3Hyvl3f95FMJjPGGiIqTno5nO/7sG0btm2r8UMCx1z0Q1jyHVuKReACS8kwep6X0bA0VxpbDxYlgPQ8TzU+DoVC6oUWhFkIUanJPo6tEI3MZYzR/2TfFxEVj+xzwsPhsNprcbam53q5XVDGgMAFlvJCsCwLnZ2diMViOY9k1I9eApDzhSGbgHgOMFFxcl0XlmXBtm0ApzMT+VwA9OWxdDp9xueJqHhJaYtsAJYVicEmpfrKaFDGgMAFlpJhdBwHx44dUzu6RmL27NkZFw8GlUTFy3VdVRMpF4t8hUIhxONxVFdXq9WQoGQriEqdZVloaWmBZVlnDSwBqAzn5MmTVYBZynFD4AJLAKoewrbtERfWV1ZWYsmSJap2KmgpbqJSIdlJx3EwadIkXHzxxYjFYnkP+I7jIBQK4cSJE9i2bZuauHKMICoNkrGUFUtpXZhrUmrbNgzDQEVFxaBld6UmcIGlBJKhUAimacI0TdUOZLikPjMcDhekPQkRjT293GVgYEB9XIhMgtx2X18fLMtiuQxRCZHNu67rwjRNOI4zaBwgu8Uloyl/l/KyeOACS/3J1Iv1h/MkyxK67PKSrCUDS6LipG/m09/L+bynpd2QfKzvHCWi0pC9YjlUP2x9g08QJpiBCyxlgNczl0PNNrJJ2wBZQjNNM+9ifyIae9lLWHpWMZ/BX8YVuX29TQkRFT95L+vX/8GSU/pkVSawpZytBAIYWOovAMdx1DLVSH5e/pYgk4iKj9RaF6LFUPbtysUmV8cJIip+cv3P7nWdTf+a1FeW+pgQuMBSMgdyfi97zBEFl9RIAYUdA/QxhoiCS09gBWWiGchRT55YyVaw/okouNLptNq5LdmFfJfCJZshY4xpmhxjiALIMAzYtq0mmYUYY853gQ0sI5EIqqqqAJT27iwiGpwEfpWVlQXrLSfjSSgUQnl5OWzbHnHJDRGVBukiU1VVFZizwg0/YNNo+XUdx1FnfRJRMEl9pZzGZRhG3n3mpLZSzgvncjhRcMl4EAqFCjbGnO8CF1gSEY22Ul/qIqJ3JwhjAwNLIiIiIioIrgMTERERUUEwsCQiIiKigmBgSUREREQFwcCSiAhAZ2cnent7C3Z7bW1t6O/vL9jtjZbsMnv937KjVT7OPp6OiCgbA0siCiwJlnzfR29vLxKJRMFuu7u7G8lksmC3Nxr0HarS0F1OCJGv6V8X+ueJiHQMLImIAig7MymBpB5c6lnJ7ECSgSUR5cLOvUREAaRnIrMzk3KmcSgUUoGmHCahN5VncElE2RhYEhEFlASR4XAYnuchkUjgtddew+bNm9HV1YWJEyfigx/8IKZNm4ZIJKKOpGP7YyIaDANLIioKuU6skKPS5G/5nuzv1T/v+/45P8pVX3oW2RnEXN8PICNzmO/vIdlI3/fR2dmJ5557Ds899xxc14Vpmnjttdfw+OOP45Of/CTWrVuHCRMmqExl9lK6PCY5ri67fjP79znXzwERjQ4GlkRUFPRAyjAM9Pf3I5FIoK6uTi3dOo4Dy7LUz9i2DQA5z+uWnzlXsoNcCfLkMTmOozKEAHDw4EE0NDQgEokU9HEYhoGBgQE89thjaGtrwze+8Q3U1tbCdV20t7fjC1/4Au6880588YtfxO233454PJ7xXOSq1dQ/rwf1AM6YBBBRaeGUkYiKgp7hcl0X+/btw5133ol77rkHr776Kjo7O1UA43meyrpZlgXf9+E4DlzXBXDuMmYSXEnNomRb5fHoO7LT6TQOHjyIJ554At/5znfwta99Dd3d3WfURObzWCS72NfXh9/85jeor69X/y+WZaG+vh7XXnstPM/Dgw8+iK6uroyAUQ8qXdfNCB4dx4HjOBlf039PLqcTlSZmLImoKEjQJR/39/fjgQcewMMPP4z6+nrMnz8fl1xyCdauXYulS5ciGo2q7JhhGAiHwxmBz7nYfJLr/rIf19GjR7Fp0yY89dRT2Lt3L/bs2YOBgQFceumlajNNOByGbdsZ2dl3Q+63ubkZmzZtwquvvory8nLcfPPNcBwHhmFg8eLFqKmpQXNzs6q7lCBRajPld3NdV/1bMqt6EK8H1sxWEpUmBpZEVDQk0xUKhdQycTKZxKFDh3Dw4EE888wz+J//+R+sW7cOl112GS688EJMmzYNVVVVKjsInFoal6XnsZCrX6TneTBNE47joLW1Fbt27cLevXvxwAMPYM+ePejp6UE4HFYBniz1y+dyLe+PhDyedDqNqqoqrF69Gq2trairq0M6nVaBudynkP/DdDqN3bt3I51OY+bMmairq4NlWSorfPLkScRiMZSVlcFxHLS3t+PIkSOYM2cOKisrM3aaE1HpYGBJROc9PdOlt8ORz+mbUA4dOoSf/OQnuO+++zBlyhTMmzcPl112Ga6++mosXbo0YxPPuXj8wKn6yZ6eHrz44ot48sknsWfPHrz55pvo6upSAaSeoZVgVLKE+m7ufNi2DdM0sWDBAvzoRz9Cf38/5syZo+7DMAwcOnQIPT09GD9+POLxOFzXRSqVwn333YeysjLs378f7e3t+Pa3v41oNArLsrBv3z587Wtfw9q1a3HrrbfCdV3cd999ePjhh/GVr3wF1157LTOWRCVqzANLqXUyTfOMHYPZRd1jPfCwPxvR2MsOGof6PslWSh2ifkIMcPo9DACpVArNzc1obm7GU089hXvvvRc33XQTVq9ejTlz5qCxsREVFRVqeVluK1/6Jhw9gJXNMG+//TZ2796N3/zmN9i+fbsKJrNPttF/H/m99SzlYP9f8r2u6551PNU3Ak2bNk19LDWq6XQaW7duxcDAAG655RZccMEFME0TL774Ig4cOIC77roLjz76KB5//HEcOXIE8+bNAwC0trbi8ccfx/ve9z4VKEejURw+fBiHDh0qSFBMROenggSW2bNx+dxgwZm+/JErmJMLx7mqf2JQSTS2hmpNA5w52fN9f0RLwZ7noaWlBd///vfxox/9CNOnT8e8efNw+eWXY+3atVi0aJEKgPI9A1uCpkgkAsuy0N3djZdeegnPPfccduzYgV27dqGzs1N9rx74DRbYhsNhFSzqS/i5vl8PvCUjOdLHL4GlLM1feeWV+NznPoeysjIMDAzgoYcewt/93d/BMAxs3boVruuivLwcwKnnatu2bXBdF8uWLQMAlJWV4VOf+hQ2b96MyspKdT9cCicqPQXLWGZfGAYLLLOzAjKjzs46nIvgjgEl0dhyHAehUEjV3wGndiNnB3eSmkSttQAAIABJREFUndQDkb179w77fvTALZVKYffu3dizZw9+//vf495778UNN9yA1atXY9asWWhvb8/rd5LayaNHj+LZZ5/F448/jq1bt6K1tfWMXprZ/TXlsea6zYGBARw6dAgdHR1qt3WuwCyVSiEajarl7MmTJ6OmpmZEj98wDHR2duKee+7B9OnT8R//8R9obGxUt/+e97wHCxcuxDvvvINnnnkGq1atwsSJE9X4/sILL2Du3Llqo49hGKisrMTChQtVlpiISlNBl8JlQBoqW6kvf+QqaDdNc8z7m+UKioHcgzYRFY4EP5Zlobq6Gul0WrXh0cn4IJk73/cRj8eHfT/6hFZu2zRNLFmyBOvWrcNFF12UEfDksyQujzUej6OhoQFXXXUVYrEYNm/ejKNHj6pNK9mT6aHuW3a1m6aJSCSiTsHJ9b1SBxkKhWBZ1ogzluFwGH19fbjrrruQSCRw9913Y+bMmeox19bW4lOf+hR838dLL72EY8eO4WMf+5jaUNXS0oIdO3bgiiuuQDQaRSgUgm3bail/7ty57+J/lYiKRUECSxkc9eLywQJDyUScPHkSPT09SCaTcBwHs2bNUq0zxrrGUb8v2QVpGEbBGxET0Zl830d1dTVqa2vP2Jij03eEe56Hrq6uEd1POBxGbW0tpk6dioULF2LJkiW48cYb0dDQgGg0iiNHjsA0TYwfPz6v8UeCvWQyicbGRqxfvx6f/OQnsX37dvzud7/DG2+8gXfeeQdHjx5FOp3OyFQOtgzveR4ikQgmTZqEhoYGdT+DBaESSL+bOsZkMomHH34YfX19+Pd//3fMnDkTANDe3o6KigpEIhEVvD777LOYOnUqFixYoO7zT3/6E5LJJJYtW6aW703TRGdnJ3p6ejBz5sxz1u6JiEbfkIGlZAgAnDG71gct6b329a9/HePGjcO//Mu/oLy8POegJktfW7ZswW9+8xu8/vrrGD9+PH7+85/jggsuOGeNc6Vu6fjx4/jxj3+MgYEB3HnnnWoph9lLosKTTNxg/xbZp7vo9dASpOhBjLTI8TwP8Xgcy5Ytw/ve9z5cdtllmDFjBqZNm4ZoNJqxFK33vMxXKBTKaMgej8exZs0arFmzBp2dnXjnnXfQ1NSETZs2YcOGDTh27FhGsKUHmLlOstHvJxd9V/fZSHYTOLXMfffdd+PEiRP4/ve/j0mTJqkA9pFHHsHatWtVYHjy5Ens2rULCxcuRGVlpWrh9M4778A0TcycORPxeFz9/JYtWzBv3jyVQOCYSlSahgws9aWZszW23bp1K+655x40NDTg2muvxSWXXJLzNmVQWbVqFWbMmIF//ud/RlNTU8YgqN+vftEYrSVy/XfbtWsXfvGLX6CrqwtLlizBrbfeqgr6XddFNBpVQSiPJSMaW/q54BI4SmCotxyqq6vDrFmzsGDBAqxcuRIf+MAHMHnyZPWelV6Q2cvJhcii6WU1uTYEjhs3DsuXL8eyZctw44034rbbbsPmzZuxefNmNDU14dChQ+p79SVyCZxlQ87ZHufZvi7jq9xPOp3Gxo0b8dZbb+GOO+5AVVUVent74fs+BgYG8Pbbb+PKK69Ut+26LhKJBKZNm4aysjJ4nof+/n7s27cPlZWVmDFjhvo/7u/vx86dO3Httdeq56AQvTiJ6Pwz5LtaH5j0ATfX4LtkyRLcdtttmDhxoqrHGYzjOGrpa8qUKdi3b9+g35td/zgaQZxePD9v3jx8+MMfRk9PD5YvXw7g1Ozfdd1BT7lgcEk0urJ3hANQJSsScFVVVWHp0qW4+uqrsXz5csyZMwcTJ07MOF9cX2kZy4yZvkFRsrK+76OsrAxXXHEFVq1ahdtvvx0tLS3Yv38/nn32WTz55JNobW2FbdsqkDNNU9Wg5ruyI49F6h9fffVVfPWrX0VZWRm+8pWvIJVKqQxuKpVCXV0dqqur1c/GYjGUl5ejr69PBcC9vb3Yt28fbNtGf3+/uq+NGzcikUhg9uzZSCaTiMVizFgSlaghA8vsVkDZg6MwDAPTpk3Dt7/9bVRXV591Ni1n96bTaTiOM+gAaRjGGX3bRotpmrBtG1OmTMGXvvQlhEIhVFZWIpVKqUJ5kb1Ux6CSaPTpqxfysWQmL7roIixZsgTXX3896uvr1c/oPR317KS+K3us6LvBswNlPTBesmQJrrvuOuzYsQPPPfcctm7dir179yIajSKVSqnfoxATWjkW8vDhw/jmN7+psqX6UY3yf/eRj3wEFRUVGbu8P/7xj+OPf/wjHn/8cVRVVeHo0aNYtWoVotEoHnvsMXR3d8N1XezatQs33XST2q0uJQIcO4lKj+EPMbLKwCIDcDqdhud5sCzrjLooGXzS6TQsyxpywJA+aaZp4m//9m+xadMmPP/885g4cWLG92VnJobaFJQvqf2U+5XBL/uiJEG1BMTDWZIiovxl11m2traiqakJjY2NmDJlihof9FpFveejvnQO4Iyztg8ePIh4PJ4RmOajqakJtbW1qKurU49ZD46Fvpwv46Je93jy5EkcOHAAAwMDeO9736t2w+eb8dNLB7q6uvD666+rcS4ejyOZTGaMudIuSDp3uK6LZDKJ3bt34/Dhw0ilUpg5cyYWLVqEEydO4O2330ZHRwcaGhowd+5cTJgwQdW1ptNpxGIxjp1EJWhYS+EdHR146623cPLkSXiep5axU6kUlixZgpMnT2LPnj04efIkIpEIli5ditra2ozMpud52L9/P/bs2YN4PA7LsrB48eKM9iHZ2YTOzk5s27YNiUQClmWhpqYGK1asUIOTPhBns20bLS0tqsZHBur58+cDALq7u3Ho0CFEo1EMDAygpqYG9fX1ePnllzEwMADP87B48WI0NjZmBJXd3d145ZVXMDAwAMMwUF5ejuXLl6O8vByu6+Lo0aMYGBhQv5PneZg2bRoOHz6sGien02lMmDAB48ePx4kTJ9Dd3a2WpBobG9VyExGdlp3lmzRpEiZNmpTxuewMpQRB+m3I90QikTHNWOrjoT7W6Y9bHq+e1aytrUVNTY2a0OoT4HwCMwm0pSZ17dq16mv6+eD6fUjnD8MwVIJh+fLlqqZekhEzZszA9OnTM3ao689NLBZjCRFRiTpr5XRPTw+++c1vYsGCBVi8eDFc10VfXx++9KUvYcKECfjP//xPdXzXE088Acdx8OCDD6K6uloVyCcSCXzrW9/CkSNHcM0116C2thYtLS3YtGkTDh48mLETXAahLVu24Dvf+Q4uv/xyXHbZZUin03jggQewYcMG3Hnnnaiurs6oVcoeoPr7+/H8889jw4YN2Lt3L+rr67F+/XrV1qi5uRnf+MY30NLSgvnz5+MTn/gELMvCE088gQ0bNqC3txf33HMPpkyZoorM9+7diy9+8YtYsGAB1q9fD9u28eSTT+K+++7DXXfdhfHjx+PVV1/F448/jldeeQW1tbW48cYb8Zd/+ZfYtGkTfvnLX6KtrQ0XX3wxbr31VqxZswZvvPEGvv3tb6OtrQ2rV6/GHXfcoU6mYA0SUW653ht64DZYCc25bnGT/bgHa6s02OcKXRqUq2do9v3ossuAsn9W/3f2Zszs22BQSVSi/EF4nucnk0n/tdde86+//nq/ra3N9zzP9zzPT6VS/t133+3feuutfk9Pj+84jn/06FH/5ptv9hsaGvwdO3b4vu/7ruv6AwMD/g9+8AN/6dKl/m9/+1s/nU77tm37/f39/q9//Wt/5syZ/nve8x7/yJEjvm3bvuM4/t69e/2rrrrK//CHP+x3d3er+3zhhRf8+fPn+z/72c98x3F8z/PUz2RzHMdPJpP+gw8+6E+dOtX/yEc+4h8/fjzjaw899JD//ve/33/llVf8ZDLpu67r9/X1+Z///Of96upqf+PGjb7neb7jOH5ra6t/xx13+GvWrPEPHTrku67r27bt79q1y1+6dKn/xS9+0e/p6fFTqZS/adMmf+LEif6qVav81tZWP51O+ydPnvR/+tOf+hUVFf7DDz/s9/f3+47j+L29vf53vvMd//LLL/d37Njhu67rJ5PJwZ4WIiogGdM8z/P379+vxohC2Lt3r9/e3l6w2yMiKgaDpsSkQbg08j1y5EjGss373vc+NDY2qgxjdXU16urqMpZ6PM/Ds88+i+9+97u4/vrr8cEPflAV3kejUVx77bWYPXs2EomEyj6mUin84he/wJtvvom/+qu/QjweV8syy5Ytw5QpU/DTn/4U/f39qjYpV987WQa75ppr8P73vx979uxRR7XJMtM777yD2267DRdddJGqlbQsC42NjWqDkSztbNiwAY8++ig+9rGPYfz48ep2Zs2ahXnz5uGpp57C0aNHYVkWli5divXr16O1tRXHjh1DKBRCRUUFFi9ejHg8jq1bt6raLjnt4/bbb8fChQtVPSkRERFRsRlyrdX3fcyePRtvv/02/u3f/g0//OEP8cgjj+Ctt97CxIkT8dnPflYFRnorIr0G6JFHHkFXVxeuuOKKjKDT/3Mfs2g0qpZdbNtGT08PtmzZAtM0EQ6HceLECbS1teHo0aPo7OxEZWWlameh747MJhuE4vE41q5di5aWFvzud79TNULt7e146623cM0112QsqUcikYw6olAohGQyiY0bN6K/vx8TJkxAT08Pjhw5giNHjqCrqwsTJ05Ec3Mz2tvbVa/LD33oQ0gmk3j55ZdV8L13715UV1fjmWeewfHjx2EYBvr7+/HOO+/giiuuUMtS56pJPBEREVE+hqyx9H0f8+fPx/e+9z3cfffduOuuuxCJRDBhwgQsW7YMX//619X35mpU3N7ejldffRUVFRWYOHHiGXVCsrtR6p5M00R3dzdOnDgB13Xx5ptv4sSJE6po3bIsXHzxxXjPe96DSCQy6PFnwOmd7IZh4JprrsHMmTNxzz334HOf+xxM08SOHTuwZs0aVaupb/KxLCsjc5hOp3H48GHYto3t27ejs7NTfd11XdTX1+Pv//7vMX78eHW/a9euxaxZs/Cb3/wGf/EXf4FQKIQ//elP+OpXv4q77roLmzdvxkc/+lG88cYbmD17NiZOnKh2g57rOjAiIiKid2PIwFKOJLv55ptx4YUX4qmnnsKBAwfQ0tKCp556Cg0NDbjrrrtQXV2dkWnTgzrZxahn4QzDQDKZVDsg9YBUdhqWl5fjmmuuwfz582GaJtLpdEZBuX6CRi6+tgOxvLwcV111FX72s5/hpZdewurVq/H6669j7dq1atei3opE2mzIfUj21DRNfOADH8Bll12m+rCZpql6y8nv4/s+qqqqsGTJEvzqV79Cc3MzkskkAOCKK65ARUUFtmzZgvXr12Pbtm1YuXKletyF7FFHRERENJaGXAoPh8N44oknsG3bNqxYsQJf/vKXcffdd+P+++/HP/3TP+GXv/wljh49qr7fcRz1sed5qKmpwaJFi5BMJnHixAkVLNm2rTKOeisKwzBQUVGBCy64AMlkEh0dHYhGowiFQigrK4NlWer75W9g8F2U+nFo1113HWpra/G///u/OHHiBI4dO4YFCxao75Vlb9/3EYvF1BGOEqBOnTpV9ee0LAumaSISicA0TVRUVJxxf4Zh4CMf+Qj6+/vx8MMP45VXXsH69etRX1+PG264AZs2bUJzczP27duHqVOnwjTNITOwREREROe7swaWfX19eOGFF+A4DhzHQTwex4QJE/DRj34UqVQKAwMDKsCT7KEs58oGHc/z8NprrwE4FXBKUCkNduXn5bSbVatWwXEctLS0qOAunU6ro8XuvfdeJBKJjF6R2SQglPtctGgRLr30UvzpT3/CfffdhxUrVqC8vFwtZ8v3SZZTAk3DMBCPx7Fu3TqEw2E8//zzatlcMq3pdBqPPvooDh06pDK0vu9j6tSpWLx4MTZu3IjW1lbMnz8foVAIH/zgB9HR0YFnnnkG48ePx/jx4884V5jZSiIiIio2QwaWtm0jGo3it7/9Lfbs2QPDMNTJOvv27cO8efPQ0NAAz/MyjmdMpVIqG/mhD30IH//4x/Hggw/irbfeUoGg67p4+OGHsXfvXiQSCXWqj+yQvvLKK/HTn/4Ura2tAKCWmZ944gns379fbbIZLAiT+5efHTduHD7zmc9g586deOSRR3DNNdeoHep6gJpOpzEwMADbtpFMJuF5HhzHwfr16/GJT3wCDz30kAqS5ed+//vfY+vWraitrVWZR8MwMGHCBFx++eVobm5GfX09xo8fD9M0MXfuXFx00UW4//77sWzZMkSjUfW45f+Qm3eIiIio2IS/8pWvfGWwL4ZCIbzyyitoampCKpVCe3s79u3bh507d+KFF17Addddh4svvhhNTU247777sG3bNvT29qK/vx8nT57EggULUFZWhlmzZmH//v1444030NnZif379+P111/H4cOHsX//fhw9ehRdXV0AgFmzZqGiogLz5s3D3r17sXPnTrS2tmLnzp1488030dLSgttuu01l+QZr8CtBnx40TpgwAY899hjWrl2LG264ISPbaRgGjhw5gh//+Md46aWX0NHRgf7+fiSTScyZMweVlZWYO3cuWlpasH37drS3t2PXrl3YtWsXdu/ejWuvvRbz589XJ37IZiMA2LFjBz7zmc9gxowZ8H0f0WgUBw4cQHd3N/7xH/8RZWVlADJP0tAzrkQ0+rq7u2FZFsrLywtye52dnYjH4+r9TUQUBEOeFS5HFEr27+DBg+jq6kJNTQ2mTJmCGTNmIBwOo729HYcPH844pqysrAxz585VGcWenh4cOnQITU1NsCwLEydOxLRp07Bz5051m42NjZgxY4ZaYu7p6UFzczNaW1uRSCQwdepUzJ49G7W1tWdsEspFr3mUx7V7927U1dVhwoQJ6vPyPT09Pdi3b1/GbZaVlWH69OmqvrK3txctLS04cuQIent7MXXqVMyaNQvjx4/P2KAkt5FIJLB//37MmDEDsVhM3efx48eRSCQwY8aMjMenB5ZcDicaffKePXjwIKLRKBoaGgpyu3JW+Lhx4/heJqLAGDKwlGyeBF6u68LzPJWJe7fBj34OrdwugIy6RX23uGzUkZ3a+cj1647kd9CbxMtu8sEeU773RUSjSx9nOjo6YJomampq8r5NADhx4gTKy8tRVlbG1QciCowhA0uhB1ESBL7b83f1ukjZSa3/vP5w5H6zG7DnI99gT7K3w3lMDCyJzm96jbV0tZCJ87slE085xGGw08GIiErRWQPL7MyhHlDJ14HhB0xyG3pto/ydnQHV73sk93G23yfbSDOWw12uZmBJdH7TA8tCvTezx6vskhwiolI2ZIP0bNJEXA+YRtoaJzvTCeQeePWNNXqD9XMdmJ2Pj4mI3p3RCPiyxwMGlUQUJMNeCs/us6h/Lftzw7k9qbPMlS3Ivs3RyCbo3u1tjzRjyQCU6PzFSSIRUf6GFVgSEREREZ0N12iIiIiIqCAYWBIRERFRQTCwJCIiIqKCCGxgydJSIsrum0tEVEhBHFcCF1jqp+Z4nqcavhNR8Ojt02RsyJfchty2NF4nouCREwuB4ASZI+pjWQpyHcMYlCebiDKFQiG4rqvGg1yHQIyUjDH6fXCMIQom6f8N5D4IphQFLrDULyS5jpQkouDwfR+mWdhhUMYY+VgyoWyUThQ8ElTqH5d6vBG4Ppb6Unj2ueVEFBwyDkgWwTTNgowH+pK6LINzjCEKJj2YzF4tLVWBy1jK4H7w4EG0tLTAsiwuVREFlO/7sG0b48ePx+zZs1FeXp73bcpyent7O3bv3p1xyhgRBYskscrLyzF//nxUVVUBKO2sZeACS+DUxSSVSqGtrU3VP5Tyk0xEuUm20nVdzJkzpyC3GQqF4HkebNtGa2vruzr2lohKg7zve3t7MW/evECMA4EMLIFTT3YoFGIWgSjA9NWKQg34cjvyN8cYouDSy2CCEFQCAWw3RERERESjg4ElERERERUEA0siIiIiKojA1VhKPZXruqpof7itQKSNiP793PhDVNz0lkOyo7sQpL2IjBl6PzsiKl5Sm60fqCD/zibfI5v6giBwgSVweuNOOBxWL4jhthuSi45hGHAcR71g2K6IqPjovSwL1WtSD1TT6TRCoZDqkUlEpUGOhQaGPl1LDmCQ07iC0CUikIElcLp/HYCM49fORs7/tSwL4XBYnbBRyi8SolIkKxaSSdADwnzI5NM0TZimyYknUYmRVQh5rw/1/rZtG77vIxKJjNXDO+cCG1gCUBnLkSx9ydJ5KpViFoKoiBmGAcuyMspZClHa4jiOWtHg+EBUerKXtGXcyBVL6BNNAAWZvJ7vAhlYuq6rspXAqQvBcGof5CKRTCYRiURUkBmEQ+WJSlE6nVZB4LFjxzKOdcxXR0eHapQ+0gksEZ2/QqGQOrVPXxKXFczBvleUerwQuMBSZhYVFRWYPn064vH4iGos33zzTWzcuFEFkyP5WSI6v5imiXA4jOPHj2PPnj3o7e0t2Pu5vr4eixcvhmVZ6sxwIipuvu/j8ssvx5VXXolQKKTe27JvI5usXLiuq7KWpS4Yv6XG932Ew2HYto1YLIZoNJpzljEY0zRVnWXQuukTlRrbtuE4DqLRKDo6OpBIJAqyhG0YBmKxGEzThG3bzFYSlQBJJKXTaVVGM1hAKaQzRDQazUhElXLcELjAUgJD4HTx/nBJ+xCpzZSWRcxYEhUn/axwvf1YIcimHcdxYFlWQW6TiMaWHghKFwm9xEVigcFKaCSjqXegKHWBCyyBU0+w3jZouMGl1Ek5jqN2hsuuUiIqLjLQW5ZV0ExC9m3JRDQIFxSiUpMdWAKnS2jk/S0xRK4kU1lZGTzPg+M4I+pAU8wCF1jqzYp7enpUO5DhSqVSmDBhAtLptFpSZzaCqDg5jqMuEitWrEA6nVbZy3dLCvrr6upQXl7OjTtERSw7sHRdF67r4ujRo3BdVwWWgwWN4XAYjuMgEolg8uTJY/nQz5nABZaSNUin02hvbx9RxlGyDsuXL1dZCd/3A1OQS1RqXNeF53mora3FjBkz1CQxn+yiTFx7e3uxd+9eeJ6n6qyIqLjoy9f6Kkdvb686AEE25uRa/QyHw0ilUqiqquLJO6VMlrGlqH4kdZahUAhlZWWj+OiIaKxIHWRFRQXmz5+PeDxekNt1XRcnTpzA4cOHC3J7RHR+kRpLKa0bqn4yGo0W9LjY810wfsscuKObiEYbs5REwSZjQJDGgsAGlkRERERUWAwsiYiIiKggGFgSERERUUEEMrCUglses0YUbDIO6F0eClELFQqFVEE/wFpuoqAyDEONMQAKNsaczwK3K1zvQyVtQUr9SSai3OSIV2kZVoidm9KSRO9tF5Q2I0SUSdqNZZ/6V8qTzcBlLPXd4OFwmIElEalgUk7TyIf0u5WLRxAyFEQ0OD2QDMKBCYHLWEoWQfrXASj5J5mIcjMMA8lkUvWyLVTGMhQKZTRVZoN0omAKh8NIJBKIRCIFPTr2fBa4wFLOBrcsCzU1NapzPhEFj+/7iMViKC8vh+d5BQkspcTGMAxUVVWpgxi4HE4UPIZhIBKJqINV5JSeUmb4AZxGS50lgMAcCk90PsqevY917ZHcn5wZLvVQhSBlNmOdrdQ3CehL8qWcISE636XT6cCcwBPIwJKIzg+yNCQDrQR49O7pgaV+1BwDSyIaCxzBieickWAnnU4jHA6r7B6DoHdPzjAu9awIEZ2fOPIQ0TkXDoeRTqe5waUALMtCMplEKBRCOp1mtpKIxhQDSyI6Z2zbhu/7OH78OH7yk59g69at5/ohFb2+vj48/vjjOHjwoOp+wYCdiMYKA0siOqd2734bDzzwAN56azfi8TIGQXkKh020th7Hz39+H/7whz/Acdxz/ZCIKEBYY0lEBec4jtpdfXp3MgDfQCh06nO9vf144IEHsWPHaygri8O2PRgIw0AIYxVbGgBc10MoHIJtO7BME0ae02390IXMZeixWY42YCAaLUNH+wE89NCjeOGFrbj55r/E3Llz1GPyPA+WZamNPQAyNlEREb1b3BVORKNC+jaeWo4F/D+3cXRdF2+/vQd/+MMf0dTUBM/zYJom+vv7cfnll6Omphqel5ll832g8GWCxp+DLB+XXbYCDQ31p+4nz9hKhtSBgQFs374dXV1dMIwwkOdIO9T/QebXDOzY8Rq6uroAAI7roKamCuvWvR8XXXQRqqqqMtoq6S2JiIjyxcCSiApKb28jTcfDoTAAA52dXXjqqafx3HPPwTRNxONxAFBNxH3fh23bY9ZySM70/n//77NYvHgRYOQfwEpNY0dHB/77v/8bBw4cQCQSB/yxCdzk/8+yrFP/r+EQwmEDPT0nMWnSJNxyyy2YPXs2LMsCcPosY55ERkSFwKVwIiqo7HOyT+34tnFg/2E8/fTT2L17N+LxOMLhsAoopd+iaZrq58aCaZr/v707eGnkiuMA/v29mWTGXEQxEwmS7MGyaemSiwXFuof2TxCUsv55Xbyk24M3YXcFI/S0vUlvQht60lOJmXHem9fD5E0MtNAyk9nL9wPeFMc5hK+/3/u937wFLDDGwvOkso61qwjmfxNQVyu81WohjuNi44cIkDzF2NjYwMPDA87Pz3FwcID9/X2sr68XP8dWOBFVgcGSiCrlKpVAXg2L4xij0U+4Gf8CESmCj1IKnuctrThz5xPrCjhKKWitV9RqzzWbTdhMyvfY/yNjDJrNJpIkAQD4vgcRwePjI4IgwHQ6xWg0wvX1NY6Pj7G3t7dUYeY2MiIqg8GSiCrngqELjMPhEH/8/icmkwmAediydmmIBFgM/dS1V3uxpWbxVTZfuoBmjFmsj7X1VQLdu1tUYxWUCKw1xTGFtbU1DAYDRFG09Nw8Z0lEZTFYElHlXEARETQaDQyHQ3yx+xIfPnzE5eUljDEIwxBZlmE2m8HzPPi+jyAIirb4qllrobUJJ1MqAAACUklEQVQGACgF+L4gsxbWSqnqpTEGnudBKVWETN9vQEk9lUAX2K2189BukCQJgqCB6XSKnZ0dnJ6eYnd3d2lohwM8RFQFBksiWjkRoNUK8fr1t2i327i6usJkMikqlm5wR2uNJElqa4VrrREEAZLkKb92SJULlcAiVMdxDCBfV6nTLJ8Mr4H7/b7vI45jeJ4q3vHR0REODw/R6/UgIkVFmTOcRFQVToUT0cpZCxidD8dYC8xmMcbjG1xcXCBNUzQaDcxmM5ydnWEweFnbc4kAaWrQ6Wzl1b35IE+ZcJllGZRSMMbg/v4+bz9DwdYyFW6Rphrv3v2M29tbhGGIp/QJ3e423rz5Af1+f6mS6o4dcGiHiKrCiiURrZwA8LxFYMurl4fY3o7w/v1H3N3dIbMZNjc30em0oVR9Ldksc1PhqKRi6Vr5IoIoivIKYo3/vidJft2Q3/ChPIXvj77D/sE36Ha7xfeIyNIVQw7b4URUFoMlEa1cNr/bUYnAAlAiCNdCvHr1Nb78aoDx+AZvf3yLWTyFUlJfDnPj4AJ4+VWblXh+TjQPb/WGtenjX3jxooeTkxP0+z0YoyEiRSXVPdfzEOnOZnIqnIjKYCuciCr1bx8p/1QJyzILY/R8G89v6HS2EUVthpsStNb49OlX9Ps9bG1tFdPerEQSUR0YLImoUv8nWLqqmda6CD8871eOe/9uMryuLUZERACDJRF9Rs839HBndbX4Lonoc2CwJCIiIqJKsOdERERERJVgsCQiIiKiSjBYEhEREVElGCyJiIiIqBJ/A2L7TmGUV31yAAAAAElFTkSuQmCC"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:0ebcbb43-c944-42e1-bf82-26894ad4513f.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Test setup with symmetric debonding"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the test setup, a TRC specimen with a notch on both faces at the middle section is clamped using hydraulic cylinders.The proposed test setup induces high transversal stress into the anchorage zone of the specimen. For non-impregnated yarns and yarns with a flexible impregnation, e.g. styrene-butadiene, the bond characteristics are not influenced by transversal pressure if the concrete remains uncracked in longitudinal direction. Due to the low stiffness of the yarns in comparison to the concrete in transversal direction, the transversal pressure is transferred by small concrete vaults, forming around the yarn channels."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![image.png](../fig/trc_carbon_crack_bridge_study.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a id=\"trc_test_results\"></a>\n",
+    "## Test specimens and measured results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![image.png](../fig/trc_carbon_crack_bridge_study_results.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "| Material parameter | Value | Unit |\n",
+    "|:- | -:| -:|\n",
+    "| matrix area | 1543 | [mm$^2$] |\n",
+    "| matrix stiffness | 28.5 | [GPa] |\n",
+    "| reinforcement area | 16.7 | [mm$^2$] |\n",
+    "| reinforcement stiffness | 170 | [GPa] |\n",
+    "| bond perimeter | 10 | [mm] |\n",
+    "| specimen length | 200-700 | [mm] |\n",
+    "| fabric strength | 1300 | [MPa] |\n",
+    "\n",
+    "The details of the test setup, test results, and bond-slip law calibration are presented in [Li et al. (2018)](../papers/Li_Bielak_Hegger_Chudoba_2017.pdf). The paper describes an automatic calibration of the bond slip law. The resulting bond-slip law is used here to reproduce the length-dependency of the pullout response of the cross section described above. Let us note the unusual shape of the pullout curve exhibiting a first peak followed by a small drop down and subsequent increase of the bond level. This kind of behavior explained by a so called jamming effect due to increasing the lateral pressure in the interface zone between the fiber and matrix."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib widget\n",
+    "import matplotlib.pylab as plt\n",
+    "import numpy as np\n",
+    "from bmcs_cross_section.pullout import PullOutModel1D"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "\n",
+       "        \\begin{array}{lrrl}\\hline\n",
+       "        \\textrm{E_m} & E_\\mathrm{m} = 28000.0 & \\textrm{[MPa]} & \\textrm{E-modulus of the matrix}  \\\\\n",
+       "                \\textrm{E_f} & E_\\mathrm{f} = 170000.0 & \\textrm{[MPa]} & \\textrm{E-modulus of the reinforcement}  \\\\\n",
+       "                \\textrm{s_data} & s = 0, 0.1, 0.5, 1, 2.1, 4, 6 & \\textrm{[mm]} & \\textrm{slip values}  \\\\\n",
+       "                \\textrm{tau_data} & \\tau = 0, 5.4, 4, 4.5, 5.5, 7.5, 8.5 & \\textrm{[MPa]} & \\textrm{shear stress values}  \\\\\n",
+       "                \\hline\n",
+       "        \\hline\n",
+       "        \\end{array}\n",
+       "        "
+      ],
+      "text/plain": [
+       "<ibvpy.tmodel.mats1D5.vmats1D5_bondslip1D.MATSBondSlipMultiLinear at 0x7f50b53509f0>"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "po_trc = PullOutModel1D(n_e_x=100, w_max=10) # mm \n",
+    "po_trc.geometry.L_x=100\n",
+    "po_trc.time_line.step = 0.05\n",
+    "po_trc.cross_section.trait_set(A_m=1543, A_f=16.7, P_b=10)\n",
+    "po_trc.material_model='multilinear'\n",
+    "po_trc.material_model_.trait_set(\n",
+    "    E_m=28000, E_f=170000,\n",
+    "    s_data = '0, 0.1, 0.5, 1, 2.1, 4, 6', \n",
+    "    tau_data = '0, 5.4, 4, 4.5, 5.5, 7.5, 8.5'\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "81358c6d843e4e6e956cb5ceec63aebb",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "po_trc.interact()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/run.png\" alt=\"Run\" width=\"40\" height=\"40\">\n",
+    "    &nbsp; &nbsp; <b>Run in a loop along the changing bond length</b> </div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To study the dependence between the maximum pullout force and the bond length, let us extend the loop that we previously introduced in the notebook [3.1](3_1_nonlinear_bond.ipynb#crfp_study). Instead of plotting the results directly after each simulation `run`, let us now store the pullout curves in a list called `Pw_list`. The `history` attribute of the model provides the method `get_Pw_t` delivering three data arrays, namely the force and the corresponding two displacements at unloaded and loaded ends. Thus, the calculated arrays are obtained by writing\n",
+    "```python\n",
+    "P, w_unloaded, w_loaded = po_trc.history.get_Pw_t()\n",
+    "```\n",
+    "In the code below, we let all the three arrays in a single variable called ``Pw_t`` and append this tuple of three values into the list ``Pw_list`` collecting the results for each studied length from the list ``L_list``"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "evaluating pullout curve for L 100\n",
+      "evaluating pullout curve for L 150\n",
+      "evaluating pullout curve for L 200\n",
+      "evaluating pullout curve for L 250\n",
+      "evaluating pullout curve for L 300\n",
+      "evaluating pullout curve for L 350\n"
+     ]
+    }
+   ],
+   "source": [
+    "L_list = [100, 150, 200, 250, 300, 350]\n",
+    "Pw_list = []\n",
+    "for L in L_list:\n",
+    "    print('evaluating pullout curve for L', L)\n",
+    "    po_trc.geometry.L_x=L\n",
+    "    po_trc.reset()\n",
+    "    po_trc.run()\n",
+    "    Pw_t = po_trc.history.get_Pw_t()\n",
+    "    Pw_list.append(Pw_t)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In addition to the parameters needed to simulate the debonding, let us also define the fabric strength so that we can plot the breaking force of the reinforcement $f_{\\mathrm{trc,t}} = 1300$ MPa"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f_trc_t = 1300 # [MPa]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us plot and decorate the results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9eeb454eafce46d18da5f5558e880116",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, (ax, ax_P_L) = plt.subplots(1,2, figsize=(10,4), tight_layout=True)\n",
+    "ax_w_L = ax_P_L.twinx()\n",
+    "fig.canvas.header_visible = False\n",
+    "P_max_list = []\n",
+    "w_argmax_list = []\n",
+    "for Pw_t, L, color in zip(Pw_list, L_list, ['red','green','blue','black','orange','gray']):\n",
+    "    P_range, w_unloaded, w_loaded = Pw_t\n",
+    "    ax.plot(w_loaded, P_range/1000, color=color, linestyle='solid', label=r'$L_\\mathrm{b}$ = %d' % L)\n",
+    "    ax.plot(w_unloaded, P_range/1000, color=color, linestyle='dashed')\n",
+    "    P_max = np.max(P_range)/1000 # kN\n",
+    "    w_argmax = w_loaded[np.argmax(P_range)]\n",
+    "    ax.plot([w_argmax], [P_max], 'o', color=color)\n",
+    "    P_max_list.append(P_max)\n",
+    "    w_argmax_list.append(w_argmax)\n",
+    "# Plotting\n",
+    "ax.set_xlabel(r'$w$ [mm]'); ax.set_ylabel(r'$P$ [kN]')\n",
+    "ax.legend()\n",
+    "ax_P_L.plot(L_list, P_max_list, 'o-', color='blue', label=r'$P_\\mathrm{max}$')\n",
+    "ax_P_L.set_xlabel(r'bond length $L_\\mathrm{b}$ [mm]')\n",
+    "ax_P_L.set_ylabel(r'pullout force $P_\\mathrm{max}$ [kN]')\n",
+    "ax_P_L.set_xlim(xmin=0); ax_P_L.set_ylim(ymin=0)\n",
+    "ax_w_L.plot(L_list, w_argmax_list, color='orange', label=r'$w_\\mathrm{argmax}$')\n",
+    "ax_w_L.set_ylabel(r'pullout displacement at $P_\\mathrm{max}$ [mm]')\n",
+    "ax_w_L.set_ylim(ymin=0);\n",
+    "P_fu = po_trc.cross_section.A_f * f_trc_t / 1000\n",
+    "ax_P_L.plot([0, 350], [P_fu, P_fu], linestyle='dashed', linewidth=1, color='red', label='breaking force' );\n",
+    "ax_P_L.legend();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## **Comments** to the study\n",
+    " - **Anchorage length**: The relation between the maximum pullout force and the bond length is linear and reaches the breaking force of the reinforcement at the length 256 mm. Comparing this value with the experimental observation, we see that the breaking load exhibits a huge scatter. It is therefore impossible to specify the deterministic value of the fabric strength. \n",
+    " - **Scatter of breaking force**: What is the reason for the experimentally observed scatter of the force at which the fabric breaks? We cannot expect that the pullout force is distributed evenly across the cross section. The statistical aspects of a parallel fiber bundle significantly affect the response of the material that needs to be accounted for in the design rules of textile fabric composites. In case of brittle fabrics this issue **must** included in the reliable design concept.\n",
+    " - **Symmetric debonding in both directions**: The fact that the test is designed as symmetric raises the question if the debonding runs symmetrically in both directions, particularly in the context of an existing scatter in the material properties across the fabrics and bond structure. The answer is, that in the current setting, the differences on both sides will balance each other. A weaker spot on a one side will lead to a debonding increment while increasing the overall force transferred over the debonded zone. The increased load will trigger a further debonding on the other side. This balancing of debonding, however, can only be assumed for an ascending branch of the pullout curve. If one side of the fabric starts to pullout with a decreasing force, the debonding process becomes one-sided.  "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **Case study: CFRP sheet**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us extend the study previously presented [for CFRP sheets in notebook 3.1](3_1_nonlinear_bond.ipynb#cfrp_sheet_test) with the goal to construct the relation between the bond length $L_\\mathrm{b}$ and the maximum pullout force $P_\\max$. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Model construction"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "\n",
+       "        \\begin{array}{lrrl}\\hline\n",
+       "        \\textrm{E_m} & E_\\mathrm{m} = 28000.0 & \\textrm{[MPa]} & \\textrm{E-modulus of the matrix}  \\\\\n",
+       "                \\textrm{E_f} & E_\\mathrm{f} = 230000.0 & \\textrm{[MPa]} & \\textrm{E-modulus of the reinforcement}  \\\\\n",
+       "                \\textrm{tau_1} & \\tau_1 = 7.0 & \\textrm{[MPa]} & \\textrm{shear strength}  \\\\\n",
+       "                \\textrm{tau_2} & \\tau_2 = 0.0 & \\textrm{[MPa]} & \\textrm{shear plateau}  \\\\\n",
+       "                \\textrm{s_1} & s_1 = 0.08 & \\textrm{[mm]} & \\textrm{slip at peak}  \\\\\n",
+       "                \\textrm{s_2} & s_2 = 0.4 & \\textrm{[mm]} & \\textrm{slip at plateau}  \\\\\n",
+       "                \\hline\n",
+       "        \\hline\n",
+       "        \\end{array}\n",
+       "        "
+      ],
+      "text/plain": [
+       "<ibvpy.tmodel.mats1D5.vmats1D5_bondslip1D_trilinear.MATSBondSlipTriLinear at 0x7f50b5108a90>"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "po_cfrp = PullOutModel1D(n_e_x=300, w_max=1) # mm \n",
+    "po_cfrp.geometry.L_x=100\n",
+    "po_cfrp.time_line.step = 0.03\n",
+    "po_cfrp.cross_section.trait_set(A_m=400*200, A_f=100*0.11, P_b=100)\n",
+    "po_cfrp.material_model='trilinear'\n",
+    "po_cfrp.material_model_.trait_set(E_m=28000, E_f=230000, tau_1=7, tau_2=0, s_1=0.08, s_2=0.4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "43276072eec345deb50ec4972641f80d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HBox(children=(VBox(children=(Tree(layout=Layout(align_items='stretch', border='solid 1px black…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "po_cfrp.interact()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/run.png\" alt=\"Run\" width=\"40\" height=\"40\">\n",
+    "    &nbsp; &nbsp; <b>Run in a loop along the changing bond length</b> </div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To study the dependence between the maximum pullout force and the bond length, let us extend the loop that we previously introduced in the notebook [3.1](3_1_nonlinear_bond.ipynb#crfp_study). Instead of plotting the results directly after each simulation `run`, let us now store the pullout curves in a list called `Pw_list`. The `history` attribute of the model provides the method `get_Pw_t` delivering three data arrays, namely the force and the corresponding two displacements at unloaded and loaded ends. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "evaluating pullout curve for L 5\n",
+      "evaluating pullout curve for L 10\n",
+      "evaluating pullout curve for L 50\n",
+      "evaluating pullout curve for L 100\n",
+      "evaluating pullout curve for L 200\n"
+     ]
+    }
+   ],
+   "source": [
+    "L_list = [5, 10, 50, 100, 200]\n",
+    "Pw_list = []\n",
+    "for L in L_list:\n",
+    "    print('evaluating pullout curve for L', L)\n",
+    "    po_cfrp.geometry.L_x=L\n",
+    "    po_cfrp.reset()\n",
+    "    po_cfrp.run()\n",
+    "    Pw_t = po_cfrp.history.get_Pw_t()\n",
+    "    Pw_list.append(Pw_t)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Postprocessing**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "dda185ccd88b427b91f36fa199ed9c6d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, (ax, ax_P_L) = plt.subplots(1,2, figsize=(10,4), tight_layout=True)\n",
+    "ax_w_L = ax_P_L.twinx()\n",
+    "fig.canvas.header_visible = False\n",
+    "P_max_list = []\n",
+    "w_argmax_list = []\n",
+    "for Pw_t, L, color in zip(Pw_list, L_list, ['red','green','blue','black','orange']):\n",
+    "    P_range, w_unloaded, w_loaded = Pw_t\n",
+    "    ax.plot(w_loaded, P_range/1000, color=color, linestyle='solid', label=r'$L_\\mathrm{b}$ = %d' % L)\n",
+    "    ax.plot(w_unloaded, P_range/1000, color=color, linestyle='dashed')\n",
+    "    P_max = np.max(P_range)/1000 # kN\n",
+    "    w_argmax = w_loaded[np.argmax(P_range)]\n",
+    "    P_max_list.append(P_max)\n",
+    "    w_argmax_list.append(w_argmax)\n",
+    "# Plotting\n",
+    "ax.set_xlabel(r'$w$ [mm]'); ax.set_ylabel(r'$P$ [kN]')\n",
+    "ax.legend()\n",
+    "ax_P_L.plot(L_list, P_max_list, 'o-', color='blue', label=r'$P_\\mathrm{max}$')\n",
+    "ax_P_L.set_xlabel(r'bond length $L_\\mathrm{b}$ [mm]')\n",
+    "ax_P_L.set_ylabel(r'pullout force $P_\\mathrm{max}$ [kN]')\n",
+    "ax_P_L.set_xlim(xmin=0); ax_P_L.set_ylim(ymin=0)\n",
+    "ax_w_L.plot(L_list, w_argmax_list, 'o-', color='orange', label=r'$w_\\mathrm{argmax}$')\n",
+    "ax_w_L.set_ylabel(r'pullout displacement at $P_\\mathrm{max}$ [mm]')\n",
+    "ax_w_L.set_ylim(ymin=0);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## **Discussion:** \n",
+    " - The evolution of the maximum pullout force with the increasing debonded length displayed in the right diagram is nonlinear and reaches the plateau at $L_b \\approx 0.75$ mm."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# **Anchorage and constant bond-slip law**\n",
+    "\n",
+    "Let us first consider the case of pull-out model with constant bond strength presented in\n",
+    "the notebook [2.1](../tour2_constant_bond/2_1_1_PO_observation.ipynb#top) and qualitatively analyze the length-dependent pull-out response. Let us\n",
+    "assume that the level of $\\bar{\\tau}$, which is the only material parameter needed to characterize \n",
+    "the bond-slip behavior, has been determined from a calibration experiment\n",
+    "with embedded length $L_1$. We can now make a prediction of the pull-out curves\n",
+    "for embedded lengths $L_2$ and $L_3$ to obtain the respective pull-out curves depicted"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div style=\"background-color:lightgray;text-align:left\"> <img src=\"../icons/exercise.png\" alt=\"Run\" width=\"40\" height=\"40\">\n",
+    "    &nbsp; &nbsp; <a href=\"../exercises/X0303 - Anchorage length.pdf\"><b>Exercise X0303:</b></a> <b>Anchorage length</b> \n",
+    "<a href=\"https://moodle.rwth-aachen.de/mod/page/view.php?id=551825\"><img src=\"../icons/bmcs_video.png\" alt=\"Run\"></a>\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
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+   "number_sections": true,
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+   "title_cell": "Table of Contents",
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+   "toc_cell": false,
+   "toc_position": {
+    "height": "calc(100% - 180px)",
+    "left": "10px",
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