Repository: PMEAL/OpenPNM

Issue:
notebook example on voronoi networks contains incorrect info
The notebook for [voronoi tessellations](https://github.com/PMEAL/OpenPNM/blob/dev/examples/notebooks/networks/generation/random_networks_based_on_delaunay_and_voronoi_tessellations.ipynb) is a duplicate of the cubic example.  

Discussion:

Patch:
diff --git a/examples/contrib/README.md b/examples/contrib/README.md
new file mode 100644
index 000000000..b476f3c26
--- /dev/null
+++ b/examples/contrib/README.md
@@ -0,0 +1,5 @@
+# Contibuted Examples
+
+This folder contains code that has been contributed by a user (or developer) that is not quite ready to be included in OpenPNM permanently, but is worth including in the repository so it can be accessible via Github.  
+
+The files in this folder are NOT included in the testing suite so they are not gauranteed to work.  Usually only a small fix is required to get them going.  It is generally encourage to include the ``openpnm.__version__`` number in the code so readers know at least which version of openpnm it was intened to work with.  
\ No newline at end of file
diff --git a/examples/notebooks/algorithms/multiphase/relative_permeability_2D.ipynb b/examples/notebooks/algorithms/multiphase/relative_permeability_2D.ipynb
index 20c0a5fc2..7f03ee1b4 100644
--- a/examples/notebooks/algorithms/multiphase/relative_permeability_2D.ipynb
+++ b/examples/notebooks/algorithms/multiphase/relative_permeability_2D.ipynb
@@ -128,7 +128,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x432 with 1 Axes>"
       ]
@@ -178,8 +178,8 @@
    "source": [
     "st = op.algorithms.StokesFlow(network=pn)\n",
     "st.setup(phase=water)\n",
-    "st.set_value_BC(pores=pn.pores('back'), values=1)\n",
-    "st.set_value_BC(pores=pn.pores('front'), values=0)"
+    "st.set_value_BC(pores=pn.pores('front'), values=1)\n",
+    "st.set_value_BC(pores=pn.pores('back'), values=0)"
    ]
   },
   {
@@ -204,7 +204,7 @@
    ],
    "source": [
     "st.run()\n",
-    "Q_abs_water = st.rate(pores=pn.pores('back'))\n",
+    "Q_abs_water = st.rate(pores=pn.pores('front'))\n",
     "print(Q_abs_water)"
    ]
   },
@@ -248,7 +248,7 @@
    ],
    "source": [
     "st.run()\n",
-    "Q_eff = st.rate(pores=pn.pores('back'))\n",
+    "Q_eff = st.rate(pores=pn.pores('front'))\n",
     "print(Q_eff)"
    ]
   },
@@ -310,7 +310,7 @@
     "    # 3: Re-run flow problem\n",
     "    st.run()\n",
     "    # 4: Compute flow through inlet phase and append to data\n",
-    "    Q_water.append(st.rate(pores=pn.pores('back')))\n",
+    "    Q_water.append(st.rate(pores=pn.pores('front')))\n",
     "    phys_water.regenerate_models()"
    ]
   },
@@ -333,10 +333,10 @@
     "#stokes flow for air\n",
     "st_a = op.algorithms.StokesFlow(network=pn)\n",
     "st_a.setup(phase=air)\n",
-    "st_a.set_value_BC(pores=pn.pores('back'), values=1)\n",
-    "st_a.set_value_BC(pores=pn.pores('front'), values=0)\n",
+    "st_a.set_value_BC(pores=pn.pores('front'), values=1)\n",
+    "st_a.set_value_BC(pores=pn.pores('back'), values=0)\n",
     "st_a.run()\n",
-    "Q_abs_air=st_a.rate(pores=pn.pores('back'))\n",
+    "Q_abs_air=st_a.rate(pores=pn.pores('front'))\n",
     "for s in np.arange(0, 1, 0.1):  # Loop through saturations\n",
     "    # 1: Update air object with occupancy at given saturation\n",
     "    air.update(ip.results(Snwp=s))\n",
@@ -345,7 +345,7 @@
     "    # 3: Re-run flow problem\n",
     "    st_a.run()\n",
     "    # 4: Compute flow through inlet phase and append to data\n",
-    "    Q_air.append(st_a.rate(pores=pn.pores('back')))\n",
+    "    Q_air.append(st_a.rate(pores=pn.pores('front')))\n",
     "    phys_air.regenerate_models()"
    ]
   },
@@ -485,7 +485,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1a5af683100>"
+       "<matplotlib.legend.Legend at 0x7fc52901d640>"
       ]
      },
      "execution_count": 15,
diff --git a/examples/notebooks/algorithms/percolation/capillary_pressure_curves.ipynb b/examples/notebooks/algorithms/percolation/capillary_pressure_curves.ipynb
index a1ce0165c..319e3ad0f 100644
--- a/examples/notebooks/algorithms/percolation/capillary_pressure_curves.ipynb
+++ b/examples/notebooks/algorithms/percolation/capillary_pressure_curves.ipynb
@@ -154,7 +154,7 @@
    "outputs": [],
    "source": [
     "mip = op.algorithms.Porosimetry(network=pn, phase=hg)\n",
-    "mip.set_inlets(pores=pn.pores('front'))\n",
+    "mip.set_inlets(pores=pn.pores('back'))\n",
     "mip.run()"
    ]
   },
diff --git a/examples/notebooks/algorithms/transient/transient_advection_diffusion.ipynb b/examples/notebooks/algorithms/transient/transient_advection_diffusion.ipynb
index 8e79afb0a..1cb4c85a8 100644
--- a/examples/notebooks/algorithms/transient/transient_advection_diffusion.ipynb
+++ b/examples/notebooks/algorithms/transient/transient_advection_diffusion.ipynb
@@ -91,8 +91,8 @@
    "outputs": [],
    "source": [
     "sf = op.algorithms.StokesFlow(network=pn, phase=water,)\n",
-    "sf.set_value_BC(pores=pn.pores('back'), values=50.0)\n",
-    "sf.set_value_BC(pores=pn.pores('front'), values=0)\n",
+    "sf.set_value_BC(pores=pn.pores('front'), values=50.0)\n",
+    "sf.set_value_BC(pores=pn.pores('back'), values=0)\n",
     "sf.run();"
    ]
   },
@@ -159,8 +159,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "inlet  = pn.pores('back') \n",
-    "outlet = pn.pores('front')\n",
+    "inlet  = pn.pores('front') \n",
+    "outlet = pn.pores('back')\n",
     "ad.set_value_BC(pores=inlet, values=1.0)\n",
     "ad.set_outflow_BC(pores=outlet)\n",
     "ad.set_IC(0)"
@@ -341,7 +341,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1080x1080 with 5 Axes>"
       ]
@@ -395,7 +395,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -409,7 +409,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average Peclet Number = 7.143648603416046\n"
+      "Average Peclet Number = 7.143648603416045\n"
      ]
     }
    ],
@@ -456,7 +456,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -469,16 +469,16 @@
    ],
    "source": [
     "# NBVAL_IGNORE_OUTPUT\n",
-    "Pores_front = pn.pores(['front'])\n",
-    "Throats_front = pn.find_neighbor_throats(pores=Pores_front, mode='xor')\n",
+    "Pores_back = pn.pores(['back'])\n",
+    "Throats_back = pn.find_neighbor_throats(pores=Pores_back, mode='xor')\n",
     "steps = tf/tstep +1\n",
     "count = 0\n",
     "C_ave = []\n",
     "td = ad.settings['t_solns']\n",
     "for step in td:\n",
-    "    conc_front = ad['pore.concentration@'+str(step)][Pores_front]\n",
-    "    q_front = sf.rate(throats=pn.Ts,mode='single')[Throats_front]\n",
-    "    C_ave.append(np.sum(q_front*conc_front)/np.sum(q_front))\n",
+    "    conc_back = ad['pore.concentration@'+str(step)][Pores_back]\n",
+    "    q_back = sf.rate(throats=pn.Ts,mode='single')[Throats_back]\n",
+    "    C_ave.append(np.sum(q_back*conc_back)/np.sum(q_back))\n",
     "plt.plot(td, C_ave)\n",
     "plt.gca().legend(('simulation','fitted'))\n",
     "plt.xlabel('time, s')\n",
@@ -563,7 +563,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -602,7 +602,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.8.6"
   }
  },
  "nbformat": 4,
diff --git a/examples/notebooks/algorithms/transient/transient_fickian_diffusion.ipynb b/examples/notebooks/algorithms/transient/transient_fickian_diffusion.ipynb
index 72c68aedf..979fbb894 100644
--- a/examples/notebooks/algorithms/transient/transient_fickian_diffusion.ipynb
+++ b/examples/notebooks/algorithms/transient/transient_fickian_diffusion.ipynb
@@ -170,7 +170,7 @@
    "metadata": {},
    "source": [
     "## Add boundary conditions\n",
-    "Next, Dirichlet boundary conditions are added over the back and front boundaries of the network."
+    "Next, Dirichlet boundary conditions are added over the front and back boundaries of the network."
    ]
   },
   {
@@ -179,8 +179,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fd.set_value_BC(pores=net.pores('back'), values=0.5)\n",
-    "fd.set_value_BC(pores=net.pores('front'), values=0.2)"
+    "fd.set_value_BC(pores=net.pores('front'), values=0.5)\n",
+    "fd.set_value_BC(pores=net.pores('back'), values=0.2)"
    ]
   },
   {
@@ -490,7 +490,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x432 with 2 Axes>"
       ]
@@ -533,7 +533,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.8.6"
   }
  },
  "nbformat": 4,
diff --git a/examples/notebooks/networks/generation/random_networks_based_on_delaunay_and_voronoi_tessellations.ipynb b/examples/notebooks/networks/generation/random_networks_based_on_delaunay_and_voronoi_tessellations.ipynb
index e0c2633f0..c8dc2ee34 100644
--- a/examples/notebooks/networks/generation/random_networks_based_on_delaunay_and_voronoi_tessellations.ipynb
+++ b/examples/notebooks/networks/generation/random_networks_based_on_delaunay_and_voronoi_tessellations.ipynb
@@ -4,30 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Generate Cubic Lattices of Various Shape, Sizes and Topologies"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The Cubic lattice network is the most commonly used pore network topology by far. When people first learn about pore network modeling they often insist on creating networks that are topologically equivalent or representative of the real network (i.e. random networks extracted from tomography images). In reality, however, a simple cubic network provides a very passable representation of more complex topologies, and provides several additional benefits as well; namely they are much easier to visualize, and applying boundary conditions is easier since the faces of the network are flat.\n",
+    "# Generate Random Networks Based on Delaunay Triangulations,  Voronoi Tessellations, or Both\n",
     "\n",
-    "The examples below will demonstrate how to create various cubic lattice networks in OpenPNM using the Cubic class, as well as illustrating a few topological manipulations that can be performed, such as adding boundary pores, and trimming throats to create a more random-like topology."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Basic Cubic Lattice with Different Connectivity"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's start with the most basic cubic lattice:"
+    "A random network offers several advantages over the traditional Cubic arrangement: the topology is more 'natural' looking, and a wider pore size distribution can be achieved since pores are not constrained by the lattice spacing.  Random networks can be tricky to generate however, since the connectivity between pores is difficult to determine or define.  One surprisingly simple option is to use Delaunay triangulation to connect base points (which become pore centers) that are randomly distributed in space.  The Voronoi tessellation is a complementary graph that arises directly from the Delaunay graph which also connects essentially randomly distributed points in space into a network.  OpenPNM offers both of these types of network, plus the ability to create a network containing *both* including interconnections between Delaunay and Voronoi networks via the ```DelaunayVoronoiDual``` class.  In fact, creating the dual, interconnected network is the starting point, and any unwanted elements can be easily trimmed."
    ]
   },
   {
@@ -36,87 +15,64 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import os\n",
-    "import warnings\n",
-    "import numpy as np\n",
-    "import openpnm as op\n",
-    "np.random.seed(10)\n",
-    "ws = op.Workspace()\n",
-    "ws.settings['loglevel'] = 40\n",
-    "warnings.filterwarnings('ignore')\n",
-    "pn = op.network.Cubic(shape=[10, 10, 10], spacing=1, connectivity=6)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In this case ```pn``` will be a 10 x 10 x 10 *cube* with each pore spaced 1 *unit* away from it's neighbors in all directions.  Each pore is connected to the 6 neighbors adjacent to each *face* of the cubic lattice site in which it sits.  The image below illustrates the resulting network with pores shown as white spheres, along with a zoomed in view of the internals, showing the connectivity of the pores."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<img src=\"http://i.imgur.com/JTUodGy.png\" style=\"width: 60%\" align=\"left\"/>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The **Cubic** network generator applies 6-connectivity by default, but different values can be specified.  In a cubic lattice, each pore can have up to 26 neighbors: 6 on each face, 8 on each corner, and 12 on each edge.  This is illustrated in the image below."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<img src=\"http://i.imgur.com/ACiQFtJ.png\" style=\"width: 60%\" align=\"left\"/>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Cubic networks can have any combination of corners, edges, and faces, which is controlled with the ```connectivity``` argument by specifying the total number of neighbors (6, 8, 12, 14, 18, 20, or 26):"
+    "import openpnm as op"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "pn = op.network.Cubic(shape=[10, 10, 10], spacing=1, connectivity=26)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This yields the following network, which clearly has a LOT of connections!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<img src=\"http://i.imgur.com/PS6d7CO.png\" style=\"width: 70%\" align=\"left\"/>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
+      "openpnm.network.DelaunayVoronoiDual : net_01\n",
+      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
+      "#     Properties                                    Valid Values\n",
+      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
+      "1     pore.coords                                     783 / 783  \n",
+      "2     throat.conns                                   4400 / 4400 \n",
+      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
+      "#     Labels                                        Assigned Locations\n",
+      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
+      "1     pore.all                                      783       \n",
+      "2     pore.back                                     56        \n",
+      "3     pore.bottom                                   77        \n",
+      "4     pore.boundary                                 329       \n",
+      "5     pore.delaunay                                 224       \n",
+      "6     pore.front                                    56        \n",
+      "7     pore.internal                                 454       \n",
+      "8     pore.left                                     65        \n",
+      "9     pore.right                                    68        \n",
+      "10    pore.surface                                  188       \n",
+      "11    pore.top                                      62        \n",
+      "12    pore.voronoi                                  559       \n",
+      "13    throat.all                                    4400      \n",
+      "14    throat.boundary                               987       \n",
+      "15    throat.delaunay                               656       \n",
+      "16    throat.interconnect                           2630      \n",
+      "17    throat.internal                               2583      \n",
+      "18    throat.surface                                830       \n",
+      "19    throat.voronoi                                1114      \n",
+      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
+     ]
+    }
+   ],
    "source": [
-    "## Trimming Random Throats to Adjust Coordination Number"
+    "# NBVAL_IGNORE_OUTPUT\n",
+    "pn = op.network.DelaunayVoronoiDual(num_points=100, shape=[1, 1, 1])\n",
+    "print(pn)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Often it is desired to create a distribution of coordination numbers on each pore, such that some pores have 2 neighbors and other have 8, while the overall average may be around 5.  It is computationally very challenging to specify a specific distribution, but OpenPNM does allow you to create a network with a specific *average* connectivity.  This is done by creating a network with far more connections than needed (say 26), then trimming some fraction of throats from the network to reduce the coordination.  "
+    "The above line of code is deceptively simple.  The returned network (```pn```) contains a fully connected Delaunay network, its complementary Voronoi network, and interconnecting throats (or bonds) between each Delaunay pore (node) and its neighboring Voronoi pores.  Such a highly complex network would be useful for modeling pore phase transport (i.e. diffusion) on one network (i.e. Delaunay), solid phase transport (i.e. heat transfer) on the other network (i.e. Voronoi), and exchange of a species (i.e. heat) between the solid and void phases via the interconnecting bonds.  Each pore and throat is labelled accordingly (i.e. 'pore.delaunay', 'throat.voronoi'), and the interconnecting throats are labelled 'throat.interconnect'.  Moreover, pores and throats lying on the surface of the network are labelled 'surface'.  \n",
+    "\n",
+    "A quick visualization of this network can be accomplished using OpenPNM's built-in graphing tool.  The following shows only the Voronoi connections that lie on the surface of the cube:"
    ]
   },
   {
@@ -125,58 +81,80 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "10476\n"
-     ]
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "import scipy as sp\n",
-    "pn = op.network.Cubic(shape=[10, 10, 10], spacing=[1, 1, 1], connectivity=26)\n",
-    "print(pn.num_throats())"
+    "# NBVAL_IGNORE_OUTPUT\n",
+    "Ts = pn.throats(['voronoi', 'boundary'], mode='and')\n",
+    "fig = op.topotools.plot_connections(network=pn, throats=Ts)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The most basic way to do this is to just trim arbitrary throats as shown below, but this can lead to problems of accidentally creating isolated and disconnected clusters."
+    "One central feature of these networks are the flat boundaries, which are essential when performing transport calculations since they provide well-defined control surfaces for calculating flux.  This flat surfaces are accomplished by reflecting the base points across each face prior to performing the tessellations.  "
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 4,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "throats_to_trim = sp.random.randint(low=0, high=pn.Nt-1, size=500)\n",
-    "from openpnm import topotools as tt\n",
-    "tt.trim(network=pn, throats=throats_to_trim)\n",
-    "# randint returns some duplicate numbers so actual number of trimmed throats varies\n",
-    "assert pn.num_throats() < 10476"
+    "Plotting the internal Voronoi throats with a different color gives a good idea of the topology:"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 4,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "The following image shows histogram of the pore connectivity before and after trimming.  Before trimming the coordination numbers fall into 4 distinct bins depending on where the pores lies (internal, face, edge or corner), while after trimming the coordination numbers show some distribution around their original values.  If the trimming is too aggressive, OpenPNM might report an error message saying that isolated pores exist, which means that some regions of the network are now disconnected from the main network due to a lack of connected throats."
+    "# NBVAL_IGNORE_OUTPUT\n",
+    "Ts = pn.throats(['voronoi', 'boundary'], mode='and')\n",
+    "fig = op.topotools.plot_connections(network=pn, throats=Ts, alpha=0.5)\n",
+    "Ts = pn.throats(['voronoi', 'internal'], mode='and')\n",
+    "fig = op.topotools.plot_connections(network=pn, throats=Ts, c='g', fig=fig)\n",
+    "Ts = pn.throats(['voronoi', 'surface'], mode='and')\n",
+    "fig = op.topotools.plot_connections(network=pn, throats=Ts, c='r', fig=fig)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://i.imgur.com/Z4HgMYC.png\" style=\"width: 70%\" align=\"left\"/>"
+    "The green lines are internal connections, and red lines are connections between internal notes and boundary nodes. "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In order to allow more aggressive trimming without creating topological problems, OpenPNM offers a tool in the ``topotools`` module called ``reduce_coordination``, which accepts an average coordination number.  This function works by first computing the minimum-spanning tree of the network (which is a set of connections that ensures every pore is connected), then deletes throats that are NOT part of the spanning tree to ensure that connection is maintained.  "
+    "## Delaunay Network\n",
+    "\n",
+    "As the name suggests, the VoronoiDelaunayDual contains both the Delaunay triangulation and the Voronoi tessellation within the same topology. It is simple to delete one network (or the other) by trimming all of the other network's pores, which also removes all connected throats including the interconnections:"
    ]
   },
   {
@@ -185,15 +163,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pn = op.network.Cubic(shape=[10, 10, 10], spacing=[1, 1, 1], connectivity=26)\n",
-    "op.topotools.reduce_coordination(network=pn, z=5)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now plotting the histogram we can see that indeed the average coordination was obtained.  Note, however, that the distribution is skewed and has a long tail.  The ``reduce_coordination`` function does not (yet) control the shapre of the distribution."
+    "# NBVAL_IGNORE_OUTPUT\n",
+    "Ps = pn.pores(['voronoi'])\n",
+    "op.topotools.trim(network=pn, pores=Ps)\n",
+    "Ts = pn.throats(['surface'])\n",
+    "op.topotools.trim(network=pn, throats=Ts)"
    ]
   },
   {
@@ -203,121 +177,145 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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mPDEAAFeJudzD4bCam5tVXFysxx9/PDIeDAYjj/fs2aPS0tL4EgIAJizmL1QPHz6s3bt3a968eXK5XJKkZ555Ru3t7QoEAkpJSVFeXp527txpWVgAwPjEXO7f/va3FQ6HrxlfsmRJXIEAAPFjhyoAGIhyBwADxbwsAwCWY2esZSh3ADcOdsZahmUZADAQ5Q4ABqLcAcBAlDsAGIhyBwADUe4AYCDKHQAMRLkDgIEodwAwEOUOAAbi9gMAkKR72kiJu68N5Q4ASbqnjZS4+9qwLAMABqLcAcBAlDsAGIhyBwADUe4AYKCElbvP51NhYaEKCgrU2tqaqGkAAFEkpNxHR0f1ox/9SK+99pqOHz+u9vZ2HT9+PBFTAQCiSEi5d3d3q6CgQLNnz9att96quro6dXZ2JmIqAEAUKeFwOGz1m/7pT3+Sz+fT888/L0navXu3/vGPf2jbtm2RY7xer7xeryTpgw8+UFFRkdUxEiIUCikzMzPZMRLG5Ovj2m5eJl9fPNfW19enoaGhqK8lZIdqtP9fXL211+PxyOPxJGL6hHK73fL7/cmOkTAmXx/XdvMy+foSdW0JWZZxOp3q7++PPB8YGFB2dnYipgIARJGQcr/rrrvU09Oj3t5effHFF+ro6FB1dXUipgIARJG2adOmTVa/aWpqqubMmaPVq1frN7/5jVavXq3a2lqrp0ma8vLyZEdIKJOvj2u7eZl8fYm4toR8oQoASC52qAKAgSh3ADAQ5T5O/f39uv/++1VcXKySkhJt3bo12ZEsNzo6qgULFuihhxLz4wHJcv78eS1fvlxFRUUqLi7W3//+92RHstSvfvUrlZSUqLS0VPX19fr888+THSlmTU1NstvtKi0tjYydO3dOVVVVmjNnjqqqqjQ8PJzEhPGJdn1PPPGEioqKVFZWppqaGp0/f96SuSj3cbLZbHr22Wf1z3/+U2+//ba2b99u3C0Vtm7dquLi4mTHsNxPfvITPfDAA/rggw/03nvvGXWNg4OD+vWvfy2/36+jR49qdHRUHR0dyY4Vs8bGRvl8vivGWltbVVlZqZ6eHlVWVt7U96qKdn1VVVU6evSo3n//fd15551qaWmxZC7KfZwcDocWLlwoSZo2bZqKi4s1ODiY5FTWGRgY0CuvvKJHHnkk2VEs9e9//1sHDx5Uc3OzJOnWW2/V17/+9SSnstbIyIj+85//aGRkRBcvXryp95RUVFQoPT39irHOzk41NDRIkhoaGrR3795kRLNEtOtbvHixbLYv95Pee++9GhgYsGQuyj0GfX19OnLkiO65555kR7HMT3/6U/3yl79UaqpZfyROnTqlzMxM/eAHP9CCBQv0yCOP6MKFC8mOZZmcnBxt2LBBubm5cjgcuv3227V48eJkx7LUmTNn5HA4JH35Ievs2bNJTpQ4L7zwgh588EFL3sus/5InwWeffaba2lo999xzmj59erLjWGL//v2y2+1G/jvikZERvfvuu1q7dq2OHDmir33tazf1X+uvNjw8rM7OTvX29upf//qXLly4oD/84Q/JjoUYPP3007LZbFq1apUl70e5T8Dly5dVW1urVatWadmyZcmOY5nDhw9r3759ysvLU11dnd58802tXr062bEs4XQ65XQ6I3/LWr58ud59990kp7LOG2+8oVmzZikzM1O33HKLli1bpr/97W/JjmWprKwsBYNBSVIwGJTdbk9yIuu1tbVp//79evHFF6+5D1esKPdxCofDam5uVnFxsR5//PFkx7FUS0uLBgYG1NfXp46ODi1atMiYT38zZszQzJkzdeLECUlSV1eX5s6dm+RU1snNzdXbb7+tixcvKhwOq6ury6gvjCWpurpabW1tkr4swaVLlyY5kbV8Pp+2bNmiffv2aerUqda9cRjjcujQobCk8Lx588Lz588Pz58/P/zKK68kO5bl3nrrrfB3vvOdZMew1JEjR8Ll5eXhefPmhZcuXRo+d+5csiNZ6qmnngoXFhaGS0pKwqtXrw5//vnnyY4Us7q6uvCMGTPCNpstnJOTE37++efDQ0ND4UWLFoULCgrCixYtCn/yySfJjhmzaNeXn58fdjqdkV754Q9/aMlc3H4AAAzEsgwAGIhyBwADUe4AYCDKHQAMRLkDgIEodwAwEOUOAAb6L7TdsL+w9avxAAAAAElFTkSuQmCC\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
     }
    ],
    "source": [
-    "#NBVAL_IGNORE_OUTPUT\n",
-    "import matplotlib.pyplot as plt\n",
-    "fig = plt.figure()\n",
-    "plt.hist(pn.num_neighbors(pn.Ps), edgecolor='k')\n",
-    "fig.patch.set_facecolor('white')"
+    "fig = op.topotools.plot_connections(network=pn)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "## Create Random Networks of Spherical or Cylindrical Shape\n",
     "\n",
-    "## Creating Domains with More Interesting Shapes\n",
-    "\n",
-    "### Rectangular Domains with Non-Uniform Spacing\n",
-    "\n",
-    "The ```shape``` and ```spacing``` arguments can of course be adjusted to create domains other than simple cubes:"
+    "Many porous materials come in spherical or cylindrical shapes, such as catalyst pellets.  The ```DelaunayVoronoiDual``` Network class can produce these geometries by specifying the ```domain_size``` in cylindrical [r, z] or spherical [r] coordinates:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "pn = op.network.Cubic(shape=[10, 20, 20], spacing=[0.001, 0.03, 0.02])"
+    "# NBVAL_IGNORE_OUTPUT\n",
+    "cyl = op.network.DelaunayVoronoiDual(num_points=200, shape=[2, 5])\n",
+    "fig = op.topotools.plot_connections(network = cyl,\n",
+    "                                    throats=cyl.throats('boundary'))"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 8,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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1dTX5+fl2RWJkqu9gk8OhctliBV67kRicSGL4rxDi1W7ZaAdxWJNDW7ULhYWFlJSUMGHChA5FhNuaF9EZ1NfXU11dzbBhwxg0aFCXttGWhWBZFL/8pZsVK1QqKlQqKxXaOuRLLw3y2WcaO3daN6QAFEwTamvla4mJgptu8vGPf3g588wQw4YJNm0y2LUrjrvvTuDzz51tbr8t7N2r4PUK7r7bxV/+4uL99zVmzZKZmWAwGJXqc7vduFyug0oSh9JSidxvKBSKaUl1YZsK8ASwRQhx7wFvsJM4bMnBmhFRV1dHdnY2iqLYKtAej4cZM2Z0yxfQkeMoLi6muLg4qvy2K5g4MZXGxmQURcMwXCQmCtLTBS5XDv36hdi82UF+fmxrJDlZUFenkJpq8uST0a6Bx6Pg94OmwfnnB3n+eRcNDQr33OPF4YA//tFNYqJJQ4PCRx9N7vLxA/h8yr7jMXj5ZY2ZM3UURdYFZGdnk52dve99PgoLC6mtrWX58uW29kJaWlq7GZ0DQUerI7sbLR883VjjcCTwU2CDoihr9712mxBicXdsfH84LMnBql3w+XxUVVXRp08fqqur2bJlC8OGDbNvwJ6GFdOwJltt2bKlyxaIYcDZZ/t54IE4cnNNMjIEO3YolJaqQByrV7f/+bo6uShrauTN7/GAxyN4/fVm5s2LIxhUGD3aZMkSJ2439OljUlio2vGJhobuXTR1dQ4ee8zB22+bzJ5tYppw3XVBJk+WlpHX67WzHLm5ua20FyI7TZ1OZ7cc06Eih5ZobGw84BoHACHEUuCQBW0OK3JoGXTUNA3DMNixYwfV1dVMmTKlSym1rqCxsZH169dHxTQ6G7sQAurqoLISJk1yoevyib97t8ru3V07LvmUBr8fAgGF446LxzShTx/BlCkGH3/soLxcadMCcbmCBIMuVHX/2YuOwO+X7kZDA/zkJ15mzDB48kk/qhpdx9FSqMXqkCwqKrI7JK1O065ahIeCHGI9LJqbm7/11ZFwGJFDrNoFXdeprKxkwIABHaoj6C5YqdHx48eTmJhovx4r2xAKwbp1CoaB/RMMwhlnaASDCooCTidETLA/IAgBhiFITpbkYAUry8oUnnkm+gnscMj35+SYlJerBAKgqhpZWYKqKoVx4wyKilQaGhRAYJqdf0jV1KgsXy7PTwgoLtb48ss4tm1rbjMGoKpqVDu11SFZVVVlNz1Z9RVWcLMjOBTk0LIoDr4bpdNwmJBDrNFz5eXlbN26Fa/Xy/Dhww/acWzZsgVd12OmRmNZDkVFcOmlGqYpiSEQAL9fYZ8YMkJg/78z0DSBrivExwsCAdD18CLTdYW6uuj3W5w1aJCMLdTXK4RCMlZRVKTSt68gIUGwe7egqkq6Gxs3Rt7UsYnB5RL06SOorZXbjIV98WIbZWUqixc7mDy5YwHClh2SVh+DNQzH4/HYZNGejN6hIIeWaUzoPrfiUOOQkkNbJdBbt26lqamJyZMns2XLloNyLM3Nzaxbt46cnBwGDBgQ8waMZTn8858OSkulWd11CBITDRoawl+Hrsvg4zHHyMX+1VcOAgHIyBCEQsLOSjgcgpwcQWIi7Nypsnu3arsLTqcMYiYlQVUV++IbHYfbDUIo7N7d9gL3eKSbY5rYNRYAF1zg5c03nQwd2nlmjOxjEELYlZv7k9E7VOQQy3L4LpDDIYveWEHHyGEyTU1NLF++HI/HY8cXuqMnAtovNNq7dy9r165lzJgx5ObmtvlkipUSHT4cVDWy/bpjx+NyCTTN+pxCQ4MDmZKUSEkxqalRefNNja+/duD1CjIzBf/5j5/t25u5/36ffV5Dhwr27FHJzTURQmYtLr44uE/oBurrIRjsnMugqpCQIJg82aC9ME+/fiZFRY1MnNjabzr//IHcdlvfTqdMI6EoCnFxceTk5DB+/HhmzJhB//79CQaDbN68meXLl7Nt2zYqKioIBoO9bkU34qCTg2UtBAKBqPhCSUkJ69atY/To0QwaNCjKkugOxNqWaZps2bKFkpISpk+fHrP02sK6dQqPPZbOHXcksWoVJCS4OOMMjYkTjX0+u3V+0Z/r00fGBwC83vD+g0EFXVdQVfn0l2a9su9Y4aKLtvLkk+txuQQ+H6Snm/j9cOutbgYNSuB//3MxapSJrkN+vsLf/uZj+3aVxETBRx818+GHTk47LWRnK5KSDH72s2AEIbWNxERBbq7JJZeE2L5dxSd5CI8HUlKiP19SorJ6tcpXX0UboR6PJMqNG908/HA4FvL66w7OOMMTZWV0BpaM3sCBA5k8eTJTp04lMzOT+vp6du7cSXl5OTt37qS6urrbHiztoddy6CZYxNBymMyGDRuoqKhgxowZUQu0OwtaWpKDz+djxYoVeDweJk+e3GY6zVrsQsC776bwxBNJHHecC9OEDz9UOflkV1TUX1Hk4rYCkeXlsnAIIBRSUJTw4kpMNNE0MIzo8zRNeOCB0eTm9mXZss2MGtXAjh0OBgxo4s9/3ss99zQzcKBJTY0kl8JClcsv99Kvn8mKFU1ceqmHujqFV15xkpIiKC1tpLjYx/HHG0ycWIuqyv0OGGDicIDXC0OHhk9CVaGgQOWee1xUV4ePLRCQFZSRD2e/H+bOjYsiRVWV8Zejjmrg4YdLueceF+++62DOnDgWLPDyzTcaH36o4fPBI48cWBrTqswcOnQoQ4cOJTs7m6SkJCorK1m9ejVr1qyhsLCQ+vr6HqmgjEUOjY2NUYHsbysOWswhlu6CVQKdm5tLTk5Oj1a3RZJDWxJuLXH22RoffaQydarg0ksNnn66iDvu6MOSJQn7zqn1ZxQl/LoVqDOMAODB44Hm5jDhZGQIdu0Kf05R5N+snxNOyCQnJ53UVEhONtm0KYG5cxOYOLGG0aOriY/PZORIweefy6KizEyTI4+Mo7JSxeOB/v0Fv/tdgI8/1ti6VeXFFzWqq1Xi4lSCQRkrSEwUNDQotnUwf36IkhKV5ctVQqHw9zFpksHHH/sYMCCB5GRBSUn4b01N0ddA0wShkMLZZ1fTv7/JscfqnHuuF0WBW28N4PXCHXe4ufRSD0lJgqOPDnHuuXEUFqrcd1+ASy9tEeHsIEzTRNO0KEWnQCBAdXW1PbzXmseZlpbWLTJ6scihubn5O2E59Dg5xBo9J4Rg9+7d7Nmzp8Ml0AcKy0rZtm1bTAm3WFiyREXXYelShaVLNWAYEE5NWk/IWLAWOkBFhVy8jY3RN+KuXfKmSkkxGDrUx5498ZSXR5dN79mjsmeP3F5amlzIa9emMnu2m8JCJ/n5Krm5jezZE8/atfLrTEwUeDxQXKxw551uRo0yGTnSxO9XuPDCAq69ti8FBRo/+YmX9eubmD49npISaQ6kpgrefddBKCTPz+kEr1ewd6/ClCnxNDdDc3P7CyoUktZFZaWDo47KpbragdMJQ4YY5Oc7eOUVmd2ZOlVn5UqNWbPC3/9zz2lommDBgs7nfmP5/263u5WMnjViL1JGLzU1tUszQtpyK74LMYceJYdYtQvBYJBNmzbhdrsPWgm0dSzr168nMzMzpoRbS+i6fPKPGSOorFQoL7e3ZD9RLWKILCiy/lVV0cpdaAt1dQ6KilzMnx9k9GjJDF9/7eD55zWEUMjM1HG7VcrKFNsaefDBcDfo7t3W4pKxi4YGhcZGGfAMBi2rRFBerjB5ci0pKX2ZOtVk+nSDp5928fXXTQwZIrfx1FMuex+qKtOwDofCpEkmICgocOD1YlsaFlQ1XCchhLwOt9+eS1ycyZAhsr38vfc0duyQxyKEwsqVrW+/1asdrFnjYOXKEP/8Z4DO3B7704+IlNHr37+/PTWr5YwQq9O0IzJ63+WYQ4+RQyw3oqamhs2bN3e6BPpAG2qqqqqorq5mxIgR5ObmdvAzcnEMHy5ISxNUV6vMnt3M0qVxDB4s6N9f8Nln8mkby70wDJkpUFURZZ7HgsslKC938X//JxeyxyNTkwkJ0NAAFRUd/ZoiA6MKug7l5Sbr1wdZs0YDBNdfP4lrrnEzYYJB//4mf/ubC0UJn0BkzYJpwi9/GeT3vw9ihWSSkhJaEYN8r9x3pGuUmBjC5VIpKHCwc6e6r4Ar+jhbQgh53f/3PydXXRVkyBBBR6urOytLFzk1K3JGSHV1NQUFBbaMXqQCdUv0uhWdQKzaBSEEO3fupLKystMl0LGk2TpzLJaEW1ZWVqdmYVZVSfN+1CjB//2fg4ULdV5+2cNf/1rCv/7Vj6VLFeLiZAyhLciKyf2TWjCo0LdvEJdLY+9eFZ8vHAOIdE8izoyMDKipkdt3OgUOhzze8eMNNm1S0XUZ/AwGVfbs8e57AgsGDqzH7XaSmwuK4sHh0Pjtb6Xb43BEWzu5uSY//KHBa69plJYqFBdbtRVtu1ORx1pb2/HOz8jzNE1puV1zjYeLLw5x/vkdczGsmENXEWtGSE1Nja1J6nK57GIsS0bPMIxW7qmlovVtR7eSg+VGrFy50jbd/X4/GzZsICUlhenTp3c6D+1wOGKy8/7QUsLNGljbUZSUyJs1OVnQ1AR33GEybVoNt92WxeefB3noIQcPPOBoY/HKzzU2RpPD0KGChoYA1dXuqIpHt9ukulpj+nSBx2Oya5eKwyFN95bbPu64EKapsmyZA49HBgNDIYW//93Pr3/tobFRIT1dcMIJOmPHSlP+448d9hO7vNxLUpKbV17R8PuVqBqNlgu+oEDlRz/ykpAgGDJEEB9vyerLv++vPyPWdZE9F/Jn4EBZ1t3yPIWQ5OD3Q1FRx++X7i6CaimjZ4nKRsroGYbRKtPV1NR0wNkKRVGeBOYC5UKIcQe0sS6i28jBGnVuEYSiKHZWoD1F5v2hK7UOlvsSKeHmcDhi1DlAW/fShg2yL+Lzz1Wys2W6LyVFMHq0j6lTE1HVtheHqoa7KC2ce65MG27f3oyiuCkrk+6EVe+gKLB6tQyAulyiVdBv3DiDP/0pyJVXevj3v31UVsp0ZXy8oKJC5cYbPcyYYXDBBTqDBpn8618u3nlHY+HCEA895GfePA9btjjYsyeBqioRQQQKYAAO2jL3GxsV1q8P/61lfKU9eDyCqVNNTjpJZ+JEg/nz4+yy7sLC6IsfFydjHLout71nj8ru3R3/7nu6QrLljJCmpia2bdtGaWkpe/bsITExkcLCQgKBQHekMp8G/o1Unz4k6DZysOIKVolxXl4eTU1NTJs27YAmRVuWQ0dgCcGUlZW1cl9a1znAEUc4GTBAMGKEID4e4uOlnx8fL3jjDekjv/eevNmSk11AFgkJBm63DKq1zD5YME1peiclCVRVLvyVKxUKChRUNcWOQVjNWLouXYPmZvm5pibFrrRUFLmd664LcsUVHh57zM/WrQ5ycgQ7d6pcd12I//3PSWmpwqpVDoSA99/3MWeOj61bVR580MnUqXFRhVr/+Iefzz/XeOUVJ6edpvPxxxpHH61zyik611/vYcKEZtatcxIKOfF6dfx+rctVjn6/wpdfOvjqK0eUxdGSPDMyZCYmK8u0MycVFUorAmkPB7N8WlEUEhISiIuLo1+/fiQkJNDQ0MBrr73G9u3bOf7445kzZw533XVXV8VlP9+nG3nI0K1uhaqqNDY20tzcTL9+/Rg5cuQB55E7Sg6hUMgWgonlvrQkB69X+tTvv+/g889lys76iBCto/EWGhst96b981JVWTAkhFzgVmow8mkb2QXZMgMiBFx4YYgxY0w+/dTBVVd5ueqqIHPmGDzxhJNvvlG55ZYAI0cK5s9v4qST4rn9dj/XX+9l+XKFGTMEI0eazJ5t8NRT0WbvT36is2aNxogRJiecoPOvf/l5+mknN97oQdchEHAzZYpg3TqB369x//2FvPpqPGvWJFFXt/8bPZarFfl7LIujslISYmWlGvWZdetUXn1V5aSTTPYX4zuUvRXWjJDbbruNd999l08//ZTly5cf9Clj3YluvZIlJSWsXbuWuLi4NpuXOouOkEN9fT0rVqygb9++jB49OuYNEmt2xR13yN91XTYZzZ5tMniwTlKSOCCtA48HTjzRxO2Gyy7TEUIu/lAIDCN8bJHVki2xfn0jDz4Y4PjjDeLj4eijDerqZGv4kiUaZ56pc+ONIebO1Rk2DFJS5A/ACSfE84c/OFm82MEvfiELjSxomkFNDVRXK5xwgs6TT0rVqCefdHHbbUEmTTIwDIV16zTi4qSLc801AyksTGPqVJUjj/SRm+tH09oOErrd8uINGtRMZ+KDQsieksivr7ZW4eKL4/jb31wsXuygsLD9UYSHuvHKqsKMj4/nuOOOO6jH0t3o1ivpcDiYMWMGHo8HvZsEDNqLOVjFVJs2bWLixIn2NKKObCcQgN27FRISpP9dVSVdiHXrNPbsUTpFDi4X3HdfyE65JScLNmxQ8Xrh+ec1EhJg3brW3YlCKG2m6SZMSODFF1VGjzZ55hk/TzzhY/FijYULPQSD8Pe/B6LeX18P11/vtXsf7r3XzYUXeomLE7zwQtgMUhSFHTtUamoU5swxKClROP74OBYuDHLddUESE6FvX2l1XHZZiFNOkQRaUKAye7bBa68ZrFqlk5jYdoDY75e3VVGRN0rHwu0WtOdhut2C8nI1pgtTUAB/+pOb8vLDmxwsfBdUt7v1Svbp08ceRd5dTS9tbUvXddavX099fT0zZszYb+ookhwKCyElxcUFFzjbjBu0DbHvuKzORRlEu+46qf7scknhlaIimWoMhWQr85QpYfMyJUXWPygKlJc3cu65zVFWhHV//+1vYa3F1FT46U9DvP66xuTJJpHW6qOPOqmqUnjoIV+UdoQUnlGoqJDn6PVCUpLOH//oobJS1kH4fAoDBpj88peWiC/U1CiUlyucfbbO00/7ueiiIELA3/7mZuTIBKZPj6OmRn4OoC3LOTJT43TKY2lP2yIQCDeetcTrr7vYtk1l3Li2Wftw0XP4LhAD9FDjlSXv1h2IRQ6NjY0sX76cjIwMxo0b16E0ZyQ55OZaikrSP87IEC3e296W5Bcvn4ICvx+uvVaKrAYC2BWJFrKzJQlY5dYAtbUy3iAETJ3q5ZNP3Lz44joyMuTxWVmU/HyV55+XdnlRkcLTTzsZMMBsMXULli1zkJUlGDPGpLlZli4PGSLbtwMBuPRSj33MRx1VzvbtKgUFKtdf7+Hqq4Ns3eqw9Sg0TVpRlZUKDz7opE+fBJ5/3sXIkQbBIKSmGhQWqigKFBerJCcLHA646y5/u9c/FAqnMKOvZeuF1NatM3Cg2W77+KGSiYvcZzAY7BZNTEVRXgC+BkYqilKsKMrCA95oJ9EjV9LhcHSrWxFJDiUlJaxfv57x48fvd15Fy+1Y5KAoYHkg1gKKRKRLkZgo952eLk3iI4+sBmR/gc8nn77336/hcmGb4JELoKJCksC4cQJVBbc7fC4OB+TnOygvd3DuuZMwDAW3W9jHEB8vuOIKD9OmxXHWWV5++UtZMbh9u8qaNfKrc7ngiSfkwrz1VvkInz3bYMKE8ElYgc9gUEHTBFOnGjQ0wAkn6NxyS5Cjj9Z5+WV5QwcCctGHQvDqqxrTpxv07y9Lo3NzTfLzHfY5WtWMt94aYNo0ub+jj9bp2zf66Z6QIGLqXEhrqeNpEGsfbeFQCcxGWgrdVQAlhDhfCNFXCOEUQvQXQjxxwBvtJLr1SloXqbvdCtM0MQyDjRs32q3dnc0jq6pKdTUsW6YwerSThobwTSnTfOEvOPJGbmhwcOyxBrt3h0hIEPTvH8ThgCVLQlx/vcG4cSYul5Rye/fd1haMRTxbtij7MgHyPddfH8Q0ITER8vIquOiiYlJTRVRxVEODLGjauVMlL0/l+eedrFnj4PbbA1x1lcc20f1+GWC0Fu6FF4b44gsH/fpJsRYLzc3w5ps5fPCBhqrCO+9obNmicsklIR54wMmsWXF8/rksmEpMlK7A6NEmTz7p4yc/CdkFSdb1ueWWIHffHaCwUOW666R18uWXGmVlLWXTYk/6sgKXIKKKsdrCpEnhc4kVlzgc1Ke/K30V8C1xK3w+H8uXLycpKYkJEyZ0qURWVVUWLhzID37gZNcuhaYmyz2w3iGfbl5v6xvv3HNNPv1UoU8fk2XLkjFN+POfHbz3nsqmTSqg7LdBKFLcZNw4k2XLNKZMMUhJEXz2mZvLLy9i7dpmamoaWbmy0c4wVFYqtpm9ZYtKbS37JlcJ7rvPRX09nHWWtLWnTZPW2rx5OnV1CgsWBNmxQx5YUpLgmGN0QiHZrp2QAH/+c4CTT/Zy+eUe8vNViovDWg2nnx5i69Ym7rknwNKlDu64w21fF0WBU04JkZkp9rWWG9x9d4AhQwySkwWDB5vk5LR8ykebDooSDlzKgTz799Mta+iTTxxkZiZQUNBSB+PQq09/VzoyoYcar7rTrWhoaKCkpIQpU6a0q9TUHgwD3n3Xw7ZtredaRroUbdU3XHGFk9mzBWDS0CCLeS67TM6euOEGjZ07lVZ+8rRpJqtWWZF3qe4MMhB5xBGCbdt8/OxnG7j66hls2SLrGaxjKCpyMGyYYOPGcACvb19ZamwYsH27XADLljl44gmNH/3IYPNmlU2bZEn1tm0yU+J2h3s0AgGF5cs14uJ0mps16uvhyivDAc9+/QQDBkif/ssvHfzwhzpffeXgttvcbNwYXnDJyYIhQ0x27HCQkyOtm4YGaR0kJ8tahZoahZqa9he7EJCWJqXwOlpg1dQU4Kuv3FxwgazHGDAg+oMHe6p3LGuolxzaQHe6FZbQbF1dHX369OkyMQDcc4+DP/85PKlKUaTF4G8zhiZbnz0egd8vz+mrrxROPFHYYqtffqny8ssqKSkCXYf0dGkdWJy4ebPKggUGL7zgIBgM30SzZpWzZEky//nPLsaOHcUzzwSJj6+nuLiRJUtK+N//BlJf7+SEEwwmTjR4+mnZvFRaqtpTryJRXq5SUyO1GgoKVLKzBc8952Tu3BCLF2voujzf+HhBdbVM3dpnuS9mMGyYQVoarFkjtSpDIbjiCi9ut2xXB1m78fLLzcyZY3L33S78fvjDH6JTD34/vP++g1/+0ssJJ+hUVjayZk1KzCuckmJSXa12WHMT4OqrvTQ3q3i9+j5isMq+wziYlkOshsDvivI09JDloGkagZZRvk7A5/Oxfv16u+mlPCym0CVcc43Bm2+arFolg25CtE0MAwcKiotlnUNGhsLFFxvcdZf0w1euVO3JUR98oJCTY7Jxo0p8PMybZ7BuncqaNQrx8ZIoKiqig5vJySbLl2cRFyf473/HcNZZfkpK3PzlL4OBQWiaQk5OkOHDa6mt9ZGXl8axx4b45BNp8ViZkIQEgc8nn9IDB5q8+aa2r9Vawe8XPPOMk1tuCbBokTxfRQlbRI2N8jWPxyrVhm3bpBhLaqrANGWH55w5Id5+W7538mSDa6/1s2GDgw8+0HjtNY3x4w3+9z+NvDx134+DoiIZUDUMwccfa5hmCpoWJkyXKyzTb6lnx7Iahg412LmztZ9WUeFm4kSDHTsUxo+v4uWXdwEaRxzhJi0trUdk4NpDrDTm4RpzUBTlDOD3LV6eAPxICPFuzM/s54J26mpb07ArKiqoqalhxIgRnfk40FrCra6ujqKiIsaN61pj2u7dMGLE/kpYTVqGXxwOOOssgwceMJg3T2PZsvDQWqdTKj7n5Sm4XDJdWVamcPPNOn/5i8b48YJNm2SBU2KinHgFkJwc5KabtjB//mguvFBj5crwPjMzA+TlhQupdu6E446L4/XXN3LiieNITAxRVRWuIFIUWLu2kcGD5QLr2zeB5mYYPNikqEjK03ePNm/YJWqJH/9YxzCgpEQhL0/FNGXQtV8/k7FjTdau1RkwwMn69WpEDYO0yrpJN3if9Fw5Tmc906blkZmZabddH0hPT0fg8/nYvn07EyZMsF/73//+R1lZGbfddltnNnXQCyMURbkc+AnwAyFEzG/jsAlImqbJtm3bKCwsZPr06ba2Y6xuyo7CMOD006NzzsnJgtRUmc8PxzVbfzdpafDGGw769HGxbJlKODkiy6Dz8hT++Eedmpogf/qTTigEzz8vn3bbtyukp8OUKcImBoCrrxb4fE4mTHCxcqWK0ym4/PIQDgdUVrpZuNDDkiUOdB3uu8/N5ZfrTJw4BFAxTVeUCe5wCFataiAUCrFhQ9gyKChQ7a7GA4UUyxVoWlg0NxJvvqnxzjsaa9Y48PkUAgF5zYuKVD78ULOb0yI/Z9V3OJ2QkxN9j1iK1SBnbnSkXEAIuOuuLP74x2EsWjSagQMHEgqF2LJlCytWrGD79u1UVVX1iBJ1W7L0h6PlEAlFUUYAvwN+2hYxQA/GHDoTkPT7/axfv5709PRWEm6xeiI6im3bYPPm6Dva8tkdDjOiz6E1OVRUtExpRv/d4YA333Swe7fK6tUKOTlSt9HrlUHO5maZNrXgcgkeecRNZeUYVBVuu03nmmt8xMUpPP+8kwsv3MmoUf25+243V10lp0vddlszJ54og28vvODj8cddLFokvzJdh0sv7dvquB0OwaOP+vn0U41nn429utxu6SrMmxdkzx4H69fLYTiVlUpUxagQ2FkYSzg3snnM5ZKitikpUFoqg5C5uVJC3+9XMAyV/v0NtmyJPg5Lr2HPHod9zIYhR/vFxcl29aOOMlrJ3UciNVXYjW0WfvzjPSQkTCEhIYHc3NwoZaf8/Hw0TSM1NZX09HRbrOVA0JZEXHtl/IcaiqI4geeBm4QQ7U5sPeSWQ1VVFatWrbKlxVt+YV0Nbq5dq3D88dKdiHUPRDZAtYXIFuPp0wXz55scdVQ5gwYJbr9dJxiEV15R2bxZYe5ck127FJKSZHovN9fANCE5WZJkMKhQWQknn7yXvXt9/Pa34WExQkBcnMmll4b45JNmjjnGYPhwk9/9Lo4VK2SB1aBBJh99FHnMVkm04M036/ZdK8Gpp+5h2bJKlixROOmk6IBhQoIgM9OPEIIVKxz8+tdeHnnERTCo8OCDPgYOlFaC2y0YNEgygK5DZqbgjTeaqatr5J//lENyR4wwUFXQNIWSEoW6OoWbbgqyYUMzd98dpLFRYfLkKj74QBJDy+yzdW3j4gTjx8sMCMjisvR0k4wM+Z62HsI1NdHE8OtfB0hNjb5PLGWnYcOGMX36dMaMGYPH46GoqIjly5ezadMmSkpK8LcdmW4X31Jx2T8Bm4QQL+7vjT1WIbm/BW1Jx+3cuZOpU6e2KQbTVXL45z8dZGZK0zSyPPrqq/PweNoPpbRMjKSnw3HHmTz3nM6llxZgGPDLX5osXx7iyit1HA5Yu1bl1FNNsrPlTb1tm4rLZVJXJ1fFsGEG5eVBfv3r7cTFRe9fPqHl4ti7V+HDDzUaGsLl1sEgzJiRQE2NpS0h7L4GIQQLF1rydwojR2by7rv9SEvTmThxV1RxUWOjQk2Ni9de83HyyTopKXI7a9Y4OPXUeDZvli7JyJEGycmwZ08jp5yiU1qqMHduHH36JPDCC05MU9ZqZGUJ7rorwMyZJj/9aYiPP5bneuaZspx8yZJ+NimkpQmczvCxWHUcl10WpE8fwZtvhnPIcXHw4Yca2dmmnWrOzpbnO2lSbIv0+uv3P3bPGrM3ZswYZsyYwcCBA9F1nby8vC65IN82cVlFUY4FzgKu7sj7e6xCsj23IhgMsnr1agzDYNq0aXg8njbf29WpV+ecY+LzSR/YyrlnZfmYNCl3n7gKbXYIttSFTEsTvPmmyty5GlddNZXiYoXMTBcej4s777R6H+Cdd1T27JHnbRgKwWA4VTd3LiQlxZ63KQRomjzHf/3LxYgROgUFKo891rwvDQkvvBAeDlFXp9DcLLMifr81ok/B4RA895yLe+8NUFPj5vjjZdt8//7ymNxuHV1XufJKjcceq2XJEh/Tp8sW6bQ0wTHHyEWxfr3GunVyzsVLL/kpLm7k0kuDBAKCb76Ri+HDDzV+/3s/mZkmmzap3H13gLIyhUsvdTNsWPy+XhLTFr4pL1eihHbr6xWmTjXYskUjK8uMqlkoKlJJSzPxeLBTsaoqP7t2bessRmKi2Cff33E3wRJryc3NZdKkSUyZMoX09HRqampYs2YNa9asoaCggIaGhjazIN+ybEUq8BSwQAjRocmu3Z7KlPMZ237ax5Jwaw+x5lN2BLt2YdckWNxSXu7hssusUmnRZlVjy6nR27ZJMtmyRWHMmDp+85t4HntMZc4cgzvvdJKbK9izRwbkAgEnMqMBN98s05vvvaeyYoXCFVdo1NUNJSfHRVycahNUKATr1iXzyCMajz3mxO+HMWNM+vZV7AXy9ttO4uLCw3FHjDBYvVrbF8xUASk5969/+Vi6VOO880IUFclg4D33hDjvPI1AQCM93U9hoYcTTnBxzz0rmDMnhw8+GMyJJ5osWSJdgP79TYqLVe64w82CBTpJSXDffUH+8IcggwcnYBhycS9c6MXjgSuvDBAXBwsWhPjkE9XuAjVNleRkk4EDBb/7XZB33nHw7LMuu2Bs1SoHLheccILgvPMkU1upz507VTQNWywnVvB47FiDTZscNDQoTJuWyAUXDGb8+LZJvz20FJe1Jn0XFRXR2NhIXFyc/XfrYWYYRqtq3cNYefoXQBbwUAsSvUsI8VKsD3RrKhOw5ei/+uorZs+eHd5QhITbhAkTOqVA3XJb7eGFF2D7dgdnnWUwdarLnpEAMGVKNfX1qYwcKXC54KGHdPr0Cac5k5Olb79uXWuDyuuF1auD3HtvMVlZA6mrk01Vy5cr7NnTuhW5Tx8ZA3joIZ1zznHaN71pRsvsCyHdhpYpPkujsv24bnSa8YwzdDZuVKmrU3jnHR8vvqjx1FNOCgqayM2Np75eQdMMRo6EvDwHgwcbVFYq3HnnDoYNK6axMYHTT5+B1yvrKFJSBLfcEuTqqyVb1tXBgAEJpKQIsrMF+fmqTaQDBxrcd5+fM86It4u1nE4dr1ejuFjWjs+aFccPf6jzwAPOVu3cGRkm9fWqPfi3JVqqaD3xhI+bb5ayeRdf7LFl8LKzBQ895OeEE7ovO2HpRVZXV1NdXU0oFCI5ORnTNElISKB///72excsWMBf//rXzqbxW5k8iqKcDNyPrPJ6XAhx94GeR2dxUMrJQqEQa9euxefzMX369E4RQ2exZInGnXc6eOQRP0lJIZsYALZsSUYIWSo8ZIjgt7/Vop4yGRlhYrDmW4J8cp13nkFJiZzF8MADDh580MFLL6ns2qUghElyshkVdGtqkgvk3XdVXC644QadwsIgb721gq1bG9iwIcCSJU385z8+HA44+uhwodfkyQZjxpikp0drPGRkCMaOjXSxwn8fMEDnmWf8TJhg0tiokJ1tkp+v2vGWK68M7nNxFIqKVO6/38+OHQ6OO87gggv6MWPGDKZOHQzAySeX4HIZ1NYq/P73bj7+WO4jL09eG6dTMHu2YRdSAeze7eCMM+JRVfjtbwMkJAji4kw7y1NcrFBWpjB/vk52dvRA3lBI6maeeqrOBx80RSlXWWjpWS5c6KWmRuHss70kJkJSknxDWZnCT37i5bzzPDFJpiuI5YJkZGTQ1NREUVGR7YJs27aNhoaGA7YcFEVxAP8HnAKMAc5XFGVMN5xKp9Dj4/Dq6urYtGkTQ4YMOSgpnqeeCrFrV4hHH01i1iyDb74J/83r1SkudrN4sTRZCwvl7AkLO3eGuXL4cGErLgsBzzzj4KmnHHi9Q/H5ZBxA1wWJiUG8Xo3aWkfUU765WeHrr4PceKOTpib5+SVLHOzePZGaGjeaBllZTrKzpSTdli2JmCZMmWJwyy1B9u5VePFFJ+XlDnuCVGWlYpczW7j55gCPPeZm8WIZudN1mDbN4Oyz4zAMQd++gupqaRV5vbLuICVF8Ic/uBk92sTpDG+vqkpejOrqPowbB/HxfgoKFC64wMvo0Q1Yt0tFhcqmTYLUVMFf/+rnyiu9tm6kokgVqtxcqS4tBKxfr7JqlYPjj5ekV1+vkJYm+POf/Vx9tTTR6+sV3n5b44MPHEyfbrJ0abhwqi1YRm9JiWx8czpNQiEpdb94sewz6QlYLkhtba09FKe6upr77ruP9evXc80113Dqqady4YUXdlVDcgawQwiRD6AoyovAPGBzN57GftHtloNlMlsSbps3b96vhFt3IRgMsmrVKh56aDejRgmWLYsOKlRXuwkEYM8exdYibBl8tApv1q9XOfHEsGlqmlKNafToerKzBT6fzDBUV7tpanK0qoMoLQ2yfLnK9u0KmibjH2ecYfDAA1vYvr2OiooAa9Y0sWSJb1/ALo64OGkZ/OIXHm680cPq1a2bktzusDaCyyXQNIW5c3UGDhRUVcEnn2g8+6yPnByDNWscrFihMnhwAr/6lduuYSgvV6mqUpg82eCttzQ++cTBhg0qS5bI22HHDpXJk03OOkth4kQHLpeD005zsnatTNHNmlVBRUWQ3/ymjBtv9NhFUp980sQZZ+iUlEil7aYmSSZ/+YuL9993cOKJOqoqW68rKxUWLND54osm+5r7fFIzcsMGOcS3b1/TzixZ2YqWsOKBhqEQCkWnenu6zcLKVrhcLvr06cN9991HTk4Ot99+O42NjQcyYCcHKIr4vXjfawcVPXL5dF0nEAhQV1fXIQm3/UFRlP1mLOrq6lixYgW5ubmMGTOMd98NkZbW+n2RRG59d9aEa+v/Fv75TyPq/YYBlZUumpoMHA6B2y0VmKqrw++ZOFEe57HHOnnpJQevvhrixz82mTnT5LbbNLZujSc+XtZC5OcrPPus07Y4mpsVXnxRo64uLPFmHY8VgxBC4cwzdcaPNwgGFR54wMkJJ4T41a+cHHFEPI2NMGhQAq+9JlOOzc2yHsDlklO309JC9rk8/7wTVRVcfrmHBQs8/O53cjJWaanCscfqnHyyztKlGhdfHGTrVrfdVj18eDIZGQ5efdWNzyfjJK+/nsfw4XU88YSPX/wiGBXs/egjjS++0Ow4wBFHGPj90sqZOFGwdWsTWVlhFiwvl9usrlZIS5PXc9Qok7g4OOaY6CBMW7fFyJH6QSOHSAghmDRpEtdcc82BNIHFMpkObuMIPUAODQ0NtiT3iBEjumVQ7v7SmcXFxWzevJnJkyfbGZA77nC0yjoAUYFDXZeVdn36iH0txGGJsqwswcCBMmtgLdBhw3Tq6lwMGSIVmmtrsSPzAIMGhbsm77jD4P33Q0yZIvZF8k0uvNDg978fxpQpSaSmupk6NYGrr44OrYdCii08u3BhkLQ0eU8oiuDpp33cdZef1atlezZIX/3ii7089JCbvXujexZSU+UvF1wQ5LzzQvj9Mr04fbphbzM+Xi6wf/wjwD/+EeDKK4P2OLp+/aQ2w9SpBosWhWdXfPqpk0suMXnvPVni/tFHtYwYoVFcXMzy5cs5+eRNOBzRUnYgbCtgxgwDhyOcYs7IEHzwQTP9+kV/x8GgQkmJPM/PPtNoboZVqzTGjTPs69IWtm7VuOyynu2taEt5uhtQDAyI+L0/UNJdG+8ouj3mUF1dzfjx49mxY0e360i2NNNM02TLli3ouh41sTsUgm++UToUkLJKcI85Rg7Mff11yZc//rHJ0Uc7SUgI+7arV2tccUUeDz00Co9H6gls327d4PJJN2GCye7dCqedZlJZCR9/rLJ0qcLzz2t2aq62VpKQwxH95Js+3eCXvwxyxRVemprgiSfCZothKCxYsP9ArqbJ9uxZs6SU/TffwPPPu3A6Ze+CyyWDlLJDUqGmRpCSIouvFiwI8fzzMj162WVe+vZt5qSTdG67zUP//nJMX0KCVKa+5hrp0C9e3MTUqRrQhz59+iCEoLGxkQkTmvjyy4R9aUiD+nqNvn0TcDikvmW4F0WWj+/YIWtCBg82KSiI3bEpW+0FGzd27IGzdKmDjRvbF6U9EMSyHKzBTgeIFcBwRVEGA3uA84ALDnSjnUW3k4M1rbinRWb9fj/r1q2jT58+5ObmRn0hv/+9akfW9wfrBpw+3aC42CrigldecXDXXToLFhikpblQVYPmZo2HHhqJpsGkSSbffBPWcWxokPLzV18tn7BHHOFkxw4ZeCsrk4RlWTK1tdE3z4gRBmVlJg8/HKS+XmlzoI6ihFWvW6ZOs7MFTU1yYlRiInzxhcbgwaadAuzfX7BmTROrVq1g+vTpFBcrHHdcHHv3KpSXw223uTj3XJ3PP3cwYIBg4kSDuXPjGDXKoKpKYeRIucCCQTloRtfhkUd8HHWUaHGMComJiVx1lYOvvxYYhsrQoQbBoI/t2xOjxGqsAb4gCW3GDIMTTzSoq5NBTV1vPUOzujqy76b9BrNJk8weIwaIbTl0h/UghNAVRbkaWIJMZT4phNh0wBvuJHrMK+tONaiW5GD1Y4wYMYKBAwdGEcMbb8C99+6f81qS+z/+ofHSS/KLNk05FWr2bJ0NG9YzZ04NwaC1TQWvV9jEYNUiCAHjx7tYulQGEauq5EIqLFSi0qkAmiazCBaGDROMHFnPn//spqEh3LUY+VCyZj4oCsyfH9xX0ajbfysrk1oKixb5+OKLZgoKGvnNb4JkZsr97NqlcO65Hhoa5Hn07y/Iy5O+vvTvVcaOjefjjzWGDjV49FE/8fGCzZsdJCYKuzJR16XU/ZFHhjjrrNjkb5qyXNzKsuTluVHVeNzu6HOKRFOTwiefaNx2m5u//tVtq1W3h0hiUBSiyrMBPvzQwa9+1XMTp1pWSAYCgXarfTsDIcRiIcQIIcRQIcRfumWjnUS3F0EZhoGu62zdupX09HQyMjK6fnT7sHHjRgYMGEBSUhIFBQWUl5czceLEVl/Egw+q3HBDx4yhnBzZ1ef3ywKn6dNNTjnF5JZb5Ofdbtld6XIJcnNhx47YpqKVwov1FPN6BWPGCFavVm2hE9lHET3qPjNToCh+ysu99O0rOPFEnc2bFVauDJ/LX//qZ+FCnUWLZIv07t2yKvLddzVSUuTCyMwU5OWpXHNNkDvukHUNr76qcemlHhwOa7KXwZw5cOaZIX70I31foDKBYFDqMFRUyEKktDTB2LEGxcUqW7eqUeemadhVodnZgowMGU/QdRlH2LNHqlY1N+vU1Tlxu8U+60qxP5+cLKiqUiK2KeM+bres76irU6mvP/Bn14oVTYwc2TOxvBUrVjBt2jT74VRRUcHPfvYzPvroo85u6qDrOXQEPVbnoGlat1oOwWCQdevW4XK5Ys7CvPlmlX/9q+Onk5ODXSh01FEyTnDHHTIuMHSoTnExZGVB//4qGzfG/u6sm9w04YEH5LkuWCBl3eLjZUBz1Sqp5xjpKkQSA8igpqJIoistVWK2Wv/qVx4efNBkwQKdN9/UeOIJnx2D+N//mnnlFSfFxQqXXhri1792s2iRk9dea+bYY2VjWCgkg6yhkMGPf2zy2mtOrrvOw/HH6/z1r36uv95jD7AdNcoaiedg+HAz5tzL+nqxT7tBVohaUvXWe+WUcPl9BAKytLxPH8GcOTqaprB9u0JdnQNNY1/mQmZmgkGVoqLo66MoAq9XaZV23h8eecTXY8RgIdJqPVz7KrqKHnUruivmYBgGW7ZsISsrizFjxrQihh07iCKGlt9PYmK0OasoghUrFFavVjn/fJ3/+z+dW2+VXYrSJ3bQ1KRRVKTx9ddq1ITqPn38tksSFyczHDfdZHL22YJrrnHue/oJXC7F1pJwOmU8Yu3aYJQ7Ex8veOIJH+ed10x2dhOxDbXwBwoLVe66S07Unj8/bt8ClFOr/vznAKWlUlk6L6+RjAzBzJnx3HOPiyFDzH19HIKGBo1339VobJRy+qYpuPfeaDIaOVLw5ZfNbNrUREaGiKoWld+H7OewZPRVVTY/9etnkpoafm98fDhdZMVJVq92sGePrNI89VSd//3Px+bNjfuG9UiScDhkhiUlxUBVZfl7Z4nhwgtDnH9+9wu8tIdvQbt2p9DtboUlFVdcXIxpmuTm5nb96ICysjI2b97MoEGDGDx4cMz3NDdDVpZrX7uxydatkcNqpX9dUtJaIToSlnvgdksRmFhGj8sln8ApKVJ41u+X1sO2bUH+8hcHjz/usBWTrH398Icmr72m75sTEWDhQje1tdIPTk42efXVBm67LZ5ly2SWwDCktoPbbWCaokNTrZOSTB54IMCUKSbHHRfHSy/JbsvHH9e45RZPu/0ZFlmFbwOrw1O6SbFuD9kNKv9uicC0vlYCh8PE5wuz8ty5Oueco/PZZw5eftnJrFkGu3cr7N6t4nZLN6ykJEyGiiKtu5oatdXgof0hLk6wd2/T/t94AFixQgZ3LSxfvpwXX3yRxx57rLObOizdisM2ICmEYNu2bRQXFzNgwIB29QCbm8M3qPTFI7cjKyLbIoaw/JlcBYFAbGIA+eQ76aQqGhsVO36QliaoqYHHHw8HMw1DEsn77wd54w1JDBs3VnH55W5mzGi0F2RdncrxxyezbJnslgS47LIA55wTQtM0Ro60Zk60PnhNs1atQn29ysUXe5kwIY4jjzS44AIvFRVywvcHHzSTnCyPMz5ekJYWxOWS55yWJuz0ahiypNyKAUReJwvjxxvs3NnIqadKa8s6n+RkWTPidMo4Sv/+0pdyOODUU0O8/77GLbe4+eYbB/fe62fRIh/LlzdTWtrIypVNPPecVUAl7O9u797OEwPA3Lkxily6EbEyE71uRQdxIG6FVQatqipTpkzB5XK1u62UFBlU1LTYcyein2yi1d9aznBUVWxx2Ei88UaIP/yhEKdT2GTTty9MnRr9dD/uOJPa2iDHHCNvoiVL9nDJJXGccw588UVKjPy9oL7ew8MPN/P3v/uprFT55S/9lJbKEuCsLGXf+8KfCU/GElHtzEOHmhgGjByZwIIFHjZvVklLkz0VoZBCdbWL++/34XZLqfpQSAZIzzknxIcfNpORIdi9u5EnnwxEVWda11BOEHcwfnwC77yjUV0tYwWzZxv84Q9BXn7ZR2lpI2vX1vDkk+sASZZLlzr56KNmVBU2bVJZvz7c0akokkymTze58EKd004z6NfPbJXZaOnexPo+5fsM/vc/F7feeuAFeG2hLVn675Jb0WO9FV0NSFpl0AMHDmTYsGH71YeQ+4LXXgvup73ZSnW1tODCT2CnUwbthAhPx5bnJBuXSksVXC6Fe+8NV1etXRuWK5OuQ5BHH9X5058czJzpJDnZxbx5gxk+PJ6vv3bYU568XoP583fKIxCyj2DePIUtW9ysXKlx+eUG1dXqvoUpCcBSf2qN8Os/+1kdeXlNjB0rKzs//FCjtDQcGxg7tpZlyzT8fikOk5IiuOeeII8/HmDGDKm9cOqpXm64IWypRZJrXZ1CU5Os69A0+POf/RxzjMHKlQ7++lcXixY59ylRy9Z0VZWWw9SpOo8+6iQ5WXDaaToPP+xi+vS4qIE5IKdaPfusnxUrmpkzRypKWR2cPl8s6zv8msslOOooncREhZ/9rJxjjlnHypUr2blzJ7W1tV0WKo6Fb5PQS1fR7TEHIQTBYLBLkvLFxcUUFRUxceJE4iLaJUtLS/H5fAwZMqTNz65dqzBrVtemGycmQp8+pl2cc8opUsFoyRI5tCYjQ0qsVVTAzJkNXHGFwW9/mxw1ji093aRfP4W8PPk0lv0aMphmXWKHQ76WkABXXbWbe+8dQGKiAEzKy50MGNDMsGGCE05Q+OUvFZKTpZhKcrKgvFwKv7QVmHM6JaGNGdPAvHm7mTpV4Re/GMV//+sjOVnhlFO8qCo0NZkEgw6cTmF3PSYlCc46S2f0aJM77nDRt6+gsVGa9JagShitZfwjYbkpmgYZGX5KSmRj1tSpcjsDB5p8+WUzX37p4IILPPj9CtdcE+SWW4K0bGCsr4cTTvCSlxe5/1gEL6GqcOONQW6+OWh3ZOq6Tk1NDVVVVdTX1+P1eklLSyM9Pf2AahJiydI//vjjOJ1Orr66Qypskfh+xRw6UyFpmiYbN26kurqaGTNmRBEDdMxF+dOfHDEbbVp//635rqFBVu3Fxck25E8+UViyRGXWLJOsLPjmmxC7dgV59lmdNWviueuu+FZzGquqVDZsUGxT2VJuTkmR5cann67v8/GlGOuHH2Zwxhkmy5cHyc/XGTbMpKgojk8+icfj2cnbb6/dtx1Z4CSENM/vuiu2A25dnuHDPaxYMZJLLhlNbm4z8+e7KCvbSJ8+Qf7ylwYSEnQ7LpKUJOsnUlMFTz3l5JZb3Dgcsitz7155MS1imDJFxhduv11nxAiz1eBbr1cwcKAU1XW7ZSakpMRjW2HBoEDTZJ+JorBPXbqZvn1NHn7YxZFHxrFunUpJCSxY4KFfv3j6908gL89h62tKxF5H2dkBHnywiqeecvLZZ2Ey0TSNzMxMRo0axfTp0xkyZAimaUbpRlZXV3dplEJLt6K5ubnTA54PZ/SY5eD3+9m0aRNTp05t9/0+n49169bRt2/fVmXQFqqqqqioqGDUqFFtbqeiAgYMaDuyn5gIoZAZMbzVQrSaUleRkCCYNctk4EAfzc1V9O2bhcfjRFVNqqsVamtVAgGd995zEAppKIo8pk2bfHbqtV8/D3V1ssXb5ZJWgtNpousq48Y1sHlzAkVFDYwYkYQVa2hZig0y0HjGGSFyckwefthNVZXCuHHNJCX5aGoyWL1aNqfNnRuislJlyxaZViwpUfj6awfBYDjGoaqSSEaNMtm5U2XqVIMVKxxMn27wzTcO0tNl7MK6jdxuaS395jf1pKUVcd11Y9F1uPrqIBs3Oti1S+Xhh/0ceaRBRYXCr3/t5o03NDvAeyCYNSvAD34gBw3fdluQhQvbD0oahkFtbS1VVVXU1tbidrttq8Lr9bbbI1FfX09JSUnUPXn33XczadIk5s+f39lDPywthx7RkISOWQ5VVVXk5eXZ063aQkdEZjMz4eGHg/ziF7EJwu8Pj7eXTzarj0KQkyP1JHftCvdWWCXMuk67KVALjY0KH37oABKABHse59ixBuvWOYiLMwkEnEydqrNihSX/Jnj4YY2bbtJZulTdpzgkg4dOp0BVFXRdlmP/6EcK27bBZ5/l8eSTJlddNZWKivC4u8iFVV2t2E1bVjZGUVx88YW0yGbN8rFqldsed5eSYlBbKwOpN9wQYt48WVxllT/Hx8uZHAkJgvff93HJJR6GDTMZN87g6addrFnTyOzZCWRlhZumfve7JGAsbjd4PIKXXnLy17/62brVwS9/6ebUU3VeecVJSYnSJilYre1WPcf+8M03br75Rp7vDTe4CQYFV1zRdiDK4XCQnp5uK5/7fD6qq6vZsWMHfr+f5ORk0tPTSUlJadX0F6vpqrGx8TtlOfRIheT+gohCCAoKCqioqGDq1Kn79f06mvm4+GLIzg5yxhmtCcKaJTlqlJ+8PA9OpywBLipSKCqKjgtYu2qZQotchFJbQf4MGiQ47ri9PPlkX1RV5tg1TWoRbNjgIDHRICEhQDDoYdkylx39r6xU+P3vnTz3nIP8fJXRo03uvDPE4487eOstjfT0MFG8+GI8oZBCRsZEVq82aW4OW0CpqUHq6pwIodi1B9ZxWpy6dm34q96502OrOQNMmNDIkCGVfPVVPA8+mLbvXAVut8xENDUpFBeHtTDOPFPnjjtcVFbKeojjjotDVeFvf/MzerRg/PhwxF6K7io0NsKVV3oJheT1feCB8HcUq/RczvHs/AP1yCMN/vUvPx995OCcczoXEPd6veTk5JCTk4NpmtTV1VFVVcWuXbvQNM22KuLj4791svRdQY/FHGJJsIMMEK1btw6/379fWXoLnUmLrlnT1ikpaJpp33ChEOzcqbQyZ9vbTeT7MjNFxFCaJsaPF+Tn+8nJkRqOSUmCwYNlv0FCQpAf/lAjPz9AdbWPzZv9/O53YZN3xw7Zu7B5s8pVV7lYu1aa61VVMqOQn+/nvvukzsJZZ7m49VYvTU3hG7OmxoVhhK939Ni8sLqVfSWU6O/liy+SaGzM5ZRTksjIkKt07Ng6AgFITdV55ZV6+vaVsY85c+IYNMigrEzlmWd8JCdLMdrGRjjnnLgoYmgJv7/19XW75TDgs88OccIJOllZgpNOir2orfNqSxUK4MsvHRQXK/z85zrtGKP7haqqpKamRg3EcblcFBQUsHz5cnbv3k1zczOhCNGQ7laeVhRlvqIomxRFMRVFmdZtG+4gDt68cqTZtXz5crKyshg9enSHlXI6Qw6bNrW9TV1XKSqSKTqZJeg6Bg8Ot2BPmaLw8MN9SU832bzZxx13BNm9W+GjjxwoiqCuzsvTT7uYP9/FZ5+p9O0r+NWvdH73u3Df9e23h7jkEp2yMmnJVFXJp3Zzs8KwYR7uu8+JyyW1Fq3FPnKkGaVi5XLJz2Rk6EycWMekSTUkJ+utUrzl5TIL4XbLa3DeeUG++MLBtGk6+flu5CTvRNLSTKqrVUpKdnDNNWsYMCBAba3gyCPjaWoSnHZaHFVVCj6fTFlOnGhyySVBbrrJT3Jyx76vnByT6dNNxowxOe00HRC8/77WikSSk4Ut8FJZqbYrPz9/flyHXMHOwO1207dvX8aNG8eMGTNITk5G13XWr1/PqlWr+M9//mNnQ7oRG4Ezgc+7c6MdRY+QQ6xATllZGevXr2f8+PH069evU9vrzGCbNWtij79rich+if1h5Eg5rs363k85pYGhQ31kZflwueQ8DCm2qnH77W4eeURjwACZc5w1y6S5WcYYPv3UwQUXuMnN9XLNNU6KilRycuR5vf22w45vJCTAxImGnX2pr1fYtk2x+xasQS9PPx3gyy9lZaWiwC23BBECyss11q1LZvPmVDweWcbs9eosWrSaNWt2kJEhWLPGQSCg8PbbAR59VOeWWwLMnZuI36/gcgmamwVHHy1z+XfdNZmCgtEYhoP4+OZ9x6CgaYL772/imWd8zJlj8MEHzUybZvLiiy7q6sKWTaTSdEvk56v8738af/yjm2uv9VBeHvuWvPbaoB18VVV47LE2RC+QrszcuT2kLou8v10uF1lZWUydOpUJEybgcrnYuXMnp59+OhdccAFNTQdeui2E2CKE2NoNh9wl9LjlIIRg69atFBcXM3369C4FbDpqOQghmDy5nrS0rs0+bAuFhQr5+Sq33ipNhQUL8lmzxuCii+TNumaNg6Iihb/9zUUw6Ofkk3fx1FONOJ1w//0h5s416NtX8J//BHj88SAnnWTw+usaTz2lUVqq4nAI1q1TefZZmcXwegVpaXDFFTonnigl0Wpr5ZBbTYOvv/aRmiqYPdvLl1+qPPBAACHgzjtd/PznIRYvDlBZ6aOkpJof/rCYH/3Ih65rHHlkLnl5Gj6f1FrweEzi4+tRFIWf/hQuvli3U7CBgEpOjkEgILtG77orjpoaBxUVCRx7rM7TT1eg6wp+/1Y2bCimoMBgzJg4XnlFo7g4fFstXBiguVlaO1ZMz3IlOiqY5PEI/vQnqZYN0mL7/e89tlx/LHz1lXbA2Y/2EBlzcDqdnHPOOaSkpLB8+XJuvfXWVun4byN6nBxWrlyJw+FgypQpODsyUz0GOmI5GIbBhg0buOqqQmpru/epYc1Z/f3v5fFfdNE4duxI5Oc/F7jdguZmuOQSnfHjAyxa5KKqagC7dqVgmlLi/rzz5GLcvl3ltNMMHn88yIQJ0hKRcu7hVWJlSVwumQHZsUNl9GjB/Pk6hiGthiOO8DJ0qNR//M1vXPztby475bhqlYM5c0xCoXq++moDb7wxkJ//XCMjQ/DVV4lcddUgTFOqRGVkmMyfn8L//reejRs3smKF9D8cDtkBOmWKsm+aeCMLFgTw+RQGDTJ47rkG5s1z4fXCbbdN5r77hmGacP/96/n88/AtlZkZ4O23XQSDUv7N6ZSaEYGA3H4s4Zdwr0sYM2bIwinLynK54LXXmsnMFEyY0Pqh0b+/yW23BTtMPl1BrDoHn89HXFwcEyZM6LBU3AknnICiKBtj/MzriePuDHqMHOrq6mhqaiInJ8cug+4q9vdZv9/PypUrSUlJYfbs0fzkJ+EbpqMCwHFxgszMyH2G/x8fj62oBBAMOggGIS3N5Mor5YL685+d5OU50XUnTzxhsHKlajc2/fCHBo2NMgaxfr3CMce4+fxzlf/8J0CfPlIVKjFRFgj94Q9BkpPh/fcdvPyyDK5df32IBx8MkZoq+NOfgkyaJBdYc7M0oXfvlrGGmTNNVq5UOesswebNm1m2bDrHHy8Dpy4XXHGFe18DFqxZE2DSJIXJk1V+85uZ1NYOYuVK6cjPnFmOw2Hym984CQbh3//28sEHLsaPN8jIgBkzUpg+PQEwCQYVMjMFe/a4uPTSieh6+IJXVbmpqpJl6z6fYPp0nWOOMcjMDE/wtpCWJpWurCyQhcREwaWXhrj1VjerVsnFePXVAc4/30N5uWIP743E9Okmv/rV/gfrHghiZSuATitOf/jhhwghxsX4eaO7jrWr6BFy2LNnD5s3byYlJaXd+oXuQE1NDatWrWL48OF2e/j99xt2wKotg0M2C5lkZsoqyrg4WR4NraP7Q4fq/Pe/n0cRhqLArbe6OP106Wp4PCbBoMqECYLHH9fYuFFl8GB5l7tccPzxOp98onLaaR4UBX796xAnnywzGyNHCrZs8RMXBw895OThh4OUl/s4/3y5eubPd5Ob66GmRhLMxo0qZ56pM3lymAQNAwoKZBzgvffieP752TzySBy33BLi4YcdlJcr/OAHBgUFCp984sPphCuuCPHVVw5+9COD88/PIC1NnmBCQiqBgEpZmfz9nXcclJQobNjgYPFijYoKhfx8B1Y3fmMj5OYaUUNoPB6TESN8PPlk3b7OWJUvvtB48UUnFRWtb7uLLw6xd28jP/hBdOFSQ4PCpZd6+Oorhz3Q59573WzZ4rBFdVqOh3jtNY0tW3rWKO5B5enDB1braRs/XUJlZaVoamoSy5cvFxUVFcLv9x/wz8cff9zqtR07dohPPvlE1NTUtPrbr34VEmC2+3PFFSHRt68p7r03YL/mdJpiwABDHHusHvXeoUPl9jTNFKpqiJEja4XbHdr3GUOMG6eLOXN04XKZIiPDFH36GOKyy4Kivr5J3H9/QCQnm0JRTPH00z6RnW2KsrIm8corPqFppvj002bR1NQknnrKL8aMMURWlil+/euguP32gLjqqqAoLm4SHo8hwBTDh+tC09o+J0UJ/z8x0RQZGYbQNFN4vfK1zExDDBhgiL59DZGRYQhVNYWqmiI52Yi5vdzckIiPN8SECQ3C4wmJ4cMbxL//XSTeeadGZGUZIi5ObsPpjPycIRQl+ljS0w2RnR19Tfv2bRZTpjRGHG/sY4j1Yx23pplC01p/btaskKivr++xn6+//lqUlpbav9fV1YlJkyZ1dcnEXH/AGUiZ+gBQBizZz3rt1p8eodfk5GQcDke3qkFFwjRNNm/eTGVlJTNmzIiZPvr1r/e/38WLVY44wuSGG6SpEB8Py5aFuPZag6VLrUsjnwiFheq+fYPXq7B9eyKBgCWFr7Bxo8r9929l6FCdujo5mCUzU3DUUR5eftnBu+/68Xrhz392cfPNoX1FQW5ycsL1EqefLpWen3nGz6pVKvfd52TUKJPUVPjww8C+41DsmRJz5xrMny+ti2OPrSElJRTV1uxySQm7fv3khK4hQwRTppj75OJkEZZpynOy5m14vWFT66yzdE46SXDUUSabNsWTmqqQlubittv6cNZZCQSDQZqb5T5CIezUqKwpMfB6ZeVpUpJJVZVCWZmKxyO7Mk8+Wcfnc7Nhg9d2/TqTQbKOW9cj29fDyMtrPS2sO9GyK1P0wM6EEK8JIfoLIdxCiGwhxA+7fSftoMcqJKFzzVcdgRCCUCjEunXrSE9PZ/To0W3GI666av+9/IWF4bF42dmCW281GDNGcMIJWoQ/LP9u3YCy+lDsm8cg9smaScHYo44aSXp6YF/Js8pdd2lkZgoqKhSOP96Nzycl7b75RmHRIjnefsmS8PAdlwsuvVTntdc0nnoqwJAhXv7wBxd+vywQssq+jz02xMaNTlavVrn7bh8vv6yxYEEDeXkpxMeLfYNx5DG//HKAefNkQ9Xu3QrFxY5WsvYOh8wkJCUJ2+T3eOD118O3h2FAaalKaWl4Qfj90dc4Pj5IICD9uVAofF719SqqKnA45EyH99/XmDEjxJ/+5KN/f8EbbzjZskVl2bKu3Y6aBm53iKYmSfIZGSaVlSrvvefglFN6Riqu5RwVn8/XowOiDwV6dJBud8rTq6pqD+UdMWIEmZHRwxh4//2WIqXtN/aUlSn88Y8O3ntP0Nho0NalMQwpKBMpN2+aVpmxSlOTN2I/StRELOu1RYvktpcvl+Kzzz0n04uTJ5ssXKgzbZqHoUNNjjrK5N57g5x6qpubb5ZWxK5dCp9+6sTphGuu8VNevh2YyOef92PUKMHatVL1KjkZxo41+elPXW3OwYiPh2HDTDZulGpLdXVyfmVBgcr69VJS36q9aHn9HA6p4O12CyZNErzxhoPqajfhluoQEA7emKZCcrK0kmprFZYudfLFF+G/xxZyAY9Hx++X10tR4OSTQ3g8gtdfd9l6nbqOTQwgi6Q++qiZ6dN7dmZFpOXwXdOPhB5OZXanW6HrOps2bWLSpEn7JQaAoUOjbzZ5Y7e2MiKDyzU1CkuWOCNmVMRGJDG4XDKAaQmxRC4gj0cGzOSPyYgRDVGly5JQ4PHHNebPd9G/v5f58100NsKvfuVi0yaFU05xU1KicOKJBpWVKn/6k3zsh0KCvXvLGTRIzld9/30Hs2fr1NbK+RUPPhjA42ktrmuds8sli5O2bFHtxT9ggKCsTGXMGJOcHJkRsb4+KSIraxQ0Tf4/Pl5aGu+/7yAtLURcnB5xjVunrWtqFEpKpFhserp0cWbN0snNNWIKuSgK+P0aWVnha/vuu05ee821r/1bdoC2VPN2u80eJQZ5LCKKHBobG79TfRVwENyKA7UchBBs376dYDDYqaG855wj+Oab8O9OJ9x3X5Crroq+aTsuDiRFTo45xuC00ww++khl2zaV5maFvXsViovVfTUL2J2Vb70V4KKLXBgG1NaqDB8eh6aZTJnSwH/+k4Kqmni9AtNUcDikYG1kb8jeveGbfuNGlWOPlWpKmibbuBcvzuGYY+QJnHSSzp13ymYmv1/h/PNj1xcnJMgFFR8vBWQcDrngCwt9GAZ88IGDxYsdlJY6mDhRKkqvXi0zFw0NsuioqUn2pNTXK9TVyUVbV+fsVF1BZaWyL/vQ9vNJiPDw4JYIhcLaGa3/Ji2h9kqsuwMtZem/C4VPkTisLYdQKMTq1atRFIXU1NRO1UpceaXJSy+FiSkUgoceko/Qc8/t+FMlLk4wfHiDPe35888d3HKLiyVLNAoKZEDT7ZYk4/HIYp8jj7QG2Lo5+2yD+Hh45JEgH3zgwO1WKCtLpE8fk1BIxe9XueCCvWRmNtiiscnJMj13zjk6q1b5+fnP5Xm88orGjh2KXUtQU6PZLepPPx0mPYdDmukuF1EDZ4cPl0/opiaoqlLIyBCcdJJBZqbgpJPcDB/u5aGHNHJyBI8+GuD//i/Ab34T4o03AsyebXLSSTq6Lsf1NTezT37OQFFaW00dw/4/YJrEcM3CGDZMb0FK0kpbs+bgpha/ax2Z0MMxB03TaO7swIF9aGxsZP369QwZMoQ+ffqwYcOGThPNvHkmn34a4thj5cKx9Ao/+KBtTlRV2QxUWanSv3+I7dudXHGFyT33qLbfLYQsbCovl4KugYADt1tWUhYWqtTUSB2CRx4JcPnlbt5+28/48YK//U2webN8qk2bZrB3rwwavvBCX2bPNsnLU8jODvGjH+1hwYLdZGRkkJ6eyUUXJTJkiMmSJQE+/jgxyv+3/vV4BLNnm8ybZzB1qsnw4YKf/czFm286cLnA4TDZvt2BwyGIj5cDf/fsUXj/fQcJCTJ7Yc2V/OILlc8+UzFNGb8wTcjPV8jIUEhJEXaPg7S6WgZ+W4vnjBkjxwUYhjXMV6pvtbQI9hcXaglFgZ07w7ewbP1W9kn6bWTNGt3Wa4iLi+uOAbdtopccOgjrS+hqQLKiooJt27Yxfvx4kpKS7G11xQqZNUvw2WdB5syxxE/kHIS2YJqyYMfpNPH5Agwa5OCuu5JtufQvvvBz6aUulixxkJIiePZZjb59BS+8EODYYz2kpspF9tVXDm66ycXf/hZk2DDBX/7iJC9PsQt2Nm50kJQkaG5WaGpS+OADBwsXhvj733WWLevLF1/04ZNPTJYvd+PxhEhJCVBZKfsJNA3mz9dZvVplzx5JNlddpRMXB1984eCxx5zs3BlepLouJ0lZ2Q6fTwYTb7wxxPHHm620G2NhyhQPzz0X4KSTWpemq6rM9jQ0KEyfbvDpp+E0YlIS/Pe/UtPx1ludvPmmA1UVrFrlZ9kylSuukLa/0ynswG5KSjOVla1NdGtuiNX/4XJFq41bLuLttwc47bTxBAIBqqqqyM/Px+fzkZKSYou3xKpu7ChipS17A5KdRGcXtBCC/Px8CgoKmD59uk0M0LnOzJY455zIqLlqm6FZWS1NUus9svGouDiBggKV224L2ovy3HPdrFkT4LbbZJdgebnC5MnGvnHycMcdQc46y8AwpHWxfr3KpEke1qyR6cXp0w0GDpSzJQ1DiSohfuIJJ5mZXs48083f/+7hq688NDU5yMoKMW6cj1BI5f77V9Cvn4/FixVOPjlEQYGPvn2lBuTRR5s880yQZcv8bNrkw+9XOP54w16oVgWjacop4jff7OQXv9B46y2Vqqr2r2FNjcK8eW5qa6Nft1SzHA4ZoLzuuhApKbIUHCAz02TRIge5uYLnnw+ydKkfTVOYMsVrE0NWluCxx2QvhK7Tihis72jmzGo0TTBpks777wfslGxkkPebb+q4/nqps6BpGn369GH8+PFMmzaNjIwMqqurWb16NevWraO4uBhfW6mcdmCaZqsy6d6AZGc33ok6B6txyu12M3Xq1FYXv6uWw+7dRA1shfATpqKiY517F19skJ+v8tJLsow4M9ONzxc+vsWLreG7gmnTTH77W6e9ACsqFG66KcR//iP39eWX7T+xDAP69jWZMcPknXcc+P2Qn5+A0xlP//4KhYWTKC11csklFcybt4X162HIkMlMmqTyk5/Ec+ONIY44wmTBAheKItOGM2aY5OdLc/uEEww2blQoKFDZtUv+vPRSeP8Ohwxa9u8vmDnT5Kc/DTFoEJSXQ9hlCLdOn322zpFHmlx3nYsHHghw5ZWuqP6InTtVXnpJ4de/lkQ8fLggIUFQXx/+TiorFR55RAY0c3IE998f5LLLXLb7MmqUzpYtGkuXpiEE7NwJJ5zginCt5PtmzTIZNkzbZ4WY9v1iGAaKopCSkkJamlS68vl8VFVVsW3bNoLBYJRVsb/+iO+DLD30sJ5DR90Kn8/H8uXLycjIaFMEpqvkMGAAPPRQ7GOwxFIAcnLa3nZurod//UujvFzZd7zqvmEzkmWsww0EFGbO9PD++459ugrSWvj735327Ah5LvLfY4/VOe88GXLXNGErZefnq7z4okZjo8KwYaF9szZVCgpk1+U55+gMHZrC9OnTmThxIgkJCsFgFUcdVcRvf6tx4okuCgsV7rknyOefBzj/fJ3mZoVTTjH4wQ9MNm4MUFsrR+Y5nfDCCwGeeCLI9OkG/fpJi2bLFpUnn9T4wQ+8DB5sFfdIYsjONsnNlXGVY44xWbjQYOJEkzvvdPHll7JHxOeTHZgABQXw619LcszK8toj7/r2DXdZVlfL1/r3F6SkwI4d4ZmkW7ZojBkTHujb3KxFxStU1eCuu7bzn/8Uommy58HpdOLxeHC5XDgcDhRFwTAMQqEQwWAQl8tFv379mDhxIlOmTCEtLY3KykpWrlzJhg0bKCkpIdDGqK1YTVffNeVpOAzcCsvMGz16NP3792/zfaqqdokcFAWOOcbg3nt3ERdnRLwux9VbN+CePfLLjlWME1nWa5mwubny6SqPrfU+I+F0wg03hEhIkP53XZ0UiTnnHJO0NIWf/zyEYUiRlZ/8xCILuRh27HDa+w8EFD79VKW5WbB3r0J5OfzrX3F8+GE8Dz6Yy5Il/TFNhWBQITU1wKxZqykpKWHy5ADNzbBwoc7jj8tFqmnw6acBzj5b54IL3NTUwJgxcMMNOs89F7CJr8WZAVBWprJ7t9RosJrLXn89QEWFwt//7uSaa0IoCnZsR9cVHnzQyUknRQc3rGpLvx+2bpWpyXXrVM4+2824cZ4oqy4/X7Gvc+RtcOaZOqWlAS66KJHm5ibWrFnDypUrKSgooLGxEUVRcDqduFwuXC4XTqcTh8NhWxahUAghBKmpqYwYMcKWr9d1nc2bN7NixYpWQ3FitWt/F1OZ3S5NbyEYDGIYBsuWLeOII45ovWEhKCoqorS0lIkTJ+5XS7KoqAghRKcH81qalUlJSUybNrZLcxctOJ2CX/9a5y9/cWIYkJoqqKlRcLmkq5KUJNOHgYBCTU3sbSQny56IL790MGqUHF03e7ZUi/r7350oiqBfv2b27JHBLZdLEAwqUYK2saBp0iSfOFHOyJg3z0DXm6ioqKCsrJLjjz+GTz7Zys9+NowHHwxx5JHhDd1zj8Yf/uAkPl7WZ7SF+Hj5vbVUgx492uSuu4Lk56vcdJOLp54KcNFFbm64Qefee9vyXMPuSST69zfJyRGsWuWw+yfa+vzKlQFGj259QQKBAJWVlVRWVtLc3ExKSgoZGRmkpaVFLWqLIEzTjAoyqqq6b1qXGjUUp66ujvj4eOLj42lubmbs2LH2Z2677TZOO+00TjrppLYOuD20uhCKovwdOA0IAjuBS4QQtV3ZeFfRo+QghOCrr75i9uzZUX+zGqeEEIwZM6ZDkWPLzGtr0nYsNDc3s27dOgYNGkRych+ystz7HZnXEh4PtmKyhdGjTbslWFXlewxD/n/AAMGLLwaYMUNOt54zR2fVKke7iy4yhed0yinfHk94EU6cqFNTI3siIgujWiI3V3DqqQZXXRWi5XCwlBQv991XyrZtQTZs8PDXv5awceMAnn46lc8/d3Qo9qJp4anaXm9rIpEzRq1GLOnGeDyC116LTRAW8bndrZW+24OVdRk50uQf/wjxgx+0Hag2TZPa2loqKyuprq7G7XaTkZFBRkZGVC+ERRAWWYAkQsslUVUVIQRNTU0UFRXZ20pPT8fhcPCPf/yDyy67rNW93kHEIoeTgI+FELqiKH/ddzy/6srGu4oeDUjGQiAQYO3atWRnZzNw4MAO5547G3Ooqalh8+bNjB07luTkZAzD4JFH/Cxc2DmVKL9fVgVWVkoLIRiELVtUsrPDk6icTjn/YswYwZw5BtOne8jIMCkrU/nsM41f/SrE9dfr/OQnbn70Ix2/H+6+22kH5WQloIHDoTBsGNTVRY+iX7dOs5u72sPu3QoPP6zx8MPya42Pl3GVuXNlh+TOnZmMH2/w73+7mTUru8MirA6HlN8vLVUYMsQkL08lEFBIT5eL2++XBCqzPOFjfPfd9kk/GFT2zSEVdjynI7D2MXOmzqhR7bOaqqqkpaXZgcjm5mYqKyvZsmULwWCQtLQ0MjIy7PSm9aCKtCoig5txcXFkZGTgdrsZMGAA1dXVPPTQQ7z33ntUVlZy4YUX8uMf//iARu0BCCHej/j1G+DsA9pgF9BjlkMoFMI0zSjLoa6ujo0bNzJq1Ch7kEhHUVFRQU1NDSNGjNjve/fs2UNRURGTJk3C6XRimiaKItOORx7pjuos7Cg0Dd56K8C558ruysjSXYdDWg+nnCI7KiP7EUxTqki9916AujqFc85xMWGCoK5OuhMvvOCgudmkuVnOkWxsVOzsiqrCD35g8NFH8oa1LIzzzguxaJGT7GzZEj1smMmnnzpazayIBYuLI9+jKJCeruPzmTQ1RccFXC5ZQ/HEExqTJkmV6N27FRYvdpCUBH/6U5AnntDYtEltk2y8XtHGENwwEhIETqdMme4Pzz8fYNYsk+zs/b61XRiGQXV1NZWVldTW1hIfH29bFa6I4g+LIKyf0tJSdF23H26qqnL++edz2WWXsXbtWm666abOZi7aPWlFUd4CXhJC/KdrZ9o1HDRpeksdavLkyZ0mBuiY5SD2idmWl5czderUKGJQFIX4+EbuuedrTj+9icjYUaTx0pbMpa7Dqae6GT9eViBGwjBkA9WiRZIYLrpIZ906P8OGydbuigqF447zkJcn52SOH28yaZLJoEE6Ho+fE05oYuZMg8JClaoqWSg1b57BT39qMGOGSVycjPwLAYMGmTz2mCx4uuSSEHv3yirGM84w+O1vQ3ZBU58+ZkyJvMi4hVW7MWqUSXW11ooYVFVw660FTJhQQ309TJpksGiRRkKCbNo6/niD666TKdObbgrSt69odT3dbuzAbXsIBJSo0X4ej2DMmOjrPHKk/P6POurAiQHkPZWZmcno0aOZNWsWgwcPJhAIsH79epYvX87OnTupq6tDURQ0TcPlctHU1ERZWRn9+vWz3ZBQKER5eTlHHHEEf/jDHzpMDCeccALjxo2LpSE5z3qPoii3Azrw3wM/487hoFgOqamp+P1+xo8f32qsWEexv6nd1gyBxMREhg4dihAiihiqqqrYvn0748aNIyEhASHg3/9WufXWcHeO2y2FXP/zn9YM0fYTORxYGz3a5J13AvaN6/PBZZe5eP11h71gfvQjg3XrVKZODTFmzE4WLx7Czp0uGhoUe9qWNaMSwDDkWDw5oBY2bPCTkyMYPdrDiScaHHuswUUXuZk0SepZPvSQxqpVYVZQVVl52BVIbQh5jqYJcXEGo0aFyMvzUl8vFaRzc2XthmnCEUcYFBWpVFQodgwhN9ekqKjzwisOh3TVrLmd//xniMsv11m3TmHixJ7vmwiFQlRVVVFZWUlDQwNJSUl4vV7KysqYPHmy7TaYpsm7777LLbfcwsqVK7v04KMNy0FRlIuAXwDHCyG61odwAOgxctB1HZ/PxxdffMGAAQMYPnz4AdW2NzY2kp+fHzXy3ILP52Pt2rUMHDiQvn37YhjGPkEWSQxFRUXs3buXiRMnRpmLAI88ovLAAy5271Y62KEZO8reEpGFQC0vcWKiSVKSn4svDnHnnckIAccea/Dyy0H+/W8Hf/mLK2akfs4cg5NPNqmtVXjySbkghwyR/RrWmIRBg2Qr8+bN0WZDnz6CU0/VeeYZp23+ezxhZe1IeDzyHCNHA7rdkihmz67no4+SW52TFVS0huzIoCX88Y9B7rrLadcx7A+aJq/daafV8MorqfZra9b4GTLk4DZTWRBCUFJSwo4dO3C73WiaRkZGBg0NDZSWlnLnnXeyePFiMjIyurqLWAHJk4F7gTlCiIoDOf6uosfIoaamhrVr16IoShTTdhXNzc1s3bqVyZMnt9pPy8CjRQxCCLZt24au64wePXq/WZGtWxXuvVfjP//pinWjY8V3rUlRnUFiomyFVpS2R/K5XHLhjR1rUlIihWRkhkTKsDU3y1oBTQsrO/fvb/LNNwF27lQ46SQPo0aZJCbKVGFblcNer9Rb8HikeGx5uWI3loEku/vv93H77S4aG2Nf00higfAxOZ202WoN8POfh3jsMSdOp2HL8A0ZItiwoXtnkXQGdXV1bNmyhYkTJ+L1evH7/ZSUlHD55ZezefNmzjzzTC6++GKOOeaYru4iFjnsANyAVdj+jRDiF13dQVfQY9mKuro6JkyYwM6dO7tFDSpWzKGkpITCwkKmTJmCy+VC1/Wo/PSGDRtITk5m5MiRHbJaRo4UPPJIqE1yOO00nU8+0WhqiuVihD8TDBr7xFFM6urCr7vdYt9sztbH0hH9xGBQPlVXrw4Tj8OBPTrPWnSKIi2F8nIFVVX44x81Hn/cyZAhgocfDnLEEbGbp0aMEEydajBihCzwGjBA/tx7r8Zjj4XP49JLdS67DH7wgxAzZ8YmGeur6tdPMH26wc6dKhs3ylkV7ZHDI49Il84ihpkzdWIYiwcN9fX1UcQA4PF4KCkpwe/3s27dOnbs2EFlZWW37lcIMaxbN9gF9Bg59O/f3y4z7Q41qMjtWAIwTU1NTJs2zW7KstwIn8/H+vXrGTRoENmdjFy114fz1luaLZbSEpGTojVNY+bMECtXyst7yimlfPRRln3Dt4SmSd2I+nqFpCQYMsRg7drY71VVqRkRFwd5ebIa0qoVcDrlsX38sZ85czwce6zB11+rPPqoXHA7dyoxicHjEUyZInj88SADB7Y2Fq2qYMtV+sc/Qnz6qcpPf+qO6ZaAbBE3DIWyMli/3tgXKFXbfH9biItTOeGE7pEa7CwaGhrYvHkzEyZMiKqJWLZsGb/61a9466236N+/PwMHDjwkx9fT6NEp29A9alAQ7srUdZ21a9cCMHHixFbEUFtby9q1axk1alSniQFg+3al3SG7LQt/FCXcmWj9XlurkJSkEgqpuFyCJUv6EAzKSz1pkuwsTE4O70PXrQG5gsZG2iQGp1M+kXfuVNm1S6pHJSUJkpKkRWIJyx5zjAfThI8/duDzSQ2G/v3NmEHBAQNk5L9PH8HMmR7uvVeLEXuRHzRNGDhQcN99GvPmuamubq0rCeybvqUiVagVysqcbN0aaUF1rLv2zjv9bNmicMwxPSMS2x4aGxvZuHEj48ePjyqLXrVqFddffz2vv/56u+X+3wX0eCqzuywHq7dixYoVZGVlMXz4cDvvbBFDaWkp27ZtY/LkySQnJ3dpP5oGDzwQIjU1PNuxPVgxgnAxlHx9yRJLFNXENBUmT5YLYu3aNG6/vYpFi9bs01wMIxRqPyhqDdAFSVJ+vySV+nrFXqTWsUSeT0ODYg+oicTYsSbnnGNSWio/P2mSwdtvO5g82cMjj2g0Nlr7Cn+moEDhjjucUZWm6ekm8fGSPFJSwsfodFpBz+jbLBDY/23ncgmuvVawbZufiM79g4LGxkY2bNjAhAkTojQa1q1bx9VXX82iRYu+s9ZCJHosIGkYBrqus2vXLjweD3379u3qpgCora1l+fLlTJ8+nZSUlKjAI8DOnTtpbGxk3LhxXU6XRiIYlB2E7fnHFiLDGQ5H9Ji3uDgTv19l1y4fAwd6URRoaPCh63DrrRoPPyxNfpdLjxK2zc012b27Zdt662BlSorBuecKHnss/MSPlXaN/mw44+JwYBdPOZ3hc7FUp2VVaGxXCiT5XHSRTr9+gmXLVD76yEFOjkDTBPn5apS7FXm92rrtFEXu66OPfMyaFfs9PYmmpiZ7GnxkvcKmTZtYuHAhL7/8MiNHjuzu3facRNUBoMfIwTRNQqEQu3fvRlEUBgwY0NVN2YFHwzCYPXu2bYlY1sSmTZvwer0HPJOzJR580MHNN3dAJmkfPB648cYQP/xhA5dfrrJ1a7K9qBISTBobVdxuOPpog88+swbitL09q/egu+H1sq9isfXXa7lIXdHViY8XZGUJiotVuy7DUgns39+Mmr7dEomJwg7KxseH+OyzDTGbpXoSVi9OS2LIy8vj4osv5oUXXohqtupGfD/JYc+ePYRCIQYNGtTpbQgh2LFjBw0NDYwfP55ly5Yxbdo0NE1DURQCgQDr1q0jJyeHnJycrh5qu3j/fZUzzmhbxtjiIo9H5vnnzm1m+PAC1qwZyvLlrpgNV6pq+eVdEWVtC3JoTGwPzrIUpEKT0wnTpgmKi2Hr1oNWJGsjOVnYE7ZiYcOGJlJSws1SHo+HjIwMMjMzcfeQpHRzczPr169n7NixUboM27dv56c//SnPPfccEydO7JF9830lh7KyMhobGxk6dGinPm+lIuPi4hg+fDhCCAoLCyktLcXj8ZCUlMTevXsZNWqU3VTTUxg40GMPce0OJCTA7beH+OMfnQgh8Ptbb1vqRigHRB5Ww1gspKdLhevaWqVDHZHHHWcwYYLJW29p1Ne3rwgtEdsyafPd+1yNPn1Mdu6MPqCmpia7BdswDNLT08nMzCQxMbFbLEWfz8e6desYM2ZMlDRhQUEB559/Pk899RRTpkw54P20g+8XOQghCAaDVFZWUlVV1Sk/ze/3s3btWgYMGEC/fv1aBR53797Nrl27cLvdOJ1OMjMzycrKOuBCq7awZYvC//2fnJy9cuWBz2CMFTuIhcgKxpZ+eiy/veVriYk6DoegttYqBw/HGqxipNGjTfbsUenXzyAvz8HYsQabNoXN+Esv1XnxRc22kM4/P0R9vcIrr2gdOoeOwuGACRMM3n03SHuCSlZZc0VFBY2NjSQnJ5OZmdll98MihtGjR0cFsYuKijj33HN59NFHmTFjRldOqTP4fpJDTU0NpaWljBkzpkOfq62tZdOmTYwZMyZm4LGwsJCqqiomTJiA0+nE7/dTXl5ORUUFhmHYRNFTSsC6DpmZ3lbzJjuLsWMNdB22bt3fDS32kUnn7x+nU87GsOByyQCiFQeQ8z7bj3scDFhB2s4aAaZpUldXR0VFha2vkJmZSUZGRoceFNZDqCUxlJSUMH/+fP71r39x1FFHdfZ0uoLvJzk0NDSwa9eumD0RLVFaWkpBQYFdjWbVR1i1DFu2bEFRFEaNGhVTZ9KyVMrLy/H7/aSnp5OVlUVSUlK3BiqffNLBtde6uhS0i4TLJdu5NQ17oG97iBX5B6lINXq0lMOXaN3/ccMNIcaPF9x6q7NVWrOjlkxsWNvan66CtPxcLoVTT9WZM8dk8GBBv36ClBRBnz5d3X8YnXE/AoEAa9asYdSoUaSkpNiv7927l7PPPpt7772XY4899sAPqmP4fpEDyC+grZ6IqJ3sCzzW19czYcKEVoVNwWCQDRs2kJmZyYABAzq00A3DoLKykoqKChoaGkhNTSUrK6tD6sL7gxAwc6aL0lJ93/DYcONRfLxUcNqf62G5AFYqUQhITjapq+uZAOGrr25k0qRkTjophx07wvvo7CCZziArS2AYEAgYjBhhMnKkypVX6kyZcvC6KmO5H7qus2bNGkaOHElqaqr9mYqKCs4880zuvvtuTjzxxB4/xgh8P8khGAyyfv16pk2bFvM9liS9x+NhxIgRrVqtm5qa2LBhA0OHDu3QAN1YME2TmpoaysvLqa2tJTExkaysLFviq7OwIttpaSMYPjwNw4AHHnDw29/KtGespqOsLNnrEFkD0ZEndlvWQleQlRVAUXTKyuLteoK20BZpdESRqiUKCvaQmdmzQeP2EOl+VFVV4ff76devHwMHDrTdj6qqKs466yz+8Ic/cOqpp3b7MRQVFbFgwQL27t2LqqpcfvnlXHvttdafv3/kEAwG0XWdFStWMCtGRYvl8/Xv35+cnJxWgUdLg6FleulAIISgvr6e8vJyqqqq8Hq9ZGVlkZGRgbMtpZcI1NXV2V2gSS1K9378Yycff9x6FkY0CXTMDO8skpP91NV5DqhOoSNoTVbtZyXi4gQVFYeuozISwWCQNWvW0L9/f3Rdp7Kykvz8fJYuXcqqVav4/e9/z7x58/a/oS6gtLSU0tJSpkyZQkNDA1OnTuX111+3YnGHJTn0uIZkW5OqLMm40aNHk5qa2kqDobi4mNLSUiZPntytuW1FUUhOTiY5OZlhw4bR1NREeXk5a9asQdM0O6AZa58VFRXk5+czadKkqEYcCwkJCieeaPD++9IamTbNoKJCpbFRuhyy5uHASKGtJ3pDg3wCdjR2kJAgSE2VwcnIoT+ZmUGE0KisVGPuL/qrFIwfLxWsGhpk+7iiwMaN1ezZ0zoDcCgRCoVYu3Ytw4YNswVZBg4cSGZmJk899RQJCQn89re/xe/3c+6553b7/vv27WtXCScmJjJ69Gj27NnT4UD9oUCPWw6xFKj37t0btcgiA4+WBkMwGOywMnV3wefzUVFRQUVFBaZpkpmZSWZmJvHx8RQVFVFWVsbEiRP3a2FkZXloagovOKdTdkwGg9FuharK1uiKCqWVxqJs6BLoevh1qf4sCIW6/qDxeGRdhaZJIm6ZqbDIQFUFubl+Sks9UaKx4WMR3HGHzuDBgkGDTAYNEiQnY7uBLWsGDiVCoRBr1qxh8ODBUa5pY2MjZ599NldccQXnn38+uq7T1NTU44RWUFDAMcccw8aNG61r9P2zHCzBFQtCCFuXb8aMGSiKYmswWP+3NBhGjBjRrRmGjsDr9ZKbm0tubi7BYNAe6FtfX4/T6WTMmDEd6tsoL5dmdGEhLF7sYMkSB2vXqrQcOG6aCrt3xz5HIYgiBrB6NmK/f9Agk4ICNaZlYSllA3bBVcttR+7XOraCgtbWEcBRRxksWdI6l2s1LLUsPz6UsCyGlsTQ1NTEeeedx2WXXcb5558PyA7iniaGxsZGzjrrLO67777DhjzbQo9aDpE6kjNnzrRnYY4cObJV4NHSYBg4cCB9uiOv1Q0wTZNNmzbhdDpJSUmxI99paWlkZmaSmpraYQITQo6F+/prlQ8/dLB4sUpDQ8+XLlvdkqoqoqyZrkBVBfHxId55Z7ltVVnuVUNDAxs3bmzVyXgoYWUlBg4cSFZWlv26z+fjvPPO49xzz+Wyyy47aMcTCoWYO3cuP/zhD7nhhhsi/3RYWg4HhRyWLl2Kpmnk5OTQv3//VoHH2tpatmzZwpgxYw4rH3X9+vVkZmZGTdkyTZPq6mrKy8upq6sjKSmJrKysLlXoCSErIOfPd1FVBRs3qu2KwcbFQSh0YG5FV5CdLWXa4uKk2+H3+233KxQKkZCQQG1tLZMmTTqsiMGqso3U9QgEAlxwwQWcdtppXHHFFQfNOhVCcNFFF5GWlsZ9993X8s/fP3KwRoktW7aMiRMnkpmZ2SrwWFpaSlFREePHj48Z5DsUsOS/Bg8eHPXEaQkhBHV1dXbmIz4+3q7Q60jmo/X2wo1cfj+cfLKLFSu6J+bidEq3JPLrPussnZISha+/bnsft9wS4ve/b1usp6qqis2bN5OYmIjP5yMlJcWuJzjQepKuwjAM1q5dS05OTpQVGgwGWbBgAccddxzXXnvtQXVbly5dytFHH8348ePt63LnnXdaadPvHzkUFxezfft2NE1jwoQJ9pPVCjzm5+fT0NDQbRoM3QHLPB49enRU5dz+IISgsbHRJgpN08jKyuqWTkLDMLnxxiqeeaa/rSgVC9ddp7NihcI33zhaDdYZNkzws5/pDB5sEgrBvHnhCeObNiksXOhk40YHqiql8CdMMHjmmSDtTR+srq5m+/bt9qxTa/RceXk5NTU1B0yWXYFFDP369YvSEAmFQlx66aXMnDmTm2+++aDHs/aDw+pgLPQoOVRUVOD1etm4cSM5OTmkpaVhjULftGkTHo/ngCXruxNWXcX48eMP2Dz2+Xx2z4cQwk6RdnYSs1UklpKSYre9f/KJwi9+4aKsTCE5WU7Pvu02PUq5StelavTmzTB8uKAjwkWBgKz07AgqKyvZuXMnkyZNikl+FllWVFRQWVlpD5CJjFN0NwzDYN26dfTp04d+/frZr+u6zs9+9jPGjx/P7bffftjcbxE47A4IDoJbEQwGqaqqYvfu3QSDQVJTU6muriYnJ+eABGC6GyUlJezZsyfmbIsDRTAYtIkiGAySkZFBVlYWCQkJ7d6ooVCIdevW0bdv3x7Tq+gKysvLKSgoYNKkSR2+Vi3jFJY+Q3e1XZumybp168jKyoq6VoZhcOWVVzJo0CD++Mc/Ho7EAN9HcvjHP/7BgAEDOP744/F6vZSWlrJ9+3a8Xi+GYdiLpLtukK5ACMGuXbuor69n/PjxPV5XYVXmlZeX09TURFpamt3zEXkNLCGbgQMHdkkot6dQVlbG7t277TmkXYF1DazsT0pKCllZWaSmpnYpTmERQ2ZmZpToq2maXHvttWRkZHDXXXcdshhIB/D9I4cvv/ySl156iU8++YS+fftSUlLCO++8YwcmKysrKSsro6mpifT0dLKzs7u9g7I9mKZJXl4eiqIwcuTIg37zmKZpNwfV1dWRnJxMVlYWXq+XDRs2MGLEiB4XsukMSktL2bNnD5MmTeq2GNGBxilM02T9+vWkp6dHWaKmaXLTTTfh8Xi49957D2digO8jOVj45z//yQsvvMCsWbP49NNPGT58OKeffjo//OEPSUhIwDAMqqqqKC8vp6Ghoc2naXfCKriyfPlDbW4KIaitrWXPnj2UlZWRkpJCTk4OGRkZh0Wwds+ePezdu5dJkyb1mHXV2TiFaZps2LCB1NTUVunm2267DV3X+fe//324EwN8n8nhww8/ZM6cOfbU6zVr1rBo0SLee+89BgwYwLx58zj11FNJTk5uVUdwoCZnLFgm+4ABAw5YFbs7UVtbS15eHuPGjUMIQXl5OZWVlbhcLjvz0d3xkI6gqKiIysrKqIzTwUB7cQohhF1+HKlPapomd9xxBzU1NTz66KPfBmKA7zM5tLnxfV/wyy+/zDvvvENWVhbz5s1j7ty5pKWl2SZnWVkZtbW1JCUlkZ2dfUA5dKv2/3Az2SsrK9mxYweTJk1qpWLU3NxsBzQVRbEzHwejLqSwsJCamhpbZ+NQoWWcwjRNUlJSGD16tH1cQgjuvPNOioqKeOqpp3qEyC699FLefvttsrKy2LhxY3dttpcc2t2REOTl5bFo0SLefvttkpOT+fGPf8zcuXPtmnjLN62uru6SJkNNTQ15eXmHVe0/yEa0oqKiDmVKAoEAFRUVlJeXo+u6HdSNj4/vdtcoPz/fngVyuDyBrQeKoihomkZNTQ0ul4vVq1dTVlbGrl27eO6553rMFfv8889JSEhgwYIFveRwsA4kaqf7GrQWLVrEm2++idvt5rTTTmPevHl2xZulyVBZWUl8fDzZ2dmkp6e3eVOUlZVRWFjIhAkTekyItisoKiqioqKCCRMmdPqGDoVCdubD5/PZsZrk5OQDIgrr+vv9fsaOHXvI4zEWhBBs3rwZj8djq5kLISgtLeXGG2/km2++Yfz48SxcuNBupuoJFBQUMHfu3F5yOFgH0uYB7JOkf+WVV3j99dcBmDt3LqeffrqdtmpsbKSsrIzKyko8Hg/Z2dlR0e5IUdrDIbgH4RSqNZPjQJ/MhmHYsZr6+voux2qsIcW6rjN69OjDihi2bNmCy+Vi6NCh9nEJIXj44Yf5/PPPefnllykvL6eoqIgjjjiix46llxwkDjk5REIIQUlJCa+88gqvvfYafr+fuXPnMm/ePAYPHoyiKHYJc0VFBU6nnAvhdDoPO9N469atmKbZIwuwZXowISHBVrtqzwWzjgtg5MiRhxUx5OXloWla1FQzIQRPPPEE7733Hq+99lqPDbxpiV5ykDisyCESVjT/tdde49VXX6W2tpZTTz2VefPmMWLECJqbm9m0aZOtROVwOMjOzu7RqUkdgdUG7vV6o56APQUhBA0NDbYL5vF4bKKIjG9YT2an09ntYwUPBBZhKYrSSuPj2Wef5dVXX+WNN944qE17veQgcdiSQ0tUVVXx+uuv88orr1BSUoLP5+OKK67gZz/7ma0XUV5eTnl5OYqikJWV1aODcGLBMIx9wrRph2xKsyWLV1lZiaqqdsFRfn4+Xq+XIUOGHFbEsG3bNoQQrSyZF154gf/+97+8/fbbne5XOVD0koPEt4YcLBQUFHDGGWdw3HHHsXPnTgoLCznxxBM5/fTT7XSclT8vLy+35eCys7N79Olj9Un069cvqinoUMIaCLRr1y5UVaV///5kZmYeFpkca1yBruuMGjUqihgWLVrEE088wTvvvHPQj/X888/n008/pbKykuzsbO644w4WLlx4oJvtJYeDgfLycoqLi+3ZhvX19bzzzju8+uqrbNu2jeOOO47TTz+dqVOnoqqq3RRlpQZ7YmKWVXQ1aNCgdvUhDjas0uPU1FT69etnFxz5fL4eGwjUEVjZkmAw2Com8+abb/Lvf/+bd95557ARBuoG9JLDoUZzczPvvvsur7zyChs2bGDOnDmcfvrpzJw5E4fDQSgUoqKigrKyMrt7Mjs7+4BqCKwZF4db0ZXl4mRkZLTqjm1Zzp6ammrL4h2MoK6VRh0zZkzUdX/33Xe55557eOeddw6ra9kN6CWHwwl+v58PPviAl19+mdWrV3PkkUdyxhlnMHv2bDRNQ9d12/Xw+Xxd6iC1hGNizbg4lLAEUfr06bPfVnBrIFBFRQU1NTUHPBBof8jPz6e5ublVfcUHH3zAX/7yFxYvXkxGRka37/cQo5ccDlcEg0E+/vhjFi1axDfffMPMmTM5/fTTOfroo3G5XHYHaXl5OY2NjbbJ3V6xUU1NDVu3bu0W4ZjuhKWtmJOT0+m+klgDgazGqO5Qetq1a5ddkRl5XT/99FN+97vfsXjx4sPKLetG9JLDtwG6rvPZZ5/x8ssvs3TpUqZMmcK8efM47rjjcLvddrFRWVmZbXJnZ2dHdZBaw28s+bTDBZZMe25ubrdoRFgdlBUVFTgcDrs5rCvnXFBQQH19fat6lKVLl3LrrbfyzjvvHFZNct2MXnL4tsEwDJYuXcorr7zCJ598wrhx45g3bx4nnHACcXFxMTtIrXr/yZMnHzTdxI4gGAzGnN/QXbAyH9ZAoMiej/1h9+7d1NTUtKoUXbZsGTfccANvvfVWlIjLdxDfD3K4+eabeeutt+wy16eeeqpTQq2HK0zTZNmyZSxatIgPPviA4cOHc8YZZ3DSSSeRkJCAaZps3bqViooKeziK5Zsf6srMQCDQahRcTyIYDNpumN/vbzdeU1RUZJe2R16nVatW8ctf/pI33njjkNWEHER8P8jh/fff57jjjkPTNH71q18B8Ne//rWLh3d4wtKkePnll3nvvffIzc1F0zSGDx/Ob3/7WxRFoa6ujrKyMqqrq0lISLAbww6mHgKEhxUfqmyJrut25qOxsZHU1FRbyKekpISKigomTpwYRQzr1q3jF7/4Ba+++qrdYNXdeO+997j22msxDIPLLruMW2+9tUf200F8P8ghEq+99hqLFi3iv//974Fs5rCGrutceOGF5OfnYxgG2dnZzJs3jx/96EekpaW1CuLFxcXZ5cs93QTm8/lYt24do0aNOiysNyvzYbkfACNGjCAzM9MmzU2bNrFw4UJefvllRo4c2SPHYRgGI0aM4IMPPqB///5Mnz6dF1544VAOtT0syaFH784nn3yyRyYWH06ora1lxowZvPDCCwBs2bKFRYsWcdZZZ5GcnGyL1wwbNoxhw4bZHaQFBQUxO0i7C1Z9xeE06VpVVdLT0wkEAjQ3NzN48GAqKyspKChg+fLlNDc388or/9/e/cdUXe9xHH9+ThIWQvGPlBwX2BExxNS0kZlXB8plLA9OgeAurqOZ4YY/MpM8abpqxdaaa9Tc+uFYszXgYD+cwoLddXWGjguNi545+RECKiAQGCaIfO4feL6BnBsm5/D9wvk8Njc8uvN5H3+8+Hy/38/n/bGTl5fnsWAAOHPmDBaLhVmzZgHwwgsv8O233xr6xGs93NPMISYmhitXrox4/d1338VqtWpfl5eXU1hYaJi1+uPJufzXbrfz3XffMXXqVK0nRVBQkMsdpM6NYWNtBdfT00NVVRXz5s3D39/fTZ/IPS5fvsylS5eG9aKUUnL8+HHeeecdBgYGmDFjBgcOHCA8PNwjNThbFH722WcAfPnll5w+fZqcnByPjHcXDPkf5J5mDiUlJX/667m5uRw9epTS0lKvDAYYPGF89uzZZGVlsWvXLq0nRVpaGiaTSetJERoayqxZs7RWcD///LP2WHD69Ol/eQepc+GV0bpdwWDHqzuDAQb7bbz99tscOnSIRYsW8csvvxAYGOixOlx9Q/TWf6d/xu2XFUVFRWRnZ/Pjjz+O+245oxJCEBISwo4dO3j11Ve1nhSbNm2it7dX60kREhJCSEiItoO0qqrqL+0g7e7u5uzZs4Y66dqppaWFpqamEcHQ2NhIamoqn376qbYfZmjDWE8wm800NjZqP29qajLMZjgjcfsNSYvFQm9vr/bILCoqioMHD95jeZObsydFYWEhhYWFdHV1ER8fj9Vq1Y4J7O3t1TaG/dkOUmfn6ieffNIwBxI7tba20tDQwMKFC4fdhL106RKJiYnk5OTw7LPPjls9/f39hIWFUVpaSnBwMEuWLOGrr74iIiJi3Gq4gyGnLWoRlIFcvXqVb775hsLCQlpbW4mLi8NqtWo7E//fDtK+vj7Onz/vsnO13tra2rSj84bedL1y5Qrr16/nww8/ZMWKFeNe17Fjx9i2bRu3bt0iPT0dm8027jUMocLBE/Lz89m3bx8Oh4MzZ86wePFivUtyi87OTr7//nvsdjsXL15k9erVJCQkaKsInTtIm5qauHbtGmazmRkzZox6/uZ4unr1KnV1dSNWi7a2trJu3Tqys7OJiYnRsULDMMZf2B0mfDg4HA5MJhObNm3igw8+mDThMJSzJ4XdbufChQtER0eTkJBAfX09U6ZMITY2lu7ublpaWrReDEFBQbqeQdre3k5tbe2IYGhvb2fdunXs37+fuLg4XWozIEOGgzFaMY/B3Llz9S7B4wICAkhJSSElJYXr169z7Ngxdu/eTV1dndau/+mnn+aRRx7RdpA2NDTc9Q5Sd2tvb6empmZEMHR2dpKYmMibb745YYNBSslzzz2HzWbTPkNeXh5ffPEFRUVFOlfnXhM+HLzNgw8+iMVi4b777qOyspLTp0+Tm5vL1q1bWbZsGQkJCSxdupSgoCDtoN7m5mYcDoe2dDkwMNBjQdHR0aEFw9D1Gt3d3SQlJbFz507WrFnjkbHHgxCCgwcPkpiYyMqVK7l16xY2m23SBQNMkMuKu1l0tWLFikl7WXEnKSU3btwY9lSir6+P0tJS7HY7ZWVlREVFaT0pnGeUdnZ20tLSop3oHRQU5NbuTs4eFgsXLhy2PuO3335j/fr1ZGRkePSwmfH0+uuv4+fnR09PD/7+/uzZs2csb2fIy4oJEQ53w5vCYTQ3b97UDnk5efIkTz31FFarlZUrV+Lr64uUUtvj0NnZSUBAwJh3kDofpd75xKSnp4fk5GQ2bNhAWlqauz6i7np6eli0aBH3338/5eXlYz3uwJDhoC4rJiEfHx+io6OJjo7WelIUFBTw1ltvERkZqfWkCA8PR0qp7SCtqam5px2kXV1dLoPh999/JzU1ldTU1EkVDAB+fn4kJyczbdo0Xc9B8aQJP3M4cuQImZmZtLW18fDDD7NgwQKKi4v1LsuQBgYGKCsro6CggJKSEsLCwrSeFH5+fve0g7SrqwuHwzFi8VVvby+pqak8//zzZGRkGObxqjvt27ePadOm8dprr431rQz5hzPhw0G5NwMDA1RUVJCfn09xcTEhISFYrVbi4uIICAhASjlsY5jzpKyh/SK7u7s5d+7ciGDo6+vjxRdfJCYmhi1btkzKYIDJHw7GODzS4IqKipgzZw4Wi4X3339f73LcwmQysXjxYrKzs6moqGD//v3U1dURHx9PYmIihw8fpr+/n8cff5yoqChmz57NjRs3qKyspKKigtraWqqrq5k/f/6wYLh58ybp6eksX7583IIhPz+fiIgITCYT5eXlHh/PW6iZwygM2BjEo5xnZhYUFHD06FECAwO1nhTOlvBtbW2cO3cOX19ffHx8tMejU6dOZePGjURGRmKz2cZtxjAJFsIZcuagbkiOwtsagwgheOKJJ9i7dy979uyhpqaGgoICkpOTeeCBB1i6dCknTpwgLy8Pf39/rbHs5s2bqaysxGKxkJaWNq6XEt6wEE4P6rJiFM3NzcNOhDKbzTQ3N+tY0fhx9qR44403OHXqFDabjUOHDgGQlJTExx9/THt7O2azmYceekjbKPbSSy9RX1+vc/XKWKmZwyhUY5BBQghOnTpFcXExERERWk+KjRs3UltbS2xsLB999BEmk4nNmze7ffy7WQinuJcKh1GoxiB/GLoKMDg4mC1btpCZmUl1dTVz5szxaAv+0bqPKe6nLitGsWTJEi5cuEB9fT19fX18/fXXE3pvgLsJIYiMjBxz30vFeFQ4jGLKlCnk5OQQGxvL3LlzSUpK0rNjkOLCkSNHMJvN/PTTT8THxxMbG6t3SZOCepSpKPoz5E0sNXNQFMUlFQ4GlZ6ezvTp05k3b57epSheSoWDQW3YsGFSNhBRJg4VDga1fPlyXQ6+VRQnFQ6KorikwkFRFJe8PhwaGxsJDQ2lo6MDGOyDGBoaSkNDg86VKYq+vD4cZs6cSUZGBllZWQBkZWXx8ssv89hjj+lcmffYuXMn4eHhzJ8/n7Vr1/Lrr7/qXZKCCgcAtm/fTllZGQcOHODkyZPs2LFD75JISUnhmWee4fz585jNZj7//HO9S/KYVatWUV1dTVVVFWFhYbz33nt6l6Qw+gpJryGEiAWKgNVSyh/0rsdbCSHWAuullP/QuxZvp2YOf4gDLgNq1ZG+0oHjehehqHAAQAixAFgFRAHbhRCP6luRPoQQM4UQ/xJCOIQQZ4UQW9343iVCiGoXP6xDfo8N6AcOu2tc5d55/WWFGOzccgrYK6X8QQiRCUR547T2dig+KqWsEEL4A/8BEqSU58Zh7H8CrwDRUsrrnh5PGZ2aOcBG4OKQ+wyfAOFCiL/pWJMupJSXpZQVt7++BjiAYE+PK4T4O7ALWKOCwTi8fuaguCaECAH+DcyTUnZ7eKwawBdov/1SmZTyFU+OqYxOtYlTRhBCTAPswDZPBwOAlNLi6TGUv05dVijDCCF8GAyGw1LKQr3rUfSjLisUze2bs7lAh5Rym87lKDpT4aBohBDLgBPAf4GB2y/vllIe068qRS8qHBRFcUndc1AUxSUVDoqiuKTCQVEUl1Q4KIrikgoHRVFcUuGgKIpLKhwURXFJhYOiKC79D2mYFGAaiiydAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "This results in the following network with is squished in the x-direction.  Note that this can also be accomplished after the fact by simple scaling the coords (e.g. ``pn['pore.coords'] =* [0.001, 0.03, 0.02]``)."
+    "# NBVAL_IGNORE_OUTPUT\n",
+    "sph = op.network.DelaunayVoronoiDual(num_points=500, shape=[2])\n",
+    "fig = op.topotools.plot_connections(network = sph,\n",
+    "                                    throats=sph.throats('surface'))"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://i.imgur.com/ICEAO7p.png\" style=\"width: 70%\" align=\"left\"/>"
+    "Note that the cylindrical and spherical networks don't look very nice when too few points are used, so at least about 200 is recommended.  "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Spherical and Other Arbitrary Domains\n",
+    "## Assign Pore Sizes to the Random Network\n",
     "\n",
-    "It's also possible to obtain cubic networks of arbitrary shapes (i.e. spheres), but still with *cubic* connectivity.  This is accomplished using the ``CubicTemplate`` class, which accepts a binary image of 1's and 0's.  The network will have pores where the 1's are and 0's elsewhere.  For instance, to make a spherical domain  for a catalyst pellet, generate an image of a sphere using Scipy's NDimage module, the pass this image to **Cubic** as follows:"
+    "With pore centers randomly distributed in space it becomes challenging to know what pore size to assign to each location.  Assigning pores that are too large results in overlaps, which makes it impossible to properly account for porosity and transport lengths.  OpenPNM includes a Geometry model called ```largest_sphere``` that solves this problem.  Let's assign the largest possible pore size to each Voronoi node in the ```sph``` network just created:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import scipy.ndimage as spim\n",
-    "im = np.ones([21, 21, 21])\n",
-    "im[10, 10, 10] = 0\n",
-    "dt = spim.distance_transform_bf(input=im)\n",
-    "sphere = dt < 10\n",
-    "pn = op.network.CubicTemplate(template=sphere, spacing=0.1)"
+    "Ps = sph.pores('voronoi')\n",
+    "Ts = sph.throats('voronoi')\n",
+    "geom = op.geometry.GenericGeometry(network=sph, pores=Ps, throats=Ts)"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 10,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 648x216 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "This results in the following:\n",
-    "\n",
-    "<img src=\"http://i.imgur.com/eyFHqNx.png\" style=\"width: 60%\" align=\"left\"/>"
+    "# NBVAL_IGNORE_OUTPUT\n",
+    "mod = op.models.geometry.pore_size.largest_sphere\n",
+    "geom.add_model(propname='pore.diameter', model=mod)\n",
+    "mod = op.models.geometry.throat_length.ctc\n",
+    "geom.add_model(propname='throat.length', model=mod)\n",
+    "mod = op.models.geometry.throat_size.from_neighbor_pores\n",
+    "geom.add_model(propname='throat.diameter', model=mod)\n",
+    "geom.show_hist(['pore.diameter', 'throat.length', 'throat.diameter'])"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "All images of networks were made with paraview by exporting a VTK file with the following command:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Does 'network.vtk' exist? True\n"
-     ]
-    }
-   ],
-   "source": [
-    "op.io.VTK.save(network=pn, filename='network')\n",
-    "print(f\"Does 'network.vtk' exist? {os.path.isfile('network.vtp')}\")"
+    "The resulting geometrical properties can be viewed with ```geom.plot_histograms()``` (note that each realization will differ slightly):"
    ]
   }
  ],
  "metadata": {
-  "@webio": {
-   "lastCommId": null,
-   "lastKernelId": null
-  },
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
@@ -333,9 +331,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/examples/tutorials/finding_neighbor_pores_and_throats.ipynb b/examples/tutorials/finding_neighbor_pores_and_throats.ipynb
index 22f04a91d..a7f1f5695 100644
--- a/examples/tutorials/finding_neighbor_pores_and_throats.ipynb
+++ b/examples/tutorials/finding_neighbor_pores_and_throats.ipynb
@@ -60,7 +60,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Start by finding all pores on the 'left' and 'back'"
+    "Start by finding all pores on the 'left' and 'front'"
    ]
   },
   {
@@ -70,7 +70,7 @@
    "outputs": [],
    "source": [
     "P_left = pn.pores('left')\n",
-    "P_bottom = pn.pores('back')"
+    "P_bottom = pn.pores('front')"
    ]
   },
   {
@@ -141,7 +141,7 @@
     }
    ],
    "source": [
-    "Ps = pn.pores(['left', 'back'])\n",
+    "Ps = pn.pores(['left', 'front'])\n",
     "print(Ps)\n",
     "Ps = pn.find_neighbor_pores(pores=Ps, mode='or')\n",
     "print(Ps)"
@@ -202,7 +202,7 @@
     }
    ],
    "source": [
-    "Ps = pn.pores(['left', 'back'])\n",
+    "Ps = pn.pores(['left', 'front'])\n",
     "print(Ps)\n",
     "Ps = pn.find_neighbor_pores (pores=Ps, mode='xor')\n",
     "print(Ps)"
@@ -264,7 +264,7 @@
     }
    ],
    "source": [
-    "Ps = pn.pores(['left', 'back'])\n",
+    "Ps = pn.pores(['left', 'front'])\n",
     "print(Ps)\n",
     "Ps = pn.find_neighbor_pores(pores=Ps, mode='xnor')\n",
     "print(Ps)"
@@ -323,7 +323,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "Ps = pn.pores(['left', 'back'])\n",
+    "Ps = pn.pores(['left', 'front'])\n",
     "Ts = pn.find_neighbor_throats(pores=Ps, mode='or')"
    ]
   },
@@ -383,7 +383,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "Ps = pn.pores(['left', 'back'])\n",
+    "Ps = pn.pores(['left', 'front'])\n",
     "Ts = pn.find_neighbor_throats(pores=Ps, mode='xnor')"
    ]
   },
@@ -443,7 +443,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "Ps = pn.pores(['left', 'back'])\n",
+    "Ps = pn.pores(['left', 'front'])\n",
     "Ts = pn.find_neighbor_throats(pores=Ps, mode='xor')"
    ]
   },
diff --git a/examples/tutorials/intro_to_openpnm_intermediate.ipynb b/examples/tutorials/intro_to_openpnm_intermediate.ipynb
index d378e42bd..a5a02d154 100644
--- a/examples/tutorials/intro_to_openpnm_intermediate.ipynb
+++ b/examples/tutorials/intro_to_openpnm_intermediate.ipynb
@@ -634,8 +634,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "alg.set_value_BC(values=202650, pores=pn.pores('back'))\n",
-    "alg.set_value_BC(values=101325, pores=pn.pores('front'))\n",
+    "alg.set_value_BC(values=202650, pores=pn.pores('front'))\n",
+    "alg.set_value_BC(values=101325, pores=pn.pores('back'))\n",
     "alg.run()"
    ]
   },
@@ -661,7 +661,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "Q = alg.rate(pores=pn.pores('back'))"
+    "Q = alg.rate(pores=pn.pores('front'))"
    ]
   },
   {
diff --git a/examples/tutorials/using_and_creating_labels.ipynb b/examples/tutorials/using_and_creating_labels.ipynb
index f1175902b..3e559a335 100644
--- a/examples/tutorials/using_and_creating_labels.ipynb
+++ b/examples/tutorials/using_and_creating_labels.ipynb
@@ -111,7 +111,7 @@
     {
      "data": {
       "text/plain": [
-       "array([0, 1, 2, 3, 4], dtype=int64)"
+       "array([0, 1, 2, 3, 4])"
       ]
      },
      "execution_count": 4,
@@ -120,7 +120,6 @@
     }
    ],
    "source": [
-    "# NBVAL_IGNORE_OUTPUT\n",
     "np.where(pn['pore.left'])[0]"
    ]
   },
@@ -155,7 +154,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The advantage of the using the OpenPNM method is that you can create more complex queries, such as pores that are 'left' *or* 'back':"
+    "The advantage of the using the OpenPNM method is that you can create more complex queries, such as pores that are 'left' *or* 'front':"
    ]
   },
   {
@@ -175,14 +174,14 @@
     }
    ],
    "source": [
-    "pn.pores(['left', 'back'])"
+    "pn.pores(['left', 'front'])"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Or, pores that are *both* left *and* back:"
+    "Or, pores that are *both* left *and* front:"
    ]
   },
   {
@@ -202,7 +201,7 @@
     }
    ],
    "source": [
-    "pn.pores(['left', 'back'], mode='and')"
+    "pn.pores(['left', 'front'], mode='and')"
    ]
   },
   {
@@ -248,7 +247,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "Ps = pn.pores(['left', 'back'], mode='and')"
+    "Ps = pn.pores(['left', 'front'], mode='and')"
    ]
   },
   {
@@ -325,7 +324,7 @@
     }
    ],
    "source": [
-    "Ps = Ps = pn.pores(['left', 'front'], mode='and')\n",
+    "Ps = Ps = pn.pores(['left', 'back'], mode='and')\n",
     "pn.set_label(label='corner', pores=Ps)\n",
     "print(pn.pores('corner'))"
    ]
@@ -372,7 +371,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.7.9"
   }
  },
  "nbformat": 4,
diff --git a/openpnm/core/Base.py b/openpnm/core/Base.py
index 248843b00..49dcec902 100644
--- a/openpnm/core/Base.py
+++ b/openpnm/core/Base.py
@@ -845,10 +845,10 @@ class Base(dict):
         --------
         >>> import openpnm as op
         >>> pn = op.network.Cubic(shape=[5, 5, 5])
-        >>> Ps = pn.pores(labels=['top', 'back'], mode='union')
+        >>> Ps = pn.pores(labels=['top', 'front'], mode='union')
         >>> Ps[:5]  # Look at first 5 pore indices
         array([ 4,  9, 14, 19, 20])
-        >>> pn.pores(labels=['top', 'back'], mode='xnor')
+        >>> pn.pores(labels=['top', 'front'], mode='xnor')
         array([ 24,  49,  74,  99, 124])
         """
         ind = self._get_indices(element='pore', labels=labels, mode=mode)
@@ -1353,8 +1353,8 @@ class Base(dict):
         >>> pn = op.network.Cubic(shape=[5, 5, 5])
         >>> pn.filter_by_label(pores=[0, 1, 25, 32], labels='left')
         array([0, 1])
-        >>> Ps = pn.pores(['top', 'bottom', 'back'], mode='or')
-        >>> pn.filter_by_label(pores=Ps, labels=['top', 'back'],
+        >>> Ps = pn.pores(['top', 'bottom', 'front'], mode='or')
+        >>> pn.filter_by_label(pores=Ps, labels=['top', 'front'],
         ...                    mode='and')
         array([ 24,  49,  74,  99, 124])
         """
diff --git a/openpnm/network/Cubic.py b/openpnm/network/Cubic.py
index f4349ed6a..41278b9c0 100644
--- a/openpnm/network/Cubic.py
+++ b/openpnm/network/Cubic.py
@@ -207,14 +207,14 @@ class Cubic(GenericNetwork):
 
         offset = {}
         shape = self.settings['shape']
-        offset["front"] = offset["left"] = offset["bottom"] = [0, 0, 0]
+        offset["back"] = offset["left"] = offset["bottom"] = [0, 0, 0]
         offset["right"] = [Lcx * shape[0], 0, 0]
-        offset["back"] = [0, Lcy * shape[1], 0]
+        offset["front"] = [0, Lcy * shape[1], 0]
         offset["top"] = [0, 0, Lcz * shape[2]]
 
         scale = {}
         scale["left"] = scale["right"] = [0, 1, 1]
-        scale["front"] = scale["back"] = [1, 0, 1]
+        scale["back"] = scale["front"] = [1, 0, 1]
         scale["bottom"] = scale["top"] = [1, 1, 0]
 
         for label in labels:
diff --git a/openpnm/topotools/topotools.py b/openpnm/topotools/topotools.py
index 8b58797ef..784b61ff4 100644
--- a/openpnm/topotools/topotools.py
+++ b/openpnm/topotools/topotools.py
@@ -432,8 +432,8 @@ def label_faces(network, tol=0.0, label='surface'):
         network['pore.left'] = (crds[:, 0] <= (xmin + tol*xspan)) * Psurf
         network['pore.right'] = (crds[:, 0] >= (xmax - tol*xspan)) * Psurf
     if dims[1]:
-        network['pore.front'] = (crds[:, 1] <= (ymin + tol*yspan)) * Psurf
-        network['pore.back'] = (crds[:, 1] >= (ymax - tol*yspan)) * Psurf
+        network['pore.back'] = (crds[:, 1] <= (ymin + tol*yspan)) * Psurf
+        network['pore.front'] = (crds[:, 1] >= (ymax - tol*yspan)) * Psurf
     if dims[2]:
         network['pore.top'] = (crds[:, 2] >= (zmax - tol*zspan)) * Psurf
         network['pore.bottom'] = (crds[:, 2] <= (zmin + tol*zspan)) * Psurf
@@ -1616,7 +1616,7 @@ def reflect_base_points(base_pts, domain_size):
         if domain_size[1] != 0:  # If not a disk
             r = np.hstack([r, r, r])
             theta = np.hstack([theta, theta, theta])
-            z = np.hstack([z, -z, 2-z])
+            z = np.hstack([z, -z, 2*domain_size[1]-z])
         base_pts = np.vstack((r, theta, z))
     elif len(domain_size) == 3:
         Nx, Ny, Nz = domain_size
diff --git a/requirements/conda_requirements.txt b/requirements/conda_requirements.txt
index d893fdd5a..b8db3296f 100644
--- a/requirements/conda_requirements.txt
+++ b/requirements/conda_requirements.txt
@@ -9,9 +9,11 @@ h5py
 jsonschema
 json_tricks
 terminaltables
+unyt
 gitpython
 flatdict
 transforms3d
 sympy
 docrep
 pardiso4py
+zarr


Test patch:
diff --git a/tests/unit/algorithms/MixedPercolationTest.py b/tests/unit/algorithms/MixedPercolationTest.py
index b526b0461..e94cedf29 100644
--- a/tests/unit/algorithms/MixedPercolationTest.py
+++ b/tests/unit/algorithms/MixedPercolationTest.py
@@ -332,8 +332,8 @@ class MixedPercolationTest:
         np.random.seed(1)
         phys['throat.entry_pressure']=0.0
         phys['pore.entry_pressure']=np.random.random(net.Np)*net.Np
-        self.inlets = net.pores('front')
-        self.outlets = net.pores('back')
+        self.inlets = net.pores('back')
+        self.outlets = net.pores('front')
         np.random.seed(1)
         self.phase['pore.occupancy'] = False
         self.phase['throat.occupancy'] = False
diff --git a/tests/unit/algorithms/MultiphysicsNernstPlanckSolverTest.py b/tests/unit/algorithms/MultiphysicsNernstPlanckSolverTest.py
index e6b47b75d..36b089b57 100644
--- a/tests/unit/algorithms/MultiphysicsNernstPlanckSolverTest.py
+++ b/tests/unit/algorithms/MultiphysicsNernstPlanckSolverTest.py
@@ -89,8 +89,8 @@ class MultiphysicsNernstPlanckSolverTest:
 
         self.p = op.algorithms.IonicConduction(network=self.net, phase=self.sw,
                                                settings=setts1)
-        self.p.set_value_BC(pores=self.net.pores('front'), values=0.02)
-        self.p.set_value_BC(pores=self.net.pores('back'), values=0.01)
+        self.p.set_value_BC(pores=self.net.pores('back'), values=0.02)
+        self.p.set_value_BC(pores=self.net.pores('front'), values=0.01)
         self.p.settings['charge_conservation'] = 'laplace'
 
         self.eA = op.algorithms.NernstPlanck(network=self.net, phase=self.sw,
diff --git a/tests/unit/algorithms/NernstPlanckTest.py b/tests/unit/algorithms/NernstPlanckTest.py
index 53dd16828..9b4a3d7a2 100644
--- a/tests/unit/algorithms/NernstPlanckTest.py
+++ b/tests/unit/algorithms/NernstPlanckTest.py
@@ -37,8 +37,8 @@ class NernstPlanckTest:
         self.oc = op.algorithms.OhmicConduction(network=self.net, phase=self.phase)
         self.oc.settings['conductance'] = 'throat.ionic_conductance'
         self.oc.settings['quantity'] = 'pore.potential'
-        self.oc.set_value_BC(pores=self.net.pores('front'), values=0.05)
-        self.oc.set_value_BC(pores=self.net.pores('back'), values=0.)
+        self.oc.set_value_BC(pores=self.net.pores('back'), values=0.05)
+        self.oc.set_value_BC(pores=self.net.pores('front'), values=0.)
         self.oc.run()
 
         self.phase.update(self.oc.results())
diff --git a/tests/unit/algorithms/ReactiveTransportTest.py b/tests/unit/algorithms/ReactiveTransportTest.py
index 62134f694..8ac3d5f97 100644
--- a/tests/unit/algorithms/ReactiveTransportTest.py
+++ b/tests/unit/algorithms/ReactiveTransportTest.py
@@ -215,8 +215,8 @@ class ReactiveTransportTest:
                              model=variable_diffusivity)
         self.phys.add_model(propname="throat.diffusive_conductance",
                             model=variable_conductance)
-        self.alg.set_value_BC(pores=self.net.pores("front"), values=10.0)
-        self.alg.set_value_BC(pores=self.net.pores("back"), values=0.0)
+        self.alg.set_value_BC(pores=self.net.pores("back"), values=10.0)
+        self.alg.set_value_BC(pores=self.net.pores("front"), values=0.0)
         self.alg.run()
         c_avg = self.alg["pore.concentration"].reshape(self.net.shape).mean(axis=(0, 2))
         desired = [10.0, 8.18175755, 5.42194391, 0.0]
diff --git a/tests/unit/algorithms/SolversTest.py b/tests/unit/algorithms/SolversTest.py
index 658359184..3214ec661 100644
--- a/tests/unit/algorithms/SolversTest.py
+++ b/tests/unit/algorithms/SolversTest.py
@@ -22,7 +22,7 @@ class SolversTest:
         self.alg.settings.update(quantity='pore.x',
                                  conductance='throat.conductance')
         self.alg.setup(phase=self.phase)
-        self.alg.set_value_BC(pores=self.net.pores('front'), values=1.0)
+        self.alg.set_value_BC(pores=self.net.pores('back'), values=1.0)
         self.alg.set_value_BC(pores=self.net.pores('bottom'), values=0.0)
 
     def test_solver_not_available(self):
diff --git a/tests/unit/algorithms/TransientMultiphysicsNernstPlanckSolverTest.py b/tests/unit/algorithms/TransientMultiphysicsNernstPlanckSolverTest.py
index 7fa433d50..c8272dcbb 100644
--- a/tests/unit/algorithms/TransientMultiphysicsNernstPlanckSolverTest.py
+++ b/tests/unit/algorithms/TransientMultiphysicsNernstPlanckSolverTest.py
@@ -90,8 +90,8 @@ class TransientMultiphysicsNernstPlanckSolverTest:
         self.p = op.algorithms.TransientIonicConduction(network=self.net,
                                                         phase=self.sw,
                                                         settings=setts1)
-        self.p.set_value_BC(pores=self.net.pores('front'), values=0.02)
-        self.p.set_value_BC(pores=self.net.pores('back'), values=0.01)
+        self.p.set_value_BC(pores=self.net.pores('back'), values=0.02)
+        self.p.set_value_BC(pores=self.net.pores('front'), values=0.01)
         self.p.settings['charge_conservation'] = 'laplace'
 
         self.eA = op.algorithms.TransientNernstPlanck(network=self.net,
diff --git a/tests/unit/algorithms/TransientReactiveTransportTest.py b/tests/unit/algorithms/TransientReactiveTransportTest.py
index dc459ef9b..19dba4223 100644
--- a/tests/unit/algorithms/TransientReactiveTransportTest.py
+++ b/tests/unit/algorithms/TransientReactiveTransportTest.py
@@ -36,9 +36,9 @@ class TransientImplicitReactiveTransportTest:
                        conductance='throat.diffusive_conductance',
                        t_initial=0, t_final=1, t_step=0.1, t_tolerance=1e-7,
                        t_precision=10, rxn_tolerance=1e-6)
-        self.alg.set_value_BC(pores=self.net.pores('front'), values=2)
+        self.alg.set_value_BC(pores=self.net.pores('back'), values=2)
         self.alg.set_source(propname='pore.reaction',
-                            pores=self.net.pores('back'))
+                            pores=self.net.pores('front'))
         self.alg.set_IC(0)
 
     def test_transient_implicit_reactive_transport(self):
diff --git a/tests/unit/algorithms/metrics/RelativePermabilityTest.py b/tests/unit/algorithms/metrics/RelativePermabilityTest.py
index 26577b557..0bdf472c4 100644
--- a/tests/unit/algorithms/metrics/RelativePermabilityTest.py
+++ b/tests/unit/algorithms/metrics/RelativePermabilityTest.py
@@ -31,7 +31,7 @@ class RelativePermeabilityTest:
                                      model=mod)
         self.wet_phase.add_model(propname='throat.entry_pressure',
                                  model=mod)
-        self.inlet_pores = self.net.pores('back')
+        self.inlet_pores = self.net.pores('front')
         ip = op.algorithms.InvasionPercolation(network=self.net,
                                                phase=self.non_wet_phase)
         ip.set_inlets(pores=self.inlet_pores)
@@ -47,8 +47,8 @@ class RelativePermeabilityTest:
         assert results['kr_wp'] is None
 
     def test_overwriting_boundary_faces(self):
-        inlets = {'x': 'back', 'y': 'back', 'z': 'back'}
-        outlets = {'x': 'front', 'y': 'front', 'z': 'front'}
+        inlets = {'x': 'front', 'y': 'front', 'z': 'front'}
+        outlets = {'x': 'back', 'y': 'back', 'z': 'back'}
         rp = op.algorithms.metrics.RelativePermeability(network=self.net)
         rp.setup(invading_phase=self.non_wet_phase.name,
                  defending_phase=self.wet_phase.name,
@@ -125,7 +125,7 @@ class RelativePermeabilityTest:
         self.wet_phase.add_model(propname='throat.entry_pressure',
                                  model=mod)
         if shape[1] != 1:
-            self.inlet_pores = self.net.pores('back')
+            self.inlet_pores = self.net.pores('front')
         else:
             self.inlet_pores = self.net.pores('left')
         ip = op.algorithms.InvasionPercolation(network=self.net,
diff --git a/tests/unit/core/BaseTest.py b/tests/unit/core/BaseTest.py
index 0845b89b8..e4cfcb339 100644
--- a/tests/unit/core/BaseTest.py
+++ b/tests/unit/core/BaseTest.py
@@ -433,14 +433,14 @@ class BaseTest:
 
     def test_labels_on_one_pore(self):
         a = self.net.labels(pores=0)
-        b = ['pore.all', 'pore.bottom', 'pore.front',
+        b = ['pore.all', 'pore.bottom', 'pore.back',
              'pore.internal', 'pore.surface',
              'pore.left', 'pore.'+self.geo.name]
         assert sorted(a) == sorted(b)
 
     def test_labels_on_list_of_pores(self):
         a = self.net.labels(pores=[0, 1])
-        b = ['pore.all', 'pore.bottom', 'pore.front',
+        b = ['pore.all', 'pore.bottom', 'pore.back',
              'pore.internal', 'pore.surface',
              'pore.left', 'pore.'+self.geo.name]
         assert sorted(a) == sorted(b)
@@ -449,21 +449,21 @@ class BaseTest:
         ind = np.zeros((self.net.Np), dtype=bool)
         ind[[0, 1]] = True
         a = self.net.labels(pores=ind)
-        b = ['pore.all', 'pore.bottom', 'pore.front',
+        b = ['pore.all', 'pore.bottom', 'pore.back',
              'pore.internal', 'pore.surface',
              'pore.left', 'pore.'+self.geo.name]
         assert sorted(a) == sorted(b)
 
     def test_labels_pores_mode_or(self):
         a = self.net.labels(pores=[0, 1, 2], mode='or')
-        b = ['pore.all', 'pore.bottom', 'pore.front',
+        b = ['pore.all', 'pore.bottom', 'pore.back',
              'pore.internal', 'pore.surface',
              'pore.left', 'pore.'+self.geo.name, 'pore.top']
         assert sorted(a) == sorted(b)
 
     def test_labels_pores_mode_and(self):
         a = self.net.labels(pores=[0, 1, 2], mode='and')
-        b = ['pore.all', 'pore.front', 'pore.geo_01',
+        b = ['pore.all', 'pore.back', 'pore.geo_01',
              'pore.internal', 'pore.left', 'pore.surface']
         assert sorted(a) == sorted(b)
 
@@ -479,13 +479,13 @@ class BaseTest:
 
     def test_labels_pores_mode_xnor(self):
         a = self.net.labels(pores=[0, 1, 2], mode='xnor')
-        b = ['pore.all', 'pore.front', 'pore.internal',
+        b = ['pore.all', 'pore.back', 'pore.internal',
              'pore.surface', 'pore.left', 'pore.'+self.geo.name]
         assert sorted(a) == sorted(b)
 
     def test_labels_pores_mode_nor(self):
         a = self.net.labels(pores=[0, 1, 2], mode='nor')
-        b = ['pore.back', 'pore.right']
+        b = ['pore.front', 'pore.right']
         assert sorted(a) == sorted(b)
 
     def test_labels_pores_mode_foo(self):
@@ -657,9 +657,9 @@ class BaseTest:
         self.net.update({'pore.all': temp})
 
     def test_get_indices_wildcard(self):
-        a = self.net._get_indices(element='pore', labels='ba*')
+        a = self.net._get_indices(element='pore', labels='fr*')
         assert np.all(a == [6, 7, 8, 15, 16, 17, 24, 25, 26])
-        b = self.net._get_indices(element='pore', labels='*ck')
+        b = self.net._get_indices(element='pore', labels='*ont')
         assert np.all(a == b)
 
     def test_write_dict(self):
@@ -714,7 +714,7 @@ class BaseTest:
     def test_getitem_with_no_matches(self):
         self.geo.pop('pore.blah', None)
         with pytest.raises(KeyError):
-            _ = self.geo['pore.blah']
+            self.geo['pore.blah']
 
     def test_interpolate_data(self):
         self.geo['throat.tester'] = np.linspace(0, 1.0, self.geo.network.Nt)
@@ -729,7 +729,7 @@ class BaseTest:
     def test_get_no_matches(self):
         self.geo.pop('pore.blah', None)
         with pytest.raises(KeyError):
-            _ = self.geo['pore.blah']
+            self.geo['pore.blah']
 
     def test_get_string(self):
         a = self.net.get('pore.coords')
@@ -899,9 +899,9 @@ class BaseTest:
         pn['pore.foo.bar'] = 1
         pn['pore.foo.baz'] = 2
         with pytest.raises(KeyError):
-            _ = pn['pore.foo.b']
+            pn['pore.foo.b']
         with pytest.raises(KeyError):
-            _ = pn['pore.fo']
+            pn['pore.fo']
 
     def test_set_label_add_to_pores(self):
         pn = op.network.Cubic(shape=[5, 5, 5])