diff --git a/examples/jupyter/candu.ipynb b/examples/jupyter/candu.ipynb
index cb83226bf..8f10b13b3 100644
--- a/examples/jupyter/candu.ipynb
+++ b/examples/jupyter/candu.ipynb
@@ -129,9 +129,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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M/cuj9L1X0pGI+FLOvudFxK0RsXV8DFwr6YeZA0DjY+452zvHX7pS0uEUbXdeCUzAjUxH\nvippvaSD44rkkYj4XNudRsRp25+XdEDSOkn3RcRTbfe7yBWSPiXpSduPj792W0R8L/M4SnCDpP3j\nQH5W0mdSNMo7BoHKlb4cANAyQgCoHCEAVI4QACpHCACVIwSAyhECQOUIAaBy/w9I0pXf8DtxcAAA\nAABJRU5ErkJggg==\n",
+      "image/png": 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y866K15Gkxus4kCPikvbFuck+noyIYyNiLXAY8JmRXbtauST1mcjs7DpbRBwJHDnNw+4D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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f45240e7550>"
+       "<matplotlib.figure.Figure at 0x7fa0cfb86be0>"
       ]
      },
      "metadata": {},
@@ -176,9 +176,9 @@
    "outputs": [
     {
      "data": {
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+      "image/png": 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SEQZZkoowyJJUhEGWpCIMsiQVMSeDHBFnRsQdEfFYRDwSET9oe6aZiIinRcSm/r/k/eK2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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f454cd98e48>"
+       "<matplotlib.figure.Figure at 0x7fa0dcce2320>"
       ]
      },
      "metadata": {},
@@ -234,9 +234,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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SPA95020fDDgS+050dWrJvjv3Zc+Y9IU99kMuZtNciCULh+a2bPceFLOnaiFaZw5+d0Vj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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f45200513c8>"
+       "<matplotlib.figure.Figure at 0x7fa0cc068470>"
       ]
      },
      "metadata": {},
@@ -306,7 +306,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": 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mu/Ka7C9sslOyyZ7PNrtXm+zDbbKjuMne6Ca7vNvsV2+y877JGQImpyGYnOtgc0KFyVkb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\nYII=\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -360,7 +360,7 @@
    "outputs": [],
    "source": [
     "fuel_tally = openmc.Tally()\n",
-    "fuel_tally.filters = [openmc.DistribcellFilter(fuel_cell.id)]\n",
+    "fuel_tally.filters = [openmc.DistribcellFilter(fuel_cell)]\n",
     "fuel_tally.scores = ['flux']\n",
     "\n",
     "tallies = openmc.Tallies([fuel_tally])\n",
@@ -1088,7 +1088,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
diff --git a/examples/jupyter/pandas-dataframes.ipynb b/examples/jupyter/pandas-dataframes.ipynb
index d56061f2c..a44ecfe96 100644
--- a/examples/jupyter/pandas-dataframes.ipynb
+++ b/examples/jupyter/pandas-dataframes.ipynb
@@ -327,7 +327,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6AgMAAAD1grKuAAAABGdBTUEAALGPC/xhBQAAACBjSFJN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\nYII=\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6AgMAAAD1grKuAAAABGdBTUEAALGPC/xhBQAAACBjSFJN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\nYII=\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -417,7 +417,7 @@
    "outputs": [],
    "source": [
     "# Instantiate tally Filter\n",
-    "cell_filter = openmc.CellFilter(fuel_cell.id)\n",
+    "cell_filter = openmc.CellFilter(fuel_cell)\n",
     "\n",
     "# Instantiate the tally\n",
     "tally = openmc.Tally(name='cell tally')\n",
@@ -445,7 +445,7 @@
    "outputs": [],
    "source": [
     "# Instantiate tally Filter\n",
-    "distribcell_filter = openmc.DistribcellFilter(moderator_cell.id)\n",
+    "distribcell_filter = openmc.DistribcellFilter(moderator_cell)\n",
     "\n",
     "# Instantiate tally Trigger for kicks\n",
     "trigger = openmc.Trigger(trigger_type='std_dev', threshold=5e-5)\n",
@@ -520,20 +520,21 @@
       "         Copyright | 2011-2017 Massachusetts Institute of Technology\n",
       "           License | http://openmc.readthedocs.io/en/latest/license.html\n",
       "           Version | 0.8.0\n",
-      "          Git SHA1 | 2d1897a051baaca9fd65ff851bc803512889a06f\n",
-      "         Date/Time | 2017-03-06 19:46:57\n",
-      "    OpenMP Threads | 4\n",
+      "          Git SHA1 | bc4683be1c853fe6d0e31bccad416ef219e3efaf\n",
+      "         Date/Time | 2017-04-13 17:23:58\n",
+      "     MPI Processes | 1\n",
+      "    OpenMP Threads | 1\n",
       "\n",
       " Reading settings XML file...\n",
       " Reading geometry XML file...\n",
       " Reading materials XML file...\n",
       " Reading cross sections XML file...\n",
-      " Reading U235 from /home/romano/openmc/scripts/nndc_hdf5/U235.h5\n",
-      " Reading U238 from /home/romano/openmc/scripts/nndc_hdf5/U238.h5\n",
-      " Reading O16 from /home/romano/openmc/scripts/nndc_hdf5/O16.h5\n",
-      " Reading H1 from /home/romano/openmc/scripts/nndc_hdf5/H1.h5\n",
-      " Reading B10 from /home/romano/openmc/scripts/nndc_hdf5/B10.h5\n",
-      " Reading Zr90 from /home/romano/openmc/scripts/nndc_hdf5/Zr90.h5\n",
+      " Reading U235 from /home/smharper/openmc/data/nndc_hdf5/U235.h5\n",
+      " Reading U238 from /home/smharper/openmc/data/nndc_hdf5/U238.h5\n",
+      " Reading O16 from /home/smharper/openmc/data/nndc_hdf5/O16.h5\n",
+      " Reading H1 from /home/smharper/openmc/data/nndc_hdf5/H1.h5\n",
+      " Reading B10 from /home/smharper/openmc/data/nndc_hdf5/B10.h5\n",
+      " Reading Zr90 from /home/smharper/openmc/data/nndc_hdf5/Zr90.h5\n",
       " Maximum neutron transport energy: 2.00000E+07 eV for U235\n",
       " Reading tallies XML file...\n",
       " Building neighboring cells lists for each surface...\n",
@@ -577,20 +578,20 @@
       "\n",
       " =======================>     TIMING STATISTICS     <=======================\n",
       "\n",
-      " Total time for initialization     =  4.8645E-01 seconds\n",
-      "   Reading cross sections          =  4.1789E-01 seconds\n",
-      " Total time in simulation          =  4.6732E+00 seconds\n",
-      "   Time in transport only          =  4.5503E+00 seconds\n",
-      "   Time in inactive batches        =  5.6790E-01 seconds\n",
-      "   Time in active batches          =  4.1053E+00 seconds\n",
-      "   Time synchronizing fission bank =  1.7410E-03 seconds\n",
-      "     Sampling source sites         =  1.2602E-03 seconds\n",
-      "     SEND/RECV source sites        =  4.4969E-04 seconds\n",
-      "   Time accumulating tallies       =  8.8049E-04 seconds\n",
-      " Total time for finalization       =  4.3874E-05 seconds\n",
-      " Total time elapsed                =  5.1725E+00 seconds\n",
-      " Calculation Rate (inactive)       =  22010.8 neutrons/second\n",
-      " Calculation Rate (active)         =  9134.46 neutrons/second\n",
+      " Total time for initialization     =  2.4022E-01 seconds\n",
+      "   Reading cross sections          =  1.9056E-01 seconds\n",
+      " Total time in simulation          =  7.5438E+00 seconds\n",
+      "   Time in transport only          =  7.5290E+00 seconds\n",
+      "   Time in inactive batches        =  1.0482E+00 seconds\n",
+      "   Time in active batches          =  6.4956E+00 seconds\n",
+      "   Time synchronizing fission bank =  2.3117E-03 seconds\n",
+      "     Sampling source sites         =  1.3344E-03 seconds\n",
+      "     SEND/RECV source sites        =  6.8338E-04 seconds\n",
+      "   Time accumulating tallies       =  3.9461E-04 seconds\n",
+      " Total time for finalization       =  1.3648E-05 seconds\n",
+      " Total time elapsed                =  7.7964E+00 seconds\n",
+      " Calculation Rate (inactive)       =  11925.2 neutrons/second\n",
+      " Calculation Rate (active)         =  5773.18 neutrons/second\n",
       "\n",
       " ============================>     RESULTS     <============================\n",
       "\n",
@@ -699,13 +700,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[ 0.17581417]]\n",
+      "[[[ 0.22614381]]\n",
       "\n",
-      " [[ 0.30578219]]\n",
+      " [[ 0.3789572 ]]\n",
       "\n",
-      " [[ 0.06842901]]\n",
+      " [[ 0.05763899]]\n",
       "\n",
-      " [[ 0.12436752]]]\n"
+      " [[ 0.14265074]]]\n"
      ]
     }
    ],
@@ -762,8 +763,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>fission</td>\n",
-       "      <td>2.24e-04</td>\n",
-       "      <td>3.94e-05</td>\n",
+       "      <td>2.28e-04</td>\n",
+       "      <td>5.15e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -773,8 +774,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>5.46e-04</td>\n",
-       "      <td>9.59e-05</td>\n",
+       "      <td>5.55e-04</td>\n",
+       "      <td>1.26e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -784,8 +785,8 @@
        "      <td>6.25e-01</td>\n",
        "      <td>2.00e+07</td>\n",
        "      <td>fission</td>\n",
-       "      <td>8.42e-05</td>\n",
-       "      <td>6.79e-06</td>\n",
+       "      <td>8.65e-05</td>\n",
+       "      <td>9.06e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -795,8 +796,8 @@
        "      <td>6.25e-01</td>\n",
        "      <td>2.00e+07</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>2.22e-04</td>\n",
-       "      <td>1.65e-05</td>\n",
+       "      <td>2.28e-04</td>\n",
+       "      <td>2.19e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -806,8 +807,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>fission</td>\n",
-       "      <td>1.85e-04</td>\n",
-       "      <td>2.70e-05</td>\n",
+       "      <td>1.83e-04</td>\n",
+       "      <td>3.54e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
@@ -817,8 +818,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>4.52e-04</td>\n",
-       "      <td>6.58e-05</td>\n",
+       "      <td>4.47e-04</td>\n",
+       "      <td>8.62e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
@@ -828,8 +829,8 @@
        "      <td>6.25e-01</td>\n",
        "      <td>2.00e+07</td>\n",
        "      <td>fission</td>\n",
-       "      <td>6.82e-05</td>\n",
-       "      <td>5.29e-06</td>\n",
+       "      <td>6.91e-05</td>\n",
+       "      <td>6.94e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
@@ -840,7 +841,7 @@
        "      <td>2.00e+07</td>\n",
        "      <td>nu-fission</td>\n",
        "      <td>1.81e-04</td>\n",
-       "      <td>1.35e-05</td>\n",
+       "      <td>1.77e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
@@ -850,8 +851,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>fission</td>\n",
-       "      <td>2.05e-04</td>\n",
-       "      <td>2.25e-05</td>\n",
+       "      <td>1.98e-04</td>\n",
+       "      <td>2.55e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
@@ -861,8 +862,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>5.00e-04</td>\n",
-       "      <td>5.49e-05</td>\n",
+       "      <td>4.82e-04</td>\n",
+       "      <td>6.20e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
@@ -872,8 +873,8 @@
        "      <td>6.25e-01</td>\n",
        "      <td>2.00e+07</td>\n",
        "      <td>fission</td>\n",
-       "      <td>7.53e-05</td>\n",
-       "      <td>7.06e-06</td>\n",
+       "      <td>7.76e-05</td>\n",
+       "      <td>9.73e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
@@ -883,8 +884,8 @@
        "      <td>6.25e-01</td>\n",
        "      <td>2.00e+07</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>1.99e-04</td>\n",
-       "      <td>1.81e-05</td>\n",
+       "      <td>2.05e-04</td>\n",
+       "      <td>2.48e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
@@ -894,8 +895,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>fission</td>\n",
-       "      <td>2.06e-04</td>\n",
-       "      <td>2.79e-05</td>\n",
+       "      <td>2.32e-04</td>\n",
+       "      <td>3.38e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
@@ -905,8 +906,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>5.03e-04</td>\n",
-       "      <td>6.80e-05</td>\n",
+       "      <td>5.66e-04</td>\n",
+       "      <td>8.23e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
@@ -916,8 +917,8 @@
        "      <td>6.25e-01</td>\n",
        "      <td>2.00e+07</td>\n",
        "      <td>fission</td>\n",
-       "      <td>6.65e-05</td>\n",
-       "      <td>3.91e-06</td>\n",
+       "      <td>6.54e-05</td>\n",
+       "      <td>4.61e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
@@ -927,8 +928,8 @@
        "      <td>6.25e-01</td>\n",
        "      <td>2.00e+07</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>1.75e-04</td>\n",
-       "      <td>1.04e-05</td>\n",
+       "      <td>1.73e-04</td>\n",
+       "      <td>1.23e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
@@ -938,8 +939,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>fission</td>\n",
-       "      <td>2.03e-04</td>\n",
-       "      <td>2.78e-05</td>\n",
+       "      <td>2.18e-04</td>\n",
+       "      <td>3.68e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
@@ -949,8 +950,8 @@
        "      <td>0.00e+00</td>\n",
        "      <td>6.25e-01</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>4.94e-04</td>\n",
-       "      <td>6.78e-05</td>\n",
+       "      <td>5.32e-04</td>\n",
+       "      <td>8.97e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
@@ -960,8 +961,8 @@
        "      <td>6.25e-01</td>\n",
        "      <td>2.00e+07</td>\n",
        "      <td>fission</td>\n",
-       "      <td>6.26e-05</td>\n",
-       "      <td>5.71e-06</td>\n",
+       "      <td>5.92e-05</td>\n",
+       "      <td>6.63e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
@@ -971,8 +972,8 @@
        "      <td>6.25e-01</td>\n",
        "      <td>2.00e+07</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>1.64e-04</td>\n",
-       "      <td>1.53e-05</td>\n",
+       "      <td>1.56e-04</td>\n",
+       "      <td>1.82e-05</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -981,49 +982,49 @@
       "text/plain": [
        "   mesh 1       energy low [eV] energy high [eV]       score     mean  \\\n",
        "        x  y  z                                                         \n",
-       "0       1  1  1        0.00e+00         6.25e-01     fission 2.24e-04   \n",
-       "1       1  1  1        0.00e+00         6.25e-01  nu-fission 5.46e-04   \n",
-       "2       1  1  1        6.25e-01         2.00e+07     fission 8.42e-05   \n",
-       "3       1  1  1        6.25e-01         2.00e+07  nu-fission 2.22e-04   \n",
-       "4       1  2  1        0.00e+00         6.25e-01     fission 1.85e-04   \n",
-       "5       1  2  1        0.00e+00         6.25e-01  nu-fission 4.52e-04   \n",
-       "6       1  2  1        6.25e-01         2.00e+07     fission 6.82e-05   \n",
+       "0       1  1  1        0.00e+00         6.25e-01     fission 2.28e-04   \n",
+       "1       1  1  1        0.00e+00         6.25e-01  nu-fission 5.55e-04   \n",
+       "2       1  1  1        6.25e-01         2.00e+07     fission 8.65e-05   \n",
+       "3       1  1  1        6.25e-01         2.00e+07  nu-fission 2.28e-04   \n",
+       "4       1  2  1        0.00e+00         6.25e-01     fission 1.83e-04   \n",
+       "5       1  2  1        0.00e+00         6.25e-01  nu-fission 4.47e-04   \n",
+       "6       1  2  1        6.25e-01         2.00e+07     fission 6.91e-05   \n",
        "7       1  2  1        6.25e-01         2.00e+07  nu-fission 1.81e-04   \n",
-       "8       1  3  1        0.00e+00         6.25e-01     fission 2.05e-04   \n",
-       "9       1  3  1        0.00e+00         6.25e-01  nu-fission 5.00e-04   \n",
-       "10      1  3  1        6.25e-01         2.00e+07     fission 7.53e-05   \n",
-       "11      1  3  1        6.25e-01         2.00e+07  nu-fission 1.99e-04   \n",
-       "12      1  4  1        0.00e+00         6.25e-01     fission 2.06e-04   \n",
-       "13      1  4  1        0.00e+00         6.25e-01  nu-fission 5.03e-04   \n",
-       "14      1  4  1        6.25e-01         2.00e+07     fission 6.65e-05   \n",
-       "15      1  4  1        6.25e-01         2.00e+07  nu-fission 1.75e-04   \n",
-       "16      1  5  1        0.00e+00         6.25e-01     fission 2.03e-04   \n",
-       "17      1  5  1        0.00e+00         6.25e-01  nu-fission 4.94e-04   \n",
-       "18      1  5  1        6.25e-01         2.00e+07     fission 6.26e-05   \n",
-       "19      1  5  1        6.25e-01         2.00e+07  nu-fission 1.64e-04   \n",
+       "8       1  3  1        0.00e+00         6.25e-01     fission 1.98e-04   \n",
+       "9       1  3  1        0.00e+00         6.25e-01  nu-fission 4.82e-04   \n",
+       "10      1  3  1        6.25e-01         2.00e+07     fission 7.76e-05   \n",
+       "11      1  3  1        6.25e-01         2.00e+07  nu-fission 2.05e-04   \n",
+       "12      1  4  1        0.00e+00         6.25e-01     fission 2.32e-04   \n",
+       "13      1  4  1        0.00e+00         6.25e-01  nu-fission 5.66e-04   \n",
+       "14      1  4  1        6.25e-01         2.00e+07     fission 6.54e-05   \n",
+       "15      1  4  1        6.25e-01         2.00e+07  nu-fission 1.73e-04   \n",
+       "16      1  5  1        0.00e+00         6.25e-01     fission 2.18e-04   \n",
+       "17      1  5  1        0.00e+00         6.25e-01  nu-fission 5.32e-04   \n",
+       "18      1  5  1        6.25e-01         2.00e+07     fission 5.92e-05   \n",
+       "19      1  5  1        6.25e-01         2.00e+07  nu-fission 1.56e-04   \n",
        "\n",
        "   std. dev.  \n",
        "              \n",
-       "0   3.94e-05  \n",
-       "1   9.59e-05  \n",
-       "2   6.79e-06  \n",
-       "3   1.65e-05  \n",
-       "4   2.70e-05  \n",
-       "5   6.58e-05  \n",
-       "6   5.29e-06  \n",
-       "7   1.35e-05  \n",
-       "8   2.25e-05  \n",
-       "9   5.49e-05  \n",
-       "10  7.06e-06  \n",
-       "11  1.81e-05  \n",
-       "12  2.79e-05  \n",
-       "13  6.80e-05  \n",
-       "14  3.91e-06  \n",
-       "15  1.04e-05  \n",
-       "16  2.78e-05  \n",
-       "17  6.78e-05  \n",
-       "18  5.71e-06  \n",
-       "19  1.53e-05  "
+       "0   5.15e-05  \n",
+       "1   1.26e-04  \n",
+       "2   9.06e-06  \n",
+       "3   2.19e-05  \n",
+       "4   3.54e-05  \n",
+       "5   8.62e-05  \n",
+       "6   6.94e-06  \n",
+       "7   1.77e-05  \n",
+       "8   2.55e-05  \n",
+       "9   6.20e-05  \n",
+       "10  9.73e-06  \n",
+       "11  2.48e-05  \n",
+       "12  3.38e-05  \n",
+       "13  8.23e-05  \n",
+       "14  4.61e-06  \n",
+       "15  1.23e-05  \n",
+       "16  3.68e-05  \n",
+       "17  8.97e-05  \n",
+       "18  6.63e-06  \n",
+       "19  1.82e-05  "
       ]
      },
      "execution_count": 22,
@@ -1051,9 +1052,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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AeEkf6+NzuraVNH78eAqFQrdXU1PTDpevrly5ssdnSUyfPp3Fixd3a2tra6NQ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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f7befa9ecc0>"
+       "<matplotlib.figure.Figure at 0x7f7d809cea90>"
       ]
      },
      "metadata": {},
@@ -1076,7 +1077,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x7f7bec6d7b00>"
+       "<matplotlib.colorbar.Colorbar at 0x7f7d7dd40a20>"
       ]
      },
      "execution_count": 24,
@@ -1085,9 +1086,9 @@
     },
     {
      "data": {
-      "image/png": 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R8XhE3AV8C9hNUnmNBayIiKfKjqY2hnMiNTOztpE0GpgE3FQ6FxEB3AjsXuW23bPr5eaU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\nE6mZmVkLnEjNzMxa8P8BkFEtrpI/UtsAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f7becbf1390>"
+       "<matplotlib.figure.Figure at 0x7f7d7de87e10>"
       ]
      },
      "metadata": {},
@@ -1174,144 +1175,144 @@
        "      <td>10000</td>\n",
        "      <td>U235</td>\n",
        "      <td>scatter-Y0,0</td>\n",
-       "      <td>3.86e-02</td>\n",
-       "      <td>6.85e-04</td>\n",
+       "      <td>3.87e-02</td>\n",
+       "      <td>8.61e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>10000</td>\n",
        "      <td>U235</td>\n",
        "      <td>scatter-Y1,-1</td>\n",
-       "      <td>6.95e-04</td>\n",
-       "      <td>3.15e-04</td>\n",
+       "      <td>6.88e-04</td>\n",
+       "      <td>3.63e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>10000</td>\n",
        "      <td>U235</td>\n",
        "      <td>scatter-Y1,0</td>\n",
-       "      <td>-1.06e-04</td>\n",
-       "      <td>3.79e-04</td>\n",
+       "      <td>-3.38e-04</td>\n",
+       "      <td>4.37e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>10000</td>\n",
        "      <td>U235</td>\n",
        "      <td>scatter-Y1,1</td>\n",
-       "      <td>-3.63e-04</td>\n",
-       "      <td>3.18e-04</td>\n",
+       "      <td>-4.27e-04</td>\n",
+       "      <td>3.74e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>10000</td>\n",
        "      <td>U235</td>\n",
        "      <td>scatter-Y2,-2</td>\n",
-       "      <td>1.20e-04</td>\n",
-       "      <td>1.59e-04</td>\n",
+       "      <td>1.88e-04</td>\n",
+       "      <td>1.86e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>10000</td>\n",
        "      <td>U235</td>\n",
        "      <td>scatter-Y2,-1</td>\n",
-       "      <td>3.93e-05</td>\n",
-       "      <td>1.86e-04</td>\n",
+       "      <td>8.96e-05</td>\n",
+       "      <td>2.02e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>10000</td>\n",
        "      <td>U235</td>\n",
        "      <td>scatter-Y2,0</td>\n",
-       "      <td>1.81e-04</td>\n",
-       "      <td>1.85e-04</td>\n",
+       "      <td>4.03e-04</td>\n",
+       "      <td>2.04e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>10000</td>\n",
        "      <td>U235</td>\n",
        "      <td>scatter-Y2,1</td>\n",
-       "      <td>1.24e-04</td>\n",
-       "      <td>1.81e-04</td>\n",
+       "      <td>1.48e-04</td>\n",
+       "      <td>2.24e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>10000</td>\n",
        "      <td>U235</td>\n",
        "      <td>scatter-Y2,2</td>\n",
-       "      <td>2.06e-04</td>\n",
-       "      <td>2.26e-04</td>\n",
+       "      <td>1.11e-04</td>\n",
+       "      <td>2.01e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>10000</td>\n",
        "      <td>U238</td>\n",
        "      <td>scatter-Y0,0</td>\n",
-       "      <td>2.33e+00</td>\n",
-       "      <td>1.10e-02</td>\n",
+       "      <td>2.34e+00</td>\n",
+       "      <td>1.08e-02</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>10000</td>\n",
        "      <td>U238</td>\n",
        "      <td>scatter-Y1,-1</td>\n",
-       "      <td>2.90e-02</td>\n",
-       "      <td>2.33e-03</td>\n",
+       "      <td>2.93e-02</td>\n",
+       "      <td>2.81e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td>10000</td>\n",
        "      <td>U238</td>\n",
        "      <td>scatter-Y1,0</td>\n",
-       "      <td>3.45e-03</td>\n",
-       "      <td>2.38e-03</td>\n",
+       "      <td>4.25e-03</td>\n",
+       "      <td>1.83e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
        "      <td>10000</td>\n",
        "      <td>U238</td>\n",
        "      <td>scatter-Y1,1</td>\n",
-       "      <td>-2.72e-02</td>\n",
-       "      <td>2.76e-03</td>\n",
+       "      <td>-2.60e-02</td>\n",
+       "      <td>3.28e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
        "      <td>10000</td>\n",
        "      <td>U238</td>\n",
        "      <td>scatter-Y2,-2</td>\n",
-       "      <td>-2.02e-03</td>\n",
-       "      <td>1.44e-03</td>\n",
+       "      <td>-1.10e-03</td>\n",
+       "      <td>1.58e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
        "      <td>10000</td>\n",
        "      <td>U238</td>\n",
        "      <td>scatter-Y2,-1</td>\n",
-       "      <td>8.07e-06</td>\n",
-       "      <td>1.49e-03</td>\n",
+       "      <td>-4.81e-04</td>\n",
+       "      <td>1.67e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
        "      <td>10000</td>\n",
        "      <td>U238</td>\n",
        "      <td>scatter-Y2,0</td>\n",
-       "      <td>-3.74e-07</td>\n",
-       "      <td>1.79e-03</td>\n",
+       "      <td>-7.95e-04</td>\n",
+       "      <td>1.53e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
        "      <td>10000</td>\n",
        "      <td>U238</td>\n",
        "      <td>scatter-Y2,1</td>\n",
-       "      <td>6.54e-04</td>\n",
-       "      <td>1.49e-03</td>\n",
+       "      <td>1.06e-03</td>\n",
+       "      <td>1.96e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
        "      <td>10000</td>\n",
        "      <td>U238</td>\n",
        "      <td>scatter-Y2,2</td>\n",
-       "      <td>-1.93e-03</td>\n",
-       "      <td>1.36e-03</td>\n",
+       "      <td>-7.65e-04</td>\n",
+       "      <td>1.67e-03</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1319,24 +1320,24 @@
       ],
       "text/plain": [
        "     cell nuclide          score      mean  std. dev.\n",
-       "0   10000    U235   scatter-Y0,0  3.86e-02   6.85e-04\n",
-       "1   10000    U235  scatter-Y1,-1  6.95e-04   3.15e-04\n",
-       "2   10000    U235   scatter-Y1,0 -1.06e-04   3.79e-04\n",
-       "3   10000    U235   scatter-Y1,1 -3.63e-04   3.18e-04\n",
-       "4   10000    U235  scatter-Y2,-2  1.20e-04   1.59e-04\n",
-       "5   10000    U235  scatter-Y2,-1  3.93e-05   1.86e-04\n",
-       "6   10000    U235   scatter-Y2,0  1.81e-04   1.85e-04\n",
-       "7   10000    U235   scatter-Y2,1  1.24e-04   1.81e-04\n",
-       "8   10000    U235   scatter-Y2,2  2.06e-04   2.26e-04\n",
-       "9   10000    U238   scatter-Y0,0  2.33e+00   1.10e-02\n",
-       "10  10000    U238  scatter-Y1,-1  2.90e-02   2.33e-03\n",
-       "11  10000    U238   scatter-Y1,0  3.45e-03   2.38e-03\n",
-       "12  10000    U238   scatter-Y1,1 -2.72e-02   2.76e-03\n",
-       "13  10000    U238  scatter-Y2,-2 -2.02e-03   1.44e-03\n",
-       "14  10000    U238  scatter-Y2,-1  8.07e-06   1.49e-03\n",
-       "15  10000    U238   scatter-Y2,0 -3.74e-07   1.79e-03\n",
-       "16  10000    U238   scatter-Y2,1  6.54e-04   1.49e-03\n",
-       "17  10000    U238   scatter-Y2,2 -1.93e-03   1.36e-03"
+       "0   10000    U235   scatter-Y0,0  3.87e-02   8.61e-04\n",
+       "1   10000    U235  scatter-Y1,-1  6.88e-04   3.63e-04\n",
+       "2   10000    U235   scatter-Y1,0 -3.38e-04   4.37e-04\n",
+       "3   10000    U235   scatter-Y1,1 -4.27e-04   3.74e-04\n",
+       "4   10000    U235  scatter-Y2,-2  1.88e-04   1.86e-04\n",
+       "5   10000    U235  scatter-Y2,-1  8.96e-05   2.02e-04\n",
+       "6   10000    U235   scatter-Y2,0  4.03e-04   2.04e-04\n",
+       "7   10000    U235   scatter-Y2,1  1.48e-04   2.24e-04\n",
+       "8   10000    U235   scatter-Y2,2  1.11e-04   2.01e-04\n",
+       "9   10000    U238   scatter-Y0,0  2.34e+00   1.08e-02\n",
+       "10  10000    U238  scatter-Y1,-1  2.93e-02   2.81e-03\n",
+       "11  10000    U238   scatter-Y1,0  4.25e-03   1.83e-03\n",
+       "12  10000    U238   scatter-Y1,1 -2.60e-02   3.28e-03\n",
+       "13  10000    U238  scatter-Y2,-2 -1.10e-03   1.58e-03\n",
+       "14  10000    U238  scatter-Y2,-1 -4.81e-04   1.67e-03\n",
+       "15  10000    U238   scatter-Y2,0 -7.95e-04   1.53e-03\n",
+       "16  10000    U238   scatter-Y2,1  1.06e-03   1.96e-03\n",
+       "17  10000    U238   scatter-Y2,2 -7.65e-04   1.67e-03"
       ]
      },
      "execution_count": 26,
@@ -1370,8 +1371,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[ 0.00136183  0.01104314]\n",
-      "  [ 0.00022601  0.00068479]]]\n"
+      "[[[ 0.0016699   0.01076055]\n",
+      "  [ 0.00020076  0.00086098]]]\n"
      ]
     }
    ],
@@ -1438,7 +1439,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[ 0.03500496]]]\n"
+      "[[[ 0.04126529]]]\n"
      ]
     }
    ],
@@ -1519,8 +1520,8 @@
        "      <td>10002</td>\n",
        "      <td>279</td>\n",
        "      <td>absorption</td>\n",
-       "      <td>7.77e-05</td>\n",
-       "      <td>7.87e-06</td>\n",
+       "      <td>7.37e-05</td>\n",
+       "      <td>7.77e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>559</th>\n",
@@ -1533,8 +1534,8 @@
        "      <td>10002</td>\n",
        "      <td>279</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.28e-02</td>\n",
-       "      <td>5.09e-04</td>\n",
+       "      <td>1.27e-02</td>\n",
+       "      <td>6.76e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>560</th>\n",
@@ -1547,8 +1548,8 @@
        "      <td>10002</td>\n",
        "      <td>280</td>\n",
        "      <td>absorption</td>\n",
-       "      <td>8.92e-05</td>\n",
-       "      <td>7.32e-06</td>\n",
+       "      <td>9.14e-05</td>\n",
+       "      <td>9.21e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>561</th>\n",
@@ -1561,8 +1562,8 @@
        "      <td>10002</td>\n",
        "      <td>280</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.37e-02</td>\n",
-       "      <td>4.99e-04</td>\n",
+       "      <td>1.39e-02</td>\n",
+       "      <td>5.27e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>562</th>\n",
@@ -1575,8 +1576,8 @@
        "      <td>10002</td>\n",
        "      <td>281</td>\n",
        "      <td>absorption</td>\n",
-       "      <td>9.50e-05</td>\n",
-       "      <td>7.80e-06</td>\n",
+       "      <td>8.98e-05</td>\n",
+       "      <td>8.99e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>563</th>\n",
@@ -1589,8 +1590,8 @@
        "      <td>10002</td>\n",
        "      <td>281</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.49e-02</td>\n",
-       "      <td>4.74e-04</td>\n",
+       "      <td>1.47e-02</td>\n",
+       "      <td>6.07e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>564</th>\n",
@@ -1603,8 +1604,8 @@
        "      <td>10002</td>\n",
        "      <td>282</td>\n",
        "      <td>absorption</td>\n",
-       "      <td>1.15e-04</td>\n",
-       "      <td>1.00e-05</td>\n",
+       "      <td>1.13e-04</td>\n",
+       "      <td>1.28e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>565</th>\n",
@@ -1617,8 +1618,8 @@
        "      <td>10002</td>\n",
        "      <td>282</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.58e-02</td>\n",
-       "      <td>6.18e-04</td>\n",
+       "      <td>1.54e-02</td>\n",
+       "      <td>6.58e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>566</th>\n",
@@ -1632,7 +1633,7 @@
        "      <td>283</td>\n",
        "      <td>absorption</td>\n",
        "      <td>1.13e-04</td>\n",
-       "      <td>1.01e-05</td>\n",
+       "      <td>9.64e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>567</th>\n",
@@ -1646,7 +1647,7 @@
        "      <td>283</td>\n",
        "      <td>scatter</td>\n",
        "      <td>1.75e-02</td>\n",
-       "      <td>5.66e-04</td>\n",
+       "      <td>5.84e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>568</th>\n",
@@ -1659,8 +1660,8 @@
        "      <td>10002</td>\n",
        "      <td>284</td>\n",
        "      <td>absorption</td>\n",
-       "      <td>1.08e-04</td>\n",
-       "      <td>9.66e-06</td>\n",
+       "      <td>1.10e-04</td>\n",
+       "      <td>1.12e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>569</th>\n",
@@ -1673,8 +1674,8 @@
        "      <td>10002</td>\n",
        "      <td>284</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.73e-02</td>\n",
-       "      <td>5.40e-04</td>\n",
+       "      <td>1.72e-02</td>\n",
+       "      <td>7.15e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>570</th>\n",
@@ -1687,8 +1688,8 @@
        "      <td>10002</td>\n",
        "      <td>285</td>\n",
        "      <td>absorption</td>\n",
-       "      <td>1.16e-04</td>\n",
-       "      <td>1.44e-05</td>\n",
+       "      <td>1.27e-04</td>\n",
+       "      <td>1.92e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>571</th>\n",
@@ -1701,8 +1702,8 @@
        "      <td>10002</td>\n",
        "      <td>285</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.70e-02</td>\n",
-       "      <td>6.90e-04</td>\n",
+       "      <td>1.75e-02</td>\n",
+       "      <td>8.93e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>572</th>\n",
@@ -1715,8 +1716,8 @@
        "      <td>10002</td>\n",
        "      <td>286</td>\n",
        "      <td>absorption</td>\n",
-       "      <td>1.16e-04</td>\n",
-       "      <td>1.02e-05</td>\n",
+       "      <td>1.24e-04</td>\n",
+       "      <td>1.26e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>573</th>\n",
@@ -1729,8 +1730,8 @@
        "      <td>10002</td>\n",
        "      <td>286</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.77e-02</td>\n",
-       "      <td>6.80e-04</td>\n",
+       "      <td>1.78e-02</td>\n",
+       "      <td>9.03e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>574</th>\n",
@@ -1743,8 +1744,8 @@
        "      <td>10002</td>\n",
        "      <td>287</td>\n",
        "      <td>absorption</td>\n",
-       "      <td>1.20e-04</td>\n",
-       "      <td>1.36e-05</td>\n",
+       "      <td>1.24e-04</td>\n",
+       "      <td>1.64e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>575</th>\n",
@@ -1757,8 +1758,8 @@
        "      <td>10002</td>\n",
        "      <td>287</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.80e-02</td>\n",
-       "      <td>7.80e-04</td>\n",
+       "      <td>1.85e-02</td>\n",
+       "      <td>1.01e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>576</th>\n",
@@ -1772,7 +1773,7 @@
        "      <td>288</td>\n",
        "      <td>absorption</td>\n",
        "      <td>1.32e-04</td>\n",
-       "      <td>1.30e-05</td>\n",
+       "      <td>1.37e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>577</th>\n",
@@ -1785,8 +1786,8 @@
        "      <td>10002</td>\n",
        "      <td>288</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.86e-02</td>\n",
-       "      <td>7.12e-04</td>\n",
+       "      <td>1.87e-02</td>\n",
+       "      <td>8.24e-04</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1820,26 +1821,26 @@
        "        mean std. dev.  \n",
        "                        \n",
        "                        \n",
-       "558 7.77e-05  7.87e-06  \n",
-       "559 1.28e-02  5.09e-04  \n",
-       "560 8.92e-05  7.32e-06  \n",
-       "561 1.37e-02  4.99e-04  \n",
-       "562 9.50e-05  7.80e-06  \n",
-       "563 1.49e-02  4.74e-04  \n",
-       "564 1.15e-04  1.00e-05  \n",
-       "565 1.58e-02  6.18e-04  \n",
-       "566 1.13e-04  1.01e-05  \n",
-       "567 1.75e-02  5.66e-04  \n",
-       "568 1.08e-04  9.66e-06  \n",
-       "569 1.73e-02  5.40e-04  \n",
-       "570 1.16e-04  1.44e-05  \n",
-       "571 1.70e-02  6.90e-04  \n",
-       "572 1.16e-04  1.02e-05  \n",
-       "573 1.77e-02  6.80e-04  \n",
-       "574 1.20e-04  1.36e-05  \n",
-       "575 1.80e-02  7.80e-04  \n",
-       "576 1.32e-04  1.30e-05  \n",
-       "577 1.86e-02  7.12e-04  "
+       "558 7.37e-05  7.77e-06  \n",
+       "559 1.27e-02  6.76e-04  \n",
+       "560 9.14e-05  9.21e-06  \n",
+       "561 1.39e-02  5.27e-04  \n",
+       "562 8.98e-05  8.99e-06  \n",
+       "563 1.47e-02  6.07e-04  \n",
+       "564 1.13e-04  1.28e-05  \n",
+       "565 1.54e-02  6.58e-04  \n",
+       "566 1.13e-04  9.64e-06  \n",
+       "567 1.75e-02  5.84e-04  \n",
+       "568 1.10e-04  1.12e-05  \n",
+       "569 1.72e-02  7.15e-04  \n",
+       "570 1.27e-04  1.92e-05  \n",
+       "571 1.75e-02  8.93e-04  \n",
+       "572 1.24e-04  1.26e-05  \n",
+       "573 1.78e-02  9.03e-04  \n",
+       "574 1.24e-04  1.64e-05  \n",
+       "575 1.85e-02  1.01e-03  \n",
+       "576 1.32e-04  1.37e-05  \n",
+       "577 1.87e-02  8.24e-04  "
       ]
      },
      "execution_count": 30,
@@ -1892,38 +1893,38 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
-       "      <td>4.17e-04</td>\n",
-       "      <td>2.05e-05</td>\n",
+       "      <td>4.19e-04</td>\n",
+       "      <td>2.40e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
        "      <td>2.42e-04</td>\n",
-       "      <td>8.32e-06</td>\n",
+       "      <td>1.03e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
-       "      <td>2.27e-05</td>\n",
-       "      <td>4.04e-06</td>\n",
+       "      <td>2.31e-05</td>\n",
+       "      <td>4.39e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
-       "      <td>2.01e-04</td>\n",
-       "      <td>1.40e-05</td>\n",
+       "      <td>2.03e-04</td>\n",
+       "      <td>1.64e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
-       "      <td>4.00e-04</td>\n",
-       "      <td>2.05e-05</td>\n",
+       "      <td>4.01e-04</td>\n",
+       "      <td>2.39e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
-       "      <td>6.08e-04</td>\n",
-       "      <td>2.60e-05</td>\n",
+       "      <td>6.17e-04</td>\n",
+       "      <td>3.02e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
-       "      <td>9.38e-04</td>\n",
-       "      <td>4.27e-05</td>\n",
+       "      <td>9.28e-04</td>\n",
+       "      <td>5.88e-05</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1934,13 +1935,13 @@
        "                        \n",
        "                        \n",
        "count 2.89e+02  2.89e+02\n",
-       "mean  4.17e-04  2.05e-05\n",
-       "std   2.42e-04  8.32e-06\n",
-       "min   2.27e-05  4.04e-06\n",
-       "25%   2.01e-04  1.40e-05\n",
-       "50%   4.00e-04  2.05e-05\n",
-       "75%   6.08e-04  2.60e-05\n",
-       "max   9.38e-04  4.27e-05"
+       "mean  4.19e-04  2.40e-05\n",
+       "std   2.42e-04  1.03e-05\n",
+       "min   2.31e-05  4.39e-06\n",
+       "25%   2.03e-04  1.64e-05\n",
+       "50%   4.01e-04  2.39e-05\n",
+       "75%   6.17e-04  3.02e-05\n",
+       "max   9.28e-04  5.88e-05"
       ]
      },
      "execution_count": 31,
@@ -1975,7 +1976,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mann-Whitney Test p-value: 0.3933685843661936\n"
+      "Mann-Whitney Test p-value: 0.7108210033985298\n"
      ]
     }
    ],
@@ -2013,7 +2014,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Mann-Whitney Test p-value: 7.927841393301949e-42\n"
+      "Mann-Whitney Test p-value: 7.454144155212731e-42\n"
      ]
     }
    ],
@@ -2049,7 +2050,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/romano/miniconda3/envs/python3/lib/python3.5/site-packages/ipykernel/__main__.py:4: SettingWithCopyWarning: \n",
+      "/usr/local/lib/python3.5/dist-packages/ipykernel/__main__.py:4: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
@@ -2059,7 +2060,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f7bec63e9b0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f7d809ce2e8>"
       ]
      },
      "execution_count": 34,
@@ -2068,9 +2069,9 @@
     },
     {
      "data": {
-      "image/png": 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tSVtSWfR0S5fO15ZKU5+IdUt5jTEmI1IuKVXdFHgoVYGyHBIyC/YymyMl4g61Mck5JuZI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\nh1fljxGV4g+sUW44ghV8uSl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3LuXLRRB+vYxCoaCQIyIySbZs2UJfXx9An7tvadV1Gq7JmUSfAm4wsxFgE8Fo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\nkOeljDLb6vEmwuzAmDQR3vh/VuurHUv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6e3ubeo8iIiJ5tmXLFvr6+gD63H1Lq67TaTU5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\nRK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f7bec673630>"
+       "<matplotlib.figure.Figure at 0x7f7d7ddf7d68>"
       ]
      },
      "metadata": {},
@@ -2097,7 +2098,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7f7bec60f358>"
+       "<matplotlib.legend.Legend at 0x7f7d7dc8d630>"
       ]
      },
      "execution_count": 35,
@@ -2106,9 +2107,9 @@
     },
     {
      "data": {
-      "image/png": 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4bD4cqG4B5NvW0ZA7y07jyOR79E/Mi7ocqQYFgVRu8eTgp4JAKjEudRxL03tx\nfcE4kqSiLkeqSEEglVs8EVoeCM33i7oSqaVKKeB3ZedwQOJjTk+qu+q6SkEgFfvmK1jxuo4GZKde\nTPfmnfR+XFnwDIWURV2OVIGCQCq25CXwlIJAMmDcUXYGbe1Lzki+EnUxUgWRBIGZLTezBWb2jpnN\njqIG2YnFE6Hx3tC6Z9SVSB3wSrobc9P7c0XBsxRRGnU5souiPCIY4O493F1XKtU2pZvgg6lw4BBI\n6KBRMmH8sexM2thqvpucHnUxsov0Vy7ftnQ6lH6jZiHZJTPSh/BW+gAuL3iOepREXY7sgqiCwIEp\nZjbHzC6paAIzu8TMZpvZ7FWr1OVtrnQcMYmnHruXdd6ATg+sp+OISTm9PaLUZcFRQWv7irOS/4y6\nGNkFUQXBke7eAxgMXG5mR28/gbvf7+693b13y5Ytc19hTCVIc1xyDv9M96RUt7SWXTQz3YXZ6QO4\npGASBTqDqM6IJAjc/ePw5xfAM8BhUdQh39bb3qe5refl1KFRlyJ1kvHnsmG0tS8Zlng96mIkQzkP\nAjNraGaNtz4HTgDezXUdUrEhyTfZ7IVMS+tsIamaaemeLEq357KC5zHSUZcjGYjiiKAVMMPM5gGz\ngEnu/kIEdcj20mkGJ2cxPd2Db6gfdTVSZxl/KRtGp8THnJCYE3UxkoGcB4G7L3X37uHjYHe/Jdc1\nSCVWvkErW8Pk1OFRVyJ13KT04axI78llBc+hnklrP50+Kv/x3rNs8UKmqllIqilFkvtSQ+mRWEq/\nxHtRlyM7oSCQQDoNiyYwPd1dt6SUGvF06ig+96Zcnnwu6lJkJxQEElj5Jqz/lElqFpIasoUiHiwb\nwneS79HdPoi6HNkBBYEEFj4LyXpMTeuWlFJzHk8NZI035McFE6IuRXZAQSBBs9DCCbD/cWoWkhq1\nkQY8mjqRE5Oz6WTFUZcjlVAQCCx/DdZ/AoecFnUlkoceLjuRjV6PHxfou4LaSkEgMP8pKGqsTuYk\nK9bQmHGp44Irjb9aGnU5UgEFQdyVfBM0C3U5GQrVLCTZ8UDZEMoogBl/iroUqYCCIO7enwwl66H7\nWVFXInlsFXswPnUMvPM4rP046nJkOwqCuJv/FOzeBjocGXUlkufuSw0FT8Pro6MuRbajIIizDauC\nO5F1PVN3IpOsK/aW0O0smPNI8N6TWkN//XG2YHxwg/puahaSHDnqZ1C2Gd74c9SVSDkKgrhyh9kP\nQ9s+0Kr94jkHAAAJk0lEQVRL1NVIXLToFJyY8NaDsGlN1NVISEEQVyteh9VL4NDvRV2JxM1R18CW\ndTDrgagrkZCCIK7mPAz1msDBuohMcqx1N+h0IrxxD2xeG3U1goIgnjauhoXPBaeMFu0WdTUSRwN+\nCZu+hpn3RF2JoCCIp3fGQapEzUISnb17Bt8VzLwHNn4ZdTWxpyCIm1QpvHkfdPgOtDo46mokzgbc\nAKXfwIw7oq4k9hQEcbPwOVhXDP1+EnUlEnctO0P3c4MvjXW1caQUBHHiHlzV2bxT8GWdSNT6/yK4\n2nj6rVFXEmsKgjhZ/hp8+g4ccbmuJJbaoWl7OPxH8PY4+Hhu1NXElv4bxIU7TB8FjfaC7mdHXY3I\nfxzzc2jYAv7xi+B9KjmnIIiLZa/Ain8FF/Oou2mpTeo3gYG/huJZMH981NXEkoIgDtxh2i1BL6O9\nLoy6GpFv63FecErpy7/SRWYRUBDEweJJwaeto66BwvpRVyPybYkEnPQH2PhFEAaSUwqCfFe6GV68\nHloepKMBqd3aHApHXBF0U710etTVxIqCIN/NHA1rVsDgUZAsjLoakR0bcD002w8m/AS2rI+6mthQ\nEOSz1R/Ca3+Eg4bCvv2jrkZk5wobwCl/hrXFMPFqnUWUIwqCfJVOwbM/Do4CBv8+6mpEMte+b3Bk\nsOBvQTORZJ2CIF+9PhpWvgFDbofd9466GpFdc+Q1sN+xwbUFutAs6xQE+WjZazD1ZjhoWHA/YpG6\nJpGA0x6ARq3g8bPg6xVRV5TXFAT55usVMP5CaL4/nHwPmEVdkUjVNGwB5/8dUltg3JnqrjqLFAT5\nZP3nMPb04PuBsx+H+rtHXZFI9bTsHLyX16yAR04K3uNS4xQE+WLDF/DoUFj3CZz7FLTYP+qKRGpG\nxyPhvL/Bmo/g4cHB2XBSoxQE+eCzd+GBgcEfynnjocMRUVckUrP2ORoueAY2r4EHBsAHU6KuKK8o\nCOoyd5j7GDx0AqRL4aLJwacnkXzUvi9cPC3oM2vs6TD5OijZGHVVeUFBUFd9sSj4Y5hwBezdAy7+\nJ7TpFXVVItm1R0f44VQ4/DKYdT+M7h18GEqnoq6sTlMQ1CXusOJ1+Pv34c9HwMpZMPg2GD4Rdm8d\ndXUiuVG0W9BlykUvBO/7CVfA3b3h9bvhm6+irq5OKohipWY2CLgTSAIPuvuoKOqoE7asD/7hfzgN\n/v0CrP4AihoH9xw+8mrYrVnUFYpEo8MRwdHBoufhjT/DSzfAlF9D+yOg8+CgKanVIVBQL+pKa72c\nB4GZJYF7gOOBYuAtM5vg7gtzXUvGtvZ34g7s4Pm2flF29tyhrARKNgRtnCUboWQ9fPM1rP8E1n0K\na1fC5+/C18uDWZNF0KFf8M//4FOhqGF2t1mkLjCDLsOCx2fvwrtPw/v/CHrcBUgUwp4HBU1Ke3SA\nJu2gQTNosAc0aBrcFCdZFIRFsug/zxMFsboGJ4ojgsOAD9x9KYCZPQmcDNR8ELxwPcx5OHhe1X/c\nUShqFHwh1roH9DwfWvcMPv3on79I5fY6JHgc92tYsxI+ngOfzIXP3wu+U/v3i8HFabvMwlDI4Gc2\nnD026G4ji6IIgjbAynKvi4HDt5/IzC4BLglfbjCz96uxzhZAHboscR3wCfBWtldUx/ZLTmnfVK7K\n+8Z+V8OV1D41/765cWB15u6QyUSRfEeQCXe/H7i/JpZlZrPdvXdNLCufaL9UTvumcto3laur+yaK\ns4Y+BtqVe902HCYiIhGIIgjeAjqZ2T5mVgScDUyIoA4RESGCpiF3LzOzK4AXCU4fHePu72V5tTXS\nxJSHtF8qp31TOe2bytXJfWOuW8GJiMSariwWEYk5BYGISMzlRRCYWTMze9nMloQ/96hkukFm9r6Z\nfWBmI8oNH2lmH5vZO+FjSO6qz47KtrXceDOzu8Lx882sV6bz1nXV3DfLzWxB+D6ZndvKsyuD/XKg\nmc00sy1mdu2uzFvXVXPf1P73jLvX+Qfwe2BE+HwE8LsKpkkCHwL7AkXAPKBLOG4kcG3U21GD+6PS\nbS03zRDgHwSXQ/YF3sx03rr8qM6+CcctB1pEvR0R7Zc9gT7ALeX/XvSeqXzf1JX3TF4cERB0UfFo\n+PxR4JQKptnWtYW7lwBbu7bIR5ls68nAXz3wBtDUzFpnOG9dVp19k892ul/c/Qt3fwso3dV567jq\n7Js6IV+CoJW7fxo+/wxoVcE0FXVt0abc65+EzQBjKmtaqkN2tq07miaTeeuy6uwbCDqgmmJmc8Ju\nUPJFdX7ves/sWK1/z9TaLia2Z2ZTgL0qGHVD+Rfu7ma2q+fE/gX4DcEv7DfAH4DvV6VOyXtHuvvH\nZrYn8LKZLXb3V6MuSmq1Wv+eqTNB4O7HVTbOzD43s9bu/ml4CP9FBZNV2rWFu39eblkPABNrpurI\nZNKNR2XTFGYwb11WnX2Du2/9+YWZPUPQbFCr/qirqDpdv+R7tzHV2r668J7Jl6ahCcDw8Plw4LkK\npqm0a4vt2n9PBd7NYq25kEk3HhOAC8MzZPoCa8PmtXzvAqTK+8bMGppZYwAzawicQN1/r2xVnd+7\n3jOVqDPvmai/ra6JB9AcmAosAaYAzcLhewOTy003BPg3wRkAN5Qb/hiwAJhP8AtuHfU21cA++da2\nApcCl4bPjeAGQR+G2957Z/spXx5V3TcEZ43MCx/v5du+yWC/7EXQPr4OWBM+313vmcr3TV15z6iL\nCRGRmMuXpiEREakiBYGISMwpCEREYk5BICIScwoCEZGYUxCIlGNmbmZjy70uMLNVZlbXLzIUqZSC\nQOS/bQQOMbMG4evjya+rZEW+RUEg8m2TgZPC5+cAT2wdEV4pOsbMZpnZ22Z2cji8o5m9ZmZzw0e/\ncHh/M5tuZn83s8VmNs7MLOdbJLIDCgKRb3sSONvM6gPdgDfLjbsBmObuhwEDgNvCrgO+AI53917A\nWcBd5ebpCfwU6EJwpel3sr8JIpmrM53OieSKu883s44ERwOTtxt9AjCs3F2o6gPtgU+Au82sB5AC\nDig3zyx3LwYws3eAjsCMbNUvsqsUBCIVmwDcDvQn6MtqKwNOd/f3y09sZiOBz4HuBEfam8uN3lLu\neQr93Ukto6YhkYqNAW5y9wXbDX+R4CZGBmBmPcPhTYBP3T0NXEBwe0OROkFBIFIBdy9297sqGPUb\ngns2zDez98LXAH8GhpvZPOBAgrOPROoE9T4qIhJzOiIQEYk5BYGISMwpCEREYk5BICIScwoCEZGY\nUxCIiMScgkBEJOb+H/MP8RDX50XfAAAAAElFTkSuQmCC\n",
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MgQMHRrhKqQ49BSMSV7oAPYOWLhVvLhLH+vfvT2ZmJsuXL2fQoEGHbq1UZPLkyUyYMIE+\nffrodkuM0xUQERGJGaU7iA4ePJh//OMf3HjjjVx22WXMmDHj0HavvfYaDRo0YN++fYdGQv300085\n5ZRTePXVVw/b94EDB5g0aVKZx/3Zz35GvXr1wv+GpFwKICIiEjNKD8UOcMMNN7B161buvvturr76\nak4++WTMjNtuuw3whlhPS0ujR48eTJw4kYyMDGrXrn3Yfvbu3cvQoUPLPG7fvn11GzPKFEBERCQm\nDBs2jGHDhpW57s477+TOO+889P3YsWOrtO8XXniBF154oVr1SXipD4iIiIhEnQKIiIiIRJ0CiIiI\niESdAoiIiIhEnQKIiIiIRJ0CiIiIiESdAoiIiIhEnQKIiIiIRJ0CiIiIiESdAoiIiIhEnQKIiIiI\nRJ0CiIiIxKU2bdpw4403+l2GhEiT0YmIJIDc3Fzy8vL8LoO0tLSQZ5V98cUXGT58OF988QU9e/Y8\nbH2/fv3YunUrS5YsASApKanM2XMrMmPGDObPn8+DDz4YUo0SPgogIiJxLjc3l06dulBYWOB3KaSk\npJKTkx1yCKkoUJRel5OTQ1JS1S7kT58+nfHjxyuAxAAFEBGROJeXlxcIH68AXXysJJvCwiHk5eWF\nHECqonbt2lV+jXMuApVUXkFBAampqb7WECvUB0REJGF0AXr6uEQ3/JTuA3LgwAHGjBlDx44dqVev\nHmlpafTt25fZs2cDMHz4cMaPHw94t2+SkpJITk4+9PqCggLuuusu0tPTSUlJoXPnzjz11FOHHbew\nsJBRo0Zx9NFH06hRIwYPHsz69etJSkpi7Nixh7Z76KGHSEpKIjs7m2uvvZamTZvSt29fAJYuXcrw\n4cM54YQTqFevHi1atOCmm25i69atJY51cB/Lly9nyJAhNGnShGOOOYYHHngAgO+++47BgwfTuHFj\nWrRowdNPPx2msxt5ugIiIiIxZceOHWzZsqVEm3OO/fv3l2grfUvmwQcf5LHHHuPmm2/mtNNOY+fO\nnXzxxRdkZWUxYMAAbrnlFtavX8+sWbOYNGnSYVdDLr30UubOncuIESM4+eSTmTlzJnfffTfr168v\nEUSGDRvGlClTGDp0KKeffjpz587lkksuOayeg99fddVVdOzYkUcfffTQMd9//31Wr17NjTfeyLHH\nHsvXX3/N888/zzfffMO8efMO28c111xD165defzxx3nnnXd4+OGHadq0Kc8//zwDBgzgiSeeYNKk\nSdx999307t2bs88+O5RTH13OuYRb8KK4W7hwoRNJBAsXLnSAg4UOXNDitetnvWY4+HNQ+u+7/J+P\naC/V+3mcOHGiM7MKl5NOOunQ9m3atHHDhw8/9H2PHj3cpZdeWuExfvWrX7mkpKTD2qdOnerMzD36\n6KMl2q+66iqXnJzsVq1a5ZxzLisry5mZu+uuu0psN3z4cJeUlOTGjBlzqO2hhx5yZuaGDBly2PEK\nCwsPa/v3v//tkpKS3CeffHLYPm699dZDbUVFRe744493ycnJ7sknnzzUvn37dpeamlrinJSlvJ+j\n0uuBni6Cv6t1C0ZERGKGmfHcc88xa9asw5bu3btX+NomTZrw9ddfs2LFiiofd8aMGdSqVYuRI0eW\naL/rrrsoLi5mxowZh7YzM2699dYS240cObLM/iVmxi9/+cvD2uvWrXvoz3v37mXLli2cfvrpOOfI\nyso6bB833XTToe+TkpI49dRTcc6VuAXVuHFjOnXqxKpVq6rwzv2jWzAiIhJTTjvttDIfwz3qqKMO\nuzUTbOzYsQwePJiOHTvSrVs3Bg0axPXXX89JJ510xGOuXbuW4447jvr165do79Kly6H14D1xlJSU\nRNu2bUts1759+3L3XXpbgG3btvHQQw/xn//8h82bNx9qNzN27Nhx2PalO/U2btyYlJQUmjZtelh7\n6X4ksUpXQEREJCH07duXlStX8sILL3DSSScxYcIEevbsyb/+9S9f66pXr95hbVdddRUTJkzgtttu\n44033uD9999n5syZOOcoLi4+bPvgzrIVtYH/T/pUlgKIiIgkjCZNmjBs2DAmTZrEd999R/fu3Xno\noYcOrS9vnJHWrVuzfv168vPzS7RnZ2cD3hM3B7crLi5m9erVJbZbvnx5pWvcvn07c+bM4d577+WB\nBx7g8ssvZ8CAAWVeKUlkCiAiIpIQSt96SE1NpX379uzdu/dQ28FbLDt37iyx7cUXX8yBAwd49tln\nS7SPGzeOpKQkBg0aBMDAgQNxzh16nPegv/zlL5UelfXglYvSVzrGjRtX5ZFd45n6gIiISMyozu2D\nrl270q9fP3r16kXTpk1ZsGABU6ZMYdSoUYe26dWrF845Ro4cycCBA0lOTuaaa67h0ksv5bzzzuO+\n++5j9erVhx7DnTZtGqNHjz50daJnz55cccUVPPPMM+Tl5XHGGWcwd+7cQ1dAKhMgGjZsyDnnnMMT\nTzzBvn37aNmyJe+99x5r1qyJm9sn4aAAIiKSMLLj/vhH+gUevN7MSnx/xx138NZbb/H++++zd+9e\nWrduzSOPPMKvf/3rQ9v87Gc/Y9SoUfz73/8+NBbINddcg5kxbdo0HnjgAf7zn/8wceJE2rRpw//9\n3/8xevToEjW8/PLLtGjRgszMTKZOncoFF1zAf/7zHzp27EhKSkql3mdmZiYjR45k/PjxOOcYOHAg\nM2bM4Ljjjqv0VZDytoubqyiRfMbXrwWNAyIJRuOAiHPlj9+wdu1al5KSenDsBl+XlJRUt3btWp/O\nkH8WLVrkzMxNnjzZ71KOKFbGAfH9CoiZ3Qv8FOgM7AE+A37jnPs2aJu6wNPANUBdYCZwm3Nu8+F7\nFBGpWdLT08nJyY772XDjRWFh4WFXOp555hmSk5M555xzfKoq/vgeQIC+wF+AL/DqeRR4z8y6OOf2\nBLZ5BrgIuALYCfwV+G/gtSIiNV56enrC/+KPFU888QQLFy7kvPPOo1atWkyfPp2ZM2fyy1/+kpYt\nW/pdXtzwPYA45y4O/t7MbgA2A72AT8ysEXAj8HPn3NzANsOBbDPr7ZybH+WSRUSkBuvTpw+zZs3i\nj3/8I7t37yY9PZ0xY8bwu9/9zu/S4orvAaQMTfDuPR18nqoXXp2zD27gnMsxs1zgTEABREREoub8\n88/n/PPP97uMuBdT44CY13X3GeAT59w3geZjgX3OuZ2lNt8UWCciIiJxJtaugIwHugJxMI+wSOzL\nzc0tt2NiTegsKCKxK2YCiJk9C1wM9HXOrQ9atRGoY2aNSl0FaR5YV67Ro0fTuHHjEm0ZGRlkZGSE\nqWqR2JWbm0unTl0oLCwoc31KSio5OdkKISI1WGZmJpmZmSXaypoMLxJiIoAEwsflwLnOudxSqxcC\nB4ABwBuB7TsB6cC8ivY7bty4MmdUFKkJ8vLyAuHjFaBLqbXZFBYOIS8vTwFEpAYr60N5VlYWvXr1\nivixfQ8gZjYeyAAuA/LNrHlg1Q7nXKFzbqeZTQCeNrNtwC7gz8CnegJGpDK64I3NJ4ni4ARpIqGI\nlZ8f3wMIcAveUy8flmofDrwU+PNooAiYgjcQ2bvA7VGqT0QkJqSlpZGamsqQIUP8LkXiXGpqKmlp\nab7W4HsAcc4d8Ukc59xeYGRgERGpkdLT08nOjo0RTyW+xUIndN8DiIiIVJ5GPJVEEVPjgIiIiEjN\noAAiIiIiUacAIiIiIlGnACIiIiJRpwAiIiIiUacAIiIiIlGnACIiIiJRpwAiIiIiUacAIiIiIlGn\nACIiIiJRpwAiIiIiUacAIiIiIlGnACIiIiJRpwAiIiIiUacAIiIiIlGnACIiIiJRpwAiIiIiUacA\nIiIiIlGnACIiIiJRpwAiIiIiUacAIiIiIlGnACIiIiJRpwAiIiIiUacAIiIiIlGnACIiIiJRpwAi\nIiIiUacAIiIiIlGnACIiIiJRpwAiIiIiUacAIiIiIlGnACIiIiJRpwAiIiIiUacAIiIiIlGnACIi\nIiJRpwAiIiIiUacAIiIiIlGnACIiIiJRpwAiIiIiUacAIiIiIlGnACIiIiJRpwAiIiIiUacAIiIi\nIlFXy+8CRCQx5ObmkpeXV+a6tLQ00tPTo1yRiMQyBRARqbbc3Fw6depCYWFBmetTUlLJyclWCBGR\nQxRARKTa8vLyAuHjFaBLqbXZFBYOIS8vTwFERA5RABGRMOoC9PS7CBGJA+qEKiIiIlGnACIiIiJR\npwAiIiIiUacAIiIiIlEXEwHEzPqa2Vtmts7Mis3sslLrXwi0By/T/apXREREqicmAghQH1gM3Aa4\ncraZATQHjg0sGdEpTURERMItJh7Ddc69C7wLYGZWzmZ7nXM/RK8qERERiZRYuQJSGf3MbJOZLTOz\n8WbW1O+CREREJDQxcQWkEmYA/wVWAycAjwLTzexM51x5t2xEREQkRsVFAHHOvRr07ddmthRYCfQD\nPvClKBGJOZoQTyR+xEUAKc05t9rM8oD2VBBARo8eTePGjUu0ZWRkkJGh/qsiiUYT4olUXWZmJpmZ\nmSXaduzYEZVjx2UAMbNWQDNgQ0XbjRs3jp49NS+FSE2gCfFEqq6sD+VZWVn06tUr4seOiQBiZvXx\nrmYcfAKmnZmdDGwNLA/i9QHZGNjuceBbYGb0qxWR2KYJ8UTiQUwEEOBUvFspLrA8FWh/EW9skO7A\nUKAJsB4veDzgnNsf/VJFRESkumIigDjn5lLxI8GDolWLiIiIRF48jQMiIiIiCUIBRERERKIupABi\nZu3CXYiIiIjUHKFeAVlhZh+Y2RAzSwlrRSIiIpLwQg0gPYElwNPARjN73sx6h68sERERSWQhBRDn\n3GLn3B3AccCNQAvgEzP7yszuNLOjw1mkiIiIJJZqPYbrnDsAvG5m7+CN1/Eo8H/AI2b2KvAb51yF\no5WKSM2QnZ19WFtNnJ+lvPlqauK5kJqtWgHEzE7FuwLycyAfL3xMAFrhjV76JqBbMyI12gYgiSFD\nhhy2pqbNz1LRfDU17VyIhBRAzOxOYDjQCZiON0rpdOdccWCT1WZ2A7AmDDWKSFzbDhRz+BwtNW9+\nlvLnq6l550Ik1CsgtwL/AiZWcItlM3BTiPsXkYSjOVp+pHMhEmoAuQDIDbriAYCZGXC8cy7XObcP\nby4XERERkRJCfQx3JZBWRntTYHXo5YiIiEhNEGoAsXLaGwCFIe5TREREaogq3YIxs6cDf3TAWDML\n7sqdDJwOLA5TbSIiIpKgqtoH5JTAVwNOAvYFrdsHfIn3KK6IiIhIuaoUQJxz5wGY2QvAHc65nRGp\nSkRERBJaSE/BOOeGh7sQERERqTkqHUDM7HXgBufczsCfy+Wc+1m1KxMREZGEVZUrIDvwOp8e/LOI\nJKDy5ioB2Lt3L3Xr1j2svax5XkREKlLpABJ820W3YEQSU0VzlXiSgaJoliQiCSrUuWDqAeacKwh8\n3xr4KfCNc+69MNYnIlFU/lwl4E379PsjrBMRqZxQh2J/E3gd+JuZNQHm4z2Gm2ZmdzrnngtXgSLi\nh7LmKsmuxDoRkcoJdSTUnsDHgT9fCWwEWuPNijsqDHWJiIhIAgs1gKQCuwJ/vhB4PTAx3f/wgoiI\niIhIuUINICuAwWZ2PDAQONjv4xhAg5OJiIhIhUINIGPxhlxfA3zunJsXaL8QWBSGukRERCSBhToS\n6hQz+wRogTf/y0GzgTfCUZiIiIgkrlCfgsE5txGv82lw2/xqVyQiIiIJL9RxQOoDvwUG4PX7KHEr\nxznXrvqliYiISKIK9QrIP4FzgZeBDfw4RLuIiIjIEYUaQC4CLnHOfRrOYkRERKRmCDWAbAO2hrMQ\nESl/IrhEnuytvPeWlpZGenp6lKsRkWgJNYD8HhhrZsMOzgcjItVz5IngEs0GIIkhQ4aUuTYlJZWc\nnGyFEJEEFWoAuQs4AdhkZmuA/cErnXOlJ4oQkSOo3ERwiWQ7UEzZ7zebwsIh5OXlKYCIJKhQA8jU\nsFYhIkFq2mRvZb1fEUl0oQ5ENibchYiIiEjNEepQ7JhZEzMbYWaPmlnTQFtPM2sZvvJEREQkEYU6\nEFl3YBawA2gD/APvqZifAenA0DDVJyIiIgko1CsgTwMTnXMdgMKg9unAOdWuSkRERBJaqAHkNOD5\nMtrXAceLFdlEAAAgAElEQVSGXo6IiIjUBKEGkL1AozLaOwI/hF6OiIiI1AShBpC3gAfMrHbge2dm\n6cDjwH/DUpmIiIgkrOoMRDYF72pHPWAu3q2XecB94SlNREKRV5DH9OXTmbZkGlwL1PkFHEiDXS1h\na3tY3wu+r+ddxxQR8Umo44DsAC4ws7OAk4EGQJZzblY4ixNJRJGa7+X7nd/z+w9+z+Slk9lXtI8T\nGp7gzVO9sznUSoWjv4bOb0C97VCcBJvg6a+f5rqG19G3dV8a1GlQreNHQnnnZO/evdStW7dS21ZX\neX9f0Zyrprwaol2HSDhVOYCYWRJwA94jt23w/otbDWw0M3POuXAWKJJIIjXfy7TvpvHku0/SoE4D\n/njeHxnWYxjf53xPr7t6AX/kx5FGHTRbDumToPVYZq2fxaTJk6iVVIszW51J15SucDywbr83Srpv\nKp4nBpKBoohXUdHfV7TmqjnSz4zmzJF4VaUAYmaG1//jYuBLYClgeGMpT8QLJYPDW6JI4gj/fC8O\nLoCHFj/EDT1u4JmBz9A4pTEA3/N9GdsbbOkIWy6HRWN55/53aNC6AbNXz2bWqllMXjkZbgL29oe1\n58GqAbDqfNjcrapvtZoqmifm4HkqvS788+WU//cVvblqKv6Z0Zw5Er+qegXkBrxxPgY45z4IXmFm\n/YGpZjbUOfdSmOoTSVDhmO/FwcBxcCbcdeJdPHnZk3ifESrPzOiU1olOaZ247bTbWLBwAb0v6w3t\nboR22XD+vVDrTth9DHzfynvQft3nsO4E2Nu4ivWGoqLzVHpdJOfLiYX5amKhBpHwqWoAyQAeKR0+\nAJxzc8zsMeA6QAFEJNJ6/xXOnATvwLWXXlvl8FGWZEuG9cD64fBJT6i1B47/DNp+AC3fhLOAlNuA\n2+CHzrCuN6w7HdZtgU1E466IiCSIqgaQ7sA9FayfAYwKvRwRqZT0T2DQ/4N518KCyZE7zoF6sHqA\nt9AFbAg0mwIt86Hl59ByPpyUCcn74QCw4QZYd54XSr7rA9vbRK42EYlrVQ0gTfE+55RnE3BU6OWI\nyBHV2Q2Dh8H3Z8D7dwARDCClOSCvLeT1hC8DUz7VKoRjH4eWD0HLVtBhOpzxZ2/dhlPgq47wNV63\nDhGRgKoGkGS8zznlKQphnyJSFQN+Bw02wiszoXin39XAgRT4vj1en9fAEzf1tni3bU58Ffq9ARcA\nK34FC34L314CLtnfmkXEd1UNCwZMNLPyhjCqW057xTs16wvcDfQCWgCDnXNvldpmLDACaAJ8Ctzq\nnFsRyvFE4tYxK+C0v8L7T3iDipHld0Vl29MMvrnSW+pMgK4j4NSdkHE5bE+HT++BRakVf5wRkYRW\n1QDyYiW2CaUDan1gMTABeL30SjP7DfArYCiwBu9j1kwz6+Kc2xfC8UTi08CnYVs7mD/S70oqb1+K\n96978UvQwsGZT8NFo+CchvAZsLAA9K9YpMapUgBxzg2PRBHOuXeBd+HQWCOl3QH8wTn3dmCboXj9\nTQYDr0aiJpGY0x444XPIfBOK6vhdTWg29ILXJ8GHY+DsEXD+XDjrcpg7FhbeDMW1j7wPEUkIoU5G\nFzVm1hZvnpnZB9ucczuBz4Ez/apLJLocnAvkngw5l/pdTPVtbQ9v/QL+DCw/Cy4eCbd3ha6v4fV0\nFZFEF/MBBC98OA5/+mZTYJ1I4mv7jTdE+kc34XXFShA7gDcfgue+9EZovfpqGHEGtF7md2UiEmF6\nYkUkHpzzpjdA2Io+Za4uayK2SE3OFhGbT4LJ70CbD+GCe2D4H+Eb4P3vYFvkR/8M9wSBkZpwUCSR\nxEMA2Yj3ka85Ja+CNAcWVfTC0aNH07hxyeGiMzIyyMjICHeNIpHTIsu7AvIqHH7140iTtsWZNf3g\nn/+DbiPh/PFw+1Xw+R3w0f0RG/o93BMERmrCQZFIyMzMJDMzs0Tbjh07onLsmA8gzrnVZrYRGAAs\nATCzRsDpwF8reu24cePo2VNzJ0icO2087GgGy7aUsbIyk7bFGZcES/vAsvFw5k1w9njo8SJ8MBay\nRoR9lt5wTxAY/gkHRSKnrA/lWVlZ9OrVK+LHjokAYmb18fr4H/x4187MTga2Oue+A54B7jezFXiP\n4f4Bb9ijN30oVyR6UrbBSZPho59A8WsVbBiOye1izH7go1/AovthwH3wk1uh97Mw8yewMhIHDPc5\nTMC/E5EwipVOqKfi3U5ZiNfh9Cm8EZbGADjnngD+AjyP9/RLPeAijQEiCa/HREg6AFn9/K7EP7ta\nwtSJ8PcFsOcouP5xuBZIW+13ZSJSDTERQJxzc51zSc655FLLjUHbPOScO845l+qcG6hRUCXxOej1\nd/jmCsiPTP+HuLL+VHjhI3h1FBwN3HoNDLoD6m31uzIRCUFMBBARKcNxX8DRy2BxRMb/i1MG3/T2\nen/NuQ1OeQFGtYfT/+xdKRKRuKEAIhKrTn4ZdrWAVQP8riT2HAA+vQH+vNybb2bgaLjtXugIGshM\nJD4ogIjEouR90C0TllynmWMrkt8cpv0dnl8EO5t6fUOuvx2O+crvykTkCBRARGJR+3ehfh58OdTv\nSuLDpu7w0m8hE2iyAW7p4U14l7LN78pEpBwKICKxqPvLsPFkb4RQqSSDHGD8qzDrUejxAozq4HXk\ntSK/ixORUhRARGJN7T3Q8R1Yeq3flcSnotrw2d3wl2/h25/Apb+Em6/35tIRkZgREwORiUiQDp96\nIeSbKyJ+qNJzkyTUXCW7W3jjh3xxC1x0E9wE92Xdxz/b/5OWjVqG5RDhnoMn7uf0EakCBRCRWNNl\njnf7ZdsJETxIgs0hU5Hvz4B/vgg9TuPzqz6n07OduK/vfdx55p3UrVU3xJ2G+/zVoL8PkQDdghGJ\nJbWAjh9H4epH8BwyC4OWP0T4uD5xSbAI3uj/Bjf3upkHPnyAE8efyLScaTgXymO75Z2/UM9huPcn\nEvt0BUQklrQD6hZAduRvv3hKz1eS2Jf7G9ZuyNMDn2ZEzxH8v3f/H5f9+zL6HN0HmgFlzfV3RJo/\nRiRUugIiEku6Aj+0hR+6+l1JQut6dFdmDpnJ1GumsjZ/LdwGXPAM1N3pd2kiNYYCiEissGJvJM9l\n/fyupEYwMy7vfDmv9XsNPgROew1GdoQzximIiESBAohIrGi1AlKBb/v6XUmNUje5LnwMPPtfWDEI\nLrgH7mwFF94Faev9Lk8kYakPiEis6PAlFADfd/O7kppp57HeY7uzH4bef4VT/wZ9tnkPqCx9CVbW\ngs3dvA6tIlJtCiAisaLDYliB5n7x266WMPsRmPsAtP8tdP8TnPc3uPBPkH805J4Fmww2A1uXwc7j\noSANML8rF4krCiAisaDhOmixFj71uxA55EAKLDsNlgG1PoDj90Db2dByPpy6ABoAXBfYti7sbOUt\nOw7ATmDnq7BjPWzsATtbooAiUpICiEgs6DAdig1Wair5mHSgLqw+E1b3DzRMgvpDoPFL0KgBNPoe\nGn/nfW2SBelAo6cg+XFv813HwuoBkJ0Gy4EDPr0PkRiiACISCzq+A993gD3f+l2JVFY+kH8irC89\nbsckYAjYPGh4LLRYCK3+5/0dd1/qve6L52Dek1DYJPp1i8QIBRARvyXvhXaz4KNLAAWQSIrqXCsu\n6cfbMjmXw+xHodmT0PseOPMVOPVNeP9xWHxDtQ9V3ntIS0sjPT292vsXiQQFEBG/tf4I6uTD8h7A\nq35Xk6BiZK6VLcfBDOCTqXDByzD4Ru/KyFsXQmEoO6z4faWkpJKTk60QIjFJAUTEb+3f9TopbtJ8\n8ZETPNdKl1LrpgO/j245u46G11+B7J/C5TfBTfPgZbzOq1VS0fvKprBwCHl5eQogEpMUQET81nYO\nrBqAnpKIhhibayX7Cm9skevPhpuAF7+DraXrq4yy3pdIbNOIOiJ+Ss2DFou9JySkZtrSCSY8APuB\nIbdDg41+VyQSFQogIn5q86H39dDjnVIj7Wrq3YKptQ+uuxhqF/hdkUjEKYCI+KntbMjr6D0pITXb\nDmDSnyFtGVxyG6AxYSSxKYCI+KntHF39kB9t6gjTnoceL0LPCX5XIxJRCiAifmn0PaR9q/4fUtKS\n62HhCBj0/6DJar+rEYkYBRARv7Sd431d08/XMiQGzXzam+Du8pvAiv2uRiQiFEBE/NJ2DmzoEZhJ\nVSTIvobw5gRo+wGcMtfvakQiQgFExBfO64Cq/h9SntUD4MshMOA1qOt3MSLhpwAi4oem30Hj7xVA\npGKzHoPae+FcvwsRCT8FEBE/tJsPxcmw9hy/K5FYtqslfHwZnA40W+N3NSJhpQAi4oe2C2Bdb+9e\nv0hF5l0Eu4Dz/uZ3JSJhpQAiEm2GF0BW6fFbqYQDdeAjoNv7cMxSv6sRCRsFEJFoOwZI3aH+H1J5\ni4FtLeG8B/2uRCRsFEBEoq0tsL8ufH+m35VIvCgG5o6ALm9Aiyy/qxEJCwUQkWhrB3x3MhxI8bsS\niSdLLoat7eCsJ/yuRCQsFEBEomh/8X5oDaw+ze9SJN4U14J5d0LX1zREuyQEBRCRKMrenu0NKrVK\nAURCsHg4FB4FZ47zuxKRalMAEYmiBXkLoBDY0MXvUiQe7U+F+bfDKROg3la/qxGpFgUQkSianzcf\n1uJdThcJxYLbvQnqTn3O70pEqkUBRCRK9uzfw5JtS0C376U68o+BL4fCaeMh6YDf1YiETAFEJErm\nfT+PfcX7YJXflUjcW3AbNFoPnRb5XYlIyBRARKJk9qrZHFXnKPjB70ok7m06GXL7wGmz/K5EJGQK\nICJRMmfNHE5LOw2c35VIQlhwG7T7Gpr5XYhIaBRARKJg596dLFi3wAsgIuHwzZWQ3xBO9bsQkdAo\ngIhEwUdrP6LIFSmASPgU1YVF50IPoPYev6sRqTIFEJEomL1qNumN02mV2srvUiSRfNEfUoAT3/e7\nEpEqUwARiYI5a+bQv21/zMzvUiSRbD/Ge6rqlDf9rkSkyhRARCJsc/5mlmxawoC2A/wuRRLRIqD1\nYmi63O9KRKpEAUQkwj5c8yEA/dv297cQSUzLgD0NocdEvysRqZK4CCBm9qCZFZdavvG7LpHKmLN6\nDp3TOnNcw+P8LkUS0QHgq4HQ40WwIr+rEam0uAggAV8BzYFjA8vZ/pYjUjmzV8+mfxtd/ZAIWnQZ\nNFoHJ6gzqsSPeAogB5xzPzjnNgcWTQUpMS93Ry4rtq7Q7ReJrPVdYfOJ0OMFvysRqbR4CiAdzGyd\nma00s1fM7Hi/CxI5ktmrZmMY/dr087sUSWgGi26EzlOhnj6bSXyIlwDyP+AGYCBwC9AW+MjM6vtZ\nlEh5li9fTlZWFq8tfI3OjTuzdtlasrKyyM7O9rs0SVRLhoAVw0mT/a5EpFJq+V1AZTjnZgZ9+5WZ\nzQfWAlcDuuYoMeXzzz+nT5+zKC4ugl8Di6HX6F5+lyWJLv8YWH6Jdxtm/q/8rkbkiOIigJTmnNth\nZt8C7SvabvTo0TRu3LhEW0ZGBhkZGZEsT2q4devWeeHjmAnQ4CZYNR44PbD2LuBD/4qTxLb4Bvj5\nT+GYpbDZ72IkHmRmZpKZmVmibceOHVE5dlwGEDNrAJwAvFTRduPGjaNnz57RKUqktHYb4UBdyL0B\nqBdobOJjQZLwll8MBc28R3Lfu9bvaiQOlPWhPCsri169In/VNi76gJjZk2Z2jpm1NrM+wBt4T79n\nHuGlIv5p+xHkngUH6h15W5FwKKoDS66D7q9A0gG/qxGpUFwEEKAVMBlvzL9/Az8AZzjntvhalUh5\nkoA2n8Cq8/2uRGqaL4dBg01wwv/8rkSkQnFxC8Y5p04bEl9aAnXzFUAk+jacApu6QY9poOlhJIbF\nyxUQkfjSDtjTGDaoD5JEm3mdUTvNhRS/axEpnwKISCS0A9acDS7Z70qkJlp6HSQVQze/CxEpnwKI\nSJjtKdrj9Vpada7fpUhNtftYWHEG9PC7EJHyKYCIhNk3+d9AMgog4q/Fl0IrWLN7jd+ViJRJAUQk\nzJbsXgI7gC0n+F2K1GTfngN74O3v3va7EpEyxcVTMCLxJGt3FqwAML9LkZrsQF34Ct456h2KiotI\nTlJ/JIktCiAiYbR622rW710fCCAiPlsMm0/bzPPvP88ZR59xqDktLY309HQfCxNRABEJqxkrZpBM\nMkWrivwuRWq8DbDOIM9x+99vh9d/XJOSkkpOTrZCiPhKfUBEwmjGihl0rt8Z9vpdich2wMHiq6FL\nXag7F1gIvEJhYQF5eXk+1yc1nQKISJgUHihkzuo5nNLwFL9LEfnRkhug1j7ouhzoCXTxuSARjwKI\nSJh8tPYjCvYXcEoDBRCJITube1MC9JjodyUiJSiAiITJjOUzaNmwJa1TWvtdikhJi4dB60/gqJV+\nVyJyiAKISJjMWDGDi9pfhJkev5UYs+ynsLchnPyS35WIHKIAIhIGq7etJmdLDhd1uMjvUkQOtz8V\nvr4aerwIVux3NSKAAohIWLyV8xZ1kutwfrvz/S5FpGyLh0GTtdA6y+9KRAAFEJGweGPZGwxoO4BG\ndRv5XYpI2XLPhq3t4GQNzS6xQQFEpJryCvL4OPdjBnce7HcpIhUw+HIYnDgL6vhdi4gCiEi1TcuZ\nhnOOyztd7ncpIhX7cijU2aOhQCQmKICIVNPUnKn0Ob4PzRs097sUkYptbwOre8HJfhciogAiUi35\n+/J5b+V7uv0i8ePLn0A72FCwwe9KpIZTABGphndXvEvhgUIFEIkf3wyAffDO9+/4XYnUcAogItXw\n+rLX6XZMN9o3be93KSKVs68+fANvffcWxU5jgoh/FEBEQpS/L583l73Jz0/8ud+liFTNQlhXsI6Z\nK2b6XYnUYAogIiGa9u008vfn8/NuCiASZ76DTo068dcFf/W7EqnBFEBEQpT5VSa9W/bmhKYn+F2K\nSJVd0/Yapi+fzsqtmqBO/KEAIhKCbXu2MWP5DK7tdq3fpYiEZGDLgRxV7yie++I5v0uRGkoBRCQE\n/83+L0WuiKtPvNrvUkRCkpKcwk2n3MSERRMo2F/gdzlSAymAiITgpS9f4rw259GiYQu/SxEJ2a2n\n3sqOwh1MWjLJ71KkBlIAEaminLwcPs79mBE9R/hdiki1tD2qLZd3vpyn5j2lR3Il6hRARKpowqIJ\nNK3XVIOPSUL4zVm/IWdLDm8ue9PvUqSGUQARqYJ9Rft48csXub779aTUSvG7HJFqO6PVGZzb+lwe\n+/QxnHN+lyM1iAKISBVMy5nG5vzNuv0iCeU3Z/2G+evmM3ftXL9LkRpEAUSkCp774jnOaHUG3Y7p\n5ncpImEzqP0gujfvzmOfPOZ3KVKDKICIVNKSTUuYvXo2o3qP8rsUkbAyM+7rex8zV87k09xP/S5H\naggFEJFKeuZ/z9CqUSuu7Hql36WIhN2VXa/k5OYn87s5v1NfEIkKBRCRSti0exOTlk5iZO+R1E6u\n7Xc5ImGXZEk83P9hPlr7Ee+tfM/vcqQGUAARqYRx/xtHneQ6/KLnL/wuRSRiLu5wMWcdf5augkhU\nKICIHMEP+T/w7PxnGdV7FEfVO8rvckQixsx4ZMAjZG3IIvOrTL/LkQSnACJyBE/Newoz484z7/S7\nFJGIO6f1OVzR5Qp+/d6v2bl3p9/lSAJTABGpwIZdG3h2/rOM7D2SZqnN/C5HJCqeHvg0O/buYOzc\nsX6XIglMAUSkAvfNuY+UWinc3eduv0sRiZr0xunc3/d+/vT5n1i6aanf5UiCUgARKcfC9QuZuHgi\nfzjvD+r7ITXOnWfeSadmnRg6dSj7ivb5XY4kIAUQkTIUFRdx+/Tb6Xp0V37RS0++SM1Tt1ZdXv7p\ny3y1+Sv+MPcPfpcjCUgBRKQMz/zvGeavm8/fL/07tZJq+V2OiC9OaXEKD5zzAI988gif5H7idzmS\nYBRARErJycvh/g/u547T76DP8X38LkfEV/f2vZezjj+Lq167ivW71vtdjiQQBRCRIPn78rnytStp\n3bg1Dw942O9yRHxXK6kWr131GsmWzBWvXsHeA3v9LkkShAKISIBzjlveuYVV21bx36v/S2rtVL9L\nEokJzRs05/VrXmfRhkVc9/p1HCg+4HdJkgAUQEQCHvzwQV5Z8gr/vPSfnHjMiX6XIxJTerfszatX\nvcrUZVMZ8dYIil2x3yVJnFMAEcHrdPqHj/7AYwMeI+OkDL/LEYlJl3W6jJd/+jIvffkSQ14fotsx\nUi3q3i81mnOOMXPHMGbuGO7pcw/3nHWP3yWJxLSMkzKonVybIa8PYcPuDUy5aopGCZaQ6AqI1Fi7\n9u5iyBtDGDN3DI8OeJTHzn8MM/O7LJGYd2XXK5k1dBZLNi3h5L+dzAerP/C7JIlDcRVAzOx2M1tt\nZnvM7H9mdprfNSWazMyaMQPm3DVzOfUfp/JWzltkXpHJb8/+bcjho6acs/D7zO8C4lDs/KydnX42\nX97yJR2adWDASwO49e1bySvI87usMunfaGyKmwBiZtcATwEPAqcAXwIzzSzN18ISTKL/Q/1689dk\n/DeDfi/2o1m9Ziy8eSE/7/bzau0z0c9Z5Mzzu4A4FFs/a60atWLW9bMYN3AcmV9l0uEvHRjz4ZiY\nCyL6Nxqb4iaAAKOB551zLznnlgG3AAXAjf6WJbGu8EAhU76Zwk8m/4Ruz3Xjs+8+Y8JlE/jkxk/o\n2Kyj3+WJxLXkpGTuOOMOlo9cztDuQ3n808dJH5fOda9fx9vfvq15ZKRccdEJ1cxqA72ARw62Oeec\nmc0CzvStMIlJm3ZvYunmpSzasIg5a+bw0dqPKNhfQO+WvZlw2QSGdB9CneQ6fpcpklCOrn80f7ro\nTzxw7gP8feHfmbR0EpOXTia1dip9ju/Dua3PpVeLXnQ5ugvpjdNJsnj6/CuREBcBBEgDkoFNpdo3\nAZ2iX05i2bV3F8u3Lsc5x/bC7Xyx/gucczgcQNT+7Fzg+3L+XOSKKNhfQP6+fPL357N7327y9+Xz\nQ8EPrN+1ng27N/Ddju/YsmcLAKm1U+mb3pcx/cZwacdL6ZQW7R+VL4HGpdq2R7kGkehqltqMe/ve\ny71972XppqW8u+JdPlz7IU9+9iQ79+4EvH+bxzc6nhYNW9CiQQua129Ow7oNaVCnAQ3qNKB+7frU\nr1OfWkm1qJVUi2RL9r4mJZf4s1F2v63S/bm2F25nwboFldoWqPR+D6qTXIdux3Qr95xI2eIlgFRV\nCkB2drbfdcSFBesWcMvbt3jf5MBpY2K/b29KrRTq1a5HvVr1aJLShKPrH0371Pac2fRM2h3VjvZH\ntadlo5YkJyUDkJ+bT1ZuVkRq2bFjB1lZP+57165dmCXhXP8KXjUdKP3z+WkI60J5TTT3V9G6rXFc\nu1/7+x6YVM1jrQai9//jgHoDGNB5AMWditm4eyOrt61m9fbVbNq9ibzNeeSszmFe4Tz27N9Dwf4C\nCvYXUFRcFN4icqD32N7h3WeQ4xoex7Rrp0Vs/9EW9LOREsnj2MFPl7EscAumALjCOfdWUPtEoLFz\n7qeltr+Wkv9KRUREpGquc85NjtTO4+IKiHNuv5ktBAYAbwGYdy1sAPDnMl4yE7gOWAMURqlMERGR\nRJACtMH7XRoxcXEFBMDMrgYm4j39Mh/vqZgrgc7OuR98LE1ERESqKC6ugAA4514NjPkxFmgOLAYG\nKnyIiIjEn7i5AiIiIiKJQw9ii4iISNQpgIiIiEjUxWUAMbOjzGySme0ws21m9k8zq3+E1/zCzD4I\nvKbYzBqFY7/xJMTzVtfM/mpmeWa2y8ymmNkxpbYpLrUUBToNx6WqTnpoZleZWXZg+y/N7KIythlr\nZuvNrMDM3jez9pF7B9EX7nNmZi+U8XM1PbLvIvqqct7MrGvg39/qwPkYVd19xqNwnzMze7CMn7Vv\nIvsuoq+K522EmX1kZlsDy/tlbV/d/9fiMoAAk4EueI/hXgKcAzx/hNfUA2YADwPldXwJZb/xJJT3\n90xg2ysC2x8H/LeM7YbhdQ4+FmgBTA1PydFV1UkPzawP3nn9B9ADeBOYamZdg7b5DfAr4GagN5Af\n2GdCjAcfiXMWMIMff6aOBTIi8gZ8UtXzBqQCK4HfABvCtM+4EolzFvAVJX/Wzg5XzbEghPN2Lt6/\n0X7AGcB3wHtm1iJon9X/f805F1cL0BkoBk4JahsIHACOrcTrzwWKgEbh3G+sL6G8P6ARsBf4aVBb\np8B+ege1FQOX+f0ew3Se/gf8Keh7wxt+8p5ytv838FaptnnA+KDv1wOjS53XPcDVfr/fGD5nLwCv\n+/3eYum8lXrtamBUOPcZD0uEztmDQJbf7y1Wz1tg+yRgBzAkqK3a/6/F4xWQM4FtzrlFQW2z8K5q\nnB6D+40Voby/XniPas8+2OCcywFyOXwSwL+a2Q9m9rmZDQ9f2dFjP056GPx+Hd55Km/SwzMD64PN\nPLi9mbXD+0QVvM+dwOcV7DNuROKcBelnZpvMbJmZjTezpmEq23chnreo7zOWRPj9dTCzdWa20sxe\nMbPjq7m/mBGm81YfqE1g/gQza0sY/l+LxwByLLA5uME5V4R3Yo6Nwf3GilDe37HAvsAPVrBNpV7z\ne+Bq4HxgCjDezH4VjqKjrKJJDys6RxVt3xwv5FVln/EkEucMvNsvQ4H+wD14Vy6nm5UzG1j8CeW8\n+bHPWBKp9/c/4Aa8K8K3AG2Bjyxx+v+F47w9Dqzjxw8OxxKG/9diZiAyM3sU7z5deRxe/wUJEgvn\nzTn3cNC3X5pZA+Bu4NlIHlcSl3Pu1aBvvzazpXj38vsBH/hSlCQk51zwcONfmdl8YC3eh6oX/Kkq\ndpjZb/HOxbnOuX3h3HfMBBDg/zjyX/YqYCNQ+imMZKBpYF2oIrXfSIvkedsI1DGzRqWugjSv4DXg\nXYa738xqO+f2H6G2WJKH1z+oean2it7vxiNsvxHvfmtzSn5aaA4sIv5F4pwdxv3/9u4t1IoqDOD4\n/ybN+o8AAAUqSURBVLNUtChDSohSSimzIoUM0i6GVBT1kIZYaJRJlEHQBbtR2UNCGfjgJaTSyMii\nh14qJMGXNBNMIdBMQQvBILxkihV1XD2sOTJn4zHdxz1ztv5/MJy915q99qyPvWd/M7PWmZR2RsQe\nYASnRwLSTNzqaLM3qaR/KaUDEbGN/Fk7HTQdt4h4jnwGcmJKaXOp6pTs13rNJZiU0t6U0rb/Wf4l\nD1YbFBFjSi+fSA7G+h5sQqvabakWx+178iDViZ0FEXElMLRorztjyONN2in5oNjezpseAl1uevht\nNy9bV16/cHtRTkppJ/nLWm7zPPK4m+7abButiNmxRMQlwGCOP5OhbTQZt8rb7E2q6l9xBnc4Z/hn\nLSJmAy+Tb3nSJak4Zfu1ukfnNrMAXwEbgLHAeOAnYHmp/mLgR+D6UtkQ4DpgJnnWxk3F8wtOtN12\nX5qM22Ly6PEJ5IFMa4FvSvX3AI8CV5O/tE8Ah4BX6+5vkzGaAhwmjz8YSZ6mvBe4sKj/EJhbWv9G\n8kyhZ8gzhOaQ78A8qrTO7KKNe4FryVOUtwP96u5vb4wZecDbW+Sd2TDyTm5D8dnsW3d/a4xb32Kf\nNZp8Pf7N4vnwE22z3ZcWxWwe+V8MDAPGAavIR/WD6+5vjXF7vvhO3kf+7exczimt0+P9Wu2BaTKY\ng4CPyNOC9pP/n8DAUv0w8imnW0plr5ETj46G5aETbbfdlybj1h9YQD6NdxD4DLioVH8nsLFo84/i\n8cy6+9rDOM0CfiZPKVtH14RsNbC0Yf3JwNZi/R/IRwyNbc4hT1s7TJ7xMaLufvbWmJFvBb6SfIT1\nF/kS4jucJj+izcat+H4eax+2+kTbPB2WUx0zYAV5Suqf5Bl+HwOX1d3PmuO28xgx66DhwLKn+zVv\nRidJkirXa8aASJKkM4cJiCRJqpwJiCRJqpwJiCRJqpwJiCRJqpwJiCRJqpwJiCRJqpwJiCRJqpwJ\niCRJqpwJiKSTEhEfRMSRiFh8jLpFRd3SOrZNUvswAZF0shL5nhlTI6J/Z2Hx+AHgl7o2TFL7MAGR\n1IxNwC5gUqlsEjn5OHrr7shejIgdEXE4IjZFxORSfZ+IeK9UvzUiniq/UUQsi4jPI+LZiNgdEXsi\nYmFEnNXiPkpqIRMQSc1IwFJgRqlsBrAMiFLZS8A04DFgFDAfWB4RNxf1fciJzGTgKuB14I2IuL/h\n/W4DLgcmkG8p/nCxSGpT3g1X0kmJiGXA+eSkYhdwBTmR2AJcCrwP7AceB/YBE1NK60uvfxcYkFKa\n1k37C4AhKaUppfe7FRieih1WRHwKdKSUHmxJJyW13Nl1b4Ck9pRS2hMRXwCPkM96fJlS2hdx9ATI\nCGAgsCpKhUBful6mebJoYygwAOhXri9sTl2Pln4FrjmF3ZFUMRMQST2xDFhIviQzq6Hu3OLv3cDu\nhrq/ASJiKjAPeBr4DjgIzAZuaFj/n4bnCS8hS23NBERST6wkn7HoAL5uqNtCTjSGpZTWdPP6ccDa\nlNKSzoKIGN6KDZXUu5iASGpaSulIRIwsHqeGukMR8TYwv5ixsoY8dmQ8cCCltBzYDkyPiDuAncB0\nYCywo8JuSKqBCYikHkkpHTpO3SsR8RvwAnkWy+/ARmBuscoSYDTwCfmyygpgEXBXK7dZUv2cBSNJ\nkirnIC5JklQ5ExBJklQ5ExBJklQ5ExBJklQ5ExBJklQ5ExBJklQ5ExBJklQ5ExBJklQ5ExBJklQ5\nExBJklQ5ExBJklQ5ExBJklS5/wD6ovxjH+G+1wAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f7bec611a20>"
+       "<matplotlib.figure.Figure at 0x7f7d7dd0a588>"
       ]
      },
      "metadata": {},
@@ -2128,7 +2129,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
diff --git a/examples/jupyter/pincell.ipynb b/examples/jupyter/pincell.ipynb
index aa9c54916..fcb0b412d 100644
--- a/examples/jupyter/pincell.ipynb
+++ b/examples/jupyter/pincell.ipynb
@@ -464,7 +464,7 @@
       "    <library materials=\"c_O_in_UO2\" path=\"c_O_in_UO2.h5\" type=\"thermal\" />\n",
       "    <library materials=\"c_para_D\" path=\"c_para_D.h5\" type=\"thermal\" />\n",
       "    <library materials=\"c_para_H\" path=\"c_para_H.h5\" type=\"thermal\" />\n",
-      "    <library materials=\"c_H_in_CH4_solid\" path=\"c_H_in_CH4_solid.h5\" type=\"thermal\" />\n",
+      "    <library materials=\"c_solid_CH4\" path=\"c_solid_CH4.h5\" type=\"thermal\" />\n",
       "    <library materials=\"c_U_in_UO2\" path=\"c_U_in_UO2.h5\" type=\"thermal\" />\n",
       "    <library materials=\"c_Zr_in_ZrH\" path=\"c_Zr_in_ZrH.h5\" type=\"thermal\" />\n",
       "</cross_sections>\n"
@@ -712,9 +712,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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+      "image/png": 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6rPAlKRMG/oi0sRqQctXW89mWzgjZ3pHGW1uDvssKX5IyYeCXoO1VgtRGOZy3Br4kZcLA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\nDHxJyoSBL0mZMPAlKRMGviRl4v8B4nacd2UOkqgAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f565d783550>"
+       "<matplotlib.figure.Figure at 0x7f64b1870a58>"
       ]
      },
      "metadata": {},
@@ -741,9 +741,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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MfElKwsCXpCQMfElKwsCXpCQMfElKwsCXpCQMfElKwsCXpCQMfElKwsCXpCQMfElKwsCX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\nlISBL0lJGPiSlMT/AffuC/0D2imKAAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f565d783908>"
+       "<matplotlib.figure.Figure at 0x7f64b162bcc0>"
       ]
      },
      "metadata": {},
@@ -770,9 +770,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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8SUrCwJekJAx8SUrCwJekJAx8SUrCwJekJAz8xKanp/vdhaHjmHXGcRsMjQV+RLwrIv4t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\nBr4kJWHgS1ISBr4kJWHgS1IS/wcG/y3HN4AdAQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f568f8f7588>"
+       "<matplotlib.figure.Figure at 0x7f64aed14198>"
       ]
      },
      "metadata": {},
@@ -1094,7 +1094,7 @@
    },
    "outputs": [],
    "source": [
-    "cell_filter = openmc.CellFilter(fuel.id)\n",
+    "cell_filter = openmc.CellFilter(fuel)\n",
     "\n",
     "t = openmc.Tally(1)\n",
     "t.filters = [cell_filter]"
@@ -1104,8 +1104,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "One oddity to point out -- we have to give the ID of the fuel cell, not the `Cell` object itself (this may change in the future).\n",
-    "\n",
     "The *what* is the total, fission, absorption, and (n,$\\gamma$) reaction rates in $^{235}$U. By default, if we only specify what reactions, it will gives us tallies over all nuclides. We can use the `nuclides` attribute to name specific nuclides we're interested in."
    ]
   },
@@ -1206,24 +1204,26 @@
       "         Copyright | 2011-2017 Massachusetts Institute of Technology\n",
       "           License | http://openmc.readthedocs.io/en/latest/license.html\n",
       "           Version | 0.8.0\n",
-      "          Git SHA1 | f7edad68f0654d775ed363bfdcbe4aa5d3cfba23\n",
-      "         Date/Time | 2017-04-03 14:32:56\n",
+      "          Git SHA1 | bc4683be1c853fe6d0e31bccad416ef219e3efaf\n",
+      "         Date/Time | 2017-04-13 17:17:32\n",
+      "     MPI Processes | 1\n",
+      "    OpenMP Threads | 4\n",
       "\n",
       " Reading settings XML file...\n",
       " Reading geometry XML file...\n",
       " Reading materials XML file...\n",
       " Reading cross sections XML file...\n",
-      " Reading U235 from /home/romano/openmc/scripts/nndc_hdf5/U235.h5\n",
-      " Reading U238 from /home/romano/openmc/scripts/nndc_hdf5/U238.h5\n",
-      " Reading O16 from /home/romano/openmc/scripts/nndc_hdf5/O16.h5\n",
-      " Reading Zr90 from /home/romano/openmc/scripts/nndc_hdf5/Zr90.h5\n",
-      " Reading Zr91 from /home/romano/openmc/scripts/nndc_hdf5/Zr91.h5\n",
-      " Reading Zr92 from /home/romano/openmc/scripts/nndc_hdf5/Zr92.h5\n",
-      " Reading Zr94 from /home/romano/openmc/scripts/nndc_hdf5/Zr94.h5\n",
-      " Reading Zr96 from /home/romano/openmc/scripts/nndc_hdf5/Zr96.h5\n",
-      " Reading H1 from /home/romano/openmc/scripts/nndc_hdf5/H1.h5\n",
-      " Reading O17 from /home/romano/openmc/scripts/nndc_hdf5/O17.h5\n",
-      " Reading c_H_in_H2O from /home/romano/openmc/scripts/nndc_hdf5/c_H_in_H2O.h5\n",
+      " Reading U235 from /home/smharper/openmc/data/nndc_hdf5/U235.h5\n",
+      " Reading U238 from /home/smharper/openmc/data/nndc_hdf5/U238.h5\n",
+      " Reading O16 from /home/smharper/openmc/data/nndc_hdf5/O16.h5\n",
+      " Reading Zr90 from /home/smharper/openmc/data/nndc_hdf5/Zr90.h5\n",
+      " Reading Zr91 from /home/smharper/openmc/data/nndc_hdf5/Zr91.h5\n",
+      " Reading Zr92 from /home/smharper/openmc/data/nndc_hdf5/Zr92.h5\n",
+      " Reading Zr94 from /home/smharper/openmc/data/nndc_hdf5/Zr94.h5\n",
+      " Reading Zr96 from /home/smharper/openmc/data/nndc_hdf5/Zr96.h5\n",
+      " Reading H1 from /home/smharper/openmc/data/nndc_hdf5/H1.h5\n",
+      " Reading O17 from /home/smharper/openmc/data/nndc_hdf5/O17.h5\n",
+      " Reading c_H_in_H2O from /home/smharper/openmc/data/nndc_hdf5/c_H_in_H2O.h5\n",
       " Maximum neutron transport energy: 2.00000E+07 eV for U235\n",
       " Reading tallies XML file...\n",
       " Building neighboring cells lists for each surface...\n",
@@ -1337,20 +1337,20 @@
       "\n",
       " =======================>     TIMING STATISTICS     <=======================\n",
       "\n",
-      " Total time for initialization     =  8.8597E-01 seconds\n",
-      "   Reading cross sections          =  8.3612E-01 seconds\n",
-      " Total time in simulation          =  1.7084E+01 seconds\n",
-      "   Time in transport only          =  1.7074E+01 seconds\n",
-      "   Time in inactive batches        =  2.0984E+00 seconds\n",
-      "   Time in active batches          =  1.4986E+01 seconds\n",
-      "   Time synchronizing fission bank =  2.5280E-03 seconds\n",
-      "     Sampling source sites         =  1.8110E-03 seconds\n",
-      "     SEND/RECV source sites        =  5.9664E-04 seconds\n",
-      "   Time accumulating tallies       =  6.1651E-05 seconds\n",
-      " Total time for finalization       =  1.3478E-04 seconds\n",
-      " Total time elapsed                =  1.7974E+01 seconds\n",
-      " Calculation Rate (inactive)       =  4765.45 neutrons/second\n",
-      " Calculation Rate (active)         =  6005.68 neutrons/second\n",
+      " Total time for initialization     =  5.3000E-01 seconds\n",
+      "   Reading cross sections          =  4.7425E-01 seconds\n",
+      " Total time in simulation          =  5.9503E+00 seconds\n",
+      "   Time in transport only          =  5.6693E+00 seconds\n",
+      "   Time in inactive batches        =  5.9508E-01 seconds\n",
+      "   Time in active batches          =  5.3552E+00 seconds\n",
+      "   Time synchronizing fission bank =  4.5385E-03 seconds\n",
+      "     Sampling source sites         =  2.4558E-03 seconds\n",
+      "     SEND/RECV source sites        =  1.0922E-03 seconds\n",
+      "   Time accumulating tallies       =  4.2963E-04 seconds\n",
+      " Total time for finalization       =  4.4542E-04 seconds\n",
+      " Total time elapsed                =  6.4846E+00 seconds\n",
+      " Calculation Rate (inactive)       =  16804.5 neutrons/second\n",
+      " Calculation Rate (active)         =  16806.1 neutrons/second\n",
       "\n",
       " ============================>     RESULTS     <============================\n",
       "\n",
@@ -1520,8 +1520,10 @@
       "         Copyright | 2011-2017 Massachusetts Institute of Technology\n",
       "           License | http://openmc.readthedocs.io/en/latest/license.html\n",
       "           Version | 0.8.0\n",
-      "          Git SHA1 | f7edad68f0654d775ed363bfdcbe4aa5d3cfba23\n",
-      "         Date/Time | 2017-04-03 14:33:15\n",
+      "          Git SHA1 | bc4683be1c853fe6d0e31bccad416ef219e3efaf\n",
+      "         Date/Time | 2017-04-13 17:18:01\n",
+      "     MPI Processes | 1\n",
+      "    OpenMP Threads | 4\n",
       "\n",
       " Reading settings XML file...\n",
       " Reading geometry XML file...\n",
@@ -1596,7 +1598,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAMgAAADIAgMAAADQNkYNAAAABGdBTUEAALGPC/xhBQAAACBjSFJN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\nTkSuQmCC\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAMgAAADIAgMAAADQNkYNAAAABGdBTUEAALGPC/xhBQAAACBjSFJN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\nTkSuQmCC\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -1627,7 +1629,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAMgAAADIAgMAAADQNkYNAAAABGdBTUEAALGPC/xhBQAAACBjSFJN\nAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAADFBMVEX///8AAP9yEhL//wDh\n3HbeAAAAAWJLR0QAiAUdSAAAAAd0SU1FB+EEAxMhD/S5fvIAAAKHSURBVGje7dlLjoJAEAZgMrNj\n4z28hKcYFhzBU5hwAFfsTQwJcIqJyzkNcU3SAw2j/agq4Zegk3Rv9Ut3VSt0V0XR/PE1ewQSSCCB\nBHIfSTGT1Hrk00lSj6OYTOrbyCeS/Z3U00hqiLqaQpLaGsUEsrdJ/Zg4kxDTRI8m8afxyPi9Q/ca\nZRLtkiFd5fDqjcmkRdQkZbRR3WhHk4tkCD7aqWFEWyIBDtHBHzaj6OYhEuAQvaxPdRtN7K/MJnpd\nB2WMb39lNunzVW5M0sZezmziTTJOk7Mk8SYZpylY0q/rtLOJ+nBXZpE+xZ+OUM3WSbNF+nW5kygV\nO8GYJPGD/0tAwZCUWtewsoohe3Jdw8p4ciKEuvCk+ySjSGPHb5A++g1F2q0Vv0FSJhQdTEUSLhQ3\nGJtkNGk4woUyBJMTJGFD0cEUNGFC0cFQJJVJRZOMIw1N9mz0Q/wE6RLGRa+UmTKTlDyJKSIlzE7Z\nM0RKmJ0ykxx50lJEyrGdZZPwCdNZJkgpkZgg3bYIQv3cN8YgJ4lcSHKWyNUnibgtemOKRchRIq1P\nUnEn9V5WixBpJ/vtd8mDzTe3/zkiiv4XswQ5yeTikXoCyRcgZ5lcX0YymTSBWOTR08J8XqxK3jZj\n70ze9l+5xkMJeFqu9Rhf45UEvCvXeYkDp4t1jj3AeQw79c0+WwInWOicPPs0Dpz5gZvFOlce4C6G\n3PiAeyVwewXuyMBNHLjvA1UFpHYBVEiAOgxQ7QFqSkjlCqiPAVU4oNYHVBSRuiVQHQVqsEClF6kn\nA1VroDaOVOCBOj/QTUB6FkBnBOm/AF0eoJeEdKyAvhjSfUN6fEgnEehX6pkK7pP/1+ENJJBAAnkF\n+QXfoOhE52QgVwAAACV0RVh0ZGF0ZTpjcmVhdGUAMjAxNy0wNC0wM1QxNDozMzoxNS0wNTowMI92\nsmsAAAAldEVYdGRhdGU6bW9kaWZ5ADIwMTctMDQtMDNUMTQ6MzM6MTUtMDU6MDD+KwrXAAAAAElF\nTkSuQmCC\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAMgAAADIAgMAAADQNkYNAAAABGdBTUEAALGPC/xhBQAAACBjSFJN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\nTkSuQmCC\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -1644,7 +1646,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
diff --git a/examples/jupyter/tally-arithmetic.ipynb b/examples/jupyter/tally-arithmetic.ipynb
index a7b338a2f..fd8d6f551 100644
--- a/examples/jupyter/tally-arithmetic.ipynb
+++ b/examples/jupyter/tally-arithmetic.ipynb
@@ -339,7 +339,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6AgMAAAD1grKuAAAABGdBTUEAALGPC/xhBQAAACBjSFJN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\nWZ8vzgAAAABJRU5ErkJggg==\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6AgMAAAD1grKuAAAABGdBTUEAALGPC/xhBQAAACBjSFJN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\n+Itr3AAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -391,14 +391,14 @@
     "\n",
     "# Instantiate flux Tally in moderator and fuel\n",
     "tally = openmc.Tally(name='flux')\n",
-    "tally.filters = [openmc.CellFilter([fuel_cell.id, moderator_cell.id])]\n",
+    "tally.filters = [openmc.CellFilter([fuel_cell, moderator_cell])]\n",
     "tally.filters.append(energy_filter)\n",
     "tally.scores = ['flux']\n",
     "tallies_file.append(tally)\n",
     "\n",
     "# Instantiate reaction rate Tally in fuel\n",
     "tally = openmc.Tally(name='fuel rxn rates')\n",
-    "tally.filters = [openmc.CellFilter([fuel_cell.id])]\n",
+    "tally.filters = [openmc.CellFilter(fuel_cell)]\n",
     "tally.filters.append(energy_filter)\n",
     "tally.scores = ['nu-fission', 'scatter']\n",
     "tally.nuclides = [u238, u235]\n",
@@ -406,7 +406,7 @@
     "\n",
     "# Instantiate reaction rate Tally in moderator\n",
     "tally = openmc.Tally(name='moderator rxn rates')\n",
-    "tally.filters = [openmc.CellFilter([moderator_cell.id])]\n",
+    "tally.filters = [openmc.CellFilter(moderator_cell)]\n",
     "tally.filters.append(energy_filter)\n",
     "tally.scores = ['absorption', 'total']\n",
     "tally.nuclides = [o16, h1]\n",
@@ -480,7 +480,7 @@
     "fuel_therm_abs_rate = openmc.Tally(name='fuel therm. abs. rate')\n",
     "fuel_therm_abs_rate.scores = ['absorption']\n",
     "fuel_therm_abs_rate.filters = [openmc.EnergyFilter([0., 0.625]),\n",
-    "                               openmc.CellFilter([fuel_cell.id])]\n",
+    "                               openmc.CellFilter([fuel_cell])]\n",
     "tallies_file.append(fuel_therm_abs_rate)"
    ]
   },
@@ -512,7 +512,7 @@
     "\n",
     "# Instantiate flux Tally in moderator and fuel\n",
     "tally = openmc.Tally(name='need-to-slice')\n",
-    "tally.filters = [openmc.CellFilter(bins=[fuel_cell.id, moderator_cell.id])]\n",
+    "tally.filters = [openmc.CellFilter([fuel_cell, moderator_cell])]\n",
     "tally.filters.append(fine_energy_filter)\n",
     "tally.scores = ['nu-fission', 'scatter']\n",
     "tally.nuclides = [h1, u238]\n",
@@ -576,35 +576,30 @@
       "                                     %%%%%%%%%%%\n",
       "\n",
       "                   | The OpenMC Monte Carlo Code\n",
-      "         Copyright | 2011-2016 Massachusetts Institute of Technology\n",
+      "         Copyright | 2011-2017 Massachusetts Institute of Technology\n",
       "           License | http://openmc.readthedocs.io/en/latest/license.html\n",
       "           Version | 0.8.0\n",
-      "          Git SHA1 | da5563eddb5f2c2d6b2c9839d518de40962b78f2\n",
-      "         Date/Time | 2016-10-31 12:54:36\n",
-      "    OpenMP Threads | 4\n",
-      "\n",
-      " ===========================================================================\n",
-      " ========================>     INITIALIZATION     <=========================\n",
-      " ===========================================================================\n",
+      "          Git SHA1 | bc4683be1c853fe6d0e31bccad416ef219e3efaf\n",
+      "         Date/Time | 2017-04-13 17:26:05\n",
+      "     MPI Processes | 1\n",
+      "    OpenMP Threads | 1\n",
       "\n",
       " Reading settings XML file...\n",
       " Reading geometry XML file...\n",
       " Reading materials XML file...\n",
       " Reading cross sections XML file...\n",
-      " Reading U235 from /home/romano/openmc/scripts/nndc_hdf5/U235.h5\n",
-      " Reading U238 from /home/romano/openmc/scripts/nndc_hdf5/U238.h5\n",
-      " Reading O16 from /home/romano/openmc/scripts/nndc_hdf5/O16.h5\n",
-      " Reading H1 from /home/romano/openmc/scripts/nndc_hdf5/H1.h5\n",
-      " Reading B10 from /home/romano/openmc/scripts/nndc_hdf5/B10.h5\n",
-      " Reading Zr90 from /home/romano/openmc/scripts/nndc_hdf5/Zr90.h5\n",
+      " Reading U235 from /home/smharper/openmc/data/nndc_hdf5/U235.h5\n",
+      " Reading U238 from /home/smharper/openmc/data/nndc_hdf5/U238.h5\n",
+      " Reading O16 from /home/smharper/openmc/data/nndc_hdf5/O16.h5\n",
+      " Reading H1 from /home/smharper/openmc/data/nndc_hdf5/H1.h5\n",
+      " Reading B10 from /home/smharper/openmc/data/nndc_hdf5/B10.h5\n",
+      " Reading Zr90 from /home/smharper/openmc/data/nndc_hdf5/Zr90.h5\n",
       " Maximum neutron transport energy: 2.00000E+07 eV for U235\n",
       " Reading tallies XML file...\n",
       " Building neighboring cells lists for each surface...\n",
       " Initializing source particles...\n",
       "\n",
-      " ===========================================================================\n",
       " ====================>     K EIGENVALUE SIMULATION     <====================\n",
-      " ===========================================================================\n",
       "\n",
       "  Bat./Gen.      k            Average k         \n",
       "  =========   ========   ====================   \n",
@@ -617,48 +612,43 @@
       "        7/1    0.99859    1.01409 +/- 0.01550\n",
       "        8/1    1.03441    1.02086 +/- 0.01123\n",
       "        9/1    1.06097    1.03089 +/- 0.01279\n",
-      "       10/1    1.06094    1.03690 +/- 0.01159\n",
-      "       11/1    1.04687    1.03856 +/- 0.00961\n",
-      "       12/1    1.02982    1.03731 +/- 0.00821\n",
-      "       13/1    1.03520    1.03705 +/- 0.00712\n",
-      "       14/1    0.99508    1.03239 +/- 0.00782\n",
-      "       15/1    1.03973    1.03312 +/- 0.00703\n",
-      "       16/1    1.03807    1.03357 +/- 0.00638\n",
-      "       17/1    1.03091    1.03335 +/- 0.00583\n",
-      "       18/1    1.01421    1.03188 +/- 0.00556\n",
-      "       19/1    0.99339    1.02913 +/- 0.00583\n",
-      "       20/1    1.04827    1.03040 +/- 0.00558\n",
+      "       10/1    1.06132    1.03698 +/- 0.01163\n",
+      "       11/1    1.04687    1.03863 +/- 0.00964\n",
+      "       12/1    1.02982    1.03737 +/- 0.00824\n",
+      "       13/1    1.03520    1.03710 +/- 0.00714\n",
+      "       14/1    0.99508    1.03243 +/- 0.00784\n",
+      "       15/1    1.03987    1.03317 +/- 0.00705\n",
+      "       16/1    1.02743    1.03265 +/- 0.00640\n",
+      "       17/1    1.02975    1.03241 +/- 0.00585\n",
+      "       18/1    0.99671    1.02966 +/- 0.00604\n",
+      "       19/1    1.02040    1.02900 +/- 0.00563\n",
+      "       20/1    1.02024    1.02842 +/- 0.00527\n",
       " Creating state point statepoint.20.h5...\n",
       "\n",
-      " ===========================================================================\n",
-      " ======================>     SIMULATION FINISHED     <======================\n",
-      " ===========================================================================\n",
-      "\n",
-      "\n",
       " =======================>     TIMING STATISTICS     <=======================\n",
       "\n",
-      " Total time for initialization     =  5.0418E-01 seconds\n",
-      "   Reading cross sections          =  3.6765E-01 seconds\n",
-      " Total time in simulation          =  8.8388E+00 seconds\n",
-      "   Time in transport only          =  8.7431E+00 seconds\n",
-      "   Time in inactive batches        =  1.4676E+00 seconds\n",
-      "   Time in active batches          =  7.3713E+00 seconds\n",
-      "   Time synchronizing fission bank =  2.2671E-03 seconds\n",
-      "     Sampling source sites         =  1.6677E-03 seconds\n",
-      "     SEND/RECV source sites        =  5.5964E-04 seconds\n",
-      "   Time accumulating tallies       =  9.0487E-05 seconds\n",
-      " Total time for finalization       =  2.7160E-03 seconds\n",
-      " Total time elapsed                =  9.3633E+00 seconds\n",
-      " Calculation Rate (inactive)       =  8517.40 neutrons/second\n",
-      " Calculation Rate (active)         =  5087.33 neutrons/second\n",
+      " Total time for initialization     =  2.2576E-01 seconds\n",
+      "   Reading cross sections          =  1.8005E-01 seconds\n",
+      " Total time in simulation          =  9.6105E+00 seconds\n",
+      "   Time in transport only          =  9.5952E+00 seconds\n",
+      "   Time in inactive batches        =  1.4678E+00 seconds\n",
+      "   Time in active batches          =  8.1427E+00 seconds\n",
+      "   Time synchronizing fission bank =  2.6325E-03 seconds\n",
+      "     Sampling source sites         =  1.5038E-03 seconds\n",
+      "     SEND/RECV source sites        =  8.8069E-04 seconds\n",
+      "   Time accumulating tallies       =  2.0568E-04 seconds\n",
+      " Total time for finalization       =  1.5435E-03 seconds\n",
+      " Total time elapsed                =  9.8506E+00 seconds\n",
+      " Calculation Rate (inactive)       =  8516.30 neutrons/second\n",
+      " Calculation Rate (active)         =  4605.35 neutrons/second\n",
       "\n",
       " ============================>     RESULTS     <============================\n",
       "\n",
-      " k-effective (Collision)     =  1.02791 +/-  0.00553\n",
-      " k-effective (Track-length)  =  1.03040 +/-  0.00558\n",
-      " k-effective (Absorption)    =  1.02011 +/-  0.00491\n",
-      " Combined k-effective        =  1.02461 +/-  0.00398\n",
-      " Leakage Fraction            =  0.01677 +/-  0.00109\n",
+      " k-effective (Collision)     =  1.02889 +/-  0.00492\n",
+      " k-effective (Track-length)  =  1.02842 +/-  0.00527\n",
+      " k-effective (Absorption)    =  1.02637 +/-  0.00349\n",
+      " Combined k-effective        =  1.02700 +/-  0.00291\n",
+      " Leakage Fraction            =  0.01717 +/-  0.00107\n",
       "\n"
      ]
     },
@@ -743,8 +733,8 @@
        "      <th>0</th>\n",
        "      <td>total</td>\n",
        "      <td>(nu-fission / (absorption + current))</td>\n",
-       "      <td>1.02431</td>\n",
-       "      <td>0.00704</td>\n",
+       "      <td>1.023002</td>\n",
+       "      <td>0.006647</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -752,7 +742,7 @@
       ],
       "text/plain": [
        "  nuclide                                  score     mean  std. dev.\n",
-       "0   total  (nu-fission / (absorption + current)) 1.02e+00   7.04e-03"
+       "0   total  (nu-fission / (absorption + current)) 1.02e+00   6.65e-03"
       ]
      },
      "execution_count": 24,
@@ -814,8 +804,8 @@
        "      <td>0.625</td>\n",
        "      <td>total</td>\n",
        "      <td>(absorption + current)</td>\n",
-       "      <td>0.695303</td>\n",
-       "      <td>0.005091</td>\n",
+       "      <td>0.694368</td>\n",
+       "      <td>0.004606</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -823,10 +813,10 @@
       ],
       "text/plain": [
        "   energy low [eV]  energy high [eV] nuclide                   score     mean  \\\n",
-       "0         0.00e+00          6.25e-01   total  (absorption + current) 6.95e-01   \n",
+       "0         0.00e+00          6.25e-01   total  (absorption + current) 6.94e-01   \n",
        "\n",
        "   std. dev.  \n",
-       "0   5.09e-03  "
+       "0   4.61e-03  "
       ]
      },
      "execution_count": 25,
@@ -882,8 +872,8 @@
        "      <td>0.625</td>\n",
        "      <td>total</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>1.202639</td>\n",
-       "      <td>0.010348</td>\n",
+       "      <td>1.203099</td>\n",
+       "      <td>0.009615</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -891,7 +881,7 @@
       ],
       "text/plain": [
        "   energy low [eV]  energy high [eV] nuclide       score     mean  std. dev.\n",
-       "0         0.00e+00          6.25e-01   total  nu-fission 1.20e+00   1.03e-02"
+       "0         0.00e+00          6.25e-01   total  nu-fission 1.20e+00   9.61e-03"
       ]
      },
      "execution_count": 26,
@@ -947,8 +937,8 @@
        "      <td>10000</td>\n",
        "      <td>total</td>\n",
        "      <td>absorption</td>\n",
-       "      <td>0.749349</td>\n",
-       "      <td>0.006731</td>\n",
+       "      <td>0.749423</td>\n",
+       "      <td>0.006089</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -959,7 +949,7 @@
        "0         0.00e+00          6.25e-01  10000   total  absorption 7.49e-01   \n",
        "\n",
        "   std. dev.  \n",
-       "0   6.73e-03  "
+       "0   6.09e-03  "
       ]
      },
      "execution_count": 27,
@@ -1013,8 +1003,8 @@
        "      <td>10000</td>\n",
        "      <td>total</td>\n",
        "      <td>(nu-fission / absorption)</td>\n",
-       "      <td>1.663736</td>\n",
-       "      <td>0.015707</td>\n",
+       "      <td>1.663727</td>\n",
+       "      <td>0.014403</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1025,7 +1015,7 @@
        "0         0.00e+00          6.25e-01  10000   total   \n",
        "\n",
        "                       score     mean  std. dev.  \n",
-       "0  (nu-fission / absorption) 1.66e+00   1.57e-02  "
+       "0  (nu-fission / absorption) 1.66e+00   1.44e-02  "
       ]
      },
      "execution_count": 28,
@@ -1076,8 +1066,8 @@
        "      <td>0.625</td>\n",
        "      <td>total</td>\n",
        "      <td>(absorption + current)</td>\n",
-       "      <td>0.985102</td>\n",
-       "      <td>0.005855</td>\n",
+       "      <td>0.984668</td>\n",
+       "      <td>0.005509</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1088,7 +1078,7 @@
        "0         0.00e+00          6.25e-01   total  (absorption + current) 9.85e-01   \n",
        "\n",
        "   std. dev.  \n",
-       "0   5.86e-03  "
+       "0   5.51e-03  "
       ]
      },
      "execution_count": 29,
@@ -1138,8 +1128,8 @@
        "      <td>0.625</td>\n",
        "      <td>total</td>\n",
        "      <td>(absorption / (absorption + current))</td>\n",
-       "      <td>0.997407</td>\n",
-       "      <td>0.008492</td>\n",
+       "      <td>0.997439</td>\n",
+       "      <td>0.007548</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1150,7 +1140,7 @@
        "0         0.00e+00          6.25e-01   total   \n",
        "\n",
        "                                   score     mean  std. dev.  \n",
-       "0  (absorption / (absorption + current)) 9.97e-01   8.49e-03  "
+       "0  (absorption / (absorption + current)) 9.97e-01   7.55e-03  "
       ]
      },
      "execution_count": 30,
@@ -1202,8 +1192,8 @@
        "      <td>10000</td>\n",
        "      <td>total</td>\n",
        "      <td>((((((absorption + current) * nu-fission) * ab...</td>\n",
-       "      <td>1.02431</td>\n",
-       "      <td>0.02062</td>\n",
+       "      <td>1.023002</td>\n",
+       "      <td>0.018791</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1214,7 +1204,7 @@
        "0         0.00e+00          6.25e-01  10000   total   \n",
        "\n",
        "                                               score     mean  std. dev.  \n",
-       "0  ((((((absorption + current) * nu-fission) * ab... 1.02e+00   2.06e-02  "
+       "0  ((((((absorption + current) * nu-fission) * ab... 1.02e+00   1.88e-02  "
       ]
      },
      "execution_count": 31,
@@ -1284,8 +1274,8 @@
        "      <td>6.250000e-01</td>\n",
        "      <td>(U238 / total)</td>\n",
        "      <td>(nu-fission / flux)</td>\n",
-       "      <td>6.662479e-07</td>\n",
-       "      <td>6.039323e-09</td>\n",
+       "      <td>6.659486e-07</td>\n",
+       "      <td>5.627975e-09</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -1294,8 +1284,8 @@
        "      <td>6.250000e-01</td>\n",
        "      <td>(U238 / total)</td>\n",
        "      <td>(scatter / flux)</td>\n",
-       "      <td>2.099897e-01</td>\n",
-       "      <td>1.843251e-03</td>\n",
+       "      <td>2.099901e-01</td>\n",
+       "      <td>1.748379e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -1304,8 +1294,8 @@
        "      <td>6.250000e-01</td>\n",
        "      <td>(U235 / total)</td>\n",
        "      <td>(nu-fission / flux)</td>\n",
-       "      <td>3.568130e-01</td>\n",
-       "      <td>3.255144e-03</td>\n",
+       "      <td>3.566329e-01</td>\n",
+       "      <td>3.030782e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -1314,8 +1304,8 @@
        "      <td>6.250000e-01</td>\n",
        "      <td>(U235 / total)</td>\n",
        "      <td>(scatter / flux)</td>\n",
-       "      <td>5.555326e-03</td>\n",
-       "      <td>4.893022e-05</td>\n",
+       "      <td>5.555466e-03</td>\n",
+       "      <td>4.635318e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -1324,8 +1314,8 @@
        "      <td>2.000000e+07</td>\n",
        "      <td>(U238 / total)</td>\n",
        "      <td>(nu-fission / flux)</td>\n",
-       "      <td>7.215044e-03</td>\n",
-       "      <td>4.968448e-05</td>\n",
+       "      <td>7.251304e-03</td>\n",
+       "      <td>5.161998e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
@@ -1334,8 +1324,8 @@
        "      <td>2.000000e+07</td>\n",
        "      <td>(U238 / total)</td>\n",
        "      <td>(scatter / flux)</td>\n",
-       "      <td>2.273966e-01</td>\n",
-       "      <td>8.969811e-04</td>\n",
+       "      <td>2.272661e-01</td>\n",
+       "      <td>9.576939e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
@@ -1344,8 +1334,8 @@
        "      <td>2.000000e+07</td>\n",
        "      <td>(U235 / total)</td>\n",
        "      <td>(nu-fission / flux)</td>\n",
-       "      <td>7.969615e-03</td>\n",
-       "      <td>5.374119e-05</td>\n",
+       "      <td>7.920169e-03</td>\n",
+       "      <td>5.751231e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
@@ -1354,8 +1344,8 @@
        "      <td>2.000000e+07</td>\n",
        "      <td>(U235 / total)</td>\n",
        "      <td>(scatter / flux)</td>\n",
-       "      <td>3.362798e-03</td>\n",
-       "      <td>1.286767e-05</td>\n",
+       "      <td>3.358280e-03</td>\n",
+       "      <td>1.341281e-05</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1373,14 +1363,14 @@
        "7  10000         6.25e-01          2.00e+07  (U235 / total)   \n",
        "\n",
        "                 score     mean  std. dev.  \n",
-       "0  (nu-fission / flux) 6.66e-07   6.04e-09  \n",
-       "1     (scatter / flux) 2.10e-01   1.84e-03  \n",
-       "2  (nu-fission / flux) 3.57e-01   3.26e-03  \n",
-       "3     (scatter / flux) 5.56e-03   4.89e-05  \n",
-       "4  (nu-fission / flux) 7.22e-03   4.97e-05  \n",
-       "5     (scatter / flux) 2.27e-01   8.97e-04  \n",
-       "6  (nu-fission / flux) 7.97e-03   5.37e-05  \n",
-       "7     (scatter / flux) 3.36e-03   1.29e-05  "
+       "0  (nu-fission / flux) 6.66e-07   5.63e-09  \n",
+       "1     (scatter / flux) 2.10e-01   1.75e-03  \n",
+       "2  (nu-fission / flux) 3.57e-01   3.03e-03  \n",
+       "3     (scatter / flux) 5.56e-03   4.64e-05  \n",
+       "4  (nu-fission / flux) 7.25e-03   5.16e-05  \n",
+       "5     (scatter / flux) 2.27e-01   9.58e-04  \n",
+       "6  (nu-fission / flux) 7.92e-03   5.75e-05  \n",
+       "7     (scatter / flux) 3.36e-03   1.34e-05  "
       ]
      },
      "execution_count": 33,
@@ -1411,11 +1401,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[  6.66247898e-07]\n",
-      "  [  3.56812954e-01]]\n",
+      "[[[  6.65948580e-07]\n",
+      "  [  3.56632881e-01]]\n",
       "\n",
-      " [[  7.21504433e-03]\n",
-      "  [  7.96961502e-03]]]\n"
+      " [[  7.25130446e-03]\n",
+      "  [  7.92016892e-03]]]\n"
      ]
     }
    ],
@@ -1443,9 +1433,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[ 0.00555533]]\n",
+      "[[[ 0.00555547]]\n",
       "\n",
-      " [[ 0.0033628 ]]]\n"
+      " [[ 0.00335828]]]\n"
      ]
     }
    ],
@@ -1467,8 +1457,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[ 0.22739657]\n",
-      "  [ 0.0033628 ]]]\n"
+      "[[[ 0.22726611]\n",
+      "  [ 0.00335828]]]\n"
      ]
     }
    ],
@@ -1520,7 +1510,7 @@
        "      <td>U238</td>\n",
        "      <td>nu-fission</td>\n",
        "      <td>0.000002</td>\n",
-       "      <td>1.057199e-08</td>\n",
+       "      <td>9.679304e-09</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -1529,8 +1519,8 @@
        "      <td>6.250000e-01</td>\n",
        "      <td>U235</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>0.856784</td>\n",
-       "      <td>5.730044e-03</td>\n",
+       "      <td>0.854805</td>\n",
+       "      <td>5.239673e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -1539,8 +1529,8 @@
        "      <td>2.000000e+07</td>\n",
        "      <td>U238</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>0.082495</td>\n",
-       "      <td>5.176027e-04</td>\n",
+       "      <td>0.082978</td>\n",
+       "      <td>5.346135e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -1549,8 +1539,8 @@
        "      <td>2.000000e+07</td>\n",
        "      <td>U235</td>\n",
        "      <td>nu-fission</td>\n",
-       "      <td>0.091123</td>\n",
-       "      <td>5.574052e-04</td>\n",
+       "      <td>0.090632</td>\n",
+       "      <td>5.981942e-04</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1559,15 +1549,15 @@
       "text/plain": [
        "    cell  energy low [eV]  energy high [eV] nuclide       score     mean  \\\n",
        "0  10000         0.00e+00          6.25e-01    U238  nu-fission 1.60e-06   \n",
-       "1  10000         0.00e+00          6.25e-01    U235  nu-fission 8.57e-01   \n",
-       "2  10000         6.25e-01          2.00e+07    U238  nu-fission 8.25e-02   \n",
-       "3  10000         6.25e-01          2.00e+07    U235  nu-fission 9.11e-02   \n",
+       "1  10000         0.00e+00          6.25e-01    U235  nu-fission 8.55e-01   \n",
+       "2  10000         6.25e-01          2.00e+07    U238  nu-fission 8.30e-02   \n",
+       "3  10000         6.25e-01          2.00e+07    U235  nu-fission 9.06e-02   \n",
        "\n",
        "   std. dev.  \n",
-       "0   1.06e-08  \n",
-       "1   5.73e-03  \n",
-       "2   5.18e-04  \n",
-       "3   5.57e-04  "
+       "0   9.68e-09  \n",
+       "1   5.24e-03  \n",
+       "2   5.35e-04  \n",
+       "3   5.98e-04  "
       ]
      },
      "execution_count": 37,
@@ -1613,8 +1603,8 @@
        "      <td>1.080060e-01</td>\n",
        "      <td>H1</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>4.547947</td>\n",
-       "      <td>0.028000</td>\n",
+       "      <td>4.541188</td>\n",
+       "      <td>0.025230</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -1623,8 +1613,8 @@
        "      <td>1.166529e+00</td>\n",
        "      <td>H1</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>2.003068</td>\n",
-       "      <td>0.008587</td>\n",
+       "      <td>2.001332</td>\n",
+       "      <td>0.006754</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -1633,8 +1623,8 @@
        "      <td>1.259921e+01</td>\n",
        "      <td>H1</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.647225</td>\n",
-       "      <td>0.011136</td>\n",
+       "      <td>1.639292</td>\n",
+       "      <td>0.011374</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -1643,8 +1633,8 @@
        "      <td>1.360790e+02</td>\n",
        "      <td>H1</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>1.831367</td>\n",
-       "      <td>0.010196</td>\n",
+       "      <td>1.821633</td>\n",
+       "      <td>0.009590</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -1653,8 +1643,8 @@
        "      <td>1.469734e+03</td>\n",
        "      <td>H1</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>2.039613</td>\n",
-       "      <td>0.008059</td>\n",
+       "      <td>2.032395</td>\n",
+       "      <td>0.009953</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
@@ -1663,8 +1653,8 @@
        "      <td>1.587401e+04</td>\n",
        "      <td>H1</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>2.137523</td>\n",
-       "      <td>0.012885</td>\n",
+       "      <td>2.120745</td>\n",
+       "      <td>0.011090</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
@@ -1673,8 +1663,8 @@
        "      <td>1.714488e+05</td>\n",
        "      <td>H1</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>2.170725</td>\n",
-       "      <td>0.012669</td>\n",
+       "      <td>2.181709</td>\n",
+       "      <td>0.013602</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
@@ -1683,8 +1673,8 @@
        "      <td>1.851749e+06</td>\n",
        "      <td>H1</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>2.002724</td>\n",
-       "      <td>0.010768</td>\n",
+       "      <td>2.013644</td>\n",
+       "      <td>0.009219</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
@@ -1693,8 +1683,8 @@
        "      <td>2.000000e+07</td>\n",
        "      <td>H1</td>\n",
        "      <td>scatter</td>\n",
-       "      <td>0.371624</td>\n",
-       "      <td>0.002959</td>\n",
+       "      <td>0.372640</td>\n",
+       "      <td>0.002903</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1702,26 +1692,26 @@
       ],
       "text/plain": [
        "    cell  energy low [eV]  energy high [eV] nuclide    score     mean  \\\n",
-       "0  10002         1.00e-02          1.08e-01      H1  scatter 4.55e+00   \n",
+       "0  10002         1.00e-02          1.08e-01      H1  scatter 4.54e+00   \n",
        "1  10002         1.08e-01          1.17e+00      H1  scatter 2.00e+00   \n",
-       "2  10002         1.17e+00          1.26e+01      H1  scatter 1.65e+00   \n",
-       "3  10002         1.26e+01          1.36e+02      H1  scatter 1.83e+00   \n",
-       "4  10002         1.36e+02          1.47e+03      H1  scatter 2.04e+00   \n",
-       "5  10002         1.47e+03          1.59e+04      H1  scatter 2.14e+00   \n",
-       "6  10002         1.59e+04          1.71e+05      H1  scatter 2.17e+00   \n",
-       "7  10002         1.71e+05          1.85e+06      H1  scatter 2.00e+00   \n",
-       "8  10002         1.85e+06          2.00e+07      H1  scatter 3.72e-01   \n",
+       "2  10002         1.17e+00          1.26e+01      H1  scatter 1.64e+00   \n",
+       "3  10002         1.26e+01          1.36e+02      H1  scatter 1.82e+00   \n",
+       "4  10002         1.36e+02          1.47e+03      H1  scatter 2.03e+00   \n",
+       "5  10002         1.47e+03          1.59e+04      H1  scatter 2.12e+00   \n",
+       "6  10002         1.59e+04          1.71e+05      H1  scatter 2.18e+00   \n",
+       "7  10002         1.71e+05          1.85e+06      H1  scatter 2.01e+00   \n",
+       "8  10002         1.85e+06          2.00e+07      H1  scatter 3.73e-01   \n",
        "\n",
        "   std. dev.  \n",
-       "0   2.80e-02  \n",
-       "1   8.59e-03  \n",
-       "2   1.11e-02  \n",
-       "3   1.02e-02  \n",
-       "4   8.06e-03  \n",
-       "5   1.29e-02  \n",
-       "6   1.27e-02  \n",
-       "7   1.08e-02  \n",
-       "8   2.96e-03  "
+       "0   2.52e-02  \n",
+       "1   6.75e-03  \n",
+       "2   1.14e-02  \n",
+       "3   9.59e-03  \n",
+       "4   9.95e-03  \n",
+       "5   1.11e-02  \n",
+       "6   1.36e-02  \n",
+       "7   9.22e-03  \n",
+       "8   2.90e-03  "
       ]
      },
      "execution_count": 38,
diff --git a/examples/python/basic/build-xml.py b/examples/python/basic/build-xml.py
index f248c0a8a..0dc83ed44 100644
--- a/examples/python/basic/build-xml.py
+++ b/examples/python/basic/build-xml.py
@@ -95,7 +95,7 @@ settings_file.export_to_xml()
 ###############################################################################
 
 # Instantiate some tally Filters
-cell_filter = openmc.CellFilter(100)
+cell_filter = openmc.CellFilter(cell2)
 energy_filter = openmc.EnergyFilter([0., 20.e6])
 energyout_filter = openmc.EnergyoutFilter([0., 20.e6])
 
diff --git a/examples/python/lattice/hexagonal/build-xml.py b/examples/python/lattice/hexagonal/build-xml.py
index 1065e6e06..24087be9e 100644
--- a/examples/python/lattice/hexagonal/build-xml.py
+++ b/examples/python/lattice/hexagonal/build-xml.py
@@ -153,7 +153,7 @@ plot_file.export_to_xml()
 
 # Instantiate a distribcell Tally
 tally = openmc.Tally(tally_id=1)
-tally.filters = [openmc.DistribcellFilter(cell2.id)]
+tally.filters = [openmc.DistribcellFilter(cell2)]
 tally.scores = ['total']
 
 # Instantiate a Tallies collection and export to XML
diff --git a/openmc/filter.py b/openmc/filter.py
index 676bc66e1..e4f67eadf 100644
--- a/openmc/filter.py
+++ b/openmc/filter.py
@@ -434,20 +434,19 @@ class Filter(object):
         return df
 
 
-class IntegralFilter(Filter):
-    """Tally modifier that describes phase-space and other characteristics.
+class UniverseFilter(Filter):
+    """Bins tally event locations based on the Universe they occured in.
 
     Parameters
     ----------
-    bins : Integral or Iterable of Integral
-        The bins for the filter. This takes on different meaning for different
-        filters. See the docstrings for sublcasses of this filter or the online
-        documentation for more details.
+    bins : openmc.Universe, Integral, or iterable thereof
+        The Universes to tally.  Either openmc.Universe objects or their
+        Integral ID numbers can be used.
 
     Attributes
     ----------
-    bins : Integral or Iterable of Integral
-        The bins for the filter
+    bins : Iterable of Integral
+        openmc.Universe IDs.
     num_bins : Integral
         The number of filter bins
     stride : Integral
@@ -455,54 +454,48 @@ class IntegralFilter(Filter):
         filter's bins.
 
     """
+    @property
+    def bins(self):
+        return self._bins
+
     @property
     def num_bins(self):
         return len(self.bins)
 
-    @num_bins.setter
-    def num_bins(self, num_bins):
-        cv.check_type('filter num_bins', num_bins, Integral)
-        cv.check_greater_than('filter num_bins', num_bins, 0, equality=True)
-        self._num_bins = num_bins
+    @bins.setter
+    def bins(self, bins):
+        # Format the bins as a 1D numpy array.
+        bins = np.atleast_1d(bins)
 
-    def check_bins(self, bins):
-        cv.check_iterable_type('filter bins', bins, Integral)
+        # Check the bin values.
+        cv.check_iterable_type('filter bins', bins, (Integral, openmc.Universe))
         for edge in bins:
-            cv.check_greater_than('filter bin', edge, 0, equality=True)
+            if isinstance(edge, Integral):
+                cv.check_greater_than('filter bin', edge, 0, equality=True)
+
+        # Extract id values.
+        if any([isinstance(b, openmc.Universe) for b in bins]):
+            bins = np.atleast_1d([b.id if isinstance(b, openmc.Universe) else b
+                                  for b in bins])
+
+        self._bins = bins
+
+    @num_bins.setter
+    def num_bins(self, num_bins): pass
 
 
-class UniverseFilter(IntegralFilter):
-    """Bins tally event locations based on the universe they occured in.
+class MaterialFilter(Filter):
+    """Bins tally event locations based on the Material they occured in.
 
     Parameters
     ----------
-    bins : Integral or Iterable of Integral
-        openmc.Universe IDs.
+    bins : openmc.Material, Integral, or iterable thereof
+        The Materials to tally.  Either openmc.Material objects or their
+        Integral ID numbers can be used.
 
     Attributes
     ----------
-    bins : Integral or Iterable of Integral
-        openmc.Universe IDs.
-    num_bins : Integral
-        The number of filter bins
-    stride : Integral
-        The number of filter, nuclide and score bins within each of this
-        filter's bins.
-
-    """
-
-
-class MaterialFilter(IntegralFilter):
-    """Bins tally events based on which material they occured in.
-
-    Parameters
-    ----------
-    bins : Integral or Iterable of Integral
-        openmc.Material IDs.
-
-    Attributes
-    ----------
-    bins : Integral or Iterable of Integral
+    bins : Iterable of Integral
         openmc.Material IDs.
     num_bins : Integral
         The number of filter bins
@@ -511,19 +504,48 @@ class MaterialFilter(IntegralFilter):
         filter's bins.
 
     """
+    @property
+    def bins(self):
+        return self._bins
+
+    @property
+    def num_bins(self):
+        return len(self.bins)
+
+    @bins.setter
+    def bins(self, bins):
+        # Format the bins as a 1D numpy array.
+        bins = np.atleast_1d(bins)
+
+        # Check the bin values.
+        cv.check_iterable_type('filter bins', bins, (Integral, openmc.Material))
+        for edge in bins:
+            if isinstance(edge, Integral):
+                cv.check_greater_than('filter bin', edge, 0, equality=True)
+
+        # Extract id values.
+        if any([isinstance(b, openmc.Material) for b in bins]):
+            bins = np.atleast_1d([b.id if isinstance(b, openmc.Material) else b
+                                  for b in bins])
+
+        self._bins = bins
+
+    @num_bins.setter
+    def num_bins(self, num_bins): pass
 
 
-class CellFilter(IntegralFilter):
-    """Bins tally event locations based on which cell they occured in.
+class CellFilter(Filter):
+    """Bins tally event locations based on the Cell they occured in.
 
     Parameters
     ----------
-    bins : Integral or Iterable of Integral
-        openmc.Cell IDs.
+    bins : openmc.Cell, Integral, or iterable thereof
+        The Cells to tally.  Either openmc.Cell objects or their
+        Integral ID numbers can be used.
 
     Attributes
     ----------
-    bins : Integral or Iterable of Integral
+    bins : Iterable of Integral
         openmc.Cell IDs.
     num_bins : Integral
         The number of filter bins
@@ -532,19 +554,48 @@ class CellFilter(IntegralFilter):
         filter's bins.
 
     """
+    @property
+    def bins(self):
+        return self._bins
+
+    @property
+    def num_bins(self):
+        return len(self.bins)
+
+    @bins.setter
+    def bins(self, bins):
+        # Format the bins as a 1D numpy array.
+        bins = np.atleast_1d(bins)
+
+        # Check the bin values.
+        cv.check_iterable_type('filter bins', bins, (Integral, openmc.Cell))
+        for edge in bins:
+            if isinstance(edge, Integral):
+                cv.check_greater_than('filter bin', edge, 0, equality=True)
+
+        # Extract id values.
+        if any([isinstance(b, openmc.Cell) for b in bins]):
+            bins = np.atleast_1d([b.id if isinstance(b, openmc.Cell) else b
+                                  for b in bins])
+
+        self._bins = bins
+
+    @num_bins.setter
+    def num_bins(self, num_bins): pass
 
 
-class CellbornFilter(IntegralFilter):
-    """Bins tally events based on the cell that the particle was born in.
+class CellbornFilter(Filter):
+    """Bins tally events based on which Cell the neutron was born in.
 
     Parameters
     ----------
-    bins : Integral or Iterable of Integral
-        openmc.Cell IDs.
+    bins : openmc.Cell, Integral, or iterable thereof
+        The birth Cells to tally.  Either openmc.Cell objects or their
+        Integral ID numbers can be used.
 
     Attributes
     ----------
-    bins : Integral or Iterable of Integral
+    bins : Iterable of Integral
         openmc.Cell IDs.
     num_bins : Integral
         The number of filter bins
@@ -553,9 +604,37 @@ class CellbornFilter(IntegralFilter):
         filter's bins.
 
     """
+    @property
+    def bins(self):
+        return self._bins
+
+    @property
+    def num_bins(self):
+        return len(self.bins)
+
+    @bins.setter
+    def bins(self, bins):
+        # Format the bins as a 1D numpy array.
+        bins = np.atleast_1d(bins)
+
+        # Check the bin values.
+        cv.check_iterable_type('filter bins', bins, (Integral, openmc.Cell))
+        for edge in bins:
+            if isinstance(edge, Integral):
+                cv.check_greater_than('filter bin', edge, 0, equality=True)
+
+        # Extract id values.
+        if any([isinstance(b, openmc.Cell) for b in bins]):
+            bins = np.atleast_1d([b.id if isinstance(b, openmc.Cell) else b
+                                  for b in bins])
+
+        self._bins = bins
+
+    @num_bins.setter
+    def num_bins(self, num_bins): pass
 
 
-class SurfaceFilter(IntegralFilter):
+class SurfaceFilter(Filter):
     """Bins particle currents on Mesh surfaces.
 
     Parameters
@@ -576,6 +655,28 @@ class SurfaceFilter(IntegralFilter):
         filter's bins.
 
     """
+    @property
+    def bins(self):
+        return self._bins
+
+    @property
+    def num_bins(self):
+        return len(self.bins)
+
+    @bins.setter
+    def bins(self, bins):
+        # Format the bins as a 1D numpy array.
+        bins = np.atleast_1d(bins)
+
+        # Check the bin values.
+        cv.check_iterable_type('filter bins', bins, Integral)
+        for edge in bins:
+            cv.check_greater_than('filter bin', edge, 0, equality=True)
+
+        self._bins = bins
+
+    @num_bins.setter
+    def num_bins(self, num_bins): pass
 
     def get_pandas_dataframe(self, data_size, **kwargs):
         """Builds a Pandas DataFrame for the Filter's bins.
@@ -1082,14 +1183,14 @@ class DistribcellFilter(Filter):
 
     Parameters
     ----------
-    bins : Integral or Iterable of Integral or Iterable of Real
-        The bins for the filter. This takes on different meaning for different
-        filters. See the OpenMC online documentation for more details.
+    cell : openmc.Cell or Integral
+        The distributed cell to tally.  Either an openmc.Cell or an Integral
+        cell ID number can be used.
 
     Attributes
     ----------
-    bins : Integral or Iterable of Integral or Iterable of Real
-        The bins for the filter
+    bins : Iterable of Integral
+        An iterable with one element---the ID of the distributed Cell.
     num_bins : Integral
         The number of filter bins
     stride : Integral
@@ -1101,9 +1202,9 @@ class DistribcellFilter(Filter):
 
     """
 
-    def __init__(self, bins):
+    def __init__(self, cell):
         self._paths = None
-        super(DistribcellFilter, self).__init__(bins)
+        super(DistribcellFilter, self).__init__(cell)
 
     @classmethod
     def from_hdf5(cls, group, **kwargs):
@@ -1117,24 +1218,36 @@ class DistribcellFilter(Filter):
 
         return out
 
+    @property
+    def bins(self):
+        return self._bins
+
     @property
     def paths(self):
         return self._paths
 
-    @paths.setter
-    def paths(self, paths):
-        cv.check_iterable_type('paths', paths, str)
-        self._paths = paths
+    @bins.setter
+    def bins(self, bins):
+        # Format the bins as a 1D numpy array.
+        bins = np.atleast_1d(bins)
 
-    def check_bins(self, bins):
+        # Make sure there is only 1 bin.
         if not len(bins) == 1:
             msg = 'Unable to add bins "{0}" to a DistribcellFilter since ' \
                   'only a single distribcell can be used per tally'.format(bins)
             raise ValueError(msg)
 
-        cv.check_iterable_type('filter bins', bins, Integral)
-        for edge in bins:
-            cv.check_greater_than('filter bin', edge, 0, equality=True)
+        # Check the type and extract the id, if necessary.
+        cv.check_type('distribcell bin', bins[0], (Integral, openmc.Cell))
+        if isinstance(bins[0], openmc.Cell):
+            bins = np.atleast_1d(bins[0].id)
+
+        self._bins = bins
+
+    @paths.setter
+    def paths(self, paths):
+        cv.check_iterable_type('paths', paths, str)
+        self._paths = paths
 
     def can_merge(self, other):
         # Distribcell filters cannot have more than one bin
@@ -1608,7 +1721,7 @@ class AzimuthalFilter(RealFilter):
         return df
 
 
-class DelayedGroupFilter(IntegralFilter):
+class DelayedGroupFilter(Filter):
     """Bins fission events based on the produced neutron precursor groups.
 
     Parameters
@@ -1631,6 +1744,28 @@ class DelayedGroupFilter(IntegralFilter):
         filter's bins.
 
     """
+    @property
+    def bins(self):
+        return self._bins
+
+    @property
+    def num_bins(self):
+        return len(self.bins)
+
+    @bins.setter
+    def bins(self, bins):
+        # Format the bins as a 1D numpy array.
+        bins = np.atleast_1d(bins)
+
+        # Check the bin values.
+        cv.check_iterable_type('filter bins', bins, Integral)
+        for edge in bins:
+            cv.check_greater_than('filter bin', edge, 0, equality=True)
+
+        self._bins = bins
+
+    @num_bins.setter
+    def num_bins(self, num_bins): pass
 
 
 class EnergyFunctionFilter(Filter):
diff --git a/tests/test_mg_tallies/test_mg_tallies.py b/tests/test_mg_tallies/test_mg_tallies.py
index 7024a4874..57767fd6b 100644
--- a/tests/test_mg_tallies/test_mg_tallies.py
+++ b/tests/test_mg_tallies/test_mg_tallies.py
@@ -26,8 +26,7 @@ if __name__ == '__main__':
     matching_eout_filter = openmc.EnergyoutFilter(energies)
     mesh_filter = openmc.MeshFilter(mesh)
 
-    mat_ids = [mat.id for mat in model.materials]
-    mat_filter = openmc.MaterialFilter(mat_ids)
+    mat_filter = openmc.MaterialFilter(model.materials)
 
     nuclides = [xs.name for xs in model.xs_data]
 
diff --git a/tests/test_tallies/test_tallies.py b/tests/test_tallies/test_tallies.py
index 315a5b6be..577d2babc 100644
--- a/tests/test_tallies/test_tallies.py
+++ b/tests/test_tallies/test_tallies.py
@@ -43,7 +43,10 @@ if __name__ == '__main__':
     azimuthal_tally3.estimator = 'tracklength'
 
     cellborn_tally = Tally()
-    cellborn_tally.filters = [CellbornFilter((10, 21, 22, 23))]
+    cellborn_tally.filters = [
+        CellbornFilter((model.geometry.get_all_cells()[10],
+                        model.geometry.get_all_cells()[21],
+                        22, 23))]  # Test both Cell objects and ids
     cellborn_tally.scores = ['total']
 
     dg_tally = Tally()
@@ -66,7 +69,10 @@ if __name__ == '__main__':
     transfer_tally.scores = ['scatter', 'nu-fission']
 
     material_tally = Tally()
-    material_tally.filters = [MaterialFilter((1, 2, 3, 4))]
+    material_tally.filters = [
+        MaterialFilter((model.geometry.get_materials_by_name('UOX fuel')[0],
+                        model.geometry.get_materials_by_name('Zircaloy')[0],
+                        3, 4))]  # Test both Material objects and ids
     material_tally.scores = ['total']
 
     mu_bins = (-1.0, -0.5, 0.0, 0.5, 1.0)
@@ -97,10 +103,15 @@ if __name__ == '__main__':
     polar_tally3.estimator = 'tracklength'
 
     universe_tally = Tally()
-    universe_tally.filters = [UniverseFilter((1, 2, 3, 4, 6, 8))]
+    universe_tally.filters = [
+        UniverseFilter((model.geometry.get_all_universes()[1],
+                        model.geometry.get_all_universes()[2],
+                        3, 4, 6, 8))]  # Test both Universe objects and ids
     universe_tally.scores = ['total']
 
-    cell_filter = CellFilter((10, 21, 22, 23, 60))
+    cell_filter = CellFilter((model.geometry.get_all_cells()[10],
+                              model.geometry.get_all_cells()[21],
+                              22, 23, 60))  # Test both Cell objects and ids
     score_tallies = [Tally(), Tally(), Tally()]
     for t in score_tallies:
         t.filters = [cell_filter]