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<date>2016-06-02</date>
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<MJD>57575</MJD>
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<dataEOP><pole type="prediction"><X>0.1709</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22158</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57576</MJD>
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<dataEOP><pole type="prediction"><X>0.1729</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22213</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57577</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1750</X>
<Y>0.4830</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22271</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57578</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1770</X>
<Y>0.4820</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22332</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57579</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1790</X>
<Y>0.4810</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22393</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57580</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1809</X>
<Y>0.4799</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22452</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57581</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1829</X>
<Y>0.4788</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22508</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57582</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1848</X>
<Y>0.4776</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22557</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57583</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1867</X>
<Y>0.4765</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22598</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57584</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1886</X>
<Y>0.4753</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22631</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57585</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1905</X>
<Y>0.4740</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22658</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57586</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1923</X>
<Y>0.4728</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22680</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57587</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1941</X>
<Y>0.4715</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22701</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57588</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1959</X>
<Y>0.4702</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22724</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57589</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1977</X>
<Y>0.4688</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22753</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>21</dateDay>
<MJD>57590</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1994</X>
<Y>0.4675</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22795</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>22</dateDay>
<MJD>57591</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2012</X>
<Y>0.4661</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22852</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57592</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2028</X>
<Y>0.4646</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22925</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57593</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2045</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.23012</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>25</dateDay>
<MJD>57594</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2062</X>
<Y>0.4617</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23107</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>26</dateDay>
<MJD>57595</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2078</X>
<Y>0.4602</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23203</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>27</dateDay>
<MJD>57596</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2094</X>
<Y>0.4587</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23295</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>28</dateDay>
<MJD>57597</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2109</X>
<Y>0.4571</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23378</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>29</dateDay>
<MJD>57598</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2125</X>
<Y>0.4556</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23449</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57599</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2140</X>
<Y>0.4540</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23509</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57600</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2154</X>
<Y>0.4523</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23561</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>01</dateDay>
<MJD>57601</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2169</X>
<Y>0.4507</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23609</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>02</dateDay>
<MJD>57602</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2183</X>
<Y>0.4490</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23660</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>03</dateDay>
<MJD>57603</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2197</X>
<Y>0.4473</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23716</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>04</dateDay>
<MJD>57604</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2210</X>
<Y>0.4456</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23780</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>05</dateDay>
<MJD>57605</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2224</X>
<Y>0.4439</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23849</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57606</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2237</X>
<Y>0.4421</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23921</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57607</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2249</X>
<Y>0.4404</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23995</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57608</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2261</X>
<Y>0.4386</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24067</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>09</dateDay>
<MJD>57609</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2273</X>
<Y>0.4368</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24135</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>10</dateDay>
<MJD>57610</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2285</X>
<Y>0.4349</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24197</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>11</dateDay>
<MJD>57611</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2296</X>
<Y>0.4331</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24253</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>12</dateDay>
<MJD>57612</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2307</X>
<Y>0.4312</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24303</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>13</dateDay>
<MJD>57613</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2318</X>
<Y>0.4293</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24347</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>14</dateDay>
<MJD>57614</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2328</X>
<Y>0.4275</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24390</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>15</dateDay>
<MJD>57615</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2338</X>
<Y>0.4255</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24433</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>16</dateDay>
<MJD>57616</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2348</X>
<Y>0.4236</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24484</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>17</dateDay>
<MJD>57617</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2357</X>
<Y>0.4217</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24546</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>18</dateDay>
<MJD>57618</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2366</X>
<Y>0.4197</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24625</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>19</dateDay>
<MJD>57619</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2374</X>
<Y>0.4177</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24723</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>20</dateDay>
<MJD>57620</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2383</X>
<Y>0.4157</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24839</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>21</dateDay>
<MJD>57621</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2390</X>
<Y>0.4137</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24968</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>22</dateDay>
<MJD>57622</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2398</X>
<Y>0.4117</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25103</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>23</dateDay>
<MJD>57623</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2405</X>
<Y>0.4097</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25234</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>24</dateDay>
<MJD>57624</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2412</X>
<Y>0.4077</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25358</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57625</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2418</X>
<Y>0.4056</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25470</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>26</dateDay>
<MJD>57626</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2424</X>
<Y>0.4036</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25570</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57627</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2430</X>
<Y>0.4015</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25664</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>28</dateDay>
<MJD>57628</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2435</X>
<Y>0.3994</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25754</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57629</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2440</X>
<Y>0.3973</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25847</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57630</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2445</X>
<Y>0.3952</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25946</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57631</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2449</X>
<Y>0.3931</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26054</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>01</dateDay>
<MJD>57632</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2453</X>
<Y>0.3910</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26171</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>02</dateDay>
<MJD>57633</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2456</X>
<Y>0.3889</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26294</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>03</dateDay>
<MJD>57634</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2459</X>
<Y>0.3868</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26421</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
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<MJD>57635</MJD>
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<UT type="prediction"><UT1-UTC>-0.26549</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.26675</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.26796</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2467</X>
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<UT type="prediction"><UT1-UTC>-0.26911</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2469</X>
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<UT type="prediction"><UT1-UTC>-0.27019</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.27122</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2470</X>
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<UT type="prediction"><UT1-UTC>-0.27223</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.27325</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2469</X>
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<UT type="prediction"><UT1-UTC>-0.27432</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2469</X>
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<UT type="prediction"><UT1-UTC>-0.27549</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2467</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.27682</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2466</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.27833</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2464</X>
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<UT type="prediction"><UT1-UTC>-0.28004</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2462</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.28191</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2459</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.28388</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2456</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.28583</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2453</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.28771</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2449</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.28944</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.29103</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.29249</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.29388</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.29526</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2424</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.29666</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.29814</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.29969</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2405</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.30131</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.30297</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2390</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.30465</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2383</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.30631</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2374</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.30792</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2366</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.30947</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2357</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.31094</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.31235</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.31370</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.31503</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.31638</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2307</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.31781</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2296</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.31935</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2285</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.32106</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2273</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.32296</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2262</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.32505</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2249</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.32728</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2237</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.32958</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57678</MJD>
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<dataEOP><pole type="prediction"><X>0.2224</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.33184</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2211</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.33399</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2197</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.33597</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2183</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.33780</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2169</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.33951</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57683</MJD>
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<dataEOP><pole type="prediction"><X>0.2155</X>
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<UT type="prediction"><UT1-UTC>-0.34117</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2140</X>
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<UT type="prediction"><UT1-UTC>-0.34282</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2125</X>
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<UT type="prediction"><UT1-UTC>-0.34452</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2110</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34627</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2094</X>
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<UT type="prediction"><UT1-UTC>-0.34807</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2078</X>
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<UT type="prediction"><UT1-UTC>-0.34991</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2062</X>
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<UT type="prediction"><UT1-UTC>-0.35177</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57690</MJD>
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<dataEOP><pole type="prediction"><X>0.2046</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.35360</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57691</MJD>
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<dataEOP><pole type="prediction"><X>0.2029</X>
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<UT type="prediction"><UT1-UTC>-0.35538</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57692</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2012</X>
<Y>0.2740</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.35710</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57693</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1995</X>
<Y>0.2725</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.35873</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57694</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1978</X>
<Y>0.2711</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36028</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57695</MJD>
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<dataEOP><pole type="prediction"><X>0.1960</X>
<Y>0.2697</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36176</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>04</dateDay>
<MJD>57696</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1942</X>
<Y>0.2683</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36319</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>05</dateDay>
<MJD>57697</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1924</X>
<Y>0.2670</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36462</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>06</dateDay>
<MJD>57698</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1906</X>
<Y>0.2656</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36608</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>07</dateDay>
<MJD>57699</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1887</X>
<Y>0.2644</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36762</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>08</dateDay>
<MJD>57700</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1868</X>
<Y>0.2631</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36929</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>09</dateDay>
<MJD>57701</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1849</X>
<Y>0.2619</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37112</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>10</dateDay>
<MJD>57702</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1830</X>
<Y>0.2606</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37312</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>11</dateDay>
<MJD>57703</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1811</X>
<Y>0.2595</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37529</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>12</dateDay>
<MJD>57704</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1791</X>
<Y>0.2583</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37756</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>13</dateDay>
<MJD>57705</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1771</X>
<Y>0.2572</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37986</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>14</dateDay>
<MJD>57706</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1751</X>
<Y>0.2561</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38209</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>15</dateDay>
<MJD>57707</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1731</X>
<Y>0.2551</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38418</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>16</dateDay>
<MJD>57708</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1711</X>
<Y>0.2540</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38611</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>17</dateDay>
<MJD>57709</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1690</X>
<Y>0.2530</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38790</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>18</dateDay>
<MJD>57710</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1669</X>
<Y>0.2521</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38961</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>19</dateDay>
<MJD>57711</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1649</X>
<Y>0.2511</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39128</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>20</dateDay>
<MJD>57712</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1628</X>
<Y>0.2502</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39297</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>21</dateDay>
<MJD>57713</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1606</X>
<Y>0.2494</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39470</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>22</dateDay>
<MJD>57714</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1585</X>
<Y>0.2485</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39647</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>23</dateDay>
<MJD>57715</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1564</X>
<Y>0.2477</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39827</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>24</dateDay>
<MJD>57716</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1542</X>
<Y>0.2469</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40007</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>25</dateDay>
<MJD>57717</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1520</X>
<Y>0.2462</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40186</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>26</dateDay>
<MJD>57718</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1499</X>
<Y>0.2455</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40360</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>27</dateDay>
<MJD>57719</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1477</X>
<Y>0.2448</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40527</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>28</dateDay>
<MJD>57720</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1455</X>
<Y>0.2442</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40686</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>29</dateDay>
<MJD>57721</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1433</X>
<Y>0.2436</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40837</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>30</dateDay>
<MJD>57722</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1410</X>
<Y>0.2430</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40982</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>01</dateDay>
<MJD>57723</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1388</X>
<Y>0.2425</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41121</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>02</dateDay>
<MJD>57724</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1366</X>
<Y>0.2420</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41259</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>03</dateDay>
<MJD>57725</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1343</X>
<Y>0.2415</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41401</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>04</dateDay>
<MJD>57726</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1321</X>
<Y>0.2411</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41552</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>05</dateDay>
<MJD>57727</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1298</X>
<Y>0.2407</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41716</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>06</dateDay>
<MJD>57728</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1275</X>
<Y>0.2403</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41897</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>07</dateDay>
<MJD>57729</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1253</X>
<Y>0.2400</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42098</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>08</dateDay>
<MJD>57730</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1230</X>
<Y>0.2397</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42319</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>09</dateDay>
<MJD>57731</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1207</X>
<Y>0.2394</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42556</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>10</dateDay>
<MJD>57732</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1184</X>
<Y>0.2392</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42802</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>11</dateDay>
<MJD>57733</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1162</X>
<Y>0.2390</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43050</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>12</dateDay>
<MJD>57734</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1139</X>
<Y>0.2388</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43289</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>13</dateDay>
<MJD>57735</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1116</X>
<Y>0.2387</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43514</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>14</dateDay>
<MJD>57736</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1093</X>
<Y>0.2386</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43721</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>15</dateDay>
<MJD>57737</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1070</X>
<Y>0.2386</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43913</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>16</dateDay>
<MJD>57738</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1047</X>
<Y>0.2386</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44094</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>17</dateDay>
<MJD>57739</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1024</X>
<Y>0.2386</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44269</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>18</dateDay>
<MJD>57740</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1002</X>
<Y>0.2386</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44441</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>19</dateDay>
<MJD>57741</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0979</X>
<Y>0.2387</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44613</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>20</dateDay>
<MJD>57742</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0956</X>
<Y>0.2389</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44783</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>21</dateDay>
<MJD>57743</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0933</X>
<Y>0.2390</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44951</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>22</dateDay>
<MJD>57744</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0911</X>
<Y>0.2392</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45112</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>23</dateDay>
<MJD>57745</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0888</X>
<Y>0.2394</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45265</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>24</dateDay>
<MJD>57746</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0865</X>
<Y>0.2397</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45406</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>25</dateDay>
<MJD>57747</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0843</X>
<Y>0.2400</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45533</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>26</dateDay>
<MJD>57748</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0820</X>
<Y>0.2403</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45645</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>27</dateDay>
<MJD>57749</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0798</X>
<Y>0.2407</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45744</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>28</dateDay>
<MJD>57750</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0776</X>
<Y>0.2411</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45831</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>29</dateDay>
<MJD>57751</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0754</X>
<Y>0.2415</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45910</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>30</dateDay>
<MJD>57752</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0731</X>
<Y>0.2420</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45988</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>31</dateDay>
<MJD>57753</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0709</X>
<Y>0.2425</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46071</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>01</dateDay>
<MJD>57754</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0687</X>
<Y>0.2431</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46165</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>02</dateDay>
<MJD>57755</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0666</X>
<Y>0.2436</Y>
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<UT type="prediction"><UT1-UTC>-0.46276</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<dataEOP><pole type="prediction"><X>0.0644</X>
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<UT type="prediction"><UT1-UTC>-0.46407</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57757</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0622</X>
<Y>0.2449</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46555</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57758</MJD>
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<dataEOP><pole type="prediction"><X>0.0601</X>
<Y>0.2455</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46717</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<dataEOP><pole type="prediction"><X>0.0580</X>
<Y>0.2463</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46884</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57760</MJD>
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<dataEOP><pole type="prediction"><X>0.0558</X>
<Y>0.2470</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47049</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57761</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0537</X>
<Y>0.2478</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47207</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57762</MJD>
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<dataEOP><pole type="prediction"><X>0.0517</X>
<Y>0.2486</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47354</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57763</MJD>
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<dataEOP><pole type="prediction"><X>0.0496</X>
<Y>0.2494</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47487</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57764</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0475</X>
<Y>0.2503</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47612</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57765</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0455</X>
<Y>0.2512</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47732</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57766</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0435</X>
<Y>0.2521</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47854</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57767</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0415</X>
<Y>0.2531</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47974</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57768</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0395</X>
<Y>0.2540</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48099</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57769</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0375</X>
<Y>0.2551</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48232</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57770</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0356</X>
<Y>0.2561</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48374</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>18</dateDay>
<MJD>57771</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0336</X>
<Y>0.2572</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48520</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>19</dateDay>
<MJD>57772</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0317</X>
<Y>0.2583</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48662</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>20</dateDay>
<MJD>57773</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0299</X>
<Y>0.2595</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48802</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>21</dateDay>
<MJD>57774</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0280</X>
<Y>0.2606</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48934</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57775</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0262</X>
<Y>0.2618</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49065</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57776</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0243</X>
<Y>0.2631</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49186</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57777</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0225</X>
<Y>0.2643</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49300</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>25</dateDay>
<MJD>57778</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0208</X>
<Y>0.2656</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49407</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>26</dateDay>
<MJD>57779</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0190</X>
<Y>0.2669</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49514</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>27</dateDay>
<MJD>57780</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0173</X>
<Y>0.2683</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49624</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57781</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0156</X>
<Y>0.2696</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49740</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>29</dateDay>
<MJD>57782</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0139</X>
<Y>0.2710</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49870</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>30</dateDay>
<MJD>57783</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0123</X>
<Y>0.2724</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50019</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>31</dateDay>
<MJD>57784</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0107</X>
<Y>0.2739</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50192</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>01</dateDay>
<MJD>57785</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0091</X>
<Y>0.2753</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50382</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57786</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0075</X>
<Y>0.2768</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50572</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57787</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0060</X>
<Y>0.2783</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50752</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57788</MJD>
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<dataEOP><pole type="prediction"><X>0.0045</X>
<Y>0.2799</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50921</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57789</MJD>
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<dataEOP><pole type="prediction"><X>0.0030</X>
<Y>0.2814</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51090</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57790</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0015</X>
<Y>0.2830</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51255</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57791</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0001</X>
<Y>0.2846</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51406</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>08</dateDay>
<MJD>57792</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0013</X>
<Y>0.2863</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51549</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57793</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0027</X>
<Y>0.2879</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51690</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57794</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0040</X>
<Y>0.2896</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51838</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>11</dateDay>
<MJD>57795</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0053</X>
<Y>0.2913</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51989</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>12</dateDay>
<MJD>57796</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0066</X>
<Y>0.2930</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52152</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>13</dateDay>
<MJD>57797</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0078</X>
<Y>0.2947</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52321</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57798</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0090</X>
<Y>0.2965</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52490</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>15</dateDay>
<MJD>57799</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0102</X>
<Y>0.2983</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52651</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57800</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0113</X>
<Y>0.3001</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52804</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57801</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0125</X>
<Y>0.3019</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52951</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57802</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0135</X>
<Y>0.3037</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53094</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57803</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0146</X>
<Y>0.3055</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53236</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57804</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0156</X>
<Y>0.3074</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53373</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57805</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0166</X>
<Y>0.3093</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53509</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57806</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0175</X>
<Y>0.3112</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53647</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57807</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0184</X>
<Y>0.3131</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53791</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57808</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0193</X>
<Y>0.3150</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53939</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57809</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0201</X>
<Y>0.3169</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54098</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57810</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0210</X>
<Y>0.3189</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54277</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<MJD>57811</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0217</X>
<Y>0.3208</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54479</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>28</dateDay>
<MJD>57812</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0225</X>
<Y>0.3228</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54695</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>01</dateDay>
<MJD>57813</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0232</X>
<Y>0.3248</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54924</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
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<MJD>57814</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0238</X>
<Y>0.3268</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55147</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>03</dateDay>
<MJD>57815</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0245</X>
<Y>0.3288</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55364</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>04</dateDay>
<MJD>57816</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0251</X>
<Y>0.3308</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55566</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>05</dateDay>
<MJD>57817</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0256</X>
<Y>0.3328</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55758</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>06</dateDay>
<MJD>57818</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0261</X>
<Y>0.3348</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55942</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>07</dateDay>
<MJD>57819</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0266</X>
<Y>0.3369</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56120</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>08</dateDay>
<MJD>57820</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0271</X>
<Y>0.3389</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56298</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>09</dateDay>
<MJD>57821</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0275</X>
<Y>0.3410</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56482</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>10</dateDay>
<MJD>57822</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0279</X>
<Y>0.3430</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56670</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>11</dateDay>
<MJD>57823</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0282</X>
<Y>0.3451</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56861</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>12</dateDay>
<MJD>57824</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0285</X>
<Y>0.3472</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57069</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>13</dateDay>
<MJD>57825</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0288</X>
<Y>0.3492</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57287</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>14</dateDay>
<MJD>57826</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0290</X>
<Y>0.3513</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57508</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>15</dateDay>
<MJD>57827</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0292</X>
<Y>0.3534</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57730</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>16</dateDay>
<MJD>57828</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0293</X>
<Y>0.3555</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57946</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>17</dateDay>
<MJD>57829</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0295</X>
<Y>0.3576</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58156</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>18</dateDay>
<MJD>57830</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0295</X>
<Y>0.3597</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58355</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>19</dateDay>
<MJD>57831</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0296</X>
<Y>0.3617</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58550</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>20</dateDay>
<MJD>57832</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0296</X>
<Y>0.3638</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58735</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>21</dateDay>
<MJD>57833</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0296</X>
<Y>0.3659</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58914</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>22</dateDay>
<MJD>57834</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0295</X>
<Y>0.3680</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59090</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>23</dateDay>
<MJD>57835</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0294</X>
<Y>0.3701</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59262</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>24</dateDay>
<MJD>57836</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0293</X>
<Y>0.3722</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59445</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>25</dateDay>
<MJD>57837</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0291</X>
<Y>0.3743</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59643</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>26</dateDay>
<MJD>57838</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0289</X>
<Y>0.3764</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59860</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>27</dateDay>
<MJD>57839</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0286</X>
<Y>0.3785</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.60099</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>28</dateDay>
<MJD>57840</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0283</X>
<Y>0.3805</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.60348</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>29</dateDay>
<MJD>57841</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0280</X>
<Y>0.3826</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.60600</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>30</dateDay>
<MJD>57842</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0277</X>
<Y>0.3847</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.60849</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>31</dateDay>
<MJD>57843</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0273</X>
<Y>0.3868</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.61089</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>01</dateDay>
<MJD>57844</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0268</X>
<Y>0.3888</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.61312</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>02</dateDay>
<MJD>57845</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0264</X>
<Y>0.3909</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.61515</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>03</dateDay>
<MJD>57846</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0259</X>
<Y>0.3929</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.61704</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>04</dateDay>
<MJD>57847</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0253</X>
<Y>0.3950</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.61892</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>05</dateDay>
<MJD>57848</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0247</X>
<Y>0.3970</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62084</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>06</dateDay>
<MJD>57849</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0241</X>
<Y>0.3990</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62285</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>07</dateDay>
<MJD>57850</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0235</X>
<Y>0.4010</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62494</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>08</dateDay>
<MJD>57851</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0228</X>
<Y>0.4030</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62715</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>09</dateDay>
<MJD>57852</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0221</X>
<Y>0.4050</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62935</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>10</dateDay>
<MJD>57853</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0214</X>
<Y>0.4070</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63158</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>11</dateDay>
<MJD>57854</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0206</X>
<Y>0.4090</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63376</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>12</dateDay>
<MJD>57855</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0198</X>
<Y>0.4109</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63588</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>13</dateDay>
<MJD>57856</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0189</X>
<Y>0.4129</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63793</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>14</dateDay>
<MJD>57857</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0180</X>
<Y>0.4148</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63986</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>15</dateDay>
<MJD>57858</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0171</X>
<Y>0.4167</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64167</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>16</dateDay>
<MJD>57859</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0162</X>
<Y>0.4186</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64343</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>17</dateDay>
<MJD>57860</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0152</X>
<Y>0.4205</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64506</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>18</dateDay>
<MJD>57861</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0142</X>
<Y>0.4224</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64666</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>19</dateDay>
<MJD>57862</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0131</X>
<Y>0.4242</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64827</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>20</dateDay>
<MJD>57863</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0120</X>
<Y>0.4261</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64992</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>21</dateDay>
<MJD>57864</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0109</X>
<Y>0.4279</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65168</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>22</dateDay>
<MJD>57865</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0098</X>
<Y>0.4297</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65356</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>23</dateDay>
<MJD>57866</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0086</X>
<Y>0.4315</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65559</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>24</dateDay>
<MJD>57867</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0074</X>
<Y>0.4333</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65771</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>25</dateDay>
<MJD>57868</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0062</X>
<Y>0.4350</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65998</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>26</dateDay>
<MJD>57869</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0049</X>
<Y>0.4368</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.66227</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>27</dateDay>
<MJD>57870</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0036</X>
<Y>0.4385</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.66443</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>28</dateDay>
<MJD>57871</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0023</X>
<Y>0.4402</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.66651</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>29</dateDay>
<MJD>57872</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0010</X>
<Y>0.4419</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.66832</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>30</dateDay>
<MJD>57873</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0004</X>
<Y>0.4435</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.67004</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>01</dateDay>
<MJD>57874</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0018</X>
<Y>0.4452</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.67167</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>02</dateDay>
<MJD>57875</MJD>
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