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<date>2016-06-09</date>
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<dataEOP><pole type="prediction"><X>0.1813</X>
<Y>0.4774</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22504</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57586</MJD>
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<dataEOP><pole type="prediction"><X>0.1832</X>
<Y>0.4763</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22533</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57587</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1851</X>
<Y>0.4752</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22558</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>0.1869</X>
<Y>0.4740</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22583</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>0.1888</X>
<Y>0.4728</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22613</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57590</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1906</X>
<Y>0.4716</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22655</UT1-UTC>
</UT>
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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>0.1923</X>
<Y>0.4703</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22710</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>23</dateDay>
<MJD>57592</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1941</X>
<Y>0.4691</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22780</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57593</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1958</X>
<Y>0.4677</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22863</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57594</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1975</X>
<Y>0.4664</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22953</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>0.1992</X>
<Y>0.4650</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23045</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57596</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2009</X>
<Y>0.4637</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23133</UT1-UTC>
</UT>
</dataEOP>
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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>0.2025</X>
<Y>0.4622</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23212</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57598</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2041</X>
<Y>0.4608</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23279</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>0.2057</X>
<Y>0.4593</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23335</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>31</dateDay>
<MJD>57600</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2072</X>
<Y>0.4579</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23384</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>01</dateDay>
<MJD>57601</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2087</X>
<Y>0.4563</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23429</UT1-UTC>
</UT>
</dataEOP>
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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>0.2102</X>
<Y>0.4548</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23477</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>0.2117</X>
<Y>0.4533</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23532</UT1-UTC>
</UT>
</dataEOP>
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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>0.2131</X>
<Y>0.4517</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23593</UT1-UTC>
</UT>
</dataEOP>
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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>0.2146</X>
<Y>0.4501</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23662</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>06</dateDay>
<MJD>57606</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2159</X>
<Y>0.4484</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23734</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>07</dateDay>
<MJD>57607</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2173</X>
<Y>0.4468</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23809</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>08</dateDay>
<MJD>57608</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2186</X>
<Y>0.4451</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23883</UT1-UTC>
</UT>
</dataEOP>
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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>0.2199</X>
<Y>0.4434</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23953</UT1-UTC>
</UT>
</dataEOP>
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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>0.2211</X>
<Y>0.4417</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24018</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>0.2224</X>
<Y>0.4400</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24077</UT1-UTC>
</UT>
</dataEOP>
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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>0.2236</X>
<Y>0.4383</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24130</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>0.2247</X>
<Y>0.4365</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24178</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>0.2258</X>
<Y>0.4347</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24223</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>0.2269</X>
<Y>0.4329</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24271</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>0.2280</X>
<Y>0.4311</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24324</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>0.2290</X>
<Y>0.4293</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24388</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>0.2300</X>
<Y>0.4274</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24468</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>0.2310</X>
<Y>0.4255</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24566</UT1-UTC>
</UT>
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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>0.2319</X>
<Y>0.4237</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24681</UT1-UTC>
</UT>
</dataEOP>
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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>0.2328</X>
<Y>0.4218</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24808</UT1-UTC>
</UT>
</dataEOP>
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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>0.2337</X>
<Y>0.4199</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24940</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>0.2345</X>
<Y>0.4179</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25069</UT1-UTC>
</UT>
</dataEOP>
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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>0.2353</X>
<Y>0.4160</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25188</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>25</dateDay>
<MJD>57625</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2360</X>
<Y>0.4140</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25293</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>0.2367</X>
<Y>0.4121</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25386</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>27</dateDay>
<MJD>57627</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2374</X>
<Y>0.4101</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>28</dateDay>
<MJD>57628</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2381</X>
<Y>0.4081</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25551</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>29</dateDay>
<MJD>57629</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2387</X>
<Y>0.4061</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25633</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57630</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2393</X>
<Y>0.4041</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25722</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>31</dateDay>
<MJD>57631</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2398</X>
<Y>0.4021</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25820</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>01</dateDay>
<MJD>57632</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2403</X>
<Y>0.4001</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25926</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>0.2408</X>
<Y>0.3981</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26041</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>03</dateDay>
<MJD>57634</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2412</X>
<Y>0.3960</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26160</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>04</dateDay>
<MJD>57635</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2416</X>
<Y>0.3940</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26280</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>05</dateDay>
<MJD>57636</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2419</X>
<Y>0.3919</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26400</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>06</dateDay>
<MJD>57637</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2423</X>
<Y>0.3899</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26516</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>07</dateDay>
<MJD>57638</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2425</X>
<Y>0.3878</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26628</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>08</dateDay>
<MJD>57639</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2428</X>
<Y>0.3858</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26734</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>09</dateDay>
<MJD>57640</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2430</X>
<Y>0.3837</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26837</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>10</dateDay>
<MJD>57641</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2432</X>
<Y>0.3816</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26937</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>11</dateDay>
<MJD>57642</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2433</X>
<Y>0.3796</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27039</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>12</dateDay>
<MJD>57643</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2434</X>
<Y>0.3775</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27146</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>13</dateDay>
<MJD>57644</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2434</X>
<Y>0.3754</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27264</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>14</dateDay>
<MJD>57645</MJD>
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<UT type="prediction"><UT1-UTC>-0.27397</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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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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<UT type="prediction"><UT1-UTC>-0.27720</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.27909</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.28107</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.28306</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.28497</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.28675</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.28838</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.28988</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.29132</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.29274</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.29416</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.29566</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.29723</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.29887</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2388</X>
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<UT type="prediction"><UT1-UTC>-0.30056</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.30226</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.30394</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.30558</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.30715</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.30866</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2346</X>
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<UT type="prediction"><UT1-UTC>-0.31009</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.31147</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.31284</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2321</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.31422</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.31568</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.31726</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2292</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.31900</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.32094</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2272</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.32306</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<UT type="prediction"><UT1-UTC>-0.32533</UT1-UTC>
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<UT type="prediction"><UT1-UTC>-0.32766</UT1-UTC>
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<UT type="prediction"><UT1-UTC>-0.32995</UT1-UTC>
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<UT type="prediction"><UT1-UTC>-0.33212</UT1-UTC>
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<UT type="prediction"><UT1-UTC>-0.33413</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2202</X>
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<UT type="prediction"><UT1-UTC>-0.33598</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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</pole>
<UT type="prediction"><UT1-UTC>-0.33771</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>0.2177</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.33938</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2163</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34105</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57685</MJD>
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<dataEOP><pole type="prediction"><X>0.2150</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34276</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2136</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34452</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57687</MJD>
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<dataEOP><pole type="prediction"><X>0.2122</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34633</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57688</MJD>
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<dataEOP><pole type="prediction"><X>0.2107</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34817</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.2093</X>
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<UT type="prediction"><UT1-UTC>-0.35003</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.2078</X>
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<UT type="prediction"><UT1-UTC>-0.35186</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.2062</X>
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<UT type="prediction"><UT1-UTC>-0.35364</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.2047</X>
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<UT type="prediction"><UT1-UTC>-0.35536</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.2031</X>
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<UT type="prediction"><UT1-UTC>-0.35699</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.2015</X>
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<UT type="prediction"><UT1-UTC>-0.35854</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.1999</X>
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<UT type="prediction"><UT1-UTC>-0.36002</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.1982</X>
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<UT type="prediction"><UT1-UTC>-0.36144</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.1966</X>
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<UT type="prediction"><UT1-UTC>-0.36286</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1949</X>
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<UT type="prediction"><UT1-UTC>-0.36432</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.1931</X>
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<UT type="prediction"><UT1-UTC>-0.36586</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1914</X>
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<UT type="prediction"><UT1-UTC>-0.36752</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1896</X>
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<UT type="prediction"><UT1-UTC>-0.36935</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1878</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.37135</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57703</MJD>
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<dataEOP><pole type="prediction"><X>0.1860</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.37351</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57704</MJD>
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<dataEOP><pole type="prediction"><X>0.1842</X>
<Y>0.2681</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37578</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57705</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1823</X>
<Y>0.2669</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37807</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>14</dateDay>
<MJD>57706</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1805</X>
<Y>0.2658</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38030</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>0.1786</X>
<Y>0.2646</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38238</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>0.1767</X>
<Y>0.2635</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38430</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>0.1747</X>
<Y>0.2625</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38608</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>0.1728</X>
<Y>0.2614</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38777</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>0.1708</X>
<Y>0.2604</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38943</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>0.1689</X>
<Y>0.2595</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39111</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>0.1669</X>
<Y>0.2585</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39282</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>0.1649</X>
<Y>0.2576</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39457</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>0.1628</X>
<Y>0.2567</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39634</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>0.1608</X>
<Y>0.2558</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39812</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>0.1587</X>
<Y>0.2550</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39987</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>0.1567</X>
<Y>0.2542</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40157</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>0.1546</X>
<Y>0.2535</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40320</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>0.1525</X>
<Y>0.2527</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40474</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>0.1504</X>
<Y>0.2520</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40619</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>0.1483</X>
<Y>0.2514</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40757</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>0.1462</X>
<Y>0.2507</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40888</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>0.1440</X>
<Y>0.2501</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41017</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>0.1419</X>
<Y>0.2496</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41147</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>0.1398</X>
<Y>0.2490</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41284</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>0.1376</X>
<Y>0.2485</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41431</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>0.1354</X>
<Y>0.2481</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41593</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>0.1333</X>
<Y>0.2476</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41771</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>0.1311</X>
<Y>0.2472</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41965</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>0.1289</X>
<Y>0.2468</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42173</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>0.1267</X>
<Y>0.2465</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42388</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>0.1245</X>
<Y>0.2462</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42605</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>0.1223</X>
<Y>0.2459</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42816</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>0.1201</X>
<Y>0.2457</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43018</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>0.1179</X>
<Y>0.2455</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43210</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>0.1157</X>
<Y>0.2453</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43396</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>0.1135</X>
<Y>0.2452</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43583</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>0.1113</X>
<Y>0.2451</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43775</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>0.1091</X>
<Y>0.2450</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43974</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>0.1069</X>
<Y>0.2450</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44181</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>0.1047</X>
<Y>0.2450</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44392</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>0.1025</X>
<Y>0.2451</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44602</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>0.1004</X>
<Y>0.2451</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44807</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>0.0982</X>
<Y>0.2452</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45002</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>0.0960</X>
<Y>0.2454</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45184</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>0.0938</X>
<Y>0.2455</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45350</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>0.0916</X>
<Y>0.2457</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45501</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>27</dateDay>
<MJD>57749</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0894</X>
<Y>0.2460</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45638</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>0.0873</X>
<Y>0.2463</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45764</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>0.0851</X>
<Y>0.2466</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.45885</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>0.0830</X>
<Y>0.2469</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46004</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>0.0808</X>
<Y>0.2473</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46127</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>0.0787</X>
<Y>0.2477</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46257</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>0.0766</X>
<Y>0.2481</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46397</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>03</dateDay>
<MJD>57756</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0744</X>
<Y>0.2486</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46549</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>04</dateDay>
<MJD>57757</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0723</X>
<Y>0.2491</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46710</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>05</dateDay>
<MJD>57758</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0702</X>
<Y>0.2496</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.46878</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>06</dateDay>
<MJD>57759</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0682</X>
<Y>0.2502</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47046</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>07</dateDay>
<MJD>57760</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0661</X>
<Y>0.2508</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47210</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>08</dateDay>
<MJD>57761</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0640</X>
<Y>0.2514</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47362</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>09</dateDay>
<MJD>57762</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0620</X>
<Y>0.2521</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47500</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>10</dateDay>
<MJD>57763</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0599</X>
<Y>0.2528</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47621</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>11</dateDay>
<MJD>57764</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0579</X>
<Y>0.2535</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47730</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>12</dateDay>
<MJD>57765</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0559</X>
<Y>0.2543</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47832</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>13</dateDay>
<MJD>57766</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0539</X>
<Y>0.2551</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.47937</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>14</dateDay>
<MJD>57767</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0520</X>
<Y>0.2559</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48050</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>15</dateDay>
<MJD>57768</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0500</X>
<Y>0.2567</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48175</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>16</dateDay>
<MJD>57769</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0481</X>
<Y>0.2576</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48313</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>17</dateDay>
<MJD>57770</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0462</X>
<Y>0.2585</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48459</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>18</dateDay>
<MJD>57771</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0443</X>
<Y>0.2595</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48607</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>19</dateDay>
<MJD>57772</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0424</X>
<Y>0.2605</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48754</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>20</dateDay>
<MJD>57773</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0405</X>
<Y>0.2615</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.48889</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>21</dateDay>
<MJD>57774</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0387</X>
<Y>0.2625</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49016</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>22</dateDay>
<MJD>57775</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0368</X>
<Y>0.2635</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49132</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>23</dateDay>
<MJD>57776</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0350</X>
<Y>0.2646</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49238</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>24</dateDay>
<MJD>57777</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0332</X>
<Y>0.2657</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49336</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>25</dateDay>
<MJD>57778</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0315</X>
<Y>0.2669</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49432</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>26</dateDay>
<MJD>57779</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0297</X>
<Y>0.2680</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49527</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>27</dateDay>
<MJD>57780</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0280</X>
<Y>0.2692</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49627</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>28</dateDay>
<MJD>57781</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0263</X>
<Y>0.2705</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49730</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>29</dateDay>
<MJD>57782</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0247</X>
<Y>0.2717</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49843</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>30</dateDay>
<MJD>57783</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0230</X>
<Y>0.2730</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.49974</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>31</dateDay>
<MJD>57784</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0214</X>
<Y>0.2743</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50127</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>01</dateDay>
<MJD>57785</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0198</X>
<Y>0.2756</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50296</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>02</dateDay>
<MJD>57786</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0182</X>
<Y>0.2770</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50472</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>03</dateDay>
<MJD>57787</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0167</X>
<Y>0.2783</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50653</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>04</dateDay>
<MJD>57788</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0152</X>
<Y>0.2797</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.50829</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>05</dateDay>
<MJD>57789</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0137</X>
<Y>0.2812</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51004</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>06</dateDay>
<MJD>57790</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0122</X>
<Y>0.2826</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51166</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>07</dateDay>
<MJD>57791</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0108</X>
<Y>0.2841</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51317</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>08</dateDay>
<MJD>57792</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0093</X>
<Y>0.2856</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51462</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>09</dateDay>
<MJD>57793</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0080</X>
<Y>0.2871</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51606</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>10</dateDay>
<MJD>57794</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0066</X>
<Y>0.2886</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51756</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>11</dateDay>
<MJD>57795</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0053</X>
<Y>0.2902</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.51911</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>12</dateDay>
<MJD>57796</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0040</X>
<Y>0.2917</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52074</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>13</dateDay>
<MJD>57797</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0027</X>
<Y>0.2933</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52249</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>14</dateDay>
<MJD>57798</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0015</X>
<Y>0.2949</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52434</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>15</dateDay>
<MJD>57799</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0003</X>
<Y>0.2966</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52622</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>16</dateDay>
<MJD>57800</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0009</X>
<Y>0.2982</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52799</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>17</dateDay>
<MJD>57801</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0021</X>
<Y>0.2999</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.52957</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>18</dateDay>
<MJD>57802</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0032</X>
<Y>0.3016</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53101</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>19</dateDay>
<MJD>57803</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0043</X>
<Y>0.3033</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53245</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>20</dateDay>
<MJD>57804</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0053</X>
<Y>0.3050</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53390</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>21</dateDay>
<MJD>57805</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0064</X>
<Y>0.3068</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53524</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>22</dateDay>
<MJD>57806</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0073</X>
<Y>0.3085</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53655</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>23</dateDay>
<MJD>57807</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0083</X>
<Y>0.3103</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53786</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>24</dateDay>
<MJD>57808</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0092</X>
<Y>0.3121</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.53927</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>25</dateDay>
<MJD>57809</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0101</X>
<Y>0.3139</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54075</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>26</dateDay>
<MJD>57810</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0110</X>
<Y>0.3157</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54242</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>27</dateDay>
<MJD>57811</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0118</X>
<Y>0.3175</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54427</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>28</dateDay>
<MJD>57812</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0126</X>
<Y>0.3194</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54625</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>01</dateDay>
<MJD>57813</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0134</X>
<Y>0.3212</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.54826</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>02</dateDay>
<MJD>57814</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0141</X>
<Y>0.3231</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55026</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>-0.0148</X>
<Y>0.3250</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55222</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>-0.0154</X>
<Y>0.3268</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55413</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>-0.0161</X>
<Y>0.3287</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55598</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>-0.0167</X>
<Y>0.3306</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55774</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>-0.0172</X>
<Y>0.3326</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.55946</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>-0.0177</X>
<Y>0.3345</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56121</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>-0.0182</X>
<Y>0.3364</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56301</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>-0.0187</X>
<Y>0.3384</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56485</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>-0.0191</X>
<Y>0.3403</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56676</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>-0.0195</X>
<Y>0.3423</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.56879</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>-0.0198</X>
<Y>0.3442</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57091</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>14</dateDay>
<MJD>57826</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0201</X>
<Y>0.3462</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57304</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>-0.0204</X>
<Y>0.3482</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57515</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>-0.0206</X>
<Y>0.3501</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57712</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>-0.0208</X>
<Y>0.3521</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.57900</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>-0.0210</X>
<Y>0.3541</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58073</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>-0.0211</X>
<Y>0.3561</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58239</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>-0.0212</X>
<Y>0.3581</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58403</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>-0.0213</X>
<Y>0.3601</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58564</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>-0.0213</X>
<Y>0.3621</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58728</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>-0.0213</X>
<Y>0.3640</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.58901</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>-0.0213</X>
<Y>0.3660</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59079</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>-0.0212</X>
<Y>0.3680</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59266</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>-0.0211</X>
<Y>0.3700</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59480</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>-0.0209</X>
<Y>0.3720</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59717</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>-0.0207</X>
<Y>0.3740</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.59969</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>-0.0205</X>
<Y>0.3760</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.60233</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>-0.0203</X>
<Y>0.3780</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.60495</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>-0.0200</X>
<Y>0.3799</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.60748</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>-0.0196</X>
<Y>0.3819</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.60986</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>-0.0193</X>
<Y>0.3839</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.61213</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>-0.0189</X>
<Y>0.3858</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.61426</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>-0.0185</X>
<Y>0.3878</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.61630</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>-0.0180</X>
<Y>0.3897</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.61831</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>-0.0175</X>
<Y>0.3917</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62027</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>-0.0170</X>
<Y>0.3936</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62230</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>-0.0164</X>
<Y>0.3955</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62441</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>-0.0158</X>
<Y>0.3975</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62658</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>-0.0152</X>
<Y>0.3994</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.62879</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>-0.0145</X>
<Y>0.4013</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63095</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>-0.0138</X>
<Y>0.4032</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63301</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>-0.0131</X>
<Y>0.4050</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63497</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>-0.0123</X>
<Y>0.4069</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63685</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>-0.0115</X>
<Y>0.4088</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.63859</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>-0.0107</X>
<Y>0.4106</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64020</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>17</dateDay>
<MJD>57860</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0098</X>
<Y>0.4124</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64171</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>-0.0089</X>
<Y>0.4142</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64324</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>-0.0080</X>
<Y>0.4160</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64485</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>-0.0071</X>
<Y>0.4178</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64655</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>-0.0061</X>
<Y>0.4196</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.64839</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>-0.0051</X>
<Y>0.4214</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65042</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>-0.0040</X>
<Y>0.4231</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65256</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>-0.0029</X>
<Y>0.4248</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65489</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>-0.0018</X>
<Y>0.4266</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65729</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>-0.0007</X>
<Y>0.4282</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.65971</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>0.0005</X>
<Y>0.4299</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.66210</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>0.0016</X>
<Y>0.4316</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.66432</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>29</dateDay>
<MJD>57872</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0029</X>
<Y>0.4332</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.66635</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>0.0041</X>
<Y>0.4348</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.66828</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>0.0054</X>
<Y>0.4365</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.67005</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>02</dateDay>
<MJD>57875</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0067</X>
<Y>0.4380</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.67177</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>03</dateDay>
<MJD>57876</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0080</X>
<Y>0.4396</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.67350</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>04</dateDay>
<MJD>57877</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0094</X>
<Y>0.4411</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.67524</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>05</dateDay>
<MJD>57878</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0107</X>
<Y>0.4427</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.67703</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>06</dateDay>
<MJD>57879</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0121</X>
<Y>0.4442</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.67881</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>07</dateDay>
<MJD>57880</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0136</X>
<Y>0.4456</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.68058</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>08</dateDay>
<MJD>57881</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0150</X>
<Y>0.4471</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.68225</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>09</dateDay>
<MJD>57882</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0165</X>
<Y>0.4485</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.68391</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>10</dateDay>
<MJD>57883</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0180</X>
<Y>0.4500</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.68546</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>11</dateDay>
<MJD>57884</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0195</X>
<Y>0.4513</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.68685</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>12</dateDay>
<MJD>57885</MJD>
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