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    <title>PyPI recent updates for GONGHAlphaAnomalyzer</title>
    <link>https://pypi.org/project/gonghalphaanomalyzer/</link>
    <description>Recent updates to the Python Package Index for GONGHAlphaAnomalyzer</description>
    <language>en</language>    <item>
      <title>1.0.0</title>
      <link>https://pypi.org/project/gonghalphaanomalyzer/1.0.0/</link>
      <description>&#34;This software identifies anomalous observations captured by the GONG network.&#34;</description>
<author>mkdgy@umsystem.edu</author>      <pubDate>Thu, 10 Oct 2024 19:12:35 GMT</pubDate>
    </item>    <item>
      <title>0.1.5</title>
      <link>https://pypi.org/project/gonghalphaanomalyzer/0.1.5/</link>
      <description>&#34;This software identifies anomalous observations captured by the GONG network.&#34;</description>
<author>mkdgy@umsystem.edu</author>      <pubDate>Thu, 10 Oct 2024 12:01:46 GMT</pubDate>
    </item>    <item>
      <title>0.1.4</title>
      <link>https://pypi.org/project/gonghalphaanomalyzer/0.1.4/</link>
      <description>&#34;This software identifies anomalous observations captured by the GONG network.&#34;</description>
<author>mkdgy@umsystem.edu</author>      <pubDate>Fri, 04 Oct 2024 12:03:26 GMT</pubDate>
    </item>    <item>
      <title>0.1.3</title>
      <link>https://pypi.org/project/gonghalphaanomalyzer/0.1.3/</link>
      <description>&#34;This software identifies anomalous observations captured by the GONG network.&#34;</description>
<author>mkdgy@umsystem.edu</author>      <pubDate>Wed, 02 Oct 2024 13:32:03 GMT</pubDate>
    </item>    <item>
      <title>0.1.1</title>
      <link>https://pypi.org/project/gonghalphaanomalyzer/0.1.1/</link>
      <description>&#34;This software identifies anomalous observations captured by the GONG network.&#34;</description>
<author>hebamahdi@umsl.edu</author>      <pubDate>Wed, 07 Aug 2024 21:45:46 GMT</pubDate>
    </item>    <item>
      <title>0.1.0</title>
      <link>https://pypi.org/project/gonghalphaanomalyzer/0.1.0/</link>
      <description>This software identifies anomalous observations captured by the GONG network.</description>
<author>hebamahdi@umsl.edu</author>      <pubDate>Fri, 12 Jul 2024 05:19:20 GMT</pubDate>
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