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    <title>cybernetics</title>
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    <language>fr</language>
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      <title>Transgenetic Cybernetics Regarding the Nucleic Acids DNA and RNA Assimilated to Cybernetic Systems with Automatic Self-organization</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=1312</link>
      <description>The capacity of the carbon atom to generate linear, branched and cyclic chains by linking with other carbon atoms, enables the human brain's natural neuronal networks to materialize, with living structures, the fundamental computing algorithmic structures sequence, selection and iteration in the artificial neuronal networks of artificial intelligence. The nucleic acids DNA and RNA consist of structural units called nucleotides, which contain a purinic or pyrimidine base having the shape of a double heterocycle or a base with the shape of a heterocycle. Analyzing the structure of the bases having the shape of a heterocycle or double heterocycle, the geometric symmetry of the double links made of a σ link and a π link can be noticed. Setting out from F. Schrödinger's wave equation we use the function of orbital wave ψ or orbital. In practical models, the orbitals are considered to be bounded by surfaces of the same electronic density, and within these bounds there may occur a high electron density which accounts for the particular shape of the orbitals in the modeling representation. In our paper, the nucleic acids DNA and RNA are assimilated to cybernetic systems with automatic self-organization, by the electrons transition owing to some external actions to the orbitals geometrical shape and their distribution in space. </description>
      <pubDate>Wed, 10 Jul 2024 10:43:44 +0200</pubDate>
      <lastBuildDate>Thu, 10 Oct 2024 16:11:10 +0200</lastBuildDate>
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      <title>Sertraline in Psychiatric Practice : a Topographical Study</title>
      <link>http://popups.lib.uliege.be/1373-5411/index.php?id=3601</link>
      <description>We propose an operational research contribution to clinical psychopharmacology ; the key problems of drug selection and outcome prediction are tackled in a retrospective study about Mood and Anxiety Disorders focusing on sertraline, a selective inhibitor of serotonin reuptake. A three-step approach to data coding, clinical modeling and rule extraction is proposed, based on topographical techniques (Kohonen's Self-Organizing Maps) and information theory (Shannon entropy and mutual information). Clinical data are bitwise sampled, allowing an unbiased definition of system metrics. Uncertainty measures are introduced for a real-world sized approach to clinical practice; top-down induction decision trees (TDIDT) for drug administration are proposed, and a default logic of prescription is analyzed in the light of direct clinical experience and available literature data. </description>
      <pubDate>Thu, 26 Sep 2024 10:13:22 +0200</pubDate>
      <lastBuildDate>Tue, 08 Oct 2024 13:28:18 +0200</lastBuildDate>
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