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      <title>Identifying microRNAs associated with anxiety proneness in a cohort of South African adolescents</title>
      <pubDate>Wed, 10 Jun 2026 12:46:49 +0000</pubDate>
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      <author>Jansen van Rensburg, Danielle</author>
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      <title>Towards a generic film style machine learning analysis framework.</title>
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      <author>Barnard, Christan</author>
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      <title>Proton single-event effects tolerance testing of a vision processing unit for satellite use</title>
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      <author>Badat, Sa'ad</author>
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      <title>Digital Twin for Photovoltaic System Maintenance Support</title>
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      <author>Swanepoel, Heinrich Marc</author>
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      <title>Utilising competitive intelligence, a key component of knowledge management, to formulate a strategy to develop and manage international markets</title>
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      <author>Marsal, Jose Javier</author>
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      <title>Functional analysis and recombinant expression of a sea urchin G-string binding factor</title>
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      <author>Riedemann, Johann</author>
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      <title>Predictive models for smart vineyards</title>
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      <title>Gender perspectives on money attitudes and materialism amongst upwardly mobile South Africans</title>
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      <title>Modelling the impact of change in systems and technology in a surface mining environment with system dynamics</title>
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      <title>Magic to manic : the evolution of the zombie figure In fiction and its basis In moral panic dissemination</title>
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      <title>The functional analysis of XhLEA3-2 -  a LEA_4 from the resurrection plant, Xerophyta humilis</title>
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      <title>Optimal placement of phasor measurement units using the Advanced Matrix Manipulation algorithm</title>
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      <title>The use of artificial intelligence for business optimisation in banking: case of Nigeria</title>
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      <title>Predictive analysis in solar kiln drying of wood using recurrent neural networks</title>
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      <title>Simulating the impact of climate change on yield reduction of vegetable crop propagation</title>
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      <title>Correction: A comparative predictive analysis of back-propagation artificial neural networks and non-linear regression models in forecasting seasonal ozone concentrations</title>
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