Showing 61 - 80 results of 52,505 for search '(( significant rate based ) OR ( significant ((genes decrease) OR (greatest decrease)) ))', query time: 0.88s Refine Results
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    DWV abundance variable over time and greatest in October. by Cayley Faurot-Daniels (9354170)

    Published 2020
    “…The first derivative of the fitted spline in panel A was calculated to identify the rate of change of DWV abundance throughout time and 95% confidence intervals (gray) were built around the first derivative to distinguish time periods when the change in virus abundance is significantly different from zero. DWV abundance significantly decreased (red) from 0 to 100 days of the study and significantly increased (blue) from 150 to 250 days of the study.…”
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    Data_Sheet_1_Organic Contaminant Mixture Significantly Changes Microbenthic Community Structure and Increases the Expression of PAH Degradation Genes.DOCX by Sven Iburg (9251132)

    Published 2020
    “…Additionally, while the abundance of active PAH degraders was significantly higher in spiked sediments than in the controls, no significant effect of our organic mixture was found on nitrification rates or the expression of AmoA (bacterial ammonia oxidizer gene). …”
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    Data_Sheet_1_Organic Contaminant Mixture Significantly Changes Microbenthic Community Structure and Increases the Expression of PAH Degradation Genes.DOCX by Sven Iburg (9251132)

    Published 2020
    “…Additionally, while the abundance of active PAH degraders was significantly higher in spiked sediments than in the controls, no significant effect of our organic mixture was found on nitrification rates or the expression of AmoA (bacterial ammonia oxidizer gene). …”
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    Significance test results. by Ning Zhang (23771)

    Published 2025
    “…<div><p>The traditional method of corn quality detection relies heavily on the subjective judgment of inspectors and suffers from a high error rate. To address these issues, this study employs the Swin Transformer as an enhanced base model, integrating machine vision and deep learning techniques for corn quality assessment. …”
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