Showing 1 - 20 results of 105,366 for search '(( significant i decrease ) OR ( significant predictions based ))', query time: 1.94s Refine Results
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    Cat Stress Score (CSS) was significantly predicted by intake type and days in the study. by Allison Andrukonis (11846404)

    Published 2025
    “…B) More days in the study predicted lower CSS (<i>p</i> <  0.001). The black line represents the line of best fit based on the reduced model with marginal means. …”
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    Full list of proteins significantly enriched by BioID2 labelling. by Jan Pyrih (229124)

    Published 2020
    “…<p>Columns B and C: predicted function and e-value based on BLASTp algorithm against the NCBI non-redundant protein "nr" database (<a href="https://www.ncbi.nlm.nih.gov/against" target="_blank">https://www.ncbi.nlm.nih.gov/against</a>) with a parameter to exclude kinetoplastids. …”
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    Image_1_Repeated Inoculation of Young Calves With Rumen Microbiota Does Not Significantly Modulate the Rumen Prokaryotic Microbiota Consistently but Decreases Diarrhea.TIF by Dengpan Bu (369549)

    Published 2020
    “…Principal coordinates analysis (PCoA) based on weighted UniFrac distance showed no significant (P > 0.05) difference in the overall rumen prokaryotic microbiota profiles among the four calf groups, and principal component analysis (PCA) based on Bray-Curtis dissimilarity showed no significant (P > 0.05) difference in functional features predicted from the detected taxa. …”
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    Data_Sheet_1_Repeated Inoculation of Young Calves With Rumen Microbiota Does Not Significantly Modulate the Rumen Prokaryotic Microbiota Consistently but Decreases Diarrhea.docx by Dengpan Bu (369549)

    Published 2020
    “…Principal coordinates analysis (PCoA) based on weighted UniFrac distance showed no significant (P > 0.05) difference in the overall rumen prokaryotic microbiota profiles among the four calf groups, and principal component analysis (PCA) based on Bray-Curtis dissimilarity showed no significant (P > 0.05) difference in functional features predicted from the detected taxa. …”
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    Charging station placement optimization based on the location significance prediction by Daria Matkovic (19539339)

    Published 2024
    “…To address this issue, we introduce a novel approach to optimize the placement of electric vehicle charging stations, integrating a novel location-based charging station significance prediction model with a lion optimization algorithm (LOA) where the significance is defined as the combination of charging energy and the number of sessions. …”
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