Showing 9,181 - 9,200 results of 48,561 for search '(( a ((mean decrease) OR (linear decrease)) ) OR ( a ((greatest decrease) OR (largest decrease)) ))', query time: 0.80s Refine Results
  1. 9181

    OPJ: Origin data for Fig 2a. by Nacer Badi (14046883)

    Published 2024
    “…<div><p>In hot dry regions, photovoltaic modules are exposed to excessive temperatures, which leads to a drop in performance and the risk of overheating. …”
  2. 9182

    OPJ: Origin data for Fig 4a. by Nacer Badi (14046883)

    Published 2024
    “…<div><p>In hot dry regions, photovoltaic modules are exposed to excessive temperatures, which leads to a drop in performance and the risk of overheating. …”
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    Figure S1 - Decrease in Formalin-Inactivated Respiratory Syncytial Virus (FI-RSV) Enhanced Disease with RSV G Glycoprotein Peptide Immunization in BALB/c Mice by Gertrud U. Rey (501694)

    Published 2013
    “…<p><b>Decreased pulmonary cell inflammatory response in FI-A2 or FI-B1 and RSV G-CH17 or G-B1 peptide vaccinated mice after RSV challenge.…”
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    Knockdown of MUC16 results in decreased tight junction function and ZO-1/occludin expression, whereas knockdown of MUC1 has no effect on tight junctions. by Ilene K. Gipson (178895)

    Published 2014
    “…<p>(A) Immunofluorescence analysis of occludin localization demonstrated normal linear distribution of occludin in the MUC16 scrambled control (scr16) cells (A) as compared to the disrupted localization seen in the shMUC16 cells (B). …”
  16. 9196

    Drying Contraction Assessment of Ceramic Products Produced by Extrusion or Pressing Formulated with Sheep Wool Waste by Cristiano Corrêa Ferreira (5110088)

    Published 2018
    “…<div><p>The main aim of this paper was to evaluate ceramic products containing a percentage of ash from sheep wool waste through drying linear shrinkage from a small brickyard in Bagé - RS. …”
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    Assessment values of machine learning models. by Bin Pan (742525)

    Published 2025
    “…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”