Showing 11,721 - 11,740 results of 226,405 for search '(( a ((a decrease) OR (linear decrease)) ) OR ( a ((greater decrease) OR (largest decrease)) ))', query time: 1.25s Refine Results
  1. 11721

    LiMMCov user interface. by Perseverence Savieri (21526298)

    Published 2025
    “…<div><p>The correct specification of covariance structures in linear mixed models (LMMs) is critical for accurate longitudinal data analysis. …”
  2. 11722

    Model fit comparison. by Perseverence Savieri (21526298)

    Published 2025
    “…<div><p>The correct specification of covariance structures in linear mixed models (LMMs) is critical for accurate longitudinal data analysis. …”
  3. 11723
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  5. 11725

    Mass loss as a function of pH at each wt% carbonate for each solution. by Mikayla M. Moynahan (10701958)

    Published 2021
    “…<p>Mass decreased for all solutions, indicating powder erosion <b>(A-D)</b>. …”
  6. 11726

    D-spacing of the c-axis (002) and a-axis (004) of CAP after exposure. by Mikayla M. Moynahan (10701958)

    Published 2021
    “…<p>Generally, the c-axis decreased, and the a-axis increased for PBS and MLC <b>(B, C)</b>. …”
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  17. 11737

    Detailed information of the observation datasets. by Weidong Ji (129916)

    Published 2025
    “…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
  18. 11738

    General technical specification for GW154/6700. by Weidong Ji (129916)

    Published 2025
    “…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
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