Showing 3,081 - 3,100 results of 18,720 for search 'significantly ((((((lower decrease) OR (greatest decrease))) OR (a decrease))) OR (mean decrease))', query time: 0.70s Refine Results
  1. 3081

    Alp5a and Alp5b are not individually required for asexual blood stage propagation, but simultaneously, they are indispensable for parasite viability. by Aastha Varshney (22601181)

    Published 2025
    “…The data are presented as the mean ± SEM, with no significant differences (P = 0.9864; one-way ANOVA). …”
  2. 3082

    Bandages: KT (3A) and RT (3B). by María García-Arrabé (21156737)

    Published 2025
    “…The objective of this study was to compare the effects of a KT and RT and no tape (control group) on lower limb balance, ankle dorsiflexion ROM, and electromyographic (EMG) activation of the pronator and supinator muscles of the ankle during a Single Leg Drop Jump (SLDJ) following a treadmill fatigue protocol. …”
  3. 3083

    TBSS results showing significant AxD and RD changes at baseline and the follow-up. by Sewon Lim (21989785)

    Published 2025
    “…The decreased diffusivity metrics (AxD and RD) exhibited no statistically significant differences at <i><i>P</i></i> < 0.05 after correcting for multiple comparisons (FWE). …”
  4. 3084

    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.…”
  5. 3085

    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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